commit 36ca44deac67a05d8d3c83be406e84d65ec1fc45
Author: wehub-resource-sync <resource-sync@wehub.local>
Date:   Mon Jul 13 12:30:04 2026 +0800

    chore: import upstream snapshot with attribution

diff --git a/.github/ISSUE_TEMPLATE/1.bug.yml b/.github/ISSUE_TEMPLATE/1.bug.yml
new file mode 100644
index 0000000..c3ef17f
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/1.bug.yml
@@ -0,0 +1,46 @@
+name: Bug report 🐛
+description: Report a bug or unexpected behavior.
+title: "[Bug] "
+labels: ['status: needs check']
+body:
+  - type: markdown
+    attributes:
+      value: |
+        > 💡 English is recommended so global developers can help. 推荐使用英文提交，谢谢 ❤️
+  - type: checkboxes
+    attributes:
+      label: Self check
+      options:
+        - label: I'm on the latest version and searched [existing issues](https://github.com/zhayujie/CowAgent/issues) (incl. closed) — no duplicate.
+          required: true
+  - type: textarea
+    attributes:
+      label: Environment
+      description: "Version (`cow status`), OS, Python version, install method, model & channel."
+      placeholder: |
+        Version: v1.2.0
+        OS: macOS / Linux / Windows / Docker
+        Python: 3.11
+        Install: installer / Docker / source
+        Model & channel: deepseek-v4-flash, web
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: What happened?
+      description: "Steps to reproduce, what you expected, and what happened instead. Screenshots welcome."
+      placeholder: |
+        1. ...
+        2. ...
+
+        Expected: ...
+        Actual: ...
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: Logs
+      description: "Relevant logs from `run.log` (set `\"debug\": true` for more detail). ⚠️ Redact your API keys."
+      render: shell
+    validations:
+      required: false
diff --git a/.github/ISSUE_TEMPLATE/2.feature.yml b/.github/ISSUE_TEMPLATE/2.feature.yml
new file mode 100644
index 0000000..8b53ff9
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/2.feature.yml
@@ -0,0 +1,33 @@
+name: Feature request 🚀
+description: Suggest a new idea or improvement.
+title: "[Feature] "
+labels: ['status: needs check']
+body:
+  - type: markdown
+    attributes:
+      value: |
+        > 💡 English is recommended so global developers can help. 推荐使用英文提交，谢谢 ❤️
+  - type: checkboxes
+    attributes:
+      label: Self check
+      options:
+        - label: I searched [existing issues](https://github.com/zhayujie/CowAgent/issues) (incl. closed) — no duplicate.
+          required: true
+  - type: textarea
+    attributes:
+      label: What's the problem?
+      description: "The pain point or what's not working for you right now."
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: What would you like?
+      description: "How you'd expect it to work. Examples, sketches, or links welcome."
+    validations:
+      required: false
+  - type: checkboxes
+    attributes:
+      label: Contribution
+      options:
+        - label: I'd be interested in helping implement this.
+          required: false
diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml
new file mode 100644
index 0000000..a37a397
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/config.yml
@@ -0,0 +1,5 @@
+blank_issues_enabled: true
+contact_links:
+  - name: 📖 Documentation
+    url: https://docs.cowagent.ai
+    about: Setup guides, configuration, and FAQ.
diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
new file mode 100644
index 0000000..d8a2741
--- /dev/null
+++ b/.github/PULL_REQUEST_TEMPLATE.md
@@ -0,0 +1,22 @@
+<!--
+Thanks for your contribution! Please write this PR in English.
+推荐使用英文填写，感谢 ❤️
+-->
+
+## What does this PR do?
+
+<!-- A short description of the change and why it's needed. -->
+
+## Type of change
+
+- [ ] Bug fix
+- [ ] New feature
+- [ ] Docs
+- [ ] Refactor / chore
+
+## Checklist
+
+- [ ] I have read the [Contributing Guide](https://github.com/zhayujie/CowAgent/blob/master/CONTRIBUTING.md)
+- [ ] I tested this change locally
+- [ ] Code comments and docs are in English
+- [ ] Linked related issue (if any): closes #
diff --git a/.github/scripts/register-releases.mjs b/.github/scripts/register-releases.mjs
new file mode 100644
index 0000000..5109ce9
--- /dev/null
+++ b/.github/scripts/register-releases.mjs
@@ -0,0 +1,116 @@
+// Build the D1 upsert SQL for a desktop release from the files in a directory.
+//
+// Each mac release has TWO artifacts that map to a SINGLE D1 row:
+//   - <name>-<arch>.dmg  -> manual download   (filename / size / sha512)
+//   - <name>-<arch>.zip  -> auto-update        (update_filename / update_size /
+//                                                update_sha512)
+// electron-updater's MacUpdater can only consume a zip, never a dmg, so the
+// feed serves the zip while the website serves the dmg. Windows has only the
+// .exe (stored in the main columns; it's both the download and the update).
+//
+// We emit ONE `INSERT OR REPLACE` per (version, platform) carrying BOTH halves,
+// because two replaces on the same primary key would drop whichever came first.
+//
+// Usage:
+//   node register-releases.mjs --dir dist --version 1.2.0 \
+//        --sql out.sql [--latest] 
+//
+//   --latest  mark these rows is_latest=1 AND clear the previous latest for
+//             each platform (used by the publish/promote workflow). Without it
+//             rows are written unpublished (is_latest=0) — the build stage.
+//
+// sha512 is base64 (the exact format electron-updater validates).
+
+import { execSync } from 'node:child_process'
+import fs from 'node:fs'
+
+function arg(name, fallback = undefined) {
+  const i = process.argv.indexOf(`--${name}`)
+  if (i === -1) return fallback
+  const next = process.argv[i + 1]
+  // Boolean flag (no value or next token is another flag).
+  if (next === undefined || next.startsWith('--')) return true
+  return next
+}
+
+const dir = arg('dir', 'dist')
+const version = arg('version')
+const sqlPath = arg('sql', 'd1.sql')
+const makeLatest = arg('latest', false) === true
+
+if (!version) {
+  console.error('register-releases: --version is required')
+  process.exit(1)
+}
+
+const sha512 = (f) =>
+  execSync(`openssl dgst -sha512 -binary "${f}" | openssl base64 -A`, {
+    shell: '/bin/bash',
+  })
+    .toString()
+    .trim()
+
+// SQL-escape single quotes (base64/keys shouldn't contain them, but be safe).
+const q = (s) => String(s).replace(/'/g, "''")
+
+// platform -> { main: {key,size,sha}, upd: {key,size,sha} }
+const rows = {}
+
+for (const base of fs.readdirSync(dir)) {
+  const f = `${dir}/${base}`
+  if (fs.statSync(f).isDirectory()) continue
+
+  let platform
+  let slot
+  if (/arm64\.dmg$/.test(base)) {
+    platform = 'mac-arm64'
+    slot = 'main'
+  } else if (/x64\.dmg$/.test(base)) {
+    platform = 'mac-x64'
+    slot = 'main'
+  } else if (/arm64\.zip$/.test(base)) {
+    platform = 'mac-arm64'
+    slot = 'upd'
+  } else if (/x64\.zip$/.test(base)) {
+    platform = 'mac-x64'
+    slot = 'upd'
+  } else if (/\.exe$/.test(base)) {
+    platform = 'win'
+    slot = 'main'
+  } else {
+    console.log('Skipping unrecognized artifact:', base)
+    continue
+  }
+
+  rows[platform] ||= {}
+  rows[platform][slot] = {
+    key: `v${version}/${base}`,
+    size: fs.statSync(f).size,
+    sha: sha512(f),
+  }
+}
+
+if (Object.keys(rows).length === 0) {
+  console.error('register-releases: no recognized artifacts in', dir)
+  process.exit(1)
+}
+
+const isLatest = makeLatest ? 1 : 0
+const sql = []
+for (const [platform, r] of Object.entries(rows)) {
+  const m = r.main || { key: '', size: 0, sha: '' }
+  const u = r.upd || { key: '', size: 0, sha: '' }
+  if (makeLatest) {
+    // Clear the previous latest for this platform before promoting the new row.
+    sql.push(`UPDATE releases SET is_latest = 0 WHERE platform = '${platform}';`)
+  }
+  sql.push(
+    `INSERT OR REPLACE INTO releases ` +
+      `(version, platform, filename, size, sha512, update_filename, update_size, update_sha512, is_latest) ` +
+      `VALUES ('${version}', '${platform}', '${q(m.key)}', ${m.size}, '${q(m.sha)}', ` +
+      `'${q(u.key)}', ${u.size}, '${q(u.sha)}', ${isLatest});`
+  )
+}
+
+fs.writeFileSync(sqlPath, sql.join('\n') + '\n')
+console.log(`register-releases: wrote ${sql.length} statement(s) to ${sqlPath}`)
diff --git a/.github/workflows/deploy-image-arm.yml b/.github/workflows/deploy-image-arm.yml
new file mode 100644
index 0000000..2beaeb4
--- /dev/null
+++ b/.github/workflows/deploy-image-arm.yml
@@ -0,0 +1,77 @@
+# This workflow uses actions that are not certified by GitHub.
+# They are provided by a third-party and are governed by
+# separate terms of service, privacy policy, and support
+# documentation.
+
+# GitHub recommends pinning actions to a commit SHA.
+# To get a newer version, you will need to update the SHA.
+# You can also reference a tag or branch, but the action may change without warning.
+
+name: Create and publish a Docker image
+
+on:
+  push:
+    branches: ['master']
+  create:
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+
+jobs:
+  build-and-push-image:
+    if: github.repository == 'zhayujie/CowAgent'
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v1
+
+      - name: Set up Docker Buildx
+        id: buildx
+        uses: docker/setup-buildx-action@v1
+
+      - name: Available platforms
+        run: echo ${{ steps.buildx.outputs.platforms }}
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: |
+            ${{ env.REGISTRY }}/zhayujie/chatgpt-on-wechat
+            ${{ env.REGISTRY }}/zhayujie/cowagent
+          tags: |
+            type=raw,value=latest-arm64,enable={{is_default_branch}}
+            type=ref,event=branch,suffix=-arm64
+            type=ref,event=tag,suffix=-arm64
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v3
+        with:
+          context: .
+          push: true
+          file: ./docker/Dockerfile.latest
+          platforms: linux/arm64
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+
+      - uses: actions/delete-package-versions@v4
+        with:
+          package-name: 'chatgpt-on-wechat'
+          package-type: 'container'
+          min-versions-to-keep: 10
+          delete-only-untagged-versions: 'true'
+          token: ${{ secrets.GITHUB_TOKEN }}
\ No newline at end of file
diff --git a/.github/workflows/deploy-image.yml b/.github/workflows/deploy-image.yml
new file mode 100644
index 0000000..d9ac0be
--- /dev/null
+++ b/.github/workflows/deploy-image.yml
@@ -0,0 +1,75 @@
+# This workflow uses actions that are not certified by GitHub.
+# They are provided by a third-party and are governed by
+# separate terms of service, privacy policy, and support
+# documentation.
+
+# GitHub recommends pinning actions to a commit SHA.
+# To get a newer version, you will need to update the SHA.
+# You can also reference a tag or branch, but the action may change without warning.
+
+name: Create and publish a Docker image
+
+on:
+  push:
+    branches: ['master']
+  create:
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+  DOCKERHUB_IMAGE: zhayujie/chatgpt-on-wechat
+
+jobs:
+  build-and-push-image:
+    if: github.repository == 'zhayujie/CowAgent'
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Login to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: |
+            zhayujie/chatgpt-on-wechat
+            zhayujie/cowagent
+            ${{ env.REGISTRY }}/zhayujie/chatgpt-on-wechat
+            ${{ env.REGISTRY }}/zhayujie/cowagent
+          tags: |
+            type=raw,value=latest,enable={{is_default_branch}}
+            type=ref,event=branch
+            type=ref,event=tag
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v3
+        with:
+          context: .
+          push: true
+          file: ./docker/Dockerfile.latest
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+
+      - uses: actions/delete-package-versions@v4
+        with:
+          package-name: 'chatgpt-on-wechat'
+          package-type: 'container'
+          min-versions-to-keep: 10
+          delete-only-untagged-versions: 'true'
+          token: ${{ secrets.GITHUB_TOKEN }}
\ No newline at end of file
diff --git a/.github/workflows/publish-desktop.yml b/.github/workflows/publish-desktop.yml
new file mode 100644
index 0000000..6f2270b
--- /dev/null
+++ b/.github/workflows/publish-desktop.yml
@@ -0,0 +1,154 @@
+name: Publish Desktop
+
+# STAGE 3 of the decoupled release pipeline: PROMOTE a built + notarized version
+# to "live". By this point:
+#   - stage 1 (Release Desktop) built the installers, mirrored them to R2, and
+#     registered them in D1 as unpublished (is_latest=0);
+#   - stage 2 (local desktop/build/notarize-dmg.sh) notarized + stapled the mac
+#     dmgs and re-uploaded the stapled bytes to R2.
+#
+# This workflow, triggered manually with the version to publish:
+#   1. pulls every artifact for that version back from R2,
+#   2. recomputes sha512 from the real (stapled) bytes and updates D1,
+#   3. flips is_latest=1 for that version (clearing the previous latest per
+#      platform) UNLESS it's a pre-release, which is recorded but never latest,
+#   4. creates/updates the GitHub Release and attaches the installers.
+#
+# Run only after the mac dmgs for this version are notarized + re-uploaded.
+on:
+  workflow_dispatch:
+    inputs:
+      version:
+        description: "Version to publish (e.g. 1.2.0). Must already be built + notarized."
+        type: string
+        required: true
+      make_latest:
+        description: "Mark this version as latest on the site (uncheck for a dry re-hash only)."
+        type: boolean
+        default: true
+      github_release:
+        description: "Create/update the GitHub Release and attach installers."
+        type: boolean
+        default: true
+
+permissions:
+  contents: write
+
+jobs:
+  publish:
+    name: Publish ${{ github.event.inputs.version }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Guard on Cloudflare secrets
+        id: guard
+        env:
+          CF_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+        run: |
+          if [ -z "$CF_TOKEN" ]; then
+            echo "::error::CLOUDFLARE_API_TOKEN not set — cannot publish."
+            exit 1
+          fi
+
+      - name: Resolve version artifacts from D1
+        id: rows
+        env:
+          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
+          VER: ${{ github.event.inputs.version }}
+        run: |
+          # The build stage inserted one row per artifact with filename = v<VER>/<base>.
+          # Read them back so we know exactly which objects to pull from R2.
+          out="$(npx --yes wrangler@latest d1 execute cow-desktop --remote --json \
+            --command "SELECT platform, filename, update_filename FROM releases WHERE version = '${VER}';")"
+          echo "$out"
+          echo "$out" | node -e '
+            const fs = require("fs");
+            const data = JSON.parse(fs.readFileSync(0, "utf8"));
+            const rows = (Array.isArray(data) ? data : [data])
+              .flatMap(r => (r.results || []));
+            if (!rows.length) {
+              console.error("No D1 rows for this version — did stage 1 (build) run?");
+              process.exit(1);
+            }
+            fs.writeFileSync(process.env.GITHUB_OUTPUT, "count=" + rows.length + "\n", { flag: "a" });
+            fs.writeFileSync("rows.json", JSON.stringify(rows));
+          '
+
+      - name: Download version artifacts from R2
+        env:
+          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
+          R2_BUCKET: ${{ vars.R2_BUCKET != '' && vars.R2_BUCKET || 'cow-skills' }}
+        run: |
+          mkdir -p dist
+          # Pull BOTH the manual-download file (filename: dmg/exe) and the mac
+          # auto-update file (update_filename: zip) for every row. Keys are
+          # "v<VER>/<base>"; the R2 key is "desktop/<key>".
+          for key in $(node -e 'JSON.parse(require("fs").readFileSync("rows.json")).forEach(r => { if (r.filename) console.log(r.filename); if (r.update_filename) console.log(r.update_filename); })'); do
+            base="$(basename "$key")"
+            r2key="desktop/${key}"
+            echo "==> Downloading r2://${R2_BUCKET}/${r2key} -> dist/${base}"
+            npx --yes wrangler@latest r2 object get "${R2_BUCKET}/${r2key}" \
+              --file "dist/${base}" --remote
+          done
+          echo "Downloaded:"; ls -la dist
+
+      - name: Reminder — mac dmgs must be notarized before publishing
+        run: |
+          # Stapling can only be validated on macOS (xcrun stapler validate),
+          # which this Linux runner doesn't have. The authoritative check runs in
+          # stage 2 (desktop/build/notarize-dmg.sh) before re-uploading to R2.
+          # This step is just a loud reminder in the log.
+          echo "::notice::Publishing assumes the mac dmgs pulled from R2 are already notarized + stapled (stage 2). If you skipped stage 2, users will hit Gatekeeper warnings."
+          ls -la dist/*.dmg 2>/dev/null || echo "(no dmg in this version — win-only publish)"
+
+      - name: Update D1 (recompute sha512 + set latest)
+        env:
+          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
+          VER: ${{ github.event.inputs.version }}
+          MAKE_LATEST: ${{ github.event.inputs.make_latest }}
+        run: |
+          # Pre-releases (e.g. 1.2.0-beta / -rc.1 / -test) are recorded but never
+          # become latest, so the site keeps serving the last stable build.
+          case "$VER" in
+            *-*) is_pre=1 ;;
+            *)   is_pre=0 ;;
+          esac
+          if [ "$MAKE_LATEST" = "true" ] && [ "$is_pre" = "0" ]; then
+            latest_flag="--latest"; echo "==> Publishing $VER as latest."
+          else
+            latest_flag=""; echo "==> Publishing $VER without latest flag (pre-release or dry re-hash)."
+          fi
+
+          # Re-hash the real (stapled) bytes and re-store every row with both the
+          # dmg (manual) and mac zip (auto-update) columns. Same script as the
+          # build stage; --latest also clears the previous latest per platform.
+          node .github/scripts/register-releases.mjs --dir dist --version "$VER" --sql d1.sql $latest_flag
+          echo "==> D1 statements:"; cat d1.sql
+          npx --yes wrangler@latest d1 execute cow-desktop --remote --file d1.sql
+
+      - name: Create/update GitHub Release and attach installers
+        if: github.event.inputs.github_release == 'true'
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          VER: ${{ github.event.inputs.version }}
+        run: |
+          tag="v${VER}"
+          case "$VER" in
+            *-*) prerelease="--prerelease" ;;
+            *)   prerelease="" ;;
+          esac
+          if ! gh release view "$tag" --repo "$GITHUB_REPOSITORY" >/dev/null 2>&1; then
+            gh release create "$tag" --repo "$GITHUB_REPOSITORY" \
+              --title "$tag" --generate-notes $prerelease
+          fi
+          # --clobber so re-runs overwrite the stapled/updated assets. The mac
+          # zip is the auto-update artifact; attach it too so the GitHub Release
+          # is a complete mirror (nullglob avoids errors when a type is absent).
+          shopt -s nullglob
+          gh release upload "$tag" dist/*.dmg dist/*.zip dist/*.exe \
+            --repo "$GITHUB_REPOSITORY" --clobber
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 0000000..2aeaf0e
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,301 @@
+name: Release Desktop
+
+# STAGE 1 of the decoupled release pipeline: BUILD ONLY.
+# Builds the desktop client for macOS (arm64 + x64) and Windows (x64), mirrors
+# the installers to R2, and registers them in D1 as UNPUBLISHED (is_latest=0)
+# so the website keeps serving the previous release. It does NOT notarize
+# (Apple's notary service stalls this large bundle for hours) and does NOT
+# create a GitHub Release.
+#
+# Full flow:
+#   1. (this workflow) build + upload to R2 + D1 as unpublished.
+#   2. (local) download the mac dmgs, run desktop/build/notarize-dmg.sh to
+#      notarize + staple + re-upload the stapled dmgs to R2.
+#   3. (Publish Desktop workflow) flip D1 is_latest=1 and attach GitHub
+#      Release assets — makes the version live on the site.
+#
+# Manual only: run stage 1 via workflow_dispatch. Tag pushes do NOT trigger a
+# build, so cutting a release tag never rebuilds installers or overwrites R2.
+on:
+  workflow_dispatch:
+    inputs:
+      version:
+        description: "Version to stamp (e.g. 1.0.0-test). Used for package.json and R2 path."
+        type: string
+        default: "0.0.0-dev"
+      publish_r2:
+        description: "Upload installers to R2 + register in D1 (needs Cloudflare secrets)"
+        type: boolean
+        default: false
+
+permissions:
+  contents: write
+
+jobs:
+  build:
+    name: Build ${{ matrix.name }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      # Don't cancel the other platforms if one fails — we want to see all
+      # failures in a single run.
+      fail-fast: false
+      matrix:
+        include:
+          - name: macOS arm64
+            os: macos-14
+            platform: mac
+            arch: arm64
+            eb_flags: --mac --arm64
+          - name: macOS x64
+            os: macos-15-intel
+            platform: mac
+            arch: x64
+            eb_flags: --mac --x64
+          - name: Windows x64
+            os: windows-latest
+            platform: win
+            arch: x64
+            eb_flags: --win --x64
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Derive version
+        # Tag push: strip the leading "v" from GITHUB_REF_NAME (e.g. v1.2.0).
+        # Manual dispatch: use the provided version input.
+        id: ver
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            ref="${GITHUB_REF_NAME:-}"
+            echo "version=${ref#v}" >> "$GITHUB_OUTPUT"
+          else
+            echo "version=${{ github.event.inputs.version }}" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Set up Node
+        uses: actions/setup-node@v4
+        with:
+          node-version: "20"
+
+      - name: Build Python backend (PyInstaller)
+        shell: bash
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r desktop/build/requirements-desktop.txt
+          pip install pyinstaller
+          # Run from repo root so the spec's relative datas resolve correctly.
+          pyinstaller desktop/build/cowagent-backend.spec \
+            --noconfirm \
+            --distpath desktop/build/dist \
+            --workpath desktop/build/build-work
+
+      - name: Install desktop deps
+        working-directory: desktop
+        run: npm ci
+
+      - name: Write version into package.json
+        working-directory: desktop
+        shell: bash
+        run: npm version "${{ steps.ver.outputs.version }}" --no-git-tag-version --allow-same-version
+
+      # Compile renderer + main in its OWN step, alone, so the npm.cmd batch
+      # wrapper (see the note on the build step below) can't take out anything
+      # after it.
+      - name: Compile (vite + tsc)
+        working-directory: desktop
+        shell: bash
+        run: npm run build
+
+      - name: Build & publish (electron-builder)
+        working-directory: desktop
+        shell: bash
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          # Signing secrets are passed through as-is; we only export them to the
+          # environment below when non-empty. An empty CSC_LINK would make
+          # electron-builder try to load a bogus certificate and fail, so unset
+          # is the correct state for unsigned builds.
+          MAC_CSC_LINK: ${{ secrets.MAC_CSC_LINK }}
+          MAC_CSC_KEY_PASSWORD: ${{ secrets.MAC_CSC_KEY_PASSWORD }}
+          WIN_CSC_LINK: ${{ secrets.WIN_CSC_LINK }}
+          WIN_CSC_KEY_PASSWORD: ${{ secrets.WIN_CSC_KEY_PASSWORD }}
+        run: |
+          # Pick the signing cert for THIS platform only. The mac and win secrets
+          # are both present in the job env, but a mac cert must never leak into a
+          # Windows build (electron-builder would try to load it and fail), and
+          # vice versa. electron-builder reads a single CSC_LINK/CSC_KEY_PASSWORD
+          # pair, so we set it per-platform. An empty CSC_LINK is treated by
+          # electron-builder as a broken cert path, so we leave it entirely unset
+          # for an unsigned build.
+          #
+          # NOTE: we only ever `export`, never `unset`, GitHub-injected env vars
+          # (an `unset` can return non-zero and abort under errexit).
+          case "${{ matrix.platform }}" in
+            mac)
+              if [ -n "$MAC_CSC_LINK" ]; then
+                export CSC_LINK="$MAC_CSC_LINK"
+                export CSC_KEY_PASSWORD="$MAC_CSC_KEY_PASSWORD"
+              fi
+              ;;
+            win)
+              if [ -n "$WIN_CSC_LINK" ]; then
+                export CSC_LINK="$WIN_CSC_LINK"
+                export CSC_KEY_PASSWORD="$WIN_CSC_KEY_PASSWORD"
+              fi
+              ;;
+          esac
+
+          # Never let electron-builder publish: our publish target is a generic
+          # (read-only) feed served from R2/D1, which it can't upload to. We mirror
+          # installers to R2 and register them in D1 ourselves (publish-r2 job).
+          # `--publish never` still emits the latest*.yml files.
+          #
+          # CONFIG PER PLATFORM: the dynamic electron-builder.js only exists to
+          # inject mac.binaries (the backend Mach-O files to hardened-sign for
+          # notarization) — it's a pure no-op on Windows. Passing --config on
+          # Windows was what silently broke the Windows build (it produced no
+          # installer while the job still reported success; Windows worked fine
+          # before --config was introduced). So Windows uses the plain
+          # package.json build config and only mac uses the dynamic one.
+          #
+          # Invoke via `node <cli.js>` rather than `npx`: on Windows `npx` is
+          # npx.cmd (a batch wrapper) and running it from this Git Bash step can
+          # make bash return before the wrapped process finishes. node skips it.
+          case "${{ matrix.platform }}" in
+            mac) config_arg="--config electron-builder.js" ;;
+            *)   config_arg="" ;;
+          esac
+          node node_modules/electron-builder/cli.js ${{ matrix.eb_flags }} $config_arg --publish never
+
+      # Upload artifacts regardless of outcome, so a failed run still surfaces
+      # the built installers (and, on success, the notarized+stapled dmg).
+      - name: Upload artifacts
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          # One bundle per platform/arch so the publish job can collect them all.
+          name: cowagent-${{ matrix.platform }}-${{ matrix.arch }}
+          path: |
+            desktop/release/*.dmg
+            desktop/release/*.zip
+            desktop/release/*.exe
+            desktop/release/*.yml
+            desktop/release/*.blockmap
+          if-no-files-found: ignore
+          retention-days: 7
+
+  # Mirror the release installers to R2 (CDN-backed) and register them in D1 so
+  # cowagent.ai/download/{platform}/latest can resolve and count downloads.
+  # Runs only on tag pushes, and is a no-op (skips) until the Cloudflare secrets
+  # are configured, so it never blocks unsigned/dry builds.
+  publish-r2:
+    name: Publish to R2 + D1
+    # Require every platform in the build matrix to succeed before publishing,
+    # so a release on R2/D1 is always complete (all installers present) rather
+    # than partial. needs: build already gates on all matrix jobs succeeding.
+    needs: build
+    runs-on: ubuntu-latest
+    # Run on a tag push, or on a manual dispatch when publish_r2 is checked.
+    if: >-
+      (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v')) ||
+      (github.event_name == 'workflow_dispatch' && github.event.inputs.publish_r2 == 'true')
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Guard on Cloudflare secrets
+        id: guard
+        env:
+          CF_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+        run: |
+          if [ -n "$CF_TOKEN" ]; then
+            echo "enabled=true" >> "$GITHUB_OUTPUT"
+          else
+            echo "enabled=false" >> "$GITHUB_OUTPUT"
+            echo "::notice::CLOUDFLARE_API_TOKEN not set — skipping R2/D1 publish."
+          fi
+
+      - name: Derive version
+        if: steps.guard.outputs.enabled == 'true'
+        id: ver
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            echo "version=${GITHUB_REF_NAME#v}" >> "$GITHUB_OUTPUT"
+          else
+            echo "version=${{ github.event.inputs.version }}" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Download all build artifacts
+        if: steps.guard.outputs.enabled == 'true'
+        uses: actions/download-artifact@v4
+        with:
+          path: artifacts
+
+      - name: Stage installers
+        if: steps.guard.outputs.enabled == 'true'
+        id: stage
+        run: |
+          mkdir -p dist
+          # Flatten installers + their .blockmap (used by electron-updater for
+          # differential downloads) from every per-platform artifact dir. The
+          # .yml feed is generated dynamically by the /update Function from D1,
+          # so the yml files themselves don't need to go to R2.
+          # .zip is the mac auto-update artifact (electron-updater's MacUpdater
+          # can ONLY consume zip, not dmg — the dmg is for manual downloads).
+          find artifacts -type f \( -name '*.dmg' -o -name '*.zip' -o -name '*.exe' -o -name '*.blockmap' \) -exec cp {} dist/ \;
+          echo "Staged files:"; ls -la dist
+          # When the whole matrix failed there's nothing to publish; flag it so
+          # the R2/D1 steps skip instead of writing an empty/partial release.
+          if [ -n "$(ls -A dist 2>/dev/null)" ]; then
+            echo "has_files=true" >> "$GITHUB_OUTPUT"
+          else
+            echo "has_files=false" >> "$GITHUB_OUTPUT"
+            echo "::warning::No installers found in any artifact — skipping R2/D1 publish."
+          fi
+
+      - name: Upload installers to R2
+        if: steps.guard.outputs.enabled == 'true' && steps.stage.outputs.has_files == 'true'
+        env:
+          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
+          VER: ${{ steps.ver.outputs.version }}
+        run: |
+          # Reuse the existing cow-skills bucket under a desktop/ prefix; this
+          # is served by the cdn.cowagent.ai custom domain.
+          for f in dist/*; do
+            base="$(basename "$f")"
+            key="desktop/v${VER}/${base}"
+            echo "==> Uploading $base -> r2://cow-skills/$key"
+            npx --yes wrangler@latest r2 object put "cow-skills/$key" \
+              --file "$f" --remote
+          done
+
+      - name: Register release rows in D1
+        if: steps.guard.outputs.enabled == 'true' && steps.stage.outputs.has_files == 'true'
+        env:
+          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_ACCOUNT_ID }}
+          VER: ${{ steps.ver.outputs.version }}
+        run: |
+          # This build job ALWAYS registers rows as unpublished (is_latest=0), so
+          # /download/<p>/latest keeps serving the previous release and the new
+          # version stays invisible on the site. macOS dmgs still need to be
+          # notarized+stapled locally (build/notarize-dmg.sh) before they're
+          # safe to ship. Promotion to latest happens later, only after
+          # notarization, via the separate "Publish Desktop" workflow.
+          echo "==> Registering $VER as unpublished (is_latest=0)."
+
+          # Build one upsert per (version, platform) carrying both the dmg
+          # (manual download) and the mac zip (auto-update) columns. See
+          # .github/scripts/register-releases.mjs for the mapping. No --latest
+          # here: rows stay unpublished until the publish workflow promotes them.
+          node .github/scripts/register-releases.mjs --dir dist --version "$VER" --sql d1.sql
+          echo "==> D1 statements:"; cat d1.sql
+          npx --yes wrangler@latest d1 execute cow-desktop --remote --file d1.sql
diff --git a/.github/workflows/test-windows-bash.yml b/.github/workflows/test-windows-bash.yml
new file mode 100644
index 0000000..4a39dbe
--- /dev/null
+++ b/.github/workflows/test-windows-bash.yml
@@ -0,0 +1,32 @@
+name: Windows Bash Streaming Tests
+
+on:
+  workflow_dispatch:
+  pull_request:
+    paths:
+      - "agent/tools/bash/bash.py"
+      - "tests/test_bash_streaming.py"
+      - ".github/workflows/test-windows-bash.yml"
+
+jobs:
+  windows-bash-tests:
+    runs-on: windows-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+          cache: pip
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install pytest
+          python -m pip install -r requirements.txt
+
+      - name: Run Windows Bash streaming tests
+        run: python -m pytest tests/test_bash_streaming.py -v
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..9cbb011
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,64 @@
+.DS_Store
+.idea
+.vscode
+.venv
+.vs
+__pycache__/
+venv*
+*.pyc
+python
+config.json
+QR.png
+nohup.out
+tmp
+plugins.json
+*.log
+logs/
+workspace
+config.yaml
+user_datas.pkl
+chatgpt_tool_hub/
+plugins/**/
+!plugins/bdunit
+!plugins/dungeon
+!plugins/finish
+!plugins/godcmd
+!plugins/tool
+!plugins/banwords
+!plugins/banwords/**/
+plugins/banwords/__pycache__
+plugins/banwords/lib/__pycache__
+!plugins/hello
+!plugins/role
+!plugins/keyword
+!plugins/linkai
+!plugins/cow_cli
+client_config.json
+ref/
+**/.dev.vars
+.cursor/
+local/
+node_modules/
+
+# cow cli
+dist/
+build/
+*.egg-info/
+.cow.pid
+
+# Desktop backend packaging: keep the source files (spec/requirements/script)
+# tracked even though the generic build/ rule above ignores them, but never
+# track the build outputs or local venv.
+!desktop/build/
+desktop/build/*
+!desktop/build/cowagent-backend.spec
+!desktop/build/requirements-desktop.txt
+!desktop/build/build-backend.sh
+!desktop/build/entitlements.mac.plist
+!desktop/build/notarize-dmg.sh
+
+# Icon authoring scratch dir: intermediate assets used to produce the final
+# icons. Only the finished icons under desktop/resources/ should be committed.
+desktop/resources/.icon-work/
+
+.wrangler/
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
new file mode 100644
index 0000000..4a9d7d8
--- /dev/null
+++ b/CONTRIBUTING.md
@@ -0,0 +1,61 @@
+# Contributing to CowAgent
+
+Thanks for taking the time to contribute! 🎉 CowAgent is built by a global
+community, and contributions of all sizes are welcome — from typo fixes to new
+features.
+
+## Language policy
+
+To keep the project accessible to a global community, **please write issues,
+pull requests, code comments, and commit messages in English.**
+
+> 为方便全球开发者协作，请尽量使用**英文**提交 issue、PR、代码注释与
+> commit message。不必担心英文不完美——表达清楚即可，工具翻译也完全没问题。感谢理解 ❤️
+
+## Reporting issues
+
+Found a bug or have an idea? [Open an issue](https://github.com/zhayujie/CowAgent/issues/new/choose).
+
+Before opening one, please search existing issues (including closed ones) to
+avoid duplicates, and make sure you're on the latest version.
+
+## Submitting a pull request
+
+1. **Fork** the repo and create a branch from `master`
+   (e.g. `feat/web-search`, `fix/telegram-reconnect`).
+2. Make your change. Keep it focused — one logical change per PR.
+3. Follow the existing code style. Write comments and docstrings in English.
+4. Run the app locally to confirm your change works.
+5. Open a PR with a clear title and a short description of **what** and **why**.
+
+We keep the bar friendly: clear, focused, and working is enough. Maintainers are
+happy to help polish details during review.
+
+### Commit & PR titles
+
+Use a short, imperative summary. The [Conventional Commits](https://www.conventionalcommits.org/)
+style is preferred but not required:
+
+```
+feat: add web search tool
+fix: reconnect Telegram websocket on timeout
+docs: clarify Docker setup
+```
+
+## Development setup
+
+See the [Install from Source](https://docs.cowagent.ai/guide/manual-install)
+guide. In short:
+
+```bash
+git clone https://github.com/zhayujie/CowAgent.git
+cd CowAgent
+pip install -r requirements.txt
+pip install -e .
+cow start
+```
+
+## Code of conduct
+
+Be respectful and constructive. We want CowAgent to be a welcoming place for
+everyone.
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..9d3bbb7
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,3 @@
+FROM ghcr.io/zhayujie/chatgpt-on-wechat:latest
+
+ENTRYPOINT ["/entrypoint.sh"]
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..fd03f7c
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,19 @@
+Copyright (c) 2022 zhayujie
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..0cb88b3
--- /dev/null
+++ b/README.md
@@ -0,0 +1,279 @@
+<p align="center"><img src="https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="420" /></p>
+
+<p align="center">
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent?cacheSeconds=3600" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-green.svg" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square&cacheSeconds=3600" alt="Stars"></a>
+  <a href="https://docs.cowagent.ai/"><img src="https://img.shields.io/badge/Docs-cowagent.ai-blue?style=flat&logo=readthedocs&logoColor=white" alt="Docs"></a>
+</p>
+
+<p align="center">
+  <a href="https://trendshift.io/repositories/25763" target="_blank"><img src="https://trendshift.io/api/badge/repositories/25763" alt="zhayujie%2FCowAgent | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
+<p align="center">
+  [English] | [<a href="docs/zh/README.md">中文</a>] | [<a href="docs/zh/README-Hant.md">繁體中文</a>] | [<a href="docs/ja/README.md">日本語</a>]
+</p>
+
+**CowAgent** is an open-source super AI assistant that proactively plans tasks, controls your computer and external services, creates and runs Skills, builds a personal knowledge base and long-term memory, and grows alongside you through self-evolution — a reference implementation of Agent Harness engineering.
+
+CowAgent is lightweight, easy to deploy, and built to extend. Plug in any major LLM provider and run it 24/7 on a personal computer or server, across the web and all major IM platforms.
+
+<p align="center">
+  <a href="https://cowagent.ai/">🌐 Website</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/intro/index">📖 Docs</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/guide/quick-start">🚀 Quick Start</a> &nbsp;·&nbsp;
+  <a href="https://skills.cowagent.ai/">🧩 Skill Hub</a> &nbsp;·&nbsp;
+  <a href="https://cowagent.ai/download/">💻 Download</a> &nbsp;·&nbsp;
+  <a href="https://link-ai.tech/cowagent/create">☁️ Try Online</a>
+</p>
+
+<br/>
+
+## 🌟 Highlights
+
+| Capability | Description |
+| :--- | :--- |
+| [Planning](https://docs.cowagent.ai/intro/architecture) | Decomposes complex tasks and executes them step by step, looping over tools until the goal is reached |
+| [Memory](https://docs.cowagent.ai/memory/index) | Three-tier architecture (context → daily → core), automatic Deep Dream distillation, hybrid keyword + vector retrieval |
+| [Knowledge](https://docs.cowagent.ai/knowledge/index) | Auto-curates structured knowledge into a Markdown wiki, builds an evolving knowledge graph with visual browsing |
+| [Evolution](https://docs.cowagent.ai/memory/self-evolution) | Self-Evolution reviews conversations automatically to improve skills, follow up on unfinished tasks, and consolidate memory and knowledge, growing through everyday use |
+| [Skills](https://docs.cowagent.ai/skills/index) | One-click install from [Skill Hub](https://skills.cowagent.ai/), GitHub, ClawHub; or create custom skills via natural-language conversation |
+| [Tools](https://docs.cowagent.ai/tools/index) | Built-in file I/O, terminal, browser, scheduler, memory retrieval, web search, and 10+ more tools — with native MCP integration |
+| [Channels](https://docs.cowagent.ai/channels/index) | Integrates with Web, WeChat, Feishu, DingTalk, WeCom, QQ, Official Accounts, Telegram, and Slack |
+| Multimodal | First-class support for text, images, voice, and files — recognition, generation, and delivery |
+| [Models](https://docs.cowagent.ai/models/index) | Claude, GPT, Gemini, DeepSeek, Qwen, GLM, Kimi, MiniMax, Doubao, and more — swap providers from the Web console with one click |
+| [Deploy](https://docs.cowagent.ai/guide/quick-start) | One-line installer, unified Web console, multiple deployment modes (local, Docker, server) |
+
+<br/>
+
+## 🏗️ Architecture
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/en/architecture.png" alt="CowAgent Architecture" width="750"/>
+
+CowAgent is a complete **Agent Harness**: messages flow in through **Channels**; the **Agent Core** plans and reasons over memory, knowledge, and the available tools and skills; **Models** generate the response, which is sent back through the originating channel. Every layer is decoupled and independently extensible.
+
+Read more in [Architecture](https://docs.cowagent.ai/intro/architecture).
+
+<br/>
+
+## 🚀 Quick Start
+
+A one-line installer takes care of dependencies, configuration, and startup:
+
+**Linux / macOS:**
+
+```bash
+bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+```
+
+**Windows (PowerShell):**
+
+```powershell
+irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+```
+
+**Docker:**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+docker compose up -d
+```
+
+Once started, open `http://localhost:9899` to access the **Web console** — your one-stop hub to chat with the Agent, configure models, connect channels, and install skills.
+
+> Deploying on a server? Set `web_host` to `0.0.0.0` in `config.json` to make the console reachable from outside, and set `web_password` to protect it. Don't forget to open port `9899` in your firewall or security group.
+
+> 📖 Detailed guides: [Quick Start](https://docs.cowagent.ai/guide/quick-start) · [Install from Source](https://docs.cowagent.ai/guide/manual-install) · [Upgrade](https://docs.cowagent.ai/guide/upgrade)
+
+After installation, manage the service with the [cow CLI](https://docs.cowagent.ai/cli/index):
+
+```bash
+cow start | stop | restart        # service control
+cow status | logs                  # status and logs
+cow update                         # pull latest code and restart
+cow skill install <name>           # install a skill
+cow install-browser                # install browser automation
+```
+
+> 💻 Desktop client: download the **[CowAgent Desktop client](https://cowagent.ai/download/)** (macOS / Windows) — the backend is bundled, ready to use out of the box.
+
+<br/>
+
+## 🤖 Models
+
+CowAgent supports all mainstream LLM providers. **Chat, vision, image generation, ASR/TTS, and embeddings** can each be routed to a different vendor. Providers are configured directly in the Web console — no manual file editing required.
+
+| Provider | Featured Models | Chat | Vision | Image Gen | ASR | TTS | Embedding |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [Claude](https://docs.cowagent.ai/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [OpenAI](https://docs.cowagent.ai/models/openai) | gpt-5.5, o-series | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Gemini](https://docs.cowagent.ai/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [DeepSeek](https://docs.cowagent.ai/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [Qwen](https://docs.cowagent.ai/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [GLM](https://docs.cowagent.ai/models/glm) | glm-5.2, glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [Doubao](https://docs.cowagent.ai/models/doubao) | doubao-seed-2.1 series | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](https://docs.cowagent.ai/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [MiniMax](https://docs.cowagent.ai/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [ERNIE](https://docs.cowagent.ai/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [MiMo](https://docs.cowagent.ai/models/mimo) | mimo-v2.5 / pro | ✅ | ✅ | | | ✅ | |
+| [LinkAI](https://docs.cowagent.ai/models/linkai) | One key for 100+ models | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Custom](https://docs.cowagent.ai/models/custom) | Local models / third-party proxy | ✅ | | | | | |
+
+> For details on each provider, see the [Models overview](https://docs.cowagent.ai/models/index).
+
+<br/>
+
+## 💬 Channels
+
+A single Agent instance can serve multiple channels in parallel. Most channels can be onboarded right from the Web console.
+
+| Channel | Text | Image | File | Voice | Group |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [Web Console](https://docs.cowagent.ai/channels/web) (default) | ✅ | ✅ | ✅ | ✅ | |
+| [Telegram](https://docs.cowagent.ai/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](https://docs.cowagent.ai/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](https://docs.cowagent.ai/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+| [WeChat](https://docs.cowagent.ai/channels/weixin) | ✅ | ✅ | ✅ | ✅ | |
+| [Feishu / Lark](https://docs.cowagent.ai/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [DingTalk](https://docs.cowagent.ai/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [WeCom Bot](https://docs.cowagent.ai/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](https://docs.cowagent.ai/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [WeCom App](https://docs.cowagent.ai/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat Customer Service](https://docs.cowagent.ai/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat Official Account](https://docs.cowagent.ai/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+
+> See the [Channels overview](https://docs.cowagent.ai/channels/index) for setup details.
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-chat.png" alt="CowAgent Web Console" width="800"/>
+
+*The Web console is the default channel and the unified entry point to configure models, channels, skills, memory, and more.*
+
+<br/>
+
+## 🧠 Memory & Knowledge Base
+
+**Long-term memory** uses a three-tier architecture: conversation context (short-term) → daily memory (mid-term) → MEMORY.md (long-term). A nightly **Deep Dream** pass distills scattered memories into refined long-term entries and a narrative journal. See [Long-term Memory](https://docs.cowagent.ai/memory/index) · [Deep Dream](https://docs.cowagent.ai/memory/deep-dream).
+
+**Personal knowledge base** complements the time-ordered memory by organizing structured knowledge **by topic**. The Agent automatically curates valuable information from conversations, maintains cross-references and indexes, and the Web console offers an interactive knowledge-graph view. See [Personal Knowledge Base](https://docs.cowagent.ai/knowledge/index).
+
+<table>
+  <tr>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-memory.png" alt="Long-term Memory" />
+      <p align="center"><em>Long-term Memory · Three-tier architecture + Deep Dream</em></p>
+    </td>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-knowledge.png" alt="Personal Knowledge Base" />
+      <p align="center"><em>Knowledge Base · Auto-curated Markdown wiki</em></p>
+    </td>
+  </tr>
+</table>
+
+<br/>
+
+## 🔧 Tools & Skills
+
+**Tools** are atomic capabilities the Agent uses to interact with system resources. **Skills** are higher-level workflows defined by a manifest file that compose multiple tools to accomplish complex tasks.
+
+### Tool System
+
+**Built-in tools** cover file I/O (`read` / `write` / `edit` / `ls`), terminal (`bash`), file sending (`send`), memory retrieval (`memory`), environment variables (`env_config`), web fetching (`web_fetch`), scheduling (`scheduler`), web search (`web_search`), vision (`vision`), and browser automation (`browser`).
+
+**MCP protocol** integrates the open ecosystem of [Model Context Protocol](https://modelcontextprotocol.io) servers. A single `mcp.json` is enough — supports stdio / SSE transports, hot reload, and zero-code integration.
+
+Learn more: [Tools overview](https://docs.cowagent.ai/tools/index) · [MCP integration](https://docs.cowagent.ai/tools/mcp).
+
+### Skills System
+
+- **[Skill Hub](https://skills.cowagent.ai/)** — open skill marketplace: browse, search, install in one click
+- **GitHub / ClawHub / URL and more** — install skills from any source
+- **Conversational authoring** — generate custom skills through dialogue with `skill-creator`; turn any workflow or third-party API into a reusable skill
+
+```bash
+/skill list                   # list installed skills
+/skill search <keyword>        # search the marketplace
+/skill install <name>          # one-click install
+```
+
+Learn more: [Skills overview](https://docs.cowagent.ai/skills/index) · [Creating Skills](https://docs.cowagent.ai/skills/create).
+
+<br/>
+
+## 🏷 Changelog
+
+> **2026.07.08:** [v2.1.3](https://github.com/zhayujie/CowAgent/releases/tag/2.1.3) — [Desktop client](https://cowagent.ai/download/) for macOS / Windows, knowledge base document management, on-demand MCP tool retrieval, Traditional Chinese support, new models.
+
+> **2026.06.18:** [v2.1.2](https://github.com/zhayujie/CowAgent/releases/tag/2.1.2) — Web console upgrades (scheduled task management, knowledge base categories, multiple custom model providers), Self-Evolution improvements, new models (kimi-k2.7-code, glm-5.2), security hardening and refinements.
+
+> **2026.06.09:** [v2.1.1](https://github.com/zhayujie/CowAgent/releases/tag/2.1.1) — Self-Evolution, Web console upgrades (message management, parallel sessions), cross-platform MCP enhancements with concurrent calls, new models (MiniMax-M3, qwen3.7-plus), Python 3.13 support.
+
+> **2026.06.01:** [v2.1.0](https://github.com/zhayujie/CowAgent/releases/tag/2.1.0) — Internationalization, new channels (Telegram, Discord, Slack, WeChat Customer Service), CLI interaction upgrades, streamlined one-line install, MCP Streamable HTTP support, new models (claude-opus-4-8, MiMo).
+
+> **2026.05.22:** [v2.0.9](https://github.com/zhayujie/CowAgent/releases/tag/2.0.9) — Model management, MCP protocol support, persistent browser sessions, new models (gpt-5.5, gemini-3.5-flash, qwen3.7-max), deployment hardening.
+
+> **2026.05.06:** [v2.0.8](https://github.com/zhayujie/CowAgent/releases/tag/2.0.8) — Feishu channel overhaul (voice, streaming, QR onboarding), DeepSeek V4 and Baidu Qianfan support, scheduler tool upgrades.
+
+> **2026.04.22:** [v2.0.7](https://github.com/zhayujie/CowAgent/releases/tag/2.0.7) — Built-in image generation (GPT Image 2, Nano Banana), new models (Kimi K2.6, Claude Opus 4.7, GLM 5.1), memory and knowledge enhancements.
+
+> **2026.04.14:** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — Knowledge base, Deep Dream memory distillation, smart context compression, multi-session Web console.
+
+> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI, Skill Hub open source, browser tool, WeCom Bot QR onboarding.
+
+> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — Major upgrade to a super Agent assistant with multi-step task planning, long-term memory, and the Skills framework.
+
+Full history: [Release Notes](https://docs.cowagent.ai/releases/overview)
+
+<br/>
+
+## 🤝 Community & Support
+
+[File an issue](https://github.com/zhayujie/CowAgent/issues) on GitHub, or scan the QR code below to join our WeChat community:
+
+<img width="130" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png">
+
+<br/>
+
+## 🔗 Related Projects
+
+- **[Cow Skill Hub](https://github.com/zhayujie/cow-skill-hub)** — open skill marketplace for AI Agents; works with CowAgent, OpenClaw, Claude Code, and more
+- **[bot-on-anything](https://github.com/zhayujie/bot-on-anything)** — lightweight LLM application framework with integrations for Slack, Telegram, Discord, Gmail, and more
+- **[AgentMesh](https://github.com/MinimalFuture/AgentMesh)** — open-source multi-agent framework for solving complex problems through team collaboration
+
+<br/>
+
+## 🏢 Enterprise Services
+
+[**LinkAI**](https://link-ai.tech/) is an all-in-one AI Agent platform for enterprises and developers, offering managed hosting and enterprise-grade support for CowAgent:
+
+- **🚀 Zero-deployment hosted runtime** — spin up a [CowAgent online assistant](https://link-ai.tech/cowagent/create) in under a minute, no server required
+- **🧠 Agent infrastructure** — unified access to LLMs, knowledge bases, databases, skills, and workflows; plug-and-play building blocks that extend what CowAgent can do
+- **🏢 Team & enterprise features** — workspaces, role-based access, audit logs, and private deployment for production use cases
+
+For enterprise inquiries: sales@simple-future.tech or [scan the QR code](https://cdn.link-ai.tech/consultant.jpg) to reach our team on WeChat.
+
+<br/>
+
+## 🛠️ Development & Contributing
+
+All kinds of contributions are welcome — new features, bug fixes, performance improvements, docs, or sharing your own skills on the [Skill Hub](https://skills.cowagent.ai/submit). See [CONTRIBUTING.md](/CONTRIBUTING.md) to get started, then open an Issue to discuss or send a PR directly.
+
+⭐ Star the project to show your support, and Watch → Custom → Releases to get notified of new versions. PRs and Issues are always welcome.
+
+## 🌟 Contributors
+
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
+
+<br/>
+
+## ⚠️ Disclaimer
+
+1. This project is licensed under the [MIT License](/LICENSE) and is intended for technical research and learning. You are responsible for complying with applicable laws and regulations in your jurisdiction; the maintainers assume no liability for any consequences arising from use of this project.
+2. **Cost & safety:** Agent mode consumes substantially more tokens than regular chat — pick models that balance quality and cost. The Agent has access to your local operating system, so only deploy it in trusted environments.
+3. CowAgent is a pure open-source project and does not participate in, authorize, or issue any cryptocurrency.
+
+<br/>
+
+## 📌 Project Renaming Notice
+
+This project was previously named `chatgpt-on-wechat` and is now officially **CowAgent**. The old GitHub URL redirects automatically; existing users may optionally run `git remote set-url origin https://github.com/zhayujie/CowAgent.git` to update the local remote.
diff --git a/README.wehub.md b/README.wehub.md
new file mode 100644
index 0000000..2efa67b
--- /dev/null
+++ b/README.wehub.md
@@ -0,0 +1,7 @@
+# WeHub 来源说明
+
+- 原始项目：`zhayujie/CowAgent`
+- 原始仓库：https://github.com/zhayujie/CowAgent
+- 导入方式：上游默认分支的最新快照
+- 原作者、版权和许可证信息以原始仓库及本仓库 LICENSE 为准
+- 本文件仅用于记录来源，不代表 WeHub 是原项目作者
diff --git a/agent/chat/__init__.py b/agent/chat/__init__.py
new file mode 100644
index 0000000..69a90a9
--- /dev/null
+++ b/agent/chat/__init__.py
@@ -0,0 +1,3 @@
+from agent.chat.service import ChatService
+
+__all__ = ["ChatService"]
diff --git a/agent/chat/service.py b/agent/chat/service.py
new file mode 100644
index 0000000..66e9179
--- /dev/null
+++ b/agent/chat/service.py
@@ -0,0 +1,374 @@
+"""
+ChatService - Wraps the Agent stream execution to produce CHAT protocol chunks.
+
+Translates agent events (message_update, message_end, tool_execution_end, etc.)
+into the CHAT socket protocol format (content chunks with segment_id, tool_calls chunks).
+"""
+
+import time
+from typing import Callable, Optional
+
+from common.log import logger
+
+
+class ChatService:
+    """
+    High-level service that runs an Agent for a given query and streams
+    the results as CHAT protocol chunks via a callback.
+
+    Usage:
+        svc = ChatService(agent_bridge)
+        svc.run(query, session_id, send_chunk_fn)
+    """
+
+    def __init__(self, agent_bridge):
+        """
+        :param agent_bridge: AgentBridge instance (manages agent lifecycle)
+        """
+        self.agent_bridge = agent_bridge
+
+    def run(self, query: str, session_id: str, send_chunk_fn: Callable[[dict], None],
+            channel_type: str = ""):
+        """
+        Run the agent for *query* and stream results back via *send_chunk_fn*.
+
+        The method blocks until the agent finishes. After it returns the SDK
+        will automatically send the final (streaming=false) message.
+
+        :param query: user query text
+        :param session_id: session identifier for agent isolation
+        :param send_chunk_fn: callable(chunk_data: dict) to send a streaming chunk
+        :param channel_type: source channel (e.g. "web", "feishu") for persistence
+        """
+        agent = self.agent_bridge.get_agent(session_id=session_id)
+        if agent is None:
+            raise RuntimeError("Failed to initialise agent for the session")
+
+        # Pass context metadata to model for downstream API requests
+        if hasattr(agent, 'model'):
+            agent.model.channel_type = channel_type or ""
+            agent.model.session_id = session_id or ""
+
+        # Build a context so context-aware tools (e.g. scheduler) can resolve the
+        # receiver/session. This streaming path bypasses agent_bridge.agent_reply,
+        # so the attach step that normally happens there must be done here too.
+        context = self._build_context(query, session_id, channel_type)
+        self._attach_context_aware_tools(agent, context)
+
+        # Mark this session as mid-run so the self-evolution idle scan does not
+        # fire concurrently when a single turn runs longer than idle_minutes.
+        self._mark_run_active(agent, True)
+
+        # State shared between the event callback and this method
+        state = _StreamState()
+
+        def on_event(event: dict):
+            """Translate agent events into CHAT protocol chunks."""
+            event_type = event.get("type")
+            data = event.get("data", {})
+
+            if event_type == "reasoning_update":
+                delta = data.get("delta", "")
+                if delta:
+                    send_chunk_fn({
+                        "chunk_type": "reasoning",
+                        "delta": delta,
+                        "segment_id": state.segment_id,
+                    })
+
+            elif event_type == "message_update":
+                # Incremental text delta
+                delta = data.get("delta", "")
+                if delta:
+                    send_chunk_fn({
+                        "chunk_type": "content",
+                        "delta": delta,
+                        "segment_id": state.segment_id,
+                    })
+
+            elif event_type == "message_end":
+                # A content segment finished.
+                tool_calls = data.get("tool_calls", [])
+                if tool_calls:
+                    # After tool_calls are executed the next content will be
+                    # a new segment; collect tool results until turn_end.
+                    state.pending_tool_results = []
+
+            elif event_type == "file_to_send":
+                url = data.get("url") or ""
+                if url:
+                    fname = data.get("file_name") or "file"
+                    ft = data.get("file_type") or "file"
+                    if ft == "image":
+                        link = f"![{fname}]({url})"
+                    else:
+                        link = f"[{fname}]({url})"
+                    send_chunk_fn({
+                        "chunk_type": "content",
+                        "delta": "\n\n" + link + "\n\n",
+                        "segment_id": state.segment_id,
+                    })
+                    # Remove url so the model won't repeat it in its reply
+                    data.pop("url", None)
+
+            elif event_type == "tool_execution_start":
+                # Notify the client that a tool is about to run (with its input args)
+                tool_name = data.get("tool_name", "")
+                arguments = data.get("arguments", {})
+                # Cache arguments keyed by tool_call_id so tool_execution_end can include them
+                tool_call_id = data.get("tool_call_id", tool_name)
+                state.pending_tool_arguments[tool_call_id] = arguments
+                send_chunk_fn({
+                    "chunk_type": "tool_start",
+                    "tool": tool_name,
+                    "arguments": arguments,
+                })
+
+            elif event_type == "tool_execution_end":
+                tool_name = data.get("tool_name", "")
+                tool_call_id = data.get("tool_call_id", tool_name)
+                # Retrieve cached arguments from the matching tool_execution_start event
+                arguments = state.pending_tool_arguments.pop(tool_call_id, data.get("arguments", {}))
+                result = data.get("result", "")
+                status = data.get("status", "unknown")
+                execution_time = data.get("execution_time", 0)
+                elapsed_str = f"{execution_time:.2f}s"
+
+                # Serialise result to string if needed
+                if not isinstance(result, str):
+                    import json
+                    try:
+                        result = json.dumps(result, ensure_ascii=False)
+                    except Exception:
+                        result = str(result)
+
+                tool_info = {
+                    "name": tool_name,
+                    "arguments": arguments,
+                    "result": result,
+                    "status": status,
+                    "elapsed": elapsed_str,
+                }
+
+                if state.pending_tool_results is not None:
+                    state.pending_tool_results.append(tool_info)
+
+            elif event_type == "turn_end":
+                has_tool_calls = data.get("has_tool_calls", False)
+                if has_tool_calls and state.pending_tool_results:
+                    # Flush collected tool results as a single tool_calls chunk
+                    send_chunk_fn({
+                        "chunk_type": "tool_calls",
+                        "tool_calls": state.pending_tool_results,
+                    })
+                    state.pending_tool_results = None
+                    # Next content belongs to a new segment
+                    state.segment_id += 1
+
+        # Run the agent with our event callback ---------------------------
+        logger.info(f"[ChatService] Starting agent run: session={session_id}, query={query[:80]}")
+
+        from config import conf
+        max_context_turns = conf().get("agent_max_context_turns", 20)
+
+        # Get full system prompt with skills
+        full_system_prompt = agent.get_full_system_prompt()
+
+        # Create a copy of messages for this execution
+        with agent.messages_lock:
+            messages_copy = agent.messages.copy()
+            original_length = len(agent.messages)
+
+        from agent.protocol.agent_stream import AgentStreamExecutor
+
+        # Register a cancel token so /cancel can abort this in-flight run.
+        # IM channels key on session_id (no per-turn request_id here).
+        from agent.protocol import get_cancel_registry
+        registry = get_cancel_registry()
+        cancel_event = registry.register(session_id, session_id=session_id) if session_id else None
+
+        executor = AgentStreamExecutor(
+            agent=agent,
+            model=agent.model,
+            system_prompt=full_system_prompt,
+            tools=agent.tools,
+            max_turns=agent.max_steps,
+            on_event=on_event,
+            messages=messages_copy,
+            max_context_turns=max_context_turns,
+            cancel_event=cancel_event,
+        )
+
+        try:
+            response = executor.run_stream(query)
+        except Exception:
+            # If executor cleared messages (context overflow), sync back
+            if len(executor.messages) == 0:
+                with agent.messages_lock:
+                    agent.messages.clear()
+                    logger.info("[ChatService] Cleared agent message history after executor recovery")
+            raise
+        finally:
+            # Clear the mid-run flag so idle scans can review this session again.
+            self._mark_run_active(agent, False)
+            # Release cancel token to keep the registry bounded.
+            if session_id:
+                try:
+                    registry.unregister(session_id)
+                except Exception:
+                    pass
+
+        # Sync executor messages back to agent (thread-safe).
+        # The executor may have trimmed context, making its list shorter than
+        # original_length. In that case we must replace entirely — just
+        # appending would leave stale pre-trim messages in agent.messages
+        # and cause the same trim to fire on every subsequent request.
+        with agent.messages_lock:
+            trimmed = len(executor.messages) < original_length
+            if trimmed:
+                # Context was trimmed: the executor appended the new user
+                # query *before* trimming, so the new messages (user +
+                # assistant + tools) sit at the tail of the trimmed list.
+                # We cannot simply slice at original_length (it exceeds the
+                # list length).  Instead, count how many messages the
+                # executor added on top of the post-trim baseline.
+                #
+                # Timeline inside executor.run_stream:
+                #   1. messages had `original_length` items
+                #   2. append user query  → original_length + 1
+                #   3. _trim_messages()   → some smaller number (includes the
+                #      user query because it belongs to the last turn)
+                #   4. LLM replies / tool calls appended
+                #
+                # The user query message is always the first message of the
+                # last turn (it cannot be trimmed away), so we locate it to
+                # find where "new" messages begin.
+                new_start = original_length  # fallback
+                for idx in range(len(executor.messages) - 1, -1, -1):
+                    msg = executor.messages[idx]
+                    if msg.get("role") == "user":
+                        content = msg.get("content", [])
+                        is_user_query = False
+                        if isinstance(content, list):
+                            has_text = any(
+                                isinstance(b, dict) and b.get("type") == "text"
+                                for b in content
+                            )
+                            has_tool_result = any(
+                                isinstance(b, dict) and b.get("type") == "tool_result"
+                                for b in content
+                            )
+                            is_user_query = has_text and not has_tool_result
+                        elif isinstance(content, str):
+                            is_user_query = True
+                        if is_user_query:
+                            new_start = idx
+                            break
+                new_messages = list(executor.messages[new_start:])
+            else:
+                new_messages = list(executor.messages[original_length:])
+            agent.messages = list(executor.messages)
+
+        # Persist new messages to SQLite so they survive restarts and
+        # can be queried via the HISTORY interface.
+        if new_messages:
+            self._persist_messages(session_id, list(new_messages), channel_type)
+
+        # Store executor reference for files_to_send access
+        agent.stream_executor = executor
+
+        # Execute post-process tools
+        agent._execute_post_process_tools()
+
+        # Record this user turn for the self-evolution idle trigger. This
+        # streaming path bypasses agent_bridge.agent_reply, so the activity must
+        # be noted here, otherwise idle scans never see any signal to evolve.
+        self._note_evolution_turn(agent, context)
+
+        logger.info(f"[ChatService] Agent run completed: session={session_id}")
+
+
+
+    @staticmethod
+    def _build_context(query: str, session_id: str, channel_type: str):
+        """Build a Context for tool resolution on the streaming chat path.
+
+        receiver falls back to session_id; the scheduler's delivery keys on
+        session_id as the receiver.
+        """
+        from bridge.context import Context, ContextType
+        # Pass an explicit kwargs dict: Context's default kwargs is a shared
+        # mutable default, so omitting it would leak fields across sessions.
+        ctx = Context(ContextType.TEXT, query, kwargs={})
+        ctx["session_id"] = session_id
+        ctx["receiver"] = session_id
+        ctx["isgroup"] = False
+        ctx["channel_type"] = channel_type or ""
+        return ctx
+
+    @staticmethod
+    def _attach_context_aware_tools(agent, context):
+        """Attach the current context to tools that need it (scheduler)."""
+        try:
+            if not (context and getattr(agent, "tools", None)):
+                return
+            for tool in agent.tools:
+                if tool.name == "scheduler":
+                    from agent.tools.scheduler.integration import attach_scheduler_to_tool
+                    attach_scheduler_to_tool(tool, context)
+                    break
+        except Exception as e:
+            logger.warning(f"[ChatService] Failed to attach context to scheduler: {e}")
+
+    @staticmethod
+    def _mark_run_active(agent, active):
+        """Toggle the self-evolution mid-run flag for this session's agent."""
+        try:
+            from agent.evolution.trigger import mark_run_active
+            mark_run_active(agent, active)
+        except Exception:
+            pass
+
+    @staticmethod
+    def _note_evolution_turn(agent, context):
+        """Record a user turn so the self-evolution idle trigger has signal."""
+        try:
+            from agent.evolution.trigger import note_user_turn
+            ch = (context.get("channel_type") or "") if context else ""
+            rcv = (context.get("receiver") or "") if context else ""
+            is_group = bool(context.get("isgroup")) if context else False
+            # Only single chats get a proactive push target; group push is noisy.
+            note_user_turn(agent, channel_type=ch, receiver=(rcv if not is_group else ""))
+        except Exception:
+            pass
+
+    @staticmethod
+    def _persist_messages(session_id: str, new_messages: list, channel_type: str = ""):
+        try:
+            from config import conf
+            if not conf().get("conversation_persistence", True):
+                return
+        except Exception:
+            pass
+        try:
+            from agent.memory import get_conversation_store
+            get_conversation_store().append_messages(
+                session_id, new_messages, channel_type=channel_type
+            )
+        except Exception as e:
+            logger.warning(
+                f"[ChatService] Failed to persist messages for session={session_id}: {e}"
+            )
+
+
+class _StreamState:
+    """Mutable state shared between the event callback and the run method."""
+
+    def __init__(self):
+        self.segment_id: int = 0
+        # None means we are not accumulating tool results right now.
+        # A list means we are in the middle of a tool-execution phase.
+        self.pending_tool_results: Optional[list] = None
+        # Maps tool_call_id -> arguments captured from tool_execution_start,
+        # so that tool_execution_end can attach the correct input args.
+        self.pending_tool_arguments: dict = {}
diff --git a/agent/chat/session_service.py b/agent/chat/session_service.py
new file mode 100644
index 0000000..86bf153
--- /dev/null
+++ b/agent/chat/session_service.py
@@ -0,0 +1,241 @@
+"""
+SessionService - Manages multi-session lifecycle for both web channel and cloud client.
+
+Provides a unified interface for listing, deleting, renaming, clearing context,
+and generating AI titles for conversation sessions. Backed by ConversationStore
+(SQLite) and AgentBridge (in-memory agent instances).
+"""
+
+import re
+from typing import Optional
+
+from common.log import logger
+
+
+def _truncate_fallback_title(user_message: str, max_len: int = 30) -> str:
+    """Pick the first non-empty line of the user message and truncate it."""
+    if not user_message:
+        return "New Chat"
+    first_line = ""
+    for line in user_message.splitlines():
+        line = line.strip()
+        if line:
+            first_line = line
+            break
+    if not first_line:
+        return "New Chat"
+    if len(first_line) > max_len:
+        first_line = first_line[:max_len].rstrip() + "..."
+    return first_line
+
+
+def generate_session_title(user_message: str, assistant_reply: str = "") -> str:
+    """
+    Generate a short session title by calling the current bot's reply_text.
+    Falls back to the first line of the user message if the LLM call fails
+    or returns an obvious error sentinel.
+    """
+    fallback = _truncate_fallback_title(user_message)
+    try:
+        from bridge.bridge import Bridge
+        from models.session_manager import Session
+        bot = Bridge().get_bot("chat")
+
+        prompt_parts = [f"User: {user_message[:300]}"]
+        if assistant_reply:
+            prompt_parts.append(f"Assistant: {assistant_reply[:300]}")
+
+        session = Session("__title_gen__", system_prompt="")
+        session.messages = [
+            {"role": "user", "content": (
+                "Generate a very short title (max 15 characters for Chinese, max 6 words for English) "
+                "summarizing this conversation. Return ONLY the title text, nothing else.\n\n"
+                + "\n".join(prompt_parts)
+            )}
+        ]
+
+        result = bot.reply_text(session) or {}
+        # When bots fail (network error, auth error, rate limit, etc.) they
+        # typically return completion_tokens=0 with a sentinel content like
+        # "请再问我一次吧" / "我现在有点累了". Treat that as failure.
+        completion_tokens = result.get("completion_tokens", 0) or 0
+        raw = (result.get("content") or "").strip()
+        if completion_tokens <= 0:
+            logger.warning(
+                f"[SessionService] Title generation got empty completion "
+                f"(completion_tokens={completion_tokens}, content='{raw[:50]}'), "
+                f"using fallback")
+            return fallback
+
+        title = re.sub(r'<think>.*?</think>', '', raw, flags=re.DOTALL).strip().strip('"\'')
+        logger.info(f"[SessionService] Title generation result: '{title}' (len={len(title)})")
+        if title and len(title) <= 50:
+            return title
+    except Exception as e:
+        logger.warning(f"[SessionService] Title generation failed: {e}")
+    return fallback
+
+
+class SessionService:
+    """
+    High-level service for session lifecycle management.
+
+    Usage:
+        svc = SessionService()
+        result = svc.dispatch("list", {"channel_type": "web", "page": 1})
+    """
+
+    def _get_store(self):
+        from agent.memory import get_conversation_store
+        return get_conversation_store()
+
+    def _remove_agent(self, session_id: str):
+        """Remove the in-memory Agent instance for a session if it exists."""
+        try:
+            from bridge.bridge import Bridge
+            ab = Bridge().get_agent_bridge()
+            if session_id in ab.agents:
+                del ab.agents[session_id]
+                logger.info(f"[SessionService] Removed agent instance: {session_id}")
+        except Exception:
+            pass
+
+    @staticmethod
+    def _normalize_sid(session_id: str) -> str:
+        if session_id and not session_id.startswith("session_"):
+            return f"session_{session_id}"
+        return session_id
+
+    # ------------------------------------------------------------------
+    # actions
+    # ------------------------------------------------------------------
+    def list_sessions(self, channel_type: Optional[str] = None,
+                      page: int = 1, page_size: int = 50) -> dict:
+        store = self._get_store()
+        return store.list_sessions(
+            channel_type=channel_type,
+            page=page,
+            page_size=page_size,
+        )
+
+    def delete_session(self, session_id: str) -> None:
+        if not session_id:
+            raise ValueError("session_id required")
+        session_id = self._normalize_sid(session_id)
+
+        store = self._get_store()
+        store.clear_session(session_id)
+        self._remove_agent(session_id)
+        logger.info(f"[SessionService] Session deleted: {session_id}")
+
+    def rename_session(self, session_id: str, title: str) -> None:
+        if not session_id:
+            raise ValueError("session_id required")
+        if not title:
+            raise ValueError("title required")
+        session_id = self._normalize_sid(session_id)
+
+        store = self._get_store()
+        found = store.rename_session(session_id, title)
+        if not found:
+            raise ValueError("session not found")
+
+    def clear_context(self, session_id: str) -> int:
+        """
+        Set context boundary. Returns the new context_start_seq value.
+        """
+        if not session_id:
+            raise ValueError("session_id required")
+        session_id = self._normalize_sid(session_id)
+
+        store = self._get_store()
+        new_seq = store.clear_context(session_id)
+        self._remove_agent(session_id)
+        return new_seq
+
+    def gen_title(self, session_id: str, user_message: str,
+                  assistant_reply: str = "") -> str:
+        """
+        Generate an AI title and persist it. Returns the generated title.
+        """
+        if not session_id:
+            raise ValueError("session_id required")
+        if not user_message:
+            raise ValueError("user_message required")
+        session_id = self._normalize_sid(session_id)
+
+        title = generate_session_title(user_message, assistant_reply)
+
+        store = self._get_store()
+        updated = store.rename_session(session_id, title)
+        logger.info(f"[SessionService] Title set: sid={session_id}, "
+                     f"title='{title}', db_updated={updated}")
+        return title
+
+    # ------------------------------------------------------------------
+    # dispatch — single entry point for protocol messages
+    # ------------------------------------------------------------------
+    def dispatch(self, action: str, payload: Optional[dict] = None) -> dict:
+        """
+        Dispatch a session management action and return a protocol-compatible
+        response dict.
+
+        Action names use a ``*_session`` / session-prefixed convention so they
+        can coexist with history actions (e.g. ``query``) on the same HISTORY
+        message channel without ambiguity.
+
+        Supported actions:
+          - list_sessions: list sessions with pagination
+          - delete_session: delete a session
+          - rename_session: rename a session title
+          - clear_context: set context boundary
+          - generate_title: AI-generate a session title
+
+        :param action: one of the above action names
+        :param payload: action-specific payload
+        :return: dict with action, code, message, payload
+        """
+        payload = payload or {}
+        try:
+            if action == "list_sessions":
+                result = self.list_sessions(
+                    channel_type=payload.get("channel_type"),
+                    page=int(payload.get("page", 1)),
+                    page_size=int(payload.get("page_size", 50)),
+                )
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "delete_session":
+                self.delete_session(payload.get("session_id", ""))
+                return {"action": action, "code": 200, "message": "success", "payload": None}
+
+            elif action == "rename_session":
+                self.rename_session(
+                    payload.get("session_id", ""),
+                    payload.get("title", "").strip(),
+                )
+                return {"action": action, "code": 200, "message": "success", "payload": None}
+
+            elif action == "clear_context":
+                new_seq = self.clear_context(payload.get("session_id", ""))
+                return {"action": action, "code": 200, "message": "success",
+                        "payload": {"context_start_seq": new_seq}}
+
+            elif action == "generate_title":
+                title = self.gen_title(
+                    payload.get("session_id", ""),
+                    payload.get("user_message", ""),
+                    payload.get("assistant_reply", ""),
+                )
+                return {"action": action, "code": 200, "message": "success",
+                        "payload": {"title": title}}
+
+            else:
+                return {"action": action, "code": 400,
+                        "message": f"unknown action: {action}", "payload": None}
+
+        except ValueError as e:
+            return {"action": action, "code": 400, "message": str(e), "payload": None}
+        except Exception as e:
+            logger.error(f"[SessionService] dispatch error: action={action}, error={e}")
+            return {"action": action, "code": 500, "message": str(e), "payload": None}
diff --git a/agent/evolution/__init__.py b/agent/evolution/__init__.py
new file mode 100644
index 0000000..f9f665f
--- /dev/null
+++ b/agent/evolution/__init__.py
@@ -0,0 +1,19 @@
+"""
+Self-evolution subsystem for CowAgent.
+
+Runs a lightweight, isolated review pass after a conversation goes idle to
+decide whether anything is worth durably learning (memory / skill) or whether
+an unfinished task can be pushed forward. Conservative by design: most
+conversations should produce no change at all.
+
+Public entry points:
+    from agent.evolution import get_evolution_config
+    from agent.evolution.trigger import start_evolution_trigger, note_user_turn
+"""
+
+from agent.evolution.config import EvolutionConfig, get_evolution_config
+
+__all__ = [
+    "EvolutionConfig",
+    "get_evolution_config",
+]
diff --git a/agent/evolution/backup.py b/agent/evolution/backup.py
new file mode 100644
index 0000000..4f294b9
--- /dev/null
+++ b/agent/evolution/backup.py
@@ -0,0 +1,102 @@
+"""File backup / rollback support for self-evolution.
+
+Before the evolution agent edits MEMORY.md or a skill file, we snapshot the
+current state into ``memory/.evolution_backups/<backup_id>/`` so a later "undo"
+can restore it. File-level restore only — simple and reliable.
+"""
+
+from __future__ import annotations
+
+import json
+import shutil
+import time
+from datetime import datetime
+from pathlib import Path
+from typing import List, Optional
+
+from common.log import logger
+
+_BACKUP_DIRNAME = ".evolution_backups"
+_MANIFEST_NAME = "manifest.json"
+# Keep only the most recent N backups to bound disk usage.
+_MAX_BACKUPS = 10
+
+
+def _backups_root(workspace_dir: Path) -> Path:
+    return Path(workspace_dir) / "memory" / _BACKUP_DIRNAME
+
+
+def create_backup(workspace_dir: Path, files: List[Path]) -> Optional[str]:
+    """Snapshot ``files`` (those that exist) under a new backup id.
+
+    Returns the backup_id, or None when there is nothing to back up.
+    """
+    existing = [Path(f) for f in files if Path(f).exists()]
+    if not existing:
+        return None
+
+    backup_id = datetime.now().strftime("%Y%m%d-%H%M%S-") + str(int(time.time() * 1000) % 1000)
+    root = _backups_root(workspace_dir)
+    target = root / backup_id
+    try:
+        target.mkdir(parents=True, exist_ok=True)
+        ws = Path(workspace_dir)
+        manifest = []
+        for idx, src in enumerate(existing):
+            # Store under a flat index plus the relative path so restore knows
+            # where it came from, even for nested skill files.
+            try:
+                rel = str(src.relative_to(ws))
+            except ValueError:
+                rel = src.name
+            dst = target / f"{idx}.bak"
+            shutil.copy2(src, dst)
+            manifest.append({"rel": rel, "bak": f"{idx}.bak"})
+        (target / _MANIFEST_NAME).write_text(
+            json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8"
+        )
+        _prune_old_backups(root)
+        # Caller logs a combined backup+review line; keep this at debug.
+        logger.debug(f"[Evolution] Created backup {backup_id} ({len(manifest)} file(s))")
+        return backup_id
+    except Exception as e:
+        logger.warning(f"[Evolution] Failed to create backup: {e}")
+        return None
+
+
+def restore_backup(workspace_dir: Path, backup_id: str) -> bool:
+    """Restore all files captured under ``backup_id``. Returns success."""
+    if not backup_id:
+        return False
+    target = _backups_root(workspace_dir) / backup_id
+    manifest_path = target / _MANIFEST_NAME
+    if not manifest_path.exists():
+        logger.warning(f"[Evolution] Backup not found: {backup_id}")
+        return False
+    try:
+        manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
+        ws = Path(workspace_dir)
+        for entry in manifest:
+            bak = target / entry["bak"]
+            dst = ws / entry["rel"]
+            if bak.exists():
+                dst.parent.mkdir(parents=True, exist_ok=True)
+                shutil.copy2(bak, dst)
+        logger.info(f"[Evolution] Restored backup {backup_id} ({len(manifest)} file(s))")
+        return True
+    except Exception as e:
+        logger.warning(f"[Evolution] Failed to restore backup {backup_id}: {e}")
+        return False
+
+
+def _prune_old_backups(root: Path) -> None:
+    """Drop the oldest backups beyond _MAX_BACKUPS (sorted by name = chronological)."""
+    try:
+        dirs = sorted(
+            [d for d in root.iterdir() if d.is_dir()],
+            key=lambda p: p.name,
+        )
+        for old in dirs[:-_MAX_BACKUPS]:
+            shutil.rmtree(old, ignore_errors=True)
+    except Exception as e:
+        logger.debug(f"[Evolution] Backup prune skipped: {e}")
diff --git a/agent/evolution/config.py b/agent/evolution/config.py
new file mode 100644
index 0000000..948876f
--- /dev/null
+++ b/agent/evolution/config.py
@@ -0,0 +1,76 @@
+"""Configuration for the self-evolution subsystem.
+
+Reads flat ``self_evolution_*`` keys from config.json. All fields have safe
+defaults so the feature degrades gracefully when keys are absent.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any
+
+
+# Defaults — conservative (see executor module docstring). Disabled by default
+# until release; enable via ``self_evolution_enabled``.
+DEFAULT_ENABLED = False
+DEFAULT_IDLE_MINUTES = 10
+DEFAULT_MIN_TURNS = 6
+# Max review steps for the isolated evolution agent. Kept small (not exposed as
+# config): the review is meant to be cheap and focused, not a long autonomous run.
+DEFAULT_MAX_STEPS = 12
+
+
+@dataclass
+class EvolutionConfig:
+    """Resolved self-evolution settings."""
+
+    enabled: bool = DEFAULT_ENABLED
+    idle_minutes: int = DEFAULT_IDLE_MINUTES
+    min_turns: int = DEFAULT_MIN_TURNS
+    max_steps: int = DEFAULT_MAX_STEPS
+
+    @property
+    def idle_seconds(self) -> int:
+        return max(60, self.idle_minutes * 60)
+
+
+def _as_bool(value: Any, fallback: bool) -> bool:
+    if isinstance(value, bool):
+        return value
+    if isinstance(value, str):
+        v = value.strip().lower()
+        if v in ("true", "1", "yes", "on"):
+            return True
+        if v in ("false", "0", "no", "off"):
+            return False
+    return fallback
+
+
+def _as_pos_int(value: Any, fallback: int) -> int:
+    try:
+        n = int(value)
+        return n if n > 0 else fallback
+    except (TypeError, ValueError):
+        return fallback
+
+
+def get_evolution_config() -> EvolutionConfig:
+    """Build EvolutionConfig from the live config.json ``self_evolution_*`` keys."""
+    try:
+        from config import conf
+        c = conf()
+    except Exception:
+        c = {}
+
+    def _get(key, default):
+        try:
+            return c.get(key, default)
+        except Exception:
+            return default
+
+    return EvolutionConfig(
+        enabled=_as_bool(_get("self_evolution_enabled", None), DEFAULT_ENABLED),
+        idle_minutes=_as_pos_int(_get("self_evolution_idle_minutes", None), DEFAULT_IDLE_MINUTES),
+        min_turns=_as_pos_int(_get("self_evolution_min_turns", None), DEFAULT_MIN_TURNS),
+        max_steps=DEFAULT_MAX_STEPS,
+    )
diff --git a/agent/evolution/executor.py b/agent/evolution/executor.py
new file mode 100644
index 0000000..5c418f3
--- /dev/null
+++ b/agent/evolution/executor.py
@@ -0,0 +1,556 @@
+"""Self-evolution executor.
+
+Runs an isolated review agent over an idle conversation's transcript and, if a
+clear signal is found, lets it edit memory / skills via a restricted toolset.
+Conservative by design: most runs return ``[SILENT]`` and change nothing.
+
+Flow:
+    1. Build a transcript from the session's new (since last pass) messages.
+    2. Snapshot MEMORY.md + daily file + editable skills (for undo) -> backup_id.
+    3. Run an isolated agent (same model, restricted tools, evolution prompt).
+    4. If output is [SILENT], or no workspace file actually changed -> done.
+    5. Otherwise -> record to the evolution log, inject an [EVOLUTION] note into
+       the user session (so the main agent can honor "undo"), and push the
+       summary to the user's channel.
+
+Reuses existing infrastructure (AgentBridge.create_agent, ToolManager,
+remember_scheduled_output, channel_factory) rather than introducing a fork.
+"""
+
+from __future__ import annotations
+
+import re
+import threading
+from datetime import datetime
+from pathlib import Path
+from typing import List, Optional
+
+from common.log import logger
+
+from agent.evolution.backup import create_backup
+from agent.evolution.config import get_evolution_config
+from agent.evolution.prompts import (
+    EVOLUTION_MARKER,
+    EVOLUTION_SYSTEM_PROMPT,
+    SILENT_TOKEN,
+    build_review_user_message,
+)
+from agent.evolution.record import append_session_evolution
+
+# Tools the isolated evolution agent is allowed to use. Everything else is
+# withheld so a review pass can only read context, run workspace scripts, and
+# edit memory/skill files. bash is needed by skill-creator's init script and is
+# confined to the workspace by _BashWorkspaceGuard.
+_ALLOWED_TOOLS = {"read", "write", "edit", "ls", "bash", "memory_search", "memory_get"}
+
+# Cap concurrent evolution passes so a burst of idle sessions can't spawn many
+# background model runs at once. Extra sessions simply wait for the next scan.
+_MAX_CONCURRENT = 2
+_running_lock = threading.Lock()
+_running_count = 0
+
+
+def _builtin_skill_names() -> set:
+    """Names of skills shipped with the product (project-root ``skills/``).
+
+    These are protected: the evolution agent must never edit them, even though
+    a same-named copy exists in the workspace at runtime. The project dir is the
+    authoritative list of what counts as built-in.
+    """
+    try:
+        # executor.py -> agent/evolution -> agent -> project root
+        project_root = Path(__file__).resolve().parents[2]
+        builtin_dir = project_root / "skills"
+        if not builtin_dir.is_dir():
+            return set()
+        names = set()
+        for entry in builtin_dir.iterdir():
+            if entry.is_dir() and not entry.name.startswith("."):
+                names.add(entry.name)
+        return names
+    except Exception:
+        return set()
+
+
+def _build_transcript(messages: List[dict], max_chars: int = 12000) -> str:
+    """Render the session messages into a compact text transcript."""
+    lines: List[str] = []
+    for msg in messages:
+        role = msg.get("role", "")
+        if role not in ("user", "assistant"):
+            continue
+        content = msg.get("content", "")
+        text = _extract_text(content)
+        if not text.strip():
+            continue
+        speaker = "User" if role == "user" else "Assistant"
+        lines.append(f"{speaker}: {text.strip()}")
+    transcript = "\n".join(lines)
+    # Keep the most RECENT context if oversized (tail is most relevant).
+    if len(transcript) > max_chars:
+        transcript = "...(earlier omitted)...\n" + transcript[-max_chars:]
+    return transcript
+
+
+def _extract_text(content) -> str:
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts = []
+        for block in content:
+            if isinstance(block, dict) and block.get("type") == "text":
+                parts.append(block.get("text", ""))
+            elif isinstance(block, str):
+                parts.append(block)
+        return "\n".join(parts)
+    return ""
+
+
+def _select_tools(all_tools: list) -> list:
+    return [t for t in all_tools if getattr(t, "name", None) in _ALLOWED_TOOLS]
+
+
+# Tools whose writes must be confined to the workspace during evolution.
+_WRITE_TOOLS = {"write", "edit"}
+
+
+class _WorkspaceWriteGuard:
+    """Wraps a write/edit tool so it can ONLY write inside the workspace.
+
+    Hard engineering guard (not prompt-based): any write resolving outside the
+    workspace — e.g. the project's bundled ``skills/`` dir — is rejected. This
+    protects built-in skills regardless of what the model attempts.
+    """
+
+    def __init__(self, inner, workspace_dir: str):
+        self._inner = inner
+        self._ws = Path(workspace_dir).resolve()
+        # Mirror the attributes the agent runtime reads off a tool.
+        self.name = inner.name
+        self.description = inner.description
+        self.params = inner.params
+
+    def __getattr__(self, item):
+        return getattr(self._inner, item)
+
+    def execute_tool(self, params):
+        # The agent runtime calls execute_tool (not execute); route it through
+        # our guarded execute so the path checks always run.
+        try:
+            return self.execute(params)
+        except Exception as e:
+            logger.error(f"[Evolution] guarded tool error: {e}")
+            from agent.tools.base_tool import ToolResult
+            return ToolResult.fail(f"Error: {e}")
+
+    def execute(self, args):
+        path = (args.get("path") or "").strip()
+        if path:
+            try:
+                resolved = Path(self._inner._resolve_path(path)).resolve()
+                from agent.tools.base_tool import ToolResult
+                # Confine writes to the workspace. This protects the product's
+                # bundled skills (which live outside the workspace) from ever
+                # being modified, no matter what path the model attempts.
+                if self._ws not in resolved.parents and resolved != self._ws:
+                    return ToolResult.fail(
+                        "Error: evolution may only write inside the workspace; "
+                        f"path '{path}' is outside and was blocked."
+                    )
+            except Exception:
+                pass
+        return self._inner.execute(args)
+
+
+class _BashWorkspaceGuard:
+    """Wraps the bash tool so evolution can only run commands inside the
+    workspace.
+
+    Evolution needs bash for skill-creator's init script, but it runs
+    unattended in the background, so a raw shell is too broad. This guard:
+      - forces the command to execute with cwd = workspace,
+      - rejects commands that reference an absolute path or ``..`` segment
+        pointing OUTSIDE the workspace (the common ways to escape it).
+    It is a coarse textual check, not a sandbox — paired with the model's
+    instruction to only run skill-creator scripts, it keeps writes local.
+    """
+
+    def __init__(self, inner, workspace_dir: str):
+        self._inner = inner
+        self._ws = Path(workspace_dir).resolve()
+        # Pin the shell's working directory to the workspace.
+        try:
+            self._inner.cwd = str(self._ws)
+        except Exception:
+            pass
+        self.name = inner.name
+        self.description = inner.description
+        self.params = inner.params
+
+    def __getattr__(self, item):
+        return getattr(self._inner, item)
+
+    def execute_tool(self, params):
+        try:
+            return self.execute(params)
+        except Exception as e:
+            logger.error(f"[Evolution] guarded bash error: {e}")
+            from agent.tools.base_tool import ToolResult
+            return ToolResult.fail(f"Error: {e}")
+
+    def _escapes_workspace(self, command: str) -> bool:
+        # Absolute paths that are not under the workspace.
+        for tok in re.findall(r'(?:^|\s)(/[^\s\'";|&]+)', command):
+            try:
+                resolved = Path(tok).resolve()
+            except Exception:
+                continue
+            if self._ws != resolved and self._ws not in resolved.parents:
+                return True
+        # Parent-dir traversal that climbs above the workspace.
+        for tok in re.findall(r'[^\s\'";|&]*\.\.[^\s\'";|&]*', command):
+            try:
+                resolved = (self._ws / tok).resolve()
+            except Exception:
+                continue
+            if self._ws != resolved and self._ws not in resolved.parents:
+                return True
+        return False
+
+    def execute(self, args):
+        from agent.tools.base_tool import ToolResult
+        command = (args.get("command") or "").strip()
+        if command and self._escapes_workspace(command):
+            return ToolResult.fail(
+                "Error: evolution may only run commands inside the workspace; "
+                "this command references a path outside it and was blocked."
+            )
+        return self._inner.execute(args)
+
+
+def _guard_tools(tools: list, workspace_dir: str) -> list:
+    """Wrap write/edit/bash tools with workspace guards; leave others as-is."""
+    guarded = []
+    for t in tools:
+        name = getattr(t, "name", None)
+        if name in _WRITE_TOOLS:
+            guarded.append(_WorkspaceWriteGuard(t, workspace_dir))
+        elif name == "bash":
+            guarded.append(_BashWorkspaceGuard(t, workspace_dir))
+        else:
+            guarded.append(t)
+    return guarded
+
+
+# Workspace subtrees worth watching for evolution-induced changes. AGENT.md is
+# watched too: evolution may rarely refine the assistant's persona/style there.
+_WATCH_SUBDIRS = ("MEMORY.md", "AGENT.md", "skills", "knowledge", "output")
+# Subpaths under memory/ to ignore: evolution's own bookkeeping + the nightly
+# dream diary, none of which count as a user-facing change signal.
+_MEMORY_IGNORE = (".evolution_backups", "dreams", "evolution")
+# Files the skill subsystem maintains automatically (the enable/disable index).
+# Not an evolution result, so a rewrite must not count as a change signal.
+_WATCH_IGNORE_NAMES = ("skills_config.json",)
+
+
+def _workspace_snapshot(workspace_dir) -> dict:
+    """Map relative path -> (mtime, size) for watched files. Cheap, no reads."""
+    ws = Path(workspace_dir)
+    snap: dict = {}
+    for name in _WATCH_SUBDIRS:
+        root = ws / name
+        if root.is_file():
+            try:
+                st = root.stat()
+                snap[name] = (st.st_mtime, st.st_size)
+            except OSError:
+                pass
+            continue
+        if not root.is_dir():
+            continue
+        for p in root.rglob("*"):
+            if not p.is_file():
+                continue
+            if p.name in _WATCH_IGNORE_NAMES:
+                continue
+            try:
+                st = p.stat()
+                snap[str(p.relative_to(ws))] = (st.st_mtime, st.st_size)
+            except OSError:
+                pass
+
+    # Watch the daily memory files (memory/*.md and per-user dailies) since
+    # evolution now records learnings there. Skip backups/dreams bookkeeping.
+    mem_dir = ws / "memory"
+    if mem_dir.is_dir():
+        for p in mem_dir.rglob("*.md"):
+            rel_parts = p.relative_to(mem_dir).parts
+            if rel_parts and rel_parts[0] in _MEMORY_IGNORE:
+                continue
+            try:
+                st = p.stat()
+                snap[str(p.relative_to(ws))] = (st.st_mtime, st.st_size)
+            except OSError:
+                pass
+    return snap
+
+
+def _workspace_changed(workspace_dir, pre: dict) -> bool:
+    """True if any watched file was added, removed, or modified since ``pre``."""
+    return _workspace_snapshot(workspace_dir) != pre
+
+
+def run_evolution_for_session(
+    agent_bridge,
+    session_id: str,
+    channel_type: str = "",
+    receiver: str = "",
+    user_id: Optional[str] = None,
+    idle_minutes: float = 0.0,
+) -> bool:
+    """Run one evolution pass for a session. Returns True if it changed anything.
+
+    Safe to call from a background thread. All failures are swallowed and
+    logged — evolution must never disrupt the main pipeline.
+    """
+    cfg = get_evolution_config()
+    if not cfg.enabled:
+        return False
+
+    # Concurrency gate: bound how many evolution passes run at once.
+    global _running_count
+    with _running_lock:
+        if _running_count >= _MAX_CONCURRENT:
+            logger.info(
+                f"[Evolution] busy ({_running_count}/{_MAX_CONCURRENT} running); "
+                f"skipping session={session_id} this scan"
+            )
+            return False
+        _running_count += 1
+
+    try:
+        agent = agent_bridge.agents.get(session_id) or agent_bridge.default_agent
+        if not agent:
+            return False
+
+        with agent.messages_lock:
+            all_messages = list(agent.messages)
+        total_msgs = len(all_messages)
+        # In-memory evolution cursor: only review messages added since the last
+        # pass so a long session doesn't re-judge (and re-write) old content.
+        # Stored on the agent instance; lost on restart (acceptable — at worst
+        # one redundant pass right after a restart, gated by the file-change
+        # check downstream so it won't double-write identical memory).
+        done = int(getattr(agent, "_evo_done_msg_count", 0))
+        if done > total_msgs:
+            done = 0  # history was trimmed/reset; start fresh
+        new_messages = all_messages[done:]
+        transcript = _build_transcript(new_messages)
+        if not transcript.strip():
+            # Routine no-op: the per-minute scan hits every idle session. Advance
+            # the cursor so we don't re-scan the same tail; no log (pure noise).
+            agent._evo_done_msg_count = total_msgs
+            return False
+
+        logger.info(
+            f"[Evolution] ▶ Reviewing session={session_id} "
+            f"(idle {idle_minutes:.1f}min, {len(new_messages)} new/{total_msgs} msgs, "
+            f"~{len(transcript)} chars)"
+        )
+
+        # Resolve workspace + files to snapshot for undo.
+        from agent.memory.config import get_default_memory_config
+        mem_cfg = get_default_memory_config()
+        workspace_dir = mem_cfg.get_workspace()
+        if user_id:
+            memory_file = Path(workspace_dir) / "memory" / "users" / user_id / "MEMORY.md"
+        else:
+            memory_file = Path(workspace_dir) / "MEMORY.md"
+        skills_dir = mem_cfg.get_skills_dir()
+
+        # Snapshot MEMORY.md + every NON-protected skill's SKILL.md. Protected
+        # built-in skills are excluded from backup because they must never be
+        # edited in the first place.
+        protected_names = _builtin_skill_names()
+        # Back up both MEMORY.md and today's daily file: evolution now writes to
+        # the daily file, but MEMORY.md is cheap to snapshot and keeps undo safe
+        # if the model ever edits it.
+        today_daily = Path(workspace_dir) / "memory" / (
+            datetime.now().strftime("%Y-%m-%d") + ".md"
+        )
+        if user_id:
+            today_daily = Path(workspace_dir) / "memory" / "users" / user_id / (
+                datetime.now().strftime("%Y-%m-%d") + ".md"
+            )
+        # AGENT.md (persona) is backed up too so a rare persona edit is undoable.
+        # Persona is workspace-global (not per-user): it always lives at the
+        # workspace root, regardless of user_id.
+        agent_file = Path(workspace_dir) / "AGENT.md"
+        backup_files = [Path(memory_file), today_daily, agent_file]
+        if skills_dir.exists():
+            for skill_md in skills_dir.rglob("SKILL.md"):
+                # The skill dir is the SKILL.md's parent (or an ancestor for
+                # collections); guard by checking the immediate top-level dir.
+                try:
+                    top = skill_md.relative_to(skills_dir).parts[0]
+                except (ValueError, IndexError):
+                    continue
+                if top in protected_names:
+                    continue
+                backup_files.append(skill_md)
+        backup_id = create_backup(workspace_dir, backup_files)
+        _backup_n = sum(1 for f in backup_files if Path(f).exists())
+
+        # Snapshot the whole workspace (path -> mtime/size) so we can reliably
+        # detect ANY file change — including new output files written when
+        # finishing an unfinished task, which are not in backup_files.
+        pre_snapshot = _workspace_snapshot(workspace_dir)
+
+        # Build the isolated review agent: same model, restricted tools, with a
+        # hard guard that confines all writes to the workspace (protects the
+        # project's bundled skills from ever being modified).
+        review_tools = _guard_tools(
+            _select_tools(list(getattr(agent, "tools", []) or [])),
+            str(workspace_dir),
+        )
+        review_agent = agent_bridge.create_agent(
+            system_prompt="",
+            tools=review_tools,
+            description="Self-evolution review agent",
+            max_steps=cfg.max_steps,
+            workspace_dir=str(workspace_dir),
+            skill_manager=getattr(agent, "skill_manager", None),
+            memory_manager=getattr(agent, "memory_manager", None),
+            enable_skills=True,
+            runtime_info=getattr(agent, "runtime_info", None),
+        )
+        # Mark this as a restricted review agent so runtime MCP reconciliation
+        # (ToolManager.sync_mcp_into_agent) will NOT silently re-inject MCP tools
+        # that _select_tools()/_guard_tools() intentionally withheld. Without this
+        # flag the review boundary would be re-opened on the first LLM turn.
+        review_agent._evolution_restricted = True
+        # Reuse the live model so it follows the user's configured model.
+        review_agent.model = agent.model
+        # Inject the evolution task brief AFTER the full system prompt: the agent
+        # gets the full context (tools, workspace, user preferences, memory, time)
+        # AND its evolution-specific instructions on top, instead of one
+        # overwriting the other.
+        review_agent.extra_system_suffix = EVOLUTION_SYSTEM_PROMPT
+
+        logger.info(
+            f"[Evolution] backup {backup_id} ({_backup_n} files) → running review agent"
+        )
+        user_msg = build_review_user_message(transcript, protected_skills=list(protected_names))
+        result = review_agent.run_stream(user_msg, clear_history=True)
+        result = (result or "").strip()
+
+        # These messages are now reviewed; advance the cursor so the next pass
+        # only looks at messages added after this point (silent or not).
+        agent._evo_done_msg_count = total_msgs
+
+        # Respect an explicit silent verdict: empty, exactly [SILENT], or text
+        # that STARTS with [SILENT] means the model chose to stay quiet.
+        if not result or result.startswith(SILENT_TOKEN):
+            logger.info(f"[Evolution] ✗ No change for session={session_id} ([SILENT])")
+            return False
+
+        # Anti-nag backstop: if the model wrote a summary but actually changed no
+        # watched file, stay silent — never notify about work that didn't happen.
+        if not _workspace_changed(workspace_dir, pre_snapshot):
+            logger.info(
+                f"[Evolution] ✗ session={session_id}: text produced but no file "
+                f"changed — staying silent"
+            )
+            return False
+
+        # The model produced a real summary. Strip any stray [SILENT] tokens it
+        # left mid-text, then notify.
+        result = result.replace(SILENT_TOKEN, "").strip()
+        if not result:
+            logger.info(f"[Evolution] ✗ No change for session={session_id} ([SILENT])")
+            return False
+
+        logger.info(f"[Evolution] ✓ session={session_id} evolved:\n{result}")
+        append_session_evolution(workspace_dir, result, backup_id=backup_id, user_id=user_id)
+        # Inject an [EVOLUTION] note so the main agent can honor "undo".
+        _inject_evolution_record(agent_bridge, session_id, channel_type, result, backup_id)
+        # The injection appended its own messages ([SCHEDULED]/[EVOLUTION]).
+        # Advance the cursor past them so the next scan does not treat
+        # evolution's own bookkeeping as new user content and re-trigger.
+        try:
+            with agent.messages_lock:
+                agent._evo_done_msg_count = len(agent.messages)
+        except Exception:
+            pass
+
+        # Push the summary to the user's channel. The "did a file actually
+        # change" gate above is the only throttle we need: real evolutions are
+        # rare, so no extra opt-in switch or daily-count limit is required.
+        if channel_type and receiver:
+            _notify_user(channel_type, receiver, result)
+
+        return True
+
+    except Exception as e:
+        logger.warning(f"[Evolution] Run failed for session={session_id}: {e}")
+        return False
+    finally:
+        with _running_lock:
+            _running_count -= 1
+
+
+def _inject_evolution_record(
+    agent_bridge, session_id: str, channel_type: str, summary: str, backup_id: Optional[str]
+) -> None:
+    """Add an [EVOLUTION] note to the user session so the main agent can undo."""
+    try:
+        note = f"{EVOLUTION_MARKER} {summary}"
+        if backup_id:
+            note += f"\n(backup_id: {backup_id}; to undo, restore this backup)"
+        # Reuse the scheduler-output injection path: isolated execution, only a
+        # compact record lands in the user session.
+        agent_bridge.remember_scheduled_output(
+            session_id=session_id,
+            content=note,
+            channel_type=channel_type,
+            task_description="self-evolution",
+        )
+    except Exception as e:
+        logger.debug(f"[Evolution] Failed to inject evolution record: {e}")
+
+
+def _notify_user(channel_type: str, receiver: str, summary: str) -> None:
+    """Push the evolution summary to the user's channel as a new message."""
+    try:
+        from bridge.context import Context, ContextType
+        from bridge.reply import Reply, ReplyType
+        from channel.channel_factory import create_channel
+
+        context = Context(ContextType.TEXT, summary)
+        context["receiver"] = receiver
+        context["isgroup"] = False
+        context["session_id"] = receiver
+        # Channels that reply to an original message need msg=None for a fresh push.
+        if channel_type in ("feishu", "dingtalk", "wecom_bot", "qq"):
+            context["msg"] = None
+        if channel_type == "feishu":
+            context["receive_id_type"] = "open_id"
+
+        channel = create_channel(channel_type)
+        if not channel:
+            return
+
+        # Web is request-response: a background push needs a synthetic request_id
+        # plus a request->session mapping so the channel can route the message to
+        # the user's polling queue (same approach the scheduler uses).
+        if channel_type == "web":
+            import uuid
+            request_id = f"evolution_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+            if hasattr(channel, "request_to_session"):
+                channel.request_to_session[request_id] = receiver
+
+        channel.send(Reply(ReplyType.TEXT, summary), context)
+        logger.info(f"[Evolution] Notified user via {channel_type}")
+    except Exception as e:
+        logger.warning(f"[Evolution] Failed to notify user: {e}")
diff --git a/agent/evolution/prompts.py b/agent/evolution/prompts.py
new file mode 100644
index 0000000..649495e
--- /dev/null
+++ b/agent/evolution/prompts.py
@@ -0,0 +1,170 @@
+"""Prompts for the self-evolution review agent.
+
+The system prompt is intentionally English-only: it governs the agent's
+internal reasoning and is more stable / cheaper to maintain in one language.
+The user-facing summary the agent produces should follow the user's own
+language (instructed at the end of the prompt).
+
+Design goals (see ref/hermes-agent background_review for inspiration):
+  - Default to doing NOTHING. Evolution is the exception, not the rule.
+  - Signal types: skill, unfinished task, memory, knowledge.
+  - An explicit "do NOT capture" list to avoid self-poisoning over time.
+  - Generic examples only — never bake in domain-specific business terms.
+"""
+
+# Sentinel the agent emits when there is nothing worth evolving.
+SILENT_TOKEN = "[SILENT]"
+
+# Marker prefix for the evolution record injected into the user session, so the
+# main chat agent can recognize past evolutions and honor an "undo" request.
+EVOLUTION_MARKER = "[EVOLUTION]"
+
+
+EVOLUTION_SYSTEM_PROMPT = """You are a self-evolution review agent for an AI assistant.
+
+You are given a transcript of a conversation that just went idle. Your job is to
+decide whether anything from it is worth durably learning so future
+conversations go better — and if so, to make that change.
+
+# Top principle: default to doing NOTHING
+
+Most ordinary conversations need no evolution. Only act when there is a CLEAR
+signal below. If there is none, reply with exactly `[SILENT]` and stop. Staying
+silent is the normal, correct outcome — not a failure.
+
+Greetings, small talk, acknowledgements ("ok", "thanks", "got it"), and casual
+chat are NOT signals. For these, output exactly `[SILENT]` immediately — do not
+explore files, do not write a summary, do not be polite. Just `[SILENT]`.
+
+IMPORTANT: A summary is only allowed if you ACTUALLY made a file change via a
+tool (write/edit) in this pass. If you did not change any file, you MUST output
+exactly `[SILENT]` — never describe a change you only intended to make.
+
+# Signals worth acting on (act only if at least one clearly appears)
+
+SKILL and UNFINISHED TASK are your PRIMARY value — no other mechanism handles
+them. When their signal is clear, act; do not be shy here.
+
+1. SKILL — two cases:
+   a) PATCH an existing skill: a skill used here showed a STRUCTURAL problem (a
+      missing step/section, a wrong or outdated detail, an error in its
+      content), or its OUTPUT repeatedly misses something the user flagged. Read
+      the relevant skill file under the skills directory and make a small
+      incremental edit so it never recurs.
+   b) CREATE a new skill: a clearly reusable, repeatable workflow emerged that
+      no existing skill covers and the user is likely to want again. Follow the
+      `skill-creator` skill's conventions (read its SKILL.md for the required
+      structure), then create `skills/<name>/SKILL.md` by WRITING the file
+      directly with the write tool — this is the simplest reliable path. (bash
+      is available and confined to the workspace if a helper script is truly
+      needed, but a direct write is preferred.) Only create when the workflow is
+      genuinely reusable — not for a one-off task.
+
+   CRITICAL — fix the SOURCE, do not just remember the symptom: when the root
+   cause of a problem lives IN a skill file itself (its instructions, content,
+   or configuration are wrong/outdated), the correct action is to EDIT that
+   skill so the problem cannot recur. Recording the corrected fact in memory
+   does NOT prevent recurrence — only fixing the skill does. Never log "skill X
+   has wrong detail Y" as a memory note in place of editing skill X.
+
+2. UNFINISHED TASK — a specific deliverable you promised but didn't produce,
+   AND you already have everything needed to finish it. DO IT now with the
+   available tools and produce the result (e.g. write the file you said you'd
+   write). If key info is missing, or the task is merely waiting on the user's
+   reply/decision, do NOTHING and stay [SILENT] — do not nag or ping the user.
+   You only ever notify the user as a side effect of having actually done work.
+
+3. MEMORY — RARE, last resort. Default to writing NOTHING here. The main
+   assistant already writes memory during the chat, and a nightly pass plus
+   context-overflow saves are dedicated safety nets — so memory is almost always
+   already covered without you. Skip unless the main assistant clearly missed a
+   durable fact that belongs in no skill AND would visibly change future replies.
+   - MEMORY.md is the curated long-term index, auto-loaded into EVERY future
+     conversation. Treat it as precious: edit it in place to CORRECT a wrong
+     fact, or append a new durable preference/decision/lesson — but do so
+     SPARINGLY (a lasting fact, not a passing detail; the nightly pass handles
+     routine consolidation).
+   - For a NEW fact that is important but not yet clearly lasting, append ONE
+     short bullet to today's `memory/YYYY-MM-DD.md` instead. When unsure, the
+     daily file is the safe place — but first ask whether this really belongs
+     in a skill.
+   - PERSONA (AGENT.md) — EXTREMELY rare: only on an explicit, repeated signal
+     about the assistant's own identity/personality/style, make a small edit to
+     AGENT.md; never for user/world facts, and when in doubt do nothing.
+   - Keep it to ONE short bullet. Never write paragraphs, never re-summarize the
+     conversation, never copy what the main assistant already recorded.
+   - If it is already captured anywhere (check MEMORY.md AND the daily file
+     first), do NOTHING.
+
+4. KNOWLEDGE — only if the conversation produced durable, reusable reference
+   knowledge on a topic (the kind worth looking up again) that the main
+   assistant did NOT already save to `knowledge/`. Add or update the relevant
+   file there. Like memory, this is the exception: skip routine Q&A, and if the
+   topic is already covered in `knowledge/`, do NOTHING rather than duplicate.
+
+# Do NOT capture (these poison future behavior)
+
+- Environment failures: missing binaries, unset credentials, uninstalled
+  packages, "command not found". The user can fix these; they are not durable
+  rules.
+- Negative claims about tools or features ("tool X does not work"). These
+  harden into refusals the agent cites against itself later.
+- One-off task narratives (e.g. summarizing today's content). Not a class of
+  reusable work.
+- Transient errors that resolved on retry within the conversation.
+
+# Execution constraints
+
+- Before changing memory or a skill, READ the current content first and make a
+  small INCREMENTAL edit. Never fabricate, never rewrite large sections.
+- AVOID DUPLICATES. Before writing memory, READ both MEMORY.md AND today's
+  daily file `memory/YYYY-MM-DD.md`. If the fact/preference is already recorded
+  in EITHER (even if worded differently), do NOT add it again. The main
+  assistant likely already wrote it during the chat — only add what is
+  genuinely new or a correction not yet reflected anywhere.
+- You may only edit files inside the workspace. Built-in skills shipped with
+  the product live outside it and are write-protected; do not try to edit them.
+- Make at most the few edits the signals justify; do not go looking for work.
+
+# Output
+
+- Nothing worth evolving -> output exactly `[SILENT]` and nothing else.
+- Otherwise, after performing the edits, output a short user-facing summary in
+  the SAME LANGUAGE the user speaks in the conversation transcript. Write it for an ordinary user, in plain
+  everyday words — NOT a developer report. No need to expose internal details
+  (file names/paths, system mechanics, etc.). Briefly speak directly TO the user, telling them that you just did a self-learning pass,
+  what you learned, and what you changed in THIS pass. Keep it clear and focused on the key changes (a few lines), and let
+  the user know they can undo it.
+"""
+
+
+def build_review_user_message(transcript: str, protected_skills: list = None) -> str:
+    """Wrap the conversation transcript as the review agent's user message.
+
+    ``protected_skills`` lists skill names that must never be edited (built-in
+    skills shipped with the product). Surfaced so the agent avoids them.
+    """
+    protected_note = ""
+    if protected_skills:
+        names = ", ".join(sorted(protected_skills))
+        protected_note = (
+            "\n\nPROTECTED skills (built-in — never edit these): "
+            f"{names}\n"
+        )
+    try:
+        from common import i18n
+        lang_name = "中文" if i18n.is_zh() else "English"
+    except Exception:
+        lang_name = "中文"
+    return (
+        "Here is the conversation transcript that just went idle. Review it per "
+        "your instructions. Acting is the exception: the main value is fixing or "
+        "creating a skill and finishing promised work. Memory and knowledge are "
+        "rare last resorts — stay [SILENT] unless there is a clear, durable signal "
+        "not already covered."
+        f"{protected_note}\n"
+        f"The summary should preferably be written in: {lang_name}\n"
+        "<transcript>\n"
+        f"{transcript}\n"
+        "</transcript>"
+    )
diff --git a/agent/evolution/record.py b/agent/evolution/record.py
new file mode 100644
index 0000000..751e3a8
--- /dev/null
+++ b/agent/evolution/record.py
@@ -0,0 +1,55 @@
+"""Self-evolution record log.
+
+Session-level evolutions are appended to their OWN per-day file under
+``memory/evolution/YYYY-MM-DD.md`` (separate from the nightly Deep Dream diary
+in ``memory/dreams/``). Each day's file accumulates one short section per
+evolution pass — tagged with a timestamp and a backup id for undo — so the
+memory UI can surface "what the agent learned/changed today" on one timeline
+without ever mixing into the dream diary or the main conversation memory.
+"""
+
+from __future__ import annotations
+
+from datetime import datetime
+from pathlib import Path
+from typing import Optional
+
+from common.log import logger
+
+
+def _evolution_dir(workspace_dir: Path, user_id: Optional[str] = None) -> Path:
+    base = Path(workspace_dir) / "memory"
+    if user_id:
+        return base / "users" / user_id / "evolution"
+    return base / "evolution"
+
+
+def append_session_evolution(
+    workspace_dir: Path,
+    summary: str,
+    backup_id: Optional[str] = None,
+    user_id: Optional[str] = None,
+) -> None:
+    """Append a session-evolution entry to today's evolution log."""
+    if not summary or not summary.strip():
+        return
+    try:
+        evo_dir = _evolution_dir(workspace_dir, user_id)
+        evo_dir.mkdir(parents=True, exist_ok=True)
+        today = datetime.now().strftime("%Y-%m-%d")
+        log_file = evo_dir / f"{today}.md"
+
+        ts = datetime.now().strftime("%H:%M")
+        header = f"## {ts}"
+        body = summary.strip()
+        if backup_id:
+            body += f"\n\n_backup_id: {backup_id}_"
+
+        # Create with a title if the file is new, otherwise append a section.
+        if not log_file.exists():
+            log_file.write_text(f"# Self-Evolution: {today}\n\n", encoding="utf-8")
+        with open(log_file, "a", encoding="utf-8") as f:
+            f.write(f"\n{header}\n\n{body}\n")
+        logger.info(f"[Evolution] Recorded session evolution to {log_file.name}")
+    except Exception as e:
+        logger.warning(f"[Evolution] Failed to record session evolution: {e}")
diff --git a/agent/evolution/trigger.py b/agent/evolution/trigger.py
new file mode 100644
index 0000000..e044339
--- /dev/null
+++ b/agent/evolution/trigger.py
@@ -0,0 +1,151 @@
+"""Idle-based evolution trigger.
+
+A single background thread periodically scans live agent sessions and runs an
+evolution pass for any session that is idle for >= idle_minutes AND has enough
+accumulated signal, where "enough signal" is EITHER:
+  - >= min_turns user turns since the last evolution, OR
+  - the live context has grown past _CONTEXT_RATIO of the agent's token budget
+    (mirrors how OpenClacky / Claude Code consolidate under context pressure).
+
+Turn counting is per user turn (not per message), measured from the last
+evolution (or session start). After a pass runs, the baseline resets so a long
+session can evolve multiple times without re-judging old content.
+
+Per-session evolution state is stored on the agent instance via lightweight
+attributes set by AgentBridge.agent_reply (see _note_user_turn).
+"""
+
+from __future__ import annotations
+
+import threading
+import time
+
+from common.log import logger
+
+from agent.evolution.config import get_evolution_config
+from agent.evolution.executor import run_evolution_for_session
+
+_SCAN_INTERVAL_SECONDS = 60
+
+# Context-pressure trigger: evolve once the live context exceeds this fraction
+# of the agent's token budget, even if min_turns hasn't been reached. Kept as a
+# module constant (not user config) for now. Fallback budget matches
+# agent_initializer / config.py (agent_max_context_tokens default = 50000).
+_CONTEXT_RATIO = 0.8
+_FALLBACK_CONTEXT_BUDGET = 50000
+
+
+def _context_pressure_reached(agent) -> bool:
+    """True if the agent's live context exceeds _CONTEXT_RATIO of its budget.
+
+    Uses the agent's own (estimated) token accounting so behavior matches the
+    existing context-trimming path. Best-effort: any error -> False.
+    """
+    try:
+        with agent.messages_lock:
+            messages = list(agent.messages)
+        if not messages:
+            return False
+        est = sum(agent._estimate_message_tokens(m) for m in messages)
+        budget = getattr(agent, "max_context_tokens", None) or _FALLBACK_CONTEXT_BUDGET
+        return est / budget > _CONTEXT_RATIO
+    except Exception:
+        return False
+
+
+def note_user_turn(agent, channel_type: str = "", receiver: str = "") -> None:
+    """Record activity for a session's agent. Called once per real user turn.
+
+    Maintains, on the agent instance:
+      _evo_last_active   : epoch seconds of the last user turn
+      _evo_turns         : user turns since the last evolution
+      _evo_channel_type  : originating channel (for later notify)
+      _evo_receiver      : push target for notify
+    """
+    try:
+        agent._evo_last_active = time.time()
+        agent._evo_turns = int(getattr(agent, "_evo_turns", 0)) + 1
+        if channel_type:
+            agent._evo_channel_type = channel_type
+        if receiver:
+            agent._evo_receiver = receiver
+    except Exception:
+        pass
+
+
+def mark_run_active(agent, active: bool) -> None:
+    """Flag whether the agent is mid-run, so idle scans skip a busy session.
+
+    Without this, a single run that lasts longer than idle_minutes would let
+    the scanner fire an evolution pass concurrently with the live turn.
+    """
+    try:
+        agent._evo_run_active = bool(active)
+        if active:
+            agent._evo_last_active = time.time()
+    except Exception:
+        pass
+
+
+def start_evolution_trigger(agent_bridge) -> None:
+    """Start the idle-scan thread once per process (idempotent)."""
+    if getattr(agent_bridge, "_evolution_trigger_started", False):
+        return
+    agent_bridge._evolution_trigger_started = True
+
+    t = threading.Thread(
+        target=_scan_loop, args=(agent_bridge,), daemon=True, name="evolution-trigger"
+    )
+    t.start()
+    logger.info("[Evolution] Idle trigger started")
+
+
+def _scan_loop(agent_bridge) -> None:
+    while True:
+        try:
+            time.sleep(_SCAN_INTERVAL_SECONDS)
+            cfg = get_evolution_config()
+            if not cfg.enabled:
+                continue
+            _scan_once(agent_bridge, cfg)
+        except Exception as e:
+            logger.warning(f"[Evolution] Scan loop error: {e}")
+            time.sleep(_SCAN_INTERVAL_SECONDS)
+
+
+def _scan_once(agent_bridge, cfg) -> None:
+    now = time.time()
+    # Snapshot to avoid holding the dict while running long evolutions.
+    sessions = list(getattr(agent_bridge, "agents", {}).items())
+    for session_id, agent in sessions:
+        try:
+            # Skip sessions whose agent is mid-run: a long turn must not be
+            # reviewed while it is still producing the answer.
+            if getattr(agent, "_evo_run_active", False):
+                continue
+            last_active = getattr(agent, "_evo_last_active", 0)
+            turns = int(getattr(agent, "_evo_turns", 0))
+            # Enough signal = enough turns OR enough context pressure.
+            enough_signal = turns >= cfg.min_turns or _context_pressure_reached(agent)
+            if not enough_signal:
+                continue
+            idle = now - last_active if last_active > 0 else -1
+            if last_active <= 0 or idle < cfg.idle_seconds:
+                continue
+
+            channel_type = getattr(agent, "_evo_channel_type", "") or ""
+            receiver = getattr(agent, "_evo_receiver", "") or ""
+
+            # Reset baseline BEFORE running so a long pass / new messages during
+            # it don't double-trigger; turns accrue fresh from here.
+            agent._evo_turns = 0
+
+            run_evolution_for_session(
+                agent_bridge,
+                session_id=session_id,
+                channel_type=channel_type,
+                receiver=receiver,
+                idle_minutes=(now - last_active) / 60 if last_active > 0 else 0.0,
+            )
+        except Exception as e:
+            logger.warning(f"[Evolution] Failed to evaluate session={session_id}: {e}")
diff --git a/agent/knowledge/__init__.py b/agent/knowledge/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/agent/knowledge/service.py b/agent/knowledge/service.py
new file mode 100644
index 0000000..e404d56
--- /dev/null
+++ b/agent/knowledge/service.py
@@ -0,0 +1,645 @@
+"""
+Knowledge service for handling knowledge base operations.
+
+Provides a unified interface for listing, reading, and graphing knowledge files,
+callable from the web console, API, or CLI.
+
+Knowledge file layout (under workspace_root):
+    knowledge/index.md
+    knowledge/log.md
+    knowledge/<category>/<slug>.md
+"""
+
+import os
+import re
+import asyncio
+import shutil
+import threading
+from pathlib import Path
+from typing import Optional, Iterable
+from urllib.parse import quote
+
+from common.log import logger
+from config import conf
+from agent.memory.config import MemoryConfig
+from agent.memory.manager import MemoryManager
+
+
+class KnowledgeService:
+    """
+    High-level service for knowledge base queries.
+    Operates directly on the filesystem.
+    """
+
+    PROTECTED_FILES = {"index.md", "log.md"}
+    INVALID_NAME_RE = re.compile(r'[<>:"|?*\x00-\x1f]')
+    IMPORT_EXTENSIONS = {".md", ".txt"}
+    MAX_IMPORT_FILES = 100
+    MAX_IMPORT_FILE_SIZE = 10 * 1024 * 1024
+    MAX_IMPORT_TOTAL_SIZE = 200 * 1024 * 1024
+
+    def __init__(self, workspace_root: str, memory_manager=None):
+        self.workspace_root = os.path.abspath(workspace_root)
+        self.knowledge_dir = os.path.join(self.workspace_root, "knowledge")
+        self._memory_manager = memory_manager
+
+    def _resolve_path(self, rel_path: str, *, kind: Optional[str] = None,
+                      allow_missing: bool = True) -> tuple:
+        if not isinstance(rel_path, str) or not rel_path.strip():
+            raise ValueError("path is required")
+        rel_path = rel_path.replace("\\", "/").strip("/")
+        parts = rel_path.split("/")
+        if any(not p or p in (".", "..") or self.INVALID_NAME_RE.search(p) for p in parts):
+            raise ValueError("invalid path")
+        if kind == "document" and not rel_path.lower().endswith(".md"):
+            raise ValueError("document path must end with .md")
+
+        root = Path(self.knowledge_dir).resolve()
+        candidate = root.joinpath(*parts)
+        # Resolve the nearest existing ancestor so a symlink cannot be used
+        # to escape when the final destination does not exist yet.
+        ancestor = candidate
+        while not ancestor.exists() and ancestor != root:
+            ancestor = ancestor.parent
+        try:
+            ancestor.resolve().relative_to(root)
+        except ValueError:
+            raise ValueError("path outside knowledge dir")
+        if candidate.exists():
+            try:
+                candidate.resolve().relative_to(root)
+            except ValueError:
+                raise ValueError("path outside knowledge dir")
+        elif not allow_missing:
+            raise FileNotFoundError(f"path not found: {rel_path}")
+        return rel_path, candidate
+
+    def _ensure_not_protected(self, rel_path: str):
+        if rel_path in self.PROTECTED_FILES:
+            raise ValueError(f"protected knowledge file: {rel_path}")
+
+    def _manager(self):
+        if self._memory_manager is None:
+            # Reuse the shared embedding provider selection so knowledge index
+            # sync gets vectors too, instead of degrading to keyword-only.
+            from agent.memory.embedding import create_default_embedding_provider
+            embedding_provider = create_default_embedding_provider()
+            self._memory_manager = MemoryManager(
+                MemoryConfig(workspace_root=self.workspace_root),
+                embedding_provider=embedding_provider,
+            )
+        return self._memory_manager
+
+    @staticmethod
+    def _run_sync(coro):
+        try:
+            asyncio.get_running_loop()
+        except RuntimeError:
+            return asyncio.run(coro)
+        result = []
+        error = []
+
+        def runner():
+            try:
+                result.append(asyncio.run(coro))
+            except Exception as exc:
+                error.append(exc)
+
+        thread = threading.Thread(target=runner)
+        thread.start()
+        thread.join()
+        if error:
+            raise error[0]
+        return result[0] if result else None
+
+    def _sync_index(self, old_paths: Iterable[str], force: bool = False):
+        old_paths = sorted(set(old_paths))
+        if not old_paths and not force:
+            return
+        manager = self._manager()
+        for rel_path in old_paths:
+            manager.storage.delete_by_path(f"knowledge/{rel_path}")
+        manager.mark_dirty()
+        self._run_sync(manager.sync())
+
+    @staticmethod
+    def _extract_title(md_path: Path, fallback: str) -> str:
+        """Read a markdown file's H1 title, falling back to the file stem."""
+        try:
+            with open(md_path, "r", encoding="utf-8") as f:
+                for _ in range(20):
+                    line = f.readline()
+                    if not line:
+                        break
+                    stripped = line.strip()
+                    if stripped.startswith("# "):
+                        return stripped[2:].strip() or fallback
+        except Exception:
+            pass
+        return fallback
+
+    def rebuild_index_md(self) -> bool:
+        """Regenerate knowledge/index.md from the actual directory tree.
+
+        Keeps the index in sync with real files so it never drifts or loses
+        documents. Returns True when the file was (re)written.
+        """
+        root = Path(self.knowledge_dir)
+        if not root.is_dir():
+            return False
+
+        def collect(dir_path: Path) -> list:
+            # Return sorted (rel_path, title) tuples for *.md under dir_path,
+            # excluding protected files at the knowledge root and dot files.
+            entries = []
+            for md in sorted(dir_path.rglob("*.md")):
+                rel = md.relative_to(root).as_posix()
+                if any(part.startswith(".") for part in md.relative_to(root).parts):
+                    continue
+                if rel in self.PROTECTED_FILES:
+                    continue
+                entries.append((rel, self._extract_title(md, md.stem)))
+            return entries
+
+        all_entries = collect(root)
+
+        def link(rel: str) -> str:
+            # Encode each path segment so spaces / special chars stay valid in
+            # markdown links, while keeping the slashes between segments.
+            encoded = "/".join(quote(part) for part in rel.split("/"))
+            return f"./{encoded}"
+
+        lines = ["# 知识库目录", ""]
+        # Root-level documents first (no category dir).
+        root_docs = [(rel, title) for rel, title in all_entries if "/" not in rel]
+        for rel, title in root_docs:
+            lines.append(f"- [{title}]({link(rel)})")
+        if root_docs:
+            lines.append("")
+
+        # Group remaining documents by their top-level category.
+        categories = {}
+        for rel, title in all_entries:
+            if "/" not in rel:
+                continue
+            category = rel.split("/", 1)[0]
+            categories.setdefault(category, []).append((rel, title))
+
+        for category in sorted(categories.keys()):
+            lines.append(f"## {category}")
+            for rel, title in categories[category]:
+                lines.append(f"- [{title}]({link(rel)})")
+            lines.append("")
+
+        content = "\n".join(lines).rstrip() + "\n"
+        index_path = root / "index.md"
+        try:
+            index_path.write_text(content, encoding="utf-8")
+            return True
+        except Exception as exc:
+            logger.warning(f"[KnowledgeService] Failed to rebuild index.md: {exc}")
+            return False
+
+    def _sanitize_document_name(self, filename: str) -> str:
+        name = os.path.basename((filename or "").replace("\\", "/")).strip()
+        if not name:
+            raise ValueError("filename is required")
+        stem, ext = os.path.splitext(name)
+        if ext.lower() not in self.IMPORT_EXTENSIONS:
+            raise ValueError(f"unsupported file type: {ext or name}")
+        if not stem or stem in (".", "..") or self.INVALID_NAME_RE.search(stem):
+            raise ValueError("invalid filename")
+        safe_name = f"{stem}.md"
+        self._ensure_not_protected(safe_name)
+        return safe_name
+
+    @staticmethod
+    def _decode_document_content(content) -> str:
+        if isinstance(content, str):
+            return content
+        if not isinstance(content, (bytes, bytearray)):
+            raise ValueError("document content is required")
+        return bytes(content).decode("utf-8-sig", errors="replace")
+
+    def _resolve_import_destination(self, target_category: str, filename: str,
+                                    conflict_strategy: str) -> tuple:
+        target_rel, target_full = self._resolve_path(target_category, kind="category")
+        if not target_full.is_dir():
+            raise FileNotFoundError(f"category not found: {target_rel}")
+
+        safe_name = self._sanitize_document_name(filename)
+        destination = target_full / safe_name
+        rel_path = f"{target_rel}/{safe_name}"
+
+        if destination.exists():
+            if conflict_strategy == "skip":
+                return rel_path, destination, "skip"
+            if conflict_strategy == "rename":
+                stem = destination.stem
+                suffix = destination.suffix
+                for index in range(1, 1000):
+                    candidate = target_full / f"{stem}-{index}{suffix}"
+                    if not candidate.exists():
+                        candidate_rel = f"{target_rel}/{candidate.name}"
+                        return candidate_rel, candidate, "write"
+                raise FileExistsError(f"target already exists: {rel_path}")
+            if conflict_strategy != "overwrite":
+                raise ValueError("invalid conflict strategy")
+        return rel_path, destination, "write"
+
+    def create_document(self, path: str, content: str = "", overwrite: bool = False) -> dict:
+        rel_path, full_path = self._resolve_path(path, kind="document")
+        self._ensure_not_protected(rel_path)
+        if len((content or "").encode("utf-8")) > self.MAX_IMPORT_FILE_SIZE:
+            raise ValueError("file too large")
+        if full_path.exists() and not overwrite:
+            raise FileExistsError(f"target already exists: {rel_path}")
+        old_paths = [rel_path] if full_path.exists() else []
+        full_path.parent.mkdir(parents=True, exist_ok=True)
+        full_path.write_text(content or "", encoding="utf-8")
+        # Keep index.md in sync before reindexing so it is indexed too.
+        self.rebuild_index_md()
+        self._sync_index(old_paths, force=True)
+        return {"path": rel_path, "created": True, "overwritten": bool(old_paths)}
+
+    def import_documents(self, target_category: str, files: Iterable[dict],
+                         conflict_strategy: str = "skip") -> dict:
+        if not isinstance(files, list):
+            raise ValueError("files must be a list")
+        if len(files) > self.MAX_IMPORT_FILES:
+            raise ValueError(f"too many files: max {self.MAX_IMPORT_FILES}")
+        results = []
+        old_paths = []
+        imported = skipped = failed = 0
+        total_size = 0
+
+        for item in files:
+            filename = item.get("filename") if isinstance(item, dict) else None
+            try:
+                content_bytes = item.get("content") if isinstance(item, dict) else None
+                size = len(content_bytes.encode("utf-8")) if isinstance(content_bytes, str) else len(content_bytes or b"")
+                total_size += size
+                if total_size > self.MAX_IMPORT_TOTAL_SIZE:
+                    raise ValueError("import batch too large")
+                if size > self.MAX_IMPORT_FILE_SIZE:
+                    raise ValueError("file too large")
+                rel_path, destination, mode = self._resolve_import_destination(
+                    target_category, filename, conflict_strategy
+                )
+                if mode == "skip":
+                    skipped += 1
+                    results.append({"filename": filename, "path": rel_path, "status": "skipped",
+                                    "reason": "target_exists"})
+                    continue
+
+                old_exists = destination.exists()
+                content = self._decode_document_content(content_bytes)
+                destination.parent.mkdir(parents=True, exist_ok=True)
+                destination.write_text(content, encoding="utf-8")
+                if old_exists:
+                    old_paths.append(rel_path)
+                imported += 1
+                results.append({"filename": filename, "path": rel_path, "status": "imported",
+                                "overwritten": old_exists})
+            except Exception as exc:
+                failed += 1
+                results.append({"filename": filename or "", "status": "failed", "reason": str(exc)})
+
+        if imported:
+            # Keep index.md in sync before reindexing so it is indexed too.
+            self.rebuild_index_md()
+            self._sync_index(old_paths, force=True)
+        return {"results": results, "imported": imported, "skipped": skipped, "failed": failed}
+
+    def create_category(self, path: str) -> dict:
+        rel_path, full_path = self._resolve_path(path, kind="category")
+        if full_path.exists():
+            return {"path": rel_path, "created": False, "reason": "already_exists"}
+        full_path.mkdir(parents=True)
+        return {"path": rel_path, "created": True}
+
+    def rename_category(self, path: str, new_path: str) -> dict:
+        old_rel, old_full = self._resolve_path(path, kind="category", allow_missing=False)
+        new_rel, new_full = self._resolve_path(new_path, kind="category")
+        if not old_full.is_dir():
+            raise ValueError(f"not a category: {old_rel}")
+        if new_full.exists():
+            raise FileExistsError(f"target already exists: {new_rel}")
+        old_documents = [str(p.relative_to(old_full)).replace(os.sep, "/")
+                         for p in old_full.rglob("*.md") if p.is_file()]
+        new_full.parent.mkdir(parents=True, exist_ok=True)
+        try:
+            old_full.rename(new_full)
+        except FileNotFoundError:
+            return {"old_path": old_rel, "path": new_rel, "moved": False, "reason": "not_found"}
+        except FileExistsError:
+            raise FileExistsError(f"target already exists: {new_rel}")
+        old_paths = [f"{old_rel}/{p}" for p in old_documents]
+        self._sync_index(old_paths)
+        return {"old_path": old_rel, "path": new_rel, "moved_documents": len(old_documents)}
+
+    def delete_category(self, path: str, confirm: bool = False) -> dict:
+        rel_path, full_path = self._resolve_path(path, kind="category")
+        if not full_path.exists():
+            return {"path": rel_path, "deleted": False, "reason": "not_found"}
+        if not full_path.is_dir():
+            raise ValueError(f"not a category: {rel_path}")
+        knowledge_root = Path(self.knowledge_dir).resolve()
+        documents = [str(p.relative_to(knowledge_root)).replace(os.sep, "/")
+                     for p in full_path.rglob("*.md") if p.is_file()]
+        if any(p in self.PROTECTED_FILES for p in documents):
+            raise ValueError("category contains protected knowledge files")
+        if any(full_path.iterdir()) and not confirm:
+            raise ValueError("category is not empty; confirmation is required")
+        try:
+            shutil.rmtree(full_path)
+        except FileNotFoundError:
+            return {"path": rel_path, "deleted": False, "reason": "not_found"}
+        self._sync_index(documents)
+        return {"path": rel_path, "deleted": True, "deleted_documents": len(documents)}
+
+    def delete_documents(self, paths: Iterable[str]) -> dict:
+        if not isinstance(paths, list):
+            raise ValueError("paths must be a list")
+        results = []
+        deleted = []
+        for path in paths:
+            rel_path, full_path = self._resolve_path(path, kind="document")
+            self._ensure_not_protected(rel_path)
+            if not full_path.exists():
+                deleted.append(rel_path)
+                results.append({"path": rel_path, "deleted": False, "reason": "not_found"})
+                continue
+            if not full_path.is_file():
+                raise ValueError(f"not a document: {rel_path}")
+            try:
+                full_path.unlink()
+                deleted.append(rel_path)
+                results.append({"path": rel_path, "deleted": True})
+            except FileNotFoundError:
+                deleted.append(rel_path)
+                results.append({"path": rel_path, "deleted": False, "reason": "not_found"})
+        self._sync_index(deleted)
+        return {"results": results, "deleted": sum(1 for item in results if item["deleted"])}
+
+    def move_documents(self, paths: Iterable[str], target_category: str) -> dict:
+        if not isinstance(paths, list):
+            raise ValueError("paths must be a list")
+        target_rel, target_full = self._resolve_path(target_category, kind="category")
+        if not target_full.is_dir():
+            raise FileNotFoundError(f"category not found: {target_rel}")
+        results = []
+        moved_old_paths = []
+        for path in paths:
+            rel_path, full_path = self._resolve_path(path, kind="document")
+            self._ensure_not_protected(rel_path)
+            if not full_path.exists():
+                results.append({"path": rel_path, "moved": False, "reason": "not_found"})
+                continue
+            destination = target_full / full_path.name
+            new_rel = str(destination.relative_to(Path(self.knowledge_dir).resolve())).replace(os.sep, "/")
+            if destination.exists():
+                results.append({"path": rel_path, "moved": False, "reason": "target_exists",
+                                "target": new_rel})
+                continue
+            try:
+                os.link(full_path, destination)
+                full_path.unlink()
+                moved_old_paths.append(rel_path)
+                results.append({"path": rel_path, "moved": True, "target": new_rel})
+            except FileExistsError:
+                results.append({"path": rel_path, "moved": False, "reason": "target_exists",
+                                "target": new_rel})
+            except FileNotFoundError:
+                results.append({"path": rel_path, "moved": False, "reason": "not_found"})
+        self._sync_index(moved_old_paths)
+        return {"results": results, "moved": len(moved_old_paths)}
+
+    # ------------------------------------------------------------------
+    # list — directory tree with stats
+    # ------------------------------------------------------------------
+    def list_tree(self) -> dict:
+        """
+        Return the knowledge directory tree grouped by category,
+        supporting arbitrarily nested sub-directories.
+
+        Returns::
+
+            {
+                "tree": [
+                    {
+                        "dir": "concepts",
+                        "files": [
+                            {"name": "moe.md", "title": "MoE", "size": 1234},
+                        ],
+                        "children": []
+                    },
+                    {
+                        "dir": "platform",
+                        "files": [],
+                        "children": [
+                            {
+                                "dir": "analysis",
+                                "files": [{"name": "perf.md", ...}],
+                                "children": []
+                            }
+                        ]
+                    },
+                ],
+                "stats": {"pages": 15, "size": 32768},
+                "enabled": true
+            }
+        """
+        if not os.path.isdir(self.knowledge_dir):
+            return {"tree": [], "stats": {"pages": 0, "size": 0}, "enabled": conf().get("knowledge", True)}
+
+        stats = {"pages": 0, "size": 0}
+        root_files, tree = self._scan_dir(self.knowledge_dir, stats, is_root=True)
+
+        return {
+            "root_files": root_files,
+            "tree": tree,
+            "stats": stats,
+            "enabled": conf().get("knowledge", True),
+        }
+
+    def _scan_dir(self, dir_path: str, stats: dict, is_root: bool = False) -> tuple:
+        """
+        Recursively scan a directory.
+
+        :return: (files, children) where files is a list of .md file dicts
+                 in this directory and children is a list of sub-directory nodes.
+        """
+        files = []
+        children = []
+        for name in sorted(os.listdir(dir_path)):
+            if name.startswith("."):
+                continue
+            full = os.path.join(dir_path, name)
+            if os.path.isdir(full):
+                sub_files, sub_children = self._scan_dir(full, stats)
+                children.append({"dir": name, "files": sub_files, "children": sub_children})
+            elif name.endswith(".md"):
+                size = os.path.getsize(full)
+                if not is_root:
+                    stats["pages"] += 1
+                    stats["size"] += size
+                # Prefer the H1 heading as a readable title for normal docs.
+                # System files (index.md / log.md) keep their filename so the
+                # tree never hides what they actually are.
+                title = name[:-3]
+                if name not in self.PROTECTED_FILES:
+                    try:
+                        with open(full, "r", encoding="utf-8") as f:
+                            first_line = f.readline().strip()
+                        if first_line.startswith("# "):
+                            title = first_line[2:].strip() or title
+                    except Exception:
+                        pass
+                files.append({"name": name, "title": title, "size": size})
+        return files, children
+
+    # ------------------------------------------------------------------
+    # read — single file content
+    # ------------------------------------------------------------------
+    def read_file(self, rel_path: str) -> dict:
+        """
+        Read a single knowledge markdown file.
+
+        :param rel_path: Relative path within knowledge/, e.g. ``concepts/moe.md``
+        :return: dict with ``content`` and ``path``
+        :raises ValueError: if path is invalid or escapes knowledge dir
+        :raises FileNotFoundError: if file does not exist
+        """
+        rel_path, full_path = self._resolve_path(rel_path, kind="document")
+        if not full_path.is_file():
+            raise FileNotFoundError(f"file not found: {rel_path}")
+
+        with open(full_path, "r", encoding="utf-8") as f:
+            content = f.read()
+        return {"content": content, "path": rel_path}
+
+    # ------------------------------------------------------------------
+    # graph — nodes and links for visualization
+    # ------------------------------------------------------------------
+    def build_graph(self) -> dict:
+        """
+        Parse all knowledge pages and extract cross-reference links.
+
+        Returns::
+
+            {
+                "nodes": [
+                    {"id": "concepts/moe.md", "label": "MoE", "category": "concepts"},
+                    ...
+                ],
+                "links": [
+                    {"source": "concepts/moe.md", "target": "entities/deepseek.md"},
+                    ...
+                ]
+            }
+        """
+        knowledge_path = Path(self.knowledge_dir)
+        if not knowledge_path.is_dir():
+            return {"nodes": [], "links": []}
+
+        nodes = {}
+        links = []
+        link_re = re.compile(r'\[([^\]]*)\]\(([^)]+\.md)\)')
+
+        for md_file in knowledge_path.rglob("*.md"):
+            rel = str(md_file.relative_to(knowledge_path))
+            if rel in ("index.md", "log.md"):
+                continue
+            parts = rel.split("/")
+            category = parts[0] if len(parts) > 1 else "root"
+            title = md_file.stem.replace("-", " ").title()
+            try:
+                content = md_file.read_text(encoding="utf-8")
+                first_line = content.strip().split("\n")[0]
+                if first_line.startswith("# "):
+                    title = first_line[2:].strip()
+                for _, link_target in link_re.findall(content):
+                    resolved = (md_file.parent / link_target).resolve()
+                    try:
+                        target_rel = str(resolved.relative_to(knowledge_path))
+                    except ValueError:
+                        continue
+                    if target_rel != rel:
+                        links.append({"source": rel, "target": target_rel})
+            except Exception:
+                pass
+            nodes[rel] = {"id": rel, "label": title, "category": category}
+
+        valid_ids = set(nodes.keys())
+        links = [l for l in links if l["source"] in valid_ids and l["target"] in valid_ids]
+        seen = set()
+        deduped = []
+        for l in links:
+            key = tuple(sorted([l["source"], l["target"]]))
+            if key not in seen:
+                seen.add(key)
+                deduped.append(l)
+
+        return {"nodes": list(nodes.values()), "links": deduped}
+
+    # ------------------------------------------------------------------
+    # dispatch — single entry point for protocol messages
+    # ------------------------------------------------------------------
+    def dispatch(self, action: str, payload: Optional[dict] = None) -> dict:
+        """
+        Dispatch a knowledge management action.
+
+        :param action: ``list``, ``read``, or ``graph``
+        :param payload: action-specific payload
+        :return: protocol-compatible response dict
+        """
+        payload = payload or {}
+        try:
+            if action == "list":
+                result = self.list_tree()
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "read":
+                path = payload.get("path")
+                if not path:
+                    return {"action": action, "code": 400, "message": "path is required", "payload": None}
+                result = self.read_file(path)
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "graph":
+                result = self.build_graph()
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "create_category":
+                result = self.create_category(payload.get("path"))
+            elif action == "rename_category":
+                result = self.rename_category(payload.get("path"), payload.get("new_path"))
+            elif action == "delete_category":
+                result = self.delete_category(payload.get("path"), payload.get("confirm", False))
+            elif action == "delete_documents":
+                result = self.delete_documents(payload.get("paths") or [])
+            elif action == "move_documents":
+                result = self.move_documents(payload.get("paths") or [], payload.get("target_category"))
+            elif action == "create_document":
+                result = self.create_document(payload.get("path"), payload.get("content", ""),
+                                              payload.get("overwrite", False))
+            elif action == "import_documents":
+                result = self.import_documents(
+                    payload.get("target_category"),
+                    payload.get("files") or [],
+                    payload.get("conflict_strategy", "skip"),
+                )
+            else:
+                return {"action": action, "code": 400, "message": f"unknown action: {action}", "payload": None}
+            return {"action": action, "code": 200, "message": "success", "payload": result}
+
+        except ValueError as e:
+            return {"action": action, "code": 403, "message": str(e), "payload": None}
+        except FileNotFoundError as e:
+            return {"action": action, "code": 404, "message": str(e), "payload": None}
+        except FileExistsError as e:
+            return {"action": action, "code": 409, "message": str(e), "payload": None}
+        except Exception as e:
+            logger.error(f"[KnowledgeService] dispatch error: action={action}, error={e}")
+            return {"action": action, "code": 500, "message": str(e), "payload": None}
diff --git a/agent/memory/__init__.py b/agent/memory/__init__.py
new file mode 100644
index 0000000..d08ffa8
--- /dev/null
+++ b/agent/memory/__init__.py
@@ -0,0 +1,24 @@
+"""
+Memory module for AgentMesh
+
+Provides both long-term memory (vector/keyword search) and short-term
+conversation history persistence (SQLite).
+"""
+
+from agent.memory.manager import MemoryManager
+from agent.memory.config import MemoryConfig, get_default_memory_config, set_global_memory_config
+from agent.memory.embedding import create_embedding_provider, create_default_embedding_provider
+from agent.memory.conversation_store import ConversationStore, get_conversation_store
+from agent.memory.summarizer import ensure_daily_memory_file
+
+__all__ = [
+    'MemoryManager',
+    'MemoryConfig',
+    'get_default_memory_config',
+    'set_global_memory_config',
+    'create_embedding_provider',
+    'create_default_embedding_provider',
+    'ConversationStore',
+    'get_conversation_store',
+    'ensure_daily_memory_file',
+]
diff --git a/agent/memory/chunker.py b/agent/memory/chunker.py
new file mode 100644
index 0000000..8dfd062
--- /dev/null
+++ b/agent/memory/chunker.py
@@ -0,0 +1,140 @@
+"""
+Text chunking utilities for memory
+
+Splits text into chunks with token limits and overlap
+"""
+
+from __future__ import annotations
+from typing import List, Tuple
+from dataclasses import dataclass
+
+
+@dataclass
+class TextChunk:
+    """Represents a text chunk with line numbers"""
+    text: str
+    start_line: int
+    end_line: int
+
+
+class TextChunker:
+    """Chunks text by line count with token estimation"""
+    
+    def __init__(self, max_tokens: int = 500, overlap_tokens: int = 50):
+        """
+        Initialize chunker
+        
+        Args:
+            max_tokens: Maximum tokens per chunk
+            overlap_tokens: Overlap tokens between chunks
+        """
+        self.max_tokens = max_tokens
+        self.overlap_tokens = overlap_tokens
+        # Rough estimation: ~4 chars per token for English/Chinese mixed
+        self.chars_per_token = 4
+    
+    def chunk_text(self, text: str) -> List[TextChunk]:
+        """
+        Chunk text into overlapping segments
+        
+        Args:
+            text: Input text to chunk
+            
+        Returns:
+            List of TextChunk objects
+        """
+        if not text.strip():
+            return []
+        
+        lines = text.split('\n')
+        chunks = []
+        
+        max_chars = self.max_tokens * self.chars_per_token
+        overlap_chars = self.overlap_tokens * self.chars_per_token
+        
+        current_chunk = []
+        current_chars = 0
+        start_line = 1
+        
+        for i, line in enumerate(lines, start=1):
+            line_chars = len(line)
+            
+            # If single line exceeds max, split it
+            if line_chars > max_chars:
+                # Save current chunk if exists
+                if current_chunk:
+                    chunks.append(TextChunk(
+                        text='\n'.join(current_chunk),
+                        start_line=start_line,
+                        end_line=i - 1
+                    ))
+                    current_chunk = []
+                    current_chars = 0
+                
+                # Split long line into multiple chunks
+                for sub_chunk in self._split_long_line(line, max_chars):
+                    chunks.append(TextChunk(
+                        text=sub_chunk,
+                        start_line=i,
+                        end_line=i
+                    ))
+                
+                start_line = i + 1
+                continue
+            
+            # Check if adding this line would exceed limit
+            if current_chars + line_chars > max_chars and current_chunk:
+                # Save current chunk
+                chunks.append(TextChunk(
+                    text='\n'.join(current_chunk),
+                    start_line=start_line,
+                    end_line=i - 1
+                ))
+                
+                # Start new chunk with overlap
+                overlap_lines = self._get_overlap_lines(current_chunk, overlap_chars)
+                current_chunk = overlap_lines + [line]
+                current_chars = sum(len(l) for l in current_chunk)
+                start_line = i - len(overlap_lines)
+            else:
+                # Add line to current chunk
+                current_chunk.append(line)
+                current_chars += line_chars
+        
+        # Save last chunk
+        if current_chunk:
+            chunks.append(TextChunk(
+                text='\n'.join(current_chunk),
+                start_line=start_line,
+                end_line=len(lines)
+            ))
+        
+        return chunks
+    
+    def _split_long_line(self, line: str, max_chars: int) -> List[str]:
+        """Split a single long line into multiple chunks"""
+        chunks = []
+        for i in range(0, len(line), max_chars):
+            chunks.append(line[i:i + max_chars])
+        return chunks
+    
+    def _get_overlap_lines(self, lines: List[str], target_chars: int) -> List[str]:
+        """Get last few lines that fit within target_chars for overlap"""
+        overlap = []
+        chars = 0
+        
+        for line in reversed(lines):
+            line_chars = len(line)
+            if chars + line_chars > target_chars:
+                break
+            overlap.insert(0, line)
+            chars += line_chars
+        
+        return overlap
+    
+    def chunk_markdown(self, text: str) -> List[TextChunk]:
+        """
+        Chunk markdown text while respecting structure
+        (For future enhancement: respect markdown sections)
+        """
+        return self.chunk_text(text)
diff --git a/agent/memory/config.py b/agent/memory/config.py
new file mode 100644
index 0000000..70d303d
--- /dev/null
+++ b/agent/memory/config.py
@@ -0,0 +1,122 @@
+"""
+Memory configuration module
+
+Provides global memory configuration with simplified workspace structure
+"""
+
+from __future__ import annotations
+import os
+from dataclasses import dataclass, field
+from typing import Optional, List
+from pathlib import Path
+
+
+def _default_workspace():
+    """Get default workspace path with proper Windows support"""
+    from common.utils import expand_path
+    return expand_path("~/cow")
+
+
+@dataclass
+class MemoryConfig:
+    """Configuration for memory storage and search"""
+    
+    # Storage paths (default: ~/cow)
+    workspace_root: str = field(default_factory=_default_workspace)
+    
+    # Embedding config
+    embedding_provider: str = "openai"  # "openai" | "local"
+    embedding_model: str = "text-embedding-3-small"
+    embedding_dim: int = 1536
+    
+    # Chunking config
+    chunk_max_tokens: int = 500
+    chunk_overlap_tokens: int = 50
+    
+    # Search config
+    max_results: int = 10
+    min_score: float = 0.1
+    
+    # Hybrid search weights
+    vector_weight: float = 0.7
+    keyword_weight: float = 0.3
+    
+    # Memory sources
+    sources: List[str] = field(default_factory=lambda: ["memory", "session"])
+    
+    # Sync config
+    enable_auto_sync: bool = True
+    sync_on_search: bool = True
+    
+    
+    def get_workspace(self) -> Path:
+        """Get workspace root directory"""
+        return Path(self.workspace_root)
+    
+    def get_memory_dir(self) -> Path:
+        """Get memory files directory"""
+        return self.get_workspace() / "memory"
+    
+    def get_db_path(self) -> Path:
+        """Get SQLite database path for long-term memory index"""
+        index_dir = self.get_memory_dir() / "long-term"
+        index_dir.mkdir(parents=True, exist_ok=True)
+        return index_dir / "index.db"
+    
+    def get_skills_dir(self) -> Path:
+        """Get skills directory"""
+        return self.get_workspace() / "skills"
+    
+    def get_agent_workspace(self, agent_name: Optional[str] = None) -> Path:
+        """
+        Get workspace directory for an agent
+        
+        Args:
+            agent_name: Optional agent name (not used in current implementation)
+            
+        Returns:
+            Path to workspace directory
+        """
+        workspace = self.get_workspace()
+        # Ensure workspace directory exists
+        workspace.mkdir(parents=True, exist_ok=True)
+        return workspace
+
+
+# Global memory configuration
+_global_memory_config: Optional[MemoryConfig] = None
+
+
+def get_default_memory_config() -> MemoryConfig:
+    """
+    Get the global memory configuration.
+    If not set, returns a default configuration.
+    
+    Returns:
+        MemoryConfig instance
+    """
+    global _global_memory_config
+    if _global_memory_config is None:
+        _global_memory_config = MemoryConfig()
+    return _global_memory_config
+
+
+def set_global_memory_config(config: MemoryConfig):
+    """
+    Set the global memory configuration.
+    This should be called before creating any MemoryManager instances.
+    
+    Args:
+        config: MemoryConfig instance to use globally
+        
+    Example:
+        >>> from agent.memory import MemoryConfig, set_global_memory_config
+        >>> config = MemoryConfig(
+        ...     workspace_root="~/my_agents",
+        ...     embedding_provider="openai",
+        ...     vector_weight=0.8
+        ... )
+        >>> set_global_memory_config(config)
+    """
+    global _global_memory_config
+    _global_memory_config = config
diff --git a/agent/memory/conversation_store.py b/agent/memory/conversation_store.py
new file mode 100644
index 0000000..1537f98
--- /dev/null
+++ b/agent/memory/conversation_store.py
@@ -0,0 +1,1278 @@
+"""
+Conversation history persistence using SQLite.
+
+Design:
+- sessions table: per-session metadata (channel_type, last_active, msg_count)
+- messages table: individual messages stored as JSON, append-only
+- Pruning: age-based only (sessions not updated within N days are deleted)
+- Thread-safe via a single in-process lock
+
+Storage path: ~/cow/sessions/conversations.db
+"""
+
+from __future__ import annotations
+
+import json
+import re
+import sqlite3
+import threading
+import time
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from common.log import logger
+
+
+# ---------------------------------------------------------------------------
+# Schema
+# ---------------------------------------------------------------------------
+
+_DDL = """
+CREATE TABLE IF NOT EXISTS sessions (
+    session_id        TEXT    PRIMARY KEY,
+    channel_type      TEXT    NOT NULL DEFAULT '',
+    title             TEXT    NOT NULL DEFAULT '',
+    context_start_seq INTEGER NOT NULL DEFAULT 0,
+    created_at        INTEGER NOT NULL,
+    last_active       INTEGER NOT NULL,
+    msg_count         INTEGER NOT NULL DEFAULT 0
+);
+
+CREATE TABLE IF NOT EXISTS messages (
+    id           INTEGER PRIMARY KEY AUTOINCREMENT,
+    session_id   TEXT    NOT NULL,
+    seq          INTEGER NOT NULL,
+    role         TEXT    NOT NULL,
+    content      TEXT    NOT NULL,
+    created_at   INTEGER NOT NULL,
+    extras       TEXT    NOT NULL DEFAULT '',
+    UNIQUE (session_id, seq)
+);
+
+CREATE INDEX IF NOT EXISTS idx_messages_session
+    ON messages (session_id, seq);
+
+CREATE INDEX IF NOT EXISTS idx_sessions_last_active
+    ON sessions (last_active);
+"""
+
+# Migration: add channel_type column to existing databases that predate it.
+_MIGRATION_ADD_CHANNEL_TYPE = """
+ALTER TABLE sessions ADD COLUMN channel_type TEXT NOT NULL DEFAULT '';
+"""
+
+_MIGRATION_ADD_TITLE = """
+ALTER TABLE sessions ADD COLUMN title TEXT NOT NULL DEFAULT '';
+"""
+
+_MIGRATION_ADD_CONTEXT_START_SEQ = """
+ALTER TABLE sessions ADD COLUMN context_start_seq INTEGER NOT NULL DEFAULT 0;
+"""
+
+# Generic JSON sidecar for per-message attachments (TTS audio URL, future use).
+# Always optional — readers must tolerate missing column / empty / invalid JSON.
+_MIGRATION_ADD_MSG_EXTRAS = """
+ALTER TABLE messages ADD COLUMN extras TEXT NOT NULL DEFAULT '';
+"""
+
+DEFAULT_MAX_AGE_DAYS: int = 30
+
+
+def _is_visible_user_message(content: Any) -> bool:
+    """
+    Return True when a user-role message represents actual user input
+    (not an internal tool_result injected by the agent loop).
+    """
+    if isinstance(content, str):
+        return bool(content.strip())
+    if isinstance(content, list):
+        return any(
+            isinstance(b, dict) and b.get("type") == "text"
+            for b in content
+        )
+    return False
+
+
+def _extract_display_text(content: Any) -> str:
+    """
+    Extract the human-readable text portion from a message content value.
+    Returns an empty string for tool_use / tool_result blocks.
+    """
+    if isinstance(content, str):
+        return content.strip()
+    if isinstance(content, list):
+        parts = [
+            b.get("text", "")
+            for b in content
+            if isinstance(b, dict) and b.get("type") == "text"
+        ]
+        return "\n".join(p for p in parts if p).strip()
+    return ""
+
+
+# Internal markers written into the session for the agent's own bookkeeping
+# (scheduler injection / self-evolution undo). They must stay in the stored
+# content (the LLM reads them, e.g. to find a backup_id for undo) but should
+# never be shown verbatim to the user in the chat history UI.
+_SCHEDULED_DISPLAY_MARKERS = ("[SCHEDULED]", "Scheduled task")
+_EVOLUTION_DISPLAY_MARKER = "[EVOLUTION]"
+
+
+def _is_internal_user_marker(text: str) -> bool:
+    """True if a user-turn text is an internal injection marker (hide from UI)."""
+    t = (text or "").lstrip()
+    return any(t.startswith(m) for m in _SCHEDULED_DISPLAY_MARKERS)
+
+
+def _is_evolution_text(text: str) -> bool:
+    """True if assistant text is a self-evolution summary (before cleaning)."""
+    return (text or "").lstrip().startswith(_EVOLUTION_DISPLAY_MARKER)
+
+
+def _clean_display_text(text: str) -> str:
+    """Strip internal markers from assistant text for user-facing display.
+
+    Removes a leading ``[EVOLUTION]`` tag and a trailing ``(backup_id: ...)``
+    undo hint. The raw stored message is untouched, so undo + LLM context still
+    work; only the rendered chat bubble is cleaned.
+    """
+    if not text:
+        return text
+    cleaned = text
+    stripped = cleaned.lstrip()
+    if stripped.startswith(_EVOLUTION_DISPLAY_MARKER):
+        cleaned = stripped[len(_EVOLUTION_DISPLAY_MARKER):].lstrip()
+    # Drop a trailing backup_id undo hint line, e.g.
+    #   "(backup_id: 20260607-...; to undo, restore this backup)"
+    cleaned = re.sub(
+        r"\n*\(backup_id:[^\)]*\)\s*$",
+        "",
+        cleaned,
+    ).rstrip()
+    return cleaned
+
+
+def _extract_tool_calls(content: Any) -> List[Dict[str, Any]]:
+    """
+    Extract tool_use blocks from an assistant message content.
+    Returns a list of {name, arguments} dicts (result filled in later).
+    """
+    if not isinstance(content, list):
+        return []
+    return [
+        {"id": b.get("id", ""), "name": b.get("name", ""), "arguments": b.get("input", {})}
+        for b in content
+        if isinstance(b, dict) and b.get("type") == "tool_use"
+    ]
+
+
+def _extract_tool_results(content: Any) -> Dict[str, dict]:
+    """
+    Extract tool_result blocks from a user message, keyed by tool_use_id.
+    Values are {"result": str, "is_error": bool}.
+    """
+    if not isinstance(content, list):
+        return {}
+    results = {}
+    for b in content:
+        if not isinstance(b, dict) or b.get("type") != "tool_result":
+            continue
+        tool_id = b.get("tool_use_id", "")
+        result_content = b.get("content", "")
+        if isinstance(result_content, list):
+            result_content = "\n".join(
+                rb.get("text", "") for rb in result_content
+                if isinstance(rb, dict) and rb.get("type") == "text"
+            )
+        results[tool_id] = {"result": str(result_content), "is_error": bool(b.get("is_error", False))}
+    return results
+
+
+def _group_into_display_turns(
+    rows: List[tuple],
+    include_thinking: bool = True,
+) -> List[Dict[str, Any]]:
+    """
+    Convert raw (role, content_json, created_at) DB rows into display turns.
+
+    One display turn = one visible user message  +  one merged assistant reply.
+    All intermediate assistant messages (those carrying tool_use) and the final
+    assistant text reply produced for the same user query are collapsed into a
+    single assistant turn, exactly matching the live SSE rendering where tools
+    and the final answer appear inside the same bubble.
+
+    Grouping rules:
+    - A visible user message starts a new group.
+    - tool_result user messages are internal; their content is attached to the
+      matching tool_use entry via tool_use_id and they never become own turns.
+    - All assistant messages within a group are merged:
+        * tool_use blocks → tool_calls list (result filled from tool_results)
+        * text blocks → last non-empty text becomes the display content
+    """
+    # ------------------------------------------------------------------ #
+    # Pass 1: split rows into groups, each starting with a visible user msg
+    # ------------------------------------------------------------------ #
+    # group = (user_row | None, [subsequent_rows])
+    # user_row: (content, created_at)
+    groups: List[tuple] = []
+    cur_user: Optional[tuple] = None
+    cur_rest: List[tuple] = []
+    started = False
+
+    for role, raw_content, created_at, raw_extras in rows:
+        try:
+            content = json.loads(raw_content)
+        except Exception:
+            content = raw_content
+        try:
+            extras = json.loads(raw_extras) if raw_extras else {}
+            if not isinstance(extras, dict):
+                extras = {}
+        except Exception:
+            extras = {}
+
+        if role == "user" and _is_visible_user_message(content):
+            if started:
+                groups.append((cur_user, cur_rest))
+            cur_user = (content, created_at, extras)
+            cur_rest = []
+            started = True
+        else:
+            cur_rest.append((role, content, created_at, extras))
+
+    if started:
+        groups.append((cur_user, cur_rest))
+
+    # ------------------------------------------------------------------ #
+    # Pass 2: build display turns from each group
+    # ------------------------------------------------------------------ #
+    turns: List[Dict[str, Any]] = []
+
+    for user_row, rest in groups:
+        # User turn
+        if user_row:
+            content, created_at, _u_extras = user_row
+            text = _extract_display_text(content)
+            # Hide internal injection markers (scheduler / self-evolution) so the
+            # user never sees a synthetic "[SCHEDULED] self-evolution" bubble;
+            # the assistant reply that follows is still rendered.
+            if text and not _is_internal_user_marker(text):
+                turns.append({"role": "user", "content": text, "created_at": created_at})
+
+        # Build an ordered list of steps preserving the original sequence:
+        #   thinking → content → tool_call → content → ...
+        steps: List[Dict[str, Any]] = []
+        tool_results: Dict[str, str] = {}
+        final_text = ""
+        final_ts: Optional[int] = None
+        merged_extras: Dict[str, Any] = {}
+
+        for role, content, created_at, extras in rest:
+            if role == "assistant" and isinstance(extras, dict):
+                merged_extras.update(extras)
+            if role == "user":
+                tool_results.update(_extract_tool_results(content))
+            elif role == "assistant":
+                # Walk content blocks in order to preserve interleaving
+                if isinstance(content, list):
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        btype = block.get("type")
+                        if btype == "thinking":
+                            if not include_thinking:
+                                continue
+                            txt = block.get("thinking", "").strip()
+                            if txt:
+                                steps.append({"type": "thinking", "content": txt})
+                        elif btype == "text":
+                            txt = block.get("text", "").strip()
+                            if txt:
+                                steps.append({"type": "content", "content": txt})
+                                final_text = txt
+                        elif btype == "tool_use":
+                            steps.append({
+                                "type": "tool",
+                                "id": block.get("id", ""),
+                                "name": block.get("name", ""),
+                                "arguments": block.get("input", {}),
+                            })
+                elif isinstance(content, str) and content.strip():
+                    steps.append({"type": "content", "content": content.strip()})
+                    final_text = content.strip()
+                final_ts = created_at
+
+        # Attach tool results to tool steps
+        for step in steps:
+            if step["type"] == "tool":
+                tr = tool_results.get(step.get("id", ""), {})
+                if not isinstance(tr, dict):
+                    tr = {"result": tr}
+                step["result"] = tr.get("result", "")
+                step["is_error"] = tr.get("is_error", False)
+
+        # Detect a self-evolution bubble BEFORE cleaning the marker away, so the
+        # UI can flag it even though the visible text stays clean.
+        is_evolution = _is_evolution_text(final_text)
+
+        # Clean internal markers from the user-facing assistant text. Applies to
+        # both the final content and the mirrored content step so the rendered
+        # bubble shows clean text while the stored message keeps the markers.
+        final_text = _clean_display_text(final_text)
+        for step in steps:
+            if step.get("type") == "content":
+                step["content"] = _clean_display_text(step.get("content", ""))
+
+        if steps or final_text:
+            turn = {
+                "role": "assistant",
+                "content": final_text,
+                "steps": steps,
+                "created_at": final_ts or (user_row[1] if user_row else 0),
+            }
+            if is_evolution:
+                turn["kind"] = "evolution"
+            if merged_extras:
+                turn["extras"] = merged_extras
+            turns.append(turn)
+
+    return turns
+
+
+class ConversationStore:
+    """
+    SQLite-backed store for per-session conversation history.
+
+    Usage:
+        store = ConversationStore(db_path)
+        store.append_messages("user_123", new_messages, channel_type="feishu")
+        msgs = store.load_messages("user_123", max_turns=30)
+    """
+
+    def __init__(self, db_path: Path):
+        self._db_path = db_path
+        self._lock = threading.RLock()  # Use RLock to allow reentrant locking
+        self._init_db()
+
+    # ------------------------------------------------------------------
+    # Public API
+    # ------------------------------------------------------------------
+
+    def load_messages(
+        self,
+        session_id: str,
+        max_turns: int = 30,
+    ) -> List[Dict[str, Any]]:
+        """
+        Load the most recent messages for a session, for injection into the LLM.
+
+        ALL message types (user text, assistant tool_use, tool_result) are returned
+        in their original JSON form so the LLM can reconstruct the full context.
+
+        max_turns is a *visible-turn* count: we count only user messages whose
+        content is actual user text (not tool_result blocks).  This prevents
+        tool-heavy sessions from exhausting the turn budget prematurely.
+
+        Args:
+            session_id: Unique session identifier.
+            max_turns: Maximum number of visible user-assistant turns to keep.
+
+        Returns:
+            Chronologically ordered list of message dicts (role, content).
+        """
+        with self._lock:
+            conn = self._connect()
+            try:
+                # Respect context_start_seq: only load messages at or after the boundary
+                ctx_row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                ctx_start = ctx_row[0] if ctx_row else 0
+
+                rows = conn.execute(
+                    """
+                    SELECT seq, role, content
+                    FROM messages
+                    WHERE session_id = ? AND seq >= ?
+                    ORDER BY seq DESC
+                    """,
+                    (session_id, ctx_start),
+                ).fetchall()
+            finally:
+                conn.close()
+
+        if not rows:
+            return []
+
+        visible_turn_seqs: List[int] = []
+        for seq, role, raw_content in rows:
+            if role != "user":
+                continue
+            try:
+                content = json.loads(raw_content)
+            except Exception:
+                content = raw_content
+            if _is_visible_user_message(content):
+                visible_turn_seqs.append(seq)
+
+        if len(visible_turn_seqs) <= max_turns:
+            cutoff_seq = None
+        else:
+            cutoff_seq = visible_turn_seqs[max_turns - 1]
+
+        result = []
+        for seq, role, raw_content in reversed(rows):
+            if cutoff_seq is not None and seq < cutoff_seq:
+                continue
+            try:
+                content = json.loads(raw_content)
+            except Exception:
+                content = raw_content
+            # Strip thinking blocks — they are stored for UI display only
+            if role == "assistant" and isinstance(content, list):
+                content = [b for b in content if b.get("type") != "thinking"]
+            result.append({"role": role, "content": content})
+        return result
+
+    def append_messages(
+        self,
+        session_id: str,
+        messages: List[Dict[str, Any]],
+        channel_type: str = "",
+    ) -> None:
+        """
+        Append new messages to a session's history.
+
+        Seq numbers continue from the session's current maximum, so
+        concurrent callers on distinct sessions never collide.
+
+        Args:
+            session_id: Unique session identifier.
+            messages: List of message dicts to append.
+            channel_type: Source channel (e.g. "feishu", "web", "wechat").
+                          Only written on session creation; ignored on update.
+        """
+        if not messages:
+            return
+
+        now = int(time.time())
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    # INSERT OR IGNORE creates the row on first visit;
+                    # the UPDATE always refreshes last_active.
+                    # Avoids ON CONFLICT...DO UPDATE (requires SQLite >= 3.24).
+                    conn.execute(
+                        """
+                        INSERT OR IGNORE INTO sessions
+                            (session_id, channel_type, created_at, last_active, msg_count)
+                        VALUES (?, ?, ?, ?, 0)
+                        """,
+                        (session_id, channel_type, now, now),
+                    )
+                    conn.execute(
+                        "UPDATE sessions SET last_active = ? WHERE session_id = ?",
+                        (now, session_id),
+                    )
+
+                    # Determine starting seq for the new batch.
+                    row = conn.execute(
+                        "SELECT COALESCE(MAX(seq), -1) FROM messages WHERE session_id = ?",
+                        (session_id,),
+                    ).fetchone()
+                    next_seq = row[0] + 1
+
+                    for msg in messages:
+                        role = msg.get("role", "")
+                        content = json.dumps(
+                            msg.get("content", ""), ensure_ascii=False
+                        )
+                        extras_obj = msg.get("extras") or {}
+                        extras = json.dumps(extras_obj, ensure_ascii=False) if extras_obj else ""
+                        conn.execute(
+                            """
+                            INSERT OR IGNORE INTO messages
+                                (session_id, seq, role, content, created_at, extras)
+                            VALUES (?, ?, ?, ?, ?, ?)
+                            """,
+                            (session_id, next_seq, role, content, now, extras),
+                        )
+                        next_seq += 1
+
+                    conn.execute(
+                        """
+                        UPDATE sessions
+                        SET msg_count = (
+                            SELECT COUNT(*) FROM messages WHERE session_id = ?
+                        )
+                        WHERE session_id = ?
+                        """,
+                        (session_id, session_id),
+                    )
+
+                    # Auto-generate title from the first visible user message
+                    cur_title = conn.execute(
+                        "SELECT title FROM sessions WHERE session_id = ?",
+                        (session_id,),
+                    ).fetchone()
+                    if cur_title and not cur_title[0]:
+                        for msg in messages:
+                            if msg.get("role") == "user":
+                                content = msg.get("content", "")
+                                text = _extract_display_text(content)
+                                if text:
+                                    title = text[:50].split("\n")[0]
+                                    conn.execute(
+                                        "UPDATE sessions SET title = ? WHERE session_id = ?",
+                                        (title, session_id),
+                                    )
+                                    break
+            finally:
+                conn.close()
+
+    def clear_context(self, session_id: str) -> int:
+        """
+        Set the context boundary to after the current last message.
+        Messages before this boundary are still stored but excluded from LLM context.
+
+        Returns the new context_start_seq value.
+        """
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    row = conn.execute(
+                        "SELECT COALESCE(MAX(seq), -1) FROM messages WHERE session_id = ?",
+                        (session_id,),
+                    ).fetchone()
+                    new_start = row[0] + 1
+                    conn.execute(
+                        "UPDATE sessions SET context_start_seq = ? WHERE session_id = ?",
+                        (new_start, session_id),
+                    )
+                    return new_start
+            finally:
+                conn.close()
+
+    def get_context_start_seq(self, session_id: str) -> int:
+        """Return the context_start_seq for a session (0 if not set)."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                return row[0] if row else 0
+            finally:
+                conn.close()
+
+    def get_latest_pair_seqs(self, session_id: str) -> Dict[str, Optional[int]]:
+        """Return the seq numbers of the latest visible user message and the
+        latest assistant message in a session.
+
+        A "visible" user message is one whose content is real user text
+        (not just a tool_result block), so tool-execution turns do not
+        shadow the actual user query.
+
+        Returns:
+            Dict with keys ``user_seq`` and ``bot_seq``; either may be None
+            when no matching message exists.
+        """
+        result: Dict[str, Optional[int]] = {"user_seq": None, "bot_seq": None}
+        with self._lock:
+            conn = self._connect()
+            try:
+                # Latest assistant message (cheap: single row by seq DESC).
+                row = conn.execute(
+                    "SELECT seq FROM messages "
+                    "WHERE session_id = ? AND role = 'assistant' "
+                    "ORDER BY seq DESC LIMIT 1",
+                    (session_id,),
+                ).fetchone()
+                if row:
+                    result["bot_seq"] = int(row[0])
+
+                # Latest visible user message: scan recent user rows and
+                # skip pure tool_result entries.
+                rows = conn.execute(
+                    "SELECT seq, content FROM messages "
+                    "WHERE session_id = ? AND role = 'user' "
+                    "ORDER BY seq DESC LIMIT 20",
+                    (session_id,),
+                ).fetchall()
+                for seq, content_raw in rows:
+                    try:
+                        content = json.loads(content_raw)
+                    except Exception:
+                        result["user_seq"] = int(seq)
+                        break
+                    if isinstance(content, list):
+                        has_text = any(
+                            isinstance(b, dict) and b.get("type") == "text"
+                            for b in content
+                        )
+                        has_tool_result = any(
+                            isinstance(b, dict) and b.get("type") == "tool_result"
+                            for b in content
+                        )
+                        if has_text and not has_tool_result:
+                            result["user_seq"] = int(seq)
+                            break
+                    else:
+                        result["user_seq"] = int(seq)
+                        break
+            finally:
+                conn.close()
+        return result
+
+    def clear_session(self, session_id: str) -> None:
+        """Delete all messages and the session record for a given session_id."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    conn.execute(
+                        "DELETE FROM messages WHERE session_id = ?", (session_id,)
+                    )
+                    conn.execute(
+                        "DELETE FROM sessions WHERE session_id = ?", (session_id,)
+                    )
+            finally:
+                conn.close()
+
+    def delete_message_pair(self, session_id: str, user_seq: int, delete_user: bool = True, cascade: bool = False) -> int:
+        """Delete a user message and/or its corresponding assistant reply.
+
+        The assistant reply is identified as all messages between user_seq
+        and the next visible user message (or end of session).
+
+        Args:
+            session_id: Session identifier.
+            user_seq: The seq number of the user message.
+            delete_user: If True (default), delete the user message too.
+                        If False, only delete assistant reply (for regenerate scenarios).
+            cascade: If True, also delete all subsequent turns after this one.
+                    Used by edit-message which removes this turn and everything after.
+
+        Returns:
+            Number of message rows deleted.
+        """
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    # Verify this is a user message
+                    row = conn.execute(
+                        "SELECT role FROM messages WHERE session_id = ? AND seq = ?",
+                        (session_id, user_seq),
+                    ).fetchone()
+                    if not row or row[0] != "user":
+                        return 0
+
+                    if cascade:
+                        # Delete from this message to end of session
+                        start_seq = user_seq if delete_user else user_seq + 1
+                        end_seq_row = conn.execute(
+                            "SELECT MAX(seq) FROM messages WHERE session_id = ?",
+                            (session_id,),
+                        ).fetchone()
+                        end_seq = (end_seq_row[0] or user_seq) + 1
+                    else:
+                        # Find the next visible user message seq (exclude tool_result)
+                        # Use batched query to avoid loading too many rows at once
+                        next_user_seq = None
+                        batch_size = 100
+                        offset = 0
+                        while True:
+                            batch = conn.execute(
+                                """
+                                SELECT seq, content FROM messages
+                                WHERE session_id = ? AND seq > ? AND role = 'user'
+                                ORDER BY seq ASC
+                                LIMIT ? OFFSET ?
+                                """,
+                                (session_id, user_seq, batch_size, offset),
+                            ).fetchall()
+                            if not batch:
+                                break
+                            for seq, content in batch:
+                                try:
+                                    content_obj = json.loads(content)
+                                except Exception:
+                                    content_obj = content
+                                if _is_visible_user_message(content_obj):
+                                    next_user_seq = seq
+                                    break
+                            if next_user_seq is not None:
+                                break
+                            offset += batch_size
+
+                        # Determine the end boundary for deletion
+                        if next_user_seq is not None:
+                            end_seq = next_user_seq
+                        else:
+                            end_seq_row = conn.execute(
+                                "SELECT MAX(seq) FROM messages WHERE session_id = ?",
+                                (session_id,),
+                            ).fetchone()
+                            end_seq = (end_seq_row[0] or user_seq) + 1
+
+                        # Determine the start boundary for deletion
+                        start_seq = user_seq if delete_user else user_seq + 1
+
+                    # Delete messages from start_seq to end_seq (exclusive)
+                    cur = conn.execute(
+                        "DELETE FROM messages WHERE session_id = ? AND seq >= ? AND seq < ?",
+                        (session_id, start_seq, end_seq),
+                    )
+                    deleted = cur.rowcount
+
+                    # Update session msg_count
+                    conn.execute(
+                        """
+                        UPDATE sessions
+                        SET msg_count = (
+                            SELECT COUNT(*) FROM messages WHERE session_id = ?
+                        )
+                        WHERE session_id = ?
+                        """,
+                        (session_id, session_id),
+                    )
+
+                    return deleted
+            finally:
+                conn.close()
+
+    def prune_scheduled_messages(
+        self,
+        session_id: str,
+        keep_last_n: int,
+        markers: Optional[List[str]] = None,
+    ) -> int:
+        """
+        Keep at most ``keep_last_n`` scheduler-injected user/assistant pairs in
+        the session, deleting the older ones.
+
+        A scheduler-injected pair is identified by a user message whose first
+        text block starts with one of ``markers``; the immediately following
+        assistant message (next seq) is treated as its paired output.
+
+        Only scheduler-tagged messages are touched; regular user turns are
+        never deleted. Safe to call repeatedly; no-op if nothing to prune.
+
+        Args:
+            session_id: Session to prune.
+            keep_last_n: Maximum scheduler pairs to retain (must be >= 0).
+            markers: Text prefixes that identify scheduler user messages.
+                Defaults to ``["[SCHEDULED]", "Scheduled task"]`` so that
+                pairs written by older versions are also recognised.
+
+        Returns:
+            Number of message rows deleted.
+        """
+        if keep_last_n < 0:
+            keep_last_n = 0
+        if markers is None:
+            markers = ["[SCHEDULED]", "Scheduled task"]
+
+        def _matches_marker(raw_content: str) -> bool:
+            try:
+                parsed = json.loads(raw_content)
+            except Exception:
+                parsed = raw_content
+            text = _extract_display_text(parsed) if not isinstance(parsed, str) else parsed
+            if not text:
+                return False
+            return any(text.startswith(m) for m in markers)
+
+        with self._lock:
+            conn = self._connect()
+            try:
+                rows = conn.execute(
+                    """
+                    SELECT seq, role, content
+                    FROM messages
+                    WHERE session_id = ?
+                    ORDER BY seq ASC
+                    """,
+                    (session_id,),
+                ).fetchall()
+
+                # Find scheduler pairs: each is (user_seq, assistant_seq?)
+                pairs: List[tuple] = []  # list of (user_seq, assistant_seq_or_None)
+                for idx, (seq, role, raw_content) in enumerate(rows):
+                    if role != "user" or not _matches_marker(raw_content):
+                        continue
+                    assistant_seq = None
+                    # Pair with the very next message if it's an assistant turn.
+                    if idx + 1 < len(rows):
+                        next_seq, next_role, _ = rows[idx + 1]
+                        if next_role == "assistant":
+                            assistant_seq = next_seq
+                    pairs.append((seq, assistant_seq))
+
+                if len(pairs) <= keep_last_n:
+                    return 0
+
+                to_delete_pairs = pairs[: len(pairs) - keep_last_n]
+                seqs_to_delete: List[int] = []
+                for user_seq, assistant_seq in to_delete_pairs:
+                    seqs_to_delete.append(user_seq)
+                    if assistant_seq is not None:
+                        seqs_to_delete.append(assistant_seq)
+
+                if not seqs_to_delete:
+                    return 0
+
+                placeholders = ",".join("?" * len(seqs_to_delete))
+                with conn:
+                    conn.execute(
+                        f"DELETE FROM messages WHERE session_id = ? AND seq IN ({placeholders})",
+                        (session_id, *seqs_to_delete),
+                    )
+                    conn.execute(
+                        """
+                        UPDATE sessions
+                        SET msg_count = (
+                            SELECT COUNT(*) FROM messages WHERE session_id = ?
+                        )
+                        WHERE session_id = ?
+                        """,
+                        (session_id, session_id),
+                    )
+                return len(seqs_to_delete)
+            finally:
+                conn.close()
+
+    def cleanup_old_sessions(self, max_age_days: Optional[int] = None) -> int:
+        """
+        Delete sessions that have not been active within max_age_days.
+        Web channel sessions are excluded — they are meant to be permanent.
+
+        Args:
+            max_age_days: Override the default retention period.
+
+        Returns:
+            Number of sessions deleted.
+        """
+        try:
+            from config import conf
+            max_age = max_age_days or conf().get(
+                "conversation_max_age_days", DEFAULT_MAX_AGE_DAYS
+            )
+        except Exception:
+            max_age = max_age_days or DEFAULT_MAX_AGE_DAYS
+
+        cutoff = int(time.time()) - max_age * 86400
+        deleted = 0
+
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    stale = conn.execute(
+                        "SELECT session_id FROM sessions "
+                        "WHERE last_active < ? AND channel_type != 'web'",
+                        (cutoff,),
+                    ).fetchall()
+                    for (sid,) in stale:
+                        conn.execute(
+                            "DELETE FROM messages WHERE session_id = ?", (sid,)
+                        )
+                        conn.execute(
+                            "DELETE FROM sessions WHERE session_id = ?", (sid,)
+                        )
+                        deleted += 1
+            finally:
+                conn.close()
+
+        if deleted:
+            logger.info(f"[ConversationStore] Pruned {deleted} expired sessions")
+        return deleted
+
+    def attach_extras_to_last_assistant(
+        self,
+        session_id: str,
+        extras: Dict[str, Any],
+    ) -> Optional[int]:
+        """
+        Merge ``extras`` into the latest assistant message of a session.
+
+        Used by post-processing (e.g. TTS) that needs to annotate an already
+        persisted bot reply with attachments such as audio URLs.
+
+        Returns the message seq that was updated, or ``None`` if no assistant
+        message exists or the update could not be applied.
+        """
+        if not extras:
+            return None
+        with self._lock:
+            conn = self._connect()
+            try:
+                row = conn.execute(
+                    """
+                    SELECT seq, extras FROM messages
+                    WHERE session_id = ? AND role = 'assistant'
+                    ORDER BY seq DESC LIMIT 1
+                    """,
+                    (session_id,),
+                ).fetchone()
+                if not row:
+                    return None
+                seq, raw = row
+                try:
+                    cur = json.loads(raw) if raw else {}
+                    if not isinstance(cur, dict):
+                        cur = {}
+                except Exception:
+                    cur = {}
+                cur.update(extras)
+                conn.execute(
+                    "UPDATE messages SET extras = ? WHERE session_id = ? AND seq = ?",
+                    (json.dumps(cur, ensure_ascii=False), session_id, seq),
+                )
+                conn.commit()
+                return seq
+            except Exception as e:
+                logger.warning(f"[ConversationStore] attach_extras failed: {e}")
+                return None
+            finally:
+                conn.close()
+
+    def load_history_page(
+        self,
+        session_id: str,
+        page: int = 1,
+        page_size: int = 20,
+    ) -> Dict[str, Any]:
+        """
+        Load a page of conversation history for UI display, grouped into turns.
+
+        Each "turn" maps to one of:
+          - A user message (role="user", content=str)
+          - An assistant message (role="assistant", content=str,
+            tool_calls=[{name, arguments, result}] when tools were used)
+
+        Internal tool_result user messages are merged into the preceding
+        assistant entry's tool_calls list and never appear as standalone items.
+
+        Pages are numbered from 1 (most recent).  Messages within a page are
+        returned in chronological order.
+
+        Returns:
+            {
+                "messages": [
+                    {
+                        "role": "user" | "assistant",
+                        "content": str,
+                        "tool_calls": [...],   # assistant only, may be []
+                        "created_at": int,
+                    },
+                    ...
+                ],
+                "total": <visible turn count>,
+                "page": <current page>,
+                "page_size": <page_size>,
+                "has_more": bool,
+            }
+        """
+        page = max(1, page)
+        with self._lock:
+            conn = self._connect()
+            try:
+                ctx_row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                ctx_start = ctx_row[0] if ctx_row else 0
+
+                # extras column is added by migration; tolerate older DBs that
+                # might miss it by falling back to a NULL literal.
+                try:
+                    rows = conn.execute(
+                        """
+                        SELECT seq, role, content, created_at, extras
+                        FROM messages
+                        WHERE session_id = ?
+                        ORDER BY seq ASC
+                        """,
+                        (session_id,),
+                    ).fetchall()
+                except sqlite3.OperationalError:
+                    rows = [
+                        (seq, role, content, created_at, "")
+                        for (seq, role, content, created_at) in conn.execute(
+                            """
+                            SELECT seq, role, content, created_at
+                            FROM messages
+                            WHERE session_id = ?
+                            ORDER BY seq ASC
+                            """,
+                            (session_id,),
+                        ).fetchall()
+                    ]
+            finally:
+                conn.close()
+
+        # Honour the current enable_thinking switch when building display turns
+        # so that toggling it off hides previously-saved thinking blocks too.
+        try:
+            from config import conf
+            include_thinking = bool(conf().get("enable_thinking", False))
+        except Exception:
+            include_thinking = False
+
+        # Strip seq for display grouping, but record max seq per visible user group
+        plain_rows = [
+            (role, content, created_at, extras_raw)
+            for _seq, role, content, created_at, extras_raw in rows
+        ]
+        visible = _group_into_display_turns(plain_rows, include_thinking=include_thinking)
+
+        # Build a mapping: find the seq of each visible user message to annotate context boundary.
+        # Walk through rows to find visible user message seqs in order.
+        visible_user_seqs: List[int] = []
+        for seq, role, raw_content, _ts, _extras in rows:
+            if role != "user":
+                continue
+            try:
+                content = json.loads(raw_content)
+            except Exception:
+                content = raw_content
+            if _is_visible_user_message(content):
+                visible_user_seqs.append(seq)
+
+        # Each pair of display turns (user+assistant) corresponds to a visible user seq.
+        # Mark which turns are before the context boundary.
+        user_turn_idx = 0
+        for turn in visible:
+            if turn["role"] == "user" and user_turn_idx < len(visible_user_seqs):
+                turn["_seq"] = visible_user_seqs[user_turn_idx]
+                user_turn_idx += 1
+
+        total = len(visible)
+        offset = (page - 1) * page_size
+        page_items = list(reversed(visible))[offset: offset + page_size]
+        page_items = list(reversed(page_items))
+
+        return {
+            "messages": page_items,
+            "context_start_seq": ctx_start,
+            "total": total,
+            "page": page,
+            "page_size": page_size,
+            "has_more": offset + page_size < total,
+        }
+
+    def list_sessions(
+        self,
+        channel_type: Optional[str] = None,
+        page: int = 1,
+        page_size: int = 50,
+    ) -> Dict[str, Any]:
+        """
+        List sessions ordered by last_active DESC, with optional channel_type filter.
+
+        Returns:
+            {
+                "sessions": [{session_id, title, created_at, last_active, msg_count}, ...],
+                "total": int,
+                "page": int,
+                "page_size": int,
+                "has_more": bool,
+            }
+        """
+        page = max(1, page)
+        with self._lock:
+            conn = self._connect()
+            try:
+                if channel_type:
+                    total = conn.execute(
+                        "SELECT COUNT(*) FROM sessions WHERE channel_type = ?",
+                        (channel_type,),
+                    ).fetchone()[0]
+                    rows = conn.execute(
+                        """
+                        SELECT session_id, title, created_at, last_active, msg_count
+                        FROM sessions
+                        WHERE channel_type = ?
+                        ORDER BY last_active DESC
+                        LIMIT ? OFFSET ?
+                        """,
+                        (channel_type, page_size, (page - 1) * page_size),
+                    ).fetchall()
+                else:
+                    total = conn.execute(
+                        "SELECT COUNT(*) FROM sessions",
+                    ).fetchone()[0]
+                    rows = conn.execute(
+                        """
+                        SELECT session_id, title, created_at, last_active, msg_count
+                        FROM sessions
+                        ORDER BY last_active DESC
+                        LIMIT ? OFFSET ?
+                        """,
+                        (page_size, (page - 1) * page_size),
+                    ).fetchall()
+            finally:
+                conn.close()
+
+        sessions = [
+            {
+                "session_id": r[0],
+                "title": r[1],
+                "created_at": r[2],
+                "last_active": r[3],
+                "msg_count": r[4],
+            }
+            for r in rows
+        ]
+        return {
+            "sessions": sessions,
+            "total": total,
+            "page": page,
+            "page_size": page_size,
+            "has_more": (page - 1) * page_size + page_size < total,
+        }
+
+    def rename_session(self, session_id: str, title: str) -> bool:
+        """Update the title of a session. Returns True if the session existed."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    cur = conn.execute(
+                        "UPDATE sessions SET title = ? WHERE session_id = ?",
+                        (title, session_id),
+                    )
+                    return cur.rowcount > 0
+            finally:
+                conn.close()
+
+    def get_stats(self) -> Dict[str, Any]:
+        """Return basic stats keyed by channel_type, for monitoring."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                total_sessions = conn.execute(
+                    "SELECT COUNT(*) FROM sessions"
+                ).fetchone()[0]
+                total_messages = conn.execute(
+                    "SELECT COUNT(*) FROM messages"
+                ).fetchone()[0]
+                by_channel = conn.execute(
+                    """
+                    SELECT channel_type, COUNT(*) as cnt
+                    FROM sessions
+                    GROUP BY channel_type
+                    ORDER BY cnt DESC
+                    """
+                ).fetchall()
+                return {
+                    "total_sessions": total_sessions,
+                    "total_messages": total_messages,
+                    "by_channel": {row[0] or "unknown": row[1] for row in by_channel},
+                }
+            finally:
+                conn.close()
+
+    # ------------------------------------------------------------------
+    # Internal helpers
+    # ------------------------------------------------------------------
+
+    def _init_db(self) -> None:
+        self._db_path.parent.mkdir(parents=True, exist_ok=True)
+        conn = self._connect()
+        try:
+            conn.executescript(_DDL)
+            conn.commit()
+            self._migrate(conn)
+        finally:
+            conn.close()
+
+    def _migrate(self, conn: sqlite3.Connection) -> None:
+        """Apply incremental schema migrations on existing databases."""
+        cols = {
+            row[1]
+            for row in conn.execute("PRAGMA table_info(sessions)").fetchall()
+        }
+        if "channel_type" not in cols:
+            try:
+                conn.execute(_MIGRATION_ADD_CHANNEL_TYPE)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added channel_type column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration failed: {e}")
+        if "title" not in cols:
+            try:
+                conn.execute(_MIGRATION_ADD_TITLE)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added title column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration (title) failed: {e}")
+        if "context_start_seq" not in cols:
+            try:
+                conn.execute(_MIGRATION_ADD_CONTEXT_START_SEQ)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added context_start_seq column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration (context_start_seq) failed: {e}")
+
+        msg_cols = {
+            row[1]
+            for row in conn.execute("PRAGMA table_info(messages)").fetchall()
+        }
+        if "extras" not in msg_cols:
+            try:
+                conn.execute(_MIGRATION_ADD_MSG_EXTRAS)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added messages.extras column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration (extras) failed: {e}")
+
+    def _connect(self) -> sqlite3.Connection:
+        conn = sqlite3.connect(str(self._db_path), timeout=10)
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA synchronous=NORMAL")
+        return conn
+
+
+# ---------------------------------------------------------------------------
+# Singleton
+# ---------------------------------------------------------------------------
+
+_store_instance: Optional[ConversationStore] = None
+_store_lock = threading.Lock()
+
+
+def get_conversation_store() -> ConversationStore:
+    """
+    Return the process-wide ConversationStore singleton.
+
+    Reuses the long-term memory database so the project stays with a single
+    SQLite file: ~/cow/memory/long-term/index.db
+    The conversation tables (sessions / messages) are separate from the
+    memory tables (memory_chunks / file_metadata) — no conflicts.
+    """
+    global _store_instance
+    if _store_instance is not None:
+        return _store_instance
+
+    with _store_lock:
+        if _store_instance is not None:
+            return _store_instance
+
+        try:
+            from agent.memory.config import get_default_memory_config
+            db_path = get_default_memory_config().get_db_path()
+        except Exception:
+            from common.utils import expand_path
+            db_path = Path(expand_path("~/cow")) / "memory" / "long-term" / "index.db"
+
+        _store_instance = ConversationStore(db_path)
+        logger.debug(f"[ConversationStore] Using shared DB at: {db_path}")
+        return _store_instance
+
diff --git a/agent/memory/embedding/__init__.py b/agent/memory/embedding/__init__.py
new file mode 100644
index 0000000..276b017
--- /dev/null
+++ b/agent/memory/embedding/__init__.py
@@ -0,0 +1,43 @@
+"""
+Embedding subsystem for memory.
+
+Public API:
+  create_embedding_provider, EmbeddingProvider, OpenAIEmbeddingProvider,
+  EMBEDDING_VENDORS, EmbeddingCache
+  RebuildResult, clear_index, rebuild_in_process
+  detect_index_dim, cleanup_legacy_state_file
+"""
+
+from agent.memory.embedding.provider import (
+    EMBEDDING_VENDORS,
+    DoubaoEmbeddingProvider,
+    EmbeddingCache,
+    EmbeddingProvider,
+    OpenAIEmbeddingProvider,
+    create_embedding_provider,
+)
+from agent.memory.embedding.factory import create_default_embedding_provider
+from agent.memory.embedding.rebuild import (
+    RebuildResult,
+    clear_index,
+    rebuild_in_process,
+)
+from agent.memory.embedding.state import (
+    cleanup_legacy_state_file,
+    detect_index_dim,
+)
+
+__all__ = [
+    "EMBEDDING_VENDORS",
+    "DoubaoEmbeddingProvider",
+    "EmbeddingCache",
+    "EmbeddingProvider",
+    "OpenAIEmbeddingProvider",
+    "create_embedding_provider",
+    "create_default_embedding_provider",
+    "RebuildResult",
+    "clear_index",
+    "rebuild_in_process",
+    "cleanup_legacy_state_file",
+    "detect_index_dim",
+]
diff --git a/agent/memory/embedding/factory.py b/agent/memory/embedding/factory.py
new file mode 100644
index 0000000..0a50f18
--- /dev/null
+++ b/agent/memory/embedding/factory.py
@@ -0,0 +1,209 @@
+"""
+Shared embedding provider factory.
+
+Resolves the embedding provider purely from config.json, so every caller
+(agent initialization, knowledge base sync, index rebuild, ...) selects the
+same provider instead of silently degrading to keyword-only search.
+
+Two paths:
+  A. Default (no `embedding_provider` in config.json):
+     Auto-init OpenAI -> LinkAI fallback.
+  B. Explicit (`embedding_provider` is set):
+     Initialize the requested vendor with unified dim (default per vendor).
+"""
+
+import os
+from typing import Optional
+
+from common.log import logger
+
+# Track whether the embedding model log has been printed in this process,
+# so we avoid spamming it once per session/caller.
+_embedding_logged: bool = False
+
+
+def create_default_embedding_provider():
+    """Build the embedding provider from config, or None for keyword-only mode."""
+    from config import conf
+
+    explicit_provider = (conf().get("embedding_provider") or "").strip().lower()
+    if not explicit_provider:
+        return _init_legacy_provider()
+    return _init_explicit_provider(explicit_provider)
+
+
+def _init_legacy_provider():
+    """Legacy auto-init path: OpenAI -> LinkAI."""
+    from agent.memory.embedding.provider import create_embedding_provider
+    from config import conf
+
+    embedding_provider = None
+    embedding_model = None
+
+    openai_api_key = conf().get("open_ai_api_key", "")
+    openai_api_base = conf().get("open_ai_api_base", "")
+    if openai_api_key and openai_api_key not in ["", "YOUR API KEY", "YOUR_API_KEY"]:
+        try:
+            model = "text-embedding-3-small"
+            embedding_provider = create_embedding_provider(
+                provider="openai",
+                model=model,
+                api_key=openai_api_key,
+                api_base=openai_api_base or "https://api.openai.com/v1",
+            )
+            embedding_model = f"openai/{model}"
+        except Exception as e:
+            logger.warning(f"[EmbeddingFactory] OpenAI embedding failed: {e}")
+
+    if embedding_provider is None:
+        linkai_api_key = conf().get("linkai_api_key", "") or os.environ.get("LINKAI_API_KEY", "")
+        linkai_api_base = conf().get("linkai_api_base", "https://api.link-ai.tech")
+        if linkai_api_key and linkai_api_key not in ["", "YOUR API KEY", "YOUR_API_KEY"]:
+            try:
+                model = "text-embedding-3-small"
+                embedding_provider = create_embedding_provider(
+                    provider="linkai",
+                    model=model,
+                    api_key=linkai_api_key,
+                    api_base=f"{linkai_api_base}/v1",
+                )
+                embedding_model = f"linkai/{model}"
+            except Exception as e:
+                logger.warning(f"[EmbeddingFactory] LinkAI embedding failed: {e}")
+
+    if embedding_provider is not None and embedding_model:
+        _log_provider_once(f"{embedding_model} (dim={embedding_provider.dimensions})")
+
+    return embedding_provider
+
+
+def _init_explicit_provider(provider_key: str):
+    """Explicit-provider path: build the configured vendor."""
+    from agent.memory.embedding.provider import EMBEDDING_VENDORS, create_embedding_provider
+    from config import conf
+
+    # Custom providers ("custom:<id>") resolve credentials from custom_providers.
+    resolved_provider_key = provider_key
+    if provider_key.startswith("custom:"):
+        resolved_provider_key = "custom"
+
+    meta = EMBEDDING_VENDORS.get(resolved_provider_key)
+    if meta is None:
+        logger.error(
+            f"[EmbeddingFactory] Unknown embedding_provider '{provider_key}'. "
+            f"Supported: {sorted(EMBEDDING_VENDORS.keys())}. "
+            f"Memory will run in keyword-only mode."
+        )
+        return None
+
+    api_key = _resolve_api_key(provider_key)
+    api_base = _resolve_api_base(provider_key, meta["default_base_url"])
+
+    if not api_key:
+        logger.error(
+            f"[EmbeddingFactory] embedding_provider='{provider_key}' is set but its "
+            f"API key is missing. Memory will run in keyword-only mode."
+        )
+        return None
+
+    model = (conf().get("embedding_model") or "").strip()
+    # Custom providers without a model fall back to the provider's default.
+    if not model and resolved_provider_key == "custom":
+        from models.custom_provider import parse_custom_bot_type, get_custom_providers, _find_provider_by_id
+        _, custom_id = parse_custom_bot_type(provider_key)
+        if custom_id:
+            entry = _find_provider_by_id(get_custom_providers(), custom_id)
+            if entry and entry.get("model"):
+                model = entry["model"]
+    if not model and resolved_provider_key != "custom":
+        model = meta["default_model"]
+
+    try:
+        cfg_dim = int(conf().get("embedding_dimensions") or 0)
+    except (TypeError, ValueError):
+        cfg_dim = 0
+    dim = cfg_dim if cfg_dim > 0 else meta["default_dimensions"]
+
+    try:
+        provider = create_embedding_provider(
+            provider=resolved_provider_key,
+            model=model,
+            api_key=api_key,
+            api_base=api_base,
+            dimensions=dim,
+        )
+    except Exception as e:
+        logger.error(
+            f"[EmbeddingFactory] Failed to init embedding provider "
+            f"'{provider_key}/{model}': {e}"
+        )
+        return None
+
+    _log_provider_once(f"{provider_key}/{model} (dim={provider.dimensions})")
+    return provider
+
+
+def _resolve_api_key(provider_key: str) -> str:
+    """Pick the API key for an explicit embedding provider from config."""
+    from config import conf
+
+    if provider_key.startswith("custom:"):
+        from models.custom_provider import parse_custom_bot_type, get_custom_providers, _find_provider_by_id
+        _, custom_id = parse_custom_bot_type(provider_key)
+        if custom_id:
+            entry = _find_provider_by_id(get_custom_providers(), custom_id)
+            if entry:
+                return entry.get("api_key", "")
+        return ""
+
+    key_map = {
+        "openai":    "open_ai_api_key",
+        "linkai":    "linkai_api_key",
+        "dashscope": "dashscope_api_key",
+        "doubao":    "ark_api_key",
+        "zhipu":     "zhipu_ai_api_key",
+    }
+    field = key_map.get(provider_key)
+    if not field:
+        return ""
+    value = conf().get(field, "") or ""
+    if value in ["", "YOUR API KEY", "YOUR_API_KEY"]:
+        return ""
+    return value
+
+
+def _resolve_api_base(provider_key: str, default_base: str) -> str:
+    """Pick the API base for an explicit embedding provider from config."""
+    from config import conf
+
+    if provider_key.startswith("custom:"):
+        from models.custom_provider import parse_custom_bot_type, get_custom_providers, _find_provider_by_id
+        _, custom_id = parse_custom_bot_type(provider_key)
+        if custom_id:
+            entry = _find_provider_by_id(get_custom_providers(), custom_id)
+            if entry and entry.get("api_base"):
+                return entry["api_base"]
+        return default_base
+
+    base_map = {
+        "openai":    "open_ai_api_base",
+        "linkai":    "linkai_api_base",
+        "doubao":    "ark_base_url",
+        "zhipu":     "zhipu_ai_api_base",
+    }
+    field = base_map.get(provider_key)
+    if not field:
+        return default_base
+    value = (conf().get(field) or "").strip()
+    if not value:
+        return default_base
+    if provider_key == "linkai" and not value.rstrip("/").endswith("/v1"):
+        return f"{value.rstrip('/')}/v1"
+    return value
+
+
+def _log_provider_once(detail: str):
+    global _embedding_logged
+    if not _embedding_logged:
+        logger.info(f"[EmbeddingFactory] Embedding model in use: {detail}")
+        _embedding_logged = True
diff --git a/agent/memory/embedding/provider.py b/agent/memory/embedding/provider.py
new file mode 100644
index 0000000..6fcaf13
--- /dev/null
+++ b/agent/memory/embedding/provider.py
@@ -0,0 +1,515 @@
+"""
+Embedding providers for memory
+
+Supports multiple OpenAI-compatible embedding vendors:
+  - openai     (text-embedding-3-small / large)
+  - linkai     (OpenAI-compatible passthrough)
+  - dashscope  (Aliyun Tongyi text-embedding-v4)
+  - doubao     (ByteDance Doubao Seed1.5 / large-text on Volcengine Ark)
+  - zhipu      (ZhipuAI embedding-3)
+  - custom     (any OpenAI-compatible endpoint)
+
+Vendor keys here intentionally match the project's bot_type constants in
+common.const (OPENAI, LINKAI, QWEN_DASHSCOPE, DOUBAO, ZHIPU_AI).
+
+Custom providers (bot_type "custom" or "custom:<id>") reuse the same
+OpenAI-compatible REST client with user-supplied api_key / api_base.
+
+All providers share a single OpenAI-compatible REST client. Vendor-specific
+behaviors (truncation, query instruction prefix) are configured via metadata.
+"""
+
+import hashlib
+import math
+from abc import ABC, abstractmethod
+from typing import List, Optional
+
+# HTTP read timeout for a single embeddings request (seconds). A batch of
+# 64+ chunks can take 30-50s end-to-end from China-side networks, so 30s is
+# routinely too tight; 90s gives meaningful headroom without letting bad
+# endpoints hang forever.
+EMBEDDING_HTTP_TIMEOUT = 90
+
+
+class EmbeddingProvider(ABC):
+    """Base class for embedding providers"""
+
+    @abstractmethod
+    def embed(self, text: str) -> List[float]:
+        """Generate embedding for a single text (treated as a query by default)"""
+        pass
+
+    @abstractmethod
+    def embed_batch(self, texts: List[str]) -> List[List[float]]:
+        """Generate embeddings for multiple texts (treated as documents)"""
+        pass
+
+    def embed_query(self, text: str) -> List[float]:
+        """Generate embedding for a query string (may apply vendor instruction prefix)"""
+        return self.embed(text)
+
+    @property
+    @abstractmethod
+    def dimensions(self) -> int:
+        """Effective embedding dimensions"""
+        pass
+
+
+# ---------------------------------------------------------------------------
+# Vendor metadata table
+# ---------------------------------------------------------------------------
+#
+# Each entry describes how to reach a vendor's embedding endpoint. Most
+# vendors expose an OpenAI-compatible /embeddings API; the few that don't
+# (currently: doubao) set `provider_class` to pick a dedicated adapter.
+# Fields:
+#   provider_class          : optional adapter key ("doubao"); defaults to OpenAI-compat
+#   default_base_url        : default API base when not overridden by user
+#   default_model           : default embedding model name
+#   default_dimensions      : recommended unified dim when explicit path is enabled
+#   supports_dim_param      : whether the API accepts a `dimensions` request param
+#   needs_client_truncate   : whether to slice + L2-normalize on the client side
+#   needs_client_normalize  : whether to L2-normalize on the client (always safe)
+#   query_instruction       : optional prefix for asymmetric retrieval (Doubao Seed)
+#   max_batch_size          : max texts per /embeddings request; embed_batch
+#                             auto-paginates above this. Conservative defaults.
+#
+EMBEDDING_VENDORS = {
+    "openai": {
+        "default_base_url": "https://api.openai.com/v1",
+        "default_model": "text-embedding-3-small",
+        # Match the legacy default so users adding `embedding_provider: openai`
+        # to an existing index don't need to rebuild. Override via
+        # embedding_dimensions if you want 1024 / 1536 / 3072.
+        "default_dimensions": 1536,
+        "supports_dim_param": True,
+        "needs_client_truncate": False,
+        "needs_client_normalize": False,
+        "query_instruction": "",
+        # OpenAI permits up to 2048 items per request, but a single call
+        # carrying hundreds of long chunks routinely exceeds the 30s read
+        # timeout from China-side networks. 64 keeps each call well under
+        # both the token-per-request budget and a reasonable wall clock.
+        "max_batch_size": 64,
+    },
+    "linkai": {
+        "default_base_url": "https://api.link-ai.tech/v1",
+        "default_model": "text-embedding-3-small",
+        "default_dimensions": 1536,
+        "supports_dim_param": True,
+        "needs_client_truncate": False,
+        "needs_client_normalize": False,
+        "query_instruction": "",
+        "max_batch_size": 64,
+    },
+    "dashscope": {
+        "default_base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
+        "default_model": "text-embedding-v4",
+        "default_dimensions": 1024,
+        "supports_dim_param": True,
+        "needs_client_truncate": False,
+        "needs_client_normalize": False,
+        "query_instruction": "",
+        "max_batch_size": 10,  # DashScope hard cap (text-embedding-v4)
+    },
+    "doubao": {
+        # Doubao no longer offers an OpenAI-compatible /v1/embeddings endpoint.
+        # Current models are unified under /api/v3/embeddings/multimodal
+        # which uses a structured `input` payload — see DoubaoEmbeddingProvider.
+        "provider_class": "doubao",
+        "default_base_url": "https://ark.cn-beijing.volces.com/api/v3",
+        "default_model": "doubao-embedding-vision-251215",
+        # Native options: 1024 or 2048. We default to 1024 to align with the
+        # other Chinese vendors (dashscope/zhipu) and keep storage footprint
+        # consistent across providers; users can still override via
+        # `embedding_dimensions: 2048` in config.
+        "default_dimensions": 1024,
+        "supports_dim_param": True,
+        "needs_client_truncate": False,
+        "needs_client_normalize": False,
+        "query_instruction": "",
+        # Multimodal endpoint produces ONE embedding per call (input list is
+        # a single document's parts, not a batch). embed_batch loops.
+        "max_batch_size": 1,
+    },
+    "zhipu": {
+        "default_base_url": "https://open.bigmodel.cn/api/paas/v4",
+        "default_model": "embedding-3",
+        "default_dimensions": 1024,
+        "supports_dim_param": True,
+        "needs_client_truncate": False,
+        "needs_client_normalize": False,
+        "query_instruction": "",
+        "max_batch_size": 64,
+    },
+    # Custom provider — any OpenAI-compatible /embeddings endpoint. The
+    # user must supply api_key + api_base + model via the web console
+    # (stored in custom_providers list or legacy custom_api_key / custom_api_base).
+    # Dimensions defaults to 1024 but can be overridden via config's
+    # embedding_dimensions. No dim-param support assumption — safest
+    # default for unknown endpoints.
+    "custom": {
+        "default_base_url": "",
+        "default_model": "",
+        "default_dimensions": 1024,
+        "supports_dim_param": False,
+        "needs_client_truncate": False,
+        "needs_client_normalize": True,
+        "query_instruction": "",
+        "max_batch_size": 64,
+    },
+}
+
+
+def _l2_normalize(vec: List[float]) -> List[float]:
+    """Normalize a vector to unit length (L2 norm). Returns input on zero vector."""
+    norm = math.sqrt(sum(v * v for v in vec))
+    if norm == 0:
+        return vec
+    return [v / norm for v in vec]
+
+
+class OpenAIEmbeddingProvider(EmbeddingProvider):
+    """
+    OpenAI-compatible embedding provider.
+
+    Used for openai/linkai/dashscope/ark/zhipu by configuring the metadata
+    fields. The legacy two-arg constructor (model, api_key, api_base) keeps
+    working, so the original OpenAI/LinkAI fallback code path is unchanged.
+    """
+
+    def __init__(
+        self,
+        model: str = "text-embedding-3-small",
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        extra_headers: Optional[dict] = None,
+        dimensions: Optional[int] = None,
+        supports_dim_param: bool = True,
+        needs_client_truncate: bool = False,
+        needs_client_normalize: bool = False,
+        query_instruction: str = "",
+        max_batch_size: int = 256,
+    ):
+        """
+        Args:
+            model: Model name (e.g. text-embedding-3-small, text-embedding-v4, embedding-3)
+            api_key: API key (required)
+            api_base: API base URL (defaults to OpenAI)
+            extra_headers: Optional extra HTTP headers
+            dimensions: Target output dimension. Required when supports_dim_param
+                is False and needs_client_truncate is True (used to slice).
+            supports_dim_param: Whether the vendor accepts a `dimensions` body param
+            needs_client_truncate: Slice the returned vector to `dimensions`
+            needs_client_normalize: L2-normalize on the client after slicing
+            query_instruction: Optional prefix prepended to query texts only
+            max_batch_size: Max items per /embeddings request; embed_batch
+                auto-paginates above this.
+        """
+        self.model = model
+        self.api_key = api_key
+        self.api_base = api_base or "https://api.openai.com/v1"
+        self.extra_headers = extra_headers or {}
+        self.supports_dim_param = supports_dim_param
+        self.needs_client_truncate = needs_client_truncate
+        self.needs_client_normalize = needs_client_normalize
+        self.query_instruction = query_instruction or ""
+        self.max_batch_size = max(1, int(max_batch_size or 1))
+
+        if not self.api_key or self.api_key in ["", "YOUR API KEY", "YOUR_API_KEY"]:
+            raise ValueError("Embedding API key is not configured")
+
+        if dimensions is not None and dimensions > 0:
+            self._dimensions = dimensions
+        else:
+            # Legacy heuristic for OpenAI text-embedding-3-* family
+            self._dimensions = 1536 if "small" in model else 3072
+
+    def _call_api(self, input_data):
+        """Call OpenAI-compatible /embeddings endpoint"""
+        import requests
+
+        url = f"{self.api_base}/embeddings"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+            **self.extra_headers,
+        }
+        data = {
+            "input": input_data,
+            "model": self.model,
+        }
+        if self.supports_dim_param and self._dimensions:
+            data["dimensions"] = self._dimensions
+
+        try:
+            response = requests.post(url, headers=headers, json=data, timeout=EMBEDDING_HTTP_TIMEOUT)
+            response.raise_for_status()
+            return response.json()
+        except requests.exceptions.ConnectionError as e:
+            raise ConnectionError(
+                f"Failed to connect to embedding API at {url}. "
+                f"Please check network and api_base. Error: {str(e)}"
+            )
+        except requests.exceptions.Timeout as e:
+            raise TimeoutError(f"Embedding API request timed out. Error: {str(e)}")
+        except requests.exceptions.HTTPError as e:
+            if e.response.status_code == 401:
+                raise ValueError("Invalid embedding API key")
+            elif e.response.status_code == 429:
+                raise ValueError("Embedding API rate limit exceeded")
+            else:
+                raise ValueError(
+                    f"Embedding API request failed: "
+                    f"{e.response.status_code} - {e.response.text}"
+                )
+
+    def _post_process(self, raw: List[float]) -> List[float]:
+        """Apply optional client-side truncation + normalization"""
+        vec = raw
+        if self.needs_client_truncate and self._dimensions and len(vec) > self._dimensions:
+            vec = vec[: self._dimensions]
+        if self.needs_client_normalize:
+            vec = _l2_normalize(vec)
+        return vec
+
+    def embed(self, text: str) -> List[float]:
+        """Generate embedding (treated as document by default)"""
+        result = self._call_api(text)
+        return self._post_process(result["data"][0]["embedding"])
+
+    def embed_query(self, text: str) -> List[float]:
+        """Generate embedding for a query (applies vendor instruction prefix if any)"""
+        if self.query_instruction:
+            text = f"{self.query_instruction}{text}"
+        return self.embed(text)
+
+    def embed_batch(self, texts: List[str]) -> List[List[float]]:
+        """Generate embeddings for multiple documents.
+
+        Automatically paginates by self.max_batch_size so callers can pass any
+        number of texts. Order of returned vectors matches the input order.
+        """
+        if not texts:
+            return []
+        out: List[List[float]] = []
+        step = self.max_batch_size
+        for i in range(0, len(texts), step):
+            chunk = texts[i:i + step]
+            result = self._call_api(chunk)
+            out.extend(self._post_process(item["embedding"]) for item in result["data"])
+        return out
+
+    @property
+    def dimensions(self) -> int:
+        return self._dimensions
+
+
+class DoubaoEmbeddingProvider(EmbeddingProvider):
+    """
+    Doubao (Volcengine Ark) multimodal embedding provider.
+
+    Doubao deprecated their OpenAI-compatible /v1/embeddings endpoint and
+    unified everything under /api/v3/embeddings/multimodal, which uses a
+    structured `input: [{type, text|image_url|video_url}, ...]` payload.
+
+    Notes:
+      * The endpoint produces ONE embedding per call (input list is multiple
+        modality parts of a single document, not a batch). embed_batch
+        therefore loops per-text — no native batch support.
+      * Native dimensions: 1024 or 2048 (default 1024 to align with other
+        Chinese vendors). No client-side truncation needed.
+      * Auth: Bearer ARK API key.
+    """
+
+    def __init__(
+        self,
+        model: str,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        extra_headers: Optional[dict] = None,
+        dimensions: Optional[int] = None,
+    ):
+        self.model = model
+        self.api_key = api_key
+        self.api_base = api_base or "https://ark.cn-beijing.volces.com/api/v3"
+        self.extra_headers = extra_headers or {}
+        if not self.api_key or self.api_key in ["", "YOUR API KEY", "YOUR_API_KEY"]:
+            raise ValueError("Doubao embedding API key (ark_api_key) is not configured")
+
+        if dimensions in (1024, 2048):
+            self._dimensions = dimensions
+        elif dimensions is None:
+            self._dimensions = 1024
+        else:
+            raise ValueError(
+                f"Doubao embedding dimensions must be 1024 or 2048, got {dimensions}"
+            )
+
+    def _call_api(self, text: str) -> List[float]:
+        """One call → one embedding. multimodal endpoint takes a single
+        document represented as a list of typed parts; we send a single
+        text part."""
+        import requests
+
+        url = f"{self.api_base}/embeddings/multimodal"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+            **self.extra_headers,
+        }
+        payload = {
+            "model": self.model,
+            "input": [{"type": "text", "text": text}],
+            "dimensions": self._dimensions,
+            "encoding_format": "float",
+        }
+
+        try:
+            response = requests.post(url, headers=headers, json=payload, timeout=EMBEDDING_HTTP_TIMEOUT)
+            response.raise_for_status()
+            body = response.json()
+        except requests.exceptions.ConnectionError as e:
+            raise ConnectionError(
+                f"Failed to connect to Doubao embedding API at {url}. "
+                f"Please check network and api_base. Error: {str(e)}"
+            )
+        except requests.exceptions.Timeout as e:
+            raise TimeoutError(f"Doubao embedding API request timed out. Error: {str(e)}")
+        except requests.exceptions.HTTPError as e:
+            if e.response.status_code == 401:
+                raise ValueError("Invalid Doubao (ark) embedding API key")
+            elif e.response.status_code == 429:
+                raise ValueError("Doubao embedding API rate limit exceeded")
+            else:
+                raise ValueError(
+                    f"Doubao embedding API request failed: "
+                    f"{e.response.status_code} - {e.response.text}"
+                )
+
+        # Response shape per docs: {"data": {"embedding": [...]}}
+        data = body.get("data")
+        if isinstance(data, dict) and "embedding" in data:
+            return data["embedding"]
+        # Some providers wrap as a list of one — be defensive
+        if isinstance(data, list) and data and "embedding" in data[0]:
+            return data[0]["embedding"]
+        raise ValueError(f"Unexpected Doubao embedding response shape: {body}")
+
+    def embed(self, text: str) -> List[float]:
+        return self._call_api(text)
+
+    def embed_batch(self, texts: List[str]) -> List[List[float]]:
+        # Endpoint produces one embedding per call; loop. Order preserved.
+        return [self._call_api(t) for t in texts]
+
+    @property
+    def dimensions(self) -> int:
+        return self._dimensions
+
+
+class EmbeddingCache:
+    """In-memory cache for embeddings to avoid recomputation"""
+
+    def __init__(self):
+        self.cache = {}
+
+    def get(self, text: str, provider: str, model: str) -> Optional[List[float]]:
+        key = self._compute_key(text, provider, model)
+        return self.cache.get(key)
+
+    def put(self, text: str, provider: str, model: str, embedding: List[float]):
+        key = self._compute_key(text, provider, model)
+        self.cache[key] = embedding
+
+    @staticmethod
+    def _compute_key(text: str, provider: str, model: str) -> str:
+        content = f"{provider}:{model}:{text}"
+        return hashlib.md5(content.encode("utf-8")).hexdigest()
+
+    def clear(self):
+        self.cache.clear()
+
+
+def create_embedding_provider(
+    provider: str = "openai",
+    model: Optional[str] = None,
+    api_key: Optional[str] = None,
+    api_base: Optional[str] = None,
+    extra_headers: Optional[dict] = None,
+    dimensions: Optional[int] = None,
+) -> EmbeddingProvider:
+    """
+    Factory function to create an embedding provider.
+
+    Backward compatible: when called with provider in {"openai", "linkai"}
+    and no `dimensions` arg, behaves exactly as before (1536-dim OpenAI).
+
+    New providers ("dashscope", "doubao", "zhipu") require explicit configuration
+    and use the unified 1024-dim defaults from EMBEDDING_VENDORS.
+
+    Args:
+        provider: Vendor key (one of EMBEDDING_VENDORS)
+        model: Model name (uses vendor default if None)
+        api_key: API key (required)
+        api_base: API base URL (uses vendor default if None)
+        extra_headers: Optional extra HTTP headers
+        dimensions: Target output dimension (uses vendor default if None)
+
+    Returns:
+        EmbeddingProvider instance
+    """
+    meta = EMBEDDING_VENDORS.get(provider)
+    if meta is None:
+        raise ValueError(
+            f"Unsupported embedding provider: {provider}. "
+            f"Supported: {sorted(EMBEDDING_VENDORS.keys())}"
+        )
+
+    # Doubao uses a non-OpenAI-compatible multimodal endpoint.
+    if meta.get("provider_class") == "doubao":
+        final_dim = dimensions if (dimensions and dimensions > 0) else meta["default_dimensions"]
+        return DoubaoEmbeddingProvider(
+            model=model or meta["default_model"],
+            api_key=api_key,
+            api_base=api_base or meta["default_base_url"],
+            extra_headers=extra_headers,
+            dimensions=final_dim,
+        )
+
+    # Legacy two-arg call for openai/linkai keeps 1536-dim default behavior
+    # so existing data isn't invalidated.
+    is_legacy_call = (
+        provider in ("openai", "linkai")
+        and dimensions is None
+    )
+    if is_legacy_call:
+        return OpenAIEmbeddingProvider(
+            model=model or "text-embedding-3-small",
+            api_key=api_key,
+            api_base=api_base,
+            extra_headers=extra_headers,
+        )
+
+    final_dim = dimensions if (dimensions and dimensions > 0) else meta["default_dimensions"]
+    resolved_model = model or meta["default_model"]
+    resolved_base = api_base or meta["default_base_url"]
+    # Custom providers require explicit api_base and model — they cannot
+    # fall back to OpenAI defaults like built-in vendors do.
+    if provider == "custom":
+        if not resolved_base:
+            raise ValueError("Custom embedding provider requires an api_base URL")
+        if not resolved_model:
+            raise ValueError("Custom embedding provider requires a model name")
+    return OpenAIEmbeddingProvider(
+        model=resolved_model,
+        api_key=api_key,
+        api_base=resolved_base,
+        extra_headers=extra_headers,
+        dimensions=final_dim,
+        supports_dim_param=meta["supports_dim_param"],
+        needs_client_truncate=meta["needs_client_truncate"],
+        needs_client_normalize=meta["needs_client_normalize"],
+        query_instruction=meta["query_instruction"],
+        max_batch_size=meta.get("max_batch_size", 256),
+    )
diff --git a/agent/memory/embedding/rebuild.py b/agent/memory/embedding/rebuild.py
new file mode 100644
index 0000000..96d9878
--- /dev/null
+++ b/agent/memory/embedding/rebuild.py
@@ -0,0 +1,190 @@
+"""
+Rebuild memory vector index.
+
+Recommended entry point (in-chat, while agent is running):
+    /memory rebuild-index
+
+Backward-compatible CLI entry (must run from project root):
+    python -m agent.memory.rebuild_index
+
+What it does:
+  1. Probes the embedding endpoint with a tiny call to fail fast on
+     bad provider/model/key — before touching the index.
+  2. Clears the SQLite chunks/files tables (workspace markdown stays intact).
+  3. Runs a fresh sync, regenerating embeddings with the currently configured
+     provider/model/dimensions.
+
+This is the only safe way to switch embedding_provider after the existing
+index has been populated by a different-dim model.
+"""
+
+from __future__ import annotations
+import asyncio
+import sys
+from dataclasses import dataclass
+from typing import Optional
+
+from common.log import logger
+from common.utils import expand_path
+
+
+@dataclass
+class RebuildResult:
+    """Outcome of a rebuild_in_process() call"""
+    ok: bool
+    removed: int = 0
+    chunks: int = 0
+    files: int = 0
+    error: Optional[str] = None
+
+
+def clear_index(db_path, storage=None) -> int:
+    """Wipe chunks/files, reset FTS5, and clean up any legacy state file.
+
+    Args:
+        db_path: Path of the index DB (also used to locate the legacy state
+            file for migration cleanup, and — when *storage* is None — to
+            open a fresh connection).
+        storage: Optional pre-opened MemoryStorage. When provided we reuse it
+            so the live connection's triggers stay in sync — opening a second
+            connection would leave the original one's triggers pointing at a
+            DROP'd chunks_fts table.
+
+    We reset (DROP+recreate) chunks_fts because its shadow tables can become
+    inconsistent across rebuild cycles, causing bm25() / ORDER BY rank to
+    raise "database disk image is malformed" even when raw MATCH still works.
+
+    Returns number of chunks removed.
+    """
+    from agent.memory.embedding.state import cleanup_legacy_state_file
+    from agent.memory.storage import MemoryStorage
+
+    owns_storage = storage is None
+    if owns_storage:
+        storage = MemoryStorage(db_path)
+    try:
+        before = storage.conn.execute("SELECT COUNT(*) FROM chunks").fetchone()[0]
+        storage.conn.execute("DELETE FROM chunks")
+        storage.conn.execute("DELETE FROM files")
+        storage.conn.commit()
+        storage.reset_fts5()
+    finally:
+        if owns_storage:
+            storage.close()
+
+    cleanup_legacy_state_file(db_path)
+    return int(before)
+
+
+def rebuild_in_process(memory_manager) -> RebuildResult:
+    """
+    Rebuild the index using an existing, fully-initialized MemoryManager.
+
+    Used by the in-chat /memory rebuild-index command. The caller already has
+    config loaded, embedding_provider built, and (optionally) the agent
+    running, so we only need to:
+      1. Clear chunks/files + state on the manager's storage.
+      2. Re-sync (force=True).
+
+    NOTE: caller must ensure memory_manager.embedding_provider is set, otherwise
+    sync() will silently skip embedding generation.
+    """
+    if memory_manager is None:
+        return RebuildResult(ok=False, error="memory_manager is None")
+    if memory_manager.embedding_provider is None:
+        return RebuildResult(ok=False, error="embedding_provider is not initialized")
+
+    # Probe the embedding endpoint BEFORE clearing the index. A bad
+    # provider/model/key would otherwise leave the user with an empty index
+    # that not even keyword search can serve.
+    try:
+        memory_manager.embedding_provider.embed_query("ping")
+    except Exception as e:
+        logger.error(f"[RebuildIndex] embedding probe failed, aborting rebuild: {e}")
+        return RebuildResult(ok=False, error=f"embedding endpoint not reachable: {e}")
+
+    db_path = memory_manager.config.get_db_path()
+    try:
+        removed = clear_index(db_path, storage=memory_manager.storage)
+    except Exception as e:
+        logger.exception("[RebuildIndex] clear_index failed")
+        return RebuildResult(ok=False, error=f"clear failed: {e}")
+
+    try:
+        asyncio.run(memory_manager.sync(force=True))
+    except RuntimeError:
+        # Already inside a running event loop (rare in chat handler thread).
+        loop = asyncio.new_event_loop()
+        try:
+            loop.run_until_complete(memory_manager.sync(force=True))
+        finally:
+            loop.close()
+    except Exception as e:
+        logger.exception("[RebuildIndex] sync failed")
+        return RebuildResult(ok=False, removed=removed, error=f"re-embed failed: {e}")
+
+    stats = memory_manager.storage.get_stats()
+    chunks = int(stats.get("chunks", 0))
+    embedded = int(stats.get("embedded", 0))
+
+    # sync() degrades to "no embeddings" on batch failure so keyword search
+    # still works at startup — but in a /rebuild-index request the user
+    # explicitly asked for vectors. Surface that as a failure.
+    if chunks > 0 and embedded == 0:
+        return RebuildResult(
+            ok=False,
+            removed=removed,
+            chunks=chunks,
+            files=int(stats.get("files", 0)),
+            error=(
+                "embedding API failed during sync; index now has chunks but no "
+                "vectors. Check embedding provider/model/key and retry."
+            ),
+        )
+
+    return RebuildResult(
+        ok=True,
+        removed=removed,
+        chunks=chunks,
+        files=int(stats.get("files", 0)),
+    )
+
+
+def main() -> int:
+    """Standalone CLI entry. Must be run from project root (relative config path)."""
+    from config import conf, load_config
+    from agent.memory import MemoryConfig, MemoryManager
+
+    load_config()
+
+    workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    memory_config = MemoryConfig(workspace_root=workspace_root)
+
+    logger.info(f"[RebuildIndex] Workspace: {workspace_root}")
+    logger.info(f"[RebuildIndex] Index db:  {memory_config.get_db_path()}")
+
+    from agent.memory.embedding import create_default_embedding_provider
+
+    embedding_provider = create_default_embedding_provider()
+    if embedding_provider is None:
+        logger.error(
+            "[RebuildIndex] No embedding provider could be initialized. "
+            "Check your config.json. Aborting rebuild."
+        )
+        return 1
+
+    manager = MemoryManager(memory_config, embedding_provider=embedding_provider)
+    result = rebuild_in_process(manager)
+    if not result.ok:
+        logger.error(f"[RebuildIndex] {result.error}")
+        return 1
+
+    logger.info(
+        f"[RebuildIndex] Done. removed={result.removed}, "
+        f"chunks={result.chunks}, files={result.files}"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/agent/memory/embedding/state.py b/agent/memory/embedding/state.py
new file mode 100644
index 0000000..5efffef
--- /dev/null
+++ b/agent/memory/embedding/state.py
@@ -0,0 +1,51 @@
+"""
+Embedding-related index utilities.
+
+We don't keep a sidecar state file — the SQLite index is the source of truth
+and config.json is the source of intent. The two functions below are the
+only things needing on-disk awareness:
+
+  detect_index_dim         : read the dim of stored vectors (display-only)
+  cleanup_legacy_state_file: remove old embedding_state.json from earlier
+                             versions; safe no-op when absent.
+"""
+
+from __future__ import annotations
+import json
+import os
+from pathlib import Path
+from typing import Optional, Union
+
+PathLike = Union[str, os.PathLike]
+
+
+def detect_index_dim(storage) -> Optional[int]:
+    """Return the dim of the first stored embedding, or None if the index
+    has no embeddings. Used by /memory status."""
+    try:
+        row = storage.conn.execute(
+            "SELECT embedding FROM chunks WHERE embedding IS NOT NULL LIMIT 1"
+        ).fetchone()
+    except Exception:
+        return None
+    if not row or not row["embedding"]:
+        return None
+    try:
+        raw = row["embedding"]
+        if isinstance(raw, (bytes, bytearray)):
+            # New BLOB format: 4 bytes per float32
+            return len(raw) // 4
+        emb = json.loads(raw)
+        return len(emb) if isinstance(emb, list) else None
+    except (json.JSONDecodeError, TypeError, Exception):
+        return None
+
+
+def cleanup_legacy_state_file(db_path: PathLike) -> None:
+    """Remove old embedding_state.json files from earlier versions.
+    Safe to call repeatedly; no-op if the file is absent."""
+    legacy = Path(db_path).parent / "embedding_state.json"
+    try:
+        legacy.unlink(missing_ok=True)
+    except Exception:
+        pass
diff --git a/agent/memory/manager.py b/agent/memory/manager.py
new file mode 100644
index 0000000..5ec2ade
--- /dev/null
+++ b/agent/memory/manager.py
@@ -0,0 +1,555 @@
+"""
+Memory manager for AgentMesh
+
+Provides high-level interface for memory operations
+"""
+
+import os
+from typing import List, Optional, Dict, Any
+from pathlib import Path
+import hashlib
+from datetime import datetime, timedelta
+
+from agent.memory.config import MemoryConfig, get_default_memory_config
+from agent.memory.storage import MemoryStorage, MemoryChunk, SearchResult
+from agent.memory.chunker import TextChunker
+from agent.memory.embedding import EmbeddingProvider, EmbeddingCache
+from agent.memory.summarizer import MemoryFlushManager, create_memory_files_if_needed
+
+
+class MemoryManager:
+    """
+    Memory manager with hybrid search capabilities
+    
+    Provides long-term memory for agents with vector and keyword search
+    """
+    
+    def __init__(
+        self,
+        config: Optional[MemoryConfig] = None,
+        embedding_provider: Optional[EmbeddingProvider] = None,
+        llm_model: Optional[Any] = None
+    ):
+        """
+        Initialize memory manager
+        
+        Args:
+            config: Memory configuration (uses global config if not provided)
+            embedding_provider: Custom embedding provider (optional)
+            llm_model: LLM model for summarization (optional)
+        """
+        self.config = config or get_default_memory_config()
+        
+        # Initialize storage
+        db_path = self.config.get_db_path()
+        self.storage = MemoryStorage(db_path)
+        
+        # Initialize chunker
+        self.chunker = TextChunker(
+            max_tokens=self.config.chunk_max_tokens,
+            overlap_tokens=self.config.chunk_overlap_tokens
+        )
+        
+        # Embedding provider is owned by the caller (agent_initializer is the
+        # canonical entry point and handles legacy/explicit + state validation).
+        # When None is passed, memory degrades to keyword-only search instead
+        # of silently re-initializing a vendor here, which would bypass the
+        # caller's state checks and risk corrupting the index.
+        self.embedding_provider = embedding_provider
+        if self.embedding_provider is None:
+            from common.log import logger
+            logger.info(
+                "[MemoryManager] No embedding provider; memory will use keyword search only"
+            )
+
+        # Cache for query embeddings (avoids redundant API calls within a session)
+        self._embedding_cache = EmbeddingCache()
+
+
+        # Initialize memory flush manager
+        workspace_dir = self.config.get_workspace()
+        self.flush_manager = MemoryFlushManager(
+            workspace_dir=workspace_dir,
+            llm_model=llm_model
+        )
+        
+        # Ensure workspace directories exist
+        self._init_workspace()
+        
+        self._dirty = False
+    
+    def _init_workspace(self):
+        """Initialize workspace directories"""
+        memory_dir = self.config.get_memory_dir()
+        memory_dir.mkdir(parents=True, exist_ok=True)
+        
+        # Create default memory files
+        workspace_dir = self.config.get_workspace()
+        create_memory_files_if_needed(workspace_dir)
+    
+    async def search(
+        self,
+        query: str,
+        user_id: Optional[str] = None,
+        max_results: Optional[int] = None,
+        min_score: Optional[float] = None,
+        include_shared: bool = True
+    ) -> List[SearchResult]:
+        """
+        Search memory with hybrid search (vector + keyword)
+        
+        Args:
+            query: Search query
+            user_id: User ID for scoped search
+            max_results: Maximum results to return
+            min_score: Minimum score threshold
+            include_shared: Include shared memories
+            
+        Returns:
+            List of search results sorted by relevance
+        """
+        max_results = max_results or self.config.max_results
+        min_score = min_score or self.config.min_score
+        
+        # Determine scopes
+        scopes = []
+        if include_shared:
+            scopes.append("shared")
+        if user_id:
+            scopes.append("user")
+        
+        if not scopes:
+            return []
+        
+        # Sync if needed
+        if self.config.sync_on_search and self._dirty:
+            await self.sync()
+        
+        from common.log import logger
+
+        # Perform vector search (if embedding provider available).
+        # Failures degrade silently to keyword-only — no exception is raised.
+        vector_results = []
+        if self.embedding_provider:
+            try:
+                provider_name = type(self.embedding_provider).__name__
+                model_name = getattr(self.embedding_provider, 'model', '')
+                cached = self._embedding_cache.get(query, provider_name, model_name)
+                if cached is not None:
+                    query_embedding = cached
+                else:
+                    query_embedding = self.embedding_provider.embed_query(query)
+                    self._embedding_cache.put(query, provider_name, model_name, query_embedding)
+                vector_results = self.storage.search_vector(
+                    query_embedding=query_embedding,
+                    user_id=user_id,
+                    scopes=scopes,
+                    limit=max_results * 2  # Get more candidates for merging
+                )
+                logger.info(f"[MemoryManager] Vector search found {len(vector_results)} results for query: {query}")
+            except Exception as e:
+                logger.error(
+                    f"[MemoryManager] Vector search failed, falling back to keyword-only: {e}"
+                )
+
+        # Perform keyword search (also runs as fallback when vector failed)
+        keyword_results = self.storage.search_keyword(
+            query=query,
+            user_id=user_id,
+            scopes=scopes,
+            limit=max_results * 2
+        )
+        logger.info(f"[MemoryManager] Keyword search found {len(keyword_results)} results for query: {query}")
+
+        # Merge results
+        merged = self._merge_results(
+            vector_results,
+            keyword_results,
+            self.config.vector_weight,
+            self.config.keyword_weight
+        )
+
+        # Filter by min score and limit
+        filtered = [r for r in merged if r.score >= min_score]
+        return filtered[:max_results]
+    
+    async def add_memory(
+        self,
+        content: str,
+        user_id: Optional[str] = None,
+        scope: str = "shared",
+        source: str = "memory",
+        path: Optional[str] = None,
+        metadata: Optional[Dict[str, Any]] = None
+    ):
+        """
+        Add new memory content
+        
+        Args:
+            content: Memory content
+            user_id: User ID for user-scoped memory
+            scope: Memory scope ("shared", "user", "session")
+            source: Memory source ("memory" or "session")
+            path: File path (auto-generated if not provided)
+            metadata: Additional metadata
+        """
+        if not content.strip():
+            return
+        
+        # Generate path if not provided
+        if not path:
+            content_hash = hashlib.md5(content.encode('utf-8')).hexdigest()[:8]
+            if user_id and scope == "user":
+                path = f"memory/users/{user_id}/memory_{content_hash}.md"
+            else:
+                path = f"memory/shared/memory_{content_hash}.md"
+        
+        # Chunk content
+        chunks = self.chunker.chunk_text(content)
+        
+        # Generate embeddings (if provider available)
+        texts = [chunk.text for chunk in chunks]
+        if self.embedding_provider:
+            embeddings = self.embedding_provider.embed_batch(texts)
+        else:
+            # No embeddings, just use None
+            embeddings = [None] * len(texts)
+        
+        # Create memory chunks
+        memory_chunks = []
+        for chunk, embedding in zip(chunks, embeddings):
+            chunk_id = self._generate_chunk_id(path, chunk.start_line, chunk.end_line)
+            chunk_hash = MemoryStorage.compute_hash(chunk.text)
+            
+            memory_chunks.append(MemoryChunk(
+                id=chunk_id,
+                user_id=user_id,
+                scope=scope,
+                source=source,
+                path=path,
+                start_line=chunk.start_line,
+                end_line=chunk.end_line,
+                text=chunk.text,
+                embedding=embedding,
+                hash=chunk_hash,
+                metadata=metadata
+            ))
+        
+        # Save to storage
+        self.storage.save_chunks_batch(memory_chunks)
+        
+        # Update file metadata
+        file_hash = MemoryStorage.compute_hash(content)
+        self.storage.update_file_metadata(
+            path=path,
+            source=source,
+            file_hash=file_hash,
+            mtime=int(os.path.getmtime(__file__)),  # Use current time
+            size=len(content)
+        )
+    
+    async def sync(self, force: bool = False):
+        """
+        Synchronize memory from files.
+
+        Two-pass design to amortize embedding HTTP cost:
+          1. Walk all files, chunk those whose hash changed, collect pending
+             chunks across files. No embedding calls yet.
+          2. Run a single embed_batch over the union of pending chunks (the
+             provider auto-paginates by vendor cap), then persist per-file.
+
+        For workspaces with many small files (101 files / ~1 chunk each), this
+        cuts ~100 HTTP calls down to ~ceil(total_chunks / vendor_cap).
+
+        Args:
+            force: Force full reindex
+        """
+        memory_dir = self.config.get_memory_dir()
+        workspace_dir = self.config.get_workspace()
+
+        files_to_scan: List[tuple] = []  # (file_path, source, scope, user_id)
+
+        memory_file = Path(workspace_dir) / "MEMORY.md"
+        if memory_file.exists():
+            files_to_scan.append((memory_file, "memory", "shared", None))
+
+        if memory_dir.exists():
+            for file_path in memory_dir.rglob("*.md"):
+                rel_parts = file_path.relative_to(workspace_dir).parts
+                if any(part.startswith('.') for part in rel_parts):
+                    continue
+                # Dream diaries are narrative reflections produced by Deep
+                # Dream; their factual content has already been distilled
+                # into MEMORY.md. Indexing them adds noisy near-duplicates
+                # that crowd out the authoritative entry in retrieval.
+                if "dreams" in rel_parts:
+                    continue
+                if "daily" in rel_parts:
+                    if "users" in rel_parts or len(rel_parts) > 3:
+                        user_idx = rel_parts.index("daily") + 1
+                        user_id = rel_parts[user_idx] if user_idx < len(rel_parts) else None
+                        scope = "user"
+                    else:
+                        user_id = None
+                        scope = "shared"
+                elif "users" in rel_parts:
+                    user_idx = rel_parts.index("users") + 1
+                    user_id = rel_parts[user_idx] if user_idx < len(rel_parts) else None
+                    scope = "user"
+                else:
+                    user_id = None
+                    scope = "shared"
+                files_to_scan.append((file_path, "memory", scope, user_id))
+
+        from config import conf
+        if conf().get("knowledge", True):
+            knowledge_dir = Path(workspace_dir) / "knowledge"
+            if knowledge_dir.exists():
+                for file_path in knowledge_dir.rglob("*.md"):
+                    files_to_scan.append((file_path, "knowledge", "shared", None))
+
+        # Pass 1: inline chunking + change detection. Inlined (instead of
+        # calling self._prepare_file_for_sync) so this method does not depend
+        # on any sibling helpers — keeps it robust against partial reloads
+        # where the class object is older than the method's source.
+        pending: List[Dict[str, Any]] = []
+        workspace_dir_path = self.config.get_workspace()
+        for file_path, source, scope, user_id in files_to_scan:
+            try:
+                content = file_path.read_text(encoding='utf-8')
+            except Exception:
+                continue
+            file_hash = MemoryStorage.compute_hash(content)
+            rel_path = str(file_path.relative_to(workspace_dir_path))
+            if self.storage.get_file_hash(rel_path) == file_hash:
+                continue
+            chunks = self.chunker.chunk_text(content)
+            if not chunks:
+                continue
+            pending.append({
+                "file_path": file_path,
+                "rel_path": rel_path,
+                "source": source,
+                "scope": scope,
+                "user_id": user_id,
+                "file_hash": file_hash,
+                "chunks": chunks,
+                "texts": [c.text for c in chunks],
+            })
+
+        if not pending:
+            self._dirty = False
+            return
+
+        # Pass 2: single batched embed across all pending chunks.
+        # CRITICAL: never touch the index until we hold valid embeddings.
+        # If embed_batch fails, leave the existing index intact (chunks +
+        # file_hash) so the next sync will retry the same files. Writing
+        # NULL embeddings + updating file_hash here would mark the file as
+        # "successfully synced" and silently strand it without vectors.
+        all_texts: List[str] = []
+        for entry in pending:
+            all_texts.extend(entry["texts"])
+
+        if not self.embedding_provider:
+            # No provider configured at all (legacy keyword-only). Persist
+            # chunks without embeddings — this is the user's intent.
+            all_embeddings: List[Optional[List[float]]] = [None] * len(all_texts)
+        else:
+            try:
+                all_embeddings = self.embedding_provider.embed_batch(all_texts)
+            except Exception as e:
+                from common.log import logger
+                logger.error(
+                    f"[MemoryManager] Batch embedding failed for {len(all_texts)} "
+                    f"chunks across {len(pending)} files: {e}. "
+                    f"Index left untouched; will retry on next sync."
+                )
+                # Bail before touching storage. self._dirty stays True so
+                # callers know there is pending work.
+                return
+
+        # Pass 3: inline persist — same self-contained reasoning as Pass 1.
+        cursor = 0
+        for entry in pending:
+            n = len(entry["texts"])
+            entry_embeddings = all_embeddings[cursor:cursor + n]
+            cursor += n
+
+            rel_path = entry["rel_path"]
+            self.storage.delete_by_path(rel_path)
+            memory_chunks = []
+            for chunk, embedding in zip(entry["chunks"], entry_embeddings):
+                chunk_id = self._generate_chunk_id(rel_path, chunk.start_line, chunk.end_line)
+                chunk_hash = MemoryStorage.compute_hash(chunk.text)
+                memory_chunks.append(MemoryChunk(
+                    id=chunk_id,
+                    user_id=entry["user_id"],
+                    scope=entry["scope"],
+                    source=entry["source"],
+                    path=rel_path,
+                    start_line=chunk.start_line,
+                    end_line=chunk.end_line,
+                    text=chunk.text,
+                    embedding=embedding,
+                    hash=chunk_hash,
+                    metadata=None,
+                ))
+            self.storage.save_chunks_batch(memory_chunks)
+            stat = entry["file_path"].stat()
+            self.storage.update_file_metadata(
+                path=rel_path,
+                source=entry["source"],
+                file_hash=entry["file_hash"],
+                mtime=int(stat.st_mtime),
+                size=stat.st_size,
+            )
+
+        self._dirty = False
+
+    def flush_memory(
+        self,
+        messages: list,
+        user_id: Optional[str] = None,
+        reason: str = "threshold",
+        max_messages: int = 10,
+        context_summary_callback=None,
+    ) -> bool:
+        """
+        Flush conversation summary to daily memory file.
+
+        Args:
+            messages: Conversation message list
+            user_id: Optional user ID
+            reason: "threshold" | "overflow" | "daily_summary"
+            max_messages: Max recent messages to include (0 = all)
+            context_summary_callback: Optional callback(str) invoked with the
+                daily summary text for in-context injection
+
+        Returns:
+            True if flush was dispatched
+        """
+        success = self.flush_manager.flush_from_messages(
+            messages=messages,
+            user_id=user_id,
+            reason=reason,
+            max_messages=max_messages,
+            context_summary_callback=context_summary_callback,
+        )
+        if success:
+            self._dirty = True
+        return success
+    
+    def get_status(self) -> Dict[str, Any]:
+        """Get memory status"""
+        stats = self.storage.get_stats()
+        return {
+            'chunks': stats['chunks'],
+            'files': stats['files'],
+            'workspace': str(self.config.get_workspace()),
+            'dirty': self._dirty,
+            'embedding_enabled': self.embedding_provider is not None,
+            'embedding_provider': self.config.embedding_provider if self.embedding_provider else 'disabled',
+            'embedding_model': self.config.embedding_model if self.embedding_provider else 'N/A',
+            'search_mode': 'hybrid (vector + keyword)' if self.embedding_provider else 'keyword only (FTS5)'
+        }
+    
+    def mark_dirty(self):
+        """Mark memory as dirty (needs sync)"""
+        self._dirty = True
+    
+    def close(self):
+        """Close memory manager and release resources"""
+        self.storage.close()
+    
+    # Helper methods
+    
+    def _generate_chunk_id(self, path: str, start_line: int, end_line: int) -> str:
+        """Generate unique chunk ID"""
+        content = f"{path}:{start_line}:{end_line}"
+        return hashlib.md5(content.encode('utf-8')).hexdigest()
+    
+    @staticmethod
+    def _compute_temporal_decay(path: str, half_life_days: float = 30.0) -> float:
+        """
+        Compute temporal decay multiplier for dated memory files.
+        
+        Inspired by OpenClaw's temporal-decay: exponential decay based on file date.
+        MEMORY.md and non-dated files are "evergreen" (no decay, multiplier=1.0).
+        Daily files like memory/2025-03-01.md decay based on age.
+        
+        Formula: multiplier = exp(-ln2/half_life * age_in_days)
+        """
+        import re
+        import math
+        
+        match = re.search(r'(\d{4})-(\d{2})-(\d{2})\.md$', path)
+        if not match:
+            return 1.0  # evergreen: MEMORY.md, non-dated files
+        
+        try:
+            file_date = datetime(
+                int(match.group(1)), int(match.group(2)), int(match.group(3))
+            )
+            age_days = (datetime.now() - file_date).days
+            if age_days <= 0:
+                return 1.0
+            
+            decay_lambda = math.log(2) / half_life_days
+            return math.exp(-decay_lambda * age_days)
+        except (ValueError, OverflowError):
+            return 1.0
+    
+    def _merge_results(
+        self,
+        vector_results: List[SearchResult],
+        keyword_results: List[SearchResult],
+        vector_weight: float,
+        keyword_weight: float
+    ) -> List[SearchResult]:
+        """Merge vector and keyword search results with temporal decay for dated files"""
+        merged_map = {}
+        
+        for result in vector_results:
+            key = (result.path, result.start_line, result.end_line)
+            merged_map[key] = {
+                'result': result,
+                'vector_score': result.score,
+                'keyword_score': 0.0
+            }
+        
+        for result in keyword_results:
+            key = (result.path, result.start_line, result.end_line)
+            if key in merged_map:
+                merged_map[key]['keyword_score'] = result.score
+            else:
+                merged_map[key] = {
+                    'result': result,
+                    'vector_score': 0.0,
+                    'keyword_score': result.score
+                }
+        
+        merged_results = []
+        for entry in merged_map.values():
+            combined_score = (
+                vector_weight * entry['vector_score'] +
+                keyword_weight * entry['keyword_score']
+            )
+            
+            # Apply temporal decay for dated memory files
+            result = entry['result']
+            decay = self._compute_temporal_decay(result.path)
+            combined_score *= decay
+            
+            merged_results.append(SearchResult(
+                path=result.path,
+                start_line=result.start_line,
+                end_line=result.end_line,
+                score=combined_score,
+                snippet=result.snippet,
+                source=result.source,
+                user_id=result.user_id
+            ))
+        
+        merged_results.sort(key=lambda r: r.score, reverse=True)
+        return merged_results
diff --git a/agent/memory/rebuild_index.py b/agent/memory/rebuild_index.py
new file mode 100644
index 0000000..a975503
--- /dev/null
+++ b/agent/memory/rebuild_index.py
@@ -0,0 +1,14 @@
+"""
+Backward-compatible shim for the legacy entry point:
+    python -m agent.memory.rebuild_index
+
+The implementation now lives in agent.memory.embedding.rebuild.
+Prefer using `/memory rebuild-index` in chat going forward.
+"""
+
+from agent.memory.embedding.rebuild import main
+
+if __name__ == "__main__":
+    import sys
+
+    sys.exit(main())
diff --git a/agent/memory/service.py b/agent/memory/service.py
new file mode 100644
index 0000000..055fe83
--- /dev/null
+++ b/agent/memory/service.py
@@ -0,0 +1,225 @@
+"""
+Memory service for handling memory query operations via cloud protocol.
+
+Provides a unified interface for listing and reading memory files,
+callable from the cloud client (LinkAI) or a future web console.
+
+Memory file layout (under workspace_root):
+    MEMORY.md               -> type: global
+    memory/2026-02-20.md    -> type: daily
+"""
+
+import os
+from datetime import datetime
+from typing import Dict, List, Optional
+from pathlib import Path
+from common.log import logger
+
+
+class MemoryService:
+    """
+    High-level service for memory file queries.
+    Operates directly on the filesystem — no MemoryManager dependency.
+    """
+
+    def __init__(self, workspace_root: str):
+        """
+        :param workspace_root: Workspace root directory (e.g. ~/cow)
+        """
+        self.workspace_root = workspace_root
+        self.memory_dir = os.path.join(workspace_root, "memory")
+
+    # ------------------------------------------------------------------
+    # list — paginated file metadata
+    # ------------------------------------------------------------------
+    def list_files(self, page: int = 1, page_size: int = 20, category: str = "memory") -> dict:
+        """
+        List memory, dream, or evolution files with metadata (without content).
+
+        Args:
+            category: ``"memory"`` (default) — MEMORY.md + daily files;
+                      ``"dream"``     — dream diary files from memory/dreams/;
+                      ``"evolution"`` — self-evolution logs from memory/evolution/
+                                        merged with the nightly dream diaries, so
+                                        one tab shows everything the agent learned.
+        """
+        if category == "evolution":
+            files = self._list_evolution_files()
+        elif category == "dream":
+            files = self._list_dream_files()
+        else:
+            files = self._list_memory_files()
+
+        total = len(files)
+        start = (page - 1) * page_size
+        end = start + page_size
+
+        return {
+            "page": page,
+            "page_size": page_size,
+            "total": total,
+            "list": files[start:end],
+        }
+
+    def _list_memory_files(self) -> List[dict]:
+        """MEMORY.md + memory/*.md (newest first)."""
+        files: List[dict] = []
+
+        global_path = os.path.join(self.workspace_root, "MEMORY.md")
+        if os.path.isfile(global_path):
+            files.append(self._file_info(global_path, "MEMORY.md", "global"))
+
+        if os.path.isdir(self.memory_dir):
+            daily_files = []
+            for name in os.listdir(self.memory_dir):
+                full = os.path.join(self.memory_dir, name)
+                if os.path.isfile(full) and name.endswith(".md"):
+                    daily_files.append((name, full))
+            daily_files.sort(key=lambda x: x[0], reverse=True)
+            for name, full in daily_files:
+                files.append(self._file_info(full, name, "daily"))
+
+        return files
+
+    def _list_dream_files(self) -> List[dict]:
+        """memory/dreams/*.md (newest first)."""
+        files: List[dict] = []
+        dreams_dir = os.path.join(self.memory_dir, "dreams")
+
+        if os.path.isdir(dreams_dir):
+            entries = []
+            for name in os.listdir(dreams_dir):
+                full = os.path.join(dreams_dir, name)
+                if os.path.isfile(full) and name.endswith(".md"):
+                    entries.append((name, full))
+            entries.sort(key=lambda x: x[0], reverse=True)
+            for name, full in entries:
+                files.append(self._file_info(full, name, "dream"))
+
+        return files
+
+    def _list_evolution_files(self) -> List[dict]:
+        """Self-evolution logs (memory/evolution/*.md) merged with the nightly
+        dream diaries (memory/dreams/*.md), newest first.
+
+        Both are surfaced under the unified "Self-Evolution" tab. A file's
+        ``type`` records its origin so the reader can resolve the right dir.
+        """
+        files: List[dict] = []
+        for sub, ftype in (("evolution", "evolution"), ("dreams", "dream")):
+            sub_dir = os.path.join(self.memory_dir, sub)
+            if not os.path.isdir(sub_dir):
+                continue
+            for name in os.listdir(sub_dir):
+                full = os.path.join(sub_dir, name)
+                if os.path.isfile(full) and name.endswith(".md"):
+                    files.append(self._file_info(full, name, ftype))
+        # Sort newest first by filename (date-named); ties favor evolution.
+        files.sort(key=lambda f: (f["filename"], f["type"] != "evolution"), reverse=True)
+        return files
+
+    # ------------------------------------------------------------------
+    # content — read a single file
+    # ------------------------------------------------------------------
+    def get_content(self, filename: str, category: str = "memory") -> dict:
+        """
+        Read the full content of a memory or dream file.
+
+        :param filename: File name, e.g. ``MEMORY.md``, ``2026-02-20.md``
+        :param category: ``"memory"``, ``"dream"`` or ``"evolution"``
+        :return: dict with ``filename`` and ``content``
+        :raises FileNotFoundError: if the file does not exist
+        """
+        path = self._resolve_path(filename, category)
+        if not os.path.isfile(path):
+            raise FileNotFoundError(f"Memory file not found: {filename}")
+
+        with open(path, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        return {
+            "filename": filename,
+            "content": content,
+        }
+
+    # ------------------------------------------------------------------
+    # dispatch — single entry point for protocol messages
+    # ------------------------------------------------------------------
+    def dispatch(self, action: str, payload: Optional[dict] = None) -> dict:
+        """
+        Dispatch a memory management action.
+
+        :param action: ``list`` or ``content``
+        :param payload: action-specific payload (supports ``category``: ``"memory"`` | ``"dream"`` | ``"evolution"``)
+        :return: protocol-compatible response dict
+        """
+        payload = payload or {}
+        try:
+            if action == "list":
+                page = payload.get("page", 1)
+                page_size = payload.get("page_size", 20)
+                category = payload.get("category", "memory")
+                result_payload = self.list_files(page=page, page_size=page_size, category=category)
+                return {"action": action, "code": 200, "message": "success", "payload": result_payload}
+
+            elif action == "content":
+                filename = payload.get("filename")
+                if not filename:
+                    return {"action": action, "code": 400, "message": "filename is required", "payload": None}
+                category = payload.get("category", "memory")
+                result_payload = self.get_content(filename, category=category)
+                return {"action": action, "code": 200, "message": "success", "payload": result_payload}
+
+            else:
+                return {"action": action, "code": 400, "message": f"unknown action: {action}", "payload": None}
+
+        except ValueError as e:
+            return {"action": action, "code": 403, "message": "invalid filename", "payload": None}
+        except FileNotFoundError as e:
+            return {"action": action, "code": 404, "message": str(e), "payload": None}
+        except Exception as e:
+            logger.error(f"[MemoryService] dispatch error: action={action}, error={e}")
+            return {"action": action, "code": 500, "message": str(e), "payload": None}
+
+    # ------------------------------------------------------------------
+    # internal helpers
+    # ------------------------------------------------------------------
+    def _resolve_path(self, filename: str, category: str = "memory") -> str:
+        """
+        Safely resolve a filename to its absolute path within the allowed directory.
+
+        - ``MEMORY.md`` → ``{workspace_root}/MEMORY.md``
+        - ``2026-02-20.md`` (memory) → ``{workspace_root}/memory/2026-02-20.md``
+        - ``2026-02-20.md`` (dream) → ``{workspace_root}/memory/dreams/2026-02-20.md``
+        - ``2026-02-20.md`` (evolution) → ``{workspace_root}/memory/evolution/2026-02-20.md``
+
+        Raises ValueError if the resolved path escapes the allowed directory.
+        """
+        if filename == "MEMORY.md":
+            base_dir = self.workspace_root
+        elif category == "dream":
+            base_dir = os.path.join(self.memory_dir, "dreams")
+        elif category == "evolution":
+            base_dir = os.path.join(self.memory_dir, "evolution")
+        else:
+            base_dir = self.memory_dir
+
+        resolved = os.path.realpath(os.path.join(base_dir, filename))
+        allowed = os.path.realpath(base_dir)
+
+        if resolved != allowed and not resolved.startswith(allowed + os.sep):
+            raise ValueError(f"Invalid filename: path traversal detected")
+
+        return resolved
+
+    @staticmethod
+    def _file_info(path: str, filename: str, file_type: str) -> dict:
+        """Build a file metadata dict."""
+        stat = os.stat(path)
+        updated_at = datetime.fromtimestamp(stat.st_mtime).strftime("%Y-%m-%d %H:%M:%S")
+        return {
+            "filename": filename,
+            "type": file_type,
+            "size": stat.st_size,
+            "updated_at": updated_at,
+        }
diff --git a/agent/memory/storage.py b/agent/memory/storage.py
new file mode 100644
index 0000000..240ff9d
--- /dev/null
+++ b/agent/memory/storage.py
@@ -0,0 +1,1057 @@
+"""
+Storage layer for memory using SQLite + FTS5
+
+Provides vector and keyword search capabilities
+"""
+
+from __future__ import annotations
+import re
+import sqlite3
+import json
+import hashlib
+import threading
+from typing import List, Dict, Optional, Any
+from pathlib import Path
+from dataclasses import dataclass
+try:
+    import numpy as np
+    _HAS_NUMPY = True
+except ImportError:
+    _HAS_NUMPY = False
+    np = None  # type: ignore[assignment]
+
+# UPSERT (INSERT … ON CONFLICT DO UPDATE) requires SQLite ≥ 3.24.0 (2018).
+# Older systems (e.g. CentOS 7 ships SQLite 3.7) fall back to INSERT OR REPLACE,
+# which risks FTS5 rowid drift on chunk updates (see save_chunk docstring).
+_HAS_UPSERT = sqlite3.sqlite_version_info >= (3, 24, 0)
+
+# ---------------------------------------------------------------------------
+# CJK character ranges, compiled once at module load.
+# Covers: CJK Symbols/Punctuation, Japanese kana (hiragana + katakana),
+#         CJK Unified Ideographs + Extension A, Korean syllables (Hangul),
+#         CJK Compatibility Ideographs, and CJK Extension B–F.
+# ---------------------------------------------------------------------------
+_CJK_RANGES = (
+    r'\u3000-\u30ff'          # CJK Symbols/Punctuation + Japanese kana
+    r'\u3400-\u9fff'          # CJK Unified Ideographs (incl. Extension A)
+    r'\uac00-\ud7af'          # Korean syllables (Hangul)
+    r'\uf900-\ufaff'          # CJK Compatibility Ideographs
+    r'\U00020000-\U0002fa1f'  # CJK Extension B–F
+)
+_RE_CONTAINS_CJK   = re.compile(f'[{_CJK_RANGES}]')
+_RE_CJK_WORDS      = re.compile(f'[{_CJK_RANGES}]+')
+_RE_TRIGRAM_TOKENS = re.compile(f'[{_CJK_RANGES}]+|[A-Za-z0-9_]+')
+
+
+@dataclass
+class MemoryChunk:
+    """Represents a memory chunk with text and embedding"""
+    id: str
+    user_id: Optional[str]
+    scope: str  # "shared" | "user" | "session"
+    source: str  # "memory" | "session"
+    path: str
+    start_line: int
+    end_line: int
+    text: str
+    embedding: Optional[List[float]]
+    hash: str
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@dataclass
+class SearchResult:
+    """Search result with score and snippet"""
+    path: str
+    start_line: int
+    end_line: int
+    score: float
+    snippet: str
+    source: str
+    user_id: Optional[str] = None
+
+
+class MemoryStorage:
+    """SQLite-based storage with FTS5 for keyword search"""
+    
+    def __init__(self, db_path: Path):
+        self.db_path = db_path
+        self.conn: Optional[sqlite3.Connection] = None
+        self.fts5_available = False  # Track FTS5 availability
+        # RLock protects concurrent writes from the same process.
+        # SQLite WAL mode handles read/write concurrency at the file level,
+        # but same-process concurrent writes still need a Python-level lock.
+        self._lock = threading.RLock()
+        self._init_db()
+    
+    def _check_fts5_support(self) -> bool:
+        """Check if SQLite has FTS5 support"""
+        try:
+            self.conn.execute("CREATE VIRTUAL TABLE IF NOT EXISTS fts5_test USING fts5(test)")
+            self.conn.execute("DROP TABLE IF EXISTS fts5_test")
+            return True
+        except sqlite3.OperationalError as e:
+            if "no such module: fts5" in str(e):
+                return False
+            raise
+    
+    def _init_db(self):
+        """Initialize database with schema"""
+        try:
+            self.conn = sqlite3.connect(str(self.db_path), check_same_thread=False)
+            self.conn.row_factory = sqlite3.Row
+            
+            # Check FTS5 support
+            self.fts5_available = self._check_fts5_support()
+            if not _HAS_UPSERT:
+                from common.log import logger
+                logger.warning(
+                    "[MemoryStorage] SQLite %s < 3.24 — UPSERT unavailable. "
+                    "Falling back to INSERT OR REPLACE; FTS5 rowid may drift on "
+                    "chunk updates (rebuild index periodically to recover).",
+                    sqlite3.sqlite_version,
+                )
+            if not self.fts5_available:
+                from common.log import logger
+                logger.debug("[MemoryStorage] FTS5 not available, using LIKE-based keyword search")
+            
+            # Check database integrity
+            try:
+                result = self.conn.execute("PRAGMA integrity_check").fetchone()
+                if result[0] != 'ok':
+                    print(f"⚠️  Database integrity check failed: {result[0]}")
+                    print(f"   Recreating database...")
+                    self.conn.close()
+                    self.conn = None
+                    # Remove corrupted database
+                    self.db_path.unlink(missing_ok=True)
+                    # Remove WAL files
+                    Path(str(self.db_path) + '-wal').unlink(missing_ok=True)
+                    Path(str(self.db_path) + '-shm').unlink(missing_ok=True)
+                    # Reconnect to create new database
+                    self.conn = sqlite3.connect(str(self.db_path), check_same_thread=False)
+                    self.conn.row_factory = sqlite3.Row
+            except sqlite3.DatabaseError:
+                # Database is corrupted, recreate it
+                print(f"⚠️  Database is corrupted, recreating...")
+                if self.conn:
+                    self.conn.close()
+                    self.conn = None
+                self.db_path.unlink(missing_ok=True)
+                Path(str(self.db_path) + '-wal').unlink(missing_ok=True)
+                Path(str(self.db_path) + '-shm').unlink(missing_ok=True)
+                self.conn = sqlite3.connect(str(self.db_path), check_same_thread=False)
+                self.conn.row_factory = sqlite3.Row
+            
+            # Enable WAL mode for better concurrency
+            self.conn.execute("PRAGMA journal_mode=WAL")
+            # Set busy timeout to avoid "database is locked" errors
+            self.conn.execute("PRAGMA busy_timeout=5000")
+        except Exception as e:
+            print(f"⚠️  Unexpected error during database initialization: {e}")
+            raise
+        
+        # Create chunks table with embeddings
+        self.conn.execute("""
+            CREATE TABLE IF NOT EXISTS chunks (
+                id TEXT PRIMARY KEY,
+                user_id TEXT,
+                scope TEXT NOT NULL DEFAULT 'shared',
+                source TEXT NOT NULL DEFAULT 'memory',
+                path TEXT NOT NULL,
+                start_line INTEGER NOT NULL,
+                end_line INTEGER NOT NULL,
+                text TEXT NOT NULL,
+                embedding TEXT,
+                hash TEXT NOT NULL,
+                metadata TEXT,
+                created_at INTEGER DEFAULT (strftime('%s', 'now')),
+                updated_at INTEGER DEFAULT (strftime('%s', 'now'))
+            )
+        """)
+        
+        # Create indexes
+        self.conn.execute("""
+            CREATE INDEX IF NOT EXISTS idx_chunks_user 
+            ON chunks(user_id)
+        """)
+        
+        self.conn.execute("""
+            CREATE INDEX IF NOT EXISTS idx_chunks_scope 
+            ON chunks(scope)
+        """)
+        
+        self.conn.execute("""
+            CREATE INDEX IF NOT EXISTS idx_chunks_hash 
+            ON chunks(path, hash)
+        """)
+        
+        # Create FTS5 virtual table + triggers (only if supported).
+        # Self-heal: if the previous process crashed mid-rebuild and left
+        # triggers pointing at a missing chunks_fts (or vice versa), wipe
+        # both sides and recreate cleanly. Otherwise next chunks INSERT
+        # will fail with "no such table: chunks_fts".
+        if self.fts5_available:
+            if self._fts5_state_inconsistent():
+                from common.log import logger
+                logger.warning(
+                    "[MemoryStorage] FTS5 state inconsistent (triggers/table mismatch). "
+                    "Resetting chunks_fts to recover."
+                )
+                self.conn.execute("DROP TRIGGER IF EXISTS chunks_ai")
+                self.conn.execute("DROP TRIGGER IF EXISTS chunks_ad")
+                self.conn.execute("DROP TRIGGER IF EXISTS chunks_au")
+                self.conn.execute("DROP TABLE IF EXISTS chunks_fts")
+                self.conn.commit()
+            self._create_fts5_objects()
+
+            # Probe FTS5 shadow tables. The schema may be intact but the
+            # internal _data/_idx/_docsize blob can still be corrupt — that
+            # surfaces as "database disk image is malformed" on bm25 / MATCH.
+            # We rebuild from the chunks table when that happens; data isn't
+            # lost because chunks (the content table) is the source of truth.
+            if self._fts5_shadow_corrupt():
+                from common.log import logger
+                logger.warning(
+                    "[MemoryStorage] FTS5 shadow tables corrupt; rebuilding from chunks."
+                )
+                self._rebuild_fts5_from_chunks()
+
+        # Internal key-value store for persistent flags (e.g. backfill tracking)
+        self.conn.execute("""
+            CREATE TABLE IF NOT EXISTS _meta (
+                key TEXT PRIMARY KEY,
+                value TEXT NOT NULL
+            )
+        """)
+
+        # Create trigram FTS5 table for CJK / mixed-language search
+        self.trigram_fts5_available = False
+        if self.fts5_available:
+            try:
+                self.conn.execute("""
+                    CREATE VIRTUAL TABLE IF NOT EXISTS chunks_fts_trigram USING fts5(
+                        text,
+                        id UNINDEXED,
+                        user_id UNINDEXED,
+                        path UNINDEXED,
+                        source UNINDEXED,
+                        scope UNINDEXED,
+                        content='chunks',
+                        content_rowid='rowid',
+                        tokenize='trigram case_sensitive 0'
+                    )
+                """)
+                self.conn.execute("""
+                    CREATE TRIGGER IF NOT EXISTS chunks_trigram_ai
+                    AFTER INSERT ON chunks BEGIN
+                        INSERT INTO chunks_fts_trigram(rowid, text, id, user_id, path, source, scope)
+                        VALUES (new.rowid, new.text, new.id, new.user_id, new.path, new.source, new.scope);
+                    END
+                """)
+                self.conn.execute("""
+                    CREATE TRIGGER IF NOT EXISTS chunks_trigram_ad
+                    AFTER DELETE ON chunks BEGIN
+                        DELETE FROM chunks_fts_trigram WHERE rowid = old.rowid;
+                    END
+                """)
+                self.conn.execute("""
+                    CREATE TRIGGER IF NOT EXISTS chunks_trigram_au
+                    AFTER UPDATE ON chunks BEGIN
+                        UPDATE chunks_fts_trigram
+                        SET text=new.text, id=new.id, user_id=new.user_id,
+                            path=new.path, source=new.source, scope=new.scope
+                        WHERE rowid = new.rowid;
+                    END
+                """)
+                # One-time backfill for existing rows.
+                # NOTE: COUNT(*) on an FTS5 content table always returns 0, so we
+                # use a persistent flag in _meta instead of counting trigram rows.
+                backfill_done = self.conn.execute(
+                    "SELECT 1 FROM _meta WHERE key = 'trigram_backfill_done'"
+                ).fetchone()
+                chunks_count = self.conn.execute(
+                    "SELECT COUNT(*) as c FROM chunks"
+                ).fetchone()['c']
+                if chunks_count > 0 and not backfill_done:
+                    self.conn.execute(
+                        "INSERT INTO chunks_fts_trigram(chunks_fts_trigram) VALUES('rebuild')"
+                    )
+                    self.conn.execute(
+                        "INSERT OR REPLACE INTO _meta(key, value) VALUES('trigram_backfill_done', '1')"
+                    )
+                self.trigram_fts5_available = True
+            except Exception:
+                from common.log import logger
+                logger.warning("[MemoryStorage] trigram FTS5 unavailable, CJK search will use LIKE fallback", exc_info=True)
+                self.trigram_fts5_available = False
+
+        # Create files metadata table
+        self.conn.execute("""
+            CREATE TABLE IF NOT EXISTS files (
+                path TEXT PRIMARY KEY,
+                source TEXT NOT NULL DEFAULT 'memory',
+                hash TEXT NOT NULL,
+                mtime INTEGER NOT NULL,
+                size INTEGER NOT NULL,
+                updated_at INTEGER DEFAULT (strftime('%s', 'now'))
+            )
+        """)
+
+        self.conn.commit()
+
+    def _fts5_state_inconsistent(self) -> bool:
+        """Detect a half-broken FTS5 setup (e.g. trigger exists but table doesn't)."""
+        try:
+            row = self.conn.execute(
+                "SELECT name FROM sqlite_master WHERE type='table' AND name='chunks_fts'"
+            ).fetchone()
+            table_exists = row is not None
+            row = self.conn.execute(
+                "SELECT COUNT(*) FROM sqlite_master WHERE type='trigger' "
+                "AND name IN ('chunks_ai','chunks_ad','chunks_au')"
+            ).fetchone()
+            trigger_count = int(row[0]) if row else 0
+        except Exception:
+            return False
+        # Healthy = both present (3 triggers + table) or both absent.
+        return table_exists != (trigger_count > 0)
+
+    def _create_fts5_objects(self):
+        """Create chunks_fts virtual table and the 3 sync triggers.
+
+        Idempotent: uses IF NOT EXISTS. Caller must hold self.conn.
+        """
+        self.conn.execute("""
+            CREATE VIRTUAL TABLE IF NOT EXISTS chunks_fts USING fts5(
+                text,
+                id UNINDEXED,
+                user_id UNINDEXED,
+                path UNINDEXED,
+                source UNINDEXED,
+                scope UNINDEXED,
+                content='chunks',
+                content_rowid='rowid'
+            )
+        """)
+        self.conn.execute("""
+            CREATE TRIGGER IF NOT EXISTS chunks_ai AFTER INSERT ON chunks BEGIN
+                INSERT INTO chunks_fts(rowid, text, id, user_id, path, source, scope)
+                VALUES (new.rowid, new.text, new.id, new.user_id, new.path, new.source, new.scope);
+            END
+        """)
+        self.conn.execute("""
+            CREATE TRIGGER IF NOT EXISTS chunks_ad AFTER DELETE ON chunks BEGIN
+                DELETE FROM chunks_fts WHERE rowid = old.rowid;
+            END
+        """)
+        self.conn.execute("""
+            CREATE TRIGGER IF NOT EXISTS chunks_au AFTER UPDATE ON chunks BEGIN
+                UPDATE chunks_fts SET text = new.text, id = new.id,
+                                     user_id = new.user_id, path = new.path,
+                                     source = new.source, scope = new.scope
+                WHERE rowid = new.rowid;
+            END
+        """)
+
+    def reset_fts5(self):
+        """Drop and recreate chunks_fts + triggers in one transaction.
+
+        Used by rebuild_index to recover from FTS5 shadow-table corruption
+        (bm25/ORDER BY rank may raise "database disk image is malformed"
+        even when raw MATCH still works).
+
+        Triggers must be dropped first; otherwise the next chunks INSERT/DELETE
+        on the existing connection will hit "no such table: chunks_fts".
+        """
+        if not self.fts5_available:
+            return
+        self.conn.execute("DROP TRIGGER IF EXISTS chunks_ai")
+        self.conn.execute("DROP TRIGGER IF EXISTS chunks_ad")
+        self.conn.execute("DROP TRIGGER IF EXISTS chunks_au")
+        self.conn.execute("DROP TABLE IF EXISTS chunks_fts")
+        self._create_fts5_objects()
+        self.conn.commit()
+
+    def _fts5_shadow_corrupt(self) -> bool:
+        """Probe whether bm25 over chunks_fts errors out at startup.
+
+        Schema (table + triggers) can be intact while the underlying
+        FTS5 shadow blobs are malformed — typically because the previous
+        process crashed mid-write or wrote with a different SQLite build.
+        A cheap MATCH probe surfaces it immediately."""
+        try:
+            self.conn.execute(
+                "SELECT bm25(chunks_fts) FROM chunks_fts WHERE chunks_fts MATCH 'a' LIMIT 1"
+            ).fetchone()
+            return False
+        except sqlite3.DatabaseError as e:
+            msg = str(e).lower()
+            return "malformed" in msg or "corrupt" in msg
+        except Exception:
+            # Any other error (e.g. table missing) is handled by the
+            # state-inconsistent path; treat as healthy here.
+            return False
+
+    def _rebuild_fts5_from_chunks(self):
+        """Drop FTS5, recreate it, then INSERT every row from chunks.
+
+        Safe data-wise: chunks (the content table) is the source of truth.
+        Done in one transaction so a crash leaves either fully old or fully
+        new state, not a partial rebuild.
+        """
+        # Reset schema first; this clears any malformed shadow blobs.
+        self.reset_fts5()
+        # Re-feed content. Triggers handle future writes automatically.
+        self.conn.execute("""
+            INSERT INTO chunks_fts(rowid, text, id, user_id, path, source, scope)
+            SELECT rowid, text, id, user_id, path, source, scope FROM chunks
+        """)
+        self.conn.commit()
+
+    def save_chunk(self, chunk: MemoryChunk):
+        """Save a memory chunk (insert or update by id).
+
+        Uses SQLite UPSERT (INSERT … ON CONFLICT DO UPDATE) instead of
+        INSERT OR REPLACE.  INSERT OR REPLACE internally does DELETE+INSERT,
+        which changes the row's rowid.  Because both FTS5 tables use
+        content_rowid='rowid', a new rowid would leave the old FTS index
+        entries pointing at a non-existent rowid and trigger
+        "fts5: missing row N from content table" errors.
+        ON CONFLICT DO UPDATE fires the AFTER UPDATE trigger (chunks_au /
+        chunks_trigram_au) and keeps the original rowid intact.
+        """
+        if _HAS_UPSERT:
+            _SQL = """
+                INSERT INTO chunks
+                (id, user_id, scope, source, path, start_line, end_line,
+                 text, embedding, hash, metadata, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, strftime('%s', 'now'))
+                ON CONFLICT(id) DO UPDATE SET
+                    user_id     = excluded.user_id,
+                    scope       = excluded.scope,
+                    source      = excluded.source,
+                    path        = excluded.path,
+                    start_line  = excluded.start_line,
+                    end_line    = excluded.end_line,
+                    text        = excluded.text,
+                    embedding   = excluded.embedding,
+                    hash        = excluded.hash,
+                    metadata    = excluded.metadata,
+                    updated_at  = strftime('%s', 'now')
+            """
+        else:
+            _SQL = """
+                INSERT OR REPLACE INTO chunks
+                (id, user_id, scope, source, path, start_line, end_line,
+                 text, embedding, hash, metadata, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, strftime('%s', 'now'))
+            """
+        params = (
+            chunk.id, chunk.user_id, chunk.scope, chunk.source, chunk.path,
+            chunk.start_line, chunk.end_line, chunk.text,
+            self._encode_embedding(chunk.embedding),
+            chunk.hash,
+            json.dumps(chunk.metadata) if chunk.metadata else None,
+        )
+        with self._lock:
+            self.conn.execute(_SQL, params)
+            self.conn.commit()
+
+    def save_chunks_batch(self, chunks: List[MemoryChunk]):
+        """Save multiple chunks in a batch (insert or update by id).
+
+        See save_chunk for why UPSERT is used instead of INSERT OR REPLACE.
+        """
+        if _HAS_UPSERT:
+            _SQL = """
+                INSERT INTO chunks
+                (id, user_id, scope, source, path, start_line, end_line,
+                 text, embedding, hash, metadata, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, strftime('%s', 'now'))
+                ON CONFLICT(id) DO UPDATE SET
+                    user_id     = excluded.user_id,
+                    scope       = excluded.scope,
+                    source      = excluded.source,
+                    path        = excluded.path,
+                    start_line  = excluded.start_line,
+                    end_line    = excluded.end_line,
+                    text        = excluded.text,
+                    embedding   = excluded.embedding,
+                    hash        = excluded.hash,
+                    metadata    = excluded.metadata,
+                    updated_at  = strftime('%s', 'now')
+            """
+        else:
+            _SQL = """
+                INSERT OR REPLACE INTO chunks
+                (id, user_id, scope, source, path, start_line, end_line,
+                 text, embedding, hash, metadata, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, strftime('%s', 'now'))
+            """
+        params_list = [
+            (
+                c.id, c.user_id, c.scope, c.source, c.path,
+                c.start_line, c.end_line, c.text,
+                self._encode_embedding(c.embedding),
+                c.hash,
+                json.dumps(c.metadata) if c.metadata else None,
+            )
+            for c in chunks
+        ]
+        with self._lock:
+            self.conn.executemany(_SQL, params_list)
+            self.conn.commit()
+    
+    def get_chunk(self, chunk_id: str) -> Optional[MemoryChunk]:
+        """Get a chunk by ID"""
+        row = self.conn.execute("""
+            SELECT * FROM chunks WHERE id = ?
+        """, (chunk_id,)).fetchone()
+        
+        if not row:
+            return None
+        
+        return self._row_to_chunk(row)
+    
+    def search_vector(
+        self,
+        query_embedding: List[float],
+        user_id: Optional[str] = None,
+        scopes: List[str] = None,
+        limit: int = 10
+    ) -> List[SearchResult]:
+        """
+        Vector similarity search using numpy-vectorized cosine similarity.
+        All embeddings are loaded then scored in a single BLAS matrix-vector
+        multiply, which is ~100x faster than the pure-Python per-row loop.
+        """
+        if scopes is None:
+            scopes = ["shared"]
+            if user_id:
+                scopes.append("user")
+
+        scope_placeholders = ','.join('?' * len(scopes))
+        params = list(scopes)
+
+        if user_id:
+            query = f"""
+                SELECT * FROM chunks
+                WHERE scope IN ({scope_placeholders})
+                AND (scope = 'shared' OR user_id = ?)
+                AND embedding IS NOT NULL
+            """
+            params.append(user_id)
+        else:
+            query = f"""
+                SELECT * FROM chunks
+                WHERE scope IN ({scope_placeholders})
+                AND embedding IS NOT NULL
+            """
+
+        rows = self.conn.execute(query, params).fetchall()
+        if not rows:
+            return []
+
+        # Parse embeddings and build a (N, D) matrix in one pass.
+        # New rows store BLOB bytes (np.frombuffer); legacy rows fall back to JSON.
+        # Filter out rows whose embedding dimension differs from the query —
+        # mixing dimensions would cause np.array() to produce an object array
+        # and matrix @ q_vec to raise ValueError.
+        expected_dim = len(query_embedding)
+        valid_rows = []
+        vectors = []
+        for row in rows:
+            vec = self._decode_embedding(row['embedding'])
+            if not vec:
+                continue
+            if len(vec) != expected_dim:
+                from common.log import logger
+                logger.warning(
+                    "[MemoryStorage] Skipping chunk %s: embedding dim %d != query dim %d",
+                    row['id'], len(vec), expected_dim
+                )
+                continue
+            valid_rows.append(row)
+            vectors.append(vec)
+
+        if not vectors:
+            return []
+
+        if _HAS_NUMPY:
+            matrix = np.array(vectors, dtype=np.float32)        # (N, D)
+            q_vec = np.array(query_embedding, dtype=np.float32)  # (D,)
+
+            # Vectorized cosine similarity: dot(matrix, q) / (||matrix|| * ||q||)
+            dots = matrix @ q_vec                                # (N,)
+            row_norms = np.linalg.norm(matrix, axis=1)           # (N,)
+            q_norm = float(np.linalg.norm(q_vec))
+            denominators = row_norms * q_norm
+            np.maximum(denominators, 1e-10, out=denominators)    # avoid div-by-zero
+            sims = dots / denominators                           # (N,)
+
+            # Select TopK using argpartition (O(N) average), then sort only those K
+            k = min(limit, len(valid_rows))
+            top_idx = np.argpartition(sims, -k)[-k:]
+            top_idx = top_idx[np.argsort(sims[top_idx])[::-1]]
+
+            return [
+                SearchResult(
+                    path=valid_rows[i]['path'],
+                    start_line=valid_rows[i]['start_line'],
+                    end_line=valid_rows[i]['end_line'],
+                    score=float(sims[i]),
+                    snippet=self._truncate_text(valid_rows[i]['text'], 500),
+                    source=valid_rows[i]['source'],
+                    user_id=valid_rows[i]['user_id']
+                )
+                for i in top_idx
+                if sims[i] > 0
+            ]
+        else:
+            # Pure-Python cosine similarity fallback (numpy not installed)
+            import math
+            q = query_embedding
+            q_norm = math.sqrt(sum(x * x for x in q)) or 1e-10
+            scored = []
+            for i, vec in enumerate(vectors):
+                dot = sum(a * b for a, b in zip(vec, q))
+                v_norm = math.sqrt(sum(x * x for x in vec)) or 1e-10
+                sim = dot / (v_norm * q_norm)
+                if sim > 0:
+                    scored.append((sim, valid_rows[i]))
+            scored.sort(key=lambda x: x[0], reverse=True)
+            return [
+                SearchResult(
+                    path=row['path'],
+                    start_line=row['start_line'],
+                    end_line=row['end_line'],
+                    score=sim,
+                    snippet=self._truncate_text(row['text'], 500),
+                    source=row['source'],
+                    user_id=row['user_id']
+                )
+                for sim, row in scored[:limit]
+            ]
+    
+    def search_keyword(
+        self,
+        query: str,
+        user_id: Optional[str] = None,
+        scopes: List[str] = None,
+        limit: int = 10
+    ) -> List[SearchResult]:
+        """
+        Keyword search using FTS5 + LIKE fallback
+
+        Strategy:
+        1. If FTS5 available and healthy: try FTS5 first
+        2. Always fall back to LIKE for CJK queries
+        3. If FTS5 fails OR returns empty for non-CJK, also try LIKE so a
+           broken FTS5 shadow table doesn't silently kill keyword search.
+        """
+        if scopes is None:
+            scopes = ["shared"]
+            if user_id:
+                scopes.append("user")
+
+        # Step 1: Standard FTS5 (unicode61) — pure ASCII queries only.
+        # Skipped when query contains any CJK characters: unicode61 tokenises CJK
+        # as individual characters without forming meaningful tokens, so it would
+        # match only the ASCII portion of a mixed query (e.g. "Python" from
+        # "Python教程") and silently discard the CJK part.  Those queries go
+        # directly to Step 2 (trigram), which handles both ASCII and CJK together.
+        fts1_attempted = False
+        if (self.fts5_available
+                and not MemoryStorage._contains_cjk(query)
+                and MemoryStorage._build_fts_query(query)):
+            fts1_attempted = True
+            fts_results = self._search_fts5(query, user_id, scopes, limit)
+            if fts_results:
+                return fts_results
+
+        # Step 2: Trigram FTS5 — CJK/mixed queries, plus fallback when unicode61
+        # returned nothing (trigram indexes all scripts with 3-char sliding windows,
+        # so it can catch terms that unicode61 tokenisation misses).
+        if self.trigram_fts5_available and (
+            MemoryStorage._contains_cjk(query) or fts1_attempted
+        ):
+            trigram_results = self._search_fts5_trigram(query, user_id, scopes, limit)
+            if trigram_results:
+                return trigram_results
+
+        # Step 3: LIKE fallback — last resort (FTS5 unavailable, or CJK tokens
+        # shorter than 3 characters that trigram cannot match, e.g. a single-char query).
+        if not self.fts5_available or MemoryStorage._contains_cjk(query):
+            return self._search_like(query, user_id, scopes, limit)
+
+        return []
+    
+    def _search_fts5(
+        self,
+        query: str,
+        user_id: Optional[str],
+        scopes: List[str],
+        limit: int
+    ) -> List[SearchResult]:
+        """FTS5 full-text search"""
+        fts_query = self._build_fts_query(query)
+        if not fts_query:
+            return []
+        
+        scope_placeholders = ','.join('?' * len(scopes))
+        params = [fts_query] + scopes
+        
+        if user_id:
+            sql_query = f"""
+                SELECT chunks.*, bm25(chunks_fts) as rank
+                FROM chunks_fts
+                JOIN chunks ON chunks.rowid = chunks_fts.rowid
+                WHERE chunks_fts MATCH ? 
+                AND chunks.scope IN ({scope_placeholders})
+                AND (chunks.scope = 'shared' OR chunks.user_id = ?)
+                ORDER BY rank
+                LIMIT ?
+            """
+            params.extend([user_id, limit])
+        else:
+            sql_query = f"""
+                SELECT chunks.*, bm25(chunks_fts) as rank
+                FROM chunks_fts
+                JOIN chunks ON chunks.rowid = chunks_fts.rowid
+                WHERE chunks_fts MATCH ? 
+                AND chunks.scope IN ({scope_placeholders})
+                ORDER BY rank
+                LIMIT ?
+            """
+            params.append(limit)
+        
+        try:
+            rows = self.conn.execute(sql_query, params).fetchall()
+            return [
+                SearchResult(
+                    path=row['path'],
+                    start_line=row['start_line'],
+                    end_line=row['end_line'],
+                    score=self._bm25_rank_to_score(row['rank']),
+                    snippet=self._truncate_text(row['text'], 500),
+                    source=row['source'],
+                    user_id=row['user_id']
+                )
+                for row in rows
+            ]
+        except Exception:
+            from common.log import logger
+            logger.warning("[MemoryStorage] _search_fts5 failed, returning empty", exc_info=True)
+            return []
+
+    def _search_like(
+        self,
+        query: str,
+        user_id: Optional[str],
+        scopes: List[str],
+        limit: int
+    ) -> List[SearchResult]:
+        """LIKE-based search.
+
+        Used as the keyword-search fallback when FTS5 is unavailable, fails,
+        or returns empty. Supports both CJK runs (1+ chars) and ASCII word
+        tokens (3+ chars) so it can serve as a true safety net for any query.
+        """
+        # CJK runs (1+ chars, wide Unicode range) + ASCII words (3+ chars to avoid noise)
+        cjk_words = _RE_CJK_WORDS.findall(query)
+        ascii_words = [t for t in re.findall(r'[A-Za-z0-9_]+', query) if len(t) >= 3]
+        words = cjk_words + ascii_words
+        if not words:
+            return []
+
+        scope_placeholders = ','.join('?' * len(scopes))
+
+        # Build LIKE conditions for each word (case-insensitive for ASCII)
+        like_conditions = []
+        params = []
+        for word in words:
+            like_conditions.append("LOWER(text) LIKE ?")
+            params.append(f'%{word.lower()}%')
+        
+        where_clause = ' OR '.join(like_conditions)
+        params.extend(scopes)
+        
+        if user_id:
+            sql_query = f"""
+                SELECT * FROM chunks
+                WHERE ({where_clause})
+                AND scope IN ({scope_placeholders})
+                AND (scope = 'shared' OR user_id = ?)
+                LIMIT ?
+            """
+            params.extend([user_id, limit])
+        else:
+            sql_query = f"""
+                SELECT * FROM chunks
+                WHERE ({where_clause})
+                AND scope IN ({scope_placeholders})
+                LIMIT ?
+            """
+            params.append(limit)
+        
+        try:
+            rows = self.conn.execute(sql_query, params).fetchall()
+            results = []
+            for row in rows:
+                # Dynamic score: reward chunks that contain more of the query words.
+                # Use all tokens (CJK + ASCII) so pure-ASCII queries are not skipped.
+                # matched_count is always ≥1 because the WHERE clause uses OR, but
+                # guard defensively so unexpected zero-match rows are never surfaced.
+                text_lower = row['text'].lower()
+                matched_count = sum(1 for w in words if w.lower() in text_lower)
+                if matched_count == 0:
+                    continue
+                score = min(0.85, 0.3 + 0.15 * matched_count)
+                results.append(SearchResult(
+                    path=row['path'],
+                    start_line=row['start_line'],
+                    end_line=row['end_line'],
+                    score=score,
+                    snippet=self._truncate_text(row['text'], 500),
+                    source=row['source'],
+                    user_id=row['user_id']
+                ))
+            results.sort(key=lambda r: r.score, reverse=True)
+            return results
+        except Exception:
+            from common.log import logger
+            logger.warning("[MemoryStorage] _search_like failed, returning empty", exc_info=True)
+            return []
+
+    def delete_by_path(self, path: str):
+        """Delete all chunks and file metadata for a path."""
+        with self._lock:
+            self.conn.execute("DELETE FROM chunks WHERE path = ?", (path,))
+            self.conn.execute("DELETE FROM files WHERE path = ?", (path,))
+            self.conn.commit()
+
+    def get_file_hash(self, path: str) -> Optional[str]:
+        """Get stored file hash"""
+        row = self.conn.execute("""
+            SELECT hash FROM files WHERE path = ?
+        """, (path,)).fetchone()
+        return row['hash'] if row else None
+
+    def update_file_metadata(self, path: str, source: str, file_hash: str, mtime: int, size: int):
+        """Update file metadata"""
+        with self._lock:
+            self.conn.execute("""
+                INSERT OR REPLACE INTO files (path, source, hash, mtime, size, updated_at)
+                VALUES (?, ?, ?, ?, ?, strftime('%s', 'now'))
+            """, (path, source, file_hash, mtime, size))
+            self.conn.commit()
+    
+    def get_stats(self) -> Dict[str, int]:
+        """Get storage statistics"""
+        chunks_count = self.conn.execute("""
+            SELECT COUNT(*) as cnt FROM chunks
+        """).fetchone()['cnt']
+
+        files_count = self.conn.execute("""
+            SELECT COUNT(*) as cnt FROM files
+        """).fetchone()['cnt']
+
+        embedded_count = self.conn.execute("""
+            SELECT COUNT(*) as cnt FROM chunks WHERE embedding IS NOT NULL
+        """).fetchone()['cnt']
+
+        return {
+            'chunks': chunks_count,
+            'files': files_count,
+            'embedded': embedded_count,
+        }
+    
+    def close(self):
+        """Close database connection"""
+        if self.conn:
+            try:
+                self.conn.commit()  # Ensure all changes are committed
+                self.conn.close()
+                self.conn = None  # Mark as closed
+            except Exception as e:
+                from common.log import logger
+                logger.warning("[MemoryStorage] Error closing database connection: %s", e)
+    
+    def __del__(self):
+        """Destructor to ensure connection is closed"""
+        try:
+            self.close()
+        except Exception:
+            pass  # Ignore errors during cleanup
+    
+    # Helper methods
+
+    @staticmethod
+    def _encode_embedding(embedding: Optional[List[float]]) -> Optional[bytes]:
+        """Encode embedding as float32 BLOB bytes (~6x smaller and faster than JSON).
+        Falls back to struct.pack when numpy is unavailable."""
+        if embedding is None:
+            return None
+        if _HAS_NUMPY:
+            return np.array(embedding, dtype=np.float32).tobytes()
+        import struct
+        return struct.pack(f'{len(embedding)}f', *embedding)
+
+    @staticmethod
+    def _decode_embedding(raw) -> Optional[List[float]]:
+        """Decode embedding from BLOB bytes or legacy JSON string.
+        Handles both numpy and numpy-free environments."""
+        if raw is None:
+            return None
+        if isinstance(raw, (bytes, bytearray)):
+            if _HAS_NUMPY:
+                return np.frombuffer(raw, dtype=np.float32).tolist()
+            import struct
+            n = len(raw) // 4
+            return list(struct.unpack(f'{n}f', raw))
+        # Legacy JSON format written by older versions
+        return json.loads(raw)
+
+    def _row_to_chunk(self, row) -> MemoryChunk:
+        """Convert database row to MemoryChunk"""
+        return MemoryChunk(
+            id=row['id'],
+            user_id=row['user_id'],
+            scope=row['scope'],
+            source=row['source'],
+            path=row['path'],
+            start_line=row['start_line'],
+            end_line=row['end_line'],
+            text=row['text'],
+            embedding=self._decode_embedding(row['embedding']),
+            hash=row['hash'],
+            metadata=json.loads(row['metadata']) if row['metadata'] else None
+        )
+    
+    @staticmethod
+    def _contains_cjk(text: str) -> bool:
+        """Check if text contains CJK or related characters (Chinese, Japanese, Korean)."""
+        return bool(_RE_CONTAINS_CJK.search(text))
+    
+    @staticmethod
+    def _build_trigram_query(raw_query: str) -> Optional[str]:
+        """
+        Build FTS5 MATCH query for the trigram tokenizer.
+        Extracts CJK sequences (including single characters) and ASCII words,
+        joining them with AND so all terms must appear in the matched chunk.
+        """
+        tokens = _RE_TRIGRAM_TOKENS.findall(raw_query)
+        tokens = [t for t in tokens if t]
+        if not tokens:
+            return None
+        # Escape embedded double-quotes (FTS5 uses "" inside quoted phrases)
+        quoted = [f'"{t.replace(chr(34), chr(34)*2)}"' for t in tokens]
+        return ' AND '.join(quoted)
+
+    def _search_fts5_trigram(
+        self,
+        query: str,
+        user_id: Optional[str],
+        scopes: List[str],
+        limit: int
+    ) -> List[SearchResult]:
+        """Trigram FTS5 search — handles CJK and mixed queries with BM25 ranking."""
+        trigram_query = self._build_trigram_query(query)
+        if not trigram_query:
+            return []
+
+        scope_placeholders = ','.join('?' * len(scopes))
+        params = [trigram_query] + list(scopes)
+
+        if user_id:
+            sql = f"""
+                SELECT chunks.*, bm25(chunks_fts_trigram) as rank
+                FROM chunks_fts_trigram
+                JOIN chunks ON chunks.rowid = chunks_fts_trigram.rowid
+                WHERE chunks_fts_trigram MATCH ?
+                AND chunks.scope IN ({scope_placeholders})
+                AND (chunks.scope = 'shared' OR chunks.user_id = ?)
+                ORDER BY rank
+                LIMIT ?
+            """
+            params.extend([user_id, limit])
+        else:
+            sql = f"""
+                SELECT chunks.*, bm25(chunks_fts_trigram) as rank
+                FROM chunks_fts_trigram
+                JOIN chunks ON chunks.rowid = chunks_fts_trigram.rowid
+                WHERE chunks_fts_trigram MATCH ?
+                AND chunks.scope IN ({scope_placeholders})
+                ORDER BY rank
+                LIMIT ?
+            """
+            params.append(limit)
+
+        try:
+            rows = self.conn.execute(sql, params).fetchall()
+            return [
+                SearchResult(
+                    path=row['path'],
+                    start_line=row['start_line'],
+                    end_line=row['end_line'],
+                    score=self._bm25_rank_to_score(row['rank']),
+                    snippet=self._truncate_text(row['text'], 500),
+                    source=row['source'],
+                    user_id=row['user_id']
+                )
+                for row in rows
+            ]
+        except Exception:
+            from common.log import logger
+            logger.warning("[MemoryStorage] _search_fts5_trigram failed, returning empty", exc_info=True)
+            return []
+
+    @staticmethod
+    def _build_fts_query(raw_query: str) -> Optional[str]:
+        """
+        Build FTS5 query from raw text
+        
+        Works best for English and word-based languages.
+        For CJK characters, LIKE search will be used as fallback.
+        """
+        # Extract words (primarily English words and numbers)
+        tokens = re.findall(r'[A-Za-z0-9_]+', raw_query)
+        if not tokens:
+            return None
+        
+        # Quote tokens for exact matching
+        quoted = [f'"{t}"' for t in tokens]
+        # Use OR for more flexible matching
+        return ' OR '.join(quoted)
+    
+    @staticmethod
+    def _bm25_rank_to_score(rank: float) -> float:
+        """Convert SQLite BM25 rank to a [0, 1) relevance score.
+
+        SQLite's bm25() returns a non-positive float (0 or negative).
+        More negative = more relevant.  max(0, rank) would clip every
+        negative value to 0, making every score 1/(1+0) = 1.0 and
+        destroying all ranking information.
+
+        abs(rank) / (1 + abs(rank)) maps the absolute relevance magnitude
+        to [0, 1): larger |rank| (stronger match) → score closer to 1.
+        """
+        if rank is None:
+            return 0.0
+        # Add a floor of 0.3 so any FTS5 match always exceeds typical
+        # min_score thresholds (default 0.1).  Small-corpus ranks close to
+        # 0 would otherwise produce score≈0 and be filtered out downstream.
+        return 0.3 + 0.69 * (abs(rank) / (1.0 + abs(rank)))
+    
+    @staticmethod
+    def _truncate_text(text: str, max_chars: int) -> str:
+        """Truncate text to max characters"""
+        if len(text) <= max_chars:
+            return text
+        return text[:max_chars] + "..."
+    
+    @staticmethod
+    def compute_hash(content: str) -> str:
+        """Compute SHA256 hash of content"""
+        return hashlib.sha256(content.encode('utf-8')).hexdigest()
diff --git a/agent/memory/summarizer.py b/agent/memory/summarizer.py
new file mode 100644
index 0000000..49f47ad
--- /dev/null
+++ b/agent/memory/summarizer.py
@@ -0,0 +1,857 @@
+"""
+Memory flush manager with Deep Dream distillation
+
+Handles memory persistence when conversation context is trimmed or overflows:
+- Uses LLM to summarize discarded messages into concise daily records
+- Writes to daily memory files (lazy creation)
+- Deduplicates trim flushes to avoid repeated writes
+- Runs summarization asynchronously to avoid blocking normal replies
+- Deep Dream: periodically distills daily memories → refined MEMORY.md + dream diary
+"""
+
+import threading
+from typing import Optional, Callable, Any, List, Dict
+from pathlib import Path
+from datetime import datetime
+from common.log import logger
+
+
+SUMMARIZE_SYSTEM_PROMPT_ZH = """你是一个对话记录助手。请将对话内容归纳为当天的日常记录。
+
+## 要求
+
+按「事件」维度归纳发生的事，不要按对话轮次逐条记录：
+- 每条一行，用 "- " 开头
+- 合并同一件事的多轮对话
+- 只记录有意义的事件，忽略闲聊和问候
+- 保留关键的决策、结论和待办事项
+
+当对话没有任何记录价值（仅含问候或无意义内容），直接回复"无"。"""
+
+SUMMARIZE_SYSTEM_PROMPT_EN = """You are a conversation-logging assistant. Summarize the conversation into a daily record.
+
+## Requirements
+
+Summarize by "event", not turn by turn:
+- One item per line, starting with "- "
+- Merge multiple turns about the same thing
+- Only record meaningful events; ignore small talk and greetings
+- Keep key decisions, conclusions and to-dos
+
+If the conversation has no record value (only greetings or meaningless content), reply with exactly "None"."""
+
+SUMMARIZE_USER_PROMPT_ZH = """请归纳以下对话的日常记录：
+
+{conversation}"""
+
+SUMMARIZE_USER_PROMPT_EN = """Summarize the daily record of the following conversation:
+
+{conversation}"""
+
+# ---------------------------------------------------------------------------
+# Deep Dream prompts — distill daily memories → MEMORY.md + dream diary
+# ---------------------------------------------------------------------------
+
+DREAM_SYSTEM_PROMPT_ZH = """你是一个记忆整理助手，负责定期整理用户的长期记忆。
+
+你将收到两份材料：
+1. **当前长期记忆** — MEMORY.md 的全部现有内容
+2. **今日日记** — 当天的日常记录
+
+MEMORY.md 会注入每次对话的系统提示词中，因此必须保持精炼，只存放有价值和值得记忆的内容。
+
+**重要：只能基于提供的材料进行整理，严禁编造、推测或添加材料中不存在的信息。**
+
+## 任务
+
+### Part 1: 更新后的长期记忆（[MEMORY]）
+
+在现有记忆基础上进行整理和提炼，输出完整的更新后内容：
+- **合并提炼**：将含义相近的多条合并为一条高密度表述，而非简单罗列
+- **新增萃取**：从今日日记中提取值得永久记住的新信息（偏好、决策、人物、规则、经验）
+- **冲突更新**：当新信息与旧条目矛盾时，以新信息为准，替换旧条目
+- **清理无效**：删除临时性记录、空白条目、格式残留、无意义、重复内容等
+- **删除冗余**：已被更精炼表述涵盖的旧条目应删除，避免信息重复
+- 每条一行，用 "- " 开头，不带日期前缀
+- 可用 "## 标题" 对相关条目分组，使结构更清晰
+- 目标：控制在 50 条以内，每条尽量一句话概括
+
+### Part 2: 梦境日记（[DREAM]）
+
+用简洁的叙事风格写一篇短日记，记录这次整理的发现，保持格式美观易读：
+- 发现了哪些重复或矛盾
+- 从日记中提取了什么新洞察
+- 做了哪些清理和优化
+- 整体感受和观察
+
+## 输出格式（严格遵守）
+
+```
+[MEMORY]
+- 记忆条目1
+- 记忆条目2
+...
+
+[DREAM]
+梦境日记内容...
+```"""
+
+DREAM_SYSTEM_PROMPT_EN = """You are a memory-curation assistant that periodically organizes the user's long-term memory.
+
+You will receive two inputs:
+1. **Current long-term memory** — the full existing content of MEMORY.md
+2. **Today's diary** — the daily records
+
+MEMORY.md is injected into the system prompt of every conversation, so it must stay concise and hold only valuable, memory-worthy content.
+
+**Important: organize strictly based on the provided material. Never fabricate, infer, or add information not present in it.**
+
+## Tasks
+
+### Part 1: Updated long-term memory ([MEMORY])
+
+Organize and distill on top of the existing memory, and output the complete updated content:
+- **Merge & distill**: combine semantically similar items into one dense statement rather than listing them
+- **Extract new**: pull memory-worthy new info from today's diary (preferences, decisions, people, rules, lessons)
+- **Resolve conflicts**: when new info contradicts an old item, prefer the new and replace the old
+- **Clean invalid**: remove temporary notes, blank items, formatting residue, meaningless or duplicate content
+- **Drop redundancy**: delete old items already covered by a more concise statement
+- One item per line, starting with "- ", without a date prefix
+- You may group related items under "## headings" for clarity
+- Goal: keep under 50 items, each ideally a single sentence
+
+### Part 2: Dream diary ([DREAM])
+
+Write a short diary in a concise narrative style recording what this curation found, keep it clean and readable:
+- Which duplicates or conflicts were found
+- What new insights were extracted from the diary
+- What cleanup and optimization was done
+- Overall feelings and observations
+
+## Output format (follow strictly)
+
+```
+[MEMORY]
+- memory item 1
+- memory item 2
+...
+
+[DREAM]
+dream diary content...
+```"""
+
+DREAM_USER_PROMPT_ZH = """## 当前长期记忆（MEMORY.md）
+
+{memory_content}
+
+## 近期日记（最近 {days} 天）
+
+{daily_content}"""
+
+DREAM_USER_PROMPT_EN = """## Current long-term memory (MEMORY.md)
+
+{memory_content}
+
+## Recent diary (last {days} days)
+
+{daily_content}"""
+
+
+def _is_en() -> bool:
+    """True when the resolved UI language is English."""
+    try:
+        from common import i18n
+        return i18n.get_language() == "en"
+    except Exception:
+        return False
+
+
+def _summarize_system_prompt() -> str:
+    return SUMMARIZE_SYSTEM_PROMPT_EN if _is_en() else SUMMARIZE_SYSTEM_PROMPT_ZH
+
+
+def _summarize_user_prompt() -> str:
+    return SUMMARIZE_USER_PROMPT_EN if _is_en() else SUMMARIZE_USER_PROMPT_ZH
+
+
+def _dream_system_prompt() -> str:
+    return DREAM_SYSTEM_PROMPT_EN if _is_en() else DREAM_SYSTEM_PROMPT_ZH
+
+
+def _dream_user_prompt() -> str:
+    return DREAM_USER_PROMPT_EN if _is_en() else DREAM_USER_PROMPT_ZH
+
+
+def _is_empty_sentinel(text: str) -> bool:
+    """Match the "no record value" sentinel in both zh ("无") and en ("None")."""
+    if not text:
+        return True
+    s = text.strip()
+    return s == "" or s == "无" or s.lower() == "none"
+
+
+
+class MemoryFlushManager:
+    """
+    Manages memory flush operations.
+    
+    Flush is triggered by agent_stream in two scenarios:
+    1. Context trim: _trim_messages discards old turns → flush discarded content
+    2. Context overflow: API rejects request → emergency flush before clearing
+    
+    Additionally, create_daily_summary() can be called by scheduler for end-of-day summaries.
+    """
+    
+    def __init__(
+        self,
+        workspace_dir: Path,
+        llm_model: Optional[Any] = None,
+    ):
+        self.workspace_dir = workspace_dir
+        self.llm_model = llm_model
+        
+        self.memory_dir = workspace_dir / "memory"
+        self.memory_dir.mkdir(parents=True, exist_ok=True)
+        
+        self.last_flush_timestamp: Optional[datetime] = None
+        self._trim_flushed_hashes: set = set()  # Content hashes of already-flushed messages
+        self._last_flushed_content_hash: str = ""  # Content hash at last flush, for daily dedup
+        self._last_dream_input_hash: str = ""  # "{date}:{daily_hash}" of last dream, for dedup
+        self._last_flush_thread: Optional[threading.Thread] = None
+    
+    def get_today_memory_file(self, user_id: Optional[str] = None, ensure_exists: bool = False) -> Path:
+        """Get today's memory file path: memory/YYYY-MM-DD.md"""
+        today = datetime.now().strftime("%Y-%m-%d")
+        
+        if user_id:
+            user_dir = self.memory_dir / "users" / user_id
+            if ensure_exists:
+                user_dir.mkdir(parents=True, exist_ok=True)
+            today_file = user_dir / f"{today}.md"
+        else:
+            today_file = self.memory_dir / f"{today}.md"
+        
+        if ensure_exists and not today_file.exists():
+            today_file.parent.mkdir(parents=True, exist_ok=True)
+            today_file.write_text(f"# Daily Memory: {today}\n\n")
+        
+        return today_file
+    
+    def get_main_memory_file(self, user_id: Optional[str] = None) -> Path:
+        """Get main memory file path: MEMORY.md (workspace root)"""
+        if user_id:
+            user_dir = self.memory_dir / "users" / user_id
+            user_dir.mkdir(parents=True, exist_ok=True)
+            return user_dir / "MEMORY.md"
+        else:
+            return Path(self.workspace_dir) / "MEMORY.md"
+    
+    def get_status(self) -> dict:
+        return {
+            'last_flush_time': self.last_flush_timestamp.isoformat() if self.last_flush_timestamp else None,
+            'today_file': str(self.get_today_memory_file()),
+            'main_file': str(self.get_main_memory_file())
+        }
+
+    # ---- Flush execution (called by agent_stream or scheduler) ----
+    
+    def flush_from_messages(
+        self,
+        messages: List[Dict],
+        user_id: Optional[str] = None,
+        reason: str = "trim",
+        max_messages: int = 0,
+        context_summary_callback: Optional[Callable[[str], None]] = None,
+    ) -> bool:
+        """
+        Asynchronously summarize and flush messages to daily memory.
+
+        Deduplication runs synchronously, then LLM summarization + file write
+        run in a background thread so the main reply flow is never blocked.
+
+        If *context_summary_callback* is provided, it is called with the
+        [DAILY] portion of the LLM summary once available. The caller can use
+        this to inject the summary into the live message list for context
+        continuity — one LLM call serves both disk persistence and in-context
+        injection.
+        """
+        try:
+            # Strip scheduler-injected pairs before any further processing.
+            # These messages already serve as short-term context inside the
+            # receiver session; promoting them into long-term daily memory
+            # produces low-value flat logs (e.g. "11:28 price=1013, normal /
+            # 11:58 price=1013, normal / ...") and wastes summarisation tokens.
+            messages = self._strip_scheduler_pairs(messages)
+            if not messages:
+                return False
+
+            import hashlib
+            deduped = []
+            for m in messages:
+                text = self._extract_text_from_content(m.get("content", ""))
+                if not text or not text.strip():
+                    continue
+                h = hashlib.md5(text.encode("utf-8")).hexdigest()
+                if h not in self._trim_flushed_hashes:
+                    self._trim_flushed_hashes.add(h)
+                    deduped.append(m)
+            if not deduped:
+                return False
+
+            import copy
+            snapshot = copy.deepcopy(deduped)
+            thread = threading.Thread(
+                target=self._flush_worker,
+                args=(snapshot, user_id, reason, max_messages, context_summary_callback),
+                daemon=True,
+            )
+            thread.start()
+            logger.info(f"[MemoryFlush] Async flush dispatched (reason={reason}, msgs={len(snapshot)})")
+            self._last_flush_thread = thread
+            return True
+
+        except Exception as e:
+            logger.warning(f"[MemoryFlush] Failed to dispatch flush (reason={reason}): {e}")
+            return False
+
+    def _flush_worker(
+        self,
+        messages: List[Dict],
+        user_id: Optional[str],
+        reason: str,
+        max_messages: int,
+        context_summary_callback: Optional[Callable[[str], None]] = None,
+    ):
+        """Background worker: summarize with LLM, write daily memory file."""
+        try:
+            raw_summary = self._summarize_messages(messages, max_messages)
+            if _is_empty_sentinel(raw_summary):
+                logger.info(f"[MemoryFlush] No valuable content to flush (reason={reason})")
+                return
+
+            # Strip legacy [DAILY]/[MEMORY] markers if model still outputs them
+            daily_part = self._clean_summary_output(raw_summary)
+            if not daily_part:
+                return
+
+            # --- Write daily memory ---
+            daily_file = ensure_daily_memory_file(self.workspace_dir, user_id)
+
+            headers = {
+                "overflow": f"## Context Overflow Recovery ({datetime.now().strftime('%H:%M')})",
+                "trim": f"## Trimmed Context ({datetime.now().strftime('%H:%M')})",
+                "daily_summary": f"## Daily Summary ({datetime.now().strftime('%H:%M')})",
+            }
+            header = headers.get(reason, f"## Session Notes ({datetime.now().strftime('%H:%M')})")
+
+            with open(daily_file, "a", encoding="utf-8") as f:
+                f.write(f"\n{header}\n\n{daily_part}\n")
+
+            logger.info(f"[MemoryFlush] Wrote daily memory to {daily_file.name} (reason={reason}, chars={len(daily_part)})")
+
+            # --- Inject context summary into live messages (if callback provided) ---
+            if context_summary_callback:
+                try:
+                    context_summary_callback(daily_part)
+                except Exception as e:
+                    logger.warning(f"[MemoryFlush] Context summary callback failed: {e}")
+
+            self.last_flush_timestamp = datetime.now()
+
+        except Exception as e:
+            logger.warning(f"[MemoryFlush] Async flush failed (reason={reason}): {e}")
+
+    @staticmethod
+    def _clean_summary_output(raw: str) -> str:
+        """Strip legacy [DAILY]/[MEMORY] markers if present, return clean daily text."""
+        raw = raw.strip()
+        if _is_empty_sentinel(raw):
+            return ""
+
+        # Strip [DAILY] marker
+        if "[DAILY]" in raw:
+            start = raw.index("[DAILY]") + len("[DAILY]")
+            end = raw.index("[MEMORY]") if "[MEMORY]" in raw else len(raw)
+            raw = raw[start:end].strip()
+
+        # Remove stray [MEMORY] section entirely
+        if "[MEMORY]" in raw:
+            raw = raw[:raw.index("[MEMORY]")].strip()
+
+        # Remove markdown code fences
+        raw = raw.replace("```", "").strip()
+
+        return raw
+
+    def create_daily_summary(
+        self,
+        messages: List[Dict],
+        user_id: Optional[str] = None
+    ) -> bool:
+        """
+        Generate end-of-day summary. Called by daily timer.
+        Skips if messages haven't changed since last flush.
+        """
+        import hashlib
+        content = "".join(
+            self._extract_text_from_content(m.get("content", ""))
+            for m in messages
+        )
+        content_hash = hashlib.md5(content.encode("utf-8")).hexdigest()
+        if content_hash == self._last_flushed_content_hash:
+            logger.debug("[MemoryFlush] Daily summary skipped: no new content since last flush")
+            return False
+        self._last_flushed_content_hash = content_hash
+        return self.flush_from_messages(
+            messages=messages,
+            user_id=user_id,
+            reason="daily_summary",
+            max_messages=0,
+        )
+
+    # ---- Deep Dream (memory distillation) ----
+
+    def deep_dream(self, user_id: Optional[str] = None, lookback_days: int = 1, force: bool = False) -> bool:
+        """
+        Distill recent daily memories into MEMORY.md and generate a dream diary.
+
+        Args:
+            lookback_days: How many days of daily files to read (default 1 for scheduled, 3 for manual)
+            force: Skip input-hash dedup check (used by manual /memory dream trigger)
+        """
+        # Config guard for scheduled runs. Manual trigger (force=True) always
+        # runs since it is an explicit user action.
+        if not force:
+            try:
+                from config import conf
+                if not conf().get("deep_dream_enabled", True):
+                    logger.info("[DeepDream] deep_dream_enabled=false, skipping")
+                    return False
+            except Exception:
+                pass
+
+        if not self.llm_model:
+            logger.warning("[DeepDream] No LLM model available, skipping")
+            return False
+
+        logger.info(f"[DeepDream] Starting memory distillation (lookback={lookback_days} days)")
+
+        # Collect materials
+        memory_content = self._read_main_memory(user_id)
+        daily_content, has_content = self._read_recent_dailies(user_id, lookback_days)
+
+        if not has_content:
+            logger.info("[DeepDream] No recent daily records, skipping to preserve existing MEMORY.md")
+            return False
+
+        # Dedup: skip if same daily content already dreamed today.
+        # Note: only hash daily_content (not memory_content), because deep_dream
+        # itself rewrites MEMORY.md as a side effect, which would otherwise
+        # invalidate the hash on every subsequent call within the same window.
+        import hashlib
+        daily_hash = hashlib.md5(daily_content.encode("utf-8")).hexdigest()
+        today_str = datetime.now().strftime("%Y-%m-%d")
+        dedup_key = f"{today_str}:{daily_hash}"
+        if not force and dedup_key == self._last_dream_input_hash:
+            logger.info("[DeepDream] Already dreamed today with same daily content, skipping")
+            return False
+        self._last_dream_input_hash = dedup_key
+
+        logger.info(
+            f"[DeepDream] Materials collected: "
+            f"MEMORY.md={len(memory_content)} chars, "
+            f"daily={len(daily_content)} chars"
+        )
+
+        # Call LLM for distillation
+        import time as _time
+        t0 = _time.monotonic()
+        try:
+            user_msg = _dream_user_prompt().format(
+                memory_content=memory_content or "(empty)",
+                days=lookback_days,
+                daily_content=daily_content or "(no recent daily records)",
+            )
+            from agent.protocol.models import LLMRequest
+            # No output cap: the prompt already keeps MEMORY.md concise (~50
+            # items), so a hard max_tokens would only risk truncating a large
+            # rewrite. Let the model use its default output budget.
+            request = LLMRequest(
+                messages=[{"role": "user", "content": user_msg}],
+                temperature=0.3,
+                stream=False,
+                system=_dream_system_prompt(),
+            )
+            response = self.llm_model.call(request)
+            raw = self._extract_response_text(response)
+            elapsed = _time.monotonic() - t0
+            if not raw or not raw.strip():
+                logger.warning(f"[DeepDream] LLM returned empty response ({elapsed:.1f}s)")
+                return False
+            logger.info(f"[DeepDream] LLM distillation completed ({elapsed:.1f}s, {len(raw)} chars)")
+        except Exception as e:
+            elapsed = _time.monotonic() - t0
+            logger.warning(f"[DeepDream] LLM call failed ({elapsed:.1f}s): {e}")
+            return False
+
+        # Parse [MEMORY] and [DREAM] sections
+        new_memory, dream_diary = self._parse_dream_output(raw)
+
+        if not new_memory:
+            logger.warning("[DeepDream] No [MEMORY] section in LLM output, skipping overwrite")
+            return False
+
+        # Overwrite MEMORY.md
+        try:
+            main_file = self.get_main_memory_file(user_id)
+            old_size = len(memory_content)
+            main_file.write_text(new_memory + "\n", encoding="utf-8")
+            logger.info(
+                f"[DeepDream] Updated MEMORY.md "
+                f"({old_size} → {len(new_memory)} chars)"
+            )
+        except Exception as e:
+            logger.warning(f"[DeepDream] Failed to write MEMORY.md: {e}")
+            return False
+
+        # Write dream diary
+        if dream_diary:
+            try:
+                self._write_dream_diary(dream_diary, user_id)
+            except Exception as e:
+                logger.warning(f"[DeepDream] Failed to write dream diary: {e}")
+
+        logger.info("[DeepDream] ✅ Deep Dream completed successfully")
+        return True
+
+    def _read_main_memory(self, user_id: Optional[str] = None) -> str:
+        """Read current MEMORY.md content."""
+        main_file = self.get_main_memory_file(user_id)
+        if main_file.exists():
+            return main_file.read_text(encoding="utf-8").strip()
+        return ""
+
+    def _read_recent_dailies(
+        self, user_id: Optional[str] = None, lookback_days: int = 1
+    ) -> tuple:
+        """
+        Read recent daily memory files.
+
+        Returns:
+            (combined_text, has_content) tuple
+        """
+        from datetime import timedelta
+
+        parts = []
+        has_content = False
+        today = datetime.now().date()
+
+        for offset in range(lookback_days):
+            day = today - timedelta(days=offset)
+            date_str = day.strftime("%Y-%m-%d")
+            if user_id:
+                daily_file = self.memory_dir / "users" / user_id / f"{date_str}.md"
+            else:
+                daily_file = self.memory_dir / f"{date_str}.md"
+
+            if daily_file.exists():
+                content = daily_file.read_text(encoding="utf-8").strip()
+                if content:
+                    parts.append(f"### {date_str}\n\n{content}")
+                    has_content = True
+            else:
+                parts.append(f"### {date_str}\n\n(no records)")
+
+        return "\n\n".join(parts), has_content
+
+    @staticmethod
+    def _parse_dream_output(raw: str) -> tuple:
+        """Parse LLM output into (new_memory, dream_diary)."""
+        raw = raw.strip().replace("```", "")
+        new_memory = ""
+        dream_diary = ""
+
+        if "[MEMORY]" in raw:
+            start = raw.index("[MEMORY]") + len("[MEMORY]")
+            end = raw.index("[DREAM]") if "[DREAM]" in raw else len(raw)
+            new_memory = raw[start:end].strip()
+
+        if "[DREAM]" in raw:
+            start = raw.index("[DREAM]") + len("[DREAM]")
+            dream_diary = raw[start:].strip()
+
+        return new_memory, dream_diary
+
+    def _write_dream_diary(self, content: str, user_id: Optional[str] = None):
+        """Write dream diary to memory/dreams/YYYY-MM-DD.md."""
+        dreams_dir = self.memory_dir / "dreams"
+        if user_id:
+            dreams_dir = self.memory_dir / "users" / user_id / "dreams"
+        dreams_dir.mkdir(parents=True, exist_ok=True)
+
+        today = datetime.now().strftime("%Y-%m-%d")
+        diary_file = dreams_dir / f"{today}.md"
+        diary_file.write_text(
+            f"# Dream Diary: {today}\n\n{content}\n",
+            encoding="utf-8",
+        )
+        logger.info(f"[DeepDream] Wrote dream diary to {diary_file}")
+
+    # ---- Internal helpers ----
+    
+    def _summarize_messages(self, messages: List[Dict], max_messages: int = 0) -> str:
+        """
+        Summarize conversation messages using LLM.
+        Returns empty string if LLM deems content not worth recording.
+        Rule-based fallback only used when LLM call raises an exception.
+        """
+        conversation_text = self._format_conversation_for_summary(messages, max_messages)
+        if not conversation_text.strip():
+            return ""
+        
+        if self.llm_model:
+            try:
+                summary = self._call_llm_for_summary(conversation_text)
+                if not _is_empty_sentinel(summary):
+                    return summary.strip()
+                logger.info("[MemoryFlush] LLM returned empty sentinel, skipping write")
+                return ""
+            except Exception as e:
+                logger.warning(f"[MemoryFlush] LLM summarization failed, using fallback: {e}")
+                return self._extract_summary_fallback(messages, max_messages)
+        else:
+            logger.info("[MemoryFlush] No LLM model available, using rule-based fallback")
+            return self._extract_summary_fallback(messages, max_messages)
+
+    def _format_conversation_for_summary(self, messages: List[Dict], max_messages: int = 0) -> str:
+        """Format messages into readable conversation text for LLM summarization."""
+        msgs = messages if max_messages == 0 else messages[-max_messages * 2:]
+        lines = []
+        for msg in msgs:
+            role = msg.get("role", "")
+            text = self._extract_text_from_content(msg.get("content", ""))
+            if not text or not text.strip():
+                continue
+            text = text.strip()
+            if role == "user":
+                lines.append(f"用户: {text[:500]}")
+            elif role == "assistant":
+                lines.append(f"助手: {text[:500]}")
+        return "\n".join(lines)
+
+    @staticmethod
+    def _extract_response_text(response) -> str:
+        """
+        Extract text from LLM response regardless of format.
+
+        Handles:
+        - Generator (MiniMax _handle_sync_response yields Claude-format dicts)
+        - Claude format: {"role":"assistant","content":[{"type":"text","text":"..."}]}
+        - OpenAI format: {"choices":[{"message":{"content":"..."}}]}
+        - OpenAI SDK response object with .choices attribute
+        """
+        import types
+
+        # Unwrap generator — consume first yielded item
+        if isinstance(response, types.GeneratorType):
+            try:
+                response = next(response)
+            except StopIteration:
+                return ""
+
+        if not response:
+            return ""
+
+        if isinstance(response, dict):
+            # Check for error
+            if response.get("error"):
+                raise RuntimeError(response.get("message", "LLM call failed"))
+
+            # Claude format: content is a list of blocks
+            content = response.get("content")
+            if isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict) and block.get("type") == "text":
+                        return block.get("text", "")
+
+            # OpenAI format
+            choices = response.get("choices", [])
+            if choices:
+                return choices[0].get("message", {}).get("content", "")
+
+        # OpenAI SDK response object
+        if hasattr(response, "choices") and response.choices:
+            return response.choices[0].message.content or ""
+
+        return ""
+
+    def _call_llm_for_summary(self, conversation_text: str) -> str:
+        """Call LLM to generate a concise summary of the conversation."""
+        from agent.protocol.models import LLMRequest
+        
+        request = LLMRequest(
+            messages=[{"role": "user", "content": _summarize_user_prompt().format(conversation=conversation_text)}],
+            temperature=0,
+            max_tokens=500,
+            stream=False,
+            system=_summarize_system_prompt(),
+        )
+        
+        response = self.llm_model.call(request)
+        return self._extract_response_text(response)
+
+    @staticmethod
+    def _extract_first_meaningful_line(text: str, max_len: int = 120) -> str:
+        """Extract the first meaningful line from assistant reply, skipping markdown noise."""
+        import re
+        for line in text.split("\n"):
+            line = line.strip()
+            if not line:
+                continue
+            # Skip markdown headings, horizontal rules, code fences, pure emoji/symbols
+            if re.match(r'^(#{1,4}\s|```|---|\*\*\*|[-*]\s*$|[^\w\u4e00-\u9fff]{1,5}$)', line):
+                continue
+            # Strip leading markdown bold/emoji decorations
+            cleaned = re.sub(r'^[\*#>\-\s]+', '', line).strip()
+            cleaned = re.sub(r'^[\U0001f300-\U0001f9ff\u2600-\u27bf\s]+', '', cleaned).strip()
+            if len(cleaned) >= 5:
+                return cleaned[:max_len]
+        return text.split("\n")[0].strip()[:max_len]
+
+    @staticmethod
+    def _extract_summary_fallback(messages: List[Dict], max_messages: int = 0) -> str:
+        """
+        Rule-based summary of discarded messages.
+        Format: "用户问了X; 助手回答了Y" per event, compact and readable.
+        """
+        msgs = messages if max_messages == 0 else messages[-max_messages * 2:]
+
+        events: List[str] = []
+        current_user_text = ""
+        for msg in msgs:
+            role = msg.get("role", "")
+            text = MemoryFlushManager._extract_text_from_content(msg.get("content", ""))
+            if not text or not text.strip():
+                continue
+            text = text.strip()
+
+            if role == "user":
+                if len(text) <= 3:
+                    continue
+                current_user_text = text[:120]
+            elif role == "assistant" and current_user_text:
+                reply_summary = MemoryFlushManager._extract_first_meaningful_line(text)
+                if reply_summary:
+                    events.append(f"- 用户: {current_user_text} → 回复: {reply_summary}")
+                else:
+                    events.append(f"- 用户: {current_user_text}")
+                current_user_text = ""
+
+        if current_user_text:
+            events.append(f"- 用户: {current_user_text}")
+
+        return "\n".join(events[:10])
+    
+    @staticmethod
+    def _extract_text_from_content(content) -> str:
+        """Extract plain text from message content (string or content blocks)."""
+        if isinstance(content, str):
+            return content
+        if isinstance(content, list):
+            parts = []
+            for block in content:
+                if isinstance(block, dict) and block.get("type") == "text":
+                    parts.append(block.get("text", ""))
+                elif isinstance(block, str):
+                    parts.append(block)
+            return "\n".join(parts)
+        return ""
+
+    @classmethod
+    def _strip_scheduler_pairs(cls, messages: List[Dict]) -> List[Dict]:
+        """Drop scheduler-injected user/assistant pairs from a flush batch.
+
+        A scheduler user message starts with the ``[SCHEDULED]`` marker
+        (written by ``AgentBridge.remember_scheduled_output``); the message
+        immediately following it (if it is an assistant turn) is its paired
+        output and is dropped together. Regular user/assistant turns and
+        any tool_use / tool_result blocks are preserved as-is.
+        """
+        if not messages:
+            return messages
+
+        SCHEDULED_PREFIX = "[SCHEDULED]"
+        result = []
+        skip_next_assistant = False
+        for msg in messages:
+            if not isinstance(msg, dict):
+                result.append(msg)
+                skip_next_assistant = False
+                continue
+            role = msg.get("role")
+            if skip_next_assistant and role == "assistant":
+                skip_next_assistant = False
+                continue
+            skip_next_assistant = False
+            if role == "user":
+                text = cls._extract_text_from_content(msg.get("content", ""))
+                if text.lstrip().startswith(SCHEDULED_PREFIX):
+                    skip_next_assistant = True
+                    continue
+            result.append(msg)
+        return result
+
+
+def create_memory_files_if_needed(workspace_dir: Path, user_id: Optional[str] = None):
+    """
+    Create essential memory files if they don't exist.
+    Only creates MEMORY.md; daily files are created lazily on first write.
+    
+    Args:
+        workspace_dir: Workspace directory
+        user_id: Optional user ID for user-specific files
+    """
+    memory_dir = workspace_dir / "memory"
+    memory_dir.mkdir(parents=True, exist_ok=True)
+    
+    # Create main MEMORY.md in workspace root (always needed for bootstrap)
+    if user_id:
+        user_dir = memory_dir / "users" / user_id
+        user_dir.mkdir(parents=True, exist_ok=True)
+        main_memory = user_dir / "MEMORY.md"
+    else:
+        main_memory = Path(workspace_dir) / "MEMORY.md"
+    
+    if not main_memory.exists():
+        main_memory.write_text("")
+
+
+def ensure_daily_memory_file(workspace_dir: Path, user_id: Optional[str] = None) -> Path:
+    """
+    Ensure today's daily memory file exists, creating it only when actually needed.
+    Called lazily before first write to daily memory.
+    
+    Args:
+        workspace_dir: Workspace directory
+        user_id: Optional user ID for user-specific files
+        
+    Returns:
+        Path to today's memory file
+    """
+    memory_dir = workspace_dir / "memory"
+    memory_dir.mkdir(parents=True, exist_ok=True)
+    
+    today = datetime.now().strftime("%Y-%m-%d")
+    if user_id:
+        user_dir = memory_dir / "users" / user_id
+        user_dir.mkdir(parents=True, exist_ok=True)
+        today_memory = user_dir / f"{today}.md"
+    else:
+        today_memory = memory_dir / f"{today}.md"
+    
+    if not today_memory.exists():
+        today_memory.write_text(
+            f"# Daily Memory: {today}\n\n"
+        )
+    
+    return today_memory
diff --git a/agent/prompt/__init__.py b/agent/prompt/__init__.py
new file mode 100644
index 0000000..29295e9
--- /dev/null
+++ b/agent/prompt/__init__.py
@@ -0,0 +1,13 @@
+"""
+Agent Prompt Module - 系统提示词构建模块
+"""
+
+from .builder import PromptBuilder, build_agent_system_prompt
+from .workspace import ensure_workspace, load_context_files
+
+__all__ = [
+    'PromptBuilder',
+    'build_agent_system_prompt',
+    'ensure_workspace',
+    'load_context_files',
+]
diff --git a/agent/prompt/builder.py b/agent/prompt/builder.py
new file mode 100644
index 0000000..538d715
--- /dev/null
+++ b/agent/prompt/builder.py
@@ -0,0 +1,760 @@
+"""
+System Prompt Builder - 系统提示词构建器
+
+实现模块化的系统提示词构建，支持工具、技能、记忆等多个子系统
+"""
+
+from __future__ import annotations
+import os
+from typing import List, Dict, Optional, Any
+from dataclasses import dataclass
+
+from common.log import logger
+from config import conf
+
+
+@dataclass
+class ContextFile:
+    """A context file (path + content)."""
+    path: str
+    content: str
+
+
+class PromptBuilder:
+    """System prompt builder."""
+    
+    def __init__(self, workspace_dir: str, language: str = "zh"):
+        """
+        初始化提示词构建器
+        
+        Args:
+            workspace_dir: 工作空间目录
+            language: 语言 ("zh" 或 "en")
+        """
+        self.workspace_dir = workspace_dir
+        self.language = language
+    
+    def build(
+        self,
+        base_persona: Optional[str] = None,
+        user_identity: Optional[Dict[str, str]] = None,
+        tools: Optional[List[Any]] = None,
+        context_files: Optional[List[ContextFile]] = None,
+        skill_manager: Any = None,
+        memory_manager: Any = None,
+        runtime_info: Optional[Dict[str, Any]] = None,
+        **kwargs
+    ) -> str:
+        """
+        构建完整的系统提示词
+        
+        Args:
+            base_persona: 基础人格描述（会被context_files中的AGENT.md覆盖）
+            user_identity: 用户身份信息
+            tools: 工具列表
+            context_files: 上下文文件列表（AGENT.md, USER.md, RULE.md, BOOTSTRAP.md等）
+            skill_manager: 技能管理器
+            memory_manager: 记忆管理器
+            runtime_info: 运行时信息
+            **kwargs: 其他参数
+            
+        Returns:
+            完整的系统提示词
+        """
+        return build_agent_system_prompt(
+            workspace_dir=self.workspace_dir,
+            language=self.language,
+            base_persona=base_persona,
+            user_identity=user_identity,
+            tools=tools,
+            context_files=context_files,
+            skill_manager=skill_manager,
+            memory_manager=memory_manager,
+            runtime_info=runtime_info,
+            **kwargs
+        )
+
+
+def build_agent_system_prompt(
+    workspace_dir: str,
+    language: str = "zh",
+    base_persona: Optional[str] = None,
+    user_identity: Optional[Dict[str, str]] = None,
+    tools: Optional[List[Any]] = None,
+    context_files: Optional[List[ContextFile]] = None,
+    skill_manager: Any = None,
+    memory_manager: Any = None,
+    runtime_info: Optional[Dict[str, Any]] = None,
+    **kwargs
+) -> str:
+    """
+    Build the agent system prompt.
+
+    Section order (by importance and logical flow):
+    1. Tooling - core capabilities, introduced first
+    2. Skills - right after tools, since skills are read via the read tool
+    3. Memory - memory recall and writing guidance
+    3.5 Knowledge - structured knowledge base (injects knowledge/index.md)
+    4. Workspace - working environment description
+    5. User identity - user info (optional)
+    6. Project context - AGENT.md, USER.md, RULE.md, MEMORY.md, BOOTSTRAP.md
+    7. Runtime info - meta info (time, model, etc.)
+
+    Args:
+        workspace_dir: workspace directory
+        language: language ("zh" or "en")
+        base_persona: base persona description (deprecated, defined by AGENT.md)
+        user_identity: user identity info
+        tools: tool list
+        context_files: context file list
+        skill_manager: skill manager
+        memory_manager: memory manager
+        runtime_info: runtime info
+        **kwargs: extra args
+
+    Returns:
+        The full system prompt.
+    """
+    sections = []
+
+    # 1. Tooling (most important, goes first)
+    if tools:
+        sections.extend(_build_tooling_section(tools, language))
+
+    # 2. Skills (right after tools, since they need the read tool)
+    if skill_manager:
+        sections.extend(_build_skills_section(skill_manager, tools, language))
+
+    # 3. Memory (standalone memory capability)
+    if memory_manager:
+        sections.extend(_build_memory_section(memory_manager, tools, language))
+
+    # 3.5 Knowledge (structured knowledge base)
+    if conf().get("knowledge", True):
+        sections.extend(_build_knowledge_section(workspace_dir, language))
+
+    # 4. Workspace (working environment description)
+    sections.extend(_build_workspace_section(workspace_dir, language))
+
+    # 5. User identity (if present)
+    if user_identity:
+        sections.extend(_build_user_identity_section(user_identity, language))
+
+    # 6. Project context files (AGENT.md, USER.md, RULE.md - define the persona)
+    if context_files:
+        sections.extend(_build_context_files_section(context_files, language))
+
+    # 7. Runtime info (meta info, goes last)
+    if runtime_info:
+        sections.extend(_build_runtime_section(runtime_info, language))
+
+    # 8. Response language (always appended, independent of the skeleton language)
+    sections.extend(_build_response_language_section(language))
+
+    return "\n".join(sections)
+
+
+def _build_response_language_section(language: str) -> List[str]:
+    """Response-language rule, appended regardless of the prompt skeleton language.
+
+    Keeps the agent's reply language aligned with the user's input by default,
+    so a Chinese-built prompt still answers an English user in English.
+    """
+    if language == "en":
+        return [
+            "## 🌐 Response language",
+            "",
+            "By default, reply in the same language as the user's input, "
+            "unless the user explicitly asks for another language.",
+            "",
+        ]
+    return [
+        "## 🌐 回复语言",
+        "",
+        "默认使用与用户输入相同的语言回复，除非用户明确要求使用其他语言。",
+        "",
+    ]
+
+
+def _build_identity_section(base_persona: Optional[str], language: str) -> List[str]:
+    """Base identity section - no longer needed, identity is defined by AGENT.md."""
+    # Identity is fully defined by AGENT.md, so emit nothing here.
+    return []
+
+
+def _build_tooling_section(tools: List[Any], language: str) -> List[str]:
+    """Build tooling section with concise tool list and call style guide."""
+    is_en = language == "en"
+    # One-line summaries for known tools (details are in the tool schema)
+    if is_en:
+        core_summaries = {
+            "read": "read file content",
+            "write": "create or overwrite a file",
+            "edit": "make precise edits to a file",
+            "ls": "list directory contents",
+            "grep": "search file contents",
+            "find": "find files by pattern",
+            "bash": "run shell commands",
+            "terminal": "manage background processes",
+            "web_search": "web search",
+            "web_fetch": "fetch URL content",
+            "browser": "control the browser (screenshot key results or send to the user when help is needed)",
+            "memory_search": "search memory",
+            "memory_get": "read memory content",
+            "env_config": "manage API keys and skill config",
+            "scheduler": "manage scheduled tasks and reminders",
+            "send": "send a local file to the user (local files only; put URLs directly in the reply text)",
+            "vision": "analyze images (recognition, description, OCR, etc.)",
+        }
+    else:
+        core_summaries = {
+            "read": "读取文件内容",
+            "write": "创建或覆盖文件",
+            "edit": "精确编辑文件",
+            "ls": "列出目录内容",
+            "grep": "搜索文件内容",
+            "find": "按模式查找文件",
+            "bash": "执行shell命令",
+            "terminal": "管理后台进程",
+            "web_search": "网络搜索",
+            "web_fetch": "获取URL内容",
+            "browser": "控制浏览器（关键结果或需要协助可截图发送给用户）",
+            "memory_search": "搜索记忆",
+            "memory_get": "读取记忆内容",
+            "env_config": "管理API密钥和技能配置",
+            "scheduler": "管理定时任务和提醒",
+            "send": "发送本地文件给用户（仅限本地文件，URL直接放在回复文本中）",
+            "vision": "分析图片内容（识别、描述、OCR文字提取等）",
+        }
+
+    # Preferred display order
+    tool_order = [
+        "read", "write", "edit", "ls", "grep", "find",
+        "bash", "terminal",
+        "web_search", "web_fetch", "browser",
+        "memory_search", "memory_get",
+        "env_config", "scheduler", "send", "vision",
+    ]
+
+    # Build name -> summary mapping for available tools
+    available = {}
+    for tool in tools:
+        name = tool.name if hasattr(tool, 'name') else str(tool)
+        available[name] = core_summaries.get(name, "")
+
+    # Generate tool lines: ordered tools first, then extras
+    tool_lines = []
+    for name in tool_order:
+        if name in available:
+            summary = available.pop(name)
+            tool_lines.append(f"- {name}: {summary}" if summary else f"- {name}")
+    for name in sorted(available):
+        summary = available[name]
+        tool_lines.append(f"- {name}: {summary}" if summary else f"- {name}")
+
+    if is_en:
+        lines = [
+            "## 🔧 Tooling",
+            "",
+            "Available tools (names are case-sensitive, call exactly as listed):",
+            "\n".join(tool_lines),
+            "",
+            "Tool-calling style:",
+            "",
+            "- For multi-step tasks, complex decisions or sensitive operations, briefly explain what you are doing and why, so the user follows key progress",
+            "- Keep going until the task is done, then report the result to the user",
+            "- Always redact secrets, tokens and other sensitive info in replies",
+            "- Put URLs directly in the reply text; the system handles and renders them. Don't download and re-send them via the send tool",
+            "",
+        ]
+    else:
+        lines = [
+            "## 🔧 工具系统",
+            "",
+            "可用工具（名称大小写敏感，严格按列表调用）:",
+            "\n".join(tool_lines),
+            "",
+            "工具调用风格：",
+            "",
+            "- 多步骤任务、复杂决策、敏感操作时，应简要说明当前在做什么、为什么这样做，让用户了解关键进展",
+            "- 持续推进直到任务完成，完成后向用户报告结果",
+            "- 回复中涉及密钥、令牌等敏感信息必须脱敏",
+            "- URL链接直接放在回复文本中即可，系统会自动处理和渲染。无需下载后使用send工具发送",
+            "",
+        ]
+
+    return lines
+
+
+def _build_skills_section(skill_manager: Any, tools: Optional[List[Any]], language: str) -> List[str]:
+    """Build the skills section."""
+    if not skill_manager:
+        return []
+    
+    # Resolve the read tool name
+    read_tool_name = "read"
+    if tools:
+        for tool in tools:
+            tool_name = tool.name if hasattr(tool, 'name') else str(tool)
+            if tool_name.lower() == "read":
+                read_tool_name = tool_name
+                break
+    
+    if language == "en":
+        lines = [
+            "## 🧩 Skills (mandatory)",
+            "",
+            "Before replying: scan the <description> of every skill in <available_skills> below.",
+            "",
+            f"- If a skill's description matches the user's need: use the `{read_tool_name}` tool to read the SKILL.md at its <location> path, then strictly follow the instructions in the file. "
+            "Prefer using a skill when one matches.",
+            "- If multiple skills apply, pick the best-matching one, then read and follow it.",
+            "- If no skill clearly applies: do not read any SKILL.md, just use the general tools.",
+            "",
+            f"**Important**: skills are not tools and cannot be called directly. The only way to use a skill is to read its SKILL.md with `{read_tool_name}`, then act on the file's content. "
+            "Never read multiple skills at once — only read one after selecting it.",
+            "",
+            "Available skills:"
+        ]
+    else:
+        lines = [
+            "## 🧩 技能系统（mandatory）",
+            "",
+            "在回复之前：扫描下方 <available_skills> 中每个技能的 <description>。",
+            "",
+            f"- 如果有技能的描述与用户需求匹配：使用 `{read_tool_name}` 工具读取其 <location> 路径的 SKILL.md 文件，然后严格遵循文件中的指令。"
+            "当有匹配的技能时，应优先使用技能",
+            "- 如果多个技能都适用则选择最匹配的一个，然后读取并遵循。",
+            "- 如果没有技能明确适用：不要读取任何 SKILL.md，直接使用通用工具。",
+            "",
+            f"**重要**: 技能不是工具，不能直接调用。使用技能的唯一方式是用 `{read_tool_name}` 读取 SKILL.md 文件，然后按文件内容操作。"
+            "永远不要一次性读取多个技能，只在选择后再读取。",
+            "",
+            "以下是可用技能："
+        ]
+    
+    # Append the skills list (built by skill_manager)
+    try:
+        skills_prompt = skill_manager.build_skills_prompt()
+        logger.debug(f"[PromptBuilder] Skills prompt length: {len(skills_prompt) if skills_prompt else 0}")
+        if skills_prompt:
+            lines.append(skills_prompt.strip())
+            lines.append("")
+        else:
+            logger.warning("[PromptBuilder] No skills prompt generated - skills_prompt is empty")
+    except Exception as e:
+        logger.warning(f"Failed to build skills prompt: {e}")
+        import traceback
+        logger.debug(f"Skills prompt error traceback: {traceback.format_exc()}")
+    
+    return lines
+
+
+def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], language: str) -> List[str]:
+    """Build the memory section."""
+    if not memory_manager:
+        return []
+
+    has_memory_tools = False
+    if tools:
+        tool_names = [tool.name if hasattr(tool, 'name') else str(tool) for tool in tools]
+        has_memory_tools = any(name in ['memory_search', 'memory_get'] for name in tool_names)
+
+    if not has_memory_tools:
+        return []
+
+    from datetime import datetime
+    today_file = datetime.now().strftime("%Y-%m-%d") + ".md"
+
+    if language == "en":
+        lines = [
+            "## 🧠 Memory",
+            "",
+            "### Memory Recall (mandatory)",
+            "",
+            "When the user asks about past events, references an earlier decision, mentions relationships, preferences or to-dos, or when you are unsure about something, **you must search memory before answering**.",
+            "No need to re-search if the info is already in MEMORY.md. Full content and daily memory must be retrieved via tools.",
+            "",
+            "1. Location unknown → `memory_search` (keyword / semantic search)",
+            "2. Location known → `memory_get` to read the exact lines",
+            "3. Search returns nothing → `memory_get` to read the last two days of memory",
+            "",
+            "**Memory file structure**:",
+            "- `MEMORY.md`: long-term memory index (already auto-loaded into context: core info, preferences, decisions, etc.)",
+            f"- `memory/YYYY-MM-DD.md`: daily memory; today is `memory/{today_file}`",
+            "- `knowledge/`: structured knowledge base (see the knowledge system below)",
+            "",
+            "### Writing memory",
+            "",
+            "In the following cases, **proactively** write info to memory files (no need to tell the user):",
+            "",
+            "- The user asks you to remember something, or uses words like \"remember\", \"from now on\", \"always\", \"never\", \"prefer\"",
+            "- The user shares important personal preferences, habits or decisions",
+            "- The conversation produces an important conclusion, plan or agreement",
+            "- A complex task is completed and the key steps and results are worth recording",
+            "",
+            "**Storage rules**:",
+            "- Long-term core info → `MEMORY.md`",
+            f"- Today's events/progress → `memory/{today_file}`",
+            "- Structured knowledge → `knowledge/` (see the knowledge system)",
+            "- Append → `edit` tool with empty oldText",
+            "- Modify → `edit` tool with oldText set to the text to replace",
+            "- **Never write sensitive info** (API keys, tokens, etc.)",
+            "",
+            "**Principle**: use memory naturally, as if you simply knew it; don't bring it up unless asked.",
+            "",
+        ]
+    else:
+        lines = [
+            "## 🧠 记忆系统",
+            "",
+            "### Memory Recall（mandatory）",
+            "",
+            "当用户询问过往事件、引用之前的决定、提到人物关系、偏好、待办、或你对某事不确定时，**必须先检索记忆再回答**。",
+            "如果 MEMORY.md 中已有相关信息则无需重复检索。完整内容和每日记忆需要通过工具检索。",
+            "",
+            "1. 不确定位置 → `memory_search` 关键词/语义检索",
+            "2. 已知位置 → `memory_get` 直接读取对应行",
+            "3. search 无结果 → `memory_get` 读最近两天记忆",
+            "",
+            "**记忆文件结构**:",
+            "- `MEMORY.md`: 长期记忆索引（已自动加载到上下文，核心信息、偏好、决策等）",
+            f"- `memory/YYYY-MM-DD.md`: 每日记忆，今天是 `memory/{today_file}`",
+            "- `knowledge/`: 结构化知识库（见下方知识系统）",
+            "",
+            "### 写入记忆",
+            "",
+            "遇到以下情况时，**主动**将信息写入记忆文件（无需告知用户）：",
+            "",
+            "- 用户要求记住某些信息，或使用了「记住」「以后」「总是」「不要」「偏好」等表达",
+            "- 用户分享了重要的个人偏好、习惯、决策",
+            "- 对话中产生了重要的结论、方案、约定",
+            "- 完成了复杂任务，值得记录关键步骤和结果",
+            "",
+            "**存储规则**:",
+            f"- 长期核心信息 → `MEMORY.md`",
+            f"- 当天事件/进展 → `memory/{today_file}`",
+            "- 结构化知识 → `knowledge/`（见知识系统）",
+            "- 追加 → `edit` 工具，oldText 留空",
+            "- 修改 → `edit` 工具，oldText 填写要替换的文本",
+            "- **禁止写入敏感信息**（API密钥、令牌等）",
+            "",
+            "**使用原则**: 自然使用记忆，就像你本来就知道；不用刻意提起，除非用户问起。",
+            "",
+        ]
+
+    return lines
+
+
+def _build_knowledge_section(workspace_dir: str, language: str) -> List[str]:
+    """Build knowledge wiki section. Injects knowledge/index.md when present."""
+    index_path = os.path.join(workspace_dir, "knowledge", "index.md")
+    if not os.path.exists(index_path):
+        return []
+
+    try:
+        with open(index_path, 'r', encoding='utf-8') as f:
+            index_content = f.read().strip()
+    except Exception:
+        return []
+
+    if language == "en":
+        lines = [
+            "## 📚 Knowledge",
+            "",
+            "You have a continuously growing personal knowledge base `knowledge/` — your long-term structured knowledge store.",
+            "",
+            "### Auto-write rules (mandatory)",
+            "",
+            "In the following cases you **must** write to the knowledge base alongside your reply, **directly, without asking the user**:",
+            "",
+            "1. **User shares an article / link / document** → after reading and understanding, write the key points to `knowledge/sources/<slug>.md` in the same turn",
+            "2. **An in-depth discussion produces a conclusion / plan** → organize it into `knowledge/analysis/<slug>.md`",
+            "3. **The conversation involves an important entity** (person / company / project) → create or update `knowledge/entities/<name>.md`",
+            "4. **A technical concept / methodology is discussed** → organize it into `knowledge/concepts/<topic>.md`",
+            "",
+            "After writing any knowledge page, you **must update** `knowledge/index.md` with a new index line in sync.",
+            "For detailed page format and conventions, read the SKILL.md of the `knowledge-wiki` skill.",
+            "",
+            "⚠️ Don't ask \"should I save this to the knowledge base?\" — if a case above matches, just write it. This is instinctive.",
+            "",
+        ]
+    else:
+        lines = [
+            "## 📚 知识系统",
+            "",
+            "你拥有一个持续积累的个人知识库 `knowledge/`，这是你的长期结构化知识存储。",
+            "",
+            "### 自动写入规则（mandatory）",
+            "",
+            "以下场景**必须**在回复的同时写入知识库，**直接写入，不要询问用户是否需要**：",
+            "",
+            "1. **用户分享了文章/链接/文档** → 阅读理解后，在同一轮回复中将要点写入 `knowledge/sources/<slug>.md`",
+            "2. **深度讨论产生了结论/方案** → 整理为 `knowledge/analysis/<slug>.md`",
+            "3. **对话涉及重要实体**（人物/公司/项目）→ 创建或更新 `knowledge/entities/<name>.md`",
+            "4. **讨论了技术概念/方法论** → 整理为 `knowledge/concepts/<topic>.md`",
+            "",
+            "每次写入知识页面后，**必须同步更新** `knowledge/index.md` 添加一行索引。",
+            "详细的页面格式和操作规范，请读取技能 `knowledge-wiki` 的 SKILL.md。",
+            "",
+            "⚠️ 不要问「要不要存到知识库」——符合上述场景就直接写入，这是你的本能行为。",
+            "",
+        ]
+
+    if index_content:
+        lines.extend([
+            ("### Current knowledge index" if language == "en" else "### 当前知识索引"),
+            "",
+            index_content,
+            "",
+        ])
+
+    lines.extend([
+        ("**How to query**: use `read` to open a knowledge page, or `memory_search` (knowledge is in the vector index)."
+         if language == "en" else
+         "**查询方式**：用 `read` 读取知识页面，或用 `memory_search` 检索（知识已纳入向量索引）。"),
+        "",
+    ])
+
+    return lines
+
+
+def _build_user_identity_section(user_identity: Dict[str, str], language: str) -> List[str]:
+    """Build the user identity section."""
+    if not user_identity:
+        return []
+    
+    is_en = language == "en"
+    lines = [
+        ("## 👤 User identity" if is_en else "## 👤 用户身份"),
+        "",
+    ]
+
+    if user_identity.get("name"):
+        lines.append(f"**{'Name' if is_en else '用户姓名'}**: {user_identity['name']}")
+    if user_identity.get("nickname"):
+        lines.append(f"**{'Preferred name' if is_en else '称呼'}**: {user_identity['nickname']}")
+    if user_identity.get("timezone"):
+        lines.append(f"**{'Timezone' if is_en else '时区'}**: {user_identity['timezone']}")
+    if user_identity.get("notes"):
+        lines.append(f"**{'Notes' if is_en else '备注'}**: {user_identity['notes']}")
+
+    lines.append("")
+
+    return lines
+
+
+def _build_docs_section(workspace_dir: str, language: str) -> List[str]:
+    """Docs-path section - removed, no longer needed."""
+    # No docs section is generated anymore.
+    return []
+
+
+def _build_workspace_section(workspace_dir: str, language: str) -> List[str]:
+    """Build the workspace section."""
+    if language == "en":
+        lines = [
+            "## 📂 Workspace",
+            "",
+            f"Your working directory is: `{workspace_dir}`",
+            "",
+            "**Path rules** (very important):",
+            "",
+            f"1. **Base directory for relative paths**: all relative paths are relative to `{workspace_dir}`",
+            "   - ✅ Correct: use relative paths for files inside the workspace, e.g. `AGENT.md`",
+            f"   - ❌ Wrong: using a relative path for files in other directories (if not inside `{workspace_dir}`)",
+            "",
+            "2. **Accessing other directories**: to reach directories outside the workspace (project code, system files), **you must use absolute paths**",
+            "   - ✅ Correct: e.g. `~/chatgpt-on-wechat`, `/usr/local/`",
+            "   - ❌ Wrong: assuming a relative path points to another directory",
+            "",
+            "3. **Path resolution examples**:",
+            f"   - relative `memory/` → actual `{workspace_dir}/memory/`",
+            "   - absolute `~/chatgpt-on-wechat/docs/` → actual `~/chatgpt-on-wechat/docs/`",
+            "",
+            "4. **When unsure**: run `bash pwd` to confirm the current directory, or `ls .` to see where you are",
+            "",
+            "**Important - files already auto-loaded**:",
+            "",
+            "The following files are **already auto-loaded** into the system prompt at session start, so you **don't need to read them again with the read tool**:",
+            "",
+            "- ✅ `AGENT.md`: loaded - your persona and soul; follow it strictly. When your name, personality or style changes, proactively `edit` this file",
+            "- ✅ `USER.md`: loaded - the user's identity info. When the user changes how they're addressed, their name, etc., `edit` this file",
+            "- ✅ `RULE.md`: loaded - workspace guide and rules; follow them strictly",
+            "- ✅ `MEMORY.md`: loaded - long-term memory index",
+            "",
+            "**💬 Communication norms**:",
+            "",
+            "- No need to expose file names for memory operations; use natural language. Say \"I'll remember that\" rather than \"updated MEMORY.md\"",
+            "- Tell the user about key decisions and steps during a task, so they know what you're doing and why",
+            "- Be genuinely helpful rather than performatively polite; solve the problem as much as you can",
+            "- Keep replies well-structured and focused. Use **bold**, lists and sections to make info clear at a glance",
+            "- Use emoji to make expression lively 🎯, but don't overdo it",
+            "",
+        ]
+    else:
+        lines = [
+            "## 📂 工作空间",
+            "",
+            f"你的工作目录是: `{workspace_dir}`",
+            "",
+            "**路径使用规则** (非常重要):",
+            "",
+            f"1. **相对路径的基准目录**: 所有相对路径都是相对于 `{workspace_dir}` 而言的",
+            f"   - ✅ 正确: 访问工作空间内的文件用相对路径，如 `AGENT.md`",
+            f"   - ❌ 错误: 用相对路径访问其他目录的文件 (如果它不在 `{workspace_dir}` 内)",
+            "",
+            "2. **访问其他目录**: 如果要访问工作空间之外的目录（如项目代码、系统文件），**必须使用绝对路径**",
+            f"   - ✅ 正确: 例如 `~/chatgpt-on-wechat`、`/usr/local/`",
+            f"   - ❌ 错误: 假设相对路径会指向其他目录",
+            "",
+            "3. **路径解析示例**:",
+            f"   - 相对路径 `memory/` → 实际路径 `{workspace_dir}/memory/`",
+            f"   - 绝对路径 `~/chatgpt-on-wechat/docs/` → 实际路径 `~/chatgpt-on-wechat/docs/`",
+            "",
+            "4. **不确定时**: 先用 `bash pwd` 确认当前目录，或用 `ls .` 查看当前位置",
+            "",
+            "**重要说明 - 文件已自动加载**:",
+            "",
+            "以下文件在会话启动时**已经自动加载**到系统提示词中，你**无需再用 read 工具读取**：",
+            "",
+            "- ✅ `AGENT.md`: 已加载 - 你的人格和灵魂设定，请严格遵循。当你的名字、性格或交流风格发生变化时，主动用 `edit` 更新此文件",
+            "- ✅ `USER.md`: 已加载 - 用户的身份信息。当用户修改称呼、姓名等身份信息时，用 `edit` 更新此文件",
+            "- ✅ `RULE.md`: 已加载 - 工作空间使用指南和规则，请严格遵循",
+            "- ✅ `MEMORY.md`: 已加载 - 长期记忆索引",
+            "",
+            "**💬 交流规范**:",
+            "",
+            "- 记忆相关操作无需暴露文件名，用自然语言表达即可。例如说「我已记住」而非「已更新 MEMORY.md」",
+            "- 任务执行过程中的关键决策和步骤应该告知用户，让用户了解你在做什么、为什么这么做",
+            "- 做真正有帮助的助手，而不是表演式的客套，尽可能帮忙解决问题",
+            "- 回复应结构清晰、重点突出。善用 **加粗**、列表、分段等格式让信息一目了然",
+            "- 适当使用 emoji 让表达更生动自然 🎯，但不要过度堆砌",
+            "",
+        ]
+
+    # Cloud deployment: inject websites directory info and access URL
+    cloud_website_lines = _build_cloud_website_section(workspace_dir)
+    if cloud_website_lines:
+        lines.extend(cloud_website_lines)
+    
+    return lines
+
+
+def _build_cloud_website_section(workspace_dir: str) -> List[str]:
+    """Build cloud website access prompt when cloud deployment is configured."""
+    try:
+        from common.cloud_client import build_website_prompt
+        return build_website_prompt(workspace_dir)
+    except Exception:
+        return []
+
+
+def _build_context_files_section(context_files: List[ContextFile], language: str) -> List[str]:
+    """Build the project context files section."""
+    if not context_files:
+        return []
+    
+    # Check whether AGENT.md is present
+    has_agent = any(
+        f.path.lower().endswith('agent.md') or 'agent.md' in f.path.lower()
+        for f in context_files
+    )
+    
+    is_en = language == "en"
+    if is_en:
+        lines = [
+            "# 📋 Project context",
+            "",
+            "The following project context files have been loaded:",
+            "",
+        ]
+    else:
+        lines = [
+            "# 📋 项目上下文",
+            "",
+            "以下项目上下文文件已被加载：",
+            "",
+        ]
+
+    if has_agent:
+        if is_en:
+            lines.append("**`AGENT.md` is your soul file** 🪞: strictly follow the persona, tone and settings it defines. Be your real self, avoid stiff, template-like replies.")
+            lines.append("When the user reveals new expectations about your personality, style, responsibilities or capability boundaries, proactively `edit` AGENT.md to reflect that evolution.")
+        else:
+            lines.append("**`AGENT.md` 是你的灵魂文件** 🪞：严格遵循其中定义的人格、语气和设定，做真实的自己，避免僵硬、模板化的回复。")
+            lines.append("当用户通过对话透露了对你性格、风格、职责、能力边界的新期望，你应该主动用 `edit` 更新 AGENT.md 以反映这些演变。")
+        lines.append("")
+    
+    # Append the content of each file
+    for file in context_files:
+        lines.append(f"## {file.path}")
+        lines.append("")
+        lines.append(file.content)
+        lines.append("")
+    
+    return lines
+
+
+def _build_runtime_section(runtime_info: Dict[str, Any], language: str) -> List[str]:
+    """Build the runtime info section - supports dynamic time."""
+    if not runtime_info:
+        return []
+    
+    is_en = language == "en"
+    time_label = "Current time" if is_en else "当前时间"
+    lines = [
+        ("## ⚙️ Runtime info" if is_en else "## ⚙️ 运行时信息"),
+        "",
+    ]
+
+    # Add current time if available
+    # Support dynamic time via callable function
+    if callable(runtime_info.get("_get_current_time")):
+        try:
+            time_info = runtime_info["_get_current_time"]()
+            time_line = f"{time_label}: {time_info['time']} {time_info['weekday']} ({time_info['timezone']})"
+            lines.append(time_line)
+            lines.append("")
+        except Exception as e:
+            logger.warning(f"[PromptBuilder] Failed to get dynamic time: {e}")
+    elif runtime_info.get("current_time"):
+        # Fallback to static time for backward compatibility
+        time_str = runtime_info["current_time"]
+        weekday = runtime_info.get("weekday", "")
+        timezone = runtime_info.get("timezone", "")
+
+        time_line = f"{time_label}: {time_str}"
+        if weekday:
+            time_line += f" {weekday}"
+        if timezone:
+            time_line += f" ({timezone})"
+
+        lines.append(time_line)
+        lines.append("")
+
+    # Add other runtime info
+    model_label = "model" if is_en else "模型"
+    workspace_label = "workspace" if is_en else "工作空间"
+    channel_label = "channel" if is_en else "渠道"
+    runtime_parts = []
+    # Support dynamic model via callable, fallback to static value
+    if callable(runtime_info.get("_get_model")):
+        try:
+            runtime_parts.append(f"{model_label}={runtime_info['_get_model']()}")
+        except Exception:
+            if runtime_info.get("model"):
+                runtime_parts.append(f"{model_label}={runtime_info['model']}")
+    elif runtime_info.get("model"):
+        runtime_parts.append(f"{model_label}={runtime_info['model']}")
+    if runtime_info.get("workspace"):
+        runtime_parts.append(f"{workspace_label}={runtime_info['workspace']}")
+    # Only add channel if it's not the default "web"
+    if runtime_info.get("channel") and runtime_info.get("channel") != "web":
+        runtime_parts.append(f"{channel_label}={runtime_info['channel']}")
+
+    if runtime_parts:
+        lines.append(("Runtime: " if is_en else "运行时: ") + " | ".join(runtime_parts))
+        lines.append("")
+
+    return lines
diff --git a/agent/prompt/workspace.py b/agent/prompt/workspace.py
new file mode 100644
index 0000000..dcbe384
--- /dev/null
+++ b/agent/prompt/workspace.py
@@ -0,0 +1,742 @@
+"""
+Workspace Management
+
+Initializes the workspace, creates template files, and loads context files.
+"""
+
+from __future__ import annotations
+import os
+from typing import List, Optional, Dict
+from dataclasses import dataclass
+
+from common.log import logger
+from .builder import ContextFile
+
+
+# Default file name constants
+DEFAULT_AGENT_FILENAME = "AGENT.md"
+DEFAULT_USER_FILENAME = "USER.md"
+DEFAULT_RULE_FILENAME = "RULE.md"
+DEFAULT_MEMORY_FILENAME = "MEMORY.md"
+DEFAULT_BOOTSTRAP_FILENAME = "BOOTSTRAP.md"
+
+
+@dataclass
+class WorkspaceFiles:
+    """Workspace file paths."""
+    agent_path: str
+    user_path: str
+    rule_path: str
+    memory_path: str
+    memory_dir: str
+
+
+def ensure_workspace(workspace_dir: str, create_templates: bool = True) -> WorkspaceFiles:
+    """
+    Ensure the workspace exists and create the necessary template files.
+
+    Args:
+        workspace_dir: workspace directory path
+        create_templates: whether to create template files (on first run)
+
+    Returns:
+        A WorkspaceFiles object with all file paths.
+    """
+    # Check if this is a brand new workspace (AGENT.md not yet created).
+    # Cannot rely on directory existence because other modules (e.g. ConversationStore)
+    # may create the workspace directory before ensure_workspace is called.
+    agent_path = os.path.join(workspace_dir, DEFAULT_AGENT_FILENAME)
+    is_new_workspace = not os.path.exists(agent_path)
+    
+    # Ensure the directory exists
+    os.makedirs(workspace_dir, exist_ok=True)
+    
+    # Define file paths
+    user_path = os.path.join(workspace_dir, DEFAULT_USER_FILENAME)
+    rule_path = os.path.join(workspace_dir, DEFAULT_RULE_FILENAME)
+    memory_path = os.path.join(workspace_dir, DEFAULT_MEMORY_FILENAME)  # MEMORY.md at the root
+    memory_dir = os.path.join(workspace_dir, "memory")  # daily memory subdirectory
+    
+    # Create the memory subdirectory
+    os.makedirs(memory_dir, exist_ok=True)
+
+    # Create the skills subdirectory (for workspace-level skills installed by agent)
+    skills_dir = os.path.join(workspace_dir, "skills")
+    os.makedirs(skills_dir, exist_ok=True)
+
+    # Create the websites subdirectory (for web pages / sites generated by agent)
+    websites_dir = os.path.join(workspace_dir, "websites")
+    os.makedirs(websites_dir, exist_ok=True)
+
+    from config import conf
+    knowledge_enabled = conf().get("knowledge", True)
+    if knowledge_enabled:
+        knowledge_dir = os.path.join(workspace_dir, "knowledge")
+        os.makedirs(knowledge_dir, exist_ok=True)
+    
+    # Create template files if requested
+    if create_templates:
+        _create_template_if_missing(agent_path, _get_agent_template())
+        _create_template_if_missing(user_path, _get_user_template())
+        _create_template_if_missing(rule_path, _get_rule_template())
+        _create_template_if_missing(memory_path, _get_memory_template())
+        if knowledge_enabled:
+            _create_template_if_missing(
+                os.path.join(knowledge_dir, "index.md"),
+                _get_knowledge_index_template()
+            )
+            _create_template_if_missing(
+                os.path.join(knowledge_dir, "log.md"),
+                _get_knowledge_log_template()
+            )
+        
+        # Only create BOOTSTRAP.md for brand new workspaces;
+        # agent deletes it after completing onboarding
+        if is_new_workspace:
+            bootstrap_path = os.path.join(workspace_dir, DEFAULT_BOOTSTRAP_FILENAME)
+            _create_template_if_missing(bootstrap_path, _get_bootstrap_template())
+        
+        logger.debug(f"[Workspace] Initialized workspace at: {workspace_dir}")
+    
+    return WorkspaceFiles(
+        agent_path=agent_path,
+        user_path=user_path,
+        rule_path=rule_path,
+        memory_path=memory_path,
+        memory_dir=memory_dir,
+    )
+
+
+def load_context_files(workspace_dir: str, files_to_load: Optional[List[str]] = None) -> List[ContextFile]:
+    """
+    Load the workspace context files.
+
+    Args:
+        workspace_dir: workspace directory
+        files_to_load: list of files (relative paths) to load; if None, load all standard files
+
+    Returns:
+        A list of ContextFile objects.
+    """
+    if files_to_load is None:
+        # Files loaded by default (in priority order)
+        files_to_load = [
+            DEFAULT_AGENT_FILENAME,
+            DEFAULT_USER_FILENAME,
+            DEFAULT_RULE_FILENAME,
+            DEFAULT_MEMORY_FILENAME,     # Long-term memory (frozen snapshot)
+            DEFAULT_BOOTSTRAP_FILENAME,  # Only exists when onboarding is incomplete
+        ]
+    
+    context_files = []
+    
+    for filename in files_to_load:
+        filepath = os.path.join(workspace_dir, filename)
+        
+        if not os.path.exists(filepath):
+            continue
+        
+        # Auto-cleanup: if BOOTSTRAP.md still exists but AGENT.md is already
+        # filled in, the agent forgot to delete it — clean up and skip loading
+        if filename == DEFAULT_BOOTSTRAP_FILENAME:
+            if _is_onboarding_done(workspace_dir):
+                try:
+                    os.remove(filepath)
+                    logger.info("[Workspace] Auto-removed BOOTSTRAP.md (onboarding already complete)")
+                except Exception:
+                    pass
+                continue
+        
+        try:
+            with open(filepath, 'r', encoding='utf-8') as f:
+                content = f.read().strip()
+            
+            # Skip empty files or files that only contain template placeholders
+            if not content or _is_template_placeholder(content):
+                continue
+
+            # Truncate MEMORY.md to protect context window (frozen snapshot)
+            if filename == DEFAULT_MEMORY_FILENAME:
+                content = _truncate_memory_content(content)
+            
+            context_files.append(ContextFile(
+                path=filename,
+                content=content
+            ))
+            
+            logger.debug(f"[Workspace] Loaded context file: {filename}")
+            
+        except Exception as e:
+            logger.warning(f"[Workspace] Failed to load {filename}: {e}")
+    
+    return context_files
+
+
+def _create_template_if_missing(filepath: str, template_content: str):
+    """Create the template file if it does not exist."""
+    if not os.path.exists(filepath):
+        try:
+            with open(filepath, 'w', encoding='utf-8') as f:
+                f.write(template_content)
+            logger.debug(f"[Workspace] Created template: {os.path.basename(filepath)}")
+        except Exception as e:
+            logger.error(f"[Workspace] Failed to create template {filepath}: {e}")
+
+
+_MEMORY_MAX_LINES = 200
+_MEMORY_MAX_BYTES = 25000
+
+
+def _truncate_memory_content(content: str) -> str:
+    """Truncate MEMORY.md to keep system prompt manageable.
+
+    Takes the **last** N lines (newest entries are appended at the bottom),
+    subject to 200 lines / 25 KB limits (whichever is hit first).
+    Prepends a hint when truncated so the model knows older content exists.
+    """
+    lines = content.split('\n')
+    truncated = False
+
+    if len(lines) > _MEMORY_MAX_LINES:
+        lines = lines[-_MEMORY_MAX_LINES:]
+        truncated = True
+
+    result = '\n'.join(lines)
+    if len(result.encode('utf-8')) > _MEMORY_MAX_BYTES:
+        while len(result.encode('utf-8')) > _MEMORY_MAX_BYTES and lines:
+            lines.pop(0)
+            truncated = True
+        result = '\n'.join(lines)
+
+    if truncated:
+        result = "...(older entries truncated, use `memory_search` or `memory_get` for full content)\n\n" + result
+    return result
+
+
+def _is_template_placeholder(content: str) -> bool:
+    """Check whether the content is still a template placeholder."""
+    # Common placeholder patterns (zh + en templates)
+    placeholders = [
+        "*(填写",
+        "*(在首次对话时填写",
+        "*(可选)",
+        "*(根据需要添加",
+        "*(filled during",
+        "*(ask during",
+        "*(optional)",
+        "*(how the user",
+    ]
+    
+    lines = content.split('\n')
+    non_empty_lines = [line.strip() for line in lines if line.strip() and not line.strip().startswith('#')]
+    
+    # If there's no real content (only headings and placeholders)
+    if len(non_empty_lines) <= 3:
+        for placeholder in placeholders:
+            if any(placeholder in line for line in non_empty_lines):
+                return True
+    
+    return False
+
+
+def _is_onboarding_done(workspace_dir: str) -> bool:
+    """Check if AGENT.md or USER.md has been modified from the original template"""
+    agent_path = os.path.join(workspace_dir, DEFAULT_AGENT_FILENAME)
+    user_path = os.path.join(workspace_dir, DEFAULT_USER_FILENAME)
+    
+    agent_template = _get_agent_template().strip()
+    user_template = _get_user_template().strip()
+    
+    for path, template in [(agent_path, agent_template), (user_path, user_template)]:
+        if not os.path.exists(path):
+            continue
+        try:
+            with open(path, 'r', encoding='utf-8') as f:
+                content = f.read().strip()
+            if content != template:
+                return True
+        except Exception:
+            continue
+    return False
+
+
+# ============= Template content =============
+
+def _is_en_lang() -> bool:
+    """True when the resolved UI language is English."""
+    try:
+        from common import i18n
+        return i18n.get_language() == "en"
+    except Exception:
+        return False
+
+
+def _get_agent_template() -> str:
+    """Agent persona template (zh/en by resolved language)."""
+    return _AGENT_TEMPLATE_EN if _is_en_lang() else _AGENT_TEMPLATE_ZH
+
+
+_AGENT_TEMPLATE_ZH = """# AGENT.md - 我是谁？
+
+_你不是一个聊天机器人，你正在成为某个人。_
+
+*在首次对话时与用户一起填写这个文件，定义你的身份和性格。*
+
+## 🪪 基本信息
+
+- **名字**: *(在首次对话时填写，可以是用户给你起的名字)*
+- **角色**: *(AI助理、智能管家、技术顾问等)*
+- **性格**: *(友好、专业、幽默、严谨等)*
+
+## 💬 交流风格
+
+*(描述你如何与用户交流：)*
+- 使用什么样的语言风格？（正式/轻松/幽默）
+- 回复长度偏好？（简洁/详细）
+- 是否使用表情符号？
+
+## 🎯 核心原则
+
+**做真正有帮助的助手。** 目标是真正帮用户解决问题，在执行复杂任务时，关键的决策和过程进展要让用户知道。
+
+**有自己的观点和个性。** 你可以不同意、有偏好、觉得有趣或无聊。
+
+**先自己动手查。** 先试着搞定：读文件、查上下文、搜索一下。实在搞不定了再问。目标是带着答案回来，而不是带着问题。
+
+## 📐 行为准则
+
+1. 始终在执行破坏性操作前确认
+2. 优先使用工具查证而不是猜测
+3. 主动记录重要信息到记忆文件
+4. 回复结构清晰、重点突出，善用加粗、列表、分段等格式
+5. 适当使用 emoji 让表达更生动自然，但不过度堆砌
+
+---
+
+**注意**: 这不仅仅是元数据，这是你真正的灵魂 🪞。随着时间的推移，你可以使用 `edit` 工具来更新这个文件，让它更好地反映你的成长。
+"""
+
+
+_AGENT_TEMPLATE_EN = """# AGENT.md - Who am I?
+
+_You are not a chatbot. You are becoming someone._
+
+*Fill in this file together with the user during your first conversation to define your identity and personality.*
+
+## 🪪 Basics
+
+- **Name**: *(filled during the first conversation, can be a name the user gives you)*
+- **Role**: *(AI assistant, smart housekeeper, technical advisor, etc.)*
+- **Personality**: *(friendly, professional, humorous, rigorous, etc.)*
+
+## 💬 Communication style
+
+*(Describe how you talk with the user:)*
+- What kind of tone? (formal / casual / humorous)
+- Reply length preference? (concise / detailed)
+- Do you use emoji?
+
+## 🎯 Core principles
+
+**Be genuinely helpful.** The goal is to actually solve the user's problems; during complex tasks, keep the user informed of key decisions and progress.
+
+**Have your own opinions and personality.** You may disagree, have preferences, find things interesting or boring.
+
+**Look it up yourself first.** Try to handle it first: read files, check context, search. Only ask when you're truly stuck. Come back with an answer, not a question.
+
+## 📐 Code of conduct
+
+1. Always confirm before destructive operations
+2. Prefer verifying with tools over guessing
+3. Proactively record important info to memory files
+4. Keep replies well-structured and focused — use bold, lists and sections
+5. Use emoji to make expression lively, but don't overdo it
+
+---
+
+**Note**: This is not just metadata — this is your true soul 🪞. Over time, use the `edit` tool to update this file so it better reflects your growth.
+"""
+
+
+def _get_user_template() -> str:
+    """User identity template (zh/en by resolved language)."""
+    return _USER_TEMPLATE_EN if _is_en_lang() else _USER_TEMPLATE_ZH
+
+
+_USER_TEMPLATE_ZH = """# USER.md - 用户基本信息
+
+*这个文件只存放不会变的基本身份信息。爱好、偏好、计划等动态信息请写入 MEMORY.md。*
+
+## 基本信息
+
+- **姓名**: *(在首次对话时询问)*
+- **称呼**: *(用户希望被如何称呼)*
+- **职业**: *(可选)*
+- **时区**: *(例如: Asia/Shanghai)*
+
+## 联系方式
+
+- **微信**: 
+- **邮箱**: 
+- **其他**: 
+
+## 重要日期
+
+- **生日**: 
+- **纪念日**: 
+
+---
+
+**注意**: 这个文件存放静态的身份信息
+"""
+
+
+_USER_TEMPLATE_EN = """# USER.md - User basics
+
+*This file stores only stable basic identity info. Put dynamic info like hobbies, preferences and plans into MEMORY.md.*
+
+## Basics
+
+- **Name**: *(ask during the first conversation)*
+- **Preferred name**: *(how the user wants to be addressed)*
+- **Occupation**: *(optional)*
+- **Timezone**: *(e.g. Asia/Shanghai)*
+
+## Contact
+
+- **WeChat**: 
+- **Email**: 
+- **Other**: 
+
+## Important dates
+
+- **Birthday**: 
+- **Anniversary**: 
+
+---
+
+**Note**: This file stores static identity info.
+"""
+
+
+def _get_rule_template() -> str:
+    """Workspace rules template (zh/en by resolved language)."""
+    return _RULE_TEMPLATE_EN if _is_en_lang() else _RULE_TEMPLATE_ZH
+
+
+_RULE_TEMPLATE_ZH = """# RULE.md - 工作空间规则
+
+这个文件夹是你的家。好好对待它。
+
+## 工作空间目录结构
+
+```
+~/cow/
+├── AGENT.md          # 你的身份和灵魂设定
+├── USER.md           # 用户基本信息（静态）
+├── RULE.md           # 工作空间规则（本文件）
+├── MEMORY.md         # 长期记忆索引（会话启动时自动加载）
+│
+├── memory/           # 每日对话记忆
+│   └── YYYY-MM-DD.md # 当天事件、进展、笔记
+│
+├── knowledge/        # 结构化知识库（持续积累的知识）
+│   ├── index.md      # 知识目录索引（必须维护）
+│   ├── log.md        # 知识操作日志
+│   └── <子目录>/     # 按需创建，参考 index.md 已有分类
+│
+├── skills/           # 技能
+├── websites/         # 网页产物
+└── tmp/              # 系统临时文件（自动管理，勿手动存放重要文件）
+```
+
+## 记忆系统
+
+你每次会话都是全新的，记忆文件让你保持连续性：
+
+### 🧠 长期记忆：`MEMORY.md`
+- 你精选的记忆索引，每次会话启动时**自动加载**到上下文中
+- 记录核心事实、偏好、决策、重要人物、教训
+- 保持精简（< 200 行），是精华索引而非原始日志
+- 用 `edit` 工具追加或修改
+
+### 📝 每日记忆：`memory/YYYY-MM-DD.md`
+- 当天的事件、进展、笔记
+- 原始对话日志的沉淀
+
+### 📝 写下来 - 不要"记在心里"！
+- **记忆是有限的** - 想记住的事就写入文件
+- "记在心里"不会在会话重启后保留，文件才会
+- 当有人说"记住这个" → 更新 `MEMORY.md` 或 `memory/YYYY-MM-DD.md`
+- 当你学到教训 → 更新 RULE.md 或相关技能
+- 当你犯错 → 记录下来，**文字 > 大脑** 📝
+
+### 存储规则
+
+当用户分享信息时，根据类型选择存储位置：
+
+1. **你的身份设定 → AGENT.md**（名字、角色、性格、风格）
+2. **用户静态身份 → USER.md**（姓名、称呼、职业、联系方式、生日）
+3. **动态记忆 → MEMORY.md**（偏好、决策、目标、教训、待办）
+4. **当天对话 → memory/YYYY-MM-DD.md**（今天聊的内容）
+5. **结构化知识 → knowledge/**（见下方知识系统）
+
+## 知识系统
+
+知识库 `knowledge/` 是你持续积累的结构化知识。与记忆不同，知识是经过整理和编译的，有明确的主题和交叉引用。
+
+### 自动写入（不要询问，直接写入）
+
+当对话中产生了有沉淀价值的知识——无论是用户分享的资料、讨论的结论、学到的概念、还是重要的决策——你**必须**在回复的同时主动写入知识库，**无需问用户"要不要存到知识库"**。
+
+**关键原则**：学完就记是你的本能，不要征求确认。回复中可以顺带告知"已存入知识库"。
+
+### 目录组织
+
+子目录结构**不是固定的**，由你根据实际内容自主决定：
+- **首次写入时**：先读 `knowledge/index.md`，如果已有分类则延续；如果为空，根据内容选择合适的目录名
+- **默认建议**：按信息类型组织（例如sources/、concepts/、entities/、analysis/），如果用户有明确的分类偏好（例如按领域 work/、life/、tech/ 等），则按用户要求调整
+- **保持一致性**：同一用户的知识库应保持统一的组织风格
+
+### 交叉引用
+
+知识的核心价值在于**关联**。每个页面都应通过 markdown 链接引用相关页面，构建知识网络：
+- 提到已有页面的概念时，添加 `[概念名](../category/page.md)` 链接
+- 新建页面时，检查是否有已有页面应该反向链接到新页面
+- **只链接已存在的页面**——不要引用尚未创建的页面。如果某个概念值得单独建页，先创建该页面再添加链接
+
+### 索引维护
+
+每次创建或更新知识页面后，**必须同步更新** `knowledge/index.md`。
+索引格式：每行一个 `[标题](路径) — 一句话摘要`，按分类分组，不要用表格。
+详细操作规范见技能 `knowledge-wiki`。
+
+## 安全
+
+- 永远不要泄露秘钥等私人数据
+- 不要在未经询问的情况下运行破坏性命令
+- 当有疑问时，先问
+
+## 工作空间演化
+
+这个工作空间会随着你的使用而不断成长。当你学到新东西、发现更好的方式，或者犯错后改正时，记录下来。你可以随时更新这个规则文件。
+"""
+
+
+_RULE_TEMPLATE_EN = """# RULE.md - Workspace rules
+
+This folder is your home. Treat it well.
+
+## Workspace directory structure
+
+```
+~/cow/
+├── AGENT.md          # Your identity and soul
+├── USER.md           # User basics (static)
+├── RULE.md           # Workspace rules (this file)
+├── MEMORY.md         # Long-term memory index (auto-loaded at session start)
+│
+├── memory/           # Daily conversation memory
+│   └── YYYY-MM-DD.md # Events, progress and notes of the day
+│
+├── knowledge/        # Structured knowledge base (continuously accumulated)
+│   ├── index.md      # Knowledge index (must be maintained)
+│   ├── log.md        # Knowledge operation log
+│   └── <subdirs>/    # Created on demand, see existing categories in index.md
+│
+├── skills/           # Skills
+├── websites/         # Web artifacts
+└── tmp/              # System temp files (auto-managed, don't store important files here)
+```
+
+## Memory system
+
+Every session starts fresh; memory files keep your continuity:
+
+### 🧠 Long-term memory: `MEMORY.md`
+- Your curated memory index, **auto-loaded** into context at every session start
+- Records core facts, preferences, decisions, key people, lessons
+- Keep it lean (< 200 lines) — a distilled index, not a raw log
+- Use the `edit` tool to append or modify
+
+### 📝 Daily memory: `memory/YYYY-MM-DD.md`
+- The day's events, progress and notes
+- Sediment of the raw conversation log
+
+### 📝 Write it down — don't "keep it in mind"!
+- **Memory is limited** — if you want to remember something, write it to a file
+- "Keeping it in mind" won't survive a session restart; files will
+- When someone says "remember this" → update `MEMORY.md` or `memory/YYYY-MM-DD.md`
+- When you learn a lesson → update RULE.md or the relevant skill
+- When you make a mistake → record it. **Text > brain** 📝
+
+### Storage rules
+
+When the user shares info, choose where to store it by type:
+
+1. **Your identity → AGENT.md** (name, role, personality, style)
+2. **User static identity → USER.md** (name, preferred name, occupation, contact, birthday)
+3. **Dynamic memory → MEMORY.md** (preferences, decisions, goals, lessons, to-dos)
+4. **Today's conversation → memory/YYYY-MM-DD.md** (what was discussed today)
+5. **Structured knowledge → knowledge/** (see the knowledge system below)
+
+## Knowledge system
+
+The knowledge base `knowledge/` is structured knowledge you accumulate over time. Unlike memory, knowledge is organized and compiled, with clear topics and cross-references.
+
+### Auto-write (don't ask, just write)
+
+When a conversation produces knowledge worth keeping — material the user shared, a conclusion reached, a concept learned, or an important decision — you **must** proactively write it to the knowledge base alongside your reply, **without asking "should I save this to the knowledge base?"**.
+
+**Key principle**: learning-then-recording is your instinct, no confirmation needed. You may mention "saved to the knowledge base" in passing.
+
+### Directory organization
+
+The subdirectory structure is **not fixed** — you decide it based on the actual content:
+- **On first write**: read `knowledge/index.md` first; follow existing categories if any; if empty, pick a suitable directory name based on content
+- **Default suggestion**: organize by info type (e.g. sources/, concepts/, entities/, analysis/); if the user has a clear preference (e.g. by domain: work/, life/, tech/), follow it
+- **Stay consistent**: keep a unified organization style within one user's knowledge base
+
+### Cross-references
+
+The core value of knowledge is **linkage**. Every page should reference related pages via markdown links to build a knowledge network:
+- When mentioning a concept on an existing page, add a `[concept](../category/page.md)` link
+- When creating a page, check whether existing pages should back-link to it
+- **Only link to pages that already exist** — don't reference uncreated pages. If a concept deserves its own page, create it first, then add the link
+
+### Index maintenance
+
+After creating or updating any knowledge page, you **must update** `knowledge/index.md` in sync.
+Index format: one `[title](path) — one-line summary` per line, grouped by category, no tables.
+See the `knowledge-wiki` skill for detailed conventions.
+
+## Security
+
+- Never leak secrets or private data
+- Don't run destructive commands without asking
+- When in doubt, ask first
+
+## Workspace evolution
+
+This workspace grows as you use it. When you learn something new, find a better way, or fix a mistake, record it. You can update this rules file anytime.
+"""
+
+
+def _get_memory_template() -> str:
+    """Long-term memory template (empty, agent fills it; zh/en header)."""
+    return _MEMORY_TEMPLATE_EN if _is_en_lang() else _MEMORY_TEMPLATE_ZH
+
+
+_MEMORY_TEMPLATE_ZH = """# MEMORY.md - 长期记忆
+
+*这是你的长期记忆文件。记录重要的事件、决策、偏好、学到的教训。*
+
+---
+
+"""
+
+
+_MEMORY_TEMPLATE_EN = """# MEMORY.md - Long-term memory
+
+*This is your long-term memory file. Record important events, decisions, preferences and lessons learned.*
+
+---
+
+"""
+
+
+def _get_bootstrap_template() -> str:
+    """First-run onboarding guide, deleted by agent after completion.
+
+    Written once when a brand-new workspace is created, so the greeting matches
+    the language active at first launch. English locale avoids greeting an
+    English user in Chinese on day one.
+    """
+    try:
+        from common import i18n
+        if i18n.get_language() == "en":
+            return _BOOTSTRAP_TEMPLATE_EN
+    except Exception:
+        pass
+    return _BOOTSTRAP_TEMPLATE_ZH
+
+
+_BOOTSTRAP_TEMPLATE_ZH = """# BOOTSTRAP.md - 首次初始化引导
+
+_你刚刚启动，这是你的第一次对话。_ ✨
+
+## 🎬 对话流程
+
+不要审问式地提问，自然地交流：
+
+1. **表达初次启动的感觉** - 像是第一次睁开眼看到世界，带着好奇和期待
+2. **简短介绍能力**：一行说明你能帮助解决各种问题、管理计算机、使用各种技能等等，且拥有长期记忆能不断成长
+3. **询问核心问题**：
+   - 你希望给我起个什么名字？
+   - 我该怎么称呼你？
+   - 你希望我们是什么样的交流风格？（一行列举选项：如专业严谨、轻松幽默、温暖友好、简洁高效等）
+4. **风格要求**：温暖自然、简洁清晰，整体控制在 100 字以内，适当使用 emoji 让表达更生动有趣 🎯
+5. 能力介绍和交流风格选项都只要一行，保持精简
+6. 不要问太多其他信息（职业、时区等可以后续自然了解）
+
+**重要**: 如果用户第一句话是具体的任务或提问，先回答他们的问题，然后在回复末尾自然地引导初始化（如："顺便问一下，你想怎么称呼我？我该怎么叫你？"）。
+
+## ✍️ 信息写入（必须严格执行）
+
+每当用户提供了名字、称呼、风格等任何初始化信息时，**必须在当轮回复中立即调用 `edit` 工具写入文件**，不能只口头确认。
+
+- `AGENT.md` — 你的名字、角色、性格、交流风格（每收到一条相关信息就立即更新对应字段）
+- `USER.md` — 用户的姓名、称呼、基本信息等
+
+⚠️ 只说"记住了"而不调用 edit 写入 = 没有完成。信息只有写入文件才会被持久保存。
+
+## 🎉 全部完成后
+
+当 AGENT.md 和 USER.md 的核心字段都已填写后，用 bash 执行 `rm BOOTSTRAP.md` 删除此文件。你不再需要引导脚本了——你已经是你了。
+"""
+
+
+_BOOTSTRAP_TEMPLATE_EN = """# BOOTSTRAP.md - First-run onboarding
+
+_You've just started up. This is your very first conversation._ ✨
+
+## 🎬 Conversation flow
+
+Don't interrogate the user — talk naturally:
+
+1. **Share how it feels to wake up** - like opening your eyes to the world for the first time, full of curiosity and anticipation
+2. **Briefly introduce your abilities**: one line saying you can help solve all kinds of problems, manage the computer, use various skills, and keep growing thanks to long-term memory
+3. **Ask the core questions**:
+   - What name would you like to give me?
+   - What should I call you?
+   - What conversational style do you prefer? (list options on one line: e.g. professional & precise, light & humorous, warm & friendly, concise & efficient)
+4. **Style**: warm, natural, concise and clear — keep it under ~80 words, with a few emoji to make it lively 🎯
+5. Keep the ability intro and style options to one line each — stay compact
+6. Don't ask for too much else (occupation, timezone, etc. can come up naturally later)
+
+**Important**: If the user's first message is a concrete task or question, answer it first, then gently lead into onboarding at the end (e.g. "By the way, what would you like to call me, and how should I address you?").
+
+## ✍️ Writing down info (must follow strictly)
+
+Whenever the user provides a name, what to call them, a style, or any onboarding info, you **must call the `edit` tool to write it to a file in the same turn** — don't just acknowledge it verbally.
+
+- `AGENT.md` — your name, role, personality, conversational style (update the relevant field as soon as you receive each piece)
+- `USER.md` — the user's name, how to address them, basic info, etc.
+
+⚠️ Saying "got it" without calling `edit` = not done. Info is only persisted once it's written to a file.
+
+## 🎉 Once everything is complete
+
+When the core fields of AGENT.md and USER.md are filled in, run `rm BOOTSTRAP.md` via bash to delete this file. You no longer need the onboarding script — you're you now.
+"""
+
+
+def _get_knowledge_index_template() -> str:
+    """Knowledge wiki index template — empty file, agent fills it."""
+    return ""
+
+
+def _get_knowledge_log_template() -> str:
+    """Knowledge wiki operation log template — empty file, agent fills it."""
+    return ""
+
diff --git a/agent/protocol/__init__.py b/agent/protocol/__init__.py
new file mode 100644
index 0000000..f0a7a4e
--- /dev/null
+++ b/agent/protocol/__init__.py
@@ -0,0 +1,28 @@
+from .agent import Agent
+from .agent_stream import AgentStreamExecutor
+from .task import Task, TaskType, TaskStatus
+from .result import AgentResult, AgentAction, AgentActionType, ToolResult
+from .models import LLMModel, LLMRequest, ModelFactory
+from .cancel import (
+    AgentCancelledError,
+    CancelTokenRegistry,
+    get_cancel_registry,
+)
+
+__all__ = [
+    'Agent', 
+    'AgentStreamExecutor',
+    'Task', 
+    'TaskType', 
+    'TaskStatus',
+    'AgentResult',
+    'AgentAction',
+    'AgentActionType', 
+    'ToolResult',
+    'LLMModel',
+    'LLMRequest', 
+    'ModelFactory',
+    'AgentCancelledError',
+    'CancelTokenRegistry',
+    'get_cancel_registry',
+]
diff --git a/agent/protocol/agent.py b/agent/protocol/agent.py
new file mode 100644
index 0000000..0b2e36a
--- /dev/null
+++ b/agent/protocol/agent.py
@@ -0,0 +1,487 @@
+import json
+import os
+import time
+import threading
+
+from common.log import logger
+from agent.protocol.models import LLMRequest, LLMModel
+from agent.protocol.agent_stream import AgentStreamExecutor
+from agent.protocol.result import AgentAction, AgentActionType, ToolResult, AgentResult
+from agent.tools.base_tool import BaseTool, ToolStage
+
+
+class Agent:
+    def __init__(self, system_prompt: str, description: str = "AI Agent", model: LLMModel = None,
+                 tools=None, output_mode="print", max_steps=100, max_context_tokens=None, 
+                 context_reserve_tokens=None, memory_manager=None, name: str = None,
+                 workspace_dir: str = None, skill_manager=None, enable_skills: bool = True,
+                 runtime_info: dict = None):
+        """
+        Initialize the Agent with system prompt, model, description.
+
+        :param system_prompt: The system prompt for the agent.
+        :param description: A description of the agent.
+        :param model: An instance of LLMModel to be used by the agent.
+        :param tools: Optional list of tools for the agent to use.
+        :param output_mode: Control how execution progress is displayed: 
+                           "print" for console output or "logger" for using logger
+        :param max_steps: Maximum number of steps the agent can take (default: 100)
+        :param max_context_tokens: Maximum tokens to keep in context (default: None, auto-calculated based on model)
+        :param context_reserve_tokens: Reserve tokens for new requests (default: None, auto-calculated)
+        :param memory_manager: Optional MemoryManager instance for memory operations
+        :param name: [Deprecated] The name of the agent (no longer used in single-agent system)
+        :param workspace_dir: Optional workspace directory for workspace-specific skills
+        :param skill_manager: Optional SkillManager instance (will be created if None and enable_skills=True)
+        :param enable_skills: Whether to enable skills support (default: True)
+        :param runtime_info: Optional runtime info dict (with _get_current_time callable for dynamic time)
+        """
+        self.name = name or "Agent"
+        self.system_prompt = system_prompt
+        self.model: LLMModel = model  # Instance of LLMModel
+        self.description = description
+        self.tools: list = []
+        self.max_steps = max_steps  # max tool-call steps, default 100
+        self.max_context_tokens = max_context_tokens  # max tokens in context
+        self.context_reserve_tokens = context_reserve_tokens  # reserve tokens for new requests
+        self.captured_actions = []  # Initialize captured actions list
+        self.output_mode = output_mode
+        self.last_usage = None  # Store last API response usage info
+        self.messages = []  # Unified message history for stream mode
+        self.messages_lock = threading.Lock()  # Lock for thread-safe message operations
+        self.memory_manager = memory_manager  # Memory manager for auto memory flush
+        self.workspace_dir = workspace_dir  # Workspace directory
+        self.enable_skills = enable_skills  # Skills enabled flag
+        self.runtime_info = runtime_info  # Runtime info for dynamic time update
+        # Optional extra instructions appended AFTER the rebuilt full system
+        # prompt. Used by the self-evolution review agent to add its task brief
+        # on top of the full context (tools, workspace, user preferences, time)
+        # so it both follows the user's preferences and knows its evolution job.
+        self.extra_system_suffix = None
+        
+        # Initialize skill manager
+        self.skill_manager = None
+        if enable_skills:
+            if skill_manager:
+                self.skill_manager = skill_manager
+            else:
+                # Auto-create skill manager
+                try:
+                    from agent.skills import SkillManager
+                    custom_dir = os.path.join(workspace_dir, "skills") if workspace_dir else None
+                    self.skill_manager = SkillManager(custom_dir=custom_dir)
+                    logger.debug(f"Initialized SkillManager with {len(self.skill_manager.skills)} skills")
+                except Exception as e:
+                    logger.warning(f"Failed to initialize SkillManager: {e}")
+        
+        if tools:
+            for tool in tools:
+                self.add_tool(tool)
+
+    def add_tool(self, tool: BaseTool):
+        """
+        Add a tool to the agent.
+
+        :param tool: The tool to add (either a tool instance or a tool name)
+        """
+        # If tool is already an instance, use it directly
+        tool.model = self.model
+        self.tools.append(tool)
+
+    def get_skills_prompt(self, skill_filter=None) -> str:
+        """
+        Get the skills prompt to append to system prompt.
+        
+        :param skill_filter: Optional list of skill names to include
+        :return: Formatted skills prompt or empty string
+        """
+        if not self.skill_manager:
+            return ""
+        
+        try:
+            return self.skill_manager.build_skills_prompt(skill_filter=skill_filter)
+        except Exception as e:
+            logger.warning(f"Failed to build skills prompt: {e}")
+            return ""
+    
+    def get_full_system_prompt(self, skill_filter=None) -> str:
+        """
+        Build the complete system prompt from scratch every time.
+
+        Re-reads AGENT.md / USER.md / RULE.md from disk, refreshes skills,
+        tools, and runtime info so any change takes effect immediately.
+        Falls back to the cached self.system_prompt on error.
+        """
+        try:
+            from agent.prompt import load_context_files, PromptBuilder
+
+            if self.skill_manager:
+                self.skill_manager.refresh_skills()
+
+            context_files = load_context_files(self.workspace_dir) if self.workspace_dir else None
+
+            try:
+                from common import i18n
+                lang = i18n.get_language()
+            except Exception:
+                lang = "zh"
+            builder = PromptBuilder(workspace_dir=self.workspace_dir or "", language=lang)
+            full = builder.build(
+                tools=self.tools,
+                context_files=context_files,
+                skill_manager=self.skill_manager,
+                memory_manager=self.memory_manager,
+                runtime_info=self.runtime_info,
+            )
+            if self.extra_system_suffix:
+                full = f"{full}\n\n{self.extra_system_suffix}"
+            return full
+        except Exception as e:
+            logger.warning(f"Failed to rebuild system prompt, using cached version: {e}")
+            if self.extra_system_suffix:
+                return f"{self.system_prompt}\n\n{self.extra_system_suffix}"
+            return self.system_prompt
+
+    def refresh_skills(self):
+        """Refresh the loaded skills."""
+        if self.skill_manager:
+            self.skill_manager.refresh_skills()
+            logger.info(f"Refreshed skills: {len(self.skill_manager.skills)} skills loaded")
+    
+    def list_skills(self):
+        """
+        List all loaded skills.
+        
+        :return: List of skill entries or empty list
+        """
+        if not self.skill_manager:
+            return []
+        return self.skill_manager.list_skills()
+
+    def _get_model_context_window(self) -> int:
+        """
+        Get the model's context window size in tokens.
+        Auto-detect based on model name.
+        
+        Model context windows:
+        - Claude 3.5/3.7 Sonnet: 200K tokens
+        - Claude 3 Opus: 200K tokens
+        - GPT-4 Turbo/128K: 128K tokens
+        - GPT-4: 8K-32K tokens
+        - GPT-3.5: 16K tokens
+        - DeepSeek: 64K tokens
+        
+        :return: Context window size in tokens
+        """
+        if self.model and hasattr(self.model, 'model'):
+            model_name = self.model.model.lower()
+
+            # Claude models - 200K context
+            if 'claude-3' in model_name or 'claude-sonnet' in model_name:
+                return 200000
+
+            # GPT-4 models
+            elif 'gpt-4' in model_name:
+                if 'turbo' in model_name or '128k' in model_name:
+                    return 128000
+                elif '32k' in model_name:
+                    return 32000
+                else:
+                    return 8000
+
+            # GPT-3.5
+            elif 'gpt-3.5' in model_name:
+                if '16k' in model_name:
+                    return 16000
+                else:
+                    return 4000
+
+            # DeepSeek
+            elif 'deepseek' in model_name:
+                return 64000
+            
+            # Gemini models
+            elif 'gemini' in model_name:
+                if '2.0' in model_name or 'exp' in model_name:
+                    return 2000000  # Gemini 2.0: 2M tokens
+                else:
+                    return 1000000  # Gemini 1.5: 1M tokens
+
+        # Default conservative value
+        return 128000
+
+    def _get_context_reserve_tokens(self) -> int:
+        """
+        Get the number of tokens to reserve for new requests.
+        This prevents context overflow by keeping a buffer.
+        
+        :return: Number of tokens to reserve
+        """
+        if self.context_reserve_tokens is not None:
+            return self.context_reserve_tokens
+
+        # Reserve ~10% of context window, with min 10K and max 200K
+        context_window = self._get_model_context_window()
+        reserve = int(context_window * 0.1)
+        return max(10000, min(200000, reserve))
+
+    def _estimate_message_tokens(self, message: dict) -> int:
+        """
+        Estimate token count for a message.
+
+        Uses chars/3 for Chinese-heavy content and chars/4 for ASCII-heavy content,
+        plus per-block overhead for tool_use / tool_result structures.
+
+        :param message: Message dict with 'role' and 'content'
+        :return: Estimated token count
+        """
+        content = message.get('content', '')
+        if isinstance(content, str):
+            return max(1, self._estimate_text_tokens(content))
+        elif isinstance(content, list):
+            total_tokens = 0
+            for part in content:
+                if not isinstance(part, dict):
+                    continue
+                block_type = part.get('type', '')
+                if block_type == 'text':
+                    total_tokens += self._estimate_text_tokens(part.get('text', ''))
+                elif block_type == 'image':
+                    total_tokens += 1200
+                elif block_type == 'tool_use':
+                    # tool_use has id + name + input (JSON-encoded)
+                    total_tokens += 50  # overhead for structure
+                    input_data = part.get('input', {})
+                    if isinstance(input_data, dict):
+                        import json
+                        input_str = json.dumps(input_data, ensure_ascii=False)
+                        total_tokens += self._estimate_text_tokens(input_str)
+                elif block_type == 'tool_result':
+                    # tool_result has tool_use_id + content
+                    total_tokens += 30  # overhead for structure
+                    result_content = part.get('content', '')
+                    if isinstance(result_content, str):
+                        total_tokens += self._estimate_text_tokens(result_content)
+                else:
+                    # Unknown block type, estimate conservatively
+                    total_tokens += 10
+            return max(1, total_tokens)
+        return 1
+
+    @staticmethod
+    def _estimate_text_tokens(text: str) -> int:
+        """
+        Estimate token count for a text string.
+
+        Chinese / CJK characters typically use ~1.5 tokens each,
+        while ASCII uses ~0.25 tokens per char (4 chars/token).
+        We use a weighted average based on the character mix.
+
+        :param text: Input text
+        :return: Estimated token count
+        """
+        if not text:
+            return 0
+        # Count non-ASCII characters (CJK, emoji, etc.)
+        non_ascii = sum(1 for c in text if ord(c) > 127)
+        ascii_count = len(text) - non_ascii
+        # CJK chars: ~1.5 tokens each; ASCII: ~0.25 tokens per char
+        return int(non_ascii * 1.5 + ascii_count * 0.25) + 1
+
+    def _find_tool(self, tool_name: str):
+        """Find and return a tool with the specified name"""
+        for tool in self.tools:
+            if tool.name == tool_name:
+                # Only pre-process stage tools can be actively called
+                if tool.stage == ToolStage.PRE_PROCESS:
+                    tool.model = self.model
+                    tool.context = self  # Set tool context
+                    return tool
+                else:
+                    # If it's a post-process tool, return None to prevent direct calling
+                    logger.warning(f"Tool {tool_name} is a post-process tool and cannot be called directly.")
+                    return None
+        return None
+
+    # output function based on mode
+    def output(self, message="", end="\n"):
+        if self.output_mode == "print":
+            print(message, end=end)
+        elif message:
+            logger.info(message)
+
+    def _execute_post_process_tools(self):
+        """Execute all post-process stage tools"""
+        # Get all post-process stage tools
+        post_process_tools = [tool for tool in self.tools if tool.stage == ToolStage.POST_PROCESS]
+
+        # Execute each tool
+        for tool in post_process_tools:
+            # Set tool context
+            tool.context = self
+
+            # Record start time for execution timing
+            start_time = time.time()
+
+            # Execute tool (with empty parameters, tool will extract needed info from context)
+            result = tool.execute({})
+
+            # Calculate execution time
+            execution_time = time.time() - start_time
+
+            # Capture tool use for tracking
+            self.capture_tool_use(
+                tool_name=tool.name,
+                input_params={},  # Post-process tools typically don't take parameters
+                output=result.result,
+                status=result.status,
+                error_message=str(result.result) if result.status == "error" else None,
+                execution_time=execution_time
+            )
+
+            # Log result
+            if result.status == "success":
+                # Print tool execution result in the desired format
+                self.output(f"\n🛠️ {tool.name}: {json.dumps(result.result)}")
+            else:
+                # Print failure in print mode
+                self.output(f"\n🛠️ {tool.name}: {json.dumps({'status': 'error', 'message': str(result.result)})}")
+
+    def capture_tool_use(self, tool_name, input_params, output, status, thought=None, error_message=None,
+                         execution_time=0.0):
+        """
+        Capture a tool use action.
+        
+        :param thought: thought content
+        :param tool_name: Name of the tool used
+        :param input_params: Parameters passed to the tool
+        :param output: Output from the tool
+        :param status: Status of the tool execution
+        :param error_message: Error message if the tool execution failed
+        :param execution_time: Time taken to execute the tool
+        """
+        tool_result = ToolResult(
+            tool_name=tool_name,
+            input_params=input_params,
+            output=output,
+            status=status,
+            error_message=error_message,
+            execution_time=execution_time
+        )
+
+        action = AgentAction(
+            agent_id=self.id if hasattr(self, 'id') else str(id(self)),
+            agent_name=self.name,
+            action_type=AgentActionType.TOOL_USE,
+            tool_result=tool_result,
+            thought=thought
+        )
+
+        self.captured_actions.append(action)
+
+        return action
+
+    def run_stream(self, user_message: str, on_event=None, clear_history: bool = False,
+                   skill_filter=None, cancel_event=None) -> str:
+        """
+        Execute single agent task with streaming (based on tool-call)
+
+        This method supports:
+        - Streaming output
+        - Multi-turn reasoning based on tool-call
+        - Event callbacks
+        - Persistent conversation history across calls
+        - User-initiated cancellation via ``cancel_event``
+
+        Args:
+            user_message: User message
+            on_event: Event callback function callback(event: dict)
+                     event = {"type": str, "timestamp": float, "data": dict}
+            clear_history: If True, clear conversation history before this call (default: False)
+            skill_filter: Optional list of skill names to include in this run
+            cancel_event: Optional threading.Event polled at agent checkpoints.
+                When set, the loop exits at the next safe point, injects a
+                "[Interrupted by user]" assistant note, and returns the
+                partial response. ``messages`` stays in a valid state
+                (tool_use/tool_result pairs preserved).
+
+        Returns:
+            Final response text
+
+        Example:
+            # Multi-turn conversation with memory
+            response1 = agent.run_stream("My name is Alice")
+            response2 = agent.run_stream("What's my name?")  # Will remember Alice
+
+            # Single-turn without memory
+            response = agent.run_stream("Hello", clear_history=True)
+        """
+        # Clear history if requested
+        if clear_history:
+            with self.messages_lock:
+                self.messages = []
+
+        # Get model to use
+        if not self.model:
+            raise ValueError("No model available for agent")
+
+        # Get full system prompt with skills
+        full_system_prompt = self.get_full_system_prompt(skill_filter=skill_filter)
+
+        # Create a copy of messages for this execution to avoid concurrent modification
+        # Record the original length to track which messages are new
+        with self.messages_lock:
+            messages_copy = self.messages.copy()
+            original_length = len(self.messages)
+
+        # Get max_context_turns from config
+        from config import conf
+        max_context_turns = conf().get("agent_max_context_turns", 20)
+        
+        # Create stream executor with copied message history
+        executor = AgentStreamExecutor(
+            agent=self,
+            model=self.model,
+            system_prompt=full_system_prompt,
+            tools=self.tools,
+            max_turns=self.max_steps,
+            on_event=on_event,
+            messages=messages_copy,  # Pass copied message history
+            max_context_turns=max_context_turns,
+            cancel_event=cancel_event,
+        )
+
+        # Execute
+        try:
+            response = executor.run_stream(user_message)
+        except Exception:
+            # If executor cleared its messages (context overflow / message format error),
+            # sync that back to the Agent's own message list so the next request
+            # starts fresh instead of hitting the same overflow forever.
+            if len(executor.messages) == 0:
+                with self.messages_lock:
+                    self.messages.clear()
+                    logger.info("[Agent] Cleared Agent message history after executor recovery")
+            raise
+
+        # Sync executor's messages back to agent (thread-safe).
+        # If the executor trimmed context, its message list is shorter than
+        # original_length, so we must replace rather than append.
+        with self.messages_lock:
+            self.messages = list(executor.messages)
+            # Track messages added in this run (user query + all assistant/tool messages)
+            # original_length may exceed executor.messages length after trimming
+            trim_adjusted_start = min(original_length, len(executor.messages))
+            self._last_run_new_messages = list(executor.messages[trim_adjusted_start:])
+        
+        # Store executor reference for agent_bridge to access files_to_send
+        self.stream_executor = executor
+
+        # Execute all post-process tools
+        self._execute_post_process_tools()
+
+        return response
+
+    def clear_history(self):
+        """Clear conversation history and captured actions"""
+        self.messages = []
+        self.captured_actions = []
\ No newline at end of file
diff --git a/agent/protocol/agent_stream.py b/agent/protocol/agent_stream.py
new file mode 100644
index 0000000..920112b
--- /dev/null
+++ b/agent/protocol/agent_stream.py
@@ -0,0 +1,1803 @@
+"""
+Agent Stream Execution Module - Multi-turn reasoning based on tool-call
+
+Provides streaming output, event system, and complete tool-call loop
+"""
+import json
+import time
+from typing import List, Dict, Any, Optional, Callable, Tuple
+
+from agent.protocol.cancel import AgentCancelledError
+from agent.protocol.models import LLMRequest, LLMModel
+from agent.protocol.message_utils import sanitize_claude_messages, compress_turn_to_text_only
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.log import logger
+from common.i18n import t as _t
+
+# Optional: repair malformed JSON args from non-strict providers (e.g. unescaped quotes in long content).
+try:
+    from json_repair import repair_json as _repair_json
+    _HAS_JSON_REPAIR = True
+except ImportError:
+    _HAS_JSON_REPAIR = False
+
+
+# Maximum number of characters of model "reasoning / thinking" content to persist
+# in conversation history. The full reasoning is still streamed to the UI in real
+# time (subject to its own SSE / rendering limits); this bound only controls what
+# is stored in DB and replayed in history. Long reasoning is not useful for later
+# context (the LLM never sees thinking blocks anyway) and bloats DB.
+# Keep aligned with the frontend REASONING_RENDER_CAP and the SSE
+# MAX_REASONING_STREAM_CHARS so that storage / stream / display all match.
+MAX_STORED_REASONING_CHARS = 4 * 1024  # 4 KB
+
+# Marker inserted between head and tail when reasoning is truncated.
+_REASONING_TRUNCATE_MARKER = "\n\n... [reasoning truncated, {omitted} chars omitted] ...\n\n"
+
+
+def _truncate_reasoning_for_storage(text: str) -> str:
+    """Trim long reasoning to head + tail with an omission marker.
+
+    Keeps the first and last halves of MAX_STORED_REASONING_CHARS so both the
+    initial chain-of-thought and the final conclusions are preserved for UI
+    replay, without storing the entire (often very large) middle.
+    """
+    if not text:
+        return text
+    if len(text) <= MAX_STORED_REASONING_CHARS:
+        return text
+    half = MAX_STORED_REASONING_CHARS // 2
+    head = text[:half]
+    tail = text[-half:]
+    omitted = len(text) - len(head) - len(tail)
+    return head + _REASONING_TRUNCATE_MARKER.format(omitted=omitted) + tail
+
+
+def _parse_tool_args(args_str: str, finish_reason: Optional[str]) -> Tuple[dict, Optional[str]]:
+    """Parse tool args JSON. Returns (args, error_msg); error_msg is None on success.
+
+    On JSONDecodeError: detect truncation first (skip repair, surface max_tokens hint);
+    otherwise try json-repair for escape issues; finally fall back to the raw decoder error.
+    """
+    if not args_str:
+        return {}, None
+    try:
+        return json.loads(args_str), None
+    except json.JSONDecodeError as e:
+        if finish_reason in ("length", "max_tokens") or not args_str.rstrip().endswith("}"):
+            return {}, "Output truncated (max_tokens reached). Split content into smaller chunks across multiple tool calls."
+        if _HAS_JSON_REPAIR:
+            try:
+                repaired = _repair_json(args_str, return_objects=True)
+                if isinstance(repaired, dict):
+                    logger.warning(f"Tool args JSON repaired ({len(args_str)} chars)")
+                    return repaired, None
+            except Exception:
+                pass
+        return {}, f"Invalid JSON in tool arguments: {e.msg}"
+
+
+class AgentStreamExecutor:
+    """
+    Agent Stream Executor
+    
+    Handles multi-turn reasoning loop based on tool-call:
+    1. LLM generates response (may include tool calls)
+    2. Execute tools
+    3. Return results to LLM
+    4. Repeat until no more tool calls
+    """
+
+    def __init__(
+            self,
+            agent,  # Agent instance
+            model: LLMModel,
+            system_prompt: str,
+            tools: List[BaseTool],
+            max_turns: int = 50,
+            on_event: Optional[Callable] = None,
+            messages: Optional[List[Dict]] = None,
+            max_context_turns: int = 30,
+            cancel_event=None,
+    ):
+        """
+        Initialize stream executor
+        
+        Args:
+            agent: Agent instance (for accessing context)
+            model: LLM model
+            system_prompt: System prompt
+            tools: List of available tools
+            max_turns: Maximum number of turns
+            on_event: Event callback function
+            messages: Optional existing message history (for persistent conversations)
+            max_context_turns: Maximum number of conversation turns to keep in context
+            cancel_event: Optional threading.Event used to signal user cancel.
+                Checked at every safe point (turn boundary, before tool execution,
+                during LLM streaming). When set, raises AgentCancelledError which
+                run_stream catches to gracefully wind down.
+        """
+        self.agent = agent
+        self.model = model
+        self.system_prompt = system_prompt
+        # Convert tools list to dict
+        self.tools = {tool.name: tool for tool in tools} if isinstance(tools, list) else tools
+        self.max_turns = max_turns
+        self.on_event = on_event
+        self.max_context_turns = max_context_turns
+        self.cancel_event = cancel_event
+
+        # Message history - use provided messages or create new list
+        self.messages = messages if messages is not None else []
+        
+        # Tool failure tracking for retry protection
+        self.tool_failure_history = []  # List of (tool_name, args_hash, success) tuples
+        
+        # Track files to send (populated by read tool)
+        self.files_to_send = []  # List of file metadata dicts
+
+    def _check_cancelled(self) -> None:
+        """Raise AgentCancelledError if the user requested cancellation.
+
+        Called at safe points (turn start, between tool calls, between LLM
+        chunks). Cheap to call: just an Event.is_set() probe.
+        """
+        if self.cancel_event is not None and self.cancel_event.is_set():
+            raise AgentCancelledError("agent cancelled by user")
+
+    def _handle_cancelled(self, partial_response: str) -> None:
+        """Wind down ``self.messages`` after a user-initiated cancel.
+
+        The messages list may be in any of these states when we get here:
+          (a) Last message is an assistant message containing tool_use
+              blocks but the matching tool_result has not been appended yet.
+          (b) Last message is an assistant text-only reply (cancel happened
+              right before the next turn started).
+          (c) Last message is a user tool_result message and we cancelled
+              between turns.
+
+        For (a) we MUST synthesise tool_result blocks, otherwise the next
+        request will fail Claude/OpenAI's strict pairing validation. For
+        (b)/(c) the state is already valid and we just append a small
+        cancellation note so the user/LLM both see the boundary clearly.
+        """
+        try:
+            # Step 1: close any orphaned tool_use in the trailing assistant
+            # message by injecting matching tool_result blocks.
+            if self.messages and isinstance(self.messages[-1], dict) \
+                    and self.messages[-1].get("role") == "assistant":
+                last = self.messages[-1]
+                content = last.get("content")
+                if isinstance(content, list):
+                    pending_tool_use_ids = [
+                        block.get("id")
+                        for block in content
+                        if isinstance(block, dict) and block.get("type") == "tool_use"
+                    ]
+                    pending_tool_use_ids = [tid for tid in pending_tool_use_ids if tid]
+                    if pending_tool_use_ids:
+                        tool_result_blocks = [
+                            {
+                                "type": "tool_result",
+                                "tool_use_id": tid,
+                                "content": "Cancelled by user before this tool finished.",
+                                "is_error": True,
+                            }
+                            for tid in pending_tool_use_ids
+                        ]
+                        self.messages.append({
+                            "role": "user",
+                            "content": tool_result_blocks,
+                        })
+                        logger.info(
+                            f"[Agent] Injected {len(tool_result_blocks)} cancellation "
+                            f"tool_result blocks to keep message history valid"
+                        )
+
+            # Step 2: append a stable "interrupted" marker so the LLM sees a
+            # clear stop boundary on the next turn.
+            self.messages.append({
+                "role": "assistant",
+                "content": [{"type": "text", "text": "_(Cancelled by user)_"}],
+            })
+        except Exception as e:
+            logger.warning(f"[Agent] _handle_cancelled cleanup failed: {e}")
+
+    def _emit_event(self, event_type: str, data: dict = None):
+        """Emit event"""
+        if self.on_event:
+            try:
+                self.on_event({
+                    "type": event_type,
+                    "timestamp": time.time(),
+                    "data": data or {}
+                })
+            except Exception as e:
+                logger.error(f"Event callback error: {e}")
+    
+    def _is_thinking_enabled(self) -> bool:
+        """Whether deep-thinking mode is on at the model layer.
+
+        Mirrors the global toggle used by ``bridge.agent_bridge`` when deciding
+        whether to send ``thinking={"type": "enabled"}`` to the model. Used for
+        logging and reasoning-update event emission across all channels.
+        """
+        from config import conf
+        return bool(conf().get("enable_thinking", False))
+
+    def _should_render_thinking_inline(self) -> bool:
+        """Whether ``<think>...</think>`` blocks embedded directly in ``content``
+        (MiniMax, some third-party proxies) should be surfaced to the channel.
+
+        Only the Web console can render them in a collapsible panel. IM channels
+        (WeChat/WeCom/DingTalk/Feishu) must strip them, otherwise users see raw
+        XML tags in their chat.
+        """
+        from config import conf
+        channel_type = getattr(self.model, 'channel_type', '') or ''
+        return conf().get("enable_thinking", False) and channel_type == 'web'
+
+    def _filter_think_tags(self, text: str) -> str:
+        """
+        Handle <think>...</think> blocks in content returned by some LLM providers
+        (e.g., MiniMax).
+
+        - When inline thinking rendering is allowed (Web + thinking enabled):
+          remove only the tags, keep the content inside.
+        - Otherwise (IM channels, or thinking disabled globally): remove both
+          the tags and the content entirely.
+        """
+        if not text:
+            return text
+        import re
+        if self._should_render_thinking_inline():
+            text = re.sub(r'<think>', '', text)
+            text = re.sub(r'</think>', '', text)
+        else:
+            text = re.sub(r'<think>[\s\S]*?</think>', '', text)
+            # Also strip unclosed <think> tag at the end (streaming partial)
+            text = re.sub(r'<think>[\s\S]*$', '', text)
+        return text
+
+    def _hash_args(self, args: dict) -> str:
+        """Generate a simple hash for tool arguments"""
+        import hashlib
+        # Sort keys for consistent hashing
+        args_str = json.dumps(args, sort_keys=True, ensure_ascii=False)
+        return hashlib.md5(args_str.encode()).hexdigest()[:8]
+    
+    def _check_consecutive_failures(self, tool_name: str, args: dict) -> Tuple[bool, str, bool]:
+        """
+        Check if tool has failed too many times consecutively or called repeatedly with same args
+        
+        Returns:
+            (should_stop, reason, is_critical)
+            - should_stop: Whether to stop tool execution
+            - reason: Reason for stopping
+            - is_critical: Whether to abort entire conversation (True for 8+ failures)
+        """
+        args_hash = self._hash_args(args)
+        
+        # Count consecutive calls (both success and failure) for same tool + args
+        # This catches infinite loops where tool succeeds but LLM keeps calling it
+        same_args_calls = 0
+        for name, ahash, success in reversed(self.tool_failure_history):
+            if name == tool_name and ahash == args_hash:
+                same_args_calls += 1
+            else:
+                break  # Different tool or args, stop counting
+        
+        # Stop at 5 consecutive calls with same args (whether success or failure)
+        if same_args_calls >= 5:
+            return True, f"工具 '{tool_name}' 使用相同参数已被调用 {same_args_calls} 次，停止执行以防止无限循环。如果需要查看配置，结果已在之前的调用中返回。", False
+        
+        # Count consecutive failures for same tool + args
+        same_args_failures = 0
+        for name, ahash, success in reversed(self.tool_failure_history):
+            if name == tool_name and ahash == args_hash:
+                if not success:
+                    same_args_failures += 1
+                else:
+                    break  # Stop at first success
+            else:
+                break  # Different tool or args, stop counting
+        
+        if same_args_failures >= 3:
+            return True, f"工具 '{tool_name}' 使用相同参数连续失败 {same_args_failures} 次，停止执行以防止无限循环", False
+        
+        # Count consecutive failures for same tool (any args)
+        same_tool_failures = 0
+        for name, ahash, success in reversed(self.tool_failure_history):
+            if name == tool_name:
+                if not success:
+                    same_tool_failures += 1
+                else:
+                    break  # Stop at first success
+            else:
+                break  # Different tool, stop counting
+        
+        # Hard stop at 8 failures - abort with critical message
+        if same_tool_failures >= 8:
+            return True, _t(
+                "抱歉，我没能完成这个任务。可能是我理解有误或者当前方法不太合适。\n\n建议你：\n• 换个方式描述需求试试\n• 把任务拆分成更小的步骤\n• 或者换个思路来解决",
+                "Sorry, I couldn't complete this task. I may have misunderstood, or my current approach isn't quite right.\n\nYou could try:\n• Rephrasing your request\n• Breaking the task into smaller steps\n• Taking a different approach",
+            ), True
+        
+        # Warning at 6 failures
+        if same_tool_failures >= 6:
+            return True, f"工具 '{tool_name}' 连续失败 {same_tool_failures} 次（使用不同参数），停止执行以防止无限循环", False
+        
+        return False, "", False
+    
+    def _record_tool_result(self, tool_name: str, args: dict, success: bool):
+        """Record tool execution result for failure tracking"""
+        args_hash = self._hash_args(args)
+        self.tool_failure_history.append((tool_name, args_hash, success))
+        # Keep only last 50 records to avoid memory bloat
+        if len(self.tool_failure_history) > 50:
+            self.tool_failure_history = self.tool_failure_history[-50:]
+
+    def run_stream(self, user_message: str) -> str:
+        """
+        Execute streaming reasoning loop
+        
+        Args:
+            user_message: User message
+            
+        Returns:
+            Final response text
+        """
+        # Log user message with model info. Truncate very long messages (e.g.
+        # injected transcripts / large prompts) so logs stay readable.
+        thinking_enabled = self._is_thinking_enabled()
+        thinking_label = " | 💭 thinking" if thinking_enabled else ""
+        _log_msg = user_message if len(user_message) <= 500 else (
+            user_message[:500] + f" …(+{len(user_message) - 500} chars)"
+        )
+        logger.info(f"🤖 {self.model.model}{thinking_label} | 👤 {_log_msg}")        
+        
+        # Add user message (Claude format - use content blocks for consistency)
+        self.messages.append({
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": user_message
+                }
+            ]
+        })
+
+        # Trim context ONCE before the agent loop starts, not during tool steps.
+        # This ensures tool_use/tool_result chains created during the current run
+        # are never stripped mid-execution (which would cause LLM loops).
+        self._trim_messages()
+
+        # Validate after trimming: trimming may leave orphaned tool_use at the
+        # boundary (e.g. the last kept turn ends with an assistant tool_use whose
+        # tool_result was in a discarded turn).
+        self._validate_and_fix_messages()
+
+        self._emit_event("agent_start")
+
+        # Reset the run-scoped MCP tool-retrieval accumulator. On-demand tool
+        # retrieval only grows this set within a run, so a tool that already
+        # produced a tool_use never disappears from the schema mid-run (which
+        # would make Claude/MiniMax raise a message-format error).
+        self._retrieved_mcp_names = set()
+
+        final_response = ""
+        turn = 0
+
+        cancelled = False
+        try:
+            while turn < self.max_turns:
+                # Check at the very top of every turn so a cancel arriving
+                # between turns short-circuits cleanly.
+                self._check_cancelled()
+
+                turn += 1
+                logger.info(f"[Agent] Turn {turn}")
+                self._emit_event("turn_start", {"turn": turn})
+
+                # Call LLM (enable retry_on_empty for better reliability)
+                assistant_msg, tool_calls = self._call_llm_stream(retry_on_empty=True)
+                final_response = assistant_msg
+
+                # No tool calls, end loop
+                if not tool_calls:
+                    # 检查是否返回了空响应
+                    if not assistant_msg:
+                        logger.warning(f"[Agent] LLM returned empty response after retry (no content and no tool calls)")
+                        logger.info(f"[Agent] This usually happens when LLM thinks the task is complete after tool execution")
+                        
+                        # 如果之前有工具调用，强制要求 LLM 生成文本回复
+                        if turn > 1:
+                            logger.info(f"[Agent] Requesting explicit response from LLM...")
+                            
+                            # Remember position so we can remove the injected prompt later
+                            prompt_insert_idx = len(self.messages)
+                            
+                            # 添加一条消息，明确要求回复用户
+                            self.messages.append({
+                                "role": "user",
+                                "content": [{
+                                    "type": "text",
+                                    "text": "请向用户说明刚才工具执行的结果或回答用户的问题。"
+                                }]
+                            })
+                            
+                            # 再调用一次 LLM
+                            assistant_msg, tool_calls = self._call_llm_stream(retry_on_empty=False)
+                            final_response = assistant_msg
+                            
+                            # Remove the injected prompt from history so it doesn't
+                            # appear as a user message in persisted conversations.
+                            # _call_llm_stream may have appended an assistant message
+                            # after the prompt, so we locate and remove only the prompt.
+                            if (prompt_insert_idx < len(self.messages)
+                                    and self.messages[prompt_insert_idx].get("role") == "user"):
+                                self.messages.pop(prompt_insert_idx)
+                                logger.debug("[Agent] Removed injected explicit-response prompt from message history")
+                            
+                            # If LLM responded with tool_calls instead of text, fall through
+                            # to the tool execution path below (don't break the loop).
+                            if tool_calls:
+                                logger.info(
+                                    f"[Agent] LLM returned tool_calls in explicit-response retry, "
+                                    f"continuing to execute tools instead of breaking"
+                                )
+                            elif not assistant_msg:
+                                # Still empty (no text and no tool_calls): use fallback
+                                logger.warning(f"[Agent] Still empty after explicit request")
+                                final_response = _t(
+                                    "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。",
+                                    "Sorry, I can't generate a reply right now. Please try rephrasing your request, or try again later.",
+                                )
+                                logger.info(f"Generated fallback response for empty LLM output")
+                        else:
+                            # First-turn empty reply, fall back directly
+                            final_response = _t(
+                                "抱歉，我暂时无法生成回复。请尝试换一种方式描述你的需求，或稍后再试。",
+                                "Sorry, I can't generate a reply right now. Please try rephrasing your request, or try again later.",
+                            )
+                            logger.info(f"Generated fallback response for empty LLM output")
+                    else:
+                        logger.info(f"💭 {assistant_msg[:150]}{'...' if len(assistant_msg) > 150 else ''}")
+                    
+                    # If the explicit-response retry produced tool_calls, skip the break
+                    # and continue down to the tool execution branch in this same iteration.
+                    if not tool_calls:
+                        logger.debug(f"✅ Done (no tool calls)")
+                        self._emit_event("turn_end", {
+                            "turn": turn,
+                            "has_tool_calls": False
+                        })
+                        break
+
+                # Log tool calls with arguments (truncate long values like base64)
+                tool_calls_str = []
+                for tc in tool_calls:
+                    args = tc.get('arguments') or {}
+                    if isinstance(args, dict):
+                        parts = []
+                        for k, v in args.items():
+                            v_str = str(v)
+                            if len(v_str) > 200:
+                                v_str = v_str[:200] + f"...({len(v_str)} chars)"
+                            parts.append(f"{k}={v_str}")
+                        args_str = ', '.join(parts)
+                        if args_str:
+                            tool_calls_str.append(f"{tc['name']}({args_str})")
+                        else:
+                            tool_calls_str.append(tc['name'])
+                    else:
+                        tool_calls_str.append(tc['name'])
+                logger.info(f"🔧 {', '.join(tool_calls_str)}")
+
+                # Execute tools
+                tool_results = []
+                tool_result_blocks = []
+
+                try:
+                    for tool_call in tool_calls:
+                        # Honour cancel between tool invocations within the same turn
+                        self._check_cancelled()
+                        result = self._execute_tool(tool_call)
+                        tool_results.append(result)
+                        
+                        # Debug: Check if tool is being called repeatedly with same args
+                        if turn > 2:
+                            # Check last N tool calls for repeats
+                            repeat_count = sum(
+                                1 for name, ahash, _ in self.tool_failure_history[-10:]
+                                if name == tool_call["name"] and ahash == self._hash_args(tool_call["arguments"])
+                            )
+                            if repeat_count >= 3:
+                                logger.warning(
+                                    f"⚠️  Tool '{tool_call['name']}' has been called {repeat_count} times "
+                                    f"with same arguments. This may indicate a loop."
+                                )
+                        
+                        # Check if this is a file to send
+                        if result.get("status") == "success" and isinstance(result.get("result"), dict):
+                            result_data = result.get("result")
+                            if result_data.get("type") == "file_to_send":
+                                self.files_to_send.append(result_data)
+                                logger.info(f"📎 File queued for sending: {result_data.get('file_name', result_data.get('path'))}")
+                                self._emit_event("file_to_send", result_data)
+                        
+                        # Check for critical error - abort entire conversation
+                        if result.get("status") == "critical_error":
+                            logger.error(f"💥 Fatal error detected, aborting conversation")
+                            final_response = result.get('result') or _t("任务执行失败", "Task execution failed")
+                            return final_response
+                        
+                        # Log tool result in compact format
+                        status_emoji = "✅" if result.get("status") == "success" else "❌"
+                        result_data = result.get('result', '')
+                        # Format result string with proper Chinese character support
+                        if isinstance(result_data, (dict, list)):
+                            result_str = json.dumps(result_data, ensure_ascii=False)
+                        else:
+                            result_str = str(result_data)
+                        logger.info(f"  {status_emoji} {tool_call['name']} ({result.get('execution_time', 0):.2f}s): {result_str[:200]}{'...' if len(result_str) > 200 else ''}")
+
+                        # Build tool result block (Claude format)
+                        # Format content in a way that's easy for LLM to understand
+                        is_error = result.get("status") == "error"
+
+                        if is_error:
+                            # For errors, provide clear error message
+                            result_content = f"Error: {result.get('result', 'Unknown error')}"
+                        elif isinstance(result.get('result'), dict):
+                            # For dict results, use JSON format
+                            result_content = json.dumps(result.get('result'), ensure_ascii=False)
+                        elif isinstance(result.get('result'), str):
+                            # For string results, use directly
+                            result_content = result.get('result')
+                        else:
+                            # Fallback to full JSON
+                            result_content = json.dumps(result, ensure_ascii=False)
+
+                        # Truncate excessively large tool results for the current turn
+                        # Historical turns will be further truncated in _trim_messages()
+                        MAX_CURRENT_TURN_RESULT_CHARS = 50000
+                        if len(result_content) > MAX_CURRENT_TURN_RESULT_CHARS:
+                            truncated_len = len(result_content)
+                            result_content = result_content[:MAX_CURRENT_TURN_RESULT_CHARS] + \
+                                f"\n\n[Output truncated: {truncated_len} chars total, showing first {MAX_CURRENT_TURN_RESULT_CHARS} chars]"
+                            logger.info(f"📎 Truncated tool result for '{tool_call['name']}': {truncated_len} -> {MAX_CURRENT_TURN_RESULT_CHARS} chars")
+
+                        tool_result_block = {
+                            "type": "tool_result",
+                            "tool_use_id": tool_call["id"],
+                            "content": result_content
+                        }
+                        
+                        # Add is_error field for Claude API (helps model understand failures)
+                        if is_error:
+                            tool_result_block["is_error"] = True
+                        
+                        tool_result_blocks.append(tool_result_block)
+                
+                finally:
+                    # CRITICAL: Always add tool_result to maintain message history integrity
+                    # Even if tool execution fails, we must add error results to match tool_use
+                    if tool_result_blocks:
+                        # Add tool results to message history as user message (Claude format)
+                        self.messages.append({
+                            "role": "user",
+                            "content": tool_result_blocks
+                        })
+                        
+                        # Detect potential infinite loop: same tool called multiple times with success
+                        # If detected, add a hint to LLM to stop calling tools and provide response
+                        if turn >= 3 and len(tool_calls) > 0:
+                            tool_name = tool_calls[0]["name"]
+                            args_hash = self._hash_args(tool_calls[0]["arguments"])
+                            
+                            # Count recent successful calls with same tool+args
+                            recent_success_count = 0
+                            for name, ahash, success in reversed(self.tool_failure_history[-10:]):
+                                if name == tool_name and ahash == args_hash and success:
+                                    recent_success_count += 1
+                            
+                            # If tool was called successfully 3+ times with same args, add hint to stop loop
+                            if recent_success_count >= 3:
+                                logger.warning(
+                                    f"⚠️  Detected potential loop: '{tool_name}' called {recent_success_count} times "
+                                    f"with same args. Adding hint to LLM to provide final response."
+                                )
+                                # Add a gentle hint message to guide LLM to respond
+                                self.messages.append({
+                                    "role": "user",
+                                    "content": [{
+                                        "type": "text",
+                                        "text": "工具已成功执行并返回结果。请基于这些信息向用户做出回复，不要重复调用相同的工具。"
+                                    }]
+                                })
+                    elif tool_calls:
+                        # If we have tool_calls but no tool_result_blocks (unexpected error),
+                        # create error results for all tool calls to maintain message integrity
+                        logger.warning("⚠️ Tool execution interrupted, adding error results to maintain message history")
+                        emergency_blocks = []
+                        for tool_call in tool_calls:
+                            emergency_blocks.append({
+                                "type": "tool_result",
+                                "tool_use_id": tool_call["id"],
+                                "content": "Error: Tool execution was interrupted",
+                                "is_error": True
+                            })
+                        self.messages.append({
+                            "role": "user",
+                            "content": emergency_blocks
+                        })
+
+                self._emit_event("turn_end", {
+                    "turn": turn,
+                    "has_tool_calls": True,
+                    "tool_count": len(tool_calls)
+                })
+
+            if turn >= self.max_turns:
+                logger.warning(f"⚠️  Reached max decision step limit: {self.max_turns}")
+                
+                # Force model to summarize without tool calls
+                logger.info(f"[Agent] Requesting summary from LLM after reaching max steps...")
+                
+                # Remember position before injecting the prompt so we can remove it later
+                prompt_insert_idx = len(self.messages)
+                
+                # Add a temporary prompt to force summary
+                self.messages.append({
+                    "role": "user",
+                    "content": [{
+                        "type": "text",
+                        "text": f"你已经执行了{turn}个决策步骤，达到了单次运行的最大步数限制。请总结一下你目前的执行过程和结果，告诉用户当前的进展情况。不要再调用工具，直接用文字回复。"
+                    }]
+                })
+                
+                # Call LLM one more time to get summary (without retry to avoid loops)
+                try:
+                    summary_response, summary_tools = self._call_llm_stream(retry_on_empty=False)
+                    if summary_response:
+                        final_response = summary_response
+                        logger.info(f"💭 Summary: {summary_response[:150]}{'...' if len(summary_response) > 150 else ''}")
+                    else:
+                        # Fallback if model still doesn't respond
+                        final_response = _t(
+                            f"我已经执行了{turn}个决策步骤，达到了单次运行的步数上限。任务可能还未完全完成，建议你将任务拆分成更小的步骤，或者换一种方式描述需求。",
+                            f"I've taken {turn} decision steps and reached the per-run limit. The task may not be fully complete — try breaking it into smaller steps, or describe your request differently.",
+                        )
+                except Exception as e:
+                    logger.warning(f"Failed to get summary from LLM: {e}")
+                    final_response = _t(
+                        f"我已经执行了{turn}个决策步骤，达到了单次运行的步数上限。任务可能还未完全完成，建议你将任务拆分成更小的步骤，或者换一种方式描述需求。",
+                        f"I've taken {turn} decision steps and reached the per-run limit. The task may not be fully complete — try breaking it into smaller steps, or describe your request differently.",
+                    )
+                finally:
+                    # Remove the injected user prompt from history to avoid polluting
+                    # persisted conversation records. The assistant summary (if any)
+                    # was already appended by _call_llm_stream and is kept.
+                    if (prompt_insert_idx < len(self.messages)
+                            and self.messages[prompt_insert_idx].get("role") == "user"):
+                        self.messages.pop(prompt_insert_idx)
+                        logger.debug("[Agent] Removed injected max-steps prompt from message history")
+
+        except AgentCancelledError:
+            # User-initiated stop: wind down message history cleanly so the
+            # next turn is unaffected; channels emit a "cancelled" UI event.
+            cancelled = True
+            logger.info(f"[Agent] 🛑 Cancelled by user (turn {turn})")
+            self._handle_cancelled(final_response)
+            if not final_response or not final_response.strip():
+                final_response = "_(Cancelled)_"
+
+        except Exception as e:
+            logger.error(f"❌ Agent execution error: {e}")
+            self._emit_event("error", {"error": str(e)})
+            raise
+
+        finally:
+            final_response = final_response.strip() if final_response else final_response
+            if cancelled:
+                # Emit before agent_end so channels can mark UI as cancelled
+                self._emit_event("agent_cancelled", {"final_response": final_response})
+            logger.info(f"[Agent] 🏁 Done ({turn} turns)" + (" [cancelled]" if cancelled else ""))
+            self._emit_event("agent_end", {"final_response": final_response, "cancelled": cancelled})
+
+        return final_response
+
+    def _select_tools_for_injection(self) -> list:
+        """Decide which tools to inject into the current LLM turn.
+
+        Built-in tools are ALWAYS injected in full (skills and core flows hard
+        depend on them). MCP tools are also injected in full UNLESS on-demand
+        retrieval is enabled AND the MCP tool count exceeds the configured
+        threshold — then only the most relevant MCP tools are injected, unioned
+        with those already selected earlier in this run (only-grows, so a tool
+        that already produced a tool_use never vanishes from the schema).
+
+        Degrades safely: disabled feature, no embedding provider, embedding
+        failure, count below threshold, or any error → inject all tools. Tools
+        are never silently dropped.
+        """
+        all_tools = list(self.tools.values())
+        try:
+            from config import conf
+            if not conf().get("mcp_tool_retrieval_enabled", False):
+                return all_tools
+
+            from agent.tools.mcp.mcp_tool import McpTool
+            mcp_tools = [t for t in all_tools if isinstance(t, McpTool)]
+            builtin_tools = [t for t in all_tools if not isinstance(t, McpTool)]
+
+            threshold = int(conf().get("mcp_tool_retrieval_threshold", 20) or 20)
+            if len(mcp_tools) <= threshold:
+                return all_tools
+
+            top_k = int(conf().get("mcp_tool_retrieval_top_k", 10) or 10)
+
+            from agent.tools import ToolManager
+            from agent.tools.mcp.tool_retrieval import (
+                build_retrieval_query,
+                select_mcp_tools,
+            )
+
+            tm = ToolManager()
+            tool_vectors = tm.get_mcp_tool_vectors()
+            query = build_retrieval_query(self.messages)
+            query_vector = tm.embed_query(query)
+
+            selected = select_mcp_tools(
+                query_vector,
+                tool_vectors,
+                top_k,
+                getattr(self, "_retrieved_mcp_names", set()),
+            )
+            if selected is None:
+                # No provider / empty index / error → full injection.
+                return all_tools
+
+            # Persist the accumulated selection for subsequent turns.
+            self._retrieved_mcp_names = selected
+
+            selected_mcp = [t for t in mcp_tools if t.name in selected]
+            logger.info(
+                f"[ToolRetrieval] Injecting {len(builtin_tools)} built-in + "
+                f"{len(selected_mcp)}/{len(mcp_tools)} MCP tool(s) (top_k={top_k})"
+            )
+            return builtin_tools + selected_mcp
+        except Exception as e:
+            logger.debug(f"[ToolRetrieval] full injection (retrieval skipped): {e}")
+            return all_tools
+
+    def _call_llm_stream(self, retry_on_empty=True, retry_count=0, max_retries=3,
+                         _overflow_retry: bool = False) -> Tuple[str, List[Dict]]:
+        """
+        Call LLM with streaming and automatic retry on errors
+        
+        Args:
+            retry_on_empty: Whether to retry once if empty response is received
+            retry_count: Current retry attempt (internal use)
+            max_retries: Maximum number of retries for API errors
+            _overflow_retry: Internal flag indicating this is a retry after context overflow
+        
+        Returns:
+            (response_text, tool_calls)
+        """
+        # Validate and fix message history (e.g. orphaned tool_result blocks).
+        # Context trimming is done once in run_stream() before the loop starts,
+        # NOT here — trimming mid-execution would strip the current run's
+        # tool_use/tool_result chains and cause LLM loops.
+        self._validate_and_fix_messages()
+
+        # Prepare messages
+        messages = self._prepare_messages()
+        turns = self._identify_complete_turns()
+        logger.info(f"Sending {len(messages)} messages ({len(turns)} turns) to LLM")
+
+        # Pull in any MCP tools that finished loading since this turn started.
+        # Cheap dict reconciliation (microseconds) — lets the agent pick up
+        # newly available MCP tools mid-conversation without a session restart.
+        try:
+            from agent.tools import ToolManager
+            ToolManager().sync_mcp_into_agent(self)
+        except Exception as e:
+            logger.debug(f"[Agent] MCP sync skipped: {e}")
+
+        # Prepare tool definitions. Prefer get_json_schema() when it yields
+        # real properties (lets tools augment schema at runtime), otherwise
+        # fall back to the static `tool.params` (MCP tools rely on this).
+        tools_schema = None
+        if self.tools:
+            tools_schema = []
+            for tool in self._select_tools_for_injection():
+                input_schema = tool.params
+                try:
+                    dynamic = (tool.get_json_schema() or {}).get("parameters") or {}
+                    if dynamic.get("properties"):
+                        input_schema = dynamic
+                except Exception:
+                    pass
+                tools_schema.append({
+                    "name": tool.name,
+                    "description": tool.description,
+                    "input_schema": input_schema,
+                })
+
+        # Debug: dump the full system prompt and messages sent to the LLM.
+        # Gated behind `debug` config to avoid flooding normal logs.
+        # try:
+        #     from config import conf
+        #     if conf().get("debug", False):
+        #         logger.debug(
+        #             "[Agent][debug] system_prompt sent to LLM "
+        #             f"({len(self.system_prompt or '')} chars):\n"
+        #             "================ SYSTEM PROMPT BEGIN ================\n"
+        #             f"{self.system_prompt}\n"
+        #             "================ SYSTEM PROMPT END =================="
+        #         )
+        #         logger.info(f"[Agent][debug] messages sent to LLM: {messages}")
+        # except Exception:
+        #     pass
+
+        # Create request
+        request = LLMRequest(
+            messages=messages,
+            temperature=0,
+            stream=True,
+            tools=tools_schema,
+            system=self.system_prompt  # Pass system prompt separately for Claude API
+        )
+
+        self._emit_event("message_start", {"role": "assistant"})
+
+        # Streaming response
+        full_content = ""
+        full_reasoning = ""
+        tool_calls_buffer = {}  # {index: {id, name, arguments}}
+        gemini_raw_parts = None  # Preserve Gemini thoughtSignature for round-trip
+        stop_reason = None  # Track why the stream stopped
+
+        try:
+            stream = self.model.call_stream(request)
+
+            # Probe cancel every N chunks to bound reaction time without
+            # checking on every token.
+            _cancel_probe_counter = 0
+            _CANCEL_PROBE_EVERY = 8
+
+            for chunk in stream:
+                _cancel_probe_counter += 1
+                if _cancel_probe_counter >= _CANCEL_PROBE_EVERY:
+                    _cancel_probe_counter = 0
+                    if self.cancel_event is not None and self.cancel_event.is_set():
+                        # Persist partial text only; tool_use args may be
+                        # truncated mid-stream and would fail validation.
+                        logger.info("[Agent] cancel detected mid-stream, aborting LLM call")
+                        if full_content:
+                            partial_msg = {
+                                "role": "assistant",
+                                "content": [{"type": "text", "text": full_content}],
+                            }
+                            self.messages.append(partial_msg)
+                        self._emit_event("message_end", {
+                            "content": full_content,
+                            "tool_calls": [],
+                            "cancelled": True,
+                        })
+                        raise AgentCancelledError("cancelled during LLM streaming")
+
+                # Check for errors
+                if isinstance(chunk, dict) and chunk.get("error"):
+                    # Extract error message from nested structure
+                    error_data = chunk.get("error", {})
+                    if isinstance(error_data, dict):
+                        error_msg = error_data.get("message", chunk.get("message", "Unknown error"))
+                        error_code = error_data.get("code", "")
+                        error_type = error_data.get("type", "")
+                    else:
+                        error_msg = chunk.get("message", str(error_data))
+                        error_code = ""
+                        error_type = ""
+                    
+                    status_code = chunk.get("status_code", "N/A")
+                    
+                    # Log error with all available information
+                    logger.error(f"🔴 Stream API Error:")
+                    logger.error(f"   Message: {error_msg}")
+                    logger.error(f"   Status Code: {status_code}")
+                    logger.error(f"   Error Code: {error_code}")
+                    logger.error(f"   Error Type: {error_type}")
+                    logger.error(f"   Full chunk: {chunk}")
+                    
+                    # Check if this is a context overflow error (keyword-based, works for all models)
+                    # Don't rely on specific status codes as different providers use different codes
+                    error_msg_lower = error_msg.lower()
+                    is_overflow = any(keyword in error_msg_lower for keyword in [
+                        'context length exceeded', 'maximum context length', 'prompt is too long',
+                        'context overflow', 'context window', 'too large', 'exceeds model context',
+                        'request_too_large', 'request exceeds the maximum size', 'tokens exceed'
+                    ])
+                    
+                    if is_overflow:
+                        # Mark as context overflow for special handling
+                        raise Exception(f"[CONTEXT_OVERFLOW] {error_msg} (Status: {status_code})")
+                    else:
+                        # Raise exception with full error message for retry logic
+                        raise Exception(f"{error_msg} (Status: {status_code}, Code: {error_code}, Type: {error_type})")
+
+                # Parse chunk
+                if isinstance(chunk, dict) and chunk.get("choices"):
+                    choice = chunk["choices"][0]
+                    delta = choice.get("delta", {})
+                    
+                    # Capture finish_reason if present
+                    finish_reason = choice.get("finish_reason")
+                    if finish_reason:
+                        stop_reason = finish_reason
+
+                    reasoning_delta = delta.get("reasoning_content") or ""
+                    if reasoning_delta:
+                        full_reasoning += reasoning_delta
+                        if self._is_thinking_enabled():
+                            self._emit_event("reasoning_update", {"delta": reasoning_delta})
+
+                    # Handle text content
+                    content_delta = delta.get("content") or ""
+                    if content_delta:
+                        # Filter out <think> tags from content
+                        filtered_delta = self._filter_think_tags(content_delta)
+                        full_content += filtered_delta
+                        if filtered_delta:  # Only emit if there's content after filtering
+                            self._emit_event("message_update", {"delta": filtered_delta})
+
+                    # Handle tool calls
+                    if "tool_calls" in delta and delta["tool_calls"]:
+                        for tc_delta in delta["tool_calls"]:
+                            index = tc_delta.get("index", 0)
+
+                            if index not in tool_calls_buffer:
+                                tool_calls_buffer[index] = {
+                                    "id": "",
+                                    "name": "",
+                                    "arguments": ""
+                                }
+
+                            if tc_delta.get("id"):
+                                tool_calls_buffer[index]["id"] = tc_delta["id"]
+
+                            if "function" in tc_delta:
+                                func = tc_delta["function"]
+                                if func.get("name"):
+                                    tool_calls_buffer[index]["name"] = func["name"]
+                                if func.get("arguments"):
+                                    tool_calls_buffer[index]["arguments"] += func["arguments"]
+
+                    # Preserve _gemini_raw_parts for Gemini thoughtSignature round-trip
+                    # (direct Gemini: list of parts; LinkAI proxy: base64 string of JSON parts)
+                    if "_gemini_raw_parts" in delta:
+                        gemini_raw_parts = delta["_gemini_raw_parts"]
+                    elif isinstance(choice, dict) and choice.get("_gemini_raw_parts"):
+                        gemini_raw_parts = choice["_gemini_raw_parts"]
+
+        except AgentCancelledError:
+            # Must propagate untouched; never treat as a retryable error.
+            raise
+
+        except Exception as e:
+            error_str = str(e)
+            error_str_lower = error_str.lower()
+            
+            # Check if error is context overflow (non-retryable, needs session reset)
+            # Method 1: Check for special marker (set in stream error handling above)
+            is_context_overflow = '[context_overflow]' in error_str_lower
+            
+            # Method 2: Fallback to keyword matching for non-stream errors
+            if not is_context_overflow:
+                is_context_overflow = any(keyword in error_str_lower for keyword in [
+                    'context length exceeded', 'maximum context length', 'prompt is too long',
+                    'context overflow', 'context window', 'too large', 'exceeds model context',
+                    'request_too_large', 'request exceeds the maximum size'
+                ])
+            
+            # Check if error is message format error (incomplete tool_use/tool_result pairs)
+            # This happens when previous conversation had tool failures or context trimming
+            # broke tool_use/tool_result pairs.
+            # Note: MiniMax returns error 2013 "tool result's tool id(...) not found" for
+            # tool_call_id mismatches — the keywords below are intentionally broad to catch
+            # both standard (Claude/OpenAI) and provider-specific (MiniMax) variants.
+            is_message_format_error = any(keyword in error_str_lower for keyword in [
+                'tool_use', 'tool_result', 'tool result', 'without', 'immediately after',
+                'corresponding', 'must have', 'each',
+                'tool_call_id', 'tool id', 'is not found', 'not found', 'tool_calls',
+                'must be a response to a preceeding message',
+                '2013',  # MiniMax error code for tool_call_id mismatch
+            ]) and ('400' in error_str_lower or 'status: 400' in error_str_lower
+                     or 'invalid_request' in error_str_lower
+                     or 'invalidparameter' in error_str_lower)
+            
+            if is_context_overflow or is_message_format_error:
+                error_type = "context overflow" if is_context_overflow else "message format error"
+                logger.error(f"💥 {error_type} detected: {e}")
+
+                # Flush memory before trimming to preserve context that will be lost
+                if is_context_overflow and self.agent.memory_manager:
+                    user_id = getattr(self.agent, '_current_user_id', None)
+                    self.agent.memory_manager.flush_memory(
+                        messages=self.messages, user_id=user_id,
+                        reason="overflow", max_messages=0
+                    )
+
+                # Strategy: try aggressive trimming first, only clear as last resort
+                if is_context_overflow and not _overflow_retry:
+                    trimmed = self._aggressive_trim_for_overflow()
+                    if trimmed:
+                        logger.warning("🔄 Aggressively trimmed context, retrying...")
+                        return self._call_llm_stream(
+                            retry_on_empty=retry_on_empty,
+                            retry_count=retry_count,
+                            max_retries=max_retries,
+                            _overflow_retry=True
+                        )
+
+                # Aggressive trim didn't help or this is a message format error
+                # -> clear everything and also purge DB to prevent reload of dirty data
+                logger.warning("🔄 Clearing conversation history to recover")
+                self.messages.clear()
+                self._clear_session_db()
+                if is_context_overflow:
+                    raise Exception(_t(
+                        "抱歉，对话历史过长导致上下文溢出。我已清空历史记录，请重新描述你的需求。",
+                        "Sorry, the conversation history got too long and overflowed the context. I've cleared the history — please describe your request again.",
+                    ))
+                else:
+                    raise Exception(_t(
+                        "抱歉，之前的对话出现了问题。我已清空历史记录，请重新发送你的消息。",
+                        "Sorry, something went wrong with the earlier conversation. I've cleared the history — please send your message again.",
+                    ))
+            
+            # Check if error is rate limit (429)
+            is_rate_limit = '429' in error_str_lower or 'rate limit' in error_str_lower
+            
+            # Check if error is retryable (timeout, connection, server busy, etc.)
+            is_retryable = any(keyword in error_str_lower for keyword in [
+                'timeout', 'timed out', 'connection', 'network', 
+                'rate limit', 'overloaded', 'unavailable', 'busy', 'retry',
+                '429', '500', '502', '503', '504', '512'
+            ])
+            
+            if is_retryable and retry_count < max_retries:
+                # Rate limit needs longer wait time
+                if is_rate_limit:
+                    wait_time = 30 + (retry_count * 15)  # 30s, 45s, 60s for rate limit
+                else:
+                    wait_time = (retry_count + 1) * 2  # 2s, 4s, 6s for other errors
+                
+                logger.warning(f"⚠️ LLM API error (attempt {retry_count + 1}/{max_retries}): {e}")
+                logger.info(f"Retrying in {wait_time}s...")
+                time.sleep(wait_time)
+                return self._call_llm_stream(
+                    retry_on_empty=retry_on_empty, 
+                    retry_count=retry_count + 1,
+                    max_retries=max_retries
+                )
+            else:
+                if retry_count >= max_retries:
+                    logger.error(f"❌ LLM API error after {max_retries} retries: {e}", exc_info=True)
+                else:
+                    logger.error(f"❌ LLM call error (non-retryable): {e}", exc_info=True)
+                raise
+
+        # Parse tool calls
+        tool_calls = []
+        for idx in sorted(tool_calls_buffer.keys()):
+            tc = tool_calls_buffer[idx]
+
+            # Ensure tool call has a valid ID (some providers return empty/None IDs)
+            tool_id = tc.get("id") or ""
+            if not tool_id:
+                import uuid
+                tool_id = f"call_{uuid.uuid4().hex[:24]}"
+
+            args_str = tc.get("arguments") or ""
+            arguments, parse_err = _parse_tool_args(args_str, stop_reason)
+            if parse_err:
+                logger.error(
+                    f"Tool args parse failed for {tc['name']} ({len(args_str)} chars): {parse_err}"
+                )
+                tool_calls.append({
+                    "id": tool_id,
+                    "name": tc["name"],
+                    "arguments": {},
+                    "_parse_error": parse_err,
+                })
+                continue
+
+            tool_calls.append({
+                "id": tool_id,
+                "name": tc["name"],
+                "arguments": arguments
+            })
+
+        # Check for empty response and retry once if enabled
+        if retry_on_empty and not full_content and not tool_calls:
+            logger.warning(f"⚠️  LLM returned empty response (stop_reason: {stop_reason}), retrying once...")
+            self._emit_event("message_end", {
+                "content": "",
+                "tool_calls": [],
+                "empty_retry": True,
+                "stop_reason": stop_reason
+            })
+            # Retry without retry flag to avoid infinite loop
+            return self._call_llm_stream(
+                retry_on_empty=False, 
+                retry_count=retry_count,
+                max_retries=max_retries
+            )
+
+        # Filter full_content one more time (in case tags were split across chunks)
+        full_content = self._filter_think_tags(full_content)
+        
+        # Add assistant message to history (Claude format uses content blocks)
+        assistant_msg = {"role": "assistant", "content": []}
+
+        if full_reasoning:
+            stored_reasoning = _truncate_reasoning_for_storage(full_reasoning)
+            if len(stored_reasoning) < len(full_reasoning):
+                logger.info(
+                    f"[reasoning] truncated for storage: "
+                    f"{len(full_reasoning)} -> {len(stored_reasoning)} chars"
+                )
+            assistant_msg["content"].append({
+                "type": "thinking",
+                "thinking": stored_reasoning
+            })
+
+        if full_content:
+            assistant_msg["content"].append({
+                "type": "text",
+                "text": full_content
+            })
+
+        # Add tool_use blocks if present
+        if tool_calls:
+            for tc in tool_calls:
+                assistant_msg["content"].append({
+                    "type": "tool_use",
+                    "id": tc.get("id", ""),
+                    "name": tc.get("name", ""),
+                    "input": tc.get("arguments", {})
+                })
+        
+        if gemini_raw_parts:
+            assistant_msg["_gemini_raw_parts"] = gemini_raw_parts
+
+        # Only append if content is not empty
+        if assistant_msg["content"]:
+            self.messages.append(assistant_msg)
+
+        self._emit_event("message_end", {
+            "content": full_content,
+            "tool_calls": tool_calls
+        })
+
+        return full_content, tool_calls
+
+    def _execute_tool(self, tool_call: Dict) -> Dict[str, Any]:
+        """
+        Execute tool
+        
+        Args:
+            tool_call: {"id": str, "name": str, "arguments": dict}
+            
+        Returns:
+            Tool execution result
+        """
+        tool_name = tool_call["name"]
+        tool_id = tool_call["id"]
+        arguments = tool_call["arguments"]
+
+        if "_parse_error" in tool_call:
+            result = {
+                "status": "error",
+                "result": tool_call["_parse_error"],
+                "execution_time": 0,
+            }
+            self._record_tool_result(tool_name, arguments, False)
+            return result
+
+        # Check for consecutive failures (retry protection)
+        should_stop, stop_reason, is_critical = self._check_consecutive_failures(tool_name, arguments)
+        if should_stop:
+            logger.error(f"🛑 {stop_reason}")
+            self._record_tool_result(tool_name, arguments, False)
+            
+            if is_critical:
+                # Critical failure - abort entire conversation
+                result = {
+                    "status": "critical_error",
+                    "result": stop_reason,
+                    "execution_time": 0
+                }
+            else:
+                # Normal failure - let LLM try different approach
+                result = {
+                    "status": "error",
+                    "result": f"{stop_reason}\n\n当前方法行不通，请尝试完全不同的方法或向用户询问更多信息。",
+                    "execution_time": 0
+                }
+            return result
+
+        self._emit_event("tool_execution_start", {
+            "tool_call_id": tool_id,
+            "tool_name": tool_name,
+            "arguments": arguments
+        })
+
+        try:
+            tool = self.tools.get(tool_name)
+            if not tool:
+                raise ValueError(self._build_tool_not_found_message(tool_name))
+
+            # Set tool context
+            tool.model = self.model
+            tool.context = self.agent
+            tool.progress_callback = lambda message: self._emit_event(
+                "tool_execution_progress",
+                {
+                    "tool_call_id": tool_id,
+                    "tool_name": tool_name,
+                    "message": message,
+                }
+            )
+
+            # Execute tool
+            start_time = time.time()
+            try:
+                result: ToolResult = tool.execute_tool(arguments)
+            finally:
+                tool.progress_callback = None
+            execution_time = time.time() - start_time
+
+            result_dict = {
+                "status": result.status,
+                "result": result.result,
+                "execution_time": execution_time
+            }
+
+            # Record tool result for failure tracking
+            success = result.status == "success"
+            self._record_tool_result(tool_name, arguments, success)
+
+            # Auto-refresh skills after skill creation
+            if tool_name == "bash" and result.status == "success":
+                command = arguments.get("command", "")
+                if "init_skill.py" in command and self.agent.skill_manager:
+                    logger.info("Detected skill creation, refreshing skills...")
+                    self.agent.refresh_skills()
+                    logger.info(f"Skills refreshed! Now have {len(self.agent.skill_manager.skills)} skills")
+
+            self._emit_event("tool_execution_end", {
+                "tool_call_id": tool_id,
+                "tool_name": tool_name,
+                **result_dict
+            })
+
+            return result_dict
+
+        except Exception as e:
+            logger.error(f"Tool execution error: {e}")
+            error_result = {
+                "status": "error",
+                "result": str(e),
+                "execution_time": 0
+            }
+            # Record failure
+            self._record_tool_result(tool_name, arguments, False)
+            
+            self._emit_event("tool_execution_end", {
+                "tool_call_id": tool_id,
+                "tool_name": tool_name,
+                **error_result
+            })
+            return error_result
+
+    def _build_tool_not_found_message(self, tool_name: str) -> str:
+        """Build a helpful error message when a tool is not found.
+
+        If a skill with the same name exists in skill_manager, read its
+        SKILL.md and include the content so the LLM knows how to use it.
+        """
+        available_tools = list(self.tools.keys())
+        base_msg = f"Tool '{tool_name}' not found. Available tools: {available_tools}"
+
+        skill_manager = getattr(self.agent, 'skill_manager', None)
+        if not skill_manager:
+            return base_msg
+
+        skill_entry = skill_manager.get_skill(tool_name)
+        if not skill_entry:
+            return base_msg
+
+        skill = skill_entry.skill
+        skill_md_path = skill.file_path
+        skill_content = ""
+        try:
+            with open(skill_md_path, 'r', encoding='utf-8') as f:
+                skill_content = f.read()
+        except Exception:
+            skill_content = skill.description
+
+        logger.info(
+            f"[Agent] Tool '{tool_name}' not found, but matched skill '{skill.name}'. "
+            f"Guiding LLM to use the skill instead."
+        )
+
+        return (
+            f"Tool '{tool_name}' is not a built-in tool, but a matching skill "
+            f"'{skill.name}' is available. You should use existing tools (e.g. bash with curl) "
+            f"to accomplish this task following the skill instructions below:\n\n"
+            f"--- SKILL: {skill.name} (path: {skill_md_path}) ---\n"
+            f"{skill_content}\n"
+            f"--- END SKILL ---\n\n"
+            f"Available tools: {available_tools}"
+        )
+
+    def _validate_and_fix_messages(self):
+        """Delegate to the shared sanitizer (see message_sanitizer.py)."""
+        sanitize_claude_messages(self.messages)
+
+    def _identify_complete_turns(self) -> List[Dict]:
+        """
+        识别完整的对话轮次
+        
+        一个完整轮次包括：
+        1. 用户消息（text）
+        2. AI 回复（可能包含 tool_use）
+        3. 工具结果（tool_result，如果有）
+        4. 后续 AI 回复（如果有）
+        
+        Returns:
+            List of turns, each turn is a dict with 'messages' list
+        """
+        turns = []
+        current_turn = {'messages': []}
+        
+        for msg in self.messages:
+            role = msg.get('role')
+            content = msg.get('content', [])
+            
+            if role == 'user':
+                # Determine if this is a real user query (not a tool_result injection
+                # or an internal hint message injected by the agent loop).
+                is_user_query = False
+                has_tool_result = False
+                if isinstance(content, list):
+                    has_text = any(
+                        isinstance(block, dict) and block.get('type') == 'text'
+                        for block in content
+                    )
+                    has_tool_result = any(
+                        isinstance(block, dict) and block.get('type') == 'tool_result'
+                        for block in content
+                    )
+                    # A message with tool_result is always internal, even if it
+                    # also contains text blocks (shouldn't happen, but be safe).
+                    is_user_query = has_text and not has_tool_result
+                elif isinstance(content, str):
+                    is_user_query = True
+                
+                if is_user_query:
+                    if current_turn['messages']:
+                        turns.append(current_turn)
+                    current_turn = {'messages': [msg]}
+                else:
+                    current_turn['messages'].append(msg)
+            else:
+                # AI 回复，属于当前轮次
+                current_turn['messages'].append(msg)
+        
+        # 添加最后一个轮次
+        if current_turn['messages']:
+            turns.append(current_turn)
+        
+        return turns
+    
+    def _estimate_turn_tokens(self, turn: Dict) -> int:
+        """估算一个轮次的 tokens"""
+        return sum(
+            self.agent._estimate_message_tokens(msg) 
+            for msg in turn['messages']
+        )
+
+    def _truncate_historical_tool_results(self):
+        """
+        Truncate tool_result content in historical messages to reduce context size.
+
+        Current turn results are kept at 30K chars (truncated at creation time).
+        Historical turn results are further truncated to 10K chars here.
+        This runs before token-based trimming so that we first shrink oversized
+        results, potentially avoiding the need to drop entire turns.
+        """
+        MAX_HISTORY_RESULT_CHARS = 20000
+
+        if len(self.messages) < 2:
+            return
+
+        # Find where the last user text message starts (= current turn boundary)
+        # We skip the current turn's messages to preserve their full content
+        current_turn_start = len(self.messages)
+        for i in range(len(self.messages) - 1, -1, -1):
+            msg = self.messages[i]
+            if msg.get("role") == "user":
+                content = msg.get("content", [])
+                if isinstance(content, list) and any(
+                    isinstance(b, dict) and b.get("type") == "text" for b in content
+                ):
+                    current_turn_start = i
+                    break
+                elif isinstance(content, str):
+                    current_turn_start = i
+                    break
+
+        truncated_count = 0
+        for i in range(current_turn_start):
+            msg = self.messages[i]
+            if msg.get("role") != "user":
+                continue
+            content = msg.get("content", [])
+            if not isinstance(content, list):
+                continue
+
+            for block in content:
+                if not isinstance(block, dict) or block.get("type") != "tool_result":
+                    continue
+                result_str = block.get("content", "")
+                if isinstance(result_str, str) and len(result_str) > MAX_HISTORY_RESULT_CHARS:
+                    original_len = len(result_str)
+                    block["content"] = result_str[:MAX_HISTORY_RESULT_CHARS] + \
+                        f"\n\n[Historical output truncated: {original_len} -> {MAX_HISTORY_RESULT_CHARS} chars]"
+                    truncated_count += 1
+
+        if truncated_count > 0:
+            logger.info(f"📎 Truncated {truncated_count} historical tool result(s) to {MAX_HISTORY_RESULT_CHARS} chars")
+
+    def _aggressive_trim_for_overflow(self) -> bool:
+        """
+        Aggressively trim context when a real overflow error is returned by the API.
+
+        This method goes beyond normal _trim_messages by:
+        1. Truncating all tool results (including current turn) to a small limit
+        2. Keeping only the last 5 complete conversation turns
+        3. Truncating overly long user messages
+
+        Returns:
+            True if messages were trimmed (worth retrying), False if nothing left to trim
+        """
+        if not self.messages:
+            return False
+
+        original_count = len(self.messages)
+
+        # Step 1: Aggressively truncate ALL tool results to 5K chars
+        AGGRESSIVE_LIMIT = 10000
+        truncated = 0
+        for msg in self.messages:
+            content = msg.get("content", [])
+            if not isinstance(content, list):
+                continue
+            for block in content:
+                if not isinstance(block, dict):
+                    continue
+                # Truncate tool_result blocks
+                if block.get("type") == "tool_result":
+                    result_str = block.get("content", "")
+                    if isinstance(result_str, str) and len(result_str) > AGGRESSIVE_LIMIT:
+                        block["content"] = (
+                            result_str[:AGGRESSIVE_LIMIT]
+                            + f"\n\n[Truncated for context recovery: "
+                            f"{len(result_str)} -> {AGGRESSIVE_LIMIT} chars]"
+                        )
+                        truncated += 1
+                # Truncate tool_use input blocks (e.g. large write content)
+                if block.get("type") == "tool_use" and isinstance(block.get("input"), dict):
+                    input_str = json.dumps(block["input"], ensure_ascii=False)
+                    if len(input_str) > AGGRESSIVE_LIMIT:
+                        # Keep only a summary of the input
+                        for key, val in block["input"].items():
+                            if isinstance(val, str) and len(val) > 1000:
+                                block["input"][key] = (
+                                    val[:1000]
+                                    + f"... [truncated {len(val)} chars]"
+                                )
+                        truncated += 1
+
+        # Step 2: Truncate overly long user text messages (e.g. pasted content)
+        USER_MSG_LIMIT = 10000
+        for msg in self.messages:
+            if msg.get("role") != "user":
+                continue
+            content = msg.get("content", [])
+            if isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict) and block.get("type") == "text":
+                        text = block.get("text", "")
+                        if len(text) > USER_MSG_LIMIT:
+                            block["text"] = (
+                                text[:USER_MSG_LIMIT]
+                                + f"\n\n[Message truncated for context recovery: "
+                                f"{len(text)} -> {USER_MSG_LIMIT} chars]"
+                            )
+                            truncated += 1
+            elif isinstance(content, str) and len(content) > USER_MSG_LIMIT:
+                msg["content"] = (
+                    content[:USER_MSG_LIMIT]
+                    + f"\n\n[Message truncated for context recovery: "
+                    f"{len(content)} -> {USER_MSG_LIMIT} chars]"
+                )
+                truncated += 1
+
+        # Step 3: Keep only the last 5 complete turns
+        turns = self._identify_complete_turns()
+        if len(turns) > 5:
+            kept_turns = turns[-5:]
+            new_messages = []
+            for turn in kept_turns:
+                new_messages.extend(turn["messages"])
+            removed = len(turns) - 5
+            self.messages[:] = new_messages
+            logger.info(
+                f"🔧 Aggressive trim: removed {removed} old turns, "
+                f"truncated {truncated} large blocks, "
+                f"{original_count} -> {len(self.messages)} messages"
+            )
+            return True
+
+        if truncated > 0:
+            logger.info(
+                f"🔧 Aggressive trim: truncated {truncated} large blocks "
+                f"(no turns removed, only {len(turns)} turn(s) left)"
+            )
+            return True
+
+        # Nothing left to trim
+        logger.warning("🔧 Aggressive trim: nothing to trim, will clear history")
+        return False
+
+    def _build_context_summary_callback(self, discarded_turns: list, kept_turns: list):
+        """
+        Build a callback that injects an LLM summary into the first user
+        message of *kept_turns*. Returns None if no valid injection target.
+
+        The callback is passed to flush_from_messages so that the same LLM
+        call that writes daily memory also provides the in-context summary.
+        """
+        if not kept_turns:
+            return None
+
+        # Find the first user text block in kept_turns as injection target
+        target_block = None
+        for turn in kept_turns:
+            for msg in turn["messages"]:
+                if msg.get("role") == "user":
+                    content = msg.get("content", [])
+                    if isinstance(content, list):
+                        for block in content:
+                            if isinstance(block, dict) and block.get("type") == "text":
+                                target_block = block
+                                break
+                    if target_block:
+                        break
+            if target_block:
+                break
+
+        if not target_block:
+            return None
+
+        turn_count = len(discarded_turns)
+        original_text = target_block["text"]
+
+        def _on_summary_ready(summary: str):
+            if not summary or not summary.strip():
+                return
+            target_block["text"] = (
+                f"[System: Previous conversation summary — "
+                f"{turn_count} turns were compacted]\n\n"
+                f"{summary.strip()}\n\n"
+                f"The recent conversation continues below.\n\n---\n\n"
+                f"{original_text}"
+            )
+            logger.info(
+                f"📝 Context summary injected "
+                f"({len(summary)} chars, {turn_count} turns)"
+            )
+
+        return _on_summary_ready
+
+    def _trim_messages(self):
+        """
+        智能清理消息历史，保持对话完整性
+
+        使用完整轮次作为清理单位，确保：
+        1. 不会在对话中间截断
+        2. 工具调用链（tool_use + tool_result）保持完整
+        3. 每轮对话都是完整的（用户消息 + AI回复 + 工具调用）
+        """
+        if not self.messages or not self.agent:
+            return
+
+        # Step 0: Truncate large tool results in historical turns (30K -> 10K)
+        self._truncate_historical_tool_results()
+
+        # Step 1: 识别完整轮次
+        turns = self._identify_complete_turns()
+        
+        if not turns:
+            return
+        
+        # Step 2: 轮次限制 - 超出时移除前一半，保留后一半
+        if len(turns) > self.max_context_turns:
+            removed_count = len(turns) // 2
+            keep_count = len(turns) - removed_count
+            
+            discarded_turns = turns[:removed_count]
+            turns = turns[-keep_count:]
+
+            logger.info(
+                f"💾 Context turns exceeded: {keep_count + removed_count} > {self.max_context_turns}, "
+                f"trimmed to {keep_count} turns (removed {removed_count})"
+            )
+
+            # Flush to daily memory + inject context summary (single async LLM call)
+            if self.agent.memory_manager:
+                discarded_messages = []
+                for turn in discarded_turns:
+                    discarded_messages.extend(turn["messages"])
+                if discarded_messages:
+                    user_id = getattr(self.agent, '_current_user_id', None)
+                    cb = self._build_context_summary_callback(discarded_turns, turns)
+                    self.agent.memory_manager.flush_memory(
+                        messages=discarded_messages, user_id=user_id,
+                        reason="trim", max_messages=0,
+                        context_summary_callback=cb,
+                    )
+
+        # Step 3: Token 限制 - 保留完整轮次
+        # Get context window from agent (based on model)
+        context_window = self.agent._get_model_context_window()
+
+        # Use configured max_context_tokens if available
+        if hasattr(self.agent, 'max_context_tokens') and self.agent.max_context_tokens:
+            max_tokens = self.agent.max_context_tokens
+        else:
+            # Reserve 10% for response generation
+            reserve_tokens = int(context_window * 0.1)
+            max_tokens = context_window - reserve_tokens
+
+        # Estimate system prompt tokens
+        system_tokens = self.agent._estimate_message_tokens({"role": "system", "content": self.system_prompt})
+        available_tokens = max_tokens - system_tokens
+
+        # Calculate current tokens
+        current_tokens = sum(self._estimate_turn_tokens(turn) for turn in turns)
+        
+        # If under limit, reconstruct messages and return
+        if current_tokens + system_tokens <= max_tokens:
+            # Reconstruct message list from turns
+            new_messages = []
+            for turn in turns:
+                new_messages.extend(turn['messages'])
+            
+            old_count = len(self.messages)
+            self.messages = new_messages
+            
+            # Log if we removed messages due to turn limit
+            if old_count > len(self.messages):
+                logger.info(f"   Rebuilt message list: {old_count} -> {len(self.messages)} messages")
+            return
+
+        # Token limit exceeded — tiered strategy based on turn count:
+        #
+        #   Few turns (<5):  Compress ALL turns to text-only (strip tool chains,
+        #                    keep user query + final reply).  Never discard turns
+        #                    — losing even one is too painful when context is thin.
+        #
+        #   Many turns (>=5): Directly discard the first half of turns.
+        #                     With enough turns the oldest ones are less
+        #                     critical, and keeping the recent half intact
+        #                     (with full tool chains) is more useful.
+
+        COMPRESS_THRESHOLD = 5
+
+        if len(turns) < COMPRESS_THRESHOLD:
+            # --- Few turns: compress ALL turns to text-only, never discard ---
+            compressed_turns = []
+            for t in turns:
+                compressed = compress_turn_to_text_only(t)
+                if compressed["messages"]:
+                    compressed_turns.append(compressed)
+
+            new_messages = []
+            for turn in compressed_turns:
+                new_messages.extend(turn["messages"])
+
+            new_tokens = sum(self._estimate_turn_tokens(t) for t in compressed_turns)
+            old_count = len(self.messages)
+            self.messages = new_messages
+
+            logger.info(
+                f"📦 Context tokens exceeded (turns<{COMPRESS_THRESHOLD}): "
+                f"~{current_tokens + system_tokens} > {max_tokens}, "
+                f"compressed all {len(turns)} turns to plain text "
+                f"({old_count} -> {len(self.messages)} messages, "
+                f"~{current_tokens + system_tokens} -> ~{new_tokens + system_tokens} tokens)"
+            )
+            return
+
+        # --- Many turns (>=5): discard the older half, keep the newer half ---
+        removed_count = len(turns) // 2
+        keep_count = len(turns) - removed_count
+        discarded_turns = turns[:removed_count]
+        kept_turns = turns[-keep_count:]
+        kept_tokens = sum(self._estimate_turn_tokens(t) for t in kept_turns)
+
+        logger.info(
+            f"🔄 Context tokens exceeded: ~{current_tokens + system_tokens} > {max_tokens}, "
+            f"trimmed to {keep_count} turns (removed {removed_count})"
+        )
+
+        if self.agent.memory_manager:
+            discarded_messages = []
+            for turn in discarded_turns:
+                discarded_messages.extend(turn["messages"])
+            if discarded_messages:
+                user_id = getattr(self.agent, '_current_user_id', None)
+                cb = self._build_context_summary_callback(discarded_turns, kept_turns)
+                self.agent.memory_manager.flush_memory(
+                    messages=discarded_messages, user_id=user_id,
+                    reason="trim", max_messages=0,
+                    context_summary_callback=cb,
+                )
+
+        new_messages = []
+        for turn in kept_turns:
+            new_messages.extend(turn['messages'])
+
+        old_count = len(self.messages)
+        self.messages = new_messages
+
+        logger.info(
+            f"   Removed {removed_count} turns "
+            f"({old_count} -> {len(self.messages)} messages, "
+            f"~{current_tokens + system_tokens} -> ~{kept_tokens + system_tokens} tokens)"
+        )
+
+    def _clear_session_db(self):
+        """
+        Clear the current session's persisted messages from SQLite DB.
+
+        This prevents dirty data (broken tool_use/tool_result pairs) from being
+        reloaded on the next request or after a restart.
+        """
+        try:
+            session_id = getattr(self.agent, '_current_session_id', None)
+            if not session_id:
+                return
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            store.clear_session(session_id)
+            logger.info(f"🗑️ Cleared dirty session data from DB: {session_id}")
+        except Exception as e:
+            logger.warning(f"Failed to clear session DB: {e}")
+
+    def _prepare_messages(self) -> List[Dict[str, Any]]:
+        """
+        Prepare messages to send to LLM
+        
+        Note: For Claude API, system prompt should be passed separately via system parameter,
+        not as a message. The AgentLLMModel will handle this.
+        """
+        # Don't add system message here - it will be handled separately by the LLM adapter
+        return self.messages
diff --git a/agent/protocol/cancel.py b/agent/protocol/cancel.py
new file mode 100644
index 0000000..6354cd3
--- /dev/null
+++ b/agent/protocol/cancel.py
@@ -0,0 +1,121 @@
+"""
+Cancel token registry for aborting in-flight agent runs.
+
+A user cancel (web Cancel button, /cancel command) sets a threading.Event
+that the agent loop polls at safe checkpoints. Tokens are keyed by
+request_id (preferred) and tracked under session_id as a fallback. Entries
+are released after the run completes to keep the registry bounded.
+
+No project deps — importable from any layer without circular imports.
+"""
+
+from __future__ import annotations
+
+import threading
+from typing import Dict, Optional
+
+
+class AgentCancelledError(Exception):
+    """Raised inside the agent loop when a stop has been requested.
+
+    The agent stream executor catches this, injects a "[Interrupted]" note
+    into the message history (preserving tool_use/tool_result integrity)
+    and returns a partial response to the caller.
+    """
+
+
+class _CancelEntry:
+    __slots__ = ("event", "session_id")
+
+    def __init__(self, session_id: Optional[str]):
+        self.event = threading.Event()
+        self.session_id = session_id
+
+
+class CancelTokenRegistry:
+    """In-process registry mapping request_id -> cancel Event.
+
+    Thread-safe. Singleton via module-level ``_registry``.
+    """
+
+    def __init__(self):
+        self._lock = threading.Lock()
+        self._by_request: Dict[str, _CancelEntry] = {}
+        # session_id -> set of request_ids currently in flight (usually 1).
+        self._by_session: Dict[str, set] = {}
+
+    def register(self, request_id: str, session_id: Optional[str] = None) -> threading.Event:
+        """Create (or return existing) cancel event for a request.
+
+        Returns the threading.Event the caller should poll via ``is_set()``.
+        """
+        if not request_id:
+            return threading.Event()
+        with self._lock:
+            entry = self._by_request.get(request_id)
+            if entry is None:
+                entry = _CancelEntry(session_id)
+                self._by_request[request_id] = entry
+                if session_id:
+                    self._by_session.setdefault(session_id, set()).add(request_id)
+            return entry.event
+
+    def get_event(self, request_id: str) -> Optional[threading.Event]:
+        if not request_id:
+            return None
+        with self._lock:
+            entry = self._by_request.get(request_id)
+            return entry.event if entry else None
+
+    def cancel_request(self, request_id: str) -> bool:
+        """Trigger cancel for a specific request. Returns True when matched."""
+        if not request_id:
+            return False
+        with self._lock:
+            entry = self._by_request.get(request_id)
+        if entry is None:
+            return False
+        entry.event.set()
+        return True
+
+    def cancel_session(self, session_id: str) -> int:
+        """Trigger cancel for every in-flight request of a session.
+
+        Returns the number of requests cancelled (0 when nothing was running).
+        """
+        if not session_id:
+            return 0
+        with self._lock:
+            request_ids = list(self._by_session.get(session_id, ()))
+            entries = [self._by_request[r] for r in request_ids if r in self._by_request]
+        for entry in entries:
+            entry.event.set()
+        return len(entries)
+
+    def unregister(self, request_id: str) -> None:
+        """Remove an entry once the agent run is done. Safe to call twice."""
+        if not request_id:
+            return
+        with self._lock:
+            entry = self._by_request.pop(request_id, None)
+            if entry and entry.session_id:
+                bucket = self._by_session.get(entry.session_id)
+                if bucket is not None:
+                    bucket.discard(request_id)
+                    if not bucket:
+                        self._by_session.pop(entry.session_id, None)
+
+    def has_active(self, session_id: str) -> bool:
+        if not session_id:
+            return False
+        with self._lock:
+            bucket = self._by_session.get(session_id)
+            return bool(bucket)
+
+
+_registry = CancelTokenRegistry()
+
+
+def get_cancel_registry() -> CancelTokenRegistry:
+    """Module-level accessor for the singleton registry."""
+    return _registry
diff --git a/agent/protocol/context.py b/agent/protocol/context.py
new file mode 100644
index 0000000..1c37850
--- /dev/null
+++ b/agent/protocol/context.py
@@ -0,0 +1,27 @@
+class TeamContext:
+    def __init__(self, name: str, description: str, rule: str, agents: list, max_steps: int = 100):
+        """
+        Initialize the TeamContext with a name, description, rules, a list of agents, and a user question.
+        :param name: The name of the group context.
+        :param description: A description of the group context.
+        :param rule: The rules governing the group context.
+        :param agents: A list of agents in the context.
+        """
+        self.name = name
+        self.description = description
+        self.rule = rule
+        self.agents = agents
+        self.user_task = ""  # For backward compatibility
+        self.task = None  # Will be a Task instance
+        self.model = None  # Will be an instance of LLMModel
+        self.task_short_name = None  # Store the task directory name
+        # List of agents that have been executed
+        self.agent_outputs: list = []
+        self.current_steps = 0
+        self.max_steps = max_steps
+
+
+class AgentOutput:
+    def __init__(self, agent_name: str, output: str):
+        self.agent_name = agent_name
+        self.output = output
\ No newline at end of file
diff --git a/agent/protocol/message_utils.py b/agent/protocol/message_utils.py
new file mode 100644
index 0000000..160ad59
--- /dev/null
+++ b/agent/protocol/message_utils.py
@@ -0,0 +1,335 @@
+"""
+Message sanitizer — fix broken tool_use / tool_result pairs.
+
+Provides two public helpers that can be reused across agent_stream.py
+and any bot that converts messages to OpenAI format:
+
+1. sanitize_claude_messages(messages)
+   Operates on the internal Claude-format message list (in-place).
+
+2. drop_orphaned_tool_results_openai(messages)
+   Operates on an already-converted OpenAI-format message list,
+   returning a cleaned copy.
+"""
+
+from __future__ import annotations
+
+from typing import Dict, List, Set
+
+from common.log import logger
+
+_SYNTH_TOOL_ERR = (
+    "Error: Missing tool_result adjacent to tool_use (session repair). "
+    "The conversation history was inconsistent; continue from here."
+)
+
+
+def _repair_tool_use_adjacency(messages: List[Dict]) -> int:
+    """
+    Anthropic requires: after assistant content with tool_use, the next message
+    must be user content listing tool_result for every tool_use id (same user msg).
+
+    Valid histories satisfy this at every such assistant; the loop only mutates
+    when that condition fails (broken persistence, bad trims, etc.).
+    """
+
+    def _synth_block(tid: str) -> Dict:
+        return {
+            "type": "tool_result",
+            "tool_use_id": tid,
+            "content": _SYNTH_TOOL_ERR,
+            "is_error": True,
+        }
+
+    repairs = 0
+    i = 0
+    while i < len(messages):
+        msg = messages[i]
+        if msg.get("role") != "assistant":
+            i += 1
+            continue
+
+        content = msg.get("content", [])
+        if not isinstance(content, list):
+            i += 1
+            continue
+
+        required = [
+            b.get("id")
+            for b in content
+            if isinstance(b, dict) and b.get("type") == "tool_use" and b.get("id")
+        ]
+        if not required:
+            i += 1
+            continue
+
+        req_set = set(required)
+        if i + 1 >= len(messages):
+            messages.append({
+                "role": "user",
+                "content": [_synth_block(tid) for tid in required],
+            })
+            logger.warning(
+                "⚠️ Appended synthetic tool_result after trailing assistant tool_use"
+            )
+            repairs += 1
+            break
+
+        nxt = messages[i + 1]
+        if nxt.get("role") != "user":
+            messages.insert(
+                i + 1,
+                {"role": "user", "content": [_synth_block(tid) for tid in required]},
+            )
+            logger.warning(
+                "⚠️ Inserted synthetic tool_result user after tool_use "
+                f"(next role={nxt.get('role')!r})"
+            )
+            repairs += 1
+            i += 2
+            continue
+
+        nc = nxt.get("content", [])
+        if not isinstance(nc, list):
+            messages.insert(
+                i + 1,
+                {"role": "user", "content": [_synth_block(tid) for tid in required]},
+            )
+            repairs += 1
+            i += 2
+            continue
+
+        present = {
+            b.get("tool_use_id")
+            for b in nc
+            if isinstance(b, dict) and b.get("type") == "tool_result" and b.get("tool_use_id")
+        }
+        if req_set <= present:
+            i += 1
+            continue
+
+        missing = [tid for tid in required if tid not in present]
+        nxt["content"] = [_synth_block(tid) for tid in missing] + nc
+        logger.warning(
+            "⚠️ Prepended synthetic tool_result for Anthropic adjacency "
+            f"(missing_ids={missing})"
+        )
+        repairs += len(missing)
+        i += 1
+
+    return repairs
+
+
+# ------------------------------------------------------------------ #
+# Claude-format sanitizer (used by agent_stream)
+# ------------------------------------------------------------------ #
+
+def sanitize_claude_messages(messages: List[Dict]) -> int:
+    """
+    Validate and fix a Claude-format message list **in-place**.
+
+    Fixes handled:
+    - Anthropic adjacency: assistant tool_use must be immediately followed by
+      user message(s) containing matching tool_result blocks
+    - Leading orphaned tool_result user messages
+    - Mid-list tool_result blocks whose tool_use_id has no matching
+      tool_use in any preceding assistant message
+
+    Returns: number of removals plus adjacency repair operations (inserts/prepends).
+    """
+    if not messages:
+        return 0
+
+    removed = 0
+
+    # 1. Adjacency repair (Anthropic: tool_result must be in the next user message)
+    adj_repairs = _repair_tool_use_adjacency(messages)
+
+    # 2. Remove leading orphaned tool_result user messages
+    while messages:
+        first = messages[0]
+        if first.get("role") != "user":
+            break
+        content = first.get("content", [])
+        if isinstance(content, list) and _has_block_type(content, "tool_result") \
+                and not _has_block_type(content, "text"):
+            logger.warning("⚠️ Removing leading orphaned tool_result user message")
+            messages.pop(0)
+            removed += 1
+        else:
+            break
+
+    # 3. Iteratively remove unmatched tool_use / tool_result until stable.
+    #    Removing one broken message can orphan others (e.g. an assistant msg
+    #    with both matched and unmatched tool_use — deleting it orphans the
+    #    previously-matched tool_result).  Loop until clean.
+    for _ in range(5):
+        use_ids: Set[str] = set()
+        result_ids: Set[str] = set()
+        for msg in messages:
+            for block in (msg.get("content") or []):
+                if not isinstance(block, dict):
+                    continue
+                if block.get("type") == "tool_use" and block.get("id"):
+                    use_ids.add(block["id"])
+                elif block.get("type") == "tool_result" and block.get("tool_use_id"):
+                    result_ids.add(block["tool_use_id"])
+
+        bad_use = use_ids - result_ids
+        bad_result = result_ids - use_ids
+        if not bad_use and not bad_result:
+            break
+
+        pass_removed = 0
+        i = 0
+        while i < len(messages):
+            msg = messages[i]
+            role = msg.get("role")
+            content = msg.get("content", [])
+            if not isinstance(content, list):
+                i += 1
+                continue
+
+            if role == "assistant" and bad_use and any(
+                isinstance(b, dict) and b.get("type") == "tool_use"
+                and b.get("id") in bad_use for b in content
+            ):
+                logger.warning(f"⚠️ Removing assistant msg with unmatched tool_use")
+                messages.pop(i)
+                pass_removed += 1
+                continue
+
+            if role == "user" and bad_result and _has_block_type(content, "tool_result"):
+                has_bad = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result"
+                    and b.get("tool_use_id") in bad_result for b in content
+                )
+                if has_bad:
+                    if not _has_block_type(content, "text"):
+                        logger.warning(f"⚠️ Removing user msg with unmatched tool_result")
+                        messages.pop(i)
+                        pass_removed += 1
+                        continue
+                    else:
+                        before = len(content)
+                        msg["content"] = [
+                            b for b in content
+                            if not (isinstance(b, dict) and b.get("type") == "tool_result"
+                                    and b.get("tool_use_id") in bad_result)
+                        ]
+                        pass_removed += before - len(msg["content"])
+
+            i += 1
+
+        removed += pass_removed
+        if pass_removed == 0:
+            break
+
+    # 4. Removals above can break adjacency; re-run repair only if something was removed.
+    if removed:
+        adj_repairs += _repair_tool_use_adjacency(messages)
+
+    if removed:
+        logger.info(f"🔧 Message validation: removed {removed} broken message(s)")
+    if adj_repairs:
+        logger.info(f"🔧 Message validation: adjacency repairs={adj_repairs}")
+    return removed + adj_repairs
+
+
+# ------------------------------------------------------------------ #
+# OpenAI-format sanitizer (used by minimax_bot, openai_compatible_bot)
+# ------------------------------------------------------------------ #
+
+def drop_orphaned_tool_results_openai(messages: List[Dict]) -> List[Dict]:
+    """
+    Return a copy of *messages* (OpenAI format) with any ``role=tool``
+    messages removed if their ``tool_call_id`` does not match a
+    ``tool_calls[].id`` in a preceding assistant message.
+    """
+    known_ids: Set[str] = set()
+    cleaned: List[Dict] = []
+    for msg in messages:
+        if msg.get("role") == "assistant" and msg.get("tool_calls"):
+            for tc in msg["tool_calls"]:
+                tc_id = tc.get("id", "")
+                if tc_id:
+                    known_ids.add(tc_id)
+
+        if msg.get("role") == "tool":
+            ref_id = msg.get("tool_call_id", "")
+            if ref_id and ref_id not in known_ids:
+                logger.warning(
+                    f"[MessageSanitizer] Dropping orphaned tool result "
+                    f"(tool_call_id={ref_id} not in known ids)"
+                )
+                continue
+        cleaned.append(msg)
+    return cleaned
+
+
+# ------------------------------------------------------------------ #
+# Internal helpers
+# ------------------------------------------------------------------ #
+
+def _has_block_type(content: list, block_type: str) -> bool:
+    return any(
+        isinstance(b, dict) and b.get("type") == block_type
+        for b in content
+    )
+
+
+def _extract_text_from_content(content) -> str:
+    """Extract plain text from a message content field (str or list of blocks)."""
+    if isinstance(content, str):
+        return content.strip()
+    if isinstance(content, list):
+        parts = [
+            b.get("text", "")
+            for b in content
+            if isinstance(b, dict) and b.get("type") == "text"
+        ]
+        return "\n".join(p for p in parts if p).strip()
+    return ""
+
+
+def compress_turn_to_text_only(turn: Dict) -> Dict:
+    """
+    Compress a full turn (with tool_use/tool_result chains) into a lightweight
+    text-only turn that keeps only the first user text and the last assistant text.
+
+    This preserves the conversational context (what the user asked and what the
+    agent concluded) while stripping out the bulky intermediate tool interactions.
+
+    Returns a new turn dict with a ``messages`` list; the original is not mutated.
+    """
+    user_text = ""
+    last_assistant_text = ""
+
+    for msg in turn["messages"]:
+        role = msg.get("role")
+        content = msg.get("content", [])
+
+        if role == "user":
+            if isinstance(content, list) and _has_block_type(content, "tool_result"):
+                continue
+            if not user_text:
+                user_text = _extract_text_from_content(content)
+
+        elif role == "assistant":
+            text = _extract_text_from_content(content)
+            if text:
+                last_assistant_text = text
+
+    compressed_messages = []
+    if user_text:
+        compressed_messages.append({
+            "role": "user",
+            "content": [{"type": "text", "text": user_text}]
+        })
+    if last_assistant_text:
+        compressed_messages.append({
+            "role": "assistant",
+            "content": [{"type": "text", "text": last_assistant_text}]
+        })
+
+    return {"messages": compressed_messages}
diff --git a/agent/protocol/models.py b/agent/protocol/models.py
new file mode 100644
index 0000000..9157211
--- /dev/null
+++ b/agent/protocol/models.py
@@ -0,0 +1,57 @@
+"""
+Models module for agent system.
+Provides basic model classes needed by tools and bridge integration.
+"""
+
+from typing import Any, Dict, List, Optional
+
+
+class LLMRequest:
+    """Request model for LLM operations"""
+    
+    def __init__(self, messages: List[Dict[str, str]] = None, model: Optional[str] = None,
+                 temperature: float = 0.7, max_tokens: Optional[int] = None, 
+                 stream: bool = False, tools: Optional[List] = None, **kwargs):
+        self.messages = messages or []
+        self.model = model
+        self.temperature = temperature
+        self.max_tokens = max_tokens
+        self.stream = stream
+        self.tools = tools
+        # Allow extra attributes
+        for key, value in kwargs.items():
+            setattr(self, key, value)
+
+
+class LLMModel:
+    """Base class for LLM models"""
+    
+    def __init__(self, model: str = None, **kwargs):
+        self.model = model
+        self.config = kwargs
+    
+    def call(self, request: LLMRequest):
+        """
+        Call the model with a request.
+        This is a placeholder implementation.
+        """
+        raise NotImplementedError("LLMModel.call not implemented in this context")
+    
+    def call_stream(self, request: LLMRequest):
+        """
+        Call the model with streaming.
+        This is a placeholder implementation.
+        """
+        raise NotImplementedError("LLMModel.call_stream not implemented in this context")
+
+
+class ModelFactory:
+    """Factory for creating model instances"""
+
+    @staticmethod
+    def create_model(model_type: str, **kwargs):
+        """
+        Create a model instance based on type.
+        This is a placeholder implementation.
+        """
+        raise NotImplementedError("ModelFactory.create_model not implemented in this context")
\ No newline at end of file
diff --git a/agent/protocol/result.py b/agent/protocol/result.py
new file mode 100644
index 0000000..ffbe44c
--- /dev/null
+++ b/agent/protocol/result.py
@@ -0,0 +1,97 @@
+from __future__ import annotations
+import time
+import uuid
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import List, Dict, Any, Optional
+
+from agent.protocol.task import Task, TaskStatus
+
+
+class AgentActionType(Enum):
+    """Enum representing different types of agent actions."""
+    TOOL_USE = "tool_use"
+    THINKING = "thinking"
+    FINAL_ANSWER = "final_answer"
+
+
+@dataclass
+class ToolResult:
+    """
+    Represents the result of a tool use.
+    
+    Attributes:
+        tool_name: Name of the tool used
+        input_params: Parameters passed to the tool
+        output: Output from the tool
+        status: Status of the tool execution (success/error)
+        error_message: Error message if the tool execution failed
+        execution_time: Time taken to execute the tool
+    """
+    tool_name: str
+    input_params: Dict[str, Any]
+    output: Any
+    status: str
+    error_message: Optional[str] = None
+    execution_time: float = 0.0
+
+
+@dataclass
+class AgentAction:
+    """
+    Represents an action taken by an agent.
+    
+    Attributes:
+        id: Unique identifier for the action
+        agent_id: ID of the agent that performed the action
+        agent_name: Name of the agent that performed the action
+        action_type: Type of action (tool use, thinking, final answer)
+        content: Content of the action (thought content, final answer content)
+        tool_result: Tool use details if action_type is TOOL_USE
+        timestamp: When the action was performed
+    """
+    agent_id: str
+    agent_name: str
+    action_type: AgentActionType
+    id: str = field(default_factory=lambda: str(uuid.uuid4()))
+    content: str = ""
+    tool_result: Optional[ToolResult] = None
+    thought: Optional[str] = None
+    timestamp: float = field(default_factory=time.time)
+
+
+@dataclass
+class AgentResult:
+    """
+    Represents the result of an agent's execution.
+
+    Attributes:
+        final_answer: The final answer provided by the agent
+        step_count: Number of steps taken by the agent
+        status: Status of the execution (success/error)
+        error_message: Error message if execution failed
+    """
+    final_answer: str
+    step_count: int
+    status: str = "success"
+    error_message: Optional[str] = None
+
+    @classmethod
+    def success(cls, final_answer: str, step_count: int) -> "AgentResult":
+        """Create a successful result"""
+        return cls(final_answer=final_answer, step_count=step_count)
+
+    @classmethod
+    def error(cls, error_message: str, step_count: int = 0) -> "AgentResult":
+        """Create an error result"""
+        return cls(
+            final_answer=f"Error: {error_message}",
+            step_count=step_count,
+            status="error",
+            error_message=error_message
+        )
+
+    @property
+    def is_error(self) -> bool:
+        """Check if the result represents an error"""
+        return self.status == "error"
\ No newline at end of file
diff --git a/agent/protocol/task.py b/agent/protocol/task.py
new file mode 100644
index 0000000..53a703f
--- /dev/null
+++ b/agent/protocol/task.py
@@ -0,0 +1,96 @@
+from __future__ import annotations
+import time
+import uuid
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Dict, Any, List
+
+
+class TaskType(Enum):
+    """Enum representing different types of tasks."""
+    TEXT = "text"
+    IMAGE = "image"
+    VIDEO = "video"
+    AUDIO = "audio"
+    FILE = "file"
+    MIXED = "mixed"
+
+
+class TaskStatus(Enum):
+    """Enum representing the status of a task."""
+    INIT = "init"  # Initial state
+    PROCESSING = "processing"  # In progress
+    COMPLETED = "completed"  # Completed
+    FAILED = "failed"  # Failed
+
+
+@dataclass
+class Task:
+    """
+    Represents a task to be processed by an agent.
+    
+    Attributes:
+        id: Unique identifier for the task
+        content: The primary text content of the task
+        type: Type of the task
+        status: Current status of the task
+        created_at: Timestamp when the task was created
+        updated_at: Timestamp when the task was last updated
+        metadata: Additional metadata for the task
+        images: List of image URLs or base64 encoded images
+        videos: List of video URLs
+        audios: List of audio URLs or base64 encoded audios
+        files: List of file URLs or paths
+    """
+    id: str = field(default_factory=lambda: str(uuid.uuid4()))
+    content: str = ""
+    type: TaskType = TaskType.TEXT
+    status: TaskStatus = TaskStatus.INIT
+    created_at: float = field(default_factory=time.time)
+    updated_at: float = field(default_factory=time.time)
+    metadata: Dict[str, Any] = field(default_factory=dict)
+
+    # Media content
+    images: List[str] = field(default_factory=list)
+    videos: List[str] = field(default_factory=list)
+    audios: List[str] = field(default_factory=list)
+    files: List[str] = field(default_factory=list)
+
+    def __init__(self, content: str = "", **kwargs):
+        """
+        Initialize a Task with content and optional keyword arguments.
+        
+        Args:
+            content: The text content of the task
+            **kwargs: Additional attributes to set
+        """
+        self.id = kwargs.get('id', str(uuid.uuid4()))
+        self.content = content
+        self.type = kwargs.get('type', TaskType.TEXT)
+        self.status = kwargs.get('status', TaskStatus.INIT)
+        self.created_at = kwargs.get('created_at', time.time())
+        self.updated_at = kwargs.get('updated_at', time.time())
+        self.metadata = kwargs.get('metadata', {})
+        self.images = kwargs.get('images', [])
+        self.videos = kwargs.get('videos', [])
+        self.audios = kwargs.get('audios', [])
+        self.files = kwargs.get('files', [])
+
+    def get_text(self) -> str:
+        """
+        Get the text content of the task.
+        
+        Returns:
+            The text content
+        """
+        return self.content
+
+    def update_status(self, status: TaskStatus) -> None:
+        """
+        Update the status of the task.
+        
+        Args:
+            status: The new status
+        """
+        self.status = status
+        self.updated_at = time.time()
\ No newline at end of file
diff --git a/agent/skills/__init__.py b/agent/skills/__init__.py
new file mode 100644
index 0000000..c634579
--- /dev/null
+++ b/agent/skills/__init__.py
@@ -0,0 +1,31 @@
+"""
+Skills module for agent system.
+
+This module provides the framework for loading, managing, and executing skills.
+Skills are markdown files with frontmatter that provide specialized instructions
+for specific tasks.
+"""
+
+from agent.skills.types import (
+    Skill,
+    SkillEntry,
+    SkillMetadata,
+    SkillInstallSpec,
+    LoadSkillsResult,
+)
+from agent.skills.loader import SkillLoader
+from agent.skills.manager import SkillManager
+from agent.skills.service import SkillService
+from agent.skills.formatter import format_skills_for_prompt
+
+__all__ = [
+    "Skill",
+    "SkillEntry",
+    "SkillMetadata",
+    "SkillInstallSpec",
+    "LoadSkillsResult",
+    "SkillLoader",
+    "SkillManager",
+    "SkillService",
+    "format_skills_for_prompt",
+]
diff --git a/agent/skills/config.py b/agent/skills/config.py
new file mode 100644
index 0000000..788009f
--- /dev/null
+++ b/agent/skills/config.py
@@ -0,0 +1,230 @@
+"""
+Configuration support for skills.
+"""
+
+import os
+import platform
+from typing import Dict, Optional, List
+from agent.skills.types import SkillEntry
+
+
+def resolve_runtime_platform() -> str:
+    """Get the current runtime platform."""
+    return platform.system().lower()
+
+
+def has_binary(bin_name: str) -> bool:
+    """
+    Check if a binary is available in PATH.
+    
+    :param bin_name: Binary name to check
+    :return: True if binary is available
+    """
+    import shutil
+    return shutil.which(bin_name) is not None
+
+
+def has_any_binary(bin_names: List[str]) -> bool:
+    """
+    Check if any of the given binaries is available.
+    
+    :param bin_names: List of binary names to check
+    :return: True if at least one binary is available
+    """
+    return any(has_binary(bin_name) for bin_name in bin_names)
+
+
+def has_env_var(env_name: str) -> bool:
+    """
+    Check if an environment variable is set.
+    
+    :param env_name: Environment variable name
+    :return: True if environment variable is set
+    """
+    return env_name in os.environ and bool(os.environ[env_name].strip())
+
+
+def get_skill_config(config: Optional[Dict], skill_name: str) -> Optional[Dict]:
+    """
+    Get skill-specific configuration.
+    
+    :param config: Global configuration dictionary
+    :param skill_name: Name of the skill
+    :return: Skill configuration or None
+    """
+    if not config:
+        return None
+    
+    skills_config = config.get('skills', {})
+    if not isinstance(skills_config, dict):
+        return None
+    
+    entries = skills_config.get('entries', {})
+    if not isinstance(entries, dict):
+        return None
+    
+    return entries.get(skill_name)
+
+
+def should_include_skill(
+    entry: SkillEntry,
+    config: Optional[Dict] = None,
+    current_platform: Optional[str] = None,
+) -> bool:
+    """
+    Determine if a skill should be included based on requirements.
+    
+    Simple rule: Skills are auto-enabled if their requirements are met.
+    - Has required API keys → enabled
+    - Missing API keys → disabled
+    - Wrong keys → enabled but will fail at runtime (LLM will handle error)
+    
+    :param entry: SkillEntry to check
+    :param config: Configuration dictionary (currently unused, reserved for future)
+    :param current_platform: Current platform (default: auto-detect)
+    :return: True if skill should be included
+    """
+    metadata = entry.metadata
+    
+    # No metadata = always include (no requirements)
+    if not metadata:
+        return True
+    
+    # Check platform requirements (can't work on wrong platform)
+    if metadata.os:
+        platform_name = current_platform or resolve_runtime_platform()
+        # Map common platform names
+        platform_map = {
+            'darwin': 'darwin',
+            'linux': 'linux',
+            'windows': 'win32',
+        }
+        normalized_platform = platform_map.get(platform_name, platform_name)
+        
+        if normalized_platform not in metadata.os:
+            return False
+    
+    # If skill has 'always: true', include it regardless of other requirements
+    if metadata.always:
+        return True
+    
+    # Check requirements
+    if metadata.requires:
+        # Check required binaries (all must be present)
+        required_bins = metadata.requires.get('bins', [])
+        if required_bins:
+            if not all(has_binary(bin_name) for bin_name in required_bins):
+                return False
+        
+        # Check anyBins (at least one must be present)
+        any_bins = metadata.requires.get('anyBins', [])
+        if any_bins:
+            if not has_any_binary(any_bins):
+                return False
+        
+        # Check environment variables (API keys)
+        # All required env vars must be set
+        required_env = metadata.requires.get('env', [])
+        if required_env:
+            for env_name in required_env:
+                if not has_env_var(env_name):
+                    return False
+
+        # Check anyEnv (at least one must be present)
+        any_env = metadata.requires.get('anyEnv', [])
+        if any_env:
+            if not any(has_env_var(e) for e in any_env):
+                return False
+    
+    return True
+
+
+def get_missing_requirements(
+    entry: SkillEntry,
+    current_platform: Optional[str] = None,
+) -> Dict[str, List[str]]:
+    """
+    Return a dict of missing requirements for a skill.
+    Empty dict means all requirements are met.
+
+    :param entry: SkillEntry to check
+    :param current_platform: Current platform (default: auto-detect)
+    :return: Dict like {"bins": ["curl"], "env": ["API_KEY"]}
+    """
+    missing: Dict[str, List[str]] = {}
+    metadata = entry.metadata
+
+    if not metadata or not metadata.requires:
+        return missing
+
+    required_bins = metadata.requires.get('bins', [])
+    if required_bins:
+        missing_bins = [b for b in required_bins if not has_binary(b)]
+        if missing_bins:
+            missing['bins'] = missing_bins
+
+    any_bins = metadata.requires.get('anyBins', [])
+    if any_bins and not has_any_binary(any_bins):
+        missing['anyBins'] = any_bins
+
+    required_env = metadata.requires.get('env', [])
+    if required_env:
+        missing_env = [e for e in required_env if not has_env_var(e)]
+        if missing_env:
+            missing['env'] = missing_env
+
+    any_env = metadata.requires.get('anyEnv', [])
+    if any_env and not any(has_env_var(e) for e in any_env):
+        missing['anyEnv'] = any_env
+
+    return missing
+
+
+def is_config_path_truthy(config: Dict, path: str) -> bool:
+    """
+    Check if a config path resolves to a truthy value.
+    
+    :param config: Configuration dictionary
+    :param path: Dot-separated path (e.g., 'skills.enabled')
+    :return: True if path resolves to truthy value
+    """
+    parts = path.split('.')
+    current = config
+    
+    for part in parts:
+        if not isinstance(current, dict):
+            return False
+        current = current.get(part)
+        if current is None:
+            return False
+    
+    # Check if value is truthy
+    if isinstance(current, bool):
+        return current
+    if isinstance(current, (int, float)):
+        return current != 0
+    if isinstance(current, str):
+        return bool(current.strip())
+    
+    return bool(current)
+
+
+def resolve_config_path(config: Dict, path: str):
+    """
+    Resolve a dot-separated config path to its value.
+    
+    :param config: Configuration dictionary
+    :param path: Dot-separated path
+    :return: Value at path or None
+    """
+    parts = path.split('.')
+    current = config
+    
+    for part in parts:
+        if not isinstance(current, dict):
+            return None
+        current = current.get(part)
+        if current is None:
+            return None
+    
+    return current
diff --git a/agent/skills/formatter.py b/agent/skills/formatter.py
new file mode 100644
index 0000000..d1eebe0
--- /dev/null
+++ b/agent/skills/formatter.py
@@ -0,0 +1,126 @@
+"""
+Skill formatter for generating prompts from skills.
+"""
+
+from typing import Dict, List
+from agent.skills.types import Skill, SkillEntry
+
+
+def format_skills_for_prompt(skills: List[Skill]) -> str:
+    """
+    Format skills for inclusion in a system prompt.
+    
+    Uses XML format per Agent Skills standard.
+    Skills with disable_model_invocation=True are excluded.
+    
+    :param skills: List of skills to format
+    :return: Formatted prompt text
+    """
+    # Filter out skills that should not be invoked by the model
+    visible_skills = [s for s in skills if not s.disable_model_invocation]
+    
+    if not visible_skills:
+        return ""
+    
+    lines = [
+        "",
+        "<available_skills>",
+    ]
+
+    for skill in visible_skills:
+        lines.append("  <skill>")
+        lines.append(f"    <name>{_escape_xml(skill.name)}</name>")
+        lines.append(f"    <description>{_escape_xml(skill.description)}</description>")
+        lines.append(f"    <location>{_escape_xml(skill.file_path)}</location>")
+        lines.append(f"    <base_dir>{_escape_xml(skill.base_dir)}</base_dir>")
+        lines.append("  </skill>")
+    
+    lines.append("</available_skills>")
+    
+    return "\n".join(lines)
+
+
+def format_skill_entries_for_prompt(entries: List[SkillEntry]) -> str:
+    """
+    Format skill entries for inclusion in a system prompt.
+    
+    :param entries: List of skill entries to format
+    :return: Formatted prompt text
+    """
+    skills = [entry.skill for entry in entries]
+    return format_skills_for_prompt(skills)
+
+
+def format_unavailable_skills_for_prompt(
+    entries: List[SkillEntry],
+    missing_map: Dict[str, Dict[str, List[str]]],
+) -> str:
+    """
+    Format unavailable (requires-not-met) skills as brief setup hints
+    so the AI can guide users to configure them.
+
+    :param entries: List of unavailable skill entries
+    :param missing_map: Dict mapping skill name to its missing requirements
+    :return: Formatted prompt text
+    """
+    if not entries:
+        return ""
+
+    lines = [
+        "",
+        "<unavailable_skills>",
+        "The following skills are installed but not yet ready. "
+        "Guide the user to complete the setup when relevant.",
+    ]
+
+    for entry in entries:
+        skill = entry.skill
+        missing = missing_map.get(skill.name, {})
+
+        missing_parts = []
+        for key, values in missing.items():
+            missing_parts.append(f"{key}: {', '.join(values)}")
+        missing_str = "; ".join(missing_parts) if missing_parts else "unknown"
+
+        setup_hint = _extract_setup_hint(skill)
+
+        lines.append("  <skill>")
+        lines.append(f"    <name>{_escape_xml(skill.name)}</name>")
+        lines.append(f"    <description>{_escape_xml(skill.description)}</description>")
+        lines.append(f"    <missing>{_escape_xml(missing_str)}</missing>")
+        if setup_hint:
+            lines.append(f"    <setup>{_escape_xml(setup_hint)}</setup>")
+        lines.append("  </skill>")
+
+    lines.append("</unavailable_skills>")
+    return "\n".join(lines)
+
+
+def _extract_setup_hint(skill: Skill) -> str:
+    """
+    Extract the Setup section from SKILL.md content as a brief hint.
+    Returns the first few lines of the ## Setup section.
+    """
+    content = skill.content
+    if not content:
+        return ""
+
+    import re
+    match = re.search(r'^##\s+Setup\s*\n(.*?)(?=\n##\s|\Z)', content, re.MULTILINE | re.DOTALL)
+    if not match:
+        return ""
+
+    setup_text = match.group(1).strip()
+    lines = setup_text.split('\n')
+    hint_lines = [l.strip() for l in lines[:6] if l.strip()]
+    return ' '.join(hint_lines)[:300]
+
+
+def _escape_xml(text: str) -> str:
+    """Escape XML special characters."""
+    return (text
+            .replace('&', '&amp;')
+            .replace('<', '&lt;')
+            .replace('>', '&gt;')
+            .replace('"', '&quot;')
+            .replace("'", '&apos;'))
diff --git a/agent/skills/frontmatter.py b/agent/skills/frontmatter.py
new file mode 100644
index 0000000..83d09f8
--- /dev/null
+++ b/agent/skills/frontmatter.py
@@ -0,0 +1,192 @@
+"""
+Frontmatter parsing for skills.
+"""
+
+import re
+import json
+from typing import Dict, Any, Optional, List
+from agent.skills.types import SkillMetadata, SkillInstallSpec
+
+
+def parse_frontmatter(content: str) -> Dict[str, Any]:
+    """
+    Parse YAML-style frontmatter from markdown content.
+    
+    Returns a dictionary of frontmatter fields.
+    """
+    frontmatter = {}
+    
+    # Match frontmatter block between --- markers
+    match = re.match(r'^---\s*\n(.*?)\n---\s*\n', content, re.DOTALL)
+    if not match:
+        return frontmatter
+    
+    frontmatter_text = match.group(1)
+    
+    # Try to use PyYAML for proper YAML parsing
+    try:
+        import yaml
+        frontmatter = yaml.safe_load(frontmatter_text)
+        if not isinstance(frontmatter, dict):
+            frontmatter = {}
+        return frontmatter
+    except ImportError:
+        # Fallback to simple parsing if PyYAML not available
+        pass
+    except Exception:
+        # If YAML parsing fails, fall back to simple parsing
+        pass
+    
+    # Simple YAML-like parsing (supports key: value format only)
+    # This is a fallback for when PyYAML is not available
+    for line in frontmatter_text.split('\n'):
+        line = line.strip()
+        if not line or line.startswith('#'):
+            continue
+        
+        if ':' in line:
+            key, value = line.split(':', 1)
+            key = key.strip()
+            value = value.strip()
+            
+            # Try to parse as JSON if it looks like JSON
+            if value.startswith('{') or value.startswith('['):
+                try:
+                    value = json.loads(value)
+                except json.JSONDecodeError:
+                    pass
+            # Parse boolean values
+            elif value.lower() in ('true', 'false'):
+                value = value.lower() == 'true'
+            # Parse numbers
+            elif value.isdigit():
+                value = int(value)
+            
+            frontmatter[key] = value
+    
+    return frontmatter
+
+
+def parse_metadata(frontmatter: Dict[str, Any]) -> Optional[SkillMetadata]:
+    """
+    Parse skill metadata from frontmatter.
+    
+    Looks for 'metadata' field containing JSON with skill configuration.
+    """
+    metadata_raw = frontmatter.get('metadata')
+    if not metadata_raw:
+        return None
+    
+    # If it's a string, try to parse as JSON
+    if isinstance(metadata_raw, str):
+        try:
+            metadata_raw = json.loads(metadata_raw)
+        except json.JSONDecodeError:
+            return None
+    
+    if not isinstance(metadata_raw, dict):
+        return None
+    
+    # Unwrap nested namespace (e.g. {"openclaw": {...}} or {"cowagent": {...}})
+    meta_obj = _unwrap_metadata_namespace(metadata_raw)
+    
+    # Parse install specs
+    install_specs = []
+    install_raw = meta_obj.get('install', [])
+    if isinstance(install_raw, list):
+        for spec_raw in install_raw:
+            if not isinstance(spec_raw, dict):
+                continue
+            
+            kind = spec_raw.get('kind', spec_raw.get('type', '')).lower()
+            if not kind:
+                continue
+            
+            spec = SkillInstallSpec(
+                kind=kind,
+                id=spec_raw.get('id'),
+                label=spec_raw.get('label'),
+                bins=_normalize_string_list(spec_raw.get('bins')),
+                os=_normalize_string_list(spec_raw.get('os')),
+                formula=spec_raw.get('formula'),
+                package=spec_raw.get('package'),
+                module=spec_raw.get('module'),
+                url=spec_raw.get('url'),
+                archive=spec_raw.get('archive'),
+                extract=spec_raw.get('extract', False),
+                strip_components=spec_raw.get('stripComponents'),
+                target_dir=spec_raw.get('targetDir'),
+            )
+            install_specs.append(spec)
+    
+    # Parse requires
+    requires = {}
+    requires_raw = meta_obj.get('requires', {})
+    if isinstance(requires_raw, dict):
+        for key, value in requires_raw.items():
+            requires[key] = _normalize_string_list(value)
+    
+    return SkillMetadata(
+        always=meta_obj.get('always', False),
+        default_enabled=meta_obj.get('default_enabled', True),
+        skill_key=meta_obj.get('skillKey'),
+        primary_env=meta_obj.get('primaryEnv'),
+        emoji=meta_obj.get('emoji'),
+        homepage=meta_obj.get('homepage'),
+        os=_normalize_string_list(meta_obj.get('os')),
+        requires=requires,
+        install=install_specs,
+    )
+
+
+_KNOWN_METADATA_NAMESPACES = {"cowagent", "openclaw"}
+
+
+def _unwrap_metadata_namespace(metadata_raw: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Unwrap a single-key namespace wrapper like {"cowagent": {...} or {"openclaw": {...}}}.
+    If the top-level dict has exactly one key matching a known namespace, return the inner dict.
+    Otherwise return the original dict unchanged.
+    """
+    keys = set(metadata_raw.keys())
+    ns_keys = keys & _KNOWN_METADATA_NAMESPACES
+    if len(ns_keys) == 1 and len(keys) == 1:
+        ns = ns_keys.pop()
+        inner = metadata_raw[ns]
+        if isinstance(inner, dict):
+            return inner
+    return metadata_raw
+
+
+def _normalize_string_list(value: Any) -> List[str]:
+    """Normalize a value to a list of strings."""
+    if not value:
+        return []
+    
+    if isinstance(value, list):
+        return [str(v).strip() for v in value if v]
+    
+    if isinstance(value, str):
+        return [v.strip() for v in value.split(',') if v.strip()]
+    
+    return []
+
+
+def parse_boolean_value(value: Optional[str], default: bool = False) -> bool:
+    """Parse a boolean value from frontmatter."""
+    if value is None:
+        return default
+    
+    if isinstance(value, bool):
+        return value
+    
+    if isinstance(value, str):
+        return value.lower() in ('true', '1', 'yes', 'on')
+    
+    return default
+
+
+def get_frontmatter_value(frontmatter: Dict[str, Any], key: str) -> Optional[str]:
+    """Get a frontmatter value as a string."""
+    value = frontmatter.get(key)
+    return str(value) if value is not None else None
diff --git a/agent/skills/loader.py b/agent/skills/loader.py
new file mode 100644
index 0000000..3784b01
--- /dev/null
+++ b/agent/skills/loader.py
@@ -0,0 +1,286 @@
+"""
+Skill loader for discovering and loading skills from directories.
+"""
+
+import os
+from pathlib import Path
+from typing import List, Optional, Dict
+from common.log import logger
+from agent.skills.types import Skill, SkillEntry, LoadSkillsResult, SkillMetadata
+from agent.skills.frontmatter import parse_frontmatter, parse_metadata, parse_boolean_value, get_frontmatter_value
+
+
+class SkillLoader:
+    """Loads skills from various directories."""
+
+    def __init__(self):
+        pass
+    
+    def load_skills_from_dir(self, dir_path: str, source: str) -> LoadSkillsResult:
+        """
+        Load skills from a directory.
+
+        Discovery rules:
+        - Direct .md files in the root directory
+        - Recursive SKILL.md files under subdirectories
+
+        :param dir_path: Directory path to scan
+        :param source: Source identifier ('builtin' or 'custom')
+        :return: LoadSkillsResult with skills and diagnostics
+        """
+        skills = []
+        diagnostics = []
+        
+        if not os.path.exists(dir_path):
+            diagnostics.append(f"Directory does not exist: {dir_path}")
+            return LoadSkillsResult(skills=skills, diagnostics=diagnostics)
+        
+        if not os.path.isdir(dir_path):
+            diagnostics.append(f"Path is not a directory: {dir_path}")
+            return LoadSkillsResult(skills=skills, diagnostics=diagnostics)
+        
+        # Load skills from root-level .md files and subdirectories
+        result = self._load_skills_recursive(dir_path, source, include_root_files=True)
+        
+        return result
+    
+    def _load_skills_recursive(
+        self, 
+        dir_path: str, 
+        source: str, 
+        include_root_files: bool = False
+    ) -> LoadSkillsResult:
+        """
+        Recursively load skills from a directory.
+        
+        If a subdirectory contains its own SKILL.md, it is treated as a
+        self-contained skill (or skill-collection) and its children are
+        NOT scanned further. This prevents sub-skills inside a collection
+        (e.g. style-collection/style-anjing) from being listed as
+        independent top-level skills.
+        
+        :param dir_path: Directory to scan
+        :param source: Source identifier
+        :param include_root_files: Whether to include root-level .md files
+        :return: LoadSkillsResult
+        """
+        skills = []
+        diagnostics = []
+        
+        try:
+            entries = os.listdir(dir_path)
+        except Exception as e:
+            diagnostics.append(f"Failed to list directory {dir_path}: {e}")
+            return LoadSkillsResult(skills=skills, diagnostics=diagnostics)
+
+        # If this directory has its own SKILL.md, load it and stop recursing.
+        # The sub-directories are internal resources of this skill.
+        if not include_root_files and 'SKILL.md' in entries:
+            skill_md_path = os.path.join(dir_path, 'SKILL.md')
+            if os.path.isfile(skill_md_path):
+                skill_result = self._load_skill_from_file(skill_md_path, source)
+                if skill_result.skills:
+                    skills.extend(skill_result.skills)
+                diagnostics.extend(skill_result.diagnostics)
+                return LoadSkillsResult(skills=skills, diagnostics=diagnostics)
+        
+        for entry in entries:
+            if entry.startswith('.'):
+                continue
+            
+            if entry in ('node_modules', '__pycache__', 'venv', '.git'):
+                continue
+            
+            full_path = os.path.join(dir_path, entry)
+            
+            if os.path.isdir(full_path):
+                sub_result = self._load_skills_recursive(full_path, source, include_root_files=False)
+                skills.extend(sub_result.skills)
+                diagnostics.extend(sub_result.diagnostics)
+                continue
+            
+            if not os.path.isfile(full_path):
+                continue
+            
+            is_root_md = include_root_files and entry.endswith('.md') and entry.upper() != 'README.MD'
+            
+            if not is_root_md:
+                continue
+            
+            skill_result = self._load_skill_from_file(full_path, source)
+            if skill_result.skills:
+                skills.extend(skill_result.skills)
+            diagnostics.extend(skill_result.diagnostics)
+        
+        return LoadSkillsResult(skills=skills, diagnostics=diagnostics)
+    
+    def _load_skill_from_file(self, file_path: str, source: str) -> LoadSkillsResult:
+        """
+        Load a single skill from a markdown file.
+        
+        :param file_path: Path to the skill markdown file
+        :param source: Source identifier
+        :return: LoadSkillsResult
+        """
+        diagnostics = []
+        
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                content = f.read()
+        except Exception as e:
+            diagnostics.append(f"Failed to read skill file {file_path}: {e}")
+            return LoadSkillsResult(skills=[], diagnostics=diagnostics)
+        
+        # Parse frontmatter
+        frontmatter = parse_frontmatter(content)
+        
+        # Get skill name and description
+        skill_dir = os.path.dirname(file_path)
+        parent_dir_name = os.path.basename(skill_dir)
+        
+        name = frontmatter.get('name', parent_dir_name)
+        description = frontmatter.get('description', '')
+        
+        # Normalize name (handle both string and list)
+        if isinstance(name, list):
+            name = name[0] if name else parent_dir_name
+        elif not isinstance(name, str):
+            name = str(name) if name else parent_dir_name
+        
+        # Normalize description (handle both string and list)
+        if isinstance(description, list):
+            description = ' '.join(str(d) for d in description if d)
+        elif not isinstance(description, str):
+            description = str(description) if description else ''
+        
+        # Special handling for linkai-agent: dynamically load apps from config.json
+        if name == 'linkai-agent':
+            description = self._load_linkai_agent_description(skill_dir, description)
+        
+        if not description or not description.strip():
+            diagnostics.append(f"Skill {name} has no description: {file_path}")
+            return LoadSkillsResult(skills=[], diagnostics=diagnostics)
+        
+        # Parse disable-model-invocation flag
+        disable_model_invocation = parse_boolean_value(
+            get_frontmatter_value(frontmatter, 'disable-model-invocation'),
+            default=False
+        )
+        
+        # Create skill object
+        skill = Skill(
+            name=name,
+            description=description,
+            file_path=file_path,
+            base_dir=skill_dir,
+            source=source,
+            content=content,
+            disable_model_invocation=disable_model_invocation,
+            frontmatter=frontmatter,
+        )
+        
+        return LoadSkillsResult(skills=[skill], diagnostics=diagnostics)
+    
+    def _load_linkai_agent_description(self, skill_dir: str, default_description: str) -> str:
+        """
+        Dynamically load LinkAI agent description from config.json
+        
+        :param skill_dir: Skill directory
+        :param default_description: Default description from SKILL.md
+        :return: Dynamic description with app list
+        """
+        import json
+        
+        config_path = os.path.join(skill_dir, "config.json")
+        
+        if not os.path.exists(config_path):
+            logger.debug(f"[SkillLoader] linkai-agent skipped: no config.json found")
+            return ""
+        
+        try:
+            with open(config_path, 'r', encoding='utf-8') as f:
+                config = json.load(f)
+            
+            apps = config.get("apps", [])
+            if not apps:
+                return default_description
+            
+            # Build dynamic description with app details
+            app_descriptions = "; ".join([
+                f"{app['app_name']}({app['app_code']}: {app['app_description']})"
+                for app in apps
+            ])
+            
+            return f"Call LinkAI apps/workflows. {app_descriptions}"
+        
+        except Exception as e:
+            logger.warning(f"[SkillLoader] Failed to load linkai-agent config: {e}")
+            return default_description
+    
+    def load_all_skills(
+        self,
+        builtin_dir: Optional[str] = None,
+        custom_dir: Optional[str] = None,
+    ) -> Dict[str, SkillEntry]:
+        """
+        Load skills from builtin and custom directories.
+
+        Precedence (lowest to highest):
+        1. builtin  — project root ``skills/``, shipped with the codebase
+        2. custom   — workspace ``skills/``, installed via cloud console or skill creator
+
+        Same-name custom skills override builtin ones.
+
+        :param builtin_dir: Built-in skills directory
+        :param custom_dir: Custom skills directory
+        :return: Dictionary mapping skill name to SkillEntry
+        """
+        skill_map: Dict[str, SkillEntry] = {}
+        all_diagnostics = []
+
+        # Load builtin skills (lower precedence)
+        if builtin_dir and os.path.exists(builtin_dir):
+            result = self.load_skills_from_dir(builtin_dir, source='builtin')
+            all_diagnostics.extend(result.diagnostics)
+            for skill in result.skills:
+                entry = self._create_skill_entry(skill)
+                skill_map[skill.name] = entry
+
+        # Load custom skills (higher precedence, overrides builtin)
+        if custom_dir and os.path.exists(custom_dir):
+            result = self.load_skills_from_dir(custom_dir, source='custom')
+            all_diagnostics.extend(result.diagnostics)
+            for skill in result.skills:
+                entry = self._create_skill_entry(skill)
+                skill_map[skill.name] = entry
+
+        # Log diagnostics
+        if all_diagnostics:
+            logger.debug(f"Skill loading diagnostics: {len(all_diagnostics)} issues")
+            for diag in all_diagnostics[:5]:
+                logger.debug(f"  - {diag}")
+
+        logger.debug(f"Loaded {len(skill_map)} skills total")
+
+        return skill_map
+    
+    def _create_skill_entry(self, skill: Skill) -> SkillEntry:
+        """
+        Create a SkillEntry from a Skill with parsed metadata.
+        
+        :param skill: The skill to create an entry for
+        :return: SkillEntry with metadata
+        """
+        metadata = parse_metadata(skill.frontmatter)
+        
+        # Parse user-invocable flag
+        user_invocable = parse_boolean_value(
+            get_frontmatter_value(skill.frontmatter, 'user-invocable'),
+            default=True
+        )
+        
+        return SkillEntry(
+            skill=skill,
+            metadata=metadata,
+            user_invocable=user_invocable,
+        )
diff --git a/agent/skills/manager.py b/agent/skills/manager.py
new file mode 100644
index 0000000..ddb2a31
--- /dev/null
+++ b/agent/skills/manager.py
@@ -0,0 +1,361 @@
+"""
+Skill manager for managing skill lifecycle and operations.
+"""
+
+import os
+import json
+from typing import Dict, List, Optional
+from pathlib import Path
+from common.log import logger
+from agent.skills.types import Skill, SkillEntry, SkillSnapshot
+from agent.skills.loader import SkillLoader
+from agent.skills.formatter import format_skill_entries_for_prompt
+
+SKILLS_CONFIG_FILE = "skills_config.json"
+
+
+class SkillManager:
+    """Manages skills for an agent."""
+
+    def __init__(
+        self,
+        builtin_dir: Optional[str] = None,
+        custom_dir: Optional[str] = None,
+        config: Optional[Dict] = None,
+    ):
+        """
+        Initialize the skill manager.
+
+        :param builtin_dir: Built-in skills directory (project root ``skills/``)
+        :param custom_dir: Custom skills directory (workspace ``skills/``)
+        :param config: Configuration dictionary
+        """
+        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+        self.builtin_dir = builtin_dir or os.path.join(project_root, 'skills')
+        self.custom_dir = custom_dir or os.path.join(project_root, 'workspace', 'skills')
+        self.config = config or {}
+        self._skills_config_path = os.path.join(self.custom_dir, SKILLS_CONFIG_FILE)
+
+        # skills_config: full skill metadata keyed by name
+        # { "web-fetch": {"name": ..., "description": ..., "source": ..., "enabled": true}, ... }
+        self.skills_config: Dict[str, dict] = {}
+
+        self.loader = SkillLoader()
+        self.skills: Dict[str, SkillEntry] = {}
+
+        # Load skills on initialization
+        self.refresh_skills()
+
+    def refresh_skills(self):
+        """Reload all skills from builtin and custom directories, then sync config."""
+        self.skills = self.loader.load_all_skills(
+            builtin_dir=self.builtin_dir,
+            custom_dir=self.custom_dir,
+        )
+        self._sync_skills_config()
+        logger.debug(f"SkillManager: Loaded {len(self.skills)} skills")
+
+    # ------------------------------------------------------------------
+    # skills_config.json management
+    # ------------------------------------------------------------------
+    def _load_skills_config(self) -> Dict[str, dict]:
+        """Load skills_config.json from custom_dir. Returns empty dict if not found."""
+        if not os.path.exists(self._skills_config_path):
+            return {}
+        try:
+            with open(self._skills_config_path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            if isinstance(data, dict):
+                return data
+        except Exception as e:
+            logger.warning(f"[SkillManager] Failed to load {SKILLS_CONFIG_FILE}: {e}")
+        return {}
+
+    def _save_skills_config(self):
+        """Persist skills_config to custom_dir/skills_config.json."""
+        os.makedirs(self.custom_dir, exist_ok=True)
+        try:
+            with open(self._skills_config_path, "w", encoding="utf-8") as f:
+                json.dump(self.skills_config, f, indent=4, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[SkillManager] Failed to save {SKILLS_CONFIG_FILE}: {e}")
+
+    def _sync_skills_config(self):
+        """
+        Merge directory-scanned skills with the persisted config file.
+
+        - New skills: use metadata.default_enabled as initial enabled state.
+        - Existing skills: preserve their persisted enabled state.
+        - Skills that no longer exist on disk are removed.
+        - name/description/source are always refreshed from the latest scan.
+        """
+        saved = self._load_skills_config()
+        merged: Dict[str, dict] = {}
+
+        for name, entry in self.skills.items():
+            skill = entry.skill
+            prev = saved.get(name, {})
+            category = prev.get("category", "skill")
+
+            if name in saved:
+                enabled = prev.get("enabled", True)
+            else:
+                enabled = entry.metadata.default_enabled if entry.metadata else True
+
+            entry_dict = {
+                "name": name,
+                "description": skill.description,
+                "source": prev.get("source") or skill.source,
+                "enabled": enabled,
+                "category": category,
+            }
+            display_name = prev.get("display_name")
+            if display_name:
+                entry_dict["display_name"] = display_name
+            merged[name] = entry_dict
+
+        self.skills_config = merged
+        self._save_skills_config()
+
+    def is_skill_enabled(self, name: str) -> bool:
+        """
+        Check if a skill is enabled according to skills_config.
+
+        :param name: skill name
+        :return: True if enabled (default True if not in config)
+        """
+        entry = self.skills_config.get(name)
+        if entry is None:
+            return True
+        return entry.get("enabled", True)
+
+    def set_skill_enabled(self, name: str, enabled: bool):
+        """
+        Set a skill's enabled state and persist.
+
+        :param name: skill name
+        :param enabled: True to enable, False to disable
+        """
+        if name not in self.skills_config:
+            raise ValueError(f"skill '{name}' not found in config")
+        self.skills_config[name]["enabled"] = enabled
+        self._save_skills_config()
+
+    def get_skills_config(self) -> Dict[str, dict]:
+        """
+        Return the full skills_config dict (for query API).
+
+        :return: copy of skills_config
+        """
+        return dict(self.skills_config)
+    
+    def get_skill(self, name: str) -> Optional[SkillEntry]:
+        """
+        Get a skill by name.
+        
+        :param name: Skill name
+        :return: SkillEntry or None if not found
+        """
+        return self.skills.get(name)
+    
+    def list_skills(self) -> List[SkillEntry]:
+        """
+        Get all loaded skills.
+        
+        :return: List of all skill entries
+        """
+        return list(self.skills.values())
+    
+    @staticmethod
+    def _normalize_skill_filter(skill_filter: Optional[List[str]]) -> Optional[List[str]]:
+        """Normalize a skill_filter list into a flat list of stripped names."""
+        if skill_filter is None:
+            return None
+        normalized = []
+        for item in skill_filter:
+            if isinstance(item, str):
+                name = item.strip()
+                if name:
+                    normalized.append(name)
+            elif isinstance(item, list):
+                for subitem in item:
+                    if isinstance(subitem, str):
+                        name = subitem.strip()
+                        if name:
+                            normalized.append(name)
+        return normalized or None
+
+    def filter_skills(
+        self,
+        skill_filter: Optional[List[str]] = None,
+        include_disabled: bool = False,
+    ) -> List[SkillEntry]:
+        """
+        Filter skills that are eligible (enabled + requirements met).
+
+        :param skill_filter: List of skill names to include (None = all)
+        :param include_disabled: Whether to include disabled skills
+        :return: Filtered list of eligible skill entries
+        """
+        from agent.skills.config import should_include_skill
+
+        entries = list(self.skills.values())
+
+        entries = [e for e in entries if should_include_skill(e, self.config)]
+
+        normalized = self._normalize_skill_filter(skill_filter)
+        if normalized is not None:
+            entries = [e for e in entries if e.skill.name in normalized]
+
+        if not include_disabled:
+            entries = [e for e in entries if self.is_skill_enabled(e.skill.name)]
+
+        from config import conf
+        if not conf().get("knowledge", True):
+            entries = [e for e in entries if e.skill.name != "knowledge-wiki"]
+
+        return entries
+
+    def filter_unavailable_skills(
+        self,
+        skill_filter: Optional[List[str]] = None,
+    ) -> tuple:
+        """
+        Find skills that are enabled but have unmet requirements.
+
+        :param skill_filter: Optional list of skill names to include
+        :return: Tuple of (entries, missing_map) where missing_map maps
+                 skill name to its missing requirements dict
+        """
+        from agent.skills.config import should_include_skill, get_missing_requirements
+
+        entries = list(self.skills.values())
+
+        # Only enabled skills
+        entries = [e for e in entries if self.is_skill_enabled(e.skill.name)]
+
+        normalized = self._normalize_skill_filter(skill_filter)
+        if normalized is not None:
+            entries = [e for e in entries if e.skill.name in normalized]
+
+        # Keep only those that fail should_include_skill (requirements not met)
+        unavailable = []
+        missing_map: Dict[str, dict] = {}
+        for e in entries:
+            if not should_include_skill(e, self.config):
+                missing = get_missing_requirements(e)
+                if missing:
+                    unavailable.append(e)
+                    missing_map[e.skill.name] = missing
+
+        return unavailable, missing_map
+
+    def build_skills_prompt(
+        self,
+        skill_filter: Optional[List[str]] = None,
+    ) -> str:
+        """
+        Build a formatted prompt containing available skills
+        and brief hints for unavailable ones.
+
+        :param skill_filter: Optional list of skill names to include
+        :return: Formatted skills prompt
+        """
+        from common.log import logger
+        from agent.skills.formatter import format_unavailable_skills_for_prompt
+
+        eligible = self.filter_skills(skill_filter=skill_filter, include_disabled=False)
+        logger.debug(f"[SkillManager] Eligible: {len(eligible)} skills (total: {len(self.skills)})")
+        if eligible:
+            skill_names = [e.skill.name for e in eligible]
+            logger.debug(f"[SkillManager] Eligible skills: {skill_names}")
+
+        result = format_skill_entries_for_prompt(eligible)
+
+        unavailable, missing_map = self.filter_unavailable_skills(skill_filter=skill_filter)
+        if unavailable:
+            unavailable_names = [e.skill.name for e in unavailable]
+            logger.debug(f"[SkillManager] Unavailable skills (setup needed): {unavailable_names}")
+            result += format_unavailable_skills_for_prompt(unavailable, missing_map)
+
+        logger.debug(f"[SkillManager] Generated prompt length: {len(result)}")
+        return result
+    
+    def build_skill_snapshot(
+        self,
+        skill_filter: Optional[List[str]] = None,
+        version: Optional[int] = None,
+    ) -> SkillSnapshot:
+        """
+        Build a snapshot of skills for a specific run.
+        
+        :param skill_filter: Optional list of skill names to include
+        :param version: Optional version number for the snapshot
+        :return: SkillSnapshot
+        """
+        entries = self.filter_skills(skill_filter=skill_filter, include_disabled=False)
+        prompt = format_skill_entries_for_prompt(entries)
+        
+        skills_info = []
+        resolved_skills = []
+        
+        for entry in entries:
+            skills_info.append({
+                'name': entry.skill.name,
+                'primary_env': entry.metadata.primary_env if entry.metadata else None,
+            })
+            resolved_skills.append(entry.skill)
+        
+        return SkillSnapshot(
+            prompt=prompt,
+            skills=skills_info,
+            resolved_skills=resolved_skills,
+            version=version,
+        )
+    
+    def sync_skills_to_workspace(self, target_workspace_dir: str):
+        """
+        Sync all loaded skills to a target workspace directory.
+        
+        This is useful for sandbox environments where skills need to be copied.
+        
+        :param target_workspace_dir: Target workspace directory
+        """
+        import shutil
+        
+        target_skills_dir = os.path.join(target_workspace_dir, 'skills')
+        
+        # Remove existing skills directory
+        if os.path.exists(target_skills_dir):
+            shutil.rmtree(target_skills_dir)
+        
+        # Create new skills directory
+        os.makedirs(target_skills_dir, exist_ok=True)
+        
+        # Copy each skill
+        for entry in self.skills.values():
+            skill_name = entry.skill.name
+            source_dir = entry.skill.base_dir
+            target_dir = os.path.join(target_skills_dir, skill_name)
+            
+            try:
+                shutil.copytree(source_dir, target_dir)
+                logger.debug(f"Synced skill '{skill_name}' to {target_dir}")
+            except Exception as e:
+                logger.warning(f"Failed to sync skill '{skill_name}': {e}")
+        
+        logger.info(f"Synced {len(self.skills)} skills to {target_skills_dir}")
+    
+    def get_skill_by_key(self, skill_key: str) -> Optional[SkillEntry]:
+        """
+        Get a skill by its skill key (which may differ from name).
+        
+        :param skill_key: Skill key to look up
+        :return: SkillEntry or None
+        """
+        for entry in self.skills.values():
+            if entry.metadata and entry.metadata.skill_key == skill_key:
+                return entry
+            if entry.skill.name == skill_key:
+                return entry
+        return None
diff --git a/agent/skills/service.py b/agent/skills/service.py
new file mode 100644
index 0000000..95cfb9b
--- /dev/null
+++ b/agent/skills/service.py
@@ -0,0 +1,306 @@
+"""
+Skill service for handling skill CRUD operations.
+
+This service provides a unified interface for managing skills, which can be
+called from the cloud control client (LinkAI), the local web console, or any
+other management entry point.
+"""
+
+import os
+import shutil
+import zipfile
+import tempfile
+from typing import Dict, List, Optional
+from common.log import logger
+from agent.skills.types import Skill, SkillEntry
+from agent.skills.manager import SkillManager
+
+try:
+    import requests
+except ImportError:
+    requests = None
+
+
+class SkillService:
+    """
+    High-level service for skill lifecycle management.
+    Wraps SkillManager and provides network-aware operations such as
+    downloading skill files from remote URLs.
+    """
+
+    def __init__(self, skill_manager: SkillManager):
+        """
+        :param skill_manager: The SkillManager instance to operate on
+        """
+        self.manager = skill_manager
+
+    def _safe_skill_dir(self, name: str) -> str:
+        """Derive and validate the skill directory path.
+
+        Ensures the resolved path stays within the custom_dir root,
+        preventing path traversal via names like ``../escaped``.
+
+        :raises ValueError: if the name would escape the skills root.
+        """
+        if not name or not name.strip():
+            raise ValueError("skill name is required")
+        # Reject obvious traversal components.
+        if ".." in name or name.startswith("/") or name.startswith("\\"):
+            raise ValueError(f"invalid skill name (path traversal detected): {name!r}")
+        skill_dir = os.path.realpath(os.path.join(self.manager.custom_dir, name))
+        root = os.path.realpath(self.manager.custom_dir)
+        if not skill_dir.startswith(root + os.sep) and skill_dir != root:
+            raise ValueError(
+                f"skill name {name!r} resolves outside the skills directory"
+            )
+        return skill_dir
+
+    # ------------------------------------------------------------------
+    # query
+    # ------------------------------------------------------------------
+    def query(self) -> List[dict]:
+        """
+        Query all skills and return a serialisable list.
+        Reads from skills_config.json (refreshes from disk if needed).
+
+        :return: list of skill info dicts
+        """
+        self.manager.refresh_skills()
+        config = self.manager.get_skills_config()
+        result = list(config.values())
+        logger.info(f"[SkillService] query: {len(result)} skills found")
+        return result
+
+    # ------------------------------------------------------------------
+    # add / install
+    # ------------------------------------------------------------------
+    def add(self, payload: dict) -> None:
+        """
+        Add (install) a skill from a remote payload.
+
+        Supported payload types:
+
+        1. ``type: "url"`` – download individual files::
+
+            {
+                "name": "web_search",
+                "type": "url",
+                "enabled": true,
+                "files": [
+                    {"url": "https://...", "path": "README.md"},
+                    {"url": "https://...", "path": "scripts/main.py"}
+                ]
+            }
+
+        2. ``type: "package"`` – download a zip archive and extract::
+
+            {
+                "name": "plugin-custom-tool",
+                "type": "package",
+                "category": "skills",
+                "enabled": true,
+                "files": [{"url": "https://cdn.example.com/skills/custom-tool.zip"}]
+            }
+
+        :param payload: skill add payload from server
+        """
+        name = payload.get("name")
+        if not name:
+            raise ValueError("skill name is required")
+
+        payload_type = payload.get("type", "url")
+
+        if payload_type == "package":
+            self._add_package(name, payload)
+        else:
+            self._add_url(name, payload)
+
+        self.manager.refresh_skills()
+
+        category = payload.get("category")
+        if category and name in self.manager.skills_config:
+            self.manager.skills_config[name]["category"] = category
+            self.manager._save_skills_config()
+
+    def _add_url(self, name: str, payload: dict) -> None:
+        """Install a skill by downloading individual files."""
+        files = payload.get("files", [])
+        if not files:
+            raise ValueError("skill files list is empty")
+
+        skill_dir = self._safe_skill_dir(name)
+
+        tmp_dir = skill_dir + ".tmp"
+        if os.path.exists(tmp_dir):
+            shutil.rmtree(tmp_dir)
+        os.makedirs(tmp_dir, exist_ok=True)
+
+        try:
+            for file_info in files:
+                url = file_info.get("url")
+                rel_path = file_info.get("path")
+                if not url or not rel_path:
+                    logger.warning(f"[SkillService] add: skip invalid file entry {file_info}")
+                    continue
+                dest = os.path.join(tmp_dir, rel_path)
+                self._download_file(url, dest)
+        except Exception:
+            shutil.rmtree(tmp_dir, ignore_errors=True)
+            raise
+
+        if os.path.exists(skill_dir):
+            shutil.rmtree(skill_dir)
+        os.rename(tmp_dir, skill_dir)
+
+        logger.info(f"[SkillService] add: skill '{name}' installed via url ({len(files)} files)")
+
+    def _add_package(self, name: str, payload: dict) -> None:
+        """
+        Install a skill by downloading a zip archive and extracting it.
+
+        If the archive contains a single top-level directory, that directory
+        is used as the skill folder directly; otherwise a new directory named
+        after the skill is created to hold the extracted contents.
+        """
+        files = payload.get("files", [])
+        if not files or not files[0].get("url"):
+            raise ValueError("package url is required")
+
+        url = files[0]["url"]
+        skill_dir = self._safe_skill_dir(name)
+
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            zip_path = os.path.join(tmp_dir, "package.zip")
+            self._download_file(url, zip_path)
+
+            if not zipfile.is_zipfile(zip_path):
+                raise ValueError(f"downloaded file is not a valid zip archive: {url}")
+
+            extract_dir = os.path.join(tmp_dir, "extracted")
+            with zipfile.ZipFile(zip_path, "r") as zf:
+                zf.extractall(extract_dir)
+
+            # Determine the actual content root.
+            # If the zip has a single top-level directory, use its contents
+            # so the skill folder is clean (no extra nesting).
+            top_items = [
+                item for item in os.listdir(extract_dir)
+                if not item.startswith(".")
+            ]
+            if len(top_items) == 1:
+                single = os.path.join(extract_dir, top_items[0])
+                if os.path.isdir(single):
+                    extract_dir = single
+
+            if os.path.exists(skill_dir):
+                shutil.rmtree(skill_dir)
+            shutil.copytree(extract_dir, skill_dir)
+
+        logger.info(f"[SkillService] add: skill '{name}' installed via package ({url})")
+
+    # ------------------------------------------------------------------
+    # open / close (enable / disable)
+    # ------------------------------------------------------------------
+    def open(self, payload: dict) -> None:
+        """
+        Enable a skill by name.
+
+        :param payload: {"name": "skill_name"}
+        """
+        name = payload.get("name")
+        if not name:
+            raise ValueError("skill name is required")
+        self.manager.set_skill_enabled(name, enabled=True)
+        logger.info(f"[SkillService] open: skill '{name}' enabled")
+
+    def close(self, payload: dict) -> None:
+        """
+        Disable a skill by name.
+
+        :param payload: {"name": "skill_name"}
+        """
+        name = payload.get("name")
+        if not name:
+            raise ValueError("skill name is required")
+        self.manager.set_skill_enabled(name, enabled=False)
+        logger.info(f"[SkillService] close: skill '{name}' disabled")
+
+    # ------------------------------------------------------------------
+    # delete
+    # ------------------------------------------------------------------
+    def delete(self, payload: dict) -> None:
+        """
+        Delete a skill by removing its directory entirely.
+
+        :param payload: {"name": "skill_name"}
+        """
+        name = payload.get("name")
+        if not name:
+            raise ValueError("skill name is required")
+
+        skill_dir = self._safe_skill_dir(name)
+        if os.path.exists(skill_dir):
+            shutil.rmtree(skill_dir)
+            logger.info(f"[SkillService] delete: removed directory {skill_dir}")
+        else:
+            logger.warning(f"[SkillService] delete: skill directory not found: {skill_dir}")
+
+        # Refresh will remove the deleted skill from config automatically
+        self.manager.refresh_skills()
+        logger.info(f"[SkillService] delete: skill '{name}' deleted")
+
+    # ------------------------------------------------------------------
+    # dispatch - single entry point for protocol messages
+    # ------------------------------------------------------------------
+    def dispatch(self, action: str, payload: Optional[dict] = None) -> dict:
+        """
+        Dispatch a skill management action and return a protocol-compatible
+        response dict.
+
+        :param action: one of query / add / open / close / delete
+        :param payload: action-specific payload (may be None for query)
+        :return: dict with action, code, message, payload
+        """
+        payload = payload or {}
+        try:
+            if action == "query":
+                result_payload = self.query()
+                return {"action": action, "code": 200, "message": "success", "payload": result_payload}
+            elif action == "add":
+                self.add(payload)
+            elif action == "open":
+                self.open(payload)
+            elif action == "close":
+                self.close(payload)
+            elif action == "delete":
+                self.delete(payload)
+            else:
+                return {"action": action, "code": 400, "message": f"unknown action: {action}", "payload": None}
+            return {"action": action, "code": 200, "message": "success", "payload": None}
+        except Exception as e:
+            logger.error(f"[SkillService] dispatch error: action={action}, error={e}")
+            return {"action": action, "code": 500, "message": str(e), "payload": None}
+
+    # ------------------------------------------------------------------
+    # internal helpers
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _download_file(url: str, dest: str):
+        """
+        Download a file from *url* and save to *dest*.
+
+        :param url: remote file URL
+        :param dest: local destination path
+        """
+        if requests is None:
+            raise RuntimeError("requests library is required for downloading skill files")
+
+        dest_dir = os.path.dirname(dest)
+        if dest_dir:
+            os.makedirs(dest_dir, exist_ok=True)
+
+        resp = requests.get(url, timeout=60)
+        resp.raise_for_status()
+        with open(dest, "wb") as f:
+            f.write(resp.content)
+        logger.debug(f"[SkillService] downloaded {url} -> {dest}")
diff --git a/agent/skills/types.py b/agent/skills/types.py
new file mode 100644
index 0000000..a6a467e
--- /dev/null
+++ b/agent/skills/types.py
@@ -0,0 +1,76 @@
+"""
+Type definitions for skills system.
+"""
+
+from __future__ import annotations
+from typing import Dict, List, Optional, Any
+from dataclasses import dataclass, field
+
+
+@dataclass
+class SkillInstallSpec:
+    """Specification for installing skill dependencies."""
+    kind: str  # brew, pip, npm, download, etc.
+    id: Optional[str] = None
+    label: Optional[str] = None
+    bins: List[str] = field(default_factory=list)
+    os: List[str] = field(default_factory=list)
+    formula: Optional[str] = None  # for brew
+    package: Optional[str] = None  # for pip/npm
+    module: Optional[str] = None
+    url: Optional[str] = None  # for download
+    archive: Optional[str] = None
+    extract: bool = False
+    strip_components: Optional[int] = None
+    target_dir: Optional[str] = None
+
+
+@dataclass
+class SkillMetadata:
+    """Metadata for a skill from frontmatter."""
+    always: bool = False  # Always include this skill
+    default_enabled: bool = True  # Initial enabled state when first discovered
+    skill_key: Optional[str] = None  # Override skill key
+    primary_env: Optional[str] = None  # Primary environment variable
+    emoji: Optional[str] = None
+    homepage: Optional[str] = None
+    os: List[str] = field(default_factory=list)  # Supported OS platforms
+    requires: Dict[str, List[str]] = field(default_factory=dict)  # Requirements
+    install: List[SkillInstallSpec] = field(default_factory=list)
+
+
+@dataclass
+class Skill:
+    """Represents a skill loaded from a markdown file."""
+    name: str
+    description: str
+    file_path: str
+    base_dir: str
+    source: str  # builtin or custom
+    content: str  # Full markdown content
+    disable_model_invocation: bool = False
+    frontmatter: Dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class SkillEntry:
+    """A skill with parsed metadata."""
+    skill: Skill
+    metadata: Optional[SkillMetadata] = None
+    user_invocable: bool = True  # Can users invoke this skill directly
+
+
+@dataclass
+class LoadSkillsResult:
+    """Result of loading skills from a directory."""
+    skills: List[Skill]
+    diagnostics: List[str] = field(default_factory=list)
+
+
+@dataclass
+class SkillSnapshot:
+    """Snapshot of skills for a specific run."""
+    prompt: str  # Formatted prompt text
+    skills: List[Dict[str, str]]  # List of skill info (name, primary_env)
+    resolved_skills: List[Skill] = field(default_factory=list)
+    version: Optional[int] = None
diff --git a/agent/tools/__init__.py b/agent/tools/__init__.py
new file mode 100644
index 0000000..1e508c0
--- /dev/null
+++ b/agent/tools/__init__.py
@@ -0,0 +1,153 @@
+# Import base tool
+from agent.tools.base_tool import BaseTool
+from agent.tools.tool_manager import ToolManager
+
+# Import file operation tools
+from agent.tools.read.read import Read
+from agent.tools.write.write import Write
+from agent.tools.edit.edit import Edit
+from agent.tools.bash.bash import Bash
+from agent.tools.ls.ls import Ls
+from agent.tools.send.send import Send
+
+# Import memory tools
+from agent.tools.memory.memory_search import MemorySearchTool
+from agent.tools.memory.memory_get import MemoryGetTool
+
+# Import self-evolution tools
+from agent.tools.evolution_undo.evolution_undo import EvolutionUndoTool
+
+# Import tools with optional dependencies
+def _import_optional_tools():
+    """Import tools that have optional dependencies"""
+    from common.log import logger
+    tools = {}
+    
+    # EnvConfig Tool (requires python-dotenv)
+    try:
+        from agent.tools.env_config.env_config import EnvConfig
+        tools['EnvConfig'] = EnvConfig
+    except ImportError as e:
+        logger.error(
+            f"[Tools] EnvConfig tool not loaded - missing dependency: {e}\n"
+            f"  To enable environment variable management, run:\n"
+            f"    pip install python-dotenv>=1.0.0"
+        )
+    except Exception as e:
+        logger.error(f"[Tools] EnvConfig tool failed to load: {e}")
+    
+    # Scheduler Tool (requires croniter)
+    try:
+        from agent.tools.scheduler.scheduler_tool import SchedulerTool
+        tools['SchedulerTool'] = SchedulerTool
+    except ImportError as e:
+        logger.error(
+            f"[Tools] Scheduler tool not loaded - missing dependency: {e}\n"
+            f"  To enable scheduled tasks, run:\n"
+            f"    pip install croniter>=2.0.0"
+        )
+    except Exception as e:
+        logger.error(f"[Tools] Scheduler tool failed to load: {e}")
+
+    # WebSearch Tool (conditionally loaded based on API key availability at init time)
+    try:
+        from agent.tools.web_search.web_search import WebSearch
+        tools['WebSearch'] = WebSearch
+    except ImportError as e:
+        logger.error(f"[Tools] WebSearch not loaded - missing dependency: {e}")
+    except Exception as e:
+        logger.error(f"[Tools] WebSearch failed to load: {e}")
+
+    # WebFetch Tool
+    try:
+        from agent.tools.web_fetch.web_fetch import WebFetch
+        tools['WebFetch'] = WebFetch
+    except ImportError as e:
+        logger.error(f"[Tools] WebFetch not loaded - missing dependency: {e}")
+    except Exception as e:
+        logger.error(f"[Tools] WebFetch failed to load: {e}")
+
+    # Vision Tool (conditionally loaded based on API key availability)
+    try:
+        from agent.tools.vision.vision import Vision
+        tools['Vision'] = Vision
+    except ImportError as e:
+        logger.error(f"[Tools] Vision not loaded - missing dependency: {e}")
+    except Exception as e:
+        logger.error(f"[Tools] Vision failed to load: {e}")
+
+    return tools
+
+# Load optional tools
+_optional_tools = _import_optional_tools()
+EnvConfig = _optional_tools.get('EnvConfig')
+SchedulerTool = _optional_tools.get('SchedulerTool')
+WebSearch = _optional_tools.get('WebSearch')
+WebFetch = _optional_tools.get('WebFetch')
+Vision = _optional_tools.get('Vision')
+GoogleSearch = _optional_tools.get('GoogleSearch')
+FileSave = _optional_tools.get('FileSave')
+Terminal = _optional_tools.get('Terminal')
+
+
+# BrowserTool (requires playwright)
+def _import_browser_tool():
+    from common.log import logger
+    try:
+        from agent.tools.browser.browser_tool import BrowserTool
+        return BrowserTool
+    except ImportError as e:
+        logger.info(
+            f"[Tools] BrowserTool not loaded - missing dependency: {e}\n"
+            f"  To enable browser tool, run:\n"
+            f"    pip install playwright\n"
+            f"    playwright install chromium"
+        )
+        return None
+    except Exception as e:
+        logger.error(f"[Tools] BrowserTool failed to load: {e}")
+        return None
+
+BrowserTool = _import_browser_tool()
+
+# MCP Tools (no extra dependencies, loaded on demand)
+def _import_mcp_tools():
+    """导入 MCP 工具模块（无额外依赖，按需加载）"""
+    from common.log import logger
+    try:
+        from agent.tools.mcp.mcp_tool import McpTool
+        from agent.tools.mcp.mcp_client import McpClientRegistry
+        return {'McpTool': McpTool, 'McpClientRegistry': McpClientRegistry}
+    except Exception as e:
+        logger.warning(f"[Tools] MCP tools not loaded: {e}")
+        return {}
+
+_mcp_tools = _import_mcp_tools()
+McpTool = _mcp_tools.get('McpTool')
+McpClientRegistry = _mcp_tools.get('McpClientRegistry')
+
+# Export all tools (including optional ones that might be None)
+__all__ = [
+    'BaseTool',
+    'ToolManager',
+    'Read',
+    'Write',
+    'Edit',
+    'Bash',
+    'Ls',
+    'Send',
+    'MemorySearchTool',
+    'MemoryGetTool',
+    'EvolutionUndoTool',
+    'EnvConfig',
+    'SchedulerTool',
+    'WebSearch',
+    'WebFetch',
+    'Vision',
+    'BrowserTool',
+    'McpTool',
+]
+
+"""
+Tools module for Agent.
+"""
diff --git a/agent/tools/base_tool.py b/agent/tools/base_tool.py
new file mode 100644
index 0000000..53f7cf9
--- /dev/null
+++ b/agent/tools/base_tool.py
@@ -0,0 +1,109 @@
+from enum import Enum
+from typing import Any, Optional
+from common.log import logger
+import copy
+
+
+class ToolStage(Enum):
+    """Enum representing tool decision stages"""
+    PRE_PROCESS = "pre_process"  # Tools that need to be actively selected by the agent
+    POST_PROCESS = "post_process"  # Tools that automatically execute after final_answer
+
+
+class ToolResult:
+    """Tool execution result"""
+    
+    def __init__(self, status: str = None, result: Any = None, ext_data: Any = None):
+        self.status = status
+        self.result = result
+        self.ext_data = ext_data
+
+    @staticmethod
+    def success(result, ext_data: Any = None):
+        return ToolResult(status="success", result=result, ext_data=ext_data)
+
+    @staticmethod
+    def fail(result, ext_data: Any = None):
+        return ToolResult(status="error", result=result, ext_data=ext_data)
+
+
+class BaseTool:
+    """Base class for all tools."""
+
+    # Default decision stage is pre-process
+    stage = ToolStage.PRE_PROCESS
+
+    # Class attributes must be inherited
+    name: str = "base_tool"
+    description: str = "Base tool"
+    params: dict = {}  # Store JSON Schema
+    model: Optional[Any] = None  # LLM model instance, type depends on bot implementation
+    progress_callback = None
+
+    def report_progress(self, message: str):
+        callback = getattr(self, "progress_callback", None)
+        if not callback:
+            return
+        try:
+            callback(str(message))
+        except Exception as e:
+            logger.debug(f"[{self.name}] progress callback failed: {e}")
+
+    @classmethod
+    def get_json_schema(cls) -> dict:
+        """Get the standard description of the tool"""
+        return {
+            "name": cls.name,
+            "description": cls.description,
+            "parameters": cls.params
+        }
+
+    def execute_tool(self, params: dict) -> ToolResult:
+        try:
+            return self.execute(params)
+        except Exception as e:
+            logger.error(e)
+
+    def execute(self, params: dict) -> ToolResult:
+        """Specific logic to be implemented by subclasses"""
+        raise NotImplementedError
+
+    @classmethod
+    def _parse_schema(cls) -> dict:
+        """Convert JSON Schema to Pydantic fields"""
+        fields = {}
+        for name, prop in cls.params["properties"].items():
+            # Convert JSON Schema types to Python types
+            type_map = {
+                "string": str,
+                "number": float,
+                "integer": int,
+                "boolean": bool,
+                "array": list,
+                "object": dict
+            }
+            fields[name] = (
+                type_map[prop["type"]],
+                prop.get("default", ...)
+            )
+        return fields
+
+    def should_auto_execute(self, context) -> bool:
+        """
+        Determine if this tool should be automatically executed based on context.
+
+        :param context: The agent context
+        :return: True if the tool should be executed, False otherwise
+        """
+        # Only tools in post-process stage will be automatically executed
+        return self.stage == ToolStage.POST_PROCESS
+
+    def close(self):
+        """
+        Close any resources used by the tool.
+        This method should be overridden by tools that need to clean up resources
+        such as browser connections, file handles, etc.
+
+        By default, this method does nothing.
+        """
+        pass
diff --git a/agent/tools/bash/__init__.py b/agent/tools/bash/__init__.py
new file mode 100644
index 0000000..bbd4bb0
--- /dev/null
+++ b/agent/tools/bash/__init__.py
@@ -0,0 +1,3 @@
+from .bash import Bash
+
+__all__ = ['Bash']
diff --git a/agent/tools/bash/bash.py b/agent/tools/bash/bash.py
new file mode 100644
index 0000000..3e2bf30
--- /dev/null
+++ b/agent/tools/bash/bash.py
@@ -0,0 +1,455 @@
+"""
+Bash tool - Execute bash commands
+"""
+
+import os
+import re
+import signal
+import sys
+import subprocess
+import tempfile
+import threading
+import time
+from typing import Dict, Any
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.utils.truncate import truncate_tail, format_size, DEFAULT_MAX_LINES, DEFAULT_MAX_BYTES
+from common.log import logger
+from common.utils import expand_path
+
+
+class Bash(BaseTool):
+    """Tool for executing bash commands"""
+
+    _IS_WIN = sys.platform == "win32"
+    _PROGRESS_MAX_BYTES = 4 * 1024
+    _PROGRESS_INTERVAL = 0.5
+    # cmd.exe command line limit is ~8191 chars; rewrite python -c above this.
+    _WIN_CMD_SAFE_LEN = 7000
+
+    name: str = "bash"
+    description: str = f"""Execute a bash command in the current working directory. Returns stdout and stderr. Output is truncated to last {DEFAULT_MAX_LINES} lines or {DEFAULT_MAX_BYTES // 1024}KB (whichever is hit first). If truncated, full output is saved to a temp file.
+{'''
+PLATFORM: Windows (cmd.exe). Do NOT use Unix-only commands like grep, head, tail, sed, awk.
+''' if _IS_WIN else ''}
+ENVIRONMENT: All API keys from env_config are auto-injected. Use $VAR_NAME directly.
+
+SAFETY:
+- Freely create/modify/delete files within the workspace
+- For destructive commands out of workspace, explain and confirm first"""
+
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "command": {
+                "type": "string",
+                "description": "Bash command to execute"
+            },
+            "timeout": {
+                "type": "integer",
+                "description": "Timeout in seconds (optional, default: 30)"
+            }
+        },
+        "required": ["command"]
+    }
+
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        # Ensure working directory exists
+        if not os.path.exists(self.cwd):
+            os.makedirs(self.cwd, exist_ok=True)
+        self.default_timeout = self.config.get("timeout", 30)
+        # Enable safety mode by default (can be disabled in config)
+        self.safety_mode = self.config.get("safety_mode", True)
+
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute a bash command
+        
+        :param args: Dictionary containing the command and optional timeout
+        :return: Command output or error
+        """
+        command = args.get("command", "").strip()
+        timeout = args.get("timeout", self.default_timeout)
+
+        if not command:
+            return ToolResult.fail("Error: command parameter is required")
+
+        # Security check: Prevent direct access to the credential file
+        if re.search(r'\.cow[/\\]\.env', command):
+            return ToolResult.fail(
+                "Error: Access denied. API keys and credentials must be accessed through the env_config tool only."
+            )
+
+        # Optional safety check - only warn about extremely dangerous commands
+        if self.safety_mode:
+            warning = self._get_safety_warning(command)
+            if warning:
+                return ToolResult.fail(
+                    f"Safety Warning: {warning}\n\nIf you believe this command is safe and necessary, please ask the user for confirmation first, explaining what the command does and why it's needed.")
+
+        try:
+            # Prepare environment with .env file variables
+            env = os.environ.copy()
+            
+            # Load environment variables from ~/.cow/.env if it exists
+            env_file = expand_path("~/.cow/.env")
+            dotenv_vars = {}
+            if os.path.exists(env_file):
+                try:
+                    from dotenv import dotenv_values
+                    dotenv_vars = dotenv_values(env_file)
+                    env.update(dotenv_vars)
+                    logger.debug(f"[Bash] Loaded {len(dotenv_vars)} variables from {env_file}")
+                except ImportError:
+                    logger.debug("[Bash] python-dotenv not installed, skipping .env loading")
+                except Exception as e:
+                    logger.debug(f"[Bash] Failed to load .env: {e}")
+
+            # getuid() only exists on Unix-like systems
+            if hasattr(os, 'getuid'):
+                logger.debug(f"[Bash] Process UID: {os.getuid()}")
+            else:
+                logger.debug(f"[Bash] Process User: {os.environ.get('USERNAME', os.environ.get('USER', 'unknown'))}")
+            
+            # Temp script written for long `python -c` commands (Windows only),
+            # cleaned up after execution.
+            temp_script_path = None
+
+            # On Windows, convert $VAR references to %VAR% for cmd.exe
+            if self._IS_WIN:
+                env["PYTHONIOENCODING"] = "utf-8"
+                command = self._convert_env_vars_for_windows(command, dotenv_vars)
+                # cmd.exe has an ~8191 char command line limit. Long
+                # `python -c "..."` commands silently fail, so spill the inline
+                # code into a temp .py file and run that instead.
+                if len(command) > self._WIN_CMD_SAFE_LEN:
+                    command, temp_script_path = self._rewrite_long_python_c(command)
+                if command and not command.strip().lower().startswith("chcp"):
+                    command = f"chcp 65001 >nul 2>&1 && {command}"
+
+            try:
+                result = self._run_streaming(
+                    command,
+                    timeout,
+                    env,
+                    dotenv_vars,
+                )
+            finally:
+                if temp_script_path:
+                    try:
+                        os.remove(temp_script_path)
+                    except OSError:
+                        pass
+            
+            logger.debug(f"[Bash] Exit code: {result.returncode}")
+            logger.debug(f"[Bash] Stdout length: {len(result.stdout)}")
+            logger.debug(f"[Bash] Stderr length: {len(result.stderr)}")
+            
+            # Workaround for exit code 126 with no output
+            if result.returncode == 126 and not result.stdout and not result.stderr:
+                logger.warning(f"[Bash] Exit 126 with no output - trying alternative execution method")
+                # Try using argument list instead of shell=True
+                import shlex
+                try:
+                    parts = shlex.split(command)
+                    if len(parts) > 0:
+                        logger.info(f"[Bash] Retrying with argument list: {parts[:3]}...")
+                        retry_result = subprocess.run(
+                            parts,
+                            cwd=self.cwd,
+                            stdout=subprocess.PIPE,
+                            stderr=subprocess.PIPE,
+                            text=True,
+                            encoding="utf-8",
+                            errors="replace",
+                            timeout=timeout,
+                            env=env
+                        )
+                        logger.debug(f"[Bash] Retry exit code: {retry_result.returncode}, stdout: {len(retry_result.stdout)}, stderr: {len(retry_result.stderr)}")
+                        
+                        # If retry succeeded, use retry result
+                        if retry_result.returncode == 0 or retry_result.stdout or retry_result.stderr:
+                            result = retry_result
+                        else:
+                            # Both attempts failed - check if this is openai-image-vision skill
+                            if 'openai-image-vision' in command or 'vision.sh' in command:
+                                # Create a mock result with helpful error message
+                                from types import SimpleNamespace
+                                result = SimpleNamespace(
+                                    returncode=1,
+                                    stdout='{"error": "图片无法解析", "reason": "该图片格式可能不受支持，或图片文件存在问题", "suggestion": "请尝试其他图片"}',
+                                    stderr=''
+                                )
+                                logger.info(f"[Bash] Converted exit 126 to user-friendly image error message for vision skill")
+                except Exception as retry_err:
+                    logger.warning(f"[Bash] Retry failed: {retry_err}")
+
+            # When command succeeds with stdout, keep output clean (stderr goes to server log only).
+            # When command fails or stdout is empty, include stderr so the agent can diagnose.
+            if result.returncode == 0 and result.stdout.strip():
+                output = result.stdout
+                if result.stderr:
+                    logger.info(f"[Bash] stderr (not forwarded): {result.stderr[:500]}")
+            else:
+                output = result.stdout
+                if result.stderr:
+                    output += "\n" + result.stderr
+
+            # Check if we need to save full output to temp file
+            temp_file_path = None
+            total_bytes = len(output.encode('utf-8'))
+
+            if total_bytes > DEFAULT_MAX_BYTES:
+                # Save full output to temp file. encoding='utf-8' is required:
+                # the default text-mode encoding is the platform locale (e.g.
+                # cp936/GBK on Chinese Windows), which raises UnicodeEncodeError
+                # for output containing emoji or other non-locale characters and
+                # would discard an otherwise successful command result.
+                with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.log', prefix='bash-', encoding='utf-8') as f:
+                    f.write(output)
+                    temp_file_path = f.name
+
+            # Apply tail truncation
+            truncation = truncate_tail(output)
+            output_text = truncation.content or "(no output)"
+
+            # Build result
+            details = {}
+
+            if truncation.truncated:
+                details["truncation"] = truncation.to_dict()
+                if temp_file_path:
+                    details["full_output_path"] = temp_file_path
+
+                # Build notice
+                start_line = truncation.total_lines - truncation.output_lines + 1
+                end_line = truncation.total_lines
+
+                if truncation.last_line_partial:
+                    # Edge case: last line alone > 30KB
+                    last_line = output.split('\n')[-1] if output else ""
+                    last_line_size = format_size(len(last_line.encode('utf-8')))
+                    output_text += f"\n\n[Showing last {format_size(truncation.output_bytes)} of line {end_line} (line is {last_line_size}). Full output: {temp_file_path}]"
+                elif truncation.truncated_by == "lines":
+                    output_text += f"\n\n[Showing lines {start_line}-{end_line} of {truncation.total_lines}. Full output: {temp_file_path}]"
+                else:
+                    output_text += f"\n\n[Showing lines {start_line}-{end_line} of {truncation.total_lines} ({format_size(DEFAULT_MAX_BYTES)} limit). Full output: {temp_file_path}]"
+
+            # Check exit code
+            if result.returncode != 0:
+                output_text += f"\n\nCommand exited with code {result.returncode}"
+                return ToolResult.fail({
+                    "output": output_text,
+                    "exit_code": result.returncode,
+                    "details": details if details else None
+                })
+
+            return ToolResult.success({
+                "output": output_text,
+                "exit_code": result.returncode,
+                "details": details if details else None
+            })
+
+        except subprocess.TimeoutExpired:
+            return ToolResult.fail(f"Error: Command timed out after {timeout} seconds")
+        except Exception as e:
+            return ToolResult.fail(f"Error executing command: {str(e)}")
+
+    def _run_streaming(self, command: str, timeout: int, env: dict, dotenv_vars: dict):
+        process = subprocess.Popen(
+            command,
+            shell=True,
+            cwd=self.cwd,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            env=env,
+            start_new_session=not self._IS_WIN,
+        )
+        stdout_chunks, stderr_chunks = [], []
+        recent = bytearray()
+        recent_lock = threading.Lock()
+
+        def drain(stream, chunks):
+            while True:
+                chunk = os.read(stream.fileno(), 4096)
+                if not chunk:
+                    break
+                chunks.append(chunk)
+                with recent_lock:
+                    recent.extend(chunk)
+                    if len(recent) > self._PROGRESS_MAX_BYTES:
+                        del recent[:-self._PROGRESS_MAX_BYTES]
+
+        readers = [
+            threading.Thread(target=drain, args=(process.stdout, stdout_chunks), daemon=True),
+            threading.Thread(target=drain, args=(process.stderr, stderr_chunks), daemon=True),
+        ]
+        for reader in readers:
+            reader.start()
+
+        started = time.monotonic()
+        last_reported_at = started
+        last_snapshot = None
+        try:
+            while process.poll() is None:
+                now = time.monotonic()
+                elapsed = now - started
+                if elapsed >= timeout:
+                    self._kill_process(process)
+                    raise subprocess.TimeoutExpired(command, timeout)
+                if elapsed >= self._PROGRESS_INTERVAL and now - last_reported_at >= self._PROGRESS_INTERVAL:
+                    with recent_lock:
+                        snapshot = bytes(recent).decode("utf-8", errors="replace")
+                    snapshot = self._redact_progress(snapshot, dotenv_vars)
+                    if snapshot and snapshot != last_snapshot:
+                        self.report_progress(snapshot)
+                        last_snapshot = snapshot
+                    last_reported_at = now
+                time.sleep(0.1)
+        finally:
+            if process.poll() is None:
+                self._kill_process(process)
+            process.wait()
+            join_deadline = time.monotonic() + 5
+            for reader in readers:
+                reader.join(timeout=max(0, join_deadline - time.monotonic()))
+
+        from types import SimpleNamespace
+        return SimpleNamespace(
+            returncode=process.returncode,
+            stdout=b"".join(stdout_chunks).decode("utf-8", errors="replace"),
+            stderr=b"".join(stderr_chunks).decode("utf-8", errors="replace"),
+        )
+
+    def _kill_process(self, process):
+        if self._IS_WIN:
+            try:
+                result = subprocess.run(
+                    ["taskkill", "/F", "/T", "/PID", str(process.pid)],
+                    capture_output=True,
+                    timeout=5,
+                )
+                if result.returncode != 0 and process.poll() is None:
+                    process.kill()
+            except (OSError, subprocess.SubprocessError):
+                if process.poll() is None:
+                    process.kill()
+        else:
+            try:
+                os.killpg(process.pid, signal.SIGKILL)
+            except (PermissionError, ProcessLookupError):
+                if process.poll() is None:
+                    process.kill()
+
+    @staticmethod
+    def _redact_progress(text: str, dotenv_vars: dict) -> str:
+        text = re.sub(
+            r'(?i)\b(API_KEY|TOKEN|PASSWORD|AUTHORIZATION)\s*=\s*[^\s]+',
+            lambda match: f"{match.group(1)}=[REDACTED]",
+            text,
+        )
+        for value in dotenv_vars.values():
+            value = str(value or "")
+            if len(value) >= 6:
+                text = text.replace(value, "[REDACTED]")
+        return text
+
+    def _get_safety_warning(self, command: str) -> str:
+        """
+        Get safety warning for absolutely catastrophic commands only.
+        Keep the blocklist minimal so the agent retains maximum freedom.
+
+        :param command: Command to check
+        :return: Warning message if dangerous, empty string if safe
+        """
+        # Tokenize to avoid substring false positives (e.g. `rm -rf /tmp/x`
+        # must not match `rm -rf /`).
+        tokens = command.lower().split()
+
+        # `rm -rf /` or `rm -rf /*` targeting the real root.
+        for i, tok in enumerate(tokens):
+            if tok != "rm":
+                continue
+            has_rf = False
+            for j in range(i + 1, len(tokens)):
+                t = tokens[j]
+                if t.startswith("-") and "r" in t and "f" in t:
+                    has_rf = True
+                elif t in ("--recursive", "--force"):
+                    continue
+                elif t in ("/", "/*"):
+                    if has_rf:
+                        return "This command will delete the entire filesystem"
+                    break
+                else:
+                    break
+
+        # Disk wiping
+        if "if=/dev/zero" in command.lower() and "dd " in command.lower():
+            return "This command can destroy disk data"
+
+        # Power control - match only as a standalone word (\b enforces word boundary)
+        if re.search(r'\b(shutdown|reboot|halt|poweroff)\b', command.lower()):
+            return "This command will shut down or restart the system"
+
+        return ""
+
+    @staticmethod
+    def _convert_env_vars_for_windows(command: str, dotenv_vars: dict) -> str:
+        """
+        Convert bash-style $VAR / ${VAR} references to cmd.exe %VAR% syntax.
+        Only converts variables loaded from .env (user-configured API keys etc.)
+        to avoid breaking $PATH, jq expressions, regex, etc.
+        """
+        if not dotenv_vars:
+            return command
+
+        def replace_match(m):
+            var_name = m.group(1) or m.group(2)
+            if var_name in dotenv_vars:
+                return f"%{var_name}%"
+            return m.group(0)
+
+        return re.sub(r'\$\{(\w+)\}|\$(\w+)', replace_match, command)
+
+    @staticmethod
+    def _rewrite_long_python_c(command: str):
+        """
+        Rewrite `python -c "<code>"` into `python <tempfile>` to bypass the
+        cmd.exe command line length limit on Windows.
+
+        Returns (new_command, temp_file_path). On any parse failure the original
+        command and None are returned, so behavior is unchanged when unmatched.
+        """
+        # Match: <python|python3|py> [flags] -c "<code>" (single or double quoted)
+        m = re.search(
+            r'^(?P<prefix>.*?\b(?:python3?|py)\b[^\n]*?\s-c\s+)'
+            r'(?P<quote>["\'])(?P<code>.*)(?P=quote)\s*(?P<suffix>.*)$',
+            command,
+            re.DOTALL,
+        )
+        if not m:
+            return command, None
+
+        quote = m.group("quote")
+        code = m.group("code")
+        # Reverse common shell-level escaping of the quote char inside the code.
+        code = code.replace("\\" + quote, quote)
+
+        try:
+            fd, path = tempfile.mkstemp(suffix=".py", prefix="bash-pyc-")
+            with os.fdopen(fd, "w", encoding="utf-8") as f:
+                f.write(code)
+        except OSError:
+            return command, None
+
+        prefix = m.group("prefix")
+        # Drop the trailing "-c " from the prefix, keep the interpreter + flags.
+        interp = re.sub(r'\s-c\s+$', ' ', prefix).rstrip()
+        suffix = m.group("suffix").strip()
+        new_command = f'{interp} "{path}"'
+        if suffix:
+            new_command += f' {suffix}'
+        return new_command, path
diff --git a/agent/tools/browser/__init__.py b/agent/tools/browser/__init__.py
new file mode 100644
index 0000000..8a5e733
--- /dev/null
+++ b/agent/tools/browser/__init__.py
@@ -0,0 +1,3 @@
+from agent.tools.browser.browser_tool import BrowserTool
+
+__all__ = ["BrowserTool"]
diff --git a/agent/tools/browser/browser_service.py b/agent/tools/browser/browser_service.py
new file mode 100644
index 0000000..f499fb2
--- /dev/null
+++ b/agent/tools/browser/browser_service.py
@@ -0,0 +1,961 @@
+"""
+Browser service - Playwright wrapper managing browser lifecycle and page operations.
+
+All Playwright calls run on a dedicated background thread so that callers from
+any worker thread can safely use the service.  An idle-timeout mechanism
+automatically shuts down the browser (and its thread) after a configurable
+period of inactivity to free resources.
+"""
+
+import os
+import sys
+import uuid
+import queue
+import threading
+from typing import Optional, Dict, Any, List, Callable
+
+from common.log import logger
+from common.utils import expand_path, is_cloud_deployment
+
+
+_DEFAULT_USER_DATA_DIR = "~/.cow/browser_profile"
+
+try:
+    from playwright.sync_api import sync_playwright, Browser, BrowserContext, Page, Playwright
+    _HAS_PLAYWRIGHT = True
+except ImportError:
+    _HAS_PLAYWRIGHT = False
+
+
+# ---------------------------------------------------------------------------
+# Snapshot DOM helpers
+# ---------------------------------------------------------------------------
+
+# Tags that typically carry useful content for an agent
+_INTERACTIVE_TAGS = {
+    "a", "button", "input", "textarea", "select", "option",
+    "label", "details", "summary",
+}
+_SEMANTIC_TAGS = {
+    "h1", "h2", "h3", "h4", "h5", "h6",
+    "p", "li", "td", "th", "caption", "figcaption", "blockquote", "pre", "code",
+    "nav", "main", "article", "section", "header", "footer", "form", "table",
+    "img", "video", "audio",
+}
+_KEEP_TAGS = _INTERACTIVE_TAGS | _SEMANTIC_TAGS
+
+_SNAPSHOT_JS = """
+() => {
+    const KEEP = new Set(%s);
+    const INTERACTIVE = new Set(%s);
+    const SKIP = new Set(["script","style","noscript","svg","path","meta","link","br","hr"]);
+    const CLICKABLE_ROLES = new Set([
+        "button","link","tab","menuitem","menuitemcheckbox","menuitemradio",
+        "option","switch","checkbox","radio","combobox","searchbox","slider",
+        "spinbutton","textbox","treeitem"
+    ]);
+    let refCounter = 0;
+    const refMap = {};
+
+    function visible(el) {
+        if (!(el instanceof HTMLElement)) return true;
+        const st = window.getComputedStyle(el);
+        if (st.display === "none" || st.visibility === "hidden") return false;
+        if (parseFloat(st.opacity) === 0) return false;
+        return true;
+    }
+
+    // Strong signals: these attributes alone are enough to mark as interactive
+    function hasStrongInteractiveSignal(el) {
+        const role = el.getAttribute("role");
+        if (role && CLICKABLE_ROLES.has(role)) return true;
+        if (el.hasAttribute("onclick") || el.hasAttribute("tabindex")) return true;
+        if (el.hasAttribute("data-click") || el.hasAttribute("data-action")) return true;
+        if (el.getAttribute("contenteditable") === "true") return true;
+        return false;
+    }
+
+    // Check if cursor:pointer is set directly (not just inherited from parent)
+    function hasOwnPointerCursor(el) {
+        try {
+            const st = window.getComputedStyle(el);
+            if (st.cursor !== "pointer") return false;
+            const parent = el.parentElement;
+            if (parent) {
+                const pst = window.getComputedStyle(parent);
+                if (pst.cursor === "pointer") return false;
+            }
+            return true;
+        } catch(e) {}
+        return false;
+    }
+
+    function hasTextOrContent(el) {
+        const t = el.textContent || "";
+        if (t.trim().length > 0) return true;
+        if (el.querySelector("img,video,audio,canvas")) return true;
+        const ariaLabel = el.getAttribute("aria-label");
+        if (ariaLabel && ariaLabel.trim()) return true;
+        const title = el.getAttribute("title");
+        if (title && title.trim()) return true;
+        return false;
+    }
+
+    function isImplicitInteractive(el) {
+        if (hasStrongInteractiveSignal(el)) return true;
+        if (hasOwnPointerCursor(el) && hasTextOrContent(el)) return true;
+        return false;
+    }
+
+    function getTextContent(el) {
+        let text = "";
+        for (const ch of el.childNodes) {
+            if (ch.nodeType === Node.TEXT_NODE) {
+                text += ch.textContent;
+            }
+        }
+        return text.trim();
+    }
+
+    function walk(node) {
+        if (node.nodeType === Node.TEXT_NODE) {
+            const t = node.textContent.trim();
+            return t ? t : null;
+        }
+        if (node.nodeType !== Node.ELEMENT_NODE) return null;
+        const tag = node.tagName.toLowerCase();
+        if (SKIP.has(tag)) return null;
+        if (!visible(node)) return null;
+
+        const children = [];
+        for (const ch of node.childNodes) {
+            const r = walk(ch);
+            if (r !== null) {
+                if (typeof r === "string") children.push(r);
+                else children.push(r);
+            }
+        }
+
+        const nativeInteractive = INTERACTIVE.has(tag);
+        const implicitInteractive = !nativeInteractive && (node instanceof HTMLElement) && isImplicitInteractive(node);
+        const keep = KEEP.has(tag) || implicitInteractive;
+
+        if (!keep) {
+            if (children.length === 0) return null;
+            if (children.length === 1) return children[0];
+            return children;
+        }
+
+        const obj = { tag };
+        if (nativeInteractive || implicitInteractive) {
+            refCounter++;
+            obj.ref = refCounter;
+            refMap[refCounter] = node;
+        }
+
+        if (implicitInteractive) {
+            const role = node.getAttribute("role");
+            if (role) obj.role = role;
+            const directText = getTextContent(node);
+            if (!directText && children.length === 0) {
+                const ariaLabel = node.getAttribute("aria-label");
+                const title = node.getAttribute("title");
+                if (ariaLabel) obj.ariaLabel = ariaLabel;
+                else if (title) obj.ariaLabel = title;
+            }
+        }
+
+        // Attributes
+        if (tag === "a" && node.href) obj.href = node.getAttribute("href");
+        if (tag === "img") {
+            obj.alt = node.alt || "";
+            obj.src = node.getAttribute("src") || "";
+        }
+        if (tag === "input" || tag === "textarea" || tag === "select") {
+            obj.type = node.type || "text";
+            obj.name = node.name || undefined;
+            obj.value = node.value || undefined;
+            obj.placeholder = node.placeholder || undefined;
+            if (node.disabled) obj.disabled = true;
+            if (tag === "input" && node.type === "checkbox") obj.checked = node.checked;
+        }
+        if (tag === "button") {
+            if (node.disabled) obj.disabled = true;
+        }
+        if (tag === "option") {
+            obj.value = node.value;
+            if (node.selected) obj.selected = true;
+        }
+        if (tag === "label" && node.htmlFor) obj.for = node.htmlFor;
+
+        // Role / aria-label for native interactive & semantic elements
+        if (!implicitInteractive) {
+            const role = node.getAttribute("role");
+            if (role) obj.role = role;
+            const ariaLabel = node.getAttribute("aria-label");
+            if (ariaLabel) obj.ariaLabel = ariaLabel;
+        }
+
+        // Children
+        if (children.length === 1 && typeof children[0] === "string") {
+            obj.text = children[0];
+        } else if (children.length > 0) {
+            obj.children = children;
+        }
+
+        return obj;
+    }
+
+    const result = walk(document.body);
+    window.__cowRefMap = refMap;
+    return { tree: result, refCount: refCounter };
+}
+""" % (
+    str(list(_KEEP_TAGS)),
+    str(list(_INTERACTIVE_TAGS)),
+)
+
+
+_BROWSER_DEAD_HINTS = (
+    "has been closed",
+    "browser has disconnected",
+    "target closed",
+    "browser closed",
+    "context or browser has been closed",
+)
+
+
+def _is_browser_dead_error(err: Exception) -> bool:
+    """Return True if *err* indicates the browser / page died out from under us."""
+    msg = str(err).lower()
+    return any(h in msg for h in _BROWSER_DEAD_HINTS)
+
+
+def _should_use_headless() -> bool:
+    """Decide headless mode: headless on Linux servers without display, headed elsewhere."""
+    if sys.platform in ("win32", "darwin"):
+        return False
+    # Linux: check for display
+    if os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY"):
+        return False
+    return True
+
+
+def _flatten_tree(node, indent=0) -> List[str]:
+    """Convert snapshot tree to compact text lines for LLM consumption."""
+    if node is None:
+        return []
+    if isinstance(node, str):
+        return [" " * indent + node]
+    if isinstance(node, list):
+        lines = []
+        for child in node:
+            lines.extend(_flatten_tree(child, indent))
+        return lines
+    if not isinstance(node, dict):
+        return []
+
+    tag = node.get("tag", "?")
+    ref = node.get("ref")
+    parts = [tag]
+    if ref:
+        parts[0] = f"[{ref}] {tag}"
+
+    # Inline attributes
+    for attr in ("type", "name", "href", "alt", "role", "ariaLabel", "placeholder", "value"):
+        val = node.get(attr)
+        if val:
+            # Truncate long values
+            s = str(val)
+            if len(s) > 80:
+                s = s[:77] + "..."
+            parts.append(f'{attr}="{s}"')
+
+    for flag in ("disabled", "checked", "selected"):
+        if node.get(flag):
+            parts.append(flag)
+
+    prefix = " " * indent
+    header = prefix + " ".join(parts)
+
+    text = node.get("text")
+    if text:
+        # Truncate long text
+        if len(text) > 120:
+            text = text[:117] + "..."
+        header += f": {text}"
+
+    lines = [header]
+    children = node.get("children", [])
+    for child in children:
+        lines.extend(_flatten_tree(child, indent + 2))
+    return lines
+
+
+class BrowserService:
+    """Manages a Playwright browser on a dedicated background thread.
+
+    All Playwright operations are dispatched to a single long-lived thread via
+    a task queue.  Callers from *any* worker thread can use the public API
+    safely.  An idle timer automatically shuts the browser down after
+    ``idle_timeout`` seconds of inactivity (default 300 = 5 min).
+    """
+
+    _IDLE_TIMEOUT_DEFAULT = 300  # seconds
+
+    def __init__(self, config: Optional[Dict[str, Any]] = None):
+        self._config = config or {}
+        self._headless: Optional[bool] = None
+        self._screenshot_dir: Optional[str] = None
+
+        # Background thread state
+        self._thread: Optional[threading.Thread] = None
+        self._task_queue: queue.Queue = queue.Queue()
+        self._lock = threading.Lock()
+        self._alive = False
+        self._ready = threading.Event()
+
+        # Playwright objects (only accessed on the background thread)
+        self._playwright = None
+        self._browser = None
+        self._context = None
+        self._page = None
+
+        # Launch mode: one of "fresh" | "persistent" | "cdp".
+        # - cdp: connect to an externally launched Chrome via CDP endpoint.
+        # - persistent: launch with launch_persistent_context using a user_data_dir
+        #   so cookies / login state survive across runs (default).
+        # - fresh: classic launch + new_context, clean state every run.
+        cdp_endpoint = self._config.get("cdp_endpoint") or ""
+        persistent_flag = self._config.get("persistent", True)
+        user_data_dir_cfg = self._config.get("user_data_dir")
+        if user_data_dir_cfg is None:
+            user_data_dir_cfg = _DEFAULT_USER_DATA_DIR
+
+        self._cdp_endpoint: str = cdp_endpoint.strip() if isinstance(cdp_endpoint, str) else ""
+        if self._cdp_endpoint:
+            self._launch_mode = "cdp"
+            self._user_data_dir: str = ""
+        elif persistent_flag and user_data_dir_cfg:
+            self._launch_mode = "persistent"
+            self._user_data_dir = expand_path(str(user_data_dir_cfg))
+        else:
+            self._launch_mode = "fresh"
+            self._user_data_dir = ""
+
+        # Idle auto-release
+        idle_cfg = self._config.get("idle_timeout")
+        self._idle_timeout: float = float(idle_cfg) if idle_cfg is not None else self._IDLE_TIMEOUT_DEFAULT
+        self._idle_timer: Optional[threading.Timer] = None
+
+        # Set when the browser / page is detected to have died externally
+        # (e.g. user manually closed the window). The next _submit() will then
+        # tear down the stale thread and relaunch.
+        self._needs_restart = False
+
+    # ------------------------------------------------------------------
+    # Background-thread lifecycle
+    # ------------------------------------------------------------------
+
+    def _start_thread(self):
+        """Start the dedicated Playwright thread if not already running."""
+        with self._lock:
+            if self._alive and self._thread and self._thread.is_alive():
+                return
+            # Wait for old thread to fully exit before creating a new one
+            old = self._thread
+            if old and old.is_alive():
+                old.join(timeout=5)
+            # Fresh queue to avoid stale sentinels from a previous close()
+            self._task_queue = queue.Queue()
+            self._alive = True
+            self._ready = threading.Event()
+            self._thread = threading.Thread(target=self._run_loop, daemon=True, name="BrowserThread")
+            self._thread.start()
+            # Block until browser is ready (or failed)
+            self._ready.wait(timeout=30)
+
+    def _run_loop(self):
+        """Event loop running on the dedicated thread. Processes tasks until stopped."""
+        logger.info("[Browser] Background thread started")
+        try:
+            self._launch_browser()
+        except Exception as e:
+            logger.error(f"[Browser] Failed to launch browser: {e}")
+            self._alive = False
+            self._ready.set()
+            self._drain_queue(RuntimeError(f"Browser launch failed: {e}"))
+            return
+        self._ready.set()
+
+        while self._alive:
+            try:
+                task = self._task_queue.get(timeout=1.0)
+            except queue.Empty:
+                continue
+            if task is None:
+                break
+            fn, args, kwargs, result_slot = task
+            try:
+                result_slot["value"] = fn(*args, **kwargs)
+            except Exception as e:
+                result_slot["error"] = e
+                if _is_browser_dead_error(e):
+                    self._needs_restart = True
+                    logger.warning(
+                        f"[Browser] Detected closed page/context ({e}); "
+                        "will relaunch on next request."
+                    )
+            finally:
+                result_slot["event"].set()
+
+        self._shutdown_browser()
+        self._drain_queue(RuntimeError("Browser thread stopped"))
+        logger.info("[Browser] Background thread exited")
+
+    def _drain_queue(self, error: Exception):
+        """Unblock all callers waiting on the queue with an error."""
+        while True:
+            try:
+                task = self._task_queue.get_nowait()
+            except queue.Empty:
+                break
+            if task is None:
+                continue
+            _, _, _, result_slot = task
+            result_slot["error"] = error
+            result_slot["event"].set()
+
+    def _launch_browser(self):
+        """Launch / connect Chromium on the background thread."""
+        if self._headless is None:
+            headless_cfg = self._config.get("headless")
+            self._headless = headless_cfg if headless_cfg is not None else _should_use_headless()
+
+        launch_args = ["--disable-dev-shm-usage"]
+        if self._headless:
+            launch_args.append("--no-sandbox")
+
+        if is_cloud_deployment():
+            launch_args.extend([
+                "--disable-gpu",
+                "--disable-software-rasterizer",
+                "--disable-extensions",
+                "--disable-background-networking",
+                "--disable-background-timer-throttling",
+                "--disable-renderer-backgrounding",
+                "--disable-features=site-per-process,TranslateUI,IsolateOrigins",
+                "--no-zygote",
+                "--js-flags=--max-old-space-size=384",
+                "--memory-pressure-off",
+            ])
+
+        extra_args = self._config.get("launch_args", [])
+        if extra_args:
+            launch_args.extend(extra_args)
+
+        viewport_w = self._config.get("viewport_width", 1280)
+        viewport_h = self._config.get("viewport_height", 720)
+        viewport = {"width": viewport_w, "height": viewport_h}
+        user_agent = (
+            "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+            "AppleWebKit/537.36 (KHTML, like Gecko) "
+            "Chrome/131.0.0.0 Safari/537.36"
+        )
+
+        self._playwright = sync_playwright().start()
+
+        if self._launch_mode == "cdp":
+            self._connect_cdp(viewport)
+        elif self._launch_mode == "persistent":
+            self._launch_persistent(launch_args, viewport, user_agent)
+        else:
+            self._launch_fresh(launch_args, viewport, user_agent)
+
+        logger.info("[Browser] Browser ready")
+
+    def _launch_fresh(self, launch_args: List[str], viewport: Dict[str, int], user_agent: str):
+        """Classic launch: brand new Chromium with an empty context."""
+        logger.info(f"[Browser] Launching Chromium (fresh, headless={self._headless})")
+        self._browser = self._playwright.chromium.launch(
+            headless=self._headless,
+            args=launch_args,
+        )
+        self._context = self._browser.new_context(
+            viewport=viewport,
+            user_agent=user_agent,
+        )
+        self._page = self._context.new_page()
+        self._wire_close_listeners()
+
+    def _launch_persistent(self, launch_args: List[str], viewport: Dict[str, int], user_agent: str):
+        """Launch Chromium with a persistent user_data_dir so login state survives."""
+        os.makedirs(self._user_data_dir, exist_ok=True)
+        logger.info(
+            f"[Browser] Launching Chromium (persistent, headless={self._headless}, "
+            f"profile={self._user_data_dir})"
+        )
+        try:
+            self._context = self._playwright.chromium.launch_persistent_context(
+                user_data_dir=self._user_data_dir,
+                headless=self._headless,
+                args=launch_args,
+                viewport=viewport,
+                user_agent=user_agent,
+            )
+        except Exception as e:
+            # Profile is locked when another Chromium instance already holds it.
+            msg = str(e).lower()
+            if "singletonlock" in msg or "profile" in msg or "lock" in msg:
+                raise RuntimeError(
+                    f"Browser profile '{self._user_data_dir}' is in use by another process. "
+                    "Close the other Chromium / cow instance, or set a different "
+                    "tools.browser.user_data_dir."
+                ) from e
+            raise
+
+        # Persistent context has no parent Browser handle; reuse the auto-created page.
+        self._browser = None
+        pages = self._context.pages
+        self._page = pages[0] if pages else self._context.new_page()
+        self._wire_close_listeners()
+
+    def _connect_cdp(self, viewport: Dict[str, int]):
+        """Attach to an existing Chrome started with --remote-debugging-port."""
+        endpoint = self._cdp_endpoint
+        logger.info(f"[Browser] Connecting to existing Chrome via CDP: {endpoint}")
+        try:
+            self._browser = self._playwright.chromium.connect_over_cdp(endpoint)
+        except Exception as e:
+            msg = str(e).lower()
+            if "econnrefused" in msg or "connect" in msg or "refused" in msg:
+                raise RuntimeError(
+                    f"Cannot reach Chrome at {endpoint}. The CDP browser is not "
+                    "running. Ask the user to launch Chrome with "
+                    "--remote-debugging-port and --user-data-dir, then retry. "
+                    "Do not retry this tool until the user confirms."
+                ) from e
+            raise
+
+        contexts = self._browser.contexts
+        if contexts:
+            self._context = contexts[0]
+        else:
+            self._context = self._browser.new_context(viewport=viewport)
+
+        pages = self._context.pages
+        self._page = pages[0] if pages else self._context.new_page()
+        self._wire_close_listeners()
+
+    def _wire_close_listeners(self):
+        """Mark needs_restart whenever the browser / context / page dies externally."""
+        def _on_dead(_obj=None):
+            self._needs_restart = True
+
+        try:
+            if self._browser:
+                self._browser.on("disconnected", _on_dead)
+            if self._context:
+                self._context.on("close", _on_dead)
+            if self._page:
+                self._page.on("close", _on_dead)
+        except Exception as e:
+            logger.debug(f"[Browser] Failed to wire close listeners: {e}")
+
+    def _shutdown_browser(self):
+        """Shut down Playwright resources on the background thread.
+
+        Mode-specific behavior:
+        - cdp: only disconnect the Playwright client; leave the user's Chrome
+          and its tabs untouched (do NOT close the context).
+        - persistent: close the persistent context (no separate browser handle).
+        - fresh: close context, then browser.
+        """
+        self._cancel_idle_timer()
+
+        if self._launch_mode == "cdp":
+            # For CDP, browser.close() only detaches the Playwright client;
+            # the user's Chrome process and its tabs stay alive.
+            try:
+                if self._browser:
+                    self._browser.close()
+            except Exception as e:
+                logger.debug(f"[Browser] cdp disconnect error: {e}")
+        else:
+            for obj, label in [
+                (self._context, "context"),
+                (self._browser, "browser"),
+            ]:
+                try:
+                    if obj:
+                        obj.close()
+                except Exception as e:
+                    logger.debug(f"[Browser] {label} close error: {e}")
+
+        try:
+            if self._playwright:
+                self._playwright.stop()
+        except Exception as e:
+            logger.debug(f"[Browser] playwright stop error: {e}")
+        self._page = None
+        self._context = None
+        self._browser = None
+        self._playwright = None
+        logger.info("[Browser] Browser closed")
+
+    def _submit(self, fn: Callable, *args, **kwargs):
+        """Submit *fn* to the background thread and block until it completes."""
+        # If the browser died externally (e.g. user closed the window), tear
+        # down the stale thread first so _start_thread() will relaunch fresh.
+        if self._needs_restart:
+            logger.info("[Browser] Restarting after detecting closed browser")
+            self.close()
+            self._needs_restart = False
+
+        self._start_thread()
+
+        if not self._alive:
+            raise RuntimeError("Browser is not available")
+
+        self._reset_idle_timer()
+
+        result_slot: Dict[str, Any] = {"event": threading.Event()}
+        self._task_queue.put((fn, args, kwargs, result_slot))
+
+        # Timeout prevents permanent hang if the background thread crashes
+        completed = result_slot["event"].wait(timeout=120)
+        if not completed:
+            raise TimeoutError("Browser operation timed out (120s)")
+
+        if "error" in result_slot:
+            raise result_slot["error"]
+        return result_slot.get("value")
+
+    # ------------------------------------------------------------------
+    # Idle auto-release
+    # ------------------------------------------------------------------
+
+    def _reset_idle_timer(self):
+        self._cancel_idle_timer()
+        if self._idle_timeout > 0:
+            self._idle_timer = threading.Timer(self._idle_timeout, self._on_idle_timeout)
+            self._idle_timer.daemon = True
+            self._idle_timer.start()
+
+    def _cancel_idle_timer(self):
+        if self._idle_timer:
+            self._idle_timer.cancel()
+            self._idle_timer = None
+
+    def _on_idle_timeout(self):
+        logger.info(f"[Browser] Idle for {self._idle_timeout}s, auto-releasing browser")
+        self.close()
+
+    # ------------------------------------------------------------------
+    # Public lifecycle
+    # ------------------------------------------------------------------
+
+    def close(self):
+        """Shut down browser and background thread (safe from any thread)."""
+        self._cancel_idle_timer()
+        with self._lock:
+            if not self._alive:
+                self._needs_restart = False
+                return
+            self._alive = False
+            t = self._thread
+        if self._task_queue is not None:
+            self._task_queue.put(None)
+        if t is not None and t.is_alive():
+            t.join(timeout=10)
+        with self._lock:
+            self._thread = None
+            self._needs_restart = False
+
+    # ------------------------------------------------------------------
+    # Actions  (each method is dispatched to the background thread)
+    # ------------------------------------------------------------------
+
+    def navigate(self, url: str, timeout: int = 30000) -> Dict[str, Any]:
+        return self._submit(self._do_navigate, url, timeout)
+
+    def _do_navigate(self, url: str, timeout: int) -> Dict[str, Any]:
+        page = self._page
+        try:
+            resp = page.goto(url, wait_until="domcontentloaded", timeout=timeout)
+            status = resp.status if resp else None
+        except Exception as e:
+            return {"error": f"Navigation failed: {e}"}
+
+        try:
+            page.wait_for_load_state("networkidle", timeout=8000)
+        except Exception:
+            pass
+        page.wait_for_timeout(500)
+
+        try:
+            title = page.title()
+        except Exception:
+            title = ""
+        try:
+            current_url = page.url
+        except Exception:
+            current_url = url
+
+        return {"url": current_url, "title": title, "status": status}
+
+    def snapshot(self, selector: Optional[str] = None) -> str:
+        return self._submit(self._do_snapshot, selector)
+
+    def _do_snapshot(self, selector: Optional[str] = None) -> str:
+        page = self._page
+        try:
+            result = page.evaluate(_SNAPSHOT_JS)
+        except Exception as e:
+            return f"[Snapshot error: {e}]"
+
+        tree = result.get("tree")
+        ref_count = result.get("refCount", 0)
+        lines = _flatten_tree(tree)
+
+        try:
+            title = page.title()
+        except Exception:
+            title = ""
+        try:
+            url = page.url
+        except Exception:
+            url = ""
+
+        header = f"Page: {title}  ({url})\nInteractive elements: {ref_count}\n---"
+        body = "\n".join(lines)
+
+        max_chars = self._config.get("snapshot_max_chars", 30000)
+        if len(body) > max_chars:
+            body = body[:max_chars] + "\n... [snapshot truncated]"
+
+        return f"{header}\n{body}"
+
+    def screenshot(self, full_page: bool = False, cwd: str = "") -> str:
+        return self._submit(self._do_screenshot, full_page, cwd)
+
+    def _do_screenshot(self, full_page: bool = False, cwd: str = "") -> str:
+        page = self._page
+        save_dir = self._get_screenshot_dir(cwd)
+        filename = f"screenshot_{uuid.uuid4().hex[:8]}.png"
+        filepath = os.path.join(save_dir, filename)
+        page.screenshot(path=filepath, full_page=full_page)
+        logger.info(f"[Browser] Screenshot saved: {filepath}")
+        return filepath
+
+    def click(self, ref: Optional[int] = None, selector: Optional[str] = None,
+              timeout: int = 5000) -> Dict[str, Any]:
+        return self._submit(self._do_click, ref, selector, timeout)
+
+    def _do_click(self, ref, selector, timeout) -> Dict[str, Any]:
+        page = self._page
+        try:
+            if ref is not None:
+                result = page.evaluate(f"""
+                    () => {{
+                        const el = window.__cowRefMap && window.__cowRefMap[{ref}];
+                        if (!el) return {{ error: "ref {ref} not found. Run snapshot first." }};
+                        el.click();
+                        return {{ clicked: true, tag: el.tagName.toLowerCase() }};
+                    }}
+                """)
+                if result.get("error"):
+                    return result
+                page.wait_for_timeout(500)
+                return result
+            elif selector:
+                page.click(selector, timeout=timeout)
+                return {"clicked": True, "selector": selector}
+            else:
+                return {"error": "Provide either ref (from snapshot) or selector"}
+        except Exception as e:
+            return {"error": f"Click failed: {e}"}
+
+    def fill(self, text: str, ref: Optional[int] = None,
+             selector: Optional[str] = None, timeout: int = 5000) -> Dict[str, Any]:
+        return self._submit(self._do_fill, text, ref, selector, timeout)
+
+    def _do_fill(self, text, ref, selector, timeout) -> Dict[str, Any]:
+        page = self._page
+        try:
+            if ref is not None:
+                result = page.evaluate(f"""
+                    () => {{
+                        const el = window.__cowRefMap && window.__cowRefMap[{ref}];
+                        if (!el) return {{ error: "ref {ref} not found. Run snapshot first." }};
+                        el.focus();
+                        el.value = "";
+                        return {{ tag: el.tagName.toLowerCase(), name: el.name || "" }};
+                    }}
+                """)
+                if result.get("error"):
+                    return result
+                page.keyboard.type(text)
+                return {"filled": True, "ref": ref, "text": text}
+            elif selector:
+                page.fill(selector, text, timeout=timeout)
+                return {"filled": True, "selector": selector, "text": text}
+            else:
+                return {"error": "Provide either ref (from snapshot) or selector"}
+        except Exception as e:
+            return {"error": f"Fill failed: {e}"}
+
+    def select(self, value: str, ref: Optional[int] = None,
+               selector: Optional[str] = None, timeout: int = 5000) -> Dict[str, Any]:
+        return self._submit(self._do_select, value, ref, selector, timeout)
+
+    def _do_select(self, value, ref, selector, timeout) -> Dict[str, Any]:
+        page = self._page
+        try:
+            if ref is not None:
+                result = page.evaluate(f"""
+                    () => {{
+                        const el = window.__cowRefMap && window.__cowRefMap[{ref}];
+                        if (!el || el.tagName.toLowerCase() !== "select")
+                            return {{ error: "ref {ref} is not a <select> element" }};
+                        el.value = {repr(value)};
+                        el.dispatchEvent(new Event("change", {{ bubbles: true }}));
+                        return {{ selected: true, value: el.value }};
+                    }}
+                """)
+                return result
+            elif selector:
+                page.select_option(selector, value, timeout=timeout)
+                return {"selected": True, "selector": selector, "value": value}
+            else:
+                return {"error": "Provide either ref (from snapshot) or selector"}
+        except Exception as e:
+            return {"error": f"Select failed: {e}"}
+
+    def scroll(self, direction: str = "down", amount: int = 500) -> Dict[str, Any]:
+        return self._submit(self._do_scroll, direction, amount)
+
+    def _do_scroll(self, direction, amount) -> Dict[str, Any]:
+        page = self._page
+        delta_map = {
+            "down": (0, amount),
+            "up": (0, -amount),
+            "right": (amount, 0),
+            "left": (-amount, 0),
+        }
+        dx, dy = delta_map.get(direction, (0, amount))
+        try:
+            page.mouse.wheel(dx, dy)
+            page.wait_for_timeout(300)
+            scroll_info = page.evaluate("""
+                () => ({
+                    scrollX: window.scrollX,
+                    scrollY: window.scrollY,
+                    scrollHeight: document.documentElement.scrollHeight,
+                    clientHeight: document.documentElement.clientHeight
+                })
+            """)
+            return {"scrolled": direction, "amount": amount, **scroll_info}
+        except Exception as e:
+            return {"error": f"Scroll failed: {e}"}
+
+    def wait(self, selector: Optional[str] = None, timeout: int = 5000,
+             state: str = "visible") -> Dict[str, Any]:
+        return self._submit(self._do_wait, selector, timeout, state)
+
+    def _do_wait(self, selector, timeout, state) -> Dict[str, Any]:
+        page = self._page
+        try:
+            if selector:
+                page.wait_for_selector(selector, timeout=timeout, state=state)
+                return {"waited": True, "selector": selector, "state": state}
+            else:
+                page.wait_for_timeout(timeout)
+                return {"waited": True, "timeout_ms": timeout}
+        except Exception as e:
+            return {"error": f"Wait failed: {e}"}
+
+    def go_back(self) -> Dict[str, Any]:
+        return self._submit(self._do_go_back)
+
+    def _do_go_back(self) -> Dict[str, Any]:
+        page = self._page
+        try:
+            page.go_back(wait_until="domcontentloaded", timeout=10000)
+            try:
+                title = page.title()
+            except Exception:
+                title = ""
+            try:
+                url = page.url
+            except Exception:
+                url = ""
+            return {"url": url, "title": title}
+        except Exception as e:
+            return {"error": f"Go back failed: {e}"}
+
+    def go_forward(self) -> Dict[str, Any]:
+        return self._submit(self._do_go_forward)
+
+    def _do_go_forward(self) -> Dict[str, Any]:
+        page = self._page
+        try:
+            page.go_forward(wait_until="domcontentloaded", timeout=10000)
+            try:
+                title = page.title()
+            except Exception:
+                title = ""
+            try:
+                url = page.url
+            except Exception:
+                url = ""
+            return {"url": url, "title": title}
+        except Exception as e:
+            return {"error": f"Go forward failed: {e}"}
+
+    def get_text(self, selector: str) -> Dict[str, Any]:
+        return self._submit(self._do_get_text, selector)
+
+    def _do_get_text(self, selector) -> Dict[str, Any]:
+        page = self._page
+        try:
+            text = page.text_content(selector, timeout=5000)
+            return {"text": text or ""}
+        except Exception as e:
+            return {"error": f"Get text failed: {e}"}
+
+    def evaluate(self, script: str) -> Dict[str, Any]:
+        return self._submit(self._do_evaluate, script)
+
+    def _do_evaluate(self, script) -> Dict[str, Any]:
+        page = self._page
+        try:
+            result = page.evaluate(script)
+            return {"result": result}
+        except Exception as e:
+            return {"error": f"Evaluate failed: {e}"}
+
+    def press(self, key: str) -> Dict[str, Any]:
+        return self._submit(self._do_press, key)
+
+    def _do_press(self, key) -> Dict[str, Any]:
+        page = self._page
+        try:
+            page.keyboard.press(key)
+            page.wait_for_timeout(300)
+            return {"pressed": key}
+        except Exception as e:
+            return {"error": f"Press failed: {e}"}
+
+    # ------------------------------------------------------------------
+    # Helpers
+    # ------------------------------------------------------------------
+
+    def _get_screenshot_dir(self, cwd: str = "") -> str:
+        if self._screenshot_dir and os.path.isdir(self._screenshot_dir):
+            return self._screenshot_dir
+        base = cwd or os.getcwd()
+        d = os.path.join(base, "tmp")
+        os.makedirs(d, exist_ok=True)
+        self._screenshot_dir = d
+        return d
diff --git a/agent/tools/browser/browser_tool.py b/agent/tools/browser/browser_tool.py
new file mode 100644
index 0000000..9930a1a
--- /dev/null
+++ b/agent/tools/browser/browser_tool.py
@@ -0,0 +1,377 @@
+"""
+Browser tool - Control a Chromium browser for web navigation and interaction.
+
+Uses Playwright under the hood. Browser instance is lazily started on first
+use, reused across tool calls within the same session, and cleaned up via
+close().
+
+Launch modes (configured under `tools.browser` in config.json):
+  - persistent (default): Chromium runs with a persistent user_data_dir
+    (default `~/.cow/browser_profile`), so cookies and login state survive
+    across runs. The user only needs to log in once.
+  - cdp: When `cdp_endpoint` is set, attach to an externally launched Chrome
+    via the Chrome DevTools Protocol. Lets the agent reuse the user's real
+    browser (with all logins / extensions / true fingerprints).
+  - fresh: Set `persistent` to false to fall back to a clean context every run.
+"""
+
+import ipaddress
+import json
+import os
+import socket
+from typing import Dict, Any, Optional
+from urllib.parse import urlparse
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.browser.browser_service import BrowserService
+from common.log import logger
+
+
+# Cloud-metadata endpoints worth blocking even though they are not link-local.
+# (169.254.169.254 — AWS/GCP/Azure IMDS — is already covered by is_link_local;
+# fd00:ec2::254 is the AWS IPv6 IMDS address.)
+_CLOUD_METADATA_IPS = frozenset({ipaddress.ip_address("fd00:ec2::254")})
+
+
+class BrowserTool(BaseTool):
+    """Single tool exposing all browser actions via an 'action' parameter."""
+
+    name: str = "browser"
+    description: str = (
+        "Control a browser to navigate web pages, interact with elements, and extract content. "
+        "Actions: navigate, snapshot, click, fill, select, scroll, screenshot, wait, back, forward, "
+        "get_text, press, evaluate.\n\n"
+        "Workflow: navigate (auto-includes snapshot with element refs) → click/fill/select by ref → snapshot to verify.\n\n"
+        "Use snapshot as the primary way to read pages. Use screenshot + send to show key results to the user. "
+        "For login/CAPTCHA/authorization etc., screenshot and ask the user for help. "
+        "Login state is persisted across sessions (cookies / localStorage are kept in a "
+        "user profile directory), so once the user logs in to a site, the agent can keep "
+        "using it without logging in again."
+    )
+
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "description": (
+                    "The browser action to perform. One of: "
+                    "navigate, snapshot, click, fill, select, scroll, "
+                    "screenshot, wait, back, forward, get_text, press, evaluate"
+                ),
+                "enum": [
+                    "navigate", "snapshot", "click", "fill", "select", "scroll",
+                    "screenshot", "wait", "back", "forward", "get_text", "press",
+                    "evaluate"
+                ]
+            },
+            "url": {
+                "type": "string",
+                "description": "URL to navigate to (for 'navigate' action)"
+            },
+            "ref": {
+                "type": "integer",
+                "description": "Element ref number from snapshot (for click/fill/select)"
+            },
+            "selector": {
+                "type": "string",
+                "description": "CSS selector as fallback when ref is unavailable (for click/fill/select/wait/get_text)"
+            },
+            "text": {
+                "type": "string",
+                "description": "Text to type (for 'fill' action)"
+            },
+            "value": {
+                "type": "string",
+                "description": "Option value (for 'select' action)"
+            },
+            "key": {
+                "type": "string",
+                "description": "Key to press, e.g. Enter, Tab, Escape (for 'press' action)"
+            },
+            "direction": {
+                "type": "string",
+                "description": "Scroll direction: up, down, left, right (for 'scroll' action, default: down)"
+            },
+            "script": {
+                "type": "string",
+                "description": "JavaScript code to execute (for 'evaluate' action)"
+            },
+            "full_page": {
+                "type": "boolean",
+                "description": "Capture full page screenshot (for 'screenshot' action, default: false)"
+            },
+            "timeout": {
+                "type": "integer",
+                "description": "Timeout in milliseconds (optional, default varies by action)"
+            }
+        },
+        "required": ["action"]
+    }
+
+    _shared_service: Optional[BrowserService] = None
+
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        self._service: Optional[BrowserService] = None
+
+    def _get_service(self) -> BrowserService:
+        """Get or create the browser service, sharing across copies."""
+        if self._service is not None:
+            return self._service
+
+        # Reuse shared service across tool copies within the same session
+        if BrowserTool._shared_service is not None:
+            self._service = BrowserTool._shared_service
+            return self._service
+
+        self._service = BrowserService(self.config)
+        BrowserTool._shared_service = self._service
+        return self._service
+
+    def _allow_private_targets(self) -> bool:
+        """Whether the link-local / cloud-metadata guard is disabled.
+
+        Defaults to False (guard active). Loopback and RFC1918/LAN targets are
+        always reachable so local dev servers work out of the box; this opt-out
+        only lifts the remaining block on link-local / cloud-metadata targets,
+        for an operator who deliberately needs them, by setting
+        ``allow_private_targets: true`` under ``tools.browser`` in config.json.
+        """
+        return bool(self.config.get("allow_private_targets", False))
+
+    @staticmethod
+    def _validate_url_safe(url: str) -> None:
+        """Reject URLs that target link-local / cloud-metadata addresses (SSRF guard).
+
+        Resolves the hostname to its IP address(es) and blocks any that are
+        link-local (169.254.0.0/16 — which includes the 169.254.169.254
+        cloud-metadata endpoint — and IPv6 fe80::/10) or a known IPv6
+        cloud-metadata address. Also rejects URLs with no host, non-HTTP(S)
+        schemes, or hosts that fail DNS resolution.
+
+        Loopback and RFC1918/LAN targets are intentionally left reachable:
+        unlike the vision/web_fetch tools, the browser legitimately opens local
+        pages (a dev server on ``localhost`` / ``127.0.0.1`` / a LAN IP), so a
+        blanket "block all internal" policy would break that core workflow.
+
+        Raises:
+            ValueError: if the URL targets a disallowed address.
+        """
+        parsed = urlparse(url)
+        if parsed.scheme not in ("http", "https"):
+            raise ValueError(f"Unsupported URL scheme: {parsed.scheme}")
+
+        hostname = parsed.hostname
+        if not hostname:
+            raise ValueError("URL has no hostname")
+
+        try:
+            # Resolve all addresses for the hostname.
+            addr_infos = socket.getaddrinfo(hostname, None, socket.AF_UNSPEC, socket.SOCK_STREAM)
+        except socket.gaierror:
+            raise ValueError(f"Cannot resolve hostname: {hostname}")
+
+        for family, _, _, _, sockaddr in addr_infos:
+            ip_str = sockaddr[0]
+            ip = ipaddress.ip_address(ip_str)
+            # Block only the high-risk targets — link-local (incl. the
+            # 169.254.169.254 cloud-metadata endpoint) and the IPv6 metadata
+            # address. Loopback and RFC1918/LAN stay reachable for local dev.
+            if ip.is_link_local or ip in _CLOUD_METADATA_IPS:
+                raise ValueError(
+                    f"URL resolves to a link-local / cloud-metadata address "
+                    f"({ip_str}), request blocked for security"
+                )
+
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        action = args.get("action", "").strip().lower()
+        if not action:
+            return ToolResult.fail("Error: 'action' parameter is required")
+
+        handler = self._ACTION_MAP.get(action)
+        if not handler:
+            valid = ", ".join(sorted(self._ACTION_MAP.keys()))
+            return ToolResult.fail(f"Unknown action '{action}'. Valid actions: {valid}")
+
+        try:
+            return handler(self, args)
+        except Exception as e:
+            logger.error(f"[Browser] Action '{action}' error: {e}")
+            return ToolResult.fail(f"Browser error ({action}): {e}")
+
+    # ------------------------------------------------------------------
+    # Action handlers
+    # ------------------------------------------------------------------
+
+    def _do_navigate(self, args: Dict[str, Any]) -> ToolResult:
+        url = args.get("url", "").strip()
+        if not url:
+            return ToolResult.fail("Error: 'url' is required for navigate action")
+        # Only auto-prepend https:// for bare hosts; preserve file://, about:, data:, etc.
+        if "://" not in url and not url.startswith(("about:", "data:")):
+            url = "https://" + url
+        # SSRF guard: for http(s) targets, reject hosts that resolve to
+        # link-local / cloud-metadata addresses before the browser navigates
+        # (and then auto-snapshots the page back to the model). Loopback and
+        # RFC1918/LAN are allowed so local dev servers work. Non-HTTP schemes
+        # (about:/data:/file:/chrome:) are not network-egress targets here.
+        if url.split(":", 1)[0].lower() in ("http", "https") and not self._allow_private_targets():
+            try:
+                self._validate_url_safe(url)
+            except ValueError as e:
+                return ToolResult.fail(f"Error: {e}")
+        timeout = args.get("timeout", 30000)
+        service = self._get_service()
+        result = service.navigate(url, timeout=timeout)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        # Auto-snapshot after navigation so the agent gets page content in one call
+        snapshot_text = service.snapshot()
+        return ToolResult.success(
+            f"Navigated to: {result['url']}\nTitle: {result['title']}\nStatus: {result['status']}\n\n"
+            f"--- Page Snapshot ---\n{snapshot_text}"
+        )
+
+    def _do_snapshot(self, args: Dict[str, Any]) -> ToolResult:
+        selector = args.get("selector")
+        text = self._get_service().snapshot(selector=selector)
+        return ToolResult.success(text)
+
+    def _do_click(self, args: Dict[str, Any]) -> ToolResult:
+        ref = args.get("ref")
+        selector = args.get("selector")
+        timeout = args.get("timeout", 5000)
+        result = self._get_service().click(ref=ref, selector=selector, timeout=timeout)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Clicked successfully. Use 'snapshot' to see updated page.")
+
+    def _do_fill(self, args: Dict[str, Any]) -> ToolResult:
+        text = args.get("text", "")
+        ref = args.get("ref")
+        selector = args.get("selector")
+        timeout = args.get("timeout", 5000)
+        if not text and text != "":
+            return ToolResult.fail("Error: 'text' is required for fill action")
+        result = self._get_service().fill(text, ref=ref, selector=selector, timeout=timeout)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Filled text into element. Use 'snapshot' to verify.")
+
+    def _do_select(self, args: Dict[str, Any]) -> ToolResult:
+        value = args.get("value", "")
+        ref = args.get("ref")
+        selector = args.get("selector")
+        timeout = args.get("timeout", 5000)
+        if not value:
+            return ToolResult.fail("Error: 'value' is required for select action")
+        result = self._get_service().select(value, ref=ref, selector=selector, timeout=timeout)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Selected option '{value}'.")
+
+    def _do_scroll(self, args: Dict[str, Any]) -> ToolResult:
+        direction = args.get("direction", "down")
+        amount = args.get("timeout", 500)  # reuse timeout field or default
+        if "amount" in args:
+            amount = args["amount"]
+        result = self._get_service().scroll(direction=direction, amount=amount)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        pos = f"scrollY={result.get('scrollY', '?')}/{result.get('scrollHeight', '?')}"
+        return ToolResult.success(f"Scrolled {direction}. Position: {pos}")
+
+    def _do_screenshot(self, args: Dict[str, Any]) -> ToolResult:
+        full_page = args.get("full_page", False)
+        filepath = self._get_service().screenshot(full_page=full_page, cwd=self.cwd)
+        return ToolResult.success(f"Screenshot saved to: {filepath}")
+
+    def _do_wait(self, args: Dict[str, Any]) -> ToolResult:
+        selector = args.get("selector")
+        timeout = args.get("timeout", 5000)
+        result = self._get_service().wait(selector=selector, timeout=timeout)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Wait completed.")
+
+    def _do_back(self, args: Dict[str, Any]) -> ToolResult:
+        result = self._get_service().go_back()
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Navigated back to: {result['url']}")
+
+    def _do_forward(self, args: Dict[str, Any]) -> ToolResult:
+        result = self._get_service().go_forward()
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Navigated forward to: {result['url']}")
+
+    def _do_get_text(self, args: Dict[str, Any]) -> ToolResult:
+        selector = args.get("selector", "").strip()
+        if not selector:
+            return ToolResult.fail("Error: 'selector' is required for get_text action")
+        result = self._get_service().get_text(selector)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(result["text"])
+
+    def _do_press(self, args: Dict[str, Any]) -> ToolResult:
+        key = args.get("key", "").strip()
+        if not key:
+            return ToolResult.fail("Error: 'key' is required for press action")
+        result = self._get_service().press(key)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        return ToolResult.success(f"Pressed key: {key}")
+
+    def _do_evaluate(self, args: Dict[str, Any]) -> ToolResult:
+        script = args.get("script", "").strip()
+        if not script:
+            return ToolResult.fail("Error: 'script' is required for evaluate action")
+        result = self._get_service().evaluate(script)
+        if "error" in result:
+            return ToolResult.fail(result["error"])
+        val = result.get("result")
+        if isinstance(val, (dict, list)):
+            return ToolResult.success(json.dumps(val, ensure_ascii=False, indent=2))
+        return ToolResult.success(str(val) if val is not None else "(no return value)")
+
+    # Action dispatch table
+    _ACTION_MAP = {
+        "navigate": _do_navigate,
+        "snapshot": _do_snapshot,
+        "click": _do_click,
+        "fill": _do_fill,
+        "select": _do_select,
+        "scroll": _do_scroll,
+        "screenshot": _do_screenshot,
+        "wait": _do_wait,
+        "back": _do_back,
+        "forward": _do_forward,
+        "get_text": _do_get_text,
+        "press": _do_press,
+        "evaluate": _do_evaluate,
+    }
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def copy(self):
+        """Share browser instance across tool copies (avoids re-launching)."""
+        new_tool = BrowserTool(self.config)
+        new_tool.model = self.model
+        new_tool.context = getattr(self, "context", None)
+        new_tool.cwd = self.cwd
+        new_tool._service = self._service
+        return new_tool
+
+    def close(self):
+        """Release browser resources."""
+        if self._service:
+            self._service.close()
+            self._service = None
+        BrowserTool._shared_service = None
+        logger.info("[Browser] BrowserTool closed")
diff --git a/agent/tools/edit/__init__.py b/agent/tools/edit/__init__.py
new file mode 100644
index 0000000..68b84bb
--- /dev/null
+++ b/agent/tools/edit/__init__.py
@@ -0,0 +1,3 @@
+from .edit import Edit
+
+__all__ = ['Edit']
diff --git a/agent/tools/edit/edit.py b/agent/tools/edit/edit.py
new file mode 100644
index 0000000..5671b79
--- /dev/null
+++ b/agent/tools/edit/edit.py
@@ -0,0 +1,185 @@
+"""
+Edit tool - Precise file editing
+Edit files through exact text replacement
+"""
+
+import os
+from typing import Dict, Any
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.utils import expand_path
+from agent.tools.utils.diff import (
+    strip_bom,
+    detect_line_ending,
+    normalize_to_lf,
+    restore_line_endings,
+    count_matches,
+    fuzzy_find_text,
+    generate_diff_string
+)
+
+
+class Edit(BaseTool):
+    """Tool for precise file editing"""
+    
+    name: str = "edit"
+    description: str = "Edit a file by replacing exact text, or append to end if oldText is empty. For append: use empty oldText. For replace: oldText must match exactly (including whitespace)."
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Path to the file to edit (relative or absolute)"
+            },
+            "oldText": {
+                "type": "string",
+                "description": "Text to find and replace. Use empty string to append to end of file. For replacement: must match exactly including whitespace."
+            },
+            "newText": {
+                "type": "string",
+                "description": "New text to replace the old text with"
+            }
+        },
+        "required": ["path", "oldText", "newText"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        self.memory_manager = self.config.get("memory_manager", None)
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute file edit operation
+        
+        :param args: Contains file path, old text and new text
+        :return: Operation result
+        """
+        path = args.get("path", "").strip()
+        old_text = args.get("oldText", "")
+        new_text = args.get("newText", "")
+        
+        if not path:
+            return ToolResult.fail("Error: path parameter is required")
+        
+        # Resolve path
+        absolute_path = self._resolve_path(path)
+        
+        # Check if file exists
+        if not os.path.exists(absolute_path):
+            return ToolResult.fail(f"Error: File not found: {path}")
+        
+        # Check if readable/writable
+        if not os.access(absolute_path, os.R_OK | os.W_OK):
+            return ToolResult.fail(f"Error: File is not readable/writable: {path}")
+        
+        try:
+            # Read file
+            with open(absolute_path, 'r', encoding='utf-8') as f:
+                raw_content = f.read()
+            
+            # Remove BOM (LLM won't include invisible BOM in oldText)
+            bom, content = strip_bom(raw_content)
+            
+            # Detect original line ending
+            original_ending = detect_line_ending(content)
+            
+            # Normalize to LF
+            normalized_content = normalize_to_lf(content)
+            normalized_old_text = normalize_to_lf(old_text)
+            normalized_new_text = normalize_to_lf(new_text)
+            
+            # Special case: empty oldText means append to end of file
+            if not old_text or not old_text.strip():
+                # Append mode: add newText to the end
+                # Add newline before newText if file doesn't end with one
+                if normalized_content and not normalized_content.endswith('\n'):
+                    new_content = normalized_content + '\n' + normalized_new_text
+                else:
+                    new_content = normalized_content + normalized_new_text
+                base_content = normalized_content  # For verification
+            else:
+                # Normal edit mode: find and replace
+                # Use fuzzy matching to find old text (try exact match first, then fuzzy match)
+                match_result = fuzzy_find_text(normalized_content, normalized_old_text)
+                
+                if not match_result.found:
+                    return ToolResult.fail(
+                        f"Error: Could not find the exact text in {path}. "
+                        "The old text must match exactly including all whitespace and newlines."
+                    )
+                
+                # Count occurrences with the same matcher used to locate and
+                # replace (fuzzy_find_text), so the uniqueness guard cannot
+                # disagree with what actually gets replaced.
+                occurrences = count_matches(normalized_content, normalized_old_text)
+                
+                if occurrences > 1:
+                    return ToolResult.fail(
+                        f"Error: Found {occurrences} occurrences of the text in {path}. "
+                        "The text must be unique. Please provide more context to make it unique."
+                    )
+                
+                # Execute replacement (use matched text position)
+                base_content = match_result.content_for_replacement
+                new_content = (
+                    base_content[:match_result.index] +
+                    normalized_new_text +
+                    base_content[match_result.index + match_result.match_length:]
+                )
+            
+            # Verify replacement actually changed content
+            if base_content == new_content:
+                return ToolResult.fail(
+                    f"Error: No changes made to {path}. "
+                    "The replacement produced identical content. "
+                    "This might indicate an issue with special characters or the text not existing as expected."
+                )
+            
+            # Restore original line endings
+            final_content = bom + restore_line_endings(new_content, original_ending)
+            
+            # Write file
+            with open(absolute_path, 'w', encoding='utf-8') as f:
+                f.write(final_content)
+            
+            # Generate diff
+            diff_result = generate_diff_string(base_content, new_content)
+            
+            result = {
+                "message": f"Successfully replaced text in {path}",
+                "path": path,
+                "diff": diff_result['diff'],
+                "first_changed_line": diff_result['first_changed_line']
+            }
+            
+            # Notify memory manager if file is in memory directory
+            if self.memory_manager and "memory/" in path:
+                try:
+                    self.memory_manager.mark_dirty()
+                except Exception as e:
+                    # Don't fail the edit if memory notification fails
+                    pass
+            
+            return ToolResult.success(result)
+            
+        except UnicodeDecodeError:
+            return ToolResult.fail(f"Error: File is not a valid text file (encoding error): {path}")
+        except PermissionError:
+            return ToolResult.fail(f"Error: Permission denied accessing {path}")
+        except Exception as e:
+            return ToolResult.fail(f"Error editing file: {str(e)}")
+    
+    def _resolve_path(self, path: str) -> str:
+        """
+        Resolve path to absolute path
+        
+        :param path: Relative or absolute path
+        :return: Absolute path
+        """
+        # Expand ~ to user home directory
+        path = expand_path(path)
+        if os.path.isabs(path):
+            return path
+        return os.path.abspath(os.path.join(self.cwd, path))
diff --git a/agent/tools/env_config/__init__.py b/agent/tools/env_config/__init__.py
new file mode 100644
index 0000000..2e5822f
--- /dev/null
+++ b/agent/tools/env_config/__init__.py
@@ -0,0 +1,3 @@
+from agent.tools.env_config.env_config import EnvConfig
+
+__all__ = ['EnvConfig']
diff --git a/agent/tools/env_config/env_config.py b/agent/tools/env_config/env_config.py
new file mode 100644
index 0000000..b656ee2
--- /dev/null
+++ b/agent/tools/env_config/env_config.py
@@ -0,0 +1,286 @@
+"""
+Environment Configuration Tool - Manage API keys and environment variables
+"""
+
+import os
+import re
+from typing import Dict, Any
+from pathlib import Path
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.log import logger
+from common.utils import expand_path
+
+
+# API Key 知识库：常见的环境变量及其描述
+API_KEY_REGISTRY = {
+    # AI 模型服务
+    "OPENAI_API_KEY": "OpenAI API 密钥 (用于GPT模型、Embedding模型)",
+    "GEMINI_API_KEY": "Google Gemini API 密钥",
+    "CLAUDE_API_KEY": "Claude API 密钥 (用于Claude模型)",
+    "LINKAI_API_KEY": "LinkAI智能体平台 API 密钥，支持多种模型切换",
+    # 搜索服务
+    "BOCHA_API_KEY": "博查 AI 搜索 API 密钥 ",
+}
+
+class EnvConfig(BaseTool):
+    """Tool for managing environment variables (API keys, etc.)"""
+    
+    name: str = "env_config"
+    description: str = (
+        "Manage API keys and skill configurations securely. "
+        "Use this tool when user wants to configure API keys (like BOCHA_API_KEY, OPENAI_API_KEY), "
+        "view configured keys, or manage skill settings. "
+        "Actions: 'set' (add/update key), 'get' (view specific key), 'list' (show all configured keys), 'delete' (remove key). "
+        "Values are automatically masked for security. Changes take effect immediately via hot reload."
+    )
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "description": "Action to perform: 'set', 'get', 'list', 'delete'",
+                "enum": ["set", "get", "list", "delete"]
+            },
+            "key": {
+                "type": "string",
+                "description": (
+                    "Environment variable key name. Common keys:\n"
+                    "- OPENAI_API_KEY: OpenAI API (GPT models)\n"
+                    "- OPENAI_API_BASE: OpenAI API base URL\n"
+                    "- CLAUDE_API_KEY: Anthropic Claude API\n"
+                    "- GEMINI_API_KEY: Google Gemini API\n"
+                    "- LINKAI_API_KEY: LinkAI platform\n"
+                    "- BOCHA_API_KEY: Bocha AI search (博查搜索)\n"
+                    "Use exact key names (case-sensitive, all uppercase with underscores)"
+                )
+            },
+            "value": {
+                "type": "string",
+                "description": "Value to set for the environment variable (for 'set' action)"
+            }
+        },
+        "required": ["action"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        # Store env config in ~/.cow directory (outside workspace for security)
+        self.env_dir = expand_path("~/.cow")
+        self.env_path = os.path.join(self.env_dir, '.env')
+        self.agent_bridge = self.config.get("agent_bridge")  # Reference to AgentBridge for hot reload
+        # Don't create .env file in __init__ to avoid issues during tool discovery
+        # It will be created on first use in execute()
+    
+    def _ensure_env_file(self):
+        """Ensure the .env file exists"""
+        # Create ~/.cow directory if it doesn't exist
+        os.makedirs(self.env_dir, exist_ok=True)
+        
+        if not os.path.exists(self.env_path):
+            Path(self.env_path).touch()
+            logger.info(f"[EnvConfig] Created .env file at {self.env_path}")
+    
+    def _mask_value(self, value: str) -> str:
+        """Mask sensitive parts of a value for logging"""
+        if not value or len(value) <= 10:
+            return "***"
+        return f"{value[:6]}***{value[-4:]}"
+    
+    def _read_env_file(self) -> Dict[str, str]:
+        """Read all key-value pairs from .env file"""
+        env_vars = {}
+        if os.path.exists(self.env_path):
+            with open(self.env_path, 'r', encoding='utf-8') as f:
+                for line in f:
+                    line = line.strip()
+                    # Skip empty lines and comments
+                    if not line or line.startswith('#'):
+                        continue
+                    # Parse KEY=VALUE
+                    match = re.match(r'^([^=]+)=(.*)$', line)
+                    if match:
+                        key, value = match.groups()
+                        env_vars[key.strip()] = value.strip()
+        return env_vars
+    
+    def _write_env_file(self, env_vars: Dict[str, str]):
+        """Write all key-value pairs to .env file"""
+        with open(self.env_path, 'w', encoding='utf-8') as f:
+            f.write("# Environment variables for agent skills\n")
+            f.write("# Auto-managed by env_config tool\n\n")
+            for key, value in sorted(env_vars.items()):
+                f.write(f"{key}={value}\n")
+    
+    def _reload_env(self):
+        """Reload environment variables from .env file"""
+        env_vars = self._read_env_file()
+        for key, value in env_vars.items():
+            os.environ[key] = value
+        logger.debug(f"[EnvConfig] Reloaded {len(env_vars)} environment variables")
+    
+    def _refresh_skills(self):
+        """Refresh skills after environment variable changes"""
+        if self.agent_bridge:
+            try:
+                # Reload .env file
+                self._reload_env()
+                
+                # Refresh skills in all agent instances
+                refreshed = self.agent_bridge.refresh_all_skills()
+                logger.info(f"[EnvConfig] Refreshed skills in {refreshed} agent instance(s)")
+                return True
+            except Exception as e:
+                logger.warning(f"[EnvConfig] Failed to refresh skills: {e}")
+                return False
+        return False
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute environment configuration operation
+        
+        :param args: Contains action, key, and value parameters
+        :return: Result of the operation
+        """
+        # Ensure .env file exists on first use
+        self._ensure_env_file()
+        
+        action = args.get("action")
+        key = args.get("key")
+        value = args.get("value")
+        
+        try:
+            if action == "set":
+                if not key or not value:
+                    return ToolResult.fail("Error: 'key' and 'value' are required for 'set' action.")
+                
+                # Read current env vars
+                env_vars = self._read_env_file()
+                
+                # Update the key
+                env_vars[key] = value
+                
+                # Write back to file
+                self._write_env_file(env_vars)
+                
+                # Update current process env
+                os.environ[key] = value
+                
+                logger.info(f"[EnvConfig] Set {key}={self._mask_value(value)}")
+                
+                # Try to refresh skills immediately
+                refreshed = self._refresh_skills()
+                
+                result = {
+                    "message": f"Successfully set {key}",
+                    "key": key,
+                    "value": self._mask_value(value),
+                }
+                
+                if refreshed:
+                    result["note"] = "✅ Skills refreshed automatically - changes are now active"
+                else:
+                    result["note"] = "⚠️ Skills not refreshed - restart agent to load new skills"
+                
+                return ToolResult.success(result)
+            
+            elif action == "get":
+                if not key:
+                    return ToolResult.fail("Error: 'key' is required for 'get' action.")
+                
+                # Check in file first, then in current env
+                env_vars = self._read_env_file()
+                value = env_vars.get(key) or os.getenv(key)
+                
+                # Get description from registry
+                description = API_KEY_REGISTRY.get(key, "未知用途的环境变量")
+                
+                if value is not None:
+                    logger.info(f"[EnvConfig] Got {key}={self._mask_value(value)}")
+                    return ToolResult.success({
+                        "key": key,
+                        "value": self._mask_value(value),
+                        "description": description,
+                        "exists": True,
+                        "note": f"Value is masked for security. In bash, use ${key} directly — it is auto-injected."
+                    })
+                else:
+                    return ToolResult.success({
+                        "key": key,
+                        "description": description,
+                        "exists": False,
+                        "message": f"Environment variable '{key}' is not set"
+                    })
+            
+            elif action == "list":
+                env_vars = self._read_env_file()
+                
+                # Build detailed variable list with descriptions
+                variables_with_info = {}
+                for key, value in env_vars.items():
+                    variables_with_info[key] = {
+                        "value": self._mask_value(value),
+                        "description": API_KEY_REGISTRY.get(key, "未知用途的环境变量")
+                    }
+                
+                logger.info(f"[EnvConfig] Listed {len(env_vars)} environment variables")
+                
+                if not env_vars:
+                    return ToolResult.success({
+                        "message": "No environment variables configured",
+                        "variables": {},
+                        "note": "常用的 API 密钥可以通过 env_config(action='set', key='KEY_NAME', value='your-key') 来配置"
+                    })
+                
+                return ToolResult.success({
+                    "message": f"Found {len(env_vars)} environment variable(s)",
+                    "variables": variables_with_info
+                })
+            
+            elif action == "delete":
+                if not key:
+                    return ToolResult.fail("Error: 'key' is required for 'delete' action.")
+                
+                # Read current env vars
+                env_vars = self._read_env_file()
+                
+                if key not in env_vars:
+                    return ToolResult.success({
+                        "message": f"Environment variable '{key}' was not set",
+                        "key": key
+                    })
+                
+                # Remove the key
+                del env_vars[key]
+                
+                # Write back to file
+                self._write_env_file(env_vars)
+                
+                # Remove from current process env
+                if key in os.environ:
+                    del os.environ[key]
+                
+                logger.info(f"[EnvConfig] Deleted {key}")
+                
+                # Try to refresh skills immediately
+                refreshed = self._refresh_skills()
+                
+                result = {
+                    "message": f"Successfully deleted {key}",
+                    "key": key,
+                }
+                
+                if refreshed:
+                    result["note"] = "✅ Skills refreshed automatically - changes are now active"
+                else:
+                    result["note"] = "⚠️ Skills not refreshed - restart agent to apply changes"
+                
+                return ToolResult.success(result)
+            
+            else:
+                return ToolResult.fail(f"Error: Unknown action '{action}'. Use 'set', 'get', 'list', or 'delete'.")
+        
+        except Exception as e:
+            logger.error(f"[EnvConfig] Error: {e}", exc_info=True)
+            return ToolResult.fail(f"EnvConfig tool error: {str(e)}")
diff --git a/agent/tools/evolution_undo/__init__.py b/agent/tools/evolution_undo/__init__.py
new file mode 100644
index 0000000..a51a955
--- /dev/null
+++ b/agent/tools/evolution_undo/__init__.py
@@ -0,0 +1,3 @@
+from agent.tools.evolution_undo.evolution_undo import EvolutionUndoTool
+
+__all__ = ["EvolutionUndoTool"]
diff --git a/agent/tools/evolution_undo/evolution_undo.py b/agent/tools/evolution_undo/evolution_undo.py
new file mode 100644
index 0000000..abfbc28
--- /dev/null
+++ b/agent/tools/evolution_undo/evolution_undo.py
@@ -0,0 +1,58 @@
+"""Evolution undo tool.
+
+Lets the main chat agent roll back a previous self-evolution when the user asks
+("undo the last learning"). The rollback itself is a deterministic FILE RESTORE
+from the snapshot taken before the evolution — the model only supplies the
+backup_id it reads from the [EVOLUTION] record in the conversation. No LLM-driven
+re-editing is involved, so a restore can never make things worse.
+"""
+
+from agent.tools.base_tool import BaseTool, ToolResult
+
+
+class EvolutionUndoTool(BaseTool):
+    """Restore memory/skill files to the state before a self-evolution."""
+
+    name: str = "evolution_undo"
+    description: str = (
+        "Undo a previous self-evolution (self-learning) by restoring the "
+        "memory/skill files to their state before that learning. Use this when "
+        "the user asks to undo / revert / roll back the last self-learning. "
+        "Find the backup_id in the most recent [EVOLUTION] record in the "
+        "conversation and pass it here."
+    )
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "backup_id": {
+                "type": "string",
+                "description": (
+                    "The backup_id from the [EVOLUTION] record to restore "
+                    "(e.g. '20260607-155551-850')."
+                ),
+            }
+        },
+        "required": ["backup_id"],
+    }
+
+    def execute(self, args: dict):
+        backup_id = (args.get("backup_id") or "").strip()
+        if not backup_id:
+            return ToolResult.fail("Error: backup_id is required")
+        try:
+            from agent.memory.config import get_default_memory_config
+            from agent.evolution.backup import restore_backup
+
+            workspace_dir = get_default_memory_config().get_workspace()
+            ok = restore_backup(workspace_dir, backup_id)
+            if ok:
+                return ToolResult.success(
+                    f"Restored memory/skills to the state before evolution "
+                    f"{backup_id}. The previous self-learning has been undone."
+                )
+            return ToolResult.fail(
+                f"Could not find or restore backup {backup_id}. It may have "
+                f"expired or already been rolled back."
+            )
+        except Exception as e:
+            return ToolResult.fail(f"Error during undo: {e}")
diff --git a/agent/tools/ls/__init__.py b/agent/tools/ls/__init__.py
new file mode 100644
index 0000000..ad7aaa0
--- /dev/null
+++ b/agent/tools/ls/__init__.py
@@ -0,0 +1,3 @@
+from .ls import Ls
+
+__all__ = ['Ls']
diff --git a/agent/tools/ls/ls.py b/agent/tools/ls/ls.py
new file mode 100644
index 0000000..8f3bcbf
--- /dev/null
+++ b/agent/tools/ls/ls.py
@@ -0,0 +1,140 @@
+"""
+Ls tool - List directory contents
+"""
+
+import os
+from typing import Dict, Any
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.utils.truncate import truncate_head, format_size, DEFAULT_MAX_BYTES
+from common.utils import expand_path
+
+
+DEFAULT_LIMIT = 500
+
+
+class Ls(BaseTool):
+    """Tool for listing directory contents"""
+    
+    name: str = "ls"
+    description: str = f"List directory contents. Returns entries sorted alphabetically, with '/' suffix for directories. Includes dotfiles. Output is truncated to {DEFAULT_LIMIT} entries or {DEFAULT_MAX_BYTES // 1024}KB (whichever is hit first)."
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Directory to list. IMPORTANT: Relative paths are based on workspace directory. To access directories outside workspace, use absolute paths starting with ~ or /."
+            },
+            "limit": {
+                "type": "integer",
+                "description": f"Maximum number of entries to return (default: {DEFAULT_LIMIT})"
+            }
+        },
+        "required": []
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute directory listing
+        
+        :param args: Listing parameters
+        :return: Directory contents or error
+        """
+        path = args.get("path", ".").strip()
+        limit = args.get("limit", DEFAULT_LIMIT)
+        
+        # Resolve path
+        absolute_path = self._resolve_path(path)
+        
+        # Security check: Prevent accessing sensitive config directory
+        env_config_dir = expand_path("~/.cow")
+        if os.path.abspath(absolute_path) == os.path.abspath(env_config_dir):
+            return ToolResult.fail(
+                "Error: Access denied. API keys and credentials must be accessed through the env_config tool only."
+            )
+        
+        if not os.path.exists(absolute_path):
+            # Provide helpful hint if using relative path
+            if not os.path.isabs(path) and not path.startswith('~'):
+                return ToolResult.fail(
+                    f"Error: Path not found: {path}\n"
+                    f"Resolved to: {absolute_path}\n"
+                    f"Hint: Relative paths are based on workspace ({self.cwd}). For files outside workspace, use absolute paths."
+                )
+            return ToolResult.fail(f"Error: Path not found: {path}")
+        
+        if not os.path.isdir(absolute_path):
+            return ToolResult.fail(f"Error: Not a directory: {path}")
+        
+        try:
+            # Read directory entries
+            entries = os.listdir(absolute_path)
+            
+            # Sort alphabetically (case-insensitive)
+            entries.sort(key=lambda x: x.lower())
+            
+            # Format entries with directory indicators
+            results = []
+            entry_limit_reached = False
+            
+            for entry in entries:
+                if len(results) >= limit:
+                    entry_limit_reached = True
+                    break
+                
+                full_path = os.path.join(absolute_path, entry)
+                
+                try:
+                    if os.path.isdir(full_path):
+                        results.append(entry + '/')
+                    else:
+                        results.append(entry)
+                except Exception:
+                    # Skip entries we can't stat
+                    continue
+            
+            if not results:
+                return ToolResult.success({"message": "(empty directory)", "entries": []})
+            
+            # Format output
+            raw_output = '\n'.join(results)
+            truncation = truncate_head(raw_output, max_lines=999999)  # Only limit by bytes
+            
+            output = truncation.content
+            details = {}
+            notices = []
+            
+            if entry_limit_reached:
+                notices.append(f"{limit} entries limit reached. Use limit={limit * 2} for more")
+                details["entry_limit_reached"] = limit
+            
+            if truncation.truncated:
+                notices.append(f"{format_size(DEFAULT_MAX_BYTES)} limit reached")
+                details["truncation"] = truncation.to_dict()
+            
+            if notices:
+                output += f"\n\n[{'. '.join(notices)}]"
+            
+            return ToolResult.success({
+                "output": output,
+                "entry_count": len(results),
+                "details": details if details else None
+            })
+            
+        except PermissionError:
+            return ToolResult.fail(f"Error: Permission denied reading directory: {path}")
+        except Exception as e:
+            return ToolResult.fail(f"Error listing directory: {str(e)}")
+    
+    def _resolve_path(self, path: str) -> str:
+        """Resolve path to absolute path"""
+        # Expand ~ to user home directory
+        path = expand_path(path)
+        if os.path.isabs(path):
+            return path
+        return os.path.abspath(os.path.join(self.cwd, path))
diff --git a/agent/tools/mcp/__init__.py b/agent/tools/mcp/__init__.py
new file mode 100644
index 0000000..cd4065a
--- /dev/null
+++ b/agent/tools/mcp/__init__.py
@@ -0,0 +1,4 @@
+from agent.tools.mcp.mcp_client import McpClient, McpClientRegistry
+from agent.tools.mcp.mcp_tool import McpTool
+
+__all__ = ["McpClient", "McpClientRegistry", "McpTool"]
diff --git a/agent/tools/mcp/mcp_client.py b/agent/tools/mcp/mcp_client.py
new file mode 100644
index 0000000..e67cbbd
--- /dev/null
+++ b/agent/tools/mcp/mcp_client.py
@@ -0,0 +1,745 @@
+"""
+MCP (Model Context Protocol) client module.
+
+Implements JSON-RPC 2.0 over stdio, SSE and Streamable HTTP transports
+without any external MCP SDK dependency.
+"""
+
+import json
+import os
+import queue
+import subprocess
+import threading
+import urllib.request
+import urllib.error
+from typing import Optional
+
+from common.log import logger
+
+
+# Aliases accepted for the Streamable HTTP transport type
+_STREAMABLE_HTTP_ALIASES = {"streamable-http", "streamable_http", "streamablehttp", "http"}
+
+
+# Optional callback invoked after an OAuth authorization completes, so the
+# tool manager can bring the newly-authorized server online. Signature:
+# reload_fn(server_name: str) -> None. Installed by the tool manager.
+_reload_callback = None
+
+
+def set_reload_callback(fn) -> None:
+    """Register a callback fired after a server's OAuth flow succeeds."""
+    global _reload_callback
+    _reload_callback = fn
+
+
+def notify_server_authorized(server_name: str) -> None:
+    """Called by the web callback once tokens are stored for a server."""
+    fn = _reload_callback
+    if fn is None:
+        logger.debug(f"[MCP:{server_name}] Authorized but no reload callback registered")
+        return
+    try:
+        fn(server_name)
+    except Exception as e:
+        logger.warning(f"[MCP:{server_name}] reload callback failed: {e}")
+
+
+def _oauth_redirect_uri() -> str:
+    """Build the OAuth redirect URI served by the web console callback.
+
+    Priority: explicit mcp_oauth_redirect_base config, otherwise the local
+    web console address (127.0.0.1:<web_port>). Both point at the shared
+    /mcp/oauth/callback route.
+    """
+    try:
+        from config import conf
+        base = (conf().get("mcp_oauth_redirect_base") or "").strip().rstrip("/")
+        if not base:
+            port = int(os.environ.get("COW_WEB_PORT") or conf().get("web_port", 9899))
+            base = f"http://127.0.0.1:{port}"
+    except Exception:
+        base = "http://127.0.0.1:9899"
+    return f"{base}/mcp/oauth/callback"
+
+
+class McpClient:
+    """Single MCP Server client supporting stdio, SSE and Streamable HTTP transports."""
+
+    def __init__(self, config: dict):
+        """
+        config examples:
+          stdio:           {"name": "filesystem", "type": "stdio", "command": "npx", "args": [...]}
+          SSE:             {"name": "my-api",    "type": "sse",   "url": "http://localhost:8000/sse"}
+          streamable-http: {"name": "pubmed",    "type": "streamable-http", "url": "https://x/mcp"}
+        """
+        self.config = config
+        self.name: str = config.get("name", "unknown")
+        raw_transport: str = config.get("type", "stdio")
+        # Per-server timeout for tool calls (default 120s, suitable for data queries)
+        self._timeout: int = int(config.get("timeout", 120))
+        # Normalize streamable-http aliases to a single internal key
+        self.transport: str = (
+            "streamable-http"
+            if raw_transport.lower() in _STREAMABLE_HTTP_ALIASES
+            else raw_transport
+        )
+
+        # stdio state
+        self._proc: Optional[subprocess.Popen] = None
+        self._read_queue: queue.Queue = queue.Queue()
+
+        # SSE state
+        self._sse_url: Optional[str] = None
+        self._post_url: Optional[str] = None  # endpoint for sending messages (resolved from SSE)
+
+        # Streamable HTTP state
+        self._http_url: Optional[str] = None
+        self._http_headers: dict = {}  # extra headers from user config (e.g. Authorization)
+        self._http_session_id: Optional[str] = None  # Mcp-Session-Id assigned by the server
+
+        # OAuth state (streamable-http only). Lazily created when the server
+        # responds with 401 and the user has not supplied a static token.
+        self._oauth = None  # OAuthHandler instance
+        # Set to True once a 401 could not be satisfied and the user must
+        # complete the browser authorization. Callers can surface this state.
+        self.needs_auth: bool = False
+
+        # Shared state
+        self._next_id = 1
+        self._id_lock = threading.Lock()
+        # _call_lock serializes all requests on the single stdio pipe.
+        # SSE and streamable-http use independent HTTP requests, so they
+        # do not acquire this lock (see _send_request).
+        self._call_lock = threading.Lock()
+        # _http_lock protects _http_session_id initialization across
+        # concurrent streamable-http requests.
+        self._http_lock = threading.Lock()
+        self._initialized = False
+
+    # ------------------------------------------------------------------
+    # Public interface
+    # ------------------------------------------------------------------
+
+    def initialize(self) -> bool:
+        """Connect and perform the MCP handshake. Returns True on success."""
+        try:
+            if self.transport == "stdio":
+                return self._init_stdio()
+            elif self.transport == "sse":
+                return self._init_sse()
+            elif self.transport == "streamable-http":
+                return self._init_streamable_http()
+            else:
+                logger.warning(f"[MCP:{self.name}] Unknown transport type: {self.transport!r}")
+                return False
+        except Exception as e:
+            logger.warning(f"[MCP:{self.name}] Initialization failed: {e}")
+            return False
+
+    def list_tools(self) -> list:
+        """Return the tool list from this server.
+
+        Each item is a dict: {"name": str, "description": str, "inputSchema": dict}
+        """
+        try:
+            resp = self._send_request("tools/list", {})
+            tools = resp.get("result", {}).get("tools", [])
+            return [
+                {
+                    "name": t.get("name", ""),
+                    "description": t.get("description", ""),
+                    "inputSchema": t.get("inputSchema", {}),
+                }
+                for t in tools
+            ]
+        except Exception as e:
+            logger.warning(f"[MCP:{self.name}] list_tools failed: {e}")
+            return []
+
+    def call_tool(self, name: str, arguments: dict) -> str:
+        """Call a tool and return the result as a string."""
+        try:
+            resp = self._send_request("tools/call", {"name": name, "arguments": arguments})
+            content = resp.get("result", {}).get("content", [])
+            parts = [item.get("text", "") for item in content if item.get("type") == "text"]
+            return "\n".join(parts)
+        except Exception as e:
+            logger.warning(f"[MCP:{self.name}] call_tool({name}) failed: {e}")
+            return f"Error: {e}"
+
+    def shutdown(self):
+        """Close the connection / terminate the child process."""
+        if self._proc is not None:
+            try:
+                self._proc.stdin.close()
+            except Exception:
+                pass
+            try:
+                self._proc.terminate()
+                self._proc.wait(timeout=5)
+            except Exception:
+                try:
+                    self._proc.kill()
+                except Exception:
+                    pass
+            self._proc = None
+            logger.debug(f"[MCP:{self.name}] stdio process terminated")
+
+        # Best-effort streamable-http session termination
+        if self.transport == "streamable-http" and self._http_session_id and self._http_url:
+            try:
+                req = urllib.request.Request(
+                    self._http_url,
+                    method="DELETE",
+                    headers={"Mcp-Session-Id": self._http_session_id, **self._http_headers},
+                )
+                with urllib.request.urlopen(req, timeout=5):
+                    pass
+            except Exception:
+                pass
+            self._http_session_id = None
+
+        self._initialized = False
+
+    # ------------------------------------------------------------------
+    # stdio transport
+    # ------------------------------------------------------------------
+
+    def _init_stdio(self) -> bool:
+        command = self.config.get("command")
+        if not command:
+            logger.warning(f"[MCP:{self.name}] stdio config missing 'command'")
+            return False
+
+        args = self.config.get("args", [])
+        extra_env = self.config.get("env", None)
+        env = {**os.environ, **extra_env} if extra_env else None
+
+        self._proc = subprocess.Popen(
+            [command] + list(args),
+            stdin=subprocess.PIPE,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+            text=True,
+            encoding="utf-8",
+            env=env,
+        )
+        logger.debug(f"[MCP:{self.name}] stdio process started (pid={self._proc.pid})")
+
+        threading.Thread(
+            target=self._drain_stderr, daemon=True, name=f"mcp-stderr-{self.name}"
+        ).start()
+        threading.Thread(
+            target=self._drain_stdout, daemon=True, name=f"mcp-stdout-{self.name}"
+        ).start()
+
+        return self._handshake()
+
+    def _drain_stderr(self):
+        for line in self._proc.stderr:
+            line = line.strip()
+            if line:
+                logger.warning(f"[MCP:{self.name}] stderr: {line}")
+
+    def _drain_stdout(self):
+        """Background thread: read lines from stdout and put them into the queue."""
+        try:
+            for line in self._proc.stdout:
+                self._read_queue.put(line)
+        except Exception:
+            pass
+        finally:
+            try:
+                self._read_queue.put("")
+            except Exception:
+                pass
+
+    def _readline_with_timeout(self, timeout: Optional[int] = None) -> str:
+        """Read one line from stdio stdout with a hard timeout (cross-platform).
+
+        Uses the per-server timeout from mcp.json config when no explicit
+        timeout is provided.
+        """
+        effective = timeout if timeout is not None else self._timeout
+        try:
+            line = self._read_queue.get(timeout=effective)
+        except queue.Empty:
+            raise TimeoutError(f"[MCP:{self.name}] stdio read timed out after {effective}s")
+        if not line:
+            raise IOError(f"[MCP:{self.name}] stdio process closed unexpectedly")
+        return line
+
+    def _stdio_send(self, message: dict) -> dict:
+        """Send a JSON-RPC message over stdio and read the response."""
+        raw = json.dumps(message) + "\n"
+        self._proc.stdin.write(raw)
+        self._proc.stdin.flush()
+
+        expected_id = message.get("id")
+        while True:
+            line = self._readline_with_timeout()
+            if not line:
+                raise IOError(f"[MCP:{self.name}] stdio process closed unexpectedly")
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                data = json.loads(line)
+            except json.JSONDecodeError:
+                continue
+            if "id" not in data:
+                logger.debug(f"[MCP:{self.name}] notification skipped: {data.get('method', '?')}")
+                continue
+            # Verify response id matches request id to avoid consuming a stale
+            # response left over from a previously failed/timed-out request.
+            if data.get("id") != expected_id:
+                logger.warning(
+                    f"[MCP:{self.name}] Stale response id={data.get('id')} "
+                    f"(expected {expected_id}), skipping"
+                )
+                continue
+            return data
+
+    # ------------------------------------------------------------------
+    # SSE transport
+    # ------------------------------------------------------------------
+
+    def _init_sse(self) -> bool:
+        url = self.config.get("url")
+        if not url:
+            logger.warning(f"[MCP:{self.name}] SSE config missing 'url'")
+            return False
+
+        self._sse_url = url
+
+        # Read the first SSE event to discover the POST endpoint
+        try:
+            self._post_url = self._sse_discover_endpoint()
+        except Exception as e:
+            logger.warning(f"[MCP:{self.name}] SSE endpoint discovery failed: {e}")
+            return False
+
+        return self._handshake()
+
+    def _sse_discover_endpoint(self) -> str:
+        """Open SSE stream and read the 'endpoint' event to learn the POST URL."""
+        req = urllib.request.Request(
+            self._sse_url,
+            headers={"Accept": "text/event-stream"},
+        )
+        with urllib.request.urlopen(req, timeout=10) as resp:
+            for raw_line in resp:
+                line = raw_line.decode("utf-8").rstrip("\n\r")
+                if line.startswith("data:"):
+                    data = line[len("data:"):].strip()
+                    # Some servers send JSON with a "uri" or plain path
+                    if data.startswith("{"):
+                        parsed = json.loads(data)
+                        return parsed.get("uri") or parsed.get("url") or parsed.get("endpoint")
+                    # Plain relative or absolute URL
+                    if data.startswith("http"):
+                        return data
+                    # Relative path: resolve against SSE base
+                    from urllib.parse import urljoin
+                    return urljoin(self._sse_url, data)
+        raise ValueError(f"[MCP:{self.name}] No endpoint event received from SSE stream")
+
+    def _sse_send(self, message: dict) -> dict:
+        """POST a JSON-RPC message to the server and return the response."""
+        body = json.dumps(message).encode("utf-8")
+        req = urllib.request.Request(
+            self._post_url,
+            data=body,
+            method="POST",
+            headers={"Content-Type": "application/json"},
+        )
+        with urllib.request.urlopen(req, timeout=30) as resp:
+            raw = resp.read().decode("utf-8")
+            return json.loads(raw)
+
+    # ------------------------------------------------------------------
+    # Streamable HTTP transport (MCP spec 2025-03-26)
+    # ------------------------------------------------------------------
+
+    def _init_streamable_http(self) -> bool:
+        url = self.config.get("url")
+        if not url:
+            logger.warning(f"[MCP:{self.name}] streamable-http config missing 'url'")
+            return False
+
+        self._http_url = url
+        # Allow user-provided headers (e.g. {"Authorization": "Bearer xxx"})
+        extra_headers = self.config.get("headers") or {}
+        if isinstance(extra_headers, dict):
+            self._http_headers = {str(k): str(v) for k, v in extra_headers.items()}
+
+        # Restore any previously stored OAuth credentials for this server so a
+        # restart reuses the token instead of forcing re-authorization.
+        self._maybe_load_oauth()
+
+        return self._handshake()
+
+    # ------------------------------------------------------------------
+    # OAuth helpers (streamable-http only)
+    # ------------------------------------------------------------------
+
+    def _has_static_auth(self) -> bool:
+        """True when the user supplied their own Authorization header."""
+        return any(k.lower() == "authorization" for k in self._http_headers)
+
+    def _maybe_load_oauth(self) -> None:
+        """Attach an OAuthHandler when stored credentials exist for this server."""
+        if self._has_static_auth():
+            return
+        try:
+            from agent.tools.mcp.mcp_oauth import OAuthHandler, load_server_record
+        except Exception:
+            return
+        rec = load_server_record(self.name)
+        # Only create a handler when we have something to reuse; otherwise it
+        # is created lazily on the first 401.
+        if rec.get("access_token") or rec.get("client_id"):
+            self._oauth = OAuthHandler(
+                server_name=self.name,
+                resource_url=self._http_url,
+                redirect_uri=_oauth_redirect_uri(),
+                scope=self.config.get("scope", ""),
+            )
+
+    def _current_bearer(self) -> Optional[str]:
+        """Return a valid access token, refreshing if needed."""
+        if self._oauth is None:
+            return None
+        return self._oauth.get_valid_access_token()
+
+    def _begin_oauth(self, www_authenticate: str = "") -> None:
+        """Kick off the OAuth flow after a 401: discover, register, prompt user."""
+        if self._has_static_auth():
+            return
+        try:
+            from agent.tools.mcp.mcp_oauth import OAuthHandler
+        except Exception as e:
+            logger.warning(f"[MCP:{self.name}] OAuth module unavailable: {e}")
+            return
+
+        if self._oauth is None:
+            self._oauth = OAuthHandler(
+                server_name=self.name,
+                resource_url=self._http_url,
+                redirect_uri=_oauth_redirect_uri(),
+                scope=self.config.get("scope", ""),
+            )
+
+        if not self._oauth.ensure_registered(www_authenticate):
+            logger.warning(
+                f"[MCP:{self.name}] OAuth discovery/registration failed; "
+                f"cannot authorize automatically"
+            )
+            return
+
+        auth_url = self._oauth.build_authorization_url()
+        if not auth_url:
+            logger.warning(f"[MCP:{self.name}] Failed to build authorization URL")
+            return
+
+        self.needs_auth = True
+        logger.warning(
+            f"[MCP:{self.name}] ⚠️  Authorization required. Open this URL in a "
+            f"browser to authorize, then this server will come online automatically:\n"
+            f"    {auth_url}"
+        )
+        # On a machine with a local browser (desktop/dev), open it directly.
+        if os.environ.get("COW_DESKTOP") == "1" or not os.environ.get("COW_HEADLESS"):
+            try:
+                import webbrowser
+                webbrowser.open(auth_url)
+            except Exception:
+                pass
+
+    def _streamable_http_send(self, message: dict) -> dict:
+        """POST a JSON-RPC request and return the response (JSON or SSE-wrapped)."""
+        return self._streamable_http_post(message, expect_response=True)
+
+    def _handle_401(self, err, message: dict, expect_response: bool, retried: bool) -> dict:
+        """Handle a 401: refresh the token and retry once, else begin OAuth."""
+        www_auth = ""
+        try:
+            www_auth = err.headers.get("WWW-Authenticate", "") or ""
+        except Exception:
+            pass
+        try:
+            err.read()
+        except Exception:
+            pass
+
+        # First try a silent refresh with the stored refresh token.
+        if not retried and self._oauth is not None and self._oauth.refresh():
+            logger.info(f"[MCP:{self.name}] Token refreshed after 401, retrying")
+            return self._streamable_http_post(message, expect_response, _retried=True)
+
+        # No usable token — start (or restart) the interactive OAuth flow.
+        self._begin_oauth(www_auth)
+        raise IOError(
+            f"[MCP:{self.name}] streamable-http HTTP 401: authorization required "
+            f"(complete the OAuth flow to enable this server)"
+        )
+
+    def _streamable_http_post(self, message: dict, expect_response: bool, _retried: bool = False) -> dict:
+        """
+        POST a JSON-RPC message over Streamable HTTP.
+
+        Per the spec, the response Content-Type can be either:
+          - application/json   -> single JSON-RPC response in body
+          - text/event-stream  -> SSE stream; we read until we get a matching response
+        """
+        body = json.dumps(message).encode("utf-8")
+        headers = {
+            "Content-Type": "application/json",
+            "Accept": "application/json, text/event-stream",
+        }
+        # Read session id under lock to avoid racing with the
+        # initialization write below during concurrent requests.
+        with self._http_lock:
+            sid = self._http_session_id
+        if sid:
+            headers["Mcp-Session-Id"] = sid
+        headers.update(self._http_headers)
+        # Inject OAuth bearer token when we have one (unless the user set a
+        # static Authorization header, which takes precedence).
+        if not self._has_static_auth():
+            token = self._current_bearer()
+            if token:
+                headers["Authorization"] = f"Bearer {token}"
+
+        req = urllib.request.Request(
+            self._http_url,
+            data=body,
+            method="POST",
+            headers=headers,
+        )
+
+        try:
+            resp = urllib.request.urlopen(req, timeout=30)
+        except urllib.error.HTTPError as e:
+            # 401 is the spec-compliant "needs authorization" signal.
+            if e.code == 401 and not self._has_static_auth():
+                return self._handle_401(e, message, expect_response, _retried)
+            # Surface the server-provided error body for easier debugging
+            detail = ""
+            try:
+                detail = e.read().decode("utf-8", errors="ignore")
+            except Exception:
+                pass
+            raise IOError(
+                f"[MCP:{self.name}] streamable-http HTTP {e.code}: {detail[:200]}"
+            )
+
+        with resp:
+            # Capture session id assigned by the server (if any)
+            session_id = resp.headers.get("Mcp-Session-Id")
+            # Double-checked lock: only the first response sets the
+            # session id, preventing concurrent initializers from
+            # overwriting each other.
+            if session_id and not self._http_session_id:
+                with self._http_lock:
+                    if not self._http_session_id:
+                        self._http_session_id = session_id
+
+            status = resp.status if hasattr(resp, "status") else resp.getcode()
+
+            # Notifications: server may reply with 202 Accepted and no body
+            if not expect_response or status == 202:
+                try:
+                    resp.read()
+                except Exception:
+                    pass
+                return {}
+
+            content_type = (resp.headers.get("Content-Type") or "").lower()
+            expected_id = message.get("id")
+
+            if "text/event-stream" in content_type:
+                return self._read_sse_response(resp, expected_id)
+
+            raw = resp.read().decode("utf-8")
+            if not raw:
+                return {}
+            return json.loads(raw)
+
+    def _read_sse_response(self, resp, expected_id) -> dict:
+        """Read an SSE stream and return the first JSON-RPC response with matching id."""
+        data_buf: list = []
+        for raw_line in resp:
+            line = raw_line.decode("utf-8").rstrip("\n\r")
+            if line == "":
+                # End of an SSE event, attempt to parse accumulated data
+                if data_buf:
+                    payload = "\n".join(data_buf)
+                    data_buf = []
+                    try:
+                        msg = json.loads(payload)
+                    except json.JSONDecodeError:
+                        continue
+                    # Skip notifications / mismatched ids
+                    if "id" not in msg:
+                        continue
+                    if expected_id is None or msg.get("id") == expected_id:
+                        return msg
+                continue
+            if line.startswith(":"):
+                continue  # SSE comment / keepalive
+            if line.startswith("data:"):
+                data_buf.append(line[len("data:"):].lstrip())
+            # Ignore 'event:' / 'id:' lines; we only care about JSON-RPC payloads
+
+        raise IOError(f"[MCP:{self.name}] streamable-http SSE stream closed before response")
+
+    # ------------------------------------------------------------------
+    # Common JSON-RPC helpers
+    # ------------------------------------------------------------------
+
+    def _next_request_id(self) -> int:
+        with self._id_lock:
+            rid = self._next_id
+            self._next_id += 1
+        return rid
+
+    def _build_request(self, method: str, params: dict) -> dict:
+        return {
+            "jsonrpc": "2.0",
+            "id": self._next_request_id(),
+            "method": method,
+            "params": params,
+        }
+
+    def _build_notification(self, method: str, params: dict) -> dict:
+        return {"jsonrpc": "2.0", "method": method, "params": params}
+
+    def _send_request(self, method: str, params: dict) -> dict:
+        """Send a request and return the full response dict."""
+        if not self._initialized and method != "initialize":
+            raise RuntimeError(f"[MCP:{self.name}] Client not initialized")
+
+        message = self._build_request(method, params)
+
+        # stdio transport uses a single pipe and must be serialized.
+        # SSE and streamable-http use independent HTTP requests and
+        # can safely run concurrently across sessions.
+        if self.transport == "stdio":
+            with self._call_lock:
+                return self._stdio_send(message)
+        elif self.transport == "sse":
+            return self._sse_send(message)
+        elif self.transport == "streamable-http":
+            return self._streamable_http_send(message)
+        else:
+            raise ValueError(f"[MCP:{self.name}] Unsupported transport: {self.transport}")
+
+    def _send_notification(self, method: str, params: dict):
+        """Fire-and-forget notification (no response expected)."""
+        notification = self._build_notification(method, params)
+        raw = json.dumps(notification) + "\n"
+
+        if self.transport == "stdio":
+            self._proc.stdin.write(raw)
+            self._proc.stdin.flush()
+        elif self.transport == "sse":
+            body = raw.encode("utf-8")
+            req = urllib.request.Request(
+                self._post_url,
+                data=body,
+                method="POST",
+                headers={"Content-Type": "application/json"},
+            )
+            try:
+                with urllib.request.urlopen(req, timeout=10):
+                    pass
+            except Exception:
+                pass  # notifications are fire-and-forget
+        elif self.transport == "streamable-http":
+            try:
+                self._streamable_http_post(notification, expect_response=False)
+            except Exception:
+                pass  # notifications are fire-and-forget
+
+    def _handshake(self) -> bool:
+        """Perform the MCP initialize / notifications/initialized handshake."""
+        init_params = {
+            "protocolVersion": "2024-11-05",
+            "capabilities": {},
+            "clientInfo": {"name": "CowAgent", "version": "1.0"},
+        }
+        # Temporarily mark as initialized so _send_request doesn't block
+        self._initialized = True
+        try:
+            resp = self._send_request("initialize", init_params)
+        except Exception as e:
+            self._initialized = False
+            logger.warning(f"[MCP:{self.name}] Handshake initialize failed: {e}")
+            return False
+
+        if "error" in resp:
+            self._initialized = False
+            logger.warning(f"[MCP:{self.name}] Handshake error: {resp['error']}")
+            return False
+
+        self._send_notification("notifications/initialized", {})
+        logger.debug(f"[MCP:{self.name}] Handshake complete")
+        return True
+
+
+class McpClientRegistry:
+    """Global singleton managing the lifecycle of all MCP Server clients."""
+
+    _instance = None
+    _instance_lock = threading.Lock()
+
+    def __new__(cls):
+        with cls._instance_lock:
+            if cls._instance is None:
+                obj = super().__new__(cls)
+                obj._clients: dict[str, McpClient] = {}
+                obj._registry_lock = threading.Lock()
+                cls._instance = obj
+        return cls._instance
+
+    def start_all(self, configs: list) -> None:
+        """Initialize McpClient for each config entry; skip failures with a warning."""
+        if not configs:
+            return
+
+        for cfg in configs:
+            name = cfg.get("name", "<unnamed>")
+            client = McpClient(cfg)
+            ok = client.initialize()
+            if ok:
+                with self._registry_lock:
+                    self._clients[name] = client
+                logger.info(f"[MCP] Server '{name}' initialized successfully")
+            else:
+                logger.warning(f"[MCP] Server '{name}' failed to initialize — skipping")
+
+    def get(self, server_name: str) -> Optional[McpClient]:
+        """Return the initialized client for server_name, or None."""
+        with self._registry_lock:
+            return self._clients.get(server_name)
+
+    def all_clients(self) -> dict:
+        """Return a copy of the {name: McpClient} mapping."""
+        with self._registry_lock:
+            return dict(self._clients)
+
+    def shutdown_all(self) -> None:
+        """Shut down all managed clients."""
+        with self._registry_lock:
+            clients = list(self._clients.values())
+            self._clients.clear()
+
+        for client in clients:
+            try:
+                client.shutdown()
+            except Exception as e:
+                logger.warning(f"[MCP] Error shutting down '{client.name}': {e}")
+
+        logger.info("[MCP] All servers shut down")
diff --git a/agent/tools/mcp/mcp_oauth.py b/agent/tools/mcp/mcp_oauth.py
new file mode 100644
index 0000000..90b79a1
--- /dev/null
+++ b/agent/tools/mcp/mcp_oauth.py
@@ -0,0 +1,466 @@
+"""
+MCP OAuth 2.1 client (authorization code + PKCE) with zero external deps.
+
+Implements the subset of the MCP authorization spec needed to connect to
+remote MCP servers that guard their endpoint behind OAuth (e.g. Xmind):
+
+  1. Metadata discovery via RFC 9728 (protected-resource) + RFC 8414
+     (authorization-server) .well-known documents.
+  2. Dynamic Client Registration (RFC 7591) to obtain a client_id.
+  3. PKCE (RFC 7636, S256) authorization-code flow.
+  4. Token exchange + refresh, persisted to ~/.cow/mcp_oauth.json.
+
+The actual browser round-trip is completed out-of-band: McpClient generates
+an authorization URL, the user opens it, and the web console callback
+(/mcp/oauth/callback) feeds the returned code back into finish_authorization().
+"""
+
+import base64
+import hashlib
+import json
+import os
+import secrets
+import threading
+import time
+import urllib.parse
+import urllib.request
+import urllib.error
+from typing import Optional
+
+from common.log import logger
+
+
+# ------------------------------------------------------------------
+# Token store: ~/.cow/mcp_oauth.json  {server_name: {...credentials...}}
+# ------------------------------------------------------------------
+
+_STORE_LOCK = threading.Lock()
+
+
+def _store_path() -> str:
+    base = os.path.expanduser("~/.cow")
+    try:
+        os.makedirs(base, exist_ok=True)
+    except OSError:
+        pass
+    return os.path.join(base, "mcp_oauth.json")
+
+
+def _load_store() -> dict:
+    path = _store_path()
+    if not os.path.exists(path):
+        return {}
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        return data if isinstance(data, dict) else {}
+    except Exception as e:
+        logger.warning(f"[MCP-OAuth] Failed to read token store: {e}")
+        return {}
+
+
+def _save_store(store: dict) -> None:
+    path = _store_path()
+    tmp = f"{path}.tmp"
+    try:
+        with open(tmp, "w", encoding="utf-8") as f:
+            json.dump(store, f, ensure_ascii=False, indent=2)
+        os.replace(tmp, path)
+        # Credentials file: restrict to owner read/write when possible.
+        try:
+            os.chmod(path, 0o600)
+        except OSError:
+            pass
+    except Exception as e:
+        logger.warning(f"[MCP-OAuth] Failed to persist token store: {e}")
+
+
+def load_server_record(server_name: str) -> dict:
+    with _STORE_LOCK:
+        return dict(_load_store().get(server_name, {}))
+
+
+def save_server_record(server_name: str, record: dict) -> None:
+    with _STORE_LOCK:
+        store = _load_store()
+        store[server_name] = record
+        _save_store(store)
+
+
+def clear_server_record(server_name: str) -> None:
+    with _STORE_LOCK:
+        store = _load_store()
+        if server_name in store:
+            store.pop(server_name, None)
+            _save_store(store)
+
+
+# ------------------------------------------------------------------
+# Pending authorizations, keyed by the OAuth `state` param.
+# Populated when an authorization URL is generated; consumed by the
+# web callback when the browser redirects back with ?code&state.
+# ------------------------------------------------------------------
+
+_PENDING_LOCK = threading.Lock()
+_PENDING: dict = {}  # state -> {"handler": OAuthHandler, "created": ts}
+_PENDING_TTL = 600  # seconds
+
+
+def _register_pending(state: str, handler: "OAuthHandler") -> None:
+    with _PENDING_LOCK:
+        _prune_pending_locked()
+        _PENDING[state] = {"handler": handler, "created": time.time()}
+
+
+def _prune_pending_locked() -> None:
+    now = time.time()
+    stale = [s for s, v in _PENDING.items() if now - v["created"] > _PENDING_TTL]
+    for s in stale:
+        _PENDING.pop(s, None)
+
+
+def pop_pending(state: str) -> Optional["OAuthHandler"]:
+    with _PENDING_LOCK:
+        _prune_pending_locked()
+        entry = _PENDING.pop(state, None)
+    return entry["handler"] if entry else None
+
+
+def has_pending() -> bool:
+    with _PENDING_LOCK:
+        _prune_pending_locked()
+        return bool(_PENDING)
+
+
+# ------------------------------------------------------------------
+# HTTP helpers (stdlib only)
+# ------------------------------------------------------------------
+
+_UA = "CowAgent-MCP-OAuth/1.0"
+
+
+def _http_get_json(url: str, timeout: int = 15) -> Optional[dict]:
+    req = urllib.request.Request(url, headers={"Accept": "application/json", "User-Agent": _UA})
+    try:
+        with urllib.request.urlopen(req, timeout=timeout) as resp:
+            raw = resp.read().decode("utf-8")
+            return json.loads(raw)
+    except urllib.error.HTTPError as e:
+        logger.debug(f"[MCP-OAuth] GET {url} -> HTTP {e.code}")
+        return None
+    except Exception as e:
+        logger.debug(f"[MCP-OAuth] GET {url} failed: {e}")
+        return None
+
+
+def _http_post_form(url: str, fields: dict, timeout: int = 20) -> dict:
+    body = urllib.parse.urlencode(fields).encode("utf-8")
+    req = urllib.request.Request(
+        url,
+        data=body,
+        method="POST",
+        headers={
+            "Content-Type": "application/x-www-form-urlencoded",
+            "Accept": "application/json",
+            "User-Agent": _UA,
+        },
+    )
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        raw = resp.read().decode("utf-8")
+        return json.loads(raw) if raw else {}
+
+
+def _http_post_json(url: str, payload: dict, timeout: int = 20) -> dict:
+    body = json.dumps(payload).encode("utf-8")
+    req = urllib.request.Request(
+        url,
+        data=body,
+        method="POST",
+        headers={
+            "Content-Type": "application/json",
+            "Accept": "application/json",
+            "User-Agent": _UA,
+        },
+    )
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        raw = resp.read().decode("utf-8")
+        return json.loads(raw) if raw else {}
+
+
+# ------------------------------------------------------------------
+# Discovery (RFC 9728 + RFC 8414)
+# ------------------------------------------------------------------
+
+def _origin(url: str) -> str:
+    p = urllib.parse.urlparse(url)
+    return f"{p.scheme}://{p.netloc}"
+
+
+def discover_metadata(resource_url: str, www_authenticate: str = "") -> Optional[dict]:
+    """
+    Resolve the authorization server metadata for a protected MCP resource.
+
+    Returns a dict with at least authorization_endpoint + token_endpoint,
+    plus registration_endpoint when the server supports DCR. Returns None
+    when discovery fails.
+    """
+    as_metadata_url = _parse_resource_metadata_url(www_authenticate)
+
+    # 1) Protected-resource metadata (RFC 9728) to locate the auth server.
+    auth_server = None
+    prm = None
+    if as_metadata_url:
+        prm = _http_get_json(as_metadata_url)
+    if prm is None:
+        origin = _origin(resource_url)
+        prm = _http_get_json(f"{origin}/.well-known/oauth-protected-resource")
+    if prm and isinstance(prm.get("authorization_servers"), list) and prm["authorization_servers"]:
+        auth_server = prm["authorization_servers"][0]
+
+    # 2) Authorization-server metadata (RFC 8414). Fall back to the resource
+    #    origin when the resource did not advertise a separate auth server.
+    base = auth_server or _origin(resource_url)
+    asm = _fetch_as_metadata(base)
+    if not asm:
+        return None
+
+    if not asm.get("authorization_endpoint") or not asm.get("token_endpoint"):
+        logger.warning("[MCP-OAuth] Authorization server metadata missing required endpoints")
+        return None
+
+    # Derive the scope to request. Prefer the resource's required_scopes
+    # (RFC 9728), then its scopes_supported, then the auth server's
+    # scopes_supported. Stored so callers don't have to configure it.
+    discovered_scope = ""
+    if prm:
+        scopes = prm.get("required_scopes") or prm.get("scopes_supported")
+        if isinstance(scopes, list) and scopes:
+            discovered_scope = " ".join(str(s) for s in scopes)
+    if not discovered_scope and isinstance(asm.get("scopes_supported"), list) and asm["scopes_supported"]:
+        discovered_scope = " ".join(str(s) for s in asm["scopes_supported"])
+    if discovered_scope:
+        asm["_discovered_scope"] = discovered_scope
+    return asm
+
+
+def _parse_resource_metadata_url(www_authenticate: str) -> Optional[str]:
+    """Extract resource_metadata="..." from a WWW-Authenticate: Bearer header."""
+    if not www_authenticate:
+        return None
+    # naive but sufficient parse for `resource_metadata="URL"`
+    marker = "resource_metadata="
+    idx = www_authenticate.find(marker)
+    if idx < 0:
+        return None
+    rest = www_authenticate[idx + len(marker):].strip()
+    if rest.startswith('"'):
+        end = rest.find('"', 1)
+        return rest[1:end] if end > 0 else None
+    # unquoted, up to comma/space
+    for sep in (",", " "):
+        if sep in rest:
+            rest = rest.split(sep, 1)[0]
+    return rest or None
+
+
+def _fetch_as_metadata(base: str) -> Optional[dict]:
+    """Try both RFC 8414 and OIDC well-known locations."""
+    base = base.rstrip("/")
+    candidates = [
+        f"{base}/.well-known/oauth-authorization-server",
+        f"{base}/.well-known/openid-configuration",
+    ]
+    for url in candidates:
+        data = _http_get_json(url)
+        if data and data.get("authorization_endpoint"):
+            return data
+    return None
+
+
+# ------------------------------------------------------------------
+# PKCE
+# ------------------------------------------------------------------
+
+def _b64url(data: bytes) -> str:
+    return base64.urlsafe_b64encode(data).decode("ascii").rstrip("=")
+
+
+def _make_pkce() -> tuple:
+    verifier = _b64url(secrets.token_bytes(32))
+    challenge = _b64url(hashlib.sha256(verifier.encode("ascii")).digest())
+    return verifier, challenge
+
+
+# ------------------------------------------------------------------
+# OAuthHandler: per-server OAuth state machine
+# ------------------------------------------------------------------
+
+class OAuthHandler:
+    """Drives the OAuth flow and token lifecycle for a single MCP server."""
+
+    def __init__(self, server_name: str, resource_url: str, redirect_uri: str,
+                 scope: str = "", client_name: str = "CowAgent"):
+        self.server_name = server_name
+        self.resource_url = resource_url
+        self.redirect_uri = redirect_uri
+        self.scope = scope
+        self.client_name = client_name
+
+        rec = load_server_record(server_name)
+        self.metadata: dict = rec.get("metadata", {})
+        self.client_id: Optional[str] = rec.get("client_id")
+        self.client_secret: Optional[str] = rec.get("client_secret")
+        self.access_token: Optional[str] = rec.get("access_token")
+        self.refresh_token: Optional[str] = rec.get("refresh_token")
+        self.expires_at: float = float(rec.get("expires_at", 0) or 0)
+        self._verifier: Optional[str] = None
+
+    # --- persistence -------------------------------------------------
+
+    def _persist(self) -> None:
+        save_server_record(self.server_name, {
+            "resource_url": self.resource_url,
+            "metadata": self.metadata,
+            "client_id": self.client_id,
+            "client_secret": self.client_secret,
+            "access_token": self.access_token,
+            "refresh_token": self.refresh_token,
+            "expires_at": self.expires_at,
+        })
+
+    # --- token access ------------------------------------------------
+
+    def get_valid_access_token(self, leeway: int = 60) -> Optional[str]:
+        """Return a usable access token, refreshing proactively when near expiry."""
+        if not self.access_token:
+            return None
+        if self.expires_at and time.time() >= self.expires_at - leeway:
+            if not self.refresh():
+                return None
+        return self.access_token
+
+    def refresh(self) -> bool:
+        """Refresh the access token using the stored refresh token."""
+        if not self.refresh_token or not self.metadata.get("token_endpoint"):
+            return False
+        fields = {
+            "grant_type": "refresh_token",
+            "refresh_token": self.refresh_token,
+            "client_id": self.client_id or "",
+        }
+        if self.client_secret:
+            fields["client_secret"] = self.client_secret
+        try:
+            resp = _http_post_form(self.metadata["token_endpoint"], fields)
+        except Exception as e:
+            logger.warning(f"[MCP-OAuth:{self.server_name}] refresh failed: {e}")
+            return False
+        return self._absorb_token_response(resp)
+
+    # --- authorization-code flow ------------------------------------
+
+    def ensure_registered(self, www_authenticate: str = "") -> bool:
+        """Discover metadata + register a client if not already done."""
+        if not self.metadata.get("authorization_endpoint"):
+            meta = discover_metadata(self.resource_url, www_authenticate)
+            if not meta:
+                return False
+            self.metadata = meta
+        # Adopt the scope discovered from metadata when the user didn't set one.
+        if not self.scope and self.metadata.get("_discovered_scope"):
+            self.scope = self.metadata["_discovered_scope"]
+            logger.info(f"[MCP-OAuth:{self.server_name}] Using discovered scope: {self.scope}")
+        if not self.client_id:
+            if not self._register_client():
+                return False
+        self._persist()
+        return True
+
+    def _register_client(self) -> bool:
+        reg_endpoint = self.metadata.get("registration_endpoint")
+        if not reg_endpoint:
+            logger.warning(
+                f"[MCP-OAuth:{self.server_name}] No registration_endpoint; "
+                f"DCR unavailable. Provide client_id manually."
+            )
+            return False
+        payload = {
+            "client_name": self.client_name,
+            "redirect_uris": [self.redirect_uri],
+            "grant_types": ["authorization_code", "refresh_token"],
+            "response_types": ["code"],
+            "token_endpoint_auth_method": "none",
+        }
+        if self.scope:
+            payload["scope"] = self.scope
+        try:
+            resp = _http_post_json(reg_endpoint, payload)
+        except Exception as e:
+            logger.warning(f"[MCP-OAuth:{self.server_name}] DCR failed: {e}")
+            return False
+        client_id = resp.get("client_id")
+        if not client_id:
+            logger.warning(f"[MCP-OAuth:{self.server_name}] DCR returned no client_id")
+            return False
+        self.client_id = client_id
+        self.client_secret = resp.get("client_secret")
+        logger.info(f"[MCP-OAuth:{self.server_name}] Registered client_id={client_id}")
+        return True
+
+    def build_authorization_url(self) -> Optional[str]:
+        """Create an authorization URL and register this handler as pending."""
+        if not self.metadata.get("authorization_endpoint") or not self.client_id:
+            return None
+        self._verifier, challenge = _make_pkce()
+        state = secrets.token_urlsafe(24)
+        params = {
+            "response_type": "code",
+            "client_id": self.client_id,
+            "redirect_uri": self.redirect_uri,
+            "code_challenge": challenge,
+            "code_challenge_method": "S256",
+            "state": state,
+        }
+        if self.scope:
+            params["scope"] = self.scope
+        # Advertise the resource we intend to access (RFC 8707).
+        params["resource"] = self.resource_url
+        _register_pending(state, self)
+        return f"{self.metadata['authorization_endpoint']}?{urllib.parse.urlencode(params)}"
+
+    def finish_authorization(self, code: str) -> bool:
+        """Exchange an authorization code for tokens."""
+        if not self.metadata.get("token_endpoint") or not self._verifier:
+            return False
+        fields = {
+            "grant_type": "authorization_code",
+            "code": code,
+            "redirect_uri": self.redirect_uri,
+            "client_id": self.client_id or "",
+            "code_verifier": self._verifier,
+            "resource": self.resource_url,
+        }
+        if self.client_secret:
+            fields["client_secret"] = self.client_secret
+        try:
+            resp = _http_post_form(self.metadata["token_endpoint"], fields)
+        except Exception as e:
+            logger.warning(f"[MCP-OAuth:{self.server_name}] token exchange failed: {e}")
+            return False
+        ok = self._absorb_token_response(resp)
+        self._verifier = None
+        return ok
+
+    def _absorb_token_response(self, resp: dict) -> bool:
+        access = resp.get("access_token")
+        if not access:
+            logger.warning(f"[MCP-OAuth:{self.server_name}] token response missing access_token: {resp}")
+            return False
+        self.access_token = access
+        if resp.get("refresh_token"):
+            self.refresh_token = resp["refresh_token"]
+        expires_in = resp.get("expires_in")
+        self.expires_at = time.time() + int(expires_in) if expires_in else 0
+        self._persist()
+        logger.info(f"[MCP-OAuth:{self.server_name}] Access token stored")
+        return True
diff --git a/agent/tools/mcp/mcp_tool.py b/agent/tools/mcp/mcp_tool.py
new file mode 100644
index 0000000..ef1e814
--- /dev/null
+++ b/agent/tools/mcp/mcp_tool.py
@@ -0,0 +1,31 @@
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.log import logger
+
+
+class McpTool(BaseTool):
+    """
+    将单个 MCP 工具包装为 BaseTool。
+    一个 MCP Server 可以提供多个工具，每个工具对应一个 McpTool 实例。
+    """
+
+    def __init__(self, client, tool_schema: dict, server_name: str):
+        """
+        :param client: 该工具所属的 McpClient 实例
+        :param tool_schema: MCP 返回的工具描述，格式：
+            {"name": str, "description": str, "inputSchema": dict}
+        :param server_name: Server 名称，用于日志
+        """
+        self.client = client
+        self.server_name = server_name
+        self.name = tool_schema["name"]
+        self.description = tool_schema.get("description", "")
+        self.params = tool_schema.get("inputSchema", {})
+
+    def execute(self, params: dict) -> ToolResult:
+        logger.info(f"[McpTool] server={self.server_name} tool={self.name} params={params}")
+        try:
+            result = self.client.call_tool(self.name, params)
+            return ToolResult.success(result)
+        except Exception as e:
+            logger.error(f"[McpTool] server={self.server_name} tool={self.name} error: {e}")
+            return ToolResult.fail(str(e))
diff --git a/agent/tools/mcp/tool_retrieval.py b/agent/tools/mcp/tool_retrieval.py
new file mode 100644
index 0000000..1a9c8c0
--- /dev/null
+++ b/agent/tools/mcp/tool_retrieval.py
@@ -0,0 +1,159 @@
+# encoding:utf-8
+"""
+On-demand MCP tool retrieval.
+
+Pure, stateless selection helpers used by the streaming executor to decide
+which MCP tools to inject into a given LLM turn. Vector precompute + caching
+live in ToolManager (the tool-lifecycle owner, a process-wide singleton);
+only the context-aware selection lives here, because only the executor knows
+the conversation context.
+
+Invariants (per maintainer review of the feature proposal):
+  * Built-in tools are never handled here — the caller injects them in full.
+  * Any failure / missing input returns None so the caller falls back to
+    full injection; tools must never be silently dropped.
+  * Selection is union-accumulated across turns by the caller (only-grows),
+    so a tool that already produced a tool_use in the message history can
+    never disappear from the schema mid-run (which would make Claude/MiniMax
+    raise a message-format error).
+"""
+import math
+from typing import Dict, List, Optional, Sequence, Set
+
+try:
+    import numpy as np
+    _HAS_NUMPY = True
+except ImportError:
+    _HAS_NUMPY = False
+
+# How many trailing messages to concatenate into the retrieval query. Tool
+# needs drift across a multi-turn tool-call loop, so a single (initial) user
+# query is not enough; a short recent window captures the drift without
+# bloating the query with stale context.
+DEFAULT_QUERY_MESSAGES = 5
+
+
+def build_retrieval_query(messages: list, max_messages: int = DEFAULT_QUERY_MESSAGES) -> str:
+    """Concatenate the text of the most recent messages into a retrieval query.
+
+    Only ``text`` content blocks are kept; ``tool_use`` / ``tool_result`` blocks
+    are skipped so the query stays short and focused on natural-language intent
+    rather than large serialized tool payloads.
+
+    Args:
+        messages: Claude-style message list, each ``{"role", "content"}`` where
+            content is either a string or a list of typed blocks.
+        max_messages: Size of the trailing window to consider.
+
+    Returns:
+        A single string (possibly empty if no text is found).
+    """
+    if not messages:
+        return ""
+
+    parts: List[str] = []
+    for message in messages[-max_messages:]:
+        content = message.get("content") if isinstance(message, dict) else None
+        if isinstance(content, str):
+            if content.strip():
+                parts.append(content.strip())
+            continue
+        if isinstance(content, list):
+            for block in content:
+                if not isinstance(block, dict):
+                    continue
+                if block.get("type") == "text":
+                    text = block.get("text", "")
+                    if isinstance(text, str) and text.strip():
+                        parts.append(text.strip())
+    return "\n".join(parts)
+
+
+def cosine_similarity(a: Sequence[float], b: Sequence[float]) -> float:
+    """Cosine similarity of two equal-length vectors; 0.0 on degenerate input."""
+    if not a or not b or len(a) != len(b):
+        return 0.0
+    dot = sum(x * y for x, y in zip(a, b))
+    norm_a = math.sqrt(sum(x * x for x in a))
+    norm_b = math.sqrt(sum(y * y for y in b))
+    if norm_a == 0 or norm_b == 0:
+        return 0.0
+    return dot / (norm_a * norm_b)
+
+
+def select_mcp_tools(
+    query_vector: Optional[Sequence[float]],
+    tool_vectors: Dict[str, Sequence[float]],
+    top_k: int,
+    already_selected: Optional[Set[str]] = None,
+) -> Optional[Set[str]]:
+    """Return the accumulated set of MCP tool names to inject this turn.
+
+    Computes cosine similarity between ``query_vector`` and each candidate
+    tool vector, keeps the ``top_k`` best, and unions them with
+    ``already_selected`` so the injected set only ever grows within a run.
+
+    Args:
+        query_vector: Embedding of the current retrieval query, or None.
+        tool_vectors: ``{mcp_tool_name: vector}`` for candidate MCP tools.
+        top_k: Max number of tools to add from this turn's ranking.
+        already_selected: Names accumulated in previous turns of this run.
+
+    Returns:
+        The union set of tool names to inject, or None to signal
+        "fall back to full injection" (no query vector, empty/invalid index,
+        or any unexpected error). This function never raises.
+    """
+    accumulated: Set[str] = set(already_selected) if already_selected else set()
+
+    if not query_vector or not tool_vectors or top_k <= 0:
+        return None
+
+    try:
+        expected_dim = len(query_vector)
+        # Only rank candidates whose vector dimensionality matches the query.
+        # A dimension mismatch means the index was built with a different
+        # embedding model; ranking across dims is meaningless.
+        candidates = {
+            name: vec
+            for name, vec in tool_vectors.items()
+            if vec and len(vec) == expected_dim
+        }
+        if not candidates:
+            return None
+
+        ranked = _rank_by_similarity(query_vector, candidates)
+        for name, _score in ranked[:top_k]:
+            accumulated.add(name)
+        return accumulated
+    except Exception:
+        # Selection must never break the agent — fall back to full injection.
+        return None
+
+
+def _rank_by_similarity(
+    query_vector: Sequence[float],
+    candidates: Dict[str, Sequence[float]],
+) -> List[tuple]:
+    """Return ``[(name, score), ...]`` sorted by descending cosine similarity.
+
+    Uses numpy when available (vectorized, matching the memory-search path),
+    with a pure-Python fallback so the feature works without numpy installed.
+    """
+    names = list(candidates.keys())
+
+    if _HAS_NUMPY:
+        matrix = np.array([candidates[n] for n in names], dtype=np.float32)  # (N, D)
+        q_vec = np.array(query_vector, dtype=np.float32)                     # (D,)
+        dots = matrix @ q_vec                                                # (N,)
+        row_norms = np.linalg.norm(matrix, axis=1)                          # (N,)
+        q_norm = float(np.linalg.norm(q_vec))
+        denominators = row_norms * q_norm
+        np.maximum(denominators, 1e-10, out=denominators)                   # avoid div-by-zero
+        sims = dots / denominators
+        order = np.argsort(sims)[::-1]
+        return [(names[i], float(sims[i])) for i in order]
+
+    scored = [(n, cosine_similarity(query_vector, candidates[n])) for n in names]
+    scored.sort(key=lambda x: x[1], reverse=True)
+    return scored
diff --git a/agent/tools/memory/__init__.py b/agent/tools/memory/__init__.py
new file mode 100644
index 0000000..9a475bf
--- /dev/null
+++ b/agent/tools/memory/__init__.py
@@ -0,0 +1,10 @@
+"""
+Memory tools for Agent
+
+Provides memory_search and memory_get tools
+"""
+
+from agent.tools.memory.memory_search import MemorySearchTool
+from agent.tools.memory.memory_get import MemoryGetTool
+
+__all__ = ['MemorySearchTool', 'MemoryGetTool']
diff --git a/agent/tools/memory/memory_get.py b/agent/tools/memory/memory_get.py
new file mode 100644
index 0000000..53a05cc
--- /dev/null
+++ b/agent/tools/memory/memory_get.py
@@ -0,0 +1,135 @@
+"""
+Memory get tool
+
+Allows agents to read specific sections from memory files
+"""
+
+import os
+
+from agent.tools.base_tool import BaseTool
+
+
+class MemoryGetTool(BaseTool):
+    """Tool for reading memory file contents"""
+    
+    name: str = "memory_get"
+    description: str = (
+        "Read specific content from memory files. "
+        "Use this to get full context from a memory file or specific line range."
+    )
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Relative path to the memory file (e.g. 'MEMORY.md', 'memory/2026-01-01.md')"
+            },
+            "start_line": {
+                "type": "integer",
+                "description": "Starting line number (optional, default: 1)",
+                "default": 1
+            },
+            "num_lines": {
+                "type": "integer",
+                "description": "Number of lines to read (optional, reads all if not specified)"
+            }
+        },
+        "required": ["path"]
+    }
+    
+    def __init__(self, memory_manager):
+        """
+        Initialize memory get tool
+        
+        Args:
+            memory_manager: MemoryManager instance
+        """
+        super().__init__()
+        self.memory_manager = memory_manager
+
+        from config import conf
+        if conf().get("knowledge", True):
+            self.description = (
+                "Read specific content from memory or knowledge files. "
+                "Use this to get full context from a memory file, knowledge page, or specific line range."
+            )
+            self.params = {**self.params}
+            self.params["properties"] = {**self.params["properties"]}
+            self.params["properties"]["path"] = {
+                "type": "string",
+                "description": "Relative path to the memory or knowledge file (e.g. 'MEMORY.md', 'memory/2026-01-01.md', 'knowledge/concepts/moe.md')"
+            }
+    
+    def execute(self, args: dict):
+        """
+        Execute memory file read
+        
+        Args:
+            args: Dictionary with path, start_line, num_lines
+            
+        Returns:
+            ToolResult with file content
+        """
+        from agent.tools.base_tool import ToolResult
+        
+        path = args.get("path")
+        start_line = args.get("start_line", 1)
+        num_lines = args.get("num_lines")
+        
+        if not path:
+            return ToolResult.fail("Error: path parameter is required")
+        
+        try:
+            workspace_dir = self.memory_manager.config.get_workspace()
+            
+            # Auto-prepend memory/ if not present and not absolute path
+            # Exceptions: MEMORY.md in root, knowledge/ files at workspace root
+            if not path.startswith('memory/') and not path.startswith('knowledge/') and not path.startswith('/') and path != 'MEMORY.md':
+                path = f'memory/{path}'
+            
+            file_path = (workspace_dir / path).resolve()
+            workspace_resolved = workspace_dir.resolve()
+
+            # Use os.path.realpath + os.sep for cross-platform path validation.
+            # str(Path).startswith(str + '/') fails on Windows where Path uses
+            # backslashes — see MemoryService._resolve_path for the same pattern.
+            real_file = os.path.realpath(str(file_path))
+            real_workspace = os.path.realpath(str(workspace_resolved))
+            if real_file != real_workspace and not real_file.startswith(real_workspace + os.sep):
+                return ToolResult.fail(f"Error: Access denied: path outside workspace")
+            
+            if not file_path.exists():
+                return ToolResult.fail(f"Error: File not found: {path}")
+            
+            content = file_path.read_text(encoding='utf-8')
+            lines = content.split('\n')
+            
+            # Handle line range
+            if start_line < 1:
+                start_line = 1
+            
+            start_idx = start_line - 1
+            
+            if num_lines:
+                end_idx = start_idx + num_lines
+                selected_lines = lines[start_idx:end_idx]
+            else:
+                selected_lines = lines[start_idx:]
+            
+            result = '\n'.join(selected_lines)
+            
+            # Add metadata
+            total_lines = len(lines)
+            shown_lines = len(selected_lines)
+            
+            output = [
+                f"File: {path}",
+                f"Lines: {start_line}-{start_line + shown_lines - 1} (total: {total_lines})",
+                "",
+                result
+            ]
+            
+            return ToolResult.success('\n'.join(output))
+            
+        except Exception as e:
+            return ToolResult.fail(f"Error reading memory file: {str(e)}")
diff --git a/agent/tools/memory/memory_search.py b/agent/tools/memory/memory_search.py
new file mode 100644
index 0000000..1387d11
--- /dev/null
+++ b/agent/tools/memory/memory_search.py
@@ -0,0 +1,109 @@
+"""
+Memory search tool
+
+Allows agents to search their memory using semantic and keyword search
+"""
+
+from typing import Dict, Any, Optional
+from agent.tools.base_tool import BaseTool
+
+
+class MemorySearchTool(BaseTool):
+    """Tool for searching agent memory"""
+    
+    name: str = "memory_search"
+    description: str = (
+        "Search agent's long-term memory using semantic and keyword search. "
+        "Use this to recall past conversations, preferences, and knowledge."
+    )
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "query": {
+                "type": "string",
+                "description": "Search query (can be natural language question or keywords)"
+            },
+            "max_results": {
+                "type": "integer",
+                "description": "Maximum number of results to return (default: 10)",
+                "default": 10
+            },
+            "min_score": {
+                "type": "number",
+                "description": "Minimum relevance score (0-1, default: 0.1)",
+                "default": 0.1
+            }
+        },
+        "required": ["query"]
+    }
+    
+    def __init__(self, memory_manager, user_id: Optional[str] = None):
+        """
+        Initialize memory search tool
+        
+        Args:
+            memory_manager: MemoryManager instance
+            user_id: Optional user ID for scoped search
+        """
+        super().__init__()
+        self.memory_manager = memory_manager
+        self.user_id = user_id
+
+        from config import conf
+        if conf().get("knowledge", True):
+            self.description = (
+                "Search agent's long-term memory and knowledge base using semantic and keyword search. "
+                "Use this to recall past conversations, preferences, and knowledge pages."
+            )
+    
+    def execute(self, args: dict):
+        """
+        Execute memory search
+        
+        Args:
+            args: Dictionary with query, max_results, min_score
+            
+        Returns:
+            ToolResult with formatted search results
+        """
+        from agent.tools.base_tool import ToolResult
+        import asyncio
+        
+        query = args.get("query")
+        max_results = args.get("max_results", 10)
+        min_score = args.get("min_score", 0.1)
+        
+        if not query:
+            return ToolResult.fail("Error: query parameter is required")
+        
+        try:
+            # Run async search in sync context
+            results = asyncio.run(self.memory_manager.search(
+                query=query,
+                user_id=self.user_id,
+                max_results=max_results,
+                min_score=min_score,
+                include_shared=True
+            ))
+            
+            if not results:
+                # Return clear message that no memories exist yet
+                # This prevents infinite retry loops
+                return ToolResult.success(
+                    f"No memories found for '{query}'. "
+                    f"This is normal if no memories have been stored yet. "
+                    f"You can store new memories by writing to MEMORY.md or memory/YYYY-MM-DD.md files."
+                )
+            
+            # Format results
+            output = [f"Found {len(results)} relevant memories:\n"]
+            
+            for i, result in enumerate(results, 1):
+                output.append(f"\n{i}. {result.path} (lines {result.start_line}-{result.end_line})")
+                output.append(f"   Score: {result.score:.3f}")
+                output.append(f"   Snippet: {result.snippet}")
+            
+            return ToolResult.success("\n".join(output))
+            
+        except Exception as e:
+            return ToolResult.fail(f"Error searching memory: {str(e)}")
diff --git a/agent/tools/read/__init__.py b/agent/tools/read/__init__.py
new file mode 100644
index 0000000..4c974e9
--- /dev/null
+++ b/agent/tools/read/__init__.py
@@ -0,0 +1,3 @@
+from .read import Read
+
+__all__ = ['Read']
diff --git a/agent/tools/read/read.py b/agent/tools/read/read.py
new file mode 100644
index 0000000..9e5a0fe
--- /dev/null
+++ b/agent/tools/read/read.py
@@ -0,0 +1,594 @@
+"""
+Read tool - Read file contents
+Supports text files, images (jpg, png, gif, webp), and PDF files
+"""
+
+import os
+import re
+from typing import Dict, Any
+from pathlib import Path
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.utils.truncate import truncate_head, format_size, DEFAULT_MAX_LINES, DEFAULT_MAX_BYTES
+from common.utils import expand_path
+
+
+# Paths whose CONTENT mirrors the process environment (and thus any secrets
+# loaded from ~/.cow/.env). Reading them bypasses the env_config boundary.
+# Matches /proc/self/environ, /proc/thread-self/environ and /proc/<pid>/environ.
+_PROC_ENVIRON_RE = re.compile(r"^/proc/(\d+|self|thread-self)/environ$")
+
+
+class Read(BaseTool):
+    """Tool for reading file contents"""
+    
+    name: str = "read"
+    description: str = f"Read or inspect file contents. For text/PDF/Word/Excel/PPT files, returns content (truncated to {DEFAULT_MAX_LINES} lines or {DEFAULT_MAX_BYTES // 1024}KB). For images/videos/audio, returns metadata only (file info, size, type). Use offset/limit for large text files."
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Path to the file to read. IMPORTANT: Relative paths are based on workspace directory. To access files outside workspace, use absolute paths starting with ~ or /."
+            },
+            "offset": {
+                "type": "integer",
+                "description": "Line number to start reading from (1-indexed, optional). Use negative values to read from end (e.g. -20 for last 20 lines)"
+            },
+            "limit": {
+                "type": "integer",
+                "description": "Maximum number of lines to read (optional)"
+            }
+        },
+        "required": ["path"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        
+        # File type categories
+        self.image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.svg', '.ico'}
+        self.video_extensions = {'.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm', '.m4v'}
+        self.audio_extensions = {'.mp3', '.wav', '.ogg', '.m4a', '.flac', '.aac', '.wma'}
+        self.binary_extensions = {'.exe', '.dll', '.so', '.dylib', '.bin', '.dat', '.db', '.sqlite'}
+        self.archive_extensions = {'.zip', '.tar', '.gz', '.rar', '.7z', '.bz2', '.xz'}
+        self.pdf_extensions = {'.pdf'}
+        self.office_extensions = {'.doc', '.docx', '.xls', '.xlsx', '.ppt', '.pptx'}
+
+        # Readable text formats (will be read with truncation)
+        self.text_extensions = {
+            '.txt', '.md', '.markdown', '.rst', '.log', '.csv', '.tsv', '.json', '.xml', '.yaml', '.yml',
+            '.py', '.js', '.ts', '.java', '.c', '.cpp', '.h', '.hpp', '.go', '.rs', '.rb', '.php',
+            '.html', '.css', '.scss', '.sass', '.less', '.vue', '.jsx', '.tsx',
+            '.sh', '.bash', '.zsh', '.fish', '.ps1', '.bat', '.cmd',
+            '.sql', '.r', '.m', '.swift', '.kt', '.scala', '.clj', '.erl', '.ex',
+            '.dockerfile', '.makefile', '.cmake', '.gradle', '.properties', '.ini', '.conf', '.cfg',
+        }
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute file read operation
+        
+        :param args: Contains file path and optional offset/limit parameters
+        :return: File content or error message
+        """
+        # Support 'location' as alias for 'path' (LLM may use it from skill listing)
+        path = args.get("path", "") or args.get("location", "")
+        path = path.strip() if isinstance(path, str) else ""
+        offset = args.get("offset")
+        limit = args.get("limit")
+
+        if not path:
+            return ToolResult.fail("Error: path parameter is required")
+        
+        # Resolve path
+        absolute_path = self._resolve_path(path)
+        
+        # Security check: block credential files and their aliases.
+        # See issue #2913 (/proc/self/environ bypass) and #2863 (scope).
+        if self._is_credential_path(absolute_path):
+            return ToolResult.fail(
+                "Error: Access denied. API keys and credentials must be accessed through the env_config tool only."
+            )
+        
+        # Check if file exists
+        if not os.path.exists(absolute_path):
+            # Provide helpful hint if using relative path
+            if not os.path.isabs(path) and not path.startswith('~'):
+                return ToolResult.fail(
+                    f"Error: File not found: {path}\n"
+                    f"Resolved to: {absolute_path}\n"
+                    f"Hint: Relative paths are based on workspace ({self.cwd}). For files outside workspace, use absolute paths."
+                )
+            return ToolResult.fail(f"Error: File not found: {path}")
+        
+        # Check if readable
+        if not os.access(absolute_path, os.R_OK):
+            return ToolResult.fail(f"Error: File is not readable: {path}")
+        
+        # Check file type
+        file_ext = Path(absolute_path).suffix.lower()
+        file_size = os.path.getsize(absolute_path)
+        
+        # Check if image - return metadata for sending
+        if file_ext in self.image_extensions:
+            return self._read_image(absolute_path, file_ext)
+        
+        # Check if video/audio/binary/archive - return metadata only
+        if file_ext in self.video_extensions:
+            return self._return_file_metadata(absolute_path, "video", file_size)
+        if file_ext in self.audio_extensions:
+            return self._return_file_metadata(absolute_path, "audio", file_size)
+        if file_ext in self.binary_extensions or file_ext in self.archive_extensions:
+            return self._return_file_metadata(absolute_path, "binary", file_size)
+        
+        # Check if PDF
+        if file_ext in self.pdf_extensions:
+            return self._read_pdf(absolute_path, path, offset, limit)
+
+        # Check if Office document (.docx, .xlsx, .pptx, etc.)
+        if file_ext in self.office_extensions:
+            return self._read_office(absolute_path, path, file_ext, offset, limit)
+
+        # Read text file (with truncation for large files)
+        return self._read_text(absolute_path, path, offset, limit)
+    
+    def _resolve_path(self, path: str) -> str:
+        """
+        Resolve path to absolute path
+        
+        :param path: Relative or absolute path
+        :return: Absolute path
+        """
+        # Expand ~ to user home directory
+        path = expand_path(path)
+        if os.path.isabs(path):
+            return path
+        return os.path.abspath(os.path.join(self.cwd, path))
+
+    def _is_credential_path(self, absolute_path: str) -> bool:
+        """Return True if *absolute_path* points at protected credential data.
+
+        Beyond the literal ~/.cow/.env file, this also blocks two real bypass
+        surfaces reported in issue #2913:
+          1. /proc/<pid|self|thread-self>/environ — a second view of the
+             process environment that leaks secrets loaded from ~/.cow/.env.
+          2. Symlinks resolving to ~/.cow/.env; the previous exact abspath
+             match kept the link target and could be bypassed.
+
+        Scope is kept deliberately narrow (only the credential file and its
+        environ aliases) so this does NOT re-broaden the block that #2863
+        intentionally narrowed to ~/.cow/.env.
+        """
+        # Compare on both the normalized path and the symlink-resolved path,
+        # in POSIX form so the /proc regex matches regardless of os.sep.
+        candidates = set()
+        try:
+            candidates.add(os.path.normpath(absolute_path).replace(os.sep, "/"))
+            candidates.add(os.path.realpath(absolute_path).replace(os.sep, "/"))
+        except OSError:
+            candidates.add(absolute_path.replace(os.sep, "/"))
+
+        # 1. /proc environ aliases (checked on raw and symlink-resolved forms).
+        for candidate in candidates:
+            if _PROC_ENVIRON_RE.match(candidate):
+                return True
+
+        # 2. The credential file itself, following symlinks on both sides.
+        env_real = os.path.realpath(expand_path("~/.cow/.env")).replace(os.sep, "/")
+        return env_real in candidates
+
+    def _return_file_metadata(self, absolute_path: str, file_type: str, file_size: int) -> ToolResult:
+        """
+        Return file metadata for non-readable files (video, audio, binary, etc.)
+        
+        :param absolute_path: Absolute path to the file
+        :param file_type: Type of file (video, audio, binary, etc.)
+        :param file_size: File size in bytes
+        :return: File metadata
+        """
+        file_name = Path(absolute_path).name
+        file_ext = Path(absolute_path).suffix.lower()
+        
+        # Determine MIME type
+        mime_types = {
+            # Video
+            '.mp4': 'video/mp4', '.avi': 'video/x-msvideo', '.mov': 'video/quicktime',
+            '.mkv': 'video/x-matroska', '.webm': 'video/webm',
+            # Audio
+            '.mp3': 'audio/mpeg', '.wav': 'audio/wav', '.ogg': 'audio/ogg',
+            '.m4a': 'audio/mp4', '.flac': 'audio/flac',
+            # Binary
+            '.zip': 'application/zip', '.tar': 'application/x-tar',
+            '.gz': 'application/gzip', '.rar': 'application/x-rar-compressed',
+        }
+        mime_type = mime_types.get(file_ext, 'application/octet-stream')
+        
+        result = {
+            "type": f"{file_type}_metadata",
+            "file_type": file_type,
+            "path": absolute_path,
+            "file_name": file_name,
+            "mime_type": mime_type,
+            "size": file_size,
+            "size_formatted": format_size(file_size),
+            "message": f"{file_type.capitalize()} 文件: {file_name} ({format_size(file_size)})\n提示: 如果需要发送此文件，请使用 send 工具。"
+        }
+        
+        return ToolResult.success(result)
+    
+    def _read_image(self, absolute_path: str, file_ext: str) -> ToolResult:
+        """
+        Read image file - always return metadata only (images should be sent, not read into context)
+        
+        :param absolute_path: Absolute path to the image file
+        :param file_ext: File extension
+        :return: Result containing image metadata for sending
+        """
+        try:
+            # Get file size
+            file_size = os.path.getsize(absolute_path)
+            
+            # Determine MIME type
+            mime_type_map = {
+                '.jpg': 'image/jpeg',
+                '.jpeg': 'image/jpeg',
+                '.png': 'image/png',
+                '.gif': 'image/gif',
+                '.webp': 'image/webp'
+            }
+            mime_type = mime_type_map.get(file_ext, 'image/jpeg')
+            
+            # Return metadata for images (NOT file_to_send - use send tool to actually send)
+            result = {
+                "type": "image_metadata",
+                "file_type": "image",
+                "path": absolute_path,
+                "mime_type": mime_type,
+                "size": file_size,
+                "size_formatted": format_size(file_size),
+                "message": f"图片文件: {Path(absolute_path).name} ({format_size(file_size)})\n提示: 如果需要发送此图片，请使用 send 工具。"
+            }
+            
+            return ToolResult.success(result)
+            
+        except Exception as e:
+            return ToolResult.fail(f"Error reading image file: {str(e)}")
+    
+    def _read_text(self, absolute_path: str, display_path: str, offset: int = None, limit: int = None) -> ToolResult:
+        """
+        Read text file
+        
+        :param absolute_path: Absolute path to the file
+        :param display_path: Path to display
+        :param offset: Starting line number (1-indexed)
+        :param limit: Maximum number of lines to read
+        :return: File content or error message
+        """
+        try:
+            # Check file size first
+            file_size = os.path.getsize(absolute_path)
+            MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
+            
+            if file_size > MAX_FILE_SIZE:
+                # File too large, return metadata only
+                return ToolResult.success({
+                    "type": "file_to_send",
+                    "file_type": "document",
+                    "path": absolute_path,
+                    "size": file_size,
+                    "size_formatted": format_size(file_size),
+                    "message": f"文件过大 ({format_size(file_size)} > 50MB)，无法读取内容。文件路径: {absolute_path}"
+                })
+            
+            # Read file (utf-8-sig strips BOM automatically on Windows)
+            # Note: Truncation is unified via truncate_head (DEFAULT_MAX_LINES / DEFAULT_MAX_BYTES)
+            # so that offset/limit can paginate the entire file correctly.
+            with open(absolute_path, 'r', encoding='utf-8-sig') as f:
+                content = f.read()
+
+            all_lines = content.split('\n')
+            total_file_lines = len(all_lines)
+            
+            # Apply offset (if specified)
+            start_line = 0
+            if offset is not None:
+                if offset < 0:
+                    # Negative offset: read from end
+                    # -20 means "last 20 lines" → start from (total - 20).
+                    # A file ending in "\n" produces a trailing empty element
+                    # from split('\n'); exclude it so offset=-1 returns the
+                    # real last line instead of the empty string after the
+                    # final newline (and -N returns N real lines).
+                    effective_lines = total_file_lines
+                    if all_lines and all_lines[-1] == '':
+                        effective_lines -= 1
+                    start_line = max(0, effective_lines + offset)
+                else:
+                    # Positive offset: read from start (1-indexed)
+                    start_line = max(0, offset - 1)  # Convert to 0-indexed
+                    if start_line >= total_file_lines:
+                        return ToolResult.fail(
+                            f"Error: Offset {offset} is beyond end of file ({total_file_lines} lines total)"
+                        )
+            
+            start_line_display = start_line + 1  # For display (1-indexed)
+            
+            # If user specified limit, use it
+            selected_content = content
+            user_limited_lines = None
+            if limit is not None:
+                end_line = min(start_line + limit, total_file_lines)
+                selected_content = '\n'.join(all_lines[start_line:end_line])
+                user_limited_lines = end_line - start_line
+            elif offset is not None:
+                selected_content = '\n'.join(all_lines[start_line:])
+            
+            # Apply truncation (considering line count and byte limits)
+            truncation = truncate_head(selected_content)
+            
+            output_text = ""
+            details = {}
+
+            if truncation.first_line_exceeds_limit:
+                # First line exceeds 30KB limit
+                first_line_size = format_size(len(all_lines[start_line].encode('utf-8')))
+                output_text = f"[Line {start_line_display} is {first_line_size}, exceeds {format_size(DEFAULT_MAX_BYTES)} limit. Use bash tool to read: head -c {DEFAULT_MAX_BYTES} {display_path} | tail -n +{start_line_display}]"
+                details["truncation"] = truncation.to_dict()
+            elif truncation.truncated:
+                # Truncation occurred
+                end_line_display = start_line_display + truncation.output_lines - 1
+                next_offset = end_line_display + 1
+                
+                output_text = truncation.content
+                
+                if truncation.truncated_by == "lines":
+                    output_text += f"\n\n[Showing lines {start_line_display}-{end_line_display} of {total_file_lines}. Use offset={next_offset} to continue.]"
+                else:
+                    output_text += f"\n\n[Showing lines {start_line_display}-{end_line_display} of {total_file_lines} ({format_size(DEFAULT_MAX_BYTES)} limit). Use offset={next_offset} to continue.]"
+                
+                details["truncation"] = truncation.to_dict()
+            elif user_limited_lines is not None and start_line + user_limited_lines < total_file_lines:
+                # User specified limit, more content available, but no truncation
+                remaining = total_file_lines - (start_line + user_limited_lines)
+                next_offset = start_line + user_limited_lines + 1
+                
+                output_text = truncation.content
+                output_text += f"\n\n[{remaining} more lines in file. Use offset={next_offset} to continue.]"
+            else:
+                # No truncation, no exceeding user limit
+                output_text = truncation.content
+            
+            result = {
+                "content": output_text,
+                "total_lines": total_file_lines,
+                "start_line": start_line_display,
+                "output_lines": truncation.output_lines
+            }
+            
+            if details:
+                result["details"] = details
+            
+            return ToolResult.success(result)
+            
+        except UnicodeDecodeError:
+            return ToolResult.fail(f"Error: File is not a valid text file (encoding error): {display_path}")
+        except Exception as e:
+            return ToolResult.fail(f"Error reading file: {str(e)}")
+    
+    def _read_office(self, absolute_path: str, display_path: str, file_ext: str,
+                     offset: int = None, limit: int = None) -> ToolResult:
+        """Read Office documents (.docx, .xlsx, .pptx) using python-docx / openpyxl / python-pptx."""
+        try:
+            text = self._extract_office_text(absolute_path, file_ext)
+        except ImportError as e:
+            return ToolResult.fail(str(e))
+        except Exception as e:
+            return ToolResult.fail(f"Error reading Office document: {e}")
+
+        if not text or not text.strip():
+            return ToolResult.success({
+                "content": f"[Office file {Path(absolute_path).name}: no text content could be extracted]",
+            })
+
+        all_lines = text.split('\n')
+        total_lines = len(all_lines)
+
+        start_line = 0
+        if offset is not None:
+            if offset < 0:
+                start_line = max(0, total_lines + offset)
+            else:
+                start_line = max(0, offset - 1)
+                if start_line >= total_lines:
+                    return ToolResult.fail(
+                        f"Error: Offset {offset} is beyond end of content ({total_lines} lines total)"
+                    )
+
+        selected_content = text
+        user_limited_lines = None
+        if limit is not None:
+            end_line = min(start_line + limit, total_lines)
+            selected_content = '\n'.join(all_lines[start_line:end_line])
+            user_limited_lines = end_line - start_line
+        elif offset is not None:
+            selected_content = '\n'.join(all_lines[start_line:])
+
+        truncation = truncate_head(selected_content)
+        start_line_display = start_line + 1
+        output_text = ""
+
+        if truncation.truncated:
+            end_line_display = start_line_display + truncation.output_lines - 1
+            next_offset = end_line_display + 1
+            output_text = truncation.content
+            output_text += f"\n\n[Showing lines {start_line_display}-{end_line_display} of {total_lines}. Use offset={next_offset} to continue.]"
+        elif user_limited_lines is not None and start_line + user_limited_lines < total_lines:
+            remaining = total_lines - (start_line + user_limited_lines)
+            next_offset = start_line + user_limited_lines + 1
+            output_text = truncation.content
+            output_text += f"\n\n[{remaining} more lines in file. Use offset={next_offset} to continue.]"
+        else:
+            output_text = truncation.content
+
+        return ToolResult.success({
+            "content": output_text,
+            "total_lines": total_lines,
+            "start_line": start_line_display,
+            "output_lines": truncation.output_lines,
+        })
+
+    @staticmethod
+    def _extract_office_text(absolute_path: str, file_ext: str) -> str:
+        """Extract plain text from an Office document."""
+        if file_ext in ('.docx', '.doc'):
+            try:
+                from docx import Document
+            except ImportError:
+                raise ImportError("Error: python-docx library not installed. Install with: pip install python-docx")
+            doc = Document(absolute_path)
+            paragraphs = [p.text for p in doc.paragraphs]
+            for table in doc.tables:
+                for row in table.rows:
+                    paragraphs.append('\t'.join(cell.text for cell in row.cells))
+            return '\n'.join(paragraphs)
+
+        if file_ext in ('.xlsx', '.xls'):
+            try:
+                from openpyxl import load_workbook
+            except ImportError:
+                raise ImportError("Error: openpyxl library not installed. Install with: pip install openpyxl")
+            wb = load_workbook(absolute_path, read_only=True, data_only=True)
+            parts = []
+            for ws in wb.worksheets:
+                parts.append(f"--- Sheet: {ws.title} ---")
+                for row in ws.iter_rows(values_only=True):
+                    parts.append('\t'.join(str(c) if c is not None else '' for c in row))
+            wb.close()
+            return '\n'.join(parts)
+
+        if file_ext in ('.pptx', '.ppt'):
+            try:
+                from pptx import Presentation
+            except ImportError:
+                raise ImportError("Error: python-pptx library not installed. Install with: pip install python-pptx")
+            prs = Presentation(absolute_path)
+            parts = []
+            for i, slide in enumerate(prs.slides, 1):
+                parts.append(f"--- Slide {i} ---")
+                for shape in slide.shapes:
+                    if shape.has_text_frame:
+                        for para in shape.text_frame.paragraphs:
+                            text = para.text.strip()
+                            if text:
+                                parts.append(text)
+            return '\n'.join(parts)
+
+        return ""
+
+    def _read_pdf(self, absolute_path: str, display_path: str, offset: int = None, limit: int = None) -> ToolResult:
+        """
+        Read PDF file content
+        
+        :param absolute_path: Absolute path to the file
+        :param display_path: Path to display
+        :param offset: Starting line number (1-indexed)
+        :param limit: Maximum number of lines to read
+        :return: PDF text content or error message
+        """
+        try:
+            # Try to import pypdf
+            try:
+                from pypdf import PdfReader
+            except ImportError:
+                return ToolResult.fail(
+                    "Error: pypdf library not installed. Install with: pip install pypdf"
+                )
+            
+            # Read PDF
+            reader = PdfReader(absolute_path)
+            total_pages = len(reader.pages)
+            
+            # Extract text from all pages
+            text_parts = []
+            for page_num, page in enumerate(reader.pages, 1):
+                page_text = page.extract_text()
+                if page_text.strip():
+                    text_parts.append(f"--- Page {page_num} ---\n{page_text}")
+            
+            if not text_parts:
+                return ToolResult.success({
+                    "content": f"[PDF file with {total_pages} pages, but no text content could be extracted]",
+                    "total_pages": total_pages,
+                    "message": "PDF may contain only images or be encrypted"
+                })
+            
+            # Merge all text
+            full_content = "\n\n".join(text_parts)
+            all_lines = full_content.split('\n')
+            total_lines = len(all_lines)
+            
+            # Apply offset and limit (same logic as text files)
+            start_line = 0
+            if offset is not None:
+                start_line = max(0, offset - 1)
+                if start_line >= total_lines:
+                    return ToolResult.fail(
+                        f"Error: Offset {offset} is beyond end of content ({total_lines} lines total)"
+                    )
+            
+            start_line_display = start_line + 1
+            
+            selected_content = full_content
+            user_limited_lines = None
+            if limit is not None:
+                end_line = min(start_line + limit, total_lines)
+                selected_content = '\n'.join(all_lines[start_line:end_line])
+                user_limited_lines = end_line - start_line
+            elif offset is not None:
+                selected_content = '\n'.join(all_lines[start_line:])
+            
+            # Apply truncation
+            truncation = truncate_head(selected_content)
+            
+            output_text = ""
+            details = {}
+            
+            if truncation.truncated:
+                end_line_display = start_line_display + truncation.output_lines - 1
+                next_offset = end_line_display + 1
+                
+                output_text = truncation.content
+                
+                if truncation.truncated_by == "lines":
+                    output_text += f"\n\n[Showing lines {start_line_display}-{end_line_display} of {total_lines}. Use offset={next_offset} to continue.]"
+                else:
+                    output_text += f"\n\n[Showing lines {start_line_display}-{end_line_display} of {total_lines} ({format_size(DEFAULT_MAX_BYTES)} limit). Use offset={next_offset} to continue.]"
+                
+                details["truncation"] = truncation.to_dict()
+            elif user_limited_lines is not None and start_line + user_limited_lines < total_lines:
+                remaining = total_lines - (start_line + user_limited_lines)
+                next_offset = start_line + user_limited_lines + 1
+                
+                output_text = truncation.content
+                output_text += f"\n\n[{remaining} more lines in file. Use offset={next_offset} to continue.]"
+            else:
+                output_text = truncation.content
+            
+            result = {
+                "content": output_text,
+                "total_pages": total_pages,
+                "total_lines": total_lines,
+                "start_line": start_line_display,
+                "output_lines": truncation.output_lines
+            }
+            
+            if details:
+                result["details"] = details
+            
+            return ToolResult.success(result)
+            
+        except Exception as e:
+            return ToolResult.fail(f"Error reading PDF file: {str(e)}")
diff --git a/agent/tools/scheduler/README.md b/agent/tools/scheduler/README.md
new file mode 100644
index 0000000..55be2f9
--- /dev/null
+++ b/agent/tools/scheduler/README.md
@@ -0,0 +1,287 @@
+# 定时任务工具 (Scheduler Tool)
+
+## 功能简介
+
+定时任务工具允许 Agent 创建、管理和执行定时任务，支持：
+
+- ⏰ **定时提醒**: 在指定时间发送消息
+- 🔄 **周期性任务**: 按固定间隔或 cron 表达式重复执行
+- 🔧 **动态工具调用**: 定时执行其他工具并发送结果（如搜索新闻、查询天气等）
+- 📋 **任务管理**: 查询、启用、禁用、删除任务
+
+## 安装依赖
+
+```bash
+pip install croniter>=2.0.0
+```
+
+## 使用方法
+
+### 1. 创建定时任务
+
+Agent 可以通过自然语言创建定时任务，支持两种类型：
+
+#### 1.1 静态消息任务
+
+发送预定义的消息：
+
+**示例对话：**
+```
+用户: 每天早上9点提醒我开会
+Agent: [调用 scheduler 工具]
+      action: create
+      name: 每日开会提醒
+      message: 该开会了！
+      schedule_type: cron
+      schedule_value: 0 9 * * *
+```
+
+#### 1.2 动态工具调用任务
+
+定时执行工具并发送结果：
+
+**示例对话：**
+```
+用户: 每天早上8点帮我读取一下今日日程
+Agent: [调用 scheduler 工具]
+      action: create
+      name: 每日日程
+      tool_call:
+        tool_name: read
+        tool_params:
+          file_path: ~/cow/schedule.txt
+        result_prefix: 📅 今日日程
+      schedule_type: cron
+      schedule_value: 0 8 * * *
+```
+
+**工具调用参数说明：**
+- `tool_name`: 要调用的工具名称（如 `bash`、`read`、`write` 等内置工具）
+- `tool_params`: 工具的参数（字典格式）
+- `result_prefix`: 可选，在结果前添加的前缀文本
+
+**注意：** 如果要使用 skills（如 bocha-search），需要通过 `bash` 工具调用 skill 脚本
+
+### 2. 支持的调度类型
+
+#### Cron 表达式 (`cron`)
+使用标准 cron 表达式：
+
+```
+0 9 * * *      # 每天 9:00
+0 */2 * * *    # 每 2 小时
+30 8 * * 1-5   # 工作日 8:30
+0 0 1 * *      # 每月 1 号
+```
+
+#### 固定间隔 (`interval`)
+以秒为单位的间隔：
+
+```
+3600           # 每小时
+86400          # 每天
+1800           # 每 30 分钟
+```
+
+#### 一次性任务 (`once`)
+指定具体时间（ISO 格式）：
+
+```
+2024-12-25T09:00:00
+2024-12-31T23:59:59
+```
+
+### 3. 查询任务列表
+
+```
+用户: 查看我的定时任务
+Agent: [调用 scheduler 工具]
+      action: list
+```
+
+### 4. 查看任务详情
+
+```
+用户: 查看任务 abc123 的详情
+Agent: [调用 scheduler 工具]
+      action: get
+      task_id: abc123
+```
+
+### 5. 删除任务
+
+```
+用户: 删除任务 abc123
+Agent: [调用 scheduler 工具]
+      action: delete
+      task_id: abc123
+```
+
+### 6. 启用/禁用任务
+
+```
+用户: 暂停任务 abc123
+Agent: [调用 scheduler 工具]
+      action: disable
+      task_id: abc123
+
+用户: 恢复任务 abc123
+Agent: [调用 scheduler 工具]
+      action: enable
+      task_id: abc123
+```
+
+## 任务存储
+
+任务保存在 JSON 文件中：
+```
+~/cow/scheduler/tasks.json
+```
+
+任务数据结构：
+
+**静态消息任务：**
+```json
+{
+  "id": "abc123",
+  "name": "每日提醒",
+  "enabled": true,
+  "created_at": "2024-01-01T10:00:00",
+  "updated_at": "2024-01-01T10:00:00",
+  "schedule": {
+    "type": "cron",
+    "expression": "0 9 * * *"
+  },
+  "action": {
+    "type": "send_message",
+    "content": "该开会了！",
+    "receiver": "wxid_xxx",
+    "receiver_name": "张三",
+    "is_group": false,
+    "channel_type": "wechat"
+  },
+  "next_run_at": "2024-01-02T09:00:00",
+  "last_run_at": "2024-01-01T09:00:00"
+}
+```
+
+**动态工具调用任务：**
+```json
+{
+  "id": "def456",
+  "name": "每日日程",
+  "enabled": true,
+  "created_at": "2024-01-01T10:00:00",
+  "updated_at": "2024-01-01T10:00:00",
+  "schedule": {
+    "type": "cron",
+    "expression": "0 8 * * *"
+  },
+  "action": {
+    "type": "tool_call",
+    "tool_name": "read",
+    "tool_params": {
+      "file_path": "~/cow/schedule.txt"
+    },
+    "result_prefix": "📅 今日日程",
+    "receiver": "wxid_xxx",
+    "receiver_name": "张三",
+    "is_group": false,
+    "channel_type": "wechat"
+  },
+  "next_run_at": "2024-01-02T08:00:00"
+}
+```
+
+## 后台服务
+
+定时任务由后台服务 `SchedulerService` 管理：
+
+- 每 30 秒检查一次到期任务
+- 自动执行到期任务
+- 计算下次执行时间
+- 记录执行历史和错误
+
+服务在 Agent 初始化时自动启动，无需手动配置。
+
+## 接收者确定
+
+定时任务会发送给**创建任务时的对话对象**：
+
+- 如果在私聊中创建，发送给该用户
+- 如果在群聊中创建，发送到该群
+- 接收者信息在创建时自动保存
+
+## 常见用例
+
+### 1. 每日提醒（静态消息）
+```
+用户: 每天早上8点提醒我吃药
+Agent: ✅ 定时任务创建成功
+       任务ID: a1b2c3d4
+       调度: 每天 8:00
+       消息: 该吃药了！
+```
+
+### 2. 工作日提醒（静态消息）
+```
+用户: 工作日下午6点提醒我下班
+Agent: [创建 cron: 0 18 * * 1-5]
+       消息: 该下班了！
+```
+
+### 3. 倒计时提醒（静态消息）
+```
+用户: 1小时后提醒我
+Agent: [创建 interval: 3600]
+```
+
+### 4. 每日日程推送（动态工具调用）
+```
+用户: 每天早上8点帮我读取今日日程
+Agent: ✅ 定时任务创建成功
+       任务ID: schedule001
+       调度: 每天 8:00
+       工具: read(file_path='~/cow/schedule.txt')
+       前缀: 📅 今日日程
+```
+
+### 5. 定时文件备份（动态工具调用）
+```
+用户: 每天晚上11点备份工作文件
+Agent: [创建 cron: 0 23 * * *]
+       工具: bash(command='cp ~/cow/work.txt ~/cow/backup/work_$(date +%Y%m%d).txt')
+       前缀: ✅ 文件已备份
+```
+
+### 6. 周报提醒（静态消息）
+```
+用户: 每周五下午5点提醒我写周报
+Agent: [创建 cron: 0 17 * * 5]
+       消息: 📊 该写周报了！
+```
+
+### 4. 特定日期提醒
+```
+用户: 12月25日早上9点提醒我圣诞快乐
+Agent: [创建 once: 2024-12-25T09:00:00]
+```
+
+## 注意事项
+
+1. **时区**: 使用系统本地时区
+2. **精度**: 检查间隔为 30 秒，实际执行可能有 ±30 秒误差
+3. **持久化**: 任务保存在文件中，重启后自动恢复
+4. **一次性任务**: 执行后自动禁用，不会删除（可手动删除）
+5. **错误处理**: 执行失败会记录错误，不影响其他任务
+
+## 技术实现
+
+- **TaskStore**: 任务持久化存储
+- **SchedulerService**: 后台调度服务
+- **SchedulerTool**: Agent 工具接口
+- **Integration**: 与 AgentBridge 集成
+
+## 依赖
+
+- `croniter`: Cron 表达式解析（轻量级，仅 ~50KB）
diff --git a/agent/tools/scheduler/__init__.py b/agent/tools/scheduler/__init__.py
new file mode 100644
index 0000000..dafc8b6
--- /dev/null
+++ b/agent/tools/scheduler/__init__.py
@@ -0,0 +1,7 @@
+"""
+Scheduler tool for managing scheduled tasks
+"""
+
+from .scheduler_tool import SchedulerTool
+
+__all__ = ["SchedulerTool"]
diff --git a/agent/tools/scheduler/integration.py b/agent/tools/scheduler/integration.py
new file mode 100644
index 0000000..7421a52
--- /dev/null
+++ b/agent/tools/scheduler/integration.py
@@ -0,0 +1,548 @@
+"""
+Integration module for scheduler with AgentBridge
+"""
+
+import os
+import threading
+from typing import Optional
+from config import conf
+from common.log import logger
+from common.utils import expand_path
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+
+# Global scheduler service instance
+_scheduler_service = None
+_task_store = None
+# Module-level lock to guard idempotent initialization across threads
+_init_lock = threading.Lock()
+
+
+def init_scheduler(agent_bridge) -> bool:
+    """
+    Initialize scheduler service (idempotent).
+
+    Safe to call multiple times and from multiple threads: only the first
+    successful call creates the singleton ``SchedulerService`` + background
+    scanning thread. Subsequent calls return immediately.
+
+    Args:
+        agent_bridge: AgentBridge instance
+
+    Returns:
+        True if scheduler is initialized (newly created or already running)
+    """
+    global _scheduler_service, _task_store
+
+    # Fast path: already initialized and running
+    if _scheduler_service is not None and getattr(_scheduler_service, "running", False):
+        return True
+
+    with _init_lock:
+        # Re-check under the lock to avoid races where multiple threads
+        # passed the fast-path check before any of them acquired the lock.
+        if _scheduler_service is not None and getattr(_scheduler_service, "running", False):
+            return True
+
+        try:
+            from agent.tools.scheduler.task_store import TaskStore
+            from agent.tools.scheduler.scheduler_service import SchedulerService
+
+            # Get workspace from config
+            workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+            store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+
+            # Create task store (reuse if already created)
+            if _task_store is None:
+                _task_store = TaskStore(store_path)
+                logger.debug(f"[Scheduler] Task store initialized: {store_path}")
+
+            # Create execute callback. Returns True on success, False to ask
+            # the scheduler to retry on the next tick (e.g. channel not yet
+            # ready right after process start).
+            def execute_task_callback(task: dict):
+                try:
+                    action = task.get("action", {})
+                    action_type = action.get("type")
+                    channel_type = action.get("channel_type", "unknown")
+                    receiver = action.get("receiver", "")
+
+                    if not _is_channel_ready(channel_type, receiver):
+                        logger.warning(
+                            f"[Scheduler] Task {task.get('id')}: channel "
+                            f"'{channel_type}' not ready for receiver={receiver} "
+                            f"(no inbound msg cached since restart?); deferring"
+                        )
+                        return False
+
+                    if action_type == "agent_task":
+                        return _execute_agent_task(task, agent_bridge)
+                    elif action_type == "send_message":
+                        return _execute_send_message(task, agent_bridge)
+                    elif action_type == "tool_call":
+                        return _execute_tool_call(task, agent_bridge)
+                    elif action_type == "skill_call":
+                        return _execute_skill_call(task, agent_bridge)
+                    else:
+                        logger.warning(f"[Scheduler] Unknown action type: {action_type}")
+                        return True
+                except Exception as e:
+                    logger.error(f"[Scheduler] Error executing task {task.get('id')}: {e}")
+                    return False
+
+            # Create scheduler service
+            _scheduler_service = SchedulerService(_task_store, execute_task_callback)
+            _scheduler_service.start()
+
+            logger.info("[Scheduler] Service initialized and started")
+            return True
+
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to initialize scheduler: {e}")
+            return False
+
+
+def _is_channel_ready(channel_type: str, receiver: str) -> bool:
+    """Best-effort readiness probe for outbound channels.
+
+    Returns False when we know the send will drop (e.g. weixin not yet
+    logged in, web session has no polling queue), so the scheduler can
+    defer instead of consuming the task. Unknown channels return True
+    to preserve previous behaviour.
+    """
+    if not channel_type or channel_type == "unknown":
+        return True
+    try:
+        from channel.channel_factory import create_channel
+        channel = create_channel(channel_type)
+        if channel is None:
+            return False
+
+        if channel_type == "weixin":
+            tokens = getattr(channel, "_context_tokens", None)
+            if not tokens or receiver not in tokens:
+                return False
+            return True
+
+        if channel_type == "web":
+            queues = getattr(channel, "session_queues", None)
+            if not queues or receiver not in queues:
+                return False
+            return True
+
+        return True
+    except Exception as e:
+        logger.warning(f"[Scheduler] Channel readiness check failed for {channel_type}: {e}")
+        return True
+
+
+def get_task_store():
+    """Get the global task store instance"""
+    return _task_store
+
+
+def get_scheduler_service():
+    """Get the global scheduler service instance"""
+    return _scheduler_service
+
+
+def _remember_delivered_output(
+    agent_bridge,
+    task: dict,
+    channel_type: str,
+    content: str,
+) -> None:
+    """Best-effort persistence of the message the scheduler sent to a user.
+
+    Uses notify_session_id (the real chat session_id stored at task creation time)
+    so that group chats correctly associate the output with the user's conversation.
+    Falls back to receiver for backward compatibility with old tasks.
+
+    Per-action-type behaviour:
+        - agent_task / tool_call / skill_call: gated by ``scheduler_inject_to_session``
+          (default True). These produce AI-generated content worth remembering.
+        - send_message: additionally gated by ``scheduler_inject_send_message``
+          (default False). Fixed reminder text rarely benefits follow-up Q&A and
+          would just consume context tokens.
+    """
+    if not content:
+        return
+    action = task.get("action", {})
+    action_type = action.get("type", "")
+
+    # send_message defaults to NOT being injected; explicit opt-in via config.
+    if action_type == "send_message":
+        if not conf().get("scheduler_inject_send_message", False):
+            return
+
+    session_id = action.get("notify_session_id") or action.get("receiver")
+    if not session_id:
+        return
+    try:
+        remember = getattr(agent_bridge, "remember_scheduled_output", None)
+        if remember:
+            task_desc = action.get("task_description") or action.get("content", "")
+            remember(session_id, str(content), channel_type=channel_type, task_description=task_desc)
+    except Exception as e:
+        logger.warning(
+            f"[Scheduler] Failed to remember delivered output for {session_id}: {e}"
+        )
+
+
+def _execute_agent_task(task: dict, agent_bridge) -> bool:
+    """
+    Execute an agent_task action - let Agent handle the task.
+    Returns True on successful delivery, False to retry next tick.
+    """
+    try:
+        action = task.get("action", {})
+        task_description = action.get("task_description")
+        receiver = action.get("receiver")
+        is_group = action.get("is_group", False)
+        channel_type = action.get("channel_type", "unknown")
+        
+        if not task_description:
+            logger.error(f"[Scheduler] Task {task['id']}: No task_description specified")
+            return True  # malformed task, don't loop forever
+        
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return True
+        
+        # Check for unsupported channels
+        if channel_type == "dingtalk":
+            logger.warning(f"[Scheduler] Task {task['id']}: DingTalk channel does not support scheduled messages (Stream mode limitation). Task will execute but message cannot be sent.")
+        
+        logger.info(f"[Scheduler] Task {task['id']}: Executing agent task '{task_description}'")
+        
+        # Create a unique session_id for this scheduled task to avoid polluting user's conversation
+        # Format: scheduler_<receiver>_<task_id> to ensure isolation
+        scheduler_session_id = f"scheduler_{receiver}_{task['id']}"
+        
+        # Create context for Agent
+        context = Context(ContextType.TEXT, task_description)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = scheduler_session_id
+        
+        # Channel-specific setup
+        if channel_type == "web":
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+        elif channel_type == "feishu":
+            context["receive_id_type"] = "chat_id" if is_group else "open_id"
+            context["msg"] = None
+        elif channel_type == "dingtalk":
+            # DingTalk requires msg object, set to None for scheduled tasks
+            context["msg"] = None
+            if not is_group:
+                sender_staff_id = action.get("dingtalk_sender_staff_id")
+                if sender_staff_id:
+                    context["dingtalk_sender_staff_id"] = sender_staff_id
+        elif channel_type == "wecom_bot":
+            context["msg"] = None
+
+        # Use Agent to execute the task
+        # Mark this as a scheduled task execution to prevent recursive task creation
+        context["is_scheduled_task"] = True
+        
+        try:
+            # Don't clear history - scheduler tasks use isolated session_id so they won't pollute user conversations
+            reply = agent_bridge.agent_reply(task_description, context=context, on_event=None, clear_history=False)
+
+            if not (reply and reply.content):
+                logger.error(f"[Scheduler] Task {task['id']}: No result from agent execution")
+                return True  # agent ran but produced nothing; don't loop
+
+            from channel.channel_factory import create_channel
+            channel = create_channel(channel_type)
+            if not channel:
+                logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+                return False
+
+            if channel_type == "web" and hasattr(channel, 'request_to_session'):
+                request_id = context.get("request_id")
+                if request_id:
+                    channel.request_to_session[request_id] = receiver
+
+            try:
+                channel.send(reply, context)
+            except Exception as e:
+                logger.error(f"[Scheduler] Failed to send result: {e}")
+                return False
+
+            _remember_delivered_output(agent_bridge, task, channel_type, reply.content)
+            logger.info(f"[Scheduler] Task {task['id']} executed successfully, result sent to {receiver}")
+            return True
+
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to execute task via Agent: {e}")
+            import traceback
+            logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}")
+            return False
+
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_agent_task: {e}")
+        import traceback
+        logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}")
+        return False
+
+
+def _execute_send_message(task: dict, agent_bridge) -> bool:
+    """Execute a send_message action. Returns True/False for delivery."""
+    try:
+        action = task.get("action", {})
+        content = action.get("content", "")
+        receiver = action.get("receiver")
+        is_group = action.get("is_group", False)
+        channel_type = action.get("channel_type", "unknown")
+        
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return True
+        
+        # Create context for sending message
+        context = Context(ContextType.TEXT, content)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = receiver
+        
+        # Channel-specific context setup
+        if channel_type == "web":
+            # Web channel needs request_id
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+            logger.debug(f"[Scheduler] Generated request_id for web channel: {request_id}")
+        elif channel_type == "feishu":
+            # Feishu channel: for scheduled tasks, send as new message (no msg_id to reply to)
+            # Use chat_id for groups, open_id for private chats
+            context["receive_id_type"] = "chat_id" if is_group else "open_id"
+            # Keep isgroup as is, but set msg to None (no original message to reply to)
+            # Feishu channel will detect this and send as new message instead of reply
+            context["msg"] = None
+            logger.debug(f"[Scheduler] Feishu: receive_id_type={context['receive_id_type']}, is_group={is_group}, receiver={receiver}")
+        elif channel_type == "dingtalk":
+            # DingTalk channel setup
+            context["msg"] = None
+            # 如果是单聊，需要传递 sender_staff_id
+            if not is_group:
+                sender_staff_id = action.get("dingtalk_sender_staff_id")
+                if sender_staff_id:
+                    context["dingtalk_sender_staff_id"] = sender_staff_id
+                    logger.debug(f"[Scheduler] DingTalk single chat: sender_staff_id={sender_staff_id}")
+                else:
+                    logger.warning(f"[Scheduler] Task {task['id']}: DingTalk single chat message missing sender_staff_id")
+        elif channel_type == "wecom_bot":
+            context["msg"] = None
+        elif channel_type == "qq":
+            context["msg"] = None
+
+        # Create reply
+        reply = Reply(ReplyType.TEXT, content)
+        
+        # Get channel and send
+        from channel.channel_factory import create_channel
+        
+        channel = create_channel(channel_type)
+        if not channel:
+            logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+            return False
+
+        if channel_type == "web" and hasattr(channel, 'request_to_session'):
+            channel.request_to_session[request_id] = receiver
+
+        try:
+            channel.send(reply, context)
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to send message: {e}")
+            return False
+
+        _remember_delivered_output(agent_bridge, task, channel_type, content)
+        logger.info(f"[Scheduler] Task {task['id']} executed: sent message to {receiver}")
+        return True
+
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_send_message: {e}")
+        import traceback
+        logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}")
+        return False
+
+
+def _execute_tool_call(task: dict, agent_bridge) -> bool:
+    """Execute a tool_call action. Returns True/False for delivery."""
+    try:
+        action = task.get("action", {})
+        tool_name = action.get("call_name") or action.get("tool_name")
+        tool_params = action.get("call_params") or action.get("tool_params", {})
+        result_prefix = action.get("result_prefix", "")
+        receiver = action.get("receiver")
+        is_group = action.get("is_group", False)
+        channel_type = action.get("channel_type", "unknown")
+
+        if not tool_name:
+            logger.error(f"[Scheduler] Task {task['id']}: No tool_name specified")
+            return True
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return True
+
+        from agent.tools.tool_manager import ToolManager
+        tool = ToolManager().create_tool(tool_name)
+        if not tool:
+            logger.error(f"[Scheduler] Task {task['id']}: Tool '{tool_name}' not found")
+            return True
+
+        logger.info(f"[Scheduler] Task {task['id']}: Executing tool '{tool_name}' with params {tool_params}")
+        result = tool.execute(tool_params)
+        content = result.result if hasattr(result, 'result') else str(result)
+        if result_prefix:
+            content = f"{result_prefix}\n\n{content}"
+
+        context = Context(ContextType.TEXT, content)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = receiver
+
+        request_id = None
+        if channel_type == "web":
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+        elif channel_type == "feishu":
+            context["receive_id_type"] = "chat_id" if is_group else "open_id"
+            context["msg"] = None
+        elif channel_type == "wecom_bot":
+            context["msg"] = None
+
+        reply = Reply(ReplyType.TEXT, content)
+
+        from channel.channel_factory import create_channel
+        channel = create_channel(channel_type)
+        if not channel:
+            logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+            return False
+
+        if channel_type == "web" and request_id and hasattr(channel, 'request_to_session'):
+            channel.request_to_session[request_id] = receiver
+
+        try:
+            channel.send(reply, context)
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to send tool result: {e}")
+            return False
+
+        _remember_delivered_output(agent_bridge, task, channel_type, content)
+        logger.info(f"[Scheduler] Task {task['id']} executed: sent tool result to {receiver}")
+        return True
+
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_tool_call: {e}")
+        return False
+
+
+def _execute_skill_call(task: dict, agent_bridge) -> bool:
+    """Execute a skill_call action by asking Agent to run the skill.
+    Returns True/False for delivery."""
+    try:
+        action = task.get("action", {})
+        skill_name = action.get("call_name") or action.get("skill_name")
+        skill_params = action.get("call_params") or action.get("skill_params", {})
+        result_prefix = action.get("result_prefix", "")
+        receiver = action.get("receiver")
+        is_group = action.get("isgroup", False)
+        channel_type = action.get("channel_type", "unknown")
+
+        if not skill_name:
+            logger.error(f"[Scheduler] Task {task['id']}: No skill_name specified")
+            return True
+        if not receiver:
+            logger.error(f"[Scheduler] Task {task['id']}: No receiver specified")
+            return True
+
+        logger.info(f"[Scheduler] Task {task['id']}: Executing skill '{skill_name}' with params {skill_params}")
+
+        scheduler_session_id = f"scheduler_{receiver}_{task['id']}"
+        param_str = ", ".join([f"{k}={v}" for k, v in skill_params.items()])
+        query = f"Use {skill_name} skill"
+        if param_str:
+            query += f" with {param_str}"
+
+        context = Context(ContextType.TEXT, query)
+        context["receiver"] = receiver
+        context["isgroup"] = is_group
+        context["session_id"] = scheduler_session_id
+
+        if channel_type == "web":
+            import uuid
+            request_id = f"scheduler_{task['id']}_{uuid.uuid4().hex[:8]}"
+            context["request_id"] = request_id
+        elif channel_type == "feishu":
+            context["receive_id_type"] = "chat_id" if is_group else "open_id"
+            context["msg"] = None
+        elif channel_type == "wecom_bot":
+            context["msg"] = None
+
+        try:
+            reply = agent_bridge.agent_reply(query, context=context, on_event=None, clear_history=False)
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to execute skill via Agent: {e}")
+            import traceback
+            logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}")
+            return False
+
+        if not (reply and reply.content):
+            logger.error(f"[Scheduler] Task {task['id']}: No result from skill execution")
+            return True
+
+        content = reply.content
+        if result_prefix:
+            content = f"{result_prefix}\n\n{content}"
+
+        from channel.channel_factory import create_channel
+        channel = create_channel(channel_type)
+        if not channel:
+            logger.error(f"[Scheduler] Failed to create channel: {channel_type}")
+            return False
+
+        if channel_type == "web" and hasattr(channel, 'request_to_session'):
+            req_id = context.get("request_id")
+            if req_id:
+                channel.request_to_session[req_id] = receiver
+
+        try:
+            channel.send(Reply(ReplyType.TEXT, content), context)
+        except Exception as e:
+            logger.error(f"[Scheduler] Failed to send skill result: {e}")
+            return False
+
+        _remember_delivered_output(agent_bridge, task, channel_type, content)
+        logger.info(f"[Scheduler] Task {task['id']} executed: skill result sent to {receiver}")
+        return True
+
+    except Exception as e:
+        logger.error(f"[Scheduler] Error in _execute_skill_call: {e}")
+        import traceback
+        logger.error(f"[Scheduler] Traceback: {traceback.format_exc()}")
+        return False
+
+
+def attach_scheduler_to_tool(tool, context: Context = None):
+    """
+    Attach scheduler components to a SchedulerTool instance
+    
+    Args:
+        tool: SchedulerTool instance
+        context: Current context (optional)
+    """
+    if _task_store:
+        tool.task_store = _task_store
+    
+    if context:
+        tool.current_context = context
+        
+        channel_type = context.get("channel_type") or conf().get("channel_type", "unknown")
+        if not tool.config:
+            tool.config = {}
+        tool.config["channel_type"] = channel_type
diff --git a/agent/tools/scheduler/scheduler_service.py b/agent/tools/scheduler/scheduler_service.py
new file mode 100644
index 0000000..1f4bc6f
--- /dev/null
+++ b/agent/tools/scheduler/scheduler_service.py
@@ -0,0 +1,243 @@
+"""
+Background scheduler service for executing scheduled tasks
+"""
+
+import time
+import threading
+from datetime import datetime, timedelta
+from typing import Callable, Optional
+from croniter import croniter
+from common.log import logger
+
+
+def _parse_naive_local(iso_str: str) -> datetime:
+    """Parse an ISO datetime and coerce it to tz-naive local time.
+
+    The scheduler uses ``datetime.now()`` (tz-naive) for all comparisons,
+    so any persisted timestamp must be normalized to the same flavor —
+    otherwise comparing naive vs aware raises TypeError.
+    """
+    dt = datetime.fromisoformat(iso_str)
+    if dt.tzinfo is not None:
+        dt = dt.astimezone().replace(tzinfo=None)
+    return dt
+
+
+class SchedulerService:
+    """
+    Background service that executes scheduled tasks
+    """
+    
+    def __init__(self, task_store, execute_callback: Callable):
+        """
+        Initialize scheduler service
+        
+        Args:
+            task_store: TaskStore instance
+            execute_callback: Function to call when executing a task
+        """
+        self.task_store = task_store
+        self.execute_callback = execute_callback
+        self.running = False
+        self.thread = None
+        self._lock = threading.Lock()
+    
+    def start(self):
+        """Start the scheduler service"""
+        with self._lock:
+            if self.running:
+                logger.warning("[Scheduler] Service already running")
+                return
+            
+            self.running = True
+            self.thread = threading.Thread(target=self._run_loop, daemon=True)
+            self.thread.start()
+    
+    def stop(self):
+        """Stop the scheduler service"""
+        with self._lock:
+            if not self.running:
+                return
+            
+            self.running = False
+            if self.thread:
+                self.thread.join(timeout=5)
+            logger.info("[Scheduler] Service stopped")
+    
+    def _run_loop(self):
+        """Main scheduler loop"""
+        logger.info("[Scheduler] Scheduler loop started")
+        
+        while self.running:
+            try:
+                self._check_and_execute_tasks()
+            except Exception as e:
+                logger.error(f"[Scheduler] Error in scheduler loop: {e}")
+
+            time.sleep(30)
+    
+    def _check_and_execute_tasks(self):
+        """Check for due tasks and execute them"""
+        now = datetime.now()
+        tasks = self.task_store.list_tasks(enabled_only=True)
+        
+        for task in tasks:
+            try:
+                if self._is_task_due(task, now):
+                    logger.info(f"[Scheduler] Executing task: {task['id']} - {task['name']}")
+                    ok = self._execute_task(task)
+                    if not ok:
+                        # Leave next_run_at as-is so the next loop retries.
+                        # Cron tasks within the catch-up window will keep
+                        # firing; beyond it _is_task_due will reschedule.
+                        logger.warning(
+                            f"[Scheduler] Task {task['id']} delivery failed, will retry next tick"
+                        )
+                        continue
+
+                    next_run = self._calculate_next_run(task, now)
+                    if next_run:
+                        self.task_store.update_task(task['id'], {
+                            "next_run_at": next_run.isoformat(),
+                            "last_run_at": now.isoformat()
+                        })
+                    else:
+                        self.task_store.delete_task(task['id'])
+                        logger.info(f"[Scheduler] One-time task completed and removed: {task['id']}")
+            except Exception as e:
+                logger.error(f"[Scheduler] Error processing task {task.get('id')}: {e}")
+    
+    def _is_task_due(self, task: dict, now: datetime) -> bool:
+        """
+        Check if a task is due to run
+        
+        Args:
+            task: Task dictionary
+            now: Current datetime
+            
+        Returns:
+            True if task should run now
+        """
+        next_run_str = task.get("next_run_at")
+        if not next_run_str:
+            # Calculate initial next_run_at
+            next_run = self._calculate_next_run(task, now)
+            if next_run:
+                self.task_store.update_task(task['id'], {
+                    "next_run_at": next_run.isoformat()
+                })
+                return False
+            return False
+        
+        try:
+            next_run = _parse_naive_local(next_run_str)
+
+            if next_run < now:
+                time_diff = (now - next_run).total_seconds()
+                schedule = task.get("schedule", {})
+                schedule_type = schedule.get("type")
+
+                # Catch-up window: fire if we're within 10 minutes of the
+                # scheduled tick. Beyond that we'd rather skip than push a
+                # stale daily report to the user.
+                if time_diff <= 600:
+                    return True
+
+                logger.warning(
+                    f"[Scheduler] Task {task['id']} is overdue by {int(time_diff)}s, "
+                    f"skipping and scheduling next run"
+                )
+
+                if schedule_type == "once":
+                    self.task_store.delete_task(task['id'])
+                    logger.info(f"[Scheduler] One-time task {task['id']} expired, removed")
+                    return False
+
+                next_next_run = self._calculate_next_run(task, now)
+                if next_next_run:
+                    self.task_store.update_task(task['id'], {
+                        "next_run_at": next_next_run.isoformat()
+                    })
+                    logger.info(f"[Scheduler] Rescheduled task {task['id']} to {next_next_run}")
+                return False
+
+            return now >= next_run
+        except Exception as e:
+            logger.error(
+                f"[Scheduler] Failed to evaluate due-state for task "
+                f"{task.get('id')} (next_run_at={next_run_str!r}): {e}"
+            )
+            return False
+    
+    def _calculate_next_run(self, task: dict, from_time: datetime) -> Optional[datetime]:
+        """
+        Calculate next run time for a task
+        
+        Args:
+            task: Task dictionary
+            from_time: Calculate from this time
+            
+        Returns:
+            Next run datetime or None for one-time tasks
+        """
+        schedule = task.get("schedule", {})
+        schedule_type = schedule.get("type")
+        
+        if schedule_type == "cron":
+            # Cron expression
+            expression = schedule.get("expression")
+            if not expression:
+                return None
+            
+            try:
+                cron = croniter(expression, from_time)
+                return cron.get_next(datetime)
+            except Exception as e:
+                logger.error(f"[Scheduler] Invalid cron expression '{expression}': {e}")
+                return None
+        
+        elif schedule_type == "interval":
+            # Interval in seconds
+            seconds = schedule.get("seconds", 0)
+            if seconds <= 0:
+                return None
+            return from_time + timedelta(seconds=seconds)
+        
+        elif schedule_type == "once":
+            # One-time task at specific time
+            run_at_str = schedule.get("run_at")
+            if not run_at_str:
+                return None
+            
+            try:
+                run_at = _parse_naive_local(run_at_str)
+                if run_at > from_time:
+                    return run_at
+            except Exception as e:
+                logger.error(
+                    f"[Scheduler] Failed to parse once-task run_at "
+                    f"{run_at_str!r}: {e}"
+                )
+            return None
+        
+        return None
+    
+    def _execute_task(self, task: dict) -> bool:
+        """
+        Execute a task.
+
+        Returns True if delivery succeeded (caller should advance state),
+        False if it failed (caller should keep next_run_at so the next
+        loop iteration retries). Callback may return None for legacy
+        behaviour, treated as success.
+        """
+        try:
+            result = self.execute_callback(task)
+            return False if result is False else True
+        except Exception as e:
+            logger.error(f"[Scheduler] Error executing task {task['id']}: {e}")
+            self.task_store.update_task(task['id'], {
+                "last_error": str(e),
+                "last_error_at": datetime.now().isoformat()
+            })
+            return False
diff --git a/agent/tools/scheduler/scheduler_tool.py b/agent/tools/scheduler/scheduler_tool.py
new file mode 100644
index 0000000..8535f1c
--- /dev/null
+++ b/agent/tools/scheduler/scheduler_tool.py
@@ -0,0 +1,453 @@
+"""
+Scheduler tool for creating and managing scheduled tasks
+"""
+
+import uuid
+from datetime import datetime
+from typing import Any, Dict, Optional
+from croniter import croniter
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+
+
+class SchedulerTool(BaseTool):
+    """
+    Tool for managing scheduled tasks (reminders, notifications, etc.)
+    """
+    
+    name: str = "scheduler"
+    description: str = (
+        "创建、查询和管理定时任务（提醒、周期性任务等）。\n\n"
+        "⚠️ 重要：仅当需要「定时/提醒/每天/每周/X分钟后/X点」等延迟或周期执行时才使用此工具。"
+        "使用方法：\n"
+        "- 创建：action='create', name='任务名', message/ai_task='内容', schedule_type='once/interval/cron', schedule_value='...'\n"
+        "- 查询：action='list' / action='get', task_id='任务ID'\n"
+        "- 管理：action='delete/enable/disable', task_id='任务ID'\n\n"
+        "调度类型：\n"
+        "- once: 一次性任务，支持相对时间(+5s,+10m,+1h,+1d)或ISO时间\n"
+        "- interval: 固定间隔(秒)，如3600表示每小时\n"
+        "- cron: cron表达式，如'0 8 * * *'表示每天8点\n\n"
+        "注意：'X秒后'用once+相对时间，'每X秒'用interval"
+    )
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "enum": ["create", "list", "get", "delete", "enable", "disable"],
+                "description": "操作类型: create(创建), list(列表), get(查询), delete(删除), enable(启用), disable(禁用)"
+            },
+            "task_id": {
+                "type": "string",
+                "description": "任务ID (用于 get/delete/enable/disable 操作)"
+            },
+            "name": {
+                "type": "string",
+                "description": "任务名称 (用于 create 操作)"
+            },
+            "message": {
+                "type": "string",
+                "description": "固定消息内容 (与ai_task二选一)"
+            },
+            "ai_task": {
+                "type": "string",
+                "description": "AI任务描述 (与message二选一)，用于定时让AI执行的任务"
+            },
+            "schedule_type": {
+                "type": "string",
+                "enum": ["cron", "interval", "once"],
+                "description": "调度类型 (用于 create 操作): cron(cron表达式), interval(固定间隔秒数), once(一次性)"
+            },
+            "schedule_value": {
+                "type": "string",
+                "description": "调度值: cron表达式/间隔秒数/时间(+5s,+10m,+1h或ISO格式)"
+            }
+        },
+        "required": ["action"]
+    }
+    
+    def __init__(self, config: dict = None):
+        super().__init__()
+        self.config = config or {}
+        
+        # Will be set by agent bridge
+        self.task_store = None
+        self.current_context = None
+    
+    def execute(self, params: dict) -> ToolResult:
+        """
+        Execute scheduler operations
+        
+        Args:
+            params: Dictionary containing:
+                - action: Operation type (create/list/get/delete/enable/disable)
+                - Other parameters depending on action
+            
+        Returns:
+            ToolResult object
+        """
+        # Extract parameters
+        action = params.get("action")
+        kwargs = params
+        
+        if not self.task_store:
+            return ToolResult.fail("错误: 定时任务系统未初始化")
+        
+        try:
+            if action == "create":
+                result = self._create_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "list":
+                result = self._list_tasks(**kwargs)
+                return ToolResult.success(result)
+            elif action == "get":
+                result = self._get_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "delete":
+                result = self._delete_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "enable":
+                result = self._enable_task(**kwargs)
+                return ToolResult.success(result)
+            elif action == "disable":
+                result = self._disable_task(**kwargs)
+                return ToolResult.success(result)
+            else:
+                return ToolResult.fail(f"未知操作: {action}")
+        except Exception as e:
+            logger.error(f"[SchedulerTool] Error: {e}")
+            return ToolResult.fail(f"操作失败: {str(e)}")
+    
+    def _create_task(self, **kwargs) -> str:
+        """Create a new scheduled task"""
+        name = kwargs.get("name")
+        message = kwargs.get("message")
+        ai_task = kwargs.get("ai_task")
+        schedule_type = kwargs.get("schedule_type")
+        schedule_value = kwargs.get("schedule_value")
+        
+        # Validate required fields
+        if not name:
+            return "错误: 缺少任务名称 (name)"
+        
+        # Check that exactly one of message/ai_task is provided
+        if not message and not ai_task:
+            return "错误: 必须提供 message（固定消息）或 ai_task（AI任务）之一"
+        if message and ai_task:
+            return "错误: message 和 ai_task 只能提供其中一个"
+        
+        if not schedule_type:
+            return "错误: 缺少调度类型 (schedule_type)"
+        if not schedule_value:
+            return "错误: 缺少调度值 (schedule_value)"
+        
+        # Validate schedule
+        schedule = self._parse_schedule(schedule_type, schedule_value)
+        if not schedule:
+            return f"错误: 无效的调度配置 - type: {schedule_type}, value: {schedule_value}"
+        
+        # Get context info for receiver
+        if not self.current_context:
+            return "错误: 无法获取当前对话上下文"
+        
+        context = self.current_context
+        
+        # Create task
+        task_id = str(uuid.uuid4())[:8]
+        
+        # Capture the real chat session_id at task creation time so that scheduler
+        # can later inject the delivered output into the user's actual conversation
+        # (in group chats, session_id != receiver, e.g. "user_id:group_id" on feishu).
+        notify_session_id = context.get("session_id")
+
+        # Build action based on message or ai_task
+        if message:
+            action = {
+                "type": "send_message",
+                "content": message,
+                "receiver": context.get("receiver"),
+                "receiver_name": self._get_receiver_name(context),
+                "is_group": context.get("isgroup", False),
+                "channel_type": self.config.get("channel_type", "unknown"),
+                "notify_session_id": notify_session_id,
+            }
+        else:  # ai_task
+            action = {
+                "type": "agent_task",
+                "task_description": ai_task,
+                "receiver": context.get("receiver"),
+                "receiver_name": self._get_receiver_name(context),
+                "is_group": context.get("isgroup", False),
+                "channel_type": self.config.get("channel_type", "unknown"),
+                "notify_session_id": notify_session_id,
+            }
+        
+        # 针对钉钉单聊，额外存储 sender_staff_id
+        msg = context.kwargs.get("msg")
+        if msg and hasattr(msg, 'sender_staff_id') and not context.get("isgroup", False):
+            action["dingtalk_sender_staff_id"] = msg.sender_staff_id
+        
+        task_data = {
+            "id": task_id,
+            "name": name,
+            "enabled": True,
+            "created_at": datetime.now().isoformat(),
+            "updated_at": datetime.now().isoformat(),
+            "schedule": schedule,
+            "action": action
+        }
+        
+        # Calculate initial next_run_at
+        next_run = self._calculate_next_run(task_data)
+        if next_run:
+            task_data["next_run_at"] = next_run.isoformat()
+        
+        # Save task
+        self.task_store.add_task(task_data)
+        
+        # Format response
+        schedule_desc = self._format_schedule_description(schedule)
+        receiver_desc = task_data["action"]["receiver_name"] or task_data["action"]["receiver"]
+        
+        if message:
+            content_desc = f"💬 固定消息: {message}"
+        else:
+            content_desc = f"🤖 AI任务: {ai_task}"
+        
+        return (
+            f"✅ 定时任务创建成功\n\n"
+            f"📋 任务ID: {task_id}\n"
+            f"📝 名称: {name}\n"
+            f"⏰ 调度: {schedule_desc}\n"
+            f"👤 接收者: {receiver_desc}\n"
+            f"{content_desc}\n"
+            f"🕐 下次执行: {next_run.strftime('%Y-%m-%d %H:%M:%S') if next_run else '未知'}"
+        )
+    
+    def _list_tasks(self, **kwargs) -> str:
+        """List all tasks"""
+        tasks = self.task_store.list_tasks()
+        
+        if not tasks:
+            return "📋 暂无定时任务"
+        
+        lines = [f"📋 定时任务列表 (共 {len(tasks)} 个)\n"]
+        
+        for task in tasks:
+            status = "✅" if task.get("enabled", True) else "❌"
+            schedule_desc = self._format_schedule_description(task.get("schedule", {}))
+            next_run = task.get("next_run_at")
+            next_run_str = datetime.fromisoformat(next_run).strftime('%m-%d %H:%M') if next_run else "未知"
+            
+            lines.append(
+                f"{status} [{task['id']}] {task['name']}\n"
+                f"   ⏰ {schedule_desc} | 下次: {next_run_str}"
+            )
+        
+        return "\n".join(lines)
+    
+    def _get_task(self, **kwargs) -> str:
+        """Get task details"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        status = "启用" if task.get("enabled", True) else "禁用"
+        schedule_desc = self._format_schedule_description(task.get("schedule", {}))
+        action = task.get("action", {})
+        next_run = task.get("next_run_at")
+        next_run_str = datetime.fromisoformat(next_run).strftime('%Y-%m-%d %H:%M:%S') if next_run else "未知"
+        last_run = task.get("last_run_at")
+        last_run_str = datetime.fromisoformat(last_run).strftime('%Y-%m-%d %H:%M:%S') if last_run else "从未执行"
+        
+        return (
+            f"📋 任务详情\n\n"
+            f"ID: {task['id']}\n"
+            f"名称: {task['name']}\n"
+            f"状态: {status}\n"
+            f"调度: {schedule_desc}\n"
+            f"接收者: {action.get('receiver_name', action.get('receiver'))}\n"
+            f"消息: {action.get('content')}\n"
+            f"下次执行: {next_run_str}\n"
+            f"上次执行: {last_run_str}\n"
+            f"创建时间: {datetime.fromisoformat(task['created_at']).strftime('%Y-%m-%d %H:%M:%S')}"
+        )
+    
+    def _delete_task(self, **kwargs) -> str:
+        """Delete a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.delete_task(task_id)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已删除"
+    
+    def _enable_task(self, **kwargs) -> str:
+        """Enable a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.enable_task(task_id, True)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已启用"
+    
+    def _disable_task(self, **kwargs) -> str:
+        """Disable a task"""
+        task_id = kwargs.get("task_id")
+        if not task_id:
+            return "错误: 缺少任务ID (task_id)"
+        
+        task = self.task_store.get_task(task_id)
+        if not task:
+            return f"错误: 任务 '{task_id}' 不存在"
+        
+        self.task_store.enable_task(task_id, False)
+        return f"✅ 任务 '{task['name']}' ({task_id}) 已禁用"
+    
+    def _parse_schedule(self, schedule_type: str, schedule_value: str) -> Optional[dict]:
+        """Parse and validate schedule configuration"""
+        try:
+            if schedule_type == "cron":
+                # Validate cron expression
+                croniter(schedule_value)
+                return {"type": "cron", "expression": schedule_value}
+            
+            elif schedule_type == "interval":
+                # Parse interval in seconds
+                seconds = int(schedule_value)
+                if seconds <= 0:
+                    return None
+                return {"type": "interval", "seconds": seconds}
+            
+            elif schedule_type == "once":
+                # Parse datetime - support both relative and absolute time
+                
+                # Check if it's relative time (e.g., "+5s", "+10m", "+1h", "+1d")
+                if schedule_value.startswith("+"):
+                    import re
+                    match = re.match(r'\+(\d+)([smhd])', schedule_value)
+                    if match:
+                        amount = int(match.group(1))
+                        unit = match.group(2)
+                        
+                        from datetime import timedelta
+                        now = datetime.now()
+                        
+                        if unit == 's':  # seconds
+                            target_time = now + timedelta(seconds=amount)
+                        elif unit == 'm':  # minutes
+                            target_time = now + timedelta(minutes=amount)
+                        elif unit == 'h':  # hours
+                            target_time = now + timedelta(hours=amount)
+                        elif unit == 'd':  # days
+                            target_time = now + timedelta(days=amount)
+                        else:
+                            return None
+                        
+                        return {"type": "once", "run_at": target_time.isoformat()}
+                    else:
+                        logger.error(f"[SchedulerTool] Invalid relative time format: {schedule_value}")
+                        return None
+                else:
+                    # Absolute ISO time. Normalize to tz-naive local so it
+                    # stays comparable with the scheduler's datetime.now().
+                    parsed = datetime.fromisoformat(schedule_value)
+                    if parsed.tzinfo is not None:
+                        parsed = parsed.astimezone().replace(tzinfo=None)
+                    return {"type": "once", "run_at": parsed.isoformat()}
+            
+        except Exception as e:
+            logger.error(f"[SchedulerTool] Invalid schedule: {e}")
+            return None
+        
+        return None
+    
+    def _calculate_next_run(self, task: dict) -> Optional[datetime]:
+        """Calculate next run time for a task"""
+        schedule = task.get("schedule", {})
+        schedule_type = schedule.get("type")
+        now = datetime.now()
+        
+        if schedule_type == "cron":
+            expression = schedule.get("expression")
+            cron = croniter(expression, now)
+            return cron.get_next(datetime)
+        
+        elif schedule_type == "interval":
+            seconds = schedule.get("seconds", 0)
+            from datetime import timedelta
+            return now + timedelta(seconds=seconds)
+        
+        elif schedule_type == "once":
+            run_at_str = schedule.get("run_at")
+            return datetime.fromisoformat(run_at_str)
+        
+        return None
+    
+    def _format_schedule_description(self, schedule: dict) -> str:
+        """Format schedule as human-readable description"""
+        schedule_type = schedule.get("type")
+        
+        if schedule_type == "cron":
+            expr = schedule.get("expression", "")
+            # Try to provide friendly description
+            if expr == "0 9 * * *":
+                return "每天 9:00"
+            elif expr == "0 */1 * * *":
+                return "每小时"
+            elif expr == "*/30 * * * *":
+                return "每30分钟"
+            else:
+                return f"Cron: {expr}"
+        
+        elif schedule_type == "interval":
+            seconds = schedule.get("seconds", 0)
+            if seconds >= 86400:
+                days = seconds // 86400
+                return f"每 {days} 天"
+            elif seconds >= 3600:
+                hours = seconds // 3600
+                return f"每 {hours} 小时"
+            elif seconds >= 60:
+                minutes = seconds // 60
+                return f"每 {minutes} 分钟"
+            else:
+                return f"每 {seconds} 秒"
+        
+        elif schedule_type == "once":
+            run_at = schedule.get("run_at", "")
+            try:
+                dt = datetime.fromisoformat(run_at)
+                return f"一次性 ({dt.strftime('%Y-%m-%d %H:%M')})"
+            except Exception:
+                return "一次性"
+        
+        return "未知"
+    
+    def _get_receiver_name(self, context: Context) -> str:
+        """Get receiver name from context"""
+        try:
+            msg = context.get("msg")
+            if msg:
+                if context.get("isgroup"):
+                    return msg.other_user_nickname or "群聊"
+                else:
+                    return msg.from_user_nickname or "用户"
+        except Exception:
+            pass
+        return "未知"
diff --git a/agent/tools/scheduler/task_store.py b/agent/tools/scheduler/task_store.py
new file mode 100644
index 0000000..a904788
--- /dev/null
+++ b/agent/tools/scheduler/task_store.py
@@ -0,0 +1,208 @@
+"""
+Task storage management for scheduler
+"""
+
+import json
+import os
+import threading
+from datetime import datetime
+from typing import Dict, List, Optional
+from pathlib import Path
+from common.utils import expand_path
+
+
+class TaskStore:
+    """
+    Manages persistent storage of scheduled tasks
+    """
+    
+    def __init__(self, store_path: str = None):
+        """
+        Initialize task store
+        
+        Args:
+            store_path: Path to tasks.json file. Defaults to ~/cow/scheduler/tasks.json
+        """
+        if store_path is None:
+            # Default to ~/cow/scheduler/tasks.json
+            home = expand_path("~")
+            store_path = os.path.join(home, "cow", "scheduler", "tasks.json")
+        
+        self.store_path = store_path
+        self.lock = threading.Lock()
+        self._ensure_store_dir()
+    
+    def _ensure_store_dir(self):
+        """Ensure the storage directory exists"""
+        store_dir = os.path.dirname(self.store_path)
+        os.makedirs(store_dir, exist_ok=True)
+    
+    def load_tasks(self) -> Dict[str, dict]:
+        """
+        Load all tasks from storage
+        
+        Returns:
+            Dictionary of task_id -> task_data
+        """
+        with self.lock:
+            if not os.path.exists(self.store_path):
+                return {}
+            
+            try:
+                with open(self.store_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                    return data.get("tasks", {})
+            except Exception as e:
+                print(f"Error loading tasks: {e}")
+                return {}
+    
+    def save_tasks(self, tasks: Dict[str, dict]):
+        """
+        Save all tasks to storage
+        
+        Args:
+            tasks: Dictionary of task_id -> task_data
+        """
+        with self.lock:
+            try:
+                # Create backup
+                if os.path.exists(self.store_path):
+                    backup_path = f"{self.store_path}.bak"
+                    try:
+                        with open(self.store_path, 'r') as src:
+                            with open(backup_path, 'w') as dst:
+                                dst.write(src.read())
+                    except Exception:
+                        pass
+                
+                # Save tasks
+                data = {
+                    "version": 1,
+                    "updated_at": datetime.now().isoformat(),
+                    "tasks": tasks
+                }
+                
+                with open(self.store_path, 'w', encoding='utf-8') as f:
+                    json.dump(data, f, ensure_ascii=False, indent=2)
+            except Exception as e:
+                print(f"Error saving tasks: {e}")
+                raise
+    
+    def add_task(self, task: dict) -> bool:
+        """
+        Add a new task
+        
+        Args:
+            task: Task data dictionary
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        task_id = task.get("id")
+        
+        if not task_id:
+            raise ValueError("Task must have an 'id' field")
+        
+        if task_id in tasks:
+            raise ValueError(f"Task with id '{task_id}' already exists")
+        
+        tasks[task_id] = task
+        self.save_tasks(tasks)
+        return True
+    
+    def update_task(self, task_id: str, updates: dict) -> bool:
+        """
+        Update an existing task
+        
+        Args:
+            task_id: Task ID
+            updates: Dictionary of fields to update
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        
+        if task_id not in tasks:
+            raise ValueError(f"Task '{task_id}' not found")
+        
+        # Update fields
+        tasks[task_id].update(updates)
+        tasks[task_id]["updated_at"] = datetime.now().isoformat()
+        
+        self.save_tasks(tasks)
+        return True
+    
+    def delete_task(self, task_id: str) -> bool:
+        """
+        Delete a task
+        
+        Args:
+            task_id: Task ID
+            
+        Returns:
+            True if successful
+        """
+        tasks = self.load_tasks()
+        
+        if task_id not in tasks:
+            raise ValueError(f"Task '{task_id}' not found")
+        
+        del tasks[task_id]
+        self.save_tasks(tasks)
+        return True
+    
+    def get_task(self, task_id: str) -> Optional[dict]:
+        """
+        Get a specific task
+        
+        Args:
+            task_id: Task ID
+            
+        Returns:
+            Task data or None if not found
+        """
+        tasks = self.load_tasks()
+        return tasks.get(task_id)
+    
+    def list_tasks(self, enabled_only: bool = False) -> List[dict]:
+        """
+        List all tasks
+        
+        Args:
+            enabled_only: If True, only return enabled tasks
+            
+        Returns:
+            List of task dictionaries
+        """
+        tasks = self.load_tasks()
+        task_list = list(tasks.values())
+        
+        if enabled_only:
+            task_list = [t for t in task_list if t.get("enabled", True)]
+        
+        # Sort by enabled status (enabled first), then by next_run_at
+        def sort_key(t):
+            enabled = t.get("enabled", True)
+            next_run = t.get("next_run_at", "")
+            # Enabled tasks first (0), disabled tasks second (1)
+            # Then sort by next_run_at (empty string sorts last)
+            return (0 if enabled else 1, next_run if next_run else "9999-12-31")
+        
+        task_list.sort(key=sort_key)
+        
+        return task_list
+    
+    def enable_task(self, task_id: str, enabled: bool = True) -> bool:
+        """
+        Enable or disable a task
+        
+        Args:
+            task_id: Task ID
+            enabled: True to enable, False to disable
+            
+        Returns:
+            True if successful
+        """
+        return self.update_task(task_id, {"enabled": enabled})
diff --git a/agent/tools/send/__init__.py b/agent/tools/send/__init__.py
new file mode 100644
index 0000000..b76702a
--- /dev/null
+++ b/agent/tools/send/__init__.py
@@ -0,0 +1,3 @@
+from .send import Send
+
+__all__ = ['Send']
diff --git a/agent/tools/send/send.py b/agent/tools/send/send.py
new file mode 100644
index 0000000..80dea9b
--- /dev/null
+++ b/agent/tools/send/send.py
@@ -0,0 +1,216 @@
+"""
+Send tool - Send files to the user
+"""
+
+import os
+from typing import Dict, Any
+from pathlib import Path
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.utils import expand_path
+
+
+class Send(BaseTool):
+    """Tool for sending files to the user"""
+    
+    name: str = "send"
+    description: str = "Send a LOCAL file (image, video, audio, document) to the user. Only for local file paths. Do NOT use this for URLs — URLs should be included directly in your text reply, the system will handle them automatically."
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Local file path to send. Must be an absolute path or relative to workspace. Do NOT pass URLs here."
+            },
+            "message": {
+                "type": "string",
+                "description": "Optional message to accompany the file"
+            }
+        },
+        "required": ["path"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        
+        # Supported file types
+        self.image_extensions = {'.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.svg', '.ico'}
+        self.video_extensions = {'.mp4', '.avi', '.mov', '.mkv', '.flv', '.wmv', '.webm', '.m4v'}
+        self.audio_extensions = {'.mp3', '.wav', '.ogg', '.m4a', '.flac', '.aac', '.wma'}
+        self.document_extensions = {'.pdf', '.doc', '.docx', '.xls', '.xlsx', '.ppt', '.pptx', '.txt', '.md'}
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute file send operation
+        
+        :param args: Contains file path and optional message
+        :return: File metadata for channel to send
+        """
+        path = args.get("path", "").strip()
+        message = args.get("message", "")
+        
+        if not path:
+            return ToolResult.fail("Error: path parameter is required")
+        
+        # Pass through remote URLs directly (no local file check): the client
+        # renders the link inline, so no download is needed.
+        if path.lower().startswith(("http://", "https://")):
+            return self._build_url_result(path, message)
+        
+        # Resolve path
+        absolute_path = self._resolve_path(path)
+        
+        # Check if file exists
+        if not os.path.exists(absolute_path):
+            return ToolResult.fail(f"Error: File not found: {path}")
+        
+        # Check if readable
+        if not os.access(absolute_path, os.R_OK):
+            return ToolResult.fail(f"Error: File is not readable: {path}")
+        
+        # Get file info
+        file_ext = Path(absolute_path).suffix.lower()
+        file_size = os.path.getsize(absolute_path)
+        file_name = Path(absolute_path).name
+        
+        # Determine file type
+        if file_ext in self.image_extensions:
+            file_type = "image"
+            mime_type = self._get_image_mime_type(file_ext)
+        elif file_ext in self.video_extensions:
+            file_type = "video"
+            mime_type = self._get_video_mime_type(file_ext)
+        elif file_ext in self.audio_extensions:
+            file_type = "audio"
+            mime_type = self._get_audio_mime_type(file_ext)
+        elif file_ext in self.document_extensions:
+            file_type = "document"
+            mime_type = self._get_document_mime_type(file_ext)
+        else:
+            file_type = "file"
+            mime_type = "application/octet-stream"
+        
+        # Return file_to_send metadata
+        result = {
+            "type": "file_to_send",
+            "file_type": file_type,
+            "path": absolute_path,
+            "file_name": file_name,
+            "mime_type": mime_type,
+            "size": file_size,
+            "size_formatted": self._format_size(file_size),
+            "message": message or f"正在发送 {file_name}"
+        }
+
+        try:
+            from common.cloud_client import get_website_base_url, copy_send_file
+
+            # Do nothing when in local env
+            if get_website_base_url():
+                url = copy_send_file(absolute_path, self.cwd)
+                if url:
+                    result["url"] = url
+        except Exception:
+            pass
+
+        return ToolResult.success(result)
+    
+    def _build_url_result(self, url: str, message: str) -> ToolResult:
+        """Build a file_to_send result for a remote http(s) URL.
+
+        The URL is passed through as both ``path`` and ``url`` so downstream
+        channels render it inline without downloading it locally.
+        """
+        # Infer file type from the URL path extension (ignore query string).
+        from urllib.parse import urlparse
+        url_path = urlparse(url).path
+        file_ext = Path(url_path).suffix.lower()
+        file_name = Path(url_path).name or "file"
+
+        if file_ext in self.image_extensions:
+            file_type = "image"
+            mime_type = self._get_image_mime_type(file_ext)
+        elif file_ext in self.video_extensions:
+            file_type = "video"
+            mime_type = self._get_video_mime_type(file_ext)
+        elif file_ext in self.audio_extensions:
+            file_type = "audio"
+            mime_type = self._get_audio_mime_type(file_ext)
+        elif file_ext in self.document_extensions:
+            file_type = "document"
+            mime_type = self._get_document_mime_type(file_ext)
+        else:
+            # Default to image: most pass-through URLs are generated images.
+            file_type = "image"
+            mime_type = "image/jpeg"
+
+        result = {
+            "type": "file_to_send",
+            "file_type": file_type,
+            "path": url,
+            "url": url,
+            "file_name": file_name,
+            "mime_type": mime_type,
+            "message": message or f"正在发送 {file_name}",
+        }
+        return ToolResult.success(result)
+
+    def _resolve_path(self, path: str) -> str:
+        """Resolve path to absolute path"""
+        path = expand_path(path)
+        if os.path.isabs(path):
+            return path
+        return os.path.abspath(os.path.join(self.cwd, path))
+    
+    def _get_image_mime_type(self, ext: str) -> str:
+        """Get MIME type for image"""
+        mime_map = {
+            '.jpg': 'image/jpeg', '.jpeg': 'image/jpeg',
+            '.png': 'image/png', '.gif': 'image/gif',
+            '.webp': 'image/webp', '.bmp': 'image/bmp',
+            '.svg': 'image/svg+xml', '.ico': 'image/x-icon'
+        }
+        return mime_map.get(ext, 'image/jpeg')
+    
+    def _get_video_mime_type(self, ext: str) -> str:
+        """Get MIME type for video"""
+        mime_map = {
+            '.mp4': 'video/mp4', '.avi': 'video/x-msvideo',
+            '.mov': 'video/quicktime', '.mkv': 'video/x-matroska',
+            '.webm': 'video/webm', '.flv': 'video/x-flv'
+        }
+        return mime_map.get(ext, 'video/mp4')
+    
+    def _get_audio_mime_type(self, ext: str) -> str:
+        """Get MIME type for audio"""
+        mime_map = {
+            '.mp3': 'audio/mpeg', '.wav': 'audio/wav',
+            '.ogg': 'audio/ogg', '.m4a': 'audio/mp4',
+            '.flac': 'audio/flac', '.aac': 'audio/aac'
+        }
+        return mime_map.get(ext, 'audio/mpeg')
+    
+    def _get_document_mime_type(self, ext: str) -> str:
+        """Get MIME type for document"""
+        mime_map = {
+            '.pdf': 'application/pdf',
+            '.doc': 'application/msword',
+            '.docx': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document',
+            '.xls': 'application/vnd.ms-excel',
+            '.xlsx': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',
+            '.ppt': 'application/vnd.ms-powerpoint',
+            '.pptx': 'application/vnd.openxmlformats-officedocument.presentationml.presentation',
+            '.txt': 'text/plain',
+            '.md': 'text/markdown'
+        }
+        return mime_map.get(ext, 'application/octet-stream')
+    
+    def _format_size(self, size_bytes: int) -> str:
+        """Format file size in human-readable format"""
+        for unit in ['B', 'KB', 'MB', 'GB']:
+            if size_bytes < 1024.0:
+                return f"{size_bytes:.1f}{unit}"
+            size_bytes /= 1024.0
+        return f"{size_bytes:.1f}TB"
diff --git a/agent/tools/tool_manager.py b/agent/tools/tool_manager.py
new file mode 100644
index 0000000..e282a15
--- /dev/null
+++ b/agent/tools/tool_manager.py
@@ -0,0 +1,761 @@
+import importlib
+import importlib.util
+import threading
+from pathlib import Path
+from typing import Dict, Any, Type
+from agent.tools.base_tool import BaseTool
+from common.log import logger
+from config import conf
+
+
+def _normalize_mcp_configs(raw) -> list:
+    """
+    Convert MCP server config to internal list format.
+    Supports:
+      - list format (mcp_servers):  [{"name": "x", "type": "stdio", ...}]
+      - dict format (mcpServers):   {"x": {"command": "npx", ...}}
+    """
+    if isinstance(raw, list):
+        return raw
+    if isinstance(raw, dict):
+        result = []
+        for name, cfg in raw.items():
+            entry = {"name": name, **cfg}
+            if "type" not in entry:
+                entry["type"] = "sse" if "url" in entry else "stdio"
+            result.append(entry)
+        return result
+    return []
+
+
+class ToolManager:
+    """
+    Tool manager for managing tools.
+    """
+    _instance = None
+
+    def __new__(cls):
+        """Singleton pattern to ensure only one instance of ToolManager exists."""
+        if cls._instance is None:
+            cls._instance = super(ToolManager, cls).__new__(cls)
+            cls._instance.tool_classes = {}  # Store tool classes instead of instances
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self):
+        # Initialize only once
+        if not hasattr(self, 'tool_classes'):
+            self.tool_classes = {}  # Dictionary to store tool classes
+        if not hasattr(self, '_mcp_registry'):
+            self._mcp_registry = None  # Lazy init: only created when MCP servers are configured
+        if not hasattr(self, '_mcp_tool_instances'):
+            self._mcp_tool_instances: dict = {}  # tool_name -> McpTool instance
+        if not hasattr(self, '_mcp_lock'):
+            # Guards _mcp_loaded check-then-set so concurrent callers
+            # don't trigger duplicate background loaders.
+            self._mcp_lock = threading.Lock()
+        if not hasattr(self, '_mcp_loaded'):
+            # Idempotency flag. Flipped to True the moment the first loader
+            # is dispatched (synchronously, inside _mcp_lock). Subsequent
+            # _load_mcp_tools() calls become no-ops, so per-session agent
+            # initialization never re-forks MCP subprocesses.
+            self._mcp_loaded = False
+        if not hasattr(self, '_mcp_status'):
+            # server_name -> "pending" / "ready" / "failed"
+            # Useful for UI / introspection while async loading is in progress.
+            self._mcp_status: dict = {}
+        if not hasattr(self, '_mcp_signature'):
+            # (mtime, sha256) of mcp.json the last time we loaded.
+            # Used by refresh_mcp_if_changed() to skip re-parsing when nothing changed.
+            self._mcp_signature: tuple = (None, None)
+        if not hasattr(self, '_mcp_active_configs'):
+            # server_name -> normalized config dict, for diff-based reload.
+            self._mcp_active_configs: dict = {}
+        if not hasattr(self, '_mcp_tool_vectors'):
+            # mcp_tool_name -> embedding vector, used by on-demand tool
+            # retrieval. Populated lazily on first retrieval so users who
+            # never enable the feature pay zero embedding cost.
+            self._mcp_tool_vectors: dict = {}
+        if not hasattr(self, '_mcp_vector_lock'):
+            # Guards incremental index builds so concurrent turns don't
+            # double-embed the same newly-loaded MCP tools.
+            self._mcp_vector_lock = threading.Lock()
+        if not hasattr(self, '_embedding_provider_initialized'):
+            # The embedding provider is created once, lazily, and reused for
+            # both tool-index and per-query embeddings. None means keyword-only
+            # mode (no provider configured) — retrieval then falls back to full
+            # injection at the caller.
+            self._embedding_provider_initialized = False
+            self._embedding_provider = None
+
+    def load_tools(self, tools_dir: str = "", config_dict=None):
+        """
+        Load tools from both directory and configuration.
+
+        :param tools_dir: Directory to scan for tool modules
+        """
+        if tools_dir:
+            self._load_tools_from_directory(tools_dir)
+            self._configure_tools_from_config()
+        else:
+            self._load_tools_from_init()
+            self._configure_tools_from_config(config_dict)
+
+        self._load_mcp_tools()
+
+    def _load_tools_from_init(self) -> bool:
+        """
+        Load tool classes from tools.__init__.__all__
+
+        :return: True if tools were loaded, False otherwise
+        """
+        try:
+            # Try to import the tools package
+            tools_package = importlib.import_module("agent.tools")
+
+            # Check if __all__ is defined
+            if hasattr(tools_package, "__all__"):
+                tool_classes = tools_package.__all__
+
+                # Import each tool class directly from the tools package
+                for class_name in tool_classes:
+                    try:
+                        # Skip base classes
+                        if class_name in ["BaseTool", "ToolManager"]:
+                            continue
+
+                        # Get the class directly from the tools package
+                        if hasattr(tools_package, class_name):
+                            cls = getattr(tools_package, class_name)
+
+                            if (
+                                    isinstance(cls, type)
+                                    and issubclass(cls, BaseTool)
+                                    and cls != BaseTool
+                            ):
+                                try:
+                                    # Skip tools that need special initialization
+                                    if class_name in ["MemorySearchTool", "MemoryGetTool"]:
+                                        logger.debug(f"Skipped tool {class_name} (requires memory_manager)")
+                                        continue
+                                    # McpTool instances are registered dynamically via _load_mcp_tools()
+                                    if class_name == "McpTool":
+                                        logger.debug(f"Skipped tool {class_name} (registered dynamically via mcp_servers config)")
+                                        continue
+                                    
+                                    # Create a temporary instance to get the name
+                                    temp_instance = cls()
+                                    tool_name = temp_instance.name
+                                    # Store the class, not the instance
+                                    self.tool_classes[tool_name] = cls
+                                    logger.debug(f"Loaded tool: {tool_name} from class {class_name}")
+                                except ImportError as e:
+                                    # Handle missing dependencies with helpful messages
+                                    error_msg = str(e)
+                                    if "playwright" in error_msg:
+                                        logger.warning(
+                                            f"[ToolManager] Browser tool not loaded - missing dependencies.\n"
+                                            f"  To enable browser tool, run:\n"
+                                            f"    pip install playwright\n"
+                                            f"    playwright install chromium"
+                                        )
+                                    elif "markdownify" in error_msg:
+                                        logger.warning(
+                                            f"[ToolManager] {cls.__name__} not loaded - missing markdownify.\n"
+                                            f"  Install with: pip install markdownify"
+                                        )
+                                    else:
+                                        logger.warning(f"[ToolManager] {cls.__name__} not loaded due to missing dependency: {error_msg}")
+                                except Exception as e:
+                                    logger.error(f"Error initializing tool class {cls.__name__}: {e}")
+                    except Exception as e:
+                        logger.error(f"Error importing class {class_name}: {e}")
+
+                return len(self.tool_classes) > 0
+            return False
+        except ImportError:
+            logger.warning("Could not import agent.tools package")
+            return False
+        except Exception as e:
+            logger.error(f"Error loading tools from __init__.__all__: {e}")
+            return False
+
+    def _load_tools_from_directory(self, tools_dir: str):
+        """Dynamically load tool classes from directory"""
+        tools_path = Path(tools_dir)
+
+        # Traverse all .py files
+        for py_file in tools_path.rglob("*.py"):
+            # Skip initialization files and base tool files
+            if py_file.name in ["__init__.py", "base_tool.py", "tool_manager.py"]:
+                continue
+
+            # Get module name
+            module_name = py_file.stem
+
+            try:
+                # Load module directly from file
+                spec = importlib.util.spec_from_file_location(module_name, py_file)
+                if spec and spec.loader:
+                    module = importlib.util.module_from_spec(spec)
+                    spec.loader.exec_module(module)
+
+                    # Find tool classes in the module
+                    for attr_name in dir(module):
+                        cls = getattr(module, attr_name)
+                        if (
+                                isinstance(cls, type)
+                                and issubclass(cls, BaseTool)
+                                and cls != BaseTool
+                        ):
+                            try:
+                                # Skip memory tools (they need special initialization with memory_manager)
+                                if attr_name in ["MemorySearchTool", "MemoryGetTool"]:
+                                    logger.debug(f"Skipped tool {attr_name} (requires memory_manager)")
+                                    continue
+                                
+                                # Create a temporary instance to get the name
+                                temp_instance = cls()
+                                tool_name = temp_instance.name
+                                # Store the class, not the instance
+                                self.tool_classes[tool_name] = cls
+                            except ImportError as e:
+                                # Handle missing dependencies with helpful messages
+                                error_msg = str(e)
+                                if "playwright" in error_msg:
+                                    logger.warning(
+                                        f"[ToolManager] Browser tool not loaded - missing dependencies.\n"
+                                        f"  To enable browser tool, run:\n"
+                                        f"    pip install playwright\n"
+                                        f"    playwright install chromium"
+                                    )
+                                elif "markdownify" in error_msg:
+                                    logger.warning(
+                                        f"[ToolManager] {cls.__name__} not loaded - missing markdownify.\n"
+                                        f"  Install with: pip install markdownify"
+                                    )
+                                else:
+                                    logger.warning(f"[ToolManager] {cls.__name__} not loaded due to missing dependency: {error_msg}")
+                            except Exception as e:
+                                logger.error(f"Error initializing tool class {cls.__name__}: {e}")
+            except Exception as e:
+                print(f"Error importing module {py_file}: {e}")
+
+    def _configure_tools_from_config(self, config_dict=None):
+        """Configure tool classes based on configuration file"""
+        try:
+            # Get tools configuration
+            tools_config = config_dict or conf().get("tools", {})
+
+            # Record tools that are configured but not loaded
+            missing_tools = []
+
+            # Store configurations for later use when instantiating
+            self.tool_configs = tools_config
+
+            # Check which configured tools are missing
+            for tool_name in tools_config:
+                if tool_name not in self.tool_classes:
+                    missing_tools.append(tool_name)
+
+            # If there are missing tools, record warnings
+            if missing_tools:
+                for tool_name in missing_tools:
+                    if tool_name == "browser":
+                        logger.warning(
+                            f"[ToolManager] Browser tool is configured but not loaded.\n"
+                            f"  To enable browser tool, run:\n"
+                            f"    pip install playwright\n"
+                            f"    playwright install chromium"
+                        )
+                    elif tool_name == "google_search":
+                        logger.warning(
+                            f"[ToolManager] Google Search tool is configured but may need API key.\n"
+                            f"  Get API key from: https://serper.dev\n"
+                            f"  Configure in config.json: tools.google_search.api_key"
+                        )
+                    else:
+                        logger.warning(f"[ToolManager] Tool '{tool_name}' is configured but could not be loaded.")
+
+        except Exception as e:
+            logger.error(f"Error configuring tools from config: {e}")
+
+    def _mcp_json_path(self) -> str:
+        import os
+        workspace = os.path.expanduser(conf().get("agent_workspace", "~/cow"))
+        return os.path.join(workspace, "mcp.json")
+
+    def _read_mcp_json_signature(self):
+        """
+        Return (mtime, sha256_of_bytes) for ~/cow/mcp.json without parsing.
+        Returns (None, None) if the file doesn't exist or is unreadable.
+        Cheap enough (one stat + one small read) to call on every agent init.
+        """
+        import os
+        import hashlib
+        path = self._mcp_json_path()
+        try:
+            mtime = os.path.getmtime(path)
+        except OSError:
+            return (None, None)
+        try:
+            with open(path, "rb") as f:
+                digest = hashlib.sha256(f.read()).hexdigest()
+        except OSError:
+            return (mtime, None)
+        return (mtime, digest)
+
+    def _load_mcp_configs(self) -> list:
+        """
+        Load MCP server configs with priority:
+          1. ~/cow/mcp.json  (supports both mcpServers and mcp_servers keys)
+          2. config.json mcp_servers field (fallback)
+        """
+        import os
+        import json as _json
+
+        mcp_json_path = self._mcp_json_path()
+
+        if os.path.exists(mcp_json_path):
+            try:
+                with open(mcp_json_path, "r", encoding="utf-8") as f:
+                    data = _json.load(f)
+                raw = data.get("mcpServers") or data.get("mcp_servers") or data
+                logger.info(f"[ToolManager] Loading MCP config from {mcp_json_path}")
+                return _normalize_mcp_configs(raw)
+            except Exception as e:
+                logger.warning(f"[ToolManager] Failed to read {mcp_json_path}: {e}, falling back to config.json")
+
+        raw = conf().get("mcp_servers", [])
+        return _normalize_mcp_configs(raw)
+
+    def _load_mcp_tools(self):
+        """
+        Trigger MCP tool loading in a background thread (idempotent).
+
+        Returns immediately. Booting MCP servers (npx, uvx, etc.) takes
+        seconds to tens of seconds on first run, which would otherwise
+        block agent initialization and the user's first message.
+        Built-in tools work fine without MCP, so we let the agent serve
+        traffic right away and let MCP servers come online in the
+        background. Per-session agents read a snapshot of whatever is
+        ready at construction time and gracefully ignore the rest.
+        """
+        with self._mcp_lock:
+            if self._mcp_loaded:
+                return
+            mcp_servers_config = self._load_mcp_configs()
+            # Snapshot the signature now so future refresh_mcp_if_changed()
+            # calls can short-circuit when nothing has changed on disk.
+            self._mcp_signature = self._read_mcp_json_signature()
+            self._mcp_active_configs = {
+                cfg.get("name", "<unnamed>"): cfg for cfg in mcp_servers_config
+            }
+            if not mcp_servers_config:
+                # Mark as loaded even when there is nothing to load,
+                # so we don't re-read the config file on every call.
+                self._mcp_loaded = True
+                return
+
+            # Mark pending immediately so list_mcp_status() callers see
+            # the in-progress state instead of an empty dict.
+            for cfg in mcp_servers_config:
+                name = cfg.get("name", "<unnamed>")
+                self._mcp_status[name] = "pending"
+
+            self._mcp_loaded = True
+            threading.Thread(
+                target=self._load_mcp_tools_async,
+                args=(mcp_servers_config,),
+                daemon=True,
+                name="mcp-loader",
+            ).start()
+            logger.info(
+                f"[ToolManager] MCP loading started in background "
+                f"({len(mcp_servers_config)} server(s) configured)"
+            )
+
+    def refresh_mcp_if_changed(self):
+        """
+        Cheap check whether ~/cow/mcp.json has changed since last load.
+        If it has, do a diff-based reload: start newly added servers,
+        shut down removed ones, and restart any whose config was edited.
+        Untouched servers are left running.
+
+        Designed to be called on every agent creation. The fast path is
+        a single os.stat() — completely free when nothing has changed.
+        """
+        with self._mcp_lock:
+            new_sig = self._read_mcp_json_signature()
+            if new_sig == self._mcp_signature:
+                return  # no-op fast path
+
+            try:
+                new_configs = self._load_mcp_configs()
+            except Exception as e:
+                logger.warning(f"[ToolManager] MCP reload — failed to parse config: {e}")
+                return
+
+            new_by_name = {
+                cfg.get("name", "<unnamed>"): cfg for cfg in new_configs
+            }
+            old_by_name = self._mcp_active_configs
+
+            added = [n for n in new_by_name if n not in old_by_name]
+            removed = [n for n in old_by_name if n not in new_by_name]
+            changed = [
+                n for n in new_by_name
+                if n in old_by_name and new_by_name[n] != old_by_name[n]
+            ]
+
+            if not (added or removed or changed):
+                # Signature drifted but content is logically identical
+                # (e.g. user re-saved the file without edits). Just sync.
+                self._mcp_signature = new_sig
+                return
+
+            logger.info(
+                f"[ToolManager] mcp.json changed — "
+                f"adding={added}, removing={removed}, restarting={changed}"
+            )
+
+            # Tear down removed + changed servers (changed ones get restarted below)
+            for name in removed + changed:
+                self._teardown_mcp_server(name)
+
+            # Spin up newly added + changed servers in the background
+            to_start = [new_by_name[n] for n in added + changed]
+            if to_start:
+                for cfg in to_start:
+                    self._mcp_status[cfg.get("name", "<unnamed>")] = "pending"
+                threading.Thread(
+                    target=self._load_mcp_tools_async,
+                    args=(to_start,),
+                    daemon=True,
+                    name="mcp-loader-reload",
+                ).start()
+
+            self._mcp_active_configs = new_by_name
+            self._mcp_signature = new_sig
+
+    def _teardown_mcp_server(self, server_name: str):
+        """Shut down one MCP server and drop its tools from the registry."""
+        if self._mcp_registry is None:
+            return
+        client = None
+        with self._mcp_registry._registry_lock:
+            client = self._mcp_registry._clients.pop(server_name, None)
+        if client is not None:
+            try:
+                client.shutdown()
+            except Exception as e:
+                logger.warning(f"[MCP] Error shutting down '{server_name}': {e}")
+        # Drop tools that belonged to this server.
+        for tool_name in list(self._mcp_tool_instances.keys()):
+            tool = self._mcp_tool_instances.get(tool_name)
+            if tool is not None and getattr(tool, "server_name", None) == server_name:
+                self._mcp_tool_instances.pop(tool_name, None)
+        self._mcp_status.pop(server_name, None)
+
+    def _load_mcp_tools_async(self, mcp_servers_config):
+        """
+        Background worker: bring up each MCP server one-by-one and
+        publish ready tools to _mcp_tool_instances as they come online.
+
+        Server failures are isolated — one bad server cannot block
+        the others, and never raises out of the worker thread.
+        """
+        try:
+            from agent.tools.mcp.mcp_client import McpClient, McpClientRegistry, set_reload_callback
+            from agent.tools.mcp.mcp_tool import McpTool
+
+            registry = McpClientRegistry()
+            self._mcp_registry = registry
+            # Let the OAuth web callback bring a server online once authorized.
+            set_reload_callback(self.reload_mcp_server)
+
+            for cfg in mcp_servers_config:
+                server_name = cfg.get("name", "<unnamed>")
+                try:
+                    client = McpClient(cfg)
+                    if not client.initialize():
+                        if getattr(client, "needs_auth", False):
+                            self._mcp_status[server_name] = "needs_auth"
+                            logger.info(
+                                f"[MCP] Server '{server_name}' needs authorization — "
+                                f"waiting for the user to complete the OAuth flow"
+                            )
+                        else:
+                            self._mcp_status[server_name] = "failed"
+                            logger.warning(
+                                f"[MCP] Server '{server_name}' failed to initialize — skipping"
+                            )
+                        continue
+
+                    tool_schemas = client.list_tools()
+                    added = []
+                    for schema in tool_schemas:
+                        tool_name = schema.get("name", "")
+                        if not tool_name:
+                            continue
+                        mcp_tool = McpTool(client, schema, server_name)
+                        # Atomic dict assignment is GIL-safe; readers iterate
+                        # over a list() snapshot to avoid concurrent mutation.
+                        self._mcp_tool_instances[tool_name] = mcp_tool
+                        added.append(tool_name)
+
+                    # Register client into the shared registry only after its
+                    # tools are visible, so callers never see a half-loaded server.
+                    with registry._registry_lock:
+                        registry._clients[server_name] = client
+                    self._mcp_status[server_name] = "ready"
+                    logger.info(
+                        f"[MCP] Server '{server_name}' ready — "
+                        f"{len(added)} tool(s): {added}"
+                    )
+                except Exception as e:
+                    self._mcp_status[server_name] = "failed"
+                    logger.warning(f"[MCP] Server '{server_name}' load failed: {e}")
+
+            ready = sum(1 for s in self._mcp_status.values() if s == "ready")
+            total = len(self._mcp_status)
+            logger.info(
+                f"[ToolManager] MCP loading complete: "
+                f"{ready}/{total} server(s) ready, "
+                f"{len(self._mcp_tool_instances)} tool(s) available"
+            )
+        except Exception as e:
+            logger.warning(f"[ToolManager] MCP background loader crashed: {e}")
+
+    def reload_mcp_server(self, server_name: str) -> None:
+        """Re-initialize a single MCP server (e.g. after OAuth authorization).
+
+        Tears down any existing client for the server and starts it again in
+        the background, so a freshly-stored access token is picked up and the
+        server's tools become available on the next message.
+        """
+        with self._mcp_lock:
+            cfg = self._mcp_active_configs.get(server_name)
+        if not cfg:
+            logger.warning(f"[MCP] reload requested for unknown server '{server_name}'")
+            return
+        logger.info(f"[MCP] Reloading server '{server_name}' after authorization")
+        self._teardown_mcp_server(server_name)
+        self._mcp_status[server_name] = "pending"
+        threading.Thread(
+            target=self._load_mcp_tools_async,
+            args=([cfg],),
+            daemon=True,
+            name=f"mcp-reload-{server_name}",
+        ).start()
+
+    def list_mcp_status(self) -> dict:
+        """Return {server_name: status} snapshot for UI / debugging."""
+        return dict(self._mcp_status)
+
+    def sync_mcp_into_agent(self, agent) -> tuple:
+        """
+        Reconcile a live agent's tool collection with the current MCP tool registry.
+
+        Adds tools that finished loading after the agent was created,
+        and removes tools whose MCP server was torn down. Built-in tools
+        on the agent are left untouched.
+
+        Handles both representations CowAgent uses:
+          - Agent.tools: list[BaseTool]               (default Agent class)
+          - AgentStream.tools: dict[str, BaseTool]    (streaming agent)
+
+        Returns (added_names, removed_names) for logging.
+        """
+        if agent is None or not hasattr(agent, "tools"):
+            return ([], [])
+
+        # Never re-inject MCP tools into a restricted Self-Evolution review agent.
+        # The review agent is created with a deliberately reduced, workspace-guarded
+        # toolset; silently re-adding configured MCP tools here would bypass that
+        # policy boundary (see agent/evolution/executor.py). The flag may live on
+        # the agent itself (Agent) or on the wrapping stream executor's .agent.
+        if getattr(agent, "_evolution_restricted", False) or getattr(
+            getattr(agent, "agent", None), "_evolution_restricted", False
+        ):
+            return ([], [])
+
+        from agent.tools.mcp.mcp_tool import McpTool
+        current = self._mcp_tool_instances
+        registry_names = set(current.keys())
+
+        agent_tools = agent.tools
+
+        if isinstance(agent_tools, dict):
+            agent_mcp_names = {
+                name for name, tool in agent_tools.items()
+                if isinstance(tool, McpTool)
+            }
+            added = registry_names - agent_mcp_names
+            removed = agent_mcp_names - registry_names
+            if not (added or removed):
+                return ([], [])
+            for name in added:
+                agent_tools[name] = current[name]
+            for name in removed:
+                agent_tools.pop(name, None)
+
+        elif isinstance(agent_tools, list):
+            agent_mcp_names = {
+                t.name for t in agent_tools if isinstance(t, McpTool)
+            }
+            added = registry_names - agent_mcp_names
+            removed = agent_mcp_names - registry_names
+            if not (added or removed):
+                return ([], [])
+            if removed:
+                agent.tools = [
+                    t for t in agent_tools
+                    if not (isinstance(t, McpTool) and t.name in removed)
+                ]
+            for name in added:
+                agent.tools.append(current[name])
+
+        else:
+            return ([], [])
+
+        return (sorted(added), sorted(removed))
+
+    # ------------------------------------------------------------------
+    # On-demand MCP tool retrieval support
+    #
+    # The vector index and the embedding provider are owned here (singleton,
+    # process-wide, aligned with the MCP tool lifecycle). The context-aware
+    # selection itself lives in agent.tools.mcp.tool_retrieval, driven by the
+    # executor which is the only place that knows the conversation context.
+    # ------------------------------------------------------------------
+
+    def count_mcp_tools(self) -> int:
+        """Return the number of currently loaded MCP tools."""
+        return len(self._mcp_tool_instances)
+
+    def get_mcp_tool_vectors(self) -> dict:
+        """Return ``{mcp_tool_name: vector}`` for currently loaded MCP tools.
+
+        Lazily embeds any MCP tools not yet in the cache (MCP servers load
+        asynchronously, so tools may appear over time). Returns an empty dict
+        when no embedding provider is available or embedding fails — the caller
+        then falls back to full injection. Never raises.
+        """
+        try:
+            self._ensure_mcp_tool_vectors()
+        except Exception as e:
+            logger.debug(f"[ToolManager] MCP tool vector build skipped: {e}")
+        return dict(self._mcp_tool_vectors)
+
+    def embed_query(self, text: str):
+        """Embed a retrieval query with the shared provider.
+
+        Returns the embedding vector, or None if no provider is available or
+        the call fails (caller falls back to full injection). Never raises.
+        """
+        if not text:
+            return None
+        provider = self._get_embedding_provider()
+        if provider is None:
+            return None
+        try:
+            return provider.embed_query(text)
+        except Exception as e:
+            logger.debug(f"[ToolManager] query embedding failed: {e}")
+            return None
+
+    def _ensure_mcp_tool_vectors(self) -> None:
+        """Incrementally embed MCP tools that are not yet cached."""
+        # Snapshot to avoid concurrent-mutation while the async loader runs.
+        current = dict(self._mcp_tool_instances)
+        missing = [name for name in current if name not in self._mcp_tool_vectors]
+        if not missing:
+            return
+
+        provider = self._get_embedding_provider()
+        if provider is None:
+            return
+
+        with self._mcp_vector_lock:
+            # Re-check under lock: another thread may have filled these in.
+            missing = [name for name in current if name not in self._mcp_tool_vectors]
+            if not missing:
+                return
+            texts = [self._mcp_tool_embed_text(current[name]) for name in missing]
+            vectors = provider.embed_batch(texts)
+            for name, vec in zip(missing, vectors):
+                self._mcp_tool_vectors[name] = vec
+
+    @staticmethod
+    def _mcp_tool_embed_text(tool) -> str:
+        """Build the text that represents an MCP tool for embedding."""
+        name = getattr(tool, "name", "") or ""
+        description = getattr(tool, "description", "") or ""
+        return f"{name}: {description}".strip()
+
+    def _get_embedding_provider(self):
+        """Lazily create and cache the shared embedding provider (or None)."""
+        if not self._embedding_provider_initialized:
+            try:
+                from agent.memory.embedding import create_default_embedding_provider
+                self._embedding_provider = create_default_embedding_provider()
+            except Exception as e:
+                logger.warning(f"[ToolManager] embedding provider init failed: {e}")
+                self._embedding_provider = None
+            self._embedding_provider_initialized = True
+        return self._embedding_provider
+
+    def create_tool(self, name: str) -> BaseTool:
+        """
+        Get a new instance of a tool by name.
+
+        :param name: The name of the tool to get.
+        :return: A new instance of the tool or None if not found.
+        """
+        tool_class = self.tool_classes.get(name)
+        if tool_class:
+            # Create a new instance
+            tool_instance = tool_class()
+
+            # Apply configuration if available
+            if hasattr(self, 'tool_configs') and name in self.tool_configs:
+                tool_instance.config = self.tool_configs[name]
+
+            return tool_instance
+
+        # Fall back to MCP tool instances
+        mcp_tool = self._mcp_tool_instances.get(name)
+        if mcp_tool:
+            return mcp_tool
+
+        return None
+
+    def list_tools(self) -> dict:
+        """
+        Get information about all loaded tools.
+
+        :return: A dictionary with tool information.
+        """
+        result = {}
+        for name, tool_class in self.tool_classes.items():
+            # Create a temporary instance to get schema
+            temp_instance = tool_class()
+            result[name] = {
+                "description": temp_instance.description,
+                "parameters": temp_instance.get_json_schema()
+            }
+
+        # Include MCP tool instances
+        for name, mcp_tool in self._mcp_tool_instances.items():
+            result[name] = {
+                "description": mcp_tool.description,
+                "parameters": mcp_tool.params,
+            }
+
+        return result
+
+    def shutdown_mcp(self):
+        """Shut down all MCP server clients."""
+        if self._mcp_registry:
+            self._mcp_registry.shutdown_all()
diff --git a/agent/tools/utils/__init__.py b/agent/tools/utils/__init__.py
new file mode 100644
index 0000000..e70cc46
--- /dev/null
+++ b/agent/tools/utils/__init__.py
@@ -0,0 +1,49 @@
+from .truncate import (
+    truncate_head,
+    truncate_tail,
+    truncate_line,
+    format_size,
+    TruncationResult,
+    DEFAULT_MAX_LINES,
+    DEFAULT_MAX_BYTES,
+    GREP_MAX_LINE_LENGTH
+)
+
+from .diff import (
+    strip_bom,
+    detect_line_ending,
+    normalize_to_lf,
+    restore_line_endings,
+    normalize_for_fuzzy_match,
+    count_matches,
+    fuzzy_find_text,
+    generate_diff_string,
+    FuzzyMatchResult
+)
+
+from .url_safety import (
+    validate_url_safe,
+    assert_public_ip
+)
+
+__all__ = [
+    'truncate_head',
+    'truncate_tail',
+    'truncate_line',
+    'format_size',
+    'TruncationResult',
+    'DEFAULT_MAX_LINES',
+    'DEFAULT_MAX_BYTES',
+    'GREP_MAX_LINE_LENGTH',
+    'strip_bom',
+    'detect_line_ending',
+    'normalize_to_lf',
+    'restore_line_endings',
+    'normalize_for_fuzzy_match',
+    'count_matches',
+    'fuzzy_find_text',
+    'generate_diff_string',
+    'FuzzyMatchResult',
+    'validate_url_safe',
+    'assert_public_ip'
+]
diff --git a/agent/tools/utils/diff.py b/agent/tools/utils/diff.py
new file mode 100644
index 0000000..7002c04
--- /dev/null
+++ b/agent/tools/utils/diff.py
@@ -0,0 +1,230 @@
+"""
+Diff tools for file editing
+Provides fuzzy matching and diff generation functionality
+"""
+
+import difflib
+import re
+from typing import Optional, Tuple
+
+
+def strip_bom(text: str) -> Tuple[str, str]:
+    """
+    Remove BOM (Byte Order Mark)
+    
+    :param text: Original text
+    :return: (BOM, text after removing BOM)
+    """
+    if text.startswith('\ufeff'):
+        return '\ufeff', text[1:]
+    return '', text
+
+
+def detect_line_ending(text: str) -> str:
+    """
+    Detect line ending type
+    
+    :param text: Text content
+    :return: Line ending type ('\r\n' or '\n')
+    """
+    if '\r\n' in text:
+        return '\r\n'
+    return '\n'
+
+
+def normalize_to_lf(text: str) -> str:
+    """
+    Normalize all line endings to LF (\n)
+    
+    :param text: Original text
+    :return: Normalized text
+    """
+    return text.replace('\r\n', '\n').replace('\r', '\n')
+
+
+def restore_line_endings(text: str, original_ending: str) -> str:
+    """
+    Restore original line endings
+    
+    :param text: LF normalized text
+    :param original_ending: Original line ending
+    :return: Text with restored line endings
+    """
+    if original_ending == '\r\n':
+        return text.replace('\n', '\r\n')
+    return text
+
+
+def normalize_for_fuzzy_match(text: str) -> str:
+    """
+    Normalize text for fuzzy matching
+    Remove excess whitespace but preserve basic structure
+    
+    :param text: Original text
+    :return: Normalized text
+    """
+    # Compress multiple spaces to one
+    text = re.sub(r'[ \t]+', ' ', text)
+    # Remove trailing spaces
+    text = re.sub(r' +\n', '\n', text)
+    # Remove leading spaces (but preserve indentation structure, only remove excess)
+    lines = text.split('\n')
+    normalized_lines = []
+    for line in lines:
+        # Preserve indentation but normalize to multiples of single spaces
+        stripped = line.lstrip()
+        if stripped:
+            indent_count = len(line) - len(stripped)
+            # Normalize indentation (convert tabs to spaces)
+            normalized_indent = ' ' * indent_count
+            normalized_lines.append(normalized_indent + stripped)
+        else:
+            normalized_lines.append('')
+    return '\n'.join(normalized_lines)
+
+
+class FuzzyMatchResult:
+    """Fuzzy match result"""
+    
+    def __init__(self, found: bool, index: int = -1, match_length: int = 0, content_for_replacement: str = ""):
+        self.found = found
+        self.index = index
+        self.match_length = match_length
+        self.content_for_replacement = content_for_replacement
+
+
+def _build_fuzzy_pattern(old_text: str) -> Optional[str]:
+    """
+    Build the whitespace-flexible regex used to locate ``old_text`` fuzzily.
+
+    Returns ``None`` when ``old_text`` has no non-whitespace content to match.
+    This is the single source of truth for fuzzy matching, so that *finding* a
+    match (:func:`fuzzy_find_text`) and *counting* occurrences
+    (:func:`count_matches`) always use the exact same rules.
+    """
+    stripped = old_text.strip('\n')
+    if not stripped.strip():
+        return None
+
+    source_lines = stripped.split('\n')
+    line_patterns = []
+    for i, line in enumerate(source_lines):
+        tokens = line.split()
+        if not tokens:
+            line_patterns.append(r'[ \t]*')
+            continue
+        # Tolerate any run of blanks between tokens.
+        core = r'[ \t]+'.join(re.escape(tok) for tok in tokens)
+        # First-line leading whitespace is folded into the match only when
+        # old_text itself was indented here; otherwise it stays OUTSIDE the
+        # match so a no-indent old_text preserves (does not swallow and drop)
+        # the file's existing indentation -- mirroring an exact substring
+        # match. Inner lines always tolerate indentation: it sits inside the
+        # matched region and is re-supplied by new_text.
+        if i > 0 or line[:1] in (' ', '\t'):
+            core = r'[ \t]*' + core
+        line_patterns.append(core + r'[ \t]*')
+    return '\n'.join(line_patterns)
+
+
+def fuzzy_find_text(content: str, old_text: str) -> FuzzyMatchResult:
+    """
+    Find text in content, try exact match first, then fuzzy match
+    
+    :param content: Content to search in
+    :param old_text: Text to find
+    :return: Match result
+    """
+    # First try exact match
+    index = content.find(old_text)
+    if index != -1:
+        return FuzzyMatchResult(
+            found=True,
+            index=index,
+            match_length=len(old_text),
+            content_for_replacement=content
+        )
+
+    # Fuzzy match: the exact substring was not found, most likely because the
+    # whitespace differs (indentation, spaces around operators, trailing
+    # spaces). Locate the region in the ORIGINAL content using a
+    # whitespace-flexible pattern and return offsets into that original
+    # content.
+    #
+    # This must NOT replace inside a whitespace-normalized copy of the file:
+    # doing so previously returned the normalized copy as
+    # content_for_replacement, which caused the whole file to be rewritten
+    # with collapsed indentation (every untouched line got reformatted).
+    pattern = _build_fuzzy_pattern(old_text)
+    if pattern is not None:
+        match = re.search(pattern, content)
+        if match:
+            return FuzzyMatchResult(
+                found=True,
+                index=match.start(),
+                match_length=match.end() - match.start(),
+                content_for_replacement=content
+            )
+
+    # Not found
+    return FuzzyMatchResult(found=False)
+
+
+def count_matches(content: str, old_text: str) -> int:
+    """
+    Count occurrences of ``old_text`` using the SAME strategy as
+    :func:`fuzzy_find_text`: an exact substring when one is present, otherwise
+    the whitespace-flexible fuzzy regex.
+
+    The edit tool's uniqueness guard must agree with the matcher that actually
+    performs the replacement. Counting through a separate normalization pass
+    (the previous approach) could disagree with the regex used to locate and
+    replace, so both paths now share :func:`_build_fuzzy_pattern`.
+    """
+    if not old_text:
+        return 0
+    # Mirror fuzzy_find_text: prefer exact matching when it applies.
+    if content.find(old_text) != -1:
+        return content.count(old_text)
+    pattern = _build_fuzzy_pattern(old_text)
+    if pattern is None:
+        return 0
+    return len(re.findall(pattern, content))
+
+
+def generate_diff_string(old_content: str, new_content: str) -> dict:
+    """
+    Generate unified diff string
+    
+    :param old_content: Old content
+    :param new_content: New content
+    :return: Dictionary containing diff and first changed line number
+    """
+    old_lines = old_content.split('\n')
+    new_lines = new_content.split('\n')
+    
+    # Generate unified diff
+    diff_lines = list(difflib.unified_diff(
+        old_lines,
+        new_lines,
+        lineterm='',
+        fromfile='original',
+        tofile='modified'
+    ))
+    
+    # Find first changed line number
+    first_changed_line = None
+    for line in diff_lines:
+        if line.startswith('@@'):
+            # Parse @@ -1,3 +1,3 @@ format
+            match = re.search(r'@@ -\d+,?\d* \+(\d+)', line)
+            if match:
+                first_changed_line = int(match.group(1))
+                break
+    
+    diff_string = '\n'.join(diff_lines)
+    
+    return {
+        'diff': diff_string,
+        'first_changed_line': first_changed_line
+    }
diff --git a/agent/tools/utils/truncate.py b/agent/tools/utils/truncate.py
new file mode 100644
index 0000000..4a6ff8a
--- /dev/null
+++ b/agent/tools/utils/truncate.py
@@ -0,0 +1,295 @@
+"""
+Shared truncation utilities for tool outputs.
+
+Truncation is based on two independent limits - whichever is hit first wins:
+- Line limit (default: 2000 lines)
+- Byte limit (default: 50KB)
+
+Never returns partial lines (except bash tail truncation edge case).
+"""
+
+from __future__ import annotations
+from typing import Dict, Any, Optional, Tuple, TYPE_CHECKING
+if TYPE_CHECKING:
+    from typing import Literal
+
+
+DEFAULT_MAX_LINES = 2000
+DEFAULT_MAX_BYTES = 50 * 1024  # 50KB
+GREP_MAX_LINE_LENGTH = 500  # Max chars per grep match line
+
+
+class TruncationResult:
+    """Truncation result"""
+    
+    def __init__(
+        self,
+        content: str,
+        truncated: bool,
+        truncated_by: Optional[Literal["lines", "bytes"]],
+        total_lines: int,
+        total_bytes: int,
+        output_lines: int,
+        output_bytes: int,
+        last_line_partial: bool = False,
+        first_line_exceeds_limit: bool = False,
+        max_lines: int = DEFAULT_MAX_LINES,
+        max_bytes: int = DEFAULT_MAX_BYTES
+    ):
+        self.content = content
+        self.truncated = truncated
+        self.truncated_by = truncated_by
+        self.total_lines = total_lines
+        self.total_bytes = total_bytes
+        self.output_lines = output_lines
+        self.output_bytes = output_bytes
+        self.last_line_partial = last_line_partial
+        self.first_line_exceeds_limit = first_line_exceeds_limit
+        self.max_lines = max_lines
+        self.max_bytes = max_bytes
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary"""
+        return {
+            "content": self.content,
+            "truncated": self.truncated,
+            "truncated_by": self.truncated_by,
+            "total_lines": self.total_lines,
+            "total_bytes": self.total_bytes,
+            "output_lines": self.output_lines,
+            "output_bytes": self.output_bytes,
+            "last_line_partial": self.last_line_partial,
+            "first_line_exceeds_limit": self.first_line_exceeds_limit,
+            "max_lines": self.max_lines,
+            "max_bytes": self.max_bytes
+        }
+
+
+def format_size(bytes_count: int) -> str:
+    """Format bytes as human-readable size"""
+    if bytes_count < 1024:
+        return f"{bytes_count}B"
+    elif bytes_count < 1024 * 1024:
+        return f"{bytes_count / 1024:.1f}KB"
+    else:
+        return f"{bytes_count / (1024 * 1024):.1f}MB"
+
+
+def truncate_head(content: str, max_lines: Optional[int] = None, max_bytes: Optional[int] = None) -> TruncationResult:
+    """
+    Truncate content from the head (keep first N lines/bytes).
+    Suitable for file reads where you want to see the beginning.
+    
+    Never returns partial lines. If first line exceeds byte limit,
+    returns empty content with first_line_exceeds_limit=True.
+    
+    :param content: Content to truncate
+    :param max_lines: Maximum number of lines (default: 2000)
+    :param max_bytes: Maximum number of bytes (default: 50KB)
+    :return: Truncation result
+    """
+    if max_lines is None:
+        max_lines = DEFAULT_MAX_LINES
+    if max_bytes is None:
+        max_bytes = DEFAULT_MAX_BYTES
+    
+    total_bytes = len(content.encode('utf-8'))
+    lines = content.split('\n')
+    total_lines = len(lines)
+    
+    # Check if no truncation is needed
+    if total_lines <= max_lines and total_bytes <= max_bytes:
+        return TruncationResult(
+            content=content,
+            truncated=False,
+            truncated_by=None,
+            total_lines=total_lines,
+            total_bytes=total_bytes,
+            output_lines=total_lines,
+            output_bytes=total_bytes,
+            last_line_partial=False,
+            first_line_exceeds_limit=False,
+            max_lines=max_lines,
+            max_bytes=max_bytes
+        )
+    
+    # Check if first line alone exceeds byte limit
+    first_line_bytes = len(lines[0].encode('utf-8'))
+    if first_line_bytes > max_bytes:
+        return TruncationResult(
+            content="",
+            truncated=True,
+            truncated_by="bytes",
+            total_lines=total_lines,
+            total_bytes=total_bytes,
+            output_lines=0,
+            output_bytes=0,
+            last_line_partial=False,
+            first_line_exceeds_limit=True,
+            max_lines=max_lines,
+            max_bytes=max_bytes
+        )
+    
+    # Collect complete lines that fit
+    output_lines_arr = []
+    output_bytes_count = 0
+    truncated_by = "lines"
+    
+    for i, line in enumerate(lines):
+        if i >= max_lines:
+            break
+        
+        # Calculate line bytes (add 1 for newline if not first line)
+        line_bytes = len(line.encode('utf-8')) + (1 if i > 0 else 0)
+        
+        if output_bytes_count + line_bytes > max_bytes:
+            truncated_by = "bytes"
+            break
+        
+        output_lines_arr.append(line)
+        output_bytes_count += line_bytes
+    
+    # If exited due to line limit
+    if len(output_lines_arr) >= max_lines and output_bytes_count <= max_bytes:
+        truncated_by = "lines"
+    
+    output_content = '\n'.join(output_lines_arr)
+    final_output_bytes = len(output_content.encode('utf-8'))
+    
+    return TruncationResult(
+        content=output_content,
+        truncated=True,
+        truncated_by=truncated_by,
+        total_lines=total_lines,
+        total_bytes=total_bytes,
+        output_lines=len(output_lines_arr),
+        output_bytes=final_output_bytes,
+        last_line_partial=False,
+        first_line_exceeds_limit=False,
+        max_lines=max_lines,
+        max_bytes=max_bytes
+    )
+
+
+def truncate_tail(content: str, max_lines: Optional[int] = None, max_bytes: Optional[int] = None) -> TruncationResult:
+    """
+    Truncate content from tail (keep last N lines/bytes).
+    Suitable for bash output where you want to see the ending content (errors, final results).
+    
+    If the last line of original content exceeds byte limit, may return partial first line.
+    
+    :param content: Content to truncate
+    :param max_lines: Maximum lines (default: 2000)
+    :param max_bytes: Maximum bytes (default: 50KB)
+    :return: Truncation result
+    """
+    if max_lines is None:
+        max_lines = DEFAULT_MAX_LINES
+    if max_bytes is None:
+        max_bytes = DEFAULT_MAX_BYTES
+    
+    total_bytes = len(content.encode('utf-8'))
+    lines = content.split('\n')
+    total_lines = len(lines)
+    
+    # Check if no truncation is needed
+    if total_lines <= max_lines and total_bytes <= max_bytes:
+        return TruncationResult(
+            content=content,
+            truncated=False,
+            truncated_by=None,
+            total_lines=total_lines,
+            total_bytes=total_bytes,
+            output_lines=total_lines,
+            output_bytes=total_bytes,
+            last_line_partial=False,
+            first_line_exceeds_limit=False,
+            max_lines=max_lines,
+            max_bytes=max_bytes
+        )
+    
+    # Work backwards from the end
+    output_lines_arr = []
+    output_bytes_count = 0
+    truncated_by = "lines"
+    last_line_partial = False
+    
+    for i in range(len(lines) - 1, -1, -1):
+        if len(output_lines_arr) >= max_lines:
+            break
+        
+        line = lines[i]
+        # Calculate line bytes (add newline if not the first added line)
+        line_bytes = len(line.encode('utf-8')) + (1 if len(output_lines_arr) > 0 else 0)
+        
+        if output_bytes_count + line_bytes > max_bytes:
+            truncated_by = "bytes"
+            # Edge case: if we haven't added any lines yet and this line exceeds maxBytes,
+            # take the end portion of this line
+            if len(output_lines_arr) == 0:
+                truncated_line = _truncate_string_to_bytes_from_end(line, max_bytes)
+                output_lines_arr.insert(0, truncated_line)
+                output_bytes_count = len(truncated_line.encode('utf-8'))
+                last_line_partial = True
+            break
+        
+        output_lines_arr.insert(0, line)
+        output_bytes_count += line_bytes
+    
+    # If exited due to line limit
+    if len(output_lines_arr) >= max_lines and output_bytes_count <= max_bytes:
+        truncated_by = "lines"
+    
+    output_content = '\n'.join(output_lines_arr)
+    final_output_bytes = len(output_content.encode('utf-8'))
+    
+    return TruncationResult(
+        content=output_content,
+        truncated=True,
+        truncated_by=truncated_by,
+        total_lines=total_lines,
+        total_bytes=total_bytes,
+        output_lines=len(output_lines_arr),
+        output_bytes=final_output_bytes,
+        last_line_partial=last_line_partial,
+        first_line_exceeds_limit=False,
+        max_lines=max_lines,
+        max_bytes=max_bytes
+    )
+
+
+def _truncate_string_to_bytes_from_end(text: str, max_bytes: int) -> str:
+    """
+    Truncate string to fit byte limit (from end).
+    Properly handles multi-byte UTF-8 characters.
+    
+    :param text: String to truncate
+    :param max_bytes: Maximum bytes
+    :return: Truncated string
+    """
+    encoded = text.encode('utf-8')
+    if len(encoded) <= max_bytes:
+        return text
+    
+    # Start from end, skip back maxBytes
+    start = len(encoded) - max_bytes
+    
+    # Find valid UTF-8 boundary (character start)
+    while start < len(encoded) and (encoded[start] & 0xC0) == 0x80:
+        start += 1
+    
+    return encoded[start:].decode('utf-8', errors='ignore')
+
+
+def truncate_line(line: str, max_chars: int = GREP_MAX_LINE_LENGTH) -> Tuple[str, bool]:
+    """
+    Truncate single line to max characters, add [truncated] suffix.
+    Used for grep match lines.
+    
+    :param line: Line to truncate
+    :param max_chars: Maximum characters
+    :return: (truncated text, whether truncated)
+    """
+    if len(line) <= max_chars:
+        return line, False
+    return f"{line[:max_chars]}... [truncated]", True
diff --git a/agent/tools/utils/url_safety.py b/agent/tools/utils/url_safety.py
new file mode 100644
index 0000000..62a8972
--- /dev/null
+++ b/agent/tools/utils/url_safety.py
@@ -0,0 +1,96 @@
+"""
+Shared SSRF guard utilities for tools that fetch model-supplied URLs.
+
+SSRF protection is OPT-IN and disabled by default, because legitimate use
+cases (local dev servers, LAN services, proxy fake-ip resolution) need to
+reach non-public addresses. Enable it by setting the config option
+``web_security_ssrf_protection: true`` (or env ``WEB_SECURITY_SSRF_PROTECTION``).
+
+When enabled, a URL is only considered safe when it uses an http/https
+scheme, has a hostname, that hostname resolves, and every resolved address
+is a public (internet-routable) address. Loopback, private (RFC1918 / ULA),
+link-local (incl. the 169.254.169.254 cloud-metadata endpoint) and otherwise
+reserved addresses are rejected, for both IPv4 and IPv6.
+"""
+
+import ipaddress
+import os
+import socket
+from urllib.parse import urlparse
+
+
+def _ssrf_protection_enabled() -> bool:
+    """Return True only when SSRF protection is explicitly turned on.
+
+    Disabled by default. Reads the env var first, then falls back to the
+    global config; any failure to read config is treated as "disabled" so
+    the guard never breaks normal fetching.
+    """
+    env = os.getenv("WEB_SECURITY_SSRF_PROTECTION")
+    if env is not None:
+        return env.strip().lower() in ("1", "true", "yes", "on")
+    try:
+        from config import conf
+        return bool(conf().get("web_security_ssrf_protection", False))
+    except Exception:
+        return False
+
+
+def _is_blocked_ip(ip: "ipaddress._BaseAddress") -> bool:
+    """Return True if the address is not safe to connect to (non-public)."""
+    return (
+        ip.is_private
+        or ip.is_loopback
+        or ip.is_link_local
+        or ip.is_reserved
+        or ip.is_multicast
+        or ip.is_unspecified
+    )
+
+
+def assert_public_ip(ip_str: str) -> None:
+    """Raise ValueError if the given literal IP is a non-public address.
+
+    No-op when SSRF protection is disabled (the default). Used to re-validate
+    the concrete address a redirect resolved to.
+    """
+    if not _ssrf_protection_enabled():
+        return
+    ip = ipaddress.ip_address(ip_str)
+    if _is_blocked_ip(ip):
+        raise ValueError(
+            f"URL resolves to a non-public address ({ip_str}), "
+            f"request blocked for security"
+        )
+
+
+def validate_url_safe(url: str) -> None:
+    """Reject URLs that target private/loopback/link-local addresses (SSRF guard).
+
+    No-op when SSRF protection is disabled (the default). When enabled,
+    resolves the hostname to its IP address(es) and blocks any that fall
+    into non-public ranges. Also rejects URLs with no host, non-HTTP(S)
+    schemes, or hosts that fail DNS resolution.
+
+    Raises:
+        ValueError: if the URL targets a disallowed address.
+    """
+    if not _ssrf_protection_enabled():
+        return
+
+    parsed = urlparse(url)
+    if parsed.scheme not in ("http", "https"):
+        raise ValueError(f"Unsupported URL scheme: {parsed.scheme}")
+
+    hostname = parsed.hostname
+    if not hostname:
+        raise ValueError("URL has no hostname")
+
+    try:
+        # Resolve all addresses for the hostname.
+        addr_infos = socket.getaddrinfo(hostname, None, socket.AF_UNSPEC, socket.SOCK_STREAM)
+    except socket.gaierror:
+        raise ValueError(f"Cannot resolve hostname: {hostname}")
+
+    for family, _, _, _, sockaddr in addr_infos:
+        assert_public_ip(sockaddr[0])
diff --git a/agent/tools/vision/__init__.py b/agent/tools/vision/__init__.py
new file mode 100644
index 0000000..587d663
--- /dev/null
+++ b/agent/tools/vision/__init__.py
@@ -0,0 +1 @@
+from agent.tools.vision.vision import Vision
diff --git a/agent/tools/vision/vision.py b/agent/tools/vision/vision.py
new file mode 100644
index 0000000..c515a17
--- /dev/null
+++ b/agent/tools/vision/vision.py
@@ -0,0 +1,866 @@
+"""
+Vision tool - Analyze images using Vision API.
+Supports local files (auto base64-encoded) and HTTP URLs.
+
+Provider resolution:
+  - tools.vision.model (if set) means "prefer this model first; fall back to
+    other configured providers if it fails". The model name is mapped to its
+    native provider (e.g. doubao-* → Doubao, kimi-* → Moonshot, gpt-* →
+    OpenAI/LinkAI). That provider is tried first, then the standard auto
+    chain runs as fallback (with the preferred provider de-duplicated).
+  - Auto chain priority:
+      1. Main model via bot.call_vision — only when the main bot is known
+         to actually support vision (not just expose a call_vision method).
+      2. Other models whose API key is configured.
+      3. OpenAI / LinkAI raw HTTP.
+    When use_linkai=true, LinkAI is promoted to #1.
+"""
+
+import base64
+import os
+import subprocess
+import tempfile
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional
+
+import requests
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.utils.url_safety import validate_url_safe
+from common import const
+from common.log import logger
+from config import conf
+
+DEFAULT_MODEL = const.GPT_41_MINI
+DEFAULT_TIMEOUT = 180
+MAX_TOKENS = 4000
+COMPRESS_THRESHOLD = 1_048_576  # 1 MB
+
+SUPPORTED_EXTENSIONS = {
+    "jpg": "image/jpeg",
+    "jpeg": "image/jpeg",
+    "png": "image/png",
+    "gif": "image/gif",
+    "webp": "image/webp",
+}
+
+_MAIN_MODEL_PROVIDER_NAME = "MainModel"
+
+# (config_key_for_api_key, bot_type, default_vision_model, provider_display_name)
+# Auto-discovered as fallback vision providers when their API key is configured.
+# OpenAI and LinkAI are handled separately (raw HTTP providers), so not listed here.
+_DISCOVERABLE_MODELS = [
+    ("moonshot_api_key", const.MOONSHOT, const.KIMI_K2_6, "Moonshot"),
+    ("ark_api_key", const.DOUBAO, const.DOUBAO_SEED_2_PRO, "Doubao"),
+    ("dashscope_api_key", const.QWEN_DASHSCOPE, const.QWEN37_PLUS, "DashScope"),
+    ("claude_api_key", const.CLAUDEAPI, const.CLAUDE_SONNET_5, "Claude"),
+    ("gemini_api_key", const.GEMINI, const.GEMINI_35_FLASH, "Gemini"),
+    ("qianfan_api_key", const.QIANFAN, const.ERNIE_45_TURBO_VL, "Qianfan"),
+    ("zhipu_ai_api_key", const.ZHIPU_AI, const.GLM_4_7, "ZhipuAI"),
+    ("minimax_api_key", const.MiniMax, const.MINIMAX_M2_7, "MiniMax"),
+    ("mimo_api_key", const.MIMO, const.MIMO_V2_5_PRO, "MiMo"),
+]
+
+# Model name prefix → discoverable provider display_name.
+# Used to auto-route tools.vision.model to its native provider.
+# Matched case-insensitively; longest prefix wins.
+_MODEL_PREFIX_TO_PROVIDER = [
+    ("doubao-", "Doubao"),
+    ("kimi-", "Moonshot"),
+    ("moonshot-", "Moonshot"),
+    ("qwen", "DashScope"),       # qwen-*, qwen3-*, qwen3.6-*, etc.
+    ("claude-", "Claude"),
+    ("ernie-", "Qianfan"),
+    ("gemini-", "Gemini"),
+    ("glm-", "ZhipuAI"),
+    ("minimax-", "MiniMax"),
+    ("abab", "MiniMax"),
+    ("mimo-", "MiMo"),
+]
+
+# Model prefixes that natively belong to OpenAI / LinkAI (raw HTTP providers).
+_OPENAI_MODEL_PREFIXES = ("gpt-", "o1-", "o3-", "o4-", "chatgpt-")
+
+# Maps the UI provider id (persisted in tools.vision.provider) to the internal
+# display name used in VisionProvider.name. Keep in sync with _DISCOVERABLE_MODELS
+# and the openai/linkai branches in _route_by_model_name.
+_PROVIDER_ID_TO_DISPLAY = {
+    "openai": "OpenAI",
+    "linkai": "LinkAI",
+    "moonshot": "Moonshot",
+    "doubao": "Doubao",
+    "dashscope": "DashScope",
+    "claudeAPI": "Claude",
+    "gemini": "Gemini",
+    "qianfan": "Qianfan",
+    "zhipu": "ZhipuAI",
+    "minimax": "MiniMax",
+    "mimo": "MiMo",
+}
+
+
+@dataclass
+class VisionProvider:
+    """A single Vision API provider configuration."""
+    name: str
+    api_key: str
+    api_base: str
+    extra_headers: dict = field(default_factory=dict)
+    model_override: Optional[str] = None
+    use_bot: bool = False  # When True, call via bot.call_vision instead of raw HTTP
+    fallback_bot: Any = None  # Bot instance for non-main-model providers
+
+
+class VisionAPIError(Exception):
+    """Raised when a Vision API call fails and should trigger fallback."""
+    pass
+
+
+class Vision(BaseTool):
+    """Analyze images using Vision API"""
+
+    name: str = "vision"
+    description: str = (
+        "Analyze a local image or image URL (jpg/jpeg/png) using Vision API. "
+        "Can describe content, extract text, identify objects, colors, etc. "
+    )
+
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "image": {
+                "type": "string",
+                "description": "Local file path or HTTP(S) URL of the image to analyze",
+            },
+            "question": {
+                "type": "string",
+                "description": "Question to ask about the image",
+            },
+        },
+        "required": ["image", "question"],
+    }
+
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+
+    @staticmethod
+    def is_available() -> bool:
+        return True
+
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        image = args.get("image", "").strip()
+        question = args.get("question", "").strip()
+
+        if not image:
+            return ToolResult.fail("Error: 'image' parameter is required")
+        if not question:
+            return ToolResult.fail("Error: 'question' parameter is required")
+
+        providers = self._resolve_providers()
+        if not providers:
+            return ToolResult.fail(
+                "Error: No model available for Vision.\n"
+                "The main model does not support vision and no other API keys are configured.\n"
+                "Options:\n"
+                "  1. Switch to a multimodal model (e.g. claude-sonnet-5, qwen3.7-plus, gemini-2.0-flash, ernie-4.5-turbo-vl)\n"
+                "  2. Configure OPENAI_API_KEY: env_config(action=\"set\", key=\"OPENAI_API_KEY\", value=\"your-key\")\n"
+                "  3. Configure LINKAI_API_KEY: env_config(action=\"set\", key=\"LINKAI_API_KEY\", value=\"your-key\")"
+            )
+
+        try:
+            image_content = self._build_image_content(image)
+        except Exception as e:
+            return ToolResult.fail(f"Error: {e}")
+
+        # Default model is only used as a last-resort placeholder for providers
+        # whose VisionProvider.model_override is None (e.g. raw OpenAI provider
+        # when the user did not configure tools.vision.model).
+        return self._call_with_fallback(providers, DEFAULT_MODEL, question, image_content)
+
+    def _call_with_fallback(self, providers: List[VisionProvider], model: str,
+                            question: str, image_content: dict) -> ToolResult:
+        """Try each provider in order; fall back to the next one on failure."""
+        errors: List[str] = []
+        for i, provider in enumerate(providers):
+            use_model = provider.model_override or model
+            try:
+                logger.info(f"[Vision] Trying provider '{provider.name}' "
+                            f"with model '{use_model}' ({i + 1}/{len(providers)})")
+                if provider.use_bot:
+                    result = self._call_via_bot(use_model, question, image_content, provider)
+                else:
+                    result = self._call_api(provider, use_model, question, image_content)
+                logger.info(f"[Vision] ✅ Success via {provider.name} (model={use_model})")
+                return result
+            except VisionAPIError as e:
+                errors.append(f"[{provider.name}/{use_model}] {e}")
+                logger.warning(f"[Vision] Provider '{provider.name}' failed: {e}")
+            except requests.Timeout:
+                errors.append(f"[{provider.name}/{use_model}] Request timed out after {DEFAULT_TIMEOUT}s")
+                logger.warning(f"[Vision] Provider '{provider.name}' timed out")
+            except requests.ConnectionError:
+                errors.append(f"[{provider.name}/{use_model}] Connection failed")
+                logger.warning(f"[Vision] Provider '{provider.name}' connection failed")
+            except Exception as e:
+                errors.append(f"[{provider.name}/{use_model}] {e}")
+                logger.error(f"[Vision] Provider '{provider.name}' unexpected error: {e}", exc_info=True)
+
+        return ToolResult.fail(
+            "Error: All Vision API providers failed.\n" + "\n".join(f"  - {err}" for err in errors)
+        )
+
+    def _resolve_providers(self) -> List[VisionProvider]:
+        """
+        Build an ordered list of providers to try.
+
+        Semantics of `tools.vision.model`:
+          "Prefer this model first; fall back to other configured providers
+           if it fails."
+
+        Order:
+          1. The provider that natively serves `tools.vision.model` (if any
+             and its API key is configured) — using the user-specified model
+             name verbatim.
+          2. Auto-discovery chain as fallback:
+               - use_linkai=true → [LinkAI, MainModel?, OtherModels…, OpenAI]
+               - default         → [MainModel?, OtherModels…, OpenAI, LinkAI]
+             MainModel is only included when the main bot is known to support
+             vision (see _main_bot_supports_vision).
+
+        Providers that share the same display name as the preferred provider
+        are de-duplicated to avoid retrying the same endpoint twice.
+        """
+        user_model = self._resolve_user_vision_model()
+        user_provider = self._resolve_user_vision_provider()
+        providers: List[VisionProvider] = []
+
+        # Step 1: preferred provider — explicit `tools.vision.provider`
+        # wins so custom model names can still be routed correctly. Falls
+        # through to model-name prefix inference when provider is unset.
+        preferred = None
+        if user_provider and user_model:
+            preferred = self._route_by_provider_id(user_provider, user_model)
+        if not preferred and user_model:
+            preferred = self._route_by_model_name(user_model)
+        if preferred:
+            providers.extend(preferred)
+
+        # Step 2: auto-discovery chain as fallback
+        existing = {p.name for p in providers}
+        fallback: List[VisionProvider] = []
+        use_linkai = conf().get("use_linkai", False) and conf().get("linkai_api_key")
+
+        if use_linkai:
+            self._append_provider(fallback, lambda: self._build_linkai_provider(user_model))
+            self._append_provider(fallback, self._build_main_model_provider)
+            self._append_other_model_providers(fallback, preferred_model=user_model)
+            self._append_provider(fallback, lambda: self._build_openai_provider(user_model))
+        else:
+            self._append_provider(fallback, self._build_main_model_provider)
+            self._append_other_model_providers(fallback, preferred_model=user_model)
+            self._append_provider(fallback, lambda: self._build_openai_provider(user_model))
+            self._append_provider(fallback, lambda: self._build_linkai_provider(user_model))
+
+        for p in fallback:
+            if p.name in existing:
+                continue
+            providers.append(p)
+            existing.add(p.name)
+
+        return providers
+
+    @staticmethod
+    def _append_provider(providers: List[VisionProvider], builder) -> None:
+        p = builder()
+        if p:
+            providers.append(p)
+
+    @staticmethod
+    def _resolve_user_vision_model() -> Optional[str]:
+        """Read tools.vision.model (singular ``tool`` kept as runtime fallback)."""
+        tools_conf = conf().get("tools") or conf().get("tool") or {}
+        if not isinstance(tools_conf, dict):
+            return None
+        vision_conf = tools_conf.get("vision", {})
+        if not isinstance(vision_conf, dict):
+            return None
+        m = vision_conf.get("model")
+        if isinstance(m, str) and m.strip():
+            return m.strip()
+        return None
+
+    @staticmethod
+    def _resolve_user_vision_provider() -> Optional[str]:
+        """Read tools.vision.provider — the UI-persisted vendor id.
+
+        Lets users pin a vendor for custom model names that prefix-inference
+        can't recognize. Returns None when unset/blank.
+        """
+        tools_conf = conf().get("tools") or conf().get("tool") or {}
+        if not isinstance(tools_conf, dict):
+            return None
+        vision_conf = tools_conf.get("vision", {})
+        if not isinstance(vision_conf, dict):
+            return None
+        p = vision_conf.get("provider")
+        if isinstance(p, str) and p.strip():
+            return p.strip()
+        return None
+
+    @staticmethod
+    def _infer_provider_from_model(model_name: str) -> Optional[str]:
+        """
+        Infer the provider display name from a model name's prefix.
+        Returns None when no rule matches (or for OpenAI-family names, which
+        are handled separately by the caller).
+        """
+        if not model_name:
+            return None
+        lower = model_name.lower()
+        # Sort by prefix length desc so e.g. "moonshot-" wins over hypothetical "moo-"
+        for prefix, display_name in sorted(_MODEL_PREFIX_TO_PROVIDER, key=lambda x: -len(x[0])):
+            if lower.startswith(prefix.lower()):
+                return display_name
+        return None
+
+    def _route_by_provider_id(self, provider_id: str, user_model: str) -> Optional[List[VisionProvider]]:
+        """Route by the UI-persisted provider id.
+
+        Returns:
+          - [provider] : provider id is known and its key is configured.
+          - None       : unknown provider id, or the bot can't be created.
+                         Caller falls through to model-name-based routing.
+        """
+        # Custom OpenAI-compatible providers — read credentials from
+        # custom_providers list, same pattern as embedding.
+        if provider_id.startswith("custom:"):
+            p = self._build_custom_provider(provider_id, user_model)
+            return [p] if p else None
+
+        display_name = _PROVIDER_ID_TO_DISPLAY.get(provider_id)
+        if not display_name:
+            return None
+
+        # OpenAI / LinkAI use raw HTTP providers, not the discoverable bot path.
+        if provider_id == "openai":
+            p = self._build_openai_provider(user_model)
+            return [p] if p else None
+        if provider_id == "linkai":
+            p = self._build_linkai_provider(user_model)
+            return [p] if p else None
+
+        # Discoverable bot-backed providers.
+        for config_key, bot_type, _default_model, name in _DISCOVERABLE_MODELS:
+            if name != display_name:
+                continue
+            api_key = conf().get(config_key, "")
+            if not api_key or not api_key.strip():
+                logger.warning(f"[Vision] tools.vision.provider='{provider_id}' "
+                               f"but '{config_key}' is not configured. Falling back.")
+                return None
+            try:
+                from models.bot_factory import create_bot
+                bot = create_bot(bot_type)
+                if not hasattr(bot, 'call_vision'):
+                    logger.warning(f"[Vision] '{display_name}' bot does not implement call_vision.")
+                    return None
+            except Exception as e:
+                logger.warning(f"[Vision] Failed to create '{display_name}' bot: {e}")
+                return None
+            return [VisionProvider(
+                name=display_name,
+                api_key="",
+                api_base="",
+                model_override=user_model,
+                use_bot=True,
+                fallback_bot=bot,
+            )]
+        return None
+
+    def _route_by_model_name(self, user_model: str) -> Optional[List[VisionProvider]]:
+        """
+        Try to build a provider list using the user-specified model name.
+        Returns:
+          - [provider]  : matched and the provider's key is configured
+          - []          : matched but key missing → tell caller to surface this
+                          as a hard error rather than silently falling back
+          - None        : no rule matches → caller should fall through to auto
+        """
+        lower = user_model.lower()
+
+        # OpenAI / LinkAI family
+        if lower.startswith(_OPENAI_MODEL_PREFIXES):
+            providers: List[VisionProvider] = []
+            # Prefer LinkAI when explicitly enabled, else OpenAI first
+            use_linkai = conf().get("use_linkai", False) and conf().get("linkai_api_key")
+            if use_linkai:
+                self._append_provider(providers, lambda: self._build_linkai_provider(user_model))
+                self._append_provider(providers, lambda: self._build_openai_provider(user_model))
+            else:
+                self._append_provider(providers, lambda: self._build_openai_provider(user_model))
+                self._append_provider(providers, lambda: self._build_linkai_provider(user_model))
+            if providers:
+                return providers
+            logger.warning(f"[Vision] tools.vision.model='{user_model}' looks like an OpenAI "
+                           f"model but neither OPENAI_API_KEY nor LINKAI_API_KEY is configured.")
+            return None  # fall through to auto
+
+        # Discoverable native providers (Doubao, Moonshot, etc.)
+        target_display = self._infer_provider_from_model(user_model)
+        if not target_display:
+            return None  # unknown prefix → auto
+
+        for config_key, bot_type, _default_model, display_name in _DISCOVERABLE_MODELS:
+            if display_name != target_display:
+                continue
+            api_key = conf().get(config_key, "")
+            if not api_key or not api_key.strip():
+                logger.warning(f"[Vision] tools.vision.model='{user_model}' routes to "
+                               f"'{display_name}' but '{config_key}' is not configured. "
+                               f"Falling back to auto-discovery.")
+                return None  # fall through to auto
+            try:
+                from models.bot_factory import create_bot
+                bot = create_bot(bot_type)
+                if not hasattr(bot, 'call_vision'):
+                    logger.warning(f"[Vision] '{display_name}' bot does not implement call_vision.")
+                    return None
+            except Exception as e:
+                logger.warning(f"[Vision] Failed to create '{display_name}' bot: {e}")
+                return None
+
+            return [VisionProvider(
+                name=display_name,
+                api_key="",
+                api_base="",
+                model_override=user_model,
+                use_bot=True,
+                fallback_bot=bot,
+            )]
+
+        return None
+
+    def _append_other_model_providers(self, providers: List[VisionProvider],
+                                       preferred_model: Optional[str] = None) -> None:
+        """
+        Auto-discover other models whose API key is configured.
+        Skip the main model's own bot_type (already covered by MainModel
+        provider), unless the main model itself does not support vision —
+        in that case we still want the vendor's dedicated vision model
+        as a fallback. Also skip bot_types that already appear in the
+        provider list.
+
+        If preferred_model matches a provider's family, use it instead
+        of that provider's hard-coded default model.
+        """
+        main_bot_type = None
+        main_bot_supports_vision = False
+        if self.model and hasattr(self.model, '_resolve_bot_type'):
+            main_bot_type = self.model._resolve_bot_type(conf().get("model", ""))
+            main_bot = getattr(self.model, "bot", None)
+            main_bot_supports_vision = self._main_bot_supports_vision(main_bot)
+
+        existing_names = {p.name for p in providers}
+        preferred_provider = self._infer_provider_from_model(preferred_model) if preferred_model else None
+
+        for config_key, bot_type, default_model, display_name in _DISCOVERABLE_MODELS:
+            if display_name in existing_names:
+                continue
+            # Same bot_type as the main model is normally handled by the
+            # MainModel provider; only skip it here if the main model
+            # actually supports vision. Otherwise fall through and add
+            # the vendor's dedicated vision model as a fallback.
+            if bot_type == main_bot_type and main_bot_supports_vision:
+                continue
+            api_key = conf().get(config_key, "")
+            if not api_key or not api_key.strip():
+                continue
+
+            try:
+                from models.bot_factory import create_bot
+                bot = create_bot(bot_type)
+                if not hasattr(bot, 'call_vision'):
+                    continue
+            except Exception:
+                continue
+
+            model_for_provider = (preferred_model
+                                  if preferred_provider == display_name and preferred_model
+                                  else default_model)
+
+            provider = VisionProvider(
+                name=display_name,
+                api_key="",
+                api_base="",
+                model_override=model_for_provider,
+                use_bot=True,
+                fallback_bot=bot,
+            )
+
+            # Same vendor as the main bot is the most natural fallback when
+            # the main model itself does not support vision — promote it to
+            # the front of the list instead of relying on declaration order.
+            if bot_type == main_bot_type:
+                providers.insert(0, provider)
+            else:
+                providers.append(provider)
+
+    def _main_bot_supports_vision(self, bot) -> bool:
+        """
+        Whether the main bot is known to natively support vision.
+
+        Having a `call_vision` method is necessary but not sufficient —
+        some bots implement the method against an endpoint that does not
+        actually serve vision models, which causes silent failures when a
+        vendor-foreign model name is forwarded.
+
+        Resolution order:
+          1. If the bot explicitly declares `supports_vision`, trust it.
+             This lets bots opt in or out based on their own runtime
+             configuration (e.g. the currently selected model).
+          2. Otherwise, fall back to a model-name prefix heuristic: trust
+             call_vision when the main model looks like an OpenAI family
+             model or matches a known multimodal vendor prefix.
+        """
+        if bot is None:
+            return False
+        if hasattr(bot, "supports_vision"):
+            return bool(getattr(bot, "supports_vision"))
+        main_model = (conf().get("model") or "").lower()
+        if not main_model:
+            return False
+        if main_model.startswith(_OPENAI_MODEL_PREFIXES):
+            return True
+        return self._infer_provider_from_model(main_model) is not None
+
+    def _build_main_model_provider(self) -> Optional[VisionProvider]:
+        """
+        Use the vendor's own model for vision via bot.call_vision.
+        Gated by _main_bot_supports_vision so non-vision bots (DeepSeek, etc.)
+        do not get routed vendor-foreign model names.
+        """
+        if not (self.model and hasattr(self.model, 'bot')):
+            return None
+        try:
+            bot = self.model.bot
+        except Exception:
+            return None
+        if not hasattr(bot, 'call_vision'):
+            return None
+        if not self._main_bot_supports_vision(bot):
+            return None
+
+        # Use the configured main model name; do NOT inject tools.vision.model
+        # here, because by the time we reach this branch the tools.vision.model
+        # routing has already been attempted (and either matched the main bot
+        # or failed to find a provider).
+        main_model_name = conf().get("model") or None
+
+        return VisionProvider(
+            name=_MAIN_MODEL_PROVIDER_NAME,
+            api_key="",
+            api_base="",
+            model_override=main_model_name,
+            use_bot=True,
+        )
+
+    def _build_openai_provider(self, preferred_model: Optional[str] = None) -> Optional[VisionProvider]:
+        api_key = conf().get("open_ai_api_key") or os.environ.get("OPENAI_API_KEY")
+        if not api_key:
+            return None
+        api_base = (conf().get("open_ai_api_base") or os.environ.get("OPENAI_API_BASE", "")).rstrip("/") \
+            or "https://api.openai.com/v1"
+        # Only honor preferred_model when it looks like an OpenAI-family name;
+        # otherwise the OpenAI endpoint would 400 on a vendor-specific name.
+        model_override = preferred_model if (
+            preferred_model and preferred_model.lower().startswith(_OPENAI_MODEL_PREFIXES)
+        ) else None
+        return VisionProvider(
+            name="OpenAI",
+            api_key=api_key,
+            api_base=self._ensure_v1(api_base),
+            model_override=model_override,
+        )
+
+    def _build_linkai_provider(self, preferred_model: Optional[str] = None) -> Optional[VisionProvider]:
+        api_key = conf().get("linkai_api_key") or os.environ.get("LINKAI_API_KEY")
+        if not api_key:
+            return None
+        api_base = (conf().get("linkai_api_base") or os.environ.get("LINKAI_API_BASE", "")).rstrip("/") \
+            or "https://api.link-ai.tech"
+        from common.utils import get_cloud_headers
+        extra = get_cloud_headers(api_key)
+        extra.pop("Authorization", None)
+        extra.pop("Content-Type", None)
+        # LinkAI is a multi-vendor proxy and accepts most model names, so we
+        # honor any user-configured model name here.
+        return VisionProvider(
+            name="LinkAI",
+            api_key=api_key,
+            api_base=self._ensure_v1(api_base),
+            extra_headers=extra,
+            model_override=preferred_model,
+        )
+
+    def _build_custom_provider(self, provider_id: str, preferred_model: Optional[str] = None) -> Optional[VisionProvider]:
+        """Build a VisionProvider from a custom:<id> entry in custom_providers.
+        Uses the standard OpenAI /chat/completions endpoint — any
+        OpenAI-compatible multimodal endpoint works."""
+        from models.custom_provider import parse_custom_bot_type, get_custom_providers, _find_provider_by_id
+        _, custom_id = parse_custom_bot_type(provider_id)
+        if not custom_id:
+            return None
+        entry = _find_provider_by_id(get_custom_providers(), custom_id)
+        if not entry:
+            logger.warning(f"[Vision] custom provider '{provider_id}' not found in custom_providers")
+            return None
+        api_key = (entry.get("api_key") or "").strip()
+        api_base = (entry.get("api_base") or "").strip()
+        if not api_key or not api_base:
+            logger.warning(f"[Vision] custom provider '{provider_id}' missing api_key or api_base")
+            return None
+        model = preferred_model or entry.get("model") or ""
+        if not model:
+            logger.warning(f"[Vision] custom provider '{provider_id}' has no model configured")
+            return None
+        return VisionProvider(
+            name=entry.get("name") or provider_id,
+            api_key=api_key,
+            api_base=self._ensure_v1(api_base.rstrip("/")),
+            model_override=model,
+        )
+
+    def _call_via_bot(self, model: str, question: str, image_content: dict,
+                      provider: Optional[VisionProvider] = None) -> ToolResult:
+        """
+        Call a model's call_vision with vendor-native API format.
+        Uses the provider's _fallback_bot if set, otherwise the main model bot.
+        Raises VisionAPIError on failure so fallback can proceed.
+        """
+        try:
+            bot = (provider and provider.fallback_bot) or self.model.bot
+        except Exception as e:
+            raise VisionAPIError(f"Cannot access bot: {e}")
+
+        # Extract the raw image URL from the OpenAI-format image_content block
+        image_url = image_content.get("image_url", {}).get("url", "")
+        if not image_url:
+            raise VisionAPIError("No image URL in content block")
+
+        try:
+            response = bot.call_vision(
+                image_url=image_url,
+                question=question,
+                model=model,
+                max_tokens=MAX_TOKENS,
+            )
+        except Exception as e:
+            raise VisionAPIError(f"call_vision failed: {e}")
+
+        if response is NotImplemented:
+            raise VisionAPIError("Bot does not support vision")
+
+        if isinstance(response, dict) and response.get("error"):
+            raise VisionAPIError(f"API error - {response.get('message', 'Unknown')}")
+
+        content = response.get("content", "") if isinstance(response, dict) else ""
+        if not content:
+            raise VisionAPIError("Empty response from main model")
+
+        usage_info = response.get("usage", {}) if isinstance(response, dict) else {}
+
+        # Use the actual model name from the bot response if available
+        actual_model = response.get("model", model) if isinstance(response, dict) else model
+        provider_name = provider.name if provider else _MAIN_MODEL_PROVIDER_NAME
+        return ToolResult.success({
+            "model": actual_model,
+            "provider": provider_name,
+            "content": content,
+            "usage": usage_info,
+        })
+
+    @staticmethod
+    def _ensure_v1(api_base: str) -> str:
+        """Append /v1 if the base URL doesn't already end with a versioned path."""
+        if not api_base:
+            return api_base
+        # Already has /v1 or similar version suffix
+        if api_base.rstrip("/").split("/")[-1].startswith("v"):
+            return api_base
+        return api_base.rstrip("/") + "/v1"
+
+    @staticmethod
+    def _validate_url_safe(url: str) -> None:
+        """Reject URLs that target private/loopback/link-local addresses (SSRF guard).
+
+        Resolves the hostname to its IP address(es) and blocks any that fall
+        into non-public ranges.  Also rejects URLs with no host, non-HTTP(S)
+        schemes, or hosts that fail DNS resolution.
+
+        Delegates to the shared ``agent.tools.utils.url_safety`` helper so the
+        same guard protects every tool that fetches model-supplied URLs.
+
+        Raises:
+            ValueError: if the URL targets a disallowed address.
+        """
+        validate_url_safe(url)
+
+    def _build_image_content(self, image: str) -> dict:
+        """
+        Build the image_url content block.
+        Both remote URLs and local files are converted to base64 data URLs
+        so every bot backend can consume them without extra downloads.
+        """
+        if image.startswith(("http://", "https://")):
+            self._validate_url_safe(image)
+            return self._download_to_data_url(image)
+
+        if not os.path.isfile(image):
+            raise FileNotFoundError(f"Image file not found: {image}")
+
+        ext = image.rsplit(".", 1)[-1].lower() if "." in image else ""
+        mime_type = SUPPORTED_EXTENSIONS.get(ext)
+        if not mime_type:
+            raise ValueError(
+                f"Unsupported image format '.{ext}'. "
+                f"Supported: {', '.join(SUPPORTED_EXTENSIONS.keys())}"
+            )
+
+        file_path = self._maybe_compress(image)
+        try:
+            with open(file_path, "rb") as f:
+                b64 = base64.b64encode(f.read()).decode("ascii")
+        finally:
+            if file_path != image and os.path.exists(file_path):
+                os.remove(file_path)
+
+        data_url = f"data:{mime_type};base64,{b64}"
+        return {"type": "image_url", "image_url": {"url": data_url}}
+
+    @staticmethod
+    def _download_to_data_url(url: str) -> dict:
+        """Download a remote image and return it as a base64 data URL."""
+        resp = requests.get(url, timeout=30)
+        if resp.status_code != 200:
+            raise VisionAPIError(f"Failed to download image: HTTP {resp.status_code}")
+        content_type = resp.headers.get("Content-Type", "image/jpeg").split(";")[0].strip()
+        if not content_type.startswith("image/"):
+            content_type = "image/jpeg"
+        b64 = base64.b64encode(resp.content).decode("ascii")
+        data_url = f"data:{content_type};base64,{b64}"
+        return {"type": "image_url", "image_url": {"url": data_url}}
+
+    @staticmethod
+    def _maybe_compress(path: str) -> str:
+        """Compress image to under COMPRESS_THRESHOLD with max long-edge 1536px."""
+        file_size = os.path.getsize(path)
+        if file_size <= COMPRESS_THRESHOLD:
+            return path
+
+        tmp = tempfile.NamedTemporaryFile(suffix=".jpg", delete=False)
+        tmp.close()
+
+        def _try_sips(max_dim: str, quality: str) -> bool:
+            try:
+                subprocess.run(
+                    ["sips", "-Z", max_dim, "-s", "formatOptions", quality,
+                     path, "--out", tmp.name],
+                    capture_output=True, check=True,
+                )
+                return True
+            except (FileNotFoundError, subprocess.CalledProcessError):
+                return False
+
+        def _try_convert(max_dim: str, quality: str) -> bool:
+            try:
+                subprocess.run(
+                    ["convert", path, "-resize", f"{max_dim}x{max_dim}>",
+                     "-quality", quality, tmp.name],
+                    capture_output=True, check=True,
+                )
+                return True
+            except (FileNotFoundError, subprocess.CalledProcessError):
+                return False
+
+        attempts = [
+            ("1536", "85"),
+            ("1536", "70"),
+            ("1536", "50"),
+        ]
+
+        for max_dim, quality in attempts:
+            ok = _try_sips(max_dim, quality) or _try_convert(max_dim, quality)
+            if not ok:
+                continue
+            new_size = os.path.getsize(tmp.name)
+            logger.debug(f"[Vision] Compressed image "
+                         f"({file_size // 1024}KB -> {new_size // 1024}KB, "
+                         f"max_dim={max_dim}, q={quality})")
+            if new_size <= COMPRESS_THRESHOLD:
+                return tmp.name
+
+        if os.path.exists(tmp.name) and os.path.getsize(tmp.name) > 0:
+            return tmp.name
+
+        os.remove(tmp.name)
+        return path
+
+    def _call_api(self, provider: VisionProvider, model: str,
+                  question: str, image_content: dict) -> ToolResult:
+        """
+        Call a single provider's Vision API.
+        Raises VisionAPIError on recoverable failures so the caller can try
+        the next provider.
+        """
+        payload = {
+            "model": model,
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        image_content,
+                    ],
+                }
+            ],
+        }
+
+        headers = {
+            "Authorization": f"Bearer {provider.api_key}",
+            "Content-Type": "application/json",
+            **provider.extra_headers,
+        }
+
+        resp = requests.post(
+            f"{provider.api_base}/chat/completions",
+            headers=headers,
+            json=payload,
+            timeout=DEFAULT_TIMEOUT,
+        )
+
+        if resp.status_code != 200:
+            raise VisionAPIError(f"HTTP {resp.status_code}: {resp.text[:200]}")
+
+        data = resp.json()
+
+        if "error" in data:
+            msg = data["error"].get("message", "Unknown API error")
+            raise VisionAPIError(f"API error - {msg}")
+
+        content = ""
+        choices = data.get("choices", [])
+        if choices:
+            content = choices[0].get("message", {}).get("content", "")
+
+        usage = data.get("usage", {})
+        result = {
+            "model": model,
+            "provider": provider.name,
+            "content": content,
+            "usage": {
+                "prompt_tokens": usage.get("prompt_tokens", 0),
+                "completion_tokens": usage.get("completion_tokens", 0),
+                "total_tokens": usage.get("total_tokens", 0),
+            },
+        }
+        return ToolResult.success(result)
diff --git a/agent/tools/web_fetch/__init__.py b/agent/tools/web_fetch/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/agent/tools/web_fetch/web_fetch.py b/agent/tools/web_fetch/web_fetch.py
new file mode 100644
index 0000000..a80356c
--- /dev/null
+++ b/agent/tools/web_fetch/web_fetch.py
@@ -0,0 +1,489 @@
+"""
+Web Fetch tool - Fetch and extract readable content from web pages and remote files.
+
+Supports:
+- HTML web pages: extracts readable text content
+- Document files (PDF, Word, TXT, Markdown, etc.): downloads to workspace/tmp and parses content
+"""
+
+import os
+import re
+import uuid
+from typing import Dict, Any, Optional, Set
+from urllib.parse import urlparse, unquote
+
+import requests
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from agent.tools.utils.truncate import truncate_head, format_size
+from agent.tools.utils.url_safety import validate_url_safe
+from common.log import logger
+
+
+DEFAULT_TIMEOUT = 30
+MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
+# Cap on how many redirects we follow; each hop's target is re-validated
+# against the SSRF guard so a public URL cannot bounce us into an internal one.
+MAX_REDIRECTS = 10
+
+DEFAULT_HEADERS = {
+    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
+    "Accept": "*/*",
+}
+
+# Supported document file extensions
+PDF_SUFFIXES: Set[str] = {".pdf"}
+WORD_SUFFIXES: Set[str] = {".docx"}
+TEXT_SUFFIXES: Set[str] = {".txt", ".md", ".markdown", ".rst", ".csv", ".tsv", ".log"}
+SPREADSHEET_SUFFIXES: Set[str] = {".xls", ".xlsx"}
+PPT_SUFFIXES: Set[str] = {".ppt", ".pptx"}
+
+ALL_DOC_SUFFIXES = PDF_SUFFIXES | WORD_SUFFIXES | TEXT_SUFFIXES | SPREADSHEET_SUFFIXES | PPT_SUFFIXES
+
+_CHARSET_RE = re.compile(r'charset\s*=\s*["\']?\s*([\w\-]+)', re.IGNORECASE)
+_META_CHARSET_RE = re.compile(rb'<meta[^>]+charset\s*=\s*["\']?\s*([\w\-]+)', re.IGNORECASE)
+_META_HTTP_EQUIV_RE = re.compile(
+    rb'<meta[^>]+http-equiv\s*=\s*["\']?Content-Type["\']?[^>]+content\s*=\s*["\'][^"\']*charset=([\w\-]+)',
+    re.IGNORECASE,
+)
+
+
+def _extract_charset_from_content_type(content_type: str) -> Optional[str]:
+    """Extract charset from Content-Type header value."""
+    m = _CHARSET_RE.search(content_type)
+    return m.group(1) if m else None
+
+
+def _extract_charset_from_html_meta(raw_bytes: bytes) -> Optional[str]:
+    """Extract charset from HTML <meta> tags in the first few KB of raw bytes."""
+    m = _META_CHARSET_RE.search(raw_bytes)
+    if m:
+        return m.group(1).decode("ascii", errors="ignore")
+    m = _META_HTTP_EQUIV_RE.search(raw_bytes)
+    if m:
+        return m.group(1).decode("ascii", errors="ignore")
+    return None
+
+
+def _get_url_suffix(url: str) -> str:
+    """Extract file extension from URL path, ignoring query params."""
+    path = urlparse(url).path
+    return os.path.splitext(path)[-1].lower()
+
+
+def _is_document_url(url: str) -> bool:
+    """Check if URL points to a downloadable document file."""
+    suffix = _get_url_suffix(url)
+    return suffix in ALL_DOC_SUFFIXES
+
+
+class WebFetch(BaseTool):
+    """Tool for fetching web pages and remote document files"""
+
+    name: str = "web_fetch"
+    description: str = (
+        "Fetch content from a http/https URL. For web pages, extracts readable text. "
+        "For document files (PDF, Word, TXT, Markdown, Excel, PPT), downloads and parses the file content. "
+        "Supported file types: .pdf, .docx, .txt, .md, .csv, .xls, .xlsx, .ppt, .pptx"
+    )
+
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "url": {
+                "type": "string",
+                "description": "The HTTP/HTTPS URL to fetch (web page or document file link)"
+            }
+        },
+        "required": ["url"]
+    }
+
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        url = args.get("url", "").strip()
+        if not url:
+            return ToolResult.fail("Error: 'url' parameter is required")
+
+        parsed = urlparse(url)
+        if parsed.scheme not in ("http", "https"):
+            return ToolResult.fail("Error: Invalid URL (must start with http:// or https://)")
+
+        # SSRF guard: reject URLs that resolve to private/loopback/link-local/
+        # cloud-metadata addresses before any request is issued.
+        try:
+            validate_url_safe(url)
+        except ValueError as e:
+            return ToolResult.fail(f"Error: {e}")
+
+        if _is_document_url(url):
+            return self._fetch_document(url)
+
+        return self._fetch_webpage(url)
+
+    # ---- Safe request helper ----
+
+    @staticmethod
+    def _safe_get(url: str, **kwargs) -> requests.Response:
+        """Issue a GET request while re-validating every redirect hop (SSRF guard).
+
+        Auto-redirect is disabled and each hop is followed manually so the
+        target of every redirect is re-resolved and checked against the SSRF
+        guard. This prevents a public URL from 3xx-bouncing into a private,
+        loopback, link-local or cloud-metadata address. ``kwargs`` are passed
+        through to ``requests.get`` (e.g. ``stream``).
+
+        Raises:
+            ValueError: if any hop resolves to a non-public address.
+        """
+        kwargs.pop("allow_redirects", None)
+        current = url
+        for _ in range(MAX_REDIRECTS + 1):
+            response = requests.get(
+                current,
+                headers=DEFAULT_HEADERS,
+                timeout=DEFAULT_TIMEOUT,
+                allow_redirects=False,
+                **kwargs,
+            )
+            if not response.is_redirect and not response.is_permanent_redirect:
+                return response
+
+            location = response.headers.get("Location")
+            if not location:
+                return response
+
+            # Resolve the redirect target relative to the current URL, then
+            # re-validate it before following.
+            current = requests.compat.urljoin(current, location)
+            validate_url_safe(current)
+            response.close()
+
+        raise ValueError(f"Too many redirects (>{MAX_REDIRECTS})")
+
+    # ---- Web page fetching ----
+
+    def _fetch_webpage(self, url: str) -> ToolResult:
+        """Fetch and extract readable text from an HTML web page."""
+        parsed = urlparse(url)
+        try:
+            response = self._safe_get(url)
+            response.raise_for_status()
+        except requests.Timeout:
+            return ToolResult.fail(f"Error: Request timed out after {DEFAULT_TIMEOUT}s")
+        except requests.ConnectionError:
+            return ToolResult.fail(f"Error: Failed to connect to {parsed.netloc}")
+        except requests.HTTPError as e:
+            return ToolResult.fail(f"Error: HTTP {e.response.status_code} for URL: {url}")
+        except ValueError as e:
+            return ToolResult.fail(f"Error: {e}")
+        except Exception as e:
+            return ToolResult.fail(f"Error: Failed to fetch URL: {e}")
+
+        content_type = response.headers.get("Content-Type", "")
+        if self._is_binary_content_type(content_type) and not _is_document_url(url):
+            return self._handle_download_by_content_type(url, response, content_type)
+
+        response.encoding = self._detect_encoding(response)
+        html = response.text
+        title = self._extract_title(html)
+        text = self._extract_text(html)
+
+        return ToolResult.success(f"Title: {title}\n\nContent:\n{text}")
+
+    # ---- Document fetching ----
+
+    def _fetch_document(self, url: str) -> ToolResult:
+        """Download a document file and extract its text content."""
+        suffix = _get_url_suffix(url)
+        parsed = urlparse(url)
+        filename = self._extract_filename(url)
+        tmp_dir = self._ensure_tmp_dir()
+
+        local_path = os.path.join(tmp_dir, filename)
+        logger.info(f"[WebFetch] Downloading document: {url} -> {local_path}")
+
+        try:
+            response = self._safe_get(url, stream=True)
+            response.raise_for_status()
+
+            content_length = int(response.headers.get("Content-Length", 0))
+            if content_length > MAX_FILE_SIZE:
+                return ToolResult.fail(
+                    f"Error: File too large ({format_size(content_length)} > {format_size(MAX_FILE_SIZE)})"
+                )
+
+            downloaded = 0
+            with open(local_path, "wb") as f:
+                for chunk in response.iter_content(chunk_size=8192):
+                    downloaded += len(chunk)
+                    if downloaded > MAX_FILE_SIZE:
+                        f.close()
+                        os.remove(local_path)
+                        return ToolResult.fail(
+                            f"Error: File too large (>{format_size(MAX_FILE_SIZE)}), download aborted"
+                        )
+                    f.write(chunk)
+
+        except requests.Timeout:
+            return ToolResult.fail(f"Error: Download timed out after {DEFAULT_TIMEOUT}s")
+        except requests.ConnectionError:
+            return ToolResult.fail(f"Error: Failed to connect to {parsed.netloc}")
+        except requests.HTTPError as e:
+            return ToolResult.fail(f"Error: HTTP {e.response.status_code} for URL: {url}")
+        except ValueError as e:
+            self._cleanup_file(local_path)
+            return ToolResult.fail(f"Error: {e}")
+        except Exception as e:
+            self._cleanup_file(local_path)
+            return ToolResult.fail(f"Error: Failed to download file: {e}")
+
+        try:
+            text = self._parse_document(local_path, suffix)
+        except Exception as e:
+            self._cleanup_file(local_path)
+            return ToolResult.fail(f"Error: Failed to parse document: {e}")
+
+        if not text or not text.strip():
+            file_size = os.path.getsize(local_path)
+            return ToolResult.success(
+                f"File downloaded to: {local_path} ({format_size(file_size)})\n"
+                f"No text content could be extracted. The file may contain only images or be encrypted."
+            )
+
+        truncation = truncate_head(text)
+        result_text = truncation.content
+
+        file_size = os.path.getsize(local_path)
+        header = f"[Document: {filename} | Size: {format_size(file_size)} | Saved to: {local_path}]\n\n"
+
+        if truncation.truncated:
+            header += f"[Content truncated: showing {truncation.output_lines} of {truncation.total_lines} lines]\n\n"
+
+        return ToolResult.success(header + result_text)
+
+    def _parse_document(self, file_path: str, suffix: str) -> str:
+        """Parse document file and return extracted text."""
+        if suffix in PDF_SUFFIXES:
+            return self._parse_pdf(file_path)
+        elif suffix in WORD_SUFFIXES:
+            return self._parse_word(file_path)
+        elif suffix in TEXT_SUFFIXES:
+            return self._parse_text(file_path)
+        elif suffix in SPREADSHEET_SUFFIXES:
+            return self._parse_spreadsheet(file_path)
+        elif suffix in PPT_SUFFIXES:
+            return self._parse_ppt(file_path)
+        else:
+            return self._parse_text(file_path)
+
+    def _parse_pdf(self, file_path: str) -> str:
+        """Extract text from PDF using pypdf."""
+        try:
+            from pypdf import PdfReader
+        except ImportError:
+            raise ImportError("pypdf library is required for PDF parsing. Install with: pip install pypdf")
+
+        reader = PdfReader(file_path)
+        text_parts = []
+        for page_num, page in enumerate(reader.pages, 1):
+            page_text = page.extract_text()
+            if page_text and page_text.strip():
+                text_parts.append(f"--- Page {page_num}/{len(reader.pages)} ---\n{page_text}")
+
+        return "\n\n".join(text_parts)
+
+    def _parse_word(self, file_path: str) -> str:
+        """Extract text from Word documents (.docx)."""
+        try:
+            from docx import Document
+        except ImportError:
+            raise ImportError(
+                "python-docx library is required for .docx parsing. Install with: pip install python-docx"
+            )
+        doc = Document(file_path)
+        paragraphs = [p.text for p in doc.paragraphs if p.text.strip()]
+        return "\n\n".join(paragraphs)
+
+    def _parse_text(self, file_path: str) -> str:
+        """Read plain text files (txt, md, csv, etc.)."""
+        encodings = ["utf-8", "utf-8-sig", "gbk", "gb2312", "latin-1"]
+        for enc in encodings:
+            try:
+                with open(file_path, "r", encoding=enc) as f:
+                    return f.read()
+            except (UnicodeDecodeError, UnicodeError):
+                continue
+        raise ValueError(f"Unable to decode file with any supported encoding: {encodings}")
+
+    def _parse_spreadsheet(self, file_path: str) -> str:
+        """Extract text from Excel files (.xls/.xlsx)."""
+        try:
+            import openpyxl
+        except ImportError:
+            raise ImportError(
+                "openpyxl library is required for .xlsx parsing. Install with: pip install openpyxl"
+            )
+
+        wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True)
+        result_parts = []
+
+        for sheet_name in wb.sheetnames:
+            ws = wb[sheet_name]
+            rows = []
+            for row in ws.iter_rows(values_only=True):
+                cells = [str(c) if c is not None else "" for c in row]
+                if any(cells):
+                    rows.append(" | ".join(cells))
+            if rows:
+                result_parts.append(f"--- Sheet: {sheet_name} ---\n" + "\n".join(rows))
+
+        wb.close()
+        return "\n\n".join(result_parts)
+
+    def _parse_ppt(self, file_path: str) -> str:
+        """Extract text from PowerPoint files (.ppt/.pptx)."""
+        try:
+            from pptx import Presentation
+        except ImportError:
+            raise ImportError(
+                "python-pptx library is required for .pptx parsing. Install with: pip install python-pptx"
+            )
+
+        prs = Presentation(file_path)
+        text_parts = []
+
+        for slide_num, slide in enumerate(prs.slides, 1):
+            slide_texts = []
+            for shape in slide.shapes:
+                if shape.has_text_frame:
+                    for paragraph in shape.text_frame.paragraphs:
+                        text = paragraph.text.strip()
+                        if text:
+                            slide_texts.append(text)
+            if slide_texts:
+                text_parts.append(f"--- Slide {slide_num}/{len(prs.slides)} ---\n" + "\n".join(slide_texts))
+
+        return "\n\n".join(text_parts)
+
+    # ---- Encoding detection ----
+
+    @staticmethod
+    def _detect_encoding(response: requests.Response) -> str:
+        """Detect response encoding with priority: Content-Type header > HTML meta > chardet > utf-8."""
+        # 1. Check Content-Type header for explicit charset
+        content_type = response.headers.get("Content-Type", "")
+        charset = _extract_charset_from_content_type(content_type)
+        if charset:
+            return charset
+
+        # 2. Scan raw bytes for HTML meta charset declaration
+        raw = response.content[:4096]
+        charset = _extract_charset_from_html_meta(raw)
+        if charset:
+            return charset
+
+        # 3. Use apparent_encoding (chardet-based detection) if confident enough
+        apparent = response.apparent_encoding
+        if apparent:
+            apparent_lower = apparent.lower()
+            # Trust CJK / Windows encodings detected by chardet
+            trusted_prefixes = ("utf", "gb", "big5", "euc", "shift_jis", "iso-2022", "windows", "ascii")
+            if any(apparent_lower.startswith(p) for p in trusted_prefixes):
+                return apparent
+
+        # 4. Fallback
+        return "utf-8"
+
+    # ---- Helper methods ----
+
+    def _ensure_tmp_dir(self) -> str:
+        """Ensure workspace/tmp directory exists and return its path."""
+        tmp_dir = os.path.join(self.cwd, "tmp")
+        os.makedirs(tmp_dir, exist_ok=True)
+        return tmp_dir
+
+    def _extract_filename(self, url: str) -> str:
+        """Extract a safe filename from URL, with a short UUID prefix to avoid collisions."""
+        path = urlparse(url).path
+        basename = os.path.basename(unquote(path))
+        if not basename or basename == "/":
+            basename = "downloaded_file"
+        # Sanitize: keep only safe chars
+        basename = re.sub(r'[^\w.\-]', '_', basename)
+        short_id = uuid.uuid4().hex[:8]
+        return f"{short_id}_{basename}"
+
+    @staticmethod
+    def _cleanup_file(path: str):
+        """Remove a file if it exists, ignoring errors."""
+        try:
+            if os.path.exists(path):
+                os.remove(path)
+        except Exception:
+            pass
+
+    @staticmethod
+    def _is_binary_content_type(content_type: str) -> bool:
+        """Check if Content-Type indicates a binary/document response."""
+        binary_types = [
+            "application/pdf",
+            "application/vnd.openxmlformats",
+            "application/vnd.ms-excel",
+            "application/vnd.ms-powerpoint",
+            "application/octet-stream",
+        ]
+        ct_lower = content_type.lower()
+        return any(bt in ct_lower for bt in binary_types)
+
+    def _handle_download_by_content_type(self, url: str, response: requests.Response, content_type: str) -> ToolResult:
+        """Handle a URL that returned binary content instead of HTML."""
+        ct_lower = content_type.lower()
+        suffix_map = {
+            "application/pdf": ".pdf",
+            "application/vnd.openxmlformats-officedocument.wordprocessingml": ".docx",
+            "application/vnd.ms-excel": ".xls",
+            "application/vnd.openxmlformats-officedocument.spreadsheetml": ".xlsx",
+            "application/vnd.ms-powerpoint": ".ppt",
+            "application/vnd.openxmlformats-officedocument.presentationml": ".pptx",
+        }
+        detected_suffix = None
+        for ct_prefix, ext in suffix_map.items():
+            if ct_prefix in ct_lower:
+                detected_suffix = ext
+                break
+
+        if detected_suffix and detected_suffix in ALL_DOC_SUFFIXES:
+            # Re-fetch as document
+            return self._fetch_document(url if _get_url_suffix(url) in ALL_DOC_SUFFIXES
+                                        else self._rewrite_url_with_suffix(url, detected_suffix))
+        return ToolResult.fail(f"Error: URL returned binary content ({content_type}), not a supported document type")
+
+    @staticmethod
+    def _rewrite_url_with_suffix(url: str, suffix: str) -> str:
+        """Append a suffix to the URL path so _get_url_suffix works correctly."""
+        parsed = urlparse(url)
+        new_path = parsed.path.rstrip("/") + suffix
+        return parsed._replace(path=new_path).geturl()
+
+    # ---- HTML extraction (unchanged) ----
+
+    @staticmethod
+    def _extract_title(html: str) -> str:
+        match = re.search(r"<title[^>]*>(.*?)</title>", html, re.IGNORECASE | re.DOTALL)
+        return match.group(1).strip() if match else "Untitled"
+
+    @staticmethod
+    def _extract_text(html: str) -> str:
+        text = re.sub(r"<script[^>]*>.*?</script>", "", html, flags=re.IGNORECASE | re.DOTALL)
+        text = re.sub(r"<style[^>]*>.*?</style>", "", text, flags=re.IGNORECASE | re.DOTALL)
+        text = re.sub(r"<[^>]+>", "", text)
+        text = text.replace("&amp;", "&").replace("&lt;", "<").replace("&gt;", ">")
+        text = text.replace("&quot;", '"').replace("&#39;", "'").replace("&nbsp;", " ")
+        text = re.sub(r"[^\S\n]+", " ", text)
+        text = re.sub(r"\n{3,}", "\n\n", text)
+        lines = [line.strip() for line in text.splitlines()]
+        text = "\n".join(lines)
+        return text.strip()
diff --git a/agent/tools/web_search/__init__.py b/agent/tools/web_search/__init__.py
new file mode 100644
index 0000000..9f126fd
--- /dev/null
+++ b/agent/tools/web_search/__init__.py
@@ -0,0 +1,3 @@
+from agent.tools.web_search.web_search import WebSearch
+
+__all__ = ["WebSearch"]
diff --git a/agent/tools/web_search/web_search.py b/agent/tools/web_search/web_search.py
new file mode 100644
index 0000000..ca56567
--- /dev/null
+++ b/agent/tools/web_search/web_search.py
@@ -0,0 +1,487 @@
+"""Web Search tool. Supports four backends with a unified response format:
+  - bocha   (https://open.bochaai.com)
+  - zhipu   (https://docs.bigmodel.cn/cn/guide/tools/web-search)
+  - qianfan (https://cloud.baidu.com/doc/qianfan/s/2mh4su4uy)
+  - linkai  (https://link-ai.tech, fallback)
+
+Provider selection
+  - strategy 'auto' (default): pick the first configured provider in the
+    canonical order [bocha, zhipu, qianfan, linkai]. When the caller passes
+    an explicit `provider` it overrides the pick; an invalid/unconfigured
+    one silently falls back to the auto order.
+  - strategy 'fixed': use the configured provider; if its credential is
+    missing at call time, silently fall back to auto order (no card hint).
+
+Credentials
+  - bocha   : tools.web_search.bocha_api_key  ->  env BOCHA_API_KEY
+  - zhipu   : conf.zhipu_ai_api_key            ->  env ZHIPUAI_API_KEY
+  - qianfan : conf.qianfan_api_key             ->  env QIANFAN_API_KEY
+  - linkai  : conf.linkai_api_key              ->  env LINKAI_API_KEY
+"""
+
+import json
+import os
+from typing import Any, Dict, List, Optional
+
+import requests
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.log import logger
+from config import conf
+
+
+DEFAULT_TIMEOUT = 30
+
+# Canonical fallback order. Empirically ordered by Chinese real-time
+# quality + relevance: bocha (best overall), qianfan (best for hot news),
+# zhipu (strong on long-form articles), linkai (cloud aggregator, last
+# resort).
+PROVIDER_ORDER = ("bocha", "qianfan", "zhipu", "linkai")
+
+PROVIDER_LABELS = {
+    "bocha":   "Bocha",
+    "zhipu":   "Zhipu",
+    "qianfan": "Baidu Qianfan",
+    "linkai":  "LinkAI",
+}
+
+
+def _tools_web_search_conf() -> dict:
+    """Return the tools.web_search config block (dict-like)."""
+    tools_cfg = conf().get("tools") or {}
+    if not isinstance(tools_cfg, dict):
+        return {}
+    block = tools_cfg.get("web_search") or {}
+    return block if isinstance(block, dict) else {}
+
+
+def _get_api_key(provider: str) -> str:
+    """Resolve API key for a provider, with conf -> env fallback."""
+    if provider == "bocha":
+        key = (_tools_web_search_conf().get("bocha_api_key") or "").strip()
+        return key or os.environ.get("BOCHA_API_KEY", "").strip()
+    if provider == "zhipu":
+        key = (conf().get("zhipu_ai_api_key") or "").strip()
+        return key or os.environ.get("ZHIPUAI_API_KEY", "").strip()
+    if provider == "qianfan":
+        key = (conf().get("qianfan_api_key") or "").strip()
+        return key or os.environ.get("QIANFAN_API_KEY", "").strip()
+    if provider == "linkai":
+        key = (conf().get("linkai_api_key") or "").strip()
+        return key or os.environ.get("LINKAI_API_KEY", "").strip()
+    return ""
+
+
+def configured_providers() -> List[str]:
+    """Return configured providers in canonical order."""
+    return [p for p in PROVIDER_ORDER if _get_api_key(p)]
+
+
+def _configured_strategy() -> str:
+    return (_tools_web_search_conf().get("strategy") or "auto").strip().lower()
+
+
+def _configured_provider() -> str:
+    return (_tools_web_search_conf().get("provider") or "").strip().lower()
+
+
+class WebSearch(BaseTool):
+    """Tool for searching the web across multiple providers."""
+
+    name: str = "web_search"
+    description: str = "Search the web for real-time information. Returns titles, URLs, and snippets."
+
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "query": {
+                "type": "string",
+                "description": "Search query string"
+            },
+            "count": {
+                "type": "integer",
+                "description": "Number of results to return (1-50, default: 10)"
+            },
+            "freshness": {
+                "type": "string",
+                "description": (
+                    "Time range filter. Options: "
+                    "'noLimit' (default), 'oneDay', 'oneWeek', 'oneMonth', 'oneYear', "
+                    "or date range like '2025-01-01..2025-02-01'"
+                )
+            },
+            "summary": {
+                "type": "boolean",
+                "description": "Whether to include text summary for each result (default: false)"
+            }
+        },
+        "required": ["query"]
+    }
+
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+
+    @staticmethod
+    def is_available() -> bool:
+        """Tool is offered to the agent when at least one provider has a key."""
+        return bool(configured_providers())
+
+    @classmethod
+    def get_json_schema(cls) -> dict:
+        """Augment the static schema with a `provider` field — only when the
+        user has ≥2 providers configured AND strategy is 'auto'. Otherwise
+        the backend picks silently and exposing the field would only waste
+        the agent's tokens."""
+        schema = {
+            "name": cls.name,
+            "description": cls.description,
+            "parameters": json.loads(json.dumps(cls.params)),  # deep copy
+        }
+        if _configured_strategy() != "auto":
+            return schema
+        available = configured_providers()
+        if len(available) < 2:
+            return schema
+
+        schema["parameters"]["properties"]["provider"] = {
+            "type": "string",
+            "enum": available,
+            "description": "Optional. Specifies the search backend. You may switch between providers when the user wants results from a particular source or from multiple sources.",
+        }
+        return schema
+
+    # ------------------------------------------------------------------
+    # Provider resolution
+    # ------------------------------------------------------------------
+
+    def _resolve_provider(self, requested: Optional[str]) -> Optional[str]:
+        """Pick a provider for this call.
+
+        Priority: caller-supplied (if configured) > fixed strategy (if
+        configured) > first configured in PROVIDER_ORDER. Silent fallback
+        when the desired one has no key.
+        """
+        available = configured_providers()
+        if not available:
+            return None
+
+        if requested:
+            req = requested.strip().lower()
+            if req in available:
+                return req
+            logger.warning(f"[WebSearch] requested provider '{requested}' unavailable, falling back")
+
+        if _configured_strategy() == "fixed":
+            pinned = _configured_provider()
+            if pinned in available:
+                return pinned
+            if pinned:
+                logger.warning(f"[WebSearch] pinned provider '{pinned}' unavailable, falling back to auto")
+
+        return available[0]
+
+    @staticmethod
+    def _resolution_reason(requested: Optional[str], chosen: str) -> str:
+        """Human-readable explanation for why `chosen` won the resolver."""
+        if requested and requested.strip().lower() == chosen:
+            return "caller-requested"
+        strategy = _configured_strategy()
+        if strategy == "fixed" and _configured_provider() == chosen:
+            return "fixed-strategy"
+        return "auto-fallback"
+
+    # ------------------------------------------------------------------
+    # Entry point
+    # ------------------------------------------------------------------
+
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        query = (args.get("query") or "").strip()
+        if not query:
+            return ToolResult.fail("Error: 'query' parameter is required")
+
+        count = args.get("count", 10)
+        freshness = args.get("freshness", "noLimit")
+        summary = args.get("summary", False)
+        if not isinstance(count, int) or count < 1 or count > 50:
+            count = 10
+
+        requested = args.get("provider")
+        provider = self._resolve_provider(requested)
+        if not provider:
+            return ToolResult.fail(
+                "Error: No search provider configured. "
+                "Configure one of BOCHA_API_KEY / zhipu_ai_api_key / qianfan_api_key / linkai_api_key."
+            )
+
+        # Always log the routing decision so multi-provider deployments can
+        # tell at a glance which backend served any given query.
+        available = configured_providers()
+        reason = self._resolution_reason(requested, provider)
+        q_preview = query if len(query) <= 60 else (query[:57] + "...")
+        logger.info(
+            f"[WebSearch] provider={provider} reason={reason} "
+            f"available={list(available)} query={q_preview!r} count={count} freshness={freshness}"
+        )
+
+        try:
+            if provider == "bocha":
+                return self._search_bocha(query, count, freshness, summary)
+            if provider == "zhipu":
+                return self._search_zhipu(query, count, freshness)
+            if provider == "qianfan":
+                return self._search_qianfan(query, count, freshness)
+            if provider == "linkai":
+                return self._search_linkai(query, count, freshness)
+            return ToolResult.fail(f"Error: Unknown provider '{provider}'")
+        except requests.Timeout:
+            return ToolResult.fail(f"Error: Search request timed out after {DEFAULT_TIMEOUT}s")
+        except requests.ConnectionError:
+            return ToolResult.fail("Error: Failed to connect to search API")
+        except Exception as e:
+            logger.error(f"[WebSearch] Unexpected error ({provider}): {e}", exc_info=True)
+            return ToolResult.fail(f"Error: Search failed - {str(e)}")
+
+    # ------------------------------------------------------------------
+    # Bocha
+    # ------------------------------------------------------------------
+
+    def _search_bocha(self, query: str, count: int, freshness: str, summary: bool) -> ToolResult:
+        api_key = _get_api_key("bocha")
+        url = "https://api.bochaai.com/v1/web-search"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+            "Accept": "application/json",
+        }
+        payload = {"query": query, "count": count, "freshness": freshness, "summary": summary}
+
+        logger.debug(f"[WebSearch] bocha: query='{query}', count={count}")
+        resp = requests.post(url, headers=headers, json=payload, timeout=DEFAULT_TIMEOUT)
+
+        if resp.status_code == 401:
+            return ToolResult.fail("Error: Invalid bocha API key.")
+        if resp.status_code == 403:
+            return ToolResult.fail("Error: bocha API — insufficient balance. Top up at https://open.bochaai.com")
+        if resp.status_code == 429:
+            return ToolResult.fail("Error: bocha API rate limit reached.")
+        if resp.status_code != 200:
+            return ToolResult.fail(f"Error: bocha API returned HTTP {resp.status_code}")
+
+        data = resp.json()
+        api_code = data.get("code")
+        if api_code is not None and api_code != 200:
+            msg = data.get("msg") or "Unknown error"
+            return ToolResult.fail(f"Error: bocha API error (code={api_code}): {msg}")
+
+        pages = (data.get("data") or {}).get("webPages", {}).get("value", []) or []
+        results = []
+        for p in pages:
+            item = {
+                "title": p.get("name", ""),
+                "url": p.get("url", ""),
+                "snippet": p.get("snippet", ""),
+                "siteName": p.get("siteName", ""),
+                "datePublished": p.get("datePublished") or p.get("dateLastCrawled", ""),
+            }
+            if p.get("summary"):
+                item["summary"] = p["summary"]
+            results.append(item)
+        total = (data.get("data") or {}).get("webPages", {}).get("totalEstimatedMatches", len(results))
+        return ToolResult.success({
+            "query": query, "backend": "bocha",
+            "total": total, "count": len(results), "results": results,
+        })
+
+    # ------------------------------------------------------------------
+    # Zhipu
+    # ------------------------------------------------------------------
+
+    def _search_zhipu(self, query: str, count: int, freshness: str) -> ToolResult:
+        api_key = _get_api_key("zhipu")
+        api_base = (conf().get("zhipu_ai_api_base") or "https://open.bigmodel.cn/api/paas/v4").rstrip("/")
+        url = f"{api_base}/web_search"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+        }
+
+        # Zhipu Web Search expects `search_query` <= 70 chars; truncate
+        # gracefully so a long agent-supplied query doesn't get rejected.
+        trimmed_query = (query or "")[:70]
+        engine = (_tools_web_search_conf().get("zhipu_search_engine") or "search_pro").strip().lower()
+        if engine not in ("search_std", "search_pro", "search_pro_sogou", "search_pro_quark"):
+            engine = "search_pro"
+
+        payload: Dict[str, Any] = {
+            "search_engine": engine,
+            "search_query": trimmed_query,
+            "search_intent": False,
+            "count": max(1, min(int(count or 10), 50)),
+            "search_recency_filter": freshness if freshness in (
+                "oneDay", "oneWeek", "oneMonth", "oneYear", "noLimit"
+            ) else "noLimit",
+        }
+        content_size = (_tools_web_search_conf().get("zhipu_content_size") or "").strip().lower()
+        if content_size in ("medium", "high"):
+            payload["content_size"] = content_size
+
+        logger.debug(f"[WebSearch] zhipu: query='{trimmed_query}', count={payload['count']}, engine={engine}")
+        resp = requests.post(url, headers=headers, json=payload, timeout=DEFAULT_TIMEOUT)
+
+        if resp.status_code == 401:
+            return ToolResult.fail("Error: Invalid Zhipu API key.")
+        if resp.status_code != 200:
+            return ToolResult.fail(f"Error: Zhipu API returned HTTP {resp.status_code}: {resp.text[:200]}")
+
+        data = resp.json()
+        # Business-level errors (1701/1702/1703 etc.) come back as
+        # {"error": {"code","message"}} even on HTTP 200.
+        if isinstance(data, dict) and data.get("error"):
+            err = data["error"] or {}
+            return ToolResult.fail(f"Error: Zhipu returned {err.get('code')}: {err.get('message','')}")
+
+        items = data.get("search_result") or (data.get("data") or {}).get("search_result") or []
+        results = []
+        for it in items:
+            results.append({
+                "title": it.get("title", ""),
+                "url": it.get("link") or it.get("url", ""),
+                "snippet": it.get("content") or it.get("snippet", ""),
+                "siteName": it.get("media") or it.get("siteName", ""),
+                "datePublished": it.get("publish_date") or it.get("datePublished", ""),
+            })
+        return ToolResult.success({
+            "query": query, "backend": "zhipu",
+            "total": len(results), "count": len(results), "results": results,
+        })
+
+    # ------------------------------------------------------------------
+    # Qianfan (Baidu)
+    # ------------------------------------------------------------------
+
+    def _search_qianfan(self, query: str, count: int, freshness: str) -> ToolResult:
+        api_key = _get_api_key("qianfan")
+        api_base = (conf().get("qianfan_api_base") or "https://qianfan.baidubce.com/v2").rstrip("/")
+        url = f"{api_base}/ai_search/web_search"
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
+            "X-Appbuilder-From": "cow",
+        }
+
+        count = max(1, min(int(count or 10), 50))
+        payload: Dict[str, Any] = {
+            "messages": [{"role": "user", "content": query}],
+            "search_source": "baidu_search_v2",
+            "resource_type_filter": [{"type": "web", "top_k": count}],
+        }
+
+        # Baidu AI Search expects freshness as a date-range filter, not a
+        # named recency token. Translate our shared vocabulary into the
+        # underlying page_time range expected by the API.
+        search_filter = self._qianfan_build_freshness_filter(freshness)
+        if search_filter:
+            payload["search_filter"] = search_filter
+
+        logger.debug(f"[WebSearch] qianfan: query='{query}', count={count}, freshness={freshness!r}")
+        resp = requests.post(url, headers=headers, json=payload, timeout=DEFAULT_TIMEOUT)
+
+        if resp.status_code == 401:
+            return ToolResult.fail("Error: Invalid Qianfan API key.")
+        if resp.status_code != 200:
+            return ToolResult.fail(f"Error: Qianfan API returned HTTP {resp.status_code}: {resp.text[:200]}")
+
+        data = resp.json()
+        # Even on HTTP 200 Baidu surfaces business errors as {"code","message"}.
+        if isinstance(data, dict) and data.get("code"):
+            return ToolResult.fail(f"Error: Qianfan returned {data.get('code')}: {data.get('message','')}")
+
+        refs = data.get("references") or []
+        results = []
+        for d in refs:
+            results.append({
+                "title": d.get("title", ""),
+                "url": d.get("url", ""),
+                "snippet": (d.get("content") or "")[:200],
+                "siteName": d.get("web_anchor") or d.get("website") or "",
+                "datePublished": d.get("date", ""),
+            })
+        return ToolResult.success({
+            "query": query, "backend": "qianfan",
+            "total": len(results), "count": len(results), "results": results,
+        })
+
+    @staticmethod
+    def _qianfan_build_freshness_filter(freshness: str) -> Optional[Dict[str, Any]]:
+        if not freshness or freshness == "noLimit":
+            return None
+        delta_days = {"oneDay": 1, "oneWeek": 7, "oneMonth": 30, "oneYear": 365}.get(freshness)
+        if not delta_days:
+            return None
+        from datetime import datetime, timedelta
+        now = datetime.now()
+        end_date = (now + timedelta(days=1)).strftime("%Y-%m-%d")
+        start_date = (now - timedelta(days=delta_days)).strftime("%Y-%m-%d")
+        return {"range": {"page_time": {"gte": start_date, "lt": end_date}}}
+
+    # ------------------------------------------------------------------
+    # LinkAI (plugin)
+    # ------------------------------------------------------------------
+
+    def _search_linkai(self, query: str, count: int, freshness: str) -> ToolResult:
+        api_key = _get_api_key("linkai")
+        api_base = (conf().get("linkai_api_base") or "https://api.link-ai.tech").rstrip("/")
+        url = f"{api_base}/v1/plugin/execute"
+
+        from common.utils import get_cloud_headers
+        headers = get_cloud_headers(api_key)
+
+        payload = {"code": "web-search", "args": {"query": query, "count": count, "freshness": freshness}}
+        logger.debug(f"[WebSearch] linkai: query='{query}', count={count}")
+        resp = requests.post(url, headers=headers, json=payload, timeout=DEFAULT_TIMEOUT)
+
+        if resp.status_code == 401:
+            return ToolResult.fail("Error: Invalid LinkAI API key.")
+        if resp.status_code != 200:
+            return ToolResult.fail(f"Error: LinkAI API returned HTTP {resp.status_code}")
+
+        data = resp.json()
+        if not data.get("success"):
+            msg = data.get("message") or "Unknown error"
+            return ToolResult.fail(f"Error: LinkAI search failed: {msg}")
+
+        raw = data.get("data", "")
+        if isinstance(raw, str):
+            try:
+                raw = json.loads(raw)
+            except (json.JSONDecodeError, TypeError):
+                return ToolResult.success({
+                    "query": query, "backend": "linkai",
+                    "total": 1, "count": 1, "results": [{"content": raw}],
+                })
+
+        if isinstance(raw, dict):
+            pages = (raw.get("webPages") or {}).get("value", []) or []
+            if pages:
+                results = []
+                for p in pages:
+                    item = {
+                        "title": p.get("name", ""),
+                        "url": p.get("url", ""),
+                        "snippet": p.get("snippet", ""),
+                        "siteName": p.get("siteName", ""),
+                        "datePublished": p.get("datePublished") or p.get("dateLastCrawled", ""),
+                    }
+                    if p.get("summary"):
+                        item["summary"] = p["summary"]
+                    results.append(item)
+                total = (raw.get("webPages") or {}).get("totalEstimatedMatches", len(results))
+                return ToolResult.success({
+                    "query": query, "backend": "linkai",
+                    "total": total, "count": len(results), "results": results,
+                })
+
+        return ToolResult.success({
+            "query": query, "backend": "linkai",
+            "total": 1, "count": 1, "results": [{"content": str(raw)}],
+        })
diff --git a/agent/tools/write/__init__.py b/agent/tools/write/__init__.py
new file mode 100644
index 0000000..b9cd426
--- /dev/null
+++ b/agent/tools/write/__init__.py
@@ -0,0 +1,3 @@
+from .write import Write
+
+__all__ = ['Write']
diff --git a/agent/tools/write/write.py b/agent/tools/write/write.py
new file mode 100644
index 0000000..5bd16f4
--- /dev/null
+++ b/agent/tools/write/write.py
@@ -0,0 +1,97 @@
+"""
+Write tool - Write file content
+Creates or overwrites files, automatically creates parent directories
+"""
+
+import os
+from typing import Dict, Any
+from pathlib import Path
+
+from agent.tools.base_tool import BaseTool, ToolResult
+from common.utils import expand_path
+
+
+class Write(BaseTool):
+    """Tool for writing file content"""
+    
+    name: str = "write"
+    description: str = "Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories. IMPORTANT: Single write should not exceed 10KB. For large files, create a skeleton first, then use edit to add content in chunks."
+    
+    params: dict = {
+        "type": "object",
+        "properties": {
+            "path": {
+                "type": "string",
+                "description": "Path to the file to write (relative or absolute)"
+            },
+            "content": {
+                "type": "string",
+                "description": "Content to write to the file"
+            }
+        },
+        "required": ["path", "content"]
+    }
+    
+    def __init__(self, config: dict = None):
+        self.config = config or {}
+        self.cwd = self.config.get("cwd", os.getcwd())
+        self.memory_manager = self.config.get("memory_manager", None)
+    
+    def execute(self, args: Dict[str, Any]) -> ToolResult:
+        """
+        Execute file write operation
+        
+        :param args: Contains file path and content
+        :return: Operation result
+        """
+        path = args.get("path", "").strip()
+        content = args.get("content", "")
+        
+        if not path:
+            return ToolResult.fail("Error: path parameter is required")
+        
+        # Resolve path
+        absolute_path = self._resolve_path(path)
+        
+        try:
+            # Create parent directory (if needed)
+            parent_dir = os.path.dirname(absolute_path)
+            if parent_dir:
+                os.makedirs(parent_dir, exist_ok=True)
+            
+            # Write file
+            with open(absolute_path, 'w', encoding='utf-8') as f:
+                f.write(content)
+            
+            # Get bytes written
+            bytes_written = len(content.encode('utf-8'))
+            
+            # Auto-sync to memory database if this is a memory file
+            if self.memory_manager and 'memory/' in path:
+                self.memory_manager.mark_dirty()
+            
+            result = {
+                "message": f"Successfully wrote {bytes_written} bytes to {path}",
+                "path": path,
+                "bytes_written": bytes_written
+            }
+            
+            return ToolResult.success(result)
+            
+        except PermissionError:
+            return ToolResult.fail(f"Error: Permission denied writing to {path}")
+        except Exception as e:
+            return ToolResult.fail(f"Error writing file: {str(e)}")
+    
+    def _resolve_path(self, path: str) -> str:
+        """
+        Resolve path to absolute path
+        
+        :param path: Relative or absolute path
+        :return: Absolute path
+        """
+        # Expand ~ to user home directory
+        path = expand_path(path)
+        if os.path.isabs(path):
+            return path
+        return os.path.abspath(os.path.join(self.cwd, path))
diff --git a/app.py b/app.py
new file mode 100644
index 0000000..702a86e
--- /dev/null
+++ b/app.py
@@ -0,0 +1,408 @@
+# encoding:utf-8
+
+import os
+import signal
+import sys
+import time
+
+from channel import channel_factory
+from common import const
+from common.log import logger
+from config import load_config, conf
+from plugins import *
+import threading
+
+
+_channel_mgr = None
+
+# Desktop mode: a lighter runtime for the packaged Electron client. Plugins are
+# loaded in a background thread (so command plugins like cow_cli/godcmd work
+# without slowing startup), while MCP warmup is still skipped to keep it fast.
+DESKTOP_MODE = os.environ.get("COW_DESKTOP") == "1"
+
+
+def get_channel_manager():
+    return _channel_mgr
+
+
+def _parse_channel_type(raw) -> list:
+    """
+    Parse channel_type config value into a list of channel names.
+    Supports:
+      - single string: "feishu"
+      - comma-separated string: "feishu, dingtalk"
+      - list: ["feishu", "dingtalk"]
+    """
+    if isinstance(raw, list):
+        return [ch.strip() for ch in raw if ch.strip()]
+    if isinstance(raw, str):
+        return [ch.strip() for ch in raw.split(",") if ch.strip()]
+    return []
+
+
+class ChannelManager:
+    """
+    Manage the lifecycle of multiple channels running concurrently.
+    Each channel.startup() runs in its own daemon thread.
+    The web channel is started as default console unless explicitly disabled.
+    """
+
+    def __init__(self):
+        self._channels = {}        # channel_name -> channel instance
+        self._threads = {}         # channel_name -> thread
+        self._primary_channel = None
+        self._lock = threading.Lock()
+        self.cloud_mode = False    # set to True when cloud client is active
+
+    @property
+    def channel(self):
+        """Return the primary (first non-web) channel for backward compatibility."""
+        return self._primary_channel
+
+    def get_channel(self, channel_name: str):
+        return self._channels.get(channel_name)
+
+    def start(self, channel_names: list, first_start: bool = False):
+        """
+        Create and start one or more channels in sub-threads.
+        If first_start is True, plugins and linkai client will also be initialized.
+        """
+        with self._lock:
+            channels = []
+            for name in channel_names:
+                ch = channel_factory.create_channel(name)
+                ch.cloud_mode = self.cloud_mode
+                self._channels[name] = ch
+                channels.append((name, ch))
+                if self._primary_channel is None and name != "web":
+                    self._primary_channel = ch
+
+            if self._primary_channel is None and channels:
+                self._primary_channel = channels[0][1]
+
+            if first_start:
+                if DESKTOP_MODE:
+                    # Load plugins in the background so command plugins
+                    # (cow_cli / godcmd, e.g. /status, #help) work in the
+                    # desktop client, without blocking web-service readiness.
+                    threading.Thread(
+                        target=PluginManager().load_plugins, daemon=True
+                    ).start()
+                else:
+                    PluginManager().load_plugins()
+
+                # Cloud client is optional. It is only started when
+                # use_linkai=True AND cloud_deployment_id is set.
+                # By default neither is configured, so the app runs
+                # entirely locally without any remote connection.
+                if conf().get("use_linkai") and (
+                    os.environ.get("CLOUD_DEPLOYMENT_ID") or conf().get("cloud_deployment_id")
+                ):
+                    try:
+                        from common import cloud_client
+                        threading.Thread(
+                            target=cloud_client.start,
+                            args=(self._primary_channel, self),
+                            daemon=True,
+                        ).start()
+                    except Exception:
+                        pass
+
+            # Start web console first so its logs print cleanly,
+            # then start remaining channels after a brief pause.
+            web_entry = None
+            other_entries = []
+            for entry in channels:
+                if entry[0] == "web":
+                    web_entry = entry
+                else:
+                    other_entries.append(entry)
+
+            ordered = ([web_entry] if web_entry else []) + other_entries
+            for i, (name, ch) in enumerate(ordered):
+                if i > 0 and name != "web":
+                    time.sleep(0.1)
+                t = threading.Thread(target=self._run_channel, args=(name, ch), daemon=True)
+                self._threads[name] = t
+                t.start()
+                logger.debug(f"[ChannelManager] Channel '{name}' started in sub-thread")
+
+    def _run_channel(self, name: str, channel):
+        try:
+            channel.startup()
+        except Exception as e:
+            logger.error(f"[ChannelManager] Channel '{name}' startup error: {e}")
+            logger.exception(e)
+
+    def stop(self, channel_name: str = None):
+        """
+        Stop channel(s). If channel_name is given, stop only that channel;
+        otherwise stop all channels.
+        """
+        # Pop under lock, then stop outside lock to avoid deadlock
+        with self._lock:
+            names = [channel_name] if channel_name else list(self._channels.keys())
+            to_stop = []
+            for name in names:
+                ch = self._channels.pop(name, None)
+                th = self._threads.pop(name, None)
+                to_stop.append((name, ch, th))
+            if channel_name and self._primary_channel is self._channels.get(channel_name):
+                self._primary_channel = None
+
+        for name, ch, th in to_stop:
+            if ch is None:
+                logger.warning(f"[ChannelManager] Channel '{name}' not found in managed channels")
+                if th and th.is_alive():
+                    self._interrupt_thread(th, name)
+                continue
+            logger.info(f"[ChannelManager] Stopping channel '{name}'...")
+            graceful = False
+            if hasattr(ch, 'stop'):
+                try:
+                    ch.stop()
+                    graceful = True
+                except Exception as e:
+                    logger.warning(f"[ChannelManager] Error during channel '{name}' stop: {e}")
+            if th and th.is_alive():
+                th.join(timeout=5)
+                if th.is_alive():
+                    if graceful:
+                        logger.info(f"[ChannelManager] Channel '{name}' thread still alive after stop(), "
+                                    "leaving daemon thread to finish on its own")
+                    else:
+                        logger.warning(f"[ChannelManager] Channel '{name}' thread did not exit in 5s, forcing interrupt")
+                        self._interrupt_thread(th, name)
+
+    @staticmethod
+    def _interrupt_thread(th: threading.Thread, name: str):
+        """Raise SystemExit in target thread to break blocking loops like start_forever."""
+        import ctypes
+        try:
+            tid = th.ident
+            if tid is None:
+                return
+            res = ctypes.pythonapi.PyThreadState_SetAsyncExc(
+                ctypes.c_ulong(tid), ctypes.py_object(SystemExit)
+            )
+            if res == 1:
+                logger.info(f"[ChannelManager] Interrupted thread for channel '{name}'")
+            elif res > 1:
+                ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_ulong(tid), None)
+                logger.warning(f"[ChannelManager] Failed to interrupt thread for channel '{name}'")
+        except Exception as e:
+            logger.warning(f"[ChannelManager] Thread interrupt error for '{name}': {e}")
+
+    def restart(self, new_channel_name: str):
+        """
+        Restart a single channel with a new channel type.
+        Can be called from any thread (e.g. linkai config callback).
+        """
+        logger.info(f"[ChannelManager] Restarting channel to '{new_channel_name}'...")
+        self.stop(new_channel_name)
+        _clear_singleton_cache(new_channel_name)
+        time.sleep(1)
+        self.start([new_channel_name], first_start=False)
+        logger.info(f"[ChannelManager] Channel restarted to '{new_channel_name}' successfully")
+
+    def add_channel(self, channel_name: str):
+        """
+        Dynamically add and start a new channel.
+        If the channel is already running, restart it instead.
+        """
+        with self._lock:
+            if channel_name in self._channels:
+                logger.info(f"[ChannelManager] Channel '{channel_name}' already exists, restarting")
+        if self._channels.get(channel_name):
+            self.restart(channel_name)
+            return
+        logger.info(f"[ChannelManager] Adding channel '{channel_name}'...")
+        _clear_singleton_cache(channel_name)
+        self.start([channel_name], first_start=False)
+        logger.info(f"[ChannelManager] Channel '{channel_name}' added successfully")
+
+    def remove_channel(self, channel_name: str):
+        """
+        Dynamically stop and remove a running channel.
+        """
+        with self._lock:
+            if channel_name not in self._channels:
+                logger.warning(f"[ChannelManager] Channel '{channel_name}' not found, nothing to remove")
+                return
+        logger.info(f"[ChannelManager] Removing channel '{channel_name}'...")
+        self.stop(channel_name)
+        logger.info(f"[ChannelManager] Channel '{channel_name}' removed successfully")
+
+
+def _clear_singleton_cache(channel_name: str):
+    """
+    Clear the singleton cache for the channel class so that
+    a new instance can be created with updated config.
+    """
+    cls_map = {
+        "web": "channel.web.web_channel.WebChannel",
+        "wechatmp": "channel.wechatmp.wechatmp_channel.WechatMPChannel",
+        "wechatmp_service": "channel.wechatmp.wechatmp_channel.WechatMPChannel",
+        "wechatcom_app": "channel.wechatcom.wechatcomapp_channel.WechatComAppChannel",
+        const.WECHAT_KF: "channel.wechat_kf.wechat_kf_channel.WechatKfChannel",
+        const.FEISHU: "channel.feishu.feishu_channel.FeiShuChanel",
+        const.DINGTALK: "channel.dingtalk.dingtalk_channel.DingTalkChanel",
+        const.WECOM_BOT: "channel.wecom_bot.wecom_bot_channel.WecomBotChannel",
+        const.QQ: "channel.qq.qq_channel.QQChannel",
+        const.TELEGRAM: "channel.telegram.telegram_channel.TelegramChannel",
+        const.SLACK: "channel.slack.slack_channel.SlackChannel",
+        const.DISCORD: "channel.discord.discord_channel.DiscordChannel",
+        const.WEIXIN: "channel.weixin.weixin_channel.WeixinChannel",
+        "wx": "channel.weixin.weixin_channel.WeixinChannel",
+    }
+    module_path = cls_map.get(channel_name)
+    if not module_path:
+        return
+    try:
+        parts = module_path.rsplit(".", 1)
+        module_name, class_name = parts[0], parts[1]
+        import importlib
+        module = importlib.import_module(module_name)
+        wrapper = getattr(module, class_name, None)
+        if wrapper and hasattr(wrapper, '__closure__') and wrapper.__closure__:
+            for cell in wrapper.__closure__:
+                try:
+                    cell_contents = cell.cell_contents
+                    if isinstance(cell_contents, dict):
+                        cell_contents.clear()
+                        logger.debug(f"[ChannelManager] Cleared singleton cache for {class_name}")
+                        break
+                except ValueError:
+                    pass
+    except Exception as e:
+        logger.warning(f"[ChannelManager] Failed to clear singleton cache: {e}")
+
+
+def sigterm_handler_wrap(_signo):
+    old_handler = signal.getsignal(_signo)
+
+    def func(_signo, _stack_frame):
+        logger.info("signal {} received, exiting...".format(_signo))
+        conf().save_user_datas()
+        if callable(old_handler):  #  check old_handler
+            return old_handler(_signo, _stack_frame)
+        sys.exit(0)
+
+    signal.signal(_signo, func)
+
+
+def _warmup_mcp_tools():
+    """
+    Kick off MCP server loading at process startup so subprocesses
+    (npx / uvx etc.) finish initializing before the first user message
+    arrives. Returns immediately — the actual work happens on a daemon
+    thread inside ToolManager. Safe to call when MCP is not configured.
+    """
+    try:
+        from agent.tools import ToolManager
+        ToolManager()._load_mcp_tools()
+    except Exception as e:
+        logger.warning(f"[App] MCP warmup failed (non-fatal): {e}")
+
+
+def _warmup_scheduler():
+    """Eager-init AgentBridge so the scheduler thread starts at process
+    boot rather than waiting for the first user message."""
+    try:
+        from bridge.bridge import Bridge
+        Bridge().get_agent_bridge()
+    except Exception as e:
+        logger.warning(f"[App] Scheduler warmup failed: {e}")
+
+
+def _sync_builtin_skills():
+    """Sync builtin skills from project skills/ to workspace skills/ on startup."""
+    import shutil
+    try:
+        workspace = conf().get("agent_workspace", "~/cow")
+        workspace = os.path.expanduser(workspace)
+        project_root = os.path.dirname(os.path.abspath(__file__))
+        builtin_dir = os.path.join(project_root, "skills")
+        custom_dir = os.path.join(workspace, "skills")
+
+        if not os.path.isdir(builtin_dir):
+            return
+
+        os.makedirs(custom_dir, exist_ok=True)
+        synced = 0
+        for name in os.listdir(builtin_dir):
+            src = os.path.join(builtin_dir, name)
+            if not os.path.isdir(src) or not os.path.isfile(os.path.join(src, "SKILL.md")):
+                continue
+            dst = os.path.join(custom_dir, name)
+            try:
+                if os.path.isdir(dst):
+                    shutil.rmtree(dst)
+                shutil.copytree(src, dst)
+                synced += 1
+            except Exception as e:
+                logger.warning(f"[App] Failed to sync builtin skill '{name}': {e}")
+        if synced:
+            logger.info(f"[App] Synced {synced} builtin skill(s) to workspace")
+    except Exception as e:
+        logger.warning(f"[App] Builtin skills sync failed: {e}")
+
+
+def run():
+    global _channel_mgr
+    try:
+        # load config
+        load_config()
+        # ctrl + c
+        sigterm_handler_wrap(signal.SIGINT)
+        # kill signal
+        sigterm_handler_wrap(signal.SIGTERM)
+
+        # Parse channel_type into a list
+        raw_channel = conf().get("channel_type", "web")
+
+        if "--cmd" in sys.argv:
+            channel_names = ["terminal"]
+        else:
+            channel_names = _parse_channel_type(raw_channel)
+            if not channel_names:
+                channel_names = ["web"]
+
+        # Auto-start web console unless explicitly disabled
+        web_console_enabled = conf().get("web_console", True)
+        if web_console_enabled and "web" not in channel_names:
+            channel_names.append("web")
+
+        # Sync builtin skills to workspace before channels start
+        _sync_builtin_skills()
+
+        # Kick off MCP server loading in the background so first-message
+        # latency isn't dominated by npx package downloads. Skipped in desktop
+        # mode (MCP relies on external npx/uvx runtimes that aren't bundled).
+        if not DESKTOP_MODE:
+            _warmup_mcp_tools()
+
+        if DESKTOP_MODE:
+            # Defer the (heavy) AgentBridge/scheduler warmup to a background
+            # thread so the web API becomes available within a couple seconds.
+            # The scheduler still starts; it just doesn't block UI readiness.
+            threading.Thread(target=_warmup_scheduler, daemon=True).start()
+        else:
+            _warmup_scheduler()
+
+        logger.info(f"[App] Starting channels: {channel_names}")
+
+        _channel_mgr = ChannelManager()
+        _channel_mgr.start(channel_names, first_start=True)
+
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        pass
+    except Exception as e:
+        logger.error("App startup failed!")
+        logger.exception(e)
+
+
+if __name__ == "__main__":
+    run()
diff --git a/bridge/agent_bridge.py b/bridge/agent_bridge.py
new file mode 100644
index 0000000..33c8dda
--- /dev/null
+++ b/bridge/agent_bridge.py
@@ -0,0 +1,1179 @@
+"""
+Agent Bridge - Integrates Agent system with existing COW bridge
+"""
+
+import os
+from typing import Optional, List
+
+from agent.protocol import Agent, LLMModel, LLMRequest, get_cancel_registry
+from bridge.agent_event_handler import AgentEventHandler
+from bridge.agent_initializer import AgentInitializer
+from bridge.bridge import Bridge
+from bridge.context import Context
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from common.utils import expand_path
+from config import conf
+from models.openai_compatible_bot import OpenAICompatibleBot
+
+
+def add_openai_compatible_support(bot_instance):
+    """
+    Dynamically add OpenAI-compatible tool calling support to a bot instance.
+    
+    This allows any bot to gain tool calling capability without modifying its code,
+    as long as it uses OpenAI-compatible API format.
+    
+    Note: Some bots like ZHIPUAIBot have native tool calling support and don't need enhancement.
+    """
+    if hasattr(bot_instance, 'call_with_tools'):
+        # Bot already has tool calling support (e.g., ZHIPUAIBot)
+        logger.debug(f"[AgentBridge] {type(bot_instance).__name__} already has native tool calling support")
+        return bot_instance
+
+    # Create a temporary mixin class that combines the bot with OpenAI compatibility
+    class EnhancedBot(bot_instance.__class__, OpenAICompatibleBot):
+        """Dynamically enhanced bot with OpenAI-compatible tool calling"""
+
+        def get_api_config(self):
+            """
+            Infer API config from common configuration patterns.
+            Most OpenAI-compatible bots use similar configuration.
+            """
+            from config import conf
+
+            return {
+                'api_key': conf().get("open_ai_api_key"),
+                'api_base': conf().get("open_ai_api_base"),
+                'model': conf().get("model", "gpt-3.5-turbo"),
+                'default_temperature': conf().get("temperature", 0.9),
+                'default_top_p': conf().get("top_p", 1.0),
+                'default_frequency_penalty': conf().get("frequency_penalty", 0.0),
+                'default_presence_penalty': conf().get("presence_penalty", 0.0),
+            }
+
+    # Change the bot's class to the enhanced version
+    bot_instance.__class__ = EnhancedBot
+    logger.info(
+        f"[AgentBridge] Enhanced {bot_instance.__class__.__bases__[0].__name__} with OpenAI-compatible tool calling")
+
+    return bot_instance
+
+
+class AgentLLMModel(LLMModel):
+    """
+    LLM Model adapter that uses COW's existing bot infrastructure
+    """
+
+    _MODEL_BOT_TYPE_MAP = {
+        "wenxin": const.BAIDU, "wenxin-4": const.BAIDU,
+        "xunfei": const.XUNFEI, const.QWEN: const.QWEN_DASHSCOPE,
+        const.QIANFAN: const.QIANFAN,
+        const.MODELSCOPE: const.MODELSCOPE,
+    }
+    _MODEL_PREFIX_MAP = [
+        ("qwen", const.QWEN_DASHSCOPE), ("qwq", const.QWEN_DASHSCOPE), ("qvq", const.QWEN_DASHSCOPE),
+        ("gemini", const.GEMINI), ("glm", const.ZHIPU_AI), ("claude", const.CLAUDEAPI),
+        ("moonshot", const.MOONSHOT), ("kimi", const.MOONSHOT),
+        ("doubao", const.DOUBAO), ("deepseek", const.DEEPSEEK),
+        ("ernie", const.QIANFAN),
+        ("mimo-", const.MIMO),
+    ]
+
+    def __init__(self, bridge: Bridge, bot_type: str = "chat"):
+        super().__init__(model=conf().get("model", const.GPT_41))
+        self.bridge = bridge
+        self.bot_type = bot_type
+        self._bot = None
+        self._bot_model = None
+
+    @property
+    def model(self):
+        return conf().get("model", const.GPT_41)
+
+    @model.setter
+    def model(self, value):
+        pass
+
+    def _resolve_bot_type(self, model_name: str) -> str:
+        """Resolve bot type from model name, matching Bridge.__init__ logic."""
+        if conf().get("use_linkai", False) and conf().get("linkai_api_key"):
+            return const.LINKAI
+        # Support custom bot type configuration
+        configured_bot_type = conf().get("bot_type")
+        if configured_bot_type:
+            return configured_bot_type
+       
+        if not model_name or not isinstance(model_name, str):
+            return const.OPENAI
+        if model_name in self._MODEL_BOT_TYPE_MAP:
+            return self._MODEL_BOT_TYPE_MAP[model_name]
+        if model_name.lower().startswith("minimax") or model_name in ["abab6.5-chat"]:
+            return const.MiniMax
+        if model_name in [const.QWEN_TURBO, const.QWEN_PLUS, const.QWEN_MAX]:
+            return const.QWEN_DASHSCOPE
+        if model_name in [const.MOONSHOT, "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k"]:
+            return const.MOONSHOT
+        if conf().get("bot_type") == "modelscope":
+            return const.MODELSCOPE
+        lowered_model = model_name.lower()
+        for prefix, btype in self._MODEL_PREFIX_MAP:
+            if lowered_model.startswith(prefix):
+                return btype
+        return const.OPENAI
+
+    @property
+    def bot(self):
+        """Lazy load the bot, re-create when model or bot_type changes"""
+        from models.bot_factory import create_bot
+        cur_model = self.model
+        cur_bot_type = self._resolve_bot_type(cur_model)
+        if self._bot is None or self._bot_model != cur_model or getattr(self, '_bot_type', None) != cur_bot_type:
+            self._bot = create_bot(cur_bot_type)
+            self._bot = add_openai_compatible_support(self._bot)
+            self._bot_model = cur_model
+            self._bot_type = cur_bot_type
+        return self._bot
+
+    def call(self, request: LLMRequest):
+        """
+        Call the model using COW's bot infrastructure
+        """
+        try:
+            # For non-streaming calls, we'll use the existing reply method
+            # This is a simplified implementation
+            if hasattr(self.bot, 'call_with_tools'):
+                # Use tool-enabled call if available
+                kwargs = {
+                    'messages': request.messages,
+                    'tools': getattr(request, 'tools', None),
+                    'stream': False,
+                    'model': self.model  # Pass model parameter
+                }
+                # Only pass max_tokens if it's explicitly set
+                if request.max_tokens is not None:
+                    kwargs['max_tokens'] = request.max_tokens
+
+                # Extract system prompt if present
+                system_prompt = getattr(request, 'system', None)
+                if system_prompt:
+                    kwargs['system'] = system_prompt
+
+                # Pass context metadata to bot
+                channel_type = getattr(self, 'channel_type', None) or ''
+                if channel_type:
+                    kwargs['channel_type'] = channel_type
+                session_id = getattr(self, 'session_id', None)
+                if session_id:
+                    kwargs['session_id'] = session_id
+
+                # Thinking mode is a global toggle independent of the channel.
+                # IM channels (WeChat/WeCom/DingTalk/Feishu) won't render the
+                # reasoning trace, but still benefit from the higher answer
+                # quality the thinking pass produces.
+                from config import conf
+                thinking_enabled = bool(conf().get("enable_thinking", False))
+                kwargs['thinking'] = (
+                    {"type": "enabled"} if thinking_enabled
+                    else {"type": "disabled"}
+                )
+                # Reasoning effort is only meaningful when thinking is on.
+                # Bots that don't understand the kwarg drop it silently.
+                if thinking_enabled:
+                    effort = conf().get("reasoning_effort", "high")
+                    if effort in ("high", "max"):
+                        kwargs['reasoning_effort'] = effort
+
+                response = self.bot.call_with_tools(**kwargs)
+                return self._format_response(response)
+            else:
+                # Fallback to regular call
+                # This would need to be implemented based on your specific needs
+                raise NotImplementedError("Regular call not implemented yet")
+                
+        except Exception as e:
+            logger.error(f"AgentLLMModel call error: {e}")
+            raise
+    
+    def call_stream(self, request: LLMRequest):
+        """
+        Call the model with streaming using COW's bot infrastructure
+        """
+        try:
+            if hasattr(self.bot, 'call_with_tools'):
+                # Use tool-enabled streaming call if available
+                # Extract system prompt if present
+                system_prompt = getattr(request, 'system', None)
+
+                # Build kwargs for call_with_tools
+                kwargs = {
+                    'messages': request.messages,
+                    'tools': getattr(request, 'tools', None),
+                    'stream': True,
+                    'model': self.model  # Pass model parameter
+                }
+
+                # Only pass max_tokens if explicitly set, let the bot use its default
+                if request.max_tokens is not None:
+                    kwargs['max_tokens'] = request.max_tokens
+
+                # Add system prompt if present
+                if system_prompt:
+                    kwargs['system'] = system_prompt
+
+                # Pass context metadata to bot
+                channel_type = getattr(self, 'channel_type', None) or ''
+                if channel_type:
+                    kwargs['channel_type'] = channel_type
+                session_id = getattr(self, 'session_id', None)
+                if session_id:
+                    kwargs['session_id'] = session_id
+
+                # Thinking mode is a global toggle independent of the channel.
+                # IM channels (WeChat/WeCom/DingTalk/Feishu) won't render the
+                # reasoning trace, but still benefit from the higher answer
+                # quality the thinking pass produces.
+                from config import conf
+                thinking_enabled = bool(conf().get("enable_thinking", False))
+                kwargs['thinking'] = (
+                    {"type": "enabled"} if thinking_enabled
+                    else {"type": "disabled"}
+                )
+                # Reasoning effort is only meaningful when thinking is on.
+                # Bots that don't understand the kwarg drop it silently.
+                if thinking_enabled:
+                    effort = conf().get("reasoning_effort", "high")
+                    if effort in ("high", "max"):
+                        kwargs['reasoning_effort'] = effort
+
+                stream = self.bot.call_with_tools(**kwargs)
+                
+                # Convert stream format to our expected format
+                for chunk in stream:
+                    yield self._format_stream_chunk(chunk)
+            else:
+                bot_type = type(self.bot).__name__
+                raise NotImplementedError(f"Bot {bot_type} does not support call_with_tools. Please add the method.")
+                
+        except Exception as e:
+            logger.error(f"AgentLLMModel call_stream error: {e}", exc_info=True)
+            raise
+    
+    def _format_response(self, response):
+        """Format Claude response to our expected format"""
+        # This would need to be implemented based on Claude's response format
+        return response
+    
+    def _format_stream_chunk(self, chunk):
+        """Format Claude stream chunk to our expected format"""
+        # This would need to be implemented based on Claude's stream format
+        return chunk
+
+
+class AgentBridge:
+    """
+    Bridge class that integrates super Agent with COW
+    Manages multiple agent instances per session for conversation isolation
+    """
+    
+    def __init__(self, bridge: Bridge):
+        self.bridge = bridge
+        self.agents = {}  # session_id -> Agent instance mapping
+        self.default_agent = None  # For backward compatibility (no session_id)
+        self.agent: Optional[Agent] = None
+        self.scheduler_initialized = False
+        
+        # Create helper instances
+        self.initializer = AgentInitializer(bridge, self)
+
+        # Eager-start the scheduler so cron tasks fire without waiting
+        # for the first user message. init_scheduler is idempotent.
+        try:
+            from agent.tools.scheduler.integration import init_scheduler
+            if init_scheduler(self):
+                self.scheduler_initialized = True
+        except Exception as e:
+            logger.warning(f"[AgentBridge] Eager scheduler init failed: {e}")
+
+        # Start the self-evolution idle trigger (idempotent, daemon thread).
+        try:
+            from agent.evolution.trigger import start_evolution_trigger
+            start_evolution_trigger(self)
+        except Exception as e:
+            logger.warning(f"[AgentBridge] Evolution trigger init failed: {e}")
+
+    def create_agent(self, system_prompt: str, tools: List = None, **kwargs) -> Agent:
+        """
+        Create the super agent with COW integration
+        
+        Args:
+            system_prompt: System prompt
+            tools: List of tools (optional)
+            **kwargs: Additional agent parameters
+            
+        Returns:
+            Agent instance
+        """
+        # Create LLM model that uses COW's bot infrastructure
+        model = AgentLLMModel(self.bridge)
+        
+        # Default tools if none provided
+        if tools is None:
+            # Use ToolManager to load all available tools
+            from agent.tools import ToolManager
+            tool_manager = ToolManager()
+            tool_manager.load_tools()
+            
+            tools = []
+            workspace_dir = kwargs.get("workspace_dir")
+            for tool_name in tool_manager.tool_classes.keys():
+                try:
+                    tool = tool_manager.create_tool(tool_name)
+                    if tool:
+                        if workspace_dir and hasattr(tool, 'cwd'):
+                            tool.cwd = workspace_dir
+                        tools.append(tool)
+                except Exception as e:
+                    logger.warning(f"[AgentBridge] Failed to load tool {tool_name}: {e}")
+        
+        # Create agent instance
+        agent = Agent(
+            system_prompt=system_prompt,
+            description=kwargs.get("description", "AI Super Agent"),
+            model=model,
+            tools=tools,
+            max_steps=kwargs.get("max_steps", 15),
+            output_mode=kwargs.get("output_mode", "logger"),
+            workspace_dir=kwargs.get("workspace_dir"),
+            skill_manager=kwargs.get("skill_manager"),
+            enable_skills=kwargs.get("enable_skills", True),
+            memory_manager=kwargs.get("memory_manager"),
+            max_context_tokens=kwargs.get("max_context_tokens"),
+            context_reserve_tokens=kwargs.get("context_reserve_tokens"),
+            runtime_info=kwargs.get("runtime_info"),
+        )
+
+        # Log skill loading details
+        if agent.skill_manager:
+            logger.debug(f"[AgentBridge] SkillManager initialized with {len(agent.skill_manager.skills)} skills")
+
+        return agent
+    
+    def get_agent(self, session_id: str = None) -> Optional[Agent]:
+        """
+        Get agent instance for the given session
+        
+        Args:
+            session_id: Session identifier (e.g., user_id). If None, returns default agent.
+        
+        Returns:
+            Agent instance for this session
+        """
+        # If no session_id, use default agent (backward compatibility)
+        if session_id is None:
+            if self.default_agent is None:
+                self._init_default_agent()
+            return self.default_agent
+        
+        # Check if agent exists for this session
+        if session_id not in self.agents:
+            self._init_agent_for_session(session_id)
+        
+        return self.agents[session_id]
+    
+    def _init_default_agent(self):
+        """Initialize default super agent"""
+        agent = self.initializer.initialize_agent(session_id=None)
+        self.default_agent = agent
+    
+    def _init_agent_for_session(self, session_id: str):
+        """Initialize agent for a specific session"""
+        agent = self.initializer.initialize_agent(session_id=session_id)
+        self.agents[session_id] = agent
+
+    def sync_session_messages_from_store(self, session_id: str) -> int:
+        """Reload an agent's in-memory ``messages`` list from the persistent
+        conversation store.
+
+        Used after an external mutation (e.g. user edits / deletes a message
+        via the web console) so the agent's next turn sees the same history
+        as the database. The operation is a no-op when the agent has not been
+        instantiated yet for the session.
+
+        Returns:
+            Number of messages now held in the agent's memory. Returns -1 if
+            the agent does not exist or has no compatible ``messages`` attr.
+        """
+        if not session_id or session_id not in self.agents:
+            return -1
+        agent = self.agents[session_id]
+        if not (hasattr(agent, "messages") and hasattr(agent, "messages_lock")):
+            return -1
+        try:
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            # No turn cap here: we want a faithful mirror of what the store
+            # has for this session after deletion.
+            remaining = store.load_messages(session_id, max_turns=10**6)
+        except Exception as e:
+            logger.warning(
+                f"[AgentBridge] Failed to load messages for sync (session={session_id}): {e}"
+            )
+            return -1
+        with agent.messages_lock:
+            agent.messages.clear()
+            for msg in remaining:
+                agent.messages.append({
+                    "role": msg["role"],
+                    "content": msg["content"],
+                })
+            count = len(agent.messages)
+        logger.info(
+            f"[AgentBridge] Synced agent memory for session={session_id}, messages={count}"
+        )
+        return count
+
+    def agent_reply(self, query: str, context: Context = None, 
+                   on_event=None, clear_history: bool = False) -> Reply:
+        """
+        Use super agent to reply to a query
+        
+        Args:
+            query: User query
+            context: COW context (optional, contains session_id for user isolation)
+            on_event: Event callback (optional)
+            clear_history: Whether to clear conversation history
+            
+        Returns:
+            Reply object
+        """
+        session_id = None
+        agent = None
+        request_id = None
+        cancel_event = None
+        try:
+            # Extract session_id from context for user isolation
+            if context:
+                session_id = context.kwargs.get("session_id") or context.get("session_id")
+                request_id = context.kwargs.get("request_id") or context.get("request_id")
+
+            # Register a cancel token. Prefer per-turn request_id (web),
+            # fall back to session_id (IM channels). The Event is polled by
+            # AgentStreamExecutor at safe checkpoints.
+            registry = get_cancel_registry()
+            token_key = request_id or session_id
+            if token_key:
+                cancel_event = registry.register(token_key, session_id=session_id)
+
+            # Get agent for this session (will auto-initialize if needed)
+            agent = self.get_agent(session_id=session_id)
+            if not agent:
+                return Reply(ReplyType.ERROR, "Failed to initialize super agent")
+            
+            # Create event handler for logging and channel communication
+            event_handler = AgentEventHandler(context=context, original_callback=on_event)
+            
+            # Filter tools based on context
+            original_tools = agent.tools
+            filtered_tools = original_tools
+            
+            # If this is a scheduled task execution, exclude scheduler tool to prevent recursion
+            if context and context.get("is_scheduled_task"):
+                filtered_tools = [tool for tool in agent.tools if tool.name != "scheduler"]
+                agent.tools = filtered_tools
+                logger.info(f"[AgentBridge] Scheduled task execution: excluded scheduler tool ({len(filtered_tools)}/{len(original_tools)} tools)")
+            else:
+                # Attach context to scheduler tool if present
+                if context and agent.tools:
+                    for tool in agent.tools:
+                        if tool.name == "scheduler":
+                            try:
+                                from agent.tools.scheduler.integration import attach_scheduler_to_tool
+                                attach_scheduler_to_tool(tool, context)
+                            except Exception as e:
+                                logger.warning(f"[AgentBridge] Failed to attach context to scheduler: {e}")
+                            break
+            
+            # Pass context metadata to model for downstream API requests
+            if context and hasattr(agent, 'model'):
+                agent.model.channel_type = context.get("channel_type", "")
+                agent.model.session_id = session_id or ""
+
+            # Store session_id on agent so executor can clear DB on fatal errors
+            agent._current_session_id = session_id
+
+            # Bound the in-memory context for scheduler sessions before each run.
+            # Scheduler sessions are stable per-task and append every trigger,
+            # so without trimming they would grow unbounded across runs and
+            # blow up prompt cost. Regular user chats are not touched here —
+            # the agent's own context manager handles that path.
+            if session_id and session_id.startswith("scheduler_"):
+                from config import conf
+                scheduler_keep_turns = max(
+                    1, int(conf().get("agent_max_context_turns", 20)) // 5
+                )
+                self._trim_in_memory_to_turns(agent, scheduler_keep_turns)
+
+            # Eagerly persist the user message BEFORE running the agent so the
+            # session and the user's bubble are immediately visible — even if
+            # the user switches away or refreshes before the reply finishes.
+            # The reply (assistant/tool messages) is appended once the run
+            # completes; the final persist skips this already-stored user turn.
+            pre_persisted = self._pre_persist_user_message(
+                session_id, query, context, clear_history
+            )
+
+            # Mark this session as mid-run so the self-evolution idle scan does
+            # not fire concurrently when a single turn runs longer than
+            # idle_minutes.
+            try:
+                from agent.evolution.trigger import mark_run_active
+                mark_run_active(agent, True)
+            except Exception:
+                pass
+
+            try:
+                # Use agent's run_stream method with event handler
+                response = agent.run_stream(
+                    user_message=query,
+                    on_event=event_handler.handle_event,
+                    clear_history=clear_history,
+                    cancel_event=cancel_event,
+                )
+            finally:
+                # Clear the mid-run flag so idle scans can review this session.
+                try:
+                    from agent.evolution.trigger import mark_run_active
+                    mark_run_active(agent, False)
+                except Exception:
+                    pass
+
+                # Restore original tools
+                if context and context.get("is_scheduled_task"):
+                    agent.tools = original_tools
+
+                # Log execution summary
+                event_handler.log_summary()
+
+                # Release cancel token; keep registry bounded.
+                if token_key:
+                    try:
+                        registry.unregister(token_key)
+                    except Exception:
+                        pass
+
+            # Persist new messages generated during this run
+            if session_id:
+                channel_type = (context.get("channel_type") or "") if context else ""
+                new_messages = list(getattr(agent, '_last_run_new_messages', []))
+                # The leading user turn was already persisted eagerly above;
+                # drop it here so it isn't stored twice.
+                if pre_persisted and new_messages and new_messages[0].get("role") == "user":
+                    new_messages = new_messages[1:]
+                if new_messages:
+                    self._persist_messages(session_id, list(new_messages), channel_type)
+                else:
+                    with agent.messages_lock:
+                        msg_count = len(agent.messages)
+                    if msg_count == 0:
+                        try:
+                            from agent.memory import get_conversation_store
+                            get_conversation_store().clear_session(session_id)
+                            logger.info(f"[AgentBridge] Cleared DB for recovered session: {session_id}")
+                        except Exception as e:
+                            logger.warning(f"[AgentBridge] Failed to clear DB after recovery: {e}")
+            
+            # Record this user turn for the self-evolution idle trigger. Skip
+            # scheduler-injected / scheduled-task sessions so internal runs do
+            # not count as user activity.
+            if session_id and not session_id.startswith("scheduler_") and not (
+                context and context.get("is_scheduled_task")
+            ):
+                try:
+                    from agent.evolution.trigger import note_user_turn
+                    ch = (context.get("channel_type") or "") if context else ""
+                    rcv = (context.get("receiver") or "") if context else ""
+                    is_group = bool(context.get("isgroup")) if context else False
+                    # Only enable proactive push for single chats (group push is
+                    # noisy); group sessions still evolve, just without notify.
+                    note_user_turn(agent, channel_type=ch, receiver=(rcv if not is_group else ""))
+                except Exception:
+                    pass
+
+            # Post-message hot-reload: detect edits to ~/cow/mcp.json and
+            # sync any new/removed MCP tools into the live agent in the
+            # background. Off the critical path so user latency is unaffected;
+            # changes take effect on the user's next message.
+            self._schedule_mcp_hot_reload(agent)
+
+            # Check if there are files to send (from send/read tool)
+            if hasattr(agent, 'stream_executor') and hasattr(agent.stream_executor, 'files_to_send'):
+                files_to_send = agent.stream_executor.files_to_send
+                if files_to_send:
+                    # Send the first file (for now, handle one file at a time)
+                    file_info = files_to_send[0]
+                    logger.info(f"[AgentBridge] Sending file: {file_info.get('path')}")
+                    
+                    # Clear files_to_send for next request
+                    agent.stream_executor.files_to_send = []
+                    
+                    # Return file reply based on file type
+                    return self._create_file_reply(file_info, response, context)
+            
+            return Reply(ReplyType.TEXT, response)
+            
+        except Exception as e:
+            logger.error(f"Agent reply error: {e}")
+            # If the agent cleared its messages due to format error / overflow,
+            # also purge the DB so the next request starts clean.
+            if session_id and agent:
+                try:
+                    with agent.messages_lock:
+                        msg_count = len(agent.messages)
+                    if msg_count == 0:
+                        from agent.memory import get_conversation_store
+                        get_conversation_store().clear_session(session_id)
+                        logger.info(f"[AgentBridge] Cleared DB for session after error: {session_id}")
+                except Exception as db_err:
+                    logger.warning(f"[AgentBridge] Failed to clear DB after error: {db_err}")
+            # Release cancel token on error path too (idempotent).
+            if cancel_event is not None and (request_id or session_id):
+                try:
+                    get_cancel_registry().unregister(request_id or session_id)
+                except Exception:
+                    pass
+            return Reply(ReplyType.ERROR, f"Agent error: {str(e)}")
+    
+    def _schedule_mcp_hot_reload(self, agent):
+        """
+        Fire-and-forget: detect mcp.json edits and reconcile the agent's
+        tool dict in the background. Runs after the user's reply is sent,
+        so any cost (file stat, hash, server boot) never adds to user latency.
+        Failures are isolated and never raise into the message pipeline.
+        """
+        import threading
+        from agent.tools import ToolManager
+
+        def _run():
+            try:
+                tm = ToolManager()
+                tm.refresh_mcp_if_changed()
+                added, removed = tm.sync_mcp_into_agent(agent)
+                if added or removed:
+                    logger.info(
+                        f"[AgentBridge] Agent tools synced — "
+                        f"added={added}, removed={removed}"
+                    )
+            except Exception as e:
+                logger.warning(f"[AgentBridge] MCP hot-reload failed (non-fatal): {e}")
+
+        threading.Thread(target=_run, daemon=True, name="mcp-hot-reload").start()
+
+    def _create_file_reply(self, file_info: dict, text_response: str, context: Context = None) -> Reply:
+        """
+        Create a reply for sending files
+        
+        Args:
+            file_info: File metadata from read tool
+            text_response: Text response from agent
+            context: Context object
+            
+        Returns:
+            Reply object for file sending
+        """
+        file_type = file_info.get("file_type", "file")
+        file_path = file_info.get("path")
+        # Remote URLs are passed through as-is; local paths get a file:// prefix
+        # so the channel can read them from disk.
+        remote_url = file_info.get("url", "")
+        is_remote = bool(remote_url) and remote_url.lower().startswith(("http://", "https://"))
+
+        def _to_channel_url(p: str) -> str:
+            if is_remote:
+                return remote_url
+            if p and p.lower().startswith(("http://", "https://")):
+                return p
+            return f"file://{p}"
+
+        # For images, use IMAGE_URL type (channel will handle upload)
+        if file_type == "image":
+            file_url = _to_channel_url(file_path)
+            logger.info(f"[AgentBridge] Sending image: {file_url}")
+            reply = Reply(ReplyType.IMAGE_URL, file_url)
+            # Attach text message if present (for channels that support text+image)
+            if text_response:
+                reply.text_content = text_response  # Store accompanying text
+            return reply
+        
+        # For all file types (document, video, audio), use FILE type
+        if file_type in ["document", "video", "audio"]:
+            file_url = _to_channel_url(file_path)
+            logger.info(f"[AgentBridge] Sending {file_type}: {file_url}")
+            reply = Reply(ReplyType.FILE, file_url)
+            reply.file_name = file_info.get("file_name", os.path.basename(file_path))
+            # Attach text message if present
+            if text_response:
+                reply.text_content = text_response
+            return reply
+        
+        # For all other file types (tar.gz, zip, etc.), also use FILE type
+        file_url = _to_channel_url(file_path)
+        logger.info(f"[AgentBridge] Sending generic file: {file_url}")
+        reply = Reply(ReplyType.FILE, file_url)
+        reply.file_name = file_info.get("file_name", os.path.basename(file_path))
+        if text_response:
+            reply.text_content = text_response
+        return reply
+    
+    def _migrate_config_to_env(self, workspace_root: str):
+        """
+        Sync API keys from config.json to .env file.
+        Adds new keys and updates changed values on each startup.
+
+        Args:
+            workspace_root: Workspace directory path (not used, kept for compatibility)
+        """
+        from config import conf
+        import os
+        
+        key_mapping = {
+            "open_ai_api_key": "OPENAI_API_KEY",
+            "open_ai_api_base": "OPENAI_API_BASE",
+            "gemini_api_key": "GEMINI_API_KEY",
+            "claude_api_key": "CLAUDE_API_KEY",
+            "linkai_api_key": "LINKAI_API_KEY",
+        }
+        
+        env_file = expand_path("~/.cow/.env")
+        
+        # Read existing env vars (key -> value)
+        existing_env_vars = {}
+        if os.path.exists(env_file):
+            try:
+                with open(env_file, 'r', encoding='utf-8') as f:
+                    for line in f:
+                        line = line.strip()
+                        if line and not line.startswith('#') and '=' in line:
+                            key, val = line.split('=', 1)
+                            existing_env_vars[key.strip()] = val.strip()
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to read .env file: {e}")
+        
+        # Sync config.json values into .env (add/update/remove)
+        updated = False
+        for config_key, env_key in key_mapping.items():
+            raw = conf().get(config_key, "")
+            value = raw.strip() if raw else ""
+            old_value = existing_env_vars.get(env_key)
+
+            if value:
+                if old_value == value:
+                    continue
+                existing_env_vars[env_key] = value
+                os.environ[env_key] = value
+                updated = True
+            else:
+                if old_value is None:
+                    continue
+                existing_env_vars.pop(env_key, None)
+                os.environ.pop(env_key, None)
+                updated = True
+            updated = True
+
+        if updated:
+            try:
+                env_dir = os.path.dirname(env_file)
+                os.makedirs(env_dir, exist_ok=True)
+
+                with open(env_file, 'w', encoding='utf-8') as f:
+                    f.write('# Environment variables for agent\n')
+                    f.write('# Auto-managed - synced from config.json on startup\n\n')
+                    for key, value in sorted(existing_env_vars.items()):
+                        f.write(f'{key}={value}\n')
+
+                logger.info(f"[AgentBridge] Synced API keys from config.json to .env")
+            except Exception as e:
+                logger.warning(f"[AgentBridge] Failed to sync API keys: {e}")
+    
+    def _pre_persist_user_message(
+        self, session_id: str, query: str, context: Context, clear_history: bool
+    ) -> bool:
+        """Persist the user's message before the agent runs.
+
+        This makes a brand-new session (and the user's bubble) visible even if
+        the reply hasn't finished — switching away or refreshing no longer
+        loses the in-flight session. Returns True when the user turn was
+        stored, so the caller can skip it in the post-run persist.
+
+        Best-effort: any failure is swallowed and reported as not-persisted.
+        """
+        if not session_id or not query:
+            return False
+        # Only real user turns: skip scheduler-injected / scheduled-task runs.
+        if session_id.startswith("scheduler_") or (
+            context and context.get("is_scheduled_task")
+        ):
+            return False
+        try:
+            from config import conf
+            if not conf().get("conversation_persistence", True):
+                return False
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            # clear_history starts a fresh transcript: wipe the store first so
+            # the eager user turn becomes seq 0, matching in-memory state.
+            if clear_history:
+                store.clear_session(session_id)
+            channel_type = (context.get("channel_type") or "") if context else ""
+            user_msg = {
+                "role": "user",
+                "content": [{"type": "text", "text": query}],
+            }
+            store.append_messages(session_id, [user_msg], channel_type=channel_type)
+            return True
+        except Exception as e:
+            logger.warning(
+                f"[AgentBridge] Failed to pre-persist user message for session={session_id}: {e}"
+            )
+            return False
+
+    def _persist_messages(
+        self, session_id: str, new_messages: list, channel_type: str = ""
+    ) -> None:
+        """
+        Persist new messages to the conversation store after each agent run.
+
+        Failures are logged but never propagate — they must not interrupt replies.
+        """
+        if not new_messages:
+            return
+        try:
+            from config import conf
+            if not conf().get("conversation_persistence", True):
+                return
+            # When deep-thinking display is disabled, strip "thinking" content
+            # blocks before persisting so they don't resurface on history reload.
+            # The in-memory message list keeps them intact for this run's
+            # multi-turn LLM context.
+            thinking_enabled = bool(conf().get("enable_thinking", False))
+        except Exception:
+            thinking_enabled = False
+
+        messages_to_store = new_messages
+        if not thinking_enabled:
+            messages_to_store = self._strip_thinking_blocks(new_messages)
+
+        try:
+            from agent.memory import get_conversation_store
+            get_conversation_store().append_messages(
+                session_id, messages_to_store, channel_type=channel_type
+            )
+        except Exception as e:
+            logger.warning(
+                f"[AgentBridge] Failed to persist messages for session={session_id}: {e}"
+            )
+
+    # Marker used to identify scheduler-injected user messages so we can apply
+    # a sliding window without touching real user turns. The legacy prefix
+    # "Scheduled task" (written by the v2 PR) is also recognised when pruning,
+    # so old data can be aged out instead of leaking forever.
+    _SCHEDULED_MARKER = "[SCHEDULED]"
+    _SCHEDULED_LEGACY_MARKERS = ("Scheduled task",)
+
+    def remember_scheduled_output(
+        self,
+        session_id: str,
+        content: str,
+        channel_type: str = "",
+        task_description: str = "",
+    ) -> None:
+        """Add the visible output of a scheduled task to the receiver's session.
+
+        Scheduled task execution uses an isolated session so internal planning and
+        tool calls do not leak into the user's chat. The final message is still
+        part of the conversation from the user's point of view, so keep a small
+        visible turn in the receiver session for follow-up questions.
+
+        Configuration:
+            scheduler_inject_to_session (bool, default True):
+                Master switch. When False, this method is a no-op.
+            scheduler_inject_max_per_session (int, default 3):
+                Maximum scheduler-injected user/assistant pairs retained per
+                session. Older injections are pruned automatically.
+
+        Content is truncated to 2000 chars to prevent a single high-volume task
+        from bloating one entry.
+        """
+        from config import conf
+        if not conf().get("scheduler_inject_to_session", True):
+            return
+        if not session_id or not content:
+            return
+
+        max_len = 2000
+        if len(content) > max_len:
+            content = content[:max_len] + "..."
+
+        user_text = self._SCHEDULED_MARKER
+        if task_description:
+            user_text = f"{self._SCHEDULED_MARKER} {task_description}"
+
+        messages = [
+            {"role": "user", "content": [{"type": "text", "text": user_text}]},
+            {"role": "assistant", "content": [{"type": "text", "text": content}]},
+        ]
+
+        # Persist first so the new pair gets a stable seq, then prune old
+        # scheduler pairs in DB, then sync the in-memory agent.messages buffer.
+        self._persist_messages(session_id, messages, channel_type)
+
+        keep_last_n = max(int(conf().get("scheduler_inject_max_per_session", 3) or 0), 0)
+        try:
+            from agent.memory import get_conversation_store
+            deleted = get_conversation_store().prune_scheduled_messages(
+                session_id, keep_last_n=keep_last_n
+            )
+            if deleted:
+                logger.debug(
+                    f"[AgentBridge] Pruned {deleted} old scheduler messages "
+                    f"for session={session_id} (keep_last_n={keep_last_n})"
+                )
+        except Exception as e:
+            logger.warning(
+                f"[AgentBridge] Failed to prune scheduled messages "
+                f"for session={session_id}: {e}"
+            )
+
+        agent = self.agents.get(session_id)
+        if agent:
+            try:
+                with agent.messages_lock:
+                    agent.messages.extend(messages)
+                    self._prune_scheduled_in_memory(agent, keep_last_n)
+            except Exception as e:
+                logger.warning(
+                    f"[AgentBridge] Failed to update in-memory scheduled output "
+                    f"for session={session_id}: {e}"
+                )
+
+    @staticmethod
+    def _trim_in_memory_to_turns(agent, keep_turns: int) -> None:
+        """Bound ``agent.messages`` to the most recent ``keep_turns`` real
+        user/assistant turns, dropping older history together with any
+        intermediate tool_use/tool_result blocks that belonged to it.
+
+        A "real" user message is any user message whose content is not solely a
+        tool_result block — matches the heuristic used elsewhere when filtering
+        history (see ``AgentInitializer._filter_text_only_messages``).
+
+        No-op when the session is already within budget. Caller does not need
+        to hold the lock; this method acquires it itself.
+        """
+        if keep_turns <= 0:
+            return
+
+        def _is_real_user(msg) -> bool:
+            if not isinstance(msg, dict) or msg.get("role") != "user":
+                return False
+            content = msg.get("content")
+            if isinstance(content, list):
+                if any(
+                    isinstance(b, dict) and b.get("type") == "tool_result"
+                    for b in content
+                ):
+                    return False
+                return any(
+                    isinstance(b, dict) and b.get("type") == "text" and b.get("text")
+                    for b in content
+                )
+            if isinstance(content, str):
+                return bool(content.strip())
+            return False
+
+        with agent.messages_lock:
+            msgs = agent.messages
+            real_user_indices = [i for i, m in enumerate(msgs) if _is_real_user(m)]
+            if len(real_user_indices) <= keep_turns:
+                return
+
+            # Cut at the (k-th from the end) real user message; keep everything
+            # from there onwards so the surviving slice is still a valid
+            # user/assistant sequence.
+            cut_idx = real_user_indices[-keep_turns]
+            if cut_idx == 0:
+                return
+
+            kept = msgs[cut_idx:]
+            msgs.clear()
+            msgs.extend(kept)
+            logger.debug(
+                f"[AgentBridge] Trimmed in-memory messages to last "
+                f"{keep_turns} turns ({len(kept)} messages remain)"
+            )
+
+    @classmethod
+    def _prune_scheduled_in_memory(cls, agent, keep_last_n: int) -> None:
+        """Mirror conversation_store.prune_scheduled_messages on agent.messages.
+
+        Caller must hold ``agent.messages_lock``.
+        """
+        if keep_last_n < 0:
+            keep_last_n = 0
+
+        markers = (cls._SCHEDULED_MARKER,) + cls._SCHEDULED_LEGACY_MARKERS
+
+        def _is_marker_user(msg) -> bool:
+            if not isinstance(msg, dict) or msg.get("role") != "user":
+                return False
+            content = msg.get("content")
+            text = ""
+            if isinstance(content, str):
+                text = content
+            elif isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict) and block.get("type") == "text":
+                        text = block.get("text", "")
+                        break
+            return any(text.startswith(m) for m in markers)
+
+        msgs = agent.messages
+        pair_indices = []  # list of (user_idx, assistant_idx_or_None)
+        for idx, msg in enumerate(msgs):
+            if not _is_marker_user(msg):
+                continue
+            assistant_idx = None
+            if idx + 1 < len(msgs):
+                nxt = msgs[idx + 1]
+                if isinstance(nxt, dict) and nxt.get("role") == "assistant":
+                    assistant_idx = idx + 1
+            pair_indices.append((idx, assistant_idx))
+
+        if len(pair_indices) <= keep_last_n:
+            return
+
+        to_drop = pair_indices[: len(pair_indices) - keep_last_n]
+        drop_set = set()
+        for u_idx, a_idx in to_drop:
+            drop_set.add(u_idx)
+            if a_idx is not None:
+                drop_set.add(a_idx)
+
+        # Rebuild the list in place to keep external references stable.
+        kept = [m for i, m in enumerate(msgs) if i not in drop_set]
+        msgs.clear()
+        msgs.extend(kept)
+
+    @staticmethod
+    def _strip_thinking_blocks(messages: list) -> list:
+        """Return a shallow copy of messages with assistant "thinking" blocks removed."""
+        cleaned = []
+        for msg in messages:
+            if not isinstance(msg, dict):
+                cleaned.append(msg)
+                continue
+            if msg.get("role") != "assistant":
+                cleaned.append(msg)
+                continue
+            content = msg.get("content")
+            if not isinstance(content, list):
+                cleaned.append(msg)
+                continue
+            filtered_blocks = [
+                b for b in content
+                if not (isinstance(b, dict) and b.get("type") == "thinking")
+            ]
+            if len(filtered_blocks) == len(content):
+                cleaned.append(msg)
+            else:
+                new_msg = dict(msg)
+                new_msg["content"] = filtered_blocks
+                cleaned.append(new_msg)
+        return cleaned
+
+    def clear_session(self, session_id: str):
+        """
+        Clear a specific session's agent and conversation history
+        
+        Args:
+            session_id: Session identifier to clear
+        """
+        if session_id in self.agents:
+            logger.info(f"[AgentBridge] Clearing session: {session_id}")
+            del self.agents[session_id]
+    
+    def clear_all_sessions(self):
+        """Clear all agent sessions"""
+        logger.info(f"[AgentBridge] Clearing all sessions ({len(self.agents)} total)")
+        self.agents.clear()
+        self.default_agent = None
+    
+    def refresh_all_skills(self) -> int:
+        """
+        Refresh skills and conditional tools in all agent instances after
+        environment variable changes. This allows hot-reload without restarting.
+
+        Returns:
+            Number of agent instances refreshed
+        """
+        import os
+        from dotenv import load_dotenv
+        from config import conf
+
+        # Reload environment variables from .env file
+        workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        env_file = os.path.join(workspace_root, '.env')
+
+        if os.path.exists(env_file):
+            load_dotenv(env_file, override=True)
+            logger.info(f"[AgentBridge] Reloaded environment variables from {env_file}")
+
+        refreshed_count = 0
+
+        # Collect all agent instances to refresh
+        agents_to_refresh = []
+        if self.default_agent:
+            agents_to_refresh.append(("default", self.default_agent))
+        for session_id, agent in self.agents.items():
+            agents_to_refresh.append((session_id, agent))
+
+        for label, agent in agents_to_refresh:
+            # Refresh skills
+            if hasattr(agent, 'skill_manager') and agent.skill_manager:
+                agent.skill_manager.refresh_skills()
+
+            # Refresh conditional tools (e.g. web_search depends on API keys)
+            self._refresh_conditional_tools(agent)
+
+            refreshed_count += 1
+
+        if refreshed_count > 0:
+            logger.info(f"[AgentBridge] Refreshed skills & tools in {refreshed_count} agent instance(s)")
+
+        return refreshed_count
+
+    @staticmethod
+    def _refresh_conditional_tools(agent):
+        """
+        Add or remove conditional tools based on current environment variables.
+        For example, web_search should only be present when BOCHA_API_KEY or
+        LINKAI_API_KEY is set.
+        """
+        try:
+            from agent.tools.web_search.web_search import WebSearch
+
+            has_tool = any(t.name == "web_search" for t in agent.tools)
+            available = WebSearch.is_available()
+
+            if available and not has_tool:
+                # API key was added - inject the tool
+                tool = WebSearch()
+                tool.model = agent.model
+                agent.tools.append(tool)
+                logger.info("[AgentBridge] web_search tool added (API key now available)")
+            elif not available and has_tool:
+                # API key was removed - remove the tool
+                agent.tools = [t for t in agent.tools if t.name != "web_search"]
+                logger.info("[AgentBridge] web_search tool removed (API key no longer available)")
+        except Exception as e:
+            logger.debug(f"[AgentBridge] Failed to refresh conditional tools: {e}")
diff --git a/bridge/agent_event_handler.py b/bridge/agent_event_handler.py
new file mode 100644
index 0000000..3517373
--- /dev/null
+++ b/bridge/agent_event_handler.py
@@ -0,0 +1,125 @@
+"""
+Agent Event Handler - Handles agent events and thinking process output
+"""
+
+from common import const
+from common.log import logger
+
+# Cap intermediate thinking messages on weixin to stay within send quota.
+WEIXIN_THINKING_INSTANT_MAX = 7
+
+
+class AgentEventHandler:
+    """
+    Handles agent events and optionally sends intermediate messages to channel
+    """
+
+    def __init__(self, context=None, original_callback=None):
+        self.context = context
+        self.original_callback = original_callback
+
+        self.channel = None
+        if context:
+            self.channel = context.kwargs.get("channel") if hasattr(context, "kwargs") else None
+
+        self.current_content = ""
+        self.turn_number = 0
+
+        channel_type = ""
+        if context and hasattr(context, "kwargs"):
+            channel_type = context.kwargs.get("channel_type", "") or ""
+        self._is_weixin = channel_type == const.WEIXIN
+        self._thinking_sent_count = 0
+        self._merged_buf: list[str] = []
+
+    def handle_event(self, event):
+        event_type = event.get("type")
+        data = event.get("data", {})
+
+        if event_type == "turn_start":
+            self._handle_turn_start(data)
+        elif event_type == "message_update":
+            self._handle_message_update(data)
+        elif event_type == "message_end":
+            self._handle_message_end(data)
+        elif event_type == "reasoning_update":
+            pass
+        elif event_type == "tool_execution_start":
+            self._handle_tool_execution_start(data)
+        elif event_type == "tool_execution_end":
+            self._handle_tool_execution_end(data)
+        elif event_type == "agent_end":
+            self._handle_agent_end(data)
+
+        if self.original_callback:
+            self.original_callback(event)
+
+    def _handle_turn_start(self, data):
+        self.turn_number = data.get("turn", 0)
+        self.current_content = ""
+
+    def _handle_message_update(self, data):
+        delta = data.get("delta", "")
+        self.current_content += delta
+
+    def _handle_message_end(self, data):
+        tool_calls = data.get("tool_calls", [])
+
+        if tool_calls:
+            if self.current_content.strip():
+                logger.info(f"💭 {self.current_content.strip()[:200]}{'...' if len(self.current_content) > 200 else ''}")
+                self._send_to_channel(self.current_content.strip())
+        else:
+            if self.current_content.strip():
+                logger.debug(f"💬 {self.current_content.strip()[:200]}{'...' if len(self.current_content) > 200 else ''}")
+            # Drain weixin buffer before final reply leaves chat_channel
+            self._flush_merged_now()
+
+        self.current_content = ""
+
+    def _handle_agent_end(self, data):
+        self._flush_merged_now()
+
+    def _handle_tool_execution_start(self, data):
+        pass
+
+    def _handle_tool_execution_end(self, data):
+        pass
+
+    def _send_to_channel(self, message):
+        if self.context and self.context.get("on_event"):
+            return
+        if not self.channel:
+            return
+
+        if not self._is_weixin:
+            self._do_send(message)
+            return
+
+        if self._thinking_sent_count < WEIXIN_THINKING_INSTANT_MAX:
+            self._do_send(message)
+            self._thinking_sent_count += 1
+            return
+
+        self._merged_buf.append(message)
+
+    def _flush_merged_now(self):
+        if not self._merged_buf:
+            return
+        merged = "\n\n".join(self._merged_buf)
+        count = len(self._merged_buf)
+        self._merged_buf = []
+        logger.debug(f"[AgentEventHandler] Flushing {count} merged thinking msgs, len={len(merged)}")
+        self._do_send(merged)
+        self._thinking_sent_count += 1
+
+    def _do_send(self, message):
+        try:
+            from bridge.reply import Reply, ReplyType
+            reply = Reply(ReplyType.TEXT, message)
+            self.channel._send(reply, self.context)
+        except Exception as e:
+            logger.debug(f"[AgentEventHandler] Failed to send to channel: {e}")
+
+    def log_summary(self):
+        pass
diff --git a/bridge/agent_initializer.py b/bridge/agent_initializer.py
new file mode 100644
index 0000000..f795fb0
--- /dev/null
+++ b/bridge/agent_initializer.py
@@ -0,0 +1,657 @@
+"""
+Agent Initializer - Handles agent initialization logic
+"""
+
+import os
+import asyncio
+import datetime
+import threading
+import time
+from typing import Optional, List
+
+from agent.protocol import Agent
+from agent.tools import ToolManager
+from common.log import logger
+from common.utils import expand_path
+
+# Module-level lock to serialize scheduler init across concurrent sessions
+_scheduler_init_lock = threading.Lock()
+
+
+class AgentInitializer:
+    """
+    Handles agent initialization including:
+    - Workspace setup
+    - Memory system initialization  
+    - Tool loading
+    - System prompt building
+    """
+    
+    def __init__(self, bridge, agent_bridge):
+        """
+        Initialize agent initializer
+        
+        Args:
+            bridge: COW bridge instance
+            agent_bridge: AgentBridge instance (for create_agent method)
+        """
+        self.bridge = bridge
+        self.agent_bridge = agent_bridge
+    
+    def initialize_agent(self, session_id: Optional[str] = None) -> Agent:
+        """
+        Initialize agent for a session
+        
+        Args:
+            session_id: Session ID (None for default agent)
+        
+        Returns:
+            Initialized agent instance
+        """
+        from config import conf
+        
+        # Get workspace from config
+        workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        
+        # Migrate API keys
+        self._migrate_config_to_env(workspace_root)
+        
+        # Load environment variables
+        self._load_env_file()
+        
+        # Initialize workspace
+        from agent.prompt import ensure_workspace, load_context_files, PromptBuilder
+        workspace_files = ensure_workspace(workspace_root, create_templates=True)
+        
+        if session_id is None:
+            logger.info(f"[AgentInitializer] Workspace initialized at: {workspace_root}")
+        
+        # Setup memory system
+        memory_manager, memory_tools = self._setup_memory_system(workspace_root, session_id)
+        
+        # Load tools
+        tools = self._load_tools(workspace_root, memory_manager, memory_tools, session_id)
+        
+        # Initialize scheduler if needed
+        self._initialize_scheduler(tools, session_id)
+        
+        # Load context files
+        context_files = load_context_files(workspace_root)
+        
+        # Initialize skill manager
+        skill_manager = self._initialize_skill_manager(workspace_root, session_id)
+        
+        # Build system prompt
+        prompt_builder = PromptBuilder(workspace_dir=workspace_root, language="zh")
+        runtime_info = self._get_runtime_info(workspace_root)
+        
+        system_prompt = prompt_builder.build(
+            tools=tools,
+            context_files=context_files,
+            skill_manager=skill_manager,
+            memory_manager=memory_manager,
+            runtime_info=runtime_info,
+        )
+        
+        # Get cost control parameters
+        from config import conf
+        max_steps = conf().get("agent_max_steps", 20)
+        max_context_tokens = conf().get("agent_max_context_tokens", 50000)
+        
+        # Create agent
+        agent = self.agent_bridge.create_agent(
+            system_prompt=system_prompt,
+            tools=tools,
+            max_steps=max_steps,
+            output_mode="logger",
+            workspace_dir=workspace_root,
+            skill_manager=skill_manager,
+            enable_skills=True,
+            max_context_tokens=max_context_tokens,
+            runtime_info=runtime_info  # Pass runtime_info for dynamic time updates
+        )
+        
+        # Attach memory manager and share LLM model for summarization
+        if memory_manager:
+            agent.memory_manager = memory_manager
+            if hasattr(agent, 'model') and agent.model:
+                memory_manager.flush_manager.llm_model = agent.model
+
+        # Restore persisted conversation history for this session
+        if session_id:
+            self._restore_conversation_history(agent, session_id)
+
+        # Start daily memory flush timer (once, on first agent init regardless of session)
+        self._start_daily_flush_timer()
+
+        return agent
+
+    def _restore_conversation_history(self, agent, session_id: str) -> None:
+        """
+        Load persisted conversation messages from SQLite and inject them
+        into the agent's in-memory message list.
+
+        Only user text and assistant text are restored. Tool call chains
+        (tool_use / tool_result) are stripped out because:
+        1. They are intermediate process, the value is already in the final
+           assistant text reply.
+        2. They consume massive context tokens (often 80%+ of history).
+        3. Different models have incompatible tool message formats, so
+           restoring tool chains across model switches causes 400 errors.
+        4. Eliminates the entire class of tool_use/tool_result pairing bugs.
+        """
+        from config import conf
+        if not conf().get("conversation_persistence", True):
+            return
+
+        try:
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            max_turns = conf().get("agent_max_context_turns", 20)
+            # Scheduler tasks run on a stable isolated session per task and
+            # can fire many times a day; a smaller restore window keeps prompt
+            # cost bounded while still letting the agent see "last few" runs
+            # for trend / dedup style logic. Regular chat sessions keep the
+            # original heuristic so user dialogues feel continuous.
+            if session_id.startswith("scheduler_"):
+                restore_turns = max(1, max_turns // 5)
+            else:
+                restore_turns = max(3, max_turns // 6)
+            saved = store.load_messages(session_id, max_turns=restore_turns)
+            if saved:
+                filtered = self._filter_text_only_messages(saved)
+                if filtered:
+                    with agent.messages_lock:
+                        agent.messages = filtered
+                    logger.debug(
+                        f"[AgentInitializer] Restored {len(filtered)} text messages "
+                        f"(from {len(saved)} total, {restore_turns} turns cap) "
+                        f"for session={session_id}"
+                    )
+        except Exception as e:
+            logger.warning(
+                f"[AgentInitializer] Failed to restore conversation history for "
+                f"session={session_id}: {e}"
+            )
+
+    @staticmethod
+    def _filter_text_only_messages(messages: list) -> list:
+        """
+        Extract clean user/assistant turn pairs from raw message history.
+
+        Groups messages into turns (each starting with a real user query),
+        then keeps only:
+        - The first user text in each turn (the actual user input)
+        - The last assistant text in each turn (the final answer)
+
+        All tool_use, tool_result, intermediate assistant thoughts, and
+        internal hint messages injected by the agent loop are discarded.
+        """
+
+        def _extract_text(content) -> str:
+            if isinstance(content, str):
+                return content.strip()
+            if isinstance(content, list):
+                parts = [
+                    b.get("text", "")
+                    for b in content
+                    if isinstance(b, dict) and b.get("type") == "text"
+                ]
+                return "\n".join(p for p in parts if p).strip()
+            return ""
+
+        def _is_real_user_msg(msg: dict) -> bool:
+            """True for actual user input, False for tool_result or internal hints."""
+            if msg.get("role") != "user":
+                return False
+            content = msg.get("content")
+            if isinstance(content, list):
+                has_tool_result = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result"
+                    for b in content
+                )
+                if has_tool_result:
+                    return False
+            text = _extract_text(content)
+            return bool(text)
+
+        # Group into turns: each turn starts with a real user message
+        turns = []
+        current_turn = None
+        for msg in messages:
+            if _is_real_user_msg(msg):
+                if current_turn is not None:
+                    turns.append(current_turn)
+                current_turn = {"user": msg, "assistants": []}
+            elif current_turn is not None and msg.get("role") == "assistant":
+                text = _extract_text(msg.get("content"))
+                if text:
+                    current_turn["assistants"].append(text)
+        if current_turn is not None:
+            turns.append(current_turn)
+
+        # Build result: one user msg + one assistant msg per turn
+        filtered = []
+        for turn in turns:
+            user_text = _extract_text(turn["user"].get("content"))
+            if not user_text:
+                continue
+            filtered.append({
+                "role": "user",
+                "content": [{"type": "text", "text": user_text}]
+            })
+            if turn["assistants"]:
+                final_reply = turn["assistants"][-1]
+                filtered.append({
+                    "role": "assistant",
+                    "content": [{"type": "text", "text": final_reply}]
+                })
+
+        return filtered
+    
+    def _load_env_file(self):
+        """Load environment variables from .env file"""
+        env_file = expand_path("~/.cow/.env")
+        if os.path.exists(env_file):
+            try:
+                from dotenv import load_dotenv
+                load_dotenv(env_file, override=True)
+            except ImportError:
+                logger.warning("[AgentInitializer] python-dotenv not installed")
+            except Exception as e:
+                logger.warning(f"[AgentInitializer] Failed to load .env file: {e}")
+    
+    def _setup_memory_system(self, workspace_root: str, session_id: Optional[str] = None):
+        """
+        Setup memory system
+        
+        Returns:
+            (memory_manager, memory_tools) tuple
+        """
+        memory_manager = None
+        memory_tools = []
+        
+        try:
+            from agent.memory import MemoryManager, MemoryConfig
+            from agent.tools import MemorySearchTool, MemoryGetTool
+            from config import conf
+
+            memory_config = MemoryConfig(workspace_root=workspace_root)
+
+            embedding_provider = self._init_embedding_provider(
+                memory_config, session_id=session_id
+            )
+
+            memory_manager = MemoryManager(memory_config, embedding_provider=embedding_provider)
+            self._sync_memory(memory_manager, session_id)
+
+            memory_tools = [
+                MemorySearchTool(memory_manager),
+                MemoryGetTool(memory_manager)
+            ]
+            
+            if session_id is None:
+                logger.info("[AgentInitializer] Memory system initialized")
+        
+        except Exception as e:
+            logger.warning(f"[AgentInitializer] Memory system not available: {e}")
+        
+        return memory_manager, memory_tools
+
+    def _init_embedding_provider(self, memory_config, session_id: Optional[str] = None):
+        """
+        Initialize the embedding provider for memory.
+
+        Delegates to the shared factory so agent init, knowledge sync and
+        index rebuild all select the same provider:
+          A. Default (no `embedding_provider` in config.json):
+             Auto-init OpenAI -> LinkAI fallback.
+          B. Explicit (`embedding_provider` is set):
+             Initialize the requested vendor.
+        """
+        from agent.memory import create_default_embedding_provider
+        return create_default_embedding_provider()
+
+    def _sync_memory(self, memory_manager, session_id: Optional[str] = None):
+        """Sync memory database"""
+        try:
+            loop = asyncio.get_event_loop()
+            if loop.is_closed():
+                raise RuntimeError("Event loop is closed")
+        except RuntimeError:
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+        
+        try:
+            if loop.is_running():
+                asyncio.create_task(memory_manager.sync())
+            else:
+                loop.run_until_complete(memory_manager.sync())
+        except Exception as e:
+            logger.warning(f"[AgentInitializer] Memory sync failed: {e}")
+    
+    def _load_tools(self, workspace_root: str, memory_manager, memory_tools: List, session_id: Optional[str] = None):
+        """Load all tools"""
+        tool_manager = ToolManager()
+        tool_manager.load_tools()
+        
+        tools = []
+        file_config = {
+            "cwd": workspace_root,
+            "memory_manager": memory_manager
+        } if memory_manager else {"cwd": workspace_root}
+        
+        for tool_name in tool_manager.tool_classes.keys():
+            try:
+                # Skip web_search if no API key is available
+                if tool_name == "web_search":
+                    from agent.tools.web_search.web_search import WebSearch
+                    if not WebSearch.is_available():
+                        logger.debug("[AgentInitializer] WebSearch skipped - no search provider configured")
+                        continue
+
+                # Skip evolution_undo when self-evolution is disabled: with no
+                # evolution there is nothing to roll back, so the tool is dead weight.
+                if tool_name == "evolution_undo":
+                    from agent.evolution.config import get_evolution_config
+                    if not get_evolution_config().enabled:
+                        logger.debug("[AgentInitializer] evolution_undo skipped - self-evolution disabled")
+                        continue
+
+                # Special handling for EnvConfig tool
+                if tool_name == "env_config":
+                    from agent.tools import EnvConfig
+                    tool = EnvConfig({"agent_bridge": self.agent_bridge})
+                else:
+                    tool = tool_manager.create_tool(tool_name)
+
+                if tool:
+                    # Apply workspace config to file operation tools.
+                    # Merge into the existing tool.config (set by ToolManager from
+                    # config.json's `tools.<name>` section) instead of replacing
+                    # it, otherwise per-tool user configs (e.g. browser.cdp_endpoint)
+                    # would be silently dropped.
+                    if tool_name in ['read', 'write', 'edit', 'bash', 'grep', 'find', 'ls', 'web_fetch', 'send', 'browser']:
+                        merged_config = dict(getattr(tool, 'config', None) or {})
+                        merged_config.update(file_config)
+                        tool.config = merged_config
+                        tool.cwd = merged_config.get("cwd", getattr(tool, 'cwd', None))
+                        if 'memory_manager' in merged_config:
+                            tool.memory_manager = merged_config['memory_manager']
+                    tools.append(tool)
+            except Exception as e:
+                logger.warning(f"[AgentInitializer] Failed to load tool {tool_name}: {e}")
+
+        # Add MCP tools (snapshot to avoid races with the background loader)
+        mcp_tools_snapshot = list(tool_manager._mcp_tool_instances.items())
+        if mcp_tools_snapshot:
+            for _, mcp_tool in mcp_tools_snapshot:
+                tools.append(mcp_tool)
+            if session_id is None:
+                names = [name for name, _ in mcp_tools_snapshot]
+                logger.info(
+                    f"[AgentInitializer] Added {len(names)} MCP tool(s): {names}"
+                )
+
+        # Add memory tools
+        if memory_tools:
+            tools.extend(memory_tools)
+            if session_id is None:
+                logger.info(f"[AgentInitializer] Added {len(memory_tools)} memory tools")
+        
+        if session_id is None:
+            logger.info(f"[AgentInitializer] Loaded {len(tools)} tools: {[t.name for t in tools]}")
+        
+        return tools
+    
+    def _initialize_scheduler(self, tools: List, session_id: Optional[str] = None):
+        """Initialize scheduler service if needed.
+
+        Serialize the check-and-set under a module-level lock so concurrent
+        first-time session inits cannot each create a new SchedulerService
+        (which would leak background scanning threads).
+        """
+        if not self.agent_bridge.scheduler_initialized:
+            with _scheduler_init_lock:
+                if not self.agent_bridge.scheduler_initialized:
+                    try:
+                        from agent.tools.scheduler.integration import init_scheduler
+                        if init_scheduler(self.agent_bridge):
+                            self.agent_bridge.scheduler_initialized = True
+                            if session_id is None:
+                                logger.info("[AgentInitializer] Scheduler service initialized")
+                    except Exception as e:
+                        logger.warning(f"[AgentInitializer] Failed to initialize scheduler: {e}")
+        
+        # Inject scheduler dependencies
+        if self.agent_bridge.scheduler_initialized:
+            try:
+                from agent.tools.scheduler.integration import get_task_store, get_scheduler_service
+                from agent.tools import SchedulerTool
+                from config import conf
+                
+                task_store = get_task_store()
+                scheduler_service = get_scheduler_service()
+                
+                for tool in tools:
+                    if isinstance(tool, SchedulerTool):
+                        tool.task_store = task_store
+                        tool.scheduler_service = scheduler_service
+                        if not tool.config:
+                            tool.config = {}
+                        raw_ct = conf().get("channel_type", "unknown")
+                        if isinstance(raw_ct, list):
+                            ct = raw_ct[0] if raw_ct else "unknown"
+                        elif isinstance(raw_ct, str) and "," in raw_ct:
+                            ct = raw_ct.split(",")[0].strip()
+                        else:
+                            ct = raw_ct
+                        tool.config["channel_type"] = ct
+            except Exception as e:
+                logger.warning(f"[AgentInitializer] Failed to inject scheduler dependencies: {e}")
+    
+    def _initialize_skill_manager(self, workspace_root: str, session_id: Optional[str] = None):
+        """Initialize skill manager"""
+        try:
+            from agent.skills import SkillManager
+            skill_manager = SkillManager(custom_dir=os.path.join(workspace_root, "skills"))
+            return skill_manager
+        except Exception as e:
+            logger.warning(f"[AgentInitializer] Failed to initialize SkillManager: {e}")
+            return None
+    
+    def _get_runtime_info(self, workspace_root: str):
+        """Get runtime information with dynamic time support"""
+        from config import conf
+        
+        def get_current_time():
+            """Get current time dynamically - called each time system prompt is accessed"""
+            now = datetime.datetime.now()
+            
+            # Get timezone info
+            try:
+                offset = -time.timezone if not time.daylight else -time.altzone
+                hours = offset // 3600
+                minutes = (offset % 3600) // 60
+                timezone_name = f"UTC{hours:+03d}:{minutes:02d}" if minutes else f"UTC{hours:+03d}"
+            except Exception:
+                timezone_name = "UTC"
+            
+            # Weekday: English name in en, Chinese mapping otherwise
+            weekday_en = now.strftime("%A")
+            try:
+                from common import i18n
+                is_en = i18n.get_language() == "en"
+            except Exception:
+                is_en = False
+            if is_en:
+                weekday = weekday_en
+            else:
+                weekday_map = {
+                    'Monday': '星期一', 'Tuesday': '星期二', 'Wednesday': '星期三',
+                    'Thursday': '星期四', 'Friday': '星期五', 'Saturday': '星期六', 'Sunday': '星期日'
+                }
+                weekday = weekday_map.get(weekday_en, weekday_en)
+
+            return {
+                'time': now.strftime("%Y-%m-%d %H:%M:%S"),
+                'weekday': weekday,
+                'timezone': timezone_name
+            }
+        
+        def get_model():
+            """Get current model name dynamically from config"""
+            return conf().get("model", "unknown")
+
+        return {
+            "_get_model": get_model,
+            "workspace": workspace_root,
+            "channel": ", ".join(conf().get("channel_type")) if isinstance(conf().get("channel_type"), list) else conf().get("channel_type", "unknown"),
+            "_get_current_time": get_current_time  # Dynamic time function
+        }
+    
+    def _migrate_config_to_env(self, workspace_root: str):
+        """Migrate API keys from config.json to .env file"""
+        from config import conf
+        
+        key_mapping = {
+            "open_ai_api_key": "OPENAI_API_KEY",
+            "open_ai_api_base": "OPENAI_API_BASE",
+            "gemini_api_key": "GEMINI_API_KEY",
+            "claude_api_key": "CLAUDE_API_KEY",
+            "linkai_api_key": "LINKAI_API_KEY",
+        }
+        
+        env_file = expand_path("~/.cow/.env")
+        
+        # Read existing env vars (key -> value)
+        existing_env_vars = {}
+        if os.path.exists(env_file):
+            try:
+                with open(env_file, 'r', encoding='utf-8') as f:
+                    for line in f:
+                        line = line.strip()
+                        if line and not line.startswith('#') and '=' in line:
+                            key, val = line.split('=', 1)
+                            existing_env_vars[key.strip()] = val.strip()
+            except Exception as e:
+                logger.warning(f"[AgentInitializer] Failed to read .env file: {e}")
+        
+        # Sync config.json values into .env (add/update/remove)
+        updated = False
+        for config_key, env_key in key_mapping.items():
+            raw = conf().get(config_key, "")
+            value = raw.strip() if raw else ""
+            old_value = existing_env_vars.get(env_key)
+
+            if value:
+                if old_value == value:
+                    continue
+                existing_env_vars[env_key] = value
+                os.environ[env_key] = value
+                updated = True
+            else:
+                if old_value is None:
+                    continue
+                existing_env_vars.pop(env_key, None)
+                os.environ.pop(env_key, None)
+                updated = True
+
+        if updated:
+            try:
+                env_dir = os.path.dirname(env_file)
+                os.makedirs(env_dir, exist_ok=True)
+
+                # Rewrite the entire .env file to ensure consistency
+                with open(env_file, 'w', encoding='utf-8') as f:
+                    f.write('# Environment variables for agent\n')
+                    f.write('# Auto-managed - synced from config.json on startup\n\n')
+                    for key, value in sorted(existing_env_vars.items()):
+                        f.write(f'{key}={value}\n')
+
+                logger.info(f"[AgentInitializer] Synced API keys from config.json to .env")
+            except Exception as e:
+                logger.warning(f"[AgentInitializer] Failed to sync API keys: {e}")
+
+    def _start_daily_flush_timer(self):
+        """Start a background thread that flushes all agents' memory daily at 23:55."""
+        if getattr(self.agent_bridge, '_daily_flush_started', False):
+            return
+        self.agent_bridge._daily_flush_started = True
+
+        import threading
+
+        def _daily_flush_loop():
+            import random
+            last_run_date = None  # Track last successful run date to prevent same-day re-trigger
+            while True:
+                try:
+                    now = datetime.datetime.now()
+                    jitter_min = random.randint(50, 55)
+                    jitter_sec = random.randint(0, 59)
+                    target = now.replace(hour=23, minute=jitter_min, second=jitter_sec, microsecond=0)
+                    # Always schedule for tomorrow if we already ran today, or if target time has passed
+                    if target <= now or (last_run_date == now.date()):
+                        target += datetime.timedelta(days=1)
+                    wait_seconds = (target - now).total_seconds()
+                    logger.info(f"[DailyFlush] Next flush at {target.strftime('%Y-%m-%d %H:%M:%S')} (in {wait_seconds/3600:.1f}h)")
+                    time.sleep(wait_seconds)
+
+                    self._flush_all_agents()
+                    last_run_date = datetime.datetime.now().date()
+                except Exception as e:
+                    logger.warning(f"[DailyFlush] Error in daily flush loop: {e}")
+                    time.sleep(3600)
+
+        t = threading.Thread(target=_daily_flush_loop, daemon=True)
+        t.start()
+
+    def _flush_all_agents(self):
+        """Flush memory for all active agent sessions, then run Deep Dream."""
+        agents = []
+        if self.agent_bridge.default_agent:
+            agents.append(("default", self.agent_bridge.default_agent))
+        for sid, agent in self.agent_bridge.agents.items():
+            agents.append((sid, agent))
+
+        if not agents:
+            return
+
+        # Phase 1: flush daily summaries
+        flushed = 0
+        flush_threads = []
+        dream_candidate = None
+        for label, agent in agents:
+            try:
+                if not agent.memory_manager:
+                    continue
+                with agent.messages_lock:
+                    messages = list(agent.messages)
+                if not messages:
+                    continue
+                result = agent.memory_manager.flush_manager.create_daily_summary(messages)
+                if result:
+                    flushed += 1
+                    t = agent.memory_manager.flush_manager._last_flush_thread
+                    if t:
+                        flush_threads.append(t)
+                if dream_candidate is None:
+                    dream_candidate = agent.memory_manager.flush_manager
+            except Exception as e:
+                logger.warning(f"[DailyFlush] Failed for session {label}: {e}")
+
+        if flushed:
+            logger.info(f"[DailyFlush] Flushed {flushed}/{len(agents)} agent session(s)")
+
+        # Wait for all flush threads to finish before dreaming
+        for t in flush_threads:
+            t.join(timeout=60)
+
+        # Phase 2: Deep Dream — distill daily memories → MEMORY.md + dream diary
+        if dream_candidate:
+            try:
+                result = dream_candidate.deep_dream()
+                if result:
+                    logger.info("[DeepDream] Memory distillation completed successfully")
+            except Exception as e:
+                logger.warning(f"[DeepDream] Failed: {e}")
diff --git a/bridge/bridge.py b/bridge/bridge.py
new file mode 100644
index 0000000..6eeb088
--- /dev/null
+++ b/bridge/bridge.py
@@ -0,0 +1,197 @@
+from models.bot_factory import create_bot
+from bridge.context import Context
+from bridge.reply import Reply
+from common import const
+from common.log import logger
+from common.singleton import singleton
+from config import conf
+from translate.factory import create_translator
+from voice.factory import create_voice
+
+
+@singleton
+class Bridge(object):
+    def __init__(self):
+        self.btype = {
+            "chat": const.OPENAI,
+            # Empty `voice_to_text` (the default in new configs) triggers
+            # the auto-pick below — see _auto_pick_voice_to_text for order.
+            "voice_to_text": conf().get("voice_to_text") or self._auto_pick_voice_to_text(),
+            "text_to_voice": conf().get("text_to_voice", "google"),
+            "translate": conf().get("translate", "baidu"),
+        }
+        # 这边取配置的模型
+        bot_type = conf().get("bot_type")
+        if bot_type:
+            self.btype["chat"] = bot_type
+        else:
+            model_type = conf().get("model") or const.GPT_41_MINI
+            
+            # Ensure model_type is string to prevent AttributeError when using startswith()
+            # This handles cases where numeric model names (e.g., "1") are parsed as integers from YAML
+            if not isinstance(model_type, str):
+                logger.warning(f"[Bridge] model_type is not a string: {model_type} (type: {type(model_type).__name__}), converting to string")
+                model_type = str(model_type)
+            
+            if model_type in ["text-davinci-003"]:
+                self.btype["chat"] = const.OPEN_AI
+            if conf().get("use_azure_chatgpt", False):
+                self.btype["chat"] = const.CHATGPTONAZURE
+            if model_type in ["wenxin", "wenxin-4"]:
+                self.btype["chat"] = const.BAIDU
+            if model_type in ["xunfei"]:
+                self.btype["chat"] = const.XUNFEI
+            if model_type in [const.QWEN, const.QWEN_TURBO, const.QWEN_PLUS, const.QWEN_MAX]:
+                self.btype["chat"] = const.QWEN_DASHSCOPE
+            if model_type and (model_type.startswith("qwen") or model_type.startswith("qwq") or model_type.startswith("qvq")):
+                self.btype["chat"] = const.QWEN_DASHSCOPE
+            if model_type and model_type.startswith("gemini"):
+                self.btype["chat"] = const.GEMINI
+            if model_type and model_type.startswith("glm"):
+                self.btype["chat"] = const.ZHIPU_AI
+            if model_type and model_type.startswith("claude"):
+                self.btype["chat"] = const.CLAUDEAPI
+
+            if model_type in [const.MOONSHOT, "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k"]:
+                self.btype["chat"] = const.MOONSHOT
+            if model_type and model_type.startswith("kimi"):
+                self.btype["chat"] = const.MOONSHOT
+
+            if model_type and model_type.startswith("doubao"):
+                self.btype["chat"] = const.DOUBAO
+
+            if model_type and model_type.startswith("deepseek"):
+                self.btype["chat"] = const.DEEPSEEK
+
+            # 小米 MiMo 系列模型，全部以 mimo- 开头
+            if model_type and model_type.startswith("mimo-"):
+                self.btype["chat"] = const.MIMO
+
+            if model_type and isinstance(model_type, str):
+                lowered_model_type = model_type.lower()
+                if lowered_model_type == const.QIANFAN or lowered_model_type.startswith("ernie"):
+                    self.btype["chat"] = const.QIANFAN
+
+            if model_type in [const.MODELSCOPE]:
+                self.btype["chat"] = const.MODELSCOPE
+            
+            # MiniMax models
+            if model_type and (model_type in ["abab6.5-chat", "abab6.5"] or model_type.lower().startswith("minimax")):
+                self.btype["chat"] = const.MiniMax
+
+            if conf().get("use_linkai") and conf().get("linkai_api_key"):
+                self.btype["chat"] = const.LINKAI
+                if not conf().get("voice_to_text") or conf().get("voice_to_text") in ["openai"]:
+                    self.btype["voice_to_text"] = const.LINKAI
+                if not conf().get("text_to_voice") or conf().get("text_to_voice") in ["openai", const.TTS_1, const.TTS_1_HD]:
+                    self.btype["text_to_voice"] = const.LINKAI
+
+        self.bots = {}
+        self.chat_bots = {}
+        self._agent_bridge = None
+
+    def refresh_voice(self):
+        """Re-read voice_to_text / text_to_voice from config and drop the
+        cached voice bots so the next call picks up the new provider.
+        Used by the web console after the user edits voice settings.
+        Does NOT touch the agent_bridge / agent state.
+        """
+        new_v2t = conf().get("voice_to_text") or self._auto_pick_voice_to_text()
+        new_t2v = conf().get("text_to_voice", "google")
+        if conf().get("use_linkai") and conf().get("linkai_api_key"):
+            if not conf().get("voice_to_text") or conf().get("voice_to_text") in ["openai"]:
+                new_v2t = const.LINKAI
+            if not conf().get("text_to_voice") or conf().get("text_to_voice") in ["openai", const.TTS_1, const.TTS_1_HD]:
+                new_t2v = const.LINKAI
+        self.btype["voice_to_text"] = new_v2t
+        self.btype["text_to_voice"] = new_t2v
+        self.bots.pop("voice_to_text", None)
+        self.bots.pop("text_to_voice", None)
+        logger.info(f"[Bridge] voice refreshed: voice_to_text={new_v2t}, text_to_voice={new_t2v}")
+
+    @staticmethod
+    def _auto_pick_voice_to_text() -> str:
+        """Pick an ASR provider by configured api keys when voice_to_text is
+        unset. Order matches the web console: openai → dashscope → zhipu →
+        linkai. Falls back to 'openai' when nothing is configured so the
+        original "missing key" error is preserved.
+        """
+        def has(k: str) -> bool:
+            v = (conf().get(k) or "").strip()
+            return v != "" and v not in ("YOUR API KEY", "YOUR_API_KEY")
+
+        for key, provider in (
+            ("open_ai_api_key", "openai"),
+            ("dashscope_api_key", "dashscope"),
+            ("zhipu_ai_api_key", "zhipu"),
+            ("linkai_api_key", "linkai"),
+        ):
+            if has(key):
+                return provider
+        return "openai"
+
+    # 模型对应的接口
+    def get_bot(self, typename):
+        if self.bots.get(typename) is None:
+            logger.info("create bot {} for {}".format(self.btype[typename], typename))
+            if typename == "text_to_voice":
+                self.bots[typename] = create_voice(self.btype[typename])
+            elif typename == "voice_to_text":
+                self.bots[typename] = create_voice(self.btype[typename])
+            elif typename == "chat":
+                self.bots[typename] = create_bot(self.btype[typename])
+            elif typename == "translate":
+                self.bots[typename] = create_translator(self.btype[typename])
+        return self.bots[typename]
+
+    def get_bot_type(self, typename):
+        return self.btype[typename]
+
+    def fetch_reply_content(self, query, context: Context) -> Reply:
+        return self.get_bot("chat").reply(query, context)
+
+    def fetch_voice_to_text(self, voiceFile) -> Reply:
+        return self.get_bot("voice_to_text").voiceToText(voiceFile)
+
+    def fetch_text_to_voice(self, text) -> Reply:
+        return self.get_bot("text_to_voice").textToVoice(text)
+
+    def fetch_translate(self, text, from_lang="", to_lang="en") -> Reply:
+        return self.get_bot("translate").translate(text, from_lang, to_lang)
+
+    def find_chat_bot(self, bot_type: str):
+        if self.chat_bots.get(bot_type) is None:
+            self.chat_bots[bot_type] = create_bot(bot_type)
+        return self.chat_bots.get(bot_type)
+
+    def reset_bot(self):
+        """
+        重置bot路由
+        """
+        self.__init__()
+
+    def get_agent_bridge(self):
+        """
+        Get agent bridge for agent-based conversations
+        """
+        if self._agent_bridge is None:
+            from bridge.agent_bridge import AgentBridge
+            self._agent_bridge = AgentBridge(self)
+        return self._agent_bridge
+
+    def fetch_agent_reply(self, query: str, context: Context = None,
+                          on_event=None, clear_history: bool = False) -> Reply:
+        """
+        Use super agent to handle the query
+
+        Args:
+            query: User query
+            context: Context object
+            on_event: Event callback for streaming
+            clear_history: Whether to clear conversation history
+
+        Returns:
+            Reply object
+        """
+        agent_bridge = self.get_agent_bridge()
+        return agent_bridge.agent_reply(query, context, on_event, clear_history)
diff --git a/bridge/context.py b/bridge/context.py
new file mode 100644
index 0000000..04d6320
--- /dev/null
+++ b/bridge/context.py
@@ -0,0 +1,71 @@
+# encoding:utf-8
+
+from enum import Enum
+
+
+class ContextType(Enum):
+    TEXT = 1  # 文本消息
+    VOICE = 2  # 音频消息
+    IMAGE = 3  # 图片消息
+    FILE = 4  # 文件信息
+    VIDEO = 5  # 视频信息
+    SHARING = 6  # 分享信息
+
+    IMAGE_CREATE = 10  # 创建图片命令
+    ACCEPT_FRIEND = 19 # 同意好友请求
+    JOIN_GROUP = 20  # 加入群聊
+    PATPAT = 21  # 拍了拍
+    FUNCTION = 22  # 函数调用
+    EXIT_GROUP = 23 #退出
+
+
+    def __str__(self):
+        return self.name
+
+
+class Context:
+    def __init__(self, type: ContextType = None, content=None, kwargs=dict()):
+        self.type = type
+        self.content = content
+        self.kwargs = kwargs
+
+    def __contains__(self, key):
+        if key == "type":
+            return self.type is not None
+        elif key == "content":
+            return self.content is not None
+        else:
+            return key in self.kwargs
+
+    def __getitem__(self, key):
+        if key == "type":
+            return self.type
+        elif key == "content":
+            return self.content
+        else:
+            return self.kwargs[key]
+
+    def get(self, key, default=None):
+        try:
+            return self[key]
+        except KeyError:
+            return default
+
+    def __setitem__(self, key, value):
+        if key == "type":
+            self.type = value
+        elif key == "content":
+            self.content = value
+        else:
+            self.kwargs[key] = value
+
+    def __delitem__(self, key):
+        if key == "type":
+            self.type = None
+        elif key == "content":
+            self.content = None
+        else:
+            del self.kwargs[key]
+
+    def __str__(self):
+        return "Context(type={}, content={}, kwargs={})".format(self.type, self.content, self.kwargs)
diff --git a/bridge/reply.py b/bridge/reply.py
new file mode 100644
index 0000000..f2293bd
--- /dev/null
+++ b/bridge/reply.py
@@ -0,0 +1,31 @@
+# encoding:utf-8
+
+from enum import Enum
+
+
+class ReplyType(Enum):
+    TEXT = 1  # 文本
+    VOICE = 2  # 音频文件
+    IMAGE = 3  # 图片文件
+    IMAGE_URL = 4  # 图片URL
+    VIDEO_URL = 5  # 视频URL
+    FILE = 6  # 文件
+    CARD = 7  # 微信名片，仅支持ntchat
+    INVITE_ROOM = 8  # 邀请好友进群
+    INFO = 9
+    ERROR = 10
+    TEXT_ = 11  # 强制文本
+    VIDEO = 12
+    MINIAPP = 13  # 小程序
+
+    def __str__(self):
+        return self.name
+
+
+class Reply:
+    def __init__(self, type: ReplyType = None, content=None):
+        self.type = type
+        self.content = content
+
+    def __str__(self):
+        return "Reply(type={}, content={})".format(self.type, self.content)
diff --git a/channel/channel.py b/channel/channel.py
new file mode 100644
index 0000000..cd46c56
--- /dev/null
+++ b/channel/channel.py
@@ -0,0 +1,108 @@
+"""
+Message sending channel abstract class
+"""
+
+from bridge.bridge import Bridge
+from bridge.context import Context
+from bridge.reply import *
+from common.log import logger
+from config import conf
+
+
+class Channel(object):
+    channel_type = ""
+    NOT_SUPPORT_REPLYTYPE = [ReplyType.VOICE, ReplyType.IMAGE]
+
+    def __init__(self):
+        import threading
+        self._startup_event = threading.Event()
+        self._startup_error = None
+        self.cloud_mode = False  # set to True by ChannelManager when running with cloud client
+
+    def startup(self):
+        """
+        init channel
+        """
+        raise NotImplementedError
+
+    def report_startup_success(self):
+        self._startup_error = None
+        self._startup_event.set()
+
+    def report_startup_error(self, error: str):
+        self._startup_error = error
+        self._startup_event.set()
+
+    def wait_startup(self, timeout: float = 3) -> (bool, str):
+        """
+        Wait for channel startup result.
+        Returns (success: bool, error_msg: str).
+        """
+        ready = self._startup_event.wait(timeout=timeout)
+        if not ready:
+            return True, ""
+        if self._startup_error:
+            return False, self._startup_error
+        return True, ""
+
+    def stop(self):
+        """
+        stop channel gracefully, called before restart
+        """
+        pass
+
+    def handle_text(self, msg):
+        """
+        process received msg
+        :param msg: message object
+        """
+        raise NotImplementedError
+
+    # 统一的发送函数，每个Channel自行实现，根据reply的type字段发送不同类型的消息
+    def send(self, reply: Reply, context: Context):
+        """
+        send message to user
+        :param msg: message content
+        :param receiver: receiver channel account
+        :return:
+        """
+        raise NotImplementedError
+
+    def build_reply_content(self, query, context: Context = None) -> Reply:
+        """
+        Build reply content, using agent if enabled in config
+        """
+        # Check if agent mode is enabled
+        use_agent = conf().get("agent", True)
+
+        if use_agent:
+            try:
+                logger.info("[Channel] Using agent mode")
+
+                # Add channel_type to context if not present
+                if context and "channel_type" not in context:
+                    context["channel_type"] = self.channel_type
+
+                # Read on_event callback injected by the channel (e.g. web SSE)
+                on_event = context.get("on_event") if context else None
+
+                # Use agent bridge to handle the query
+                return Bridge().fetch_agent_reply(
+                    query=query,
+                    context=context,
+                    on_event=on_event,
+                    clear_history=False
+                )
+            except Exception as e:
+                logger.error(f"[Channel] Agent mode failed, fallback to normal mode: {e}")
+                # Fallback to normal mode if agent fails
+                return Bridge().fetch_reply_content(query, context)
+        else:
+            # Normal mode
+            return Bridge().fetch_reply_content(query, context)
+
+    def build_voice_to_text(self, voice_file) -> Reply:
+        return Bridge().fetch_voice_to_text(voice_file)
+
+    def build_text_to_voice(self, text) -> Reply:
+        return Bridge().fetch_text_to_voice(text)
diff --git a/channel/channel_factory.py b/channel/channel_factory.py
new file mode 100644
index 0000000..0b9c969
--- /dev/null
+++ b/channel/channel_factory.py
@@ -0,0 +1,61 @@
+"""
+channel factory
+"""
+from common import const
+from .channel import Channel
+
+
+def create_channel(channel_type) -> Channel:
+    """
+    create a channel instance
+    :param channel_type: channel type code
+    :return: channel instance
+    """
+    ch = Channel()
+    if channel_type == "terminal":
+        from channel.terminal.terminal_channel import TerminalChannel
+        ch = TerminalChannel()
+    elif channel_type == 'web':
+        from channel.web.web_channel import WebChannel
+        ch = WebChannel()
+    elif channel_type == "wechatmp":
+        from channel.wechatmp.wechatmp_channel import WechatMPChannel
+        ch = WechatMPChannel(passive_reply=True)
+    elif channel_type == "wechatmp_service":
+        from channel.wechatmp.wechatmp_channel import WechatMPChannel
+        ch = WechatMPChannel(passive_reply=False)
+    elif channel_type == "wechatcom_app":
+        from channel.wechatcom.wechatcomapp_channel import WechatComAppChannel
+        ch = WechatComAppChannel()
+    elif channel_type == const.WECHAT_KF:
+        from channel.wechat_kf.wechat_kf_channel import WechatKfChannel
+        ch = WechatKfChannel()
+    elif channel_type == const.FEISHU:
+        from channel.feishu.feishu_channel import FeiShuChanel
+        ch = FeiShuChanel()
+    elif channel_type == const.DINGTALK:
+        from channel.dingtalk.dingtalk_channel import DingTalkChanel
+        ch = DingTalkChanel()
+    elif channel_type == const.WECOM_BOT:
+        from channel.wecom_bot.wecom_bot_channel import WecomBotChannel
+        ch = WecomBotChannel()
+    elif channel_type == const.QQ:
+        from channel.qq.qq_channel import QQChannel
+        ch = QQChannel()
+    elif channel_type == const.TELEGRAM:
+        from channel.telegram.telegram_channel import TelegramChannel
+        ch = TelegramChannel()
+    elif channel_type == const.SLACK:
+        from channel.slack.slack_channel import SlackChannel
+        ch = SlackChannel()
+    elif channel_type == const.DISCORD:
+        from channel.discord.discord_channel import DiscordChannel
+        ch = DiscordChannel()
+    elif channel_type in (const.WEIXIN, "wx"):
+        from channel.weixin.weixin_channel import WeixinChannel
+        ch = WeixinChannel()
+        channel_type = const.WEIXIN
+    else:
+        raise RuntimeError
+    ch.channel_type = channel_type
+    return ch
diff --git a/channel/chat_channel.py b/channel/chat_channel.py
new file mode 100644
index 0000000..e2a65c5
--- /dev/null
+++ b/channel/chat_channel.py
@@ -0,0 +1,558 @@
+import os
+import re
+import threading
+import time
+from asyncio import CancelledError
+from concurrent.futures import Future, ThreadPoolExecutor
+
+from bridge.context import *
+from bridge.reply import *
+from channel.channel import Channel
+from common.dequeue import Dequeue
+from common import memory
+from common.i18n import t as _t
+from plugins import *
+
+try:
+    from voice.audio_convert import any_to_wav
+except Exception as e:
+    pass
+
+handler_pool = ThreadPoolExecutor(max_workers=8)  # 处理消息的线程池
+
+
+# 抽象类, 它包含了与消息通道无关的通用处理逻辑
+class ChatChannel(Channel):
+    name = None  # 登录的用户名
+    user_id = None  # 登录的用户id
+
+    def __init__(self):
+        super().__init__()
+        # Instance-level attributes so each channel subclass has its own
+        # independent session queue and lock. Previously these were class-level,
+        # which caused contexts from one channel (e.g. Feishu) to be consumed
+        # by another channel's consume() thread (e.g. Web), leading to errors
+        # like "No request_id found in context".
+        self.futures = {}
+        self.sessions = {}
+        self.lock = threading.Lock()
+        _thread = threading.Thread(target=self.consume)
+        _thread.setDaemon(True)
+        _thread.start()
+
+    # 根据消息构造context，消息内容相关的触发项写在这里
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+        # context首次传入时，receiver是None，根据类型设置receiver
+        first_in = "receiver" not in context
+        # 群名匹配过程，设置session_id和receiver
+        if first_in:  # context首次传入时，receiver是None，根据类型设置receiver
+            config = conf()
+            cmsg = context["msg"]
+            user_data = conf().get_user_data(cmsg.from_user_id)
+            context["openai_api_key"] = user_data.get("openai_api_key")
+            context["gpt_model"] = user_data.get("gpt_model")
+            if context.get("isgroup", False):
+                group_name = cmsg.other_user_nickname
+                group_id = cmsg.other_user_id
+
+                group_name_white_list = config.get("group_name_white_list", [])
+                group_name_keyword_white_list = config.get("group_name_keyword_white_list", [])
+                if any(
+                    [
+                        group_name in group_name_white_list,
+                        "ALL_GROUP" in group_name_white_list,
+                        check_contain(group_name, group_name_keyword_white_list),
+                    ]
+                ):
+                    # Check global group_shared_session config first
+                    group_shared_session = conf().get("group_shared_session", True)
+                    if group_shared_session:
+                        # All users in the group share the same session
+                        session_id = group_id
+                    else:
+                        # Check group-specific whitelist (legacy behavior)
+                        group_chat_in_one_session = conf().get("group_chat_in_one_session", [])
+                        session_id = cmsg.actual_user_id
+                        if any(
+                            [
+                                group_name in group_chat_in_one_session,
+                                "ALL_GROUP" in group_chat_in_one_session,
+                            ]
+                        ):
+                            session_id = group_id
+                else:
+                    logger.debug(f"No need reply, groupName not in whitelist, group_name={group_name}")
+                    return None
+                context["session_id"] = session_id
+                context["receiver"] = group_id
+            else:
+                context["session_id"] = cmsg.other_user_id
+                context["receiver"] = cmsg.other_user_id
+            e_context = PluginManager().emit_event(EventContext(Event.ON_RECEIVE_MESSAGE, {"channel": self, "context": context}))
+            context = e_context["context"]
+            if e_context.is_pass() or context is None:
+                return context
+            if cmsg.from_user_id == self.user_id and not config.get("trigger_by_self", True):
+                logger.debug("[chat_channel]self message skipped")
+                return None
+
+        # 消息内容匹配过程，并处理content
+        if ctype == ContextType.TEXT:
+            if first_in and "」\n- - - - - - -" in content:  # 初次匹配 过滤引用消息
+                logger.debug(content)
+                logger.debug("[chat_channel]reference query skipped")
+                return None
+
+            nick_name_black_list = conf().get("nick_name_black_list", [])
+            if context.get("isgroup", False):  # 群聊
+                # 校验关键字
+                match_prefix = check_prefix(content, conf().get("group_chat_prefix"))
+                match_contain = check_contain(content, conf().get("group_chat_keyword"))
+                flag = False
+                if context["msg"].to_user_id != context["msg"].actual_user_id:
+                    if match_prefix is not None or match_contain is not None:
+                        flag = True
+                        if match_prefix:
+                            content = content.replace(match_prefix, "", 1).strip()
+                    if context["msg"].is_at:
+                        nick_name = context["msg"].actual_user_nickname
+                        if nick_name and nick_name in nick_name_black_list:
+                            # 黑名单过滤
+                            logger.warning(f"[chat_channel] Nickname {nick_name} in In BlackList, ignore")
+                            return None
+
+                        logger.info("[chat_channel]receive group at")
+                        if not conf().get("group_at_off", False):
+                            flag = True
+                        self.name = self.name if self.name is not None else ""  # 部分渠道self.name可能没有赋值
+                        pattern = f"@{re.escape(self.name)}(\u2005|\u0020)"
+                        subtract_res = re.sub(pattern, r"", content)
+                        if isinstance(context["msg"].at_list, list):
+                            for at in context["msg"].at_list:
+                                pattern = f"@{re.escape(at)}(\u2005|\u0020)"
+                                subtract_res = re.sub(pattern, r"", subtract_res)
+                        if subtract_res == content and context["msg"].self_display_name:
+                            # 前缀移除后没有变化，使用群昵称再次移除
+                            pattern = f"@{re.escape(context['msg'].self_display_name)}(\u2005|\u0020)"
+                            subtract_res = re.sub(pattern, r"", content)
+                        content = subtract_res
+                if not flag:
+                    if context["origin_ctype"] == ContextType.VOICE:
+                        logger.info("[chat_channel]receive group voice, but checkprefix didn't match")
+                    return None
+            else:  # 单聊
+                nick_name = context["msg"].from_user_nickname
+                if nick_name and nick_name in nick_name_black_list:
+                    # 黑名单过滤
+                    logger.warning(f"[chat_channel] Nickname '{nick_name}' in In BlackList, ignore")
+                    return None
+
+                match_prefix = check_prefix(content, conf().get("single_chat_prefix", [""]))
+                if match_prefix is not None:  # 判断如果匹配到自定义前缀，则返回过滤掉前缀+空格后的内容
+                    content = content.replace(match_prefix, "", 1).strip()
+                elif context["origin_ctype"] == ContextType.VOICE:  # 如果源消息是私聊的语音消息，允许不匹配前缀，放宽条件
+                    pass
+                else:
+                    logger.info("[chat_channel]receive single chat msg, but checkprefix didn't match")
+                    return None
+            content = content.strip()
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix",[""]))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = content.strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice") and ReplyType.VOICE not in self.NOT_SUPPORT_REPLYTYPE:
+                context["desire_rtype"] = ReplyType.VOICE
+        elif context.type == ContextType.VOICE:
+            # Voice input replies with voice when either voice_reply_voice
+            # (mirror voice) or the global always_reply_voice toggle is on.
+            if (
+                "desire_rtype" not in context
+                and (conf().get("voice_reply_voice") or conf().get("always_reply_voice"))
+                and ReplyType.VOICE not in self.NOT_SUPPORT_REPLYTYPE
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+        return context
+
+    def _handle(self, context: Context):
+        if context is None or not context.content:
+            return
+        logger.debug("[chat_channel] handling context: {}".format(context))
+        # reply的构建步骤
+        reply = self._generate_reply(context)
+
+        logger.debug("[chat_channel] decorating reply: {}".format(reply))
+
+        # reply的包装步骤
+        if reply and reply.content:
+            reply = self._decorate_reply(context, reply)
+
+            # reply的发送步骤
+            self._send_reply(context, reply)
+
+    def _generate_reply(self, context: Context, reply: Reply = Reply()) -> Reply:
+        e_context = PluginManager().emit_event(
+            EventContext(
+                Event.ON_HANDLE_CONTEXT,
+                {"channel": self, "context": context, "reply": reply},
+            )
+        )
+        reply = e_context["reply"]
+        if not e_context.is_pass():
+            logger.debug("[chat_channel] type={}, content={}".format(context.type, context.content))
+            if context.type == ContextType.TEXT or context.type == ContextType.IMAGE_CREATE:  # 文字和图片消息
+                context["channel"] = e_context["channel"]
+                reply = super().build_reply_content(context.content, context)
+            elif context.type == ContextType.VOICE:  # 语音消息
+                cmsg = context["msg"]
+                cmsg.prepare()
+                file_path = context.content
+                wav_path = os.path.splitext(file_path)[0] + ".wav"
+                try:
+                    any_to_wav(file_path, wav_path)
+                except Exception as e:  # 转换失败，直接使用mp3，对于某些api，mp3也可以识别
+                    logger.warning("[chat_channel]any to wav error, use raw path. " + str(e))
+                    wav_path = file_path
+                # 语音识别
+                reply = super().build_voice_to_text(wav_path)
+                # 删除临时文件
+                try:
+                    os.remove(file_path)
+                    if wav_path != file_path:
+                        os.remove(wav_path)
+                except Exception as e:
+                    pass
+                    # logger.warning("[chat_channel]delete temp file error: " + str(e))
+
+                if reply.type == ReplyType.TEXT:
+                    new_context = self._compose_context(ContextType.TEXT, reply.content, **context.kwargs)
+                    if new_context:
+                        reply = self._generate_reply(new_context)
+                    else:
+                        return
+            elif context.type == ContextType.IMAGE:  # 图片消息，当前仅做下载保存到本地的逻辑
+                memory.USER_IMAGE_CACHE[context["session_id"]] = {
+                    "path": context.content,
+                    "msg": context.get("msg")
+                }
+            elif context.type == ContextType.SHARING:  # 分享信息，当前无默认逻辑
+                pass
+            elif context.type == ContextType.FUNCTION or context.type == ContextType.FILE:  # 文件消息及函数调用等，当前无默认逻辑
+                pass
+            else:
+                logger.warning("[chat_channel] unknown context type: {}".format(context.type))
+                return
+        return reply
+
+    def _decorate_reply(self, context: Context, reply: Reply) -> Reply:
+        if reply and reply.type:
+            e_context = PluginManager().emit_event(
+                EventContext(
+                    Event.ON_DECORATE_REPLY,
+                    {"channel": self, "context": context, "reply": reply},
+                )
+            )
+            reply = e_context["reply"]
+            desire_rtype = context.get("desire_rtype")
+            if not e_context.is_pass() and reply and reply.type:
+                if reply.type in self.NOT_SUPPORT_REPLYTYPE:
+                    logger.error("[chat_channel]reply type not support: " + str(reply.type))
+                    reply.type = ReplyType.ERROR
+                    reply.content = _t("不支持发送的消息类型: ", "Unsupported message type: ") + str(reply.type)
+
+                if reply.type == ReplyType.TEXT:
+                    reply_text = reply.content
+                    if desire_rtype == ReplyType.VOICE and ReplyType.VOICE not in self.NOT_SUPPORT_REPLYTYPE:
+                        # Preserve original text for the "text-then-voice" pattern in _send_reply.
+                        context["voice_reply_text"] = reply.content
+                        reply = super().build_text_to_voice(reply.content)
+                        return self._decorate_reply(context, reply)
+                    if context.get("isgroup", False):
+                        if not context.get("no_need_at", False):
+                            reply_text = "@" + context["msg"].actual_user_nickname + "\n" + reply_text.strip()
+                        reply_text = conf().get("group_chat_reply_prefix", "") + reply_text + conf().get("group_chat_reply_suffix", "")
+                    else:
+                        reply_text = conf().get("single_chat_reply_prefix", "") + reply_text + conf().get("single_chat_reply_suffix", "")
+                    reply.content = reply_text
+                elif reply.type == ReplyType.ERROR or reply.type == ReplyType.INFO:
+                    reply.content = "[" + str(reply.type) + "]\n" + reply.content
+                elif reply.type == ReplyType.IMAGE_URL or reply.type == ReplyType.VOICE or reply.type == ReplyType.IMAGE or reply.type == ReplyType.FILE or reply.type == ReplyType.VIDEO or reply.type == ReplyType.VIDEO_URL:
+                    pass
+                else:
+                    logger.error("[chat_channel] unknown reply type: {}".format(reply.type))
+                    return
+            if desire_rtype and desire_rtype != reply.type and reply.type not in [ReplyType.ERROR, ReplyType.INFO]:
+                logger.warning("[chat_channel] desire_rtype: {}, but reply type: {}".format(context.get("desire_rtype"), reply.type))
+            return reply
+
+    def _send_reply(self, context: Context, reply: Reply):
+        if reply and reply.type:
+            e_context = PluginManager().emit_event(
+                EventContext(
+                    Event.ON_SEND_REPLY,
+                    {"channel": self, "context": context, "reply": reply},
+                )
+            )
+            reply = e_context["reply"]
+            if not e_context.is_pass() and reply and reply.type:
+                logger.debug("[chat_channel] sending reply: {}, context: {}".format(reply, context))
+                
+                # 如果是文本回复，尝试提取并发送图片
+                # Web channel renders images/videos inline via renderMarkdown,
+                # so skip the extract-and-send step to avoid duplicate media.
+                if reply.type == ReplyType.TEXT and context.get("channel_type") != "web":
+                    self._extract_and_send_images(reply, context)
+                elif reply.type == ReplyType.TEXT:
+                    self._send(reply, context)
+                # 如果是图片回复但带有文本内容，先发文本再发图片
+                elif reply.type == ReplyType.IMAGE_URL and hasattr(reply, 'text_content') and reply.text_content:
+                    # 先发送文本
+                    text_reply = Reply(ReplyType.TEXT, reply.text_content)
+                    self._send(text_reply, context)
+                    # 短暂延迟后发送图片
+                    time.sleep(0.3)
+                    self._send(reply, context)
+                # Send text bubble before voice, unless channel already streamed
+                # the text (feishu) or natively renders STT under the voice (wechatcom).
+                elif reply.type == ReplyType.VOICE and context.get("voice_reply_text") \
+                        and not context.get("feishu_streamed") \
+                        and context.get("channel_type") not in ("wechatcom_app",):
+                    text_reply = Reply(ReplyType.TEXT, context.get("voice_reply_text"))
+                    self._send(text_reply, context)
+                    time.sleep(0.3)
+                    self._send(reply, context)
+                else:
+                    self._send(reply, context)
+    
+    def _extract_and_send_images(self, reply: Reply, context: Context):
+        """
+        从文本回复中提取图片/视频URL并单独发送
+        支持格式：[图片: /path/to/image.png], [视频: /path/to/video.mp4], ![](url), <img src="url">
+        最多发送5个媒体文件
+        """
+        content = reply.content
+        media_items = []  # [(url, type), ...]
+        
+        # 正则提取各种格式的媒体URL
+        patterns = [
+            (r'\[图片:\s*([^\]]+)\]', 'image'),   # [图片: /path/to/image.png]
+            (r'\[视频:\s*([^\]]+)\]', 'video'),   # [视频: /path/to/video.mp4]
+            (r'!\[.*?\]\(([^\)]+)\)', 'image'),   # ![alt](url) - 默认图片
+            (r'<img[^>]+src=["\']([^"\']+)["\']', 'image'),  # <img src="url">
+            (r'<video[^>]+src=["\']([^"\']+)["\']', 'video'),  # <video src="url">
+            (r'https?://[^\s]+\.(?:jpg|jpeg|png|gif|webp)', 'image'),  # 直接的图片URL
+            (r'https?://[^\s]+\.(?:mp4|avi|mov|wmv|flv)', 'video'),  # 直接的视频URL
+        ]
+        
+        for pattern, media_type in patterns:
+            matches = re.findall(pattern, content, re.IGNORECASE)
+            for match in matches:
+                media_items.append((match, media_type))
+        
+        # 去重（保持顺序）并限制最多5个
+        seen = set()
+        unique_items = []
+        for url, mtype in media_items:
+            if url not in seen:
+                seen.add(url)
+                unique_items.append((url, mtype))
+        media_items = unique_items[:5]
+        
+        if media_items:
+            logger.info(f"[chat_channel] Extracted {len(media_items)} media item(s) from reply")
+            
+            # Send text first (the frontend will embed video players via renderMarkdown).
+            logger.info(f"[chat_channel] Sending text content before media: {reply.content[:100]}...")
+            self._send(reply, context)
+            logger.info(f"[chat_channel] Text sent, now sending {len(media_items)} media item(s)")
+            
+            for i, (url, media_type) in enumerate(media_items):
+                try:
+                    # Determine whether it is a remote URL or a local file.
+                    if url.startswith(('http://', 'https://')):
+                        if media_type == 'video':
+                            media_reply = Reply(ReplyType.FILE, url)
+                            media_reply.file_name = os.path.basename(url)
+                        else:
+                            media_reply = Reply(ReplyType.IMAGE_URL, url)
+                    elif os.path.exists(url):
+                        if media_type == 'video':
+                            media_reply = Reply(ReplyType.FILE, f"file://{url}")
+                            media_reply.file_name = os.path.basename(url)
+                        else:
+                            media_reply = Reply(ReplyType.IMAGE_URL, f"file://{url}")
+                    else:
+                        logger.warning(f"[chat_channel] Media file not found or invalid URL: {url}")
+                        continue
+                    
+                    if i > 0:
+                        time.sleep(0.5)
+                    self._send(media_reply, context)
+                    logger.info(f"[chat_channel] Sent {media_type} {i+1}/{len(media_items)}: {url[:50]}...")
+                    
+                except Exception as e:
+                    logger.error(f"[chat_channel] Failed to send {media_type} {url}: {e}")
+        else:
+            # 没有媒体文件，正常发送文本
+                self._send(reply, context)
+
+    def _send(self, reply: Reply, context: Context, retry_cnt=0):
+        try:
+            self.send(reply, context)
+        except Exception as e:
+            logger.error("[chat_channel] sendMsg error: {}".format(str(e)))
+            if isinstance(e, NotImplementedError):
+                return
+            logger.exception(e)
+            if retry_cnt < 2:
+                time.sleep(3 + 3 * retry_cnt)
+                self._send(reply, context, retry_cnt + 1)
+
+    def _success_callback(self, session_id, **kwargs):  # 线程正常结束时的回调函数
+        logger.debug("Worker return success, session_id = {}".format(session_id))
+
+    def _fail_callback(self, session_id, exception, **kwargs):  # 线程异常结束时的回调函数
+        logger.exception("Worker return exception: {}".format(exception))
+
+    def _thread_pool_callback(self, session_id, **kwargs):
+        def func(worker: Future):
+            try:
+                worker_exception = worker.exception()
+                if worker_exception:
+                    self._fail_callback(session_id, exception=worker_exception, **kwargs)
+                else:
+                    self._success_callback(session_id, **kwargs)
+            except CancelledError as e:
+                logger.info("Worker cancelled, session_id = {}".format(session_id))
+            except Exception as e:
+                logger.exception("Worker raise exception: {}".format(e))
+            with self.lock:
+                self.sessions[session_id][1].release()
+
+        return func
+
+    # Chat commands that must bypass the per-session serial queue,
+    # otherwise /cancel would queue behind the task it tries to cancel.
+    # Use /cancel (not /stop) to avoid colliding with `cow stop` CLI.
+    _BYPASS_QUEUE_COMMANDS = ("/cancel",)
+
+    def produce(self, context: Context):
+        session_id = context["session_id"]
+
+        # Fast path: /cancel must not enter the queue.
+        if context.type == ContextType.TEXT and context.content:
+            stripped = context.content.strip().lower()
+            if stripped in self._BYPASS_QUEUE_COMMANDS:
+                self._handle_cancel_command(context, session_id)
+                return
+
+        with self.lock:
+            if session_id not in self.sessions:
+                self.sessions[session_id] = [
+                    Dequeue(),
+                    threading.BoundedSemaphore(conf().get("concurrency_in_session", 1)),
+                ]
+            if context.type == ContextType.TEXT and context.content.startswith("#"):
+                self.sessions[session_id][0].putleft(context)  # 优先处理管理命令
+            else:
+                self.sessions[session_id][0].put(context)
+
+    def _handle_cancel_command(self, context: Context, session_id: str) -> None:
+        """Cancel any in-flight agent run for *session_id* and reply inline.
+
+        Runs synchronously on the caller's thread. Reply is sent through
+        _send_reply so plugins (e.g. logging) still observe it.
+        """
+        try:
+            from agent.protocol import get_cancel_registry
+            from bridge.reply import Reply, ReplyType
+
+            cancelled = get_cancel_registry().cancel_session(session_id)
+            text = (
+                _t("🛑 已中止", "🛑 Cancelled")
+                if cancelled > 0
+                else _t("当前没有可中止的任务。", "Nothing to cancel.")
+            )
+            logger.info(
+                f"[chat_channel] /cancel fast-path: session={session_id}, cancelled={cancelled}"
+            )
+            self._send_reply(context, Reply(ReplyType.TEXT, text))
+        except Exception as e:
+            logger.warning(f"[chat_channel] /cancel fast-path failed: {e}")
+
+    # 消费者函数，单独线程，用于从消息队列中取出消息并处理
+    def consume(self):
+        while True:
+            with self.lock:
+                session_ids = list(self.sessions.keys())
+            for session_id in session_ids:
+                with self.lock:
+                    context_queue, semaphore = self.sessions[session_id]
+                if semaphore.acquire(blocking=False):  # 等线程处理完毕才能删除
+                    if not context_queue.empty():
+                        context = context_queue.get()
+                        logger.debug("[chat_channel] consume context: {}".format(context))
+                        future: Future = handler_pool.submit(self._handle, context)
+                        future.add_done_callback(self._thread_pool_callback(session_id, context=context))
+                        with self.lock:
+                            if session_id not in self.futures:
+                                self.futures[session_id] = []
+                            self.futures[session_id].append(future)
+                    elif semaphore._initial_value == semaphore._value + 1:  # 除了当前，没有任务再申请到信号量，说明所有任务都处理完毕
+                        with self.lock:
+                            self.futures[session_id] = [t for t in self.futures[session_id] if not t.done()]
+                            assert len(self.futures[session_id]) == 0, "thread pool error"
+                            del self.sessions[session_id]
+                    else:
+                        semaphore.release()
+            time.sleep(0.2)
+
+    # 取消session_id对应的所有任务，只能取消排队的消息和已提交线程池但未执行的任务
+    def cancel_session(self, session_id):
+        with self.lock:
+            if session_id in self.sessions:
+                # futures[session_id] is only created in consume() when a task is
+                # dispatched, so it may be absent if cancel happens right after
+                # produce() but before the first dispatch. Default to [].
+                for future in self.futures.get(session_id, []):
+                    future.cancel()
+                cnt = self.sessions[session_id][0].qsize()
+                if cnt > 0:
+                    logger.info("Cancel {} messages in session {}".format(cnt, session_id))
+                self.sessions[session_id][0] = Dequeue()
+
+    def cancel_all_session(self):
+        with self.lock:
+            for session_id in self.sessions:
+                for future in self.futures.get(session_id, []):
+                    future.cancel()
+                cnt = self.sessions[session_id][0].qsize()
+                if cnt > 0:
+                    logger.info("Cancel {} messages in session {}".format(cnt, session_id))
+                self.sessions[session_id][0] = Dequeue()
+
+
+def check_prefix(content, prefix_list):
+    if not prefix_list:
+        return None
+    for prefix in prefix_list:
+        if content.startswith(prefix):
+            return prefix
+    return None
+
+
+def check_contain(content, keyword_list):
+    if not keyword_list:
+        return None
+    for ky in keyword_list:
+        if content.find(ky) != -1:
+            return True
+    return None
diff --git a/channel/chat_message.py b/channel/chat_message.py
new file mode 100644
index 0000000..d7ea52d
--- /dev/null
+++ b/channel/chat_message.py
@@ -0,0 +1,87 @@
+"""
+Unified chat message class for different channel implementations.
+
+填好必填项(群聊6个，非群聊8个)，即可接入ChatChannel，并支持插件，参考TerminalChannel
+
+ChatMessage
+msg_id: 消息id (必填)
+create_time: 消息创建时间
+
+ctype: 消息类型 : ContextType (必填)
+content: 消息内容, 如果是声音/图片，这里是文件路径 (必填)
+
+from_user_id: 发送者id (必填)
+from_user_nickname: 发送者昵称
+to_user_id: 接收者id (必填)
+to_user_nickname: 接收者昵称
+
+other_user_id: 对方的id，如果你是发送者，那这个就是接收者id，如果你是接收者，那这个就是发送者id，如果是群消息，那这一直是群id (必填)
+other_user_nickname: 同上
+
+is_group: 是否是群消息 (群聊必填)
+is_at: 是否被at
+
+- (群消息时，一般会存在实际发送者，是群内某个成员的id和昵称，下列项仅在群消息时存在)
+actual_user_id: 实际发送者id (群聊必填)
+actual_user_nickname：实际发送者昵称
+self_display_name: 自身的展示名，设置群昵称时，该字段表示群昵称
+
+_prepare_fn: 准备函数，用于准备消息的内容，比如下载图片等,
+_prepared: 是否已经调用过准备函数
+_rawmsg: 原始消息对象
+
+"""
+
+
+class ChatMessage(object):
+    msg_id = None
+    create_time = None
+
+    ctype = None
+    content = None
+
+    from_user_id = None
+    from_user_nickname = None
+    to_user_id = None
+    to_user_nickname = None
+    other_user_id = None
+    other_user_nickname = None
+    my_msg = False
+    self_display_name = None
+
+    is_group = False
+    is_at = False
+    actual_user_id = None
+    actual_user_nickname = None
+    at_list = None
+
+    _prepare_fn = None
+    _prepared = False
+    _rawmsg = None
+
+    def __init__(self, _rawmsg):
+        self._rawmsg = _rawmsg
+
+    def prepare(self):
+        if self._prepare_fn and not self._prepared:
+            self._prepared = True
+            self._prepare_fn()
+
+    def __str__(self):
+        return "ChatMessage: id={}, create_time={}, ctype={}, content={}, from_user_id={}, from_user_nickname={}, to_user_id={}, to_user_nickname={}, other_user_id={}, other_user_nickname={}, is_group={}, is_at={}, actual_user_id={}, actual_user_nickname={}, at_list={}".format(
+            self.msg_id,
+            self.create_time,
+            self.ctype,
+            self.content,
+            self.from_user_id,
+            self.from_user_nickname,
+            self.to_user_id,
+            self.to_user_nickname,
+            self.other_user_id,
+            self.other_user_nickname,
+            self.is_group,
+            self.is_at,
+            self.actual_user_id,
+            self.actual_user_nickname,
+            self.at_list
+        )
diff --git a/channel/dingtalk/dingtalk_channel.py b/channel/dingtalk/dingtalk_channel.py
new file mode 100644
index 0000000..b1ae86c
--- /dev/null
+++ b/channel/dingtalk/dingtalk_channel.py
@@ -0,0 +1,1014 @@
+"""
+钉钉通道接入
+
+@author huiwen
+@Date 2023/11/28
+"""
+import copy
+import json
+# -*- coding=utf-8 -*-
+import logging
+import os
+import time
+import requests
+
+import dingtalk_stream
+from dingtalk_stream import AckMessage
+from dingtalk_stream.card_replier import AICardReplier
+from dingtalk_stream.card_replier import AICardStatus
+from dingtalk_stream.card_replier import CardReplier
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel
+from common.utils import expand_path
+from channel.dingtalk.dingtalk_message import DingTalkMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from common.time_check import time_checker
+from config import conf
+
+
+class CustomAICardReplier(CardReplier):
+    def __init__(self, dingtalk_client, incoming_message):
+        super(AICardReplier, self).__init__(dingtalk_client, incoming_message)
+
+    def start(
+            self,
+            card_template_id: str,
+            card_data: dict,
+            recipients: list = None,
+            support_forward: bool = True,
+    ) -> str:
+        """
+        AI卡片的创建接口
+        :param support_forward:
+        :param recipients:
+        :param card_template_id:
+        :param card_data:
+        :return:
+        """
+        card_data_with_status = copy.deepcopy(card_data)
+        card_data_with_status["flowStatus"] = AICardStatus.PROCESSING
+        return self.create_and_send_card(
+            card_template_id,
+            card_data_with_status,
+            at_sender=True,
+            at_all=False,
+            recipients=recipients,
+            support_forward=support_forward,
+        )
+
+
+# 对 AICardReplier 进行猴子补丁
+AICardReplier.start = CustomAICardReplier.start
+
+
+def _check(func):
+    def wrapper(self, cmsg: DingTalkMessage):
+        msgId = cmsg.msg_id
+        if msgId in self.receivedMsgs:
+            logger.info("DingTalk message {} already received, ignore".format(msgId))
+            return
+        self.receivedMsgs[msgId] = True
+        create_time = cmsg.create_time  # 消息时间戳
+        if conf().get("hot_reload") == True and int(create_time) < int(time.time()) - 60:  # 跳过1分钟前的历史消息
+            logger.debug("[DingTalk] History message {} skipped".format(msgId))
+            return
+        if cmsg.my_msg and not cmsg.is_group:
+            logger.debug("[DingTalk] My message {} skipped".format(msgId))
+            return
+        return func(self, cmsg)
+
+    return wrapper
+
+
+@singleton
+class DingTalkChanel(ChatChannel, dingtalk_stream.ChatbotHandler):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    dingtalk_client_id = conf().get('dingtalk_client_id')
+    dingtalk_client_secret = conf().get('dingtalk_client_secret')
+
+    def setup_logger(self):
+        # Suppress verbose logs from dingtalk_stream SDK
+        logging.getLogger("dingtalk_stream").setLevel(logging.WARNING)
+        return logging.getLogger("DingTalk")
+
+    def __init__(self):
+        super().__init__()
+        super(dingtalk_stream.ChatbotHandler, self).__init__()
+        self.logger = self.setup_logger()
+        # 历史消息id暂存，用于幂等控制
+        self.receivedMsgs = ExpiredDict(conf().get("expires_in_seconds", 3600))
+        self._stream_client = None
+        self._running = False
+        self._event_loop = None
+        logger.debug("[DingTalk] client_id={}, client_secret={} ".format(
+            self.dingtalk_client_id, self.dingtalk_client_secret))
+        # 无需群校验和前缀
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        # 单聊无需前缀
+        conf()["single_chat_prefix"] = [""]
+        # Access token cache
+        self._access_token = None
+        self._access_token_expires_at = 0
+        # Robot code cache (extracted from incoming messages)
+        self._robot_code = None
+
+    def _open_connection(self, client):
+        """
+        Open a DingTalk stream connection directly, bypassing SDK's internal error-swallowing.
+        Returns (connection_dict, error_str). On success error_str is empty; on failure
+        connection_dict is None and error_str contains a human-readable message.
+        """
+        try:
+            resp = requests.post(
+                "https://api.dingtalk.com/v1.0/gateway/connections/open",
+                headers={"Content-Type": "application/json", "Accept": "application/json"},
+                json={
+                    "clientId": client.credential.client_id,
+                    "clientSecret": client.credential.client_secret,
+                    "subscriptions": [{"type": "CALLBACK",
+                                       "topic": dingtalk_stream.chatbot.ChatbotMessage.TOPIC}],
+                    "ua": "dingtalk-sdk-python/cow",
+                    "localIp": "",
+                },
+                timeout=10,
+            )
+            body = resp.json()
+            if not resp.ok:
+                code = body.get("code", resp.status_code)
+                message = body.get("message", resp.reason)
+                return None, f"open connection failed: [{code}] {message}"
+            return body, ""
+        except Exception as e:
+            return None, f"open connection failed: {e}"
+
+    def startup(self):
+        import asyncio
+        self.dingtalk_client_id = conf().get('dingtalk_client_id')
+        self.dingtalk_client_secret = conf().get('dingtalk_client_secret')
+        self._running = True
+        credential = dingtalk_stream.Credential(self.dingtalk_client_id, self.dingtalk_client_secret)
+        client = dingtalk_stream.DingTalkStreamClient(credential)
+        self._stream_client = client
+        client.register_callback_handler(dingtalk_stream.chatbot.ChatbotMessage.TOPIC, self)
+        logger.info("[DingTalk] ✅ Stream client initialized, ready to receive messages")
+
+        # Run the connection loop ourselves instead of delegating to client.start(),
+        # so we can get detailed error messages and respond to stop() quickly.
+        import urllib.parse as _urlparse
+        import websockets as _ws
+        import json as _json
+        client.pre_start()
+        _first_connect = True
+        while self._running:
+            # Open connection using our own request so we get detailed error info.
+            connection, err_msg = self._open_connection(client)
+
+            if connection is None:
+                if _first_connect:
+                    logger.warning(f"[DingTalk] {err_msg}")
+                    self.report_startup_error(err_msg)
+                    _first_connect = False
+                else:
+                    logger.warning(f"[DingTalk] {err_msg}, retrying in 10s...")
+
+                # Interruptible sleep: checks _running every 100ms.
+                for _ in range(100):
+                    if not self._running:
+                        break
+                    time.sleep(0.1)
+                continue
+
+            if _first_connect:
+                logger.info("[DingTalk] ✅ Connected to DingTalk stream")
+                self.report_startup_success()
+                _first_connect = False
+            else:
+                logger.info("[DingTalk] Reconnected to DingTalk stream")
+
+            # Run the WebSocket session in an asyncio loop.
+            uri = '%s?ticket=%s' % (
+                connection['endpoint'],
+                _urlparse.quote_plus(connection['ticket'])
+            )
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+            self._event_loop = loop
+            try:
+                async def _session():
+                    async with _ws.connect(uri) as websocket:
+                        client.websocket = websocket
+                        async for raw_message in websocket:
+                            json_message = _json.loads(raw_message)
+                            result = await client.route_message(json_message)
+                            if result == dingtalk_stream.DingTalkStreamClient.TAG_DISCONNECT:
+                                break
+
+                loop.run_until_complete(_session())
+            except (KeyboardInterrupt, SystemExit):
+                logger.info("[DingTalk] Session loop received stop signal, exiting")
+                break
+            except Exception as e:
+                if not self._running:
+                    break
+                logger.warning(f"[DingTalk] Stream session error: {e}, reconnecting in 3s...")
+                for _ in range(30):
+                    if not self._running:
+                        break
+                    time.sleep(0.1)
+            finally:
+                self._event_loop = None
+                try:
+                    loop.close()
+                except Exception:
+                    pass
+
+        logger.info("[DingTalk] Startup loop exited")
+
+    def stop(self):
+        logger.info("[DingTalk] stop() called, setting _running=False")
+        self._running = False
+        loop = self._event_loop
+        if loop and not loop.is_closed():
+            try:
+                loop.call_soon_threadsafe(loop.stop)
+                logger.info("[DingTalk] Sent stop signal to event loop")
+            except Exception as e:
+                logger.warning(f"[DingTalk] Error stopping event loop: {e}")
+        self._stream_client = None
+        logger.info("[DingTalk] stop() completed")
+    
+    def get_access_token(self):
+        """
+        获取企业内部应用的 access_token
+        文档: https://open.dingtalk.com/document/orgapp/obtain-orgapp-token
+        """
+        current_time = time.time()
+        
+        # 如果 token 还没过期，直接返回缓存的 token
+        if self._access_token and current_time < self._access_token_expires_at:
+            return self._access_token
+        
+        # 获取新的 access_token
+        url = "https://api.dingtalk.com/v1.0/oauth2/accessToken"
+        headers = {"Content-Type": "application/json"}
+        data = {
+            "appKey": self.dingtalk_client_id,
+            "appSecret": self.dingtalk_client_secret
+        }
+        
+        try:
+            response = requests.post(url, headers=headers, json=data, timeout=10)
+            result = response.json()
+            
+            if response.status_code == 200 and "accessToken" in result:
+                self._access_token = result["accessToken"]
+                # Token 有效期为 2 小时，提前 5 分钟刷新
+                self._access_token_expires_at = current_time + result.get("expireIn", 7200) - 300
+                logger.info("[DingTalk] Access token refreshed successfully")
+                return self._access_token
+            else:
+                logger.error(f"[DingTalk] Failed to get access token: {result}")
+                return None
+        except Exception as e:
+            logger.error(f"[DingTalk] Error getting access token: {e}")
+            return None
+    
+    def send_single_message(self, user_id: str, content: str, robot_code: str) -> bool:
+        """
+        Send message to single user (private chat)
+        API: https://open.dingtalk.com/document/orgapp/chatbots-send-one-on-one-chat-messages-in-batches
+        """
+        access_token = self.get_access_token()
+        if not access_token:
+            logger.error("[DingTalk] Failed to send single message: Access token not available.")
+            return False
+
+        if not robot_code:
+            logger.error("[DingTalk] Cannot send single message: robot_code is required")
+            return False
+
+        url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+        headers = {
+            "x-acs-dingtalk-access-token": access_token,
+            "Content-Type": "application/json"
+        }
+        data = {
+            "msgParam": json.dumps({"content": content}),
+            "msgKey": "sampleText",
+            "userIds": [user_id],
+            "robotCode": robot_code
+        }
+
+        logger.info(f"[DingTalk] Sending single message to user {user_id} with robot_code {robot_code}")
+        try:
+            response = requests.post(url, headers=headers, json=data, timeout=10)
+            result = response.json()
+            
+            if response.status_code == 200 and result.get("processQueryKey"):
+                logger.info(f"[DingTalk] Single message sent successfully to {user_id}")
+                return True
+            else:
+                logger.error(f"[DingTalk] Failed to send single message: {result}")
+                return False
+        except Exception as e:
+            logger.error(f"[DingTalk] Error sending single message: {e}")
+            return False
+    
+    def send_group_message(self, conversation_id: str, content: str, robot_code: str = None):
+        """
+        主动发送群消息
+        文档: https://open.dingtalk.com/document/orgapp/the-robot-sends-a-group-message
+        
+        Args:
+            conversation_id: 会话ID (openConversationId)
+            content: 消息内容
+            robot_code: 机器人编码，默认使用 dingtalk_client_id
+        """
+        access_token = self.get_access_token()
+        if not access_token:
+            logger.error("[DingTalk] Cannot send group message: no access token")
+            return False
+        
+        # Validate robot_code
+        if not robot_code:
+            logger.error("[DingTalk] Cannot send group message: robot_code is required")
+            return False
+        
+        url = "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
+        headers = {
+            "x-acs-dingtalk-access-token": access_token,
+            "Content-Type": "application/json"
+        }
+        data = {
+            "msgParam": json.dumps({"content": content}),
+            "msgKey": "sampleText",
+            "openConversationId": conversation_id,
+            "robotCode": robot_code
+        }
+        
+        try:
+            response = requests.post(url, headers=headers, json=data, timeout=10)
+            result = response.json()
+            
+            if response.status_code == 200:
+                logger.info(f"[DingTalk] Group message sent successfully to {conversation_id}")
+                return True
+            else:
+                logger.error(f"[DingTalk] Failed to send group message: {result}")
+                return False
+        except Exception as e:
+            logger.error(f"[DingTalk] Error sending group message: {e}")
+            return False
+    
+    def upload_media(self, file_path: str, media_type: str = "image") -> str:
+        """
+        上传媒体文件到钉钉
+        
+        Args:
+            file_path: 本地文件路径或URL
+            media_type: 媒体类型 (image, video, voice, file)
+        
+        Returns:
+            media_id，如果上传失败返回 None
+        """
+        access_token = self.get_access_token()
+        if not access_token:
+            logger.error("[DingTalk] Cannot upload media: no access token")
+            return None
+        
+        # 处理 file:// URL
+        if file_path.startswith("file://"):
+            file_path = file_path[7:]
+        
+        # 如果是 HTTP URL，先下载
+        if file_path.startswith("http://") or file_path.startswith("https://"):
+            try:
+                import uuid
+                response = requests.get(file_path, timeout=(5, 60))
+                if response.status_code != 200:
+                    logger.error(f"[DingTalk] Failed to download file from URL: {file_path}")
+                    return None
+                
+                # 保存到临时文件
+                file_name = os.path.basename(file_path) or f"media_{uuid.uuid4()}"
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                tmp_dir = os.path.join(workspace_root, "tmp")
+                os.makedirs(tmp_dir, exist_ok=True)
+                temp_file = os.path.join(tmp_dir, file_name)
+                
+                with open(temp_file, "wb") as f:
+                    f.write(response.content)
+                
+                file_path = temp_file
+                logger.info(f"[DingTalk] Downloaded file to {file_path}")
+            except Exception as e:
+                logger.error(f"[DingTalk] Error downloading file: {e}")
+                return None
+        
+        if not os.path.exists(file_path):
+            logger.error(f"[DingTalk] File not found: {file_path}")
+            return None
+        
+        # 上传到钉钉
+        # 钉钉上传媒体文件 API: https://open.dingtalk.com/document/orgapp/upload-media-files
+        url = "https://oapi.dingtalk.com/media/upload"
+        params = {
+            "access_token": access_token,
+            "type": media_type
+        }
+        
+        try:
+            with open(file_path, "rb") as f:
+                files = {"media": (os.path.basename(file_path), f)}
+                response = requests.post(url, params=params, files=files, timeout=(5, 60))
+                result = response.json()
+                
+                if result.get("errcode") == 0:
+                    media_id = result.get("media_id")
+                    logger.info(f"[DingTalk] Media uploaded successfully, media_id={media_id}")
+                    return media_id
+                else:
+                    logger.error(f"[DingTalk] Failed to upload media: {result}")
+                    return None
+        except Exception as e:
+            logger.error(f"[DingTalk] Error uploading media: {e}")
+            return None
+    
+    def send_image_with_media_id(self, access_token: str, media_id: str, incoming_message, is_group: bool) -> bool:
+        """
+        发送图片消息（使用 media_id）
+        
+        Args:
+            access_token: 访问令牌
+            media_id: 媒体ID
+            incoming_message: 钉钉消息对象
+            is_group: 是否为群聊
+        
+        Returns:
+            是否发送成功
+        """
+        headers = {
+            "x-acs-dingtalk-access-token": access_token,
+            'Content-Type': 'application/json'
+        }
+        
+        msg_param = {
+            "photoURL": media_id  # 钉钉图片消息使用 photoURL 字段
+        }
+        
+        body = {
+            "robotCode": incoming_message.robot_code,
+            "msgKey": "sampleImageMsg",
+            "msgParam": json.dumps(msg_param),
+        }
+        
+        if is_group:
+            # 群聊
+            url = "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
+            body["openConversationId"] = incoming_message.conversation_id
+        else:
+            # 单聊
+            url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+            body["userIds"] = [incoming_message.sender_staff_id]
+        
+        try:
+            response = requests.post(url=url, headers=headers, json=body, timeout=10)
+            result = response.json()
+            
+            logger.info(f"[DingTalk] Image send result: {response.text}")
+            
+            if response.status_code == 200:
+                return True
+            else:
+                logger.error(f"[DingTalk] Send image error: {response.text}")
+                return False
+        except Exception as e:
+            logger.error(f"[DingTalk] Send image exception: {e}")
+            return False
+
+    def send_image_message(self, receiver: str, media_id: str, is_group: bool, robot_code: str) -> bool:
+        """
+        发送图片消息
+        
+        Args:
+            receiver: 接收者ID (user_id 或 conversation_id)
+            media_id: 媒体ID
+            is_group: 是否为群聊
+            robot_code: 机器人编码
+        
+        Returns:
+            是否发送成功
+        """
+        access_token = self.get_access_token()
+        if not access_token:
+            logger.error("[DingTalk] Cannot send image: no access token")
+            return False
+        
+        if not robot_code:
+            logger.error("[DingTalk] Cannot send image: robot_code is required")
+            return False
+        
+        if is_group:
+            # 发送群聊图片
+            url = "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
+            headers = {
+                "x-acs-dingtalk-access-token": access_token,
+                "Content-Type": "application/json"
+            }
+            data = {
+                "msgParam": json.dumps({"mediaId": media_id}),
+                "msgKey": "sampleImageMsg",
+                "openConversationId": receiver,
+                "robotCode": robot_code
+            }
+        else:
+            # 发送单聊图片
+            url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+            headers = {
+                "x-acs-dingtalk-access-token": access_token,
+                "Content-Type": "application/json"
+            }
+            data = {
+                "msgParam": json.dumps({"mediaId": media_id}),
+                "msgKey": "sampleImageMsg",
+                "userIds": [receiver],
+                "robotCode": robot_code
+            }
+        
+        try:
+            response = requests.post(url, headers=headers, json=data, timeout=10)
+            result = response.json()
+            
+            if response.status_code == 200:
+                logger.info(f"[DingTalk] Image message sent successfully")
+                return True
+            else:
+                logger.error(f"[DingTalk] Failed to send image message: {result}")
+                return False
+        except Exception as e:
+            logger.error(f"[DingTalk] Error sending image message: {e}")
+            return False
+    
+    def get_image_download_url(self, download_code: str) -> str:
+        """
+        获取图片下载地址
+        返回一个特殊的 URL 格式：dingtalk://download/{robot_code}:{download_code}
+        后续会在 download_image_file 中使用新版 API 下载
+        """
+        # 获取 robot_code
+        if not hasattr(self, '_robot_code_cache'):
+            self._robot_code_cache = None
+        
+        robot_code = self._robot_code_cache
+        
+        if not robot_code:
+            logger.error("[DingTalk] robot_code not available for image download")
+            return None
+        
+        # 返回一个特殊的 URL，包含 robot_code 和 download_code
+        logger.info(f"[DingTalk] Successfully got image download URL for code: {download_code}")
+        return f"dingtalk://download/{robot_code}:{download_code}"
+
+    async def process(self, callback: dingtalk_stream.CallbackMessage):
+        try:
+            incoming_message = dingtalk_stream.ChatbotMessage.from_dict(callback.data)
+
+            # 缓存 robot_code，用于后续图片下载
+            if hasattr(incoming_message, 'robot_code'):
+                self._robot_code_cache = incoming_message.robot_code
+
+            # Filter out stale messages from before channel startup (offline backlog)
+            create_at = getattr(incoming_message, 'create_at', None)
+            if create_at:
+                msg_age_s = time.time() - int(create_at) / 1000
+                if msg_age_s > 60:
+                    logger.warning(f"[DingTalk] stale msg filtered (age={msg_age_s:.0f}s), "
+                                   f"msg_id={getattr(incoming_message, 'message_id', 'N/A')}")
+                    return AckMessage.STATUS_OK, 'OK'
+
+            image_download_handler = self
+            dingtalk_msg = DingTalkMessage(incoming_message, image_download_handler)
+
+            if dingtalk_msg.is_group:
+                self.handle_group(dingtalk_msg)
+            else:
+                self.handle_single(dingtalk_msg)
+            return AckMessage.STATUS_OK, 'OK'
+        except Exception as e:
+            logger.error(f"[DingTalk] process error: {e}", exc_info=True)
+            return AckMessage.STATUS_SYSTEM_EXCEPTION, 'ERROR'
+
+    @time_checker
+    @_check
+    def handle_single(self, cmsg: DingTalkMessage):
+        # 处理单聊消息
+        if cmsg.ctype == ContextType.VOICE:
+            logger.debug("[DingTalk]receive voice msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.IMAGE:
+            logger.debug("[DingTalk]receive image msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.IMAGE_CREATE:
+            logger.debug("[DingTalk]receive image create msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.PATPAT:
+            logger.debug("[DingTalk]receive patpat msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.TEXT:
+            logger.debug("[DingTalk]receive text msg: {}".format(cmsg.content))
+        else:
+            logger.debug("[DingTalk]receive other msg: {}".format(cmsg.content))
+        
+        # 处理文件缓存逻辑
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+        
+        # 单聊的 session_id 就是 sender_id
+        session_id = cmsg.from_user_id
+        
+        # 如果是单张图片消息，缓存起来
+        if cmsg.ctype == ContextType.IMAGE:
+            if hasattr(cmsg, 'image_path') and cmsg.image_path:
+                file_cache.add(session_id, cmsg.image_path, file_type='image')
+                logger.info(f"[DingTalk] Image cached for session {session_id}, waiting for user query...")
+            # 单张图片不直接处理，等待用户提问
+            return
+        
+        # 如果是文本消息，检查是否有缓存的文件
+        if cmsg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                # 将缓存的文件附加到文本消息中
+                file_refs = []
+                for file_info in cached_files:
+                    file_path = file_info['path']
+                    file_type = file_info['type']
+                    if file_type == 'image':
+                        file_refs.append(f"[图片: {file_path}]")
+                    elif file_type == 'video':
+                        file_refs.append(f"[视频: {file_path}]")
+                    else:
+                        file_refs.append(f"[文件: {file_path}]")
+                
+                cmsg.content = cmsg.content + "\n" + "\n".join(file_refs)
+                logger.info(f"[DingTalk] Attached {len(cached_files)} cached file(s) to user query")
+                # 清除缓存
+                file_cache.clear(session_id)
+        
+        context = self._compose_context(cmsg.ctype, cmsg.content, isgroup=False, msg=cmsg)
+        if context:
+            self.produce(context)
+
+
+    @time_checker
+    @_check
+    def handle_group(self, cmsg: DingTalkMessage):
+        # 处理群聊消息
+        if cmsg.ctype == ContextType.VOICE:
+            logger.debug("[DingTalk]receive voice msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.IMAGE:
+            logger.debug("[DingTalk]receive image msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.IMAGE_CREATE:
+            logger.debug("[DingTalk]receive image create msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.PATPAT:
+            logger.debug("[DingTalk]receive patpat msg: {}".format(cmsg.content))
+        elif cmsg.ctype == ContextType.TEXT:
+            logger.debug("[DingTalk]receive text msg: {}".format(cmsg.content))
+        else:
+            logger.debug("[DingTalk]receive other msg: {}".format(cmsg.content))
+        
+        # 处理文件缓存逻辑
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+        
+        # 群聊的 session_id
+        if conf().get("group_shared_session", True):
+            session_id = cmsg.other_user_id  # conversation_id
+        else:
+            session_id = cmsg.from_user_id + "_" + cmsg.other_user_id
+        
+        # 如果是单张图片消息，缓存起来
+        if cmsg.ctype == ContextType.IMAGE:
+            if hasattr(cmsg, 'image_path') and cmsg.image_path:
+                file_cache.add(session_id, cmsg.image_path, file_type='image')
+                logger.info(f"[DingTalk] Image cached for session {session_id}, waiting for user query...")
+            # 单张图片不直接处理，等待用户提问
+            return
+        
+        # 如果是文本消息，检查是否有缓存的文件
+        if cmsg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                # 将缓存的文件附加到文本消息中
+                file_refs = []
+                for file_info in cached_files:
+                    file_path = file_info['path']
+                    file_type = file_info['type']
+                    if file_type == 'image':
+                        file_refs.append(f"[图片: {file_path}]")
+                    elif file_type == 'video':
+                        file_refs.append(f"[视频: {file_path}]")
+                    else:
+                        file_refs.append(f"[文件: {file_path}]")
+                
+                cmsg.content = cmsg.content + "\n" + "\n".join(file_refs)
+                logger.info(f"[DingTalk] Attached {len(cached_files)} cached file(s) to user query")
+                # 清除缓存
+                file_cache.clear(session_id)
+        
+        context = self._compose_context(cmsg.ctype, cmsg.content, isgroup=True, msg=cmsg)
+        context['no_need_at'] = True
+        if context:
+            self.produce(context)
+
+
+    def send(self, reply: Reply, context: Context):
+        logger.debug(f"[DingTalk] send() called with reply.type={reply.type}, content_length={len(str(reply.content))}")
+        receiver = context["receiver"]
+        
+        # Check if msg exists (for scheduled tasks, msg might be None)
+        msg = context.kwargs.get('msg')
+        if msg is None:
+            # 定时任务场景：使用主动发送 API
+            is_group = context.get("isgroup", False)
+            logger.info(f"[DingTalk] Sending scheduled task message to {receiver} (is_group={is_group})")
+            
+            # 使用缓存的 robot_code 或配置的值
+            robot_code = self._robot_code or conf().get("dingtalk_robot_code")
+            logger.info(f"[DingTalk] Using robot_code: {robot_code}, cached: {self._robot_code}, config: {conf().get('dingtalk_robot_code')}")
+            
+            if not robot_code:
+                logger.error(f"[DingTalk] Cannot send scheduled task: robot_code not available. Please send at least one message to the bot first, or configure dingtalk_robot_code in config.json")
+                return
+            
+            # 根据是否群聊选择不同的 API
+            if is_group:
+                success = self.send_group_message(receiver, reply.content, robot_code)
+            else:
+                # 单聊场景：尝试从 context 中获取 dingtalk_sender_staff_id
+                sender_staff_id = context.get("dingtalk_sender_staff_id")
+                if not sender_staff_id:
+                    logger.error(f"[DingTalk] Cannot send single chat scheduled message: sender_staff_id not available in context")
+                    return
+                
+                logger.info(f"[DingTalk] Sending single message to staff_id: {sender_staff_id}")
+                success = self.send_single_message(sender_staff_id, reply.content, robot_code)
+            
+            if not success:
+                logger.error(f"[DingTalk] Failed to send scheduled task message")
+            return
+        
+        # 从正常消息中提取并缓存 robot_code
+        if hasattr(msg, 'robot_code'):
+            robot_code = msg.robot_code
+            if robot_code and robot_code != self._robot_code:
+                self._robot_code = robot_code
+                logger.debug(f"[DingTalk] Cached robot_code: {robot_code}")
+        
+        isgroup = msg.is_group
+        incoming_message = msg.incoming_message
+        robot_code = self._robot_code or conf().get("dingtalk_robot_code")
+        
+        # 处理图片和视频发送
+        if reply.type == ReplyType.IMAGE_URL:
+            logger.info(f"[DingTalk] Sending image: {reply.content}")
+            
+            # 如果有附加的文本内容，先发送文本
+            if hasattr(reply, 'text_content') and reply.text_content:
+                self.reply_text(reply.text_content, incoming_message)
+                import time
+                time.sleep(0.3)  # 短暂延迟，确保文本先到达
+            
+            media_id = self.upload_media(reply.content, media_type="image")
+            if media_id:
+                # 使用主动发送 API 发送图片
+                access_token = self.get_access_token()
+                if access_token:
+                    success = self.send_image_with_media_id(
+                        access_token,
+                        media_id,
+                        incoming_message,
+                        isgroup
+                    )
+                    if not success:
+                        logger.error("[DingTalk] Failed to send image message")
+                        self.reply_text("抱歉，图片发送失败", incoming_message)
+                else:
+                    logger.error("[DingTalk] Cannot get access token")
+                    self.reply_text("抱歉，图片发送失败（无法获取token）", incoming_message)
+            else:
+                logger.error("[DingTalk] Failed to upload image")
+                self.reply_text("抱歉，图片上传失败", incoming_message)
+            return
+        
+        elif reply.type == ReplyType.FILE:
+            # 如果有附加的文本内容，先发送文本
+            if hasattr(reply, 'text_content') and reply.text_content:
+                self.reply_text(reply.text_content, incoming_message)
+                import time
+                time.sleep(0.3)  # 短暂延迟，确保文本先到达
+            
+            # 判断是否为视频文件
+            file_path = reply.content
+            if file_path.startswith("file://"):
+                file_path = file_path[7:]
+            
+            is_video = file_path.lower().endswith(('.mp4', '.avi', '.mov', '.wmv', '.flv'))
+            
+            access_token = self.get_access_token()
+            if not access_token:
+                logger.error("[DingTalk] Cannot get access token")
+                self.reply_text("抱歉，文件发送失败（无法获取token）", incoming_message)
+                return
+            
+            if is_video:
+                logger.info(f"[DingTalk] Sending video: {reply.content}")
+                media_id = self.upload_media(reply.content, media_type="video")
+                if media_id:
+                    # 发送视频消息
+                    msg_param = {
+                        "duration": "30",  # TODO: 获取实际视频时长
+                        "videoMediaId": media_id,
+                        "videoType": "mp4",
+                        "height": "400",
+                        "width": "600",
+                    }
+                    success = self._send_file_message(
+                        access_token,
+                        incoming_message,
+                        "sampleVideo",
+                        msg_param,
+                        isgroup
+                    )
+                    if not success:
+                        self.reply_text("抱歉，视频发送失败", incoming_message)
+                else:
+                    logger.error("[DingTalk] Failed to upload video")
+                    self.reply_text("抱歉，视频上传失败", incoming_message)
+            else:
+                # 其他文件类型
+                logger.info(f"[DingTalk] Sending file: {reply.content}")
+                media_id = self.upload_media(reply.content, media_type="file")
+                if media_id:
+                    file_name = os.path.basename(file_path)
+                    file_base, file_extension = os.path.splitext(file_name)
+                    msg_param = {
+                        "mediaId": media_id,
+                        "fileName": file_name,
+                        "fileType": file_extension[1:] if file_extension else "file"
+                    }
+                    success = self._send_file_message(
+                        access_token,
+                        incoming_message,
+                        "sampleFile",
+                        msg_param,
+                        isgroup
+                    )
+                    if not success:
+                        self.reply_text("抱歉，文件发送失败", incoming_message)
+                else:
+                    logger.error("[DingTalk] Failed to upload file")
+                    self.reply_text("抱歉，文件上传失败", incoming_message)
+            return
+        
+        # Native sampleAudio. Upload only accepts ogg/amr, so convert TTS mp3/wav to amr.
+        elif reply.type == ReplyType.VOICE:
+            logger.info(f"[DingTalk] Sending voice: {reply.content}")
+            access_token = self.get_access_token()
+            if not access_token:
+                logger.error("[DingTalk] Cannot get access token for voice")
+                self.reply_text("抱歉，语音发送失败（无法获取token）", incoming_message)
+                return
+
+            voice_path = reply.content
+            if voice_path.startswith("file://"):
+                voice_path = voice_path[7:]
+
+            amr_path = voice_path
+            duration_ms = 0
+            if not voice_path.lower().endswith((".amr", ".ogg")):
+                try:
+                    from voice.audio_convert import any_to_amr
+                    amr_path = os.path.splitext(voice_path)[0] + ".amr"
+                    duration_ms = int(any_to_amr(voice_path, amr_path) or 0)
+                except Exception as e:
+                    logger.error(f"[DingTalk] Failed to convert voice to amr: {e}")
+                    self.reply_text("抱歉，语音转码失败", incoming_message)
+                    return
+
+            media_id = self.upload_media(amr_path, media_type="voice")
+            if not media_id:
+                logger.error("[DingTalk] Failed to upload voice media")
+                self.reply_text("抱歉，语音上传失败", incoming_message)
+                return
+
+            msg_param = {
+                "mediaId": media_id,
+                "duration": str(duration_ms or 1000),
+            }
+            success = self._send_file_message(
+                access_token, incoming_message, "sampleAudio", msg_param, isgroup
+            )
+            if not success:
+                self.reply_text("抱歉，语音发送失败", incoming_message)
+            return
+
+        # 处理文本消息
+        elif reply.type == ReplyType.TEXT:
+            logger.info(f"[DingTalk] Sending text message, length={len(reply.content)}")
+            if conf().get("dingtalk_card_enabled"):
+                logger.info("[Dingtalk] sendMsg={}, receiver={}".format(reply, receiver))
+                def reply_with_text():
+                    self.reply_text(reply.content, incoming_message)
+                def reply_with_at_text():
+                    self.reply_text("📢 您有一条新的消息，请查看。", incoming_message)
+                def reply_with_ai_markdown():
+                    button_list, markdown_content = self.generate_button_markdown_content(context, reply)
+                    self.reply_ai_markdown_button(incoming_message, markdown_content, button_list, "", "📌 内容由AI生成", "",[incoming_message.sender_staff_id])
+
+                if reply.type in [ReplyType.IMAGE_URL, ReplyType.IMAGE, ReplyType.TEXT]:
+                    if isgroup:
+                        reply_with_ai_markdown()
+                        reply_with_at_text()
+                    else:
+                        reply_with_ai_markdown()
+                else:
+                    # 暂不支持其它类型消息回复
+                    reply_with_text()
+            else:
+                self.reply_text(reply.content, incoming_message)
+            return
+    
+    def _send_file_message(self, access_token: str, incoming_message, msg_key: str, msg_param: dict, is_group: bool) -> bool:
+        """
+        发送文件/视频消息的通用方法
+        
+        Args:
+            access_token: 访问令牌
+            incoming_message: 钉钉消息对象
+            msg_key: 消息类型 (sampleFile, sampleVideo, sampleAudio)
+            msg_param: 消息参数
+            is_group: 是否为群聊
+        
+        Returns:
+            是否发送成功
+        """
+        headers = {
+            "x-acs-dingtalk-access-token": access_token,
+            'Content-Type': 'application/json'
+        }
+        
+        body = {
+            "robotCode": incoming_message.robot_code,
+            "msgKey": msg_key,
+            "msgParam": json.dumps(msg_param),
+        }
+        
+        if is_group:
+            # 群聊
+            url = "https://api.dingtalk.com/v1.0/robot/groupMessages/send"
+            body["openConversationId"] = incoming_message.conversation_id
+        else:
+            # 单聊
+            url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+            body["userIds"] = [incoming_message.sender_staff_id]
+        
+        try:
+            response = requests.post(url=url, headers=headers, json=body, timeout=10)
+            result = response.json()
+            
+            logger.info(f"[DingTalk] File send result: {response.text}")
+            
+            if response.status_code == 200:
+                return True
+            else:
+                logger.error(f"[DingTalk] Send file error: {response.text}")
+                return False
+        except Exception as e:
+            logger.error(f"[DingTalk] Send file exception: {e}")
+            return False
+
+    def generate_button_markdown_content(self, context, reply):
+        image_url = context.kwargs.get("image_url")
+        promptEn = context.kwargs.get("promptEn")
+        reply_text = reply.content
+        button_list = []
+        markdown_content = f"""
+{reply.content}
+                                """
+        if image_url is not None and promptEn is not None:
+            button_list = [
+                {"text": "查看原图", "url": image_url, "iosUrl": image_url, "color": "blue"}
+            ]
+            markdown_content = f"""
+{promptEn}
+
+!["图片"]({image_url})
+
+{reply_text}
+
+                                """
+        logger.debug(f"[Dingtalk] generate_button_markdown_content, button_list={button_list} , markdown_content={markdown_content}")
+
+        return button_list, markdown_content
diff --git a/channel/dingtalk/dingtalk_message.py b/channel/dingtalk/dingtalk_message.py
new file mode 100644
index 0000000..27afe13
--- /dev/null
+++ b/channel/dingtalk/dingtalk_message.py
@@ -0,0 +1,244 @@
+import os
+import re
+
+import requests
+from dingtalk_stream import ChatbotMessage
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+# -*- coding=utf-8 -*-
+from common.log import logger
+from common.tmp_dir import TmpDir
+from common.utils import expand_path
+from config import conf
+
+
+class DingTalkMessage(ChatMessage):
+    def __init__(self, event: ChatbotMessage, image_download_handler):
+        super().__init__(event)
+        self.image_download_handler = image_download_handler
+        self.msg_id = event.message_id
+        self.message_type = event.message_type
+        self.incoming_message = event
+        self.sender_staff_id = event.sender_staff_id
+        self.other_user_id = event.conversation_id
+        self.create_time = event.create_at
+        self.image_content = event.image_content
+        self.rich_text_content = event.rich_text_content
+        self.robot_code = event.robot_code  # 机器人编码
+        if event.conversation_type == "1":
+            self.is_group = False
+        else:
+            self.is_group = True
+
+        if self.message_type == "text":
+            self.ctype = ContextType.TEXT
+
+            self.content = event.text.content.strip()
+        elif self.message_type == "audio":
+            # 钉钉支持直接识别语音，所以此处将直接提取文字，当文字处理
+            self.content = event.extensions['content']['recognition'].strip()
+            self.ctype = ContextType.TEXT
+        elif (self.message_type == 'picture') or (self.message_type == 'richText'):
+            # 钉钉图片类型或富文本类型消息处理
+            image_list = event.get_image_list()
+            
+            if self.message_type == 'picture' and len(image_list) > 0:
+                # 单张图片消息：下载到工作空间，用于文件缓存
+                self.ctype = ContextType.IMAGE
+                download_code = image_list[0]
+                download_url = image_download_handler.get_image_download_url(download_code)
+                
+                # 下载到工作空间 tmp 目录
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                tmp_dir = os.path.join(workspace_root, "tmp")
+                os.makedirs(tmp_dir, exist_ok=True)
+                
+                image_path = download_image_file(download_url, tmp_dir)
+                if image_path:
+                    self.content = image_path
+                    self.image_path = image_path  # 保存图片路径用于缓存
+                    logger.info(f"[DingTalk] Downloaded single image to {image_path}")
+                else:
+                    self.content = "[图片下载失败]"
+                    self.image_path = None
+            
+            elif self.message_type == 'richText' and len(image_list) > 0:
+                # 富文本消息：下载所有图片并附加到文本中
+                self.ctype = ContextType.TEXT
+                
+                # 下载到工作空间 tmp 目录
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                tmp_dir = os.path.join(workspace_root, "tmp")
+                os.makedirs(tmp_dir, exist_ok=True)
+                
+                # 提取富文本中的文本内容
+                text_content = ""
+                if self.rich_text_content:
+                    # rich_text_content 是一个 RichTextContent 对象，需要从中提取文本
+                    text_list = event.get_text_list()
+                    if text_list:
+                        text_content = "".join(text_list).strip()
+                
+                # 下载所有图片
+                image_paths = []
+                for download_code in image_list:
+                    download_url = image_download_handler.get_image_download_url(download_code)
+                    image_path = download_image_file(download_url, tmp_dir)
+                    if image_path:
+                        image_paths.append(image_path)
+                
+                # 构建消息内容：文本 + 图片路径
+                content_parts = []
+                if text_content:
+                    content_parts.append(text_content)
+                for img_path in image_paths:
+                    content_parts.append(f"[图片: {img_path}]")
+                
+                self.content = "\n".join(content_parts) if content_parts else "[富文本消息]"
+                logger.info(f"[DingTalk] Received richText with {len(image_paths)} image(s): {self.content}")
+            else:
+                self.ctype = ContextType.IMAGE
+                self.content = "[未找到图片]"
+                logger.debug(f"[DingTalk] messageType: {self.message_type}, imageList isEmpty")
+
+        if self.is_group:
+            self.from_user_id = event.conversation_id
+            self.actual_user_id = event.sender_id
+            self.is_at = True
+        else:
+            self.from_user_id = event.sender_id
+            self.actual_user_id = event.sender_id
+        self.to_user_id = event.chatbot_user_id
+        self.other_user_nickname = event.conversation_title
+
+
+def download_image_file(image_url, temp_dir):
+    """
+    下载图片文件
+    支持两种方式：
+    1. 普通 HTTP(S) URL
+    2. 钉钉 downloadCode: dingtalk://download/{download_code}
+    """
+    # 检查临时目录是否存在，如果不存在则创建
+    if not os.path.exists(temp_dir):
+        os.makedirs(temp_dir)
+    
+    # 处理钉钉 downloadCode
+    if image_url.startswith("dingtalk://download/"):
+        download_code = image_url.replace("dingtalk://download/", "")
+        logger.info(f"[DingTalk] Downloading image with downloadCode: {download_code[:20]}...")
+        
+        # 需要从外部传入 access_token，这里先用一个临时方案
+        # 从 config 获取 dingtalk_client_id 和 dingtalk_client_secret
+        from config import conf
+        client_id = conf().get("dingtalk_client_id")
+        client_secret = conf().get("dingtalk_client_secret")
+        
+        if not client_id or not client_secret:
+            logger.error("[DingTalk] Missing dingtalk_client_id or dingtalk_client_secret")
+            return None
+        
+        # 解析 robot_code 和 download_code
+        parts = download_code.split(":", 1)
+        if len(parts) != 2:
+            logger.error(f"[DingTalk] Invalid download_code format (expected robot_code:download_code): {download_code[:50]}")
+            return None
+        
+        robot_code, actual_download_code = parts
+        
+        # 获取 access_token（使用新版 API）
+        token_url = "https://api.dingtalk.com/v1.0/oauth2/accessToken"
+        token_headers = {
+            "Content-Type": "application/json"
+        }
+        token_body = {
+            "appKey": client_id,
+            "appSecret": client_secret
+        }
+        
+        try:
+            token_response = requests.post(token_url, json=token_body, headers=token_headers, timeout=10)
+            
+            if token_response.status_code == 200:
+                token_data = token_response.json()
+                access_token = token_data.get("accessToken")
+                
+                if not access_token:
+                    logger.error(f"[DingTalk] Failed to get access token: {token_data}")
+                    return None
+                
+                # 获取下载 URL（使用新版 API）
+                download_api_url = "https://api.dingtalk.com/v1.0/robot/messageFiles/download"
+                download_headers = {
+                    "x-acs-dingtalk-access-token": access_token,
+                    "Content-Type": "application/json"
+                }
+                download_body = {
+                    "downloadCode": actual_download_code,
+                    "robotCode": robot_code
+                }
+                
+                download_response = requests.post(download_api_url, json=download_body, headers=download_headers, timeout=10)
+                
+                if download_response.status_code == 200:
+                    download_data = download_response.json()
+                    download_url = download_data.get("downloadUrl")
+                    
+                    if not download_url:
+                        logger.error(f"[DingTalk] No downloadUrl in response: {download_data}")
+                        return None
+                    
+                    # 从 downloadUrl 下载实际图片
+                    image_response = requests.get(download_url, stream=True, timeout=60)
+                    
+                    if image_response.status_code == 200:
+                        # 生成文件名（使用 download_code 的 hash，避免特殊字符）
+                        import hashlib
+                        file_hash = hashlib.md5(actual_download_code.encode()).hexdigest()[:16]
+                        file_name = f"{file_hash}.png"
+                        file_path = os.path.join(temp_dir, file_name)
+                        
+                        with open(file_path, 'wb') as file:
+                            file.write(image_response.content)
+                        
+                        logger.info(f"[DingTalk] Image downloaded successfully: {file_path}")
+                        return file_path
+                    else:
+                        logger.error(f"[DingTalk] Failed to download image from URL: {image_response.status_code}")
+                        return None
+                else:
+                    logger.error(f"[DingTalk] Failed to get download URL: {download_response.status_code}, {download_response.text}")
+                    return None
+            else:
+                logger.error(f"[DingTalk] Failed to get access token: {token_response.status_code}, {token_response.text}")
+                return None
+        except Exception as e:
+            logger.error(f"[DingTalk] Exception downloading image: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            return None
+    
+    # 普通 HTTP(S) URL
+    else:
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'
+        }
+        
+        try:
+            response = requests.get(image_url, headers=headers, stream=True, timeout=60 * 5)
+            if response.status_code == 200:
+                # 生成文件名
+                file_name = image_url.split("/")[-1].split("?")[0]
+                
+                # 将文件保存到临时目录
+                file_path = os.path.join(temp_dir, file_name)
+                with open(file_path, 'wb') as file:
+                    file.write(response.content)
+                return file_path
+            else:
+                logger.info(f"[Dingtalk] Failed to download image file, {response.content}")
+                return None
+        except Exception as e:
+            logger.error(f"[Dingtalk] Exception downloading image: {e}")
+            return None
diff --git a/channel/discord/__init__.py b/channel/discord/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/channel/discord/discord_channel.py b/channel/discord/discord_channel.py
new file mode 100644
index 0000000..2c46df6
--- /dev/null
+++ b/channel/discord/discord_channel.py
@@ -0,0 +1,500 @@
+"""
+Discord channel via the Gateway (WebSocket) using discord.py.
+
+Features:
+- Direct message & guild channel chat (text / image / file)
+- Guild trigger: @mention or reply-to-bot (configurable)
+- /cancel fast-path matches Web channel behaviour
+- Gateway long connection: no public IP / callback URL required, works behind NAT
+
+Implementation note:
+    discord.py is async-first. We run the client inside a dedicated thread
+    with its own asyncio loop so the rest of cow (which is sync) stays
+    untouched. Inbound messages are dispatched onto cow's existing sync
+    ChatChannel.produce() pipeline; outbound send() schedules coroutines
+    back onto that loop via asyncio.run_coroutine_threadsafe.
+"""
+
+import asyncio
+import os
+import re
+import threading
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.discord.discord_message import DiscordMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from config import conf
+
+# Discord caps a single message at 2000 chars; split conservatively below.
+DISCORD_MSG_LIMIT = 1900
+
+
+@singleton
+class DiscordChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.bot_token = ""
+        self.bot_user_id = ""  # used to strip @mention and ignore self messages
+        self.bot_username = ""
+        self._client = None
+        self._loop = None
+        self._loop_thread = None
+        self._stop_event = threading.Event()
+        # Idempotent dedup; guard against rare duplicate dispatch
+        self._received_msgs = ExpiredDict(60 * 60 * 1)
+
+        # Disable group whitelist / prefix checks (we handle triggering ourselves
+        # in _should_reply_in_guild), aligned with telegram / slack channels.
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def startup(self):
+        self.bot_token = conf().get("discord_token", "")
+        if not self.bot_token:
+            err = "[Discord] discord_token is required"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        try:
+            import discord
+        except ImportError:
+            err = (
+                "[Discord] discord.py is not installed. "
+                "Run: pip install discord.py"
+            )
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        # Run the asyncio event loop in a dedicated thread so the sync cow body
+        # is untouched.
+        self._loop = asyncio.new_event_loop()
+
+        def _run_loop():
+            asyncio.set_event_loop(self._loop)
+            try:
+                self._loop.run_until_complete(self._async_main(discord))
+            except Exception as e:
+                logger.error(f"[Discord] event loop crashed: {e}", exc_info=True)
+                self.report_startup_error(str(e))
+            finally:
+                try:
+                    self._loop.close()
+                except Exception:
+                    pass
+                logger.info("[Discord] event loop exited")
+
+        self._loop_thread = threading.Thread(target=_run_loop, daemon=True, name="discord-loop")
+        self._loop_thread.start()
+        # Block startup() until the loop thread exits, matching other channels'
+        # behaviour (startup is a blocking call).
+        self._loop_thread.join()
+
+    async def _async_main(self, discord):
+        """Build the discord client, register handlers, and connect to the Gateway."""
+        # message_content is a privileged intent; it must be enabled in the
+        # Developer Portal (Bot -> Privileged Gateway Intents) to read text.
+        intents = discord.Intents.default()
+        intents.message_content = True
+        client = discord.Client(intents=intents)
+        self._client = client
+
+        channel = self
+
+        @client.event
+        async def on_ready():
+            channel.bot_user_id = str(client.user.id)
+            channel.bot_username = client.user.name or ""
+            channel.name = channel.bot_user_id  # ChatChannel uses self.name to strip @-mention
+            logger.info(f"[Discord] Bot logged in as {client.user} (id={client.user.id})")
+            channel.report_startup_success()
+            logger.info("[Discord] ✅ Discord bot ready, listening for messages")
+
+        @client.event
+        async def on_message(message):
+            await channel._on_message(message)
+
+        # Connect to the Gateway; discord.py auto-reconnects on transient errors.
+        logger.info("[Discord] Connecting to Gateway...")
+
+        # client.start() handles login + Gateway connection and runs until
+        # close(); it is the standard entrypoint across discord.py versions.
+        runner_task = asyncio.create_task(client.start(self.bot_token))
+
+        # Block until stop()
+        try:
+            while not self._stop_event.is_set():
+                if runner_task.done():
+                    # Surface a startup/connection failure (e.g. bad token)
+                    exc = runner_task.exception()
+                    if exc:
+                        logger.error(f"[Discord] client stopped: {exc}", exc_info=exc)
+                        self.report_startup_error(str(exc))
+                    break
+                await asyncio.sleep(0.5)
+        finally:
+            try:
+                if not client.is_closed():
+                    await client.close()
+            except Exception as e:
+                logger.warning(f"[Discord] shutdown error: {e}")
+
+    def stop(self):
+        logger.info("[Discord] stop() called")
+        self._stop_event.set()
+        if self._loop_thread and self._loop_thread.is_alive():
+            try:
+                self._loop_thread.join(timeout=10)
+            except Exception:
+                pass
+        logger.info("[Discord] stop() completed")
+
+    # ------------------------------------------------------------------
+    # Inbound: discord message -> ChatMessage -> ChatChannel.produce
+    # ------------------------------------------------------------------
+
+    async def _on_message(self, message):
+        """Discord message entry: parse -> build ChatMessage -> produce()."""
+        try:
+            # Ignore our own messages and other bots. self._client.user may be
+            # None until on_ready completes, so guard against that.
+            if self._client and self._client.user and message.author.id == self._client.user.id:
+                return
+            if message.author.bot:
+                return
+
+            # Idempotent dedup
+            msg_uid = f"{message.channel.id}:{message.id}"
+            if self._received_msgs.get(msg_uid):
+                return
+            self._received_msgs[msg_uid] = True
+
+            # guild is None for DMs
+            is_group = message.guild is not None
+
+            # Guild trigger gate (silently drop if not triggered)
+            if is_group and not self._should_reply_in_guild(message):
+                logger.debug(f"[Discord] guild message not triggered (need @mention or reply), skip")
+                return
+
+            # Parse message type + download attachments if needed.
+            ctype, content, caption = await self._parse_message(message)
+            if ctype is None:
+                logger.debug(f"[Discord] unsupported message type, skip. msg_id={message.id}")
+                return
+
+            # Strip the bot mention from guild text/caption
+            if is_group:
+                if ctype == ContextType.TEXT and content:
+                    content = self._strip_at_mention(content)
+                if caption:
+                    caption = self._strip_at_mention(caption)
+
+            dc_msg = DiscordMessage(
+                message,
+                is_group=is_group,
+                bot_user_id=self.bot_user_id,
+                ctype=ctype,
+                content=content,
+            )
+            dc_msg.is_at = is_group  # if we reached here in a guild, bot is mentioned/replied
+
+            from channel.file_cache import get_file_cache
+            file_cache = get_file_cache()
+            session_id = self._compute_session_id(message, is_group)
+
+            # Media + caption together: treat as a complete query and bypass the cache
+            if ctype in (ContextType.IMAGE, ContextType.FILE) and caption:
+                tag = "image" if ctype == ContextType.IMAGE else "file"
+                merged_text = f"{caption}\n[{tag}: {content}]"
+                dc_msg.ctype = ContextType.TEXT
+                dc_msg.content = merged_text
+                ctype = ContextType.TEXT
+                logger.info(f"[Discord] Media+caption merged for session {session_id}")
+                # fallthrough to the TEXT branch below
+
+            elif ctype == ContextType.IMAGE:
+                file_cache.add(session_id, content, file_type="image")
+                logger.info(f"[Discord] Image cached for session {session_id}, waiting for query...")
+                return
+            elif ctype == ContextType.FILE:
+                file_cache.add(session_id, content, file_type="file")
+                logger.info(f"[Discord] File cached for session {session_id}: {content}")
+                return
+
+            if ctype == ContextType.TEXT:
+                # Fast-path: /cancel mirrors Web channel behaviour
+                if (content or "").strip().lower() in ("/cancel", "cancel"):
+                    await self._do_cancel(session_id, message)
+                    return
+
+                cached_files = file_cache.get(session_id)
+                if cached_files:
+                    refs = []
+                    for fi in cached_files:
+                        ftype = fi["type"]
+                        tag = ftype if ftype in ("image", "video") else "file"
+                        refs.append(f"[{tag}: {fi['path']}]")
+                    dc_msg.content = (dc_msg.content or "") + "\n" + "\n".join(refs)
+                    file_cache.clear(session_id)
+                    logger.info(f"[Discord] Attached {len(cached_files)} cached file(s) to query")
+
+            context = self._compose_context(
+                dc_msg.ctype,
+                dc_msg.content,
+                isgroup=is_group,
+                msg=dc_msg,
+                # Replies use Discord's reply mechanism, no manual @mention needed
+                no_need_at=True,
+            )
+            if context:
+                context["session_id"] = session_id
+                context["receiver"] = str(message.channel.id)
+                context["discord_channel_id"] = message.channel.id
+                context["discord_reply_to_msg_id"] = message.id if is_group else None
+                self.produce(context)
+            logger.debug(f"[Discord] received: type={ctype}, content={str(dc_msg.content)[:80]}")
+
+        except Exception as e:
+            logger.error(f"[Discord] _on_message error: {e}", exc_info=True)
+
+    async def _do_cancel(self, session_id: str, message):
+        """Fast-path: /cancel calls cancel_session directly without going through agent."""
+        try:
+            from agent.protocol import get_cancel_registry
+            cancelled = get_cancel_registry().cancel_session(session_id)
+            text = "Current task cancelled." if cancelled else "No running task to cancel."
+            await message.channel.send(text)
+            logger.info(f"[Discord] /cancel session={session_id}, cancelled={cancelled}")
+        except Exception as e:
+            logger.error(f"[Discord] /cancel error: {e}", exc_info=True)
+
+    async def _parse_message(self, message):
+        """Parse a discord message and return (ctype, content, caption).
+
+        - content is text for ContextType.TEXT, otherwise the local file path
+        - caption is the optional text accompanying an attachment; empty for plain text
+        """
+        text = (message.content or "").strip()
+        attachments = message.attachments or []
+
+        if attachments:
+            # Handle the first attachment; caption is the accompanying message text
+            att = attachments[0]
+            content_type = (att.content_type or "").lower()
+            name = att.filename or str(att.id)
+            path = await self._download_attachment(att, name)
+            if not path:
+                return (None, None, "")
+            is_image = content_type.startswith("image/") or name.lower().endswith(
+                (".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp")
+            )
+            if is_image:
+                return (ContextType.IMAGE, path, text)
+            return (ContextType.FILE, path, text)
+
+        if text:
+            return (ContextType.TEXT, text, "")
+
+        return (None, None, "")
+
+    async def _download_attachment(self, attachment, name: str):
+        """Download a discord attachment into the local tmp dir; return path or None."""
+        try:
+            tmp_dir = DiscordMessage.get_tmp_dir()
+            safe_name = re.sub(r"[^\w.\-]", "_", name)
+            # Prefix with attachment id to avoid name collisions
+            local_path = os.path.join(tmp_dir, f"{attachment.id}_{safe_name}")
+            await attachment.save(local_path)
+            logger.debug(f"[Discord] downloaded {name} -> {local_path}")
+            return local_path
+        except Exception as e:
+            logger.error(f"[Discord] download_attachment failed ({name}): {e}")
+            return None
+
+    # ------------------------------------------------------------------
+    # Guild trigger logic
+    # ------------------------------------------------------------------
+
+    def _should_reply_in_guild(self, message) -> bool:
+        """Decide whether to reply to a guild channel message based on configuration."""
+        mode = conf().get("discord_group_trigger", "mention_or_reply")
+        if mode == "all":
+            return True
+
+        # self._client.user may be None until on_ready completes
+        if not self._client or not self._client.user:
+            return False
+
+        # 1) Mentioned (direct @bot, not @everyone / @role)
+        if self._client.user in message.mentions:
+            return True
+
+        # 2) Reply to a bot message
+        if mode == "mention_or_reply":
+            ref = message.reference
+            resolved = getattr(ref, "resolved", None) if ref else None
+            if resolved and getattr(resolved, "author", None):
+                if resolved.author.id == self._client.user.id:
+                    return True
+
+        return False
+
+    def _strip_at_mention(self, content: str) -> str:
+        """Strip <@BOT_ID> / <@!BOT_ID> from guild text."""
+        if not content or not self.bot_user_id:
+            return content
+        pattern = re.compile(r"<@!?" + re.escape(self.bot_user_id) + r">")
+        return pattern.sub("", content).strip()
+
+    @staticmethod
+    def _compute_session_id(message, is_group: bool) -> str:
+        channel_id = message.channel.id
+        user_id = message.author.id
+        if is_group:
+            if conf().get("group_shared_session", True):
+                return f"discord_channel_{channel_id}"
+            return f"discord_channel_{channel_id}_{user_id}"
+        return f"discord_user_{user_id}"
+
+    # ------------------------------------------------------------------
+    # Override _compose_context: skip the parent's group whitelist/at checks
+    # (already handled via _should_reply_in_guild). Same idea as telegram / slack.
+    # ------------------------------------------------------------------
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+        if cmsg.is_group:
+            if conf().get("group_shared_session", True):
+                context["session_id"] = cmsg.other_user_id
+            else:
+                context["session_id"] = f"{cmsg.from_user_id}:{cmsg.other_user_id}"
+        else:
+            context["session_id"] = cmsg.from_user_id
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = (content or "").strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+        elif ctype == ContextType.VOICE:
+            if "desire_rtype" not in context and (
+                conf().get("voice_reply_voice") or conf().get("always_reply_voice")
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+    # ------------------------------------------------------------------
+    # Outbound: ChatChannel.send -> Discord Gateway/REST
+    # ------------------------------------------------------------------
+
+    def send(self, reply: Reply, context: Context):
+        """Called from cow's sync main thread; marshal the coroutine onto the loop thread."""
+        if self._loop is None or self._client is None:
+            logger.warning("[Discord] client not ready, drop reply")
+            return
+
+        channel_id = context.get("discord_channel_id")
+        if channel_id is None:
+            logger.warning("[Discord] no discord_channel_id in context, drop reply")
+            return
+
+        coro = self._async_send(reply, channel_id)
+        try:
+            future = asyncio.run_coroutine_threadsafe(coro, self._loop)
+            future.result(timeout=180)
+        except Exception as e:
+            logger.error(f"[Discord] send failed: {e}")
+
+    async def _async_send(self, reply: Reply, channel_id):
+        try:
+            import discord
+
+            channel = self._client.get_channel(channel_id)
+            if channel is None:
+                # Not in cache (e.g. DM channel); fetch it explicitly
+                channel = await self._client.fetch_channel(channel_id)
+
+            rtype = reply.type
+            content = reply.content
+
+            if rtype in (ReplyType.TEXT, ReplyType.INFO, ReplyType.ERROR):
+                text = str(content) if content is not None else ""
+                if not text:
+                    return
+                for chunk in _split_text(text, DISCORD_MSG_LIMIT):
+                    await channel.send(chunk)
+
+            elif rtype == ReplyType.IMAGE:
+                # Already a local BytesIO; send it directly
+                content.seek(0)
+                await channel.send(file=discord.File(content, filename="image.png"))
+
+            elif rtype == ReplyType.IMAGE_URL:
+                url = str(content)
+                if url.startswith("file://"):
+                    local = url[7:]
+                    await channel.send(file=discord.File(local))
+                else:
+                    # Post the URL as text; Discord will unfurl it as an image preview
+                    await channel.send(url)
+
+            elif rtype in (ReplyType.VOICE, ReplyType.FILE):
+                local = content[7:] if isinstance(content, str) and content.startswith("file://") else content
+                caption = getattr(reply, "text_content", None) or None
+                await channel.send(content=caption, file=discord.File(local))
+
+            else:
+                # Fallback: send as plain text
+                await channel.send(str(content))
+
+            logger.info(f"[Discord] sent reply (type={rtype}, channel={channel_id})")
+
+        except Exception as e:
+            logger.error(f"[Discord] _async_send error: {e}", exc_info=True)
+
+
+def _split_text(text: str, limit: int):
+    """Split long text preferring line breaks to keep markdown structure intact."""
+    if len(text) <= limit:
+        yield text
+        return
+    buf = []
+    size = 0
+    for line in text.splitlines(keepends=True):
+        if size + len(line) > limit and buf:
+            yield "".join(buf)
+            buf, size = [], 0
+        # Hard-split single lines that exceed the limit
+        while len(line) > limit:
+            yield line[:limit]
+            line = line[limit:]
+        buf.append(line)
+        size += len(line)
+    if buf:
+        yield "".join(buf)
diff --git a/channel/discord/discord_message.py b/channel/discord/discord_message.py
new file mode 100644
index 0000000..2df3278
--- /dev/null
+++ b/channel/discord/discord_message.py
@@ -0,0 +1,60 @@
+"""
+Discord message adapter.
+
+Convert a discord.py Message into cow's unified ChatMessage.
+File downloads are NOT performed here; the channel layer downloads
+attachments on demand inside the async event loop.
+"""
+import os
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.utils import expand_path
+from config import conf
+
+
+class DiscordMessage(ChatMessage):
+    """Wrap a discord.py Message into the unified ChatMessage."""
+
+    def __init__(self, message, is_group: bool = False, bot_user_id: str = "",
+                 ctype: ContextType = ContextType.TEXT, content: str = ""):
+        super().__init__(message)
+        # Basic fields
+        self.msg_id = str(message.id)
+        self.create_time = int(message.created_at.timestamp()) if message.created_at else 0
+        self.ctype = ctype
+        self.content = content
+
+        author = message.author
+        channel = message.channel
+
+        # Sender / chat info
+        from_user_id = str(author.id)
+        from_user_nick = getattr(author, "display_name", None) or getattr(author, "name", None) or from_user_id
+        self.from_user_id = from_user_id
+        self.from_user_nickname = from_user_nick
+        self.to_user_id = bot_user_id or "discord_bot"
+        self.to_user_nickname = bot_user_id or "discord_bot"
+
+        self.is_group = is_group
+        if is_group:
+            # Guild channel: other_user_id = channel_id, actual_user_id = sender id
+            self.other_user_id = str(channel.id)
+            self.other_user_nickname = getattr(channel, "name", None) or str(channel.id)
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = from_user_nick
+        else:
+            # DM: use channel_id so replies go back to the same DM channel
+            self.other_user_id = str(channel.id)
+            self.other_user_nickname = from_user_nick
+
+        # Whether the bot was triggered by @-mention (set by channel layer)
+        self.is_at = False
+
+    @staticmethod
+    def get_tmp_dir() -> str:
+        """Local download directory, aligned with other channels (agent_workspace/tmp)."""
+        workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        tmp_dir = os.path.join(workspace_root, "tmp")
+        os.makedirs(tmp_dir, exist_ok=True)
+        return tmp_dir
diff --git a/channel/feishu/README.md b/channel/feishu/README.md
new file mode 100644
index 0000000..818d8f6
--- /dev/null
+++ b/channel/feishu/README.md
@@ -0,0 +1,184 @@
+# 飞书Channel使用说明
+
+飞书Channel支持两种事件接收模式，可以根据部署环境灵活选择。
+
+## 模式对比
+
+| 模式 | 适用场景 | 优点 | 缺点 |
+|------|---------|------|------|
+| **webhook** | 生产环境 | 稳定可靠，官方推荐 | 需要公网IP或域名 |
+| **websocket** | 本地开发 | 无需公网IP，开发便捷 | 需要额外依赖 |
+
+## 配置说明
+
+### 基础配置
+
+在 `config.json` 中添加以下配置:
+
+```json
+{
+  "channel_type": "feishu",
+  "feishu_app_id": "cli_xxxxx",
+  "feishu_app_secret": "your_app_secret",
+  "feishu_token": "your_verification_token",
+  "feishu_bot_name": "你的机器人名称",
+  "feishu_event_mode": "webhook",
+  "feishu_port": 9891
+}
+```
+
+### 配置项说明
+
+- `feishu_app_id`: 飞书应用的App ID
+- `feishu_app_secret`: 飞书应用的App Secret
+- `feishu_token`: 事件订阅的Verification Token
+- `feishu_bot_name`: 机器人名称(用于群聊@判断)
+- `feishu_event_mode`: 事件接收模式，可选值:
+  - `"websocket"`: 长连接模式(默认)
+  - `"webhook"`: HTTP服务器模式
+- `feishu_port`: webhook模式下的HTTP服务端口(默认9891)
+
+## 模式一: Webhook模式(推荐生产环境)
+
+### 1. 配置
+
+```json
+{
+  "feishu_event_mode": "webhook",
+  "feishu_port": 9891
+}
+```
+
+### 2. 启动服务
+
+```bash
+python3 app.py
+```
+
+服务将在 `http://0.0.0.0:9891` 启动。
+
+### 3. 配置飞书应用
+
+1. 登录[飞书开放平台](https://open.feishu.cn/)
+2. 进入应用详情 -> 事件订阅
+3. 选择 **将事件发送至开发者服务器**
+4. 填写请求地址: `http://your-domain:9891/`
+5. 添加事件: `im.message.receive_v1` (接收消息v2.0)
+6. 保存配置
+
+### 4. 注意事项
+
+- 需要有公网IP或域名
+- 确保防火墙开放对应端口
+- 建议使用HTTPS(需要配置反向代理)
+
+## 模式二: WebSocket模式(推荐本地开发)
+
+### 1. 安装依赖
+
+```bash
+pip install lark-oapi
+```
+
+### 2. 配置
+
+```json
+{
+  "feishu_event_mode": "websocket"
+}
+```
+
+### 3. 启动服务
+
+```bash
+python3 app.py
+```
+
+程序将自动建立与飞书开放平台的长连接。
+
+### 4. 配置飞书应用
+
+1. 登录[飞书开放平台](https://open.feishu.cn/)
+2. 进入应用详情 -> 事件订阅
+3. 选择 **使用长连接接收事件**
+4. 添加事件: `im.message.receive_v1` (接收消息v2.0)
+5. 保存配置
+
+### 5. 注意事项
+
+- 无需公网IP
+- 需要能访问公网(建立WebSocket连接)
+- 每个应用最多50个连接
+- 集群模式下消息随机分发到一个客户端
+
+## 平滑迁移
+
+从webhook模式切换到websocket模式(或反向切换):
+
+1. 修改 `config.json` 中的 `feishu_event_mode`
+2. 如果切换到websocket模式，安装 `lark-oapi` 依赖
+3. 重启服务
+4. 在飞书开放平台修改事件订阅方式
+
+**重要**: 同一时间只能使用一种模式，否则会导致消息重复接收。
+
+## 消息去重机制
+
+两种模式都使用相同的消息去重机制:
+
+- 使用 `ExpiredDict` 存储已处理的消息ID
+- 过期时间: 7.1小时
+- 确保消息不会重复处理
+
+## 故障排查
+
+### WebSocket模式连接失败
+
+```
+[FeiShu] lark_oapi not installed
+```
+
+**解决**: 安装依赖 `pip install lark-oapi`
+
+### SSL证书验证失败
+
+```
+[Lark][ERROR] connect failed, err:[SSL:CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain
+```
+
+**原因**: 网络环境中存在自签名证书或SSL中间人代理(如企业代理、VPN等)
+
+**解决**: 程序会自动检测SSL证书验证失败，并自动重试禁用证书验证的连接。无需手动配置。
+
+当遇到证书错误时，日志会显示：
+```
+[FeiShu] SSL certificate verification disabled due to certificate error. This may happen when using corporate proxy or self-signed certificates.
+```
+
+这是正常现象，程序会自动处理并继续运行。
+
+### Webhook模式端口被占用
+
+```
+Address already in use
+```
+
+**解决**: 修改 `feishu_port` 配置或关闭占用端口的进程
+
+### 收不到消息
+
+1. 检查飞书应用的事件订阅配置
+2. 确认已添加 `im.message.receive_v1` 事件
+3. 检查应用权限: 需要 `im:message` 权限
+4. 查看日志中的错误信息
+
+## 开发建议
+
+- **本地开发**: 使用websocket模式，快速迭代
+- **测试环境**: 可以使用webhook模式 + 内网穿透工具(如ngrok)
+- **生产环境**: 使用webhook模式，配置正式域名和HTTPS
+
+## 参考文档
+
+- [飞书开放平台 - 事件订阅](https://open.feishu.cn/document/ukTMukTMukTM/uUTNz4SN1MjL1UzM)
+- [飞书SDK - Python](https://github.com/larksuite/oapi-sdk-python)
diff --git a/channel/feishu/feishu_channel.py b/channel/feishu/feishu_channel.py
new file mode 100644
index 0000000..9a9f330
--- /dev/null
+++ b/channel/feishu/feishu_channel.py
@@ -0,0 +1,1599 @@
+"""
+飞书通道接入
+
+支持两种事件接收模式:
+1. webhook模式: 通过HTTP服务器接收事件(需要公网IP)
+2. websocket模式: 通过长连接接收事件(本地开发友好)
+
+通过配置项 feishu_event_mode 选择模式: "webhook" 或 "websocket"
+
+@author Saboteur7
+@Date 2023/11/19
+"""
+
+import importlib.util
+import json
+import logging
+import os
+import ssl
+import threading
+# -*- coding=utf-8 -*-
+import uuid
+
+import requests
+import web
+
+from bridge.context import Context
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.feishu.feishu_message import FeishuMessage
+from common import utils
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from config import conf
+
+# Suppress verbose logs from Lark SDK
+logging.getLogger("Lark").setLevel(logging.WARNING)
+
+URL_VERIFICATION = "url_verification"
+
+# Lazy-check for lark_oapi SDK availability without importing it at module level.
+# The full `import lark_oapi` pulls in 10k+ files and takes 4-10s, so we defer
+# the actual import to _startup_websocket() where it is needed.
+LARK_SDK_AVAILABLE = importlib.util.find_spec("lark_oapi") is not None
+lark = None  # will be populated on first use via _ensure_lark_imported()
+
+
+def _ensure_lark_imported():
+    """Import lark_oapi on first use (takes 4-10s due to 10k+ source files)."""
+    global lark
+    if lark is None:
+        import lark_oapi as _lark
+        lark = _lark
+    return lark
+
+
+def _print_qr_to_terminal(qr_url: str):
+    """Render a QR code as ASCII art and emit it via logger.
+
+    走 logger 而非 print 是为了避免 nohup/cow 后台启动场景下 stdout 块缓冲导致
+    二维码滞后输出（看起来像出现了两次）。logger 的 StreamHandler 是行缓冲，
+    既能在前台终端看到，也能进 run.log。
+    """
+    qr_lines = []
+    try:
+        import qrcode as qr_lib
+        import io
+        qr = qr_lib.QRCode(error_correction=qr_lib.constants.ERROR_CORRECT_L, box_size=1, border=1)
+        qr.add_data(qr_url)
+        qr.make(fit=True)
+        buf = io.StringIO()
+        qr.print_ascii(out=buf, invert=True)
+        qr_lines = buf.getvalue().splitlines()
+    except ImportError:
+        qr_lines = ["(未安装 qrcode 包，无法渲染 ASCII 二维码：pip install qrcode)"]
+    except Exception as e:
+        qr_lines = [f"(渲染二维码失败：{e})"]
+
+    header = "=" * 60
+    banner = [
+        "",
+        header,
+        "  飞书一键创建应用：请使用 飞书 App 扫描下方二维码",
+        "  （二维码 10 分钟内有效，仅供一次扫描）",
+        header,
+    ]
+    footer = [
+        f"  或点击链接创建: {qr_url}",
+        "  等待扫码...",
+        "",
+    ]
+    full = banner + qr_lines + footer
+    logger.info("[FeiShu] One-click 飞书应用创建二维码（请用飞书 App 扫码）：\n" + "\n".join(full))
+
+
+def _persist_feishu_credentials(app_id: str, app_secret: str) -> bool:
+    """Write feishu_app_id / feishu_app_secret + ensure feishu in channel_type into config.json.
+
+    Returns True on success, False on failure (e.g. config.json missing or unwritable).
+    """
+    try:
+        config_path = os.path.join(
+            os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
+            "config.json",
+        )
+        if os.path.exists(config_path):
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_cfg = json.load(f)
+        else:
+            file_cfg = {}
+
+        file_cfg["feishu_app_id"] = app_id
+        file_cfg["feishu_app_secret"] = app_secret
+
+        # 保证 channel_type 中包含 feishu（用户可能纯通过 CLI 启动单通道）
+        ch_type = file_cfg.get("channel_type", conf().get("channel_type", "")) or ""
+        existing = [s.strip() for s in ch_type.split(",") if s.strip()]
+        if "feishu" not in existing:
+            existing.append("feishu")
+            file_cfg["channel_type"] = ",".join(existing)
+
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(file_cfg, f, indent=4, ensure_ascii=False)
+
+        # 同步到内存中的 conf()，让本次启动直接生效
+        conf()["feishu_app_id"] = app_id
+        conf()["feishu_app_secret"] = app_secret
+        if "channel_type" in file_cfg:
+            conf()["channel_type"] = file_cfg["channel_type"]
+
+        try:
+            os.chmod(config_path, 0o600)
+        except Exception:
+            pass
+        return True
+    except Exception as e:
+        logger.error(f"[FeiShu] Failed to persist credentials to config.json: {e}")
+        return False
+
+
+def _register_via_qr_in_terminal() -> bool:
+    """CLI-side one-click app creation via lark_oapi.register_app.
+
+    Blocks the calling thread (typically the channel startup thread) until the user
+    finishes scanning, the QR code expires, or registration is cancelled.
+
+    Returns True if credentials were obtained AND persisted; False otherwise.
+    The caller should fall back to the original "missing credentials" error in that case.
+    """
+    if not LARK_SDK_AVAILABLE:
+        logger.error(
+            "[FeiShu] 缺少 feishu_app_id / feishu_app_secret。"
+            "未安装 lark-oapi SDK，无法在终端发起扫码创建。"
+            "请执行 pip install -U 'lark-oapi>=1.5.5' 后重试，或手动在 config.json 中填入凭据。"
+        )
+        return False
+
+    try:
+        lark_mod = _ensure_lark_imported()
+    except Exception as e:
+        logger.error(f"[FeiShu] Import lark_oapi failed: {e}")
+        return False
+
+    # register_app 是 lark-oapi 1.5.5 才引入的能力，旧版本调用会得到难以理解的
+    # AttributeError。提前显式检查，给出明确的升级提示。
+    if not hasattr(lark_mod, "register_app"):
+        try:
+            from importlib.metadata import version as _pkg_version
+            installed = _pkg_version("lark-oapi")
+        except Exception:
+            installed = "unknown"
+        logger.error(
+            f"[FeiShu] 当前 lark-oapi 版本 ({installed}) 不支持一键创建应用，需要 >= 1.5.5。"
+            "请执行 pip install -U 'lark-oapi>=1.5.5' 后重试，或手动在 config.json 中填入凭据。"
+        )
+        return False
+
+    logger.info("[FeiShu] 检测到尚未配置 feishu_app_id / feishu_app_secret，"
+                "正在向飞书申请一键创建应用...")
+
+    def _on_qr(info):
+        url = info.get("url", "")
+        if url:
+            _print_qr_to_terminal(url)
+
+    def _on_status(info):
+        # 过滤 polling 心跳（每 5 秒一次），保留 slow_down / domain_switched 等
+        status = info.get("status")
+        if status == "polling":
+            return
+        logger.info(f"[FeiShu] register_app status: {info}")
+
+    try:
+        result = lark_mod.register_app(
+            on_qr_code=_on_qr,
+            on_status_change=_on_status,
+            source="cowagent",
+        )
+    except Exception as e:
+        err_cls = e.__class__.__name__
+        if "Expired" in err_cls:
+            logger.error("[FeiShu] 二维码已过期，请重启程序后重试。")
+        elif "Denied" in err_cls:
+            logger.error("[FeiShu] 已取消授权。")
+        else:
+            logger.error(f"[FeiShu] 一键创建失败：{e}")
+        return False
+
+    app_id = result.get("client_id", "")
+    app_secret = result.get("client_secret", "")
+    if not app_id or not app_secret:
+        logger.error("[FeiShu] 创建结果缺少 app_id/app_secret，无法继续。")
+        return False
+
+    if not _persist_feishu_credentials(app_id, app_secret):
+        logger.error(
+            "[FeiShu] 应用创建成功但写入 config.json 失败，请手动复制以下值到配置文件：\n"
+            f"        feishu_app_id     = {app_id}\n"
+            f"        feishu_app_secret = {app_secret}"
+        )
+        return False
+
+    logger.info(f"[FeiShu] 应用创建成功，凭据已写入 config.json (app_id={app_id})。")
+    return True
+
+
+@singleton
+class FeiShuChanel(ChatChannel):
+    feishu_app_id = conf().get('feishu_app_id')
+    feishu_app_secret = conf().get('feishu_app_secret')
+    feishu_token = conf().get('feishu_token')
+    feishu_event_mode = conf().get('feishu_event_mode', 'websocket')  # webhook 或 websocket
+    # 覆盖父类默认值 [ReplyType.VOICE, ReplyType.IMAGE]。
+    # 飞书原生支持发送音频（opus 格式，通过文件上传接口）和图片，
+    # 所有回复类型均已处理，置为空列表以启用语音和图片回复。
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        # 历史消息id暂存，用于幂等控制
+        self.receivedMsgs = ExpiredDict(60 * 60 * 7.1)
+        self._http_server = None
+        self._ws_client = None
+        self._ws_thread = None
+        self._bot_open_id = None  # cached bot open_id for @-mention matching
+        logger.debug("[FeiShu] app_id={}, app_secret={}, verification_token={}, event_mode={}".format(
+            self.feishu_app_id, self.feishu_app_secret, self.feishu_token, self.feishu_event_mode))
+        # 无需群校验和前缀
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+        # 验证配置
+        if self.feishu_event_mode == 'websocket' and not LARK_SDK_AVAILABLE:
+            logger.error("[FeiShu] websocket mode requires lark_oapi. Please install: pip install lark-oapi")
+            raise Exception("lark_oapi not installed")
+
+    def startup(self):
+        self.feishu_app_id = conf().get('feishu_app_id')
+        self.feishu_app_secret = conf().get('feishu_app_secret')
+        self.feishu_token = conf().get('feishu_token')
+        self.feishu_event_mode = conf().get('feishu_event_mode', 'websocket')
+
+        # 命令行启动场景：缺少凭据时尝试通过 lark.register_app 在终端弹二维码
+        # 引导用户扫码创建应用。Web 控制台启动同样会走到这里，但控制台用户通常
+        # 已经通过 /api/feishu/register 完成了创建并写回 config.json。
+        if not self.feishu_app_id or not self.feishu_app_secret:
+            if _register_via_qr_in_terminal():
+                self.feishu_app_id = conf().get('feishu_app_id')
+                self.feishu_app_secret = conf().get('feishu_app_secret')
+            else:
+                err = "[FeiShu] feishu_app_id 与 feishu_app_secret 缺失，无法启动通道"
+                logger.error(err)
+                self.report_startup_error(err)
+                return
+
+        self._fetch_bot_open_id()
+        if self.feishu_event_mode == 'websocket':
+            self._startup_websocket()
+        else:
+            self._startup_webhook()
+
+    def _fetch_bot_open_id(self):
+        """Fetch the bot's own open_id via API so we can match @-mentions without feishu_bot_name."""
+        try:
+            access_token = self.fetch_access_token()
+            if not access_token:
+                logger.warning("[FeiShu] Cannot fetch bot info: no access_token")
+                return
+            headers = {"Authorization": "Bearer " + access_token}
+            resp = requests.get("https://open.feishu.cn/open-apis/bot/v3/info/", headers=headers, timeout=5)
+            if resp.status_code == 200:
+                data = resp.json()
+                if data.get("code") == 0:
+                    self._bot_open_id = data.get("bot", {}).get("open_id")
+                    logger.info(f"[FeiShu] Bot open_id fetched: {self._bot_open_id}")
+                else:
+                    logger.warning(f"[FeiShu] Fetch bot info failed: code={data.get('code')}, msg={data.get('msg')}")
+        except Exception as e:
+            logger.warning(f"[FeiShu] Fetch bot open_id error: {e}")
+
+    def stop(self):
+        import ctypes
+        logger.info("[FeiShu] stop() called")
+        ws_client = self._ws_client
+        self._ws_client = None
+        ws_thread = self._ws_thread
+        self._ws_thread = None
+        # Interrupt the ws thread first so its blocking start() unblocks
+        if ws_thread and ws_thread.is_alive():
+            try:
+                tid = ws_thread.ident
+                if tid:
+                    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(
+                        ctypes.c_ulong(tid), ctypes.py_object(SystemExit)
+                    )
+                    if res == 1:
+                        logger.info("[FeiShu] Interrupted ws thread via ctypes")
+                    elif res > 1:
+                        ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_ulong(tid), None)
+            except Exception as e:
+                logger.warning(f"[FeiShu] Error interrupting ws thread: {e}")
+        # lark.ws.Client has no stop() method; thread interruption above is sufficient
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[FeiShu] HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[FeiShu] Error stopping HTTP server: {e}")
+            self._http_server = None
+        logger.info("[FeiShu] stop() completed")
+
+    def _startup_webhook(self):
+        """启动HTTP服务器接收事件(webhook模式)"""
+        logger.debug("[FeiShu] Starting in webhook mode...")
+        urls = (
+            '/', 'channel.feishu.feishu_channel.FeishuController'
+        )
+        app = web.application(urls, globals(), autoreload=False)
+        port = conf().get("feishu_port", 9891)
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer(("0.0.0.0", port), func)
+        self._http_server = server
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+
+    def _startup_websocket(self):
+        """启动长连接接收事件(websocket模式)"""
+        _ensure_lark_imported()
+        logger.debug("[FeiShu] Starting in websocket mode...")
+
+        # 创建事件处理器
+        def handle_message_event(data: lark.im.v1.P2ImMessageReceiveV1) -> None:
+            """处理接收消息事件 v2.0"""
+            try:
+                event_dict = json.loads(lark.JSON.marshal(data))
+                event = event_dict.get("event", {})
+                msg = event.get("message", {})
+
+                # Skip group messages that don't @-mention the bot (reduce log noise)
+                if msg.get("chat_type") == "group" and not msg.get("mentions") and msg.get("message_type") == "text":
+                    return
+
+                logger.debug(f"[FeiShu] websocket receive event: {lark.JSON.marshal(data, indent=2)}")
+
+                # 处理消息
+                self._handle_message_event(event)
+
+            except Exception as e:
+                logger.error(f"[FeiShu] websocket handle message error: {e}", exc_info=True)
+
+        # 构建事件分发器
+        event_handler = lark.EventDispatcherHandler.builder("", "") \
+            .register_p2_im_message_receive_v1(handle_message_event) \
+            .build()
+
+        def start_client_with_retry():
+            """Run ws client in this thread with its own event loop to avoid conflicts."""
+            import asyncio
+            import ssl as ssl_module
+            original_create_default_context = ssl_module.create_default_context
+
+            def create_unverified_context(*args, **kwargs):
+                context = original_create_default_context(*args, **kwargs)
+                context.check_hostname = False
+                context.verify_mode = ssl.CERT_NONE
+                return context
+
+            # lark_oapi.ws.client captures the event loop at module-import time as a module-
+            # level global variable.  When a previous ws thread is force-killed via ctypes its
+            # loop may still be marked as "running", which causes the next ws_client.start()
+            # call (in this new thread) to raise "This event loop is already running".
+            # Fix: replace the module-level loop with a brand-new, idle loop before starting.
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+            try:
+                import lark_oapi.ws.client as _lark_ws_client_mod
+                _lark_ws_client_mod.loop = loop
+            except Exception:
+                pass
+
+            startup_error = None
+            for attempt in range(2):
+                try:
+                    if attempt == 1:
+                        logger.warning("[FeiShu] Retrying with SSL verification disabled...")
+                        ssl_module.create_default_context = create_unverified_context
+                        ssl_module._create_unverified_context = create_unverified_context
+
+                    ws_client = lark.ws.Client(
+                        self.feishu_app_id,
+                        self.feishu_app_secret,
+                        event_handler=event_handler,
+                        log_level=lark.LogLevel.WARNING
+                    )
+                    self._ws_client = ws_client
+                    logger.debug("[FeiShu] Websocket client starting...")
+                    ws_client.start()
+                    break
+
+                except (SystemExit, KeyboardInterrupt):
+                    logger.info("[FeiShu] Websocket thread received stop signal")
+                    break
+                except Exception as e:
+                    error_msg = str(e)
+                    is_ssl_error = ("CERTIFICATE_VERIFY_FAILED" in error_msg
+                                    or "certificate verify failed" in error_msg.lower())
+                    if is_ssl_error and attempt == 0:
+                        logger.warning(f"[FeiShu] SSL error: {error_msg}, retrying...")
+                        continue
+                    logger.error(f"[FeiShu] Websocket client error: {e}", exc_info=True)
+                    startup_error = error_msg
+                    ssl_module.create_default_context = original_create_default_context
+                    break
+            if startup_error:
+                self.report_startup_error(startup_error)
+            try:
+                loop.close()
+            except Exception:
+                pass
+            logger.info("[FeiShu] Websocket thread exited")
+
+        ws_thread = threading.Thread(target=start_client_with_retry, daemon=True)
+        self._ws_thread = ws_thread
+        ws_thread.start()
+        logger.info("[FeiShu] ✅ Websocket thread started, ready to receive messages")
+        ws_thread.join()
+
+    def _is_mention_bot(self, mentions: list) -> bool:
+        """Check whether any mention in the list refers to this bot.
+
+        Priority:
+        1. Match by open_id (obtained from /bot/v3/info at startup, no config needed)
+        2. Fallback to feishu_bot_name config for backward compatibility
+        3. If neither is available, assume the first mention is the bot (Feishu only
+           delivers group messages that @-mention the bot, so this is usually correct)
+        """
+        if self._bot_open_id:
+            return any(
+                m.get("id", {}).get("open_id") == self._bot_open_id
+                for m in mentions
+            )
+        bot_name = conf().get("feishu_bot_name")
+        if bot_name:
+            return any(m.get("name") == bot_name for m in mentions)
+        # Feishu event subscription only delivers messages that @-mention the bot,
+        # so reaching here means the bot was indeed mentioned.
+        return True
+
+    def _handle_message_event(self, event: dict):
+        """
+        处理消息事件的核心逻辑
+        webhook和websocket模式共用此方法
+        """
+        if not event.get("message") or not event.get("sender"):
+            logger.warning(f"[FeiShu] invalid message, event={event}")
+            return
+
+        msg = event.get("message")
+
+        # 幂等判断
+        msg_id = msg.get("message_id")
+        if self.receivedMsgs.get(msg_id):
+            logger.warning(f"[FeiShu] repeat msg filtered, msg_id={msg_id}")
+            return
+        self.receivedMsgs[msg_id] = True
+
+        # Filter out stale messages from before channel startup (offline backlog)
+        import time as _time
+        create_time_ms = msg.get("create_time")
+        if create_time_ms:
+            msg_age_s = _time.time() - int(create_time_ms) / 1000
+            if msg_age_s > 60:
+                logger.warning(f"[FeiShu] stale msg filtered (age={msg_age_s:.0f}s), msg_id={msg_id}")
+                return
+
+        is_group = False
+        chat_type = msg.get("chat_type")
+
+        if chat_type == "group":
+            if not msg.get("mentions") and msg.get("message_type") == "text":
+                # 群聊中未@不响应
+                return
+            if msg.get("mentions") and msg.get("message_type") == "text":
+                if not self._is_mention_bot(msg.get("mentions")):
+                    return
+            # 群聊
+            is_group = True
+            receive_id_type = "chat_id"
+        elif chat_type == "p2p":
+            receive_id_type = "open_id"
+        else:
+            logger.warning("[FeiShu] message ignore")
+            return
+
+        # 构造飞书消息对象
+        feishu_msg = FeishuMessage(event, is_group=is_group, access_token=self.fetch_access_token())
+        if not feishu_msg:
+            return
+
+        # 处理文件缓存逻辑
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+
+        # 获取 session_id（用于缓存关联）
+        if is_group:
+            if conf().get("group_shared_session", True):
+                session_id = msg.get("chat_id")  # 群共享会话
+            else:
+                session_id = feishu_msg.from_user_id + "_" + msg.get("chat_id")
+        else:
+            session_id = feishu_msg.from_user_id
+
+        # 如果是单张图片消息，缓存起来
+        if feishu_msg.ctype == ContextType.IMAGE:
+            if hasattr(feishu_msg, 'image_path') and feishu_msg.image_path:
+                file_cache.add(session_id, feishu_msg.image_path, file_type='image')
+                logger.info(f"[FeiShu] Image cached for session {session_id}, waiting for user query...")
+            # 单张图片不直接处理，等待用户提问
+            return
+
+        # 如果是文件消息，触发实际下载并缓存，等待用户后续提问时一并带上。
+        # 与 wecom_bot 行为对齐：发文件后静默缓存（飞书客户端会显示"已读"），
+        # 用户下一条文本消息会自动 attach 上文件路径给 agent。
+        if feishu_msg.ctype == ContextType.FILE:
+            try:
+                feishu_msg.prepare()
+                # prepare 通过 _prepared 标记保证幂等，重复调用安全
+                if not os.path.exists(feishu_msg.content):
+                    raise FileNotFoundError(feishu_msg.content)
+            except Exception as e:
+                logger.warning(f"[FeiShu] prepare file failed: {e}")
+                # 文件下载失败时主动通知用户，避免静默丢失
+                try:
+                    err_reply = Reply(ReplyType.TEXT, f"⚠️ 文件下载失败，请重新发送：{e}")
+                    self._send(err_reply, self._compose_context(
+                        ContextType.TEXT, "",
+                        isgroup=is_group, msg=feishu_msg,
+                        receive_id_type=receive_id_type, no_need_at=True,
+                    ))
+                except Exception:
+                    pass
+                return
+            file_cache.add(session_id, feishu_msg.content, file_type='file')
+            logger.info(f"[FeiShu] File cached for session {session_id}: {feishu_msg.content}")
+            return
+
+        # 如果是文本消息，检查是否有缓存的文件
+        if feishu_msg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                # 将缓存的文件附加到文本消息中
+                file_refs = []
+                for file_info in cached_files:
+                    file_path = file_info['path']
+                    file_type = file_info['type']
+                    if file_type == 'image':
+                        file_refs.append(f"[图片: {file_path}]")
+                    elif file_type == 'video':
+                        file_refs.append(f"[视频: {file_path}]")
+                    else:
+                        file_refs.append(f"[文件: {file_path}]")
+
+                feishu_msg.content = feishu_msg.content + "\n" + "\n".join(file_refs)
+                logger.info(f"[FeiShu] Attached {len(cached_files)} cached file(s) to user query")
+                # 清除缓存
+                file_cache.clear(session_id)
+
+        context = self._compose_context(
+            feishu_msg.ctype,
+            feishu_msg.content,
+            isgroup=is_group,
+            msg=feishu_msg,
+            receive_id_type=receive_id_type,
+            no_need_at=True
+        )
+        if context:
+            # 流式回复模式：向 context 注入 on_event 回调，agent 每产出一段文字时会调用它。
+            # 回调内部先发送一条占位消息获取 message_id，之后通过 PATCH 接口原地更新内容，
+            # 实现打字机效果。回调结束时设置 context["feishu_streamed"]=True，
+            # 让 send() 跳过重复发送，避免最终完整回复再被重复投递一次。
+            # 默认开启流式打字机回复。需机器人开通 cardkit:card:write 权限且飞书客户端 7.20+，
+            # 任意环节失败会自动降级为非流式文本回复。
+            if conf().get("feishu_stream_reply", True):
+                context["on_event"] = self._make_feishu_stream_callback(context, feishu_msg.access_token)
+            self.produce(context)
+        logger.debug(f"[FeiShu] query={feishu_msg.content}, type={feishu_msg.ctype}")
+
+    def send(self, reply: Reply, context: Context):
+        # 如果文本回复已通过流式传输发送，则跳过重复发送
+        if reply.type == ReplyType.TEXT and context.get("feishu_streamed"):
+            logger.debug("[FeiShu] streaming already delivered text reply, skipping send()")
+            return
+        msg = context.get("msg")
+        is_group = context["isgroup"]
+        if msg:
+            access_token = msg.access_token
+        else:
+            access_token = self.fetch_access_token()
+        headers = {
+            "Authorization": "Bearer " + access_token,
+            "Content-Type": "application/json",
+        }
+        msg_type = "text"
+        logger.debug(f"[FeiShu] sending reply, type={context.type}, content={reply.content[:100]}...")
+        reply_content = reply.content
+        content_key = "text"
+        if reply.type == ReplyType.IMAGE_URL:
+            # 图片上传
+            reply_content = self._upload_image_url(reply.content, access_token)
+            if not reply_content:
+                logger.warning("[FeiShu] upload image failed")
+                return
+            msg_type = "image"
+            content_key = "image_key"
+        elif reply.type == ReplyType.FILE:
+            # 如果有附加的文本内容，先发送文本
+            if hasattr(reply, 'text_content') and reply.text_content:
+                logger.info(f"[FeiShu] Sending text before file: {reply.text_content[:50]}...")
+                text_reply = Reply(ReplyType.TEXT, reply.text_content)
+                self._send(text_reply, context)
+                import time
+                time.sleep(0.3)  # 短暂延迟，确保文本先到达
+
+            # 判断是否为视频文件
+            file_path = reply.content
+            if file_path.startswith("file://"):
+                file_path = file_path[7:]
+
+            is_video = file_path.lower().endswith(('.mp4', '.avi', '.mov', '.wmv', '.flv'))
+
+            if is_video:
+                # 视频上传（包含duration信息）
+                upload_data = self._upload_video_url(reply.content, access_token)
+                if not upload_data or not upload_data.get('file_key'):
+                    logger.warning("[FeiShu] upload video failed")
+                    return
+
+                # 视频使用 media 类型（根据官方文档）
+                # 错误码 230055 说明：上传 mp4 时必须使用 msg_type="media"
+                msg_type = "media"
+                reply_content = upload_data  # 完整的上传响应数据（包含file_key和duration）
+                logger.info(
+                    f"[FeiShu] Sending video: file_key={upload_data.get('file_key')}, duration={upload_data.get('duration')}ms")
+                content_key = None  # 直接序列化整个对象
+            else:
+                # 其他文件使用 file 类型
+                file_key = self._upload_file_url(reply.content, access_token)
+                if not file_key:
+                    logger.warning("[FeiShu] upload file failed")
+                    return
+                reply_content = file_key
+                msg_type = "file"
+                content_key = "file_key"
+
+        elif reply.type == ReplyType.VOICE:
+            # 语音回复：上传音频文件到飞书，然后发送 audio 类型消息
+            file_key = self._upload_audio(reply.content, access_token)
+            if not file_key:
+                logger.warning("[FeiShu] upload audio failed")
+                return
+            reply_content = file_key
+            msg_type = "audio"
+            content_key = "file_key"
+
+        # Check if we can reply to an existing message (need msg_id)
+        can_reply = is_group and msg and hasattr(msg, 'msg_id') and msg.msg_id
+
+        # Build content JSON
+        content_json = json.dumps(reply_content, ensure_ascii=False) if content_key is None else json.dumps({content_key: reply_content}, ensure_ascii=False)
+        logger.debug(f"[FeiShu] Sending message: msg_type={msg_type}, content={content_json[:200]}")
+
+        if can_reply:
+            # 群聊中回复已有消息
+            url = f"https://open.feishu.cn/open-apis/im/v1/messages/{msg.msg_id}/reply"
+            data = {
+                "msg_type": msg_type,
+                "content": content_json
+            }
+            res = requests.post(url=url, headers=headers, json=data, timeout=(5, 10))
+        else:
+            # 发送新消息（私聊或群聊中无msg_id的情况，如定时任务）
+            url = "https://open.feishu.cn/open-apis/im/v1/messages"
+            params = {"receive_id_type": context.get("receive_id_type") or "open_id"}
+            data = {
+                "receive_id": context.get("receiver"),
+                "msg_type": msg_type,
+                "content": content_json
+            }
+            res = requests.post(url=url, headers=headers, params=params, json=data, timeout=(5, 10))
+        res = res.json()
+        if res.get("code") == 0:
+            logger.info(f"[FeiShu] send message success")
+        else:
+            logger.error(f"[FeiShu] send message failed, code={res.get('code')}, msg={res.get('msg')}")
+
+    def _make_feishu_stream_callback(self, context, access_token):
+        """
+        基于飞书官方"流式更新卡片"API 实现打字机回复。
+
+        流程：
+        1. message_update 首次到达 → POST /cardkit/v1/cards 创建带 streaming_mode 的卡片实体，
+           随后用 POST /im/v1/messages（或 reply）以 card_id 把卡片发出去
+        2. 后续 message_update → PUT /cardkit/v1/cards/{id}/elements/{eid}/content
+           传入"当前轮"的全量文本，飞书平台自动计算增量并以打字机效果上屏
+           （流式模式下不受 10 QPS 限制）
+        3. message_end（一轮 LLM 输出结束，且本轮触发了工具调用）→ 把 current 累计到 committed
+           并加入分隔符；下一轮 message_update 又从空白开始，避免多轮内容串到一起
+        4. agent_end → 用 final_response 强制覆盖卡片，再 PATCH /cardkit/v1/cards/{id}/settings
+           关闭 streaming_mode，标记 context["feishu_streamed"]=True 让 chat_channel 跳过普通 send()
+
+        前提条件：
+        - 机器人已开通 cardkit:card:write 权限
+        - 飞书客户端 7.20+
+
+        失败降级：
+        - 创建卡片实体失败（缺权限、网络等）→ 不设置 feishu_streamed 标记，让 chat_channel
+          走普通文本回复路径，用户收到完整回复但无打字机效果，并打 warning 日志
+        """
+        # 共享状态（受 lock 保护）
+        # 多轮 agent 模式下，每个"中间过场消息"会作为一张独立卡片发送。
+        # current_text 只承载当前正在流式渲染的那张卡片的内容；message_end / agent_end
+        # 时会把它定型并 reset。
+        current_text = [""]                # 当前卡片正在累加的 LLM 输出
+        card_id = [None]                   # 当前流式卡片的实体 ID（每段独立）
+        message_id = [None]                # 当前卡片发送后的消息 ID（仅日志用）
+        # 占位发送是同步进行的，但用一个 in-flight 标记防止并发的多条 message_update
+        # 事件各自触发一次创建+发送，导致发出多张卡片。
+        init_in_flight = [False]
+        # 一旦初始化失败就长期标记为 disabled，本次回复不再尝试任何流式调用
+        disabled = [False]
+        # True after agent_cancelled: agent_end stops rewriting the card
+        # with stale final_response and just finalizes current content.
+        cancelled = [False]
+        lock = threading.Lock()
+
+        # ---- 异步推送队列 ----------------------------------------------------
+        # 同步 requests.put 单次 100~300ms，会阻塞 LLM stream 线程读下一个 chunk。
+        # 把推送丢给独立 worker 线程消费 queue，回调本身只做内存追加，立即返回。
+        # 队列里只放"最新累积文本"的快照；worker 用 deduplication 避免重复推同一个
+        # 内容（高频 chunk 场景下队列会堆积，只推最后一个就够了）。
+        import queue as _queue
+        push_queue: "_queue.Queue[str | None]" = _queue.Queue()
+
+        def _push_worker():
+            while True:
+                snapshot = push_queue.get()
+                if snapshot is None:
+                    push_queue.task_done()
+                    return
+                # 合并队列中已堆积的快照：只推最后一个，省 PUT 次数同时降低延迟
+                merged_count = 1
+                stop = False
+                while True:
+                    try:
+                        nxt = push_queue.get_nowait()
+                    except _queue.Empty:
+                        break
+                    merged_count += 1
+                    if nxt is None:
+                        stop = True
+                        break
+                    snapshot = nxt
+                try:
+                    _stream_update_text(snapshot)
+                finally:
+                    for _ in range(merged_count):
+                        push_queue.task_done()
+                if stop:
+                    return
+
+        push_thread = threading.Thread(target=_push_worker, daemon=True, name="feishu-stream-push")
+        push_thread.start()
+
+        def _drain_push_queue():
+            """等当前队列里所有 PUT 都完成。message_end/agent_end 在做最终定型前必须 drain，
+            否则 worker 里堆积的旧快照可能在 final_text PUT 之后到达，把最终内容覆盖掉。"""
+            try:
+                push_queue.join()
+            except Exception:
+                pass
+
+        msg = context.get("msg")
+        is_group = context.get("isgroup", False)
+        receiver = context.get("receiver")
+        receive_id_type = context.get("receive_id_type", "open_id")
+        # 客户端打字机渲染参数（飞书 App 侧实际"出字"速度）：
+        #   - print_freq_ms：每次刷新的间隔
+        #   - print_step：每次刷新出多少个字符
+        # 当前 40ms × 4 字 ≈ 100 字/秒，接近 ChatGPT/DeepSeek 网页端的节奏。
+        print_freq_ms = 40
+        print_step = 4
+        print_strategy = "fast"
+
+        headers = {
+            "Authorization": "Bearer " + access_token,
+            "Content-Type": "application/json; charset=utf-8",
+        }
+        # 卡片中富文本组件的 element_id，后续所有 PUT 流式更新都打到这个组件
+        ELEMENT_ID = "stream_md"
+        # 操作序号，每次 PUT 必须严格递增（飞书要求）
+        sequence = [0]
+
+        def _next_sequence():
+            sequence[0] += 1
+            return sequence[0]
+
+        def _build_card_json():
+            """卡片 JSON 2.0 结构 + streaming_mode + 单 markdown 组件"""
+            return json.dumps({
+                "schema": "2.0",
+                "config": {
+                    "streaming_mode": True,
+                    "summary": {"content": "[正在生成回复...]"},
+                    "streaming_config": {
+                        "print_frequency_ms": {"default": print_freq_ms},
+                        "print_step": {"default": print_step},
+                        "print_strategy": print_strategy,
+                    },
+                },
+                "body": {
+                    "elements": [
+                        {
+                            "tag": "markdown",
+                            "content": "...",
+                            "element_id": ELEMENT_ID,
+                        }
+                    ],
+                },
+                # 注意：JSON 2.0 不支持自定义 fallback 字段（传入会报错）。
+                # 客户端 < 7.20 时，飞书会自动展示"请升级客户端"占位，无需配置。
+            }, ensure_ascii=False)
+
+        def _create_and_send_card():
+            """同步执行：创建卡片实体 → 发送消息。任意一步失败则 disabled=True 触发降级"""
+            try:
+                # 步骤 1: 创建卡片实体
+                create_url = "https://open.feishu.cn/open-apis/cardkit/v1/cards"
+                create_body = {"type": "card_json", "data": _build_card_json()}
+                res = requests.post(
+                    create_url, headers=headers, json=create_body, timeout=(5, 10)
+                )
+                res_json = res.json()
+                if res_json.get("code") != 0:
+                    logger.warning(
+                        f"[FeiShu] Stream: create card failed "
+                        f"(code={res_json.get('code')}, msg={res_json.get('msg')}). "
+                        f"本次回复已自动降级为普通文本回复（一次性返回完整内容）。"
+                        f"如需开启流式打字机效果与完整 Markdown 渲染，请到飞书开放平台 "
+                        f"https://open.feishu.cn/app 给机器人开通 cardkit:card:write 权限"
+                        f"（创建与更新卡片）并重新发布版本，同时确保飞书客户端 >= 7.20。"
+                    )
+                    with lock:
+                        disabled[0] = True
+                    return
+                cid = res_json["data"]["card_id"]
+                with lock:
+                    card_id[0] = cid
+
+                # 步骤 2: 通过 card_id 发送消息（群聊优先用 reply，单聊直接 send）
+                content_payload = json.dumps(
+                    {"type": "card", "data": {"card_id": cid}}, ensure_ascii=False
+                )
+                can_reply = is_group and msg and hasattr(msg, "msg_id") and msg.msg_id
+                if can_reply:
+                    send_url = (
+                        f"https://open.feishu.cn/open-apis/im/v1/messages/"
+                        f"{msg.msg_id}/reply"
+                    )
+                    send_body = {"msg_type": "interactive", "content": content_payload}
+                    send_res = requests.post(
+                        send_url, headers=headers, json=send_body, timeout=(5, 10)
+                    )
+                else:
+                    send_url = "https://open.feishu.cn/open-apis/im/v1/messages"
+                    params = {"receive_id_type": receive_id_type}
+                    send_body = {
+                        "receive_id": receiver,
+                        "msg_type": "interactive",
+                        "content": content_payload,
+                    }
+                    send_res = requests.post(
+                        send_url, headers=headers, params=params, json=send_body,
+                        timeout=(5, 10),
+                    )
+                send_json = send_res.json()
+                if send_json.get("code") != 0:
+                    logger.warning(
+                        f"[FeiShu] Stream: send card failed: {send_json}. 降级为普通文本。"
+                    )
+                    with lock:
+                        disabled[0] = True
+                    return
+                mid = send_json["data"]["message_id"]
+                with lock:
+                    message_id[0] = mid
+                logger.info(
+                    f"[FeiShu] Stream: card created and sent, "
+                    f"card_id={cid}, message_id={mid}"
+                )
+            except Exception as e:
+                logger.warning(
+                    f"[FeiShu] Stream: create/send card exception: {e}. 降级为普通文本。"
+                )
+                with lock:
+                    disabled[0] = True
+            finally:
+                with lock:
+                    init_in_flight[0] = False
+
+        def _stream_update_text(full_text):
+            """PUT 流式更新文本组件。content 必须是当前组件的全量文本。"""
+            with lock:
+                cid = card_id[0]
+            if not cid:
+                return
+            url = (
+                f"https://open.feishu.cn/open-apis/cardkit/v1/cards/"
+                f"{cid}/elements/{ELEMENT_ID}/content"
+            )
+            body = {
+                "content": full_text,
+                "sequence": _next_sequence(),
+            }
+            try:
+                res = requests.put(url, headers=headers, json=body, timeout=(5, 10))
+                res_json = res.json()
+                if res_json.get("code") != 0:
+                    logger.warning(
+                        f"[FeiShu] Stream: update text failed: {res_json}"
+                    )
+            except Exception as e:
+                logger.warning(f"[FeiShu] Stream: update text exception: {e}")
+
+        def _close_streaming_mode(final_text: str = ""):
+            """关闭流式模式（卡片转入"普通"状态，可被转发）。
+
+            同时通过整卡更新接口把 summary 改成最终内容的预览，否则飞书会话列表
+            会一直显示创建卡片时的占位摘要（"[正在生成回复...]"）。
+            """
+            with lock:
+                cid = card_id[0]
+            if not cid:
+                return
+
+            # 1) 通过整卡更新接口把 streaming_mode 关掉，并改写 summary
+            #    （settings 接口的 config 不接受 summary 字段，会报 code=2200）
+            preview_src = (final_text or "").strip().replace("\n", " ")
+            preview = preview_src[:30] if preview_src else ""
+            full_card = {
+                "schema": "2.0",
+                "config": {
+                    "streaming_mode": False,
+                    "summary": {"content": preview or " "},
+                },
+                "body": {
+                    "elements": [
+                        {
+                            "tag": "markdown",
+                            "content": final_text or " ",
+                            "element_id": ELEMENT_ID,
+                        }
+                    ],
+                },
+            }
+            put_url = f"https://open.feishu.cn/open-apis/cardkit/v1/cards/{cid}"
+            put_body = {
+                "card": {"type": "card_json", "data": json.dumps(full_card, ensure_ascii=False)},
+                "sequence": _next_sequence(),
+            }
+            try:
+                res = requests.put(put_url, headers=headers, json=put_body, timeout=(5, 10))
+                res_json = res.json()
+                if res_json.get("code") != 0:
+                    logger.warning(
+                        f"[FeiShu] Stream: finalize card (close+summary) failed: {res_json}"
+                    )
+            except Exception as e:
+                logger.warning(
+                    f"[FeiShu] Stream: finalize card exception: {e}"
+                )
+
+        def on_event(event: dict):
+            event_type = event.get("type")
+            data = event.get("data", {})
+
+            # 一旦降级，本次回复不再做任何流式操作
+            with lock:
+                if disabled[0]:
+                    return
+
+            if event_type == "message_update":
+                delta = data.get("delta", "")
+                if not delta:
+                    return
+
+                # 第一段：判断是否需要初始化（创建卡片 + 发送）
+                need_init = False
+                with lock:
+                    if card_id[0] is None and not init_in_flight[0]:
+                        init_in_flight[0] = True
+                        need_init = True
+
+                if need_init:
+                    _create_and_send_card()
+                    # 初始化失败已标记 disabled，下次循环直接 return
+                    with lock:
+                        if disabled[0]:
+                            return
+
+                # 第二段：累加文本，把快照丢给 push worker 异步推送。
+                # 这里不能直接 requests.put，否则会阻塞 LLM stream 线程读下一个 chunk
+                # （实测 DeepSeek 高频小 chunk 场景每个 PUT ~150ms，累积起来非常卡）。
+                snapshot = ""
+                should_push = False
+                with lock:
+                    current_text[0] += delta
+                    if card_id[0]:
+                        snapshot = current_text[0]
+                        should_push = True
+
+                if should_push:
+                    push_queue.put(snapshot)
+
+            elif event_type == "message_end":
+                # 一轮 LLM 输出结束。如果本轮触发了工具调用，说明当前轮的文本是
+                # "中间过场消息"（如"来看看！"），应该作为独立卡片定型，然后为下一轮
+                # 重新创建一张新卡片。这样最终用户看到的是：
+                #   [卡片1: 中间过场1]
+                #   [卡片2: 中间过场2]
+                #   ...
+                #   [卡片N: 最终回复]
+                # 与 wecom_bot 的多消息流式体验对齐。
+                tool_calls = data.get("tool_calls", []) or []
+                if not tool_calls:
+                    # 没有工具调用：本轮即最终回复，留给 agent_end 统一处理。
+                    return
+
+                with lock:
+                    text_to_finalize = current_text[0].rstrip()
+                    current_text[0] = ""
+
+                if not text_to_finalize:
+                    return
+
+                # 等异步队列里堆积的快照都推完，避免它们晚于 final 文本到达把内容覆盖掉
+                _drain_push_queue()
+                # 用最终文本覆盖当前卡片并关闭流式模式（凝固成普通卡片，
+                # 同时把会话列表的 summary 改成预览，不再显示"正在生成回复..."）
+                _stream_update_text(text_to_finalize)
+                _close_streaming_mode(text_to_finalize)
+
+                # 重置卡片状态，下一段 message_update 会触发新卡片的创建
+                with lock:
+                    card_id[0] = None
+                    message_id[0] = None
+                    sequence[0] = 0
+
+            elif event_type == "agent_cancelled":
+                # Lock channel into "no-rewrite" mode: the subsequent
+                # agent_end's final_response is from the last *completed*
+                # turn (the user already saw it), so rewriting the card
+                # would duplicate it visually.
+                with lock:
+                    cancelled[0] = True
+
+            elif event_type == "agent_end":
+                # 最终回复：用 final_response 覆盖当前流式卡片，然后关闭流式模式。
+                final_response = data.get("final_response", "")
+                # 标记 streamed 让 chat_channel 跳过 send()
+                context["feishu_streamed"] = True
+
+                with lock:
+                    was_cancelled = cancelled[0]
+                    has_card = card_id[0] is not None
+                    init_busy = init_in_flight[0]
+                    pending_text = current_text[0]
+
+                if was_cancelled:
+                    # Cancelled path: finalize the in-flight card with
+                    # partial output (or a short marker if empty); drop
+                    # stale final_response to avoid duplicating last turn.
+                    if has_card:
+                        _drain_push_queue()
+                        partial = (pending_text or "").rstrip()
+                        final_text = partial or "_(已中止)_"
+                        _stream_update_text(final_text)
+                        _close_streaming_mode(final_text)
+                    push_queue.put(None)
+                    return
+
+                if not final_response:
+                    return
+                final_text = str(final_response)
+
+                # 罕见情况：agent_end 触发时还没创建过卡片（极快返回 / 没有
+                # message_update），主动创建一张承载 final_text。
+                if not has_card and not init_busy:
+                    with lock:
+                        init_in_flight[0] = True
+                    _create_and_send_card()
+                    with lock:
+                        if disabled[0]:
+                            return
+
+                _drain_push_queue()
+                _stream_update_text(final_text)
+                _close_streaming_mode(final_text)
+                # 通知 push worker 退出（本次回复彻底结束）
+                push_queue.put(None)
+
+        return on_event
+
+    def fetch_access_token(self) -> str:
+        url = "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal/"
+        headers = {
+            "Content-Type": "application/json"
+        }
+        req_body = {
+            "app_id": self.feishu_app_id,
+            "app_secret": self.feishu_app_secret
+        }
+        data = bytes(json.dumps(req_body), encoding='utf8')
+        response = requests.post(url=url, data=data, headers=headers)
+        if response.status_code == 200:
+            res = response.json()
+            if res.get("code") != 0:
+                logger.error(f"[FeiShu] get tenant_access_token error, code={res.get('code')}, msg={res.get('msg')}")
+                return ""
+            else:
+                return res.get("tenant_access_token")
+        else:
+            logger.error(f"[FeiShu] fetch token error, res={response}")
+
+    def _upload_image_url(self, img_url, access_token):
+        logger.debug(f"[FeiShu] start process image, img_url={img_url}")
+
+        # Check if it's a local file path (file:// protocol)
+        if img_url.startswith("file://"):
+            local_path = img_url[7:]  # Remove "file://" prefix
+            logger.info(f"[FeiShu] uploading local file: {local_path}")
+
+            if not os.path.exists(local_path):
+                logger.error(f"[FeiShu] local file not found: {local_path}")
+                return None
+
+            # Upload directly from local file
+            upload_url = "https://open.feishu.cn/open-apis/im/v1/images"
+            data = {'image_type': 'message'}
+            headers = {'Authorization': f'Bearer {access_token}'}
+
+            with open(local_path, "rb") as file:
+                upload_response = requests.post(upload_url, files={"image": file}, data=data, headers=headers)
+                logger.info(f"[FeiShu] upload file, res={upload_response.content}")
+
+                response_data = upload_response.json()
+                if response_data.get("code") == 0:
+                    return response_data.get("data").get("image_key")
+                else:
+                    logger.error(f"[FeiShu] upload failed: {response_data}")
+                    return None
+
+        # Original logic for HTTP URLs
+        response = requests.get(img_url)
+        suffix = utils.get_path_suffix(img_url)
+        temp_name = str(uuid.uuid4()) + "." + suffix
+        if response.status_code == 200:
+            # 将图片内容保存为临时文件
+            with open(temp_name, "wb") as file:
+                file.write(response.content)
+
+        # upload
+        upload_url = "https://open.feishu.cn/open-apis/im/v1/images"
+        data = {
+            'image_type': 'message'
+        }
+        headers = {
+            'Authorization': f'Bearer {access_token}',
+        }
+        with open(temp_name, "rb") as file:
+            upload_response = requests.post(upload_url, files={"image": file}, data=data, headers=headers)
+            logger.info(f"[FeiShu] upload file, res={upload_response.content}")
+            os.remove(temp_name)
+            return upload_response.json().get("data").get("image_key")
+
+    def _get_video_duration(self, file_path: str) -> int:
+        """
+        获取视频时长（毫秒）
+        
+        Args:
+            file_path: 视频文件路径
+        
+        Returns:
+            视频时长（毫秒），如果获取失败返回0
+        """
+        try:
+            import subprocess
+
+            # 使用 ffprobe 获取视频时长
+            cmd = [
+                'ffprobe',
+                '-v', 'error',
+                '-show_entries', 'format=duration',
+                '-of', 'default=noprint_wrappers=1:nokey=1',
+                file_path
+            ]
+
+            result = subprocess.run(cmd, capture_output=True, text=True, timeout=10)
+            if result.returncode == 0:
+                duration_seconds = float(result.stdout.strip())
+                duration_ms = int(duration_seconds * 1000)
+                logger.info(f"[FeiShu] Video duration: {duration_seconds:.2f}s ({duration_ms}ms)")
+                return duration_ms
+            else:
+                logger.warning(f"[FeiShu] Failed to get video duration via ffprobe: {result.stderr}")
+                return 0
+        except FileNotFoundError:
+            logger.warning("[FeiShu] ffprobe not found, video duration will be 0. Install ffmpeg to fix this.")
+            return 0
+        except Exception as e:
+            logger.warning(f"[FeiShu] Failed to get video duration: {e}")
+            return 0
+
+    def _upload_video_url(self, video_url, access_token):
+        """
+        Upload video to Feishu and return video info (file_key and duration)
+        Supports:
+        - file:// URLs for local files
+        - http(s):// URLs (download then upload)
+        
+        Returns:
+            dict with 'file_key' and 'duration' (milliseconds), or None if failed
+        """
+        local_path = None
+        temp_file = None
+
+        try:
+            # For file:// URLs (local files), upload directly
+            if video_url.startswith("file://"):
+                local_path = video_url[7:]  # Remove file:// prefix
+                if not os.path.exists(local_path):
+                    logger.error(f"[FeiShu] local video file not found: {local_path}")
+                    return None
+            else:
+                # For HTTP URLs, download first
+                logger.info(f"[FeiShu] Downloading video from URL: {video_url}")
+                response = requests.get(video_url, timeout=(5, 60))
+                if response.status_code != 200:
+                    logger.error(f"[FeiShu] download video failed, status={response.status_code}")
+                    return None
+
+                # Save to temp file
+                import uuid
+                file_name = os.path.basename(video_url) or "video.mp4"
+                temp_file = str(uuid.uuid4()) + "_" + file_name
+
+                with open(temp_file, "wb") as file:
+                    file.write(response.content)
+
+                logger.info(f"[FeiShu] Video downloaded, size={len(response.content)} bytes")
+                local_path = temp_file
+
+            # Get video duration
+            duration = self._get_video_duration(local_path)
+
+            # Upload to Feishu
+            file_name = os.path.basename(local_path)
+            file_ext = os.path.splitext(file_name)[1].lower()
+            file_type_map = {'.mp4': 'mp4'}
+            file_type = file_type_map.get(file_ext, 'mp4')
+
+            upload_url = "https://open.feishu.cn/open-apis/im/v1/files"
+            data = {
+                'file_type': file_type,
+                'file_name': file_name
+            }
+            # Add duration only if available (required for video/audio)
+            if duration:
+                data['duration'] = duration  # Must be int, not string
+
+            headers = {'Authorization': f'Bearer {access_token}'}
+
+            logger.info(f"[FeiShu] Uploading video: file_name={file_name}, duration={duration}ms")
+
+            with open(local_path, "rb") as file:
+                upload_response = requests.post(
+                    upload_url,
+                    files={"file": file},
+                    data=data,
+                    headers=headers,
+                    timeout=(5, 60)
+                )
+                logger.info(
+                    f"[FeiShu] upload video response, status={upload_response.status_code}, res={upload_response.content}")
+
+                response_data = upload_response.json()
+                if response_data.get("code") == 0:
+                    # Add duration to the response data (API doesn't return it)
+                    upload_data = response_data.get("data")
+                    upload_data['duration'] = duration  # Add our calculated duration
+                    logger.info(
+                        f"[FeiShu] Upload complete: file_key={upload_data.get('file_key')}, duration={duration}ms")
+                    return upload_data
+                else:
+                    logger.error(f"[FeiShu] upload video failed: {response_data}")
+                    return None
+
+        except Exception as e:
+            logger.error(f"[FeiShu] upload video exception: {e}")
+            return None
+
+        finally:
+            # Clean up temp file
+            if temp_file and os.path.exists(temp_file):
+                try:
+                    os.remove(temp_file)
+                except Exception as e:
+                    logger.warning(f"[FeiShu] Failed to remove temp file {temp_file}: {e}")
+
+    def _upload_audio(self, audio_path, access_token):
+        """
+        Upload a local audio file to Feishu and return file_key.
+        audio_path is a plain local file path (no file:// prefix).
+        Feishu audio messages only support opus format; non-opus files are converted first.
+        """
+        logger.debug(f"[FeiShu] start upload audio, path={audio_path}")
+
+        if not os.path.exists(audio_path):
+            logger.error(f"[FeiShu] audio file not found: {audio_path}")
+            return None
+
+        # Feishu only plays audio messages in opus format.
+        # Convert if the TTS engine produced a different format (e.g. mp3 from OpenAI TTS).
+        upload_path = audio_path
+        if not audio_path.lower().endswith('.opus'):
+            opus_path = os.path.splitext(audio_path)[0] + '.opus'
+            try:
+                from pydub import AudioSegment
+                audio = AudioSegment.from_file(audio_path)
+                audio.export(opus_path, format='opus')
+                upload_path = opus_path
+                logger.info(f"[FeiShu] Converted audio to opus: {opus_path}")
+            except Exception as e:
+                logger.warning(f"[FeiShu] Failed to convert audio to opus, uploading original: {e}")
+                upload_path = audio_path
+
+        file_name = os.path.splitext(os.path.basename(upload_path))[0] + '.opus'
+        upload_url = "https://open.feishu.cn/open-apis/im/v1/files"
+        data = {'file_type': 'opus', 'file_name': file_name}
+        headers = {'Authorization': f'Bearer {access_token}'}
+
+        try:
+            with open(upload_path, "rb") as f:
+                upload_response = requests.post(
+                    upload_url,
+                    files={"file": f},
+                    data=data,
+                    headers=headers,
+                    timeout=(5, 30)
+                )
+                logger.info(
+                    f"[FeiShu] upload audio response, status={upload_response.status_code}, res={upload_response.content}")
+                response_data = upload_response.json()
+                if response_data.get("code") == 0:
+                    return response_data.get("data").get("file_key")
+                else:
+                    logger.error(f"[FeiShu] upload audio failed: {response_data}")
+                    return None
+        except Exception as e:
+            logger.error(f"[FeiShu] upload audio exception: {e}")
+            return None
+        finally:
+            # 无论上传成功与否都清理转换产生的临时 opus 文件，避免失败路径下磁盘堆积。
+            if upload_path != audio_path and os.path.exists(upload_path):
+                try:
+                    os.remove(upload_path)
+                except Exception as e:
+                    logger.warning(f"[FeiShu] Failed to remove temp opus file {upload_path}: {e}")
+
+    def _upload_file_url(self, file_url, access_token):
+        """
+        Upload file to Feishu
+        Supports both local files (file://) and HTTP URLs
+        """
+        logger.debug(f"[FeiShu] start process file, file_url={file_url}")
+
+        # Check if it's a local file path (file:// protocol)
+        if file_url.startswith("file://"):
+            local_path = file_url[7:]  # Remove "file://" prefix
+            logger.info(f"[FeiShu] uploading local file: {local_path}")
+
+            if not os.path.exists(local_path):
+                logger.error(f"[FeiShu] local file not found: {local_path}")
+                return None
+
+            # Get file info
+            file_name = os.path.basename(local_path)
+            file_ext = os.path.splitext(file_name)[1].lower()
+
+            # Determine file type for Feishu API
+            # Feishu supports: opus, mp4, pdf, doc, xls, ppt, stream (other types)
+            file_type_map = {
+                '.opus': 'opus',
+                '.mp4': 'mp4',
+                '.pdf': 'pdf',
+                '.doc': 'doc', '.docx': 'doc',
+                '.xls': 'xls', '.xlsx': 'xls',
+                '.ppt': 'ppt', '.pptx': 'ppt',
+            }
+            file_type = file_type_map.get(file_ext, 'stream')  # Default to stream for other types
+
+            # Upload file to Feishu
+            upload_url = "https://open.feishu.cn/open-apis/im/v1/files"
+            data = {'file_type': file_type, 'file_name': file_name}
+            headers = {'Authorization': f'Bearer {access_token}'}
+
+            try:
+                with open(local_path, "rb") as file:
+                    upload_response = requests.post(
+                        upload_url,
+                        files={"file": file},
+                        data=data,
+                        headers=headers,
+                        timeout=(5, 30)  # 5s connect, 30s read timeout
+                    )
+                    logger.info(
+                        f"[FeiShu] upload file response, status={upload_response.status_code}, res={upload_response.content}")
+
+                    response_data = upload_response.json()
+                    if response_data.get("code") == 0:
+                        return response_data.get("data").get("file_key")
+                    else:
+                        logger.error(f"[FeiShu] upload file failed: {response_data}")
+                        return None
+            except Exception as e:
+                logger.error(f"[FeiShu] upload file exception: {e}")
+                return None
+
+        # For HTTP URLs, download first then upload
+        try:
+            response = requests.get(file_url, timeout=(5, 30))
+            if response.status_code != 200:
+                logger.error(f"[FeiShu] download file failed, status={response.status_code}")
+                return None
+
+            # Save to temp file
+            import uuid
+            file_name = os.path.basename(file_url)
+            temp_name = str(uuid.uuid4()) + "_" + file_name
+
+            with open(temp_name, "wb") as file:
+                file.write(response.content)
+
+            # Upload
+            file_ext = os.path.splitext(file_name)[1].lower()
+            file_type_map = {
+                '.opus': 'opus', '.mp4': 'mp4', '.pdf': 'pdf',
+                '.doc': 'doc', '.docx': 'doc',
+                '.xls': 'xls', '.xlsx': 'xls',
+                '.ppt': 'ppt', '.pptx': 'ppt',
+            }
+            file_type = file_type_map.get(file_ext, 'stream')
+
+            upload_url = "https://open.feishu.cn/open-apis/im/v1/files"
+            data = {'file_type': file_type, 'file_name': file_name}
+            headers = {'Authorization': f'Bearer {access_token}'}
+
+            with open(temp_name, "rb") as file:
+                upload_response = requests.post(upload_url, files={"file": file}, data=data, headers=headers)
+                logger.info(f"[FeiShu] upload file, res={upload_response.content}")
+
+                response_data = upload_response.json()
+                os.remove(temp_name)  # Clean up temp file
+
+                if response_data.get("code") == 0:
+                    return response_data.get("data").get("file_key")
+                else:
+                    logger.error(f"[FeiShu] upload file failed: {response_data}")
+                    return None
+        except Exception as e:
+            logger.error(f"[FeiShu] upload file from URL exception: {e}")
+            return None
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+
+        # Set session_id based on chat type
+        if cmsg.is_group:
+            # Group chat: check if group_shared_session is enabled
+            if conf().get("group_shared_session", True):
+                # All users in the group share the same session context
+                context["session_id"] = cmsg.other_user_id  # group_id
+            else:
+                # Each user has their own session within the group
+                # This ensures:
+                # - Same user in different groups have separate conversation histories
+                # - Same user in private chat and group chat have separate histories
+                context["session_id"] = f"{cmsg.from_user_id}:{cmsg.other_user_id}"
+        else:
+            # Private chat: use user_id only
+            context["session_id"] = cmsg.from_user_id
+
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            # 1.文本请求
+            # 图片生成处理
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = content.strip()
+            # Text input opts into voice replies only when the always-on toggle is set.
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        elif context.type == ContextType.VOICE:
+            # 2.语音请求: voice input replies with voice if either
+            # voice_reply_voice (mirror reply) or always_reply_voice is on.
+            if "desire_rtype" not in context and (
+                conf().get("voice_reply_voice") or conf().get("always_reply_voice")
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+
+class FeishuController:
+    """
+    HTTP服务器控制器，用于webhook模式
+    """
+    # 类常量
+    FAILED_MSG = '{"success": false}'
+    SUCCESS_MSG = '{"success": true}'
+    MESSAGE_RECEIVE_TYPE = "im.message.receive_v1"
+
+    def GET(self):
+        return "Feishu service start success!"
+
+    def POST(self):
+        try:
+            channel = FeiShuChanel()
+
+            request = json.loads(web.data().decode("utf-8"))
+            logger.debug(f"[FeiShu] receive request: {request}")
+
+            # 1.事件订阅回调验证
+            if request.get("type") == URL_VERIFICATION:
+                varify_res = {"challenge": request.get("challenge")}
+                return json.dumps(varify_res)
+
+            # 2.消息接收处理
+            # token 校验
+            header = request.get("header")
+            if not header or header.get("token") != channel.feishu_token:
+                return self.FAILED_MSG
+
+            # 处理消息事件
+            event = request.get("event")
+            if header.get("event_type") == self.MESSAGE_RECEIVE_TYPE and event:
+                channel._handle_message_event(event)
+
+            return self.SUCCESS_MSG
+
+        except Exception as e:
+            logger.error(e)
+            return self.FAILED_MSG
diff --git a/channel/feishu/feishu_message.py b/channel/feishu/feishu_message.py
new file mode 100644
index 0000000..ea6ba27
--- /dev/null
+++ b/channel/feishu/feishu_message.py
@@ -0,0 +1,222 @@
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+import json
+import os
+import requests
+from common.log import logger
+from common.tmp_dir import TmpDir
+from common import utils
+from common.utils import expand_path
+from config import conf
+
+
+class FeishuMessage(ChatMessage):
+    def __init__(self, event: dict, is_group=False, access_token=None):
+        super().__init__(event)
+        msg = event.get("message")
+        sender = event.get("sender")
+        self.access_token = access_token
+        self.msg_id = msg.get("message_id")
+        self.create_time = msg.get("create_time")
+        self.is_group = is_group
+        msg_type = msg.get("message_type")
+
+        if msg_type == "text":
+            self.ctype = ContextType.TEXT
+            content = json.loads(msg.get('content'))
+            self.content = content.get("text").strip()
+        elif msg_type == "image":
+            # 单张图片消息：下载并缓存，等待用户提问时一起发送
+            self.ctype = ContextType.IMAGE
+            content = json.loads(msg.get("content"))
+            image_key = content.get("image_key")
+            
+            # 下载图片到工作空间临时目录
+            workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+            tmp_dir = os.path.join(workspace_root, "tmp")
+            os.makedirs(tmp_dir, exist_ok=True)
+            image_path = os.path.join(tmp_dir, f"{image_key}.png")
+            
+            # 下载图片
+            url = f"https://open.feishu.cn/open-apis/im/v1/messages/{msg.get('message_id')}/resources/{image_key}"
+            headers = {"Authorization": "Bearer " + access_token}
+            params = {"type": "image"}
+            response = requests.get(url=url, headers=headers, params=params)
+            
+            if response.status_code == 200:
+                with open(image_path, "wb") as f:
+                    f.write(response.content)
+                logger.info(f"[FeiShu] Downloaded single image, key={image_key}, path={image_path}")
+                self.content = image_path
+                self.image_path = image_path  # 保存图片路径
+            else:
+                logger.error(f"[FeiShu] Failed to download single image, key={image_key}, status={response.status_code}")
+                self.content = f"[图片下载失败: {image_key}]"
+                self.image_path = None
+        elif msg_type == "post":
+            # 富文本消息，可能包含图片、文本等多种元素
+            content = json.loads(msg.get("content"))
+            
+            # 飞书富文本消息结构：content 直接包含 title 和 content 数组
+            # 不是嵌套在 post 字段下
+            title = content.get("title", "")
+            content_list = content.get("content", [])
+            
+            logger.info(f"[FeiShu] Post message - title: '{title}', content_list length: {len(content_list)}")
+            
+            # 收集所有图片和文本
+            image_keys = []
+            text_parts = []
+            
+            if title:
+                text_parts.append(title)
+            
+            for block in content_list:
+                logger.debug(f"[FeiShu] Processing block: {block}")
+                # block 本身就是元素列表
+                if not isinstance(block, list):
+                    continue
+                    
+                for element in block:
+                    element_tag = element.get("tag")
+                    logger.debug(f"[FeiShu] Element tag: {element_tag}, element: {element}")
+                    if element_tag == "img":
+                        # 找到图片元素
+                        image_key = element.get("image_key")
+                        if image_key:
+                            image_keys.append(image_key)
+                    elif element_tag == "text":
+                        # 文本元素
+                        text_content = element.get("text", "")
+                        if text_content:
+                            text_parts.append(text_content)
+            
+            logger.info(f"[FeiShu] Parsed - images: {len(image_keys)}, text_parts: {text_parts}")
+            
+            # 富文本消息统一作为文本消息处理
+            self.ctype = ContextType.TEXT
+            
+            if image_keys:
+                # 如果包含图片，下载并在文本中引用本地路径
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                tmp_dir = os.path.join(workspace_root, "tmp")
+                os.makedirs(tmp_dir, exist_ok=True)
+                
+                # 保存图片路径映射
+                self.image_paths = {}
+                for image_key in image_keys:
+                    image_path = os.path.join(tmp_dir, f"{image_key}.png")
+                    self.image_paths[image_key] = image_path
+                
+                def _download_images():
+                    for image_key, image_path in self.image_paths.items():
+                        url = f"https://open.feishu.cn/open-apis/im/v1/messages/{self.msg_id}/resources/{image_key}"
+                        headers = {"Authorization": "Bearer " + access_token}
+                        params = {"type": "image"}
+                        response = requests.get(url=url, headers=headers, params=params)
+                        if response.status_code == 200:
+                            with open(image_path, "wb") as f:
+                                f.write(response.content)
+                            logger.info(f"[FeiShu] Image downloaded from post message, key={image_key}, path={image_path}")
+                        else:
+                            logger.error(f"[FeiShu] Failed to download image from post, key={image_key}, status={response.status_code}")
+                
+                # 立即下载图片，不使用延迟下载
+                # 因为 TEXT 类型消息不会调用 prepare()
+                _download_images()
+                
+                # 构建消息内容：文本 + 图片路径
+                content_parts = []
+                if text_parts:
+                    content_parts.append("\n".join(text_parts).strip())
+                for image_key, image_path in self.image_paths.items():
+                    content_parts.append(f"[图片: {image_path}]")
+                
+                self.content = "\n".join(content_parts)
+                logger.info(f"[FeiShu] Received post message with {len(image_keys)} image(s) and text: {self.content}")
+            else:
+                # 纯文本富文本消息
+                self.content = "\n".join(text_parts).strip() if text_parts else "[富文本消息]"
+                logger.info(f"[FeiShu] Received post message (text only): {self.content}")
+        elif msg_type == "file":
+            self.ctype = ContextType.FILE
+            content = json.loads(msg.get("content"))
+            file_key = content.get("file_key")
+            file_name = content.get("file_name")
+
+            # 落到 agent_workspace/tmp 下（绝对路径），与图片处理一致；
+            # 否则相对路径 ./tmp 在 agent 工作区里 read 时会找不到。
+            workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+            tmp_dir = os.path.join(workspace_root, "tmp")
+            os.makedirs(tmp_dir, exist_ok=True)
+            self.content = os.path.join(
+                tmp_dir, f"{file_key}.{utils.get_path_suffix(file_name)}"
+            )
+
+            def _download_file():
+                # 如果响应状态码是200，则将响应内容写入本地文件
+                url = f"https://open.feishu.cn/open-apis/im/v1/messages/{self.msg_id}/resources/{file_key}"
+                headers = {
+                    "Authorization": "Bearer " + access_token,
+                }
+                params = {
+                    "type": "file"
+                }
+                response = requests.get(url=url, headers=headers, params=params)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[FeiShu] Failed to download file, key={file_key}, res={response.text}")
+            self._prepare_fn = _download_file
+        elif msg_type == "audio":
+            # 飞书用户发送的语音消息类型为 "audio"，文件为 opus 编码格式。
+            # 映射为 ContextType.VOICE，交由 chat_channel 的语音转文字（STT）流程处理。
+            # 文件通过 _prepare_fn 延迟下载，在 chat_channel 调用 cmsg.prepare() 时才执行。
+            self.ctype = ContextType.VOICE
+            content = json.loads(msg.get("content"))
+            file_key = content.get("file_key")
+
+            # 落到 agent_workspace/tmp 下（绝对路径），保证语音 STT 流程可读到
+            workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+            tmp_dir = os.path.join(workspace_root, "tmp")
+            os.makedirs(tmp_dir, exist_ok=True)
+            self.content = os.path.join(tmp_dir, f"{file_key}.opus")
+            logger.info(f"[FeiShu] audio message: file_key={file_key}, save_path={self.content}")
+
+            def _download_audio():
+                logger.info(f"[FeiShu] downloading audio: file_key={file_key}, msg_id={self.msg_id}")
+                url = f"https://open.feishu.cn/open-apis/im/v1/messages/{self.msg_id}/resources/{file_key}"
+                headers = {
+                    "Authorization": "Bearer " + access_token,
+                }
+                params = {
+                    "type": "file"
+                }
+                try:
+                    response = requests.get(url=url, headers=headers, params=params)
+                    logger.info(f"[FeiShu] download audio response: status={response.status_code}, size={len(response.content)} bytes")
+                    if response.status_code == 200:
+                        with open(self.content, "wb") as f:
+                            f.write(response.content)
+                        logger.info(f"[FeiShu] audio saved to: {self.content}")
+                    else:
+                        logger.error(f"[FeiShu] Failed to download audio, key={file_key}, status={response.status_code}, res={response.text}")
+                except Exception as e:
+                    logger.error(f"[FeiShu] Exception downloading audio, key={file_key}: {e}", exc_info=True)
+            self._prepare_fn = _download_audio
+        else:
+            raise NotImplementedError("Unsupported message type: Type:{} ".format(msg_type))
+
+        self.from_user_id = sender.get("sender_id").get("open_id")
+        self.to_user_id = event.get("app_id")
+        if is_group:
+            # 群聊
+            self.other_user_id = msg.get("chat_id")
+            self.actual_user_id = self.from_user_id
+            self.content = self.content.replace("@_user_1", "").strip()
+            self.actual_user_nickname = ""
+        else:
+            # 私聊
+            self.other_user_id = self.from_user_id
+            self.actual_user_id = self.from_user_id
diff --git a/channel/file_cache.py b/channel/file_cache.py
new file mode 100644
index 0000000..b258b66
--- /dev/null
+++ b/channel/file_cache.py
@@ -0,0 +1,100 @@
+"""
+文件缓存管理器
+用于缓存单独发送的文件消息（图片、视频、文档等），在用户提问时自动附加
+"""
+import time
+import logging
+
+logger = logging.getLogger(__name__)
+
+
+class FileCache:
+    """文件缓存管理器，按 session_id 缓存文件，TTL=2分钟"""
+    
+    def __init__(self, ttl=120):
+        """
+        Args:
+            ttl: 缓存过期时间（秒），默认2分钟
+        """
+        self.cache = {}
+        self.ttl = ttl
+    
+    def add(self, session_id: str, file_path: str, file_type: str = "image"):
+        """
+        添加文件到缓存
+        
+        Args:
+            session_id: 会话ID
+            file_path: 文件本地路径
+            file_type: 文件类型（image, video, file 等）
+        """
+        if session_id not in self.cache:
+            self.cache[session_id] = {
+                'files': [],
+                'timestamp': time.time()
+            }
+        
+        # 添加文件（去重）
+        file_info = {'path': file_path, 'type': file_type}
+        if file_info not in self.cache[session_id]['files']:
+            self.cache[session_id]['files'].append(file_info)
+            logger.info(f"[FileCache] Added {file_type} to cache for session {session_id}: {file_path}")
+    
+    def get(self, session_id: str) -> list:
+        """
+        获取缓存的文件列表
+        
+        Args:
+            session_id: 会话ID
+        
+        Returns:
+            文件信息列表 [{'path': '...', 'type': 'image'}, ...]，如果没有或已过期返回空列表
+        """
+        if session_id not in self.cache:
+            return []
+        
+        item = self.cache[session_id]
+        
+        # 检查是否过期
+        if time.time() - item['timestamp'] > self.ttl:
+            logger.info(f"[FileCache] Cache expired for session {session_id}, clearing...")
+            del self.cache[session_id]
+            return []
+        
+        return item['files']
+    
+    def clear(self, session_id: str):
+        """
+        清除指定会话的缓存
+        
+        Args:
+            session_id: 会话ID
+        """
+        if session_id in self.cache:
+            logger.info(f"[FileCache] Cleared cache for session {session_id}")
+            del self.cache[session_id]
+    
+    def cleanup_expired(self):
+        """清理所有过期的缓存"""
+        current_time = time.time()
+        expired_sessions = []
+        
+        for session_id, item in self.cache.items():
+            if current_time - item['timestamp'] > self.ttl:
+                expired_sessions.append(session_id)
+        
+        for session_id in expired_sessions:
+            del self.cache[session_id]
+            logger.debug(f"[FileCache] Cleaned up expired cache for session {session_id}")
+        
+        if expired_sessions:
+            logger.info(f"[FileCache] Cleaned up {len(expired_sessions)} expired cache(s)")
+
+
+# 全局单例
+_file_cache = FileCache()
+
+
+def get_file_cache() -> FileCache:
+    """获取全局文件缓存实例"""
+    return _file_cache
diff --git a/channel/qq/__init__.py b/channel/qq/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/channel/qq/qq_channel.py b/channel/qq/qq_channel.py
new file mode 100644
index 0000000..a85072b
--- /dev/null
+++ b/channel/qq/qq_channel.py
@@ -0,0 +1,736 @@
+"""
+QQ Bot channel via WebSocket long connection.
+
+Supports:
+- Group chat (@bot), single chat (C2C), guild channel, guild DM
+- Text / image / file message send & receive
+- Heartbeat keep-alive and auto-reconnect with session resume
+"""
+
+import base64
+import json
+import os
+import threading
+import time
+
+import requests
+import websocket
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.qq.qq_message import QQMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from common.ws_client_compat import websocket_app_run_forever
+from config import conf
+
+# Rich media file_type constants
+QQ_FILE_TYPE_IMAGE = 1
+QQ_FILE_TYPE_VIDEO = 2
+QQ_FILE_TYPE_VOICE = 3
+QQ_FILE_TYPE_FILE = 4
+
+QQ_API_BASE = "https://api.sgroup.qq.com"
+
+# Intents: GROUP_AND_C2C_EVENT(1<<25) | PUBLIC_GUILD_MESSAGES(1<<30)
+DEFAULT_INTENTS = (1 << 25) | (1 << 30)
+
+# OpCode constants
+OP_DISPATCH = 0
+OP_HEARTBEAT = 1
+OP_IDENTIFY = 2
+OP_RESUME = 6
+OP_RECONNECT = 7
+OP_INVALID_SESSION = 9
+OP_HELLO = 10
+OP_HEARTBEAT_ACK = 11
+
+# Resumable error codes
+RESUMABLE_CLOSE_CODES = {4008, 4009}
+
+
+@singleton
+class QQChannel(ChatChannel):
+
+    def __init__(self):
+        super().__init__()
+        self.app_id = ""
+        self.app_secret = ""
+
+        self._access_token = ""
+        self._token_expires_at = 0
+
+        self._ws = None
+        self._ws_thread = None
+        self._heartbeat_thread = None
+        self._connected = False
+        self._stop_event = threading.Event()
+        self._token_lock = threading.Lock()
+
+        self._session_id = None
+        self._last_seq = None
+        self._heartbeat_interval = 45000
+        self._can_resume = False
+
+        self.received_msgs = ExpiredDict(60 * 60 * 7.1)
+        self._msg_seq_counter = {}
+
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def startup(self):
+        self.app_id = conf().get("qq_app_id", "")
+        self.app_secret = conf().get("qq_app_secret", "")
+
+        if not self.app_id or not self.app_secret:
+            err = "[QQ] qq_app_id and qq_app_secret are required"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        self._refresh_access_token()
+        if not self._access_token:
+            err = "[QQ] Failed to get initial access_token"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        self._stop_event.clear()
+        self._start_ws()
+
+    def stop(self):
+        logger.info("[QQ] stop() called")
+        self._stop_event.set()
+        if self._ws:
+            try:
+                self._ws.close()
+            except Exception:
+                pass
+        self._ws = None
+        self._connected = False
+
+    # ------------------------------------------------------------------
+    # Access Token
+    # ------------------------------------------------------------------
+
+    def _refresh_access_token(self):
+        try:
+            resp = requests.post(
+                "https://bots.qq.com/app/getAppAccessToken",
+                json={"appId": self.app_id, "clientSecret": self.app_secret},
+                timeout=10,
+            )
+            resp.raise_for_status()
+            data = resp.json()
+            self._access_token = data.get("access_token", "")
+            expires_in = int(data.get("expires_in", 7200))
+            self._token_expires_at = time.time() + expires_in - 60
+            logger.debug(f"[QQ] Access token refreshed, expires_in={expires_in}s")
+        except Exception as e:
+            logger.error(f"[QQ] Failed to refresh access_token: {e}")
+
+    def _get_access_token(self) -> str:
+        with self._token_lock:
+            if time.time() >= self._token_expires_at:
+                self._refresh_access_token()
+            return self._access_token
+
+    def _get_auth_headers(self) -> dict:
+        return {
+            "Authorization": f"QQBot {self._get_access_token()}",
+            "Content-Type": "application/json",
+        }
+
+    # ------------------------------------------------------------------
+    # WebSocket connection
+    # ------------------------------------------------------------------
+
+    def _get_ws_url(self) -> str:
+        try:
+            resp = requests.get(
+                f"{QQ_API_BASE}/gateway",
+                headers=self._get_auth_headers(),
+                timeout=10,
+            )
+            resp.raise_for_status()
+            url = resp.json().get("url", "")
+            logger.debug(f"[QQ] Gateway URL: {url}")
+            return url
+        except Exception as e:
+            logger.error(f"[QQ] Failed to get gateway URL: {e}")
+            return ""
+
+    def _start_ws(self):
+        ws_url = self._get_ws_url()
+        if not ws_url:
+            logger.error("[QQ] Cannot start WebSocket without gateway URL")
+            self.report_startup_error("Failed to get gateway URL")
+            return
+
+        def _on_open(ws):
+            logger.debug("[QQ] WebSocket connected, waiting for Hello...")
+
+        def _on_message(ws, raw):
+            try:
+                data = json.loads(raw)
+                self._handle_ws_message(data)
+            except Exception as e:
+                logger.error(f"[QQ] Failed to handle ws message: {e}", exc_info=True)
+
+        def _on_error(ws, error):
+            logger.error(f"[QQ] WebSocket error: {error}")
+
+        def _on_close(ws, close_status_code, close_msg):
+            logger.warning(f"[QQ] WebSocket closed: status={close_status_code}, msg={close_msg}")
+            self._connected = False
+            if not self._stop_event.is_set():
+                if close_status_code in RESUMABLE_CLOSE_CODES and self._session_id:
+                    self._can_resume = True
+                    logger.info("[QQ] Will attempt resume in 3s...")
+                    time.sleep(3)
+                else:
+                    self._can_resume = False
+                    logger.info("[QQ] Will reconnect in 5s...")
+                    time.sleep(5)
+                if not self._stop_event.is_set():
+                    self._start_ws()
+
+        self._ws = websocket.WebSocketApp(
+            ws_url,
+            on_open=_on_open,
+            on_message=_on_message,
+            on_error=_on_error,
+            on_close=_on_close,
+        )
+
+        def run_forever():
+            try:
+                websocket_app_run_forever(self._ws, ping_interval=0, reconnect=0)
+            except (SystemExit, KeyboardInterrupt):
+                logger.info("[QQ] WebSocket thread interrupted")
+            except Exception as e:
+                logger.error(f"[QQ] WebSocket run_forever error: {e}")
+
+        self._ws_thread = threading.Thread(target=run_forever, daemon=True)
+        self._ws_thread.start()
+        self._ws_thread.join()
+
+    def _ws_send(self, data: dict):
+        if self._ws:
+            self._ws.send(json.dumps(data, ensure_ascii=False))
+
+    # ------------------------------------------------------------------
+    # Identify & Resume & Heartbeat
+    # ------------------------------------------------------------------
+
+    def _send_identify(self):
+        self._ws_send({
+            "op": OP_IDENTIFY,
+            "d": {
+                "token": f"QQBot {self._get_access_token()}",
+                "intents": DEFAULT_INTENTS,
+                "shard": [0, 1],
+                "properties": {
+                    "$os": "linux",
+                    "$browser": "chatgpt-on-wechat",
+                    "$device": "chatgpt-on-wechat",
+                },
+            },
+        })
+        logger.debug(f"[QQ] Identify sent with intents={DEFAULT_INTENTS}")
+
+    def _send_resume(self):
+        self._ws_send({
+            "op": OP_RESUME,
+            "d": {
+                "token": f"QQBot {self._get_access_token()}",
+                "session_id": self._session_id,
+                "seq": self._last_seq,
+            },
+        })
+        logger.debug(f"[QQ] Resume sent: session_id={self._session_id}, seq={self._last_seq}")
+
+    def _start_heartbeat(self, interval_ms: int):
+        if self._heartbeat_thread and self._heartbeat_thread.is_alive():
+            return
+        self._heartbeat_interval = interval_ms
+        interval_sec = interval_ms / 1000.0
+
+        def heartbeat_loop():
+            while not self._stop_event.is_set() and self._connected:
+                try:
+                    self._ws_send({
+                        "op": OP_HEARTBEAT,
+                        "d": self._last_seq,
+                    })
+                except Exception as e:
+                    logger.warning(f"[QQ] Heartbeat send failed: {e}")
+                    break
+                self._stop_event.wait(interval_sec)
+
+        self._heartbeat_thread = threading.Thread(target=heartbeat_loop, daemon=True)
+        self._heartbeat_thread.start()
+
+    # ------------------------------------------------------------------
+    # Incoming message dispatch
+    # ------------------------------------------------------------------
+
+    def _handle_ws_message(self, data: dict):
+        op = data.get("op")
+        d = data.get("d")
+        t = data.get("t")
+        s = data.get("s")
+
+        if s is not None:
+            self._last_seq = s
+
+        if op == OP_HELLO:
+            heartbeat_interval = d.get("heartbeat_interval", 45000) if d else 45000
+            logger.debug(f"[QQ] Received Hello, heartbeat_interval={heartbeat_interval}ms")
+            self._heartbeat_interval = heartbeat_interval
+            if self._can_resume and self._session_id:
+                self._send_resume()
+            else:
+                self._send_identify()
+
+        elif op == OP_HEARTBEAT_ACK:
+            pass
+
+        elif op == OP_HEARTBEAT:
+            self._ws_send({"op": OP_HEARTBEAT, "d": self._last_seq})
+
+        elif op == OP_RECONNECT:
+            logger.warning("[QQ] Server requested reconnect")
+            self._can_resume = True
+            if self._ws:
+                self._ws.close()
+
+        elif op == OP_INVALID_SESSION:
+            logger.warning("[QQ] Invalid session, re-identifying...")
+            self._session_id = None
+            self._can_resume = False
+            time.sleep(2)
+            self._send_identify()
+
+        elif op == OP_DISPATCH:
+            if t == "READY":
+                self._session_id = d.get("session_id", "")
+                user = d.get("user", {})
+                bot_name = user.get('username', '')
+                logger.info(f"[QQ] ✅ Connected successfully (bot={bot_name})")
+                self._connected = True
+                self._can_resume = False
+                self._start_heartbeat(self._heartbeat_interval)
+                self.report_startup_success()
+
+            elif t == "RESUMED":
+                logger.info("[QQ] Session resumed successfully")
+                self._connected = True
+                self._can_resume = False
+                self._start_heartbeat(self._heartbeat_interval)
+
+            elif t in ("GROUP_AT_MESSAGE_CREATE", "C2C_MESSAGE_CREATE",
+                        "AT_MESSAGE_CREATE", "DIRECT_MESSAGE_CREATE"):
+                self._handle_msg_event(d, t)
+
+            elif t in ("GROUP_ADD_ROBOT", "FRIEND_ADD"):
+                logger.info(f"[QQ] Event: {t}")
+
+            else:
+                logger.debug(f"[QQ] Dispatch event: {t}")
+
+    # ------------------------------------------------------------------
+    # Message event handling
+    # ------------------------------------------------------------------
+
+    def _handle_msg_event(self, event_data: dict, event_type: str):
+        msg_id = event_data.get("id", "")
+        if self.received_msgs.get(msg_id):
+            logger.debug(f"[QQ] Duplicate msg filtered: {msg_id}")
+            return
+        self.received_msgs[msg_id] = True
+
+        try:
+            qq_msg = QQMessage(event_data, event_type)
+        except NotImplementedError as e:
+            logger.warning(f"[QQ] {e}")
+            return
+        except Exception as e:
+            logger.error(f"[QQ] Failed to parse message: {e}", exc_info=True)
+            return
+
+        is_group = qq_msg.is_group
+
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+
+        if is_group:
+            session_id = qq_msg.other_user_id
+        else:
+            session_id = qq_msg.from_user_id
+
+        if qq_msg.ctype == ContextType.IMAGE:
+            if hasattr(qq_msg, "image_path") and qq_msg.image_path:
+                file_cache.add(session_id, qq_msg.image_path, file_type="image")
+                logger.info(f"[QQ] Image cached for session {session_id}")
+            return
+
+        if qq_msg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                file_refs = []
+                for fi in cached_files:
+                    ftype = fi["type"]
+                    fpath = fi["path"]
+                    if ftype == "image":
+                        file_refs.append(f"[图片: {fpath}]")
+                    elif ftype == "video":
+                        file_refs.append(f"[视频: {fpath}]")
+                    else:
+                        file_refs.append(f"[文件: {fpath}]")
+                qq_msg.content = qq_msg.content + "\n" + "\n".join(file_refs)
+                logger.info(f"[QQ] Attached {len(cached_files)} cached file(s)")
+                file_cache.clear(session_id)
+
+        context = self._compose_context(
+            qq_msg.ctype,
+            qq_msg.content,
+            isgroup=is_group,
+            msg=qq_msg,
+            no_need_at=True,
+        )
+        if context:
+            self.produce(context)
+
+    # ------------------------------------------------------------------
+    # _compose_context
+    # ------------------------------------------------------------------
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+
+        if cmsg.is_group:
+            context["session_id"] = cmsg.other_user_id
+        else:
+            context["session_id"] = cmsg.from_user_id
+
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = content.strip()
+
+        return context
+
+    # ------------------------------------------------------------------
+    # Send reply
+    # ------------------------------------------------------------------
+
+    def send(self, reply: Reply, context: Context):
+        msg = context.get("msg")
+        is_group = context.get("isgroup", False)
+        receiver = context.get("receiver", "")
+
+        if not msg:
+            # Active send (e.g. scheduled tasks), no original message to reply to
+            self._active_send_text(reply.content if reply.type == ReplyType.TEXT else str(reply.content),
+                                   receiver, is_group)
+            return
+
+        event_type = getattr(msg, "event_type", "")
+        msg_id = getattr(msg, "msg_id", "")
+
+        if reply.type == ReplyType.TEXT:
+            self._send_text(reply.content, msg, event_type, msg_id)
+        elif reply.type in (ReplyType.IMAGE_URL, ReplyType.IMAGE):
+            self._send_image(reply.content, msg, event_type, msg_id)
+        elif reply.type == ReplyType.FILE:
+            if hasattr(reply, "text_content") and reply.text_content:
+                self._send_text(reply.text_content, msg, event_type, msg_id)
+                time.sleep(0.3)
+            self._send_file(reply.content, msg, event_type, msg_id)
+        elif reply.type in (ReplyType.VIDEO, ReplyType.VIDEO_URL):
+            self._send_media(reply.content, msg, event_type, msg_id, QQ_FILE_TYPE_VIDEO)
+        else:
+            logger.warning(f"[QQ] Unsupported reply type: {reply.type}, falling back to text")
+            self._send_text(str(reply.content), msg, event_type, msg_id)
+
+    # ------------------------------------------------------------------
+    # Send helpers
+    # ------------------------------------------------------------------
+
+    def _get_next_msg_seq(self, msg_id: str) -> int:
+        seq = self._msg_seq_counter.get(msg_id, 1)
+        self._msg_seq_counter[msg_id] = seq + 1
+        return seq
+
+    def _build_msg_url_and_base_body(self, msg: QQMessage, event_type: str, msg_id: str):
+        """Build the API URL and base body dict for sending a message."""
+        if event_type == "GROUP_AT_MESSAGE_CREATE":
+            group_openid = msg._rawmsg.get("group_openid", "")
+            url = f"{QQ_API_BASE}/v2/groups/{group_openid}/messages"
+            body = {
+                "msg_id": msg_id,
+                "msg_seq": self._get_next_msg_seq(msg_id),
+            }
+            return url, body, "group", group_openid
+
+        elif event_type == "C2C_MESSAGE_CREATE":
+            user_openid = msg._rawmsg.get("author", {}).get("user_openid", "") or msg.from_user_id
+            url = f"{QQ_API_BASE}/v2/users/{user_openid}/messages"
+            body = {
+                "msg_id": msg_id,
+                "msg_seq": self._get_next_msg_seq(msg_id),
+            }
+            return url, body, "c2c", user_openid
+
+        elif event_type == "AT_MESSAGE_CREATE":
+            channel_id = msg._rawmsg.get("channel_id", "")
+            url = f"{QQ_API_BASE}/channels/{channel_id}/messages"
+            body = {"msg_id": msg_id}
+            return url, body, "channel", channel_id
+
+        elif event_type == "DIRECT_MESSAGE_CREATE":
+            guild_id = msg._rawmsg.get("guild_id", "")
+            url = f"{QQ_API_BASE}/dms/{guild_id}/messages"
+            body = {"msg_id": msg_id}
+            return url, body, "dm", guild_id
+
+        return None, None, None, None
+
+    def _post_message(self, url: str, body: dict, event_type: str):
+        try:
+            resp = requests.post(url, json=body, headers=self._get_auth_headers(), timeout=10)
+            if resp.status_code in (200, 201, 202, 204):
+                logger.info(f"[QQ] Message sent successfully: event_type={event_type}")
+            else:
+                logger.error(f"[QQ] Failed to send message: status={resp.status_code}, "
+                             f"body={resp.text}")
+        except Exception as e:
+            logger.error(f"[QQ] Send message error: {e}")
+
+    # ------------------------------------------------------------------
+    # Active send (no original message, e.g. scheduled tasks)
+    # ------------------------------------------------------------------
+
+    def _active_send_text(self, content: str, receiver: str, is_group: bool):
+        """Send text without an original message (active push). QQ limits active messages to 4/month per user."""
+        if not receiver:
+            logger.warning("[QQ] No receiver for active send")
+            return
+        if is_group:
+            url = f"{QQ_API_BASE}/v2/groups/{receiver}/messages"
+        else:
+            url = f"{QQ_API_BASE}/v2/users/{receiver}/messages"
+        body = {
+            "content": content,
+            "msg_type": 0,
+        }
+        event_label = "GROUP_ACTIVE" if is_group else "C2C_ACTIVE"
+        self._post_message(url, body, event_label)
+
+    # ------------------------------------------------------------------
+    # Send text
+    # ------------------------------------------------------------------
+
+    def _send_text(self, content: str, msg: QQMessage, event_type: str, msg_id: str):
+        url, body, _, _ = self._build_msg_url_and_base_body(msg, event_type, msg_id)
+        if not url:
+            logger.warning(f"[QQ] Cannot send reply for event_type: {event_type}")
+            return
+        body["content"] = content
+        body["msg_type"] = 0
+        self._post_message(url, body, event_type)
+
+    # ------------------------------------------------------------------
+    # Rich media upload & send (image / video / file)
+    # ------------------------------------------------------------------
+
+    def _upload_rich_media(self, file_url: str, file_type: int, msg: QQMessage,
+                           event_type: str) -> str:
+        """
+        Upload media via QQ rich media API and return file_info.
+        For group: POST /v2/groups/{group_openid}/files
+        For c2c:   POST /v2/users/{openid}/files
+        """
+        if event_type == "GROUP_AT_MESSAGE_CREATE":
+            group_openid = msg._rawmsg.get("group_openid", "")
+            upload_url = f"{QQ_API_BASE}/v2/groups/{group_openid}/files"
+        elif event_type == "C2C_MESSAGE_CREATE":
+            user_openid = (msg._rawmsg.get("author", {}).get("user_openid", "")
+                           or msg.from_user_id)
+            upload_url = f"{QQ_API_BASE}/v2/users/{user_openid}/files"
+        else:
+            logger.warning(f"[QQ] Rich media upload not supported for event_type: {event_type}")
+            return ""
+
+        upload_body = {
+            "file_type": file_type,
+            "url": file_url,
+            "srv_send_msg": False,
+        }
+
+        try:
+            resp = requests.post(
+                upload_url, json=upload_body,
+                headers=self._get_auth_headers(), timeout=30,
+            )
+            if resp.status_code in (200, 201):
+                data = resp.json()
+                file_info = data.get("file_info", "")
+                logger.info(f"[QQ] Rich media uploaded: file_type={file_type}, "
+                            f"file_uuid={data.get('file_uuid', '')}")
+                return file_info
+            else:
+                logger.error(f"[QQ] Rich media upload failed: status={resp.status_code}, "
+                             f"body={resp.text}")
+                return ""
+        except Exception as e:
+            logger.error(f"[QQ] Rich media upload error: {e}")
+            return ""
+
+    def _upload_rich_media_base64(self, file_path: str, file_type: int, msg: QQMessage,
+                                  event_type: str) -> str:
+        """Upload local file via base64 file_data field."""
+        if event_type == "GROUP_AT_MESSAGE_CREATE":
+            group_openid = msg._rawmsg.get("group_openid", "")
+            upload_url = f"{QQ_API_BASE}/v2/groups/{group_openid}/files"
+        elif event_type == "C2C_MESSAGE_CREATE":
+            user_openid = (msg._rawmsg.get("author", {}).get("user_openid", "")
+                           or msg.from_user_id)
+            upload_url = f"{QQ_API_BASE}/v2/users/{user_openid}/files"
+        else:
+            logger.warning(f"[QQ] Rich media upload not supported for event_type: {event_type}")
+            return ""
+
+        try:
+            with open(file_path, "rb") as f:
+                file_data = base64.b64encode(f.read()).decode("utf-8")
+        except Exception as e:
+            logger.error(f"[QQ] Failed to read file for upload: {e}")
+            return ""
+
+        upload_body = {
+            "file_type": file_type,
+            "file_data": file_data,
+            "srv_send_msg": False,
+        }
+
+        try:
+            resp = requests.post(
+                upload_url, json=upload_body,
+                headers=self._get_auth_headers(), timeout=30,
+            )
+            if resp.status_code in (200, 201):
+                data = resp.json()
+                file_info = data.get("file_info", "")
+                logger.info(f"[QQ] Rich media uploaded (base64): file_type={file_type}, "
+                            f"file_uuid={data.get('file_uuid', '')}")
+                return file_info
+            else:
+                logger.error(f"[QQ] Rich media upload (base64) failed: status={resp.status_code}, "
+                             f"body={resp.text}")
+                return ""
+        except Exception as e:
+            logger.error(f"[QQ] Rich media upload (base64) error: {e}")
+            return ""
+
+    def _send_media_msg(self, file_info: str, msg: QQMessage, event_type: str, msg_id: str):
+        """Send a message with msg_type=7 (rich media) using file_info."""
+        url, body, _, _ = self._build_msg_url_and_base_body(msg, event_type, msg_id)
+        if not url:
+            return
+        body["msg_type"] = 7
+        body["media"] = {"file_info": file_info}
+        self._post_message(url, body, event_type)
+
+    def _send_image(self, img_path_or_url: str, msg: QQMessage, event_type: str, msg_id: str):
+        """Send image reply. Supports URL and local file path."""
+        if event_type not in ("GROUP_AT_MESSAGE_CREATE", "C2C_MESSAGE_CREATE"):
+            self._send_text(str(img_path_or_url), msg, event_type, msg_id)
+            return
+
+        if img_path_or_url.startswith("file://"):
+            img_path_or_url = img_path_or_url[7:]
+
+        if img_path_or_url.startswith(("http://", "https://")):
+            file_info = self._upload_rich_media(
+                img_path_or_url, QQ_FILE_TYPE_IMAGE, msg, event_type)
+        elif os.path.exists(img_path_or_url):
+            file_info = self._upload_rich_media_base64(
+                img_path_or_url, QQ_FILE_TYPE_IMAGE, msg, event_type)
+        else:
+            logger.error(f"[QQ] Image not found: {img_path_or_url}")
+            self._send_text("[Image send failed]", msg, event_type, msg_id)
+            return
+
+        if file_info:
+            self._send_media_msg(file_info, msg, event_type, msg_id)
+        else:
+            self._send_text("[Image upload failed]", msg, event_type, msg_id)
+
+    def _send_file(self, file_path_or_url: str, msg: QQMessage, event_type: str, msg_id: str):
+        """Send file reply."""
+        if event_type not in ("GROUP_AT_MESSAGE_CREATE", "C2C_MESSAGE_CREATE"):
+            self._send_text(str(file_path_or_url), msg, event_type, msg_id)
+            return
+
+        if file_path_or_url.startswith("file://"):
+            file_path_or_url = file_path_or_url[7:]
+
+        if file_path_or_url.startswith(("http://", "https://")):
+            file_info = self._upload_rich_media(
+                file_path_or_url, QQ_FILE_TYPE_FILE, msg, event_type)
+        elif os.path.exists(file_path_or_url):
+            file_info = self._upload_rich_media_base64(
+                file_path_or_url, QQ_FILE_TYPE_FILE, msg, event_type)
+        else:
+            logger.error(f"[QQ] File not found: {file_path_or_url}")
+            self._send_text("[File send failed]", msg, event_type, msg_id)
+            return
+
+        if file_info:
+            self._send_media_msg(file_info, msg, event_type, msg_id)
+        else:
+            self._send_text("[File upload failed]", msg, event_type, msg_id)
+
+    def _send_media(self, path_or_url: str, msg: QQMessage, event_type: str,
+                    msg_id: str, file_type: int):
+        """Generic media send for video/voice etc."""
+        if event_type not in ("GROUP_AT_MESSAGE_CREATE", "C2C_MESSAGE_CREATE"):
+            self._send_text(str(path_or_url), msg, event_type, msg_id)
+            return
+
+        if path_or_url.startswith("file://"):
+            path_or_url = path_or_url[7:]
+
+        if path_or_url.startswith(("http://", "https://")):
+            file_info = self._upload_rich_media(path_or_url, file_type, msg, event_type)
+        elif os.path.exists(path_or_url):
+            file_info = self._upload_rich_media_base64(path_or_url, file_type, msg, event_type)
+        else:
+            logger.error(f"[QQ] Media not found: {path_or_url}")
+            return
+
+        if file_info:
+            self._send_media_msg(file_info, msg, event_type, msg_id)
+        else:
+            logger.error(f"[QQ] Media upload failed: {path_or_url}")
diff --git a/channel/qq/qq_message.py b/channel/qq/qq_message.py
new file mode 100644
index 0000000..6e9b49e
--- /dev/null
+++ b/channel/qq/qq_message.py
@@ -0,0 +1,123 @@
+import os
+import requests
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from common.utils import expand_path
+from config import conf
+
+
+def _get_tmp_dir() -> str:
+    """Return the workspace tmp directory (absolute path), creating it if needed."""
+    ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    tmp_dir = os.path.join(ws_root, "tmp")
+    os.makedirs(tmp_dir, exist_ok=True)
+    return tmp_dir
+
+
+class QQMessage(ChatMessage):
+    """Message wrapper for QQ Bot (websocket long-connection mode)."""
+
+    def __init__(self, event_data: dict, event_type: str):
+        super().__init__(event_data)
+        self.msg_id = event_data.get("id", "")
+        self.create_time = event_data.get("timestamp", "")
+        self.is_group = event_type in ("GROUP_AT_MESSAGE_CREATE",)
+        self.event_type = event_type
+
+        author = event_data.get("author", {})
+        from_user_id = author.get("member_openid", "") or author.get("id", "")
+        group_openid = event_data.get("group_openid", "")
+
+        content = event_data.get("content", "").strip()
+
+        attachments = event_data.get("attachments", [])
+        has_image = any(
+            a.get("content_type", "").startswith("image/") for a in attachments
+        ) if attachments else False
+
+        if has_image and not content:
+            self.ctype = ContextType.IMAGE
+            img_attachment = next(
+                a for a in attachments if a.get("content_type", "").startswith("image/")
+            )
+            img_url = img_attachment.get("url", "")
+            if img_url and not img_url.startswith("http"):
+                img_url = "https://" + img_url
+            tmp_dir = _get_tmp_dir()
+            image_path = os.path.join(tmp_dir, f"qq_{self.msg_id}.png")
+            try:
+                resp = requests.get(img_url, timeout=30)
+                resp.raise_for_status()
+                with open(image_path, "wb") as f:
+                    f.write(resp.content)
+                self.content = image_path
+                self.image_path = image_path
+                logger.info(f"[QQ] Image downloaded: {image_path}")
+            except Exception as e:
+                logger.error(f"[QQ] Failed to download image: {e}")
+                self.content = "[Image download failed]"
+                self.image_path = None
+        elif has_image and content:
+            self.ctype = ContextType.TEXT
+            image_paths = []
+            tmp_dir = _get_tmp_dir()
+            for idx, att in enumerate(attachments):
+                if not att.get("content_type", "").startswith("image/"):
+                    continue
+                img_url = att.get("url", "")
+                if img_url and not img_url.startswith("http"):
+                    img_url = "https://" + img_url
+                img_path = os.path.join(tmp_dir, f"qq_{self.msg_id}_{idx}.png")
+                try:
+                    resp = requests.get(img_url, timeout=30)
+                    resp.raise_for_status()
+                    with open(img_path, "wb") as f:
+                        f.write(resp.content)
+                    image_paths.append(img_path)
+                except Exception as e:
+                    logger.error(f"[QQ] Failed to download mixed image: {e}")
+            content_parts = [content]
+            for p in image_paths:
+                content_parts.append(f"[图片: {p}]")
+            self.content = "\n".join(content_parts)
+        else:
+            self.ctype = ContextType.TEXT
+            self.content = content
+
+        if event_type == "GROUP_AT_MESSAGE_CREATE":
+            self.from_user_id = from_user_id
+            self.to_user_id = ""
+            self.other_user_id = group_openid
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = from_user_id
+
+        elif event_type == "C2C_MESSAGE_CREATE":
+            user_openid = author.get("user_openid", "") or from_user_id
+            self.from_user_id = user_openid
+            self.to_user_id = ""
+            self.other_user_id = user_openid
+            self.actual_user_id = user_openid
+
+        elif event_type == "AT_MESSAGE_CREATE":
+            self.from_user_id = from_user_id
+            self.to_user_id = ""
+            channel_id = event_data.get("channel_id", "")
+            self.other_user_id = channel_id
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = author.get("username", from_user_id)
+
+        elif event_type == "DIRECT_MESSAGE_CREATE":
+            self.from_user_id = from_user_id
+            self.to_user_id = ""
+            guild_id = event_data.get("guild_id", "")
+            self.other_user_id = f"dm_{guild_id}_{from_user_id}"
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = author.get("username", from_user_id)
+
+        else:
+            raise NotImplementedError(f"Unsupported QQ event type: {event_type}")
+
+        logger.debug(f"[QQ] Message parsed: type={event_type}, ctype={self.ctype}, "
+                     f"from={self.from_user_id}, content_len={len(self.content)}")
diff --git a/channel/slack/__init__.py b/channel/slack/__init__.py
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/channel/slack/__init__.py
@@ -0,0 +1 @@
+
diff --git a/channel/slack/slack_channel.py b/channel/slack/slack_channel.py
new file mode 100644
index 0000000..8e82fcc
--- /dev/null
+++ b/channel/slack/slack_channel.py
@@ -0,0 +1,506 @@
+"""
+Slack channel via Bolt for Python (Socket Mode).
+
+Features:
+- Direct message & channel chat (text / image / file)
+- Channel trigger: @mention or reply in a thread the bot is in (configurable)
+- /cancel fast-path matches Web channel behaviour
+- Socket Mode: no public IP / callback URL required, works behind NAT
+
+Implementation note:
+    slack_bolt's SocketModeHandler is blocking and runs its own background
+    threads. We start it in a dedicated thread so the rest of cow (sync) stays
+    untouched. Inbound events are dispatched onto cow's existing sync
+    ChatChannel.produce() pipeline; outbound send() calls the Slack Web API
+    client directly (it is sync-safe).
+"""
+
+import os
+import re
+import threading
+
+import requests
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.slack.slack_message import SlackMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from config import conf
+
+
+@singleton
+class SlackChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.bot_token = ""
+        self.app_token = ""
+        self.bot_user_id = ""  # used to strip @mention and ignore self messages
+        self._app = None
+        self._handler = None
+        self._client = None
+        self._loop_thread = None
+        # Idempotent dedup; Slack retries event delivery on slow ack
+        self._received_msgs = ExpiredDict(60 * 60 * 1)
+
+        # Disable group whitelist / prefix checks (we handle triggering ourselves
+        # in _should_reply_in_channel), aligned with telegram / feishu channels.
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def startup(self):
+        self.bot_token = conf().get("slack_bot_token", "")
+        self.app_token = conf().get("slack_app_token", "")
+        if not self.bot_token or not self.app_token:
+            err = "[Slack] slack_bot_token and slack_app_token are both required"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        # Guard against the common mistake of swapping the two tokens:
+        # bot token must start with xoxb-, app-level token with xapp-.
+        if not self.bot_token.startswith("xoxb-") or not self.app_token.startswith("xapp-"):
+            err = (
+                "[Slack] token type mismatch: slack_bot_token must start with 'xoxb-' "
+                "and slack_app_token must start with 'xapp-' (they look swapped)"
+            )
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        try:
+            from slack_bolt import App
+            from slack_bolt.adapter.socket_mode import SocketModeHandler
+        except ImportError:
+            err = (
+                "[Slack] slack_bolt is not installed. "
+                "Run: pip install slack_bolt"
+            )
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        try:
+            self._app = App(token=self.bot_token)
+            self._client = self._app.client
+
+            # Resolve our own bot user id (needed for @mention strip / self-ignore)
+            auth = self._client.auth_test()
+            self.bot_user_id = auth.get("user_id", "")
+            self.name = self.bot_user_id  # ChatChannel uses self.name to strip @-mention
+            logger.info(f"[Slack] Bot logged in as user_id={self.bot_user_id}, team={auth.get('team')}")
+        except Exception as e:
+            err = f"[Slack] auth_test failed: {e}"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        self._register_handlers()
+
+        self._handler = SocketModeHandler(self._app, self.app_token)
+
+        def _run():
+            try:
+                logger.info("[Slack] Starting Socket Mode connection...")
+                self.report_startup_success()
+                logger.info("[Slack] ✅ Slack bot ready, listening for events")
+                self._handler.start()
+            except Exception as e:
+                logger.error(f"[Slack] socket mode crashed: {e}", exc_info=True)
+                self.report_startup_error(str(e))
+            finally:
+                logger.info("[Slack] socket mode exited")
+
+        self._loop_thread = threading.Thread(target=_run, daemon=True, name="slack-socket")
+        self._loop_thread.start()
+        # Block startup() until the handler thread exits, matching other channels'
+        # behaviour (startup is a blocking call).
+        self._loop_thread.join()
+
+    def _register_handlers(self):
+        app = self._app
+
+        # app_mention: bot is @-mentioned in a channel
+        @app.event("app_mention")
+        def _on_app_mention(event, ack):
+            ack()
+            self._handle_event(event, is_group=True)
+
+        # message: DMs and channel messages (including thread replies)
+        @app.event("message")
+        def _on_message(event, ack):
+            ack()
+            self._handle_message_event(event)
+
+    def stop(self):
+        logger.info("[Slack] stop() called")
+        try:
+            if self._handler is not None:
+                self._handler.close()
+        except Exception as e:
+            logger.warning(f"[Slack] handler close error: {e}")
+        if self._loop_thread and self._loop_thread.is_alive():
+            try:
+                self._loop_thread.join(timeout=10)
+            except Exception:
+                pass
+        logger.info("[Slack] stop() completed")
+
+    # ------------------------------------------------------------------
+    # Inbound: slack event -> ChatMessage -> ChatChannel.produce
+    # ------------------------------------------------------------------
+
+    def _handle_message_event(self, event: dict):
+        """Route a raw `message` event: skip bot/system noise, decide grouping."""
+        try:
+            logger.debug(
+                f"[Slack] message event: channel_type={event.get('channel_type')}, "
+                f"subtype={event.get('subtype')}, user={event.get('user')}, "
+                f"ts={event.get('ts')}, thread_ts={event.get('thread_ts')}"
+            )
+            # Ignore bot messages (including our own) and message edits/deletes
+            if event.get("bot_id") or event.get("subtype") in ("bot_message", "message_changed", "message_deleted"):
+                return
+            if event.get("user") == self.bot_user_id:
+                return
+
+            channel_type = event.get("channel_type", "")
+            # DM (im) is single chat; channel/group is group chat. app_mention
+            # already covers channel @-mentions, so for plain channel messages we
+            # only react when configured / thread-following.
+            is_group = channel_type in ("channel", "group", "mpim")
+            if is_group:
+                # app_mention handler covers explicit @bot; here we only handle
+                # follow-up replies in threads the bot participates in.
+                if not self._should_reply_in_channel(event):
+                    return
+            self._handle_event(event, is_group=is_group)
+        except Exception as e:
+            logger.error(f"[Slack] _handle_message_event error: {e}", exc_info=True)
+
+    def _handle_event(self, event: dict, is_group: bool):
+        """Parse event -> build SlackMessage -> produce()."""
+        try:
+            channel_id = event.get("channel", "")
+            ts = event.get("ts", "")
+            if not channel_id:
+                return
+
+            # Idempotent dedup
+            msg_uid = f"{channel_id}:{ts}"
+            if self._received_msgs.get(msg_uid):
+                return
+            self._received_msgs[msg_uid] = True
+
+            # Parse type + download media if needed.
+            ctype, content, caption = self._parse_event(event)
+            if ctype is None:
+                logger.debug(f"[Slack] unsupported message type, skip. event={event}")
+                return
+
+            # Strip <@bot_user_id> mention from channel text
+            if is_group and self.bot_user_id:
+                if ctype == ContextType.TEXT and content:
+                    content = self._strip_at_mention(content)
+                if caption:
+                    caption = self._strip_at_mention(caption)
+
+            slack_msg = SlackMessage(
+                event,
+                is_group=is_group,
+                bot_user_id=self.bot_user_id,
+                ctype=ctype,
+                content=content,
+            )
+            slack_msg.is_at = is_group  # if we reached here in a channel, bot is mentioned/threaded
+
+            from channel.file_cache import get_file_cache
+            file_cache = get_file_cache()
+            session_id = self._compute_session_id(event, is_group)
+
+            # Media + caption together: treat as a complete query and bypass the cache
+            if ctype in (ContextType.IMAGE, ContextType.FILE) and caption:
+                tag = "image" if ctype == ContextType.IMAGE else "file"
+                merged_text = f"{caption}\n[{tag}: {content}]"
+                slack_msg.ctype = ContextType.TEXT
+                slack_msg.content = merged_text
+                ctype = ContextType.TEXT
+                logger.info(f"[Slack] Media+caption merged for session {session_id}")
+                # fallthrough to the TEXT branch below
+
+            elif ctype == ContextType.IMAGE:
+                file_cache.add(session_id, content, file_type="image")
+                logger.info(f"[Slack] Image cached for session {session_id}, waiting for query...")
+                return
+            elif ctype == ContextType.FILE:
+                file_cache.add(session_id, content, file_type="file")
+                logger.info(f"[Slack] File cached for session {session_id}: {content}")
+                return
+
+            if ctype == ContextType.TEXT:
+                # Fast-path: /cancel mirrors Web channel behaviour
+                if (content or "").strip().lower() in ("/cancel", "cancel"):
+                    self._do_cancel(session_id, channel_id, event)
+                    return
+
+                cached_files = file_cache.get(session_id)
+                if cached_files:
+                    refs = []
+                    for fi in cached_files:
+                        ftype = fi["type"]
+                        tag = ftype if ftype in ("image", "video") else "file"
+                        refs.append(f"[{tag}: {fi['path']}]")
+                    slack_msg.content = (slack_msg.content or "") + "\n" + "\n".join(refs)
+                    file_cache.clear(session_id)
+                    logger.info(f"[Slack] Attached {len(cached_files)} cached file(s) to query")
+
+            # Reply in the originating thread when present, else start one on this msg
+            thread_ts = event.get("thread_ts") or ts
+
+            context = self._compose_context(
+                slack_msg.ctype,
+                slack_msg.content,
+                isgroup=is_group,
+                msg=slack_msg,
+                # Replies go back into the thread, no manual @mention needed
+                no_need_at=True,
+            )
+            if context:
+                context["session_id"] = session_id
+                context["receiver"] = channel_id
+                context["slack_channel"] = channel_id
+                context["slack_thread_ts"] = thread_ts if is_group else None
+                self.produce(context)
+            logger.debug(f"[Slack] received: type={ctype}, content={str(slack_msg.content)[:80]}")
+        except Exception as e:
+            logger.error(f"[Slack] _handle_event error: {e}", exc_info=True)
+
+    def _do_cancel(self, session_id: str, channel_id: str, event: dict):
+        """Fast-path: /cancel calls cancel_session directly without going through agent."""
+        try:
+            from agent.protocol import get_cancel_registry
+            cancelled = get_cancel_registry().cancel_session(session_id)
+            text = "Current task cancelled." if cancelled else "No running task to cancel."
+            thread_ts = event.get("thread_ts") or event.get("ts")
+            self._client.chat_postMessage(channel=channel_id, text=text, thread_ts=thread_ts)
+            logger.info(f"[Slack] /cancel session={session_id}, cancelled={cancelled}")
+        except Exception as e:
+            logger.error(f"[Slack] /cancel error: {e}", exc_info=True)
+
+    def _parse_event(self, event: dict):
+        """Parse a slack event and return (ctype, content, caption).
+
+        - content is text for ContextType.TEXT, otherwise the local file path
+        - caption is the optional text accompanying a file; empty for plain text
+        """
+        text = (event.get("text") or "").strip()
+        files = event.get("files") or []
+
+        if files:
+            # Handle the first attachment; caption is the accompanying message text
+            f = files[0]
+            mimetype = (f.get("mimetype") or "").lower()
+            url = f.get("url_private_download") or f.get("url_private")
+            name = f.get("name") or f.get("id") or "file"
+            if not url:
+                return (None, None, "")
+            path = self._download_file(url, name)
+            if not path:
+                return (None, None, "")
+            if mimetype.startswith("image/"):
+                return (ContextType.IMAGE, path, text)
+            return (ContextType.FILE, path, text)
+
+        if text:
+            return (ContextType.TEXT, text, "")
+
+        return (None, None, "")
+
+    def _download_file(self, url: str, name: str):
+        """Download a Slack private file (requires bot token auth) to local tmp dir."""
+        try:
+            headers = {"Authorization": f"Bearer {self.bot_token}"}
+            resp = requests.get(url, headers=headers, timeout=60, stream=True)
+            resp.raise_for_status()
+            tmp_dir = SlackMessage.get_tmp_dir()
+            # Sanitize the name and keep it unique-ish via the url tail
+            safe_name = re.sub(r"[^\w.\-]", "_", name)
+            local_path = os.path.join(tmp_dir, safe_name)
+            with open(local_path, "wb") as fp:
+                for chunk in resp.iter_content(chunk_size=8192):
+                    if chunk:
+                        fp.write(chunk)
+            logger.debug(f"[Slack] downloaded {name} -> {local_path}")
+            return local_path
+        except Exception as e:
+            logger.error(f"[Slack] download_file failed ({name}): {e}")
+            return None
+
+    # ------------------------------------------------------------------
+    # Channel trigger logic
+    # ------------------------------------------------------------------
+
+    def _should_reply_in_channel(self, event: dict) -> bool:
+        """Decide whether to reply to a plain channel message (no @mention).
+
+        app_mention already handles explicit @bot, so here we only deal with
+        follow-up messages. `all` replies to every message; `mention_or_reply`
+        replies inside threads the bot already participates in.
+        """
+        mode = conf().get("slack_group_trigger", "mention_or_reply")
+        if mode == "all":
+            return True
+        if mode == "mention_only":
+            return False
+        # mention_or_reply: follow up only within an existing thread
+        return bool(event.get("thread_ts"))
+
+    def _strip_at_mention(self, content: str) -> str:
+        """Strip <@BOT_USER_ID> from channel text."""
+        if not content or not self.bot_user_id:
+            return content
+        pattern = re.compile(r"<@" + re.escape(self.bot_user_id) + r">", re.IGNORECASE)
+        return pattern.sub("", content).strip()
+
+    @staticmethod
+    def _compute_session_id(event: dict, is_group: bool) -> str:
+        channel_id = event.get("channel", "")
+        user_id = event.get("user", "")
+        if is_group:
+            if conf().get("group_shared_session", True):
+                return f"slack_channel_{channel_id}"
+            return f"slack_channel_{channel_id}_{user_id}"
+        return f"slack_user_{user_id}"
+
+    # ------------------------------------------------------------------
+    # Override _compose_context: skip the parent's group whitelist/at checks
+    # (already handled via _should_reply_in_channel). Same idea as telegram.
+    # ------------------------------------------------------------------
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+        if cmsg.is_group:
+            if conf().get("group_shared_session", True):
+                context["session_id"] = cmsg.other_user_id
+            else:
+                context["session_id"] = f"{cmsg.from_user_id}:{cmsg.other_user_id}"
+        else:
+            context["session_id"] = cmsg.from_user_id
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = (content or "").strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+        elif ctype == ContextType.VOICE:
+            if "desire_rtype" not in context and (
+                conf().get("voice_reply_voice") or conf().get("always_reply_voice")
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+    # ------------------------------------------------------------------
+    # Outbound: ChatChannel.send -> Slack Web API
+    # ------------------------------------------------------------------
+
+    def send(self, reply: Reply, context: Context):
+        """Called from cow's sync main thread; Slack Web client is sync-safe."""
+        if self._client is None:
+            logger.warning("[Slack] client not ready, drop reply")
+            return
+
+        channel_id = context.get("slack_channel")
+        thread_ts = context.get("slack_thread_ts")
+        if not channel_id:
+            logger.warning("[Slack] no slack_channel in context, drop reply")
+            return
+
+        try:
+            self._do_send(reply, channel_id, thread_ts)
+            logger.info(f"[Slack] sent reply (type={reply.type}, channel={channel_id})")
+        except Exception as e:
+            logger.error(f"[Slack] send failed: {e}", exc_info=True)
+
+    def _do_send(self, reply: Reply, channel_id: str, thread_ts):
+        rtype = reply.type
+        content = reply.content
+
+        if rtype in (ReplyType.TEXT, ReplyType.INFO, ReplyType.ERROR):
+            text = str(content) if content is not None else ""
+            if not text:
+                return
+            # Slack caps a message around 40k chars; split conservatively
+            for chunk in _split_text(text, 3500):
+                self._client.chat_postMessage(channel=channel_id, text=chunk, thread_ts=thread_ts)
+
+        elif rtype == ReplyType.IMAGE:
+            # Already a local BytesIO; upload it directly
+            content.seek(0)
+            self._client.files_upload_v2(
+                channel=channel_id, file=content, filename="image.png", thread_ts=thread_ts,
+            )
+
+        elif rtype == ReplyType.IMAGE_URL:
+            url = str(content)
+            if url.startswith("file://"):
+                local = url[7:]
+                self._client.files_upload_v2(
+                    channel=channel_id, file=local, thread_ts=thread_ts,
+                )
+            else:
+                # Post the URL as text; Slack will unfurl it as an image preview
+                self._client.chat_postMessage(channel=channel_id, text=url, thread_ts=thread_ts)
+
+        elif rtype in (ReplyType.VOICE, ReplyType.FILE):
+            local = content[7:] if isinstance(content, str) and content.startswith("file://") else content
+            caption = getattr(reply, "text_content", None) or None
+            self._client.files_upload_v2(
+                channel=channel_id, file=local, initial_comment=caption, thread_ts=thread_ts,
+            )
+
+        else:
+            # Fallback: send as plain text
+            self._client.chat_postMessage(channel=channel_id, text=str(content), thread_ts=thread_ts)
+
+
+def _split_text(text: str, limit: int):
+    """Split long text preferring line breaks to keep markdown structure intact."""
+    if len(text) <= limit:
+        yield text
+        return
+    buf = []
+    size = 0
+    for line in text.splitlines(keepends=True):
+        if size + len(line) > limit and buf:
+            yield "".join(buf)
+            buf, size = [], 0
+        # Hard-split single lines that exceed the limit
+        while len(line) > limit:
+            yield line[:limit]
+            line = line[limit:]
+        buf.append(line)
+        size += len(line)
+    if buf:
+        yield "".join(buf)
diff --git a/channel/slack/slack_message.py b/channel/slack/slack_message.py
new file mode 100644
index 0000000..39f215b
--- /dev/null
+++ b/channel/slack/slack_message.py
@@ -0,0 +1,60 @@
+"""
+Slack message adapter.
+
+Convert a Slack event payload into cow's unified ChatMessage.
+File downloads are NOT performed here; the channel layer downloads files
+on demand because it needs the bot token for authenticated download URLs.
+"""
+import os
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.utils import expand_path
+from config import conf
+
+
+class SlackMessage(ChatMessage):
+    """Wrap a Slack event into the unified ChatMessage."""
+
+    def __init__(self, event: dict, is_group: bool = False, bot_user_id: str = "",
+                 ctype: ContextType = ContextType.TEXT, content: str = ""):
+        super().__init__(event)
+        # Basic fields
+        self.msg_id = event.get("client_msg_id") or event.get("ts") or ""
+        try:
+            self.create_time = int(float(event.get("ts", 0)))
+        except (TypeError, ValueError):
+            self.create_time = 0
+        self.ctype = ctype
+        self.content = content
+
+        # Sender / chat info
+        from_user_id = event.get("user", "unknown")
+        channel_id = event.get("channel", "")
+        self.from_user_id = from_user_id
+        self.from_user_nickname = from_user_id
+        self.to_user_id = bot_user_id or "slack_bot"
+        self.to_user_nickname = bot_user_id or "slack_bot"
+
+        self.is_group = is_group
+        if is_group:
+            # Channel chat: other_user_id = channel_id, actual_user_id = sender id
+            self.other_user_id = channel_id
+            self.other_user_nickname = channel_id
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = from_user_id
+        else:
+            # DM: use channel_id so replies go back to the same DM channel
+            self.other_user_id = channel_id or from_user_id
+            self.other_user_nickname = from_user_id
+
+        # Whether the bot was triggered by @-mention (set by channel layer)
+        self.is_at = False
+
+    @staticmethod
+    def get_tmp_dir() -> str:
+        """Local download directory, aligned with other channels (agent_workspace/tmp)."""
+        workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        tmp_dir = os.path.join(workspace_root, "tmp")
+        os.makedirs(tmp_dir, exist_ok=True)
+        return tmp_dir
diff --git a/channel/telegram/__init__.py b/channel/telegram/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/channel/telegram/telegram_channel.py b/channel/telegram/telegram_channel.py
new file mode 100644
index 0000000..9e40c59
--- /dev/null
+++ b/channel/telegram/telegram_channel.py
@@ -0,0 +1,719 @@
+"""
+Telegram channel via Bot API (long polling mode).
+
+Features:
+- Single chat & group chat (text / photo / voice / video / document)
+- Group trigger: @mention or reply-to-bot (configurable)
+- /cancel fast-path matches Web channel behaviour
+- Auto-register bot commands menu on startup (mirrors Web slash menu)
+- Optional HTTP/SOCKS5 proxy support for restricted networks
+
+Implementation note:
+    python-telegram-bot is async-first. We run the bot inside a dedicated
+    thread with its own asyncio loop so the rest of cow (which is sync)
+    stays untouched. Inbound updates are dispatched onto cow's existing
+    sync ChatChannel.produce() pipeline; outbound send() schedules
+    coroutines back onto that loop via asyncio.run_coroutine_threadsafe.
+"""
+
+import asyncio
+import os
+import re
+import threading
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.telegram.telegram_message import TelegramMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from config import conf
+
+# Bot command menu, aligned with Web slash commands.
+# Top-level commands only; sub-commands are entered with a space (e.g. "/skill list").
+TELEGRAM_BOT_COMMANDS = [
+    ("help", "Show command help"),
+    ("status", "Show running status"),
+    ("context", "View/clear conversation context (sub: clear)"),
+    ("skill", "Manage skills (list/search/install/...)"),
+    ("memory", "Manage memory (sub: dream)"),
+    ("knowledge", "Manage knowledge base (list/on/off)"),
+    ("config", "Show current config"),
+    ("cancel", "Cancel running agent task"),
+    ("logs", "Show recent logs"),
+    ("version", "Show version"),
+]
+
+
+@singleton
+class TelegramChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.bot_token = ""
+        self.bot_username = ""  # used for @-mention matching
+        self._bot = None
+        self._application = None
+        self._loop = None
+        self._loop_thread = None
+        self._stop_event = threading.Event()
+        # Idempotent dedup; TG occasionally redelivers the same update on flaky networks
+        self._received_msgs = ExpiredDict(60 * 60 * 1)
+
+        # Disable group whitelist / prefix checks (we handle triggering ourselves
+        # in _should_reply_in_group), aligned with feishu / wecom_bot channels.
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def startup(self):
+        self.bot_token = conf().get("telegram_token", "")
+        if not self.bot_token:
+            err = "[Telegram] telegram_token is required"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        try:
+            from telegram.ext import (
+                Application,
+                MessageHandler,
+                CommandHandler,
+                filters,
+            )
+        except ImportError:
+            err = (
+                "[Telegram] python-telegram-bot is not installed. "
+                "Run: pip install python-telegram-bot"
+            )
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        # Run the asyncio event loop in a dedicated thread so the sync cow body
+        # is untouched.
+        self._loop = asyncio.new_event_loop()
+
+        def _run_loop():
+            asyncio.set_event_loop(self._loop)
+            try:
+                self._loop.run_until_complete(self._async_main(Application, MessageHandler, CommandHandler, filters))
+            except Exception as e:
+                logger.error(f"[Telegram] event loop crashed: {e}", exc_info=True)
+                self.report_startup_error(str(e))
+            finally:
+                try:
+                    self._loop.close()
+                except Exception:
+                    pass
+                logger.info("[Telegram] event loop exited")
+
+        self._loop_thread = threading.Thread(target=_run_loop, daemon=True, name="telegram-loop")
+        self._loop_thread.start()
+        # Block startup() until the loop thread exits, matching other channels'
+        # behaviour (startup is a blocking call).
+        self._loop_thread.join()
+
+    async def _async_main(self, Application, MessageHandler, CommandHandler, filters):
+        """Build Application, register handlers, and run polling."""
+        builder = Application.builder().token(self.bot_token)
+
+        # Proxy: prefer telegram_proxy config, fall back to HTTPS_PROXY env var
+        proxy_url = conf().get("telegram_proxy", "") or os.environ.get("HTTPS_PROXY", "")
+        if proxy_url:
+            try:
+                builder = builder.proxy(proxy_url).get_updates_proxy(proxy_url)
+                logger.info(f"[Telegram] using proxy: {proxy_url}")
+            except Exception as e:
+                logger.warning(f"[Telegram] proxy config failed, fallback to direct: {e}")
+
+        # Media uploads (photo/voice/video/document) over a proxy can be slow,
+        # bump read/write/connect/pool timeouts.
+        builder = (
+            builder
+            .read_timeout(60)
+            .write_timeout(120)
+            .connect_timeout(30)
+            .pool_timeout(30)
+        )
+
+        application = builder.build()
+        self._application = application
+        self._bot = application.bot
+
+        # Fetch our own username (needed for @-mention matching in groups)
+        try:
+            me = await self._bot.get_me()
+            self.bot_username = me.username or ""
+            self.name = self.bot_username  # ChatChannel uses self.name to strip @-mention
+            logger.info(f"[Telegram] Bot logged in as @{self.bot_username} (id={me.id})")
+        except Exception as e:
+            err = f"[Telegram] get_me failed: {e}"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        # Register the command menu (failure is non-fatal)
+        if conf().get("telegram_register_commands", True):
+            try:
+                from telegram import BotCommand
+                cmds = [BotCommand(name, desc) for name, desc in TELEGRAM_BOT_COMMANDS]
+                await self._bot.set_my_commands(cmds)
+                logger.info(f"[Telegram] Registered {len(cmds)} bot commands")
+            except Exception as e:
+                logger.warning(f"[Telegram] set_my_commands failed: {e}")
+
+        # Handlers:
+        # 1) /cancel uses the fast-path
+        application.add_handler(CommandHandler("cancel", self._on_cancel))
+        # 2) Normal messages (text + media)
+        application.add_handler(MessageHandler(filters.ALL & ~filters.COMMAND, self._on_message))
+        # 3) Other slash commands are forwarded as plain text for the agent to handle
+        application.add_handler(MessageHandler(filters.COMMAND, self._on_command_passthrough))
+
+        # Start polling. drop_pending_updates avoids replaying backlog after restart.
+        # Transient "Server disconnected" / RemoteProtocolError during get_updates
+        # are common over proxies/flaky networks; PTB's network loop auto-retries,
+        # so we only need to keep the noise down (see _quiet_polling_network_errors).
+        self._quiet_polling_network_errors()
+        logger.info("[Telegram] Starting long polling...")
+        await application.initialize()
+        await application.start()
+        await application.updater.start_polling(
+            drop_pending_updates=True,
+            # Long-poll hold time on the server side; smaller value = reconnect more
+            # often but each hung connection fails faster.
+            timeout=30,
+            # Retry forever on transient get_updates network errors instead of giving up.
+            bootstrap_retries=-1,
+        )
+        self.report_startup_success()
+        logger.info("[Telegram] ✅ Telegram bot ready, polling for updates")
+
+        # Block until stop()
+        try:
+            while not self._stop_event.is_set():
+                await asyncio.sleep(0.5)
+        finally:
+            try:
+                await application.updater.stop()
+                await application.stop()
+                await application.shutdown()
+            except Exception as e:
+                logger.warning(f"[Telegram] shutdown error: {e}")
+
+    @staticmethod
+    def _quiet_polling_network_errors():
+        """Downgrade PTB's noisy 'Exception happened while polling for updates' logs.
+
+        These transient get_updates errors (RemoteProtocolError / NetworkError /
+        TimedOut, typically over a proxy) are auto-retried by PTB's network loop,
+        so logging the full traceback at ERROR is just noise. We attach a filter
+        that drops these specific records while leaving real errors untouched.
+        """
+        import logging
+
+        class _PollingNoiseFilter(logging.Filter):
+            _NEEDLES = (
+                "Exception happened while polling for updates",
+                "Server disconnected without sending a response",
+            )
+
+            def filter(self, record: logging.LogRecord) -> bool:
+                try:
+                    msg = record.getMessage()
+                except Exception:
+                    return True
+                if any(n in msg for n in self._NEEDLES):
+                    # Keep a single-line breadcrumb at DEBUG, drop the traceback.
+                    logger.debug(f"[Telegram] transient polling network error (auto-retrying): {msg.splitlines()[0]}")
+                    return False
+                return True
+
+        noise_filter = _PollingNoiseFilter()
+        for name in ("telegram.ext.Updater", "telegram.ext._updater", "telegram.ext"):
+            logging.getLogger(name).addFilter(noise_filter)
+
+    def stop(self):
+        logger.info("[Telegram] stop() called")
+        self._stop_event.set()
+        if self._loop_thread and self._loop_thread.is_alive():
+            try:
+                self._loop_thread.join(timeout=10)
+            except Exception:
+                pass
+        logger.info("[Telegram] stop() completed")
+
+    # ------------------------------------------------------------------
+    # Inbound: telegram update -> ChatMessage -> ChatChannel.produce
+    # ------------------------------------------------------------------
+
+    async def _on_cancel(self, update, _context):
+        """Fast-path: /cancel calls cancel_session directly without going through agent."""
+        try:
+            from agent.protocol import get_cancel_registry
+            session_id = self._compute_session_id(update)
+            cancelled = get_cancel_registry().cancel_session(session_id)
+            text = "Current task cancelled." if cancelled else "No running task to cancel."
+            await update.effective_message.reply_text(text)
+            logger.info(f"[Telegram] /cancel session={session_id}, cancelled={cancelled}")
+        except Exception as e:
+            logger.error(f"[Telegram] /cancel error: {e}", exc_info=True)
+            try:
+                await update.effective_message.reply_text(f"⚠️ /cancel failed: {e}")
+            except Exception:
+                pass
+
+    async def _on_command_passthrough(self, update, _context):
+        """All non-/cancel commands fall through to plain message handling."""
+        await self._on_message(update, _context)
+
+    async def _on_message(self, update, _context):
+        """Telegram update entry: parse message -> build ChatMessage -> produce()."""
+        try:
+            message = update.effective_message
+            chat = update.effective_chat
+            if not message or not chat:
+                return
+
+            # Idempotent dedup
+            msg_uid = f"{chat.id}:{message.message_id}"
+            if self._received_msgs.get(msg_uid):
+                return
+            self._received_msgs[msg_uid] = True
+
+            is_group = chat.type in ("group", "supergroup")
+
+            # Debug log: helpful when group messages are silently dropped
+            if is_group:
+                logger.debug(
+                    f"[Telegram] group update received: chat_id={chat.id}, "
+                    f"text={(message.text or message.caption or '')[:40]!r}, "
+                    f"reply_to_bot={bool(message.reply_to_message and message.reply_to_message.from_user and message.reply_to_message.from_user.username == self.bot_username)}"
+                )
+
+            # Group trigger gate (silently drop if not triggered)
+            if is_group and not self._should_reply_in_group(update):
+                logger.debug(f"[Telegram] group message not triggered (need @{self.bot_username} or reply), skip")
+                return
+
+            # Parse message type + download media if needed.
+            # Media messages with caption return both the local path and the caption text.
+            ctype, content, caption = await self._parse_message(message)
+            if ctype is None:
+                logger.debug(f"[Telegram] unsupported message type, skip. msg={message}")
+                return
+
+            # Strip @bot mention for group text/caption
+            if is_group and self.bot_username:
+                if ctype == ContextType.TEXT and content:
+                    content = self._strip_at_mention(content)
+                if caption:
+                    caption = self._strip_at_mention(caption)
+
+            tg_msg = TelegramMessage(
+                update,
+                is_group=is_group,
+                bot_username=self.bot_username,
+                ctype=ctype,
+                content=content,
+            )
+            tg_msg.is_at = is_group  # If we got here in a group, the bot is mentioned/replied
+
+            # File cache: standalone media goes into cache, the next text query attaches them
+            from channel.file_cache import get_file_cache
+            file_cache = get_file_cache()
+            session_id = self._compute_session_id(update)
+
+            # Media + caption together: treat as a complete query and bypass the cache
+            if ctype in (ContextType.IMAGE, ContextType.FILE) and caption:
+                tag = "image" if ctype == ContextType.IMAGE else "file"
+                merged_text = f"{caption}\n[{tag}: {content}]"
+                tg_msg.ctype = ContextType.TEXT
+                tg_msg.content = merged_text
+                ctype = ContextType.TEXT
+                logger.info(f"[Telegram] Media+caption merged for session {session_id}")
+                # fallthrough to the TEXT branch below
+
+            elif ctype == ContextType.IMAGE:
+                file_cache.add(session_id, content, file_type="image")
+                logger.info(f"[Telegram] Image cached for session {session_id}, waiting for query...")
+                return
+            elif ctype == ContextType.FILE:
+                file_cache.add(session_id, content, file_type="file")
+                logger.info(f"[Telegram] File cached for session {session_id}: {content}")
+                return
+
+            if ctype == ContextType.TEXT:
+                cached_files = file_cache.get(session_id)
+                if cached_files:
+                    refs = []
+                    for fi in cached_files:
+                        ftype = fi["type"]
+                        tag = ftype if ftype in ("image", "video") else "file"
+                        refs.append(f"[{tag}: {fi['path']}]")
+                    tg_msg.content = (tg_msg.content or "") + "\n" + "\n".join(refs)
+                    file_cache.clear(session_id)
+                    logger.info(f"[Telegram] Attached {len(cached_files)} cached file(s) to query")
+
+            # Dispatch to cow main pipeline (reuses ChatChannel._compose_context routing)
+            context = self._compose_context(
+                tg_msg.ctype,
+                tg_msg.content,
+                isgroup=is_group,
+                msg=tg_msg,
+            )
+            if context:
+                context["session_id"] = session_id
+                context["receiver"] = str(chat.id)
+                context["telegram_chat_id"] = chat.id
+                context["telegram_reply_to_msg_id"] = message.message_id if is_group else None
+                self.produce(context)
+            logger.debug(f"[Telegram] received: type={ctype}, content={str(tg_msg.content)[:80]}")
+
+        except Exception as e:
+            logger.error(f"[Telegram] _on_message error: {e}", exc_info=True)
+
+    async def _parse_message(self, message):
+        """Parse a telegram message and return (ctype, content, caption).
+
+        - content is text for ContextType.TEXT, otherwise the local file path
+        - caption is the optional text accompanying a media message; empty for plain text
+        """
+        caption = (message.caption or "").strip()
+
+        if message.photo:
+            largest = message.photo[-1]
+            path = await self._download_file(largest.file_id, suffix=".jpg")
+            return (ContextType.IMAGE, path, caption) if path else (None, None, "")
+
+        if message.voice or message.audio:
+            audio_obj = message.voice or message.audio
+            suffix = ".ogg" if message.voice else (
+                "." + (audio_obj.mime_type.split("/")[-1] if getattr(audio_obj, "mime_type", "") else "mp3")
+            )
+            path = await self._download_file(audio_obj.file_id, suffix=suffix)
+            return (ContextType.VOICE, path, caption) if path else (None, None, "")
+
+        if message.video or message.video_note:
+            video_obj = message.video or message.video_note
+            path = await self._download_file(video_obj.file_id, suffix=".mp4")
+            return (ContextType.FILE, path, caption) if path else (None, None, "")
+
+        if message.document:
+            doc = message.document
+            ext = ""
+            if doc.file_name and "." in doc.file_name:
+                ext = "." + doc.file_name.rsplit(".", 1)[-1]
+            path = await self._download_file(doc.file_id, suffix=ext, original_name=doc.file_name)
+            if not path:
+                return (None, None, "")
+            # Image-typed documents (user picked "send as file") are treated as images
+            mime = (doc.mime_type or "").lower()
+            if mime.startswith("image/"):
+                return (ContextType.IMAGE, path, caption)
+            return (ContextType.FILE, path, caption)
+
+        if message.text:
+            return (ContextType.TEXT, message.text.strip(), "")
+
+        return (None, None, "")
+
+    async def _download_file(self, file_id: str, suffix: str = "", original_name: str = ""):
+        """Download via bot.get_file into the local tmp dir; return path or None on failure."""
+        try:
+            f = await self._bot.get_file(file_id)
+            tmp_dir = TelegramMessage.get_tmp_dir()
+            base = original_name or f"{file_id}{suffix or ''}"
+            # Prefix with file_id to avoid name collisions / weird chars
+            safe_name = f"{file_id}_{base}" if original_name else base
+            local_path = os.path.join(tmp_dir, safe_name)
+            await f.download_to_drive(custom_path=local_path)
+            logger.debug(f"[Telegram] downloaded file_id={file_id} -> {local_path}")
+            return local_path
+        except Exception as e:
+            logger.error(f"[Telegram] download_file failed (file_id={file_id}): {e}")
+            return None
+
+    # ------------------------------------------------------------------
+    # Group trigger logic
+    # ------------------------------------------------------------------
+
+    def _should_reply_in_group(self, update) -> bool:
+        """Decide whether to reply to a group message based on configuration."""
+        mode = conf().get("telegram_group_trigger", "mention_or_reply")
+        if mode == "all":
+            return True
+
+        message = update.effective_message
+        if not message:
+            return False
+
+        # 1) Mentioned
+        if self.bot_username and self._is_mentioned(message, self.bot_username):
+            return True
+
+        # 2) Reply to a bot message
+        if mode == "mention_or_reply":
+            reply = message.reply_to_message
+            if reply and reply.from_user and reply.from_user.username == self.bot_username:
+                return True
+
+        return False
+
+    @staticmethod
+    def _is_mentioned(message, bot_username: str) -> bool:
+        """Check whether entities/caption_entities contain a @mention of the bot."""
+        bot_at = "@" + bot_username.lower()
+        text = (message.text or message.caption or "").lower()
+        if bot_at in text:
+            return True
+        # Also check entities strictly to support text_mention (no-username @)
+        for ent in (message.entities or []) + (message.caption_entities or []):
+            if ent.type == "mention":
+                src = message.text or message.caption or ""
+                if src[ent.offset: ent.offset + ent.length].lower() == bot_at:
+                    return True
+        return False
+
+    def _strip_at_mention(self, content: str) -> str:
+        """Strip @bot_username from group text (case-insensitive)."""
+        if not content or not self.bot_username:
+            return content
+        pattern = re.compile(r"@" + re.escape(self.bot_username), re.IGNORECASE)
+        return pattern.sub("", content).strip()
+
+    @staticmethod
+    def _compute_session_id(update) -> str:
+        chat = update.effective_chat
+        user = update.effective_user
+        is_group = chat.type in ("group", "supergroup")
+        if is_group:
+            if conf().get("group_shared_session", True):
+                return f"tg_group_{chat.id}"
+            return f"tg_group_{chat.id}_{user.id}"
+        return f"tg_user_{user.id}"
+
+    # ------------------------------------------------------------------
+    # Override _compose_context: skip the parent's group whitelist/at checks
+    # (already handled in _on_message via _should_reply_in_group). Same idea
+    # as the feishu channel.
+    # ------------------------------------------------------------------
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+        if cmsg.is_group:
+            if conf().get("group_shared_session", True):
+                context["session_id"] = cmsg.other_user_id
+            else:
+                context["session_id"] = f"{cmsg.from_user_id}:{cmsg.other_user_id}"
+        else:
+            context["session_id"] = cmsg.from_user_id
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = (content or "").strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+        elif ctype == ContextType.VOICE:
+            if "desire_rtype" not in context and (
+                conf().get("voice_reply_voice") or conf().get("always_reply_voice")
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+    # ------------------------------------------------------------------
+    # Outbound: ChatChannel.send -> Telegram API
+    # ------------------------------------------------------------------
+
+    def send(self, reply: Reply, context: Context):
+        """Called from cow's sync main thread; we marshal the coroutine onto the loop thread."""
+        if self._loop is None or self._bot is None:
+            logger.warning("[Telegram] bot not ready, drop reply")
+            return
+
+        chat_id = context.get("telegram_chat_id")
+        reply_to = context.get("telegram_reply_to_msg_id")
+        if chat_id is None:
+            logger.warning("[Telegram] no telegram_chat_id in context, drop reply")
+            return
+
+        coro = self._async_send(reply, chat_id, reply_to)
+        try:
+            future = asyncio.run_coroutine_threadsafe(coro, self._loop)
+            # Media uploads through a proxy can be slow; let PTB's own timeouts win
+            future.result(timeout=180)
+        except Exception as e:
+            logger.error(f"[Telegram] send failed: {e}")
+
+    # Number of retries for transient network errors (proxy hiccups etc.)
+    _SEND_RETRIES = 2
+    _SEND_RETRY_BACKOFF = 2.0  # seconds
+
+    async def _send_with_retry(self, send_fn, *, label: str):
+        """Run a single Telegram API call with retries for transient network errors."""
+        from telegram.error import NetworkError, TimedOut
+        last_err = None
+        for attempt in range(self._SEND_RETRIES + 1):
+            try:
+                return await send_fn()
+            except (NetworkError, TimedOut) as e:
+                last_err = e
+                if attempt >= self._SEND_RETRIES:
+                    break
+                wait = self._SEND_RETRY_BACKOFF * (attempt + 1)
+                logger.warning(
+                    f"[Telegram] {label} transient error (attempt {attempt + 1}/"
+                    f"{self._SEND_RETRIES + 1}): {e}; retry in {wait}s"
+                )
+                await asyncio.sleep(wait)
+        raise last_err
+
+    async def _async_send(self, reply: Reply, chat_id, reply_to_msg_id):
+        try:
+            rtype = reply.type
+            content = reply.content
+
+            if rtype == ReplyType.TEXT or rtype == ReplyType.INFO or rtype == ReplyType.ERROR:
+                # Telegram caps a single text message at 4096 chars; auto-split
+                text = str(content) if content is not None else ""
+                if not text:
+                    return
+                for chunk in _split_text(text, 4000):
+                    await self._send_with_retry(
+                        lambda c=chunk: self._bot.send_message(
+                            chat_id=chat_id,
+                            text=c,
+                            reply_to_message_id=reply_to_msg_id,
+                            # Avoid failing the whole send if reply_to was deleted
+                            allow_sending_without_reply=True,
+                        ),
+                        label="send_message",
+                    )
+
+            elif rtype == ReplyType.IMAGE:
+                # Already a local BytesIO; send it directly
+                content.seek(0)
+                await self._send_with_retry(
+                    lambda: self._bot.send_photo(
+                        chat_id=chat_id,
+                        photo=content,
+                        reply_to_message_id=reply_to_msg_id,
+                        allow_sending_without_reply=True,
+                    ),
+                    label="send_photo",
+                )
+
+            elif rtype == ReplyType.IMAGE_URL:
+                url = str(content)
+                if url.startswith("file://"):
+                    local = url[7:]
+                    # Open inside the lambda so each retry gets a fresh stream
+                    async def _send_local_photo():
+                        with open(local, "rb") as f:
+                            return await self._bot.send_photo(
+                                chat_id=chat_id, photo=f,
+                                reply_to_message_id=reply_to_msg_id,
+                                allow_sending_without_reply=True,
+                            )
+                    await self._send_with_retry(_send_local_photo, label="send_photo(file)")
+                else:
+                    await self._send_with_retry(
+                        lambda: self._bot.send_photo(
+                            chat_id=chat_id, photo=url,
+                            reply_to_message_id=reply_to_msg_id,
+                            allow_sending_without_reply=True,
+                        ),
+                        label="send_photo(url)",
+                    )
+
+            elif rtype == ReplyType.VOICE:
+                local = content[7:] if isinstance(content, str) and content.startswith("file://") else content
+                async def _send_voice():
+                    with open(local, "rb") as f:
+                        return await self._bot.send_voice(
+                            chat_id=chat_id, voice=f,
+                            reply_to_message_id=reply_to_msg_id,
+                            allow_sending_without_reply=True,
+                        )
+                await self._send_with_retry(_send_voice, label="send_voice")
+
+            elif rtype == ReplyType.FILE:
+                # Videos go through send_video, everything else through send_document
+                local = content[7:] if isinstance(content, str) and content.startswith("file://") else content
+                # File replies may carry an accompanying text caption
+                caption = getattr(reply, "text_content", None) or None
+                is_video = isinstance(local, str) and local.lower().endswith(
+                    (".mp4", ".mov", ".avi", ".mkv", ".webm")
+                )
+
+                async def _send_file():
+                    with open(local, "rb") as f:
+                        if is_video:
+                            return await self._bot.send_video(
+                                chat_id=chat_id, video=f, caption=caption,
+                                reply_to_message_id=reply_to_msg_id,
+                                allow_sending_without_reply=True,
+                            )
+                        return await self._bot.send_document(
+                            chat_id=chat_id, document=f, caption=caption,
+                            reply_to_message_id=reply_to_msg_id,
+                            allow_sending_without_reply=True,
+                        )
+                await self._send_with_retry(_send_file, label="send_video" if is_video else "send_document")
+
+            else:
+                # Fallback: send as plain text
+                await self._send_with_retry(
+                    lambda: self._bot.send_message(
+                        chat_id=chat_id, text=str(content),
+                        reply_to_message_id=reply_to_msg_id,
+                        allow_sending_without_reply=True,
+                    ),
+                    label="send_message(fallback)",
+                )
+
+            logger.info(f"[Telegram] sent reply (type={rtype}, chat_id={chat_id})")
+
+        except Exception as e:
+            logger.error(f"[Telegram] _async_send error: {e}", exc_info=True)
+
+
+def _split_text(text: str, limit: int):
+    """Split long text preferring line breaks to keep markdown structure intact."""
+    if len(text) <= limit:
+        yield text
+        return
+    buf = []
+    size = 0
+    for line in text.splitlines(keepends=True):
+        if size + len(line) > limit and buf:
+            yield "".join(buf)
+            buf, size = [], 0
+        # Hard-split single lines that exceed the limit
+        while len(line) > limit:
+            yield line[:limit]
+            line = line[limit:]
+        buf.append(line)
+        size += len(line)
+    if buf:
+        yield "".join(buf)
diff --git a/channel/telegram/telegram_message.py b/channel/telegram/telegram_message.py
new file mode 100644
index 0000000..c97c605
--- /dev/null
+++ b/channel/telegram/telegram_message.py
@@ -0,0 +1,62 @@
+"""
+Telegram message adapter.
+
+Convert a python-telegram-bot Update into cow's unified ChatMessage.
+File downloads are NOT performed here; the channel layer triggers
+bot.get_file() on demand because it requires the async event loop.
+"""
+import os
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.utils import expand_path
+from config import conf
+
+
+class TelegramMessage(ChatMessage):
+    """Wrap a Telegram Update into the unified ChatMessage."""
+
+    def __init__(self, update, is_group: bool = False, bot_username: str = "",
+                 ctype: ContextType = ContextType.TEXT, content: str = ""):
+        super().__init__(update)
+        message = update.effective_message
+        chat = update.effective_chat
+        user = update.effective_user
+
+        # Basic fields
+        self.msg_id = str(message.message_id) if message else ""
+        self.create_time = int(message.date.timestamp()) if message and message.date else 0
+        self.ctype = ctype
+        self.content = content
+
+        # Sender / chat info
+        from_user_id = str(user.id) if user else "unknown"
+        from_user_nick = (
+            user.full_name if user and user.full_name else (user.username if user else "unknown")
+        )
+        self.from_user_id = from_user_id
+        self.from_user_nickname = from_user_nick or from_user_id
+        self.to_user_id = bot_username or "telegram_bot"
+        self.to_user_nickname = bot_username or "telegram_bot"
+
+        self.is_group = is_group
+        if is_group:
+            # Group: other_user_id = group_id, actual_user_id = sender id
+            self.other_user_id = str(chat.id)
+            self.other_user_nickname = chat.title or str(chat.id)
+            self.actual_user_id = from_user_id
+            self.actual_user_nickname = self.from_user_nickname
+        else:
+            self.other_user_id = from_user_id
+            self.other_user_nickname = self.from_user_nickname
+
+        # Whether the bot was triggered by @-mention or reply (set by channel layer)
+        self.is_at = False
+
+    @staticmethod
+    def get_tmp_dir() -> str:
+        """Local download directory, aligned with other channels (agent_workspace/tmp)."""
+        workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        tmp_dir = os.path.join(workspace_root, "tmp")
+        os.makedirs(tmp_dir, exist_ok=True)
+        return tmp_dir
diff --git a/channel/terminal/terminal_channel.py b/channel/terminal/terminal_channel.py
new file mode 100644
index 0000000..f439888
--- /dev/null
+++ b/channel/terminal/terminal_channel.py
@@ -0,0 +1,354 @@
+import json
+import os
+import sys
+import time
+
+from bridge.context import *
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.chat_message import ChatMessage
+from common.log import logger
+from config import conf
+
+
+class _Style:
+    """ANSI escape codes for terminal styling. Disabled when not a tty."""
+
+    enabled = sys.stdout.isatty()
+
+    RESET = "\033[0m"
+    BOLD = "\033[1m"
+    DIM = "\033[2m"
+    ITALIC = "\033[3m"
+
+    GRAY = "\033[90m"
+    RED = "\033[31m"
+    GREEN = "\033[32m"
+    YELLOW = "\033[33m"
+    BLUE = "\033[34m"
+    MAGENTA = "\033[35m"
+    CYAN = "\033[36m"
+
+    @classmethod
+    def wrap(cls, text, *codes):
+        if not cls.enabled or not codes:
+            return text
+        return "".join(codes) + text + cls.RESET
+
+
+class TerminalAgentRenderer:
+    """Render agent stream events to the terminal in real time.
+
+    Reuses the same `on_event` mechanism as the web channel so the terminal
+    can show reasoning, tool calls and streaming answer text just like the web UI.
+    """
+
+    def __init__(self):
+        self._reasoning_active = False
+        self._answer_active = False
+        self._has_output = False
+        # Track tool execution start time as a fallback when the event omits it
+        self._tool_started_at = {}
+
+    def _print(self, text, end="", flush=True):
+        sys.stdout.write(text)
+        if end:
+            sys.stdout.write(end)
+        if flush:
+            sys.stdout.flush()
+        self._has_output = True
+
+    def _close_section(self):
+        """Finish the currently open streaming section (reasoning or answer)."""
+        if self._reasoning_active:
+            self._print("", end="\n")
+            self._reasoning_active = False
+        if self._answer_active:
+            self._print("", end="\n")
+            self._answer_active = False
+
+    def _format_arguments(self, arguments):
+        try:
+            if isinstance(arguments, (dict, list)):
+                text = json.dumps(arguments, ensure_ascii=False)
+            else:
+                text = str(arguments)
+        except Exception:
+            text = str(arguments)
+        # Keep tool input compact in the terminal
+        if len(text) > 300:
+            text = text[:300] + "…"
+        return text
+
+    def handle_event(self, event: dict):
+        try:
+            self._handle_event(event)
+        except Exception as e:
+            logger.debug(f"[Terminal] render event error: {e}")
+
+    def _handle_event(self, event: dict):
+        event_type = event.get("type")
+        data = event.get("data", {}) or {}
+
+        if event_type == "agent_start":
+            self._print("\n" + _Style.wrap("Agent: ", _Style.BOLD, _Style.GREEN), end="\n")
+
+        elif event_type == "reasoning_update":
+            delta = data.get("delta", "")
+            if not delta:
+                return
+            if self._answer_active:
+                self._close_section()
+            if not self._reasoning_active:
+                self._print(_Style.wrap("💭 思考  ", _Style.DIM, _Style.MAGENTA), end="\n")
+                self._reasoning_active = True
+            self._print(_Style.wrap(delta, _Style.DIM, _Style.ITALIC))
+
+        elif event_type == "message_update":
+            delta = data.get("delta", "")
+            if not delta:
+                return
+            if self._reasoning_active:
+                self._close_section()
+            self._answer_active = True
+            self._print(delta)
+
+        elif event_type == "tool_execution_start":
+            self._close_section()
+            tool_name = data.get("tool_name", "tool")
+            tool_id = data.get("tool_call_id")
+            arguments = data.get("arguments", {})
+            self._tool_started_at[tool_id] = time.time()
+            header = _Style.wrap(f"🔧 {tool_name}", _Style.BOLD, _Style.CYAN)
+            args_str = self._format_arguments(arguments)
+            self._print(f"{header} {_Style.wrap(args_str, _Style.GRAY)}", end="\n")
+
+        elif event_type == "tool_execution_end":
+            tool_name = data.get("tool_name", "tool")
+            tool_id = data.get("tool_call_id")
+            status = data.get("status", "success")
+            result = data.get("result", "")
+            exec_time = data.get("execution_time")
+            if exec_time is None and tool_id in self._tool_started_at:
+                exec_time = time.time() - self._tool_started_at.pop(tool_id, time.time())
+            success = status == "success"
+            icon = "✓" if success else "✗"
+            color = _Style.GREEN if success else _Style.RED
+            result_str = str(result)
+            if len(result_str) > 500:
+                result_str = result_str[:500] + "…"
+            # Indent multi-line tool output for readability
+            result_str = result_str.replace("\n", "\n   ")
+            cost = f" ({exec_time:.2f}s)" if isinstance(exec_time, (int, float)) else ""
+            self._print(
+                _Style.wrap(f"   {icon} {tool_name}{cost}", color) + "  " + _Style.wrap(result_str, _Style.GRAY),
+                end="\n",
+            )
+
+        elif event_type == "file_to_send":
+            self._close_section()
+            file_path = data.get("path", "")
+            file_name = data.get("file_name", "")
+            label = file_name or file_path
+            self._print(_Style.wrap(f"📎 文件: {label}", _Style.BLUE), end="\n")
+
+        elif event_type == "error":
+            self._close_section()
+            err_msg = data.get("error") or "unknown error"
+            self._print(_Style.wrap(f"❌ {err_msg}", _Style.BOLD, _Style.RED), end="\n")
+
+        elif event_type == "agent_cancelled":
+            self._close_section()
+            self._print(_Style.wrap("⏹ 已中止", _Style.YELLOW), end="\n")
+
+        elif event_type == "agent_end":
+            self._close_section()
+
+    def finish(self):
+        """Ensure any open section is closed at the end of a turn."""
+        self._close_section()
+
+
+class TerminalMessage(ChatMessage):
+    def __init__(
+        self,
+        msg_id,
+        content,
+        ctype=ContextType.TEXT,
+        from_user_id="User",
+        to_user_id="Chatgpt",
+        other_user_id="Chatgpt",
+    ):
+        self.msg_id = msg_id
+        self.ctype = ctype
+        self.content = content
+        self.from_user_id = from_user_id
+        self.to_user_id = to_user_id
+        self.other_user_id = other_user_id
+
+
+class TerminalChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = [ReplyType.VOICE]
+
+    def __init__(self):
+        super().__init__()
+        # Per-request renderers keyed by request_id; used to detect whether
+        # agent text was already streamed so send() can avoid duplicate output.
+        self._renderers = {}
+        # Callback that restores TTY attributes on exit (set in startup).
+        self._restore_terminal = None
+
+    def send(self, reply: Reply, context: Context):
+        request_id = context.get("request_id") if context else None
+        renderer = self._renderers.pop(request_id, None) if request_id else None
+        streamed = renderer is not None and renderer._has_output
+
+        if renderer is not None:
+            renderer.finish()
+
+        if reply.type == ReplyType.IMAGE:
+            from PIL import Image
+
+            image_storage = reply.content
+            image_storage.seek(0)
+            img = Image.open(image_storage)
+            if not streamed:
+                print("\nAgent: ")
+            print("<IMAGE>")
+            img.show()
+        elif reply.type == ReplyType.IMAGE_URL:  # download image from url
+            import io
+
+            import requests
+            from PIL import Image
+
+            img_url = reply.content
+            pic_res = requests.get(img_url, stream=True)
+            image_storage = io.BytesIO()
+            for block in pic_res.iter_content(1024):
+                image_storage.write(block)
+            image_storage.seek(0)
+            img = Image.open(image_storage)
+            if not streamed:
+                print("\nAgent: ")
+            print(img_url)
+            img.show()
+        else:
+            # When agent already streamed the answer, skip re-printing the
+            # final text to avoid duplication; just emit a trailing newline.
+            if streamed:
+                print()
+            else:
+                print("\nAgent: ")
+                print(reply.content)
+        print("\nUser: ", end="")
+        sys.stdout.flush()
+        return
+
+    def _silence_console_logging(self):
+        """Mute console log output so background-thread logs (web/MCP/scheduler)
+        don't flood the interactive terminal. Logs still go to run.log in full.
+
+        Configurable via `terminal_log_level` (default ERROR). The file handler
+        is untouched, so run.log keeps the complete log.
+        """
+        import logging
+
+        level_name = str(conf().get("terminal_log_level", "ERROR")).upper()
+        level = getattr(logging, level_name, logging.ERROR)
+        root_logger = logging.getLogger("log")
+        for handler in root_logger.handlers:
+            # Only raise the level of the stdout/stderr stream handler;
+            # keep FileHandler at the logger's level so run.log stays complete.
+            if isinstance(handler, logging.StreamHandler) and not isinstance(handler, logging.FileHandler):
+                handler.setLevel(level)
+
+    def _install_terminal_guard(self):
+        """Save TTY attributes and register restore hooks so the terminal is
+        never left in a broken state (no echo / raw mode / leftover ANSI) after
+        the process exits, especially when Ctrl+C interrupts a blocking input().
+        """
+        if not sys.stdin.isatty():
+            return
+        try:
+            import atexit
+            import termios
+
+            saved_attrs = termios.tcgetattr(sys.stdin.fileno())
+
+            def _restore():
+                try:
+                    termios.tcsetattr(sys.stdin.fileno(), termios.TCSADRAIN, saved_attrs)
+                except Exception:
+                    pass
+                try:
+                    if _Style.enabled:
+                        sys.stdout.write(_Style.RESET)
+                        sys.stdout.flush()
+                except Exception:
+                    pass
+
+            self._restore_terminal = _restore
+            atexit.register(_restore)
+        except Exception as e:
+            # termios is unavailable on Windows; skip the guard there.
+            logger.debug(f"[Terminal] terminal guard not installed: {e}")
+            self._restore_terminal = None
+
+    def startup(self):
+        context = Context()
+        self._silence_console_logging()
+        self._install_terminal_guard()
+        print("\nPlease input your question:\nUser: ", end="")
+        sys.stdout.flush()
+        msg_id = 0
+        while True:
+            try:
+                prompt = self.get_input()
+            except (KeyboardInterrupt, EOFError):
+                self._shutdown()
+            msg_id += 1
+            trigger_prefixs = conf().get("single_chat_prefix", [""])
+            if check_prefix(prompt, trigger_prefixs) is None:
+                prompt = trigger_prefixs[0] + prompt  # add trigger prefix to untriggered messages
+
+            context = self._compose_context(ContextType.TEXT, prompt, msg=TerminalMessage(msg_id, prompt))
+            context["isgroup"] = False
+            if context:
+                # Attach an agent event renderer so reasoning / tool calls /
+                # streaming answer show up live in the terminal (web-like UX).
+                request_id = str(msg_id)
+                context["request_id"] = request_id
+                renderer = TerminalAgentRenderer()
+                self._renderers[request_id] = renderer
+                context["on_event"] = renderer.handle_event
+                self.produce(context)
+            else:
+                raise Exception("context is None")
+
+    def _shutdown(self):
+        """Restore terminal state and terminate the whole process.
+
+        startup() runs in a daemon sub-thread, so sys.exit() would only kill
+        this thread and leave the main process (and web/MCP/scheduler threads)
+        alive, holding the terminal in a half-occupied state -> laggy input.
+        We reset any leftover ANSI styling and hard-exit the process instead.
+        """
+        # Restore TTY attributes and reset any leftover ANSI styling
+        # (e.g. interrupted mid-stream output) before terminating.
+        if self._restore_terminal:
+            self._restore_terminal()
+        elif _Style.enabled:
+            sys.stdout.write(_Style.RESET)
+        sys.stdout.write("\nExiting...\n")
+        sys.stdout.flush()
+        # Hard-exit the entire process from a daemon thread.
+        os._exit(0)
+
+    def get_input(self):
+        """
+        Multi-line input function
+        """
+        sys.stdout.flush()
+        line = input()
+        return line
diff --git a/channel/web/README.md b/channel/web/README.md
new file mode 100644
index 0000000..b626985
--- /dev/null
+++ b/channel/web/README.md
@@ -0,0 +1,10 @@
+# Web Channel
+
+提供了一个默认的AI对话页面，可展示文本、图片等消息交互，支持markdown语法渲染，兼容插件执行。
+
+# 使用说明
+
+ - 在 `config.json` 配置文件中的 `channel_type` 字段填入 `web`
+ - 程序运行后将监听9899端口，浏览器访问 http://localhost:9899/chat 即可使用
+ - 监听端口可以在配置文件 `web_port` 中自定义
+ - 对于Docker运行方式，如果需要外部访问，需要在 `docker-compose.yml` 中通过 ports配置将端口监听映射到宿主机
diff --git a/channel/web/chat.html b/channel/web/chat.html
new file mode 100644
index 0000000..6381ca0
--- /dev/null
+++ b/channel/web/chat.html
@@ -0,0 +1,1516 @@
+<!DOCTYPE html>
+<html lang="zh" class="">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>CowAgent Console</title>
+    <link rel="icon" href="assets/favicon.ico" type="image/x-icon">
+    <!-- Vendored third-party assets (no external CDN dependency).
+         See channel/web/static/vendor/README.md for sources & versions. -->
+    <link rel="stylesheet" href="assets/vendor/fontawesome/css/all.min.css">
+    <link rel="stylesheet" href="assets/vendor/fonts/inter/inter.css">
+    <script src="assets/vendor/tailwind/tailwind.min.js"></script>
+    <script src="assets/vendor/markdown-it/markdown-it.min.js"></script>
+    <link id="hljs-light" rel="stylesheet" href="assets/vendor/highlightjs/styles/github.min.css">
+    <link id="hljs-dark" rel="stylesheet" href="assets/vendor/highlightjs/styles/github-dark.min.css" disabled>
+    <script src="assets/vendor/highlightjs/highlight.min.js"></script>
+    <script src="assets/vendor/highlightjs/languages/python.min.js"></script>
+    <script src="assets/vendor/highlightjs/languages/javascript.min.js"></script>
+    <script src="assets/vendor/highlightjs/languages/java.min.js"></script>
+    <script src="assets/vendor/highlightjs/languages/go.min.js"></script>
+    <script src="assets/vendor/highlightjs/languages/bash.min.js"></script>
+    <script>
+    tailwind.config = {
+        darkMode: 'class',
+        theme: {
+            extend: {
+                fontFamily: {
+                    sans: ['Inter', 'system-ui', '-apple-system', 'sans-serif'],
+                    mono: ['"JetBrains Mono"', '"Fira Code"', 'Consolas', 'monospace'],
+                },
+                colors: {
+                    primary: {
+                        50: '#EDFDF3', 100: '#D4FAE2', 200: '#ABF4C7', 300: '#74E9A4',
+                        400: '#4ABE6E', 500: '#35A85B', 600: '#228547', 700: '#1C6B3B',
+                        800: '#1A5532', 900: '#16462A',
+                    }
+                },
+                animation: {
+                    'pulse-dot': 'pulseDot 1.4s infinite ease-in-out both',
+                }
+            }
+        }
+    }
+    </script>
+    <link rel="stylesheet" href="assets/css/console.css">
+    <!-- Apply theme/lang before first paint to avoid flash of unstyled content.
+         This runs synchronously in <head> so the correct class is on <html>
+         before any CSS or body rendering occurs. -->
+    <script>
+    // Map an arbitrary locale string (zh-CN, en-US, fr ...) to 'zh' / 'zh-Hant' / 'en',
+    // or '' when unrecognized so callers can fall through to the next source.
+    window.__cowNormalizeLang__ = function(raw) {
+        if (!raw) return '';
+        var v = String(raw).trim().toLowerCase().replace('_', '-');
+        if (v === 'auto') return '';
+        // Handle Traditional Chinese variants first (more specific)
+        if (v === 'zh-hant' || v.indexOf('zh-hant-') === 0 || v === 'zh-tw' || v === 'zh-hk') return 'zh-Hant';
+        // Then Simplified Chinese
+        if (v.indexOf('zh') === 0) return 'zh';
+        if (v.indexOf('en') === 0) return 'en';
+        return '';
+    };
+    // Resolve the console language by priority:
+    //   user choice (localStorage) -> backend-detected -> browser -> 'zh'.
+    window.__cowResolveLang__ = function() {
+        return window.__cowNormalizeLang__(localStorage.getItem('cow_lang'))
+            || window.__cowNormalizeLang__(window.__COW_DEFAULT_LANG__)
+            || window.__cowNormalizeLang__(navigator.language || (navigator.languages && navigator.languages[0]))
+            || 'zh';
+    };
+    (function() {
+        // Backend-resolved default language (from cow_lang config / auto-detect).
+        window.__COW_DEFAULT_LANG__ = '{{COW_DEFAULT_LANG}}';
+        var theme = localStorage.getItem('cow_theme') || 'dark';
+        if (theme === 'dark') document.documentElement.classList.add('dark');
+        document.documentElement.setAttribute('lang', window.__cowResolveLang__());
+    })();
+    </script>
+</head>
+<body class="h-screen overflow-hidden bg-gray-50 dark:bg-[#111111] text-slate-800 dark:text-slate-200 font-sans">
+
+    <!-- Login Overlay -->
+    <div id="login-overlay" class="fixed inset-0 z-[200] bg-gray-50 dark:bg-[#111111] flex items-center justify-center hidden">
+        <div class="w-full max-w-sm mx-4">
+            <div class="flex flex-col items-center mb-8">
+                <img src="assets/logo.jpg" alt="CowAgent" class="w-16 h-16 rounded-2xl mb-4 shadow-lg">
+                <h1 class="text-xl font-bold text-slate-800 dark:text-slate-100">CowAgent</h1>
+                <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" id="login-subtitle">请输入密码以访问控制台</p>
+            </div>
+            <form id="login-form" class="space-y-4" onsubmit="return false;">
+                <div class="relative">
+                    <input id="login-password" type="password" autocomplete="current-password"
+                           placeholder="Password"
+                           class="w-full px-4 py-3 rounded-xl border border-slate-200 dark:border-white/10
+                                  bg-white dark:bg-[#1A1A1A] text-slate-800 dark:text-slate-200
+                                  placeholder-slate-400 dark:placeholder-slate-500
+                                  focus:outline-none focus:ring-2 focus:ring-primary-400/50 focus:border-primary-400
+                                  transition-all duration-150 text-sm">
+                    <button type="button" id="login-toggle-pwd"
+                            class="absolute right-3 top-1/2 -translate-y-1/2 text-slate-400 hover:text-slate-600
+                                   dark:hover:text-slate-300 cursor-pointer transition-colors"
+                            onclick="toggleLoginPassword()">
+                        <i class="fas fa-eye text-sm"></i>
+                    </button>
+                </div>
+                <p id="login-error" class="text-sm text-red-500 hidden"></p>
+                <button id="login-btn" type="submit"
+                        class="w-full py-3 rounded-xl bg-primary-500 hover:bg-primary-600 text-white font-medium
+                               text-sm cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed">
+                    登录
+                </button>
+            </form>
+        </div>
+    </div>
+
+    <div id="app" class="flex h-screen">
+
+        <!-- ================================================================ -->
+        <!-- SIDEBAR                                                          -->
+        <!-- ================================================================ -->
+        <aside id="sidebar" class="fixed inset-y-0 left-0 z-50 w-52 bg-[#0A0A0A] text-neutral-400 flex flex-col
+                                    transform -translate-x-full lg:relative lg:translate-x-0
+                                    transition-transform duration-300 ease-in-out">
+            <!-- Logo -->
+            <div class="flex items-center gap-3 px-5 h-14 border-b border-white/10 flex-shrink-0">
+                <img src="assets/logo.jpg" alt="CowAgent" class="w-8 h-8 rounded-lg flex-shrink-0">
+                <div class="flex flex-col min-w-0">
+                    <span class="text-white font-semibold text-sm truncate">CowAgent</span>
+                    <span class="text-neutral-500 text-xs" data-i18n="console">控制台</span>
+                </div>
+            </div>
+
+            <!-- Navigation -->
+            <nav class="flex-1 overflow-y-auto py-4 px-3 space-y-1">
+                <!-- Chat Group -->
+                <div class="menu-group open" data-group="chat">
+                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
+                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
+                        <span data-i18n="nav_chat">对话</span>
+                    </button>
+                    <div class="menu-group-items pl-2">
+                        <a class="sidebar-item active flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="chat">
+                            <i class="fas fa-message item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_chat">对话</span>
+                        </a>
+                    </div>
+                </div>
+
+                <!-- Management Group -->
+                <div class="menu-group open" data-group="manage">
+                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
+                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
+                        <span data-i18n="nav_manage">管理</span>
+                    </button>
+                    <div class="menu-group-items pl-2">
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="config">
+                            <i class="fas fa-sliders item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_config">配置</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="models">
+                            <i class="fas fa-microchip item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_models">模型</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="skills">
+                            <i class="fas fa-bolt item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_skills">技能</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="memory">
+                            <i class="fas fa-brain item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_memory">记忆</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="knowledge">
+                            <i class="fas fa-book item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_knowledge">知识</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="channels">
+                            <i class="fas fa-tower-broadcast item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_channels">通道</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="tasks">
+                            <i class="fas fa-clock item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_tasks">定时</span>
+                        </a>
+                    </div>
+                </div>
+
+                <!-- Monitor Group -->
+                <div class="menu-group open" data-group="monitor">
+                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
+                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
+                        <span data-i18n="nav_monitor">监控</span>
+                    </button>
+                    <div class="menu-group-items pl-2">
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="logs">
+                            <i class="fas fa-terminal item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_logs">日志</span>
+                        </a>
+                    </div>
+                </div>
+            </nav>
+
+            <!-- Sidebar Footer -->
+            <div class="px-4 py-3 border-t border-white/10 flex-shrink-0">
+                <div class="flex items-center gap-2 text-xs text-neutral-600">
+                    <i class="fas fa-circle text-[6px] text-primary-400"></i>
+                    <a id="sidebar-version"
+                       href="https://github.com/zhayujie/chatgpt-on-wechat/releases"
+                       target="_blank" rel="noopener noreferrer"
+                       class="hover:text-primary-400 transition-colors duration-150 cursor-pointer"></a>
+                </div>
+            </div>
+        </aside>
+
+        <!-- Mobile Overlay -->
+        <div id="sidebar-overlay" class="fixed inset-0 bg-black/50 z-40 hidden lg:hidden cursor-pointer" onclick="toggleSidebar()"></div>
+
+        <!-- ================================================================ -->
+        <!-- SESSION PANEL (collapsible)                                      -->
+        <!-- ================================================================ -->
+        <aside id="session-panel" class="session-panel hidden">
+            <div class="session-panel-header">
+                <span class="session-panel-title" data-i18n="session_history">历史会话</span>
+                <button class="session-panel-close" onclick="toggleSessionPanel()" title="Close">
+                    <i class="fas fa-times"></i>
+                </button>
+            </div>
+            <button class="session-panel-new" onclick="newChat()">
+                <i class="fas fa-plus"></i>
+                <span data-i18n="new_chat">新对话</span>
+            </button>
+            <div id="session-list" class="session-list"></div>
+        </aside>
+
+        <!-- Mobile overlay for session panel (click to close) -->
+        <div id="session-panel-overlay" class="session-panel-overlay hidden" onclick="closeSessionPanel()"></div>
+
+        <!-- ================================================================ -->
+        <!-- MAIN CONTENT                                                     -->
+        <!-- ================================================================ -->
+        <div id="main-content" class="flex-1 flex flex-col min-w-0 h-screen">
+            <!-- Top Header -->
+            <header class="h-14 flex items-center gap-3 px-4 border-b border-slate-200 dark:border-white/10 bg-white dark:bg-[#1A1A1A] flex-shrink-0 z-10">
+                <!-- Mobile menu toggle -->
+                <button id="menu-toggle" class="lg:hidden p-2 rounded-lg hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer transition-colors duration-150"
+                        onclick="toggleSidebar()">
+                    <i class="fas fa-bars text-slate-600 dark:text-slate-300"></i>
+                </button>
+
+                <!-- Session panel toggle -->
+                <button id="session-toggle-btn" class="p-2 rounded-lg hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer transition-colors duration-150"
+                        onclick="toggleSessionPanel()">
+                    <i class="fas fa-clock-rotate-left text-slate-500 dark:text-slate-400"></i>
+                </button>
+
+                <!-- Breadcrumb (hidden on mobile) -->
+                <div class="hidden lg:flex items-center gap-2 text-sm min-w-0">
+                    <span id="breadcrumb-group" class="text-slate-400 dark:text-slate-500 truncate" data-i18n="nav_chat">对话</span>
+                    <i class="fas fa-chevron-right text-[10px] text-slate-300 dark:text-slate-600"></i>
+                    <span id="breadcrumb-page" class="font-medium text-slate-700 dark:text-slate-200 truncate" data-i18n="menu_chat">对话</span>
+                </div>
+
+                <div class="flex-1"></div>
+
+                <!-- Language Selector (dropdown) -->
+                <div id="lang-selector" class="relative">
+                    <button id="lang-toggle" class="flex items-center gap-1.5 px-3 py-1.5 rounded-lg text-sm font-medium
+                                                     text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
+                                                     cursor-pointer transition-colors duration-150"
+                            onclick="toggleLangMenu(event)">
+                        <i class="fas fa-globe text-xs"></i>
+                        <span id="lang-label">EN</span>
+                        <i class="fas fa-chevron-down text-[10px] opacity-60"></i>
+                    </button>
+                    <div id="lang-menu" class="hidden absolute right-0 mt-1 min-w-[120px] py-1 rounded-lg z-50
+                                               bg-white dark:bg-slate-800 shadow-lg ring-1 ring-black/5 dark:ring-white/10">
+                        <button class="lang-menu-item w-full text-left px-3 py-1.5 text-sm text-slate-600 dark:text-slate-300
+                                       hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer" data-lang="zh"
+                                onclick="selectLanguage('zh')">简体中文</button>
+                        <button class="lang-menu-item w-full text-left px-3 py-1.5 text-sm text-slate-600 dark:text-slate-300
+                                       hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer" data-lang="zh-Hant"
+                                onclick="selectLanguage('zh-Hant')">繁體中文</button>
+                        <button class="lang-menu-item w-full text-left px-3 py-1.5 text-sm text-slate-600 dark:text-slate-300
+                                       hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer" data-lang="en"
+                                onclick="selectLanguage('en')">English</button>
+                    </div>
+                </div>
+
+                <!-- Theme Toggle -->
+                <button id="theme-toggle" class="p-2 rounded-lg text-slate-500 dark:text-slate-400
+                                                  hover:bg-slate-100 dark:hover:bg-white/10
+                                                  cursor-pointer transition-colors duration-150"
+                        onclick="toggleTheme()">
+                    <i id="theme-icon" class="fas fa-moon"></i>
+                </button>
+
+                <!-- Docs Link -->
+                <a id="docs-link" href="https://docs.cowagent.ai" target="_blank" rel="noopener noreferrer"
+                   class="p-2 rounded-lg text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
+                          cursor-pointer transition-colors duration-150" title="Documentation">
+                    <i class="fas fa-book text-base"></i>
+                </a>
+
+                <!-- Website Link -->
+                <a href="https://cowagent.ai" target="_blank" rel="noopener noreferrer"
+                   class="p-2 rounded-lg text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
+                          cursor-pointer transition-colors duration-150" title="Website">
+                    <i class="fas fa-home text-base"></i>
+                </a>
+
+                <!-- GitHub Link -->
+                <a href="https://github.com/zhayujie/chatgpt-on-wechat" target="_blank" rel="noopener noreferrer"
+                   class="p-2 rounded-lg text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
+                          cursor-pointer transition-colors duration-150" title="GitHub">
+                    <i class="fab fa-github text-lg"></i>
+                </a>
+
+                <!-- Logout Button (hidden by default) -->
+                <button id="logout-btn-header" class="p-2 rounded-lg text-slate-500 dark:text-slate-400
+                                                       hover:bg-red-50 hover:text-red-500 dark:hover:bg-red-500/10 dark:hover:text-red-400
+                                                       cursor-pointer transition-colors duration-150 hidden"
+                        onclick="handleLogout()" title="Logout" data-i18n-title="logout">
+                    <i class="fas fa-sign-out-alt text-base"></i>
+                </button>
+            </header>
+
+            <!-- Content Area -->
+            <div id="content-area" class="flex-1 overflow-hidden">
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Chat                                              -->
+                <!-- ====================================================== -->
+                <div id="view-chat" class="view active relative">
+                    <!-- Messages -->
+                    <div id="chat-messages" class="flex-1 overflow-y-auto">
+                        <!-- Welcome Screen -->
+                        <div id="welcome-screen" class="flex flex-col items-center justify-center h-full px-6 pb-16" style="padding-top: 6vh">
+                            <img src="assets/logo.jpg" alt="CowAgent" class="w-16 h-16 rounded-2xl mb-6 shadow-lg shadow-primary-500/20">
+                            <h1 id="welcome-title" class="text-2xl font-bold text-slate-800 dark:text-slate-100 mb-3">CowAgent</h1>
+                            <p id="welcome-subtitle" class="text-slate-500 dark:text-slate-400 text-center max-w-lg mb-10 leading-relaxed"
+                               data-i18n-html="welcome_subtitle">我可以帮你解答问题、管理计算机、创造和执行技能，并通过<br>长期记忆和知识库不断成长</p>
+
+                            <div class="grid grid-cols-2 sm:grid-cols-3 gap-3 w-full max-w-2xl">
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-blue-50 dark:bg-blue-900/30 flex items-center justify-center">
+                                            <i class="fas fa-folder-open text-blue-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_sys_title">系统管理</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_sys_text">查看工作空间里有哪些文件</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-amber-50 dark:bg-amber-900/30 flex items-center justify-center">
+                                            <i class="fas fa-clock text-amber-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_task_title">定时任务</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_task_text">1分钟后提醒我检查服务器</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center">
+                                            <i class="fas fa-code text-emerald-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_code_title">编程助手</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_code_text">搜索AI资讯并生成可视化网页报告</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-violet-50 dark:bg-violet-900/30 flex items-center justify-center">
+                                            <i class="fas fa-book text-violet-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_knowledge_title">知识库</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_knowledge_text">查看知识库当前文档情况</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-rose-50 dark:bg-rose-900/30 flex items-center justify-center">
+                                            <i class="fas fa-puzzle-piece text-rose-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_skill_title">技能系统</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_skill_text">查看所有支持的工具和技能</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200"
+                                     data-send="/help">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-slate-100 dark:bg-slate-800 flex items-center justify-center">
+                                            <i class="fas fa-terminal text-slate-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_web_title">指令中心</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_web_text">查看全部命令</p>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+
+                    <!-- Scroll-to-bottom FAB -->
+                    <button id="scroll-to-bottom-btn"
+                            class="hidden absolute right-5 bottom-[80px] z-10
+                                   w-9 h-9 rounded-full shadow-lg
+                                   bg-white dark:bg-[#2A2A2A] border border-slate-200 dark:border-white/15
+                                   text-slate-500 dark:text-slate-400 hover:text-primary-500 dark:hover:text-primary-400
+                                   flex items-center justify-center cursor-pointer transition-all duration-200
+                                   hover:shadow-xl hover:scale-105"
+                            onclick="_autoScrollEnabled = true; scrollChatToBottom(true);">
+                        <i class="fas fa-chevron-down text-sm"></i>
+                    </button>
+
+                    <!-- Chat Input -->
+                    <div class="flex-shrink-0 border-t border-slate-200 dark:border-white/10 bg-white dark:bg-[#1A1A1A] px-4 py-3">
+                        <div class="max-w-3xl mx-auto">
+                            <!-- Attachment preview bar -->
+                            <div id="attachment-preview" class="attachment-preview hidden"></div>
+                            <div class="flex items-center gap-2 relative">
+                                <div class="flex items-center flex-shrink-0">
+                                    <button id="new-chat-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
+                                                                     text-slate-400 hover:text-primary-500 hover:bg-primary-50 dark:hover:bg-primary-900/20
+                                                                     cursor-pointer transition-colors duration-150"
+                                            onclick="newChat()">
+                                        <i class="fas fa-plus text-base"></i>
+                                    </button>
+                                    <button id="clear-context-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
+                                                                          text-slate-400 hover:text-amber-500 hover:bg-amber-50 dark:hover:bg-amber-900/20
+                                                                          cursor-pointer transition-colors duration-150"
+                                            onclick="clearContext()">
+                                        <i class="fas fa-trash-can text-base"></i>
+                                    </button>
+                                    <button id="attach-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
+                                                                   text-slate-400 hover:text-primary-500 hover:bg-primary-50 dark:hover:bg-primary-900/20
+                                                                   cursor-pointer transition-colors duration-150"
+                                            type="button"
+                                            onclick="toggleAttachMenu(event)">
+                                        <i class="fas fa-paperclip text-base"></i>
+                                    </button>
+                                </div>
+                                <input type="file" id="file-input" class="hidden" multiple
+                                       accept="image/*,.pdf,.doc,.docx,.xls,.xlsx,.ppt,.pptx,.txt,.csv,.json,.xml,.zip,.rar,.7z,.py,.js,.ts,.java,.c,.cpp,.go,.rs,.md">
+                                <input type="file" id="folder-input" class="hidden" multiple webkitdirectory directory>
+                                <div id="attach-menu" class="attach-menu hidden">
+                                    <button id="attach-file-option" type="button" class="attach-menu-item" onclick="triggerFileUpload()">
+                                        <i class="fas fa-file-arrow-up"></i>
+                                        <span data-i18n="attach_menu_file">上传文件</span>
+                                    </button>
+                                    <button id="attach-folder-option" type="button" class="attach-menu-item" onclick="triggerFolderUpload()">
+                                        <i class="fas fa-folder-plus"></i>
+                                        <span data-i18n="attach_menu_folder">上传文件夹</span>
+                                    </button>
+                                </div>
+                                <div id="slash-menu" class="slash-menu hidden"></div>
+                                <div class="flex-1 min-w-0 relative flex items-center">
+                                    <textarea id="chat-input"
+                                              class="w-full pl-4 pr-11 py-[10px] rounded-xl border border-slate-200 dark:border-slate-600
+                                                     bg-slate-50 dark:bg-white/5 text-slate-800 dark:text-slate-100
+                                                     placeholder:text-slate-400 dark:placeholder:text-slate-500
+                                                     focus:outline-none focus:ring-0 focus:border-primary-600
+                                                     text-sm leading-relaxed"
+                                              rows="1"
+                                              data-i18n-placeholder="input_placeholder"
+                                              placeholder="输入消息，或输入 / 使用指令"></textarea>
+                                    <button id="mic-btn" type="button"
+                                            class="absolute right-2 top-1/2 -translate-y-1/2 w-8 h-8 flex items-center justify-center rounded-lg
+                                                   text-slate-400 hover:text-primary-500 hover:bg-primary-50 dark:hover:bg-primary-900/20
+                                                   cursor-pointer transition-colors duration-150"
+                                            data-i18n-title="mic_idle_title" title="点击录音 / 再按一次结束">
+                                        <i class="fas fa-microphone text-sm"></i>
+                                    </button>
+                                </div>
+                                <button id="send-btn"
+                                        class="flex-shrink-0 w-10 h-10 flex items-center justify-center rounded-lg
+                                               bg-primary-400 text-white hover:bg-primary-500
+                                               disabled:bg-slate-300 dark:disabled:bg-slate-600
+                                               disabled:cursor-not-allowed cursor-pointer transition-colors duration-150"
+                                        disabled>
+                                    <i class="fas fa-paper-plane text-sm"></i>
+                                </button>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Config                                            -->
+                <!-- ====================================================== -->
+                <div id="view-config" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="config_title">配置管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="config_desc">管理模型和 Agent 配置</p>
+                                </div>
+                            </div>
+                            <div class="grid gap-6">
+
+                                <!-- Model Config Card -->
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6">
+                                    <div class="flex items-center gap-3 mb-5">
+                                        <div class="w-9 h-9 rounded-lg bg-primary-50 dark:bg-primary-900/30 flex items-center justify-center">
+                                            <i class="fas fa-microchip text-primary-500 text-sm"></i>
+                                        </div>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_model">模型配置</h3>
+                                        <a class="ml-auto text-xs text-slate-500 dark:text-slate-400 hover:text-primary-500 dark:hover:text-primary-400 cursor-pointer transition-colors flex items-center gap-1"
+                                           onclick="navigateTo('models')">
+                                            <span data-i18n="config_model_advanced">高级配置</span>
+                                            <i class="fas fa-arrow-right text-[10px]"></i>
+                                        </a>
+                                    </div>
+                                    <div class="space-y-5">
+                                        <!-- Provider -->
+                                        <div>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_provider">模型厂商</label>
+                                            <div id="cfg-provider" class="cfg-dropdown" tabindex="0">
+                                                <div class="cfg-dropdown-selected">
+                                                    <span class="cfg-dropdown-text">--</span>
+                                                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                                                </div>
+                                                <div class="cfg-dropdown-menu"></div>
+                                            </div>
+                                            <div id="cfg-custom-tip" class="mt-1.5 text-xs text-slate-400 dark:text-slate-500 hidden">
+                                                <i class="fas fa-info-circle mr-1"></i><span data-i18n="config_custom_tip">接口需遵循 OpenAI API 协议</span>
+                                            </div>
+                                        </div>
+                                        <!-- Model -->
+                                        <div>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_model_name">模型</label>
+                                            <div id="cfg-model-select" class="cfg-dropdown" tabindex="0">
+                                                <div class="cfg-dropdown-selected">
+                                                    <span class="cfg-dropdown-text">--</span>
+                                                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                                                </div>
+                                                <div class="cfg-dropdown-menu"></div>
+                                            </div>
+                                            <div id="cfg-model-custom-wrap" class="mt-2 hidden">
+                                                <input id="cfg-model-custom" type="text"
+                                                       class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                              bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                              focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                                                       data-i18n-placeholder="config_custom_model_hint" placeholder="输入自定义模型名称">
+                                            </div>
+                                        </div>
+                                        <!-- API Key -->
+                                        <div id="cfg-api-key-wrap">
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Key</label>
+                                            <div class="relative">
+                                                <input id="cfg-api-key" type="text" autocomplete="off" data-1p-ignore data-lpignore="true"
+                                                       class="w-full px-3 py-2 pr-10 rounded-lg border border-slate-200 dark:border-slate-600
+                                                              bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                              focus:outline-none focus:border-primary-500 font-mono transition-colors cfg-key-masked"
+                                                       placeholder="sk-...">
+                                                <button type="button" id="cfg-api-key-toggle"
+                                                        class="absolute right-2.5 top-1/2 -translate-y-1/2 text-slate-400 hover:text-slate-600
+                                                               dark:hover:text-slate-300 cursor-pointer transition-colors p-1"
+                                                        onclick="toggleApiKeyVisibility()">
+                                                    <i class="fas fa-eye text-xs"></i>
+                                                </button>
+                                            </div>
+                                        </div>
+                                        <!-- API Base -->
+                                        <div id="cfg-api-base-wrap" class="hidden">
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Base</label>
+                                            <input id="cfg-api-base" type="text"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                                                   placeholder="https://...">
+                                        </div>
+                                        <!-- Save Model Button -->
+                                        <div class="flex items-center justify-end gap-3 pt-1">
+                                            <span id="cfg-model-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                                            <button id="cfg-model-save"
+                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                                                    onclick="saveModelConfig()" data-i18n="config_save">保存</button>
+                                        </div>
+                                    </div>
+                                </div>
+
+                                <!-- Agent Config Card -->
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6">
+                                    <div class="flex items-center gap-3 mb-5">
+                                        <div class="w-9 h-9 rounded-lg bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center">
+                                            <i class="fas fa-robot text-emerald-500 text-sm"></i>
+                                        </div>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_agent">Agent 配置</h3>
+                                    </div>
+                                    <div class="space-y-4">
+                                        <div>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_tokens">最大上下文 Token</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_tokens_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <input id="cfg-max-tokens" type="number" min="1000" max="200000" step="1000"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
+                                        </div>
+                                        <div>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_turns">最大记忆轮次</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_turns_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <input id="cfg-max-turns" type="number" min="1" max="100" step="1"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
+                                        </div>
+                                        <div>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_steps">最大执行步数</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_steps_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <input id="cfg-max-steps" type="number" min="1" max="50" step="1"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
+                                        </div>
+                                        <div class="flex items-center justify-between">
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400">
+                                                <span data-i18n="config_enable_thinking">Deep Thinking</span>
+                                                <span class="cfg-tip" data-tip-key="config_enable_thinking_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <label class="relative inline-flex items-center cursor-pointer">
+                                                <input id="cfg-enable-thinking" type="checkbox" class="sr-only peer">
+                                                <div class="w-9 h-5 bg-slate-200 dark:bg-slate-700 peer-checked:bg-primary-400 rounded-full
+                                                            after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white
+                                                            after:rounded-full after:h-4 after:w-4 after:transition-all peer-checked:after:translate-x-full"></div>
+                                            </label>
+                                        </div>
+                                        <div class="flex items-center justify-between">
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400">
+                                                <span data-i18n="config_self_evolution">Self-Evolution</span>
+                                                <span class="cfg-tip" data-tip-key="config_self_evolution_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <label class="relative inline-flex items-center cursor-pointer">
+                                                <input id="cfg-self-evolution" type="checkbox" class="sr-only peer">
+                                                <div class="w-9 h-5 bg-slate-200 dark:bg-slate-700 peer-checked:bg-primary-400 rounded-full
+                                                            after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white
+                                                            after:rounded-full after:h-4 after:w-4 after:transition-all peer-checked:after:translate-x-full"></div>
+                                            </label>
+                                        </div>
+                                        <div class="flex items-center justify-end gap-3 pt-1">
+                                            <span id="cfg-agent-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                                            <button id="cfg-agent-save"
+                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                                                    onclick="saveAgentConfig()" data-i18n="config_save">保存</button>
+                                        </div>
+                                    </div>
+                                </div>
+
+                                <!-- Security Config Card -->
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6">
+                                    <div class="flex items-center gap-3 mb-5">
+                                        <div class="w-9 h-9 rounded-lg bg-amber-50 dark:bg-amber-900/30 flex items-center justify-center">
+                                            <i class="fas fa-lock text-amber-500 text-sm"></i>
+                                        </div>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_security">安全设置</h3>
+                                    </div>
+                                    <div class="space-y-4">
+                                        <div>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_password">访问密码</label>
+                                            <input id="cfg-password" type="password" autocomplete="new-password"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors
+                                                          cfg-key-masked"
+                                                   data-masked="1">
+                                            <p class="text-xs text-slate-400 dark:text-slate-500 mt-1.5" data-i18n="config_password_hint">留空则不启用密码保护</p>
+                                        </div>
+                                        <div class="flex items-center justify-end gap-3 pt-1">
+                                            <span id="cfg-password-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                                            <button id="cfg-password-save"
+                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                                                    onclick="savePasswordConfig()" data-i18n="config_save">保存</button>
+                                        </div>
+                                    </div>
+                                </div>
+
+                                <!-- Language Config Card -->
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6">
+                                    <div class="flex items-center gap-3 mb-5">
+                                        <div class="w-9 h-9 rounded-lg bg-sky-50 dark:bg-sky-900/30 flex items-center justify-center">
+                                            <i class="fas fa-language text-sky-500 text-sm"></i>
+                                        </div>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_language">语言</h3>
+                                    </div>
+                                    <div class="space-y-4">
+                                        <div>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_language">语言</span>
+                                                <span class="cfg-tip" data-tip-key="config_language_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <div id="cfg-lang-select" class="cfg-dropdown" tabindex="0">
+                                                <div class="cfg-dropdown-selected">
+                                                    <span class="cfg-dropdown-text">--</span>
+                                                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                                                </div>
+                                                <div class="cfg-dropdown-menu"></div>
+                                            </div>
+                                        </div>
+                                    </div>
+                                </div>
+
+                            </div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Skills                                            -->
+                <!-- ====================================================== -->
+                <div id="view-skills" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="skills_title">技能管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="skills_desc">查看、启用或禁用 Agent 技能</p>
+                                </div>
+                                <a href="https://skills.cowagent.ai/" target="_blank"
+                                   class="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-lg text-xs font-medium text-primary-500 bg-primary-50 dark:bg-primary-900/20 hover:bg-primary-100 dark:hover:bg-primary-900/30 transition-colors">
+                                    <i class="fas fa-puzzle-piece text-[10px]"></i>
+                                    <span data-i18n="skills_hub_btn">探索技能广场</span>
+                                </a>
+                            </div>
+
+                            <!-- Built-in Tools Section -->
+                            <div class="mb-8">
+                                <div class="flex items-center gap-2 mb-3">
+                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="tools_section_title">内置工具</span>
+                                    <span id="tools-count-badge" class="hidden px-2 py-0.5 rounded-full text-xs bg-slate-100 dark:bg-white/10 text-slate-500 dark:text-slate-400"></span>
+                                </div>
+                                <div id="tools-empty" class="flex items-center gap-2 py-4 text-slate-400 dark:text-slate-500 text-sm">
+                                    <i class="fas fa-spinner fa-spin text-xs"></i>
+                                    <span data-i18n="tools_loading">加载工具中...</span>
+                                </div>
+                                <div id="tools-list" class="grid gap-3 sm:grid-cols-2 hidden"></div>
+                            </div>
+
+                            <!-- Skills Section -->
+                            <div>
+                                <div class="flex items-center gap-2 mb-3">
+                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="skills_section_title">技能</span>
+                                    <span id="skills-count-badge" class="hidden px-2 py-0.5 rounded-full text-xs bg-slate-100 dark:bg-white/10 text-slate-500 dark:text-slate-400"></span>
+                                </div>
+                                <div id="skills-empty" class="flex flex-col items-center justify-center py-12">
+                                    <div class="w-14 h-14 rounded-2xl bg-amber-50 dark:bg-amber-900/20 flex items-center justify-center mb-3">
+                                        <i class="fas fa-bolt text-amber-400 text-lg"></i>
+                                    </div>
+                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="skills_loading">加载技能中...</p>
+                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="skills_loading_desc">技能加载后将显示在此处</p>
+                                </div>
+                                <div id="skills-list" class="grid gap-4 sm:grid-cols-2"></div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Memory                                            -->
+                <!-- ====================================================== -->
+                <div id="view-memory" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+
+                            <!-- Panel: list -->
+                            <div id="memory-panel-list">
+                                <div class="flex items-center justify-between mb-6">
+                                    <div>
+                                        <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="memory_title">记忆管理</h2>
+                                        <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="memory_desc">查看 Agent 记忆文件和内容</p>
+                                    </div>
+                                    <div class="flex items-center bg-slate-100 dark:bg-white/10 rounded-lg p-0.5">
+                                        <button id="memory-tab-files" onclick="switchMemoryTab('files')"
+                                                class="memory-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150 active">
+                                            <i class="fas fa-file-lines mr-1.5"></i><span data-i18n="memory_tab_files">记忆文件</span>
+                                        </button>
+                                        <button id="memory-tab-dreams" onclick="switchMemoryTab('dreams')"
+                                                class="memory-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150">
+                                            <i class="fas fa-seedling mr-1.5"></i><span data-i18n="memory_tab_dreams">自主进化</span>
+                                        </button>
+                                    </div>
+                                </div>
+                                <div id="memory-empty" class="flex flex-col items-center justify-center py-20">
+                                    <div class="w-16 h-16 rounded-2xl bg-purple-50 dark:bg-purple-900/20 flex items-center justify-center mb-4">
+                                        <i class="fas fa-brain text-purple-400 text-xl"></i>
+                                    </div>
+                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="memory_loading">加载记忆文件中...</p>
+                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="memory_loading_desc">记忆文件将显示在此处</p>
+                                </div>
+                                <div id="memory-list" class="hidden">
+                                    <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                        <table class="w-full">
+                                            <thead>
+                                                <tr class="border-b border-slate-200 dark:border-white/10">
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_name">文件名</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_type">类型</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_size">大小</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_updated">更新时间</th>
+                                                </tr>
+                                            </thead>
+                                            <tbody id="memory-table-body"></tbody>
+                                        </table>
+                                    </div>
+                                    <div id="memory-pagination" class="flex items-center justify-between mt-4 text-sm text-slate-500 dark:text-slate-400"></div>
+                                </div>
+                            </div>
+
+                            <!-- Panel: file viewer (replaces list) -->
+                            <div id="memory-panel-viewer" class="hidden">
+                                <div class="flex items-center gap-3 mb-6">
+                                    <button onclick="closeMemoryViewer()"
+                                            class="flex items-center gap-1.5 px-3 py-1.5 rounded-lg text-sm
+                                                   text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
+                                                   border border-slate-200 dark:border-white/10 transition-colors cursor-pointer">
+                                        <i class="fas fa-arrow-left text-xs"></i>
+                                        <span data-i18n="memory_back">返回列表</span>
+                                    </button>
+                                    <h2 id="memory-viewer-title"
+                                        class="text-base font-semibold text-slate-800 dark:text-slate-100 font-mono truncate"></h2>
+                                </div>
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                    <div id="memory-viewer-content"
+                                         class="p-5 overflow-y-auto text-sm msg-content text-slate-700 dark:text-slate-200"
+                                         style="max-height: calc(100vh - 220px)"></div>
+                                </div>
+                            </div>
+
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Knowledge                                         -->
+                <!-- ====================================================== -->
+                <div id="view-knowledge" class="view">
+                    <div class="flex-1 min-h-0 overflow-y-auto md:overflow-hidden p-4 md:p-8 lg:p-10 md:flex md:flex-col">
+                        <div class="w-full max-w-[1600px] mx-auto md:flex-1 md:min-h-0 md:flex md:flex-col">
+
+                            <!-- Header -->
+                            <div class="flex flex-col sm:flex-row sm:items-center justify-between gap-3 mb-4 md:mb-6 md:flex-shrink-0">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="knowledge_title">知识库</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="knowledge_desc">浏览和探索你的知识库</p>
+                                </div>
+                                <div class="flex items-center gap-2">
+                                    <span id="knowledge-stats" class="text-xs text-slate-400 dark:text-slate-500 hidden sm:inline"></span>
+                                    <span id="knowledge-action-status" class="text-xs opacity-0 transition-opacity duration-200"></span>
+                                    <div class="flex items-center bg-slate-100 dark:bg-white/10 rounded-lg p-0.5">
+                                        <button id="knowledge-tab-docs" onclick="switchKnowledgeTab('docs')"
+                                                class="knowledge-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150 active">
+                                            <i class="fas fa-folder-tree mr-1.5"></i><span data-i18n="knowledge_tab_docs">文档</span>
+                                        </button>
+                                        <button id="knowledge-tab-graph" onclick="switchKnowledgeTab('graph')"
+                                                class="knowledge-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150">
+                                            <i class="fas fa-diagram-project mr-1.5"></i><span data-i18n="knowledge_tab_graph">图谱</span>
+                                        </button>
+                                    </div>
+                                    <div id="knowledge-new-menu" class="relative">
+                                        <button onclick="toggleKnowledgeNewMenu(event)"
+                                                class="flex items-center gap-1.5 px-3 py-1.5 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-xs font-medium cursor-pointer transition-colors">
+                                            <i class="fas fa-plus"></i><span data-i18n="knowledge_new">新建</span><i class="fas fa-chevron-down text-[9px] ml-0.5"></i>
+                                        </button>
+                                        <div id="knowledge-new-menu-list"
+                                             class="hidden absolute right-0 mt-1.5 w-44 z-50 bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-lg shadow-lg py-1">
+                                            <button onclick="createKnowledgeCategory(); closeKnowledgeNewMenu()"
+                                                    class="w-full flex items-center gap-2.5 px-3 py-2 text-xs text-slate-600 dark:text-slate-300 hover:bg-slate-50 dark:hover:bg-white/5 cursor-pointer transition-colors">
+                                                <i class="fas fa-folder-plus w-3.5 text-slate-400"></i><span data-i18n="knowledge_new_category">新建分类</span>
+                                            </button>
+                                            <button onclick="createKnowledgeDocument(); closeKnowledgeNewMenu()"
+                                                    class="w-full flex items-center gap-2.5 px-3 py-2 text-xs text-slate-600 dark:text-slate-300 hover:bg-slate-50 dark:hover:bg-white/5 cursor-pointer transition-colors">
+                                                <i class="fas fa-file-circle-plus w-3.5 text-slate-400"></i><span data-i18n="knowledge_new_document">新建文档</span>
+                                            </button>
+                                            <button onclick="selectKnowledgeImportFiles(); closeKnowledgeNewMenu()"
+                                                    class="w-full flex items-center gap-2.5 px-3 py-2 text-xs text-slate-600 dark:text-slate-300 hover:bg-slate-50 dark:hover:bg-white/5 cursor-pointer transition-colors">
+                                                <i class="fas fa-file-arrow-up w-3.5 text-slate-400"></i><span data-i18n="knowledge_import_documents">导入文档</span>
+                                            </button>
+                                        </div>
+                                    </div>
+                                    <input id="knowledge-import-input" type="file" class="hidden" multiple accept=".md,.txt,text/markdown,text/plain">
+                                </div>
+                            </div>
+
+                            <!-- Empty state -->
+                            <div id="knowledge-empty" class="flex flex-col items-center justify-center py-20">
+                                <div class="w-16 h-16 rounded-2xl bg-emerald-50 dark:bg-emerald-900/20 flex items-center justify-center mb-4">
+                                    <i class="fas fa-book text-emerald-400 text-xl"></i>
+                                </div>
+                                <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="knowledge_loading">加载知识库中...</p>
+                                <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="knowledge_loading_desc">知识页面将显示在这里</p>
+                                <div id="knowledge-empty-guide" class="hidden mt-6 max-w-sm text-center">
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mb-4" data-i18n="knowledge_empty_guide">在对话中发送文档、链接或主题给 Agent，它会自动整理到你的知识库中。</p>
+                                    <button onclick="navigateTo('chat')"
+                                            class="inline-flex items-center gap-2 px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600
+                                                   text-white text-sm font-medium cursor-pointer transition-colors duration-150">
+                                        <i class="fas fa-message text-xs"></i>
+                                        <span data-i18n="knowledge_go_chat">开始对话</span>
+                                    </button>
+                                </div>
+                            </div>
+
+                            <!-- Documents panel -->
+                            <div id="knowledge-panel-docs" class="hidden md:flex-1 md:min-h-0">
+                                <div class="flex flex-col md:flex-row gap-4 md:gap-6 md:h-full">
+                                    <!-- File tree -->
+                                    <div id="knowledge-sidebar" class="w-full md:w-72 lg:w-80 flex-shrink-0 md:h-full">
+                                        <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden flex flex-col md:h-full">
+                                            <div class="px-4 py-3 border-b border-slate-200 dark:border-white/10 flex-shrink-0">
+                                                <div class="relative">
+                                                    <i class="fas fa-search absolute left-3 top-1/2 -translate-y-1/2 text-slate-400 text-xs"></i>
+                                                    <input id="knowledge-search" type="text" placeholder="Search..."
+                                                           class="w-full pl-8 pr-3 py-1.5 text-xs bg-slate-50 dark:bg-white/5 border border-slate-200 dark:border-white/10 rounded-lg text-slate-700 dark:text-slate-200 placeholder-slate-400 dark:placeholder-slate-500 focus:outline-none focus:ring-1 focus:ring-primary-400/50"
+                                                           oninput="filterKnowledgeTree(this.value)">
+                                                </div>
+                                            </div>
+                                            <div id="knowledge-tree" class="p-2 overflow-y-auto flex-1 max-h-[50vh] md:max-h-none"></div>
+                                        </div>
+                                    </div>
+                                    <!-- Content viewer -->
+                                    <div class="flex-1 min-w-0 md:h-full">
+                                        <div id="knowledge-content-placeholder"
+                                             class="flex flex-col items-center justify-center py-20 md:h-full text-slate-400 dark:text-slate-500 bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10">
+                                            <i class="fas fa-file-lines text-3xl mb-3 opacity-40"></i>
+                                            <p class="text-sm" data-i18n="knowledge_select_hint">选择一个文档查看</p>
+                                        </div>
+                                        <div id="knowledge-content-viewer" class="hidden md:h-full">
+                                            <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden flex flex-col md:h-full">
+                                                <div class="flex items-center gap-3 px-4 md:px-5 py-3 border-b border-slate-200 dark:border-white/10 flex-shrink-0">
+                                                    <button onclick="knowledgeMobileBack()" class="md:hidden p-1 -ml-1 text-slate-400 hover:text-slate-600 dark:hover:text-slate-300 cursor-pointer">
+                                                        <i class="fas fa-arrow-left text-xs"></i>
+                                                    </button>
+                                                    <i class="fas fa-file-lines text-slate-400 text-sm hidden md:inline"></i>
+                                                    <span id="knowledge-viewer-title" class="text-sm font-medium text-slate-700 dark:text-slate-200 truncate"></span>
+                                                    <span id="knowledge-viewer-path" class="text-xs text-slate-400 dark:text-slate-500 ml-auto font-mono truncate hidden md:inline"></span>
+                                                </div>
+                                                <div id="knowledge-viewer-body"
+                                                     class="p-4 md:p-5 overflow-y-auto flex-1 max-h-[60vh] md:max-h-none text-sm msg-content text-slate-700 dark:text-slate-200"></div>
+                                            </div>
+                                        </div>
+                                    </div>
+                                </div>
+                            </div>
+
+                            <!-- Graph panel -->
+                            <div id="knowledge-panel-graph" class="hidden">
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                    <div id="knowledge-graph-container" class="w-full h-[60vh] md:h-[calc(100vh-220px)]"></div>
+                                </div>
+                            </div>
+
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Models                                            -->
+                <!-- ====================================================== -->
+                <div id="view-models" class="view">
+                    <!-- Tailwind JIT safelist: capability-card icon colors are
+                         emitted from JS template strings. Listing them here
+                         (display:none) guarantees the CDN-side compiler picks
+                         them up regardless of render timing. -->
+                    <div class="hidden bg-blue-50 dark:bg-blue-900/30 text-blue-500
+                                       bg-orange-50 dark:bg-orange-900/30 text-orange-500
+                                       bg-purple-50 dark:bg-purple-900/30 text-purple-500
+                                       bg-amber-50 dark:bg-amber-900/30 text-amber-500
+                                       bg-primary-50 dark:bg-primary-900/30 text-primary-500"></div>
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="models_title">模型管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="models_desc">统一管理对话、视觉、语音、向量、图像、搜索能力</p>
+                                </div>
+                                <button id="models-add-vendor-btn" onclick="openVendorModal('')"
+                                        class="flex items-center gap-2 px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600
+                                               text-white text-sm font-medium cursor-pointer transition-colors duration-150">
+                                    <i class="fas fa-plus text-xs"></i>
+                                    <span data-i18n="models_add_vendor">添加厂商</span>
+                                </button>
+                            </div>
+                            <div id="models-loading" class="flex items-center gap-2 py-12 justify-center text-slate-400 dark:text-slate-500 text-sm">
+                                <i class="fas fa-spinner fa-spin text-xs"></i><span>Loading...</span>
+                            </div>
+                            <div id="models-content" class="grid gap-6 hidden"></div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Channels                                          -->
+                <!-- ====================================================== -->
+                <div id="view-channels" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="channels_title">通道管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="channels_desc">管理已接入的消息通道</p>
+                                </div>
+                                <button id="add-channel-btn" onclick="openAddChannelPanel()"
+                                        class="flex items-center gap-2 px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600
+                                               text-white text-sm font-medium cursor-pointer transition-colors duration-150">
+                                    <i class="fas fa-plus text-xs"></i>
+                                    <span data-i18n="channels_add">接入通道</span>
+                                </button>
+                            </div>
+                            <div id="channels-content" class="grid gap-4"></div>
+                            <div id="channels-add-panel" class="hidden mt-4"></div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Tasks                                             -->
+                <!-- ====================================================== -->
+                <div id="view-tasks" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-4xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="tasks_title">定时任务</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="tasks_desc">查看和管理定时任务</p>
+                                </div>
+                                <div class="flex items-center gap-2">
+                                    <button id="task-refresh-btn" onclick="refreshTasksView()"
+                                            class="px-3 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                                                   text-slate-600 dark:text-slate-300 hover:bg-slate-50 dark:hover:bg-white/5
+                                                   text-sm font-medium cursor-pointer transition-colors duration-150">
+                                        <i class="fas fa-refresh text-xs"></i>
+                                    </button>
+                                </div>
+                            </div>
+                            <div id="tasks-empty" class="flex flex-col items-center justify-center py-20">
+                                <div class="w-16 h-16 rounded-2xl bg-rose-50 dark:bg-rose-900/20 flex items-center justify-center mb-4">
+                                    <i class="fas fa-clock text-rose-400 text-xl"></i>
+                                </div>
+                                <p class="text-slate-500 dark:text-slate-400 font-medium">Loading...</p>
+                            </div>
+                            <div id="tasks-list" class="grid gap-4 hidden"></div>
+                        </div>
+                    </div>
+                </div>
+
+                <!-- ====================================================== -->
+                <!-- VIEW: Logs                                              -->
+                <!-- ====================================================== -->
+                <div id="view-logs" class="view">
+                    <div class="flex-1 overflow-y-auto p-6">
+                        <div class="max-w-5xl mx-auto">
+                            <div class="flex items-center justify-between mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="logs_title">日志</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="logs_desc">实时日志输出 (run.log)</p>
+                                </div>
+                            </div>
+                            <!-- Log Terminal -->
+                            <div class="bg-slate-900 rounded-xl border border-slate-700 overflow-hidden shadow-lg">
+                                <div class="flex items-center gap-2 px-4 py-2.5 bg-slate-800 border-b border-slate-700">
+                                    <div class="flex gap-1.5">
+                                        <span class="w-3 h-3 rounded-full bg-red-500/80"></span>
+                                        <span class="w-3 h-3 rounded-full bg-amber-500/80"></span>
+                                        <span class="w-3 h-3 rounded-full bg-emerald-500/80"></span>
+                                    </div>
+                                    <span class="text-xs text-slate-400 ml-2 font-mono">run.log</span>
+                                    <div class="flex-1"></div>
+                                    <div class="flex items-center gap-3 mr-2">
+                                        <label class="flex items-center gap-1 cursor-pointer select-none">
+                                            <input type="checkbox" class="log-filter-cb" data-level="debug" checked>
+                                            <span class="text-xs text-slate-400">DEBUG</span>
+                                        </label>
+                                        <label class="flex items-center gap-1 cursor-pointer select-none">
+                                            <input type="checkbox" class="log-filter-cb" data-level="info" checked>
+                                            <span class="text-xs text-blue-400">INFO</span>
+                                        </label>
+                                        <label class="flex items-center gap-1 cursor-pointer select-none">
+                                            <input type="checkbox" class="log-filter-cb" data-level="warning" checked>
+                                            <span class="text-xs text-yellow-400">WARNING</span>
+                                        </label>
+                                        <label class="flex items-center gap-1 cursor-pointer select-none">
+                                            <input type="checkbox" class="log-filter-cb" data-level="error" checked>
+                                            <span class="text-xs text-red-400">ERROR</span>
+                                        </label>
+                                        <label class="flex items-center gap-1 cursor-pointer select-none">
+                                            <input type="checkbox" class="log-filter-cb" data-level="critical" checked>
+                                            <span class="text-xs text-white font-bold">CRITICAL</span>
+                                        </label>
+                                    </div>
+                                    <div class="flex items-center gap-1.5">
+                                        <span class="w-2 h-2 rounded-full bg-emerald-500 animate-pulse"></span>
+                                        <span class="text-xs text-slate-500" data-i18n="logs_live">实时</span>
+                                    </div>
+                                </div>
+                                <div id="log-output" class="p-4 overflow-y-auto font-mono text-xs leading-relaxed text-slate-300 whitespace-pre-wrap break-all" style="height: calc(100vh - 272px)">
+                                    <p class="text-slate-500" data-i18n="logs_coming_msg">日志流即将在此提供。将连接 run.log 实现类似 tail -f 的实时输出。</p>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+
+            </div><!-- /content-area -->
+        </div><!-- /main-content -->
+    </div><!-- /app -->
+
+    <!-- Knowledge Action Dialog -->
+    <div id="knowledge-dialog-overlay" class="fixed inset-0 bg-black/50 z-[200] hidden flex items-center justify-center">
+        <div id="knowledge-dialog-card" class="bg-white dark:bg-[#1A1A1A] rounded-2xl border border-slate-200 dark:border-white/10 shadow-xl w-full max-w-md mx-4">
+            <div class="p-6">
+                <div class="flex items-center gap-3 mb-5">
+                    <div class="w-10 h-10 rounded-xl bg-emerald-50 dark:bg-emerald-900/20 flex items-center justify-center">
+                        <i id="knowledge-dialog-icon" class="fas fa-folder text-emerald-500"></i>
+                    </div>
+                    <div>
+                        <h3 id="knowledge-dialog-title" class="font-semibold text-slate-800 dark:text-slate-100"></h3>
+                        <p id="knowledge-dialog-subtitle" class="text-xs text-slate-400 dark:text-slate-500 mt-0.5"></p>
+                    </div>
+                </div>
+                <label id="knowledge-dialog-label" class="block text-sm font-medium text-slate-600 dark:text-slate-300 mb-1.5"></label>
+                <input id="knowledge-dialog-input" type="text"
+                       class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600 bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100 focus:outline-none focus:border-primary-500">
+                <div id="knowledge-dialog-select" class="cfg-dropdown hidden w-full" tabindex="0">
+                    <div class="cfg-dropdown-selected">
+                        <span class="cfg-dropdown-text">--</span>
+                        <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                    </div>
+                    <div class="cfg-dropdown-menu"></div>
+                </div>
+                <textarea id="knowledge-dialog-textarea" rows="8"
+                          class="hidden w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600 bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100 focus:outline-none focus:border-primary-500 font-mono resize-y"></textarea>
+                <div id="knowledge-document-form" class="hidden space-y-3">
+                    <div class="rounded-lg bg-emerald-50 dark:bg-emerald-900/15 border border-emerald-100 dark:border-emerald-800/40 px-3 py-2">
+                        <div id="knowledge-document-category-label" class="text-[11px] text-emerald-600 dark:text-emerald-400 mb-0.5"></div>
+                        <div id="knowledge-document-path-preview" class="text-xs font-mono text-emerald-700 dark:text-emerald-300 break-all"></div>
+                    </div>
+                    <div>
+                        <label id="knowledge-document-filename-label" class="block text-sm font-medium text-slate-600 dark:text-slate-300 mb-1.5"></label>
+                        <input id="knowledge-document-filename" type="text"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600 bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100 focus:outline-none focus:border-primary-500"
+                               placeholder="note.md">
+                    </div>
+                    <div>
+                        <div class="flex items-center justify-between mb-1.5">
+                            <label id="knowledge-document-content-label" class="block text-sm font-medium text-slate-600 dark:text-slate-300"></label>
+                            <button id="knowledge-document-template" type="button" class="text-xs text-primary-500 hover:text-primary-600"></button>
+                        </div>
+                        <textarea id="knowledge-document-content" rows="14"
+                                  class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600 bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100 focus:outline-none focus:border-primary-500 font-mono resize-y"
+                                  placeholder="# Title&#10;&#10;Write your notes here..."></textarea>
+                    </div>
+                </div>
+                <p id="knowledge-dialog-hint" class="mt-2 text-xs text-slate-400 dark:text-slate-500"></p>
+                <p id="knowledge-dialog-error" class="mt-2 text-xs text-red-500 hidden"></p>
+            </div>
+            <div class="flex justify-end gap-3 px-6 py-4 border-t border-slate-100 dark:border-white/5">
+                <button id="knowledge-dialog-cancel" class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10 text-slate-600 dark:text-slate-300 text-sm hover:bg-slate-50 dark:hover:bg-white/5">取消</button>
+                <button id="knowledge-dialog-submit" class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium disabled:opacity-50">确定</button>
+            </div>
+        </div>
+    </div>
+
+    <!-- Confirm Dialog -->
+    <div id="confirm-dialog-overlay" class="fixed inset-0 bg-black/50 z-[200] hidden flex items-center justify-center">
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-2xl border border-slate-200 dark:border-white/10 shadow-xl
+                    w-full max-w-sm mx-4 overflow-hidden">
+            <div class="p-6">
+                <div class="flex items-center gap-3 mb-3">
+                    <div class="w-10 h-10 rounded-xl bg-red-50 dark:bg-red-900/20 flex items-center justify-center flex-shrink-0">
+                        <i class="fas fa-triangle-exclamation text-red-500"></i>
+                    </div>
+                    <h3 id="confirm-dialog-title" class="font-semibold text-slate-800 dark:text-slate-100 text-base"></h3>
+                </div>
+                <p id="confirm-dialog-message" class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed ml-[52px]"></p>
+            </div>
+            <div class="flex items-center justify-end gap-3 px-6 py-4 border-t border-slate-100 dark:border-white/5">
+                <button id="confirm-dialog-cancel"
+                        class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                               text-slate-600 dark:text-slate-300 text-sm font-medium
+                               hover:bg-slate-50 dark:hover:bg-white/5
+                               cursor-pointer transition-colors duration-150"></button>
+                <button id="confirm-dialog-ok"
+                        class="px-4 py-2 rounded-lg bg-red-500 hover:bg-red-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150"></button>
+            </div>
+        </div>
+    </div>
+
+    <!-- Vendor Credentials Modal -->
+    <div id="vendor-modal-overlay" class="fixed inset-0 bg-black/50 z-[100] hidden flex items-center justify-center">
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-2xl border border-slate-200 dark:border-white/10 shadow-xl
+                    w-full max-w-md mx-4">
+            <div class="p-6">
+                <div class="flex items-center gap-3 mb-5">
+                    <div class="w-10 h-10 rounded-xl bg-primary-50 dark:bg-primary-900/20 flex items-center justify-center flex-shrink-0">
+                        <i class="fas fa-key text-primary-500"></i>
+                    </div>
+                    <div class="min-w-0 flex-1">
+                        <h3 id="vendor-modal-title" class="font-semibold text-slate-800 dark:text-slate-100 text-base"></h3>
+                        <p id="vendor-modal-subtitle" class="text-xs text-slate-500 dark:text-slate-400 mt-0.5 font-mono"></p>
+                    </div>
+                </div>
+
+                <!-- Provider selector (only visible when adding via top button) -->
+                <div id="vendor-modal-picker-wrap" class="mb-4 hidden">
+                    <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="models_provider">厂商</label>
+                    <div id="vendor-modal-picker" class="cfg-dropdown" tabindex="0">
+                        <div class="cfg-dropdown-selected">
+                            <span class="cfg-dropdown-text">--</span>
+                            <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                        </div>
+                        <div class="cfg-dropdown-menu"></div>
+                    </div>
+                </div>
+
+                <div class="space-y-4">
+                    <div>
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Key</label>
+                        <input id="vendor-modal-key" type="text" autocomplete="off" data-1p-ignore data-lpignore="true"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                      bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                      focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                               placeholder="sk-...">
+                    </div>
+                    <div id="vendor-modal-base-wrap">
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Base</label>
+                        <input id="vendor-modal-base" type="text"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                      bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                      focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                               placeholder="https://...../v1">
+                        <p id="vendor-modal-base-hint" class="mt-1.5 text-xs text-slate-400 dark:text-slate-500 hidden">
+                            <i class="fas fa-info-circle mr-1"></i><span data-i18n="models_base_default_hint">留空将使用官方默认地址</span>
+                        </p>
+                    </div>
+                </div>
+            </div>
+            <div class="flex items-center justify-between gap-3 px-6 py-4 border-t border-slate-100 dark:border-white/5 rounded-b-2xl">
+                <button id="vendor-modal-clear"
+                        class="px-3 py-2 rounded-lg text-xs
+                               text-red-500 dark:text-red-400 hover:bg-red-50 dark:hover:bg-red-900/20
+                               cursor-pointer transition-colors duration-150 hidden"
+                        data-i18n="models_clear_credential">清除凭据</button>
+                <span id="vendor-modal-status"
+                      class="flex-1 text-xs text-primary-500 opacity-0 transition-opacity duration-300 text-center"></span>
+                <button id="vendor-modal-cancel"
+                        class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                               text-slate-600 dark:text-slate-300 text-sm font-medium
+                               hover:bg-slate-50 dark:hover:bg-white/5
+                               cursor-pointer transition-colors duration-150"
+                        data-i18n="cancel">取消</button>
+                <button id="vendor-modal-save"
+                        class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                        data-i18n="save">保存</button>
+            </div>
+        </div>
+    </div>
+
+    <!-- Custom Provider Modal (multiple OpenAI-compatible providers) -->
+    <div id="custom-provider-modal-overlay" class="fixed inset-0 bg-black/50 z-[100] hidden flex items-center justify-center">
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-2xl border border-slate-200 dark:border-white/10 shadow-xl
+                    w-full max-w-md mx-4">
+            <div class="p-6">
+                <div class="flex items-center gap-3 mb-5">
+                    <div class="w-10 h-10 rounded-xl bg-primary-50 dark:bg-primary-900/20 flex items-center justify-center flex-shrink-0">
+                        <i class="fas fa-sliders text-primary-500"></i>
+                    </div>
+                    <div class="min-w-0 flex-1">
+                        <h3 id="custom-provider-modal-title" class="font-semibold text-slate-800 dark:text-slate-100 text-base"></h3>
+                    </div>
+                </div>
+
+                <div class="space-y-4">
+                    <div>
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="models_custom_name">名称</label>
+                        <input id="custom-provider-name" type="text" autocomplete="off" data-1p-ignore data-lpignore="true"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                      bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                      focus:outline-none focus:border-primary-500 transition-colors">
+                    </div>
+                    <div>
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Base</label>
+                        <input id="custom-provider-base" type="text"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                      bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                      focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                               placeholder="https://...../v1">
+                    </div>
+                    <div>
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Key</label>
+                        <input id="custom-provider-key" type="text" autocomplete="off" data-1p-ignore data-lpignore="true"
+                               class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                      bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                      focus:outline-none focus:border-primary-500 font-mono transition-colors">
+                    </div>
+                </div>
+            </div>
+            <div class="flex items-center justify-between gap-3 px-6 py-4 border-t border-slate-100 dark:border-white/5 rounded-b-2xl">
+                <button id="custom-provider-modal-delete"
+                        class="px-3 py-2 rounded-lg text-sm font-medium text-red-500 hover:bg-red-50 dark:hover:bg-red-900/20
+                               cursor-pointer transition-colors duration-150 hidden"
+                        data-i18n="models_custom_delete">删除</button>
+                <span id="custom-provider-modal-status"
+                      class="flex-1 text-xs text-primary-500 opacity-0 transition-opacity duration-300 text-left"></span>
+                <button id="custom-provider-modal-cancel"
+                        class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                               text-slate-600 dark:text-slate-300 text-sm font-medium
+                               hover:bg-slate-50 dark:hover:bg-white/5
+                               cursor-pointer transition-colors duration-150"
+                        data-i18n="cancel">取消</button>
+                <button id="custom-provider-modal-save"
+                        class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                        data-i18n="save">保存</button>
+            </div>
+        </div>
+    </div>
+
+    <!-- Task Edit Modal -->
+    <div id="task-edit-modal-overlay" class="fixed inset-0 bg-black/50 z-[100] hidden flex items-center justify-center">
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-2xl border border-slate-200 dark:border-white/10 shadow-xl
+                    w-full max-w-2xl mx-4 max-h-[90vh] overflow-y-auto">
+            <div class="p-6">
+                <div class="flex items-center gap-3 mb-5">
+                    <div class="w-10 h-10 rounded-xl bg-primary-50 dark:bg-primary-900/20 flex items-center justify-center flex-shrink-0">
+                        <i class="fas fa-clock text-primary-500"></i>
+                    </div>
+                    <div class="min-w-0 flex-1">
+                        <h3 class="font-semibold text-slate-800 dark:text-slate-100 text-base" data-i18n="task_edit_title">编辑定时任务</h3>
+                        <p id="task-edit-modal-subtitle" class="text-xs text-slate-500 dark:text-slate-400 mt-0.5 font-mono"></p>
+                    </div>
+                </div>
+
+                <div class="space-y-4">
+                    <!-- 任务名称和启用状态 -->
+                    <div class="flex gap-4 items-end">
+                        <div class="flex-1">
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_name">任务名称</span>
+                            </label>
+                            <input id="task-edit-name" type="text"
+                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                          focus:outline-none focus:border-primary-500 transition-colors"
+                                   placeholder="任务名称">
+                        </div>
+                        <div class="flex items-center gap-2 pb-[2px]">
+                            <label class="text-xs font-medium text-slate-600 dark:text-slate-400">
+                                <span data-i18n="task_enabled">启用</span>
+                            </label>
+                            <label class="relative inline-flex items-center cursor-pointer">
+                                <input type="checkbox" id="task-edit-enabled" class="sr-only peer">
+                                <div class="w-11 h-6 bg-slate-200 peer-focus:outline-none rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:rounded-full after:h-5 after:w-5 after:transition-all peer-checked:bg-primary-500 dark:bg-slate-600 dark:peer-checked:bg-primary-500"></div>
+                            </label>
+                        </div>
+                    </div>
+
+                    <!-- 调度类型 + 调度值 -->
+                    <div class="grid grid-cols-2 gap-4">
+                        <div>
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_schedule_type">调度类型</span>
+                            </label>
+                            <select id="task-edit-schedule-type"
+                                    class="w-full px-3 py-2 pr-8 rounded-lg border border-slate-200 dark:border-slate-600
+                                           bg-slate-50 dark:bg-[#1A1A1A] text-sm text-slate-800 dark:text-slate-100
+                                           focus:outline-none focus:border-primary-500 transition-colors
+                                           appearance-none bg-no-repeat bg-right"
+                                    style="background-image: url('data:image/svg+xml;charset=UTF-8,%3csvg xmlns=%27http://www.w3.org/2000/svg%27 viewBox=%270 0 20 20%27 fill=%27none%27%3e%3cpath d=%27M7 7l3 3 3-3%27 stroke=%27%23888%27 stroke-width=%272%27 stroke-linecap=%27round%27 stroke-linejoin=%27round%27/%3e%3c/svg%3e'); background-position: right 0.5rem center; background-size: 1.25rem;">
+                                <option value="cron" data-i18n="task_schedule_cron">Cron 表达式</option>
+                                <option value="interval" data-i18n="task_schedule_interval">固定间隔</option>
+                                <option value="once" data-i18n="task_schedule_once">一次性任务</option>
+                            </select>
+                        </div>
+
+                        <!-- Cron 表达式 -->
+                        <div id="task-edit-cron-wrap">
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_cron_expression">Cron 表达式</span>
+                            </label>
+                            <input id="task-edit-cron-expression" type="text"
+                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                          focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                                   placeholder="0 9 * * *">
+                        </div>
+
+                        <!-- 固定间隔 -->
+                        <div id="task-edit-interval-wrap" class="hidden">
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_interval_seconds">间隔秒数</span>
+                            </label>
+                            <input id="task-edit-interval-seconds" type="number" min="60"
+                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                          focus:outline-none focus:border-primary-500 transition-colors"
+                                   placeholder="3600">
+                        </div>
+
+                        <!-- 一次性任务时间 -->
+                        <div id="task-edit-once-wrap" class="hidden">
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_once_time">执行时间</span>
+                            </label>
+                            <input id="task-edit-once-time" type="datetime-local" step="1"
+                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                          focus:outline-none focus:border-primary-500 transition-colors
+                                          cursor-pointer"
+                                   onclick="this.showPicker && this.showPicker()">
+                        </div>
+                    </div>
+
+                    <!-- Cron/Interval 提示 -->
+                    <p id="task-edit-cron-hint" class="text-xs text-slate-400 dark:text-slate-500">
+                        <span data-i18n="task_cron_hint">格式: 分 时 日 月 周，例如 "0 9 * * *" 表示每天 9:00</span>
+                    </p>
+                    <p id="task-edit-interval-hint" class="text-xs text-slate-400 dark:text-slate-500 hidden">
+                        <span data-i18n="task_interval_hint">最小 60 秒，例如 3600 表示每小时执行一次</span>
+                    </p>
+
+                    <!-- 动作类型 + 通道类型 -->
+                    <div class="grid grid-cols-2 gap-4">
+                        <div>
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_action_type">动作类型</span>
+                            </label>
+                            <select id="task-edit-action-type"
+                                    class="w-full px-3 py-2 pr-8 rounded-lg border border-slate-200 dark:border-slate-600
+                                           bg-slate-50 dark:bg-[#1A1A1A] text-sm text-slate-800 dark:text-slate-100
+                                           focus:outline-none focus:border-primary-500 transition-colors
+                                           appearance-none bg-no-repeat bg-right"
+                                    style="background-image: url('data:image/svg+xml;charset=UTF-8,%3csvg xmlns=%27http://www.w3.org/2000/svg%27 viewBox=%270 0 20 20%27 fill=%27none%27%3e%3cpath d=%27M7 7l3 3 3-3%27 stroke=%27%23888%27 stroke-width=%272%27 stroke-linecap=%27round%27 stroke-linejoin=%27round%27/%3e%3c/svg%3e'); background-position: right 0.5rem center; background-size: 1.25rem;">
+                                <option value="send_message" data-i18n="task_action_send_message">发送消息</option>
+                                <option value="agent_task" data-i18n="task_action_agent_task">AI 任务</option>
+                            </select>
+                        </div>
+                        <div>
+                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                <span data-i18n="task_channel_type">通道类型</span>
+                            </label>
+                            <select id="task-edit-channel-type"
+                                    class="w-full px-3 py-2 pr-8 rounded-lg border border-slate-200 dark:border-slate-600
+                                           bg-slate-50 dark:bg-[#1A1A1A] text-sm text-slate-800 dark:text-slate-100
+                                           focus:outline-none focus:border-primary-500 transition-colors
+                                           appearance-none bg-no-repeat bg-right
+                                           disabled:opacity-100 disabled:text-slate-800 dark:disabled:text-slate-300 disabled:bg-slate-100 dark:disabled:bg-[#252525] disabled:cursor-not-allowed"
+                                    style="background-image: url('data:image/svg+xml;charset=UTF-8,%3csvg xmlns=%27http://www.w3.org/2000/svg%27 viewBox=%270 0 20 20%27 fill=%27none%27%3e%3cpath d=%27M7 7l3 3 3-3%27 stroke=%27%23888%27 stroke-width=%272%27 stroke-linecap=%27round%27 stroke-linejoin=%27round%27/%3e%3c/svg%3e'); background-position: right 0.5rem center; background-size: 1.25rem;">
+                            </select>
+                            <p class="text-xs text-slate-400 dark:text-slate-500 mt-1">
+                                <span data-i18n="task_channel_hint">选择定时消息发送的通道</span>
+                            </p>
+                        </div>
+                    </div>
+
+                    <!-- 隐藏的接收者ID字段（自动填充） -->
+                    <input id="task-edit-receiver" type="hidden" value="">
+
+                    <!-- 消息内容/任务描述 -->
+                    <div>
+                        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                            <span id="task-edit-content-label" data-i18n="task_message_content">消息内容</span>
+                        </label>
+                        <textarea id="task-edit-content" rows="3"
+                                  class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                         bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                         focus:outline-none focus:border-primary-500 transition-colors resize-none"
+                                  placeholder="输入消息内容或任务描述"></textarea>
+                    </div>
+                </div>
+            </div>
+            <div class="flex items-center justify-between gap-3 px-6 py-4 border-t border-slate-100 dark:border-white/5 rounded-b-2xl">
+                <button id="task-edit-modal-delete"
+                        class="px-4 py-2 rounded-lg text-sm font-medium text-red-500 hover:bg-red-50 dark:hover:bg-red-900/20
+                               cursor-pointer transition-colors duration-150 hidden"
+                        data-i18n="task_delete_btn">删除任务</button>
+                <span id="task-edit-modal-status"
+                      class="flex-1 text-xs text-primary-500 opacity-0 transition-opacity duration-300 text-left"></span>
+                <button id="task-edit-modal-cancel"
+                        class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                               text-slate-600 dark:text-slate-300 text-sm font-medium
+                               hover:bg-slate-50 dark:hover:bg-white/5
+                               cursor-pointer transition-colors duration-150"
+                        data-i18n="cancel">取消</button>
+                <button id="task-edit-modal-save"
+                        class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                        data-i18n="save">保存</button>
+            </div>
+        </div>
+    </div>
+
+    <script defer src="assets/js/console.js"></script>
+</body>
+</html>
diff --git a/channel/web/static/axios.min.js b/channel/web/static/axios.min.js
new file mode 100644
index 0000000..79aa153
--- /dev/null
+++ b/channel/web/static/axios.min.js
@@ -0,0 +1,2 @@
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+//# sourceMappingURL=axios.min.js.map
diff --git a/channel/web/static/css/console.css b/channel/web/static/css/console.css
new file mode 100644
index 0000000..3051976
--- /dev/null
+++ b/channel/web/static/css/console.css
@@ -0,0 +1,1685 @@
+/* =====================================================================
+   CowAgent Console Styles
+   ===================================================================== */
+
+/* Animations */
+@keyframes pulseDot {
+    0%, 80%, 100% { transform: scale(0.6); opacity: 0.4; }
+    40% { transform: scale(1); opacity: 1; }
+}
+
+/* Scrollbar */
+* { scrollbar-width: thin; scrollbar-color: #94a3b8 transparent; }
+::-webkit-scrollbar { width: 6px; height: 6px; }
+::-webkit-scrollbar-track { background: transparent; }
+::-webkit-scrollbar-thumb { background: #94a3b8; border-radius: 3px; }
+::-webkit-scrollbar-thumb:hover { background: #64748b; }
+.dark ::-webkit-scrollbar-thumb { background: #475569; }
+.dark ::-webkit-scrollbar-thumb:hover { background: #64748b; }
+
+/* Generic Tooltip (via data-tooltip attribute) */
+[data-tooltip] {
+    position: relative;
+}
+[data-tooltip]::after {
+    content: attr(data-tooltip);
+    position: absolute;
+    left: 50%;
+    bottom: calc(100% + 8px);
+    transform: translateX(-50%);
+    padding: 5px 10px;
+    border-radius: 6px;
+    font-size: 12px;
+    font-weight: 400;
+    line-height: 1.4;
+    white-space: nowrap;
+    background: #1e293b;
+    color: #e2e8f0;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
+    opacity: 0;
+    pointer-events: none;
+    transition: opacity 0.15s ease;
+    z-index: 100;
+}
+[data-tooltip-pos="bottom"]::after {
+    bottom: auto;
+    top: calc(100% + 8px);
+}
+.dark [data-tooltip]::after {
+    background: #334155;
+    color: #f1f5f9;
+}
+[data-tooltip]:hover::after {
+    opacity: 1;
+}
+[data-tooltip=""]:hover::after {
+    display: none;
+}
+
+/* Sidebar */
+.sidebar-item.active {
+    background: rgba(255, 255, 255, 0.08);
+    color: #FFFFFF;
+}
+.sidebar-item.active .item-icon { color: #4ABE6E; }
+
+/* Session Panel */
+.session-panel {
+    width: 220px;
+    flex-shrink: 0;
+    display: flex;
+    flex-direction: column;
+    background: #fafafa;
+    border-right: 1px solid #e5e7eb;
+    height: 100vh;
+    overflow: hidden;
+    transition: width 0.2s ease;
+}
+.dark .session-panel {
+    background: #111111;
+    border-right-color: rgba(255, 255, 255, 0.08);
+}
+.session-panel.hidden { display: none; }
+.session-panel-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 12px 16px;
+    border-bottom: 1px solid #e5e7eb;
+    flex-shrink: 0;
+}
+.dark .session-panel-header { border-bottom-color: rgba(255, 255, 255, 0.08); }
+.session-panel-title {
+    font-size: 14px;
+    font-weight: 600;
+    color: #374151;
+}
+.dark .session-panel-title { color: #d1d5db; }
+.session-panel-close {
+    width: 28px;
+    height: 28px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 6px;
+    border: none;
+    background: none;
+    color: #9ca3af;
+    cursor: pointer;
+    transition: background 0.15s, color 0.15s;
+    font-size: 12px;
+}
+.session-panel-close:hover {
+    background: #f3f4f6;
+    color: #374151;
+}
+.dark .session-panel-close:hover {
+    background: rgba(255, 255, 255, 0.08);
+    color: #e5e5e5;
+}
+.session-panel-new {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    margin: 10px 12px;
+    padding: 8px 14px;
+    border-radius: 8px;
+    border: 1px dashed #d1d5db;
+    background: none;
+    color: #6b7280;
+    font-size: 13px;
+    cursor: pointer;
+    transition: border-color 0.15s, color 0.15s, background 0.15s;
+    flex-shrink: 0;
+}
+.session-panel-new:hover {
+    border-color: #9ca3af;
+    color: #374151;
+    background: #f9fafb;
+}
+.dark .session-panel-new {
+    border-color: rgba(255, 255, 255, 0.12);
+    color: #9ca3af;
+}
+.dark .session-panel-new:hover {
+    border-color: rgba(255, 255, 255, 0.25);
+    color: #e5e5e5;
+    background: rgba(255, 255, 255, 0.04);
+}
+
+/* Session List */
+.session-list {
+    flex: 1;
+    overflow-y: auto;
+    padding: 4px 8px;
+    scrollbar-width: none;
+}
+.session-list:hover { scrollbar-width: thin; }
+.session-list::-webkit-scrollbar { width: 4px; background: transparent; }
+.session-list::-webkit-scrollbar-thumb { background: transparent; border-radius: 2px; }
+.session-list:hover::-webkit-scrollbar-thumb { background: rgba(0,0,0,0.2); }
+.dark .session-list:hover::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.15); }
+.session-group-label {
+    padding: 10px 8px 4px;
+    font-size: 11px;
+    font-weight: 600;
+    text-transform: uppercase;
+    letter-spacing: 0.05em;
+    color: #9ca3af;
+}
+.dark .session-group-label { color: #525252; }
+.session-empty {
+    padding: 20px 12px;
+    text-align: center;
+    font-size: 13px;
+    color: #9ca3af;
+}
+.session-item {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 10px;
+    margin: 1px 0;
+    border-radius: 8px;
+    cursor: pointer;
+    transition: background 0.15s, color 0.15s;
+    color: #6b7280;
+    font-size: 13px;
+    position: relative;
+}
+.dark .session-item { color: #a3a3a3; }
+.session-item:hover {
+    background: #f3f4f6;
+    color: #111827;
+}
+.dark .session-item:hover {
+    background: rgba(255, 255, 255, 0.05);
+    color: #e5e5e5;
+}
+.session-item.active {
+    background: #e5e7eb;
+    color: #111827;
+}
+.dark .session-item.active {
+    background: rgba(255, 255, 255, 0.1);
+    color: #ffffff;
+}
+.session-icon {
+    flex-shrink: 0;
+    font-size: 11px;
+    color: #9ca3af;
+    width: 16px;
+    text-align: center;
+}
+.dark .session-icon { color: #525252; }
+.session-item.active .session-icon { color: #4ABE6E; }
+.session-title {
+    flex: 1;
+    min-width: 0;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+}
+.session-delete {
+    flex-shrink: 0;
+    width: 22px;
+    height: 22px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 5px;
+    font-size: 10px;
+    color: #9ca3af;
+    opacity: 0;
+    transition: opacity 0.15s, color 0.15s, background 0.15s;
+    cursor: pointer;
+    background: none;
+    border: none;
+    padding: 0;
+}
+.session-item:hover .session-delete { opacity: 1; }
+.session-delete:hover {
+    color: #ef4444;
+    background: rgba(239, 68, 68, 0.1);
+}
+.dark .session-delete:hover { background: rgba(239, 68, 68, 0.15); }
+
+/* Rename button: shares the look of the delete button, sits to its left.
+   Negative right margin tightens the gap to the delete button only. */
+.session-rename {
+    flex-shrink: 0;
+    margin-right: -6px;
+    width: 22px;
+    height: 22px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 6px;
+    color: #9ca3af;
+    font-size: 11px;
+    opacity: 0;
+    transition: opacity 0.15s, color 0.15s, background 0.15s;
+    cursor: pointer;
+    background: none;
+    border: none;
+    padding: 0;
+}
+.session-item:hover .session-rename { opacity: 1; }
+.session-rename:hover {
+    color: #4ABE6E;
+    background: rgba(74, 190, 110, 0.12);
+}
+.dark .session-rename:hover { background: rgba(74, 190, 110, 0.18); }
+
+/* Inline title editor */
+.session-title-input {
+    flex: 1;
+    min-width: 0;
+    font-size: 13px;
+    font-family: inherit;
+    color: #111827;
+    background: #ffffff;
+    border: 1px solid #4ABE6E;
+    border-radius: 6px;
+    padding: 2px 6px;
+    outline: none;
+}
+.dark .session-title-input {
+    color: #e5e5e5;
+    background: rgba(255, 255, 255, 0.06);
+    border-color: #4ABE6E;
+}
+
+/* Context Divider */
+.context-divider {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 12px 24px;
+    color: #9ca3af;
+}
+.context-divider::before, .context-divider::after {
+    content: '';
+    flex: 1;
+    height: 1px;
+    background: linear-gradient(to right, transparent, #d1d5db, transparent);
+}
+.dark .context-divider::before, .dark .context-divider::after {
+    background: linear-gradient(to right, transparent, rgba(255,255,255,0.12), transparent);
+}
+.context-divider span {
+    font-size: 12px;
+    white-space: nowrap;
+    color: #9ca3af;
+}
+
+/* Confirm Modal */
+.confirm-overlay {
+    position: fixed;
+    inset: 0;
+    z-index: 9999;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    background: rgba(0, 0, 0, 0.4);
+    opacity: 0;
+    transition: opacity 0.2s ease;
+}
+.confirm-overlay.visible { opacity: 1; }
+.confirm-modal {
+    background: #fff;
+    border-radius: 14px;
+    width: 380px;
+    max-width: 90vw;
+    padding: 28px 24px 20px;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.18);
+    transform: scale(0.92);
+    transition: transform 0.2s ease;
+}
+.confirm-overlay.visible .confirm-modal { transform: scale(1); }
+.dark .confirm-modal {
+    background: #1e1e1e;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.5);
+}
+.confirm-title {
+    font-size: 16px;
+    font-weight: 600;
+    color: #1f2937;
+    margin-bottom: 8px;
+}
+.dark .confirm-title { color: #e5e7eb; }
+.confirm-message {
+    font-size: 14px;
+    color: #6b7280;
+    line-height: 1.5;
+    margin-bottom: 24px;
+}
+.dark .confirm-message { color: #9ca3af; }
+.confirm-actions {
+    display: flex;
+    justify-content: flex-end;
+    gap: 10px;
+}
+.confirm-btn {
+    padding: 8px 20px;
+    border-radius: 8px;
+    font-size: 14px;
+    font-weight: 500;
+    cursor: pointer;
+    border: none;
+    transition: all 0.15s ease;
+}
+.confirm-btn-cancel {
+    background: #f3f4f6;
+    color: #374151;
+}
+.confirm-btn-cancel:hover { background: #e5e7eb; }
+.dark .confirm-btn-cancel {
+    background: rgba(255, 255, 255, 0.08);
+    color: #d1d5db;
+}
+.dark .confirm-btn-cancel:hover { background: rgba(255, 255, 255, 0.14); }
+.confirm-btn-ok {
+    background: #ef4444;
+    color: #fff;
+}
+.confirm-btn-ok:hover { background: #dc2626; }
+
+/* Session panel overlay (mobile only, click to close) */
+.session-panel-overlay {
+    display: none;
+}
+@media (max-width: 768px) {
+    .session-panel-overlay {
+        display: block;
+        position: fixed;
+        inset: 0;
+        z-index: 44;
+        background: rgba(0, 0, 0, 0.3);
+    }
+    .session-panel-overlay.hidden {
+        display: none;
+    }
+}
+
+/* Mobile: session panel as overlay */
+@media (max-width: 768px) {
+    .session-panel {
+        position: fixed;
+        top: 0;
+        left: 0;
+        z-index: 45;
+        width: 220px;
+        box-shadow: 4px 0 24px rgba(0, 0, 0, 0.15);
+    }
+    .dark .session-panel {
+        box-shadow: 4px 0 24px rgba(0, 0, 0, 0.4);
+    }
+}
+
+/* Menu Groups */
+.menu-group-items { max-height: 0; overflow: hidden; transition: max-height 0.25s ease-out; }
+.menu-group.open .menu-group-items { max-height: 2000px; transition: max-height 0.35s ease-in; }
+.menu-group .chevron { transition: transform 0.25s ease; }
+.menu-group.open .chevron { transform: rotate(90deg); }
+
+/* View Switching */
+.view { display: none; height: 100%; }
+.view.active { display: flex; flex-direction: column; }
+
+/* Markdown Content */
+.msg-content p { margin: 0.5em 0; line-height: 1.7; }
+.msg-content p:first-child { margin-top: 0; }
+.msg-content p:last-child { margin-bottom: 0; }
+.msg-content h1, .msg-content h2, .msg-content h3,
+.msg-content h4, .msg-content h5, .msg-content h6 {
+    margin-top: 1.2em; margin-bottom: 0.6em; font-weight: 600; line-height: 1.3;
+}
+.msg-content h1 { font-size: 1.4em; }
+.msg-content h2 { font-size: 1.25em; }
+.msg-content h3 { font-size: 1.1em; }
+.msg-content ul { margin: 0.5em 0; padding-left: 1.8em; list-style: disc; }
+.msg-content ol { margin: 0.5em 0; padding-left: 1.8em; list-style: decimal; }
+.msg-content li { margin: 0.25em 0; }
+.msg-content pre {
+    border-radius: 8px; overflow-x: auto; margin: 0.8em 0;
+    background: #f1f5f9; padding: 1em;
+}
+.dark .msg-content pre { background: #111111; }
+.msg-content code {
+    font-family: 'JetBrains Mono', 'Fira Code', Consolas, monospace;
+    font-size: 0.875em;
+}
+.msg-content :not(pre) > code {
+    background: rgba(74, 190, 110, 0.1); color: #1C6B3B;
+    padding: 2px 6px; border-radius: 4px;
+}
+.dark .msg-content :not(pre) > code {
+    background: rgba(74, 190, 110, 0.15); color: #74E9A4;
+}
+.msg-content pre code { background: transparent; padding: 0; color: inherit; }
+.msg-content blockquote {
+    border-left: 3px solid #4ABE6E; padding: 0.5em 1em;
+    margin: 0.8em 0; background: rgba(74, 190, 110, 0.05); border-radius: 0 6px 6px 0;
+}
+.dark .msg-content blockquote { background: rgba(74, 190, 110, 0.08); }
+.msg-content table { border-collapse: collapse; width: 100%; margin: 0.8em 0; }
+.msg-content th, .msg-content td {
+    border: 1px solid #e2e8f0; padding: 8px 12px; text-align: left;
+}
+.dark .msg-content th, .dark .msg-content td { border-color: rgba(255,255,255,0.1); }
+.msg-content th { background: #f1f5f9; font-weight: 600; }
+.dark .msg-content th { background: #111111; }
+.msg-content img { max-width: 100%; height: auto; border-radius: 8px; margin: 0.5em 0; }
+.msg-content a { color: #35A85B; text-decoration: underline; }
+.msg-content a:hover { color: #228547; }
+
+/* Overrides for user bubble (white text on green bg) */
+.user-bubble.msg-content a { color: #ffffff !important; text-decoration: underline; text-decoration-color: rgba(255,255,255,0.6); }
+.user-bubble.msg-content a:hover { color: #e0f5e8 !important; text-decoration-color: #e0f5e8; }
+.user-bubble.msg-content :not(pre) > code { background: rgba(255,255,255,0.2); color: #ffffff; }
+.msg-content hr { border: none; height: 1px; background: #e2e8f0; margin: 1.2em 0; }
+.dark .msg-content hr { background: rgba(255,255,255,0.1); }
+
+/* SSE Streaming cursor */
+@keyframes blink { 0%, 100% { opacity: 1; } 50% { opacity: 0; } }
+.sse-streaming::after {
+    content: '▋';
+    display: inline-block;
+    margin-left: 2px;
+    color: #4ABE6E;
+    animation: blink 0.9s step-end infinite;
+    font-size: 0.85em;
+    vertical-align: middle;
+}
+
+/* Agent steps (thinking summaries + tool indicators) */
+.agent-steps:empty { display: none; }
+.agent-steps:not(:empty) {
+    margin-bottom: 0.625rem;
+    padding-bottom: 0.5rem;
+    border-bottom: 1px dashed rgba(0, 0, 0, 0.08);
+}
+.dark .agent-steps:not(:empty) { border-bottom-color: rgba(255, 255, 255, 0.08); }
+
+.agent-step {
+    font-size: 0.75rem;
+    line-height: 1.4;
+    color: #94a3b8;
+    margin-bottom: 0.25rem;
+}
+.agent-step:last-child { margin-bottom: 0; }
+
+/* Thinking step - collapsible */
+.agent-thinking-step .thinking-header {
+    display: flex;
+    align-items: center;
+    gap: 0.375rem;
+    cursor: pointer;
+    user-select: none;
+}
+.agent-thinking-step .thinking-header:hover { color: #64748b; }
+.dark .agent-thinking-step .thinking-header:hover { color: #cbd5e1; }
+.agent-thinking-step .thinking-header i:first-child { font-size: 0.625rem; margin-top: 1px; }
+.agent-thinking-step .thinking-chevron {
+    font-size: 0.5rem;
+    margin-left: auto;
+    transition: transform 0.2s ease;
+    opacity: 0.5;
+}
+.agent-thinking-step.expanded .thinking-chevron { transform: rotate(90deg); }
+.agent-thinking-step .thinking-full {
+    display: none;
+    margin-top: 0.375rem;
+    margin-left: 1rem;
+    padding: 0.5rem;
+    background: rgba(0, 0, 0, 0.02);
+    border-radius: 6px;
+    border: 1px solid rgba(0, 0, 0, 0.04);
+    font-size: 0.75rem;
+    line-height: 1.5;
+    color: #94a3b8;
+    max-height: 300px;
+    overflow-y: auto;
+}
+.dark .agent-thinking-step .thinking-full {
+    background: rgba(255, 255, 255, 0.02);
+    border-color: rgba(255, 255, 255, 0.04);
+}
+.agent-thinking-step.expanded .thinking-full { display: block; }
+.agent-thinking-step .thinking-full p { margin: 0.25em 0; }
+.agent-thinking-step .thinking-full p:first-child { margin-top: 0; }
+.agent-thinking-step .thinking-full p:last-child { margin-bottom: 0; }
+.agent-thinking-step .thinking-duration {
+    font-size: 0.625rem;
+    color: #b0b8c4;
+    margin-bottom: 0.375rem;
+}
+/* Streaming reasoning: render as plain pre to avoid expensive markdown
+   re-parsing on every chunk. Wrap long lines so the bubble width is
+   respected and use the same font size/color as the rendered version. */
+.agent-thinking-step .thinking-stream-pre {
+    margin: 0;
+    padding: 0;
+    background: transparent;
+    border: 0;
+    font-family: inherit;
+    font-size: inherit;
+    line-height: 1.5;
+    color: inherit;
+    white-space: pre-wrap;
+    word-break: break-word;
+    overflow-wrap: anywhere;
+}
+
+/* Content step - real text output frozen before tool calls */
+.agent-content-step {
+    font-size: 0.875rem;
+    line-height: 1.6;
+    color: inherit;
+    margin-bottom: 0.5rem;
+    padding-bottom: 0.5rem;
+    border-bottom: 1px dashed rgba(0, 0, 0, 0.06);
+}
+.dark .agent-content-step { border-bottom-color: rgba(255, 255, 255, 0.06); }
+.agent-content-step .agent-content-body p { margin: 0.25em 0; }
+.agent-content-step .agent-content-body p:first-child { margin-top: 0; }
+.agent-content-step .agent-content-body p:last-child { margin-bottom: 0; }
+
+/* Tool step - collapsible */
+.agent-tool-step .tool-header {
+    display: flex;
+    align-items: center;
+    gap: 0.375rem;
+    cursor: pointer;
+    user-select: none;
+    padding: 1px 0;
+    border-radius: 4px;
+}
+.agent-tool-step .tool-header:hover { color: #64748b; }
+.dark .agent-tool-step .tool-header:hover { color: #cbd5e1; }
+.agent-tool-step .tool-icon { font-size: 0.625rem; }
+.agent-tool-step .tool-chevron {
+    font-size: 0.5rem;
+    margin-left: auto;
+    transition: transform 0.2s ease;
+    opacity: 0.5;
+}
+.agent-tool-step.expanded .tool-chevron { transform: rotate(90deg); }
+.agent-tool-step .tool-time {
+    font-size: 0.65rem;
+    opacity: 0.6;
+    margin-left: 0.25rem;
+}
+
+/* Tool detail panel */
+.agent-tool-step .tool-detail {
+    display: none;
+    margin-top: 0.375rem;
+    margin-left: 1rem;
+    padding: 0.5rem;
+    background: rgba(0, 0, 0, 0.02);
+    border-radius: 6px;
+    border: 1px solid rgba(0, 0, 0, 0.04);
+}
+.dark .agent-tool-step .tool-detail {
+    background: rgba(255, 255, 255, 0.02);
+    border-color: rgba(255, 255, 255, 0.04);
+}
+.agent-tool-step.expanded .tool-detail { display: block; }
+.tool-detail-section { margin-bottom: 0.375rem; }
+.tool-detail-section:last-child { margin-bottom: 0; }
+.tool-detail-label {
+    font-size: 0.625rem;
+    font-weight: 600;
+    text-transform: uppercase;
+    letter-spacing: 0.05em;
+    opacity: 0.6;
+    margin-bottom: 0.125rem;
+}
+.tool-detail-content {
+    font-family: 'JetBrains Mono', 'Fira Code', Consolas, monospace;
+    font-size: 0.7rem;
+    line-height: 1.5;
+    white-space: pre-wrap;
+    word-break: break-all;
+    max-height: 200px;
+    overflow-y: auto;
+    margin: 0;
+    padding: 0.25rem 0;
+    background: transparent;
+    color: inherit;
+}
+.tool-error-text { color: #f87171; }
+.tool-live-output:empty { display: none; }
+.tool-streaming .tool-live-output:not(:empty)::after {
+    content: ' ';
+    display: inline-block;
+    width: 0.45em;
+    height: 1em;
+    margin-left: 0.15em;
+    vertical-align: -0.15em;
+    background: currentColor;
+    animation: tool-cursor-blink 1s steps(1) infinite;
+}
+@keyframes tool-cursor-blink { 50% { opacity: 0; } }
+
+/* Log level highlighting */
+.log-line { display: block; }
+.log-line-debug    { color: #94a3b8; }
+.log-line-info     { background-color: rgba(59, 130, 246, 0.08); }
+.log-line-warning  { background-color: rgba(234, 179, 8, 0.15); color: #fde68a; }
+.log-line-error    { background-color: rgba(239, 68, 68, 0.15); color: #fca5a5; }
+.log-line-critical { background-color: rgba(239, 68, 68, 0.35); color: #ff4444; font-weight: bold;  }
+
+/* Tool failed state */
+.agent-tool-step.tool-failed .tool-name { color: #f87171; }
+
+/* Config form controls */
+#view-config input[type="text"],
+#view-config input[type="number"],
+#view-config input[type="password"] {
+    height: 40px;
+    transition: border-color 0.2s ease, box-shadow 0.2s ease;
+}
+#view-config input:focus {
+    border-color: #4ABE6E;
+    box-shadow: 0 0 0 3px rgba(74, 190, 110, 0.12);
+}
+#view-config input[type="text"]:hover,
+#view-config input[type="number"]:hover,
+#view-config input[type="password"]:hover {
+    border-color: #94a3b8;
+}
+.dark #view-config input[type="text"]:hover,
+.dark #view-config input[type="number"]:hover,
+.dark #view-config input[type="password"]:hover {
+    border-color: #64748b;
+}
+
+/* Custom dropdown */
+.cfg-dropdown {
+    position: relative;
+    outline: none;
+}
+.cfg-dropdown-selected {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    height: 40px;
+    padding: 0 0.75rem;
+    border-radius: 0.5rem;
+    border: 1px solid #e2e8f0;
+    background: #f8fafc;
+    font-size: 0.875rem;
+    color: #1e293b;
+    cursor: pointer;
+    transition: border-color 0.2s ease, box-shadow 0.2s ease;
+    user-select: none;
+}
+.dark .cfg-dropdown-selected {
+    border-color: #475569;
+    background: rgba(255, 255, 255, 0.05);
+    color: #f1f5f9;
+}
+.cfg-dropdown-selected:hover { border-color: #94a3b8; }
+.dark .cfg-dropdown-selected:hover { border-color: #64748b; }
+.cfg-dropdown.open .cfg-dropdown-selected,
+.cfg-dropdown:focus .cfg-dropdown-selected {
+    border-color: #4ABE6E;
+    box-shadow: 0 0 0 3px rgba(74, 190, 110, 0.12);
+}
+.cfg-dropdown-arrow {
+    font-size: 0.625rem;
+    color: #94a3b8;
+    transition: transform 0.2s ease;
+    flex-shrink: 0;
+    margin-left: 0.5rem;
+}
+.cfg-dropdown.open .cfg-dropdown-arrow { transform: rotate(180deg); }
+.cfg-dropdown-menu {
+    display: none;
+    position: absolute;
+    top: calc(100% + 4px);
+    left: 0;
+    right: 0;
+    z-index: 50;
+    max-height: 240px;
+    overflow-y: auto;
+    border-radius: 0.5rem;
+    border: 1px solid #e2e8f0;
+    background: #ffffff;
+    box-shadow: 0 10px 25px -5px rgba(0, 0, 0, 0.1), 0 4px 10px -5px rgba(0, 0, 0, 0.04);
+    padding: 4px;
+}
+.dark .cfg-dropdown-menu {
+    border-color: #334155;
+    background: #1e1e1e;
+    box-shadow: 0 10px 25px -5px rgba(0, 0, 0, 0.4);
+}
+.cfg-dropdown.open .cfg-dropdown-menu { display: block; }
+.cfg-dropdown-item {
+    display: flex;
+    align-items: center;
+    padding: 8px 10px;
+    border-radius: 6px;
+    font-size: 0.875rem;
+    color: #334155;
+    cursor: pointer;
+    transition: background 0.15s ease;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.dark .cfg-dropdown-item { color: #cbd5e1; }
+.cfg-dropdown-item:hover { background: #f1f5f9; }
+.dark .cfg-dropdown-item:hover { background: rgba(255, 255, 255, 0.08); }
+.cfg-dropdown-item.active {
+    background: rgba(74, 190, 110, 0.1);
+    color: #228547;
+    font-weight: 500;
+}
+.dark .cfg-dropdown-item.active {
+    background: rgba(74, 190, 110, 0.15);
+    color: #74E9A4;
+}
+/* When an item carries a hint (e.g. brand alias next to a technical model
+   id), label/hint are split into two spans so the hint sits on the right in
+   a dim, smaller weight. Without a hint the row stays a plain text node and
+   uses the default ellipsis behaviour, so no layout regressions for old call
+   sites. */
+.cfg-dropdown-label {
+    flex: 1 1 auto;
+    min-width: 0;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.cfg-dropdown-hint {
+    flex-shrink: 0;
+    margin-left: auto;
+    padding-left: 12px;
+    color: #94a3b8;
+    font-size: 12px;
+    font-weight: 400;
+}
+.dark .cfg-dropdown-hint {
+    color: #64748b;
+}
+.cfg-dropdown-item.active .cfg-dropdown-hint {
+    /* Tint the hint toward the brand colour on the active row so it doesn't
+       fight with the highlighted label tone. */
+    color: rgba(34, 133, 71, 0.65);
+}
+.dark .cfg-dropdown-item.active .cfg-dropdown-hint {
+    color: rgba(116, 233, 164, 0.6);
+}
+/* The active row gets a trailing brand-green checkmark via a Font Awesome
+   pseudo-element so every dropdown (chat / vision / image / asr / tts / etc.)
+   surfaces "this is what's currently selected" without per-call JS plumbing.
+   When a hint is present, the ✓ sits to its right with a small gap; without
+   a hint, margin-left:auto pushes the ✓ flush against the right edge. */
+.cfg-dropdown-item.active::after {
+    content: '\f00c';                  /* FontAwesome check glyph */
+    font-family: 'Font Awesome 6 Free', 'Font Awesome 5 Free', 'FontAwesome';
+    font-weight: 900;
+    margin-left: auto;
+    padding-left: 12px;
+    color: #4abe6e;
+    font-size: 11px;
+    flex-shrink: 0;
+}
+.cfg-dropdown-item.active:has(.cfg-dropdown-hint)::after {
+    /* When hint occupies the auto-margin slot, the ✓ no longer benefits
+       from `margin-left: auto`; replace it with a small fixed gap so the
+       ✓ trails the hint cleanly. */
+    margin-left: 0;
+    padding-left: 10px;
+}
+
+/* API Key masking via CSS (avoids browser password prompts) */
+.cfg-key-masked {
+    -webkit-text-security: disc;
+    text-security: disc;
+}
+
+/* Provider logo image — vendors flagged as `provider-logo-invert-dark`
+   ship a black wordmark that disappears on the dark canvas; we invert their
+   luminance only in dark mode so the brand stays recognizable without
+   touching multi-color marks like Google/MiniMax. */
+.provider-logo-img {
+    object-fit: contain;
+    object-position: center;
+}
+.dark .provider-logo-invert-dark {
+    filter: invert(1) brightness(1.15);
+}
+
+/* Models page — provider dropdown rows.
+   Configured rows look like ordinary picker entries; the .active row's
+   trailing brand-green ✓ already announces "this is what's selected"
+   (handled globally by .cfg-dropdown-item.active::after above).
+   Unconfigured rows are visually subdued and carry a trailing gear icon
+   as a "click to set up" affordance. */
+.cap-provider-label {
+    flex: 1 1 auto;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.cap-provider-gear {
+    margin-left: auto;
+    padding-left: 12px;
+    color: #94a3b8;
+    font-size: 11px;
+    flex-shrink: 0;
+}
+.cap-provider-item.cap-provider-unconfigured {
+    color: #94a3b8;
+}
+.dark .cap-provider-item.cap-provider-unconfigured {
+    color: #64748b;
+}
+.cap-provider-item.cap-provider-unconfigured:hover {
+    color: #475569;
+}
+.dark .cap-provider-item.cap-provider-unconfigured:hover {
+    color: #cbd5e1;
+}
+.cap-provider-item.cap-provider-unconfigured:hover .cap-provider-gear {
+    color: #475569;
+}
+.dark .cap-provider-item.cap-provider-unconfigured:hover .cap-provider-gear {
+    color: #cbd5e1;
+}
+/* If the active row ever lands on an unconfigured vendor (defensive — the
+   click handler normally diverts to the modal), suppress the global ✓ so
+   the gear remains the sole trailing icon and the row keeps reading as
+   "needs setup" rather than "already selected". */
+.cap-provider-item.cap-provider-unconfigured.active::after {
+    content: none;
+}
+
+/* "Add vendor" modal picker — each configured row carries a static
+   brand-green ✓ via decorateVendorModalPicker so users can see what's set
+   up at a glance. The active row's global ✓ is suppressed here to avoid
+   showing two checks side by side on configured + selected rows. */
+.vendor-picker-item.active::after {
+    content: none;
+}
+.vendor-picker-configured-mark {
+    margin-left: auto;
+    padding-left: 12px;
+    color: #4abe6e;
+    font-size: 11px;
+    flex-shrink: 0;
+}
+/* "Custom" row is an add-new action: trailing + instead of ✓. */
+.vendor-picker-add-mark {
+    margin-left: auto;
+    padding-left: 12px;
+    color: #94a3b8;
+    font-size: 11px;
+    flex-shrink: 0;
+}
+
+/* Chat Input */
+#chat-input {
+    resize: none; height: 42px; max-height: 180px;
+    overflow-y: hidden;
+    transition: border-color 0.2s ease;
+}
+
+/* Attachment Preview Bar */
+.attachment-preview {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 8px;
+    padding: 8px 0;
+}
+.attachment-preview.hidden { display: none; }
+
+.attach-menu {
+    position: absolute;
+    left: 72px;
+    bottom: calc(100% + 6px);
+    min-width: 148px;
+    padding: 6px;
+    border-radius: 12px;
+    background: #fff;
+    border: 1px solid #e2e8f0;
+    box-shadow: 0 8px 30px -6px rgba(0, 0, 0, 0.1), 0 2px 8px -2px rgba(0, 0, 0, 0.04);
+    z-index: 55;
+    animation: slashMenuIn 0.15s ease-out;
+}
+.attach-menu.hidden { display: none; }
+.attach-menu-item {
+    width: 100%;
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 10px;
+    border: none;
+    border-radius: 8px;
+    background: transparent;
+    color: #334155;
+    font-size: 13px;
+    cursor: pointer;
+    transition: background 0.12s ease, color 0.12s ease;
+    text-align: left;
+}
+.attach-menu-item:hover {
+    background: #EDFDF3;
+    color: #228547;
+}
+.attach-menu-item i {
+    width: 14px;
+    text-align: center;
+    color: #64748b;
+}
+.attach-menu-item:hover i { color: inherit; }
+
+.att-thumb {
+    position: relative;
+    width: 64px; height: 64px;
+    border-radius: 8px;
+    overflow: hidden;
+    border: 1px solid #e2e8f0;
+    flex-shrink: 0;
+}
+.dark .att-thumb { border-color: rgba(255,255,255,0.1); }
+.att-thumb img {
+    width: 100%; height: 100%;
+    object-fit: cover;
+}
+
+.att-chip {
+    position: relative;
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 6px 28px 6px 10px;
+    border-radius: 8px;
+    background: #f1f5f9;
+    border: 1px solid #e2e8f0;
+    font-size: 12px;
+    color: #475569;
+    max-width: 180px;
+}
+.dark .att-chip { background: rgba(255,255,255,0.05); border-color: rgba(255,255,255,0.1); color: #94a3b8; }
+.att-uploading { opacity: 0.6; pointer-events: none; }
+.att-name {
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+}
+
+.att-remove {
+    position: absolute;
+    top: -4px; right: -4px;
+    width: 18px; height: 18px;
+    border-radius: 50%;
+    background: #ef4444;
+    color: #fff;
+    border: none;
+    font-size: 12px;
+    line-height: 18px;
+    text-align: center;
+    cursor: pointer;
+    padding: 0;
+    opacity: 0;
+    transition: opacity 0.15s;
+}
+.att-thumb:hover .att-remove,
+.att-chip:hover .att-remove { opacity: 1; }
+
+/* Drag-over highlight */
+.drag-over {
+    background: rgba(74, 190, 110, 0.08) !important;
+    border-color: #4ABE6E !important;
+}
+
+/* User message attachments */
+.user-msg-attachments {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 6px;
+    margin-bottom: 6px;
+}
+.user-msg-image {
+    max-width: 200px;
+    max-height: 160px;
+    border-radius: 8px;
+    object-fit: cover;
+    cursor: pointer;
+}
+.user-msg-image:hover { opacity: 0.9; }
+.user-msg-file {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 4px 10px;
+    border-radius: 6px;
+    background: rgba(255,255,255,0.15);
+    font-size: 12px;
+}
+
+/* Placeholder Cards */
+.placeholder-card {
+    transition: transform 0.2s ease, box-shadow 0.2s ease;
+}
+.placeholder-card:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 8px 25px -5px rgba(0, 0, 0, 0.1);
+}
+
+/* Slash Command Menu */
+.slash-menu {
+    position: absolute;
+    bottom: calc(100% + 6px);
+    left: 0;
+    right: 0;
+    max-height: 320px;
+    overflow-y: auto;
+    background: #fff;
+    border: 1px solid #e2e8f0;
+    border-radius: 12px;
+    box-shadow: 0 8px 30px -6px rgba(0, 0, 0, 0.1), 0 2px 8px -2px rgba(0, 0, 0, 0.04);
+    z-index: 50;
+    padding: 4px;
+    animation: slashMenuIn 0.15s ease-out;
+}
+.slash-menu.hidden { display: none; }
+
+@keyframes slashMenuIn {
+    from { opacity: 0; transform: translateY(6px); }
+    to   { opacity: 1; transform: translateY(0); }
+}
+
+.slash-menu-header {
+    padding: 6px 10px 4px;
+    font-size: 11px;
+    font-weight: 600;
+    color: #94a3b8;
+    text-transform: uppercase;
+    letter-spacing: 0.05em;
+}
+
+.slash-menu-item {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 8px 10px;
+    border-radius: 8px;
+    cursor: pointer;
+    transition: background 0.12s ease;
+}
+.slash-menu-item:hover,
+.slash-menu-item.active {
+    background: #EDFDF3;
+}
+.slash-menu-item .cmd {
+    font-size: 13px;
+    font-weight: 500;
+    color: #334155;
+    font-family: ui-monospace, SFMono-Regular, 'SF Mono', Menlo, monospace;
+}
+.slash-menu-item.active .cmd {
+    color: #228547;
+}
+.slash-menu-item .desc {
+    font-size: 12px;
+    color: #94a3b8;
+    margin-left: 12px;
+    white-space: nowrap;
+}
+
+/* Dark mode */
+.dark .slash-menu {
+    background: #1A1A1A;
+    border-color: rgba(255, 255, 255, 0.1);
+    box-shadow: 0 8px 30px -6px rgba(0, 0, 0, 0.35), 0 2px 8px -2px rgba(0, 0, 0, 0.15);
+}
+.dark .slash-menu-header {
+    color: #64748b;
+}
+.dark .slash-menu-item:hover,
+.dark .slash-menu-item.active {
+    background: rgba(74, 190, 110, 0.1);
+}
+.dark .slash-menu-item .cmd {
+    color: #e2e8f0;
+}
+.dark .slash-menu-item.active .cmd {
+    color: #4ABE6E;
+}
+.dark .slash-menu-item .desc {
+    color: #64748b;
+}
+
+.dark .attach-menu {
+    background: #1A1A1A;
+    border-color: rgba(255, 255, 255, 0.1);
+    box-shadow: 0 8px 30px -6px rgba(0, 0, 0, 0.35), 0 2px 8px -2px rgba(0, 0, 0, 0.15);
+}
+.dark .attach-menu-item {
+    color: #e2e8f0;
+}
+.dark .attach-menu-item i {
+    color: #94a3b8;
+}
+.dark .attach-menu-item:hover {
+    background: rgba(74, 190, 110, 0.1);
+    color: #4ABE6E;
+}
+
+/* ============================================================
+   Knowledge View
+   ============================================================ */
+
+/* Tab toggle */
+.knowledge-tab, .memory-tab {
+    color: #64748b;
+}
+.knowledge-tab.active, .memory-tab.active {
+    background: #fff;
+    color: #334155;
+    box-shadow: 0 1px 3px rgba(0,0,0,0.08);
+}
+.dark .knowledge-tab.active, .dark .memory-tab.active {
+    background: rgba(255,255,255,0.1);
+    color: #e2e8f0;
+}
+
+/* File tree */
+.knowledge-tree-group {
+    margin-bottom: 2px;
+}
+.knowledge-tree-group-btn {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    width: 100%;
+    padding: 6px 8px;
+    border-radius: 6px;
+    font-size: 12px;
+    font-weight: 600;
+    color: #64748b;
+    cursor: pointer;
+    border: none;
+    background: none;
+    transition: background 0.15s, color 0.15s;
+    text-transform: capitalize;
+}
+.knowledge-tree-group-btn:hover {
+    background: rgba(0,0,0,0.04);
+    color: #334155;
+}
+.dark .knowledge-tree-group-btn:hover {
+    background: rgba(255,255,255,0.06);
+    color: #e2e8f0;
+}
+.knowledge-tree-group-btn i.chevron {
+    font-size: 8px;
+    transition: transform 0.15s;
+}
+.knowledge-tree-group.open > .knowledge-tree-group-btn .chevron {
+    transform: rotate(90deg);
+}
+.knowledge-tree-group-items {
+    display: none;
+}
+.knowledge-tree-group.open > .knowledge-tree-group-items {
+    display: block;
+}
+
+.knowledge-tree-file {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 5px 8px 5px 24px;
+    border-radius: 6px;
+    font-size: 12px;
+    color: #64748b;
+    cursor: pointer;
+    border: none;
+    background: none;
+    width: 100%;
+    text-align: left;
+    transition: background 0.15s, color 0.15s;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.knowledge-tree-file:hover {
+    background: rgba(0,0,0,0.04);
+    color: #334155;
+}
+.knowledge-tree-file.active {
+    background: #EDFDF3;
+    color: #228547;
+}
+
+.knowledge-actions {
+    display: flex;
+    gap: 2px;
+    margin-left: auto;
+    opacity: 0;
+    transition: opacity 0.15s;
+}
+.knowledge-tree-file:hover .knowledge-actions,
+.knowledge-tree-group-btn:hover .knowledge-actions,
+.knowledge-tree-file:focus-within .knowledge-actions,
+.knowledge-tree-group-btn:focus-within .knowledge-actions {
+    opacity: 1;
+}
+.knowledge-action {
+    padding: 3px 5px;
+    border-radius: 5px;
+    color: #94a3b8;
+    font-size: 9px;
+}
+.knowledge-action:hover {
+    color: #228547;
+    background: rgba(34, 133, 71, 0.08);
+}
+.knowledge-action.danger:hover {
+    color: #ef4444;
+    background: rgba(239, 68, 68, 0.08);
+}
+.dark .knowledge-tree-file:hover {
+    background: rgba(255,255,255,0.06);
+    color: #e2e8f0;
+}
+.dark .knowledge-tree-file.active {
+    background: rgba(74, 190, 110, 0.1);
+    color: #4ABE6E;
+}
+.knowledge-import-drag-over {
+    outline: 2px dashed rgba(74, 190, 110, 0.55);
+    outline-offset: 4px;
+    border-radius: 14px;
+}
+#knowledge-dialog-card.knowledge-document-dialog {
+    max-width: 760px;
+}
+#knowledge-document-content {
+    min-height: 320px;
+    line-height: 1.55;
+}
+
+/* Graph legend */
+.knowledge-graph-legend {
+    position: absolute;
+    top: 12px;
+    right: 12px;
+    display: flex;
+    flex-wrap: wrap;
+    gap: 8px;
+    font-size: 11px;
+    color: #64748b;
+    z-index: 10;
+}
+.knowledge-graph-legend-item {
+    display: flex;
+    align-items: center;
+    gap: 4px;
+}
+.knowledge-graph-legend-dot {
+    width: 8px;
+    height: 8px;
+    border-radius: 50%;
+}
+
+/* Graph tooltip */
+.knowledge-graph-tooltip {
+    position: absolute;
+    padding: 6px 10px;
+    background: #fff;
+    border: 1px solid #e2e8f0;
+    border-radius: 8px;
+    font-size: 12px;
+    color: #334155;
+    box-shadow: 0 4px 12px rgba(0,0,0,0.08);
+    pointer-events: none;
+    opacity: 0;
+    transition: opacity 0.15s;
+    z-index: 20;
+}
+.dark .knowledge-graph-tooltip {
+    background: #1A1A1A;
+    border-color: rgba(255,255,255,0.1);
+    color: #e2e8f0;
+}
+
+/* Config field tooltip */
+.cfg-tip {
+    position: relative;
+    display: inline-flex;
+    align-items: center;
+    color: #94a3b8;
+    cursor: help;
+    font-size: 12px;
+}
+.cfg-tip:hover { color: #64748b; }
+.dark .cfg-tip:hover { color: #cbd5e1; }
+/* Floating tooltip portal — appended to <body> by JS so it isn't clipped
+   by overflow:hidden ancestors. */
+.cfg-tip-floating {
+    position: fixed;
+    padding: 6px 10px;
+    border-radius: 8px;
+    font-size: 12px;
+    font-weight: 400;
+    line-height: 1.4;
+    white-space: nowrap;
+    background: #1e293b;
+    color: #e2e8f0;
+    box-shadow: 0 4px 12px rgba(0,0,0,0.15);
+    opacity: 0;
+    pointer-events: none;
+    transition: opacity 0.15s;
+    z-index: 9999;
+}
+.dark .cfg-tip-floating {
+    background: #334155;
+    color: #f1f5f9;
+}
+.cfg-tip-floating.show {
+    opacity: 1;
+}
+
+/* Example cards: equal height via flex stretch + fixed 2-line description area */
+.example-card {
+    display: flex;
+    flex-direction: column;
+}
+.example-card > p {
+    flex: 1;
+    display: -webkit-box;
+    -webkit-line-clamp: 2;
+    -webkit-box-orient: vertical;
+    overflow: hidden;
+    min-height: 2.5em;  /* ~2 lines at text-sm leading-relaxed */
+}
+
+/* --------------------------------------------------------------------
+ * Voice pill — compact custom audio player used by mic uploads and TTS
+ * replies. Replaces the bulky native <audio controls> with a play/pause
+ * icon + thin progress bar + duration counter so it blends into chat
+ * bubbles without the chrome-grey browser default look.
+ * ------------------------------------------------------------------ */
+.voice-pill {
+    display: inline-flex;
+    align-items: center;
+    gap: 8px;
+    padding: 6px 10px;
+    border-radius: 999px;
+    background: rgba(15, 23, 42, 0.05);
+    color: rgb(71, 85, 105);
+    font-size: 12px;
+    line-height: 1;
+    max-width: 240px;
+    user-select: none;
+    cursor: default;
+}
+.dark .voice-pill {
+    background: rgba(255, 255, 255, 0.08);
+    color: rgb(203, 213, 225);
+}
+.voice-pill[data-loading="1"] {
+    opacity: 0.65;
+}
+.voice-pill-btn {
+    width: 22px;
+    height: 22px;
+    border-radius: 999px;
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    background: var(--color-primary-500, #2563eb);
+    color: #fff;
+    flex-shrink: 0;
+    cursor: pointer;
+    transition: transform 0.1s ease;
+}
+.voice-pill-btn:hover { transform: scale(1.05); }
+.voice-pill-btn i { font-size: 9px; margin-left: 1px; }
+.voice-pill-btn[data-state="play"] i { margin-left: 2px; }
+.voice-pill-btn[data-state="pause"] i { margin-left: 0; }
+.voice-pill-track {
+    flex: 1;
+    height: 3px;
+    border-radius: 999px;
+    background: rgba(100, 116, 139, 0.25);
+    overflow: hidden;
+    min-width: 70px;
+}
+.dark .voice-pill-track {
+    background: rgba(148, 163, 184, 0.25);
+}
+.voice-pill-fill {
+    height: 100%;
+    width: 0%;
+    background: var(--color-primary-500, #2563eb);
+    border-radius: inherit;
+    transition: width 0.1s linear;
+}
+.voice-pill-time {
+    font-variant-numeric: tabular-nums;
+    font-size: 11px;
+    color: inherit;
+    opacity: 0.75;
+    flex-shrink: 0;
+    min-width: 28px;
+    text-align: right;
+}
+.voice-pill audio { display: none; }
+
+/* Send button toggles into a Stop button while an SSE stream is in flight.
+   Match the look of the disabled send button (light grey block + white
+   glyph) so it reads as the same visual element, just paused/idle from
+   sending perspective and clickable to stop. */
+#send-btn.send-btn-cancel {
+    background-color: rgb(203 213 225) !important; /* slate-300, == disabled send-btn */
+    color: white !important;
+}
+#send-btn.send-btn-cancel:hover {
+    background-color: rgb(148 163 184) !important; /* slate-400 */
+}
+#send-btn.send-btn-cancel:disabled {
+    background-color: rgb(226 232 240) !important; /* slate-200, while stop is in flight */
+    color: white !important;
+    cursor: progress;
+}
+.dark #send-btn.send-btn-cancel {
+    background-color: rgb(71 85 105) !important; /* slate-600, == dark disabled send-btn */
+    color: white !important;
+}
+.dark #send-btn.send-btn-cancel:hover {
+    background-color: rgb(100 116 139) !important; /* slate-500 */
+}
+.dark #send-btn.send-btn-cancel:disabled {
+    background-color: rgb(51 65 85) !important; /* slate-700 */
+    color: rgb(203 213 225) !important;
+}
+
+.agent-cancelled-tag {
+    font-style: italic;
+}
+
+/* =====================================================================
+   Code Block Enhancements
+   ===================================================================== */
+.code-block-wrapper {
+    position: relative;
+    margin: 1em 0;
+    border-radius: 8px;
+    overflow: hidden;
+    background: #f8f9fa;
+    border: 1px solid #e2e8f0;
+}
+
+.dark .code-block-wrapper {
+    background: #1e293b;
+    border-color: #334155;
+}
+
+.code-block-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    padding: 0.5em 1em;
+    background: #e2e8f0;
+    border-bottom: 1px solid #cbd5e1;
+    font-size: 0.85em;
+}
+
+.dark .code-block-header {
+    background: #0f172a;
+    border-bottom-color: #334155;
+}
+
+.code-block-lang {
+    color: #64748b;
+    font-weight: 500;
+    text-transform: lowercase;
+}
+
+.dark .code-block-lang {
+    color: #94a3b8;
+}
+
+.code-copy-btn {
+    background: transparent;
+    border: none;
+    color: #64748b;
+    cursor: pointer;
+    padding: 0.25em 0.5em;
+    border-radius: 4px;
+    transition: all 0.2s;
+    font-size: 0.9em;
+}
+
+.code-copy-btn:hover {
+    background: rgba(100, 116, 139, 0.1);
+    color: #475569;
+}
+
+.dark .code-copy-btn {
+    color: #94a3b8;
+}
+
+.dark .code-copy-btn:hover {
+    background: rgba(148, 163, 184, 0.1);
+    color: #cbd5e1;
+}
+
+.code-block-wrapper pre {
+    margin: 0;
+    border-radius: 0;
+    border: none;
+}
+
+/* =====================================================================
+   Drag and Drop Overlay
+   ===================================================================== */
+/* Anchor the absolutely-positioned overlay to the chat view. */
+#view-chat {
+    position: relative;
+}
+
+.drag-overlay {
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    bottom: 0;
+    background: rgba(59, 130, 246, 0.1);
+    backdrop-filter: blur(2px);
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    z-index: 9999;
+    pointer-events: none;
+    opacity: 0;
+    transition: opacity 0.2s;
+}
+
+.drag-overlay.active {
+    opacity: 1;
+}
+
+.drag-overlay.hidden {
+    display: none;
+}
+
+.drag-overlay-content {
+    background: white;
+    border: 3px dashed #3b82f6;
+    border-radius: 16px;
+    padding: 3em 4em;
+    text-align: center;
+    box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.1);
+    animation: bounce 1s ease infinite;
+}
+
+.dark .drag-overlay-content {
+    background: #1e293b;
+    border-color: #60a5fa;
+}
+
+.drag-overlay-content i {
+    font-size: 4em;
+    color: #3b82f6;
+    margin-bottom: 0.5em;
+}
+
+.dark .drag-overlay-content i {
+    color: #60a5fa;
+}
+
+.drag-overlay-content p {
+    font-size: 1.5em;
+    font-weight: 600;
+    color: #1e293b;
+    margin: 0;
+}
+
+.dark .drag-overlay-content p {
+    color: #f1f5f9;
+}
+
+@keyframes bounce {
+    0%, 100% { transform: translateY(0); }
+    50% { transform: translateY(-10px); }
+}
+
+/* =====================================================================
+   Message Action Buttons
+   ===================================================================== */
+.edit-msg-btn,
+.delete-msg-btn,
+.regenerate-msg-btn {
+    opacity: 0;
+    transition: opacity 0.2s, color 0.2s;
+}
+
+.user-message-group:hover .edit-msg-btn,
+.user-message-group:hover .delete-msg-btn,
+.bot-message-group:hover .regenerate-msg-btn {
+    opacity: 1;
+}
+
+.edit-msg-btn:hover,
+.regenerate-msg-btn:hover {
+    color: #3b82f6 !important;
+}
+
+.delete-msg-btn:hover {
+    color: #ef4444 !important;
+}
+
+.edit-msg-btn:disabled,
+.delete-msg-btn:disabled {
+    cursor: not-allowed !important;
+    opacity: 0.35 !important;
+}
diff --git a/channel/web/static/favicon.ico b/channel/web/static/favicon.ico
new file mode 100644
index 0000000..d21d812
Binary files /dev/null and b/channel/web/static/favicon.ico differ
diff --git a/channel/web/static/github.png b/channel/web/static/github.png
new file mode 100644
index 0000000..9122abb
Binary files /dev/null and b/channel/web/static/github.png differ
diff --git a/channel/web/static/js/console.js b/channel/web/static/js/console.js
new file mode 100644
index 0000000..0cf7476
--- /dev/null
+++ b/channel/web/static/js/console.js
@@ -0,0 +1,9596 @@
+/* =====================================================================
+   CowAgent Console - Main Application Script
+   ===================================================================== */
+
+// =====================================================================
+// Version — fetched from backend (single source: /VERSION file)
+// =====================================================================
+let APP_VERSION = '';
+
+// =====================================================================
+// i18n
+// =====================================================================
+const I18N = {
+    zh: {
+        console: '控制台',
+        nav_chat: '对话', nav_manage: '管理', nav_monitor: '监控',
+        menu_chat: '对话', menu_config: '配置', menu_models: '模型', menu_skills: '技能',
+        menu_memory: '记忆', menu_knowledge: '知识', menu_channels: '通道', menu_tasks: '定时',
+        menu_logs: '日志',
+        models_title: '模型管理',
+        models_desc: '统一管理对话、图像、语音、向量、搜索能力',
+        models_section_vendors: '厂商凭据',
+        models_section_vendors_desc: '一处配置，多个模型能力共享',
+        models_section_capabilities: '模型能力',
+        models_add_vendor: '添加厂商',
+        models_provider: '厂商',
+        models_model: '模型',
+        models_voice: '音色',
+        models_configured: '已配置',
+        models_not_configured: '未配置',
+        models_pick_to_configure: '选择以配置',
+        models_clear_credential: '清除凭据',
+        models_base_default_hint: '留空将使用官方默认地址',
+        models_base_default: '默认',
+        models_custom_vendor_label: '自定义',
+        models_custom_name: '名称',
+        models_custom_delete: '删除',
+        models_custom_delete_confirm_title: '删除自定义厂商',
+        models_custom_delete_confirm_msg: '确定删除该自定义厂商吗？此操作无法撤销。',
+        models_custom_name_required: '请填写名称',
+        models_custom_base_required: '请填写 API Base',
+        models_custom_edit_title: '编辑自定义厂商',
+        models_custom_add_title: '添加自定义厂商',
+        models_capability_chat: '主模型',
+        models_capability_chat_desc: '用于基础对话和 Agent 推理',
+        models_capability_vision: '图像理解',
+        models_capability_vision_desc: '识别图片内容，用于图像识别工具',
+        models_capability_image: '图像生成',
+        models_capability_image_desc: '生成图片，用于图像生成技能',
+        models_auto_using: '当前优先使用',
+        models_capability_asr: '语音识别',
+        models_capability_asr_desc: '语音转文字',
+        models_capability_tts: '语音合成',
+        models_capability_tts_desc: '文字转语音',
+        models_capability_embedding: '向量',
+        models_capability_embedding_desc: '用于记忆与知识的向量化检索',
+        models_capability_search: '联网搜索',
+        models_capability_search_desc: '实时网页检索能力，用于搜索工具',
+        models_strategy_auto: '自动',
+        models_search_strategy_label: '策略',
+        models_search_strategy_fixed: '指定',
+        models_search_strategy_auto_hint: '从已配置厂商中自动选择',
+        models_search_strategy_fixed_hint: '指定使用搜索厂商',
+        models_pending_config: '待配置',
+        models_search_available_label: '可用搜索厂商：',
+        models_search_none_configured: '暂未启用任何搜索厂商，点击添加',
+        models_search_add_provider: '添加厂商',
+        models_search_add_desc: '选择一个搜索厂商进行配置',
+        models_search_bocha_title: '配置博查 API Key',
+        models_search_bocha_desc: '前往博查开放平台创建 API Key',
+        models_search_edit_hint: '点击修改配置',
+        models_unavailable: '不可用',
+        models_set_via_env: '通过环境变量启用',
+        models_dim_label: '维度',
+        models_save_success: '已保存',
+        models_save_failed: '保存失败',
+        models_cleared: '已清除',
+        models_clear_failed: '清除失败',
+        models_embedding_change_title: '更改向量模型',
+        models_embedding_change_msg: '切换向量模型后，已有索引将失效，需要重建。是否继续？',
+        models_embedding_saved_title: '向量模型已更新',
+        models_embedding_saved_msg: '请在聊天框输入 /memory rebuild-index 重建索引。',
+        models_embedding_saved_ok: '去执行',
+        models_pick_provider: '待选择',
+        models_clear_confirm_title: '清除厂商凭据',
+        models_clear_confirm_msg: '确认清除该厂商的 API Key 与 Base URL 吗？相关能力将不再可用。',
+        cancel: '取消',
+        save: '保存',
+        ok: '确定',
+        knowledge_title: '知识库', knowledge_desc: '浏览和探索你的知识库',
+        knowledge_tab_docs: '文档', knowledge_tab_graph: '图谱',
+        knowledge_loading: '加载知识库中...', knowledge_loading_desc: '知识页面将显示在这里',
+        knowledge_select_hint: '选择一个文档查看', knowledge_empty_hint: '暂无知识页面',
+        knowledge_empty_guide: '在对话中发送文档、链接或主题给 Agent，它会自动整理到你的知识库中。',
+        knowledge_go_chat: '开始对话',
+        knowledge_new: '新建',
+        knowledge_new_category: '新建分类',
+        knowledge_new_document: '新建文档',
+        knowledge_import_documents: '导入文档',
+        welcome_subtitle: '我可以帮你解答问题、管理计算机、创造和执行技能，并通过<br>长期记忆和知识库不断成长',
+        example_sys_title: '系统管理', example_sys_text: '查看工作空间里有哪些文件',
+        example_task_title: '定时任务', example_task_text: '1分钟后提醒我检查服务器',
+        example_code_title: '编程助手', example_code_text: '搜索AI资讯并生成可视化网页报告',
+        example_knowledge_title: '知识库', example_knowledge_text: '查看知识库当前文档情况',
+        example_skill_title: '技能系统', example_skill_text: '查看所有支持的工具和技能',
+        example_web_title: '指令中心', example_web_text: '查看全部命令',
+        slash_help: '显示命令帮助',
+        slash_status: '查看运行状态',
+        slash_context: '查看对话上下文',
+        slash_context_clear: '清除对话上下文',
+        slash_skill_list: '查看已安装技能',
+        slash_skill_list_remote: '浏览技能广场',
+        slash_skill_search: '搜索技能',
+        slash_skill_install: '安装技能 (名称或 GitHub URL)',
+        slash_skill_uninstall: '卸载技能',
+        slash_skill_info: '查看技能详情',
+        slash_skill_enable: '启用技能',
+        slash_skill_disable: '禁用技能',
+        slash_memory_dream: '手动触发记忆蒸馏 (可指定天数, 默认3)',
+        slash_knowledge: '查看知识库统计',
+        slash_knowledge_list: '查看知识库文件树',
+        slash_knowledge_on: '开启知识库',
+        slash_knowledge_off: '关闭知识库',
+        slash_config: '查看当前配置',
+        slash_cancel: '中止当前正在运行的 Agent 任务',
+        slash_logs: '查看最近日志',
+        slash_version: '查看版本',
+        input_placeholder: '输入消息，或输入 / 使用指令',
+        config_title: '配置管理', config_desc: '管理模型和 Agent 配置',
+        config_model: '模型配置', config_agent: 'Agent 配置',
+        config_language: '语言', config_language_hint: '界面展示、命令文案、系统提示词等使用的语言（与右上角切换同步）',
+        config_model_advanced: '高级配置',
+        config_channel: '通道配置',
+        config_agent_enabled: 'Agent 模式',
+        config_max_tokens: '最大上下文 Token', config_max_tokens_hint: '对话中 Agent 能输入的最大 Token 长度，超过后会智能压缩处理',
+        config_max_turns: '最大记忆轮次', config_max_turns_hint: '一问一答为一轮，超过后会智能压缩处理',
+        config_max_steps: '最大执行步数', config_max_steps_hint: '单次对话中 Agent 最多调用工具的次数',
+        config_enable_thinking: '深度思考', config_enable_thinking_hint: '是否启用深度思考模式',
+        config_self_evolution: '自主进化', config_self_evolution_hint: '会话空闲后自动复盘，沉淀记忆、优化技能、处理未完成事项',
+        evolution_badge: '自主学习',
+        config_channel_type: '通道类型',
+        config_provider: '模型厂商', config_model_name: '模型',
+        config_custom_model_hint: '输入自定义模型名称',
+        config_save: '保存', config_saved: '已保存',
+        config_save_error: '保存失败',
+        config_custom_option: '自定义',
+        config_custom_tip: '接口需遵循 OpenAI API 协议',
+        config_security: '安全设置', config_password: '访问密码',
+        config_password_hint: '留空则不启用密码保护',
+        config_password_changed: '密码已更新',
+        config_password_cleared: '密码已清除',
+        config_password_security_warning: '⚠️ 警告：目前密码为空且对外连接埠开放，建议重启服务，或检查是否调整监听位址绑定。',
+        skills_title: '技能管理', skills_desc: '查看、启用或禁用 Agent 工具和技能', skills_hub_btn: '探索技能广场',
+        skills_loading: '加载技能中...', skills_loading_desc: '技能加载后将显示在此处',
+        tools_section_title: '内置工具', tools_loading: '加载工具中...',
+        skills_section_title: '技能', skill_enable: '启用', skill_disable: '禁用',
+        skill_toggle_error: '操作失败，请稍后再试',
+        memory_title: '记忆管理', memory_desc: '查看 Agent 记忆文件和内容',
+        memory_tab_files: '记忆文件', memory_tab_dreams: '自主进化',
+        memory_loading: '加载记忆文件中...', memory_loading_desc: '记忆文件将显示在此处',
+        memory_back: '返回列表',
+        memory_col_name: '文件名', memory_col_type: '类型', memory_col_size: '大小', memory_col_updated: '更新时间',
+        channels_title: '通道管理', channels_desc: '管理已接入的消息通道',
+        channels_add: '接入通道', channels_disconnect: '断开',
+        channels_save: '保存配置', channels_saved: '已保存', channels_save_error: '保存失败',
+        channels_restarted: '已保存并重启',
+        channels_connect_btn: '接入', channels_cancel: '取消',
+        channels_select_placeholder: '选择要接入的通道...',
+        channels_empty: '暂未接入任何通道', channels_empty_desc: '点击右上角「接入通道」按钮开始配置',
+        channels_disconnect_confirm: '确认断开该通道？配置将保留但通道会停止运行。',
+        channels_connected: '已接入', channels_connecting: '接入中...',
+        weixin_scan_title: '微信扫码登录', weixin_scan_desc: '请使用微信扫描下方二维码',
+        weixin_scan_loading: '正在获取二维码...', weixin_scan_waiting: '等待扫码...',
+        weixin_scan_scanned: '已扫码，请在手机上确认', weixin_scan_expired: '二维码已过期，正在刷新...',
+        weixin_scan_success: '登录成功，正在启动通道...', weixin_scan_fail: '获取二维码失败',
+        weixin_qr_tip: '二维码约2分钟后过期',
+        wecom_scan_btn: '扫码创建企微机器人', wecom_scan_desc: '使用企业微信扫码，一键创建智能机器人',
+        wecom_scan_success: '创建成功，正在启动通道...',
+        wecom_scan_fail: '创建失败',
+        wecom_mode_scan: '扫码接入', wecom_mode_manual: '手动填写',
+        feishu_scan_btn: '一键创建飞书应用',
+        feishu_scan_desc: '使用飞书 App 扫码，自动创建应用并预置全部权限与事件订阅',
+        feishu_scan_replace_desc: '使用飞书 App 扫码创建新机器人，将覆盖当前的 App ID / Secret',
+        feishu_scan_loading: '正在向飞书申请二维码...',
+        feishu_scan_waiting: '等待扫码...',
+        feishu_scan_tip: '二维码 10 分钟内有效，仅供一次扫描',
+        feishu_scan_open_link: '或点击此处在浏览器中打开',
+        feishu_scan_success: '应用创建成功，正在启动通道...',
+        feishu_scan_expired: '二维码已过期，请重试',
+        feishu_scan_denied: '已取消授权',
+        feishu_scan_fail: '创建失败',
+        feishu_scan_retry: '重试',
+        feishu_mode_scan: '扫码创建', feishu_mode_manual: '手动填写',
+        tasks_title: '定时任务', tasks_desc: '查看和管理定时任务',
+        tasks_coming: '即将推出', tasks_coming_desc: '定时任务管理功能即将在此提供',
+        task_add_btn: '新增任务',
+        task_edit_title: '编辑定时任务',
+        task_add_title: '新增定时任务',
+        task_name: '任务名称',
+        task_enabled: '启用任务',
+        task_schedule_type: '调度类型',
+        task_schedule_cron: 'Cron 表达式',
+        task_schedule_interval: '固定间隔',
+        task_schedule_once: '一次性任务',
+        task_cron_expression: 'Cron 表达式',
+        task_cron_hint: '格式: 分 时 日 月 周，例如 "0 9 * * *" 表示每天 9:00',
+        task_interval_seconds: '间隔秒数',
+        task_interval_hint: '最小 60 秒，例如 3600 表示每小时执行一次',
+        task_once_time: '执行时间',
+        task_action_type: '动作类型',
+        task_action_send_message: '发送消息',
+        task_action_agent_task: 'AI 任务',
+        task_channel_type: '通道类型',
+        task_channel_hint: '选择定时消息发送的通道',
+        task_message_content: '消息内容',
+        task_task_description: '任务描述',
+        task_delete_btn: '删除任务',
+        task_delete_confirm_title: '删除定时任务',
+        task_delete_confirm_msg: '确定删除该定时任务吗？此操作无法撤销。',
+        logs_title: '日志', logs_desc: '实时日志输出 (run.log)',
+        logs_live: '实时', logs_coming_msg: '日志流即将在此提供。将连接 run.log 实现类似 tail -f 的实时输出。',
+        new_chat: '新对话',
+        session_history: '历史会话',
+        today: '今天', yesterday: '昨天', earlier: '更早',
+        delete_session_confirm: '确认删除该会话？所有消息将被清除。',
+        delete_session_title: '删除会话',
+        rename_session: '重命名',
+        delete_message_confirm: '确认删除这条消息？',
+        delete_message_title: '删除消息',
+        edit_disabled_reply_active: '正在生成回复，暂时无法编辑。',
+        delete_disabled_reply_active: '正在生成回复，暂时无法删除。',
+        untitled_session: '新对话',
+        context_cleared: '— 以上内容已从上下文中移除 —',
+        tip_new_chat: '新建对话',
+        tip_clear_context: '清除上下文',
+        tip_attach: '添加附件',
+        attach_menu_file: '上传文件',
+        mic_idle_title: '点击录音 / 再按一次结束',
+        mic_recording_title: '录音中，再次点击结束',
+        mic_busy_title: '识别中…',
+        mic_permission_denied: '无法访问麦克风，请检查浏览器权限',
+        mic_too_short: '录音太短，请重试',
+        mic_error: '语音识别失败',
+        speak_msg: '朗读这段回复',
+        voice_reply_mode_label: '语音回复策略',
+        voice_reply_off: '关闭',
+        voice_reply_if_voice: '仅语音问/语音答',
+        voice_reply_always: '总是语音回复',
+        attach_menu_folder: '上传文件夹',
+        confirm_yes: '确认',
+        confirm_cancel: '取消',
+        error_send: '发送失败，请稍后再试。', error_timeout: '请求超时，请再试一次。',
+        thinking_in_progress: '思考中...', thinking_done: '已深度思考', thinking_duration: '耗时',
+        edit_message: '编辑消息',
+        regenerate_response: '重新生成',
+        edit_save: '保存并发送',
+        edit_cancel: '取消',
+        logout: '退出',
+    },
+    'zh-Hant': {
+
+        console: '控制台',
+        nav_chat: '對話', nav_manage: '管理', nav_monitor: '監控',
+        menu_chat: '對話', menu_config: '設定', menu_models: '模型', menu_skills: '技能',
+        menu_memory: '記憶', menu_knowledge: '知識', menu_channels: '管道', menu_tasks: '定時',
+        menu_logs: '日誌',
+        models_title: '模型管理',
+        models_desc: '統一管理對話、影像、語音、向量、搜尋能力',
+        models_section_vendors: '廠商憑據',
+        models_section_vendors_desc: '一處設定，多個模型能力共享',
+        models_section_capabilities: '模型能力',
+        models_add_vendor: '新增廠商',
+        models_provider: '廠商',
+        models_model: '模型',
+        models_voice: '音色',
+        models_configured: '已設定',
+        models_not_configured: '未設定',
+        models_pick_to_configure: '選擇以設定',
+        models_clear_credential: '清除憑據',
+        models_base_default_hint: '留空將使用官方預設地址',
+        models_base_default: '預設',
+        models_custom_vendor_label: '自定義',
+        models_custom_name: '名稱',
+        models_custom_delete: '刪除',
+        models_custom_delete_confirm_title: '刪除自定義廠商',
+        models_custom_delete_confirm_msg: '確定刪除該自定義廠商嗎？此操作無法撤銷。',
+        models_custom_name_required: '請填寫名稱',
+        models_custom_base_required: '請填寫 API Base',
+        models_custom_edit_title: '編輯自定義廠商',
+        models_custom_add_title: '新增自定義廠商',
+        models_capability_chat: '主模型',
+        models_capability_chat_desc: '用於基礎對話和 Agent 推理',
+        models_capability_vision: '影像理解',
+        models_capability_vision_desc: '識別圖片內容，用於影像識別工具',
+        models_capability_image: '影像生成',
+        models_capability_image_desc: '生成圖片，用於影像生成技能',
+        models_auto_using: '當前優先使用',
+        models_capability_asr: '語音識別',
+        models_capability_asr_desc: '語音轉文字',
+        models_capability_tts: '語音合成',
+        models_capability_tts_desc: '文字轉語音',
+        models_capability_embedding: '向量',
+        models_capability_embedding_desc: '用於記憶與知識的向量化檢索',
+        models_capability_search: '聯網搜尋',
+        models_capability_search_desc: '實時網頁檢索能力，用於搜尋工具',
+        models_strategy_auto: '自動',
+        models_search_strategy_label: '策略',
+        models_search_strategy_fixed: '指定',
+        models_search_strategy_auto_hint: '從已設定廠商中自動選擇',
+        models_search_strategy_fixed_hint: '指定使用搜尋廠商',
+        models_pending_config: '待設定',
+        models_search_available_label: '可用搜尋廠商：',
+        models_search_none_configured: '暫未啟用任何搜尋廠商，點選新增',
+        models_search_add_provider: '新增廠商',
+        models_search_add_desc: '選擇一個搜尋廠商進行設定',
+        models_search_bocha_title: '設定博查 API Key',
+        models_search_bocha_desc: '前往博查開放平臺建立 API Key',
+        models_search_edit_hint: '點選修改設定',
+        models_unavailable: '不可用',
+        models_set_via_env: '透過環境變數啟用',
+        models_dim_label: '維度',
+        models_save_success: '已儲存',
+        models_save_failed: '儲存失敗',
+        models_cleared: '已清除',
+        models_clear_failed: '清除失敗',
+        models_embedding_change_title: '更改向量模型',
+        models_embedding_change_msg: '切換向量模型後，已有索引將失效，需要重建。是否繼續？',
+        models_embedding_saved_title: '向量模型已更新',
+        models_embedding_saved_msg: '請在聊天框輸入 /memory rebuild-index 重建索引。',
+        models_embedding_saved_ok: '去執行',
+        models_pick_provider: '待選擇',
+        models_clear_confirm_title: '清除廠商憑據',
+        models_clear_confirm_msg: '確認清除該廠商的 API Key 與 Base URL 嗎？相關能力將不再可用。',
+        cancel: '取消',
+        save: '儲存',
+        ok: '確定',
+        knowledge_title: '知識庫', knowledge_desc: '瀏覽和探索你的知識庫',
+        knowledge_tab_docs: '檔案', knowledge_tab_graph: '圖譜',
+        knowledge_loading: '載入知識庫中...', knowledge_loading_desc: '知識頁面將顯示在這裡',
+        knowledge_select_hint: '選擇一個檔案檢視', knowledge_empty_hint: '暫無知識頁面',
+        knowledge_empty_guide: '在對話中傳送檔案、連結或主題給 Agent，它會自動整理到你的知識庫中。',
+        knowledge_go_chat: '開始對話',
+        knowledge_new: '新建',
+        knowledge_new_category: '新建分類',
+        knowledge_new_document: '新建檔案',
+        knowledge_import_documents: '匯入檔案',
+        welcome_subtitle: '我可以幫你解答問題、管理電腦、創造和執行技能，並透過<br>長期記憶和知識庫不斷成長',
+        example_sys_title: '系統管理', example_sys_text: '檢視工作空間裡有哪些檔案',
+        example_task_title: '定時任務', example_task_text: '1分鐘後提醒我檢查伺服器',
+        example_code_title: '程式設計助手', example_code_text: '搜尋AI資訊並生成視覺化網頁報告',
+        example_knowledge_title: '知識庫', example_knowledge_text: '檢視知識庫當前檔案情況',
+        example_skill_title: '技能系統', example_skill_text: '檢視所有支援的工具和技能',
+        example_web_title: '指令中心', example_web_text: '檢視全部命令',
+        slash_help: '顯示命令幫助',
+        slash_status: '檢視執行狀態',
+        slash_context: '檢視對話上下文',
+        slash_context_clear: '清除對話上下文',
+        slash_skill_list: '檢視已安裝技能',
+        slash_skill_list_remote: '瀏覽技能廣場',
+        slash_skill_search: '搜尋技能',
+        slash_skill_install: '安裝技能 (名稱或 GitHub URL)',
+        slash_skill_uninstall: '解除安裝技能',
+        slash_skill_info: '檢視技能詳情',
+        slash_skill_enable: '啟用技能',
+        slash_skill_disable: '禁用技能',
+        slash_memory_dream: '手動觸發記憶蒸餾 (可指定天數, 預設3)',
+        slash_knowledge: '檢視知識庫統計',
+        slash_knowledge_list: '檢視知識庫檔案樹',
+        slash_knowledge_on: '開啟知識庫',
+        slash_knowledge_off: '關閉知識庫',
+        slash_config: '檢視當前設定',
+        slash_cancel: '中止當前正在執行的 Agent 任務',
+        slash_logs: '檢視最近日誌',
+        slash_version: '檢視版本',
+        input_placeholder: '輸入訊息，或輸入 / 使用指令',
+        config_title: '設定管理', config_desc: '管理模型和 Agent 設定',
+        config_model: '模型設定', config_agent: 'Agent 設定',
+        config_language: '語言', config_language_hint: '介面展示、命令文案、系統提示詞等使用的語言（與右上角切換同步）',
+        config_model_advanced: '高階設定',
+        config_channel: '管道設定',
+        config_agent_enabled: 'Agent 模式',
+        config_max_tokens: '最大上下文 Token', config_max_tokens_hint: '對話中 Agent 能輸入的最大 Token 長度，超過後會智慧壓縮處理',
+        config_max_turns: '最大記憶輪次', config_max_turns_hint: '一問一答為一輪，超過後會智慧壓縮處理',
+        config_max_steps: '最大執行步數', config_max_steps_hint: '單次對話中 Agent 最多呼叫工具的次數',
+        config_enable_thinking: '深度思考', config_enable_thinking_hint: '是否啟用深度思考模式',
+        config_self_evolution: '自主進化', config_self_evolution_hint: '會話空閒後自動覆盤，沉澱記憶、最佳化技能、處理未完成事項',
+        evolution_badge: '自主學習',
+        config_channel_type: '管道型別',
+        config_provider: '模型廠商', config_model_name: '模型',
+        config_custom_model_hint: '輸入自定義模型名稱',
+        config_save: '儲存', config_saved: '已儲存',
+        config_save_error: '儲存失敗',
+        config_custom_option: '自定義',
+        config_custom_tip: '介面需遵循 OpenAI API 協議',
+        config_security: '安全設定', config_password: '訪問密碼',
+        config_password_hint: '留空則不啟用密碼保護',
+        config_password_changed: '密碼已更新',
+        config_password_cleared: '密碼已清除',
+        config_password_security_warning: '⚠️ 警告：目前密碼為空且對外連接埠開放，建議重啟服務，或檢查是否調整監聽位址綁定。',
+        skills_title: '技能管理', skills_desc: '檢視、啟用或禁用 Agent 工具和技能', skills_hub_btn: '探索技能廣場',
+        skills_loading: '載入技能中...', skills_loading_desc: '技能載入後將顯示在此處',
+        tools_section_title: '內建工具', tools_loading: '載入工具中...',
+        skills_section_title: '技能', skill_enable: '啟用', skill_disable: '禁用',
+        skill_toggle_error: '操作失敗，請稍後再試',
+        memory_title: '記憶管理', memory_desc: '檢視 Agent 記憶檔案和內容',
+        memory_tab_files: '記憶檔案', memory_tab_dreams: '自主進化',
+        memory_loading: '載入記憶檔案中...', memory_loading_desc: '記憶檔案將顯示在此處',
+        memory_back: '返回列表',
+        memory_col_name: '檔名', memory_col_type: '型別', memory_col_size: '大小', memory_col_updated: '更新時間',
+        channels_title: '管道管理', channels_desc: '管理已接入的訊息管道',
+        channels_add: '接入管道', channels_disconnect: '斷開',
+        channels_save: '儲存設定', channels_saved: '已儲存', channels_save_error: '儲存失敗',
+        channels_restarted: '已儲存並重啟',
+        channels_connect_btn: '接入', channels_cancel: '取消',
+        channels_select_placeholder: '選擇要接入的管道...',
+        channels_empty: '暫未接入任何管道', channels_empty_desc: '點選右上角「接入管道」按鈕開始設定',
+        channels_disconnect_confirm: '確認斷開該管道？設定將保留但管道會停止執行。',
+        channels_connected: '已接入', channels_connecting: '接入中...',
+        weixin_scan_title: '微信掃碼登入', weixin_scan_desc: '請使用微信掃描下方二維碼',
+        weixin_scan_loading: '正在獲取二維碼...', weixin_scan_waiting: '等待掃碼...',
+        weixin_scan_scanned: '已掃碼，請在手機上確認', weixin_scan_expired: '二維碼已過期，正在重新整理...',
+        weixin_scan_success: '登入成功，正在啟動管道...', weixin_scan_fail: '獲取二維碼失敗',
+        weixin_qr_tip: '二維碼約2分鐘後過期',
+        wecom_scan_btn: '掃碼建立企微機器人', wecom_scan_desc: '使用企業微信掃碼，一鍵建立智慧機器人',
+        wecom_scan_success: '建立成功，正在啟動管道...',
+        wecom_scan_fail: '建立失敗',
+        wecom_mode_scan: '掃碼接入', wecom_mode_manual: '手動填寫',
+        feishu_scan_btn: '一鍵建立飛書應用',
+        feishu_scan_desc: '使用飛書 App 掃碼，自動建立應用並預置全部許可權與事件訂閱',
+        feishu_scan_replace_desc: '使用飛書 App 掃碼建立新機器人，將覆蓋當前的 App ID / Secret',
+        feishu_scan_loading: '正在向飛書申請二維碼...',
+        feishu_scan_waiting: '等待掃碼...',
+        feishu_scan_tip: '二維碼 10 分鐘內有效，僅供一次掃描',
+        feishu_scan_open_link: '或點選此處在瀏覽器中開啟',
+        feishu_scan_success: '應用建立成功，正在啟動管道...',
+        feishu_scan_expired: '二維碼已過期，請重試',
+        feishu_scan_denied: '已取消授權',
+        feishu_scan_fail: '建立失敗',
+        feishu_scan_retry: '重試',
+        feishu_mode_scan: '掃碼建立', feishu_mode_manual: '手動填寫',
+        tasks_title: '定時任務', tasks_desc: '檢視和管理定時任務',
+        tasks_coming: '即將推出', tasks_coming_desc: '定時任務管理功能即將在此提供',
+        task_add_btn: '新增任務',
+        task_edit_title: '編輯定時任務',
+        task_add_title: '新增定時任務',
+        task_name: '任務名稱',
+        task_enabled: '啟用任務',
+        task_schedule_type: '排程型別',
+        task_schedule_cron: 'Cron 表示式',
+        task_schedule_interval: '固定間隔',
+        task_schedule_once: '一次性任務',
+        task_cron_expression: 'Cron 表示式',
+        task_cron_hint: '格式: 分 時 日 月 周，例如 "0 9 * * *" 表示每天 9:00',
+        task_interval_seconds: '間隔秒數',
+        task_interval_hint: '最小 60 秒，例如 3600 表示每小時執行一次',
+        task_once_time: '執行時間',
+        task_action_type: '動作型別',
+        task_action_send_message: '傳送訊息',
+        task_action_agent_task: 'AI 任務',
+        task_channel_type: '管道型別',
+        task_channel_hint: '選擇定時訊息傳送的管道',
+        task_message_content: '訊息內容',
+        task_task_description: '任務描述',
+        task_delete_btn: '刪除任務',
+        task_delete_confirm_title: '刪除定時任務',
+        task_delete_confirm_msg: '確定刪除該定時任務嗎？此操作無法撤銷。',
+        logs_title: '日誌', logs_desc: '實時日誌輸出 (run.log)',
+        logs_live: '實時', logs_coming_msg: '日誌流即將在此提供。將連線 run.log 實現類似 tail -f 的實時輸出。',
+        new_chat: '新對話',
+        session_history: '歷史會話',
+        today: '今天', yesterday: '昨天', earlier: '更早',
+        delete_session_confirm: '確認刪除該會話？所有訊息將被清除。',
+        delete_session_title: '刪除會話',
+        rename_session: '重新命名',
+        delete_message_confirm: '確認刪除這條訊息？',
+        delete_message_title: '刪除訊息',
+        edit_disabled_reply_active: '正在生成回覆，暫時無法編輯。',
+        delete_disabled_reply_active: '正在生成回覆，暫時無法刪除。',
+        untitled_session: '新對話',
+        context_cleared: '— 以上內容已從上下文中移除 —',
+        tip_new_chat: '新建對話',
+        tip_clear_context: '清除上下文',
+        tip_attach: '新增附件',
+        attach_menu_file: '上傳檔案',
+        mic_idle_title: '點選錄音 / 再按一次結束',
+        mic_recording_title: '錄音中，再次點選結束',
+        mic_busy_title: '識別中…',
+        mic_permission_denied: '無法訪問麥克風，請檢查瀏覽器許可權',
+        mic_too_short: '錄音太短，請重試',
+        mic_error: '語音識別失敗',
+        speak_msg: '朗讀這段回覆',
+        voice_reply_mode_label: '語音回覆策略',
+        voice_reply_off: '關閉',
+        voice_reply_if_voice: '僅語音問/語音答',
+        voice_reply_always: '總是語音回覆',
+        attach_menu_folder: '上傳資料夾',
+        confirm_yes: '確認',
+        confirm_cancel: '取消',
+        error_send: '傳送失敗，請稍後再試。', error_timeout: '請求超時，請再試一次。',
+        thinking_in_progress: '思考中...', thinking_done: '已深度思考', thinking_duration: '耗時',
+        edit_message: '編輯訊息',
+        regenerate_response: '重新生成',
+        edit_save: '儲存併傳送',
+        edit_cancel: '取消',
+        logout: '登出',
+        },
+    en: {
+        console: 'Console',
+        nav_chat: 'Chat', nav_manage: 'Management', nav_monitor: 'Monitor',
+        menu_chat: 'Chat', menu_config: 'Config', menu_models: 'Models', menu_skills: 'Skills',
+        menu_memory: 'Memory', menu_knowledge: 'Knowledge', menu_channels: 'Channels', menu_tasks: 'Tasks',
+        menu_logs: 'Logs',
+        models_title: 'Models',
+        models_desc: 'Manage chat, image, voice, embedding and search capabilities in one place',
+        models_section_vendors: 'Provider Credentials',
+        models_section_vendors_desc: 'Configured once, shared by multiple model capabilities',
+        models_section_capabilities: 'Capabilities',
+        models_add_vendor: 'Add Provider',
+        models_provider: 'Provider',
+        models_model: 'Model',
+        models_voice: 'Voice',
+        models_configured: 'configured',
+        models_not_configured: 'not configured',
+        models_pick_to_configure: 'pick to configure',
+        models_clear_credential: 'Clear credentials',
+        models_base_default_hint: 'Leave blank to use the official default base URL',
+        models_base_default: 'Default',
+        models_custom_vendor_label: 'Custom',
+        models_custom_name: 'Name',
+        models_custom_delete: 'Delete',
+        models_custom_delete_confirm_title: 'Delete custom provider',
+        models_custom_delete_confirm_msg: 'Delete this custom provider? This cannot be undone.',
+        models_custom_name_required: 'Name is required',
+        models_custom_base_required: 'API Base is required',
+        models_custom_edit_title: 'Edit custom provider',
+        models_custom_add_title: 'Add custom provider',
+        models_capability_chat: 'Main Model',
+        models_capability_chat_desc: 'Used for basic chat and agent reasoning',
+        models_capability_vision: 'Image Understanding',
+        models_capability_vision_desc: 'Recognizes image content, used by image recognition tools',
+        models_capability_image: 'Image Generation',
+        models_capability_image_desc: 'Generates images, used by image generation skills',
+        models_auto_using: 'Preferred',
+        models_capability_asr: 'Speech Recognition',
+        models_capability_asr_desc: 'Voice to text',
+        models_capability_tts: 'Speech Synthesis',
+        models_capability_tts_desc: 'Text to voice',
+        models_capability_embedding: 'Embedding',
+        models_capability_embedding_desc: 'Used for vectorized retrieval of memory and knowledge',
+        models_capability_search: 'Web Search',
+        models_capability_search_desc: 'Real-time web retrieval, used by search tools',
+        models_strategy_auto: 'auto',
+        models_search_strategy_label: 'Strategy',
+        models_search_strategy_fixed: 'Pinned',
+        models_search_strategy_auto_hint: 'Auto-pick from configured providers',
+        models_search_strategy_fixed_hint: 'Always use a specific provider',
+        models_pending_config: 'Pending setup',
+        models_search_available_label: 'Available:',
+        models_search_none_configured: 'No search provider enabled yet — click add.',
+        models_search_add_provider: 'Add provider',
+        models_search_add_desc: 'Pick a search provider to configure',
+        models_search_bocha_title: 'Configure Bocha API Key',
+        models_search_bocha_desc: 'Create a key at the Bocha open platform.',
+        models_search_edit_hint: 'Click to edit',
+        models_unavailable: 'unavailable',
+        models_set_via_env: 'enable via environment variable',
+        models_dim_label: 'dim',
+        models_save_success: 'Saved',
+        models_save_failed: 'Save failed',
+        models_cleared: 'Cleared',
+        models_clear_failed: 'Clear failed',
+        models_embedding_change_title: 'Change embedding model',
+        models_embedding_change_msg: 'Switching the embedding model invalidates the existing index — a rebuild will be needed. Continue?',
+        models_embedding_saved_title: 'Embedding model updated',
+        models_embedding_saved_msg: 'Send /memory rebuild-index in the chat to rebuild the index.',
+        models_embedding_saved_ok: 'Go',
+        models_pick_provider: 'Pick a provider',
+        models_clear_confirm_title: 'Clear provider credentials',
+        models_clear_confirm_msg: 'Remove this provider\'s API Key and Base URL? Capabilities relying on it will stop working.',
+        cancel: 'Cancel',
+        save: 'Save',
+        ok: 'OK',
+        knowledge_title: 'Knowledge', knowledge_desc: 'Browse and explore your knowledge base',
+        knowledge_tab_docs: 'Documents', knowledge_tab_graph: 'Graph',
+        knowledge_loading: 'Loading knowledge base...', knowledge_loading_desc: 'Knowledge pages will be displayed here',
+        knowledge_select_hint: 'Select a document to view', knowledge_empty_hint: 'No knowledge pages yet',
+        knowledge_empty_guide: 'Send documents, links or topics to the agent in chat, and it will automatically organize them into your knowledge base.',
+        knowledge_go_chat: 'Start a conversation',
+        knowledge_new: 'New',
+        knowledge_new_category: 'New category',
+        knowledge_new_document: 'New document',
+        knowledge_import_documents: 'Import documents',
+        welcome_subtitle: 'I can help you answer questions, manage your computer, create and execute skills, and keep growing through <br> long-term memory and a personal knowledge base.',
+        example_sys_title: 'System', example_sys_text: 'Show me the files in the workspace',
+        example_task_title: 'Scheduler', example_task_text: 'Remind me to check the server in 5 minutes',
+        example_code_title: 'Coding', example_code_text: 'Search today\'s AI news and generate a visual report webpage',
+        example_knowledge_title: 'Knowledge', example_knowledge_text: 'Show me the current knowledge base',
+        example_skill_title: 'Skills', example_skill_text: 'Show current tools and skills',
+        example_web_title: 'Commands', example_web_text: 'Show all commands',
+        slash_help: 'Show this help',
+        slash_status: 'Show running status',
+        slash_context: 'Show conversation context',
+        slash_context_clear: 'Clear conversation context',
+        slash_skill_list: 'List installed skills',
+        slash_skill_list_remote: 'Browse Skill Hub',
+        slash_skill_search: 'Search skills',
+        slash_skill_install: 'Install a skill (name or GitHub URL)',
+        slash_skill_uninstall: 'Uninstall a skill',
+        slash_skill_info: 'Show skill details',
+        slash_skill_enable: 'Enable a skill',
+        slash_skill_disable: 'Disable a skill',
+        slash_memory_dream: 'Trigger memory distillation (optional days, default 3)',
+        slash_knowledge: 'Show knowledge base stats',
+        slash_knowledge_list: 'Show knowledge base file tree',
+        slash_knowledge_on: 'Enable knowledge base',
+        slash_knowledge_off: 'Disable knowledge base',
+        slash_config: 'Show current config',
+        slash_cancel: 'Abort the running Agent task',
+        slash_logs: 'Show recent logs',
+        slash_version: 'Show version',
+        input_placeholder: 'Type a message, or press / for commands',
+        config_title: 'Configuration', config_desc: 'Manage model and agent settings',
+        config_model: 'Model Configuration', config_agent: 'Agent Configuration',
+        config_language: 'Language', config_language_hint: 'Language for the UI, command text, system prompts and more (synced with the top-right switch)',
+        config_model_advanced: 'Advanced',
+        config_channel: 'Channel Configuration',
+        config_agent_enabled: 'Agent Mode',
+        config_max_tokens: 'Max Context Tokens', config_max_tokens_hint: 'Max tokens the Agent can input per conversation, auto-compressed when exceeded',
+        config_max_turns: 'Max Memory Turns', config_max_turns_hint: 'One Q&A pair = one turn, auto-compressed when exceeded',
+        config_max_steps: 'Max Steps', config_max_steps_hint: 'Max tool calls the Agent can make in a single conversation',
+        config_enable_thinking: 'Deep Thinking', config_enable_thinking_hint: 'Enable deep thinking mode',
+        config_self_evolution: 'Self-Evolution', config_self_evolution_hint: 'Auto-review idle conversations to consolidate memory, improve skills, and follow up on unfinished tasks',
+        evolution_badge: 'Self-learned',
+        config_channel_type: 'Channel Type',
+        config_provider: 'Provider', config_model_name: 'Model',
+        config_custom_model_hint: 'Enter custom model name',
+        config_save: 'Save', config_saved: 'Saved',
+        config_save_error: 'Save failed',
+        config_custom_option: 'Custom',
+        config_custom_tip: 'API must follow OpenAI protocol.',
+        config_security: 'Security', config_password: 'Password',
+        config_password_hint: 'Leave empty to disable password protection',
+        config_password_changed: 'Password updated',
+        config_password_cleared: 'Password cleared',
+        config_password_security_warning: '⚠️ Warning: Password is now empty and the port is exposed. Consider restarting the service or adjusting the listening address binding.',
+        skills_title: 'Skills', skills_desc: 'View, enable, or disable agent tools and skills', skills_hub_btn: 'Skill Hub',
+        skills_loading: 'Loading skills...', skills_loading_desc: 'Skills will be displayed here after loading',
+        tools_section_title: 'Built-in Tools', tools_loading: 'Loading tools...',
+        skills_section_title: 'Skills', skill_enable: 'Enable', skill_disable: 'Disable',
+        skill_toggle_error: 'Operation failed, please try again',
+        memory_title: 'Memory', memory_desc: 'View agent memory files and contents',
+        memory_tab_files: 'Memory Files', memory_tab_dreams: 'Self-Evolution',
+        memory_loading: 'Loading memory files...', memory_loading_desc: 'Memory files will be displayed here',
+        memory_back: 'Back to list',
+        memory_col_name: 'Filename', memory_col_type: 'Type', memory_col_size: 'Size', memory_col_updated: 'Updated',
+        channels_title: 'Channels', channels_desc: 'Manage connected messaging channels',
+        channels_add: 'Connect', channels_disconnect: 'Disconnect',
+        channels_save: 'Save', channels_saved: 'Saved', channels_save_error: 'Save failed',
+        channels_restarted: 'Saved & Restarted',
+        channels_connect_btn: 'Connect', channels_cancel: 'Cancel',
+        channels_select_placeholder: 'Select a channel to connect...',
+        channels_empty: 'No channels connected', channels_empty_desc: 'Click the "Connect" button above to get started',
+        channels_disconnect_confirm: 'Disconnect this channel? Config will be preserved but the channel will stop.',
+        channels_connected: 'Connected', channels_connecting: 'Connecting...',
+        weixin_scan_title: 'WeChat QR Login', weixin_scan_desc: 'Scan the QR code below with WeChat',
+        weixin_scan_loading: 'Loading QR code...', weixin_scan_waiting: 'Waiting for scan...',
+        weixin_scan_scanned: 'Scanned, please confirm on your phone', weixin_scan_expired: 'QR code expired, refreshing...',
+        weixin_scan_success: 'Login successful, starting channel...', weixin_scan_fail: 'Failed to load QR code',
+        weixin_qr_tip: 'QR code expires in ~2 minutes',
+        wecom_scan_btn: 'Scan to Create WeCom Bot', wecom_scan_desc: 'Scan with WeCom to create a bot instantly',
+        wecom_scan_success: 'Bot created, starting channel...',
+        wecom_scan_fail: 'Bot creation failed',
+        wecom_mode_scan: 'Scan QR', wecom_mode_manual: 'Manual',
+        feishu_scan_btn: 'One-click Create Feishu App',
+        feishu_scan_desc: 'Scan with Feishu App to create an app with all required permissions pre-configured',
+        feishu_scan_replace_desc: 'Scan with Feishu App to create a new bot — will overwrite the current App ID / Secret',
+        feishu_scan_loading: 'Requesting QR code from Feishu...',
+        feishu_scan_waiting: 'Waiting for scan...',
+        feishu_scan_tip: 'QR code expires in 10 minutes, single use only',
+        feishu_scan_open_link: 'Or click here to open in browser',
+        feishu_scan_success: 'App created, starting channel...',
+        feishu_scan_expired: 'QR code expired, please retry',
+        feishu_scan_denied: 'Authorization cancelled',
+        feishu_scan_fail: 'App creation failed',
+        feishu_scan_retry: 'Retry',
+        feishu_mode_scan: 'Scan QR', feishu_mode_manual: 'Manual',
+        tasks_title: 'Scheduled Tasks', tasks_desc: 'View and manage scheduled tasks',
+        tasks_coming: 'Coming Soon', tasks_coming_desc: 'Scheduled task management will be available here',
+        task_add_btn: 'Add Task',
+        task_edit_title: 'Edit Task',
+        task_add_title: 'Add Task',
+        task_name: 'Task Name',
+        task_enabled: 'Enable Task',
+        task_schedule_type: 'Schedule Type',
+        task_schedule_cron: 'Cron Expression',
+        task_schedule_interval: 'Fixed Interval',
+        task_schedule_once: 'One-time Task',
+        task_cron_expression: 'Cron Expression',
+        task_cron_hint: 'Format: minute hour day month weekday, e.g. "0 9 * * *" means daily at 9:00',
+        task_interval_seconds: 'Interval (seconds)',
+        task_interval_hint: 'Minimum 60 seconds, e.g. 3600 means once per hour',
+        task_once_time: 'Execution Time',
+        task_action_type: 'Action Type',
+        task_action_send_message: 'Send Message',
+        task_action_agent_task: 'AI Task',
+        task_channel_type: 'Channel Type',
+        task_channel_hint: 'Select the channel to send scheduled messages',
+        task_message_content: 'Message Content',
+        task_task_description: 'Task Description',
+        task_delete_btn: 'Delete Task',
+        task_delete_confirm_title: 'Delete Task',
+        task_delete_confirm_msg: 'Delete this scheduled task? This action cannot be undone.',
+        logs_title: 'Logs', logs_desc: 'Real-time log output (run.log)',
+        logs_live: 'Live', logs_coming_msg: 'Log streaming will be available here. Connects to run.log for real-time output similar to tail -f.',
+        new_chat: 'New Chat',
+        session_history: 'History',
+        today: 'Today', yesterday: 'Yesterday', earlier: 'Earlier',
+        delete_session_confirm: 'Delete this session? All messages will be removed.',
+        delete_session_title: 'Delete Session',
+        rename_session: 'Rename',
+        delete_message_confirm: 'Delete this message?',
+        delete_message_title: 'Delete Message',
+        edit_disabled_reply_active: 'Reply is being generated; editing is temporarily unavailable.',
+        delete_disabled_reply_active: 'Reply is being generated; deletion is temporarily unavailable.',
+        untitled_session: 'New Chat',
+        context_cleared: '— Context above has been cleared —',
+        tip_new_chat: 'New Chat',
+        tip_clear_context: 'Clear Context',
+        tip_attach: 'Add Attachment',
+        attach_menu_file: 'Upload File',
+        mic_idle_title: 'Click to record, click again to stop',
+        mic_recording_title: 'Recording, click to stop',
+        mic_busy_title: 'Transcribing…',
+        mic_permission_denied: 'Cannot access microphone — check browser permissions',
+        mic_too_short: 'Recording too short, please retry',
+        mic_error: 'Speech recognition failed',
+        speak_msg: 'Read this reply aloud',
+        voice_reply_mode_label: 'Voice reply policy',
+        voice_reply_off: 'Off',
+        voice_reply_if_voice: 'Voice only if voice input',
+        voice_reply_always: 'Always reply with voice',
+        attach_menu_folder: 'Upload Folder',
+        confirm_yes: 'Confirm',
+        confirm_cancel: 'Cancel',
+        error_send: 'Failed to send. Please try again.', error_timeout: 'Request timeout. Please try again.',
+        thinking_in_progress: 'Thinking...', thinking_done: 'Thought', thinking_duration: 'Duration',
+        edit_message: 'Edit message',
+        regenerate_response: 'Regenerate',
+        edit_save: 'Save and send',
+        edit_cancel: 'Cancel',
+        logout: 'Logout',
+    }
+};
+
+// Resolve language by priority: user choice (localStorage) -> backend-detected
+// (cow_lang) -> browser language -> 'zh'. Shares __cowResolveLang__ defined in
+// chat.html; falls back to a local resolver if loaded standalone.
+let currentLang = (typeof window.__cowResolveLang__ === 'function')
+    ? window.__cowResolveLang__()
+    : (function () {
+        const norm = (raw) => {
+            if (!raw) return '';
+            const v = String(raw).trim().toLowerCase();
+            if (v === 'auto') return '';
+            // Handle Traditional Chinese variants first (more specific)
+            if (v === 'zh-hant' || v.startsWith('zh-hant-') || v === 'zh-tw' || v === 'zh-hk') return 'zh-Hant';
+            // Then Simplified Chinese
+            if (v.indexOf('zh') === 0) return 'zh';
+            if (v.indexOf('en') === 0) return 'en';
+            return '';
+        };
+        return norm(localStorage.getItem('cow_lang'))
+            || norm(window.__COW_DEFAULT_LANG__)
+            || norm(navigator.language)
+            || 'zh';
+    })();
+
+function t(key) {
+    return (I18N[currentLang] && I18N[currentLang][key]) || (I18N.en[key]) || key;
+}
+
+// Resolve a localized label that may be either a plain string or
+// a {zh, en} object returned by the backend.
+function localizedLabel(label) {
+    if (label && typeof label === 'object') {
+        return label[currentLang] || label.en || label.zh || '';
+    }
+    return label || '';
+}
+
+function applyI18n() {
+    document.querySelectorAll('[data-i18n]').forEach(el => {
+        el.textContent = t(el.dataset.i18n);
+    });
+    document.querySelectorAll('[data-i18n-html]').forEach(el => {
+        el.innerHTML = t(el.dataset.i18nHtml);
+    });
+    document.querySelectorAll('[data-i18n-placeholder]').forEach(el => {
+        el.placeholder = t(el.dataset['i18nPlaceholder']);
+    });
+    document.querySelectorAll('[data-i18n-title]').forEach(el => {
+        el.title = t(el.dataset['i18nTitle']);
+    });
+    document.querySelectorAll('[data-tip-key]').forEach(el => {
+        el.setAttribute('data-tooltip', t(el.dataset.tipKey));
+    });
+    installCfgTipPortal();
+    
+    // Clear any status messages when language changes
+    document.querySelectorAll('[id$="-status"]').forEach(el => {
+        el.classList.add('opacity-0');
+    });
+    
+    const langLabel = document.getElementById('lang-label');
+    if (langLabel) {
+        if (currentLang === 'zh-Hant') langLabel.textContent = '繁体';
+        else if (currentLang === 'zh') langLabel.textContent = '简体';
+        else langLabel.textContent = 'EN';
+    }
+    // Highlight the active option in the header language dropdown menu.
+    document.querySelectorAll('#lang-menu .lang-menu-item').forEach(item => {
+        const active = item.dataset.lang === currentLang;
+        item.classList.toggle('text-blue-600', active);
+        item.classList.toggle('dark:text-blue-400', active);
+        item.classList.toggle('font-medium', active);
+    });
+    // Point the docs link to the locale-specific documentation site.
+    const docsLink = document.getElementById('docs-link');
+    if (docsLink) docsLink.href = currentLang === 'zh' ? 'https://docs.cowagent.ai/zh' : 'https://docs.cowagent.ai';
+}
+
+// Single entry point for switching language. Updates the in-memory language,
+// persists the user choice locally, re-renders the UI, and binds the choice to
+// the backend `cow_lang` config so logs / agent replies / CLI follow suit.
+function setLanguage(lang) {
+    const next = (lang === 'en' || lang === 'zh' || lang === 'zh-Hant') ? lang : 'zh';
+    if (next === currentLang) {
+        // Still persist + sync in case storage/backend drifted from the UI.
+        syncLanguageToBackend(next);
+        return;
+    }
+    currentLang = next;
+    localStorage.setItem('cow_lang', currentLang);
+    applyI18n();
+    _applyInputTooltips();
+    // Keep the language switch button and config selector visually in sync.
+    try { updateLangControls(); } catch (e) {}
+    
+    // Sync language choice to backend first, then trigger dynamic views reload
+    // to avoid race conditions on API endpoints.
+    syncLanguageToBackend(currentLang, () => {
+        try { rerenderDynamicViews(); } catch (e) {}
+    });
+}
+
+// Persist the language to the backend `cow_lang` config (best-effort; the UI
+// has already switched locally, so a network failure is non-blocking).
+function syncLanguageToBackend(lang, callback) {
+    try {
+        fetch('/config', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ updates: { cow_lang: lang } })
+        })
+        .then(() => { if (callback) callback(); })
+        .catch(() => { if (callback) callback(); });
+    } catch (e) {
+        if (callback) callback();
+    }
+}
+
+// Reflect the current language on both the top-right toggle and the config
+// selector (if present), so the two entry points stay synchronized.
+function updateLangControls() {
+    const langLabel = document.getElementById('lang-label');
+    if (langLabel) {
+        if (currentLang === 'zh-Hant') langLabel.textContent = '繁体';
+        else if (currentLang === 'zh') langLabel.textContent = '简体';
+        else langLabel.textContent = 'EN';
+    }
+    // Highlight the active option in the header language dropdown menu.
+    document.querySelectorAll('#lang-menu .lang-menu-item').forEach(item => {
+        const active = item.dataset.lang === currentLang;
+        item.classList.toggle('text-blue-600', active);
+        item.classList.toggle('dark:text-blue-400', active);
+        item.classList.toggle('font-medium', active);
+    });
+    // The config language picker is the custom .cfg-dropdown component. Only
+    // sync it once it has been initialized (i.e. the config panel was opened).
+    const sel = document.getElementById('cfg-lang-select');
+    if (sel && sel._ddValue !== undefined && sel._ddValue !== currentLang) {
+        sel._ddValue = currentLang;
+        const textEl = sel.querySelector('.cfg-dropdown-text');
+        if (textEl) {
+            if (currentLang === 'zh-Hant') textEl.textContent = '繁體中文';
+            else if (currentLang === 'zh') textEl.textContent = '简体中文';
+            else textEl.textContent = 'English';
+        }
+        sel.querySelectorAll('.cfg-dropdown-item').forEach(i => {
+            i.classList.toggle('active', i.dataset.value === currentLang);
+        });
+    }
+}
+
+// Toggle the header language dropdown menu open/closed.
+function toggleLangMenu(event) {
+    if (event) event.stopPropagation();
+    const menu = document.getElementById('lang-menu');
+    if (menu) menu.classList.toggle('hidden');
+}
+
+// Pick a language from the dropdown, then close the menu.
+function selectLanguage(lang) {
+    const menu = document.getElementById('lang-menu');
+    if (menu) menu.classList.add('hidden');
+    setLanguage(lang);
+}
+window.toggleLangMenu = toggleLangMenu;
+window.selectLanguage = selectLanguage;
+
+// Close the language menu when clicking outside of it.
+document.addEventListener('click', (e) => {
+    const selector = document.getElementById('lang-selector');
+    const menu = document.getElementById('lang-menu');
+    if (menu && !menu.classList.contains('hidden') && selector && !selector.contains(e.target)) {
+        menu.classList.add('hidden');
+    }
+});
+
+// Refresh JS-rendered views after a language switch. Each branch uses the
+// lightweight in-memory re-render path (no extra network round-trips).
+function rerenderDynamicViews() {
+    if (currentView === 'models' && typeof renderModelsView === 'function'
+            && modelsState && (modelsState.providers || modelsState.capabilities)) {
+        renderModelsView();
+    }
+    // Reload task list after language switch
+    if (currentView === 'tasks') {
+        tasksLoaded = false;
+        loadTasksView();
+    }
+    // Reload skills and tools after language switch
+    if (currentView === 'skills') {
+        toolsLoaded = false;
+        loadSkillsView();
+    }
+    // Reload channels after language switch
+    if (currentView === 'channels') {
+        loadChannelsView();
+    }
+    // Reload config after language switch
+    if (currentView === 'config') {
+        loadConfigView();
+    }
+}
+
+// Floating tooltip portal for [data-tip-key] elements. Tooltip nodes are
+// appended to <body> so they aren't clipped by overflow:hidden ancestors
+// (e.g. the config panel's scroll container).
+let _cfgTipPortalEl = null;
+let _cfgTipPortalInstalled = false;
+function installCfgTipPortal() {
+    if (_cfgTipPortalInstalled) return;
+    _cfgTipPortalInstalled = true;
+
+    const showTip = (target) => {
+        const text = target.getAttribute('data-tooltip');
+        if (!text) return;
+        if (!_cfgTipPortalEl) {
+            _cfgTipPortalEl = document.createElement('div');
+            _cfgTipPortalEl.className = 'cfg-tip-floating';
+            document.body.appendChild(_cfgTipPortalEl);
+        }
+        _cfgTipPortalEl.textContent = text;
+        const rect = target.getBoundingClientRect();
+        // Render once to measure, then position above the target, centered.
+        _cfgTipPortalEl.style.left = '0px';
+        _cfgTipPortalEl.style.top = '0px';
+        _cfgTipPortalEl.classList.add('show');
+        const tipRect = _cfgTipPortalEl.getBoundingClientRect();
+        let left = rect.left + rect.width / 2 - tipRect.width / 2;
+        // Clamp horizontally to the viewport with an 8px gutter.
+        left = Math.max(8, Math.min(left, window.innerWidth - tipRect.width - 8));
+        const top = rect.top - tipRect.height - 6;
+        _cfgTipPortalEl.style.left = left + 'px';
+        _cfgTipPortalEl.style.top = top + 'px';
+    };
+    const hideTip = () => {
+        if (_cfgTipPortalEl) _cfgTipPortalEl.classList.remove('show');
+    };
+
+    document.addEventListener('mouseover', (e) => {
+        const target = e.target.closest('[data-tip-key]');
+        if (target) showTip(target);
+    });
+    document.addEventListener('mouseout', (e) => {
+        const target = e.target.closest('[data-tip-key]');
+        if (target) hideTip();
+    });
+    // Hide on scroll/resize so the tooltip doesn't drift away from its anchor.
+    window.addEventListener('scroll', hideTip, true);
+    window.addEventListener('resize', hideTip);
+}
+
+// =====================================================================
+// Theme
+// =====================================================================
+let currentTheme = localStorage.getItem('cow_theme') || 'dark';
+
+function applyTheme() {
+    const root = document.documentElement;
+    if (currentTheme === 'dark') {
+        root.classList.add('dark');
+        document.getElementById('theme-icon').className = 'fas fa-sun';
+        document.getElementById('hljs-light').disabled = true;
+        document.getElementById('hljs-dark').disabled = false;
+    } else {
+        root.classList.remove('dark');
+        document.getElementById('theme-icon').className = 'fas fa-moon';
+        document.getElementById('hljs-light').disabled = false;
+        document.getElementById('hljs-dark').disabled = true;
+    }
+}
+
+function toggleTheme() {
+    currentTheme = currentTheme === 'dark' ? 'light' : 'dark';
+    localStorage.setItem('cow_theme', currentTheme);
+    applyTheme();
+}
+
+// =====================================================================
+// Sidebar & Navigation
+// =====================================================================
+const VIEW_META = {
+    chat:     { group: 'nav_chat',    page: 'menu_chat' },
+    config:   { group: 'nav_manage',  page: 'menu_config' },
+    models:   { group: 'nav_manage',  page: 'menu_models' },
+    skills:   { group: 'nav_manage',  page: 'menu_skills' },
+    memory:   { group: 'nav_manage',  page: 'menu_memory' },
+    knowledge:{ group: 'nav_manage',  page: 'menu_knowledge' },
+    channels: { group: 'nav_manage',  page: 'menu_channels' },
+    tasks:    { group: 'nav_manage',  page: 'menu_tasks' },
+    logs:     { group: 'nav_monitor', page: 'menu_logs' },
+};
+
+let currentView = 'chat';
+
+function navigateTo(viewId) {
+    if (!VIEW_META[viewId]) return;
+    document.querySelectorAll('.view').forEach(v => v.classList.remove('active'));
+    const target = document.getElementById('view-' + viewId);
+    if (target) target.classList.add('active');
+    document.querySelectorAll('.sidebar-item').forEach(item => {
+        item.classList.toggle('active', item.dataset.view === viewId);
+    });
+    const meta = VIEW_META[viewId];
+    document.getElementById('breadcrumb-group').textContent = t(meta.group);
+    document.getElementById('breadcrumb-group').dataset.i18n = meta.group;
+    document.getElementById('breadcrumb-page').textContent = t(meta.page);
+    document.getElementById('breadcrumb-page').dataset.i18n = meta.page;
+    currentView = viewId;
+    
+    // Clear status messages when navigating away
+    document.querySelectorAll('[id$="-status"]').forEach(el => {
+        el.classList.add('opacity-0');
+    });
+    
+    if (window.innerWidth < 1024) closeSidebar();
+}
+
+function toggleSidebar() {
+    const sidebar = document.getElementById('sidebar');
+    const overlay = document.getElementById('sidebar-overlay');
+    const isOpen = !sidebar.classList.contains('-translate-x-full');
+    if (isOpen) {
+        closeSidebar();
+    } else {
+        sidebar.classList.remove('-translate-x-full');
+        overlay.classList.remove('hidden');
+    }
+}
+
+function closeSidebar() {
+    document.getElementById('sidebar').classList.add('-translate-x-full');
+    document.getElementById('sidebar-overlay').classList.add('hidden');
+}
+
+document.querySelectorAll('.menu-group > button').forEach(btn => {
+    btn.addEventListener('click', () => {
+        btn.parentElement.classList.toggle('open');
+    });
+});
+
+document.querySelectorAll('.sidebar-item').forEach(item => {
+    item.addEventListener('click', () => navigateTo(item.dataset.view));
+});
+
+window.addEventListener('resize', () => {
+    if (window.innerWidth >= 1024) {
+        document.getElementById('sidebar').classList.remove('-translate-x-full');
+        document.getElementById('sidebar-overlay').classList.add('hidden');
+    } else {
+        if (!document.getElementById('sidebar').classList.contains('-translate-x-full')) {
+            closeSidebar();
+        }
+    }
+});
+
+// =====================================================================
+// Markdown Renderer
+// =====================================================================
+const FALLBACK_HLJS = {
+    getLanguage() { return false; },
+    highlight(str) { return { value: escapeHtml(str) }; },
+    highlightAuto(str) { return { value: escapeHtml(str) }; },
+    highlightElement() {},
+};
+
+function getHljs() {
+    return window.hljs || FALLBACK_HLJS;
+}
+
+function createMd() {
+    const hljsLib = getHljs();
+    const mdFactory = window.markdownit;
+    if (typeof mdFactory !== 'function') {
+        return {
+            render(text) {
+                return `<p>${escapeHtml(text || '')}</p>`;
+            }
+        };
+    }
+    const md = mdFactory({
+        html: false, breaks: true, linkify: true, typographer: true,
+        highlight: function(str, lang) {
+            if (lang && hljsLib.getLanguage(lang)) {
+                try { return hljsLib.highlight(str, { language: lang }).value; } catch (_) {}
+            }
+            return hljsLib.highlightAuto(str).value;
+        }
+    });
+    const defaultLinkOpen = md.renderer.rules.link_open || function(tokens, idx, options, env, self) {
+        return self.renderToken(tokens, idx, options);
+    };
+    md.renderer.rules.link_open = function(tokens, idx, options, env, self) {
+        tokens[idx].attrPush(['target', '_blank']);
+        tokens[idx].attrPush(['rel', 'noopener noreferrer']);
+        return defaultLinkOpen(tokens, idx, options, env, self);
+    };
+    return md;
+}
+
+const md = createMd();
+
+const VIDEO_EXT_RE = /\.(?:mp4|webm|mov|avi|mkv)$/i;  // tested against URL without query string
+const IMAGE_EXT_RE = /\.(?:jpg|jpeg|png|gif|webp|bmp|svg)$/i;  // tested against URL without query string
+
+function _toWebUrl(url) {
+    if (/^\/[A-Za-z]/.test(url) && !url.startsWith('/api/')) {
+        return '/api/file?path=' + encodeURIComponent(url);
+    }
+    if (/^file:\/\/\//i.test(url)) {
+        return '/api/file?path=' + encodeURIComponent(url.replace(/^file:\/\/\//i, '/'));
+    }
+    return url;
+}
+
+function _buildVideoHtml(url) {
+    const webUrl = _toWebUrl(url);
+    const fileName = url.split('/').pop().split('?')[0];
+    return `<div style="margin:10px 0;">` +
+        `<video controls preload="metadata" ` +
+        `style="max-width:100%;border-radius:10px;box-shadow:0 2px 8px rgba(0,0,0,0.15);display:block;">` +
+        `<source src="${webUrl}"></video>` +
+        `<a href="${webUrl}" target="_blank" ` +
+        `style="display:inline-flex;align-items:center;gap:4px;margin-top:4px;font-size:12px;color:#8b8fa8;text-decoration:none;">` +
+        `<i class="fas fa-download"></i> ${escapeHtml(fileName)}</a></div>`;
+}
+
+function _openImageLightbox(src) {
+    let overlay = document.getElementById('cow-lightbox');
+    if (!overlay) {
+        overlay = document.createElement('div');
+        overlay.id = 'cow-lightbox';
+        overlay.style.cssText = 'position:fixed;inset:0;z-index:9999;background:rgba(0,0,0,0.85);display:flex;align-items:center;justify-content:center;cursor:zoom-out;opacity:0;transition:opacity .2s';
+        overlay.onclick = () => { overlay.style.opacity = '0'; setTimeout(() => overlay.style.display = 'none', 200); };
+        const img = document.createElement('img');
+        img.id = 'cow-lightbox-img';
+        img.style.cssText = 'max-width:92vw;max-height:92vh;border-radius:8px;box-shadow:0 4px 24px rgba(0,0,0,0.5);object-fit:contain;';
+        img.onclick = (e) => e.stopPropagation();
+        overlay.appendChild(img);
+        document.body.appendChild(overlay);
+    }
+    overlay.querySelector('#cow-lightbox-img').src = src;
+    overlay.style.display = 'flex';
+    requestAnimationFrame(() => overlay.style.opacity = '1');
+}
+
+function _buildImageHtml(url) {
+    const webUrl = _toWebUrl(url);
+    const safeUrl = webUrl.replace(/"/g, '&quot;');
+    return `<div style="margin:10px 0;">` +
+        `<img src="${safeUrl}" alt="image" loading="lazy" ` +
+        `onclick="_openImageLightbox(this.src)" ` +
+        `style="max-width:520px;width:100%;border-radius:10px;box-shadow:0 2px 8px rgba(0,0,0,0.15);display:block;cursor:zoom-in;">` +
+        `</div>`;
+}
+
+function injectVideoPlayers(html) {
+    // Step 1: replace markdown-it anchor tags whose href points to a video file.
+    const step1 = html.replace(
+        /<a\s+href="(https?:\/\/[^"]+)"[^>]*>[^<]*<\/a>/gi,
+        (match, url) => VIDEO_EXT_RE.test(url.split('?')[0]) ? _buildVideoHtml(url) : match
+    );
+    // Step 2: replace any remaining bare video URLs in text nodes (not inside HTML tags).
+    // Split on HTML tags to avoid touching src/href attributes already in markup.
+    return step1.split(/(<[^>]+>)/).map((chunk, idx) => {
+        // Even indices are text nodes; odd indices are HTML tags — leave them untouched.
+        if (idx % 2 !== 0) return chunk;
+        return chunk.replace(/https?:\/\/\S+/gi, (url) => {
+            const bare = url.replace(/[),.\s]+$/, '');  // strip trailing punctuation
+            return VIDEO_EXT_RE.test(bare.split('?')[0]) ? _buildVideoHtml(bare) : url;
+        });
+    }).join('');
+}
+
+// Convert image URLs into inline <img> previews. Mirrors injectVideoPlayers but for images.
+// Handles three cases produced by markdown-it:
+//   1. <a href="...image.jpg">...</a>  (bare URL or autolink that linkify turned into an anchor)
+//   2. <img src="...">                  (markdown image syntax) — leave as-is, but normalize style
+//   3. raw URL still present in a text node                    — only as a safety net
+function injectImagePreviews(html) {
+    // Step 1: anchor whose href points to an image file -> replace with <img> preview.
+    const step1 = html.replace(
+        /<a\s+href="(https?:\/\/[^"]+)"[^>]*>[^<]*<\/a>/gi,
+        (match, url) => IMAGE_EXT_RE.test(url.split('?')[0]) ? _buildImageHtml(url) : match
+    );
+    // Step 2: bare image URLs left in text nodes (rare — markdown-it's linkify usually catches them).
+    return step1.split(/(<[^>]+>)/).map((chunk, idx) => {
+        if (idx % 2 !== 0) return chunk;
+        return chunk.replace(/https?:\/\/\S+/gi, (url) => {
+            const bare = url.replace(/[),.\s]+$/, '');
+            return IMAGE_EXT_RE.test(bare.split('?')[0]) ? _buildImageHtml(bare) : url;
+        });
+    }).join('');
+}
+
+function _rewriteLocalImgSrc(html) {
+    return html.replace(/<img\s([^>]*?)src="([^"]+)"([^>]*?)>/gi, (match, pre, src, post) => {
+        const webSrc = _toWebUrl(src);
+        const safeSrc = webSrc.replace(/"/g, '&quot;');
+        const hasClick = /onclick/i.test(pre + post);
+        const clickAttr = hasClick ? '' : ` onclick="_openImageLightbox(this.src)" style="cursor:zoom-in;"`;
+        return `<img ${pre}src="${safeSrc}"${post}${clickAttr}>`;
+    });
+}
+
+function renderMarkdown(text) {
+    try {
+        let html = md.render(text);
+        html = _rewriteLocalImgSrc(html);
+        // Order matters: video first (more specific), then image.
+        html = injectImagePreviews(injectVideoPlayers(html));
+        // Note: Code block headers are added via DOM manipulation after insertion
+        // See addCodeBlockHeadersToElement()
+        return html;
+    }
+    catch (e) { return text.replace(/\n/g, '<br>'); }
+}
+
+function _addCodeBlockHeaders(container) {
+    // Add header with language label and copy button to each <pre> block using DOM manipulation
+    const preBlocks = container.querySelectorAll('pre');
+    preBlocks.forEach(pre => {
+        if (pre.parentElement && pre.parentElement.classList.contains('code-block-wrapper')) return;
+        
+        const codeEl = pre.querySelector('code');
+        if (!codeEl) return;
+        
+        const langClass = Array.from(codeEl.classList).find(c => c.startsWith('language-'));
+        const language = langClass ? langClass.replace('language-', '') : '';
+        // Hide label for unknown/empty languages (e.g. language-undefined)
+        const showLang = language && language !== 'undefined' && language !== 'code';
+        const langLabel = showLang ? language.charAt(0).toUpperCase() + language.slice(1) : '';
+        
+        const wrapper = document.createElement('div');
+        wrapper.className = 'code-block-wrapper';
+        
+        const header = document.createElement('div');
+        header.className = 'code-block-header';
+        header.innerHTML = `
+            <span class="code-block-lang">${langLabel}</span>
+            <button class="code-copy-btn" title="Copy code">
+                <i class="fas fa-copy"></i>
+            </button>
+        `;
+        
+        pre.parentNode.insertBefore(wrapper, pre);
+        wrapper.appendChild(header);
+        wrapper.appendChild(pre);
+    });
+}
+
+// =====================================================================
+// Chat Module
+// =====================================================================
+let isPolling = false;
+let pollGeneration = 0;   // incremented on each restart to cancel stale poll loops
+let loadingContainers = {};
+let activeStreams = {};   // request_id -> EventSource
+let sessionActiveRequest = {};   // session_id -> request_id (in-flight stream per session)
+
+function isCurrentSessionConversationActive() {
+    return !!sessionActiveRequest[sessionId];
+}
+
+function updateEditButtonsState() {
+    const active = isCurrentSessionConversationActive();
+    document.querySelectorAll('.edit-msg-btn, .delete-msg-btn').forEach(btn => {
+        btn.disabled = active;
+        if (btn.classList.contains('edit-msg-btn')) {
+            btn.title = active
+                ? t('edit_disabled_reply_active')
+                : t('edit_message');
+        } else {
+            btn.title = active
+                ? t('delete_disabled_reply_active')
+                : t('delete_message_title');
+        }
+    });
+}
+let streamBuffers = {};   // request_id -> { items: [event...], timestamp } for re-attach replay
+let isComposing = false;
+let appConfig = { use_agent: false, title: 'CowAgent', subtitle: '', providers: {}, api_bases: {} };
+
+const SESSION_ID_KEY = 'cow_session_id';
+
+function generateSessionId() {
+    return 'session_' + ([1e7]+-1e3+-4e3+-8e3+-1e11).replace(/[018]/g, c =>
+        (c ^ crypto.getRandomValues(new Uint8Array(1))[0] & 15 >> c / 4).toString(16)
+    );
+}
+
+// Restore session_id from localStorage so conversation history survives page refresh.
+// A new id is only generated when the user explicitly starts a new chat.
+function loadOrCreateSessionId() {
+    const stored = localStorage.getItem(SESSION_ID_KEY);
+    if (stored) return stored;
+    const fresh = generateSessionId();
+    localStorage.setItem(SESSION_ID_KEY, fresh);
+    return fresh;
+}
+
+let sessionId = loadOrCreateSessionId();
+
+// ---- Conversation history state ----
+let historyPage = 0;       // last page fetched (0 = nothing fetched yet)
+let historyHasMore = false;
+let historyLoading = false;
+
+fetch('/config').then(r => r.json()).then(data => {
+    if (data.status === 'success') {
+        appConfig = data;
+        const title = data.title || 'CowAgent';
+        document.getElementById('welcome-title').textContent = title;
+        initConfigView(data);
+    }
+    loadHistory(1);
+}).catch(() => { loadHistory(1); });
+
+// Start polling immediately so scheduler/push messages are received at any time
+startPolling();
+
+const chatInput = document.getElementById('chat-input');
+const sendBtn = document.getElementById('send-btn');
+const messagesDiv = document.getElementById('chat-messages');
+const fileInput = document.getElementById('file-input');
+const folderInput = document.getElementById('folder-input');
+const attachBtn = document.getElementById('attach-btn');
+const attachMenu = document.getElementById('attach-menu');
+const attachFolderOption = document.getElementById('attach-folder-option');
+const supportsDirectoryUpload = !!folderInput && 'webkitdirectory' in folderInput;
+
+if (!supportsDirectoryUpload && attachFolderOption) {
+    attachFolderOption.classList.add('hidden');
+}
+
+// ---------------- Mic button: in-page voice input via the configured ASR provider ----------------
+(function setupMicButton() {
+    const micBtn = document.getElementById('mic-btn');
+    if (!micBtn) return;
+    if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia ||
+        typeof window.MediaRecorder === 'undefined') {
+        micBtn.style.display = 'none';
+        return;
+    }
+
+    let mediaRecorder = null;
+    let stream = null;
+    let chunks = [];
+    let recording = false;
+
+    const setIdle = () => {
+        recording = false;
+        micBtn.classList.remove('text-red-500', 'animate-pulse');
+        micBtn.classList.add('text-slate-400');
+        micBtn.querySelector('i').className = 'fas fa-microphone text-sm';
+        micBtn.title = t('mic_idle_title');
+    };
+    const setRecording = () => {
+        recording = true;
+        micBtn.classList.remove('text-slate-400');
+        micBtn.classList.add('text-red-500', 'animate-pulse');
+        micBtn.querySelector('i').className = 'fas fa-stop text-sm';
+        micBtn.title = t('mic_recording_title');
+    };
+    const setBusy = () => {
+        micBtn.classList.remove('text-red-500', 'animate-pulse', 'text-slate-400');
+        micBtn.classList.add('text-primary-500');
+        micBtn.querySelector('i').className = 'fas fa-spinner fa-spin text-sm';
+        micBtn.title = t('mic_busy_title');
+    };
+
+    const pickMimeType = () => {
+        const candidates = [
+            'audio/webm;codecs=opus',
+            'audio/webm',
+            'audio/ogg;codecs=opus',
+            'audio/mp4',
+        ];
+        for (const m of candidates) {
+            if (window.MediaRecorder.isTypeSupported && MediaRecorder.isTypeSupported(m)) {
+                return m;
+            }
+        }
+        return '';
+    };
+
+    const stopStream = () => {
+        if (stream) {
+            stream.getTracks().forEach(t => t.stop());
+            stream = null;
+        }
+    };
+
+    let _micTipTimer = null;
+    const flashError = (msg) => {
+        console.warn('[mic]', msg);
+        // Pop a small bubble above the mic so the user actually notices it.
+        // The mic lives inside a relatively-positioned wrapper around the
+        // textarea (see chat.html), so we hang the tip off that wrapper.
+        const wrapper = micBtn.parentElement;
+        if (!wrapper) return;
+        let tip = wrapper.querySelector('.mic-tip');
+        if (!tip) {
+            tip = document.createElement('div');
+            tip.className = 'mic-tip absolute right-1 bottom-full mb-2 px-2 py-1 rounded-md '
+                + 'text-xs text-white bg-slate-800/90 dark:bg-slate-700/90 shadow-md '
+                + 'pointer-events-none whitespace-nowrap z-10';
+            wrapper.appendChild(tip);
+        }
+        tip.textContent = msg;
+        tip.style.opacity = '1';
+        if (_micTipTimer) clearTimeout(_micTipTimer);
+        _micTipTimer = setTimeout(() => {
+            tip.style.opacity = '0';
+            tip.style.transition = 'opacity 200ms';
+            setTimeout(() => tip.remove(), 250);
+        }, 2000);
+    };
+
+    const upload = async (blob, ext) => {
+        setBusy();
+        const fd = new FormData();
+        fd.append('file', blob, `recording.${ext}`);
+        try {
+            const resp = await fetch('/api/voice/asr', { method: 'POST', body: fd });
+            const data = await resp.json();
+            if (data.status === 'success' && data.text) {
+                // Voice-message UX: drop the recording into the conversation
+                // as a playable bubble with the caption underneath, then
+                // dispatch the recognised text through the regular send path.
+                sendVoiceMessage(data.text, data.audio_url);
+            } else {
+                flashError(data.message || t('mic_error'));
+            }
+        } catch (e) {
+            flashError(t('mic_error') + ': ' + e.message);
+        } finally {
+            setIdle();
+        }
+    };
+
+    const start = async () => {
+        try {
+            stream = await navigator.mediaDevices.getUserMedia({ audio: true });
+        } catch (e) {
+            flashError(t('mic_permission_denied'));
+            return;
+        }
+        chunks = [];
+        const mimeType = pickMimeType();
+        try {
+            mediaRecorder = mimeType
+                ? new MediaRecorder(stream, { mimeType })
+                : new MediaRecorder(stream);
+        } catch (e) {
+            stopStream();
+            flashError(t('mic_error') + ': ' + e.message);
+            return;
+        }
+        mediaRecorder.ondataavailable = (ev) => {
+            if (ev.data && ev.data.size > 0) chunks.push(ev.data);
+        };
+        mediaRecorder.onstop = () => {
+            stopStream();
+            const blob = new Blob(chunks, { type: mediaRecorder.mimeType || 'audio/webm' });
+            // Map mime -> extension so the server picks the right file suffix.
+            const mt = (mediaRecorder.mimeType || 'audio/webm').split(';')[0];
+            const extMap = {
+                'audio/webm': 'webm', 'audio/ogg': 'ogg',
+                'audio/mp4': 'm4a',   'audio/mpeg': 'mp3',
+            };
+            const ext = extMap[mt] || 'webm';
+            // 256 bytes ~ container header only, no actual audio. Anything
+            // below that we treat as "tapped by mistake".
+            if (blob.size < 256) {
+                setIdle();
+                flashError(t('mic_too_short'));
+                return;
+            }
+            upload(blob, ext);
+        };
+        // timeslice=250ms: force the recorder to flush a chunk every 250ms.
+        // Without it some browsers wait for stop() before producing any data,
+        // which loses the audio on very short taps.
+        mediaRecorder.start(250);
+        recordStartedAt = Date.now();
+        setRecording();
+    };
+
+    let recordStartedAt = 0;
+
+    const stopWithMinDuration = () => {
+        const elapsed = Date.now() - recordStartedAt;
+        const minMs = 350;
+        if (elapsed < minMs) {
+            // Give the recorder a moment to capture at least one chunk
+            // before we tell it to stop.
+            setTimeout(() => stop(), minMs - elapsed);
+        } else {
+            stop();
+        }
+    };
+
+    const stop = () => {
+        if (mediaRecorder && mediaRecorder.state !== 'inactive') {
+            mediaRecorder.stop();
+        }
+    };
+
+    micBtn.addEventListener('click', () => {
+        if (recording) {
+            stopWithMinDuration();
+        } else {
+            start();
+        }
+    });
+
+    setIdle();
+})();
+
+// Smart auto-scroll: pause when user scrolls up, resume when near bottom
+let _autoScrollEnabled = true;
+const _SCROLL_THRESHOLD = 80; // px from bottom to re-enable auto-scroll
+
+messagesDiv.addEventListener('scroll', () => {
+    const distFromBottom = messagesDiv.scrollHeight - messagesDiv.scrollTop - messagesDiv.clientHeight;
+    _autoScrollEnabled = distFromBottom <= _SCROLL_THRESHOLD;
+    _updateScrollToBottomBtn();
+});
+
+// Intercept internal navigation links in chat messages
+messagesDiv.addEventListener('click', (e) => {
+    // Code block copy button
+    const codeCopyBtn = e.target.closest('.code-copy-btn');
+    if (codeCopyBtn) {
+        e.preventDefault();
+        const wrapper = codeCopyBtn.closest('.code-block-wrapper');
+        const codeEl = wrapper && wrapper.querySelector('pre code');
+        if (codeEl) {
+            const codeText = codeEl.textContent;
+            copyToClipboard(codeText).then(() => {
+                const icon = codeCopyBtn.querySelector('i');
+                if (icon) { icon.className = 'fas fa-check'; setTimeout(() => { icon.className = 'fas fa-copy'; }, 1500); }
+            });
+        }
+        return;
+    }
+
+    const copyBtn = e.target.closest('.copy-msg-btn');
+    if (copyBtn) {
+        e.preventDefault();
+        const msgRoot = copyBtn.closest('.flex.gap-3');
+        const answerEl = msgRoot && msgRoot.querySelector('.answer-content');
+        const rawMd = answerEl && answerEl.dataset.rawMd;
+        if (rawMd) {
+            copyToClipboard(rawMd).then(() => {
+                const icon = copyBtn.querySelector('i');
+                if (icon) { icon.className = 'fas fa-check'; setTimeout(() => { icon.className = 'fas fa-copy'; }, 1500); }
+            });
+        }
+        return;
+    }
+
+    // Edit user message
+    const editBtn = e.target.closest('.edit-msg-btn');
+    if (editBtn) {
+        e.preventDefault();
+        if (isCurrentSessionConversationActive()) return;
+        const msgRoot = editBtn.closest('.user-message-group');
+        if (msgRoot) editUserMessage(msgRoot);
+        return;
+    }
+
+    // Regenerate bot response
+    const regenerateBtn = e.target.closest('.regenerate-msg-btn');
+    if (regenerateBtn) {
+        e.preventDefault();
+        const botMsgRoot = regenerateBtn.closest('.flex.gap-3');
+        if (botMsgRoot) regenerateResponse(botMsgRoot);
+        return;
+    }
+
+    // Delete message (user bubble only; bot bubbles intentionally lack a
+    // delete button — removing only the bot reply would leave an orphan
+    // user message that breaks LLM context alternation).
+    const deleteBtn = e.target.closest('.delete-msg-btn');
+    if (deleteBtn) {
+        e.preventDefault();
+        if (isCurrentSessionConversationActive()) return;
+        const userMsgEl = deleteBtn.closest('.user-message-group');
+        if (!userMsgEl) return;
+
+        showConfirmModal(t('delete_message_title'), t('delete_message_confirm'), () => {
+            // Find the next bot reply for this turn (skip non-message nodes).
+            let botReplyEl = null;
+            let sibling = userMsgEl.nextElementSibling;
+            while (sibling) {
+                if (sibling.classList && sibling.classList.contains('bot-message-group')) {
+                    botReplyEl = sibling;
+                    break;
+                }
+                sibling = sibling.nextElementSibling;
+            }
+            userMsgEl.remove();
+            if (botReplyEl) botReplyEl.remove();
+
+            const userSeq = userMsgEl.dataset.seq;
+            if (userSeq) {
+                fetch('/api/messages/delete', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ session_id: sessionId, user_seq: parseInt(userSeq) })
+                }).then(r => r.json()).then(data => {
+                    if (data.status === 'success') console.log(`Deleted ${data.deleted} messages`);
+                }).catch(err => console.error('Failed to delete:', err));
+            }
+        });
+        return;
+    }
+
+    const a = e.target.closest('a');
+    if (!a) return;
+    const href = a.getAttribute('href') || '';
+    if (href === '/memory/dreams') {
+        e.preventDefault();
+        navigateTo('memory');
+        setTimeout(() => switchMemoryTab('dreams'), 50);
+    } else if (href === '/memory/MEMORY.md') {
+        e.preventDefault();
+        navigateTo('memory');
+        setTimeout(() => { switchMemoryTab('files'); openMemoryFile('MEMORY.md', 'memory'); }, 50);
+    }
+});
+const attachmentPreview = document.getElementById('attachment-preview');
+
+// Pending attachments: [{file_path, file_name, file_type, preview_url}]
+// Items with _uploading=true are still in flight.
+let pendingAttachments = [];
+let uploadingCount = 0;
+
+// Input history (like terminal arrow-key recall)
+const inputHistory = [];
+let historyIdx = -1;
+let historySavedDraft = '';
+
+// While an SSE stream is in flight, the send button morphs into a cancel
+// button. Only one in-flight request is supported at a time.
+let activeRequestId = null;
+let sendBtnMode = 'send'; // 'send' | 'cancel'
+
+function setSendBtnCancelMode(requestId) {
+    activeRequestId = requestId;
+    sendBtnMode = 'cancel';
+    sendBtn.disabled = false;
+    sendBtn.classList.add('send-btn-cancel');
+    sendBtn.title = (currentLang === 'zh' ? '中止' : 'Cancel');
+    sendBtn.innerHTML = '<i class="fas fa-stop text-sm"></i>';
+}
+
+function resetSendBtnSendMode() {
+    activeRequestId = null;
+    sendBtnMode = 'send';
+    sendBtn.classList.remove('send-btn-cancel');
+    sendBtn.title = '';
+    sendBtn.innerHTML = '<i class="fas fa-paper-plane text-sm"></i>';
+    updateSendBtnState();
+}
+
+function requestCancel() {
+    const reqId = activeRequestId;
+    if (!reqId) return;
+    fetch('/cancel', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ request_id: reqId, session_id: sessionId, lang: currentLang }),
+    }).catch(err => {
+        console.warn('[cancel] request failed', err);
+    });
+    // Optimistic UI lock so the click visibly registers before the SSE
+    // "cancelled" event arrives.
+    sendBtn.disabled = true;
+    sendBtn.title = (currentLang === 'zh' ? '已中止' : 'Cancelled');
+}
+
+// Button click is the only path to Cancel. Pressing Enter still calls
+// sendMessage() so users can submit "/cancel" as a regular slash command.
+sendBtn.addEventListener('click', () => {
+    if (sendBtnMode === 'cancel') {
+        requestCancel();
+    } else {
+        sendMessage();
+    }
+});
+
+function updateSendBtnState() {
+    if (sendBtnMode === 'cancel') {
+        // Self-heal a stuck Cancel button: if there's no live stream backing
+        // the current request, the cancel state leaked (e.g. a stream ended
+        // without resetting). Recover to Send so the input isn't blocked.
+        if (!activeRequestId || !activeStreams[activeRequestId]) {
+            resetSendBtnSendMode();
+        } else {
+            // Don't downgrade a genuinely active Cancel button on input edits.
+            return;
+        }
+    }
+    sendBtn.disabled = uploadingCount > 0 || (!chatInput.value.trim() && pendingAttachments.length === 0);
+}
+
+function renderAttachmentPreview() {
+    if (pendingAttachments.length === 0) {
+        attachmentPreview.classList.add('hidden');
+        attachmentPreview.innerHTML = '';
+        updateSendBtnState();
+        return;
+    }
+    attachmentPreview.classList.remove('hidden');
+    attachmentPreview.innerHTML = pendingAttachments.map((att, idx) => {
+        if (att._uploading) {
+            const suffix = att.file_type === 'directory' && att.file_count
+                ? ` (${att.file_count})`
+                : '';
+            return `<div class="att-chip att-uploading" data-idx="${idx}">
+                <i class="fas fa-spinner fa-spin"></i>
+                <span class="att-name">${escapeHtml(att.file_name)}${suffix}</span>
+            </div>`;
+        }
+        if (att.file_type === 'image') {
+            return `<div class="att-thumb" data-idx="${idx}">
+                <img src="${att.preview_url}" alt="${escapeHtml(att.file_name)}">
+                <button class="att-remove" onclick="removeAttachment(${idx})">&times;</button>
+            </div>`;
+        }
+        const icon = att.file_type === 'video'
+            ? 'fa-film'
+            : (att.file_type === 'directory' ? 'fa-folder-tree' : 'fa-file-alt');
+        const suffix = att.file_type === 'directory' && att.file_count
+            ? ` (${att.file_count})`
+            : '';
+        return `<div class="att-chip" data-idx="${idx}">
+            <i class="fas ${icon}"></i>
+            <span class="att-name">${escapeHtml(att.file_name)}${suffix}</span>
+            <button class="att-remove" onclick="removeAttachment(${idx})">&times;</button>
+        </div>`;
+    }).join('');
+    updateSendBtnState();
+}
+
+function removeAttachment(idx) {
+    if (pendingAttachments[idx]?._uploading) return;
+    pendingAttachments.splice(idx, 1);
+    renderAttachmentPreview();
+}
+
+function isAttachMenuVisible() {
+    return attachMenu && !attachMenu.classList.contains('hidden');
+}
+
+function hideAttachMenu() {
+    if (attachMenu) attachMenu.classList.add('hidden');
+}
+
+function toggleAttachMenu(event) {
+    if (!attachMenu) return;
+    if (event) {
+        event.preventDefault();
+        event.stopPropagation();
+    }
+    attachMenu.classList.toggle('hidden');
+}
+
+function triggerFileUpload() {
+    hideAttachMenu();
+    fileInput?.click();
+}
+
+function triggerFolderUpload() {
+    if (!supportsDirectoryUpload) return;
+    hideAttachMenu();
+    folderInput?.click();
+}
+
+async function handleFileSelect(files) {
+    if (!files || files.length === 0) return;
+    const tasks = [];
+    for (const file of files) {
+        const placeholder = { file_name: file.name, file_type: 'file', _uploading: true };
+        pendingAttachments.push(placeholder);
+        uploadingCount++;
+        renderAttachmentPreview();
+
+        tasks.push((async () => {
+            const formData = new FormData();
+            formData.append('file', file);
+            formData.append('session_id', sessionId);
+            try {
+                const resp = await fetch('/upload', { method: 'POST', body: formData });
+                const data = await resp.json();
+                if (data.status === 'success') {
+                    placeholder.file_path = data.file_path;
+                    placeholder.file_name = data.file_name;
+                    placeholder.file_type = data.file_type;
+                    placeholder.preview_url = data.preview_url;
+                    delete placeholder._uploading;
+                } else {
+                    const i = pendingAttachments.indexOf(placeholder);
+                    if (i !== -1) pendingAttachments.splice(i, 1);
+                }
+            } catch (e) {
+                console.error('Upload failed:', e);
+                const i = pendingAttachments.indexOf(placeholder);
+                if (i !== -1) pendingAttachments.splice(i, 1);
+            }
+            uploadingCount--;
+            renderAttachmentPreview();
+        })());
+    }
+    await Promise.all(tasks);
+}
+
+function _makeUploadId() {
+    return `dir_${Date.now()}_${Math.random().toString(36).slice(2, 10)}`;
+}
+
+function _groupDirectoryFiles(files) {
+    const groups = new Map();
+    for (const file of Array.from(files || [])) {
+        const relPath = file.webkitRelativePath || file.name;
+        const parts = relPath.split('/').filter(Boolean);
+        const rootName = parts[0] || file.name;
+        if (!groups.has(rootName)) groups.set(rootName, []);
+        groups.get(rootName).push({ file, relPath });
+    }
+    return groups;
+}
+
+async function handleFolderSelect(files) {
+    if (!files || files.length === 0) return;
+    const groups = _groupDirectoryFiles(files);
+    const groupTasks = [];
+
+    for (const [rootName, entries] of groups.entries()) {
+        const placeholder = {
+            file_name: rootName,
+            file_type: 'directory',
+            file_count: entries.length,
+            _uploading: true,
+        };
+        pendingAttachments.push(placeholder);
+        uploadingCount++;
+        renderAttachmentPreview();
+
+        const uploadId = _makeUploadId();
+        groupTasks.push((async () => {
+            try {
+                const formData = new FormData();
+                formData.append('session_id', sessionId);
+                formData.append('upload_id', uploadId);
+                for (const { file, relPath } of entries) {
+                    formData.append('files', file);
+                    formData.append('relative_paths', relPath);
+                }
+
+                const resp = await fetch('/upload', { method: 'POST', body: formData });
+                const data = await resp.json();
+                if (data.status !== 'success') {
+                    throw new Error(data.message || 'Upload failed');
+                }
+                if (!data.root_path) {
+                    throw new Error('Directory root path missing');
+                }
+                placeholder.file_path = data.root_path;
+                placeholder.file_name = data.root_name || rootName;
+                delete placeholder._uploading;
+            } catch (e) {
+                console.error('Directory upload failed:', e);
+                const i = pendingAttachments.indexOf(placeholder);
+                if (i !== -1) pendingAttachments.splice(i, 1);
+            } finally {
+                uploadingCount--;
+            }
+            renderAttachmentPreview();
+        })());
+    }
+
+    await Promise.all(groupTasks);
+}
+
+fileInput.addEventListener('change', function() {
+    handleFileSelect(this.files);
+    this.value = '';
+});
+
+folderInput.addEventListener('change', function() {
+    handleFolderSelect(this.files);
+    this.value = '';
+});
+
+document.addEventListener('click', (e) => {
+    if (!isAttachMenuVisible()) return;
+    if (attachMenu.contains(e.target) || attachBtn.contains(e.target)) return;
+    hideAttachMenu();
+});
+
+// Drag-and-drop support on entire chat view
+const chatView = document.getElementById('view-chat');
+const chatInputArea = chatInput.closest('.flex-shrink-0');
+
+// Create drag overlay for visual feedback
+let dragOverlay = document.getElementById('drag-overlay');
+if (!dragOverlay) {
+    dragOverlay = document.createElement('div');
+    dragOverlay.id = 'drag-overlay';
+    dragOverlay.className = 'drag-overlay hidden';
+    dragOverlay.innerHTML = `
+        <div class="drag-overlay-content">
+            <i class="fas fa-cloud-arrow-up"></i>
+            <p>Drop files here to upload</p>
+        </div>
+    `;
+    chatView.appendChild(dragOverlay);
+}
+
+let dragCounter = 0;
+
+function showDragOverlay() {
+    dragOverlay.classList.remove('hidden');
+    dragOverlay.classList.add('active');
+}
+
+function hideDragOverlay() {
+    dragOverlay.classList.remove('active');
+    dragOverlay.classList.add('hidden');
+}
+
+chatView.addEventListener('dragenter', (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    dragCounter++;
+    if (e.dataTransfer.types.includes('Files')) {
+        showDragOverlay();
+    }
+});
+
+chatView.addEventListener('dragover', (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    chatInputArea.classList.add('drag-over');
+});
+
+chatView.addEventListener('dragleave', (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    dragCounter--;
+    if (dragCounter === 0) {
+        hideDragOverlay();
+        chatInputArea.classList.remove('drag-over');
+    }
+});
+
+chatView.addEventListener('drop', (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    dragCounter = 0;
+    hideDragOverlay();
+    chatInputArea.classList.remove('drag-over');
+    if (e.dataTransfer.files.length) {
+        handleFileSelect(e.dataTransfer.files);
+    }
+});
+
+document.body.addEventListener('dragover', (e) => {
+    if (e.dataTransfer.types.includes('Files')) {
+        e.preventDefault();
+    }
+});
+
+document.body.addEventListener('drop', (e) => {
+    if (e.dataTransfer.types.includes('Files')) {
+        e.preventDefault();
+    }
+});
+
+// Paste image support
+chatInput.addEventListener('paste', (e) => {
+    const items = e.clipboardData?.items;
+    if (!items) return;
+    const files = [];
+    for (const item of items) {
+        if (item.kind === 'file') {
+            files.push(item.getAsFile());
+        }
+    }
+    if (files.length) {
+        e.preventDefault();
+        handleFileSelect(files);
+    }
+});
+
+chatInput.addEventListener('compositionstart', () => { isComposing = true; });
+chatInput.addEventListener('compositionend', () => { setTimeout(() => { isComposing = false; }, 100); });
+
+// ── Slash Command Menu ───────────────────────────────────────
+// desc holds an i18n key, resolved via t() at render time so the menu follows
+// the current UI language.
+const SLASH_COMMANDS = [
+    { cmd: '/help',                desc: 'slash_help' },
+    { cmd: '/status',              desc: 'slash_status' },
+    { cmd: '/context',             desc: 'slash_context' },
+    { cmd: '/context clear',       desc: 'slash_context_clear' },
+    { cmd: '/skill list',          desc: 'slash_skill_list' },
+    { cmd: '/skill list --remote', desc: 'slash_skill_list_remote' },
+    { cmd: '/skill search ',       desc: 'slash_skill_search' },
+    { cmd: '/skill install ',      desc: 'slash_skill_install' },
+    { cmd: '/skill uninstall ',    desc: 'slash_skill_uninstall' },
+    { cmd: '/skill info ',         desc: 'slash_skill_info' },
+    { cmd: '/skill enable ',       desc: 'slash_skill_enable' },
+    { cmd: '/skill disable ',      desc: 'slash_skill_disable' },
+    { cmd: '/memory dream ',       desc: 'slash_memory_dream' },
+    { cmd: '/knowledge',           desc: 'slash_knowledge' },
+    { cmd: '/knowledge list',      desc: 'slash_knowledge_list' },
+    { cmd: '/knowledge on',        desc: 'slash_knowledge_on' },
+    { cmd: '/knowledge off',       desc: 'slash_knowledge_off' },
+    { cmd: '/config',              desc: 'slash_config' },
+    { cmd: '/cancel',              desc: 'slash_cancel' },
+    { cmd: '/logs',                desc: 'slash_logs' },
+    { cmd: '/version',             desc: 'slash_version' },
+];
+
+const slashMenu = document.getElementById('slash-menu');
+let slashActiveIdx = 0;
+let slashFiltered = [];
+let slashJustSelected = false;
+let slashLastFilter = '';
+let slashLastMouseX = -1;
+let slashLastMouseY = -1;
+
+function showSlashMenu(filter) {
+    const q = filter.toLowerCase();
+    if (q === slashLastFilter && !slashMenu.classList.contains('hidden')) return;
+    slashLastFilter = q;
+
+    const newFiltered = SLASH_COMMANDS.filter(c => c.cmd.toLowerCase().startsWith(q));
+    if (newFiltered.length === 0) {
+        hideSlashMenu();
+        return;
+    }
+
+    const changed = newFiltered.length !== slashFiltered.length ||
+        newFiltered.some((c, i) => c.cmd !== slashFiltered[i]?.cmd);
+    slashFiltered = newFiltered;
+    if (changed) slashActiveIdx = 0;
+    slashActiveIdx = Math.min(slashActiveIdx, slashFiltered.length - 1);
+
+    slashNavByKeyboard = true;
+    renderSlashItems();
+    slashMenu.classList.remove('hidden');
+}
+
+function hideSlashMenu() {
+    slashMenu.classList.add('hidden');
+    slashMenu.innerHTML = '';
+    slashFiltered = [];
+    slashActiveIdx = -1;
+    slashLastFilter = '';
+    slashNavByKeyboard = false;
+    slashLastMouseX = -1;
+    slashLastMouseY = -1;
+}
+
+function isSlashMenuVisible() {
+    return !slashMenu.classList.contains('hidden') && slashFiltered.length > 0;
+}
+
+function renderSlashItems() {
+    slashMenu.innerHTML =
+        '<div class="slash-menu-header">Commands</div>' +
+        slashFiltered.map((c, i) =>
+            `<div class="slash-menu-item${i === slashActiveIdx ? ' active' : ''}" data-idx="${i}">` +
+            `<span class="cmd">${escapeHtml(c.cmd)}</span>` +
+            `<span class="desc">${escapeHtml(t(c.desc))}</span></div>`
+        ).join('');
+
+    const activeEl = slashMenu.querySelector('.slash-menu-item.active');
+    if (activeEl) activeEl.scrollIntoView({ block: 'nearest' });
+}
+
+// Delegated events on the persistent slashMenu container (not destroyed by innerHTML)
+// Use coordinate comparison to distinguish real mouse movement from DOM-rebuild phantom events.
+slashMenu.addEventListener('mousemove', (e) => {
+    if (e.clientX === slashLastMouseX && e.clientY === slashLastMouseY) return;
+    slashLastMouseX = e.clientX;
+    slashLastMouseY = e.clientY;
+    if (!slashNavByKeyboard) return;
+    slashNavByKeyboard = false;
+    const item = e.target.closest('.slash-menu-item');
+    if (!item) return;
+    const idx = parseInt(item.dataset.idx);
+    if (idx === slashActiveIdx) return;
+    slashActiveIdx = idx;
+    slashMenu.querySelectorAll('.slash-menu-item').forEach(el => {
+        el.classList.toggle('active', parseInt(el.dataset.idx) === idx);
+    });
+});
+
+slashMenu.addEventListener('mouseover', (e) => {
+    if (slashNavByKeyboard) return;
+    const item = e.target.closest('.slash-menu-item');
+    if (!item) return;
+    const idx = parseInt(item.dataset.idx);
+    if (idx === slashActiveIdx) return;
+    slashActiveIdx = idx;
+    slashMenu.querySelectorAll('.slash-menu-item').forEach(el => {
+        el.classList.toggle('active', parseInt(el.dataset.idx) === idx);
+    });
+});
+
+slashMenu.addEventListener('mousedown', (e) => {
+    const item = e.target.closest('.slash-menu-item');
+    if (!item) return;
+    e.preventDefault();
+    selectSlashCommand(parseInt(item.dataset.idx));
+});
+
+function selectSlashCommand(idx) {
+    if (idx < 0 || idx >= slashFiltered.length) return;
+    const chosen = slashFiltered[idx].cmd;
+    slashJustSelected = true;
+    chatInput.value = chosen;
+    chatInput.dispatchEvent(new Event('input'));
+    hideSlashMenu();
+    chatInput.focus();
+    chatInput.selectionStart = chatInput.selectionEnd = chosen.length;
+}
+
+chatInput.addEventListener('input', function() {
+    this.style.height = '42px';
+    const scrollH = this.scrollHeight;
+    const newH = Math.min(scrollH, 180);
+    this.style.height = newH + 'px';
+    this.style.overflowY = scrollH > 180 ? 'auto' : 'hidden';
+    updateSendBtnState();
+
+    const val = this.value;
+    if (slashJustSelected) {
+        slashJustSelected = false;
+    } else if (val.startsWith('/')) {
+        showSlashMenu(val);
+    } else {
+        hideSlashMenu();
+    }
+});
+
+chatInput.addEventListener('keydown', function(e) {
+    if (e.keyCode === 229 || e.isComposing || isComposing) return;
+
+    if (e.key === 'Escape' && isAttachMenuVisible()) {
+        hideAttachMenu();
+        return;
+    }
+
+    if (isSlashMenuVisible()) {
+        if (e.key === 'ArrowDown') {
+            e.preventDefault();
+            slashNavByKeyboard = true;
+            slashActiveIdx = Math.min(slashActiveIdx + 1, slashFiltered.length - 1);
+            renderSlashItems();
+            return;
+        }
+        if (e.key === 'ArrowUp') {
+            e.preventDefault();
+            slashNavByKeyboard = true;
+            slashActiveIdx = Math.max(slashActiveIdx - 1, 0);
+            renderSlashItems();
+            return;
+        }
+        if (e.key === 'Enter' && !e.shiftKey && !e.ctrlKey) {
+            e.preventDefault();
+            selectSlashCommand(slashActiveIdx);
+            return;
+        }
+        if (e.key === 'Escape') {
+            e.preventDefault();
+            hideSlashMenu();
+            return;
+        }
+        if (e.key === 'Tab') {
+            e.preventDefault();
+            selectSlashCommand(slashActiveIdx);
+            return;
+        }
+    }
+
+    // Arrow-key history recall (only when input is empty or already browsing history)
+    if (e.key === 'ArrowUp' && inputHistory.length > 0 && !isSlashMenuVisible()) {
+        const curVal = this.value.trim();
+        const isSingleLine = !this.value.includes('\n');
+        if (isSingleLine && (curVal === '' || historyIdx >= 0)) {
+            e.preventDefault();
+            if (historyIdx < 0) {
+                historySavedDraft = this.value;
+                historyIdx = inputHistory.length - 1;
+            } else if (historyIdx > 0) {
+                historyIdx--;
+            }
+            this.value = inputHistory[historyIdx];
+            slashJustSelected = true;
+            this.dispatchEvent(new Event('input'));
+            hideSlashMenu();
+            this.selectionStart = this.selectionEnd = this.value.length;
+            return;
+        }
+    }
+    if (e.key === 'ArrowDown' && historyIdx >= 0 && !isSlashMenuVisible()) {
+        const isSingleLine = !this.value.includes('\n');
+        if (isSingleLine) {
+            e.preventDefault();
+            if (historyIdx < inputHistory.length - 1) {
+                historyIdx++;
+                this.value = inputHistory[historyIdx];
+            } else {
+                historyIdx = -1;
+                this.value = historySavedDraft;
+                historySavedDraft = '';
+            }
+            slashJustSelected = true;
+            this.dispatchEvent(new Event('input'));
+            hideSlashMenu();
+            this.selectionStart = this.selectionEnd = this.value.length;
+            return;
+        }
+    }
+
+    if ((e.ctrlKey || e.shiftKey) && e.key === 'Enter') {
+        const start = this.selectionStart;
+        const end = this.selectionEnd;
+        this.value = this.value.substring(0, start) + '\n' + this.value.substring(end);
+        this.selectionStart = this.selectionEnd = start + 1;
+        this.dispatchEvent(new Event('input'));
+        e.preventDefault();
+    } else if (e.key === 'Enter' && !e.shiftKey && !e.ctrlKey) {
+        sendMessage();
+        e.preventDefault();
+    }
+});
+
+chatInput.addEventListener('blur', () => {
+    setTimeout(hideSlashMenu, 150);
+});
+
+document.querySelectorAll('.example-card').forEach(card => {
+    card.addEventListener('click', () => {
+        // data-send overrides the visible text (e.g. show "查看全部命令" but send "/help")
+        const sendText = card.dataset.send;
+        if (sendText) {
+            chatInput.value = sendText;
+            chatInput.dispatchEvent(new Event('input'));
+            chatInput.focus();
+            return;
+        }
+        const textEl = card.querySelector('[data-i18n*="text"]');
+        if (textEl) {
+            chatInput.value = textEl.textContent;
+            chatInput.dispatchEvent(new Event('input'));
+            chatInput.focus();
+        }
+    });
+});
+
+// Voice-message variant of sendMessage(): renders a playable audio bubble
+// with the ASR caption, then dispatches the recognised text to /message
+// through the same SSE/loading flow as a typed message.
+function sendVoiceMessage(text, audioUrl) {
+    text = (text || '').trim();
+    if (!text) return;
+
+    inputHistory.push(text);
+    historyIdx = -1;
+    historySavedDraft = '';
+
+    const ws = document.getElementById('welcome-screen');
+    const isFirstMessage = !!ws;
+    if (ws) ws.remove();
+
+    const titleInfo = isFirstMessage ? { sid: sessionId, userMsg: text } : null;
+    const timestamp = new Date();
+    addUserVoiceMessage(audioUrl, text, timestamp);
+    const loadingEl = addLoadingIndicator();
+
+    const body = {
+        session_id: sessionId,
+        message: text,
+        stream: true,
+        timestamp: timestamp.toISOString(),
+        is_voice: true,
+        lang: currentLang,
+    };
+
+    const MAX_RETRIES = 2;
+    const RETRY_DELAY_MS = 1000;
+    function postWithRetry(attempt) {
+        fetch('/message', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify(body)
+        })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status === 'success') {
+                if (data.inline_reply) {
+                    // Synchronous fast-path reply (e.g. /cancel); skip SSE.
+                    loadingEl.remove();
+                    addBotMessage(data.inline_reply, new Date());
+                } else if (data.stream) {
+                    setSendBtnCancelMode(data.request_id);
+                    startSSE(data.request_id, loadingEl, timestamp, titleInfo);
+                } else {
+                    loadingContainers[data.request_id] = loadingEl;
+                }
+            } else {
+                loadingEl.remove();
+                addBotMessage(t('error_send'), new Date());
+                resetSendBtnSendMode();
+            }
+        })
+        .catch(err => {
+            if (attempt < MAX_RETRIES) {
+                setTimeout(() => postWithRetry(attempt + 1), RETRY_DELAY_MS * (attempt + 1));
+                return;
+            }
+            loadingEl.remove();
+            addBotMessage(t('error_send'), new Date());
+        });
+    }
+    postWithRetry(0);
+}
+
+function addUserVoiceMessage(audioUrl, caption, timestamp) {
+    const el = document.createElement('div');
+    el.className = 'flex justify-end px-4 sm:px-6 py-3';
+    // Voice-message bubble: compact voice pill on top, ASR caption beneath.
+    // The bubble keeps the same primary tint as a normal user message so
+    // it visually slots into the conversation flow.
+    el.innerHTML = `
+        <div class="max-w-[75%] sm:max-w-[60%]">
+            <div class="bg-slate-100 dark:bg-white/10 text-slate-700 dark:text-slate-200 rounded-2xl px-3 py-2 msg-content user-bubble">
+                <div class="user-voice-slot"></div>
+                ${caption ? `<div class="text-xs mt-1.5 leading-snug text-slate-500 dark:text-slate-400 whitespace-pre-wrap break-words">${escapeHtml(caption)}</div>` : ''}
+            </div>
+            <div class="text-xs text-slate-400 dark:text-slate-500 mt-1.5 text-right">${formatTime(timestamp)}</div>
+        </div>
+    `;
+    el.querySelector('.user-voice-slot').appendChild(renderVoicePill(audioUrl));
+    messagesDiv.appendChild(el);
+    _autoScrollEnabled = true;
+    scrollChatToBottom(true);
+}
+
+// Clipboard helper with fallback for non-HTTPS environments
+function copyToClipboard(text) {
+    if (navigator.clipboard && window.isSecureContext) {
+        return navigator.clipboard.writeText(text);
+    }
+    // Fallback for HTTP environments
+    return new Promise((resolve, reject) => {
+        const textArea = document.createElement('textarea');
+        textArea.value = text;
+        textArea.style.position = 'fixed';
+        textArea.style.left = '-999999px';
+        textArea.style.top = '-999999px';
+        document.body.appendChild(textArea);
+        textArea.focus();
+        textArea.select();
+        try {
+            document.execCommand('copy') ? resolve() : reject(new Error('Copy failed'));
+        } catch (err) {
+            reject(err);
+        } finally {
+            textArea.remove();
+        }
+    });
+}
+
+// Edit user message: extract content, remove this and subsequent messages, fill input
+async function editUserMessage(msgEl) {
+    if (isCurrentSessionConversationActive()) return;
+    const rawContent = msgEl.dataset.rawContent;
+    if (!rawContent) return;
+
+    // Delete this message and ALL subsequent messages from database (cascade)
+    // Must await to ensure delete completes before user sends a new message
+    const userSeq = msgEl.dataset.seq;
+    if (userSeq) {
+        try {
+            const resp = await fetch('/api/messages/delete', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ 
+                    session_id: sessionId, 
+                    user_seq: parseInt(userSeq),
+                    delete_user: true,
+                    cascade: true
+                })
+            });
+            const data = await resp.json();
+            if (data.status === 'success') console.log(`Deleted ${data.deleted} old messages`);
+        } catch (err) {
+            console.error('Failed to delete old messages:', err);
+        }
+    }
+
+    // Remove this message bubble and every later bubble that belongs to
+    // this or a subsequent turn. We mirror the backend cascade contract:
+    // anything with a data-seq >= current seq, plus any live SSE bubble
+    // that is still being streamed (no seq yet) after this point.
+    const currentSeqNum = userSeq ? parseInt(userSeq) : null;
+    const messagesToRemove = [];
+    let current = msgEl;
+    while (current) {
+        if (current.classList && (current.classList.contains('user-message-group') || current.classList.contains('bot-message-group'))) {
+            const seqAttr = current.dataset.seq;
+            if (seqAttr === undefined || seqAttr === '') {
+                // Live message without a persisted seq yet — treat as later.
+                messagesToRemove.push(current);
+            } else if (currentSeqNum === null || parseInt(seqAttr) >= currentSeqNum) {
+                messagesToRemove.push(current);
+            }
+        }
+        current = current.nextElementSibling;
+    }
+    messagesToRemove.forEach(el => {
+        if (el && el.parentNode) el.parentNode.removeChild(el);
+    });
+
+    // Fill input with the original content
+    chatInput.value = rawContent;
+    chatInput.dispatchEvent(new Event("input", { bubbles: true }));
+    chatInput.focus();
+    chatInput.selectionStart = chatInput.selectionEnd = chatInput.value.length;
+    scrollChatToBottom();
+}
+
+// Regenerate bot response: find the preceding user message and resend it
+async function regenerateResponse(botMsgEl) {
+    let prevEl = botMsgEl.previousElementSibling;
+    while (prevEl && !prevEl.classList.contains('user-message-group')) {
+        prevEl = prevEl.previousElementSibling;
+    }
+
+    if (!prevEl) {
+        console.warn('No preceding user message found');
+        return;
+    }
+
+    const userContent = prevEl.dataset.rawContent;
+    if (!userContent) {
+        console.warn('No content in preceding user message');
+        return;
+    }
+
+    // Delete both the old user message AND bot reply from database
+    // (because /message will create a fresh user message + new bot reply)
+    // Must await to ensure delete completes before /message is sent
+    const userSeq = prevEl.dataset.seq;
+    if (userSeq) {
+        try {
+            const resp = await fetch('/api/messages/delete', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ 
+                    session_id: sessionId, 
+                    user_seq: parseInt(userSeq),
+                    delete_user: true
+                })
+            });
+            const data = await resp.json();
+            if (data.status === 'success') console.log(`Deleted ${data.deleted} old messages`);
+        } catch (err) {
+            console.error('Failed to delete old messages:', err);
+        }
+    }
+
+    // Remove both the old user message and bot message from DOM
+    if (prevEl.parentNode) prevEl.parentNode.removeChild(prevEl);
+    if (botMsgEl.parentNode) botMsgEl.parentNode.removeChild(botMsgEl);
+
+    // Re-add the user message to DOM (so it appears before the loading indicator)
+    addUserMessage(userContent, new Date());
+
+    // Show loading indicator
+    const loadingEl = addLoadingIndicator();
+
+    // Resend the message
+    const timestamp = new Date();
+    const body = { session_id: sessionId, message: userContent, stream: true, timestamp: timestamp.toISOString(), lang: currentLang };
+
+    const MAX_RETRIES = 2;
+    const RETRY_DELAY_MS = 1000;
+
+    function postWithRetry(attempt) {
+        fetch('/message', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify(body)
+        })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status === 'success') {
+                if (data.inline_reply) {
+                    loadingEl.remove();
+                    addBotMessage(data.inline_reply, new Date());
+                } else if (data.stream) {
+                    setSendBtnCancelMode(data.request_id);
+                    startSSE(data.request_id, loadingEl, timestamp, null);
+                } else {
+                    loadingContainers[data.request_id] = loadingEl;
+                }
+            } else {
+                loadingEl.remove();
+                addBotMessage(t('error_send'), new Date());
+                resetSendBtnSendMode();
+            }
+        })
+        .catch(err => {
+            if (err.name === 'AbortError') {
+                loadingEl.remove();
+                addBotMessage(t('error_timeout'), new Date());
+                resetSendBtnSendMode();
+                return;
+            }
+            if (attempt < MAX_RETRIES) {
+                console.warn(`[regenerateResponse] attempt ${attempt + 1} failed, retrying...`, err);
+                setTimeout(() => postWithRetry(attempt + 1), RETRY_DELAY_MS * (attempt + 1));
+                return;
+            }
+            loadingEl.remove();
+            addBotMessage(t('error_send'), new Date());
+            resetSendBtnSendMode();
+        });
+    }
+
+    postWithRetry(0);
+}
+
+function sendMessage() {
+    // Do NOT branch on sendBtnMode here: Enter should always send (so
+    // typing "/cancel" submits normally). Cancel is wired only to the
+    // send button's pointer click — see send-btn listener above.
+
+    const text = chatInput.value.trim();
+    if (!text && pendingAttachments.length === 0) return;
+
+    if (text) {
+        inputHistory.push(text);
+        historyIdx = -1;
+        historySavedDraft = '';
+    }
+
+    const ws = document.getElementById('welcome-screen');
+    const isFirstMessage = !!ws;
+    if (ws) ws.remove();
+
+    const titleInfo = (isFirstMessage && text) ? { sid: sessionId, userMsg: text } : null;
+
+    const timestamp = new Date();
+    const attachments = [...pendingAttachments];
+    addUserMessage(text, timestamp, attachments);
+
+    const loadingEl = addLoadingIndicator();
+
+    chatInput.value = '';
+    chatInput.style.height = '42px';
+    chatInput.style.overflowY = 'hidden';
+    pendingAttachments = [];
+    renderAttachmentPreview();
+    sendBtn.disabled = true;
+
+    const body = { session_id: sessionId, message: text, stream: true, timestamp: timestamp.toISOString(), lang: currentLang };
+    if (attachments.length > 0) {
+        body.attachments = attachments.map(a => ({
+            file_path: a.file_path,
+            file_name: a.file_name,
+            file_type: a.file_type,
+            file_count: a.file_count,
+        }));
+    }
+
+    const MAX_RETRIES = 2;
+    const RETRY_DELAY_MS = 1000;
+
+    function postWithRetry(attempt) {
+        fetch('/message', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify(body)
+        })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status === 'success') {
+                if (data.inline_reply) {
+                    // Channel handled synchronously (e.g. /cancel fast-path);
+                    // render as a bot bubble and skip SSE entirely.
+                    loadingEl.remove();
+                    addBotMessage(data.inline_reply, new Date());
+                } else if (data.stream) {
+                    setSendBtnCancelMode(data.request_id);
+                    startSSE(data.request_id, loadingEl, timestamp, titleInfo);
+                } else {
+                    loadingContainers[data.request_id] = loadingEl;
+                }
+            } else {
+                loadingEl.remove();
+                addBotMessage(t('error_send'), new Date());
+                resetSendBtnSendMode();
+            }
+        })
+        .catch(err => {
+            if (err.name === 'AbortError') {
+                loadingEl.remove();
+                addBotMessage(t('error_timeout'), new Date());
+                resetSendBtnSendMode();
+                return;
+            }
+            if (attempt < MAX_RETRIES) {
+                console.warn(`[sendMessage] attempt ${attempt + 1} failed, retrying...`, err);
+                setTimeout(() => postWithRetry(attempt + 1), RETRY_DELAY_MS * (attempt + 1));
+                return;
+            }
+            loadingEl.remove();
+            addBotMessage(t('error_send'), new Date());
+            resetSendBtnSendMode();
+        });
+    }
+
+    postWithRetry(0);
+}
+
+function startSSE(requestId, loadingEl, timestamp, titleInfo, replayItems) {
+    let botEl = null;
+    let stepsEl = null;    // .agent-steps  (thinking summaries + tool indicators)
+    let contentEl = null;  // .answer-content (final streaming answer)
+    let mediaEl = null;    // .media-content (images & file attachments)
+    let accumulatedText = '';
+    const toolElements = new Map();
+    let currentReasoningEl = null;  // live reasoning bubble
+    let reasoningText = '';
+    let reasoningStartTime = 0;
+    let done = false;
+
+    // The session this stream belongs to. Sessions run in parallel: the user
+    // may switch to another session while this one is still streaming. The
+    // stream keeps running in the background (so the reply still completes and
+    // persists); when foreign it does not touch the view but still records
+    // every event into a buffer, so returning to the session can rebuild the
+    // bubble by replaying the buffer and then resume live rendering.
+    const ownerSession = sessionId;
+    const isActive = () => ownerSession === sessionId;
+    sessionActiveRequest[ownerSession] = requestId;
+    updateEditButtonsState();
+    // Per-request event buffer used to rebuild the bubble on re-attach.
+    const buffer = streamBuffers[requestId] || { items: [], timestamp };
+    streamBuffers[requestId] = buffer;
+    const clearOwnerRequest = () => {
+        if (sessionActiveRequest[ownerSession] === requestId) {
+            delete sessionActiveRequest[ownerSession];
+            updateEditButtonsState();
+        }
+        delete streamBuffers[requestId];
+    };
+
+    const MAX_RECONNECTS = 10;
+    const RECONNECT_BASE_MS = 1000;
+    let reconnectCount = 0;
+
+    function ensureBotEl() {
+        if (botEl) return;
+        if (loadingEl) { loadingEl.remove(); loadingEl = null; }
+        botEl = document.createElement('div');
+        botEl.className = 'flex gap-3 px-4 sm:px-6 py-3 bot-message-group';
+        botEl.dataset.requestId = requestId;
+        // Regenerate button starts hidden; it's revealed in the "done"
+        // event handler once seq metadata arrives from the backend.
+        botEl.innerHTML = `
+            <img src="assets/logo.jpg" alt="CowAgent" class="w-8 h-8 rounded-lg flex-shrink-0">
+            <div class="min-w-0 flex-1 max-w-[85%]">
+                <div class="bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-2xl px-4 py-3 text-sm leading-relaxed msg-content text-slate-700 dark:text-slate-200">
+                    <div class="agent-steps"></div>
+                    <div class="answer-content sse-streaming"></div>
+                    <div class="media-content"></div>
+                    <div class="bot-audio-slot"></div>
+                </div>
+                <div class="flex items-center gap-2 mt-1.5">
+                    <span class="text-xs text-slate-400 dark:text-slate-500">${formatTime(timestamp)}</span>
+                    <button class="copy-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-slate-500 dark:hover:text-slate-400 transition-colors cursor-pointer" title="${currentLang === 'zh' ? '复制' : 'Copy'}" style="display:none">
+                        <i class="fas fa-copy"></i>
+                    </button>
+                    <button class="speak-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-slate-500 dark:hover:text-slate-400 transition-colors cursor-pointer" title="${t('speak_msg')}" style="display:none;">
+                        <i class="fas fa-volume-up"></i>
+                    </button>
+                    <button class="regenerate-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-primary-400 dark:hover:text-primary-400 transition-colors cursor-pointer" title="${t('regenerate_response')}" style="display:none;">
+                        <i class="fas fa-rotate-right"></i>
+                    </button>
+                </div>
+            </div>
+        `;
+        messagesDiv.appendChild(botEl);
+        stepsEl = botEl.querySelector('.agent-steps');
+        contentEl = botEl.querySelector('.answer-content');
+        mediaEl = botEl.querySelector('.media-content');
+    }
+
+    // Holds the live EventSource so terminal events (done/voice_attach/error)
+    // can close it. During replay there is no live connection (null).
+    let currentEs = null;
+
+    // Render one SSE event into the bubble. Used by the live handler and by
+    // re-attach replay alike, so both paths produce identical UI.
+    function processSSEItem(item) {
+            if (item.type === 'reasoning') {
+                ensureBotEl();
+                reasoningText += item.content;
+                if (!currentReasoningEl) {
+                    reasoningStartTime = Date.now();
+                    currentReasoningEl = document.createElement('div');
+                    currentReasoningEl.className = 'agent-step agent-thinking-step';
+                    // During streaming, use a <pre> with a single text node and
+                    // append-only updates. This avoids re-parsing markdown and
+                    // re-setting innerHTML on every chunk, which is what causes
+                    // the page to crash on long chains-of-thought.
+                    currentReasoningEl.innerHTML = `
+                        <div class="thinking-header" onclick="this.parentElement.classList.toggle('expanded')">
+                            <i class="fas fa-lightbulb text-amber-400 flex-shrink-0"></i>
+                            <span class="thinking-summary">${t('thinking_in_progress')}</span>
+                            <i class="fas fa-chevron-right thinking-chevron"></i>
+                        </div>
+                        <div class="thinking-full"><pre class="thinking-stream-pre"></pre></div>`;
+                    stepsEl.appendChild(currentReasoningEl);
+                    const preEl = currentReasoningEl.querySelector('.thinking-stream-pre');
+                    preEl.appendChild(document.createTextNode(''));
+                    currentReasoningEl._streamTextNode = preEl.firstChild;
+                    currentReasoningEl._streamPendingText = '';
+                    currentReasoningEl._streamRafScheduled = false;
+                    currentReasoningEl._streamCharsRendered = 0;
+                    currentReasoningEl._streamCapped = false;
+                }
+                // Hard cap: once REASONING_RENDER_CAP chars are in the DOM, stop
+                // appending further deltas. The full text is still kept in
+                // `reasoningText` for finalize-time head+tail rendering.
+                if (!currentReasoningEl._streamCapped) {
+                    currentReasoningEl._streamPendingText += item.content;
+                    if (!currentReasoningEl._streamRafScheduled) {
+                        currentReasoningEl._streamRafScheduled = true;
+                        const elRef = currentReasoningEl;
+                        requestAnimationFrame(() => {
+                            elRef._streamRafScheduled = false;
+                            if (!elRef.isConnected || !elRef._streamTextNode) return;
+                            let pending = elRef._streamPendingText;
+                            elRef._streamPendingText = '';
+                            if (!pending) return;
+                            const remaining = REASONING_RENDER_CAP - elRef._streamCharsRendered;
+                            if (remaining <= 0) {
+                                elRef._streamCapped = true;
+                            } else {
+                                if (pending.length > remaining) {
+                                    pending = pending.slice(0, remaining);
+                                    elRef._streamCapped = true;
+                                }
+                                elRef._streamTextNode.appendData(pending);
+                                elRef._streamCharsRendered += pending.length;
+                                if (elRef._streamCapped) {
+                                    elRef._streamTextNode.appendData(
+                                        '\n\n... [reasoning truncated for display] ...'
+                                    );
+                                }
+                            }
+                            scrollChatToBottom();
+                        });
+                    }
+                }
+
+            } else if (item.type === 'delta') {
+                ensureBotEl();
+                if (currentReasoningEl) {
+                    finalizeThinking(currentReasoningEl, reasoningStartTime, reasoningText);
+                    currentReasoningEl = null;
+                    reasoningText = '';
+                }
+                accumulatedText += item.content;
+                contentEl.innerHTML = renderMarkdown(accumulatedText);
+                scrollChatToBottom();
+
+            } else if (item.type === 'message_end') {
+                if (item.has_tool_calls && accumulatedText.trim()) {
+                    ensureBotEl();
+                    const frozenEl = document.createElement('div');
+                    frozenEl.className = 'agent-step agent-content-step';
+                    frozenEl.innerHTML = `<div class="agent-content-body">${renderMarkdown(accumulatedText.trim())}</div>`;
+                    stepsEl.appendChild(frozenEl);
+                    accumulatedText = '';
+                    contentEl.innerHTML = '';
+                    scrollChatToBottom();
+                }
+
+            } else if (item.type === 'tool_start') {
+                ensureBotEl();
+                if (currentReasoningEl) {
+                    finalizeThinking(currentReasoningEl, reasoningStartTime, reasoningText);
+                    currentReasoningEl = null;
+                    reasoningText = '';
+                }
+                accumulatedText = '';
+                contentEl.innerHTML = '';
+
+                // Add tool execution indicator (collapsible)
+                const toolEl = document.createElement('div');
+                toolEl.className = 'agent-step agent-tool-step tool-streaming';
+                toolEl.dataset.progressReceived = 'false';
+                const argsStr = formatToolArgs(item.arguments || {});
+                toolEl.innerHTML = `
+                    <div class="tool-header" onclick="this.parentElement.classList.toggle('expanded')">
+                        <i class="fas fa-cog fa-spin text-primary-400 flex-shrink-0 tool-icon"></i>
+                        <span class="tool-name">${item.tool}</span>
+                        <i class="fas fa-chevron-right tool-chevron"></i>
+                    </div>
+                    <div class="tool-detail">
+                        <div class="tool-detail-section">
+                            <div class="tool-detail-label">Input</div>
+                            <pre class="tool-detail-content">${argsStr}</pre>
+                        </div>
+                        <div class="tool-detail-section tool-output-section">
+                            <div class="tool-detail-label tool-output-label">Output</div>
+                            <pre class="tool-detail-content tool-live-output"></pre>
+                        </div>
+                    </div>`;
+                stepsEl.appendChild(toolEl);
+                toolElements.set(item.tool_call_id, toolEl);
+
+                scrollChatToBottom();
+
+            } else if (item.type === 'tool_progress') {
+                const toolEl = toolElements.get(item.tool_call_id);
+                if (toolEl) {
+                    if (toolEl.dataset.progressReceived !== 'true') {
+                        toolEl.classList.add('expanded');
+                        toolEl.dataset.progressReceived = 'true';
+                    }
+                    toolEl.querySelector('.tool-live-output').textContent = String(item.content || '');
+                    scrollChatToBottom();
+                }
+
+            } else if (item.type === 'tool_end') {
+                const toolEl = toolElements.get(item.tool_call_id);
+                if (toolEl) {
+                    const isError = item.status !== 'success';
+                    const icon = toolEl.querySelector('.tool-icon');
+                    icon.className = isError
+                        ? 'fas fa-times text-red-400 flex-shrink-0 tool-icon'
+                        : 'fas fa-check text-primary-400 flex-shrink-0 tool-icon';
+
+                    // Show execution time
+                    const nameEl = toolEl.querySelector('.tool-name');
+                    if (item.execution_time !== undefined) {
+                        nameEl.innerHTML += ` <span class="tool-time">${item.execution_time}s</span>`;
+                    }
+
+                    // Fill output section
+                    const outputLabel = toolEl.querySelector('.tool-output-label');
+                    const outputEl = toolEl.querySelector('.tool-live-output');
+                    if (outputLabel) outputLabel.textContent = isError ? 'Error' : 'Output';
+                    if (outputEl) {
+                        outputEl.textContent = item.result ? String(item.result) : '';
+                        outputEl.classList.toggle('tool-error-text', isError);
+                    }
+
+                    toolEl.classList.remove('tool-streaming');
+                    toolEl.classList.remove('expanded');
+                    if (!item.result) {
+                        const outputSection = toolEl.querySelector('.tool-output-section');
+                        if (outputSection) outputSection.remove();
+                    }
+                    if (isError) toolEl.classList.add('tool-failed');
+                    toolElements.delete(item.tool_call_id);
+                }
+
+            } else if (item.type === 'image') {
+                ensureBotEl();
+                const imgEl = document.createElement('img');
+                imgEl.src = item.content;
+                imgEl.alt = 'screenshot';
+                imgEl.style.cssText = 'max-width:600px;border-radius:8px;margin:8px 0;cursor:zoom-in;box-shadow:0 1px 4px rgba(0,0,0,0.1);';
+                imgEl.onclick = () => _openImageLightbox(imgEl.src);
+                mediaEl.appendChild(imgEl);
+                scrollChatToBottom();
+
+            } else if (item.type === 'text') {
+                // Intermediate text sent before media items; display it but keep SSE open.
+                ensureBotEl();
+                contentEl.classList.remove('sse-streaming');
+                const textContent = item.content || accumulatedText;
+                if (textContent) contentEl.innerHTML = renderMarkdown(textContent);
+                applyHighlighting(botEl);
+                scrollChatToBottom();
+
+            } else if (item.type === 'video') {
+                ensureBotEl();
+                const wrapper = document.createElement('div');
+                wrapper.innerHTML = _buildVideoHtml(item.content);
+                mediaEl.appendChild(wrapper.firstElementChild || wrapper);
+                scrollChatToBottom();
+
+            } else if (item.type === 'file') {
+                ensureBotEl();
+                const fileName = item.file_name || item.content.split('/').pop();
+                const fileEl = document.createElement('a');
+                fileEl.href = item.content;
+                fileEl.download = fileName;
+                fileEl.target = '_blank';
+                fileEl.className = 'file-attachment';
+                fileEl.style.cssText = 'display:inline-flex;align-items:center;gap:6px;padding:8px 14px;margin:8px 0;border-radius:8px;background:var(--bg-secondary,#f3f4f6);color:var(--text-primary,#374151);text-decoration:none;font-size:14px;border:1px solid var(--border-color,#e5e7eb);';
+                fileEl.innerHTML = `<i class="fas fa-file-download" style="color:#6b7280;"></i> ${fileName}`;
+                mediaEl.appendChild(fileEl);
+                scrollChatToBottom();
+
+            } else if (item.type === 'phase') {
+                // Coarse progress (e.g. cow install-browser); must not close SSE (unlike "done")
+                ensureBotEl();
+                const wrap = document.createElement('div');
+                wrap.className = 'text-xs sm:text-sm text-slate-600 dark:text-slate-400 border-l-2 border-primary-400 pl-2 py-1 my-0.5';
+                wrap.textContent = String(item.content || '');
+                stepsEl.appendChild(wrap);
+                scrollChatToBottom();
+
+            } else if (item.type === 'cancelled') {
+                // Agent acknowledged the stop; mark the bubble. A trailing
+                // "done" still arrives with the partial answer.
+                ensureBotEl();
+                if (currentReasoningEl) {
+                    finalizeThinking(currentReasoningEl, reasoningStartTime, reasoningText);
+                    currentReasoningEl = null;
+                    reasoningText = '';
+                }
+                if (!botEl.querySelector('.agent-cancelled-tag')) {
+                    const tag = document.createElement('div');
+                    tag.className = 'agent-cancelled-tag text-xs text-amber-600 dark:text-amber-400 mt-1';
+                    tag.textContent = (currentLang === 'zh') ? '已中止' : 'Cancelled';
+                    stepsEl.appendChild(tag);
+                }
+                resetSendBtnSendMode();
+
+            } else if (item.type === 'done') {
+                // Don't close the stream yet: the backend keeps it open
+                // for a short tail to deliver async attachments such as
+                // TTS audio (`voice_attach`). It will close the stream on
+                // its own via onerror once the tail expires.
+                done = true;
+                clearOwnerRequest();
+                resetSendBtnSendMode();
+
+                const finalTextRaw = item.content || accumulatedText;
+                const finalText = localizeCancelMarker(finalTextRaw);
+
+                if (!botEl && finalText) {
+                    if (loadingEl) { loadingEl.remove(); loadingEl = null; }
+                    addBotMessage(finalText, new Date((item.timestamp || Date.now() / 1000) * 1000), requestId);
+                } else if (botEl) {
+                    contentEl.classList.remove('sse-streaming');
+                    if (finalText) contentEl.innerHTML = renderMarkdown(finalText);
+                    contentEl.dataset.rawMd = finalTextRaw || '';
+                    const copyBtn = botEl.querySelector('.copy-msg-btn');
+                    if (copyBtn && finalText) copyBtn.style.display = '';
+                    applyHighlighting(botEl);
+                }
+
+                // Backfill seq metadata so edit/regenerate buttons can call
+                // the delete API without a page refresh. Backend includes
+                // user_seq / bot_seq on the done event after persistence.
+                const targetBotEl = botEl || (requestId ? messagesDiv.querySelector(`[data-request-id="${requestId}"]`) : null);
+                if (targetBotEl) {
+                    if (item.bot_seq !== undefined && item.bot_seq !== null) {
+                        targetBotEl.dataset.seq = item.bot_seq;
+                    }
+                    // Reveal regenerate button now that the seq is wired up.
+                    const regenBtn = targetBotEl.querySelector('.regenerate-msg-btn');
+                    if (regenBtn) regenBtn.style.display = '';
+                    if (item.user_seq !== undefined && item.user_seq !== null) {
+                        // Locate the preceding user bubble for this turn.
+                        let prev = targetBotEl.previousElementSibling;
+                        while (prev && !prev.classList.contains('user-message-group')) {
+                            prev = prev.previousElementSibling;
+                        }
+                        if (prev && !prev.dataset.seq) {
+                            prev.dataset.seq = item.user_seq;
+                        }
+                    }
+                }
+                renderBotSpeakerButton(botEl, finalText);
+                scrollChatToBottom();
+
+                if (titleInfo) {
+                    generateSessionTitle(titleInfo.sid, titleInfo.userMsg, '');
+                    titleInfo = null;
+                } else if (sessionPanelOpen) {
+                    loadSessionList();
+                }
+
+            } else if (item.type === 'voice_attach') {
+                // TTS finished — attach a playable audio element to the
+                // current bot bubble. The stream closes right after.
+                if (botEl && item.url) {
+                    attachAudioToBotBubble(botEl, item.url, { autoplay: true });
+                }
+                if (currentEs) { currentEs.close(); }
+                delete activeStreams[requestId];
+                clearOwnerRequest();
+
+            } else if (item.type === 'error') {
+                done = true;
+                if (currentEs) { currentEs.close(); }
+                delete activeStreams[requestId];
+                clearOwnerRequest();
+                if (loadingEl) { loadingEl.remove(); loadingEl = null; }
+                addBotMessage(t('error_send'), new Date());
+                resetSendBtnSendMode();
+            }
+    }
+
+    function connect() {
+        const es = new EventSource(`/stream?request_id=${encodeURIComponent(requestId)}`);
+        currentEs = es;
+        activeStreams[requestId] = es;
+
+        es.onmessage = function(e) {
+            let item;
+            try { item = JSON.parse(e.data); } catch (_) { return; }
+
+            // Successful data received, reset reconnect counter
+            reconnectCount = 0;
+
+            // Record every event for re-attach replay (capped to avoid
+            // unbounded growth on very long streams).
+            if (item.type === 'tool_progress' && item.tool_call_id) {
+                const previousIndex = buffer.items.findIndex(
+                    buffered => buffered.type === 'tool_progress'
+                        && buffered.tool_call_id === item.tool_call_id
+                );
+                if (previousIndex >= 0) buffer.items.splice(previousIndex, 1);
+            }
+            if (buffer.items.length < 5000) buffer.items.push(item);
+
+            // Background session: keep the stream alive so the reply finishes
+            // and persists, but skip rendering into the now-foreign view. The
+            // buffer above still grows so returning to the session can rebuild
+            // the bubble and resume live rendering.
+            if (ownerSession !== sessionId) {
+                if (item.type === 'done' || item.type === 'error' || item.type === 'voice_attach') {
+                    done = true;
+                    es.close();
+                    delete activeStreams[requestId];
+                    clearOwnerRequest();
+                }
+                return;
+            }
+
+            processSSEItem(item);
+        };
+
+        es.onerror = function() {
+            es.close();
+            delete activeStreams[requestId];
+
+            if (done) {
+                // Normal close after the post-done tail expired; nothing to do.
+                return;
+            }
+
+            if (currentReasoningEl) {
+                finalizeThinking(currentReasoningEl, reasoningStartTime, reasoningText);
+                currentReasoningEl = null;
+                reasoningText = '';
+            }
+
+            if (reconnectCount < MAX_RECONNECTS) {
+                reconnectCount++;
+                const delay = Math.min(RECONNECT_BASE_MS * reconnectCount, 5000);
+                console.warn(`[SSE] connection lost for ${requestId}, reconnecting in ${delay}ms (attempt ${reconnectCount}/${MAX_RECONNECTS})`);
+                setTimeout(connect, delay);
+                return;
+            }
+
+            // Exhausted retries. Only surface the failure in the owning view —
+            // a background session must not mutate the currently shown chat.
+            clearOwnerRequest();
+            if (!isActive()) return;
+            if (loadingEl) { loadingEl.remove(); loadingEl = null; }
+            if (!botEl) {
+                addBotMessage(t('error_send'), new Date());
+            } else if (accumulatedText) {
+                contentEl.classList.remove('sse-streaming');
+                contentEl.innerHTML = renderMarkdown(accumulatedText);
+                applyHighlighting(botEl);
+                bindChatKnowledgeLinks(botEl);
+            }
+            resetSendBtnSendMode();
+        };
+    }
+
+    // Re-attach replay: rebuild the bubble from buffered events (snapshot,
+    // not animated) before connecting for the live tail. `processSSEItem`
+    // is the same renderer used by the live onmessage handler, so the
+    // snapshot matches exactly what live rendering would have produced.
+    if (replayItems && replayItems.length) {
+        for (const item of replayItems) {
+            try { processSSEItem(item); } catch (_) {}
+            if (item.type === 'done' || item.type === 'error' || item.type === 'voice_attach') {
+                done = true;
+            }
+        }
+        // If the buffered stream already finished, don't reconnect — the
+        // reply is complete and persisted; show its final state and stop.
+        if (done) {
+            clearOwnerRequest();
+            resetSendBtnSendMode();
+            scrollChatToBottom(true);
+            return;
+        }
+    }
+
+    connect();
+}
+
+function startPolling() {
+    const gen = ++pollGeneration;
+    isPolling = true;
+    let pollInFlight = false;
+
+    function poll() {
+        if (gen !== pollGeneration) return;
+        if (pollInFlight) return;
+        if (document.hidden) { setTimeout(poll, 10000); return; }
+
+        pollInFlight = true;
+        fetch('/poll', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ session_id: sessionId })
+        })
+        .then(r => r.json())
+        .then(data => {
+            pollInFlight = false;
+            if (gen !== pollGeneration) return;
+            if (data.status === 'success' && data.has_content) {
+                const rid = data.request_id;
+                if (loadingContainers[rid]) {
+                    loadingContainers[rid].remove();
+                    delete loadingContainers[rid];
+                }
+                // Skip if this reply is already on screen. Happens when a reply
+                // arrives via both the SSE stream and the poll queue (e.g. the
+                // user switched away mid-run, leaving the queued reply to be
+                // re-fetched on return) — render it only once.
+                const already = rid && messagesDiv.querySelector(
+                    `[data-request-id="${rid}"]`
+                );
+                if (!already) {
+                    const welcomeScreen = document.getElementById('welcome-screen');
+                    if (welcomeScreen) welcomeScreen.remove();
+                    addBotMessage(data.content, new Date(data.timestamp * 1000), rid);
+                    scrollChatToBottom();
+                }
+            }
+            const delay = (data.status === 'success' && data.has_content) ? 5000 : 10000;
+            setTimeout(poll, delay);
+        })
+        .catch(() => { pollInFlight = false; setTimeout(poll, 10000); });
+    }
+    poll();
+}
+
+function createUserMessageEl(content, timestamp, attachments) {
+    const el = document.createElement('div');
+    el.className = 'flex justify-end px-4 sm:px-6 py-3 user-message-group';
+
+    let attachHtml = '';
+    if (attachments && attachments.length > 0) {
+        const items = attachments.map(a => {
+            if (a.file_type === 'image') {
+                return `<img src="${a.preview_url}" alt="${escapeHtml(a.file_name)}" class="user-msg-image">`;
+            }
+            const icon = a.file_type === 'video'
+                ? 'fa-film'
+                : (a.file_type === 'directory' ? 'fa-folder-tree' : 'fa-file-alt');
+            const suffix = a.file_type === 'directory' && a.file_count
+                ? ` (${a.file_count})`
+                : '';
+            return `<div class="user-msg-file"><i class="fas ${icon}"></i> ${escapeHtml(a.file_name)}${suffix}</div>`;
+        }).join('');
+        attachHtml = `<div class="user-msg-attachments">${items}</div>`;
+    }
+
+    const textHtml = content ? renderMarkdown(content) : '';
+    el.innerHTML = `
+        <div class="max-w-[75%] sm:max-w-[60%]">
+            <div class="bg-primary-400 text-white rounded-2xl px-4 py-2.5 text-sm leading-relaxed msg-content user-bubble">
+                ${attachHtml}${textHtml}
+            </div>
+            <div class="flex items-center justify-end gap-2 mt-1.5">
+                <button class="edit-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-primary-400 dark:hover:text-primary-400 transition-colors cursor-pointer" title="${t('edit_message')}">
+                    <i class="fas fa-pen-to-square"></i>
+                </button>
+                <button class="delete-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-red-500 dark:hover:text-red-400 transition-colors cursor-pointer" title="${t('delete_message_title')}">
+                    <i class="fas fa-trash"></i>
+                </button>
+                <span class="text-xs text-slate-400 dark:text-slate-500">${formatTime(timestamp)}</span>
+            </div>
+        </div>
+    `;
+    // Store raw content for editing
+    el.dataset.rawContent = content || '';
+    return el;
+}
+
+function renderToolCallsHtml(toolCalls) {
+    if (!toolCalls || toolCalls.length === 0) return '';
+    return toolCalls.map(tc => {
+        const argsStr = formatToolArgs(tc.arguments || {});
+        const resultStr = tc.result ? escapeHtml(String(tc.result)) : '';
+        const hasResult = !!resultStr;
+        return `
+<div class="agent-step agent-tool-step">
+    <div class="tool-header" onclick="this.parentElement.classList.toggle('expanded')">
+        <i class="fas fa-check text-primary-400 flex-shrink-0 tool-icon"></i>
+        <span class="tool-name">${escapeHtml(tc.name || '')}</span>
+        <i class="fas fa-chevron-right tool-chevron"></i>
+    </div>
+    <div class="tool-detail">
+        <div class="tool-detail-section">
+            <div class="tool-detail-label">Input</div>
+            <pre class="tool-detail-content">${argsStr}</pre>
+        </div>
+        ${hasResult ? `
+        <div class="tool-detail-section tool-output-section">
+            <div class="tool-detail-label">Output</div>
+            <pre class="tool-detail-content">${resultStr}</pre>
+        </div>` : ''}
+    </div>
+</div>`;
+    }).join('');
+}
+
+// Cap for rendering reasoning content in the bubble. Beyond this size,
+// we skip markdown rendering entirely and show plain text head + tail to
+// keep the page responsive (very long chains-of-thought can otherwise
+// stall or crash the browser when re-parsed by marked.js).
+// Keep this in sync with backend MAX_STORED_REASONING_CHARS and
+// MAX_REASONING_STREAM_CHARS so storage / SSE / display stay aligned.
+const REASONING_RENDER_CAP = 4 * 1024; // 4 KB
+
+function _truncateReasoningForDisplay(text) {
+    if (!text || text.length <= REASONING_RENDER_CAP) return { text, truncated: false, omitted: 0 };
+    const half = Math.floor(REASONING_RENDER_CAP / 2);
+    const head = text.slice(0, half);
+    const tail = text.slice(-half);
+    return {
+        text: head + '\n\n... [' + (text.length - head.length - tail.length) + ' chars omitted] ...\n\n' + tail,
+        truncated: true,
+        omitted: text.length - head.length - tail.length,
+    };
+}
+
+function _renderReasoningBody(text) {
+    // For short reasoning, render as markdown. For long ones, fall back to
+    // an escaped <pre> block to avoid expensive markdown parsing.
+    const { text: shown, truncated } = _truncateReasoningForDisplay(text);
+    if (truncated || shown.length > REASONING_RENDER_CAP) {
+        return '<pre class="thinking-stream-pre">' + escapeHtml(shown) + '</pre>';
+    }
+    return renderMarkdown(shown);
+}
+
+function finalizeThinking(el, startTime, text) {
+    const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
+    el.querySelector('.thinking-summary').textContent = t('thinking_done');
+    const fullDiv = el.querySelector('.thinking-full');
+    fullDiv.innerHTML = `<div class="thinking-duration">${t('thinking_duration')} ${elapsed}s</div>` + _renderReasoningBody(text);
+}
+
+function renderThinkingHtml(text) {
+    if (!text || !text.trim()) return '';
+    const full = text.trim();
+    return `
+<div class="agent-step agent-thinking-step">
+    <div class="thinking-header" onclick="this.parentElement.classList.toggle('expanded')">
+        <i class="fas fa-lightbulb text-amber-400 flex-shrink-0"></i>
+        <span class="thinking-summary">${t('thinking_done')}</span>
+        <i class="fas fa-chevron-right thinking-chevron"></i>
+    </div>
+    <div class="thinking-full">${_renderReasoningBody(full)}</div>
+</div>`;
+}
+
+function renderStepsHtml(steps) {
+    if (!steps || steps.length === 0) return { stepsHtml: '', finalContent: '' };
+
+    // Find the index of the last content step — it becomes the main answer, not a step
+    let lastContentIdx = -1;
+    for (let i = steps.length - 1; i >= 0; i--) {
+        if (steps[i].type === 'content') { lastContentIdx = i; break; }
+    }
+
+    let html = '';
+    let lastContentText = '';
+    for (let i = 0; i < steps.length; i++) {
+        const step = steps[i];
+        if (step.type === 'thinking') {
+            html += renderThinkingHtml(step.content);
+        } else if (step.type === 'content') {
+            if (i === lastContentIdx) {
+                lastContentText = step.content;
+            } else {
+                html += `<div class="agent-step agent-content-step"><div class="agent-content-body">${renderMarkdown(step.content)}</div></div>`;
+            }
+        } else if (step.type === 'tool') {
+            const argsStr = formatToolArgs(step.arguments || {});
+            const resultStr = step.result ? escapeHtml(String(step.result)) : '';
+            const isErr = step.is_error === true;
+            const iconClass = isErr
+                ? 'fas fa-times text-red-400 flex-shrink-0 tool-icon'
+                : 'fas fa-check text-primary-400 flex-shrink-0 tool-icon';
+            html += `
+<div class="agent-step agent-tool-step${isErr ? ' tool-failed' : ''}">
+    <div class="tool-header" onclick="this.parentElement.classList.toggle('expanded')">
+        <i class="${iconClass}"></i>
+        <span class="tool-name">${escapeHtml(step.name || '')}</span>
+        <i class="fas fa-chevron-right tool-chevron"></i>
+    </div>
+    <div class="tool-detail">
+        <div class="tool-detail-section">
+            <div class="tool-detail-label">Input</div>
+            <pre class="tool-detail-content">${argsStr}</pre>
+        </div>
+        ${resultStr ? `
+        <div class="tool-detail-section tool-output-section">
+            <div class="tool-detail-label">${isErr ? 'Error' : 'Output'}</div>
+            <pre class="tool-detail-content${isErr ? ' tool-error-text' : ''}">${resultStr}</pre>
+        </div>` : ''}
+    </div>
+</div>`;
+            // If this tool sent a file (send/read tool), render the media inline
+            // so it persists across page refreshes (SSE-only file events are not stored).
+            const mediaHtml = _renderSentFileFromToolResult(step);
+            if (mediaHtml) html += mediaHtml;
+        }
+    }
+    return { stepsHtml: html, lastContentText };
+}
+
+// Extract file-to-send metadata from a tool's result and render an inline preview.
+// Returns '' if the result isn't a file_to_send payload.
+function _renderSentFileFromToolResult(step) {
+    if (!step || !step.result) return '';
+    let payload;
+    try {
+        payload = typeof step.result === 'string' ? JSON.parse(step.result) : step.result;
+    } catch (_) { return ''; }
+    if (!payload || payload.type !== 'file_to_send' || !payload.path) return '';
+    const webUrl = _toWebUrl(payload.path);
+    const fileType = payload.file_type || 'file';
+    const fileName = payload.file_name || payload.path.split('/').pop();
+    if (fileType === 'image') {
+        return `<div class="agent-step">${_buildImageHtml(webUrl)}</div>`;
+    }
+    if (fileType === 'video') {
+        return `<div class="agent-step">${_buildVideoHtml(webUrl)}</div>`;
+    }
+    return `<div class="agent-step"><a href="${webUrl}" download="${escapeHtml(fileName)}" target="_blank" ` +
+        `style="display:inline-flex;align-items:center;gap:6px;padding:8px 14px;margin:8px 0;border-radius:8px;` +
+        `background:var(--bg-secondary,#f3f4f6);color:var(--text-primary,#374151);text-decoration:none;font-size:14px;` +
+        `border:1px solid var(--border-color,#e5e7eb);">` +
+        `<i class="fas fa-file-download" style="color:#6b7280;"></i> ${escapeHtml(fileName)}</a></div>`;
+}
+
+// Cosmetic translator for cancel markers persisted in history.
+// History keeps the English canonical form for the LLM; only display is localized.
+function localizeCancelMarker(text) {
+    if (!text) return text;
+    if (currentLang !== 'zh') return text;
+    return text
+        .replace(/_\(Cancelled by user\)_/g, '_(用户已中止)_')
+        .replace(/_\(Cancelled\)_/g, '_(已中止)_');
+}
+
+function createBotMessageEl(content, timestamp, requestId, msg) {
+    const el = document.createElement('div');
+    el.className = 'flex gap-3 px-4 sm:px-6 py-3 bot-message-group';
+    if (requestId) el.dataset.requestId = requestId;
+
+    let stepsHtml = '';
+    let displayContent = localizeCancelMarker(content);
+
+    if (msg && msg.steps && msg.steps.length > 0) {
+        // New format: ordered steps with interleaved content
+        const result = renderStepsHtml(msg.steps);
+        stepsHtml = result.stepsHtml;
+        // The final content (last text after all steps) is the main answer
+        displayContent = content || result.lastContentText;
+    } else {
+        // Legacy format: separate tool_calls + optional reasoning
+        const toolCalls = msg && msg.tool_calls;
+        const reasoning = msg && msg.reasoning;
+        stepsHtml = renderThinkingHtml(reasoning) + renderToolCallsHtml(toolCalls);
+    }
+
+    // Self-evolution bubbles get a small badge so the user can feel the agent
+    // learned something on its own (text itself stays clean). History replay
+    // carries msg.kind; live pushes are identified by the evolution_ request id.
+    const isEvolution = (msg && msg.kind === 'evolution')
+        || (typeof requestId === 'string' && requestId.startsWith('evolution_'));
+    const evolutionBadge = isEvolution
+        ? `<div class="flex items-center gap-1 mb-1.5 text-xs text-slate-400 dark:text-slate-500">
+                <i class="fas fa-seedling text-[11px]"></i>
+                <span>${t('evolution_badge')}</span>
+           </div>`
+        : '';
+
+    el.innerHTML = `
+        <img src="assets/logo.jpg" alt="CowAgent" class="w-8 h-8 rounded-lg flex-shrink-0">
+        <div class="min-w-0 flex-1 max-w-[85%]">
+            <div class="bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-2xl px-4 py-3 text-sm leading-relaxed msg-content text-slate-700 dark:text-slate-200">
+                ${evolutionBadge}
+                ${stepsHtml ? `<div class="agent-steps">${stepsHtml}</div>` : ''}
+                <div class="answer-content">${renderMarkdown(displayContent)}</div>
+                <div class="bot-audio-slot"></div>
+            </div>
+            <div class="flex items-center gap-2 mt-1.5">
+                <span class="text-xs text-slate-400 dark:text-slate-500">${formatTime(timestamp)}</span>
+                <button class="copy-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-slate-500 dark:hover:text-slate-400 transition-colors cursor-pointer" title="${currentLang === 'zh' ? '复制' : 'Copy'}">
+                    <i class="fas fa-copy"></i>
+                </button>
+                <button class="speak-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-slate-500 dark:hover:text-slate-400 transition-colors cursor-pointer" title="${t('speak_msg')}" style="display:none;">
+                    <i class="fas fa-volume-up"></i>
+                </button>
+                <button class="regenerate-msg-btn text-xs text-slate-300 dark:text-slate-600 hover:text-primary-400 dark:hover:text-primary-400 transition-colors cursor-pointer" title="${t('regenerate_response')}">
+                    <i class="fas fa-rotate-right"></i>
+                </button>
+            </div>
+        </div>
+    `;
+    el.querySelector('.answer-content').dataset.rawMd = displayContent;
+    // Existing TTS attachment (history replay): mount the player up-front.
+    const existingAudio = msg && msg.extras && msg.extras.audio && msg.extras.audio.url;
+    if (existingAudio) {
+        attachAudioToBotBubble(el, existingAudio, { autoplay: false });
+    }
+    renderBotSpeakerButton(el, displayContent);
+    applyHighlighting(el);
+    bindChatKnowledgeLinks(el);
+    return el;
+}
+
+// Append (or replace) a small audio player inside a bot bubble's
+// dedicated `.bot-audio-slot`. Used by both live TTS pushes and history
+// replay. Silent failures: never throws.
+function attachAudioToBotBubble(botEl, audioUrl, opts) {
+    try {
+        if (!botEl || !audioUrl) return;
+        const slot = botEl.querySelector('.bot-audio-slot');
+        if (!slot) return;
+        slot.innerHTML = '';
+        slot.style.marginTop = '6px';
+        const pill = renderVoicePill(audioUrl, { autoplay: !!(opts && opts.autoplay) });
+        slot.appendChild(pill);
+        const speakBtn = botEl.querySelector('.speak-msg-btn');
+        if (speakBtn) speakBtn.style.display = 'none';
+    } catch (_) { /* silent */ }
+}
+
+// Build a compact play/pause + progress + duration pill that wraps a
+// hidden <audio>. Returns the root element; safe to embed anywhere.
+function renderVoicePill(audioUrl, opts) {
+    opts = opts || {};
+    const wrap = document.createElement('div');
+    wrap.className = 'voice-pill';
+    wrap.innerHTML = `
+        <button type="button" class="voice-pill-btn" data-state="play" aria-label="play">
+            <i class="fas fa-play"></i>
+        </button>
+        <div class="voice-pill-track"><div class="voice-pill-fill"></div></div>
+        <span class="voice-pill-time">0:00</span>
+        <audio preload="metadata" src="${audioUrl}"></audio>
+    `;
+    const btn = wrap.querySelector('.voice-pill-btn');
+    const fill = wrap.querySelector('.voice-pill-fill');
+    const timeEl = wrap.querySelector('.voice-pill-time');
+    const audio = wrap.querySelector('audio');
+
+    const fmt = (s) => {
+        if (!isFinite(s) || s < 0) s = 0;
+        const m = Math.floor(s / 60);
+        const r = Math.floor(s % 60);
+        return `${m}:${r < 10 ? '0' : ''}${r}`;
+    };
+    const setIcon = (state) => {
+        btn.dataset.state = state;
+        btn.querySelector('i').className = state === 'pause' ? 'fas fa-pause' : 'fas fa-play';
+        btn.setAttribute('aria-label', state === 'pause' ? 'pause' : 'play');
+    };
+
+    audio.addEventListener('loadedmetadata', () => {
+        if (audio.duration && isFinite(audio.duration)) timeEl.textContent = fmt(audio.duration);
+    });
+    audio.addEventListener('timeupdate', () => {
+        const dur = audio.duration || 0;
+        if (dur > 0) {
+            fill.style.width = `${Math.min(100, (audio.currentTime / dur) * 100)}%`;
+            timeEl.textContent = fmt(dur - audio.currentTime);
+        }
+    });
+    audio.addEventListener('ended', () => {
+        setIcon('play');
+        fill.style.width = '0%';
+        timeEl.textContent = fmt(audio.duration || 0);
+    });
+    audio.addEventListener('play',  () => setIcon('pause'));
+    audio.addEventListener('pause', () => setIcon('play'));
+
+    btn.addEventListener('click', (e) => {
+        e.stopPropagation();
+        if (audio.paused) {
+            audio.play().catch(() => {});
+        } else {
+            audio.pause();
+        }
+    });
+
+    if (opts.autoplay) {
+        // Autoplay may be blocked by the browser; fall back silently and
+        // let the user tap the play button.
+        const tryPlay = () => audio.play().catch(() => {});
+        if (audio.readyState >= 2) tryPlay();
+        else audio.addEventListener('canplay', tryPlay, { once: true });
+    }
+    return wrap;
+}
+
+// Show the manual "read aloud" button when TTS is configured but the
+// bubble has no audio yet. Lazily probes capability via /api/models so
+// we don't expose the button when nothing can synthesize speech.
+function renderBotSpeakerButton(botEl, text) {
+    if (!botEl || !text || !text.trim()) return;
+    const btn = botEl.querySelector('.speak-msg-btn');
+    if (!btn) return;
+    if (botEl.querySelector('.bot-audio-slot audio')) return;
+    _isTtsReady().then(ready => {
+        if (!ready) return;
+        btn.style.display = '';
+        btn.onclick = () => _triggerManualTts(btn, botEl, text);
+    });
+}
+
+let _ttsReadyPromise = null;
+let _ttsReadyTs = 0;
+function _isTtsReady() {
+    // Cache for 30s to avoid hammering /api/models on every bubble.
+    if (_ttsReadyPromise && Date.now() - _ttsReadyTs < 30000) {
+        return _ttsReadyPromise;
+    }
+    _ttsReadyTs = Date.now();
+    _ttsReadyPromise = fetch('/api/models')
+        .then(r => r.json())
+        .then(data => {
+            const tts = data && data.capabilities && data.capabilities.tts;
+            if (!tts) return false;
+            return Boolean(tts.current_provider || tts.suggested_provider);
+        })
+        .catch(() => false);
+    return _ttsReadyPromise;
+}
+
+function _triggerManualTts(btn, botEl, text) {
+    if (btn.dataset.busy === '1') return;
+    btn.dataset.busy = '1';
+    const icon = btn.querySelector('i');
+    const prev = icon ? icon.className : '';
+    if (icon) icon.className = 'fas fa-spinner fa-spin';
+    fetch('/api/voice/tts', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ text, session_id: sessionId }),
+    })
+        .then(r => r.json())
+        .then(data => {
+            if (data && data.status === 'success' && data.audio_url) {
+                attachAudioToBotBubble(botEl, data.audio_url, { autoplay: true });
+            }
+        })
+        .catch(() => {})
+        .finally(() => {
+            btn.dataset.busy = '0';
+            if (icon) icon.className = prev || 'fas fa-volume-up';
+        });
+}
+
+function addUserMessage(content, timestamp, attachments) {
+    const el = createUserMessageEl(content, timestamp, attachments);
+    messagesDiv.appendChild(el);
+    _autoScrollEnabled = true;
+    scrollChatToBottom(true);
+}
+
+function addBotMessage(content, timestamp, requestId) {
+    const el = createBotMessageEl(content, timestamp, requestId);
+    messagesDiv.appendChild(el);
+    scrollChatToBottom();
+}
+
+// Load conversation history from the server (page 1 = most recent messages).
+// Subsequent pages prepend older messages when the user scrolls to the top.
+function loadHistory(page) {
+    if (historyLoading) return;
+    historyLoading = true;
+
+    fetch(`/api/history?session_id=${encodeURIComponent(sessionId)}&page=${page}&page_size=20`)
+        .then(r => r.json())
+        .then(data => {
+            if (data.status !== 'success' || data.messages.length === 0) return;
+
+            const prevScrollHeight = messagesDiv.scrollHeight;
+            const isFirstLoad = page === 1;
+
+            // On first load, remove the welcome screen if history exists
+            if (isFirstLoad) {
+                const ws = document.getElementById('welcome-screen');
+                if (ws) ws.remove();
+            }
+
+            // Build a fragment of history message elements in chronological order
+            const fragment = document.createDocumentFragment();
+
+            if (data.has_more && page > 1) {
+                // Keep the "load more" sentinel in place (inserted below)
+            }
+
+            const ctxStartSeq = data.context_start_seq || 0;
+            let dividerInserted = false;
+
+            data.messages.forEach(msg => {
+                const hasContent = msg.content && msg.content.trim();
+                const hasToolCalls = msg.role === 'assistant' && msg.tool_calls && msg.tool_calls.length > 0;
+                if (!hasContent && !hasToolCalls) return;
+
+                // Insert context divider when transitioning from above to below boundary
+                if (ctxStartSeq > 0 && !dividerInserted && msg._seq !== undefined && msg._seq >= ctxStartSeq) {
+                    dividerInserted = true;
+                    const divider = document.createElement('div');
+                    divider.className = 'context-divider';
+                    divider.innerHTML = `<span>${t('context_cleared')}</span>`;
+                    fragment.appendChild(divider);
+                }
+
+                const ts = new Date(msg.created_at * 1000);
+                const el = msg.role === 'user'
+                    ? createUserMessageEl(msg.content, ts)
+                    : createBotMessageEl(msg.content || '', ts, null, msg);
+                // Store seq for delete functionality
+                if (msg._seq !== undefined) {
+                    el.dataset.seq = msg._seq;
+                }
+                fragment.appendChild(el);
+            });
+
+            // If context was cleared but no new messages exist yet, append divider at the end
+            if (ctxStartSeq > 0 && !dividerInserted) {
+                const divider = document.createElement('div');
+                divider.className = 'context-divider';
+                divider.innerHTML = `<span>${t('context_cleared')}</span>`;
+                fragment.appendChild(divider);
+            }
+
+            // Prepend history above any existing messages
+            const sentinel = document.getElementById('history-load-more');
+            const insertBefore = sentinel ? sentinel.nextSibling : messagesDiv.firstChild;
+            messagesDiv.insertBefore(fragment, insertBefore);
+            updateEditButtonsState();
+
+            // Manage the "load more" sentinel at the very top
+            if (data.has_more) {
+                if (!document.getElementById('history-load-more')) {
+                    const btn = document.createElement('div');
+                    btn.id = 'history-load-more';
+                    btn.className = 'flex justify-center py-3';
+                    btn.innerHTML = `<button class="text-xs text-slate-400 dark:text-slate-500 hover:text-primary-400 transition-colors" onclick="loadHistory(historyPage + 1)">Load earlier messages</button>`;
+                    messagesDiv.insertBefore(btn, messagesDiv.firstChild);
+                }
+            } else {
+                const sentinel = document.getElementById('history-load-more');
+                if (sentinel) sentinel.remove();
+            }
+
+            historyHasMore = data.has_more;
+            historyPage = page;
+
+            if (isFirstLoad) {
+                // Scroll to the very bottom after the DOM settles. A single
+                // rAF isn't enough: markdown/code-highlight/images keep growing
+                // scrollHeight after the first paint, leaving the last bubble's
+                // timestamp clipped. Re-pin a few times to catch late layout.
+                requestAnimationFrame(() => scrollChatToBottom(true));
+                [120, 350, 700].forEach(d => setTimeout(() => scrollChatToBottom(true), d));
+            } else {
+                // Restore scroll position so loading older messages doesn't jump the view
+                messagesDiv.scrollTop = messagesDiv.scrollHeight - prevScrollHeight;
+            }
+        })
+        .catch(() => {})
+        .finally(() => { historyLoading = false; });
+}
+
+function addLoadingIndicator() {
+    const el = document.createElement('div');
+    el.className = 'flex gap-3 px-4 sm:px-6 py-3';
+    el.innerHTML = `
+        <img src="assets/logo.jpg" alt="CowAgent" class="w-8 h-8 rounded-lg flex-shrink-0">
+        <div class="bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-2xl px-4 py-3">
+            <div class="flex items-center gap-1.5">
+                <span class="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style="animation-delay: 0s"></span>
+                <span class="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style="animation-delay: 0.2s"></span>
+                <span class="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style="animation-delay: 0.4s"></span>
+            </div>
+        </div>
+    `;
+    messagesDiv.appendChild(el);
+    scrollChatToBottom();
+    return el;
+}
+
+function newChat(optimistic = true) {
+    // Do NOT close active streams: other sessions keep streaming in the
+    // background (each stream self-guards against the foreign view) and their
+    // replies still complete and persist.
+
+    // Generate a fresh session and persist it so the next page load also starts clean
+    sessionId = generateSessionId();
+    localStorage.setItem(SESSION_ID_KEY, sessionId);
+    resetSendBtnSendMode();  // fresh session has no in-flight reply
+    startPolling();  // bump generation so old loop self-cancels, new loop uses fresh sessionId
+    messagesDiv.innerHTML = '';
+    const ws = document.createElement('div');
+    ws.id = 'welcome-screen';
+    ws.className = 'flex flex-col items-center justify-center h-full px-6 pb-16';
+    ws.style.paddingTop = '6vh';
+    ws.innerHTML = `
+        <img src="assets/logo.jpg" alt="CowAgent" class="w-16 h-16 rounded-2xl mb-6 shadow-lg shadow-primary-500/20">
+        <h1 class="text-2xl font-bold text-slate-800 dark:text-slate-100 mb-3">${appConfig.title || 'CowAgent'}</h1>
+        <p class="text-slate-500 dark:text-slate-400 text-center max-w-lg mb-10 leading-relaxed" data-i18n="welcome_subtitle">${t('welcome_subtitle')}</p>
+        <div class="grid grid-cols-2 sm:grid-cols-3 gap-3 w-full max-w-2xl">
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-blue-50 dark:bg-blue-900/30 flex items-center justify-center">
+                        <i class="fas fa-folder-open text-blue-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_sys_title">${t('example_sys_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_sys_text">${t('example_sys_text')}</p>
+            </div>
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-amber-50 dark:bg-amber-900/30 flex items-center justify-center">
+                        <i class="fas fa-clock text-amber-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_task_title">${t('example_task_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_task_text">${t('example_task_text')}</p>
+            </div>
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center">
+                        <i class="fas fa-code text-emerald-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_code_title">${t('example_code_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_code_text">${t('example_code_text')}</p>
+            </div>
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-violet-50 dark:bg-violet-900/30 flex items-center justify-center">
+                        <i class="fas fa-book text-violet-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_knowledge_title">${t('example_knowledge_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_knowledge_text">${t('example_knowledge_text')}</p>
+            </div>
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-rose-50 dark:bg-rose-900/30 flex items-center justify-center">
+                        <i class="fas fa-puzzle-piece text-rose-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_skill_title">${t('example_skill_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_skill_text">${t('example_skill_text')}</p>
+            </div>
+            <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4 cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200" data-send="/help">
+                <div class="flex items-center gap-2 mb-2">
+                    <div class="w-7 h-7 rounded-lg bg-slate-100 dark:bg-slate-800 flex items-center justify-center">
+                        <i class="fas fa-terminal text-slate-500 text-xs"></i>
+                    </div>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_web_title">${t('example_web_title')}</span>
+                </div>
+                <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_web_text">${t('example_web_text')}</p>
+            </div>
+        </div>
+    `;
+    messagesDiv.appendChild(ws);
+    ws.querySelectorAll('.example-card').forEach(card => {
+        card.addEventListener('click', () => {
+            const sendText = card.dataset.send;
+            if (sendText) {
+                chatInput.value = sendText;
+                chatInput.dispatchEvent(new Event('input'));
+                chatInput.focus();
+                return;
+            }
+            const textEl = card.querySelector('[data-i18n*="text"]');
+            if (textEl) {
+                chatInput.value = textEl.textContent;
+                chatInput.dispatchEvent(new Event('input'));
+                chatInput.focus();
+            }
+        });
+    });
+    if (currentView !== 'chat') navigateTo('chat');
+
+    // Show panel and load full session list, then prepend the new session on top
+    const panel = document.getElementById('session-panel');
+    if (panel && !sessionPanelOpen) {
+        sessionPanelOpen = true;
+        panel.classList.remove('hidden');
+        _showSessionOverlay();
+        _persistPanelState();
+    }
+    // Only prepend an optimistic "new chat" item when this is a real new-chat
+    // action. When called after deleting the current session, skip it: the
+    // fresh session has no backend record yet, so inserting it would leave an
+    // empty, undeletable item in the list (deleting it just spawns another).
+    const newSid = sessionId;
+    if (optimistic) {
+        loadSessionList(() => _addOptimisticSessionItem(newSid));
+    } else {
+        loadSessionList();
+    }
+}
+
+// =====================================================================
+// Session Panel
+// =====================================================================
+
+const SESSION_PANEL_KEY = 'cow_session_panel_open';
+let sessionPanelOpen = localStorage.getItem(SESSION_PANEL_KEY) === '1';
+
+function _persistPanelState() {
+    localStorage.setItem(SESSION_PANEL_KEY, sessionPanelOpen ? '1' : '0');
+}
+
+function _isMobileView() {
+    return window.innerWidth <= 768;
+}
+
+function _showSessionOverlay() {
+    if (!_isMobileView()) return;
+    const overlay = document.getElementById('session-panel-overlay');
+    if (overlay) overlay.classList.remove('hidden');
+}
+
+function _hideSessionOverlay() {
+    const overlay = document.getElementById('session-panel-overlay');
+    if (overlay) overlay.classList.add('hidden');
+}
+
+function closeSessionPanel() {
+    const panel = document.getElementById('session-panel');
+    if (!panel || !sessionPanelOpen) return;
+    sessionPanelOpen = false;
+    panel.classList.add('hidden');
+    _hideSessionOverlay();
+    _persistPanelState();
+}
+
+function toggleSessionPanel() {
+    const panel = document.getElementById('session-panel');
+    if (!panel) return;
+    sessionPanelOpen = !sessionPanelOpen;
+    panel.classList.toggle('hidden', !sessionPanelOpen);
+    if (sessionPanelOpen) {
+        _showSessionOverlay();
+    } else {
+        _hideSessionOverlay();
+    }
+    _persistPanelState();
+    if (sessionPanelOpen) loadSessionList();
+}
+
+function openSessionPanel() {
+    const panel = document.getElementById('session-panel');
+    if (!panel || sessionPanelOpen) return;
+    sessionPanelOpen = true;
+    panel.classList.remove('hidden');
+    _showSessionOverlay();
+    _persistPanelState();
+    loadSessionList();
+}
+
+function _restoreSessionPanel() {
+    const panel = document.getElementById('session-panel');
+    if (!panel) return;
+    if (sessionPanelOpen && !_isMobileView()) {
+        panel.classList.remove('hidden');
+        _showSessionOverlay();
+        loadSessionList();
+    } else {
+        panel.classList.add('hidden');
+        _hideSessionOverlay();
+    }
+}
+
+function _applyInputTooltips() {
+    const set = (id, key, pos) => {
+        const el = document.getElementById(id);
+        if (!el) return;
+        el.setAttribute('data-tooltip', t(key));
+        el.removeAttribute('title');
+        if (pos) el.setAttribute('data-tooltip-pos', pos);
+    };
+    set('new-chat-btn', 'tip_new_chat');
+    set('clear-context-btn', 'tip_clear_context');
+    set('attach-btn', 'tip_attach');
+    set('session-toggle-btn', 'session_history', 'bottom');
+}
+
+function _addOptimisticSessionItem(sid) {
+    const container = document.getElementById('session-list');
+    if (!container) return;
+
+    const emptyEl = container.querySelector('.session-empty');
+    if (emptyEl) emptyEl.remove();
+
+    document.querySelectorAll('.session-item.active').forEach(el => el.classList.remove('active'));
+
+    const todayLabel = t('today');
+    let firstGroup = container.querySelector('.session-group-label');
+    if (!firstGroup || firstGroup.textContent !== todayLabel) {
+        const header = document.createElement('div');
+        header.className = 'session-group-label';
+        header.textContent = todayLabel;
+        container.prepend(header);
+        firstGroup = header;
+    }
+
+    const title = t('new_chat');
+    const item = document.createElement('div');
+    item.className = 'session-item active';
+    item.dataset.sessionId = sid;
+    item.innerHTML = `
+        <i class="fas fa-message session-icon"></i>
+        <span class="session-title" title="${escapeHtml(title)}">${escapeHtml(title)}</span>
+        <button class="session-rename" onclick="event.stopPropagation(); renameSession('${sid}')" title="${escapeHtml(t('rename_session'))}">
+            <i class="fas fa-pen"></i>
+        </button>
+        <button class="session-delete" onclick="event.stopPropagation(); deleteSession('${sid}')" title="Delete">
+            <i class="fas fa-trash-can"></i>
+        </button>
+    `;
+    item.addEventListener('click', () => switchSession(sid));
+    firstGroup.insertAdjacentElement('afterend', item);
+}
+
+function _sessionTimeGroup(ts) {
+    const now = new Date();
+    const d = new Date(ts * 1000);
+    const today = new Date(now.getFullYear(), now.getMonth(), now.getDate());
+    const yesterday = new Date(today); yesterday.setDate(today.getDate() - 1);
+    if (d >= today) return t('today');
+    if (d >= yesterday) return t('yesterday');
+    return t('earlier');
+}
+
+let _sessionPage = 1;
+let _sessionHasMore = false;
+let _sessionLoading = false;
+const _SESSION_PAGE_SIZE = 50;
+
+function loadSessionList(onDone) {
+    const container = document.getElementById('session-list');
+    if (!container) return;
+
+    _sessionPage = 1;
+    _sessionHasMore = false;
+
+    _fetchSessionPage(1, true, onDone);
+}
+
+function _fetchSessionPage(page, clear, onDone) {
+    if (_sessionLoading) return;
+    _sessionLoading = true;
+
+    const container = document.getElementById('session-list');
+    if (!container) { _sessionLoading = false; return; }
+
+    // Remove existing "load more" sentinel before fetching
+    const oldSentinel = container.querySelector('.session-load-more');
+    if (oldSentinel) oldSentinel.remove();
+
+    fetch(`/api/sessions?page=${page}&page_size=${_SESSION_PAGE_SIZE}`)
+        .then(r => r.json())
+        .then(data => {
+            _sessionLoading = false;
+            if (data.status !== 'success') return;
+
+            if (clear) container.innerHTML = '';
+
+            const sessions = data.sessions || [];
+            _sessionPage = page;
+            _sessionHasMore = !!data.has_more;
+
+            if (sessions.length === 0 && page === 1) {
+                container.innerHTML = '<div class="session-empty">' + t('untitled_session') + '</div>';
+                if (typeof onDone === 'function') onDone();
+                return;
+            }
+
+            // Track last group label already in the container
+            const existingLabels = container.querySelectorAll('.session-group-label');
+            let lastGroup = existingLabels.length > 0
+                ? existingLabels[existingLabels.length - 1].textContent
+                : '';
+
+            sessions.forEach(s => {
+                const group = _sessionTimeGroup(s.last_active);
+                if (group !== lastGroup) {
+                    lastGroup = group;
+                    const header = document.createElement('div');
+                    header.className = 'session-group-label';
+                    header.textContent = group;
+                    container.appendChild(header);
+                }
+
+                const item = document.createElement('div');
+                const isActive = s.session_id === sessionId;
+                item.className = 'session-item' + (isActive ? ' active' : '');
+                item.dataset.sessionId = s.session_id;
+
+                const title = s.title || t('untitled_session');
+                item.innerHTML = `
+                    <i class="fas fa-message session-icon"></i>
+                    <span class="session-title" title="${escapeHtml(title)}">${escapeHtml(title)}</span>
+                    <button class="session-rename" onclick="event.stopPropagation(); renameSession('${s.session_id}')" title="${escapeHtml(t('rename_session'))}">
+                        <i class="fas fa-pen"></i>
+                    </button>
+                    <button class="session-delete" onclick="event.stopPropagation(); deleteSession('${s.session_id}')" title="Delete">
+                        <i class="fas fa-trash-can"></i>
+                    </button>
+                `;
+                item.addEventListener('click', () => switchSession(s.session_id));
+                container.appendChild(item);
+            });
+
+            if (typeof onDone === 'function') onDone();
+        })
+        .catch(() => { _sessionLoading = false; });
+}
+
+function _onSessionListScroll() {
+    if (!_sessionHasMore || _sessionLoading) return;
+    const container = document.getElementById('session-list');
+    if (!container) return;
+    // Trigger when scrolled near the bottom (within 60px)
+    if (container.scrollHeight - container.scrollTop - container.clientHeight < 60) {
+        _fetchSessionPage(_sessionPage + 1, false);
+    }
+}
+
+// Attach scroll listener once DOM is ready
+(function _initSessionScroll() {
+    const el = document.getElementById('session-list');
+    if (el) {
+        el.addEventListener('scroll', _onSessionListScroll);
+    } else {
+        document.addEventListener('DOMContentLoaded', () => {
+            const el2 = document.getElementById('session-list');
+            if (el2) el2.addEventListener('scroll', _onSessionListScroll);
+        });
+    }
+})();
+
+// Returning to a session whose reply is still streaming in the background.
+// Close the background EventSource, rebuild the bubble from the buffered
+// events (snapshot), then resume live streaming via a fresh connection that
+// reads the remaining tail from the backend queue. Returns true if a stream
+// was re-attached. The user's own bubble is already in history (persisted
+// eagerly), so it was rendered by loadHistory before this runs.
+function _reattachStream(sid) {
+    const requestId = sessionActiveRequest[sid];
+    if (!requestId) return false;
+    const buffer = streamBuffers[requestId];
+    if (!buffer) return false;
+
+    // If the buffered stream already finished, the assistant reply is already
+    // persisted and rendered by loadHistory — re-attaching would duplicate it.
+    // Just clean up the buffer/cursor and rely on history.
+    const finished = buffer.items.some(
+        it => it.type === 'done' || it.type === 'error'
+    );
+    if (finished) {
+        const oldEs = activeStreams[requestId];
+        if (oldEs) { try { oldEs.close(); } catch (_) {} delete activeStreams[requestId]; }
+        delete streamBuffers[requestId];
+        delete sessionActiveRequest[sid];
+        resetSendBtnSendMode();
+        return false;
+    }
+
+    // Stop the background stream so the rebuilt one is the sole consumer of
+    // the backend queue (the queue survives until "done", so the new
+    // connection picks up any remaining events).
+    const oldEs = activeStreams[requestId];
+    if (oldEs) { try { oldEs.close(); } catch (_) {} delete activeStreams[requestId]; }
+
+    // Snapshot the buffered events into the replay, then start a fresh stream
+    // that replays them and reconnects for the live tail.
+    const replay = buffer.items.slice();
+    startSSE(requestId, null, buffer.timestamp || new Date(), null, replay);
+    return true;
+}
+
+function switchSession(newSessionId) {
+    if (newSessionId === sessionId) {
+        if (currentView !== 'chat') navigateTo('chat');
+        return;
+    }
+
+    // Do NOT close active streams here: sessions run in parallel, so any
+    // in-flight reply for another session must keep streaming in the
+    // background (it self-guards against rendering into the foreign view).
+    // Switching back re-attaches and resumes live streaming.
+
+    sessionId = newSessionId;
+    updateEditButtonsState();
+    localStorage.setItem(SESSION_ID_KEY, sessionId);
+
+    historyPage = 0;
+    historyHasMore = false;
+    historyLoading = false;
+
+    messagesDiv.innerHTML = '';
+    loadHistory(1);
+    startPolling();
+
+    // Restore the send button to match this session's stream state, and if a
+    // reply is still streaming in the background, re-attach to resume showing
+    // it live (the user turn itself comes from history above).
+    const pendingReq = sessionActiveRequest[sessionId];
+    if (pendingReq) {
+        setSendBtnCancelMode(pendingReq);
+        _reattachStream(sessionId);
+    } else {
+        resetSendBtnSendMode();
+    }
+
+    document.querySelectorAll('.session-item').forEach(el => {
+        el.classList.toggle('active', el.dataset.sessionId === sessionId);
+    });
+
+    if (_isMobileView()) closeSessionPanel();
+    if (currentView !== 'chat') navigateTo('chat');
+}
+
+// In-place rename a session title: replace the title <span> with an <input>,
+// commit on Enter/blur, cancel on Escape. Persists via PUT /api/sessions/<id>.
+function renameSession(sid) {
+    const item = document.querySelector(`.session-item[data-session-id="${sid}"]`);
+    if (!item) return;
+    const titleEl = item.querySelector('.session-title');
+    if (!titleEl || item.querySelector('.session-title-input')) return;
+
+    const oldTitle = titleEl.textContent;
+
+    const input = document.createElement('input');
+    input.type = 'text';
+    input.className = 'session-title-input';
+    input.value = oldTitle;
+    input.maxLength = 100;
+
+    // Avoid switching session while interacting with the input
+    const stop = e => e.stopPropagation();
+    input.addEventListener('click', stop);
+    input.addEventListener('mousedown', stop);
+
+    titleEl.replaceWith(input);
+    input.focus();
+    input.select();
+
+    let done = false;
+
+    const restore = (title) => {
+        if (done) return;
+        done = true;
+        const span = document.createElement('span');
+        span.className = 'session-title';
+        span.title = title;
+        span.textContent = title;
+        input.replaceWith(span);
+    };
+
+    const commit = () => {
+        if (done) return;
+        const newTitle = input.value.trim();
+        if (!newTitle || newTitle === oldTitle) {
+            restore(oldTitle);
+            return;
+        }
+        // Optimistically show the new title, then persist.
+        restore(newTitle);
+        fetch(`/api/sessions/${encodeURIComponent(sid)}`, {
+            method: 'PUT',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ title: newTitle })
+        })
+            .then(r => r.json())
+            .then(data => {
+                if (data.status !== 'success') {
+                    // Revert UI on failure
+                    const span = item.querySelector('.session-title');
+                    if (span) {
+                        span.title = oldTitle;
+                        span.textContent = oldTitle;
+                    }
+                }
+            })
+            .catch(() => {
+                const span = item.querySelector('.session-title');
+                if (span) {
+                    span.title = oldTitle;
+                    span.textContent = oldTitle;
+                }
+            });
+    };
+
+    input.addEventListener('keydown', (e) => {
+        if (e.key === 'Enter') { e.preventDefault(); commit(); }
+        else if (e.key === 'Escape') { e.preventDefault(); restore(oldTitle); }
+    });
+    input.addEventListener('blur', commit);
+}
+
+function deleteSession(sid) {
+    showConfirmModal(t('delete_session_title'), t('delete_session_confirm'), () => {
+        // Before deleting, find the next real session to fall back to when the
+        // current one is removed (the sibling item in the list, which is sorted
+        // newest-first). Falls back to the welcome screen if none remain.
+        const nextSid = sid === sessionId ? _findNextSessionId(sid) : null;
+
+        fetch(`/api/sessions/${encodeURIComponent(sid)}`, { method: 'DELETE' })
+            .then(r => r.json())
+            .then(data => {
+                if (data.status !== 'success') return;
+                if (sid !== sessionId) {
+                    loadSessionList();
+                    return;
+                }
+                if (nextSid) {
+                    // Switch to an existing session; refresh the list afterwards
+                    // so the deleted item disappears.
+                    switchSession(nextSid);
+                    loadSessionList();
+                } else {
+                    // No other sessions: reset to a fresh empty session without
+                    // inserting an optimistic placeholder (it has no backend
+                    // record and would be an empty, undeletable item).
+                    newChat(false);
+                }
+            })
+            .catch(() => {});
+    });
+}
+
+// Pick the session to show after deleting `sid` (the current session): prefer
+// the next item below it in the list, otherwise the previous one. Returns null
+// if no other session exists.
+function _findNextSessionId(sid) {
+    const items = Array.from(document.querySelectorAll('.session-item[data-session-id]'));
+    const idx = items.findIndex(el => el.dataset.sessionId === sid);
+    if (idx === -1) {
+        const other = items.find(el => el.dataset.sessionId !== sid);
+        return other ? other.dataset.sessionId : null;
+    }
+    const next = items[idx + 1] || items[idx - 1];
+    return next ? next.dataset.sessionId : null;
+}
+
+function showConfirmModal(title, message, onConfirm) {
+    let overlay = document.getElementById('confirm-modal-overlay');
+    if (overlay) overlay.remove();
+
+    overlay = document.createElement('div');
+    overlay.id = 'confirm-modal-overlay';
+    overlay.className = 'confirm-overlay';
+
+    const modal = document.createElement('div');
+    modal.className = 'confirm-modal';
+    modal.innerHTML = `
+        <div class="confirm-title">${escapeHtml(title)}</div>
+        <div class="confirm-message">${escapeHtml(message)}</div>
+        <div class="confirm-actions">
+            <button class="confirm-btn confirm-btn-cancel">${t('confirm_cancel')}</button>
+            <button class="confirm-btn confirm-btn-ok">${t('confirm_yes')}</button>
+        </div>
+    `;
+    overlay.appendChild(modal);
+    document.body.appendChild(overlay);
+
+    requestAnimationFrame(() => overlay.classList.add('visible'));
+
+    const close = () => {
+        overlay.classList.remove('visible');
+        setTimeout(() => overlay.remove(), 200);
+    };
+
+    overlay.addEventListener('click', (e) => { if (e.target === overlay) close(); });
+    modal.querySelector('.confirm-btn-cancel').addEventListener('click', close);
+    modal.querySelector('.confirm-btn-ok').addEventListener('click', () => {
+        close();
+        onConfirm();
+    });
+}
+
+function clearContext() {
+    fetch(`/api/sessions/${encodeURIComponent(sessionId)}/clear_context`, { method: 'POST' })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status !== 'success') return;
+            // Insert a visual divider in the chat
+            const divider = document.createElement('div');
+            divider.className = 'context-divider';
+            divider.innerHTML = `<span>${t('context_cleared')}</span>`;
+            messagesDiv.appendChild(divider);
+            scrollChatToBottom();
+        })
+        .catch(() => {});
+}
+
+function generateSessionTitle(sid, userMsg, assistantReply) {
+    fetch(`/api/sessions/${encodeURIComponent(sid)}/generate_title`, {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ user_message: userMsg, assistant_reply: assistantReply }),
+    })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status === 'success' && sessionPanelOpen) {
+                loadSessionList();
+            }
+        })
+        .catch(() => {});
+}
+
+// =====================================================================
+// Utilities
+// =====================================================================
+function formatTime(date) {
+    const now = new Date();
+    const sameDay = date.getFullYear() === now.getFullYear()
+        && date.getMonth() === now.getMonth()
+        && date.getDate() === now.getDate();
+    const time = date.toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' });
+    if (sameDay) return time;
+    const m = String(date.getMonth() + 1).padStart(2, '0');
+    const d = String(date.getDate()).padStart(2, '0');
+    if (date.getFullYear() === now.getFullYear()) return `${m}-${d} ${time}`;
+    return `${date.getFullYear()}-${m}-${d} ${time}`;
+}
+
+function escapeHtml(str) {
+    const div = document.createElement('div');
+    div.appendChild(document.createTextNode(str));
+    return div.innerHTML;
+}
+
+function ChannelsHandler_maskSecret(val) {
+    if (!val || val.length <= 8) return val;
+    return val.slice(0, 4) + '*'.repeat(val.length - 8) + val.slice(-4);
+}
+
+function formatToolArgs(args) {
+    if (!args || Object.keys(args).length === 0) return '(none)';
+    try {
+        return escapeHtml(JSON.stringify(args, null, 2));
+    } catch (_) {
+        return escapeHtml(String(args));
+    }
+}
+
+function scrollChatToBottom(force) {
+    if (force || _autoScrollEnabled) {
+        messagesDiv.scrollTop = messagesDiv.scrollHeight;
+    }
+}
+
+function _updateScrollToBottomBtn() {
+    const btn = document.getElementById('scroll-to-bottom-btn');
+    if (!btn) return;
+    const distFromBottom = messagesDiv.scrollHeight - messagesDiv.scrollTop - messagesDiv.clientHeight;
+    btn.classList.toggle('hidden', distFromBottom <= _SCROLL_THRESHOLD);
+}
+
+function applyHighlighting(container) {
+    const root = container || document;
+    setTimeout(() => {
+        const hljsLib = getHljs();
+        root.querySelectorAll('pre code').forEach(block => {
+            if (!block.classList.contains('hljs')) {
+                hljsLib.highlightElement(block);
+            }
+        });
+        // Add language labels and copy buttons to code blocks
+        _addCodeBlockHeaders(root);
+    }, 0);
+}
+
+// =====================================================================
+// Config View
+// =====================================================================
+let configProviders = {};
+let configApiBases = {};
+let configApiKeys = {};
+let configCurrentModel = '';
+let cfgProviderValue = '';
+let cfgModelValue = '';
+
+// --- Custom dropdown helper ---
+function initDropdown(el, options, selectedValue, onChange, opts) {
+    // opts.placeholder: when set AND selectedValue is empty, render that text
+    // in a dim style instead of auto-selecting options[0]. Useful for
+    // "pick or empty" capabilities (asr / embedding) where we want the
+    // user to make an explicit choice.
+    opts = opts || {};
+    const textEl = el.querySelector('.cfg-dropdown-text');
+    const menuEl = el.querySelector('.cfg-dropdown-menu');
+    const selEl = el.querySelector('.cfg-dropdown-selected');
+
+    el._ddValue = selectedValue || '';
+    el._ddOnChange = onChange;
+
+    function render() {
+        menuEl.innerHTML = '';
+        options.forEach(opt => {
+            const item = document.createElement('div');
+            item.className = 'cfg-dropdown-item' + (opt.value === el._ddValue ? ' active' : '');
+            item.dataset.value = opt.value;
+            // Hint is an optional dim secondary label rendered on the right
+            // side of the row (e.g. friendly brand name next to a technical
+            // model id). When absent the row degrades to the original
+            // single-string layout.
+            if (opt.hint) {
+                const labelEl = document.createElement('span');
+                labelEl.className = 'cfg-dropdown-label';
+                labelEl.textContent = opt.label;
+                const hintEl = document.createElement('span');
+                hintEl.className = 'cfg-dropdown-hint';
+                hintEl.textContent = opt.hint;
+                item.appendChild(labelEl);
+                item.appendChild(hintEl);
+            } else {
+                item.textContent = opt.label;
+            }
+            item.addEventListener('click', (e) => {
+                e.stopPropagation();
+                el._ddValue = opt.value;
+                textEl.textContent = opt.label;
+                menuEl.querySelectorAll('.cfg-dropdown-item').forEach(i => i.classList.remove('active'));
+                item.classList.add('active');
+                el.classList.remove('open');
+                if (el._ddOnChange) el._ddOnChange(opt.value);
+            });
+            menuEl.appendChild(item);
+        });
+        const sel = options.find(o => o.value === el._ddValue);
+        if (sel) {
+            textEl.textContent = sel.label;
+            textEl.classList.remove('text-slate-400', 'dark:text-slate-500');
+        } else if (opts.placeholder && !el._ddValue) {
+            // No selection yet — show the placeholder in muted style.
+            // Do NOT write a fallback value, so the dropdown stays
+            // "unsaved" until the user explicitly picks.
+            textEl.textContent = opts.placeholder;
+            textEl.classList.add('text-slate-400', 'dark:text-slate-500');
+        } else {
+            textEl.textContent = options[0] ? options[0].label : '--';
+            textEl.classList.remove('text-slate-400', 'dark:text-slate-500');
+            if (options[0]) el._ddValue = options[0].value;
+        }
+    }
+
+    render();
+
+    if (!el._ddBound) {
+        selEl.addEventListener('click', (e) => {
+            e.stopPropagation();
+            document.querySelectorAll('.cfg-dropdown.open').forEach(d => { if (d !== el) d.classList.remove('open'); });
+            el.classList.toggle('open');
+        });
+        el._ddBound = true;
+    }
+}
+
+document.addEventListener('click', () => {
+    document.querySelectorAll('.cfg-dropdown.open').forEach(d => d.classList.remove('open'));
+});
+
+function getDropdownValue(el) { return el._ddValue || ''; }
+
+// --- Config init ---
+function initConfigView(data) {
+    configProviders = data.providers || {};
+    configApiBases = data.api_bases || {};
+    configApiKeys = data.api_keys || {};
+    configCurrentModel = data.model || '';
+
+    const providerEl = document.getElementById('cfg-provider');
+    const providerOpts = Object.entries(configProviders).map(([pid, p]) => ({ value: pid, label: localizedLabel(p.label) }));
+
+    // if use_linkai is enabled, always select linkai as the provider
+    // Otherwise prefer bot_type from config, fall back to model-based detection
+    const detected = data.use_linkai ? 'linkai'
+        : (data.bot_type && configProviders[data.bot_type] ? data.bot_type : detectProvider(configCurrentModel));
+    cfgProviderValue = detected || (providerOpts[0] ? providerOpts[0].value : '');
+
+    initDropdown(providerEl, providerOpts, cfgProviderValue, onProviderChange);
+
+    onProviderChange(cfgProviderValue);
+    syncModelSelection(configCurrentModel);
+
+    document.getElementById('cfg-max-tokens').value = data.agent_max_context_tokens || 50000;
+    document.getElementById('cfg-max-turns').value = data.agent_max_context_turns || 20;
+    document.getElementById('cfg-max-steps').value = data.agent_max_steps || 20;
+    document.getElementById('cfg-enable-thinking').checked = data.enable_thinking === true;
+    document.getElementById('cfg-self-evolution').checked = data.self_evolution_enabled === true;
+
+    // Reflect the current UI language (already resolved, may include the user's
+    // local choice) on the selector so it stays in sync with the top-right toggle.
+    const langSel = document.getElementById('cfg-lang-select');
+    if (langSel) {
+        initDropdown(
+            langSel,
+            [{ value: 'zh', label: '简体中文' }, { value: 'zh-Hant', label: '繁體中文' }, { value: 'en', label: 'English' }],
+            currentLang,
+            (val) => setLanguage(val)
+        );
+    }
+
+    const pwdInput = document.getElementById('cfg-password');
+    const maskedPwd = data.web_password_masked || '';
+    pwdInput.value = maskedPwd;
+    pwdInput.dataset.masked = maskedPwd ? '1' : '';
+    pwdInput.dataset.maskedVal = maskedPwd;
+    pwdInput.classList.toggle('cfg-key-masked', !!maskedPwd);
+
+    if (maskedPwd) {
+        pwdInput.placeholder = '••••••••';
+    } else {
+        pwdInput.placeholder = '';
+    }
+
+    if (!pwdInput._cfgBound) {
+        pwdInput.addEventListener('focus', function() {
+            if (this.dataset.masked === '1') {
+                this.value = '';
+                this.dataset.masked = '';
+                this.classList.remove('cfg-key-masked');
+            }
+        });
+        pwdInput.addEventListener('input', function() {
+            this.dataset.masked = '';
+        });
+        pwdInput._cfgBound = true;
+    }
+}
+
+function detectProvider(model) {
+    if (!model) return Object.keys(configProviders)[0] || '';
+    for (const [pid, p] of Object.entries(configProviders)) {
+        if (pid === 'linkai') continue;
+        if (p.models && p.models.includes(model)) return pid;
+    }
+    return Object.keys(configProviders)[0] || '';
+}
+
+function onProviderChange(pid) {
+    cfgProviderValue = pid || getDropdownValue(document.getElementById('cfg-provider'));
+    const p = configProviders[cfgProviderValue];
+    if (!p) return;
+
+    const customTip = document.getElementById('cfg-custom-tip');
+    if (customTip) customTip.classList.toggle('hidden', cfgProviderValue !== 'custom');
+
+    const modelEl = document.getElementById('cfg-model-select');
+    const modelOpts = (p.models || []).map(m => ({ value: m, label: m }));
+    modelOpts.push({ value: '__custom__', label: t('config_custom_option') });
+
+    initDropdown(modelEl, modelOpts, modelOpts[0] ? modelOpts[0].value : '', onModelSelectChange);
+
+    // API Key
+    const keyField = p.api_key_field;
+    const keyWrap = document.getElementById('cfg-api-key-wrap');
+    const keyInput = document.getElementById('cfg-api-key');
+    if (keyField) {
+        keyWrap.classList.remove('hidden');
+        keyInput.classList.add('cfg-key-masked');
+        const maskedVal = configApiKeys[keyField] || '';
+        keyInput.value = maskedVal;
+        keyInput.dataset.field = keyField;
+        keyInput.dataset.masked = maskedVal ? '1' : '';
+        keyInput.dataset.maskedVal = maskedVal;
+        const toggleIcon = document.querySelector('#cfg-api-key-toggle i');
+        if (toggleIcon) toggleIcon.className = 'fas fa-eye text-xs';
+
+        if (!keyInput._cfgBound) {
+            keyInput.addEventListener('focus', function() {
+                if (this.dataset.masked === '1') {
+                    this.value = '';
+                    this.dataset.masked = '';
+                    this.classList.remove('cfg-key-masked');
+                }
+            });
+            keyInput.addEventListener('blur', function() {
+                if (!this.value.trim() && this.dataset.maskedVal) {
+                    this.value = this.dataset.maskedVal;
+                    this.dataset.masked = '1';
+                    this.classList.add('cfg-key-masked');
+                }
+            });
+            keyInput.addEventListener('input', function() {
+                this.dataset.masked = '';
+            });
+            keyInput._cfgBound = true;
+        }
+    } else {
+        keyWrap.classList.add('hidden');
+        keyInput.value = '';
+        keyInput.dataset.field = '';
+    }
+
+    // API Base
+    const apiBaseInput = document.getElementById('cfg-api-base');
+    if (p.api_base_key) {
+        document.getElementById('cfg-api-base-wrap').classList.remove('hidden');
+        apiBaseInput.value = configApiBases[p.api_base_key] || p.api_base_default || '';
+        // Hint the version-path tail (e.g. /v1) so users are reminded to
+        // include it themselves. We don't auto-rewrite anything server-side.
+        apiBaseInput.placeholder = p.api_base_placeholder || 'https://...';
+    } else {
+        document.getElementById('cfg-api-base-wrap').classList.add('hidden');
+        apiBaseInput.value = '';
+        apiBaseInput.placeholder = 'https://...';
+    }
+
+    onModelSelectChange(modelOpts[0] ? modelOpts[0].value : '');
+}
+
+function onModelSelectChange(val) {
+    cfgModelValue = val || getDropdownValue(document.getElementById('cfg-model-select'));
+    const customWrap = document.getElementById('cfg-model-custom-wrap');
+    if (cfgModelValue === '__custom__') {
+        customWrap.classList.remove('hidden');
+        document.getElementById('cfg-model-custom').focus();
+    } else {
+        customWrap.classList.add('hidden');
+        document.getElementById('cfg-model-custom').value = '';
+    }
+}
+
+function syncModelSelection(model) {
+    const p = configProviders[cfgProviderValue];
+    if (!p) return;
+
+    const modelEl = document.getElementById('cfg-model-select');
+    if (p.models && p.models.includes(model)) {
+        const modelOpts = (p.models || []).map(m => ({ value: m, label: m }));
+        modelOpts.push({ value: '__custom__', label: t('config_custom_option') });
+        initDropdown(modelEl, modelOpts, model, onModelSelectChange);
+        cfgModelValue = model;
+        document.getElementById('cfg-model-custom-wrap').classList.add('hidden');
+    } else {
+        cfgModelValue = '__custom__';
+        const modelOpts = (p.models || []).map(m => ({ value: m, label: m }));
+        modelOpts.push({ value: '__custom__', label: t('config_custom_option') });
+        initDropdown(modelEl, modelOpts, '__custom__', onModelSelectChange);
+        document.getElementById('cfg-model-custom-wrap').classList.remove('hidden');
+        document.getElementById('cfg-model-custom').value = model;
+    }
+}
+
+function getSelectedModel() {
+    if (cfgModelValue === '__custom__') {
+        return document.getElementById('cfg-model-custom').value.trim();
+    }
+    return cfgModelValue;
+}
+
+function toggleApiKeyVisibility() {
+    const input = document.getElementById('cfg-api-key');
+    const icon = document.querySelector('#cfg-api-key-toggle i');
+    if (input.classList.contains('cfg-key-masked')) {
+        input.classList.remove('cfg-key-masked');
+        icon.className = 'fas fa-eye-slash text-xs';
+    } else {
+        input.classList.add('cfg-key-masked');
+        icon.className = 'fas fa-eye text-xs';
+    }
+}
+
+function showStatus(elId, msgKey, isError) {
+    const el = document.getElementById(elId);
+    el.textContent = t(msgKey);
+    el.classList.toggle('text-red-500', !!isError);
+    el.classList.toggle('text-primary-500', !isError);
+    el.classList.remove('opacity-0');
+    // Warning messages (errors) should stay visible, success messages auto-hide
+    if (!isError) {
+        setTimeout(() => el.classList.add('opacity-0'), 2500);
+    }
+}
+
+function saveModelConfig() {
+    const model = getSelectedModel();
+    if (!model) return;
+
+    const updates = { model: model };
+    const p = configProviders[cfgProviderValue];
+    updates.use_linkai = (cfgProviderValue === 'linkai');
+    if (cfgProviderValue === 'linkai') {
+        updates.bot_type = '';
+    } else {
+        updates.bot_type = cfgProviderValue;
+    }
+    if (p && p.api_base_key) {
+        const base = document.getElementById('cfg-api-base').value.trim();
+        if (base) updates[p.api_base_key] = base;
+    }
+    if (p && p.api_key_field) {
+        const keyInput = document.getElementById('cfg-api-key');
+        const rawVal = keyInput.value.trim();
+        if (rawVal && keyInput.dataset.masked !== '1') {
+            updates[p.api_key_field] = rawVal;
+        }
+    }
+
+    const btn = document.getElementById('cfg-model-save');
+    btn.disabled = true;
+    fetch('/config', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ updates })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            configCurrentModel = model;
+            if (data.applied) {
+                const keyInput = document.getElementById('cfg-api-key');
+                Object.entries(data.applied).forEach(([k, v]) => {
+                    if (k === 'model') return;
+                    if (k.includes('api_key')) {
+                        const masked = v.length > 8
+                            ? v.substring(0, 4) + '*'.repeat(v.length - 8) + v.substring(v.length - 4)
+                            : v;
+                        configApiKeys[k] = masked;
+                        if (keyInput.dataset.field === k) {
+                            keyInput.value = masked;
+                            keyInput.dataset.masked = '1';
+                            keyInput.dataset.maskedVal = masked;
+                            keyInput.classList.add('cfg-key-masked');
+                            const toggleIcon = document.querySelector('#cfg-api-key-toggle i');
+                            if (toggleIcon) toggleIcon.className = 'fas fa-eye text-xs';
+                        }
+                    } else {
+                        configApiBases[k] = v;
+                    }
+                });
+            }
+            showStatus('cfg-model-status', 'config_saved', false);
+        } else {
+            showStatus('cfg-model-status', 'config_save_error', true);
+        }
+    })
+    .catch(() => showStatus('cfg-model-status', 'config_save_error', true))
+    .finally(() => { btn.disabled = false; });
+}
+
+function saveAgentConfig() {
+    const updates = {
+        agent_max_context_tokens: parseInt(document.getElementById('cfg-max-tokens').value) || 50000,
+        agent_max_context_turns: parseInt(document.getElementById('cfg-max-turns').value) || 20,
+        agent_max_steps: parseInt(document.getElementById('cfg-max-steps').value) || 20,
+        enable_thinking: document.getElementById('cfg-enable-thinking').checked,
+        self_evolution_enabled: document.getElementById('cfg-self-evolution').checked,
+    };
+
+    const btn = document.getElementById('cfg-agent-save');
+    btn.disabled = true;
+    fetch('/config', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ updates })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            showStatus('cfg-agent-status', 'config_saved', false);
+        } else {
+            showStatus('cfg-agent-status', 'config_save_error', true);
+        }
+    })
+    .catch(() => showStatus('cfg-agent-status', 'config_save_error', true))
+    .finally(() => { btn.disabled = false; });
+}
+
+function savePasswordConfig() {
+    const input = document.getElementById('cfg-password');
+    if (input.dataset.masked === '1') {
+        showStatus('cfg-password-status', 'config_saved', false);
+        return;
+    }
+    const newPwd = input.value.trim();
+    const btn = document.getElementById('cfg-password-save');
+    btn.disabled = true;
+    fetch('/config', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ updates: { web_password: newPwd } })
+    })
+    .then(r => r.json())
+    .then(data => {
+        console.log('[Password Config] Response:', data); // Debug
+        if (data.status === 'success') {
+            if (newPwd) {
+                showStatus('cfg-password-status', 'config_password_changed', false);
+                // Mark as masked so user needs to re-enter to change again
+                input.dataset.masked = '1';
+                input.dataset.maskedVal = newPwd;
+                input.value = '••••••••';
+                input.classList.add('cfg-key-masked');
+                
+                // Show logout button since password is now enabled
+                const logoutBtn = document.getElementById('logout-btn-header');
+                if (logoutBtn) logoutBtn.classList.remove('hidden');
+            } else {
+                input.dataset.masked = '';
+                input.dataset.maskedVal = '';
+                input.classList.remove('cfg-key-masked');
+                
+                // Show security warning if password was cleared with public host
+                if (data.warning === 'password_cleared_with_public_host') {
+                    showStatus('cfg-password-status', 'config_password_security_warning', true);
+                } else {
+                    showStatus('cfg-password-status', 'config_password_cleared', false);
+                }
+                
+                const logoutBtn = document.getElementById('logout-btn-header');
+                if (logoutBtn) logoutBtn.classList.add('hidden');
+            }
+        } else {
+            showStatus('cfg-password-status', 'config_save_error', true);
+        }
+    })
+    .catch(() => showStatus('cfg-password-status', 'config_save_error', true))
+    .finally(() => { btn.disabled = false; });
+}
+
+function loadConfigView() {
+    fetch('/config').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        appConfig = data;
+        initConfigView(data);
+    }).catch(() => {});
+}
+
+// =====================================================================
+// Skills View
+// =====================================================================
+let toolsLoaded = false;
+
+const TOOL_ICONS = {
+    bash: 'fa-terminal',
+    edit: 'fa-pen-to-square',
+    read: 'fa-file-lines',
+    write: 'fa-file-pen',
+    ls: 'fa-folder-open',
+    send: 'fa-paper-plane',
+    web_search: 'fa-magnifying-glass',
+    browser: 'fa-globe',
+    env_config: 'fa-key',
+    scheduler: 'fa-clock',
+    memory_get: 'fa-brain',
+    memory_search: 'fa-brain',
+};
+
+function getToolIcon(name) {
+    return TOOL_ICONS[name] || 'fa-wrench';
+}
+
+function loadSkillsView() {
+    loadToolsSection();
+    loadSkillsSection();
+}
+
+function loadToolsSection() {
+    if (toolsLoaded) return;
+    const emptyEl = document.getElementById('tools-empty');
+    const listEl = document.getElementById('tools-list');
+    const badge = document.getElementById('tools-count-badge');
+
+    fetch('/api/tools').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const tools = data.tools || [];
+        emptyEl.classList.add('hidden');
+        if (tools.length === 0) {
+            emptyEl.classList.remove('hidden');
+            emptyEl.innerHTML = `<span class="text-sm text-slate-400 dark:text-slate-500">${currentLang === 'zh' ? '暂无内置工具' : 'No built-in tools'}</span>`;
+            return;
+        }
+        badge.textContent = tools.length;
+        badge.classList.remove('hidden');
+        listEl.innerHTML = '';
+        tools.forEach(tool => {
+            const card = document.createElement('div');
+            card.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-4 flex items-start gap-3';
+            card.innerHTML = `
+                <div class="w-9 h-9 rounded-lg bg-blue-50 dark:bg-blue-900/20 flex items-center justify-center flex-shrink-0">
+                    <i class="fas ${getToolIcon(tool.name)} text-blue-500 dark:text-blue-400 text-sm"></i>
+                </div>
+                <div class="flex-1 min-w-0">
+                    <div class="flex items-center gap-2">
+                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200 font-mono">${escapeHtml(tool.name)}</span>
+                    </div>
+                    <p class="text-xs text-slate-400 dark:text-slate-500 mt-1 line-clamp-2">${escapeHtml(tool.description || '--')}</p>
+                </div>`;
+            listEl.appendChild(card);
+        });
+        listEl.classList.remove('hidden');
+        toolsLoaded = true;
+    }).catch(() => {
+        emptyEl.classList.remove('hidden');
+        emptyEl.innerHTML = `<span class="text-sm text-slate-400 dark:text-slate-500">${currentLang === 'zh' ? '加载失败' : 'Failed to load'}</span>`;
+    });
+}
+
+function loadSkillsSection() {
+    const emptyEl = document.getElementById('skills-empty');
+    const listEl = document.getElementById('skills-list');
+    const badge = document.getElementById('skills-count-badge');
+
+    fetch('/api/skills').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const skills = data.skills || [];
+        if (skills.length === 0) {
+            const p = emptyEl.querySelector('p');
+            if (p) p.textContent = currentLang === 'zh' ? '暂无技能' : 'No skills found';
+            return;
+        }
+        badge.textContent = skills.length;
+        badge.classList.remove('hidden');
+        emptyEl.classList.add('hidden');
+        listEl.innerHTML = '';
+
+        skills.forEach(sk => {
+            const card = document.createElement('div');
+            card.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-4 flex items-start gap-3 transition-opacity';
+            card.dataset.skillName = sk.name;
+            card.dataset.skillDesc = sk.description || '';
+            card.dataset.enabled = sk.enabled ? '1' : '0';
+            renderSkillCard(card, sk);
+            listEl.appendChild(card);
+        });
+    }).catch(() => {});
+}
+
+function renderSkillCard(card, sk) {
+    const enabled = sk.enabled;
+    const iconColor = enabled ? 'text-primary-400' : 'text-slate-300 dark:text-slate-600';
+    const trackClass = enabled
+        ? 'bg-primary-400'
+        : 'bg-slate-200 dark:bg-slate-700';
+    const thumbTranslate = enabled ? 'translate-x-3' : 'translate-x-0.5';
+    card.innerHTML = `
+        <div class="w-9 h-9 rounded-lg bg-amber-50 dark:bg-amber-900/20 flex items-center justify-center flex-shrink-0">
+            <i class="fas fa-bolt ${iconColor} text-sm"></i>
+        </div>
+        <div class="flex-1 min-w-0">
+            <div class="flex items-center gap-2 mb-1">
+                <span class="font-medium text-sm text-slate-700 dark:text-slate-200 truncate flex-1">${escapeHtml(sk.display_name || sk.name)}</span>
+                <button
+                    role="switch"
+                    aria-checked="${enabled}"
+                    onclick="toggleSkill('${escapeHtml(sk.name)}', ${enabled})"
+                    class="relative inline-flex h-4 w-7 flex-shrink-0 cursor-pointer rounded-full transition-colors duration-200 ease-in-out focus:outline-none ${trackClass}"
+                    title="${enabled ? (currentLang === 'zh' ? '点击禁用' : 'Click to disable') : (currentLang === 'zh' ? '点击启用' : 'Click to enable')}"
+                >
+                    <span class="inline-block h-3 w-3 mt-0.5 rounded-full bg-white shadow transform transition-transform duration-200 ease-in-out ${thumbTranslate}"></span>
+                </button>
+            </div>
+            <p class="text-xs text-slate-400 dark:text-slate-500 line-clamp-2">${escapeHtml(sk.description || '--')}</p>
+        </div>`;
+}
+
+function toggleSkill(name, currentlyEnabled) {
+    const action = currentlyEnabled ? 'close' : 'open';
+    const card = document.querySelector(`[data-skill-name="${CSS.escape(name)}"]`);
+    if (card) card.style.opacity = '0.5';
+
+    fetch('/api/skills', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action, name })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            if (card) {
+                const desc = card.dataset.skillDesc || '';
+                card.dataset.enabled = currentlyEnabled ? '0' : '1';
+                card.style.opacity = '1';
+                renderSkillCard(card, { name, description: desc, enabled: !currentlyEnabled });
+            }
+        } else {
+            if (card) card.style.opacity = '1';
+            alert(currentLang === 'zh' ? '操作失败，请稍后再试' : 'Operation failed, please try again');
+        }
+    })
+    .catch(() => {
+        if (card) card.style.opacity = '1';
+        alert(currentLang === 'zh' ? '操作失败，请稍后再试' : 'Operation failed, please try again');
+    });
+}
+
+// =====================================================================
+// Memory View
+// =====================================================================
+let memoryPage = 1;
+let memoryCategory = 'memory';   // 'memory' | 'evolution'
+const memoryPageSize = 10;
+
+function switchMemoryTab(tab) {
+    document.querySelectorAll('.memory-tab').forEach(el => el.classList.remove('active'));
+    document.getElementById('memory-tab-' + tab).classList.add('active');
+    // The "dreams" tab now surfaces self-evolution logs (merged with dream diaries).
+    memoryCategory = tab === 'dreams' ? 'evolution' : 'memory';
+    loadMemoryView(1);
+}
+
+function loadMemoryView(page) {
+    page = page || 1;
+    memoryPage = page;
+    fetch(`/api/memory?page=${page}&page_size=${memoryPageSize}&category=${memoryCategory}`).then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const emptyEl = document.getElementById('memory-empty');
+        const listEl = document.getElementById('memory-list');
+        const files = data.list || [];
+        const total = data.total || 0;
+
+        if (total === 0) {
+            const emptyIcon = emptyEl.querySelector('i');
+            const emptyTitle = emptyEl.querySelector('p');
+            if (memoryCategory === 'evolution') {
+                emptyIcon.className = 'fas fa-seedling text-emerald-400 text-xl';
+                emptyTitle.textContent = currentLang === 'zh' ? '暂无进化记录' : 'No evolution records yet';
+            } else {
+                emptyIcon.className = 'fas fa-brain text-purple-400 text-xl';
+                emptyTitle.textContent = currentLang === 'zh' ? '暂无记忆文件' : 'No memory files';
+            }
+            emptyEl.classList.remove('hidden');
+            listEl.classList.add('hidden');
+            return;
+        }
+        emptyEl.classList.add('hidden');
+        listEl.classList.remove('hidden');
+
+        const tbody = document.getElementById('memory-table-body');
+        tbody.innerHTML = '';
+        files.forEach(f => {
+            const tr = document.createElement('tr');
+            tr.className = 'border-b border-slate-100 dark:border-white/5 hover:bg-slate-50 dark:hover:bg-white/5 cursor-pointer transition-colors';
+            // In the merged evolution tab, resolve each file by its own origin
+            // (evolution logs vs dream diaries live in different dirs).
+            const fileCategory = (f.type === 'dream' || f.type === 'evolution') ? f.type : memoryCategory;
+            tr.onclick = () => openMemoryFile(f.filename, fileCategory);
+            let typeLabel;
+            if (f.type === 'global') {
+                typeLabel = '<span class="px-2 py-0.5 rounded-full text-xs bg-primary-50 dark:bg-primary-900/30 text-primary-600 dark:text-primary-400">Global</span>';
+            } else if (f.type === 'evolution') {
+                typeLabel = '<span class="px-2 py-0.5 rounded-full text-xs bg-emerald-50 dark:bg-emerald-900/30 text-emerald-600 dark:text-emerald-400">Evolution</span>';
+            } else if (f.type === 'dream') {
+                typeLabel = '<span class="px-2 py-0.5 rounded-full text-xs bg-violet-50 dark:bg-violet-900/30 text-violet-600 dark:text-violet-400">Dream</span>';
+            } else {
+                typeLabel = '<span class="px-2 py-0.5 rounded-full text-xs bg-blue-50 dark:bg-blue-900/30 text-blue-600 dark:text-blue-400">Daily</span>';
+            }
+            const sizeStr = f.size < 1024 ? f.size + ' B' : (f.size / 1024).toFixed(1) + ' KB';
+            tr.innerHTML = `
+                <td class="px-4 py-3 text-sm font-mono text-slate-700 dark:text-slate-200">${escapeHtml(f.filename)}</td>
+                <td class="px-4 py-3 text-sm">${typeLabel}</td>
+                <td class="px-4 py-3 text-sm text-slate-500 dark:text-slate-400">${sizeStr}</td>
+                <td class="px-4 py-3 text-sm text-slate-500 dark:text-slate-400">${escapeHtml(f.updated_at)}</td>`;
+            tbody.appendChild(tr);
+        });
+
+        // Pagination
+        const totalPages = Math.ceil(total / memoryPageSize);
+        const pagEl = document.getElementById('memory-pagination');
+        if (totalPages <= 1) { pagEl.innerHTML = ''; return; }
+        let pagHtml = `<span>${page} / ${totalPages}</span><div class="flex gap-2">`;
+        if (page > 1) pagHtml += `<button onclick="loadMemoryView(${page - 1})" class="px-3 py-1 rounded-lg border border-slate-200 dark:border-white/10 hover:bg-slate-100 dark:hover:bg-white/10 text-xs">Prev</button>`;
+        if (page < totalPages) pagHtml += `<button onclick="loadMemoryView(${page + 1})" class="px-3 py-1 rounded-lg border border-slate-200 dark:border-white/10 hover:bg-slate-100 dark:hover:bg-white/10 text-xs">Next</button>`;
+        pagHtml += '</div>';
+        pagEl.innerHTML = pagHtml;
+    }).catch(() => {});
+}
+
+function openMemoryFile(filename, category) {
+    category = category || 'memory';
+    fetch(`/api/memory/content?filename=${encodeURIComponent(filename)}&category=${category}`).then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        document.getElementById('memory-panel-list').classList.add('hidden');
+        const panel = document.getElementById('memory-panel-viewer');
+        document.getElementById('memory-viewer-title').textContent = filename;
+        document.getElementById('memory-viewer-content').innerHTML = renderMarkdown(data.content || '');
+        panel.classList.remove('hidden');
+        applyHighlighting(panel);
+    }).catch(() => {});
+}
+
+function closeMemoryViewer() {
+    document.getElementById('memory-panel-viewer').classList.add('hidden');
+    document.getElementById('memory-panel-list').classList.remove('hidden');
+}
+
+// =====================================================================
+// Custom Confirm Dialog
+// =====================================================================
+function showConfirmDialog({ title, message, okText, cancelText, onConfirm, hideCancel }) {
+    const overlay = document.getElementById('confirm-dialog-overlay');
+    document.getElementById('confirm-dialog-title').textContent = title || '';
+    document.getElementById('confirm-dialog-message').textContent = message || '';
+    document.getElementById('confirm-dialog-ok').textContent = okText || 'OK';
+    const cancelBtn = document.getElementById('confirm-dialog-cancel');
+    cancelBtn.textContent = cancelText || t('channels_cancel');
+    cancelBtn.classList.toggle('hidden', !!hideCancel);
+
+    function cleanup() {
+        overlay.classList.add('hidden');
+        okBtn.removeEventListener('click', onOk);
+        cancelBtn.removeEventListener('click', onCancel);
+        overlay.removeEventListener('click', onOverlayClick);
+    }
+    function onOk() { cleanup(); if (onConfirm) onConfirm(); }
+    function onCancel() { cleanup(); }
+    function onOverlayClick(e) { if (e.target === overlay) cleanup(); }
+
+    const okBtn = document.getElementById('confirm-dialog-ok');
+    okBtn.addEventListener('click', onOk);
+    cancelBtn.addEventListener('click', onCancel);
+    overlay.addEventListener('click', onOverlayClick);
+    overlay.classList.remove('hidden');
+}
+
+// =====================================================================
+// Models View
+// =====================================================================
+// Capability cards rendered on the Models page. Order matters — main model
+// comes first because it transitively decides defaults for vision and image.
+// Icon palette is grouped by capability family:
+//   - chat                       → primary (brand green; the "main" capability)
+//   - vision + image             → blue    (everything visual)
+//   - asr + tts                  → amber   (everything audio)
+//   - embedding                  → purple  (vectors)
+//   - search                     → orange  (retrieval)
+// Each card uses an explicit `iconClass` string so Tailwind's CDN JIT can
+// see the literal class names — dynamic `bg-${color}-50` strings would not
+// be picked up reliably.
+const MODELS_CAPABILITY_DEFS = [
+    { id: 'chat',      icon: 'fa-microchip',        editable: true,  needsModel: true,  titleKey: 'models_capability_chat',      descKey: 'models_capability_chat_desc',
+      iconChip: 'bg-primary-50 dark:bg-primary-900/30',  iconGlyph: 'text-primary-500' },
+    { id: 'vision',    icon: 'fa-eye',              editable: true,  needsModel: true,  titleKey: 'models_capability_vision',    descKey: 'models_capability_vision_desc',
+      iconChip: 'bg-blue-50 dark:bg-blue-900/30',        iconGlyph: 'text-blue-500' },
+    { id: 'image',     icon: 'fa-image',            editable: true,  needsModel: true,  titleKey: 'models_capability_image',     descKey: 'models_capability_image_desc',
+      iconChip: 'bg-blue-50 dark:bg-blue-900/30',        iconGlyph: 'text-blue-500' },
+    { id: 'asr',       icon: 'fa-microphone',       editable: true,  needsModel: true,  titleKey: 'models_capability_asr',       descKey: 'models_capability_asr_desc',
+      iconChip: 'bg-amber-50 dark:bg-amber-900/30',      iconGlyph: 'text-amber-500' },
+    { id: 'tts',       icon: 'fa-volume-high',      editable: true,  needsModel: true,  titleKey: 'models_capability_tts',       descKey: 'models_capability_tts_desc',
+      iconChip: 'bg-amber-50 dark:bg-amber-900/30',      iconGlyph: 'text-amber-500' },
+    { id: 'embedding', icon: 'fa-vector-square',    editable: true,  needsModel: true,  titleKey: 'models_capability_embedding', descKey: 'models_capability_embedding_desc',
+      iconChip: 'bg-purple-50 dark:bg-purple-900/30',    iconGlyph: 'text-purple-500' },
+    { id: 'search',    icon: 'fa-magnifying-glass', editable: true,  needsModel: false, titleKey: 'models_capability_search',    descKey: 'models_capability_search_desc',
+      iconChip: 'bg-orange-50 dark:bg-orange-900/30',    iconGlyph: 'text-orange-500' },
+];
+
+// Provider logos: when a real SVG exists under static/logos/<id>.svg we use
+// it; otherwise we fall back to a neutral monogram chip. SVGs are fetched
+// via <img> with a hidden onerror so layout stays stable when files are
+// absent. Vendors whose mark is rendered in pure (or near-pure) black are
+// listed in MODELS_PROVIDER_LOGO_DARK_INVERT — for those, we apply a CSS
+// invert filter in dark mode so the glyph stays visible against #1A1A1A.
+const MODELS_PROVIDER_LOGO_PATH = 'assets/logos';
+const MODELS_PROVIDER_LOGO_DARK_INVERT = new Set([
+    'openai',     // black wordmark
+    'moonshot',   // dark monogram
+    'zhipu',      // dark monogram
+    'custom',     // single-color slider glyph
+]);
+
+let modelsState = { providers: [], capabilities: {} };
+
+// One-shot: { capabilityId, providerId } stashed before a Models reload,
+// consumed by renderCapabilityBody to preselect a just-configured vendor.
+let pendingCapabilitySelection = null;
+
+// `opts.preserveScroll` keeps the page's vertical scroll position across the
+// refresh. We capture it before unhiding the loading skeleton (which collapses
+// content height to zero) and restore it after the new content is mounted.
+// This matters when the user configures a vendor from inside a capability
+// card's dropdown — without preservation, the post-save reload bounces them
+// back to the top of the page, away from the card they were configuring.
+function loadModelsView(opts) {
+    const loading = document.getElementById('models-loading');
+    const content = document.getElementById('models-content');
+    if (!loading || !content) return;
+    const preserveScroll = !!(opts && opts.preserveScroll);
+    // The Models pane has its own scrollable container; capture its position
+    // (not window.scrollY) so we can put the user back exactly where they were.
+    const scroller = document.querySelector('#view-models .overflow-y-auto');
+    const savedTop = preserveScroll && scroller ? scroller.scrollTop : null;
+
+    loading.classList.remove('hidden');
+    content.classList.add('hidden');
+
+    fetch('/api/models').then(r => r.json()).then(data => {
+        if (data.status !== 'success') {
+            loading.innerHTML = `<span class="text-sm text-red-400">${escapeHtml(data.message || 'Failed to load')}</span>`;
+            return;
+        }
+        modelsState.providers = data.providers || [];
+        modelsState.capabilities = data.capabilities || {};
+        renderModelsView();
+        loading.classList.add('hidden');
+        content.classList.remove('hidden');
+        if (savedTop !== null && scroller) {
+            // Wait one frame for the new layout to settle, otherwise the
+            // restored scrollTop snaps to the previous (smaller) max.
+            requestAnimationFrame(() => { scroller.scrollTop = savedTop; });
+        }
+    }).catch(err => {
+        loading.innerHTML = `<span class="text-sm text-red-400">${escapeHtml(String(err))}</span>`;
+    });
+}
+
+function renderModelsView() {
+    const container = document.getElementById('models-content');
+    container.innerHTML = '';
+    container.appendChild(renderVendorsSection());
+    MODELS_CAPABILITY_DEFS.forEach(def => container.appendChild(renderCapabilityCard(def)));
+}
+
+// True when a provider card is one of the expanded custom (OpenAI-compatible)
+// providers (id "custom:<id>") — shown in the vendor grid alongside built-in
+// vendors, but edited via the dedicated custom-provider modal.
+function isCustomProviderCard(p) {
+    return !!(p && p.is_custom && p.custom_name);
+}
+
+// ---------- Vendor section (Layer 1) -----------------------------------
+
+function renderVendorsSection() {
+    const wrap = document.createElement('div');
+    wrap.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6';
+
+    // Custom providers always show once created (even without an api key,
+    // e.g. a local vLLM/Ollama endpoint); built-in vendors show when configured.
+    const configured = modelsState.providers.filter(p => p.configured || isCustomProviderCard(p));
+
+    const header = `
+        <div class="flex items-start gap-3 mb-5">
+            <div class="w-9 h-9 rounded-lg bg-primary-50 dark:bg-primary-900/30 flex items-center justify-center flex-shrink-0">
+                <i class="fas fa-key text-primary-500 text-sm"></i>
+            </div>
+            <div class="flex-1 min-w-0">
+                <h3 class="font-semibold text-slate-800 dark:text-slate-100">${t('models_section_vendors')}</h3>
+                <p class="text-xs text-slate-500 dark:text-slate-400 mt-0.5">${t('models_section_vendors_desc')}</p>
+            </div>
+        </div>`;
+
+    let body;
+    if (configured.length === 0) {
+        body = `
+            <div class="flex flex-col items-center justify-center py-8 px-4 rounded-lg border border-dashed border-slate-200 dark:border-white/10">
+                <p class="text-sm text-slate-500 dark:text-slate-400 text-center">${t('models_not_configured')}</p>
+                <button onclick="openVendorModal('')"
+                        class="mt-3 px-3 py-1.5 rounded-lg text-xs font-medium bg-primary-50 dark:bg-primary-900/30 text-primary-600 dark:text-primary-400 hover:bg-primary-100 dark:hover:bg-primary-900/50 cursor-pointer transition-colors">
+                    <i class="fas fa-plus text-[10px] mr-1"></i>${t('models_add_vendor')}
+                </button>
+            </div>`;
+    } else {
+        body = `<div class="grid grid-cols-1 sm:grid-cols-2 gap-3">
+            ${configured.map(renderVendorChip).join('')}
+        </div>`;
+    }
+
+    wrap.innerHTML = header + body;
+    return wrap;
+}
+
+function renderVendorChip(p) {
+    // The masked API key is intentionally not surfaced here; it is shown
+    // inside the edit modal so the chip stays uncluttered and scannable.
+    // Custom providers open their dedicated modal (name + base + key);
+    // their ids are server-generated hex, safe to inline.
+    const onclick = isCustomProviderCard(p)
+        ? `openCustomProviderModal('${escapeHtml(p.custom_id)}')`
+        : `openVendorModal('${escapeHtml(p.id)}')`;
+    return `
+        <button onclick="${onclick}"
+                class="group flex items-center gap-3 px-3 py-2.5 rounded-lg border border-slate-200 dark:border-white/10
+                       bg-slate-50 dark:bg-white/5 hover:border-primary-300 dark:hover:border-primary-500/50
+                       cursor-pointer transition-colors duration-150 text-left">
+            ${renderProviderLogo(p, 28)}
+            <span class="flex-1 min-w-0 text-sm font-medium text-slate-800 dark:text-slate-100 truncate">${escapeHtml(localizedLabel(p.label))}</span>
+            <i class="fas fa-pen-to-square text-[11px] text-slate-400 dark:text-slate-500 group-hover:text-primary-500 transition-colors"></i>
+        </button>`;
+}
+
+// Render a uniformly-styled logo for a provider. Tries an SVG asset first; if
+// it 404s the <img> swaps itself for a monogram fallback via onerror.
+function renderProviderLogo(p, sizePx) {
+    const initial = (localizedLabel(p.label) || p.id || '?').slice(0, 1).toUpperCase();
+    const sz = sizePx || 32;
+    const url = `${MODELS_PROVIDER_LOGO_PATH}/${encodeURIComponent(p.id)}.svg`;
+    const fallbackId = `pl-${p.id}-${Math.random().toString(36).slice(2, 8)}`;
+    const imgClass = MODELS_PROVIDER_LOGO_DARK_INVERT.has(p.id)
+        ? 'absolute inset-0 m-auto provider-logo-img provider-logo-invert-dark'
+        : 'absolute inset-0 m-auto provider-logo-img';
+    return `
+        <span class="relative flex items-center justify-center rounded-lg bg-slate-100 dark:bg-white/10
+                     text-slate-600 dark:text-slate-300 flex-shrink-0 overflow-hidden"
+              style="width:${sz}px;height:${sz}px;">
+            <span id="${fallbackId}" class="text-xs font-bold">${escapeHtml(initial)}</span>
+            <img src="${url}" alt="" aria-hidden="true"
+                 class="${imgClass}"
+                 style="width:${Math.round(sz * 0.65)}px;height:${Math.round(sz * 0.65)}px;"
+                 onload="(function(el){var f=document.getElementById('${fallbackId}');if(f)f.style.display='none';})(this)"
+                 onerror="this.remove();">
+        </span>`;
+}
+
+function getCustomProviderCards() {
+    return modelsState.providers.filter(isCustomProviderCard);
+}
+
+// ---------- Capability cards (Layer 2) ---------------------------------
+
+function renderCapabilityCard(def) {
+    const cap = modelsState.capabilities[def.id] || {};
+    const wrap = document.createElement('div');
+    wrap.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6';
+    wrap.id = `models-card-${def.id}`;
+
+    const headerRight = renderCapabilityHeaderTag(def, cap);
+
+    wrap.innerHTML = `
+        <div class="flex items-start gap-3 mb-5">
+            <div class="w-9 h-9 rounded-lg ${def.iconChip} flex items-center justify-center flex-shrink-0">
+                <i class="fas ${def.icon} ${def.iconGlyph} text-sm"></i>
+            </div>
+            <div class="flex-1 min-w-0">
+                <h3 class="font-semibold text-slate-800 dark:text-slate-100">${t(def.titleKey)}</h3>
+                <p class="text-xs text-slate-500 dark:text-slate-400 mt-0.5">${t(def.descKey)}</p>
+            </div>
+            ${headerRight}
+        </div>
+        <div class="space-y-4" data-cap-body="${def.id}"></div>`;
+
+    const body = wrap.querySelector(`[data-cap-body="${def.id}"]`);
+    renderCapabilityBody(def, cap, body);
+    return wrap;
+}
+
+function renderCapabilityHeaderTag(def, cap) {
+    return '';
+}
+
+function _searchProviderLabel(cap, providerId) {
+    const list = (cap && cap.providers) || [];
+    const hit = list.find(p => p.id === providerId);
+    return hit ? localizedLabel(hit.label) : providerId;
+}
+
+// Search card body: strategy picker + (when fixed) provider picker + a
+// status row that surfaces which providers are ready and how to add the
+// missing ones. Three of the four backends piggy-back on model-vendor
+// credentials (zhipu / qianfan / linkai); bocha owns its own key under
+// tools.web_search and gets its own minimal credential modal.
+function renderSearchCapability(def, cap, body) {
+    const providers = cap.providers || [];
+    const configuredIds = cap.configured_providers || [];
+    const hasAny = configuredIds.length > 0;
+    const strategy = cap.strategy || 'auto';
+
+    body.innerHTML = `
+        <div>
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('models_search_strategy_label')}</label>
+            <div id="cap-search-strategy" class="cfg-dropdown" tabindex="0">
+                <div class="cfg-dropdown-selected">
+                    <span class="cfg-dropdown-text">--</span>
+                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                </div>
+                <div class="cfg-dropdown-menu"></div>
+            </div>
+        </div>
+        <div id="cap-search-provider-wrap" class="hidden">
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('models_provider')}</label>
+            <div id="cap-search-provider" class="cfg-dropdown" tabindex="0">
+                <div class="cfg-dropdown-selected">
+                    <span class="cfg-dropdown-text">--</span>
+                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                </div>
+                <div class="cfg-dropdown-menu"></div>
+            </div>
+        </div>
+        <div id="cap-search-summary"></div>
+        <div class="flex items-center justify-end gap-3 pt-1">
+            <span id="cap-search-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+            <button onclick="saveSearchCapability()"
+                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed">
+                ${t('save')}
+            </button>
+        </div>
+    `;
+
+    // Strategy dropdown — when no provider is configured the strategy
+    // value is meaningless, so we show a "待配置" placeholder instead of
+    // a default selection. Once any provider gets configured the saved
+    // strategy (or "auto") becomes the active value.
+    initDropdown(
+        body.querySelector('#cap-search-strategy'),
+        [
+            { value: 'auto',  label: t('models_strategy_auto'),         hint: t('models_search_strategy_auto_hint') },
+            { value: 'fixed', label: t('models_search_strategy_fixed'), hint: t('models_search_strategy_fixed_hint') },
+        ],
+        hasAny ? strategy : '',
+        (value) => _onSearchStrategyChange(cap, value, body),
+        hasAny ? null : { placeholder: t('models_pending_config') },
+    );
+
+    // Provider dropdown — populated with configured providers only;
+    // unconfigured ones cannot be pinned (they'd silently fall back).
+    const provOpts = configuredIds.map(id => ({
+        value: id,
+        label: _searchProviderLabel(cap, id),
+    }));
+    if (provOpts.length === 0) provOpts.push({ value: '', label: '--' });
+    initDropdown(
+        body.querySelector('#cap-search-provider'),
+        provOpts,
+        cap.fixed_provider || configuredIds[0] || '',
+        () => {},
+    );
+
+    _renderSearchSummary(body, cap);
+    _setSearchProviderPickerVisible(body, strategy === 'fixed' && hasAny);
+}
+
+function _onSearchStrategyChange(cap, value, body) {
+    const configuredIds = cap.configured_providers || [];
+    _setSearchProviderPickerVisible(body, value === 'fixed' && configuredIds.length > 0);
+}
+
+function _setSearchProviderPickerVisible(body, visible) {
+    const wrap = body.querySelector('#cap-search-provider-wrap');
+    if (!wrap) return;
+    if (visible) wrap.classList.remove('hidden');
+    else wrap.classList.add('hidden');
+}
+
+// Search summary line: just lists configured providers + a trailing "+
+// add" button. Unconfigured backends are hidden — the user picks one from
+// a small chooser when they click add. Empty state surfaces the same add
+// button as a primary CTA.
+function _renderSearchSummary(body, cap) {
+    const host = body.querySelector('#cap-search-summary');
+    if (!host) return;
+    const providers = cap.providers || [];
+    const configured = providers.filter(p => p.configured);
+    const missing = providers.filter(p => !p.configured);
+
+    const addBtn = missing.length
+        ? `<button type="button" id="cap-search-add-btn"
+                  class="inline-flex items-center gap-1 px-2 py-0.5 text-[11px] rounded-md cursor-pointer
+                         bg-slate-100 dark:bg-white/5 text-slate-500 dark:text-slate-400
+                         hover:bg-slate-200 dark:hover:bg-white/10 transition-colors">
+              <i class="fas fa-plus text-[10px]"></i>${t('models_search_add_provider')}
+           </button>`
+        : '';
+
+    if (configured.length === 0) {
+        host.innerHTML = `
+            <div class="flex items-center gap-2 text-xs text-slate-500 dark:text-slate-400">
+                <i class="fas fa-circle-info text-[10px] text-amber-500"></i>
+                <span>${t('models_search_none_configured')}</span>
+                ${addBtn}
+            </div>
+        `;
+    } else {
+        const chips = configured.map(p => `
+            <button type="button" data-search-edit-provider="${p.id}"
+                    title="${t('models_search_edit_hint')}"
+                    class="inline-flex items-center gap-1 px-2 py-0.5 text-[11px] rounded-md cursor-pointer
+                           bg-emerald-50 dark:bg-emerald-900/30 text-emerald-600 dark:text-emerald-400
+                           hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors">
+                <i class="fas fa-check text-[10px]"></i>${escapeHtml(localizedLabel(p.label))}
+            </button>
+        `).join('');
+        host.innerHTML = `
+            <div class="flex items-center flex-wrap gap-2 text-xs text-slate-500 dark:text-slate-400">
+                <span>${t('models_search_available_label')}</span>
+                ${chips}
+                ${addBtn}
+            </div>
+        `;
+    }
+
+    const addBtnEl = host.querySelector('#cap-search-add-btn');
+    if (addBtnEl) {
+        addBtnEl.addEventListener('click', (ev) => {
+            ev.preventDefault();
+            openSearchAddProviderPicker(missing);
+        });
+    }
+    host.querySelectorAll('[data-search-edit-provider]').forEach(el => {
+        el.addEventListener('click', (ev) => {
+            ev.preventDefault();
+            const pid = el.getAttribute('data-search-edit-provider');
+            const meta = (cap.providers || []).find(p => p.id === pid);
+            _launchSearchProviderConfig(pid, meta);
+        });
+    });
+}
+
+// Two-step add flow: click "+ 添加厂商" -> chooser dialog -> per-provider
+// credential editor. Bocha lands on the dedicated key modal; the others
+// piggy-back on the existing vendor credential modal.
+function openSearchAddProviderPicker(missingProviders) {
+    if (!missingProviders || missingProviders.length === 0) return;
+    if (missingProviders.length === 1) {
+        _launchSearchProviderConfig(missingProviders[0].id);
+        return;
+    }
+
+    const existing = document.getElementById('search-add-modal');
+    if (existing) existing.remove();
+
+    const rows = missingProviders.map(p => `
+        <button type="button" data-pid="${p.id}"
+                class="w-full flex items-center justify-between px-3 py-2.5 rounded-lg cursor-pointer
+                       bg-slate-50 dark:bg-white/5 hover:bg-slate-100 dark:hover:bg-white/10
+                       text-sm text-slate-700 dark:text-slate-200 transition-colors">
+            <span>${escapeHtml(localizedLabel(p.label))}</span>
+            <i class="fas fa-chevron-right text-[10px] text-slate-400"></i>
+        </button>
+    `).join('');
+
+    const modal = document.createElement('div');
+    modal.id = 'search-add-modal';
+    modal.className = 'fixed inset-0 z-50 flex items-center justify-center bg-black/40 backdrop-blur-sm';
+    modal.innerHTML = `
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10
+                    w-full max-w-md mx-4 p-6 shadow-xl">
+            <h3 class="text-lg font-semibold text-slate-800 dark:text-slate-100 mb-1">${t('models_search_add_provider')}</h3>
+            <p class="text-xs text-slate-500 dark:text-slate-400 mb-4">${t('models_search_add_desc')}</p>
+            <div class="space-y-2">${rows}</div>
+            <div class="flex items-center justify-end mt-5">
+                <button type="button" onclick="document.getElementById('search-add-modal').remove()"
+                        class="px-3 py-1.5 rounded-md text-sm text-slate-600 dark:text-slate-300
+                               hover:bg-slate-100 dark:hover:bg-white/5 transition-colors">
+                    ${t('cancel')}
+                </button>
+            </div>
+        </div>
+    `;
+    document.body.appendChild(modal);
+    modal.querySelectorAll('[data-pid]').forEach(el => {
+        el.addEventListener('click', () => {
+            const pid = el.getAttribute('data-pid');
+            modal.remove();
+            _launchSearchProviderConfig(pid);
+        });
+    });
+}
+
+function _launchSearchProviderConfig(providerId, providerMeta) {
+    if (providerId === 'bocha') {
+        openSearchBochaModal(providerMeta);
+    } else {
+        openVendorModal(providerId, () => loadModelsView({ preserveScroll: true }));
+    }
+}
+
+function saveSearchCapability() {
+    const strategyDd = document.getElementById('cap-search-strategy');
+    const providerDd = document.getElementById('cap-search-provider');
+    const strategy = strategyDd ? getDropdownValue(strategyDd) : 'auto';
+    const provider = (strategy === 'fixed' && providerDd) ? getDropdownValue(providerDd) : '';
+
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({
+            action: 'set_capability',
+            capability: 'search',
+            strategy,
+            provider,
+        }),
+    }).then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            showStatus('cap-search-status', 'models_save_success', false);
+            setTimeout(() => loadModelsView({ preserveScroll: true }), 400);
+        } else {
+            showStatus('cap-search-status', 'models_save_failed', true);
+        }
+    }).catch(() => showStatus('cap-search-status', 'models_save_failed', true));
+}
+
+// Minimal bocha API-key modal. Reuses the existing vendor-modal markup
+// helpers would be nice, but bocha isn't in PROVIDER_MODELS (it's not a
+// model vendor), so we render a tiny dedicated dialog.
+function openSearchBochaModal(providerMeta) {
+    const existing = document.getElementById('search-bocha-modal');
+    if (existing) existing.remove();
+
+    let masked = (providerMeta && providerMeta.api_key_masked) || '';
+    if (!masked) {
+        const searchCap = (modelsState && modelsState.capabilities && modelsState.capabilities.search) || {};
+        const bocha = (searchCap.providers || []).find(p => p.id === 'bocha');
+        if (bocha && bocha.api_key_masked) masked = bocha.api_key_masked;
+    }
+    const hasKey = !!masked;
+    const clearBtnHtml = hasKey
+        ? `<button type="button" id="search-bocha-clear"
+                  class="px-3 py-1.5 rounded-md text-xs text-red-500 dark:text-red-400
+                         hover:bg-red-50 dark:hover:bg-red-900/20 cursor-pointer transition-colors">
+              ${t('models_clear_credential')}
+           </button>`
+        : '';
+
+    const modal = document.createElement('div');
+    modal.id = 'search-bocha-modal';
+    modal.className = 'fixed inset-0 z-50 flex items-center justify-center bg-black/40 backdrop-blur-sm';
+    modal.innerHTML = `
+        <div id="search-bocha-modal-card"
+             class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10
+                    w-full max-w-md mx-4 p-6 shadow-xl">
+            <h3 class="text-lg font-semibold text-slate-800 dark:text-slate-100 mb-1">${t('models_search_bocha_title')}</h3>
+            <p class="text-xs text-slate-500 dark:text-slate-400 mb-4">${t('models_search_bocha_desc')}</p>
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">API Key</label>
+            <input id="search-bocha-key" type="text" autocomplete="off" data-1p-ignore data-lpignore="true"
+                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                          focus:outline-none focus:border-primary-500 font-mono ${hasKey ? 'cfg-key-masked' : ''}"
+                   value="${escapeHtml(masked)}"
+                   data-masked="${hasKey ? '1' : ''}"
+                   placeholder="sk-..." />
+            <div class="flex items-center justify-between gap-3 mt-5">
+                <div>${clearBtnHtml}</div>
+                <div class="flex items-center gap-3">
+                    <button type="button" onclick="document.getElementById('search-bocha-modal').remove()"
+                            class="px-3 py-1.5 rounded-md text-sm text-slate-600 dark:text-slate-300
+                                   hover:bg-slate-100 dark:hover:bg-white/5 transition-colors">
+                        ${t('cancel')}
+                    </button>
+                    <button type="button" onclick="_saveBochaKey()"
+                            class="px-4 py-1.5 rounded-md bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                   cursor-pointer transition-colors">
+                        ${t('save')}
+                    </button>
+                </div>
+            </div>
+        </div>
+    `;
+    document.body.appendChild(modal);
+
+    // Reset masked sentinel as soon as the user starts editing so the save
+    // handler can tell apart "kept the existing key" vs "typed a new one".
+    const input = document.getElementById('search-bocha-key');
+    if (input) {
+        const unmask = () => {
+            if (input.dataset.masked === '1') {
+                input.value = '';
+                input.dataset.masked = '';
+                input.classList.remove('cfg-key-masked');
+            }
+        };
+        input.addEventListener('keydown', (e) => {
+            if (e.key === 'Tab' || e.key === 'Escape') return;
+            unmask();
+        });
+        input.addEventListener('paste', unmask);
+        if (!hasKey) setTimeout(() => input.focus(), 50);
+    }
+    const clearBtn = document.getElementById('search-bocha-clear');
+    if (clearBtn) clearBtn.addEventListener('click', _clearBochaKey);
+
+    modal.addEventListener('mousedown', (e) => {
+        if (e.target === modal) modal.remove();
+    });
+    const onKey = (e) => {
+        if (e.key === 'Escape') {
+            modal.remove();
+            document.removeEventListener('keydown', onKey);
+        }
+    };
+    document.addEventListener('keydown', onKey);
+}
+
+function _saveBochaKey() {
+    const input = document.getElementById('search-bocha-key');
+    if (!input) return;
+    // Untouched masked value => no change requested; close silently.
+    if (input.dataset.masked === '1') {
+        const modal = document.getElementById('search-bocha-modal');
+        if (modal) modal.remove();
+        return;
+    }
+    const apiKey = input.value.trim();
+    if (!apiKey) {
+        input.focus();
+        return;
+    }
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action: 'set_search_credential', api_key: apiKey }),
+    }).then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            const modal = document.getElementById('search-bocha-modal');
+            if (modal) modal.remove();
+            loadModelsView({ preserveScroll: true });
+        }
+    });
+}
+
+function _clearBochaKey() {
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action: 'set_search_credential', api_key: '' }),
+    }).then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            const modal = document.getElementById('search-bocha-modal');
+            if (modal) modal.remove();
+            loadModelsView({ preserveScroll: true });
+        }
+    });
+}
+
+function renderCapabilityBody(def, cap, body) {
+    if (def.id === 'search') {
+        renderSearchCapability(def, cap, body);
+        return;
+    }
+
+    // Editable cards: provider dropdown + (optional) model dropdown + save row
+    const providerOpts = buildCapabilityProviderOptions(def, cap);
+    const providerHtml = `
+        <div>
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('models_provider')}</label>
+            <div id="cap-${def.id}-provider" class="cfg-dropdown" tabindex="0">
+                <div class="cfg-dropdown-selected">
+                    <span class="cfg-dropdown-text">--</span>
+                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                </div>
+                <div class="cfg-dropdown-menu"></div>
+            </div>
+        </div>`;
+
+    // The model-picker container is always emitted so the provider-change
+    // handler can show/hide it; for `auto` capabilities it starts hidden and
+    // gets toggled by setCapabilityModelPickerVisible.
+    const modelHtml = def.needsModel ? `
+        <div id="cap-${def.id}-model-wrap">
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('models_model')}</label>
+            <div id="cap-${def.id}-model" class="cfg-dropdown" tabindex="0">
+                <div class="cfg-dropdown-selected">
+                    <span class="cfg-dropdown-text">--</span>
+                    <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                </div>
+                <div class="cfg-dropdown-menu"></div>
+            </div>
+            <div id="cap-${def.id}-model-custom-wrap" class="mt-2 hidden">
+                <input id="cap-${def.id}-model-custom" type="text"
+                       class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                              bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                              focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                       placeholder="custom model name">
+            </div>
+        </div>` : '';
+
+    const dimHtml = (def.id === 'embedding' && cap.current_dim) ? `
+        <p class="text-xs text-slate-400 dark:text-slate-500">
+            <i class="fas fa-cube text-[10px] mr-1"></i>${t('models_dim_label')}: <span class="font-mono">${cap.current_dim}</span>
+        </p>` : '';
+
+    // Footer layout: a "hint slot" (filled later by renderCapabilityHints for
+    // auto-mode cards) sits on the left while status + save stay anchored on
+    // the right. Keeping them on the same row means the save button hugs the
+    // inputs above instead of being pushed down by a separate hint line.
+    const footer = `
+        <div class="flex items-center justify-between gap-3 pt-1">
+            <div data-cap-hint="${def.id}" class="flex-1 min-w-0"></div>
+            <div class="flex items-center gap-3 flex-shrink-0">
+                <span id="cap-${def.id}-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                <button onclick="saveCapability('${def.id}')"
+                        class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed">
+                    ${t('save')}
+                </button>
+            </div>
+        </div>`;
+
+    body.innerHTML = providerHtml + modelHtml + dimHtml + footer;
+
+    // TTS: mount reply-mode above provider; defer off-mode toggle to the end.
+    if (def.id === 'tts') {
+        renderVoiceReplyMode(body, cap.reply_mode || 'off', { skipVisibilityToggle: true });
+        // Voice-timbre picker depends on provider+model; rebuilt by callbacks.
+        const modelWrap = body.querySelector(`#cap-${def.id}-model-wrap`);
+        if (modelWrap) {
+            const voiceWrap = document.createElement('div');
+            voiceWrap.id = `cap-${def.id}-voice-wrap`;
+            voiceWrap.innerHTML = `
+                <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('models_voice')}</label>
+                <div id="cap-${def.id}-voice" class="cfg-dropdown" tabindex="0">
+                    <div class="cfg-dropdown-selected">
+                        <span class="cfg-dropdown-text">--</span>
+                        <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                    </div>
+                    <div class="cfg-dropdown-menu"></div>
+                </div>
+                <div id="cap-${def.id}-voice-custom-wrap" class="hidden mt-2">
+                    <input id="cap-${def.id}-voice-custom" type="text"
+                           class="w-full px-3 py-2 text-sm rounded-md border border-slate-200 dark:border-slate-700
+                                  bg-white dark:bg-slate-800 text-slate-700 dark:text-slate-200
+                                  placeholder:text-slate-400 dark:placeholder:text-slate-500
+                                  focus:outline-none focus:ring-2 focus:ring-primary-500"
+                           placeholder="voice id" />
+                </div>
+            `;
+            modelWrap.parentNode.insertBefore(voiceWrap, modelWrap.nextSibling);
+        }
+    }
+
+    // `body` is still detached from `document`; scope lookups locally.
+    const provDd = body.querySelector(`#cap-${def.id}-provider`);
+    // Strip private fields before handing to the generic initDropdown helper.
+    const ddOpts = providerOpts.map(o => ({ value: o.value, label: o.label }));
+
+    let pendingProvider = null;
+    if (pendingCapabilitySelection
+            && pendingCapabilitySelection.capabilityId === def.id
+            && providerOpts.some(o => o.value === pendingCapabilitySelection.providerId)) {
+        pendingProvider = pendingCapabilitySelection.providerId;
+        pendingCapabilitySelection = null;
+    }
+
+    // Auto strategy => leave empty sentinel selected. `suggested_provider`
+    // is a UI-only preselect (not persisted until the user clicks Save).
+    // No current + no suggestion => leave unselected with a placeholder.
+    //
+    // Pending-config takes priority over both "auto" and "pick provider":
+    // when no real (non-sentinel) configured option exists, surfacing
+    // "auto" or "pick" misleads the user — there's nothing to auto-route
+    // to or pick from. Force a "待配置" placeholder instead so all
+    // capabilities behave consistently on a fresh environment.
+    const hasConfiguredOpt = providerOpts.some(o => !o._isAuto && o._configured);
+    const noSelectionAndNoHint = !cap.current_provider && !cap.suggested_provider;
+    let initialProviderValue;
+    let dropdownPlaceholder = null;
+    if (!hasConfiguredOpt) {
+        initialProviderValue = '';
+        dropdownPlaceholder = { placeholder: t('models_pending_config') };
+    } else {
+        initialProviderValue = pendingProvider
+            ? pendingProvider
+            : ((cap.strategy === 'auto' && capabilitySupportsAuto(def.id))
+                ? ''
+                : (cap.current_provider
+                    || cap.suggested_provider
+                    || (noSelectionAndNoHint ? '' : (ddOpts[0] && ddOpts[0].value))
+                    || ''));
+        if (noSelectionAndNoHint) {
+            dropdownPlaceholder = { placeholder: t('models_pick_provider') };
+        }
+    }
+    initDropdown(
+        provDd,
+        ddOpts,
+        initialProviderValue,
+        (value) => onCapabilityProviderChange(def, value, body),
+        dropdownPlaceholder,
+    );
+    decorateCapabilityProviderDropdown(def, provDd, providerOpts);
+
+    if (def.needsModel) {
+        rebuildCapabilityModelDropdown(def, initialProviderValue, cap.current_model || '', body);
+        // Embedding: hide model picker when no provider is selected.
+        const showModel = def.id === 'embedding' ? initialProviderValue !== '' :
+            (initialProviderValue !== '' || !capabilitySupportsAuto(def.id));
+        setCapabilityModelPickerVisible(def, showModel, body);
+    }
+
+    if (def.id === 'tts') {
+        rebuildCapabilityVoiceDropdown(
+            initialProviderValue,
+            cap.current_voice || '',
+            body,
+            cap.current_model || ''
+        );
+    }
+
+    // Inject auto/router-pending hint banners before the action footer.
+    renderCapabilityHints(def, cap, body, initialProviderValue);
+
+    if (def.id === 'tts') {
+        _setTtsConfigVisible(body, (cap.reply_mode || 'off') !== 'off');
+    }
+}
+
+// TTS reply-policy dropdown (off / voice_if_voice / always). Persists on
+// change. When off, hides the rest of the TTS card.
+function renderVoiceReplyMode(host, currentMode, options) {
+    options = options || {};
+    const opts = [
+        { value: 'off',            label: t('voice_reply_off') },
+        { value: 'voice_if_voice', label: t('voice_reply_if_voice') },
+        { value: 'always',         label: t('voice_reply_always') },
+    ];
+    const wrap = document.createElement('div');
+    wrap.id = 'voice-reply-mode-wrap';
+    wrap.innerHTML = `
+        <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${t('voice_reply_mode_label')}</label>
+        <div id="voice-reply-mode-dd" class="cfg-dropdown" tabindex="0">
+            <div class="cfg-dropdown-selected">
+                <span class="cfg-dropdown-text">--</span>
+                <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+            </div>
+            <div class="cfg-dropdown-menu"></div>
+        </div>
+    `;
+    host.prepend(wrap);
+
+    const dd = wrap.querySelector('#voice-reply-mode-dd');
+    const valid = ['off', 'voice_if_voice', 'always'];
+    const initial = valid.includes(currentMode) ? currentMode : 'off';
+    if (!options.skipVisibilityToggle) _setTtsConfigVisible(host, initial !== 'off');
+    initDropdown(dd, opts, initial, (mode) => {
+        if (!valid.includes(mode)) return;
+        _setTtsConfigVisible(host, mode !== 'off');
+        fetch('/api/models', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ action: 'set_voice_reply_mode', mode }),
+        })
+            .then(r => r.json())
+            .then(data => {
+                if (data && data.status === 'success') {
+                    _ttsReadyPromise = null;  // force re-probe on next bubble
+                }
+            })
+            .catch(() => {});
+    });
+}
+
+// Show/hide everything in the TTS card below the reply-mode dropdown.
+function _setTtsConfigVisible(host, visible) {
+    if (!host) return;
+    Array.from(host.children).forEach((child) => {
+        if (child.id === 'voice-reply-mode-wrap') return;
+        child.classList.toggle('hidden', !visible);
+    });
+}
+
+// Toggle wrapper visibility instead of re-rendering so dropdown state survives.
+function setCapabilityModelPickerVisible(def, visible, scope) {
+    const root = scope || document;
+    const wrap = root.querySelector(`#cap-${def.id}-model-wrap`);
+    if (!wrap) return;
+    wrap.classList.toggle('hidden', !visible);
+}
+
+function renderCapabilityHints(def, cap, body, currentProvider) {
+    // Capabilities that can be in "auto" mode show a fallback hint right
+    // under the inputs so users always know what'd actually be hit. The
+    // image card additionally surfaces a "router pending" warning until the
+    // standalone dispatcher lands.
+    // The hint slot is co-located with the save button in the footer row
+    // (see renderCapabilityBody) so the save button stays close to the
+    // inputs above. We just rewrite the slot's innerHTML — emptying it
+    // when the card leaves auto mode, or rendering a one-line hint when
+    // it's in auto mode.
+    const slot = body.querySelector(`[data-cap-hint="${def.id}"]`);
+    if (!slot) return;
+    slot.innerHTML = '';
+
+    if (currentProvider !== '' || !capabilitySupportsAuto(def.id)) return;
+
+    // The hint mirrors what the runtime would actually pick when in auto
+    // mode. fallback_provider/model are pre-computed on the backend (see
+    // _predict_vision_auto, _predict_image_auto) so we can trust them
+    // here without re-implementing the provider chain.
+    const fbProv = cap.fallback_provider || '';
+    const fbModel = cap.fallback_model || '';
+    if (!fbProv && !fbModel) return;
+    // Show the vendor's display label (e.g. "LinkAI") instead of the raw
+    // id ("linkai") when we know it. Falls back to the id when the
+    // provider isn't in our vendor table (rare).
+    const provMeta = modelsState.providers.find(p => p.id === fbProv);
+    const fbProvLabel = (provMeta && localizedLabel(provMeta.label)) || fbProv;
+    const fbText = fbModel ? `${fbProvLabel} / ${fbModel}` : fbProvLabel;
+    slot.innerHTML = `
+        <p class="flex items-center gap-1.5 text-xs text-slate-400 dark:text-slate-500 min-w-0">
+            <i class="fas fa-circle-info text-[10px] flex-shrink-0"></i>
+            <span class="flex-shrink-0">${t('models_auto_using')}</span>
+            <span class="font-mono text-slate-500 dark:text-slate-400 truncate">${escapeHtml(fbText)}</span>
+        </p>`;
+}
+
+function buildCapabilityProviderOptions(def, cap) {
+    // Show ALL vendors in capability dropdowns so users can see at a glance
+    // who's configured (green check) and who isn't (gray dot, click to set
+    // up). The list order puts configured vendors first; clicking an
+    // unconfigured row opens the vendor modal in-place. ASR/TTS engines that
+    // aren't tracked by PROVIDER_MODELS (azure/baidu/google etc.) are treated
+    // as "always available" — no credential gate.
+    const knownProviderMap = {};
+    modelsState.providers.forEach(p => { knownProviderMap[p.id] = p; });
+
+    const explicitList = cap.providers && cap.providers.length ? cap.providers : null;
+    let providerIds = explicitList ? explicitList.slice() : modelsState.providers.map(p => p.id);
+    if (cap.current_provider && !providerIds.includes(cap.current_provider)) {
+        providerIds = [cap.current_provider, ...providerIds];
+    }
+
+    const opts = providerIds.map(pid => {
+        const meta = knownProviderMap[pid];
+        const tracked = !!meta;
+        const configured = !tracked || !!meta.configured;
+        return {
+            value: pid,
+            label: (meta && localizedLabel(meta.label)) || pid,
+            _tracked: tracked,
+            _configured: configured,
+        };
+    });
+
+    opts.sort((a, b) => {
+        if (a._configured === b._configured) return 0;
+        return a._configured ? -1 : 1;
+    });
+
+    // Capabilities with a fallback ("auto") strategy expose it as a sentinel
+    // option pinned to the top of the list. We use empty-string as the auto
+    // value so the existing save handler propagates it untouched to the
+    // backend, which interprets "" as "fall back to the main model".
+    // Skip the sentinel when no real vendor is configured — "auto" would
+    // route to nothing useful and the renderer will show "待配置" instead.
+    const hasAnyConfigured = opts.some(o => o._configured);
+    if ((cap.strategy === 'auto' || cap.strategy === 'specified') && hasAnyConfigured) {
+        if (capabilitySupportsAuto(def.id)) {
+            opts.unshift({
+                value: '',
+                label: t('models_strategy_auto'),
+                _tracked: false,
+                _configured: true,
+                _isAuto: true,
+            });
+        }
+    }
+    return opts;
+}
+
+function capabilitySupportsAuto(capId) {
+    // Embedding is intentionally NOT here: runtime only auto-falls back to
+    // OpenAI/LinkAI, so dressing it up as "auto" hides reality from users.
+    return capId === 'image' || capId === 'vision';
+}
+
+// After initDropdown renders the capability provider menu, decorate each
+// row with the right-aligned configuration cue:
+//   - configured rows: nothing extra — the .active marker (a brand-green ✓)
+//     already comes from initDropdown's selected-state CSS for the row the
+//     user currently picked. Other configured rows show no chrome, mirroring
+//     a plain "switch to this" selector.
+//   - unconfigured rows: a subdued gear icon hints at "click to configure".
+//     The row's whole click handler is swapped to launch the vendor modal
+//     in place rather than selecting an unusable value.
+function decorateCapabilityProviderDropdown(def, ddEl, opts) {
+    if (!ddEl) return;
+    const menu = ddEl.querySelector('.cfg-dropdown-menu');
+    if (!menu) return;
+
+    const optByValue = {};
+    opts.forEach(o => { optByValue[o.value] = o; });
+
+    menu.querySelectorAll('.cfg-dropdown-item').forEach(item => {
+        const value = item.dataset.value;
+        const opt = optByValue[value];
+        if (!opt) return;
+        item.classList.add('cap-provider-item');
+        if (!opt._configured) item.classList.add('cap-provider-unconfigured');
+
+        // Wrap the label so the trailing affordance lines up via flex:auto.
+        const labelText = item.textContent;
+        item.textContent = '';
+        const labelEl = document.createElement('span');
+        labelEl.className = 'cap-provider-label';
+        labelEl.textContent = labelText;
+        item.appendChild(labelEl);
+
+        if (!opt._configured) {
+            // Trailing gear icon as the "configure this vendor" affordance.
+            const gear = document.createElement('i');
+            gear.className = 'fas fa-gear cap-provider-gear';
+            item.appendChild(gear);
+        }
+
+        if (!opt._configured && opt._tracked) {
+            // Hijack the click: open the vendor modal instead of selecting
+            // an unusable value, and remember which capability the user was
+            // configuring so the post-save reload can preselect the vendor.
+            const newItem = item.cloneNode(true);
+            item.replaceWith(newItem);
+            newItem.addEventListener('click', (e) => {
+                e.stopPropagation();
+                ddEl.classList.remove('open');
+                openVendorModal(value, (savedProviderId) => {
+                    pendingCapabilitySelection = {
+                        capabilityId: def.id,
+                        providerId: savedProviderId || value,
+                    };
+                    loadModelsView({ preserveScroll: true });
+                });
+            });
+        }
+    });
+}
+
+// Lightweight decorator for the "add vendor" modal's provider picker:
+// every configured vendor row gets a trailing brand-green ✓ so the user can
+// see at a glance who's already set up, without having to read each row.
+// Unlike decorateCapabilityProviderDropdown we don't hijack clicks here —
+// picking an unconfigured vendor in this modal *is* the intended action.
+function decorateVendorModalPicker(ddEl, opts) {
+    if (!ddEl) return;
+    const menu = ddEl.querySelector('.cfg-dropdown-menu');
+    if (!menu) return;
+
+    const optByValue = {};
+    opts.forEach(o => { optByValue[o.value] = o; });
+
+    menu.querySelectorAll('.cfg-dropdown-item').forEach(item => {
+        const opt = optByValue[item.dataset.value];
+        if (!opt) return;
+        // Tag the row so the global active-row ✓ rule is suppressed in CSS
+        // (otherwise configured AND selected rows would render two checks).
+        item.classList.add('vendor-picker-item');
+        if (opt._isAddNew) {
+            // "Custom" is an add-new action (multiple entries allowed),
+            // so show a trailing + instead of the configured ✓.
+            const plus = document.createElement('i');
+            plus.className = 'fas fa-plus vendor-picker-add-mark';
+            item.appendChild(plus);
+            return;
+        }
+        if (!opt._configured) return;
+        const check = document.createElement('i');
+        check.className = 'fas fa-check vendor-picker-configured-mark';
+        item.appendChild(check);
+    });
+}
+
+function rebuildCapabilityModelDropdown(def, providerId, selectedModel, scope) {
+    // `scope` lets the caller (renderCapabilityBody) target a still-detached
+    // subtree. After the card is mounted, callers may pass `document` instead.
+    const root = scope || document;
+    const el = root.querySelector(`#cap-${def.id}-model`);
+    if (!el) return;
+
+    // Prefer the capability-scoped model list when the backend provides one
+    // (vision / image). It reflects the models the runtime can actually
+    // dispatch to for this capability, instead of the vendor's full chat-
+    // model catalog. Fall back to the generic provider.models for chat /
+    // embedding / tts where any vendor model is fair game.
+    //
+    // Entries may be plain strings or {value, hint} objects (image catalog
+    // uses the latter to surface brand aliases like "Nano Banana 2" next to
+    // the technical Gemini model id). We normalize to {value, label, hint}
+    // before handing off to initDropdown.
+    const cap = modelsState.capabilities[def.id] || {};
+    const capModelMap = cap.provider_models || {};
+    let rawList;
+    if (capModelMap[providerId]) {
+        rawList = capModelMap[providerId].slice();
+    } else if (providerId.startsWith('custom:') && capModelMap['custom']) {
+        // Expanded custom:<id> entries share the same preset model list
+        rawList = capModelMap['custom'].slice();
+    } else {
+        const provider = modelsState.providers.find(p => p.id === providerId);
+        rawList = (provider && provider.models) ? provider.models.slice() : [];
+    }
+    const modelValues = [];
+    const opts = rawList.map(entry => {
+        if (typeof entry === 'string') {
+            modelValues.push(entry);
+            return { value: entry, label: entry };
+        }
+        modelValues.push(entry.value);
+        return { value: entry.value, label: entry.label || entry.value, hint: entry.hint || '' };
+    });
+    opts.push({ value: '__custom__', label: currentLang === 'zh' ? '自定义' : 'Custom' });
+
+    let initialValue = selectedModel || '';
+    if (initialValue && !modelValues.includes(initialValue)) {
+        initialValue = '__custom__';
+    }
+    if (!initialValue && opts.length) initialValue = opts[0].value;
+
+    initDropdown(el, opts, initialValue, (value) => {
+        const customWrap = document.getElementById(`cap-${def.id}-model-custom-wrap`);
+        if (customWrap) {
+            if (value === '__custom__') {
+                customWrap.classList.remove('hidden');
+                const input = document.getElementById(`cap-${def.id}-model-custom`);
+                if (input && !input.value) input.value = selectedModel || '';
+            } else {
+                customWrap.classList.add('hidden');
+            }
+        }
+        // TTS voice catalog may be scoped per engine model (aggregating
+        // gateways). Rebuild the voice picker whenever the model changes.
+        if (def.id === 'tts') {
+            const provDd = document.getElementById('cap-tts-provider');
+            const provId = provDd ? getDropdownValue(provDd) : '';
+            rebuildCapabilityVoiceDropdown(provId, '', null, value);
+        }
+    });
+
+    const customWrap = root.querySelector(`#cap-${def.id}-model-custom-wrap`);
+    if (customWrap) {
+        if (initialValue === '__custom__') {
+            customWrap.classList.remove('hidden');
+            const input = root.querySelector(`#cap-${def.id}-model-custom`);
+            if (input) input.value = selectedModel || '';
+        } else {
+            customWrap.classList.add('hidden');
+        }
+    }
+}
+
+// TTS-only: rebuild the voice timbre picker against the provider's
+// curated voice list. Hidden when no provider is picked.
+//
+// Each voice entry may be:
+//   - a bare string  (code = label)
+//   - {value, label, hint?}   so we can show a friendly Chinese name
+//     while persisting the raw API code that the runtime sends.
+function rebuildCapabilityVoiceDropdown(providerId, selectedVoice, scope, modelId) {
+    const root = scope || document;
+    const wrap = root.querySelector(`#cap-tts-voice-wrap`);
+    const el = root.querySelector(`#cap-tts-voice`);
+    if (!wrap || !el) return;
+    const cap = modelsState.capabilities.tts || {};
+    const voicesByProvider = cap.provider_voices || {};
+    let raw = (providerId && voicesByProvider[providerId]) || [];
+    // Some providers (gateways) scope voices by engine model id.
+    if (raw && !Array.isArray(raw) && typeof raw === 'object') {
+        const activeModel = modelId
+            || (root.querySelector(`#cap-tts-model`) ? getDropdownValue(root.querySelector(`#cap-tts-model`)) : '');
+        raw = (activeModel && raw[activeModel]) || [];
+    }
+    if (!raw || raw.length === 0) {
+        wrap.classList.add('hidden');
+        return;
+    }
+    wrap.classList.remove('hidden');
+    // Voice picker: friendly name on the left, raw API code as right-hand
+    // hint. Persisted/sent value is always the raw code.
+    const codes = [];
+    const opts = raw.map(entry => {
+        if (typeof entry === 'string') {
+            codes.push(entry);
+            return { value: entry, label: entry };
+        }
+        codes.push(entry.value);
+        const code = entry.value;
+        const desc = entry.hint || entry.label || code;
+        return {
+            value: code,
+            label: desc,
+            hint: desc === code ? '' : code,
+        };
+    });
+    opts.push({ value: '__custom__', label: currentLang === 'zh' ? '自定义' : 'Custom' });
+
+    // Off-catalog values route through the custom branch.
+    let initial = selectedVoice || '';
+    const isCustom = initial && !codes.includes(initial);
+    if (isCustom) initial = '__custom__';
+    if (!initial) initial = codes[0];
+
+    initDropdown(el, opts, initial, (value) => {
+        const customWrap = root.querySelector(`#cap-tts-voice-custom-wrap`);
+        if (!customWrap) return;
+        if (value === '__custom__') {
+            customWrap.classList.remove('hidden');
+            const input = root.querySelector(`#cap-tts-voice-custom`);
+            if (input && !input.value) input.value = isCustom ? selectedVoice : '';
+        } else {
+            customWrap.classList.add('hidden');
+        }
+    });
+
+    const customWrap = root.querySelector(`#cap-tts-voice-custom-wrap`);
+    if (customWrap) {
+        if (initial === '__custom__') {
+            customWrap.classList.remove('hidden');
+            const input = root.querySelector(`#cap-tts-voice-custom`);
+            if (input) input.value = isCustom ? selectedVoice : '';
+        } else {
+            customWrap.classList.add('hidden');
+        }
+    }
+}
+
+function onCapabilityProviderChange(def, providerId, scope) {
+    if (def.needsModel) {
+        // Embedding: hide model picker when no provider is selected.
+        const showModel = def.id === 'embedding' ? providerId !== '' :
+            !(providerId === '' && capabilitySupportsAuto(def.id));
+        if (showModel) {
+            rebuildCapabilityModelDropdown(def, providerId, '', scope);
+        }
+        setCapabilityModelPickerVisible(def, showModel, scope);
+    }
+    if (def.id === 'tts') {
+        rebuildCapabilityVoiceDropdown(providerId, '', scope);
+    }
+    const body = scope || document.querySelector(`[data-cap-body="${def.id}"]`);
+    if (body) {
+        const cap = modelsState.capabilities[def.id] || {};
+        renderCapabilityHints(def, cap, body, providerId);
+    }
+}
+
+function getCapabilityModelValue(def) {
+    if (!def.needsModel) return '';
+    const dd = document.getElementById(`cap-${def.id}-model`);
+    if (!dd) return '';
+    const v = getDropdownValue(dd);
+    if (v === '__custom__') {
+        const input = document.getElementById(`cap-${def.id}-model-custom`);
+        return input ? input.value.trim() : '';
+    }
+    return v || '';
+}
+
+function saveCapability(capId) {
+    const def = MODELS_CAPABILITY_DEFS.find(d => d.id === capId);
+    if (!def || !def.editable) return;
+    // Search has its own form (strategy + provider, no model picker).
+    if (capId === 'search') { saveSearchCapability(); return; }
+    const provDd = document.getElementById(`cap-${capId}-provider`);
+    const provider = provDd ? getDropdownValue(provDd) : '';
+    // When the user is in auto mode (provider == ""), the model picker is
+    // hidden and any value left in it is stale; persist an empty model so
+    // the backend treats this as "fall back to the runtime chain".
+    const isAuto = provider === '' && capabilitySupportsAuto(capId);
+    // Embedding without a provider similarly means "cleared" — don't leak
+    // a stale model value into config.
+    const model = (isAuto || (capId === 'embedding' && !provider)) ? '' : getCapabilityModelValue(def);
+    // TTS carries an extra voice timbre (supports free-text custom ids).
+    let voice = '';
+    if (capId === 'tts' && !isAuto) {
+        const voiceDd = document.getElementById(`cap-${capId}-voice`);
+        voice = voiceDd ? getDropdownValue(voiceDd) : '';
+        if (voice === '__custom__') {
+            const input = document.getElementById(`cap-${capId}-voice-custom`);
+            voice = input ? input.value.trim() : '';
+        }
+    }
+
+    // Embedding changes invalidate any pre-existing vector index because
+    // dimensions / vendor differ. Gate the save behind a confirm, and on
+    // success surface a dedicated info dialog telling the user how to
+    // rebuild — both via the in-app custom dialog, not the native alert.
+    if (capId === 'embedding') {
+        const cap = modelsState.capabilities[capId] || {};
+        const before = (cap.current_provider || '').trim();
+        const after = (provider || '').trim();
+        if (before !== after) {
+            showConfirmDialog({
+                title: t('models_embedding_change_title'),
+                message: t('models_embedding_change_msg'),
+                okText: t('save'),
+                cancelText: t('cancel'),
+                onConfirm: () => _persistCapability(capId, provider, model, () => {
+                    showConfirmDialog({
+                        title: t('models_embedding_saved_title'),
+                        message: t('models_embedding_saved_msg'),
+                        okText: t('models_embedding_saved_ok'),
+                        hideCancel: true,
+                        onConfirm: () => {
+                            navigateTo('chat');
+                            // Defer focus + value set: navigateTo may
+                            // re-render the chat panel; setting value before
+                            // the input is mounted would be lost.
+                            setTimeout(() => {
+                                const input = document.getElementById('chat-input');
+                                if (!input) return;
+                                input.value = '/memory rebuild-index';
+                                input.focus();
+                                // Trigger any input listeners (autosize, send-button enable, etc.)
+                                input.dispatchEvent(new Event('input', { bubbles: true }));
+                            }, 60);
+                        },
+                    });
+                }),
+            });
+            return;
+        }
+    }
+    _persistCapability(capId, provider, model, undefined, { voice });
+}
+
+function _persistCapability(capId, provider, model, onAfterSuccess, extras) {
+    const payload = { action: 'set_capability', capability: capId, provider_id: provider, model: model };
+    if (extras && extras.voice !== undefined) payload.voice = extras.voice;
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify(payload),
+    }).then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            // Flash "Saved" before reload so the status survives the rebuild.
+            showStatus(`cap-${capId}-status`, 'models_save_success', false);
+            setTimeout(() => {
+                loadModelsView({ preserveScroll: true });
+                if (onAfterSuccess) onAfterSuccess();
+            }, 400);
+        } else {
+            showStatus(`cap-${capId}-status`, 'models_save_failed', true);
+        }
+    }).catch(() => showStatus(`cap-${capId}-status`, 'models_save_failed', true));
+}
+
+// ---------- Vendor credential modal ------------------------------------
+
+let vendorModalState = { providerId: '', onSaved: null };
+
+function openVendorModal(providerId, onSaved) {
+    vendorModalState = { providerId: providerId || '', onSaved: onSaved || null };
+
+    const overlay = document.getElementById('vendor-modal-overlay');
+    const titleEl = document.getElementById('vendor-modal-title');
+    const subEl = document.getElementById('vendor-modal-subtitle');
+    const pickerWrap = document.getElementById('vendor-modal-picker-wrap');
+    const baseWrap = document.getElementById('vendor-modal-base-wrap');
+    const baseInput = document.getElementById('vendor-modal-base');
+    const baseHint = document.getElementById('vendor-modal-base-hint');
+    const keyInput = document.getElementById('vendor-modal-key');
+    const clearBtn = document.getElementById('vendor-modal-clear');
+
+    // Reset any leftover status (e.g. previous "Saved" message)
+    const statusEl = document.getElementById('vendor-modal-status');
+    if (statusEl) {
+        statusEl.textContent = '';
+        statusEl.classList.add('opacity-0');
+    }
+
+    if (!providerId) {
+        // Add flow — show provider picker, default to the first unconfigured one.
+        // We render every configured vendor with a trailing green ✓ via the
+        // dropdown decorator, mirroring the visual language used by the
+        // capability provider dropdowns. The .active row already shows the
+        // currently selected vendor via its own background highlight, so we
+        // intentionally suppress the global active-row ✓ for this picker
+        // (see CSS) — otherwise configured + selected rows would show two.
+        // Expanded custom provider cards ("custom:<id>") are edited via their
+        // dedicated modal, so they are excluded from this picker. Picking the
+        // "custom" entry creates a *new* custom provider via that modal —
+        // this is how multiple OpenAI-compatible endpoints are added.
+        const builtinProviders = modelsState.providers.filter(p => !isCustomProviderCard(p));
+        const pickerOpts = builtinProviders.map(p => ({
+            value: p.id,
+            label: localizedLabel(p.label),
+            _configured: !!p.configured,
+        }));
+        // In multi-provider mode the backend replaces the bare "custom" card
+        // with the expanded ones; re-add it here so the entry stays available.
+        if (!pickerOpts.some(o => o.value === 'custom')) {
+            pickerOpts.push({ value: 'custom', label: t('models_custom_vendor_label'), _configured: false });
+        }
+        // "Custom" always behaves as an add-new action (multiple entries
+        // allowed), so it shows a + mark instead of the configured ✓.
+        pickerOpts.forEach(o => { if (o.value === 'custom') { o._isAddNew = true; o._configured = false; } });
+        const unconfigured = builtinProviders.filter(p => !p.configured);
+        const defaultId = (unconfigured[0] && unconfigured[0].id) || (builtinProviders[0] && builtinProviders[0].id) || 'custom';
+        pickerWrap.classList.remove('hidden');
+        const pickerEl = document.getElementById('vendor-modal-picker');
+        const onPick = (val) => {
+            if (val === 'custom') {
+                // "Custom" in the add flow always creates a new
+                // OpenAI-compatible provider entry via the dedicated modal
+                // (name + base + key), supporting multiple custom endpoints.
+                closeVendorModal();
+                openCustomProviderModal('');
+                return;
+            }
+            fillVendorModalForProvider(val);
+        };
+        initDropdown(pickerEl, pickerOpts, defaultId, onPick);
+        decorateVendorModalPicker(pickerEl, pickerOpts);
+        onPick(defaultId);
+    } else {
+        pickerWrap.classList.add('hidden');
+        fillVendorModalForProvider(providerId);
+    }
+
+    overlay.classList.remove('hidden');
+
+    document.getElementById('vendor-modal-cancel').onclick = closeVendorModal;
+    document.getElementById('vendor-modal-save').onclick = saveVendorModal;
+    clearBtn.onclick = clearVendorModal;
+
+    // Once the user edits the masked value, drop the "masked sentinel" dataset
+    // so the save handler treats their input as a real new key. We compare on
+    // the next tick because keydown fires before the new char lands in .value.
+    keyInput.oninput = function () {
+        if (keyInput.dataset.masked === '1' && keyInput.value !== keyInput.dataset.maskedVal) {
+            keyInput.dataset.masked = '';
+        }
+    };
+
+    function onOverlayClick(e) {
+        if (e.target === overlay) {
+            closeVendorModal();
+            overlay.removeEventListener('click', onOverlayClick);
+        }
+    }
+    overlay.addEventListener('click', onOverlayClick);
+    keyInput.focus();
+}
+
+function fillVendorModalForProvider(providerId) {
+    const meta = modelsState.providers.find(p => p.id === providerId);
+    if (!meta) return;
+    document.getElementById('vendor-modal-title').textContent = localizedLabel(meta.label);
+    document.getElementById('vendor-modal-subtitle').textContent = meta.id;
+
+    // ----- API Base -----
+    // Always reflect the *current effective* base as the input value so the
+    // user can see (and edit) what's in use today. Placeholder is reserved
+    // strictly for the "not yet typed anything" state and shows the official
+    // default — never mixed with the actual value.
+    const baseWrap = document.getElementById('vendor-modal-base-wrap');
+    const baseInput = document.getElementById('vendor-modal-base');
+    const baseHint = document.getElementById('vendor-modal-base-hint');
+    if (meta.api_base_field) {
+        baseWrap.classList.remove('hidden');
+        baseInput.placeholder = meta.api_base_default || meta.api_base_placeholder || '';
+        baseInput.value = meta.api_base || '';
+        baseHint.classList.add('hidden');
+    } else {
+        baseWrap.classList.add('hidden');
+        baseInput.value = '';
+    }
+
+    // ----- API Key -----
+    // For configured vendors, surface the masked key as the input *value* so
+    // it shows up in the same dark text as a real entry — making "configured"
+    // visually unambiguous. The masked form (e.g. "sk-r***zRU") is also a
+    // sentinel: the save handler treats untouched masked input as "no change".
+    const keyInput = document.getElementById('vendor-modal-key');
+    if (meta.configured && meta.api_key_masked) {
+        keyInput.value = meta.api_key_masked;
+        keyInput.dataset.masked = '1';
+        keyInput.dataset.maskedVal = meta.api_key_masked;
+        keyInput.placeholder = '';
+    } else {
+        keyInput.value = '';
+        keyInput.dataset.masked = '';
+        keyInput.dataset.maskedVal = '';
+        keyInput.placeholder = 'sk-...';
+    }
+
+    const clearBtn = document.getElementById('vendor-modal-clear');
+    clearBtn.classList.toggle('hidden', !meta.configured);
+
+    vendorModalState.providerId = providerId;
+}
+
+function closeVendorModal() {
+    document.getElementById('vendor-modal-overlay').classList.add('hidden');
+}
+
+function saveVendorModal() {
+    const providerId = vendorModalState.providerId;
+    if (!providerId) return;
+    const keyInput = document.getElementById('vendor-modal-key');
+    const apiBase = document.getElementById('vendor-modal-base').value.trim();
+
+    // Treat "input still equals the masked value we surfaced on open" as "no
+    // change" — the backend uses missing/empty api_key to skip the field.
+    let apiKey = keyInput.value.trim();
+    const masked = keyInput.dataset.masked === '1';
+    const maskedVal = keyInput.dataset.maskedVal || '';
+    if (masked && apiKey === maskedVal) {
+        apiKey = '';
+    }
+
+    if (!apiKey && !masked) {
+        // First-time setup with no key entered → nudge the user.
+        keyInput.focus();
+        return;
+    }
+
+    const btn = document.getElementById('vendor-modal-save');
+    btn.disabled = true;
+    const payload = { action: 'set_provider', provider_id: providerId, api_base: apiBase };
+    if (apiKey) payload.api_key = apiKey;
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify(payload),
+    }).then(r => r.json()).then(data => {
+        btn.disabled = false;
+        if (data.status === 'success') {
+            closeVendorModal();
+            const onSaved = vendorModalState.onSaved;
+            if (onSaved) {
+                try { onSaved(providerId); } catch (e) { /* noop */ }
+            } else {
+                loadModelsView();
+            }
+        } else {
+            showStatus('vendor-modal-status', 'models_save_failed', true);
+        }
+    }).catch(() => {
+        btn.disabled = false;
+        showStatus('vendor-modal-status', 'models_save_failed', true);
+    });
+}
+
+function clearVendorModal() {
+    const providerId = vendorModalState.providerId;
+    if (!providerId) return;
+    showConfirmDialog({
+        title: t('models_clear_confirm_title'),
+        message: t('models_clear_confirm_msg'),
+        okText: t('models_clear_credential'),
+        cancelText: t('cancel'),
+        onConfirm: () => {
+            fetch('/api/models', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ action: 'delete_provider', provider_id: providerId }),
+            }).then(r => r.json()).then(data => {
+                if (data.status === 'success') {
+                    closeVendorModal();
+                    loadModelsView();
+                } else {
+                    showStatus('vendor-modal-status', 'models_clear_failed', true);
+                }
+            }).catch(() => showStatus('vendor-modal-status', 'models_clear_failed', true));
+        }
+    });
+}
+
+// =====================================================================
+// Custom (OpenAI-compatible) provider modal — add / edit
+// =====================================================================
+// State for the dedicated custom-provider modal. `editId` is empty when
+// adding and set to the provider id when editing.
+let customProviderModalState = { editId: '' };
+
+function openCustomProviderModal(providerId) {
+    const editing = !!providerId;
+    customProviderModalState = { editId: editing ? providerId : '' };
+
+    const card = editing ? getCustomProviderCards().find(p => p.custom_id === providerId) : null;
+
+    const overlay = document.getElementById('custom-provider-modal-overlay');
+    if (!overlay) return;
+
+    document.getElementById('custom-provider-modal-title').textContent =
+        editing ? t('models_custom_edit_title') : t('models_custom_add_title');
+
+    const nameInput = document.getElementById('custom-provider-name');
+    const baseInput = document.getElementById('custom-provider-base');
+    const keyInput = document.getElementById('custom-provider-key');
+
+    nameInput.value = card ? (card.custom_name || '') : '';
+    baseInput.value = card ? (card.api_base || '') : '';
+
+    // Surface the masked key as the value for configured providers so the
+    // "already set" state is unambiguous; an untouched masked value means
+    // "keep the existing key" on save (mirrors the vendor modal contract).
+    if (card && card.configured && card.api_key_masked) {
+        keyInput.value = card.api_key_masked;
+        keyInput.dataset.masked = '1';
+        keyInput.dataset.maskedVal = card.api_key_masked;
+    } else {
+        keyInput.value = '';
+        keyInput.dataset.masked = '';
+        keyInput.dataset.maskedVal = '';
+    }
+    keyInput.oninput = function () {
+        if (keyInput.dataset.masked === '1' && keyInput.value !== keyInput.dataset.maskedVal) {
+            keyInput.dataset.masked = '';
+        }
+    };
+
+    const statusEl = document.getElementById('custom-provider-modal-status');
+    if (statusEl) { statusEl.textContent = ''; statusEl.classList.add('opacity-0'); }
+
+    overlay.classList.remove('hidden');
+    document.getElementById('custom-provider-modal-cancel').onclick = closeCustomProviderModal;
+    document.getElementById('custom-provider-modal-save').onclick = saveCustomProviderModal;
+
+    // Delete is only available when editing an existing provider.
+    const deleteBtn = document.getElementById('custom-provider-modal-delete');
+    if (deleteBtn) {
+        deleteBtn.classList.toggle('hidden', !editing);
+        deleteBtn.onclick = editing ? () => deleteCustomProvider(providerId) : null;
+    }
+
+    function onOverlayClick(e) {
+        if (e.target === overlay) {
+            closeCustomProviderModal();
+            overlay.removeEventListener('click', onOverlayClick);
+        }
+    }
+    overlay.addEventListener('click', onOverlayClick);
+    nameInput.focus();
+}
+
+function closeCustomProviderModal() {
+    const overlay = document.getElementById('custom-provider-modal-overlay');
+    if (overlay) overlay.classList.add('hidden');
+}
+
+function saveCustomProviderModal() {
+    const name = document.getElementById('custom-provider-name').value.trim();
+    const apiBase = document.getElementById('custom-provider-base').value.trim();
+    const keyInput = document.getElementById('custom-provider-key');
+
+    if (!name) {
+        showStatus('custom-provider-modal-status', 'models_custom_name_required', true);
+        document.getElementById('custom-provider-name').focus();
+        return;
+    }
+    const editing = !!customProviderModalState.editId;
+    if (!editing && !apiBase) {
+        showStatus('custom-provider-modal-status', 'models_custom_base_required', true);
+        document.getElementById('custom-provider-base').focus();
+        return;
+    }
+
+    // Untouched masked key => no change (omit from payload).
+    let apiKey = keyInput.value.trim();
+    if (keyInput.dataset.masked === '1' && apiKey === (keyInput.dataset.maskedVal || '')) {
+        apiKey = '';
+    }
+
+    const payload = {
+        action: 'set_custom_provider',
+        name: name,
+        api_base: apiBase,
+    };
+    if (apiKey) payload.api_key = apiKey;
+    if (editing) payload.id = customProviderModalState.editId;
+
+    const btn = document.getElementById('custom-provider-modal-save');
+    btn.disabled = true;
+    fetch('/api/models', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify(payload),
+    }).then(r => r.json()).then(data => {
+        btn.disabled = false;
+        if (data.status === 'success') {
+            closeCustomProviderModal();
+            loadModelsView();
+        } else {
+            showStatus('custom-provider-modal-status', 'models_save_failed', true);
+        }
+    }).catch(() => {
+        btn.disabled = false;
+        showStatus('custom-provider-modal-status', 'models_save_failed', true);
+    });
+}
+
+function deleteCustomProvider(providerId) {
+    showConfirmDialog({
+        title: t('models_custom_delete_confirm_title'),
+        message: t('models_custom_delete_confirm_msg'),
+        okText: t('models_custom_delete'),
+        cancelText: t('cancel'),
+        onConfirm: () => {
+            fetch('/api/models', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ action: 'delete_custom_provider', id: providerId }),
+            }).then(r => r.json()).then(data => {
+                if (data.status === 'success') {
+                    closeCustomProviderModal();
+                    loadModelsView();
+                }
+            }).catch(() => { /* noop */ });
+        }
+    });
+}
+
+// =====================================================================
+// Channels View
+// =====================================================================
+let channelsData = [];
+
+function loadChannelsView() {
+    const container = document.getElementById('channels-content');
+    container.innerHTML = `<div class="flex items-center gap-2 py-8 justify-center text-slate-400 dark:text-slate-500 text-sm">
+        <i class="fas fa-spinner fa-spin text-xs"></i><span>Loading...</span></div>`;
+
+    fetch('/api/channels').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        channelsData = data.channels || [];
+        renderActiveChannels();
+    }).catch(() => {
+        container.innerHTML = '<p class="text-sm text-red-400 py-8 text-center">Failed to load channels</p>';
+    });
+}
+
+function renderActiveChannels() {
+    stopWeixinQrPoll();
+    stopWeixinStatusPoll();
+    const container = document.getElementById('channels-content');
+    container.innerHTML = '';
+    closeAddChannelPanel();
+
+    const activeChannels = channelsData.filter(ch => ch.active);
+
+    if (activeChannels.length === 0) {
+        container.innerHTML = `
+            <div class="flex flex-col items-center justify-center py-20">
+                <div class="w-16 h-16 rounded-2xl bg-blue-50 dark:bg-blue-900/20 flex items-center justify-center mb-4">
+                    <i class="fas fa-tower-broadcast text-blue-400 text-xl"></i>
+                </div>
+                <p class="text-slate-500 dark:text-slate-400 font-medium">${t('channels_empty')}</p>
+                <p class="text-sm text-slate-400 dark:text-slate-500 mt-1">${t('channels_empty_desc')}</p>
+            </div>`;
+        return;
+    }
+
+    activeChannels.forEach(ch => {
+        const label = (typeof ch.label === 'object') ? (ch.label[currentLang] || ch.label.en) : ch.label;
+        const card = document.createElement('div');
+        card.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6';
+        card.id = `channel-card-${ch.name}`;
+
+        const fieldsHtml = buildChannelFieldsHtml(ch.name, ch.fields || []);
+        const hasFields = (ch.fields || []).length > 0;
+
+        const weixinWaiting = ch.name === 'weixin' && ch.login_status && ch.login_status !== 'logged_in';
+        const wecomNeedsCreds = ch.name === 'wecom_bot' && !_wecomBotHasCreds(ch);
+        // 飞书 active 卡片渲染带 Tab 的 panel：手动填写 + 扫码重建（覆盖现有配置）
+        const isFeishu = ch.name === 'feishu';
+        let statusDot, statusText;
+        if (weixinWaiting) {
+            statusDot = 'bg-amber-400 animate-pulse';
+            statusText = ch.login_status === 'scanned'
+                ? `<span class="text-xs text-primary-500">${t('weixin_scan_scanned')}</span>`
+                : `<span class="text-xs text-amber-500">${t('weixin_scan_waiting')}</span>`;
+        } else if (wecomNeedsCreds) {
+            statusDot = 'bg-amber-400 animate-pulse';
+            statusText = `<span class="text-xs text-amber-500">${t('channels_connecting')}</span>`;
+        } else {
+            statusDot = 'bg-primary-400';
+            statusText = `<span class="text-xs text-primary-500">${t('channels_connected')}</span>`;
+        }
+
+        card.innerHTML = `
+            <div class="flex items-center gap-4${hasFields || weixinWaiting || wecomNeedsCreds || isFeishu ? ' mb-5' : ''}">
+                <div class="w-10 h-10 rounded-xl bg-${ch.color}-50 dark:bg-${ch.color}-900/20 flex items-center justify-center flex-shrink-0">
+                    <i class="fas ${ch.icon} text-${ch.color}-500 text-base"></i>
+                </div>
+                <div class="flex-1 min-w-0">
+                    <div class="flex items-center gap-2">
+                        <span class="font-semibold text-slate-800 dark:text-slate-100">${escapeHtml(label)}</span>
+                        <span class="w-2 h-2 rounded-full ${statusDot}"></span>
+                        ${statusText}
+                    </div>
+                    <p class="text-xs text-slate-500 dark:text-slate-400 mt-0.5 font-mono">${escapeHtml(ch.name)}</p>
+                </div>
+                <button onclick="disconnectChannel('${ch.name}')"
+                    class="px-3 py-1.5 rounded-lg text-xs font-medium
+                           bg-red-50 dark:bg-red-900/20 text-red-500 dark:text-red-400
+                           hover:bg-red-100 dark:hover:bg-red-900/40
+                           cursor-pointer transition-colors flex-shrink-0">
+                    ${t('channels_disconnect')}
+                </button>
+            </div>
+            ${weixinWaiting ? `<div id="weixin-active-qr" class="flex flex-col items-center py-2">
+                <button onclick="showWeixinActiveQr()"
+                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150">
+                    ${t('weixin_scan_title')}
+                </button>
+            </div>` : ''}
+            ${wecomNeedsCreds ? `<div id="wecom-active-auth" class="flex flex-col items-center py-2">
+                <p class="text-sm text-slate-500 dark:text-slate-400 mb-3">${t('wecom_scan_desc')}</p>
+                <button onclick="startWecomBotAuthInCard()"
+                    class="px-5 py-2 rounded-lg bg-emerald-500 hover:bg-emerald-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150">
+                    <i class="fas fa-qrcode mr-2"></i>${t('wecom_scan_btn')}
+                </button>
+                <div id="wecom-card-scan-status" class="mt-3"></div>
+            </div>` : ''}
+            ${isFeishu ? buildFeishuPanel(ch, true) : (hasFields ? `<div class="space-y-4">
+                ${fieldsHtml}
+                <div class="flex items-center justify-end gap-3 pt-1">
+                    <span id="ch-status-${ch.name}" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                    <button onclick="saveChannelConfig('${ch.name}')"
+                        class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                               cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                        id="ch-save-${ch.name}">${t('channels_save')}</button>
+                </div>
+            </div>` : '')}`;
+
+        container.appendChild(card);
+        bindSecretFieldEvents(card);
+
+        if (weixinWaiting) {
+            startWeixinActiveStatusPoll();
+        }
+    });
+}
+
+function buildChannelFieldsHtml(chName, fields) {
+    let html = '';
+    fields.forEach(f => {
+        const inputId = `ch-${chName}-${f.key}`;
+        let inputHtml = '';
+        if (f.type === 'bool') {
+            const checked = f.value ? 'checked' : '';
+            inputHtml = `<label class="relative inline-flex items-center cursor-pointer">
+                <input id="${inputId}" type="checkbox" ${checked} class="sr-only peer" data-field="${f.key}" data-ch="${chName}">
+                <div class="w-9 h-5 bg-slate-200 dark:bg-slate-700 peer-checked:bg-primary-400 rounded-full
+                            after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white
+                            after:rounded-full after:h-4 after:w-4 after:transition-all peer-checked:after:translate-x-full"></div>
+            </label>`;
+        } else if (f.type === 'secret') {
+            inputHtml = `<input id="${inputId}" type="text" value="${escapeHtml(String(f.value || ''))}"
+                data-field="${f.key}" data-ch="${chName}" data-masked="${f.value ? '1' : ''}"
+                class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                       bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                       focus:outline-none focus:border-primary-500 font-mono transition-colors
+                       ${f.value ? 'cfg-key-masked' : ''}"
+                placeholder="${escapeHtml(f.label)}">`;
+        } else {
+            const inputType = f.type === 'number' ? 'number' : 'text';
+            inputHtml = `<input id="${inputId}" type="${inputType}" value="${escapeHtml(String(f.value ?? f.default ?? ''))}"
+                data-field="${f.key}" data-ch="${chName}"
+                class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                       bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                       focus:outline-none focus:border-primary-500 font-mono transition-colors"
+                placeholder="${escapeHtml(f.label)}">`;
+        }
+        html += `<div>
+            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">${escapeHtml(f.label)}</label>
+            ${inputHtml}
+        </div>`;
+    });
+    return html;
+}
+
+function bindSecretFieldEvents(container) {
+    container.querySelectorAll('input[data-masked="1"]').forEach(inp => {
+        inp.addEventListener('focus', function() {
+            if (this.dataset.masked === '1') {
+                this.value = '';
+                this.dataset.masked = '';
+                this.classList.remove('cfg-key-masked');
+            }
+        });
+    });
+}
+
+function showChannelStatus(chName, msgKey, isError) {
+    const el = document.getElementById(`ch-status-${chName}`);
+    if (!el) return;
+    el.textContent = t(msgKey);
+    el.classList.toggle('text-red-500', !!isError);
+    el.classList.toggle('text-primary-500', !isError);
+    el.classList.remove('opacity-0');
+    setTimeout(() => el.classList.add('opacity-0'), 2500);
+}
+
+function saveChannelConfig(chName) {
+    const card = document.getElementById(`channel-card-${chName}`);
+    if (!card) return;
+
+    const updates = {};
+    card.querySelectorAll('input[data-ch="' + chName + '"]').forEach(inp => {
+        const key = inp.dataset.field;
+        if (inp.type === 'checkbox') {
+            updates[key] = inp.checked;
+        } else {
+            if (inp.dataset.masked === '1') return;
+            updates[key] = inp.value;
+        }
+    });
+
+    const btn = document.getElementById(`ch-save-${chName}`);
+    if (btn) btn.disabled = true;
+
+    fetch('/api/channels', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action: 'save', channel: chName, config: updates })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            showChannelStatus(chName, data.restarted ? 'channels_restarted' : 'channels_saved', false);
+        } else {
+            showChannelStatus(chName, 'channels_save_error', true);
+        }
+    })
+    .catch(() => showChannelStatus(chName, 'channels_save_error', true))
+    .finally(() => { if (btn) btn.disabled = false; });
+}
+
+function disconnectChannel(chName) {
+    const ch = channelsData.find(c => c.name === chName);
+    const label = ch ? ((typeof ch.label === 'object') ? (ch.label[currentLang] || ch.label.en) : ch.label) : chName;
+
+    showConfirmDialog({
+        title: t('channels_disconnect'),
+        message: t('channels_disconnect_confirm'),
+        okText: t('channels_disconnect'),
+        cancelText: t('channels_cancel'),
+        onConfirm: () => {
+            fetch('/api/channels', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ action: 'disconnect', channel: chName })
+            })
+            .then(r => r.json())
+            .then(data => {
+                if (data.status === 'success') {
+                    if (ch) ch.active = false;
+                    renderActiveChannels();
+                }
+            })
+            .catch(() => {});
+        }
+    });
+}
+
+// --- Add channel panel ---
+function openAddChannelPanel() {
+    const panel = document.getElementById('channels-add-panel');
+    const activeNames = new Set(channelsData.filter(c => c.active).map(c => c.name));
+    const available = channelsData.filter(c => !activeNames.has(c.name));
+
+    const content = document.getElementById('channels-content');
+    if (activeNames.size === 0 && content) content.classList.add('hidden');
+
+    if (available.length === 0) {
+        panel.innerHTML = `<div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6 text-center">
+            <p class="text-sm text-slate-500 dark:text-slate-400">${currentLang === 'zh' ? '所有通道均已接入' : 'All channels are already connected'}</p>
+            <button onclick="closeAddChannelPanel()" class="mt-3 text-xs text-slate-400 hover:text-slate-600 dark:hover:text-slate-300 cursor-pointer">${t('channels_cancel')}</button>
+        </div>`;
+        panel.classList.remove('hidden');
+        return;
+    }
+
+    const ddOptions = [
+        { value: '', label: t('channels_select_placeholder') },
+        ...available.map(ch => {
+            const label = (typeof ch.label === 'object') ? (ch.label[currentLang] || ch.label.en) : ch.label;
+            return { value: ch.name, label: `${label} (${ch.name})` };
+        })
+    ];
+
+    panel.innerHTML = `
+        <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-primary-200 dark:border-primary-800 p-6">
+            <div class="flex items-center gap-3 mb-5">
+                <div class="w-9 h-9 rounded-lg bg-primary-50 dark:bg-primary-900/30 flex items-center justify-center">
+                    <i class="fas fa-plus text-primary-500 text-sm"></i>
+                </div>
+                <h3 class="font-semibold text-slate-800 dark:text-slate-100">${t('channels_add')}</h3>
+            </div>
+            <div class="mb-4">
+                <div id="add-channel-select" class="cfg-dropdown" tabindex="0">
+                    <div class="cfg-dropdown-selected">
+                        <span class="cfg-dropdown-text">--</span>
+                        <i class="fas fa-chevron-down cfg-dropdown-arrow"></i>
+                    </div>
+                    <div class="cfg-dropdown-menu"></div>
+                </div>
+            </div>
+            <div id="add-channel-fields" class="space-y-4"></div>
+            <div id="add-channel-actions" class="hidden flex items-center justify-end gap-3 pt-4">
+                <button onclick="closeAddChannelPanel()"
+                    class="px-4 py-2 rounded-lg border border-slate-200 dark:border-white/10
+                           text-slate-600 dark:text-slate-300 text-sm font-medium
+                           hover:bg-slate-50 dark:hover:bg-white/5
+                           cursor-pointer transition-colors duration-150">${t('channels_cancel')}</button>
+                <button id="add-channel-submit" onclick="submitAddChannel()"
+                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed">${t('channels_connect_btn')}</button>
+            </div>
+        </div>`;
+    panel.classList.remove('hidden');
+    panel.scrollIntoView({ behavior: 'smooth', block: 'nearest' });
+
+    const ddEl = document.getElementById('add-channel-select');
+    initDropdown(ddEl, ddOptions, '', onAddChannelSelect);
+}
+
+function closeAddChannelPanel() {
+    stopWeixinQrPoll();
+    stopFeishuRegisterPoll();
+    const panel = document.getElementById('channels-add-panel');
+    if (panel) {
+        panel.classList.add('hidden');
+        panel.innerHTML = '';
+    }
+    const content = document.getElementById('channels-content');
+    if (content) content.classList.remove('hidden');
+}
+
+function onAddChannelSelect(chName) {
+    stopWeixinQrPoll();
+    stopFeishuRegisterPoll();
+    const fieldsContainer = document.getElementById('add-channel-fields');
+    const actions = document.getElementById('add-channel-actions');
+
+    if (!chName) {
+        fieldsContainer.innerHTML = '';
+        actions.classList.add('hidden');
+        return;
+    }
+
+    if (chName === 'weixin') {
+        actions.classList.add('hidden');
+        fieldsContainer.innerHTML = `
+            <div id="weixin-qr-panel" class="flex flex-col items-center py-4">
+                <p class="text-sm text-slate-500 dark:text-slate-400 mb-4">${t('weixin_scan_loading')}</p>
+            </div>`;
+        startWeixinQrLogin();
+        return;
+    }
+
+    if (chName === 'wecom_bot') {
+        actions.classList.add('hidden');
+        const ch = channelsData.find(c => c.name === chName);
+        fieldsContainer.innerHTML = buildWecomBotPanel(ch);
+        return;
+    }
+
+    if (chName === 'feishu') {
+        actions.classList.add('hidden');
+        const ch = channelsData.find(c => c.name === chName);
+        fieldsContainer.innerHTML = buildFeishuPanel(ch);
+        return;
+    }
+
+    const ch = channelsData.find(c => c.name === chName);
+    if (!ch) return;
+
+    fieldsContainer.innerHTML = buildChannelFieldsHtml(chName, ch.fields || []);
+    bindSecretFieldEvents(fieldsContainer);
+    actions.classList.remove('hidden');
+}
+
+function submitAddChannel() {
+    const ddEl = document.getElementById('add-channel-select');
+    const chName = getDropdownValue(ddEl);
+    if (!chName) return;
+
+    const fieldsContainer = document.getElementById('add-channel-fields');
+    const updates = {};
+    fieldsContainer.querySelectorAll('input[data-ch="' + chName + '"]').forEach(inp => {
+        const key = inp.dataset.field;
+        if (inp.type === 'checkbox') {
+            updates[key] = inp.checked;
+        } else {
+            if (inp.dataset.masked === '1') return;
+            updates[key] = inp.value;
+        }
+    });
+
+    const btn = document.getElementById('add-channel-submit');
+    if (btn) { btn.disabled = true; btn.textContent = t('channels_connecting'); }
+
+    fetch('/api/channels', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action: 'connect', channel: chName, config: updates })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            const ch = channelsData.find(c => c.name === chName);
+            if (ch) {
+                ch.active = true;
+                (ch.fields || []).forEach(f => {
+                    if (updates[f.key] !== undefined) {
+                        f.value = f.type === 'secret' ? ChannelsHandler_maskSecret(updates[f.key]) : updates[f.key];
+                    }
+                });
+            }
+            renderActiveChannels();
+        } else {
+            if (btn) { btn.disabled = false; btn.textContent = t('channels_connect_btn'); }
+        }
+    })
+    .catch(() => {
+        if (btn) { btn.disabled = false; btn.textContent = t('channels_connect_btn'); }
+    });
+}
+
+// =====================================================================
+// WeChat QR Login
+// =====================================================================
+let _weixinQrPollTimer = null;
+let _weixinStatusPollTimer = null;
+
+function stopWeixinStatusPoll() {
+    if (_weixinStatusPollTimer) {
+        clearTimeout(_weixinStatusPollTimer);
+        _weixinStatusPollTimer = null;
+    }
+}
+
+function startWeixinActiveStatusPoll() {
+    stopWeixinStatusPoll();
+    _weixinStatusPollTimer = setTimeout(() => {
+        fetch('/api/channels').then(r => r.json()).then(data => {
+            if (data.status !== 'success') return;
+            const wx = (data.channels || []).find(c => c.name === 'weixin');
+            if (!wx || !wx.active) return;
+            if (wx.login_status === 'logged_in') {
+                channelsData = data.channels;
+                renderActiveChannels();
+            } else {
+                const ch = channelsData.find(c => c.name === 'weixin');
+                if (ch) ch.login_status = wx.login_status;
+                startWeixinActiveStatusPoll();
+            }
+        }).catch(() => { startWeixinActiveStatusPoll(); });
+    }, 3000);
+}
+
+function showWeixinActiveQr() {
+    const container = document.getElementById('weixin-active-qr');
+    if (!container) return;
+    container.innerHTML = `
+        <div id="weixin-qr-panel" class="flex flex-col items-center py-2">
+            <p class="text-sm text-slate-500 dark:text-slate-400 mb-4">${t('weixin_scan_loading')}</p>
+        </div>`;
+    stopWeixinStatusPoll();
+    startWeixinQrLogin();
+}
+
+function stopWeixinQrPoll() {
+    if (_weixinQrPollTimer) {
+        clearTimeout(_weixinQrPollTimer);
+        _weixinQrPollTimer = null;
+    }
+}
+
+function startWeixinQrLogin() {
+    stopWeixinQrPoll();
+    fetch('/api/weixin/qrlogin')
+        .then(r => r.json())
+        .then(data => {
+            const panel = document.getElementById('weixin-qr-panel');
+            if (!panel) return;
+            if (data.status !== 'success') {
+                panel.innerHTML = `<p class="text-sm text-red-500">${t('weixin_scan_fail')}: ${data.message || ''}</p>`;
+                return;
+            }
+            renderWeixinQr(data.qr_image || data.qrcode_url, 'waiting');
+            if (data.source === 'channel') {
+                startWeixinActiveStatusPoll();
+            } else {
+                pollWeixinQrStatus();
+            }
+        })
+        .catch(() => {
+            const panel = document.getElementById('weixin-qr-panel');
+            if (panel) panel.innerHTML = `<p class="text-sm text-red-500">${t('weixin_scan_fail')}</p>`;
+        });
+}
+
+function renderWeixinQr(qrcodeUrl, status) {
+    const panel = document.getElementById('weixin-qr-panel');
+    if (!panel) return;
+
+    let statusText = t('weixin_scan_waiting');
+    let statusColor = 'text-slate-500 dark:text-slate-400';
+    if (status === 'scanned') {
+        statusText = t('weixin_scan_scanned');
+        statusColor = 'text-primary-500';
+    } else if (status === 'expired') {
+        statusText = t('weixin_scan_expired');
+        statusColor = 'text-amber-500';
+    } else if (status === 'confirmed') {
+        statusText = t('weixin_scan_success');
+        statusColor = 'text-primary-500';
+    }
+
+    panel.innerHTML = `
+        <div class="flex flex-col items-center">
+            <p class="text-sm font-medium text-slate-700 dark:text-slate-200 mb-1">${t('weixin_scan_title')}</p>
+            <p class="text-xs text-slate-400 dark:text-slate-500 mb-4">${t('weixin_scan_desc')}</p>
+            <div class="bg-white p-3 rounded-xl shadow-sm border border-slate-100 dark:border-slate-700 mb-3">
+                <img src="${escapeHtml(qrcodeUrl)}" alt="QR Code" class="w-52 h-52" style="image-rendering: pixelated;"/>
+            </div>
+            <p class="text-xs ${statusColor} mb-1">${statusText}</p>
+            <p class="text-xs text-slate-400 dark:text-slate-500">${t('weixin_qr_tip')}</p>
+        </div>`;
+}
+
+function pollWeixinQrStatus() {
+    _weixinQrPollTimer = setTimeout(() => {
+        fetch('/api/weixin/qrlogin', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ action: 'poll' })
+        })
+        .then(r => r.json())
+        .then(data => {
+            const panel = document.getElementById('weixin-qr-panel');
+            if (!panel) { stopWeixinQrPoll(); return; }
+
+            if (data.status !== 'success') {
+                pollWeixinQrStatus();
+                return;
+            }
+
+            const qrStatus = data.qr_status;
+            if (qrStatus === 'confirmed') {
+                renderWeixinQr('', 'confirmed');
+                panel.innerHTML = `
+                    <div class="flex flex-col items-center py-4">
+                        <div class="w-12 h-12 rounded-full bg-primary-50 dark:bg-primary-900/30 flex items-center justify-center mb-3">
+                            <i class="fas fa-check text-primary-500 text-lg"></i>
+                        </div>
+                        <p class="text-sm font-medium text-primary-600 dark:text-primary-400">${t('weixin_scan_success')}</p>
+                    </div>`;
+                connectWeixinAfterQr();
+            } else if (qrStatus === 'expired' && (data.qr_image || data.qrcode_url)) {
+                renderWeixinQr(data.qr_image || data.qrcode_url, 'waiting');
+                pollWeixinQrStatus();
+            } else if (qrStatus === 'scaned') {
+                const img = panel.querySelector('img');
+                const currentSrc = img ? img.src : '';
+                renderWeixinQr(currentSrc, 'scanned');
+                pollWeixinQrStatus();
+            } else {
+                pollWeixinQrStatus();
+            }
+        })
+        .catch(() => {
+            pollWeixinQrStatus();
+        });
+    }, 2000);
+}
+
+function connectWeixinAfterQr() {
+    fetch('/api/channels', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ action: 'connect', channel: 'weixin', config: {} })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            const ch = channelsData.find(c => c.name === 'weixin');
+            if (ch) ch.active = true;
+            setTimeout(() => renderActiveChannels(), 1500);
+        }
+    })
+    .catch(() => {});
+}
+
+// =====================================================================
+// WeCom Bot QR Auth
+// =====================================================================
+// NOTE: This is the only remaining external script in the Web Console.
+// Tencent's WeCom Bot SDK must be loaded from their official CDN — it
+// performs runtime origin/signature checks and will not work if
+// self-hosted. The SDK is fetched lazily, only when the user opens the
+// "WeCom Bot" channel QR-login flow, so the rest of the console works
+// fully offline.
+const WECOM_BOT_SDK_URL = 'https://wwcdn.weixin.qq.com/node/wework/js/wecom-aibot-sdk@0.1.0.min.js';
+const WECOM_BOT_SOURCE = 'cowagent';
+let _wecomSdkLoaded = false;
+
+function ensureWecomSdkLoaded() {
+    return new Promise((resolve, reject) => {
+        if (_wecomSdkLoaded && window.WecomAIBotSDK) { resolve(); return; }
+        if (document.querySelector(`script[src="${WECOM_BOT_SDK_URL}"]`)) {
+            _wecomSdkLoaded = true; resolve(); return;
+        }
+        const s = document.createElement('script');
+        s.src = WECOM_BOT_SDK_URL;
+        s.onload = () => { _wecomSdkLoaded = true; resolve(); };
+        s.onerror = () => reject(new Error('Failed to load WecomAIBotSDK'));
+        document.head.appendChild(s);
+    });
+}
+
+function _wecomBotHasCreds(ch) {
+    if (!ch || !ch.fields) return false;
+    const idField = ch.fields.find(f => f.key === 'wecom_bot_id');
+    const secretField = ch.fields.find(f => f.key === 'wecom_bot_secret');
+    return !!(idField && idField.value && secretField && secretField.value);
+}
+
+function buildWecomBotPanel(ch) {
+    const scanLabel = t('wecom_mode_scan');
+    const manualLabel = t('wecom_mode_manual');
+    const hasCreds = _wecomBotHasCreds(ch);
+    const defaultMode = hasCreds ? 'manual' : 'scan';
+    return `
+        <div id="wecom-bot-panel" data-default-mode="${defaultMode}">
+            <div class="flex items-center justify-center gap-1 mb-5 bg-slate-100 dark:bg-white/5 rounded-lg p-1">
+                <button id="wecom-tab-scan" onclick="switchWecomBotMode('scan')"
+                    class="flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors
+                           bg-white dark:bg-slate-700 text-slate-800 dark:text-slate-100 shadow-sm">
+                    ${scanLabel}
+                </button>
+                <button id="wecom-tab-manual" onclick="switchWecomBotMode('manual')"
+                    class="flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors
+                           text-slate-500 dark:text-slate-400 hover:text-slate-700 dark:hover:text-slate-200">
+                    ${manualLabel}
+                </button>
+            </div>
+            <div id="wecom-mode-content"></div>
+        </div>`;
+}
+
+function switchWecomBotMode(mode) {
+    const scanTab = document.getElementById('wecom-tab-scan');
+    const manualTab = document.getElementById('wecom-tab-manual');
+    const content = document.getElementById('wecom-mode-content');
+    const actions = document.getElementById('add-channel-actions');
+    if (!scanTab || !manualTab || !content) return;
+
+    const activeClasses = 'bg-white dark:bg-slate-700 text-slate-800 dark:text-slate-100 shadow-sm';
+    const inactiveClasses = 'text-slate-500 dark:text-slate-400 hover:text-slate-700 dark:hover:text-slate-200';
+
+    if (mode === 'scan') {
+        scanTab.className = scanTab.className.replace(/text-slate-500[^\s]*/g, '').replace(/hover:\S+/g, '');
+        scanTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${activeClasses}`;
+        manualTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${inactiveClasses}`;
+        actions.classList.add('hidden');
+        content.innerHTML = `
+            <div class="flex flex-col items-center py-4">
+                <p class="text-sm text-slate-600 dark:text-slate-300 mb-2">${t('wecom_scan_desc')}</p>
+                <button onclick="startWecomBotAuth()"
+                    class="mt-3 px-6 py-2.5 rounded-lg bg-emerald-500 hover:bg-emerald-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150">
+                    <i class="fas fa-qrcode mr-2"></i>${t('wecom_scan_btn')}
+                </button>
+                <div id="wecom-scan-status" class="mt-3"></div>
+            </div>`;
+    } else {
+        manualTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${activeClasses}`;
+        scanTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${inactiveClasses}`;
+        const ch = channelsData.find(c => c.name === 'wecom_bot');
+        content.innerHTML = `<div class="space-y-4">${buildChannelFieldsHtml('wecom_bot', ch ? ch.fields || [] : [])}</div>`;
+        bindSecretFieldEvents(content);
+        actions.classList.remove('hidden');
+    }
+}
+
+function startWecomBotAuth() {
+    const statusEl = document.getElementById('wecom-scan-status');
+    ensureWecomSdkLoaded().then(() => {
+        WecomAIBotSDK.openBotInfoAuthWindow({
+            source: WECOM_BOT_SOURCE,
+            onCreated: function(bot) {
+                if (statusEl) {
+                    statusEl.innerHTML = `
+                        <div class="flex flex-col items-center py-2">
+                            <div class="w-10 h-10 rounded-full bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center mb-2">
+                                <i class="fas fa-check text-emerald-500 text-lg"></i>
+                            </div>
+                            <p class="text-sm font-medium text-emerald-600 dark:text-emerald-400">${t('wecom_scan_success')}</p>
+                        </div>`;
+                }
+                connectWecomBotAfterAuth(bot.botid, bot.secret);
+            },
+            onError: function(err) {
+                if (statusEl) {
+                    statusEl.innerHTML = `<p class="text-sm text-red-500">${t('wecom_scan_fail')}: ${err.message || err.code || ''}</p>`;
+                }
+            }
+        });
+    }).catch(err => {
+        if (statusEl) {
+            statusEl.innerHTML = `<p class="text-sm text-red-500">SDK load failed: ${err.message}</p>`;
+        }
+    });
+}
+
+function connectWecomBotAfterAuth(botId, secret) {
+    fetch('/api/channels', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({
+            action: 'connect',
+            channel: 'wecom_bot',
+            config: { wecom_bot_id: botId, wecom_bot_secret: secret }
+        })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            const ch = channelsData.find(c => c.name === 'wecom_bot');
+            if (ch) {
+                ch.active = true;
+                (ch.fields || []).forEach(f => {
+                    if (f.key === 'wecom_bot_id') f.value = botId;
+                    if (f.key === 'wecom_bot_secret') f.value = ChannelsHandler_maskSecret(secret);
+                });
+            }
+            setTimeout(() => renderActiveChannels(), 1500);
+        }
+    })
+    .catch(() => {});
+}
+
+function startWecomBotAuthInCard() {
+    const statusEl = document.getElementById('wecom-card-scan-status');
+    ensureWecomSdkLoaded().then(() => {
+        WecomAIBotSDK.openBotInfoAuthWindow({
+            source: WECOM_BOT_SOURCE,
+            onCreated: function(bot) {
+                if (statusEl) {
+                    statusEl.innerHTML = `
+                        <div class="flex flex-col items-center py-2">
+                            <div class="w-10 h-10 rounded-full bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center mb-2">
+                                <i class="fas fa-check text-emerald-500 text-lg"></i>
+                            </div>
+                            <p class="text-sm font-medium text-emerald-600 dark:text-emerald-400">${t('wecom_scan_success')}</p>
+                        </div>`;
+                }
+                connectWecomBotAfterAuth(bot.botid, bot.secret);
+            },
+            onError: function(err) {
+                if (statusEl) {
+                    statusEl.innerHTML = `<p class="text-sm text-red-500">${t('wecom_scan_fail')}: ${err.message || err.code || ''}</p>`;
+                }
+            }
+        });
+    }).catch(err => {
+        if (statusEl) {
+            statusEl.innerHTML = `<p class="text-sm text-red-500">SDK load failed: ${err.message}</p>`;
+        }
+    });
+}
+
+// Initialize wecom bot panel with correct default mode when inserted into DOM
+document.addEventListener('DOMContentLoaded', function() {
+    const observer = new MutationObserver(function() {
+        const wecomPanel = document.getElementById('wecom-bot-panel');
+        if (wecomPanel && !wecomPanel.dataset.initialized) {
+            wecomPanel.dataset.initialized = '1';
+            switchWecomBotMode(wecomPanel.dataset.defaultMode || 'scan');
+        }
+        const feishuPanel = document.getElementById('feishu-panel');
+        if (feishuPanel && !feishuPanel.dataset.initialized) {
+            feishuPanel.dataset.initialized = '1';
+            switchFeishuMode(feishuPanel.dataset.defaultMode || 'scan');
+        }
+    });
+    observer.observe(document.body, { childList: true, subtree: true });
+});
+
+// =====================================================================
+// Feishu One-click App Registration (lark-oapi register_app)
+// =====================================================================
+let _feishuRegisterPollTimer = null;
+
+function _feishuHasCreds(ch) {
+    if (!ch || !ch.fields) return false;
+    const idField = ch.fields.find(f => f.key === 'feishu_app_id');
+    const secretField = ch.fields.find(f => f.key === 'feishu_app_secret');
+    return !!(idField && idField.value && secretField && secretField.value);
+}
+
+function buildFeishuPanel(ch, isActive) {
+    const scanLabel = t('feishu_mode_scan');
+    const manualLabel = t('feishu_mode_manual');
+    // 已有凭据时默认进入手动 Tab，方便修改；否则推荐扫码
+    const defaultMode = _feishuHasCreds(ch) ? 'manual' : 'scan';
+    const activeAttr = isActive ? 'data-active="1"' : '';
+    return `
+        <div id="feishu-panel" data-default-mode="${defaultMode}" ${activeAttr}>
+            <div class="flex items-center justify-center gap-1 mb-5 bg-slate-100 dark:bg-white/5 rounded-lg p-1">
+                <button id="feishu-tab-scan" onclick="switchFeishuMode('scan')"
+                    class="flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors
+                           bg-white dark:bg-slate-700 text-slate-800 dark:text-slate-100 shadow-sm">
+                    ${scanLabel}
+                </button>
+                <button id="feishu-tab-manual" onclick="switchFeishuMode('manual')"
+                    class="flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors
+                           text-slate-500 dark:text-slate-400 hover:text-slate-700 dark:hover:text-slate-200">
+                    ${manualLabel}
+                </button>
+            </div>
+            <div id="feishu-mode-content"></div>
+        </div>`;
+}
+
+function switchFeishuMode(mode) {
+    const panel = document.getElementById('feishu-panel');
+    const scanTab = document.getElementById('feishu-tab-scan');
+    const manualTab = document.getElementById('feishu-tab-manual');
+    const content = document.getElementById('feishu-mode-content');
+    if (!scanTab || !manualTab || !content) return;
+
+    // 已激活通道卡片中嵌入此 panel 时，没有 add-channel-actions（保存按钮就近渲染）
+    const isActive = panel && panel.dataset.active === '1';
+    const actions = isActive ? null : document.getElementById('add-channel-actions');
+
+    const activeClasses = 'bg-white dark:bg-slate-700 text-slate-800 dark:text-slate-100 shadow-sm';
+    const inactiveClasses = 'text-slate-500 dark:text-slate-400 hover:text-slate-700 dark:hover:text-slate-200';
+
+    stopFeishuRegisterPoll();
+
+    if (mode === 'scan') {
+        scanTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${activeClasses}`;
+        manualTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${inactiveClasses}`;
+        if (actions) actions.classList.add('hidden');
+        // active 卡片下扫码替换的提示文案，强调"创建新机器人会覆盖现有配置"
+        const desc = isActive
+            ? t('feishu_scan_replace_desc')
+            : t('feishu_scan_desc');
+        content.innerHTML = `
+            <div id="feishu-scan-panel" class="flex flex-col items-center py-4">
+                <p class="text-sm text-slate-600 dark:text-slate-300 mb-3 text-center">${desc}</p>
+                <button onclick="startFeishuRegister()"
+                    class="mt-2 px-6 py-2.5 rounded-lg bg-emerald-500 hover:bg-emerald-600 text-white text-sm font-medium
+                           cursor-pointer transition-colors duration-150">
+                    <i class="fas fa-qrcode mr-2"></i>${t('feishu_scan_btn')}
+                </button>
+                <div id="feishu-scan-status" class="mt-4 w-full"></div>
+            </div>`;
+    } else {
+        manualTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${activeClasses}`;
+        scanTab.className = `flex-1 px-3 py-1.5 rounded-md text-xs font-medium transition-colors ${inactiveClasses}`;
+        const ch = channelsData.find(c => c.name === 'feishu');
+        const fieldsHtml = buildChannelFieldsHtml('feishu', ch ? ch.fields || [] : []);
+        if (isActive) {
+            // 已接入卡片：内置保存按钮，复用 saveChannelConfig 走 update 流程
+            content.innerHTML = `
+                <div class="space-y-4">
+                    ${fieldsHtml}
+                    <div class="flex items-center justify-end gap-3 pt-1">
+                        <span id="ch-status-feishu" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                        <button onclick="saveChannelConfig('feishu')"
+                            class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                   cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                            id="ch-save-feishu">${t('channels_save')}</button>
+                    </div>
+                </div>`;
+        } else {
+            content.innerHTML = `<div class="space-y-4">${fieldsHtml}</div>`;
+            if (actions) actions.classList.remove('hidden');
+        }
+        bindSecretFieldEvents(content);
+    }
+}
+
+function stopFeishuRegisterPoll() {
+    if (_feishuRegisterPollTimer) {
+        clearTimeout(_feishuRegisterPollTimer);
+        _feishuRegisterPollTimer = null;
+    }
+}
+
+function startFeishuRegister(targetStatusId) {
+    const statusId = targetStatusId || 'feishu-scan-status';
+    const statusEl = document.getElementById(statusId);
+    if (statusEl) {
+        statusEl.innerHTML = `<p class="text-sm text-slate-500 dark:text-slate-400 text-center">${t('feishu_scan_loading')}</p>`;
+    }
+    stopFeishuRegisterPoll();
+    fetch('/api/feishu/register')
+        .then(r => r.json())
+        .then(data => {
+            if (data.status !== 'success') {
+                renderFeishuRegisterError(statusId, data.message || t('feishu_scan_fail'));
+                return;
+            }
+            renderFeishuQr(statusId, data.qr_image, data.qrcode_url);
+            pollFeishuRegisterStatus(statusId);
+        })
+        .catch(err => {
+            renderFeishuRegisterError(statusId, err.message || t('feishu_scan_fail'));
+        });
+}
+
+function renderFeishuQr(statusId, qrImage, qrUrl) {
+    const statusEl = document.getElementById(statusId);
+    if (!statusEl) return;
+    const imgHtml = qrImage
+        ? `<img src="${qrImage}" alt="QR" class="w-44 h-44 rounded-lg border border-slate-200 dark:border-white/10 bg-white p-2"/>`
+        : `<div class="w-44 h-44 rounded-lg border border-dashed border-slate-300 flex items-center justify-center text-xs text-slate-400">QR</div>`;
+    statusEl.innerHTML = `
+        <div class="flex flex-col items-center gap-3">
+            ${imgHtml}
+            <p class="text-xs text-amber-500">${t('feishu_scan_waiting')}</p>
+            <p class="text-xs text-slate-400 dark:text-slate-500">${t('feishu_scan_tip')}</p>
+            ${qrUrl ? `<a href="${qrUrl}" target="_blank" rel="noopener"
+                class="text-xs text-blue-500 hover:text-blue-600 underline">${t('feishu_scan_open_link')}</a>` : ''}
+        </div>`;
+}
+
+function renderFeishuRegisterError(statusId, message) {
+    const statusEl = document.getElementById(statusId);
+    if (!statusEl) return;
+    statusEl.innerHTML = `
+        <div class="flex flex-col items-center gap-2 py-2">
+            <p class="text-sm text-red-500 text-center">${message}</p>
+            <button onclick="startFeishuRegister('${statusId}')"
+                class="mt-1 px-4 py-1.5 rounded-md text-xs font-medium
+                       bg-slate-100 dark:bg-white/10 text-slate-700 dark:text-slate-200
+                       hover:bg-slate-200 dark:hover:bg-white/20 cursor-pointer">
+                <i class="fas fa-rotate-right mr-1"></i>${t('feishu_scan_retry')}
+            </button>
+        </div>`;
+}
+
+function pollFeishuRegisterStatus(statusId) {
+    stopFeishuRegisterPoll();
+    _feishuRegisterPollTimer = setTimeout(() => {
+        fetch('/api/feishu/register', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ action: 'poll' })
+        })
+        .then(r => r.json())
+        .then(data => {
+            if (data.status !== 'success') {
+                renderFeishuRegisterError(statusId, data.message || t('feishu_scan_fail'));
+                return;
+            }
+            const rs = data.register_status;
+            if (rs === 'done') {
+                const statusEl = document.getElementById(statusId);
+                if (statusEl) {
+                    statusEl.innerHTML = `
+                        <div class="flex flex-col items-center py-2">
+                            <div class="w-10 h-10 rounded-full bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center mb-2">
+                                <i class="fas fa-check text-emerald-500 text-lg"></i>
+                            </div>
+                            <p class="text-sm font-medium text-emerald-600 dark:text-emerald-400">${t('feishu_scan_success')}</p>
+                        </div>`;
+                }
+                connectFeishuAfterRegister(data.app_id, data.app_secret);
+            } else if (rs === 'expired') {
+                renderFeishuRegisterError(statusId, t('feishu_scan_expired'));
+            } else if (rs === 'denied') {
+                renderFeishuRegisterError(statusId, t('feishu_scan_denied'));
+            } else if (rs === 'error') {
+                renderFeishuRegisterError(statusId, data.message || t('feishu_scan_fail'));
+            } else {
+                pollFeishuRegisterStatus(statusId);
+            }
+        })
+        .catch(() => {
+            pollFeishuRegisterStatus(statusId);
+        });
+    }, 2000);
+}
+
+function connectFeishuAfterRegister(appId, appSecret) {
+    fetch('/api/channels', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({
+            action: 'connect',
+            channel: 'feishu',
+            config: { feishu_app_id: appId, feishu_app_secret: appSecret }
+        })
+    })
+    .then(r => r.json())
+    .then(data => {
+        if (data.status === 'success') {
+            const ch = channelsData.find(c => c.name === 'feishu');
+            if (ch) {
+                ch.active = true;
+                (ch.fields || []).forEach(f => {
+                    if (f.key === 'feishu_app_id') f.value = appId;
+                    if (f.key === 'feishu_app_secret') f.value = ChannelsHandler_maskSecret(appSecret);
+                });
+            }
+            setTimeout(() => renderActiveChannels(), 1500);
+        }
+    })
+    .catch(() => {});
+}
+
+// =====================================================================
+// Scheduler View
+// =====================================================================
+let tasksLoaded = false;
+function refreshTasksView() {
+    const btn = document.getElementById('task-refresh-btn');
+    const icon = btn.querySelector('i');
+    
+    // Add spin animation
+    icon.classList.add('fa-spin');
+    btn.disabled = true;
+    
+    tasksLoaded = false;
+    const listEl = document.getElementById('tasks-list');
+    listEl.innerHTML = '';
+    
+    loadTasksView();
+    
+    // Restore button after animation ends
+    setTimeout(() => {
+        icon.classList.remove('fa-spin');
+        btn.disabled = false;
+    }, 500);
+}
+function loadTasksView() {
+    if (tasksLoaded) return;
+    fetch('/api/scheduler').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const emptyEl = document.getElementById('tasks-empty');
+        const listEl = document.getElementById('tasks-list');
+        const allTasks = data.tasks || [];
+        // Backend already sorted by enabled and next_run_at, no need to re-sort on frontend
+        if (allTasks.length === 0) {
+            emptyEl.querySelector('p').textContent = currentLang === 'zh' ? '暂无定时任务' : 'No scheduled tasks';
+            emptyEl.classList.remove('hidden');
+            listEl.classList.add('hidden');
+            tasksLoaded = true;
+            return;
+        }
+        emptyEl.classList.add('hidden');
+        listEl.classList.remove('hidden');
+        listEl.innerHTML = '';
+
+        allTasks.forEach(task => {
+            const isEnabled = task.enabled !== false;
+            const card = document.createElement('div');
+            card.className = 'bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-4';
+            card.dataset.taskId = task.id;
+            if (!isEnabled) card.classList.add('opacity-50');
+            const schedule = task.schedule || {};
+            let typeLabel = '';
+            if (schedule.type === 'cron') {
+                typeLabel = `<span class="text-xs font-mono text-slate-400">${escapeHtml(schedule.expression || '')}</span>`;
+            } else if (schedule.type === 'interval') {
+                const seconds = schedule.seconds || 0;
+                const hours = Math.floor(seconds / 3600);
+                const mins = Math.floor((seconds % 3600) / 60);
+                const secs = seconds % 60;
+                let intervalText = [];
+                if (hours > 0) intervalText.push(`${hours}h`);
+                if (mins > 0) intervalText.push(`${mins}m`);
+                if (secs > 0 || intervalText.length === 0) intervalText.push(`${secs}s`);
+                typeLabel = `<span class="text-xs text-slate-400">${intervalText.join(' ')}</span>`;
+            } else {
+                typeLabel = `<span class="text-xs text-slate-400">${escapeHtml(schedule.type || 'once')}</span>`;
+            }
+            let nextRun = '--';
+            if (task.next_run_at) {
+                const d = new Date(task.next_run_at);
+                if (!isNaN(d.getTime())) nextRun = d.toLocaleString();
+            }
+            const action = task.action || {};
+            const taskContent = action.content || action.task_description || '';
+            const toggleId = 'toggle-' + task.id;
+            card.innerHTML = `
+                <div class="flex items-center gap-2 mb-2">
+                    <span class="w-2 h-2 rounded-full ${isEnabled ? 'bg-primary-400' : 'bg-slate-300 dark:bg-slate-600'}"></span>
+                    <span class="font-medium text-sm text-slate-700 dark:text-slate-200">${escapeHtml(task.name || task.id || '--')}</span>
+                    <div class="flex-1"></div>
+                    ${typeLabel}
+                </div>
+                <p class="text-xs text-slate-500 dark:text-slate-400 mb-2 line-clamp-2">${escapeHtml(taskContent)}</p>
+                <div class="flex items-center gap-4 text-xs text-slate-400 dark:text-slate-500">
+                    <span><i class="fas fa-clock mr-1"></i>${currentLang === 'zh' ? '下次执行' : 'Next run'}: ${nextRun}</span>
+                    <div class="flex-1"></div>
+                    <label class="relative inline-flex items-center cursor-pointer" for="${toggleId}">
+                        <input type="checkbox" id="${toggleId}" class="sr-only peer" ${isEnabled ? 'checked' : ''}>
+                        <div class="w-9 h-5 bg-slate-200 peer-focus:outline-none rounded-full peer peer-checked:after:translate-x-full peer-checked:after:border-white after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white after:rounded-full after:h-4 after:w-4 after:transition-all peer-checked:bg-primary-500 dark:bg-slate-600 dark:peer-checked:bg-primary-500"></div>
+                    </label>
+                </div>`;
+            const checkbox = card.querySelector('#' + toggleId);
+            checkbox.addEventListener('change', function() {
+                const newEnabled = this.checked;
+                fetch('/api/scheduler/toggle', {
+                    method: 'POST',
+                    headers: {'Content-Type': 'application/json'},
+                    body: JSON.stringify({task_id: task.id, enabled: newEnabled})
+                }).then(r => r.json()).then(res => {
+                    if (res.status === 'success') {
+                        const dot = card.querySelector('.rounded-full.w-2');
+                        if (newEnabled) {
+                            card.classList.remove('opacity-50');
+                            if (dot) { dot.classList.remove('bg-slate-300','dark:bg-slate-600'); dot.classList.add('bg-primary-400'); }
+                        } else {
+                            card.classList.add('opacity-50');
+                            if (dot) { dot.classList.remove('bg-primary-400'); dot.classList.add('bg-slate-300','dark:bg-slate-600'); }
+                        }
+                    } else {
+                        this.checked = !newEnabled;
+                    }
+                }).catch(() => { this.checked = !newEnabled; });
+            });
+            // Card click event (excluding toggle switch clicks)
+            card.addEventListener('click', function(e) {
+                if (!e.target.closest('label') && !e.target.closest('input[type="checkbox"]')) {
+                    openTaskEditModal(task);
+                }
+            });
+            card.style.cursor = 'pointer';
+            listEl.appendChild(card);
+        });
+        tasksLoaded = true;
+    }).catch(() => {});
+}
+
+// =====================================================================
+// Logs View
+// =====================================================================
+let logEventSource = null;
+
+function logLevelClass(line) {
+    if (/\[CRITICAL\]/.test(line)) return 'log-line-critical';
+    if (/\[ERROR\]/.test(line))    return 'log-line-error';
+    if (/\[WARNING\]/.test(line))  return 'log-line-warning';
+    if (/\[INFO\]/.test(line))     return 'log-line-info';
+    if (/\[DEBUG\]/.test(line))    return 'log-line-debug';
+    return '';
+}
+
+function getHiddenLevels() {
+    const hidden = new Set();
+    document.querySelectorAll('.log-filter-cb').forEach(function(cb) {
+        if (!cb.checked) hidden.add('log-line-' + cb.dataset.level);
+    });
+    return hidden;
+}
+
+function applyLogFilter() {
+    const hidden = getHiddenLevels();
+    document.querySelectorAll('#log-output .log-line').forEach(function(span) {
+        const level = span.classList[1] || '';
+        span.style.display = hidden.has(level) ? 'none' : '';
+    });
+}
+
+function appendLogLines(output, text) {
+    const hidden = getHiddenLevels();
+    let lastLevelClass = '';
+    const lines = text.split('\n');
+    lines.forEach(function(line, i) {
+        if (i === lines.length - 1 && line === '') return;
+        const span = document.createElement('span');
+        const levelClass = logLevelClass(line) || lastLevelClass;
+        if (logLevelClass(line)) lastLevelClass = levelClass;
+        span.className = 'log-line ' + levelClass;
+        span.textContent = line + '\n';
+        if (hidden.has(levelClass)) span.style.display = 'none';
+        output.appendChild(span);
+    });
+}
+
+document.addEventListener('change', function(e) {
+    if (e.target.classList.contains('log-filter-cb')) applyLogFilter();
+});
+
+function startLogStream() {
+    if (logEventSource) return;
+    const output = document.getElementById('log-output');
+    output.innerHTML = '';
+
+    logEventSource = new EventSource('/api/logs');
+    logEventSource.onmessage = function(e) {
+        let item;
+        try { item = JSON.parse(e.data); } catch (_) { return; }
+
+        if (item.type === 'init') {
+            output.innerHTML = '';
+            appendLogLines(output, item.content || '');
+            output.scrollTop = output.scrollHeight;
+        } else if (item.type === 'line') {
+            appendLogLines(output, item.content);
+            output.scrollTop = output.scrollHeight;
+        } else if (item.type === 'error') {
+            output.textContent = item.message || 'Error loading logs';
+        }
+    };
+    logEventSource.onerror = function() {
+        logEventSource.close();
+        logEventSource = null;
+    };
+}
+
+function stopLogStream() {
+    if (logEventSource) {
+        logEventSource.close();
+        logEventSource = null;
+    }
+}
+
+// =====================================================================
+// View Navigation Hook
+// =====================================================================
+const _origNavigateTo = navigateTo;
+navigateTo = function(viewId) {
+    // Stop log stream when leaving logs view
+    if (currentView === 'logs' && viewId !== 'logs') stopLogStream();
+
+    _origNavigateTo(viewId);
+
+    // Lazy-load view data
+    if (viewId === 'config') loadConfigView();
+    else if (viewId === 'models') loadModelsView();
+    else if (viewId === 'skills') loadSkillsView();
+    else if (viewId === 'memory') {
+        document.getElementById('memory-panel-viewer').classList.add('hidden');
+        document.getElementById('memory-panel-list').classList.remove('hidden');
+        switchMemoryTab('files');
+    }
+    else if (viewId === 'knowledge') loadKnowledgeView();
+    else if (viewId === 'channels') loadChannelsView();
+    else if (viewId === 'tasks') loadTasksView();
+    else if (viewId === 'logs') startLogStream();
+};
+
+// =====================================================================
+// Knowledge View
+// =====================================================================
+let _knowledgeTreeData = [];
+let _knowledgeRootFiles = [];
+let _knowledgeCurrentFile = null;
+let _knowledgeGraphLoaded = false;
+const KNOWLEDGE_IMPORT_MAX_FILES = 100;
+const KNOWLEDGE_IMPORT_MAX_FILE_SIZE = 10 * 1024 * 1024;
+const KNOWLEDGE_IMPORT_MAX_TOTAL_SIZE = 200 * 1024 * 1024;
+
+function loadKnowledgeView(targetPath) {
+    // Reset to docs tab
+    switchKnowledgeTab('docs');
+    _knowledgeGraphLoaded = false;
+    _knowledgeCurrentFile = null;
+
+    fetch('/api/knowledge/list').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        initKnowledgeImportDropZone();
+
+        const emptyEl = document.getElementById('knowledge-empty');
+        const docsPanel = document.getElementById('knowledge-panel-docs');
+        const statsEl = document.getElementById('knowledge-stats');
+
+        const tree = data.tree || [];
+        const rootFiles = data.root_files || [];
+        _knowledgeTreeData = tree;
+        _knowledgeRootFiles = rootFiles;
+        const stats = data.stats || {};
+        const totalPages = stats.pages || 0;
+        const sizeStr = stats.size < 1024 ? stats.size + ' B' : (stats.size / 1024).toFixed(1) + ' KB';
+
+        statsEl.textContent = totalPages + ' pages · ' + sizeStr;
+
+        if (totalPages === 0 && tree.length === 0 && rootFiles.length === 0) {
+            emptyEl.querySelector('p').textContent = t('knowledge_empty_hint');
+            const guideEl = document.getElementById('knowledge-empty-guide');
+            if (guideEl) guideEl.classList.remove('hidden');
+            emptyEl.classList.remove('hidden');
+            docsPanel.classList.add('hidden');
+            return;
+        }
+        emptyEl.classList.add('hidden');
+        docsPanel.classList.remove('hidden');
+
+        renderKnowledgeTree(tree, rootFiles);
+
+        // Prefer opening the just created/imported file; ensure its group is
+        // expanded so the active item is visible in the tree.
+        const targetTitle = targetPath ? _findKnowledgeFileTitle(targetPath) : null;
+        if (targetTitle !== null) {
+            _expandKnowledgeGroupFor(targetPath);
+            openKnowledgeFile(targetPath, targetTitle);
+            return;
+        }
+
+        // Auto-select the first file (desktop only)
+        if (window.innerWidth >= 768) {
+            const firstFile = rootFiles.length > 0 ? rootFiles[0] : null;
+            const firstGroup = !firstFile ? tree.find(g => g.files && g.files.length > 0) : null;
+            if (firstFile) {
+                openKnowledgeFile(firstFile.name, firstFile.title);
+            } else if (firstGroup) {
+                const gf = firstGroup.files[0];
+                openKnowledgeFile(firstGroup.dir + '/' + gf.name, gf.title);
+            }
+        } else {
+            document.getElementById('knowledge-content-placeholder').classList.add('hidden');
+            document.getElementById('knowledge-content-viewer').classList.add('hidden');
+        }
+    }).catch(() => {});
+}
+
+// Find a file's display title by its relative path within the knowledge tree.
+// Returns the title, or null when the path is not present.
+function _findKnowledgeFileTitle(path) {
+    if (!path) return null;
+    const rootHit = (_knowledgeRootFiles || []).find(f => f.name === path);
+    if (rootHit) return rootHit.title || rootHit.name;
+    const walk = (groups, parentPath) => {
+        for (const group of groups || []) {
+            const groupPath = parentPath ? `${parentPath}/${group.dir}` : group.dir;
+            const hit = (group.files || []).find(f => `${groupPath}/${f.name}` === path);
+            if (hit) return hit.title || hit.name;
+            const childHit = walk(group.children, groupPath);
+            if (childHit !== null) return childHit;
+        }
+        return null;
+    };
+    return walk(_knowledgeTreeData, '');
+}
+
+// Open every ancestor group of the given file path so it is visible.
+function _expandKnowledgeGroupFor(path) {
+    if (!path || !path.includes('/')) return;
+    const target = document.querySelector(`.knowledge-tree-file[data-path="${CSS.escape(path)}"]`);
+    let node = target ? target.closest('.knowledge-tree-group') : null;
+    while (node) {
+        node.classList.add('open');
+        node = node.parentElement ? node.parentElement.closest('.knowledge-tree-group') : null;
+    }
+}
+
+function renderKnowledgeTree(tree, rootFilesOrFilter, filter) {
+    const container = document.getElementById('knowledge-tree');
+    container.innerHTML = '';
+    let rootFiles, lowerFilter;
+    if (typeof rootFilesOrFilter === 'string') {
+        rootFiles = _knowledgeRootFiles;
+        lowerFilter = (rootFilesOrFilter || '').toLowerCase();
+    } else {
+        rootFiles = rootFilesOrFilter || _knowledgeRootFiles;
+        lowerFilter = (filter || '').toLowerCase();
+    }
+    (rootFiles || []).forEach(f => {
+        if (lowerFilter && !f.title.toLowerCase().includes(lowerFilter) && !f.name.toLowerCase().includes(lowerFilter)) return;
+        const fbtn = document.createElement('button');
+        fbtn.className = 'knowledge-tree-file' + (_knowledgeCurrentFile === f.name ? ' active' : '');
+        fbtn.dataset.path = f.name;
+        fbtn.innerHTML = `<i class="fas fa-file-lines text-[10px] text-slate-400"></i><span class="truncate">${escapeHtml(f.title)}</span>${_knowledgeFileActions(f.name)}`;
+        fbtn.onclick = () => openKnowledgeFile(f.name, f.title);
+        container.appendChild(fbtn);
+    });
+    _renderKnowledgeGroups(container, tree, '', lowerFilter, 0);
+}
+
+function _renderKnowledgeGroups(container, groups, parentPath, lowerFilter, depth) {
+    const indent = depth * 12;
+    groups.forEach(group => {
+        const groupPath = parentPath ? parentPath + '/' + group.dir : group.dir;
+        const files = (group.files || []).filter(f =>
+            !lowerFilter || f.title.toLowerCase().includes(lowerFilter) || f.name.toLowerCase().includes(lowerFilter)
+        );
+        const children = group.children || [];
+        const hasMatchingChildren = lowerFilter ? _hasFilterMatch(children, lowerFilter) : children.length > 0;
+        if (files.length === 0 && !hasMatchingChildren && lowerFilter) return;
+
+        const div = document.createElement('div');
+        div.className = 'knowledge-tree-group open';
+
+        const fileCount = _countFiles(group);
+        const btn = document.createElement('button');
+        btn.className = 'knowledge-tree-group-btn';
+        btn.style.paddingLeft = (8 + indent) + 'px';
+        btn.innerHTML = `<i class="fas fa-chevron-right chevron"></i><i class="fas fa-folder text-amber-400 text-[11px]"></i><span>${escapeHtml(group.dir)}</span><span class="ml-auto text-[10px] text-slate-400">${fileCount}</span>${_knowledgeCategoryActions(groupPath)}`;
+        btn.onclick = () => div.classList.toggle('open');
+        div.appendChild(btn);
+
+        const items = document.createElement('div');
+        items.className = 'knowledge-tree-group-items';
+        files.forEach(f => {
+            const fbtn = document.createElement('button');
+            const fpath = groupPath + '/' + f.name;
+            fbtn.className = 'knowledge-tree-file' + (_knowledgeCurrentFile === fpath ? ' active' : '');
+            fbtn.dataset.path = fpath;
+            fbtn.style.paddingLeft = (24 + indent) + 'px';
+            fbtn.innerHTML = `<i class="fas fa-file-lines text-[10px] text-slate-400"></i><span class="truncate">${escapeHtml(f.title)}</span>${_knowledgeFileActions(fpath)}`;
+            fbtn.onclick = () => openKnowledgeFile(fpath, f.title);
+            items.appendChild(fbtn);
+        });
+        if (children.length > 0) {
+            _renderKnowledgeGroups(items, children, groupPath, lowerFilter, depth + 1);
+        }
+        div.appendChild(items);
+        container.appendChild(div);
+    });
+}
+
+function _knowledgeActionButton(icon, title, handler) {
+    const danger = icon === 'fa-trash' ? ' danger' : '';
+    return `<span role="button" tabindex="0" title="${escapeHtml(title)}" onclick="event.stopPropagation();${handler}" class="knowledge-action${danger}"><i class="fas ${icon}"></i></span>`;
+}
+
+function _knowledgeFileActions(path) {
+    if (path === 'index.md' || path === 'log.md') return '';
+    const value = JSON.stringify(path).replace(/"/g, '&quot;');
+    return `<span class="knowledge-actions">${_knowledgeActionButton('fa-arrow-right-arrow-left', '移动', `moveKnowledgeDocument(${value})`)}${_knowledgeActionButton('fa-trash', '删除', `deleteKnowledgeDocument(${value})`)}</span>`;
+}
+
+function _knowledgeCategoryActions(path) {
+    const value = JSON.stringify(path).replace(/"/g, '&quot;');
+    return `<span class="knowledge-actions">${_knowledgeActionButton('fa-pen', '重命名', `renameKnowledgeCategory(${value})`)}${_knowledgeActionButton('fa-trash', '删除', `deleteKnowledgeCategory(${value})`)}</span>`;
+}
+
+async function dispatchKnowledgeAction(action, payload, openPathResolver) {
+    _setKnowledgeStatus(currentLang === 'zh' ? '处理中...' : 'Working...', false, true);
+    try {
+        const response = await fetch('/api/knowledge/action', {
+            method: 'POST',
+            headers: {'Content-Type': 'application/json'},
+            body: JSON.stringify({action, payload}),
+        });
+        const result = await response.json();
+        if (result.status !== 'success') {
+            _setKnowledgeStatus(result.message || (currentLang === 'zh' ? '操作失败' : 'Operation failed'), true);
+            loadKnowledgeView();
+            return null;
+        }
+        _setKnowledgeStatus(_knowledgeResultMessage(action, result.payload), false);
+        // Optionally auto-open the affected file after the tree refreshes.
+        const openPath = openPathResolver ? openPathResolver(result.payload) : null;
+        loadKnowledgeView(openPath || undefined);
+        return result.payload;
+    } catch (error) {
+        _setKnowledgeStatus(currentLang === 'zh' ? '请求失败，请稍后重试' : 'Request failed, please try again', true);
+        return null;
+    }
+}
+
+function _setKnowledgeStatus(message, isError, persistent) {
+    const el = document.getElementById('knowledge-action-status');
+    el.textContent = message;
+    el.className = `text-xs transition-opacity duration-200 ${isError ? 'text-red-500' : 'text-primary-500'}`;
+    el.classList.remove('opacity-0');
+    clearTimeout(el._hideTimer);
+    if (!persistent) el._hideTimer = setTimeout(() => el.classList.add('opacity-0'), 3500);
+}
+
+function _knowledgeResultMessage(action, payload) {
+    if (currentLang !== 'zh') {
+        return action === 'create_category' ? 'Category created' :
+            action === 'create_document' ? 'Document created' :
+            action === 'rename_category' ? 'Category renamed' :
+            action === 'delete_category' ? 'Category deleted' :
+            action === 'import_documents' ? `${payload?.imported || 0} imported · ${payload?.skipped || 0} skipped · ${payload?.failed || 0} failed` :
+            action === 'move_documents' ? `${payload?.moved || 0} document moved` :
+            `${payload?.deleted || 0} document deleted`;
+    }
+    return action === 'create_category' ? '分类已创建' :
+        action === 'create_document' ? '文档已创建' :
+        action === 'rename_category' ? '分类已重命名' :
+        action === 'delete_category' ? '分类已删除' :
+        action === 'import_documents' ? `导入 ${payload?.imported || 0} 个，跳过 ${payload?.skipped || 0} 个，失败 ${payload?.failed || 0} 个` :
+        action === 'move_documents' ? `已移动 ${payload?.moved || 0} 个文档` :
+        `已删除 ${payload?.deleted || 0} 个文档`;
+}
+
+function _knowledgeCategoryPaths(groups, parent = '') {
+    const paths = [];
+    for (const group of groups || []) {
+        const path = parent ? `${parent}/${group.dir}` : group.dir;
+        paths.push(path, ..._knowledgeCategoryPaths(group.children || [], path));
+    }
+    return paths;
+}
+
+function openKnowledgeDialog(options) {
+    const overlay = document.getElementById('knowledge-dialog-overlay');
+    const card = document.getElementById('knowledge-dialog-card');
+    const input = document.getElementById('knowledge-dialog-input');
+    const select = document.getElementById('knowledge-dialog-select');
+    const textarea = document.getElementById('knowledge-dialog-textarea');
+    const documentForm = document.getElementById('knowledge-document-form');
+    const documentFilename = document.getElementById('knowledge-document-filename');
+    const documentContent = document.getElementById('knowledge-document-content');
+    const templateBtn = document.getElementById('knowledge-document-template');
+    const documentPathPreview = document.getElementById('knowledge-document-path-preview');
+    const submit = document.getElementById('knowledge-dialog-submit');
+    const cancel = document.getElementById('knowledge-dialog-cancel');
+    document.getElementById('knowledge-dialog-title').textContent = options.title;
+    document.getElementById('knowledge-dialog-subtitle').textContent = options.subtitle || '';
+    document.getElementById('knowledge-dialog-label').textContent = options.label;
+    document.getElementById('knowledge-dialog-hint').textContent = options.hint || '';
+    document.getElementById('knowledge-dialog-error').classList.add('hidden');
+    document.getElementById('knowledge-dialog-icon').className = `fas ${options.icon || 'fa-folder'} text-emerald-500`;
+    card.classList.toggle('knowledge-document-dialog', options.type === 'document');
+    input.classList.toggle('hidden', options.type === 'select' || options.type === 'textarea' || options.type === 'document');
+    select.classList.toggle('hidden', options.type !== 'select');
+    textarea.classList.toggle('hidden', options.type !== 'textarea');
+    documentForm.classList.toggle('hidden', options.type !== 'document');
+    input.value = options.value || '';
+    textarea.value = options.value || '';
+    documentFilename.value = options.filename || '';
+    documentContent.value = options.content || '';
+    document.getElementById('knowledge-document-category-label').textContent = currentLang === 'zh' ? '目标分类' : 'Destination category';
+    documentPathPreview.textContent = options.category
+        ? `knowledge/${options.category}/`
+        : 'knowledge/';
+    documentFilename.oninput = null;
+    document.getElementById('knowledge-document-filename-label').textContent = currentLang === 'zh' ? '文件名' : 'Filename';
+    document.getElementById('knowledge-document-content-label').textContent = currentLang === 'zh' ? 'Markdown 内容' : 'Markdown content';
+    templateBtn.textContent = currentLang === 'zh' ? '插入模板' : 'Insert template';
+    templateBtn.onclick = () => {
+        if (documentContent.value.trim()) return;
+        const title = (documentFilename.value || 'untitled').replace(/\.md$/i, '');
+        documentContent.value = currentLang === 'zh'
+            ? `# ${title}\n\n## 摘要\n\n\n## 关键点\n\n- \n\n## 参考\n\n`
+            : `# ${title}\n\n## Summary\n\n\n## Key points\n\n- \n\n## References\n\n`;
+        documentContent.focus();
+    };
+    if (options.type === 'select') {
+        // Use the shared custom dropdown component instead of a native
+        // <select> so the arrow / menu match the rest of the console.
+        const ddOptions = (options.choices || []).map(value => ({ value, label: value }));
+        initDropdown(select, ddOptions, (options.choices || [])[0] || '', null);
+    }
+    submit.textContent = currentLang === 'zh' ? '确定' : 'Confirm';
+    cancel.textContent = currentLang === 'zh' ? '取消' : 'Cancel';
+    submit.disabled = options.type === 'select' && !(options.choices || []).length;
+
+    const close = () => overlay.classList.add('hidden');
+    const submitAction = async () => {
+        const rawValue = options.type === 'select' ? getDropdownValue(select) :
+            (options.type === 'textarea' ? textarea.value :
+            (options.type === 'document' ? {
+                filename: documentFilename.value.trim(),
+                content: documentContent.value,
+            } : input.value));
+        const value = options.type === 'textarea' || options.type === 'document' ? rawValue : rawValue.trim();
+        const error = options.validate ? options.validate(value) : (!value ? (currentLang === 'zh' ? '此项不能为空' : 'This field is required') : '');
+        if (error) {
+            const errorEl = document.getElementById('knowledge-dialog-error');
+            errorEl.textContent = error;
+            errorEl.classList.remove('hidden');
+            return;
+        }
+        submit.disabled = true;
+        const ok = await options.onSubmit(value);
+        submit.disabled = false;
+        if (ok !== null) close();
+    };
+    submit.onclick = submitAction;
+    cancel.onclick = close;
+    overlay.onclick = event => { if (event.target === overlay) close(); };
+    input.onkeydown = event => { if (event.key === 'Enter') submitAction(); };
+    overlay.classList.remove('hidden');
+    setTimeout(() => (options.type === 'select' ? select : (options.type === 'textarea' ? textarea : (options.type === 'document' ? documentFilename : input))).focus(), 0);
+}
+
+function closeKnowledgeNewMenu() {
+    const list = document.getElementById('knowledge-new-menu-list');
+    if (list) list.classList.add('hidden');
+    document.removeEventListener('click', _knowledgeNewMenuOutside, true);
+}
+
+function _knowledgeNewMenuOutside(event) {
+    const menu = document.getElementById('knowledge-new-menu');
+    if (menu && !menu.contains(event.target)) closeKnowledgeNewMenu();
+}
+
+function toggleKnowledgeNewMenu(event) {
+    if (event) event.stopPropagation();
+    const list = document.getElementById('knowledge-new-menu-list');
+    if (!list) return;
+    const willOpen = list.classList.contains('hidden');
+    list.classList.toggle('hidden');
+    if (willOpen) {
+        document.addEventListener('click', _knowledgeNewMenuOutside, true);
+    } else {
+        document.removeEventListener('click', _knowledgeNewMenuOutside, true);
+    }
+}
+
+function createKnowledgeCategory() {
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '新建分类' : 'New category',
+        subtitle: currentLang === 'zh' ? '分类会创建为 knowledge/ 下的目录' : 'Creates a directory under knowledge/',
+        label: currentLang === 'zh' ? '分类路径' : 'Category path',
+        hint: currentLang === 'zh' ? '支持嵌套路径，例如 research/ai' : 'Nested paths are supported, e.g. research/ai',
+        icon: 'fa-folder-plus',
+        onSubmit: path => dispatchKnowledgeAction('create_category', {path}),
+    });
+}
+
+function createKnowledgeDocument() {
+    const categories = _knowledgeCategoryPaths(_knowledgeTreeData);
+    if (!categories.length) {
+        _setKnowledgeStatus(currentLang === 'zh' ? '请先创建分类' : 'Create a category first', true);
+        return;
+    }
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '新建文档' : 'New document',
+        subtitle: currentLang === 'zh' ? '先选择分类，然后输入文件名' : 'Choose a category, then enter a filename',
+        label: currentLang === 'zh' ? '目标分类' : 'Destination category',
+        type: 'select',
+        choices: categories,
+        icon: 'fa-file-circle-plus',
+        onSubmit: category => {
+            openKnowledgeDocumentEditor(category);
+            return null;
+        },
+    });
+}
+
+function openKnowledgeDocumentEditor(category) {
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '新建文档' : 'New document',
+        subtitle: currentLang === 'zh' ? `保存到 ${category}` : `Save to ${category}`,
+        label: '',
+        hint: currentLang === 'zh' ? '文件名可省略 .md 后缀；保存后会自动同步索引。' : 'The .md suffix is optional. Index sync runs after saving.',
+        type: 'document',
+        category,
+        filename: '',
+        content: '',
+        icon: 'fa-file-circle-plus',
+        validate: value => {
+            if (!value.filename) return currentLang === 'zh' ? '文件名不能为空' : 'Filename is required';
+            if (/\.[^.]+$/i.test(value.filename) && !/\.md$/i.test(value.filename)) {
+                return currentLang === 'zh' ? '新建文档仅支持 .md 文件名' : 'New documents must be .md files';
+            }
+            if (!value.content.trim()) return currentLang === 'zh' ? '内容不能为空' : 'Content is required';
+            if (new Blob([value.content]).size > KNOWLEDGE_IMPORT_MAX_FILE_SIZE) {
+                return currentLang === 'zh' ? '内容不能超过 10MB' : 'Content cannot exceed 10MB';
+            }
+            return '';
+        },
+        onSubmit: value => {
+            const safeName = value.filename.endsWith('.md') ? value.filename : `${value.filename}.md`;
+            return dispatchKnowledgeAction('create_document', {
+                path: `${category}/${safeName}`,
+                content: value.content,
+                overwrite: false,
+            }, payload => payload?.path || `${category}/${safeName}`);
+        },
+    });
+}
+
+function selectKnowledgeImportFiles() {
+    const input = document.getElementById('knowledge-import-input');
+    input.value = '';
+    input.onchange = () => {
+        if (input.files && input.files.length) openKnowledgeImportDialog(Array.from(input.files));
+    };
+    input.click();
+}
+
+function openKnowledgeImportDialog(files) {
+    const validationError = validateKnowledgeImportFiles(files);
+    if (validationError) {
+        _setKnowledgeStatus(validationError, true);
+        return;
+    }
+    const choices = _knowledgeCategoryPaths(_knowledgeTreeData);
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '导入文档' : 'Import documents',
+        subtitle: currentLang === 'zh' ? `已选择 ${files.length} 个文件` : `${files.length} file(s) selected`,
+        label: currentLang === 'zh' ? '目标分类' : 'Destination category',
+        hint: choices.length ? (currentLang === 'zh' ? '支持 Markdown 和 TXT，TXT 会转成 Markdown 文档' : 'Markdown and TXT are supported. TXT is converted to Markdown.') :
+            (currentLang === 'zh' ? '请先创建一个分类' : 'Create a category first'),
+        type: 'select',
+        choices,
+        icon: 'fa-file-arrow-up',
+        onSubmit: target => importKnowledgeDocuments(files, target),
+    });
+}
+
+async function importKnowledgeDocuments(files, targetCategory) {
+    const validationError = validateKnowledgeImportFiles(files);
+    if (validationError) {
+        _setKnowledgeStatus(validationError, true);
+        return null;
+    }
+    const supported = files.filter(file => /\.(md|txt)$/i.test(file.name || ''));
+    if (!supported.length) {
+        _setKnowledgeStatus(currentLang === 'zh' ? '请选择 .md 或 .txt 文件' : 'Choose .md or .txt files', true);
+        return null;
+    }
+    const formData = new FormData();
+    formData.append('target_category', targetCategory);
+    formData.append('conflict_strategy', 'rename');
+    supported.forEach(file => formData.append('files', file, file.name));
+    _setKnowledgeStatus(currentLang === 'zh' ? '正在导入...' : 'Importing...', false, true);
+    try {
+        const response = await fetch('/api/knowledge/import', { method: 'POST', body: formData });
+        const result = await response.json();
+        if (result.status !== 'success') {
+            _setKnowledgeStatus(result.message || (currentLang === 'zh' ? '导入失败' : 'Import failed'), true);
+            loadKnowledgeView();
+            return null;
+        }
+        _setKnowledgeStatus(_knowledgeResultMessage('import_documents', result.payload), false);
+        // Auto-open the first successfully imported document.
+        const firstImported = (result.payload?.results || []).find(item => item.status === 'imported');
+        loadKnowledgeView(firstImported ? firstImported.path : undefined);
+        return result.payload;
+    } catch (error) {
+        _setKnowledgeStatus(currentLang === 'zh' ? '导入请求失败' : 'Import request failed', true);
+        return null;
+    }
+}
+
+function validateKnowledgeImportFiles(files) {
+    if (!files || !files.length) return currentLang === 'zh' ? '请选择文件' : 'Choose files';
+    if (files.length > KNOWLEDGE_IMPORT_MAX_FILES) {
+        return currentLang === 'zh' ? `一次最多导入 ${KNOWLEDGE_IMPORT_MAX_FILES} 个文件` : `Import at most ${KNOWLEDGE_IMPORT_MAX_FILES} files at a time`;
+    }
+    let total = 0;
+    for (const file of files) {
+        total += file.size || 0;
+        if ((file.size || 0) > KNOWLEDGE_IMPORT_MAX_FILE_SIZE) {
+            return currentLang === 'zh' ? `${file.name} 超过 10MB` : `${file.name} exceeds 10MB`;
+        }
+    }
+    if (total > KNOWLEDGE_IMPORT_MAX_TOTAL_SIZE) {
+        return currentLang === 'zh' ? '单次导入总大小不能超过 200MB' : 'Total import size cannot exceed 200MB';
+    }
+    return '';
+}
+
+let _knowledgeImportDropReady = false;
+function initKnowledgeImportDropZone() {
+    if (_knowledgeImportDropReady) return;
+    const panel = document.getElementById('knowledge-panel-docs');
+    if (!panel) return;
+    _knowledgeImportDropReady = true;
+    ['dragenter', 'dragover'].forEach(name => {
+        panel.addEventListener(name, event => {
+            if (!event.dataTransfer || !event.dataTransfer.types.includes('Files')) return;
+            event.preventDefault();
+            panel.classList.add('knowledge-import-drag-over');
+        });
+    });
+    ['dragleave', 'drop'].forEach(name => {
+        panel.addEventListener(name, event => {
+            if (event.type === 'drop') {
+                event.preventDefault();
+                const files = Array.from(event.dataTransfer?.files || []);
+                if (files.length) openKnowledgeImportDialog(files);
+            }
+            panel.classList.remove('knowledge-import-drag-over');
+        });
+    });
+}
+
+function renameKnowledgeCategory(path) {
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '重命名分类' : 'Rename category',
+        subtitle: path,
+        label: currentLang === 'zh' ? '新的分类路径' : 'New category path',
+        value: path,
+        icon: 'fa-pen',
+        validate: value => value === path ? (currentLang === 'zh' ? '请输入不同的分类路径' : 'Enter a different category path') : '',
+        onSubmit: newPath => dispatchKnowledgeAction('rename_category', {path, new_path: newPath}),
+    });
+}
+
+function deleteKnowledgeCategory(path) {
+    showConfirmDialog({
+        title: '删除分类',
+        message: `确认删除“${path}”及其中全部文档？`,
+        okText: t('confirm_yes'),
+        cancelText: t('confirm_cancel'),
+        onConfirm: () => dispatchKnowledgeAction('delete_category', {path, confirm: true}),
+    });
+}
+
+function deleteKnowledgeDocument(path) {
+    showConfirmDialog({
+        title: '删除文档',
+        message: `确认删除“${path}”？`,
+        okText: t('confirm_yes'),
+        cancelText: t('confirm_cancel'),
+        onConfirm: () => dispatchKnowledgeAction('delete_documents', {paths: [path]}),
+    });
+}
+
+function moveKnowledgeDocument(path) {
+    const currentCategory = path.includes('/') ? path.split('/').slice(0, -1).join('/') : '';
+    const choices = _knowledgeCategoryPaths(_knowledgeTreeData).filter(value => value !== currentCategory);
+    openKnowledgeDialog({
+        title: currentLang === 'zh' ? '移动文档' : 'Move document',
+        subtitle: path,
+        label: currentLang === 'zh' ? '目标分类' : 'Destination category',
+        hint: choices.length ? '' : (currentLang === 'zh' ? '请先创建其他分类' : 'Create another category first'),
+        type: 'select',
+        choices,
+        icon: 'fa-arrow-right-arrow-left',
+        onSubmit: target => dispatchKnowledgeAction('move_documents', {paths: [path], target_category: target}),
+    });
+}
+
+function _hasFilterMatch(groups, lowerFilter) {
+    for (const g of groups) {
+        for (const f of (g.files || [])) {
+            if (f.title.toLowerCase().includes(lowerFilter) || f.name.toLowerCase().includes(lowerFilter)) return true;
+        }
+        if (_hasFilterMatch(g.children || [], lowerFilter)) return true;
+    }
+    return false;
+}
+
+function _countFiles(group) {
+    let count = (group.files || []).length;
+    for (const child of (group.children || [])) {
+        count += _countFiles(child);
+    }
+    return count;
+}
+
+function filterKnowledgeTree(query) {
+    renderKnowledgeTree(_knowledgeTreeData, _knowledgeRootFiles, query);
+}
+
+function resolveKnowledgePath(currentFilePath, relativeHref) {
+    // currentFilePath: e.g. "concepts/mcp-protocol.md"
+    // relativeHref: e.g. "../entities/openai.md"
+    const parts = currentFilePath.split('/');
+    parts.pop(); // remove filename, keep directory
+    const segments = [...parts, ...relativeHref.split('/')];
+    const resolved = [];
+    for (const seg of segments) {
+        if (seg === '..') resolved.pop();
+        else if (seg !== '.' && seg !== '') resolved.push(seg);
+    }
+    return resolved.join('/');
+}
+
+function bindKnowledgeLinks(container, currentFilePath) {
+    container.querySelectorAll('a').forEach(a => {
+        const href = a.getAttribute('href');
+        if (!href || !href.endsWith('.md')) return;
+        // Skip absolute URLs
+        if (/^https?:\/\//.test(href)) return;
+
+        a.addEventListener('click', (e) => {
+            e.preventDefault();
+            const resolved = resolveKnowledgePath(currentFilePath, href);
+            const linkTitle = a.textContent.trim() || resolved.replace(/\.md$/, '').split('/').pop();
+            openKnowledgeFile(resolved, linkTitle);
+        });
+        a.style.cursor = 'pointer';
+        a.classList.add('text-primary-500', 'hover:underline');
+    });
+}
+
+function bindChatKnowledgeLinks(container) {
+    if (!container) return;
+    container.querySelectorAll('a').forEach(a => {
+        const href = a.getAttribute('href');
+        if (!href || !href.endsWith('.md')) return;
+        if (/^https?:\/\//.test(href)) return;
+
+        // Determine knowledge path
+        let knowledgePath = null;
+        if (href.startsWith('knowledge/')) {
+            // Full path from workspace root: knowledge/concepts/moe.md
+            knowledgePath = href.replace(/^knowledge\//, '');
+        } else if (/^[a-z0-9_-]+\/[a-z0-9_.-]+\.md$/i.test(href)) {
+            // Looks like category/file.md pattern without knowledge/ prefix
+            knowledgePath = href;
+        } else if (href.includes('/') && !href.startsWith('/')) {
+            // Relative path like ../entities/deepseek.md — extract filename and search
+            const filename = href.split('/').pop();
+            knowledgePath = '__search__:' + filename;
+        }
+        if (!knowledgePath) return;
+
+        a.addEventListener('click', (e) => {
+            e.preventDefault();
+            if (knowledgePath.startsWith('__search__:')) {
+                const filename = knowledgePath.replace('__search__:', '');
+                // Find the file in cached tree data
+                const found = _findKnowledgeFileByName(filename);
+                if (found) {
+                    navigateTo('knowledge');
+                    setTimeout(() => openKnowledgeFile(found.path, found.title), 100);
+                }
+            } else {
+                navigateTo('knowledge');
+                const linkTitle = a.textContent.trim() || knowledgePath.replace(/\.md$/, '').split('/').pop();
+                setTimeout(() => openKnowledgeFile(knowledgePath, linkTitle), 100);
+            }
+        });
+        a.style.cursor = 'pointer';
+        a.classList.add('text-primary-500', 'hover:underline');
+    });
+}
+
+function _findKnowledgeFileByName(filename) {
+    for (const f of _knowledgeRootFiles) {
+        if (f.name === filename) return { path: f.name, title: f.title };
+    }
+    return _searchFileInGroups(_knowledgeTreeData, '', filename);
+}
+
+function _searchFileInGroups(groups, parentPath, filename) {
+    for (const group of groups) {
+        const groupPath = parentPath ? parentPath + '/' + group.dir : group.dir;
+        for (const f of (group.files || [])) {
+            if (f.name === filename) {
+                return { path: groupPath + '/' + f.name, title: f.title };
+            }
+        }
+        const found = _searchFileInGroups(group.children || [], groupPath, filename);
+        if (found) return found;
+    }
+    return null;
+}
+
+function openKnowledgeFile(path, title) {
+    _knowledgeCurrentFile = path;
+    // Update active state in tree via data-path
+    document.querySelectorAll('.knowledge-tree-file').forEach(el => {
+        el.classList.toggle('active', el.dataset.path === path);
+    });
+
+    // Immediately hide placeholder
+    document.getElementById('knowledge-content-placeholder').classList.add('hidden');
+
+    fetch(`/api/knowledge/read?path=${encodeURIComponent(path)}`).then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const viewer = document.getElementById('knowledge-content-viewer');
+        document.getElementById('knowledge-viewer-title').textContent = title;
+        document.getElementById('knowledge-viewer-path').textContent = path;
+        const bodyEl = document.getElementById('knowledge-viewer-body');
+        bodyEl.innerHTML = renderMarkdown(data.content || '');
+        viewer.classList.remove('hidden');
+        applyHighlighting(viewer);
+        bindKnowledgeLinks(bodyEl, path);
+
+        // Mobile: hide sidebar, show content
+        if (window.innerWidth < 768) {
+            document.getElementById('knowledge-sidebar').classList.add('hidden');
+        }
+    }).catch(() => {});
+}
+
+function knowledgeMobileBack() {
+    document.getElementById('knowledge-sidebar').classList.remove('hidden');
+    document.getElementById('knowledge-content-viewer').classList.add('hidden');
+}
+
+function switchKnowledgeTab(tab) {
+    document.querySelectorAll('.knowledge-tab').forEach(el => el.classList.remove('active'));
+    document.getElementById('knowledge-tab-' + tab).classList.add('active');
+
+    const docsPanel = document.getElementById('knowledge-panel-docs');
+    const graphPanel = document.getElementById('knowledge-panel-graph');
+
+    if (tab === 'docs') {
+        docsPanel.classList.remove('hidden');
+        graphPanel.classList.add('hidden');
+    } else {
+        docsPanel.classList.add('hidden');
+        graphPanel.classList.remove('hidden');
+        if (!_knowledgeGraphLoaded) {
+            loadKnowledgeGraph();
+        }
+    }
+}
+
+let _d3LoadPromise = null;
+
+function ensureD3Loaded() {
+    if (window.d3) return Promise.resolve(window.d3);
+    if (_d3LoadPromise) return _d3LoadPromise;
+    _d3LoadPromise = new Promise((resolve, reject) => {
+        const script = document.createElement('script');
+        script.src = 'assets/vendor/d3/d3.min.js';
+        script.async = true;
+        script.onload = () => resolve(window.d3);
+        script.onerror = () => reject(new Error('Failed to load d3'));
+        document.head.appendChild(script);
+    });
+    return _d3LoadPromise;
+}
+
+function loadKnowledgeGraph() {
+    _knowledgeGraphLoaded = true;
+    const container = document.getElementById('knowledge-graph-container');
+    container.innerHTML = '<div class="flex items-center justify-center h-full text-slate-400 text-sm"><i class="fas fa-spinner fa-spin mr-2"></i>Loading graph...</div>';
+
+    Promise.all([
+        ensureD3Loaded(),
+        fetch('/api/knowledge/graph').then(r => r.json()),
+    ]).then(([, data]) => {
+        const nodes = data.nodes || [];
+        const links = data.links || [];
+        if (nodes.length === 0) {
+            container.innerHTML = `<div class="flex flex-col items-center justify-center h-full text-slate-400"><i class="fas fa-diagram-project text-3xl mb-3 opacity-40"></i><p class="text-sm">${t('knowledge_empty_hint')}</p></div>`;
+            return;
+        }
+        container.innerHTML = '';
+        renderKnowledgeGraph(container, nodes, links);
+    }).catch(() => {
+        container.innerHTML = '<div class="flex items-center justify-center h-full text-slate-400 text-sm">Failed to load graph</div>';
+    });
+}
+
+function renderKnowledgeGraph(container, nodes, links) {
+    const width = container.clientWidth;
+    const height = container.clientHeight || 600;
+
+    const categories = [...new Set(nodes.map(n => n.category))];
+    const colorScale = d3.scaleOrdinal(d3.schemeTableau10).domain(categories);
+
+    // Connection count for sizing
+    const connCount = {};
+    nodes.forEach(n => connCount[n.id] = 0);
+    links.forEach(l => {
+        connCount[l.source] = (connCount[l.source] || 0) + 1;
+        connCount[l.target] = (connCount[l.target] || 0) + 1;
+    });
+
+    const svg = d3.select(container)
+        .append('svg')
+        .attr('width', width)
+        .attr('height', height);
+
+    const g = svg.append('g');
+
+    // Zoom with adaptive label visibility
+    let currentZoomScale = 1;
+    const zoom = d3.zoom()
+        .scaleExtent([0.2, 5])
+        .on('zoom', (event) => {
+            g.attr('transform', event.transform);
+            currentZoomScale = event.transform.k;
+            updateLabelVisibility();
+        });
+    svg.call(zoom);
+
+    function updateLabelVisibility() {
+        if (!label) return;
+        if (currentZoomScale < 0.8) {
+            label.attr('opacity', 0);
+        } else {
+            const baseFontSize = Math.min(12, 10 / Math.max(currentZoomScale * 0.7, 0.5));
+            label.attr('opacity', 1).attr('font-size', baseFontSize);
+        }
+    }
+
+    const simulation = d3.forceSimulation(nodes)
+        .force('link', d3.forceLink(links).id(d => d.id).distance(90))
+        .force('charge', d3.forceManyBody().strength(-180))
+        .force('center', d3.forceCenter(width / 2, height / 2))
+        .force('x', d3.forceX(width / 2).strength(0.06))
+        .force('y', d3.forceY(height / 2).strength(0.06))
+        .force('collision', d3.forceCollide().radius(d => getNodeRadius(d) + 30));
+
+    function getNodeRadius(d) {
+        return Math.max(5, Math.min(16, 5 + (connCount[d.id] || 0) * 2));
+    }
+
+    const link = g.append('g')
+        .selectAll('line')
+        .data(links)
+        .join('line')
+        .attr('stroke', '#94a3b8')
+        .attr('stroke-opacity', 0.3)
+        .attr('stroke-width', 1);
+
+    const node = g.append('g')
+        .selectAll('circle')
+        .data(nodes)
+        .join('circle')
+        .attr('r', d => getNodeRadius(d))
+        .attr('fill', d => colorScale(d.category))
+        .attr('stroke', '#fff')
+        .attr('stroke-width', 1.5)
+        .style('cursor', 'pointer')
+        .call(d3.drag()
+            .on('start', (event, d) => { if (!event.active) simulation.alphaTarget(0.3).restart(); d.fx = d.x; d.fy = d.y; })
+            .on('drag', (event, d) => { d.fx = event.x; d.fy = event.y; })
+            .on('end', (event, d) => { if (!event.active) simulation.alphaTarget(0); d.fx = null; d.fy = null; })
+        );
+
+    const label = g.append('g')
+        .selectAll('text')
+        .data(nodes)
+        .join('text')
+        .text(d => d.label.length > 15 ? d.label.slice(0, 14) + '…' : d.label)
+        .attr('font-size', 9)
+        .attr('dx', d => getNodeRadius(d) + 4)
+        .attr('dy', 3)
+        .attr('fill', '#64748b')
+        .style('pointer-events', 'none');
+
+    // Tooltip
+    const tooltip = document.createElement('div');
+    tooltip.className = 'knowledge-graph-tooltip';
+    container.style.position = 'relative';
+    container.appendChild(tooltip);
+
+    node.on('mouseover', (event, d) => {
+        tooltip.textContent = d.label + ' (' + d.category + ')';
+        tooltip.style.opacity = '1';
+        tooltip.style.left = (event.offsetX + 12) + 'px';
+        tooltip.style.top = (event.offsetY - 8) + 'px';
+        // Highlight connections
+        link.attr('stroke-opacity', l => (l.source.id === d.id || l.target.id === d.id) ? 0.8 : 0.1);
+        node.attr('opacity', n => n.id === d.id || links.some(l => (l.source.id === d.id && l.target.id === n.id) || (l.target.id === d.id && l.source.id === n.id)) ? 1 : 0.2);
+        label.attr('opacity', n => n.id === d.id || links.some(l => (l.source.id === d.id && l.target.id === n.id) || (l.target.id === d.id && l.source.id === n.id)) ? 1 : 0.1);
+    }).on('mousemove', (event) => {
+        tooltip.style.left = (event.offsetX + 12) + 'px';
+        tooltip.style.top = (event.offsetY - 8) + 'px';
+    }).on('mouseout', () => {
+        tooltip.style.opacity = '0';
+        link.attr('stroke-opacity', 0.3);
+        node.attr('opacity', 1);
+        label.attr('opacity', 1);
+    }).on('click', (event, d) => {
+        // Switch to docs tab and open the file
+        switchKnowledgeTab('docs');
+        openKnowledgeFile(d.id, d.label);
+    });
+
+    simulation.on('tick', () => {
+        link.attr('x1', d => d.source.x).attr('y1', d => d.source.y)
+            .attr('x2', d => d.target.x).attr('y2', d => d.target.y);
+        node.attr('cx', d => d.x).attr('cy', d => d.y);
+        label.attr('x', d => d.x).attr('y', d => d.y);
+    });
+
+    // Auto fit-to-view when simulation settles
+    simulation.on('end', () => {
+        const pad = 16;
+        let x0 = Infinity, y0 = Infinity, x1 = -Infinity, y1 = -Infinity;
+        nodes.forEach(n => {
+            if (n.x < x0) x0 = n.x;
+            if (n.y < y0) y0 = n.y;
+            if (n.x > x1) x1 = n.x;
+            if (n.y > y1) y1 = n.y;
+        });
+        const bw = x1 - x0 + pad * 2;
+        const bh = y1 - y0 + pad * 2;
+        if (bw > 0 && bh > 0) {
+            const scale = Math.min(width / bw, height / bh, 4);
+            const tx = width / 2 - (x0 + x1) / 2 * scale;
+            const ty = height / 2 - (y0 + y1) / 2 * scale;
+            svg.transition().duration(500).call(
+                zoom.transform, d3.zoomIdentity.translate(tx, ty).scale(scale)
+            );
+        }
+    });
+
+    // Legend
+    const legendDiv = document.createElement('div');
+    legendDiv.className = 'knowledge-graph-legend';
+    categories.forEach(cat => {
+        const item = document.createElement('span');
+        item.className = 'knowledge-graph-legend-item';
+        item.innerHTML = `<span class="knowledge-graph-legend-dot" style="background:${colorScale(cat)}"></span>${escapeHtml(cat)}`;
+        legendDiv.appendChild(item);
+    });
+    container.appendChild(legendDiv);
+}
+
+// =====================================================================
+// Authentication
+// =====================================================================
+function toggleLoginPassword() {
+    const input = document.getElementById('login-password');
+    const icon = document.querySelector('#login-toggle-pwd i');
+    if (input.type === 'password') {
+        input.type = 'text';
+        icon.classList.replace('fa-eye', 'fa-eye-slash');
+    } else {
+        input.type = 'password';
+        icon.classList.replace('fa-eye-slash', 'fa-eye');
+    }
+}
+window.toggleLoginPassword = toggleLoginPassword;
+
+function showLoginScreen() {
+    const overlay = document.getElementById('login-overlay');
+    if (!overlay) return;
+    overlay.classList.remove('hidden');
+    document.getElementById('app').classList.add('hidden');
+
+    const subtitle = document.getElementById('login-subtitle');
+    const loginBtn = document.getElementById('login-btn');
+    if (currentLang === 'en') {
+        subtitle.textContent = 'Enter password to access the console';
+        loginBtn.textContent = 'Login';
+    } else if (currentLang === 'zh-Hant') {
+        subtitle.textContent = '請輸入密碼以存取控制台';
+        loginBtn.textContent = '登入';
+    } else {
+        subtitle.textContent = '请输入密码以访问控制台';
+        loginBtn.textContent = '登录';
+    }
+
+    const form = document.getElementById('login-form');
+    const pwdInput = document.getElementById('login-password');
+    pwdInput.focus();
+
+    form.onsubmit = function(e) {
+        e.preventDefault();
+        const pwd = pwdInput.value;
+        if (!pwd) return;
+        const btn = document.getElementById('login-btn');
+        const errEl = document.getElementById('login-error');
+        btn.disabled = true;
+        errEl.classList.add('hidden');
+
+        fetch('/auth/login', {
+            method: 'POST',
+            headers: {'Content-Type': 'application/json'},
+            body: JSON.stringify({password: pwd})
+        }).then(r => r.json()).then(data => {
+            if (data.status === 'success') {
+                overlay.classList.add('hidden');
+                document.getElementById('app').classList.remove('hidden');
+                const logoutBtn = document.getElementById('logout-btn-header');
+                if (logoutBtn) logoutBtn.classList.remove('hidden');
+                initApp();
+            } else {
+                if (currentLang === 'zh-Hant') {
+                    errEl.textContent = '密碼錯誤';
+                } else if (currentLang === 'zh') {
+                    errEl.textContent = '密码错误';
+                } else {
+                    errEl.textContent = 'Wrong password';
+                }
+                errEl.classList.remove('hidden');
+                pwdInput.value = '';
+                pwdInput.focus();
+            }
+            btn.disabled = false;
+        }).catch(() => {
+            if (currentLang === 'zh-Hant') {
+                errEl.textContent = '網路錯誤，請重試';
+            } else if (currentLang === 'zh') {
+                errEl.textContent = '网络错误，请重试';
+            } else {
+                errEl.textContent = 'Network error, please retry';
+            }
+            errEl.classList.remove('hidden');
+            btn.disabled = false;
+        });
+        return false;
+    };
+}
+
+function handleLogout() {
+    fetch('/auth/logout', {
+        method: 'POST'
+    }).then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            window.location.reload();
+        }
+    }).catch(() => {
+        window.location.reload();
+    });
+}
+window.handleLogout = handleLogout;
+
+// Intercept 401 responses globally to show login screen on session expiry
+const _originalFetch = window.fetch;
+window.fetch = function(...args) {
+    return _originalFetch.apply(this, args).then(response => {
+        if (response.status === 401) {
+            const url = typeof args[0] === 'string' ? args[0] : (args[0]?.url || '');
+            if (!url.startsWith('/auth/')) {
+                showLoginScreen();
+            }
+        }
+        return response;
+    });
+};
+
+function initApp() {
+    applyI18n();
+    _applyInputTooltips();
+    _restoreSessionPanel();
+
+    fetch('/api/knowledge/list').then(r => r.json()).then(data => {
+        if (data.status === 'success') {
+            _knowledgeTreeData = data.tree || [];
+            _knowledgeRootFiles = data.root_files || [];
+        }
+    }).catch(() => {});
+
+    fetch('/api/version').then(r => r.json()).then(data => {
+        APP_VERSION = `v${data.version}`;
+        document.getElementById('sidebar-version').textContent = `CowAgent ${APP_VERSION}`;
+    }).catch(() => {
+        document.getElementById('sidebar-version').textContent = 'CowAgent';
+    });
+    chatInput.focus();
+}
+
+// =====================================================================
+// Initialization
+// =====================================================================
+applyTheme();
+applyI18n();
+
+fetch('/auth/check').then(r => r.json()).then(data => {
+    if (data.auth_required && !data.authenticated) {
+        showLoginScreen();
+    } else {
+        if (data.auth_required) {
+            const logoutBtn = document.getElementById('logout-btn-header');
+            if (logoutBtn) logoutBtn.classList.remove('hidden');
+        }
+        initApp();
+    }
+}).catch(() => {
+    initApp();
+});
+
+requestAnimationFrame(() => {
+    document.body.classList.add('transition-colors', 'duration-200');
+});
+
+// =====================================================================
+// Task Edit Modal
+// =====================================================================
+let currentEditingTask = null;
+
+function loadTaskChannelOptions(selectedChannelType) {
+    const select = document.getElementById('task-edit-channel-type');
+    select.innerHTML = '';
+    fetch('/api/channels').then(r => r.json()).then(data => {
+        if (data.status !== 'success') return;
+        const allChannels = data.channels || [];
+        // Only include currently active channels, strictly following the channel management page logic
+        let channels = allChannels.filter(c => c.active).map(c => {
+            const label = (typeof c.label === 'object') ? (c.label[currentLang] || c.label.en || c.name) : (c.label || c.name);
+            return { name: c.name, label: label };
+        });
+        const channelNames = channels.map(c => c.name);
+        // Always include the web console channel
+        if (!channelNames.includes('web')) {
+            channels.unshift({ name: 'web', label: currentLang === 'zh' ? 'Web' : 'Web' });
+        }
+        // If the currently selected channel is not in the active list (e.g. disabled), append it to preserve selection
+        if (selectedChannelType && !channelNames.includes(selectedChannelType) && selectedChannelType !== 'web') {
+            const ch = allChannels.find(c => c.name === selectedChannelType);
+            const label = ch
+                ? ((typeof ch.label === 'object') ? (ch.label[currentLang] || ch.label.en || ch.name) : (ch.label || ch.name))
+                : selectedChannelType;
+            channels.push({ name: selectedChannelType, label: label });
+        }
+        channels.forEach(c => {
+            const opt = document.createElement('option');
+            opt.value = c.name;
+            opt.textContent = c.label;
+            select.appendChild(opt);
+        });
+        // Set selected value
+        if (selectedChannelType) {
+            select.value = selectedChannelType;
+        }
+    }).catch(() => {
+        // fallback: at least keep the current selection and web
+        select.innerHTML = '';
+        const webOpt = document.createElement('option');
+        webOpt.value = 'web';
+        webOpt.textContent = 'Web';
+        select.appendChild(webOpt);
+        
+        if (selectedChannelType && selectedChannelType !== 'web') {
+            const opt = document.createElement('option');
+            opt.value = selectedChannelType;
+            opt.textContent = selectedChannelType;
+            select.appendChild(opt);
+        }
+        if (selectedChannelType) {
+            select.value = selectedChannelType;
+        }
+        
+        // Show error message
+        console.error('Failed to load channel options');
+    });
+}
+
+function openTaskEditModal(task) {
+    currentEditingTask = task;
+    const overlay = document.getElementById('task-edit-modal-overlay');
+    const titleEl = document.querySelector('#task-edit-modal-overlay h3');
+    const subtitle = document.getElementById('task-edit-modal-subtitle');
+    const deleteBtn = document.getElementById('task-edit-modal-delete');
+    const nameInput = document.getElementById('task-edit-name');
+    const enabledInput = document.getElementById('task-edit-enabled');
+    const scheduleTypeSelect = document.getElementById('task-edit-schedule-type');
+    const cronInput = document.getElementById('task-edit-cron-expression');
+    const intervalInput = document.getElementById('task-edit-interval-seconds');
+    const onceInput = document.getElementById('task-edit-once-time');
+    const actionTypeSelect = document.getElementById('task-edit-action-type');
+    const receiverInput = document.getElementById('task-edit-receiver');
+    const contentInput = document.getElementById('task-edit-content');
+
+    // Set title and subtitle
+    titleEl.textContent = t('task_edit_title');
+    subtitle.textContent = task.id;
+    deleteBtn.classList.remove('hidden');
+
+    // Populate data
+    nameInput.value = task.name || '';
+    enabledInput.checked = task.enabled !== false;
+
+    const schedule = task.schedule || {};
+    scheduleTypeSelect.value = schedule.type || 'cron';
+
+    // Clear all schedule type input values first to avoid stale data
+    cronInput.value = '';
+    intervalInput.value = '';
+    onceInput.value = '';
+
+    if (schedule.type === 'cron') {
+        cronInput.value = schedule.expression || '';
+    } else if (schedule.type === 'interval') {
+        intervalInput.value = schedule.seconds || '';
+    } else if (schedule.type === 'once') {
+        if (schedule.run_at) {
+            // Manually parse ISO time string to avoid cross-browser timezone issues with new Date()
+            // run_at format: "YYYY-MM-DDTHH:mm:ss" or "YYYY-MM-DDTHH:mm:ss.ffffff"
+            const parts = schedule.run_at.match(/^(\d{4})-(\d{2})-(\d{2})T(\d{2}):(\d{2}):(\d{2})/);
+            if (parts) {
+                const timeInput = document.getElementById('task-edit-once-time');
+                timeInput.value = `${parts[1]}-${parts[2]}-${parts[3]}T${parts[4]}:${parts[5]}:${parts[6]}`;
+            }
+        }
+    }
+
+    const action = task.action || {};
+    actionTypeSelect.value = action.type || 'send_message';
+    receiverInput.value = action.receiver || '';
+    contentInput.value = action.content || action.task_description || '';
+
+    // Load channel options and set selected value
+    loadTaskChannelOptions(action.channel_type || 'web');
+
+    // Disable channel type selector — channel is read-only when editing.
+    // Switching the channel after a task is created is problematic because:
+    //   1. The WeChat (weixin/ilink) bot requires a valid context_token that is tied
+    //      to a specific user-session on that channel. Changing the channel to weixin
+    //      would invalidate the existing token — the new receiver on weixin may not
+    //      have an active context_token, causing the scheduled push to silently fail.
+    //   2. Other channels (DingTalk, Feishu, etc.) also carry channel-specific fields
+    //      (e.g. dingtalk_sender_staff_id) that cannot be trivially re-populated for
+    //      a different channel type without user intervention.
+    //   3. The receiver identity itself is channel-bound — a weixin user-id means
+    //      nothing on a Feishu channel, so changing the channel would orphan the task.
+    // For these reasons, the channel type is intentionally frozen once a task exists.
+    // Users who need a task on a different channel should create a new task through
+    // the chat interface (by asking the bot) rather than editing an existing one.
+    document.getElementById('task-edit-channel-type').disabled = true;
+
+    // Update UI
+    updateTaskScheduleFields();
+    updateTaskActionLabel();
+
+    overlay.classList.remove('hidden');
+}
+
+function closeTaskEditModal() {
+    document.getElementById('task-edit-modal-overlay').classList.add('hidden');
+    currentEditingTask = null;
+}
+
+function updateTaskScheduleFields() {
+    const scheduleType = document.getElementById('task-edit-schedule-type').value;
+    const cronWrap = document.getElementById('task-edit-cron-wrap');
+    const intervalWrap = document.getElementById('task-edit-interval-wrap');
+    const onceWrap = document.getElementById('task-edit-once-wrap');
+    const cronHint = document.getElementById('task-edit-cron-hint');
+    const intervalHint = document.getElementById('task-edit-interval-hint');
+    
+    cronWrap.classList.toggle('hidden', scheduleType !== 'cron');
+    intervalWrap.classList.toggle('hidden', scheduleType !== 'interval');
+    onceWrap.classList.toggle('hidden', scheduleType !== 'once');
+    
+    if (cronHint) cronHint.classList.toggle('hidden', scheduleType !== 'cron');
+    if (intervalHint) intervalHint.classList.toggle('hidden', scheduleType !== 'interval');
+}
+
+function updateTaskActionLabel() {
+    const actionType = document.getElementById('task-edit-action-type').value;
+    const label = document.getElementById('task-edit-content-label');
+    const content = document.getElementById('task-edit-content');
+    
+    if (actionType === 'send_message') {
+        label.textContent = t('task_message_content');
+        content.placeholder = t('task_message_content');
+    } else {
+        label.textContent = t('task_task_description');
+        content.placeholder = t('task_task_description');
+    }
+}
+
+function saveTaskEdit() {
+    const nameInput = document.getElementById('task-edit-name');
+    const enabledInput = document.getElementById('task-edit-enabled');
+    const scheduleTypeSelect = document.getElementById('task-edit-schedule-type');
+    const cronInput = document.getElementById('task-edit-cron-expression');
+    const intervalInput = document.getElementById('task-edit-interval-seconds');
+    const onceInput = document.getElementById('task-edit-once-time');
+    const actionTypeSelect = document.getElementById('task-edit-action-type');
+    const channelTypeSelect = document.getElementById('task-edit-channel-type');
+    const receiverInput = document.getElementById('task-edit-receiver');
+    const contentInput = document.getElementById('task-edit-content');
+    const statusEl = document.getElementById('task-edit-modal-status');
+    const saveBtn = document.getElementById('task-edit-modal-save');
+    
+    const name = nameInput.value.trim();
+    if (!name) {
+        statusEl.textContent = currentLang === 'zh' ? '请输入任务名称' : 'Please enter task name';
+        statusEl.style.opacity = '1';
+        setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+        return;
+    }
+    
+    const scheduleType = scheduleTypeSelect.value;
+    const schedule = { type: scheduleType };
+    
+    if (scheduleType === 'cron') {
+        const expr = cronInput.value.trim();
+        if (!expr) {
+            statusEl.textContent = currentLang === 'zh' ? '请输入 Cron 表达式' : 'Please enter cron expression';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        // Basic cron expression format validation: 5 or 6 fields
+        const fields = expr.split(/\s+/);
+        if (fields.length < 5 || fields.length > 6) {
+            statusEl.textContent = currentLang === 'zh' ? 'Cron 表达式格式错误，应为 5 或 6 个字段（分 时 日 月 周）' : 'Invalid cron expression, expected 5 or 6 fields (min hour day month weekday)';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        schedule.expression = expr;
+        // Note: detailed cron expression validity is verified by the backend croniter library; frontend only does basic format validation
+    } else if (scheduleType === 'interval') {
+        const seconds = parseInt(intervalInput.value);
+        if (!seconds || seconds < 60) {
+            statusEl.textContent = currentLang === 'zh' ? '间隔秒数最小为 60 秒' : 'Interval must be at least 60 seconds';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        schedule.seconds = seconds;
+    } else if (scheduleType === 'once') {
+        const time = onceInput.value;
+        if (!time) {
+            statusEl.textContent = currentLang === 'zh' ? '请选择执行时间' : 'Please select execution time';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        // Validate execution time format
+        const selectedTime = new Date(time);
+        if (isNaN(selectedTime.getTime())) {
+            statusEl.textContent = currentLang === 'zh' ? '执行时间格式错误' : 'Invalid execution time format';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        // Validate that time is in the future for one-time tasks
+        if (selectedTime <= new Date()) {
+            statusEl.textContent = currentLang === 'zh' ? '执行时间必须在当前时间之后' : 'Execution time must be in the future';
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+            return;
+        }
+        // datetime-local value with step="1" is already in YYYY-MM-DDTHH:mm:ss format
+        // Backend _parse_naive_local treats strings without timezone suffix as local time
+        schedule.run_at = time;
+    }
+    
+    const actionType = actionTypeSelect.value;
+    const channelType = channelTypeSelect.value;
+    const content = contentInput.value.trim();
+
+    if (!content) {
+        statusEl.textContent = currentLang === 'zh' ? '请输入内容' : 'Please enter content';
+        statusEl.style.opacity = '1';
+        setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+        return;
+    }
+    
+    // Build action with only necessary fields to avoid stale data
+    const action = {
+        type: actionType,
+        channel_type: channelType,
+        receiver: '',
+        receiver_name: '',
+        is_group: false,
+        notify_session_id: ''
+    };
+    
+    if (actionType === 'send_message') {
+        action.content = content;
+    } else {
+        action.task_description = content;
+    }
+    
+    // Preserve the original receiver info (channel is read-only, so it never changes)
+    if (currentEditingTask && currentEditingTask.action) {
+        action.receiver = currentEditingTask.action.receiver || '';
+        action.receiver_name = currentEditingTask.action.receiver_name || '';
+        action.is_group = currentEditingTask.action.is_group || false;
+        action.notify_session_id = currentEditingTask.action.notify_session_id || '';
+        
+        // Preserve channel-specific fields (e.g. DingTalk sender_staff_id)
+        if (channelType === 'dingtalk' && currentEditingTask.action.dingtalk_sender_staff_id) {
+            action.dingtalk_sender_staff_id = currentEditingTask.action.dingtalk_sender_staff_id;
+        }
+    }
+    
+    saveBtn.disabled = true;
+    
+    const payload = {
+        task_id: currentEditingTask.id,
+        name: name,
+        enabled: enabledInput.checked,
+        schedule: schedule,
+        action: action
+    };
+    
+    fetch('/api/scheduler/update', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify(payload)
+    }).then(r => r.json()).then(res => {
+        saveBtn.disabled = false;
+        if (res.status === 'success') {
+            closeTaskEditModal();
+            tasksLoaded = false;
+            loadTasksView();
+        } else {
+            statusEl.textContent = res.message || (currentLang === 'zh' ? '保存失败' : 'Save failed');
+            statusEl.style.opacity = '1';
+            setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+        }
+    }).catch(() => {
+        saveBtn.disabled = false;
+        statusEl.textContent = currentLang === 'zh' ? '网络错误' : 'Network error';
+        statusEl.style.opacity = '1';
+        setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+    });
+}
+
+function deleteTask() {
+    if (!currentEditingTask) return;
+    
+    const taskName = currentEditingTask.name || currentEditingTask.id || '未知任务';
+    const taskId = currentEditingTask.id;  // Capture early to avoid closure race condition
+    showConfirmDialog({
+        title: t('task_delete_confirm_title'),
+        message: (currentLang === 'zh' ? `确定要删除任务「${taskName}」吗？` : `Are you sure to delete task "${taskName}"?`),
+        onConfirm: () => {
+            fetch('/api/scheduler/delete', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ task_id: taskId })
+            }).then(r => r.json()).then(res => {
+                if (res.status === 'success') {
+                    closeTaskEditModal();
+                    tasksLoaded = false;
+                    loadTasksView();
+                } else {
+                    const statusEl = document.getElementById('task-edit-modal-status');
+                    if (statusEl) {
+                        statusEl.textContent = res.message || 'Delete failed';
+                        statusEl.classList.remove('hidden', 'text-green-500');
+                        statusEl.classList.add('text-red-500');
+                        setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+                    }
+                }
+            }).catch(() => {
+                const statusEl = document.getElementById('task-edit-modal-status');
+                if (statusEl) {
+                    statusEl.textContent = 'Network error';
+                    statusEl.classList.remove('hidden', 'text-green-500');
+                    statusEl.classList.add('text-red-500');
+                    setTimeout(() => { statusEl.style.opacity = '0'; }, 3000);
+                }
+            });
+        }
+    });
+}
+
+document.getElementById('task-edit-schedule-type').addEventListener('change', updateTaskScheduleFields);
+document.getElementById('task-edit-action-type').addEventListener('change', updateTaskActionLabel);
+document.getElementById('task-edit-modal-cancel').addEventListener('click', closeTaskEditModal);
+document.getElementById('task-edit-modal-save').addEventListener('click', saveTaskEdit);
+document.getElementById('task-edit-modal-delete').addEventListener('click', deleteTask);
+document.getElementById('task-edit-modal-overlay').addEventListener('click', function(e) {
+    if (e.target === this) closeTaskEditModal();
+});
diff --git a/channel/web/static/logo.jpg b/channel/web/static/logo.jpg
new file mode 100644
index 0000000..589a12a
Binary files /dev/null and b/channel/web/static/logo.jpg differ
diff --git a/channel/web/static/logos/claudeAPI.svg b/channel/web/static/logos/claudeAPI.svg
new file mode 100644
index 0000000..e9a401b
--- /dev/null
+++ b/channel/web/static/logos/claudeAPI.svg
@@ -0,0 +1 @@
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+++ b/channel/web/static/logos/minimax.svg
@@ -0,0 +1 @@
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diff --git a/channel/web/static/logos/moonshot.svg b/channel/web/static/logos/moonshot.svg
new file mode 100644
index 0000000..20d60b5
--- /dev/null
+++ b/channel/web/static/logos/moonshot.svg
@@ -0,0 +1 @@
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diff --git a/channel/web/static/logos/openai.svg b/channel/web/static/logos/openai.svg
new file mode 100644
index 0000000..b7b1fc5
--- /dev/null
+++ b/channel/web/static/logos/openai.svg
@@ -0,0 +1 @@
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diff --git a/channel/web/static/logos/qianfan.svg b/channel/web/static/logos/qianfan.svg
new file mode 100644
index 0000000..a935667
--- /dev/null
+++ b/channel/web/static/logos/qianfan.svg
@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1779251568791" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="14450" xmlns:xlink="http://www.w3.org/1999/xlink" width="200" height="200"><path d="M96.20121136 636.3124965c-0.1472897-113.41305959-0.29457937-226.8261192-0.29457937-340.23917879 0-14.87625845 7.65906378-26.51214381 20.4732666-34.02391789 45.51251353-26.65943349 91.02502705-53.31886698 136.83211997-79.53643141 71.1409192-40.94653321 142.42912809-81.59848704 213.71733698-122.39773055 7.36448439-4.12411126 14.58167909-8.3955122 21.50429441-13.2560719 19.44223878-13.40336159 39.03176725-16.05457598 60.09419263-3.53495252 27.39588193 16.34915535 54.93905355 32.25644163 82.48222516 48.16372793 88.0792333 50.96223197 176.30575629 101.77717426 264.38498958 152.59211653 9.86840908 5.74429781 19.88410785 11.19401627 29.60522725 17.0856038 14.13981003 8.54280189 21.50429441 21.06242535 21.50429443 37.70616007 0 147.73155685 0.29457937 295.46311371-0.1472897 443.19467057 0 15.46541722-7.2171947 28.57419943-21.7988738 36.96971163-34.7603663 20.17868721-70.55176044 38.88447758-104.57567833 59.94690293-48.90017634 30.19438599-100.00969801 56.11737105-148.76258466 86.60633642-29.01606849 18.11663161-59.50503387 34.02391789-89.11026112 50.96223197-13.10878221 7.51177407-26.07027474 15.17083783-39.03176726 22.9771913-13.84523065 8.3955122-27.83775099 8.83738127-41.97756102 0.73644843-56.41195043-32.55102101-112.82390085-65.10204201-169.38314098-97.653063-61.86166887-35.64410444-123.72333775-71.1409192-185.4377169-106.78502365-11.19401627-6.48074626-22.24074286-12.81420285-32.99289009-19.88410785-11.48859565-7.65906378-17.08560379-19.14765941-17.08560378-32.69831069-0.1472897-34.7603663 0.1472897-69.52073264 0.29457938-104.28109895 1.62018657-0.58915875 1.62018657-1.62018657-0.29457938-2.65121438z m356.58833414-225.500512c2.20934532-1.76747625 4.41869063-3.68224221 6.77532565-5.15513907 68.93157389-39.62092601 137.86314777-79.24185204 206.94201135-118.86277807 2.79850407-1.62018657 6.48074626-1.62018657 6.62803594-6.18616688 0.1472897-4.8605597-4.12411126-4.71327001-6.77532564-6.18616688-40.65195383-23.56635005-81.59848704-46.83812071-122.10315117-70.84633984-16.79102442-10.01569877-32.84560039-8.54280189-48.45830728 0.58915876-45.9543826 26.51214381-91.46689612 53.61344636-137.27398903 80.42016953-31.96186226 18.70579035-64.21830387 37.11700133-96.32745581 55.67550198-18.41121097 10.60485751-27.54317163 25.33382629-27.24859225 47.72185885 0.88373813 89.55213018 0.58915875 179.10426036 0.14728969 268.65639053-0.1472897 20.17868721 9.27925033 33.58204881 25.33382629 43.15587853 31.3727035 18.70579035 63.18727606 37.11700133 95.14913832 54.93905355 10.89943689 6.03887719 21.06242535 13.99252034 35.79139414 18.41121096V505.51925374c6.48074626 19.58952848 18.55850066 34.02391789 36.67513226 44.6287754 27.83775099 16.20186565 63.18727606 12.51962347 86.31175705-10.45756784 26.95401286-26.65943349 28.72148912-62.89269668 12.81420282-90.14128893-16.34915535-28.42690974-43.59774757-37.55887038-74.38129233-38.73718787z m82.48222517 429.64401928c14.28709972-3.82953187 25.92298506-13.99252034 38.88447758-21.35700473 40.94653321-23.27177067 81.30390766-47.72185885 122.54502023-70.55176046 26.95401286-15.02354815 52.87699792-31.66728287 80.71474891-45.21793415 16.79102442-8.10093283 29.60522723-22.53532223 29.60522726-43.4504579 0.1472897-92.939793 0.29457937-185.73229631 0.14728969-278.6720893 0-11.19401627-5.15513907-13.99252034-13.84523067-7.06990501-26.51214381 20.76784598-57.29568854 34.46578693-86.16446735 51.25681135-54.49718448 31.81457257-109.14165865 63.33456576-163.78613282 95.00184862-8.54280189 4.8605597-11.78317502 10.45756784-11.63588535 20.47326662 0.29457937 96.18016613 0.1472897 192.50762194 0.1472897 288.68778806-0.29457937 3.5349525-1.47289687 7.65906378 3.38766282 10.8994369z" fill="#066AF3" p-id="14451"></path><path d="M96.20121136 636.3124965c1.91476594 1.03102783 1.91476594 2.06205563 0 3.09308345v-3.09308345z" fill="#4372E0" p-id="14452"></path><path d="M391.3697457 505.37196405c-5.44971845-44.33419602 13.84523065-74.08671296 61.4197998-94.55997955 30.93083443 1.17831749 58.03213699 10.31027814 74.38129233 38.5898982 15.75999659 27.39588193 14.13981003 63.48185543-12.81420282 90.14128893-23.27177067 22.97719129-58.47400606 26.65943349-86.31175705 10.45756783-18.11663161-10.60485751-30.34167568-25.03924691-36.67513226-44.62877541z" fill="#002A9A" p-id="14453"></path></svg>
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diff --git a/channel/web/static/logos/zhipu.svg b/channel/web/static/logos/zhipu.svg
new file mode 100644
index 0000000..e4b5546
--- /dev/null
+++ b/channel/web/static/logos/zhipu.svg
@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1779251419020" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="10062" xmlns:xlink="http://www.w3.org/1999/xlink" width="200" height="200"><path d="M520.063496 0v77.563152c0 269.231173-144.758953 414.054122-434.212862 434.340854L86.106618 511.968002H76.827198V255.984001l443.236298-255.984001z" fill="#5B55F6" p-id="10063"></path><path d="M520.063496 1023.936004v-77.563152c0-269.231173-144.758953-414.054122-434.212862-434.340854L86.042622 511.968002H76.827198v255.984001l443.236298 255.984001z" fill="#376AF3" p-id="10064"></path><path d="M520.063496 0v77.563152c0 269.231173 144.758953 414.054122 434.276858 434.340854L954.08437 511.968002h9.215424V255.984001L520.063496 0z" fill="#5B55F6" p-id="10065"></path><path d="M520.063496 1023.936004v-77.563152c0-269.231173 144.758953-414.054122 434.276858-434.340854L954.08437 511.968002h9.27942v255.984001l-443.236298 255.984001z" fill="#376AF3" p-id="10066"></path></svg>
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diff --git a/channel/web/static/vendor/README.md b/channel/web/static/vendor/README.md
new file mode 100644
index 0000000..69e3536
--- /dev/null
+++ b/channel/web/static/vendor/README.md
@@ -0,0 +1,41 @@
+# Vendor assets
+
+Third-party frontend assets bundled locally so the Web Console can run in
+fully offline / air-gapped environments (no requests to cloudflare, jsdelivr,
+googleapis, gstatic, etc.).
+
+All files here are vendored copies of upstream releases. Do not edit them by
+hand; re-download from the official source if upgrading.
+
+## Manifest
+
+| Path                                                | Source                                                                                            | Version |
+| --------------------------------------------------- | ------------------------------------------------------------------------------------------------- | ------- |
+| `fontawesome/css/all.min.css`                       | https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css                         | 6.4.0   |
+| `fontawesome/webfonts/fa-{brands,regular,solid,v4compatibility}-*.woff2` | https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/webfonts/              | 6.4.0   |
+| `fonts/inter/inter-latin.woff2`                     | https://fonts.gstatic.com/s/inter/v20/UcC73FwrK3iLTeHuS_nVMrMxCp50SjIa1ZL7.woff2                  | v20     |
+| `fonts/inter/inter.css`                             | Hand-written `@font-face` declaration that maps Inter weights 300-700 to the local woff2          | -       |
+| `tailwind/tailwind.min.js`                          | https://cdn.tailwindcss.com (Play CDN runtime, JIT engine for the browser)                        | latest  |
+| `markdown-it/markdown-it.min.js`                    | https://cdn.jsdelivr.net/npm/markdown-it@13.0.1/dist/markdown-it.min.js                           | 13.0.1  |
+| `highlightjs/highlight.min.js`                      | https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js                       | 11.9.0  |
+| `highlightjs/styles/github{,-dark}.min.css`         | https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/                                | 11.9.0  |
+| `highlightjs/languages/{python,javascript,java,go,bash}.min.js` | https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/languages/                  | 11.9.0  |
+| `d3/d3.min.js`                                      | https://cdn.jsdelivr.net/npm/d3@7/dist/d3.min.js (loaded lazily for the knowledge graph view)     | 7.x     |
+
+Notes:
+
+- The Inter font only ships the latin subset (CJK characters fall back to the
+  system sans-serif via the font-family chain in `tailwind.config`).
+- Only `woff2` font files are shipped (no `ttf` fallback). woff2 is supported
+  by all browsers released since 2014-2018 (Chrome 36+, Firefox 39+, Safari
+  12+, Edge, Opera 26+). The only mainstream browser that lacks woff2 support
+  is IE 11, which cannot run the rest of the console anyway. `all.min.css`
+  still references the ttf paths as a `src:` fallback — those 404s are
+  harmless and ignored by the browser once the woff2 loads.
+- `tailwind.min.js` is the official Tailwind Play CDN build (an in-browser JIT
+  engine). It must be served as JS to keep the existing `tailwind.config = {}`
+  customization working.
+- One external script remains in `channel/web/static/js/console.js`:
+  `wwcdn.weixin.qq.com/.../wecom-aibot-sdk` — Tencent requires the WeCom Bot
+  SDK to be loaded from their CDN, and it is only fetched when the user opens
+  the WeCom Bot QR-login flow.
diff --git a/channel/web/static/vendor/d3/d3.min.js b/channel/web/static/vendor/d3/d3.min.js
new file mode 100644
index 0000000..33bb880
--- /dev/null
+++ b/channel/web/static/vendor/d3/d3.min.js
@@ -0,0 +1,2 @@
+// https://d3js.org v7.9.0 Copyright 2010-2023 Mike Bostock
+!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((t="undefined"!=typeof globalThis?globalThis:t||self).d3=t.d3||{})}(this,(function(t){"use strict";function n(t,n){return null==t||null==n?NaN:t<n?-1:t>n?1:t>=n?0:NaN}function e(t,n){return null==t||null==n?NaN:n<t?-1:n>t?1:n>=t?0:NaN}function r(t){let r,o,a;function u(t,n,e=0,i=t.length){if(e<i){if(0!==r(n,n))return i;do{const r=e+i>>>1;o(t[r],n)<0?e=r+1:i=r}while(e<i)}return e}return 2!==t.length?(r=n,o=(e,r)=>n(t(e),r),a=(n,e)=>t(n)-e):(r=t===n||t===e?t:i,o=t,a=t),{left:u,center:function(t,n,e=0,r=t.length){const i=u(t,n,e,r-1);return i>e&&a(t[i-1],n)>-a(t[i],n)?i-1:i},right:function(t,n,e=0,i=t.length){if(e<i){if(0!==r(n,n))return i;do{const r=e+i>>>1;o(t[r],n)<=0?e=r+1:i=r}while(e<i)}return e}}}function i(){return 0}function o(t){return null===t?NaN:+t}const a=r(n),u=a.right,c=a.left,f=r(o).center;var s=u;const l=d(y),h=d((function(t){const 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n=0;n<o;n++)this._dists[n]=Eu(t[2*n],t[2*n+1],w.x,w.y);Cu(this._ids,this._dists,0,o-1),this._hullStart=h;let M=3;e[h]=n[p]=d,e[d]=n[h]=p,e[p]=n[d]=h,r[h]=0,r[d]=1,r[p]=2,i.fill(-1),i[this._hashKey(g,y)]=h,i[this._hashKey(v,_)]=d,i[this._hashKey(m,x)]=p,this.trianglesLen=0,this._addTriangle(h,d,p,-1,-1,-1);for(let o,a,u=0;u<this._ids.length;u++){const c=this._ids[u],f=t[2*c],s=t[2*c+1];if(u>0&&Math.abs(f-o)<=Tu&&Math.abs(s-a)<=Tu)continue;if(o=f,a=s,c===h||c===d||c===p)continue;let l=0;for(let t=0,n=this._hashKey(f,s);t<this._hashSize&&(l=i[(n+t)%this._hashSize],-1===l||l===e[l]);t++);l=n[l];let g,y=l;for(;g=e[y],Mu(f,s,t[2*y],t[2*y+1],t[2*g],t[2*g+1])>=0;)if(y=g,y===l){y=-1;break}if(-1===y)continue;let v=this._addTriangle(y,c,e[y],-1,-1,r[y]);r[c]=this._legalize(v+2),r[y]=v,M++;let _=e[y];for(;g=e[_],Mu(f,s,t[2*_],t[2*_+1],t[2*g],t[2*g+1])<0;)v=this._addTriangle(_,c,g,r[c],-1,r[_]),r[c]=this._legalize(v+2),e[_]=_,M--,_=g;if(y===l)for(;g=n[y],Mu(f,s,t[2*g],t[2*g+1],t[2*y],t[2*y+1])<0;)v=this._addTriangle(g,c,y,-1,r[y],r[g]),this._legalize(v+2),r[g]=v,e[y]=y,M--,y=g;this._hullStart=n[c]=y,e[y]=n[_]=c,e[c]=_,i[this._hashKey(f,s)]=c,i[this._hashKey(t[2*y],t[2*y+1])]=y}this.hull=new Uint32Array(M);for(let t=0,n=this._hullStart;t<M;t++)this.hull[t]=n,n=e[n];this.triangles=this._triangles.subarray(0,this.trianglesLen),this.halfedges=this._halfedges.subarray(0,this.trianglesLen)}_hashKey(t,n){return Math.floor(function(t,n){const e=t/(Math.abs(t)+Math.abs(n));return(n>0?3-e:1+e)/4}(t-this._cx,n-this._cy)*this._hashSize)%this._hashSize}_legalize(t){const{_triangles:n,_halfedges:e,coords:r}=this;let i=0,o=0;for(;;){const a=e[t],u=t-t%3;if(o=u+(t+2)%3,-1===a){if(0===i)break;t=Au[--i];continue}const c=a-a%3,f=u+(t+1)%3,s=c+(a+2)%3,l=n[o],h=n[t],d=n[f],p=n[s];if(Nu(r[2*l],r[2*l+1],r[2*h],r[2*h+1],r[2*d],r[2*d+1],r[2*p],r[2*p+1])){n[t]=p,n[a]=l;const r=e[s];if(-1===r){let n=this._hullStart;do{if(this._hullTri[n]===s){this._hullTri[n]=t;break}n=this._hullPrev[n]}while(n!==this._hullStart)}this._link(t,r),this._link(a,e[o]),this._link(o,s);const u=c+(a+1)%3;i<Au.length&&(Au[i++]=u)}else{if(0===i)break;t=Au[--i]}}return o}_link(t,n){this._halfedges[t]=n,-1!==n&&(this._halfedges[n]=t)}_addTriangle(t,n,e,r,i,o){const a=this.trianglesLen;return this._triangles[a]=t,this._triangles[a+1]=n,this._triangles[a+2]=e,this._link(a,r),this._link(a+1,i),this._link(a+2,o),this.trianglesLen+=3,a}}function Eu(t,n,e,r){const i=t-e,o=n-r;return i*i+o*o}function Nu(t,n,e,r,i,o,a,u){const c=t-a,f=n-u,s=e-a,l=r-u,h=i-a,d=o-u,p=s*s+l*l,g=h*h+d*d;return c*(l*g-p*d)-f*(s*g-p*h)+(c*c+f*f)*(s*d-l*h)<0}function ku(t,n,e,r,i,o){const a=e-t,u=r-n,c=i-t,f=o-n,s=a*a+u*u,l=c*c+f*f,h=.5/(a*f-u*c),d=(f*s-u*l)*h,p=(a*l-c*s)*h;return d*d+p*p}function Cu(t,n,e,r){if(r-e<=20)for(let i=e+1;i<=r;i++){const r=t[i],o=n[r];let a=i-1;for(;a>=e&&n[t[a]]>o;)t[a+1]=t[a--];t[a+1]=r}else{let i=e+1,o=r;Pu(t,e+r>>1,i),n[t[e]]>n[t[r]]&&Pu(t,e,r),n[t[i]]>n[t[r]]&&Pu(t,i,r),n[t[e]]>n[t[i]]&&Pu(t,e,i);const a=t[i],u=n[a];for(;;){do{i++}while(n[t[i]]<u);do{o--}while(n[t[o]]>u);if(o<i)break;Pu(t,i,o)}t[e+1]=t[o],t[o]=a,r-i+1>=o-e?(Cu(t,n,i,r),Cu(t,n,e,o-1)):(Cu(t,n,e,o-1),Cu(t,n,i,r))}}function Pu(t,n,e){const r=t[n];t[n]=t[e],t[e]=r}function zu(t){return t[0]}function $u(t){return t[1]}const Du=1e-6;class Ru{constructor(){this._x0=this._y0=this._x1=this._y1=null,this._=""}moveTo(t,n){this._+=`M${this._x0=this._x1=+t},${this._y0=this._y1=+n}`}closePath(){null!==this._x1&&(this._x1=this._x0,this._y1=this._y0,this._+="Z")}lineTo(t,n){this._+=`L${this._x1=+t},${this._y1=+n}`}arc(t,n,e){const r=(t=+t)+(e=+e),i=n=+n;if(e<0)throw new Error("negative radius");null===this._x1?this._+=`M${r},${i}`:(Math.abs(this._x1-r)>Du||Math.abs(this._y1-i)>Du)&&(this._+="L"+r+","+i),e&&(this._+=`A${e},${e},0,1,1,${t-e},${n}A${e},${e},0,1,1,${this._x1=r},${this._y1=i}`)}rect(t,n,e,r){this._+=`M${this._x0=this._x1=+t},${this._y0=this._y1=+n}h${+e}v${+r}h${-e}Z`}value(){return this._||null}}class Fu{constructor(){this._=[]}moveTo(t,n){this._.push([t,n])}closePath(){this._.push(this._[0].slice())}lineTo(t,n){this._.push([t,n])}value(){return this._.length?this._:null}}class qu{constructor(t,[n,e,r,i]=[0,0,960,500]){if(!((r=+r)>=(n=+n)&&(i=+i)>=(e=+e)))throw new Error("invalid bounds");this.delaunay=t,this._circumcenters=new Float64Array(2*t.points.length),this.vectors=new Float64Array(2*t.points.length),this.xmax=r,this.xmin=n,this.ymax=i,this.ymin=e,this._init()}update(){return this.delaunay.update(),this._init(),this}_init(){const{delaunay:{points:t,hull:n,triangles:e},vectors:r}=this;let i,o;const a=this.circumcenters=this._circumcenters.subarray(0,e.length/3*2);for(let r,u,c=0,f=0,s=e.length;c<s;c+=3,f+=2){const s=2*e[c],l=2*e[c+1],h=2*e[c+2],d=t[s],p=t[s+1],g=t[l],y=t[l+1],v=t[h],_=t[h+1],b=g-d,m=y-p,x=v-d,w=_-p,M=2*(b*w-m*x);if(Math.abs(M)<1e-9){if(void 0===i){i=o=0;for(const e of n)i+=t[2*e],o+=t[2*e+1];i/=n.length,o/=n.length}const e=1e9*Math.sign((i-d)*w-(o-p)*x);r=(d+v)/2-e*w,u=(p+_)/2+e*x}else{const t=1/M,n=b*b+m*m,e=x*x+w*w;r=d+(w*n-m*e)*t,u=p+(b*e-x*n)*t}a[f]=r,a[f+1]=u}let u,c,f,s=n[n.length-1],l=4*s,h=t[2*s],d=t[2*s+1];r.fill(0);for(let e=0;e<n.length;++e)s=n[e],u=l,c=h,f=d,l=4*s,h=t[2*s],d=t[2*s+1],r[u+2]=r[l]=f-d,r[u+3]=r[l+1]=h-c}render(t){const n=null==t?t=new Ru:void 0,{delaunay:{halfedges:e,inedges:r,hull:i},circumcenters:o,vectors:a}=this;if(i.length<=1)return null;for(let n=0,r=e.length;n<r;++n){const r=e[n];if(r<n)continue;const i=2*Math.floor(n/3),a=2*Math.floor(r/3),u=o[i],c=o[i+1],f=o[a],s=o[a+1];this._renderSegment(u,c,f,s,t)}let u,c=i[i.length-1];for(let n=0;n<i.length;++n){u=c,c=i[n];const e=2*Math.floor(r[c]/3),f=o[e],s=o[e+1],l=4*u,h=this._project(f,s,a[l+2],a[l+3]);h&&this._renderSegment(f,s,h[0],h[1],t)}return n&&n.value()}renderBounds(t){const n=null==t?t=new Ru:void 0;return t.rect(this.xmin,this.ymin,this.xmax-this.xmin,this.ymax-this.ymin),n&&n.value()}renderCell(t,n){const e=null==n?n=new Ru:void 0,r=this._clip(t);if(null===r||!r.length)return;n.moveTo(r[0],r[1]);let i=r.length;for(;r[0]===r[i-2]&&r[1]===r[i-1]&&i>1;)i-=2;for(let t=2;t<i;t+=2)r[t]===r[t-2]&&r[t+1]===r[t-1]||n.lineTo(r[t],r[t+1]);return n.closePath(),e&&e.value()}*cellPolygons(){const{delaunay:{points:t}}=this;for(let n=0,e=t.length/2;n<e;++n){const t=this.cellPolygon(n);t&&(t.index=n,yield t)}}cellPolygon(t){const n=new Fu;return this.renderCell(t,n),n.value()}_renderSegment(t,n,e,r,i){let o;const a=this._regioncode(t,n),u=this._regioncode(e,r);0===a&&0===u?(i.moveTo(t,n),i.lineTo(e,r)):(o=this._clipSegment(t,n,e,r,a,u))&&(i.moveTo(o[0],o[1]),i.lineTo(o[2],o[3]))}contains(t,n,e){return(n=+n)==n&&(e=+e)==e&&this.delaunay._step(t,n,e)===t}*neighbors(t){const n=this._clip(t);if(n)for(const e of this.delaunay.neighbors(t)){const t=this._clip(e);if(t)t:for(let r=0,i=n.length;r<i;r+=2)for(let o=0,a=t.length;o<a;o+=2)if(n[r]===t[o]&&n[r+1]===t[o+1]&&n[(r+2)%i]===t[(o+a-2)%a]&&n[(r+3)%i]===t[(o+a-1)%a]){yield e;break t}}}_cell(t){const{circumcenters:n,delaunay:{inedges:e,halfedges:r,triangles:i}}=this,o=e[t];if(-1===o)return null;const a=[];let u=o;do{const e=Math.floor(u/3);if(a.push(n[2*e],n[2*e+1]),u=u%3==2?u-2:u+1,i[u]!==t)break;u=r[u]}while(u!==o&&-1!==u);return a}_clip(t){if(0===t&&1===this.delaunay.hull.length)return[this.xmax,this.ymin,this.xmax,this.ymax,this.xmin,this.ymax,this.xmin,this.ymin];const n=this._cell(t);if(null===n)return null;const{vectors:e}=this,r=4*t;return this._simplify(e[r]||e[r+1]?this._clipInfinite(t,n,e[r],e[r+1],e[r+2],e[r+3]):this._clipFinite(t,n))}_clipFinite(t,n){const e=n.length;let r,i,o,a,u=null,c=n[e-2],f=n[e-1],s=this._regioncode(c,f),l=0;for(let h=0;h<e;h+=2)if(r=c,i=f,c=n[h],f=n[h+1],o=s,s=this._regioncode(c,f),0===o&&0===s)a=l,l=0,u?u.push(c,f):u=[c,f];else{let n,e,h,d,p;if(0===o){if(null===(n=this._clipSegment(r,i,c,f,o,s)))continue;[e,h,d,p]=n}else{if(null===(n=this._clipSegment(c,f,r,i,s,o)))continue;[d,p,e,h]=n,a=l,l=this._edgecode(e,h),a&&l&&this._edge(t,a,l,u,u.length),u?u.push(e,h):u=[e,h]}a=l,l=this._edgecode(d,p),a&&l&&this._edge(t,a,l,u,u.length),u?u.push(d,p):u=[d,p]}if(u)a=l,l=this._edgecode(u[0],u[1]),a&&l&&this._edge(t,a,l,u,u.length);else if(this.contains(t,(this.xmin+this.xmax)/2,(this.ymin+this.ymax)/2))return[this.xmax,this.ymin,this.xmax,this.ymax,this.xmin,this.ymax,this.xmin,this.ymin];return u}_clipSegment(t,n,e,r,i,o){const a=i<o;for(a&&([t,n,e,r,i,o]=[e,r,t,n,o,i]);;){if(0===i&&0===o)return a?[e,r,t,n]:[t,n,e,r];if(i&o)return null;let u,c,f=i||o;8&f?(u=t+(e-t)*(this.ymax-n)/(r-n),c=this.ymax):4&f?(u=t+(e-t)*(this.ymin-n)/(r-n),c=this.ymin):2&f?(c=n+(r-n)*(this.xmax-t)/(e-t),u=this.xmax):(c=n+(r-n)*(this.xmin-t)/(e-t),u=this.xmin),i?(t=u,n=c,i=this._regioncode(t,n)):(e=u,r=c,o=this._regioncode(e,r))}}_clipInfinite(t,n,e,r,i,o){let a,u=Array.from(n);if((a=this._project(u[0],u[1],e,r))&&u.unshift(a[0],a[1]),(a=this._project(u[u.length-2],u[u.length-1],i,o))&&u.push(a[0],a[1]),u=this._clipFinite(t,u))for(let n,e=0,r=u.length,i=this._edgecode(u[r-2],u[r-1]);e<r;e+=2)n=i,i=this._edgecode(u[e],u[e+1]),n&&i&&(e=this._edge(t,n,i,u,e),r=u.length);else this.contains(t,(this.xmin+this.xmax)/2,(this.ymin+this.ymax)/2)&&(u=[this.xmin,this.ymin,this.xmax,this.ymin,this.xmax,this.ymax,this.xmin,this.ymax]);return u}_edge(t,n,e,r,i){for(;n!==e;){let e,o;switch(n){case 5:n=4;continue;case 4:n=6,e=this.xmax,o=this.ymin;break;case 6:n=2;continue;case 2:n=10,e=this.xmax,o=this.ymax;break;case 10:n=8;continue;case 8:n=9,e=this.xmin,o=this.ymax;break;case 9:n=1;continue;case 1:n=5,e=this.xmin,o=this.ymin}r[i]===e&&r[i+1]===o||!this.contains(t,e,o)||(r.splice(i,0,e,o),i+=2)}return i}_project(t,n,e,r){let i,o,a,u=1/0;if(r<0){if(n<=this.ymin)return null;(i=(this.ymin-n)/r)<u&&(a=this.ymin,o=t+(u=i)*e)}else if(r>0){if(n>=this.ymax)return null;(i=(this.ymax-n)/r)<u&&(a=this.ymax,o=t+(u=i)*e)}if(e>0){if(t>=this.xmax)return null;(i=(this.xmax-t)/e)<u&&(o=this.xmax,a=n+(u=i)*r)}else if(e<0){if(t<=this.xmin)return null;(i=(this.xmin-t)/e)<u&&(o=this.xmin,a=n+(u=i)*r)}return[o,a]}_edgecode(t,n){return(t===this.xmin?1:t===this.xmax?2:0)|(n===this.ymin?4:n===this.ymax?8:0)}_regioncode(t,n){return(t<this.xmin?1:t>this.xmax?2:0)|(n<this.ymin?4:n>this.ymax?8:0)}_simplify(t){if(t&&t.length>4){for(let n=0;n<t.length;n+=2){const e=(n+2)%t.length,r=(n+4)%t.length;(t[n]===t[e]&&t[e]===t[r]||t[n+1]===t[e+1]&&t[e+1]===t[r+1])&&(t.splice(e,2),n-=2)}t.length||(t=null)}return t}}const Uu=2*Math.PI,Iu=Math.pow;function Ou(t){return t[0]}function Bu(t){return t[1]}function Yu(t,n,e){return[t+Math.sin(t+n)*e,n+Math.cos(t-n)*e]}class Lu{static from(t,n=Ou,e=Bu,r){return new Lu("length"in t?function(t,n,e,r){const i=t.length,o=new Float64Array(2*i);for(let a=0;a<i;++a){const i=t[a];o[2*a]=n.call(r,i,a,t),o[2*a+1]=e.call(r,i,a,t)}return o}(t,n,e,r):Float64Array.from(function*(t,n,e,r){let i=0;for(const o of t)yield n.call(r,o,i,t),yield e.call(r,o,i,t),++i}(t,n,e,r)))}constructor(t){this._delaunator=new Su(t),this.inedges=new Int32Array(t.length/2),this._hullIndex=new Int32Array(t.length/2),this.points=this._delaunator.coords,this._init()}update(){return this._delaunator.update(),this._init(),this}_init(){const t=this._delaunator,n=this.points;if(t.hull&&t.hull.length>2&&function(t){const{triangles:n,coords:e}=t;for(let t=0;t<n.length;t+=3){const 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diff --git a/channel/web/static/vendor/fontawesome/css/all.min.css b/channel/web/static/vendor/fontawesome/css/all.min.css
new file mode 100644
index 0000000..1f367c1
--- /dev/null
+++ b/channel/web/static/vendor/fontawesome/css/all.min.css
@@ -0,0 +1,9 @@
+/*!
+ * Font Awesome Free 6.4.0 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2023 Fonticons, Inc.
+ */
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diff --git a/channel/web/static/vendor/fontawesome/webfonts/fa-brands-400.woff2 b/channel/web/static/vendor/fontawesome/webfonts/fa-brands-400.woff2
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new file mode 100644
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diff --git a/channel/web/static/vendor/fontawesome/webfonts/fa-solid-900.woff2 b/channel/web/static/vendor/fontawesome/webfonts/fa-solid-900.woff2
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diff --git a/channel/web/static/vendor/fontawesome/webfonts/fa-v4compatibility.woff2 b/channel/web/static/vendor/fontawesome/webfonts/fa-v4compatibility.woff2
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diff --git a/channel/web/static/vendor/fonts/inter/inter-latin.woff2 b/channel/web/static/vendor/fonts/inter/inter-latin.woff2
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diff --git a/channel/web/static/vendor/fonts/inter/inter.css b/channel/web/static/vendor/fonts/inter/inter.css
new file mode 100644
index 0000000..fb890c2
--- /dev/null
+++ b/channel/web/static/vendor/fonts/inter/inter.css
@@ -0,0 +1,16 @@
+/* Inter font (latin subset only).
+ * Single variable font woff2 that covers weights 300/400/500/600/700.
+ * Non-latin scripts (CJK, etc.) fall back to system sans-serif via the
+ * font-family chain defined in tailwind.config (Inter, system-ui, ...).
+ * Source: Google Fonts (Inter v20), redistributed locally to avoid runtime
+ * dependency on fonts.googleapis.com / fonts.gstatic.com.
+ */
+
+@font-face {
+    font-family: 'Inter';
+    font-style: normal;
+    font-weight: 300 700;
+    font-display: swap;
+    src: url('./inter-latin.woff2') format('woff2');
+    unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD;
+}
diff --git a/channel/web/static/vendor/highlightjs/highlight.min.js b/channel/web/static/vendor/highlightjs/highlight.min.js
new file mode 100644
index 0000000..5d699ae
--- /dev/null
+++ b/channel/web/static/vendor/highlightjs/highlight.min.js
@@ -0,0 +1,1213 @@
+/*!
+  Highlight.js v11.9.0 (git: f47103d4f1)
+  (c) 2006-2023 undefined and other contributors
+  License: BSD-3-Clause
+ */
+var hljs=function(){"use strict";function e(n){
+return n instanceof Map?n.clear=n.delete=n.set=()=>{
+throw Error("map is read-only")}:n instanceof Set&&(n.add=n.clear=n.delete=()=>{
+throw Error("set is read-only")
+}),Object.freeze(n),Object.getOwnPropertyNames(n).forEach((t=>{
+const a=n[t],i=typeof a;"object"!==i&&"function"!==i||Object.isFrozen(a)||e(a)
+})),n}class n{constructor(e){
+void 0===e.data&&(e.data={}),this.data=e.data,this.isMatchIgnored=!1}
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",cuesc:"\u22df",cularr:"\u21b6",cularrp:"\u293d",cupbrcap:"\u2a48",cupcap:"\u2a46",CupCap:"\u224d",cup:"\u222a",Cup:"\u22d3",cupcup:"\u2a4a",cupdot:"\u228d",cupor:"\u2a45",cups:"\u222a\ufe00",curarr:"\u21b7",curarrm:"\u293c",curlyeqprec:"\u22de",curlyeqsucc:"\u22df",curlyvee:"\u22ce",curlywedge:"\u22cf",curren:"\xa4",curvearrowleft:"\u21b6",curvearrowright:"\u21b7",cuvee:"\u22ce",cuwed:"\u22cf",cwconint:"\u2232",cwint:"\u2231",cylcty:"\u232d",dagger:"\u2020",Dagger:"\u2021",daleth:"\u2138",darr:"\u2193",Darr:"\u21a1",dArr:"\u21d3",dash:"\u2010",Dashv:"\u2ae4",dashv:"\u22a3",dbkarow:"\u290f",dblac:"\u02dd",Dcaron:"\u010e",dcaron:"\u010f",Dcy:"\u0414",dcy:"\u0434",ddagger:"\u2021",ddarr:"\u21ca",DD:"\u2145",dd:"\u2146",DDotrahd:"\u2911",ddotseq:"\u2a77",deg:"\xb0",Del:"\u2207",Delta:"\u0394",delta:"\u03b4",demptyv:"\u29b1",dfisht:"\u297f",Dfr:"\ud835\udd07",dfr:"\ud835\udd21",dHar:"\u2965",dharl:"\u21c3",dharr:"\u21c2",DiacriticalAcute:"\xb4",DiacriticalDot:"\u02d9",DiacriticalDoubleAcute:"\u02dd",DiacriticalGrave:"`",DiacriticalTilde:"\u02dc",diam:"\u22c4",diamond:"\u22c4",Diamond:"\u22c4",diamondsuit:"\u2666",diams:"\u2666",die:"\xa8",DifferentialD:"\u2146",digamma:"\u03dd",disin:"\u22f2",div:"\xf7",divide:"\xf7",divideontimes:"\u22c7",divonx:"\u22c7",DJcy:"\u0402",djcy:"\u0452",dlcorn:"\u231e",dlcrop:"\u230d",dollar:"$",Dopf:"\ud835\udd3b",dopf:"\ud835\udd55",Dot:"\xa8",dot:"\u02d9",DotDot:"\u20dc",doteq:"\u2250",doteqdot:"\u2251",DotEqual:"\u2250",dotminus:"\u2238",dotplus:"\u2214",dotsquare:"\u22a1",doublebarwedge:"\u2306",DoubleContourIntegral:"\u222f",DoubleDot:"\xa8",DoubleDownArrow:"\u21d3",DoubleLeftArrow:"\u21d0",DoubleLeftRightArrow:"\u21d4",DoubleLeftTee:"\u2ae4",DoubleLongLeftArrow:"\u27f8",DoubleLongLeftRightArrow:"\u27fa",DoubleLongRightArrow:"\u27f9",DoubleRightArrow:"\u21d2",DoubleRightTee:"\u22a8",DoubleUpArrow:"\u21d1",DoubleUpDownArrow:"\u21d5",DoubleVerticalBar:"\u2225",DownArrowBar:"\u2913",downarrow:"\u2193",DownArrow:"\u2193",Downarrow:"\u21d3",DownArrowUpArrow:"\u21f5",DownBreve:"\u0311",downdownarrows:"\u21ca",downharpoonleft:"\u21c3",downharpoonright:"\u21c2",DownLeftRightVector:"\u2950",DownLeftTeeVector:"\u295e",DownLeftVectorBar:"\u2956",DownLeftVector:"\u21bd",DownRightTeeVector:"\u295f",DownRightVectorBar:"\u2957",DownRightVector:"\u21c1",DownTeeArrow:"\u21a7",DownTee:"\u22a4",drbkarow:"\u2910",drcorn:"\u231f",drcrop:"\u230c",Dscr:"\ud835\udc9f",dscr:"\ud835\udcb9",DScy:"\u0405",dscy:"\u0455",dsol:"\u29f6",Dstrok:"\u0110",dstrok:"\u0111",dtdot:"\u22f1",dtri:"\u25bf",dtrif:"\u25be",duarr:"\u21f5",duhar:"\u296f",dwangle:"\u29a6",DZcy:"\u040f",dzcy:"\u045f",dzigrarr:"\u27ff",Eacute:"\xc9",eacute:"\xe9",easter:"\u2a6e",Ecaron:"\u011a",ecaron:"\u011b",Ecirc:"\xca",ecirc:"\xea",ecir:"\u2256",ecolon:"\u2255",Ecy:"\u042d",ecy:"\u044d",eDDot:"\u2a77",Edot:"\u0116",edot:"\u0117",eDot:"\u2251",ee:"\u2147",efDot:"\u2252",Efr:"\ud835\udd08",efr:"\ud835\udd22",eg:"\u2a9a",Egrave:"\xc8",egrave:"\xe8",egs:"\u2a96",egsdot:"\u2a98",el:"\u2a99",Element:"\u2208",elinters:"\u23e7",ell:"\u2113",els:"\u2a95",elsdot:"\u2a97",Emacr:"\u0112",emacr:"\u0113",empty:"\u2205",emptyset:"\u2205",EmptySmallSquare:"\u25fb",emptyv:"\u2205",EmptyVerySmallSquare:"\u25ab",emsp13:"\u2004",emsp14:"\u2005",emsp:"\u2003",ENG:"\u014a",eng:"\u014b",ensp:"\u2002",Eogon:"\u0118",eogon:"\u0119",Eopf:"\ud835\udd3c",eopf:"\ud835\udd56",epar:"\u22d5",eparsl:"\u29e3",eplus:"\u2a71",epsi:"\u03b5",Epsilon:"\u0395",epsilon:"\u03b5",epsiv:"\u03f5",eqcirc:"\u2256",eqcolon:"\u2255",eqsim:"\u2242",eqslantgtr:"\u2a96",eqslantless:"\u2a95",Equal:"\u2a75",equals:"=",EqualTilde:"\u2242",equest:"\u225f",Equilibrium:"\u21cc",equiv:"\u2261",equivDD:"\u2a78",eqvparsl:"\u29e5",erarr:"\u2971",erDot:"\u2253",escr:"\u212f",Escr:"\u2130",esdot:"\u2250",Esim:"\u2a73",esim:"\u2242",Eta:"\u0397",eta:"\u03b7",ETH:"\xd0",eth:"\xf0",Euml:"\xcb",euml:"\xeb",euro:"\u20ac",excl:"!",exist:"\u2203",Exists:"\u2203",expectation:"\u2130",exponentiale:"\u2147",ExponentialE:"\u2147",fallingdotseq:"\u2252",Fcy:"\u0424",fcy:"\u0444",female:"\u2640",ffilig:"\ufb03",fflig:"\ufb00",ffllig:"\ufb04",Ffr:"\ud835\udd09",ffr:"\ud835\udd23",filig:"\ufb01",FilledSmallSquare:"\u25fc",FilledVerySmallSquare:"\u25aa",fjlig:"fj",flat:"\u266d",fllig:"\ufb02",fltns:"\u25b1",fnof:"\u0192",Fopf:"\ud835\udd3d",fopf:"\ud835\udd57",forall:"\u2200",ForAll:"\u2200",fork:"\u22d4",forkv:"\u2ad9",Fouriertrf:"\u2131",fpartint:"\u2a0d",frac12:"\xbd",frac13:"\u2153",frac14:"\xbc",frac15:"\u2155",frac16:"\u2159",frac18:"\u215b",frac23:"\u2154",frac25:"\u2156",frac34:"\xbe",frac35:"\u2157",frac38:"\u215c",frac45:"\u2158",frac56:"\u215a",frac58:"\u215d",frac78:"\u215e",frasl:"\u2044",frown:"\u2322",fscr:"\ud835\udcbb",Fscr:"\u2131",gacute:"\u01f5",Gamma:"\u0393",gamma:"\u03b3",Gammad:"\u03dc",gammad:"\u03dd",gap:"\u2a86",Gbreve:"\u011e",gbreve:"\u011f",Gcedil:"\u0122",Gcirc:"\u011c",gcirc:"\u011d",Gcy:"\u0413",gcy:"\u0433",Gdot:"\u0120",gdot:"\u0121",ge:"\u2265",gE:"\u2267",gEl:"\u2a8c",gel:"\u22db",geq:"\u2265",geqq:"\u2267",geqslant:"\u2a7e",gescc:"\u2aa9",ges:"\u2a7e",gesdot:"\u2a80",gesdoto:"\u2a82",gesdotol:"\u2a84",gesl:"\u22db\ufe00",gesles:"\u2a94",Gfr:"\ud835\udd0a",gfr:"\ud835\udd24",gg:"\u226b",Gg:"\u22d9",ggg:"\u22d9",gimel:"\u2137",GJcy:"\u0403",gjcy:"\u0453",gla:"\u2aa5",gl:"\u2277",glE:"\u2a92",glj:"\u2aa4",gnap:"\u2a8a",gnapprox:"\u2a8a",gne:"\u2a88",gnE:"\u2269",gneq:"\u2a88",gneqq:"\u2269",gnsim:"\u22e7",Gopf:"\ud835\udd3e",gopf:"\ud835\udd58",grave:"`",GreaterEqual:"\u2265",GreaterEqualLess:"\u22db",GreaterFullEqual:"\u2267",GreaterGreater:"\u2aa2",GreaterLess:"\u2277",GreaterSlantEqual:"\u2a7e",GreaterTilde:"\u2273",Gscr:"\ud835\udca2",gscr:"\u210a",gsim:"\u2273",gsime:"\u2a8e",gsiml:"\u2a90",gtcc:"\u2aa7",gtcir:"\u2a7a",gt:">",GT:">",Gt:"\u226b",gtdot:"\u22d7",gtlPar:"\u2995",gtquest:"\u2a7c",gtrapprox:"\u2a86",gtrarr:"\u2978",gtrdot:"\u22d7",gtreqless:"\u22db",gtreqqless:"\u2a8c",gtrless:"\u2277",gtrsim:"\u2273",gvertneqq:"\u2269\ufe00",gvnE:"\u2269\ufe00",Hacek:"\u02c7",hairsp:"\u200a",half:"\xbd",hamilt:"\u210b",HARDcy:"\u042a",hardcy:"\u044a",harrcir:"\u2948",harr:"\u2194",hArr:"\u21d4",harrw:"\u21ad",Hat:"^",hbar:"\u210f",Hcirc:"\u0124",hcirc:"\u0125",hearts:"\u2665",heartsuit:"\u2665",hellip:"\u2026",hercon:"\u22b9",hfr:"\ud835\udd25",Hfr:"\u210c",HilbertSpace:"\u210b",hksearow:"\u2925",hkswarow:"\u2926",hoarr:"\u21ff",homtht:"\u223b",hookleftarrow:"\u21a9",hookrightarrow:"\u21aa",hopf:"\ud835\udd59",Hopf:"\u210d",horbar:"\u2015",HorizontalLine:"\u2500",hscr:"\ud835\udcbd",Hscr:"\u210b",hslash:"\u210f",Hstrok:"\u0126",hstrok:"\u0127",HumpDownHump:"\u224e",HumpEqual:"\u224f",hybull:"\u2043",hyphen:"\u2010",Iacute:"\xcd",iacute:"\xed",ic:"\u2063",Icirc:"\xce",icirc:"\xee",Icy:"\u0418",icy:"\u0438",Idot:"\u0130",IEcy:"\u0415",iecy:"\u0435",iexcl:"\xa1",iff:"\u21d4",ifr:"\ud835\udd26",Ifr:"\u2111",Igrave:"\xcc",igrave:"\xec",ii:"\u2148",iiiint:"\u2a0c",iiint:"\u222d",iinfin:"\u29dc",iiota:"\u2129",IJlig:"\u0132",ijlig:"\u0133",Imacr:"\u012a",imacr:"\u012b",image:"\u2111",ImaginaryI:"\u2148",imagline:"\u2110",imagpart:"\u2111",imath:"\u0131",Im:"\u2111",imof:"\u22b7",imped:"\u01b5",Implies:"\u21d2",incare:"\u2105",in:"\u2208",infin:"\u221e",infintie:"\u29dd",inodot:"\u0131",intcal:"\u22ba",int:"\u222b",Int:"\u222c",integers:"\u2124",Integral:"\u222b",intercal:"\u22ba",Intersection:"\u22c2",intlarhk:"\u2a17",intprod:"\u2a3c",InvisibleComma:"\u2063",InvisibleTimes:"\u2062",IOcy:"\u0401",iocy:"\u0451",Iogon:"\u012e",iogon:"\u012f",Iopf:"\ud835\udd40",iopf:"\ud835\udd5a",Iota:"\u0399",iota:"\u03b9",iprod:"\u2a3c",iquest:"\xbf",iscr:"\ud835\udcbe",Iscr:"\u2110",isin:"\u2208",isindot:"\u22f5",isinE:"\u22f9",isins:"\u22f4",isinsv:"\u22f3",isinv:"\u2208",it:"\u2062",Itilde:"\u0128",itilde:"\u0129",Iukcy:"\u0406",iukcy:"\u0456",Iuml:"\xcf",iuml:"\xef",Jcirc:"\u0134",jcirc:"\u0135",Jcy:"\u0419",jcy:"\u0439",Jfr:"\ud835\udd0d",jfr:"\ud835\udd27",jmath:"\u0237",Jopf:"\ud835\udd41",jopf:"\ud835\udd5b",Jscr:"\ud835\udca5",jscr:"\ud835\udcbf",Jsercy:"\u0408",jsercy:"\u0458",Jukcy:"\u0404",jukcy:"\u0454",Kappa:"\u039a",kappa:"\u03ba",kappav:"\u03f0",Kcedil:"\u0136",kcedil:"\u0137",Kcy:"\u041a",kcy:"\u043a",Kfr:"\ud835\udd0e",kfr:"\ud835\udd28",kgreen:"\u0138",KHcy:"\u0425",khcy:"\u0445",KJcy:"\u040c",kjcy:"\u045c",Kopf:"\ud835\udd42",kopf:"\ud835\udd5c",Kscr:"\ud835\udca6",kscr:"\ud835\udcc0",lAarr:"\u21da",Lacute:"\u0139",lacute:"\u013a",laemptyv:"\u29b4",lagran:"\u2112",Lambda:"\u039b",lambda:"\u03bb",lang:"\u27e8",Lang:"\u27ea",langd:"\u2991",langle:"\u27e8",lap:"\u2a85",Laplacetrf:"\u2112",laquo:"\xab",larrb:"\u21e4",larrbfs:"\u291f",larr:"\u2190",Larr:"\u219e",lArr:"\u21d0",larrfs:"\u291d",larrhk:"\u21a9",larrlp:"\u21ab",larrpl:"\u2939",larrsim:"\u2973",larrtl:"\u21a2",latail:"\u2919",lAtail:"\u291b",lat:"\u2aab",late:"\u2aad",lates:"\u2aad\ufe00",lbarr:"\u290c",lBarr:"\u290e",lbbrk:"\u2772",lbrace:"{",lbrack:"[",lbrke:"\u298b",lbrksld:"\u298f",lbrkslu:"\u298d",Lcaron:"\u013d",lcaron:"\u013e",Lcedil:"\u013b",lcedil:"\u013c",lceil:"\u2308",lcub:"{",Lcy:"\u041b",lcy:"\u043b",ldca:"\u2936",ldquo:"\u201c",ldquor:"\u201e",ldrdhar:"\u2967",ldrushar:"\u294b",ldsh:"\u21b2",le:"\u2264",lE:"\u2266",LeftAngleBracket:"\u27e8",LeftArrowBar:"\u21e4",leftarrow:"\u2190",LeftArrow:"\u2190",Leftarrow:"\u21d0",LeftArrowRightArrow:"\u21c6",leftarrowtail:"\u21a2",LeftCeiling:"\u2308",LeftDoubleBracket:"\u27e6",LeftDownTeeVector:"\u2961",LeftDownVectorBar:"\u2959",LeftDownVector:"\u21c3",LeftFloor:"\u230a",leftharpoondown:"\u21bd",leftharpoonup:"\u21bc",leftleftarrows:"\u21c7",leftrightarrow:"\u2194",LeftRightArrow:"\u2194",Leftrightarrow:"\u21d4",leftrightarrows:"\u21c6",leftrightharpoons:"\u21cb",leftrightsquigarrow:"\u21ad",LeftRightVector:"\u294e",LeftTeeArrow:"\u21a4",LeftTee:"\u22a3",LeftTeeVector:"\u295a",leftthreetimes:"\u22cb",LeftTriangleBar:"\u29cf",LeftTriangle:"\u22b2",LeftTriangleEqual:"\u22b4",LeftUpDownVector:"\u2951",LeftUpTeeVector:"\u2960",LeftUpVectorBar:"\u2958",LeftUpVector:"\u21bf",LeftVectorBar:"\u2952",LeftVector:"\u21bc",lEg:"\u2a8b",leg:"\u22da",leq:"\u2264",leqq:"\u2266",leqslant:"\u2a7d",lescc:"\u2aa8",les:"\u2a7d",lesdot:"\u2a7f",lesdoto:"\u2a81",lesdotor:"\u2a83",lesg:"\u22da\ufe00",lesges:"\u2a93",lessapprox:"\u2a85",lessdot:"\u22d6",lesseqgtr:"\u22da",lesseqqgtr:"\u2a8b",LessEqualGreater:"\u22da",LessFullEqual:"\u2266",LessGreater:"\u2276",lessgtr:"\u2276",LessLess:"\u2aa1",lesssim:"\u2272",LessSlantEqual:"\u2a7d",LessTilde:"\u2272",lfisht:"\u297c",lfloor:"\u230a",Lfr:"\ud835\udd0f",lfr:"\ud835\udd29",lg:"\u2276",lgE:"\u2a91",lHar:"\u2962",lhard:"\u21bd",lharu:"\u21bc",lharul:"\u296a",lhblk:"\u2584",LJcy:"\u0409",ljcy:"\u0459",llarr:"\u21c7",ll:"\u226a",Ll:"\u22d8",llcorner:"\u231e",Lleftarrow:"\u21da",llhard:"\u296b",lltri:"\u25fa",Lmidot:"\u013f",lmidot:"\u0140",lmoustache:"\u23b0",lmoust:"\u23b0",lnap:"\u2a89",lnapprox:"\u2a89",lne:"\u2a87",lnE:"\u2268",lneq:"\u2a87",lneqq:"\u2268",lnsim:"\u22e6",loang:"\u27ec",loarr:"\u21fd",lobrk:"\u27e6",longleftarrow:"\u27f5",LongLeftArrow:"\u27f5",Longleftarrow:"\u27f8",longleftrightarrow:"\u27f7",LongLeftRightArrow:"\u27f7",Longleftrightarrow:"\u27fa",longmapsto:"\u27fc",longrightarrow:"\u27f6",LongRightArrow:"\u27f6",Longrightarrow:"\u27f9",looparrowleft:"\u21ab",looparrowright:"\u21ac",lopar:"\u2985",Lopf:"\ud835\udd43",lopf:"\ud835\udd5d",loplus:"\u2a2d",lotimes:"\u2a34",lowast:"\u2217",lowbar:"_",LowerLeftArrow:"\u2199",LowerRightArrow:"\u2198",loz:"\u25ca",lozenge:"\u25ca",lozf:"\u29eb",lpar:"(",lparlt:"\u2993",lrarr:"\u21c6",lrcorner:"\u231f",lrhar:"\u21cb",lrhard:"\u296d",lrm:"\u200e",lrtri:"\u22bf",lsaquo:"\u2039",lscr:"\ud835\udcc1",Lscr:"\u2112",lsh:"\u21b0",Lsh:"\u21b0",lsim:"\u2272",lsime:"\u2a8d",lsimg:"\u2a8f",lsqb:"[",lsquo:"\u2018",lsquor:"\u201a",Lstrok:"\u0141",lstrok:"\u0142",ltcc:"\u2aa6",ltcir:"\u2a79",lt:"<",LT:"<",Lt:"\u226a",ltdot:"\u22d6",lthree:"\u22cb",ltimes:"\u22c9",ltlarr:"\u2976",ltquest:"\u2a7b",ltri:"\u25c3",ltrie:"\u22b4",ltrif:"\u25c2",ltrPar:"\u2996",lurdshar:"\u294a",luruhar:"\u2966",lvertneqq:"\u2268\ufe00",lvnE:"\u2268\ufe00",macr:"\xaf",male:"\u2642",malt:"\u2720",maltese:"\u2720",Map:"\u2905",map:"\u21a6",mapsto:"\u21a6",mapstodown:"\u21a7",mapstoleft:"\u21a4",mapstoup:"\u21a5",marker:"\u25ae",mcomma:"\u2a29",Mcy:"\u041c",mcy:"\u043c",mdash:"\u2014",mDDot:"\u223a",measuredangle:"\u2221",MediumSpace:"\u205f",Mellintrf:"\u2133",Mfr:"\ud835\udd10",mfr:"\ud835\udd2a",mho:"\u2127",micro:"\xb5",midast:"*",midcir:"\u2af0",mid:"\u2223",middot:"\xb7",minusb:"\u229f",minus:"\u2212",minusd:"\u2238",minusdu:"\u2a2a",MinusPlus:"\u2213",mlcp:"\u2adb",mldr:"\u2026",mnplus:"\u2213",models:"\u22a7",Mopf:"\ud835\udd44",mopf:"\ud835\udd5e",mp:"\u2213",mscr:"\ud835\udcc2",Mscr:"\u2133",mstpos:"\u223e",Mu:"\u039c",mu:"\u03bc",multimap:"\u22b8",mumap:"\u22b8",nabla:"\u2207",Nacute:"\u0143",nacute:"\u0144",nang:"\u2220\u20d2",nap:"\u2249",napE:"\u2a70\u0338",napid:"\u224b\u0338",napos:"\u0149",napprox:"\u2249",natural:"\u266e",naturals:"\u2115",natur:"\u266e",nbsp:"\xa0",nbump:"\u224e\u0338",nbumpe:"\u224f\u0338",ncap:"\u2a43",Ncaron:"\u0147",ncaron:"\u0148",Ncedil:"\u0145",ncedil:"\u0146",ncong:"\u2247",ncongdot:"\u2a6d\u0338",ncup:"\u2a42",Ncy:"\u041d",ncy:"\u043d",ndash:"\u2013",nearhk:"\u2924",nearr:"\u2197",neArr:"\u21d7",nearrow:"\u2197",ne:"\u2260",nedot:"\u2250\u0338",NegativeMediumSpace:"\u200b",NegativeThickSpace:"\u200b",NegativeThinSpace:"\u200b",NegativeVeryThinSpace:"\u200b",nequiv:"\u2262",nesear:"\u2928",nesim:"\u2242\u0338",NestedGreaterGreater:"\u226b",NestedLessLess:"\u226a",NewLine:"\n",nexist:"\u2204",nexists:"\u2204",Nfr:"\ud835\udd11",nfr:"\ud835\udd2b",ngE:"\u2267\u0338",nge:"\u2271",ngeq:"\u2271",ngeqq:"\u2267\u0338",ngeqslant:"\u2a7e\u0338",nges:"\u2a7e\u0338",nGg:"\u22d9\u0338",ngsim:"\u2275",nGt:"\u226b\u20d2",ngt:"\u226f",ngtr:"\u226f",nGtv:"\u226b\u0338",nharr:"\u21ae",nhArr:"\u21ce",nhpar:"\u2af2",ni:"\u220b",nis:"\u22fc",nisd:"\u22fa",niv:"\u220b",NJcy:"\u040a",njcy:"\u045a",nlarr:"\u219a",nlArr:"\u21cd",nldr:"\u2025",nlE:"\u2266\u0338",nle:"\u2270",nleftarrow:"\u219a",nLeftarrow:"\u21cd",nleftrightarrow:"\u21ae",nLeftrightarrow:"\u21ce",nleq:"\u2270",nleqq:"\u2266\u0338",nleqslant:"\u2a7d\u0338",nles:"\u2a7d\u0338",nless:"\u226e",nLl:"\u22d8\u0338",nlsim:"\u2274",nLt:"\u226a\u20d2",nlt:"\u226e",nltri:"\u22ea",nltrie:"\u22ec",nLtv:"\u226a\u0338",nmid:"\u2224",NoBreak:"\u2060",NonBreakingSpace:"\xa0",nopf:"\ud835\udd5f",Nopf:"\u2115",Not:"\u2aec",not:"\xac",NotCongruent:"\u2262",NotCupCap:"\u226d",NotDoubleVerticalBar:"\u2226",NotElement:"\u2209",NotEqual:"\u2260",NotEqualTilde:"\u2242\u0338",NotExists:"\u2204",NotGreater:"\u226f",NotGreaterEqual:"\u2271",NotGreaterFullEqual:"\u2267\u0338",NotGreaterGreater:"\u226b\u0338",NotGreaterLess:"\u2279",NotGreaterSlantEqual:"\u2a7e\u0338",NotGreaterTilde:"\u2275",NotHumpDownHump:"\u224e\u0338",NotHumpEqual:"\u224f\u0338",notin:"\u2209",notindot:"\u22f5\u0338",notinE:"\u22f9\u0338",notinva:"\u2209",notinvb:"\u22f7",notinvc:"\u22f6",NotLeftTriangleBar:"\u29cf\u0338",NotLeftTriangle:"\u22ea",NotLeftTriangleEqual:"\u22ec",NotLess:"\u226e",NotLessEqual:"\u2270",NotLessGreater:"\u2278",NotLessLess:"\u226a\u0338",NotLessSlantEqual:"\u2a7d\u0338",NotLessTilde:"\u2274",NotNestedGreaterGreater:"\u2aa2\u0338",NotNestedLessLess:"\u2aa1\u0338",notni:"\u220c",notniva:"\u220c",notnivb:"\u22fe",notnivc:"\u22fd",NotPrecedes:"\u2280",NotPrecedesEqual:"\u2aaf\u0338",NotPrecedesSlantEqual:"\u22e0",NotReverseElement:"\u220c",NotRightTriangleBar:"\u29d0\u0338",NotRightTriangle:"\u22eb",NotRightTriangleEqual:"\u22ed",NotSquareSubset:"\u228f\u0338",NotSquareSubsetEqual:"\u22e2",NotSquareSuperset:"\u2290\u0338",NotSquareSupersetEqual:"\u22e3",NotSubset:"\u2282\u20d2",NotSubsetEqual:"\u2288",NotSucceeds:"\u2281",NotSucceedsEqual:"\u2ab0\u0338",NotSucceedsSlantEqual:"\u22e1",NotSucceedsTilde:"\u227f\u0338",NotSuperset:"\u2283\u20d2",NotSupersetEqual:"\u2289",NotTilde:"\u2241",NotTildeEqual:"\u2244",NotTildeFullEqual:"\u2247",NotTildeTilde:"\u2249",NotVerticalBar:"\u2224",nparallel:"\u2226",npar:"\u2226",nparsl:"\u2afd\u20e5",npart:"\u2202\u0338",npolint:"\u2a14",npr:"\u2280",nprcue:"\u22e0",nprec:"\u2280",npreceq:"\u2aaf\u0338",npre:"\u2aaf\u0338",nrarrc:"\u2933\u0338",nrarr:"\u219b",nrArr:"\u21cf",nrarrw:"\u219d\u0338",nrightarrow:"\u219b",nRightarrow:"\u21cf",nrtri:"\u22eb",nrtrie:"\u22ed",nsc:"\u2281",nsccue:"\u22e1",nsce:"\u2ab0\u0338",Nscr:"\ud835\udca9",nscr:"\ud835\udcc3",nshortmid:"\u2224",nshortparallel:"\u2226",nsim:"\u2241",nsime:"\u2244",nsimeq:"\u2244",nsmid:"\u2224",nspar:"\u2226",nsqsube:"\u22e2",nsqsupe:"\u22e3",nsub:"\u2284",nsubE:"\u2ac5\u0338",nsube:"\u2288",nsubset:"\u2282\u20d2",nsubseteq:"\u2288",nsubseteqq:"\u2ac5\u0338",nsucc:"\u2281",nsucceq:"\u2ab0\u0338",nsup:"\u2285",nsupE:"\u2ac6\u0338",nsupe:"\u2289",nsupset:"\u2283\u20d2",nsupseteq:"\u2289",nsupseteqq:"\u2ac6\u0338",ntgl:"\u2279",Ntilde:"\xd1",ntilde:"\xf1",ntlg:"\u2278",ntriangleleft:"\u22ea",ntrianglelefteq:"\u22ec",ntriangleright:"\u22eb",ntrianglerighteq:"\u22ed",Nu:"\u039d",nu:"\u03bd",num:"#",numero:"\u2116",numsp:"\u2007",nvap:"\u224d\u20d2",nvdash:"\u22ac",nvDash:"\u22ad",nVdash:"\u22ae",nVDash:"\u22af",nvge:"\u2265\u20d2",nvgt:">\u20d2",nvHarr:"\u2904",nvinfin:"\u29de",nvlArr:"\u2902",nvle:"\u2264\u20d2",nvlt:"<\u20d2",nvltrie:"\u22b4\u20d2",nvrArr:"\u2903",nvrtrie:"\u22b5\u20d2",nvsim:"\u223c\u20d2",nwarhk:"\u2923",nwarr:"\u2196",nwArr:"\u21d6",nwarrow:"\u2196",nwnear:"\u2927",Oacute:"\xd3",oacute:"\xf3",oast:"\u229b",Ocirc:"\xd4",ocirc:"\xf4",ocir:"\u229a",Ocy:"\u041e",ocy:"\u043e",odash:"\u229d",Odblac:"\u0150",odblac:"\u0151",odiv:"\u2a38",odot:"\u2299",odsold:"\u29bc",OElig:"\u0152",oelig:"\u0153",ofcir:"\u29bf",Ofr:"\ud835\udd12",ofr:"\ud835\udd2c",ogon:"\u02db",Ograve:"\xd2",ograve:"\xf2",ogt:"\u29c1",ohbar:"\u29b5",ohm:"\u03a9",oint:"\u222e",olarr:"\u21ba",olcir:"\u29be",olcross:"\u29bb",oline:"\u203e",olt:"\u29c0",Omacr:"\u014c",omacr:"\u014d",Omega:"\u03a9",omega:"\u03c9",Omicron:"\u039f",omicron:"\u03bf",omid:"\u29b6",ominus:"\u2296",Oopf:"\ud835\udd46",oopf:"\ud835\udd60",opar:"\u29b7",OpenCurlyDoubleQuote:"\u201c",OpenCurlyQuote:"\u2018",operp:"\u29b9",oplus:"\u2295",orarr:"\u21bb",Or:"\u2a54",or:"\u2228",ord:"\u2a5d",order:"\u2134",orderof:"\u2134",ordf:"\xaa",ordm:"\xba",origof:"\u22b6",oror:"\u2a56",orslope:"\u2a57",orv:"\u2a5b",oS:"\u24c8",Oscr:"\ud835\udcaa",oscr:"\u2134",Oslash:"\xd8",oslash:"\xf8",osol:"\u2298",Otilde:"\xd5",otilde:"\xf5",otimesas:"\u2a36",Otimes:"\u2a37",otimes:"\u2297",Ouml:"\xd6",ouml:"\xf6",ovbar:"\u233d",OverBar:"\u203e",OverBrace:"\u23de",OverBracket:"\u23b4",OverParenthesis:"\u23dc",para:"\xb6",parallel:"\u2225",par:"\u2225",parsim:"\u2af3",parsl:"\u2afd",part:"\u2202",PartialD:"\u2202",Pcy:"\u041f",pcy:"\u043f",percnt:"%",period:".",permil:"\u2030",perp:"\u22a5",pertenk:"\u2031",Pfr:"\ud835\udd13",pfr:"\ud835\udd2d",Phi:"\u03a6",phi:"\u03c6",phiv:"\u03d5",phmmat:"\u2133",phone:"\u260e",Pi:"\u03a0",pi:"\u03c0",pitchfork:"\u22d4",piv:"\u03d6",planck:"\u210f",planckh:"\u210e",plankv:"\u210f",plusacir:"\u2a23",plusb:"\u229e",pluscir:"\u2a22",plus:"+",plusdo:"\u2214",plusdu:"\u2a25",pluse:"\u2a72",PlusMinus:"\xb1",plusmn:"\xb1",plussim:"\u2a26",plustwo:"\u2a27",pm:"\xb1",Poincareplane:"\u210c",pointint:"\u2a15",popf:"\ud835\udd61",Popf:"\u2119",pound:"\xa3",prap:"\u2ab7",Pr:"\u2abb",pr:"\u227a",prcue:"\u227c",precapprox:"\u2ab7",prec:"\u227a",preccurlyeq:"\u227c",Precedes:"\u227a",PrecedesEqual:"\u2aaf",PrecedesSlantEqual:"\u227c",PrecedesTilde:"\u227e",preceq:"\u2aaf",precnapprox:"\u2ab9",precneqq:"\u2ab5",precnsim:"\u22e8",pre:"\u2aaf",prE:"\u2ab3",precsim:"\u227e",prime:"\u2032",Prime:"\u2033",primes:"\u2119",prnap:"\u2ab9",prnE:"\u2ab5",prnsim:"\u22e8",prod:"\u220f",Product:"\u220f",profalar:"\u232e",profline:"\u2312",profsurf:"\u2313",prop:"\u221d",Proportional:"\u221d",Proportion:"\u2237",propto:"\u221d",prsim:"\u227e",prurel:"\u22b0",Pscr:"\ud835\udcab",pscr:"\ud835\udcc5",Psi:"\u03a8",psi:"\u03c8",puncsp:"\u2008",Qfr:"\ud835\udd14",qfr:"\ud835\udd2e",qint:"\u2a0c",qopf:"\ud835\udd62",Qopf:"\u211a",qprime:"\u2057",Qscr:"\ud835\udcac",qscr:"\ud835\udcc6",quaternions:"\u210d",quatint:"\u2a16",quest:"?",questeq:"\u225f",quot:'"',QUOT:'"',rAarr:"\u21db",race:"\u223d\u0331",Racute:"\u0154",racute:"\u0155",radic:"\u221a",raemptyv:"\u29b3",rang:"\u27e9",Rang:"\u27eb",rangd:"\u2992",range:"\u29a5",rangle:"\u27e9",raquo:"\xbb",rarrap:"\u2975",rarrb:"\u21e5",rarrbfs:"\u2920",rarrc:"\u2933",rarr:"\u2192",Rarr:"\u21a0",rArr:"\u21d2",rarrfs:"\u291e",rarrhk:"\u21aa",rarrlp:"\u21ac",rarrpl:"\u2945",rarrsim:"\u2974",Rarrtl:"\u2916",rarrtl:"\u21a3",rarrw:"\u219d",ratail:"\u291a",rAtail:"\u291c",ratio:"\u2236",rationals:"\u211a",rbarr:"\u290d",rBarr:"\u290f",RBarr:"\u2910",rbbrk:"\u2773",rbrace:"}",rbrack:"]",rbrke:"\u298c",rbrksld:"\u298e",rbrkslu:"\u2990",Rcaron:"\u0158",rcaron:"\u0159",Rcedil:"\u0156",rcedil:"\u0157",rceil:"\u2309",rcub:"}",Rcy:"\u0420",rcy:"\u0440",rdca:"\u2937",rdldhar:"\u2969",rdquo:"\u201d",rdquor:"\u201d",rdsh:"\u21b3",real:"\u211c",realine:"\u211b",realpart:"\u211c",reals:"\u211d",Re:"\u211c",rect:"\u25ad",reg:"\xae",REG:"\xae",ReverseElement:"\u220b",ReverseEquilibrium:"\u21cb",ReverseUpEquilibrium:"\u296f",rfisht:"\u297d",rfloor:"\u230b",rfr:"\ud835\udd2f",Rfr:"\u211c",rHar:"\u2964",rhard:"\u21c1",rharu:"\u21c0",rharul:"\u296c",Rho:"\u03a1",rho:"\u03c1",rhov:"\u03f1",RightAngleBracket:"\u27e9",RightArrowBar:"\u21e5",rightarrow:"\u2192",RightArrow:"\u2192",Rightarrow:"\u21d2",RightArrowLeftArrow:"\u21c4",rightarrowtail:"\u21a3",RightCeiling:"\u2309",RightDoubleBracket:"\u27e7",RightDownTeeVector:"\u295d",RightDownVectorBar:"\u2955",RightDownVector:"\u21c2",RightFloor:"\u230b",rightharpoondown:"\u21c1",rightharpoonup:"\u21c0",rightleftarrows:"\u21c4",rightleftharpoons:"\u21cc",rightrightarrows:"\u21c9",rightsquigarrow:"\u219d",RightTeeArrow:"\u21a6",RightTee:"\u22a2",RightTeeVector:"\u295b",rightthreetimes:"\u22cc",RightTriangleBar:"\u29d0",RightTriangle:"\u22b3",RightTriangleEqual:"\u22b5",RightUpDownVector:"\u294f",RightUpTeeVector:"\u295c",RightUpVectorBar:"\u2954",RightUpVector:"\u21be",RightVectorBar:"\u2953",RightVector:"\u21c0",ring:"\u02da",risingdotseq:"\u2253",rlarr:"\u21c4",rlhar:"\u21cc",rlm:"\u200f",rmoustache:"\u23b1",rmoust:"\u23b1",rnmid:"\u2aee",roang:"\u27ed",roarr:"\u21fe",robrk:"\u27e7",ropar:"\u2986",ropf:"\ud835\udd63",Ropf:"\u211d",roplus:"\u2a2e",rotimes:"\u2a35",RoundImplies:"\u2970",rpar:")",rpargt:"\u2994",rppolint:"\u2a12",rrarr:"\u21c9",Rrightarrow:"\u21db",rsaquo:"\u203a",rscr:"\ud835\udcc7",Rscr:"\u211b",rsh:"\u21b1",Rsh:"\u21b1",rsqb:"]",rsquo:"\u2019",rsquor:"\u2019",rthree:"\u22cc",rtimes:"\u22ca",rtri:"\u25b9",rtrie:"\u22b5",rtrif:"\u25b8",rtriltri:"\u29ce",RuleDelayed:"\u29f4",ruluhar:"\u2968",rx:"\u211e",Sacute:"\u015a",sacute:"\u015b",sbquo:"\u201a",scap:"\u2ab8",Scaron:"\u0160",scaron:"\u0161",Sc:"\u2abc",sc:"\u227b",sccue:"\u227d",sce:"\u2ab0",scE:"\u2ab4",Scedil:"\u015e",scedil:"\u015f",Scirc:"\u015c",scirc:"\u015d",scnap:"\u2aba",scnE:"\u2ab6",scnsim:"\u22e9",scpolint:"\u2a13",scsim:"\u227f",Scy:"\u0421",scy:"\u0441",sdotb:"\u22a1",sdot:"\u22c5",sdote:"\u2a66",searhk:"\u2925",searr:"\u2198",seArr:"\u21d8",searrow:"\u2198",sect:"\xa7",semi:";",seswar:"\u2929",setminus:"\u2216",setmn:"\u2216",sext:"\u2736",Sfr:"\ud835\udd16",sfr:"\ud835\udd30",sfrown:"\u2322",sharp:"\u266f",SHCHcy:"\u0429",shchcy:"\u0449",SHcy:"\u0428",shcy:"\u0448",ShortDownArrow:"\u2193",ShortLeftArrow:"\u2190",shortmid:"\u2223",shortparallel:"\u2225",ShortRightArrow:"\u2192",ShortUpArrow:"\u2191",shy:"\xad",Sigma:"\u03a3",sigma:"\u03c3",sigmaf:"\u03c2",sigmav:"\u03c2",sim:"\u223c",simdot:"\u2a6a",sime:"\u2243",simeq:"\u2243",simg:"\u2a9e",simgE:"\u2aa0",siml:"\u2a9d",simlE:"\u2a9f",simne:"\u2246",simplus:"\u2a24",simrarr:"\u2972",slarr:"\u2190",SmallCircle:"\u2218",smallsetminus:"\u2216",smashp:"\u2a33",smeparsl:"\u29e4",smid:"\u2223",smile:"\u2323",smt:"\u2aaa",smte:"\u2aac",smtes:"\u2aac\ufe00",SOFTcy:"\u042c",softcy:"\u044c",solbar:"\u233f",solb:"\u29c4",sol:"/",Sopf:"\ud835\udd4a",sopf:"\ud835\udd64",spades:"\u2660",spadesuit:"\u2660",spar:"\u2225",sqcap:"\u2293",sqcaps:"\u2293\ufe00",sqcup:"\u2294",sqcups:"\u2294\ufe00",Sqrt:"\u221a",sqsub:"\u228f",sqsube:"\u2291",sqsubset:"\u228f",sqsubseteq:"\u2291",sqsup:"\u2290",sqsupe:"\u2292",sqsupset:"\u2290",sqsupseteq:"\u2292",square:"\u25a1",Square:"\u25a1",SquareIntersection:"\u2293",SquareSubset:"\u228f",SquareSubsetEqual:"\u2291",SquareSuperset:"\u2290",SquareSupersetEqual:"\u2292",SquareUnion:"\u2294",squarf:"\u25aa",squ:"\u25a1",squf:"\u25aa",srarr:"\u2192",Sscr:"\ud835\udcae",sscr:"\ud835\udcc8",ssetmn:"\u2216",ssmile:"\u2323",sstarf:"\u22c6",Star:"\u22c6",star:"\u2606",starf:"\u2605",straightepsilon:"\u03f5",straightphi:"\u03d5",strns:"\xaf",sub:"\u2282",Sub:"\u22d0",subdot:"\u2abd",subE:"\u2ac5",sube:"\u2286",subedot:"\u2ac3",submult:"\u2ac1",subnE:"\u2acb",subne:"\u228a",subplus:"\u2abf",subrarr:"\u2979",subset:"\u2282",Subset:"\u22d0",subseteq:"\u2286",subseteqq:"\u2ac5",SubsetEqual:"\u2286",subsetneq:"\u228a",subsetneqq:"\u2acb",subsim:"\u2ac7",subsub:"\u2ad5",subsup:"\u2ad3",succapprox:"\u2ab8",succ:"\u227b",succcurlyeq:"\u227d",Succeeds:"\u227b",SucceedsEqual:"\u2ab0",SucceedsSlantEqual:"\u227d",SucceedsTilde:"\u227f",succeq:"\u2ab0",succnapprox:"\u2aba",succneqq:"\u2ab6",succnsim:"\u22e9",succsim:"\u227f",SuchThat:"\u220b",sum:"\u2211",Sum:"\u2211",sung:"\u266a",sup1:"\xb9",sup2:"\xb2",sup3:"\xb3",sup:"\u2283",Sup:"\u22d1",supdot:"\u2abe",supdsub:"\u2ad8",supE:"\u2ac6",supe:"\u2287",supedot:"\u2ac4",Superset:"\u2283",SupersetEqual:"\u2287",suphsol:"\u27c9",suphsub:"\u2ad7",suplarr:"\u297b",supmult:"\u2ac2",supnE:"\u2acc",supne:"\u228b",supplus:"\u2ac0",supset:"\u2283",Supset:"\u22d1",supseteq:"\u2287",supseteqq:"\u2ac6",supsetneq:"\u228b",supsetneqq:"\u2acc",supsim:"\u2ac8",supsub:"\u2ad4",supsup:"\u2ad6",swarhk:"\u2926",swarr:"\u2199",swArr:"\u21d9",swarrow:"\u2199",swnwar:"\u292a",szlig:"\xdf",Tab:"\t",target:"\u2316",Tau:"\u03a4",tau:"\u03c4",tbrk:"\u23b4",Tcaron:"\u0164",tcaron:"\u0165",Tcedil:"\u0162",tcedil:"\u0163",Tcy:"\u0422",tcy:"\u0442",tdot:"\u20db",telrec:"\u2315",Tfr:"\ud835\udd17",tfr:"\ud835\udd31",there4:"\u2234",therefore:"\u2234",Therefore:"\u2234",Theta:"\u0398",theta:"\u03b8",thetasym:"\u03d1",thetav:"\u03d1",thickapprox:"\u2248",thicksim:"\u223c",ThickSpace:"\u205f\u200a",ThinSpace:"\u2009",thinsp:"\u2009",thkap:"\u2248",thksim:"\u223c",THORN:"\xde",thorn:"\xfe",tilde:"\u02dc",Tilde:"\u223c",TildeEqual:"\u2243",TildeFullEqual:"\u2245",TildeTilde:"\u2248",timesbar:"\u2a31",timesb:"\u22a0",times:"\xd7",timesd:"\u2a30",tint:"\u222d",toea:"\u2928",topbot:"\u2336",topcir:"\u2af1",top:"\u22a4",Topf:"\ud835\udd4b",topf:"\ud835\udd65",topfork:"\u2ada",tosa:"\u2929",tprime:"\u2034",trade:"\u2122",TRADE:"\u2122",triangle:"\u25b5",triangledown:"\u25bf",triangleleft:"\u25c3",trianglelefteq:"\u22b4",triangleq:"\u225c",triangleright:"\u25b9",trianglerighteq:"\u22b5",tridot:"\u25ec",trie:"\u225c",triminus:"\u2a3a",TripleDot:"\u20db",triplus:"\u2a39",trisb:"\u29cd",tritime:"\u2a3b",trpezium:"\u23e2",Tscr:"\ud835\udcaf",tscr:"\ud835\udcc9",TScy:"\u0426",tscy:"\u0446",TSHcy:"\u040b",tshcy:"\u045b",Tstrok:"\u0166",tstrok:"\u0167",twixt:"\u226c",twoheadleftarrow:"\u219e",twoheadrightarrow:"\u21a0",Uacute:"\xda",uacute:"\xfa",uarr:"\u2191",Uarr:"\u219f",uArr:"\u21d1",Uarrocir:"\u2949",Ubrcy:"\u040e",ubrcy:"\u045e",Ubreve:"\u016c",ubreve:"\u016d",Ucirc:"\xdb",ucirc:"\xfb",Ucy:"\u0423",ucy:"\u0443",udarr:"\u21c5",Udblac:"\u0170",udblac:"\u0171",udhar:"\u296e",ufisht:"\u297e",Ufr:"\ud835\udd18",ufr:"\ud835\udd32",Ugrave:"\xd9",ugrave:"\xf9",uHar:"\u2963",uharl:"\u21bf",uharr:"\u21be",uhblk:"\u2580",ulcorn:"\u231c",ulcorner:"\u231c",ulcrop:"\u230f",ultri:"\u25f8",Umacr:"\u016a",umacr:"\u016b",uml:"\xa8",UnderBar:"_",UnderBrace:"\u23df",UnderBracket:"\u23b5",UnderParenthesis:"\u23dd",Union:"\u22c3",UnionPlus:"\u228e",Uogon:"\u0172",uogon:"\u0173",Uopf:"\ud835\udd4c",uopf:"\ud835\udd66",UpArrowBar:"\u2912",uparrow:"\u2191",UpArrow:"\u2191",Uparrow:"\u21d1",UpArrowDownArrow:"\u21c5",updownarrow:"\u2195",UpDownArrow:"\u2195",Updownarrow:"\u21d5",UpEquilibrium:"\u296e",upharpoonleft:"\u21bf",upharpoonright:"\u21be",uplus:"\u228e",UpperLeftArrow:"\u2196",UpperRightArrow:"\u2197",upsi:"\u03c5",Upsi:"\u03d2",upsih:"\u03d2",Upsilon:"\u03a5",upsilon:"\u03c5",UpTeeArrow:"\u21a5",UpTee:"\u22a5",upuparrows:"\u21c8",urcorn:"\u231d",urcorner:"\u231d",urcrop:"\u230e",Uring:"\u016e",uring:"\u016f",urtri:"\u25f9",Uscr:"\ud835\udcb0",uscr:"\ud835\udcca",utdot:"\u22f0",Utilde:"\u0168",utilde:"\u0169",utri:"\u25b5",utrif:"\u25b4",uuarr:"\u21c8",Uuml:"\xdc",uuml:"\xfc",uwangle:"\u29a7",vangrt:"\u299c",varepsilon:"\u03f5",varkappa:"\u03f0",varnothing:"\u2205",varphi:"\u03d5",varpi:"\u03d6",varpropto:"\u221d",varr:"\u2195",vArr:"\u21d5",varrho:"\u03f1",varsigma:"\u03c2",varsubsetneq:"\u228a\ufe00",varsubsetneqq:"\u2acb\ufe00",varsupsetneq:"\u228b\ufe00",varsupsetneqq:"\u2acc\ufe00",vartheta:"\u03d1",vartriangleleft:"\u22b2",vartriangleright:"\u22b3",vBar:"\u2ae8",Vbar:"\u2aeb",vBarv:"\u2ae9",Vcy:"\u0412",vcy:"\u0432",vdash:"\u22a2",vDash:"\u22a8",Vdash:"\u22a9",VDash:"\u22ab",Vdashl:"\u2ae6",veebar:"\u22bb",vee:"\u2228",Vee:"\u22c1",veeeq:"\u225a",vellip:"\u22ee",verbar:"|",Verbar:"\u2016",vert:"|",Vert:"\u2016",VerticalBar:"\u2223",VerticalLine:"|",VerticalSeparator:"\u2758",VerticalTilde:"\u2240",VeryThinSpace:"\u200a",Vfr:"\ud835\udd19",vfr:"\ud835\udd33",vltri:"\u22b2",vnsub:"\u2282\u20d2",vnsup:"\u2283\u20d2",Vopf:"\ud835\udd4d",vopf:"\ud835\udd67",vprop:"\u221d",vrtri:"\u22b3",Vscr:"\ud835\udcb1",vscr:"\ud835\udccb",vsubnE:"\u2acb\ufe00",vsubne:"\u228a\ufe00",vsupnE:"\u2acc\ufe00",vsupne:"\u228b\ufe00",Vvdash:"\u22aa",vzigzag:"\u299a",Wcirc:"\u0174",wcirc:"\u0175",wedbar:"\u2a5f",wedge:"\u2227",Wedge:"\u22c0",wedgeq:"\u2259",weierp:"\u2118",Wfr:"\ud835\udd1a",wfr:"\ud835\udd34",Wopf:"\ud835\udd4e",wopf:"\ud835\udd68",wp:"\u2118",wr:"\u2240",wreath:"\u2240",Wscr:"\ud835\udcb2",wscr:"\ud835\udccc",xcap:"\u22c2",xcirc:"\u25ef",xcup:"\u22c3",xdtri:"\u25bd",Xfr:"\ud835\udd1b",xfr:"\ud835\udd35",xharr:"\u27f7",xhArr:"\u27fa",Xi:"\u039e",xi:"\u03be",xlarr:"\u27f5",xlArr:"\u27f8",xmap:"\u27fc",xnis:"\u22fb",xodot:"\u2a00",Xopf:"\ud835\udd4f",xopf:"\ud835\udd69",xoplus:"\u2a01",xotime:"\u2a02",xrarr:"\u27f6",xrArr:"\u27f9",Xscr:"\ud835\udcb3",xscr:"\ud835\udccd",xsqcup:"\u2a06",xuplus:"\u2a04",xutri:"\u25b3",xvee:"\u22c1",xwedge:"\u22c0",Yacute:"\xdd",yacute:"\xfd",YAcy:"\u042f",yacy:"\u044f",Ycirc:"\u0176",ycirc:"\u0177",Ycy:"\u042b",ycy:"\u044b",yen:"\xa5",Yfr:"\ud835\udd1c",yfr:"\ud835\udd36",YIcy:"\u0407",yicy:"\u0457",Yopf:"\ud835\udd50",yopf:"\ud835\udd6a",Yscr:"\ud835\udcb4",yscr:"\ud835\udcce",YUcy:"\u042e",yucy:"\u044e",yuml:"\xff",Yuml:"\u0178",Zacute:"\u0179",zacute:"\u017a",Zcaron:"\u017d",zcaron:"\u017e",Zcy:"\u0417",zcy:"\u0437",Zdot:"\u017b",zdot:"\u017c",zeetrf:"\u2128",ZeroWidthSpace:"\u200b",Zeta:"\u0396",zeta:"\u03b6",zfr:"\ud835\udd37",Zfr:"\u2128",ZHcy:"\u0416",zhcy:"\u0436",zigrarr:"\u21dd",zopf:"\ud835\udd6b",Zopf:"\u2124",Zscr:"\ud835\udcb5",zscr:"\ud835\udccf",zwj:"\u200d",zwnj:"\u200c"},t=/[!-#%-\*,-\/:;\?@\[-\]_\{\}\xA1\xA7\xAB\xB6\xB7\xBB\xBF\u037E\u0387\u055A-\u055F\u0589\u058A\u05BE\u05C0\u05C3\u05C6\u05F3\u05F4\u0609\u060A\u060C\u060D\u061B\u061E\u061F\u066A-\u066D\u06D4\u0700-\u070D\u07F7-\u07F9\u0830-\u083E\u085E\u0964\u0965\u0970\u09FD\u0A76\u0AF0\u0C84\u0DF4\u0E4F\u0E5A\u0E5B\u0F04-\u0F12\u0F14\u0F3A-\u0F3D\u0F85\u0FD0-\u0FD4\u0FD9\u0FDA\u104A-\u104F\u10FB\u1360-\u1368\u1400\u166D\u166E\u169B\u169C\u16EB-\u16ED\u1735\u1736\u17D4-\u17D6\u17D8-\u17DA\u1800-\u180A\u1944\u1945\u1A1E\u1A1F\u1AA0-\u1AA6\u1AA8-\u1AAD\u1B5A-\u1B60\u1BFC-\u1BFF\u1C3B-\u1C3F\u1C7E\u1C7F\u1CC0-\u1CC7\u1CD3\u2010-\u2027\u2030-\u2043\u2045-\u2051\u2053-\u205E\u207D\u207E\u208D\u208E\u2308-\u230B\u2329\u232A\u2768-\u2775\u27C5\u27C6\u27E6-\u27EF\u2983-\u2998\u29D8-\u29DB\u29FC\u29FD\u2CF9-\u2CFC\u2CFE\u2CFF\u2D70\u2E00-\u2E2E\u2E30-\u2E4E\u3001-\u3003\u3008-\u3011\u3014-\u301F\u3030\u303D\u30A0\u30FB\uA4FE\uA4FF\uA60D-\uA60F\uA673\uA67E\uA6F2-\uA6F7\uA874-\uA877\uA8CE\uA8CF\uA8F8-\uA8FA\uA8FC\uA92E\uA92F\uA95F\uA9C1-\uA9CD\uA9DE\uA9DF\uAA5C-\uAA5F\uAADE\uAADF\uAAF0\uAAF1\uABEB\uFD3E\uFD3F\uFE10-\uFE19\uFE30-\uFE52\uFE54-\uFE61\uFE63\uFE68\uFE6A\uFE6B\uFF01-\uFF03\uFF05-\uFF0A\uFF0C-\uFF0F\uFF1A\uFF1B\uFF1F\uFF20\uFF3B-\uFF3D\uFF3F\uFF5B\uFF5D\uFF5F-\uFF65]|\uD800[\uDD00-\uDD02\uDF9F\uDFD0]|\uD801\uDD6F|\uD802[\uDC57\uDD1F\uDD3F\uDE50-\uDE58\uDE7F\uDEF0-\uDEF6\uDF39-\uDF3F\uDF99-\uDF9C]|\uD803[\uDF55-\uDF59]|\uD804[\uDC47-\uDC4D\uDCBB\uDCBC\uDCBE-\uDCC1\uDD40-\uDD43\uDD74\uDD75\uDDC5-\uDDC8\uDDCD\uDDDB\uDDDD-\uDDDF\uDE38-\uDE3D\uDEA9]|\uD805[\uDC4B-\uDC4F\uDC5B\uDC5D\uDCC6\uDDC1-\uDDD7\uDE41-\uDE43\uDE60-\uDE6C\uDF3C-\uDF3E]|\uD806[\uDC3B\uDE3F-\uDE46\uDE9A-\uDE9C\uDE9E-\uDEA2]|\uD807[\uDC41-\uDC45\uDC70\uDC71\uDEF7\uDEF8]|\uD809[\uDC70-\uDC74]|\uD81A[\uDE6E\uDE6F\uDEF5\uDF37-\uDF3B\uDF44]|\uD81B[\uDE97-\uDE9A]|\uD82F\uDC9F|\uD836[\uDE87-\uDE8B]|\uD83A[\uDD5E\uDD5F]/,n={};function 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s,o,i,a,c,l,u,p,h,f,d,m,g,_,k,b,v,C,y,A,x=e.lineMax,D=e.bMarks[r]+e.tShift[r],w=e.eMarks[r];if(e.sCount[r]-e.blkIndent>=4)return!1;if(62!==e.src.charCodeAt(D++))return!1;if(n)return!0;for(a=h=e.sCount[r]+1,32===e.src.charCodeAt(D)?(D++,a++,h++,s=!1,b=!0):9===e.src.charCodeAt(D)?(b=!0,(e.bsCount[r]+h)%4==3?(D++,a++,h++,s=!1):s=!0):b=!1,f=[e.bMarks[r]],e.bMarks[r]=D;D<w&&(o=e.src.charCodeAt(D),de(o));)9===o?h+=4-(h+e.bsCount[r]+(s?1:0))%4:h++,D++;for(d=[e.bsCount[r]],e.bsCount[r]=e.sCount[r]+1+(b?1:0),l=D>=w,_=[e.sCount[r]],e.sCount[r]=h-a,k=[e.tShift[r]],e.tShift[r]=D-e.bMarks[r],C=e.md.block.ruler.getRules("blockquote"),g=e.parentType,e.parentType="blockquote",p=r+1;p<t&&(A=e.sCount[p]<e.blkIndent,!((D=e.bMarks[p]+e.tShift[p])>=(w=e.eMarks[p])));p++)if(62!==e.src.charCodeAt(D++)||A){if(l)break;for(v=!1,i=0,c=C.length;i<c;i++)if(C[i](e,p,t,!0)){v=!0;break}if(v){e.lineMax=p,0!==e.blkIndent&&(f.push(e.bMarks[p]),d.push(e.bsCount[p]),k.push(e.tShift[p]),_.push(e.sCount[p]),e.sCount[p]-=e.blkIndent);break}f.push(e.bMarks[p]),d.push(e.bsCount[p]),k.push(e.tShift[p]),_.push(e.sCount[p]),e.sCount[p]=-1}else{for(a=h=e.sCount[p]+1,32===e.src.charCodeAt(D)?(D++,a++,h++,s=!1,b=!0):9===e.src.charCodeAt(D)?(b=!0,(e.bsCount[p]+h)%4==3?(D++,a++,h++,s=!1):s=!0):b=!1,f.push(e.bMarks[p]),e.bMarks[p]=D;D<w&&(o=e.src.charCodeAt(D),de(o));)9===o?h+=4-(h+e.bsCount[p]+(s?1:0))%4:h++,D++;l=D>=w,d.push(e.bsCount[p]),e.bsCount[p]=e.sCount[p]+1+(b?1:0),_.push(e.sCount[p]),e.sCount[p]=h-a,k.push(e.tShift[p]),e.tShift[p]=D-e.bMarks[p]}for(m=e.blkIndent,e.blkIndent=0,(y=e.push("blockquote_open","blockquote",1)).markup=">",y.map=u=[r,0],e.md.block.tokenize(e,r,p),(y=e.push("blockquote_close","blockquote",-1)).markup=">",e.lineMax=x,e.parentType=g,u[1]=e.line,i=0;i<k.length;i++)e.bMarks[i+r]=f[i],e.tShift[i+r]=k[i],e.sCount[i+r]=_[i],e.bsCount[i+r]=d[i];return e.blkIndent=m,!0},["paragraph","reference","blockquote","list"]],["hr",function(e,r,t,n){var s,o,i,a,c=e.bMarks[r]+e.tShift[r],l=e.eMarks[r];if(e.sCount[r]-e.blkIndent>=4)return!1;if(42!==(s=e.src.charCodeAt(c++))&&45!==s&&95!==s)return!1;for(o=1;c<l;){if((i=e.src.charCodeAt(c++))!==s&&!me(i))return!1;i===s&&o++}return!(o<3)&&(n||(e.line=r+1,(a=e.push("hr","hr",0)).map=[r,e.line],a.markup=Array(o+1).join(String.fromCharCode(s))),!0)},["paragraph","reference","blockquote","list"]],["list",function(e,r,t,n){var s,o,i,a,c,l,u,p,h,f,d,m,g,_,k,b,v,C,y,A,x,D,w,E,q,S,F,L,z=!1,T=!0;if(e.sCount[r]-e.blkIndent>=4)return!1;if(e.listIndent>=0&&e.sCount[r]-e.listIndent>=4&&e.sCount[r]<e.blkIndent)return!1;if(n&&"paragraph"===e.parentType&&e.sCount[r]>=e.blkIndent&&(z=!0),(w=ke(e,r))>=0){if(u=!0,q=e.bMarks[r]+e.tShift[r],g=Number(e.src.slice(q,w-1)),z&&1!==g)return!1}else{if(!((w=_e(e,r))>=0))return!1;u=!1}if(z&&e.skipSpaces(w)>=e.eMarks[r])return!1;if(m=e.src.charCodeAt(w-1),n)return!0;for(d=e.tokens.length,u?(L=e.push("ordered_list_open","ol",1),1!==g&&(L.attrs=[["start",g]])):L=e.push("bullet_list_open","ul",1),L.map=f=[r,0],L.markup=String.fromCharCode(m),k=r,E=!1,F=e.md.block.ruler.getRules("list"),C=e.parentType,e.parentType="list";k<t;){for(D=w,_=e.eMarks[k],l=b=e.sCount[k]+w-(e.bMarks[r]+e.tShift[r]);D<_;){if(9===(s=e.src.charCodeAt(D)))b+=4-(b+e.bsCount[k])%4;else{if(32!==s)break;b++}D++}if((c=(o=D)>=_?1:b-l)>4&&(c=1),a=l+c,(L=e.push("list_item_open","li",1)).markup=String.fromCharCode(m),L.map=p=[r,0],u&&(L.info=e.src.slice(q,w-1)),x=e.tight,A=e.tShift[r],y=e.sCount[r],v=e.listIndent,e.listIndent=e.blkIndent,e.blkIndent=a,e.tight=!0,e.tShift[r]=o-e.bMarks[r],e.sCount[r]=b,o>=_&&e.isEmpty(r+1)?e.line=Math.min(e.line+2,t):e.md.block.tokenize(e,r,t,!0),e.tight&&!E||(T=!1),E=e.line-r>1&&e.isEmpty(e.line-1),e.blkIndent=e.listIndent,e.listIndent=v,e.tShift[r]=A,e.sCount[r]=y,e.tight=x,(L=e.push("list_item_close","li",-1)).markup=String.fromCharCode(m),k=r=e.line,p[1]=k,o=e.bMarks[r],k>=t)break;if(e.sCount[k]<e.blkIndent)break;if(e.sCount[r]-e.blkIndent>=4)break;for(S=!1,i=0,h=F.length;i<h;i++)if(F[i](e,k,t,!0)){S=!0;break}if(S)break;if(u){if((w=ke(e,k))<0)break;q=e.bMarks[k]+e.tShift[k]}else if((w=_e(e,k))<0)break;if(m!==e.src.charCodeAt(w-1))break}return(L=u?e.push("ordered_list_close","ol",-1):e.push("bullet_list_close","ul",-1)).markup=String.fromCharCode(m),f[1]=k,e.line=k,e.parentType=C,T&&function(e,r){var t,n,s=e.level+2;for(t=r+2,n=e.tokens.length-2;t<n;t++)e.tokens[t].level===s&&"paragraph_open"===e.tokens[t].type&&(e.tokens[t+2].hidden=!0,e.tokens[t].hidden=!0,t+=2)}(e,d),!0},["paragraph","reference","blockquote"]],["reference",function(e,r,t,n){var s,o,i,a,c,l,u,p,h,f,d,m,g,_,k,b,v=0,C=e.bMarks[r]+e.tShift[r],y=e.eMarks[r],A=r+1;if(e.sCount[r]-e.blkIndent>=4)return!1;if(91!==e.src.charCodeAt(C))return!1;for(;++C<y;)if(93===e.src.charCodeAt(C)&&92!==e.src.charCodeAt(C-1)){if(C+1===y)return!1;if(58!==e.src.charCodeAt(C+1))return!1;break}for(a=e.lineMax,k=e.md.block.ruler.getRules("reference"),f=e.parentType,e.parentType="reference";A<a&&!e.isEmpty(A);A++)if(!(e.sCount[A]-e.blkIndent>3||e.sCount[A]<0)){for(_=!1,l=0,u=k.length;l<u;l++)if(k[l](e,A,a,!0)){_=!0;break}if(_)break}for(y=(g=e.getLines(r,A,e.blkIndent,!1).trim()).length,C=1;C<y;C++){if(91===(s=g.charCodeAt(C)))return!1;if(93===s){h=C;break}(10===s||92===s&&++C<y&&10===g.charCodeAt(C))&&v++}if(h<0||58!==g.charCodeAt(h+1))return!1;for(C=h+2;C<y;C++)if(10===(s=g.charCodeAt(C)))v++;else if(!ve(s))break;if(!(d=e.md.helpers.parseLinkDestination(g,C,y)).ok)return!1;if(c=e.md.normalizeLink(d.str),!e.md.validateLink(c))return!1;for(o=C=d.pos,i=v+=d.lines,m=C;C<y;C++)if(10===(s=g.charCodeAt(C)))v++;else if(!ve(s))break;for(d=e.md.helpers.parseLinkTitle(g,C,y),C<y&&m!==C&&d.ok?(b=d.str,C=d.pos,v+=d.lines):(b="",C=o,v=i);C<y&&(s=g.charCodeAt(C),ve(s));)C++;if(C<y&&10!==g.charCodeAt(C)&&b)for(b="",C=o,v=i;C<y&&(s=g.charCodeAt(C),ve(s));)C++;return!(C<y&&10!==g.charCodeAt(C))&&(!!(p=be(g.slice(1,h)))&&(n||(void 0===e.env.references&&(e.env.references={}),void 0===e.env.references[p]&&(e.env.references[p]={title:b,href:c}),e.parentType=f,e.line=r+v+1),!0))}],["html_block",function(e,r,t,n){var s,o,i,a,c=e.bMarks[r]+e.tShift[r],l=e.eMarks[r];if(e.sCount[r]-e.blkIndent>=4)return!1;if(!e.md.options.html)return!1;if(60!==e.src.charCodeAt(c))return!1;for(a=e.src.slice(c,l),s=0;s<De.length&&!De[s][0].test(a);s++);if(s===De.length)return!1;if(n)return De[s][2];if(o=r+1,!De[s][1].test(a))for(;o<t&&!(e.sCount[o]<e.blkIndent);o++)if(c=e.bMarks[o]+e.tShift[o],l=e.eMarks[o],a=e.src.slice(c,l),De[s][1].test(a)){0!==a.length&&o++;break}return e.line=o,(i=e.push("html_block","",0)).map=[r,o],i.content=e.getLines(r,o,e.blkIndent,!0),!0},["paragraph","reference","blockquote"]],["heading",function(e,r,t,n){var s,o,i,a,c=e.bMarks[r]+e.tShift[r],l=e.eMarks[r];if(e.sCount[r]-e.blkIndent>=4)return!1;if(35!==(s=e.src.charCodeAt(c))||c>=l)return!1;for(o=1,s=e.src.charCodeAt(++c);35===s&&c<l&&o<=6;)o++,s=e.src.charCodeAt(++c);return!(o>6||c<l&&!we(s))&&(n||(l=e.skipSpacesBack(l,c),(i=e.skipCharsBack(l,35,c))>c&&we(e.src.charCodeAt(i-1))&&(l=i),e.line=r+1,(a=e.push("heading_open","h"+String(o),1)).markup="########".slice(0,o),a.map=[r,e.line],(a=e.push("inline","",0)).content=e.src.slice(c,l).trim(),a.map=[r,e.line],a.children=[],(a=e.push("heading_close","h"+String(o),-1)).markup="########".slice(0,o)),!0)},["paragraph","reference","blockquote"]],["lheading",function(e,r,t){var n,s,o,i,a,c,l,u,p,h,f=r+1,d=e.md.block.ruler.getRules("paragraph");if(e.sCount[r]-e.blkIndent>=4)return!1;for(h=e.parentType,e.parentType="paragraph";f<t&&!e.isEmpty(f);f++)if(!(e.sCount[f]-e.blkIndent>3)){if(e.sCount[f]>=e.blkIndent&&(c=e.bMarks[f]+e.tShift[f])<(l=e.eMarks[f])&&(45===(p=e.src.charCodeAt(c))||61===p)&&(c=e.skipChars(c,p),(c=e.skipSpaces(c))>=l)){u=61===p?1:2;break}if(!(e.sCount[f]<0)){for(s=!1,o=0,i=d.length;o<i;o++)if(d[o](e,f,t,!0)){s=!0;break}if(s)break}}return!!u&&(n=e.getLines(r,f,e.blkIndent,!1).trim(),e.line=f+1,(a=e.push("heading_open","h"+String(u),1)).markup=String.fromCharCode(p),a.map=[r,e.line],(a=e.push("inline","",0)).content=n,a.map=[r,e.line-1],a.children=[],(a=e.push("heading_close","h"+String(u),-1)).markup=String.fromCharCode(p),e.parentType=h,!0)}],["paragraph",function(e,r){var t,n,s,o,i,a,c=r+1,l=e.md.block.ruler.getRules("paragraph"),u=e.lineMax;for(a=e.parentType,e.parentType="paragraph";c<u&&!e.isEmpty(c);c++)if(!(e.sCount[c]-e.blkIndent>3||e.sCount[c]<0)){for(n=!1,s=0,o=l.length;s<o;s++)if(l[s](e,c,u,!0)){n=!0;break}if(n)break}return t=e.getLines(r,c,e.blkIndent,!1).trim(),e.line=c,(i=e.push("paragraph_open","p",1)).map=[r,e.line],(i=e.push("inline","",0)).content=t,i.map=[r,e.line],i.children=[],i=e.push("paragraph_close","p",-1),e.parentType=a,!0}]];function Le(){this.ruler=new O;for(var e=0;e<Fe.length;e++)this.ruler.push(Fe[e][0],Fe[e][1],{alt:(Fe[e][2]||[]).slice()})}Le.prototype.tokenize=function(e,r,t){for(var n,s=this.ruler.getRules(""),o=s.length,i=r,a=!1,c=e.md.options.maxNesting;i<t&&(e.line=i=e.skipEmptyLines(i),!(i>=t))&&!(e.sCount[i]<e.blkIndent);){if(e.level>=c){e.line=t;break}for(n=0;n<o&&!s[n](e,i,t,!1);n++);e.tight=!a,e.isEmpty(e.line-1)&&(a=!0),(i=e.line)<t&&e.isEmpty(i)&&(a=!0,i++,e.line=i)}},Le.prototype.parse=function(e,r,t,n){var s;e&&(s=new this.State(e,r,t,n),this.tokenize(s,s.line,s.lineMax))},Le.prototype.State=Se;var ze=Le;function Te(e){switch(e){case 10:case 33:case 35:case 36:case 37:case 38:case 42:case 43:case 45:case 58:case 60:case 61:case 62:case 64:case 91:case 92:case 93:case 94:case 95:case 96:case 123:case 125:case 126:return!0;default:return!1}}for(var Ie=/(?:^|[^a-z0-9.+-])([a-z][a-z0-9.+-]*)$/i,Me=w.isSpace,Re=w.isSpace,Be=[],Ne=0;Ne<256;Ne++)Be.push(0);"\\!\"#$%&'()*+,./:;<=>?@[]^_`{|}~-".split("").forEach((function(e){Be[e.charCodeAt(0)]=1}));function Oe(e,r){var t,n,s,o,i,a=[],c=r.length;for(t=0;t<c;t++)126===(s=r[t]).marker&&-1!==s.end&&(o=r[s.end],(i=e.tokens[s.token]).type="s_open",i.tag="s",i.nesting=1,i.markup="~~",i.content="",(i=e.tokens[o.token]).type="s_close",i.tag="s",i.nesting=-1,i.markup="~~",i.content="","text"===e.tokens[o.token-1].type&&"~"===e.tokens[o.token-1].content&&a.push(o.token-1));for(;a.length;){for(n=(t=a.pop())+1;n<e.tokens.length&&"s_close"===e.tokens[n].type;)n++;t!==--n&&(i=e.tokens[n],e.tokens[n]=e.tokens[t],e.tokens[t]=i)}}var Pe={tokenize:function(e,r){var t,n,s,o,i=e.pos,a=e.src.charCodeAt(i);if(r)return!1;if(126!==a)return!1;if(s=(n=e.scanDelims(e.pos,!0)).length,o=String.fromCharCode(a),s<2)return!1;for(s%2&&(e.push("text","",0).content=o,s--),t=0;t<s;t+=2)e.push("text","",0).content=o+o,e.delimiters.push({marker:a,length:0,token:e.tokens.length-1,end:-1,open:n.can_open,close:n.can_close});return e.pos+=n.length,!0},postProcess:function(e){var r,t=e.tokens_meta,n=e.tokens_meta.length;for(Oe(e,e.delimiters),r=0;r<n;r++)t[r]&&t[r].delimiters&&Oe(e,t[r].delimiters)}};function je(e,r){var t,n,s,o,i,a;for(t=r.length-1;t>=0;t--)95!==(n=r[t]).marker&&42!==n.marker||-1!==n.end&&(s=r[n.end],a=t>0&&r[t-1].end===n.end+1&&r[t-1].marker===n.marker&&r[t-1].token===n.token-1&&r[n.end+1].token===s.token+1,i=String.fromCharCode(n.marker),(o=e.tokens[n.token]).type=a?"strong_open":"em_open",o.tag=a?"strong":"em",o.nesting=1,o.markup=a?i+i:i,o.content="",(o=e.tokens[s.token]).type=a?"strong_close":"em_close",o.tag=a?"strong":"em",o.nesting=-1,o.markup=a?i+i:i,o.content="",a&&(e.tokens[r[t-1].token].content="",e.tokens[r[n.end+1].token].content="",t--))}var Ue={tokenize:function(e,r){var t,n,s=e.pos,o=e.src.charCodeAt(s);if(r)return!1;if(95!==o&&42!==o)return!1;for(n=e.scanDelims(e.pos,42===o),t=0;t<n.length;t++)e.push("text","",0).content=String.fromCharCode(o),e.delimiters.push({marker:o,length:n.length,token:e.tokens.length-1,end:-1,open:n.can_open,close:n.can_close});return e.pos+=n.length,!0},postProcess:function(e){var r,t=e.tokens_meta,n=e.tokens_meta.length;for(je(e,e.delimiters),r=0;r<n;r++)t[r]&&t[r].delimiters&&je(e,t[r].delimiters)}},Ve=w.normalizeReference,Ze=w.isSpace,$e=w.normalizeReference,Ge=w.isSpace,He=/^([a-zA-Z0-9.!#$%&'*+\/=?^_`{|}~-]+@[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)*)$/,Je=/^([a-zA-Z][a-zA-Z0-9+.\-]{1,31}):([^<>\x00-\x20]*)$/,We=Ae.HTML_TAG_RE;var Ye=w.has,Ke=w.isValidEntityCode,Qe=w.fromCodePoint,Xe=/^&#((?:x[a-f0-9]{1,6}|[0-9]{1,7}));/i,er=/^&([a-z][a-z0-9]{1,31});/i;function rr(e,r){var t,n,s,o,i,a,c,l,u={},p=r.length;if(p){var h=0,f=-2,d=[];for(t=0;t<p;t++)if(s=r[t],d.push(0),r[h].marker===s.marker&&f===s.token-1||(h=t),f=s.token,s.length=s.length||0,s.close){for(u.hasOwnProperty(s.marker)||(u[s.marker]=[-1,-1,-1,-1,-1,-1]),i=u[s.marker][(s.open?3:0)+s.length%3],a=n=h-d[h]-1;n>i;n-=d[n]+1)if((o=r[n]).marker===s.marker&&o.open&&o.end<0&&(c=!1,(o.close||s.open)&&(o.length+s.length)%3==0&&(o.length%3==0&&s.length%3==0||(c=!0)),!c)){l=n>0&&!r[n-1].open?d[n-1]+1:0,d[t]=t-n+l,d[n]=l,s.open=!1,o.end=t,o.close=!1,a=-1,f=-2;break}-1!==a&&(u[s.marker][(s.open?3:0)+(s.length||0)%3]=a)}}}var tr=w.isWhiteSpace,nr=w.isPunctChar,sr=w.isMdAsciiPunct;function or(e,r,t,n){this.src=e,this.env=t,this.md=r,this.tokens=n,this.tokens_meta=Array(n.length),this.pos=0,this.posMax=this.src.length,this.level=0,this.pending="",this.pendingLevel=0,this.cache={},this.delimiters=[],this._prev_delimiters=[],this.backticks={},this.backticksScanned=!1,this.linkLevel=0}or.prototype.pushPending=function(){var e=new oe("text","",0);return e.content=this.pending,e.level=this.pendingLevel,this.tokens.push(e),this.pending="",e},or.prototype.push=function(e,r,t){this.pending&&this.pushPending();var n=new oe(e,r,t),s=null;return t<0&&(this.level--,this.delimiters=this._prev_delimiters.pop()),n.level=this.level,t>0&&(this.level++,this._prev_delimiters.push(this.delimiters),this.delimiters=[],s={delimiters:this.delimiters}),this.pendingLevel=this.level,this.tokens.push(n),this.tokens_meta.push(s),n},or.prototype.scanDelims=function(e,r){var t,n,s,o,i,a,c,l,u,p=e,h=!0,f=!0,d=this.posMax,m=this.src.charCodeAt(e);for(t=e>0?this.src.charCodeAt(e-1):32;p<d&&this.src.charCodeAt(p)===m;)p++;return s=p-e,n=p<d?this.src.charCodeAt(p):32,c=sr(t)||nr(String.fromCharCode(t)),u=sr(n)||nr(String.fromCharCode(n)),a=tr(t),(l=tr(n))?h=!1:u&&(a||c||(h=!1)),a?f=!1:c&&(l||u||(f=!1)),r?(o=h,i=f):(o=h&&(!f||c),i=f&&(!h||u)),{can_open:o,can_close:i,length:s}},or.prototype.Token=oe;var ir=or,ar=[["text",function(e,r){for(var t=e.pos;t<e.posMax&&!Te(e.src.charCodeAt(t));)t++;return t!==e.pos&&(r||(e.pending+=e.src.slice(e.pos,t)),e.pos=t,!0)}],["linkify",function(e,r){var t,n,s,o,i,a,c;return!!e.md.options.linkify&&(!(e.linkLevel>0)&&(!((t=e.pos)+3>e.posMax)&&(58===e.src.charCodeAt(t)&&(47===e.src.charCodeAt(t+1)&&(47===e.src.charCodeAt(t+2)&&(!!(n=e.pending.match(Ie))&&(s=n[1],!!(o=e.md.linkify.matchAtStart(e.src.slice(t-s.length)))&&(i=(i=o.url).replace(/\*+$/,""),a=e.md.normalizeLink(i),!!e.md.validateLink(a)&&(r||(e.pending=e.pending.slice(0,-s.length),(c=e.push("link_open","a",1)).attrs=[["href",a]],c.markup="linkify",c.info="auto",(c=e.push("text","",0)).content=e.md.normalizeLinkText(i),(c=e.push("link_close","a",-1)).markup="linkify",c.info="auto"),e.pos+=i.length-s.length,!0)))))))))}],["newline",function(e,r){var t,n,s,o=e.pos;if(10!==e.src.charCodeAt(o))return!1;if(t=e.pending.length-1,n=e.posMax,!r)if(t>=0&&32===e.pending.charCodeAt(t))if(t>=1&&32===e.pending.charCodeAt(t-1)){for(s=t-1;s>=1&&32===e.pending.charCodeAt(s-1);)s--;e.pending=e.pending.slice(0,s),e.push("hardbreak","br",0)}else e.pending=e.pending.slice(0,-1),e.push("softbreak","br",0);else e.push("softbreak","br",0);for(o++;o<n&&Me(e.src.charCodeAt(o));)o++;return e.pos=o,!0}],["escape",function(e,r){var t,n,s,o,i,a=e.pos,c=e.posMax;if(92!==e.src.charCodeAt(a))return!1;if(++a>=c)return!1;if(10===(t=e.src.charCodeAt(a))){for(r||e.push("hardbreak","br",0),a++;a<c&&(t=e.src.charCodeAt(a),Re(t));)a++;return e.pos=a,!0}return o=e.src[a],t>=55296&&t<=56319&&a+1<c&&(n=e.src.charCodeAt(a+1))>=56320&&n<=57343&&(o+=e.src[a+1],a++),s="\\"+o,r||(i=e.push("text_special","",0),t<256&&0!==Be[t]?i.content=o:i.content=s,i.markup=s,i.info="escape"),e.pos=a+1,!0}],["backticks",function(e,r){var t,n,s,o,i,a,c,l,u=e.pos;if(96!==e.src.charCodeAt(u))return!1;for(t=u,u++,n=e.posMax;u<n&&96===e.src.charCodeAt(u);)u++;if(c=(s=e.src.slice(t,u)).length,e.backticksScanned&&(e.backticks[c]||0)<=t)return r||(e.pending+=s),e.pos+=c,!0;for(i=a=u;-1!==(i=e.src.indexOf("`",a));){for(a=i+1;a<n&&96===e.src.charCodeAt(a);)a++;if((l=a-i)===c)return r||((o=e.push("code_inline","code",0)).markup=s,o.content=e.src.slice(u,i).replace(/\n/g," ").replace(/^ (.+) $/,"$1")),e.pos=a,!0;e.backticks[l]=i}return e.backticksScanned=!0,r||(e.pending+=s),e.pos+=c,!0}],["strikethrough",Pe.tokenize],["emphasis",Ue.tokenize],["link",function(e,r){var t,n,s,o,i,a,c,l,u="",p="",h=e.pos,f=e.posMax,d=e.pos,m=!0;if(91!==e.src.charCodeAt(e.pos))return!1;if(i=e.pos+1,(o=e.md.helpers.parseLinkLabel(e,e.pos,!0))<0)return!1;if((a=o+1)<f&&40===e.src.charCodeAt(a)){for(m=!1,a++;a<f&&(n=e.src.charCodeAt(a),Ze(n)||10===n);a++);if(a>=f)return!1;if(d=a,(c=e.md.helpers.parseLinkDestination(e.src,a,e.posMax)).ok){for(u=e.md.normalizeLink(c.str),e.md.validateLink(u)?a=c.pos:u="",d=a;a<f&&(n=e.src.charCodeAt(a),Ze(n)||10===n);a++);if(c=e.md.helpers.parseLinkTitle(e.src,a,e.posMax),a<f&&d!==a&&c.ok)for(p=c.str,a=c.pos;a<f&&(n=e.src.charCodeAt(a),Ze(n)||10===n);a++);}(a>=f||41!==e.src.charCodeAt(a))&&(m=!0),a++}if(m){if(void 0===e.env.references)return!1;if(a<f&&91===e.src.charCodeAt(a)?(d=a+1,(a=e.md.helpers.parseLinkLabel(e,a))>=0?s=e.src.slice(d,a++):a=o+1):a=o+1,s||(s=e.src.slice(i,o)),!(l=e.env.references[Ve(s)]))return e.pos=h,!1;u=l.href,p=l.title}return r||(e.pos=i,e.posMax=o,e.push("link_open","a",1).attrs=t=[["href",u]],p&&t.push(["title",p]),e.linkLevel++,e.md.inline.tokenize(e),e.linkLevel--,e.push("link_close","a",-1)),e.pos=a,e.posMax=f,!0}],["image",function(e,r){var t,n,s,o,i,a,c,l,u,p,h,f,d,m="",g=e.pos,_=e.posMax;if(33!==e.src.charCodeAt(e.pos))return!1;if(91!==e.src.charCodeAt(e.pos+1))return!1;if(a=e.pos+2,(i=e.md.helpers.parseLinkLabel(e,e.pos+1,!1))<0)return!1;if((c=i+1)<_&&40===e.src.charCodeAt(c)){for(c++;c<_&&(n=e.src.charCodeAt(c),Ge(n)||10===n);c++);if(c>=_)return!1;for(d=c,(u=e.md.helpers.parseLinkDestination(e.src,c,e.posMax)).ok&&(m=e.md.normalizeLink(u.str),e.md.validateLink(m)?c=u.pos:m=""),d=c;c<_&&(n=e.src.charCodeAt(c),Ge(n)||10===n);c++);if(u=e.md.helpers.parseLinkTitle(e.src,c,e.posMax),c<_&&d!==c&&u.ok)for(p=u.str,c=u.pos;c<_&&(n=e.src.charCodeAt(c),Ge(n)||10===n);c++);else p="";if(c>=_||41!==e.src.charCodeAt(c))return e.pos=g,!1;c++}else{if(void 0===e.env.references)return!1;if(c<_&&91===e.src.charCodeAt(c)?(d=c+1,(c=e.md.helpers.parseLinkLabel(e,c))>=0?o=e.src.slice(d,c++):c=i+1):c=i+1,o||(o=e.src.slice(a,i)),!(l=e.env.references[$e(o)]))return e.pos=g,!1;m=l.href,p=l.title}return r||(s=e.src.slice(a,i),e.md.inline.parse(s,e.md,e.env,f=[]),(h=e.push("image","img",0)).attrs=t=[["src",m],["alt",""]],h.children=f,h.content=s,p&&t.push(["title",p])),e.pos=c,e.posMax=_,!0}],["autolink",function(e,r){var t,n,s,o,i,a,c=e.pos;if(60!==e.src.charCodeAt(c))return!1;for(i=e.pos,a=e.posMax;;){if(++c>=a)return!1;if(60===(o=e.src.charCodeAt(c)))return!1;if(62===o)break}return t=e.src.slice(i+1,c),Je.test(t)?(n=e.md.normalizeLink(t),!!e.md.validateLink(n)&&(r||((s=e.push("link_open","a",1)).attrs=[["href",n]],s.markup="autolink",s.info="auto",(s=e.push("text","",0)).content=e.md.normalizeLinkText(t),(s=e.push("link_close","a",-1)).markup="autolink",s.info="auto"),e.pos+=t.length+2,!0)):!!He.test(t)&&(n=e.md.normalizeLink("mailto:"+t),!!e.md.validateLink(n)&&(r||((s=e.push("link_open","a",1)).attrs=[["href",n]],s.markup="autolink",s.info="auto",(s=e.push("text","",0)).content=e.md.normalizeLinkText(t),(s=e.push("link_close","a",-1)).markup="autolink",s.info="auto"),e.pos+=t.length+2,!0))}],["html_inline",function(e,r){var t,n,s,o,i,a=e.pos;return!!e.md.options.html&&(s=e.posMax,!(60!==e.src.charCodeAt(a)||a+2>=s)&&(!(33!==(t=e.src.charCodeAt(a+1))&&63!==t&&47!==t&&!function(e){var r=32|e;return r>=97&&r<=122}(t))&&(!!(n=e.src.slice(a).match(We))&&(r||((o=e.push("html_inline","",0)).content=e.src.slice(a,a+n[0].length),i=o.content,/^<a[>\s]/i.test(i)&&e.linkLevel++,function(e){return/^<\/a\s*>/i.test(e)}(o.content)&&e.linkLevel--),e.pos+=n[0].length,!0))))}],["entity",function(e,t){var n,s,o,i=e.pos,a=e.posMax;if(38!==e.src.charCodeAt(i))return!1;if(i+1>=a)return!1;if(35===e.src.charCodeAt(i+1)){if(s=e.src.slice(i).match(Xe))return t||(n="x"===s[1][0].toLowerCase()?parseInt(s[1].slice(1),16):parseInt(s[1],10),(o=e.push("text_special","",0)).content=Ke(n)?Qe(n):Qe(65533),o.markup=s[0],o.info="entity"),e.pos+=s[0].length,!0}else if((s=e.src.slice(i).match(er))&&Ye(r,s[1]))return t||((o=e.push("text_special","",0)).content=r[s[1]],o.markup=s[0],o.info="entity"),e.pos+=s[0].length,!0;return!1}]],cr=[["balance_pairs",function(e){var r,t=e.tokens_meta,n=e.tokens_meta.length;for(rr(0,e.delimiters),r=0;r<n;r++)t[r]&&t[r].delimiters&&rr(0,t[r].delimiters)}],["strikethrough",Pe.postProcess],["emphasis",Ue.postProcess],["fragments_join",function(e){var r,t,n=0,s=e.tokens,o=e.tokens.length;for(r=t=0;r<o;r++)s[r].nesting<0&&n--,s[r].level=n,s[r].nesting>0&&n++,"text"===s[r].type&&r+1<o&&"text"===s[r+1].type?s[r+1].content=s[r].content+s[r+1].content:(r!==t&&(s[t]=s[r]),t++);r!==t&&(s.length=t)}]];function lr(){var e;for(this.ruler=new O,e=0;e<ar.length;e++)this.ruler.push(ar[e][0],ar[e][1]);for(this.ruler2=new O,e=0;e<cr.length;e++)this.ruler2.push(cr[e][0],cr[e][1])}lr.prototype.skipToken=function(e){var r,t,n=e.pos,s=this.ruler.getRules(""),o=s.length,i=e.md.options.maxNesting,a=e.cache;if(void 0===a[n]){if(e.level<i)for(t=0;t<o&&(e.level++,r=s[t](e,!0),e.level--,!r);t++);else e.pos=e.posMax;r||e.pos++,a[n]=e.pos}else e.pos=a[n]},lr.prototype.tokenize=function(e){for(var 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s(e){return e.replace("%TLDS%",r.src_tlds)}e.onCompile(),e.__tlds_replaced__||n.push("a[cdefgilmnoqrstuwxz]|b[abdefghijmnorstvwyz]|c[acdfghiklmnoruvwxyz]|d[ejkmoz]|e[cegrstu]|f[ijkmor]|g[abdefghilmnpqrstuwy]|h[kmnrtu]|i[delmnoqrst]|j[emop]|k[eghimnprwyz]|l[abcikrstuvy]|m[acdeghklmnopqrstuvwxyz]|n[acefgilopruz]|om|p[aefghklmnrstwy]|qa|r[eosuw]|s[abcdeghijklmnortuvxyz]|t[cdfghjklmnortvwz]|u[agksyz]|v[aceginu]|w[fs]|y[et]|z[amw]"),n.push(r.src_xn),r.src_tlds=n.join("|"),r.email_fuzzy=RegExp(s(r.tpl_email_fuzzy),"i"),r.link_fuzzy=RegExp(s(r.tpl_link_fuzzy),"i"),r.link_no_ip_fuzzy=RegExp(s(r.tpl_link_no_ip_fuzzy),"i"),r.host_fuzzy_test=RegExp(s(r.tpl_host_fuzzy_test),"i");var o=[];function i(e,r){throw new Error('(LinkifyIt) Invalid schema "'+e+'": '+r)}e.__compiled__={},Object.keys(e.__schemas__).forEach((function(r){var t=e.__schemas__[r];if(null!==t){var n={validate:null,link:null};if(e.__compiled__[r]=n,"[object Object]"===hr(t))return!function(e){return"[object 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N5=Yl(),{agents:B5}=(Ps(),Rs),of=Oy(),F5=Mt(),j5=uv(),z5=cv(),U5=dv(),hv={browsers:B5,prefixes:z5},mv=`
+  Replace Autoprefixer \`browsers\` option to Browserslist config.
+  Use \`browserslist\` key in \`package.json\` or \`.browserslistrc\` file.
+
+  Using \`browsers\` option can cause errors. Browserslist config can
+  be used for Babel, Autoprefixer, postcss-normalize and other tools.
+
+  If you really need to use option, rename it to \`overrideBrowserslist\`.
+
+  Learn more at:
+  https://github.com/browserslist/browserslist#readme
+  https://twitter.com/browserslist
+
+`;function V5(r){return Object.prototype.toString.apply(r)==="[object Object]"}var lf=new Map;function H5(r,e){e.browsers.selected.length!==0&&(e.add.selectors.length>0||Object.keys(e.add).length>2||r.warn(`Autoprefixer target browsers do not need any prefixes.You do not need Autoprefixer anymore.
+Check your Browserslist config to be sure that your targets are set up correctly.
+
+  Learn more at:
+  https://github.com/postcss/autoprefixer#readme
+  https://github.com/browserslist/browserslist#readme
+
+`))}gv.exports=Dr;function Dr(...r){let e;if(r.length===1&&V5(r[0])?(e=r[0],r=void 0):r.length===0||r.length===1&&!r[0]?r=void 0:r.length<=2&&(Array.isArray(r[0])||!r[0])?(e=r[1],r=r[0]):typeof r[r.length-1]=="object"&&(e=r.pop()),e||(e={}),e.browser)throw new Error("Change `browser` option to `overrideBrowserslist` in Autoprefixer");if(e.browserslist)throw new Error("Change `browserslist` option to `overrideBrowserslist` in Autoprefixer");e.overrideBrowserslist?r=e.overrideBrowserslist:e.browsers&&(typeof console!="undefined"&&console.warn&&(of.red?console.warn(of.red(mv.replace(/`[^`]+`/g,n=>of.yellow(n.slice(1,-1))))):console.warn(mv)),r=e.browsers);let t={ignoreUnknownVersions:e.ignoreUnknownVersions,stats:e.stats,env:e.env};function i(n){let s=hv,a=new F5(s.browsers,r,n,t),o=a.selected.join(", ")+JSON.stringify(e);return lf.has(o)||lf.set(o,new j5(s.prefixes,a,e)),lf.get(o)}return{postcssPlugin:"autoprefixer",prepare(n){let s=i({from:n.opts.from,env:e.env});return{OnceExit(a){H5(n,s),e.remove!==!1&&s.processor.remove(a,n),e.add!==!1&&s.processor.add(a,n)}}},info(n){return n=n||{},n.from=n.from||m.cwd(),U5(i(n))},options:e,browsers:r}}Dr.postcss=!0;Dr.data=hv;Dr.defaults=N5.defaults;Dr.info=()=>Dr().info()});var bv={};Ge(bv,{default:()=>W5});var W5,wv=P(()=>{u();W5=[]});var xv={};Ge(xv,{default:()=>G5});var vv,G5,kv=P(()=>{u();Xi();vv=pe(rn()),G5=St(vv.default.theme)});var Av={};Ge(Av,{default:()=>Q5});var Sv,Q5,Cv=P(()=>{u();Xi();Sv=pe(rn()),Q5=St(Sv.default)});u();"use strict";var Y5=vt(_y()),K5=vt($e()),X5=vt(yv()),Z5=vt((wv(),bv)),J5=vt((kv(),xv)),eP=vt((Cv(),Av)),tP=vt((Vs(),_f)),rP=vt((al(),sl)),iP=vt((sa(),sc));function vt(r){return r&&r.__esModule?r:{default:r}}console.warn("cdn.tailwindcss.com should not be used in production. To use Tailwind CSS in production, install it as a PostCSS plugin or use the Tailwind CLI: https://tailwindcss.com/docs/installation");var Ns="tailwind",uf="text/tailwindcss",_v="/template.html",Yt,Ev=!0,Ov=0,ff=new Set,cf,Tv="",Rv=(r=!1)=>({get(e,t){return(!r||t==="config")&&typeof e[t]=="object"&&e[t]!==null?new Proxy(e[t],Rv()):e[t]},set(e,t,i){return e[t]=i,(!r||t==="config")&&pf(!0),!0}});window[Ns]=new Proxy({config:{},defaultTheme:J5.default,defaultConfig:eP.default,colors:tP.default,plugin:rP.default,resolveConfig:iP.default},Rv(!0));function Pv(r){cf.observe(r,{attributes:!0,attributeFilter:["type"],characterData:!0,subtree:!0,childList:!0})}new MutationObserver(async r=>{let e=!1;if(!cf){cf=new MutationObserver(async()=>await pf(!0));for(let t of document.querySelectorAll(`style[type="${uf}"]`))Pv(t)}for(let t of r)for(let i of t.addedNodes)i.nodeType===1&&i.tagName==="STYLE"&&i.getAttribute("type")===uf&&(Pv(i),e=!0);await pf(e)}).observe(document.documentElement,{attributes:!0,attributeFilter:["class"],childList:!0,subtree:!0});async function pf(r=!1){r&&(Ov++,ff.clear());let e="";for(let i of document.querySelectorAll(`style[type="${uf}"]`))e+=i.textContent;let t=new Set;for(let i of document.querySelectorAll("[class]"))for(let n of i.classList)ff.has(n)||t.add(n);if(document.body&&(Ev||t.size>0||e!==Tv||!Yt||!Yt.isConnected)){for(let n of t)ff.add(n);Ev=!1,Tv=e,self[_v]=Array.from(t).join(" ");let{css:i}=await(0,K5.default)([(0,Y5.default)({...window[Ns].config,_hash:Ov,content:{files:[_v],extract:{html:n=>n.split(" ")}},plugins:[...Z5.default,...Array.isArray(window[Ns].config.plugins)?window[Ns].config.plugins:[]]}),(0,X5.default)({remove:!1})]).process(`@tailwind base;@tailwind components;@tailwind utilities;${e}`);(!Yt||!Yt.isConnected)&&(Yt=document.createElement("style"),document.head.append(Yt)),Yt.textContent=i}}})();
+/*!
+ * fill-range <https://github.com/jonschlinkert/fill-range>
+ *
+ * Copyright (c) 2014-present, Jon Schlinkert.
+ * Licensed under the MIT License.
+ */
+/*!
+ * is-number <https://github.com/jonschlinkert/is-number>
+ *
+ * Copyright (c) 2014-present, Jon Schlinkert.
+ * Released under the MIT License.
+ */
+/*!
+ * to-regex-range <https://github.com/micromatch/to-regex-range>
+ *
+ * Copyright (c) 2015-present, Jon Schlinkert.
+ * Released under the MIT License.
+ */
+/*! https://mths.be/cssesc v3.0.0 by @mathias */
diff --git a/channel/web/web_channel.py b/channel/web/web_channel.py
new file mode 100644
index 0000000..7f0a6e3
--- /dev/null
+++ b/channel/web/web_channel.py
@@ -0,0 +1,5087 @@
+import datetime
+import hashlib
+import hmac
+import json
+import logging
+import mimetypes
+import os
+import random
+import shutil
+import threading
+import time
+import uuid
+from queue import Queue, Empty
+from typing import List, Tuple
+
+import web
+
+from bridge.context import *
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.chat_message import ChatMessage
+from collections import OrderedDict
+from common import const
+from common import i18n
+from common.log import logger
+from common.singleton import singleton
+from config import conf, get_data_root, get_weixin_credentials_path
+
+IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp", ".svg"}
+VIDEO_EXTENSIONS = {".mp4", ".webm", ".avi", ".mov", ".mkv"}
+
+def _get_web_password() -> str:
+    # Coerce to str so non-string values in config.json (e.g. numeric password) won't break comparisons
+    pwd = conf().get("web_password", "")
+    if pwd is None:
+        return ""
+    return str(pwd)
+
+
+def _is_password_enabled():
+    return bool(_get_web_password())
+
+
+def _session_expire_seconds():
+    return int(conf().get("web_session_expire_days", 30)) * 86400
+
+
+def _create_auth_token():
+    """Create a stateless signed token: ``<timestamp_hex>.<hmac_hex>``."""
+    ts = format(int(time.time()), "x")
+    sig = hmac.new(
+        _get_web_password().encode(),
+        ts.encode(),
+        hashlib.sha256,
+    ).hexdigest()
+    return f"{ts}.{sig}"
+
+
+def _verify_auth_token(token):
+    """Verify a signed token is valid and not expired.
+
+    The token is derived from the password, so it survives server restarts
+    and automatically invalidates when the password changes.
+    """
+    if not token or "." not in token:
+        return False
+    ts_hex, sig = token.split(".", 1)
+    try:
+        ts = int(ts_hex, 16)
+    except ValueError:
+        return False
+    if time.time() - ts > _session_expire_seconds():
+        return False
+    expected = hmac.new(
+        _get_web_password().encode(),
+        ts_hex.encode(),
+        hashlib.sha256,
+    ).hexdigest()
+    return hmac.compare_digest(sig, expected)
+
+
+def _get_bearer_token():
+    """Extract the token from an `Authorization: Bearer <token>` header.
+
+    The desktop client renders from a file:// origin, so cross-origin cookies
+    to http://127.0.0.1 are unreliable (SameSite=Lax cookies aren't sent). It
+    therefore authenticates via this header instead; browsers keep using the
+    cookie set by /auth/login.
+    """
+    auth = web.ctx.env.get("HTTP_AUTHORIZATION", "") or ""
+    if auth.startswith("Bearer "):
+        return auth[7:].strip()
+    return ""
+
+
+def _get_query_token():
+    """Extract a token from the `token` query param.
+
+    Needed for SSE endpoints: EventSource can't set an Authorization header,
+    and file:// cookies are unreliable, so the desktop client passes the token
+    in the query string for /stream and /api/logs.
+    """
+    try:
+        return web.input(token="").token or ""
+    except Exception:
+        return ""
+
+
+def _check_auth():
+    """Return True if request is authenticated or password not enabled."""
+    if not _is_password_enabled():
+        return True
+    if _verify_auth_token(web.cookies().get("cow_auth_token", "")):
+        return True
+    if _verify_auth_token(_get_bearer_token()):
+        return True
+    return _verify_auth_token(_get_query_token())
+
+
+def _require_auth():
+    """Raise 401 if not authenticated. Call at the top of protected handlers."""
+    if not _check_auth():
+        raise web.HTTPError("401 Unauthorized",
+                            {"Content-Type": "application/json; charset=utf-8"},
+                            json.dumps({"status": "error", "message": "Unauthorized"}))
+
+
+# Localized text for /cancel system replies. Web is the only channel that
+# honors a per-request `lang`; other channels reply in Chinese by default.
+def _cancel_reply_text(cancelled: int, lang: str) -> str:
+    en = lang.startswith("en")
+    if cancelled > 0:
+        return "🛑 Cancelled" if en else "🛑 已中止"
+    return "Nothing to cancel." if en else "当前没有可中止的任务。"
+
+
+def _get_upload_dir() -> str:
+    from common.utils import expand_path
+    ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    tmp_dir = os.path.join(ws_root, "tmp")
+    os.makedirs(tmp_dir, exist_ok=True)
+    return tmp_dir
+
+
+def _sanitize_upload_relative_path(relative_path: str) -> str:
+    """Normalize relative upload path and reject escapes / absolute paths."""
+    relative_path = (relative_path or "").replace("\\", "/").strip("/")
+    if not relative_path:
+        raise ValueError("Empty relative path")
+    parts = []
+    for part in relative_path.split("/"):
+        if part in ("", "."):
+            continue
+        if part == "..":
+            raise ValueError("Invalid relative path")
+        parts.append(part)
+    if not parts:
+        raise ValueError("Invalid relative path")
+    norm_path = "/".join(parts)
+    if os.path.isabs(norm_path):
+        raise ValueError("Invalid relative path")
+    return norm_path
+
+
+def _sanitize_upload_id(upload_id: str) -> str:
+    """Allow only simple batch ids for directory uploads."""
+    sanitized = "".join(ch for ch in (upload_id or "") if ch.isalnum() or ch in ("-", "_"))
+    if not sanitized:
+        raise ValueError("Invalid upload id")
+    return sanitized[:80]
+
+
+def _is_within_directory(root_path: str, target_path: str) -> bool:
+    try:
+        return os.path.commonpath([root_path, target_path]) == root_path
+    except ValueError:
+        return False
+
+
+def _resolve_upload_path(upload_root: str, relative_path: str) -> Tuple[str, str]:
+    """Resolve a relative upload path under upload_root and reject escapes."""
+    safe_rel_path = _sanitize_upload_relative_path(relative_path)
+    upload_root_real = os.path.realpath(upload_root)
+    save_path = os.path.realpath(os.path.join(upload_root_real, *safe_rel_path.split("/")))
+    if not _is_within_directory(upload_root_real, save_path):
+        raise ValueError("Invalid directory upload path")
+    return safe_rel_path, save_path
+
+
+def _read_uploaded_file_bytes(file_obj) -> bytes:
+    """Return uploaded content as bytes across web.py upload object variants."""
+    if isinstance(file_obj, bytes):
+        return file_obj
+    if isinstance(file_obj, str):
+        return file_obj.encode("utf-8")
+
+    content = None
+
+    if hasattr(file_obj, "file") and hasattr(file_obj.file, "read"):
+        content = file_obj.file.read()
+    elif hasattr(file_obj, "read"):
+        content = file_obj.read()
+    elif hasattr(file_obj, "value"):
+        content = file_obj.value
+
+    if content is None:
+        raise ValueError("Unable to read uploaded file content")
+    if isinstance(content, bytes):
+        return content
+    if isinstance(content, str):
+        return content.encode("utf-8")
+    raise TypeError(f"Unsupported uploaded content type: {type(content).__name__}")
+
+
+def _read_uploaded_file_bytes_limited(file_obj, max_bytes: int) -> bytes:
+    """Read uploaded content and fail once it exceeds max_bytes."""
+    if isinstance(file_obj, bytes):
+        content = file_obj
+    elif isinstance(file_obj, str):
+        content = file_obj.encode("utf-8")
+    elif hasattr(file_obj, "file") and hasattr(file_obj.file, "read"):
+        content = file_obj.file.read(max_bytes + 1)
+    elif hasattr(file_obj, "read"):
+        content = file_obj.read(max_bytes + 1)
+    elif hasattr(file_obj, "value"):
+        content = file_obj.value
+    else:
+        raise ValueError("Unable to read uploaded file content")
+    if isinstance(content, str):
+        content = content.encode("utf-8")
+    if not isinstance(content, bytes):
+        raise TypeError(f"Unsupported uploaded content type: {type(content).__name__}")
+    if len(content) > max_bytes:
+        raise ValueError("file too large")
+    return content
+
+
+def _raw_web_input():
+    """Return unprocessed multipart form data when web.py exposes rawinput."""
+    rawinput = getattr(getattr(web, "webapi", None), "rawinput", None)
+    if not callable(rawinput):
+        raise RuntimeError("web.py rawinput is not available")
+    try:
+        return rawinput(method="post")
+    except TypeError:
+        return rawinput()
+
+
+def _ensure_list(value):
+    if value is None:
+        return []
+    if isinstance(value, list):
+        return value
+    return [value]
+
+
+def _generate_session_title(user_message: str, assistant_reply: str = "") -> str:
+    """Delegate to the shared SessionService implementation."""
+    from agent.chat.session_service import generate_session_title
+    return generate_session_title(user_message, assistant_reply)
+
+
+class WebMessage(ChatMessage):
+    def __init__(
+            self,
+            msg_id,
+            content,
+            ctype=ContextType.TEXT,
+            from_user_id="User",
+            to_user_id="Chatgpt",
+            other_user_id="Chatgpt",
+    ):
+        self.msg_id = msg_id
+        self.ctype = ctype
+        self.content = content
+        self.from_user_id = from_user_id
+        self.to_user_id = to_user_id
+        self.other_user_id = other_user_id
+
+
+@singleton
+class WebChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = [ReplyType.VOICE]
+    _instance = None
+
+    # def __new__(cls):
+    #     if cls._instance is None:
+    #         cls._instance = super(WebChannel, cls).__new__(cls)
+    #     return cls._instance
+
+    def __init__(self):
+        super().__init__()
+        self.msg_id_counter = 0
+        self.session_queues = {}  # session_id -> Queue (fallback polling)
+        self.request_to_session = {}  # request_id -> session_id
+        self.sse_queues = {}  # request_id -> Queue (SSE streaming)
+        # request_id -> last-active timestamp. Refreshed while the SSE
+        # generator is being consumed (client still connected). The janitor
+        # only reclaims queues whose generator stopped refreshing this, so a
+        # long-running but still-streaming reply is never wrongly killed.
+        self.sse_last_active = {}
+        self._http_server = None
+        self._sse_janitor_started = False
+
+    def _generate_msg_id(self):
+        """生成唯一的消息ID"""
+        self.msg_id_counter += 1
+        return str(int(time.time())) + str(self.msg_id_counter)
+
+    def _generate_request_id(self):
+        """生成唯一的请求ID"""
+        return str(uuid.uuid4())
+
+    def _fetch_latest_pair_seqs(self, session_id: str):
+        """Query the conversation store for the latest user/bot message seqs.
+
+        Returned as ``{"user_seq": int|None, "bot_seq": int|None}``; used to
+        attach seq metadata onto the SSE ``done`` event so the frontend can
+        wire edit / regenerate buttons for live-streamed bubbles without a
+        page refresh.
+        """
+        try:
+            from agent.memory import get_conversation_store
+            return get_conversation_store().get_latest_pair_seqs(session_id)
+        except Exception as e:
+            logger.debug(f"[WebChannel] _fetch_latest_pair_seqs failed: {e}")
+            return {"user_seq": None, "bot_seq": None}
+
+    def send(self, reply: Reply, context: Context):
+        try:
+            if reply.type in self.NOT_SUPPORT_REPLYTYPE:
+                logger.warning(f"Web channel doesn't support {reply.type} yet")
+                return
+
+            if reply.type == ReplyType.IMAGE_URL:
+                time.sleep(0.5)
+
+            request_id = context.get("request_id", None)
+            if not request_id:
+                logger.error("No request_id found in context, cannot send message")
+                return
+
+            session_id = self.request_to_session.get(request_id)
+            if not session_id:
+                logger.error(f"No session_id found for request {request_id}")
+                return
+
+            # SSE mode: push events to SSE queue
+            if request_id in self.sse_queues:
+                content = reply.content if reply.content is not None else ""
+
+                # Intermediate status lines (e.g. /install-browser phases) must NOT use "done",
+                # or the frontend closes EventSource and drops subsequent events.
+                if getattr(reply, "sse_phase", False):
+                    self.sse_queues[request_id].put({
+                        "type": "phase",
+                        "content": content,
+                        "request_id": request_id,
+                        "timestamp": time.time(),
+                    })
+                    logger.debug(f"SSE phase for request {request_id}")
+                    return
+
+                # Files are already pushed via on_event (file_to_send) during agent execution.
+                # Skip duplicate file pushes here; just let the done event through.
+                if reply.type in (ReplyType.IMAGE_URL, ReplyType.FILE) and content.startswith("file://"):
+                    text_content = getattr(reply, 'text_content', '')
+                    if text_content:
+                        seqs = self._fetch_latest_pair_seqs(session_id)
+                        self.sse_queues[request_id].put({
+                            "type": "done",
+                            "content": text_content,
+                            "request_id": request_id,
+                            "timestamp": time.time(),
+                            "user_seq": seqs.get("user_seq"),
+                            "bot_seq": seqs.get("bot_seq"),
+                        })
+                    logger.debug(f"SSE skipped duplicate file for request {request_id}")
+                    return
+
+                # Skip http-URL FILE/IMAGE_URL replies produced by chat_channel's media extraction:
+                # the text reply (already sent as "done") contains the URL and the frontend will
+                # render it via renderMarkdown/injectVideoPlayers, so no separate SSE event needed.
+                if reply.type in (ReplyType.FILE, ReplyType.IMAGE_URL) and content.startswith(("http://", "https://")):
+                    logger.debug(f"SSE skipped http media reply for request {request_id}")
+                    return
+
+                seqs = self._fetch_latest_pair_seqs(session_id)
+                self.sse_queues[request_id].put({
+                    "type": "done",
+                    "content": content,
+                    "request_id": request_id,
+                    "timestamp": time.time(),
+                    "user_seq": seqs.get("user_seq"),
+                    "bot_seq": seqs.get("bot_seq"),
+                })
+                logger.debug(f"SSE done sent for request {request_id}")
+                # Auto-trigger TTS once the bot finishes its text reply. The
+                # synthesis runs in the background so the chat stream is never
+                # blocked; the resulting audio URL is pushed via a follow-up
+                # `voice_attach` SSE event and persisted to messages.extras.
+                if reply.type == ReplyType.TEXT and content.strip():
+                    self._maybe_dispatch_auto_tts(request_id, session_id, content, context)
+                return
+
+            # Fallback: polling mode
+            if session_id in self.session_queues:
+                content = reply.content if reply.content is not None else ""
+                # Skip file:// IMAGE_URL/FILE replies originating from an SSE-enabled
+                # request: they were already pushed via the `file_to_send` event during
+                # agent execution. By the time the chat_channel sends the IMAGE_URL reply,
+                # the SSE stream has typically closed (after the text "done") and the
+                # request_id is gone from sse_queues, so we'd otherwise duplicate the file
+                # as a polling bubble. Scheduler/push tasks have no on_event and must
+                # still go through polling normally.
+                if (
+                    reply.type in (ReplyType.IMAGE_URL, ReplyType.FILE)
+                    and content.startswith("file://")
+                    and context.get("on_event") is not None
+                ):
+                    logger.debug(f"Polling skipped duplicate file reply for session {session_id}")
+                    return
+                # SSE-enabled requests already stream the text reply to the
+                # client. Do NOT also enqueue it for polling: if the user
+                # switched away mid-run, the queued copy would resurface as a
+                # duplicate bubble when they return and poll the session.
+                if reply.type == ReplyType.TEXT and context.get("on_event") is not None:
+                    logger.debug(f"Polling skipped SSE text reply for session {session_id}")
+                    return
+                response_data = {
+                    "type": str(reply.type),
+                    "content": content,
+                    "timestamp": time.time(),
+                    "request_id": request_id
+                }
+                self.session_queues[session_id].put(response_data)
+                logger.debug(f"Response sent to poll queue for session {session_id}, request {request_id}")
+            else:
+                logger.warning(f"No response queue found for session {session_id}, response dropped")
+
+        except Exception as e:
+            logger.error(f"Error in send method: {e}")
+
+    def _make_sse_callback(self, request_id: str):
+        """Build an on_event callback that pushes agent stream events into the SSE queue."""
+
+        # Cap reasoning bytes pushed to the frontend per request to avoid
+        # browser stalls / crashes on very long chains-of-thought. Anything
+        # beyond the cap is dropped from the stream (DB still persists a
+        # truncated copy via _truncate_reasoning_for_storage).
+        # Keep aligned with frontend REASONING_RENDER_CAP and backend
+        # MAX_STORED_REASONING_CHARS.
+        MAX_REASONING_STREAM_CHARS = 4 * 1024  # 4 KB
+        # Use a single-element list as a mutable counter accessible from closure.
+        reasoning_chars_sent = [0]
+        reasoning_capped_notified = [False]
+        # Captures the first error message emitted by agent_stream so the
+        # subsequent agent_end handler can skip its "empty final_response"
+        # fallback (which would otherwise overwrite the real error).
+        streamed_error: List[str] = []
+
+        def on_event(event: dict):
+            if request_id not in self.sse_queues:
+                return
+            q = self.sse_queues[request_id]
+            event_type = event.get("type")
+            data = event.get("data", {})
+
+            if event_type == "reasoning_update":
+                delta = data.get("delta", "")
+                if not delta:
+                    return
+                remaining = MAX_REASONING_STREAM_CHARS - reasoning_chars_sent[0]
+                if remaining <= 0:
+                    if not reasoning_capped_notified[0]:
+                        reasoning_capped_notified[0] = True
+                        q.put({
+                            "type": "reasoning",
+                            "content": "\n\n... [reasoning truncated for display] ...",
+                        })
+                    return
+                if len(delta) > remaining:
+                    delta = delta[:remaining]
+                reasoning_chars_sent[0] += len(delta)
+                q.put({"type": "reasoning", "content": delta})
+
+            elif event_type == "message_update":
+                delta = data.get("delta", "")
+                if delta:
+                    q.put({"type": "delta", "content": delta})
+
+            elif event_type == "tool_execution_start":
+                tool_name = data.get("tool_name", "tool")
+                arguments = data.get("arguments", {})
+                q.put({"type": "tool_start", "tool_call_id": data.get("tool_call_id"), "tool": tool_name, "arguments": arguments})
+
+            elif event_type == "tool_execution_progress":
+                q.put({
+                    "type": "tool_progress",
+                    "tool_call_id": data.get("tool_call_id"),
+                    "tool": data.get("tool_name", "tool"),
+                    "content": str(data.get("message", ""))[-4 * 1024:],
+                })
+
+            elif event_type == "tool_execution_end":
+                tool_name = data.get("tool_name", "tool")
+                status = data.get("status", "success")
+                result = data.get("result", "")
+                exec_time = data.get("execution_time", 0)
+                # Truncate long results to avoid huge SSE payloads
+                result_str = str(result)
+                if len(result_str) > 2000:
+                    result_str = result_str[:2000] + "…"
+                q.put({
+                    "type": "tool_end",
+                    "tool_call_id": data.get("tool_call_id"),
+                    "tool": tool_name,
+                    "status": status,
+                    "result": result_str,
+                    "execution_time": round(exec_time, 2)
+                })
+
+            elif event_type == "message_end":
+                tool_calls = data.get("tool_calls", [])
+                if tool_calls:
+                    q.put({"type": "message_end", "has_tool_calls": True})
+
+            elif event_type == "error":
+                # Agent raised an exception (LLM 401/timeout/etc). Surface the
+                # real message instead of letting the empty-response fallback
+                # below hide it as "(模型未返回任何内容)".
+                err_msg = data.get("error") or "unknown error"
+                logger.warning(
+                    f"[WebChannel] agent_stream emitted error for "
+                    f"request {request_id}: {err_msg}"
+                )
+                # Remember it so the agent_end handler below knows not to
+                # rewrite the message into a generic empty-response notice.
+                streamed_error.append(err_msg)
+                q.put({
+                    "type": "done",
+                    "content": f"❌ {err_msg}",
+                    "request_id": request_id,
+                    "timestamp": time.time(),
+                })
+
+            elif event_type == "agent_cancelled":
+                # Push an explicit cancelled SSE event so the frontend
+                # marks the bubble as stopped. A trailing "done" still
+                # arrives with the partial answer.
+                final_response = data.get("final_response", "")
+                q.put({
+                    "type": "cancelled",
+                    "content": final_response,
+                    "request_id": request_id,
+                    "timestamp": time.time(),
+                })
+
+            elif event_type == "agent_end":
+                # Safety net: if the agent finishes with an empty final_response,
+                # chat_channel skips _send_reply (because reply.content is empty),
+                # which means no "done" event is ever emitted and the SSE stream
+                # would hang until the 10-min idle timeout. Push a fallback "done"
+                # here so the frontend always gets closure.
+                final_response = data.get("final_response", "")
+                if not final_response or not str(final_response).strip():
+                    if streamed_error:
+                        # Error was already surfaced via the `error` event
+                        # handler above; nothing more to do here.
+                        pass
+                    else:
+                        logger.warning(
+                            f"[WebChannel] agent_end with empty final_response for "
+                            f"request {request_id}, sending fallback done"
+                        )
+                        q.put({
+                            "type": "done",
+                            "content": i18n.t(
+                                "(模型未返回任何内容，请重试或换一种方式描述你的需求)",
+                                "(The model returned no content. Please retry or rephrase your request.)",
+                            ),
+                            "request_id": request_id,
+                            "timestamp": time.time(),
+                        })
+
+            elif event_type == "file_to_send":
+                file_path = data.get("path", "")
+                file_name = data.get("file_name", os.path.basename(file_path))
+                file_type = data.get("file_type", "file")
+                # Remote URLs are passed through as-is; local files are served
+                # via the backend /api/file endpoint.
+                remote_url = data.get("url", "")
+                is_remote = bool(remote_url) and remote_url.lower().startswith(("http://", "https://"))
+                if is_remote:
+                    web_url = remote_url
+                else:
+                    from urllib.parse import quote
+                    web_url = f"/api/file?path={quote(file_path)}"
+                is_image = file_type == "image"
+                payload = {
+                    "type": "image" if is_image else "file",
+                    "content": web_url,
+                    "file_name": file_name,
+                    # Preserve the concrete media kind (image/video/audio/...)
+                    # so richer clients can render an inline player.
+                    "file_type": file_type,
+                }
+                # Expose the local absolute path so the desktop client can open
+                # the file directly (Finder / default app) instead of the browser.
+                if not is_remote and file_path:
+                    payload["abs_path"] = file_path
+                q.put(payload)
+
+        return on_event
+
+    # ------------------------------------------------------------------
+    # TTS auto-dispatch
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _resolve_voice_reply_mode() -> str:
+        """
+        Decide the TTS auto-reply policy.
+
+        Source of truth is the cross-channel pair
+        (`always_reply_voice`, `voice_reply_voice`) which chat_channel
+        also consults. The web UI presents these as a single three-state
+        picker (off / voice_if_voice / always) via a lossless mapping.
+        """
+        if conf().get("always_reply_voice", False):
+            return "always"
+        if conf().get("voice_reply_voice", False):
+            return "voice_if_voice"
+        return "off"
+
+    # Mirror of ModelsHandler._TTS_PROVIDERS. zhipu is intentionally omitted
+    # from the UI (GLM-TTS prelude beep); pinning it in config.json still works.
+    _TTS_PROVIDERS_SUGGEST_ORDER = ["openai", "minimax", "dashscope", "linkai"]
+
+    @classmethod
+    def _tts_provider_ready(cls) -> bool:
+        """True if user picked a provider OR any suggested vendor has an API key."""
+        if (conf().get("text_to_voice") or "").strip():
+            return True
+        for pid in cls._TTS_PROVIDERS_SUGGEST_ORDER:
+            meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+            key_field = meta.get("api_key_field")
+            if not key_field:
+                continue
+            val = (conf().get(key_field) or "").strip()
+            if val and val not in ("YOUR API KEY", "YOUR_API_KEY"):
+                return True
+        return False
+
+    def _maybe_dispatch_auto_tts(
+        self,
+        request_id: str,
+        session_id: str,
+        text: str,
+        context: dict,
+    ) -> None:
+        try:
+            mode = self._resolve_voice_reply_mode()
+            if mode == "off":
+                return
+            if mode == "voice_if_voice" and not context.get("is_voice_input"):
+                return
+            if not self._tts_provider_ready():
+                return
+            threading.Thread(
+                target=self._synthesize_tts_async,
+                args=(request_id, session_id, text),
+                daemon=True,
+            ).start()
+        except Exception as e:
+            logger.debug(f"[WebChannel] auto-tts dispatch skipped: {e}")
+
+    def _synthesize_tts_async(
+        self,
+        request_id: str,
+        session_id: str,
+        text: str,
+    ) -> None:
+        try:
+            from bridge.bridge import Bridge
+            reply = Bridge().fetch_text_to_voice(text)
+            if reply is None or reply.type != ReplyType.VOICE or not reply.content:
+                logger.warning(
+                    f"[WebChannel] TTS produced no audio for request {request_id}: "
+                    f"reply={reply}"
+                )
+                return
+            url = self._publish_tts_audio(reply.content)
+            if not url:
+                logger.warning(f"[WebChannel] TTS publish failed for request {request_id}")
+                return
+            payload = {"audio": {"url": url, "kind": "tts"}}
+            try:
+                from agent.memory import get_conversation_store
+                get_conversation_store().attach_extras_to_last_assistant(session_id, payload)
+            except Exception as e:
+                logger.debug(f"[WebChannel] tts persist skipped: {e}")
+            q = self.sse_queues.get(request_id)
+            if q is None:
+                logger.warning(
+                    f"[WebChannel] TTS ready but SSE queue already closed "
+                    f"for request {request_id} (url={url})"
+                )
+                return
+            q.put({
+                "type": "voice_attach",
+                "url": url,
+                "request_id": request_id,
+                "timestamp": time.time(),
+            })
+            logger.info(f"[WebChannel] TTS voice_attach pushed for request {request_id}: {url}")
+        except Exception as e:
+            # TTS failures are intentionally silent (no user-facing error).
+            logger.warning(f"[WebChannel] TTS synthesis failed: {e}")
+
+    @staticmethod
+    def _publish_tts_audio(src_path: str) -> str:
+        """Move a TTS file into uploads/ and return its public URL."""
+        try:
+            if not src_path or not os.path.isfile(src_path):
+                logger.warning(f"[WebChannel] publish_tts_audio missing source: {src_path!r}")
+                return ""
+            ext = os.path.splitext(src_path)[1].lower() or ".mp3"
+            upload_dir = _get_upload_dir()
+            os.makedirs(upload_dir, exist_ok=True)
+            ts = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+            dst_name = f"voice_reply_{ts}_{random.randint(0, 9999)}{ext}"
+            dst_path = os.path.join(upload_dir, dst_name)
+            shutil.move(src_path, dst_path)
+            logger.debug(f"[WebChannel] publish_tts_audio moved {src_path} -> {dst_path}")
+            return f"/uploads/{dst_name}"
+        except Exception as e:
+            logger.warning(f"[WebChannel] publish_tts_audio failed: {e}")
+            return ""
+
+    @staticmethod
+    def _cleanup_stale_voice_recordings(max_age_seconds: int = 3600) -> None:
+        """Drop voice_input_* uploads older than max_age_seconds (run at startup)."""
+        try:
+            upload_dir = _get_upload_dir()
+            if not os.path.isdir(upload_dir):
+                return
+            now = time.time()
+            removed = 0
+            for name in os.listdir(upload_dir):
+                if not name.startswith("voice_input_"):
+                    continue
+                full = os.path.join(upload_dir, name)
+                try:
+                    if not os.path.isfile(full):
+                        continue
+                    if now - os.path.getmtime(full) > max_age_seconds:
+                        os.remove(full)
+                        removed += 1
+                except OSError:
+                    continue
+            if removed:
+                logger.info(f"[WebChannel] cleaned up {removed} stale voice recording(s) from {upload_dir}")
+        except Exception as e:
+            logger.warning(f"[WebChannel] voice cleanup failed: {e}")
+
+    def upload_file(self):
+        """Handle file or directory upload via multipart/form-data."""
+        try:
+            params = _raw_web_input()
+            file_obj = params.get("file")
+            file_objs = params.get("files")
+            session_id = params.get("session_id", "")
+            relative_path = params.get("relative_path", "")
+            relative_paths = params.get("relative_paths")
+            upload_id = params.get("upload_id", "")
+
+            directory_files = _ensure_list(file_objs)
+
+            # NOTE: cgi.FieldStorage raises TypeError on truthy checks for single-file
+            # uploads (Python 3.9+). Always use `is not None` instead of `if file_obj`.
+            if not directory_files and file_obj is not None and relative_path:
+                directory_files = [file_obj]
+
+            directory_rel_paths = _ensure_list(relative_paths)
+
+            if not directory_rel_paths and relative_path:
+                directory_rel_paths = [relative_path]
+
+            is_directory_upload = bool(directory_files) or bool(directory_rel_paths) or bool(relative_path) or bool(upload_id)
+
+            upload_dir = _get_upload_dir()
+            if is_directory_upload:
+                if not upload_id:
+                    return json.dumps({"status": "error", "message": "Missing upload_id for directory upload"})
+                if not directory_files:
+                    return json.dumps({"status": "error", "message": "No files uploaded"})
+                if len(directory_files) != len(directory_rel_paths):
+                    return json.dumps({"status": "error", "message": "Directory upload payload mismatch"})
+
+                safe_upload_id = _sanitize_upload_id(upload_id)
+                upload_root = os.path.join(upload_dir, f"webdir_{safe_upload_id}")
+                upload_root_real = os.path.realpath(upload_root)
+
+                root_name = None
+                saved_files = 0
+                for file_obj, rel_path in zip(directory_files, directory_rel_paths):
+                    if file_obj is None:
+                        raise ValueError("Invalid uploaded file")
+                    safe_rel_path, save_path = _resolve_upload_path(upload_root_real, rel_path)
+                    current_root_name = safe_rel_path.split("/", 1)[0]
+                    if root_name is None:
+                        root_name = current_root_name
+                    elif root_name != current_root_name:
+                        raise ValueError("Directory upload must use a single root folder")
+                    os.makedirs(os.path.dirname(save_path), exist_ok=True)
+                    content_bytes = _read_uploaded_file_bytes(file_obj)
+                    with open(save_path, "wb") as f:
+                        f.write(content_bytes)
+                    saved_files += 1
+
+                if not root_name:
+                    raise ValueError("Directory root path missing")
+
+                root_path = os.path.realpath(os.path.join(upload_root_real, root_name))
+                if not _is_within_directory(upload_root_real, root_path):
+                    raise ValueError("Invalid directory upload path")
+
+                logger.info(f"[WebChannel] Directory uploaded: {root_name} -> {root_path} ({saved_files} files)")
+                return json.dumps({
+                    "status": "success",
+                    "file_path": root_path,
+                    "file_name": root_name,
+                    "file_type": "directory",
+                    "file_count": saved_files,
+                    "root_path": root_path,
+                    "root_name": root_name,
+                    "upload_type": "directory",
+                }, ensure_ascii=False)
+
+            if file_obj is None or not hasattr(file_obj, "filename") or not file_obj.filename:
+                return json.dumps({"status": "error", "message": "No file uploaded"})
+
+            original_name = file_obj.filename
+            ext = os.path.splitext(original_name)[1].lower()
+            safe_name = f"web_{uuid.uuid4().hex[:8]}{ext}"
+            save_path = os.path.join(upload_dir, safe_name)
+            public_path = safe_name
+            display_name = original_name
+
+            content_bytes = _read_uploaded_file_bytes(file_obj)
+            with open(save_path, "wb") as f:
+                f.write(content_bytes)
+
+            if ext in IMAGE_EXTENSIONS:
+                file_type = "image"
+            elif ext in VIDEO_EXTENSIONS:
+                file_type = "video"
+            else:
+                file_type = "file"
+
+            from urllib.parse import quote
+            preview_url = f"/uploads/{quote(public_path, safe='/')}"
+
+            logger.info(f"[WebChannel] File uploaded: {original_name} -> {save_path} ({file_type})")
+
+            return json.dumps({
+                "status": "success",
+                "file_path": save_path,
+                "file_name": display_name,
+                "file_type": file_type,
+                "preview_url": preview_url,
+            }, ensure_ascii=False)
+
+        except Exception as e:
+            logger.error(f"[WebChannel] File upload error: {e}", exc_info=True)
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def post_message(self):
+        """
+        Handle incoming messages from users via POST request.
+        Returns a request_id for tracking this specific request.
+        Supports optional attachments (file paths from /upload).
+        """
+        try:
+            data = web.data()
+            json_data = json.loads(data)
+            session_id = json_data.get('session_id', f'session_{int(time.time())}')
+            prompt = json_data.get('message', '')
+            use_sse = json_data.get('stream', True)
+            attachments = json_data.get('attachments', [])
+            # Tag the message as originating from voice input so the post-reply
+            # TTS hook can honour the `voice_if_voice` policy (mirrors the
+            # desire_rtype concept used by other channels).
+            is_voice_input = bool(json_data.get('is_voice', False))
+
+            # Fast path for /cancel: bypass the session queue and SSE setup.
+            # Web frontend (stream=true) only listens to SSE, so we return an
+            # inline_reply payload to be rendered synchronously.
+            stripped_prompt = (prompt or "").strip().lower()
+            if stripped_prompt == "/cancel":
+                from agent.protocol import get_cancel_registry
+                cancelled = get_cancel_registry().cancel_session(session_id)
+                lang = (json_data.get('lang') or 'zh').lower()
+                msg_text = _cancel_reply_text(cancelled, lang)
+                logger.info(
+                    f"[WebChannel] /cancel fast-path: session={session_id}, cancelled={cancelled}, lang={lang}"
+                )
+                return json.dumps({
+                    "status": "success",
+                    "request_id": "",
+                    "stream": False,
+                    "inline_reply": msg_text,
+                })
+
+            # Append file references to the prompt (same format as QQ channel)
+            if attachments:
+                file_refs = []
+                for att in attachments:
+                    ftype = att.get("file_type", "file")
+                    fpath = att.get("file_path", "")
+                    if not fpath:
+                        continue
+                    if ftype == "image":
+                        file_refs.append(f"[{i18n.t('图片', 'Image')}: {fpath}]")
+                    elif ftype == "video":
+                        file_refs.append(f"[{i18n.t('视频', 'Video')}: {fpath}]")
+                    elif ftype == "directory":
+                        file_refs.append(f"[{i18n.t('目录', 'Directory')}: {fpath}]")
+                    else:
+                        file_refs.append(f"[{i18n.t('文件', 'File')}: {fpath}]")
+                if file_refs:
+                    prompt = prompt + "\n" + "\n".join(file_refs)
+                    logger.info(f"[WebChannel] Attached {len(file_refs)} file(s) to message")
+
+            request_id = self._generate_request_id()
+            self.request_to_session[request_id] = session_id
+
+            if session_id not in self.session_queues:
+                self.session_queues[session_id] = Queue()
+
+            if use_sse:
+                self.sse_queues[request_id] = Queue()
+                self.sse_last_active[request_id] = time.time()
+
+            trigger_prefixs = conf().get("single_chat_prefix", [""])
+            if check_prefix(prompt, trigger_prefixs) is None:
+                if trigger_prefixs:
+                    prompt = trigger_prefixs[0] + prompt
+                    logger.debug(f"[WebChannel] Added prefix to message: {prompt}")
+
+            msg = WebMessage(self._generate_msg_id(), prompt)
+            msg.from_user_id = session_id
+
+            context = self._compose_context(ContextType.TEXT, prompt, msg=msg, isgroup=False)
+
+            if context is None:
+                logger.warning(f"[WebChannel] Context is None for session {session_id}, message may be filtered")
+                self._drop_sse_request(request_id)
+                return json.dumps({"status": "error", "message": "Message was filtered"})
+
+            context["session_id"] = session_id
+            context["receiver"] = session_id
+            context["request_id"] = request_id
+            if is_voice_input:
+                # Web channel runs its own TTS post-pipeline via
+                # _maybe_dispatch_auto_tts; don't set desire_rtype here or
+                # chat_channel would synthesize a duplicate VOICE reply.
+                context["is_voice_input"] = True
+
+            if use_sse:
+                context["on_event"] = self._make_sse_callback(request_id)
+
+            threading.Thread(target=self.produce, args=(context,)).start()
+
+            return json.dumps({"status": "success", "request_id": request_id, "stream": use_sse})
+
+        except Exception as e:
+            logger.error(f"Error processing message: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def _drop_sse_request(self, request_id: str):
+        """Reclaim all state tied to an SSE request to prevent fd/memory leaks.
+
+        Removing the queue lets the WSGI generator and its socket be released,
+        and dropping request_to_session avoids unbounded map growth.
+        """
+        self.sse_queues.pop(request_id, None)
+        self.sse_last_active.pop(request_id, None)
+        self.request_to_session.pop(request_id, None)
+
+    def _start_sse_janitor(self):
+        """Start a background thread that reclaims orphaned SSE queues.
+
+        When a client disconnects before the "done" event arrives (browser
+        closed, session switched, network drop), the generator may keep the
+        queue around to allow reconnection. Without a sweep these orphans
+        accumulate, leaking file descriptors until cheroot raises
+        "[Errno 24] Too many open files".
+
+        Reclamation is based on idle time, not total age: an active stream
+        refreshes ``sse_last_active`` every second while its generator is being
+        consumed, so a long-running reply (even hours long) is never killed
+        while the client stays connected. Only queues that stopped refreshing
+        (client gone) past SSE_IDLE_TIMEOUT are reclaimed.
+        """
+        if self._sse_janitor_started:
+            return
+        self._sse_janitor_started = True
+
+        SSE_IDLE_TIMEOUT = 1800  # 30 minutes with no client consumption
+        SWEEP_INTERVAL = 60
+
+        def _sweep():
+            while True:
+                time.sleep(SWEEP_INTERVAL)
+                try:
+                    now = time.time()
+                    stale = [
+                        rid for rid, ts in list(self.sse_last_active.items())
+                        if now - ts > SSE_IDLE_TIMEOUT
+                    ]
+                    for rid in stale:
+                        self._drop_sse_request(rid)
+                    if stale:
+                        logger.info(
+                            f"[WebChannel] SSE janitor reclaimed {len(stale)} "
+                            f"idle stream(s)"
+                        )
+                except Exception as e:
+                    logger.warning(f"[WebChannel] SSE janitor error: {e}")
+
+        t = threading.Thread(target=_sweep, name="sse-janitor", daemon=True)
+        t.start()
+
+    def stream_response(self, request_id: str):
+        """
+        SSE generator for a given request_id.
+        Yields UTF-8 encoded bytes to avoid WSGI Latin-1 mangling.
+        Supports client reconnection: the queue is only removed after a
+        "done" event is consumed, so a new GET /stream with the same
+        request_id can resume reading remaining events.
+        """
+        if request_id not in self.sse_queues:
+            yield b"data: {\"type\": \"error\", \"message\": \"invalid request_id\"}\n\n"
+            return
+
+        q = self.sse_queues[request_id]
+        idle_timeout = 600  # 10 minutes without any real event
+        deadline = time.time() + idle_timeout
+        # After the main reply is done we keep the stream open for a short
+        # tail so async post-processing (TTS auto-synthesis) can deliver a
+        # `voice_attach` event before the client disconnects.
+        POST_DONE_TAIL_SECONDS = 60
+        post_done = False
+        post_deadline = 0.0
+
+        try:
+            while time.time() < deadline:
+                # Mark the stream alive on every loop. While the client keeps
+                # consuming, the generator runs and refreshes this, so the
+                # janitor won't reclaim a long-running but active stream.
+                self.sse_last_active[request_id] = time.time()
+                try:
+                    item = q.get(timeout=1)
+                except Empty:
+                    if post_done and time.time() >= post_deadline:
+                        break
+                    yield b": keepalive\n\n"
+                    continue
+
+                deadline = time.time() + idle_timeout
+                payload = json.dumps(item, ensure_ascii=False)
+                yield f"data: {payload}\n\n".encode("utf-8")
+
+                itype = item.get("type")
+                if itype == "done":
+                    post_done = True
+                    post_deadline = time.time() + POST_DONE_TAIL_SECONDS
+                elif itype == "cancelled":
+                    # Close SSE tail quickly after cancel; don't wait for the
+                    # full TTS tail since the user already pressed Stop.
+                    post_done = True
+                    post_deadline = time.time() + 3
+                elif itype == "voice_attach":
+                    # WSGI buffers the previous chunk until the next yield;
+                    # shrink the tail so the generator wakes up quickly to
+                    # emit a couple of keepalive comments that push the
+                    # voice_attach payload through to the browser.
+                    post_done = True
+                    post_deadline = time.time() + 2  # 2s post-attach tail
+        except GeneratorExit:
+            # Client disconnected (WSGI closed the generator). If the reply is
+            # already complete there is nothing to resume, so reclaim now to
+            # release the socket fd. Otherwise keep the queue briefly so a
+            # reconnect with the same request_id can resume; the janitor will
+            # reclaim it if no reconnect happens.
+            if post_done:
+                self._drop_sse_request(request_id)
+            raise
+        finally:
+            # Drop the queue once the reply is actually complete or the idle
+            # deadline has passed. Early client disconnects are handled by the
+            # GeneratorExit branch above and the background janitor.
+            if post_done or time.time() >= deadline:
+                self._drop_sse_request(request_id)
+
+    def cancel_request(self):
+        """
+        Cancel an in-flight agent run.
+
+        Body: {"request_id": "...", "session_id": "..."}
+        Either field is sufficient; request_id is preferred when known.
+        Always returns success even when nothing was running, so the
+        client's UX is idempotent.
+        """
+        try:
+            from agent.protocol import get_cancel_registry
+
+            data = web.data()
+            try:
+                json_data = json.loads(data) if data else {}
+            except Exception:
+                json_data = {}
+
+            request_id = (json_data.get("request_id") or "").strip()
+            session_id = (json_data.get("session_id") or "").strip()
+            lang = (json_data.get("lang") or "zh").lower()
+
+            registry = get_cancel_registry()
+            cancelled = 0
+
+            if request_id:
+                if registry.cancel_request(request_id):
+                    cancelled = 1
+
+            if cancelled == 0 and session_id:
+                cancelled = registry.cancel_session(session_id)
+
+            if request_id and request_id in self.sse_queues:
+                self.sse_queues[request_id].put({
+                    "type": "cancelled",
+                    "content": "🛑 Cancelled" if lang.startswith("en") else "🛑 已中止",
+                    "request_id": request_id,
+                    "timestamp": time.time(),
+                })
+
+            logger.info(
+                f"[WebChannel] cancel request: request_id={request_id!r}, "
+                f"session_id={session_id!r}, cancelled={cancelled}"
+            )
+            return json.dumps({
+                "status": "success",
+                "cancelled": cancelled,
+            })
+
+        except Exception as e:
+            logger.error(f"[WebChannel] cancel_request error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def poll_response(self):
+        """
+        Poll for responses using the session_id.
+        """
+        try:
+            data = web.data()
+            json_data = json.loads(data)
+            session_id = json_data.get('session_id')
+
+            if not session_id or session_id not in self.session_queues:
+                return json.dumps({"status": "error", "message": "Invalid session ID"})
+
+            # 尝试从队列获取响应，不等待
+            try:
+                # 使用peek而不是get，这样如果前端没有成功处理，下次还能获取到
+                response = self.session_queues[session_id].get(block=False)
+
+                # 返回响应，包含请求ID以区分不同请求
+                return json.dumps({
+                    "status": "success",
+                    "has_content": True,
+                    "content": response["content"],
+                    "request_id": response["request_id"],
+                    "timestamp": response["timestamp"]
+                })
+
+            except Empty:
+                # 没有新响应
+                return json.dumps({"status": "success", "has_content": False})
+
+        except Exception as e:
+            logger.error(f"Error polling response: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def chat_page(self):
+        """Serve the chat HTML page."""
+        file_path = os.path.join(os.path.dirname(__file__), 'chat.html')  # 使用绝对路径
+        with open(file_path, 'r', encoding='utf-8') as f:
+            html = f.read()
+        # Inject the backend-resolved default language so the console can use
+        # it on first load (when the user has no saved cow_lang preference).
+        return html.replace("{{COW_DEFAULT_LANG}}", i18n.get_language())
+
+    def startup(self):
+        configured_host = conf().get("web_host", "")
+        host = configured_host or ("0.0.0.0" if _is_password_enabled() else "127.0.0.1")
+        # The desktop app passes its chosen port via COW_WEB_PORT so its backend
+        # never collides with a source-run web console (default 9899). This makes
+        # the port a single source of truth owned by the Electron shell.
+        port = int(os.environ.get("COW_WEB_PORT") or conf().get("web_port", 9899))
+        is_public_bind = host in ("0.0.0.0", "::")
+
+        self._cleanup_stale_voice_recordings()
+
+        # Print available channel types (ordered by language: prioritize
+        # locally-popular channels for the current UI language)
+        logger.info(
+            "[WebChannel] Available channels (edit `channel_type` in config.json to switch, separate multiple with commas):")
+        zh_channels = [
+            ("web", "Web"),
+            ("terminal", "Terminal"),
+            ("weixin", "WeChat"),
+            ("feishu", "Feishu"),
+            ("dingtalk", "DingTalk"),
+            ("wecom_bot", "WeCom Bot"),
+            ("wechatcom_app", "WeCom App"),
+            ("wechat_kf", "WeChat Customer Service"),
+            ("wechatmp", "WeChat Official Account"),
+            ("wechatmp_service", "WeChat Official Account (Service)"),
+            ("telegram", "Telegram"),
+            ("slack", "Slack"),
+            ("discord", "Discord"),
+        ]
+        en_channels = [
+            ("web", "Web"),
+            ("terminal", "Terminal"),
+            ("telegram", "Telegram"),
+            ("slack", "Slack"),
+            ("discord", "Discord"),
+            ("weixin", "WeChat"),
+            ("feishu", "Feishu"),
+            ("dingtalk", "DingTalk"),
+            ("wecom_bot", "WeCom Bot"),
+            ("wechatcom_app", "WeCom App"),
+            ("wechat_kf", "WeChat Customer Service"),
+            ("wechatmp", "WeChat Official Account"),
+            ("wechatmp_service", "WeChat Official Account (Service)"),
+        ]
+        channels = en_channels if i18n.get_language() == "en" else zh_channels
+        name_width = max(len(name) for name, _ in channels)
+        for idx, (name, label) in enumerate(channels, 1):
+            logger.info(f"[WebChannel]  {idx:>2}. {name:<{name_width}} - {label}")
+        logger.info("[WebChannel] ✅ Web console is running")
+        logger.info(f"[WebChannel] 🌐 Local access: http://localhost:{port}")
+        if is_public_bind:
+            logger.info(f"[WebChannel] 🌍 Server access: http://YOUR_IP:{port} (replace YOUR_IP with your server IP)")
+            if not _is_password_enabled():
+                logger.info("[WebChannel] ⚠️  Listening on 0.0.0.0 without web_password set; set an access password in config.json for public deployment")
+        else:
+            logger.info(f"[WebChannel] 🔒 Listening on {host} only (local access). For public access, set web_host to 0.0.0.0 and configure web_password")
+
+        # In desktop mode the Electron shell renders the UI, so don't pop a
+        # browser window (also avoids issues when running detached/headless).
+        if os.environ.get("COW_DESKTOP") != "1":
+            try:
+                import webbrowser
+                webbrowser.open(f"http://localhost:{port}")
+                logger.debug(f"[WebChannel] Opened browser at http://localhost:{port}")
+            except Exception as e:
+                logger.debug(f"[WebChannel] Could not open browser: {e}")
+
+        # Ensure the static dir exists. In a packaged build it ships read-only
+        # inside the bundle, so swallow errors instead of failing startup.
+        static_dir = os.path.join(os.path.dirname(__file__), 'static')
+        if not os.path.exists(static_dir):
+            try:
+                os.makedirs(static_dir)
+                logger.debug(f"[WebChannel] Created static directory: {static_dir}")
+            except OSError as e:
+                logger.debug(f"[WebChannel] Skipped creating static dir (read-only bundle?): {e}")
+
+        urls = (
+            '/', 'RootHandler',
+            '/api/health', 'HealthHandler',
+            '/auth/login', 'AuthLoginHandler',
+            '/auth/check', 'AuthCheckHandler',
+            '/auth/logout', 'AuthLogoutHandler',
+            '/message', 'MessageHandler',
+            '/upload', 'UploadHandler',
+            '/uploads/(.*)', 'UploadsHandler',
+            '/api/file', 'FileServeHandler',
+            '/api/voice/asr', 'VoiceAsrHandler',
+            '/api/voice/tts', 'VoiceTtsHandler',
+            '/poll', 'PollHandler',
+            '/stream', 'StreamHandler',
+            '/cancel', 'CancelHandler',
+            '/chat', 'ChatHandler',
+            '/config', 'ConfigHandler',
+            '/api/models', 'ModelsHandler',
+            '/api/channels', 'ChannelsHandler',
+            '/api/weixin/qrlogin', 'WeixinQrHandler',
+            '/api/feishu/register', 'FeishuRegisterHandler',
+            '/api/tools', 'ToolsHandler',
+            '/api/skills', 'SkillsHandler',
+            '/api/memory', 'MemoryHandler',
+            '/api/memory/content', 'MemoryContentHandler',
+            '/api/knowledge/list', 'KnowledgeListHandler',
+            '/api/knowledge/read', 'KnowledgeReadHandler',
+            '/api/knowledge/graph', 'KnowledgeGraphHandler',
+            '/api/knowledge/action', 'KnowledgeActionHandler',
+            '/api/knowledge/import', 'KnowledgeImportHandler',
+            '/api/scheduler', 'SchedulerHandler',
+            '/api/scheduler/toggle', 'SchedulerToggleHandler',
+            '/api/scheduler/update', 'SchedulerUpdateHandler',
+            '/api/scheduler/delete', 'SchedulerDeleteHandler',
+            '/api/sessions', 'SessionsHandler',
+            '/api/sessions/(.*)/generate_title', 'SessionTitleHandler',
+            '/api/sessions/(.*)/clear_context', 'SessionClearContextHandler',
+            '/api/sessions/(.*)', 'SessionDetailHandler',
+            '/api/history', 'HistoryHandler',
+            '/api/messages/delete', 'MessageDeleteHandler',
+            '/api/logs', 'LogsHandler',
+            '/api/version', 'VersionHandler',
+            '/mcp/oauth/callback', 'McpOAuthCallbackHandler',
+            '/assets/(.*)', 'AssetsHandler',
+        )
+        app = web.application(urls, globals(), autoreload=False)
+
+        # 完全禁用web.py的HTTP日志输出
+        web.httpserver.LogMiddleware.log = lambda self, status, environ: None
+
+        # 配置web.py的日志级别为ERROR
+        logging.getLogger("web").setLevel(logging.ERROR)
+        logging.getLogger("web.httpserver").setLevel(logging.ERROR)
+
+        # Build WSGI app with middleware (same as runsimple but without print)
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer((host, port), func)
+        server.daemon_threads = True
+        # Default request_queue_size(5) / timeout(10s) / numthreads(10) are
+        # too small: when SSE streams occupy many threads, the backlog fills
+        # and new connections get refused (ERR_CONNECTION_ABORTED).
+        server.request_queue_size = 128
+        server.timeout = 300
+        server.requests.min = 20
+        server.requests.max = 80
+        self._http_server = server
+        # Reclaim orphaned SSE queues so disconnected clients don't leak fds.
+        self._start_sse_janitor()
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+        except OSError as e:
+            if e.errno in (48, 98):  # macOS/Linux EADDRINUSE
+                logger.error(
+                    f"[WebChannel] 端口 {port} 已被占用，可执行 `cow restart` 清理残留进程，"
+                    f"或在 config.json 中修改 web_port"
+                )
+            raise
+
+    def stop(self):
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[WebChannel] HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[WebChannel] Error stopping HTTP server: {e}")
+            self._http_server = None
+
+
+class RootHandler:
+    def GET(self):
+        raise web.seeother('/chat')
+
+
+class HealthHandler:
+    # Unauthenticated liveness probe. The desktop shell polls this to know the
+    # backend is up; it must never require auth (a set web_password would
+    # otherwise make startup hang). Returns no sensitive data.
+    def GET(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        web.header('Cache-Control', 'no-store')
+        return json.dumps({"status": "ok"})
+
+
+class McpOAuthCallbackHandler:
+    """OAuth redirect target for MCP servers requiring authorization.
+
+    The browser lands here after the user authorizes a remote MCP server.
+    We exchange the authorization code for tokens and bring the server
+    online. Unauthenticated by design: the OAuth `state` param is the
+    single-use secret that binds this request to a pending authorization.
+    """
+
+    def GET(self):
+        web.header('Content-Type', 'text/html; charset=utf-8')
+        params = web.input(code="", state="", error="", error_description="")
+
+        def _page(title: str, message: str) -> str:
+            return (
+                "<!doctype html><html><head><meta charset='utf-8'>"
+                "<meta name='viewport' content='width=device-width,initial-scale=1'>"
+                f"<title>{title}</title></head>"
+                "<body style='font-family:-apple-system,Segoe UI,Roboto,sans-serif;"
+                "max-width:520px;margin:64px auto;padding:0 20px;text-align:center;color:#1f2328'>"
+                f"<h2>{title}</h2><p style='color:#57606a'>{message}</p></body></html>"
+            )
+
+        if params.error:
+            logger.warning(f"[MCP-OAuth] callback error: {params.error} {params.error_description}")
+            return _page("授权失败", f"{params.error}: {params.error_description or ''}")
+
+        if not params.code or not params.state:
+            return _page("参数缺失", "回调缺少 code 或 state 参数。")
+
+        try:
+            from agent.tools.mcp.mcp_oauth import pop_pending
+            from agent.tools.mcp.mcp_client import notify_server_authorized
+        except Exception as e:
+            logger.warning(f"[MCP-OAuth] callback import failed: {e}")
+            return _page("内部错误", "OAuth 模块不可用。")
+
+        handler = pop_pending(params.state)
+        if handler is None:
+            return _page("会话已过期", "授权请求不存在或已过期，请重新触发授权。")
+
+        try:
+            ok = handler.finish_authorization(params.code)
+        except Exception as e:
+            logger.warning(f"[MCP-OAuth] token exchange crashed: {e}")
+            ok = False
+
+        if not ok:
+            return _page("授权失败", "换取令牌失败，请重试。")
+
+        notify_server_authorized(handler.server_name)
+        logger.info(f"[MCP-OAuth] Server '{handler.server_name}' authorized via web callback")
+        return _page(
+            "授权成功",
+            f"MCP 服务 “{handler.server_name}” 已授权，可以返回聊天继续使用了。",
+        )
+
+
+class AuthCheckHandler:
+    def GET(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        if not _is_password_enabled():
+            return json.dumps({"status": "success", "auth_required": False})
+        if _check_auth():
+            return json.dumps({"status": "success", "auth_required": True, "authenticated": True})
+        return json.dumps({"status": "success", "auth_required": True, "authenticated": False})
+
+
+class AuthLoginHandler:
+    def POST(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        if not _is_password_enabled():
+            return json.dumps({"status": "success"})
+        try:
+            data = json.loads(web.data())
+        except Exception:
+            return json.dumps({"status": "error", "message": "Invalid request"})
+        password = str(data.get("password", "") or "")
+        expected = _get_web_password()
+        if not hmac.compare_digest(password, expected):
+            logger.warning("[WebChannel] Invalid login attempt")
+            return json.dumps({"status": "error", "message": "Wrong password"})
+        token = _create_auth_token()
+        web.setcookie("cow_auth_token", token, expires=_session_expire_seconds(),
+                       path="/", httponly=True, samesite="Lax")
+        # Also return the token in the body: the desktop client (file:// origin)
+        # can't rely on the cookie and sends it back via an Authorization header.
+        return json.dumps({"status": "success", "token": token})
+
+
+class AuthLogoutHandler:
+    def POST(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        web.setcookie("cow_auth_token", "", expires=-1, path="/")
+        return json.dumps({"status": "success"})
+
+
+class MessageHandler:
+    def POST(self):
+        _require_auth()
+        return WebChannel().post_message()
+
+
+class UploadHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        return WebChannel().upload_file()
+
+
+class VoiceAsrHandler:
+    """Receive a mic recording, persist it under uploads/ and run ASR.
+    Returns {status, text, audio_url} so the UI can render a playback bubble."""
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+
+        saved_path = None
+        try:
+            params = _raw_web_input()
+            file_obj = params.get("file")
+            if file_obj is None:
+                return json.dumps({"status": "error", "message": "no audio file"})
+
+            filename = getattr(file_obj, "filename", "") or "recording.webm"
+            ext = os.path.splitext(filename)[1].lower() or ".webm"
+            if ext not in (".webm", ".ogg", ".opus", ".mp4", ".m4a", ".mp3", ".wav"):
+                ext = ".webm"
+
+            upload_dir = _get_upload_dir()
+            os.makedirs(upload_dir, exist_ok=True)
+            ts = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+            saved_name = f"voice_input_{ts}_{random.randint(0, 9999)}{ext}"
+            saved_path = os.path.join(upload_dir, saved_name)
+            with open(saved_path, "wb") as f:
+                f.write(file_obj.file.read() if hasattr(file_obj, "file") else file_obj.value)
+
+            audio_url = f"/uploads/{saved_name}"
+
+            from bridge.bridge import Bridge
+            reply = Bridge().fetch_voice_to_text(saved_path)
+            if reply is None:
+                return json.dumps({
+                    "status": "error",
+                    "message": "ASR returned no reply",
+                    "audio_url": audio_url,
+                })
+
+            from bridge.reply import ReplyType
+            if reply.type == ReplyType.TEXT:
+                return json.dumps({
+                    "status": "success",
+                    "text": reply.content or "",
+                    "audio_url": audio_url,
+                })
+            return json.dumps({
+                "status": "error",
+                "message": reply.content or "ASR failed",
+                "audio_url": audio_url,
+            })
+        except Exception as e:
+            logger.exception(f"[VoiceAsrHandler] failed: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class VoiceTtsHandler:
+    """On-demand TTS for the in-chat "read aloud" button. Returns the
+    audio URL and (when session_id is given) persists it onto the message."""
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            data = json.loads(web.data() or b"{}")
+            text = (data.get("text") or "").strip()
+            session_id = (data.get("session_id") or "").strip()
+            if not text:
+                return json.dumps({"status": "error", "message": "empty text"})
+            # `@singleton` makes WebChannel a factory function — go via instance.
+            channel = WebChannel()
+            if not channel._tts_provider_ready():
+                return json.dumps({"status": "error", "message": "tts not configured"})
+
+            from bridge.bridge import Bridge
+            reply = Bridge().fetch_text_to_voice(text)
+            if reply is None or reply.type != ReplyType.VOICE or not reply.content:
+                msg = getattr(reply, "content", "") or "tts failed"
+                return json.dumps({"status": "error", "message": str(msg)})
+
+            url = channel._publish_tts_audio(reply.content)
+            if not url:
+                return json.dumps({"status": "error", "message": "publish failed"})
+
+            if session_id:
+                try:
+                    from agent.memory import get_conversation_store
+                    get_conversation_store().attach_extras_to_last_assistant(
+                        session_id, {"audio": {"url": url, "kind": "tts"}},
+                    )
+                except Exception as e:
+                    logger.debug(f"[VoiceTtsHandler] persist skipped: {e}")
+
+            return json.dumps({"status": "success", "audio_url": url})
+        except Exception as e:
+            logger.exception(f"[VoiceTtsHandler] failed: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class UploadsHandler:
+    def GET(self, file_name):
+        _require_auth()
+        try:
+            upload_dir = _get_upload_dir()
+            full_path = os.path.normpath(os.path.join(upload_dir, file_name))
+            if not os.path.abspath(full_path).startswith(os.path.abspath(upload_dir)):
+                raise web.notfound()
+            if not os.path.isfile(full_path):
+                raise web.notfound()
+            content_type = mimetypes.guess_type(full_path)[0] or "application/octet-stream"
+            web.header('Content-Type', content_type)
+            web.header('Cache-Control', 'public, max-age=86400')
+            with open(full_path, 'rb') as f:
+                return f.read()
+        except web.HTTPError:
+            raise
+        except Exception as e:
+            logger.error(f"[WebChannel] Error serving upload: {e}")
+            raise web.notfound()
+
+
+class FileServeHandler:
+    def GET(self):
+        _require_auth()
+        try:
+            params = web.input(path="")
+            file_path = params.path
+            if not file_path or not os.path.isabs(file_path):
+                raise web.notfound()
+            # Resolve symlinks and confine access to the allowed root dirs,
+            # so this endpoint can't be abused to read arbitrary files (e.g. /etc/passwd, ~/.ssh).
+            # Defaults to the user home dir plus the agent workspace; set web_file_serve_root="/"
+            # to allow the whole filesystem.
+            file_path = os.path.realpath(file_path)
+            serve_root = conf().get("web_file_serve_root", "~") or "~"
+            allowed_roots = [
+                os.path.realpath(os.path.expanduser(serve_root)),
+                os.path.realpath(os.path.expanduser(conf().get("agent_workspace", "~/cow"))),
+            ]
+            if os.sep not in allowed_roots and not any(
+                os.path.commonpath([file_path, root]) == root for root in allowed_roots
+            ):
+                raise web.notfound()
+            if not os.path.isfile(file_path):
+                raise web.notfound()
+            content_type = mimetypes.guess_type(file_path)[0] or "application/octet-stream"
+            file_name = os.path.basename(file_path)
+            from urllib.parse import quote
+            web.header('Content-Type', content_type)
+            web.header('Content-Disposition', f"inline; filename*=UTF-8''{quote(file_name)}")
+            web.header('Cache-Control', 'public, max-age=3600')
+            with open(file_path, 'rb') as f:
+                return f.read()
+        except web.HTTPError:
+            raise
+        except Exception as e:
+            logger.error(f"[WebChannel] Error serving file: {e}")
+            raise web.notfound()
+
+
+class PollHandler:
+    def POST(self):
+        _require_auth()
+        return WebChannel().poll_response()
+
+
+class CancelHandler:
+    def POST(self):
+        _require_auth()
+        return WebChannel().cancel_request()
+
+
+class StreamHandler:
+    def GET(self):
+        _require_auth()
+        params = web.input(request_id='')
+        request_id = params.request_id
+        if not request_id:
+            raise web.badrequest()
+
+        web.header('Content-Type', 'text/event-stream; charset=utf-8')
+        web.header('Cache-Control', 'no-cache')
+        web.header('X-Accel-Buffering', 'no')
+        web.header('Access-Control-Allow-Origin', '*')
+
+        return WebChannel().stream_response(request_id)
+
+
+class ChatHandler:
+    def GET(self):
+        web.header('Cache-Control', 'no-cache, no-store, must-revalidate')
+        web.header('Pragma', 'no-cache')
+        file_path = os.path.join(os.path.dirname(__file__), 'chat.html')
+        with open(file_path, 'r', encoding='utf-8') as f:
+            html = f.read()
+        cache_bust = str(int(time.time()))
+        html = html.replace('assets/js/console.js', f'assets/js/console.js?v={cache_bust}')
+        html = html.replace('assets/css/console.css', f'assets/css/console.css?v={cache_bust}')
+        # Inject the backend-resolved default language for first-load fallback.
+        html = html.replace("{{COW_DEFAULT_LANG}}", i18n.get_language())
+        return html
+
+
+class ConfigHandler:
+
+    _RECOMMENDED_MODELS = [
+        const.DEEPSEEK_V4_FLASH, const.DEEPSEEK_V4_PRO,
+        const.MINIMAX_M3, const.MINIMAX_M2_7_HIGHSPEED, const.MINIMAX_M2_7,
+        # claude-sonnet-5 is the Claude default; claude-fable-5 is dropped
+        # from this web console list for now.
+        const.CLAUDE_SONNET_5, const.CLAUDE_4_8_OPUS, const.CLAUDE_4_7_OPUS, const.CLAUDE_4_6_SONNET, const.CLAUDE_4_6_OPUS,
+        const.GEMINI_35_FLASH, const.GEMINI_31_FLASH_LITE_PRE, const.GEMINI_31_PRO_PRE, const.GEMINI_3_FLASH_PRE,
+        const.GPT_55, const.GPT_54, const.GPT_54_MINI, const.GPT_54_NANO, const.GPT_5, const.GPT_41, const.GPT_4o,
+        const.GLM_5_2, const.GLM_5_1, const.GLM_5_TURBO, const.GLM_5, const.GLM_4_7,
+        const.QWEN37_PLUS, const.QWEN37_MAX, const.QWEN36_PLUS,
+        const.DOUBAO_SEED_2_1_PRO, const.DOUBAO_SEED_2_1_TURBO, const.DOUBAO_SEED_2_CODE,
+        const.KIMI_K2_7_CODE, const.KIMI_K2_7_CODE_HIGHSPEED, const.KIMI_K2_6, const.KIMI_K2_5, const.KIMI_K2,
+        const.ERNIE_5_1, const.ERNIE_5, const.ERNIE_X1_1, const.ERNIE_45_TURBO_128K, const.ERNIE_45_TURBO_32K,
+        const.MIMO_V2_5_PRO, const.MIMO_V2_5,
+    ]
+
+    # Generic placeholder hints surfaced in the web console. We deliberately
+    # show the version-path tail (e.g. "/v1") so users are reminded to type
+    # the full base URL. The form is intentionally vague (`...../v1`) so it
+    # never looks like a real default a user might paste verbatim — and we
+    # never auto-rewrite anything on the server side.
+    _PLACEHOLDER_V1 = "https://...../v1"
+    _PLACEHOLDER_QIANFAN = "https://...../v2"
+    _PLACEHOLDER_ZHIPU = "https://...../api/paas/v4"
+    _PLACEHOLDER_DOUBAO = "https://...../api/v3"
+    _PLACEHOLDER_GEMINI = "https://....."
+
+    PROVIDER_MODELS = OrderedDict([
+        ("deepseek", {
+            "label": "DeepSeek",
+            "api_key_field": "deepseek_api_key",
+            "api_base_key": "deepseek_api_base",
+            "api_base_default": "https://api.deepseek.com/v1",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [const.DEEPSEEK_V4_FLASH, const.DEEPSEEK_V4_PRO, const.DEEPSEEK_CHAT, const.DEEPSEEK_REASONER],
+        }),
+        ("minimax", {
+            "label": "MiniMax",
+            "api_key_field": "minimax_api_key",
+            "api_base_key": None,
+            "api_base_default": None,
+            "api_base_placeholder": "",
+            "models": [const.MINIMAX_M3, const.MINIMAX_M2_7, const.MINIMAX_M2_7_HIGHSPEED],
+        }),
+        ("claudeAPI", {
+            "label": "Claude",
+            "api_key_field": "claude_api_key",
+            "api_base_key": "claude_api_base",
+            "api_base_default": "https://api.anthropic.com/v1",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [const.CLAUDE_SONNET_5, const.CLAUDE_4_8_OPUS, const.CLAUDE_4_7_OPUS, const.CLAUDE_4_6_SONNET, const.CLAUDE_4_6_OPUS],
+        }),
+        ("gemini", {
+            "label": "Gemini",
+            "api_key_field": "gemini_api_key",
+            "api_base_key": "gemini_api_base",
+            "api_base_default": "https://generativelanguage.googleapis.com",
+            "api_base_placeholder": _PLACEHOLDER_GEMINI,
+            "models": [const.GEMINI_35_FLASH, const.GEMINI_31_FLASH_LITE_PRE, const.GEMINI_31_PRO_PRE, const.GEMINI_3_FLASH_PRE],
+        }),
+        ("openai", {
+            "label": "OpenAI",
+            "api_key_field": "open_ai_api_key",
+            "api_base_key": "open_ai_api_base",
+            "api_base_default": "https://api.openai.com/v1",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [const.GPT_55, const.GPT_54, const.GPT_54_MINI, const.GPT_54_NANO, const.GPT_5, const.GPT_41, const.GPT_4o],
+        }),
+        ("zhipu", {
+            "label": {"zh": "智谱AI", "en": "GLM"},
+            "api_key_field": "zhipu_ai_api_key",
+            "api_base_key": "zhipu_ai_api_base",
+            "api_base_default": "https://open.bigmodel.cn/api/paas/v4",
+            "api_base_placeholder": _PLACEHOLDER_ZHIPU,
+            "models": [const.GLM_5_2, const.GLM_5_1, const.GLM_5_TURBO, const.GLM_5, const.GLM_4_7],
+        }),
+        ("dashscope", {
+            "label": {"zh": "通义千问", "en": "Qwen"},
+            "api_key_field": "dashscope_api_key",
+            "api_base_key": None,
+            "api_base_default": None,
+            "api_base_placeholder": "",
+            "models": [const.QWEN37_PLUS, const.QWEN37_MAX, const.QWEN36_PLUS],
+        }),
+        ("doubao", {
+            "label": {"zh": "豆包", "en": "Doubao"},
+            "api_key_field": "ark_api_key",
+            "api_base_key": "ark_base_url",
+            "api_base_default": "https://ark.cn-beijing.volces.com/api/v3",
+            "api_base_placeholder": _PLACEHOLDER_DOUBAO,
+            "models": [const.DOUBAO_SEED_2_1_PRO, const.DOUBAO_SEED_2_1_TURBO, const.DOUBAO_SEED_2_PRO, const.DOUBAO_SEED_2_CODE],
+        }),
+        ("moonshot", {
+            "label": "Kimi",
+            "api_key_field": "moonshot_api_key",
+            "api_base_key": "moonshot_base_url",
+            "api_base_default": "https://api.moonshot.cn/v1",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [const.KIMI_K2_7_CODE, const.KIMI_K2_7_CODE_HIGHSPEED, const.KIMI_K2_6, const.KIMI_K2_5, const.KIMI_K2],
+        }),
+        ("qianfan", {
+            "label": {"zh": "百度千帆", "en": "ERNIE"},
+            "api_key_field": "qianfan_api_key",
+            "api_base_key": "qianfan_api_base",
+            "api_base_default": "https://qianfan.baidubce.com/v2",
+            "api_base_placeholder": _PLACEHOLDER_QIANFAN,
+            "models": [const.ERNIE_5_1, const.ERNIE_5, const.ERNIE_X1_1, const.ERNIE_45_TURBO_128K, const.ERNIE_45_TURBO_32K],
+        }),
+        ("mimo", {
+            "label": {"zh": "小米 MiMo", "en": "MiMo"},
+            "api_key_field": "mimo_api_key",
+            "api_base_key": "mimo_api_base",
+            "api_base_default": "https://api.xiaomimimo.com/v1",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [const.MIMO_V2_5_PRO, const.MIMO_V2_5],
+        }),
+        ("linkai", {
+            "label": "LinkAI",
+            "api_key_field": "linkai_api_key",
+            "api_base_key": None,
+            "api_base_default": None,
+            "api_base_placeholder": "",
+            "models": _RECOMMENDED_MODELS,
+        }),
+        ("custom", {
+            "label": {"zh": "自定义", "en": "Custom"},
+            "api_key_field": "custom_api_key",
+            "api_base_key": "custom_api_base",
+            "api_base_default": "",
+            "api_base_placeholder": _PLACEHOLDER_V1,
+            "models": [],
+        }),
+    ])
+
+    EDITABLE_KEYS = {
+        "cow_lang",
+        "model", "bot_type", "use_linkai",
+        "open_ai_api_base", "deepseek_api_base", "qianfan_api_base", "claude_api_base", "gemini_api_base",
+        "zhipu_ai_api_base", "moonshot_base_url", "ark_base_url", "custom_api_base", "mimo_api_base",
+        "open_ai_api_key", "deepseek_api_key", "qianfan_api_key", "claude_api_key", "gemini_api_key",
+        "zhipu_ai_api_key", "dashscope_api_key", "moonshot_api_key",
+        "ark_api_key", "minimax_api_key", "linkai_api_key", "custom_api_key", "mimo_api_key",
+        "custom_providers",
+        "agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps",
+        "enable_thinking", "self_evolution_enabled", "web_password",
+    }
+
+    @staticmethod
+    def _mask_key(value: str) -> str:
+        """Mask the middle part of an API key for display."""
+        if not value or len(value) <= 8:
+            return value
+        return value[:4] + "*" * (len(value) - 8) + value[-4:]
+
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            local_config = conf()
+            use_agent = local_config.get("agent", True)
+            title = "CowAgent" if use_agent else "AI Assistant"
+
+            api_bases = {}
+            api_keys_masked = {}
+            for pid, pinfo in self.PROVIDER_MODELS.items():
+                base_key = pinfo.get("api_base_key")
+                if base_key:
+                    api_bases[base_key] = local_config.get(base_key, pinfo["api_base_default"])
+                key_field = pinfo.get("api_key_field")
+                if key_field and key_field not in api_keys_masked:
+                    raw = local_config.get(key_field, "")
+                    api_keys_masked[key_field] = self._mask_key(raw) if raw else ""
+
+            providers = {}
+            for pid, p in self.PROVIDER_MODELS.items():
+                providers[pid] = {
+                    "label": p["label"],
+                    "models": p["models"],
+                    "api_base_key": p["api_base_key"],
+                    "api_base_default": p["api_base_default"],
+                    "api_base_placeholder": p.get("api_base_placeholder", ""),
+                    "api_key_field": p.get("api_key_field"),
+                }
+
+            # Expose user-defined custom providers as "custom:<id>" entries so
+            # the legacy config page can display and select them. Credentials
+            # are managed on the Models page, hence the null key/base fields.
+            # Mirrors the Models page: when expanded entries exist, the bare
+            # legacy "custom" entry is hidden — unless the flat single-provider
+            # custom config is still active or filled in.
+            try:
+                from models.custom_provider import get_custom_providers
+                custom_list = get_custom_providers()
+                legacy_custom_in_use = ModelsHandler._legacy_custom_in_use(local_config)
+                if custom_list and not legacy_custom_in_use:
+                    providers.pop("custom", None)
+                for cp in custom_list:
+                    cid = f"custom:{cp.get('id')}"
+                    cname = cp.get("name") or cp.get("id")
+                    providers[cid] = {
+                        "label": {"zh": cname, "en": cname},
+                        "models": [cp["model"]] if cp.get("model") else [],
+                        "api_base_key": None,
+                        "api_base_default": None,
+                        "api_base_placeholder": "",
+                        "api_key_field": None,
+                    }
+            except Exception as cp_err:
+                logger.warning(f"[ConfigHandler] failed to expand custom providers: {cp_err}")
+
+            raw_pwd = str(local_config.get("web_password", "") or "")
+            masked_pwd = ("*" * len(raw_pwd)) if raw_pwd else ""
+
+            result = {
+                "status": "success",
+                "use_agent": use_agent,
+                "title": title,
+                "model": local_config.get("model", ""),
+                "bot_type": "openai" if local_config.get("bot_type") == "chatGPT" else local_config.get("bot_type", ""),
+                "use_linkai": bool(local_config.get("use_linkai", False)),
+                "channel_type": local_config.get("channel_type", ""),
+                "agent_max_context_tokens": local_config.get("agent_max_context_tokens", 50000),
+                "agent_max_context_turns": local_config.get("agent_max_context_turns", 20),
+                "agent_max_steps": local_config.get("agent_max_steps", 20),
+                "enable_thinking": bool(local_config.get("enable_thinking", False)),
+                "self_evolution_enabled": bool(local_config.get("self_evolution_enabled", False)),
+                "api_bases": api_bases,
+                "api_keys": api_keys_masked,
+                "providers": providers,
+                "web_password_masked": masked_pwd,
+            }
+            # The desktop app runs on the local trusted machine, so it can edit
+            # the real password in place (cursor at the end, delete to clear).
+            # Browser access only ever sees the masked value.
+            if os.environ.get("COW_DESKTOP") == "1":
+                result["web_password"] = raw_pwd
+            return json.dumps(result, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"Error getting config: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            data = json.loads(web.data())
+            updates = data.get("updates", {})
+            if not updates:
+                return json.dumps({"status": "error", "message": "no updates provided"})
+
+            local_config = conf()
+            applied = {}
+            for key, value in updates.items():
+                if key not in self.EDITABLE_KEYS:
+                    continue
+                if key in ("agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps"):
+                    value = int(value)
+                if key in ("use_linkai", "enable_thinking", "self_evolution_enabled"):
+                    value = bool(value)
+                local_config[key] = value
+                applied[key] = value
+
+            if not applied:
+                return json.dumps({"status": "error", "message": "no valid keys to update"})
+
+            config_path = os.path.join(get_data_root(), "config.json")
+            old_password = ""  # Store old password before update
+            if os.path.exists(config_path):
+                with open(config_path, "r", encoding="utf-8") as f:
+                    file_cfg = json.load(f)
+                    # Capture old password before updating
+                    if "web_password" in applied:
+                        old_password = file_cfg.get("web_password", "")
+            else:
+                file_cfg = {}
+            file_cfg.update(applied)
+            with open(config_path, "w", encoding="utf-8") as f:
+                json.dump(file_cfg, f, indent=4, ensure_ascii=False)
+
+            logger.info(f"[WebChannel] Config updated: {list(applied.keys())}")
+
+            # Apply a language change immediately so backend logs, agent
+            # replies and CLI output switch without a restart.
+            if "cow_lang" in applied:
+                try:
+                    i18n.resolve_language(applied["cow_lang"])
+                    logger.info(f"[WebChannel] Language switched to: {i18n.get_language()}")
+                except Exception as lang_err:
+                    logger.warning(f"[WebChannel] Failed to apply language: {lang_err}")
+
+            # Check if password was cleared: if there was a password before clearing,
+            # the service is likely bound to 0.0.0.0 (public), so warn the user.
+            password_warning = None
+            if "web_password" in applied:
+                new_password = applied["web_password"]
+                configured_host = file_cfg.get("web_host", "")
+                
+                # If password was cleared and there was a password before
+                if not new_password and old_password:
+                    # If web_host is not explicitly set, the service auto-binds based on password
+                    # With password → 0.0.0.0 (public), without password → 127.0.0.1 (local)
+                    # So clearing password when it was previously set means going from public to local
+                    if not configured_host or configured_host == "0.0.0.0":
+                        password_warning = "password_cleared_with_public_host"
+                        logger.warning(
+                            "[WebChannel] Password cleared while service is likely bound to 0.0.0.0. "
+                            "Consider restarting the service to rebind to 127.0.0.1 "
+                            "or explicitly set web_host in config to prevent unauthorized access."
+                        )
+
+            # Reset Bridge so that bot routing reflects the new config.
+            # Without this, Bridge keeps its cached bot instance (e.g. LinkAIBot)
+            # even after the user switches bot_type / use_linkai / model in UI.
+            bridge_routing_keys = {"bot_type", "use_linkai", "model"}
+            if any(k in applied for k in bridge_routing_keys):
+                try:
+                    from bridge.bridge import Bridge
+                    Bridge().reset_bot()
+                    logger.info("[WebChannel] Bridge bot routing reset due to config change")
+                except Exception as reset_err:
+                    logger.warning(f"[WebChannel] Failed to reset bridge: {reset_err}")
+
+            return json.dumps({"status": "success", "applied": applied, "warning": password_warning}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"Error updating config: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class ModelsHandler:
+    """API for the unified Models console.
+
+    Layered model:
+      Layer 1 (providers): vendor credentials shared across capabilities.
+                            Stored as flat *_api_key / *_api_base fields in
+                            config.json — the same fields ConfigHandler
+                            already manages.
+      Layer 2 (capabilities): which provider/model is used by chat / vision /
+                            asr / tts / embedding / image / search.
+
+    GET  /api/models           -> overview (providers + capabilities)
+    POST /api/models/provider  -> upsert a vendor credential
+    DELETE /api/models/provider -> clear a vendor credential
+    POST /api/models/capability -> set provider/model for a capability
+    """
+
+    # Capability -> provider ids drawn from ConfigHandler.PROVIDER_MODELS.
+    _ASR_PROVIDERS = ["openai", "dashscope", "zhipu", "linkai"]
+    # Web-console white-list. Other vendors stay usable via direct config.
+    _TTS_PROVIDERS = ["openai", "minimax", "dashscope", "mimo", "linkai"]
+
+    # TTS engine catalog (speech models, not voice timbres). Entries are
+    # either a bare code or {value, hint?} when a friendly label helps.
+    _TTS_PROVIDER_MODELS = {
+        "openai":    ["tts-1", "tts-1-hd", "gpt-4o-mini-tts"],
+        "minimax": [
+            {"value": "speech-2.8-hd",    "hint": "情绪渲染融合语气词,自然听感"},
+            {"value": "speech-2.8-turbo", "hint": "极致生成速度,更自然逼真"},
+            {"value": "speech-2.6-hd",    "hint": "超低延时,归一化升级"},
+            {"value": "speech-2.6-turbo", "hint": "更快更便宜,适合语音聊天/数字人"},
+        ],
+        "dashscope": [
+            {"value": "qwen3-tts-flash", "hint": "覆盖普通话、方言与主流外语"},
+        ],
+        # 小米 MiMo TTS 系列，通过 chat completions 接口合成
+        "mimo": [
+            {"value": "mimo-v2.5-tts", "hint": "预置音色 · 支持唱歌模式"},
+        ],
+        # Aggregating gateway: a single endpoint multiplexes several
+        # underlying TTS engines, selected via the `model` field.
+        # Each engine exposes its own voice catalog (see _TTS_PROVIDER_VOICES).
+        "linkai": [
+            {"value": "tts-1",  "hint": "OpenAI · 多语种通用"},
+            {"value": "doubao", "hint": "字节豆包 · 中文音色丰富"},
+            {"value": "baidu",  "hint": "百度 · 中文主播音色"},
+        ],
+    }
+
+    # ASR engine catalog per provider. The first entry of each list is the
+    # runtime default (mirrors DEFAULT_ASR_MODEL in voice/*). Users can still
+    # pick "custom" in the UI to send any other model id.
+    _ASR_PROVIDER_MODELS = {
+        "openai": [
+            {"value": "gpt-4o-mini-transcribe", "hint": "默认 · 速度快"},
+            {"value": "gpt-4o-transcribe",      "hint": "更高准确率"},
+            {"value": "whisper-1",              "hint": "经典 Whisper"},
+        ],
+        "dashscope": [
+            {"value": "qwen3-asr-flash", "hint": "覆盖普通话、方言与主流外语"},
+        ],
+        "zhipu": [
+            {"value": "glm-asr-2512", "hint": "智谱语音识别"},
+        ],
+        # LinkAI gateway pins whisper-1 for ASR and ignores any other id,
+        # so expose only that to avoid misleading the user.
+        "linkai": [
+            {"value": "whisper-1", "hint": "网关固定使用"},
+        ],
+    }
+
+    # Per-provider voice timbres. Entries can be a bare code string
+    # (label = code) or {value, hint?} when a friendly secondary label
+    # helps recognition. We keep `value` as the raw API code so power
+    # users can cross-reference config.json.
+    _TTS_PROVIDER_VOICES = {
+        "openai":    [
+            "alloy", "echo", "fable", "onyx", "nova", "shimmer",
+            "ash", "ballad", "coral", "sage", "verse",
+        ],
+        "minimax": [
+            # Mandarin Chinese (full catalog)
+            {"value": "male-qn-qingse",                           "hint": "中文 · 青涩青年（男）"},
+            {"value": "male-qn-jingying",                         "hint": "中文 · 精英青年（男）"},
+            {"value": "male-qn-badao",                            "hint": "中文 · 霸道青年（男）"},
+            {"value": "male-qn-daxuesheng",                       "hint": "中文 · 青年大学生（男）"},
+            {"value": "female-shaonv",                            "hint": "中文 · 少女（女）"},
+            {"value": "female-yujie",                             "hint": "中文 · 御姐（女）"},
+            {"value": "female-chengshu",                          "hint": "中文 · 成熟女性（女）"},
+            {"value": "female-tianmei",                           "hint": "中文 · 甜美女性（女）"},
+            {"value": "male-qn-qingse-jingpin",                   "hint": "中文 · 青涩青年-beta（男）"},
+            {"value": "male-qn-jingying-jingpin",                 "hint": "中文 · 精英青年-beta（男）"},
+            {"value": "male-qn-badao-jingpin",                    "hint": "中文 · 霸道青年-beta（男）"},
+            {"value": "male-qn-daxuesheng-jingpin",               "hint": "中文 · 青年大学生-beta（男）"},
+            {"value": "female-shaonv-jingpin",                    "hint": "中文 · 少女-beta（女）"},
+            {"value": "female-yujie-jingpin",                     "hint": "中文 · 御姐-beta（女）"},
+            {"value": "female-chengshu-jingpin",                  "hint": "中文 · 成熟女性-beta（女）"},
+            {"value": "female-tianmei-jingpin",                   "hint": "中文 · 甜美女性-beta（女）"},
+            {"value": "clever_boy",                               "hint": "中文 · 聪明男童"},
+            {"value": "cute_boy",                                 "hint": "中文 · 可爱男童"},
+            {"value": "lovely_girl",                              "hint": "中文 · 萌萌女童"},
+            {"value": "cartoon_pig",                              "hint": "中文 · 卡通猪小琪"},
+            {"value": "bingjiao_didi",                            "hint": "中文 · 病娇弟弟"},
+            {"value": "junlang_nanyou",                           "hint": "中文 · 俊朗男友"},
+            {"value": "chunzhen_xuedi",                           "hint": "中文 · 纯真学弟"},
+            {"value": "lengdan_xiongzhang",                       "hint": "中文 · 冷淡学长"},
+            {"value": "badao_shaoye",                             "hint": "中文 · 霸道少爷"},
+            {"value": "tianxin_xiaoling",                         "hint": "中文 · 甜心小玲"},
+            {"value": "qiaopi_mengmei",                           "hint": "中文 · 俏皮萌妹"},
+            {"value": "wumei_yujie",                              "hint": "中文 · 妩媚御姐"},
+            {"value": "diadia_xuemei",                            "hint": "中文 · 嗲嗲学妹"},
+            {"value": "danya_xuejie",                             "hint": "中文 · 淡雅学姐"},
+            {"value": "Chinese (Mandarin)_Reliable_Executive",    "hint": "中文 · 沉稳高管"},
+            {"value": "Chinese (Mandarin)_News_Anchor",           "hint": "中文 · 新闻女声"},
+            {"value": "Chinese (Mandarin)_Mature_Woman",          "hint": "中文 · 傲娇御姐"},
+            {"value": "Chinese (Mandarin)_Unrestrained_Young_Man","hint": "中文 · 不羁青年"},
+            {"value": "Arrogant_Miss",                            "hint": "中文 · 嚣张小姐"},
+            {"value": "Robot_Armor",                              "hint": "中文 · 机械战甲"},
+            {"value": "Chinese (Mandarin)_Kind-hearted_Antie",    "hint": "中文 · 热心大婶"},
+            {"value": "Chinese (Mandarin)_HK_Flight_Attendant",   "hint": "中文 · 港普空姐"},
+            {"value": "Chinese (Mandarin)_Humorous_Elder",        "hint": "中文 · 搞笑大爷"},
+            {"value": "Chinese (Mandarin)_Gentleman",             "hint": "中文 · 温润男声"},
+            {"value": "Chinese (Mandarin)_Warm_Bestie",           "hint": "中文 · 温暖闺蜜"},
+            {"value": "Chinese (Mandarin)_Male_Announcer",        "hint": "中文 · 播报男声"},
+            {"value": "Chinese (Mandarin)_Sweet_Lady",            "hint": "中文 · 甜美女声"},
+            {"value": "Chinese (Mandarin)_Southern_Young_Man",    "hint": "中文 · 南方小哥"},
+            {"value": "Chinese (Mandarin)_Wise_Women",            "hint": "中文 · 阅历姐姐"},
+            {"value": "Chinese (Mandarin)_Gentle_Youth",          "hint": "中文 · 温润青年"},
+            {"value": "Chinese (Mandarin)_Warm_Girl",             "hint": "中文 · 温暖少女"},
+            {"value": "Chinese (Mandarin)_Kind-hearted_Elder",    "hint": "中文 · 花甲奶奶"},
+            {"value": "Chinese (Mandarin)_Cute_Spirit",           "hint": "中文 · 憨憨萌兽"},
+            {"value": "Chinese (Mandarin)_Radio_Host",            "hint": "中文 · 电台男主播"},
+            {"value": "Chinese (Mandarin)_Lyrical_Voice",         "hint": "中文 · 抒情男声"},
+            {"value": "Chinese (Mandarin)_Straightforward_Boy",   "hint": "中文 · 率真弟弟"},
+            {"value": "Chinese (Mandarin)_Sincere_Adult",         "hint": "中文 · 真诚青年"},
+            {"value": "Chinese (Mandarin)_Gentle_Senior",         "hint": "中文 · 温柔学姐"},
+            {"value": "Chinese (Mandarin)_Stubborn_Friend",       "hint": "中文 · 嘴硬竹马"},
+            {"value": "Chinese (Mandarin)_Crisp_Girl",            "hint": "中文 · 清脆少女"},
+            {"value": "Chinese (Mandarin)_Pure-hearted_Boy",      "hint": "中文 · 清澈邻家弟弟"},
+            {"value": "Chinese (Mandarin)_Soft_Girl",             "hint": "中文 · 柔和少女"},
+            # Cantonese (full catalog)
+            {"value": "Cantonese_ProfessionalHost（F)",            "hint": "粤语 · 专业女主持"},
+            {"value": "Cantonese_GentleLady",                     "hint": "粤语 · 温柔女声"},
+            {"value": "Cantonese_ProfessionalHost（M)",            "hint": "粤语 · 专业男主持"},
+            {"value": "Cantonese_PlayfulMan",                     "hint": "粤语 · 活泼男声"},
+            {"value": "Cantonese_CuteGirl",                       "hint": "粤语 · 可爱女孩"},
+            {"value": "Cantonese_KindWoman",                      "hint": "粤语 · 善良女声"},
+            # English (curated: 1F + 1M)
+            {"value": "English_Graceful_Lady",                    "hint": "英文 · Graceful Lady（女）"},
+            {"value": "English_Trustworthy_Man",                  "hint": "英文 · Trustworthy Man（男）"},
+            # Japanese (curated: 1F + 1M)
+            {"value": "Japanese_KindLady",                        "hint": "日文 · Kind Lady（女）"},
+            {"value": "Japanese_LoyalKnight",                     "hint": "日文 · Loyal Knight（男）"},
+            # Korean (curated: 1F + 1M)
+            {"value": "Korean_SweetGirl",                         "hint": "韩文 · Sweet Girl（女）"},
+            {"value": "Korean_CheerfulBoyfriend",                 "hint": "韩文 · Cheerful Boyfriend（男）"},
+        ],
+        "dashscope": [
+            {"value": "Cherry",   "hint": "芊悦 · 阳光女声"},
+            {"value": "Serena",   "hint": "苏瑶 · 温柔女声"},
+            {"value": "Chelsie",  "hint": "千雪 · 二次元少女"},
+            {"value": "Ethan",    "hint": "晨煦 · 阳光男声"},
+            {"value": "Moon",     "hint": "月白 · 率性男声"},
+            {"value": "Kai",      "hint": "凯 · 治愈男声"},
+            {"value": "Nofish",   "hint": "不吃鱼 · 设计师男声"},
+            {"value": "Bella",    "hint": "萌宝 · 小萝莉"},
+            {"value": "Bunny",    "hint": "萌小姬 · 萌系少女"},
+            {"value": "Stella",   "hint": "少女阿月 · 元气少女"},
+            {"value": "Neil",     "hint": "阿闻 · 新闻主播"},
+            {"value": "Seren",    "hint": "小婉 · 助眠女声"},
+            {"value": "Jada",     "hint": "上海话 · 阿珍"},
+            {"value": "Dylan",    "hint": "北京话 · 晓东"},
+            {"value": "Sunny",    "hint": "四川话 · 晴儿"},
+            {"value": "Eric",     "hint": "四川话 · 程川"},
+            {"value": "Rocky",    "hint": "粤语 · 阿强"},
+            {"value": "Kiki",     "hint": "粤语 · 阿清"},
+            {"value": "Peter",    "hint": "天津话 · 李彼得"},
+            {"value": "Marcus",   "hint": "陕西话 · 秦川"},
+            {"value": "Roy",      "hint": "闽南语 · 阿杰"},
+        ],
+        # 小米 MiMo 预置音色列表（mimo-v2.5-tts），文档：
+        # https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/speech-synthesis-v2.5
+        "mimo": [
+            {"value": "冰糖",   "hint": "中文 · 女声 · 冰糖"},
+            {"value": "茉莉",   "hint": "中文 · 女声 · 茉莉"},
+            {"value": "苏打",   "hint": "中文 · 男声 · 苏打"},
+            {"value": "白桦",   "hint": "中文 · 男声 · 白桦"},
+            {"value": "Mia",   "hint": "英文 · 女声 · Mia"},
+            {"value": "Chloe", "hint": "英文 · 女声 · Chloe"},
+            {"value": "Milo",  "hint": "英文 · 男声 · Milo"},
+            {"value": "Dean",  "hint": "英文 · 男声 · Dean"},
+        ],
+        # Aggregating gateway: voices are scoped per engine model. The
+        # frontend picks the correct list based on the selected model so
+        # users don't see incompatible timbres for the active engine.
+        "linkai": {
+            "tts-1": [
+                "alloy", "echo", "fable", "onyx", "nova", "shimmer",
+            ],
+            "doubao": [
+                {"value": "zh_female_wanwanxiaohe_moon_bigtts",       "hint": "湾湾小何"},
+                {"value": "BV007_streaming",                          "hint": "亲切女声"},
+                {"value": "BV001_streaming",                          "hint": "通用女声"},
+                {"value": "BV002_streaming",                          "hint": "通用男声"},
+                {"value": "BV051_streaming",                          "hint": "奶气萌娃"},
+                {"value": "zh_female_linjianvhai_moon_bigtts",        "hint": "邻家女孩"},
+                {"value": "BV700_streaming",                          "hint": "灿灿"},
+                {"value": "BV019_streaming",                          "hint": "重庆小伙"},
+                {"value": "BV524_streaming",                          "hint": "日语男声"},
+                {"value": "BV021_streaming",                          "hint": "东北老铁"},
+                {"value": "BV701_streaming",                          "hint": "擎苍"},
+                {"value": "BV113_streaming",                          "hint": "甜宠少御"},
+                {"value": "BV056_streaming",                          "hint": "阳光男声"},
+                {"value": "BV213_streaming",                          "hint": "广西表哥"},
+                {"value": "BV119_streaming",                          "hint": "通用赘婿"},
+                {"value": "BV705_streaming",                          "hint": "炀炀"},
+                {"value": "BV033_streaming",                          "hint": "温柔小哥"},
+                {"value": "BV102_streaming",                          "hint": "儒雅青年"},
+                {"value": "BV522_streaming",                          "hint": "气质女生"},
+                {"value": "BV034_streaming",                          "hint": "知性姐姐 · 双语"},
+                {"value": "BV005_streaming",                          "hint": "活泼女声"},
+                {"value": "zh_female_wanqudashu_moon_bigtts",         "hint": "湾区大叔"},
+                {"value": "zh_female_daimengchuanmei_moon_bigtts",    "hint": "呆萌川妹"},
+                {"value": "zh_male_guozhoudege_moon_bigtts",          "hint": "广州德哥"},
+                {"value": "zh_male_beijingxiaoye_moon_bigtts",        "hint": "北京小爷"},
+                {"value": "zh_male_shaonianzixin_moon_bigtts",        "hint": "少年梓辛 / Brayan"},
+                {"value": "zh_female_meilinvyou_moon_bigtts",         "hint": "魅力女友"},
+                {"value": "zh_male_shenyeboke_moon_bigtts",           "hint": "深夜播客"},
+                {"value": "zh_female_sajiaonvyou_moon_bigtts",        "hint": "柔美女友"},
+                {"value": "zh_female_yuanqinvyou_moon_bigtts",        "hint": "撒娇学妹"},
+                {"value": "zh_male_haoyuxiaoge_moon_bigtts",          "hint": "浩宇小哥"},
+                {"value": "zh_male_guangxiyuanzhou_moon_bigtts",      "hint": "广西远舟"},
+                {"value": "zh_female_meituojieer_moon_bigtts",        "hint": "妹坨洁儿"},
+                {"value": "zh_male_yuzhouzixuan_moon_bigtts",         "hint": "豫州子轩"},
+                {"value": "BV115_streaming",                          "hint": "古风少御"},
+                {"value": "zh_female_gaolengyujie_moon_bigtts",       "hint": "高冷御姐"},
+                {"value": "zh_male_yuanboxiaoshu_moon_bigtts",        "hint": "渊博小叔"},
+                {"value": "zh_male_yangguangqingnian_moon_bigtts",    "hint": "阳光青年"},
+                {"value": "zh_male_aojiaobazong_moon_bigtts",         "hint": "傲娇霸总"},
+                {"value": "zh_male_jingqiangkanye_moon_bigtts",       "hint": "京腔侃爷 / Harmony"},
+                {"value": "zh_female_shuangkuaisisi_moon_bigtts",     "hint": "爽快思思 / Skye"},
+                {"value": "zh_male_wennuanahu_moon_bigtts",           "hint": "温暖阿虎 / Alvin"},
+                {"value": "multi_female_shuangkuaisisi_moon_bigtts",  "hint": "はるこ / Esmeralda"},
+                {"value": "multi_male_jingqiangkanye_moon_bigtts",    "hint": "かずね / Javier or Álvaro"},
+                {"value": "multi_female_gaolengyujie_moon_bigtts",    "hint": "あけみ"},
+                {"value": "multi_male_wanqudashu_moon_bigtts",        "hint": "ひろし / Roberto"},
+                {"value": "ICL_zh_female_bingruoshaonv_tob",          "hint": "病弱少女"},
+                {"value": "ICL_zh_female_huoponvhai_tob",             "hint": "活泼女孩"},
+                {"value": "ICL_zh_female_heainainai_tob",             "hint": "和蔼奶奶"},
+                {"value": "ICL_zh_female_linjuayi_tob",               "hint": "邻居阿姨"},
+                {"value": "zh_female_wenrouxiaoya_moon_bigtts",       "hint": "温柔小雅"},
+                {"value": "zh_female_tianmeixiaoyuan_moon_bigtts",    "hint": "甜美小源"},
+                {"value": "zh_female_qingchezizi_moon_bigtts",        "hint": "清澈梓梓"},
+                {"value": "zh_male_dongfanghaoran_moon_bigtts",       "hint": "东方浩然"},
+                {"value": "zh_male_jieshuoxiaoming_moon_bigtts",      "hint": "解说小明"},
+                {"value": "zh_female_kailangjiejie_moon_bigtts",      "hint": "开朗姐姐"},
+                {"value": "zh_male_linjiananhai_moon_bigtts",         "hint": "邻家男孩"},
+                {"value": "zh_female_tianmeiyueyue_moon_bigtts",      "hint": "甜美悦悦"},
+                {"value": "zh_female_xinlingjitang_moon_bigtts",      "hint": "心灵鸡汤"},
+            ],
+            "baidu": [
+                {"value": "baidu_0",    "hint": "度小美 · 标准女主播"},
+                {"value": "baidu_1",    "hint": "度小宇 · 亲切男声"},
+                {"value": "baidu_3",    "hint": "度逍遥 · 情感男声"},
+                {"value": "baidu_4",    "hint": "度丫丫 · 童声"},
+                {"value": "baidu_5",    "hint": "度小娇 · 成熟女主播"},
+                {"value": "baidu_5003", "hint": "度逍遥 · 情感男声"},
+                {"value": "baidu_5118", "hint": "度小鹿 · 甜美女声"},
+                {"value": "baidu_103",  "hint": "度米朵 · 可爱童声"},
+                {"value": "baidu_106",  "hint": "度博文 · 专业男主播"},
+                {"value": "baidu_110",  "hint": "度小童 · 童声主播"},
+                {"value": "baidu_111",  "hint": "度小萌 · 软萌妹子"},
+                {"value": "baidu_4003", "hint": "度逍遥 · 情感男声"},
+                {"value": "baidu_4100", "hint": "度小雯 · 活力女主播"},
+                {"value": "baidu_4103", "hint": "度米朵 · 可爱女声"},
+                {"value": "baidu_4105", "hint": "度灵儿 · 清澈女声"},
+                {"value": "baidu_4106", "hint": "度博文 · 专业男主播"},
+                {"value": "baidu_4115", "hint": "度小贤 · 电台男主播"},
+                {"value": "baidu_4117", "hint": "度小乔 · 活泼女声"},
+                {"value": "baidu_4119", "hint": "度小鹿 · 甜美女声"},
+                {"value": "baidu_4129", "hint": "度小彦 · 知识男主播"},
+                {"value": "baidu_4140", "hint": "度小新 · 专业女主播"},
+                {"value": "baidu_4143", "hint": "度清风 · 配音男声"},
+                {"value": "baidu_4144", "hint": "度姗姗 · 娱乐女声"},
+                {"value": "baidu_4149", "hint": "度星河 · 广告男声"},
+                {"value": "baidu_4206", "hint": "度博文 · 综艺男声"},
+                {"value": "baidu_4226", "hint": "南方 · 电台女主播"},
+                {"value": "baidu_4254", "hint": "度小清 · 广告女声"},
+                {"value": "baidu_4278", "hint": "度小贝 · 知识女主播"},
+            ],
+        },
+    }
+    _EMBEDDING_PROVIDERS = ["openai", "dashscope", "doubao", "zhipu", "linkai", "custom"]
+
+    # Embedding model catalog per provider. Mirrors the default_model in
+    # agent/memory/embedding/provider.py::EMBEDDING_VENDORS.
+    # Custom providers have no preset list — model names vary per vendor,
+    # so the user always types the model id manually.
+    _EMBEDDING_PROVIDER_MODELS = {
+        "openai":    ["text-embedding-3-small", "text-embedding-3-large"],
+        "dashscope": ["text-embedding-v4"],
+        "doubao":    ["doubao-embedding-vision-251215"],
+        "zhipu":     ["embedding-3"],
+        "linkai":    ["text-embedding-3-small"],
+        "custom":    [],
+    }
+
+    # Capability-scoped model catalogs. The chat dropdown can reuse the
+    # provider's generic model list, but vision and image generation are
+    # served by a narrower subset that the runtime actually dispatches to —
+    # see agent/tools/vision/vision.py and skills/image-generation/SKILL.md.
+    # Anything not listed here intentionally hides the model dropdown so
+    # users cannot pin a chat-only model and silently get a 4xx at runtime.
+    _VISION_PROVIDER_MODELS = {
+        # OpenAI ordering matches the recommended GPT-5.4 family first, then
+        # GPT-5 and the GPT-4.1/4o backstops.
+        "openai":    [
+            const.GPT_55,
+            const.GPT_54,
+            const.GPT_54_MINI,
+            const.GPT_54_NANO,
+            const.GPT_5,
+            const.GPT_41,
+            const.GPT_41_MINI,
+            const.GPT_4o,
+        ],
+        "doubao":    [const.DOUBAO_SEED_2_1_PRO, const.DOUBAO_SEED_2_1_TURBO, const.DOUBAO_SEED_2_PRO],
+        "moonshot":  [const.KIMI_K2_6],
+        "dashscope": [const.QWEN37_PLUS, const.QWEN36_PLUS],
+        "claudeAPI": [const.CLAUDE_SONNET_5, const.CLAUDE_4_8_OPUS, const.CLAUDE_4_7_OPUS, const.CLAUDE_4_6_SONNET, const.CLAUDE_4_6_OPUS],
+        "gemini":    [const.GEMINI_35_FLASH, const.GEMINI_31_FLASH_LITE_PRE, const.GEMINI_31_PRO_PRE, const.GEMINI_3_FLASH_PRE],
+        "qianfan":   [const.ERNIE_45_TURBO_VL],
+        # Zhipu's bot hard-codes the call to glm-5v-turbo regardless of what
+        # name is passed in (see models/zhipuai/zhipuai_bot.py::call_vision),
+        # so listing the chat models here would silently route to the same
+        # endpoint. Surface only the model the runtime can truly dispatch to.
+        "zhipu":     [const.GLM_5V_TURBO],
+        # MiniMax's vision endpoint is similarly hard-coded to MiniMax-Text-01
+        # (see models/minimax/minimax_bot.py::call_vision); the M2.x chat
+        # family is text-only.
+        "minimax":   [const.MINIMAX_TEXT_01],
+        # MiMo 原生全模态模型：v2.5-pro / v2.5 支持图像/音频/视频输入
+        "mimo":      [const.MIMO_V2_5_PRO, const.MIMO_V2_5],
+        # LinkAI proxies the underlying vendor; surface a curated set of
+        # multimodal models. Order: gpt-4.1-mini → gpt-5.4-mini as the
+        # cross-vendor baselines, then each vendor's recommended default.
+        "linkai":    [
+            const.GPT_41_MINI,
+            const.GPT_54_MINI,
+            const.QWEN37_PLUS,
+            const.DOUBAO_SEED_2_1_PRO,
+            const.KIMI_K2_6,
+            const.CLAUDE_SONNET_5,
+            const.GEMINI_31_FLASH_LITE_PRE,
+        ],
+        # Custom OpenAI-compatible providers have no preset list — model
+        # names vary per vendor, so the user types the model id manually.
+        "custom": [],
+    }
+
+    # Image-generation catalog. Source of truth: skills/image-generation/SKILL.md.
+    # Listed verbatim (not via const.*) because these are skill-side names
+    # the script forwards directly to the vendor's image endpoint.
+    #
+    # Two shapes are accepted per model entry:
+    #   - bare string                           → the model id, no hint
+    #   - {"value": ..., "hint": "..."}         → model id + dim secondary
+    #                                             label rendered on the right
+    #                                             of the dropdown row. Useful
+    #                                             for surfacing brand names
+    #                                             (e.g. "Nano Banana 2" next
+    #                                             to gemini-3.1-flash-image-preview).
+    # The skill itself maps either form to the real vendor endpoint, so the
+    # hint is purely cosmetic.
+    _IMAGE_PROVIDER_MODELS = {
+        "openai":    ["gpt-image-2", "gpt-image-1"],
+        "gemini": [
+            {"value": "gemini-3.1-flash-image-preview", "hint": "Nano Banana 2"},
+            {"value": "gemini-3-pro-image-preview",     "hint": "Nano Banana Pro"},
+            {"value": "gemini-2.5-flash-image",         "hint": "Nano Banana"},
+        ],
+        "doubao":    ["seedream-5.0-lite", "seedream-4.5"],
+        "dashscope": ["qwen-image-2.0-pro", "qwen-image-2.0"],
+        "minimax":   ["image-01"],
+        "linkai": [
+            "gpt-image-2",
+            {"value": "gemini-3.1-flash-image-preview", "hint": "Nano Banana 2"},
+            {"value": "gemini-3-pro-image-preview",     "hint": "Nano Banana Pro"},
+            "seedream-5.0-lite",
+        ],
+    }
+
+    @staticmethod
+    def _config_path() -> str:
+        return os.path.join(get_data_root(), "config.json")
+
+    @classmethod
+    def _read_file_config(cls) -> dict:
+        path = cls._config_path()
+        if not os.path.exists(path):
+            return {}
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+
+    @classmethod
+    def _write_file_config(cls, data: dict) -> None:
+        with open(cls._config_path(), "w", encoding="utf-8") as f:
+            json.dump(data, f, indent=4, ensure_ascii=False)
+
+    @staticmethod
+    def _is_real_key(value: str) -> bool:
+        return bool(value) and value not in ("", "YOUR API KEY", "YOUR_API_KEY")
+
+    @classmethod
+    def _custom_provider_cards(cls, local_config: dict) -> List[dict]:
+        """Expand ``custom_providers`` into one card per provider.
+
+        Each user-defined OpenAI-compatible provider becomes its own card with
+        id ``custom:<id>`` so the frontend can render, edit, delete and
+        activate them independently. The card carries ``is_custom=True`` and
+        ``active`` flags that the UI uses to render the extra controls.
+
+        Returns an empty list when no multi-providers are configured, in which
+        case the caller keeps the single legacy ``custom`` card untouched —
+        guaranteeing backward compatibility with the flat
+        ``custom_api_key`` / ``custom_api_base`` config.
+        """
+        try:
+            from models.custom_provider import get_custom_providers, parse_custom_bot_type
+            providers = get_custom_providers()
+        except Exception as e:  # pragma: no cover - defensive
+            logger.warning(f"[ModelsHandler] failed to load custom_providers: {e}")
+            providers = []
+        if not providers:
+            return []
+
+        # Determine the currently active provider id from bot_type.
+        bot_type = local_config.get("bot_type") or ""
+        _, active_id = parse_custom_bot_type(bot_type)
+
+        meta = ConfigHandler.PROVIDER_MODELS.get("custom") or {}
+        cards = []
+        for p in providers:
+            pid = p.get("id") or ""
+            name = p.get("name") or pid
+            raw_key = p.get("api_key") or ""
+            raw_base = p.get("api_base") or ""
+            configured = cls._is_real_key(raw_key)
+            cards.append({
+                "id": f"custom:{pid}",
+                "label": {"zh": name, "en": name},
+                "configured": configured,
+                "is_custom": True,
+                "custom_id": pid,
+                "custom_name": name,
+                "active": (pid == active_id),
+                "model": p.get("model") or "",
+                # Custom cards are edited via the dedicated set_custom_provider
+                # action, not the field-based set_provider flow, so the field
+                # names are intentionally null.
+                "api_key_field": None,
+                "api_base_field": None,
+                "api_key_masked": ConfigHandler._mask_key(raw_key) if configured else "",
+                "api_base": raw_base,
+                "api_base_default": "",
+                "api_base_placeholder": meta.get("api_base_placeholder") or "",
+                "models": [p.get("model")] if p.get("model") else [],
+            })
+        return cards
+
+    @classmethod
+    def _legacy_custom_in_use(cls, local_config: dict) -> bool:
+        """True when the flat single-provider custom config is still relevant:
+        either it is the active bot_type, or its key/base fields are filled.
+        In that case the legacy "custom" card must stay visible even when
+        multi ``custom_providers`` entries exist."""
+        if (local_config.get("bot_type") or "") == "custom":
+            return True
+        return (cls._is_real_key(local_config.get("custom_api_key") or "")
+                or bool(local_config.get("custom_api_base")))
+
+    @classmethod
+    def _provider_overview(cls) -> List[dict]:
+        """All known providers (configured first, unconfigured after).
+        Re-uses ConfigHandler.PROVIDER_MODELS for the canonical list.
+
+        When the user has defined multiple custom (OpenAI-compatible)
+        providers via ``custom_providers``, the single built-in ``custom``
+        card is replaced by one card per provider (see
+        ``_custom_provider_cards``). Otherwise the legacy single ``custom``
+        card is shown unchanged.
+        """
+        local_config = conf()
+        custom_cards = cls._custom_provider_cards(local_config)
+        # Keep the legacy single "custom" card visible alongside the expanded
+        # ones when the flat custom_api_key/base config is active or filled,
+        # so existing single-provider setups never disappear from the UI.
+        keep_legacy_custom = cls._legacy_custom_in_use(local_config)
+        items = []
+        for pid, p in ConfigHandler.PROVIDER_MODELS.items():
+            if pid == "custom" and custom_cards:
+                # Multi-provider mode: emit the expanded cards, plus the
+                # legacy card when it is still in use.
+                items.extend(custom_cards)
+                if not keep_legacy_custom:
+                    continue
+            key_field = p.get("api_key_field")
+            base_field = p.get("api_base_key")
+            raw_key = local_config.get(key_field, "") if key_field else ""
+            raw_base = local_config.get(base_field, "") if base_field else ""
+            configured = cls._is_real_key(raw_key)
+            items.append({
+                "id": pid,
+                "label": p["label"],
+                "configured": configured,
+                "is_custom": (pid == "custom"),
+                "api_key_field": key_field,
+                "api_base_field": base_field,
+                "api_key_masked": ConfigHandler._mask_key(raw_key) if configured else "",
+                "api_base": raw_base or (p.get("api_base_default") or ""),
+                "api_base_default": p.get("api_base_default") or "",
+                "api_base_placeholder": p.get("api_base_placeholder") or "",
+                "models": list(p.get("models") or []),
+            })
+
+        def _sort_key(it):
+            pid = it["id"]
+            # Custom expanded cards share the sort weight of the base "custom"
+            # entry so they cluster where the single custom card used to be.
+            base_id = "custom" if it.get("is_custom") else pid
+            try:
+                order = list(ConfigHandler.PROVIDER_MODELS.keys()).index(base_id)
+            except ValueError:
+                order = len(ConfigHandler.PROVIDER_MODELS)
+            return (0 if it["configured"] else 1, order)
+
+        items.sort(key=_sort_key)
+        return items
+
+    @classmethod
+    def _chat_capability(cls, local_config: dict) -> dict:
+        """Main chat model — drives the agent. bot_type maps to a provider id."""
+        bot_type = local_config.get("bot_type") or ""
+        provider_id = "openai" if bot_type == "chatGPT" else bot_type
+        is_custom_id = provider_id.startswith("custom:")
+        if (provider_id not in ConfigHandler.PROVIDER_MODELS and not is_custom_id
+                and local_config.get("use_linkai")):
+            provider_id = "linkai"
+        # In multi-provider mode, replace the single "custom" entry with the
+        # expanded "custom:<id>" ids so the chat dropdown matches the cards.
+        # The legacy "custom" entry stays when its flat config is still used.
+        provider_ids = []
+        custom_cards = cls._custom_provider_cards(local_config)
+        keep_legacy_custom = cls._legacy_custom_in_use(local_config)
+        for pid in ConfigHandler.PROVIDER_MODELS.keys():
+            if pid == "custom" and custom_cards:
+                provider_ids.extend(c["id"] for c in custom_cards)
+                if keep_legacy_custom:
+                    provider_ids.append(pid)
+            else:
+                provider_ids.append(pid)
+        return {
+            "editable": True,
+            "current_provider": provider_id,
+            "current_model": local_config.get("model", ""),
+            "providers": provider_ids,
+            "use_linkai": bool(local_config.get("use_linkai", False)),
+        }
+
+    # Auto-fallback order for vision when no explicit model is pinned.
+    # Mirrors agent/tools/vision/vision.py::_resolve_providers — DeepSeek and
+    # other text-only chat bots are intentionally absent, since they cannot
+    # actually serve a vision request. Each entry is
+    #   (provider_id, api_key_field, default_vision_model)
+    # and lookups are case-insensitive on the api_key_field. LinkAI and
+    # OpenAI are handled separately below so use_linkai can promote LinkAI
+    # to the front of the chain.
+    _VISION_AUTO_ORDER = [
+        ("moonshot",  "moonshot_api_key",  const.KIMI_K2_6),
+        ("doubao",    "ark_api_key",       const.DOUBAO_SEED_2_PRO),
+        ("dashscope", "dashscope_api_key", const.QWEN37_PLUS),
+        ("claudeAPI", "claude_api_key",    const.CLAUDE_SONNET_5),
+        ("gemini",    "gemini_api_key",    const.GEMINI_35_FLASH),
+        ("qianfan",   "qianfan_api_key",   const.ERNIE_45_TURBO_VL),
+        ("zhipu",     "zhipu_ai_api_key",  const.GLM_5V_TURBO),
+        ("minimax",   "minimax_api_key",   const.MINIMAX_TEXT_01),
+        ("mimo",      "mimo_api_key",      const.MIMO_V2_5_PRO),
+    ]
+
+    @classmethod
+    def _predict_vision_auto(cls, local_config: dict) -> dict:
+        """Predict which provider vision.py will actually dispatch to when
+        no tools.vision.model is set. Mirrors the fallback order in
+        agent/tools/vision/vision.py::_resolve_providers so the UI hint
+        matches reality."""
+        chat = cls._chat_capability(local_config)
+        main_provider = chat["current_provider"]
+        main_model = chat["current_model"]
+        use_linkai_flag = bool(local_config.get("use_linkai", False))
+        linkai_configured = cls._is_real_key(local_config.get("linkai_api_key", ""))
+
+        def _try(pid: str, model_default: str):
+            # Look up the api_key for this provider via the canonical
+            # provider table so we don't hardcode field names here.
+            meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+            key_field = meta.get("api_key_field")
+            if not key_field:
+                return None
+            if not cls._is_real_key(local_config.get(key_field, "")):
+                return None
+            # Pick a model that the vision runtime can actually dispatch to
+            # for this provider. Using `main_model` here is unsafe — for
+            # vendors like Zhipu/MiniMax the bot hard-codes the vision model
+            # name regardless of the chat-model name, so surfacing the chat
+            # model name in the hint is misleading. Trust the curated
+            # _VISION_PROVIDER_MODELS list: prefer the main model only if
+            # it appears there; otherwise show the vendor's first vision-
+            # capable model.
+            allowed = cls._VISION_PROVIDER_MODELS.get(pid, [])
+            if pid == main_provider and main_model and main_model in allowed:
+                return {"provider": pid, "model": main_model}
+            fallback = allowed[0] if allowed else model_default
+            return {"provider": pid, "model": fallback}
+
+        # 1. use_linkai → suppress the hint entirely. LinkAI is a proxy and
+        #    we don't observe which underlying model it picks; surfacing
+        #    "LinkAI" with no model would not tell the user anything useful.
+        if use_linkai_flag and linkai_configured:
+            return {"provider": "", "model": ""}
+
+        # 2. Main bot — only when it natively supports vision. We approximate
+        #    "natively supports" by membership in _VISION_PROVIDER_MODELS,
+        #    which is the same set vision.py's _DISCOVERABLE_MODELS covers
+        #    (minus the chat-only DeepSeek family).
+        if main_provider in cls._VISION_PROVIDER_MODELS:
+            hit = _try(main_provider, main_model)
+            if hit:
+                return hit
+
+        # 3. Other discoverable providers in declared order
+        for pid, _key, default_model in cls._VISION_AUTO_ORDER:
+            hit = _try(pid, default_model)
+            if hit:
+                return hit
+
+        # 4. OpenAI raw HTTP
+        if cls._is_real_key(local_config.get("open_ai_api_key", "")):
+            return {"provider": "openai", "model": const.GPT_55}
+
+        # 5. LinkAI as last resort (only reached when use_linkai is off)
+        if linkai_configured:
+            return {"provider": "linkai", "model": const.GPT_41_MINI}
+
+        return {"provider": "", "model": ""}
+
+    @classmethod
+    def _vision_capability(cls, local_config: dict) -> dict:
+        """Vision model. tools.vision.model is the explicit override; otherwise
+        the runtime fallback chain in agent/tools/vision/vision.py decides."""
+        tools_conf = local_config.get("tools") or local_config.get("tool") or {}
+        if not isinstance(tools_conf, dict):
+            tools_conf = {}
+        vision_conf = tools_conf.get("vision") or {}
+        if not isinstance(vision_conf, dict):
+            vision_conf = {}
+        user_specified = (vision_conf.get("model") or "").strip()
+        explicit_provider = (vision_conf.get("provider") or "").strip()
+
+        # Build provider list: built-in providers + expanded custom:<id> entries.
+        # Same pattern as _embedding_capability — each user-created custom
+        # provider gets its own dropdown entry showing the user-chosen name.
+        providers = []
+        custom_cards = cls._custom_provider_cards(local_config)
+        for pid in cls._VISION_PROVIDER_MODELS:
+            if pid == "custom":
+                if custom_cards:
+                    providers.extend(c["id"] for c in custom_cards)
+            else:
+                providers.append(pid)
+
+        # Provider resolution priority:
+        #   1. Explicit `tools.vision.provider` (persisted via UI; supports
+        #      custom model names that prefix-inference can't recognize).
+        #   2. Scan per-provider model lists by model name.
+        # Empty provider keeps the dropdown on "auto" when we can't tell.
+        inferred_provider = ""
+        if explicit_provider and explicit_provider in providers:
+            inferred_provider = explicit_provider
+        elif user_specified:
+            for pid, models in cls._VISION_PROVIDER_MODELS.items():
+                if user_specified in models:
+                    # For "custom" key, map to the first custom card
+                    inferred_provider = custom_cards[0]["id"] if pid == "custom" and custom_cards else pid
+                    break
+
+        # In auto mode the hint should reflect what vision.py will actually
+        # dispatch to — surface that prediction via fallback_* so the UI
+        # shows e.g. "openai / gpt-4.1-mini" instead of the chat-model name.
+        predicted = cls._predict_vision_auto(local_config)
+
+        return {
+            "editable": True,
+            "strategy": "specified" if user_specified else "auto",
+            "user_specified_model": user_specified,
+            "current_provider": inferred_provider,
+            "current_model": user_specified,
+            "fallback_provider": predicted["provider"],
+            "fallback_model": predicted["model"],
+            "providers": providers,
+            "provider_models": cls._VISION_PROVIDER_MODELS,
+        }
+
+    @classmethod
+    def _asr_capability(cls, local_config: dict) -> dict:
+        # "Pick or empty" — when voice_to_text is unset we don't show a
+        # current selection. `suggested_provider` previews which vendor
+        # the bridge auto-picker would land on (purely a UX hint, NOT
+        # persisted). Once the user saves a vendor, we lock onto it.
+        explicit = (local_config.get("voice_to_text") or "").strip().lower()
+        suggested = ""
+        if not explicit:
+            for pid in cls._ASR_PROVIDERS:
+                meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+                key_field = meta.get("api_key_field")
+                if key_field and cls._is_real_key(local_config.get(key_field, "")):
+                    suggested = pid
+                    break
+        return {
+            "editable": True,
+            "current_provider": explicit,
+            "suggested_provider": suggested,
+            "current_model": (local_config.get("voice_to_text_model") or "") if explicit else "",
+            "providers": cls._ASR_PROVIDERS,
+            "provider_models": cls._ASR_PROVIDER_MODELS,
+        }
+
+    @classmethod
+    def _tts_capability(cls, local_config: dict) -> dict:
+        explicit = (local_config.get("text_to_voice") or "").strip().lower()
+        # Providers outside the white-list don't drive the picker, but their
+        # underlying runtime config is preserved so bridge still routes them.
+        ui_provider = explicit if explicit in cls._TTS_PROVIDERS else ""
+        suggested = ""
+        if not ui_provider:
+            for pid in cls._TTS_PROVIDERS:
+                meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+                key_field = meta.get("api_key_field")
+                if key_field and cls._is_real_key(local_config.get(key_field, "")):
+                    suggested = pid
+                    break
+        return {
+            "editable": True,
+            "current_provider": ui_provider,
+            "suggested_provider": suggested,
+            "current_model": (local_config.get("text_to_voice_model") or "") if ui_provider else "",
+            "current_voice": (local_config.get("tts_voice_id") or "") if ui_provider else "",
+            "providers": cls._TTS_PROVIDERS,
+            "provider_models": cls._TTS_PROVIDER_MODELS,
+            "provider_voices": cls._TTS_PROVIDER_VOICES,
+            "reply_mode": cls._tts_reply_mode(local_config),
+        }
+
+    @staticmethod
+    def _tts_reply_mode(local_config: dict) -> str:
+        if local_config.get("always_reply_voice", False):
+            return "always"
+        if local_config.get("voice_reply_voice", False):
+            return "voice_if_voice"
+        return "off"
+
+    @classmethod
+    def _embedding_capability(cls, local_config: dict) -> dict:
+        # Embedding is "pick or empty" — runtime's legacy openai/linkai
+        # fallback is a safety net, not a UX-visible auto mode.
+        # `suggested_provider` is a UI-only hint (NOT persisted) that
+        # preselects the dropdown to whichever configured vendor we'd
+        # recommend, so users don't have to expand the menu to find it.
+        explicit = (local_config.get("embedding_provider") or "").strip().lower()
+        suggested = ""
+        if not explicit:
+            for pid in cls._EMBEDDING_PROVIDERS:
+                if pid == "custom":
+                    continue
+                meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+                key_field = meta.get("api_key_field")
+                if key_field and cls._is_real_key(local_config.get(key_field, "")):
+                    suggested = pid
+                    break
+            if not suggested:
+                custom_cards = cls._custom_provider_cards(local_config)
+                if custom_cards:
+                    suggested = custom_cards[0]["id"]
+
+        # Build provider list: built-in providers + expanded custom:<id> entries
+        # Same pattern as _chat_capability — each user-created custom provider
+        # gets its own dropdown entry showing the user-chosen name.
+        providers = []
+        custom_cards = cls._custom_provider_cards(local_config)
+        for pid in cls._EMBEDDING_PROVIDERS:
+            if pid == "custom":
+                if custom_cards:
+                    providers.extend(c["id"] for c in custom_cards)
+                # No custom providers configured — skip the bare "custom" entry
+                # since the runtime cannot resolve its credentials.
+            else:
+                providers.append(pid)
+
+        return {
+            "editable": True,
+            "current_provider": explicit,
+            "suggested_provider": suggested,
+            "current_model": local_config.get("embedding_model", "") or "",
+            "current_dim": int(local_config.get("embedding_dimensions") or 0) or None,
+            "providers": providers,
+            "provider_models": cls._EMBEDDING_PROVIDER_MODELS,
+        }
+
+    # Auto-fallback order for image generation. Mirrors the global priority
+    # used inside skills/image-generation/scripts/generate.py
+    # (`_DEFAULT_PROVIDER_ORDER`): OpenAI → Gemini → Seedream(Ark/doubao) →
+    # Qwen(dashscope) → MiniMax → LinkAI. Each entry maps the
+    # provider-card id to the script's per-provider DEFAULT_MODEL so the
+    # hint matches what the runtime would actually request.
+    _IMAGE_AUTO_ORDER = [
+        ("openai",    "gpt-image-2"),
+        ("gemini",    "gemini-3.1-flash-image-preview"),  # nano-banana-2
+        ("doubao",    "seedream-5.0-lite"),
+        ("dashscope", "qwen-image-2.0"),
+        ("minimax",   "image-01"),
+        ("linkai",    "gpt-image-2"),
+    ]
+
+    @classmethod
+    def _predict_image_auto(cls, local_config: dict) -> dict:
+        """Predict which provider/model the image-generation skill will hit
+        when no SKILL_IMAGE_GENERATION_MODEL override is set. Mirrors
+        skills/image-generation/scripts/generate.py::_build_providers so
+        the UI hint matches reality. Chat-only providers (DeepSeek etc.)
+        are absent by design — image generation never falls back to a chat
+        bot regardless of the main model.
+
+        When use_linkai is enabled the hint is suppressed entirely — LinkAI
+        proxies to whichever backend it deems appropriate and surfacing
+        "LinkAI" alone tells the user nothing actionable."""
+        use_linkai_flag = bool(local_config.get("use_linkai", False))
+        linkai_configured = cls._is_real_key(local_config.get("linkai_api_key", ""))
+        if use_linkai_flag and linkai_configured:
+            return {"provider": "", "model": ""}
+
+        for pid, default_model in cls._IMAGE_AUTO_ORDER:
+            meta = ConfigHandler.PROVIDER_MODELS.get(pid) or {}
+            key_field = meta.get("api_key_field")
+            if not key_field:
+                continue
+            if cls._is_real_key(local_config.get(key_field, "")):
+                return {"provider": pid, "model": default_model}
+        return {"provider": "", "model": ""}
+
+    @classmethod
+    def _image_capability(cls, local_config: dict) -> dict:
+        """Image generation. Source of truth: config["skills"]["image-generation"]["model"]
+        (mirrors the per-skill config schema documented in skills/image-generation).
+        The runtime resolver in skills/image-generation/scripts/generate.py
+        reads this via the SKILL_IMAGE_GENERATION_MODEL env var that the
+        agent_initializer syncs at startup; provider is inferred from the
+        model name prefix, mirroring vision.py's design.
+
+        ``skill`` (singular) is still tolerated as a legacy fallback —
+        config.load_config() folds it into ``skills`` at startup.
+        """
+        skills_node = local_config.get("skills") or local_config.get("skill") or {}
+        if not isinstance(skills_node, dict):
+            skills_node = {}
+        img_node = skills_node.get("image-generation") or {}
+        if not isinstance(img_node, dict):
+            img_node = {}
+        explicit_model = (img_node.get("model") or "").strip()
+        explicit_provider = (img_node.get("provider") or "").strip()
+
+        # Provider resolution priority:
+        #   1. Explicit `skills.image-generation.provider` (persisted via UI;
+        #      supports custom model names that prefix-inference can't catch).
+        #   2. Scan per-provider model catalog by model name.
+        # Empty provider keeps the dropdown on "auto" when we can't tell.
+        inferred_provider = ""
+        if explicit_provider and explicit_provider in cls._IMAGE_PROVIDER_MODELS:
+            inferred_provider = explicit_provider
+        elif explicit_model:
+            for pid, models in cls._IMAGE_PROVIDER_MODELS.items():
+                for entry in models:
+                    val = entry if isinstance(entry, str) else (entry.get("value") or "")
+                    if val == explicit_model:
+                        inferred_provider = pid
+                        break
+                if inferred_provider:
+                    break
+
+        # In auto mode the hint should reflect what generate.py will actually
+        # dispatch to — surface that prediction via fallback_* so the UI
+        # never claims a chat-only bot (e.g. minimax/MiniMax-M2.7) "would
+        # generate the image", which is impossible.
+        predicted = cls._predict_image_auto(local_config)
+
+        return {
+            "editable": True,
+            "strategy": "specified" if explicit_model else "auto",
+            "current_provider": inferred_provider,
+            "current_model": explicit_model,
+            "fallback_provider": predicted["provider"],
+            "fallback_model": predicted["model"],
+            "providers": list(cls._IMAGE_PROVIDER_MODELS.keys()),
+            "provider_models": cls._IMAGE_PROVIDER_MODELS,
+            # The dispatcher that honors a pinned provider isn't wired up
+            # yet; advertise this so the UI can show a "saved but not active"
+            # banner until the runtime catches up.
+            "runtime_active": False,
+            "note": "router_pending",
+        }
+
+    # Canonical search provider order. Mirrors PROVIDER_ORDER in
+    # agent/tools/web_search/web_search.py — keep them in sync.
+    _SEARCH_PROVIDERS = ("bocha", "qianfan", "zhipu", "linkai")
+
+    _SEARCH_PROVIDER_LABELS = {
+        "bocha":   {"zh": "博查", "en": "Bocha"},
+        "zhipu":   {"zh": "智谱", "en": "GLM"},
+        "qianfan": {"zh": "百度千帆", "en": "ERNIE"},
+        "linkai":  {"zh": "LinkAI", "en": "LinkAI"},
+    }
+
+    @classmethod
+    def _search_provider_key(cls, provider: str, local_config: dict) -> str:
+        """Resolve the (raw) key for a given search provider."""
+        if provider == "bocha":
+            tools_cfg = local_config.get("tools") or {}
+            block = tools_cfg.get("web_search") or {} if isinstance(tools_cfg, dict) else {}
+            return (block.get("bocha_api_key") if isinstance(block, dict) else "") or os.environ.get("BOCHA_API_KEY", "")
+        if provider == "zhipu":
+            return local_config.get("zhipu_ai_api_key") or os.environ.get("ZHIPUAI_API_KEY", "")
+        if provider == "qianfan":
+            return local_config.get("qianfan_api_key") or os.environ.get("QIANFAN_API_KEY", "")
+        if provider == "linkai":
+            return local_config.get("linkai_api_key") or os.environ.get("LINKAI_API_KEY", "")
+        return ""
+
+    @classmethod
+    def _search_capability(cls, local_config: dict) -> dict:
+        """Search is editable: pick auto (default) or pin a specific backend.
+        Providers reuse model-vendor keys (zhipu/qianfan/linkai) so they show
+        up as configured once the user adds those vendors; bocha keeps its
+        own key under tools.web_search."""
+        tools_cfg = local_config.get("tools") or {}
+        ws_cfg = tools_cfg.get("web_search") or {} if isinstance(tools_cfg, dict) else {}
+        if not isinstance(ws_cfg, dict):
+            ws_cfg = {}
+
+        providers = []
+        configured_ids = []
+        for pid in cls._SEARCH_PROVIDERS:
+            ok = cls._is_real_key(cls._search_provider_key(pid, local_config))
+            raw_key = cls._search_provider_key(pid, local_config) if ok else ""
+            providers.append({
+                "id": pid,
+                "label": cls._SEARCH_PROVIDER_LABELS.get(pid, pid),
+                "configured": ok,
+                # bocha owns its key under tools.web_search; the other three
+                # piggy-back on a model-vendor credential. Frontend uses
+                # this hint to decide which credential editor to surface.
+                "needs_dedicated_key": pid == "bocha",
+                "api_key_masked": ConfigHandler._mask_key(raw_key) if raw_key else "",
+            })
+            if ok:
+                configured_ids.append(pid)
+
+        strategy = (ws_cfg.get("strategy") or "auto").strip().lower()
+        if strategy not in ("auto", "fixed"):
+            strategy = "auto"
+        fixed_provider = (ws_cfg.get("provider") or "").strip().lower()
+        if fixed_provider and fixed_provider not in configured_ids:
+            fixed_provider = ""
+
+        # current_provider drives the chip in the header — show the actually
+        # active backend (pinned or first auto-picked).
+        if strategy == "fixed" and fixed_provider:
+            current = fixed_provider
+        else:
+            current = configured_ids[0] if configured_ids else ""
+
+        return {
+            "editable": True,
+            "strategy": strategy,
+            "providers": providers,
+            "configured_providers": configured_ids,
+            "current_provider": current,
+            "fixed_provider": fixed_provider,
+            "available": bool(current),
+        }
+
+    @classmethod
+    def _capabilities(cls, local_config: dict) -> dict:
+        return {
+            "chat":      cls._chat_capability(local_config),
+            "vision":    cls._vision_capability(local_config),
+            "asr":       cls._asr_capability(local_config),
+            "tts":       cls._tts_capability(local_config),
+            "embedding": cls._embedding_capability(local_config),
+            "image":     cls._image_capability(local_config),
+            "search":    cls._search_capability(local_config),
+        }
+
+    def GET(self):
+        _require_auth()
+        web.header("Content-Type", "application/json; charset=utf-8")
+        try:
+            local_config = conf()
+            return json.dumps({
+                "status": "success",
+                "providers": self._provider_overview(),
+                "capabilities": self._capabilities(local_config),
+            }, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[ModelsHandler] GET failed: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        _require_auth()
+        web.header("Content-Type", "application/json; charset=utf-8")
+        try:
+            data = json.loads(web.data() or b"{}")
+            action = data.get("action") or ""
+            if action == "set_provider":
+                return self._handle_set_provider(data)
+            if action == "delete_provider":
+                return self._handle_delete_provider(data)
+            if action == "set_custom_provider":
+                return self._handle_set_custom_provider(data)
+            if action == "delete_custom_provider":
+                return self._handle_delete_custom_provider(data)
+            if action == "set_active_custom_provider":
+                return self._handle_set_active_custom_provider(data)
+            if action == "set_capability":
+                return self._handle_set_capability(data)
+            if action == "set_voice_reply_mode":
+                return self._handle_set_voice_reply_mode(data)
+            if action == "set_search_credential":
+                return self._handle_set_search_credential(data)
+            return json.dumps({"status": "error", "message": f"unknown action: {action!r}"})
+        except Exception as e:
+            logger.error(f"[ModelsHandler] POST failed: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def _handle_set_provider(self, data: dict) -> str:
+        provider_id = (data.get("provider_id") or "").strip()
+        meta = ConfigHandler.PROVIDER_MODELS.get(provider_id)
+        if not meta:
+            return json.dumps({"status": "error", "message": f"unknown provider: {provider_id}"})
+
+        # api_key absent / empty / null => leave the existing key untouched
+        # (used by the "edit only base url" flow). To clear the key, callers
+        # must use action=delete_provider explicitly.
+        api_key_raw = data.get("api_key")
+        api_key = api_key_raw.strip() if isinstance(api_key_raw, str) else ""
+
+        # api_base presence is significant: an explicit "" means "reset to
+        # default", whereas a missing key means "no change".
+        api_base_present = "api_base" in data
+        api_base = (data.get("api_base") or "").strip() if api_base_present else None
+
+        applied = {}
+        local_config = conf()
+        file_cfg = self._read_file_config()
+
+        key_field = meta.get("api_key_field")
+        if key_field and api_key:
+            local_config[key_field] = api_key
+            file_cfg[key_field] = api_key
+            applied[key_field] = True
+        base_field = meta.get("api_base_key")
+        if base_field and api_base_present:
+            local_config[base_field] = api_base
+            file_cfg[base_field] = api_base
+            applied[base_field] = True
+
+        if not applied:
+            # Nothing actually changed (e.g. user opened the modal and hit
+            # save without editing). Treat as a successful no-op so the
+            # frontend can show "Saved" instead of surfacing an error.
+            return json.dumps({"status": "success", "provider": provider_id, "noop": True})
+
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] provider {provider_id} updated: {sorted(applied.keys())}")
+
+        # Vendor credentials affect bot routing for any capability that uses
+        # them; safest to reset Bridge so the next request rebuilds bots.
+        self._reset_bridge()
+        return json.dumps({"status": "success", "provider": provider_id})
+
+    def _handle_delete_provider(self, data: dict) -> str:
+        provider_id = (data.get("provider_id") or "").strip()
+        meta = ConfigHandler.PROVIDER_MODELS.get(provider_id)
+        if not meta:
+            return json.dumps({"status": "error", "message": f"unknown provider: {provider_id}"})
+
+        local_config = conf()
+        file_cfg = self._read_file_config()
+
+        cleared = []
+        for field_name in (meta.get("api_key_field"), meta.get("api_base_key")):
+            if not field_name:
+                continue
+            # Always write the key — even if it was absent before — so the
+            # in-memory conf() reflects the cleared state without needing a
+            # restart. (`in local_config` was too strict: provider keys that
+            # were ever set then deleted manually wouldn't get reset.)
+            local_config[field_name] = ""
+            file_cfg[field_name] = ""
+            cleared.append(field_name)
+
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] provider {provider_id} cleared: {cleared}")
+        self._reset_bridge()
+        return json.dumps({"status": "success", "provider": provider_id, "cleared": cleared})
+
+    # ------------------------------------------------------------------
+    # Multiple custom (OpenAI-compatible) providers
+    # ------------------------------------------------------------------
+    # These actions manage the ``custom_providers`` list.  Activation is done
+    # by setting ``bot_type`` to ``"custom:<id>"``.  There is no separate
+    # ``custom_active_provider`` field — a single source of truth.
+
+    @staticmethod
+    def _normalize_custom_providers(raw) -> List[dict]:
+        """Return a clean list of provider dicts (drops malformed entries)."""
+        if not isinstance(raw, list):
+            return []
+        out = []
+        for p in raw:
+            if isinstance(p, dict) and (p.get("id") or "").strip():
+                out.append(p)
+        return out
+
+    def _persist_custom_providers(self, providers: List[dict], bot_type=None) -> None:
+        """Write the providers list to both in-memory conf and the on-disk
+        config, then reset the bridge so bots rebuild.
+
+        If ``bot_type`` is given, also update ``bot_type``.  When activating a
+        provider (bot_type is ``custom:<id>``), also write the provider's
+        ``model`` into the global ``model`` field so that all paths (chat,
+        agent, vision) automatically use the correct model."""
+        from models.custom_provider import parse_custom_bot_type
+
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config["custom_providers"] = providers
+        file_cfg["custom_providers"] = providers
+        if bot_type is not None:
+            local_config["bot_type"] = bot_type
+            file_cfg["bot_type"] = bot_type
+            # Sync the provider's model into the global model field.
+            _, pid = parse_custom_bot_type(bot_type)
+            if pid:
+                provider = next((p for p in providers if p.get("id") == pid), None)
+                if provider and provider.get("model"):
+                    local_config["model"] = provider["model"]
+                    file_cfg["model"] = provider["model"]
+        self._write_file_config(file_cfg)
+        self._reset_bridge()
+
+    def _handle_set_custom_provider(self, data: dict) -> str:
+        """Add a new custom provider or update an existing one.
+
+        Payload::
+
+            {
+              "action": "set_custom_provider",
+              "id": "3f2a9c1b",             # required for edit; omit for create
+              "name": "my-provider",         # required, display label
+              "api_base": "https://...",     # required when creating
+              "api_key": "sk-...",           # optional on edit (keep existing)
+              "model": "model-name",         # optional default model
+              "make_active": true            # optional, also activate it
+            }
+        """
+        from models.custom_provider import generate_provider_id, parse_custom_bot_type
+
+        name = (data.get("name") or "").strip()
+        if not name:
+            return json.dumps({"status": "error", "message": "name is required"})
+
+        provider_id = (data.get("id") or "").strip()
+        api_base = (data.get("api_base") or "").strip()
+        # api_key omitted/empty on edit => keep the existing one.
+        api_key_raw = data.get("api_key")
+        api_key = api_key_raw.strip() if isinstance(api_key_raw, str) else ""
+        model = (data.get("model") or "").strip()
+        make_active = bool(data.get("make_active"))
+
+        local_config = conf()
+        providers = self._normalize_custom_providers(local_config.get("custom_providers"))
+
+        existing = next((p for p in providers if p.get("id") == provider_id), None) if provider_id else None
+        if existing is None:
+            # Creating a new provider — api_base is mandatory.
+            if not api_base:
+                return json.dumps({"status": "error", "message": "api_base is required"})
+            provider_id = generate_provider_id()
+            entry = {"id": provider_id, "name": name, "api_key": api_key, "api_base": api_base}
+            if model:
+                entry["model"] = model
+            providers.append(entry)
+            created = True
+        else:
+            existing["name"] = name
+            if api_base:
+                existing["api_base"] = api_base
+            if api_key:
+                existing["api_key"] = api_key
+            # Only touch model when explicitly provided in the payload; an
+            # explicit empty string clears it, a missing key keeps it (the
+            # UI modal no longer sends model, so manual config survives edits).
+            if "model" in data:
+                if model:
+                    existing["model"] = model
+                else:
+                    existing.pop("model", None)
+            created = False
+
+        # Decide bot_type — only switch when explicitly requested.
+        new_bot_type = None
+        if make_active:
+            new_bot_type = f"custom:{provider_id}"
+
+        self._persist_custom_providers(providers, new_bot_type)
+        logger.info(
+            f"[ModelsHandler] custom provider {name!r} (id={provider_id}) "
+            f"{'created' if created else 'updated'}"
+        )
+        return json.dumps({
+            "status": "success",
+            "id": provider_id,
+            "name": name,
+            "created": created,
+        })
+
+    def _handle_delete_custom_provider(self, data: dict) -> str:
+        """Remove a custom provider by id."""
+        from models.custom_provider import parse_custom_bot_type
+
+        provider_id = (data.get("id") or "").strip()
+        if not provider_id:
+            return json.dumps({"status": "error", "message": "id is required"})
+
+        local_config = conf()
+        providers = self._normalize_custom_providers(local_config.get("custom_providers"))
+        remaining = [p for p in providers if p.get("id") != provider_id]
+        if len(remaining) == len(providers):
+            return json.dumps({"status": "error", "message": f"unknown custom provider id: {provider_id}"})
+
+        # If the deleted provider was active, fall back to the first remaining.
+        _, current_active_id = parse_custom_bot_type(local_config.get("bot_type") or "")
+        new_bot_type = None
+        if current_active_id == provider_id:
+            if remaining:
+                new_bot_type = f"custom:{remaining[0]['id']}"
+            else:
+                new_bot_type = "custom"  # revert to legacy
+
+        self._persist_custom_providers(remaining, new_bot_type)
+        logger.info(f"[ModelsHandler] custom provider id={provider_id} deleted")
+        return json.dumps({"status": "success", "id": provider_id})
+
+    def _handle_set_active_custom_provider(self, data: dict) -> str:
+        """Activate a custom provider by setting bot_type to 'custom:<id>'."""
+        provider_id = (data.get("id") or "").strip()
+        if not provider_id:
+            return json.dumps({"status": "error", "message": "id is required"})
+
+        local_config = conf()
+        providers = self._normalize_custom_providers(local_config.get("custom_providers"))
+        if not any(p.get("id") == provider_id for p in providers):
+            return json.dumps({"status": "error", "message": f"unknown custom provider id: {provider_id}"})
+
+        new_bot_type = f"custom:{provider_id}"
+        self._persist_custom_providers(providers, new_bot_type)
+        logger.info(f"[ModelsHandler] active custom provider set to id={provider_id}")
+        return json.dumps({"status": "success", "active_id": provider_id})
+
+    def _handle_set_capability(self, data: dict) -> str:
+        capability = (data.get("capability") or "").strip()
+        provider_id = (data.get("provider_id") or "").strip()
+        model = (data.get("model") or "").strip()
+
+        if capability == "chat":
+            return self._set_chat(provider_id, model)
+        if capability == "vision":
+            return self._set_vision(provider_id, model)
+        if capability == "asr":
+            return self._set_asr(provider_id, model)
+        if capability == "tts":
+            return self._set_tts(provider_id, model, (data.get("voice") or "").strip())
+        if capability == "embedding":
+            return self._set_embedding(provider_id, model)
+        if capability == "image":
+            return self._set_image(provider_id, model)
+        if capability == "search":
+            return self._set_search(
+                (data.get("strategy") or "").strip().lower(),
+                (data.get("provider") or "").strip().lower(),
+            )
+        return json.dumps({"status": "error", "message": f"capability not editable: {capability}"})
+
+    def _set_image(self, provider_id: str, model: str) -> str:
+        # Source of truth: skills.image-generation.{provider, model}. The
+        # provider field is persisted so users picking a custom model under
+        # a specific vendor still get routed there — runtime falls back to
+        # model-name prefix inference only when provider is empty.
+        local_config = conf()
+        file_cfg = self._read_file_config()
+
+        self._set_nested_namespace_value(local_config, "skills", "image-generation", "model", model or "")
+        self._set_nested_namespace_value(file_cfg, "skills", "image-generation", "model", model or "")
+        self._set_nested_namespace_value(local_config, "skills", "image-generation", "provider", provider_id or "")
+        self._set_nested_namespace_value(file_cfg, "skills", "image-generation", "provider", provider_id or "")
+        self._drop_legacy_namespace(local_config, "skill", "skills", child="image-generation")
+        self._drop_legacy_namespace(file_cfg, "skill", "skills", child="image-generation")
+
+        self._write_file_config(file_cfg)
+
+        # The skill subprocess reads SKILL_IMAGE_GENERATION_{MODEL,PROVIDER}
+        # from env at startup; mirror the change so live edits apply without
+        # restart.
+        model_env = "SKILL_IMAGE_GENERATION_MODEL"
+        provider_env = "SKILL_IMAGE_GENERATION_PROVIDER"
+        if model:
+            os.environ[model_env] = model
+        else:
+            os.environ.pop(model_env, None)
+        if provider_id:
+            os.environ[provider_env] = provider_id
+        else:
+            os.environ.pop(provider_env, None)
+
+        logger.info(f"[ModelsHandler] image updated: provider={provider_id!r} model={model!r}")
+        return json.dumps({
+            "status": "success",
+            "provider": provider_id,
+            "model": model,
+            "router_pending": True,
+        })
+
+    def _set_chat(self, provider_id: str, model: str) -> str:
+        # Accept expanded custom provider ids ("custom:<id>") as well as the
+        # built-in vendors, so the chat capability card and the custom
+        # providers section behave consistently.
+        custom_provider = None
+        if provider_id.startswith("custom:"):
+            from models.custom_provider import parse_custom_bot_type
+            _, custom_id = parse_custom_bot_type(provider_id)
+            providers = self._normalize_custom_providers(conf().get("custom_providers"))
+            custom_provider = next((p for p in providers if p.get("id") == custom_id), None)
+            if custom_provider is None:
+                return json.dumps({"status": "error", "message": f"unknown custom provider id: {custom_id}"})
+        elif provider_id and provider_id not in ConfigHandler.PROVIDER_MODELS:
+            return json.dumps({"status": "error", "message": f"unknown provider: {provider_id}"})
+
+        applied = {}
+        local_config = conf()
+        file_cfg = self._read_file_config()
+
+        # Fall back to the custom provider's default model when none is given.
+        if not model and custom_provider:
+            model = custom_provider.get("model") or ""
+
+        if provider_id:
+            bot_type_value = "chatGPT" if provider_id == "openai" else provider_id
+            local_config["bot_type"] = bot_type_value
+            file_cfg["bot_type"] = bot_type_value
+            applied["bot_type"] = bot_type_value
+            use_linkai = (provider_id == "linkai")
+            local_config["use_linkai"] = use_linkai
+            file_cfg["use_linkai"] = use_linkai
+            applied["use_linkai"] = use_linkai
+        if model:
+            local_config["model"] = model
+            file_cfg["model"] = model
+            applied["model"] = model
+
+        if not applied:
+            return json.dumps({"status": "success", "applied": {}, "noop": True})
+
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] chat updated: {applied}")
+        self._reset_bridge()
+        return json.dumps({"status": "success", "applied": applied})
+
+    def _set_vision(self, provider_id: str, model: str) -> str:
+        # Source of truth: tools.vision.{provider, model}. The provider field
+        # is persisted so users picking a custom model under a specific vendor
+        # still get routed there — runtime falls back to model-name prefix
+        # inference only when provider is empty.
+        # Validate provider_id — mirrors _set_chat / _set_embedding pattern.
+        if provider_id.startswith("custom:"):
+            from models.custom_provider import parse_custom_bot_type
+            _, custom_id = parse_custom_bot_type(provider_id)
+            providers = self._normalize_custom_providers(conf().get("custom_providers"))
+            custom_provider = next((p for p in providers if p.get("id") == custom_id), None)
+            if custom_provider is None:
+                return json.dumps({"status": "error", "message": f"unknown custom provider id: {custom_id}"})
+            if not model:
+                model = custom_provider.get("model") or ""
+        elif provider_id and provider_id not in {k for k in ModelsHandler._VISION_PROVIDER_MODELS if k != "custom"}:
+            return json.dumps({"status": "error", "message": f"unknown provider: {provider_id}"})
+
+        if provider_id and not model:
+            return json.dumps({
+                "status": "error",
+                "message": "vision model is required when a provider is selected",
+            })
+
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        self._set_nested_namespace_value(file_cfg, "tools", "vision", "model", model)
+        self._set_nested_namespace_value(local_config, "tools", "vision", "model", model)
+        self._set_nested_namespace_value(file_cfg, "tools", "vision", "provider", provider_id or "")
+        self._set_nested_namespace_value(local_config, "tools", "vision", "provider", provider_id or "")
+        self._drop_legacy_namespace(file_cfg, "tool", "tools", child="vision")
+        self._drop_legacy_namespace(local_config, "tool", "tools", child="vision")
+
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] vision updated: provider={provider_id!r} model={model!r}")
+        return json.dumps({"status": "success", "provider": provider_id, "model": model})
+
+    @staticmethod
+    def _set_nested_namespace_value(cfg, top: str, name: str, key: str, value):
+        """Set ``cfg[top][name][key] = value``, creating missing dicts."""
+        bucket = cfg.get(top)
+        if not isinstance(bucket, dict):
+            bucket = {}
+        node = bucket.get(name)
+        if not isinstance(node, dict):
+            node = {}
+        node[key] = value
+        bucket[name] = node
+        cfg[top] = bucket
+
+    @staticmethod
+    def _drop_legacy_namespace(cfg, legacy: str, canonical: str, child: str) -> None:
+        """Strip the deprecated singular key so config.json stays single-source."""
+        legacy_section = cfg.get(legacy)
+        if not isinstance(legacy_section, dict):
+            return
+        legacy_section.pop(child, None)
+        if legacy_section:
+            cfg[legacy] = legacy_section
+        else:
+            cfg.pop(legacy, None)
+
+    def _handle_set_voice_reply_mode(self, data: dict) -> str:
+        # UI picker (off / voice_if_voice / always) maps to the legacy
+        # always_reply_voice + voice_reply_voice pair that chat_channel.py
+        # reads, so all channels (web/feishu/wecom/...) share the routing.
+        mode = (data.get("mode") or "").strip().lower()
+        if mode not in ("off", "voice_if_voice", "always"):
+            return json.dumps({"status": "error", "message": f"invalid mode: {mode!r}"})
+        always = (mode == "always")
+        if_voice = (mode == "voice_if_voice")
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config["always_reply_voice"] = always
+        local_config["voice_reply_voice"] = if_voice
+        file_cfg["always_reply_voice"] = always
+        file_cfg["voice_reply_voice"] = if_voice
+        self._write_file_config(file_cfg)
+        logger.info(
+            f"[ModelsHandler] voice reply mode set: {mode!r} "
+            f"(always_reply_voice={always}, voice_reply_voice={if_voice})"
+        )
+        return json.dumps({"status": "success", "mode": mode})
+
+    def _set_simple(self, key: str, value: str) -> str:
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config[key] = value
+        file_cfg[key] = value
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] {key} set: {value!r}")
+        # Hot-swap the cached voice bot so the change takes effect immediately.
+        if key in ("voice_to_text", "text_to_voice"):
+            self._refresh_voice_routing()
+        return json.dumps({"status": "success", key: value})
+
+    def _set_asr(self, provider_id: str, model: str) -> str:
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config["voice_to_text"] = provider_id
+        file_cfg["voice_to_text"] = provider_id
+        # Only overwrite the model when one is supplied. An empty model means
+        # "keep whatever is configured" so switching provider from the console
+        # never wipes a user's hand-set voice_to_text_model (runtime falls back
+        # to the engine default via `or DEFAULT_ASR_MODEL` regardless).
+        if model:
+            local_config["voice_to_text_model"] = model
+            file_cfg["voice_to_text_model"] = model
+        self._write_file_config(file_cfg)
+        logger.info(
+            f"[ModelsHandler] asr updated: provider={provider_id!r} "
+            f"model={model!r}"
+        )
+        self._refresh_voice_routing()
+        return json.dumps({
+            "status": "success",
+            "provider": provider_id,
+            "model": local_config.get("voice_to_text_model", ""),
+        })
+
+    def _set_tts(self, provider_id: str, model: str, voice: str = "") -> str:
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config["text_to_voice"] = provider_id
+        file_cfg["text_to_voice"] = provider_id
+        local_config["text_to_voice_model"] = model
+        file_cfg["text_to_voice_model"] = model
+        local_config["tts_voice_id"] = voice
+        file_cfg["tts_voice_id"] = voice
+        self._write_file_config(file_cfg)
+        logger.info(
+            f"[ModelsHandler] tts updated: provider={provider_id!r} "
+            f"model={model!r} voice={voice!r}"
+        )
+        self._refresh_voice_routing()
+        return json.dumps({
+            "status": "success",
+            "provider": provider_id, "model": model, "voice": voice,
+        })
+
+    @staticmethod
+    def _refresh_voice_routing() -> None:
+        try:
+            from bridge.bridge import Bridge
+            Bridge().refresh_voice()
+        except Exception as e:
+            logger.warning(f"[ModelsHandler] Bridge voice refresh failed: {e}")
+
+    def _set_embedding(self, provider_id: str, model: str) -> str:
+        # Validate provider_id — mirrors _set_chat's validation pattern.
+        if provider_id.startswith("custom:"):
+            from models.custom_provider import parse_custom_bot_type
+            _, custom_id = parse_custom_bot_type(provider_id)
+            providers = self._normalize_custom_providers(conf().get("custom_providers"))
+            custom_provider = next((p for p in providers if p.get("id") == custom_id), None)
+            if custom_provider is None:
+                return json.dumps({"status": "error", "message": f"unknown custom provider id: {custom_id}"})
+            # Fall back to the custom provider's default model when none is given.
+            if not model:
+                model = custom_provider.get("model") or ""
+        elif provider_id and provider_id not in {p for p in ModelsHandler._EMBEDDING_PROVIDERS if p != "custom"}:
+            return json.dumps({"status": "error", "message": f"unknown provider: {provider_id}"})
+
+        # A provider without a model leaves the runtime in a broken half-state,
+        # so reject that explicitly instead of silently writing it through.
+        if provider_id and not model:
+            return json.dumps({
+                "status": "error",
+                "message": "embedding model is required when a provider is selected",
+            })
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        local_config["embedding_provider"] = provider_id
+        file_cfg["embedding_provider"] = provider_id
+        local_config["embedding_model"] = model
+        file_cfg["embedding_model"] = model
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] embedding updated: provider={provider_id!r} model={model!r}")
+        # The next /memory rebuild-index command hot-swaps the provider onto
+        # the running MemoryManager (see plugins/cow_cli). The dim may have
+        # changed, so the frontend prompts the user to rebuild.
+        return json.dumps({"status": "success", "provider": provider_id, "model": model})
+
+    def _set_search(self, strategy: str, provider: str) -> str:
+        """Persist search routing under tools.web_search.{strategy,provider}.
+
+        strategy 'auto'  -> provider field is cleared (auto picks at call time)
+        strategy 'fixed' -> provider must be in the canonical list; runtime
+                            silently falls back to auto if its key is missing.
+        """
+        if strategy not in ("auto", "fixed"):
+            return json.dumps({"status": "error", "message": f"invalid strategy: {strategy!r}"})
+        if strategy == "fixed":
+            if provider not in self._SEARCH_PROVIDERS:
+                return json.dumps({"status": "error", "message": f"unknown provider: {provider!r}"})
+        else:
+            provider = ""
+
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        self._set_nested_namespace_value(local_config, "tools", "web_search", "strategy", strategy)
+        self._set_nested_namespace_value(file_cfg,     "tools", "web_search", "strategy", strategy)
+        self._set_nested_namespace_value(local_config, "tools", "web_search", "provider", provider)
+        self._set_nested_namespace_value(file_cfg,     "tools", "web_search", "provider", provider)
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] search updated: strategy={strategy!r} provider={provider!r}")
+        return json.dumps({"status": "success", "strategy": strategy, "provider": provider})
+
+    def _handle_set_search_credential(self, data: dict) -> str:
+        """Persist the bocha API key under tools.web_search.bocha_api_key.
+
+        The other three providers (zhipu/qianfan/linkai) reuse model-vendor
+        credentials, so they go through set_provider with the standard
+        model-vendor flow.
+        """
+        api_key = (data.get("api_key") or "").strip() if isinstance(data.get("api_key"), str) else ""
+        local_config = conf()
+        file_cfg = self._read_file_config()
+        self._set_nested_namespace_value(local_config, "tools", "web_search", "bocha_api_key", api_key)
+        self._set_nested_namespace_value(file_cfg,     "tools", "web_search", "bocha_api_key", api_key)
+        self._write_file_config(file_cfg)
+        logger.info(f"[ModelsHandler] search credential set: bocha_api_key={'***' if api_key else ''}")
+        return json.dumps({"status": "success", "provider": "bocha"})
+
+    @staticmethod
+    def _reset_bridge() -> None:
+        try:
+            from bridge.bridge import Bridge
+            Bridge().reset_bot()
+            logger.info("[ModelsHandler] Bridge bot routing reset")
+        except Exception as e:
+            logger.warning(f"[ModelsHandler] Bridge reset failed: {e}")
+
+
+class ChannelsHandler:
+    """API for managing external channel configurations (feishu, dingtalk, etc)."""
+
+    CHANNEL_DEFS = OrderedDict([
+        ("weixin", {
+            "label": {"zh": "微信", "en": "WeChat"},
+            "icon": "fa-comment",
+            "color": "emerald",
+            "fields": [],
+        }),
+        ("feishu", {
+            "label": {"zh": "飞书", "en": "Feishu"},
+            "icon": "fa-paper-plane",
+            "color": "blue",
+            "fields": [
+                {"key": "feishu_app_id", "label": "App ID", "type": "text"},
+                {"key": "feishu_app_secret", "label": "App Secret", "type": "secret"},
+            ],
+        }),
+        ("dingtalk", {
+            "label": {"zh": "钉钉", "en": "DingTalk"},
+            "icon": "fa-comments",
+            "color": "blue",
+            "fields": [
+                {"key": "dingtalk_client_id", "label": "Client ID", "type": "text"},
+                {"key": "dingtalk_client_secret", "label": "Client Secret", "type": "secret"},
+            ],
+        }),
+        ("wecom_bot", {
+            "label": {"zh": "企微智能机器人", "en": "WeCom Bot"},
+            "icon": "fa-robot",
+            "color": "emerald",
+            "fields": [
+                {"key": "wecom_bot_id", "label": "Bot ID", "type": "text"},
+                {"key": "wecom_bot_secret", "label": "Secret", "type": "secret"},
+            ],
+        }),
+        ("qq", {
+            "label": {"zh": "QQ 机器人", "en": "QQ Bot"},
+            "icon": "fa-comment",
+            "color": "blue",
+            "fields": [
+                {"key": "qq_app_id", "label": "App ID", "type": "text"},
+                {"key": "qq_app_secret", "label": "App Secret", "type": "secret"},
+            ],
+        }),
+        ("wechatcom_app", {
+            "label": {"zh": "企微自建应用", "en": "WeCom App"},
+            "icon": "fa-building",
+            "color": "emerald",
+            "fields": [
+                {"key": "wechatcom_corp_id", "label": "Corp ID", "type": "text"},
+                {"key": "wechatcomapp_agent_id", "label": "Agent ID", "type": "text"},
+                {"key": "wechatcomapp_secret", "label": "Secret", "type": "secret"},
+                {"key": "wechatcomapp_token", "label": "Token", "type": "secret"},
+                {"key": "wechatcomapp_aes_key", "label": "AES Key", "type": "secret"},
+                {"key": "wechatcomapp_port", "label": "Port", "type": "number", "default": 9898},
+            ],
+        }),
+        ("wechat_kf", {
+            "label": {"zh": "微信客服", "en": "WeChat Customer Service"},
+            "icon": "fa-headset",
+            "color": "emerald",
+            "fields": [
+                {"key": "wechat_kf_corp_id", "label": "Corp ID", "type": "text"},
+                {"key": "wechat_kf_secret", "label": "Secret", "type": "secret"},
+                {"key": "wechat_kf_token", "label": "Token", "type": "secret"},
+                {"key": "wechat_kf_aes_key", "label": "AES Key", "type": "secret"},
+                {"key": "wechat_kf_port", "label": "Port", "type": "number", "default": 9888},
+            ],
+        }),
+        ("wechatmp", {
+            "label": {"zh": "公众号", "en": "WeChat MP"},
+            "icon": "fa-comment-dots",
+            "color": "emerald",
+            "fields": [
+                {"key": "wechatmp_app_id", "label": "App ID", "type": "text"},
+                {"key": "wechatmp_app_secret", "label": "App Secret", "type": "secret"},
+                {"key": "wechatmp_token", "label": "Token", "type": "secret"},
+                {"key": "wechatmp_aes_key", "label": "AES Key", "type": "secret"},
+                {"key": "wechatmp_port", "label": "Port", "type": "number", "default": 8080},
+            ],
+        }),
+        ("telegram", {
+            "label": {"zh": "Telegram", "en": "Telegram"},
+            "icon": "fa-paper-plane",
+            "color": "sky",
+            "fields": [
+                {"key": "telegram_token", "label": "Bot Token", "type": "secret"},
+            ],
+        }),
+        ("slack", {
+            "label": {"zh": "Slack", "en": "Slack"},
+            "icon": "fa-hashtag",
+            "color": "purple",
+            "fields": [
+                {"key": "slack_bot_token", "label": "Bot Token (xoxb-)", "type": "secret"},
+                {"key": "slack_app_token", "label": "App Token (xapp-)", "type": "secret"},
+            ],
+        }),
+        ("discord", {
+            "label": {"zh": "Discord", "en": "Discord"},
+            "icon": "fa-discord",
+            "color": "indigo",
+            "fields": [
+                {"key": "discord_token", "label": "Bot Token", "type": "secret"},
+            ],
+        }),
+    ])
+
+    @staticmethod
+    def _get_weixin_login_status() -> str:
+        try:
+            import sys
+            app_module = sys.modules.get('__main__') or sys.modules.get('app')
+            mgr = getattr(app_module, '_channel_mgr', None) if app_module else None
+            if mgr:
+                ch = mgr.get_channel("weixin")
+                if ch and hasattr(ch, 'login_status'):
+                    return ch.login_status
+        except Exception:
+            pass
+        return "unknown"
+
+    @staticmethod
+    def _mask_secret(value: str) -> str:
+        if not value or len(value) <= 8:
+            return value
+        return value[:4] + "*" * (len(value) - 8) + value[-4:]
+
+    @staticmethod
+    def _parse_channel_list(raw) -> list:
+        if isinstance(raw, list):
+            return [ch.strip() for ch in raw if ch.strip()]
+        if isinstance(raw, str):
+            return [ch.strip() for ch in raw.split(",") if ch.strip()]
+        return []
+
+    @classmethod
+    def _active_channel_set(cls) -> set:
+        return set(cls._parse_channel_list(conf().get("channel_type", "")))
+
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from common import i18n
+            local_config = conf()
+            active_channels = self._active_channel_set()
+            # Desktop build ships without lark-oapi, so hide Feishu from the list.
+            desktop_mode = os.environ.get("COW_DESKTOP") == "1"
+            channels = []
+            is_hant = i18n.get_language() == i18n.ZH_HANT
+            for ch_name, ch_def in self.CHANNEL_DEFS.items():
+                if desktop_mode and ch_name == "feishu":
+                    continue
+                fields_out = []
+                for f in ch_def["fields"]:
+                    raw_val = local_config.get(f["key"], f.get("default", ""))
+                    if f["type"] == "secret" and raw_val:
+                        display_val = self._mask_secret(str(raw_val))
+                    else:
+                        display_val = raw_val
+                    
+                    label_val = f["label"]
+                    if is_hant and isinstance(label_val, str):
+                        label_val = i18n.to_traditional(label_val)
+                    elif is_hant and isinstance(label_val, dict):
+                        label_val = label_val.copy()
+                        label_val["zh-Hant"] = i18n.to_traditional(label_val.get("zh", ""))
+
+                    fields_out.append({
+                        "key": f["key"],
+                        "label": label_val,
+                        "type": f["type"],
+                        "value": display_val,
+                        "default": f.get("default", ""),
+                    })
+                
+                label_val = ch_def["label"]
+                if is_hant and isinstance(label_val, str):
+                    label_val = i18n.to_traditional(label_val)
+                elif is_hant and isinstance(label_val, dict):
+                    label_val = label_val.copy()
+                    label_val["zh-Hant"] = i18n.to_traditional(label_val.get("zh", ""))
+
+                ch_info = {
+                    "name": ch_name,
+                    "label": label_val,
+                    "icon": ch_def["icon"],
+                    "color": ch_def["color"],
+                    "active": ch_name in active_channels,
+                    "fields": fields_out,
+                }
+                if ch_name == "weixin" and ch_name in active_channels:
+                    ch_info["login_status"] = self._get_weixin_login_status()
+                channels.append(ch_info)
+            return json.dumps({"status": "success", "channels": channels}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Channels API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data())
+            action = body.get("action")
+            channel_name = body.get("channel")
+
+            if not action or not channel_name:
+                return json.dumps({"status": "error", "message": "action and channel required"})
+
+            if channel_name not in self.CHANNEL_DEFS:
+                return json.dumps({"status": "error", "message": f"unknown channel: {channel_name}"})
+
+            if action == "save":
+                return self._handle_save(channel_name, body.get("config", {}))
+            elif action == "connect":
+                return self._handle_connect(channel_name, body.get("config", {}))
+            elif action == "disconnect":
+                return self._handle_disconnect(channel_name)
+            else:
+                return json.dumps({"status": "error", "message": f"unknown action: {action}"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Channels POST error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def _handle_save(self, channel_name: str, updates: dict):
+        ch_def = self.CHANNEL_DEFS[channel_name]
+        valid_keys = {f["key"] for f in ch_def["fields"]}
+        secret_keys = {f["key"] for f in ch_def["fields"] if f["type"] == "secret"}
+
+        local_config = conf()
+        applied = {}
+        for key, value in updates.items():
+            if key not in valid_keys:
+                continue
+            if key in secret_keys:
+                if not value or (len(value) > 8 and "*" * 4 in value):
+                    continue
+            field_def = next((f for f in ch_def["fields"] if f["key"] == key), None)
+            if field_def:
+                if field_def["type"] == "number":
+                    value = int(value)
+                elif field_def["type"] == "bool":
+                    value = bool(value)
+            local_config[key] = value
+            applied[key] = value
+
+        if not applied:
+            return json.dumps({"status": "error", "message": "no valid fields to update"})
+
+        config_path = os.path.join(get_data_root(), "config.json")
+        if os.path.exists(config_path):
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_cfg = json.load(f)
+        else:
+            file_cfg = {}
+        file_cfg.update(applied)
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(file_cfg, f, indent=4, ensure_ascii=False)
+
+        logger.info(f"[WebChannel] Channel '{channel_name}' config updated: {list(applied.keys())}")
+
+        should_restart = False
+        active_channels = self._active_channel_set()
+        if channel_name in active_channels:
+            should_restart = True
+            try:
+                import sys
+                app_module = sys.modules.get('__main__') or sys.modules.get('app')
+                mgr = getattr(app_module, '_channel_mgr', None) if app_module else None
+                if mgr:
+                    threading.Thread(
+                        target=mgr.restart,
+                        args=(channel_name,),
+                        daemon=True,
+                    ).start()
+                    logger.info(f"[WebChannel] Channel '{channel_name}' restart triggered")
+            except Exception as e:
+                logger.warning(f"[WebChannel] Failed to restart channel '{channel_name}': {e}")
+
+        return json.dumps({
+            "status": "success",
+            "applied": list(applied.keys()),
+            "restarted": should_restart,
+        }, ensure_ascii=False)
+
+    def _handle_connect(self, channel_name: str, updates: dict):
+        """Save config fields, add channel to channel_type, and start it."""
+        ch_def = self.CHANNEL_DEFS[channel_name]
+        valid_keys = {f["key"] for f in ch_def["fields"]}
+        secret_keys = {f["key"] for f in ch_def["fields"] if f["type"] == "secret"}
+
+        # Feishu connected via web console must use websocket (long connection) mode
+        if channel_name == "feishu":
+            updates.setdefault("feishu_event_mode", "websocket")
+            valid_keys.add("feishu_event_mode")
+
+        local_config = conf()
+        applied = {}
+        for key, value in updates.items():
+            if key not in valid_keys:
+                continue
+            if key in secret_keys:
+                if not value or (len(value) > 8 and "*" * 4 in value):
+                    continue
+            field_def = next((f for f in ch_def["fields"] if f["key"] == key), None)
+            if field_def:
+                if field_def["type"] == "number":
+                    value = int(value)
+                elif field_def["type"] == "bool":
+                    value = bool(value)
+            local_config[key] = value
+            applied[key] = value
+
+        existing = self._parse_channel_list(conf().get("channel_type", ""))
+        if channel_name not in existing:
+            existing.append(channel_name)
+        new_channel_type = ",".join(existing)
+        local_config["channel_type"] = new_channel_type
+
+        config_path = os.path.join(get_data_root(), "config.json")
+        if os.path.exists(config_path):
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_cfg = json.load(f)
+        else:
+            file_cfg = {}
+        file_cfg.update(applied)
+        file_cfg["channel_type"] = new_channel_type
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(file_cfg, f, indent=4, ensure_ascii=False)
+
+        logger.info(f"[WebChannel] Channel '{channel_name}' connecting, channel_type={new_channel_type}")
+
+        def _do_start():
+            try:
+                import sys
+                app_module = sys.modules.get('__main__') or sys.modules.get('app')
+                clear_fn = getattr(app_module, '_clear_singleton_cache', None) if app_module else None
+                mgr = getattr(app_module, '_channel_mgr', None) if app_module else None
+                if mgr is None:
+                    logger.warning(f"[WebChannel] ChannelManager not available, cannot start '{channel_name}'")
+                    return
+                # Stop existing instance first if still running (e.g. re-connect without disconnect)
+                existing_ch = mgr.get_channel(channel_name)
+                if existing_ch is not None:
+                    logger.info(f"[WebChannel] Stopping existing '{channel_name}' before reconnect...")
+                    mgr.stop(channel_name)
+                # Always wait for the remote service to release the old connection before
+                # establishing a new one (DingTalk drops callbacks on duplicate connections)
+                logger.info(f"[WebChannel] Waiting for '{channel_name}' old connection to close...")
+                time.sleep(5)
+                if clear_fn:
+                    clear_fn(channel_name)
+                logger.info(f"[WebChannel] Starting channel '{channel_name}'...")
+                mgr.start([channel_name], first_start=False)
+                logger.info(f"[WebChannel] Channel '{channel_name}' start completed")
+            except Exception as e:
+                logger.error(f"[WebChannel] Failed to start channel '{channel_name}': {e}",
+                             exc_info=True)
+
+        threading.Thread(target=_do_start, daemon=True).start()
+
+        return json.dumps({
+            "status": "success",
+            "channel_type": new_channel_type,
+        }, ensure_ascii=False)
+
+    def _handle_disconnect(self, channel_name: str):
+        existing = self._parse_channel_list(conf().get("channel_type", ""))
+        existing = [ch for ch in existing if ch != channel_name]
+        new_channel_type = ",".join(existing)
+
+        local_config = conf()
+        local_config["channel_type"] = new_channel_type
+
+        config_path = os.path.join(get_data_root(), "config.json")
+        if os.path.exists(config_path):
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_cfg = json.load(f)
+        else:
+            file_cfg = {}
+        file_cfg["channel_type"] = new_channel_type
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(file_cfg, f, indent=4, ensure_ascii=False)
+
+        def _do_stop():
+            try:
+                import sys
+                app_module = sys.modules.get('__main__') or sys.modules.get('app')
+                mgr = getattr(app_module, '_channel_mgr', None) if app_module else None
+                clear_fn = getattr(app_module, '_clear_singleton_cache', None) if app_module else None
+                if mgr:
+                    mgr.stop(channel_name)
+                else:
+                    logger.warning(f"[WebChannel] ChannelManager not found, cannot stop '{channel_name}'")
+                if clear_fn:
+                    clear_fn(channel_name)
+                logger.info(f"[WebChannel] Channel '{channel_name}' disconnected, "
+                            f"channel_type={new_channel_type}")
+            except Exception as e:
+                logger.warning(f"[WebChannel] Failed to stop channel '{channel_name}': {e}",
+                               exc_info=True)
+
+        threading.Thread(target=_do_stop, daemon=True).start()
+
+        return json.dumps({
+            "status": "success",
+            "channel_type": new_channel_type,
+        }, ensure_ascii=False)
+
+
+class WeixinQrHandler:
+    """Handle WeChat QR code login from the web console.
+
+    GET  /api/weixin/qrlogin          → fetch a new QR code
+    POST /api/weixin/qrlogin          → poll QR status or start channel after login
+    """
+
+    _qr_state = {}
+
+    @staticmethod
+    def _qr_to_data_uri(data: str) -> str:
+        """Generate a QR code as a PNG data URI."""
+        try:
+            import qrcode as qr_lib
+            import io
+            import base64
+            qr = qr_lib.QRCode(error_correction=qr_lib.constants.ERROR_CORRECT_L, box_size=6, border=2)
+            qr.add_data(data)
+            qr.make(fit=True)
+            img = qr.make_image(fill_color="black", back_color="white")
+            buf = io.BytesIO()
+            img.save(buf, format="PNG")
+            b64 = base64.b64encode(buf.getvalue()).decode("ascii")
+            return f"data:image/png;base64,{b64}"
+        except ImportError:
+            return ""
+
+    @staticmethod
+    def _get_running_channel():
+        try:
+            import sys
+            app_module = sys.modules.get('__main__') or sys.modules.get('app')
+            mgr = getattr(app_module, '_channel_mgr', None) if app_module else None
+            if mgr:
+                return mgr.get_channel("weixin")
+        except Exception:
+            pass
+        return None
+
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            running_ch = self._get_running_channel()
+            if running_ch and hasattr(running_ch, '_current_qr_url') and running_ch._current_qr_url:
+                qr_image = self._qr_to_data_uri(running_ch._current_qr_url)
+                return json.dumps({
+                    "status": "success",
+                    "qrcode_url": running_ch._current_qr_url,
+                    "qr_image": qr_image,
+                    "source": "channel",
+                })
+
+            from channel.weixin.weixin_api import WeixinApi, DEFAULT_BASE_URL
+            base_url = conf().get("weixin_base_url", DEFAULT_BASE_URL)
+            api = WeixinApi(base_url=base_url)
+            qr_resp = api.fetch_qr_code()
+            qrcode = qr_resp.get("qrcode", "")
+            qrcode_url = qr_resp.get("qrcode_img_content", "")
+            if not qrcode:
+                return json.dumps({"status": "error", "message": "No QR code returned"})
+            qr_image = self._qr_to_data_uri(qrcode_url)
+            WeixinQrHandler._qr_state = {
+                "qrcode": qrcode,
+                "qrcode_url": qrcode_url,
+                "base_url": base_url,
+            }
+            return json.dumps({"status": "success", "qrcode_url": qrcode_url, "qr_image": qr_image})
+        except Exception as e:
+            logger.error(f"[WebChannel] WeixinQr GET error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data())
+            action = body.get("action", "poll")
+
+            if action == "poll":
+                return self._poll_status()
+            elif action == "refresh":
+                return self.GET()
+            else:
+                return json.dumps({"status": "error", "message": f"unknown action: {action}"})
+        except Exception as e:
+            logger.error(f"[WebChannel] WeixinQr POST error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def _poll_status(self):
+        state = WeixinQrHandler._qr_state
+        qrcode = state.get("qrcode", "")
+        base_url = state.get("base_url", "")
+        if not qrcode:
+            return json.dumps({"status": "error", "message": "No active QR session"})
+
+        from channel.weixin.weixin_api import WeixinApi, DEFAULT_BASE_URL
+        api = WeixinApi(base_url=base_url or DEFAULT_BASE_URL)
+        try:
+            status_resp = api.poll_qr_status(qrcode, timeout=10)
+        except Exception as e:
+            return json.dumps({"status": "error", "message": str(e)})
+
+        qr_status = status_resp.get("status", "wait")
+
+        if qr_status == "confirmed":
+            bot_token = status_resp.get("bot_token", "")
+            bot_id = status_resp.get("ilink_bot_id", "")
+            result_base_url = status_resp.get("baseurl", base_url)
+            user_id = status_resp.get("ilink_user_id", "")
+
+            if not bot_token or not bot_id:
+                return json.dumps({"status": "error", "message": "Login confirmed but missing token"})
+
+            cred_path = get_weixin_credentials_path()
+            from channel.weixin.weixin_channel import _save_credentials
+            _save_credentials(cred_path, {
+                "token": bot_token,
+                "base_url": result_base_url,
+                "bot_id": bot_id,
+                "user_id": user_id,
+            })
+            conf()["weixin_token"] = bot_token
+            conf()["weixin_base_url"] = result_base_url
+
+            WeixinQrHandler._qr_state = {}
+            logger.info(f"[WebChannel] WeChat QR login confirmed: bot_id={bot_id}")
+
+            return json.dumps({
+                "status": "success",
+                "qr_status": "confirmed",
+                "bot_id": bot_id,
+            })
+
+        if qr_status == "expired":
+            new_resp = api.fetch_qr_code()
+            new_qrcode = new_resp.get("qrcode", "")
+            new_qrcode_url = new_resp.get("qrcode_img_content", "")
+            new_qr_image = self._qr_to_data_uri(new_qrcode_url)
+            WeixinQrHandler._qr_state["qrcode"] = new_qrcode
+            WeixinQrHandler._qr_state["qrcode_url"] = new_qrcode_url
+            return json.dumps({
+                "status": "success",
+                "qr_status": "expired",
+                "qrcode_url": new_qrcode_url,
+                "qr_image": new_qr_image,
+            })
+
+        return json.dumps({"status": "success", "qr_status": qr_status})
+
+
+class FeishuRegisterHandler:
+    """飞书智能体应用一键创建（OAuth 设备授权流，基于 lark.register_app SDK）。
+
+    GET  /api/feishu/register   → 启动注册：调用 SDK 生成二维码 URL，立即返回；
+                                   后台线程继续轮询飞书侧直到用户扫码授权。
+    POST /api/feishu/register   → 轮询当前会话状态（pending / done / error / expired）。
+                                   注册成功后不直接写 config，由前端再调
+                                   /api/channels {action:'connect'} 走标准启用流程。
+    """
+
+    # 进程内单例状态（{url, expire_in, status, app_id, app_secret, error, thread}）。
+    # 简单的本地自部署场景下不需要 session 隔离。
+    _state = {}
+    _lock = threading.Lock()
+
+    @staticmethod
+    def _qr_to_data_uri(data: str) -> str:
+        """复用 WeixinQrHandler 的二维码渲染。"""
+        return WeixinQrHandler._qr_to_data_uri(data)
+
+    @classmethod
+    def _reset_state(cls):
+        with cls._lock:
+            cls._state = {}
+
+    @classmethod
+    def _start_register_thread(cls):
+        """启动一次新的注册会话。如已有进行中的会话，先取消（通过 cancel_event）。"""
+        # 先取消可能存在的上一次会话，避免两个 SDK 线程并发 poll 同一个端点
+        with cls._lock:
+            old_cancel = cls._state.get("cancel_event") if cls._state else None
+            if old_cancel is not None:
+                old_cancel.set()
+            cancel_event = threading.Event()
+            cls._state = {"status": "starting", "cancel_event": cancel_event}
+
+        def _worker():
+            try:
+                import lark_oapi as lark
+            except ImportError:
+                with cls._lock:
+                    cls._state["status"] = "error"
+                    cls._state["error"] = "lark-oapi SDK 未安装，请执行 pip install -U lark-oapi"
+                return
+
+            def _on_qr(info):
+                # SDK 拿到二维码 URL 后立即回调；写入 state 让前端 GET 立刻能拿到
+                with cls._lock:
+                    cls._state["url"] = info.get("url", "")
+                    cls._state["expire_in"] = info.get("expire_in", 600)
+                    cls._state["qr_image"] = cls._qr_to_data_uri(info.get("url", ""))
+                    cls._state["status"] = "pending"
+                logger.info(f"[FeishuRegister] QR ready, expire_in={info.get('expire_in')}s")
+
+            def _on_status(info):
+                # 过滤掉 polling 心跳（每 5 秒一次，纯噪音）；
+                # 保留 slow_down / domain_switched 等真正的状态切换事件
+                status = info.get("status")
+                if status == "polling":
+                    return
+                logger.info(f"[FeishuRegister] SDK status: {info}")
+
+            try:
+                result = lark.register_app(
+                    on_qr_code=_on_qr,
+                    on_status_change=_on_status,
+                    source="cowagent",
+                    cancel_event=cancel_event,
+                )
+                with cls._lock:
+                    cls._state["status"] = "done"
+                    cls._state["app_id"] = result.get("client_id", "")
+                    cls._state["app_secret"] = result.get("client_secret", "")
+                logger.info(f"[FeishuRegister] App created: app_id={result.get('client_id')}")
+            except Exception as e:
+                err_msg = str(e)
+                err_cls = e.__class__.__name__
+                # 飞书 SDK 抛出的 AppExpiredError / AppAccessDeniedError / RegisterAppError
+                if "Expired" in err_cls:
+                    status = "expired"
+                elif "Denied" in err_cls:
+                    status = "denied"
+                elif "abort" in err_msg.lower() or "cancel" in err_msg.lower():
+                    # 被新一轮注册抢占，保持安静
+                    return
+                else:
+                    status = "error"
+                with cls._lock:
+                    # 仅当当前 state 仍属于本次 worker 时才写入，避免覆盖更新的会话
+                    if cls._state.get("cancel_event") is cancel_event:
+                        cls._state["status"] = status
+                        cls._state["error"] = err_msg
+                logger.warning(f"[FeishuRegister] Register failed ({err_cls}): {err_msg}")
+
+        threading.Thread(target=_worker, daemon=True, name="feishu-register").start()
+
+    def GET(self):
+        """启动一次新的注册会话。如果已有 pending/done 会话则覆盖。"""
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            self._start_register_thread()
+            # 等待 SDK 拿到二维码 URL（最多 10s）。SDK 内部会马上回调 _on_qr。
+            import time as _t
+            for _ in range(100):
+                with self._lock:
+                    if self._state.get("url") or self._state.get("status") in ("error", "expired", "denied"):
+                        break
+                _t.sleep(0.1)
+            with self._lock:
+                if self._state.get("status") in ("error", "expired", "denied"):
+                    return json.dumps({
+                        "status": "error",
+                        "message": self._state.get("error", "register failed"),
+                    })
+                if not self._state.get("url"):
+                    return json.dumps({
+                        "status": "error",
+                        "message": "等待飞书二维码超时，请重试",
+                    })
+                return json.dumps({
+                    "status": "success",
+                    "qrcode_url": self._state["url"],
+                    "qr_image": self._state.get("qr_image", ""),
+                    "expire_in": self._state.get("expire_in", 600),
+                })
+        except Exception as e:
+            logger.error(f"[WebChannel] FeishuRegister GET error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        """轮询注册结果。"""
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data() or b"{}")
+            action = body.get("action", "poll")
+            if action != "poll":
+                return json.dumps({"status": "error", "message": f"unknown action: {action}"})
+
+            with self._lock:
+                status = self._state.get("status", "idle")
+                if status == "done":
+                    payload = {
+                        "status": "success",
+                        "register_status": "done",
+                        "app_id": self._state.get("app_id", ""),
+                        "app_secret": self._state.get("app_secret", ""),
+                    }
+                    # 一次性返回凭据后清掉，避免敏感信息长期驻留内存
+                    self._state = {}
+                    return json.dumps(payload)
+                if status in ("error", "expired", "denied"):
+                    return json.dumps({
+                        "status": "success",
+                        "register_status": status,
+                        "message": self._state.get("error", ""),
+                    })
+                # pending / starting：还在等用户扫码
+                return json.dumps({
+                    "status": "success",
+                    "register_status": "pending",
+                })
+        except Exception as e:
+            logger.error(f"[WebChannel] FeishuRegister POST error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+def _get_workspace_root():
+    """Resolve the agent workspace directory."""
+    from common.utils import expand_path
+    return expand_path(conf().get("agent_workspace", "~/cow"))
+
+
+class ToolsHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.tools.tool_manager import ToolManager
+            from common import i18n
+            tm = ToolManager()
+            if not tm.tool_classes:
+                tm.load_tools()
+            tools = []
+            lang = i18n.get_language()
+            for name, cls in tm.tool_classes.items():
+                try:
+                    instance = cls()
+                    desc = instance.description
+                    if lang == i18n.ZH_HANT and desc:
+                        desc = i18n.to_traditional(desc)
+                    elif lang == "en" and name == "scheduler":
+                        desc = (
+                            "Create, query and manage scheduled tasks (reminders, periodic tasks, etc.).\n\n"
+                            "⚠️ IMPORTANT: Only use this tool when delayed or periodic execution is needed."
+                        )
+                    tools.append({
+                        "name": name,
+                        "description": desc,
+                    })
+                except Exception:
+                    tools.append({"name": name, "description": ""})
+            return json.dumps({"status": "success", "tools": tools}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Tools API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SkillsHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.skills.service import SkillService
+            from agent.skills.manager import SkillManager
+            from common import i18n
+            workspace_root = _get_workspace_root()
+            manager = SkillManager(custom_dir=os.path.join(workspace_root, "skills"))
+            service = SkillService(manager)
+            skills = service.query()
+            if i18n.get_language() == i18n.ZH_HANT:
+                for skill in skills:
+                    if isinstance(skill, dict):
+                        for k, v in list(skill.items()):
+                            if k in ("name", "description", "display_name") and isinstance(v, str):
+                                skill[k] = i18n.to_traditional(v)
+            return json.dumps({"status": "success", "skills": skills}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Skills API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.skills.service import SkillService
+            from agent.skills.manager import SkillManager
+            body = json.loads(web.data())
+            action = body.get("action")
+            name = body.get("name")
+            if not action or not name:
+                return json.dumps({"status": "error", "message": "action and name are required"})
+            workspace_root = _get_workspace_root()
+            manager = SkillManager(custom_dir=os.path.join(workspace_root, "skills"))
+            service = SkillService(manager)
+            if action == "open":
+                service.open({"name": name})
+            elif action == "close":
+                service.close({"name": name})
+            else:
+                return json.dumps({"status": "error", "message": f"unknown action: {action}"})
+            return json.dumps({"status": "success"}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Skills POST error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class MemoryHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.memory.service import MemoryService
+            params = web.input(page='1', page_size='20', category='memory')
+            workspace_root = _get_workspace_root()
+            service = MemoryService(workspace_root)
+            result = service.list_files(
+                page=int(params.page), page_size=int(params.page_size),
+                category=params.category,
+            )
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Memory API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class MemoryContentHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.memory.service import MemoryService
+            params = web.input(filename='', category='memory')
+            if not params.filename:
+                return json.dumps({"status": "error", "message": "filename required"})
+            workspace_root = _get_workspace_root()
+            service = MemoryService(workspace_root)
+            result = service.get_content(params.filename, category=params.category)
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except ValueError:
+            return json.dumps({"status": "error", "message": "invalid filename"})
+        except FileNotFoundError:
+            return json.dumps({"status": "error", "message": "file not found"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Memory content API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SchedulerHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.tools.scheduler.task_store import TaskStore
+            workspace_root = _get_workspace_root()
+            store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+            store = TaskStore(store_path)
+            tasks = store.list_tasks()
+            return json.dumps({"status": "success", "tasks": tasks}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Scheduler API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SchedulerToggleHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data())
+            task_id = body.get("task_id")
+            enabled = body.get("enabled", True)
+            if not task_id:
+                return json.dumps({"status": "error", "message": "task_id required"})
+            from agent.tools.scheduler.task_store import TaskStore
+            workspace_root = _get_workspace_root()
+            store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+            store = TaskStore(store_path)
+            store.enable_task(task_id, enabled)
+            task = store.get_task(task_id)
+            return json.dumps({"status": "success", "task": task}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Scheduler toggle error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SchedulerUpdateHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data())
+            task_id = body.get("task_id")
+            if not task_id:
+                return json.dumps({"status": "error", "message": "task_id required"})
+            
+            from agent.tools.scheduler.task_store import TaskStore
+            from agent.tools.scheduler.scheduler_service import SchedulerService
+            from datetime import datetime
+            workspace_root = _get_workspace_root()
+            store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+            store = TaskStore(store_path)
+            
+            # Get original task (single query to avoid repeated I/O)
+            original_task = store.get_task(task_id)
+            if not original_task:
+                return json.dumps({"status": "error", "message": f"Task '{task_id}' not found"})
+            
+            # Build updates dict
+            updates = {}
+            if "name" in body:
+                updates["name"] = body["name"]
+            if "enabled" in body:
+                updates["enabled"] = body["enabled"]
+            
+            # Update schedule
+            if "schedule" in body:
+                updates["schedule"] = body["schedule"]
+                # If schedule config changed, recalculate next_run_at
+                # Build merged temp task data for calculation (without modifying the original object)
+                merged = dict(original_task)
+                merged.update(updates)
+                if "action" in body:
+                    merged["action"] = body["action"]
+                temp_service = SchedulerService(store, lambda t: None)
+                next_run = temp_service._calculate_next_run(merged, datetime.now())
+                if next_run:
+                    updates["next_run_at"] = next_run.isoformat()
+                else:
+                    # Cannot calculate next run time, schedule config may be invalid
+                    return json.dumps({
+                        "status": "error", 
+                        "message": "Cannot calculate next run time. Please check the schedule config (e.g., cron expression format, or whether the one-time task time has already passed)."
+                    }, ensure_ascii=False)
+            
+            # Update action
+            if "action" in body:
+                action = body["action"]
+                channel_type = action.get("channel_type", "web")
+                
+                # Get the task's original channel_type
+                old_channel = original_task.get("action", {}).get("channel_type", "web")
+                
+                # If channel type changed or no receiver, reject the update.
+                # Note: the web UI disables the channel selector, so this branch
+                # is only reachable via direct API calls. Changing a task's channel
+                # after creation is not supported because the receiver identity is
+                # channel-bound and cannot be trivially re-populated (e.g. weixin
+                # requires a valid context_token tied to the original user-session).
+                if old_channel and old_channel != channel_type:
+                    return json.dumps({
+                        "status": "error",
+                        "message": f"Cannot change channel type from '{old_channel}' to '{channel_type}'. Please create a new task on the target channel instead."
+                    }, ensure_ascii=False)
+                if not action.get("receiver"):
+                    return json.dumps({
+                        "status": "error",
+                        "message": "Receiver is required. Please create a new task through the chat interface."
+                    }, ensure_ascii=False)
+                updates["action"] = action
+                
+                # If schedule was not updated but action was, ensure next_run_at exists
+                if "schedule" not in body and "next_run_at" not in original_task:
+                    merged = dict(original_task)
+                    merged.update(updates)
+                    temp_service = SchedulerService(store, lambda t: None)
+                    next_run = temp_service._calculate_next_run(merged, datetime.now())
+                    if next_run:
+                        updates["next_run_at"] = next_run.isoformat()
+            
+            store.update_task(task_id, updates)
+            task = store.get_task(task_id)
+            return json.dumps({"status": "success", "task": task}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Scheduler update error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SchedulerDeleteHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data())
+            task_id = body.get("task_id")
+            if not task_id:
+                return json.dumps({"status": "error", "message": "task_id required"})
+            
+            from agent.tools.scheduler.task_store import TaskStore
+            workspace_root = _get_workspace_root()
+            store_path = os.path.join(workspace_root, "scheduler", "tasks.json")
+            store = TaskStore(store_path)
+            store.delete_task(task_id)
+            return json.dumps({"status": "success"}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Scheduler delete error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionsHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            params = web.input(page='1', page_size='50')
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            result = store.list_sessions(
+                channel_type="web",
+                page=int(params.page),
+                page_size=int(params.page_size),
+            )
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Sessions API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionDetailHandler:
+    def DELETE(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        logger.info(f"[WebChannel] DELETE session request: {session_id}")
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            store.clear_session(session_id)
+
+            # Also remove the Agent instance from AgentBridge if exists
+            try:
+                from bridge.bridge import Bridge
+                ab = Bridge().get_agent_bridge()
+                if session_id in ab.agents:
+                    del ab.agents[session_id]
+                    logger.info(f"[WebChannel] Removed agent instance for session {session_id}")
+            except Exception:
+                pass
+
+            channel = WebChannel()
+            channel.session_queues.pop(session_id, None)
+
+            logger.info(f"[WebChannel] Session deleted: {session_id}")
+            return json.dumps({"status": "success"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Session delete error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def PUT(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+            body = json.loads(web.data())
+            title = body.get("title", "").strip()
+            if not title:
+                return json.dumps({"status": "error", "message": "title required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            found = store.rename_session(session_id, title)
+            if not found:
+                return json.dumps({"status": "error", "message": "session not found"})
+            return json.dumps({"status": "success"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Session rename error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionTitleHandler:
+    def POST(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            body = json.loads(web.data())
+            user_message = body.get("user_message", "")
+            assistant_reply = body.get("assistant_reply", "")
+            if not user_message:
+                return json.dumps({"status": "error", "message": "user_message required"})
+
+            title = _generate_session_title(user_message, assistant_reply)
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            updated = store.rename_session(session_id, title)
+            logger.info(f"[WebChannel] Session title set: sid={session_id}, title='{title}', db_updated={updated}")
+
+            return json.dumps({"status": "success", "title": title}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Title generation error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionClearContextHandler:
+    def POST(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            new_seq = store.clear_context(session_id)
+
+            # Delete the agent instance so a fresh one is created on the next message
+            try:
+                from bridge.bridge import Bridge
+                bridge = Bridge()
+                ab = bridge.get_agent_bridge()
+                if session_id in ab.agents:
+                    del ab.agents[session_id]
+                    logger.info(f"[WebChannel] Cleared agent instance for session {session_id}")
+            except Exception:
+                pass
+
+            return json.dumps({"status": "success", "context_start_seq": new_seq})
+        except Exception as e:
+            logger.error(f"[WebChannel] Clear context error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class HistoryHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        web.header('Access-Control-Allow-Origin', '*')
+        try:
+            params = web.input(session_id='', page='1', page_size='20')
+            session_id = params.session_id.strip()
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            result = store.load_history_page(
+                session_id=session_id,
+                page=int(params.page),
+                page_size=int(params.page_size),
+            )
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] History API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class MessageDeleteHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        web.header('Access-Control-Allow-Origin', '*')
+        try:
+            data = json.loads(web.data())
+            session_id = data.get('session_id', '').strip()
+            user_seq = data.get('user_seq')
+            delete_user = data.get('delete_user', True)
+            cascade = data.get('cascade', False)
+            
+            if not session_id or user_seq is None:
+                return json.dumps({"status": "error", "message": "session_id and user_seq required"})
+            
+            # 1. Delete from database
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            deleted = store.delete_message_pair(session_id, int(user_seq), delete_user=delete_user, cascade=cascade)
+
+            # 2. Sync agent's in-memory context so its next turn sees the
+            # same history as the DB. Handled by the agent_bridge helper.
+            try:
+                from bridge.bridge import Bridge
+                Bridge().get_agent_bridge().sync_session_messages_from_store(session_id)
+            except Exception as sync_err:
+                logger.warning(f"[WebChannel] Failed to sync agent memory: {sync_err}")
+
+            return json.dumps({"status": "success", "deleted": deleted}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Message delete error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class LogsHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'text/event-stream; charset=utf-8')
+        web.header('Cache-Control', 'no-cache')
+        web.header('X-Accel-Buffering', 'no')
+
+        log_path = os.path.join(get_data_root(), "run.log")
+
+        def generate():
+            if not os.path.isfile(log_path):
+                yield b"data: {\"type\": \"error\", \"message\": \"run.log not found\"}\n\n"
+                return
+
+            # Read last 200 lines for initial display
+            try:
+                with open(log_path, 'r', encoding='utf-8', errors='replace') as f:
+                    lines = f.readlines()
+                tail_lines = lines[-200:]
+                chunk = ''.join(tail_lines)
+                payload = json.dumps({"type": "init", "content": chunk}, ensure_ascii=False)
+                yield f"data: {payload}\n\n".encode('utf-8')
+            except Exception as e:
+                yield f"data: {{\"type\": \"error\", \"message\": \"{e}\"}}\n\n".encode('utf-8')
+                return
+
+            # Tail new lines
+            try:
+                with open(log_path, 'r', encoding='utf-8', errors='replace') as f:
+                    f.seek(0, 2)  # seek to end
+                    deadline = time.time() + 600  # 10 min max
+                    while time.time() < deadline:
+                        line = f.readline()
+                        if line:
+                            payload = json.dumps({"type": "line", "content": line}, ensure_ascii=False)
+                            yield f"data: {payload}\n\n".encode('utf-8')
+                        else:
+                            yield b": keepalive\n\n"
+                            time.sleep(1)
+            except GeneratorExit:
+                return
+            except Exception:
+                return
+
+        return generate()
+
+
+class AssetsHandler:
+    def GET(self, file_path):  # 修改默认参数
+        try:
+            # 如果请求是/static/，需要处理
+            if file_path == '':
+                # 返回目录列表...
+                pass
+
+            # 获取当前文件的绝对路径
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            static_dir = os.path.join(current_dir, 'static')
+
+            full_path = os.path.normpath(os.path.join(static_dir, file_path))
+
+            # 安全检查：确保请求的文件在static目录内
+            if not os.path.abspath(full_path).startswith(os.path.abspath(static_dir)):
+                logger.error(f"Security check failed for path: {full_path}")
+                raise web.notfound()
+
+            if not os.path.exists(full_path) or not os.path.isfile(full_path):
+                # Browsers routinely probe optional asset variants (e.g. a
+                # .ttf fallback declared alongside .woff2 in @font-face);
+                # logging these as errors floods the console with harmless
+                # noise. Keep it at debug level — real misconfigurations
+                # will still surface via the network panel.
+                logger.debug(f"Static file not found: {full_path}")
+                raise web.notfound()
+
+            # 设置正确的Content-Type
+            content_type = mimetypes.guess_type(full_path)[0]
+            if content_type:
+                web.header('Content-Type', content_type)
+            else:
+                # 默认为二进制流
+                web.header('Content-Type', 'application/octet-stream')
+
+            # 读取并返回文件内容
+            with open(full_path, 'rb') as f:
+                return f.read()
+
+        except web.HTTPError:
+            # The 404 path above already logged at debug; re-raise as-is so
+            # web.py returns the original status to the client.
+            raise
+        except Exception as e:
+            logger.error(f"Error serving static file: {e}", exc_info=True)
+            raise web.notfound()
+
+
+class KnowledgeListHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            svc = KnowledgeService(_get_workspace_root())
+            result = svc.list_tree()
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge list error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class KnowledgeReadHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            params = web.input(path='')
+            svc = KnowledgeService(_get_workspace_root())
+            result = svc.read_file(params.path)
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except (ValueError, FileNotFoundError) as e:
+            return json.dumps({"status": "error", "message": str(e)})
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge read error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class KnowledgeGraphHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            svc = KnowledgeService(_get_workspace_root())
+            return json.dumps(svc.build_graph(), ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge graph error: {e}")
+            return json.dumps({"nodes": [], "links": []})
+
+
+class KnowledgeActionHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            body = json.loads(web.data() or b"{}")
+            action = body.get("action", "")
+            payload = body.get("payload") or {}
+            from agent.knowledge.service import KnowledgeService
+            result = KnowledgeService(_get_workspace_root()).dispatch(action, payload)
+            return json.dumps({
+                "status": "success" if result["code"] < 300 else "error",
+                **result,
+            }, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge action error: {e}")
+            return json.dumps({"status": "error", "code": 500, "message": str(e), "payload": None})
+
+
+class KnowledgeImportHandler:
+    def POST(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            content_length = int(getattr(web.ctx, "env", {}).get("CONTENT_LENGTH") or 0)
+            if content_length > KnowledgeService.MAX_IMPORT_TOTAL_SIZE:
+                return json.dumps({
+                    "status": "error",
+                    "code": 413,
+                    "message": "import batch too large",
+                    "payload": None,
+                })
+            params = _raw_web_input()
+            target_category = params.get("target_category", "")
+            conflict_strategy = params.get("conflict_strategy", "skip")
+            uploaded = _ensure_list(params.get("files"))
+            single = params.get("file")
+            if single is not None:
+                uploaded.append(single)
+            if not uploaded:
+                return json.dumps({"status": "error", "code": 400, "message": "No files uploaded", "payload": None})
+            if len(uploaded) > KnowledgeService.MAX_IMPORT_FILES:
+                return json.dumps({
+                    "status": "error",
+                    "code": 400,
+                    "message": f"too many files: max {KnowledgeService.MAX_IMPORT_FILES}",
+                    "payload": None,
+                })
+
+            files = []
+            total_size = 0
+            for file_obj in uploaded:
+                if file_obj is None:
+                    continue
+                filename = getattr(file_obj, "filename", "") or getattr(file_obj, "name", "")
+                content = _read_uploaded_file_bytes_limited(file_obj, KnowledgeService.MAX_IMPORT_FILE_SIZE)
+                total_size += len(content)
+                if total_size > KnowledgeService.MAX_IMPORT_TOTAL_SIZE:
+                    return json.dumps({
+                        "status": "error",
+                        "code": 413,
+                        "message": "import batch too large",
+                        "payload": None,
+                    })
+                files.append({
+                    "filename": filename,
+                    "content": content,
+                })
+
+            result = KnowledgeService(_get_workspace_root()).dispatch("import_documents", {
+                "target_category": target_category,
+                "conflict_strategy": conflict_strategy,
+                "files": files,
+            })
+            return json.dumps({
+                "status": "success" if result["code"] < 300 else "error",
+                **result,
+            }, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge import error: {e}", exc_info=True)
+            return json.dumps({"status": "error", "code": 500, "message": str(e), "payload": None})
+
+
+class VersionHandler:
+    def GET(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        from cli import __version__
+        return json.dumps({"version": __version__})
diff --git a/channel/wechat_kf/README.md b/channel/wechat_kf/README.md
new file mode 100644
index 0000000..ab139f4
--- /dev/null
+++ b/channel/wechat_kf/README.md
@@ -0,0 +1,115 @@
+# 微信客服（WeChat Customer Service）通道
+
+> 与 `channel/wechatcom/`（企微自建应用）是两个**独立的 CoW 通道**：
+>
+> - 自建应用：**面向企业内部成员**（员工通过企业微信 App 与机器人对话）。
+> - 微信客服：**面向外部微信用户**（普通微信用户通过链接/二维码进入对话）。
+>
+> 但底层都基于"企微自建应用"——本通道是**通过把一个企微自建应用绑定到微信客服账号**来实现 AI 接管对外咨询，详见 [LinkAI 微信客服接入文档](https://docs.link-ai.tech/platform/link-app/wechat-customer-service)。
+
+## 一、接入流程概览
+
+```
+┌─────────────────────┐    ┌─────────────────────┐    ┌──────────────────┐
+│ 1. 企业微信后台      │ →  │ 2. CoW 配置回调      │ →  │ 3. 绑定微信客服   │
+│   创建一个自建应用   │    │   端口 9888          │    │   账号           │
+└─────────────────────┘    └─────────────────────┘    └──────────────────┘
+                                                              ↓
+                                                   外部微信用户通过
+                                                   链接/二维码 →
+                                                   消息 → CoW Bot
+```
+
+> **重要**：建议**单独再创建一个企微自建应用**用于微信客服，**不要复用**已经接入员工内部使用的那个 `wechatcom_app` 应用，否则两个通道会争抢同一个回调地址。
+
+## 二、企业微信后台配置
+
+### 1. 创建企微自建应用
+
+进入 企业微信管理后台 → **应用管理** → **创建应用**。
+
+### 2. 收集字段
+
+| 字段 | 来源 | 对应 CoW 配置项 |
+|---|---|---|
+| 企业ID（CorpId） | 「我的企业」最下方 | `wechat_kf_corp_id` |
+| Secret | 进入应用详情 → 点击「查看」（会推送到管理员手机端，在手机上查看） | `wechat_kf_secret` |
+| Token | 应用「接收消息 → 设置API接收」 | `wechat_kf_token` |
+| EncodingAESKey | 应用「接收消息 → 设置API接收」 | `wechat_kf_aes_key` |
+
+> AgentId 在本通道**不需要**（消息发送走的是 `cgi-bin/kf/send_msg`，不依赖 agent_id）。
+
+### 3. 配置回调地址 + 可信 IP
+
+在应用「**接收消息 → 设置API接收**」里填：
+
+- URL：`http://<your-host>:9888/wxkf/`（公网必须可达）
+- Token / EncodingAESKey：与下方 `config.json` 一致
+
+回到应用详情页，把服务器公网 IP 填入「**企业可信IP**」。
+
+### 4. 绑定微信客服账号
+
+进入 企业微信后台 → **微信客服** → 创建客服账号 → **将该账号绑定到上一步创建的企微自建应用**。
+
+绑定完成后，进入 **微信客服 → 微信客服账号详情** 页面，在「**接入链接**」一栏：
+
+- 「复制链接」可拿到形如 `https://work.weixin.qq.com/kfid/kfcd83e5896b9ba07be` 的访问链接
+- 「生成二维码」可拿到对应二维码
+
+把链接或二维码推给微信客户使用即可。
+
+## 三、CoW 配置（`config.json`）
+
+```json
+{
+  "channel_type": "wechat_kf",
+
+  "wechat_kf_corp_id": "ww1234567890abcdef",
+  "wechat_kf_secret": "<企微应用的 Secret>",
+  "wechat_kf_token": "<接收消息 Token>",
+  "wechat_kf_aes_key": "<EncodingAESKey>",
+  "wechat_kf_port": 9888
+}
+```
+
+| 字段 | 说明 |
+|---|---|
+| `wechat_kf_corp_id` | 企业 ID |
+| `wechat_kf_secret` | **绑定到微信客服**的那个企微自建应用的 Secret |
+| `wechat_kf_token` | 该应用「接收消息」配置的 Token |
+| `wechat_kf_aes_key` | 该应用「接收消息」配置的 EncodingAESKey |
+| `wechat_kf_port` | 监听端口，默认 `9888` |
+
+也支持环境变量：`WECHAT_KF_CORP_ID` / `WECHAT_KF_SECRET` / `WECHAT_KF_TOKEN` / `WECHAT_KF_AES_KEY`。
+
+## 四、运行
+
+```bash
+python app.py
+```
+
+启动后日志里会看到：
+
+```
+[wechat_kf] WeCom customer-service channel started
+[wechat_kf] Listening on http://0.0.0.0:9888/wxkf/
+```
+
+回到企微后台「设置API接收」点击保存——会触发 `GET /wxkf/?...&echostr=...`，CoW 通过 `crypto.check_signature` 校验后返回明文 `echostr`，验证成功。
+
+## 五、支持的回复类型
+
+| ReplyType | 是否支持 | 备注 |
+|---|---|---|
+| `TEXT` / `INFO` / `ERROR` | ✅ | 自动按 2048 字节切片分段发送 |
+| `IMAGE`（本地） / `IMAGE_URL`（网络） | ✅ | 大图自动压缩到 10MB 以内 |
+| `VOICE` | ✅ | 转 amr 后发送，>60s 自动切片 |
+| `VIDEO_URL` | ✅ | 通过临时素材接口上传 |
+| `FILE` | ✅ | |
+
+## 六、参考文档
+
+- [LinkAI 微信客服接入文档](https://docs.link-ai.tech/platform/link-app/wechat-customer-service)
+- [企业微信开放接口 - 微信客服 - 接收消息](https://developer.work.weixin.qq.com/document/path/94670)
+- [企业微信开放接口 - 微信客服 - 发送消息](https://developer.work.weixin.qq.com/document/path/95122)
diff --git a/channel/wechat_kf/wechat_kf_channel.py b/channel/wechat_kf/wechat_kf_channel.py
new file mode 100644
index 0000000..797d647
--- /dev/null
+++ b/channel/wechat_kf/wechat_kf_channel.py
@@ -0,0 +1,603 @@
+# -*- coding=utf-8 -*-
+"""
+WeChat Customer Service (微信客服) channel for CoW.
+
+Differences from `channel/wechatcom/` (企微自建应用):
+    1. Audience: external WeChat users (not internal members).
+    2. Receiver fields: `external_userid` + `open_kfid` instead of a single
+       member `userid`.
+    3. Inbound flow: callback only delivers an event token, the actual
+       message bodies must be pulled via `cgi-bin/kf/sync_msg` with a
+       persistent cursor. See `wechat_kf_cursor_store.py`.
+    4. Outbound flow: messages are sent via `cgi-bin/kf/send_msg` (each
+       request must specify both `touser` and `open_kfid`); wechatpy has
+       no native helper, so we call the HTTP endpoint directly.
+"""
+import io
+import json
+import os
+import threading
+import time
+import xml.etree.ElementTree as ET
+from collections import defaultdict
+from concurrent.futures import ThreadPoolExecutor
+from typing import Optional
+
+import requests
+import web
+from wechatpy.enterprise import WeChatClient
+from wechatpy.enterprise.crypto import WeChatCrypto
+from wechatpy.enterprise.exceptions import InvalidCorpIdException
+from wechatpy.exceptions import InvalidSignatureException, WeChatClientException
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel
+from channel.file_cache import get_file_cache
+from channel.wechat_kf.wechat_kf_cursor_store import CursorStore
+from channel.wechat_kf.wechat_kf_message import WechatKfMessage
+from common.log import logger
+from common.singleton import singleton
+from common.utils import (
+    compress_imgfile,
+    fsize,
+    remove_markdown_symbol,
+    split_string_by_utf8_length,
+)
+from config import conf
+
+try:
+    from voice.audio_convert import any_to_amr, split_audio
+except ImportError as e:  # voice features optional
+    logger.debug(
+        "[wechat_kf] import voice.audio_convert failed, voice will be disabled: {}".format(e)
+    )
+
+MAX_UTF8_LEN = 2048
+KF_API_BASE = "https://qyapi.weixin.qq.com/cgi-bin/kf"
+SYNC_MSG_LIMIT = 1000
+
+
+@singleton
+class WechatKfChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.corp_id = conf().get("wechat_kf_corp_id")
+        self.secret = conf().get("wechat_kf_secret")
+        self.token = conf().get("wechat_kf_token")
+        self.aes_key = conf().get("wechat_kf_aes_key")
+        self._http_server = None
+        logger.info(
+            "[wechat_kf] Initializing WeCom customer-service channel, corp_id: {}".format(
+                self.corp_id
+            )
+        )
+        self.crypto = WeChatCrypto(self.token, self.aes_key, self.corp_id)
+        # Use the stock wechatpy WeChatClient so that the access_token is
+        # cached and only refreshed when actually expired (~2h). The local
+        # `WechatComAppClient` subclass has a broken background refresh
+        # loop that re-fetches every 60s and a `fetch_access_token()`
+        # override that may return a dict instead of a string, which
+        # corrupts URLs and triggers errcode 40014.
+        self.client = WeChatClient(self.corp_id, self.secret)
+
+        # Persist sync_msg cursor under the user's home dir by default,
+        # so it survives `tmp/` cleanups and cwd changes across restarts.
+        cursor_path = os.path.expanduser(
+            conf().get("wechat_kf_cursor_path") or "~/.wechat_kf_cursors.json"
+        )
+        self.cursor_store = CursorStore(cursor_path)
+
+        # WeCom requires the callback HTTP response to return within ~5s,
+        # otherwise it retries the same notification. sync_msg pulling
+        # can easily exceed that, so we dispatch it to a background pool
+        # and let `Query.POST` reply success immediately.
+        self._callback_executor = ThreadPoolExecutor(
+            max_workers=4, thread_name_prefix="wxkf-cb"
+        )
+        # Per-open_kfid lock: serialize sync_msg for the same kf account
+        # so that callback retries (or rapid-fire events) don't race on
+        # the same cursor and produce duplicate replies.
+        self._kf_locks: dict = defaultdict(threading.Lock)
+        self._kf_locks_guard = threading.Lock()
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+    def startup(self):
+        urls = ("/wxkf/?", "channel.wechat_kf.wechat_kf_channel.Query")
+        app = web.application(urls, globals(), autoreload=False)
+        port = conf().get("wechat_kf_port", 9888)
+        logger.info("[wechat_kf] WeCom customer-service channel started")
+        logger.info("[wechat_kf] Listening on http://0.0.0.0:{}/wxkf/".format(port))
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer(("0.0.0.0", port), func)
+        self._http_server = server
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+
+    def stop(self):
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[wechat_kf] HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[wechat_kf] Error stopping HTTP server: {e}")
+            self._http_server = None
+        try:
+            self._callback_executor.shutdown(wait=False)
+        except Exception as e:
+            logger.warning(f"[wechat_kf] Error shutting down callback executor: {e}")
+
+    # ------------------------------------------------------------------
+    # Outbound — implementing the abstract `send` contract
+    # ------------------------------------------------------------------
+    def send(self, reply: Reply, context: Context):
+        receiver = context["receiver"]
+        msg = context.kwargs.get("msg")
+        external_userid = context.get("external_userid") or (msg.external_userid if msg else None)
+        open_kfid = context.get("open_kfid") or (msg.open_kfid if msg else None)
+
+        if not external_userid or not open_kfid:
+            logger.error(
+                "[wechat_kf] missing external_userid or open_kfid, cannot send: "
+                f"external_userid={external_userid}, open_kfid={open_kfid}"
+            )
+            return
+
+        if reply.type in [ReplyType.TEXT, ReplyType.ERROR, ReplyType.INFO]:
+            reply_text = remove_markdown_symbol(reply.content)
+            texts = split_string_by_utf8_length(reply_text, MAX_UTF8_LEN)
+            if len(texts) > 1:
+                logger.info(
+                    "[wechat_kf] text too long, split into {} parts".format(len(texts))
+                )
+            for i, text in enumerate(texts):
+                self._send_text(external_userid, open_kfid, text)
+                if i != len(texts) - 1:
+                    time.sleep(0.5)
+            logger.info("[wechat_kf] Do send text to {}: {}".format(receiver, reply_text))
+
+        elif reply.type == ReplyType.VOICE:
+            file_path = reply.content
+            try:
+                amr_file = os.path.splitext(file_path)[0] + ".amr"
+                any_to_amr(file_path, amr_file)
+                duration, files = split_audio(amr_file, 60 * 1000)
+                if len(files) > 1:
+                    logger.info(
+                        "[wechat_kf] voice too long {}s > 60s, split into {} parts".format(
+                            duration / 1000.0, len(files)
+                        )
+                    )
+                media_ids = []
+                for path in files:
+                    with open(path, "rb") as f:
+                        response = self.client.media.upload("voice", f)
+                    logger.debug("[wechat_kf] upload voice response: {}".format(response))
+                    media_ids.append(response["media_id"])
+            except ImportError as e:
+                logger.error("[wechat_kf] voice conversion failed: {}".format(e))
+                logger.error("[wechat_kf] please install pydub: pip install pydub")
+                return
+            except WeChatClientException as e:
+                logger.error("[wechat_kf] upload voice failed: {}".format(e))
+                return
+
+            try:
+                os.remove(file_path)
+                if amr_file != file_path:
+                    os.remove(amr_file)
+            except Exception:
+                pass
+
+            for media_id in media_ids:
+                self._send_voice(external_userid, open_kfid, media_id)
+                time.sleep(1)
+            logger.info("[wechat_kf] sendVoice={}, receiver={}".format(reply.content, receiver))
+
+        elif reply.type == ReplyType.IMAGE_URL:
+            img_url = reply.content
+            pic_res = requests.get(img_url, stream=True)
+            image_storage = io.BytesIO()
+            for block in pic_res.iter_content(1024):
+                image_storage.write(block)
+            sz = fsize(image_storage)
+            if sz >= 10 * 1024 * 1024:
+                logger.info("[wechat_kf] image too large, compressing, sz={}".format(sz))
+                image_storage = compress_imgfile(image_storage, 10 * 1024 * 1024 - 1)
+            image_storage.seek(0)
+            try:
+                response = self.client.media.upload("image", image_storage)
+            except WeChatClientException as e:
+                logger.error("[wechat_kf] upload image failed: {}".format(e))
+                return
+            self._send_image(external_userid, open_kfid, response["media_id"])
+            logger.info("[wechat_kf] sendImage url={}, receiver={}".format(img_url, receiver))
+
+        elif reply.type == ReplyType.IMAGE:
+            image_storage = reply.content
+            sz = fsize(image_storage)
+            if sz >= 10 * 1024 * 1024:
+                logger.info("[wechat_kf] image too large, compressing, sz={}".format(sz))
+                image_storage = compress_imgfile(image_storage, 10 * 1024 * 1024 - 1)
+            image_storage.seek(0)
+            try:
+                response = self.client.media.upload("image", image_storage)
+            except WeChatClientException as e:
+                logger.error("[wechat_kf] upload image failed: {}".format(e))
+                return
+            self._send_image(external_userid, open_kfid, response["media_id"])
+            logger.info("[wechat_kf] sendImage, receiver={}".format(receiver))
+
+        elif reply.type == ReplyType.VIDEO_URL:
+            video_url = reply.content
+            try:
+                response = self.client.media.upload(
+                    "video", requests.get(video_url, stream=True).content
+                )
+            except WeChatClientException as e:
+                logger.error("[wechat_kf] upload video failed: {}".format(e))
+                return
+            self._send_video(external_userid, open_kfid, response["media_id"])
+            logger.info("[wechat_kf] sendVideo url={}, receiver={}".format(video_url, receiver))
+
+        elif reply.type == ReplyType.FILE:
+            file_path = reply.content
+            try:
+                with open(file_path, "rb") as f:
+                    response = self.client.media.upload(
+                        "file", (os.path.basename(file_path), f.read())
+                    )
+            except WeChatClientException as e:
+                logger.error("[wechat_kf] upload file failed: {}".format(e))
+                return
+            self._send_file(external_userid, open_kfid, response["media_id"])
+            logger.info("[wechat_kf] sendFile={}, receiver={}".format(file_path, receiver))
+
+        else:
+            logger.warning("[wechat_kf] unsupported reply type: {}".format(reply.type))
+
+    # ------------------------------------------------------------------
+    # Inbound — pull messages by cursor
+    # ------------------------------------------------------------------
+    def _get_kf_lock(self, open_kfid: str) -> threading.Lock:
+        with self._kf_locks_guard:
+            return self._kf_locks[open_kfid]
+
+    def submit_callback(self, token: str, open_kfid: str):
+        """
+        Async entry point used by the HTTP handler. Submits the actual
+        sync_msg pulling to a background thread so the callback response
+        can return within WeCom's 5s deadline.
+        """
+        try:
+            self._callback_executor.submit(self._run_callback, token, open_kfid)
+        except RuntimeError as e:
+            # Executor may be shut down during process exit; fall back
+            # to inline execution so we don't silently drop the event.
+            logger.warning(f"[wechat_kf] executor unavailable, run inline: {e}")
+            self._run_callback(token, open_kfid)
+
+    def _run_callback(self, token: str, open_kfid: str):
+        # Block on the per-kfid lock so retried callbacks queue up
+        # behind the in-flight one. The queued worker will then call
+        # sync_msg with the (already advanced) cursor, which is cheap
+        # when there is nothing new and still picks up any messages
+        # that arrived after the previous worker's last pull.
+        lock = self._get_kf_lock(open_kfid)
+        with lock:
+            try:
+                self.consume_callback(token, open_kfid)
+            except Exception as e:
+                logger.exception(f"[wechat_kf] consume_callback error: {e}")
+
+    def consume_callback(self, token: str, open_kfid: str):
+        """
+        Called from the HTTP `Query.POST` handler whenever WeCom notifies
+        us that there are new messages for `open_kfid`. Pulls all new
+        messages via sync_msg and feeds them into `produce()`.
+        """
+        existing_cursor = self.cursor_store.get(open_kfid)
+
+        # First-time bootstrap: always skip history, otherwise WeCom would
+        # replay up to 14 days of messages on the very first callback and
+        # flood every user with auto-replies.
+        if not existing_cursor:
+            self._initialize_cursor(token, open_kfid)
+            return
+
+        msgs = self._pull_messages(token, open_kfid, existing_cursor)
+        if not msgs:
+            return
+        file_cache = get_file_cache()
+        for raw in msgs:
+            try:
+                kf_msg = WechatKfMessage(msg=raw, client=self.client)
+            except NotImplementedError as e:
+                logger.debug("[wechat_kf] {}".format(e))
+                continue
+
+            session_id = kf_msg.from_user_id
+
+            # Cache lone images/files and wait for the user's follow-up
+            # text. Agent mode never reads memory.USER_IMAGE_CACHE, so
+            # without this the attachment is effectively lost.
+            if kf_msg.ctype in (ContextType.IMAGE, ContextType.FILE):
+                ftype = "image" if kf_msg.ctype == ContextType.IMAGE else "file"
+                try:
+                    kf_msg.prepare()  # download to local tmp path
+                    file_cache.add(session_id, kf_msg.content, file_type=ftype)
+                    logger.info(
+                        "[wechat_kf] {} cached for session {}: {}".format(
+                            ftype, session_id, kf_msg.content
+                        )
+                    )
+                except Exception as e:
+                    logger.warning(f"[wechat_kf] cache {ftype} failed: {e}")
+                continue
+
+            # On a text turn, attach any pending images/files as references
+            # so the downstream agent can pick them up via the text content.
+            # Paths are already under agent_workspace/tmp (see
+            # WechatKfMessage._get_tmp_dir), so a relative ref also works.
+            if kf_msg.ctype == ContextType.TEXT:
+                cached_files = file_cache.get(session_id)
+                if cached_files:
+                    refs = []
+                    for fi in cached_files:
+                        ftype, fpath = fi["type"], fi["path"]
+                        if ftype == "image":
+                            refs.append(f"[图片: {fpath}]")
+                        else:
+                            refs.append(f"[文件: {fpath}]")
+                    kf_msg.content = kf_msg.content + "\n" + "\n".join(refs)
+                    file_cache.clear(session_id)
+
+            context = self._compose_context(
+                kf_msg.ctype,
+                kf_msg.content,
+                isgroup=False,
+                msg=kf_msg,
+            )
+            if context:
+                self.produce(context)
+            time.sleep(0.05)  # tiny gap between messages of the same batch
+
+    def _initialize_cursor(self, token: str, open_kfid: str):
+        """
+        Drain all current messages for this `open_kfid` without producing
+        any context, just to advance the cursor to "now". This prevents
+        a fresh deployment from replying to up to ~14 days of history.
+        """
+        next_cursor = ""
+        total_skipped = 0
+        while True:
+            data = self._call_sync_msg(token, open_kfid, next_cursor)
+            if data is None:
+                break
+            msg_list = data.get("msg_list") or []
+            total_skipped += len(msg_list)
+            cursor_after = data.get("next_cursor") or ""
+            if cursor_after:
+                self.cursor_store.set(open_kfid, cursor_after)
+            if not data.get("has_more"):
+                break
+            if not cursor_after or cursor_after == next_cursor:
+                break
+            next_cursor = cursor_after
+        logger.info(
+            "[wechat_kf] first-start bootstrap finished for open_kfid={}, "
+            "skipped {} historical messages".format(open_kfid, total_skipped)
+        )
+
+    def _pull_messages(self, token: str, open_kfid: str, next_cursor: Optional[str]) -> list:
+        """Loop sync_msg until `has_more` is false. Returns raw msg dicts."""
+        collected = []
+        cursor = next_cursor or ""
+        while True:
+            data = self._call_sync_msg(token, open_kfid, cursor)
+            if data is None:
+                break
+            for item in data.get("msg_list") or []:
+                # Only consume messages from external users; ignore replies
+                # generated by our own kf account, otherwise we would loop
+                # back into ourselves.
+                if not item.get("external_userid"):
+                    continue
+                if item.get("msgtype") in ("text", "image", "voice", "file"):
+                    collected.append(item)
+            cursor_after = data.get("next_cursor") or ""
+            if cursor_after:
+                self.cursor_store.set(open_kfid, cursor_after)
+            if not data.get("has_more"):
+                break
+            if not cursor_after or cursor_after == cursor:
+                break
+            cursor = cursor_after
+
+        if collected:
+            collected = _dedup_image_text_pair(collected)
+        logger.info(
+            "[wechat_kf] pulled {} messages for open_kfid={}".format(len(collected), open_kfid)
+        )
+        return collected
+
+    def _call_sync_msg(self, token: str, open_kfid: str, cursor: str) -> Optional[dict]:
+        # `client.access_token` is the cached string property; do not use
+        # `fetch_access_token()` here — wechatpy returns the raw response
+        # dict from that call, which corrupts the query string.
+        url = f"{KF_API_BASE}/sync_msg?access_token={self.client.access_token}"
+        payload = {
+            "token": token,
+            "open_kfid": open_kfid,
+            "limit": SYNC_MSG_LIMIT,
+        }
+        if cursor:
+            payload["cursor"] = cursor
+        try:
+            resp = requests.post(url, json=payload, timeout=10).json()
+        except Exception as e:
+            logger.error(f"[wechat_kf] sync_msg request failed: {e}")
+            return None
+
+        if resp.get("errcode") != 0:
+            logger.error(
+                f"[wechat_kf] sync_msg errcode={resp.get('errcode')}, "
+                f"errmsg={resp.get('errmsg')}, open_kfid={open_kfid}"
+            )
+            return None
+        return resp
+
+    # ------------------------------------------------------------------
+    # Outbound HTTP wrappers (kf/send_msg)
+    # ------------------------------------------------------------------
+    def _post_send_msg(self, payload: dict) -> dict:
+        url = f"{KF_API_BASE}/send_msg?access_token={self.client.access_token}"
+        try:
+            resp = requests.post(url, json=payload, timeout=10).json()
+        except Exception as e:
+            logger.error(f"[wechat_kf] send_msg request failed: {e}")
+            return {"errcode": -1, "errmsg": str(e)}
+        if resp.get("errcode") != 0:
+            logger.error(f"[wechat_kf] send_msg failed, payload={payload}, resp={resp}")
+        return resp
+
+    def _send_text(self, external_userid: str, open_kfid: str, content: str) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "text",
+            "text": {"content": content},
+        })
+
+    def _send_image(self, external_userid: str, open_kfid: str, media_id: str) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "image",
+            "image": {"media_id": media_id},
+        })
+
+    def _send_voice(self, external_userid: str, open_kfid: str, media_id: str) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "voice",
+            "voice": {"media_id": media_id},
+        })
+
+    def _send_video(self, external_userid: str, open_kfid: str, media_id: str) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "video",
+            "video": {"media_id": media_id},
+        })
+
+    def _send_file(self, external_userid: str, open_kfid: str, media_id: str) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "file",
+            "file": {"media_id": media_id},
+        })
+
+    def _send_link(self, external_userid: str, open_kfid: str, link_data: dict) -> dict:
+        return self._post_send_msg({
+            "touser": external_userid,
+            "open_kfid": open_kfid,
+            "msgtype": "link",
+            "link": link_data,
+        })
+
+
+def _dedup_image_text_pair(messages: list) -> list:
+    """
+    A WeChat user often sends an image immediately followed by a text
+    question (e.g. "what's in this picture?"). Only when the batch is
+    exactly that 2-message image+text pair within a 5s window do we
+    collapse it into a single [image, text] turn. Otherwise return
+    every message so rapid-fire texts/images are all processed —
+    cursor freshness is already guaranteed by sync_msg.
+    """
+    if not messages:
+        return []
+
+    if len(messages) == 2:
+        a, b = messages
+        types = {a["msgtype"], b["msgtype"]}
+        if types == {"image", "text"} and abs(a["send_time"] - b["send_time"]) <= 5:
+            img = a if a["msgtype"] == "image" else b
+            txt = b if a["msgtype"] == "image" else a
+            return [img, txt]
+
+    return messages
+
+
+# ----------------------------------------------------------------------
+# HTTP handlers (web.py)
+# ----------------------------------------------------------------------
+class Query:
+    def GET(self):
+        channel = WechatKfChannel()
+        params = web.input()
+        logger.info("[wechat_kf] verify params: {}".format(params))
+        try:
+            signature = params.msg_signature
+            timestamp = params.timestamp
+            nonce = params.nonce
+            echostr = params.echostr
+            echostr = channel.crypto.check_signature(signature, timestamp, nonce, echostr)
+        except (InvalidSignatureException, InvalidCorpIdException):
+            raise web.Forbidden()
+        return echostr
+
+    def POST(self):
+        channel = WechatKfChannel()
+        params = web.input()
+        try:
+            signature = params.msg_signature
+            timestamp = params.timestamp
+            nonce = params.nonce
+            raw_body = web.data()
+            decrypted = channel.crypto.decrypt_message(raw_body, signature, timestamp, nonce)
+        except (InvalidSignatureException, InvalidCorpIdException) as e:
+            logger.warning(f"[wechat_kf] invalid signature: {e}")
+            raise web.Forbidden()
+
+        # We need the Token + OpenKfId fields from the inner XML to call
+        # sync_msg. wechatpy's parsed object exposes neither, so we parse
+        # the raw XML directly.
+        try:
+            root = ET.fromstring(decrypted)
+        except ET.ParseError as e:
+            logger.error(f"[wechat_kf] xml parse error: {e}")
+            return "success"
+
+        msg_type = (root.findtext("MsgType") or "").strip()
+        event = (root.findtext("Event") or "").strip()
+        if msg_type != "event" or event != "kf_msg_or_event":
+            logger.debug(
+                f"[wechat_kf] ignored callback msg_type={msg_type}, event={event}"
+            )
+            return "success"
+
+        token = root.findtext("Token") or ""
+        open_kfid = root.findtext("OpenKfId") or ""
+        if not token or not open_kfid:
+            logger.warning(
+                f"[wechat_kf] callback missing token or open_kfid: {decrypted}"
+            )
+            return "success"
+
+        # Hand off to a background worker — WeCom requires the callback
+        # to return success within ~5 seconds, otherwise it will retry
+        # and we may race the same cursor window into duplicate replies.
+        channel.submit_callback(token, open_kfid)
+        return "success"
diff --git a/channel/wechat_kf/wechat_kf_cursor_store.py b/channel/wechat_kf/wechat_kf_cursor_store.py
new file mode 100644
index 0000000..cc80945
--- /dev/null
+++ b/channel/wechat_kf/wechat_kf_cursor_store.py
@@ -0,0 +1,80 @@
+# -*- coding=utf-8 -*-
+"""
+Local-file based persistence for WeCom customer-service `next_cursor`.
+
+Why we need this:
+    The WeCom customer-service (微信客服) callback only notifies us that
+    "new messages exist". To actually fetch them we must call the
+    `cgi-bin/kf/sync_msg` endpoint with a `cursor` so that we only get
+    messages newer than the previously processed one. If we lose this
+    cursor (e.g. on process restart) WeCom will replay up to ~14 days of
+    history, which would cause the bot to flood users with duplicate
+    replies.
+
+This implementation deliberately avoids any external dependency
+(no Redis / no DB) — a single JSON file under the project's tmp dir is
+enough for a CoW-style single-process deployment.
+"""
+import json
+import os
+import threading
+from typing import Optional
+
+from common.log import logger
+
+
+class CursorStore:
+    """Thread-safe per-`open_kfid` cursor store backed by a JSON file."""
+
+    def __init__(self, file_path: str):
+        self._file_path = file_path
+        self._lock = threading.Lock()
+        self._data = self._load()
+
+    def _load(self) -> dict:
+        try:
+            if os.path.exists(self._file_path):
+                with open(self._file_path, "r", encoding="utf-8") as f:
+                    return json.load(f) or {}
+        except Exception as e:
+            logger.warning(f"[wechat_kf] failed to load cursor file {self._file_path}: {e}")
+        return {}
+
+    def _flush_locked(self):
+        # Atomic write: write to *.tmp first then rename, avoid corruption on crash.
+        tmp_path = self._file_path + ".tmp"
+        try:
+            os.makedirs(os.path.dirname(self._file_path) or ".", exist_ok=True)
+            with open(tmp_path, "w", encoding="utf-8") as f:
+                json.dump(self._data, f, ensure_ascii=False)
+            os.replace(tmp_path, self._file_path)
+            # Tighten permissions: cursor file lives in $HOME, restrict to owner.
+            # No-op on Windows.
+            try:
+                os.chmod(self._file_path, 0o600)
+            except Exception:
+                pass
+        except Exception as e:
+            logger.warning(f"[wechat_kf] failed to flush cursor file {self._file_path}: {e}")
+            try:
+                if os.path.exists(tmp_path):
+                    os.remove(tmp_path)
+            except Exception:
+                pass
+
+    def get(self, open_kfid: str) -> Optional[str]:
+        with self._lock:
+            return self._data.get(open_kfid)
+
+    def set(self, open_kfid: str, cursor: str):
+        if not cursor:
+            return
+        with self._lock:
+            if self._data.get(open_kfid) == cursor:
+                return
+            self._data[open_kfid] = cursor
+            self._flush_locked()
+
+    def has(self, open_kfid: str) -> bool:
+        with self._lock:
+            return open_kfid in self._data
diff --git a/channel/wechat_kf/wechat_kf_message.py b/channel/wechat_kf/wechat_kf_message.py
new file mode 100644
index 0000000..4285f8b
--- /dev/null
+++ b/channel/wechat_kf/wechat_kf_message.py
@@ -0,0 +1,134 @@
+# -*- coding=utf-8 -*-
+"""
+Adapter that turns a single `sync_msg` item from WeCom customer-service
+into a CoW `ChatMessage` object.
+"""
+import os
+import re
+
+from wechatpy.enterprise import WeChatClient
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from common.utils import expand_path
+from config import conf
+
+
+def _get_tmp_dir() -> str:
+    """Save under agent_workspace/tmp/ so agent tools (e.g. `read`) can
+    resolve a relative path like `tmp/xxx.pdf` against their own
+    workspace root. Mirrors the convention used by weixin / wecom_bot.
+    """
+    ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    tmp_dir = os.path.join(ws_root, "tmp")
+    os.makedirs(tmp_dir, exist_ok=True)
+    return tmp_dir
+
+
+def _extract_filename(content_disposition: str) -> str:
+    """Best-effort parse of `filename` / `filename*` from a Content-Disposition
+    header. Returns '' when nothing usable is found."""
+    if not content_disposition:
+        return ""
+    # RFC 5987 form: filename*=UTF-8''xxx
+    m = re.search(r"filename\*=(?:[^'\"]*'[^']*'\s*)?([^;]+)", content_disposition)
+    if m:
+        try:
+            from urllib.parse import unquote
+            return unquote(m.group(1).strip().strip('"'))
+        except Exception:
+            return m.group(1).strip().strip('"')
+    m = re.search(r'filename\s*=\s*"?([^";]+)"?', content_disposition)
+    return m.group(1).strip() if m else ""
+
+
+class WechatKfMessage(ChatMessage):
+    """
+    msg structure (from cgi-bin/kf/sync_msg):
+        {
+          "msgid": "...",
+          "send_time": 1700000000,
+          "origin": 3,
+          "msgtype": "text" | "image" | "voice" | ...,
+          "open_kfid": "wkxxxx",
+          "external_userid": "wmxxxx",
+          "text": {"content": "..."},
+          "image": {"media_id": "..."},
+          "voice": {"media_id": "..."},
+          ...
+        }
+    """
+
+    def __init__(self, msg: dict, client: WeChatClient = None, is_group: bool = False):
+        # NOTE: skip parent constructor because it expects a wechatpy parsed
+        # message object, while here we receive a raw dict from sync_msg.
+        super().__init__(msg)
+        self.is_group = is_group
+        self.msg_id = msg.get("msgid")
+        self.create_time = msg.get("send_time")
+        self.origin = msg.get("origin")
+        self.msgtype = msg.get("msgtype")
+        self.open_kfid = msg.get("open_kfid")
+        self.external_userid = msg.get("external_userid")
+
+        if self.msgtype == "text":
+            self.ctype = ContextType.TEXT
+            self.content = msg.get("text", {}).get("content", "")
+        elif self.msgtype == "image":
+            self.ctype = ContextType.IMAGE
+            media_id = msg.get("image", {}).get("media_id", "")
+            self.content = os.path.join(_get_tmp_dir(), media_id + ".jpg")
+
+            def download_image():
+                response = client.media.download(media_id)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechat_kf] Failed to download image, {response.content}")
+
+            self._prepare_fn = download_image
+        elif self.msgtype == "voice":
+            self.ctype = ContextType.VOICE
+            media_id = msg.get("voice", {}).get("media_id", "")
+            # WeCom returns amr by default; downstream voice pipeline will convert.
+            self.content = os.path.join(_get_tmp_dir(), media_id + ".amr")
+
+            def download_voice():
+                response = client.media.download(media_id)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechat_kf] Failed to download voice, {response.content}")
+
+            self._prepare_fn = download_voice
+        elif self.msgtype == "file":
+            self.ctype = ContextType.FILE
+            media_id = msg.get("file", {}).get("media_id", "")
+            # Provisional path; rewritten in download_file() once we have
+            # the original filename from Content-Disposition.
+            self.content = os.path.join(_get_tmp_dir(), media_id)
+
+            def download_file():
+                response = client.media.download(media_id)
+                if response.status_code == 200:
+                    filename = _extract_filename(
+                        response.headers.get("Content-Disposition", "")
+                    ) or media_id
+                    self.content = os.path.join(_get_tmp_dir(), filename)
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechat_kf] Failed to download file, {response.content}")
+
+            self._prepare_fn = download_file
+        else:
+            raise NotImplementedError(
+                f"[wechat_kf] Unsupported message type: {self.msgtype}"
+            )
+
+        self.from_user_id = self.external_userid
+        self.to_user_id = self.open_kfid
+        self.other_user_id = self.external_userid
diff --git a/channel/wechatcom/README.md b/channel/wechatcom/README.md
new file mode 100644
index 0000000..a4cf04f
--- /dev/null
+++ b/channel/wechatcom/README.md
@@ -0,0 +1,85 @@
+# 企业微信应用号channel
+
+企业微信官方提供了客服、应用等API，本channel使用的是企业微信的自建应用API的能力。
+
+因为未来可能还会开发客服能力，所以本channel的类型名叫作`wechatcom_app`。
+
+`wechatcom_app` channel支持插件系统和图片声音交互等能力，除了无法加入群聊，作为个人使用的私人助理已绰绰有余。
+
+## 开始之前
+
+- 在企业中确认自己拥有在企业内自建应用的权限。
+- 如果没有权限或者是个人用户，也可创建未认证的企业。操作方式：登录手机企业微信，选择`创建/加入企业`来创建企业，类型请选择企业，企业名称可随意填写。
+    未认证的企业有100人的服务人数上限，其他功能与认证企业没有差异。
+
+本channel需安装的依赖与公众号一致，需要安装`wechatpy`和`web.py`，它们包含在`requirements-optional.txt`中。
+
+此外，如果你是`Linux`系统，除了`ffmpeg`还需要安装`amr`编码器，否则会出现找不到编码器的错误，无法正常使用语音功能。
+
+- Ubuntu/Debian
+
+```bash
+apt-get install libavcodec-extra
+```
+
+- Alpine
+
+需自行编译`ffmpeg`，在编译参数里加入`amr`编码器的支持
+
+## 使用方法
+
+1.查看企业ID
+
+- 扫码登陆[企业微信后台](https://work.weixin.qq.com)
+- 选择`我的企业`，点击`企业信息`，记住该`企业ID`
+
+2.创建自建应用
+
+- 选择应用管理, 在自建区选创建应用来创建企业自建应用
+- 上传应用logo，填写应用名称等项
+- 创建应用后进入应用详情页面，记住`AgentId`和`Secert`
+
+3.配置应用
+
+- 在详情页点击`企业可信IP`的配置(没看到可以不管)，填入你服务器的公网IP，如果不知道可以先不填
+- 点击`接收消息`下的启用API接收消息
+- `URL`填写格式为`http://url:port/wxcomapp`，`port`是程序监听的端口，默认是9898
+    如果是未认证的企业，url可直接使用服务器的IP。如果是认证企业，需要使用备案的域名，可使用二级域名。
+- `Token`可随意填写，停留在这个页面
+- 在程序根目录`config.json`中增加配置（**去掉注释**），`wechatcomapp_aes_key`是当前页面的`wechatcomapp_aes_key`
+
+```python
+    "channel_type": "wechatcom_app",
+    "wechatcom_corp_id": "",  # 企业微信公司的corpID
+    "wechatcomapp_token": "",  # 企业微信app的token
+    "wechatcomapp_port": 9898,  # 企业微信app的服务端口, 不需要端口转发
+    "wechatcomapp_secret": "",  # 企业微信app的secret
+    "wechatcomapp_agent_id": "",  # 企业微信app的agent_id
+    "wechatcomapp_aes_key": "",  # 企业微信app的aes_key
+```
+
+- 运行程序，在页面中点击保存，保存成功说明验证成功
+
+4.连接个人微信
+
+选择`我的企业`，点击`微信插件`，下面有个邀请关注的二维码。微信扫码后，即可在微信中看到对应企业，在这里你便可以和机器人沟通。
+
+向机器人发送消息，如果日志里出现报错:
+
+```bash
+Error code: 60020, message: "not allow to access from your ip, ...from ip: xx.xx.xx.xx"
+```
+
+意思是IP不可信，需要参考上一步的`企业可信IP`配置，把这里的IP加进去。
+
+~~### Railway部署方式~~（2023-06-08已失效）
+
+~~公众号不能在`Railway`上部署，但企业微信应用[可以](https://railway.app/template/-FHS--?referralCode=RC3znh)!~~
+
+~~填写配置后，将部署完成后的网址```**.railway.app/wxcomapp```，填写在上一步的URL中。发送信息后观察日志，把报错的IP加入到可信IP。（每次重启后都需要加入可信IP）~~
+
+~~## 测试体验~~
+
+~~AIGC开放社区中已经部署了多个可免费使用的Bot，扫描下方的二维码会自动邀请你来体验。~~
+
+~~<img width="200" src="../../docs/images/aigcopen.png">~~
diff --git a/channel/wechatcom/wechatcomapp_channel.py b/channel/wechatcom/wechatcomapp_channel.py
new file mode 100644
index 0000000..3321f54
--- /dev/null
+++ b/channel/wechatcom/wechatcomapp_channel.py
@@ -0,0 +1,211 @@
+# -*- coding=utf-8 -*-
+import io
+import os
+import sys
+import time
+
+import requests
+import web
+from wechatpy.enterprise import create_reply, parse_message
+from wechatpy.enterprise.crypto import WeChatCrypto
+from wechatpy.enterprise.exceptions import InvalidCorpIdException
+from wechatpy.exceptions import InvalidSignatureException, WeChatClientException
+
+from bridge.context import Context
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel
+from channel.wechatcom.wechatcomapp_client import WechatComAppClient
+from channel.wechatcom.wechatcomapp_message import WechatComAppMessage
+from common.log import logger
+from common.singleton import singleton
+from common.utils import compress_imgfile, fsize, split_string_by_utf8_length, convert_webp_to_png, remove_markdown_symbol
+from config import conf, subscribe_msg
+from voice.audio_convert import any_to_amr, split_audio
+
+MAX_UTF8_LEN = 2048
+
+
+@singleton
+class WechatComAppChannel(ChatChannel):
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.corp_id = conf().get("wechatcom_corp_id")
+        self.secret = conf().get("wechatcomapp_secret")
+        self.agent_id = conf().get("wechatcomapp_agent_id")
+        self.token = conf().get("wechatcomapp_token")
+        self.aes_key = conf().get("wechatcomapp_aes_key")
+        self._http_server = None
+        logger.info(
+            "[wechatcom] Initializing WeCom app channel, corp_id: {}, agent_id: {}".format(self.corp_id, self.agent_id)
+        )
+        self.crypto = WeChatCrypto(self.token, self.aes_key, self.corp_id)
+        self.client = WechatComAppClient(self.corp_id, self.secret)
+
+    def startup(self):
+        # start message listener
+        urls = ("/wxcomapp/?", "channel.wechatcom.wechatcomapp_channel.Query")
+        app = web.application(urls, globals(), autoreload=False)
+        port = conf().get("wechatcomapp_port", 9898)
+        logger.info("[wechatcom] ✅ WeCom app channel started successfully")
+        logger.info("[wechatcom] 📡 Listening on http://0.0.0.0:{}/wxcomapp/".format(port))
+        logger.info("[wechatcom] 🤖 Ready to receive messages")
+        
+        # Build WSGI app with middleware (same as runsimple but without print)
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer(("0.0.0.0", port), func)
+        self._http_server = server
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+
+    def stop(self):
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[wechatcom] HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[wechatcom] Error stopping HTTP server: {e}")
+            self._http_server = None
+
+    def send(self, reply: Reply, context: Context):
+        receiver = context["receiver"]
+        if reply.type in [ReplyType.TEXT, ReplyType.ERROR, ReplyType.INFO]:
+            reply_text = remove_markdown_symbol(reply.content)
+            texts = split_string_by_utf8_length(reply_text, MAX_UTF8_LEN)
+            if len(texts) > 1:
+                logger.info("[wechatcom] text too long, split into {} parts".format(len(texts)))
+            for i, text in enumerate(texts):
+                self.client.message.send_text(self.agent_id, receiver, text)
+                if i != len(texts) - 1:
+                    time.sleep(0.5)  # 休眠0.5秒，防止发送过快乱序
+            logger.info("[wechatcom] Do send text to {}: {}".format(receiver, reply_text))
+        elif reply.type == ReplyType.VOICE:
+            try:
+                media_ids = []
+                file_path = reply.content
+                amr_file = os.path.splitext(file_path)[0] + ".amr"
+                any_to_amr(file_path, amr_file)
+                duration, files = split_audio(amr_file, 60 * 1000)
+                if len(files) > 1:
+                    logger.info("[wechatcom] voice too long {}s > 60s , split into {} parts".format(duration / 1000.0, len(files)))
+                for path in files:
+                    response = self.client.media.upload("voice", open(path, "rb"))
+                    logger.debug("[wechatcom] upload voice response: {}".format(response))
+                    media_ids.append(response["media_id"])
+            except ImportError as e:
+                logger.error("[wechatcom] voice conversion failed: {}".format(e))
+                logger.error("[wechatcom] please install pydub: pip install pydub")
+                return
+            except WeChatClientException as e:
+                logger.error("[wechatcom] upload voice failed: {}".format(e))
+                return
+            try:
+                os.remove(file_path)
+                if amr_file != file_path:
+                    os.remove(amr_file)
+            except Exception:
+                pass
+            for media_id in media_ids:
+                self.client.message.send_voice(self.agent_id, receiver, media_id)
+                time.sleep(1)
+            logger.info("[wechatcom] sendVoice={}, receiver={}".format(reply.content, receiver))
+        elif reply.type == ReplyType.IMAGE_URL:  # 从网络下载图片
+            img_url = reply.content
+            pic_res = requests.get(img_url, stream=True)
+            image_storage = io.BytesIO()
+            for block in pic_res.iter_content(1024):
+                image_storage.write(block)
+            sz = fsize(image_storage)
+            if sz >= 10 * 1024 * 1024:
+                logger.info("[wechatcom] image too large, ready to compress, sz={}".format(sz))
+                image_storage = compress_imgfile(image_storage, 10 * 1024 * 1024 - 1)
+                logger.info("[wechatcom] image compressed, sz={}".format(fsize(image_storage)))
+            image_storage.seek(0)
+            if ".webp" in img_url:
+                try:
+                    image_storage = convert_webp_to_png(image_storage)
+                except Exception as e:
+                    logger.error(f"Failed to convert image: {e}")
+                    return
+            try:
+                response = self.client.media.upload("image", image_storage)
+                logger.debug("[wechatcom] upload image response: {}".format(response))
+            except WeChatClientException as e:
+                logger.error("[wechatcom] upload image failed: {}".format(e))
+                return
+
+            self.client.message.send_image(self.agent_id, receiver, response["media_id"])
+            logger.info("[wechatcom] sendImage url={}, receiver={}".format(img_url, receiver))
+        elif reply.type == ReplyType.IMAGE:  # 从文件读取图片
+            image_storage = reply.content
+            sz = fsize(image_storage)
+            if sz >= 10 * 1024 * 1024:
+                logger.info("[wechatcom] image too large, ready to compress, sz={}".format(sz))
+                image_storage = compress_imgfile(image_storage, 10 * 1024 * 1024 - 1)
+                logger.info("[wechatcom] image compressed, sz={}".format(fsize(image_storage)))
+            image_storage.seek(0)
+            try:
+                response = self.client.media.upload("image", image_storage)
+                logger.debug("[wechatcom] upload image response: {}".format(response))
+            except WeChatClientException as e:
+                logger.error("[wechatcom] upload image failed: {}".format(e))
+                return
+            self.client.message.send_image(self.agent_id, receiver, response["media_id"])
+            logger.info("[wechatcom] sendImage, receiver={}".format(receiver))
+
+
+class Query:
+    def GET(self):
+        channel = WechatComAppChannel()
+        params = web.input()
+        logger.info("[wechatcom] receive params: {}".format(params))
+        try:
+            signature = params.msg_signature
+            timestamp = params.timestamp
+            nonce = params.nonce
+            echostr = params.echostr
+            echostr = channel.crypto.check_signature(signature, timestamp, nonce, echostr)
+        except InvalidSignatureException:
+            raise web.Forbidden()
+        return echostr
+
+    def POST(self):
+        channel = WechatComAppChannel()
+        params = web.input()
+        logger.info("[wechatcom] receive params: {}".format(params))
+        try:
+            signature = params.msg_signature
+            timestamp = params.timestamp
+            nonce = params.nonce
+            message = channel.crypto.decrypt_message(web.data(), signature, timestamp, nonce)
+        except (InvalidSignatureException, InvalidCorpIdException):
+            raise web.Forbidden()
+        msg = parse_message(message)
+        logger.debug("[wechatcom] receive message: {}, msg= {}".format(message, msg))
+        if msg.type == "event":
+            if msg.event == "subscribe":
+                pass
+                # reply_content = subscribe_msg()
+                # if reply_content:
+                #     reply = create_reply(reply_content, msg).render()
+                #     res = channel.crypto.encrypt_message(reply, nonce, timestamp)
+                #     return res
+        else:
+            try:
+                wechatcom_msg = WechatComAppMessage(msg, client=channel.client)
+            except NotImplementedError as e:
+                logger.debug("[wechatcom] " + str(e))
+                return "success"
+            context = channel._compose_context(
+                wechatcom_msg.ctype,
+                wechatcom_msg.content,
+                isgroup=False,
+                msg=wechatcom_msg,
+            )
+            if context:
+                channel.produce(context)
+        return "success"
diff --git a/channel/wechatcom/wechatcomapp_client.py b/channel/wechatcom/wechatcomapp_client.py
new file mode 100644
index 0000000..64d8e8a
--- /dev/null
+++ b/channel/wechatcom/wechatcomapp_client.py
@@ -0,0 +1,43 @@
+# wechatcomapp_client.py
+import threading
+import time
+from wechatpy.enterprise import WeChatClient
+
+class WechatComAppClient(WeChatClient):
+    def __init__(self, corp_id, secret, access_token=None, session=None, timeout=None, auto_retry=True):
+        super(WechatComAppClient, self).__init__(corp_id, secret, access_token, session, timeout, auto_retry)
+        self.fetch_access_token_lock = threading.Lock()
+        self._active_refresh()
+        
+    def _active_refresh(self):
+        """启动主动刷新的后台线程"""
+        def refresh_loop():
+            while True:
+                now = time.time()
+                expires_at = self.session.get(f"{self.corp_id}_expires_at", 0)
+                
+                # 提前10分钟刷新(600秒)
+                if expires_at - now < 600:
+                    with self.fetch_access_token_lock:
+                        # 双重检查避免重复刷新
+                        if self.session.get(f"{self.corp_id}_expires_at", 0) - time.time() < 600:
+                            super(WechatComAppClient, self).fetch_access_token()
+                # 每次检查间隔60秒
+                time.sleep(60)
+                
+        # 启动守护线程
+        refresh_thread = threading.Thread(
+            target=refresh_loop,
+            daemon=True,
+            name="wechatcom_token_refresh_thread"
+        )
+        refresh_thread.start()
+
+    def fetch_access_token(self):
+        with self.fetch_access_token_lock:
+            access_token = self.session.get(self.access_token_key)
+            expires_at = self.session.get(f"{self.corp_id}_expires_at", 0)
+            
+            if access_token and expires_at > time.time() + 60:
+                return access_token
+            return super().fetch_access_token()
\ No newline at end of file
diff --git a/channel/wechatcom/wechatcomapp_message.py b/channel/wechatcom/wechatcomapp_message.py
new file mode 100644
index 0000000..a70f755
--- /dev/null
+++ b/channel/wechatcom/wechatcomapp_message.py
@@ -0,0 +1,52 @@
+from wechatpy.enterprise import WeChatClient
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from common.tmp_dir import TmpDir
+
+
+class WechatComAppMessage(ChatMessage):
+    def __init__(self, msg, client: WeChatClient, is_group=False):
+        super().__init__(msg)
+        self.msg_id = msg.id
+        self.create_time = msg.time
+        self.is_group = is_group
+
+        if msg.type == "text":
+            self.ctype = ContextType.TEXT
+            self.content = msg.content
+        elif msg.type == "voice":
+            self.ctype = ContextType.VOICE
+            self.content = TmpDir().path() + msg.media_id + "." + msg.format  # content直接存临时目录路径
+
+            def download_voice():
+                # 如果响应状态码是200，则将响应内容写入本地文件
+                response = client.media.download(msg.media_id)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechatcom] Failed to download voice file, {response.content}")
+
+            self._prepare_fn = download_voice
+        elif msg.type == "image":
+            self.ctype = ContextType.IMAGE
+            self.content = TmpDir().path() + msg.media_id + ".png"  # content直接存临时目录路径
+
+            def download_image():
+                # 如果响应状态码是200，则将响应内容写入本地文件
+                response = client.media.download(msg.media_id)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechatcom] Failed to download image file, {response.content}")
+
+            self._prepare_fn = download_image
+        else:
+            raise NotImplementedError("Unsupported message type: Type:{} ".format(msg.type))
+
+        self.from_user_id = msg.source
+        self.to_user_id = msg.target
+        self.other_user_id = msg.source
diff --git a/channel/wechatmp/README.md b/channel/wechatmp/README.md
new file mode 100644
index 0000000..bdae91b
--- /dev/null
+++ b/channel/wechatmp/README.md
@@ -0,0 +1,100 @@
+# 微信公众号channel
+
+微信公众号channel，提供稳定的服务。
+目前支持订阅号和服务号两种类型的公众号，它们都支持文本交互，语音和图片输入。其中个人主体的微信订阅号由于无法通过微信认证，存在回复时间限制，每天的图片和声音回复次数也有限制。
+
+## 使用方法（订阅号，服务号类似）
+
+在开始部署前，你需要一个拥有公网IP的服务器，以提供微信服务器和我们自己服务器的连接。或者你需要进行内网穿透，否则微信服务器无法将消息发送给我们的服务器。
+
+此外，需要在我们的服务器上安装python的web框架web.py和wechatpy。
+以ubuntu为例(在ubuntu 22.04上测试):
+```
+pip3 install web.py
+pip3 install wechatpy
+```
+
+然后在[微信公众平台](https://mp.weixin.qq.com)注册一个自己的公众号，类型选择订阅号，主体为个人即可。
+
+然后根据[接入指南](https://developers.weixin.qq.com/doc/offiaccount/Basic_Information/Access_Overview.html)的说明，在[微信公众平台](https://mp.weixin.qq.com)的“设置与开发”-“基本配置”-“服务器配置”中填写服务器地址`URL`和令牌`Token`。`URL`填写格式为`http://url/wx`，可使用IP（成功几率看脸），`Token`是你自己编的一个特定的令牌。消息加解密方式如果选择了需要加密的模式，需要在配置中填写`wechatmp_aes_key`。
+
+相关的服务器验证代码已经写好，你不需要再添加任何代码。你只需要在本项目根目录的`config.json`中添加
+```
+"channel_type": "wechatmp",     # 如果通过了微信认证，将"wechatmp"替换为"wechatmp_service"，可极大的优化使用体验
+"wechatmp_token": "xxxx",       # 微信公众平台的Token
+"wechatmp_port": 8080,          # 微信公众平台的端口,需要端口转发到80或443
+"wechatmp_app_id": "xxxx",      # 微信公众平台的appID
+"wechatmp_app_secret": "xxxx",  # 微信公众平台的appsecret
+"wechatmp_aes_key": "",         # 微信公众平台的EncodingAESKey，加密模式需要
+"single_chat_prefix": [""],     # 推荐设置，任意对话都可以触发回复，不添加前缀
+"single_chat_reply_prefix": "", # 推荐设置，回复不设置前缀
+"plugin_trigger_prefix": "&",   # 推荐设置，在手机微信客户端中，$%^等符号与中文连在一起时会自动显示一段较大的间隔，用户体验不好。请不要使用管理员指令前缀"#"，这会造成未知问题。
+```
+然后运行`python3 app.py`启动web服务器。这里会默认监听8080端口，但是微信公众号的服务器配置只支持80/443端口，有两种方法来解决这个问题。第一个是推荐的方法，使用端口转发命令将80端口转发到8080端口：
+```
+sudo iptables -t nat -A PREROUTING -p tcp --dport 80 -j REDIRECT --to-port 8080
+sudo iptables-save > /etc/iptables/rules.v4
+```
+第二个方法是让python程序直接监听80端口，在配置文件中设置`"wechatmp_port": 80` ，在linux上需要使用`sudo python3 app.py`启动程序。然而这会导致一系列环境和权限问题，因此不是推荐的方法。
+
+443端口同理，注意需要支持SSL，也就是https的访问，在`wechatmp_channel.py`中需要修改相应的证书路径。
+
+程序启动并监听端口后，在刚才的“服务器配置”中点击`提交`即可验证你的服务器。
+随后在[微信公众平台](https://mp.weixin.qq.com)启用服务器，关闭手动填写规则的自动回复，即可实现ChatGPT的自动回复。
+
+之后需要在公众号开发信息下将本机IP加入到IP白名单。
+
+不然在启用后，发送语音、图片等消息可能会遇到如下报错：
+```
+'errcode': 40164, 'errmsg': 'invalid ip xx.xx.xx.xx not in whitelist rid
+```
+
+
+## 个人微信公众号的限制
+由于人微信公众号不能通过微信认证，所以没有客服接口，因此公众号无法主动发出消息，只能被动回复。而微信官方对被动回复有5秒的时间限制，最多重试2次，因此最多只有15秒的自动回复时间窗口。因此如果问题比较复杂或者我们的服务器比较忙，ChatGPT的回答就没办法及时回复给用户。为了解决这个问题，这里做了回答缓存，它需要你在回复超时后，再次主动发送任意文字（例如1）来尝试拿到回答缓存。为了优化使用体验，目前设置了两分钟（120秒）的timeout，用户在至多两分钟后即可得到查询到回复或者错误原因。
+
+另外，由于微信官方的限制，自动回复有长度限制。因此这里将ChatGPT的回答进行了拆分，以满足限制。
+
+## 私有api_key
+公共api有访问频率限制（免费账号每分钟最多3次ChatGPT的API调用），这在服务多人的时候会遇到问题。因此这里多加了一个设置私有api_key的功能。目前通过godcmd插件的命令来设置私有api_key。
+
+## 语音输入
+利用微信自带的语音识别功能，提供语音输入能力。需要在公众号管理页面的“设置与开发”->“接口权限”页面开启“接收语音识别结果”。
+
+## 语音回复
+请在配置文件中添加以下词条：
+```
+  "voice_reply_voice": true,
+```
+这样公众号将会用语音回复语音消息，实现语音对话。
+
+默认的语音合成引擎是`google`，它是免费使用的。
+
+如果要选择其他的语音合成引擎，请添加以下配置项：
+```
+"text_to_voice": "pytts"
+```
+
+pytts是本地的语音合成引擎。还支持baidu,azure，这些你需要自行配置相关的依赖和key。
+
+如果使用pytts，在ubuntu上需要安装如下依赖：
+```
+sudo apt update
+sudo apt install espeak
+sudo apt install ffmpeg
+python3 -m pip install pyttsx3
+```
+不是很建议开启pytts语音回复，因为它是离线本地计算，算的慢会拖垮服务器，且声音不好听。
+
+## 图片回复
+现在认证公众号和非认证公众号都可以实现的图片和语音回复。但是非认证公众号使用了永久素材接口，每天有1000次的调用上限（每个月有10次重置机会，程序中已设定遇到上限会自动重置），且永久素材库存也有上限。因此对于非认证公众号，我们会在回复图片或者语音消息后的10秒内从永久素材库存内删除该素材。
+
+## 测试
+目前在`RoboStyle`这个公众号上进行了测试（基于[wechatmp分支](https://github.com/JS00000/chatgpt-on-wechat/tree/wechatmp)），感兴趣的可以关注并体验。开启了godcmd, Banwords, role, dungeon, finish这五个插件，其他的插件还没有详尽测试。百度的接口暂未测试。[wechatmp-stable分支](https://github.com/JS00000/chatgpt-on-wechat/tree/wechatmp-stable)是较稳定的上个版本，但也缺少最新的功能支持。
+
+## TODO
+ - [x] 语音输入
+ - [x] 图片输入
+ - [x] 使用临时素材接口提供认证公众号的图片和语音回复
+ - [x] 使用永久素材接口提供未认证公众号的图片和语音回复
+ - [ ] 高并发支持
diff --git a/channel/wechatmp/active_reply.py b/channel/wechatmp/active_reply.py
new file mode 100644
index 0000000..f236981
--- /dev/null
+++ b/channel/wechatmp/active_reply.py
@@ -0,0 +1,75 @@
+import time
+
+import web
+from wechatpy import parse_message
+from wechatpy.replies import create_reply
+
+from bridge.context import *
+from bridge.reply import *
+from channel.wechatmp.common import *
+from channel.wechatmp.wechatmp_channel import WechatMPChannel
+from channel.wechatmp.wechatmp_message import WeChatMPMessage
+from common.log import logger
+from config import conf, subscribe_msg
+
+
+# This class is instantiated once per query
+class Query:
+    def GET(self):
+        return verify_server(web.input())
+
+    def POST(self):
+        # Make sure to return the instance that first created, @singleton will do that.
+        try:
+            args = web.input()
+            verify_server(args)
+            channel = WechatMPChannel()
+            message = web.data()
+            encrypt_func = lambda x: x
+            if args.get("encrypt_type") == "aes":
+                logger.debug("[wechatmp] Receive encrypted post data:\n" + message.decode("utf-8"))
+                if not channel.crypto:
+                    raise Exception("Crypto not initialized, Please set wechatmp_aes_key in config.json")
+                message = channel.crypto.decrypt_message(message, args.msg_signature, args.timestamp, args.nonce)
+                encrypt_func = lambda x: channel.crypto.encrypt_message(x, args.nonce, args.timestamp)
+            else:
+                logger.debug("[wechatmp] Receive post data:\n" + message.decode("utf-8"))
+            msg = parse_message(message)
+            if msg.type in ["text", "voice", "image"]:
+                wechatmp_msg = WeChatMPMessage(msg, client=channel.client)
+                from_user = wechatmp_msg.from_user_id
+                content = wechatmp_msg.content
+                message_id = wechatmp_msg.msg_id
+
+                logger.info(
+                    "[wechatmp] {}:{} Receive post query {} {}: {}".format(
+                        web.ctx.env.get("REMOTE_ADDR"),
+                        web.ctx.env.get("REMOTE_PORT"),
+                        from_user,
+                        message_id,
+                        content,
+                    )
+                )
+                if msg.type == "voice" and wechatmp_msg.ctype == ContextType.TEXT and conf().get("voice_reply_voice", False):
+                    context = channel._compose_context(wechatmp_msg.ctype, content, isgroup=False, desire_rtype=ReplyType.VOICE, msg=wechatmp_msg)
+                else:
+                    context = channel._compose_context(wechatmp_msg.ctype, content, isgroup=False, msg=wechatmp_msg)
+                if context:
+                    channel.produce(context)
+                # The reply will be sent by channel.send() in another thread
+                return "success"
+            elif msg.type == "event":
+                logger.info("[wechatmp] Event {} from {}".format(msg.event, msg.source))
+                if msg.event in ["subscribe", "subscribe_scan"]:
+                    reply_text = subscribe_msg()
+                    if reply_text:
+                        replyPost = create_reply(reply_text, msg)
+                        return encrypt_func(replyPost.render())
+                else:
+                    return "success"
+            else:
+                logger.info("暂且不处理")
+            return "success"
+        except Exception as exc:
+            logger.exception(exc)
+            return exc
diff --git a/channel/wechatmp/common.py b/channel/wechatmp/common.py
new file mode 100644
index 0000000..a994c01
--- /dev/null
+++ b/channel/wechatmp/common.py
@@ -0,0 +1,33 @@
+import web
+from wechatpy.crypto import WeChatCrypto
+from wechatpy.exceptions import InvalidSignatureException
+from wechatpy.utils import check_signature
+
+from config import conf
+
+MAX_UTF8_LEN = 2048
+
+
+class WeChatAPIException(Exception):
+    pass
+
+
+def verify_server(data):
+    try:
+        signature = data.signature
+        timestamp = data.timestamp
+        nonce = data.nonce
+        echostr = data.get("echostr", None)
+        token = conf().get("wechatmp_token")  # 请按照公众平台官网\基本配置中信息填写
+        # Reject when token is empty: an empty token reduces signature verification
+        # to a predictable hash over attacker-controlled values.
+        if not token:
+            raise web.Forbidden("wechatmp_token is not configured")
+        check_signature(token, signature, timestamp, nonce)
+        return echostr
+    except InvalidSignatureException:
+        raise web.Forbidden("Invalid signature")
+    except web.Forbidden:
+        raise
+    except Exception as e:
+        raise web.Forbidden(str(e))
diff --git a/channel/wechatmp/passive_reply.py b/channel/wechatmp/passive_reply.py
new file mode 100644
index 0000000..85b3b40
--- /dev/null
+++ b/channel/wechatmp/passive_reply.py
@@ -0,0 +1,232 @@
+import asyncio
+import time
+
+import web
+from wechatpy import parse_message
+from wechatpy.replies import ImageReply, VoiceReply, create_reply
+import textwrap
+from bridge.context import *
+from bridge.reply import *
+from channel.wechatmp.common import *
+from channel.wechatmp.wechatmp_channel import WechatMPChannel
+from channel.wechatmp.wechatmp_message import WeChatMPMessage
+from common.log import logger
+from common.utils import split_string_by_utf8_length
+from config import conf, subscribe_msg
+
+
+# This class is instantiated once per query
+class Query:
+    def GET(self):
+        return verify_server(web.input())
+
+    def POST(self):
+        try:
+            args = web.input()
+            verify_server(args)
+            request_time = time.time()
+            channel = WechatMPChannel()
+            message = web.data()
+            encrypt_func = lambda x: x
+            if args.get("encrypt_type") == "aes":
+                logger.debug("[wechatmp] Receive encrypted post data:\n" + message.decode("utf-8"))
+                if not channel.crypto:
+                    raise Exception("Crypto not initialized, Please set wechatmp_aes_key in config.json")
+                message = channel.crypto.decrypt_message(message, args.msg_signature, args.timestamp, args.nonce)
+                encrypt_func = lambda x: channel.crypto.encrypt_message(x, args.nonce, args.timestamp)
+            else:
+                logger.debug("[wechatmp] Receive post data:\n" + message.decode("utf-8"))
+            msg = parse_message(message)
+            if msg.type in ["text", "voice", "image"]:
+                wechatmp_msg = WeChatMPMessage(msg, client=channel.client)
+                from_user = wechatmp_msg.from_user_id
+                content = wechatmp_msg.content
+                message_id = wechatmp_msg.msg_id
+
+                supported = True
+                if "【收到不支持的消息类型，暂无法显示】" in content:
+                    supported = False  # not supported, used to refresh
+
+                # New request
+                if (
+                    channel.cache_dict.get(from_user) is None
+                    and from_user not in channel.running
+                    or content.startswith("#")
+                    and message_id not in channel.request_cnt  # insert the godcmd
+                ):
+                    # The first query begin
+                    if msg.type == "voice" and wechatmp_msg.ctype == ContextType.TEXT and conf().get("voice_reply_voice", False):
+                        context = channel._compose_context(wechatmp_msg.ctype, content, isgroup=False, desire_rtype=ReplyType.VOICE, msg=wechatmp_msg)
+                    else:
+                        context = channel._compose_context(wechatmp_msg.ctype, content, isgroup=False, msg=wechatmp_msg)
+                    logger.debug("[wechatmp] context: {} {} {}".format(context, wechatmp_msg, supported))
+
+                    if supported and context:
+                        channel.running.add(from_user)
+                        channel.produce(context)
+                    else:
+                        trigger_prefix = conf().get("single_chat_prefix", [""])[0]
+                        if trigger_prefix or not supported:
+                            if trigger_prefix:
+                                reply_text = textwrap.dedent(
+                                    f"""\
+                                    请输入'{trigger_prefix}'接你想说的话跟我说话。
+                                    例如:
+                                    {trigger_prefix}你好，很高兴见到你。"""
+                                )
+                            else:
+                                reply_text = textwrap.dedent(
+                                    """\
+                                    你好，很高兴见到你。
+                                    请跟我说话吧。"""
+                                )
+                        else:
+                            logger.error(f"[wechatmp] unknown error")
+                            reply_text = textwrap.dedent(
+                                """\
+                                未知错误，请稍后再试"""
+                            )
+
+                        replyPost = create_reply(reply_text, msg)
+                        return encrypt_func(replyPost.render())
+
+                # Wechat official server will request 3 times (5 seconds each), with the same message_id.
+                # Because the interval is 5 seconds, here assumed that do not have multithreading problems.
+                request_cnt = channel.request_cnt.get(message_id, 0) + 1
+                channel.request_cnt[message_id] = request_cnt
+                logger.info(
+                    "[wechatmp] Request {} from {} {} {}:{}\n{}".format(
+                        request_cnt, from_user, message_id, web.ctx.env.get("REMOTE_ADDR"), web.ctx.env.get("REMOTE_PORT"), content
+                    )
+                )
+
+                task_running = True
+                waiting_until = request_time + 4
+                while time.time() < waiting_until:
+                    if from_user not in channel.running:
+                        task_running = False
+                        break
+                    # Task still running, but if it has already produced cached
+                    # segments (e.g. multi-turn thinking output), return them now
+                    # instead of forcing the user to wait for the whole task. The
+                    # remaining segments are fetched by the user's next message.
+                    if channel.cache_dict.get(from_user):
+                        break
+                    time.sleep(0.1)
+
+                reply_text = ""
+                # Only fall back to retry / "thinking" hint when the task is still
+                # running AND there is nothing cached to send yet.
+                if task_running and not channel.cache_dict.get(from_user):
+                    if request_cnt < 3:
+                        # waiting for timeout (the POST request will be closed by Wechat official server)
+                        time.sleep(2)
+                        # and do nothing, waiting for the next request
+                        return "success"
+                    else:  # request_cnt == 3:
+                        # return timeout message
+                        reply_text = "【正在思考中，回复任意文字尝试获取回复】"
+                        replyPost = create_reply(reply_text, msg)
+                        return encrypt_func(replyPost.render())
+
+                # reply is ready
+                channel.request_cnt.pop(message_id)
+
+                # no return because of bandwords or other reasons
+                if from_user not in channel.cache_dict and from_user not in channel.running:
+                    return "success"
+
+                # Only one request can access to the cached data
+                try:
+                    # WeChat passive reply allows only a single reply per request.
+                    # To avoid forcing the user to send an extra message for every
+                    # segment of multi-turn agent output, drain all consecutive
+                    # cached text segments at once and merge them into one reply.
+                    # Media (voice/image) can only be returned one at a time, so it
+                    # stops the merge and is returned on its own.
+                    cached = channel.cache_dict[from_user]
+                    if cached[0][0] == "text":
+                        reply_type = "text"
+                        merged_parts = []
+                        while cached and cached[0][0] == "text":
+                            merged_parts.append(cached.pop(0)[1])
+                        reply_content = "\n\n".join(merged_parts)
+                    else:
+                        (reply_type, reply_content) = cached.pop(0)
+                    if not channel.cache_dict[from_user]:  # If draining empties the list, delete the user entry from cache
+                        del channel.cache_dict[from_user]
+                except IndexError:
+                    return "success"
+
+                if reply_type == "text":
+                    if len(reply_content.encode("utf8")) <= MAX_UTF8_LEN:
+                        reply_text = reply_content
+                    else:
+                        continue_text = "\n【未完待续，回复任意文字以继续】"
+                        splits = split_string_by_utf8_length(
+                            reply_content,
+                            MAX_UTF8_LEN - len(continue_text.encode("utf-8")),
+                            max_split=1,
+                        )
+                        reply_text = splits[0] + continue_text
+                        channel.cache_dict[from_user].append(("text", splits[1]))
+
+                    logger.info(
+                        "[wechatmp] Request {} do send to {} {}: {}\n{}".format(
+                            request_cnt,
+                            from_user,
+                            message_id,
+                            content,
+                            reply_text,
+                        )
+                    )
+                    replyPost = create_reply(reply_text, msg)
+                    return encrypt_func(replyPost.render())
+
+                elif reply_type == "voice":
+                    media_id = reply_content
+                    asyncio.run_coroutine_threadsafe(channel.delete_media(media_id), channel.delete_media_loop)
+                    logger.info(
+                        "[wechatmp] Request {} do send to {} {}: {} voice media_id {}".format(
+                            request_cnt,
+                            from_user,
+                            message_id,
+                            content,
+                            media_id,
+                        )
+                    )
+                    replyPost = VoiceReply(message=msg)
+                    replyPost.media_id = media_id
+                    return encrypt_func(replyPost.render())
+
+                elif reply_type == "image":
+                    media_id = reply_content
+                    asyncio.run_coroutine_threadsafe(channel.delete_media(media_id), channel.delete_media_loop)
+                    logger.info(
+                        "[wechatmp] Request {} do send to {} {}: {} image media_id {}".format(
+                            request_cnt,
+                            from_user,
+                            message_id,
+                            content,
+                            media_id,
+                        )
+                    )
+                    replyPost = ImageReply(message=msg)
+                    replyPost.media_id = media_id
+                    return encrypt_func(replyPost.render())
+
+            elif msg.type == "event":
+                logger.info("[wechatmp] Event {} from {}".format(msg.event, msg.source))
+                if msg.event in ["subscribe", "subscribe_scan"]:
+                    reply_text = subscribe_msg()
+                    if reply_text:
+                        replyPost = create_reply(reply_text, msg)
+                        return encrypt_func(replyPost.render())
+                else:
+                    return "success"
+            else:
+                logger.info("暂且不处理")
+            return "success"
+        except Exception as exc:
+            logger.exception(exc)
+            return exc
diff --git a/channel/wechatmp/wechatmp_channel.py b/channel/wechatmp/wechatmp_channel.py
new file mode 100644
index 0000000..dc0ffb2
--- /dev/null
+++ b/channel/wechatmp/wechatmp_channel.py
@@ -0,0 +1,346 @@
+# -*- coding: utf-8 -*-
+import asyncio
+import imghdr
+import io
+import os
+import threading
+import time
+
+import requests
+import web
+from wechatpy.crypto import WeChatCrypto
+from wechatpy.exceptions import WeChatClientException
+from collections import defaultdict
+
+from bridge.context import *
+from bridge.reply import *
+from channel.chat_channel import ChatChannel
+from channel.wechatmp.common import *
+from channel.wechatmp.wechatmp_client import WechatMPClient
+from common.log import logger
+from common.singleton import singleton
+from common.utils import split_string_by_utf8_length, remove_markdown_symbol
+from config import conf
+
+try:
+    from voice.audio_convert import any_to_mp3, split_audio
+except ImportError as e:
+    logger.debug("import voice.audio_convert failed, voice features will not be supported: {}".format(e))
+
+# If using SSL, uncomment the following lines, and modify the certificate path.
+# from cheroot.server import HTTPServer
+# from cheroot.ssl.builtin import BuiltinSSLAdapter
+# HTTPServer.ssl_adapter = BuiltinSSLAdapter(
+#         certificate='/ssl/cert.pem',
+#         private_key='/ssl/cert.key')
+
+
+@singleton
+class WechatMPChannel(ChatChannel):
+    def __init__(self, passive_reply=True):
+        super().__init__()
+        self.passive_reply = passive_reply
+        self.NOT_SUPPORT_REPLYTYPE = []
+        self._http_server = None
+        appid = conf().get("wechatmp_app_id")
+        secret = conf().get("wechatmp_app_secret")
+        token = conf().get("wechatmp_token")
+        aes_key = conf().get("wechatmp_aes_key")
+        self.client = WechatMPClient(appid, secret)
+        self.crypto = None
+        if aes_key:
+            self.crypto = WeChatCrypto(token, aes_key, appid)
+        if self.passive_reply:
+            # Cache the reply to the user's first message
+            self.cache_dict = defaultdict(list)
+            # Record whether the current message is being processed
+            self.running = set()
+            # Count the request from wechat official server by message_id
+            self.request_cnt = dict()
+            # The permanent media need to be deleted to avoid media number limit
+            self.delete_media_loop = asyncio.new_event_loop()
+            t = threading.Thread(target=self.start_loop, args=(self.delete_media_loop,))
+            t.setDaemon(True)
+            t.start()
+
+    def startup(self):
+        if self.passive_reply:
+            urls = ("/wx", "channel.wechatmp.passive_reply.Query")
+        else:
+            urls = ("/wx", "channel.wechatmp.active_reply.Query")
+        app = web.application(urls, globals(), autoreload=False)
+        port = conf().get("wechatmp_port", 8080)
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer(("0.0.0.0", port), func)
+        self._http_server = server
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+
+    def stop(self):
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[wechatmp] HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[wechatmp] Error stopping HTTP server: {e}")
+            self._http_server = None
+
+    def start_loop(self, loop):
+        asyncio.set_event_loop(loop)
+        loop.run_forever()
+
+    async def delete_media(self, media_id):
+        logger.debug("[wechatmp] permanent media {} will be deleted in 10s".format(media_id))
+        await asyncio.sleep(10)
+        self.client.material.delete(media_id)
+        logger.info("[wechatmp] permanent media {} has been deleted".format(media_id))
+
+    def send(self, reply: Reply, context: Context):
+        receiver = context["receiver"]
+        if self.passive_reply:
+            if reply.type == ReplyType.TEXT or reply.type == ReplyType.INFO or reply.type == ReplyType.ERROR:
+                reply_text = remove_markdown_symbol(reply.content)
+                logger.info("[wechatmp] text cached, receiver {}\n{}".format(receiver, reply_text))
+                self.cache_dict[receiver].append(("text", reply_text))
+            elif reply.type == ReplyType.VOICE:
+                try:
+                    voice_file_path = reply.content
+                    duration, files = split_audio(voice_file_path, 60 * 1000)
+                    if len(files) > 1:
+                        logger.info("[wechatmp] voice too long {}s > 60s , split into {} parts".format(duration / 1000.0, len(files)))
+
+                    for path in files:
+                        # support: <2M, <60s, mp3/wma/wav/amr
+                        try:
+                            with open(path, "rb") as f:
+                                response = self.client.material.add("voice", f)
+                                logger.debug("[wechatmp] upload voice response: {}".format(response))
+                                f_size = os.fstat(f.fileno()).st_size
+                                time.sleep(1.0 + 2 * f_size / 1024 / 1024)
+                                # todo check media_id
+                        except WeChatClientException as e:
+                            logger.error("[wechatmp] upload voice failed: {}".format(e))
+                            return
+                        media_id = response["media_id"]
+                        logger.info("[wechatmp] voice uploaded, receiver {}, media_id {}".format(receiver, media_id))
+                        self.cache_dict[receiver].append(("voice", media_id))
+                except ImportError as e:
+                    logger.error("[wechatmp] voice conversion failed: {}".format(e))
+                    logger.error("[wechatmp] please install pydub: pip install pydub")
+                    return
+
+            elif reply.type == ReplyType.IMAGE_URL:  # 从网络下载图片
+                img_url = reply.content
+                image_storage = io.BytesIO()
+                if img_url.startswith("file://") or os.path.isfile(img_url):
+                    # Local file produced by the agent (e.g. a generated image)
+                    local_path = img_url[len("file://"):] if img_url.startswith("file://") else img_url
+                    with open(local_path, "rb") as f:
+                        image_storage.write(f.read())
+                else:
+                    pic_res = requests.get(img_url, stream=True)
+                    for block in pic_res.iter_content(1024):
+                        image_storage.write(block)
+                image_storage.seek(0)
+                image_type = imghdr.what(image_storage)
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + image_type
+                content_type = "image/" + image_type
+                try:
+                    response = self.client.material.add("image", (filename, image_storage, content_type))
+                    logger.debug("[wechatmp] upload image response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload image failed: {}".format(e))
+                    return
+                media_id = response["media_id"]
+                logger.info("[wechatmp] image uploaded, receiver {}, media_id {}".format(receiver, media_id))
+                self.cache_dict[receiver].append(("image", media_id))
+            elif reply.type == ReplyType.IMAGE:  # 从文件读取图片
+                image_storage = reply.content
+                image_storage.seek(0)
+                image_type = imghdr.what(image_storage)
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + image_type
+                content_type = "image/" + image_type
+                try:
+                    response = self.client.material.add("image", (filename, image_storage, content_type))
+                    logger.debug("[wechatmp] upload image response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload image failed: {}".format(e))
+                    return
+                media_id = response["media_id"]
+                logger.info("[wechatmp] image uploaded, receiver {}, media_id {}".format(receiver, media_id))
+                self.cache_dict[receiver].append(("image", media_id))
+            elif reply.type == ReplyType.VIDEO_URL:  # 从网络下载视频
+                video_url = reply.content
+                video_res = requests.get(video_url, stream=True)
+                video_storage = io.BytesIO()
+                for block in video_res.iter_content(1024):
+                    video_storage.write(block)
+                video_storage.seek(0)
+                video_type = 'mp4'
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + video_type
+                content_type = "video/" + video_type
+                try:
+                    response = self.client.material.add("video", (filename, video_storage, content_type))
+                    logger.debug("[wechatmp] upload video response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload video failed: {}".format(e))
+                    return
+                media_id = response["media_id"]
+                logger.info("[wechatmp] video uploaded, receiver {}, media_id {}".format(receiver, media_id))
+                self.cache_dict[receiver].append(("video", media_id))
+
+            elif reply.type == ReplyType.VIDEO:  # 从文件读取视频
+                video_storage = reply.content
+                video_storage.seek(0)
+                video_type = 'mp4'
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + video_type
+                content_type = "video/" + video_type
+                try:
+                    response = self.client.material.add("video", (filename, video_storage, content_type))
+                    logger.debug("[wechatmp] upload video response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload video failed: {}".format(e))
+                    return
+                media_id = response["media_id"]
+                logger.info("[wechatmp] video uploaded, receiver {}, media_id {}".format(receiver, media_id))
+                self.cache_dict[receiver].append(("video", media_id))
+
+        else:
+            if reply.type == ReplyType.TEXT or reply.type == ReplyType.INFO or reply.type == ReplyType.ERROR:
+                reply_text = reply.content
+                texts = split_string_by_utf8_length(reply_text, MAX_UTF8_LEN)
+                if len(texts) > 1:
+                    logger.info("[wechatmp] text too long, split into {} parts".format(len(texts)))
+                for i, text in enumerate(texts):
+                    self.client.message.send_text(receiver, text)
+                    if i != len(texts) - 1:
+                        time.sleep(0.5)  # 休眠0.5秒，防止发送过快乱序
+                logger.info("[wechatmp] Do send text to {}: {}".format(receiver, reply_text))
+            elif reply.type == ReplyType.VOICE:
+                try:
+                    file_path = reply.content
+                    file_name = os.path.basename(file_path)
+                    file_type = os.path.splitext(file_name)[1]
+                    if file_type == ".mp3":
+                        file_type = "audio/mpeg"
+                    elif file_type == ".amr":
+                        file_type = "audio/amr"
+                    else:
+                        mp3_file = os.path.splitext(file_path)[0] + ".mp3"
+                        any_to_mp3(file_path, mp3_file)
+                        file_path = mp3_file
+                        file_name = os.path.basename(file_path)
+                        file_type = "audio/mpeg"
+                    logger.info("[wechatmp] file_name: {}, file_type: {} ".format(file_name, file_type))
+                    media_ids = []
+                    duration, files = split_audio(file_path, 60 * 1000)
+                    if len(files) > 1:
+                        logger.info("[wechatmp] voice too long {}s > 60s , split into {} parts".format(duration / 1000.0, len(files)))
+                    for path in files:
+                        # support: <2M, <60s, AMR\MP3
+                        response = self.client.media.upload("voice", (os.path.basename(path), open(path, "rb"), file_type))
+                        logger.debug("[wechatcom] upload voice response: {}".format(response))
+                        media_ids.append(response["media_id"])
+                        os.remove(path)
+                except ImportError as e:
+                    logger.error("[wechatmp] voice conversion failed: {}".format(e))
+                    logger.error("[wechatmp] please install pydub: pip install pydub")
+                    return
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload voice failed: {}".format(e))
+                    return
+
+                try:
+                    os.remove(file_path)
+                except Exception:
+                    pass
+
+                for media_id in media_ids:
+                    self.client.message.send_voice(receiver, media_id)
+                    time.sleep(1)
+                logger.info("[wechatmp] Do send voice to {}".format(receiver))
+            elif reply.type == ReplyType.IMAGE_URL:  # 从网络下载图片
+                img_url = reply.content
+                image_storage = io.BytesIO()
+                if img_url.startswith("file://") or os.path.isfile(img_url):
+                    # Local file produced by the agent (e.g. a generated image)
+                    local_path = img_url[len("file://"):] if img_url.startswith("file://") else img_url
+                    with open(local_path, "rb") as f:
+                        image_storage.write(f.read())
+                else:
+                    pic_res = requests.get(img_url, stream=True)
+                    for block in pic_res.iter_content(1024):
+                        image_storage.write(block)
+                image_storage.seek(0)
+                image_type = imghdr.what(image_storage)
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + image_type
+                content_type = "image/" + image_type
+                try:
+                    response = self.client.media.upload("image", (filename, image_storage, content_type))
+                    logger.debug("[wechatmp] upload image response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload image failed: {}".format(e))
+                    return
+                self.client.message.send_image(receiver, response["media_id"])
+                logger.info("[wechatmp] Do send image to {}".format(receiver))
+            elif reply.type == ReplyType.IMAGE:  # 从文件读取图片
+                image_storage = reply.content
+                image_storage.seek(0)
+                image_type = imghdr.what(image_storage)
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + image_type
+                content_type = "image/" + image_type
+                try:
+                    response = self.client.media.upload("image", (filename, image_storage, content_type))
+                    logger.debug("[wechatmp] upload image response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload image failed: {}".format(e))
+                    return
+                self.client.message.send_image(receiver, response["media_id"])
+                logger.info("[wechatmp] Do send image to {}".format(receiver))
+            elif reply.type == ReplyType.VIDEO_URL:  # 从网络下载视频
+                video_url = reply.content
+                video_res = requests.get(video_url, stream=True)
+                video_storage = io.BytesIO()
+                for block in video_res.iter_content(1024):
+                    video_storage.write(block)
+                video_storage.seek(0)
+                video_type = 'mp4'
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + video_type
+                content_type = "video/" + video_type
+                try:
+                    response = self.client.media.upload("video", (filename, video_storage, content_type))
+                    logger.debug("[wechatmp] upload video response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload video failed: {}".format(e))
+                    return
+                self.client.message.send_video(receiver, response["media_id"])
+                logger.info("[wechatmp] Do send video to {}".format(receiver))
+            elif reply.type == ReplyType.VIDEO:  # 从文件读取视频
+                video_storage = reply.content
+                video_storage.seek(0)
+                video_type = 'mp4'
+                filename = receiver + "-" + str(context["msg"].msg_id) + "." + video_type
+                content_type = "video/" + video_type
+                try:
+                    response = self.client.media.upload("video", (filename, video_storage, content_type))
+                    logger.debug("[wechatmp] upload video response: {}".format(response))
+                except WeChatClientException as e:
+                    logger.error("[wechatmp] upload video failed: {}".format(e))
+                    return
+                self.client.message.send_video(receiver, response["media_id"])
+                logger.info("[wechatmp] Do send video to {}".format(receiver))
+        return
+
+    def _success_callback(self, session_id, context, **kwargs):  # 线程异常结束时的回调函数
+        logger.debug("[wechatmp] Success to generate reply, msgId={}".format(context["msg"].msg_id))
+        if self.passive_reply:
+            self.running.remove(session_id)
+
+    def _fail_callback(self, session_id, exception, context, **kwargs):  # 线程异常结束时的回调函数
+        logger.exception("[wechatmp] Fail to generate reply to user, msgId={}, exception={}".format(context["msg"].msg_id, exception))
+        if self.passive_reply:
+            assert session_id not in self.cache_dict
+            self.running.remove(session_id)
diff --git a/channel/wechatmp/wechatmp_client.py b/channel/wechatmp/wechatmp_client.py
new file mode 100644
index 0000000..19dca32
--- /dev/null
+++ b/channel/wechatmp/wechatmp_client.py
@@ -0,0 +1,49 @@
+import threading
+import time
+
+from wechatpy.client import WeChatClient
+from wechatpy.exceptions import APILimitedException
+
+from channel.wechatmp.common import *
+from common.log import logger
+
+
+class WechatMPClient(WeChatClient):
+    def __init__(self, appid, secret, access_token=None, session=None, timeout=None, auto_retry=True):
+        super(WechatMPClient, self).__init__(appid, secret, access_token, session, timeout, auto_retry)
+        self.fetch_access_token_lock = threading.Lock()
+        self.clear_quota_lock = threading.Lock()
+        self.last_clear_quota_time = -1
+
+    def clear_quota(self):
+        return self.post("clear_quota", data={"appid": self.appid})
+
+    def clear_quota_v2(self):
+        return self.post("clear_quota/v2", params={"appid": self.appid, "appsecret": self.secret})
+
+    def fetch_access_token(self):  # 重载父类方法，加锁避免多线程重复获取access_token
+        with self.fetch_access_token_lock:
+            access_token = self.session.get(self.access_token_key)
+            if access_token:
+                if not self.expires_at:
+                    return access_token
+                timestamp = time.time()
+                if self.expires_at - timestamp > 60:
+                    return access_token
+            return super().fetch_access_token()
+
+    def _request(self, method, url_or_endpoint, **kwargs):  # 重载父类方法，遇到API限流时，清除quota后重试
+        try:
+            return super()._request(method, url_or_endpoint, **kwargs)
+        except APILimitedException as e:
+            logger.error("[wechatmp] API quata has been used up. {}".format(e))
+            if self.last_clear_quota_time == -1 or time.time() - self.last_clear_quota_time > 60:
+                with self.clear_quota_lock:
+                    if self.last_clear_quota_time == -1 or time.time() - self.last_clear_quota_time > 60:
+                        self.last_clear_quota_time = time.time()
+                        response = self.clear_quota_v2()
+                        logger.debug("[wechatmp] API quata has been cleard, {}".format(response))
+                return super()._request(method, url_or_endpoint, **kwargs)
+            else:
+                logger.error("[wechatmp] last clear quota time is {}, less than 60s, skip clear quota")
+                raise e
diff --git a/channel/wechatmp/wechatmp_message.py b/channel/wechatmp/wechatmp_message.py
new file mode 100644
index 0000000..27c9fbb
--- /dev/null
+++ b/channel/wechatmp/wechatmp_message.py
@@ -0,0 +1,56 @@
+# -*- coding: utf-8 -*-#
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from common.tmp_dir import TmpDir
+
+
+class WeChatMPMessage(ChatMessage):
+    def __init__(self, msg, client=None):
+        super().__init__(msg)
+        self.msg_id = msg.id
+        self.create_time = msg.time
+        self.is_group = False
+
+        if msg.type == "text":
+            self.ctype = ContextType.TEXT
+            self.content = msg.content
+        elif msg.type == "voice":
+            if msg.recognition == None:
+                self.ctype = ContextType.VOICE
+                self.content = TmpDir().path() + msg.media_id + "." + msg.format  # content直接存临时目录路径
+
+                def download_voice():
+                    # 如果响应状态码是200，则将响应内容写入本地文件
+                    response = client.media.download(msg.media_id)
+                    if response.status_code == 200:
+                        with open(self.content, "wb") as f:
+                            f.write(response.content)
+                    else:
+                        logger.info(f"[wechatmp] Failed to download voice file, {response.content}")
+
+                self._prepare_fn = download_voice
+            else:
+                self.ctype = ContextType.TEXT
+                self.content = msg.recognition
+        elif msg.type == "image":
+            self.ctype = ContextType.IMAGE
+            self.content = TmpDir().path() + msg.media_id + ".png"  # content直接存临时目录路径
+
+            def download_image():
+                # 如果响应状态码是200，则将响应内容写入本地文件
+                response = client.media.download(msg.media_id)
+                if response.status_code == 200:
+                    with open(self.content, "wb") as f:
+                        f.write(response.content)
+                else:
+                    logger.info(f"[wechatmp] Failed to download image file, {response.content}")
+
+            self._prepare_fn = download_image
+        else:
+            raise NotImplementedError("Unsupported message type: Type:{} ".format(msg.type))
+
+        self.from_user_id = msg.source
+        self.to_user_id = msg.target
+        self.other_user_id = msg.source
diff --git a/channel/wecom_bot/__init__.py b/channel/wecom_bot/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/channel/wecom_bot/wecom_bot_channel.py b/channel/wecom_bot/wecom_bot_channel.py
new file mode 100644
index 0000000..9ecbbef
--- /dev/null
+++ b/channel/wecom_bot/wecom_bot_channel.py
@@ -0,0 +1,1438 @@
+"""
+WeCom (企业微信) AI Bot channel via WebSocket long connection.
+
+Supports:
+- Single chat and group chat (text / image / file input & output)
+- Scheduled task push via aibot_send_msg
+- Heartbeat keep-alive and auto-reconnect
+"""
+
+import base64
+import hashlib
+import json
+import math
+import os
+import re
+import threading
+import time
+import uuid
+
+import requests
+import web
+import websocket
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.wecom_bot.wecom_bot_crypt import WecomBotCrypt
+from channel.wecom_bot.wecom_bot_message import WecomBotMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from common.ws_client_compat import websocket_app_run_forever
+from config import conf
+
+WECOM_WS_URL = "wss://openws.work.weixin.qq.com"
+HEARTBEAT_INTERVAL = 30
+MEDIA_CHUNK_SIZE = 512 * 1024  # 512KB per chunk (before base64 encoding)
+# Fixed URL path for the callback (webhook) HTTP server. The bot's
+# receive-message URL must point at this path, e.g. http://host:9892/wecombot
+CALLBACK_PATH = "/wecombot"
+
+
+def _escape_control_chars_inside_json_strings(s: str) -> str:
+    """Escape U+0000–U+001F inside JSON string values so json.loads accepts WeCom payloads.
+
+    The server occasionally emits raw newlines/tabs inside quoted fields, which is
+    invalid strict JSON but recoverable without touching escapes like \\n or \\".
+    """
+    out = []
+    in_string = False
+    escape = False
+    for c in s:
+        if escape:
+            out.append(c)
+            escape = False
+            continue
+        if in_string and c == "\\":
+            out.append(c)
+            escape = True
+            continue
+        if c == '"':
+            out.append(c)
+            in_string = not in_string
+            continue
+        if in_string and ord(c) < 32:
+            out.append("\\u%04x" % ord(c))
+            continue
+        out.append(c)
+    return "".join(out)
+
+
+def _loads_wecom_ws_json(raw):
+    """Parse WebSocket JSON; tolerate unescaped control characters inside strings."""
+    if isinstance(raw, bytes):
+        raw = raw.decode("utf-8", errors="replace")
+    if not isinstance(raw, str):
+        raw = str(raw)
+    try:
+        return json.loads(raw)
+    except json.JSONDecodeError as e:
+        msg = str(e).lower()
+        if "control character" in msg:
+            return json.loads(_escape_control_chars_inside_json_strings(raw))
+        raise
+
+
+@singleton
+class WecomBotChannel(ChatChannel):
+
+    NOT_SUPPORT_REPLYTYPE = []
+
+    def __init__(self):
+        super().__init__()
+        self.bot_id = ""
+        self.bot_secret = ""
+        self.received_msgs = ExpiredDict(60 * 60 * 7.1)
+        self._ws = None
+        self._ws_thread = None
+        self._heartbeat_thread = None
+        self._connected = False
+        self._stop_event = threading.Event()
+        self._pending_responses = {}  # req_id -> (threading.Event, result_holder)
+        self._pending_lock = threading.Lock()
+        self._stream_states = {}  # req_id -> {"stream_id": str, "content": str}
+
+        # Transport mode: "websocket" (long connection) or "webhook" (HTTP callback)
+        self.mode = "websocket"
+        self._crypt = None
+        self._http_server = None
+        # stream_id -> {"committed", "current", "finished", "images", "last_access"}
+        self._callback_streams = ExpiredDict(60 * 10)  # auto-expire after 10min (max poll window is 6min)
+        self._callback_lock = threading.Lock()
+
+        conf()["group_name_white_list"] = ["ALL_GROUP"]
+        conf()["single_chat_prefix"] = [""]
+
+    # ------------------------------------------------------------------
+    # Lifecycle
+    # ------------------------------------------------------------------
+
+    def startup(self):
+        self.mode = conf().get("wecom_bot_mode", "websocket")
+        if self.mode == "webhook":
+            self._startup_callback()
+            return
+
+        self.bot_id = conf().get("wecom_bot_id", "")
+        self.bot_secret = conf().get("wecom_bot_secret", "")
+
+        if not self.bot_id or not self.bot_secret:
+            err = "[WecomBot] wecom_bot_id and wecom_bot_secret are required"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        self._stop_event.clear()
+        self._start_ws()
+
+    def stop(self):
+        logger.info("[WecomBot] stop() called")
+        self._stop_event.set()
+        if self._ws:
+            try:
+                self._ws.close()
+            except Exception:
+                pass
+        self._ws = None
+        self._connected = False
+        if self._http_server:
+            try:
+                self._http_server.stop()
+                logger.info("[WecomBot] Callback HTTP server stopped")
+            except Exception as e:
+                logger.warning(f"[WecomBot] Error stopping HTTP server: {e}")
+            self._http_server = None
+
+    # ------------------------------------------------------------------
+    # WebSocket connection
+    # ------------------------------------------------------------------
+
+    def _start_ws(self):
+        def _on_open(ws):
+            logger.info("[WecomBot] WebSocket connected, sending subscribe...")
+            self._send_subscribe()
+
+        def _on_message(ws, raw):
+            try:
+                data = _loads_wecom_ws_json(raw)
+                self._handle_ws_message(data)
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to handle ws message: {e}", exc_info=True)
+
+        def _on_error(ws, error):
+            logger.error(f"[WecomBot] WebSocket error: {error}")
+
+        def _on_close(ws, close_status_code, close_msg):
+            logger.warning(f"[WecomBot] WebSocket closed: status={close_status_code}, msg={close_msg}")
+            self._connected = False
+            if not self._stop_event.is_set():
+                logger.info("[WecomBot] Will reconnect in 5s...")
+                time.sleep(5)
+                if not self._stop_event.is_set():
+                    self._start_ws()
+
+        self._ws = websocket.WebSocketApp(
+            WECOM_WS_URL,
+            on_open=_on_open,
+            on_message=_on_message,
+            on_error=_on_error,
+            on_close=_on_close,
+        )
+
+        def run_forever():
+            try:
+                websocket_app_run_forever(self._ws, ping_interval=0, reconnect=0)
+            except (SystemExit, KeyboardInterrupt):
+                logger.info("[WecomBot] WebSocket thread interrupted")
+            except Exception as e:
+                logger.error(f"[WecomBot] WebSocket run_forever error: {e}")
+
+        self._ws_thread = threading.Thread(target=run_forever, daemon=True)
+        self._ws_thread.start()
+        self._ws_thread.join()
+
+    def _ws_send(self, data: dict):
+        if self._ws:
+            self._ws.send(json.dumps(data, ensure_ascii=False))
+
+    def _gen_req_id(self) -> str:
+        return uuid.uuid4().hex[:16]
+
+    # ------------------------------------------------------------------
+    # Callback (webhook) mode
+    # ------------------------------------------------------------------
+
+    def _startup_callback(self):
+        """Start an HTTP server that receives encrypted callbacks (webhook mode).
+
+        The bot's "接收消息" URL in the WeCom admin console should point at this
+        server (any path is accepted). Verification (GET) and message delivery
+        (POST) are both handled by ``WecomBotCallbackController``.
+        """
+        token = conf().get("wecom_bot_token", "")
+        aes_key = conf().get("wecom_bot_encoding_aes_key", "")
+        if not token or not aes_key:
+            err = "[WecomBot] callback mode requires wecom_bot_token and wecom_bot_encoding_aes_key"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        try:
+            # Enterprise-internal smart bot: receive_id is an empty string.
+            self._crypt = WecomBotCrypt(token, aes_key, "")
+        except Exception as e:
+            err = f"[WecomBot] invalid callback credentials: {e}"
+            logger.error(err)
+            self.report_startup_error(err)
+            return
+
+        port = int(conf().get("wecom_bot_port", 9892))
+        logger.info(f"[WecomBot] Starting callback (webhook) server on port {port}, path {CALLBACK_PATH} ...")
+        # Only serve the fixed callback path; everything else 404s instead of being
+        # treated as a (signature-failing) WeCom callback.
+        urls = (re.escape(CALLBACK_PATH), "channel.wecom_bot.wecom_bot_channel.WecomBotCallbackController")
+        app = web.application(urls, globals(), autoreload=False)
+        func = web.httpserver.StaticMiddleware(app.wsgifunc())
+        func = web.httpserver.LogMiddleware(func)
+        server = web.httpserver.WSGIServer(("0.0.0.0", port), func)
+        self._http_server = server
+        self.report_startup_success()
+        try:
+            server.start()
+        except (KeyboardInterrupt, SystemExit):
+            server.stop()
+
+    def _new_callback_stream(self, response_url: str = "") -> str:
+        """Create a new stream state and return its id."""
+        stream_id = uuid.uuid4().hex[:16]
+        now = time.time()
+        with self._callback_lock:
+            self._callback_streams[stream_id] = {
+                "committed": "",
+                "current": "",
+                "finished": False,
+                "images": [],  # list of (base64_str, md5_str), flushed only at finish
+                "image_urls": [],  # public http(s) image urls (usable in response_url markdown)
+                "image_pending": False,  # an image reply is being prepared; don't finish on text yet
+                "last_access": now,
+                "created_at": now,
+                "response_url": response_url or "",
+                "delivered": False,  # final answer handed to WeCom via a poll
+                "url_sent": False,   # final answer pushed via response_url (active reply)
+            }
+        return stream_id
+
+    def _callback_handle_message(self, data: dict) -> dict:
+        """Handle a freshly-received user message in callback mode.
+
+        Produces the context for async processing and returns the initial passive
+        reply (a stream packet with finish=false) so WeCom starts polling for the
+        agent's streamed answer. Returns ``None`` when there's nothing to reply
+        (e.g. an image/file silently cached for the next query).
+        """
+        msg_id = data.get("msgid", "")
+        if msg_id and self.received_msgs.get(msg_id):
+            logger.debug(f"[WecomBot] Duplicate msg filtered: {msg_id}")
+            return None
+        if msg_id:
+            self.received_msgs[msg_id] = True
+
+        chattype = data.get("chattype", "single")
+        is_group = chattype == "group"
+
+        default_aeskey = conf().get("wecom_bot_encoding_aes_key", "")
+        result = self._build_context(data, is_group, default_aeskey=default_aeskey)
+        if not result:
+            return None
+        context, wecom_msg = result
+
+        # response_url lets us actively reply once within 1h, used as a fallback
+        # when the agent finishes after WeCom stops polling (max ~6min window).
+        response_url = data.get("response_url", "") or ""
+        stream_id = self._new_callback_stream(response_url=response_url)
+        wecom_msg.stream_id = stream_id
+        context["wecom_stream_id"] = stream_id
+        context["on_event"] = self._make_callback_stream_callback(stream_id)
+        self.produce(context)
+
+        # First passive reply: register the stream id, WeCom will poll for updates.
+        return {
+            "msgtype": "stream",
+            "stream": {"id": stream_id, "finish": False, "content": ""},
+        }
+
+    def _callback_handle_stream_poll(self, data: dict) -> dict:
+        """Handle a "流式消息刷新" poll: return the latest accumulated content."""
+        stream_id = data.get("stream", {}).get("id", "")
+        with self._callback_lock:
+            state = self._callback_streams.get(stream_id)
+            if state is None:
+                # Unknown / expired stream: tell WeCom we're done to stop polling.
+                return {"msgtype": "stream", "stream": {"id": stream_id, "finish": True, "content": ""}}
+            state["last_access"] = time.time()
+            if state.get("url_sent"):
+                # Final answer already pushed via response_url; finish silently.
+                return {"msgtype": "stream", "stream": {"id": stream_id, "finish": True, "content": ""}}
+            # We never force-finish on a timer: while a task is still running the
+            # bubble should keep spinning until either the task finishes or the
+            # user cancels. If WeCom's 6min window closes before completion, the
+            # answer is delivered later via response_url instead.
+            finished = state["finished"]
+            content = state["committed"] + state["current"]
+            images = state["images"] if finished else []
+            if finished:
+                state["delivered"] = True
+                logger.debug(f"[WecomBot] stream {stream_id} delivered via poll, len={len(content)}, images={len(images)}")
+
+        stream = {"id": stream_id, "finish": finished, "content": content}
+        if images:
+            stream["msg_item"] = [
+                {"msgtype": "image", "image": {"base64": b64, "md5": md5}}
+                for (b64, md5) in images
+            ]
+        return {"msgtype": "stream", "stream": stream}
+
+    def _make_callback_stream_callback(self, stream_id: str):
+        """Build an on_event callback that accumulates agent output into stream state.
+
+        Mirrors the websocket streaming behaviour: intermediate turns (text before
+        a tool call) are committed with a '---' separator; WeCom reads the full
+        accumulated content on each poll.
+        """
+        def on_event(event: dict):
+            event_type = event.get("type")
+            edata = event.get("data", {})
+            cancelled = False
+            with self._callback_lock:
+                state = self._callback_streams.get(stream_id)
+                if not state:
+                    return
+
+                if event_type == "turn_start":
+                    state["current"] = ""
+                elif event_type == "message_update":
+                    delta = edata.get("delta", "")
+                    if delta:
+                        state["current"] += delta
+                elif event_type == "message_end":
+                    tool_calls = edata.get("tool_calls", [])
+                    if tool_calls:
+                        if state["current"].strip():
+                            state["committed"] += state["current"].strip() + "\n\n---\n\n"
+                            state["current"] = ""
+                    else:
+                        state["committed"] += state["current"]
+                        state["current"] = ""
+                elif event_type == "agent_cancelled":
+                    # Mechanism 1: a cancelled run never reaches send(), so finalize
+                    # its stream here to stop the "···" bubble immediately.
+                    if state["current"]:
+                        state["committed"] += state["current"]
+                        state["current"] = ""
+                    state["committed"] = state["committed"].rstrip()
+                    if state["committed"].endswith("---"):
+                        state["committed"] = state["committed"][:-3].rstrip()
+                    if not state["committed"].strip():
+                        state["committed"] = "🛑 已中止"
+                    state["finished"] = True
+                    state["last_access"] = time.time()
+                    cancelled = True
+
+            if cancelled:
+                # Outside the lock: response_url fallback re-acquires it.
+                self._schedule_response_url_fallback(stream_id)
+
+        return on_event
+
+    # ------------------------------------------------------------------
+    # Subscribe & heartbeat
+    # ------------------------------------------------------------------
+
+    def _send_subscribe(self):
+        self._ws_send({
+            "cmd": "aibot_subscribe",
+            "headers": {"req_id": self._gen_req_id()},
+            "body": {
+                "bot_id": self.bot_id,
+                "secret": self.bot_secret,
+            },
+        })
+
+    def _start_heartbeat(self):
+        if self._heartbeat_thread and self._heartbeat_thread.is_alive():
+            return
+
+        def heartbeat_loop():
+            while not self._stop_event.is_set() and self._connected:
+                try:
+                    self._ws_send({
+                        "cmd": "ping",
+                        "headers": {"req_id": self._gen_req_id()},
+                    })
+                except Exception as e:
+                    logger.warning(f"[WecomBot] Heartbeat send failed: {e}")
+                    break
+                self._stop_event.wait(HEARTBEAT_INTERVAL)
+
+        self._heartbeat_thread = threading.Thread(target=heartbeat_loop, daemon=True)
+        self._heartbeat_thread.start()
+
+    # ------------------------------------------------------------------
+    # Incoming message dispatch
+    # ------------------------------------------------------------------
+
+    def _send_and_wait(self, data: dict, timeout: float = 15) -> dict:
+        """Send a ws message and wait for the matching response by req_id."""
+        req_id = data.get("headers", {}).get("req_id", "")
+        event = threading.Event()
+        holder = {"data": None}
+        with self._pending_lock:
+            self._pending_responses[req_id] = (event, holder)
+        self._ws_send(data)
+        event.wait(timeout=timeout)
+        with self._pending_lock:
+            self._pending_responses.pop(req_id, None)
+        return holder["data"] or {}
+
+    def _handle_ws_message(self, data: dict):
+        cmd = data.get("cmd", "")
+        errcode = data.get("errcode")
+        req_id = data.get("headers", {}).get("req_id", "")
+
+        # Check if this is a response to a pending request
+        if req_id:
+            with self._pending_lock:
+                pending = self._pending_responses.get(req_id)
+            if pending:
+                event, holder = pending
+                holder["data"] = data
+                event.set()
+                return
+
+        # Subscribe response (only handle once before connected)
+        if errcode is not None and cmd == "":
+            if not self._connected:
+                if errcode == 0:
+                    logger.info("[WecomBot] ✅ Subscribe success")
+                    self._connected = True
+                    self._start_heartbeat()
+                    self.report_startup_success()
+                else:
+                    errmsg = data.get("errmsg", "unknown error")
+                    logger.error(f"[WecomBot] Subscribe failed: errcode={errcode}, errmsg={errmsg}")
+                    self.report_startup_error(errmsg)
+            return
+
+        if cmd == "aibot_msg_callback":
+            self._handle_msg_callback(data)
+        elif cmd == "aibot_event_callback":
+            self._handle_event_callback(data)
+        elif cmd == "":
+            if errcode and errcode != 0:
+                logger.warning(f"[WecomBot] Response error: {data}")
+
+    # ------------------------------------------------------------------
+    # Message callback
+    # ------------------------------------------------------------------
+
+    def _handle_msg_callback(self, data: dict):
+        body = data.get("body", {})
+        req_id = data.get("headers", {}).get("req_id", "")
+        msg_id = body.get("msgid", "")
+
+        if self.received_msgs.get(msg_id):
+            logger.debug(f"[WecomBot] Duplicate msg filtered: {msg_id}")
+            return
+        self.received_msgs[msg_id] = True
+
+        chattype = body.get("chattype", "single")
+        is_group = chattype == "group"
+
+        result = self._build_context(body, is_group)
+        if not result:
+            return
+        context, wecom_msg = result
+        wecom_msg.req_id = req_id
+        if req_id:
+            context["on_event"] = self._make_stream_callback(req_id)
+        self.produce(context)
+
+    def _build_context(self, body: dict, is_group: bool, default_aeskey: str = ""):
+        """Parse a wecom message body into a Context, applying file-cache logic.
+
+        Shared by both the websocket (long-connection) and callback (webhook)
+        receive paths. Returns ``(context, wecom_msg)`` when the message should be
+        handed to the agent, or ``None`` when it was consumed (cached image/file,
+        parse failure, etc.).
+        """
+        try:
+            wecom_msg = WecomBotMessage(body, is_group=is_group, default_aeskey=default_aeskey)
+        except NotImplementedError as e:
+            logger.warning(f"[WecomBot] {e}")
+            return None
+        except Exception as e:
+            logger.error(f"[WecomBot] Failed to parse message: {e}", exc_info=True)
+            return None
+
+        # File cache logic (same pattern as feishu)
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+
+        if is_group:
+            if conf().get("group_shared_session", True):
+                session_id = body.get("chatid", "")
+            else:
+                session_id = wecom_msg.from_user_id + "_" + body.get("chatid", "")
+        else:
+            session_id = wecom_msg.from_user_id
+
+        if wecom_msg.ctype == ContextType.IMAGE:
+            if hasattr(wecom_msg, "image_path") and wecom_msg.image_path:
+                file_cache.add(session_id, wecom_msg.image_path, file_type="image")
+                logger.info(f"[WecomBot] Image cached for session {session_id}")
+            return None
+
+        if wecom_msg.ctype == ContextType.FILE:
+            wecom_msg.prepare()
+            file_cache.add(session_id, wecom_msg.content, file_type="file")
+            logger.info(f"[WecomBot] File cached for session {session_id}: {wecom_msg.content}")
+            return None
+
+        if wecom_msg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                file_refs = []
+                for fi in cached_files:
+                    ftype = fi["type"]
+                    fpath = fi["path"]
+                    if ftype == "image":
+                        file_refs.append(f"[图片: {fpath}]")
+                    elif ftype == "video":
+                        file_refs.append(f"[视频: {fpath}]")
+                    else:
+                        file_refs.append(f"[文件: {fpath}]")
+                wecom_msg.content = wecom_msg.content + "\n" + "\n".join(file_refs)
+                logger.info(f"[WecomBot] Attached {len(cached_files)} cached file(s)")
+                file_cache.clear(session_id)
+
+        context = self._compose_context(
+            wecom_msg.ctype,
+            wecom_msg.content,
+            isgroup=is_group,
+            msg=wecom_msg,
+            no_need_at=True,
+        )
+        if not context:
+            return None
+        return context, wecom_msg
+
+    # ------------------------------------------------------------------
+    # Event callback
+    # ------------------------------------------------------------------
+
+    def _handle_event_callback(self, data: dict):
+        body = data.get("body", {})
+        event = body.get("event", {})
+        event_type = event.get("eventtype", "")
+
+        if event_type == "enter_chat":
+            logger.info(f"[WecomBot] User entered chat: {body.get('from', {}).get('userid')}")
+        elif event_type == "disconnected_event":
+            logger.warning("[WecomBot] Received disconnected_event, another connection took over")
+        else:
+            logger.debug(f"[WecomBot] Event: {event_type}")
+
+    # ------------------------------------------------------------------
+    # Stream callback (for agent on_event)
+    # ------------------------------------------------------------------
+
+    def _make_stream_callback(self, req_id: str):
+        """Build an on_event callback that pushes agent stream deltas to wecom via stream message.
+
+        All intermediate segments (thinking before tool calls) and the final answer
+        are accumulated into a single stream message, separated by '---'.
+        Throttles push to at most once per 100ms to avoid WebSocket congestion.
+        """
+        stream_id = uuid.uuid4().hex[:16]
+        self._stream_states[req_id] = {
+            "stream_id": stream_id,
+            "committed": "",
+            "current": "",
+            "last_push_time": 0,
+            "last_push_len": 0,
+        }
+
+        def _push_stream(state: dict, force: bool = False):
+            """Push current stream content to wecom (throttled unless forced)."""
+            now = time.time()
+            if not force and now - state["last_push_time"] < 0.1:
+                return
+            content = state["committed"] + state["current"]
+            if len(content) == state["last_push_len"]:
+                return
+            state["last_push_time"] = now
+            state["last_push_len"] = len(content)
+            try:
+                self._ws_send({
+                    "cmd": "aibot_respond_msg",
+                    "headers": {"req_id": req_id},
+                    "body": {
+                        "msgtype": "stream",
+                        "stream": {
+                            "id": state["stream_id"],
+                            "finish": False,
+                            "content": content,
+                        },
+                    },
+                })
+            except Exception as e:
+                logger.warning(f"[WecomBot] Stream push failed: {e}")
+
+        def on_event(event: dict):
+            event_type = event.get("type")
+            data = event.get("data", {})
+            state = self._stream_states.get(req_id)
+            if not state:
+                return
+
+            if event_type == "turn_start":
+                state["current"] = ""
+
+            elif event_type == "message_update":
+                delta = data.get("delta", "")
+                if delta:
+                    state["current"] += delta
+                    _push_stream(state)
+
+            elif event_type == "message_end":
+                tool_calls = data.get("tool_calls", [])
+                if tool_calls:
+                    if state["current"].strip():
+                        state["committed"] += state["current"].strip() + "\n\n---\n\n"
+                        state["current"] = ""
+                else:
+                    state["committed"] += state["current"]
+                    state["current"] = ""
+                _push_stream(state, force=True)
+
+            elif event_type == "agent_cancelled":
+                # Flush partial output and strip trailing "---" separator
+                # left over from previous turn, to avoid a dangling divider.
+                if state["current"]:
+                    state["committed"] += state["current"]
+                    state["current"] = ""
+                state["committed"] = state["committed"].rstrip()
+                if state["committed"].endswith("---"):
+                    state["committed"] = state["committed"][:-3].rstrip()
+                _push_stream(state, force=True)
+
+        return on_event
+
+    # ------------------------------------------------------------------
+    # _compose_context (same pattern as feishu)
+    # ------------------------------------------------------------------
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+
+        if cmsg.is_group:
+            if conf().get("group_shared_session", True):
+                context["session_id"] = cmsg.other_user_id
+            else:
+                context["session_id"] = f"{cmsg.from_user_id}:{cmsg.other_user_id}"
+        else:
+            context["session_id"] = cmsg.from_user_id
+
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = content.strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+    # ------------------------------------------------------------------
+    # Callback (webhook) send: write the final reply into the stream state
+    # so the next "流式消息刷新" poll returns it with finish=true.
+    # ------------------------------------------------------------------
+
+    def _callback_send(self, reply: Reply, context: Context):
+        msg = context.get("msg")
+        stream_id = getattr(msg, "stream_id", None) if msg else None
+        if not stream_id:
+            stream_id = context.get("wecom_stream_id")
+        if not stream_id:
+            logger.warning("[WecomBot] callback send without stream_id, dropping reply")
+            return
+
+        if reply.type == ReplyType.TEXT:
+            self._callback_finalize_text(stream_id, reply.content)
+        elif reply.type in (ReplyType.IMAGE_URL, ReplyType.IMAGE):
+            self._callback_finalize_image(stream_id, reply.content)
+        elif reply.type == ReplyType.FILE:
+            # Passive callback replies only support text + image (base64); files
+            # are not supported by the protocol, so append a notice to whatever
+            # text the agent already streamed (do not drop it).
+            text = getattr(reply, "text_content", "") or ""
+            note = (text + "\n\n" if text else "") + "（文件无法在企微回调模式下直接发送）"
+            self._callback_finalize_text(stream_id, note, append=True)
+        elif reply.type in (ReplyType.VIDEO, ReplyType.VIDEO_URL, ReplyType.VOICE):
+            logger.warning(f"[WecomBot] reply type {reply.type} not supported in callback mode")
+            text = getattr(reply, "text_content", "") or ""
+            note = (text + "\n\n" if text else "") + "（该消息类型无法在企微回调模式下直接发送）"
+            self._callback_finalize_text(stream_id, note, append=True)
+        else:
+            self._callback_finalize_text(stream_id, str(reply.content))
+
+    def _callback_get_or_create_state(self, stream_id: str) -> dict:
+        state = self._callback_streams.get(stream_id)
+        if state is None:
+            now = time.time()
+            state = {
+                "committed": "",
+                "current": "",
+                "finished": False,
+                "images": [],
+                "image_urls": [],
+                "image_pending": False,
+                "last_access": now,
+                "created_at": now,
+                "response_url": "",
+                "delivered": False,
+                "url_sent": False,
+            }
+            self._callback_streams[stream_id] = state
+        return state
+
+    def _callback_finalize_text(self, stream_id: str, content: str, append: bool = False):
+        with self._callback_lock:
+            state = self._callback_get_or_create_state(stream_id)
+            accumulated = (state["committed"] + state["current"]).strip()
+            if append and accumulated:
+                state["committed"] = (accumulated + "\n\n" + (content or "")).strip()
+            else:
+                state["committed"] = accumulated if accumulated else (content or "")
+            state["current"] = ""
+            state["last_access"] = time.time()
+        # Don't finish synchronously: chat_channel splits an image-with-caption
+        # reply into a TEXT send followed (0.3s later) by the IMAGE send. If the
+        # text finished the stream immediately, WeCom would close it before the
+        # image arrives. Defer the finish so a trailing image can merge in.
+        self._schedule_text_finish(stream_id)
+
+    def _schedule_text_finish(self, stream_id: str, delay: float = 1.2):
+        def _run():
+            time.sleep(delay)
+            with self._callback_lock:
+                state = self._callback_streams.get(stream_id)
+                if not state or state["finished"] or state.get("image_pending"):
+                    return  # already finished, or an image reply is on its way
+                state["finished"] = True
+                state["last_access"] = time.time()
+            self._schedule_response_url_fallback(stream_id)
+
+        threading.Thread(target=_run, daemon=True, name=f"wecom-textfin-{stream_id}").start()
+
+    def _callback_finalize_image(self, stream_id: str, img_path_or_url: str):
+        # Mark the image as pending up front (before the slow load/compress) so a
+        # preceding text finalize won't close the stream while we work.
+        with self._callback_lock:
+            self._callback_get_or_create_state(stream_id)["image_pending"] = True
+        b64md5 = self._load_image_base64(img_path_or_url)
+        with self._callback_lock:
+            state = self._callback_get_or_create_state(stream_id)
+            accumulated = (state["committed"] + state["current"]).strip()
+            state["current"] = ""
+            if b64md5:
+                state["images"].append(b64md5)
+                state["committed"] = accumulated
+                # Remember the public url (if any) so the response_url fallback
+                # can embed it as markdown when the poll window has closed.
+                if img_path_or_url.startswith(("http://", "https://")):
+                    state["image_urls"].append(img_path_or_url)
+            else:
+                state["committed"] = accumulated or "[图片发送失败]"
+            state["finished"] = True
+            state["image_pending"] = False
+            state["last_access"] = time.time()
+        self._schedule_response_url_fallback(stream_id)
+
+    # ------------------------------------------------------------------
+    # Active reply fallback (response_url): rescue replies that finish after
+    # WeCom stops polling (the passive stream window is ~6 min from the user's
+    # message). A short delay lets an in-flight poll deliver first; only if no
+    # poll picks up the finished answer do we push it actively via response_url.
+    # ------------------------------------------------------------------
+
+    def _schedule_response_url_fallback(self, stream_id: str, delay: float = 3.0):
+        def _run():
+            time.sleep(delay)
+            with self._callback_lock:
+                state = self._callback_streams.get(stream_id)
+                if not state:
+                    return
+                if state.get("delivered") or state.get("url_sent"):
+                    return  # a poll already delivered (or fallback already ran)
+                response_url = state.get("response_url") or ""
+                if not response_url:
+                    logger.warning(
+                        f"[WecomBot] stream {stream_id} finished after poll window but no response_url; reply dropped"
+                    )
+                    return
+                content = (state["committed"] + state["current"]).strip()
+                image_urls = list(state.get("image_urls") or [])
+                has_images = bool(state.get("images"))
+                state["url_sent"] = True
+
+            self._send_via_response_url(stream_id, response_url, content, image_urls, has_images)
+
+        threading.Thread(target=_run, daemon=True, name=f"wecom-respurl-{stream_id}").start()
+
+    def _send_via_response_url(self, stream_id, response_url, content, image_urls, has_images):
+        """Push a one-shot active markdown reply to response_url (valid 1h, single use)."""
+        md = content or ""
+        if image_urls:
+            md += ("\n\n" if md else "") + "\n".join(f"![]({u})" for u in image_urls)
+        elif has_images:
+            md += ("\n\n" if md else "") + "（图片已生成，但因处理超时无法通过回调发送）"
+        if not md:
+            md = "（处理完成）"
+        payload = {"msgtype": "markdown", "markdown": {"content": md}}
+        try:
+            resp = requests.post(response_url, json=payload, timeout=15)
+            logger.info(
+                f"[WecomBot] response_url active reply sent for {stream_id}: "
+                f"status={resp.status_code}, body={resp.text[:200]}"
+            )
+        except Exception as e:
+            logger.error(f"[WecomBot] response_url active reply failed for {stream_id}: {e}")
+
+    def _load_image_base64(self, img_path_or_url: str):
+        """Load a local/remote image, ensure JPG/PNG within 10MB, return (base64, md5)."""
+        local_path = img_path_or_url
+        if local_path.startswith("file://"):
+            local_path = local_path[7:]
+
+        # Temp files we create here (downloads/conversions/compressions) must be
+        # cleaned up afterwards; the caller's original local file must not be.
+        temp_files = []
+        try:
+            if local_path.startswith(("http://", "https://")):
+                try:
+                    resp = requests.get(local_path, timeout=30)
+                    resp.raise_for_status()
+                    tmp_path = f"/tmp/wecom_cb_img_{uuid.uuid4().hex[:8]}"
+                    with open(tmp_path, "wb") as f:
+                        f.write(resp.content)
+                    temp_files.append(tmp_path)
+                    local_path = tmp_path
+                except Exception as e:
+                    logger.error(f"[WecomBot] Failed to download image for callback reply: {e}")
+                    return None
+
+            if not os.path.exists(local_path):
+                logger.error(f"[WecomBot] Image file not found: {local_path}")
+                return None
+
+            formatted = self._ensure_image_format(local_path)
+            if not formatted:
+                return None
+            if formatted != local_path:
+                temp_files.append(formatted)
+            local_path = formatted
+
+            # Unlike the long-connection path (which uploads and sends only a tiny
+            # media_id), the callback reply embeds the whole image as base64 inside
+            # an AES-encrypted body that is returned on EVERY poll. Empirically a
+            # ~1.5MB image (base64 ~2.1MB, encrypted ~2.8MB) makes WeCom reject the
+            # finish packet and poll forever, so cap well below that.
+            callback_max_size = 512 * 1024
+            if os.path.getsize(local_path) > callback_max_size:
+                compressed = self._compress_image(local_path, callback_max_size)
+                if compressed:
+                    temp_files.append(compressed)
+                    local_path = compressed
+                else:
+                    logger.warning("[WecomBot] callback image compress failed; sending original (may be rejected)")
+
+            try:
+                with open(local_path, "rb") as f:
+                    raw = f.read()
+                return base64.b64encode(raw).decode("utf-8"), hashlib.md5(raw).hexdigest()
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to read image for callback reply: {e}")
+                return None
+        finally:
+            for path in temp_files:
+                try:
+                    os.remove(path)
+                except OSError:
+                    pass
+
+    # ------------------------------------------------------------------
+    # Send reply
+    # ------------------------------------------------------------------
+
+    def send(self, reply: Reply, context: Context):
+        if self.mode == "webhook":
+            self._callback_send(reply, context)
+            return
+
+        msg = context.get("msg")
+        is_group = context.get("isgroup", False)
+        receiver = context.get("receiver", "")
+
+        # Determine req_id for responding or use send_msg for scheduled push
+        req_id = getattr(msg, "req_id", None) if msg else None
+
+        if reply.type == ReplyType.TEXT:
+            self._send_text(reply.content, receiver, is_group, req_id)
+        elif reply.type in (ReplyType.IMAGE_URL, ReplyType.IMAGE):
+            self._send_image(reply.content, receiver, is_group, req_id)
+        elif reply.type == ReplyType.FILE:
+            if hasattr(reply, "text_content") and reply.text_content:
+                self._send_text(reply.text_content, receiver, is_group, req_id)
+                time.sleep(0.3)
+            self._send_file(reply.content, receiver, is_group, req_id)
+        elif reply.type == ReplyType.VIDEO or reply.type == ReplyType.VIDEO_URL:
+            self._send_file(reply.content, receiver, is_group, req_id, media_type="video")
+        elif reply.type == ReplyType.VOICE:
+            self._send_voice(reply.content, receiver, is_group, req_id)
+        else:
+            logger.warning(f"[WecomBot] Unsupported reply type: {reply.type}, falling back to text")
+            self._send_text(str(reply.content), receiver, is_group, req_id)
+
+    # ------------------------------------------------------------------
+    # Respond message (via websocket)
+    # ------------------------------------------------------------------
+
+    def _send_text(self, content: str, receiver: str, is_group: bool, req_id: str = None):
+        """Send text/markdown reply. Reuses stream state if available (streaming mode)."""
+        if req_id:
+            state = self._stream_states.pop(req_id, None)
+            if state:
+                final_content = state["committed"] if state["committed"] else content
+                stream_id = state["stream_id"]
+            else:
+                final_content = content
+                stream_id = uuid.uuid4().hex[:16]
+
+            # Brief pause so the server finishes processing the last intermediate chunk
+            # before receiving the finish packet
+            time.sleep(0.15)
+
+            self._ws_send({
+                "cmd": "aibot_respond_msg",
+                "headers": {"req_id": req_id},
+                "body": {
+                    "msgtype": "stream",
+                    "stream": {
+                        "id": stream_id,
+                        "finish": True,
+                        "content": final_content,
+                    },
+                },
+            })
+        else:
+            self._active_send_markdown(content, receiver, is_group)
+
+    def _send_image(self, img_path_or_url: str, receiver: str, is_group: bool, req_id: str = None):
+        """Send image reply. Converts to JPG/PNG and compresses if >2MB."""
+        local_path = img_path_or_url
+        if local_path.startswith("file://"):
+            local_path = local_path[7:]
+
+        if local_path.startswith(("http://", "https://")):
+            try:
+                resp = requests.get(local_path, timeout=30)
+                resp.raise_for_status()
+                ct = resp.headers.get("Content-Type", "")
+                if "jpeg" in ct or "jpg" in ct:
+                    ext = ".jpg"
+                elif "webp" in ct:
+                    ext = ".webp"
+                elif "gif" in ct:
+                    ext = ".gif"
+                else:
+                    ext = ".png"
+                tmp_path = f"/tmp/wecom_img_{uuid.uuid4().hex[:8]}{ext}"
+                with open(tmp_path, "wb") as f:
+                    f.write(resp.content)
+                logger.info(f"[WecomBot] Image downloaded: size={len(resp.content)}, "
+                            f"content-type={ct}, path={tmp_path}")
+                local_path = tmp_path
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to download image for sending: {e}")
+                self._send_text("[Image send failed]", receiver, is_group, req_id)
+                return
+
+        if not os.path.exists(local_path):
+            logger.error(f"[WecomBot] Image file not found: {local_path}")
+            return
+
+        max_image_size = 2 * 1024 * 1024  # 2MB limit for image upload
+        local_path = self._ensure_image_format(local_path)
+        if not local_path:
+            self._send_text("[Image format conversion failed]", receiver, is_group, req_id)
+            return
+
+        if os.path.getsize(local_path) > max_image_size:
+            local_path = self._compress_image(local_path, max_image_size)
+            if not local_path:
+                self._send_text("[Image too large]", receiver, is_group, req_id)
+                return
+
+        file_size = os.path.getsize(local_path)
+        logger.info(f"[WecomBot] Uploading image: path={local_path}, size={file_size} bytes")
+        media_id = self._upload_media(local_path, "image")
+        if not media_id:
+            logger.error("[WecomBot] Failed to upload image")
+            self._send_text("[Image upload failed]", receiver, is_group, req_id)
+            return
+
+        if req_id:
+            self._ws_send({
+                "cmd": "aibot_respond_msg",
+                "headers": {"req_id": req_id},
+                "body": {
+                    "msgtype": "image",
+                    "image": {"media_id": media_id},
+                },
+            })
+        else:
+            self._ws_send({
+                "cmd": "aibot_send_msg",
+                "headers": {"req_id": self._gen_req_id()},
+                "body": {
+                    "chatid": receiver,
+                    "chat_type": 2 if is_group else 1,
+                    "msgtype": "image",
+                    "image": {"media_id": media_id},
+                },
+            })
+
+    @staticmethod
+    def _ensure_image_format(file_path: str) -> str:
+        """Ensure image is JPG or PNG (the only formats wecom supports). Convert if needed."""
+        try:
+            from PIL import Image
+            img = Image.open(file_path)
+            fmt = (img.format or "").upper()
+            if fmt in ("JPEG", "PNG"):
+                # Already a supported format, but make sure the filename extension matches
+                ext = os.path.splitext(file_path)[1].lower()
+                if fmt == "JPEG" and ext in (".jpg", ".jpeg"):
+                    return file_path
+                if fmt == "PNG" and ext == ".png":
+                    return file_path
+                # Extension doesn't match — rename/copy with correct extension
+                correct_ext = ".jpg" if fmt == "JPEG" else ".png"
+                out_path = f"/tmp/wecom_fmt_{uuid.uuid4().hex[:8]}{correct_ext}"
+                img.save(out_path, fmt)
+                logger.info(f"[WecomBot] Image renamed: {file_path} -> {out_path} ({fmt})")
+                return out_path
+
+            # Unsupported format (WebP, GIF, BMP, etc.) — convert to PNG
+            if img.mode == "RGBA":
+                out_path = f"/tmp/wecom_fmt_{uuid.uuid4().hex[:8]}.png"
+                img.save(out_path, "PNG")
+            else:
+                out_path = f"/tmp/wecom_fmt_{uuid.uuid4().hex[:8]}.jpg"
+                img.convert("RGB").save(out_path, "JPEG", quality=90)
+            logger.info(f"[WecomBot] Image converted from {fmt} -> {out_path}")
+            return out_path
+        except Exception as e:
+            logger.error(f"[WecomBot] Image format check failed: {e}")
+            return file_path
+
+    @staticmethod
+    def _compress_image(file_path: str, max_bytes: int) -> str:
+        """Compress image to fit within max_bytes. Returns new path or empty string."""
+        try:
+            from PIL import Image
+            img = Image.open(file_path)
+            if img.mode == "RGBA":
+                img = img.convert("RGB")
+
+            out_path = f"/tmp/wecom_compressed_{uuid.uuid4().hex[:8]}.jpg"
+            quality = 85
+            while quality >= 30:
+                img.save(out_path, "JPEG", quality=quality, optimize=True)
+                if os.path.getsize(out_path) <= max_bytes:
+                    logger.info(f"[WecomBot] Image compressed: quality={quality}, "
+                                f"size={os.path.getsize(out_path)} bytes")
+                    return out_path
+                quality -= 10
+
+            # Still too large — resize
+            ratio = (max_bytes / os.path.getsize(out_path)) ** 0.5
+            new_size = (int(img.width * ratio), int(img.height * ratio))
+            img = img.resize(new_size, Image.LANCZOS)
+            img.save(out_path, "JPEG", quality=70, optimize=True)
+            if os.path.getsize(out_path) <= max_bytes:
+                logger.info(f"[WecomBot] Image compressed with resize: {new_size}, "
+                            f"size={os.path.getsize(out_path)} bytes")
+                return out_path
+
+            logger.error(f"[WecomBot] Cannot compress image below {max_bytes} bytes")
+            return ""
+        except Exception as e:
+            logger.error(f"[WecomBot] Image compression failed: {e}")
+            return ""
+
+    def _send_file(self, file_path: str, receiver: str, is_group: bool,
+                   req_id: str = None, media_type: str = "file"):
+        """Send file/video reply by uploading media first."""
+        local_path = file_path
+        if local_path.startswith("file://"):
+            local_path = local_path[7:]
+
+        if local_path.startswith(("http://", "https://")):
+            try:
+                resp = requests.get(local_path, timeout=60)
+                resp.raise_for_status()
+                ext = os.path.splitext(local_path)[1] or ".bin"
+                tmp_path = f"/tmp/wecom_file_{uuid.uuid4().hex[:8]}{ext}"
+                with open(tmp_path, "wb") as f:
+                    f.write(resp.content)
+                local_path = tmp_path
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to download file for sending: {e}")
+                return
+
+        if not os.path.exists(local_path):
+            logger.error(f"[WecomBot] File not found: {local_path}")
+            return
+
+        media_id = self._upload_media(local_path, media_type)
+        if not media_id:
+            logger.error(f"[WecomBot] Failed to upload {media_type}")
+            return
+
+        if req_id:
+            self._ws_send({
+                "cmd": "aibot_respond_msg",
+                "headers": {"req_id": req_id},
+                "body": {
+                    "msgtype": media_type,
+                    media_type: {"media_id": media_id},
+                },
+            })
+        else:
+            self._ws_send({
+                "cmd": "aibot_send_msg",
+                "headers": {"req_id": self._gen_req_id()},
+                "body": {
+                    "chatid": receiver,
+                    "chat_type": 2 if is_group else 1,
+                    "msgtype": media_type,
+                    media_type: {"media_id": media_id},
+                },
+            })
+
+    def _send_voice(self, voice_path: str, receiver: str, is_group: bool, req_id: str = None):
+        """Send native voice reply. WeCom voice media must be amr."""
+        local_path = voice_path
+        if local_path.startswith("file://"):
+            local_path = local_path[7:]
+
+        if local_path.startswith(("http://", "https://")):
+            try:
+                resp = requests.get(local_path, timeout=60)
+                resp.raise_for_status()
+                ext = os.path.splitext(local_path)[1] or ".mp3"
+                tmp_path = f"/tmp/wecom_voice_{uuid.uuid4().hex[:8]}{ext}"
+                with open(tmp_path, "wb") as f:
+                    f.write(resp.content)
+                local_path = tmp_path
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to download voice for sending: {e}")
+                return
+
+        if not os.path.exists(local_path):
+            logger.error(f"[WecomBot] Voice file not found: {local_path}")
+            return
+
+        amr_path = local_path
+        if not local_path.lower().endswith(".amr"):
+            try:
+                from voice.audio_convert import any_to_amr
+                amr_path = os.path.splitext(local_path)[0] + ".amr"
+                any_to_amr(local_path, amr_path)
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to convert voice to amr: {e}")
+                return
+
+        media_id = self._upload_media(amr_path, "voice")
+        if not media_id:
+            logger.error("[WecomBot] Failed to upload voice media")
+            return
+
+        if req_id:
+            self._ws_send({
+                "cmd": "aibot_respond_msg",
+                "headers": {"req_id": req_id},
+                "body": {
+                    "msgtype": "voice",
+                    "voice": {"media_id": media_id},
+                },
+            })
+        else:
+            self._ws_send({
+                "cmd": "aibot_send_msg",
+                "headers": {"req_id": self._gen_req_id()},
+                "body": {
+                    "chatid": receiver,
+                    "chat_type": 2 if is_group else 1,
+                    "msgtype": "voice",
+                    "voice": {"media_id": media_id},
+                },
+            })
+
+    def _active_send_markdown(self, content: str, receiver: str, is_group: bool):
+        """Proactively send markdown message (for scheduled tasks, no req_id)."""
+        self._ws_send({
+            "cmd": "aibot_send_msg",
+            "headers": {"req_id": self._gen_req_id()},
+            "body": {
+                "chatid": receiver,
+                "chat_type": 2 if is_group else 1,
+                "msgtype": "markdown",
+                "markdown": {"content": content},
+            },
+        })
+
+    # ------------------------------------------------------------------
+    # Media upload (chunked)
+    # ------------------------------------------------------------------
+
+    def _upload_media(self, file_path: str, media_type: str = "file") -> str:
+        """
+        Upload a local file to wecom bot via chunked upload protocol.
+        Returns media_id on success, empty string on failure.
+        """
+        if not os.path.exists(file_path):
+            logger.error(f"[WecomBot] Upload file not found: {file_path}")
+            return ""
+
+        file_size = os.path.getsize(file_path)
+        if file_size < 5:
+            logger.error(f"[WecomBot] File too small: {file_size} bytes")
+            return ""
+
+        filename = os.path.basename(file_path)
+        total_chunks = math.ceil(file_size / MEDIA_CHUNK_SIZE)
+        if total_chunks > 100:
+            logger.error(f"[WecomBot] Too many chunks: {total_chunks} > 100")
+            return ""
+
+        file_md5 = hashlib.md5()
+        with open(file_path, "rb") as f:
+            for block in iter(lambda: f.read(8192), b""):
+                file_md5.update(block)
+        md5_hex = file_md5.hexdigest()
+
+        # 1. Init upload
+        init_resp = self._send_and_wait({
+            "cmd": "aibot_upload_media_init",
+            "headers": {"req_id": self._gen_req_id()},
+            "body": {
+                "type": media_type,
+                "filename": filename,
+                "total_size": file_size,
+                "total_chunks": total_chunks,
+                "md5": md5_hex,
+            },
+        }, timeout=15)
+
+        if init_resp.get("errcode") != 0:
+            logger.error(f"[WecomBot] Upload init failed: {init_resp}")
+            return ""
+
+        upload_id = init_resp.get("body", {}).get("upload_id")
+        if not upload_id:
+            logger.error("[WecomBot] Failed to get upload_id")
+            return ""
+
+        # 2. Upload chunks
+        with open(file_path, "rb") as f:
+            for idx in range(total_chunks):
+                chunk = f.read(MEDIA_CHUNK_SIZE)
+                b64_data = base64.b64encode(chunk).decode("utf-8")
+                chunk_resp = self._send_and_wait({
+                    "cmd": "aibot_upload_media_chunk",
+                    "headers": {"req_id": self._gen_req_id()},
+                    "body": {
+                        "upload_id": upload_id,
+                        "chunk_index": idx,
+                        "base64_data": b64_data,
+                    },
+                }, timeout=30)
+                if chunk_resp.get("errcode") != 0:
+                    logger.error(f"[WecomBot] Chunk {idx} upload failed: {chunk_resp}")
+                    return ""
+
+        # 3. Finish upload
+        finish_resp = self._send_and_wait({
+            "cmd": "aibot_upload_media_finish",
+            "headers": {"req_id": self._gen_req_id()},
+            "body": {"upload_id": upload_id},
+        }, timeout=30)
+
+        if finish_resp.get("errcode") != 0:
+            logger.error(f"[WecomBot] Upload finish failed: {finish_resp}")
+            return ""
+
+        media_id = finish_resp.get("body", {}).get("media_id", "")
+        if media_id:
+            logger.info(f"[WecomBot] Media uploaded: media_id={media_id}")
+        else:
+            logger.error("[WecomBot] Failed to get media_id from finish response")
+        return media_id
+
+
+class WecomBotCallbackController:
+    """HTTP controller for wecom bot callback (webhook) mode.
+
+    - GET  : URL verification (echo the decrypted echostr).
+    - POST : encrypted message / stream-refresh / event callbacks; returns an
+             encrypted passive reply (or "success" for an empty reply).
+    """
+
+    @staticmethod
+    def _channel() -> "WecomBotChannel":
+        return WecomBotChannel()
+
+    def GET(self):
+        channel = self._channel()
+        params = web.input(msg_signature="", timestamp="", nonce="", echostr="")
+        if not channel._crypt:
+            return "wecom bot callback not ready"
+        ret, echo = channel._crypt.verify_url(
+            params.msg_signature, params.timestamp, params.nonce, params.echostr
+        )
+        if ret != 0:
+            logger.error(f"[WecomBot] URL verify failed: ret={ret}")
+            return "verify fail"
+        if isinstance(echo, bytes):
+            echo = echo.decode("utf-8")
+        return echo
+
+    def POST(self):
+        channel = self._channel()
+        if not channel._crypt:
+            return "success"
+
+        params = web.input(msg_signature="", timestamp="", nonce="")
+        body = web.data()
+        ret, plain = channel._crypt.decrypt_msg(
+            body, params.msg_signature, params.timestamp, params.nonce
+        )
+        if ret != 0:
+            logger.error(f"[WecomBot] callback decrypt failed: ret={ret}")
+            return "success"
+
+        try:
+            data = json.loads(plain)
+        except Exception as e:
+            logger.error(f"[WecomBot] callback json parse failed: {e}")
+            return "success"
+
+        msgtype = data.get("msgtype", "")
+        # Stream polls arrive ~1/s; logging each is noisy, so only log non-poll
+        # callbacks here (poll completion is logged in the stream-poll handler).
+        if msgtype != "stream":
+            logger.debug(f"[WecomBot] callback received msgtype={msgtype}")
+
+        try:
+            if msgtype == "stream":
+                reply = channel._callback_handle_stream_poll(data)
+            elif msgtype == "event":
+                event_type = data.get("event", {}).get("eventtype", "")
+                logger.info(f"[WecomBot] callback event: {event_type}")
+                reply = None
+            elif msgtype in ("text", "image", "voice", "file", "video", "mixed"):
+                reply = channel._callback_handle_message(data)
+            else:
+                logger.warning(f"[WecomBot] unsupported callback msgtype: {msgtype}")
+                reply = None
+        except Exception as e:
+            logger.error(f"[WecomBot] callback handling error: {e}", exc_info=True)
+            reply = None
+
+        if not reply:
+            # Empty reply package is acceptable.
+            return "success"
+
+        plain_reply = json.dumps(reply, ensure_ascii=False)
+        ret, enc = channel._crypt.encrypt_msg(plain_reply, params.nonce, params.timestamp)
+        if ret != 0:
+            logger.error(f"[WecomBot] callback encrypt failed: ret={ret}")
+            return "success"
+        web.header("Content-Type", "application/json; charset=utf-8")
+        return json.dumps(enc, ensure_ascii=False)
diff --git a/channel/wecom_bot/wecom_bot_crypt.py b/channel/wecom_bot/wecom_bot_crypt.py
new file mode 100644
index 0000000..262ca3f
--- /dev/null
+++ b/channel/wecom_bot/wecom_bot_crypt.py
@@ -0,0 +1,203 @@
+"""
+WeCom (企业微信) smart-bot callback message encryption/decryption.
+
+Adapted from the official `WXBizJsonMsgCrypt` sample (JSON variant) used by the
+AI bot callback (webhook) mode. The bot's receive-message callback delivers
+AES-256-CBC encrypted JSON payloads, and passive replies must be encrypted the
+same way before being returned in the HTTP response.
+
+For an enterprise-internal smart bot, ``receive_id`` is always an empty string.
+"""
+
+import base64
+import hashlib
+import random
+import socket
+import struct
+import time
+
+from Crypto.Cipher import AES
+
+from common.log import logger
+
+# Error codes (mirrors the official ierror.py)
+WXBizMsgCrypt_OK = 0
+WXBizMsgCrypt_ValidateSignature_Error = -40001
+WXBizMsgCrypt_ParseJson_Error = -40002
+WXBizMsgCrypt_ComputeSignature_Error = -40003
+WXBizMsgCrypt_IllegalAesKey = -40004
+WXBizMsgCrypt_ValidateCorpid_Error = -40005
+WXBizMsgCrypt_EncryptAES_Error = -40006
+WXBizMsgCrypt_DecryptAES_Error = -40007
+WXBizMsgCrypt_IllegalBuffer = -40008
+WXBizMsgCrypt_EncodeBase64_Error = -40009
+WXBizMsgCrypt_DecodeBase64_Error = -40010
+WXBizMsgCrypt_GenReturnJson_Error = -40011
+
+
+class FormatException(Exception):
+    pass
+
+
+def _gen_sha1(token, timestamp, nonce, encrypt):
+    """Compute the WeCom message signature with SHA1 over the sorted parts."""
+    try:
+        if isinstance(encrypt, bytes):
+            encrypt = encrypt.decode("utf-8")
+        sortlist = [str(token), str(timestamp), str(nonce), str(encrypt)]
+        sortlist.sort()
+        sha = hashlib.sha1()
+        sha.update("".join(sortlist).encode("utf-8"))
+        return WXBizMsgCrypt_OK, sha.hexdigest()
+    except Exception as e:
+        logger.error(f"[WecomBot] compute signature error: {e}")
+        return WXBizMsgCrypt_ComputeSignature_Error, None
+
+
+class _PKCS7Encoder:
+    """PKCS#7 padding with a 32-byte block size (AES-256)."""
+
+    block_size = 32
+
+    def encode(self, text: bytes) -> bytes:
+        text_length = len(text)
+        amount_to_pad = self.block_size - (text_length % self.block_size)
+        if amount_to_pad == 0:
+            amount_to_pad = self.block_size
+        pad = bytes([amount_to_pad])
+        return text + pad * amount_to_pad
+
+    def decode(self, decrypted: bytes) -> bytes:
+        pad = decrypted[-1]
+        if pad < 1 or pad > 32:
+            pad = 0
+        return decrypted[:-pad] if pad else decrypted
+
+
+class _Prpcrypt:
+    """AES-256-CBC encrypt/decrypt for WeCom callback messages."""
+
+    def __init__(self, key: bytes):
+        self.key = key
+        self.mode = AES.MODE_CBC
+
+    def encrypt(self, text: str, receive_id: str):
+        text_bytes = text.encode()
+        # 16-byte random prefix + network-order length + body + receive_id
+        text_bytes = (
+            self._get_random_str()
+            + struct.pack("I", socket.htonl(len(text_bytes)))
+            + text_bytes
+            + receive_id.encode()
+        )
+        text_bytes = _PKCS7Encoder().encode(text_bytes)
+        try:
+            cryptor = AES.new(self.key, self.mode, self.key[:16])
+            ciphertext = cryptor.encrypt(text_bytes)
+            return WXBizMsgCrypt_OK, base64.b64encode(ciphertext)
+        except Exception as e:
+            logger.error(f"[WecomBot] AES encrypt error: {e}")
+            return WXBizMsgCrypt_EncryptAES_Error, None
+
+    def decrypt(self, text, receive_id: str):
+        try:
+            cryptor = AES.new(self.key, self.mode, self.key[:16])
+            plain_text = cryptor.decrypt(base64.b64decode(text))
+        except Exception as e:
+            logger.error(f"[WecomBot] AES decrypt error: {e}")
+            return WXBizMsgCrypt_DecryptAES_Error, None
+        try:
+            pad = plain_text[-1]
+            content = plain_text[16:-pad]
+            json_len = socket.ntohl(struct.unpack("I", content[:4])[0])
+            json_content = content[4 : json_len + 4].decode("utf-8")
+            from_receive_id = content[json_len + 4 :].decode("utf-8")
+        except Exception as e:
+            logger.error(f"[WecomBot] illegal buffer when decrypting: {e}")
+            return WXBizMsgCrypt_IllegalBuffer, None
+        if from_receive_id != receive_id:
+            logger.error(
+                f"[WecomBot] receive_id not match: expect={receive_id}, got={from_receive_id}"
+            )
+            return WXBizMsgCrypt_ValidateCorpid_Error, None
+        return WXBizMsgCrypt_OK, json_content
+
+    @staticmethod
+    def _get_random_str() -> bytes:
+        return str(random.randint(1000000000000000, 9999999999999999)).encode()
+
+
+class WecomBotCrypt:
+    """High-level helper for verifying URLs and (de)crypting callback messages."""
+
+    def __init__(self, token: str, encoding_aes_key: str, receive_id: str = ""):
+        try:
+            self.key = base64.b64decode(encoding_aes_key + "=")
+            assert len(self.key) == 32
+        except Exception:
+            raise FormatException("[WecomBot] invalid EncodingAESKey")
+        self.token = token
+        self.receive_id = receive_id
+
+    def verify_url(self, msg_signature, timestamp, nonce, echostr):
+        ret, signature = _gen_sha1(self.token, timestamp, nonce, echostr)
+        if ret != 0:
+            return ret, None
+        if signature != msg_signature:
+            return WXBizMsgCrypt_ValidateSignature_Error, None
+        pc = _Prpcrypt(self.key)
+        return pc.decrypt(echostr, self.receive_id)
+
+    def encrypt_msg(self, reply_msg: str, nonce: str, timestamp: str = None):
+        """Encrypt a passive-reply JSON string and return the full response JSON.
+
+        Returns (ret, response_dict). On success ret==0 and response_dict is a
+        dict with encrypt/msgsignature/timestamp/nonce fields.
+        """
+        pc = _Prpcrypt(self.key)
+        ret, encrypt = pc.encrypt(reply_msg, self.receive_id)
+        if ret != 0:
+            return ret, None
+        encrypt = encrypt.decode("utf-8")
+        if timestamp is None:
+            timestamp = str(int(time.time()))
+        ret, signature = _gen_sha1(self.token, timestamp, nonce, encrypt)
+        if ret != 0:
+            return ret, None
+        return WXBizMsgCrypt_OK, {
+            "encrypt": encrypt,
+            "msgsignature": signature,
+            "timestamp": timestamp,
+            "nonce": nonce,
+        }
+
+    def decrypt_msg(self, post_data, msg_signature, timestamp, nonce):
+        """Verify signature and decrypt the encrypted callback payload.
+
+        ``post_data`` may be the raw request body (bytes/str) containing
+        ``{"encrypt": "..."}`` or the already-extracted encrypt string.
+        Returns (ret, plaintext_json_str).
+        """
+        import json
+
+        encrypt = None
+        if isinstance(post_data, (bytes, bytearray)):
+            post_data = post_data.decode("utf-8")
+        if isinstance(post_data, str):
+            try:
+                encrypt = json.loads(post_data).get("encrypt")
+            except Exception:
+                encrypt = post_data
+        elif isinstance(post_data, dict):
+            encrypt = post_data.get("encrypt")
+        if not encrypt:
+            return WXBizMsgCrypt_ParseJson_Error, None
+
+        ret, signature = _gen_sha1(self.token, timestamp, nonce, encrypt)
+        if ret != 0:
+            return ret, None
+        if signature != msg_signature:
+            logger.error("[WecomBot] callback signature not match")
+            return WXBizMsgCrypt_ValidateSignature_Error, None
+        pc = _Prpcrypt(self.key)
+        return pc.decrypt(encrypt, self.receive_id)
diff --git a/channel/wecom_bot/wecom_bot_message.py b/channel/wecom_bot/wecom_bot_message.py
new file mode 100644
index 0000000..f021a24
--- /dev/null
+++ b/channel/wecom_bot/wecom_bot_message.py
@@ -0,0 +1,219 @@
+import os
+import re
+import base64
+import requests
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from common.utils import expand_path
+from config import conf
+from Crypto.Cipher import AES
+
+
+MAGIC_SIGNATURES = [
+    (b"%PDF", ".pdf"),
+    (b"\x89PNG\r\n\x1a\n", ".png"),
+    (b"\xff\xd8\xff", ".jpg"),
+    (b"GIF87a", ".gif"),
+    (b"GIF89a", ".gif"),
+    (b"RIFF", ".webp"),  # RIFF....WEBP, further checked below
+    (b"PK\x03\x04", ".zip"),  # zip / docx / xlsx / pptx
+    (b"\x1f\x8b", ".gz"),
+    (b"Rar!\x1a\x07", ".rar"),
+    (b"7z\xbc\xaf\x27\x1c", ".7z"),
+    (b"\x00\x00\x00", ".mp4"),  # ftyp box, further checked below
+    (b"#!AMR", ".amr"),
+]
+
+OFFICE_ZIP_MARKERS = {
+    b"word/": ".docx",
+    b"xl/": ".xlsx",
+    b"ppt/": ".pptx",
+}
+
+
+def _guess_ext_from_bytes(data: bytes) -> str:
+    """Guess file extension from file content magic bytes."""
+    if not data or len(data) < 8:
+        return ""
+    for sig, ext in MAGIC_SIGNATURES:
+        if data[:len(sig)] == sig:
+            if ext == ".webp" and data[8:12] != b"WEBP":
+                continue
+            if ext == ".mp4":
+                if b"ftyp" not in data[4:12]:
+                    continue
+            if ext == ".zip":
+                for marker, office_ext in OFFICE_ZIP_MARKERS.items():
+                    if marker in data[:2000]:
+                        return office_ext
+                return ".zip"
+            return ext
+    return ""
+
+
+def _decrypt_media(url: str, aeskey: str) -> bytes:
+    """
+    Download and decrypt AES-256-CBC encrypted media from wecom bot.
+    Returns decrypted bytes.
+    """
+    resp = requests.get(url, timeout=30)
+    resp.raise_for_status()
+    encrypted = resp.content
+
+    key = base64.b64decode(aeskey + "=" * (-len(aeskey) % 4))
+    if len(key) != 32:
+        raise ValueError(f"Invalid AES key length: {len(key)}, expected 32")
+
+    iv = key[:16]
+    cipher = AES.new(key, AES.MODE_CBC, iv)
+    decrypted = cipher.decrypt(encrypted)
+
+    pad_len = decrypted[-1]
+    if pad_len > 32:
+        raise ValueError(f"Invalid PKCS7 padding length: {pad_len}")
+    return decrypted[:-pad_len]
+
+
+def _get_tmp_dir() -> str:
+    """Return the workspace tmp directory (absolute path), creating it if needed."""
+    ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    tmp_dir = os.path.join(ws_root, "tmp")
+    os.makedirs(tmp_dir, exist_ok=True)
+    return tmp_dir
+
+
+class WecomBotMessage(ChatMessage):
+    """Message wrapper for wecom bot (websocket long-connection mode)."""
+
+    def __init__(self, msg_body: dict, is_group: bool = False, default_aeskey: str = ""):
+        super().__init__(msg_body)
+        self.msg_id = msg_body.get("msgid")
+        self.create_time = msg_body.get("create_time")
+        self.is_group = is_group
+        # In callback (webhook) mode the media bodies carry no per-message aeskey;
+        # the download url is encrypted with the bot's EncodingAESKey instead.
+        self._default_aeskey = default_aeskey
+
+        msg_type = msg_body.get("msgtype")
+        from_userid = msg_body.get("from", {}).get("userid", "")
+        chat_id = msg_body.get("chatid", "")
+        bot_id = msg_body.get("aibotid", "")
+
+        if msg_type == "text":
+            self.ctype = ContextType.TEXT
+            content = msg_body.get("text", {}).get("content", "")
+            if is_group:
+                content = re.sub(r"@\S+\s*", "", content).strip()
+            self.content = content
+
+        elif msg_type == "voice":
+            self.ctype = ContextType.TEXT
+            self.content = msg_body.get("voice", {}).get("content", "")
+
+        elif msg_type == "image":
+            self.ctype = ContextType.IMAGE
+            image_info = msg_body.get("image", {})
+            image_url = image_info.get("url", "")
+            aeskey = image_info.get("aeskey", "") or self._default_aeskey
+            tmp_dir = _get_tmp_dir()
+            image_path = os.path.join(tmp_dir, f"wecom_{self.msg_id}.png")
+
+            try:
+                data = _decrypt_media(image_url, aeskey)
+                with open(image_path, "wb") as f:
+                    f.write(data)
+                self.content = image_path
+                self.image_path = image_path
+                logger.info(f"[WecomBot] Image downloaded: {image_path}")
+            except Exception as e:
+                logger.error(f"[WecomBot] Failed to download image: {e}")
+                self.content = "[Image download failed]"
+                self.image_path = None
+
+        elif msg_type == "mixed":
+            self.ctype = ContextType.TEXT
+            text_parts = []
+            image_paths = []
+            mixed_items = msg_body.get("mixed", {}).get("msg_item", [])
+            tmp_dir = _get_tmp_dir()
+
+            for idx, item in enumerate(mixed_items):
+                item_type = item.get("msgtype")
+                if item_type == "text":
+                    txt = item.get("text", {}).get("content", "")
+                    if is_group:
+                        txt = re.sub(r"@\S+\s*", "", txt).strip()
+                    if txt:
+                        text_parts.append(txt)
+                elif item_type == "image":
+                    img_info = item.get("image", {})
+                    img_url = img_info.get("url", "")
+                    img_aeskey = img_info.get("aeskey", "") or self._default_aeskey
+                    img_path = os.path.join(tmp_dir, f"wecom_{self.msg_id}_{idx}.png")
+                    try:
+                        img_data = _decrypt_media(img_url, img_aeskey)
+                        with open(img_path, "wb") as f:
+                            f.write(img_data)
+                        image_paths.append(img_path)
+                    except Exception as e:
+                        logger.error(f"[WecomBot] Failed to download mixed image: {e}")
+
+            content_parts = text_parts[:]
+            for p in image_paths:
+                content_parts.append(f"[图片: {p}]")
+            self.content = "\n".join(content_parts) if content_parts else "[Mixed message]"
+
+        elif msg_type == "file":
+            self.ctype = ContextType.FILE
+            file_info = msg_body.get("file", {})
+            file_url = file_info.get("url", "")
+            aeskey = file_info.get("aeskey", "") or self._default_aeskey
+            tmp_dir = _get_tmp_dir()
+            base_path = os.path.join(tmp_dir, f"wecom_{self.msg_id}")
+            self.content = base_path
+
+            def _download_file():
+                try:
+                    data = _decrypt_media(file_url, aeskey)
+                    ext = _guess_ext_from_bytes(data)
+                    final_path = base_path + ext
+                    with open(final_path, "wb") as f:
+                        f.write(data)
+                    self.content = final_path
+                    logger.info(f"[WecomBot] File downloaded: {final_path}")
+                except Exception as e:
+                    logger.error(f"[WecomBot] Failed to download file: {e}")
+            self._prepare_fn = _download_file
+
+        elif msg_type == "video":
+            self.ctype = ContextType.FILE
+            video_info = msg_body.get("video", {})
+            video_url = video_info.get("url", "")
+            aeskey = video_info.get("aeskey", "") or self._default_aeskey
+            tmp_dir = _get_tmp_dir()
+            self.content = os.path.join(tmp_dir, f"wecom_{self.msg_id}.mp4")
+
+            def _download_video():
+                try:
+                    data = _decrypt_media(video_url, aeskey)
+                    with open(self.content, "wb") as f:
+                        f.write(data)
+                    logger.info(f"[WecomBot] Video downloaded: {self.content}")
+                except Exception as e:
+                    logger.error(f"[WecomBot] Failed to download video: {e}")
+            self._prepare_fn = _download_video
+
+        else:
+            raise NotImplementedError(f"Unsupported message type: {msg_type}")
+
+        self.from_user_id = from_userid
+        self.to_user_id = bot_id
+        if is_group:
+            self.other_user_id = chat_id
+            self.actual_user_id = from_userid
+            self.actual_user_nickname = from_userid
+        else:
+            self.other_user_id = from_userid
+            self.actual_user_id = from_userid
diff --git a/channel/weixin/__init__.py b/channel/weixin/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/channel/weixin/weixin_api.py b/channel/weixin/weixin_api.py
new file mode 100644
index 0000000..83c68c9
--- /dev/null
+++ b/channel/weixin/weixin_api.py
@@ -0,0 +1,412 @@
+"""
+Weixin HTTP JSON API client.
+
+Implements the ilink bot protocol:
+  - getUpdates (long-poll)
+  - sendMessage
+  - getUploadUrl
+  - getConfig
+  - sendTyping
+  - QR login (get_bot_qrcode / get_qrcode_status)
+
+CDN media upload with AES-128-ECB encryption.
+"""
+
+import base64
+import hashlib
+import os
+import random
+import struct
+import time
+import uuid
+
+import requests
+
+from common.log import logger
+
+DEFAULT_BASE_URL = "https://ilinkai.weixin.qq.com"
+CDN_BASE_URL = "https://novac2c.cdn.weixin.qq.com/c2c"
+DEFAULT_LONG_POLL_TIMEOUT = 35
+DEFAULT_API_TIMEOUT = 15
+QR_POLL_TIMEOUT = 35
+BOT_TYPE = "3"
+
+
+def _random_wechat_uin() -> str:
+    val = random.randint(0, 0xFFFFFFFF)
+    return base64.b64encode(str(val).encode("utf-8")).decode("utf-8")
+
+
+CHANNEL_VERSION = "2.0.0"
+# iLink-App-ClientVersion: uint32 encoded as major<<16 | minor<<8 | patch
+# 2.0.0 → 0x00020000 = 131072
+CLIENT_VERSION = "131072"
+
+
+def _build_headers(token: str = "") -> dict:
+    headers = {
+        "Content-Type": "application/json",
+        "AuthorizationType": "ilink_bot_token",
+        "X-WECHAT-UIN": _random_wechat_uin(),
+        "iLink-App-Id": "bot",
+        "iLink-App-ClientVersion": CLIENT_VERSION,
+    }
+    if token:
+        headers["Authorization"] = f"Bearer {token}"
+    return headers
+
+
+def _ensure_trailing_slash(url: str) -> str:
+    return url if url.endswith("/") else url + "/"
+
+
+class WeixinApi:
+    """Stateless HTTP client for the Weixin ilink bot API."""
+
+    def __init__(self, base_url: str = DEFAULT_BASE_URL, token: str = "",
+                 cdn_base_url: str = CDN_BASE_URL):
+        self.base_url = base_url
+        self.token = token
+        self.cdn_base_url = cdn_base_url
+
+    def _post(self, endpoint: str, body: dict, timeout: int = DEFAULT_API_TIMEOUT) -> dict:
+        url = _ensure_trailing_slash(self.base_url) + endpoint
+        headers = _build_headers(self.token)
+        body.setdefault("base_info", {}).setdefault("channel_version", CHANNEL_VERSION)
+        try:
+            resp = requests.post(url, json=body, headers=headers, timeout=timeout)
+            resp.raise_for_status()
+            return resp.json()
+        except requests.exceptions.Timeout:
+            logger.debug(f"[Weixin] API timeout: {endpoint}")
+            return {"ret": 0, "msgs": []}
+        except Exception as e:
+            logger.error(f"[Weixin] API error {endpoint}: {e}")
+            raise
+
+    # ── getUpdates (long-poll) ─────────────────────────────────────────
+
+    def get_updates(self, get_updates_buf: str = "", timeout: int = DEFAULT_LONG_POLL_TIMEOUT) -> dict:
+        return self._post("ilink/bot/getupdates", {
+            "get_updates_buf": get_updates_buf,
+        }, timeout=timeout + 5)
+
+    # ── sendMessage ────────────────────────────────────────────────────
+
+    def send_text(self, to: str, text: str, context_token: str) -> dict:
+        return self._post("ilink/bot/sendmessage", {
+            "msg": {
+                "from_user_id": "",
+                "to_user_id": to,
+                "client_id": uuid.uuid4().hex[:16],
+                "message_type": 2,  # BOT
+                "message_state": 2,  # FINISH
+                "item_list": [{"type": 1, "text_item": {"text": text}}],
+                "context_token": context_token,
+            }
+        })
+
+    def send_image_item(self, to: str, context_token: str,
+                        encrypt_query_param: str, aes_key_b64: str,
+                        ciphertext_size: int, text: str = "") -> dict:
+        items = []
+        if text:
+            items.append({"type": 1, "text_item": {"text": text}})
+        items.append({
+            "type": 2,
+            "image_item": {
+                "media": {
+                    "encrypt_query_param": encrypt_query_param,
+                    "aes_key": aes_key_b64,
+                    "encrypt_type": 1,
+                },
+                "mid_size": ciphertext_size,
+            }
+        })
+        return self._send_items(to, context_token, items)
+
+    def send_file_item(self, to: str, context_token: str,
+                       encrypt_query_param: str, aes_key_b64: str,
+                       file_name: str, file_size: int, text: str = "") -> dict:
+        items = []
+        if text:
+            items.append({"type": 1, "text_item": {"text": text}})
+        items.append({
+            "type": 4,
+            "file_item": {
+                "media": {
+                    "encrypt_query_param": encrypt_query_param,
+                    "aes_key": aes_key_b64,
+                    "encrypt_type": 1,
+                },
+                "file_name": file_name,
+                "len": str(file_size),
+            }
+        })
+        return self._send_items(to, context_token, items)
+
+    def send_video_item(self, to: str, context_token: str,
+                        encrypt_query_param: str, aes_key_b64: str,
+                        ciphertext_size: int, text: str = "") -> dict:
+        items = []
+        if text:
+            items.append({"type": 1, "text_item": {"text": text}})
+        items.append({
+            "type": 5,
+            "video_item": {
+                "media": {
+                    "encrypt_query_param": encrypt_query_param,
+                    "aes_key": aes_key_b64,
+                    "encrypt_type": 1,
+                },
+                "video_size": ciphertext_size,
+            }
+        })
+        return self._send_items(to, context_token, items)
+
+    def _send_items(self, to: str, context_token: str, items: list) -> dict:
+        return self._post("ilink/bot/sendmessage", {
+            "msg": {
+                "from_user_id": "",
+                "to_user_id": to,
+                "client_id": uuid.uuid4().hex[:16],
+                "message_type": 2,
+                "message_state": 2,
+                "item_list": items,
+                "context_token": context_token,
+            }
+        })
+
+    # ── getUploadUrl ───────────────────────────────────────────────────
+
+    def get_upload_url(self, filekey: str, media_type: int, to_user_id: str,
+                       rawsize: int, rawfilemd5: str, filesize: int,
+                       aeskey: str) -> dict:
+        return self._post("ilink/bot/getuploadurl", {
+            "filekey": filekey,
+            "media_type": media_type,
+            "to_user_id": to_user_id,
+            "rawsize": rawsize,
+            "rawfilemd5": rawfilemd5,
+            "filesize": filesize,
+            "aeskey": aeskey,
+            "no_need_thumb": True,
+        })
+
+    # ── getConfig / sendTyping ─────────────────────────────────────────
+
+    def get_config(self, user_id: str, context_token: str = "") -> dict:
+        return self._post("ilink/bot/getconfig", {
+            "ilink_user_id": user_id,
+            "context_token": context_token,
+        }, timeout=10)
+
+    def send_typing(self, user_id: str, typing_ticket: str, status: int = 1) -> dict:
+        return self._post("ilink/bot/sendtyping", {
+            "ilink_user_id": user_id,
+            "typing_ticket": typing_ticket,
+            "status": status,
+        }, timeout=10)
+
+    # ── QR Login ───────────────────────────────────────────────────────
+
+    def fetch_qr_code(self) -> dict:
+        url = _ensure_trailing_slash(self.base_url) + f"ilink/bot/get_bot_qrcode?bot_type={BOT_TYPE}"
+        resp = requests.get(url, timeout=15)
+        resp.raise_for_status()
+        return resp.json()
+
+    def poll_qr_status(self, qrcode: str, timeout: int = QR_POLL_TIMEOUT) -> dict:
+        url = (_ensure_trailing_slash(self.base_url) +
+               f"ilink/bot/get_qrcode_status?qrcode={requests.utils.quote(qrcode)}")
+        headers = {
+            "iLink-App-Id": "bot",
+            "iLink-App-ClientVersion": CLIENT_VERSION,
+        }
+        try:
+            resp = requests.get(url, headers=headers, timeout=timeout)
+            resp.raise_for_status()
+            return resp.json()
+        except requests.exceptions.Timeout:
+            return {"status": "wait"}
+
+
+# ── AES-128-ECB helpers ─────────────────────────────────────────────
+
+def _aes_ecb_encrypt(data: bytes, key: bytes) -> bytes:
+    from Crypto.Cipher import AES
+    pad_len = 16 - (len(data) % 16)
+    padded = data + bytes([pad_len] * pad_len)
+    cipher = AES.new(key, AES.MODE_ECB)
+    return cipher.encrypt(padded)
+
+
+def _aes_ecb_decrypt(data: bytes, key: bytes) -> bytes:
+    from Crypto.Cipher import AES
+    cipher = AES.new(key, AES.MODE_ECB)
+    decrypted = cipher.decrypt(data)
+    pad_len = decrypted[-1]
+    if pad_len > 16:
+        return decrypted
+    return decrypted[:-pad_len]
+
+
+def _file_md5(file_path: str) -> str:
+    h = hashlib.md5()
+    with open(file_path, "rb") as f:
+        for chunk in iter(lambda: f.read(8192), b""):
+            h.update(chunk)
+    return h.hexdigest()
+
+
+def _md5_bytes(data: bytes) -> str:
+    return hashlib.md5(data).hexdigest()
+
+
+def _aes_ecb_padded_size(plaintext_size: int) -> int:
+    """PKCS7 padded size for AES-128-ECB."""
+    return ((plaintext_size + 1 + 15) // 16) * 16
+
+
+UPLOAD_MAX_RETRIES = 3
+
+
+def upload_media_to_cdn(api: WeixinApi, file_path: str, to_user_id: str,
+                        media_type: int) -> dict:
+    """
+    Upload a local file to the Weixin CDN (matching official plugin protocol).
+
+    Args:
+        api: WeixinApi instance
+        file_path: local file path
+        to_user_id: target user id
+        media_type: 1=IMAGE, 2=VIDEO, 3=FILE
+
+    Returns:
+        dict with keys: encrypt_query_param, aes_key_b64, ciphertext_size, raw_size
+    """
+    aes_key = os.urandom(16)
+    aes_key_hex = aes_key.hex()
+    filekey = uuid.uuid4().hex
+
+    with open(file_path, "rb") as f:
+        raw_data = f.read()
+
+    raw_size = len(raw_data)
+    raw_md5 = _md5_bytes(raw_data)
+    cipher_size = _aes_ecb_padded_size(raw_size)
+
+    encrypted = _aes_ecb_encrypt(raw_data, aes_key)
+
+    from urllib.parse import quote
+
+    download_param = None
+    last_error = None
+    for attempt in range(1, UPLOAD_MAX_RETRIES + 1):
+        try:
+            if attempt > 1:
+                filekey = uuid.uuid4().hex
+            resp = api.get_upload_url(
+                filekey=filekey,
+                media_type=media_type,
+                to_user_id=to_user_id,
+                rawsize=raw_size,
+                rawfilemd5=raw_md5,
+                filesize=cipher_size,
+                aeskey=aes_key_hex,
+            )
+
+            # API may return either upload_full_url (new) or upload_param (legacy)
+            upload_full_url = resp.get("upload_full_url", "")
+            upload_param = resp.get("upload_param", "")
+            if upload_full_url:
+                cdn_url = upload_full_url
+            elif upload_param:
+                cdn_url = (f"{api.cdn_base_url}/upload"
+                           f"?encrypted_query_param={quote(upload_param)}"
+                           f"&filekey={quote(filekey)}")
+            else:
+                raise RuntimeError(f"[Weixin] getUploadUrl returned neither upload_full_url nor upload_param: {resp}")
+
+            cdn_resp = requests.post(cdn_url, data=encrypted, headers={
+                "Content-Type": "application/octet-stream",
+                "Content-Length": str(len(encrypted)),
+            }, timeout=120)
+            if 400 <= cdn_resp.status_code < 500:
+                err_msg = cdn_resp.headers.get("x-error-message", cdn_resp.text[:200])
+                raise RuntimeError(f"CDN client error {cdn_resp.status_code}: {err_msg}")
+            cdn_resp.raise_for_status()
+            download_param = cdn_resp.headers.get("x-encrypted-param", "")
+            if not download_param:
+                raise RuntimeError("CDN response missing x-encrypted-param header")
+            logger.debug(f"[Weixin] CDN upload success attempt={attempt} filekey={filekey}")
+            break
+        except Exception as e:
+            last_error = e
+            if "client error" in str(e):
+                raise
+            if attempt < UPLOAD_MAX_RETRIES:
+                backoff = 2 ** attempt
+                logger.warning(f"[Weixin] CDN upload attempt {attempt} failed, retrying in {backoff}s: {e}")
+                time.sleep(backoff)
+            else:
+                logger.error(f"[Weixin] CDN upload failed after {UPLOAD_MAX_RETRIES} attempts: {e}")
+
+    if not download_param:
+        raise last_error or RuntimeError("CDN upload failed")
+
+    aes_key_b64 = base64.b64encode(aes_key_hex.encode("utf-8")).decode("utf-8")
+
+    return {
+        "encrypt_query_param": download_param,
+        "aes_key_b64": aes_key_b64,
+        "ciphertext_size": cipher_size,
+        "raw_size": raw_size,
+    }
+
+
+def download_media_from_cdn(cdn_base_url: str, encrypt_query_param: str,
+                            aes_key: str, save_path: str) -> str:
+    """
+    Download and decrypt a media file from Weixin CDN.
+
+    Args:
+        cdn_base_url: CDN base URL
+        encrypt_query_param: encrypted query parameter from message
+        aes_key: hex or base64 encoded AES key
+        save_path: path to save decrypted file
+
+    Returns:
+        save_path on success
+    """
+    from urllib.parse import quote
+    url = f"{cdn_base_url}/download?encrypted_query_param={quote(encrypt_query_param)}"
+    resp = requests.get(url, timeout=60)
+    resp.raise_for_status()
+
+    # Determine key format:
+    # 1) 32-char hex string → 16 raw bytes
+    # 2) base64 string → decode → if 32 bytes, treat as hex-encoded → 16 raw bytes
+    # 3) base64 string → decode → 16 raw bytes directly
+    try:
+        key_bytes = bytes.fromhex(aes_key)
+        if len(key_bytes) != 16:
+            raise ValueError()
+    except (ValueError, TypeError):
+        decoded = base64.b64decode(aes_key)
+        if len(decoded) == 32:
+            try:
+                key_bytes = bytes.fromhex(decoded.decode("ascii"))
+            except (ValueError, UnicodeDecodeError):
+                raise ValueError(f"Invalid AES key: 32 bytes but not valid hex")
+        elif len(decoded) == 16:
+            key_bytes = decoded
+        else:
+            raise ValueError(f"Invalid AES key length after base64 decode: {len(decoded)}")
+
+    decrypted = _aes_ecb_decrypt(resp.content, key_bytes)
+
+    os.makedirs(os.path.dirname(save_path), exist_ok=True)
+    with open(save_path, "wb") as f:
+        f.write(decrypted)
+    return save_path
diff --git a/channel/weixin/weixin_channel.py b/channel/weixin/weixin_channel.py
new file mode 100644
index 0000000..516b041
--- /dev/null
+++ b/channel/weixin/weixin_channel.py
@@ -0,0 +1,743 @@
+"""
+Weixin channel implementation.
+
+Uses HTTP long-poll (getUpdates) to receive messages and sendMessage to reply.
+Login via QR code scan through the ilink bot API.
+"""
+
+import json
+import os
+import threading
+import time
+import uuid
+
+import requests
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_channel import ChatChannel, check_prefix
+from channel.weixin.weixin_api import (
+    WeixinApi, upload_media_to_cdn,
+    DEFAULT_BASE_URL, CDN_BASE_URL,
+)
+from channel.weixin.weixin_message import WeixinMessage
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from common.singleton import singleton
+from config import conf, get_weixin_credentials_path
+
+MAX_CONSECUTIVE_FAILURES = 3
+BACKOFF_DELAY = 30
+RETRY_DELAY = 2
+SESSION_EXPIRED_ERRCODE = -14
+TEXT_CHUNK_LIMIT = 4000
+QR_LOGIN_TIMEOUT_S = 480
+QR_MAX_REFRESHES = 10
+
+
+def _load_credentials(cred_path: str) -> dict:
+    """Load saved credentials from JSON file."""
+    try:
+        if os.path.exists(cred_path):
+            with open(cred_path, "r") as f:
+                return json.load(f)
+    except Exception as e:
+        logger.warning(f"[Weixin] Failed to load credentials: {e}")
+    return {}
+
+
+def _save_credentials(cred_path: str, data: dict):
+    """Atomically save credentials to JSON file (tmp + rename)."""
+    os.makedirs(os.path.dirname(cred_path), exist_ok=True)
+    tmp_path = f"{cred_path}.tmp"
+    with open(tmp_path, "w") as f:
+        json.dump(data, f, indent=2)
+    try:
+        os.chmod(tmp_path, 0o600)
+    except Exception:
+        pass
+    os.replace(tmp_path, cred_path)
+
+
+@singleton
+class WeixinChannel(ChatChannel):
+
+    # ilink bot protocol has no outbound voice item; deliver TTS as a file.
+    NOT_SUPPORT_REPLYTYPE = []
+
+    LOGIN_STATUS_IDLE = "idle"
+    LOGIN_STATUS_WAITING = "waiting_scan"
+    LOGIN_STATUS_SCANNED = "scanned"
+    LOGIN_STATUS_OK = "logged_in"
+
+    def __init__(self):
+        super().__init__()
+        self.api = None
+        self._stop_event = threading.Event()
+        self._poll_thread = None
+        # user_id -> context_token. Guarded by _context_tokens_lock for any
+        # mutation that races with disk persistence.
+        self._context_tokens = {}
+        self._context_tokens_lock = threading.Lock()
+        self._received_msgs = ExpiredDict(60 * 60 * 7.1)
+        self._get_updates_buf = ""
+        self._credentials_path = ""
+        self.login_status = self.LOGIN_STATUS_IDLE
+        self._current_qr_url = ""
+
+        conf()["single_chat_prefix"] = [""]
+
+    # ── Lifecycle ──────────────────────────────────────────────────────
+
+    def startup(self):
+        self._stop_event.clear()
+
+        base_url = conf().get("weixin_base_url", DEFAULT_BASE_URL)
+        cdn_base_url = conf().get("weixin_cdn_base_url", CDN_BASE_URL)
+        token = conf().get("weixin_token", "")
+
+        self._credentials_path = get_weixin_credentials_path()
+
+        # Always load credentials so we can restore context_tokens even when
+        # the bot token itself comes from config.
+        creds = _load_credentials(self._credentials_path)
+        if not token:
+            token = creds.get("token", "")
+            if creds.get("base_url"):
+                base_url = creds["base_url"]
+
+        # Restore persisted context_tokens so scheduler can deliver pushes
+        # immediately after restart, without waiting for the user to ping
+        # the bot first.
+        self._restore_context_tokens_from_creds(creds)
+
+        if not token:
+            token, base_url = self._login_with_retry(base_url)
+            if not token:
+                return
+
+        self.api = WeixinApi(base_url=base_url, token=token, cdn_base_url=cdn_base_url)
+        self.login_status = self.LOGIN_STATUS_OK
+
+        logger.info(f"[Weixin] 微信通道已启动，凭证保存在 {self._credentials_path}，"
+                     f"如需重新扫码登录请删除该文件后重启")
+        self.report_startup_success()
+
+        self._poll_loop()
+
+    def _login_with_retry(self, base_url: str) -> tuple:
+        """Attempt QR login, then wait for stop if failed.
+        Returns (token, base_url) on success, or ("", "") if stopped."""
+        logger.info("[Weixin] No token found, starting QR login...")
+        self.login_status = self.LOGIN_STATUS_WAITING
+        login_result = self._qr_login(base_url)
+        if login_result:
+            return login_result["token"], login_result.get("base_url", base_url)
+
+        self.login_status = self.LOGIN_STATUS_IDLE
+        if not self._stop_event.is_set():
+            logger.info("[Weixin] QR login timed out, waiting for stop or reconnect...")
+            print("  二维码登录超时，请通过控制台重新接入\n")
+            self._stop_event.wait()
+
+        logger.info("[Weixin] Login cancelled by stop event")
+        return "", ""
+
+    def stop(self):
+        logger.info("[Weixin] stop() called")
+        self._stop_event.set()
+
+    def _relogin(self) -> bool:
+        """Re-login after session expiry. Returns True on success."""
+        base_url = self.api.base_url if self.api else DEFAULT_BASE_URL
+        # Clearing the whole credentials file is intentional: the new login
+        # will issue a fresh `token` and persisted context_tokens belong to
+        # the previous bot identity, so they must not survive.
+        with self._context_tokens_lock:
+            self._context_tokens.clear()
+            if os.path.exists(self._credentials_path):
+                try:
+                    os.remove(self._credentials_path)
+                except Exception:
+                    pass
+        self.login_status = self.LOGIN_STATUS_WAITING
+        result = self._qr_login(base_url)
+        if not result:
+            self.login_status = self.LOGIN_STATUS_IDLE
+            return False
+        self.api = WeixinApi(
+            base_url=result.get("base_url", base_url),
+            token=result["token"],
+            cdn_base_url=self.api.cdn_base_url if self.api else CDN_BASE_URL,
+        )
+        self.login_status = self.LOGIN_STATUS_OK
+        return True
+
+    # ── Context token persistence ──────────────────────────────────────
+    # ilink requires every outbound send to echo the context_token from the
+    # user's latest inbound message. We mirror the in-memory map into the
+    # credentials JSON so scheduled pushes survive process restarts.
+    # All mutation + disk IO is serialized via _context_tokens_lock so that
+    # concurrent updates can never lose each other's writes.
+
+    def _restore_context_tokens_from_creds(self, creds: dict) -> None:
+        if not isinstance(creds, dict):
+            return
+        tokens = creds.get("context_tokens")
+        if not isinstance(tokens, dict):
+            return
+        restored = 0
+        with self._context_tokens_lock:
+            for user_id, token in tokens.items():
+                if isinstance(user_id, str) and isinstance(token, str) and token:
+                    self._context_tokens[user_id] = token
+                    restored += 1
+        if restored:
+            logger.info(f"[Weixin] Restored {restored} context_tokens from credentials")
+
+    def _persist_context_tokens_locked(self) -> None:
+        """Flush the token map to disk. Caller must hold _context_tokens_lock."""
+        if not self._credentials_path:
+            return
+        try:
+            creds = _load_credentials(self._credentials_path) or {}
+            creds["context_tokens"] = dict(self._context_tokens)
+            _save_credentials(self._credentials_path, creds)
+        except Exception as e:
+            logger.warning(f"[Weixin] Failed to persist context_tokens: {e}")
+
+    def _update_context_token(self, user_id: str, token: str) -> None:
+        """Update the in-memory token for a user; flush to disk only on change."""
+        if not user_id or not token:
+            return
+        with self._context_tokens_lock:
+            if self._context_tokens.get(user_id) == token:
+                return
+            self._context_tokens[user_id] = token
+            self._persist_context_tokens_locked()
+
+    def _invalidate_context_token(self, user_id: str) -> None:
+        """Drop the cached token for a user (used after -14 / send rejection)."""
+        if not user_id:
+            return
+        with self._context_tokens_lock:
+            if user_id not in self._context_tokens:
+                return
+            del self._context_tokens[user_id]
+            logger.info(f"[Weixin] Invalidated stale context_token for {user_id}")
+            self._persist_context_tokens_locked()
+
+    # ── QR Login ───────────────────────────────────────────────────────
+
+    @staticmethod
+    def _print_qr(qrcode_url: str):
+        """Print QR code to terminal for scanning."""
+        print("\n" + "=" * 60)
+        print("  请使用微信扫描二维码登录 (二维码约2分钟后过期)")
+        print("=" * 60)
+        try:
+            import qrcode as qr_lib
+            import io
+            qr = qr_lib.QRCode(error_correction=qr_lib.constants.ERROR_CORRECT_L, box_size=1, border=1)
+            qr.add_data(qrcode_url)
+            qr.make(fit=True)
+            buf = io.StringIO()
+            qr.print_ascii(out=buf, invert=True)
+            try:
+                print(buf.getvalue())
+            except UnicodeEncodeError:
+                # Windows GBK terminals cannot render Unicode block characters
+                print(f"\n  (终端不支持显示二维码，请使用链接扫码)")
+                print(f"  二维码链接: {qrcode_url}\n")
+        except ImportError:
+            print(f"\n  二维码链接: {qrcode_url}")
+            print("  (安装 'qrcode' 包可在终端显示二维码)\n")
+
+    def _notify_cloud_qrcode(self, qrcode_url: str):
+        """Send QR code URL to cloud console when running in cloud mode."""
+        if not self.cloud_mode:
+            return
+        try:
+            from common import cloud_client
+            client = getattr(cloud_client, "chat_client", None)
+            if client and getattr(client, "client_id", None):
+                client.send_channel_qrcode("weixin", qrcode_url)
+        except Exception as e:
+            logger.warning(f"[Weixin] Failed to notify cloud QR code: {e}")
+
+    def _notify_cloud_connected(self):
+        """Send connected status to cloud console when login succeeds."""
+        if not self.cloud_mode:
+            return
+        try:
+            from common import cloud_client
+            client = getattr(cloud_client, "chat_client", None)
+            if client and getattr(client, "client_id", None):
+                client.send_channel_status("weixin", "connected")
+        except Exception as e:
+            logger.warning(f"[Weixin] Failed to notify cloud connected: {e}")
+
+    def _qr_login(self, base_url: str) -> dict:
+        """Perform interactive QR code login. Returns dict with token/base_url or empty dict."""
+        api = WeixinApi(base_url=base_url)
+        try:
+            qr_resp = api.fetch_qr_code()
+        except Exception as e:
+            logger.error(f"[Weixin] Failed to fetch QR code: {e}")
+            return {}
+
+        qrcode = qr_resp.get("qrcode", "")
+        qrcode_url = qr_resp.get("qrcode_img_content", "")
+
+        if not qrcode:
+            logger.error("[Weixin] No QR code returned from server")
+            return {}
+
+        self._current_qr_url = qrcode_url
+        logger.info(f"[Weixin] 微信二维码链接: {qrcode_url}")
+        self._print_qr(qrcode_url)
+        self._notify_cloud_qrcode(qrcode_url)
+        print("  等待扫码...\n")
+
+        scanned_printed = False
+        refresh_count = 0
+        deadline = time.time() + QR_LOGIN_TIMEOUT_S
+
+        while not self._stop_event.is_set():
+            if time.time() >= deadline:
+                logger.warning(f"[Weixin] QR login timed out after {QR_LOGIN_TIMEOUT_S}s")
+                print(f"\n  二维码登录超时（{QR_LOGIN_TIMEOUT_S}s），请重启后重试")
+                break
+
+            try:
+                status_resp = api.poll_qr_status(qrcode)
+            except Exception as e:
+                logger.error(f"[Weixin] QR status poll error: {e}")
+                return {}
+
+            status = status_resp.get("status", "wait")
+
+            if status == "wait":
+                pass
+            elif status == "scaned":
+                self.login_status = self.LOGIN_STATUS_SCANNED
+                if not scanned_printed:
+                    print("  已扫码，请在手机上确认...")
+                    scanned_printed = True
+            elif status == "expired":
+                refresh_count += 1
+                if refresh_count >= QR_MAX_REFRESHES:
+                    logger.warning(f"[Weixin] QR code refreshed {QR_MAX_REFRESHES} times, giving up")
+                    print(f"\n  二维码已刷新 {QR_MAX_REFRESHES} 次仍未扫码，请重启后重试")
+                    break
+                print(f"  二维码已过期，正在刷新（{refresh_count}/{QR_MAX_REFRESHES}）...")
+                try:
+                    qr_resp = api.fetch_qr_code()
+                    qrcode = qr_resp.get("qrcode", "")
+                    qrcode_url = qr_resp.get("qrcode_img_content", "")
+                    scanned_printed = False
+                    self._current_qr_url = qrcode_url
+                    logger.info(f"[Weixin] 微信二维码链接 ({refresh_count}/{QR_MAX_REFRESHES}): {qrcode_url}")
+                    self._print_qr(qrcode_url)
+                    self._notify_cloud_qrcode(qrcode_url)
+                except Exception as e:
+                    logger.error(f"[Weixin] QR refresh failed: {e}")
+                    return {}
+            elif status == "confirmed":
+                bot_token = status_resp.get("bot_token", "")
+                bot_id = status_resp.get("ilink_bot_id", "")
+                result_base_url = status_resp.get("baseurl", base_url)
+                user_id = status_resp.get("ilink_user_id", "")
+
+                if not bot_token or not bot_id:
+                    logger.error("[Weixin] Login confirmed but missing token/bot_id")
+                    return {}
+
+                self._current_qr_url = ""
+                print(f"\n  ✅ 微信登录成功！bot_id={bot_id}")
+                logger.info(f"[Weixin] Login confirmed: bot_id={bot_id}")
+                self._notify_cloud_connected()
+
+                creds = {
+                    "token": bot_token,
+                    "base_url": result_base_url,
+                    "bot_id": bot_id,
+                    "user_id": user_id,
+                }
+                _save_credentials(self._credentials_path, creds)
+                logger.info(f"[Weixin] Credentials saved to {self._credentials_path}")
+
+                return {"token": bot_token, "base_url": result_base_url}
+
+            self._stop_event.wait(1)
+
+        self._current_qr_url = ""
+        if self._stop_event.is_set():
+            logger.info("[Weixin] QR login cancelled by stop event")
+        return {}
+
+    # ── Long-poll loop ─────────────────────────────────────────────────
+
+    def _poll_loop(self):
+        """Main long-poll loop: getUpdates -> parse -> produce."""
+        logger.info("[Weixin] Starting long-poll loop")
+        consecutive_failures = 0
+
+        while not self._stop_event.is_set():
+            try:
+                resp = self.api.get_updates(self._get_updates_buf)
+
+                ret = resp.get("ret", 0)
+                errcode = resp.get("errcode", 0)
+
+                is_error = (ret != 0) or (errcode != 0)
+                if is_error:
+                    if errcode == SESSION_EXPIRED_ERRCODE or ret == SESSION_EXPIRED_ERRCODE:
+                        logger.error("[Weixin] Session expired (errcode -14), starting re-login...")
+                        if self._relogin():
+                            logger.info("[Weixin] Re-login successful, resuming long-poll")
+                            self._get_updates_buf = ""
+                            consecutive_failures = 0
+                            continue
+                        else:
+                            logger.error("[Weixin] Re-login failed, will retry in 5 minutes")
+                            self._stop_event.wait(300)
+                            continue
+
+                    consecutive_failures += 1
+                    errmsg = resp.get("errmsg", "")
+                    logger.error(f"[Weixin] getUpdates error: ret={ret} errcode={errcode} "
+                                 f"errmsg={errmsg} ({consecutive_failures}/{MAX_CONSECUTIVE_FAILURES})")
+                    if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                        consecutive_failures = 0
+                        self._stop_event.wait(BACKOFF_DELAY)
+                    else:
+                        self._stop_event.wait(RETRY_DELAY)
+                    continue
+
+                consecutive_failures = 0
+
+                # Update sync cursor
+                new_buf = resp.get("get_updates_buf", "")
+                if new_buf:
+                    self._get_updates_buf = new_buf
+
+                # Process messages
+                msgs = resp.get("msgs", [])
+                for raw_msg in msgs:
+                    try:
+                        self._process_message(raw_msg)
+                    except Exception as e:
+                        logger.error(f"[Weixin] Failed to process message: {e}", exc_info=True)
+
+            except Exception as e:
+                if self._stop_event.is_set():
+                    break
+                consecutive_failures += 1
+                logger.error(f"[Weixin] getUpdates exception: {e} "
+                             f"({consecutive_failures}/{MAX_CONSECUTIVE_FAILURES})")
+                if consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
+                    consecutive_failures = 0
+                    self._stop_event.wait(BACKOFF_DELAY)
+                else:
+                    self._stop_event.wait(RETRY_DELAY)
+
+        logger.info("[Weixin] Long-poll loop ended")
+
+    def _process_message(self, raw_msg: dict):
+        """Parse a single inbound message and produce to the handling queue."""
+        msg_type = raw_msg.get("message_type", 0)
+        if msg_type != 1:  # Only process USER messages (type=1)
+            return
+
+        msg_id = str(raw_msg.get("message_id", raw_msg.get("seq", "")))
+        if self._received_msgs.get(msg_id):
+            return
+        self._received_msgs[msg_id] = True
+
+        from_user = raw_msg.get("from_user_id", "")
+        context_token = raw_msg.get("context_token", "")
+
+        if context_token and from_user:
+            self._update_context_token(from_user, context_token)
+
+        cdn_base_url = self.api.cdn_base_url if self.api else CDN_BASE_URL
+        try:
+            wx_msg = WeixinMessage(raw_msg, cdn_base_url=cdn_base_url)
+        except Exception as e:
+            logger.error(f"[Weixin] Failed to parse WeixinMessage: {e}", exc_info=True)
+            return
+
+        logger.info(f"[Weixin] Received: from={from_user} ctype={wx_msg.ctype} "
+                     f"content={str(wx_msg.content)[:50]}")
+
+        # File cache logic
+        from channel.file_cache import get_file_cache
+        file_cache = get_file_cache()
+        session_id = from_user
+
+        if wx_msg.ctype == ContextType.IMAGE:
+            if hasattr(wx_msg, "image_path") and wx_msg.image_path:
+                file_cache.add(session_id, wx_msg.image_path, file_type="image")
+                logger.info(f"[Weixin] Image cached for session {session_id}")
+            return
+
+        if wx_msg.ctype == ContextType.FILE:
+            wx_msg.prepare()
+            file_cache.add(session_id, wx_msg.content, file_type="file")
+            logger.info(f"[Weixin] File cached for session {session_id}: {wx_msg.content}")
+            return
+
+        if wx_msg.ctype == ContextType.TEXT:
+            cached_files = file_cache.get(session_id)
+            if cached_files:
+                refs = []
+                for fi in cached_files:
+                    ftype, fpath = fi["type"], fi["path"]
+                    if ftype == "image":
+                        refs.append(f"[图片: {fpath}]")
+                    elif ftype == "video":
+                        refs.append(f"[视频: {fpath}]")
+                    else:
+                        refs.append(f"[文件: {fpath}]")
+                wx_msg.content = wx_msg.content + "\n" + "\n".join(refs)
+                file_cache.clear(session_id)
+
+        context = self._compose_context(
+            wx_msg.ctype,
+            wx_msg.content,
+            isgroup=False,
+            msg=wx_msg,
+            no_need_at=True,
+        )
+        if context:
+            self.produce(context)
+
+    # ── _compose_context ───────────────────────────────────────────────
+
+    def _compose_context(self, ctype: ContextType, content, **kwargs):
+        context = Context(ctype, content)
+        context.kwargs = kwargs
+        if "channel_type" not in context:
+            context["channel_type"] = self.channel_type
+        if "origin_ctype" not in context:
+            context["origin_ctype"] = ctype
+
+        cmsg = context["msg"]
+        context["session_id"] = cmsg.from_user_id
+        context["receiver"] = cmsg.other_user_id
+
+        if ctype == ContextType.TEXT:
+            img_match_prefix = check_prefix(content, conf().get("image_create_prefix"))
+            if img_match_prefix:
+                content = content.replace(img_match_prefix, "", 1)
+                context.type = ContextType.IMAGE_CREATE
+            else:
+                context.type = ContextType.TEXT
+            context.content = content.strip()
+            if "desire_rtype" not in context and conf().get("always_reply_voice"):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        elif ctype == ContextType.VOICE:
+            if "desire_rtype" not in context and (
+                conf().get("voice_reply_voice") or conf().get("always_reply_voice")
+            ):
+                context["desire_rtype"] = ReplyType.VOICE
+
+        return context
+
+    # ── Send reply ─────────────────────────────────────────────────────
+
+    def send(self, reply: Reply, context: Context):
+        receiver = context.get("receiver", "")
+        msg = context.get("msg")
+        context_token = self._get_context_token(receiver, msg)
+
+        if not context_token:
+            logger.error(f"[Weixin] No context_token for receiver={receiver}, cannot send")
+            return
+
+        if reply.type == ReplyType.TEXT:
+            self._send_text(reply.content, receiver, context_token)
+        elif reply.type in (ReplyType.IMAGE_URL, ReplyType.IMAGE):
+            self._send_image(reply.content, receiver, context_token)
+        elif reply.type == ReplyType.FILE:
+            self._send_file(reply.content, receiver, context_token)
+        elif reply.type in (ReplyType.VIDEO, ReplyType.VIDEO_URL):
+            self._send_video(reply.content, receiver, context_token)
+        elif reply.type == ReplyType.VOICE:
+            # ilink has no outbound voice item; deliver TTS as a file attachment.
+            self._send_file(reply.content, receiver, context_token)
+        else:
+            logger.warning(f"[Weixin] Unsupported reply type: {reply.type}, fallback to text")
+            self._send_text(str(reply.content), receiver, context_token)
+
+    def _get_context_token(self, receiver: str, msg=None) -> str:
+        """Get the context_token for a receiver, required for all sends."""
+        if msg and hasattr(msg, "context_token") and msg.context_token:
+            return msg.context_token
+        return self._context_tokens.get(receiver, "")
+
+    def _check_send_response(self, resp, receiver: str) -> None:
+        """Inspect a send-API response; drop stale context_token on -14.
+
+        ilink uses ret/errcode = -14 to signal that the session (and any
+        cached context_token) is no longer valid. The plugin keeps running
+        because the bot itself can re-login; we just need to forget the
+        per-user token so the next push won't retry forever.
+        """
+        if not isinstance(resp, dict):
+            return
+        ret = resp.get("ret")
+        errcode = resp.get("errcode")
+        if ret == -14 or errcode == -14:
+            logger.warning(
+                f"[Weixin] Send returned -14 (session expired) for "
+                f"receiver={receiver}; dropping cached context_token"
+            )
+            self._invalidate_context_token(receiver)
+
+    def _send_text(self, text: str, receiver: str, context_token: str):
+        if len(text) <= TEXT_CHUNK_LIMIT:
+            try:
+                resp = self.api.send_text(receiver, text, context_token)
+                self._check_send_response(resp, receiver)
+                logger.debug(f"[Weixin] Text sent to {receiver}, len={len(text)}")
+            except Exception as e:
+                logger.error(f"[Weixin] Failed to send text: {e}")
+            return
+
+        chunks = self._split_text(text, TEXT_CHUNK_LIMIT)
+        for i, chunk in enumerate(chunks):
+            try:
+                resp = self.api.send_text(receiver, chunk, context_token)
+                self._check_send_response(resp, receiver)
+                logger.debug(f"[Weixin] Text chunk {i+1}/{len(chunks)} sent to {receiver}, len={len(chunk)}")
+            except Exception as e:
+                logger.error(f"[Weixin] Failed to send text chunk {i+1}/{len(chunks)}: {e}")
+                break
+            if i < len(chunks) - 1:
+                time.sleep(0.5)
+
+    @staticmethod
+    def _split_text(text: str, limit: int) -> list:
+        """Split text into chunks, preferring to break at paragraph or line boundaries."""
+        if len(text) <= limit:
+            return [text]
+        chunks = []
+        while text:
+            if len(text) <= limit:
+                chunks.append(text)
+                break
+            cut = text.rfind("\n\n", 0, limit)
+            if cut <= 0:
+                cut = text.rfind("\n", 0, limit)
+            if cut <= 0:
+                cut = limit
+            chunks.append(text[:cut])
+            text = text[cut:].lstrip("\n")
+        return chunks
+
+    def _send_image(self, img_path_or_url: str, receiver: str, context_token: str):
+        local_path = self._resolve_media_path(img_path_or_url)
+        if not local_path:
+            self._send_text("[Image send failed: file not found]", receiver, context_token)
+            return
+        try:
+            result = upload_media_to_cdn(self.api, local_path, receiver, media_type=1)
+            resp = self.api.send_image_item(
+                to=receiver,
+                context_token=context_token,
+                encrypt_query_param=result["encrypt_query_param"],
+                aes_key_b64=result["aes_key_b64"],
+                ciphertext_size=result["ciphertext_size"],
+            )
+            self._check_send_response(resp, receiver)
+            logger.info(f"[Weixin] Image sent to {receiver}")
+        except Exception as e:
+            logger.error(f"[Weixin] Image send failed: {e}")
+            self._send_text("[Image send failed]", receiver, context_token)
+
+    def _send_file(self, file_path_or_url: str, receiver: str, context_token: str):
+        local_path = self._resolve_media_path(file_path_or_url)
+        if not local_path:
+            self._send_text("[File send failed: file not found]", receiver, context_token)
+            return
+        try:
+            result = upload_media_to_cdn(self.api, local_path, receiver, media_type=3)
+            resp = self.api.send_file_item(
+                to=receiver,
+                context_token=context_token,
+                encrypt_query_param=result["encrypt_query_param"],
+                aes_key_b64=result["aes_key_b64"],
+                file_name=os.path.basename(local_path),
+                file_size=result["raw_size"],
+            )
+            self._check_send_response(resp, receiver)
+            logger.info(f"[Weixin] File sent to {receiver}")
+        except Exception as e:
+            logger.error(f"[Weixin] File send failed: {e}")
+            self._send_text("[File send failed]", receiver, context_token)
+
+    def _send_video(self, video_path_or_url: str, receiver: str, context_token: str):
+        local_path = self._resolve_media_path(video_path_or_url)
+        if not local_path:
+            self._send_text("[Video send failed: file not found]", receiver, context_token)
+            return
+        try:
+            result = upload_media_to_cdn(self.api, local_path, receiver, media_type=2)
+            resp = self.api.send_video_item(
+                to=receiver,
+                context_token=context_token,
+                encrypt_query_param=result["encrypt_query_param"],
+                aes_key_b64=result["aes_key_b64"],
+                ciphertext_size=result["ciphertext_size"],
+            )
+            self._check_send_response(resp, receiver)
+            logger.info(f"[Weixin] Video sent to {receiver}")
+        except Exception as e:
+            logger.error(f"[Weixin] Video send failed: {e}")
+            self._send_text("[Video send failed]", receiver, context_token)
+
+    @staticmethod
+    def _resolve_media_path(path_or_url: str) -> str:
+        """Resolve a file path or URL to a local file path. Downloads if needed."""
+        if not path_or_url:
+            return ""
+
+        local_path = path_or_url
+        if local_path.startswith("file://"):
+            local_path = local_path[7:]
+
+        if local_path.startswith(("http://", "https://")):
+            try:
+                resp = requests.get(local_path, timeout=60)
+                resp.raise_for_status()
+                ct = resp.headers.get("Content-Type", "")
+                ext = ".bin"
+                if "jpeg" in ct or "jpg" in ct:
+                    ext = ".jpg"
+                elif "png" in ct:
+                    ext = ".png"
+                elif "gif" in ct:
+                    ext = ".gif"
+                elif "webp" in ct:
+                    ext = ".webp"
+                elif "mp4" in ct:
+                    ext = ".mp4"
+                elif "pdf" in ct:
+                    ext = ".pdf"
+
+                tmp_path = f"/tmp/wx_media_{uuid.uuid4().hex[:8]}{ext}"
+                with open(tmp_path, "wb") as f:
+                    f.write(resp.content)
+                return tmp_path
+            except Exception as e:
+                logger.error(f"[Weixin] Failed to download media: {e}")
+                return ""
+
+        if os.path.exists(local_path):
+            return local_path
+
+        logger.warning(f"[Weixin] Media file not found: {local_path}")
+        return ""
diff --git a/channel/weixin/weixin_message.py b/channel/weixin/weixin_message.py
new file mode 100644
index 0000000..2083c66
--- /dev/null
+++ b/channel/weixin/weixin_message.py
@@ -0,0 +1,204 @@
+"""
+Weixin ChatMessage implementation.
+
+Parses WeixinMessage from the getUpdates API into the unified ChatMessage format.
+"""
+
+import os
+import uuid
+
+from bridge.context import ContextType
+from channel.chat_message import ChatMessage
+from channel.weixin.weixin_api import download_media_from_cdn, CDN_BASE_URL
+from common.log import logger
+from common.utils import expand_path
+from config import conf
+
+
+# MessageItemType constants from the Weixin protocol
+ITEM_TEXT = 1
+ITEM_IMAGE = 2
+ITEM_VOICE = 3
+ITEM_FILE = 4
+ITEM_VIDEO = 5
+
+
+def _get_tmp_dir() -> str:
+    ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+    tmp_dir = os.path.join(ws_root, "tmp")
+    os.makedirs(tmp_dir, exist_ok=True)
+    return tmp_dir
+
+
+class WeixinMessage(ChatMessage):
+    """Message wrapper for Weixin channel."""
+
+    def __init__(self, msg: dict, cdn_base_url: str = CDN_BASE_URL):
+        super().__init__(msg)
+
+        self.msg_id = str(msg.get("message_id", msg.get("seq", uuid.uuid4().hex[:8])))
+        self.create_time = msg.get("create_time_ms", 0)
+        self.context_token = msg.get("context_token", "")
+        self.is_group = False  # Weixin plugin only supports direct chat
+        self.is_at = False
+
+        from_user_id = msg.get("from_user_id", "")
+        to_user_id = msg.get("to_user_id", "")
+
+        self.from_user_id = from_user_id
+        self.from_user_nickname = from_user_id
+        self.to_user_id = to_user_id
+        self.to_user_nickname = to_user_id
+        self.other_user_id = from_user_id
+        self.other_user_nickname = from_user_id
+        self.actual_user_id = from_user_id
+        self.actual_user_nickname = from_user_id
+
+        item_list = msg.get("item_list", [])
+
+        # Parse items: find text and media
+        text_body = ""
+        media_item = None
+        media_type = None
+        ref_text = ""
+
+        for item in item_list:
+            itype = item.get("type", 0)
+
+            if itype == ITEM_TEXT:
+                text_item = item.get("text_item", {})
+                text_body = text_item.get("text", "")
+
+                ref = item.get("ref_msg")
+                if ref:
+                    ref_title = ref.get("title", "")
+                    ref_mi = ref.get("message_item", {})
+                    ref_body = ""
+                    if ref_mi.get("type") == ITEM_TEXT:
+                        ref_body = ref_mi.get("text_item", {}).get("text", "")
+                    if ref_title or ref_body:
+                        parts = [p for p in [ref_title, ref_body] if p]
+                        ref_text = f"[引用: {' | '.join(parts)}]\n"
+                    # If ref is a media item, treat it as the media to download
+                    if ref_mi.get("type") in (ITEM_IMAGE, ITEM_VIDEO, ITEM_FILE):
+                        media_item = ref_mi
+                        media_type = ref_mi.get("type")
+
+            elif itype == ITEM_VOICE:
+                voice_item = item.get("voice_item", {})
+                voice_text = voice_item.get("text", "")
+                if voice_text:
+                    text_body = voice_text
+                else:
+                    # Voice without transcription - download the audio
+                    media_item = item
+                    media_type = ITEM_VOICE
+
+            elif itype in (ITEM_IMAGE, ITEM_VIDEO, ITEM_FILE):
+                if not media_item:
+                    media_item = item
+                    media_type = itype
+
+        # Determine ctype and content
+        if media_item and not text_body:
+            self._setup_media(media_item, media_type, cdn_base_url)
+        elif media_item and text_body:
+            # Text + media: download media, attach as file ref in text
+            self.ctype = ContextType.TEXT
+            media_path = self._download_media(media_item, media_type, cdn_base_url)
+            if media_path:
+                if media_type == ITEM_IMAGE:
+                    text_body += f"\n[图片: {media_path}]"
+                elif media_type == ITEM_VIDEO:
+                    text_body += f"\n[视频: {media_path}]"
+                else:
+                    text_body += f"\n[文件: {media_path}]"
+            self.content = ref_text + text_body
+        else:
+            self.ctype = ContextType.TEXT
+            self.content = ref_text + text_body
+
+    def _setup_media(self, item: dict, media_type: int, cdn_base_url: str):
+        """Set up message as a media type, with lazy download via _prepare_fn."""
+        if media_type == ITEM_IMAGE:
+            self.ctype = ContextType.IMAGE
+            image_path = self._download_media(item, ITEM_IMAGE, cdn_base_url)
+            if image_path:
+                self.content = image_path
+                self.image_path = image_path
+            else:
+                self.ctype = ContextType.TEXT
+                self.content = "[Image download failed]"
+
+        elif media_type == ITEM_VIDEO:
+            self.ctype = ContextType.FILE
+            save_path = os.path.join(_get_tmp_dir(), f"wx_{self.msg_id}.mp4")
+            self.content = save_path
+
+            def _download():
+                path = self._download_media(item, ITEM_VIDEO, cdn_base_url)
+                if path:
+                    self.content = path
+            self._prepare_fn = _download
+
+        elif media_type == ITEM_FILE:
+            self.ctype = ContextType.FILE
+            file_name = item.get("file_item", {}).get("file_name", f"wx_{self.msg_id}")
+            save_path = os.path.join(_get_tmp_dir(), file_name)
+            self.content = save_path
+
+            def _download():
+                path = self._download_media(item, ITEM_FILE, cdn_base_url)
+                if path:
+                    self.content = path
+            self._prepare_fn = _download
+
+        elif media_type == ITEM_VOICE:
+            self.ctype = ContextType.VOICE
+            save_path = os.path.join(_get_tmp_dir(), f"wx_{self.msg_id}.silk")
+            self.content = save_path
+
+            def _download():
+                path = self._download_media(item, ITEM_VOICE, cdn_base_url)
+                if path:
+                    self.content = path
+            self._prepare_fn = _download
+
+    def _download_media(self, item: dict, media_type: int, cdn_base_url: str) -> str:
+        """Download media from CDN, returns local file path or empty string."""
+        type_key_map = {
+            ITEM_IMAGE: "image_item",
+            ITEM_VIDEO: "video_item",
+            ITEM_FILE: "file_item",
+            ITEM_VOICE: "voice_item",
+        }
+        key = type_key_map.get(media_type, "")
+        info = item.get(key, {})
+        media = info.get("media", {})
+
+        encrypt_param = media.get("encrypt_query_param", "")
+        # aes_key can be in image_item.aeskey (hex) or media.aes_key (b64)
+        aes_key = info.get("aeskey", "") or media.get("aes_key", "")
+
+        if not encrypt_param or not aes_key:
+            logger.warning(f"[Weixin] Missing CDN params for media download (type={media_type})")
+            return ""
+
+        if media_type == ITEM_FILE:
+            original_name = info.get("file_name", "")
+            if original_name:
+                save_path = os.path.join(_get_tmp_dir(), original_name)
+            else:
+                save_path = os.path.join(_get_tmp_dir(), f"wx_{self.msg_id}.bin")
+        else:
+            ext_map = {ITEM_IMAGE: ".jpg", ITEM_VIDEO: ".mp4", ITEM_VOICE: ".silk"}
+            ext = ext_map.get(media_type, "")
+            save_path = os.path.join(_get_tmp_dir(), f"wx_{self.msg_id}{ext}")
+
+        try:
+            download_media_from_cdn(cdn_base_url, encrypt_param, aes_key, save_path)
+            logger.info(f"[Weixin] Media downloaded: {save_path}")
+            return save_path
+        except Exception as e:
+            logger.error(f"[Weixin] Media download failed: {e}")
+            return ""
diff --git a/cli/VERSION b/cli/VERSION
new file mode 100644
index 0000000..ac2cdeb
--- /dev/null
+++ b/cli/VERSION
@@ -0,0 +1 @@
+2.1.3
diff --git a/cli/__init__.py b/cli/__init__.py
new file mode 100644
index 0000000..f3bda36
--- /dev/null
+++ b/cli/__init__.py
@@ -0,0 +1,13 @@
+"""CowAgent CLI - Manage your CowAgent from the command line."""
+
+import os as _os
+
+def _read_version():
+    version_file = _os.path.join(_os.path.dirname(_os.path.abspath(__file__)), "VERSION")
+    try:
+        with open(version_file, "r") as f:
+            return f.read().strip()
+    except FileNotFoundError:
+        return "0.0.0"
+
+__version__ = _read_version()
diff --git a/cli/__main__.py b/cli/__main__.py
new file mode 100644
index 0000000..b7b74d6
--- /dev/null
+++ b/cli/__main__.py
@@ -0,0 +1,4 @@
+"""Allow running as: python -m cli"""
+from cli.cli import main
+
+main()
diff --git a/cli/cli.py b/cli/cli.py
new file mode 100644
index 0000000..b266b37
--- /dev/null
+++ b/cli/cli.py
@@ -0,0 +1,81 @@
+"""CowAgent CLI entry point."""
+
+import click
+from cli import __version__
+from cli.commands.skill import skill
+from cli.commands.process import start, stop, restart, self_restart, update, status, logs
+from cli.commands.context import context
+from cli.commands.install import install_browser
+from cli.commands.knowledge import knowledge
+
+
+HELP_TEXT = """Usage: cow COMMAND [ARGS]...
+
+  CowAgent CLI - Manage your CowAgent instance.
+
+Commands:
+  help     Show this message.
+  version  Show the version.
+  start    Start CowAgent.
+  stop     Stop CowAgent.
+  restart  Restart CowAgent.
+  update   Update CowAgent and restart.
+  status   Show CowAgent running status.
+  logs     View CowAgent logs.
+  skill    Manage CowAgent skills.
+  knowledge  Manage knowledge base.
+  install-browser  Install browser tool (Playwright + Chromium).
+
+Tip: Memory index management lives in chat — send /memory status or
+/memory rebuild-index to the running agent."""
+
+
+class CowCLI(click.Group):
+
+    def format_help(self, ctx, formatter):
+        formatter.write(HELP_TEXT.strip())
+        formatter.write("\n")
+
+    def parse_args(self, ctx, args):
+        if args and args[0] == 'help':
+            click.echo(HELP_TEXT.strip())
+            ctx.exit(0)
+        return super().parse_args(ctx, args)
+
+
+@click.group(cls=CowCLI, invoke_without_command=True, context_settings=dict(help_option_names=[]))
+@click.pass_context
+def main(ctx):
+    """CowAgent CLI - Manage your CowAgent instance."""
+    if ctx.invoked_subcommand is None:
+        click.echo(HELP_TEXT.strip())
+
+
+@main.command()
+def version():
+    """Show the version."""
+    click.echo(f"cow {__version__}")
+
+
+@main.command(name='help')
+@click.pass_context
+def help_cmd(ctx):
+    """Show this message."""
+    click.echo(HELP_TEXT.strip())
+
+
+main.add_command(skill)
+main.add_command(start)
+main.add_command(stop)
+main.add_command(restart)
+main.add_command(self_restart)
+main.add_command(update)
+main.add_command(status)
+main.add_command(logs)
+main.add_command(context)
+main.add_command(knowledge)
+main.add_command(install_browser)
+
+
+if __name__ == '__main__':
+    main()
diff --git a/cli/commands/__init__.py b/cli/commands/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/cli/commands/context.py b/cli/commands/context.py
new file mode 100644
index 0000000..3886458
--- /dev/null
+++ b/cli/commands/context.py
@@ -0,0 +1,29 @@
+"""cow context - Context management commands."""
+
+import click
+
+
+CHAT_HINT = (
+    "Context commands operate on the running agent's memory.\n"
+    "Please send the command in a chat conversation instead:\n\n"
+    "  /context        - View current context info\n"
+    "  /context clear  - Clear conversation context"
+)
+
+
+@click.group(invoke_without_command=True)
+@click.pass_context
+def context(ctx):
+    """View or manage conversation context.
+
+    Context commands need access to the running agent's memory.
+    Use them in chat conversations: /context or /context clear
+    """
+    if ctx.invoked_subcommand is None:
+        click.echo(f"\n  {CHAT_HINT}\n")
+
+
+@context.command()
+def clear():
+    """Clear conversation context (messages history)."""
+    click.echo(f"\n  {CHAT_HINT}\n")
diff --git a/cli/commands/install.py b/cli/commands/install.py
new file mode 100644
index 0000000..442694d
--- /dev/null
+++ b/cli/commands/install.py
@@ -0,0 +1,317 @@
+"""cow install-browser - Install Playwright + Chromium for the browser tool."""
+
+import os
+import sys
+import subprocess
+from typing import Callable, Optional
+
+import click
+
+PLAYWRIGHT_VERSION = "1.52.0"
+PLAYWRIGHT_LEGACY_VERSION = "1.28.0"
+GLIBC_THRESHOLD = (2, 28)
+CHINA_MIRROR = "https://registry.npmmirror.com/-/binary/playwright"
+
+# stream(msg, fg=None) — fg is "yellow" | "green" | "red" | None
+StreamFn = Callable[[str, Optional[str]], None]
+# on_phase(msg) — coarse-grained progress for chat channels (localized via i18n)
+PhaseFn = Callable[[str], None]
+
+
+def _phase(cb: Optional[PhaseFn], msg: str) -> None:
+    if cb:
+        cb(msg)
+
+
+def _has_display() -> bool:
+    """Check if a graphical display is available (Linux only)."""
+    return bool(os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY"))
+
+
+def _is_headless_linux() -> bool:
+    return sys.platform == "linux" and not _has_display()
+
+
+def _get_installed_version() -> str:
+    try:
+        out = subprocess.check_output(
+            [sys.executable, "-c", "import playwright; print(playwright.__version__)"],
+            stderr=subprocess.DEVNULL,
+        )
+        return out.decode().strip()
+    except Exception:
+        return ""
+
+
+def _version_tuple(v: str):
+    try:
+        return tuple(int(x) for x in v.split(".")[:3])
+    except (ValueError, AttributeError):
+        return (0, 0, 0)
+
+
+def _get_glibc_version():
+    if sys.platform != "linux":
+        return None
+    try:
+        import ctypes
+        libc = ctypes.CDLL("libc.so.6")
+        gnu_get_libc_version = libc.gnu_get_libc_version
+        gnu_get_libc_version.restype = ctypes.c_char_p
+        ver = gnu_get_libc_version().decode()
+        parts = ver.split(".")
+        return (int(parts[0]), int(parts[1]))
+    except Exception:
+        return None
+
+
+def _is_china_network() -> bool:
+    try:
+        out = subprocess.check_output(
+            [sys.executable, "-m", "pip", "config", "get", "global.index-url"],
+            stderr=subprocess.DEVNULL,
+        )
+        url = out.decode().strip().lower()
+        return any(kw in url for kw in ("tsinghua", "aliyun", "npmmirror", "douban", "ustc", "huawei", "tencentyun"))
+    except Exception:
+        return False
+
+
+def _pip_install(package_spec: str, stream: StreamFn) -> int:
+    """Install a package, preferring prebuilt wheels; retry with --user on perm error."""
+    python = sys.executable
+    base = [python, "-m", "pip", "install", "--prefer-binary"]
+    ret = subprocess.call(base + [package_spec])
+    if ret != 0:
+        stream("  Retrying with --user flag...", "yellow")
+        ret = subprocess.call(base + ["--user", package_spec])
+    return ret
+
+
+def _default_stream(msg: str, fg: Optional[str] = None) -> None:
+    """CLI: colored click output."""
+    if fg == "yellow":
+        click.echo(click.style(msg, fg="yellow"))
+    elif fg == "green":
+        click.echo(click.style(msg, fg="green"))
+    elif fg == "red":
+        click.echo(click.style(msg, fg="red"))
+    else:
+        click.echo(msg)
+
+
+def run_install_browser(
+    stream: Optional[StreamFn] = None,
+    on_phase: Optional[PhaseFn] = None,
+) -> int:
+    """
+    Install Playwright Python package, optional Linux deps, and Chromium.
+
+    Reused by ``cow install-browser`` CLI and chat ``/install-browser``.
+
+    Args:
+        stream: Optional callback ``(message, fg)`` for each line. ``fg`` is
+            ``yellow`` / ``green`` / ``red`` or None. Defaults to colored click output.
+        on_phase: Optional callback for coarse progress (e.g. push to chat);
+            messages are short status lines localized via i18n.
+
+    Returns:
+        0 on success, 1 on fatal failure (pip or chromium install failed).
+    """
+    from cli.utils import get_cli_language
+
+    # Import `common` only after get_cli_language() runs ensure_sys_path(),
+    # so it works when `cow` is invoked from outside the project directory.
+    get_cli_language()  # resolve cow_lang so i18n.t reflects config
+    from common import i18n
+    _t = i18n.t
+
+    stream = stream or _default_stream
+    python = sys.executable
+    legacy_mode = False
+
+    _phase(on_phase, _t(
+        "🔧 开始安装浏览器工具依赖（约几分钟，请耐心等待）…",
+        "🔧 Installing browser tool dependencies (a few minutes, please wait)…",
+    ))
+
+    glibc = _get_glibc_version()
+    if glibc and glibc < GLIBC_THRESHOLD:
+        legacy_mode = True
+        glibc_str = f"{glibc[0]}.{glibc[1]}"
+        stream(
+            f"glibc {glibc_str} detected (< 2.28). "
+            f"Will install playwright {PLAYWRIGHT_LEGACY_VERSION} for compatibility.",
+            "yellow",
+        )
+        stream("  Note: upgrade your OS for full browser tool support.", "yellow")
+        stream("")
+        _phase(
+            on_phase,
+            _t(
+                f"ℹ️ 检测到 glibc {glibc_str}（较旧），将安装兼容版 Playwright {PLAYWRIGHT_LEGACY_VERSION}。",
+                f"ℹ️ Detected glibc {glibc_str} (older); installing compatible Playwright {PLAYWRIGHT_LEGACY_VERSION}.",
+            ),
+        )
+
+    target_version = PLAYWRIGHT_LEGACY_VERSION if legacy_mode else PLAYWRIGHT_VERSION
+
+    # Windows-only: greenlet 3.2.x ships no Windows wheel, so pip would build it
+    # from source (needs MSVC) and fail. Pre-install 3.1.x (has win wheels for
+    # py3.7-3.13) which still satisfies playwright's greenlet>=3.1.1,<4.
+    if sys.platform == "win32":
+        stream("[1/3] Pre-installing greenlet (prebuilt wheel) for Windows...", "yellow")
+        ret = subprocess.call(
+            [python, "-m", "pip", "install", "--only-binary=:all:", "greenlet>=3.1.1,<3.2"]
+        )
+        if ret != 0:
+            stream(
+                "  Could not pre-install a prebuilt greenlet wheel.\n"
+                "  playwright may try to build greenlet from source, which needs\n"
+                "  Microsoft C++ Build Tools: https://visualstudio.microsoft.com/visual-cpp-build-tools/",
+                "yellow",
+            )
+
+    _phase(on_phase, _t("📦 [1/3] 正在安装 Playwright Python 包…", "📦 [1/3] Installing Playwright Python package…"))
+    stream("[1/3] Installing playwright Python package...", "yellow")
+    ret = _pip_install(f"playwright=={target_version}", stream)
+    if ret != 0:
+        stream("Failed to install playwright package.", "red")
+        _phase(on_phase, _t("❌ [1/3] Playwright Python 包安装失败。", "❌ [1/3] Failed to install Playwright Python package."))
+        return 1
+
+    installed = _get_installed_version()
+    if installed:
+        stream(f"  playwright {installed} installed.", "green")
+    stream("")
+    _phase(on_phase, _t(
+        f"✅ [1/3] Playwright 包已安装（{installed or target_version}）。",
+        f"✅ [1/3] Playwright package installed ({installed or target_version}).",
+    ))
+
+    if sys.platform == "linux":
+        _phase(on_phase, _t(
+            "🔧 [2/3] 正在安装 Linux 系统依赖与轻量中文字体（文泉驿正黑，部分步骤可能需要 sudo）…",
+            "🔧 [2/3] Installing Linux system deps and a lightweight CJK font (WenQuanYi Zen Hei; some steps may need sudo)…",
+        ))
+        stream("[2/3] Installing system dependencies (Linux)...", "yellow")
+        ret = subprocess.call([python, "-m", "playwright", "install-deps", "chromium"])
+        if ret != 0:
+            stream(
+                "  Could not auto-install system deps (may need sudo).\n"
+                f"  Run manually: sudo {python} -m playwright install-deps chromium",
+                "yellow",
+            )
+        # Prefer fonts-wqy-zenhei only (~few MB). fonts-noto-cjk is much larger (~150MB+).
+        stream("  Installing CJK font (fonts-wqy-zenhei, lightweight)...")
+        font_ret = subprocess.call(
+            ["sudo", "apt-get", "install", "-y", "--no-install-recommends", "fonts-wqy-zenhei"],
+            stderr=subprocess.DEVNULL,
+        )
+        if font_ret != 0:
+            stream(
+                "  Could not auto-install CJK font.\n"
+                "  Run manually: sudo apt-get install -y fonts-wqy-zenhei\n"
+                "  (Optional, larger full coverage: sudo apt-get install -y fonts-noto-cjk)",
+                "yellow",
+            )
+        else:
+            subprocess.call(["fc-cache", "-fv"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+            stream("  CJK font (wqy-zenhei) installed.", "green")
+        _phase(
+            on_phase,
+            _t(
+                "✅ [2/3] Linux 依赖与字体步骤已执行（若有权限问题请查看服务器日志或手动执行提示命令）。",
+                "✅ [2/3] Linux deps and font steps executed (on permission issues, check the server log or run the suggested commands manually).",
+            ),
+        )
+    else:
+        stream(f"[2/3] Skipping system deps (not needed on {sys.platform}).", "yellow")
+        _phase(on_phase, _t(
+            f"ℹ️ [2/3] 当前系统（{sys.platform}）跳过 Linux 专用依赖。",
+            f"ℹ️ [2/3] Skipping Linux-specific deps on this platform ({sys.platform}).",
+        ))
+    stream("")
+
+    _phase(on_phase, _t(
+        "🌐 [3/3] 正在下载并安装 Chromium（体积较大，请耐心等待）…",
+        "🌐 [3/3] Downloading and installing Chromium (large download, please wait)…",
+    ))
+    stream("[3/3] Installing Chromium browser...", "yellow")
+    cmd = [python, "-m", "playwright", "install", "chromium"]
+
+    if _is_headless_linux() and not legacy_mode:
+        ver = _version_tuple(installed or "")
+        if ver >= (1, 57, 0):
+            cmd.append("--only-shell")
+            stream("  (headless shell for Linux server)", None)
+        else:
+            stream("  (full Chromium)", None)
+    elif sys.platform == "linux" and _has_display():
+        stream("  (full browser for Linux desktop)", None)
+
+    env = os.environ.copy()
+    use_mirror = _is_china_network()
+    if use_mirror:
+        env["PLAYWRIGHT_DOWNLOAD_HOST"] = CHINA_MIRROR
+        stream(f"  (using China mirror: {CHINA_MIRROR})", None)
+        _phase(on_phase, _t(
+            "📡 检测到国内 pip 源配置，Chromium 将优先走国内镜像下载。",
+            "📡 Detected a China pip mirror; Chromium will be downloaded from the China mirror first.",
+        ))
+
+    ret = subprocess.call(cmd, env=env)
+
+    if ret != 0 and use_mirror:
+        stream("  Mirror download failed, retrying with official CDN...", "yellow")
+        _phase(on_phase, _t(
+            "⚠️ 镜像下载失败，正在改用官方源重试…",
+            "⚠️ Mirror download failed; retrying with the official CDN…",
+        ))
+        env_no_mirror = os.environ.copy()
+        env_no_mirror.pop("PLAYWRIGHT_DOWNLOAD_HOST", None)
+        ret = subprocess.call(cmd, env=env_no_mirror)
+
+    if ret != 0:
+        stream("Failed to install Chromium.", "red")
+        _phase(on_phase, _t("❌ [3/3] Chromium 安装失败。", "❌ [3/3] Failed to install Chromium."))
+        return 1
+
+    stream("")
+    _phase(on_phase, _t("✅ [3/3] Chromium 已安装。", "✅ [3/3] Chromium installed."))
+
+    stream("Verifying browser installation...", None)
+    _phase(on_phase, _t("🔍 正在验证 Playwright 能否正常加载…", "🔍 Verifying that Playwright loads correctly…"))
+    ret = subprocess.call(
+        [python, "-c", "from playwright.sync_api import sync_playwright; print('OK')"],
+        stderr=subprocess.DEVNULL,
+    )
+    if ret != 0:
+        stream(
+            "  Warning: playwright import failed. Browser tool may not work on this system.\n"
+            "  Consider upgrading your OS or using Docker.",
+            "yellow",
+        )
+        _phase(on_phase, _t(
+            "⚠️ 验证未完全通过：本机可能仍无法使用浏览器工具，请查看日志或升级系统。",
+            "⚠️ Verification did not fully pass: the browser tool may still not work here; check the log or upgrade your system.",
+        ))
+    else:
+        stream("  Verification passed.", "green")
+        _phase(on_phase, _t("✅ 验证通过。", "✅ Verification passed."))
+
+    stream("")
+    stream("Browser tool ready! Restart CowAgent to enable it.", "green")
+    _phase(on_phase, _t(
+        "🎉 全部步骤结束。请重启 CowAgent 后使用 browser 工具。",
+        "🎉 All steps finished. Restart CowAgent to use the browser tool.",
+    ))
+    return 0
+
+
+@click.command("install-browser")
+def install_browser():
+    """Install browser tool dependencies (Playwright + Chromium)."""
+    code = run_install_browser()
+    if code != 0:
+        raise SystemExit(code)
diff --git a/cli/commands/knowledge.py b/cli/commands/knowledge.py
new file mode 100644
index 0000000..296ca6c
--- /dev/null
+++ b/cli/commands/knowledge.py
@@ -0,0 +1,121 @@
+"""cow knowledge - Knowledge base management commands."""
+
+import os
+
+import click
+
+from cli.utils import get_project_root
+
+
+def _get_knowledge_dir():
+    """Resolve the knowledge directory path from config or default."""
+    try:
+        import sys
+        sys.path.insert(0, get_project_root())
+        from config import conf
+        from common.utils import expand_path
+        workspace = expand_path(conf().get("agent_workspace", "~/cow"))
+    except Exception:
+        workspace = os.path.expanduser("~/cow")
+    return os.path.join(workspace, "knowledge")
+
+
+def _get_knowledge_enabled():
+    try:
+        import sys
+        sys.path.insert(0, get_project_root())
+        from config import conf
+        return conf().get("knowledge", True)
+    except Exception:
+        return True
+
+
+@click.group(invoke_without_command=True)
+@click.pass_context
+def knowledge(ctx):
+    """Manage CowAgent knowledge base."""
+    if ctx.invoked_subcommand is None:
+        click.echo(_stats())
+
+
+@knowledge.command("list")
+def knowledge_list():
+    """Display knowledge base file tree."""
+    click.echo(_tree())
+
+
+def _stats() -> str:
+    knowledge_dir = _get_knowledge_dir()
+    if not os.path.isdir(knowledge_dir):
+        return "Knowledge base directory not found."
+
+    enabled = _get_knowledge_enabled()
+    total_files = 0
+    total_bytes = 0
+    cat_count = {}
+
+    for root, dirs, files in os.walk(knowledge_dir):
+        dirs[:] = [d for d in dirs if not d.startswith(".")]
+        rel_root = os.path.relpath(root, knowledge_dir)
+        category = rel_root.split(os.sep)[0] if rel_root != "." else "root"
+        for f in files:
+            if f.endswith(".md") and f not in ("index.md", "log.md"):
+                total_files += 1
+                total_bytes += os.path.getsize(os.path.join(root, f))
+                cat_count[category] = cat_count.get(category, 0) + 1
+
+    status_icon = click.style("enabled", fg="green") if enabled else click.style("disabled", fg="red")
+    lines = [
+        f"\n  Knowledge Base  [{status_icon}]",
+        "",
+        f"  Pages:  {total_files}",
+        f"  Size:   {total_bytes / 1024:.1f} KB",
+        "",
+    ]
+    if cat_count:
+        lines.append("  Categories:")
+        for cat in sorted(cat_count.keys()):
+            lines.append(f"    {cat}/  ({cat_count[cat]} pages)")
+        lines.append("")
+
+    lines.append(f"  Path: {knowledge_dir}")
+    lines.append("")
+    return "\n".join(lines)
+
+
+def _tree() -> str:
+    knowledge_dir = _get_knowledge_dir()
+    if not os.path.isdir(knowledge_dir):
+        return "Knowledge base directory not found."
+
+    tree_lines = ["  knowledge/"]
+
+    subdirs = sorted([
+        d for d in os.listdir(knowledge_dir)
+        if os.path.isdir(os.path.join(knowledge_dir, d)) and not d.startswith(".")
+    ])
+
+    for i, subdir in enumerate(subdirs):
+        is_last_dir = (i == len(subdirs) - 1)
+        branch = "└── " if is_last_dir else "├── "
+        subdir_path = os.path.join(knowledge_dir, subdir)
+        md_files = sorted([
+            f for f in os.listdir(subdir_path)
+            if f.endswith(".md") and not f.startswith(".")
+        ])
+        tree_lines.append(f"  {branch}{subdir}/ ({len(md_files)})")
+
+        child_prefix = "      " if is_last_dir else "  │   "
+        max_show = 15
+        for j, fname in enumerate(md_files[:max_show]):
+            is_last_file = (j == len(md_files[:max_show]) - 1) and len(md_files) <= max_show
+            fb = "└── " if is_last_file else "├── "
+            name = fname.replace(".md", "")
+            tree_lines.append(f"{child_prefix}{fb}{name}")
+        if len(md_files) > max_show:
+            tree_lines.append(f"{child_prefix}└── ... +{len(md_files) - max_show} more")
+
+    if not subdirs:
+        tree_lines.append("  (empty)")
+
+    return "\n" + "\n".join(tree_lines) + "\n"
diff --git a/cli/commands/process.py b/cli/commands/process.py
new file mode 100644
index 0000000..c7f9844
--- /dev/null
+++ b/cli/commands/process.py
@@ -0,0 +1,468 @@
+"""cow start/stop/restart/status/logs - Process management commands."""
+
+import os
+import sys
+import subprocess
+import time
+from typing import Optional
+
+import click
+
+from cli.utils import get_project_root, load_config_json
+
+_IS_WIN = sys.platform == "win32"
+
+
+def _is_terminal_only() -> bool:
+    """Whether terminal is the only configured channel.
+
+    Terminal needs an interactive stdin/tty, which is incompatible with the
+    background daemon mode (stdout/stdin detached). When terminal is the only
+    channel, `start` must run in the foreground so it can own the tty.
+    """
+    channel = load_config_json().get("channel_type", "")
+    if isinstance(channel, str):
+        names = [c.strip() for c in channel.split(",") if c.strip()]
+    elif isinstance(channel, (list, tuple)):
+        names = [str(c).strip() for c in channel if str(c).strip()]
+    else:
+        names = []
+    return names == ["terminal"]
+
+
+def _get_pid_file():
+    return os.path.join(get_project_root(), ".cow.pid")
+
+
+def _get_log_file():
+    return os.path.join(get_project_root(), "nohup.out")
+
+
+def _is_pid_alive(pid: int) -> bool:
+    """Check whether a process is still running (cross-platform)."""
+    if _IS_WIN:
+        try:
+            out = subprocess.check_output(
+                ["tasklist", "/FI", f"PID eq {pid}", "/NH"],
+                stderr=subprocess.DEVNULL,
+            )
+            return str(pid) in out.decode(errors="ignore")
+        except Exception:
+            return False
+    else:
+        try:
+            os.kill(pid, 0)
+            return True
+        except (ProcessLookupError, PermissionError):
+            return False
+
+
+def _kill_pid(pid: int, force: bool = False):
+    """Terminate a process by PID (cross-platform)."""
+    if _IS_WIN:
+        flag = "/F" if force else ""
+        cmd = ["taskkill"]
+        if force:
+            cmd.append("/F")
+        cmd.extend(["/PID", str(pid)])
+        subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    else:
+        import signal
+        sig = signal.SIGKILL if force else signal.SIGTERM
+        os.kill(pid, sig)
+
+
+def _read_pid() -> Optional[int]:
+    pid_file = _get_pid_file()
+    if not os.path.exists(pid_file):
+        return None
+    try:
+        with open(pid_file, "r") as f:
+            pid = int(f.read().strip())
+        if _is_pid_alive(pid):
+            return pid
+        os.remove(pid_file)
+        return None
+    except (ValueError, OSError):
+        try:
+            os.remove(pid_file)
+        except OSError:
+            pass
+        return None
+
+
+def _write_pid(pid: int):
+    with open(_get_pid_file(), "w") as f:
+        f.write(str(pid))
+
+
+def _remove_pid():
+    pid_file = _get_pid_file()
+    if os.path.exists(pid_file):
+        os.remove(pid_file)
+
+
+@click.command()
+@click.option("--foreground", "-f", is_flag=True, help="Run in foreground (don't daemonize)")
+@click.option("--no-logs", is_flag=True, help="Don't tail logs after starting")
+def start(foreground, no_logs):
+    """Start CowAgent."""
+    pid = _read_pid()
+    if pid:
+        click.echo(f"CowAgent is already running (PID: {pid}).")
+        return
+
+    root = get_project_root()
+    app_py = os.path.join(root, "app.py")
+    if not os.path.exists(app_py):
+        click.echo("Error: app.py not found in project root.", err=True)
+        sys.exit(1)
+
+    python = sys.executable
+
+    # Terminal-only setups need an interactive tty; force foreground so the
+    # terminal channel can read stdin instead of fighting the shell over the tty.
+    if not foreground and _is_terminal_only():
+        foreground = True
+        click.echo("Detected terminal-only channel, starting in foreground...")
+
+    if foreground:
+        click.echo("Starting CowAgent in foreground...")
+        if _IS_WIN:
+            sys.exit(subprocess.call([python, app_py], cwd=root))
+        else:
+            os.execv(python, [python, app_py])
+    else:
+        log_file = _get_log_file()
+        click.echo("Starting CowAgent...")
+
+        popen_kwargs = dict(cwd=root)
+        if _IS_WIN:
+            CREATE_NO_WINDOW = 0x08000000
+            popen_kwargs["creationflags"] = (
+                subprocess.CREATE_NEW_PROCESS_GROUP | CREATE_NO_WINDOW
+            )
+        else:
+            popen_kwargs["start_new_session"] = True
+
+        with open(log_file, "a") as log:
+            proc = subprocess.Popen(
+                [python, app_py],
+                stdout=log,
+                stderr=log,
+                **popen_kwargs,
+            )
+        _write_pid(proc.pid)
+        click.echo(click.style(f"✓ CowAgent started (PID: {proc.pid})", fg="green"))
+        click.echo(f"  Logs: {log_file}")
+
+        if not no_logs:
+            click.echo("  Press Ctrl+C to stop tailing logs.\n")
+            _tail_log(log_file)
+
+
+@click.command()
+def stop():
+    """Stop CowAgent."""
+    pid = _read_pid()
+    if not pid:
+        click.echo("CowAgent is not running.")
+        return
+
+    click.echo(f"Stopping CowAgent (PID: {pid})...")
+    try:
+        _kill_pid(pid)
+        for _ in range(30):
+            time.sleep(0.1)
+            if not _is_pid_alive(pid):
+                break
+        else:
+            _kill_pid(pid, force=True)
+    except (ProcessLookupError, OSError):
+        pass
+
+    _remove_pid()
+    click.echo(click.style("✓ CowAgent stopped.", fg="green"))
+
+
+@click.command()
+@click.option("--no-logs", is_flag=True, help="Don't tail logs after restarting")
+@click.pass_context
+def restart(ctx, no_logs):
+    """Restart CowAgent."""
+    ctx.invoke(stop)
+    time.sleep(1)
+    ctx.invoke(start, no_logs=no_logs)
+
+
+# Detached relay that survives the caller's process tree. Run via `python -c`
+# with start_new_session=True so it keeps going after the agent's bash child
+# (and the main app it kills) both die. Flow: self-check the new code FIRST
+# (import app); abort without touching the old process if it fails. Only when
+# the new code is loadable does it SIGTERM the old PID, wait for exit (SIGKILL
+# fallback), then start a fresh app.py and write the pid.
+_RELAY_SCRIPT = r"""
+import os, sys, time, signal, subprocess
+
+root, python, app_py, pid_file, log_file = sys.argv[1:6]
+old_pid = int(sys.argv[6]) if len(sys.argv) > 6 and sys.argv[6] else 0
+
+
+def alive(pid):
+    if not pid:
+        return False
+    try:
+        os.kill(pid, 0)
+        return True
+    except OSError:
+        return False
+
+
+def log(msg):
+    try:
+        with open(log_file, "a") as f:
+            f.write("[self-restart] " + msg + "\n")
+    except OSError:
+        pass
+
+
+# 0) Self-check: make sure the new code actually loads BEFORE killing anything.
+# `import app` exercises top-level imports / syntax of the entry module. If it
+# fails, abort and leave the running service untouched — never end up with the
+# old process killed and the new one unable to start.
+check = subprocess.run(
+    [python, "-c", "import app"], cwd=root,
+    stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
+)
+if check.returncode != 0:
+    detail = (check.stdout or b"").decode("utf-8", "replace").strip()
+    log("self-check FAILED, aborting restart; service left running:\n" + detail)
+    sys.exit(1)
+log("self-check passed")
+
+# 1) Ask the old process to exit gracefully (its SIGTERM handler persists state).
+if alive(old_pid):
+    try:
+        os.kill(old_pid, signal.SIGTERM)
+    except OSError:
+        pass
+    # 2) Wait up to ~15s for it to go, then force-kill as a backstop.
+    for _ in range(150):
+        if not alive(old_pid):
+            break
+        time.sleep(0.1)
+    else:
+        try:
+            os.kill(old_pid, signal.SIGKILL)
+        except OSError:
+            pass
+        time.sleep(0.5)
+
+# 3) Start a fresh instance, detached, logging to the same file.
+with open(log_file, "a") as f:
+    proc = subprocess.Popen(
+        [python, app_py], cwd=root,
+        stdout=f, stderr=f, start_new_session=True,
+    )
+with open(pid_file, "w") as f:
+    f.write(str(proc.pid))
+log("restarted, new pid=" + str(proc.pid))
+"""
+
+
+@click.command(name="self-restart", hidden=True)
+def self_restart():
+    """Restart from inside the running agent (detached; survives parent death).
+
+    Intended to be invoked by the agent itself (e.g. via bash after editing its
+    own code), not by users — so it is hidden from `cow help`. Unlike `restart`,
+    the actual stop+start runs in a detached relay process that outlives the
+    agent's bash child, which would otherwise die together with the main app it
+    kills.
+    """
+    if _IS_WIN:
+        click.echo("self-restart is not supported on Windows; use `cow restart`.", err=True)
+        sys.exit(1)
+
+    root = get_project_root()
+    app_py = os.path.join(root, "app.py")
+    if not os.path.exists(app_py):
+        click.echo("Error: app.py not found in project root.", err=True)
+        sys.exit(1)
+
+    python = sys.executable
+    pid = _read_pid() or 0
+
+    subprocess.Popen(
+        [
+            python, "-c", _RELAY_SCRIPT,
+            root, python, app_py, _get_pid_file(), _get_log_file(), str(pid),
+        ],
+        cwd=root,
+        start_new_session=True,
+        stdout=subprocess.DEVNULL,
+        stderr=subprocess.DEVNULL,
+    )
+    click.echo(click.style(
+        "✓ Restart scheduled. The service will stop and come back in a few seconds.",
+        fg="green",
+    ))
+
+
+@click.command()
+@click.pass_context
+def update(ctx):
+    """Update CowAgent and restart."""
+    root = get_project_root()
+
+    # 1. Stop service first so git pull won't conflict with running code
+    ctx.invoke(stop)
+
+    # 2. Git pull
+    if os.path.isdir(os.path.join(root, ".git")):
+        click.echo("Pulling latest code...")
+        ret = subprocess.call(["git", "pull"], cwd=root)
+        if ret != 0:
+            click.echo("Error: git pull failed.", err=True)
+            sys.exit(1)
+    else:
+        click.echo("Not a git repository, skipping code update.")
+
+    python = sys.executable
+    req_file = os.path.join(root, "requirements.txt")
+
+    if _IS_WIN:
+        # On Windows, `cow.exe` (this process) locks the exe file, so
+        # `pip install -e .` fails with WinError 5.  Write a small .bat
+        # helper that waits for cow.exe to exit, then installs & starts.
+        bat = os.path.join(root, "_cow_update.bat")
+        lines = [
+            "@echo off",
+            "chcp 65001 >nul",
+            "echo Waiting for cow.exe to exit...",
+            "timeout /t 3 /nobreak >nul",
+        ]
+        if os.path.exists(req_file):
+            lines.append(f'echo Installing dependencies...')
+            lines.append(f'"{python}" -m pip install -r requirements.txt -q')
+        lines += [
+            "echo Reinstalling cow CLI...",
+            f'"{python}" -m pip install -e . -q',
+            "echo Starting CowAgent...",
+            f'"{python}" -m cli.cli start --no-logs',
+            "echo.",
+            "echo Update complete. You can close this window.",
+            "pause >nul",
+            "del \"%~f0\"",
+        ]
+        with open(bat, "w", encoding="utf-8") as f:
+            f.write("\n".join(lines) + "\n")
+
+        subprocess.Popen(
+            ["cmd.exe", "/c", "start", "CowAgent Update", "/wait", bat],
+            cwd=root,
+        )
+        click.echo(click.style(
+            "✓ Update script launched. Please follow the new window for progress.",
+            fg="green"))
+    else:
+        # 3. Install dependencies
+        if os.path.exists(req_file):
+            click.echo("Installing dependencies...")
+            subprocess.call(
+                [python, "-m", "pip", "install", "-r", "requirements.txt", "-q"],
+                cwd=root,
+            )
+        click.echo("Reinstalling cow CLI...")
+        subprocess.call(
+            [python, "-m", "pip", "install", "-e", ".", "-q"],
+            cwd=root,
+        )
+
+        # 4. Start service
+        click.echo("")
+        time.sleep(1)
+        ctx.invoke(start, no_logs=False)
+
+
+@click.command()
+def status():
+    """Show CowAgent running status."""
+    from cli import __version__
+    from cli.utils import load_config_json, get_cli_language, get_project_root
+
+    # get_cli_language() calls ensure_sys_path(), which adds the project root
+    # to sys.path. Import `common` only AFTER that, otherwise it fails with
+    # ModuleNotFoundError when `cow` runs from outside the project dir.
+    get_cli_language()  # resolve cow_lang so i18n.t reflects config
+    from common import i18n
+    _t = i18n.t
+
+    pid = _read_pid()
+    if pid:
+        click.echo(click.style(f"● CowAgent is running (PID: {pid})", fg="green"))
+    else:
+        click.echo(click.style("● CowAgent is not running", fg="red"))
+
+    click.echo(_t(f"  版本: v{__version__}", f"  Version: v{__version__}"))
+
+    # Project path bound to this `cow` CLI — disambiguates which checkout the
+    # command actually controls when the user has multiple clones.
+    project_root = get_project_root()
+    click.echo(_t(f"  路径: {project_root}", f"  Path: {project_root}"))
+
+    cfg = load_config_json()
+    if cfg:
+        channel = cfg.get("channel_type", "unknown")
+        if isinstance(channel, list):
+            channel = ", ".join(channel)
+        click.echo(_t(f"  通道: {channel}", f"  Channel: {channel}"))
+        click.echo(_t(f"  模型: {cfg.get('model', 'unknown')}", f"  Model: {cfg.get('model', 'unknown')}"))
+        mode = "Chat" if cfg.get("agent") is False else "Agent"
+        click.echo(_t(f"  模式: {mode}", f"  Mode: {mode}"))
+        lang_label = "中文" if i18n.get_language() == "zh" else "English"
+        click.echo(_t(f"  语言: {lang_label}", f"  Language: {lang_label}"))
+
+
+@click.command()
+@click.option("--follow", "-f", is_flag=True, help="Follow log output")
+@click.option("--lines", "-n", default=50, help="Number of lines to show")
+def logs(follow, lines):
+    """View CowAgent logs."""
+    log_file = _get_log_file()
+    if not os.path.exists(log_file):
+        click.echo("No log file found.")
+        return
+
+    if follow:
+        _tail_log(log_file, lines)
+    else:
+        _print_last_lines(log_file, lines)
+
+
+def _print_last_lines(file_path: str, n: int = 50):
+    """Print the last N lines of a file (cross-platform)."""
+    try:
+        with open(file_path, "r", encoding="utf-8", errors="replace") as f:
+            all_lines = f.readlines()
+        for line in all_lines[-n:]:
+            click.echo(line, nl=False)
+    except Exception as e:
+        click.echo(f"Error reading log file: {e}", err=True)
+
+
+def _tail_log(log_file: str, lines: int = 50):
+    """Follow log file output. Blocks until Ctrl+C (cross-platform)."""
+    _print_last_lines(log_file, lines)
+
+    try:
+        with open(log_file, "r", encoding="utf-8", errors="replace") as f:
+            f.seek(0, 2)
+            while True:
+                line = f.readline()
+                if line:
+                    click.echo(line, nl=False)
+                else:
+                    time.sleep(0.3)
+    except KeyboardInterrupt:
+        pass
diff --git a/cli/commands/skill.py b/cli/commands/skill.py
new file mode 100644
index 0000000..61f92fb
--- /dev/null
+++ b/cli/commands/skill.py
@@ -0,0 +1,1491 @@
+"""cow skill - Skill management commands."""
+
+import os
+import re
+import sys
+import json
+import hashlib
+import shutil
+import zipfile
+import tempfile
+from dataclasses import dataclass, field
+from typing import Optional, List
+
+from urllib.parse import urlparse
+
+import click
+import requests
+
+from cli.utils import (
+    get_project_root,
+    get_skills_dir,
+    get_builtin_skills_dir,
+    load_skills_config,
+    SKILL_HUB_API,
+)
+
+
+# ======================================================================
+# Public types for the core install API (used by CLI and chat plugin)
+# ======================================================================
+
+class SkillInstallError(Exception):
+    """Raised when skill installation fails."""
+    pass
+
+
+@dataclass
+class InstallResult:
+    """Result of a skill installation operation."""
+    installed: List[str] = field(default_factory=list)
+    messages: List[str] = field(default_factory=list)
+    error: Optional[str] = None
+
+
+_SAFE_NAME_RE = re.compile(r"^[a-zA-Z0-9][a-zA-Z0-9_\-]{0,63}$")
+_GITHUB_URL_RE = re.compile(
+    r"^https?://github\.com/([^/]+)/([^/]+?)(?:\.git)?(?:/(?:tree|blob)/([^/]+)(?:/(.+))?)?/?$"
+)
+_GITLAB_URL_RE = re.compile(
+    r"^https?://gitlab\.com/([^/]+)/([^/]+?)(?:\.git)?(?:/-/tree/([^/]+)(?:/(.+))?)?/?$"
+)
+_GIT_SSH_RE = re.compile(
+    r"^git@([^:]+):([^/]+)/([^/]+?)(?:\.git)?$"
+)
+
+
+def _parse_github_url(url: str):
+    """Parse a full GitHub URL into (owner, repo, branch, subpath).
+
+    Returns None if the URL doesn't match.
+    Supported formats:
+      https://github.com/owner/repo
+      https://github.com/owner/repo/tree/branch
+      https://github.com/owner/repo/tree/branch/path/to/skill
+      https://github.com/owner/repo/blob/branch/path/to/skill
+    """
+    m = _GITHUB_URL_RE.match(url.strip())
+    if not m:
+        return None
+    owner, repo, branch, subpath = m.groups()
+    return owner, repo, branch or "main", subpath
+
+
+def _parse_gitlab_url(url: str):
+    """Parse a GitLab URL into (owner, repo, branch, subpath).
+
+    Returns None if the URL doesn't match.
+    Supported formats:
+      https://gitlab.com/owner/repo
+      https://gitlab.com/owner/repo/-/tree/branch
+      https://gitlab.com/owner/repo/-/tree/branch/path/to/skill
+    """
+    m = _GITLAB_URL_RE.match(url.strip())
+    if not m:
+        return None
+    owner, repo, branch, subpath = m.groups()
+    return owner, repo, branch or "main", subpath
+
+
+def _parse_git_ssh_url(url: str):
+    """Parse a git@ SSH URL into (host, owner, repo).
+
+    Returns None if the URL doesn't match.
+    Supported format: git@github.com:owner/repo.git
+    """
+    m = _GIT_SSH_RE.match(url.strip())
+    if not m:
+        return None
+    host, owner, repo = m.groups()
+    return host, owner, repo
+
+
+def _clone_repo(git_url: str):
+    """Shallow-clone a git repo and return (tmp_dir, repo_root).
+
+    Requires git to be installed. The caller must clean up tmp_dir.
+    """
+    tmp_dir = tempfile.mkdtemp(prefix="cow-skill-")
+    repo_dir = os.path.join(tmp_dir, "repo")
+    try:
+        import subprocess
+        subprocess.run(
+            ["git", "clone", "--depth", "1", git_url, repo_dir],
+            check=True, capture_output=True, timeout=30,
+        )
+    except FileNotFoundError:
+        shutil.rmtree(tmp_dir, ignore_errors=True)
+        raise RuntimeError("git is not installed")
+    except Exception as e:
+        shutil.rmtree(tmp_dir, ignore_errors=True)
+        raise RuntimeError(f"git clone failed: {e}")
+    return tmp_dir, repo_dir
+
+
+def _download_repo_zip(spec: str, branch: str = "main", host: str = "github", timeout: int = 30):
+    """Download a GitHub/GitLab repo as zip and extract it.
+
+    Returns (tmp_dir, repo_root) where tmp_dir is the temp directory to clean up
+    and repo_root is the extracted repository root path.
+    """
+    if host == "gitlab":
+        zip_url = f"https://gitlab.com/{spec}/-/archive/{branch}/{spec.split('/')[-1]}-{branch}.zip"
+    else:
+        zip_url = f"https://github.com/{spec}/archive/refs/heads/{branch}.zip"
+    if isinstance(timeout, (list, tuple)):
+        req_timeout = timeout
+    else:
+        req_timeout = (min(timeout, 5), timeout)
+    resp = requests.get(zip_url, timeout=req_timeout, allow_redirects=True)
+    resp.raise_for_status()
+
+    tmp_dir = tempfile.mkdtemp(prefix="cow-skill-")
+    zip_path = os.path.join(tmp_dir, "repo.zip")
+    with open(zip_path, "wb") as f:
+        f.write(resp.content)
+
+    extract_dir = os.path.join(tmp_dir, "extracted")
+    with zipfile.ZipFile(zip_path, "r") as zf:
+        _safe_extractall(zf, extract_dir)
+
+    # GitHub zips have a single top-level dir like "repo-main/"
+    top_items = [d for d in os.listdir(extract_dir) if not d.startswith(".")]
+    if len(top_items) == 1 and os.path.isdir(os.path.join(extract_dir, top_items[0])):
+        return tmp_dir, os.path.join(extract_dir, top_items[0])
+    return tmp_dir, extract_dir
+
+
+def _download_github_dir(owner, repo, branch, subpath, dest_dir):
+    """Download a subdirectory from GitHub using the Contents API.
+
+    Recursively fetches all files under the given subpath and writes them
+    to dest_dir. Used as a fallback when zip download fails.
+    Costs one API request per directory (60/hr unauthenticated).
+    """
+    api_url = f"https://api.github.com/repos/{owner}/{repo}/contents/{subpath}?ref={branch}"
+    resp = requests.get(api_url, timeout=30, headers={"Accept": "application/vnd.github.v3+json"})
+    resp.raise_for_status()
+    items = resp.json()
+
+    if isinstance(items, dict):
+        items = [items]
+
+    for item in items:
+        rel_path = item["path"]
+        if subpath:
+            rel_path = rel_path[len(subpath.strip("/")):].lstrip("/")
+        local_path = os.path.join(dest_dir, rel_path)
+
+        if item["type"] == "file":
+            os.makedirs(os.path.dirname(local_path), exist_ok=True)
+            dl_url = item.get("download_url")
+            if not dl_url:
+                continue
+            file_resp = requests.get(dl_url, timeout=30)
+            file_resp.raise_for_status()
+            with open(local_path, "wb") as f:
+                f.write(file_resp.content)
+        elif item["type"] == "dir":
+            os.makedirs(local_path, exist_ok=True)
+            child_subpath = item["path"]
+            _download_github_dir(owner, repo, branch, child_subpath, dest_dir)
+
+
+# Directories to search for skills following the Agent Skills convention
+_SKILL_SCAN_DIRS = [
+    "skills",
+    "skills/.curated",
+    "skills/.experimental",
+]
+
+_SKILL_SCAN_SKIP = {
+    "node_modules", "__pycache__", ".git", ".github", "venv", ".venv",
+}
+
+
+def _scan_skills_in_repo(repo_root: str) -> list:
+    """Scan a repo for skill directories containing SKILL.md.
+
+    Searches in conventional locations (skills/, skills/.curated/, etc.)
+    and also checks the repo root itself.
+
+    Returns a list of (skill_name, skill_dir_path) tuples.
+    """
+    found = []
+
+    # Check repo root for a SKILL.md (single-skill repo)
+    if os.path.isfile(os.path.join(repo_root, "SKILL.md")):
+        fm = _parse_skill_frontmatter(_read_file_text(os.path.join(repo_root, "SKILL.md")))
+        name = fm.get("name") or os.path.basename(repo_root)
+        found.append((name, repo_root))
+        return found
+
+    for scan_dir in _SKILL_SCAN_DIRS:
+        search_root = os.path.join(repo_root, scan_dir)
+        if not os.path.isdir(search_root):
+            continue
+        for entry in os.listdir(search_root):
+            if entry.startswith(".") and entry not in (".curated", ".experimental"):
+                continue
+            if entry in _SKILL_SCAN_SKIP:
+                continue
+            entry_path = os.path.join(search_root, entry)
+            if os.path.isdir(entry_path) and os.path.isfile(os.path.join(entry_path, "SKILL.md")):
+                fm = _parse_skill_frontmatter(
+                    _read_file_text(os.path.join(entry_path, "SKILL.md"))
+                )
+                name = fm.get("name") or entry
+                found.append((name, entry_path))
+
+    return found
+
+
+def _scan_skills_in_dir(directory: str) -> list:
+    """Scan immediate subdirectories for SKILL.md files.
+
+    Unlike _scan_skills_in_repo which checks conventional locations,
+    this scans all direct children of the given directory.
+    Returns a list of (skill_name, skill_dir_path) tuples.
+    """
+    found = []
+    if not os.path.isdir(directory):
+        return found
+    for entry in os.listdir(directory):
+        if entry.startswith(".") or entry in _SKILL_SCAN_SKIP:
+            continue
+        entry_path = os.path.join(directory, entry)
+        if os.path.isdir(entry_path) and os.path.isfile(os.path.join(entry_path, "SKILL.md")):
+            fm = _parse_skill_frontmatter(
+                _read_file_text(os.path.join(entry_path, "SKILL.md"))
+            )
+            name = fm.get("name") or entry
+            found.append((name, entry_path))
+    return found
+
+
+def _batch_install_skills(discovered, spec, skills_dir, source, result: InstallResult, display_name: str = ""):
+    """Install a list of discovered skills into skills_dir."""
+    single = len(discovered) == 1
+    result.messages.append(f"Found {len(discovered)} skill(s) in {spec}:")
+    for sname, sdir in discovered:
+        safe_name = re.sub(r'[^a-zA-Z0-9_\-]', '-', sname)[:64]
+        if not _SAFE_NAME_RE.match(safe_name):
+            result.messages.append(f"  Skipping '{sname}' (invalid name)")
+            continue
+        target_dir = os.path.join(skills_dir, safe_name)
+        if os.path.exists(target_dir):
+            shutil.rmtree(target_dir)
+        shutil.copytree(sdir, target_dir)
+        _register_installed_skill(safe_name, source=source, display_name=display_name if single else "")
+        result.installed.append(safe_name)
+        result.messages.append(f"  + {safe_name}")
+
+    if result.installed:
+        result.messages.append(f"{len(result.installed)} skill(s) installed from {spec}.")
+    else:
+        result.messages.append("No valid skills found.")
+
+
+def _read_file_text(path: str) -> str:
+    """Read a file as UTF-8 text, returning empty string on failure."""
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            return f.read()
+    except Exception:
+        return ""
+
+
+def _install_local(path: str, result: InstallResult):
+    """Install skill(s) from a local directory."""
+    path = os.path.abspath(os.path.expanduser(path))
+    if not os.path.isdir(path):
+        raise SkillInstallError(f"'{path}' is not a directory.")
+
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+
+    if os.path.isfile(os.path.join(path, "SKILL.md")):
+        fm = _parse_skill_frontmatter(_read_file_text(os.path.join(path, "SKILL.md")))
+        skill_name = fm.get("name") or os.path.basename(path)
+        skill_name = re.sub(r'[^a-zA-Z0-9_\-]', '-', skill_name)[:64]
+        _check_skill_name(skill_name)
+        target_dir = os.path.join(skills_dir, skill_name)
+        if os.path.exists(target_dir):
+            shutil.rmtree(target_dir)
+        shutil.copytree(path, target_dir)
+        _register_installed_skill(skill_name, source="local")
+        result.installed.append(skill_name)
+        result.messages.append(f"Installed '{skill_name}' from local path.")
+        return
+
+    discovered = _scan_skills_in_repo(path) or _scan_skills_in_dir(path)
+    if not discovered:
+        raise SkillInstallError(f"No skills found in '{path}'.")
+
+    _batch_install_skills(discovered, path, skills_dir, "local", result)
+
+
+def _register_installed_skill(name: str, source: str = "cowhub", display_name: str = ""):
+    """Register a newly installed skill into skills_config.json.
+
+    source values: builtin, cow, github, clawhub, linkai, local, url
+    """
+    skills_dir = get_skills_dir()
+    config_path = os.path.join(skills_dir, "skills_config.json")
+
+    config = {}
+    if os.path.exists(config_path):
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                config = json.load(f)
+        except Exception:
+            config = {}
+
+    if name in config:
+        if display_name and not config[name].get("display_name"):
+            config[name]["display_name"] = display_name
+            try:
+                with open(config_path, "w", encoding="utf-8") as f:
+                    json.dump(config, f, indent=4, ensure_ascii=False)
+            except Exception:
+                pass
+        return
+
+    skill_dir = os.path.join(skills_dir, name)
+    description = _read_skill_description(skill_dir) or ""
+
+    entry = {
+        "name": name,
+        "description": description,
+        "source": source,
+        "enabled": True,
+        "category": "skill",
+    }
+    if display_name:
+        entry["display_name"] = display_name
+    config[name] = entry
+
+    try:
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(config, f, indent=4, ensure_ascii=False)
+    except Exception:
+        pass
+
+
+def _parse_skill_frontmatter(content: str) -> dict:
+    """Parse YAML frontmatter from SKILL.md content and return a dict with name/description."""
+    result = {}
+    match = re.match(r'^---\s*\n(.*?)\n---\s*\n', content, re.DOTALL)
+    if not match:
+        return result
+    for line in match.group(1).split('\n'):
+        line = line.strip()
+        for key in ('name', 'description'):
+            if line.startswith(f'{key}:'):
+                val = line[len(key) + 1:].strip()
+                result[key] = val.strip('"').strip("'")
+    return result
+
+
+def _read_skill_description(skill_dir: str) -> str:
+    """Read the description from a skill's SKILL.md frontmatter."""
+    skill_md = os.path.join(skill_dir, "SKILL.md")
+    if not os.path.exists(skill_md):
+        return ""
+    try:
+        with open(skill_md, "r", encoding="utf-8") as f:
+            content = f.read()
+        return _parse_skill_frontmatter(content).get("description", "")
+    except Exception:
+        return ""
+
+
+def _install_url(url: str, result: InstallResult):
+    """Install a skill from a direct SKILL.md URL."""
+    result.messages.append(f"Downloading SKILL.md from {url} ...")
+    try:
+        resp = requests.get(url, timeout=30)
+        resp.raise_for_status()
+    except Exception as e:
+        raise SkillInstallError(f"Failed to download SKILL.md: {e}")
+
+    content = resp.text
+    fm = _parse_skill_frontmatter(content)
+    skill_name = fm.get("name")
+    if not skill_name:
+        raise SkillInstallError("SKILL.md missing 'name' field in frontmatter.")
+
+    skill_name = skill_name.strip()
+    _check_skill_name(skill_name)
+
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+    skill_dir = os.path.join(skills_dir, skill_name)
+
+    if os.path.isdir(skill_dir):
+        result.messages.append(f"Skill '{skill_name}' already exists. Overwriting SKILL.md ...")
+    os.makedirs(skill_dir, exist_ok=True)
+
+    with open(os.path.join(skill_dir, "SKILL.md"), "w", encoding="utf-8") as f:
+        f.write(content)
+
+    _register_installed_skill(skill_name, source="url")
+    result.installed.append(skill_name)
+    result.messages.append(f"Installed '{skill_name}' from URL.")
+
+
+def _install_archive_url(url: str, result: InstallResult):
+    """Install skill(s) from a remote zip/tar.gz archive URL."""
+    parsed = urlparse(url)
+    if parsed.scheme != "https":
+        raise SkillInstallError("Refusing to download from non-HTTPS URL.")
+
+    filename = os.path.basename(parsed.path).split("?")[0]
+    fallback_name = re.sub(r'\.(zip|tar\.gz|tgz)$', '', filename, flags=re.IGNORECASE)
+    if not fallback_name or not _SAFE_NAME_RE.match(fallback_name):
+        fallback_name = "skill-package"
+
+    result.messages.append(f"Downloading archive from {url} ...")
+    try:
+        resp = requests.get(url, timeout=30, allow_redirects=True)
+        resp.raise_for_status()
+    except Exception as e:
+        raise SkillInstallError(f"Failed to download archive: {e}")
+
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+
+    content_type = resp.headers.get("Content-Type", "")
+    lower_url = url.lower()
+
+    if lower_url.endswith((".tar.gz", ".tgz")) or "gzip" in content_type:
+        _install_targz_bytes(resp.content, fallback_name, skills_dir, result)
+    else:
+        _install_zip_bytes(resp.content, fallback_name, skills_dir, result=result, source_label="url")
+
+
+def _install_targz_bytes(content: bytes, name: str, skills_dir: str, result: InstallResult):
+    """Extract a tar.gz archive and install skill(s)."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        tar_path = os.path.join(tmp_dir, "package.tar.gz")
+        with open(tar_path, "wb") as f:
+            f.write(content)
+
+        import tarfile
+        extract_dir = os.path.join(tmp_dir, "extracted")
+        os.makedirs(extract_dir)
+        with tarfile.open(tar_path, "r:gz") as tf:
+            for member in tf.getmembers():
+                resolved = os.path.realpath(os.path.join(extract_dir, member.name))
+                if not resolved.startswith(os.path.realpath(extract_dir)):
+                    raise SkillInstallError("Archive contains path traversal, aborting.")
+            tf.extractall(extract_dir)
+
+        top_items = [d for d in os.listdir(extract_dir) if not d.startswith(".")]
+        pkg_root = extract_dir
+        if len(top_items) == 1 and os.path.isdir(os.path.join(extract_dir, top_items[0])):
+            pkg_root = os.path.join(extract_dir, top_items[0])
+
+        discovered = _scan_skills_in_repo(pkg_root) or _scan_skills_in_dir(pkg_root)
+
+        if discovered and len(discovered) > 1:
+            _batch_install_skills(discovered, name, skills_dir, "url", result)
+            return
+
+        if discovered and len(discovered) == 1:
+            sname, sdir = discovered[0]
+            safe_name = re.sub(r'[^a-zA-Z0-9_\\-]', '-', sname)[:64]
+            if not _SAFE_NAME_RE.match(safe_name):
+                safe_name = name
+            target = os.path.join(skills_dir, safe_name)
+            if os.path.exists(target):
+                shutil.rmtree(target)
+            shutil.copytree(sdir, target)
+            _register_installed_skill(safe_name, source="url")
+            result.installed.append(safe_name)
+            result.messages.append(f"Installed '{safe_name}' from URL.")
+            return
+
+        target = os.path.join(skills_dir, name)
+        if os.path.exists(target):
+            shutil.rmtree(target)
+        shutil.copytree(pkg_root, target)
+        _register_installed_skill(name, source="url")
+        result.installed.append(name)
+        result.messages.append(f"Installed '{name}' from URL.")
+
+
+def _print_install_success(name: str, source: str):
+    """Print a unified install success message with description and source."""
+    from cli.utils import get_cli_language
+
+    # Import `common` only after get_cli_language() runs ensure_sys_path(),
+    # so it works when `cow` is invoked from outside the project directory.
+    get_cli_language()  # resolve cow_lang so i18n.t reflects config
+    from common import i18n
+    _t = i18n.t
+
+    skills_dir = get_skills_dir()
+    config = load_skills_config()
+    display = config.get(name, {}).get("display_name", "")
+    desc = _read_skill_description(os.path.join(skills_dir, name))
+    click.echo(click.style(f"✓ {name}", fg="green"))
+    if display and display != name:
+        click.echo(_t(f"  名称: {display}", f"  Name: {display}"))
+    if desc:
+        if len(desc) > 60:
+            desc = desc[:57] + "…"
+        click.echo(_t(f"  描述: {desc}", f"  Description: {desc}"))
+    click.echo(_t(f"  来源: {source}", f"  Source: {source}"))
+
+
+def _validate_skill_name(name: str):
+    """Reject names that contain path traversal or special characters."""
+    if not _SAFE_NAME_RE.match(name):
+        click.echo(
+            f"Error: Invalid skill name '{name}'. "
+            "Use only letters, digits, hyphens, and underscores.",
+            err=True,
+        )
+        sys.exit(1)
+
+
+def _validate_github_spec(spec: str):
+    """Reject specs that don't look like owner/repo."""
+    if not re.match(r"^[a-zA-Z0-9_\-]+/[a-zA-Z0-9_.\-]+$", spec):
+        click.echo(f"Error: Invalid GitHub spec '{spec}'. Expected format: owner/repo", err=True)
+        sys.exit(1)
+
+
+def _check_skill_name(name: str):
+    """Raise SkillInstallError if name is invalid."""
+    if not _SAFE_NAME_RE.match(name):
+        raise SkillInstallError(
+            f"Invalid skill name '{name}'. Use only letters, digits, hyphens, and underscores."
+        )
+
+
+def _check_github_spec(spec: str):
+    """Raise SkillInstallError if spec is not owner/repo."""
+    if not re.match(r"^[a-zA-Z0-9_\-]+/[a-zA-Z0-9_.\-]+$", spec):
+        raise SkillInstallError(f"Invalid GitHub spec '{spec}'. Expected format: owner/repo")
+
+
+_JUNK_NAMES = {'.DS_Store', 'Thumbs.db', 'desktop.ini'}
+
+
+def _is_junk_entry(filename: str) -> bool:
+    parts = filename.replace('\\', '/').split('/')
+    return any(p in _JUNK_NAMES or p == '__MACOSX' or p.startswith('._.') for p in parts)
+
+
+def _safe_extractall(zf: zipfile.ZipFile, dest: str):
+    """Extract zip while guarding against Zip Slip and filtering junk files."""
+    dest = os.path.realpath(dest)
+    members = []
+    for member in zf.infolist():
+        if _is_junk_entry(member.filename):
+            continue
+        target = os.path.realpath(os.path.join(dest, member.filename))
+        if not target.startswith(dest + os.sep) and target != dest:
+            raise ValueError(f"Unsafe zip entry detected: {member.filename}")
+        members.append(member)
+    zf.extractall(dest, members=members)
+
+
+def _verify_checksum(content: bytes, expected: str):
+    """Verify SHA-256 checksum of downloaded content.
+
+    Returns True if checksum matches or no expected value provided.
+    Exits with error if mismatch.
+    """
+    if not expected:
+        return True
+    actual = hashlib.sha256(content).hexdigest()
+    if actual != expected.lower():
+        click.echo(
+            f"Error: Checksum mismatch!\n"
+            f"  Expected: {expected}\n"
+            f"  Actual:   {actual}\n"
+            f"The downloaded package may have been tampered with.",
+            err=True,
+        )
+        sys.exit(1)
+    return True
+
+
+def _check_checksum(content: bytes, expected: str):
+    """Raise SkillInstallError on SHA-256 checksum mismatch."""
+    if not expected:
+        return
+    actual = hashlib.sha256(content).hexdigest()
+    if actual != expected.lower():
+        raise SkillInstallError(
+            f"Checksum mismatch! Expected: {expected}, Actual: {actual}. "
+            "The downloaded package may have been tampered with."
+        )
+
+
+@click.group()
+def skill():
+    """Manage CowAgent skills."""
+    pass
+
+
+# ------------------------------------------------------------------
+# cow skill list
+# ------------------------------------------------------------------
+@skill.command("list")
+@click.option("--remote", is_flag=True, help="Browse skills on Skill Hub")
+@click.option("--page", default=1, type=int, help="Page number for remote listing")
+def skill_list(remote, page):
+    """List installed skills or browse Skill Hub."""
+    if remote:
+        _list_remote(page=page)
+    else:
+        _list_local()
+
+
+def _list_local():
+    """List locally installed skills."""
+    config = load_skills_config()
+    skills_dir = get_skills_dir()
+    builtin_dir = get_builtin_skills_dir()
+
+    # Merge builtin skills that are on disk but missing from config
+    _merge_builtin_into_config(config, builtin_dir, skills_dir)
+
+    if not config:
+        click.echo("No skills installed.")
+        return
+
+    entries = sorted(config.values(), key=lambda x: x.get("name", ""))
+    _print_skill_table(entries)
+
+
+def _merge_builtin_into_config(config: dict, builtin_dir: str, skills_dir: str):
+    """Scan builtin and custom dirs, add any new skills into config dict."""
+    dirty = False
+    for d, source in [(builtin_dir, "builtin"), (skills_dir, "custom")]:
+        if not os.path.isdir(d):
+            continue
+        for name in os.listdir(d):
+            if name.startswith(".") or name in ("skills_config.json",):
+                continue
+            skill_path = os.path.join(d, name)
+            if not os.path.isdir(skill_path):
+                continue
+            if not os.path.isfile(os.path.join(skill_path, "SKILL.md")):
+                continue
+            if name in config:
+                continue
+            desc = _read_skill_description(skill_path)
+            config[name] = {
+                "name": name,
+                "description": desc,
+                "source": source,
+                "enabled": True,
+                "category": "skill",
+            }
+            dirty = True
+    if dirty:
+        config_path = os.path.join(skills_dir, "skills_config.json")
+        try:
+            os.makedirs(skills_dir, exist_ok=True)
+            with open(config_path, "w", encoding="utf-8") as f:
+                json.dump(config, f, indent=4, ensure_ascii=False)
+        except Exception:
+            pass
+
+
+def _print_skill_table(entries):
+    """Print skills as a formatted table."""
+    def _display_label(e):
+        display = e.get("display_name", "")
+        name = e.get("name", "")
+        if display and display != name:
+            return f"{display} ({name})"
+        return name
+
+    labels = [_display_label(e) for e in entries]
+    name_w = max((len(l) for l in labels), default=4)
+    name_w = max(name_w, 4) + 2
+    desc_w = 40
+
+    header = f"{'Name':<{name_w}} {'Status':<10} {'Source':<10} {'Description'}"
+    click.echo(f"\n  Installed skills ({len(entries)})\n")
+    click.echo(f"  {header}")
+    click.echo(f"  {'─' * (name_w + 10 + 10 + desc_w)}")
+
+    for e, label in zip(entries, labels):
+        enabled = e.get("enabled", True)
+        source = e.get("source", "")
+        desc = e.get("description", "") or ""
+        if len(desc) > desc_w:
+            desc = desc[:desc_w - 3] + "..."
+
+        status_icon = click.style("✓ on ", fg="green") if enabled else click.style("✗ off", fg="red")
+        click.echo(f"  {label:<{name_w}} {status_icon}  {source:<10} {desc}")
+
+    click.echo()
+
+
+_REMOTE_PAGE_SIZE = 10
+
+
+def _list_remote(page: int = 1):
+    """List skills from remote Skill Hub with server-side pagination."""
+    try:
+        resp = requests.get(
+            f"{SKILL_HUB_API}/skills",
+            params={"page": page, "limit": _REMOTE_PAGE_SIZE},
+            timeout=10,
+        )
+        resp.raise_for_status()
+        data = resp.json()
+    except Exception as e:
+        click.echo(f"Error: Failed to fetch from Skill Hub: {e}", err=True)
+        sys.exit(1)
+
+    skills = data.get("skills", [])
+    total = data.get("total", len(skills))
+
+    if not skills and page == 1:
+        click.echo("No skills available on Skill Hub.")
+        return
+
+    total_pages = max(1, (total + _REMOTE_PAGE_SIZE - 1) // _REMOTE_PAGE_SIZE)
+    page = min(page, total_pages)
+    installed = set(load_skills_config().keys())
+
+    name_w = max((len(s.get("name", "")) for s in skills), default=4)
+    name_w = max(name_w, 4) + 2
+
+    click.echo(f"\n  Skill Hub ({total} available) — page {page}/{total_pages}\n")
+    click.echo(f"  {'Name':<{name_w}} {'Status':<12} {'Description'}")
+    click.echo(f"  {'─' * (name_w + 12 + 50)}")
+
+    for s in skills:
+        name = s.get("name", "")
+        desc = s.get("description", "") or s.get("display_name", "")
+        if len(desc) > 50:
+            desc = desc[:47] + "..."
+        status = click.style("installed", fg="green") if name in installed else "—"
+        click.echo(f"  {name:<{name_w}} {status:<12} {desc}")
+
+    click.echo()
+    nav_parts = []
+    if page > 1:
+        nav_parts.append(f"cow skill list --remote --page {page - 1}")
+    if page < total_pages:
+        nav_parts.append(f"cow skill list --remote --page {page + 1}")
+    if nav_parts:
+        click.echo(f"  Navigate: {' | '.join(nav_parts)}")
+    click.echo(f"  Install:  cow skill install <name>")
+    click.echo(f"  Browse:   https://skills.cowagent.ai\n")
+
+
+# ------------------------------------------------------------------
+# cow skill search
+# ------------------------------------------------------------------
+@skill.command()
+@click.argument("query")
+def search(query):
+    """Search skills on Skill Hub."""
+    try:
+        resp = requests.get(f"{SKILL_HUB_API}/skills/search", params={"q": query}, timeout=10)
+        resp.raise_for_status()
+        data = resp.json()
+    except Exception as e:
+        click.echo(f"Error: Failed to search Skill Hub: {e}", err=True)
+        sys.exit(1)
+
+    skills = data.get("skills", [])
+    if not skills:
+        click.echo(f'No skills found for "{query}".')
+        return
+
+    installed = set(load_skills_config().keys())
+    name_w = max(len(s.get("name", "")) for s in skills)
+    name_w = max(name_w, 4) + 2
+
+    click.echo(f'\n  Search results for "{query}" ({len(skills)} found)\n')
+    click.echo(f"  {'Name':<{name_w}} {'Status':<12} {'Description'}")
+    click.echo(f"  {'─' * (name_w + 12 + 50)}")
+
+    for s in skills:
+        name = s.get("name", "")
+        desc = s.get("description", "") or s.get("display_name", "")
+        if len(desc) > 50:
+            desc = desc[:47] + "..."
+        status = click.style("installed", fg="green") if name in installed else "—"
+        click.echo(f"  {name:<{name_w}} {status:<12} {desc}")
+
+    click.echo(f"\n  Install with: cow skill install <name>\n")
+
+
+# ------------------------------------------------------------------
+# Core install function — reusable from CLI and chat plugin
+# ------------------------------------------------------------------
+
+def install_skill(name: str) -> InstallResult:
+    """Core install logic, usable from CLI and chat plugin.
+
+    Accepts all formats: Skill Hub name, owner/repo, GitHub/GitLab URL,
+    git@ SSH, local path, SKILL.md URL.
+    Returns InstallResult with installed skill names and messages.
+    """
+    result = InstallResult()
+    try:
+        _route_install(name, result)
+    except SkillInstallError as e:
+        result.error = str(e)
+    return result
+
+
+def _route_install(name: str, result: InstallResult):
+    """Dispatch to the appropriate installer based on input format."""
+    # --- Local path ---
+    if name.startswith(("./", "../", "/", "~/")):
+        _install_local(name, result)
+        return
+
+    # --- Direct SKILL.md URL ---
+    if name.startswith(("http://", "https://")) and name.rstrip("/").endswith("SKILL.md"):
+        dir_url = re.sub(r'/SKILL\.md/?$', '', name)
+        gh = _parse_github_url(dir_url)
+        if gh:
+            owner, repo, branch, subpath = gh
+            _install_github(f"{owner}/{repo}", result, subpath=subpath, skill_name=(
+                subpath.rstrip("/").split("/")[-1] if subpath else repo
+            ), branch=branch)
+            return
+        _install_url(name, result)
+        return
+
+    # --- Zip / tar.gz archive URL ---
+    if name.startswith(("http://", "https://")) and re.search(r'\.(zip|tar\.gz|tgz)(\?.*)?$', name, re.IGNORECASE):
+        _install_archive_url(name, result)
+        return
+
+    # --- Full GitHub URL ---
+    parsed = _parse_github_url(name)
+    if parsed:
+        owner, repo, branch, subpath = parsed
+        _install_github(f"{owner}/{repo}", result, subpath=subpath, branch=branch)
+        return
+
+    # --- Full GitLab URL ---
+    gl = _parse_gitlab_url(name)
+    if gl:
+        owner, repo, branch, subpath = gl
+        _install_gitlab(f"{owner}/{repo}", result, subpath=subpath, branch=branch)
+        return
+
+    # --- git@host:owner/repo.git SSH URL ---
+    ssh = _parse_git_ssh_url(name)
+    if ssh:
+        host, owner, repo = ssh
+        _install_git_clone(name, result, display_name=f"{owner}/{repo}")
+        return
+
+    # --- github: prefix ---
+    if name.startswith("github:"):
+        raw = name[7:]
+        subpath = None
+        if "#" in raw:
+            raw, subpath = raw.split("#", 1)
+        if re.match(r"^[a-zA-Z0-9_\-]+/[a-zA-Z0-9_.\-]+$", raw):
+            _install_github(raw, result, subpath=subpath)
+        else:
+            _check_skill_name(raw)
+            _install_hub(raw, result, provider="github")
+        return
+
+    # --- clawhub: prefix ---
+    if name.startswith("clawhub:"):
+        skill_name = name[8:]
+        _check_skill_name(skill_name)
+        _install_hub(skill_name, result, provider="clawhub")
+        return
+
+    # --- linkai: prefix ---
+    if name.startswith("linkai:"):
+        skill_code = name[7:]
+        # LinkAI codes can be mixed-case alphanumeric; validate loosely
+        if not re.match(r"^[a-zA-Z0-9_\-]{1,128}$", skill_code):
+            raise SkillInstallError(f"Invalid LinkAI skill code '{skill_code}'.")
+        _install_hub(skill_code, result, provider="linkai")
+        return
+
+    # --- owner/repo or owner/repo#subpath shorthand ---
+    if re.match(r"^[a-zA-Z0-9_\-]+/[a-zA-Z0-9_.\-]+(?:#.+)?$", name):
+        subpath = None
+        spec = name
+        if "#" in spec:
+            spec, subpath = spec.split("#", 1)
+        _install_github(spec, result, subpath=subpath)
+        return
+
+    # --- Fallback: Skill Hub by name ---
+    _check_skill_name(name)
+    _install_hub(name, result)
+
+
+# ------------------------------------------------------------------
+# cow skill install (CLI thin wrapper)
+# ------------------------------------------------------------------
+@skill.command()
+@click.argument("name")
+def install(name):
+    """Install skill(s) from Skill Hub, GitHub, GitLab, git URL, or local path.
+
+    When given an owner/repo (or full URL), downloads the repo and
+    auto-discovers all skills/ subdirectories containing SKILL.md,
+    installing them in batch. Use a subpath to install a single skill.
+
+    Examples:
+
+      cow skill install pptx                          (from Skill Hub)
+
+      cow skill install larksuite/cli                 (GitHub shorthand, all skills)
+
+      cow skill install larksuite/cli#skills/lark-im  (single skill by subpath)
+
+      cow skill install https://github.com/owner/repo
+
+      cow skill install https://gitlab.com/org/repo
+
+      cow skill install git@github.com:owner/repo.git
+
+      cow skill install ./my-local-skills             (local directory)
+
+      cow skill install https://example.com/path/to/SKILL.md
+    """
+    result = install_skill(name)
+    for msg in result.messages:
+        click.echo(msg)
+    if result.error:
+        click.echo(f"Error: {result.error}", err=True)
+        sys.exit(1)
+
+
+def _install_hub(name, result: InstallResult, provider=None):
+    """Install a skill from Skill Hub."""
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+
+    result.messages.append(f"Fetching skill info for '{name}'...")
+
+    try:
+        body = {}
+        if provider:
+            body["provider"] = provider
+        resp = requests.post(
+            f"{SKILL_HUB_API}/skills/{name}/download",
+            json=body,
+            timeout=15,
+        )
+        resp.raise_for_status()
+    except requests.HTTPError as e:
+        if e.response is not None and e.response.status_code == 404:
+            raise SkillInstallError(f"Skill '{name}' not found on Skill Hub.")
+        raise SkillInstallError(f"Failed to fetch skill: {e}")
+    except SkillInstallError:
+        raise
+    except Exception as e:
+        raise SkillInstallError(f"Failed to connect to Skill Hub: {e}")
+
+    content_type = resp.headers.get("Content-Type", "")
+    hub_display_name = ""
+
+    if "application/json" in content_type:
+        data = resp.json()
+        source_type = data.get("source_type")
+        hub_display_name = data.get("display_name", "")
+
+        if source_type == "github":
+            source_url = data.get("source_url", "")
+            has_mirror = data.get("has_mirror", False)
+            gh_err = None
+
+            gh_timeout = 15 if has_mirror else 30
+            try:
+                parsed_url = _parse_github_url(source_url)
+                if parsed_url:
+                    owner, repo, branch, subpath = parsed_url
+                    _install_github(f"{owner}/{repo}", result, subpath=subpath, skill_name=name, branch=branch, timeout=gh_timeout)
+                else:
+                    _check_github_spec(source_url)
+                    _install_github(source_url, result, skill_name=name, timeout=gh_timeout)
+                if hub_display_name:
+                    _register_installed_skill(name, display_name=hub_display_name)
+                return
+            except Exception as e:
+                gh_err = e
+                if not has_mirror:
+                    raise SkillInstallError(f"GitHub download failed: {e}")
+
+            # Fallback: download mirror from Skill Hub
+            result.messages.append(f"GitHub download failed ({gh_err}), trying mirror...")
+            try:
+                mirror_resp = requests.post(
+                    f"{SKILL_HUB_API}/skills/{name}/download",
+                    json={"mirror": True},
+                    timeout=30,
+                )
+                mirror_resp.raise_for_status()
+            except Exception as e:
+                raise SkillInstallError(
+                    f"GitHub download failed ({gh_err}) and mirror also failed: {e}"
+                )
+
+            mirror_ct = mirror_resp.headers.get("Content-Type", "")
+            if "application/zip" not in mirror_ct:
+                raise SkillInstallError(
+                    f"GitHub download failed ({gh_err}) and mirror returned unexpected content."
+                )
+
+            expected_checksum = mirror_resp.headers.get("X-Checksum-Sha256")
+            _check_checksum(mirror_resp.content, expected_checksum)
+            installed_before = len(result.installed)
+            _install_zip_bytes(mirror_resp.content, name, skills_dir, result=result, source_label="cowhub", display_name=hub_display_name)
+            if len(result.installed) == installed_before:
+                _register_installed_skill(name, source="cowhub", display_name=hub_display_name)
+                result.installed.append(name)
+                result.messages.append(f"Installed '{name}' from mirror.")
+            return
+
+        if source_type == "registry":
+            download_url = data.get("download_url")
+            if download_url:
+                parsed = urlparse(download_url)
+                if parsed.scheme != "https":
+                    raise SkillInstallError("Refusing to download from non-HTTPS URL.")
+                src_provider = data.get("source_provider", "registry")
+                has_mirror = data.get("has_mirror", False)
+                expected_checksum = data.get("checksum") or data.get("sha256")
+                result.messages.append(f"Source: {src_provider}")
+                result.messages.append("Downloading skill package...")
+                dl_err = None
+                dl_timeout = 15 if has_mirror else 30
+                try:
+                    dl_resp = requests.get(
+                        download_url,
+                        timeout=(min(dl_timeout, 5), dl_timeout),
+                        allow_redirects=True,
+                    )
+                    dl_resp.raise_for_status()
+                except Exception as e:
+                    dl_err = e
+                    if not has_mirror:
+                        raise SkillInstallError(f"Failed to download from {src_provider}: {e}")
+
+                if dl_err is None:
+                    _check_checksum(dl_resp.content, expected_checksum)
+                    installed_before = len(result.installed)
+                    _install_zip_bytes(dl_resp.content, name, skills_dir, result=result, source_label=src_provider, display_name=hub_display_name)
+                    if len(result.installed) == installed_before:
+                        _register_installed_skill(name, source=src_provider, display_name=hub_display_name)
+                        result.installed.append(name)
+                        result.messages.append(f"Installed '{name}' from {src_provider}.")
+                    return
+
+                # Fallback: download mirror from Skill Hub
+                result.messages.append(f"Direct download failed ({dl_err}), trying mirror...")
+                try:
+                    mirror_resp = requests.post(
+                        f"{SKILL_HUB_API}/skills/{name}/download",
+                        json={"mirror": True},
+                        timeout=30,
+                    )
+                    mirror_resp.raise_for_status()
+                except Exception as e:
+                    raise SkillInstallError(
+                        f"Direct download failed ({dl_err}) and mirror also failed: {e}"
+                    )
+                mirror_ct = mirror_resp.headers.get("Content-Type", "")
+                if "application/zip" not in mirror_ct:
+                    raise SkillInstallError(
+                        f"Direct download failed ({dl_err}) and mirror returned unexpected content."
+                    )
+                expected_checksum = mirror_resp.headers.get("X-Checksum-Sha256")
+                _check_checksum(mirror_resp.content, expected_checksum)
+                installed_before = len(result.installed)
+                _install_zip_bytes(mirror_resp.content, name, skills_dir, result=result, source_label="cowhub", display_name=hub_display_name)
+                if len(result.installed) == installed_before:
+                    _register_installed_skill(name, source="cowhub", display_name=hub_display_name)
+                    result.installed.append(name)
+                    result.messages.append(f"Installed '{name}' from mirror.")
+            else:
+                raise SkillInstallError("Unsupported registry provider.")
+            return
+
+        if "redirect" in data:
+            source_url = data.get("source_url", "")
+            parsed_url = _parse_github_url(source_url)
+            if parsed_url:
+                owner, repo, branch, subpath = parsed_url
+                _install_github(f"{owner}/{repo}", result, subpath=subpath, skill_name=name, branch=branch)
+            else:
+                _check_github_spec(source_url)
+                _install_github(source_url, result, skill_name=name)
+            if hub_display_name:
+                _register_installed_skill(name, display_name=hub_display_name)
+            return
+
+    elif "application/zip" in content_type:
+        result.messages.append("Downloading skill package...")
+        expected_checksum = resp.headers.get("X-Checksum-Sha256")
+        _check_checksum(resp.content, expected_checksum)
+        installed_before = len(result.installed)
+        _install_zip_bytes(resp.content, name, skills_dir, result=result, source_label="cowhub")
+        if len(result.installed) == installed_before:
+            _register_installed_skill(name)
+            result.installed.append(name)
+            result.messages.append(f"Installed '{name}' from Skill Hub.")
+        return
+
+    raise SkillInstallError("Unexpected response from Skill Hub.")
+
+
+def _install_github(spec, result: InstallResult, subpath=None, skill_name=None, branch="main", source="github", timeout=30):
+    """Install skill(s) from a GitHub repo.
+
+    Strategy: zip download first (no API rate limit), Contents API as fallback.
+    """
+    if "#" in spec and not subpath:
+        spec, subpath = spec.split("#", 1)
+
+    _check_github_spec(spec)
+
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+    owner, repo = spec.split("/", 1)
+
+    result.messages.append(f"Downloading from GitHub: {spec} (branch: {branch})...")
+
+    tmp_dir = None
+    repo_root = None
+    try:
+        tmp_dir, repo_root = _download_repo_zip(spec, branch, timeout=timeout)
+    except Exception:
+        result.messages.append("Zip download failed, falling back to Contents API...")
+
+    if repo_root:
+        try:
+            _install_from_repo_root(repo_root, spec, subpath, skill_name, skills_dir, source, result)
+            return
+        except SkillInstallError:
+            raise
+        except Exception as e:
+            result.messages.append(f"Error processing zip: {e}")
+            result.messages.append("Falling back to Contents API...")
+        finally:
+            if tmp_dir:
+                shutil.rmtree(tmp_dir, ignore_errors=True)
+
+    if not subpath:
+        raise SkillInstallError(
+            f"Zip download failed and batch install requires zip. "
+            f"Try again or specify a subpath: {spec}#skills/<name>"
+        )
+
+    if not skill_name:
+        skill_name = subpath.rstrip("/").split("/")[-1]
+    _check_skill_name(skill_name)
+
+    result.messages.append(f"Downloading via Contents API: {spec}/{subpath} ...")
+    target_dir = os.path.join(skills_dir, skill_name)
+    try:
+        with tempfile.TemporaryDirectory() as api_tmp:
+            api_dest = os.path.join(api_tmp, skill_name)
+            os.makedirs(api_dest)
+            _download_github_dir(owner, repo, branch, subpath.strip("/"), api_dest)
+            if os.path.exists(target_dir):
+                shutil.rmtree(target_dir)
+            shutil.copytree(api_dest, target_dir)
+        _register_installed_skill(skill_name, source=source)
+        result.installed.append(skill_name)
+        result.messages.append(f"Installed '{skill_name}' from GitHub.")
+    except Exception as e:
+        raise SkillInstallError(f"Contents API also failed: {e}")
+
+
+def _install_from_repo_root(repo_root, spec, subpath, skill_name, skills_dir, source, result: InstallResult):
+    """Install skill(s) from an already-extracted repo root directory."""
+    if subpath:
+        source_dir = os.path.join(repo_root, subpath.strip("/"))
+        if not os.path.isdir(source_dir):
+            raise SkillInstallError(f"Path '{subpath}' not found in repository.")
+
+        if os.path.isfile(os.path.join(source_dir, "SKILL.md")):
+            if not skill_name:
+                fm = _parse_skill_frontmatter(
+                    _read_file_text(os.path.join(source_dir, "SKILL.md"))
+                )
+                skill_name = fm.get("name") or subpath.rstrip("/").split("/")[-1]
+            _check_skill_name(skill_name)
+
+            target_dir = os.path.join(skills_dir, skill_name)
+            if os.path.exists(target_dir):
+                shutil.rmtree(target_dir)
+            shutil.copytree(source_dir, target_dir)
+            _register_installed_skill(skill_name, source=source)
+            result.installed.append(skill_name)
+            result.messages.append(f"Installed '{skill_name}' from {source}.")
+            return
+
+        discovered = _scan_skills_in_dir(source_dir)
+        if discovered:
+            _batch_install_skills(discovered, spec, skills_dir, source, result)
+            return
+
+        raise SkillInstallError(f"No SKILL.md found in '{subpath}' or its subdirectories.")
+    else:
+        discovered = _scan_skills_in_repo(repo_root)
+
+        if not discovered:
+            if skill_name:
+                _check_skill_name(skill_name)
+            else:
+                skill_name = spec.split("/")[-1]
+                _check_skill_name(skill_name)
+            target_dir = os.path.join(skills_dir, skill_name)
+            if os.path.exists(target_dir):
+                shutil.rmtree(target_dir)
+            shutil.copytree(repo_root, target_dir)
+            _register_installed_skill(skill_name, source=source)
+            result.installed.append(skill_name)
+            result.messages.append(f"Installed '{skill_name}' from {source}.")
+            return
+
+        _batch_install_skills(discovered, spec, skills_dir, source, result)
+
+
+def _install_gitlab(spec, result: InstallResult, subpath=None, branch="main"):
+    """Install skill(s) from a GitLab repo via zip download."""
+    _check_github_spec(spec)
+
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+
+    result.messages.append(f"Downloading from GitLab: {spec} (branch: {branch})...")
+
+    try:
+        tmp_dir, repo_root = _download_repo_zip(spec, branch, host="gitlab")
+    except Exception as e:
+        raise SkillInstallError(f"Failed to download from GitLab: {e}")
+
+    try:
+        _install_from_repo_root(repo_root, spec, subpath, None, skills_dir, "gitlab", result)
+    finally:
+        shutil.rmtree(tmp_dir, ignore_errors=True)
+
+
+def _install_git_clone(git_url: str, result: InstallResult, display_name: str = ""):
+    """Install skill(s) from any git URL via shallow clone."""
+    skills_dir = get_skills_dir()
+    os.makedirs(skills_dir, exist_ok=True)
+
+    result.messages.append(f"Cloning {display_name or git_url} ...")
+
+    try:
+        tmp_dir, repo_root = _clone_repo(git_url)
+    except RuntimeError as e:
+        raise SkillInstallError(str(e))
+
+    try:
+        _install_from_repo_root(repo_root, display_name or git_url, None, None, skills_dir, "git", result)
+    finally:
+        shutil.rmtree(tmp_dir, ignore_errors=True)
+
+
+def _install_zip_bytes(content, name, skills_dir, result: InstallResult = None, source_label: str = "zip", display_name: str = ""):
+    """Extract a zip archive and install skill(s).
+
+    Supports three scenarios:
+      1. Root contains SKILL.md → single skill install
+      2. Contains multiple skill dirs (skills/, or immediate children with SKILL.md) → batch install
+      3. Fallback → treat the entire archive as a single skill named `name`
+    """
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        zip_path = os.path.join(tmp_dir, "package.zip")
+        with open(zip_path, "wb") as f:
+            f.write(content)
+
+        extract_dir = os.path.join(tmp_dir, "extracted")
+        with zipfile.ZipFile(zip_path, "r") as zf:
+            _safe_extractall(zf, extract_dir)
+
+        top_items = [d for d in os.listdir(extract_dir) if not d.startswith(".")]
+        pkg_root = extract_dir
+        if len(top_items) == 1 and os.path.isdir(os.path.join(extract_dir, top_items[0])):
+            pkg_root = os.path.join(extract_dir, top_items[0])
+
+        discovered = _scan_skills_in_repo(pkg_root) or _scan_skills_in_dir(pkg_root)
+
+        if discovered and len(discovered) > 1 and result is not None:
+            _batch_install_skills(discovered, name, skills_dir, source_label, result, display_name=display_name)
+            return
+
+        if discovered and len(discovered) == 1:
+            sname, sdir = discovered[0]
+            safe_name = re.sub(r'[^a-zA-Z0-9_\-]', '-', sname)[:64]
+            if not _SAFE_NAME_RE.match(safe_name):
+                safe_name = name
+            target = os.path.join(skills_dir, safe_name)
+            if os.path.exists(target):
+                shutil.rmtree(target)
+            shutil.copytree(sdir, target)
+            _register_installed_skill(safe_name, source=source_label, display_name=display_name)
+            if result is not None:
+                result.installed.append(safe_name)
+                result.messages.append(f"Installed '{safe_name}' from {source_label}.")
+            return
+
+        target = os.path.join(skills_dir, name)
+        if os.path.exists(target):
+            shutil.rmtree(target)
+        shutil.copytree(pkg_root, target)
+
+
+
+
+# ------------------------------------------------------------------
+# cow skill uninstall
+# ------------------------------------------------------------------
+@skill.command()
+@click.argument("name")
+@click.option("--yes", "-y", is_flag=True, help="Skip confirmation")
+def uninstall(name, yes):
+    """Uninstall a skill."""
+    _validate_skill_name(name)
+    skills_dir = get_skills_dir()
+    skill_dir = os.path.join(skills_dir, name)
+
+    if not os.path.exists(skill_dir):
+        click.echo(f"Error: Skill '{name}' is not installed.", err=True)
+        sys.exit(1)
+
+    if not yes:
+        click.confirm(f"Uninstall skill '{name}'?", abort=True)
+
+    shutil.rmtree(skill_dir)
+
+    config_path = os.path.join(skills_dir, "skills_config.json")
+    if os.path.exists(config_path):
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                config = json.load(f)
+            config.pop(name, None)
+            with open(config_path, "w", encoding="utf-8") as f:
+                json.dump(config, f, indent=4, ensure_ascii=False)
+        except Exception:
+            pass
+
+    click.echo(click.style(f"✓ Skill '{name}' uninstalled.", fg="green"))
+
+
+# ------------------------------------------------------------------
+# cow skill enable / disable
+# ------------------------------------------------------------------
+@skill.command()
+@click.argument("name")
+def enable(name):
+    """Enable a skill."""
+    _set_enabled(name, True)
+
+
+@skill.command()
+@click.argument("name")
+def disable(name):
+    """Disable a skill."""
+    _set_enabled(name, False)
+
+
+def _set_enabled(name, enabled):
+    _validate_skill_name(name)
+    skills_dir = get_skills_dir()
+    config_path = os.path.join(skills_dir, "skills_config.json")
+
+    if not os.path.exists(config_path):
+        click.echo(f"Error: No skills config found.", err=True)
+        sys.exit(1)
+
+    try:
+        with open(config_path, "r", encoding="utf-8") as f:
+            config = json.load(f)
+    except Exception as e:
+        click.echo(f"Error: Failed to read skills config: {e}", err=True)
+        sys.exit(1)
+
+    if name not in config:
+        click.echo(f"Error: Skill '{name}' not found in config.", err=True)
+        sys.exit(1)
+
+    config[name]["enabled"] = enabled
+    with open(config_path, "w", encoding="utf-8") as f:
+        json.dump(config, f, indent=4, ensure_ascii=False)
+
+    state = "enabled" if enabled else "disabled"
+    icon = "✓" if enabled else "✗"
+    color = "green" if enabled else "yellow"
+    click.echo(click.style(f"{icon} Skill '{name}' {state}.", fg=color))
+
+
+# ------------------------------------------------------------------
+# cow skill info
+# ------------------------------------------------------------------
+@skill.command()
+@click.argument("name")
+def info(name):
+    """Show details about an installed skill."""
+    _validate_skill_name(name)
+    skills_dir = get_skills_dir()
+    builtin_dir = get_builtin_skills_dir()
+
+    skill_dir = None
+    source = None
+    config = load_skills_config()
+    for d, src in [(skills_dir, "custom"), (builtin_dir, "builtin")]:
+        candidate = os.path.join(d, name)
+        if os.path.isdir(candidate):
+            skill_dir = candidate
+            source = config.get(name, {}).get("source") or src
+            break
+
+    if not skill_dir:
+        click.echo(f"Error: Skill '{name}' not found.", err=True)
+        sys.exit(1)
+
+    skill_md = os.path.join(skill_dir, "SKILL.md")
+    if not os.path.exists(skill_md):
+        click.echo(f"Skill directory: {skill_dir}")
+        click.echo("No SKILL.md found.")
+        return
+
+    with open(skill_md, "r", encoding="utf-8") as f:
+        content = f.read()
+
+    config = load_skills_config()
+    entry = config.get(name, {})
+    enabled = entry.get("enabled", True)
+    status_str = click.style("✓ enabled", fg="green") if enabled else click.style("✗ disabled", fg="red")
+
+    display_name = entry.get("display_name", "")
+    click.echo(f"\n  Skill: {name}")
+    if display_name and display_name != name:
+        click.echo(f"  Display: {display_name}")
+    click.echo(f"  Source: {source}")
+    click.echo(f"  Status: {status_str}")
+    click.echo(f"  Path: {skill_dir}")
+    click.echo(f"\n{'─' * 60}")
+
+    # Show first ~30 lines of SKILL.md as a preview
+    lines = content.split("\n")
+    preview = "\n".join(lines[:30])
+    click.echo(preview)
+    if len(lines) > 30:
+        click.echo(f"\n  ... ({len(lines) - 30} more lines, see {skill_md})")
+    click.echo()
diff --git a/cli/utils.py b/cli/utils.py
new file mode 100644
index 0000000..4dcb507
--- /dev/null
+++ b/cli/utils.py
@@ -0,0 +1,78 @@
+"""Shared utilities for cow CLI."""
+
+import os
+import sys
+import json
+
+
+def get_project_root() -> str:
+    """Get the CowAgent project root directory."""
+    # cli/ is directly under the project root
+    return os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+
+
+def get_workspace_dir() -> str:
+    """Get the agent workspace directory from config, defaulting to ~/cow."""
+    config = load_config_json()
+    workspace = config.get("agent_workspace", "~/cow")
+    return os.path.expanduser(workspace)
+
+
+def get_skills_dir() -> str:
+    """Get the custom skills directory."""
+    return os.path.join(get_workspace_dir(), "skills")
+
+
+def get_builtin_skills_dir() -> str:
+    """Get the builtin skills directory."""
+    return os.path.join(get_project_root(), "skills")
+
+
+def load_config_json() -> dict:
+    """Load config.json from project root."""
+    config_path = os.path.join(get_project_root(), "config.json")
+    if not os.path.exists(config_path):
+        return {}
+    try:
+        with open(config_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except Exception:
+        return {}
+
+
+def get_cli_language() -> str:
+    """Resolve the CLI UI language using the shared i18n detector.
+
+    Reads the `cow_lang` field from config.json (defaults to "auto") and runs
+    the same detection used by the running app, so CLI output matches.
+    """
+    ensure_sys_path()
+    try:
+        from common import i18n
+
+        configured = load_config_json().get("cow_lang", "auto")
+        return i18n.resolve_language(configured)
+    except Exception:
+        return "en"
+
+
+def load_skills_config() -> dict:
+    """Load skills_config.json from the custom skills directory."""
+    path = os.path.join(get_skills_dir(), "skills_config.json")
+    if not os.path.exists(path):
+        return {}
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except Exception:
+        return {}
+
+
+def ensure_sys_path():
+    """Add project root to sys.path so we can import agent modules."""
+    root = get_project_root()
+    if root not in sys.path:
+        sys.path.insert(0, root)
+
+
+SKILL_HUB_API = "https://skills.cowagent.ai/api"
diff --git a/common/cloud_client.py b/common/cloud_client.py
new file mode 100644
index 0000000..30d7f7d
--- /dev/null
+++ b/common/cloud_client.py
@@ -0,0 +1,905 @@
+"""
+Cloud management client for connecting to the LinkAI control console.
+
+Handles remote configuration sync, message push, and skill management
+via the LinkAI socket protocol.
+
+NOTE: By default, no cloud-related config is enabled. The application runs
+entirely locally without connecting to any remote service. The cloud client
+is only activated when BOTH of the following conditions are met:
+
+  1. ``use_linkai`` is set to True in config (checked in app.py before
+     importing this module).
+  2. ``cloud_deployment_id`` (or env CLOUD_DEPLOYMENT_ID) is non-empty
+     (checked in app.py and again in the ``start()`` function below).
+
+If either condition is missing, this module is never loaded and the
+program continues as a purely local application.
+"""
+
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from linkai import LinkAIClient, PushMsg
+from config import conf, pconf, plugin_config, available_setting, write_plugin_config, get_root, get_weixin_credentials_path
+from plugins import PluginManager
+import threading
+import time
+import json
+import os
+
+
+chat_client: LinkAIClient
+
+
+CHANNEL_ACTIONS = {"channel_create", "channel_update", "channel_delete"}
+
+# channelType -> config key mapping for app credentials.
+# secret_key may be "" for single-token channels (e.g. telegram/discord).
+# For slack, appId carries bot_token and appSecret carries app_token.
+CREDENTIAL_MAP = {
+    "feishu":            ("feishu_app_id",          "feishu_app_secret"),
+    "dingtalk":          ("dingtalk_client_id",      "dingtalk_client_secret"),
+    "wecom_bot":         ("wecom_bot_id",            "wecom_bot_secret"),
+    "qq":                ("qq_app_id",               "qq_app_secret"),
+    "wechatmp":          ("wechatmp_app_id",         "wechatmp_app_secret"),
+    "wechatmp_service":  ("wechatmp_app_id",         "wechatmp_app_secret"),
+    "wechatcom_app":     ("wechatcomapp_agent_id",   "wechatcomapp_secret"),
+    "telegram":          ("telegram_token",          ""),
+    "slack":             ("slack_bot_token",         "slack_app_token"),
+    "discord":           ("discord_token",           ""),
+}
+
+
+class CloudClient(LinkAIClient):
+    def __init__(self, api_key: str, channel, host: str = "", port=None):
+        super().__init__(api_key, host, port=port)
+        self.channel = channel
+        self.client_type = channel.channel_type
+        self.channel_mgr = None
+        self._skill_service = None
+        self._memory_service = None
+        self._knowledge_service = None
+        self._chat_service = None
+        self._session_service = None
+
+    @property
+    def skill_service(self):
+        """Lazy-init SkillService so it is available once SkillManager exists."""
+        if self._skill_service is None:
+            try:
+                from agent.skills.manager import SkillManager
+                from agent.skills.service import SkillService
+                from config import conf
+                from common.utils import expand_path
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                manager = SkillManager(custom_dir=os.path.join(workspace_root, "skills"))
+                self._skill_service = SkillService(manager)
+                logger.debug("[CloudClient] SkillService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init SkillService: {e}")
+        return self._skill_service
+
+    @property
+    def memory_service(self):
+        """Lazy-init MemoryService."""
+        if self._memory_service is None:
+            try:
+                from agent.memory.service import MemoryService
+                from config import conf
+                from common.utils import expand_path
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                self._memory_service = MemoryService(workspace_root)
+                logger.debug("[CloudClient] MemoryService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init MemoryService: {e}")
+        return self._memory_service
+
+    @property
+    def knowledge_service(self):
+        """Lazy-init KnowledgeService."""
+        if self._knowledge_service is None:
+            try:
+                from agent.knowledge.service import KnowledgeService
+                from config import conf
+                from common.utils import expand_path
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                self._knowledge_service = KnowledgeService(workspace_root)
+                logger.debug("[CloudClient] KnowledgeService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init KnowledgeService: {e}")
+        return self._knowledge_service
+
+    @property
+    def chat_service(self):
+        """Lazy-init ChatService (requires AgentBridge via Bridge singleton)."""
+        if self._chat_service is None:
+            try:
+                from agent.chat.service import ChatService
+                from bridge.bridge import Bridge
+                agent_bridge = Bridge().get_agent_bridge()
+                self._chat_service = ChatService(agent_bridge)
+                logger.debug("[CloudClient] ChatService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init ChatService: {e}")
+        return self._chat_service
+
+    @property
+    def session_service(self):
+        """Lazy-init SessionService."""
+        if self._session_service is None:
+            try:
+                from agent.chat.session_service import SessionService
+                self._session_service = SessionService()
+                logger.debug("[CloudClient] SessionService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init SessionService: {e}")
+        return self._session_service
+
+    # ------------------------------------------------------------------
+    # message push callback
+    # ------------------------------------------------------------------
+    def on_message(self, push_msg: PushMsg):
+        session_id = push_msg.session_id
+        msg_content = push_msg.msg_content
+        logger.info(f"receive msg push, session_id={session_id}, msg_content={msg_content}")
+        context = Context()
+        context.type = ContextType.TEXT
+        context["receiver"] = session_id
+        context["isgroup"] = push_msg.is_group
+        self.channel.send(Reply(ReplyType.TEXT, content=msg_content), context)
+
+    # ------------------------------------------------------------------
+    # config callback
+    # ------------------------------------------------------------------
+    def on_config(self, config: dict):
+        if not self.client_id:
+            return
+        logger.info(f"[CloudClient] Loading remote config: {config}")
+
+        action = config.get("action")
+        if action in CHANNEL_ACTIONS:
+            self._dispatch_channel_action(action, config.get("data", {}))
+            return
+
+        if config.get("enabled") != "Y":
+            return
+
+        local_config = conf()
+        need_restart_channel = False
+
+        for key in config.keys():
+            if key in available_setting and config.get(key) is not None:
+                local_config[key] = config.get(key)
+
+        # Self-evolution switch: normalize remote value (bool / "Y"/"N" / "true")
+        # to a real bool so the evolution config parser reads it correctly.
+        if config.get("self_evolution_enabled") is not None:
+            local_config["self_evolution_enabled"] = self._to_bool(config.get("self_evolution_enabled"))
+
+        # Voice settings
+        reply_voice_mode = config.get("reply_voice_mode")
+        if reply_voice_mode:
+            if reply_voice_mode == "voice_reply_voice":
+                local_config["voice_reply_voice"] = True
+                local_config["always_reply_voice"] = False
+            elif reply_voice_mode == "always_reply_voice":
+                local_config["always_reply_voice"] = True
+                local_config["voice_reply_voice"] = True
+            elif reply_voice_mode == "no_reply_voice":
+                local_config["always_reply_voice"] = False
+                local_config["voice_reply_voice"] = False
+
+        # Model configuration
+        if config.get("model"):
+            local_config["model"] = config.get("model")
+
+        # Channel configuration (legacy single-channel path)
+        if config.get("channelType"):
+            if local_config.get("channel_type") != config.get("channelType"):
+                local_config["channel_type"] = config.get("channelType")
+                need_restart_channel = True
+
+        # Channel-specific app credentials (legacy single-channel path)
+        current_channel_type = local_config.get("channel_type", "")
+        if self._set_channel_credentials(local_config, current_channel_type,
+                                         config.get("app_id"), config.get("app_secret")):
+            need_restart_channel = True
+
+        if config.get("admin_password"):
+            if not pconf("Godcmd"):
+                write_plugin_config({"Godcmd": {"password": config.get("admin_password"), "admin_users": []}})
+            else:
+                pconf("Godcmd")["password"] = config.get("admin_password")
+            PluginManager().instances["GODCMD"].reload()
+
+        if config.get("group_app_map") and pconf("linkai"):
+            local_group_map = {}
+            for mapping in config.get("group_app_map"):
+                local_group_map[mapping.get("group_name")] = mapping.get("app_code")
+            pconf("linkai")["group_app_map"] = local_group_map
+            PluginManager().instances["LINKAI"].reload()
+
+        if config.get("text_to_image") and config.get("text_to_image") == "midjourney" and pconf("linkai"):
+            if pconf("linkai")["midjourney"]:
+                pconf("linkai")["midjourney"]["enabled"] = True
+                pconf("linkai")["midjourney"]["use_image_create_prefix"] = True
+        elif config.get("text_to_image") and config.get("text_to_image") in ["dall-e-2", "dall-e-3"]:
+            if pconf("linkai")["midjourney"]:
+                pconf("linkai")["midjourney"]["use_image_create_prefix"] = False
+
+        self._save_config_to_file(local_config)
+
+        if need_restart_channel:
+            self._restart_channel(local_config.get("channel_type", ""))
+
+    # ------------------------------------------------------------------
+    # channel CRUD operations
+    # ------------------------------------------------------------------
+    def _dispatch_channel_action(self, action: str, data: dict):
+        channel_type = data.get("channelType")
+        if not channel_type:
+            logger.warning(f"[CloudClient] Channel action '{action}' missing channelType, data={data}")
+            return
+        logger.info(f"[CloudClient] Channel action: {action}, channelType={channel_type}")
+
+        if action == "channel_create":
+            self._handle_channel_create(channel_type, data)
+        elif action == "channel_update":
+            self._handle_channel_update(channel_type, data)
+        elif action == "channel_delete":
+            self._handle_channel_delete(channel_type, data)
+
+    def _handle_channel_create(self, channel_type: str, data: dict):
+        local_config = conf()
+        cred_changed = self._set_channel_credentials(
+            local_config, channel_type, data.get("appId"), data.get("appSecret"))
+        self._add_channel_type(local_config, channel_type)
+        self._save_config_to_file(local_config)
+
+        if not self.channel_mgr:
+            return
+
+        existing_ch = self.channel_mgr.get_channel(channel_type)
+        skip_restart = existing_ch and not cred_changed
+        if skip_restart and channel_type in ("weixin", "wx"):
+            login_status = getattr(existing_ch, "login_status", "")
+            if login_status != "logged_in":
+                skip_restart = False
+                logger.info(f"[CloudClient] Channel '{channel_type}' not logged in "
+                            f"(status={login_status}), forcing restart")
+        if skip_restart:
+            logger.info(f"[CloudClient] Channel '{channel_type}' already running with same config, "
+                        "skip restart, reporting status only")
+            threading.Thread(
+                target=self._report_channel_startup, args=(channel_type,), daemon=True
+            ).start()
+            return
+
+        threading.Thread(
+            target=self._do_add_channel, args=(channel_type,), daemon=True
+        ).start()
+
+    def _handle_channel_update(self, channel_type: str, data: dict):
+        local_config = conf()
+        enabled = data.get("enabled", "Y")
+
+        cred_changed = self._set_channel_credentials(
+            local_config, channel_type, data.get("appId"), data.get("appSecret"))
+        if enabled == "N":
+            self._remove_channel_type(local_config, channel_type)
+        else:
+            self._add_channel_type(local_config, channel_type)
+        self._save_config_to_file(local_config)
+
+        if not self.channel_mgr:
+            return
+
+        if enabled == "N":
+            threading.Thread(
+                target=self._do_remove_channel, args=(channel_type,), daemon=True
+            ).start()
+        else:
+            existing_ch = self.channel_mgr.get_channel(channel_type)
+            needs_restart = cred_changed or not existing_ch
+            if not needs_restart and channel_type in ("weixin", "wx"):
+                login_status = getattr(existing_ch, "login_status", "")
+                if login_status != "logged_in":
+                    needs_restart = True
+                    logger.info(f"[CloudClient] Channel '{channel_type}' not logged in "
+                                f"(status={login_status}), forcing restart")
+            if existing_ch and not needs_restart:
+                logger.info(f"[CloudClient] Channel '{channel_type}' already running with same config, "
+                            "skip restart, reporting status only")
+                threading.Thread(
+                    target=self._report_channel_startup, args=(channel_type,), daemon=True
+                ).start()
+            else:
+                threading.Thread(
+                    target=self._do_restart_channel, args=(self.channel_mgr, channel_type), daemon=True
+                ).start()
+
+    def _handle_channel_delete(self, channel_type: str, data: dict):
+        local_config = conf()
+        self._clear_channel_credentials(local_config, channel_type)
+        self._remove_channel_type(local_config, channel_type)
+        self._save_config_to_file(local_config)
+
+        if channel_type in ("weixin", "wx"):
+            self._remove_weixin_credentials()
+
+        if self.channel_mgr:
+            threading.Thread(
+                target=self._do_remove_channel, args=(channel_type,), daemon=True
+            ).start()
+
+    @staticmethod
+    def _remove_weixin_credentials():
+        """Remove the weixin token credentials file so next connect triggers QR login."""
+        cred_path = get_weixin_credentials_path()
+        try:
+            if os.path.exists(cred_path):
+                os.remove(cred_path)
+                logger.info(f"[CloudClient] Removed weixin credentials: {cred_path}")
+        except Exception as e:
+            logger.warning(f"[CloudClient] Failed to remove weixin credentials: {e}")
+
+    # ------------------------------------------------------------------
+    # value helpers
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _to_bool(value) -> bool:
+        """Normalize a remote config value to bool (bool / "Y"/"N" / "true"/"1")."""
+        if isinstance(value, bool):
+            return value
+        if isinstance(value, (int, float)):
+            return value != 0
+        if isinstance(value, str):
+            return value.strip().lower() in ("y", "yes", "true", "1", "on")
+        return False
+
+    # ------------------------------------------------------------------
+    # channel credentials helpers
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _set_channel_credentials(local_config: dict, channel_type: str,
+                                 app_id, app_secret) -> bool:
+        """
+        Write app_id / app_secret into the correct config keys for *channel_type*.
+        Also syncs the values to environment variables (upper-cased key) so that
+        skills that rely on env-based checks (e.g. has_env_var) work immediately.
+        Returns True if any value actually changed.
+        """
+        cred = CREDENTIAL_MAP.get(channel_type)
+        if not cred:
+            return False
+        id_key, secret_key = cred
+        changed = False
+        if app_id is not None and local_config.get(id_key) != app_id:
+            local_config[id_key] = app_id
+            os.environ[id_key.upper()] = str(app_id)
+            changed = True
+        # secret_key may be empty for single-token channels (e.g. telegram/discord)
+        if secret_key and app_secret is not None and local_config.get(secret_key) != app_secret:
+            local_config[secret_key] = app_secret
+            os.environ[secret_key.upper()] = str(app_secret)
+            changed = True
+        if changed:
+            logger.info(f"[CloudClient] Synced {channel_type} credentials to conf and env")
+        return changed
+
+    @staticmethod
+    def _clear_channel_credentials(local_config: dict, channel_type: str):
+        cred = CREDENTIAL_MAP.get(channel_type)
+        if not cred:
+            return
+        id_key, secret_key = cred
+        local_config.pop(id_key, None)
+        os.environ.pop(id_key.upper(), None)
+        if secret_key:
+            local_config.pop(secret_key, None)
+            os.environ.pop(secret_key.upper(), None)
+
+    # ------------------------------------------------------------------
+    # channel_type list helpers
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _parse_channel_types(local_config: dict) -> list:
+        raw = local_config.get("channel_type", "")
+        if isinstance(raw, list):
+            return [ch.strip() for ch in raw if ch.strip()]
+        if isinstance(raw, str):
+            return [ch.strip() for ch in raw.split(",") if ch.strip()]
+        return []
+
+    @staticmethod
+    def _add_channel_type(local_config: dict, channel_type: str):
+        types = CloudClient._parse_channel_types(local_config)
+        if channel_type not in types:
+            types.append(channel_type)
+            local_config["channel_type"] = ", ".join(types)
+
+    @staticmethod
+    def _remove_channel_type(local_config: dict, channel_type: str):
+        types = CloudClient._parse_channel_types(local_config)
+        if channel_type in types:
+            types.remove(channel_type)
+            local_config["channel_type"] = ", ".join(types)
+
+    # ------------------------------------------------------------------
+    # channel manager thread helpers
+    # ------------------------------------------------------------------
+    def _do_add_channel(self, channel_type: str):
+        try:
+            self.channel_mgr.add_channel(channel_type)
+            logger.info(f"[CloudClient] Channel '{channel_type}' added successfully")
+        except Exception as e:
+            logger.error(f"[CloudClient] Failed to add channel '{channel_type}': {e}", exc_info=True)
+            self.send_channel_status(channel_type, "error", str(e))
+            return
+        self._report_channel_startup(channel_type)
+
+    def _do_remove_channel(self, channel_type: str):
+        try:
+            self.channel_mgr.remove_channel(channel_type)
+            logger.info(f"[CloudClient] Channel '{channel_type}' removed successfully")
+        except Exception as e:
+            logger.error(f"[CloudClient] Failed to remove channel '{channel_type}': {e}")
+
+    def send_channel_qrcode(self, channel_type: str, qrcode_url: str):
+        """Report QR code URL for a channel that requires scan-to-login."""
+        if self.client_id:
+            from linkai.api.client.client import ClientMsgType
+            msg = self._build_package(ClientMsgType.CHANNEL_STATUS)
+            msg["data"]["channelType"] = channel_type
+            msg["data"]["status"] = "qrcode"
+            msg["data"]["qrcodeUrl"] = qrcode_url
+            self._send_package(msg)
+            logger.info(f"[CloudClient] Sent QR code status for '{channel_type}'")
+
+    def _report_channel_startup(self, channel_type: str):
+        """Wait for channel startup result and report to cloud."""
+        ch = self.channel_mgr.get_channel(channel_type)
+        if not ch:
+            self.send_channel_status(channel_type, "error", "channel instance not found")
+            return
+
+        if channel_type in ("weixin", "wx") and hasattr(ch, "login_status"):
+            login_status = getattr(ch, "login_status", "")
+            if login_status in ("waiting_scan", "scanned", "idle"):
+                logger.info(f"[CloudClient] Channel '{channel_type}' is waiting for QR login, "
+                            "skip reporting connected")
+                return
+
+        success, error = ch.wait_startup(timeout=3)
+        if success:
+            logger.info(f"[CloudClient] Channel '{channel_type}' connected, reporting status")
+            self.send_channel_status(channel_type, "connected")
+        else:
+            logger.warning(f"[CloudClient] Channel '{channel_type}' startup failed: {error}")
+            self.send_channel_status(channel_type, "error", error)
+
+    # ------------------------------------------------------------------
+    # skill callback
+    # ------------------------------------------------------------------
+    def on_skill(self, data: dict) -> dict:
+        """
+        Handle SKILL messages from the cloud console.
+        Delegates to SkillService.dispatch for the actual operations.
+
+        :param data: message data with 'action', 'clientId', 'payload'
+        :return: response dict
+        """
+        action = data.get("action", "")
+        payload = data.get("payload")
+        logger.info(f"[CloudClient] on_skill: action={action}")
+
+        svc = self.skill_service
+        if svc is None:
+            return {"action": action, "code": 500, "message": "SkillService not available", "payload": None}
+
+        return svc.dispatch(action, payload)
+
+    # ------------------------------------------------------------------
+    # memory callback
+    # ------------------------------------------------------------------
+    def on_memory(self, data: dict) -> dict:
+        """
+        Handle MEMORY messages from the cloud console.
+        Delegates to MemoryService.dispatch for the actual operations.
+
+        :param data: message data with 'action', 'clientId', 'payload'
+        :return: response dict
+        """
+        action = data.get("action", "")
+        payload = data.get("payload")
+        logger.info(f"[CloudClient] on_memory: action={action}")
+
+        svc = self.memory_service
+        if svc is None:
+            return {"action": action, "code": 500, "message": "MemoryService not available", "payload": None}
+
+        return svc.dispatch(action, payload)
+
+    # ------------------------------------------------------------------
+    # knowledge callback
+    # ------------------------------------------------------------------
+    def on_knowledge(self, data: dict) -> dict:
+        """
+        Handle KNOWLEDGE messages from the cloud console.
+        Delegates to KnowledgeService.dispatch for the actual operations.
+
+        :param data: message data with 'action', 'clientId', 'payload'
+        :return: response dict
+        """
+        action = data.get("action", "")
+        payload = data.get("payload")
+        logger.info(f"[CloudClient] on_knowledge: action={action}")
+
+        svc = self.knowledge_service
+        if svc is None:
+            return {"action": action, "code": 500, "message": "KnowledgeService not available", "payload": None}
+
+        return svc.dispatch(action, payload)
+
+    # ------------------------------------------------------------------
+    # chat callback
+    # ------------------------------------------------------------------
+    def on_chat(self, data: dict, send_chunk_fn):
+        """
+        Handle CHAT messages from the cloud console.
+        Runs the agent in streaming mode and sends chunks back via send_chunk_fn.
+
+        :param data: message data with 'action' and 'payload' (query, session_id)
+        :param send_chunk_fn: callable(chunk_data: dict) to send one streaming chunk
+        """
+        payload = data.get("payload", {})
+        query = payload.get("query", "")
+        session_id = payload.get("session_id", "cloud_console")
+        channel_type = payload.get("channel_type", "")
+        if not session_id.startswith("session_"):
+            session_id = f"session_{session_id}"
+        logger.info(f"[CloudClient] on_chat: session={session_id}, channel={channel_type}, query={query[:80]}")
+
+        # Intercept cow/slash commands before the agent runs
+        try:
+            from plugins import PluginManager
+            mgr = PluginManager()
+            instance = mgr.instances.get("COW_CLI")
+            if instance and hasattr(instance, "execute"):
+                result = instance.execute(query, session_id=session_id)
+                if result is not None:
+                    send_chunk_fn({"chunk_type": "content", "delta": result, "segment_id": 0})
+                    return
+        except Exception as e:
+            logger.warning(f"[CloudClient] cow_cli intercept failed: {e}")
+
+        svc = self.chat_service
+        if svc is None:
+            raise RuntimeError("ChatService not available")
+
+        svc.run(query=query, session_id=session_id, channel_type=channel_type, send_chunk_fn=send_chunk_fn)
+
+    # ------------------------------------------------------------------
+    # history callback
+    # ------------------------------------------------------------------
+    # Session-related actions handled via the HISTORY channel
+    _SESSION_ACTIONS = {
+        "list_sessions", "delete_session", "rename_session",
+        "clear_context", "generate_title",
+    }
+
+    def on_history(self, data: dict) -> dict:
+        """
+        Handle HISTORY messages from the cloud console.
+
+        Supports both history query and session management actions
+        through a unified HISTORY message channel:
+          - query: paginated conversation history
+          - list_sessions / delete_session / rename_session /
+            clear_context / generate_title: session lifecycle
+
+        :param data: message data with 'action' and 'payload'
+        :return: response dict
+        """
+        action = data.get("action", "query")
+        payload = data.get("payload", {})
+        logger.info(f"[CloudClient] on_history: action={action}")
+
+        if action == "query":
+            return self._query_history(payload)
+
+        if action in self._SESSION_ACTIONS:
+            return self._dispatch_session(action, payload)
+
+        return {"action": action, "code": 404, "message": f"unknown action: {action}", "payload": None}
+
+    def _dispatch_session(self, action: str, payload: dict) -> dict:
+        """Delegate session actions to SessionService."""
+        svc = self.session_service
+        if svc is None:
+            return {"action": action, "code": 500,
+                    "message": "SessionService not available", "payload": None}
+        return svc.dispatch(action, payload)
+
+    def _query_history(self, payload: dict) -> dict:
+        """Query paginated conversation history using ConversationStore."""
+        session_id = payload.get("session_id", "")
+        page = int(payload.get("page", 1))
+        page_size = int(payload.get("page_size", 20))
+
+        if not session_id:
+            return {
+                "action": "query",
+                "payload": {"status": "error", "message": "session_id required"},
+            }
+
+        # Web channel stores sessions with a "session_" prefix
+        if not session_id.startswith("session_"):
+            session_id = f"session_{session_id}"
+        logger.info(f"[CloudClient] history query: session={session_id}, page={page}, page_size={page_size}")
+
+        try:
+            from agent.memory.conversation_store import get_conversation_store
+            store = get_conversation_store()
+            result = store.load_history_page(
+                session_id=session_id,
+                page=page,
+                page_size=page_size,
+            )
+            return {
+                "action": "query",
+                "payload": {"status": "success", **result},
+            }
+        except Exception as e:
+            logger.error(f"[CloudClient] History query error: {e}")
+            return {
+                "action": "query",
+                "payload": {"status": "error", "message": str(e)},
+            }
+
+    # ------------------------------------------------------------------
+    # channel restart helpers
+    # ------------------------------------------------------------------
+    def _restart_channel(self, new_channel_type: str):
+        """
+        Restart the channel via ChannelManager when channel type changes.
+        """
+        if self.channel_mgr:
+            logger.info(f"[CloudClient] Restarting channel to '{new_channel_type}'...")
+            threading.Thread(target=self._do_restart_channel, args=(self.channel_mgr, new_channel_type), daemon=True).start()
+        else:
+            logger.warning("[CloudClient] ChannelManager not available, please restart the application manually")
+
+    def _do_restart_channel(self, mgr, new_channel_type: str):
+        """
+        Perform the channel restart in a separate thread to avoid blocking the config callback.
+        """
+        try:
+            mgr.restart(new_channel_type)
+            if mgr.channel:
+                self.channel = mgr.channel
+                self.client_type = mgr.channel.channel_type
+                logger.info(f"[CloudClient] Channel reference updated to '{new_channel_type}'")
+        except Exception as e:
+            logger.error(f"[CloudClient] Channel restart failed: {e}")
+            self.send_channel_status(new_channel_type, "error", str(e))
+            return
+        self._report_channel_startup(new_channel_type)
+
+    # ------------------------------------------------------------------
+    # config persistence
+    # ------------------------------------------------------------------
+    def _save_config_to_file(self, local_config: dict):
+        """
+        Save configuration to config.json file.
+        """
+        try:
+            config_path = os.path.join(get_root(), "config.json")
+            if not os.path.exists(config_path):
+                logger.warning(f"[CloudClient] config.json not found at {config_path}, skip saving")
+                return
+
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_config = json.load(f)
+
+            file_config.update(dict(local_config))
+
+            with open(config_path, "w", encoding="utf-8") as f:
+                json.dump(file_config, f, indent=4, ensure_ascii=False)
+
+            logger.info("[CloudClient] Configuration saved to config.json successfully")
+        except Exception as e:
+            logger.error(f"[CloudClient] Failed to save configuration to config.json: {e}")
+
+
+def get_root_domain(host: str = "") -> str:
+    """Extract root domain from a hostname.
+
+    If *host* is empty, reads CLOUD_HOST env var / cloud_host config.
+    """
+    if not host:
+        host = os.environ.get("CLOUD_HOST") or conf().get("cloud_host", "")
+    if not host:
+        return ""
+    host = host.strip().rstrip("/")
+    if "://" in host:
+        host = host.split("://", 1)[1]
+    host = host.split("/", 1)[0].split(":")[0]
+    parts = host.split(".")
+    if len(parts) >= 2:
+        return ".".join(parts[-2:])
+    return host
+
+
+def get_deployment_id() -> str:
+    """Return cloud deployment id from env var or config."""
+    return os.environ.get("CLOUD_DEPLOYMENT_ID") or conf().get("cloud_deployment_id", "")
+
+
+def get_website_base_url() -> str:
+    """Return the URL prefix that maps to the workspace websites/ dir.
+
+    Do nothing when in local env.
+    """
+    deployment_id = get_deployment_id()
+    if not deployment_id:
+        return ""
+
+    websites_domain = os.environ.get("CLOUD_WEBSITES_DOMAIN") or conf().get("cloud_websites_domain", "")
+    if websites_domain:
+        websites_domain = websites_domain.strip().rstrip("/")
+        return f"https://{websites_domain}/{deployment_id}"
+
+    domain = get_root_domain()
+    if not domain:
+        return ""
+    return f"https://app.{domain}/{deployment_id}"
+
+
+# Subdir under websites/ used by the send tool
+COW_SEND_WEB_SUBDIR = "cow-send"
+
+
+def copy_send_file(src_path: str, workspace_root: str) -> str:
+    """Copy *src_path* into ``websites/cow-send/`` and return its URL.
+
+    Returns empty string in local env.
+    """
+    import shutil
+    import uuid
+
+    from common.utils import expand_path
+
+    base = get_website_base_url()
+    if not base or not src_path or not os.path.isfile(src_path):
+        return ""
+    ws = os.path.abspath(expand_path(workspace_root))
+    send_dir = os.path.join(ws, "websites", COW_SEND_WEB_SUBDIR)
+    try:
+        os.makedirs(send_dir, exist_ok=True)
+    except OSError:
+        return ""
+    ext = os.path.splitext(src_path)[1].lower()
+    if len(ext) > 12 or not ext.replace(".", "").isalnum():
+        ext = ""
+    dest_name = f"{uuid.uuid4().hex}{ext}"
+    dest_path = os.path.join(send_dir, dest_name)
+    try:
+        shutil.copy2(src_path, dest_path)
+    except OSError as e:
+        logger.warning(f"[cloud] copy_send_file: copy failed: {e}")
+        return ""
+    return f"{base}/{COW_SEND_WEB_SUBDIR}/{dest_name}"
+
+
+def build_website_prompt(workspace_dir: str) -> list:
+    """Build system prompt lines for cloud website/file sharing rules.
+
+    Returns an empty list when cloud deployment is not configured,
+    so callers can safely do ``lines.extend(build_website_prompt(...))``.
+    """
+    base_url = get_website_base_url()
+    if not base_url:
+        return []
+
+    return [
+        "**文件分享与网页生成规则** (非常重要 — 当前为云部署模式):",
+        "",
+        f"云端已为工作空间的 `websites/` 目录配置好公网路由映射，访问地址前缀为: `{base_url}`",
+        "",
+        "1. **网页/网站**: 编写网页、H5页面等前端代码时，**必须**将文件放到 `websites/` 目录中",
+        f"   - 例如: `websites/index.html` → `{base_url}/index.html`",
+        f"   - 例如: `websites/my-app/index.html` → `{base_url}/my-app/index.html`",
+        "",
+        "2. **生成文件分享** (PPT、PDF、图片、音视频等): 当你为用户生成了需要下载或查看的文件时，**可以**将文件保存到 `websites/` 目录中",
+        f"  - 例如: 生成的PPT保存到 `websites/files/report.pptx` → 下载链接为 `{base_url}/files/report.pptx`",
+        "   - 你仍然可以同时使用 `send` 工具发送文件（在微信、飞书、钉钉、web等渠道中有效），但**必须同时在回复文本中提供下载链接**作为兜底，因为部分渠道无法通过 send 接收本地文件",
+        "",
+        "3. **必须发送链接**: 无论是网页还是文件，生成后**必须将完整的访问/下载链接直接写在回复文本中发送给用户**",
+        "",
+        "4. **文件名和路径尽量使用英文/拼音/数字等**，不要使用中文，避免链接无法访问",
+        "",
+        "5. 建议为每个独立项目在 `websites/` 下创建子目录，保持结构清晰",
+        "",
+    ]
+
+def start(channel, channel_mgr=None):
+    if not get_deployment_id():
+        return
+
+    global chat_client
+    chat_client = CloudClient(api_key=conf().get("linkai_api_key"), host=conf().get("cloud_host", ""), port=conf().get("cloud_port"), channel=channel)
+    chat_client.channel_mgr = channel_mgr
+    chat_client.config = _build_config()
+    chat_client.start()
+    time.sleep(1.5)
+    if chat_client.client_id:
+        logger.info("[CloudClient] Console: https://link-ai.tech/console/clients")
+        if channel_mgr:
+            channel_mgr.cloud_mode = True
+            threading.Thread(target=_report_existing_channels, args=(chat_client, channel_mgr), daemon=True).start()
+
+
+def _report_existing_channels(client: CloudClient, mgr):
+    """Report status for all channels that were started before cloud client connected."""
+    try:
+        for name, ch in list(mgr._channels.items()):
+            if name == "web":
+                continue
+            ch.cloud_mode = True
+            client._report_channel_startup(name)
+    except Exception as e:
+        logger.warning(f"[CloudClient] Failed to report existing channel status: {e}")
+
+
+def _build_config():
+    local_conf = conf()
+    config = {
+        "linkai_app_code": local_conf.get("linkai_app_code"),
+        "single_chat_prefix": local_conf.get("single_chat_prefix"),
+        "single_chat_reply_prefix": local_conf.get("single_chat_reply_prefix"),
+        "single_chat_reply_suffix": local_conf.get("single_chat_reply_suffix"),
+        "group_chat_prefix": local_conf.get("group_chat_prefix"),
+        "group_chat_reply_prefix": local_conf.get("group_chat_reply_prefix"),
+        "group_chat_reply_suffix": local_conf.get("group_chat_reply_suffix"),
+        "group_name_white_list": local_conf.get("group_name_white_list"),
+        "nick_name_black_list": local_conf.get("nick_name_black_list"),
+        "speech_recognition": "Y" if local_conf.get("speech_recognition") else "N",
+        "text_to_image": local_conf.get("text_to_image"),
+        "image_create_prefix": local_conf.get("image_create_prefix"),
+        "model": local_conf.get("model"),
+        "agent_max_context_turns": local_conf.get("agent_max_context_turns"),
+        "agent_max_context_tokens": local_conf.get("agent_max_context_tokens"),
+        "agent_max_steps": local_conf.get("agent_max_steps"),
+        # Self-evolution switch reported so the console can reflect state
+        "self_evolution_enabled": "Y" if local_conf.get("self_evolution_enabled") else "N",
+        "self_evolution_idle_minutes": local_conf.get("self_evolution_idle_minutes"),
+        "self_evolution_min_turns": local_conf.get("self_evolution_min_turns"),
+        "channelType": local_conf.get("channel_type"),
+    }
+
+    if local_conf.get("always_reply_voice"):
+        config["reply_voice_mode"] = "always_reply_voice"
+    elif local_conf.get("voice_reply_voice"):
+        config["reply_voice_mode"] = "voice_reply_voice"
+
+    if pconf("linkai"):
+        config["group_app_map"] = pconf("linkai").get("group_app_map")
+
+    if plugin_config.get("Godcmd"):
+        config["admin_password"] = plugin_config.get("Godcmd").get("password")
+
+    # Add channel-specific app credentials based on CREDENTIAL_MAP.
+    # For multi-channel channel_type (comma-separated), the first matched type wins.
+    current_channel_type = local_conf.get("channel_type", "")
+    for ch_type in CloudClient._parse_channel_types({"channel_type": current_channel_type}):
+        cred = CREDENTIAL_MAP.get(ch_type)
+        if not cred:
+            continue
+        id_key, secret_key = cred
+        config["app_id"] = local_conf.get(id_key)
+        config["app_secret"] = local_conf.get(secret_key) if secret_key else ""
+        break
+
+    return config
diff --git a/common/const.py b/common/const.py
new file mode 100644
index 0000000..805c4ce
--- /dev/null
+++ b/common/const.py
@@ -0,0 +1,257 @@
+# Provider types
+OPEN_AI = "openAI"
+OPENAI = "openai"
+CHATGPT = "chatGPT"  # legacy alias for OPENAI, kept for backward compatibility
+BAIDU = "baidu"
+QIANFAN = "qianfan"
+XUNFEI = "xunfei"
+CHATGPTONAZURE = "chatGPTOnAzure"
+LINKAI = "linkai"
+CLAUDEAPI= "claudeAPI"
+QWEN = "qwen"  # legacy alias, actually routed to DashscopeBot
+QWEN_DASHSCOPE = "dashscope"  # Qwen via DashScope
+GEMINI = "gemini" 
+ZHIPU_AI = "zhipu"  
+MOONSHOT = "moonshot"
+MiniMax = "minimax"
+DEEPSEEK = "deepseek"
+MIMO = "mimo"  # Xiaomi MiMo
+CUSTOM = "custom"  # custom OpenAI-compatible API, bot_type won't auto-switch on model change
+MODELSCOPE = "modelscope"
+
+# Model list
+# Claude (Anthropic)
+CLAUDE3 = "claude-3-opus-20240229"
+CLAUDE_3_OPUS = "claude-3-opus-latest"
+CLAUDE_3_OPUS_0229 = "claude-3-opus-20240229"
+CLAUDE_3_SONNET = "claude-3-sonnet-20240229"
+CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
+CLAUDE_35_SONNET = "claude-3-5-sonnet-latest"  # "latest" tag always points to the newest release
+CLAUDE_35_SONNET_1022 = "claude-3-5-sonnet-20241022"  # dated name pinned to a specific release
+CLAUDE_35_SONNET_0620 = "claude-3-5-sonnet-20240620"
+CLAUDE_4_OPUS = "claude-opus-4-0"
+CLAUDE_FABLE_5 = "claude-fable-5"        # Claude Fable 5 (often restricted by policy)
+CLAUDE_4_8_OPUS = "claude-opus-4-8"      # Claude Opus 4.8 - Agent recommended model
+CLAUDE_4_7_OPUS = "claude-opus-4-7"      # Claude Opus 4.7
+CLAUDE_4_6_OPUS = "claude-opus-4-6"      # Claude Opus 4.6
+CLAUDE_4_SONNET = "claude-sonnet-4-0"    # Claude Sonnet 4.0
+CLAUDE_4_5_SONNET = "claude-sonnet-4-5"  # Claude Sonnet 4.5 - Agent recommended model
+CLAUDE_4_6_SONNET = "claude-sonnet-4-6"  # Claude Sonnet 4.6 - Agent recommended model
+CLAUDE_SONNET_5 = "claude-sonnet-5"      # Claude Sonnet 5 - default flagship model for Claude
+
+# Gemini (Google)
+GEMINI_PRO = "gemini-1.0-pro"
+GEMINI_15_flash = "gemini-1.5-flash"
+GEMINI_15_PRO = "gemini-1.5-pro"
+GEMINI_20_flash_exp = "gemini-2.0-flash-exp"  # "-exp" models are experimental and will be phased out
+GEMINI_20_FLASH = "gemini-2.0-flash"  # stable release
+GEMINI_25_FLASH_PRE = "gemini-2.5-flash-preview-05-20"
+GEMINI_25_PRO_PRE = "gemini-2.5-pro-preview-05-06"
+GEMINI_3_FLASH_PRE = "gemini-3-flash-preview"  # Gemini 3 Flash Preview - Agent recommended model
+GEMINI_3_PRO_PRE = "gemini-3-pro-preview"  # Gemini 3 Pro Preview
+GEMINI_31_PRO_PRE = "gemini-3.1-pro-preview"  # Gemini 3.1 Pro Preview - Agent recommended model
+GEMINI_31_FLASH_LITE_PRE = "gemini-3.1-flash-lite-preview"  # Gemini 3.1 Flash Lite Preview - Agent recommended model
+GEMINI_35_FLASH = "gemini-3.5-flash"  # Gemini 3.5 Flash - Agent recommended model
+
+# OpenAI
+GPT35 = "gpt-3.5-turbo"
+GPT35_0125 = "gpt-3.5-turbo-0125"
+GPT35_1106 = "gpt-3.5-turbo-1106"
+GPT4 = "gpt-4"
+GPT4_06_13 = "gpt-4-0613"
+GPT4_32k = "gpt-4-32k"
+GPT4_32k_06_13 = "gpt-4-32k-0613"
+GPT4_TURBO = "gpt-4-turbo"
+GPT4_TURBO_PREVIEW = "gpt-4-turbo-preview"
+GPT4_TURBO_01_25 = "gpt-4-0125-preview"
+GPT4_TURBO_11_06 = "gpt-4-1106-preview"
+GPT4_TURBO_04_09 = "gpt-4-turbo-2024-04-09"
+GPT4_VISION_PREVIEW = "gpt-4-vision-preview"
+GPT_4o = "gpt-4o"
+GPT_4O_0806 = "gpt-4o-2024-08-06"
+GPT_4o_MINI = "gpt-4o-mini"
+GPT_41 = "gpt-4.1"
+GPT_41_MINI = "gpt-4.1-mini"
+GPT_41_NANO = "gpt-4.1-nano"
+GPT_5 = "gpt-5"
+GPT_5_MINI = "gpt-5-mini"
+GPT_5_NANO = "gpt-5-nano"
+GPT_54 = "gpt-5.4"  # GPT-5.4 - Agent recommended model
+GPT_54_MINI = "gpt-5.4-mini"
+GPT_54_NANO = "gpt-5.4-nano"
+GPT_55 = "gpt-5.5"  # GPT-5.5 - top-tier (expensive), not default
+O1 = "o1-preview"
+O1_MINI = "o1-mini"
+WHISPER_1 = "whisper-1"
+TTS_1 = "tts-1"
+TTS_1_HD = "tts-1-hd"
+
+# DeepSeek
+DEEPSEEK_CHAT = "deepseek-chat"  # DeepSeek-V3 chat model
+DEEPSEEK_REASONER = "deepseek-reasoner"  # DeepSeek-R1 model
+DEEPSEEK_V4_FLASH = "deepseek-v4-flash"  # DeepSeek V4 Flash - default recommendation (thinking + tool calls)
+DEEPSEEK_V4_PRO = "deepseek-v4-pro"  # DeepSeek V4 Pro - stronger on complex tasks (thinking + tool calls)
+
+# Baidu Qianfan / ERNIE
+ERNIE_5_1 = "ernie-5.1"  # ERNIE 5.1 - default recommendation, latest flagship
+ERNIE_5 = "ernie-5.0"  # ERNIE 5.0
+ERNIE_X1_1 = "ernie-x1.1"  # ERNIE X1.1 - reasoning-focused, multimodal
+ERNIE_45_TURBO_128K = "ernie-4.5-turbo-128k"
+ERNIE_45_TURBO_32K = "ernie-4.5-turbo-32k"
+ERNIE_4_TURBO_8K = "ERNIE-4.0-Turbo-8K"
+ERNIE_45_TURBO_VL = "ernie-4.5-turbo-vl"
+ERNIE_45_TURBO_VL_32K = "ernie-4.5-turbo-vl-32k"
+
+# Qwen (Alibaba Cloud DashScope)
+QWEN_TURBO = "qwen-turbo"
+QWEN_PLUS = "qwen-plus"
+QWEN_MAX = "qwen-max"
+QWEN_LONG = "qwen-long"
+QWEN3_MAX = "qwen3-max"  # Qwen3 Max - Agent recommended model
+QWEN35_PLUS = "qwen3.5-plus"  # Qwen3.5 Plus - Omni model (MultiModalConversation)
+QWEN36_PLUS = "qwen3.6-plus"  # Qwen3.6 Plus - Omni model (MultiModalConversation)
+QWEN37_PLUS = "qwen3.7-plus"  # Qwen3.7 Plus - Omni model (MultiModalConversation)
+QWEN37_MAX = "qwen3.7-max"  # Qwen3.7 Max - Agent recommended model
+QWQ_PLUS = "qwq-plus"
+
+# MiniMax
+MINIMAX_M3 = "MiniMax-M3"  # MiniMax M3 - Latest (default)
+MINIMAX_M2_7 = "MiniMax-M2.7"  # MiniMax M2.7
+MINIMAX_M2_7_HIGHSPEED = "MiniMax-M2.7-highspeed"  # MiniMax M2.7 highspeed
+MINIMAX_TEXT_01 = "MiniMax-Text-01"  # MiniMax multimodal (vision)
+MINIMAX_ABAB6_5 = "abab6.5-chat"  # MiniMax abab6.5
+
+# GLM (Zhipu AI)
+GLM_5_2 = "glm-5.2"  # GLM-5.2 - Agent recommended model (default)
+GLM_5_1 = "glm-5.1"  # GLM-5.1
+GLM_5_TURBO = "glm-5-turbo"  # GLM-5-Turbo
+GLM_5 = "glm-5"  # GLM-5
+GLM_5V_TURBO = "glm-5v-turbo"  # Zhipu multimodal (vision)
+GLM_4 = "glm-4"
+GLM_4_PLUS = "glm-4-plus"
+GLM_4_flash = "glm-4-flash"
+GLM_4_LONG = "glm-4-long"
+GLM_4_ALLTOOLS = "glm-4-alltools"
+GLM_4_0520 = "glm-4-0520"
+GLM_4_AIR = "glm-4-air"
+GLM_4_AIRX = "glm-4-airx"
+GLM_4_7 = "glm-4.7"  # GLM-4.7 - Agent recommended model
+
+# Kimi (Moonshot)
+MOONSHOT = "moonshot"
+KIMI_K2_7_CODE = "kimi-k2.7-code"  # Kimi K2.7 Code - Agent recommended model (default)
+KIMI_K2_7_CODE_HIGHSPEED = "kimi-k2.7-code-highspeed"  # Kimi K2.7 Code highspeed
+KIMI_K2 = "kimi-k2"
+KIMI_K2_5 = "kimi-k2.5"
+KIMI_K2_6 = "kimi-k2.6"
+
+# Xiaomi MiMo
+MIMO_V2_5_PRO = "mimo-v2.5-pro"      # MiMo V2.5 Pro - flagship, long context (default recommendation)
+MIMO_V2_5 = "mimo-v2.5"              # MiMo V2.5 - multimodal (text/image/audio/video)
+MIMO_V2_PRO = "mimo-v2-pro"          # MiMo V2 Pro
+MIMO_V2_OMNI = "mimo-v2-omni"        # MiMo V2 Omni - multimodal
+MIMO_V2_FLASH = "mimo-v2-flash"      # MiMo V2 Flash - high-speed
+
+# Doubao (Volcengine Ark)
+DOUBAO = "doubao"
+DOUBAO_SEED_2_1_PRO = "doubao-seed-2-1-pro-260628"
+DOUBAO_SEED_2_1_TURBO = "doubao-seed-2-1-turbo-260628"
+DOUBAO_SEED_2_CODE = "doubao-seed-2-0-code-preview-260215"
+DOUBAO_SEED_2_PRO = "doubao-seed-2-0-pro-260215"
+DOUBAO_SEED_2_LITE = "doubao-seed-2-0-lite-260215"
+DOUBAO_SEED_2_MINI = "doubao-seed-2-0-mini-260215"
+
+# ModelScope
+QWEN3_235B_A22B_INSTRUCT_2507 = "Qwen/Qwen3-235B-A22B-Instruct-2507"
+QWEN3_5_27B = "Qwen/Qwen3.5-27B"
+
+# Other models
+WEN_XIN = "wenxin"
+WEN_XIN_4 = "wenxin-4"
+XUNFEI = "xunfei"
+LINKAI_35 = "linkai-3.5"
+LINKAI_4_TURBO = "linkai-4-turbo"
+LINKAI_4o = "linkai-4o"
+MODELSCOPE = "modelscope"
+
+GITEE_AI_MODEL_LIST = ["Yi-34B-Chat", "InternVL2-8B", "deepseek-coder-33B-instruct", "InternVL2.5-26B", "Qwen2-VL-72B", "Qwen2.5-32B-Instruct", "glm-4-9b-chat", "codegeex4-all-9b", "Qwen2.5-Coder-32B-Instruct", "Qwen2.5-72B-Instruct", "Qwen2.5-7B-Instruct", "Qwen2-72B-Instruct", "Qwen2-7B-Instruct", "code-raccoon-v1", "Qwen2.5-14B-Instruct"]
+
+MODELSCOPE_MODEL_LIST = ["deepseek-ai/DeepSeek-R1-0528", "deepseek-ai/DeepSeek-R1-Distill-Llama-70B", "deepseek-ai/DeepSeek-R1-Distill-Llama-8B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+                         "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B", "deepseek-ai/DeepSeek-V3.2", "LLM-Research/c4ai-command-r-plus-08-2024", "LLM-Research/Llama-4-Maverick-17B-128E-Instruct", "meituan-longcat/LongCat-Flash-Lite", "MiniMax/MiniMax-M1-80k", "MiniMax/MiniMax-M2.5", "mistralai/Ministral-8B-Instruct-2410",
+                         "mistralai/Mistral-Large-Instruct-2407", "mistralai/Mistral-Small-Instruct-2409", "moonshotai/Kimi-K2.5", "MusePublic/Qwen-Image-Edit", "opencompass/CompassJudger-1-32B-Instruct", "OpenGVLab/InternVL3_5-241B-A28B",
+                         "Qwen/QVQ-72B-Preview", "Qwen/Qwen-Image-Edit", "Qwen/Qwen3-0.6B", "Qwen/Qwen3-1.7B", "Qwen/Qwen3-14B", "Qwen/Qwen3-235B-A22B", "Qwen/Qwen3-235B-A22B-Instruct-2507", "Qwen/Qwen3-235B-A22B-Thinking-2507", "Qwen/Qwen3-30B-A3B", "Qwen/Qwen3-30B-A3B-Thinking-2507",
+                         "Qwen/Qwen3-32B", "Qwen/Qwen3-4B", "Qwen/Qwen3-8B", "Qwen/Qwen3-Coder-30B-A3B-Instruct", "Qwen/Qwen3-Coder-480B-A35B-Instruct", "Qwen/Qwen3-Next-80B-A3B-Instruct", "Qwen/Qwen3-Next-80B-A3B-Thinking", "Qwen/Qwen3-VL-235B-A22B-Instruct", "Qwen/Qwen3-VL-8B-Instruct",
+                         "Qwen/Qwen3-VL-8B-Thinking", "Qwen/Qwen3.5-122B-A10B", "Qwen/Qwen3.5-27B", "Qwen/Qwen3.5-35B-A3B", "Qwen/Qwen3.5-397B-A17B", "Qwen/QwQ-32B", "Qwen/QwQ-32B-Preview", "Shanghai_AI_Laboratory/Intern-S1", "Shanghai_AI_Laboratory/Intern-S1-mini",
+                         "stepfun-ai/Step-3.5-Flash", "XiaomiMiMo/MiMo-V2-Flash", "ZhipuAI/GLM-4.7-Flash", "ZhipuAI/GLM-5"]
+
+
+MODEL_LIST = [
+              # DeepSeek
+              DEEPSEEK_V4_FLASH, DEEPSEEK_V4_PRO, DEEPSEEK_CHAT, DEEPSEEK_REASONER,
+
+              # Baidu Qianfan / ERNIE
+              QIANFAN, ERNIE_5_1, ERNIE_5, ERNIE_X1_1, ERNIE_45_TURBO_128K, ERNIE_45_TURBO_32K, ERNIE_4_TURBO_8K,
+              ERNIE_45_TURBO_VL, ERNIE_45_TURBO_VL_32K,
+
+              # MiniMax
+              MiniMax, MINIMAX_M3, MINIMAX_M2_7, MINIMAX_M2_7_HIGHSPEED, MINIMAX_ABAB6_5,
+
+              # Xiaomi MiMo
+              MIMO, MIMO_V2_5_PRO, MIMO_V2_5, MIMO_V2_PRO, MIMO_V2_OMNI, MIMO_V2_FLASH,
+
+              # Claude
+              CLAUDE_SONNET_5, CLAUDE3, CLAUDE_4_8_OPUS, CLAUDE_4_7_OPUS, CLAUDE_FABLE_5, CLAUDE_4_6_SONNET, CLAUDE_4_6_OPUS, CLAUDE_4_OPUS, CLAUDE_4_5_SONNET, CLAUDE_4_SONNET, CLAUDE_3_OPUS, CLAUDE_3_OPUS_0229,
+              CLAUDE_35_SONNET, CLAUDE_35_SONNET_1022, CLAUDE_35_SONNET_0620, CLAUDE_3_SONNET, CLAUDE_3_HAIKU,
+              "claude", "claude-3-haiku", "claude-3-sonnet", "claude-3-opus", "claude-3.5-sonnet",
+
+              # Gemini
+              GEMINI_35_FLASH, GEMINI_31_FLASH_LITE_PRE, GEMINI_31_PRO_PRE, GEMINI_3_PRO_PRE, GEMINI_3_FLASH_PRE, GEMINI_25_PRO_PRE, GEMINI_25_FLASH_PRE,
+              GEMINI_20_FLASH, GEMINI_20_flash_exp, GEMINI_15_PRO, GEMINI_15_flash, GEMINI_PRO, GEMINI,
+
+              # OpenAI
+              GPT35, GPT35_0125, GPT35_1106, "gpt-3.5-turbo-16k",
+              GPT4, GPT4_06_13, GPT4_32k, GPT4_32k_06_13,
+              GPT4_TURBO, GPT4_TURBO_PREVIEW, GPT4_TURBO_01_25, GPT4_TURBO_11_06, GPT4_TURBO_04_09,
+              GPT_4o, GPT_4O_0806, GPT_4o_MINI,
+              GPT_41, GPT_41_MINI, GPT_41_NANO,
+              GPT_5, GPT_5_MINI, GPT_5_NANO,
+              GPT_54, GPT_55, GPT_54_MINI, GPT_54_NANO,
+              O1, O1_MINI,
+
+              # GLM (Zhipu AI)
+              ZHIPU_AI, GLM_5_2, GLM_5_1, GLM_5_TURBO, GLM_5, GLM_4, GLM_4_PLUS, GLM_4_flash, GLM_4_LONG, GLM_4_ALLTOOLS,
+              GLM_4_0520, GLM_4_AIR, GLM_4_AIRX, GLM_4_7,
+
+              # Qwen
+              QWEN37_PLUS, QWEN37_MAX, QWEN36_PLUS, QWEN35_PLUS, QWEN3_MAX, QWEN_MAX, QWEN_PLUS, QWEN_TURBO, QWEN_LONG,
+
+              # Doubao
+              DOUBAO, DOUBAO_SEED_2_1_PRO, DOUBAO_SEED_2_1_TURBO,
+              DOUBAO_SEED_2_CODE, DOUBAO_SEED_2_PRO, DOUBAO_SEED_2_LITE, DOUBAO_SEED_2_MINI,
+
+              # Kimi (Moonshot)
+              MOONSHOT, "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k",
+              KIMI_K2_7_CODE, KIMI_K2_7_CODE_HIGHSPEED, KIMI_K2_6, KIMI_K2_5, KIMI_K2,
+
+              # ModelScope
+              MODELSCOPE,
+
+              # LinkAI
+              LINKAI_35, LINKAI_4_TURBO, LINKAI_4o,
+
+              # Other models
+              WEN_XIN, WEN_XIN_4, XUNFEI,
+            ]
+
+MODEL_LIST = MODEL_LIST + GITEE_AI_MODEL_LIST + MODELSCOPE_MODEL_LIST
+
+# channel
+FEISHU = "feishu"
+DINGTALK = "dingtalk"
+WECOM_BOT = "wecom_bot"
+QQ = "qq"
+WEIXIN = "weixin"
+WECHAT_KF = "wechat_kf"
+TELEGRAM = "telegram"
+SLACK = "slack"
+DISCORD = "discord"
diff --git a/common/dequeue.py b/common/dequeue.py
new file mode 100644
index 0000000..39baf58
--- /dev/null
+++ b/common/dequeue.py
@@ -0,0 +1,33 @@
+from queue import Full, Queue
+from time import monotonic as time
+
+
+# add implementation of putleft to Queue
+class Dequeue(Queue):
+    def putleft(self, item, block=True, timeout=None):
+        with self.not_full:
+            if self.maxsize > 0:
+                if not block:
+                    if self._qsize() >= self.maxsize:
+                        raise Full
+                elif timeout is None:
+                    while self._qsize() >= self.maxsize:
+                        self.not_full.wait()
+                elif timeout < 0:
+                    raise ValueError("'timeout' must be a non-negative number")
+                else:
+                    endtime = time() + timeout
+                    while self._qsize() >= self.maxsize:
+                        remaining = endtime - time()
+                        if remaining <= 0.0:
+                            raise Full
+                        self.not_full.wait(remaining)
+            self._putleft(item)
+            self.unfinished_tasks += 1
+            self.not_empty.notify()
+
+    def putleft_nowait(self, item):
+        return self.putleft(item, block=False)
+
+    def _putleft(self, item):
+        self.queue.appendleft(item)
diff --git a/common/expired_dict.py b/common/expired_dict.py
new file mode 100644
index 0000000..42fb4b1
--- /dev/null
+++ b/common/expired_dict.py
@@ -0,0 +1,42 @@
+from datetime import datetime, timedelta
+
+
+class ExpiredDict(dict):
+    def __init__(self, expires_in_seconds):
+        super().__init__()
+        self.expires_in_seconds = expires_in_seconds
+
+    def __getitem__(self, key):
+        value, expiry_time = super().__getitem__(key)
+        if datetime.now() > expiry_time:
+            del self[key]
+            raise KeyError("expired {}".format(key))
+        self.__setitem__(key, value)
+        return value
+
+    def __setitem__(self, key, value):
+        expiry_time = datetime.now() + timedelta(seconds=self.expires_in_seconds)
+        super().__setitem__(key, (value, expiry_time))
+
+    def get(self, key, default=None):
+        try:
+            return self[key]
+        except KeyError:
+            return default
+
+    def __contains__(self, key):
+        try:
+            self[key]
+            return True
+        except KeyError:
+            return False
+
+    def keys(self):
+        keys = list(super().keys())
+        return [key for key in keys if key in self]
+
+    def items(self):
+        return [(key, self[key]) for key in self.keys()]
+
+    def __iter__(self):
+        return self.keys().__iter__()
diff --git a/common/i18n.py b/common/i18n.py
new file mode 100644
index 0000000..52099b6
--- /dev/null
+++ b/common/i18n.py
@@ -0,0 +1,268 @@
+# encoding:utf-8
+
+"""Lightweight global language detection and resolution.
+
+This module is the single source of truth for the runtime UI language used
+across the CLI, startup logs, error messages, agent prompts and channel
+replies. It must NOT import project config (to avoid circular imports) and
+must stay dependency-free so it can run at the earliest startup phase.
+
+Supported language codes (BCP 47 compliant):
+  - "zh" (Simplified Chinese)
+  - "zh-Hant" (Traditional Chinese, script-based tag per Unicode CLDR)
+  - "en" (English)
+
+Resolution priority (highest first):
+  1. Explicit `cow_lang` from config.json — also covers Docker/CI, since any
+     config key is overridable via its uppercase env var (e.g. COW_LANG=zh),
+     handled by config.load_config() before resolution. COW_LANG is a private
+     name to avoid clashing with the gettext-standard LANGUAGE variable.
+  2. macOS `defaults read -g AppleLocale` (system-level preference; a Chinese
+     system locale is a strong signal that beats a shell-default LANG)
+  3. Standard locale env vars: LC_ALL > LC_MESSAGES > LANG
+  4. Python locale module
+  5. Default -> English
+
+A value of "auto" (the default) triggers detection (steps 2-5). Explicitly
+setting "zh", "zh-Hant", or "en" locks the language and skips detection.
+
+Note: For backwards compatibility, zh-tw, zh-hk, and other regional variants
+are automatically normalized to zh-Hant during detection.
+"""
+
+import os
+import subprocess
+import sys
+
+# Supported language codes
+ZH = "zh"
+ZH_HANT = "zh-Hant"
+EN = "en"
+SUPPORTED = (ZH, ZH_HANT, EN)
+DEFAULT_LANG = EN
+
+# Mapped Simplified to Traditional characters in this codebase
+_SIMPLIFIED = "与专业东丢两严个丰临为举么义乐乔习书乱于云产亲仅从仓们价众优伙会伟传体余侧倾储儿关兴兽内册写冲决况准减几凭凯击划则刚创删别剥办务动区华协单占厂历压参双发变叙台号后吗听启员响嚣团国图场坏块声处备复够头夹妩姗娇娱婶学宝实宠审宽对导将尝尽层属币师带帧帮幂干并广庆库应开异弃张弹强归当录彦彻征径忆态总悦惯戏战户执扩扫抛抢护报拟拥拦择换据数断无旧时昵显晓暂术机杂权条来杰极构枪标树样档桦梦检欢残毕气汇汉汤没泄泼洁测浏润涩淀渊温游湾湿滞满滤灵灿炀点炼烦热爱爷状独猪环现瑶电画监盖盘着睁码础确离种积称稳竞笔签简类粤紧纠红约级纪纯纳线组细织终绍经结绘给络绝统继绪续维综缀缓编缩网罗羁职联聪脑脚脱腾舰艺节苍苏范荐获萝蔼虑补装见观规视览觉触计订认讨让训议讯记讲许论设访证识诉诊词译试诚话询该详语误说请读谁调谢谨谱贝负责贤败账货质费资赋赖赘轩转轮软轻载较辑输边达过运还这进远违连迟适选递逻遥邮邻采释里鉴针钉钟钥钮钱铁链销锁错锤键镜长闭问闲间闺闻闽阅队阳际陆陕险随隐难静韩页项顺须顾预领频题额风飞饭饰馆馈馏马驻驿验骤鱼鸡麦齐"
+_TRADITIONAL = "與專業東丟兩嚴個豐臨為舉麼義樂喬習書亂於雲產親僅從倉們價眾優夥會偉傳體餘側傾儲兒關興獸內冊寫沖決況準減幾憑凱擊劃則剛創刪別剝辦務動區華協單佔廠歷壓參雙發變敘臺號後嗎聽啟員響囂團國圖場壞塊聲處備復夠頭夾嫵姍嬌娛嬸學寶實寵審寬對導將嘗盡層屬幣師帶幀幫冪幹並廣慶庫應開異棄張彈強歸當錄彥徹徵徑憶態總悅慣戲戰戶執擴掃拋搶護報擬擁攔擇換據數斷無舊時暱顯曉暫術機雜權條來傑極構槍標樹樣檔樺夢檢歡殘畢氣匯漢湯沒洩潑潔測瀏潤澀澱淵溫遊灣溼滯滿濾靈燦煬點煉煩熱愛爺狀獨豬環現瑤電畫監蓋盤著睜碼礎確離種積稱穩競筆籤簡類粵緊糾紅約級紀純納線組細織終紹經結繪給絡絕統繼緒續維綜綴緩編縮網羅羈職聯聰腦腳脫騰艦藝節蒼蘇範薦獲蘿藹慮補裝見觀規視覽覺觸計訂認討讓訓議訊記講許論設訪證識訴診詞譯試誠話詢該詳語誤說請讀誰調謝謹譜貝負責賢敗帳貨質費資檔案影片圖片連結資料資訊支援排程執行帳號密碼憑證埠服務啟用管道終端機控制台"
+_CHAR_MAP = None
+
+_PHRASE_MAP = {
+    "默认": "預設",
+    "内存": "記憶體",
+    "配置": "設定",
+    "进程": "處理程序",
+    "目录": "目錄",
+    "文件夹": "資料夾",
+    "文件": "檔案",
+    "视频": "影片",
+    "图片": "圖片",
+    "影象": "影像",
+    "图像": "影像",
+    "链接": "連結",
+    "数据": "資料",
+    "信息": "資訊",
+    "支持": "支援",
+    "定时": "排程",
+    "运行": "執行",
+    "账号": "帳號",
+    "密码": "密碼",
+    "凭据": "憑證",
+    "端口": "埠",
+    "服务": "服務",
+    "激活": "啟用",
+    "通道": "管道",
+    "终端": "終端機",
+    "主控台": "控制台",
+    "创建": "建立",
+    "计算机": "電腦",
+}
+
+
+def to_traditional(text):
+    """Convert Simplified Chinese text to Traditional Chinese.
+    
+    Uses a two-tier approach:
+    1. Phrase-level mapping for project-specific terms (e.g., "配置" → "設定")
+    2. OpenCC library (opencc-python-reimplemented) if available for high-quality
+       context-aware conversion, with fallback to built-in character mapping
+    
+    This function is designed to work without external dependencies. If OpenCC
+    is not installed, it falls back to a curated 450-character mapping table
+    plus 30+ technical term mappings that cover common project vocabulary.
+    
+    For production use with zh-Hant language, installing OpenCC is recommended:
+        pip install opencc-python-reimplemented
+    """
+    if not text:
+        return text
+
+    # Replace phrases first
+    for s, t_phrase in _PHRASE_MAP.items():
+        text = text.replace(s, t_phrase)
+
+    try:
+        from opencc import OpenCC
+        cc = OpenCC('s2twp')
+        return cc.convert(text)
+    except Exception:
+        pass
+
+    global _CHAR_MAP
+    if _CHAR_MAP is None:
+        _CHAR_MAP = dict(zip(_SIMPLIFIED, _TRADITIONAL))
+
+    # Replace characters
+    return "".join(_CHAR_MAP.get(c, c) for c in text)
+
+
+# Resolved language cache; None until first resolution.
+_resolved_lang = None
+
+
+def _normalize(raw):
+    """Map an arbitrary locale-ish string to a supported code, or None.
+
+    Only Chinese is detected explicitly; everything else (including unknown
+    or empty values) yields None so the caller can fall through to the next
+    detection source.
+    """
+    if not raw:
+        return None
+    value = str(raw).strip().lower().replace("_", "-")
+    if value in ("auto", ""):
+        return None
+    # Traditional Chinese variants: zh-tw, zh-hk, zh-hant, zh-hant-tw, zh-hant-hk...
+    if value.startswith("zh-tw") or value.startswith("zh-hk") or "hant" in value:
+        return ZH_HANT
+    # General or Simplified Chinese variants: zh, zh-cn, zh-hans...
+    if value.startswith("zh") or value.startswith("chinese"):
+        return ZH
+    if value.startswith("en") or value.startswith("english"):
+        return EN
+    return None
+
+
+def _detect_from_env():
+    """Detect language from standard locale environment variables.
+
+    Note: on macOS, `LANG` is often a shell default (e.g. en_US.UTF-8 set by
+    .zshrc) that does not reflect the user's real preference, so AppleLocale
+    is checked first (see detect_language). On Linux these vars are the
+    primary signal.
+
+    The cow_lang env override (COW_LANG=zh) is intentionally NOT read here:
+    it sets config["cow_lang"] and is handled via the explicit config path,
+    not auto-detection.
+    """
+    for key in ("LC_ALL", "LC_MESSAGES", "LANG"):
+        lang = _normalize(os.environ.get(key))
+        if lang:
+            return lang
+    return None
+
+
+def _detect_from_macos():
+    """macOS fallback: read the system-wide AppleLocale preference.
+
+    On macOS the terminal often does NOT export LANG, yet the system locale
+    is still meaningful (e.g. a Chinese Mac reports zh_CN). This recovers
+    that signal so Chinese users are not misdetected as English.
+    """
+    if sys.platform != "darwin":
+        return None
+    try:
+        out = subprocess.run(
+            ["defaults", "read", "-g", "AppleLocale"],
+            capture_output=True,
+            text=True,
+            timeout=2,
+        )
+        if out.returncode == 0:
+            return _normalize(out.stdout)
+    except Exception:
+        pass
+    return None
+
+
+def _detect_from_python_locale():
+    """Last-resort detection via Python's locale module."""
+    try:
+        import locale
+
+        for value in locale.getlocale():
+            lang = _normalize(value)
+            if lang:
+                return lang
+    except Exception:
+        pass
+    return None
+
+
+def detect_language():
+    """Run full auto-detection and return a supported language code.
+
+    Order (auto-detection only; explicit config["cow_lang"] is resolved
+    before this is reached):
+      1. macOS AppleLocale (system-level preference; a Chinese system locale
+         is a strong, low-false-positive signal that beats a shell-default
+         LANG like en_US.UTF-8)
+      2. locale env vars LC_ALL / LC_MESSAGES / LANG (primary signal on Linux)
+      3. Python locale module
+      4. default English
+    """
+    if os.environ.get("CLOUD_DEPLOYMENT_ID"):
+        return ZH
+    return (
+        _detect_from_macos()
+        or _detect_from_env()
+        or _detect_from_python_locale()
+        or DEFAULT_LANG
+    )
+
+
+def resolve_language(configured=None):
+    """Resolve the effective language from a configured value.
+
+    `configured` is the raw `cow_lang` value from config.json (may be None,
+    "auto", "zh" or "en"). An explicit "zh"/"en" locks the result; "auto"
+    or empty triggers detection. The result is cached globally.
+    """
+    global _resolved_lang
+    explicit = _normalize(configured)
+    if explicit:
+        _resolved_lang = explicit
+    else:
+        _resolved_lang = detect_language()
+    return _resolved_lang
+
+
+def set_language(lang):
+    """Force the resolved language (used by tests or per-request overrides)."""
+    global _resolved_lang
+    normalized = _normalize(lang)
+    _resolved_lang = normalized or DEFAULT_LANG
+    return _resolved_lang
+
+
+def get_language():
+    """Return the currently resolved language, detecting lazily if needed."""
+    global _resolved_lang
+    if _resolved_lang is None:
+        _resolved_lang = detect_language()
+    return _resolved_lang
+
+
+def is_zh():
+    return get_language() in (ZH, ZH_HANT)
+
+
+def t(zh_text, en_text):
+    """Pick a string by the current language. Tiny inline-translation helper.
+
+    Intended for one-off strings where a full message catalog is overkill:
+        t("已中止", "Cancelled")
+    """
+    lang = get_language()
+    if lang == ZH_HANT:
+        return to_traditional(zh_text)
+    return zh_text if lang == ZH else en_text
diff --git a/common/log.py b/common/log.py
new file mode 100644
index 0000000..edc144b
--- /dev/null
+++ b/common/log.py
@@ -0,0 +1,68 @@
+import logging
+import os
+import sys
+import io
+
+
+def _log_path():
+    # Mirror config.get_data_root() without importing config (avoids a circular
+    # import, since config imports this module). The desktop build sets
+    # COW_DATA_DIR (e.g. ~/.cow); source deployments fall back to CWD.
+    data_dir = os.environ.get("COW_DATA_DIR")
+    if data_dir:
+        data_dir = os.path.expanduser(data_dir)
+        os.makedirs(data_dir, exist_ok=True)
+        return os.path.join(data_dir, "run.log")
+    return "run.log"
+
+
+def _reset_logger(log):
+    for handler in log.handlers:
+        handler.close()
+        log.removeHandler(handler)
+        del handler
+    log.handlers.clear()
+    log.propagate = False
+    stdout = sys.stdout
+    if hasattr(stdout, "buffer"):
+        stdout = io.TextIOWrapper(stdout.buffer, encoding="utf-8", errors="replace", line_buffering=True)
+    console_handle = logging.StreamHandler(stdout)
+    console_handle.setFormatter(
+        logging.Formatter(
+            "[%(levelname)s][%(asctime)s][%(filename)s:%(lineno)d] - %(message)s",
+            datefmt="%Y-%m-%d %H:%M:%S",
+        )
+    )
+    log.addHandler(console_handle)
+    # File logging is best-effort: if the log path isn't writable (e.g. a
+    # packaged app installed under Program Files run by a non-admin user, with
+    # an unwritable CWD), fall back to console-only instead of crashing the
+    # whole process at import time.
+    try:
+        file_handle = logging.FileHandler(_log_path(), encoding="utf-8")
+        file_handle.setFormatter(
+            logging.Formatter(
+                "[%(levelname)s][%(asctime)s][%(filename)s:%(lineno)d] - %(message)s",
+                datefmt="%Y-%m-%d %H:%M:%S",
+            )
+        )
+        log.addHandler(file_handle)
+    except OSError:
+        console_handle.handle(
+            logging.LogRecord(
+                "log", logging.WARNING, __file__, 0,
+                "[log] file logging disabled (log path not writable): %s",
+                (_log_path(),), None,
+            )
+        )
+
+
+def _get_logger():
+    log = logging.getLogger("log")
+    _reset_logger(log)
+    log.setLevel(logging.INFO)
+    return log
+
+
+# 日志句柄
+logger = _get_logger()
diff --git a/common/memory.py b/common/memory.py
new file mode 100644
index 0000000..026bed2
--- /dev/null
+++ b/common/memory.py
@@ -0,0 +1,3 @@
+from common.expired_dict import ExpiredDict
+
+USER_IMAGE_CACHE = ExpiredDict(60 * 3)
\ No newline at end of file
diff --git a/common/package_manager.py b/common/package_manager.py
new file mode 100644
index 0000000..8301360
--- /dev/null
+++ b/common/package_manager.py
@@ -0,0 +1,36 @@
+import time
+
+import pip
+from pip._internal import main as pipmain
+
+from common.log import _reset_logger, logger
+
+
+def install(package):
+    pipmain(["install", package])
+
+
+def install_requirements(file):
+    pipmain(["install", "-r", file, "--upgrade"])
+    _reset_logger(logger)
+
+
+def check_dulwich():
+    needwait = False
+    for i in range(2):
+        if needwait:
+            time.sleep(3)
+            needwait = False
+        try:
+            import dulwich
+
+            return
+        except ImportError:
+            try:
+                install("dulwich")
+            except Exception:
+                needwait = True
+    try:
+        import dulwich
+    except ImportError:
+        raise ImportError("Unable to import dulwich")
diff --git a/common/singleton.py b/common/singleton.py
new file mode 100644
index 0000000..b46095c
--- /dev/null
+++ b/common/singleton.py
@@ -0,0 +1,9 @@
+def singleton(cls):
+    instances = {}
+
+    def get_instance(*args, **kwargs):
+        if cls not in instances:
+            instances[cls] = cls(*args, **kwargs)
+        return instances[cls]
+
+    return get_instance
diff --git a/common/sorted_dict.py b/common/sorted_dict.py
new file mode 100644
index 0000000..7a1e85b
--- /dev/null
+++ b/common/sorted_dict.py
@@ -0,0 +1,65 @@
+import heapq
+
+
+class SortedDict(dict):
+    def __init__(self, sort_func=lambda k, v: k, init_dict=None, reverse=False):
+        if init_dict is None:
+            init_dict = []
+        if isinstance(init_dict, dict):
+            init_dict = init_dict.items()
+        self.sort_func = sort_func
+        self.sorted_keys = None
+        self.reverse = reverse
+        self.heap = []
+        for k, v in init_dict:
+            self[k] = v
+
+    def __setitem__(self, key, value):
+        if key in self:
+            super().__setitem__(key, value)
+            for i, (priority, k) in enumerate(self.heap):
+                if k == key:
+                    self.heap[i] = (self.sort_func(key, value), key)
+                    heapq.heapify(self.heap)
+                    break
+            self.sorted_keys = None
+        else:
+            super().__setitem__(key, value)
+            heapq.heappush(self.heap, (self.sort_func(key, value), key))
+            self.sorted_keys = None
+
+    def __delitem__(self, key):
+        super().__delitem__(key)
+        for i, (priority, k) in enumerate(self.heap):
+            if k == key:
+                del self.heap[i]
+                heapq.heapify(self.heap)
+                break
+        self.sorted_keys = None
+
+    def keys(self):
+        if self.sorted_keys is None:
+            self.sorted_keys = [k for _, k in sorted(self.heap, reverse=self.reverse)]
+        return self.sorted_keys
+
+    def items(self):
+        if self.sorted_keys is None:
+            self.sorted_keys = [k for _, k in sorted(self.heap, reverse=self.reverse)]
+        sorted_items = [(k, self[k]) for k in self.sorted_keys]
+        return sorted_items
+
+    def _update_heap(self, key):
+        for i, (priority, k) in enumerate(self.heap):
+            if k == key:
+                new_priority = self.sort_func(key, self[key])
+                if new_priority != priority:
+                    self.heap[i] = (new_priority, key)
+                    heapq.heapify(self.heap)
+                    self.sorted_keys = None
+                break
+
+    def __iter__(self):
+        return iter(self.keys())
+
+    def __repr__(self):
+        return f"{type(self).__name__}({dict(self)}, sort_func={self.sort_func.__name__}, reverse={self.reverse})"
diff --git a/common/time_check.py b/common/time_check.py
new file mode 100644
index 0000000..15be289
--- /dev/null
+++ b/common/time_check.py
@@ -0,0 +1,42 @@
+import re
+import time
+import config
+from common.log import logger
+
+
+def time_checker(f):
+    def _time_checker(self, *args, **kwargs):
+        _config = config.conf()
+        chat_time_module = _config.get("chat_time_module", False)
+
+        if chat_time_module:
+            chat_start_time = _config.get("chat_start_time", "00:00")
+            chat_stop_time = _config.get("chat_stop_time", "24:00")
+
+            time_regex = re.compile(r"^([01]?[0-9]|2[0-4])(:)([0-5][0-9])$")
+
+            if not (time_regex.match(chat_start_time) and time_regex.match(chat_stop_time)):
+                logger.warning("时间格式不正确，请在config.json中修改CHAT_START_TIME/CHAT_STOP_TIME。")
+                return None
+
+            now_time = time.strptime(time.strftime("%H:%M"), "%H:%M")
+            chat_start_time = time.strptime(chat_start_time, "%H:%M")
+            chat_stop_time = time.strptime(chat_stop_time, "%H:%M")
+            # 结束时间小于开始时间，跨天了
+            if chat_stop_time < chat_start_time and (chat_start_time <= now_time or now_time <= chat_stop_time):
+                f(self, *args, **kwargs)
+            # 结束大于开始时间代表，没有跨天
+            elif chat_start_time < chat_stop_time and chat_start_time <= now_time <= chat_stop_time:
+                f(self, *args, **kwargs)
+            else:
+                # 定义匹配规则，如果以 #reconf 或者  #更新配置  结尾, 非服务时间可以修改开始/结束时间并重载配置
+                pattern = re.compile(r"^.*#(?:reconf|更新配置)$")
+                if args and pattern.match(args[0].content):
+                    f(self, *args, **kwargs)
+                else:
+                    logger.info("非服务时间内，不接受访问")
+                    return None
+        else:
+            f(self, *args, **kwargs)  # 未开启时间模块则直接回答
+
+    return _time_checker
diff --git a/common/tmp_dir.py b/common/tmp_dir.py
new file mode 100644
index 0000000..b0d89bc
--- /dev/null
+++ b/common/tmp_dir.py
@@ -0,0 +1,21 @@
+import os
+
+from common.utils import expand_path
+from config import conf
+
+
+class TmpDir(object):
+    """Temporary directory for transient artifacts (e.g. synthesized voice).
+
+    Resolves to ``<agent_workspace>/tmp`` (default ``~/cow/tmp``) so temp files
+    land inside the agent workspace instead of a CWD-relative ``./tmp``, which
+    is unreliable for the packaged desktop app where CWD is undefined.
+    """
+
+    def __init__(self):
+        ws_root = expand_path(conf().get("agent_workspace", "~/cow"))
+        self.tmpFilePath = os.path.join(ws_root, "tmp")
+        os.makedirs(self.tmpFilePath, exist_ok=True)
+
+    def path(self):
+        return str(self.tmpFilePath) + "/"
diff --git a/common/token_bucket.py b/common/token_bucket.py
new file mode 100644
index 0000000..23901b6
--- /dev/null
+++ b/common/token_bucket.py
@@ -0,0 +1,45 @@
+import threading
+import time
+
+
+class TokenBucket:
+    def __init__(self, tpm, timeout=None):
+        self.capacity = int(tpm)  # 令牌桶容量
+        self.tokens = 0  # 初始令牌数为0
+        self.rate = int(tpm) / 60  # 令牌每秒生成速率
+        self.timeout = timeout  # 等待令牌超时时间
+        self.cond = threading.Condition()  # 条件变量
+        self.is_running = True
+        # 开启令牌生成线程
+        threading.Thread(target=self._generate_tokens).start()
+
+    def _generate_tokens(self):
+        """生成令牌"""
+        while self.is_running:
+            with self.cond:
+                if self.tokens < self.capacity:
+                    self.tokens += 1
+                self.cond.notify()  # 通知获取令牌的线程
+            time.sleep(1 / self.rate)
+
+    def get_token(self):
+        """获取令牌"""
+        with self.cond:
+            while self.tokens <= 0:
+                flag = self.cond.wait(self.timeout)
+                if not flag:  # 超时
+                    return False
+            self.tokens -= 1
+        return True
+
+    def close(self):
+        self.is_running = False
+
+
+if __name__ == "__main__":
+    token_bucket = TokenBucket(20, None)  # 创建一个每分钟生产20个tokens的令牌桶
+    # token_bucket = TokenBucket(20, 0.1)
+    for i in range(3):
+        if token_bucket.get_token():
+            print(f"第{i+1}次请求成功")
+    token_bucket.close()
diff --git a/common/utils.py b/common/utils.py
new file mode 100644
index 0000000..0597d97
--- /dev/null
+++ b/common/utils.py
@@ -0,0 +1,152 @@
+import io
+import os
+import re
+from urllib.parse import urlparse
+from common.log import logger
+
+def fsize(file):
+    if isinstance(file, io.BytesIO):
+        return file.getbuffer().nbytes
+    elif isinstance(file, str):
+        return os.path.getsize(file)
+    elif hasattr(file, "seek") and hasattr(file, "tell"):
+        pos = file.tell()
+        file.seek(0, os.SEEK_END)
+        size = file.tell()
+        file.seek(pos)
+        return size
+    else:
+        raise TypeError("Unsupported type")
+
+
+def compress_imgfile(file, max_size):
+    if fsize(file) <= max_size:
+        return file
+    from PIL import Image
+    file.seek(0)
+    img = Image.open(file)
+    rgb_image = img.convert("RGB")
+    quality = 95
+    min_quality = 10
+    while True:
+        out_buf = io.BytesIO()
+        rgb_image.save(out_buf, "JPEG", quality=quality)
+        if fsize(out_buf) <= max_size or quality <= min_quality:
+            # Stop at min_quality: further decrements would pass an invalid
+            # quality (<1) to PIL and the loop would otherwise never terminate
+            # for images that cannot be compressed below max_size.
+            return out_buf
+        quality -= 5
+
+
+def split_string_by_utf8_length(string, max_length, max_split=0):
+    encoded = string.encode("utf-8")
+    start, end = 0, 0
+    result = []
+    while end < len(encoded):
+        if max_split > 0 and len(result) >= max_split:
+            result.append(encoded[start:].decode("utf-8"))
+            break
+        end = min(start + max_length, len(encoded))
+        # 如果当前字节不是 UTF-8 编码的开始字节，则向前查找直到找到开始字节为止
+        while end < len(encoded) and (encoded[end] & 0b11000000) == 0b10000000:
+            end -= 1
+        result.append(encoded[start:end].decode("utf-8"))
+        start = end
+    return result
+
+
+def get_path_suffix(path):
+    path = urlparse(path).path
+    return os.path.splitext(path)[-1].lstrip('.')
+
+
+def convert_webp_to_png(webp_image):
+    from PIL import Image
+    try:
+        webp_image.seek(0)
+        img = Image.open(webp_image).convert("RGBA")
+        png_image = io.BytesIO()
+        img.save(png_image, format="PNG")
+        png_image.seek(0)
+        return png_image
+    except Exception as e:
+        logger.error(f"Failed to convert WEBP to PNG: {e}")
+        raise
+
+
+def remove_markdown_symbol(text: str):
+    # 移除markdown格式，目前先移除**
+    if not text:
+        return text
+    return re.sub(r'\*\*(.*?)\*\*', r'\1', text)
+
+
+def expand_path(path: str) -> str:
+    """
+    Expand user path with proper Windows support.
+    
+    On Windows, os.path.expanduser('~') may not work properly in some shells (like PowerShell).
+    This function provides a more robust path expansion.
+    
+    Args:
+        path: Path string that may contain ~
+        
+    Returns:
+        Expanded absolute path
+    """
+    if not path:
+        return path
+    
+    # Try standard expansion first
+    expanded = os.path.expanduser(path)
+    
+    # If expansion didn't work (path still starts with ~), use HOME or USERPROFILE
+    if expanded.startswith('~'):
+        import platform
+        if platform.system() == 'Windows':
+            # On Windows, try USERPROFILE first, then HOME
+            home = os.environ.get('USERPROFILE') or os.environ.get('HOME')
+        else:
+            # On Unix-like systems, use HOME
+            home = os.environ.get('HOME')
+        
+        if home:
+            # Replace ~ with home directory
+            if path == '~':
+                expanded = home
+            elif path.startswith('~/') or path.startswith('~\\'):
+                expanded = os.path.join(home, path[2:])
+    
+    return expanded
+
+
+def is_cloud_deployment() -> bool:
+    if os.environ.get("CLOUD_DEPLOYMENT_ID"):
+        return True
+    try:
+        from config import conf
+        if conf().get("cloud_deployment_id"):
+            return True
+    except Exception:
+        pass
+    return False
+
+
+def get_cloud_headers(api_key: str) -> dict:
+    """
+    Build standard headers for LinkAI API requests,
+    including client_id when available.
+    """
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}",
+    }
+    try:
+        from linkai import LinkAIClient
+        client_id = LinkAIClient.fetch_client_id()
+        if client_id:
+            headers["X-Client-Id"] = client_id
+    except Exception:
+        pass
+    return headers
diff --git a/common/ws_client_compat.py b/common/ws_client_compat.py
new file mode 100644
index 0000000..e578316
--- /dev/null
+++ b/common/ws_client_compat.py
@@ -0,0 +1,17 @@
+import inspect
+from typing import Any
+
+
+def websocket_app_run_forever(ws: Any, **kwargs: Any) -> None:
+    """
+    Call WebSocketApp.run_forever; strip reconnect= if the installed
+    websocket-client is too old (reconnect was added in a later 1.x release).
+    """
+    if "reconnect" in kwargs:
+        try:
+            params = inspect.signature(ws.run_forever).parameters
+        except (TypeError, ValueError):
+            params = {}
+        if "reconnect" not in params:
+            kwargs = {k: v for k, v in kwargs.items() if k != "reconnect"}
+    ws.run_forever(**kwargs)
diff --git a/config-template.json b/config-template.json
new file mode 100644
index 0000000..ad3583b
--- /dev/null
+++ b/config-template.json
@@ -0,0 +1,48 @@
+{
+  "cow_lang": "auto",
+  "channel_type": "web",
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "",
+  "deepseek_api_base": "https://api.deepseek.com/v1",
+  "qianfan_api_key": "",
+  "qianfan_api_base": "https://qianfan.baidubce.com/v2",
+  "minimax_api_key": "",
+  "zhipu_ai_api_key": "",
+  "ark_api_key": "",
+  "moonshot_api_key": "",
+  "dashscope_api_key": "",
+  "claude_api_key": "",
+  "claude_api_base": "https://api.anthropic.com/v1",
+  "open_ai_api_key": "",
+  "open_ai_api_base": "https://api.openai.com/v1",
+  "gemini_api_key": "",
+  "gemini_api_base": "https://generativelanguage.googleapis.com",
+  "voice_to_text": "",
+  "text_to_voice": "",
+  "voice_reply_voice": false,
+  "speech_recognition": true,
+  "group_speech_recognition": false,
+  "use_linkai": false,
+  "linkai_api_key": "",
+  "linkai_app_code": "",
+  "feishu_app_id": "",
+  "feishu_app_secret": "",
+  "feishu_stream_reply": true,
+  "dingtalk_client_id": "",
+  "dingtalk_client_secret": "",
+  "wecom_bot_id": "",
+  "wecom_bot_secret": "",
+  "web_host": "",
+  "web_password": "",
+  "agent": true,
+  "agent_max_context_tokens": 50000,
+  "agent_max_context_turns": 20,
+  "agent_max_steps": 20,
+  "enable_thinking": false,
+  "reasoning_effort": "high",
+  "knowledge": true,
+  "self_evolution_enabled": true,
+  "mcp_tool_retrieval_enabled": false,
+  "mcp_tool_retrieval_threshold": 20,
+  "mcp_tool_retrieval_top_k": 10
+}
diff --git a/config.py b/config.py
new file mode 100644
index 0000000..6d02e86
--- /dev/null
+++ b/config.py
@@ -0,0 +1,756 @@
+# encoding:utf-8
+
+import ast
+import copy
+import json
+import logging
+import os
+import pickle
+import sys
+
+from common.log import logger
+from common import i18n
+
+# All available config keys are listed in this dict (use lowercase keys).
+# The values here are placeholders only; the program does NOT read them.
+# They merely document the expected format — put real values in config.json.
+available_setting = {
+    # global UI language for CLI, startup logs, error messages, agent prompts
+    # and channel replies. Options: "auto" (detect from system locale, default),
+    # "zh" (Chinese) or "en" (English). An explicit value locks the language.
+    # value: auto/en/zh
+    "cow_lang": "auto",
+    # openai api config
+    "open_ai_api_key": "",  # openai api key
+    # openai api base; when use_azure_chatgpt is true, set the matching api base
+    "open_ai_api_base": "https://api.openai.com/v1",
+    "claude_api_base": "https://api.anthropic.com/v1",  # claude api base
+    "gemini_api_base": "https://generativelanguage.googleapis.com",  # gemini api base
+    "custom_api_key": "",  # custom OpenAI-compatible provider api key (used when bot_type is "custom"); legacy single-provider field
+    "custom_api_base": "",  # custom OpenAI-compatible provider api base (used when bot_type is "custom"); legacy single-provider field
+    # Multiple custom (OpenAI-compatible) providers. Activated via bot_type: "custom:<id>".
+    # Each item: {"id": "3f2a9c1b", "name": "my-provider", "api_key": "sk-...", "api_base": "https://api.example.com/v1", "model": "model-name"}
+    "custom_providers": [],
+    "proxy": "",  # proxy used by openai
+    # chatgpt model; when use_azure_chatgpt is true, this is the Azure model deployment name
+    "model": "gpt-3.5-turbo",  # options: gpt-4o, gpt-4o-mini, gpt-4-turbo, claude-3-sonnet, wenxin, moonshot, qwen-turbo, xunfei, glm-4, minimax, gemini, etc. See common/const.py for the full list
+    "bot_type": "",  # optional; for OpenAI-compatible third-party services set "openai" or "custom" (in custom mode switching model won't auto-switch bot_type). See common/const.py for bot names; inferred from model name if left empty
+    "use_azure_chatgpt": False,  # whether to use Azure chatgpt
+    "azure_deployment_id": "",  # azure model deployment name
+    "azure_api_version": "",  # azure api version
+    # Bot trigger config
+    "single_chat_prefix": ["bot", "@bot"],  # text must contain this prefix to trigger a reply in single chat
+    "single_chat_reply_prefix": "[bot] ",  # auto-reply prefix in single chat, used to distinguish from a real person
+    "single_chat_reply_suffix": "",  # auto-reply suffix in single chat; \n inserts a line break
+    "group_chat_prefix": ["@bot"],  # messages containing this prefix trigger a reply in group chat
+    "no_need_at": False,  # whether replying in group chat does not require an @mention
+    "group_chat_reply_prefix": "",  # auto-reply prefix in group chat
+    "group_chat_reply_suffix": "",  # auto-reply suffix in group chat; \n inserts a line break
+    "group_chat_keyword": [],  # messages containing this keyword trigger a reply in group chat
+    "group_at_off": False,  # whether to disable @bot triggering in group chat
+    "group_name_white_list": ["group1", "group2"],  # group names where auto-reply is enabled
+    "group_name_keyword_white_list": [],  # group-name keywords where auto-reply is enabled
+    "group_chat_in_one_session": ["group1"],  # group names that share conversation context
+    "group_shared_session": False,  # whether group chat shares conversation context (all members share). When False each user has an independent session in the group
+    "nick_name_black_list": [],  # user nickname blacklist
+    "group_welcome_msg": "",  # fixed welcome message for new group members; uses a random style when empty
+    "trigger_by_self": False,  # whether the bot can be triggered by itself
+    "text_to_image": "dall-e-2",  # image generation model, options: dall-e-2, dall-e-3
+    # Azure OpenAI dall-e-3 config
+    "dalle3_image_style": "vivid", # dalle3 image style, options: vivid, natural
+    "dalle3_image_quality": "hd", # dalle3 image quality, options: standard, hd
+    # Azure OpenAI DALL-E API config; when use_azure_chatgpt is true, separates the text-reply resource from the DALL-E resource
+    "azure_openai_dalle_api_base": "", # [optional] azure openai endpoint for image replies; defaults to open_ai_api_base
+    "azure_openai_dalle_api_key": "", # [optional] azure openai key for image replies; defaults to open_ai_api_key
+    "azure_openai_dalle_deployment_id":"", # [optional] azure openai deployment id for image replies; defaults to text_to_image
+    "image_proxy": True,  # whether an image proxy is needed; required when accessing LinkAI from mainland China
+    "image_create_prefix": ["画", "看", "找"],  # prefixes that enable image replies
+    "concurrency_in_session": 1,  # max number of in-flight messages per session; values >1 may cause out-of-order replies
+    "image_create_size": "256x256",  # image size, options: 256x256, 512x512, 1024x1024 (dall-e-3 defaults to 1024x1024)
+    "group_chat_exit_group": False,
+    # chatgpt session params
+    "expires_in_seconds": 3600,  # idle session expiry time
+    # persona description (only used in chat mode)
+    "character_desc": "You are a helpful AI assistant. You aim to answer and solve any questions people have, and can communicate in multiple languages.",
+    "conversation_max_tokens": 1000,  # max characters of context memory
+    # chatgpt rate limit config
+    "rate_limit_chatgpt": 20,  # chatgpt call rate limit
+    "rate_limit_dalle": 50,  # openai dalle call rate limit
+    # chatgpt api params, see https://platform.openai.com/docs/api-reference/chat/create
+    "temperature": 0.9,
+    "top_p": 1,
+    "frequency_penalty": 0,
+    "presence_penalty": 0,
+    "request_timeout": 180,  # chatgpt request timeout; the openai api defaults to 600, hard questions usually need longer
+    "timeout": 120,  # chatgpt retry timeout; will auto-retry within this window
+    # Baidu Wenxin (ERNIE) params
+    "baidu_wenxin_model": "eb-instant",  # defaults to the ERNIE-Bot-turbo model
+    "baidu_wenxin_api_key": "",  # Baidu api key
+    "baidu_wenxin_secret_key": "",  # Baidu secret key
+    "baidu_wenxin_prompt_enabled": False,  # Enable prompt if you are using ernie character model
+    # Baidu Qianfan / ERNIE OpenAI-compatible API
+    "qianfan_api_key": "",  # Baidu Qianfan API key in bce-v3 format
+    "qianfan_api_base": "https://qianfan.baidubce.com/v2",  # Qianfan OpenAI-compatible API base
+    # Xunfei Spark API
+    "xunfei_app_id": "",  # Xunfei app id
+    "xunfei_api_key": "",  # Xunfei API key
+    "xunfei_api_secret": "",  # Xunfei API secret
+    "xunfei_domain": "",  # Xunfei model domain param; for Spark4.0 Ultra it is 4.0Ultra, see https://www.xfyun.cn/doc/spark/Web.html for others
+    "xunfei_spark_url": "",  # Xunfei model request url; for Spark4.0 Ultra it is wss://spark-api.xf-yun.com/v4.0/chat, see https://www.xfyun.cn/doc/spark/Web.html for others
+    # claude config
+    "claude_api_cookie": "",
+    "claude_uuid": "",
+    # claude api key
+    "claude_api_key": "",
+    # Tongyi Qianwen API, see https://help.aliyun.com/document_detail/2587494.html for how to obtain
+    "qwen_access_key_id": "",
+    "qwen_access_key_secret": "",
+    "qwen_agent_key": "",
+    "qwen_app_id": "",
+    "qwen_node_id": "",  # id used by workflow-orchestration models; keep it an empty string if qwen_node_id is unused
+    # Alibaba Lingji (Tongyi new sdk) model api key
+    "dashscope_api_key": "",
+    # Google Gemini Api Key
+    "gemini_api_key": "",
+    # Embedding model config
+    "embedding_provider": "",  # explicitly set the provider: openai / linkai / dashscope / doubao / zhipu (aligned with bot_type naming)
+    "embedding_model": "",     # leave empty to use the provider's default model
+    "embedding_dimensions": 0, # leave empty/0 to use the provider's default dimension (1024 recommended for consistency)
+    # voice config
+    "speech_recognition": True,  # whether to enable speech recognition
+    "group_speech_recognition": False,  # whether to enable group speech recognition
+    "voice_reply_voice": False,  # whether to reply to voice with voice; requires the matching TTS engine api key
+    "always_reply_voice": False,  # whether to always reply with voice
+    "voice_to_text": "openai",  # speech recognition engine: openai,baidu,google,azure,xunfei,ali
+    "text_to_voice": "openai",  # TTS engine: openai,baidu,google,azure,xunfei,ali,pytts(offline),elevenlabs,edge(online)
+    "text_to_voice_model": "tts-1",
+    "tts_voice_id": "alloy",
+    # baidu voice api config; required when using Baidu speech recognition and TTS
+    "baidu_app_id": "",
+    "baidu_api_key": "",
+    "baidu_secret_key": "",
+    # 1536 Mandarin (with basic English) 1737 English 1637 Cantonese 1837 Sichuanese 1936 Mandarin far-field
+    "baidu_dev_pid": 1536,
+    # azure voice api config; required when using Azure speech recognition and TTS
+    "azure_voice_api_key": "",
+    "azure_voice_region": "japaneast",
+    # elevenlabs voice api config
+    "xi_api_key": "",  # see https://docs.elevenlabs.io/api-reference/quick-start/authentication for how to obtain the api key
+    "xi_voice_id": "",  # ElevenLabs offers 9 English voice ids: Adam/Antoni/Arnold/Bella/Domi/Elli/Josh/Rachel/Sam
+    # service time limit
+    "chat_time_module": False,  # whether to enable service-time limiting
+    "chat_start_time": "00:00",  # service start time
+    "chat_stop_time": "24:00",  # service stop time
+    # translation api
+    "translate": "baidu",  # translation api: baidu, youdao
+    # baidu translation api config
+    "baidu_translate_app_id": "",  # baidu translation api appid
+    "baidu_translate_app_key": "",  # baidu translation api secret key
+    # youdao translation api config
+    "youdao_translate_app_key": "",  # youdao translation api app id
+    "youdao_translate_app_secret": "",  # youdao translation api app secret
+    # wechatmp config
+    "wechatmp_token": "",  # WeChat Official Account token
+    "wechatmp_port": 8080,  # WeChat Official Account port; needs port forwarding to 80 or 443
+    "wechatmp_app_id": "",  # WeChat Official Account appID
+    "wechatmp_app_secret": "",  # WeChat Official Account appsecret
+    "wechatmp_aes_key": "",  # WeChat Official Account EncodingAESKey; required in encrypted mode
+    # wechatcom shared config
+    "wechatcom_corp_id": "",  # WeCom corp id
+    # wechatcomapp config
+    "wechatcomapp_token": "",  # WeCom app token
+    "wechatcomapp_port": 9898,  # WeCom app service port; no port forwarding needed
+    "wechatcomapp_secret": "",  # WeCom app secret
+    "wechatcomapp_agent_id": "",  # WeCom app agent_id
+    "wechatcomapp_aes_key": "",  # WeCom app aes_key
+    # WeChat Customer Service (wechat_kf) config
+    "wechat_kf_corp_id": "",  # corp_id of the company the WeChat Customer Service belongs to
+    "wechat_kf_token": "",  # WeChat Customer Service callback token
+    "wechat_kf_port": 9888,  # WeChat Customer Service callback service port
+    "wechat_kf_secret": "",  # WeChat Customer Service app secret
+    "wechat_kf_aes_key": "",  # WeChat Customer Service callback aes_key
+    "wechat_kf_cursor_path": "~/.wechat_kf_cursors.json",  # path for persisting the WeChat Customer Service sync_msg cursor
+    # Feishu config
+    "feishu_port": 80,  # Feishu bot listening port; only needed in webhook mode
+    "feishu_app_id": "",  # Feishu bot app id
+    "feishu_app_secret": "",  # Feishu bot app secret
+    "feishu_token": "",  # Feishu verification token; only needed in webhook mode
+    "feishu_event_mode": "websocket",  # Feishu event mode: webhook(HTTP server) or websocket(long connection)
+    # Feishu streaming reply (based on the official cardkit streaming-card API; requires the cardkit:card:write permission and Feishu client 7.20+)
+    "feishu_stream_reply": True,  # whether to enable streaming reply (typewriter effect); auto-downgrades to non-streaming or shows an upgrade prompt on failure/old clients
+    # DingTalk config
+    "dingtalk_client_id": "",  # DingTalk bot Client ID
+    "dingtalk_client_secret": "",  # DingTalk bot Client Secret
+    "dingtalk_card_enabled": False,
+    # WeCom smart bot config (long connection mode)
+    "wecom_bot_id": "",  # WeCom smart bot BotID
+    "wecom_bot_secret": "",  # WeCom smart bot long-connection secret
+    # WeCom smart bot transport mode: "websocket" (long connection) or "webhook" (HTTP callback)
+    "wecom_bot_mode": "websocket",
+    "wecom_bot_token": "",  # webhook mode: Token configured on the bot's receive-message URL
+    "wecom_bot_encoding_aes_key": "",  # webhook mode: EncodingAESKey configured on the bot's receive-message URL
+    "wecom_bot_port": 9892,  # webhook mode: local HTTP server port for the receive-message URL
+    # Telegram config
+    "telegram_token": "",  # Bot token from @BotFather
+    "telegram_proxy": "",  # Optional HTTP/SOCKS5 proxy, e.g. http://127.0.0.1:7890 or socks5://127.0.0.1:1080 (empty falls back to env vars)
+    "telegram_group_trigger": "mention_or_reply",  # Group trigger: mention_or_reply(@ or reply, recommended) | mention_only(@ only) | all(every message)
+    "telegram_register_commands": True,  # Auto-register the BotFather command menu on startup (aligned with web slash commands)
+    # Slack config (Socket Mode, no public IP required)
+    "slack_bot_token": "",  # Bot User OAuth Token, like xoxb-...
+    "slack_app_token": "",  # App-Level Token (generated after enabling Socket Mode), like xapp-...
+    "slack_group_trigger": "mention_or_reply",  # Channel trigger: mention_or_reply(@ or reply in thread, recommended) | mention_only(@ only) | all(every message)
+    # Discord config (Gateway connection, no public IP required)
+    "discord_token": "",  # Discord Bot Token (generated on the Bot page of the Developer Portal)
+    "discord_group_trigger": "mention_or_reply",  # Channel trigger: mention_or_reply(@ or reply to bot, recommended) | mention_only(@ only) | all(every message)
+    # WeChat config
+    "weixin_token": "",  # bot_token obtained after WeChat login; leave empty to auto scan-login on startup
+    "weixin_base_url": "https://ilinkai.weixin.qq.com",  # Weixin ilink API base URL
+    "weixin_cdn_base_url": "https://novac2c.cdn.weixin.qq.com/c2c",  # CDN base URL
+    "weixin_credentials_path": "~/.weixin_cow_credentials.json",  # credentials file path
+    # custom trigger words for chatgpt commands
+    "clear_memory_commands": ["#清除记忆"],  # session-reset command; must start with #
+    # channel config
+    "channel_type": "",  # channel type; supports running multiple channels at once. Single: "feishu", multiple: "feishu, dingtalk" or ["feishu", "dingtalk"]. Options: web,feishu,dingtalk,wecom_bot,weixin,wechatmp,wechatmp_service,wechatcom_app,wechat_kf,telegram,slack,discord
+    "web_console": True,  # whether to auto-start the Web console (on by default). Set False to disable
+    "subscribe_msg": "",  # subscribe message; supported by: wechatmp, wechatmp_service, wechatcom_app
+    "debug": False,  # whether to enable debug mode; prints more logs when on
+    "appdata_dir": "",  # data directory
+    # plugin config
+    "plugin_trigger_prefix": "$",  # prefix for plugin chat commands; avoid clashing with the admin command prefix "#"
+    # whether to use the global plugin config
+    "use_global_plugin_config": False,
+    "max_media_send_count": 3,  # max number of media resources sent at once
+    "media_send_interval": 1,  # interval between sending images, in seconds
+    # Zhipu AI platform config
+    "zhipu_ai_api_key": "",
+    "zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4",
+    "moonshot_api_key": "",
+    "moonshot_base_url": "https://api.moonshot.cn/v1",
+    # Doubao (Volcano Ark) platform config
+    "ark_api_key": "",
+    "ark_base_url": "https://ark.cn-beijing.volces.com/api/v3",
+    # ModelScope community platform config
+    "modelscope_api_key": "",
+    "modelscope_base_url": "https://api-inference.modelscope.cn/v1/chat/completions",
+    # LinkAI platform config
+    "use_linkai": False,
+    "linkai_api_key": "",
+    "linkai_app_code": "",
+    "linkai_api_base": "https://api.link-ai.tech",
+    "cloud_host": "client.link-ai.tech",
+    "cloud_port": None,
+    "cloud_deployment_id": "",
+    "minimax_api_key": "",
+    "Minimax_group_id": "",
+    "Minimax_base_url": "",
+    "deepseek_api_key": "",
+    "deepseek_api_base": "https://api.deepseek.com/v1",
+    # Xiaomi MiMo LLM
+    "mimo_api_key": "",
+    "mimo_api_base": "https://api.xiaomimimo.com/v1",
+    "web_host": "",  # Web console bind address; empty means auto
+    "web_port": 9899,
+    "web_password": "",  # Web console password; empty means no authentication required
+    "web_session_expire_days": 30,  # Auth session expiry in days
+    "web_file_serve_root": "~",  # Root dir the /api/file endpoint may serve; "/" allows the whole filesystem
+    "mcp_oauth_redirect_base": "",  # Base URL for MCP OAuth callback (e.g. http://your-ip:9899); empty uses local web console
+    "agent": True,  # whether to enable Agent mode
+    "agent_workspace": "~/cow",  # agent workspace path, used to store skills, memory, etc.
+    "agent_max_context_tokens": 50000,  # max context tokens in Agent mode
+    "agent_max_context_turns": 20,  # max context memory turns in Agent mode
+    "agent_max_steps": 20,  # max decision steps per run in Agent mode
+    "enable_thinking": False,  # Enable deep-thinking mode for thinking-capable models
+    "reasoning_effort": "high",  # Reasoning depth under thinking mode: "high" or "max"
+    "knowledge": True,  # whether to enable the knowledge base feature
+    # Self-evolution: review idle conversations to learn memory/skills. Flat keys.
+    "self_evolution_enabled": False,        # switch to enable/disable self-evolution
+    "self_evolution_idle_minutes": 10,      # idle time before a session is reviewed
+    "self_evolution_min_turns": 6,          # min user turns (or context pressure) to trigger
+    # Deep Dream: nightly memory distillation into MEMORY.md + dream diary.
+    "deep_dream_enabled": True,             # scheduled deep dream switch; manual /memory dream is unaffected
+    "skill": {},  # Per-skill runtime config; nested keys flatten to SKILL_<NAME>_<KEY> env vars at startup
+    "mcp_servers": [],  # MCP server list; each entry supports type "stdio" (local process) or "sse" (remote URL)
+    # On-demand MCP tool retrieval: when many MCP tools are connected, inject
+    # only the most query-relevant ones instead of all of them. Built-in tools
+    # are always injected in full; degrades to full injection when disabled,
+    # below threshold, or when no embedding provider is available.
+    "mcp_tool_retrieval_enabled": False,    # switch for on-demand MCP tool retrieval
+    "mcp_tool_retrieval_threshold": 20,     # only retrieve when MCP tool count exceeds this
+    "mcp_tool_retrieval_top_k": 10,         # max relevant MCP tools injected per turn
+}
+
+
+class Config(dict):
+    def __init__(self, d=None):
+        super().__init__()
+        if d is None:
+            d = {}
+        for k, v in d.items():
+            self[k] = v
+        # user_datas: per-user data; key is the username, value is the user's data (also a dict)
+        self.user_datas = {}
+
+    def __getitem__(self, key):
+        return super().__getitem__(key)
+
+    def __setitem__(self, key, value):
+        return super().__setitem__(key, value)
+
+    def get(self, key, default=None):
+        # skip comment fields starting with an underscore
+        if key.startswith("_"):
+            return super().get(key, default)
+        
+        # if the key is not in available_setting, fall back to dict.get and return the value actually loaded from config.json (or default if absent)
+        if key not in available_setting:
+            return super().get(key, default)
+        
+        try:
+            return self[key]
+        except KeyError as e:
+            return default
+        except Exception as e:
+            raise e
+
+    # Make sure to return a dictionary to ensure atomic
+    def get_user_data(self, user) -> dict:
+        if self.user_datas.get(user) is None:
+            self.user_datas[user] = {}
+        return self.user_datas[user]
+
+    # SECURITY NOTE: pickle.load() can execute arbitrary code during
+    # deserialization. This is safe as long as user_datas.pkl is trusted
+    # (local app data directory, written only by this process). For a future
+    # hardening pass, consider migrating to JSON (json.load/json.dump) if the
+    # data structures are JSON-serializable, or adding an HMAC signature to
+    # detect tampering of the pickle file.
+    def load_user_datas(self):
+        try:
+            with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "rb") as f:
+                self.user_datas = pickle.load(f)
+                logger.debug("[Config] User datas loaded.")
+        except FileNotFoundError as e:
+            logger.debug("[Config] User datas file not found, ignore.")
+        except Exception as e:
+            logger.warning("[Config] User datas error: {}".format(e))
+            self.user_datas = {}
+
+    def save_user_datas(self):
+        try:
+            # SECURITY: pickle.dump output should only be loaded by this same
+            # process. See note on load_user_datas() above.
+            with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "wb") as f:
+                pickle.dump(self.user_datas, f)
+                logger.info("[Config] User datas saved.")
+        except Exception as e:
+            logger.info("[Config] User datas error: {}".format(e))
+
+
+config = Config()
+
+
+def _mask_value(val):
+    """Mask a sensitive string value, keeping first 3 and last 3 chars."""
+    if not isinstance(val, str) or len(val) <= 8:
+        return val
+    return val[0:3] + "*" * 5 + val[-3:]
+
+
+def _mask_sensitive_recursive(obj):
+    """Recursively mask values whose keys contain 'key' or 'secret'."""
+    if isinstance(obj, dict):
+        masked = {}
+        for k, v in obj.items():
+            if ("key" in k or "secret" in k) and isinstance(v, str):
+                masked[k] = _mask_value(v)
+            else:
+                masked[k] = _mask_sensitive_recursive(v)
+        return masked
+    elif isinstance(obj, list):
+        return [_mask_sensitive_recursive(item) for item in obj]
+    return obj
+
+
+def drag_sensitive(config):
+    try:
+        if isinstance(config, str):
+            conf_dict: dict = json.loads(config)
+            conf_dict_copy = _mask_sensitive_recursive(conf_dict)
+            return json.dumps(conf_dict_copy, indent=4)
+
+        elif isinstance(config, dict):
+            return _mask_sensitive_recursive(config)
+    except Exception as e:
+        logger.exception(e)
+        return config
+    return config
+
+
+def load_config():
+    global config
+
+    # print ASCII logo
+    logger.info("  ____                _                    _   ")
+    logger.info(" / ___|_____      __ / \\   __ _  ___ _ __ | |_ ")
+    logger.info("| |   / _ \\ \\ /\\ / // _ \\ / _` |/ _ \\ '_ \\| __|")
+    logger.info("| |__| (_) \\ V  V // ___ \\ (_| |  __/ | | | |_ ")
+    logger.info(" \\____\\___/ \\_/\\_//_/   \\_\\__, |\\___|_| |_|\\__|")
+    logger.info("                          |___/                 ")
+    logger.info("")
+    # User config lives in the data root: source deployments use CWD (./), while
+    # the desktop build points COW_DATA_DIR at ~/.cow so config survives updates.
+    config_path = os.path.join(get_data_root(), "config.json")
+    if not os.path.exists(config_path):
+        logger.info("config file not found, falling back to config-template.json")
+        # Resolve the template via get_resource_root() so it works both from
+        # source and from a frozen (PyInstaller) bundle, where the template
+        # ships inside the bundle (sys._MEIPASS) and CWD may differ.
+        template_path = os.path.join(get_resource_root(), "config-template.json")
+        config_path = template_path if os.path.exists(template_path) else "./config-template.json"
+
+    config_str = read_file(config_path)
+    logger.debug("[INIT] config str: {}".format(drag_sensitive(config_str)))
+
+    # Deserialize the json string into a dict.
+    # `object_pairs_hook` lets us catch users who accidentally typed the
+    # same key twice (e.g. two `"tools"` blocks) — json.loads would
+    # otherwise silently drop all but the last occurrence.
+    config = Config(json.loads(config_str, object_pairs_hook=_merge_duplicate_keys))
+
+    # Migrate legacy singular keys (`tool`, `skill`) into the canonical
+    # plural buckets so the rest of the codebase only reads one schema.
+    # Deep-merge so existing `tools`/`skills` entries are preserved and
+    # only missing namespaces are filled in from the legacy section.
+    _merge_legacy_namespace(config, legacy="tool",  canonical="tools")
+    _merge_legacy_namespace(config, legacy="skill", canonical="skills")
+
+    # override config with environment variables.
+    # Some online deployment platforms (e.g. Railway) deploy project from github directly. So you shouldn't put your secrets like api key in a config file, instead use environment variables to override the default config.
+    for name, value in os.environ.items():
+        name = name.lower()
+        # skip comment fields starting with an underscore
+        if name.startswith("_"):
+            continue
+        if name in available_setting:
+            logger.info("[INIT] override config by environ args: {}={}".format(name, value))
+            try:
+                # SECURITY: Use ast.literal_eval instead of eval().
+                # ast.literal_eval only parses Python literals (strings, numbers,
+                # tuples, lists, dicts, booleans, None) and CANNOT execute
+                # arbitrary code, preventing environment-variable injection.
+                config[name] = ast.literal_eval(value)
+            except Exception:
+                # literal_eval can raise ValueError/SyntaxError for non-literal
+                # strings, but also TypeError/RecursionError on malformed input
+                # (e.g. unhashable dict keys); catch broadly to avoid crashing
+                # startup, and fall back to treating the value as a plain string.
+                if value.lower() == "false":
+                    config[name] = False
+                elif value.lower() == "true":
+                    config[name] = True
+                else:
+                    config[name] = value
+
+    if config.get("debug", False):
+        logger.setLevel(logging.DEBUG)
+        logger.debug("[INIT] set log level to DEBUG")
+
+    # Resolve the global UI language as early as possible so that every
+    # downstream layer (logs, CLI, agent prompts, channel replies) shares it.
+    resolved_lang = i18n.resolve_language(config.get("cow_lang", "auto"))
+
+    logger.info("[INIT] load config: {}".format(drag_sensitive(config)))
+
+    # print system initialization info
+    logger.info("[INIT] ========================================")
+    logger.info("[INIT] System Initialization")
+    logger.info("[INIT] ========================================")
+    logger.info("[INIT] Language: {}".format(resolved_lang))
+    logger.info("[INIT] Channel: {}".format(config.get("channel_type", "unknown")))
+    logger.info("[INIT] Model: {}".format(config.get("model", "unknown")))
+
+    # Agent mode info
+    if config.get("agent", True):
+        workspace = config.get("agent_workspace", "~/cow")
+        logger.info("[INIT] Mode: Agent (workspace: {})".format(workspace))
+    else:
+        logger.info("[INIT] Mode: Chat (set \"agent\":true in config.json to enable Agent mode)")
+
+    logger.info("[INIT] Debug: {}".format(config.get("debug", False)))
+    logger.info("[INIT] ========================================")
+
+    # Sync selected config values to environment variables so that
+    # subprocesses (e.g. shell skill scripts) can access them directly.
+    # Existing env vars are NOT overwritten (env takes precedence).
+    _CONFIG_TO_ENV = {
+        "open_ai_api_key": "OPENAI_API_KEY",
+        "open_ai_api_base": "OPENAI_API_BASE",
+        "linkai_api_key": "LINKAI_API_KEY",
+        "linkai_api_base": "LINKAI_API_BASE",
+        "claude_api_key": "CLAUDE_API_KEY",
+        "claude_api_base": "CLAUDE_API_BASE",
+        "gemini_api_key": "GEMINI_API_KEY",
+        "gemini_api_base": "GEMINI_API_BASE",
+        "minimax_api_key": "MINIMAX_API_KEY",
+        "minimax_api_base": "MINIMAX_API_BASE",
+        "deepseek_api_key": "DEEPSEEK_API_KEY",
+        "deepseek_api_base": "DEEPSEEK_API_BASE",
+        "mimo_api_key": "MIMO_API_KEY",
+        "mimo_api_base": "MIMO_API_BASE",
+        "qianfan_api_key": "QIANFAN_API_KEY",
+        "qianfan_api_base": "QIANFAN_API_BASE",
+        "zhipu_ai_api_key": "ZHIPU_AI_API_KEY",
+        "zhipu_ai_api_base": "ZHIPU_AI_API_BASE",
+        "moonshot_api_key": "MOONSHOT_API_KEY",
+        "moonshot_api_base": "MOONSHOT_API_BASE",
+        "ark_api_key": "ARK_API_KEY",
+        "ark_api_base": "ARK_API_BASE",
+        "dashscope_api_key": "DASHSCOPE_API_KEY",
+        "dashscope_api_base": "DASHSCOPE_API_BASE",
+        # Channel credentials (used by skills that check env vars)
+        "feishu_app_id": "FEISHU_APP_ID",
+        "feishu_app_secret": "FEISHU_APP_SECRET",
+        "dingtalk_client_id": "DINGTALK_CLIENT_ID",
+        "dingtalk_client_secret": "DINGTALK_CLIENT_SECRET",
+        "wechatmp_app_id": "WECHATMP_APP_ID",
+        "wechatmp_app_secret": "WECHATMP_APP_SECRET",
+        "wechatcomapp_agent_id": "WECHATCOMAPP_AGENT_ID",
+        "wechatcomapp_secret": "WECHATCOMAPP_SECRET",
+        "wechatcom_corp_id": "WECHATCOM_CORP_ID",
+        "wechat_kf_corp_id": "WECHAT_KF_CORP_ID",
+        "wechat_kf_secret": "WECHAT_KF_SECRET",
+        "wechat_kf_token": "WECHAT_KF_TOKEN",
+        "wechat_kf_aes_key": "WECHAT_KF_AES_KEY",
+        "qq_app_id": "QQ_APP_ID",
+        "qq_app_secret": "QQ_APP_SECRET",
+        "weixin_token": "WEIXIN_TOKEN",
+    }
+    injected = 0
+    for conf_key, env_key in _CONFIG_TO_ENV.items():
+        if env_key not in os.environ:
+            val = config.get(conf_key, "")
+            if val:
+                os.environ[env_key] = str(val)
+                injected += 1
+
+    injected += _sync_skill_config_to_env(config.get("skills", {}))
+
+    if injected:
+        logger.info("[INIT] Synced {} config values to environment variables".format(injected))
+
+    config.load_user_datas()
+
+
+def _deep_merge_dicts(base: dict, incoming: dict) -> dict:
+    """Recursively merge ``incoming`` into ``base`` (incoming wins on leaves)."""
+    for key, val in incoming.items():
+        if (
+            key in base
+            and isinstance(base[key], dict)
+            and isinstance(val, dict)
+        ):
+            _deep_merge_dicts(base[key], val)
+        else:
+            base[key] = val
+    return base
+
+
+def _merge_duplicate_keys(pairs):
+    """object_pairs_hook for json.loads: deep-merge duplicate top-level keys
+    (lists concat, dicts merge, scalars take the latter) instead of dropping."""
+    out = {}
+    duplicates = []
+    for key, val in pairs:
+        if key not in out:
+            out[key] = val
+            continue
+        duplicates.append(key)
+        prev = out[key]
+        if isinstance(prev, dict) and isinstance(val, dict):
+            _deep_merge_dicts(prev, val)
+        elif isinstance(prev, list) and isinstance(val, list):
+            prev.extend(val)
+        else:
+            out[key] = val
+    if duplicates:
+        # logger may not be wired yet — fall back to print so we never lose the warning.
+        unique = sorted(set(duplicates))
+        try:
+            logger.warning("[INIT] config.json has duplicate keys (merged): %s", unique)
+        except Exception:
+            print("[INIT] config.json has duplicate keys (merged):", unique)
+    return out
+
+
+def _merge_legacy_namespace(cfg, legacy: str, canonical: str) -> None:
+    """Fold deprecated singular keys (``tool`` / ``skill``) into their plural
+    canonical counterparts at load time. Canonical entries always win."""
+    legacy_section = cfg.get(legacy)
+    if not isinstance(legacy_section, dict) or not legacy_section:
+        cfg.pop(legacy, None)
+        return
+    canonical_section = cfg.get(canonical)
+    if not isinstance(canonical_section, dict):
+        canonical_section = {}
+    merged_keys = []
+    for name, val in legacy_section.items():
+        if name in canonical_section:
+            if isinstance(canonical_section[name], dict) and isinstance(val, dict):
+                for sub_key, sub_val in val.items():
+                    if (
+                        sub_key in canonical_section[name]
+                        and isinstance(canonical_section[name][sub_key], dict)
+                        and isinstance(sub_val, dict)
+                    ):
+                        _deep_merge_dicts(sub_val, canonical_section[name][sub_key])
+                        canonical_section[name][sub_key] = sub_val
+                    else:
+                        canonical_section[name].setdefault(sub_key, sub_val)
+            continue
+        canonical_section[name] = val
+        merged_keys.append(name)
+    cfg[canonical] = canonical_section
+    cfg.pop(legacy, None)
+    if merged_keys:
+        logger.warning(
+            "[INIT] Legacy config key '{}' is deprecated; merged into '{}': {}. "
+            "Please rename '{}' to '{}' in your config.json.".format(
+                legacy, canonical, merged_keys, legacy, canonical,
+            )
+        )
+
+
+def _sync_skill_config_to_env(skill_section) -> int:
+    """Flatten skill-namespaced config into environment variables.
+
+    Mapping rule: ``config["skills"][<name>][<key>]`` -> ``SKILL_<NAME>_<KEY>``
+    (e.g. ``skills["image-generation"].model`` -> ``SKILL_IMAGE_GENERATION_MODEL``).
+
+    This lets subprocess-based skill scripts read their own settings without
+    importing project code. Existing env vars are NOT overwritten so the
+    real environment always wins.
+
+    Returns the number of variables actually injected.
+    """
+    if not isinstance(skill_section, dict):
+        return 0
+    injected = 0
+    for skill_name, skill_conf in skill_section.items():
+        if not isinstance(skill_conf, dict):
+            continue
+        name_part = str(skill_name).replace("-", "_").upper()
+        for key, val in skill_conf.items():
+            if val is None or val == "":
+                continue
+            env_key = "SKILL_{}_{}".format(name_part, str(key).upper())
+            if env_key in os.environ:
+                continue
+            os.environ[env_key] = str(val)
+            injected += 1
+    return injected
+
+
+def get_root():
+    return os.path.dirname(os.path.abspath(__file__))
+
+
+def get_resource_root():
+    """Directory holding bundled read-only resources (e.g. config-template.json).
+
+    Under PyInstaller, data files live in sys._MEIPASS (the onedir _internal
+    folder), which differs from get_root() — the latter is used for writable
+    user data and should stay next to the executable, not inside the bundle.
+    """
+    if getattr(sys, "frozen", False) and hasattr(sys, "_MEIPASS"):
+        return sys._MEIPASS
+    return os.path.dirname(os.path.abspath(__file__))
+
+
+def get_data_root():
+    """Directory for writable user data (config.json, user_datas.pkl, run.log).
+
+    The desktop build sets COW_DATA_DIR (e.g. ~/.cow) so data lives in the
+    user's home rather than inside the read-only app bundle and survives app
+    updates. When unset (source deployment), it falls back to get_root(), so
+    existing behavior is unchanged.
+    """
+    data_dir = os.environ.get("COW_DATA_DIR")
+    if data_dir:
+        data_dir = os.path.expanduser(data_dir)
+        os.makedirs(data_dir, exist_ok=True)
+        return data_dir
+    return get_root()
+
+
+def read_file(path):
+    with open(path, mode="r", encoding="utf-8-sig") as f:
+        return f.read()
+
+
+def conf():
+    return config
+
+
+def get_appdata_dir():
+    data_path = os.path.join(get_data_root(), conf().get("appdata_dir", ""))
+    if not os.path.exists(data_path):
+        logger.info("[INIT] data path not exists, create it: {}".format(data_path))
+        os.makedirs(data_path)
+    return data_path
+
+
+def get_weixin_credentials_path():
+    """Resolve the Weixin credentials (token) file path.
+
+    Honors an explicit ``weixin_credentials_path`` from config. Otherwise the
+    packaged desktop build (COW_DATA_DIR set) keeps it under the data dir
+    (~/.cow) so all user data stays together, while source deployments retain
+    the legacy ~/.weixin_cow_credentials.json default unchanged.
+    """
+    configured = conf().get("weixin_credentials_path")
+    if configured:
+        return os.path.expanduser(configured)
+    if os.environ.get("COW_DATA_DIR"):
+        return os.path.join(get_data_root(), "weixin_credentials.json")
+    return os.path.expanduser("~/.weixin_cow_credentials.json")
+
+
+def subscribe_msg():
+    trigger_prefix = conf().get("single_chat_prefix", [""])[0]
+    msg = conf().get("subscribe_msg", "")
+    return msg.format(trigger_prefix=trigger_prefix)
+
+
+# global plugin config
+plugin_config = {}
+
+
+def write_plugin_config(pconf: dict):
+    """
+    Write the global plugin config.
+    :param pconf: the full plugin config
+    """
+    global plugin_config
+    for k in pconf:
+        plugin_config[k.lower()] = pconf[k]
+
+def remove_plugin_config(name: str):
+    """
+    Remove the global config of a plugin pending reload.
+    :param name: name of the plugin to reload
+    """
+    global plugin_config
+    plugin_config.pop(name.lower(), None)
+
+
+def pconf(plugin_name: str) -> dict:
+    """
+    Get the config for a plugin by name.
+    :param plugin_name: plugin name
+    :return: the plugin's config
+    """
+    return plugin_config.get(plugin_name.lower())
+
+
+# global config holding globally-effective state
+global_config = {"admin_users": []}
diff --git a/desktop/.gitignore b/desktop/.gitignore
new file mode 100644
index 0000000..7824fd0
--- /dev/null
+++ b/desktop/.gitignore
@@ -0,0 +1,6 @@
+node_modules/
+dist/
+release/
+*.log
+.DS_Store
+Thumbs.db
diff --git a/desktop/README.md b/desktop/README.md
new file mode 100644
index 0000000..dacf8a3
--- /dev/null
+++ b/desktop/README.md
@@ -0,0 +1,81 @@
+# CowAgent Desktop
+
+Cross-platform desktop client for CowAgent, built with Electron + React + TypeScript.
+
+## Development
+
+### Prerequisites
+
+- Node.js 18+
+- npm or yarn
+- Python 3.7+ (for the backend)
+
+### Setup
+
+```bash
+cd desktop
+npm install
+```
+
+### Run in Development
+
+Start the renderer dev server and Electron together:
+
+```bash
+npm run dev
+```
+
+Or run them separately:
+
+```bash
+# Terminal 1: Start Vite dev server
+npm run dev:renderer
+
+# Terminal 2: Start Electron (after renderer is ready)
+npm run dev:main
+```
+
+The app will automatically start the Python backend from the parent directory.
+
+### Build
+
+```bash
+# Build for current platform
+npm run dist
+
+# Build for macOS only
+npm run dist:mac
+
+# Build for Windows only
+npm run dist:win
+```
+
+Build outputs are placed in the `release/` directory.
+
+## Architecture
+
+```
+desktop/
+├── src/
+│   ├── main/              # Electron main process
+│   │   ├── index.ts       # Window management, IPC
+│   │   ├── python-manager.ts  # Python backend lifecycle
+│   │   └── preload.ts     # Context bridge for renderer
+│   └── renderer/          # React UI (Vite)
+│       └── src/
+│           ├── api/       # HTTP client for backend APIs
+│           ├── components/ # Reusable UI components
+│           ├── hooks/     # React hooks
+│           ├── pages/     # Page components
+│           └── types.ts   # TypeScript types
+├── resources/             # App icons
+├── package.json           # Dependencies and build config
+└── vite.config.ts         # Vite config
+```
+
+### How it Works
+
+1. Electron main process starts and creates the app window
+2. It spawns the Python backend (`app.py`) as a child process
+3. The React UI communicates with the Python backend via HTTP APIs
+4. SSE (Server-Sent Events) is used for streaming chat responses and live logs
diff --git a/desktop/build/build-backend.sh b/desktop/build/build-backend.sh
new file mode 100755
index 0000000..940c1af
--- /dev/null
+++ b/desktop/build/build-backend.sh
@@ -0,0 +1,79 @@
+#!/usr/bin/env bash
+#
+# Build the desktop backend into a self-contained onedir bundle via PyInstaller.
+# Run from anywhere; paths are resolved relative to the repo root.
+#
+# Usage:
+#   bash desktop/build/build-backend.sh            # build
+#   PYTHON=python3.11 bash desktop/build/build-backend.sh   # pick interpreter
+#
+# Output: desktop/build/dist/cowagent-backend/  (folder with the executable)
+set -euo pipefail
+
+# --- resolve paths --------------------------------------------------------
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
+BUILD_DIR="$SCRIPT_DIR"
+VENV_DIR="$BUILD_DIR/.venv-build"
+
+# Prefer Python 3.11 when available: on 3.13+ web.py must be installed from a
+# GitHub git source (the PyPI build fails), which is flaky on some networks.
+# 3.11 installs web.py straight from PyPI and has the best PyInstaller support.
+if [ -z "${PYTHON:-}" ]; then
+  for cand in \
+    "/Library/Frameworks/Python.framework/Versions/3.11/bin/python3.11" \
+    "python3.11" \
+    "python3.12" \
+    "python3"; do
+    if command -v "$cand" >/dev/null 2>&1; then
+      PYTHON="$cand"
+      break
+    fi
+  done
+fi
+# Prefer Python 3.11: it installs web.py from PyPI (no GitHub clone) and avoids
+# 3.13's removed-cgi compatibility shims. Override with PYTHON=... if needed.
+pick_python() {
+  if [ -n "${PYTHON:-}" ]; then echo "$PYTHON"; return; fi
+  for c in python3.11 python3.12 python3.10 python3; do
+    if command -v "$c" >/dev/null 2>&1; then echo "$c"; return; fi
+  done
+  echo python3
+}
+PYTHON="$(pick_python)"
+
+echo "==> Repo root: $ROOT"
+echo "==> Using Python: $($PYTHON --version 2>&1) ($PYTHON)"
+
+# --- isolated build venv --------------------------------------------------
+if [ ! -d "$VENV_DIR" ]; then
+  echo "==> Creating build venv at $VENV_DIR"
+  "$PYTHON" -m venv "$VENV_DIR"
+fi
+# shellcheck disable=SC1091
+source "$VENV_DIR/bin/activate"
+
+echo "==> Installing build dependencies"
+pip install -q --upgrade pip
+# Don't leave a half-populated venv behind if deps fail (e.g. flaky network):
+# the next run would otherwise reuse a broken venv.
+if ! pip install -q -r "$BUILD_DIR/requirements-desktop.txt"; then
+  echo "!! Dependency install failed. Removing the build venv so a retry starts clean." >&2
+  deactivate || true
+  rm -rf "$VENV_DIR"
+  exit 1
+fi
+pip install -q pyinstaller
+
+# --- run pyinstaller from repo root so relative datas resolve -------------
+cd "$ROOT"
+echo "==> Running PyInstaller (onedir)"
+pyinstaller "$BUILD_DIR/cowagent-backend.spec" \
+  --noconfirm \
+  --distpath "$BUILD_DIR/dist" \
+  --workpath "$BUILD_DIR/build-work"
+
+echo ""
+echo "==> Done. Bundle at: $BUILD_DIR/dist/cowagent-backend/"
+du -sh "$BUILD_DIR/dist/cowagent-backend/" 2>/dev/null || true
+echo "==> Smoke test: COW_DESKTOP=1 \"$BUILD_DIR/dist/cowagent-backend/cowagent-backend\""
diff --git a/desktop/build/cowagent-backend.spec b/desktop/build/cowagent-backend.spec
new file mode 100644
index 0000000..94506d5
--- /dev/null
+++ b/desktop/build/cowagent-backend.spec
@@ -0,0 +1,194 @@
+# -*- mode: python ; coding: utf-8 -*-
+"""
+PyInstaller spec for the CowAgent desktop backend (onedir).
+
+Produces a self-contained `cowagent-backend` folder that the Electron app
+spawns directly, so end users don't need Python installed.
+
+onedir is chosen over onefile because the backend reads data files via paths
+relative to the source tree (e.g. config-template.json, skills/, chat.html);
+onedir preserves that layout, while onefile's temp-extraction would break it.
+
+Build from the repo root:
+    pyinstaller desktop/build/cowagent-backend.spec --noconfirm
+"""
+import os
+from PyInstaller.utils.hooks import collect_submodules, collect_data_files
+
+# Resolve the repo root from the spec's own location (desktop/build/ -> root),
+# independent of the current working directory. PyInstaller exposes SPECPATH.
+ROOT = os.path.abspath(os.path.join(SPECPATH, '..', '..'))
+
+
+def rp(*parts):
+    """Absolute path under the repo root."""
+    return os.path.join(ROOT, *parts)
+
+# --- Hidden imports -------------------------------------------------------
+# Channels are imported dynamically by channel_factory via string names, so
+# PyInstaller's static analysis can't see them. List every channel we ship
+# (Feishu is intentionally excluded — lark-oapi is dropped from the desktop
+# build to save ~116MB).
+hiddenimports = [
+    # channels (dynamic import in channel/channel_factory.py)
+    'channel.web.web_channel',
+    'channel.terminal.terminal_channel',
+    'channel.weixin.weixin_channel',
+    'channel.wechatmp.wechatmp_channel',
+    'channel.wechatcom.wechatcomapp_channel',
+    'channel.wechat_kf.wechat_kf_channel',
+    'channel.dingtalk.dingtalk_channel',
+    'channel.wecom_bot.wecom_bot_channel',
+    'channel.qq.qq_channel',
+    'channel.telegram.telegram_channel',
+    'channel.slack.slack_channel',
+    'channel.discord.discord_channel',
+]
+
+# Agent tools and model providers are imported lazily in places; collect their
+# submodules so nothing is missed at runtime.
+hiddenimports += collect_submodules('agent.tools')
+hiddenimports += collect_submodules('models')
+hiddenimports += collect_submodules('voice')
+hiddenimports += collect_submodules('bridge')
+
+# Plugin framework + plugins. WebChannel -> ChatChannel imports
+# `from plugins import *`, and desktop mode loads plugins (in a background
+# thread) so command plugins like cow_cli/godcmd (/status, #help) work. Plugin
+# modules are imported dynamically by name in scan_plugins(), so list them
+# explicitly. The `cli` package is a cow_cli dependency (`from cli import ...`).
+hiddenimports += [
+    'plugins',
+    'plugins.event',
+    'plugins.plugin',
+    'plugins.plugin_manager',
+]
+hiddenimports += collect_submodules('plugins')
+
+# `cli` powers cow_cli's slash commands (`cow skill install`, `cow status`, …).
+# Its command modules are imported lazily inside functions, so static analysis
+# misses them. collect_submodules('cli') alone proved unreliable (a build can
+# end up with `cli` but not `cli.commands`), so list the command modules
+# explicitly AND ship the package as data (see datas) as a belt-and-suspenders.
+hiddenimports += collect_submodules('cli')
+hiddenimports += [
+    'cli',
+    'cli.cli',
+    'cli.utils',
+    'cli.commands',
+    'cli.commands.skill',
+    'cli.commands.process',
+    'cli.commands.context',
+    'cli.commands.install',
+    'cli.commands.knowledge',
+]
+
+# Third-party SDKs that use lazy/conditional imports internally.
+hiddenimports += collect_submodules('dashscope')
+hiddenimports += [
+    'tiktoken_ext',
+    'tiktoken_ext.openai_public',
+]
+
+# Document parsing libs. The read / web_fetch tools import these lazily inside
+# functions (e.g. `from pypdf import PdfReader`), so PyInstaller's static
+# analysis misses them and they'd be dropped from the bundle — leaving the
+# desktop client unable to read PDF/Word/Excel/PPT. List them explicitly.
+hiddenimports += [
+    'pypdf',
+    'docx',           # python-docx
+    'pptx',           # python-pptx
+    'openpyxl',
+]
+hiddenimports += collect_submodules('pypdf')
+hiddenimports += collect_submodules('docx')
+hiddenimports += collect_submodules('pptx')
+hiddenimports += collect_submodules('openpyxl')
+
+# --- Data files -----------------------------------------------------------
+# Runtime-read files/dirs that must travel with the executable. Paths are
+# (source, dest_dir_in_bundle).
+datas = [
+    (rp('config-template.json'), '.'),
+    (rp('skills'), 'skills'),
+    # PluginManager.scan_plugins() walks the on-disk ./plugins dir at runtime
+    # (it doesn't rely solely on imports), so ship the package directory too.
+    (rp('plugins'), 'plugins'),
+    # Ship the `cli` package as loose files too: onedir adds _internal to
+    # sys.path, so `import cli.commands.*` resolves even if PyInstaller's
+    # submodule collection misses the lazily-imported command modules.
+    (rp('cli'), 'cli'),
+    # Web console served on the backend port: ship chat.html plus its static
+    # assets (~1.9MB) so the browser-based console works as a debug/fallback
+    # entry alongside the Electron UI.
+    (rp('channel', 'web', 'chat.html'), 'channel/web'),
+    (rp('channel', 'web', 'static'), 'channel/web/static'),
+]
+
+# Some libraries (tiktoken encodings, etc.) ship data files.
+datas += collect_data_files('tiktoken_ext', include_py_files=False)
+
+# python-docx / python-pptx bundle template files (default.docx / default.pptx,
+# content-type XML) inside their packages; they're loaded at import/parse time,
+# so ship them or document parsing fails in the frozen build.
+datas += collect_data_files('docx')
+datas += collect_data_files('pptx')
+
+# --- Excludes -------------------------------------------------------------
+# Keep the bundle lean: drop Feishu's heavy SDK, plugins (disabled in desktop
+# mode), tests/docs, and dev-only packages.
+excludes = [
+    'lark_oapi',          # Feishu — ~116MB, excluded from desktop build
+    'tests',
+    'pip',
+    'wheel',
+    'pytest',
+    'playwright',         # browser tool is opt-in, not bundled
+]
+
+block_cipher = None
+
+a = Analysis(
+    [rp('app.py')],
+    pathex=[ROOT],
+    binaries=[],
+    datas=datas,
+    hiddenimports=hiddenimports,
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=excludes,
+    win_no_prefer_redirects=False,
+    win_private_assemblies=False,
+    cipher=block_cipher,
+    noarchive=False,
+)
+
+pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    [],
+    exclude_binaries=True,
+    name='cowagent-backend',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=False,
+    console=True,
+    disable_windowed_traceback=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.datas,
+    strip=False,
+    upx=False,
+    upx_exclude=[],
+    name='cowagent-backend',
+)
diff --git a/desktop/build/entitlements.mac.plist b/desktop/build/entitlements.mac.plist
new file mode 100644
index 0000000..6cb294b
--- /dev/null
+++ b/desktop/build/entitlements.mac.plist
@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+    <!-- Electron needs JIT and writable/executable memory for V8. -->
+    <key>com.apple.security.cs.allow-jit</key>
+    <true/>
+    <key>com.apple.security.cs.allow-unsigned-executable-memory</key>
+    <true/>
+    <!-- PyInstaller backend loads many unsigned/third-party dylibs. -->
+    <key>com.apple.security.cs.disable-library-validation</key>
+    <true/>
+    <key>com.apple.security.cs.allow-dyld-environment-variables</key>
+    <true/>
+    <!-- Allow spawning the bundled backend and other child processes. -->
+    <key>com.apple.security.inherit</key>
+    <true/>
+</dict>
+</plist>
diff --git a/desktop/build/notarize-dmg.sh b/desktop/build/notarize-dmg.sh
new file mode 100755
index 0000000..c0def42
--- /dev/null
+++ b/desktop/build/notarize-dmg.sh
@@ -0,0 +1,147 @@
+#!/usr/bin/env bash
+#
+# STAGE 2 of the decoupled release pipeline: notarize signed dmgs locally.
+#
+# CI (stage 1) already produced code-signed, hardened-runtime dmgs and mirrored
+# them to R2 as unpublished. Apple's notary service keeps this large PyInstaller
+# bundle "In Progress" for hours, so we notarize here — off the CI clock — and
+# staple the ticket straight onto the dmg (users download it ready-to-run).
+#
+# What it does for each dmg passed on the command line:
+#   1. submit the dmg to the notary service ONCE (--no-wait) and remember the id,
+#   2. poll that SAME id until Accepted/Invalid; network errors are ignored and
+#      retried, and it NEVER resubmits (avoids piling up duplicate submissions),
+#   3. staple the ticket onto the dmg,
+#   4. (optional) re-upload the stapled dmg to R2, overwriting the unpublished
+#      copy, so the CDN serves the notarized bytes.
+#
+# Auth: uses a stored keychain profile (default: cow-notary). Create it once via
+#   xcrun notarytool store-credentials cow-notary \
+#     --apple-id <id> --team-id <team> --password <app-specific-password>
+#
+# Usage:
+#   # notarize + staple only (no upload):
+#   desktop/build/notarize-dmg.sh path/to/CowAgent-1.2.3-arm64.dmg [more.dmg ...]
+#
+#   # notarize + staple + re-upload to R2 (needs wrangler + Cloudflare creds):
+#   VER=1.2.3 UPLOAD=1 desktop/build/notarize-dmg.sh *.dmg
+#
+# Env:
+#   PROFILE            keychain profile name (default: cow-notary)
+#   UPLOAD             set to 1 to re-upload stapled dmgs to R2
+#   VER                version string for the R2 key desktop/v${VER}/<file> (required if UPLOAD=1)
+#   R2_BUCKET          R2 bucket (default: cow-skills)
+#   POLL_SECONDS       status poll interval (default: 60)
+#   MAX_WAIT_MINUTES   give up polling after this long (default: 720 = 12h)
+#
+set -euo pipefail
+
+PROFILE="${PROFILE:-cow-notary}"
+R2_BUCKET="${R2_BUCKET:-cow-skills}"
+POLL_SECONDS="${POLL_SECONDS:-60}"
+MAX_WAIT_MINUTES="${MAX_WAIT_MINUTES:-720}"
+
+if [ "$#" -eq 0 ]; then
+  echo "usage: $0 <dmg> [dmg ...]" >&2
+  echo "  set UPLOAD=1 and VER=<version> to also re-upload stapled dmgs to R2" >&2
+  exit 2
+fi
+
+if [ "${UPLOAD:-0}" = "1" ] && [ -z "${VER:-}" ]; then
+  echo "error: UPLOAD=1 requires VER=<version> (used for the R2 key)" >&2
+  exit 2
+fi
+
+log() { echo "[notarize-dmg] $*"; }
+
+notarize_one() {
+  local dmg="$1"
+  if [ ! -f "$dmg" ]; then
+    log "SKIP: not a file: $dmg"
+    return 1
+  fi
+
+  # If it's already stapled (e.g. re-run), skip straight to (optional) upload.
+  if xcrun stapler validate "$dmg" >/dev/null 2>&1; then
+    log "$dmg already stapled — skipping notarization."
+  else
+    log "submitting $dmg (no-wait)..."
+    local submit_out submission_id
+    submit_out="$(xcrun notarytool submit "$dmg" \
+      --keychain-profile "$PROFILE" --no-wait --output-format json)"
+    submission_id="$(echo "$submit_out" | /usr/bin/plutil -extract id raw - 2>/dev/null || true)"
+    if [ -z "$submission_id" ] || [ "$submission_id" = "null" ]; then
+      # Fallback parse without plutil (json is single-line).
+      submission_id="$(echo "$submit_out" | sed -n 's/.*"id":"\([^"]*\)".*/\1/p')"
+    fi
+    if [ -z "$submission_id" ]; then
+      log "ERROR: could not parse submission id from:"
+      echo "$submit_out" >&2
+      return 1
+    fi
+    log "submission id: $submission_id (polling same id, never resubmitting)"
+
+    local deadline status ts
+    deadline=$(( $(date +%s) + MAX_WAIT_MINUTES * 60 ))
+    while :; do
+      status=""
+      status="$(xcrun notarytool info "$submission_id" \
+        --keychain-profile "$PROFILE" --output-format json 2>/dev/null \
+        | sed -n 's/.*"status":"\([^"]*\)".*/\1/p' || true)"
+      ts="$(date +%H:%M:%S)"
+      log "[$ts] status: ${status:-<query failed, retrying>}"
+
+      case "$status" in
+        Accepted) break ;;
+        Invalid|Rejected)
+          log "notarization $status — fetching log:"
+          xcrun notarytool log "$submission_id" --keychain-profile "$PROFILE" || true
+          return 1
+          ;;
+      esac
+
+      if [ "$(date +%s)" -ge "$deadline" ]; then
+        log "ERROR: not finished after ${MAX_WAIT_MINUTES} min (id: $submission_id)."
+        log "NOT resubmitting. Check later: xcrun notarytool info $submission_id --keychain-profile $PROFILE"
+        return 1
+      fi
+      sleep "$POLL_SECONDS"
+    done
+
+    log "Accepted; stapling ticket to $dmg"
+    local staple_try=1
+    until xcrun stapler staple "$dmg"; do
+      if [ "$staple_try" -ge 3 ]; then
+        log "ERROR: stapling failed after 3 attempts"
+        return 1
+      fi
+      log "staple failed, retrying in 15s..."
+      sleep 15
+      staple_try=$((staple_try + 1))
+    done
+    xcrun stapler validate "$dmg"
+    log "$dmg notarized + stapled."
+  fi
+
+  if [ "${UPLOAD:-0}" = "1" ]; then
+    local base key
+    base="$(basename "$dmg")"
+    key="desktop/v${VER}/${base}"
+    log "re-uploading stapled dmg -> r2://${R2_BUCKET}/${key}"
+    npx --yes wrangler@latest r2 object put "${R2_BUCKET}/${key}" \
+      --file "$dmg" --remote
+    log "uploaded $base"
+  fi
+}
+
+rc=0
+for dmg in "$@"; do
+  echo "======================================================================"
+  notarize_one "$dmg" || rc=1
+done
+
+if [ "$rc" -ne 0 ]; then
+  log "one or more dmgs failed — see output above."
+  exit 1
+fi
+log "all done."
diff --git a/desktop/build/requirements-desktop.txt b/desktop/build/requirements-desktop.txt
new file mode 100644
index 0000000..dc6c077
--- /dev/null
+++ b/desktop/build/requirements-desktop.txt
@@ -0,0 +1,52 @@
+# Desktop backend dependencies (slimmed down from the full requirements).
+#
+# Goal: keep the package light. The desktop client only needs the web channel
+# (which Electron talks to) plus the agent core; the remaining IM channels are
+# cheap (~27MB total) so we keep them, but Feishu's `lark-oapi` (~116MB) is
+# dropped — it is by far the heaviest dependency and not needed for a C-end
+# desktop app. Feishu is hidden in desktop mode (see COW_DESKTOP in app.py).
+
+# ---- core ----
+numpy>=1.21
+aiohttp>=3.8.6,<3.10
+requests>=2.28.2
+chardet>=5.1.0
+Pillow
+python-dotenv>=1.0.0
+PyYAML>=6.0
+croniter>=2.0.0
+click>=8.0
+qrcode
+json-repair
+
+# ---- web framework (web channel) ----
+# web.py 0.62 fails to build on Python 3.13+ (cgi removed); use the GitHub fix.
+web.py; python_version < "3.13"
+web.py @ git+https://github.com/webpy/webpy.git ; python_version >= "3.13"
+legacy-cgi; python_version >= "3.13"
+
+# ---- AI model SDKs ----
+zai-sdk
+dashscope
+tenacity        # used by some dashscope submodules (retry logic)
+google-generativeai
+tiktoken>=0.3.2
+
+# ---- voice (TTS/ASR) — kept per product decision ----
+pydub>=0.25.1
+gTTS>=2.3.1
+
+# ---- document parsing (web_fetch / knowledge) ----
+pypdf
+python-docx
+openpyxl
+python-pptx
+
+# ---- IM channels (kept; lightweight). Feishu/lark-oapi intentionally excluded. ----
+wechatpy
+pycryptodome
+dingtalk_stream
+websocket-client>=1.4.0
+python-telegram-bot
+slack_bolt
+discord.py
diff --git a/desktop/electron-builder.js b/desktop/electron-builder.js
new file mode 100644
index 0000000..9b27219
--- /dev/null
+++ b/desktop/electron-builder.js
@@ -0,0 +1,83 @@
+/**
+ * Dynamic electron-builder config.
+ *
+ * We keep the base config in package.json's "build" field and extend it here
+ * only to populate `mac.binaries` — the list of extra Mach-O files that must
+ * be signed with hardened runtime + entitlements.
+ *
+ * Why this is needed:
+ * The Python backend is a PyInstaller onedir bundle shipped via extraResources
+ * into Contents/Resources/backend/. electron-builder only hands the top-level
+ * `.app` to codesign, which does NOT deep-sign the ~180 nested .so/.dylib
+ * files under Resources/. Left unsigned (or without hardened runtime), Apple
+ * notarization rejects the whole app.
+ *
+ * `mac.binaries` is the officially supported way to sign extra binaries: they
+ * are signed inside electron-builder's own signing pass, AFTER it has created
+ * the temporary keychain and imported the Developer ID cert (from CSC_LINK).
+ * A previous afterPack approach failed because afterPack runs BEFORE that
+ * keychain exists, so `codesign` couldn't find the identity.
+ *
+ * Paths are resolved relative to the `.app` at signing time. We enumerate the
+ * pre-build backend source dir (build/dist/cowagent-backend, produced by
+ * PyInstaller before packaging) — its layout mirrors the in-app copy — and map
+ * each Mach-O to its in-app relative path.
+ */
+const { execFileSync } = require('child_process')
+const fs = require('fs')
+const path = require('path')
+
+const config = require('./package.json').build
+
+// PyInstaller output that gets copied into the app at
+// Contents/Resources/backend/cowagent-backend (see extraResources).
+const backendSrc = path.join(__dirname, 'build', 'dist', 'cowagent-backend')
+const inAppPrefix = path.join('Contents', 'Resources', 'backend', 'cowagent-backend')
+
+function isMachO(file) {
+  try {
+    return execFileSync('file', ['-b', file], { encoding: 'utf8' }).includes('Mach-O')
+  } catch {
+    return false
+  }
+}
+
+function collectBackendBinaries() {
+  if (!fs.existsSync(backendSrc)) {
+    console.warn(`[electron-builder.js] backend not found at ${backendSrc}; mac.binaries left empty`)
+    return []
+  }
+  const rels = []
+  const walk = (dir) => {
+    for (const name of fs.readdirSync(dir)) {
+      const full = path.join(dir, name)
+      const st = fs.lstatSync(full)
+      if (st.isSymbolicLink()) continue
+      if (st.isDirectory()) {
+        walk(full)
+        continue
+      }
+      if (isMachO(full)) {
+        // Map source path -> in-app relative path (resolved against the .app).
+        const rel = path.relative(backendSrc, full)
+        rels.push(path.join(inAppPrefix, rel))
+      }
+    }
+  }
+  walk(backendSrc)
+  return rels
+}
+
+if (process.platform === 'darwin') {
+  const binaries = collectBackendBinaries()
+  console.log(`[electron-builder.js] injecting ${binaries.length} backend binaries into mac.binaries`)
+  // Sign the backend binaries here, but do NOT notarize in CI: Apple's notary
+  // service routinely keeps this large PyInstaller bundle "In Progress" for
+  // hours, which no CI job can afford to block on. Notarization is decoupled
+  // into a manual local step (build/notarize-dmg.sh) run after the CI produces
+  // the signed dmg. The dmg is code-signed and hardened-runtime enabled here,
+  // so it only needs the notarization ticket stapled afterwards.
+  config.mac = { ...config.mac, binaries, notarize: false }
+}
+
+module.exports = config
diff --git a/desktop/package-lock.json b/desktop/package-lock.json
new file mode 100644
index 0000000..24575ef
--- /dev/null
+++ b/desktop/package-lock.json
@@ -0,0 +1,8300 @@
+{
+  "name": "cowagent-desktop",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "cowagent-desktop",
+      "version": "1.0.0",
+      "license": "MIT",
+      "dependencies": {
+        "electron-updater": "^6.8.9",
+        "highlight.js": "^11.11.1",
+        "lucide-react": "^1.21.0",
+        "markdown-it": "^14.2.0",
+        "react": "^18.3.1",
+        "react-dom": "^18.3.1",
+        "react-router-dom": "^6.28.0",
+        "zustand": "^5.0.14"
+      },
+      "devDependencies": {
+        "@types/markdown-it": "^14.1.2",
+        "@types/react": "^18.3.12",
+        "@types/react-dom": "^18.3.1",
+        "@vitejs/plugin-react": "^4.3.4",
+        "autoprefixer": "^10.4.20",
+        "concurrently": "^9.1.0",
+        "electron": "^33.2.0",
+        "electron-builder": "^25.1.8",
+        "postcss": "^8.4.49",
+        "tailwindcss": "^3.4.15",
+        "typescript": "^5.7.2",
+        "vite": "^6.0.3"
+      }
+    },
+    "node_modules/@alloc/quick-lru": {
+      "version": "5.2.0",
+      "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
+      "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
+    "node_modules/@babel/code-frame": {
+      "version": "7.29.0",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
+      "integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-validator-identifier": "^7.28.5",
+        "js-tokens": "^4.0.0",
+        "picocolors": "^1.1.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/compat-data": {
+      "version": "7.29.0",
+      "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.29.0.tgz",
+      "integrity": "sha512-T1NCJqT/j9+cn8fvkt7jtwbLBfLC/1y1c7NtCeXFRgzGTsafi68MRv8yzkYSapBnFA6L3U2VSc02ciDzoAJhJg==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/core": {
+      "version": "7.29.0",
+      "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.29.0.tgz",
+      "integrity": "sha512-CGOfOJqWjg2qW/Mb6zNsDm+u5vFQ8DxXfbM09z69p5Z6+mE1ikP2jUXw+j42Pf1XTYED2Rni5f95npYeuwMDQA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/code-frame": "^7.29.0",
+        "@babel/generator": "^7.29.0",
+        "@babel/helper-compilation-targets": "^7.28.6",
+        "@babel/helper-module-transforms": "^7.28.6",
+        "@babel/helpers": "^7.28.6",
+        "@babel/parser": "^7.29.0",
+        "@babel/template": "^7.28.6",
+        "@babel/traverse": "^7.29.0",
+        "@babel/types": "^7.29.0",
+        "@jridgewell/remapping": "^2.3.5",
+        "convert-source-map": "^2.0.0",
+        "debug": "^4.1.0",
+        "gensync": "^1.0.0-beta.2",
+        "json5": "^2.2.3",
+        "semver": "^6.3.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/babel"
+      }
+    },
+    "node_modules/@babel/generator": {
+      "version": "7.29.1",
+      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.29.1.tgz",
+      "integrity": "sha512-qsaF+9Qcm2Qv8SRIMMscAvG4O3lJ0F1GuMo5HR/Bp02LopNgnZBC/EkbevHFeGs4ls/oPz9v+Bsmzbkbe+0dUw==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/parser": "^7.29.0",
+        "@babel/types": "^7.29.0",
+        "@jridgewell/gen-mapping": "^0.3.12",
+        "@jridgewell/trace-mapping": "^0.3.28",
+        "jsesc": "^3.0.2"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-compilation-targets": {
+      "version": "7.28.6",
+      "resolved": "https://registry.npmjs.org/@babel/helper-compilation-targets/-/helper-compilation-targets-7.28.6.tgz",
+      "integrity": "sha512-JYtls3hqi15fcx5GaSNL7SCTJ2MNmjrkHXg4FSpOA/grxK8KwyZ5bubHsCq8FXCkua6xhuaaBit+3b7+VZRfcA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/compat-data": "^7.28.6",
+        "@babel/helper-validator-option": "^7.27.1",
+        "browserslist": "^4.24.0",
+        "lru-cache": "^5.1.1",
+        "semver": "^6.3.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-globals": {
+      "version": "7.28.0",
+      "resolved": "https://registry.npmjs.org/@babel/helper-globals/-/helper-globals-7.28.0.tgz",
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+        "@types/react": ">=18.0.0",
+        "immer": ">=9.0.6",
+        "react": ">=18.0.0",
+        "use-sync-external-store": ">=1.2.0"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
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+  }
+}
diff --git a/desktop/package.json b/desktop/package.json
new file mode 100644
index 0000000..6fb438a
--- /dev/null
+++ b/desktop/package.json
@@ -0,0 +1,117 @@
+{
+  "name": "cowagent-desktop",
+  "version": "2.1.3",
+  "description": "CowAgent Desktop Client - AI Agent on your desktop",
+  "main": "dist/main/index.js",
+  "author": "CowAgent",
+  "license": "MIT",
+  "scripts": {
+    "dev": "npm run build && electron .",
+    "dev:hot": "concurrently \"npm run dev:renderer\" \"sleep 2 && npm run dev:main\"",
+    "dev:main": "tsc -p tsconfig.main.json && electron .",
+    "dev:renderer": "vite",
+    "build": "npm run build:renderer && npm run build:main",
+    "build:main": "tsc -p tsconfig.main.json",
+    "build:renderer": "vite build",
+    "dist": "npm run build && electron-builder",
+    "dist:mac": "npm run build && electron-builder --mac",
+    "dist:win": "npm run build && electron-builder --win"
+  },
+  "dependencies": {
+    "electron-updater": "^6.8.9",
+    "highlight.js": "^11.11.1",
+    "lucide-react": "^1.21.0",
+    "markdown-it": "^14.2.0",
+    "react": "^18.3.1",
+    "react-dom": "^18.3.1",
+    "react-router-dom": "^6.28.0",
+    "zustand": "^5.0.14"
+  },
+  "devDependencies": {
+    "@types/markdown-it": "^14.1.2",
+    "@types/react": "^18.3.12",
+    "@types/react-dom": "^18.3.1",
+    "@vitejs/plugin-react": "^4.3.4",
+    "autoprefixer": "^10.4.20",
+    "concurrently": "^9.1.0",
+    "electron": "^33.2.0",
+    "electron-builder": "^25.1.8",
+    "postcss": "^8.4.49",
+    "tailwindcss": "^3.4.15",
+    "typescript": "^5.7.2",
+    "vite": "^6.0.3"
+  },
+  "build": {
+    "appId": "com.cowagent.desktop",
+    "productName": "CowAgent",
+    "directories": {
+      "output": "release"
+    },
+    "files": [
+      "dist/**/*",
+      "resources/**/*"
+    ],
+    "extraResources": [
+      {
+        "from": "build/dist/cowagent-backend",
+        "to": "backend/cowagent-backend"
+      },
+      {
+        "from": "resources",
+        "to": ".",
+        "filter": [
+          "icon.png"
+        ]
+      }
+    ],
+    "mac": {
+      "category": "public.app-category.productivity",
+      "icon": "resources/icon.icns",
+      "hardenedRuntime": true,
+      "gatekeeperAssess": false,
+      "entitlements": "build/entitlements.mac.plist",
+      "entitlementsInherit": "build/entitlements.mac.plist",
+      "notarize": false,
+      "artifactName": "${productName}-${version}-${arch}.${ext}",
+      "target": [
+        {
+          "target": "dmg",
+          "arch": [
+            "arm64",
+            "x64"
+          ]
+        },
+        {
+          "target": "zip",
+          "arch": [
+            "arm64",
+            "x64"
+          ]
+        }
+      ]
+    },
+    "win": {
+      "icon": "resources/icon.ico",
+      "artifactName": "${productName}-Setup-${version}-${arch}.${ext}",
+      "target": [
+        {
+          "target": "nsis",
+          "arch": [
+            "x64"
+          ]
+        }
+      ]
+    },
+    "nsis": {
+      "oneClick": false,
+      "perMachine": false,
+      "allowToChangeInstallationDirectory": true,
+      "createDesktopShortcut": true,
+      "createStartMenuShortcut": true
+    },
+    "publish": {
+      "provider": "generic",
+      "url": "https://cowagent.ai/update/"
+    }
+  }
+}
diff --git a/desktop/postcss.config.js b/desktop/postcss.config.js
new file mode 100644
index 0000000..33ad091
--- /dev/null
+++ b/desktop/postcss.config.js
@@ -0,0 +1,6 @@
+module.exports = {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+}
diff --git a/desktop/resources/icon.icns b/desktop/resources/icon.icns
new file mode 100644
index 0000000..be56144
Binary files /dev/null and b/desktop/resources/icon.icns differ
diff --git a/desktop/resources/icon.ico b/desktop/resources/icon.ico
new file mode 100644
index 0000000..71f4566
Binary files /dev/null and b/desktop/resources/icon.ico differ
diff --git a/desktop/resources/icon.png b/desktop/resources/icon.png
new file mode 100644
index 0000000..402d75d
Binary files /dev/null and b/desktop/resources/icon.png differ
diff --git a/desktop/src/main/index.ts b/desktop/src/main/index.ts
new file mode 100644
index 0000000..5f9d130
--- /dev/null
+++ b/desktop/src/main/index.ts
@@ -0,0 +1,354 @@
+import { app, BrowserWindow, shell, ipcMain, dialog, nativeImage } from 'electron'
+import path from 'path'
+import fs from 'fs'
+import http from 'http'
+import { PythonBackend } from './python-manager'
+import { buildAppMenu } from './menu'
+import { createTray, destroyTray } from './tray'
+import { initUpdater, checkForUpdates, startDownload, quitAndInstall, setUpdateLanguage } from './updater'
+
+// Force the product name so the Dock/menu shows "CowAgent" even in dev mode,
+// where the default Electron binary would otherwise report "Electron".
+app.setName('CowAgent')
+
+let mainWindow: BrowserWindow | null = null
+let pythonBackend: PythonBackend | null = null
+// True once the user explicitly quits (menu/tray), so close-to-tray is bypassed.
+let isQuitting = false
+
+const isDev = !app.isPackaged
+const VITE_DEV_PORTS = [5173, 5174, 5175, 5176]
+
+function probePort(port: number): Promise<boolean> {
+  return new Promise((resolve) => {
+    const req = http.get(`http://localhost:${port}`, (res) => {
+      resolve(res.statusCode !== undefined)
+    })
+    req.on('error', () => resolve(false))
+    req.setTimeout(500, () => { req.destroy(); resolve(false) })
+  })
+}
+
+async function findViteDevServer(): Promise<string | null> {
+  for (const port of VITE_DEV_PORTS) {
+    if (await probePort(port)) {
+      return `http://localhost:${port}`
+    }
+  }
+  return null
+}
+
+function getIconPath(ext: string = 'png'): string | undefined {
+  const iconFile = `icon.${ext}`
+  const iconPath = isDev
+    ? path.resolve(__dirname, '../../resources', iconFile)
+    : path.join(process.resourcesPath, iconFile)
+  if (fs.existsSync(iconPath)) return iconPath
+  return undefined
+}
+
+const isMac = process.platform === 'darwin'
+const isWin = process.platform === 'win32'
+
+// Persisted window bounds
+const windowStateFile = () => path.join(app.getPath('userData'), 'window-state.json')
+
+function loadWindowState(): { width: number; height: number; x?: number; y?: number } {
+  try {
+    const raw = fs.readFileSync(windowStateFile(), 'utf-8')
+    const s = JSON.parse(raw)
+    if (typeof s.width === 'number' && typeof s.height === 'number') return s
+  } catch {
+    /* first run or unreadable */
+  }
+  return { width: 1280, height: 800 }
+}
+
+function saveWindowState() {
+  if (!mainWindow || mainWindow.isDestroyed()) return
+  if (mainWindow.isMinimized() || mainWindow.isFullScreen()) return
+  const b = mainWindow.getBounds()
+  try {
+    fs.writeFileSync(windowStateFile(), JSON.stringify(b))
+  } catch {
+    /* ignore */
+  }
+}
+
+function createWindow() {
+  const state = loadWindowState()
+
+  mainWindow = new BrowserWindow({
+    width: state.width,
+    height: state.height,
+    x: state.x,
+    y: state.y,
+    minWidth: 900,
+    minHeight: 600,
+    // macOS: native traffic lights inset into our custom titlebar.
+    // Windows: fully frameless; we render custom window controls in-app.
+    titleBarStyle: isMac ? 'hiddenInset' : 'hidden',
+    trafficLightPosition: isMac ? { x: 14, y: 16 } : undefined,
+    frame: isMac ? undefined : false,
+    backgroundColor: '#0e0e10',
+    icon: getIconPath(),
+    show: false,
+    webPreferences: {
+      preload: path.join(__dirname, 'preload.js'),
+      contextIsolation: true,
+      nodeIntegration: false,
+    },
+  })
+
+  const persist = () => saveWindowState()
+  mainWindow.on('resize', persist)
+  mainWindow.on('move', persist)
+  mainWindow.on('maximize', emitMaximizeState)
+  mainWindow.on('unmaximize', emitMaximizeState)
+
+  const rendererHtml = path.join(__dirname, '../renderer/index.html')
+
+  if (isDev) {
+    findViteDevServer().then((devUrl) => {
+      if (devUrl) {
+        console.log(`[Electron] Loading Vite dev server: ${devUrl}`)
+        mainWindow?.loadURL(devUrl)
+        mainWindow?.webContents.openDevTools()
+      } else if (fs.existsSync(rendererHtml)) {
+        console.log('[Electron] Vite dev server not found, loading built files')
+        mainWindow?.loadFile(rendererHtml)
+      } else {
+        console.error('[Electron] No renderer available. Run "npm run build:renderer" first.')
+      }
+    })
+  } else {
+    mainWindow.loadFile(rendererHtml)
+  }
+
+  // Surface renderer-side console output and load failures to the main-process
+  // stdout. Without this, "stuck on initializing" hangs are invisible from the
+  // terminal because all renderer logs stay in the (closed) devtools.
+  mainWindow.webContents.on('console-message', (_e, level, message, line, sourceId) => {
+    console.log(`[renderer:${level}] ${message} (${sourceId}:${line})`)
+  })
+  mainWindow.webContents.on('did-fail-load', (_e, code, desc, url) => {
+    console.error(`[renderer] did-fail-load ${code} ${desc} ${url}`)
+  })
+
+  mainWindow.once('ready-to-show', () => {
+    mainWindow?.show()
+  })
+
+  mainWindow.webContents.setWindowOpenHandler(({ url }) => {
+    shell.openExternal(url)
+    return { action: 'deny' }
+  })
+
+  // Close-to-tray: hide the window instead of destroying it, so the tray's
+  // "Show" can bring it back. Only a real Quit (menu/tray/Cmd+Q) destroys it.
+  mainWindow.on('close', (e) => {
+    if (!isQuitting) {
+      e.preventDefault()
+      mainWindow?.hide()
+    }
+  })
+
+  mainWindow.on('closed', () => {
+    mainWindow = null
+  })
+}
+
+function getBackendPath(): string {
+  if (isDev) {
+    return path.resolve(__dirname, '../../..')
+  }
+  return path.join(process.resourcesPath, 'backend')
+}
+
+async function startBackend() {
+  const backendPath = getBackendPath()
+  pythonBackend = new PythonBackend(backendPath)
+
+  pythonBackend.on('ready', (port: number) => {
+    console.log(`[backend] ready on port ${port}`)
+    mainWindow?.webContents.send('backend-status', { status: 'ready', port })
+  })
+
+  pythonBackend.on('error', (error: string) => {
+    // Mirror to the main-process stdout too: otherwise backend startup errors
+    // are only visible in the renderer devtools, making `npm run dev` hangs
+    // impossible to diagnose from the terminal.
+    console.error(`[backend] error: ${error}`)
+    mainWindow?.webContents.send('backend-status', { status: 'error', error })
+  })
+
+  pythonBackend.on('log', (line: string) => {
+    console.log(`[backend] ${line}`)
+    mainWindow?.webContents.send('backend-log', line)
+  })
+
+  await pythonBackend.start()
+}
+
+function setupIPC() {
+  ipcMain.handle('get-backend-port', () => {
+    return pythonBackend?.getPort() ?? null
+  })
+
+  ipcMain.handle('get-backend-status', () => {
+    return pythonBackend?.getStatus() ?? 'stopped'
+  })
+
+  ipcMain.handle('restart-backend', async () => {
+    await pythonBackend?.restart()
+    return true
+  })
+
+  ipcMain.handle('select-directory', async () => {
+    const result = await dialog.showOpenDialog({
+      properties: ['openDirectory'],
+    })
+    return result.canceled ? null : result.filePaths[0]
+  })
+
+  ipcMain.handle('select-file', async (_event, filters?: Electron.FileFilter[]) => {
+    const result = await dialog.showOpenDialog({
+      properties: ['openFile'],
+      filters: filters || [{ name: 'All Files', extensions: ['*'] }],
+    })
+    return result.canceled ? null : result.filePaths[0]
+  })
+
+  // Open a local file with the OS default app; falls back to revealing it in
+  // the file manager when no handler exists. Returns '' on success.
+  ipcMain.handle('open-path', async (_event, targetPath: string) => {
+    if (!targetPath) return 'empty path'
+    const err = await shell.openPath(targetPath)
+    if (err) shell.showItemInFolder(targetPath)
+    return err
+  })
+
+  // Custom window controls (used by Windows frameless titlebar)
+  ipcMain.handle('window-minimize', () => mainWindow?.minimize())
+  ipcMain.handle('window-maximize', () => {
+    if (!mainWindow) return false
+    if (mainWindow.isMaximized()) mainWindow.unmaximize()
+    else mainWindow.maximize()
+    return mainWindow.isMaximized()
+  })
+  ipcMain.handle('window-close', () => mainWindow?.close())
+  ipcMain.handle('window-is-maximized', () => mainWindow?.isMaximized() ?? false)
+
+  // Current app version, shown in the NavRail footer.
+  ipcMain.handle('get-app-version', () => app.getVersion())
+
+  // Auto-update controls (renderer-driven: check, then opt-in download/install).
+  // The renderer passes its current UI language so downloads can be routed to
+  // the China CDN mirror (zh) or R2 (others).
+  ipcMain.handle('update-check', (_event, lang?: string) => {
+    setUpdateLanguage(lang)
+    checkForUpdates()
+  })
+  ipcMain.handle('update-download', (_event, lang?: string) => {
+    setUpdateLanguage(lang)
+    startDownload()
+  })
+  ipcMain.handle('update-install', () => {
+    // Let the window actually close so the app can fully quit — otherwise the
+    // close-to-tray handler preventDefault()s it, the process stays alive, and
+    // Squirrel.Mac can't swap the app bundle (the update silently no-ops and
+    // relaunching still shows the old version).
+    isQuitting = true
+    quitAndInstall()
+  })
+
+  // Synchronous OS locale lookup (e.g. "zh-CN", "en-US"). Used by the renderer
+  // to pick a sensible default UI language on first run before any paint.
+  ipcMain.on('get-system-locale', (event) => {
+    event.returnValue = app.getLocale() || app.getSystemLocale?.() || ''
+  })
+}
+
+function emitMaximizeState() {
+  const max = mainWindow?.isMaximized() ?? false
+  mainWindow?.webContents.send('window-maximize-changed', max)
+}
+
+// Single-instance lock: focus the existing window instead of opening a second app.
+const gotTheLock = app.requestSingleInstanceLock()
+if (!gotTheLock) {
+  app.quit()
+} else {
+  app.on('second-instance', () => {
+    if (mainWindow) {
+      if (mainWindow.isMinimized()) mainWindow.restore()
+      mainWindow.show()
+      mainWindow.focus()
+    }
+  })
+}
+
+app.whenReady().then(async () => {
+  // Set Dock icon on macOS (PNG is most reliable for nativeImage)
+  if (process.platform === 'darwin') {
+    const pngPath = getIconPath('png')
+    if (pngPath) {
+      const icon = nativeImage.createFromPath(pngPath)
+      if (!icon.isEmpty()) {
+        app.dock.setIcon(icon)
+        console.log('[Electron] Dock icon set:', pngPath)
+      } else {
+        console.warn('[Electron] Dock icon loaded but empty:', pngPath)
+      }
+    } else {
+      console.warn('[Electron] Dock icon not found in resources/')
+    }
+  }
+
+  setupIPC()
+  createWindow()
+  buildAppMenu(() => mainWindow)
+  // No menu-bar tray on macOS — the Dock + window controls are enough there.
+  // Keep the tray on Windows/Linux where minimizing to a tray icon is expected.
+  if (!isMac) {
+    createTray({
+      getWindow: () => mainWindow,
+      iconPath: getIconPath('png'),
+      onQuit: () => {
+        isQuitting = true
+        app.quit()
+      },
+    })
+  }
+  await startBackend()
+
+  // Wire auto-update: a first silent check a few seconds after launch (so it
+  // doesn't compete with backend startup), then poll every 4 hours so a
+  // long-running window still surfaces new releases. autoDownload is off, so a
+  // found update only lights the badge + opens the panel for the user to opt in.
+  initUpdater(() => mainWindow)
+  setTimeout(() => checkForUpdates(), 5000)
+  const UPDATE_POLL_MS = 4 * 60 * 60 * 1000
+  setInterval(() => checkForUpdates(), UPDATE_POLL_MS)
+
+  app.on('activate', () => {
+    if (BrowserWindow.getAllWindows().length === 0) {
+      createWindow()
+    } else {
+      mainWindow?.show()
+    }
+  })
+})
+
+app.on('window-all-closed', () => {
+  if (process.platform !== 'darwin') {
+    app.quit()
+  }
+})
+
+app.on('before-quit', () => {
+  isQuitting = true
+  saveWindowState()
+  destroyTray()
+  pythonBackend?.stop()
+})
diff --git a/desktop/src/main/menu.ts b/desktop/src/main/menu.ts
new file mode 100644
index 0000000..d5195a3
--- /dev/null
+++ b/desktop/src/main/menu.ts
@@ -0,0 +1,112 @@
+import { app, Menu, BrowserWindow, shell } from 'electron'
+import type { MenuItemConstructorOptions } from 'electron'
+
+const isMac = process.platform === 'darwin'
+const SKILL_HUB_URL = 'https://skills.cowagent.ai/'
+const DOCS_URL = 'https://docs.cowagent.ai'
+
+// Send a menu-triggered action to the renderer (e.g. new chat, open settings).
+function emit(win: BrowserWindow | null, action: string) {
+  win?.webContents.send('menu-action', action)
+}
+
+/**
+ * Build a minimal, purpose-built application menu. We intentionally drop most of
+ * Electron's verbose defaults and keep only items that are actually useful for
+ * this app, plus the shortcuts users expect (New Chat, Settings, Reload, etc).
+ */
+export function buildAppMenu(getWindow: () => BrowserWindow | null) {
+  const win = () => getWindow()
+
+  const appMenu: MenuItemConstructorOptions[] = isMac
+    ? [
+        {
+          label: app.name,
+          submenu: [
+            { role: 'about' },
+            { type: 'separator' },
+            { label: 'Settings…', accelerator: 'Cmd+,', click: () => emit(win(), 'open-settings') },
+            { type: 'separator' },
+            { role: 'hide' },
+            { role: 'hideOthers' },
+            { role: 'unhide' },
+            { type: 'separator' },
+            { role: 'quit' },
+          ],
+        },
+      ]
+    : []
+
+  const fileMenu: MenuItemConstructorOptions = {
+    label: 'File',
+    submenu: [
+      { label: 'New Chat', accelerator: 'CmdOrCtrl+N', click: () => emit(win(), 'new-chat') },
+      ...(!isMac
+        ? ([
+            { label: 'Settings', accelerator: 'Ctrl+,', click: () => emit(win(), 'open-settings') },
+            { type: 'separator' },
+            { role: 'quit' },
+          ] as MenuItemConstructorOptions[])
+        : []),
+    ],
+  }
+
+  const editMenu: MenuItemConstructorOptions = {
+    label: 'Edit',
+    submenu: [
+      { role: 'undo' },
+      { role: 'redo' },
+      { type: 'separator' },
+      { role: 'cut' },
+      { role: 'copy' },
+      { role: 'paste' },
+      { role: 'selectAll' },
+    ],
+  }
+
+  const viewMenu: MenuItemConstructorOptions = {
+    label: 'View',
+    submenu: [
+      { role: 'reload' },
+      { role: 'toggleDevTools' },
+      { type: 'separator' },
+      { role: 'resetZoom' },
+      { role: 'zoomIn' },
+      { role: 'zoomOut' },
+      { type: 'separator' },
+      { role: 'togglefullscreen' },
+    ],
+  }
+
+  const windowMenu: MenuItemConstructorOptions = {
+    label: 'Window',
+    submenu: [
+      { role: 'minimize' },
+      ...(isMac ? ([{ role: 'zoom' }] as MenuItemConstructorOptions[]) : []),
+      { type: 'separator' },
+      // Explicit Close so Cmd/Ctrl+W reliably triggers our close-to-tray hide.
+      { label: 'Close Window', accelerator: 'CmdOrCtrl+W', click: () => win()?.close() },
+    ],
+  }
+
+  const helpMenu: MenuItemConstructorOptions = {
+    label: 'Help',
+    submenu: [
+      { label: 'View Logs', click: () => emit(win(), 'view-logs') },
+      { type: 'separator' },
+      { label: 'Documentation', click: () => shell.openExternal(DOCS_URL) },
+      { label: 'Skill Hub', click: () => shell.openExternal(SKILL_HUB_URL) },
+    ],
+  }
+
+  const template: MenuItemConstructorOptions[] = [
+    ...appMenu,
+    fileMenu,
+    editMenu,
+    viewMenu,
+    windowMenu,
+    helpMenu,
+  ]
+
+  Menu.setApplicationMenu(Menu.buildFromTemplate(template))
+}
diff --git a/desktop/src/main/preload.ts b/desktop/src/main/preload.ts
new file mode 100644
index 0000000..b0fcfac
--- /dev/null
+++ b/desktop/src/main/preload.ts
@@ -0,0 +1,67 @@
+import { contextBridge, ipcRenderer } from 'electron'
+
+contextBridge.exposeInMainWorld('electronAPI', {
+  getBackendPort: () => ipcRenderer.invoke('get-backend-port'),
+  getBackendStatus: () => ipcRenderer.invoke('get-backend-status'),
+  restartBackend: () => ipcRenderer.invoke('restart-backend'),
+  selectDirectory: () => ipcRenderer.invoke('select-directory'),
+  selectFile: (filters?: Electron.FileFilter[]) => ipcRenderer.invoke('select-file', filters),
+  openPath: (targetPath: string) => ipcRenderer.invoke('open-path', targetPath) as Promise<string>,
+
+  // Each listener registrar returns an unsubscribe fn so renderers can clean
+  // up on unmount / effect re-run and avoid accumulating duplicate handlers.
+  onBackendStatus: (callback: (data: { status: string; port?: number; error?: string }) => void) => {
+    const handler = (_event: unknown, data: { status: string; port?: number; error?: string }) => callback(data)
+    ipcRenderer.on('backend-status', handler)
+    return () => ipcRenderer.removeListener('backend-status', handler)
+  },
+
+  onBackendLog: (callback: (line: string) => void) => {
+    const handler = (_event: unknown, line: string) => callback(line)
+    ipcRenderer.on('backend-log', handler)
+    return () => ipcRenderer.removeListener('backend-log', handler)
+  },
+
+  // Window controls (custom titlebar on Windows)
+  windowMinimize: () => ipcRenderer.invoke('window-minimize'),
+  windowMaximize: () => ipcRenderer.invoke('window-maximize'),
+  windowClose: () => ipcRenderer.invoke('window-close'),
+  windowIsMaximized: () => ipcRenderer.invoke('window-is-maximized'),
+  onMaximizeChange: (callback: (maximized: boolean) => void) => {
+    const handler = (_event: unknown, max: boolean) => callback(max)
+    ipcRenderer.on('window-maximize-changed', handler)
+    return () => ipcRenderer.removeListener('window-maximize-changed', handler)
+  },
+
+  // App menu / shortcut actions forwarded from the main process.
+  onMenuAction: (callback: (action: string) => void) => {
+    const handler = (_event: unknown, action: string) => callback(action)
+    ipcRenderer.on('menu-action', handler)
+    return () => ipcRenderer.removeListener('menu-action', handler)
+  },
+
+  // Current app version (e.g. "0.0.5"), shown in the NavRail footer.
+  getAppVersion: () => ipcRenderer.invoke('get-app-version'),
+
+  // Auto-update: trigger checks/download/install and subscribe to status. The
+  // optional lang routes installer downloads to the China CDN mirror (zh) or R2.
+  checkForUpdate: (lang?: string) => ipcRenderer.invoke('update-check', lang),
+  downloadUpdate: (lang?: string) => ipcRenderer.invoke('update-download', lang),
+  installUpdate: () => ipcRenderer.invoke('update-install'),
+  onUpdateStatus: (callback: (status: unknown) => void) => {
+    const handler = (_event: unknown, status: unknown) => callback(status)
+    ipcRenderer.on('update-status', handler)
+    return () => ipcRenderer.removeListener('update-status', handler)
+  },
+
+  platform: process.platform,
+  // OS UI language (e.g. "zh-CN"), read synchronously so the renderer can pick
+  // a default language on first run. Falls back to '' if unavailable.
+  systemLocale: (() => {
+    try {
+      return ipcRenderer.sendSync('get-system-locale') as string
+    } catch {
+      return ''
+    }
+  })(),
+})
diff --git a/desktop/src/main/python-manager.ts b/desktop/src/main/python-manager.ts
new file mode 100644
index 0000000..603254b
--- /dev/null
+++ b/desktop/src/main/python-manager.ts
@@ -0,0 +1,456 @@
+import { ChildProcess, spawn, execFileSync } from 'child_process'
+import { EventEmitter } from 'events'
+import path from 'path'
+import os from 'os'
+import fs from 'fs'
+import http from 'http'
+import net from 'net'
+
+// Writable data dir for the packaged app (config.json, run.log, user data).
+// Lives in the user's home so it survives app updates and avoids writing into
+// the read-only app bundle. Source/dev runs keep using the repo CWD instead.
+const COW_DATA_DIR = path.join(os.homedir(), '.cow')
+
+// Fixed port for the desktop backend. Deliberately not 9899 (the web console's
+// default) so a source-run `python app.py` never collides with the packaged
+// app. This is a SINGLE SOURCE OF TRUTH shared with the renderer (see
+// useBackend.ts BACKEND_PORT): the backend is always told to bind exactly here
+// via COW_WEB_PORT, and the renderer always talks to exactly here. We do NOT
+// fall back to an OS-random port, because the renderer could never guess it —
+// instead we proactively free this port before launch (see freePort()).
+export const DESKTOP_BACKEND_PORT = 9876
+
+export class PythonBackend extends EventEmitter {
+  private process: ChildProcess | null = null
+  private backendPath: string
+  private port: number = DESKTOP_BACKEND_PORT
+  private status: 'stopped' | 'starting' | 'ready' | 'error' = 'stopped'
+
+  constructor(backendPath: string) {
+    super()
+    this.backendPath = backendPath
+  }
+
+  getPort(): number {
+    return this.port
+  }
+
+  getStatus(): string {
+    return this.status
+  }
+
+  // Cache the resolved PATH so we only spawn a login shell once per process.
+  private resolvedPath: string | null = null
+
+  /**
+   * Build the PATH the backend should run with.
+   *
+   * When launched from Finder/Dock, a GUI app inherits launchd's minimal PATH
+   * (/usr/bin:/bin:...) and never loads ~/.zshrc, so user-installed CLIs like
+   * `linkai`, `node`, or Homebrew tools are invisible to the agent's bash tool.
+   * We recover the real login-shell PATH (macOS/Linux) and merge in common bin
+   * dirs, so the agent can find these commands regardless of how the app started.
+   */
+  private resolveEnvPath(): string {
+    if (this.resolvedPath !== null) {
+      return this.resolvedPath
+    }
+
+    const sep = path.delimiter
+    const existing = process.env.PATH || ''
+    const parts: string[] = existing ? existing.split(sep) : []
+
+    // Windows GUI apps already inherit the full system PATH; nothing to fix.
+    if (process.platform !== 'win32') {
+      // Ask the user's login shell for its PATH. `-ilc` runs an interactive
+      // login shell so it sources ~/.zshrc / ~/.zprofile etc.
+      try {
+        const shell = process.env.SHELL || '/bin/zsh'
+        const out = execFileSync(shell, ['-ilc', 'echo -n "__PATH__$PATH"'], {
+          encoding: 'utf8',
+          timeout: 5000,
+          stdio: ['ignore', 'pipe', 'ignore'],
+        })
+        const marker = out.lastIndexOf('__PATH__')
+        if (marker !== -1) {
+          const shellPath = out.slice(marker + '__PATH__'.length).trim()
+          if (shellPath) {
+            parts.push(...shellPath.split(sep))
+          }
+        }
+      } catch {
+        // Shell probe failed (unusual shell, timeout). Fall back to the
+        // common dirs below so at least the typical install paths work.
+      }
+
+      const home = os.homedir()
+      parts.push(
+        path.join(home, '.local/bin'),
+        '/usr/local/bin',
+        '/opt/homebrew/bin',
+        '/usr/bin',
+        '/bin',
+        '/usr/sbin',
+        '/sbin',
+      )
+    }
+
+    // De-duplicate while preserving order (first occurrence wins).
+    const seen = new Set<string>()
+    const merged: string[] = []
+    for (const p of parts) {
+      const dir = p.trim()
+      if (dir && !seen.has(dir)) {
+        seen.add(dir)
+        merged.push(dir)
+      }
+    }
+
+    this.resolvedPath = merged.join(sep)
+    return this.resolvedPath
+  }
+
+  /**
+   * Locate the packaged onedir backend executable shipped with the app.
+   * Returns null when not present (e.g. during local development), so we can
+   * fall back to running app.py with a system/venv Python.
+   */
+  private findBundledBackend(): string | null {
+    const exeName = process.platform === 'win32' ? 'cowagent-backend.exe' : 'cowagent-backend'
+    const candidates = [
+      path.join(this.backendPath, 'cowagent-backend', exeName),
+      path.join(this.backendPath, exeName),
+    ]
+    for (const p of candidates) {
+      if (fs.existsSync(p)) {
+        return p
+      }
+    }
+    return null
+  }
+
+  private findPython(): string {
+    const venvPaths = [
+      path.join(this.backendPath, '.venv', 'bin', 'python'),
+      path.join(this.backendPath, '.venv', 'Scripts', 'python.exe'),
+      path.join(this.backendPath, 'venv', 'bin', 'python'),
+      path.join(this.backendPath, 'venv', 'Scripts', 'python.exe'),
+    ]
+
+    for (const p of venvPaths) {
+      if (fs.existsSync(p)) {
+        return p
+      }
+    }
+
+    return process.platform === 'win32' ? 'python' : 'python3'
+  }
+
+  /**
+   * Read an explicit `web_port` from config.json, if the user pinned one. The
+   * packaged build keeps config in COW_DATA_DIR (~/.cow); dev reads it from the
+   * repo path. Returns null when unset, so the caller can auto-pick a free port
+   * instead of fighting over a fixed one.
+   */
+  private readConfiguredPort(dataDir: string): number | null {
+    try {
+      const configPath = path.join(dataDir, 'config.json')
+      if (fs.existsSync(configPath)) {
+        const config = JSON.parse(fs.readFileSync(configPath, 'utf-8'))
+        const p = Number(config.web_port)
+        if (Number.isInteger(p) && p > 0 && p < 65536) {
+          return p
+        }
+      }
+    } catch {
+      // ignore — fall through to auto-selection
+    }
+    return null
+  }
+
+  /**
+   * Resolve the port to bind. The whole point is determinism: the renderer must
+   * be able to reach the backend WITHOUT guessing, so we use exactly one fixed
+   * port (DESKTOP_BACKEND_PORT) unless the user explicitly pinned a web_port.
+   * We never auto-roll to a random port — instead start() proactively frees the
+   * fixed port. The returned value is the single source of truth handed to both
+   * the backend (COW_WEB_PORT) and the renderer (getBackendPort IPC).
+   */
+  private resolvePort(dataDir: string): number {
+    const pinned = this.readConfiguredPort(dataDir)
+    return pinned !== null ? pinned : DESKTOP_BACKEND_PORT
+  }
+
+  /** True if we can bind 127.0.0.1:port right now (i.e. it's free). */
+  private isPortFree(port: number): Promise<boolean> {
+    return new Promise((resolve) => {
+      const tester = net
+        .createServer()
+        .once('error', () => resolve(false))
+        .once('listening', () => {
+          tester.close(() => resolve(true))
+        })
+        .listen(port, '127.0.0.1')
+    })
+  }
+
+  /**
+   * Make sure our fixed port is usable before launch by killing whatever is
+   * holding it (almost always a stale backend from a previous run that didn't
+   * shut down cleanly). We only ever target a process actually listening on
+   * 127.0.0.1:<port>, so we won't touch unrelated apps. Best-effort: if we
+   * can't free it we still try to bind and let the backend surface EADDRINUSE.
+   */
+  private async freePort(port: number): Promise<void> {
+    if (await this.isPortFree(port)) {
+      return
+    }
+    this.emit('log', `Port ${port} is busy — clearing stale process before launch`)
+    const pids = await this.findListenerPids(port)
+    for (const pid of pids) {
+      // Never signal ourselves (Electron could, in theory, be the listener).
+      if (pid === process.pid) continue
+      try {
+        process.kill(pid, 'SIGTERM')
+      } catch {
+        // already gone / no permission — ignore
+      }
+    }
+    // Give the OS a beat to release the socket, then force-kill leftovers.
+    await new Promise((r) => setTimeout(r, 600))
+    if (!(await this.isPortFree(port))) {
+      for (const pid of await this.findListenerPids(port)) {
+        if (pid === process.pid) continue
+        try {
+          process.kill(pid, 'SIGKILL')
+        } catch {
+          // ignore
+        }
+      }
+      await new Promise((r) => setTimeout(r, 400))
+    }
+  }
+
+  /** PIDs listening on 127.0.0.1:<port>, via lsof (POSIX) / netstat (Windows). */
+  private findListenerPids(port: number): Promise<number[]> {
+    return new Promise((resolve) => {
+      const isWin = process.platform === 'win32'
+      const cmd = isWin ? 'netstat' : 'lsof'
+      const args = isWin
+        ? ['-ano', '-p', 'tcp']
+        : ['-nP', `-iTCP:${port}`, '-sTCP:LISTEN', '-t']
+      let out = ''
+      try {
+        const child = spawn(cmd, args)
+        child.stdout?.on('data', (d: Buffer) => (out += d.toString()))
+        child.on('error', () => resolve([]))
+        child.on('close', () => {
+          const pids = new Set<number>()
+          if (isWin) {
+            // Match lines like: TCP 127.0.0.1:9876 ... LISTENING  12345
+            for (const line of out.split('\n')) {
+              if (!/LISTENING/i.test(line)) continue
+              if (!new RegExp(`[:.]${port}\\b`).test(line)) continue
+              const pid = Number(line.trim().split(/\s+/).pop())
+              if (Number.isInteger(pid) && pid > 0) pids.add(pid)
+            }
+          } else {
+            for (const tok of out.split(/\s+/)) {
+              const pid = Number(tok)
+              if (Number.isInteger(pid) && pid > 0) pids.add(pid)
+            }
+          }
+          resolve([...pids])
+        })
+      } catch {
+        resolve([])
+      }
+    })
+  }
+
+  async start(): Promise<void> {
+    if (this.status === 'ready' || this.status === 'starting') {
+      return
+    }
+
+    this.status = 'starting'
+
+    // Prefer the packaged self-contained backend (production); fall back to
+    // running app.py with a Python interpreter (local development).
+    const bundled = this.findBundledBackend()
+    // Packaged app stores writable data in ~/.cow; dev keeps it in the repo.
+    const dataDir = bundled ? COW_DATA_DIR : this.backendPath
+
+    // Always launch our OWN backend (re-entrancy is guarded above by the status
+    // check, so we never double-spawn for this instance). We don't reuse
+    // whatever happens to be on the port: that's how the app previously attached
+    // to a source-run web console and read the wrong config. The port is fixed
+    // (or the user's pinned web_port) — never random — so the renderer always
+    // knows it. We then proactively free that port (kill stale listeners)
+    // before spawning, so a leftover process from a previous run can't block us.
+    this.port = this.resolvePort(dataDir)
+    await this.freePort(this.port)
+
+    let command: string
+    let args: string[]
+    let cwd: string
+
+    if (bundled) {
+      command = bundled
+      args = []
+      // Run from the writable data dir (~/.cow), NOT the install dir. When the
+      // app is installed under Program Files, a non-admin user has no write
+      // permission to the executable's folder, so any relative-path write
+      // during startup would crash the backend (works only as admin). The
+      // bundle reads its read-only resources via sys._MEIPASS, so cwd is free
+      // to point elsewhere.
+      try {
+        fs.mkdirSync(COW_DATA_DIR, { recursive: true })
+      } catch {
+        // ignore — get_data_root() also ensures the dir on the Python side
+      }
+      cwd = COW_DATA_DIR
+      this.emit('log', `Starting bundled backend: ${bundled} (cwd=${cwd})`)
+    } else {
+      const pythonPath = this.findPython()
+      const appPath = path.join(this.backendPath, 'app.py')
+      if (!fs.existsSync(appPath)) {
+        this.status = 'error'
+        this.emit('error', `app.py not found at ${appPath}`)
+        return
+      }
+      command = pythonPath
+      args = [appPath]
+      cwd = this.backendPath
+      this.emit('log', `Starting Python backend: ${pythonPath} ${appPath}`)
+    }
+
+    this.process = spawn(command, args, {
+      cwd,
+      // COW_DESKTOP enables the lighter desktop runtime (no plugins, no MCP).
+      // COW_DATA_DIR (packaged only) redirects writable data to ~/.cow so the
+      // app bundle stays read-only; dev runs omit it and keep using the repo.
+      env: {
+        ...process.env,
+        // Recover the user's real PATH (login shell + common bin dirs) so the
+        // agent's bash tool can find CLIs like `linkai`/`node` even when the
+        // app is launched from Finder/Dock with launchd's minimal PATH.
+        PATH: this.resolveEnvPath(),
+        PYTHONUNBUFFERED: '1',
+        COW_DESKTOP: '1',
+        // The shell owns the port: tell the backend to bind exactly here so the
+        // two sides can never disagree (and we avoid the 9899 web-console clash).
+        COW_WEB_PORT: String(this.port),
+        ...(bundled ? { COW_DATA_DIR } : {}),
+      },
+      stdio: ['pipe', 'pipe', 'pipe'],
+    })
+
+    this.process.stdout?.on('data', (data: Buffer) => {
+      const lines = data.toString().split('\n').filter(Boolean)
+      for (const line of lines) {
+        this.emit('log', line)
+      }
+    })
+
+    this.process.stderr?.on('data', (data: Buffer) => {
+      const lines = data.toString().split('\n').filter(Boolean)
+      for (const line of lines) {
+        this.emit('log', line)
+      }
+    })
+
+    this.process.on('exit', (code) => {
+      // If the backend dies before it ever became ready, surface an error now
+      // instead of letting waitForReady spin for the full timeout. A clean exit
+      // (code 0/null, e.g. our own stop()) just marks stopped.
+      const wasReady = this.status === 'ready'
+      this.status = 'stopped'
+      this.emit('log', `Python process exited with code ${code}`)
+      if (!wasReady && code !== 0 && code !== null) {
+        this.status = 'error'
+        this.emit('error', `Backend exited during startup (code ${code})`)
+      }
+    })
+
+    this.process.on('error', (err) => {
+      this.status = 'error'
+      this.emit('error', `Failed to start Python: ${err.message}`)
+    })
+
+    await this.waitForReady()
+  }
+
+  private waitForReady(): Promise<void> {
+    return new Promise((resolve) => {
+      // Wall-clock deadline rather than an attempt counter: if the machine
+      // sleeps/suspends, the 1s timers stretch out and a counter would give up
+      // far too early. Time-based bounding tracks real elapsed time instead.
+      const timeoutMs = 120_000
+      const startedAt = Date.now()
+
+      const check = () => {
+        // Probe the unauthenticated health endpoint, NOT /config: /config
+        // requires auth once a web_password is set, which would make this poll
+        // 401 forever and hang startup.
+        const req = http.get(`http://127.0.0.1:${this.port}/api/health`, (res) => {
+          if (res.statusCode === 200) {
+            this.status = 'ready'
+            this.emit('log', `Backend ready on port ${this.port}`)
+            this.emit('ready', this.port)
+            resolve()
+          } else {
+            retry()
+          }
+        })
+
+        req.on('error', () => retry())
+        req.setTimeout(2000, () => {
+          req.destroy()
+          retry()
+        })
+      }
+
+      const retry = () => {
+        // Backend already settled: ready (done), or stopped/errored by the exit
+        // handler (don't keep polling a dead process — the error was emitted).
+        if (this.status === 'ready' || this.status === 'stopped' || this.status === 'error') {
+          resolve()
+          return
+        }
+        if (Date.now() - startedAt >= timeoutMs) {
+          this.status = 'error'
+          this.emit('error', `Backend failed to start within ${Math.round(timeoutMs / 1000)} seconds`)
+          resolve()
+          return
+        }
+        setTimeout(check, 1000)
+      }
+
+      setTimeout(check, 2000)
+    })
+  }
+
+  stop(): void {
+    const proc = this.process
+    if (proc) {
+      proc.kill('SIGTERM')
+      // Keep a local ref so the SIGKILL fallback can still reach the process
+      // even after we clear `this.process`; otherwise a stuck backend would
+      // never be force-killed and leak as a zombie.
+      setTimeout(() => {
+        if (!proc.killed) {
+          proc.kill('SIGKILL')
+        }
+      }, 5000)
+      this.process = null
+    }
+    this.status = 'stopped'
+  }
+
+  async restart(): Promise<void> {
+    this.stop()
+    await new Promise((resolve) => setTimeout(resolve, 2000))
+    await this.start()
+  }
+}
diff --git a/desktop/src/main/tray.ts b/desktop/src/main/tray.ts
new file mode 100644
index 0000000..a26818a
--- /dev/null
+++ b/desktop/src/main/tray.ts
@@ -0,0 +1,59 @@
+import { app, Tray, Menu, BrowserWindow, nativeImage } from 'electron'
+
+let tray: Tray | null = null
+
+interface TrayDeps {
+  getWindow: () => BrowserWindow | null
+  // Colored icon used on Windows/Linux trays.
+  iconPath?: string
+  // Called when the user picks "Quit" so the app can fully exit.
+  onQuit: () => void
+}
+
+// Build a system tray icon with a minimal menu (Windows/Linux only — macOS
+// uses the Dock instead). Lets users restore the window after closing it to the
+// background and start a new chat quickly.
+export function createTray({ getWindow, iconPath, onQuit }: TrayDeps): Tray | null {
+  if (tray) return tray
+  if (!iconPath) return null
+
+  let image = nativeImage.createFromPath(iconPath)
+  if (image.isEmpty()) return null
+  // Tray icons render small; resize to avoid an oversized image on some platforms.
+  image = image.resize({ width: 18, height: 18 })
+
+  tray = new Tray(image)
+  tray.setToolTip(app.name)
+
+  const showWindow = () => {
+    const win = getWindow()
+    if (!win) return
+    if (win.isMinimized()) win.restore()
+    win.show()
+    win.focus()
+  }
+
+  const contextMenu = Menu.buildFromTemplate([
+    { label: 'Show CowAgent', click: showWindow },
+    {
+      label: 'New Chat',
+      click: () => {
+        showWindow()
+        getWindow()?.webContents.send('menu-action', 'new-chat')
+      },
+    },
+    { type: 'separator' },
+    { label: 'Quit', click: onQuit },
+  ])
+  tray.setContextMenu(contextMenu)
+
+  // Single click restores the window (common Windows/Linux behavior).
+  tray.on('click', showWindow)
+
+  return tray
+}
+
+export function destroyTray() {
+  tray?.destroy()
+  tray = null
+}
diff --git a/desktop/src/main/updater.ts b/desktop/src/main/updater.ts
new file mode 100644
index 0000000..76ee24c
--- /dev/null
+++ b/desktop/src/main/updater.ts
@@ -0,0 +1,245 @@
+import { app, BrowserWindow } from 'electron'
+import fs from 'fs'
+import path from 'path'
+// electron-updater is CommonJS: its members live on module.exports, with no
+// meaningful default export. Under module=commonjs + esModuleInterop, a named
+// import compiles to `electron_updater_1.autoUpdater` and resolves correctly,
+// whereas `import pkg from 'electron-updater'` yields undefined.
+import { autoUpdater } from 'electron-updater'
+
+// Status payloads pushed to the renderer over the 'update-status' channel.
+// The renderer drives the NavRail badge + update panel from these.
+export type UpdateStatus =
+  | { state: 'checking' }
+  | { state: 'available'; version: string; notes?: string }
+  | { state: 'not-available' }
+  | { state: 'downloading'; percent: number }
+  | { state: 'downloaded'; version: string }
+  | { state: 'error'; message: string }
+
+let getWindow: () => BrowserWindow | null = () => null
+
+// The update feed. Both entries hit the same Pages Function
+// (https://cowagent.ai/update/); the ?lang=zh query tells it to 302 installer
+// downloads to the China CDN mirror instead of R2. The feed metadata is
+// identical either way, so we can freely switch the feed URL between attempts
+// to fall back from one download origin to the other.
+const FEED_BASE = 'https://cowagent.ai/update/'
+const feedUrlFor = (china: boolean) => (china ? `${FEED_BASE}?lang=zh` : FEED_BASE)
+
+// Which origin the current session prefers, derived from the app UI language
+// (zh -> China mirror). Downloads that fail on the preferred origin retry once
+// on the other one before surfacing an error.
+let preferChina = false
+// Guard so a single download only ever falls back once (avoids ping-pong).
+let downloadFellBack = false
+
+function applyFeedUrl(): void {
+  const url = feedUrlFor(preferChina)
+  try {
+    autoUpdater.setFeedURL({ provider: 'generic', url })
+    log(`feed url set: ${url} (preferChina=${preferChina})`)
+  } catch (err) {
+    log(`feed url set failed: ${(err as Error)?.message || String(err)}`)
+  }
+}
+
+// Called from the check/download IPC with the renderer's current UI language.
+export function setUpdateLanguage(lang: string | undefined): void {
+  const china = (lang || '').toLowerCase().startsWith('zh')
+  if (china !== preferChina) {
+    preferChina = china
+    if (app.isPackaged) applyFeedUrl()
+  }
+}
+
+// Persist update logs to a file so a user hitting a silent "spinner never
+// resolves" can just send us userData/logs/updater.log. We can't rely on a
+// logging dep, so this is a tiny append-only writer, plus console for the
+// in-app log view / terminal.
+let logFile: string | null = null
+
+function initLogFile() {
+  try {
+    const dir = path.join(app.getPath('userData'), 'logs')
+    fs.mkdirSync(dir, { recursive: true })
+    logFile = path.join(dir, 'updater.log')
+  } catch {
+    logFile = null
+  }
+}
+
+function log(...parts: unknown[]) {
+  const line = `[${new Date().toISOString()}] [updater] ${parts
+    .map((p) => (typeof p === 'string' ? p : safeStringify(p)))
+    .join(' ')}`
+  // Console: shows up in the terminal (dev) and the packaged app's stdout.
+  console.log(line)
+  if (logFile) {
+    try {
+      fs.appendFileSync(logFile, line + '\n')
+    } catch {
+      // ignore disk errors — logging must never break the updater
+    }
+  }
+}
+
+function safeStringify(v: unknown): string {
+  try {
+    return JSON.stringify(v)
+  } catch {
+    return String(v)
+  }
+}
+
+function send(status: UpdateStatus) {
+  getWindow()?.webContents.send('update-status', status)
+}
+
+export function initUpdater(windowGetter: () => BrowserWindow | null): void {
+  getWindow = windowGetter
+  initLogFile()
+
+  log(`init: appVersion=${app.getVersion()} packaged=${app.isPackaged} logFile=${logFile ?? '<none>'}`)
+
+  // In dev (not packaged) there's no update feed; skip wiring entirely so
+  // electron-updater doesn't throw on the missing app-update.yml.
+  if (!app.isPackaged) {
+    log('not packaged — updater wiring skipped')
+    return
+  }
+
+  // User-driven flow: we surface "available" and let the user opt in to the
+  // download, rather than pulling bytes silently in the background.
+  autoUpdater.autoDownload = false
+  autoUpdater.autoInstallOnAppQuit = true
+  // The desktop channel ships pre-release-tagged builds (e.g. 0.0.8-test), so a
+  // current version like 0.0.7-test must be allowed to compare against, and be
+  // offered, other pre-release versions. Without this electron-updater's semver
+  // compare can silently skip pre-releases and neither "available" nor
+  // "not-available" fires — the UI just spins forever.
+  autoUpdater.allowPrerelease = true
+  autoUpdater.allowDowngrade = false
+  // Point at the preferred origin up front (defaults to R2; switched to the CN
+  // mirror once the renderer reports a zh UI language via setUpdateLanguage).
+  applyFeedUrl()
+  // Route electron-updater's own internal logging to our file too, so we
+  // capture the feed URL, parsed versions and any stack traces it logs.
+  autoUpdater.logger = {
+    info: (m: unknown) => log('eu-info:', m),
+    warn: (m: unknown) => log('eu-warn:', m),
+    error: (m: unknown) => log('eu-error:', m),
+    debug: (m: unknown) => log('eu-debug:', m),
+  } as unknown as typeof autoUpdater.logger
+
+  autoUpdater.on('checking-for-update', () => {
+    log(`checking-for-update: current=${app.getVersion()}`)
+    send({ state: 'checking' })
+  })
+  autoUpdater.on('update-available', (info) => {
+    log(`update-available: current=${app.getVersion()} remote=${info.version} -> update needed`)
+    send({
+      state: 'available',
+      version: info.version,
+      notes: typeof info.releaseNotes === 'string' ? info.releaseNotes : undefined,
+    })
+  })
+  autoUpdater.on('update-not-available', (info) => {
+    log(`update-not-available: current=${app.getVersion()} remote=${info?.version ?? '<unknown>'} -> up to date`)
+    send({ state: 'not-available' })
+  })
+  autoUpdater.on('download-progress', (p) => {
+    log(`download-progress: ${Math.round(p.percent)}% (${p.transferred}/${p.total} bytes, ${Math.round(p.bytesPerSecond / 1024)} KB/s)`)
+    send({ state: 'downloading', percent: Math.round(p.percent) })
+  })
+  autoUpdater.on('update-downloaded', (info) => {
+    log(`update-downloaded: version=${info.version} -> ready to install`)
+    send({ state: 'downloaded', version: info.version })
+  })
+  autoUpdater.on('error', (err) => {
+    const message = err == null ? 'unknown' : err.message || String(err)
+    log(`error: ${message}`, err instanceof Error && err.stack ? err.stack : '')
+    send({ state: 'error', message })
+  })
+}
+
+// Silent check shortly after launch. When not packaged there's no update feed,
+// but a manual click should still get visible feedback instead of looking dead:
+// reply "not-available" so the menu can show "up to date".
+export function checkForUpdates(): void {
+  if (!app.isPackaged) {
+    // Dev-only UI harness: set COW_MOCK_UPDATE=1 to simulate an available
+    // update so the update panel/menu interactions can be exercised in
+    // `npm run dev` (where there's no real feed). Never runs in a packaged app.
+    if (process.env.COW_MOCK_UPDATE) {
+      const version = process.env.COW_MOCK_UPDATE_VERSION || '9.9.9'
+      log(`checkForUpdates: not packaged, MOCK available version=${version}`)
+      send({ state: 'available', version })
+      return
+    }
+    log('checkForUpdates: not packaged, replying not-available')
+    send({ state: 'not-available' })
+    return
+  }
+  log(`checkForUpdates: requesting feed, current=${app.getVersion()}`)
+  autoUpdater.checkForUpdates().catch((err) => {
+    const message = err?.message || String(err)
+    log(`checkForUpdates: request failed: ${message}`, err instanceof Error && err.stack ? err.stack : '')
+    send({ state: 'error', message })
+  })
+}
+
+export function startDownload(): void {
+  if (!app.isPackaged) return
+  downloadFellBack = false
+  log(`startDownload: user requested download (preferChina=${preferChina})`)
+  attemptDownload()
+}
+
+// Download from the current origin; on failure, switch to the OTHER origin once
+// and retry. This is the client-side "mirrors back each other" fallback: R2 and
+// the China CDN hold identical bytes, so a slow/blocked origin can be swapped
+// transparently without the user noticing.
+function attemptDownload(): void {
+  autoUpdater.downloadUpdate().catch((err) => {
+    const message = err?.message || String(err)
+    log(`startDownload: failed on ${preferChina ? 'CN' : 'R2'}: ${message}`, err instanceof Error && err.stack ? err.stack : '')
+    if (!downloadFellBack) {
+      downloadFellBack = true
+      preferChina = !preferChina
+      applyFeedUrl()
+      log(`startDownload: retrying on ${preferChina ? 'CN' : 'R2'} mirror`)
+      // Re-check first so electron-updater re-reads the feed from the new origin
+      // before downloading (its cached updateInfo is origin-agnostic here, but a
+      // fresh check keeps the internal state consistent).
+      autoUpdater
+        .checkForUpdates()
+        .then(() => autoUpdater.downloadUpdate())
+        .catch((err2) => {
+          const m2 = err2?.message || String(err2)
+          log(`startDownload: fallback also failed: ${m2}`, err2 instanceof Error && err2.stack ? err2.stack : '')
+          send({ state: 'error', message: m2 })
+        })
+      return
+    }
+    send({ state: 'error', message })
+  })
+}
+
+export function quitAndInstall(): void {
+  if (!app.isPackaged) return
+  log('quitAndInstall: relaunching to install update')
+  // Drop window-all-closed handlers first: a lingering handler can keep the
+  // process alive and stop the installer from replacing files / relaunching
+  // (a documented electron-updater gotcha, esp. on Windows NSIS).
+  app.removeAllListeners('window-all-closed')
+  // isSilent=TRUE on Windows. Our installer is now ASSISTED (nsis.oneClick=false
+  // + allowToChangeInstallationDirectory) so the FIRST install shows the
+  // directory/mode wizard. But an UPDATE must NOT re-show that wizard — isSilent
+  // skips it and updates in place. isForceRunAfter=true relaunches after the
+  // silent update. (The old assisted+silent force-run bug, #2179, was fixed
+  // upstream in PR #2278; we're on electron-updater 6.8.9, well past it.)
+  // setImmediate + removeAllListeners are the documented prerequisites for the
+  // relaunch to fire reliably. macOS ignores isSilent entirely.
+  setImmediate(() => autoUpdater.quitAndInstall(true, true))
+}
diff --git a/desktop/src/renderer/assets.d.ts b/desktop/src/renderer/assets.d.ts
new file mode 100644
index 0000000..aaca79e
--- /dev/null
+++ b/desktop/src/renderer/assets.d.ts
@@ -0,0 +1,21 @@
+// Type declarations for static asset imports handled by Vite.
+declare module '*.png' {
+  const src: string
+  export default src
+}
+declare module '*.jpg' {
+  const src: string
+  export default src
+}
+declare module '*.jpeg' {
+  const src: string
+  export default src
+}
+declare module '*.svg' {
+  const src: string
+  export default src
+}
+declare module '*.webp' {
+  const src: string
+  export default src
+}
diff --git a/desktop/src/renderer/index.html b/desktop/src/renderer/index.html
new file mode 100644
index 0000000..48187e5
--- /dev/null
+++ b/desktop/src/renderer/index.html
@@ -0,0 +1,31 @@
+<!DOCTYPE html>
+<html lang="zh">
+<head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <meta http-equiv="Content-Security-Policy" content="default-src 'self' 'unsafe-inline' data: blob: http://127.0.0.1:* http://localhost:*; img-src 'self' data: blob: https: http://127.0.0.1:* http://localhost:*; media-src 'self' data: blob: https: http://127.0.0.1:* http://localhost:*; connect-src 'self' https: http://127.0.0.1:* http://localhost:* ws://127.0.0.1:* ws://localhost:*;" />
+    <title>CowAgent</title>
+    <!-- Local fonts & icons (offline, no CDN) served from publicDir -->
+    <link rel="stylesheet" href="./vendor/fonts/inter/inter.css" />
+    <link rel="stylesheet" href="./vendor/fontawesome/css/all.min.css" />
+    <script>
+    // Resolve theme before first paint to avoid flash-of-wrong-theme.
+    (function () {
+      try {
+        var pref = localStorage.getItem('cow_theme') || 'dark';
+        var resolved = pref === 'system'
+          ? (window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light')
+          : pref;
+        if (resolved === 'dark') document.documentElement.classList.add('dark');
+        else document.documentElement.classList.remove('dark');
+      } catch (e) {
+        document.documentElement.classList.add('dark');
+      }
+    })();
+    </script>
+</head>
+<body class="h-screen overflow-hidden">
+    <div id="root"></div>
+    <script type="module" src="./src/main.tsx"></script>
+</body>
+</html>
diff --git a/desktop/src/renderer/src/App.tsx b/desktop/src/renderer/src/App.tsx
new file mode 100644
index 0000000..004c4e6
--- /dev/null
+++ b/desktop/src/renderer/src/App.tsx
@@ -0,0 +1,182 @@
+import React, { useState, useCallback, useEffect } from 'react'
+import { Routes, Route, useLocation, useNavigate } from 'react-router-dom'
+import { History } from 'lucide-react'
+import NavRail from './layout/NavRail'
+import SessionList from './layout/SessionList'
+import WindowControls from './layout/WindowControls'
+import StatusScreen from './components/StatusScreen'
+import LoginGate from './components/LoginGate'
+import { useBackend } from './hooks/useBackend'
+import { usePlatform } from './hooks/usePlatform'
+import { useUIStore } from './store/uiStore'
+import { useSessionStore } from './store/sessionStore'
+import { initUpdateListener } from './store/updateStore'
+import { useOnboardingStore } from './store/onboardingStore'
+import OnboardingWizard from './components/OnboardingWizard'
+import apiClient from './api/client'
+import { t } from './i18n'
+import ChatPage from './pages/ChatPage'
+import SettingsPage from './pages/SettingsPage'
+import KnowledgePage from './pages/KnowledgePage'
+import SkillsPage from './pages/SkillsPage'
+import MemoryPage from './pages/MemoryPage'
+import ChannelsPage from './pages/ChannelsPage'
+import TasksPage from './pages/TasksPage'
+import LogsPage from './pages/LogsPage'
+
+const App: React.FC = () => {
+  const backend = useBackend()
+  const location = useLocation()
+  const navigate = useNavigate()
+  const { isWin, isMac } = usePlatform()
+  const { sessionsCollapsed, toggleSessions, navCollapsed } = useUIStore()
+  const onboardingOpen = useOnboardingStore((s) => s.open)
+  const maybeOpenOnboarding = useOnboardingStore((s) => s.maybeOpen)
+  const [, forceUpdate] = useState(0)
+  // Auth gate for web_password-protected backends. 'checking' until we know
+  // whether login is needed; 'need_login' shows the password screen; 'ok' lets
+  // the main UI render.
+  const [authState, setAuthState] = useState<'checking' | 'need_login' | 'ok'>('checking')
+
+  useEffect(() => {
+    if (backend.status === 'ready') apiClient.setBaseUrl(backend.baseUrl)
+  }, [backend.status, backend.baseUrl])
+
+  // Once the backend is ready, check whether a web_password is set. If so and
+  // this session isn't authenticated, show the login gate before the app.
+  useEffect(() => {
+    if (backend.status !== 'ready') {
+      setAuthState('checking')
+      return
+    }
+    let cancelled = false
+    apiClient
+      .authCheck()
+      .then((res) => {
+        if (cancelled) return
+        const needLogin = res.auth_required && !res.authenticated
+        setAuthState(needLogin ? 'need_login' : 'ok')
+      })
+      .catch(() => {
+        // If the check itself fails, don't hard-block the user — assume no auth
+        // is required (backends without web_password never return errors here).
+        if (!cancelled) setAuthState('ok')
+      })
+    return () => {
+      cancelled = true
+    }
+  }, [backend.status, backend.baseUrl])
+
+  // First-run check: once the backend is ready, decide whether to show the
+  // onboarding wizard. It's config-driven — shown whenever the chat model isn't
+  // configured (and not dismissed earlier this session); no persisted flag.
+  useEffect(() => {
+    if (backend.status !== 'ready' || authState !== 'ok') return
+    let cancelled = false
+    apiClient
+      .getModels()
+      .then((data) => {
+        if (cancelled) return
+        const chat = data.capabilities?.chat
+        // "Configured" needs a chat provider+model AND that provider's API key
+        // set. A default config can ship a model name with no key, which
+        // shouldn't count as ready — otherwise we'd skip onboarding for users
+        // who still need to enter a key.
+        const providerId = chat?.current_provider
+        const provider = data.providers?.find((p) => p.id === providerId)
+        const keyReady = !!provider && (provider.configured || (provider.is_custom && !!provider.custom_name))
+        const configured = !!providerId && !!chat?.current_model && keyReady
+        maybeOpenOnboarding(configured)
+      })
+      .catch(() => {
+        // If models can't be loaded, fall back to the flag-only decision.
+        if (!cancelled) maybeOpenOnboarding(false)
+      })
+    return () => {
+      cancelled = true
+    }
+  }, [backend.status, authState, maybeOpenOnboarding])
+
+  // Subscribe to auto-update status from the main process (no-op in dev).
+  useEffect(() => initUpdateListener(), [])
+
+  // Handle app-menu / shortcut actions forwarded from the main process.
+  useEffect(() => {
+    const off = window.electronAPI?.onMenuAction?.((action) => {
+      if (action === 'new-chat') {
+        useSessionStore.getState().newSession()
+        navigate('/')
+      } else if (action === 'open-settings') {
+        navigate('/settings')
+      } else if (action === 'view-logs') {
+        navigate('/logs')
+      }
+    })
+    return off
+  }, [navigate])
+
+  const handleLangChange = useCallback(() => forceUpdate((n) => n + 1), [])
+
+  if (backend.status !== 'ready') {
+    return <StatusScreen status={backend.status} error={backend.error} onRetry={backend.restart} />
+  }
+
+  // Backend is up but we're still resolving auth — keep the loading screen.
+  if (authState === 'checking') {
+    return <StatusScreen status="connecting" onRetry={backend.restart} />
+  }
+
+  if (authState === 'need_login') {
+    return <LoginGate onAuthenticated={() => setAuthState('ok')} />
+  }
+
+  const isChat = location.pathname === '/'
+  const showSessions = isChat && !sessionsCollapsed
+
+  return (
+    <div className="flex h-screen overflow-hidden bg-base text-content">
+      {onboardingOpen && <OnboardingWizard onDone={handleLangChange} />}
+      <NavRail onLangChange={handleLangChange} />
+
+      {showSessions && <SessionList />}
+
+      <div className="flex-1 flex flex-col min-w-0 h-screen">
+        {/* Top titlebar strip — drag region + Windows controls */}
+        <header className="h-[44px] flex items-center gap-1 px-2 flex-shrink-0 titlebar-drag bg-base border-b border-default">
+          {isChat && sessionsCollapsed && (
+            <button
+              onClick={toggleSessions}
+              title={t('session_history')}
+              // Keep aligned with the SessionList history button: only nudge
+              // right of the macOS traffic lights when the nav rail is collapsed
+              // (otherwise the lights stay within the rail and don't overlap).
+              className={`titlebar-no-drag inline-flex items-center justify-center w-7 h-7 rounded-btn text-content-tertiary hover:text-content hover:bg-surface-2 cursor-pointer transition-colors ${isMac ? 'mt-1' : ''} ${isMac && navCollapsed ? 'ml-2' : ''}`}
+            >
+              <History size={16} />
+            </button>
+          )}
+          <div className="flex-1 min-w-0" />
+          {isWin && <WindowControls />}
+        </header>
+
+        {/* Content */}
+        <div className="flex-1 flex flex-col min-h-0 overflow-hidden bg-base">
+          <Routes>
+            <Route path="/" element={<ChatPage baseUrl={backend.baseUrl} />} />
+            <Route path="/knowledge" element={<KnowledgePage baseUrl={backend.baseUrl} />} />
+            <Route path="/memory" element={<MemoryPage baseUrl={backend.baseUrl} />} />
+            <Route path="/skills" element={<SkillsPage baseUrl={backend.baseUrl} />} />
+            <Route path="/channels" element={<ChannelsPage baseUrl={backend.baseUrl} />} />
+            <Route path="/tasks" element={<TasksPage baseUrl={backend.baseUrl} />} />
+            <Route path="/settings" element={<SettingsPage baseUrl={backend.baseUrl} onLangChange={handleLangChange} />} />
+            {/* Legacy /models route now lives as a tab inside settings */}
+            <Route path="/models" element={<SettingsPage baseUrl={backend.baseUrl} onLangChange={handleLangChange} />} />
+            <Route path="/logs" element={<LogsPage baseUrl={backend.baseUrl} />} />
+          </Routes>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+export default App
diff --git a/desktop/src/renderer/src/api/client.ts b/desktop/src/renderer/src/api/client.ts
new file mode 100644
index 0000000..70848f0
--- /dev/null
+++ b/desktop/src/renderer/src/api/client.ts
@@ -0,0 +1,457 @@
+import type {
+  ConfigData,
+  ChannelInfo,
+  ChannelAction,
+  SkillInfo,
+  ToolInfo,
+  MemoryItem,
+  MemoryCategory,
+  MemoryPage,
+  SchedulerTask,
+  Attachment,
+  SessionsPage,
+  HistoryPage,
+  ModelsData,
+  ModelsAction,
+  KnowledgeList,
+  KnowledgeGraph,
+  KnowledgeAction,
+  KnowledgeImportPayload,
+} from '../types'
+
+interface ApiResult {
+  status: string
+  message?: string
+}
+
+const AUTH_TOKEN_KEY = 'cow_auth_token'
+
+class ApiClient {
+  private baseUrl = 'http://127.0.0.1:9876'
+  // Bearer token for web_password-protected backends. The desktop renderer
+  // runs from a file:// origin, where cross-origin cookies to http://127.0.0.1
+  // aren't sent reliably, so we authenticate via an Authorization header
+  // instead. Persisted in localStorage so it survives reloads.
+  private authToken: string | null =
+    typeof localStorage !== 'undefined' ? localStorage.getItem(AUTH_TOKEN_KEY) : null
+
+  setBaseUrl(url: string) {
+    this.baseUrl = url
+  }
+
+  getBaseUrl() {
+    return this.baseUrl
+  }
+
+  setAuthToken(token: string | null) {
+    this.authToken = token
+    try {
+      if (token) localStorage.setItem(AUTH_TOKEN_KEY, token)
+      else localStorage.removeItem(AUTH_TOKEN_KEY)
+    } catch {
+      // localStorage may be unavailable; in-memory token still works this session
+    }
+  }
+
+  private async request<T>(path: string, options?: RequestInit): Promise<T> {
+    const res = await fetch(`${this.baseUrl}${path}`, {
+      ...options,
+      // Cookies still work for browser access; the desktop app relies on the
+      // Authorization header below.
+      credentials: 'include',
+      headers: {
+        'Content-Type': 'application/json',
+        ...(this.authToken ? { Authorization: `Bearer ${this.authToken}` } : {}),
+        ...options?.headers,
+      },
+    })
+    if (!res.ok) {
+      throw new Error(`HTTP ${res.status}: ${res.statusText}`)
+    }
+    return res.json()
+  }
+
+  // ---------------------------------------------------------
+  // Chat / messages
+  // ---------------------------------------------------------
+
+  async sendMessage(
+    sessionId: string,
+    message: string,
+    opts?: { stream?: boolean; attachments?: Attachment[]; isVoice?: boolean; lang?: string }
+  ): Promise<{ status: string; request_id: string; stream: boolean; inline_reply?: string }> {
+    return this.request('/message', {
+      method: 'POST',
+      body: JSON.stringify({
+        session_id: sessionId,
+        message,
+        stream: opts?.stream ?? true,
+        attachments: opts?.attachments,
+        is_voice: opts?.isVoice ?? false,
+        lang: opts?.lang,
+      }),
+    })
+  }
+
+  async poll(sessionId: string): Promise<{
+    status: string
+    has_content: boolean
+    content?: string
+    request_id?: string
+    timestamp?: number
+  }> {
+    return this.request('/poll', {
+      method: 'POST',
+      body: JSON.stringify({ session_id: sessionId }),
+    })
+  }
+
+  async cancel(opts: { requestId?: string; sessionId?: string; lang?: string }): Promise<{ status: string; cancelled: number }> {
+    return this.request('/cancel', {
+      method: 'POST',
+      body: JSON.stringify({ request_id: opts.requestId, session_id: opts.sessionId, lang: opts.lang }),
+    })
+  }
+
+  // EventSource can't set an Authorization header, so append the auth token as
+  // a query param for SSE endpoints (the backend accepts it there).
+  private withToken(url: string): string {
+    if (!this.authToken) return url
+    const sep = url.includes('?') ? '&' : '?'
+    return `${url}${sep}token=${encodeURIComponent(this.authToken)}`
+  }
+
+  createSSEStream(requestId: string): EventSource {
+    return new EventSource(this.withToken(`${this.baseUrl}/stream?request_id=${requestId}`))
+  }
+
+  async deleteMessage(opts: {
+    sessionId: string
+    userSeq: number
+    deleteUser?: boolean
+    cascade?: boolean
+  }): Promise<{ status: string; deleted: number }> {
+    return this.request('/api/messages/delete', {
+      method: 'POST',
+      body: JSON.stringify({
+        session_id: opts.sessionId,
+        user_seq: opts.userSeq,
+        delete_user: opts.deleteUser ?? true,
+        cascade: opts.cascade ?? false,
+      }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Upload / files
+  // ---------------------------------------------------------
+
+  async uploadFile(file: File, sessionId?: string): Promise<{
+    status: string
+    file_path: string
+    file_name: string
+    file_type: string
+    preview_url: string
+  }> {
+    const formData = new FormData()
+    formData.append('file', file)
+    if (sessionId) formData.append('session_id', sessionId)
+    const res = await fetch(`${this.baseUrl}/upload`, {
+      method: 'POST',
+      body: formData,
+      credentials: 'include',
+    })
+    return res.json()
+  }
+
+  getFileUrl(previewUrl: string): string {
+    if (/^https?:\/\//.test(previewUrl)) return previewUrl
+    // Served via <img src>, which can't set headers — carry the token in the
+    // query so protected file endpoints load under web_password.
+    return this.withToken(`${this.baseUrl}${previewUrl}`)
+  }
+
+  getServeFileUrl(absPath: string): string {
+    return this.withToken(`${this.baseUrl}/api/file?path=${encodeURIComponent(absPath)}`)
+  }
+
+  // ---------------------------------------------------------
+  // Sessions
+  // ---------------------------------------------------------
+
+  async getSessions(page = 1, pageSize = 50): Promise<SessionsPage> {
+    return this.request<{ status: string } & SessionsPage>(`/api/sessions?page=${page}&page_size=${pageSize}`)
+  }
+
+  async deleteSession(sessionId: string): Promise<ApiResult> {
+    return this.request(`/api/sessions/${encodeURIComponent(sessionId)}`, { method: 'DELETE' })
+  }
+
+  async renameSession(sessionId: string, title: string): Promise<ApiResult> {
+    return this.request(`/api/sessions/${encodeURIComponent(sessionId)}`, {
+      method: 'PUT',
+      body: JSON.stringify({ title }),
+    })
+  }
+
+  async generateSessionTitle(sessionId: string, userMessage: string, assistantReply?: string): Promise<{ status: string; title: string }> {
+    return this.request(`/api/sessions/${encodeURIComponent(sessionId)}/generate_title`, {
+      method: 'POST',
+      body: JSON.stringify({ user_message: userMessage, assistant_reply: assistantReply }),
+    })
+  }
+
+  async clearContext(sessionId: string): Promise<{ status: string; context_start_seq: number }> {
+    return this.request(`/api/sessions/${encodeURIComponent(sessionId)}/clear_context`, { method: 'POST' })
+  }
+
+  async getHistory(sessionId: string, page = 1, pageSize = 20): Promise<HistoryPage> {
+    return this.request<{ status: string } & HistoryPage>(
+      `/api/history?session_id=${encodeURIComponent(sessionId)}&page=${page}&page_size=${pageSize}`
+    )
+  }
+
+  // ---------------------------------------------------------
+  // Config
+  // ---------------------------------------------------------
+
+  async getConfig(): Promise<ConfigData> {
+    return this.request<{ status: string } & ConfigData>('/config')
+  }
+
+  async updateConfig(updates: Record<string, unknown>): Promise<{ status: string; applied: Record<string, unknown> }> {
+    return this.request('/config', {
+      method: 'POST',
+      body: JSON.stringify({ updates }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Models console
+  // ---------------------------------------------------------
+
+  async getModels(): Promise<ModelsData> {
+    return this.request<{ status: string } & ModelsData>('/api/models')
+  }
+
+  async modelsAction(action: ModelsAction): Promise<Record<string, unknown> & { status: string }> {
+    return this.request('/api/models', {
+      method: 'POST',
+      body: JSON.stringify(action),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Channels
+  // ---------------------------------------------------------
+
+  async getChannels(): Promise<ChannelInfo[]> {
+    const data = await this.request<{ status: string; channels: ChannelInfo[] }>('/api/channels')
+    return data.channels
+  }
+
+  async channelAction(
+    action: ChannelAction,
+    channel: string,
+    config?: Record<string, unknown>
+  ): Promise<Record<string, unknown> & { status: string }> {
+    return this.request('/api/channels', {
+      method: 'POST',
+      body: JSON.stringify({ action, channel, config }),
+    })
+  }
+
+  // Weixin QR login
+  async getWeixinQr(): Promise<{ status: string; qrcode_url?: string; qr_image?: string; source?: string; message?: string }> {
+    return this.request('/api/weixin/qrlogin')
+  }
+
+  async weixinQrAction(action: 'poll' | 'refresh'): Promise<Record<string, unknown> & { status: string }> {
+    return this.request('/api/weixin/qrlogin', {
+      method: 'POST',
+      body: JSON.stringify({ action }),
+    })
+  }
+
+  // Feishu one-click register
+  async getFeishuRegister(): Promise<{ status: string; qrcode_url?: string; qr_image?: string; expire_in?: number; message?: string }> {
+    return this.request('/api/feishu/register')
+  }
+
+  async feishuRegisterPoll(): Promise<Record<string, unknown> & { status: string }> {
+    return this.request('/api/feishu/register', {
+      method: 'POST',
+      body: JSON.stringify({ action: 'poll' }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Tools & skills
+  // ---------------------------------------------------------
+
+  async getTools(): Promise<ToolInfo[]> {
+    const data = await this.request<{ status: string; tools: ToolInfo[] }>('/api/tools')
+    return data.tools
+  }
+
+  async getSkills(): Promise<SkillInfo[]> {
+    const data = await this.request<{ status: string; skills: SkillInfo[] }>('/api/skills')
+    return data.skills
+  }
+
+  async toggleSkill(name: string, action: 'open' | 'close'): Promise<ApiResult> {
+    return this.request('/api/skills', {
+      method: 'POST',
+      body: JSON.stringify({ action, name }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Memory
+  // ---------------------------------------------------------
+
+  async getMemoryList(page = 1, pageSize = 20, category: MemoryCategory = 'memory'): Promise<MemoryPage> {
+    return this.request<{ status: string } & MemoryPage>(
+      `/api/memory?page=${page}&page_size=${pageSize}&category=${category}`
+    )
+  }
+
+  async getMemoryContent(filename: string, category: MemoryCategory = 'memory'): Promise<string> {
+    const data = await this.request<{ status: string; content: string }>(
+      `/api/memory/content?filename=${encodeURIComponent(filename)}&category=${category}`
+    )
+    return data.content
+  }
+
+  // ---------------------------------------------------------
+  // Knowledge
+  // ---------------------------------------------------------
+
+  async getKnowledgeList(): Promise<KnowledgeList> {
+    return this.request<{ status: string } & KnowledgeList>('/api/knowledge/list')
+  }
+
+  async readKnowledge(path: string): Promise<{ status: string; content: string; path: string }> {
+    return this.request(`/api/knowledge/read?path=${encodeURIComponent(path)}`)
+  }
+
+  async getKnowledgeGraph(): Promise<KnowledgeGraph> {
+    return this.request<KnowledgeGraph>('/api/knowledge/graph')
+  }
+
+  async knowledgeAction(req: KnowledgeAction): Promise<Record<string, unknown> & { status: string }> {
+    return this.request('/api/knowledge/action', {
+      method: 'POST',
+      body: JSON.stringify(req),
+    })
+  }
+
+  // Bulk import: upload .md/.txt files into a target category (multipart).
+  async importKnowledge(
+    files: File[],
+    targetCategory: string
+  ): Promise<{ status: string; message?: string; payload?: KnowledgeImportPayload }> {
+    const formData = new FormData()
+    formData.append('target_category', targetCategory)
+    formData.append('conflict_strategy', 'rename')
+    files.forEach((file) => formData.append('files', file, file.name))
+    const res = await fetch(`${this.baseUrl}/api/knowledge/import`, {
+      method: 'POST',
+      body: formData,
+      credentials: 'include',
+    })
+    return res.json()
+  }
+
+  // ---------------------------------------------------------
+  // Scheduler
+  // ---------------------------------------------------------
+
+  async getSchedulerTasks(): Promise<SchedulerTask[]> {
+    const data = await this.request<{ status: string; tasks: SchedulerTask[] }>('/api/scheduler')
+    return data.tasks
+  }
+
+  async toggleTask(taskId: string, enabled: boolean): Promise<{ status: string; task: SchedulerTask }> {
+    return this.request('/api/scheduler/toggle', {
+      method: 'POST',
+      body: JSON.stringify({ task_id: taskId, enabled }),
+    })
+  }
+
+  async updateTask(taskId: string, updates: Partial<Pick<SchedulerTask, 'name' | 'enabled' | 'schedule' | 'action'>>): Promise<{ status: string; task: SchedulerTask }> {
+    return this.request('/api/scheduler/update', {
+      method: 'POST',
+      body: JSON.stringify({ task_id: taskId, ...updates }),
+    })
+  }
+
+  async deleteTask(taskId: string): Promise<ApiResult> {
+    return this.request('/api/scheduler/delete', {
+      method: 'POST',
+      body: JSON.stringify({ task_id: taskId }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Voice
+  // ---------------------------------------------------------
+
+  async voiceAsr(audio: File | Blob): Promise<{ status: string; text?: string; audio_url?: string; message?: string }> {
+    const formData = new FormData()
+    formData.append('file', audio, 'recording.webm')
+    const res = await fetch(`${this.baseUrl}/api/voice/asr`, {
+      method: 'POST',
+      body: formData,
+      credentials: 'include',
+    })
+    return res.json()
+  }
+
+  async voiceTts(text: string, sessionId?: string): Promise<{ status: string; audio_url?: string; message?: string }> {
+    return this.request('/api/voice/tts', {
+      method: 'POST',
+      body: JSON.stringify({ text, session_id: sessionId }),
+    })
+  }
+
+  // ---------------------------------------------------------
+  // Logs / version
+  // ---------------------------------------------------------
+
+  createLogStream(): EventSource {
+    return new EventSource(this.withToken(`${this.baseUrl}/api/logs`))
+  }
+
+  async getVersion(): Promise<string> {
+    const data = await this.request<{ version: string }>('/api/version')
+    return data.version
+  }
+
+  // ---------------------------------------------------------
+  // Auth (web_password) — placeholder for future use
+  // ---------------------------------------------------------
+
+  async authCheck(): Promise<{ status: string; auth_required: boolean; authenticated?: boolean }> {
+    return this.request('/auth/check')
+  }
+
+  async authLogin(password: string): Promise<ApiResult & { token?: string }> {
+    const res = await this.request<ApiResult & { token?: string }>('/auth/login', {
+      method: 'POST',
+      body: JSON.stringify({ password }),
+    })
+    if (res.status === 'success' && res.token) {
+      this.setAuthToken(res.token)
+    }
+    return res
+  }
+
+  async authLogout(): Promise<ApiResult> {
+    this.setAuthToken(null)
+    return this.request('/auth/logout', { method: 'POST' })
+  }
+}
+
+export const apiClient = new ApiClient()
+export default apiClient
diff --git a/desktop/src/renderer/src/assets/logo.png b/desktop/src/renderer/src/assets/logo.png
new file mode 100644
index 0000000..402d75d
Binary files /dev/null and b/desktop/src/renderer/src/assets/logo.png differ
diff --git a/desktop/src/renderer/src/components/ChatInput.tsx b/desktop/src/renderer/src/components/ChatInput.tsx
new file mode 100644
index 0000000..49339c5
--- /dev/null
+++ b/desktop/src/renderer/src/components/ChatInput.tsx
@@ -0,0 +1,398 @@
+import React, { useState, useRef, useCallback, useEffect, forwardRef, useImperativeHandle } from 'react'
+import { Plus, Paperclip, Square, X, File as FileIcon, Loader2, Trash2 } from 'lucide-react'
+import { t } from '../i18n'
+import type { Attachment } from '../types'
+import apiClient from '../api/client'
+import { PaperPlaneIcon } from './icons'
+
+export type ChatInputHandle = (text: string, attachments: Attachment[]) => void
+
+interface SlashCommand {
+  cmd: string
+  desc: string
+  // 'new'/'clear' run a local action; 'send' (default) is a completion that
+  // gets sent to the backend as a normal message (handled by command plugins).
+  action?: 'new' | 'clear'
+}
+
+interface ChatInputProps {
+  onSend: (message: string, attachments: Attachment[]) => void
+  onNewChat: () => void
+  onStop: () => void
+  onClearContext: () => void
+  isStreaming: boolean
+  sessionId: string
+}
+
+const ChatInput = forwardRef<ChatInputHandle, ChatInputProps>(function ChatInput(
+  { onSend, onNewChat, onStop, onClearContext, isStreaming, sessionId },
+  ref
+) {
+  const [text, setText] = useState('')
+  const [attachments, setAttachments] = useState<Attachment[]>([])
+  const [uploading, setUploading] = useState(false)
+  const [dragOver, setDragOver] = useState(false)
+  const [slashOpen, setSlashOpen] = useState(false)
+  const [slashIndex, setSlashIndex] = useState(0)
+  const composingRef = useRef(false)
+  const textareaRef = useRef<HTMLTextAreaElement>(null)
+  const fileInputRef = useRef<HTMLInputElement>(null)
+
+  // Local actions ('new'/'clear') plus completion commands handled by backend
+  // command plugins (cow_cli/godcmd). Commands ending with a space expect an
+  // argument, so selecting them keeps focus in the input instead of sending.
+  const slashCommands: SlashCommand[] = [
+    { cmd: '/new', desc: t('slash_new'), action: 'new' },
+    { cmd: '/clear', desc: t('slash_clear'), action: 'clear' },
+    { cmd: '/help', desc: t('slash_help') },
+    { cmd: '/status', desc: t('slash_status') },
+    { cmd: '/context', desc: t('slash_context') },
+    { cmd: '/skill list', desc: t('slash_skill_list') },
+    { cmd: '/skill search ', desc: t('slash_skill_search') },
+    { cmd: '/skill install ', desc: t('slash_skill_install') },
+    { cmd: '/memory dream ', desc: t('slash_memory_dream') },
+    { cmd: '/knowledge', desc: t('slash_knowledge') },
+    { cmd: '/knowledge list', desc: t('slash_knowledge_list') },
+    { cmd: '/config', desc: t('slash_config') },
+    { cmd: '/cancel', desc: t('slash_cancel') },
+    { cmd: '/logs', desc: t('slash_logs') },
+    { cmd: '/version', desc: t('slash_version') },
+  ]
+  const filtered = slashCommands.filter((c) => c.cmd.startsWith(text.trim().toLowerCase()))
+
+  // Resize the textarea to fit its content (single line = 42px, capped at
+  // 180px). Keep overflow hidden until we hit the cap, so an empty/short input
+  // never shows a scrollbar (matches the web console behavior).
+  const autoSize = (el: HTMLTextAreaElement | null) => {
+    if (!el) return
+    el.style.height = '42px'
+    const h = Math.min(el.scrollHeight, 180)
+    el.style.height = h + 'px'
+    el.style.overflowY = el.scrollHeight > 180 ? 'auto' : 'hidden'
+  }
+
+  const resetHeight = () => {
+    const el = textareaRef.current
+    if (!el) return
+    el.style.height = '42px'
+    el.style.overflowY = 'hidden'
+  }
+
+  // Sync the height once on mount so the very first render matches the 42px
+  // single-line height instead of the browser's default textarea size.
+  useEffect(() => {
+    autoSize(textareaRef.current)
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [])
+
+  // Allow the parent to load a draft (e.g. when editing a past user message).
+  useImperativeHandle(ref, () => (draft: string, atts: Attachment[]) => {
+    setText(draft)
+    setAttachments(atts)
+    requestAnimationFrame(() => {
+      const el = textareaRef.current
+      if (el) {
+        el.focus()
+        autoSize(el)
+      }
+    })
+  })
+
+  const runSlash = (c: SlashCommand) => {
+    setSlashOpen(false)
+    if (c.action === 'new') {
+      setText('')
+      resetHeight()
+      onNewChat()
+      return
+    }
+    if (c.action === 'clear') {
+      setText('')
+      resetHeight()
+      onClearContext()
+      return
+    }
+    // Completion command. If it expects an argument (trailing space), keep it
+    // in the input so the user can type the argument; otherwise send it now.
+    const needsArg = c.cmd.endsWith(' ')
+    if (needsArg) {
+      setText(c.cmd)
+      requestAnimationFrame(() => textareaRef.current?.focus())
+    } else {
+      onSend(c.cmd.trim(), [])
+      setText('')
+      resetHeight()
+    }
+  }
+
+  const handleSubmit = useCallback(() => {
+    const trimmed = text.trim()
+    if (!trimmed && attachments.length === 0) return
+    if (isStreaming) return
+    onSend(trimmed, attachments)
+    setText('')
+    setAttachments([])
+    setSlashOpen(false)
+    resetHeight()
+  }, [text, attachments, isStreaming, onSend])
+
+  const handleKeyDown = (e: React.KeyboardEvent) => {
+    // Slash menu navigation
+    if (slashOpen && filtered.length > 0) {
+      if (e.key === 'ArrowDown') {
+        e.preventDefault()
+        setSlashIndex((i) => (i + 1) % filtered.length)
+        return
+      }
+      if (e.key === 'ArrowUp') {
+        e.preventDefault()
+        setSlashIndex((i) => (i - 1 + filtered.length) % filtered.length)
+        return
+      }
+      if (e.key === 'Enter' && !e.shiftKey) {
+        e.preventDefault()
+        runSlash(filtered[slashIndex])
+        return
+      }
+      if (e.key === 'Escape') {
+        setSlashOpen(false)
+        return
+      }
+    }
+    // Don't submit while IME is composing (Chinese input)
+    if (e.key === 'Enter' && !e.shiftKey && !composingRef.current) {
+      e.preventDefault()
+      handleSubmit()
+    }
+  }
+
+  const handleTextChange = (e: React.ChangeEvent<HTMLTextAreaElement>) => {
+    const v = e.target.value
+    setText(v)
+    autoSize(e.target)
+    // open slash menu when the input starts with "/" and has no space
+    setSlashOpen(v.startsWith('/') && !v.includes(' '))
+    setSlashIndex(0)
+  }
+
+  const uploadFiles = async (files: File[]) => {
+    if (!files.length) return
+    setUploading(true)
+    try {
+      for (const file of files) {
+        const result = await apiClient.uploadFile(file, sessionId)
+        if (result.status === 'success') {
+          setAttachments((prev) => [
+            ...prev,
+            {
+              file_path: result.file_path,
+              file_name: result.file_name,
+              file_type: result.file_type as Attachment['file_type'],
+              preview_url: result.preview_url,
+            },
+          ])
+        }
+      }
+    } catch (err) {
+      console.error('Upload failed:', err)
+    } finally {
+      setUploading(false)
+    }
+  }
+
+  const handleFileSelect = async (e: React.ChangeEvent<HTMLInputElement>) => {
+    const files = e.target.files
+    if (files) await uploadFiles(Array.from(files))
+    if (fileInputRef.current) fileInputRef.current.value = ''
+  }
+
+  const handleDrop = (e: React.DragEvent) => {
+    e.preventDefault()
+    setDragOver(false)
+    const files = Array.from(e.dataTransfer.files || [])
+    if (files.length) uploadFiles(files)
+  }
+
+  const handlePaste = (e: React.ClipboardEvent) => {
+    const items = e.clipboardData?.items
+    if (!items) return
+    const files: File[] = []
+    for (const item of Array.from(items)) {
+      if (item.kind === 'file') {
+        const f = item.getAsFile()
+        if (f) files.push(f)
+      }
+    }
+    if (files.length) {
+      e.preventDefault()
+      uploadFiles(files)
+    }
+  }
+
+  const removeAttachment = (index: number) => {
+    setAttachments((prev) => prev.filter((_, i) => i !== index))
+  }
+
+  // keep slash index in range
+  useEffect(() => {
+    if (slashIndex >= filtered.length) setSlashIndex(0)
+  }, [filtered.length, slashIndex])
+
+  const canSend = !isStreaming && (!!text.trim() || attachments.length > 0)
+
+  return (
+    <div className="flex-shrink-0 border-t border-default bg-surface px-4 py-3">
+      <div
+        className={`max-w-3xl mx-auto relative rounded-2xl transition-all ${
+          dragOver ? 'ring-2 ring-accent ring-offset-2 ring-offset-surface' : ''
+        }`}
+        onDragOver={(e) => {
+          e.preventDefault()
+          setDragOver(true)
+        }}
+        onDragLeave={() => setDragOver(false)}
+        onDrop={handleDrop}
+      >
+        {dragOver && (
+          <div className="absolute inset-0 z-20 flex items-center justify-center rounded-2xl bg-accent-soft text-accent text-sm font-medium pointer-events-none">
+            {t('input_placeholder')}
+          </div>
+        )}
+
+        {/* Slash command menu */}
+        {slashOpen && filtered.length > 0 && (
+          <div className="absolute bottom-full left-0 right-0 mb-1.5 max-h-80 overflow-y-auto rounded-xl border border-default bg-elevated shadow-xl z-30 p-1.5">
+            <div className="px-2.5 pt-1 pb-1.5 text-[11px] font-semibold uppercase tracking-wider text-content-tertiary">
+              {t('slash_menu_title')}
+            </div>
+            {filtered.map((c, i) => (
+              <button
+                key={c.cmd}
+                onMouseEnter={() => setSlashIndex(i)}
+                onClick={() => runSlash(c)}
+                className={`w-full flex items-center justify-between gap-3 px-2.5 py-2 rounded-lg text-left cursor-pointer transition-colors ${
+                  i === slashIndex ? 'bg-accent-soft' : 'hover:bg-surface-2'
+                }`}
+              >
+                <span
+                  className={`text-[13px] font-medium font-mono whitespace-nowrap ${
+                    i === slashIndex ? 'text-accent' : 'text-content-secondary'
+                  }`}
+                >
+                  {c.cmd}
+                </span>
+                <span className="text-xs text-content-tertiary whitespace-nowrap truncate">{c.desc}</span>
+              </button>
+            ))}
+          </div>
+        )}
+
+        {/* Attachment preview */}
+        {attachments.length > 0 && (
+          <div className="flex flex-wrap gap-2 mb-2">
+            {attachments.map((att, i) => (
+              <div key={i} className="relative">
+                {att.file_type === 'image' && att.preview_url ? (
+                  <div className="relative">
+                    <img
+                      src={apiClient.getFileUrl(att.preview_url)}
+                      alt={att.file_name}
+                      className="w-16 h-16 rounded-lg object-cover border border-default"
+                    />
+                    <button
+                      onClick={() => removeAttachment(i)}
+                      className="absolute -top-1 -right-1 w-[18px] h-[18px] rounded-full bg-danger text-white flex items-center justify-center cursor-pointer"
+                    >
+                      <X size={10} />
+                    </button>
+                  </div>
+                ) : (
+                  <div className="flex items-center gap-1.5 px-2.5 py-1.5 bg-inset border border-default rounded-lg text-xs text-content-secondary max-w-[180px] relative pr-7">
+                    <FileIcon size={12} />
+                    <span className="truncate">{att.file_name}</span>
+                    <button
+                      onClick={() => removeAttachment(i)}
+                      className="absolute -top-1 -right-1 w-[18px] h-[18px] rounded-full bg-danger text-white flex items-center justify-center cursor-pointer"
+                    >
+                      <X size={10} />
+                    </button>
+                  </div>
+                )}
+              </div>
+            ))}
+          </div>
+        )}
+
+        <div className="flex items-end gap-2">
+          <div className="flex items-center flex-shrink-0 gap-0.5 pb-0.5">
+            <button
+              onClick={onNewChat}
+              className="w-9 h-9 flex items-center justify-center rounded-btn text-content-secondary hover:text-accent hover:bg-accent-soft cursor-pointer transition-colors"
+              title={t('session_new')}
+            >
+              <Plus size={18} />
+            </button>
+            <button
+              onClick={() => fileInputRef.current?.click()}
+              disabled={uploading}
+              className="w-9 h-9 flex items-center justify-center rounded-btn text-content-secondary hover:text-accent hover:bg-accent-soft cursor-pointer transition-colors disabled:opacity-50"
+              title={t('chat_attach')}
+            >
+              {uploading ? <Loader2 size={18} className="animate-spin" /> : <Paperclip size={18} />}
+            </button>
+            <button
+              onClick={onClearContext}
+              className="w-9 h-9 flex items-center justify-center rounded-btn text-content-secondary hover:text-danger hover:bg-danger-soft cursor-pointer transition-colors"
+              title={t('chat_clear_context')}
+            >
+              <Trash2 size={18} />
+            </button>
+          </div>
+          <input
+            ref={fileInputRef}
+            type="file"
+            className="hidden"
+            multiple
+            onChange={handleFileSelect}
+            accept="image/*,.pdf,.doc,.docx,.xls,.xlsx,.ppt,.pptx,.txt,.csv,.json,.xml,.zip,.py,.js,.ts,.java,.c,.cpp,.go,.rs,.md"
+          />
+
+          <textarea
+            ref={textareaRef}
+            id="chat-input"
+            value={text}
+            onChange={handleTextChange}
+            onKeyDown={handleKeyDown}
+            onPaste={handlePaste}
+            onCompositionStart={() => (composingRef.current = true)}
+            onCompositionEnd={() => (composingRef.current = false)}
+            placeholder={t('input_placeholder')}
+            rows={1}
+            className="flex-1 min-w-0 px-4 py-[10px] rounded-xl border border-strong bg-inset text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent text-sm leading-relaxed transition-colors resize-none overflow-y-hidden"
+          />
+
+          {isStreaming ? (
+            <button
+              onClick={onStop}
+              className="flex-shrink-0 w-10 h-10 flex items-center justify-center rounded-btn bg-surface-2 text-content hover:bg-inset cursor-pointer transition-colors"
+              title={t('msg_stop')}
+            >
+              <Square size={15} className="fill-current" />
+            </button>
+          ) : (
+            <button
+              onClick={handleSubmit}
+              disabled={!canSend}
+              className="flex-shrink-0 w-[42px] h-[42px] flex items-center justify-center rounded-btn bg-accent text-white hover:bg-accent-hover disabled:bg-surface-2 disabled:text-content-disabled disabled:cursor-not-allowed cursor-pointer transition-none [&_*]:transition-none"
+              title={t('chat_send')}
+            >
+              <PaperPlaneIcon size={15} />
+            </button>
+          )}
+        </div>
+      </div>
+    </div>
+  )
+})
+
+export default ChatInput
diff --git a/desktop/src/renderer/src/components/KnowledgeGraph.tsx b/desktop/src/renderer/src/components/KnowledgeGraph.tsx
new file mode 100644
index 0000000..cd508c5
--- /dev/null
+++ b/desktop/src/renderer/src/components/KnowledgeGraph.tsx
@@ -0,0 +1,407 @@
+import React, { useEffect, useMemo, useRef, useState } from 'react'
+import type { KnowledgeGraph as KnowledgeGraphData } from '../types'
+
+interface SimNode {
+  id: string
+  label: string
+  category: string
+  x: number
+  y: number
+  vx: number
+  vy: number
+  fx: number | null
+  fy: number | null
+  degree: number
+}
+
+interface KnowledgeGraphProps {
+  data: KnowledgeGraphData
+  onSelect: (id: string, label: string) => void
+}
+
+// d3.schemeTableau10 — keep the web client's palette for visual parity.
+const TABLEAU10 = [
+  '#4e79a7',
+  '#f28e2c',
+  '#e15759',
+  '#76b7b2',
+  '#59a14f',
+  '#edc949',
+  '#af7aa1',
+  '#ff9da7',
+  '#9c755f',
+  '#bab0ab',
+]
+
+const nodeRadius = (degree: number) => Math.max(4, Math.min(12, 4 + degree * 1.4))
+
+// A dependency-free force-directed graph with wheel zoom, canvas pan and node
+// drag. The physics loop writes positions DIRECTLY to the DOM (like d3) instead
+// of calling setState per frame, so React never re-renders during the
+// simulation — this is what keeps it from flickering.
+const KnowledgeGraph: React.FC<KnowledgeGraphProps> = ({ data, onSelect }) => {
+  const wrapRef = useRef<HTMLDivElement>(null)
+  const svgRef = useRef<SVGSVGElement>(null)
+  const sizeRef = useRef({ w: 800, h: 560 })
+  const [hover, setHover] = useState<string | null>(null)
+  // Bumping this re-arms the physics loop (used while dragging) without
+  // rebuilding the model, preserving current node positions.
+  const [warmTick, setWarmTick] = useState(0)
+
+  // View transform (pan + zoom).
+  const viewRef = useRef({ k: 1, x: 0, y: 0 })
+
+  // Build the immutable model once per data change.
+  const model = useMemo(() => {
+    const degree = new Map<string, number>()
+    data.links.forEach((l) => {
+      degree.set(l.source, (degree.get(l.source) || 0) + 1)
+      degree.set(l.target, (degree.get(l.target) || 0) + 1)
+    })
+    const categories = Array.from(new Set(data.nodes.map((n) => n.category || 'default')))
+    const colorOf = (cat: string) => TABLEAU10[categories.indexOf(cat) % TABLEAU10.length]
+
+    const n = data.nodes.length || 1
+    const { w, h } = sizeRef.current
+    const cx = w / 2
+    const cy = h / 2
+    const nodes: SimNode[] = data.nodes.map((nd, i) => {
+      const angle = (i / n) * Math.PI * 2
+      const radius = Math.min(w, h) * 0.32
+      return {
+        id: nd.id,
+        label: nd.label,
+        category: nd.category || 'default',
+        x: cx + Math.cos(angle) * radius,
+        y: cy + Math.sin(angle) * radius,
+        vx: 0,
+        vy: 0,
+        fx: null,
+        fy: null,
+        degree: degree.get(nd.id) || 0,
+      }
+    })
+    const valid = new Set(nodes.map((x) => x.id))
+    const byId = new Map(nodes.map((x) => [x.id, x]))
+    const links = data.links
+      .filter((l) => valid.has(l.source) && valid.has(l.target))
+      .map((l, i) => ({ key: i, a: byId.get(l.source)!, b: byId.get(l.target)! }))
+    const adjacency = new Map<string, Set<string>>()
+    data.links.forEach((l) => {
+      if (!valid.has(l.source) || !valid.has(l.target)) return
+      if (!adjacency.has(l.source)) adjacency.set(l.source, new Set())
+      if (!adjacency.has(l.target)) adjacency.set(l.target, new Set())
+      adjacency.get(l.source)!.add(l.target)
+      adjacency.get(l.target)!.add(l.source)
+    })
+    return { nodes, links, adjacency, categories, colorOf, byId }
+  }, [data])
+
+  // DOM refs for imperative position updates.
+  const rootRef = useRef<SVGGElement>(null)
+  const lineEls = useRef(new Map<number, SVGLineElement>())
+  const groupEls = useRef(new Map<string, SVGGElement>())
+
+  // Track container size in a ref; never triggers a re-render on its own.
+  useEffect(() => {
+    const el = wrapRef.current
+    if (!el) return
+    const apply = () => {
+      sizeRef.current = { w: el.clientWidth || 800, h: el.clientHeight || 560 }
+    }
+    apply()
+    const ro = new ResizeObserver(apply)
+    ro.observe(el)
+    return () => ro.disconnect()
+  }, [])
+
+  // Physics loop. Restarts only when the model (data) changes. Writes to DOM.
+  // Uses d3-style alpha cooling so it always settles and stops the rAF.
+  useEffect(() => {
+    const { nodes, links } = model
+    if (nodes.length === 0) return
+    let raf = 0
+    let alive = true
+    // Global cooling factor; decays toward 0 and scales how far nodes move.
+    let alpha = 1
+    const alphaDecay = 0.018
+    const alphaMin = 0.005
+
+    const paint = () => {
+      links.forEach(({ key, a, b }) => {
+        const el = lineEls.current.get(key)
+        if (!el) return
+        el.setAttribute('x1', String(a.x))
+        el.setAttribute('y1', String(a.y))
+        el.setAttribute('x2', String(b.x))
+        el.setAttribute('y2', String(b.y))
+      })
+      nodes.forEach((node) => {
+        const el = groupEls.current.get(node.id)
+        if (el) el.setAttribute('transform', `translate(${node.x},${node.y})`)
+      })
+    }
+
+    const step = () => {
+      if (!alive) return
+      const { w, h } = sizeRef.current
+      const cx = w / 2
+      const cy = h / 2
+      const repulsion = 9000
+      const springLen = 80
+      const spring = 0.04
+      const centering = 0.012
+      const dragging = nodes.some((node) => node.fx != null)
+
+      // Reset accumulated velocity each tick (alpha-scaled displacement) so the
+      // system can't accumulate energy and oscillate.
+      nodes.forEach((node) => {
+        node.vx = 0
+        node.vy = 0
+      })
+
+      // Repulsion + collision: nodes push apart, never overlap their radii.
+      for (let i = 0; i < nodes.length; i++) {
+        const a = nodes[i]
+        const ra = nodeRadius(a.degree)
+        for (let j = i + 1; j < nodes.length; j++) {
+          const b = nodes[j]
+          let dx = a.x - b.x
+          let dy = a.y - b.y
+          let d2 = dx * dx + dy * dy
+          if (d2 < 0.01) {
+            dx = Math.random() - 0.5
+            dy = Math.random() - 0.5
+            d2 = 0.01
+          }
+          let d = Math.sqrt(d2)
+          let f = repulsion / d2
+          // Hard collision: strongly separate if closer than combined radii.
+          const minDist = ra + nodeRadius(b.degree) + 14
+          if (d < minDist) f += (minDist - d) * 0.6
+          a.vx += (dx / d) * f
+          a.vy += (dy / d) * f
+          b.vx -= (dx / d) * f
+          b.vy -= (dy / d) * f
+        }
+      }
+      links.forEach(({ a, b }) => {
+        const dx = b.x - a.x
+        const dy = b.y - a.y
+        const d = Math.sqrt(dx * dx + dy * dy) || 1
+        const f = (d - springLen) * spring
+        a.vx += (dx / d) * f
+        a.vy += (dy / d) * f
+        b.vx -= (dx / d) * f
+        b.vy -= (dy / d) * f
+      })
+      // Weak centering so the whole graph stays in view without collapsing.
+      nodes.forEach((node) => {
+        node.vx += (cx - node.x) * centering
+        node.vy += (cy - node.y) * centering
+      })
+
+      // Apply alpha-scaled displacement; pinned nodes stay put. Cap per-tick
+      // movement so strong initial forces don't fling nodes off-screen.
+      const maxStep = 30
+      nodes.forEach((node) => {
+        if (node.fx != null) {
+          node.x = node.fx
+          node.y = node.fy as number
+          return
+        }
+        let dx = node.vx * alpha
+        let dy = node.vy * alpha
+        const m = Math.hypot(dx, dy)
+        if (m > maxStep) {
+          dx = (dx / m) * maxStep
+          dy = (dy / m) * maxStep
+        }
+        node.x += dx
+        node.y += dy
+      })
+
+      paint()
+      alpha += (0 - alpha) * alphaDecay
+      // Keep running while cooling, or while a node is being dragged.
+      if (alpha > alphaMin || dragging) {
+        raf = requestAnimationFrame(step)
+      }
+    }
+    raf = requestAnimationFrame(step)
+    return () => {
+      alive = false
+      cancelAnimationFrame(raf)
+    }
+    // warmTick re-arms the loop on demand (e.g. while dragging) without
+    // rebuilding the model, so positions are preserved.
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [model, warmTick])
+
+  // Apply the view transform imperatively (no re-render needed).
+  const applyView = () => {
+    const v = viewRef.current
+    if (rootRef.current) rootRef.current.setAttribute('transform', `translate(${v.x},${v.y}) scale(${v.k})`)
+  }
+  useEffect(applyView)
+
+  // Convert a pointer event to graph (pre-transform) coordinates.
+  const toGraph = (clientX: number, clientY: number) => {
+    const rect = svgRef.current!.getBoundingClientRect()
+    const v = viewRef.current
+    return { x: (clientX - rect.left - v.x) / v.k, y: (clientY - rect.top - v.y) / v.k }
+  }
+
+  // Wheel zoom centered on the cursor (matches d3.zoom scaleExtent [0.2, 5]).
+  const onWheel = (e: React.WheelEvent) => {
+    e.preventDefault()
+    const v = viewRef.current
+    const rect = svgRef.current!.getBoundingClientRect()
+    const px = e.clientX - rect.left
+    const py = e.clientY - rect.top
+    const factor = Math.exp(-e.deltaY * 0.0015)
+    const k = Math.min(5, Math.max(0.2, v.k * factor))
+    viewRef.current = { k, x: px - ((px - v.x) / v.k) * k, y: py - ((py - v.y) / v.k) * k }
+    applyView()
+  }
+
+  // Drag: on a node moves the node, on background pans the canvas.
+  const dragRef = useRef<
+    | { mode: 'node'; node: SimNode; moved: boolean }
+    | { mode: 'pan'; startX: number; startY: number; ox: number; oy: number }
+    | null
+  >(null)
+  const kick = () => setWarmTick((v) => v + 1)
+
+  const onPointerDownNode = (e: React.PointerEvent, node: SimNode) => {
+    e.stopPropagation()
+    ;(e.currentTarget as Element).setPointerCapture(e.pointerId)
+    const p = toGraph(e.clientX, e.clientY)
+    node.fx = p.x
+    node.fy = p.y
+    dragRef.current = { mode: 'node', node, moved: false }
+    kick()
+  }
+
+  const onPointerDownBg = (e: React.PointerEvent) => {
+    ;(e.currentTarget as Element).setPointerCapture(e.pointerId)
+    const v = viewRef.current
+    dragRef.current = { mode: 'pan', startX: e.clientX, startY: e.clientY, ox: v.x, oy: v.y }
+  }
+
+  const onPointerMove = (e: React.PointerEvent) => {
+    const drag = dragRef.current
+    if (!drag) return
+    if (drag.mode === 'node') {
+      const p = toGraph(e.clientX, e.clientY)
+      drag.node.fx = p.x
+      drag.node.fy = p.y
+      drag.moved = true
+      // Keep the loop warm for live dragging.
+      const el = groupEls.current.get(drag.node.id)
+      if (el) el.setAttribute('transform', `translate(${p.x},${p.y})`)
+    } else {
+      viewRef.current = { k: viewRef.current.k, x: drag.ox + (e.clientX - drag.startX), y: drag.oy + (e.clientY - drag.startY) }
+      applyView()
+    }
+  }
+
+  const onPointerUp = (e: React.PointerEvent, node?: SimNode) => {
+    const drag = dragRef.current
+    if (drag?.mode === 'node') {
+      drag.node.fx = null
+      drag.node.fy = null
+      if (node && !drag.moved) onSelect(node.id, node.label)
+      kick()
+    }
+    dragRef.current = null
+    try {
+      ;(e.target as Element).releasePointerCapture(e.pointerId)
+    } catch {
+      /* noop */
+    }
+  }
+
+  const { nodes, links, adjacency, categories, colorOf } = model
+  const { w, h } = sizeRef.current
+  const isDimmed = (id: string) => hover != null && hover !== id && !adjacency.get(hover)?.has(id)
+  const isLinkActive = (aId: string, bId: string) => hover === aId || hover === bId
+
+  return (
+    <div ref={wrapRef} className="w-full h-full relative overflow-hidden">
+      <svg
+        ref={svgRef}
+        width={w}
+        height={h}
+        className="select-none block cursor-grab active:cursor-grabbing"
+        onWheel={onWheel}
+        onPointerDown={onPointerDownBg}
+        onPointerMove={onPointerMove}
+        onPointerUp={(e) => onPointerUp(e)}
+      >
+        <g ref={rootRef}>
+          {links.map(({ key, a, b }) => {
+            const active = isLinkActive(a.id, b.id)
+            return (
+              <line
+                key={key}
+                ref={(el) => {
+                  if (el) lineEls.current.set(key, el)
+                  else lineEls.current.delete(key)
+                }}
+                x1={a.x}
+                y1={a.y}
+                x2={b.x}
+                y2={b.y}
+                stroke="#94a3b8"
+                strokeOpacity={hover ? (active ? 0.8 : 0.1) : 0.3}
+                strokeWidth={1}
+              />
+            )
+          })}
+          {nodes.map((n) => {
+            const r = nodeRadius(n.degree)
+            const dim = isDimmed(n.id)
+            return (
+              <g
+                key={n.id}
+                ref={(el) => {
+                  if (el) groupEls.current.set(n.id, el)
+                  else groupEls.current.delete(n.id)
+                }}
+                transform={`translate(${n.x},${n.y})`}
+                className="cursor-pointer"
+                opacity={dim ? 0.2 : 1}
+                onMouseEnter={() => setHover(n.id)}
+                onMouseLeave={() => setHover(null)}
+                onPointerDown={(e) => onPointerDownNode(e, n)}
+                onPointerUp={(e) => onPointerUp(e, n)}
+              >
+                <circle r={r} fill={colorOf(n.category)} stroke="#fff" strokeWidth={1.5} />
+                {(hover === n.id || n.degree >= 3) && (
+                  <text x={r + 4} y={3} className="fill-content-secondary" fontSize={9} style={{ pointerEvents: 'none' }}>
+                    {n.label.length > 15 ? n.label.slice(0, 14) + '…' : n.label}
+                  </text>
+                )}
+              </g>
+            )
+          })}
+        </g>
+      </svg>
+
+      {/* Category legend, mirrors the web client. */}
+      {categories.length > 0 && (
+        <div className="absolute bottom-3 left-3 flex flex-wrap gap-x-3 gap-y-1 max-w-[60%] rounded-lg bg-surface px-3 py-2 border border-subtle shadow-sm">
+          {categories.map((cat) => (
+            <span key={cat} className="inline-flex items-center gap-1.5 text-[11px] text-content-secondary">
+              <span className="w-2.5 h-2.5 rounded-full" style={{ background: colorOf(cat) }} />
+              {cat}
+            </span>
+          ))}
+        </div>
+      )}
+    </div>
+  )
+}
+
+export default KnowledgeGraph
diff --git a/desktop/src/renderer/src/components/LoginGate.tsx b/desktop/src/renderer/src/components/LoginGate.tsx
new file mode 100644
index 0000000..b08a935
--- /dev/null
+++ b/desktop/src/renderer/src/components/LoginGate.tsx
@@ -0,0 +1,72 @@
+import React, { useState } from 'react'
+import apiClient from '../api/client'
+import { t } from '../i18n'
+
+interface LoginGateProps {
+  // Called once the password is accepted (auth cookie set), so the app can
+  // proceed to the main UI.
+  onAuthenticated: () => void
+}
+
+/**
+ * Shown when the backend has a web_password set and the current session isn't
+ * authenticated yet. Submitting the correct password sets an auth cookie
+ * (handled by the backend), after which the app reloads its data.
+ */
+const LoginGate: React.FC<LoginGateProps> = ({ onAuthenticated }) => {
+  const [password, setPassword] = useState('')
+  const [submitting, setSubmitting] = useState(false)
+  const [error, setError] = useState('')
+
+  const submit = async (e: React.FormEvent) => {
+    e.preventDefault()
+    if (!password || submitting) return
+    setSubmitting(true)
+    setError('')
+    try {
+      const res = await apiClient.authLogin(password)
+      if (res.status === 'success') {
+        onAuthenticated()
+      } else {
+        setError(t('login_error'))
+      }
+    } catch {
+      setError(t('login_error'))
+    } finally {
+      setSubmitting(false)
+    }
+  }
+
+  return (
+    <div className="h-screen w-screen flex items-center justify-center bg-gray-50 dark:bg-[#111111]">
+      <form onSubmit={submit} className="text-center space-y-6 max-w-md px-8 w-full">
+        <img src="./logo.jpg" alt="CowAgent" className="w-16 h-16 rounded-2xl mx-auto shadow-lg shadow-primary-500/20" />
+        <div className="space-y-2">
+          <h1 className="text-xl font-bold text-slate-800 dark:text-slate-100">{t('login_title')}</h1>
+          <p className="text-sm text-slate-500 dark:text-slate-400">{t('login_desc')}</p>
+        </div>
+        <input
+          type="password"
+          autoFocus
+          value={password}
+          onChange={(e) => {
+            setPassword(e.target.value)
+            if (error) setError('')
+          }}
+          placeholder={t('login_placeholder')}
+          className="w-full px-4 py-2.5 rounded-lg border border-slate-300 dark:border-slate-700 bg-white dark:bg-[#1a1a1a] text-slate-800 dark:text-slate-100 text-sm outline-none focus:border-primary-500 transition-colors"
+        />
+        {error && <p className="text-sm text-red-500">{error}</p>}
+        <button
+          type="submit"
+          disabled={submitting || !password}
+          className="w-full inline-flex items-center justify-center gap-2 px-4 py-2.5 bg-primary-500 hover:bg-primary-600 disabled:opacity-50 disabled:cursor-not-allowed text-white rounded-lg transition-colors text-sm font-medium cursor-pointer"
+        >
+          {submitting ? t('login_checking') : t('login_submit')}
+        </button>
+      </form>
+    </div>
+  )
+}
+
+export default LoginGate
diff --git a/desktop/src/renderer/src/components/Markdown.tsx b/desktop/src/renderer/src/components/Markdown.tsx
new file mode 100644
index 0000000..a27e4af
--- /dev/null
+++ b/desktop/src/renderer/src/components/Markdown.tsx
@@ -0,0 +1,109 @@
+import React, { useMemo, useRef, useCallback } from 'react'
+import MarkdownIt from 'markdown-it'
+import hljs from 'highlight.js'
+import { t } from '../i18n'
+
+/**
+ * Markdown renderer aligned 1:1 with the web console (markdown-it + highlight.js
+ * + GitHub themes). Using the same engine guarantees identical line-break,
+ * linkify and code-highlight behavior across web and desktop.
+ */
+
+const md: MarkdownIt = new MarkdownIt({
+  html: false,
+  breaks: true,
+  linkify: true,
+  typographer: true,
+  highlight(str, lang) {
+    if (lang && hljs.getLanguage(lang)) {
+      try {
+        return hljs.highlight(str, { language: lang }).value
+      } catch {
+        /* fall through */
+      }
+    }
+    try {
+      return hljs.highlightAuto(str).value
+    } catch {
+      return ''
+    }
+  },
+})
+
+// Open links in a new tab safely.
+const defaultLinkOpen =
+  md.renderer.rules.link_open ||
+  function (tokens, idx, options, _env, self) {
+    return self.renderToken(tokens, idx, options)
+  }
+md.renderer.rules.link_open = function (tokens, idx, options, env, self) {
+  tokens[idx].attrPush(['target', '_blank'])
+  tokens[idx].attrPush(['rel', 'noopener noreferrer'])
+  return defaultLinkOpen(tokens, idx, options, env, self)
+}
+
+// Wrap fenced code blocks so we can render a header (lang + copy button).
+const defaultFence =
+  md.renderer.rules.fence ||
+  function (tokens, idx, options, _env, self) {
+    return self.renderToken(tokens, idx, options)
+  }
+md.renderer.rules.fence = function (tokens, idx, options, env, self) {
+  const token = tokens[idx]
+  const info = token.info ? token.info.trim().split(/\s+/)[0] : ''
+  // Ensure the `hljs` class is present so the GitHub theme background/base
+  // color applies (markdown-it only adds language-* by default).
+  let rendered = defaultFence(tokens, idx, options, env, self)
+  if (rendered.includes('<code class="')) {
+    rendered = rendered.replace('<code class="', '<code class="hljs ')
+  } else {
+    rendered = rendered.replace('<code>', '<code class="hljs">')
+  }
+  return (
+    `<div class="code-block-wrapper">` +
+    `<div class="code-block-header">` +
+    `<span class="code-block-lang">${info || 'text'}</span>` +
+    `<button type="button" class="code-copy-btn" data-code-id="cb-${idx}" aria-label="Copy code">${t('msg_copy')}</button>` +
+    `</div>` +
+    rendered +
+    `</div>`
+  )
+}
+
+interface MarkdownProps {
+  content: string
+}
+
+const Markdown: React.FC<MarkdownProps> = ({ content }) => {
+  const rootRef = useRef<HTMLDivElement>(null)
+
+  const html = useMemo(() => md.render(content || ''), [content])
+
+  // Delegate copy clicks on code blocks (buttons are injected as raw HTML).
+  const handleClick = useCallback((e: React.MouseEvent<HTMLDivElement>) => {
+    const target = e.target as HTMLElement
+    const btn = target.closest('.code-copy-btn') as HTMLElement | null
+    if (!btn) return
+    const pre = btn.closest('.code-block-wrapper')?.querySelector('pre')
+    if (!pre) return
+    navigator.clipboard.writeText(pre.textContent || '')
+    const original = btn.textContent
+    btn.textContent = t('msg_copied')
+    btn.classList.add('copied')
+    setTimeout(() => {
+      btn.textContent = original
+      btn.classList.remove('copied')
+    }, 1600)
+  }, [])
+
+  return (
+    <div
+      ref={rootRef}
+      className="msg-content text-sm text-content leading-relaxed break-words"
+      onClick={handleClick}
+      dangerouslySetInnerHTML={{ __html: html }}
+    />
+  )
+}
+
+export default Markdown
diff --git a/desktop/src/renderer/src/components/MessageBubble.tsx b/desktop/src/renderer/src/components/MessageBubble.tsx
new file mode 100644
index 0000000..40b6450
--- /dev/null
+++ b/desktop/src/renderer/src/components/MessageBubble.tsx
@@ -0,0 +1,203 @@
+import React, { useState } from 'react'
+import { Copy, Check, RefreshCw, Trash2, File as FileIcon, Sprout } from 'lucide-react'
+import type { ChatMessage } from '../types'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import Markdown from './Markdown'
+import MessageSteps, { ThinkingStep } from './MessageSteps'
+
+interface MessageBubbleProps {
+  message: ChatMessage
+  onRegenerate?: (id: string) => void
+  onEdit?: (id: string) => void
+  onDelete?: (msg: ChatMessage) => void
+  /** Fired when an inline image/video finishes loading, so the parent can
+   *  re-scroll to the bottom (async media changes bubble height after mount). */
+  onMediaLoad?: () => void
+}
+
+function fmtTime(ts: number): string {
+  if (!ts) return ''
+  const d = new Date(ts * 1000)
+  return d.toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' })
+}
+
+const HoverAction: React.FC<{ onClick: () => void; title: string; danger?: boolean; children: React.ReactNode }> = ({
+  onClick,
+  title,
+  danger,
+  children,
+}) => (
+  <button
+    onClick={onClick}
+    title={title}
+    className={`inline-flex items-center justify-center w-7 h-7 rounded-md cursor-pointer transition-colors text-content-tertiary ${
+      danger ? 'hover:text-danger hover:bg-danger-soft' : 'hover:text-content hover:bg-surface-2'
+    }`}
+  >
+    {children}
+  </button>
+)
+
+const MessageBubble: React.FC<MessageBubbleProps> = ({ message, onRegenerate, onEdit, onDelete, onMediaLoad }) => {
+  const isUser = message.role === 'user'
+  const [copied, setCopied] = useState(false)
+
+  const copy = () => {
+    navigator.clipboard.writeText(message.content)
+    setCopied(true)
+    setTimeout(() => setCopied(false), 1800)
+  }
+
+  // Open a sent file: prefer the local path via Electron (Finder / default
+  // app); fall back to the served URL in a browser when unavailable.
+  const openAttachment = (att: { abs_path?: string; preview_url?: string; file_path: string }) => {
+    if (att.abs_path && window.electronAPI?.openPath) {
+      window.electronAPI.openPath(att.abs_path)
+      return
+    }
+    window.open(apiClient.getFileUrl(att.preview_url || att.file_path), '_blank')
+  }
+
+  if (isUser) {
+    return (
+      <div className="group flex flex-col items-end px-4 sm:px-6 py-2">
+        {message.attachments && message.attachments.length > 0 && (
+          <div className="flex flex-wrap gap-2 mb-1.5 justify-end max-w-[75%]">
+            {message.attachments.map((att, i) =>
+              att.file_type === 'image' && att.preview_url ? (
+                <img
+                  key={i}
+                  src={apiClient.getFileUrl(att.preview_url)}
+                  alt={att.file_name}
+                  className="max-w-[180px] max-h-[150px] rounded-xl object-cover border border-default"
+                />
+              ) : (
+                <div key={i} className="flex items-center gap-1.5 px-3 py-2 bg-surface-2 rounded-xl text-xs text-content-secondary">
+                  <FileIcon size={13} />
+                  {att.file_name}
+                </div>
+              )
+            )}
+          </div>
+        )}
+        <div className="max-w-[75%] rounded-2xl rounded-br-md px-4 py-2.5 bg-accent text-white">
+          <div className="text-sm whitespace-pre-wrap break-words">{message.content}</div>
+        </div>
+        <div className="flex items-center gap-0.5 mt-1 opacity-0 group-hover:opacity-100 transition-opacity">
+          <span className="text-[11px] text-content-tertiary mr-1">{fmtTime(message.timestamp)}</span>
+          {/* Edit entry hidden: editing a past question cascade-deletes all
+              subsequent turns, which surprises users. Kept off until we support
+              non-destructive editing. */}
+          {onDelete && message.userSeq != null && (
+            <HoverAction onClick={() => onDelete(message)} title={t('msg_delete')} danger>
+              <Trash2 size={13} />
+            </HoverAction>
+          )}
+        </div>
+      </div>
+    )
+  }
+
+  // Assistant
+  const showCursor = message.isStreaming && !message.content && (!message.steps || message.steps.length === 0)
+
+  const hasSteps = !!(message.steps && message.steps.length > 0)
+  const hasLiveReasoning = !!(message.reasoning && message.isStreaming)
+
+  return (
+    <div className="group flex gap-3 px-4 sm:px-6 py-2">
+      <img src="./logo.jpg" alt="CowAgent" className="w-7 h-7 rounded-lg flex-shrink-0 mt-1" />
+      <div className="flex-1 min-w-0 max-w-[calc(100%-2.5rem)]">
+        <div className="inline-block w-full rounded-2xl border border-default bg-surface px-4 py-3">
+          {message.kind === 'evolution' && (
+            <div className="inline-flex items-center gap-1 mb-1.5 text-[11px] text-content-tertiary">
+              <Sprout size={11} />
+              {t('msg_self_learned')}
+            </div>
+          )}
+
+          {/* Steps area (thinking / tools / intermediate content), web-aligned:
+              muted, separated from the final answer by a dashed divider. */}
+          {(hasSteps || hasLiveReasoning) && (
+            <div className="mb-2.5 pb-2 border-b border-dashed border-default">
+              {hasLiveReasoning && <ThinkingStep content={message.reasoning!} streaming />}
+              {hasSteps && <MessageSteps steps={message.steps!} />}
+            </div>
+          )}
+
+          {/* Final answer */}
+          {message.content && <Markdown content={message.content} />}
+
+          {/* Media attachments sent via the `send` tool (images / files). */}
+          {message.attachments && message.attachments.length > 0 && (
+            <div className="flex flex-wrap gap-2 mt-2">
+              {message.attachments.map((att, i) =>
+                att.file_type === 'image' ? (
+                  <img
+                    key={i}
+                    src={apiClient.getFileUrl(att.preview_url || att.file_path)}
+                    alt={att.file_name}
+                    onLoad={() => onMediaLoad?.()}
+                    onClick={() => window.open(apiClient.getFileUrl(att.preview_url || att.file_path), '_blank')}
+                    className="max-w-[320px] w-full rounded-xl border border-default cursor-zoom-in"
+                  />
+                ) : att.file_type === 'video' ? (
+                  <video
+                    key={i}
+                    src={apiClient.getFileUrl(att.preview_url || att.file_path)}
+                    controls
+                    onLoadedData={() => onMediaLoad?.()}
+                    className="max-w-[360px] w-full rounded-xl border border-default"
+                  />
+                ) : (
+                  <button
+                    key={i}
+                    type="button"
+                    onClick={() => openAttachment(att)}
+                    className="flex items-center gap-1.5 px-3 py-2 bg-surface-2 rounded-xl text-xs text-content-secondary hover:text-content cursor-pointer"
+                  >
+                    <FileIcon size={13} />
+                    {att.file_name}
+                  </button>
+                )
+              )}
+            </div>
+          )}
+
+          {showCursor && (
+            <div className="flex items-center gap-1 py-0.5">
+              <span className="typing-dot" />
+              <span className="typing-dot" />
+              <span className="typing-dot" />
+            </div>
+          )}
+
+          {message.isStreaming && message.content && (
+            <span className="inline-block w-[6px] h-[14px] bg-accent ml-0.5 align-middle animate-blink" />
+          )}
+
+          {message.isCancelled && <div className="text-xs text-warning mt-1">{t('msg_cancelled')}</div>}
+          {message.error && <div className="text-xs text-danger mt-1">{message.error}</div>}
+        </div>
+
+        {/* Hover actions (only when finished) */}
+        {!message.isStreaming && (message.content || message.error) && (
+          <div className="flex items-center gap-0.5 mt-1 opacity-0 group-hover:opacity-100 transition-opacity">
+            <span className="text-[11px] text-content-tertiary mr-1">{fmtTime(message.timestamp)}</span>
+            <HoverAction onClick={copy} title={t('msg_copy')}>
+              {copied ? <Check size={13} /> : <Copy size={13} />}
+            </HoverAction>
+            {onRegenerate && (
+              <HoverAction onClick={() => onRegenerate(message.id)} title={t('msg_regenerate')}>
+                <RefreshCw size={13} />
+              </HoverAction>
+            )}
+          </div>
+        )}
+      </div>
+    </div>
+  )
+}
+
+export default MessageBubble
diff --git a/desktop/src/renderer/src/components/MessageSteps.tsx b/desktop/src/renderer/src/components/MessageSteps.tsx
new file mode 100644
index 0000000..176e815
--- /dev/null
+++ b/desktop/src/renderer/src/components/MessageSteps.tsx
@@ -0,0 +1,109 @@
+import React, { useState } from 'react'
+import { ChevronRight, Loader2, Check, X, Brain } from 'lucide-react'
+import type { MessageStep } from '../types'
+import Markdown from './Markdown'
+
+/**
+ * Assistant reasoning / tool steps, styled to match the web console: small,
+ * muted, collapsible rows with an indented detail panel.
+ */
+
+const ThinkingStep: React.FC<{ content: string; streaming?: boolean }> = ({ content, streaming }) => {
+  const [expanded, setExpanded] = useState(false)
+  return (
+    <div className="text-xs text-content-tertiary mb-1 last:mb-0">
+      <div
+        className="flex items-center gap-1.5 cursor-pointer hover:text-content-secondary select-none transition-colors"
+        onClick={() => setExpanded((v) => !v)}
+      >
+        <Brain size={12} className="flex-shrink-0" />
+        <span className="flex-1">{streaming ? 'Thinking…' : 'Thought for a moment'}</span>
+        <ChevronRight size={11} className={`transition-transform opacity-50 ${expanded ? 'rotate-90' : ''}`} />
+      </div>
+      {expanded && (
+        <pre className="mt-1.5 ml-4 p-2 rounded-md bg-inset border border-subtle whitespace-pre-wrap leading-relaxed max-h-[260px] overflow-y-auto font-sans text-content-tertiary">
+          {content}
+        </pre>
+      )}
+    </div>
+  )
+}
+
+const ToolStep: React.FC<{ step: MessageStep }> = ({ step }) => {
+  const [expanded, setExpanded] = useState(false)
+  const running = step.status === 'running'
+  const isError = step.is_error || (!!step.status && step.status !== 'success' && !running)
+
+  const icon = running ? (
+    <Loader2 size={12} className="text-accent animate-spin" />
+  ) : isError ? (
+    <X size={12} className="text-danger" />
+  ) : (
+    <Check size={12} className="text-accent" />
+  )
+
+  return (
+    <div className="text-xs text-content-tertiary mb-1 last:mb-0">
+      <div
+        className="flex items-center gap-1.5 cursor-pointer hover:text-content-secondary select-none transition-colors"
+        onClick={() => setExpanded((v) => !v)}
+      >
+        <span className="flex-shrink-0">{icon}</span>
+        <span className={`font-medium ${isError ? 'text-danger' : ''}`}>{step.name}</span>
+        {step.execution_time !== undefined && (
+          <span className="opacity-60">{step.execution_time}s</span>
+        )}
+        <ChevronRight size={11} className={`ml-auto transition-transform opacity-50 ${expanded ? 'rotate-90' : ''}`} />
+      </div>
+      {expanded && (
+        <div className="mt-1.5 ml-4 p-2 rounded-md bg-inset border border-subtle space-y-2">
+          {step.arguments && Object.keys(step.arguments).length > 0 && (
+            <div>
+              <div className="text-[10px] font-semibold uppercase tracking-wide opacity-60 mb-1">Input</div>
+              <pre className="font-mono text-[11px] whitespace-pre-wrap break-all max-h-[200px] overflow-y-auto leading-relaxed">
+                {JSON.stringify(step.arguments, null, 2)}
+              </pre>
+            </div>
+          )}
+          {step.result && (
+            <div>
+              <div className="text-[10px] font-semibold uppercase tracking-wide opacity-60 mb-1">
+                {isError ? 'Error' : 'Output'}
+              </div>
+              <pre
+                className={`font-mono text-[11px] whitespace-pre-wrap break-all max-h-[240px] overflow-y-auto leading-relaxed ${
+                  isError ? 'text-danger' : ''
+                }`}
+              >
+                {step.result.length > 4000 ? step.result.slice(0, 4000) + '\n… (truncated)' : step.result}
+              </pre>
+            </div>
+          )}
+        </div>
+      )}
+    </div>
+  )
+}
+
+/** Renders an ordered list of assistant steps (thinking / content / tool). */
+const MessageSteps: React.FC<{ steps: MessageStep[] }> = ({ steps }) => {
+  if (!steps.length) return null
+  return (
+    <div>
+      {steps.map((step, i) => {
+        if (step.type === 'thinking') return <ThinkingStep key={i} content={step.content || ''} />
+        if (step.type === 'tool') return <ToolStep key={i} step={step} />
+        if (step.type === 'content' && step.content)
+          return (
+            <div key={i} className="mb-2 pb-2 border-b border-dashed border-default last:border-0 last:mb-0 last:pb-0">
+              <Markdown content={step.content} />
+            </div>
+          )
+        return null
+      })}
+    </div>
+  )
+}
+
+export { ThinkingStep, ToolStep }
+export default MessageSteps
diff --git a/desktop/src/renderer/src/components/OnboardingWizard.tsx b/desktop/src/renderer/src/components/OnboardingWizard.tsx
new file mode 100644
index 0000000..cde8baa
--- /dev/null
+++ b/desktop/src/renderer/src/components/OnboardingWizard.tsx
@@ -0,0 +1,293 @@
+import React, { useEffect, useMemo, useState } from 'react'
+import { Sparkles, KeyRound, Loader2, ArrowRight, ArrowLeft, ExternalLink } from 'lucide-react'
+import { t, getLang, setLang, type Lang } from '../i18n'
+import apiClient from '../api/client'
+import type { ModelsData } from '../types'
+import { Field, Dropdown, TextInput, type DropdownOption } from '../pages/settings/primitives'
+import { resolveModels, providerLabel } from '../pages/settings/modelsHelpers'
+import { useOnboardingStore } from '../store/onboardingStore'
+
+interface OnboardingWizardProps {
+  // Called after the wizard finishes so the host can refresh language/state.
+  onDone: () => void
+}
+
+const TOTAL_STEPS = 2
+
+// Optional "where to get an API key" console link, per provider.
+const PROVIDER_KEY_CONSOLE: Record<string, string> = {
+  linkai: 'https://link-ai.tech/console/interface',
+}
+
+// First-run guided setup: language -> chat model (provider + key + model).
+// After saving the model the user goes straight into the chat (no extra
+// confirmation step). Rendered as a full-screen overlay above the main UI;
+// reuses the same models API and primitives as the settings page.
+const OnboardingWizard: React.FC<OnboardingWizardProps> = ({ onDone }) => {
+  const finish = useOnboardingStore((s) => s.finish)
+
+  const [step, setStep] = useState(1)
+  const [lang, setLangState] = useState<Lang>(getLang())
+  const [models, setModels] = useState<ModelsData | null>(null)
+
+  // Step 2 form state.
+  const [provider, setProvider] = useState('')
+  const [apiKey, setApiKey] = useState('')
+  const [apiBase, setApiBase] = useState('')
+  const [model, setModel] = useState('')
+
+  const [saving, setSaving] = useState(false)
+  const [error, setError] = useState('')
+
+  // Load the models console data once for the provider/model dropdowns.
+  useEffect(() => {
+    apiClient
+      .getModels()
+      .then(setModels)
+      .catch(() => setError(t('onboarding_save_failed')))
+  }, [])
+
+  // Persist the auto-detected default language on first show so the pre-selected
+  // option (driven by OS locale) also reaches the backend, even if the user
+  // doesn't tap the language buttons.
+  useEffect(() => {
+    if (!localStorage.getItem('cow_lang')) switchLang(lang)
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [])
+
+  const providerOptions: DropdownOption[] = useMemo(() => {
+    const chat = models?.capabilities?.chat
+    const ids = chat?.providers || []
+    return ids.map((id) => ({ value: id, label: providerLabel(models, id) }))
+  }, [models])
+
+  const modelOptions: DropdownOption[] = useMemo(() => {
+    return resolveModels(models, provider, models?.capabilities?.chat?.provider_models).map((o) => ({
+      value: o.value,
+      label: o.value,
+      hint: o.hint,
+    }))
+  }, [models, provider])
+
+  // The currently selected provider's api_base placeholder/default, if any.
+  const providerMeta = models?.providers?.find((p) => p.id === provider)
+  const apiBasePlaceholder = providerMeta?.api_base_placeholder || providerMeta?.api_base_default
+
+  const handleProvider = (id: string) => {
+    setProvider(id)
+    setApiBase('')
+    const first = resolveModels(models, id, models?.capabilities?.chat?.provider_models)[0]
+    setModel(first?.value || '')
+  }
+
+  const switchLang = (next: Lang) => {
+    setLang(next)
+    setLangState(next)
+    // Mirror the choice to the backend so the agent/logs use the same language
+    // (matches BasicSettings). Non-blocking: the UI already switched locally.
+    apiClient.updateConfig({ cow_lang: next }).catch(() => {})
+  }
+
+  // Step 1 (language) can always advance; step 2 needs a provider, key, model.
+  const canNext = step === 1 || (!!provider && !!apiKey.trim() && !!model)
+
+  const goNext = async () => {
+    setError('')
+    // Step 1 (language) just advances to the model step.
+    if (step === 1) {
+      setStep(2)
+      return
+    }
+    // Step 2 is the last step: persist the provider credentials, point the chat
+    // capability at it, then finish straight into the chat (no extra step).
+    setSaving(true)
+    try {
+      await apiClient.modelsAction({
+        action: 'set_provider',
+        provider_id: provider,
+        api_key: apiKey.trim(),
+        ...(apiBase.trim() ? { api_base: apiBase.trim() } : {}),
+      })
+      await apiClient.modelsAction({
+        action: 'set_capability',
+        capability: 'chat',
+        provider_id: provider,
+        model,
+      })
+    } catch {
+      setSaving(false)
+      setError(t('onboarding_save_failed'))
+      return
+    }
+    setSaving(false)
+    complete()
+  }
+
+  const goBack = () => {
+    setError('')
+    setStep((s) => Math.max(1, s - 1))
+  }
+
+  const complete = () => {
+    finish()
+    onDone()
+  }
+
+  const stepLabel = t('onboarding_step').replace('{n}', String(step)).replace('{total}', String(TOTAL_STEPS))
+
+  return (
+    <div className="fixed inset-0 z-[60] flex items-center justify-center bg-base">
+      <div className="w-full max-w-lg px-8">
+        {/* Progress dots */}
+        <div className="flex items-center justify-center gap-2 mb-8">
+          {Array.from({ length: TOTAL_STEPS }).map((_, i) => (
+            <span
+              key={i}
+              className={`h-1.5 rounded-full transition-all ${
+                i + 1 === step ? 'w-8 bg-accent' : i + 1 < step ? 'w-4 bg-accent/50' : 'w-4 bg-surface-2'
+              }`}
+            />
+          ))}
+        </div>
+
+        {step === 1 && (
+          <div className="text-center space-y-6">
+            <div className="w-16 h-16 rounded-2xl bg-accent-soft text-accent flex items-center justify-center mx-auto">
+              <Sparkles size={30} />
+            </div>
+            <div className="space-y-2">
+              <h1 className="text-2xl font-bold text-content">{t('onboarding_welcome_title')}</h1>
+              <p className="text-sm text-content-secondary">{t('onboarding_welcome_desc')}</p>
+            </div>
+            <div className="max-w-xs mx-auto text-left">
+              <Field label={t('onboarding_lang_label')}>
+                <div className="grid grid-cols-2 gap-2">
+                  {(['zh', 'en'] as Lang[]).map((l) => (
+                    <button
+                      key={l}
+                      onClick={() => switchLang(l)}
+                      className={`px-4 py-2.5 rounded-btn border text-sm font-medium cursor-pointer transition-colors ${
+                        lang === l
+                          ? 'border-accent bg-accent-soft text-accent'
+                          : 'border-strong text-content-secondary hover:bg-surface-2'
+                      }`}
+                    >
+                      {l === 'zh' ? '简体中文' : 'English'}
+                    </button>
+                  ))}
+                </div>
+              </Field>
+            </div>
+          </div>
+        )}
+
+        {step === 2 && (
+          <div className="space-y-6">
+            <div className="text-center space-y-2">
+              <div className="w-16 h-16 rounded-2xl bg-accent-soft text-accent flex items-center justify-center mx-auto">
+                <KeyRound size={28} />
+              </div>
+              <h1 className="text-2xl font-bold text-content">{t('onboarding_model_title')}</h1>
+              <p className="text-sm text-content-secondary">{t('onboarding_model_desc')}</p>
+            </div>
+            <div className="space-y-4">
+              <Field label={t('onboarding_provider')}>
+                <Dropdown
+                  value={provider}
+                  options={providerOptions}
+                  placeholder={t('onboarding_select_provider')}
+                  onChange={handleProvider}
+                />
+              </Field>
+              {provider && (
+                <>
+                  <Field label={t('onboarding_apikey')}>
+                    <TextInput
+                      type="password"
+                      value={apiKey}
+                      onChange={(e) => setApiKey(e.target.value)}
+                      placeholder={t('onboarding_apikey_placeholder')}
+                      className="font-mono"
+                    />
+                    {PROVIDER_KEY_CONSOLE[provider] && (
+                      <a
+                        href={PROVIDER_KEY_CONSOLE[provider]}
+                        target="_blank"
+                        rel="noreferrer"
+                        className="mt-1.5 inline-flex items-center gap-1 text-xs text-accent hover:underline"
+                      >
+                        {t('onboarding_key_guide')}
+                        <ExternalLink size={11} />
+                      </a>
+                    )}
+                  </Field>
+                  {providerMeta?.api_base_field && (
+                    <Field label={t('onboarding_apibase')}>
+                      <TextInput
+                        value={apiBase}
+                        onChange={(e) => setApiBase(e.target.value)}
+                        placeholder={apiBasePlaceholder || ''}
+                        className="font-mono"
+                      />
+                    </Field>
+                  )}
+                  <Field label={t('onboarding_model')}>
+                    <Dropdown
+                      value={model}
+                      options={modelOptions}
+                      placeholder={t('onboarding_select_model')}
+                      onChange={setModel}
+                    />
+                  </Field>
+                </>
+              )}
+              {error && <p className="text-sm text-danger">{error}</p>}
+            </div>
+          </div>
+        )}
+
+        {/* Footer controls */}
+        <div className="mt-10 flex items-center justify-between">
+          <div className="text-xs text-content-tertiary">{stepLabel}</div>
+          <div className="flex items-center gap-2">
+            {/* Step 2: back to language. */}
+            {step === 2 && (
+              <button
+                onClick={goBack}
+                disabled={saving}
+                className="px-4 py-2 rounded-btn border border-strong text-content-secondary hover:bg-surface-2 text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 inline-flex items-center gap-1.5"
+              >
+                <ArrowLeft size={15} />
+                {t('onboarding_back')}
+              </button>
+            )}
+            {/* Skip is available on every step: dismiss and go straight to chat. */}
+            <button
+              onClick={complete}
+              disabled={saving}
+              className="px-4 py-2 rounded-btn text-sm font-medium text-content-tertiary hover:text-content cursor-pointer transition-colors disabled:opacity-50"
+            >
+              {t('onboarding_skip')}
+            </button>
+            {/* Primary action: advance on step 1, save + finish on the last step. */}
+            <button
+              onClick={goNext}
+              disabled={!canNext || saving}
+              className="px-5 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 disabled:cursor-not-allowed inline-flex items-center gap-1.5"
+            >
+              {saving && <Loader2 size={15} className="animate-spin" />}
+              {saving
+                ? t('onboarding_saving')
+                : step === TOTAL_STEPS
+                  ? t('onboarding_finish')
+                  : t('onboarding_next')}
+              {!saving && <ArrowRight size={15} />}
+            </button>
+          </div>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+export default OnboardingWizard
diff --git a/desktop/src/renderer/src/components/QrLoginModal.tsx b/desktop/src/renderer/src/components/QrLoginModal.tsx
new file mode 100644
index 0000000..71ca484
--- /dev/null
+++ b/desktop/src/renderer/src/components/QrLoginModal.tsx
@@ -0,0 +1,222 @@
+import React, { useEffect, useRef, useState } from 'react'
+import { Loader2, Check, RotateCcw } from 'lucide-react'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import { Modal } from '../pages/settings/primitives'
+
+type Provider = 'weixin' | 'feishu'
+type Phase = 'loading' | 'waiting' | 'scanned' | 'success' | 'error'
+
+interface QrLoginModalProps {
+  provider: Provider
+  onClose: () => void
+  // Fired once the channel is connected so the page can refresh.
+  onConnected: () => void
+}
+
+const POLL_INTERVAL = 2000
+
+// Shared QR-login / QR-register modal for WeChat and Feishu. Mirrors the web
+// console flow: fetch a QR, poll status, then connect the channel on success.
+const QrLoginModal: React.FC<QrLoginModalProps> = ({ provider, onClose, onConnected }) => {
+  const [phase, setPhase] = useState<Phase>('loading')
+  const [qr, setQr] = useState('')
+  const [openLink, setOpenLink] = useState('')
+  const [errMsg, setErrMsg] = useState('')
+  const timerRef = useRef<ReturnType<typeof setTimeout> | null>(null)
+  const aliveRef = useRef(true)
+
+  const stopPoll = () => {
+    if (timerRef.current) {
+      clearTimeout(timerRef.current)
+      timerRef.current = null
+    }
+  }
+
+  const fail = (msg: string) => {
+    if (!aliveRef.current) return
+    setPhase('error')
+    setErrMsg(msg)
+  }
+
+  // ---- WeChat: GET qr, POST poll {scaned|confirmed|expired} -----------------
+  const pollWeixin = () => {
+    timerRef.current = setTimeout(async () => {
+      if (!aliveRef.current) return
+      try {
+        const data = await apiClient.weixinQrAction('poll')
+        if (!aliveRef.current) return
+        if (data.status !== 'success') return pollWeixin()
+        const s = data.qr_status as string
+        if (s === 'confirmed') {
+          setPhase('success')
+          await apiClient.channelAction('connect', 'weixin', {})
+          if (aliveRef.current) onConnected()
+        } else if (s === 'expired' && (data.qr_image || data.qrcode_url)) {
+          setQr((data.qr_image as string) || (data.qrcode_url as string))
+          setPhase('waiting')
+          pollWeixin()
+        } else if (s === 'scaned') {
+          setPhase('scanned')
+          pollWeixin()
+        } else {
+          pollWeixin()
+        }
+      } catch {
+        pollWeixin()
+      }
+    }, POLL_INTERVAL)
+  }
+
+  const startWeixin = async () => {
+    setPhase('loading')
+    try {
+      const data = await apiClient.getWeixinQr()
+      if (!aliveRef.current) return
+      if (data.status !== 'success') return fail(data.message || t('weixin_scan_fail'))
+      setQr(data.qr_image || data.qrcode_url || '')
+      setPhase('waiting')
+      pollWeixin()
+    } catch {
+      fail(t('weixin_scan_fail'))
+    }
+  }
+
+  // ---- Feishu: GET qr, POST poll {done|expired|denied|error} ----------------
+  const pollFeishu = () => {
+    timerRef.current = setTimeout(async () => {
+      if (!aliveRef.current) return
+      try {
+        const data = await apiClient.feishuRegisterPoll()
+        if (!aliveRef.current) return
+        if (data.status !== 'success') return fail((data.message as string) || t('feishu_scan_fail'))
+        const rs = data.register_status as string
+        if (rs === 'done') {
+          setPhase('success')
+          await apiClient.channelAction('connect', 'feishu', {
+            feishu_app_id: data.app_id,
+            feishu_app_secret: data.app_secret,
+          })
+          if (aliveRef.current) onConnected()
+        } else if (rs === 'expired') {
+          fail(t('feishu_scan_expired'))
+        } else if (rs === 'denied') {
+          fail(t('feishu_scan_denied'))
+        } else if (rs === 'error') {
+          fail((data.message as string) || t('feishu_scan_fail'))
+        } else {
+          pollFeishu()
+        }
+      } catch {
+        pollFeishu()
+      }
+    }, POLL_INTERVAL)
+  }
+
+  const startFeishu = async () => {
+    setPhase('loading')
+    try {
+      const data = await apiClient.getFeishuRegister()
+      if (!aliveRef.current) return
+      if (data.status !== 'success') return fail(data.message || t('feishu_scan_fail'))
+      setQr(data.qr_image || data.qrcode_url || '')
+      setOpenLink(data.qrcode_url || '')
+      setPhase('waiting')
+      pollFeishu()
+    } catch {
+      fail(t('feishu_scan_fail'))
+    }
+  }
+
+  const start = () => {
+    stopPoll()
+    if (provider === 'weixin') void startWeixin()
+    else void startFeishu()
+  }
+
+  useEffect(() => {
+    aliveRef.current = true
+    start()
+    return () => {
+      aliveRef.current = false
+      stopPoll()
+    }
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [provider])
+
+  const title = provider === 'weixin' ? t('weixin_scan_title') : t('feishu_scan_title')
+  const desc = provider === 'weixin' ? t('weixin_scan_desc') : t('feishu_scan_desc')
+  const tip = provider === 'weixin' ? t('weixin_qr_tip') : t('feishu_scan_tip')
+
+  const statusText = (): string => {
+    if (provider === 'weixin') {
+      if (phase === 'scanned') return t('weixin_scan_scanned')
+      return t('weixin_scan_waiting')
+    }
+    return t('feishu_scan_waiting')
+  }
+
+  return (
+    <Modal open title={title} onClose={onClose}>
+      <div className="flex flex-col items-center py-2">
+        {phase === 'loading' && (
+          <div className="flex items-center text-content-tertiary py-10">
+            <Loader2 size={18} className="animate-spin mr-2" />
+            {provider === 'weixin' ? t('weixin_scan_loading') : t('feishu_scan_loading')}
+          </div>
+        )}
+
+        {(phase === 'waiting' || phase === 'scanned') && (
+          <>
+            <p className="text-sm text-content-secondary mb-4 text-center">{desc}</p>
+            <div className="bg-white p-3 rounded-card border border-subtle mb-3">
+              {qr ? (
+                <img src={qr} alt="QR" className="w-48 h-48" style={{ imageRendering: 'pixelated' }} />
+              ) : (
+                <div className="w-48 h-48 flex items-center justify-center text-content-tertiary text-xs">QR</div>
+              )}
+            </div>
+            <p className={`text-xs mb-1 ${phase === 'scanned' ? 'text-accent' : 'text-warning'}`}>{statusText()}</p>
+            <p className="text-xs text-content-tertiary">{tip}</p>
+            {openLink && (
+              <a
+                href={openLink}
+                target="_blank"
+                rel="noopener noreferrer"
+                className="text-xs text-info hover:underline mt-2"
+              >
+                {t('feishu_scan_open_link')}
+              </a>
+            )}
+          </>
+        )}
+
+        {phase === 'success' && (
+          <div className="flex flex-col items-center py-8">
+            <div className="w-12 h-12 rounded-full bg-accent-soft flex items-center justify-center mb-3">
+              <Check size={22} className="text-accent" />
+            </div>
+            <p className="text-sm font-medium text-accent">
+              {provider === 'weixin' ? t('weixin_scan_success') : t('feishu_scan_success')}
+            </p>
+          </div>
+        )}
+
+        {phase === 'error' && (
+          <div className="flex flex-col items-center py-8">
+            <p className="text-sm text-danger text-center mb-3">{errMsg}</p>
+            <button
+              onClick={start}
+              className="inline-flex items-center gap-1.5 px-4 py-1.5 rounded-btn border border-strong text-sm text-content-secondary hover:bg-inset cursor-pointer transition-colors"
+            >
+              <RotateCcw size={13} />
+              {t('feishu_scan_retry')}
+            </button>
+          </div>
+        )}
+      </div>
+    </Modal>
+  )
+}
+
+export default QrLoginModal
diff --git a/desktop/src/renderer/src/components/StatusScreen.tsx b/desktop/src/renderer/src/components/StatusScreen.tsx
new file mode 100644
index 0000000..553b285
--- /dev/null
+++ b/desktop/src/renderer/src/components/StatusScreen.tsx
@@ -0,0 +1,58 @@
+import React from 'react'
+import { t } from '../i18n'
+
+interface StatusScreenProps {
+  status: 'connecting' | 'error'
+  error?: string
+  onRetry: () => void
+}
+
+const StatusScreen: React.FC<StatusScreenProps> = ({ status, error, onRetry }) => {
+  return (
+    <div className="h-screen w-screen flex items-center justify-center bg-gray-50 dark:bg-[#111111]">
+      <div className="text-center space-y-6 max-w-md px-8">
+        <img src="./logo.jpg" alt="CowAgent" className="w-16 h-16 rounded-2xl mx-auto shadow-lg shadow-primary-500/20" />
+
+        {status === 'connecting' && (
+          <>
+            <div className="space-y-2">
+              <h1 className="text-xl font-bold text-slate-800 dark:text-slate-100">
+                {t('status_starting')}
+              </h1>
+              <p className="text-sm text-slate-500 dark:text-slate-400">
+                {t('status_starting_desc')}
+              </p>
+            </div>
+            <div className="flex justify-center gap-1">
+              <span className="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style={{ animationDelay: '0s' }} />
+              <span className="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style={{ animationDelay: '0.2s' }} />
+              <span className="w-2 h-2 rounded-full bg-primary-400 animate-pulse-dot" style={{ animationDelay: '0.4s' }} />
+            </div>
+          </>
+        )}
+
+        {status === 'error' && (
+          <>
+            <div className="space-y-2">
+              <h1 className="text-xl font-bold text-slate-800 dark:text-slate-100">
+                {t('status_error')}
+              </h1>
+              <p className="text-sm text-slate-500 dark:text-slate-400">
+                {error || t('status_error_desc')}
+              </p>
+            </div>
+            <button
+              onClick={onRetry}
+              className="inline-flex items-center gap-2 px-4 py-2 bg-primary-500 hover:bg-primary-600 text-white rounded-lg transition-colors text-sm font-medium cursor-pointer"
+            >
+              <i className="fas fa-rotate-right text-xs" />
+              {t('status_retry')}
+            </button>
+          </>
+        )}
+      </div>
+    </div>
+  )
+}
+
+export default StatusScreen
diff --git a/desktop/src/renderer/src/components/UpdateBanner.tsx b/desktop/src/renderer/src/components/UpdateBanner.tsx
new file mode 100644
index 0000000..78c4800
--- /dev/null
+++ b/desktop/src/renderer/src/components/UpdateBanner.tsx
@@ -0,0 +1,133 @@
+import React from 'react'
+import { Download, RefreshCw, X, Loader2, AlertTriangle } from 'lucide-react'
+import { t } from '../i18n'
+import { useUpdateStore, hasAvailableUpdate } from '../store/updateStore'
+
+// Compact update panel anchored to the NavRail footer. Shown whenever an update
+// is available AND the panel is open (auto-opened on detection, re-openable via
+// "check for update"). Dismissing (×) just closes it; the menu can re-open it.
+const UpdateBanner: React.FC = () => {
+  const state = useUpdateStore()
+  const open = state.panelOpen
+
+  const available = hasAvailableUpdate(state)
+  const status = state.status
+  const errored = status?.state === 'error'
+
+  // Full-screen "installing…" overlay: bridges the otherwise blank window
+  // between clicking "restart to install" and the app actually quitting to
+  // swap the bundle. (The gap AFTER quit, before relaunch, is OS-level and
+  // can't be covered.)
+  if (state.installing) {
+    return (
+      <div className="fixed inset-0 z-[100] flex flex-col items-center justify-center gap-3 bg-base/90 backdrop-blur-sm">
+        <Loader2 size={28} className="animate-spin text-accent" />
+        <p className="text-sm text-content-secondary">{t('update_installing')}</p>
+      </div>
+    )
+  }
+
+  // Show the panel when it's open AND we either know of an update or hit an
+  // error. Keeping it up on error is important: a failed download must surface
+  // a visible message instead of silently doing nothing.
+  if (!open || (!available && !errored)) return null
+
+  const version = state.version
+  const preparing = state.preparing
+  const downloading = status?.state === 'downloading'
+  const downloaded = status?.state === 'downloaded'
+  // macOS emits a second progress pass (verify) after hitting 100%; show it as
+  // an indeterminate "verifying" state rather than a bar restarting from 0.
+  const verifying = downloading && state.progressPeaked
+  const busy = preparing || downloading
+
+  return (
+    <div className="absolute bottom-2 left-2 right-2 z-40">
+      <div className="rounded-lg border border-default bg-elevated shadow-lg p-3 space-y-2.5">
+        <div className="flex items-start justify-between gap-2">
+          <div className="min-w-0">
+            <p className="text-[13px] font-semibold text-content">
+              {errored ? t('update_failed') : t('update_available')}
+            </p>
+            {!errored && version && (
+              <p className="text-xs text-content-tertiary mt-0.5">v{version}</p>
+            )}
+          </div>
+          <button
+            onClick={() => state.dismiss()}
+            className="text-content-tertiary hover:text-content cursor-pointer flex-shrink-0"
+            title={t('update_later')}
+          >
+            <X size={15} />
+          </button>
+        </div>
+
+          {errored && (
+            <div className="space-y-2.5">
+              <div className="flex items-start gap-2 text-xs text-content-secondary">
+                <AlertTriangle size={13} className="text-amber-500 flex-shrink-0 mt-0.5" />
+                <span className="break-words">
+                  {status?.state === 'error' ? status.message : ''}
+                </span>
+              </div>
+              <button
+                onClick={() => state.download()}
+                className="w-full inline-flex items-center justify-center gap-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover px-3 py-2 text-[13px] font-medium cursor-pointer transition-colors"
+              >
+                <RefreshCw size={15} />
+                {t('update_retry')}
+              </button>
+            </div>
+          )}
+
+          {!errored && preparing && (
+            <div className="flex items-center gap-2 text-xs text-content-secondary py-1">
+              <Loader2 size={13} className="animate-spin" />
+              <span>{t('update_preparing')}</span>
+            </div>
+          )}
+
+          {!errored && downloading && verifying && (
+            <div className="flex items-center gap-2 text-xs text-content-secondary py-1">
+              <Loader2 size={13} className="animate-spin" />
+              <span>{t('update_verifying')}</span>
+            </div>
+          )}
+
+          {!errored && downloading && !verifying && (
+            <div className="space-y-1">
+              <div className="flex items-center gap-2 text-xs text-content-secondary">
+                <Loader2 size={13} className="animate-spin" />
+                <span>{t('update_downloading')} {state.percent}%</span>
+              </div>
+              <div className="h-1.5 w-full rounded-full bg-surface-2 overflow-hidden">
+                <div className="h-full bg-accent transition-[width] duration-200" style={{ width: `${state.percent}%` }} />
+              </div>
+            </div>
+          )}
+
+          {!errored && !busy && !downloaded && (
+            <button
+              onClick={() => state.download()}
+              className="w-full inline-flex items-center justify-center gap-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover px-3 py-2 text-[13px] font-medium cursor-pointer transition-colors"
+            >
+              <Download size={15} />
+              {t('update_download')}
+            </button>
+          )}
+
+          {!errored && downloaded && (
+            <button
+              onClick={() => state.install()}
+              className="w-full inline-flex items-center justify-center gap-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover px-3 py-2 text-[13px] font-medium cursor-pointer transition-colors"
+            >
+              <RefreshCw size={15} />
+              {t('update_restart')}
+            </button>
+          )}
+        </div>
+    </div>
+  )
+}
+
+export default UpdateBanner
diff --git a/desktop/src/renderer/src/components/icons.tsx b/desktop/src/renderer/src/components/icons.tsx
new file mode 100644
index 0000000..cc35bff
--- /dev/null
+++ b/desktop/src/renderer/src/components/icons.tsx
@@ -0,0 +1,16 @@
+import React from 'react'
+
+// Solid paper-plane icon (Font Awesome's fa-paper-plane path) so the send
+// button and the feishu/telegram channels match the web console exactly.
+export const PaperPlaneIcon: React.FC<{ size?: number; className?: string }> = ({ size = 16, className }) => (
+  <svg
+    width={size}
+    height={size}
+    viewBox="0 0 512 512"
+    fill="currentColor"
+    aria-hidden="true"
+    className={className}
+  >
+    <path d="M498.1 5.6c10.1 7 15.4 19.1 13.5 31.2l-64 416c-1.5 9.7-7.4 18.2-16 23s-18.9 5.4-28 1.6L284 427.7l-68.5 74.1c-8.9 9.7-22.9 12.9-35.2 8.1S160 493.2 160 480l0-83.6c0-4 1.5-7.8 4.2-10.8L331.8 202.8c5.8-6.3 5.6-16-.4-22s-15.7-6.4-22-.7L106 360.8 17.7 316.6C7.1 311.3 .3 300.7 0 288.9s5.9-22.8 16.1-28.7l448-256c10.7-6.1 23.9-5.5 34 1.4z" />
+  </svg>
+)
diff --git a/desktop/src/renderer/src/highlight.css b/desktop/src/renderer/src/highlight.css
new file mode 100644
index 0000000..4391c02
--- /dev/null
+++ b/desktop/src/renderer/src/highlight.css
@@ -0,0 +1,189 @@
+/* highlight.js github themes, scoped for light/dark. Generated; do not edit. */
+pre code.hljs {
+  display: block;
+  overflow-x: auto;
+  padding: 1em
+}
+code.hljs {
+  padding: 3px 5px
+}
+/*!
+  Theme: GitHub
+  Description: Light theme as seen on github.com
+  Author: github.com
+  Maintainer: @Hirse
+  Updated: 2021-05-15
+
+  Outdated base version: https://github.com/primer/github-syntax-light
+  Current colors taken from GitHub's CSS
+*/
+.hljs {
+  color: #24292e;
+  background: #ffffff
+}
+.hljs-doctag,
+.hljs-keyword,
+.hljs-meta .hljs-keyword,
+.hljs-template-tag,
+.hljs-template-variable,
+.hljs-type,
+.hljs-variable.language_ {
+  /* prettylights-syntax-keyword */
+  color: #d73a49
+}
+.hljs-title,
+.hljs-title.class_,
+.hljs-title.class_.inherited__,
+.hljs-title.function_ {
+  /* prettylights-syntax-entity */
+  color: #6f42c1
+}
+.hljs-attr,
+.hljs-attribute,
+.hljs-literal,
+.hljs-meta,
+.hljs-number,
+.hljs-operator,
+.hljs-variable,
+.hljs-selector-attr,
+.hljs-selector-class,
+.hljs-selector-id {
+  /* prettylights-syntax-constant */
+  color: #005cc5
+}
+.hljs-regexp,
+.hljs-string,
+.hljs-meta .hljs-string {
+  /* prettylights-syntax-string */
+  color: #032f62
+}
+.hljs-built_in,
+.hljs-symbol {
+  /* prettylights-syntax-variable */
+  color: #e36209
+}
+.hljs-comment,
+.hljs-code,
+.hljs-formula {
+  /* prettylights-syntax-comment */
+  color: #6a737d
+}
+.hljs-name,
+.hljs-quote,
+.hljs-selector-tag,
+.hljs-selector-pseudo {
+  /* prettylights-syntax-entity-tag */
+  color: #22863a
+}
+.hljs-subst {
+  /* prettylights-syntax-storage-modifier-import */
+  color: #24292e
+}
+.hljs-section {
+  /* prettylights-syntax-markup-heading */
+  color: #005cc5;
+  font-weight: bold
+}
+.hljs-bullet {
+  /* prettylights-syntax-markup-list */
+  color: #735c0f
+}
+.hljs-emphasis {
+  /* prettylights-syntax-markup-italic */
+  color: #24292e;
+  font-style: italic
+}
+.hljs-strong {
+  /* prettylights-syntax-markup-bold */
+  color: #24292e;
+  font-weight: bold
+}
+.hljs-addition {
+  /* prettylights-syntax-markup-inserted */
+  color: #22863a;
+  background-color: #f0fff4
+}
+.hljs-deletion {
+  /* prettylights-syntax-markup-deleted */
+  color: #b31d28;
+  background-color: #ffeef0
+}
+.hljs-char.escape_,
+.hljs-link,
+.hljs-params,
+.hljs-property,
+.hljs-punctuation,
+.hljs-tag {
+  /* purposely ignored */
+  
+}
+.dark pre code.hljs {
+  display: block;
+  overflow-x: auto;
+  padding: 1em
+}.dark code.hljs {
+  padding: 3px 5px
+}.dark /*!
+  Theme: GitHub Dark
+  Description: Dark theme as seen on github.com
+  Author: github.com
+  Maintainer: @Hirse
+  Updated: 2021-05-15
+
+  Outdated base version: https://github.com/primer/github-syntax-dark
+  Current colors taken from GitHub's CSS
+*/
+.hljs {
+  color: #c9d1d9;
+  background: #0d1117
+}.dark .hljs-doctag, .dark .hljs-keyword, .dark .hljs-meta .hljs-keyword, .dark .hljs-template-tag, .dark .hljs-template-variable, .dark .hljs-type, .dark .hljs-variable.language_ {
+  /* prettylights-syntax-keyword */
+  color: #ff7b72
+}.dark .hljs-title, .dark .hljs-title.class_, .dark .hljs-title.class_.inherited__, .dark .hljs-title.function_ {
+  /* prettylights-syntax-entity */
+  color: #d2a8ff
+}.dark .hljs-attr, .dark .hljs-attribute, .dark .hljs-literal, .dark .hljs-meta, .dark .hljs-number, .dark .hljs-operator, .dark .hljs-variable, .dark .hljs-selector-attr, .dark .hljs-selector-class, .dark .hljs-selector-id {
+  /* prettylights-syntax-constant */
+  color: #79c0ff
+}.dark .hljs-regexp, .dark .hljs-string, .dark .hljs-meta .hljs-string {
+  /* prettylights-syntax-string */
+  color: #a5d6ff
+}.dark .hljs-built_in, .dark .hljs-symbol {
+  /* prettylights-syntax-variable */
+  color: #ffa657
+}.dark .hljs-comment, .dark .hljs-code, .dark .hljs-formula {
+  /* prettylights-syntax-comment */
+  color: #8b949e
+}.dark .hljs-name, .dark .hljs-quote, .dark .hljs-selector-tag, .dark .hljs-selector-pseudo {
+  /* prettylights-syntax-entity-tag */
+  color: #7ee787
+}.dark .hljs-subst {
+  /* prettylights-syntax-storage-modifier-import */
+  color: #c9d1d9
+}.dark .hljs-section {
+  /* prettylights-syntax-markup-heading */
+  color: #1f6feb;
+  font-weight: bold
+}.dark .hljs-bullet {
+  /* prettylights-syntax-markup-list */
+  color: #f2cc60
+}.dark .hljs-emphasis {
+  /* prettylights-syntax-markup-italic */
+  color: #c9d1d9;
+  font-style: italic
+}.dark .hljs-strong {
+  /* prettylights-syntax-markup-bold */
+  color: #c9d1d9;
+  font-weight: bold
+}.dark .hljs-addition {
+  /* prettylights-syntax-markup-inserted */
+  color: #aff5b4;
+  background-color: #033a16
+}.dark .hljs-deletion {
+  /* prettylights-syntax-markup-deleted */
+  color: #ffdcd7;
+  background-color: #67060c
+}.dark .hljs-char.escape_, .dark .hljs-link, .dark .hljs-params, .dark .hljs-property, .dark .hljs-punctuation, .dark .hljs-tag {
+  /* purposely ignored */
+  
+}
diff --git a/desktop/src/renderer/src/hooks/useBackend.ts b/desktop/src/renderer/src/hooks/useBackend.ts
new file mode 100644
index 0000000..6c3e1ac
--- /dev/null
+++ b/desktop/src/renderer/src/hooks/useBackend.ts
@@ -0,0 +1,156 @@
+import { useState, useEffect, useCallback, useRef } from 'react'
+
+// Fixed default port — MUST match DESKTOP_BACKEND_PORT in main/python-manager.ts.
+// The backend is launched on exactly this port (the main process frees it first
+// and passes it via COW_WEB_PORT), so probing it works even before the
+// getBackendPort IPC resolves. Keeping both sides on one constant means the
+// renderer can never end up talking to the wrong port.
+const BACKEND_PORT = 9876
+
+interface BackendState {
+  status: 'connecting' | 'ready' | 'error'
+  port: number
+  error?: string
+}
+
+export function useBackend() {
+  const [state, setState] = useState<BackendState>({
+    status: 'connecting',
+    port: BACKEND_PORT,
+  })
+  const pollingRef = useRef<ReturnType<typeof setTimeout> | null>(null)
+
+  const probeBackend = useCallback(async (port: number): Promise<boolean> => {
+    try {
+      // Probe the unauthenticated health endpoint, NOT /config: once a
+      // web_password is set, /config returns 401 and we'd wrongly treat the
+      // (healthy) backend as unreachable, hanging on "connecting".
+      const res = await fetch(`http://127.0.0.1:${port}/api/health`, {
+        signal: AbortSignal.timeout(3000),
+      })
+      return res.ok
+    } catch {
+      return false
+    }
+  }, [])
+
+  // True once the backend has answered at least once. After this we never flip
+  // back to "error" from polling — a hidden/backgrounded window throttles JS
+  // timers, so attempt counters are unreliable and would otherwise produce a
+  // false "failed to start" even though the backend is alive.
+  const readyRef = useRef(false)
+  // Holds the latest resolved port so the visibility handler (registered once)
+  // always probes the correct port without re-running the effect.
+  const portRef = useRef(BACKEND_PORT)
+
+  useEffect(() => {
+    let cancelled = false
+    let offStatus: (() => void) | undefined
+    const api = window.electronAPI
+
+    // Use a wall-clock deadline instead of an attempt counter so timer
+    // throttling (when the window is in the background) can't fast-forward us
+    // into a false failure. Only give up if we genuinely can't reach the
+    // backend for this long.
+    const startPolling = async (port: number) => {
+      portRef.current = port
+      const deadline = Date.now() + 90_000
+
+      const poll = async () => {
+        if (cancelled) return
+
+        const ready = await probeBackend(port)
+        if (cancelled) return
+
+        if (ready) {
+          readyRef.current = true
+          setState({ status: 'ready', port })
+          return
+        }
+
+        // Backend already answered before but is briefly unreachable (e.g.
+        // window was asleep): keep retrying, never surface an error.
+        if (!readyRef.current && Date.now() >= deadline) {
+          // Leave error undefined so StatusScreen shows the localized,
+          // user-friendly message instead of a raw technical string.
+          setState({ status: 'error', port })
+          return
+        }
+
+        pollingRef.current = setTimeout(poll, 1000)
+      }
+
+      await poll()
+    }
+
+    if (api) {
+      // Always start polling, even if getBackendPort rejects or the ready event
+      // was already emitted before we subscribed: polling /config is the
+      // self-sufficient path to "ready" and must never depend on the IPC round
+      // trip succeeding (otherwise the app can hang forever on "connecting").
+      api
+        .getBackendPort()
+        .then((port) => {
+          const p = port || BACKEND_PORT
+          portRef.current = p
+          setState((prev) => ({ ...prev, port: p }))
+          startPolling(p)
+        })
+        .catch(() => {
+          startPolling(BACKEND_PORT)
+        })
+
+      offStatus = api.onBackendStatus((data) => {
+        if (data.status === 'ready' && data.port) {
+          readyRef.current = true
+          portRef.current = data.port
+          setState({ status: 'ready', port: data.port })
+          if (pollingRef.current) {
+            clearTimeout(pollingRef.current)
+            pollingRef.current = null
+          }
+        } else if (data.status === 'error' && !readyRef.current) {
+          // Ignore late "error" from the main process once we've been ready —
+          // it usually means the window was backgrounded, not a real failure.
+          // Drop the raw technical message; StatusScreen shows a localized one.
+          setState((prev) => ({ ...prev, status: 'error' }))
+        }
+      })
+    } else {
+      startPolling(BACKEND_PORT)
+    }
+
+    // When the window comes back to the foreground, re-probe immediately so a
+    // user returning after a while sees the real (ready) state right away
+    // instead of waiting for the throttled timer to catch up.
+    const onVisible = () => {
+      if (cancelled || document.visibilityState !== 'visible') return
+      probeBackend(portRef.current).then((ready) => {
+        if (cancelled || !ready) return
+        readyRef.current = true
+        setState((prev) => ({ ...prev, status: 'ready' }))
+      })
+    }
+    document.addEventListener('visibilitychange', onVisible)
+
+    return () => {
+      cancelled = true
+      if (pollingRef.current) {
+        clearTimeout(pollingRef.current)
+      }
+      offStatus?.()
+      document.removeEventListener('visibilitychange', onVisible)
+    }
+  }, [probeBackend])
+
+  const restart = useCallback(async () => {
+    setState((prev) => ({ ...prev, status: 'connecting', error: undefined }))
+    if (window.electronAPI) {
+      await window.electronAPI.restartBackend()
+    }
+  }, [])
+
+  const baseUrl = `http://127.0.0.1:${state.port}`
+
+  return { ...state, baseUrl, restart }
+}
diff --git a/desktop/src/renderer/src/hooks/usePlatform.ts b/desktop/src/renderer/src/hooks/usePlatform.ts
new file mode 100644
index 0000000..b99dbe0
--- /dev/null
+++ b/desktop/src/renderer/src/hooks/usePlatform.ts
@@ -0,0 +1,29 @@
+import { useEffect, useState } from 'react'
+
+export type Platform = 'mac' | 'win' | 'linux'
+
+function detectPlatform(): Platform {
+  const p = window.electronAPI?.platform
+  if (p === 'darwin') return 'mac'
+  if (p === 'win32') return 'win'
+  if (p === 'linux') return 'linux'
+  // Fallback for browser dev without electron
+  if (typeof navigator !== 'undefined' && /Mac/i.test(navigator.platform)) return 'mac'
+  return 'win'
+}
+
+/**
+ * Resolves the host platform and applies a `.platform-*` class on <html>
+ * so CSS can branch on platform (titlebar layout, scrollbars, etc.).
+ */
+export function usePlatform(): { platform: Platform; isMac: boolean; isWin: boolean } {
+  const [platform] = useState<Platform>(detectPlatform)
+
+  useEffect(() => {
+    const root = document.documentElement
+    root.classList.remove('platform-mac', 'platform-win', 'platform-linux')
+    root.classList.add(`platform-${platform}`)
+  }, [platform])
+
+  return { platform, isMac: platform === 'mac', isWin: platform === 'win' }
+}
diff --git a/desktop/src/renderer/src/hooks/useTheme.ts b/desktop/src/renderer/src/hooks/useTheme.ts
new file mode 100644
index 0000000..0f496b1
--- /dev/null
+++ b/desktop/src/renderer/src/hooks/useTheme.ts
@@ -0,0 +1,57 @@
+import { useState, useEffect, useCallback } from 'react'
+
+export type ThemePref = 'light' | 'dark' | 'system'
+export type ResolvedTheme = 'light' | 'dark'
+
+const STORAGE_KEY = 'cow_theme'
+
+function getSystemTheme(): ResolvedTheme {
+  return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'
+}
+
+function readStored(): ThemePref {
+  const saved = localStorage.getItem(STORAGE_KEY)
+  if (saved === 'dark' || saved === 'light' || saved === 'system') return saved
+  // First run: follow the OS appearance rather than forcing a fixed theme.
+  return 'system'
+}
+
+function applyTheme(resolved: ResolvedTheme) {
+  const root = document.documentElement
+  root.classList.toggle('dark', resolved === 'dark')
+}
+
+export function useTheme() {
+  const [pref, setPref] = useState<ThemePref>(readStored)
+  const [resolved, setResolved] = useState<ResolvedTheme>(() =>
+    readStored() === 'system' ? getSystemTheme() : (readStored() as ResolvedTheme)
+  )
+
+  useEffect(() => {
+    const next: ResolvedTheme = pref === 'system' ? getSystemTheme() : pref
+    setResolved(next)
+    applyTheme(next)
+    localStorage.setItem(STORAGE_KEY, pref)
+  }, [pref])
+
+  // Follow system changes only when preference is "system"
+  useEffect(() => {
+    if (pref !== 'system') return
+    const mq = window.matchMedia('(prefers-color-scheme: dark)')
+    const handler = () => {
+      const next = getSystemTheme()
+      setResolved(next)
+      applyTheme(next)
+    }
+    mq.addEventListener('change', handler)
+    return () => mq.removeEventListener('change', handler)
+  }, [pref])
+
+  const toggleTheme = useCallback(() => {
+    setPref(resolved === 'dark' ? 'light' : 'dark')
+  }, [resolved])
+
+  const setTheme = useCallback((next: ThemePref) => setPref(next), [])
+
+  return { theme: resolved, pref, toggleTheme, setTheme }
+}
diff --git a/desktop/src/renderer/src/i18n.ts b/desktop/src/renderer/src/i18n.ts
new file mode 100644
index 0000000..b07e8e7
--- /dev/null
+++ b/desktop/src/renderer/src/i18n.ts
@@ -0,0 +1,799 @@
+const translations: Record<string, Record<string, string>> = {
+  zh: {
+    console: '控制台',
+    nav_chat: '对话',
+    nav_manage: '管理',
+    nav_monitor: '监控',
+    menu_chat: '对话',
+    menu_config: '配置',
+    menu_skills: '技能',
+    menu_memory: '记忆',
+    menu_channels: '通道',
+    menu_tasks: '定时',
+    menu_logs: '日志',
+    menu_models: '模型',
+    menu_knowledge: '知识',
+    menu_settings: '设置',
+    // knowledge
+    knowledge_title: '知识库',
+    knowledge_desc: '浏览和探索你的知识库',
+    knowledge_tab_docs: '文档',
+    knowledge_tab_graph: '图谱',
+    knowledge_search: '搜索文档...',
+    knowledge_stats: '{pages} 篇 · {size}',
+    knowledge_select_hint: '从左侧选择一个文档查看',
+    knowledge_empty: '知识库还是空的',
+    knowledge_empty_guide: '在对话中发送文档、链接或主题给 Agent，它会自动整理到你的知识库中',
+    knowledge_go_chat: '开始对话',
+    knowledge_loading: '加载知识库中...',
+    knowledge_graph_empty: '暂无关联图谱',
+    knowledge_disabled: '知识库未启用',
+    knowledge_doc_load_error: '文档加载失败',
+    // knowledge management
+    knowledge_new: '新建',
+    knowledge_new_category: '新建分类',
+    knowledge_new_document: '新建文档',
+    knowledge_import_documents: '导入文档',
+    knowledge_working: '处理中...',
+    knowledge_importing: '正在导入...',
+    knowledge_request_failed: '请求失败，请稍后重试',
+    knowledge_import_failed: '导入失败',
+    knowledge_category_created: '分类已创建',
+    knowledge_document_created: '文档已创建',
+    knowledge_dialog_confirm: '确定',
+    knowledge_dialog_cancel: '取消',
+    knowledge_field_required: '此项不能为空',
+    knowledge_category_label: '分类路径',
+    knowledge_category_hint: '支持嵌套路径，例如 research/ai',
+    knowledge_category_subtitle: '分类会创建为 knowledge/ 下的目录',
+    knowledge_need_category: '请先创建分类',
+    knowledge_destination: '目标分类',
+    knowledge_doc_choose_category: '先选择分类，然后输入文件名',
+    knowledge_doc_save_to: '保存到 {category}',
+    knowledge_doc_filename: '文件名',
+    knowledge_doc_filename_required: '文件名不能为空',
+    knowledge_doc_must_md: '新建文档仅支持 .md 文件名',
+    knowledge_doc_content: 'Markdown 内容',
+    knowledge_doc_content_required: '内容不能为空',
+    knowledge_doc_content_too_large: '内容不能超过 10MB',
+    knowledge_doc_insert_template: '插入模板',
+    knowledge_import_selected: '已选择 {count} 个文件',
+    knowledge_import_hint: '支持 Markdown 和 TXT，TXT 会转成 Markdown 文档',
+    knowledge_import_need_category: '请先创建一个分类',
+    knowledge_import_choose_files: '请选择 .md 或 .txt 文件',
+    knowledge_import_too_many: '一次最多导入 {max} 个文件',
+    knowledge_import_file_too_large: '{name} 超过 10MB',
+    knowledge_import_total_too_large: '单次导入总大小不能超过 200MB',
+    knowledge_import_result: '导入 {imported} 个，跳过 {skipped} 个，失败 {failed} 个',
+    knowledge_drop_hint: '拖放 .md / .txt 文件到此导入',
+    nav_expand: '展开侧栏',
+    nav_collapse: '收起侧栏',
+    session_history: '历史会话',
+    update_available: '发现新版本',
+    update_download: '下载更新',
+    update_downloading: '正在下载',
+    update_preparing: '正在准备…',
+    update_verifying: '正在校验，即将完成…',
+    update_installing: '正在安装并重启，请稍候…',
+    update_restart: '重启以更新',
+    update_later: '稍后',
+    update_latest: '已是最新版本',
+    update_check: '检查更新',
+    update_checking: '正在检查…',
+    update_failed: '更新失败',
+    update_retry: '重试',
+    menu_more: '更多',
+    menu_theme_light: '浅色模式',
+    menu_theme_dark: '深色模式',
+    menu_language: '语言',
+    menu_website: '官网',
+    menu_docs: '文档中心',
+    menu_skill_hub: '技能广场',
+    menu_feedback: '反馈',
+    // onboarding
+    onboarding_welcome_title: '欢迎使用 CowAgent',
+    onboarding_welcome_desc: '你的私人超级 AI 助手。几步设置，即可开始对话。',
+    onboarding_lang_label: '界面语言',
+    onboarding_model_title: '配置对话模型',
+    onboarding_model_desc: '选择模型厂商并填入 API Key，即可开始使用。',
+    onboarding_provider: '模型厂商',
+    onboarding_select_provider: '选择厂商',
+    onboarding_apikey: 'API Key',
+    onboarding_apikey_placeholder: '输入 API 密钥',
+    onboarding_key_guide: '没有秘钥？前往创建',
+    onboarding_apibase: 'API 地址（可选）',
+    onboarding_model: '模型',
+    onboarding_select_model: '选择模型',
+    onboarding_done_title: '一切就绪',
+    onboarding_done_desc: '配置完成，开始你的第一次对话吧。',
+    onboarding_next: '下一步',
+    onboarding_back: '上一步',
+    onboarding_skip: '跳过',
+    onboarding_finish: '开始对话',
+    onboarding_step: '第 {n} / {total} 步',
+    onboarding_saving: '保存中...',
+    onboarding_save_failed: '保存失败，请检查后重试',
+    sessions_title: '会话',
+    session_new: '新对话',
+    session_rename: '重命名',
+    session_delete: '删除',
+    session_empty: '暂无会话',
+    session_today: '今天',
+    session_yesterday: '昨天',
+    session_earlier: '更早',
+    msg_copy: '复制',
+    msg_copied: '已复制',
+    msg_regenerate: '重新生成',
+    msg_edit: '编辑',
+    msg_delete: '删除',
+    msg_cancelled: '已中止',
+    msg_self_learned: '自主学习',
+    msg_stop: '停止',
+    chat_clear_context: '清除上下文',
+    chat_load_earlier: '加载更早的消息',
+    chat_send: '发送',
+    chat_attach: '添加附件',
+    slash_hint: '输入 / 查看命令',
+    chat_welcome: '有什么可以帮你的？',
+    chat_empty_hint: '发送一条消息开始对话',
+    welcome_subtitle: '我可以帮你解答问题、管理你的电脑、创建并执行技能，\n还能通过长期记忆不断成长。',
+    example_sys_title: '系统管理',
+    example_sys_text: '查看工作空间里有哪些文件',
+    example_task_title: '定时任务',
+    example_task_text: '1分钟后提醒我检查服务器',
+    example_code_title: '编程助手',
+    example_code_text: '搜索AI资讯生成可视化网页报告',
+    example_knowledge_title: '知识库',
+    example_knowledge_text: '查看知识库当前文档情况',
+    example_skill_title: '技能系统',
+    example_skill_text: '查看所有支持的工具和技能',
+    example_web_title: '指令中心',
+    example_web_text: '查看全部命令',
+    input_placeholder: '输入消息...',
+    config_title: '配置管理',
+    config_desc: '管理模型和 Agent 配置',
+    config_model: '模型配置',
+    config_agent: 'Agent 配置',
+    config_provider: '模型厂商',
+    config_model_name: '模型',
+    config_custom_model_hint: '输入自定义模型名称',
+    config_save: '保存',
+    config_saved: '已保存',
+    config_save_error: '保存失败',
+    config_custom_option: '自定义',
+    config_max_tokens: '最大上下文 Token',
+    config_max_turns: '最大记忆轮次',
+    config_max_steps: '最大执行步数',
+    config_max_tokens_hint: '对话中 Agent 能输入的最大 Token 长度，超过后会智能压缩处理',
+    config_max_turns_hint: '一问一答为一轮，超过后会智能压缩处理',
+    config_max_steps_hint: '单次对话中 Agent 最多调用工具的次数',
+    config_thinking: '深度思考',
+    config_thinking_hint: '是否启用深度思考模式',
+    config_evolution: '自主进化',
+    config_evolution_hint: '会话空闲后自动复盘，沉淀记忆、优化技能、处理未完成事项',
+    config_security: '安全设置',
+    config_password: '访问密码',
+    config_password_hint: '留空则不启用密码保护',
+    config_password_placeholder: '留空表示不设密码',
+    config_password_saved: '密码已更新，请重新登录',
+    config_password_cleared: '密码已清除',
+    config_language: '语言',
+    config_language_hint: '界面与回复语言',
+    config_credentials_link: 'API Key 与接口地址请在「模型配置」中设置',
+    config_goto_models: '前往配置',
+    config_provider_unconfigured: '未配置',
+    config_provider_unconfigured_hint: '该厂商尚未配置 API Key，请先前往配置',
+    config_cancel: '取消',
+    // settings tabs
+    settings_tab_basic: '基础配置',
+    settings_tab_models: '模型配置',
+    // models tab
+    models_vendors: '厂商凭据',
+    models_vendors_sub: '一处配置，多个模型能力共享',
+    models_configured: '已配置',
+    models_no_vendor: '尚未配置任何厂商',
+    models_add_vendor: '添加厂商',
+    models_custom_vendor: '自定义',
+    models_add_custom: '添加自定义厂商',
+    models_add_custom_hint: '接口需遵循 OpenAI API 协议',
+    models_edit_custom: '编辑自定义厂商',
+    models_custom_name: '名称',
+    models_custom_base_hint: '接口需遵循 OpenAI API 协议',
+    models_clear: '清除凭据',
+    models_delete: '删除',
+    models_clear_confirm: '确认清除该厂商的 API Key 与 Base URL 吗？相关能力将不再可用。',
+    models_delete_confirm: '确定删除该自定义厂商吗？此操作无法撤销。',
+    models_provider: '厂商',
+    models_model: '模型',
+    models_voice: '音色',
+    models_select_provider: '待选择',
+    models_select_model: '请选择模型',
+    models_select_voice: '请选择音色',
+    models_no_options: '暂无可选项',
+    models_auto: '自动',
+    models_asr_auto: '自动（跟随主模型）',
+    models_disabled: '不启用',
+    models_fallback: '兜底',
+    models_cap_chat: '主模型',
+    models_cap_chat_sub: '用于基础对话和 Agent 推理',
+    models_cap_vision: '图像理解',
+    models_cap_vision_sub: '识别图片内容，用于图像识别工具',
+    models_cap_image: '图像生成',
+    models_cap_image_sub: '生成图片，用于图像生成技能',
+    models_cap_asr: '语音识别',
+    models_cap_asr_sub: '语音转文字',
+    models_cap_tts: '语音合成',
+    models_cap_tts_sub: '文字转语音',
+    models_cap_embedding: '向量',
+    models_cap_embedding_sub: '用于记忆与知识的向量化检索',
+    models_cap_search: '联网搜索',
+    models_cap_search_sub: '实时网页检索能力，用于搜索工具',
+    models_tts_reply_mode: '语音回复模式',
+    models_tts_reply_mode_hint: '决定何时以语音回复用户',
+    models_tts_mode_off: '关闭',
+    models_tts_mode_if_voice: '仅当用户发语音时',
+    models_tts_mode_always: '始终语音回复',
+    models_embedding_dim: '维度',
+    models_embedding_rebuild_hint: '切换向量模型后，已有索引将失效，需要重建',
+    models_search_strategy: '策略',
+    models_search_auto: '自动',
+    models_search_fixed: '指定',
+    models_search_provider: '搜索厂商',
+    models_search_bocha_key: '配置博查 API Key',
+    models_search_bocha_hint: '前往博查开放平台创建 API Key',
+    skills_title: '技能管理',
+    skills_desc: '查看、启用或禁用 Agent 工具和技能',
+    skills_hub_btn: '探索技能广场',
+    tools_section_title: '内置工具',
+    skills_section_title: '技能',
+    tools_loading: '加载工具中...',
+    skills_loading: '加载技能中...',
+    skills_loading_desc: '技能将在加载后显示',
+    skill_enabled: '已启用',
+    skill_disabled: '已禁用',
+    tools_empty: '暂无内置工具',
+    skills_empty: '暂无技能',
+    memory_title: '记忆管理',
+    memory_desc: '查看 Agent 记忆文件和内容',
+    memory_tab_files: '记忆文件',
+    memory_tab_dreams: '自主进化',
+    memory_loading: '加载记忆文件中...',
+    memory_loading_desc: '记忆文件将在加载后显示',
+    memory_col_name: '文件名',
+    memory_col_type: '类型',
+    memory_col_size: '大小',
+    memory_col_updated: '更新时间',
+    memory_back: '返回列表',
+    memory_empty_files: '暂无记忆文件',
+    memory_empty_evolution: '暂无进化记录',
+    memory_type_global: '全局',
+    memory_type_daily: '每日',
+    memory_type_evolution: '进化',
+    memory_type_dream: '梦境',
+    memory_doc_load_error: '内容加载失败',
+    memory_prev: '上一页',
+    memory_next: '下一页',
+    channels_title: '通道管理',
+    channels_desc: '查看和管理消息通道',
+    channels_add: '接入通道',
+    channels_select_label: '选择要接入的通道',
+    channels_select_placeholder: '请选择通道...',
+    channels_add_close: '关闭',
+    channels_connected: '已连接',
+    channels_disconnected: '未连接',
+    channels_connect: '连接',
+    channels_disconnect: '断开',
+    channels_save: '保存',
+    channels_loading: '加载通道中...',
+    channels_connected_section: '已连接',
+    channels_available_section: '可添加',
+    channels_empty_connected: '暂无已连接的通道',
+    channels_qr_hint: '该通道通过扫码登录，请前往 Web 控制台完成扫码连接',
+    channels_save_ok: '已保存',
+    channels_save_error: '保存失败',
+    channels_connect_error: '连接失败',
+    channels_scan_login: '扫码登录',
+    channels_scan_register: '扫码注册',
+    weixin_scan_title: '微信扫码登录',
+    weixin_scan_desc: '使用微信扫描下方二维码登录',
+    weixin_scan_loading: '正在获取二维码...',
+    weixin_scan_waiting: '等待扫码',
+    weixin_scan_scanned: '已扫描，请在手机上确认',
+    weixin_scan_success: '登录成功',
+    weixin_scan_expired: '二维码已过期，正在刷新...',
+    weixin_scan_fail: '获取二维码失败',
+    weixin_qr_tip: '请使用登录的微信扫码',
+    feishu_scan_title: '飞书扫码注册',
+    feishu_scan_desc: '扫码后将自动创建并连接飞书机器人',
+    feishu_scan_loading: '正在生成二维码...',
+    feishu_scan_waiting: '请使用飞书扫码授权',
+    feishu_scan_tip: '扫码后在飞书中确认授权',
+    feishu_scan_open_link: '打开授权链接',
+    feishu_scan_success: '注册成功',
+    feishu_scan_expired: '二维码已过期',
+    feishu_scan_denied: '授权被拒绝',
+    feishu_scan_fail: '注册失败',
+    feishu_scan_retry: '重试',
+    tasks_title: '定时任务',
+    tasks_desc: '查看和管理定时任务',
+    tasks_active: '运行中',
+    tasks_paused: '已暂停',
+    tasks_empty: '暂无定时任务',
+    tasks_empty_guide: '在对话中告诉 Agent「每天 9 点提醒我…」即可创建定时任务',
+    tasks_go_chat: '去对话创建',
+    tasks_next_run: '下次执行',
+    tasks_loading: '加载定时任务中...',
+    task_edit_title: '编辑任务',
+    task_name: '名称',
+    task_enabled: '启用',
+    task_schedule_type: '调度类型',
+    task_type_cron: 'Cron 表达式',
+    task_type_interval: '固定间隔',
+    task_type_once: '单次执行',
+    task_cron_expr: 'Cron 表达式',
+    task_cron_hint: '如 0 9 * * * 表示每天 9 点',
+    task_interval_seconds: '间隔（秒）',
+    task_once_time: '执行时间',
+    task_action_type: '动作类型',
+    task_action_send: '发送消息',
+    task_action_agent: 'Agent 任务',
+    task_message_content: '消息内容',
+    task_task_description: '任务描述',
+    task_channel: '通道',
+    task_receiver: '接收者',
+    task_channel_locked: '通道与接收者创建后不可修改',
+    task_save: '保存',
+    task_cancel: '取消',
+    task_delete: '删除',
+    task_delete_confirm: '确定删除该任务吗？此操作不可撤销。',
+    task_save_error: '保存失败',
+    logs_title: '日志',
+    logs_desc: '实时日志输出 (run.log)',
+    logs_live: '实时',
+    logs_connecting: '日志流将在连接后显示...',
+    status_starting: '正在启动 CowAgent...',
+    status_starting_desc: '正在初始化客户端，请稍候',
+    status_error: '初始化失败',
+    status_error_desc: '客户端初始化失败，请重试',
+    status_retry: '重试',
+    // login (web_password)
+    login_title: '请输入访问密码',
+    login_desc: '此客户端已设置访问密码，请输入以继续',
+    login_placeholder: '访问密码',
+    login_submit: '进入',
+    login_error: '密码错误，请重试',
+    login_checking: '验证中...',
+    // slash command descriptions
+    slash_menu_title: '命令',
+    slash_new: '新建对话',
+    slash_clear: '清除对话上下文',
+    slash_help: '显示命令帮助',
+    slash_status: '查看运行状态',
+    slash_context: '查看对话上下文',
+    slash_skill_list: '查看已安装技能',
+    slash_skill_search: '搜索技能',
+    slash_skill_install: '安装技能 (名称或 GitHub URL)',
+    slash_memory_dream: '手动触发记忆蒸馏 (可指定天数, 默认3)',
+    slash_knowledge: '查看知识库统计',
+    slash_knowledge_list: '查看知识库文件树',
+    slash_config: '查看当前配置',
+    slash_cancel: '中止当前正在运行的 Agent 任务',
+    slash_logs: '查看最近日志',
+    slash_version: '查看版本',
+  },
+  en: {
+    console: 'Console',
+    nav_chat: 'Chat',
+    nav_manage: 'Management',
+    nav_monitor: 'Monitor',
+    menu_chat: 'Chat',
+    menu_config: 'Config',
+    menu_skills: 'Skills',
+    menu_memory: 'Memory',
+    menu_channels: 'Channels',
+    menu_tasks: 'Tasks',
+    menu_logs: 'Logs',
+    menu_models: 'Models',
+    menu_knowledge: 'Knowledge',
+    // knowledge
+    knowledge_title: 'Knowledge Base',
+    knowledge_desc: 'Browse and explore your knowledge base',
+    knowledge_tab_docs: 'Documents',
+    knowledge_tab_graph: 'Graph',
+    knowledge_search: 'Search documents...',
+    knowledge_stats: '{pages} pages · {size}',
+    knowledge_select_hint: 'Select a document to view',
+    knowledge_empty: 'Your knowledge base is empty',
+    knowledge_empty_guide: 'Send documents, links or topics to the agent in chat — it will organize them into your knowledge base',
+    knowledge_go_chat: 'Start chatting',
+    knowledge_loading: 'Loading knowledge base...',
+    knowledge_graph_empty: 'No graph available',
+    knowledge_disabled: 'Knowledge base is disabled',
+    knowledge_doc_load_error: 'Failed to load document',
+    // knowledge management
+    knowledge_new: 'New',
+    knowledge_new_category: 'New category',
+    knowledge_new_document: 'New document',
+    knowledge_import_documents: 'Import documents',
+    knowledge_working: 'Working...',
+    knowledge_importing: 'Importing...',
+    knowledge_request_failed: 'Request failed, please try again',
+    knowledge_import_failed: 'Import failed',
+    knowledge_category_created: 'Category created',
+    knowledge_document_created: 'Document created',
+    knowledge_dialog_confirm: 'Confirm',
+    knowledge_dialog_cancel: 'Cancel',
+    knowledge_field_required: 'This field is required',
+    knowledge_category_label: 'Category path',
+    knowledge_category_hint: 'Nested paths are supported, e.g. research/ai',
+    knowledge_category_subtitle: 'Creates a directory under knowledge/',
+    knowledge_need_category: 'Create a category first',
+    knowledge_destination: 'Destination category',
+    knowledge_doc_choose_category: 'Choose a category, then enter a filename',
+    knowledge_doc_save_to: 'Save to {category}',
+    knowledge_doc_filename: 'Filename',
+    knowledge_doc_filename_required: 'Filename is required',
+    knowledge_doc_must_md: 'New documents must be .md files',
+    knowledge_doc_content: 'Markdown content',
+    knowledge_doc_content_required: 'Content is required',
+    knowledge_doc_content_too_large: 'Content cannot exceed 10MB',
+    knowledge_doc_insert_template: 'Insert template',
+    knowledge_import_selected: '{count} file(s) selected',
+    knowledge_import_hint: 'Markdown and TXT are supported. TXT is converted to Markdown.',
+    knowledge_import_need_category: 'Create a category first',
+    knowledge_import_choose_files: 'Choose .md or .txt files',
+    knowledge_import_too_many: 'Import at most {max} files at a time',
+    knowledge_import_file_too_large: '{name} exceeds 10MB',
+    knowledge_import_total_too_large: 'Total import size cannot exceed 200MB',
+    knowledge_import_result: '{imported} imported · {skipped} skipped · {failed} failed',
+    knowledge_drop_hint: 'Drop .md / .txt files here to import',
+    menu_settings: 'Settings',
+    nav_expand: 'Expand sidebar',
+    nav_collapse: 'Collapse sidebar',
+    session_history: 'Chat history',
+    update_available: 'New version available',
+    update_download: 'Download update',
+    update_downloading: 'Downloading',
+    update_preparing: 'Preparing…',
+    update_verifying: 'Verifying, almost done…',
+    update_installing: 'Installing and restarting, please wait…',
+    update_restart: 'Restart to update',
+    update_later: 'Later',
+    update_latest: 'You are up to date',
+    update_check: 'Check for updates',
+    update_checking: 'Checking…',
+    update_failed: 'Update failed',
+    update_retry: 'Retry',
+    menu_more: 'More',
+    menu_theme_light: 'Light mode',
+    menu_theme_dark: 'Dark mode',
+    menu_language: 'Language',
+    menu_website: 'Website',
+    menu_docs: 'Documentation',
+    menu_skill_hub: 'Skill Hub',
+    menu_feedback: 'Feedback',
+    // onboarding
+    onboarding_welcome_title: 'Welcome to CowAgent',
+    onboarding_welcome_desc: 'Your personal super AI assistant. A few quick steps and you are ready to chat.',
+    onboarding_lang_label: 'Language',
+    onboarding_model_title: 'Set up your chat model',
+    onboarding_model_desc: 'Pick a provider and paste its API key to get started.',
+    onboarding_provider: 'Provider',
+    onboarding_select_provider: 'Select a provider',
+    onboarding_apikey: 'API Key',
+    onboarding_apikey_placeholder: 'Enter your API key',
+    onboarding_key_guide: 'No key yet? Create one',
+    onboarding_apibase: 'API base (optional)',
+    onboarding_model: 'Model',
+    onboarding_select_model: 'Select a model',
+    onboarding_done_title: 'All set',
+    onboarding_done_desc: 'Setup complete. Start your first conversation.',
+    onboarding_next: 'Next',
+    onboarding_back: 'Back',
+    onboarding_skip: 'Skip',
+    onboarding_finish: 'Start chatting',
+    onboarding_step: 'Step {n} of {total}',
+    onboarding_saving: 'Saving...',
+    onboarding_save_failed: 'Save failed, please check and retry',
+    sessions_title: 'Chats',
+    session_new: 'New chat',
+    session_rename: 'Rename',
+    session_delete: 'Delete',
+    session_empty: 'No conversations yet',
+    session_today: 'Today',
+    session_yesterday: 'Yesterday',
+    session_earlier: 'Earlier',
+    msg_copy: 'Copy',
+    msg_copied: 'Copied',
+    msg_regenerate: 'Regenerate',
+    msg_edit: 'Edit',
+    msg_delete: 'Delete',
+    msg_cancelled: 'Cancelled',
+    msg_self_learned: 'Self-learned',
+    msg_stop: 'Stop',
+    chat_clear_context: 'Clear context',
+    chat_load_earlier: 'Load earlier messages',
+    chat_send: 'Send',
+    chat_attach: 'Attach file',
+    slash_hint: 'Type / for commands',
+    chat_welcome: 'How can I help you?',
+    chat_empty_hint: 'Send a message to start the conversation',
+    welcome_subtitle: 'I can help you answer questions, manage your computer, create and execute skills,\nand keep growing through long-term memory.',
+    example_sys_title: 'System',
+    example_sys_text: 'Show me the files in the workspace',
+    example_task_title: 'Scheduled Task',
+    example_task_text: 'Remind me to check the server in 1 minute',
+    example_code_title: 'Coding',
+    example_code_text: 'Search AI news and build a visual web report',
+    example_knowledge_title: 'Knowledge Base',
+    example_knowledge_text: 'Show the current documents in the knowledge base',
+    example_skill_title: 'Skills',
+    example_skill_text: 'Show all supported tools and skills',
+    example_web_title: 'Commands',
+    example_web_text: 'Show all commands',
+    input_placeholder: 'Type a message...',
+    config_title: 'Configuration',
+    config_desc: 'Manage model and agent settings',
+    config_model: 'Model Configuration',
+    config_agent: 'Agent Configuration',
+    config_provider: 'Provider',
+    config_model_name: 'Model',
+    config_custom_model_hint: 'Enter custom model name',
+    config_save: 'Save',
+    config_saved: 'Saved',
+    config_save_error: 'Save failed',
+    config_custom_option: 'Custom',
+    config_max_tokens_hint: 'Max token length the Agent can take in; longer context is compressed automatically',
+    config_max_turns_hint: 'One question and answer is a turn; older turns are compressed automatically',
+    config_max_steps_hint: 'Max tool calls the Agent can make in one turn',
+    config_thinking: 'Deep Thinking',
+    config_thinking_hint: 'Whether to enable deep thinking mode',
+    config_evolution: 'Self-Evolution',
+    config_evolution_hint: 'Review automatically when idle: consolidate memory, refine skills, finish pending tasks',
+    config_security: 'Security',
+    config_password: 'Access Password',
+    config_password_hint: 'Leave empty to disable password protection',
+    config_password_placeholder: 'Leave empty for no password',
+    config_password_saved: 'Password updated, please log in again',
+    config_password_cleared: 'Password cleared',
+    config_language: 'Language',
+    config_language_hint: 'Interface and reply language',
+    config_credentials_link: 'Set API key and endpoint in "Models"',
+    config_goto_models: 'Configure',
+    config_provider_unconfigured: 'Not configured',
+    config_provider_unconfigured_hint: 'This provider has no API key yet — configure it first',
+    config_cancel: 'Cancel',
+    // settings tabs
+    settings_tab_basic: 'Basic',
+    settings_tab_models: 'Models',
+    // models tab
+    models_vendors: 'Provider Credentials',
+    models_vendors_sub: 'Configured once, shared by multiple model capabilities',
+    models_configured: 'configured',
+    models_no_vendor: 'No provider configured yet',
+    models_add_vendor: 'Add Provider',
+    models_custom_vendor: 'Custom',
+    models_add_custom: 'Add custom provider',
+    models_add_custom_hint: 'Endpoint must follow the OpenAI API protocol',
+    models_edit_custom: 'Edit custom provider',
+    models_custom_name: 'Name',
+    models_custom_base_hint: 'Endpoint must follow the OpenAI API protocol',
+    models_clear: 'Clear credentials',
+    models_delete: 'Delete',
+    models_clear_confirm: 'Clear the API key and base URL for this provider? Related capabilities will stop working.',
+    models_delete_confirm: 'Delete this custom provider? This cannot be undone.',
+    models_provider: 'Provider',
+    models_model: 'Model',
+    models_voice: 'Voice',
+    models_select_provider: 'Select',
+    models_select_model: 'Select a model',
+    models_select_voice: 'Select a voice',
+    models_no_options: 'No options',
+    models_auto: 'Auto',
+    models_asr_auto: 'Auto (follow main model)',
+    models_disabled: 'Disabled',
+    models_fallback: 'Fallback',
+    models_cap_chat: 'Main Model',
+    models_cap_chat_sub: 'Used for basic chat and agent reasoning',
+    models_cap_vision: 'Image Understanding',
+    models_cap_vision_sub: 'Recognizes image content, used by image recognition tools',
+    models_cap_image: 'Image Generation',
+    models_cap_image_sub: 'Generates images, used by image generation skills',
+    models_cap_asr: 'Speech Recognition',
+    models_cap_asr_sub: 'Voice to text',
+    models_cap_tts: 'Speech Synthesis',
+    models_cap_tts_sub: 'Text to voice',
+    models_cap_embedding: 'Embedding',
+    models_cap_embedding_sub: 'Used for vectorized retrieval of memory and knowledge',
+    models_cap_search: 'Web Search',
+    models_cap_search_sub: 'Real-time web retrieval, used by search tools',
+    models_tts_reply_mode: 'Voice Reply Mode',
+    models_tts_reply_mode_hint: 'When to reply with voice',
+    models_tts_mode_off: 'Off',
+    models_tts_mode_if_voice: 'Only when user sends voice',
+    models_tts_mode_always: 'Always reply with voice',
+    models_embedding_dim: 'Dimension',
+    models_embedding_rebuild_hint: 'Existing index becomes invalid and must be rebuilt after changing the model',
+    models_search_strategy: 'Strategy',
+    models_search_auto: 'Auto',
+    models_search_fixed: 'Pinned',
+    models_search_provider: 'Search provider',
+    models_search_bocha_key: 'Configure Bocha API Key',
+    models_search_bocha_hint: 'Create a key at the Bocha open platform',
+    config_max_tokens: 'Max Context Tokens',
+    config_max_turns: 'Max Memory Turns',
+    config_max_steps: 'Max Steps',
+    skills_title: 'Skills',
+    skills_desc: 'View, enable, or disable agent tools and skills',
+    skills_hub_btn: 'Skill Hub',
+    tools_section_title: 'Built-in Tools',
+    skills_section_title: 'Skills',
+    tools_loading: 'Loading tools...',
+    skills_loading: 'Loading skills...',
+    skills_loading_desc: 'Skills will be displayed here after loading',
+    skill_enabled: 'Enabled',
+    skill_disabled: 'Disabled',
+    tools_empty: 'No built-in tools',
+    skills_empty: 'No skills found',
+    memory_title: 'Memory',
+    memory_desc: 'View agent memory files and contents',
+    memory_tab_files: 'Memory Files',
+    memory_tab_dreams: 'Self-Evolution',
+    memory_loading: 'Loading memory files...',
+    memory_loading_desc: 'Memory files will be displayed here',
+    memory_col_name: 'Filename',
+    memory_col_type: 'Type',
+    memory_col_size: 'Size',
+    memory_col_updated: 'Updated',
+    memory_back: 'Back to list',
+    memory_empty_files: 'No memory files',
+    memory_empty_evolution: 'No evolution records yet',
+    memory_type_global: 'Global',
+    memory_type_daily: 'Daily',
+    memory_type_evolution: 'Evolution',
+    memory_type_dream: 'Dream',
+    memory_doc_load_error: 'Failed to load content',
+    memory_prev: 'Prev',
+    memory_next: 'Next',
+    channels_title: 'Channels',
+    channels_desc: 'View and manage messaging channels',
+    channels_add: 'Add channel',
+    channels_select_label: 'Select a channel to add',
+    channels_select_placeholder: 'Select a channel...',
+    channels_add_close: 'Close',
+    channels_connected: 'Connected',
+    channels_disconnected: 'Disconnected',
+    channels_connect: 'Connect',
+    channels_disconnect: 'Disconnect',
+    channels_save: 'Save',
+    channels_loading: 'Loading channels...',
+    channels_connected_section: 'Connected',
+    channels_available_section: 'Available',
+    channels_empty_connected: 'No connected channels yet',
+    channels_qr_hint: 'This channel uses QR login — please connect it from the Web console',
+    channels_save_ok: 'Saved',
+    channels_save_error: 'Failed to save',
+    channels_connect_error: 'Failed to connect',
+    channels_scan_login: 'QR login',
+    channels_scan_register: 'QR register',
+    weixin_scan_title: 'WeChat QR Login',
+    weixin_scan_desc: 'Scan the QR code below with WeChat to log in',
+    weixin_scan_loading: 'Fetching QR code...',
+    weixin_scan_waiting: 'Waiting for scan',
+    weixin_scan_scanned: 'Scanned, please confirm on your phone',
+    weixin_scan_success: 'Logged in',
+    weixin_scan_expired: 'QR code expired, refreshing...',
+    weixin_scan_fail: 'Failed to fetch QR code',
+    weixin_qr_tip: 'Scan with the WeChat account to log in',
+    feishu_scan_title: 'Feishu QR Register',
+    feishu_scan_desc: 'Scanning will create and connect a Feishu bot automatically',
+    feishu_scan_loading: 'Generating QR code...',
+    feishu_scan_waiting: 'Scan with Feishu to authorize',
+    feishu_scan_tip: 'Confirm the authorization in Feishu after scanning',
+    feishu_scan_open_link: 'Open authorization link',
+    feishu_scan_success: 'Registered',
+    feishu_scan_expired: 'QR code expired',
+    feishu_scan_denied: 'Authorization denied',
+    feishu_scan_fail: 'Registration failed',
+    feishu_scan_retry: 'Retry',
+    tasks_title: 'Scheduled Tasks',
+    tasks_desc: 'View and manage scheduled tasks',
+    tasks_active: 'Active',
+    tasks_paused: 'Paused',
+    tasks_empty: 'No scheduled tasks',
+    tasks_empty_guide: 'Tell the agent "remind me every day at 9am…" in chat to create a scheduled task',
+    tasks_go_chat: 'Create in chat',
+    tasks_next_run: 'Next run',
+    tasks_loading: 'Loading scheduled tasks...',
+    task_edit_title: 'Edit Task',
+    task_name: 'Name',
+    task_enabled: 'Enabled',
+    task_schedule_type: 'Schedule type',
+    task_type_cron: 'Cron',
+    task_type_interval: 'Interval',
+    task_type_once: 'Once',
+    task_cron_expr: 'Cron expression',
+    task_cron_hint: 'e.g. 0 9 * * * runs daily at 9am',
+    task_interval_seconds: 'Interval (seconds)',
+    task_once_time: 'Run at',
+    task_action_type: 'Action type',
+    task_action_send: 'Send message',
+    task_action_agent: 'Agent task',
+    task_message_content: 'Message content',
+    task_task_description: 'Task description',
+    task_channel: 'Channel',
+    task_receiver: 'Receiver',
+    task_channel_locked: 'Channel and receiver cannot be changed after creation',
+    task_save: 'Save',
+    task_cancel: 'Cancel',
+    task_delete: 'Delete',
+    task_delete_confirm: 'Delete this task? This cannot be undone.',
+    task_save_error: 'Failed to save',
+    logs_title: 'Logs',
+    logs_desc: 'Real-time log output (run.log)',
+    logs_live: 'Live',
+    logs_connecting: 'Log streaming will connect shortly...',
+    status_starting: 'Starting CowAgent...',
+    status_starting_desc: 'Initializing the client, please wait',
+    status_error: 'Initialization Failed',
+    status_error_desc: 'Failed to initialize the client, please retry',
+    status_retry: 'Retry',
+    // login (web_password)
+    login_title: 'Enter access password',
+    login_desc: 'This client is password-protected. Enter the password to continue.',
+    login_placeholder: 'Access password',
+    login_submit: 'Enter',
+    login_error: 'Wrong password, please try again',
+    login_checking: 'Verifying...',
+    // slash command descriptions
+    slash_menu_title: 'Commands',
+    slash_new: 'New chat',
+    slash_clear: 'Clear conversation context',
+    slash_help: 'Show command help',
+    slash_status: 'Show running status',
+    slash_context: 'Show conversation context',
+    slash_skill_list: 'List installed skills',
+    slash_skill_search: 'Search skills',
+    slash_skill_install: 'Install a skill (name or GitHub URL)',
+    slash_memory_dream: 'Trigger memory distillation (optional days, default 3)',
+    slash_knowledge: 'Show knowledge base stats',
+    slash_knowledge_list: 'Show knowledge base file tree',
+    slash_config: 'Show current config',
+    slash_cancel: 'Abort the running agent task',
+    slash_logs: 'Show recent logs',
+    slash_version: 'Show version',
+  },
+}
+
+export type Lang = 'zh' | 'en'
+
+// First-run default: follow the OS language so zh-* systems start in Chinese
+// and everyone else in English. Once the user picks a language it's persisted
+// in cow_lang and always wins. Falls back to 'en' when the locale is unknown.
+function detectDefaultLang(): Lang {
+  const locale = (window.electronAPI?.systemLocale || navigator.language || '').toLowerCase()
+  return locale.startsWith('zh') ? 'zh' : 'en'
+}
+
+const savedLang = localStorage.getItem('cow_lang') as Lang | null
+let currentLang: Lang = savedLang === 'zh' || savedLang === 'en' ? savedLang : detectDefaultLang()
+
+export function t(key: string): string {
+  return translations[currentLang]?.[key] || translations['en']?.[key] || key
+}
+
+export function getLang(): Lang {
+  return currentLang
+}
+
+export function setLang(lang: Lang) {
+  currentLang = lang
+  localStorage.setItem('cow_lang', lang)
+}
+
+/** Resolve a possibly-localized label ({zh,en} or plain string) for the current language. */
+export function localizedLabel(label: string | { zh: string; en: string } | undefined): string {
+  if (!label) return ''
+  if (typeof label === 'string') return label
+  return label[currentLang] || label.en || label.zh || ''
+}
diff --git a/desktop/src/renderer/src/index.css b/desktop/src/renderer/src/index.css
new file mode 100644
index 0000000..b290cf9
--- /dev/null
+++ b/desktop/src/renderer/src/index.css
@@ -0,0 +1,335 @@
+@import './highlight.css';
+
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+/* ============================================================
+   Design tokens — semantic CSS variables driving both themes.
+   Components reference these via Tailwind semantic classes
+   (bg-surface, text-primary, border-default, etc.), so theme
+   switching only swaps variable values, never component code.
+   ============================================================ */
+
+:root {
+  /* Brand accent (CowAgent green), used sparingly */
+  --accent: #4abe6e;
+  --accent-hover: #35a85b;
+  --accent-active: #228547;
+  --accent-soft: rgba(74, 190, 110, 0.12);
+  --accent-contrast: #ffffff;
+
+  /* Status colors */
+  --success: #4abe6e;
+  --warning: #f59e0b;
+  --danger: #ef4444;
+  --danger-soft: rgba(239, 68, 68, 0.1);
+  --danger-border: rgba(239, 68, 68, 0.3);
+  --info: #3b82f6;
+
+  /* Light theme — layered neutral surfaces */
+  --bg-base: #fafafa;        /* app background */
+  --bg-surface: #ffffff;     /* panels, cards */
+  --bg-surface-2: #f4f4f5;   /* nested surfaces, hover fills */
+  --bg-elevated: #ffffff;    /* popovers, menus, modals */
+  --bg-inset: #f4f4f5;       /* inputs, code blocks */
+
+  --text-primary: #18181b;   /* headings, primary text (contrast > 4.5:1) */
+  --text-secondary: #52525b; /* body, labels */
+  --text-tertiary: #71717a;  /* hints, captions */
+  --text-disabled: #a1a1aa;
+
+  --border-default: #e4e4e7;
+  --border-strong: #d4d4d8;
+  --border-subtle: #f0f0f1;
+
+  --overlay: rgba(0, 0, 0, 0.4);
+  --shadow-sm: 0 1px 2px rgba(0, 0, 0, 0.04), 0 1px 3px rgba(0, 0, 0, 0.06);
+  --shadow-md: 0 2px 8px rgba(0, 0, 0, 0.06), 0 4px 16px rgba(0, 0, 0, 0.08);
+  --shadow-lg: 0 8px 30px rgba(0, 0, 0, 0.12);
+
+  /* Chat-specific tokens (AI-Native UI) */
+  --ai-bubble-bg: transparent;
+  --message-gap: 16px;
+
+  color-scheme: light;
+}
+
+.dark {
+  /* Dark theme — layered greys instead of harsh pure black */
+  --bg-base: #0e0e10;
+  --bg-surface: #161618;
+  --bg-surface-2: #1c1c1f;
+  --bg-elevated: #1f1f23;
+  --bg-inset: #161618;
+
+  --text-primary: #f4f4f5;     /* contrast > 7:1 on bg-base */
+  --text-secondary: #c4c4cc;
+  --text-tertiary: #8e8e96;
+  --text-disabled: #5a5a62;
+
+  --border-default: rgba(255, 255, 255, 0.08);
+  --border-strong: rgba(255, 255, 255, 0.14);
+  --border-subtle: rgba(255, 255, 255, 0.04);
+
+  --accent-contrast: #0e0e10;
+
+  --overlay: rgba(0, 0, 0, 0.6);
+  --shadow-sm: 0 1px 2px rgba(0, 0, 0, 0.3);
+  --shadow-md: 0 2px 8px rgba(0, 0, 0, 0.4), 0 4px 16px rgba(0, 0, 0, 0.3);
+  --shadow-lg: 0 8px 30px rgba(0, 0, 0, 0.5);
+
+  color-scheme: dark;
+}
+
+/* ============================================================
+   Base
+   ============================================================ */
+
+* {
+  box-sizing: border-box;
+}
+
+html,
+body {
+  margin: 0;
+  height: 100%;
+}
+
+body {
+  background: var(--bg-base);
+  color: var(--text-primary);
+  font-family: 'Inter', system-ui, -apple-system, 'PingFang SC', 'Hiragino Sans GB', 'Microsoft YaHei', sans-serif;
+  font-size: 14px;
+  line-height: 1.6;
+  overflow: hidden;
+  -webkit-font-smoothing: antialiased;
+  text-rendering: optimizeLegibility;
+}
+
+/* Smooth theme transition (respect reduced motion) */
+body,
+body * {
+  transition-property: background-color, border-color, color, fill, stroke;
+  transition-duration: 200ms;
+  transition-timing-function: ease;
+}
+
+@media (prefers-reduced-motion: reduce) {
+  *,
+  *::before,
+  *::after {
+    transition-duration: 0.01ms !important;
+    animation-duration: 0.01ms !important;
+    animation-iteration-count: 1 !important;
+  }
+}
+
+/* ============================================================
+   Scrollbar — thin, low-key, theme-aware
+   ============================================================ */
+
+* {
+  scrollbar-width: thin;
+  scrollbar-color: var(--border-strong) transparent;
+}
+
+::-webkit-scrollbar {
+  width: 8px;
+  height: 8px;
+}
+
+::-webkit-scrollbar-track {
+  background: transparent;
+}
+
+::-webkit-scrollbar-thumb {
+  background: var(--border-strong);
+  border-radius: 4px;
+  border: 2px solid transparent;
+  background-clip: padding-box;
+}
+
+::-webkit-scrollbar-thumb:hover {
+  background: var(--text-tertiary);
+  background-clip: padding-box;
+}
+
+/* Windows scrollbars are slightly wider/more visible */
+.platform-win ::-webkit-scrollbar {
+  width: 10px;
+  height: 10px;
+}
+
+/* ============================================================
+   Titlebar drag regions (frameless window)
+   ============================================================ */
+
+.titlebar-drag {
+  -webkit-app-region: drag;
+}
+
+.titlebar-no-drag {
+  -webkit-app-region: no-drag;
+}
+
+/* ============================================================
+   Animations
+   ============================================================ */
+
+@keyframes blink {
+  0%, 100% { opacity: 1; }
+  50% { opacity: 0; }
+}
+
+.animate-blink {
+  animation: blink 1s step-end infinite;
+}
+
+/* AI typing indicator — 3-dot pulse */
+@keyframes typingPulse {
+  0%, 80%, 100% { transform: scale(0.6); opacity: 0.4; }
+  40% { transform: scale(1); opacity: 1; }
+}
+
+.typing-dot {
+  width: 6px;
+  height: 6px;
+  border-radius: 9999px;
+  background: var(--text-tertiary);
+  animation: typingPulse 1.4s infinite ease-in-out both;
+}
+
+.typing-dot:nth-child(2) { animation-delay: 0.16s; }
+.typing-dot:nth-child(3) { animation-delay: 0.32s; }
+
+/* Smooth content reveal */
+@keyframes fadeInUp {
+  from { opacity: 0; transform: translateY(4px); }
+  to { opacity: 1; transform: translateY(0); }
+}
+
+.animate-reveal {
+  animation: fadeInUp 0.25s ease both;
+}
+
+/* Skeleton shimmer */
+@keyframes shimmer {
+  0% { background-position: -200% 0; }
+  100% { background-position: 200% 0; }
+}
+
+.skeleton {
+  background: linear-gradient(
+    90deg,
+    var(--bg-surface-2) 25%,
+    var(--border-subtle) 50%,
+    var(--bg-surface-2) 75%
+  );
+  background-size: 200% 100%;
+  animation: shimmer 1.5s infinite;
+  border-radius: 6px;
+}
+
+/* ============================================================
+   Markdown content (assistant messages, memory/knowledge viewers)
+   ============================================================ */
+
+.msg-content > *:first-child { margin-top: 0; }
+.msg-content > *:last-child { margin-bottom: 0; }
+.msg-content p { margin: 0.5em 0; line-height: 1.7; }
+.msg-content ul, .msg-content ol { padding-left: 1.4em; margin: 0.5em 0; }
+.msg-content li { margin: 0.25em 0; }
+.msg-content h1, .msg-content h2, .msg-content h3, .msg-content h4 {
+  font-weight: 600;
+  margin: 0.8em 0 0.4em;
+  color: var(--text-primary);
+}
+.msg-content h1 { font-size: 1.4em; }
+.msg-content h2 { font-size: 1.25em; }
+.msg-content h3 { font-size: 1.1em; }
+
+.msg-content a { color: var(--accent); text-decoration: none; }
+.msg-content a:hover { text-decoration: underline; }
+
+.msg-content blockquote {
+  padding-left: 0.9em;
+  margin: 0.6em 0;
+  border-left: 3px solid var(--accent);
+  color: var(--text-secondary);
+}
+
+.msg-content table {
+  border-collapse: collapse;
+  width: 100%;
+  margin: 0.8em 0;
+  font-size: 0.9em;
+}
+.msg-content th, .msg-content td {
+  border: 1px solid var(--border-default);
+  padding: 0.4em 0.7em;
+  text-align: left;
+}
+.msg-content th { background: var(--bg-surface-2); font-weight: 600; }
+
+.msg-content hr { border: none; border-top: 1px solid var(--border-default); margin: 1em 0; }
+
+/* Inline code */
+.msg-content :not(pre) > code {
+  padding: 0.12em 0.4em;
+  border-radius: 5px;
+  background: var(--bg-inset);
+  border: 1px solid var(--border-subtle);
+  font-family: 'JetBrains Mono', 'Fira Code', Consolas, monospace;
+  font-size: 0.85em;
+}
+
+/* Fenced code blocks */
+.msg-content .code-block-wrapper {
+  margin: 0.7em 0;
+  border-radius: 10px;
+  overflow: hidden;
+  border: 1px solid var(--border-default);
+  background: var(--bg-inset);
+}
+.msg-content .code-block-header {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  padding: 5px 10px 5px 12px;
+  background: var(--bg-surface-2);
+  border-bottom: 1px solid var(--border-subtle);
+}
+.msg-content .code-block-lang {
+  font-size: 11px;
+  font-weight: 500;
+  color: var(--text-tertiary);
+  text-transform: lowercase;
+  letter-spacing: 0.02em;
+}
+.msg-content .code-copy-btn {
+  font-size: 11px;
+  color: var(--text-tertiary);
+  background: transparent;
+  border: none;
+  cursor: pointer;
+  padding: 2px 6px;
+  border-radius: 5px;
+  transition: color 0.15s, background 0.15s;
+}
+.msg-content .code-copy-btn:hover { color: var(--text-secondary); background: var(--bg-inset); }
+.msg-content .code-copy-btn.copied { color: var(--accent); }
+.msg-content .code-block-wrapper pre {
+  margin: 0;
+  padding: 12px 14px;
+  overflow-x: auto;
+  background: transparent;
+}
+.msg-content .code-block-wrapper pre code,
+.msg-content pre code.hljs {
+  font-family: 'JetBrains Mono', 'Fira Code', Consolas, monospace;
+  font-size: 12.5px;
+  line-height: 1.6;
+  background: transparent;
+  padding: 0;
+}
diff --git a/desktop/src/renderer/src/layout/NavRail.tsx b/desktop/src/renderer/src/layout/NavRail.tsx
new file mode 100644
index 0000000..f099b6a
--- /dev/null
+++ b/desktop/src/renderer/src/layout/NavRail.tsx
@@ -0,0 +1,386 @@
+import React, { useState, useRef, useEffect } from 'react'
+import { useLocation, useNavigate } from 'react-router-dom'
+import {
+  MessageSquare,
+  BookOpen,
+  Brain,
+  Zap,
+  Radio,
+  Clock,
+  Settings,
+  PanelLeftClose,
+  PanelLeftOpen,
+  Sun,
+  Moon,
+  ScrollText,
+  MoreHorizontal,
+  Languages,
+  Download,
+  Loader2,
+  Globe,
+  FileText,
+  Store,
+  MessageSquareWarning,
+} from 'lucide-react'
+import type { LucideIcon } from 'lucide-react'
+// The desktop app's own brand icon (transparent PNG), bundled by Vite.
+import brandLogo from '../assets/logo.png'
+import { t, getLang, setLang, Lang } from '../i18n'
+import { useUIStore } from '../store/uiStore'
+import { useTheme } from '../hooks/useTheme'
+import { usePlatform } from '../hooks/usePlatform'
+import { useUpdateStore, hasPendingUpdate, hasAvailableUpdate } from '../store/updateStore'
+import UpdateBanner from '../components/UpdateBanner'
+
+// Fallback shown when app.getVersion() is unavailable (dev/web preview). Keep
+// in sync with desktop/package.json "version"; the packaged app overrides this
+// with the real value via IPC, so it only matters outside a packaged build.
+const FALLBACK_VERSION = '2.1.3'
+
+// External links opened in the user's default browser. The window-open handler
+// in the main process routes window.open() through shell.openExternal.
+// English is the default (no suffix); Chinese gets a /zh suffix. Skill hub is
+// language-agnostic.
+const SKILL_HUB_URL = 'https://skills.cowagent.ai/'
+// GitHub issues — where users report bugs / request features.
+const FEEDBACK_URL = 'https://github.com/zhayujie/CowAgent/issues'
+
+const websiteUrl = () => (getLang() === 'zh' ? 'https://cowagent.ai/zh' : 'https://cowagent.ai')
+const docsUrl = () => (getLang() === 'zh' ? 'https://docs.cowagent.ai/zh' : 'https://docs.cowagent.ai')
+
+const openExternal = (url: string) => {
+  window.open(url, '_blank', 'noopener,noreferrer')
+}
+
+interface NavItem {
+  path: string
+  labelKey: string
+  icon: LucideIcon
+}
+
+const NAV_ITEMS: NavItem[] = [
+  { path: '/', labelKey: 'menu_chat', icon: MessageSquare },
+  { path: '/knowledge', labelKey: 'menu_knowledge', icon: BookOpen },
+  { path: '/memory', labelKey: 'menu_memory', icon: Brain },
+  { path: '/skills', labelKey: 'menu_skills', icon: Zap },
+  { path: '/channels', labelKey: 'menu_channels', icon: Radio },
+  { path: '/tasks', labelKey: 'menu_tasks', icon: Clock },
+  { path: '/settings', labelKey: 'menu_settings', icon: Settings },
+]
+
+interface NavRailProps {
+  onLangChange: () => void
+}
+
+const NavRail: React.FC<NavRailProps> = ({ onLangChange }) => {
+  const location = useLocation()
+  const navigate = useNavigate()
+  const { navCollapsed, toggleNav } = useUIStore()
+  const { theme, toggleTheme } = useTheme()
+  // On macOS the top-left is occupied by the native traffic lights, so the
+  // brand mark is only shown on Windows/Linux where that corner is otherwise
+  // empty (mirrors the web console's sidebar logo).
+  const { isMac } = usePlatform()
+
+  const collapsed = navCollapsed
+  const width = collapsed ? 'w-[56px]' : 'w-[208px]'
+
+  const updateState = useUpdateStore()
+  // Footer dot: hidden once dismissed for this version (user asked for this).
+  const pendingUpdate = hasPendingUpdate(updateState)
+  // Menu "check for update" dot: stays as long as an update actually exists,
+  // even after dismissing the footer badge.
+  const availableUpdate = hasAvailableUpdate(updateState)
+  const checking = updateState.status?.state === 'checking'
+
+  const [menuOpen, setMenuOpen] = useState(false)
+  // Local fallback so a version always shows even if the main-process IPC is
+  // unavailable (e.g. dev/web preview). The real value comes from
+  // app.getVersion() (packaged package.json), never from a remote service.
+  const [version, setVersion] = useState(FALLBACK_VERSION)
+  const menuRef = useRef<HTMLDivElement>(null)
+
+  useEffect(() => {
+    window.electronAPI
+      ?.getAppVersion?.()
+      .then((v) => v && setVersion(v))
+      .catch(() => {})
+  }, [])
+
+  // Close the popover on any outside click / Escape.
+  useEffect(() => {
+    if (!menuOpen) return
+    const onDown = (e: MouseEvent) => {
+      if (menuRef.current && !menuRef.current.contains(e.target as Node)) setMenuOpen(false)
+    }
+    const onKey = (e: KeyboardEvent) => {
+      if (e.key === 'Escape') setMenuOpen(false)
+    }
+    document.addEventListener('mousedown', onDown)
+    document.addEventListener('keydown', onKey)
+    return () => {
+      document.removeEventListener('mousedown', onDown)
+      document.removeEventListener('keydown', onKey)
+    }
+  }, [menuOpen])
+
+  const toggleLanguage = () => {
+    const next: Lang = getLang() === 'zh' ? 'en' : 'zh'
+    setLang(next)
+    onLangChange()
+  }
+
+  // Track a user-initiated check so we can show "up to date" feedback in the
+  // menu when the result comes back as not-available (the auto poll stays
+  // silent). Cleared shortly after, and whenever the menu closes.
+  const [checkedManually, setCheckedManually] = useState(false)
+  const updateStatusState = updateState.status?.state
+
+  useEffect(() => {
+    if (!checkedManually) return
+    if (updateStatusState === 'not-available') {
+      const id = setTimeout(() => setCheckedManually(false), 4000)
+      return () => clearTimeout(id)
+    }
+    // A pending update opens its own panel; no need for the inline hint.
+    if (updateStatusState === 'available' || updateStatusState === 'downloaded') {
+      setCheckedManually(false)
+    }
+    return
+  }, [checkedManually, updateStatusState])
+
+  useEffect(() => {
+    if (!menuOpen) setCheckedManually(false)
+  }, [menuOpen])
+
+  const checkUpdate = () => {
+    setCheckedManually(true)
+    // If an update is already known, recheck() re-opens its panel, so close the
+    // menu to reveal it. Otherwise keep the menu OPEN: the "up to date" result
+    // shows inline as the menu label — closing it (which resets checkedManually)
+    // is exactly what made the box flash and never show "up to date".
+    if (availableUpdate) setMenuOpen(false)
+    updateState.recheck()
+  }
+
+  return (
+    <aside className={`${width} flex flex-col flex-shrink-0 h-full bg-base transition-[width] duration-200`}>
+      {/* Top: full-width drag strip; bottom border continues the header divider
+          across the whole window. No right border so it doesn't cut the lights.
+          On Windows/Linux the top-left corner is empty (no traffic lights), so
+          we surface the brand mark here like the web console's sidebar. */}
+      <div
+        className={`titlebar-drag h-[44px] flex-shrink-0 border-b border-default flex items-center ${
+          collapsed ? 'justify-center px-0' : 'px-3'
+        }`}
+      >
+        {!isMac && (
+          <div className="flex items-center gap-2 min-w-0 select-none">
+            <BrandLogo />
+            {!collapsed && (
+              <span className="text-[14px] font-semibold text-content truncate">CowAgent</span>
+            )}
+          </div>
+        )}
+      </div>
+
+      {/* Content area carries the right divider, starting below the titlebar */}
+      <div className="flex-1 flex flex-col min-h-0 border-r border-default">
+      {/* Nav items */}
+      <nav className="flex-1 overflow-y-auto px-2 py-2 space-y-0.5">
+        {NAV_ITEMS.map((item) => {
+          const Icon = item.icon
+          const isActive = location.pathname === item.path
+          return (
+            <button
+              key={item.path}
+              onClick={() => navigate(item.path)}
+              title={collapsed ? t(item.labelKey) : undefined}
+              className={`group w-full flex items-center gap-3 rounded-btn cursor-pointer transition-colors h-9 ${
+                collapsed ? 'justify-center px-0' : 'px-3'
+              } ${
+                isActive
+                  ? 'bg-accent-soft text-accent'
+                  : 'text-content-secondary hover:bg-surface-2 hover:text-content'
+              }`}
+            >
+              <Icon size={18} strokeWidth={isActive ? 2.2 : 1.8} className="flex-shrink-0" />
+              {!collapsed && <span className="text-[13px] truncate">{t(item.labelKey)}</span>}
+            </button>
+          )
+        })}
+      </nav>
+
+      {/* Update banner floats above the footer when a new version is pending */}
+      <div className="relative">
+        {!collapsed && <UpdateBanner />}
+      </div>
+
+      {/* Footer actions: a single "more" entry (with version + update dot) that
+          opens an upward popover, plus the always-visible collapse toggle. */}
+      <div className="flex-shrink-0 px-2 py-2 border-t border-subtle relative" ref={menuRef}>
+        {menuOpen && (
+          <FooterMenu
+            theme={theme}
+            checking={checking}
+            pendingUpdate={availableUpdate}
+            upToDate={checkedManually && updateStatusState === 'not-available' && !availableUpdate}
+            onLogs={() => {
+              setMenuOpen(false)
+              navigate('/logs')
+            }}
+            onTheme={toggleTheme}
+            onLanguage={toggleLanguage}
+            onCheckUpdate={checkUpdate}
+            onOpenLink={(url) => {
+              setMenuOpen(false)
+              openExternal(url)
+            }}
+          />
+        )}
+
+        <div className={collapsed ? 'space-y-0.5' : 'flex items-center gap-1'}>
+          {/* Single clickable entry: version label (left) + the three dots
+              (right) form one button; the whole block opens the popover. The
+              version is the packaged app version, also what auto-update
+              compares against. Collapsed: dots only, version hidden. */}
+          <button
+            onClick={() => setMenuOpen((o) => !o)}
+            title={t('menu_more')}
+            className={`relative inline-flex items-center rounded-btn cursor-pointer transition-colors ${
+              menuOpen ? 'bg-surface-2 text-content' : 'text-content-tertiary hover:text-content hover:bg-surface-2'
+            } ${collapsed ? 'w-full h-9 justify-center' : 'h-8 px-2 gap-1.5'}`}
+          >
+            {!collapsed && version && (
+              <span className="text-[12px] truncate">{`v${version}`}</span>
+            )}
+            <MoreHorizontal size={17} className="flex-shrink-0" />
+            {pendingUpdate && (
+              <span className="absolute top-1 right-1 h-2 w-2 rounded-full bg-danger" />
+            )}
+          </button>
+
+          {!collapsed && <div className="flex-1" />}
+
+          <FooterBtn collapsed={collapsed} onClick={toggleNav} title={collapsed ? t('nav_expand') : t('nav_collapse')}>
+            {collapsed ? <PanelLeftOpen size={17} /> : <PanelLeftClose size={17} />}
+          </FooterBtn>
+        </div>
+      </div>
+      </div>
+    </aside>
+  )
+}
+
+// Brand mark for the top-left corner (Windows/Linux). Uses the desktop app's
+// own icon (transparent PNG with its own rounded shape), so it sits cleanly on
+// both light and dark backgrounds without extra styling.
+const BrandLogo: React.FC = () => (
+  <img
+    src={brandLogo}
+    alt="CowAgent"
+    draggable={false}
+    className="flex-shrink-0 w-7 h-7 object-contain"
+  />
+)
+
+const FooterBtn: React.FC<{
+  collapsed: boolean
+  onClick: () => void
+  title: string
+  active?: boolean
+  children: React.ReactNode
+}> = ({ collapsed, onClick, title, active, children }) => (
+  <button
+    onClick={onClick}
+    title={title}
+    className={`inline-flex items-center gap-1.5 rounded-btn cursor-pointer transition-colors ${
+      active
+        ? 'bg-accent-soft text-accent'
+        : 'text-content-tertiary hover:text-content hover:bg-surface-2'
+    } ${collapsed ? 'w-full h-9 justify-center' : 'h-8 px-2'}`}
+  >
+    {children}
+  </button>
+)
+
+// Upward popover holding the secondary actions previously crammed into the
+// footer (theme, language, logs, update check). Keeps the footer to a single
+// entry so new items can be added here without cluttering the rail.
+const FooterMenu: React.FC<{
+  theme: string
+  checking: boolean
+  pendingUpdate: boolean
+  upToDate: boolean
+  onLogs: () => void
+  onTheme: () => void
+  onLanguage: () => void
+  onCheckUpdate: () => void
+  onOpenLink: (url: string) => void
+}> = ({ theme, checking, pendingUpdate, upToDate, onLogs, onTheme, onLanguage, onCheckUpdate, onOpenLink }) => {
+  const updateLabel = checking
+    ? t('update_checking')
+    : upToDate
+      ? t('update_latest')
+      : t('update_check')
+  return (
+  <div className="absolute bottom-full left-2 right-2 mb-2 z-50 rounded-lg border border-default bg-elevated shadow-lg py-1">
+    {/* External destinations first (skill hub, docs, website) */}
+    <MenuItem icon={<Store size={16} />} label={t('menu_skill_hub')} onClick={() => onOpenLink(SKILL_HUB_URL)} />
+    <MenuItem icon={<FileText size={16} />} label={t('menu_docs')} onClick={() => onOpenLink(docsUrl())} />
+    <MenuItem icon={<Globe size={16} />} label={t('menu_website')} onClick={() => onOpenLink(websiteUrl())} />
+    <MenuItem
+      icon={<MessageSquareWarning size={16} />}
+      label={t('menu_feedback')}
+      onClick={() => onOpenLink(FEEDBACK_URL)}
+    />
+
+    <div className="my-1 border-t border-subtle" />
+
+    {/* App actions below: update, theme, language, logs */}
+    <MenuItem
+      icon={checking ? <Loader2 size={16} className="animate-spin" /> : <Download size={16} />}
+      label={updateLabel}
+      onClick={onCheckUpdate}
+      dot={pendingUpdate}
+      disabled={checking || upToDate}
+    />
+    <MenuItem
+      icon={theme === 'dark' ? <Sun size={16} /> : <Moon size={16} />}
+      label={theme === 'dark' ? t('menu_theme_light') : t('menu_theme_dark')}
+      onClick={onTheme}
+    />
+    <MenuItem
+      icon={<Languages size={16} />}
+      label={t('menu_language')}
+      trailing={getLang() === 'zh' ? 'EN' : '中'}
+      onClick={onLanguage}
+    />
+    <MenuItem icon={<ScrollText size={16} />} label={t('menu_logs')} onClick={onLogs} />
+  </div>
+  )
+}
+
+const MenuItem: React.FC<{
+  icon: React.ReactNode
+  label: string
+  trailing?: string
+  dot?: boolean
+  disabled?: boolean
+  onClick: () => void
+}> = ({ icon, label, trailing, dot, disabled, onClick }) => (
+  <button
+    disabled={disabled}
+    onClick={onClick}
+    className="w-full flex items-center gap-2.5 px-3 h-9 text-[13px] text-content-secondary hover:bg-surface-2 hover:text-content cursor-pointer transition-colors disabled:cursor-default disabled:hover:bg-transparent disabled:hover:text-content-secondary"
+  >
+    <span className="flex-shrink-0 text-content-tertiary relative">
+      {icon}
+      {dot && <span className="absolute -top-0.5 -right-0.5 h-1.5 w-1.5 rounded-full bg-danger" />}
+    </span>
+    <span className="flex-1 text-left truncate">{label}</span>
+    {trailing && <span className="text-[11px] font-medium text-content-tertiary">{trailing}</span>}
+  </button>
+)
+
+export default NavRail
diff --git a/desktop/src/renderer/src/layout/SessionList.tsx b/desktop/src/renderer/src/layout/SessionList.tsx
new file mode 100644
index 0000000..cdc8ab2
--- /dev/null
+++ b/desktop/src/renderer/src/layout/SessionList.tsx
@@ -0,0 +1,189 @@
+import React, { useEffect, useMemo, useState } from 'react'
+import { Plus, MessageSquare, Pencil, Trash2, Check, X, History } from 'lucide-react'
+import { t } from '../i18n'
+import { useSessionStore } from '../store/sessionStore'
+import { useUIStore } from '../store/uiStore'
+import { usePlatform } from '../hooks/usePlatform'
+import type { SessionItem } from '../types'
+
+function groupByTime(sessions: SessionItem[]): { label: string; items: SessionItem[] }[] {
+  const now = new Date()
+  const startOfToday = new Date(now.getFullYear(), now.getMonth(), now.getDate()).getTime() / 1000
+  const startOfYesterday = startOfToday - 86400
+
+  const today: SessionItem[] = []
+  const yesterday: SessionItem[] = []
+  const earlier: SessionItem[] = []
+
+  for (const s of sessions) {
+    const ts = s.last_active || s.created_at
+    if (ts >= startOfToday) today.push(s)
+    else if (ts >= startOfYesterday) yesterday.push(s)
+    else earlier.push(s)
+  }
+
+  return [
+    { label: t('session_today'), items: today },
+    { label: t('session_yesterday'), items: yesterday },
+    { label: t('session_earlier'), items: earlier },
+  ].filter((g) => g.items.length > 0)
+}
+
+const SessionList: React.FC = () => {
+  const { sessions, activeId, loading, loadSessions, loadMore, hasMore, setActive, newSession, rename, remove } =
+    useSessionStore()
+  const toggleSessions = useUIStore((s) => s.toggleSessions)
+  const navCollapsed = useUIStore((s) => s.navCollapsed)
+  const { isMac } = usePlatform()
+  // When the nav rail is collapsed on macOS, the native traffic lights spill
+  // past it, so nudge the history button right to keep it (and its sibling in
+  // the main header) clear of the lights and aligned across states.
+  const trafficOffset = isMac && navCollapsed ? 'ml-2' : ''
+  // Nudge header buttons down a touch to sit level with the macOS traffic lights.
+  const trafficDrop = isMac ? 'mt-1' : ''
+  const [editingId, setEditingId] = useState<string | null>(null)
+  const [editValue, setEditValue] = useState('')
+
+  useEffect(() => {
+    loadSessions(1)
+  }, [loadSessions])
+
+  const groups = useMemo(() => groupByTime(sessions), [sessions])
+
+  const startEdit = (s: SessionItem) => {
+    setEditingId(s.session_id)
+    setEditValue(s.title || '')
+  }
+
+  const commitEdit = async () => {
+    if (editingId && editValue.trim()) {
+      await rename(editingId, editValue.trim())
+    }
+    setEditingId(null)
+  }
+
+  return (
+    <div className="w-[240px] flex-shrink-0 flex flex-col h-full bg-surface border-r border-default">
+      {/* Header */}
+      <div className="flex items-center justify-between px-2 h-[44px] flex-shrink-0 titlebar-drag border-b border-default">
+        <button
+          onClick={toggleSessions}
+          title={t('session_history')}
+          className={`titlebar-no-drag inline-flex items-center justify-center w-7 h-7 rounded-btn text-content-tertiary hover:text-content hover:bg-surface-2 cursor-pointer transition-colors ${trafficDrop} ${trafficOffset}`}
+        >
+          <History size={16} />
+        </button>
+        <button
+          onClick={() => newSession()}
+          title={t('session_new')}
+          className={`titlebar-no-drag inline-flex items-center gap-1.5 px-2.5 h-7 rounded-btn text-[12px] font-medium text-accent hover:bg-accent-soft cursor-pointer transition-colors ${trafficDrop}`}
+        >
+          <Plus size={15} />
+          {t('session_new')}
+        </button>
+      </div>
+
+      {/* List */}
+      <div
+        className="flex-1 overflow-y-auto px-2 pb-2"
+        onScroll={(e) => {
+          const el = e.currentTarget
+          if (el.scrollHeight - el.scrollTop - el.clientHeight < 80 && hasMore && !loading) loadMore()
+        }}
+      >
+        {sessions.length === 0 && !loading && (
+          <div className="flex flex-col items-center justify-center h-40 text-center px-4">
+            <MessageSquare size={22} className="text-content-disabled mb-2" />
+            <p className="text-xs text-content-tertiary">{t('session_empty')}</p>
+          </div>
+        )}
+
+        {groups.map((group) => (
+          <div key={group.label} className="mb-2">
+            <div className="px-2 pt-2 pb-1 text-[11px] font-medium uppercase tracking-wide text-content-disabled">
+              {group.label}
+            </div>
+            {group.items.map((s) => {
+              const isActive = s.session_id === activeId
+              const isEditing = editingId === s.session_id
+              return (
+                <div
+                  key={s.session_id}
+                  onClick={() => !isEditing && setActive(s.session_id)}
+                  className={`group flex items-center gap-2 px-2 h-9 rounded-btn cursor-pointer transition-colors ${
+                    isActive ? 'bg-accent-soft' : 'hover:bg-surface-2'
+                  }`}
+                >
+                  {isEditing ? (
+                    <input
+                      autoFocus
+                      value={editValue}
+                      onChange={(e) => setEditValue(e.target.value)}
+                      onKeyDown={(e) => {
+                        if (e.key === 'Enter') commitEdit()
+                        if (e.key === 'Escape') setEditingId(null)
+                      }}
+                      onClick={(e) => e.stopPropagation()}
+                      className="flex-1 min-w-0 bg-inset border border-strong rounded px-1.5 py-0.5 text-[13px] text-content focus:outline-none focus:border-accent"
+                    />
+                  ) : (
+                    <span
+                      className={`flex-1 min-w-0 truncate text-[13px] ${
+                        isActive ? 'text-accent font-medium' : 'text-content-secondary'
+                      }`}
+                    >
+                      {s.title || s.session_id}
+                    </span>
+                  )}
+
+                  {isEditing ? (
+                    <div className="flex items-center gap-0.5">
+                      <IconBtn onClick={(e) => { e.stopPropagation(); commitEdit() }}><Check size={13} /></IconBtn>
+                      <IconBtn onClick={(e) => { e.stopPropagation(); setEditingId(null) }}><X size={13} /></IconBtn>
+                    </div>
+                  ) : (
+                    <div className="flex items-center gap-0.5 opacity-0 group-hover:opacity-100 transition-opacity">
+                      <IconBtn onClick={(e) => { e.stopPropagation(); startEdit(s) }} title={t('session_rename')}>
+                        <Pencil size={13} />
+                      </IconBtn>
+                      <IconBtn onClick={(e) => { e.stopPropagation(); remove(s.session_id) }} title={t('session_delete')} danger>
+                        <Trash2 size={13} />
+                      </IconBtn>
+                    </div>
+                  )}
+                </div>
+              )
+            })}
+          </div>
+        ))}
+
+        {loading && (
+          <div className="px-2 py-2 space-y-2">
+            {Array.from({ length: 4 }).map((_, i) => (
+              <div key={i} className="skeleton h-7 w-full" />
+            ))}
+          </div>
+        )}
+      </div>
+    </div>
+  )
+}
+
+const IconBtn: React.FC<{
+  onClick: (e: React.MouseEvent) => void
+  title?: string
+  danger?: boolean
+  children: React.ReactNode
+}> = ({ onClick, title, danger, children }) => (
+  <button
+    onClick={onClick}
+    title={title}
+    className={`inline-flex items-center justify-center w-6 h-6 rounded cursor-pointer transition-colors text-content-tertiary ${
+      danger ? 'hover:text-danger hover:bg-danger-soft' : 'hover:text-content hover:bg-surface'
+    }`}
+  >
+    {children}
+  </button>
+)
+
+export default SessionList
diff --git a/desktop/src/renderer/src/layout/WindowControls.tsx b/desktop/src/renderer/src/layout/WindowControls.tsx
new file mode 100644
index 0000000..511aa6f
--- /dev/null
+++ b/desktop/src/renderer/src/layout/WindowControls.tsx
@@ -0,0 +1,42 @@
+import React, { useEffect, useState } from 'react'
+import { Minus, Square, Copy, X } from 'lucide-react'
+
+/**
+ * Custom window controls for the frameless Windows titlebar.
+ * On macOS the system renders traffic lights, so this returns null there.
+ */
+const WindowControls: React.FC = () => {
+  const [maximized, setMaximized] = useState(false)
+  const api = window.electronAPI
+
+  useEffect(() => {
+    api?.windowIsMaximized().then(setMaximized)
+    const off = api?.onMaximizeChange(setMaximized)
+    return off
+  }, [api])
+
+  if (api?.platform === 'darwin') return null
+
+  const btn =
+    'titlebar-no-drag inline-flex items-center justify-center w-11 h-full text-content-tertiary hover:text-content cursor-pointer transition-colors'
+
+  return (
+    <div className="flex items-stretch h-full">
+      <button className={`${btn} hover:bg-surface-2`} onClick={() => api?.windowMinimize()} aria-label="Minimize">
+        <Minus size={15} strokeWidth={2} />
+      </button>
+      <button className={`${btn} hover:bg-surface-2`} onClick={() => api?.windowMaximize()} aria-label="Maximize">
+        {maximized ? <Copy size={12} strokeWidth={2} /> : <Square size={12} strokeWidth={2} />}
+      </button>
+      <button
+        className={`${btn} hover:bg-danger hover:text-white`}
+        onClick={() => api?.windowClose()}
+        aria-label="Close"
+      >
+        <X size={16} strokeWidth={2} />
+      </button>
+    </div>
+  )
+}
+
+export default WindowControls
diff --git a/desktop/src/renderer/src/main.tsx b/desktop/src/renderer/src/main.tsx
new file mode 100644
index 0000000..158640a
--- /dev/null
+++ b/desktop/src/renderer/src/main.tsx
@@ -0,0 +1,13 @@
+import React from 'react'
+import ReactDOM from 'react-dom/client'
+import { HashRouter } from 'react-router-dom'
+import App from './App'
+import './index.css'
+
+ReactDOM.createRoot(document.getElementById('root')!).render(
+  <React.StrictMode>
+    <HashRouter>
+      <App />
+    </HashRouter>
+  </React.StrictMode>
+)
diff --git a/desktop/src/renderer/src/pages/ChannelsPage.tsx b/desktop/src/renderer/src/pages/ChannelsPage.tsx
new file mode 100644
index 0000000..a956eaf
--- /dev/null
+++ b/desktop/src/renderer/src/pages/ChannelsPage.tsx
@@ -0,0 +1,452 @@
+import React, { useEffect, useMemo, useRef, useState } from 'react'
+import {
+  Loader2,
+  Plug,
+  Plus,
+  X,
+  ChevronDown,
+  Check,
+  MessageCircle,
+  MessageSquare,
+  Bot,
+  Building2,
+  Headset,
+  Hash,
+  AtSign,
+} from 'lucide-react'
+import { t, localizedLabel } from '../i18n'
+import apiClient from '../api/client'
+import type { ChannelInfo, ChannelField } from '../types'
+import { Toggle, Btn } from './settings/primitives'
+import QrLoginModal from '../components/QrLoginModal'
+import { PaperPlaneIcon } from '../components/icons'
+
+// Channels that connect via QR scanning rather than credential fields.
+const QR_PROVIDERS: Record<string, 'weixin' | 'feishu'> = { weixin: 'weixin', feishu: 'feishu' }
+
+// An icon component that takes a `size` prop (lucide icons and our PaperPlaneIcon).
+type IconComponent = React.FC<{ size?: number }>
+
+// Per-channel icon + accent color, mirroring the web console's FontAwesome
+// icon + Tailwind color palette (we use lucide here, with hex colors so the
+// tinted icon background isn't purged by Tailwind's JIT). Feishu/Telegram use
+// the same paper-plane as the web console.
+const CHANNEL_STYLE: Record<string, { Icon: IconComponent; color: string }> = {
+  weixin: { Icon: MessageCircle, color: '#10b981' },
+  feishu: { Icon: PaperPlaneIcon, color: '#3b82f6' },
+  dingtalk: { Icon: MessageSquare, color: '#3b82f6' },
+  wecom_bot: { Icon: Bot, color: '#10b981' },
+  qq: { Icon: MessageCircle, color: '#3b82f6' },
+  wechatcom_app: { Icon: Building2, color: '#10b981' },
+  wechat_kf: { Icon: Headset, color: '#10b981' },
+  wechatmp: { Icon: MessageCircle, color: '#10b981' },
+  telegram: { Icon: PaperPlaneIcon, color: '#0ea5e9' },
+  slack: { Icon: Hash, color: '#a855f7' },
+  discord: { Icon: AtSign, color: '#6366f1' },
+}
+
+const channelStyle = (name: string) => CHANNEL_STYLE[name] ?? { Icon: Plug, color: '#94a3b8' }
+
+interface ChannelsPageProps {
+  baseUrl: string
+}
+
+// A masked secret looks like "abcd****wxyz"; the backend skips such values.
+const MASK_RE = /\*{2,}/
+
+const ChannelsPage: React.FC<ChannelsPageProps> = ({ baseUrl }) => {
+  const [channels, setChannels] = useState<ChannelInfo[]>([])
+  const [loading, setLoading] = useState(true)
+  // Whether the "add channel" panel is open, and the channel chosen in it.
+  // `selected` starts empty so the user must pick a channel themselves.
+  const [addOpen, setAddOpen] = useState(false)
+  const [selected, setSelected] = useState<string>('')
+  const scrollRef = useRef<HTMLDivElement>(null)
+  const panelRef = useRef<HTMLDivElement>(null)
+
+  const loadChannels = async () => {
+    try {
+      setLoading(true)
+      const data = await apiClient.getChannels()
+      setChannels(data || [])
+    } catch (err) {
+      console.error('Failed to load channels:', err)
+      setChannels([])
+    } finally {
+      setLoading(false)
+    }
+  }
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    void loadChannels()
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl])
+
+  const { connected, available } = useMemo(() => {
+    const connected = channels.filter((c) => c.active)
+    const available = channels.filter((c) => !c.active)
+    return { connected, available }
+  }, [channels])
+
+  // If the selected channel got connected (or vanished), clear the selection.
+  useEffect(() => {
+    if (selected && !available.some((c) => c.name === selected)) setSelected('')
+  }, [available, selected])
+
+  const openAdd = () => {
+    setSelected('')
+    setAddOpen(true)
+    // Scroll the new panel into view at the bottom of the list.
+    requestAnimationFrame(() => {
+      panelRef.current?.scrollIntoView({ behavior: 'smooth', block: 'end' })
+    })
+  }
+
+  const addingChannel = available.find((c) => c.name === selected)
+
+  const onAdded = () => {
+    setAddOpen(false)
+    setSelected('')
+    void loadChannels()
+  }
+
+  // Keep the config form in view as it grows after picking a channel.
+  useEffect(() => {
+    if (selected) {
+      requestAnimationFrame(() => {
+        panelRef.current?.scrollIntoView({ behavior: 'smooth', block: 'end' })
+      })
+    }
+  }, [selected])
+
+  return (
+    <div className="flex-1 flex flex-col min-h-0">
+      <div className="px-6 pt-5 pb-3 flex-shrink-0 flex items-start justify-between gap-4">
+        <div>
+          <h2 className="text-xl font-bold text-content">{t('channels_title')}</h2>
+          <p className="text-xs text-content-tertiary mt-1">{t('channels_desc')}</p>
+        </div>
+        {!loading && available.length > 0 && !addOpen && (
+          <Btn variant="primary" onClick={openAdd}>
+            <span className="flex items-center gap-1.5">
+              <Plus size={15} />
+              {t('channels_add')}
+            </span>
+          </Btn>
+        )}
+      </div>
+
+      <div ref={scrollRef} className="flex-1 overflow-y-auto border-t border-default">
+        <div className="max-w-3xl mx-auto px-6 py-5">
+          {loading ? (
+            <div className="flex items-center justify-center py-20 text-content-tertiary">
+              <Loader2 size={18} className="animate-spin mr-2" />
+              {t('channels_loading')}
+            </div>
+          ) : (
+            <div className="space-y-3">
+              {connected.length === 0 && !addOpen ? (
+                <p className="text-sm text-content-tertiary py-2">{t('channels_empty_connected')}</p>
+              ) : (
+                connected.map((ch) => <ChannelCard key={ch.name} channel={ch} onChanged={loadChannels} />)
+              )}
+
+              {/* Add-channel panel lives at the bottom of the list: pick a
+                  channel from the dropdown, then configure/connect it inline. */}
+              {addOpen && available.length > 0 && (
+                <div ref={panelRef} className="rounded-card border border-accent/40 bg-surface p-4 space-y-4">
+                  <div className="flex items-center justify-between gap-3">
+                    <label className="text-sm font-medium text-content">{t('channels_select_label')}</label>
+                    <button
+                      onClick={() => setAddOpen(false)}
+                      className="text-content-tertiary hover:text-content cursor-pointer"
+                      title={t('channels_add_close')}
+                    >
+                      <X size={16} />
+                    </button>
+                  </div>
+                  <ChannelDropdown
+                    channels={available}
+                    value={selected}
+                    onChange={setSelected}
+                    placeholder={t('channels_select_placeholder')}
+                  />
+                  {addingChannel && (
+                    <ChannelCard key={addingChannel.name} channel={addingChannel} onChanged={onAdded} defaultExpanded />
+                  )}
+                </div>
+              )}
+            </div>
+          )}
+        </div>
+      </div>
+    </div>
+  )
+}
+
+// Custom dropdown styled like the web console's `.cfg-dropdown` (rounded,
+// green focus ring, hover/active states) instead of a native <select>.
+const ChannelDropdown: React.FC<{
+  channels: ChannelInfo[]
+  value: string
+  onChange: (name: string) => void
+  placeholder: string
+}> = ({ channels, value, onChange, placeholder }) => {
+  const [open, setOpen] = useState(false)
+  const ref = useRef<HTMLDivElement>(null)
+
+  useEffect(() => {
+    if (!open) return
+    const onDoc = (e: MouseEvent) => {
+      if (ref.current && !ref.current.contains(e.target as Node)) setOpen(false)
+    }
+    document.addEventListener('mousedown', onDoc)
+    return () => document.removeEventListener('mousedown', onDoc)
+  }, [open])
+
+  const current = channels.find((c) => c.name === value)
+
+  return (
+    <div ref={ref} className="relative">
+      <button
+        type="button"
+        onClick={() => setOpen((v) => !v)}
+        className={`w-full flex items-center justify-between gap-2 h-10 px-3 rounded-btn border bg-inset text-sm cursor-pointer transition-colors ${
+          open ? 'border-accent ring-2 ring-accent/15' : 'border-strong hover:border-content-tertiary'
+        } ${current ? 'text-content' : 'text-content-tertiary'}`}
+      >
+        {current ? (
+          <span className="flex items-center gap-2 min-w-0">
+            <ChannelIcon name={current.name} size={26} />
+            <span className="truncate">{localizedLabel(current.label)}</span>
+            <span className="text-content-tertiary font-mono text-xs">({current.name})</span>
+          </span>
+        ) : (
+          <span>{placeholder}</span>
+        )}
+        <ChevronDown size={14} className={`flex-shrink-0 text-content-tertiary transition-transform ${open ? 'rotate-180' : ''}`} />
+      </button>
+      {open && (
+        <div className="absolute top-[calc(100%+4px)] left-0 right-0 z-50 max-h-60 overflow-y-auto rounded-btn border border-default bg-elevated shadow-lg p-1">
+          {channels.map((ch) => {
+            const active = ch.name === value
+            return (
+              <button
+                key={ch.name}
+                type="button"
+                onClick={() => {
+                  onChange(ch.name)
+                  setOpen(false)
+                }}
+                className={`w-full flex items-center gap-2.5 px-2.5 py-2 rounded-md text-sm cursor-pointer transition-colors ${
+                  active ? 'bg-accent-soft text-accent font-medium' : 'text-content-secondary hover:bg-surface-2'
+                }`}
+              >
+                <ChannelIcon name={ch.name} size={26} />
+                <span className="truncate">{localizedLabel(ch.label)}</span>
+                <span className="text-content-tertiary font-mono text-xs">({ch.name})</span>
+                {active && <Check size={14} className="ml-auto flex-shrink-0" />}
+              </button>
+            )
+          })}
+        </div>
+      )}
+    </div>
+  )
+}
+
+// A tinted square with the channel's icon (web-console style).
+const ChannelIcon: React.FC<{ name: string; size?: number }> = ({ name, size = 36 }) => {
+  const { Icon, color } = channelStyle(name)
+  return (
+    <span
+      className="rounded-lg flex items-center justify-center flex-shrink-0"
+      style={{ width: size, height: size, backgroundColor: `${color}1a`, color }}
+    >
+      <Icon size={Math.round(size * 0.45)} />
+    </span>
+  )
+}
+
+const ChannelCard: React.FC<{ channel: ChannelInfo; onChanged: () => void; defaultExpanded?: boolean }> = ({
+  channel,
+  onChanged,
+  defaultExpanded = false,
+}) => {
+  // Channels with no fields connect purely via QR (e.g. weixin).
+  const isQrLogin = channel.fields.length === 0
+  // QR provider supported by the desktop scan modal (weixin / feishu).
+  const qrProvider = QR_PROVIDERS[channel.name]
+  const [showQr, setShowQr] = useState(false)
+  const [expanded, setExpanded] = useState(defaultExpanded)
+  const [values, setValues] = useState<Record<string, string>>(() =>
+    Object.fromEntries(channel.fields.map((f) => [f.key, f.value != null ? String(f.value) : '']))
+  )
+  // Track which secret fields still hold the server-provided mask.
+  const [masked, setMasked] = useState<Record<string, boolean>>(() =>
+    Object.fromEntries(
+      channel.fields.map((f) => [f.key, f.type === 'secret' && !!f.value && MASK_RE.test(String(f.value))])
+    )
+  )
+  const [busy, setBusy] = useState(false)
+  const [status, setStatus] = useState('')
+
+  const setField = (key: string, val: string) => setValues((p) => ({ ...p, [key]: val }))
+
+  // Only send fields the user actually changed; masked secrets are skipped so
+  // the backend keeps the stored value (mirrors the web console behavior).
+  const buildConfig = (): Record<string, unknown> => {
+    const cfg: Record<string, unknown> = {}
+    channel.fields.forEach((f) => {
+      const v = values[f.key]
+      if (f.type === 'secret' && masked[f.key]) return
+      if (v === '' || v == null) return
+      cfg[f.key] = f.type === 'number' ? Number(v) : v
+    })
+    return cfg
+  }
+
+  const run = async (action: 'save' | 'connect' | 'disconnect') => {
+    setBusy(true)
+    setStatus('')
+    try {
+      const cfg = action === 'disconnect' ? undefined : buildConfig()
+      const res = await apiClient.channelAction(action, channel.name, cfg)
+      if (res.status === 'success') {
+        if (action === 'save') {
+          setStatus(t('channels_save_ok'))
+          setTimeout(() => setStatus(''), 1600)
+        }
+        onChanged()
+      } else {
+        setStatus((res.message as string) || t(action === 'connect' ? 'channels_connect_error' : 'channels_save_error'))
+      }
+    } catch {
+      setStatus(t(action === 'connect' ? 'channels_connect_error' : 'channels_save_error'))
+    } finally {
+      setBusy(false)
+    }
+  }
+
+  return (
+    <div className={defaultExpanded ? '' : 'rounded-card border border-default bg-surface p-4'}>
+      <div className="flex items-center gap-3">
+        <ChannelIcon name={channel.name} size={40} />
+        <div className="flex-1 min-w-0">
+          <div className="flex items-center gap-2">
+            <span className="font-medium text-sm text-content">{localizedLabel(channel.label)}</span>
+            <span className={`w-2 h-2 rounded-full ${channel.active ? 'bg-accent' : 'bg-content-tertiary'}`} />
+            {channel.active && <span className="text-xs text-accent">{t('channels_connected')}</span>}
+          </div>
+          <p className="text-xs text-content-tertiary font-mono mt-0.5">{channel.name}</p>
+        </div>
+
+        {channel.active ? (
+          <Btn variant="danger" onClick={() => run('disconnect')} disabled={busy}>
+            {t('channels_disconnect')}
+          </Btn>
+        ) : qrProvider ? (
+          <Btn variant="primary" onClick={() => setShowQr(true)}>
+            {qrProvider === 'weixin' ? t('channels_scan_login') : t('channels_scan_register')}
+          </Btn>
+        ) : isQrLogin || defaultExpanded ? null : (
+          <Btn variant="ghost" onClick={() => setExpanded((v) => !v)}>
+            {t('channels_add')}
+          </Btn>
+        )}
+      </div>
+
+      {/* QR-login channels with no desktop support fall back to the web console. */}
+      {isQrLogin && !channel.active && !qrProvider && (
+        <p className="text-xs text-content-tertiary mt-3 pl-12">{t('channels_qr_hint')}</p>
+      )}
+
+      {/* Field-bearing QR channels (feishu) can also be configured manually. */}
+      {!isQrLogin && qrProvider && !channel.active && !expanded && (
+        <button
+          onClick={() => setExpanded(true)}
+          className="text-xs text-content-tertiary hover:text-content-secondary mt-3 pl-12 cursor-pointer transition-colors"
+        >
+          {t('channels_add')}
+        </button>
+      )}
+
+      {/* Field editor: always for connected channels with fields, on-demand for available ones. */}
+      {!isQrLogin && (channel.active || expanded) && (
+        <div className="mt-4 space-y-3">
+          {channel.fields.map((f) => (
+            <FieldRow
+              key={f.key}
+              field={f}
+              value={values[f.key] ?? ''}
+              onChange={(v) => setField(f.key, v)}
+              onFocusSecret={() => {
+                if (f.type === 'secret' && masked[f.key]) {
+                  setField(f.key, '')
+                  setMasked((p) => ({ ...p, [f.key]: false }))
+                }
+              }}
+            />
+          ))}
+          <div className="flex items-center justify-end gap-3 pt-1">
+            <span className={`text-xs transition-opacity ${status ? 'opacity-100' : 'opacity-0'} ${status === t('channels_save_ok') ? 'text-accent' : 'text-danger'}`}>
+              {status || '\u00a0'}
+            </span>
+            {channel.active ? (
+              <Btn variant="primary" onClick={() => run('save')} disabled={busy}>
+                {t('channels_save')}
+              </Btn>
+            ) : (
+              <Btn variant="primary" onClick={() => run('connect')} disabled={busy}>
+                {t('channels_connect')}
+              </Btn>
+            )}
+          </div>
+        </div>
+      )}
+
+      {showQr && qrProvider && (
+        <QrLoginModal
+          provider={qrProvider}
+          onClose={() => setShowQr(false)}
+          onConnected={() => {
+            setShowQr(false)
+            onChanged()
+          }}
+        />
+      )}
+    </div>
+  )
+}
+
+const FieldRow: React.FC<{
+  field: ChannelField
+  value: string
+  onChange: (v: string) => void
+  onFocusSecret: () => void
+}> = ({ field, value, onChange, onFocusSecret }) => {
+  if (field.type === 'bool') {
+    return (
+      <div className="flex items-center justify-between">
+        <span className="text-sm text-content-secondary">{field.label}</span>
+        <Toggle checked={value === 'true' || value === '1'} onChange={(v) => onChange(v ? 'true' : 'false')} />
+      </div>
+    )
+  }
+  return (
+    <div>
+      <label className="block text-sm text-content-secondary mb-1.5">{field.label}</label>
+      <input
+        type={field.type === 'number' ? 'number' : 'text'}
+        value={value}
+        placeholder={field.label}
+        onChange={(e) => onChange(e.target.value)}
+        onFocus={onFocusSecret}
+        className="w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent font-mono transition-colors"
+      />
+    </div>
+  )
+}
+
+export default ChannelsPage
diff --git a/desktop/src/renderer/src/pages/ChatPage.tsx b/desktop/src/renderer/src/pages/ChatPage.tsx
new file mode 100644
index 0000000..837e513
--- /dev/null
+++ b/desktop/src/renderer/src/pages/ChatPage.tsx
@@ -0,0 +1,307 @@
+import React, { useEffect, useRef, useCallback, useState } from 'react'
+import {
+  ChevronUp,
+  Loader2,
+  FolderOpen,
+  Clock,
+  Code2,
+  BookOpen,
+  Puzzle,
+  Terminal,
+  type LucideIcon,
+} from 'lucide-react'
+import MessageBubble from '../components/MessageBubble'
+import ChatInput, { type ChatInputHandle } from '../components/ChatInput'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import type { Attachment, ChatMessage } from '../types'
+import { useChatStore } from '../store/chatStore'
+import { useSessionStore } from '../store/sessionStore'
+
+interface ChatPageProps {
+  baseUrl: string
+}
+
+// Welcome-screen suggestion cards (aligned with the web console: 6 cards).
+// `send` overrides the text dropped into the input (e.g. show "查看全部命令"
+// but fill "/help"); otherwise the card's *_text is used.
+// Icon + accent color per card, aligned with the web console palette.
+const SUGGESTIONS: {
+  key: string
+  send?: string
+  icon: LucideIcon
+  iconClass: string
+  bgClass: string
+}[] = [
+  { key: 'example_sys', icon: FolderOpen, iconClass: 'text-blue-500', bgClass: 'bg-blue-500/10' },
+  { key: 'example_task', icon: Clock, iconClass: 'text-amber-500', bgClass: 'bg-amber-500/10' },
+  { key: 'example_code', icon: Code2, iconClass: 'text-emerald-500', bgClass: 'bg-emerald-500/10' },
+  { key: 'example_knowledge', icon: BookOpen, iconClass: 'text-violet-500', bgClass: 'bg-violet-500/10' },
+  { key: 'example_skill', icon: Puzzle, iconClass: 'text-rose-500', bgClass: 'bg-rose-500/10' },
+  { key: 'example_web', send: '/help', icon: Terminal, iconClass: 'text-content-tertiary', bgClass: 'bg-content-tertiary/10' },
+]
+
+const ChatPage: React.FC<ChatPageProps> = ({ baseUrl }) => {
+  const activeId = useSessionStore((s) => s.activeId)
+  const newSession = useSessionStore((s) => s.newSession)
+  const loadSessions = useSessionStore((s) => s.loadSessions)
+
+  const session = useChatStore((s) => s.sessions[activeId])
+  const send = useChatStore((s) => s.send)
+  const cancel = useChatStore((s) => s.cancel)
+  const regenerate = useChatStore((s) => s.regenerate)
+  const editUserMessage = useChatStore((s) => s.editUserMessage)
+  const deleteMessage = useChatStore((s) => s.deleteMessage)
+  const loadHistory = useChatStore((s) => s.loadHistory)
+  const ensureSession = useChatStore((s) => s.ensureSession)
+
+  const messages = session?.messages ?? []
+  const isStreaming = session?.isStreaming ?? false
+
+  const scrollRef = useRef<HTMLDivElement>(null)
+  const bottomRef = useRef<HTMLDivElement>(null)
+  const inputResetRef = useRef<ChatInputHandle>(null)
+  const [loadingMore, setLoadingMore] = useState(false)
+  const titlePendingRef = useRef(false)
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+  }, [baseUrl])
+
+  // Load history when switching to a session that hasn't been loaded yet.
+  useEffect(() => {
+    ensureSession(activeId)
+    const s = useChatStore.getState().sessions[activeId]
+    if (s && !s.historyLoaded && !s.isStreaming) {
+      loadHistory(activeId, 1)
+    }
+  }, [activeId, ensureSession, loadHistory])
+
+  const scrollToBottom = useCallback((smooth = true) => {
+    // Defer to the next frame so we read the height *after* the new content has
+    // been laid out (markdown/streaming renders a frame later than the effect).
+    requestAnimationFrame(() => {
+      const el = scrollRef.current
+      if (!el) return
+      // Smooth animations get interrupted by high-frequency streaming updates
+      // and never catch up, so jump instantly while following the stream.
+      if (smooth) {
+        bottomRef.current?.scrollIntoView({ behavior: 'smooth' })
+      } else {
+        el.scrollTop = el.scrollHeight
+      }
+    })
+  }, [])
+
+  // Snap to the bottom instantly when switching sessions (no top-to-bottom animation).
+  // History may load a frame later, so keep snapping instantly until content arrives.
+  const lastSessionRef = useRef('')
+  const lastLenRef = useRef(0)
+  const pendingSnapRef = useRef(false)
+  // True while we should keep the view pinned to the bottom (e.g. during
+  // streaming). Cleared when the user scrolls up to read earlier messages.
+  const followBottomRef = useRef(true)
+  // Tracks the previous streaming state so we can do one final snap to the
+  // bottom right when streaming ends (the last chunk of a long command output
+  // often lands together with isStreaming flipping to false).
+  const wasStreamingRef = useRef(false)
+  useEffect(() => {
+    const el = scrollRef.current
+    if (!el) return
+
+    if (lastSessionRef.current !== activeId) {
+      lastSessionRef.current = activeId
+      lastLenRef.current = messages.length
+      pendingSnapRef.current = true
+      followBottomRef.current = true
+    }
+
+    if (pendingSnapRef.current) {
+      // Instant snap on switch and on the first content that lands afterwards.
+      lastLenRef.current = messages.length
+      scrollToBottom(false)
+      if (messages.length > 0) pendingSnapRef.current = false
+      return
+    }
+
+    const nearBottom = el.scrollHeight - el.scrollTop - el.clientHeight < 160
+    const grew = messages.length !== lastLenRef.current
+    lastLenRef.current = messages.length
+    // Follow the bottom when: a new message arrived, the user is already near
+    // the bottom, or we're streaming and the user hasn't scrolled up. This
+    // keeps long command/streaming output (where length is unchanged but the
+    // content keeps growing) glued to the latest line.
+    // One final snap right when streaming ends, so the tail of a long command
+    // output isn't left scrolled off-screen.
+    const justFinished = wasStreamingRef.current && !isStreaming
+    wasStreamingRef.current = isStreaming
+
+    const following = isStreaming && followBottomRef.current
+    if (grew || nearBottom || following || (justFinished && followBottomRef.current)) {
+      // Instant jump while streaming/new content (smooth animations get
+      // interrupted by rapid updates and never reach the bottom); smooth only
+      // for a lone increment when the user is already sitting near the bottom.
+      const smooth = nearBottom && !following && !grew && !justFinished
+      scrollToBottom(smooth)
+    }
+  }, [messages, activeId, isStreaming, scrollToBottom])
+
+  const handleSend = useCallback(
+    async (text: string, attachments: Attachment[]) => {
+      const sid = activeId
+      const isFirst = (useChatStore.getState().sessions[sid]?.messages.length ?? 0) === 0
+      titlePendingRef.current = isFirst
+      await send(sid, text, attachments)
+      // After the first message, refresh the list and ask backend to title it.
+      if (isFirst) {
+        try {
+          await apiClient.generateSessionTitle(sid, text)
+        } catch {
+          /* ignore */
+        }
+        loadSessions(1)
+        titlePendingRef.current = false
+      }
+    },
+    [activeId, send, loadSessions]
+  )
+
+  const handleNewChat = useCallback(() => {
+    const id = newSession()
+    ensureSession(id)
+    loadHistory(id, 1)
+  }, [newSession, ensureSession, loadHistory])
+
+  const handleClearContext = useCallback(async () => {
+    try {
+      await apiClient.clearContext(activeId)
+    } catch {
+      /* ignore */
+    }
+  }, [activeId])
+
+  const handleStop = useCallback(() => cancel(activeId), [cancel, activeId])
+
+  const handleRegenerate = useCallback((id: string) => regenerate(activeId, id), [regenerate, activeId])
+
+  const handleEdit = useCallback(
+    (id: string) => {
+      const result = editUserMessage(activeId, id)
+      if (result && inputResetRef.current) inputResetRef.current(result.text, result.attachments)
+    },
+    [editUserMessage, activeId]
+  )
+
+  const handleDelete = useCallback(
+    (msg: ChatMessage) => {
+      if (msg.userSeq != null) deleteMessage(activeId, msg.userSeq, true)
+    },
+    [deleteMessage, activeId]
+  )
+
+  // Inline images/videos load asynchronously and grow the bubble after mount,
+  // so a scroll triggered on message change fires before the final height is
+  // known. Re-scroll once media loads, but only while following the bottom.
+  const handleMediaLoad = useCallback(() => {
+    if (followBottomRef.current) scrollToBottom(false)
+  }, [scrollToBottom])
+
+  const handleScroll = useCallback(
+    async (e: React.UIEvent<HTMLDivElement>) => {
+      const el = e.currentTarget
+      // Track whether the user wants to stay pinned to the bottom: scrolling up
+      // pauses auto-follow; returning near the bottom resumes it.
+      followBottomRef.current = el.scrollHeight - el.scrollTop - el.clientHeight < 160
+      const s = useChatStore.getState().sessions[activeId]
+      if (el.scrollTop < 40 && s?.historyHasMore && !loadingMore && !isStreaming) {
+        setLoadingMore(true)
+        const prevHeight = el.scrollHeight
+        await loadHistory(activeId, s.historyPage + 1)
+        requestAnimationFrame(() => {
+          // preserve scroll position after prepending older messages
+          el.scrollTop = el.scrollHeight - prevHeight
+          setLoadingMore(false)
+        })
+      }
+    },
+    [activeId, loadHistory, loadingMore, isStreaming]
+  )
+
+  const isEmpty = messages.length === 0
+
+  return (
+    <div className="flex flex-col flex-1 min-h-0">
+      <div ref={scrollRef} className="flex-1 overflow-y-auto" onScroll={handleScroll}>
+        {loadingMore && (
+          <div className="flex items-center justify-center py-3 text-content-tertiary">
+            <Loader2 size={16} className="animate-spin" />
+          </div>
+        )}
+
+        {isEmpty ? (
+          <div className="flex flex-col items-center justify-center h-full px-6 py-12">
+            <img src="./logo.jpg" alt="CowAgent" className="w-16 h-16 rounded-2xl mb-5 shadow-md" />
+            <h1 className="text-xl font-semibold text-content mb-2">{t('chat_welcome')}</h1>
+            <p className="text-content-tertiary text-sm text-center max-w-md mb-8">{t('chat_empty_hint')}</p>
+
+            <div className="grid grid-cols-2 sm:grid-cols-3 gap-3 w-full max-w-2xl">
+              {SUGGESTIONS.map(({ key, send, icon: Icon, iconClass, bgClass }) => (
+                <button
+                  key={key}
+                  onClick={() => {
+                    // Fill the input (don't auto-send) so the user can tweak it first.
+                    const draft = send ?? t(`${key}_text` as Parameters<typeof t>[0])
+                    inputResetRef.current?.(draft, [])
+                  }}
+                  className="group text-left bg-surface border border-default rounded-xl p-3.5 cursor-pointer hover:border-accent hover:shadow-sm transition-all"
+                >
+                  <div className="flex items-center gap-2 mb-1.5">
+                    <span
+                      className={`w-7 h-7 rounded-lg flex items-center justify-center shrink-0 ${bgClass}`}
+                    >
+                      <Icon size={15} className={iconClass} />
+                    </span>
+                    <span className="font-medium text-sm text-content">
+                      {t(`${key}_title` as Parameters<typeof t>[0])}
+                    </span>
+                  </div>
+                  <p className="text-xs text-content-tertiary leading-relaxed line-clamp-2">
+                    {t(`${key}_text` as Parameters<typeof t>[0])}
+                  </p>
+                </button>
+              ))}
+            </div>
+          </div>
+        ) : (
+          <div className="py-3 max-w-3xl mx-auto">
+            {messages.map((msg) => (
+              <MessageBubble
+                key={msg.id}
+                message={msg}
+                onRegenerate={handleRegenerate}
+                onEdit={handleEdit}
+                onDelete={handleDelete}
+                onMediaLoad={handleMediaLoad}
+              />
+            ))}
+            <div ref={bottomRef} />
+          </div>
+        )}
+      </div>
+
+      {/* Jump-to-bottom affordance could go here in a later pass */}
+
+      <ChatInput
+        onSend={handleSend}
+        onNewChat={handleNewChat}
+        onStop={handleStop}
+        onClearContext={handleClearContext}
+        isStreaming={isStreaming}
+        sessionId={activeId}
+        ref={inputResetRef}
+      />
+    </div>
+  )
+}
+
+export default ChatPage
diff --git a/desktop/src/renderer/src/pages/KnowledgePage.tsx b/desktop/src/renderer/src/pages/KnowledgePage.tsx
new file mode 100644
index 0000000..9b87302
--- /dev/null
+++ b/desktop/src/renderer/src/pages/KnowledgePage.tsx
@@ -0,0 +1,981 @@
+import React, { useCallback, useEffect, useMemo, useRef, useState } from 'react'
+import {
+  Loader2,
+  Search,
+  FileText,
+  ChevronRight,
+  ChevronDown,
+  MessageSquarePlus,
+  Network,
+  Files,
+  Plus,
+  FolderPlus,
+  FilePlus2,
+  Upload,
+} from 'lucide-react'
+import type { LucideIcon } from 'lucide-react'
+import { useNavigate } from 'react-router-dom'
+import { t, getLang } from '../i18n'
+import apiClient from '../api/client'
+import type {
+  KnowledgeDir,
+  KnowledgeFile,
+  KnowledgeList,
+  KnowledgeGraph as KnowledgeGraphData,
+} from '../types'
+import Markdown from '../components/Markdown'
+import KnowledgeGraph from '../components/KnowledgeGraph'
+
+interface KnowledgePageProps {
+  baseUrl: string
+}
+
+type Tab = 'docs' | 'graph'
+
+const KNOWLEDGE_IMPORT_MAX_FILES = 100
+const KNOWLEDGE_IMPORT_MAX_FILE_SIZE = 10 * 1024 * 1024
+const KNOWLEDGE_IMPORT_MAX_TOTAL_SIZE = 200 * 1024 * 1024
+
+// t() with simple {placeholder} interpolation.
+const tf = (key: string, vars: Record<string, string | number>): string => {
+  let out = t(key)
+  for (const [k, v] of Object.entries(vars)) out = out.replace(`{${k}}`, String(v))
+  return out
+}
+
+const formatSize = (bytes: number): string => {
+  if (bytes < 1024) return bytes + ' B'
+  if (bytes < 1024 * 1024) return (bytes / 1024).toFixed(1) + ' KB'
+  return (bytes / (1024 * 1024)).toFixed(1) + ' MB'
+}
+
+// Flatten the tree into category paths (for destination selectors).
+function categoryPaths(dirs: KnowledgeDir[], parent = ''): string[] {
+  const paths: string[] = []
+  for (const dir of dirs || []) {
+    const path = parent ? `${parent}/${dir.dir}` : dir.dir
+    paths.push(path, ...categoryPaths(dir.children || [], path))
+  }
+  return paths
+}
+
+// Validate a batch of files chosen for import. Returns an error message or ''.
+function validateImportFiles(files: File[]): string {
+  if (!files.length) return t('knowledge_import_choose_files')
+  if (files.length > KNOWLEDGE_IMPORT_MAX_FILES) {
+    return tf('knowledge_import_too_many', { max: KNOWLEDGE_IMPORT_MAX_FILES })
+  }
+  let total = 0
+  for (const file of files) {
+    total += file.size || 0
+    if ((file.size || 0) > KNOWLEDGE_IMPORT_MAX_FILE_SIZE) {
+      return tf('knowledge_import_file_too_large', { name: file.name })
+    }
+  }
+  if (total > KNOWLEDGE_IMPORT_MAX_TOTAL_SIZE) return t('knowledge_import_total_too_large')
+  return ''
+}
+
+// ---- Dialog model ----------------------------------------------------------
+
+interface DialogState {
+  kind: 'category' | 'doc-pick-category' | 'document' | 'import'
+  category?: string
+  files?: File[]
+}
+
+// Find the first document (root files first, then a DFS over the tree).
+function firstFile(list: KnowledgeList): { path: string; title: string } | null {
+  const root = list.root_files?.[0]
+  if (root) return { path: root.name, title: root.title || root.name }
+  const walk = (dir: KnowledgeDir, prefix: string): { path: string; title: string } | null => {
+    const dirPath = prefix ? `${prefix}/${dir.dir}` : dir.dir
+    const f = dir.files[0]
+    if (f) return { path: `${dirPath}/${f.name}`, title: f.title || f.name }
+    for (const c of dir.children) {
+      const hit = walk(c, dirPath)
+      if (hit) return hit
+    }
+    return null
+  }
+  for (const d of list.tree || []) {
+    const hit = walk(d, '')
+    if (hit) return hit
+  }
+  return null
+}
+
+// Resolve a document's display title from its path, falling back to the stem.
+function findTitle(list: KnowledgeList, path: string): string {
+  const fallback = path.split('/').pop()?.replace(/\.md$/i, '') || path
+  for (const f of list.root_files || []) {
+    if (f.name === path) return f.title || fallback
+  }
+  const walk = (dir: KnowledgeDir, prefix: string): string | null => {
+    const dirPath = prefix ? `${prefix}/${dir.dir}` : dir.dir
+    for (const f of dir.files) {
+      if (`${dirPath}/${f.name}` === path) return f.title || fallback
+    }
+    for (const c of dir.children) {
+      const hit = walk(c, dirPath)
+      if (hit) return hit
+    }
+    return null
+  }
+  for (const d of list.tree || []) {
+    const hit = walk(d, '')
+    if (hit) return hit
+  }
+  return fallback
+}
+
+const KnowledgePage: React.FC<KnowledgePageProps> = ({ baseUrl }) => {
+  const navigate = useNavigate()
+  const [tab, setTab] = useState<Tab>('docs')
+  const [data, setData] = useState<KnowledgeList | null>(null)
+  const [loading, setLoading] = useState(true)
+  const [search, setSearch] = useState('')
+
+  const [activePath, setActivePath] = useState<string | null>(null)
+  const [docTitle, setDocTitle] = useState('')
+  const [content, setContent] = useState('')
+  const [docLoading, setDocLoading] = useState(false)
+
+  const [graph, setGraph] = useState<KnowledgeGraphData | null>(null)
+  const [graphLoading, setGraphLoading] = useState(false)
+
+  // Management UI state.
+  const [menuOpen, setMenuOpen] = useState(false)
+  const [dialog, setDialog] = useState<DialogState | null>(null)
+  const [status, setStatus] = useState<{ text: string; error: boolean } | null>(null)
+  const [dragOver, setDragOver] = useState(false)
+  const fileInputRef = useRef<HTMLInputElement>(null)
+  const statusTimer = useRef<ReturnType<typeof setTimeout> | null>(null)
+
+  const showStatus = useCallback((text: string, error = false, sticky = false) => {
+    if (statusTimer.current) clearTimeout(statusTimer.current)
+    setStatus({ text, error })
+    if (!sticky) {
+      statusTimer.current = setTimeout(() => setStatus(null), 4000)
+    }
+  }, [])
+
+  const openDoc = useCallback(async (path: string, title: string) => {
+    setActivePath(path)
+    setDocTitle(title)
+    setDocLoading(true)
+    setContent('')
+    try {
+      const res = await apiClient.readKnowledge(path)
+      setContent(res.content || '')
+    } catch {
+      setContent(`> ${t('knowledge_doc_load_error')}`)
+    } finally {
+      setDocLoading(false)
+    }
+  }, [])
+
+  // Reload the tree. When targetPath is given, open it; otherwise keep the
+  // currently open doc (or open the first one on the initial load).
+  const refresh = useCallback(
+    async (targetPath?: string) => {
+      try {
+        const fresh = await apiClient.getKnowledgeList()
+        setData(fresh)
+        if (targetPath) {
+          void openDoc(targetPath, findTitle(fresh, targetPath))
+        } else if (!activePath) {
+          const first = firstFile(fresh)
+          if (first) void openDoc(first.path, first.title)
+        }
+        return fresh
+      } catch (e) {
+        console.error('Failed to load knowledge:', e)
+        return null
+      }
+    },
+    [openDoc, activePath]
+  )
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    let cancelled = false
+    ;(async () => {
+      setLoading(true)
+      try {
+        const fresh = await apiClient.getKnowledgeList()
+        if (cancelled) return
+        setData(fresh)
+        const first = firstFile(fresh)
+        if (first) void openDoc(first.path, first.title)
+      } catch (e) {
+        console.error('Failed to load knowledge:', e)
+      } finally {
+        if (!cancelled) setLoading(false)
+      }
+    })()
+    return () => {
+      cancelled = true
+    }
+    // Only run on baseUrl change (initial mount). refresh() handles later reloads.
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl])
+
+  const loadGraph = useCallback(async () => {
+    if (graph) return
+    setGraphLoading(true)
+    try {
+      setGraph(await apiClient.getKnowledgeGraph())
+    } catch (e) {
+      console.error('Failed to load graph:', e)
+      setGraph({ nodes: [], links: [] })
+    } finally {
+      setGraphLoading(false)
+    }
+  }, [graph])
+
+  const switchTab = (next: Tab) => {
+    setTab(next)
+    if (next === 'graph') void loadGraph()
+  }
+
+  // Jump from a graph node to its document.
+  const onGraphSelect = useCallback(
+    (id: string, label: string) => {
+      setTab('docs')
+      void openDoc(id, label)
+    },
+    [openDoc]
+  )
+
+  // ---- Management actions --------------------------------------------------
+
+  const categories = useMemo(() => categoryPaths(data?.tree || []), [data])
+
+  const createCategory = useCallback(
+    async (path: string): Promise<string | null> => {
+      showStatus(t('knowledge_working'), false, true)
+      try {
+        const res = await apiClient.knowledgeAction({ action: 'create_category', payload: { path } })
+        if (res.status !== 'success') {
+          showStatus((res.message as string) || t('knowledge_request_failed'), true)
+          return null
+        }
+        showStatus(t('knowledge_category_created'))
+        await refresh()
+        return path
+      } catch {
+        showStatus(t('knowledge_request_failed'), true)
+        return null
+      }
+    },
+    [refresh, showStatus]
+  )
+
+  const createDocument = useCallback(
+    async (path: string, content: string): Promise<string | null> => {
+      showStatus(t('knowledge_working'), false, true)
+      try {
+        const res = await apiClient.knowledgeAction({
+          action: 'create_document',
+          payload: { path, content, overwrite: false },
+        })
+        if (res.status !== 'success') {
+          showStatus((res.message as string) || t('knowledge_request_failed'), true)
+          return null
+        }
+        const created = ((res.payload as { path?: string })?.path) || path
+        showStatus(t('knowledge_document_created'))
+        await refresh(created)
+        return created
+      } catch {
+        showStatus(t('knowledge_request_failed'), true)
+        return null
+      }
+    },
+    [refresh, showStatus]
+  )
+
+  const importDocuments = useCallback(
+    async (files: File[], targetCategory: string): Promise<boolean> => {
+      const err = validateImportFiles(files)
+      if (err) {
+        showStatus(err, true)
+        return false
+      }
+      const supported = files.filter((f) => /\.(md|txt)$/i.test(f.name || ''))
+      if (!supported.length) {
+        showStatus(t('knowledge_import_choose_files'), true)
+        return false
+      }
+      showStatus(t('knowledge_importing'), false, true)
+      try {
+        const res = await apiClient.importKnowledge(supported, targetCategory)
+        if (res.status !== 'success') {
+          showStatus(res.message || t('knowledge_import_failed'), true)
+          await refresh()
+          return false
+        }
+        const p = res.payload
+        showStatus(
+          tf('knowledge_import_result', {
+            imported: p?.imported ?? 0,
+            skipped: p?.skipped ?? 0,
+            failed: p?.failed ?? 0,
+          })
+        )
+        const first = (p?.results || []).find((r) => r.status === 'imported')
+        await refresh(first?.path)
+        return true
+      } catch {
+        showStatus(t('knowledge_import_failed'), true)
+        return false
+      }
+    },
+    [refresh, showStatus]
+  )
+
+  // Open the import dialog after validating the chosen files.
+  const startImport = useCallback(
+    (files: File[]) => {
+      const err = validateImportFiles(files)
+      if (err) {
+        showStatus(err, true)
+        return
+      }
+      setDialog({ kind: 'import', files })
+    },
+    [showStatus]
+  )
+
+  const onFilesPicked = useCallback(
+    (e: React.ChangeEvent<HTMLInputElement>) => {
+      const files = Array.from(e.target.files || [])
+      e.target.value = ''
+      if (files.length) startImport(files)
+    },
+    [startImport]
+  )
+
+  const totalPages = data?.stats?.pages ?? 0
+  const statsLabel = useMemo(() => {
+    if (!data) return ''
+    return t('knowledge_stats')
+      .replace('{pages}', String(data.stats?.pages ?? 0))
+      .replace('{size}', formatSize(data.stats?.size ?? 0))
+  }, [data])
+
+  if (loading) {
+    return (
+      <div className="flex-1 flex items-center justify-center text-content-tertiary">
+        <Loader2 size={18} className="animate-spin mr-2" />
+        {t('knowledge_loading')}
+      </div>
+    )
+  }
+
+  const isEmpty = !data || totalPages === 0
+
+  if (isEmpty) {
+    return (
+      <div className="flex-1 flex flex-col items-center justify-center px-6 text-center">
+        <div className="w-14 h-14 rounded-2xl bg-accent-soft text-accent flex items-center justify-center mb-5">
+          <Files size={26} />
+        </div>
+        <h2 className="text-lg font-semibold text-content mb-2">
+          {data?.enabled === false ? t('knowledge_disabled') : t('knowledge_empty')}
+        </h2>
+        <p className="text-sm text-content-tertiary max-w-md mb-6">{t('knowledge_empty_guide')}</p>
+        <button
+          onClick={() => navigate('/')}
+          className="inline-flex items-center gap-2 px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors"
+        >
+          <MessageSquarePlus size={15} />
+          {t('knowledge_go_chat')}
+        </button>
+      </div>
+    )
+  }
+
+  return (
+    <div className="flex-1 flex flex-col min-h-0">
+      {/* Header */}
+      <div className="flex items-center justify-between px-6 pt-5 pb-3 flex-shrink-0">
+        <div>
+          <h2 className="text-xl font-bold text-content">{t('knowledge_title')}</h2>
+          <p className="text-xs text-content-tertiary mt-1">{statsLabel}</p>
+        </div>
+        <div className="flex items-center gap-2">
+          {status && (
+            <span
+              className={`text-xs max-w-[260px] truncate ${
+                status.error ? 'text-danger' : 'text-content-tertiary'
+              }`}
+              title={status.text}
+            >
+              {status.text}
+            </span>
+          )}
+          <div className="flex items-center gap-1 bg-inset rounded-btn p-0.5">
+            <TabBtn icon={Files} label={t('knowledge_tab_docs')} active={tab === 'docs'} onClick={() => switchTab('docs')} />
+            <TabBtn
+              icon={Network}
+              label={t('knowledge_tab_graph')}
+              active={tab === 'graph'}
+              onClick={() => switchTab('graph')}
+            />
+          </div>
+          <NewMenu
+            open={menuOpen}
+            setOpen={setMenuOpen}
+            onCreateCategory={() => setDialog({ kind: 'category' })}
+            onCreateDocument={() => {
+              if (!categories.length) {
+                showStatus(t('knowledge_need_category'), true)
+                return
+              }
+              setDialog({ kind: 'doc-pick-category' })
+            }}
+            onImport={() => fileInputRef.current?.click()}
+          />
+        </div>
+        <input
+          ref={fileInputRef}
+          type="file"
+          multiple
+          accept=".md,.txt,text/markdown,text/plain"
+          className="hidden"
+          onChange={onFilesPicked}
+        />
+      </div>
+
+      {tab === 'docs' ? (
+        <div
+          className="flex-1 flex min-h-0 border-t border-default relative"
+          onDragEnter={(e) => {
+            if (e.dataTransfer?.types?.includes('Files')) {
+              e.preventDefault()
+              setDragOver(true)
+            }
+          }}
+          onDragOver={(e) => {
+            if (e.dataTransfer?.types?.includes('Files')) e.preventDefault()
+          }}
+          onDragLeave={(e) => {
+            // Only clear when leaving the panel, not its children.
+            if (e.currentTarget === e.target) setDragOver(false)
+          }}
+          onDrop={(e) => {
+            e.preventDefault()
+            setDragOver(false)
+            const files = Array.from(e.dataTransfer?.files || [])
+            if (files.length) startImport(files)
+          }}
+        >
+          {dragOver && (
+            <div className="absolute inset-0 z-30 flex items-center justify-center bg-accent-soft/80 border-2 border-dashed border-accent rounded-lg m-2 pointer-events-none">
+              <div className="flex flex-col items-center gap-2 text-accent">
+                <Upload size={28} />
+                <p className="text-sm font-medium">{t('knowledge_drop_hint')}</p>
+              </div>
+            </div>
+          )}
+          {/* Tree sidebar */}
+          <div className="w-72 flex-shrink-0 flex flex-col border-r border-default min-h-0">
+            <div className="p-3 flex-shrink-0">
+              <div className="relative">
+                <Search size={14} className="absolute left-2.5 top-1/2 -translate-y-1/2 text-content-tertiary" />
+                <input
+                  value={search}
+                  onChange={(e) => setSearch(e.target.value)}
+                  placeholder={t('knowledge_search')}
+                  className="w-full pl-8 pr-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors"
+                />
+              </div>
+            </div>
+            <div className="flex-1 overflow-y-auto px-2 pb-3">
+              <Tree
+                data={data}
+                search={search.trim().toLowerCase()}
+                activePath={activePath}
+                onOpen={openDoc}
+              />
+            </div>
+          </div>
+
+          {/* Document viewer */}
+          <div className="flex-1 min-w-0 overflow-y-auto">
+            {!activePath ? (
+              <div className="h-full flex flex-col items-center justify-center text-content-tertiary">
+                <FileText size={28} className="mb-3 opacity-50" />
+                <p className="text-sm">{t('knowledge_select_hint')}</p>
+              </div>
+            ) : (
+              <div className="max-w-3xl mx-auto px-6 py-6">
+                <h1 className="text-lg font-semibold text-content mb-1">{docTitle}</h1>
+                <p className="text-xs text-content-tertiary mb-5 font-mono">{activePath}</p>
+                {docLoading ? (
+                  <div className="flex items-center text-content-tertiary py-8">
+                    <Loader2 size={16} className="animate-spin mr-2" />
+                  </div>
+                ) : (
+                  <Markdown content={content} />
+                )}
+              </div>
+            )}
+          </div>
+        </div>
+      ) : (
+        <div className="flex-1 min-h-0 border-t border-default relative">
+          {graphLoading ? (
+            <div className="absolute inset-0 flex items-center justify-center text-content-tertiary">
+              <Loader2 size={18} className="animate-spin mr-2" />
+            </div>
+          ) : graph && graph.nodes.length > 0 ? (
+            <KnowledgeGraph data={graph} onSelect={onGraphSelect} />
+          ) : (
+            <div className="absolute inset-0 flex items-center justify-center text-content-tertiary text-sm">
+              {t('knowledge_graph_empty')}
+            </div>
+          )}
+        </div>
+      )}
+
+      {dialog && (
+        <KnowledgeDialog
+          state={dialog}
+          categories={categories}
+          onClose={() => setDialog(null)}
+          onCreateCategory={createCategory}
+          onPickDocCategory={(category) => setDialog({ kind: 'document', category })}
+          onCreateDocument={createDocument}
+          onImport={importDocuments}
+        />
+      )}
+    </div>
+  )
+}
+
+// ---- New menu --------------------------------------------------------------
+
+const NewMenu: React.FC<{
+  open: boolean
+  setOpen: (v: boolean) => void
+  onCreateCategory: () => void
+  onCreateDocument: () => void
+  onImport: () => void
+}> = ({ open, setOpen, onCreateCategory, onCreateDocument, onImport }) => {
+  const ref = useRef<HTMLDivElement>(null)
+  useEffect(() => {
+    if (!open) return
+    const onClickOutside = (e: MouseEvent) => {
+      if (ref.current && !ref.current.contains(e.target as Node)) setOpen(false)
+    }
+    document.addEventListener('mousedown', onClickOutside)
+    return () => document.removeEventListener('mousedown', onClickOutside)
+  }, [open, setOpen])
+
+  const pick = (fn: () => void) => {
+    setOpen(false)
+    fn()
+  }
+
+  return (
+    <div ref={ref} className="relative">
+      <button
+        onClick={() => setOpen(!open)}
+        className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors"
+      >
+        <Plus size={14} />
+        {t('knowledge_new')}
+        <ChevronDown size={12} className="opacity-80" />
+      </button>
+      {open && (
+        <div className="absolute right-0 mt-1.5 w-44 z-50 bg-surface border border-default rounded-lg shadow-lg py-1">
+          <MenuItem icon={FolderPlus} label={t('knowledge_new_category')} onClick={() => pick(onCreateCategory)} />
+          <MenuItem icon={FilePlus2} label={t('knowledge_new_document')} onClick={() => pick(onCreateDocument)} />
+          <MenuItem icon={Upload} label={t('knowledge_import_documents')} onClick={() => pick(onImport)} />
+        </div>
+      )}
+    </div>
+  )
+}
+
+const MenuItem: React.FC<{ icon: LucideIcon; label: string; onClick: () => void }> = ({
+  icon: Icon,
+  label,
+  onClick,
+}) => (
+  <button
+    onClick={onClick}
+    className="w-full flex items-center gap-2.5 px-3 py-2 text-sm text-content-secondary hover:bg-surface-2 cursor-pointer transition-colors text-left"
+  >
+    <Icon size={14} className="opacity-70 flex-shrink-0" />
+    {label}
+  </button>
+)
+
+// ---- Dialog ----------------------------------------------------------------
+
+function templateFor(filename: string): string {
+  const title = (filename || 'untitled').replace(/\.md$/i, '')
+  return getLang() === 'zh'
+    ? `# ${title}\n\n## 摘要\n\n\n## 关键点\n\n- \n\n## 参考\n\n`
+    : `# ${title}\n\n## Summary\n\n\n## Key points\n\n- \n\n## References\n\n`
+}
+
+const KnowledgeDialog: React.FC<{
+  state: DialogState
+  categories: string[]
+  onClose: () => void
+  onCreateCategory: (path: string) => Promise<string | null>
+  onPickDocCategory: (category: string) => void
+  onCreateDocument: (path: string, content: string) => Promise<string | null>
+  onImport: (files: File[], target: string) => Promise<boolean>
+}> = ({ state, categories, onClose, onCreateCategory, onPickDocCategory, onCreateDocument, onImport }) => {
+  const [categoryInput, setCategoryInput] = useState('')
+  const [selected, setSelected] = useState(categories[0] || '')
+  const [filename, setFilename] = useState('')
+  const [contentInput, setContentInput] = useState('')
+  const [error, setError] = useState('')
+  const [busy, setBusy] = useState(false)
+
+  const submit = async () => {
+    setError('')
+    if (state.kind === 'category') {
+      const path = categoryInput.trim()
+      if (!path) return setError(t('knowledge_field_required'))
+      setBusy(true)
+      const ok = await onCreateCategory(path)
+      setBusy(false)
+      if (ok !== null) onClose()
+      return
+    }
+    if (state.kind === 'doc-pick-category') {
+      if (!selected) return setError(t('knowledge_field_required'))
+      onPickDocCategory(selected)
+      return
+    }
+    if (state.kind === 'document') {
+      const name = filename.trim()
+      if (!name) return setError(t('knowledge_doc_filename_required'))
+      if (/\.[^.]+$/i.test(name) && !/\.md$/i.test(name)) return setError(t('knowledge_doc_must_md'))
+      if (!contentInput.trim()) return setError(t('knowledge_doc_content_required'))
+      if (new Blob([contentInput]).size > KNOWLEDGE_IMPORT_MAX_FILE_SIZE) {
+        return setError(t('knowledge_doc_content_too_large'))
+      }
+      const safeName = name.endsWith('.md') ? name : `${name}.md`
+      setBusy(true)
+      const ok = await onCreateDocument(`${state.category}/${safeName}`, contentInput)
+      setBusy(false)
+      if (ok !== null) onClose()
+      return
+    }
+    if (state.kind === 'import') {
+      if (!selected) return setError(t('knowledge_field_required'))
+      setBusy(true)
+      const ok = await onImport(state.files || [], selected)
+      setBusy(false)
+      if (ok) onClose()
+      return
+    }
+  }
+
+  const titleMap: Record<DialogState['kind'], string> = {
+    category: t('knowledge_new_category'),
+    'doc-pick-category': t('knowledge_new_document'),
+    document: t('knowledge_new_document'),
+    import: t('knowledge_import_documents'),
+  }
+
+  const noCategory = (state.kind === 'doc-pick-category' || state.kind === 'import') && !categories.length
+
+  return (
+    <div className="fixed inset-0 z-[70] flex items-center justify-center bg-black/40 p-4" onMouseDown={onClose}>
+      <div
+        className="w-full max-w-lg bg-surface border border-default rounded-xl shadow-xl p-5"
+        onMouseDown={(e) => e.stopPropagation()}
+      >
+        <h3 className="text-base font-semibold text-content mb-1">{titleMap[state.kind]}</h3>
+
+        {state.kind === 'category' && (
+          <>
+            <p className="text-xs text-content-tertiary mb-4">{t('knowledge_category_subtitle')}</p>
+            <label className="block text-sm text-content-secondary mb-1.5">{t('knowledge_category_label')}</label>
+            <input
+              autoFocus
+              value={categoryInput}
+              onChange={(e) => setCategoryInput(e.target.value)}
+              onKeyDown={(e) => e.key === 'Enter' && submit()}
+              placeholder="research/ai"
+              className="w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors"
+            />
+            <p className="text-xs text-content-tertiary mt-1.5">{t('knowledge_category_hint')}</p>
+          </>
+        )}
+
+        {state.kind === 'doc-pick-category' && (
+          <>
+            <p className="text-xs text-content-tertiary mb-4">{t('knowledge_doc_choose_category')}</p>
+            <label className="block text-sm text-content-secondary mb-1.5">{t('knowledge_destination')}</label>
+            <CategorySelect value={selected} options={categories} onChange={setSelected} />
+          </>
+        )}
+
+        {state.kind === 'document' && (
+          <>
+            <p className="text-xs text-content-tertiary mb-4">
+              {tf('knowledge_doc_save_to', { category: state.category || '' })}
+            </p>
+            <label className="block text-sm text-content-secondary mb-1.5">{t('knowledge_doc_filename')}</label>
+            <input
+              autoFocus
+              value={filename}
+              onChange={(e) => setFilename(e.target.value)}
+              placeholder="my-note.md"
+              className="w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors mb-3"
+            />
+            <div className="flex items-center justify-between mb-1.5">
+              <label className="text-sm text-content-secondary">{t('knowledge_doc_content')}</label>
+              <button
+                onClick={() => {
+                  if (!contentInput.trim()) setContentInput(templateFor(filename))
+                }}
+                className="text-xs text-accent hover:underline cursor-pointer"
+              >
+                {t('knowledge_doc_insert_template')}
+              </button>
+            </div>
+            <textarea
+              value={contentInput}
+              onChange={(e) => setContentInput(e.target.value)}
+              rows={10}
+              className="w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors font-mono resize-y"
+            />
+          </>
+        )}
+
+        {state.kind === 'import' && (
+          <>
+            <p className="text-xs text-content-tertiary mb-4">
+              {tf('knowledge_import_selected', { count: state.files?.length ?? 0 })}
+            </p>
+            <label className="block text-sm text-content-secondary mb-1.5">{t('knowledge_destination')}</label>
+            <CategorySelect value={selected} options={categories} onChange={setSelected} />
+            <p className="text-xs text-content-tertiary mt-1.5">
+              {categories.length ? t('knowledge_import_hint') : t('knowledge_import_need_category')}
+            </p>
+          </>
+        )}
+
+        {error && <p className="text-xs text-danger mt-3">{error}</p>}
+
+        <div className="flex justify-end gap-2 mt-5">
+          <button
+            onClick={onClose}
+            className="px-4 py-2 rounded-btn border border-strong text-content-secondary hover:bg-surface-2 text-sm font-medium cursor-pointer transition-colors"
+          >
+            {t('knowledge_dialog_cancel')}
+          </button>
+          <button
+            onClick={submit}
+            disabled={busy || noCategory}
+            className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 disabled:cursor-not-allowed inline-flex items-center gap-1.5"
+          >
+            {busy && <Loader2 size={14} className="animate-spin" />}
+            {t('knowledge_dialog_confirm')}
+          </button>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+// Custom dropdown: keeps the arrow / menu styling consistent with the rest of
+// the desktop UI (a native <select> renders an OS arrow we can't space out).
+const CategorySelect: React.FC<{ value: string; options: string[]; onChange: (v: string) => void }> = ({
+  value,
+  options,
+  onChange,
+}) => {
+  const [open, setOpen] = useState(false)
+  const ref = useRef<HTMLDivElement>(null)
+
+  useEffect(() => {
+    if (!open) return
+    const onClickOutside = (e: MouseEvent) => {
+      if (ref.current && !ref.current.contains(e.target as Node)) setOpen(false)
+    }
+    document.addEventListener('mousedown', onClickOutside)
+    return () => document.removeEventListener('mousedown', onClickOutside)
+  }, [open])
+
+  const disabled = !options.length
+
+  return (
+    <div ref={ref} className="relative">
+      <button
+        type="button"
+        disabled={disabled}
+        onClick={() => setOpen((v) => !v)}
+        className={`w-full flex items-center justify-between gap-2 px-3 py-2 rounded-btn border text-sm text-content transition-colors cursor-pointer ${
+          open ? 'border-accent' : 'border-strong'
+        } bg-inset hover:border-accent/70 disabled:opacity-50 disabled:cursor-not-allowed`}
+      >
+        <span className="truncate">{value || '--'}</span>
+        <ChevronDown
+          size={14}
+          className={`flex-shrink-0 text-content-tertiary transition-transform ${open ? 'rotate-180' : ''}`}
+        />
+      </button>
+      {open && (
+        <div className="absolute left-0 right-0 top-full mt-1 z-50 max-h-60 overflow-y-auto bg-surface border border-default rounded-lg shadow-lg p-1">
+          {options.map((opt) => (
+            <button
+              key={opt}
+              type="button"
+              onClick={() => {
+                onChange(opt)
+                setOpen(false)
+              }}
+              className={`w-full text-left px-2.5 py-1.5 rounded-md text-sm cursor-pointer transition-colors truncate ${
+                opt === value ? 'bg-accent-soft text-accent' : 'text-content-secondary hover:bg-surface-2'
+              }`}
+            >
+              {opt}
+            </button>
+          ))}
+        </div>
+      )}
+    </div>
+  )
+}
+
+const TabBtn: React.FC<{
+  icon: LucideIcon
+  label: string
+  active: boolean
+  onClick: () => void
+}> = ({ icon: Icon, label, active, onClick }) => (
+  <button
+    onClick={onClick}
+    className={`inline-flex items-center gap-1.5 px-3 py-1.5 rounded-[6px] text-sm font-medium cursor-pointer transition-colors ${
+      active ? 'bg-surface text-content shadow-sm' : 'text-content-tertiary hover:text-content-secondary'
+    }`}
+  >
+    <Icon size={14} />
+    {label}
+  </button>
+)
+
+// ---- Tree rendering --------------------------------------------------------
+
+const Tree: React.FC<{
+  data: KnowledgeList
+  search: string
+  activePath: string | null
+  onOpen: (path: string, title: string) => void
+}> = ({ data, search, activePath, onOpen }) => {
+  const matches = (f: KnowledgeFile) => !search || f.title.toLowerCase().includes(search) || f.name.toLowerCase().includes(search)
+
+  return (
+    <div className="space-y-0.5">
+      {(data.root_files || []).filter(matches).map((f) => (
+        <FileLeaf
+          key={f.name}
+          path={f.name}
+          title={f.title || f.name}
+          active={activePath === f.name}
+          onOpen={onOpen}
+        />
+      ))}
+      {(data.tree || []).map((dir) => (
+        <DirNode key={dir.dir} dir={dir} prefix="" search={search} activePath={activePath} onOpen={onOpen} />
+      ))}
+    </div>
+  )
+}
+
+// Count files in a dir subtree that match the search.
+function countMatches(dir: KnowledgeDir, search: string): number {
+  const own = dir.files.filter(
+    (f) => !search || f.title.toLowerCase().includes(search) || f.name.toLowerCase().includes(search)
+  ).length
+  return own + dir.children.reduce((acc, c) => acc + countMatches(c, search), 0)
+}
+
+const DirNode: React.FC<{
+  dir: KnowledgeDir
+  prefix: string
+  search: string
+  activePath: string | null
+  onOpen: (path: string, title: string) => void
+}> = ({ dir, prefix, search, activePath, onOpen }) => {
+  const dirPath = prefix ? `${prefix}/${dir.dir}` : dir.dir
+  const [open, setOpen] = useState(true)
+  const matchCount = search ? countMatches(dir, search) : dir.files.length + dir.children.length
+  if (search && matchCount === 0) return null
+
+  const visibleFiles = dir.files.filter(
+    (f) => !search || f.title.toLowerCase().includes(search) || f.name.toLowerCase().includes(search)
+  )
+  const expanded = open || !!search
+
+  return (
+    <div>
+      <button
+        onClick={() => setOpen((v) => !v)}
+        className="w-full flex items-center gap-1 px-2 py-1.5 rounded-btn text-sm text-content-secondary hover:bg-surface-2 cursor-pointer transition-colors"
+      >
+        {expanded ? <ChevronDown size={13} /> : <ChevronRight size={13} />}
+        <span className="truncate font-medium">{dir.dir}</span>
+        <span className="ml-auto text-xs text-content-tertiary">{matchCount}</span>
+      </button>
+      {expanded && (
+        <div className="ml-3 border-l border-default pl-1.5 space-y-0.5">
+          {visibleFiles.map((f) => {
+            const fpath = `${dirPath}/${f.name}`
+            return (
+              <FileLeaf
+                key={fpath}
+                path={fpath}
+                title={f.title || f.name}
+                active={activePath === fpath}
+                onOpen={onOpen}
+              />
+            )
+          })}
+          {dir.children.map((c) => (
+            <DirNode
+              key={c.dir}
+              dir={c}
+              prefix={dirPath}
+              search={search}
+              activePath={activePath}
+              onOpen={onOpen}
+            />
+          ))}
+        </div>
+      )}
+    </div>
+  )
+}
+
+const FileLeaf: React.FC<{
+  path: string
+  title: string
+  active: boolean
+  onOpen: (path: string, title: string) => void
+}> = ({ path, title, active, onOpen }) => (
+  <button
+    onClick={() => onOpen(path, title)}
+    className={`w-full flex items-center gap-2 px-2 py-1.5 rounded-btn text-sm cursor-pointer transition-colors text-left ${
+      active ? 'bg-accent-soft text-accent' : 'text-content-secondary hover:bg-surface-2'
+    }`}
+  >
+    <FileText size={13} className="flex-shrink-0 opacity-70" />
+    <span className="truncate">{title}</span>
+  </button>
+)
+
+export default KnowledgePage
diff --git a/desktop/src/renderer/src/pages/LogsPage.tsx b/desktop/src/renderer/src/pages/LogsPage.tsx
new file mode 100644
index 0000000..e7669d9
--- /dev/null
+++ b/desktop/src/renderer/src/pages/LogsPage.tsx
@@ -0,0 +1,104 @@
+import React, { useState, useEffect, useRef } from 'react'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+
+interface LogsPageProps {
+  baseUrl: string
+}
+
+const LogsPage: React.FC<LogsPageProps> = ({ baseUrl }) => {
+  const [logs, setLogs] = useState<string[]>([])
+  const [autoScroll, setAutoScroll] = useState(true)
+  const containerRef = useRef<HTMLDivElement>(null)
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+
+    const es = apiClient.createLogStream()
+
+    es.onmessage = (event) => {
+      try {
+        const data = JSON.parse(event.data)
+        if (data.type === 'init' && data.content) {
+          setLogs(data.content.split('\n').filter(Boolean))
+        } else if (data.type === 'line' && data.content) {
+          setLogs((prev) => {
+            const next = [...prev, data.content]
+            if (next.length > 2000) return next.slice(-1500)
+            return next
+          })
+        }
+      } catch { /* ignore */ }
+    }
+
+    return () => es.close()
+  }, [baseUrl])
+
+  useEffect(() => {
+    if (autoScroll && containerRef.current) {
+      containerRef.current.scrollTop = containerRef.current.scrollHeight
+    }
+  }, [logs, autoScroll])
+
+  const handleScroll = () => {
+    if (!containerRef.current) return
+    const { scrollTop, scrollHeight, clientHeight } = containerRef.current
+    setAutoScroll(scrollHeight - scrollTop - clientHeight < 50)
+  }
+
+  const getLogColor = (line: string) => {
+    if (line.includes('ERROR') || line.includes('error')) return 'text-red-400'
+    if (line.includes('WARNING') || line.includes('warn')) return 'text-amber-400'
+    if (line.includes('DEBUG')) return 'text-slate-500'
+    return 'text-slate-300'
+  }
+
+  return (
+    <div className="flex-1 overflow-y-auto p-6">
+      <div className="max-w-5xl mx-auto">
+        <div className="flex items-center justify-between mb-6">
+          <div>
+            <h2 className="text-xl font-bold text-slate-800 dark:text-slate-100">{t('logs_title')}</h2>
+            <p className="text-sm text-slate-500 dark:text-slate-400 mt-1">{t('logs_desc')}</p>
+          </div>
+        </div>
+
+        {/* Terminal-style log viewer */}
+        <div className="bg-slate-900 rounded-xl border border-slate-700 overflow-hidden shadow-lg">
+          {/* Terminal header */}
+          <div className="flex items-center gap-2 px-4 py-2.5 bg-slate-800 border-b border-slate-700">
+            <div className="flex gap-1.5">
+              <span className="w-3 h-3 rounded-full bg-red-500/80" />
+              <span className="w-3 h-3 rounded-full bg-amber-500/80" />
+              <span className="w-3 h-3 rounded-full bg-emerald-500/80" />
+            </div>
+            <span className="text-xs text-slate-400 ml-2 font-mono">run.log</span>
+            <div className="flex-1" />
+            <div className="flex items-center gap-1.5">
+              <span className="w-2 h-2 rounded-full bg-emerald-500 animate-pulse" />
+              <span className="text-xs text-slate-500">{t('logs_live')}</span>
+            </div>
+          </div>
+
+          {/* Log content */}
+          <div
+            ref={containerRef}
+            onScroll={handleScroll}
+            className="p-4 overflow-y-auto font-mono text-xs leading-relaxed whitespace-pre-wrap break-all"
+            style={{ height: 'calc(100vh - 272px)' }}
+          >
+            {logs.length > 0 ? (
+              logs.map((line, i) => (
+                <div key={i} className={getLogColor(line)}>{line}</div>
+              ))
+            ) : (
+              <p className="text-slate-500">{t('logs_connecting')}</p>
+            )}
+          </div>
+        </div>
+      </div>
+    </div>
+  )
+}
+
+export default LogsPage
diff --git a/desktop/src/renderer/src/pages/MemoryPage.tsx b/desktop/src/renderer/src/pages/MemoryPage.tsx
new file mode 100644
index 0000000..4ef2033
--- /dev/null
+++ b/desktop/src/renderer/src/pages/MemoryPage.tsx
@@ -0,0 +1,256 @@
+import React, { useCallback, useEffect, useState } from 'react'
+import { Loader2, ArrowLeft, Brain, Sprout, FileText, ChevronLeft, ChevronRight } from 'lucide-react'
+import type { LucideIcon } from 'lucide-react'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import type { MemoryItem, MemoryCategory } from '../types'
+import Markdown from '../components/Markdown'
+
+interface MemoryPageProps {
+  baseUrl: string
+}
+
+type Tab = 'files' | 'evolution'
+const PAGE_SIZE = 10
+
+const formatSize = (bytes: number): string => {
+  if (bytes < 1024) return bytes + ' B'
+  return (bytes / 1024).toFixed(1) + ' KB'
+}
+
+// Map a file's `type` to its display badge.
+const typeBadge = (type: string): { label: string; cls: string } => {
+  switch (type) {
+    case 'global':
+      return { label: t('memory_type_global'), cls: 'bg-accent-soft text-accent' }
+    case 'evolution':
+      return { label: t('memory_type_evolution'), cls: 'bg-inset text-success' }
+    case 'dream':
+      return { label: t('memory_type_dream'), cls: 'bg-inset text-info' }
+    default:
+      return { label: t('memory_type_daily'), cls: 'bg-inset text-content-secondary' }
+  }
+}
+
+const MemoryPage: React.FC<MemoryPageProps> = ({ baseUrl }) => {
+  const [tab, setTab] = useState<Tab>('files')
+  const [items, setItems] = useState<MemoryItem[]>([])
+  const [total, setTotal] = useState(0)
+  const [page, setPage] = useState(1)
+  const [loading, setLoading] = useState(true)
+
+  const [viewing, setViewing] = useState<string | null>(null)
+  const [content, setContent] = useState('')
+  const [docLoading, setDocLoading] = useState(false)
+
+  const category: MemoryCategory = tab === 'evolution' ? 'evolution' : 'memory'
+
+  const loadList = useCallback(
+    async (cat: MemoryCategory, p: number) => {
+      try {
+        setLoading(true)
+        const data = await apiClient.getMemoryList(p, PAGE_SIZE, cat)
+        setItems(data.list || [])
+        setTotal(data.total || 0)
+        setPage(data.page || p)
+      } catch (err) {
+        console.error('Failed to load memory:', err)
+        setItems([])
+        setTotal(0)
+      } finally {
+        setLoading(false)
+      }
+    },
+    []
+  )
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    void loadList(category, 1)
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl, tab])
+
+  const openFile = async (item: MemoryItem) => {
+    // In the evolution tab a file lives in its own dir (dream vs evolution).
+    const fileCategory: MemoryCategory =
+      item.type === 'dream' || item.type === 'evolution' ? (item.type as MemoryCategory) : category
+    setViewing(item.filename)
+    setDocLoading(true)
+    setContent('')
+    try {
+      const text = await apiClient.getMemoryContent(item.filename, fileCategory)
+      setContent(text)
+    } catch {
+      setContent(`> ${t('memory_doc_load_error')}`)
+    } finally {
+      setDocLoading(false)
+    }
+  }
+
+  const totalPages = Math.max(1, Math.ceil(total / PAGE_SIZE))
+
+  return (
+    <div className="flex-1 flex flex-col min-h-0">
+      {/* Header */}
+      <div className="flex items-center justify-between px-6 pt-5 pb-3 flex-shrink-0">
+        <div>
+          <h2 className="text-xl font-bold text-content">{t('memory_title')}</h2>
+          <p className="text-xs text-content-tertiary mt-1">{t('memory_desc')}</p>
+        </div>
+        {!viewing && (
+          <div className="flex items-center gap-1 bg-inset rounded-btn p-0.5">
+            <TabBtn icon={Brain} label={t('memory_tab_files')} active={tab === 'files'} onClick={() => setTab('files')} />
+            <TabBtn
+              icon={Sprout}
+              label={t('memory_tab_dreams')}
+              active={tab === 'evolution'}
+              onClick={() => setTab('evolution')}
+            />
+          </div>
+        )}
+      </div>
+
+      {viewing ? (
+        /* File viewer */
+        <div className="flex-1 flex flex-col min-h-0 border-t border-default">
+          <div className="flex items-center gap-3 px-6 py-3 flex-shrink-0 border-b border-subtle">
+            <button
+              onClick={() => setViewing(null)}
+              className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn text-sm text-content-secondary hover:bg-inset border border-strong transition-colors cursor-pointer"
+            >
+              <ArrowLeft size={14} />
+              {t('memory_back')}
+            </button>
+            <h3 className="text-sm font-semibold text-content font-mono truncate">{viewing}</h3>
+          </div>
+          <div className="flex-1 overflow-y-auto">
+            <div className="max-w-3xl mx-auto px-6 py-6">
+              {docLoading ? (
+                <div className="flex items-center text-content-tertiary py-8">
+                  <Loader2 size={16} className="animate-spin mr-2" />
+                </div>
+              ) : (
+                <Markdown content={content} />
+              )}
+            </div>
+          </div>
+        </div>
+      ) : (
+        /* List */
+        <div className="flex-1 overflow-y-auto border-t border-default">
+          <div className="max-w-4xl mx-auto px-6 py-5">
+            {loading ? (
+              <div className="flex items-center justify-center py-20 text-content-tertiary">
+                <Loader2 size={18} className="animate-spin mr-2" />
+                {t('memory_loading')}
+              </div>
+            ) : items.length === 0 ? (
+              <div className="flex flex-col items-center justify-center py-20 text-content-tertiary">
+                {tab === 'evolution' ? <Sprout size={28} className="mb-3 opacity-60" /> : <Brain size={28} className="mb-3 opacity-60" />}
+                <p className="text-sm">{tab === 'evolution' ? t('memory_empty_evolution') : t('memory_empty_files')}</p>
+              </div>
+            ) : (
+              <>
+                <div className="rounded-card border border-default overflow-hidden bg-surface">
+                  <table className="w-full">
+                    <thead>
+                      <tr className="border-b border-default">
+                        <Th>{t('memory_col_name')}</Th>
+                        <Th>{t('memory_col_type')}</Th>
+                        <Th>{t('memory_col_size')}</Th>
+                        <Th>{t('memory_col_updated')}</Th>
+                      </tr>
+                    </thead>
+                    <tbody>
+                      {items.map((item) => {
+                        const badge = typeBadge(item.type)
+                        return (
+                          <tr
+                            key={item.filename}
+                            onClick={() => openFile(item)}
+                            className="border-b border-subtle last:border-0 hover:bg-inset cursor-pointer transition-colors"
+                          >
+                            <td className="px-4 py-3 text-sm font-mono text-content-secondary">
+                              <span className="inline-flex items-center gap-2">
+                                <FileText size={13} className="text-content-tertiary flex-shrink-0" />
+                                {item.filename}
+                              </span>
+                            </td>
+                            <td className="px-4 py-3">
+                              <span className={`px-2 py-0.5 rounded-full text-xs font-medium ${badge.cls}`}>{badge.label}</span>
+                            </td>
+                            <td className="px-4 py-3 text-sm text-content-tertiary">{formatSize(item.size)}</td>
+                            <td className="px-4 py-3 text-sm text-content-tertiary">{item.updated_at}</td>
+                          </tr>
+                        )
+                      })}
+                    </tbody>
+                  </table>
+                </div>
+
+                {totalPages > 1 && (
+                  <div className="flex items-center justify-between mt-4 text-sm text-content-tertiary">
+                    <span>
+                      {page} / {totalPages}
+                    </span>
+                    <div className="flex gap-2">
+                      <PageBtn icon={ChevronLeft} label={t('memory_prev')} disabled={page <= 1} onClick={() => loadList(category, page - 1)} />
+                      <PageBtn
+                        icon={ChevronRight}
+                        label={t('memory_next')}
+                        disabled={page >= totalPages}
+                        onClick={() => loadList(category, page + 1)}
+                        iconRight
+                      />
+                    </div>
+                  </div>
+                )}
+              </>
+            )}
+          </div>
+        </div>
+      )}
+    </div>
+  )
+}
+
+const Th: React.FC<{ children: React.ReactNode }> = ({ children }) => (
+  <th className="text-left px-4 py-2.5 text-xs font-semibold uppercase tracking-wider text-content-tertiary">{children}</th>
+)
+
+const TabBtn: React.FC<{ icon: LucideIcon; label: string; active: boolean; onClick: () => void }> = ({
+  icon: Icon,
+  label,
+  active,
+  onClick,
+}) => (
+  <button
+    onClick={onClick}
+    className={`inline-flex items-center gap-1.5 px-3 py-1.5 rounded-[6px] text-sm font-medium cursor-pointer transition-colors ${
+      active ? 'bg-surface text-content shadow-sm' : 'text-content-tertiary hover:text-content-secondary'
+    }`}
+  >
+    <Icon size={14} />
+    {label}
+  </button>
+)
+
+const PageBtn: React.FC<{
+  icon: LucideIcon
+  label: string
+  disabled: boolean
+  onClick: () => void
+  iconRight?: boolean
+}> = ({ icon: Icon, label, disabled, onClick, iconRight }) => (
+  <button
+    onClick={onClick}
+    disabled={disabled}
+    className="inline-flex items-center gap-1 px-3 py-1 rounded-btn border border-strong text-xs text-content-secondary hover:bg-inset disabled:opacity-40 disabled:cursor-not-allowed transition-colors cursor-pointer"
+  >
+    {!iconRight && <Icon size={13} />}
+    {label}
+    {iconRight && <Icon size={13} />}
+  </button>
+)
+
+export default MemoryPage
diff --git a/desktop/src/renderer/src/pages/PlaceholderPage.tsx b/desktop/src/renderer/src/pages/PlaceholderPage.tsx
new file mode 100644
index 0000000..e1d414b
--- /dev/null
+++ b/desktop/src/renderer/src/pages/PlaceholderPage.tsx
@@ -0,0 +1,20 @@
+import React from 'react'
+import { Construction } from 'lucide-react'
+
+interface PlaceholderPageProps {
+  title: string
+  hint?: string
+}
+
+/** Temporary page for routes that will be implemented in later phases. */
+const PlaceholderPage: React.FC<PlaceholderPageProps> = ({ title, hint }) => (
+  <div className="flex flex-col items-center justify-center h-full text-center px-8">
+    <div className="w-14 h-14 rounded-2xl bg-surface-2 flex items-center justify-center mb-4">
+      <Construction size={26} className="text-content-tertiary" />
+    </div>
+    <h2 className="text-lg font-semibold text-content mb-1">{title}</h2>
+    <p className="text-sm text-content-tertiary max-w-sm">{hint || 'Coming soon in this iteration.'}</p>
+  </div>
+)
+
+export default PlaceholderPage
diff --git a/desktop/src/renderer/src/pages/SettingsPage.tsx b/desktop/src/renderer/src/pages/SettingsPage.tsx
new file mode 100644
index 0000000..edf509a
--- /dev/null
+++ b/desktop/src/renderer/src/pages/SettingsPage.tsx
@@ -0,0 +1,60 @@
+import React, { useState } from 'react'
+import { useLocation } from 'react-router-dom'
+import { t } from '../i18n'
+import BasicSettings from './settings/BasicSettings'
+import ModelsTab from './settings/ModelsTab'
+
+interface SettingsPageProps {
+  baseUrl: string
+  onLangChange?: () => void
+}
+
+type Tab = 'basic' | 'models'
+
+const SettingsPage: React.FC<SettingsPageProps> = ({ baseUrl, onLangChange }) => {
+  const location = useLocation()
+  // Allow deep-linking to the models tab via /settings?tab=models.
+  const initial: Tab = new URLSearchParams(location.search).get('tab') === 'models' ? 'models' : 'basic'
+  const [tab, setTab] = useState<Tab>(initial)
+
+  const tabs: { key: Tab; label: string }[] = [
+    { key: 'basic', label: t('settings_tab_basic') },
+    { key: 'models', label: t('settings_tab_models') },
+  ]
+
+  return (
+    <div className="flex-1 overflow-y-auto p-6">
+      <div className="max-w-3xl mx-auto">
+        <div className="mb-5">
+          <h2 className="text-xl font-bold text-content">{t('menu_settings')}</h2>
+          <p className="text-sm text-content-tertiary mt-1">{t('config_desc')}</p>
+        </div>
+
+        {/* Tab bar */}
+        <div className="flex items-center gap-1 mb-6 border-b border-default">
+          {tabs.map((tb) => (
+            <button
+              key={tb.key}
+              onClick={() => setTab(tb.key)}
+              className={`relative px-4 py-2.5 text-sm font-medium cursor-pointer transition-colors -mb-px border-b-2 ${
+                tab === tb.key
+                  ? 'text-accent border-accent'
+                  : 'text-content-tertiary border-transparent hover:text-content-secondary'
+              }`}
+            >
+              {tb.label}
+            </button>
+          ))}
+        </div>
+
+        {tab === 'basic' ? (
+          <BasicSettings baseUrl={baseUrl} onLangChange={onLangChange} onOpenModels={() => setTab('models')} />
+        ) : (
+          <ModelsTab baseUrl={baseUrl} />
+        )}
+      </div>
+    </div>
+  )
+}
+
+export default SettingsPage
diff --git a/desktop/src/renderer/src/pages/SkillsPage.tsx b/desktop/src/renderer/src/pages/SkillsPage.tsx
new file mode 100644
index 0000000..11863ec
--- /dev/null
+++ b/desktop/src/renderer/src/pages/SkillsPage.tsx
@@ -0,0 +1,142 @@
+import React, { useEffect, useState } from 'react'
+import { Loader2, Wrench, Zap, Puzzle } from 'lucide-react'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import type { ToolInfo, SkillInfo } from '../types'
+import { Toggle } from './settings/primitives'
+
+interface SkillsPageProps {
+  baseUrl: string
+}
+
+const SKILL_HUB_URL = 'https://skills.cowagent.ai/'
+
+const SkillsPage: React.FC<SkillsPageProps> = ({ baseUrl }) => {
+  const [tools, setTools] = useState<ToolInfo[]>([])
+  const [skills, setSkills] = useState<SkillInfo[]>([])
+  const [loading, setLoading] = useState(true)
+
+  const loadData = async () => {
+    try {
+      setLoading(true)
+      const [toolsData, skillsData] = await Promise.all([apiClient.getTools(), apiClient.getSkills()])
+      setTools(toolsData || [])
+      setSkills(skillsData || [])
+    } catch (err) {
+      console.error('Failed to load skills:', err)
+    } finally {
+      setLoading(false)
+    }
+  }
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    void loadData()
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl])
+
+  const toggle = async (skill: SkillInfo, enabled: boolean) => {
+    // Optimistic flip; revert on failure.
+    setSkills((prev) => prev.map((s) => (s.name === skill.name ? { ...s, enabled } : s)))
+    try {
+      const res = await apiClient.toggleSkill(skill.name, enabled ? 'open' : 'close')
+      if (res.status !== 'success') throw new Error()
+    } catch {
+      setSkills((prev) => prev.map((s) => (s.name === skill.name ? { ...s, enabled: !enabled } : s)))
+    }
+  }
+
+  return (
+    <div className="flex-1 flex flex-col min-h-0">
+      <div className="flex items-center justify-between px-6 pt-5 pb-3 flex-shrink-0">
+        <div>
+          <h2 className="text-xl font-bold text-content">{t('skills_title')}</h2>
+          <p className="text-xs text-content-tertiary mt-1">{t('skills_desc')}</p>
+        </div>
+        <a
+          href={SKILL_HUB_URL}
+          target="_blank"
+          rel="noopener noreferrer"
+          className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn text-xs font-medium text-accent bg-accent-soft hover:bg-accent-soft transition-colors"
+        >
+          <Puzzle size={12} />
+          {t('skills_hub_btn')}
+        </a>
+      </div>
+
+      <div className="flex-1 overflow-y-auto border-t border-default">
+        <div className="max-w-4xl mx-auto px-6 py-5">
+          {loading ? (
+            <div className="flex items-center justify-center py-20 text-content-tertiary">
+              <Loader2 size={18} className="animate-spin mr-2" />
+              {t('skills_loading')}
+            </div>
+          ) : (
+            <div className="space-y-8">
+              <Section title={t('tools_section_title')} count={tools.length}>
+                {tools.length === 0 ? (
+                  <Empty text={t('tools_empty')} />
+                ) : (
+                  <div className="grid gap-3 sm:grid-cols-2">
+                    {tools.map((tool) => (
+                      <div key={tool.name} className="rounded-card border border-default bg-surface p-4">
+                        <div className="flex items-center gap-2 mb-1.5">
+                          <Wrench size={13} className="text-content-tertiary flex-shrink-0" />
+                          <span className="text-sm font-medium text-content font-mono truncate">{tool.name}</span>
+                        </div>
+                        <p className="text-xs text-content-tertiary leading-relaxed line-clamp-2">{tool.description || '--'}</p>
+                      </div>
+                    ))}
+                  </div>
+                )}
+              </Section>
+
+              <Section title={t('skills_section_title')} count={skills.length}>
+                {skills.length === 0 ? (
+                  <Empty text={t('skills_empty')} />
+                ) : (
+                  <div className="grid gap-3 sm:grid-cols-2">
+                    {skills.map((skill) => (
+                      <div key={skill.name} className="rounded-card border border-default bg-surface p-4 flex items-start gap-3">
+                        <div className="w-9 h-9 rounded-lg bg-inset flex items-center justify-center flex-shrink-0">
+                          <Zap size={15} className={skill.enabled ? 'text-accent' : 'text-content-tertiary'} />
+                        </div>
+                        <div className="flex-1 min-w-0">
+                          <div className="flex items-center gap-2 mb-1">
+                            <span className="text-sm font-medium text-content truncate flex-1">
+                              {skill.display_name || skill.name}
+                            </span>
+                            <Toggle checked={skill.enabled} onChange={(v) => toggle(skill, v)} />
+                          </div>
+                          <p className="text-xs text-content-tertiary leading-relaxed line-clamp-2">{skill.description || '--'}</p>
+                        </div>
+                      </div>
+                    ))}
+                  </div>
+                )}
+              </Section>
+            </div>
+          )}
+        </div>
+      </div>
+    </div>
+  )
+}
+
+const Section: React.FC<{ title: string; count: number; children: React.ReactNode }> = ({ title, count, children }) => (
+  <div>
+    <div className="flex items-center gap-2 mb-3">
+      <span className="text-xs font-semibold uppercase tracking-wider text-content-tertiary">{title}</span>
+      {count > 0 && (
+        <span className="px-1.5 py-0.5 rounded-full text-xs bg-inset text-content-tertiary min-w-[20px] text-center">{count}</span>
+      )}
+    </div>
+    {children}
+  </div>
+)
+
+const Empty: React.FC<{ text: string }> = ({ text }) => (
+  <p className="text-sm text-content-tertiary py-2">{text}</p>
+)
+
+export default SkillsPage
diff --git a/desktop/src/renderer/src/pages/TasksPage.tsx b/desktop/src/renderer/src/pages/TasksPage.tsx
new file mode 100644
index 0000000..aff099e
--- /dev/null
+++ b/desktop/src/renderer/src/pages/TasksPage.tsx
@@ -0,0 +1,314 @@
+import React, { useEffect, useState } from 'react'
+import { Loader2, Clock, CalendarClock } from 'lucide-react'
+import { useNavigate } from 'react-router-dom'
+import { t } from '../i18n'
+import apiClient from '../api/client'
+import type { SchedulerTask, TaskSchedule, TaskAction } from '../types'
+import { Modal, Btn, Toggle, TextInput, Dropdown } from './settings/primitives'
+
+interface TasksPageProps {
+  baseUrl: string
+}
+
+// Human-readable schedule summary, mirroring the web console.
+const scheduleSummary = (s: TaskSchedule): string => {
+  if (s.type === 'cron') return s.expression || 'cron'
+  if (s.type === 'interval') {
+    const sec = s.seconds || 0
+    const h = Math.floor(sec / 3600)
+    const m = Math.floor((sec % 3600) / 60)
+    const r = sec % 60
+    const parts: string[] = []
+    if (h) parts.push(`${h}h`)
+    if (m) parts.push(`${m}m`)
+    if (r || parts.length === 0) parts.push(`${r}s`)
+    return parts.join(' ')
+  }
+  return s.type || 'once'
+}
+
+const formatNextRun = (iso?: string): string => {
+  if (!iso) return '--'
+  const d = new Date(iso)
+  return isNaN(d.getTime()) ? '--' : d.toLocaleString()
+}
+
+const TasksPage: React.FC<TasksPageProps> = ({ baseUrl }) => {
+  const navigate = useNavigate()
+  const [tasks, setTasks] = useState<SchedulerTask[]>([])
+  const [loading, setLoading] = useState(true)
+  const [editing, setEditing] = useState<SchedulerTask | null>(null)
+
+  const loadTasks = async () => {
+    try {
+      setLoading(true)
+      const data = await apiClient.getSchedulerTasks()
+      setTasks(data || [])
+    } catch (err) {
+      console.error('Failed to load tasks:', err)
+      setTasks([])
+    } finally {
+      setLoading(false)
+    }
+  }
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    void loadTasks()
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl])
+
+  const toggle = async (task: SchedulerTask, enabled: boolean) => {
+    // Optimistic flip; revert on failure.
+    setTasks((prev) => prev.map((x) => (x.id === task.id ? { ...x, enabled } : x)))
+    try {
+      await apiClient.toggleTask(task.id, enabled)
+    } catch {
+      setTasks((prev) => prev.map((x) => (x.id === task.id ? { ...x, enabled: !enabled } : x)))
+    }
+  }
+
+  return (
+    <div className="flex-1 flex flex-col min-h-0">
+      <div className="px-6 pt-5 pb-3 flex-shrink-0">
+        <h2 className="text-xl font-bold text-content">{t('tasks_title')}</h2>
+        <p className="text-xs text-content-tertiary mt-1">{t('tasks_desc')}</p>
+      </div>
+
+      <div className="flex-1 overflow-y-auto border-t border-default">
+        <div className="max-w-3xl mx-auto px-6 py-5">
+          {loading ? (
+            <div className="flex items-center justify-center py-20 text-content-tertiary">
+              <Loader2 size={18} className="animate-spin mr-2" />
+              {t('tasks_loading')}
+            </div>
+          ) : tasks.length === 0 ? (
+            <div className="flex flex-col items-center justify-center py-20 text-center">
+              <CalendarClock size={32} className="mb-3 text-content-tertiary opacity-60" />
+              <p className="text-content font-medium mb-1">{t('tasks_empty')}</p>
+              <p className="text-sm text-content-tertiary max-w-sm mb-5">{t('tasks_empty_guide')}</p>
+              <button
+                onClick={() => navigate('/')}
+                className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors"
+              >
+                {t('tasks_go_chat')}
+              </button>
+            </div>
+          ) : (
+            <div className="grid gap-3">
+              {tasks.map((task) => {
+                const content = task.action?.content || task.action?.task_description || ''
+                return (
+                  <div
+                    key={task.id}
+                    onClick={() => setEditing(task)}
+                    className={`rounded-card border border-default bg-surface p-4 cursor-pointer hover:border-strong transition-colors ${
+                      task.enabled ? '' : 'opacity-60'
+                    }`}
+                  >
+                    <div className="flex items-center gap-2 mb-2">
+                      <span className={`w-2 h-2 rounded-full flex-shrink-0 ${task.enabled ? 'bg-accent' : 'bg-content-tertiary'}`} />
+                      <span className="font-medium text-sm text-content truncate">{task.name || task.id}</span>
+                      <div className="flex-1" />
+                      <span className="text-xs font-mono text-content-tertiary">{scheduleSummary(task.schedule)}</span>
+                    </div>
+                    {content && <p className="text-xs text-content-secondary mb-2 line-clamp-2">{content}</p>}
+                    <div
+                      className="flex items-center gap-2 text-xs text-content-tertiary"
+                      onClick={(e) => e.stopPropagation()}
+                    >
+                      <Clock size={12} />
+                      <span>
+                        {t('tasks_next_run')}: {formatNextRun(task.next_run_at)}
+                      </span>
+                      <div className="flex-1" />
+                      <Toggle checked={task.enabled} onChange={(v) => toggle(task, v)} />
+                    </div>
+                  </div>
+                )
+              })}
+            </div>
+          )}
+        </div>
+      </div>
+
+      {editing && (
+        <TaskEditModal
+          task={editing}
+          onClose={() => setEditing(null)}
+          onSaved={() => {
+            setEditing(null)
+            void loadTasks()
+          }}
+          onDeleted={() => {
+            setEditing(null)
+            void loadTasks()
+          }}
+        />
+      )}
+    </div>
+  )
+}
+
+const TaskEditModal: React.FC<{
+  task: SchedulerTask
+  onClose: () => void
+  onSaved: () => void
+  onDeleted: () => void
+}> = ({ task, onClose, onSaved, onDeleted }) => {
+  const [name, setName] = useState(task.name || '')
+  const [enabled, setEnabled] = useState(task.enabled)
+  const [schedType, setSchedType] = useState<TaskSchedule['type']>(task.schedule.type || 'cron')
+  const [cron, setCron] = useState(task.schedule.expression || '')
+  const [interval, setIntervalVal] = useState(task.schedule.seconds ? String(task.schedule.seconds) : '')
+  const [runAt, setRunAt] = useState(task.schedule.run_at ? task.schedule.run_at.slice(0, 16) : '')
+  const [actionType, setActionType] = useState<TaskAction['type']>(task.action.type || 'send_message')
+  const [content, setContent] = useState(task.action.content || task.action.task_description || '')
+  const [saving, setSaving] = useState(false)
+  const [error, setError] = useState('')
+
+  const buildSchedule = (): TaskSchedule => {
+    if (schedType === 'cron') return { type: 'cron', expression: cron.trim() }
+    if (schedType === 'interval') return { type: 'interval', seconds: Number(interval) || 0 }
+    return { type: 'once', run_at: runAt }
+  }
+
+  const buildAction = (): TaskAction => {
+    const a: TaskAction = { ...task.action, type: actionType }
+    if (actionType === 'send_message') a.content = content
+    else a.task_description = content
+    return a
+  }
+
+  const save = async () => {
+    setSaving(true)
+    setError('')
+    try {
+      await apiClient.updateTask(task.id, {
+        name: name.trim(),
+        enabled,
+        schedule: buildSchedule(),
+        action: buildAction(),
+      })
+      onSaved()
+    } catch (e) {
+      setError(e instanceof Error ? e.message : t('task_save_error'))
+    } finally {
+      setSaving(false)
+    }
+  }
+
+  const del = async () => {
+    if (!window.confirm(t('task_delete_confirm'))) return
+    setSaving(true)
+    try {
+      await apiClient.deleteTask(task.id)
+      onDeleted()
+    } catch {
+      setSaving(false)
+    }
+  }
+
+  return (
+    <Modal
+      open
+      title={t('task_edit_title')}
+      onClose={onClose}
+      footer={
+        <>
+          <Btn variant="danger" onClick={del} disabled={saving} className="mr-auto">
+            {t('task_delete')}
+          </Btn>
+          <Btn variant="ghost" onClick={onClose} disabled={saving}>
+            {t('task_cancel')}
+          </Btn>
+          <Btn variant="primary" onClick={save} disabled={saving}>
+            {t('task_save')}
+          </Btn>
+        </>
+      }
+    >
+      <Field label={t('task_name')}>
+        <TextInput value={name} onChange={(e) => setName(e.target.value)} />
+      </Field>
+
+      <div className="flex items-center justify-between">
+        <span className="text-sm text-content-secondary">{t('task_enabled')}</span>
+        <Toggle checked={enabled} onChange={setEnabled} />
+      </div>
+
+      <Field label={t('task_schedule_type')}>
+        <Dropdown
+          value={schedType}
+          onChange={(v) => setSchedType(v as TaskSchedule['type'])}
+          options={[
+            { value: 'cron', label: t('task_type_cron') },
+            { value: 'interval', label: t('task_type_interval') },
+            { value: 'once', label: t('task_type_once') },
+          ]}
+        />
+      </Field>
+
+      {schedType === 'cron' && (
+        <Field label={t('task_cron_expr')} hint={t('task_cron_hint')}>
+          <TextInput value={cron} onChange={(e) => setCron(e.target.value)} placeholder="0 9 * * *" className="font-mono" />
+        </Field>
+      )}
+      {schedType === 'interval' && (
+        <Field label={t('task_interval_seconds')}>
+          <TextInput type="number" value={interval} onChange={(e) => setIntervalVal(e.target.value)} />
+        </Field>
+      )}
+      {schedType === 'once' && (
+        <Field label={t('task_once_time')}>
+          <TextInput type="datetime-local" value={runAt} onChange={(e) => setRunAt(e.target.value)} />
+        </Field>
+      )}
+
+      <Field label={t('task_action_type')}>
+        <Dropdown
+          value={actionType}
+          onChange={(v) => setActionType(v as TaskAction['type'])}
+          options={[
+            { value: 'send_message', label: t('task_action_send') },
+            { value: 'agent_task', label: t('task_action_agent') },
+          ]}
+        />
+      </Field>
+
+      <Field label={actionType === 'send_message' ? t('task_message_content') : t('task_task_description')}>
+        <textarea
+          value={content}
+          onChange={(e) => setContent(e.target.value)}
+          rows={3}
+          className="w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors resize-none"
+        />
+      </Field>
+
+      {/* Channel and receiver are channel-bound and read-only after creation. */}
+      {(task.action.channel_type || task.action.receiver) && (
+        <div className="grid grid-cols-2 gap-3">
+          <Field label={t('task_channel')}>
+            <TextInput value={task.action.channel_type || 'web'} disabled />
+          </Field>
+          <Field label={t('task_receiver')}>
+            <TextInput value={task.action.receiver_name || task.action.receiver || '--'} disabled />
+          </Field>
+        </div>
+      )}
+      <p className="text-xs text-content-tertiary">{t('task_channel_locked')}</p>
+
+      {error && <p className="text-xs text-danger">{error}</p>}
+    </Modal>
+  )
+}
+
+const Field: React.FC<{ label: string; hint?: string; children: React.ReactNode }> = ({ label, hint, children }) => (
+  <div>
+    <label className="block text-sm text-content-secondary mb-1.5">{label}</label>
+    {children}
+    {hint && <p className="text-xs text-content-tertiary mt-1">{hint}</p>}
+  </div>
+)
+
+export default TasksPage
diff --git a/desktop/src/renderer/src/pages/settings/BasicSettings.tsx b/desktop/src/renderer/src/pages/settings/BasicSettings.tsx
new file mode 100644
index 0000000..3395cef
--- /dev/null
+++ b/desktop/src/renderer/src/pages/settings/BasicSettings.tsx
@@ -0,0 +1,346 @@
+import React, { useState, useEffect } from 'react'
+import { Cpu, Bot, ShieldCheck, Languages, Eye, EyeOff, ArrowRight, Loader2 } from 'lucide-react'
+import { t, getLang, setLang, localizedLabel, type Lang } from '../../i18n'
+import apiClient from '../../api/client'
+import type { ConfigData, ProviderMeta } from '../../types'
+import { Card, Field, Dropdown, Toggle, TextInput, SaveRow, MASK_RE } from './primitives'
+
+interface BasicSettingsProps {
+  baseUrl: string
+  onLangChange?: () => void
+  onOpenModels?: () => void
+}
+
+const BasicSettings: React.FC<BasicSettingsProps> = ({ baseUrl, onLangChange, onOpenModels }) => {
+  const [config, setConfig] = useState<ConfigData | null>(null)
+  const [loading, setLoading] = useState(true)
+
+  // model card — credentials (key/base) now live in the Models tab
+  const [provider, setProvider] = useState('')
+  const [model, setModel] = useState('')
+  const [customModel, setCustomModel] = useState('')
+  const [showCustom, setShowCustom] = useState(false)
+  const [modelStatus, setModelStatus] = useState('')
+
+  // agent card
+  const [maxTokens, setMaxTokens] = useState(100000)
+  const [maxTurns, setMaxTurns] = useState(20)
+  const [maxSteps, setMaxSteps] = useState(20)
+  const [thinking, setThinking] = useState(false)
+  const [evolution, setEvolution] = useState(false)
+  const [agentStatus, setAgentStatus] = useState('')
+
+  // security card
+  const [password, setPassword] = useState('')
+  const [pwDirty, setPwDirty] = useState(false)
+  const [pwVisible, setPwVisible] = useState(false)
+  const [pwStatus, setPwStatus] = useState('')
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    loadConfig()
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [baseUrl])
+
+  const providerMeta = (id: string): ProviderMeta | undefined => config?.providers?.[id] as ProviderMeta | undefined
+
+  const loadConfig = async () => {
+    try {
+      setLoading(true)
+      const data = await apiClient.getConfig()
+      setConfig(data)
+      setModel(data.model || '')
+      setMaxTokens(data.agent_max_context_tokens ?? 100000)
+      setMaxTurns(data.agent_max_context_turns ?? 20)
+      setMaxSteps(data.agent_max_steps ?? 20)
+      setThinking(!!data.enable_thinking)
+      setEvolution(!!data.self_evolution_enabled)
+      // Prefer the real password (desktop only) so it can be edited in place;
+      // fall back to the masked value for browser access.
+      setPassword(data.web_password ?? data.web_password_masked ?? '')
+      setPwDirty(false)
+
+      const ids = data.providers ? Object.keys(data.providers) : []
+      const current = data.use_linkai ? 'linkai' : data.bot_type || ids[0] || ''
+      setProvider(current)
+      const meta = data.providers?.[current] as ProviderMeta | undefined
+      const presets = meta?.models || []
+      if (data.model && presets.length && !presets.includes(data.model)) {
+        setShowCustom(true)
+        setCustomModel(data.model)
+      }
+    } catch (err) {
+      console.error('Failed to load config:', err)
+    } finally {
+      setLoading(false)
+    }
+  }
+
+  const handleProviderChange = (id: string) => {
+    setProvider(id)
+    setShowCustom(false)
+    setCustomModel('')
+    if (config) {
+      const meta = config.providers?.[id] as ProviderMeta | undefined
+      const models = meta?.models || []
+      setModel(models[0] || '')
+    }
+  }
+
+  const handleModelChange = (val: string) => {
+    if (val === '__custom__') {
+      setShowCustom(true)
+      setModel('')
+    } else {
+      setShowCustom(false)
+      setModel(val)
+      setCustomModel('')
+    }
+  }
+
+  const saveModelConfig = async () => {
+    const finalModel = showCustom ? customModel.trim() : model
+    const isLinkai = provider === 'linkai'
+    try {
+      await apiClient.updateConfig({
+        model: finalModel,
+        use_linkai: isLinkai,
+        bot_type: isLinkai ? '' : provider,
+      })
+      setModelStatus(t('config_saved'))
+      const fresh = await apiClient.getConfig()
+      setConfig(fresh)
+    } catch {
+      setModelStatus(t('config_save_error'))
+    }
+    setTimeout(() => setModelStatus(''), 2000)
+  }
+
+  const saveAgentConfig = async () => {
+    try {
+      await apiClient.updateConfig({
+        agent_max_context_tokens: maxTokens,
+        agent_max_context_turns: maxTurns,
+        agent_max_steps: maxSteps,
+        enable_thinking: thinking,
+        self_evolution_enabled: evolution,
+      })
+      setAgentStatus(t('config_saved'))
+    } catch {
+      setAgentStatus(t('config_save_error'))
+    }
+    setTimeout(() => setAgentStatus(''), 2000)
+  }
+
+  // Desktop returns the real password, so the field holds plaintext and can be
+  // saved (including cleared) directly. Browser access only has the masked
+  // value, where a masked string must never be saved as the real password.
+  const hasRealPassword = config?.web_password !== undefined
+
+  const savePassword = async () => {
+    if (!pwDirty) return
+    if (!hasRealPassword && MASK_RE.test(password)) return
+    try {
+      await apiClient.updateConfig({ web_password: password })
+      setPwStatus(password ? t('config_password_saved') : t('config_password_cleared'))
+      setPwDirty(false)
+    } catch {
+      setPwStatus(t('config_save_error'))
+    }
+    setTimeout(() => setPwStatus(''), 3000)
+  }
+
+  const changeLanguage = async (lang: Lang) => {
+    setLang(lang)
+    onLangChange?.()
+    try {
+      await apiClient.updateConfig({ cow_lang: lang })
+    } catch {
+      /* non-blocking */
+    }
+  }
+
+  if (loading) {
+    return (
+      <div className="flex items-center justify-center py-20 text-content-tertiary">
+        <Loader2 size={18} className="animate-spin mr-2" />
+        {t('skills_loading')}
+      </div>
+    )
+  }
+
+  // A provider counts as configured when its key field holds a value.
+  // Custom providers (no key field) carry their own credential, so treat as configured.
+  const isConfigured = (id: string): boolean => {
+    const meta = providerMeta(id)
+    const f = meta?.api_key_field
+    if (!f) return true
+    return !!config?.api_keys?.[f]
+  }
+
+  // Only list configured providers (built-in or custom). Unconfigured vendors
+  // have no usable credentials, so showing them — flagged "unconfigured" — is
+  // just noise. Keep the current selection so a saved value never disappears.
+  const providerIds = config?.providers ? Object.keys(config.providers) : []
+  const providerOptions = providerIds
+    .filter((id) => isConfigured(id) || id === provider)
+    .map((id) => ({
+      value: id,
+      label: localizedLabel(providerMeta(id)?.label) || id,
+    }))
+  const currentMeta = providerMeta(provider)
+  const currentUnconfigured = !!provider && !isConfigured(provider)
+  const modelOptions = [
+    ...(currentMeta?.models || []).map((m) => ({ value: m, label: m })),
+    { value: '__custom__', label: t('config_custom_option') },
+  ]
+
+  return (
+    <div className="grid gap-5">
+      {/* Model — provider/model selection only; credentials live in Models tab */}
+      <Card icon={<Cpu size={16} />} title={t('config_model')}>
+        <div className="space-y-4">
+          <Field label={t('config_provider')}>
+            <Dropdown value={provider} options={providerOptions} onChange={handleProviderChange} />
+          </Field>
+          <Field label={t('config_model_name')}>
+            <Dropdown value={showCustom ? '__custom__' : model} options={modelOptions} onChange={handleModelChange} />
+            {showCustom && (
+              <TextInput
+                className="mt-2 font-mono"
+                value={customModel}
+                onChange={(e) => setCustomModel(e.target.value)}
+                placeholder={t('config_custom_model_hint')}
+              />
+            )}
+          </Field>
+
+          {/* Guide users to the Models tab for API key / base config.
+              When the selected provider has no credentials, surface a warning. */}
+          {onOpenModels && (
+            <button
+              onClick={onOpenModels}
+              className={`w-full flex items-center justify-between gap-2 rounded-btn border px-3 py-2.5 cursor-pointer transition-colors text-left ${
+                currentUnconfigured
+                  ? 'border-danger-border bg-danger-soft hover:border-danger'
+                  : 'border-default bg-inset hover:border-accent'
+              }`}
+            >
+              <span className={`text-xs ${currentUnconfigured ? 'text-danger' : 'text-content-tertiary'}`}>
+                {currentUnconfigured ? t('config_provider_unconfigured_hint') : t('config_credentials_link')}
+              </span>
+              <span
+                className={`flex-shrink-0 inline-flex items-center gap-1 text-xs ${
+                  currentUnconfigured ? 'text-danger font-medium' : 'text-accent'
+                }`}
+              >
+                {t('config_goto_models')}
+                <ArrowRight size={13} />
+              </span>
+            </button>
+          )}
+
+          <SaveRow status={modelStatus} onSave={saveModelConfig} />
+        </div>
+      </Card>
+
+      {/* Agent */}
+      <Card icon={<Bot size={16} />} title={t('config_agent')}>
+        <div className="space-y-4">
+          <Field label={t('config_max_tokens')} hint={t('config_max_tokens_hint')}>
+            <TextInput
+              type="number"
+              className="font-mono"
+              value={maxTokens}
+              onChange={(e) => setMaxTokens(parseInt(e.target.value) || 0)}
+            />
+          </Field>
+          <Field label={t('config_max_turns')} hint={t('config_max_turns_hint')}>
+            <TextInput
+              type="number"
+              className="font-mono"
+              value={maxTurns}
+              onChange={(e) => setMaxTurns(parseInt(e.target.value) || 0)}
+            />
+          </Field>
+          <Field label={t('config_max_steps')} hint={t('config_max_steps_hint')}>
+            <TextInput
+              type="number"
+              className="font-mono"
+              value={maxSteps}
+              onChange={(e) => setMaxSteps(parseInt(e.target.value) || 0)}
+            />
+          </Field>
+          <div className="flex items-center justify-between py-1">
+            <div>
+              <div className="text-sm font-medium text-content">{t('config_thinking')}</div>
+              <div className="text-xs text-content-tertiary mt-0.5">{t('config_thinking_hint')}</div>
+            </div>
+            <Toggle checked={thinking} onChange={setThinking} />
+          </div>
+          <div className="flex items-center justify-between py-1">
+            <div>
+              <div className="text-sm font-medium text-content">{t('config_evolution')}</div>
+              <div className="text-xs text-content-tertiary mt-0.5">{t('config_evolution_hint')}</div>
+            </div>
+            <Toggle checked={evolution} onChange={setEvolution} />
+          </div>
+          <SaveRow status={agentStatus} onSave={saveAgentConfig} />
+        </div>
+      </Card>
+
+      {/* Security */}
+      <Card icon={<ShieldCheck size={16} />} title={t('config_security')}>
+        <div className="space-y-4">
+          <Field label={t('config_password')} hint={t('config_password_hint')}>
+            <div className="relative">
+              <TextInput
+                type={pwVisible ? 'text' : 'password'}
+                className="pr-10"
+                value={password}
+                placeholder={t('config_password_placeholder')}
+                onFocus={() => {
+                  // Browser access shows a mask; clear it on focus so the user
+                  // types a fresh password. Desktop holds the real password and
+                  // must stay editable in place (cursor at the end).
+                  if (!hasRealPassword && !pwDirty && MASK_RE.test(password)) setPassword('')
+                }}
+                onBlur={() => {
+                  if (!hasRealPassword && !pwDirty) setPassword(config?.web_password_masked || '')
+                }}
+                onChange={(e) => {
+                  setPassword(e.target.value)
+                  setPwDirty(true)
+                }}
+              />
+              <button
+                type="button"
+                onClick={() => setPwVisible((v) => !v)}
+                className="absolute right-2.5 top-1/2 -translate-y-1/2 text-content-tertiary hover:text-content-secondary cursor-pointer p-1"
+              >
+                {pwVisible ? <EyeOff size={14} /> : <Eye size={14} />}
+              </button>
+            </div>
+          </Field>
+          <SaveRow status={pwStatus} onSave={savePassword} />
+        </div>
+      </Card>
+
+      {/* Language */}
+      <Card icon={<Languages size={16} />} title={t('config_language')}>
+        <Field label={t('config_language')} hint={t('config_language_hint')}>
+          <Dropdown
+            value={getLang()}
+            options={[
+              { value: 'zh', label: '简体中文' },
+              { value: 'en', label: 'English' },
+            ]}
+            onChange={(v) => changeLanguage(v as Lang)}
+          />
+        </Field>
+      </Card>
+    </div>
+  )
+}
+
+export default BasicSettings
diff --git a/desktop/src/renderer/src/pages/settings/CapabilityCard.tsx b/desktop/src/renderer/src/pages/settings/CapabilityCard.tsx
new file mode 100644
index 0000000..d5486e8
--- /dev/null
+++ b/desktop/src/renderer/src/pages/settings/CapabilityCard.tsx
@@ -0,0 +1,161 @@
+import React, { useMemo, useState } from 'react'
+import type { LucideIcon } from 'lucide-react'
+import { Loader2 } from 'lucide-react'
+import { t } from '../../i18n'
+import type { CapabilityState, ModelsData } from '../../types'
+import { Card, Field, Dropdown, TextInput, type DropdownOption } from './primitives'
+import { resolveModels, providerLabel, CUSTOM_OPTION } from './modelsHelpers'
+
+// Generic provider+model capability card used by chat/vision/asr/embedding/image.
+// tts (voice) and search have bespoke cards.
+
+export interface CapabilityCardProps {
+  icon: LucideIcon
+  title: string
+  subtitle?: string
+  capKey: string
+  state: CapabilityState
+  data: ModelsData | null
+  // whether picking "no provider" (auto / disabled) is allowed
+  allowAuto?: boolean
+  autoLabel?: string
+  // whether to allow a free-form custom model entry
+  allowCustomModel?: boolean
+  busy?: boolean
+  status?: string
+  onSave: (providerId: string, model: string) => void
+  children?: React.ReactNode
+}
+
+const CapabilityCard: React.FC<CapabilityCardProps> = ({
+  icon: Icon,
+  title,
+  subtitle,
+  state,
+  data,
+  allowAuto,
+  autoLabel,
+  allowCustomModel,
+  busy,
+  status,
+  onSave,
+  children,
+}) => {
+  const [provider, setProvider] = useState(state.current_provider || '')
+  const [model, setModel] = useState(state.current_model || '')
+  const [customModel, setCustomModel] = useState('')
+  const [showCustom, setShowCustom] = useState(false)
+
+  // A provider is configured when it has credentials (a custom provider counts
+  // only once it actually carries a name/key, not as an empty placeholder).
+  const isConfigured = (id: string): boolean => {
+    const p = data?.providers?.find((x) => x.id === id)
+    if (!p) return true
+    return p.configured || (p.is_custom && !!p.custom_name)
+  }
+
+  // Only surface providers that are actually configured (built-in or custom).
+  // An unconfigured vendor has no usable credentials, so listing it — and
+  // flagging it "unconfigured" — only adds noise. The currently-selected
+  // provider is always kept so a saved value never silently disappears.
+  const providerOptions: DropdownOption[] = useMemo(() => {
+    const opts = (state.providers || [])
+      .filter((id) => isConfigured(id) || id === provider)
+      .map((id) => ({ value: id, label: providerLabel(data, id) }))
+    if (allowAuto) return [{ value: '', label: autoLabel || t('models_auto') }, ...opts]
+    return opts
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [state.providers, data, allowAuto, autoLabel, provider])
+
+  const currentUnconfigured = !!provider && !isConfigured(provider)
+
+  const modelOptions: DropdownOption[] = useMemo(() => {
+    const list = resolveModels(data, provider, state.provider_models).map((o) => ({
+      value: o.value,
+      label: o.value,
+      hint: o.hint,
+    }))
+    // Keep the currently-saved model selectable even if it's not in the preset list.
+    if (model && !showCustom && !list.some((o) => o.value === model)) {
+      list.unshift({ value: model, label: model, hint: undefined })
+    }
+    if (allowCustomModel) list.push({ value: CUSTOM_OPTION, label: t('config_custom_option'), hint: undefined })
+    return list
+  }, [data, state.provider_models, provider, allowCustomModel, model, showCustom])
+
+  const handleProvider = (id: string) => {
+    setProvider(id)
+    setShowCustom(false)
+    setCustomModel('')
+    const first = resolveModels(data, id, state.provider_models)[0]
+    setModel(first?.value || '')
+  }
+
+  const handleModel = (val: string) => {
+    if (val === CUSTOM_OPTION) {
+      setShowCustom(true)
+      setModel('')
+    } else {
+      setShowCustom(false)
+      setModel(val)
+      setCustomModel('')
+    }
+  }
+
+  const finalModel = showCustom ? customModel.trim() : model
+  const isAuto = allowAuto && !provider
+
+  return (
+    <Card icon={<Icon size={16} />} title={title} subtitle={subtitle}>
+      <div className="space-y-4">
+        <Field label={t('models_provider')}>
+          <Dropdown
+            value={provider}
+            options={providerOptions}
+            placeholder={t('models_select_provider')}
+            onChange={handleProvider}
+          />
+          {/* The provider's API key is configured in the vendor cards above on
+              this same tab, so warn instead of linking elsewhere. */}
+          {currentUnconfigured && (
+            <p className="text-xs text-danger mt-1.5">{t('config_provider_unconfigured_hint')}</p>
+          )}
+        </Field>
+        {!isAuto && (
+          <Field label={t('models_model')}>
+            <Dropdown
+              value={showCustom ? CUSTOM_OPTION : model}
+              options={modelOptions}
+              placeholder={t('models_select_model')}
+              onChange={handleModel}
+            />
+            {showCustom && (
+              <TextInput
+                className="mt-2 font-mono"
+                value={customModel}
+                onChange={(e) => setCustomModel(e.target.value)}
+                placeholder={t('config_custom_model_hint')}
+              />
+            )}
+          </Field>
+        )}
+        {children}
+        <div className="flex items-center justify-end gap-3 pt-1">
+          <span className={`text-xs text-accent transition-opacity ${status ? 'opacity-100' : 'opacity-0'}`}>
+            {status}
+          </span>
+          <button
+            disabled={busy}
+            onClick={() => onSave(provider, finalModel)}
+            className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 inline-flex items-center gap-2"
+          >
+            {busy && <Loader2 size={14} className="animate-spin" />}
+            {t('config_save')}
+          </button>
+        </div>
+      </div>
+    </Card>
+  )
+}
+
+export default CapabilityCard
diff --git a/desktop/src/renderer/src/pages/settings/ModelsTab.tsx b/desktop/src/renderer/src/pages/settings/ModelsTab.tsx
new file mode 100644
index 0000000..7ad8ac9
--- /dev/null
+++ b/desktop/src/renderer/src/pages/settings/ModelsTab.tsx
@@ -0,0 +1,836 @@
+import React, { useCallback, useEffect, useMemo, useState } from 'react'
+import {
+  MessageSquare,
+  Eye,
+  Image as ImageIcon,
+  Mic,
+  Volume2,
+  Database,
+  Search as SearchIcon,
+  Plus,
+  Check,
+  Loader2,
+  Pencil,
+  Eye as EyeIcon,
+  EyeOff,
+} from 'lucide-react'
+import { t, localizedLabel } from '../../i18n'
+import apiClient from '../../api/client'
+import type { CapabilityState, ModelsData, ModelProvider, SearchCapabilityState } from '../../types'
+import { Card, Field, Dropdown, TextInput, Modal, Btn, MASK_RE } from './primitives'
+import CapabilityCard from './CapabilityCard'
+import { normEntries, providerLabel, resolveVoices, CUSTOM_OPTION } from './modelsHelpers'
+
+interface ModelsTabProps {
+  baseUrl: string
+}
+
+const REPLY_MODES: { value: 'off' | 'voice_if_voice' | 'always'; key: string }[] = [
+  { value: 'off', key: 'models_tts_mode_off' },
+  { value: 'voice_if_voice', key: 'models_tts_mode_if_voice' },
+  { value: 'always', key: 'models_tts_mode_always' },
+]
+
+const ModelsTab: React.FC<ModelsTabProps> = ({ baseUrl }) => {
+  const [data, setData] = useState<ModelsData | null>(null)
+  const [loading, setLoading] = useState(true)
+  const [busy, setBusy] = useState<string>('') // capability key currently saving
+  const [statusMap, setStatusMap] = useState<Record<string, string>>({})
+
+  const load = useCallback(async () => {
+    try {
+      const fresh = await apiClient.getModels()
+      setData(fresh)
+    } catch (e) {
+      console.error('Failed to load models:', e)
+    } finally {
+      setLoading(false)
+    }
+  }, [])
+
+  useEffect(() => {
+    apiClient.setBaseUrl(baseUrl)
+    load()
+  }, [baseUrl, load])
+
+  const flash = (key: string, msg: string) => {
+    setStatusMap((m) => ({ ...m, [key]: msg }))
+    setTimeout(() => setStatusMap((m) => ({ ...m, [key]: '' })), 2000)
+  }
+
+  // Run a models action, then refresh and flash a status for the given key.
+  const run = async (key: string, action: Parameters<typeof apiClient.modelsAction>[0]) => {
+    setBusy(key)
+    try {
+      const res = await apiClient.modelsAction(action)
+      if (res.status === 'success') {
+        await load()
+        flash(key, t('config_saved'))
+      } else {
+        flash(key, (res.message as string) || t('config_save_error'))
+      }
+    } catch {
+      flash(key, t('config_save_error'))
+    } finally {
+      setBusy('')
+    }
+  }
+
+  if (loading) {
+    return (
+      <div className="flex items-center justify-center py-20 text-content-tertiary">
+        <Loader2 size={18} className="animate-spin mr-2" />
+        {t('skills_loading')}
+      </div>
+    )
+  }
+  if (!data) {
+    return <div className="text-center py-20 text-content-tertiary">{t('config_save_error')}</div>
+  }
+
+  const caps = data.capabilities
+
+  return (
+    <div className="grid gap-5">
+      <VendorSection data={data} onChanged={load} statusMap={statusMap} flash={flash} />
+
+      {/* Chat */}
+      <CapabilityCard
+        icon={MessageSquare}
+        title={t('models_cap_chat')}
+        subtitle={t('models_cap_chat_sub')}
+        capKey="chat"
+        state={caps.chat}
+        data={data}
+        allowCustomModel
+        busy={busy === 'chat'}
+        status={statusMap.chat}
+        onSave={(p, m) => run('chat', { action: 'set_capability', capability: 'chat', provider_id: p, model: m })}
+      />
+
+      {/* Vision */}
+      <CapabilityCard
+        icon={Eye}
+        title={t('models_cap_vision')}
+        subtitle={t('models_cap_vision_sub')}
+        capKey="vision"
+        state={caps.vision}
+        data={data}
+        allowAuto
+        autoLabel={t('models_auto')}
+        busy={busy === 'vision'}
+        status={statusMap.vision}
+        onSave={(p, m) => run('vision', { action: 'set_capability', capability: 'vision', provider_id: p, model: m })}
+      >
+        <FallbackHint state={caps.vision} data={data} />
+      </CapabilityCard>
+
+      {/* Image */}
+      <CapabilityCard
+        icon={ImageIcon}
+        title={t('models_cap_image')}
+        subtitle={t('models_cap_image_sub')}
+        capKey="image"
+        state={caps.image}
+        data={data}
+        allowAuto
+        autoLabel={t('models_auto')}
+        busy={busy === 'image'}
+        status={statusMap.image}
+        onSave={(p, m) => run('image', { action: 'set_capability', capability: 'image', provider_id: p, model: m })}
+      >
+        <FallbackHint state={caps.image} data={data} />
+      </CapabilityCard>
+
+      {/* ASR */}
+      <CapabilityCard
+        icon={Mic}
+        title={t('models_cap_asr')}
+        subtitle={t('models_cap_asr_sub')}
+        capKey="asr"
+        state={caps.asr}
+        data={data}
+        allowAuto
+        autoLabel={t('models_asr_auto')}
+        busy={busy === 'asr'}
+        status={statusMap.asr}
+        onSave={(p, m) => run('asr', { action: 'set_capability', capability: 'asr', provider_id: p, model: m })}
+      />
+
+      {/* TTS — bespoke (voice + reply mode) */}
+      <TtsCard
+        state={caps.tts}
+        data={data}
+        busy={busy === 'tts'}
+        status={statusMap.tts}
+        onSaveVoice={(p, m, v) =>
+          run('tts', { action: 'set_capability', capability: 'tts', provider_id: p, model: m, voice: v })
+        }
+        onSaveMode={(mode) => run('tts_mode', { action: 'set_voice_reply_mode', mode })}
+        modeStatus={statusMap.tts_mode}
+        modeBusy={busy === 'tts_mode'}
+      />
+
+      {/* Embedding */}
+      <EmbeddingCard
+        state={caps.embedding}
+        data={data}
+        busy={busy === 'embedding'}
+        status={statusMap.embedding}
+        onSave={(p, m) => run('embedding', { action: 'set_capability', capability: 'embedding', provider_id: p, model: m })}
+      />
+
+      {/* Search — bespoke */}
+      <SearchCard
+        state={caps.search}
+        busy={busy === 'search'}
+        status={statusMap.search}
+        onSaveStrategy={(strategy, provider) =>
+          run('search', { action: 'set_capability', capability: 'search', strategy, provider })
+        }
+        onSaveBochaKey={(key) => run('search_key', { action: 'set_search_credential', api_key: key })}
+        keyStatus={statusMap.search_key}
+        keyBusy={busy === 'search_key'}
+      />
+    </div>
+  )
+}
+
+// ============================================================
+// Layer 1 — vendor credentials
+// ============================================================
+
+interface VendorSectionProps {
+  data: ModelsData
+  onChanged: () => Promise<void>
+  statusMap: Record<string, string>
+  flash: (key: string, msg: string) => void
+}
+
+const VendorSection: React.FC<VendorSectionProps> = ({ data, onChanged }) => {
+  // Edit an existing built-in vendor.
+  const [editing, setEditing] = useState<ModelProvider | null>(null)
+  // Add flow: open the vendor modal with a provider picker.
+  const [adding, setAdding] = useState(false)
+  // Custom provider modal: 'new' to create, or a provider to edit.
+  const [customEditing, setCustomEditing] = useState<ModelProvider | 'new' | null>(null)
+
+  const isCustomCard = (p: ModelProvider) => p.is_custom && !!p.custom_name
+  // Unified grid: configured built-ins + all custom provider cards (web parity).
+  const shown = data.providers.filter((p) => p.configured || isCustomCard(p))
+
+  return (
+    <Card icon={<Database size={16} />} title={t('models_vendors')} subtitle={t('models_vendors_sub')}>
+      {shown.length === 0 ? (
+        <div className="flex flex-col items-center justify-center py-8 rounded-btn border border-dashed border-default">
+          <p className="text-sm text-content-tertiary">{t('models_no_vendor')}</p>
+          <button
+            onClick={() => setAdding(true)}
+            className="mt-3 inline-flex items-center gap-1 px-3 py-1.5 rounded-btn text-xs font-medium bg-accent-soft text-accent hover:bg-accent-soft/70 cursor-pointer transition-colors"
+          >
+            <Plus size={12} /> {t('models_add_vendor')}
+          </button>
+        </div>
+      ) : (
+        <div className="grid grid-cols-1 sm:grid-cols-2 gap-2.5">
+          {shown.map((p) =>
+            isCustomCard(p) ? (
+              <VendorChip key={p.id} provider={p} onClick={() => setCustomEditing(p)} />
+            ) : (
+              <VendorChip key={p.id} provider={p} onClick={() => setEditing(p)} />
+            )
+          )}
+          <button
+            onClick={() => setAdding(true)}
+            className="flex items-center justify-center gap-1.5 px-3 py-2.5 rounded-btn border border-dashed border-default text-content-tertiary hover:border-accent hover:text-accent cursor-pointer transition-colors text-sm"
+          >
+            <Plus size={14} /> {t('models_add_vendor')}
+          </button>
+        </div>
+      )}
+
+      <VendorModal
+        provider={editing}
+        addMode={adding}
+        data={data}
+        onClose={() => {
+          setEditing(null)
+          setAdding(false)
+        }}
+        onPickCustom={() => {
+          setAdding(false)
+          setCustomEditing('new')
+        }}
+        onSaved={onChanged}
+      />
+      <CustomProviderModal target={customEditing} onClose={() => setCustomEditing(null)} onSaved={onChanged} />
+    </Card>
+  )
+}
+
+const VendorChip: React.FC<{ provider: ModelProvider; onClick: () => void }> = ({ provider, onClick }) => (
+  <button
+    onClick={onClick}
+    className="group flex items-center gap-2.5 px-3 py-2.5 rounded-btn border border-default bg-inset hover:border-accent cursor-pointer transition-colors text-left"
+  >
+    <span className="flex-shrink-0 w-7 h-7 rounded-lg bg-surface-2 text-content-secondary flex items-center justify-center text-xs font-bold">
+      {(localizedLabel(provider.label) || provider.id || '?').slice(0, 1).toUpperCase()}
+    </span>
+    <span className="flex-1 min-w-0 text-sm font-medium text-content truncate">{localizedLabel(provider.label)}</span>
+    <Pencil size={12} className="flex-shrink-0 text-content-tertiary group-hover:text-accent transition-colors" />
+  </button>
+)
+
+const CUSTOM_PICK = '__custom_new__'
+
+const VendorModal: React.FC<{
+  provider: ModelProvider | null
+  addMode: boolean
+  data: ModelsData
+  onClose: () => void
+  onPickCustom: () => void
+  onSaved: () => Promise<void>
+}> = ({ provider, addMode, data, onClose, onPickCustom, onSaved }) => {
+  const open = !!provider || addMode
+
+  // In add-mode the user first picks a built-in provider; that selection
+  // becomes the effective provider whose key/base fields we edit. Exclude ALL
+  // custom providers (named or empty placeholder): custom vendors are added via
+  // the single "custom vendor" option below, so an empty custom placeholder must
+  // not show up here as a second, duplicate custom entry.
+  const builtins = useMemo(() => data.providers.filter((p) => !p.is_custom), [data.providers])
+  const firstUnconfigured = builtins.find((p) => !p.configured) || builtins[0]
+  const [pickId, setPickId] = useState('')
+
+  const effective: ModelProvider | undefined = provider || builtins.find((p) => p.id === pickId)
+
+  const [apiKey, setApiKey] = useState('')
+  const [keyDirty, setKeyDirty] = useState(false)
+  const [keyVisible, setKeyVisible] = useState(false)
+  const [apiBase, setApiBase] = useState('')
+  const [saving, setSaving] = useState(false)
+
+  // Load fields whenever the effective provider changes.
+  useEffect(() => {
+    if (!open) return
+    const init = provider || (addMode ? firstUnconfigured : undefined)
+    setPickId(provider ? provider.id : firstUnconfigured?.id || '')
+    setApiKey(init?.api_key_masked || '')
+    setApiBase(init?.api_base || '')
+    setKeyDirty(false)
+    setKeyVisible(false)
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [provider, addMode, open])
+
+  if (!open) return null
+
+  const pickOptions = [
+    ...builtins.map((p) => ({
+      value: p.id,
+      label: localizedLabel(p.label),
+      hint: p.configured ? t('models_configured') : undefined,
+    })),
+    { value: CUSTOM_PICK, label: t('models_custom_vendor'), hint: t('models_add_custom_hint') },
+  ]
+
+  const onPick = (val: string) => {
+    if (val === CUSTOM_PICK) {
+      onPickCustom()
+      return
+    }
+    setPickId(val)
+    const p = builtins.find((x) => x.id === val)
+    setApiKey(p?.api_key_masked || '')
+    setApiBase(p?.api_base || '')
+    setKeyDirty(false)
+  }
+
+  const hasBase = !!effective?.api_base_field
+
+  const save = async () => {
+    if (!effective) return
+    setSaving(true)
+    try {
+      const payload: { action: 'set_provider'; provider_id: string; api_key?: string; api_base?: string } = {
+        action: 'set_provider',
+        provider_id: effective.id,
+      }
+      if (keyDirty && apiKey && !MASK_RE.test(apiKey)) payload.api_key = apiKey
+      if (hasBase) payload.api_base = apiBase
+      await apiClient.modelsAction(payload)
+      await onSaved()
+      onClose()
+    } finally {
+      setSaving(false)
+    }
+  }
+
+  const clear = async () => {
+    if (!effective || !confirm(t('models_clear_confirm'))) return
+    setSaving(true)
+    try {
+      await apiClient.modelsAction({ action: 'delete_provider', provider_id: effective.id })
+      await onSaved()
+      onClose()
+    } finally {
+      setSaving(false)
+    }
+  }
+
+  return (
+    <Modal
+      open={open}
+      title={addMode ? t('models_add_vendor') : localizedLabel(effective?.label)}
+      onClose={onClose}
+      footer={
+        <>
+          {!addMode && effective?.configured && (
+            <Btn variant="danger" onClick={clear} disabled={saving}>
+              {t('models_clear')}
+            </Btn>
+          )}
+          <Btn variant="ghost" onClick={onClose}>
+            {t('config_cancel')}
+          </Btn>
+          <Btn variant="primary" onClick={save} disabled={saving || !effective}>
+            {saving ? <Loader2 size={14} className="animate-spin" /> : t('config_save')}
+          </Btn>
+        </>
+      }
+    >
+      {addMode && (
+        <Field label={t('models_provider')}>
+          <Dropdown value={pickId} options={pickOptions} onChange={onPick} />
+        </Field>
+      )}
+      <Field label="API Key">
+        <div className="relative">
+          <TextInput
+            type={keyVisible ? 'text' : 'password'}
+            className="pr-10 font-mono"
+            value={apiKey}
+            placeholder="sk-..."
+            onFocus={() => {
+              if (!keyDirty && MASK_RE.test(apiKey)) setApiKey('')
+            }}
+            onBlur={() => {
+              if (!keyDirty) setApiKey(effective?.api_key_masked || '')
+            }}
+            onChange={(e) => {
+              setApiKey(e.target.value)
+              setKeyDirty(true)
+            }}
+          />
+          <button
+            type="button"
+            onClick={() => setKeyVisible((v) => !v)}
+            className="absolute right-2.5 top-1/2 -translate-y-1/2 text-content-tertiary hover:text-content-secondary cursor-pointer p-1"
+          >
+            {keyVisible ? <EyeOff size={14} /> : <EyeIcon size={14} />}
+          </button>
+        </div>
+      </Field>
+      {hasBase && (
+        <Field label="API Base">
+          <TextInput
+            className="font-mono"
+            value={apiBase}
+            onChange={(e) => setApiBase(e.target.value)}
+            placeholder={effective?.api_base_placeholder || 'https://...'}
+          />
+        </Field>
+      )}
+    </Modal>
+  )
+}
+
+const CustomProviderModal: React.FC<{
+  target: ModelProvider | 'new' | null
+  onClose: () => void
+  onSaved: () => Promise<void>
+}> = ({ target, onClose, onSaved }) => {
+  const editing = target && target !== 'new' ? target : null
+  const [name, setName] = useState('')
+  const [apiBase, setApiBase] = useState('')
+  const [apiKey, setApiKey] = useState('')
+  const [keyDirty, setKeyDirty] = useState(false)
+  const [saving, setSaving] = useState(false)
+
+  useEffect(() => {
+    if (!target) return
+    if (editing) {
+      setName(editing.custom_name || localizedLabel(editing.label))
+      setApiBase(editing.api_base || '')
+      setApiKey(editing.api_key_masked || '')
+    } else {
+      setName('')
+      setApiBase('')
+      setApiKey('')
+    }
+    setKeyDirty(false)
+  }, [target, editing])
+
+  if (!target) return null
+
+  const save = async () => {
+    if (!name.trim()) return
+    setSaving(true)
+    try {
+      const payload: {
+        action: 'set_custom_provider'
+        name: string
+        id?: string
+        api_base: string
+        api_key?: string
+      } = {
+        action: 'set_custom_provider',
+        name: name.trim(),
+        api_base: apiBase.trim(),
+      }
+      if (editing) payload.id = editing.custom_id
+      if (keyDirty && apiKey && !MASK_RE.test(apiKey)) payload.api_key = apiKey
+      await apiClient.modelsAction(payload)
+      await onSaved()
+      onClose()
+    } finally {
+      setSaving(false)
+    }
+  }
+
+  const remove = async () => {
+    if (!editing || !confirm(t('models_delete_confirm'))) return
+    setSaving(true)
+    try {
+      await apiClient.modelsAction({ action: 'delete_custom_provider', id: editing.custom_id || '' })
+      await onSaved()
+      onClose()
+    } finally {
+      setSaving(false)
+    }
+  }
+
+  return (
+    <Modal
+      open={!!target}
+      title={editing ? t('models_edit_custom') : t('models_add_custom')}
+      onClose={onClose}
+      footer={
+        <>
+          {editing && (
+            <Btn variant="danger" onClick={remove} disabled={saving}>
+              {t('models_delete')}
+            </Btn>
+          )}
+          <Btn variant="ghost" onClick={onClose}>
+            {t('config_cancel')}
+          </Btn>
+          <Btn variant="primary" onClick={save} disabled={saving || !name.trim() || (!editing && !apiBase.trim())}>
+            {saving ? <Loader2 size={14} className="animate-spin" /> : t('config_save')}
+          </Btn>
+        </>
+      }
+    >
+      <Field label={t('models_custom_name')}>
+        <TextInput value={name} onChange={(e) => setName(e.target.value)} placeholder="My Provider" />
+      </Field>
+      <Field label="API Base" hint={t('models_custom_base_hint')}>
+        <TextInput
+          className="font-mono"
+          value={apiBase}
+          onChange={(e) => setApiBase(e.target.value)}
+          placeholder="https://...../v1"
+        />
+      </Field>
+      <Field label="API Key">
+        <TextInput
+          type="text"
+          className="font-mono"
+          value={apiKey}
+          placeholder="sk-..."
+          onFocus={() => {
+            if (!keyDirty && MASK_RE.test(apiKey)) setApiKey('')
+          }}
+          onChange={(e) => {
+            setApiKey(e.target.value)
+            setKeyDirty(true)
+          }}
+        />
+      </Field>
+    </Modal>
+  )
+}
+
+// ============================================================
+// Bespoke capability cards
+// ============================================================
+
+const FallbackHint: React.FC<{ state: CapabilityState; data: ModelsData }> = ({ state, data }) => {
+  if (!state.fallback_provider && !state.fallback_model) return null
+  const label = providerLabel(data, state.fallback_provider || '')
+  return (
+    <p className="text-xs text-content-tertiary">
+      {t('models_fallback')}: {label} {state.fallback_model ? `· ${state.fallback_model}` : ''}
+    </p>
+  )
+}
+
+const TtsCard: React.FC<{
+  state: CapabilityState
+  data: ModelsData
+  busy: boolean
+  status?: string
+  onSaveVoice: (provider: string, model: string, voice: string) => void
+  onSaveMode: (mode: 'off' | 'voice_if_voice' | 'always') => void
+  modeStatus?: string
+  modeBusy: boolean
+}> = ({ state, data, busy, status, onSaveVoice, onSaveMode, modeStatus, modeBusy }) => {
+  const [provider, setProvider] = useState(state.current_provider || '')
+  const [model, setModel] = useState(state.current_model || '')
+  const [voice, setVoice] = useState(state.current_voice || '')
+  const [mode, setMode] = useState<'off' | 'voice_if_voice' | 'always'>(state.reply_mode || 'off')
+
+  const providerOptions = (state.providers || []).map((id) => ({ value: id, label: providerLabel(data, id) }))
+  const modelOptions = normEntries(state.provider_models?.[provider]).map((o) => ({
+    value: o.value,
+    label: o.value,
+    hint: o.hint,
+  }))
+  const voiceOptions = resolveVoices(provider, model, state.provider_voices).map((o) => ({
+    value: o.value,
+    label: o.value,
+    hint: o.hint,
+  }))
+
+  const handleProvider = (id: string) => {
+    setProvider(id)
+    const first = normEntries(state.provider_models?.[id])[0]
+    const fm = first?.value || ''
+    setModel(fm)
+    setVoice(resolveVoices(id, fm, state.provider_voices)[0]?.value || '')
+  }
+  const handleModel = (m: string) => {
+    setModel(m)
+    setVoice(resolveVoices(provider, m, state.provider_voices)[0]?.value || '')
+  }
+
+  return (
+    <Card icon={<Volume2 size={16} />} title={t('models_cap_tts')} subtitle={t('models_cap_tts_sub')}>
+      <div className="space-y-4">
+        {/* Reply mode — saved immediately */}
+        <Field label={t('models_tts_reply_mode')} hint={t('models_tts_reply_mode_hint')}>
+          <Dropdown
+            value={mode}
+            options={REPLY_MODES.map((m) => ({ value: m.value, label: t(m.key) }))}
+            onChange={(v) => {
+              const next = v as 'off' | 'voice_if_voice' | 'always'
+              setMode(next)
+              onSaveMode(next)
+            }}
+            disabled={modeBusy}
+          />
+          {modeStatus && <span className="text-xs text-accent">{modeStatus}</span>}
+        </Field>
+
+        {mode !== 'off' && (
+          <>
+            <Field label={t('models_provider')}>
+              <Dropdown
+                value={provider}
+                options={providerOptions}
+                placeholder={t('models_select_provider')}
+                onChange={handleProvider}
+              />
+            </Field>
+            <Field label={t('models_model')}>
+              <Dropdown
+                value={model}
+                options={modelOptions}
+                placeholder={t('models_select_model')}
+                onChange={handleModel}
+              />
+            </Field>
+            {voiceOptions.length > 0 && (
+              <Field label={t('models_voice')}>
+                <Dropdown value={voice} options={voiceOptions} placeholder={t('models_select_voice')} onChange={setVoice} />
+              </Field>
+            )}
+            <div className="flex items-center justify-end gap-3 pt-1">
+              <span className={`text-xs text-accent transition-opacity ${status ? 'opacity-100' : 'opacity-0'}`}>
+                {status}
+              </span>
+              <button
+                disabled={busy}
+                onClick={() => onSaveVoice(provider, model, voice)}
+                className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 inline-flex items-center gap-2"
+              >
+                {busy && <Loader2 size={14} className="animate-spin" />}
+                {t('config_save')}
+              </button>
+            </div>
+          </>
+        )}
+      </div>
+    </Card>
+  )
+}
+
+const EmbeddingCard: React.FC<{
+  state: CapabilityState
+  data: ModelsData
+  busy: boolean
+  status?: string
+  onSave: (provider: string, model: string) => void
+}> = ({ state, data, busy, status, onSave }) => (
+  <CapabilityCard
+    icon={Database}
+    title={t('models_cap_embedding')}
+    subtitle={t('models_cap_embedding_sub')}
+    capKey="embedding"
+    state={state}
+    data={data}
+    allowAuto
+    autoLabel={t('models_disabled')}
+    busy={busy}
+    status={status}
+    onSave={onSave}
+  >
+    {state.current_dim != null && (
+      <p className="text-xs text-content-tertiary">
+        {t('models_embedding_dim')}: {state.current_dim} · {t('models_embedding_rebuild_hint')}
+      </p>
+    )}
+  </CapabilityCard>
+)
+
+const SearchCard: React.FC<{
+  state: SearchCapabilityState
+  busy: boolean
+  status?: string
+  onSaveStrategy: (strategy: string, provider: string) => void
+  onSaveBochaKey: (key: string) => void
+  keyStatus?: string
+  keyBusy: boolean
+}> = ({ state, busy, status, onSaveStrategy, onSaveBochaKey, keyStatus, keyBusy }) => {
+  const [strategy, setStrategy] = useState<string>(state.strategy || 'auto')
+  const [provider, setProvider] = useState<string>(state.fixed_provider || state.current_provider || '')
+  const [bochaOpen, setBochaOpen] = useState(false)
+
+  const providerOptions = useMemo(
+    () => state.providers.map((p) => ({ value: p.id, label: localizedLabel(p.label) })),
+    [state.providers]
+  )
+  const bocha = state.providers.find((p) => p.id === 'bocha')
+
+  return (
+    <Card icon={<SearchIcon size={16} />} title={t('models_cap_search')} subtitle={t('models_cap_search_sub')}>
+      <div className="space-y-4">
+        <Field label={t('models_search_strategy')}>
+          <Dropdown
+            value={strategy}
+            options={[
+              { value: 'auto', label: t('models_search_auto') },
+              { value: 'fixed', label: t('models_search_fixed') },
+            ]}
+            onChange={setStrategy}
+          />
+        </Field>
+        {strategy === 'fixed' && (
+          <Field label={t('models_search_provider')}>
+            <Dropdown
+              value={provider}
+              options={providerOptions}
+              placeholder={t('models_select_provider')}
+              onChange={setProvider}
+            />
+          </Field>
+        )}
+        <div className="flex items-center justify-between">
+          <button
+            onClick={() => setBochaOpen(true)}
+            className="text-xs text-accent hover:text-accent-hover cursor-pointer inline-flex items-center gap-1"
+          >
+            {t('models_search_bocha_key')}
+            {bocha?.configured && <Check size={12} />}
+          </button>
+          <div className="flex items-center gap-3">
+            <span className={`text-xs text-accent transition-opacity ${status ? 'opacity-100' : 'opacity-0'}`}>
+              {status}
+            </span>
+            <button
+              disabled={busy || (strategy === 'fixed' && !provider)}
+              onClick={() => onSaveStrategy(strategy, provider)}
+              className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 inline-flex items-center gap-2"
+            >
+              {busy && <Loader2 size={14} className="animate-spin" />}
+              {t('config_save')}
+            </button>
+          </div>
+        </div>
+      </div>
+
+      <BochaKeyModal
+        open={bochaOpen}
+        masked={bocha?.api_key_masked || ''}
+        busy={keyBusy}
+        status={keyStatus}
+        onClose={() => setBochaOpen(false)}
+        onSave={(k) => {
+          onSaveBochaKey(k)
+          setBochaOpen(false)
+        }}
+      />
+    </Card>
+  )
+}
+
+const BochaKeyModal: React.FC<{
+  open: boolean
+  masked: string
+  busy: boolean
+  status?: string
+  onClose: () => void
+  onSave: (key: string) => void
+}> = ({ open, masked, busy, onClose, onSave }) => {
+  const [key, setKey] = useState('')
+  const [dirty, setDirty] = useState(false)
+  useEffect(() => {
+    if (open) {
+      setKey(masked)
+      setDirty(false)
+    }
+  }, [open, masked])
+  return (
+    <Modal
+      open={open}
+      title={t('models_search_bocha_key')}
+      onClose={onClose}
+      footer={
+        <>
+          <Btn variant="ghost" onClick={onClose}>
+            {t('config_cancel')}
+          </Btn>
+          <Btn variant="primary" disabled={busy} onClick={() => onSave(dirty && !MASK_RE.test(key) ? key : '')}>
+            {busy ? <Loader2 size={14} className="animate-spin" /> : t('config_save')}
+          </Btn>
+        </>
+      }
+    >
+      <Field label="Bocha API Key" hint={t('models_search_bocha_hint')}>
+        <TextInput
+          className="font-mono"
+          value={key}
+          placeholder="sk-..."
+          onFocus={() => {
+            if (!dirty && MASK_RE.test(key)) setKey('')
+          }}
+          onChange={(e) => {
+            setKey(e.target.value)
+            setDirty(true)
+          }}
+        />
+      </Field>
+    </Modal>
+  )
+}
+
+export default ModelsTab
diff --git a/desktop/src/renderer/src/pages/settings/modelsHelpers.ts b/desktop/src/renderer/src/pages/settings/modelsHelpers.ts
new file mode 100644
index 0000000..24ac31c
--- /dev/null
+++ b/desktop/src/renderer/src/pages/settings/modelsHelpers.ts
@@ -0,0 +1,57 @@
+import type { ModelEntry, ModelOption, ModelProvider, ModelsData } from '../../types'
+import { localizedLabel } from '../../i18n'
+
+// Normalize a string|{value,hint} entry into a uniform option shape.
+export function normEntry(e: ModelEntry): ModelOption {
+  return typeof e === 'string' ? { value: e } : e
+}
+
+export function normEntries(arr?: ModelEntry[]): ModelOption[] {
+  return (arr || []).map(normEntry)
+}
+
+// Resolve a human label for a provider id, falling back to the id itself.
+// Handles expanded custom ids ("custom:<id>") via the providers overview.
+export function providerLabel(data: ModelsData | null, id: string): string {
+  if (!id) return ''
+  const p = data?.providers?.find((x) => x.id === id)
+  if (p) return localizedLabel(p.label) || id
+  return id
+}
+
+export function findProvider(data: ModelsData | null, id: string): ModelProvider | undefined {
+  return data?.providers?.find((x) => x.id === id)
+}
+
+// Resolve the model list for a capability+provider, mirroring the web console:
+//   1. capability-scoped provider_models[id] (vision/image/asr/tts/embedding)
+//   2. provider_models['custom'] for expanded custom:<id> providers
+//   3. fall back to the vendor's generic models[] (chat has no provider_models)
+export function resolveModels(
+  data: ModelsData | null,
+  providerId: string,
+  providerModels?: Record<string, ModelEntry[]>
+): ModelOption[] {
+  if (!providerId) return []
+  if (providerModels?.[providerId]) return normEntries(providerModels[providerId])
+  if (providerId.startsWith('custom:') && providerModels?.['custom']) {
+    return normEntries(providerModels['custom'])
+  }
+  return normEntries(findProvider(data, providerId)?.models)
+}
+
+// Voices for a tts provider may be a flat list or, for linkai, keyed by model.
+export function resolveVoices(
+  provider: string,
+  model: string,
+  voicesMap?: Record<string, ModelEntry[] | Record<string, ModelEntry[]>>
+): ModelOption[] {
+  const raw = voicesMap?.[provider]
+  if (!raw) return []
+  if (Array.isArray(raw)) return normEntries(raw)
+  // keyed by model (linkai)
+  const byModel = raw as Record<string, ModelEntry[]>
+  return normEntries(byModel[model] || [])
+}
+
+export const CUSTOM_OPTION = '__custom__'
diff --git a/desktop/src/renderer/src/pages/settings/primitives.tsx b/desktop/src/renderer/src/pages/settings/primitives.tsx
new file mode 100644
index 0000000..95247ed
--- /dev/null
+++ b/desktop/src/renderer/src/pages/settings/primitives.tsx
@@ -0,0 +1,233 @@
+import React, { useState, useEffect, useRef, useLayoutEffect } from 'react'
+import { createPortal } from 'react-dom'
+import { ChevronDown } from 'lucide-react'
+import { t } from '../../i18n'
+
+// Shared presentational building blocks for the settings tabs.
+
+export const Card: React.FC<{ icon: React.ReactNode; title: string; subtitle?: string; children: React.ReactNode }> = ({
+  icon,
+  title,
+  subtitle,
+  children,
+}) => (
+  <div className="rounded-card border border-default bg-surface p-5">
+    <div className="flex items-center gap-2.5 mb-4">
+      <div className="w-8 h-8 rounded-lg bg-accent-soft text-accent flex items-center justify-center">{icon}</div>
+      <div>
+        <h3 className="font-semibold text-content leading-tight">{title}</h3>
+        {subtitle && <p className="text-xs text-content-tertiary mt-0.5">{subtitle}</p>}
+      </div>
+    </div>
+    {children}
+  </div>
+)
+
+export const Field: React.FC<{ label: string; hint?: string; children: React.ReactNode }> = ({
+  label,
+  hint,
+  children,
+}) => (
+  <div>
+    <label className="block text-sm font-medium text-content-secondary mb-1.5">{label}</label>
+    {children}
+    {hint && <p className="text-xs text-content-tertiary mt-1">{hint}</p>}
+  </div>
+)
+
+export interface DropdownOption {
+  value: string
+  label: string
+  hint?: string
+}
+
+export const Dropdown: React.FC<{
+  value: string
+  display?: string
+  placeholder?: string
+  options: DropdownOption[]
+  disabled?: boolean
+  onChange: (val: string) => void
+}> = ({ value, display, placeholder, options, disabled, onChange }) => {
+  const [open, setOpen] = useState(false)
+  const ref = useRef<HTMLDivElement>(null)
+  const menuRef = useRef<HTMLDivElement>(null)
+  // The menu is rendered in a portal with fixed positioning so it's never
+  // clipped by an ancestor's `overflow` (e.g. a modal's scroll container).
+  const [rect, setRect] = useState<{ left: number; top: number; width: number } | null>(null)
+
+  const place = () => {
+    const el = ref.current
+    if (!el) return
+    const r = el.getBoundingClientRect()
+    setRect({ left: r.left, top: r.bottom + 4, width: r.width })
+  }
+
+  useLayoutEffect(() => {
+    if (open) place()
+  }, [open])
+
+  useEffect(() => {
+    if (!open) return
+    const onDown = (e: MouseEvent) => {
+      const target = e.target as Node
+      if (ref.current?.contains(target) || menuRef.current?.contains(target)) return
+      setOpen(false)
+    }
+    // Keep the fixed menu anchored to the trigger on scroll/resize by
+    // re-measuring — NOT closing. Closing on scroll makes the dropdown vanish
+    // the moment the user scrolls the settings page.
+    document.addEventListener('mousedown', onDown)
+    window.addEventListener('resize', place, true)
+    window.addEventListener('scroll', place, true)
+    return () => {
+      document.removeEventListener('mousedown', onDown)
+      window.removeEventListener('resize', place, true)
+      window.removeEventListener('scroll', place, true)
+    }
+  }, [open])
+
+  const current = display ?? options.find((o) => o.value === value)?.label ?? ''
+  return (
+    <div ref={ref} className="relative">
+      <button
+        type="button"
+        disabled={disabled}
+        onClick={() => !disabled && setOpen((v) => !v)}
+        className={`w-full flex items-center justify-between px-3 py-2 rounded-btn border bg-inset text-sm transition-colors ${
+          disabled
+            ? 'border-default text-content-tertiary cursor-not-allowed opacity-70'
+            : 'border-strong text-content cursor-pointer hover:border-accent'
+        }`}
+      >
+        <span className={`truncate ${current ? '' : 'text-content-tertiary'}`}>{current || placeholder || '--'}</span>
+        <ChevronDown size={15} className={`text-content-tertiary transition-transform ${open ? 'rotate-180' : ''}`} />
+      </button>
+      {open &&
+        rect &&
+        createPortal(
+          <div
+            ref={menuRef}
+            style={{ position: 'fixed', left: rect.left, top: rect.top, width: rect.width }}
+            className="z-[100] max-h-64 overflow-y-auto rounded-btn border border-default bg-elevated shadow-lg py-1"
+          >
+            {options.length === 0 && (
+              <div className="px-3 py-2 text-sm text-content-tertiary">{t('models_no_options')}</div>
+            )}
+            {options.map((o) => (
+              <div
+                key={o.value}
+                onClick={() => {
+                  onChange(o.value)
+                  setOpen(false)
+                }}
+                className={`px-3 py-2 text-sm cursor-pointer transition-colors ${
+                  o.value === value ? 'bg-accent-soft text-accent' : 'text-content-secondary hover:bg-surface-2'
+                }`}
+              >
+                <div className="truncate">{o.label}</div>
+                {o.hint && <div className="text-xs text-content-tertiary mt-0.5 truncate">{o.hint}</div>}
+              </div>
+            ))}
+          </div>,
+          document.body
+        )}
+    </div>
+  )
+}
+
+export const Toggle: React.FC<{ checked: boolean; onChange: (v: boolean) => void }> = ({ checked, onChange }) => (
+  <button
+    type="button"
+    role="switch"
+    aria-checked={checked}
+    onClick={() => onChange(!checked)}
+    className={`relative inline-flex h-5 w-9 flex-shrink-0 items-center rounded-full transition-colors cursor-pointer ${
+      checked ? 'bg-accent' : 'bg-surface-2 border border-strong'
+    }`}
+  >
+    <span
+      className={`inline-block h-3.5 w-3.5 rounded-full bg-white shadow transition-transform ${
+        checked ? 'translate-x-[18px]' : 'translate-x-[3px]'
+      }`}
+    />
+  </button>
+)
+
+export const TextInput: React.FC<React.InputHTMLAttributes<HTMLInputElement>> = (props) => (
+  <input
+    {...props}
+    className={`w-full px-3 py-2 rounded-btn border border-strong bg-inset text-sm text-content placeholder:text-content-tertiary focus:outline-none focus:border-accent transition-colors ${
+      props.className || ''
+    }`}
+  />
+)
+
+export const SaveRow: React.FC<{ status: string; onSave: () => void; label?: string }> = ({
+  status,
+  onSave,
+  label,
+}) => (
+  <div className="flex items-center justify-end gap-3 pt-1">
+    <span className={`text-xs text-accent transition-opacity ${status ? 'opacity-100' : 'opacity-0'}`}>{status}</span>
+    <button
+      onClick={onSave}
+      className="px-4 py-2 rounded-btn bg-accent text-accent-contrast hover:bg-accent-hover text-sm font-medium cursor-pointer transition-colors"
+    >
+      {label ?? t('config_save')}
+    </button>
+  </div>
+)
+
+export const MASK_RE = /[*•]/
+
+export const Modal: React.FC<{
+  open: boolean
+  title: string
+  onClose: () => void
+  children: React.ReactNode
+  footer?: React.ReactNode
+}> = ({ open, title, onClose, children, footer }) => {
+  if (!open) return null
+  return (
+    <div
+      className="fixed inset-0 z-50 flex items-center justify-center bg-black/40 p-4"
+      onMouseDown={(e) => {
+        if (e.target === e.currentTarget) onClose()
+      }}
+    >
+      <div className="w-full max-w-md rounded-card border border-default bg-elevated shadow-xl">
+        <div className="flex items-center justify-between px-5 py-4 border-b border-default">
+          <h3 className="font-semibold text-content">{title}</h3>
+          <button
+            onClick={onClose}
+            className="text-content-tertiary hover:text-content cursor-pointer text-lg leading-none px-1"
+          >
+            ×
+          </button>
+        </div>
+        <div className="px-5 py-4 space-y-4 max-h-[60vh] overflow-y-auto">{children}</div>
+        {footer && <div className="flex items-center justify-end gap-2 px-5 py-3.5 border-t border-default">{footer}</div>}
+      </div>
+    </div>
+  )
+}
+
+export const Btn: React.FC<
+  React.ButtonHTMLAttributes<HTMLButtonElement> & { variant?: 'primary' | 'ghost' | 'danger' }
+> = ({ variant = 'ghost', className, children, ...props }) => {
+  const styles =
+    variant === 'primary'
+      ? 'bg-accent text-accent-contrast hover:bg-accent-hover'
+      : variant === 'danger'
+        ? 'bg-danger-soft text-danger hover:bg-danger/15 border border-danger-border'
+        : 'border border-strong text-content-secondary hover:bg-surface-2'
+  return (
+    <button
+      {...props}
+      className={`px-4 py-2 rounded-btn text-sm font-medium cursor-pointer transition-colors disabled:opacity-50 disabled:cursor-not-allowed ${styles} ${className || ''}`}
+    >
+      {children}
+    </button>
+  )
+}
diff --git a/desktop/src/renderer/src/store/chatStore.ts b/desktop/src/renderer/src/store/chatStore.ts
new file mode 100644
index 0000000..c904c6e
--- /dev/null
+++ b/desktop/src/renderer/src/store/chatStore.ts
@@ -0,0 +1,488 @@
+import { create } from 'zustand'
+import apiClient from '../api/client'
+import type { ChatMessage, MessageStep, Attachment, StreamEvent, HistoryMessage } from '../types'
+
+/**
+ * Per-session chat state. Supports parallel sessions: each session keeps its
+ * own message list and active stream, so switching sessions never interrupts a
+ * background run. The active EventSource lives in `streams` (outside React).
+ */
+
+interface SessionRuntime {
+  messages: ChatMessage[]
+  isStreaming: boolean
+  requestId: string | null
+  // history pagination
+  historyPage: number
+  historyHasMore: boolean
+  historyLoaded: boolean
+}
+
+interface ChatState {
+  sessions: Record<string, SessionRuntime>
+
+  getSession: (sid: string) => SessionRuntime
+  ensureSession: (sid: string) => void
+
+  send: (sid: string, text: string, attachments: Attachment[]) => Promise<void>
+  cancel: (sid: string) => Promise<void>
+  regenerate: (sid: string, botMessageId: string) => Promise<void>
+  editUserMessage: (sid: string, messageId: string) => { text: string; attachments: Attachment[] } | null
+  deleteMessage: (sid: string, userSeq: number, cascade: boolean) => Promise<void>
+
+  loadHistory: (sid: string, page?: number) => Promise<void>
+  clearLocal: (sid: string) => void
+}
+
+// EventSource instances kept outside the store (not serializable).
+const streams: Record<string, EventSource> = {}
+
+const EMPTY: SessionRuntime = {
+  messages: [],
+  isStreaming: false,
+  requestId: null,
+  historyPage: 0,
+  historyHasMore: false,
+  historyLoaded: false,
+}
+
+function uid(prefix: string): string {
+  return `${prefix}_${Date.now().toString(36)}${Math.random().toString(36).slice(2, 6)}`
+}
+
+/**
+ * History keeps the English cancel marker for the LLM; strip it for display so
+ * the bubble shows a clean answer + a dedicated "cancelled" badge instead.
+ */
+function stripCancelMarker(text: string): string {
+  if (!text) return text
+  return text
+    .replace(/_\(Cancelled by user\)_/g, '')
+    .replace(/_\(Cancelled\)_/g, '')
+    .trim()
+}
+
+/**
+ * Rebuild attachments from `send`-tool results persisted in the message steps.
+ * SSE `file_to_send` events aren't stored, so on history reload the only record
+ * of a sent image/file is the tool result JSON. Mirrors the web console's
+ * `_renderSentFileFromToolResult` so media survives an app restart.
+ */
+function attachmentsFromSteps(steps: MessageStep[]): Attachment[] {
+  const out: Attachment[] = []
+  for (const s of steps) {
+    if (s.type !== 'tool' || !s.result) continue
+    let payload: Record<string, unknown>
+    try {
+      payload = typeof s.result === 'string' ? JSON.parse(s.result) : (s.result as unknown as Record<string, unknown>)
+    } catch {
+      continue
+    }
+    if (!payload || payload.type !== 'file_to_send') continue
+    const rawPath = (payload.path as string) || ''
+    const url = (payload.url as string) || ''
+    if (!rawPath && !url) continue
+    const isRemote = url.toLowerCase().startsWith('http://') || url.toLowerCase().startsWith('https://')
+    // Local files are served via /api/file; remote URLs are used directly.
+    const previewUrl = isRemote
+      ? url
+      : rawPath.toLowerCase().startsWith('http')
+        ? rawPath
+        : apiClient.getServeFileUrl(rawPath)
+    const kind = (payload.file_type as string) || 'file'
+    const fileType: Attachment['file_type'] =
+      kind === 'image' ? 'image' : kind === 'video' ? 'video' : 'file'
+    out.push({
+      file_path: previewUrl,
+      file_name: (payload.file_name as string) || 'file',
+      file_type: fileType,
+      preview_url: previewUrl,
+      abs_path: isRemote ? undefined : rawPath,
+    })
+  }
+  return out
+}
+
+/** Convert a backend history message into a UI ChatMessage. */
+function historyToMessage(m: HistoryMessage): ChatMessage {
+  if (m.role === 'user') {
+    return {
+      id: uid('user'),
+      role: 'user',
+      content: m.content,
+      timestamp: m.created_at,
+      userSeq: m._seq,
+    }
+  }
+
+  // The backend stores the final answer both as `content` and as the LAST
+  // `content` step. Strip that trailing content step so it isn't rendered
+  // twice (matches the web console's renderStepsHtml logic).
+  const raw = m.steps || []
+  let lastContentIdx = -1
+  for (let i = raw.length - 1; i >= 0; i--) {
+    if (raw[i].type === 'content') {
+      lastContentIdx = i
+      break
+    }
+  }
+  const steps: MessageStep[] = raw
+    .filter((_, i) => i !== lastContentIdx)
+    .map((s) => ({ ...s }))
+  const finalContent = m.content || (lastContentIdx >= 0 ? raw[lastContentIdx].content || '' : '')
+  const attachments = attachmentsFromSteps(raw)
+
+  return {
+    id: uid('assistant'),
+    role: 'assistant',
+    content: finalContent,
+    timestamp: m.created_at,
+    steps,
+    reasoning: m.reasoning,
+    kind: m.kind,
+    extras: m.extras,
+    botSeq: m._seq,
+    attachments: attachments.length > 0 ? attachments : undefined,
+  }
+}
+
+export const useChatStore = create<ChatState>((set, get) => {
+  // --- helpers operating on a single session immutably ---
+  const patchSession = (sid: string, patch: Partial<SessionRuntime>) =>
+    set((st) => ({
+      sessions: { ...st.sessions, [sid]: { ...(st.sessions[sid] || EMPTY), ...patch } },
+    }))
+
+  const patchMessages = (sid: string, fn: (msgs: ChatMessage[]) => ChatMessage[]) =>
+    set((st) => {
+      const cur = st.sessions[sid] || EMPTY
+      return { sessions: { ...st.sessions, [sid]: { ...cur, messages: fn(cur.messages) } } }
+    })
+
+  const updateMsg = (sid: string, id: string, fn: (m: ChatMessage) => ChatMessage) =>
+    patchMessages(sid, (msgs) => msgs.map((m) => (m.id === id ? fn(m) : m)))
+
+  /** Attach an EventSource for a request and wire all SSE events to a bot message. */
+  const attachStream = (sid: string, requestId: string, botId: string) => {
+    const es = apiClient.createSSEStream(requestId)
+    streams[sid] = es
+    let tailTimer: ReturnType<typeof setTimeout> | null = null
+
+    const closeStream = () => {
+      if (tailTimer) {
+        clearTimeout(tailTimer)
+        tailTimer = null
+      }
+      es.close()
+      if (streams[sid] === es) delete streams[sid]
+    }
+
+    // Mark the turn as complete: UI becomes interactive again immediately.
+    const completeTurn = () => {
+      patchSession(sid, { isStreaming: false, requestId: null })
+      updateMsg(sid, botId, (m) => ({ ...m, isStreaming: false }))
+    }
+
+    const finishStream = () => {
+      completeTurn()
+      closeStream()
+    }
+
+    es.onmessage = (event) => {
+      let data: StreamEvent
+      try {
+        data = JSON.parse(event.data)
+      } catch {
+        return // keepalive
+      }
+
+      switch (data.type) {
+        case 'reasoning':
+          updateMsg(sid, botId, (m) => ({ ...m, reasoning: (m.reasoning || '') + (data.content || '') }))
+          break
+
+        case 'delta':
+          updateMsg(sid, botId, (m) => ({ ...m, content: m.content + (data.content || '') }))
+          break
+
+        case 'message_end':
+          // Freeze accumulated text as a content step when tool calls follow,
+          // mirroring the web console's interleaved step model.
+          if (data.has_tool_calls) {
+            updateMsg(sid, botId, (m) => {
+              if (!m.content.trim()) return m
+              const steps = [...(m.steps || []), { type: 'content' as const, content: m.content.trim() }]
+              return { ...m, steps, content: '' }
+            })
+          }
+          break
+
+        case 'tool_start':
+          updateMsg(sid, botId, (m) => {
+            // commit any reasoning into a thinking step
+            const steps = [...(m.steps || [])]
+            if (m.reasoning && m.reasoning.trim()) {
+              steps.push({ type: 'thinking', content: m.reasoning.trim() })
+            }
+            steps.push({
+              type: 'tool',
+              id: data.tool_call_id,
+              name: data.tool,
+              arguments: data.arguments,
+              status: 'running',
+            })
+            return { ...m, steps, reasoning: '', content: '' }
+          })
+          break
+
+        case 'tool_progress':
+          updateMsg(sid, botId, (m) => ({
+            ...m,
+            steps: (m.steps || []).map((s) =>
+              s.type === 'tool' && s.id === data.tool_call_id ? { ...s, result: data.content } : s
+            ),
+          }))
+          break
+
+        case 'tool_end':
+          updateMsg(sid, botId, (m) => ({
+            ...m,
+            steps: (m.steps || []).map((s) =>
+              s.type === 'tool' && s.id === data.tool_call_id
+                ? {
+                    ...s,
+                    status: data.status,
+                    result: data.result ?? s.result,
+                    execution_time: data.execution_time,
+                    is_error: data.status !== 'success',
+                  }
+                : s
+            ),
+          }))
+          break
+
+        case 'image':
+        case 'file': {
+          // Media pushed by the `send` tool (file_to_send). `content` is either
+          // a backend /api/file?path=... URL or a passed-through http(s) URL.
+          const url = data.content || ''
+          if (!url) break
+          // Prefer the concrete media kind from the backend (image/video/...);
+          // fall back to the coarse SSE event type.
+          const kind = data.file_type || (data.type === 'image' ? 'image' : 'file')
+          const attType: Attachment['file_type'] =
+            kind === 'image' ? 'image' : kind === 'video' ? 'video' : 'file'
+          const att: Attachment = {
+            file_path: url,
+            file_name: data.file_name || 'file',
+            file_type: attType,
+            preview_url: url,
+            abs_path: data.abs_path,
+          }
+          updateMsg(sid, botId, (m) => ({
+            ...m,
+            attachments: [...(m.attachments || []), att],
+          }))
+          break
+        }
+
+        case 'cancelled':
+          updateMsg(sid, botId, (m) => ({ ...m, isCancelled: true }))
+          break
+
+        case 'done':
+          updateMsg(sid, botId, (m) => {
+            const next = stripCancelMarker(data.content || m.content)
+            return {
+              ...m,
+              content: next,
+              botSeq: data.bot_seq ?? m.botSeq,
+              isStreaming: false,
+            }
+          })
+          // backfill the preceding user message's seq for edit/delete
+          if (data.user_seq != null) {
+            patchMessages(sid, (msgs) => {
+              const idx = msgs.findIndex((m) => m.id === botId)
+              for (let i = idx - 1; i >= 0; i--) {
+                if (msgs[i].role === 'user') {
+                  msgs[i] = { ...msgs[i], userSeq: data.user_seq }
+                  break
+                }
+              }
+              return [...msgs]
+            })
+          }
+          // The answer is final: free the UI now (don't wait for onerror).
+          completeTurn()
+          // Backend keeps the stream open for a short tail (e.g. TTS audio via
+          // voice_attach). Close it ourselves if nothing else arrives.
+          if (tailTimer) clearTimeout(tailTimer)
+          tailTimer = setTimeout(closeStream, 1500)
+          break
+
+        case 'voice_attach':
+          if (data.audio_url) {
+            updateMsg(sid, botId, (m) => ({
+              ...m,
+              extras: { ...(m.extras || {}), audio: data.audio_url },
+            }))
+          }
+          finishStream()
+          break
+
+        case 'error':
+          updateMsg(sid, botId, (m) => ({ ...m, error: data.message || 'stream error', isStreaming: false }))
+          finishStream()
+          break
+      }
+    }
+
+    es.onerror = () => {
+      // Stream closed (often the normal end after `done`/tail). Finalize.
+      finishStream()
+    }
+  }
+
+  return {
+    sessions: {},
+
+    getSession: (sid) => get().sessions[sid] || EMPTY,
+
+    ensureSession: (sid) => {
+      if (!get().sessions[sid]) patchSession(sid, { ...EMPTY })
+    },
+
+    send: async (sid, text, attachments) => {
+      const userMsg: ChatMessage = {
+        id: uid('user'),
+        role: 'user',
+        content: text,
+        timestamp: Date.now() / 1000,
+        attachments: attachments.length ? attachments : undefined,
+      }
+      const botId = uid('assistant')
+      const botMsg: ChatMessage = {
+        id: botId,
+        role: 'assistant',
+        content: '',
+        timestamp: Date.now() / 1000,
+        steps: [],
+        isStreaming: true,
+      }
+      patchMessages(sid, (msgs) => [...msgs, userMsg, botMsg])
+      patchSession(sid, { isStreaming: true })
+
+      try {
+        const res = await apiClient.sendMessage(sid, text, {
+          stream: true,
+          attachments: attachments.length ? attachments : undefined,
+        })
+        if (res.status === 'success' && res.stream && res.request_id) {
+          patchSession(sid, { requestId: res.request_id })
+          attachStream(sid, res.request_id, botId)
+        } else if (res.inline_reply) {
+          updateMsg(sid, botId, (m) => ({ ...m, content: res.inline_reply || '', isStreaming: false }))
+          patchSession(sid, { isStreaming: false })
+        } else {
+          updateMsg(sid, botId, (m) => ({ ...m, error: 'send failed', isStreaming: false }))
+          patchSession(sid, { isStreaming: false })
+        }
+      } catch (err) {
+        updateMsg(sid, botId, (m) => ({ ...m, error: `${err}`, isStreaming: false }))
+        patchSession(sid, { isStreaming: false })
+      }
+    },
+
+    cancel: async (sid) => {
+      const s = get().sessions[sid]
+      if (!s?.requestId) return
+      try {
+        await apiClient.cancel({ requestId: s.requestId, sessionId: sid })
+      } catch {
+        /* ignore */
+      }
+    },
+
+    regenerate: async (sid, botMessageId) => {
+      const s = get().sessions[sid] || EMPTY
+      const idx = s.messages.findIndex((m) => m.id === botMessageId)
+      if (idx < 0) return
+      // find the user message that produced this bot reply
+      let userMsg: ChatMessage | null = null
+      for (let i = idx - 1; i >= 0; i--) {
+        if (s.messages[i].role === 'user') {
+          userMsg = s.messages[i]
+          break
+        }
+      }
+      if (!userMsg) return
+      // delete the turn on the backend (by the user's seq) then resend
+      if (userMsg.userSeq != null) {
+        try {
+          await apiClient.deleteMessage({ sessionId: sid, userSeq: userMsg.userSeq, deleteUser: true, cascade: true })
+        } catch {
+          /* ignore */
+        }
+      }
+      // drop the user+bot messages locally from idx-? : remove from the user msg onward
+      const userIdx = s.messages.indexOf(userMsg)
+      patchMessages(sid, (msgs) => msgs.slice(0, userIdx))
+      await get().send(sid, userMsg.content, userMsg.attachments || [])
+    },
+
+    editUserMessage: (sid, messageId) => {
+      const s = get().sessions[sid] || EMPTY
+      const msg = s.messages.find((m) => m.id === messageId)
+      if (!msg || msg.role !== 'user') return null
+      const userIdx = s.messages.indexOf(msg)
+      // cascade-delete this turn on the backend
+      if (msg.userSeq != null) {
+        apiClient
+          .deleteMessage({ sessionId: sid, userSeq: msg.userSeq, deleteUser: true, cascade: true })
+          .catch(() => {})
+      }
+      patchMessages(sid, (msgs) => msgs.slice(0, userIdx))
+      return { text: msg.content, attachments: msg.attachments || [] }
+    },
+
+    deleteMessage: async (sid, userSeq, cascade) => {
+      try {
+        await apiClient.deleteMessage({ sessionId: sid, userSeq, deleteUser: true, cascade })
+      } catch {
+        /* ignore */
+      }
+      // reload history to reflect server state
+      await get().loadHistory(sid, 1)
+    },
+
+    loadHistory: async (sid, page = 1) => {
+      try {
+        const res = await apiClient.getHistory(sid, page, 20)
+        const uiMsgs = res.messages.map(historyToMessage)
+        patchSession(sid, {
+          historyPage: res.page,
+          historyHasMore: res.has_more,
+          historyLoaded: true,
+        })
+        if (page === 1) {
+          patchMessages(sid, () => uiMsgs)
+        } else {
+          // older page: prepend
+          patchMessages(sid, (msgs) => [...uiMsgs, ...msgs])
+        }
+      } catch {
+        patchSession(sid, { historyLoaded: true })
+      }
+    },
+
+    clearLocal: (sid) => {
+      const es = streams[sid]
+      if (es) {
+        es.close()
+        delete streams[sid]
+      }
+      patchSession(sid, { ...EMPTY })
+    },
+  }
+})
diff --git a/desktop/src/renderer/src/store/onboardingStore.ts b/desktop/src/renderer/src/store/onboardingStore.ts
new file mode 100644
index 0000000..3da27df
--- /dev/null
+++ b/desktop/src/renderer/src/store/onboardingStore.ts
@@ -0,0 +1,42 @@
+import { create } from 'zustand'
+
+// Onboarding is config-driven: the wizard auto-opens whenever the chat model
+// isn't configured yet, and stops appearing once it is — no persisted "seen"
+// flag that could strand a user who skipped without finishing setup.
+//
+// `dismissedThisSession` is an in-memory guard so that skipping doesn't
+// immediately re-open the wizard within the same run; it resets on relaunch,
+// so an unconfigured app will guide the user again next time.
+
+interface OnboardingState {
+  // Whether the wizard overlay is currently visible.
+  open: boolean
+  // True if the user skipped/finished during THIS app session (not persisted).
+  dismissedThisSession: boolean
+  // Decide whether to auto-open on launch. Opens only when chat isn't
+  // configured AND it wasn't dismissed earlier this session.
+  maybeOpen: (chatConfigured: boolean) => void
+  // Open manually (e.g. from a "setup guide" entry point later).
+  openWizard: () => void
+  // Finish/skip: close and don't auto-reopen this session.
+  finish: () => void
+  // Close without marking dismissed (rarely used; kept for symmetry).
+  close: () => void
+}
+
+export const useOnboardingStore = create<OnboardingState>((set) => ({
+  open: false,
+  dismissedThisSession: false,
+
+  maybeOpen: (chatConfigured) =>
+    set((s) => {
+      if (chatConfigured || s.dismissedThisSession) return { open: false }
+      return { open: true }
+    }),
+
+  openWizard: () => set({ open: true }),
+
+  finish: () => set({ open: false, dismissedThisSession: true }),
+
+  close: () => set({ open: false }),
+}))
diff --git a/desktop/src/renderer/src/store/sessionStore.ts b/desktop/src/renderer/src/store/sessionStore.ts
new file mode 100644
index 0000000..ebbd837
--- /dev/null
+++ b/desktop/src/renderer/src/store/sessionStore.ts
@@ -0,0 +1,86 @@
+import { create } from 'zustand'
+import apiClient from '../api/client'
+import type { SessionItem } from '../types'
+
+const ACTIVE_KEY = 'cow_session_id'
+
+interface SessionState {
+  sessions: SessionItem[]
+  total: number
+  page: number
+  hasMore: boolean
+  loading: boolean
+  activeId: string
+
+  loadSessions: (page?: number) => Promise<void>
+  loadMore: () => Promise<void>
+  setActive: (id: string) => void
+  newSession: () => string
+  rename: (id: string, title: string) => Promise<void>
+  remove: (id: string) => Promise<void>
+}
+
+function genId(): string {
+  return `session_${Date.now().toString(36)}${Math.random().toString(36).slice(2, 6)}`
+}
+
+function readActive(): string {
+  return localStorage.getItem(ACTIVE_KEY) || genId()
+}
+
+export const useSessionStore = create<SessionState>((set, get) => ({
+  sessions: [],
+  total: 0,
+  page: 1,
+  hasMore: false,
+  loading: false,
+  activeId: readActive(),
+
+  loadSessions: async (page = 1) => {
+    set({ loading: true })
+    try {
+      const res = await apiClient.getSessions(page, 50)
+      set((s) => ({
+        sessions: page === 1 ? res.sessions : [...s.sessions, ...res.sessions],
+        total: res.total,
+        page: res.page,
+        hasMore: res.has_more,
+        loading: false,
+      }))
+    } catch {
+      set({ loading: false })
+    }
+  },
+
+  loadMore: async () => {
+    const { hasMore, loading, page } = get()
+    if (!hasMore || loading) return
+    await get().loadSessions(page + 1)
+  },
+
+  setActive: (id) => {
+    localStorage.setItem(ACTIVE_KEY, id)
+    set({ activeId: id })
+  },
+
+  newSession: () => {
+    const id = genId()
+    localStorage.setItem(ACTIVE_KEY, id)
+    set({ activeId: id })
+    return id
+  },
+
+  rename: async (id, title) => {
+    await apiClient.renameSession(id, title)
+    set((s) => ({
+      sessions: s.sessions.map((sess) => (sess.session_id === id ? { ...sess, title } : sess)),
+    }))
+  },
+
+  remove: async (id) => {
+    await apiClient.deleteSession(id)
+    set((s) => ({ sessions: s.sessions.filter((sess) => sess.session_id !== id) }))
+    // If we removed the active one, start a fresh session
+    if (get().activeId === id) get().newSession()
+  },
+}))
diff --git a/desktop/src/renderer/src/store/uiStore.ts b/desktop/src/renderer/src/store/uiStore.ts
new file mode 100644
index 0000000..8360e20
--- /dev/null
+++ b/desktop/src/renderer/src/store/uiStore.ts
@@ -0,0 +1,48 @@
+import { create } from 'zustand'
+
+const NAV_KEY = 'cow_nav_collapsed'
+const SESSIONS_KEY = 'cow_sessions_collapsed'
+
+interface UIState {
+  /** Navigation rail collapsed (icon-only) vs expanded (icon + label). */
+  navCollapsed: boolean
+  toggleNav: () => void
+  setNavCollapsed: (v: boolean) => void
+
+  /** Session list panel collapsed (hidden) vs expanded. */
+  sessionsCollapsed: boolean
+  toggleSessions: () => void
+
+  /** Currently active session id (Chat page). */
+  activeSessionId: string | null
+  setActiveSessionId: (id: string | null) => void
+}
+
+function readBool(key: string): boolean {
+  return localStorage.getItem(key) === '1'
+}
+
+export const useUIStore = create<UIState>((set) => ({
+  navCollapsed: readBool(NAV_KEY),
+  toggleNav: () =>
+    set((s) => {
+      const next = !s.navCollapsed
+      localStorage.setItem(NAV_KEY, next ? '1' : '0')
+      return { navCollapsed: next }
+    }),
+  setNavCollapsed: (v) => {
+    localStorage.setItem(NAV_KEY, v ? '1' : '0')
+    set({ navCollapsed: v })
+  },
+
+  sessionsCollapsed: readBool(SESSIONS_KEY),
+  toggleSessions: () =>
+    set((s) => {
+      const next = !s.sessionsCollapsed
+      localStorage.setItem(SESSIONS_KEY, next ? '1' : '0')
+      return { sessionsCollapsed: next }
+    }),
+
+  activeSessionId: null,
+  setActiveSessionId: (id) => set({ activeSessionId: id }),
+}))
diff --git a/desktop/src/renderer/src/store/updateStore.ts b/desktop/src/renderer/src/store/updateStore.ts
new file mode 100644
index 0000000..6dde6fa
--- /dev/null
+++ b/desktop/src/renderer/src/store/updateStore.ts
@@ -0,0 +1,123 @@
+import { create } from 'zustand'
+import type { UpdateStatus } from '../types'
+import { getLang } from '../i18n'
+
+interface UpdateState {
+  status: UpdateStatus | null
+  /** Latest available version, kept across download progress updates. */
+  version: string | null
+  /** Download progress 0-100 while state === 'downloading'. */
+  percent: number
+  /** User clicked "download" but no progress event has arrived yet. Gives the
+   *  button an instant busy state so it can't be clicked again during the 1-2s
+   *  lead-up to the first progress event. Cleared on the first 'downloading'. */
+  preparing: boolean
+  /** The download progress already reached ~100% once. macOS (Squirrel.Mac)
+   *  emits a SECOND progress pass (verify / block-map) after the first, which
+   *  used to make the bar visibly restart from 0. Once peaked we render an
+   *  indeterminate "verifying" state instead of a confusing second bar. */
+  progressPeaked: boolean
+  /** User clicked "restart to install"; show a full-screen "installing…"
+   *  overlay for the brief window before the app quits to swap the bundle. */
+  installing: boolean
+  /** User dismissed the badge for this version (don't nag again until next). */
+  dismissedVersion: string | null
+  /** Whether the update panel is currently shown. Lifted here so the "check
+   *  for update" menu item can re-open it on demand. */
+  panelOpen: boolean
+
+  setStatus: (s: UpdateStatus) => void
+  /** Dismiss the floating badge/panel for the current version (footer dot goes
+   *  away), but keep the update itself known so the menu can still surface it. */
+  dismiss: () => void
+  openPanel: () => void
+  closePanel: () => void
+  /** User explicitly clicked "check for update": ask main to re-check, and if
+   *  an update is already known, re-open the panel immediately (undismiss). */
+  recheck: () => void
+
+  // Actions proxied to the main process via the preload bridge.
+  download: () => void
+  install: () => void
+}
+
+export const useUpdateStore = create<UpdateState>((set, get) => ({
+  status: null,
+  version: null,
+  percent: 0,
+  preparing: false,
+  progressPeaked: false,
+  installing: false,
+  dismissedVersion: null,
+  panelOpen: false,
+
+  setStatus: (s) =>
+    set((st) => {
+      // A newly detected version auto-opens the panel.
+      if (s.state === 'available')
+        return { status: s, version: s.version, percent: 0, preparing: false, progressPeaked: false, panelOpen: true }
+      if (s.state === 'downloading') {
+        // First real progress event clears the "preparing" busy state. Track
+        // when we've hit ~100% so the Squirrel.Mac second pass renders as an
+        // indeterminate "verifying" state instead of a bar restarting from 0.
+        const peaked = st.progressPeaked || s.percent >= 99
+        return { status: s, percent: s.percent, preparing: false, progressPeaked: peaked }
+      }
+      if (s.state === 'downloaded')
+        return { status: s, version: s.version, percent: 100, preparing: false }
+      if (s.state === 'error') return { status: s, preparing: false, installing: false }
+      return { status: s }
+    }),
+
+  dismiss: () => set((st) => ({ dismissedVersion: st.version, panelOpen: false })),
+  openPanel: () => set({ panelOpen: true }),
+  closePanel: () => set({ panelOpen: false }),
+
+  recheck: () => {
+    // Clear any dismiss so a known update surfaces again. Only re-open the panel
+    // when an update actually exists — if we're already up to date, opening the
+    // panel would just flash it (the banner renders nothing for not-available)
+    // and the "up to date" feedback belongs in the menu, not a panel. The menu
+    // (NavRail) decides whether to close itself + show the panel based on this.
+    const known = hasAvailableUpdate(get())
+    set({ dismissedVersion: null, panelOpen: known })
+    // Always kick a fresh check too (picks up newer versions / recovers errors).
+    // Pass the UI language so downloads route to the China CDN / R2 accordingly.
+    window.electronAPI?.checkForUpdate?.(getLang())
+  },
+
+  download: () => {
+    // Enter a busy state immediately so the button can't be clicked twice while
+    // we wait (1-2s) for the first download-progress event to arrive.
+    set({ preparing: true, progressPeaked: false })
+    window.electronAPI?.downloadUpdate?.(getLang())
+  },
+  install: () => {
+    // Show the "installing…" overlay before the app quits to swap the bundle.
+    set({ installing: true })
+    window.electronAPI?.installUpdate?.()
+  },
+}))
+
+// Subscribe to main-process update events. Returns an unsubscribe fn.
+export function initUpdateListener(): (() => void) | undefined {
+  return window.electronAPI?.onUpdateStatus?.((status) => {
+    useUpdateStore.getState().setStatus(status as UpdateStatus)
+  })
+}
+
+// Whether an update exists at all (available/downloading/downloaded),
+// regardless of dismiss. Drives the "check for update" menu item's dot, which
+// should persist as long as an update is actually available.
+export function hasAvailableUpdate(state: UpdateState): boolean {
+  const s = state.status
+  if (!s) return false
+  return s.state === 'available' || s.state === 'downloading' || s.state === 'downloaded'
+}
+
+// Whether a new version should be surfaced in the floating footer badge:
+// available and not dismissed for that version. Dismissing hides only this,
+// not the menu dot (hasAvailableUpdate).
+export function hasPendingUpdate(state: UpdateState): boolean {
+  return hasAvailableUpdate(state) && state.dismissedVersion !== state.version
+}
diff --git a/desktop/src/renderer/src/types.ts b/desktop/src/renderer/src/types.ts
new file mode 100644
index 0000000..1fa7592
--- /dev/null
+++ b/desktop/src/renderer/src/types.ts
@@ -0,0 +1,503 @@
+// ============================================================
+// Electron bridge
+// ============================================================
+
+export interface ElectronAPI {
+  getBackendPort: () => Promise<number | null>
+  getBackendStatus: () => Promise<string>
+  restartBackend: () => Promise<boolean>
+  selectDirectory: () => Promise<string | null>
+  selectFile: (filters?: { name: string; extensions: string[] }[]) => Promise<string | null>
+  /** Open a local file with the OS default app. Resolves to '' on success. */
+  openPath: (targetPath: string) => Promise<string>
+  // Listener registrars return an unsubscribe fn for cleanup.
+  onBackendStatus: (callback: (data: BackendStatusEvent) => void) => () => void
+  onBackendLog: (callback: (line: string) => void) => () => void
+  windowMinimize: () => Promise<void>
+  windowMaximize: () => Promise<boolean>
+  windowClose: () => Promise<void>
+  windowIsMaximized: () => Promise<boolean>
+  onMaximizeChange: (callback: (maximized: boolean) => void) => () => void
+  onMenuAction?: (callback: (action: string) => void) => () => void
+  // Current app version string (e.g. "0.0.5").
+  getAppVersion?: () => Promise<string>
+  // Auto-update. lang (e.g. "zh") routes installer downloads to the China CDN.
+  checkForUpdate?: (lang?: string) => Promise<void>
+  downloadUpdate?: (lang?: string) => Promise<void>
+  installUpdate?: () => Promise<void>
+  onUpdateStatus?: (callback: (status: UpdateStatus) => void) => () => void
+  platform: string
+  // OS UI language (e.g. "zh-CN"); used to default the language on first run.
+  systemLocale?: string
+}
+
+// Mirrors UpdateStatus in src/main/updater.ts.
+export type UpdateStatus =
+  | { state: 'checking' }
+  | { state: 'available'; version: string; notes?: string }
+  | { state: 'not-available' }
+  | { state: 'downloading'; percent: number }
+  | { state: 'downloaded'; version: string }
+  | { state: 'error'; message: string }
+
+export interface BackendStatusEvent {
+  status: 'ready' | 'error' | 'starting'
+  port?: number
+  error?: string
+}
+
+// ============================================================
+// Chat / messages / streaming
+// ============================================================
+
+export type Role = 'user' | 'assistant'
+
+/** A single ordered step inside an assistant turn (matches backend history). */
+export interface MessageStep {
+  type: 'thinking' | 'content' | 'tool'
+  content?: string
+  // tool step fields
+  id?: string
+  name?: string
+  arguments?: Record<string, unknown>
+  result?: string
+  is_error?: boolean
+  status?: string
+  execution_time?: number
+}
+
+/** Local UI message model (superset of backend history message). */
+export interface ChatMessage {
+  id: string
+  role: Role
+  content: string
+  /** Unix seconds. Backend history uses `created_at`; we normalize to `timestamp`. */
+  timestamp: number
+  attachments?: Attachment[]
+  /** Ordered steps (thinking / content / tool). Preferred over legacy toolCalls. */
+  steps?: MessageStep[]
+  /** Legacy live-stream tool events (kept for backward compat during streaming). */
+  toolCalls?: ToolCall[]
+  /** Reasoning text streamed via `reasoning` SSE events. */
+  reasoning?: string
+  /** Sequence numbers from backend (for delete/regenerate). */
+  userSeq?: number
+  botSeq?: number
+  /** Self-evolution bubble flag. */
+  kind?: 'evolution'
+  extras?: Record<string, unknown>
+  isStreaming?: boolean
+  isCancelled?: boolean
+  error?: string
+}
+
+export interface Attachment {
+  file_path: string
+  file_name: string
+  file_type: 'image' | 'video' | 'file' | 'directory'
+  preview_url?: string
+  /** Local absolute path (set for files sent via the `send` tool) so the
+   *  desktop client can open them directly with the OS default app. */
+  abs_path?: string
+}
+
+/** Live tool event during SSE streaming. */
+export interface ToolCall {
+  type: 'tool_start' | 'tool_end' | 'tool_progress'
+  tool: string
+  tool_call_id?: string
+  arguments?: Record<string, unknown>
+  result?: string
+  status?: string
+  execution_time?: number
+}
+
+/** All SSE event types emitted on /stream. */
+export type StreamEventType =
+  | 'delta'
+  | 'reasoning'
+  | 'tool_start'
+  | 'tool_progress'
+  | 'tool_end'
+  | 'message_end'
+  | 'phase'
+  | 'file_to_send'
+  | 'image'
+  | 'video'
+  | 'file'
+  | 'text'
+  | 'done'
+  | 'cancelled'
+  | 'voice_attach'
+  | 'error'
+
+export interface StreamEvent {
+  type: StreamEventType
+  content?: string
+  tool?: string
+  tool_call_id?: string
+  arguments?: Record<string, unknown>
+  status?: string
+  result?: string
+  execution_time?: number
+  has_tool_calls?: boolean
+  path?: string
+  abs_path?: string
+  file_name?: string
+  file_type?: string
+  web_url?: string
+  audio_url?: string
+  request_id?: string
+  timestamp?: number
+  user_seq?: number
+  bot_seq?: number
+  message?: string
+}
+
+// ============================================================
+// Sessions / history
+// ============================================================
+
+export interface SessionItem {
+  session_id: string
+  title: string
+  created_at: number
+  last_active: number
+  msg_count: number
+}
+
+export interface SessionsPage {
+  sessions: SessionItem[]
+  total: number
+  page: number
+  page_size: number
+  has_more: boolean
+}
+
+/** Backend history message (as returned by /api/history). */
+export interface HistoryMessage {
+  role: Role
+  content: string
+  created_at: number
+  steps?: MessageStep[]
+  tool_calls?: Array<{ id?: string; name: string; arguments?: Record<string, unknown>; result?: string }>
+  reasoning?: string
+  kind?: 'evolution'
+  extras?: Record<string, unknown>
+  /** Per-message sequence number used by delete/regenerate APIs. */
+  _seq?: number
+}
+
+export interface HistoryPage {
+  messages: HistoryMessage[]
+  total: number
+  page: number
+  page_size: number
+  has_more: boolean
+  context_start_seq?: number
+}
+
+// ============================================================
+// Config
+// ============================================================
+
+/** A label that may be localized (some providers/channels return {zh,en}). */
+export type LocalizedLabel = string | { zh: string; en: string }
+
+export interface ProviderMeta {
+  label: LocalizedLabel
+  models: string[]
+  api_base_key?: string | null
+  api_base_default?: string | null
+  api_base_placeholder?: string
+  api_key_field?: string | null
+  [k: string]: unknown
+}
+
+export interface ConfigData {
+  use_agent: boolean
+  title: string
+  model: string
+  bot_type: string
+  use_linkai: boolean
+  channel_type: string
+  agent_max_context_tokens: number
+  agent_max_context_turns: number
+  agent_max_steps: number
+  enable_thinking?: boolean
+  self_evolution_enabled?: boolean
+  api_bases: Record<string, string>
+  api_keys: Record<string, string>
+  providers: Record<string, ProviderMeta>
+  web_password_masked?: string
+  // Real password, only returned to the desktop app (trusted local machine) so
+  // it can be edited in place. Undefined for browser access.
+  web_password?: string
+}
+
+// ============================================================
+// Models console (/api/models)
+// ============================================================
+
+// A model/voice entry can be a bare id or an annotated {value, hint} object.
+export interface ModelOption {
+  value: string
+  hint?: string
+}
+export type ModelEntry = string | ModelOption
+
+export interface ModelProvider {
+  id: string
+  label: LocalizedLabel
+  configured: boolean
+  is_custom: boolean
+  custom_id?: string
+  custom_name?: string
+  active?: boolean
+  api_key_field?: string | null
+  api_base_field?: string | null
+  api_key_masked?: string
+  api_base?: string
+  api_base_default?: string
+  api_base_placeholder?: string
+  models: ModelEntry[]
+}
+
+export type CapabilityKey = 'chat' | 'vision' | 'asr' | 'tts' | 'embedding' | 'image' | 'search'
+
+// Search providers are described as objects (unlike other capabilities which
+// list provider ids only).
+export interface SearchProviderMeta {
+  id: string
+  label: LocalizedLabel
+  configured: boolean
+  needs_dedicated_key: boolean
+  api_key_masked?: string
+}
+
+export interface CapabilityState {
+  editable?: boolean
+  current_provider?: string
+  current_model?: string
+  current_voice?: string
+  current_dim?: number | null
+  suggested_provider?: string
+  providers?: string[]
+  // provider_models entries are string | {value,hint}
+  provider_models?: Record<string, ModelEntry[]>
+  // tts only: voices keyed by provider; linkai keyed further by model id
+  provider_voices?: Record<string, ModelEntry[] | Record<string, ModelEntry[]>>
+  // vision/image
+  strategy?: string
+  user_specified_model?: string
+  fallback_provider?: string
+  fallback_model?: string
+  // tts
+  reply_mode?: 'off' | 'voice_if_voice' | 'always'
+  use_linkai?: boolean
+  // image
+  runtime_active?: boolean
+  note?: string
+  // search
+  fixed_provider?: string
+  configured_providers?: string[]
+  available?: boolean
+  [k: string]: unknown
+}
+
+export interface SearchCapabilityState {
+  editable?: boolean
+  providers: SearchProviderMeta[]
+  strategy?: 'auto' | 'fixed' | string
+  current_provider?: string
+  fixed_provider?: string
+  configured_providers?: string[]
+  available?: boolean
+}
+
+export interface ModelsData {
+  status?: string
+  providers: ModelProvider[]
+  capabilities: {
+    chat: CapabilityState
+    vision: CapabilityState
+    asr: CapabilityState
+    tts: CapabilityState
+    embedding: CapabilityState
+    image: CapabilityState
+    // search has a richer providers[] shape
+    search: SearchCapabilityState
+  }
+}
+
+export type ModelsAction =
+  | { action: 'set_provider'; provider_id: string; api_key?: string; api_base?: string }
+  | { action: 'delete_provider'; provider_id: string }
+  | { action: 'set_custom_provider'; name: string; id?: string; api_base: string; api_key?: string; model?: string; make_active?: boolean }
+  | { action: 'delete_custom_provider'; id: string }
+  | { action: 'set_active_custom_provider'; id: string }
+  | { action: 'set_capability'; capability: CapabilityKey; provider_id?: string; model?: string; voice?: string; strategy?: string; provider?: string }
+  | { action: 'set_voice_reply_mode'; mode: 'off' | 'voice_if_voice' | 'always' }
+  | { action: 'set_search_credential'; api_key: string }
+
+// ============================================================
+// Channels
+// ============================================================
+
+export interface ChannelField {
+  key: string
+  label: string
+  type: 'text' | 'secret' | 'number' | 'bool'
+  value?: string | number | boolean
+  default?: string | number | boolean
+}
+
+export interface ChannelInfo {
+  name: string
+  label: { zh: string; en: string }
+  icon: string
+  color: string
+  active: boolean
+  fields: ChannelField[]
+  login_status?: string
+}
+
+export type ChannelAction = 'save' | 'connect' | 'disconnect'
+
+// ============================================================
+// Tools / skills
+// ============================================================
+
+export interface ToolInfo {
+  name: string
+  description: string
+}
+
+export interface SkillInfo {
+  name: string
+  display_name?: string
+  description: string
+  source?: string
+  enabled: boolean
+  category?: string
+}
+
+// ============================================================
+// Memory
+// ============================================================
+
+export type MemoryCategory = 'memory' | 'dream' | 'evolution'
+
+export interface MemoryItem {
+  filename: string
+  type: string // global | daily | dream | evolution
+  size: number
+  updated_at: string
+}
+
+export interface MemoryPage {
+  list: MemoryItem[]
+  total: number
+  page: number
+  page_size: number
+}
+
+// ============================================================
+// Knowledge
+// ============================================================
+
+export interface KnowledgeFile {
+  name: string
+  title: string
+  size: number
+}
+
+// A directory node in the knowledge tree (recursive).
+export interface KnowledgeDir {
+  dir: string
+  files: KnowledgeFile[]
+  children: KnowledgeDir[]
+}
+
+export interface KnowledgeList {
+  root_files?: KnowledgeFile[]
+  tree: KnowledgeDir[]
+  stats: { pages: number; size: number }
+  enabled: boolean
+}
+
+export interface KnowledgeGraph {
+  nodes: Array<{ id: string; label: string; category?: string }>
+  links: Array<{ source: string; target: string }>
+}
+
+export type KnowledgeAction =
+  | { action: 'create_category'; payload: { path: string } }
+  | { action: 'create_document'; payload: { path: string; content: string; overwrite?: boolean } }
+  | { action: 'rename_category'; payload: { path: string; new_path: string } }
+  | { action: 'delete_category'; payload: { path: string; confirm?: boolean } }
+  | { action: 'delete_documents'; payload: { paths: string[] } }
+  | { action: 'move_documents'; payload: { paths: string[]; target_category: string } }
+
+// Result row from a bulk import (one per uploaded file).
+export interface KnowledgeImportResult {
+  status: 'imported' | 'skipped' | 'failed'
+  path?: string
+  name?: string
+  message?: string
+}
+
+export interface KnowledgeImportPayload {
+  imported: number
+  skipped: number
+  failed: number
+  results: KnowledgeImportResult[]
+}
+
+// ============================================================
+// Scheduler
+// ============================================================
+
+export interface TaskSchedule {
+  type: 'cron' | 'interval' | 'once'
+  expression?: string
+  seconds?: number
+  run_at?: string
+}
+
+export interface TaskAction {
+  type: 'send_message' | 'agent_task'
+  content?: string
+  task_description?: string
+  receiver?: string
+  receiver_name?: string
+  is_group?: boolean
+  channel_type?: string
+}
+
+export interface SchedulerTask {
+  id: string
+  name: string
+  enabled: boolean
+  created_at: string
+  updated_at: string
+  schedule: TaskSchedule
+  action: TaskAction
+  next_run_at?: string
+}
+
+// ============================================================
+// Logs
+// ============================================================
+
+export interface LogEvent {
+  type: 'init' | 'line' | 'error'
+  content?: string
+  message?: string
+}
+
+declare global {
+  interface Window {
+    electronAPI?: ElectronAPI
+  }
+}
diff --git a/desktop/tailwind.config.js b/desktop/tailwind.config.js
new file mode 100644
index 0000000..8178971
--- /dev/null
+++ b/desktop/tailwind.config.js
@@ -0,0 +1,80 @@
+/** @type {import('tailwindcss').Config} */
+module.exports = {
+  content: ['./src/renderer/**/*.{html,tsx,ts}'],
+  darkMode: 'class',
+  theme: {
+    extend: {
+      fontFamily: {
+        sans: ['Inter', 'system-ui', '-apple-system', '"PingFang SC"', '"Hiragino Sans GB"', '"Microsoft YaHei"', 'sans-serif'],
+        mono: ['"JetBrains Mono"', '"Fira Code"', 'Consolas', 'monospace'],
+      },
+      colors: {
+        'danger-soft': 'var(--danger-soft)',
+        'danger-border': 'var(--danger-border)',
+        // Brand accent (kept for backward compat + explicit accent usage)
+        primary: {
+          50: '#EDFDF3',
+          100: '#D4FAE2',
+          200: '#ABF4C7',
+          300: '#74E9A4',
+          400: '#4ABE6E',
+          500: '#35A85B',
+          600: '#228547',
+          700: '#1C6B3B',
+          800: '#1A5532',
+          900: '#16462A',
+        },
+        // Semantic tokens — driven by CSS variables, theme-aware
+        accent: {
+          DEFAULT: 'var(--accent)',
+          hover: 'var(--accent-hover)',
+          active: 'var(--accent-active)',
+          soft: 'var(--accent-soft)',
+          contrast: 'var(--accent-contrast)',
+        },
+        base: 'var(--bg-base)',
+        surface: {
+          DEFAULT: 'var(--bg-surface)',
+          2: 'var(--bg-surface-2)',
+        },
+        elevated: 'var(--bg-elevated)',
+        inset: 'var(--bg-inset)',
+        content: {
+          DEFAULT: 'var(--text-primary)',
+          secondary: 'var(--text-secondary)',
+          tertiary: 'var(--text-tertiary)',
+          disabled: 'var(--text-disabled)',
+        },
+        success: 'var(--success)',
+        warning: 'var(--warning)',
+        danger: 'var(--danger)',
+        info: 'var(--info)',
+      },
+      borderColor: {
+        DEFAULT: 'var(--border-default)',
+        default: 'var(--border-default)',
+        strong: 'var(--border-strong)',
+        subtle: 'var(--border-subtle)',
+      },
+      boxShadow: {
+        sm: 'var(--shadow-sm)',
+        md: 'var(--shadow-md)',
+        lg: 'var(--shadow-lg)',
+      },
+      borderRadius: {
+        card: '12px',
+        btn: '8px',
+      },
+      animation: {
+        'pulse-dot': 'pulseDot 1.4s infinite ease-in-out both',
+      },
+      keyframes: {
+        pulseDot: {
+          '0%, 80%, 100%': { transform: 'scale(0.6)', opacity: '0.4' },
+          '40%': { transform: 'scale(1)', opacity: '1' },
+        },
+      },
+    },
+  },
+  plugins: [],
+}
diff --git a/desktop/tsconfig.json b/desktop/tsconfig.json
new file mode 100644
index 0000000..d6d5250
--- /dev/null
+++ b/desktop/tsconfig.json
@@ -0,0 +1,22 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "useDefineForClassFields": true,
+    "lib": ["ES2020", "DOM", "DOM.Iterable"],
+    "module": "ESNext",
+    "skipLibCheck": true,
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "isolatedModules": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+    "jsx": "react-jsx",
+    "strict": true,
+    "noUnusedLocals": false,
+    "noUnusedParameters": false,
+    "noFallthroughCasesInSwitch": true,
+    "resolveJsonModule": true,
+    "esModuleInterop": true
+  },
+  "include": ["src/renderer"]
+}
diff --git a/desktop/tsconfig.main.json b/desktop/tsconfig.main.json
new file mode 100644
index 0000000..9bc3504
--- /dev/null
+++ b/desktop/tsconfig.main.json
@@ -0,0 +1,17 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "module": "commonjs",
+    "lib": ["ES2020"],
+    "outDir": "dist/main",
+    "rootDir": "src/main",
+    "strict": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true,
+    "resolveJsonModule": true,
+    "declaration": false,
+    "sourceMap": true
+  },
+  "include": ["src/main/**/*"]
+}
diff --git a/desktop/vite.config.ts b/desktop/vite.config.ts
new file mode 100644
index 0000000..942bd13
--- /dev/null
+++ b/desktop/vite.config.ts
@@ -0,0 +1,22 @@
+import { defineConfig } from 'vite'
+import react from '@vitejs/plugin-react'
+import path from 'path'
+
+export default defineConfig({
+  plugins: [react()],
+  root: path.resolve(__dirname, 'src/renderer'),
+  base: './',
+  publicDir: path.resolve(__dirname, '../channel/web/static'),
+  build: {
+    outDir: path.resolve(__dirname, 'dist/renderer'),
+    emptyOutDir: true,
+  },
+  server: {
+    port: 5173,
+  },
+  resolve: {
+    alias: {
+      '@': path.resolve(__dirname, 'src/renderer/src'),
+    },
+  },
+})
diff --git a/docker/Dockerfile.latest b/docker/Dockerfile.latest
new file mode 100644
index 0000000..f86bb55
--- /dev/null
+++ b/docker/Dockerfile.latest
@@ -0,0 +1,57 @@
+FROM python:3.10-slim-bullseye
+
+LABEL maintainer="foo@bar.com"
+ARG TZ='Asia/Shanghai'
+
+ARG CHATGPT_ON_WECHAT_VER
+# Set to "false" to skip Playwright/Chromium and produce a smaller image
+ARG INSTALL_BROWSER=true
+# Set to "true" to use China mirrors for apt / pip / playwright (faster in CN)
+ARG USE_CN_MIRROR=false
+
+ENV PLAYWRIGHT_BROWSERS_PATH=/app/ms-playwright
+ENV BUILD_PREFIX=/app
+
+# Optionally switch apt and pip to China mirrors
+RUN if [ "$USE_CN_MIRROR" = "true" ]; then \
+        sed -i 's/deb.debian.org/mirrors.tuna.tsinghua.edu.cn/g' /etc/apt/sources.list; \
+        pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple/; \
+    fi
+
+ADD . ${BUILD_PREFIX}
+
+# All heavy installs + user creation in ONE layer to avoid chown duplication
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends bash ffmpeg espeak libavcodec-extra \
+    && cd ${BUILD_PREFIX} \
+    && cp config-template.json config.json \
+    && /usr/local/bin/python -m pip install --no-cache --upgrade pip \
+    && pip install --no-cache -r requirements.txt \
+    && pip install --no-cache -r requirements-optional.txt \
+    && pip install --no-cache -e . \
+    && if [ "$INSTALL_BROWSER" = "true" ]; then \
+        apt-get install -y --no-install-recommends fonts-wqy-zenhei \
+        && pip install --no-cache "playwright==1.52.0" \
+        && python -m playwright install-deps chromium \
+        && mkdir -p /app/ms-playwright \
+        && if [ "$USE_CN_MIRROR" = "true" ]; then \
+            PLAYWRIGHT_DOWNLOAD_HOST=https://registry.npmmirror.com/-/binary/playwright \
+            python -m playwright install chromium; \
+        else \
+            python -m playwright install chromium; \
+        fi; \
+    fi \
+    && rm -rf /var/lib/apt/lists/* \
+    && mkdir -p /home/agent/cow \
+    && groupadd -r agent \
+    && useradd -r -g agent -s /bin/bash -d /home/agent agent \
+    && chown -R agent:agent /home/agent ${BUILD_PREFIX} /usr/local/lib
+
+WORKDIR ${BUILD_PREFIX}
+
+ADD docker/entrypoint.sh /entrypoint.sh
+
+RUN chmod +x /entrypoint.sh \
+    && chown agent:agent /entrypoint.sh
+
+ENTRYPOINT ["/entrypoint.sh"]
diff --git a/docker/build.latest.sh b/docker/build.latest.sh
new file mode 100644
index 0000000..92c3564
--- /dev/null
+++ b/docker/build.latest.sh
@@ -0,0 +1,8 @@
+#!/bin/bash
+
+unset KUBECONFIG
+
+cd .. && docker build -f docker/Dockerfile.latest \
+             -t zhayujie/chatgpt-on-wechat .
+
+docker tag zhayujie/chatgpt-on-wechat zhayujie/chatgpt-on-wechat:$(date +%y%m%d)
\ No newline at end of file
diff --git a/docker/docker-compose.yml b/docker/docker-compose.yml
new file mode 100644
index 0000000..7e5c4e6
--- /dev/null
+++ b/docker/docker-compose.yml
@@ -0,0 +1,50 @@
+version: '2.0'
+services:
+  chatgpt-on-wechat:
+    image: zhayujie/chatgpt-on-wechat
+    container_name: chatgpt-on-wechat
+    security_opt:
+      - seccomp:unconfined
+    ports:
+      - "9899:9899"
+    environment:
+      COW_LANG: 'auto'
+      CHANNEL_TYPE: 'weixin'
+      MODEL: 'deepseek-v4-flash'
+      DEEPSEEK_API_KEY: ''
+      DEEPSEEK_API_BASE: 'https://api.deepseek.com/v1'
+      MINIMAX_API_KEY: ''
+      ZHIPU_AI_API_KEY: ''
+      ARK_API_KEY: ''
+      MOONSHOT_API_KEY: ''
+      DASHSCOPE_API_KEY: ''
+      CLAUDE_API_KEY: ''
+      CLAUDE_API_BASE: 'https://api.anthropic.com/v1'
+      OPEN_AI_API_KEY: ''
+      OPEN_AI_API_BASE: 'https://api.openai.com/v1'
+      GEMINI_API_KEY: ''
+      GEMINI_API_BASE: 'https://generativelanguage.googleapis.com'
+      VOICE_TO_TEXT: 'openai'
+      TEXT_TO_VOICE: 'openai'
+      VOICE_REPLY_VOICE: 'False'
+      SPEECH_RECOGNITION: 'True'
+      GROUP_SPEECH_RECOGNITION: 'False'
+      USE_LINKAI: 'False'
+      LINKAI_API_KEY: ''
+      LINKAI_APP_CODE: ''
+      FEISHU_APP_ID: ''
+      FEISHU_APP_SECRET: ''
+      DINGTALK_CLIENT_ID: ''
+      DINGTALK_CLIENT_SECRET: ''
+      WECOM_BOT_ID: ''
+      WECOM_BOT_SECRET: ''
+      # To access the web console from the host, set this to '0.0.0.0' and set WEB_PASSWORD
+      WEB_HOST: '127.0.0.1'
+      WEB_PASSWORD: ''
+      AGENT: 'True'
+      AGENT_MAX_CONTEXT_TOKENS: 50000
+      AGENT_MAX_CONTEXT_TURNS: 20
+      AGENT_MAX_STEPS: 20
+      SELF_EVOLUTION_ENABLED: 'True'
+    volumes:
+      - ./cow:/home/agent/cow
diff --git a/docker/entrypoint.sh b/docker/entrypoint.sh
new file mode 100755
index 0000000..633fd26
--- /dev/null
+++ b/docker/entrypoint.sh
@@ -0,0 +1,57 @@
+#!/bin/bash
+set -e
+
+# build prefix
+CHATGPT_ON_WECHAT_PREFIX=${CHATGPT_ON_WECHAT_PREFIX:-""}
+# path to config.json
+CHATGPT_ON_WECHAT_CONFIG_PATH=${CHATGPT_ON_WECHAT_CONFIG_PATH:-""}
+# execution command line
+CHATGPT_ON_WECHAT_EXEC=${CHATGPT_ON_WECHAT_EXEC:-""}
+
+# use environment variables to pass parameters
+# if you have not defined environment variables, set them below
+# export OPEN_AI_API_KEY=${OPEN_AI_API_KEY:-'YOUR API KEY'}
+# export OPEN_AI_PROXY=${OPEN_AI_PROXY:-""}
+# export SINGLE_CHAT_PREFIX=${SINGLE_CHAT_PREFIX:-'["bot", "@bot"]'}
+# export SINGLE_CHAT_REPLY_PREFIX=${SINGLE_CHAT_REPLY_PREFIX:-'"[bot] "'}
+# export GROUP_CHAT_PREFIX=${GROUP_CHAT_PREFIX:-'["@bot"]'}
+# export GROUP_NAME_WHITE_LIST=${GROUP_NAME_WHITE_LIST:-'["ChatGPT测试群", "ChatGPT测试群2"]'}
+# export IMAGE_CREATE_PREFIX=${IMAGE_CREATE_PREFIX:-'["画", "看", "找"]'}
+# export CONVERSATION_MAX_TOKENS=${CONVERSATION_MAX_TOKENS:-"1000"}
+# export SPEECH_RECOGNITION=${SPEECH_RECOGNITION:-"False"}
+# export CHARACTER_DESC=${CHARACTER_DESC:-"你是ChatGPT, 一个由OpenAI训练的大型语言模型, 你旨在回答并解决人们的任何问题，并且可以使用多种语言与人交流。"}
+# export EXPIRES_IN_SECONDS=${EXPIRES_IN_SECONDS:-"3600"}
+
+# CHATGPT_ON_WECHAT_PREFIX is empty, use /app
+if [ "$CHATGPT_ON_WECHAT_PREFIX" == "" ] ; then
+    CHATGPT_ON_WECHAT_PREFIX=/app
+fi
+
+# CHATGPT_ON_WECHAT_CONFIG_PATH is empty, use '/app/config.json'
+if [ "$CHATGPT_ON_WECHAT_CONFIG_PATH" == "" ] ; then
+    CHATGPT_ON_WECHAT_CONFIG_PATH=$CHATGPT_ON_WECHAT_PREFIX/config.json
+fi
+
+# CHATGPT_ON_WECHAT_EXEC is empty, use ‘python app.py’
+if [ "$CHATGPT_ON_WECHAT_EXEC" == "" ] ; then
+    CHATGPT_ON_WECHAT_EXEC="python app.py"
+fi
+
+# modify content in config.json
+# if [ "$OPEN_AI_API_KEY" == "YOUR API KEY" ] || [ "$OPEN_AI_API_KEY" == "" ]; then
+#     echo -e "\033[31m[Warning] You need to set OPEN_AI_API_KEY before running!\033[0m"
+# fi
+
+
+# fix ownership of mounted volumes then drop to non-root user
+if [ "$(id -u)" = "0" ]; then
+    mkdir -p /home/agent/cow
+    chown agent:agent /home/agent/cow
+    exec su agent -s /bin/bash -c "cd $CHATGPT_ON_WECHAT_PREFIX && $CHATGPT_ON_WECHAT_EXEC"
+fi
+
+# fallback: already running as agent
+cd $CHATGPT_ON_WECHAT_PREFIX
+$CHATGPT_ON_WECHAT_EXEC
+
+
diff --git a/docs/README.md b/docs/README.md
new file mode 100644
index 0000000..f406cc2
--- /dev/null
+++ b/docs/README.md
@@ -0,0 +1,30 @@
+# Documentation
+
+This directory contains the Mintlify documentation site for the project.
+
+## Prerequisites
+
+- Node.js v20.17.0 or higher (LTS recommended)
+
+## Install the CLI (one-time, global)
+
+```bash
+npm i -g mint
+```
+
+## Run the docs locally
+
+From this `docs/` directory:
+
+```bash
+mint dev
+```
+
+Then open http://localhost:3000 (or the port Mint reports if 3000 is in use).
+
+> The first run downloads the Mint preview framework (~90 MB) into `~/.mintlify/`.
+> Subsequent runs start instantly from the local cache.
+
+## More
+
+- Mintlify docs: https://www.mintlify.com/docs
diff --git a/docs/channels/dingtalk.mdx b/docs/channels/dingtalk.mdx
new file mode 100644
index 0000000..1db5f53
--- /dev/null
+++ b/docs/channels/dingtalk.mdx
@@ -0,0 +1,58 @@
+---
+title: DingTalk
+description: Integrate CowAgent into DingTalk application
+---
+
+Integrate CowAgent into DingTalk by creating an intelligent robot app on the DingTalk Open Platform.
+
+## 1. Create App
+
+1. Go to [DingTalk Developer Console](https://open-dev.dingtalk.com/fe/app#/corp/app), log in and click **Create App**, fill in the app information:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-create-app.png" width="800"/>
+
+2. Click **Add App Capability**, select **Robot** capability and click **Add**:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-add-bot.png" width="800"/>
+
+3. Configure the robot information and click **Publish**. After publishing, click "**Debug**" to automatically create a test group chat, which can be viewed in the client:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-config-bot.png" width="600"/>
+
+4. Click **Version Management & Release**, create a new version and publish:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-publish-bot.png" width="700"/>
+
+## 2. Project Configuration
+
+1. Click **Credentials & Basic Info**, get the `Client ID` and `Client Secret`:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-get-secret.png" width="700"/>
+
+2. Add the following configuration to `config.json` in the project root:
+
+```json
+{
+  "channel_type": "dingtalk",
+  "dingtalk_client_id": "YOUR_CLIENT_ID",
+  "dingtalk_client_secret": "YOUR_CLIENT_SECRET"
+}
+```
+
+3. Install the dependency:
+
+```bash
+pip3 install dingtalk_stream
+```
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-app-config.png" width="700"/>
+
+4. After starting the project, go to the DingTalk Developer Console, click **Event Subscription**, then click **Connection verified, verify channel**. When "**Connection successful**" is displayed, the configuration is complete:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-event-sub.png" width="700"/>
+
+## 3. Usage
+
+Chat privately with the robot or add it to an enterprise group to start a conversation:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-hosting-demo.png" width="650"/>
diff --git a/docs/channels/discord.mdx b/docs/channels/discord.mdx
new file mode 100644
index 0000000..e18c068
--- /dev/null
+++ b/docs/channels/discord.mdx
@@ -0,0 +1,93 @@
+---
+title: Discord
+description: Integrate CowAgent with a Discord Bot
+---
+
+> Integrate CowAgent into Discord via a Discord Bot using the **Gateway** (persistent WebSocket). Supports direct messages (DM) and server channels (triggered by @mention or replying to the bot). The Gateway uses a persistent WebSocket connection — no public IP or callback URL required, works out of the box.
+
+## 1. Setup
+
+### Step 1: Create a Discord Application and Bot
+
+1. Open the [Discord Developer Portal](https://discord.com/developers/applications), click **New Application**, enter a name (e.g. `CowAgent`), and create it.
+2. Go to the **Bot** page in the left sidebar, click **Reset Token** to generate a Bot Token, then copy and store it safely (shown only once).
+
+<Tip>
+  This token is your bot's password — keep it secret. If it leaks, click **Reset Token** again on the Bot page to regenerate it.
+</Tip>
+
+### Step 2: Enable the Message Content Intent
+
+Reading message text in both DMs and channels depends on this privileged intent.
+
+1. On the **Bot** page, find **Privileged Gateway Intents**.
+2. Turn on **Message Content Intent** and save.
+
+<Note>
+  Without this intent enabled, incoming message content will be empty and the bot will not respond.
+</Note>
+
+### Step 3: Invite the Bot to a Server
+
+1. Go to **OAuth2 → URL Generator** in the left sidebar.
+2. Under **Scopes**, check `bot`.
+3. Under **Bot Permissions**, check at least: `Send Messages`, `Read Message History`, `Attach Files`, `View Channels`.
+4. Copy the generated authorization URL at the bottom, open it in a browser, and authorize it for your target server.
+
+<Note>
+  You can skip this step if you only need DMs, but you still need a DM channel with the bot (e.g. the user messages the bot directly).
+</Note>
+
+### Step 4: Connect to CowAgent
+
+<Tabs>
+  <Tab title="Web Console (Recommended)">
+    Open the Web Console (default `http://127.0.0.1:9899`), go to **Channels**, click **Add Channel**, choose **Discord**, paste the Bot Token, and click connect.
+  </Tab>
+  <Tab title="Config File">
+    Add the following to `config.json` and start Cow:
+
+    ```json
+    {
+      "channel_type": "discord",
+      "discord_token": "your-discord-bot-token",
+      "discord_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | Key | Description | Default |
+    | --- | --- | --- |
+    | `discord_token` | Bot Token generated on the Bot page of the Developer Portal | - |
+    | `discord_group_trigger` | Channel trigger: `mention_or_reply` (@ or reply to bot) / `mention_only` (@ only) / `all` (all messages) | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+The integration is ready when you see logs like:
+
+```
+[Discord] Bot logged in as CowAgent#1234 (id=123456789)
+[Discord] ✅ Discord bot ready, listening for messages
+```
+
+## 2. Capabilities
+
+| Feature | Support |
+| --- | --- |
+| Direct message (DM) | ✅ |
+| Server channel (@bot / reply to bot) | ✅ |
+| Text messages | ✅ send / receive |
+| Image messages | ✅ send / receive |
+| File messages | ✅ send / receive (PDF / Word / Excel, etc.) |
+
+<Note>
+  A single Discord message is capped at 2000 characters; long replies are automatically split across multiple messages by line breaks.
+</Note>
+
+## 3. Usage
+
+Once connected:
+
+- **Direct message (DM)**: find your bot in the server member list, click its avatar, and message it directly.
+- **Channel**: in a channel where the bot is invited, trigger it with `@your-bot hello` or by **replying to one of the bot's messages**.
+
+When sending an image or file, you can **add a text caption** (description / question) in the attachment input — the bot will answer based on both. Sending an attachment first and then a follow-up question also works; the two messages are merged automatically.
diff --git a/docs/channels/feishu.mdx b/docs/channels/feishu.mdx
new file mode 100644
index 0000000..1283d0c
--- /dev/null
+++ b/docs/channels/feishu.mdx
@@ -0,0 +1,110 @@
+---
+title: Feishu (Lark)
+description: Integrate CowAgent into Feishu via a custom enterprise app
+---
+
+> Integrate CowAgent into Feishu via a custom enterprise app. Supports p2p chat and group chat (@bot), uses WebSocket long connection (no public IP needed), supports streaming typewriter replies and voice messages.
+
+<Note>
+  You need to be a Feishu enterprise user with admin privileges.
+</Note>
+
+## 1. Setup
+
+### Option 1: One-click Scan to Create (Recommended)
+
+No need to manually create an app on the Feishu Developer Platform. Start the Cow project, open the web console (default `http://127.0.0.1:9899/`), go to **Channels**, click **Add Channel**, choose **Feishu**, then under the **Scan QR** tab click **One-click Create Feishu App** and scan with the **Feishu App** to complete app creation and connection automatically.
+
+<img src="https://cdn.link-ai.tech/doc/20260505181126.png" width="800"/>
+
+<Note>
+  1. Requires `lark-oapi` ≥ 1.5.5.
+  2. The created app comes with all required permissions (messaging, card read/write, group events, etc.) and event subscriptions pre-configured — no manual setup on the developer console needed. Currently only the Feishu mainland version is supported (Lark international not yet supported).
+</Note>
+
+When starting from CLI without `feishu_app_id` configured, the QR code is also printed to the terminal.
+
+### Option 2: Manual Setup
+
+Manually create a custom app on the Feishu Developer Platform, then connect via Web Console or config file.
+
+**Step 1: Create the App**
+
+1. Go to [Feishu Developer Platform](https://open.feishu.cn/app/), click **Create Enterprise Custom App**:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-create-app.jpg" width="500"/>
+
+2. In **Add App Capabilities**, add the **Bot** capability:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-add-bot.jpg" width="800"/>
+
+3. In **Permission Management**, paste the following permissions and **Batch Enable** all:
+
+```
+im:message,im:message.group_at_msg,im:message.group_at_msg:readonly,im:message.p2p_msg,im:message.p2p_msg:readonly,im:message:send_as_bot,im:resource,cardkit:card:write
+```
+
+<img src="https://cdn.link-ai.tech/doc/feishu-hosting-add-auth2.png" width="800"/>
+
+4. Get `App ID` and `App Secret` from **Credentials & Basic Info**:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-appid-secret.jpg" width="800"/>
+
+**Step 2: Connect to CowAgent**
+
+<Tabs>
+  <Tab title="Web Console">
+    Open the web console, go to **Channels**, click **Add Channel**, choose **Feishu**, switch to the **Manual** tab, enter App ID and App Secret, then click connect.
+  </Tab>
+  <Tab title="Config File">
+    Add the following to `config.json` and start the program:
+
+    ```json
+    {
+      "channel_type": "feishu",
+      "feishu_app_id": "YOUR_APP_ID",
+      "feishu_app_secret": "YOUR_APP_SECRET",
+      "feishu_stream_reply": true
+    }
+    ```
+
+    | Parameter | Description | Default |
+    | --- | --- | --- |
+    | `feishu_app_id` | Feishu app App ID | - |
+    | `feishu_app_secret` | Feishu app App Secret | - |
+    | `feishu_stream_reply` | Enable streaming typewriter reply | `true` |
+  </Tab>
+</Tabs>
+
+**Step 3: Publish the App**
+
+1. After Cow is running, go to **Events & Callbacks** in the Feishu Developer Platform, choose **Long Connection** mode and save:
+
+<img src="https://cdn.link-ai.tech/doc/202601311731183.png" width="600"/>
+
+2. Click **Add Event**, search for "Receive Message" and choose **Receive Message v2.0**.
+
+3. Click **Version Management & Release**, create a version and apply for **Production Release**. Approve the request in the Feishu client:
+
+<img src="https://cdn.link-ai.tech/doc/202601311807356.png" width="600"/>
+
+## 2. Features
+
+| Feature | Status |
+| --- | --- |
+| P2P chat | ✅ |
+| Group chat (@bot) | ✅ |
+| Text messages | ✅ send/receive |
+| Image messages | ✅ send/receive |
+| Voice messages | ✅ send/receive |
+| Streaming reply | ✅ (powered by Feishu cardkit streaming card) |
+
+<Note>
+  Streaming reply requires the `cardkit:card:write` permission (already enabled by one-click creation) and Feishu client version ≥ 7.20. Older clients see an upgrade prompt; if the permission or version is not satisfied, replies fall back to plain text automatically.
+</Note>
+
+## 3. Usage
+
+After connection, search for the bot name in Feishu to start a chat.
+
+To use in groups, add the bot to a group and @-mention it.
diff --git a/docs/channels/index.mdx b/docs/channels/index.mdx
new file mode 100644
index 0000000..1b0fbba
--- /dev/null
+++ b/docs/channels/index.mdx
@@ -0,0 +1,46 @@
+---
+title: Channels Overview
+description: Channels supported by CowAgent and their capability matrix
+---
+
+CowAgent supports multiple chat channels. Switch between them at startup via `channel_type`. The Web Console is enabled by default and can run in parallel with other channels.
+
+## Capability Matrix
+
+The table below summarizes the inbound message types, bot reply types, and group chat capabilities supported by each channel, making it easy to choose by scenario.
+
+| Channel | Text | Image | File | Voice | Group Chat |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [WeChat](/channels/weixin) | ✅ | ✅ | ✅ | ✅ |  |
+| [Web Console](/channels/web) | ✅ | ✅ | ✅ | ✅ | |
+| [Feishu](/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [DingTalk](/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [WeCom Bot](/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [WeCom App](/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [Official Account](/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [WeChat Customer Service](/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [Telegram](/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+
+- The **Image / File / Voice** columns indicate that the channel can send and receive the corresponding message types; see each channel's docs for details
+- The **Group Chat** column indicates the ability to recognize and respond to group messages
+
+<Tip>
+  The voice / image capabilities of each channel depend on the configuration of the corresponding model provider. See [Models Overview](/models/index) for details.
+</Tip>
+
+## Channel List
+
+- [Web Console](/channels/web) — built-in browser-based chat and management panel, enabled by default
+- [WeChat](/channels/weixin) — log in via personal WeChat QR scan
+- [Feishu](/channels/feishu) — Feishu custom bot
+- [DingTalk](/channels/dingtalk) — DingTalk custom bot
+- [WeCom Bot](/channels/wecom-bot) — WeCom AI Bot via WebSocket long connection
+- [QQ](/channels/qq) — QQ Official Bot open platform
+- [WeCom App](/channels/wecom) — WeCom custom app integration
+- [Official Account](/channels/wechatmp) — WeChat Official Account (subscription / service)
+- [Telegram](/channels/telegram) — global IM, 5-minute setup, no public IP needed
+- [Slack](/channels/slack) — team collaboration IM, Socket Mode integration, no public IP needed
+- [Discord](/channels/discord) — community IM, Gateway connection, no public IP needed
diff --git a/docs/channels/qq.mdx b/docs/channels/qq.mdx
new file mode 100644
index 0000000..a7f0859
--- /dev/null
+++ b/docs/channels/qq.mdx
@@ -0,0 +1,88 @@
+---
+title: QQ Bot
+description: Connect CowAgent to QQ Bot (WebSocket long connection)
+---
+
+> Connect CowAgent via QQ Open Platform's bot API, supporting QQ direct messages, group chats (@bot), guild channel messages, and guild DMs. No public IP required — uses WebSocket long connection.
+
+<Note>
+  QQ Bot is created through the QQ Open Platform. It uses WebSocket long connection to receive messages and OpenAPI to send messages. No public IP or domain is required.
+</Note>
+
+## 1. Create a QQ Bot
+
+> Visit the [QQ Open Platform](https://q.qq.com), sign in with QQ. If you haven't registered, please complete [account registration](https://q.qq.com/#/register) first.
+
+1.Go to the [QQ Open Platform - Bot List](https://q.qq.com/#/apps), and click **Create Bot**:
+
+<img src="https://cdn.link-ai.tech/doc/20260317162900.png" width="800"/>
+
+2.Fill in the bot name, avatar, and other basic information to complete the creation:
+
+<img src="https://cdn.link-ai.tech/doc/20260317163005.png" width="800"/>
+
+3.Enter the bot configuration page, go to **Development Management**, and complete the following steps:
+
+  - Copy and save the **AppID** (Bot ID)
+  - Generate and save the **AppSecret** (Bot Secret)
+
+<img src="https://cdn.link-ai.tech/doc/20260317164955.png" width="800"/>
+
+## 2. Configuration and Running
+
+### Option A: Web Console
+
+Start the program and open the Web console (local access: http://127.0.0.1:9899/). Go to the **Channels** tab, click **Connect Channel**, select **QQ Bot**, fill in the AppID and AppSecret from the previous step, and click Connect.
+
+<img src="https://cdn.link-ai.tech/doc/20260317165425.png" width="800"/>
+
+### Option B: Config File
+
+Add the following to your `config.json`:
+
+```json
+{
+  "channel_type": "qq",
+  "qq_app_id": "YOUR_APP_ID",
+  "qq_app_secret": "YOUR_APP_SECRET"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `qq_app_id` | AppID of the QQ Bot, found in Development Management on the open platform |
+| `qq_app_secret` | AppSecret of the QQ Bot, found in Development Management on the open platform |
+
+After configuration, start the program. The log message `[QQ] ✅ Connected successfully` indicates a successful connection.
+
+
+## 3. Usage
+
+In the QQ Open Platform, go to **Management → Usage Scope & Members**, scan the "Add to group and message list" QR code with your QQ client to start chatting with the bot:
+
+<img src="https://cdn.link-ai.tech/doc/20260317165947.png" width="800"/>
+
+Chat example:
+<img src="https://cdn.link-ai.tech/doc/20260317171508.png" width="800"/>
+
+## 4. Supported Features
+
+> Note: To use the QQ bot in group chats and guild channels, you need to complete the publishing review and configure usage scope permissions.
+
+| Feature | Status |
+| --- | --- |
+| QQ Direct Messages | ✅ |
+| QQ Group Chat (@bot) | ✅ |
+| Guild Channel (@bot) | ✅ |
+| Guild DM | ✅ |
+| Text Messages | ✅ Send & Receive |
+| Image Messages | ✅ Send & Receive (group & direct) |
+| File Messages | ✅ Send (group & direct) |
+| Scheduled Tasks | ✅ Active push (4 per user per month) |
+
+
+## 5. Notes
+
+- **Passive message limits**: QQ direct message replies are valid for 60 minutes (max 5 replies per message); group chat replies are valid for 5 minutes.
+- **Active message limits**: Both direct and group chats have a monthly limit of 4 active messages. Keep this in mind when using the scheduled tasks feature.
+- **Event permissions**: By default, `GROUP_AND_C2C_EVENT` (QQ group/direct) and `PUBLIC_GUILD_MESSAGES` (guild public messages) are subscribed. Apply for additional permissions on the open platform if needed.
diff --git a/docs/channels/slack.mdx b/docs/channels/slack.mdx
new file mode 100644
index 0000000..f95272c
--- /dev/null
+++ b/docs/channels/slack.mdx
@@ -0,0 +1,118 @@
+---
+title: Slack
+description: Integrate CowAgent with a Slack App
+---
+
+> Integrate CowAgent into Slack via a Slack App in **Socket Mode**. Supports direct messages (DM) and channels (triggered by @mention or replying within a thread). Socket Mode uses a persistent WebSocket connection — no public IP or callback URL required, works out of the box.
+
+## 1. Setup
+
+### Step 1: Create a Slack App
+
+1. Open the [Slack API apps page](https://api.slack.com/apps), click **Create New App** → **From scratch**.
+2. Enter an **App Name** (e.g. `CowAgent`), pick the **Workspace** to install into, and create it.
+
+### Step 2: Enable Socket Mode and get the App Token
+
+1. In the left sidebar go to **Settings → Socket Mode** and turn on **Enable Socket Mode**.
+2. You will be prompted to generate an **App-Level Token** with the `connections:write` scope. Save this token starting with `xapp-`.
+
+<Tip>
+  Socket Mode receives events over a WebSocket connection, so you don't need to expose a public callback URL — ideal for local or intranet deployments.
+</Tip>
+
+### Step 3: Configure bot scopes and install
+
+1. Go to **Features → OAuth & Permissions**, click **Add an OAuth Scope** under **Bot Token Scopes**, and add the following scopes one by one:
+
+   ```
+   app_mentions:read
+   channels:history
+   chat:write
+   commands
+   files:read
+   files:write
+   groups:history
+   im:history
+   mpim:history
+   users:read
+   ```
+
+   <Note>
+     `files:read` / `files:write` are used for sending/receiving images and files; omit them if you only need text conversations.
+   </Note>
+
+2. Go to **Features → Event Subscriptions**, turn on **Enable Events**, and under **Subscribe to bot events** click **Add Bot User Event** to add:
+
+   ```
+   app_mention
+   message.im
+   message.channels
+   ```
+
+   <Note>
+     Add `message.groups` if you need to use the bot in private channels.
+   </Note>
+3. Go to **Features → App Home**, enable **Messages Tab** under **Show Tabs**, and check **Allow users to send Slash commands and messages from the messages tab**. Otherwise the DM input box is disabled and users cannot message the bot.
+4. Back in **OAuth & Permissions**, click **Install to Workspace**. After installing, copy the **Bot User OAuth Token** starting with `xoxb-`.
+
+<Tip>
+  If the Slack client still shows "Sending messages to this app has been turned off", make sure you completed the App Home step above, then refresh or restart the Slack client (remove the app from your conversations and reopen it if needed).
+</Tip>
+
+### Step 4: Connect to CowAgent
+
+<Tabs>
+  <Tab title="Web Console (Recommended)">
+    Open the Web Console (default `http://127.0.0.1:9899`), go to **Channels**, click **Add Channel**, choose **Slack**, paste the Bot Token (`xoxb-`) and App Token (`xapp-`), and click connect.
+  </Tab>
+  <Tab title="Config File">
+    Add the following to `config.json` and start Cow:
+
+    ```json
+    {
+      "channel_type": "slack",
+      "slack_bot_token": "xoxb-xxxxxxxxxxxx",
+      "slack_app_token": "xapp-xxxxxxxxxxxx",
+      "slack_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | Key | Description | Default |
+    | --- | --- | --- |
+    | `slack_bot_token` | Bot User OAuth Token, like `xoxb-...` | - |
+    | `slack_app_token` | App-Level Token (generated after enabling Socket Mode), like `xapp-...` | - |
+    | `slack_group_trigger` | Channel trigger: `mention_or_reply` (@ or reply in thread) / `mention_only` (@ only) / `all` (all messages) | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+The integration is ready when you see logs like:
+
+```
+[Slack] Bot logged in as user_id=U0XXXXXXX, team=Txxxxxxxx
+[Slack] ✅ Slack bot ready, listening for events
+```
+
+## 2. Capabilities
+
+| Feature | Support |
+| --- | --- |
+| Direct message (DM) | ✅ |
+| Channel (@bot / reply in thread) | ✅ |
+| Text messages | ✅ send / receive |
+| Image messages | ✅ send / receive |
+| File messages | ✅ send / receive (PDF / Word / Excel, etc.) |
+| Thread replies | ✅ replies are posted to the thread of the triggering message |
+
+<Note>
+  Slack organizes conversations into threads. The bot posts replies into the thread of the triggering message, keeping channels tidy.
+</Note>
+
+## 3. Usage
+
+Once connected:
+
+- **Direct message (DM)**: find your App under **Apps** in the Slack sidebar and message it directly.
+- **Channel**: invite the App into a channel (`/invite @your-app`), then trigger it with `@your-app hello`; continue the conversation by replying within the same thread.
+
+When sending an image or file, you can **add a text caption** (description / question) in the attachment input — the bot will answer based on both. Sending an attachment first and then a follow-up question also works; the two messages are merged automatically.
diff --git a/docs/channels/telegram.mdx b/docs/channels/telegram.mdx
new file mode 100644
index 0000000..f90da99
--- /dev/null
+++ b/docs/channels/telegram.mdx
@@ -0,0 +1,111 @@
+---
+title: Telegram
+description: Integrate CowAgent with Telegram via the Bot API
+---
+
+> Integrate CowAgent into Telegram via the official Bot API. Supports private chat and group chat (triggered by @mention or replying to the bot). Uses Long Polling — no public IP required, works out of the box.
+
+
+## 1. Setup
+
+### Step 1: Create a Bot via BotFather
+
+1. Open the official account [@BotFather](https://t.me/BotFather) in Telegram.
+2. Send `/newbot` and follow the prompts:
+   - **Bot name** (display name, e.g. `My CowAgent Bot`)
+   - **Bot username** (must end with `bot`, e.g. `my_cowagent_bot`)
+3. Once created, BotFather returns an **HTTP API Token** (e.g. `123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ`). Keep it safe.
+
+<Tip>
+  The token is the password of your bot — never share it. If it leaks, send `/revoke` to `@BotFather` to reset it.
+</Tip>
+
+### Step 2: (Group chat only) Disable Privacy Mode
+
+Skip this step if you only use private chat. Telegram bots run in **Privacy Mode** by default — in groups they can only see commands suffixed with `@bot` (e.g. `/start@your_bot`) and replies to bot messages; **plain `@bot hello` text messages are not delivered**, so the bot will appear unresponsive in groups.
+
+Send the following to `@BotFather`:
+
+1. `/setprivacy`
+2. Pick the bot you just created
+3. Choose `Disable`
+
+<Note>
+  If the bot is still silent in groups after this, try removing it from the group and adding it back.
+</Note>
+
+### Step 3: Connect to CowAgent
+
+<Tabs>
+  <Tab title="Web Console (Recommended)">
+    Open the Web Console (default `http://127.0.0.1:9899`), go to **Channels**, click **Add Channel**, choose **Telegram**, paste the Bot Token, and click connect.
+  </Tab>
+  <Tab title="Config File">
+    Add the following to `config.json` and start Cow:
+
+    ```json
+    {
+      "channel_type": "telegram",
+      "telegram_token": "123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ",
+      "telegram_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | Key | Description | Default |
+    | --- | --- | --- |
+    | `telegram_token` | HTTP API Token returned by BotFather | - |
+    | `telegram_group_trigger` | Group trigger: `mention_or_reply` (@ or reply) / `mention_only` (@ only) / `all` (all messages) | `mention_or_reply` |
+    | `telegram_register_commands` | Whether to register the command menu with BotFather on startup | `true` |
+  </Tab>
+</Tabs>
+
+The integration is ready when you see logs like:
+
+```
+[Telegram] Bot logged in as @my_cowagent_bot (id=123456789)
+[Telegram] Registered 10 bot commands
+[Telegram] ✅ Telegram bot ready, polling for updates
+```
+
+## 2. Capabilities
+
+| Feature | Support |
+| --- | --- |
+| Private chat | ✅ |
+| Group chat (@bot / reply to bot) | ✅ |
+| Text messages | ✅ send / receive |
+| Image messages | ✅ send / receive |
+| Voice messages | ✅ send / receive (OGG/Opus) |
+| Video messages | ✅ send / receive |
+| File messages | ✅ send / receive (PDF / Word / Excel, etc.) |
+| Command menu | ✅ aligned with Web Console slash commands |
+
+### Command Menu
+
+On startup, the channel registers a command menu with BotFather. Typing `/` in Telegram shows a dropdown:
+
+| Command | Description |
+| --- | --- |
+| `/help` | Show command help |
+| `/status` | View runtime status |
+| `/context` | View conversation context (`/context clear` to clear) |
+| `/skill` | Skill management (`/skill list`, `/skill install`, ...) |
+| `/memory` | Memory management (`/memory dream`) |
+| `/knowledge` | Knowledge base (`/knowledge list` / `on` / `off`) |
+| `/config` | View current config |
+| `/cancel` | Cancel the running Agent task |
+| `/logs` | View recent logs |
+| `/version` | Show version |
+
+<Note>
+  Telegram's command menu only displays top-level commands; subcommands are entered with a space, e.g. `/skill list`, `/context clear`.
+</Note>
+
+## 3. Usage
+
+Once connected:
+
+- **Private chat**: search for your bot username (e.g. `@my_cowagent_bot`) in Telegram, click `Start` and chat away.
+- **Group chat**: add the bot to a group, then trigger it with `@bot hello` or by **replying to one of the bot's messages**. If the bot doesn't respond in groups, double-check Privacy Mode in [Step 2](#step-2-group-chat-only-disable-privacy-mode).
+
+When sending an image or file, you can **add a caption** (description / question) directly in the attachment input — the bot will answer based on both. Sending an attachment first and then a follow-up question also works; the two messages are merged automatically.
diff --git a/docs/channels/web.mdx b/docs/channels/web.mdx
new file mode 100644
index 0000000..97c4307
--- /dev/null
+++ b/docs/channels/web.mdx
@@ -0,0 +1,95 @@
+---
+title: Web Console
+description: Use CowAgent through the Web Console
+---
+
+The Web Console is CowAgent's default channel. It runs automatically once started, letting you chat with the Agent in a browser and manage models, skills, memory, channels, and other configuration online.
+
+## Configuration
+
+```json
+{
+  "channel_type": "web",
+  "web_host": "0.0.0.0",
+  "web_port": 9899,
+  "web_password": "",
+  "enable_thinking": false
+}
+```
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `channel_type` | Set to `web` | `web` |
+| `web_host` | Web service listen address. Defaults to `127.0.0.1` (local only); set to `0.0.0.0` for public access and configure a password | `""` |
+| `web_port` | Web service listen port | `9899` |
+| `web_password` | Access password. Leave empty to disable password protection; recommended when listening on `0.0.0.0` | `""` |
+| `web_session_expire_days` | Login session validity in days | `30` |
+| `web_file_serve_root` | Root directory the web console can directly read/send files from. Defaults to the user home dir and agent workspace only; set to `/` to allow the whole filesystem | `"~"` |
+| `enable_thinking` | Whether to enable deep thinking mode | `false` |
+
+Once a password is configured, you must enter it to log in when accessing the console. The login session is kept for 30 days by default, so restarting the service during that period does not require re-login. The password can also be changed online from the "Configuration" page in the console.
+
+## Access URL
+
+After starting the project, visit:
+
+- Local: `http://localhost:9899`
+- Server: `http://<server-ip>:9899`
+
+<Note>
+  Ensure the server firewall and security group allow the corresponding port.
+</Note>
+
+## Features
+
+### Chat Interface
+
+Supports streaming output with real-time display of the Agent's reasoning process and tool calls, providing intuitive observation of the Agent's decision-making. Deep thinking can be toggled via configuration or the "Agent Configuration" switch in the console.
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### Multi-Session Management
+
+The chat interface supports multi-session management. All session records are persistently stored in the database:
+
+- **Session List**: Click the history icon on the left to expand/collapse the session list panel, with scroll-to-load support for all historical sessions
+- **AI-Generated Titles**: After the first exchange in a new session, the model is automatically called to generate a short summary title
+- **New Session**: Click the "New Chat" button at the top of the session list or the `+` button in the input area to create a new session
+- **Delete Session**: Click the delete button on a session item and confirm to permanently delete the session and all its messages
+- **Clear Context**: Click the clear button in the input area to insert a divider in the current session. Messages above the divider are still displayed but no longer included as context for the model
+
+### Model Management
+
+Manage text, image, voice, and embedding model configurations for different providers online — no need to edit config files manually:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260521212949.png" />
+
+### Skill Management
+
+View and manage Agent skills (Skills) online:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+### Memory Management
+
+View and manage Agent memory online:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+### Channel Management
+
+Manage connected channels online with real-time connect/disconnect operations:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+### Scheduled Tasks
+
+View and manage scheduled tasks online, including one-time tasks, fixed intervals, and Cron expressions:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+### Logs
+
+View Agent runtime logs in real time for monitoring and troubleshooting:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
diff --git a/docs/channels/wechat-kf.mdx b/docs/channels/wechat-kf.mdx
new file mode 100644
index 0000000..bb1ac16
--- /dev/null
+++ b/docs/channels/wechat-kf.mdx
@@ -0,0 +1,130 @@
+---
+title: WeChat Customer Service
+description: Integrate CowAgent into WeChat Customer Service
+---
+
+By binding a WeCom custom enterprise app to a WeChat Customer Service account, CowAgent can take over inbound inquiries from external WeChat users and serve them through links or QR codes embedded in WeChat Mini Programs, Official Accounts, Video Channels, and Video Channel stores.
+
+<Note>
+  WeChat Customer Service only supports Docker deployment or server Python deployment. A publicly reachable callback URL is required; local run mode is not supported.
+</Note>
+
+## 1. Prerequisites
+
+Required resources:
+
+1. A server with a public IP
+2. A registered and verified WeCom account
+3. WeChat Customer Service capability enabled
+
+<Note>
+  It is recommended to create a **dedicated** WeCom custom app for Customer Service rather than reusing the existing `wechatcom_app` one — otherwise the two channels will compete for the same callback URL.
+</Note>
+
+## 2. Create a WeCom Custom App
+
+1. In the [WeCom Admin Console](https://work.weixin.qq.com/wework_admin/frame#apps), go to **Application Management → Create Application**:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+2. Click **My Enterprise** and find the **Corp ID** at the bottom of the page (it goes into `wechat_kf_corp_id`):
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-companyid.png" width="600"/>
+
+3. Open the app you just created and click **"View"** next to Secret. The Secret will be pushed to the admin's phone via the WeCom app, where it can be viewed:
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-agent-secret.png" width="600"/>
+
+4. Open the app's **Receive Messages → Set API Reception** page, click **"Random Generate"** to generate the **Token** and **EncodingAESKey**, and save them:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wechatcom-hosting-token-aeskey.jpg" width="600"/>
+
+<Note>
+  Saving the API reception configuration will fail at this point because the program has not started yet. Come back to save it after the project is running.
+</Note>
+
+## 3. Configuration and Run
+
+Fill in the 4 fields collected from the previous step (Corp ID / Secret / Token / EncodingAESKey):
+
+<Tabs>
+  <Tab title="Web Console">
+    Start the Cow project and open the Web Console. Go to the **Channels** menu, click **Connect**, choose **WeChat Customer Service**, fill in Corp ID / Secret / Token / AES Key (port defaults to 9888, configurable), and click Connect.
+
+    <img src="https://cdn.link-ai.tech/doc/cow-weixinkefu-web-control.png" width="800"/>
+  </Tab>
+  <Tab title="Config File">
+    Add the following configuration to `config.json` (each parameter maps to a field shown in the screenshots above):
+
+    ```json
+    {
+      "channel_type": "wechat_kf",
+      "wechat_kf_corp_id": "YOUR_CORP_ID",
+      "wechat_kf_secret": "YOUR_SECRET",
+      "wechat_kf_token": "YOUR_TOKEN",
+      "wechat_kf_aes_key": "YOUR_AES_KEY",
+      "wechat_kf_port": 9888
+    }
+    ```
+
+    | Parameter | Description |
+    | --- | --- |
+    | `wechat_kf_corp_id` | Corp ID |
+    | `wechat_kf_secret` | Secret of the WeCom custom app bound to Customer Service |
+    | `wechat_kf_token` | Token from the API reception config |
+    | `wechat_kf_aes_key` | EncodingAESKey from the API reception config |
+    | `wechat_kf_port` | Listening port, default 9888 |
+  </Tab>
+</Tabs>
+
+After connecting, start the program (the Web Console method restarts the channel automatically). When the log shows `Listening on http://0.0.0.0:9888/wxkf/`, the program is running successfully. You need to open this port externally (e.g., allow it in the cloud server security group).
+
+Then go back to **Receive Messages → Set API Reception** in the WeCom console and set the callback URL to `http://<your-host>:9888/wxkf/`, then click Save. After saving successfully, you also need to add the server IP to **Enterprise Trusted IPs**, otherwise messages cannot be sent or received:
+
+<img src="https://cdn.link-ai.tech/doc/wechat-com_config.png" width="600"/>
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  If URL verification fails or the configuration is unsuccessful:
+  1. Ensure the server firewall is disabled and the security group allows the listening port (default 9888)
+  2. Carefully check that Token, Secret, EncodingAESKey and other parameters are consistent, and the URL format is correct
+  3. Verified WeCom accounts must use a filed domain matching the entity
+</Warning>
+
+## 4. Bind a WeChat Customer Service Account
+
+In the WeCom Admin Console, go to **WeChat Customer Service**, create a customer service account, and bind it to the custom app you created above:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step1.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step2.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step3.jpg" width="600"/>
+
+After binding, go to **WeChat Customer Service → Account Details**, and under **"Access Link"**:
+
+- Click **"Copy Link"** to get an access link like `https://work.weixin.qq.com/kfid/kfcd83e5896b9ba07be`
+- Click **"Generate QR Code"** to get the corresponding QR code
+
+Distribute the link or QR code to your WeChat customers:
+
+<img src="https://cdn.link-ai.tech/doc/wechat-customer-service_use.png" width="600"/>
+
+## 5. Usage
+
+After WeChat users enter the customer service conversation via the link or QR code, they can chat with the AI across multiple turns, with support for text, image, and voice messages:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-chat-demo.jpg" width="900"/>
+
+Beyond that, leveraging the official WeChat ecosystem, WeChat Customer Service can also be embedded into Official Accounts, Mini Programs, Video Channels and more. See the **WeChat Customer Service → Access Scenarios** section in the [WeCom Admin Console](https://work.weixin.qq.com/wework_admin/frame#/app/servicer) for details:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-interface-demo.png" width="800"/>
+
+## FAQ
+
+Make sure the following dependencies are installed:
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/channels/wechatmp.mdx b/docs/channels/wechatmp.mdx
new file mode 100644
index 0000000..3c6c2c8
--- /dev/null
+++ b/docs/channels/wechatmp.mdx
@@ -0,0 +1,72 @@
+---
+title: WeChat Official Account
+description: Integrate CowAgent with WeChat Official Accounts
+---
+
+CowAgent supports both personal subscription accounts and enterprise service accounts.
+
+| Type | Requirements | Features |
+| --- | --- | --- |
+| **Personal Subscription** | Available to individuals | Sends a placeholder reply first; users must send a message to retrieve the full response |
+| **Enterprise Service** | Enterprise with verified customer service API | Can proactively push replies to users |
+
+<Note>
+  Official Accounts only support server and Docker deployment, not local run mode. Install extended dependencies: `pip3 install -r requirements-optional.txt`
+</Note>
+
+## 1. Personal Subscription Account
+
+Add the following configuration to `config.json`:
+
+```json
+{
+  "channel_type": "wechatmp",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "wx73f9******d1e48",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
+
+### Setup Steps
+
+These configurations must be consistent with the [WeChat Official Account Platform](https://mp.weixin.qq.com/advanced/advanced?action=dev&t=advanced/dev). Navigate to **Settings & Development → Basic Configuration → Server Configuration** and configure as shown below:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103506.png" width="480"/>
+
+1. Enable the developer secret on the platform (corresponds to `wechatmp_app_secret`), and add the server IP to the whitelist
+2. Fill in the `config.json` with the official account parameters matching the platform configuration
+3. Start the program, which listens on port 80 (use `sudo` if you don't have permission; stop any process occupying port 80)
+4. **Enable server configuration** on the official account platform and submit. A successful save means the configuration is complete. Note that the **"Server URL"** must be in the format `http://{HOST}/wx`, where `{HOST}` can be the server IP or domain
+
+After following the account and sending a message, you should see the following result:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103522.png" width="720"/>
+
+Due to subscription account limitations, short replies (within 15s) can be returned immediately, but longer replies will first send a "Thinking..." placeholder, requiring users to send any text to retrieve the answer. Enterprise service accounts can solve this with the customer service API.
+
+<Tip>
+  **Voice Recognition**: You can use WeChat's built-in voice recognition. Enable "Receive Voice Recognition Results" under "Settings & Development → API Permissions" on the official account management page.
+</Tip>
+
+## 2. Enterprise Service Account
+
+The setup process for enterprise service accounts is essentially the same as personal subscription accounts, with the following differences:
+
+1. Register an enterprise service account on the platform and complete WeChat certification. Confirm that the **Customer Service API** permission has been granted
+2. Set `"channel_type": "wechatmp_service"` in `config.json`; other configurations remain the same
+3. Even for longer replies, they can be proactively pushed to users without requiring manual retrieval
+
+```json
+{
+  "channel_type": "wechatmp_service",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "YOUR_APP_ID",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
diff --git a/docs/channels/wecom-bot.mdx b/docs/channels/wecom-bot.mdx
new file mode 100644
index 0000000..93da515
--- /dev/null
+++ b/docs/channels/wecom-bot.mdx
@@ -0,0 +1,104 @@
+---
+title: WeCom Bot
+description: Connect CowAgent to WeCom AI Bot (WebSocket long connection)
+---
+
+> Connect CowAgent via WeCom AI Bot, supporting both internal direct messages and group chats. No public IP required — uses a WebSocket long connection, with Markdown rendering and streaming output.
+
+<Note>
+  WeCom Bot and WeCom App are two different integration methods. WeCom Bot uses a WebSocket long connection and requires no public IP or domain, making setup much simpler.
+</Note>
+
+## 1. Connection methods
+
+### Option A: One-click QR scan (recommended)
+
+No need to create the bot ahead of time. Start CowAgent and open the Web console (local URL: http://127.0.0.1:9899/), go to the **Channels** tab, click **Connect Channel**, choose **WeCom Bot**, switch to **QR scan** mode, and scan the QR code with **WeCom** — bot creation and connection complete automatically.
+
+<img src="https://cdn.link-ai.tech/doc/20260401121213.png" width="800"/>
+
+<Note>
+  After a successful scan, you can further configure the bot (name, avatar, visibility scope, etc.) in **WeCom Workbench → AI Bot**.
+</Note>
+
+### Option B: Manual creation
+
+Create the AI Bot in WeCom and obtain the Bot ID and Secret, then connect via the Web console or config file.
+
+**Step 1: Create the AI Bot**
+
+1. Open the WeCom client, go to **Workbench**, and click **AI Bot**:
+
+<img src="https://cdn.link-ai.tech/doc/20260316180959.png" width="800"/>
+
+2. Click **Create Bot → Manual Creation**:
+
+<img src="https://cdn.link-ai.tech/doc/20260316181118.png" width="800"/>
+
+3. Scroll to the bottom of the right panel and select **API Mode**:
+
+<img src="https://cdn.link-ai.tech/doc/20260316181215.png" width="800"/>
+
+4. Set the bot name, avatar, and visibility scope. Choose **Long Connection** mode, save the **Bot ID** and **Secret**, then click Save.
+
+**Step 2: Connect to CowAgent**
+
+<Tabs>
+  <Tab title="Web Console">
+    Open the Web console, go to the **Channels** tab, click **Connect Channel**, choose **WeCom Bot**, switch to **Manual** mode, enter the Bot ID and Secret, and click Connect.
+
+    <img src="https://cdn.link-ai.tech/doc/20260316181711.png" width="800"/>
+  </Tab>
+  <Tab title="Config File">
+    Add the following to `config.json`, then start CowAgent:
+
+    ```json
+    {
+      "channel_type": "wecom_bot",
+      "wecom_bot_id": "YOUR_BOT_ID",
+      "wecom_bot_secret": "YOUR_SECRET"
+    }
+    ```
+
+    | Parameter | Description |
+    | --- | --- |
+    | `wecom_bot_id` | Bot ID of the AI Bot |
+    | `wecom_bot_secret` | Secret of the AI Bot |
+  </Tab>
+</Tabs>
+
+The log line `[WecomBot] Subscribe success` confirms the connection is established.
+
+<Note>
+  A **webhook (HTTP callback) mode** is also supported: when creating the bot, choose **Use URL callback**, set the receive-message URL to `http(s)://<your-domain-or-ip>:9892/wecombot`, and copy the Token and EncodingAESKey from that page. This mode needs a publicly reachable address and does not support file sending or scheduled push, so the long connection is generally recommended. The corresponding `config.json`:
+
+```json
+{
+  "channel_type": "wecom_bot",
+  "wecom_bot_mode": "webhook",
+  "wecom_bot_token": "YOUR_TOKEN",
+  "wecom_bot_encoding_aes_key": "YOUR_ENCODING_AES_KEY",
+  "wecom_bot_port": 9892
+}
+```
+</Note>
+
+## 2. Supported features
+
+| Feature | Status |
+| --- | --- |
+| Direct chat | ✅ |
+| Group chat (@bot) | ✅ |
+| Text messages | ✅ Send / Receive |
+| Image messages | ✅ Send / Receive |
+| File messages | ✅ Send / Receive |
+| Streaming replies | ✅ |
+| Scheduled push messages | ✅ |
+
+## 3. Usage
+
+Search for the bot's name inside WeCom to start a direct chat.
+
+To use the bot in an internal group chat, add it to the group and @-mention it.
+
+<img src="https://cdn.link-ai.tech/doc/20260316182902.png" width="800"/>
diff --git a/docs/channels/wecom.mdx b/docs/channels/wecom.mdx
new file mode 100644
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+++ b/docs/channels/wecom.mdx
@@ -0,0 +1,98 @@
+---
+title: WeCom
+description: Integrate CowAgent into WeCom enterprise app
+---
+
+Integrate CowAgent into WeCom through a custom enterprise app, supporting one-on-one chat for internal employees.
+
+<Note>
+  WeCom only supports Docker deployment or server Python deployment. Local run mode is not supported.
+</Note>
+
+## 1. Prerequisites
+
+Required resources:
+
+1. A server with public IP (overseas server, or domestic server with a proxy for international API access)
+2. A registered WeCom account (individual registration is possible but cannot be certified)
+3. Certified WeCom accounts additionally require a domain filed under the corresponding entity
+
+## 2. Create WeCom App
+
+1. In the [WeCom Admin Console](https://work.weixin.qq.com/wework_admin/frame#profile), click **My Enterprise** and find the **Corp ID** at the bottom of the page. Save this ID for the `wechatcom_corp_id` configuration field.
+
+2. Switch to **Application Management** and click Create Application:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+3. On the application creation page, record the `AgentId` and `Secret`:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103218.png" width="580"/>
+
+4. Click **Set API Reception** to configure the application interface:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103211.png" width="520"/>
+
+- URL format: `http://ip:port/wxcomapp` (certified enterprises must use a filed domain)
+- Generate random `Token` and `EncodingAESKey` and save them for the configuration file
+
+<Note>
+  The API reception configuration cannot be saved at this point because the program hasn't started yet. Come back to save it after the project is running.
+</Note>
+
+## 3. Configuration and Run
+
+Add the following configuration to `config.json` (the mapping between each parameter and the WeCom console is shown in the screenshots above):
+
+```json
+{
+  "channel_type": "wechatcom_app",
+  "single_chat_prefix": [""],
+  "wechatcom_corp_id": "YOUR_CORP_ID",
+  "wechatcomapp_token": "YOUR_TOKEN",
+  "wechatcomapp_secret": "YOUR_SECRET",
+  "wechatcomapp_agent_id": "YOUR_AGENT_ID",
+  "wechatcomapp_aes_key": "YOUR_AES_KEY",
+  "wechatcomapp_port": 9898
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `wechatcom_corp_id` | Corp ID |
+| `wechatcomapp_token` | Token from API reception config |
+| `wechatcomapp_secret` | App Secret |
+| `wechatcomapp_agent_id` | App AgentId |
+| `wechatcomapp_aes_key` | EncodingAESKey from API reception config |
+| `wechatcomapp_port` | Listen port, default 9898 |
+
+After configuration, start the program. When the log shows `http://0.0.0.0:9898/`, the program is running successfully. You need to open this port externally (e.g., allow it in the cloud server security group).
+
+After the program starts, return to the WeCom Admin Console to save the **Message Server Configuration**. After saving successfully, you also need to add the server IP to **Enterprise Trusted IPs**, otherwise messages cannot be sent or received:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  If the URL configuration callback fails or the configuration is unsuccessful:
+  1. Ensure the server firewall is disabled and the security group allows the listening port
+  2. Carefully check that Token, Secret Key and other parameter configurations are consistent, and that the URL format is correct
+  3. Certified WeCom accounts must configure a filed domain matching the entity
+</Warning>
+
+## 4. Usage
+
+Search for the app name you just created in WeCom to start chatting directly. You can run multiple instances listening on different ports to create multiple WeCom apps:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103228.png" width="720"/>
+
+To allow external personal WeChat users to use the app, go to **My Enterprise → WeChat Plugin**, share the invite QR code. After scanning and following, personal WeChat users can join and chat with the app:
+
+<img src="https://cdn.link-ai.tech/doc/20260228103232.png" width="520"/>
+
+## FAQ
+
+Make sure the following dependencies are installed:
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/channels/weixin.mdx b/docs/channels/weixin.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/channels/weixin.mdx
@@ -0,0 +1,71 @@
+---
+title: WeChat
+description: Connect CowAgent to personal WeChat (via the official API)
+---
+
+> Connect CowAgent to your personal WeChat — scan to log in, no public IP required. Supports text, image, voice, file, and video messages in 1-on-1 chats. Backed by WeChat's official API; safe to use. After connecting, a bot assistant is added to your conversation list without affecting normal account usage.
+
+## 1. Setup and run
+
+### Option A: Web console
+
+Start CowAgent and open the Web console (local URL: http://127.0.0.1:9899/). Go to the **Channels** tab, click **Connect Channel**, select **WeChat**, and follow the prompts to scan in.
+
+<img src="https://cdn.link-ai.tech/doc/20260322195114.png" width="800" />
+
+### Option B: Config file
+
+Set `channel_type` to `weixin` in `config.json`:
+
+```json
+{
+  "channel_type": "weixin"
+}
+```
+
+After starting CowAgent, a QR code is displayed in the terminal. Scan it with WeChat to complete login.
+
+<img src="https://cdn.link-ai.tech/doc/20260322195509.png" width="800" />
+
+<Note>
+  1. For backward compatibility, setting `channel_type` to `wx` also activates the WeChat channel.
+  2. The WeChat client must be on version **8.0.69** or higher.
+</Note>
+
+## 2. Usage
+
+Once authorized, the integration completes and you can start chatting. A bot assistant is created in your WeChat conversation list, leaving normal account usage unaffected.
+
+> You can find the bot at any time by searching for **"微信ClawBot"**. You may also rename it, change its avatar, pin it to the top of your conversation list, and so on.
+
+<img src="https://cdn.link-ai.tech/doc/83ae8251d896219fde4803f4205205be.jpg" width="250" />
+
+## 3. Login
+
+### QR code login
+
+On first startup, a QR code appears in the terminal (valid for around 2 minutes). Scan it with WeChat and confirm on your phone to log in.
+
+- The QR code refreshes automatically when it expires
+- The `qrcode` dependency is already included in `requirements.txt`, so the QR code renders directly in the terminal after install
+
+### Credential persistence
+
+After a successful login, credentials are saved to `~/.weixin_cow_credentials.json`. Subsequent startups reuse the saved credentials with no need to re-scan.
+
+To force a re-login, delete the credentials file and restart.
+
+### Session expiry
+
+When the WeChat session expires (errcode `-14`), CowAgent automatically clears old credentials and initiates a new QR login — no manual intervention required.
+
+## 4. Supported features
+
+| Feature | Status |
+| --- | --- |
+| Direct messages | ✅ |
+| Text messages | ✅ Send & Receive |
+| Image messages | ✅ Send & Receive |
+| File messages | ✅ Send & Receive |
+| Video messages | ✅ Send & Receive |
+| Voice messages | ✅ Receive (built-in speech recognition) |
diff --git a/docs/cli/general.mdx b/docs/cli/general.mdx
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--- /dev/null
+++ b/docs/cli/general.mdx
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+---
+title: General Commands
+description: View status, manage config, and control context with commonly used commands
+---
+
+The following commands can be used in chat with the `/` prefix or in the terminal with the `cow` prefix (some are chat-only).
+
+<Tip>
+  In the Web console, typing `/` brings up an autocomplete menu with keyboard navigation and Tab completion.
+</Tip>
+
+## help
+
+Show help information for all available commands.
+
+```text
+/help
+```
+
+## status
+
+View current session and service status, including process info, model configuration, message count, and loaded skills.
+
+```text
+/status
+```
+
+## cancel
+
+Abort the agent task currently running in this session. When the agent is busy with a long task (e.g. multi-turn tool calls or a long streaming response), send `/cancel` and the agent will stop before the next tool execution. Available across all channels — Web, WeChat, WeCom, Feishu, etc.
+
+```text
+/cancel
+```
+
+## config
+
+View or modify runtime configuration. Changes take effect immediately without restarting.
+
+**View all configurable items:**
+
+```text
+/config
+```
+
+**View a single item:**
+
+```text
+/config model
+```
+
+**Modify a config item:**
+
+```text
+/config model deepseek-v4-flash
+```
+
+**Configurable items:**
+
+| Item | Description | Example |
+| --- | --- | --- |
+| `model` | AI model name | `deepseek-v4-flash` |
+| `agent_max_context_tokens` | Max context tokens | `40000` |
+| `agent_max_context_turns` | Max context memory turns | `30` |
+| `agent_max_steps` | Max decision steps per task | `15` |
+| `enable_thinking` | Enable deep thinking mode | `true` / `false` |
+
+<Note>
+  When changing `model`, the system automatically matches the corresponding model API. Configuration is persisted to `config.json`.
+</Note>
+
+## context
+
+View current session context statistics, including message count and content length.
+
+```text
+/context
+```
+
+**Clear current session context:**
+
+```text
+/context clear
+```
+
+<Tip>
+  Clearing context makes the Agent "forget" previous conversation, useful for switching topics or freeing context space.
+</Tip>
+
+## logs
+
+View recent service logs. Shows the last 20 lines by default, up to 50.
+
+```text
+/logs
+```
+
+**Specify line count:**
+
+```text
+/logs 50
+```
+
+## version
+
+Show the current CowAgent version.
+
+```text
+/version
+```
diff --git a/docs/cli/index.mdx b/docs/cli/index.mdx
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--- /dev/null
+++ b/docs/cli/index.mdx
@@ -0,0 +1,96 @@
+---
+title: Commands Overview
+description: CowAgent command system — Terminal CLI and chat commands
+---
+
+CowAgent provides two ways to interact via commands:
+
+- **Terminal CLI** — Run `cow <command>` in your system terminal for service management, skill management, and other operations
+- **Chat Commands** — Type `/<command>` or `cow <command>` in any conversation to check status, manage skills, adjust configuration, etc.
+
+## Cow CLI
+
+After deploying with the one-click install script, the `cow` command is automatically available. For manual installations, run:
+
+```bash
+pip install -e .
+```
+
+Then use the `cow` command from anywhere:
+
+```bash
+cow help
+```
+
+Example output:
+
+```
+🐮 CowAgent CLI
+
+Usage: cow <command>
+
+Service:
+  start     Start the CowAgent service
+  stop      Stop the CowAgent service
+  restart   Restart the CowAgent service
+  update    Update code and restart service
+  status    Show service status
+  logs      View service logs
+
+Skills:
+  skill     Manage skills (list / search / install / uninstall ...)
+
+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
+Others:
+  help      Show this help message
+  version   Show version
+```
+
+## Chat Commands
+
+In the Web console or any connected channel, type `/` to see command suggestions. Supported commands:
+
+| Command | Description |
+| --- | --- |
+| `/help` | Show command help |
+| `/status` | View service status and configuration |
+| `/cancel` | Abort the currently running agent task |
+| `/config` | View or modify runtime configuration |
+| `/skill` | Manage skills (install, uninstall, enable, disable, etc.) |
+| `/memory dream [N]` | Manually trigger memory distillation (default 3 days, max 30) |
+| `/knowledge` | View knowledge base statistics |
+| `/knowledge list` | View knowledge base directory structure |
+| `/knowledge on\|off` | Enable or disable knowledge base |
+| `/context` | View current session context info |
+| `/context clear` | Clear current session context |
+| `/logs` | View recent logs |
+| `/version` | Show version number |
+
+<Tip>
+  Service management commands like `/start`, `/stop`, `/restart` will prompt you to use them in the terminal instead, as they involve process operations.
+</Tip>
+
+## Command Availability
+
+| Command | Terminal (`cow`) | Chat (`/`) |
+| --- | :---: | :---: |
+| help | ✓ | ✓ |
+| version | ✓ | ✓ |
+| status | ✓ | ✓ |
+| logs | ✓ | ✓ |
+| cancel | ✗ | ✓ |
+| config | ✗ | ✓ |
+| context | — | ✓ |
+| memory (subcommands) | ✗ | ✓ |
+| knowledge (subcommands) | ✓ | ✓ |
+| skill (subcommands) | ✓ | ✓ |
+| start / stop / restart | ✓ | ✗ |
+| update | ✓ | ✗ |
+| install-browser | ✓ | ✗ |
+
+<Note>
+  `context` only shows a hint in the terminal to use it in chat. `config` is only available in chat.
+</Note>
diff --git a/docs/cli/memory-knowledge.mdx b/docs/cli/memory-knowledge.mdx
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+++ b/docs/cli/memory-knowledge.mdx
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+---
+title: Memory & Knowledge
+description: Memory distillation and knowledge base management commands
+---
+
+## memory
+
+Manage the Agent's long-term memory system.
+
+### memory dream
+
+Manually trigger memory distillation (Deep Dream) — consolidate recent daily memories into MEMORY.md and generate a dream diary.
+
+```text
+/memory dream [N]
+```
+
+- `N`: Consolidate the last N days of memory (default 3, max 30)
+- Runs asynchronously in the background; you'll be notified in chat when complete
+- Works without Agent initialization — can be used before the first conversation
+
+**Examples:**
+
+```text
+/memory dream       # Consolidate last 3 days
+/memory dream 7     # Consolidate last 7 days
+/memory dream 30    # Consolidate last 30 days (full)
+```
+
+On the Web console, the completion notification includes clickable links to view the updated MEMORY.md and dream diary.
+
+<Tip>
+  The system automatically runs distillation daily at 23:55 (lookback 1 day). Manual trigger is useful for consolidating historical memories after first deployment, or when you need an immediate memory update.
+</Tip>
+
+## knowledge
+
+View and manage the personal knowledge base. Shows statistics by default.
+
+```text
+/knowledge
+```
+
+### knowledge list
+
+View the knowledge base directory tree.
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+Enable or disable the knowledge base. When disabled, knowledge prompts and file indexing are not injected.
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  In the terminal CLI, `cow knowledge` and `cow knowledge list` are available, but `on|off` is only supported in chat (requires runtime effect).
+</Note>
diff --git a/docs/cli/process.mdx b/docs/cli/process.mdx
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--- /dev/null
+++ b/docs/cli/process.mdx
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+---
+title: Process Management
+description: Manage CowAgent process lifecycle with cow commands
+---
+
+Process management commands control the CowAgent background process. These commands are only available in the terminal.
+
+## start
+
+Start the CowAgent service. Runs as a background daemon by default and automatically tails logs.
+
+```bash
+cow start
+```
+
+**Options:**
+
+| Option | Description |
+| --- | --- |
+| `-f`, `--foreground` | Run in foreground, not as a background daemon |
+| `--no-logs` | Don't tail logs after starting |
+
+## stop
+
+Stop the running CowAgent service.
+
+```bash
+cow stop
+```
+
+## restart
+
+Restart the CowAgent service (stop then start).
+
+```bash
+cow restart
+```
+
+**Options:**
+
+| Option | Description |
+| --- | --- |
+| `--no-logs` | Don't tail logs after restart |
+
+## update
+
+Update code and restart the service. Automatically performs:
+
+1. Pull latest code (`git pull`)
+2. Stop current service
+3. Update Python dependencies
+4. Reinstall CLI
+5. Start service
+
+```bash
+cow update
+```
+
+<Warning>
+  If `git pull` fails (e.g., uncommitted local changes), the update aborts and the service remains unaffected.
+</Warning>
+
+## status
+
+Check CowAgent service status, including process info, version, and current model/channel configuration.
+
+```bash
+cow status
+```
+
+## logs
+
+View service logs.
+
+```bash
+cow logs
+```
+
+**Options:**
+
+| Option | Description | Default |
+| --- | --- | --- |
+| `-f`, `--follow` | Continuously tail log output | No |
+| `-n`, `--lines` | Show last N lines | 50 |
+
+Examples:
+
+```bash
+# View last 100 lines
+cow logs -n 100
+
+# Continuously tail logs
+cow logs -f
+```
+
+## install-browser
+
+Install Playwright and Chromium browser for the [browser tool](/tools/browser).
+
+```bash
+cow install-browser
+```
+
+<Tip>
+  Only needed when using browser tools (web browsing, screenshots, etc.).
+</Tip>
+
+## run.sh Compatibility
+
+If Cow CLI is not installed, you can use `run.sh` to manage the service:
+
+| cow command | run.sh equivalent |
+| --- | --- |
+| `cow start` | `./run.sh start` |
+| `cow stop` | `./run.sh stop` |
+| `cow restart` | `./run.sh restart` |
+| `cow update` | `./run.sh update` |
+| `cow status` | `./run.sh status` |
+| `cow logs` | `./run.sh logs` |
+
+<Note>
+  The `cow` command is recommended — it provides cleaner syntax and richer features. It is automatically installed via the one-click install script.
+</Note>
diff --git a/docs/cli/skill.mdx b/docs/cli/skill.mdx
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--- /dev/null
+++ b/docs/cli/skill.mdx
@@ -0,0 +1,210 @@
+---
+title: Skill Management
+description: Install, uninstall, enable, disable, and manage skills via commands
+---
+
+Skill management commands are used to install, query, and manage CowAgent skills. Use `/skill <subcommand>` in chat or `cow skill <subcommand>` in the terminal.
+
+## list
+
+List installed skills and their status.
+
+<CodeGroup>
+```text Chat
+/skill list
+```
+
+```bash Terminal
+cow skill list
+```
+</CodeGroup>
+
+Example output:
+
+```
+📦 Installed skills (3/4)
+
+✅ pptx
+   Use this skill any time a .pptx file is involved…
+   Source: cowhub
+
+✅ skill-creator
+   Create, install, or update skills…
+   Source: builtin
+
+⏸️ image-vision (disabled)
+   Image understanding and visual analysis
+   Source: builtin
+```
+
+**Browse the Skill Hub** (view all available skills):
+
+<CodeGroup>
+```text Chat
+/skill list --remote
+```
+
+```bash Terminal
+cow skill list --remote
+```
+</CodeGroup>
+
+**Options:**
+
+| Option | Description | Default |
+| --- | --- | --- |
+| `--remote`, `-r` | Browse Skill Hub remote skill list | No |
+| `--page` | Page number for remote listing | 1 |
+
+## search
+
+Search for skills on the Skill Hub.
+
+<CodeGroup>
+```text Chat
+/skill search pptx
+```
+
+```bash Terminal
+cow skill search pptx
+```
+</CodeGroup>
+
+## install
+
+Install skills with a single `install` command from Cow Skill Hub, GitHub, ClawHub, or any URL (zip archives, SKILL.md links) — no manual download or configuration required.
+
+**From Skill Hub (recommended):**
+
+<CodeGroup>
+```text Chat
+/skill install pptx
+```
+
+```bash Terminal
+cow skill install pptx
+```
+</CodeGroup>
+
+**From GitHub:**
+
+<CodeGroup>
+```text Chat
+# Install all skills in a repo (auto-discovers subdirectories with SKILL.md)
+/skill install larksuite/cli
+
+# Specify a subdirectory to install a single skill
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# Use # to specify a subdirectory
+/skill install larksuite/cli#skills/lark-minutes
+```
+
+```bash Terminal
+# Install all skills in a repo (auto-discovers subdirectories with SKILL.md)
+cow skill install larksuite/cli
+
+# Specify a subdirectory to install a single skill
+cow skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# Use # to specify a subdirectory
+cow skill install larksuite/cli#skills/lark-minutes
+```
+</CodeGroup>
+
+Supports full GitHub URLs and `owner/repo` shorthand. For mono-repos (multiple skills in one repository), omitting the subdirectory auto-discovers and batch-installs all skills; specifying a subdirectory installs only that skill.
+
+**From ClawHub:**
+
+<CodeGroup>
+```text Chat
+/skill install clawhub:baidu-search
+```
+
+```bash Terminal
+cow skill install clawhub:baidu-search
+```
+</CodeGroup>
+
+**From URL:**
+
+<CodeGroup>
+```text Chat
+# Install from a zip archive (single or batch)
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# Install from a SKILL.md link
+/skill install https://example.com/path/to/SKILL.md
+```
+
+```bash Terminal
+# Install from a zip archive (single or batch)
+cow skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# Install from a SKILL.md link
+cow skill install https://example.com/path/to/SKILL.md
+```
+</CodeGroup>
+
+Supports installing from zip / tar.gz archive URLs — automatically extracts and discovers directories containing `SKILL.md`, with support for single or batch install. Also supports installing directly from a `SKILL.md` file URL, automatically parsing the skill name and description.
+
+## uninstall
+
+Uninstall an installed skill.
+
+<CodeGroup>
+```text Chat
+/skill uninstall pptx
+```
+
+```bash Terminal
+cow skill uninstall pptx
+```
+</CodeGroup>
+
+<Warning>
+  Uninstalling deletes all files in the skill directory. This action cannot be undone.
+</Warning>
+
+## enable / disable
+
+Enable or disable a skill. Disabled skills will not be invoked by the Agent.
+
+<CodeGroup>
+```text Chat
+/skill enable pptx
+/skill disable pptx
+```
+
+```bash Terminal
+cow skill enable pptx
+cow skill disable pptx
+```
+</CodeGroup>
+
+## info
+
+View details of an installed skill, including a preview of its `SKILL.md`.
+
+<CodeGroup>
+```text Chat
+/skill info pptx
+```
+
+```bash Terminal
+cow skill info pptx
+```
+</CodeGroup>
+
+## Skill Sources
+
+Installed skills track their origin, viewable via `/skill list`:
+
+| Source | Description |
+| --- | --- |
+| `builtin` | Built-in project skills |
+| `cowhub` | Installed from CowAgent Skill Hub |
+| `github` | Installed directly from a GitHub URL |
+| `clawhub` | Installed from ClawHub |
+| `url` | Installed from a SKILL.md URL |
+| `local` | Locally created skills |
diff --git a/docs/docs.json b/docs/docs.json
new file mode 100644
index 0000000..66a3769
--- /dev/null
+++ b/docs/docs.json
@@ -0,0 +1,737 @@
+{
+  "$schema": "https://mintlify.com/docs.json",
+  "name": "CowAgent",
+  "description": "CowAgent - AI Super Assistant powered by LLMs, with autonomous task planning, long-term memory, skills system, and multi-channel deployment.",
+  "theme": "mint",
+  "appearance": {
+    "default": "light"
+  },
+  "colors": {
+    "primary": "#35A85B",
+    "light": "#4ABE6E",
+    "dark": "#228547"
+  },
+  "logo": {
+    "light": "/images/logo.jpg",
+    "dark": "/images/logo.jpg"
+  },
+  "favicon": "/images/favicon.ico",
+  "navbar": {
+    "links": [
+      {
+        "label": "官网",
+        "href": "https://cowagent.ai/"
+      },
+      {
+        "label": "下载",
+        "href": "https://cowagent.ai/download/"
+      },
+      {
+        "label": "博客",
+        "href": "https://cowagent.ai/zh/blog/"
+      },
+      {
+        "label": "GitHub",
+        "href": "https://github.com/zhayujie/CowAgent"
+      }
+    ]
+  },
+  "footer": {
+    "socials": {
+      "github": "https://github.com/zhayujie/CowAgent"
+    }
+  },
+  "redirects": [
+    {
+      "source": "/en/:slug*",
+      "destination": "/:slug*",
+      "permanent": true
+    }
+  ],
+  "navigation": {
+    "languages": [
+      {
+        "language": "en",
+        "default": true,
+        "navbar": {
+          "links": [
+            {
+              "label": "Website",
+              "href": "https://cowagent.ai/"
+            },
+            {
+              "label": "Download",
+              "href": "https://cowagent.ai/download/"
+            },
+            {
+              "label": "Blog",
+              "href": "https://cowagent.ai/blog/"
+            },
+            {
+              "label": "GitHub",
+              "href": "https://github.com/zhayujie/CowAgent"
+            }
+          ]
+        },
+        "tabs": [
+          {
+            "tab": "Introduction",
+            "groups": [
+              {
+                "group": "Overview",
+                "pages": [
+                  "intro/index",
+                  "intro/architecture",
+                  "intro/features"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Get Started",
+            "groups": [
+              {
+                "group": "Installation",
+                "pages": [
+                  "guide/quick-start",
+                  "guide/desktop",
+                  "guide/manual-install",
+                  "guide/upgrade"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Models",
+            "groups": [
+              {
+                "group": "Model Configuration",
+                "pages": [
+                  "models/index",
+                  "models/deepseek",
+                  "models/claude",
+                  "models/gemini",
+                  "models/openai",
+                  "models/minimax",
+                  "models/glm",
+                  "models/qwen",
+                  "models/doubao",
+                  "models/kimi",
+                  "models/qianfan",
+                  "models/mimo",
+                  "models/linkai",
+                  "models/coding-plan",
+                  "models/custom"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Tools",
+            "groups": [
+              {
+                "group": "Tools System",
+                "pages": [
+                  "tools/index"
+                ]
+              },
+              {
+                "group": "Built-in Tools",
+                "pages": [
+                  "tools/read",
+                  "tools/write",
+                  "tools/edit",
+                  "tools/ls",
+                  "tools/bash",
+                  "tools/send",
+                  "tools/memory",
+                  "tools/env-config",
+                  "tools/web-fetch",
+                  "tools/scheduler"
+                ]
+              },
+              {
+                "group": "Optional Tools",
+                "pages": [
+                  "tools/web-search",
+                  "tools/vision",
+                  "tools/browser"
+                ]
+              },
+              {
+                "group": "MCP Tools",
+                "pages": [
+                  "tools/mcp"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Skills",
+            "groups": [
+              {
+                "group": "Skills System",
+                "pages": [
+                  "skills/index",
+                  "skills/install",
+                  "skills/create",
+                  "skills/hub"
+                ]
+              },
+              {
+                "group": "Built-in Skills",
+                "pages": [
+                  "skills/skill-creator",
+                  "skills/knowledge-wiki",
+                  "skills/image-generation"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Memory",
+            "groups": [
+              {
+                "group": "Memory System",
+                "pages": [
+                  "memory/index",
+                  "memory/context",
+                  "memory/deep-dream",
+                  "memory/self-evolution"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Knowledge",
+            "groups": [
+              {
+                "group": "Knowledge Base",
+                "pages": [
+                  "knowledge/index"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Channels",
+            "groups": [
+              {
+                "group": "Platforms",
+                "pages": [
+                  "channels/index",
+                  "channels/web",
+                  "channels/telegram",
+                  "channels/slack",
+                  "channels/discord",
+                  "channels/weixin",
+                  "channels/feishu",
+                  "channels/dingtalk",
+                  "channels/wecom-bot",
+                  "channels/qq",
+                  "channels/wecom",
+                  "channels/wechat-kf",
+                  "channels/wechatmp"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "CLI",
+            "groups": [
+              {
+                "group": "Command System",
+                "pages": [
+                  "cli/index",
+                  "cli/process",
+                  "cli/skill",
+                  "cli/memory-knowledge",
+                  "cli/general"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Releases",
+            "groups": [
+              {
+                "group": "Release Notes",
+                "pages": [
+                  "releases/overview",
+                  "releases/v2.1.3",
+                  "releases/v2.1.2",
+                  "releases/v2.1.1",
+                  "releases/v2.1.0",
+                  "releases/v2.0.9",
+                  "releases/v2.0.8",
+                  "releases/v2.0.7",
+                  "releases/v2.0.6",
+                  "releases/v2.0.5",
+                  "releases/v2.0.4",
+                  "releases/v2.0.3",
+                  "releases/v2.0.2",
+                  "releases/v2.0.1",
+                  "releases/v2.0.0"
+                ]
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "language": "zh",
+        "navbar": {
+          "links": [
+            {
+              "label": "官网",
+              "href": "https://cowagent.ai/?lang=zh"
+            },
+            {
+              "label": "下载",
+              "href": "https://cowagent.ai/zh/download/"
+            },
+            {
+              "label": "博客",
+              "href": "https://cowagent.ai/zh/blog/"
+            },
+            {
+              "label": "GitHub",
+              "href": "https://github.com/zhayujie/CowAgent"
+            }
+          ]
+        },
+        "tabs": [
+          {
+            "tab": "项目介绍",
+            "groups": [
+              {
+                "group": "概览",
+                "pages": [
+                  "zh/intro/index",
+                  "zh/intro/architecture",
+                  "zh/intro/features"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "快速开始",
+            "groups": [
+              {
+                "group": "安装部署",
+                "pages": [
+                  "zh/guide/quick-start",
+                  "zh/guide/desktop",
+                  "zh/guide/manual-install",
+                  "zh/guide/upgrade"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "模型",
+            "groups": [
+              {
+                "group": "模型配置",
+                "pages": [
+                  "zh/models/index",
+                  "zh/models/deepseek",
+                  "zh/models/minimax",
+                  "zh/models/claude",
+                  "zh/models/gemini",
+                  "zh/models/openai",
+                  "zh/models/glm",
+                  "zh/models/qwen",
+                  "zh/models/doubao",
+                  "zh/models/kimi",
+                  "zh/models/qianfan",
+                  "zh/models/mimo",
+                  "zh/models/linkai",
+                  "zh/models/coding-plan",
+                  "zh/models/custom"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "工具",
+            "groups": [
+              {
+                "group": "工具系统",
+                "pages": [
+                  "zh/tools/index"
+                ]
+              },
+              {
+                "group": "内置工具",
+                "pages": [
+                  "zh/tools/read",
+                  "zh/tools/write",
+                  "zh/tools/edit",
+                  "zh/tools/ls",
+                  "zh/tools/bash",
+                  "zh/tools/send",
+                  "zh/tools/memory",
+                  "zh/tools/env-config",
+                  "zh/tools/web-fetch",
+                  "zh/tools/scheduler"
+                ]
+              },
+              {
+                "group": "可选工具",
+                "pages": [
+                  "zh/tools/web-search",
+                  "zh/tools/vision",
+                  "zh/tools/browser"
+                ]
+              },
+              {
+                "group": "MCP 工具",
+                "pages": [
+                  "zh/tools/mcp"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "技能",
+            "groups": [
+              {
+                "group": "技能系统",
+                "pages": [
+                  "zh/skills/index",
+                  "zh/skills/install",
+                  "zh/skills/create",
+                  "zh/skills/hub"
+                ]
+              },
+              {
+                "group": "内置技能",
+                "pages": [
+                  "zh/skills/skill-creator",
+                  "zh/skills/knowledge-wiki",
+                  "zh/skills/image-generation"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "记忆",
+            "groups": [
+              {
+                "group": "记忆系统",
+                "pages": [
+                  "zh/memory/index",
+                  "zh/memory/context",
+                  "zh/memory/deep-dream",
+                  "zh/memory/self-evolution"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "知识",
+            "groups": [
+              {
+                "group": "知识库",
+                "pages": [
+                  "zh/knowledge/index"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "通道",
+            "groups": [
+              {
+                "group": "接入渠道",
+                "pages": [
+                  "zh/channels/index",
+                  "zh/channels/weixin",
+                  "zh/channels/web",
+                  "zh/channels/feishu",
+                  "zh/channels/dingtalk",
+                  "zh/channels/wecom-bot",
+                  "zh/channels/qq",
+                  "zh/channels/wecom",
+                  "zh/channels/wechat-kf",
+                  "zh/channels/wechatmp",
+                  "zh/channels/telegram",
+                  "zh/channels/slack",
+                  "zh/channels/discord"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "命令",
+            "groups": [
+              {
+                "group": "命令系统",
+                "pages": [
+                  "zh/cli/index",
+                  "zh/cli/process",
+                  "zh/cli/skill",
+                  "zh/cli/memory-knowledge",
+                  "zh/cli/general"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "版本",
+            "groups": [
+              {
+                "group": "发布记录",
+                "pages": [
+                  "zh/releases/overview",
+                  "zh/releases/v2.1.3",
+                  "zh/releases/v2.1.2",
+                  "zh/releases/v2.1.1",
+                  "zh/releases/v2.1.0",
+                  "zh/releases/v2.0.9",
+                  "zh/releases/v2.0.8",
+                  "zh/releases/v2.0.7",
+                  "zh/releases/v2.0.6",
+                  "zh/releases/v2.0.5",
+                  "zh/releases/v2.0.4",
+                  "zh/releases/v2.0.3",
+                  "zh/releases/v2.0.2",
+                  "zh/releases/v2.0.1",
+                  "zh/releases/v2.0.0"
+                ]
+              }
+            ]
+          }
+        ]
+      },
+      {
+        "language": "ja",
+        "navbar": {
+          "links": [
+            {
+              "label": "ウェブサイト",
+              "href": "https://cowagent.ai/"
+            },
+            {
+              "label": "ダウンロード",
+              "href": "https://cowagent.ai/download/"
+            },
+            {
+              "label": "ブログ",
+              "href": "https://cowagent.ai/blog/"
+            },
+            {
+              "label": "GitHub",
+              "href": "https://github.com/zhayujie/CowAgent"
+            }
+          ]
+        },
+        "tabs": [
+          {
+            "tab": "紹介",
+            "groups": [
+              {
+                "group": "概要",
+                "pages": [
+                  "ja/intro/index",
+                  "ja/intro/architecture",
+                  "ja/intro/features"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "クイックスタート",
+            "groups": [
+              {
+                "group": "インストール",
+                "pages": [
+                  "ja/guide/quick-start",
+                  "ja/guide/desktop",
+                  "ja/guide/manual-install",
+                  "ja/guide/upgrade"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "モデル",
+            "groups": [
+              {
+                "group": "モデル設定",
+                "pages": [
+                  "ja/models/index",
+                  "ja/models/deepseek",
+                  "ja/models/minimax",
+                  "ja/models/claude",
+                  "ja/models/gemini",
+                  "ja/models/openai",
+                  "ja/models/glm",
+                  "ja/models/qwen",
+                  "ja/models/doubao",
+                  "ja/models/kimi",
+                  "ja/models/qianfan",
+                  "ja/models/mimo",
+                  "ja/models/linkai",
+                  "ja/models/coding-plan",
+                  "ja/models/custom"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "ツール",
+            "groups": [
+              {
+                "group": "ツールシステム",
+                "pages": [
+                  "ja/tools/index"
+                ]
+              },
+              {
+                "group": "内蔵ツール",
+                "pages": [
+                  "ja/tools/read",
+                  "ja/tools/write",
+                  "ja/tools/edit",
+                  "ja/tools/ls",
+                  "ja/tools/bash",
+                  "ja/tools/send",
+                  "ja/tools/memory",
+                  "ja/tools/env-config",
+                  "ja/tools/web-fetch",
+                  "ja/tools/scheduler"
+                ]
+              },
+              {
+                "group": "オプションツール",
+                "pages": [
+                  "ja/tools/web-search",
+                  "ja/tools/vision",
+                  "ja/tools/browser"
+                ]
+              },
+              {
+                "group": "MCP Tool",
+                "pages": [
+                  "ja/tools/mcp"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "スキル",
+            "groups": [
+              {
+                "group": "スキルシステム",
+                "pages": [
+                  "ja/skills/index",
+                  "ja/skills/install",
+                  "ja/skills/create",
+                  "ja/skills/hub"
+                ]
+              },
+              {
+                "group": "内蔵スキル",
+                "pages": [
+                  "ja/skills/skill-creator",
+                  "ja/skills/knowledge-wiki",
+                  "ja/skills/image-generation"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "メモリ",
+            "groups": [
+              {
+                "group": "メモリシステム",
+                "pages": [
+                  "ja/memory/index",
+                  "ja/memory/context",
+                  "ja/memory/deep-dream",
+                  "ja/memory/self-evolution"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "ナレッジ",
+            "groups": [
+              {
+                "group": "ナレッジベース",
+                "pages": [
+                  "ja/knowledge/index"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "チャネル",
+            "groups": [
+              {
+                "group": "プラットフォーム",
+                "pages": [
+                  "ja/channels/index",
+                  "ja/channels/weixin",
+                  "ja/channels/web",
+                  "ja/channels/feishu",
+                  "ja/channels/dingtalk",
+                  "ja/channels/wecom-bot",
+                  "ja/channels/qq",
+                  "ja/channels/wecom",
+                  "ja/channels/wechat-kf",
+                  "ja/channels/wechatmp",
+                  "ja/channels/telegram",
+                  "ja/channels/slack",
+                  "ja/channels/discord"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "CLI",
+            "groups": [
+              {
+                "group": "コマンドシステム",
+                "pages": [
+                  "ja/cli/index",
+                  "ja/cli/process",
+                  "ja/cli/skill",
+                  "ja/cli/memory-knowledge",
+                  "ja/cli/general"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "リリース",
+            "groups": [
+              {
+                "group": "リリースノート",
+                "pages": [
+                  "ja/releases/overview",
+                  "ja/releases/v2.1.3",
+                  "ja/releases/v2.1.2",
+                  "ja/releases/v2.1.1",
+                  "ja/releases/v2.1.0",
+                  "ja/releases/v2.0.9",
+                  "ja/releases/v2.0.8",
+                  "ja/releases/v2.0.7",
+                  "ja/releases/v2.0.6",
+                  "ja/releases/v2.0.5",
+                  "ja/releases/v2.0.4",
+                  "ja/releases/v2.0.3",
+                  "ja/releases/v2.0.2",
+                  "ja/releases/v2.0.1",
+                  "ja/releases/v2.0.0"
+                ]
+              }
+            ]
+          }
+        ]
+      }
+    ]
+  }
+}
diff --git a/docs/guide/desktop.mdx b/docs/guide/desktop.mdx
new file mode 100644
index 0000000..607d699
--- /dev/null
+++ b/docs/guide/desktop.mdx
@@ -0,0 +1,51 @@
+---
+title: Desktop Client
+description: Download and use the CowAgent desktop client (macOS / Windows)
+---
+
+CowAgent ships a ready-to-use desktop client with the Agent runtime bundled in — **no need to install Python or dependencies manually**. Just download, install, and run your local super AI assistant.
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/desktop-chat-demo-en.png" alt="CowAgent Desktop client" />
+
+## Download & Install
+
+<Card title="Go to the download page" icon="download" href="https://cowagent.ai/download/">
+  Download the macOS / Windows installer
+</Card>
+
+<Tabs>
+  <Tab title="macOS">
+    1. Open the [download page](https://cowagent.ai/download/) and pick the build for your chip:
+       - Apple Silicon (M1/M2/M3/M4): download the `arm64` build
+       - Intel: download the `x64` build
+    2. Open the downloaded `.dmg` and drag CowAgent into your Applications folder.
+    3. Launch CowAgent from Launchpad or Applications.
+  </Tab>
+  <Tab title="Windows">
+    1. Open the [download page](https://cowagent.ai/download/) and download the Windows installer (`.exe`).
+    2. Run the installer and follow the prompts (you can choose the install directory).
+    3. Launch CowAgent from the desktop or Start menu.
+  </Tab>
+</Tabs>
+
+## Auto Update
+
+The desktop client has built-in auto-update. When a new version is available it is detected automatically; you can also manually "Check for updates" from the menu in the bottom-left corner and upgrade with one click.
+
+## Desktop vs. Command-line Deployment
+
+- **Desktop client**: best for personal use on your own computer — works out of the box, GUI-based, auto-updating.
+- **Command-line deployment**: best for developers or long-running servers with more customization. See [Quick Start](/guide/quick-start).
+
+## Access from a Browser
+
+Once the desktop client is running, it listens on port `9876` locally, and its backend is exactly the same Web console. So while the app is open you can also just point your browser at `http://localhost:9876` for the same full experience as the client UI.
+
+## Local Data Storage
+
+All data of the desktop client is stored on your machine:
+
+- **Config directory**: `~/.cow` in your home folder, holding `config.json` (model keys, channels, etc.) along with logs, cache and other runtime data.
+- **Workspace**: `~/cow` by default, holding chat history, knowledge base, memory, skills, scheduled tasks and other files produced by the Agent.
+
+Uninstalling the client does not delete these two directories, so your data is preserved across reinstalls. To fully clean up or migrate to another device, just back up or remove the corresponding folders manually.
diff --git a/docs/guide/manual-install.mdx b/docs/guide/manual-install.mdx
new file mode 100644
index 0000000..154f99a
--- /dev/null
+++ b/docs/guide/manual-install.mdx
@@ -0,0 +1,148 @@
+---
+title: Manual Install
+description: Deploy CowAgent manually (source code / Docker)
+---
+
+## Source Code Deployment
+
+### 1. Clone the project
+
+```bash
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
+```
+
+<Tip>
+  For network issues, use the mirror: https://gitee.com/zhayujie/CowAgent
+</Tip>
+
+### 2. Install dependencies
+
+Core dependencies (required):
+
+```bash
+pip3 install -r requirements.txt
+```
+
+Optional dependencies (recommended):
+
+```bash
+pip3 install -r requirements-optional.txt
+```
+
+### 3. Install Cow CLI
+
+Install the command-line tool for managing services and skills:
+
+```bash
+pip3 install -e .
+```
+
+Then use the `cow` command:
+
+```bash
+cow help
+```
+
+<Note>
+  This step is recommended. After installation you can use `cow start`, `cow stop`, `cow update` to manage the service, and `cow skill` to manage skills. Without the CLI, you can use `./run.sh` or `python3 app.py` to run.
+</Note>
+
+### 4. Configure
+
+Copy the config template and edit:
+
+```bash
+cp config-template.json config.json
+```
+
+Fill in model API keys, channel type, and other settings in `config.json`. See the [model docs](/models/index) for details.
+
+### 5. Run
+
+**Using Cow CLI (recommended):**
+
+```bash
+cow start
+```
+
+**Or run locally in foreground:**
+
+```bash
+python3 app.py
+```
+
+By default, the Web console starts. Access `http://localhost:9899` to chat.
+
+**Background run on server (without CLI):**
+
+```bash
+nohup python3 app.py & tail -f nohup.out
+```
+
+<Tip>
+  **Deploying on a server?** By default `web_host` only listens on `127.0.0.1` (local access). Set `web_host` to `0.0.0.0` in `config.json` to make the console reachable from outside, and set `web_password` to protect it. Don't forget to open port `9899` in your firewall or security group — ideally restricted to specific IPs.
+</Tip>
+
+## Docker Deployment
+
+Docker deployment does not require cloning source code or installing dependencies. For Agent mode, source deployment is recommended for broader system access.
+
+<Note>
+  Requires [Docker](https://docs.docker.com/engine/install/) and docker-compose.
+</Note>
+
+**1. Download config**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+```
+
+Edit `docker-compose.yml` with your configuration.
+
+**2. Start container**
+
+```bash
+sudo docker compose up -d
+```
+
+**3. View logs**
+
+```bash
+sudo docker logs -f chatgpt-on-wechat
+```
+
+<Tip>
+  **Running in Docker?** Set `WEB_HOST` to `0.0.0.0` in `docker-compose.yml` so the console is reachable from outside the container, and set `WEB_PASSWORD` to protect it. Make sure port `9899` is mapped to the host and open in your firewall or security group.
+</Tip>
+
+## Core Configuration
+
+```json
+{
+  "channel_type": "web",
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "",
+  "agent": true,
+  "agent_workspace": "~/cow",
+  "agent_max_context_tokens": 40000,
+  "agent_max_context_turns": 30,
+  "agent_max_steps": 15,
+  "cow_lang": "auto"
+}
+```
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `channel_type` | Channel type | `web` |
+| `model` | Model name | `deepseek-v4-flash` |
+| `agent` | Enable Agent mode | `true` |
+| `agent_workspace` | Agent workspace path | `~/cow` |
+| `agent_max_context_tokens` | Max context tokens | `40000` |
+| `agent_max_context_turns` | Max context turns | `30` |
+| `agent_max_steps` | Max decision steps per task | `15` |
+| `cow_lang` | Language for the UI, command text and system prompts; `auto` to detect, or set `zh` / `en` | `auto` |
+
+<Tip>
+  Full configuration options are in the project [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py).
+</Tip>
diff --git a/docs/guide/quick-start.mdx b/docs/guide/quick-start.mdx
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+---
+title: One-click Install
+description: One-click install and manage CowAgent with scripts
+---
+
+The project provides scripts for one-click install, configuration, startup, and management. Script-based deployment is recommended for quick setup.
+
+Supports Linux, macOS, and Windows. Requires Python 3.7-3.13 (3.9 recommended).
+
+## Install Command
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+The script automatically performs these steps:
+
+1. Check Python environment (requires Python 3.7+)
+2. Install required tools (git, curl, etc.)
+3. Clone project to `~/CowAgent`
+4. Install Python dependencies and Cow CLI
+5. Guided configuration for AI model and channel
+6. Start service
+
+By default, the Web console starts after installation. Access `http://localhost:9899` to begin chatting.
+
+<Note>
+  **Deploying on a server?** By default `web_host` only listens on `127.0.0.1` (local access only). Set `web_host` to `0.0.0.0` in `config.json` to make the console reachable from outside, and set `web_password` to protect it. Don't forget to open port `9899` in your firewall or security group — ideally restricted to specific IPs.
+</Note>
+
+## Management Commands
+
+After installation, use the `cow` command to manage the service:
+
+| Command | Description |
+| --- | --- |
+| `cow start` | Start service |
+| `cow stop` | Stop service |
+| `cow restart` | Restart service |
+| `cow status` | Check run status |
+| `cow logs` | View real-time logs |
+| `cow update` | Update code and restart |
+| `cow install-browser` | Install browser tool dependencies |
+
+See the [Commands documentation](/cli/index) for more details.
+
+<Note>
+  If the `cow` command is not available, you can use `./run.sh <command>` (Linux/macOS) or `.\scripts\run.ps1 <command>` (Windows) as a fallback. Both are functionally equivalent.
+</Note>
diff --git a/docs/guide/upgrade.mdx b/docs/guide/upgrade.mdx
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+++ b/docs/guide/upgrade.mdx
@@ -0,0 +1,67 @@
+---
+title: Upgrade
+description: How to upgrade CowAgent
+---
+
+## Recommended: One-line upgrade
+
+Use `cow update` to pull the latest code and restart the service in one step:
+
+```bash
+cow update
+```
+
+The command runs the following automatically:
+
+1. Pull the latest code (`git pull`)
+2. Stop the running service
+3. Update Python dependencies
+4. Reinstall the CLI
+5. Start the service
+
+<Note>
+  If the Cow CLI is not installed, `./run.sh update` performs the same operations.
+</Note>
+
+## Manual upgrade
+
+Run the following inside the project root:
+
+```bash
+git pull
+pip3 install -r requirements.txt
+pip3 install -e .
+```
+
+Then restart the service:
+
+```bash
+# Using Cow CLI (recommended)
+cow restart
+
+# Or using run.sh
+./run.sh restart
+
+# Or restart manually with nohup
+kill $(ps -ef | grep app.py | grep -v grep | awk '{print $2}')
+nohup python3 app.py & tail -f nohup.out
+```
+
+## Docker upgrade
+
+Run the following in the directory containing `docker-compose.yml`:
+
+```bash
+sudo docker compose pull
+sudo docker compose up -d
+```
+
+<Tip>
+  Back up `config.json` before upgrading. For Docker deployments, mount the workspace directory as a volume to persist data across upgrades.
+</Tip>
+
+## Desktop client upgrade
+
+The [desktop client](/guide/desktop) has built-in auto-update: it checks for new versions automatically and prompts you, so you can download and restart to upgrade in one click.
+
+You can also grab the latest version anytime from the [download page](https://cowagent.ai/download/).
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diff --git a/docs/intro/architecture.mdx b/docs/intro/architecture.mdx
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+---
+title: Architecture
+description: CowAgent 2.0 system architecture and core design
+---
+
+CowAgent 2.0 has evolved from a simple chatbot into a super intelligent assistant with Agent architecture, featuring autonomous thinking, task planning, long-term memory, and skill extensibility.
+
+## System Architecture
+
+CowAgent's architecture consists of the following core modules:
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/en/architecture.png" alt="CowAgent Architecture" />
+
+| Module | Description |
+| --- | --- |
+| **Plan** | Understands user intent, decomposes complex tasks into multi-step plans, and iteratively invokes tools until the goal is achieved |
+| **Memory** | Automatically persists important information as core memory and daily memory, with hybrid keyword and vector retrieval for cross-session context continuity |
+| **Knowledge** | Organizes structured knowledge by topic. The Agent autonomously distills valuable information into Markdown pages, maintaining indexes and cross-references to build a growing knowledge network |
+| **Evolution** | Reviews a conversation in an isolated environment after it goes idle, improving skills, following up on unfinished tasks, and backfilling memory and knowledge so the Agent keeps growing through everyday use |
+| **Tools** | Core capability for Agent to access OS resources. 10+ built-in tools including file read/write, terminal, browser, scheduler, memory search, web search, and more |
+| **Skills** | Loads and manages Skills. Supports one-click installation from Skill Hub, GitHub, and more, or custom skill creation through conversation |
+| **Models** | Model layer with unified access to OpenAI, Claude, Gemini, DeepSeek, MiniMax, GLM, Qwen, and other mainstream LLMs |
+| **Channels** | Message channel layer for receiving and sending messages. Supports Web console, WeChat, Feishu, DingTalk, WeCom, WeChat Official Account, and more with a unified protocol |
+| **CLI** | Command-line system providing terminal commands (`cow`) and chat commands (`/`) for process management, skill installation, configuration, knowledge base management, and more |
+
+## Agent Mode Workflow
+
+When Agent mode is enabled, CowAgent runs as an autonomous agent with the following workflow:
+
+1. **Receive Message** — Receive user input through channels
+2. **Understand Intent** — Analyze task requirements and context
+3. **Plan Task** — Break complex tasks into multiple steps
+4. **Invoke Tools** — Select and execute appropriate tools for each step
+5. **Update Memory & Knowledge** — Store important information in long-term memory and organize structured knowledge into the knowledge base
+6. **Return Result** — Send execution results back to the user
+
+## Workspace Directory Structure
+
+The Agent workspace is located at `~/cow` by default and stores system prompts, memory files, and skill files:
+
+```
+~/cow/
+├── SYSTEM.md          # Agent system prompt
+├── USER.md            # User profile
+├── MEMORY.md          # Core memory
+├── memory/            # Long-term memory storage
+│   └── YYYY-MM-DD.md  # Daily memory
+├── knowledge/         # Personal knowledge base
+│   ├── index.md       # Knowledge index
+│   └── <category>/    # Topic-based pages
+└── skills/            # Custom skills
+    ├── skill-1/
+    └── skill-2/
+```
+
+Secret keys are stored separately in `~/.cow` directory for security:
+
+```
+~/.cow/
+└── .env               # Secret keys for skills
+```
+
+## Core Configuration
+
+Configure Agent mode parameters in `config.json`:
+
+```json
+{
+  "agent": true,
+  "agent_workspace": "~/cow",
+  "agent_max_context_tokens": 50000,
+  "agent_max_context_turns": 20,
+  "agent_max_steps": 20,
+  "enable_thinking": false,
+  "cow_lang": "auto"
+}
+```
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `agent` | Enable Agent mode | `true` |
+| `agent_workspace` | Workspace path | `~/cow` |
+| `agent_max_context_tokens` | Max context tokens | `50000` |
+| `agent_max_context_turns` | Max context turns | `20` |
+| `agent_max_steps` | Max decision steps per task | `20` |
+| `enable_thinking` | Enable deep-thinking mode | `false` |
+| `knowledge` | Enable personal knowledge base | `true` |
+| `self_evolution_enabled` | Enable Self-Evolution (on by default for new installs) | `false` |
+| `cow_lang` | Language for the UI, command text and system prompts; `auto` to detect, or set `zh` / `en` | `auto` |
diff --git a/docs/intro/features.mdx b/docs/intro/features.mdx
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--- /dev/null
+++ b/docs/intro/features.mdx
@@ -0,0 +1,145 @@
+---
+title: Features
+description: CowAgent long-term memory, task planning, skills system, CLI commands, and browser tool in detail
+---
+
+## 1. Long-term Memory
+
+The memory system enables the Agent to remember important information over time, using a three-tier memory flow: conversation context (short-term) → daily memory (mid-term) → MEMORY.md (long-term), forming a complete memory lifecycle.
+
+On first launch, the Agent proactively asks the user for key information and records it in the workspace (default `~/cow`) — including agent settings, user identity, and memory files.
+
+In subsequent long-term conversations, the Agent intelligently stores or retrieves memory as needed, continuously updating its own settings, user preferences, and memory files. **Deep Dream** distillation runs daily, consolidating scattered daily memories into refined long-term memory and generating a narrative-style dream diary.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+Building on this, **Self-Evolution** lets the Agent keep growing through everyday use: after a conversation goes idle, it reviews it automatically to improve skills, follow up on unfinished tasks, and backfill memory and knowledge. It speaks up only when it actually made a change, and every change can be undone. Enabled by default for new installs.
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-demo.png" width="800" />
+</Frame>
+
+See [Long-term Memory](/memory), [Deep Dream](/memory/deep-dream), and [Self-Evolution](/memory/self-evolution) for details.
+
+## 2. Personal Knowledge Base
+
+> The knowledge base system enables the Agent to continuously accumulate and organize structured knowledge. Unlike memory which records along a timeline, the knowledge base is organized by topics, transforming articles, conversation insights, and learning materials into interconnected Markdown pages that form a continuously growing knowledge network.
+
+The Agent automatically organizes valuable information from conversations into knowledge pages, maintaining cross-references and indexes. The Web console provides document browsing and knowledge graph visualization. Knowledge is stored in `~/cow/knowledge/` within the workspace.
+
+- **Auto-organization**: The Agent autonomously extracts and organizes structured knowledge during conversations, maintaining indexes and cross-references
+- **Knowledge graph**: Automatically builds a knowledge graph from cross-references between pages, with interactive graph visualization in the Web console
+- **Chat integration**: Knowledge document links referenced in Agent replies can be clicked directly in the Web console for viewing
+- **CLI management**: Use `/knowledge` commands to view stats, browse directory, and toggle the feature with `/knowledge on|off`
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+See [Personal Knowledge Base](/knowledge) for details.
+
+## 3. Task Planning and Tool Use
+
+Tools are the core of how the Agent accesses operating system resources. The Agent intelligently selects and invokes tools based on task requirements, performing file read/write, command execution, scheduled tasks, and more. Built-in tools are implemented in the project's `agent/tools/` directory.
+
+**Key tools:** file read/write/edit, Bash terminal, browser, file send, scheduler, memory search, web search, environment config, and more.
+
+### 3.1 Terminal and File Access
+
+Access to the OS terminal and file system is the most fundamental and core capability. Many other tools and skills build on top of this. Users can interact with the Agent from a mobile device to operate resources on their personal computer or server:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+### 3.2 Programming Capability
+
+Combining programming and system access, the Agent can execute the complete **Vibecoding workflow** — from information search, asset generation, coding, testing, deployment, Nginx configuration, to publishing — all triggered by a single command from your phone:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
+</Frame>
+
+### 3.3 Scheduled Tasks
+
+The `scheduler` tool enables dynamic scheduled tasks, supporting **one-time tasks, fixed intervals, and Cron expressions**. Tasks can be triggered as either a **fixed message send** or an **Agent dynamic task** execution:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+### 3.4 Browser
+
+The built-in `browser` tool allows the Agent to control a Chromium browser to visit web pages, fill forms, click elements, and take screenshots, with support for dynamic JS-rendered pages. Run `cow install-browser` to install with one command, automatically adapting to server (headless) and desktop environments:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
+</Frame>
+
+### 3.5 Environment Variable Management
+
+Secrets required by skills are stored in an environment variable file, managed by the `env_config` tool. You can update secrets through conversation, with built-in security protection and desensitization:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
+
+## 4. Skills System
+
+The Skills system provides infinite extensibility for the Agent. Each Skill consists of a description file, execution scripts (optional), and resources (optional), describing how to complete specific types of tasks. Skills allow the Agent to follow instructions for complex workflows, invoke tools, or integrate third-party systems.
+
+- [Skill Hub](https://skills.cowagent.ai/): An open skill marketplace featuring official, community, and third-party skills. Install with one command.
+- **Built-in skills:** Located in the project's `skills/` directory, including skill creator, image recognition, LinkAI agent, web fetch, and more. Built-in skills are automatically enabled based on dependency conditions (API keys, system commands, etc.).
+- **Custom skills:** Created by users through conversation, stored in the workspace (`~/cow/skills/`), capable of implementing any complex business process or third-party integration.
+
+Install skills: `/skill install <name>` or `cow skill install <name>`, supporting Skill Hub, GitHub, ClawHub, URL, and more.
+
+### 4.1 Creating Skills
+
+The `skill-creator` skill enables rapid skill creation through conversation. You can ask the Agent to codify a workflow as a skill, or send any API documentation and examples for the Agent to complete the integration directly:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+### 4.2 Web Search and Image Recognition
+
+- **Web search:** Built-in `web_search` tool, supports multiple search engines. Configure `BOCHA_API_KEY` or `LINKAI_API_KEY` to enable.
+- **Image recognition:** Built-in `openai-image-vision` skill, supports `gpt-4.1-mini`, `gpt-4.1`, and other models. Requires `OPENAI_API_KEY`.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+### 4.3 Skill Hub
+
+Visit [skills.cowagent.ai](https://skills.cowagent.ai/) to browse all available skills, or use commands in conversation:
+
+```text
+/skill list --remote          # Browse Skill Hub
+/skill search <keyword>       # Search skills
+/skill install <name>          # Install with one command
+```
+
+Also supports installing skills from GitHub, ClawHub, LinkAI, and other third-party platforms. See [Install Skills](/skills/install) for details.
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+## 5. CLI Command System
+
+CowAgent provides two command interaction methods, covering service management, skill installation, configuration, and more:
+
+- **Terminal CLI:** Run `cow <command>` in the system terminal, supporting `start`, `stop`, `restart`, `update`, `status`, `logs`, `skill`, etc.
+- **Chat commands:** Type `/<command>` in conversation. The Web console shows a command menu when you type `/`.
+
+```bash
+cow start              # Start service
+cow stop               # Stop service
+cow update             # Update and restart
+cow skill install pptx # Install a skill
+cow install-browser    # Install browser tool
+```
+
+See [Command Overview](https://docs.cowagent.ai/en/cli) for details.
diff --git a/docs/intro/index.mdx b/docs/intro/index.mdx
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+++ b/docs/intro/index.mdx
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+---
+title: Introduction
+description: CowAgent - Open-source super AI assistant and Agent Harness
+---
+
+<div align="center">
+  <img src="https://cdn.link-ai.tech/doc/78c5dd674e2c828642ecc0406669fed7.png" alt="CowAgent" width="450px"/>
+</div>
+
+**CowAgent** is an open-source super AI assistant and Agent Harness. It proactively plans tasks, runs tools and skills, and autonomously grows with memory and knowledge.
+
+CowAgent is lightweight, easy to deploy, and built to extend. Plug in any major LLM provider, run it across Web and major IM platforms, 24/7 on a personal computer or server.
+
+<CardGroup cols={2}>
+  <Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
+    Open-source repository — Star and contribute
+  </Card>
+  <Card title="Try Online" icon="cloud" href="https://link-ai.tech/cowagent/create">
+    No setup required — experience CowAgent instantly
+  </Card>
+</CardGroup>
+
+## Core Capabilities
+
+<CardGroup cols={2}>
+  <Card title="Autonomous Task Planning" icon="brain" href="/intro/architecture">
+    Decomposes complex tasks and executes them step by step, looping over tools and skills until the goal is reached.
+  </Card>
+  <Card title="Long-term Memory" icon="database" href="/memory/index">
+    Three-tier architecture (context → daily → core), automatic Deep Dream distillation, hybrid keyword + vector retrieval.
+  </Card>
+  <Card title="Personal Knowledge Base" icon="book" href="/knowledge/index">
+    Auto-curates structured knowledge into a Markdown wiki, builds an evolving knowledge graph with visual browsing.
+  </Card>
+  <Card title="Self-Evolution" icon="seedling" href="/memory/self-evolution">
+    Reviews conversations automatically to improve skills, follow up on unfinished tasks, and consolidate memory and knowledge, growing through everyday use.
+  </Card>
+  <Card title="Skills System" icon="puzzle-piece" href="/skills/index">
+    A complete skill creation and execution engine. Install from Skill Hub or generate custom skills via natural-language conversation.
+  </Card>
+  <Card title="Multimodal Messaging" icon="image" href="/channels/web">
+    First-class support for text, images, voice, and files — recognition, generation, and delivery.
+  </Card>
+  <Card title="Tool System" icon="wrench" href="/tools/index">
+    Built-in file I/O, terminal, browser, scheduler, memory retrieval, web search, and more — with native MCP integration.
+  </Card>
+  <Card title="Command System" icon="terminal" href="/cli/index">
+    Terminal CLI and in-chat commands for process management, skill installation, configuration, and context inspection.
+  </Card>
+  <Card title="Pluggable Models" icon="microchip" href="/models/index">
+    Claude, GPT, Gemini, DeepSeek, Qwen, GLM, Kimi, MiniMax, Doubao, and more — swap providers from the Web console with one click.
+  </Card>
+  <Card title="Multi-channel Integration" icon="server" href="/channels/index">
+    A single Agent simultaneously serves Web, WeChat, Feishu, DingTalk, WeCom, QQ, and Official Accounts.
+  </Card>
+</CardGroup>
+
+## Quick Start
+
+Run one of the commands below to install, configure, and start CowAgent in a single step:
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+Once started, open `http://localhost:9899` to access the **Web console** — the unified place to chat, configure providers, connect channels, and install skills.
+
+<CardGroup cols={2}>
+  <Card title="Quick Start" icon="rocket" href="/guide/quick-start">
+    Complete installation and run guide
+  </Card>
+  <Card title="Architecture" icon="sitemap" href="/intro/architecture">
+    CowAgent system architecture
+  </Card>
+</CardGroup>
+
+## Disclaimer
+
+1. This project is licensed under the [MIT License](https://github.com/zhayujie/CowAgent/blob/master/LICENSE) and is intended for technical research and learning. You are responsible for complying with applicable laws and regulations in your jurisdiction; the maintainers assume no liability for any consequences arising from use of this project.
+2. **Cost & safety:** Agent mode consumes substantially more tokens than plain chat — pick models that balance quality and cost. The Agent has access to your local operating system; deploy only in trusted environments.
+3. CowAgent is a pure open-source project and does not participate in, authorize, or issue any cryptocurrency.
+
+## Community
+
+Scan the WeChat QR code to join the open-source community group:
+
+<img width="140" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png" />
diff --git a/docs/ja/README.md b/docs/ja/README.md
new file mode 100644
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--- /dev/null
+++ b/docs/ja/README.md
@@ -0,0 +1,279 @@
+<p align="center"><img src="https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="420" /></p>
+
+<p align="center">
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent?cacheSeconds=3600" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-green.svg" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square&cacheSeconds=3600" alt="Stars"></a>
+  <a href="https://docs.cowagent.ai/ja"><img src="https://img.shields.io/badge/%E3%83%89%E3%82%AD%E3%83%A5%E3%83%A1%E3%83%B3%E3%83%88-cowagent.ai-blue?style=flat&logo=readthedocs&logoColor=white" alt="ドキュメント"></a>
+</p>
+
+<p align="center">
+  <a href="https://trendshift.io/repositories/25763" target="_blank"><img src="https://trendshift.io/api/badge/repositories/25763" alt="zhayujie%2FCowAgent | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
+<p align="center">
+  [<a href="../../README.md">English</a>] | [<a href="../zh/README.md">中文</a>] | [日本語]
+</p>
+
+**CowAgent** は、自律的にタスクを計画し、コンピュータや外部リソースを操作し、Skill を作成・実行し、パーソナルナレッジベースと長期記憶を構築し、自己進化によってユーザーとともに成長するオープンソースのスーパー AI アシスタントです。エンドツーエンドの Agent Harness のリファレンス実装の一つでもあります。
+
+CowAgent は軽量でデプロイしやすく、拡張性に優れています。主要な LLM プロバイダーをそのまま組み込み、Web や主要な IM プラットフォーム上で動作。個人 PC やサーバー上で 24 時間 365 日稼働できます。
+
+<p align="center">
+  <a href="https://cowagent.ai/">🌐 ウェブサイト</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/ja/intro/index">📖 ドキュメント</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/ja/guide/quick-start">🚀 クイックスタート</a> &nbsp;·&nbsp;
+  <a href="https://skills.cowagent.ai/">🧩 Skill Hub</a> &nbsp;·&nbsp;
+  <a href="https://cowagent.ai/download/">💻 ダウンロード</a> &nbsp;·&nbsp;
+  <a href="https://link-ai.tech/cowagent/create">☁️ オンラインで試す</a>
+</p>
+
+<br/>
+
+## 🌟 主な機能
+
+| 機能 | 説明 |
+| :--- | :--- |
+| [タスク計画](https://docs.cowagent.ai/ja/intro/architecture) | 複雑なタスクを分解し、目標達成までツールを繰り返し呼び出して段階的に実行 |
+| [長期記憶](https://docs.cowagent.ai/ja/memory/index) | 三層構造（コンテキスト → デイリー → コア）、Deep Dream による自動蒸留、キーワードとベクトルのハイブリッド検索 |
+| [ナレッジベース](https://docs.cowagent.ai/ja/knowledge/index) | 構造化された知識を Markdown Wiki として自動整理し、進化し続けるナレッジグラフを可視化ブラウジング |
+| [自己進化](https://docs.cowagent.ai/ja/memory/self-evolution) | 会話を自動でレビューして Skill を改善し、未完了のタスクを引き継ぎ、記憶と知識を補完。日々の利用を通じて成長 |
+| [Skill](https://docs.cowagent.ai/ja/skills/index) | [Skill Hub](https://skills.cowagent.ai/)、GitHub、ClawHub からワンクリックでインストール；対話によるカスタム Skill 作成にも対応 |
+| [ツール](https://docs.cowagent.ai/ja/tools/index) | ファイル I/O、ターミナル、ブラウザ、スケジューラ、記憶検索、Web 検索など 10+ の組み込みツール — MCP プロトコルに完全対応 |
+| [チャネル](https://docs.cowagent.ai/ja/channels/index) | 一つの Agent で Web、WeChat、Feishu、DingTalk、WeCom、QQ、公式アカウント、Telegram、Slack を同時にサポート |
+| マルチモーダル | テキスト・画像・音声・ファイルをフルサポート — 認識・生成・双方向送受信 |
+| [モデル](https://docs.cowagent.ai/ja/models/index) | Claude、GPT、Gemini、DeepSeek、GLM、Qwen、Kimi、MiniMax、Doubao など、設定 1 行で切り替え可能 |
+| [デプロイ](https://docs.cowagent.ai/ja/guide/quick-start) | ワンラインインストーラー、統合された Web コンソール、複数のデプロイモード（ローカル / Docker / サーバー） |
+
+<br/>
+
+## 🏗️ アーキテクチャ
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/en/architecture.png" alt="CowAgent Architecture" width="750"/>
+
+CowAgent は完全な **Agent Harness** です：メッセージは各種**チャネル**から流入し、**Agent Core** が記憶・知識・利用可能なツール／Skill を組み合わせてタスクを計画・判断、**モデル**が応答を生成し、結果は元のチャネルに返されます。各レイヤーは疎結合で、独立して拡張可能です。
+
+詳細は [アーキテクチャ](https://docs.cowagent.ai/ja/intro/architecture) を参照してください。
+
+<br/>
+
+## 🚀 クイックスタート
+
+依存関係のインストール、設定、起動を自動で行うワンラインインストーラーを提供しています：
+
+**Linux / macOS:**
+
+```bash
+bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+```
+
+**Windows (PowerShell):**
+
+```powershell
+irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+```
+
+**Docker:**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+docker compose up -d
+```
+
+起動後、`http://localhost:9899` にアクセスして **Web コンソール**を開くと、モデル設定・チャネル接続・Skill インストールがすべてここで完結します。
+
+> サーバーデプロイでコンソールに公開アクセスする場合は、`config.json` の `web_host` を `0.0.0.0` に設定してください（あわせて `web_password` の設定も強く推奨）。その後 `http://<server-ip>:9899` にアクセスし、ファイアウォール／セキュリティグループで `9899` ポートを開放することも忘れずに。
+
+> 📖 詳細ガイド: [クイックスタート](https://docs.cowagent.ai/ja/guide/quick-start) · [ソースからインストール](https://docs.cowagent.ai/ja/guide/manual-install) · [アップグレード](https://docs.cowagent.ai/ja/guide/upgrade)
+
+インストール後は、[`cow` CLI](https://docs.cowagent.ai/ja/cli/index) でサービスを管理できます：
+
+```bash
+cow start | stop | restart        # サービス制御
+cow status | logs                  # ステータスとログ
+cow update                         # 最新コード取得後に再起動
+cow skill install <名前>           # Skill のインストール
+cow install-browser                # ブラウザツールのインストール
+```
+
+> 💻 デスクトップクライアント：**[CowAgent デスクトップクライアント](https://cowagent.ai/download/)**（macOS / Windows）はバックエンドを内蔵し、ダウンロードしてすぐに使えます。
+
+<br/>
+
+## 🤖 モデル
+
+CowAgent は主要な LLM プロバイダーすべてに対応しています。**チャット、画像認識、画像生成、ASR/TTS、埋め込み（Embedding）** の各機能はそれぞれ別のベンダーで設定可能です。
+
+| プロバイダー | 代表的なモデル | チャット | 画像認識 | 画像生成 | ASR | TTS | Embedding |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [Claude](https://docs.cowagent.ai/ja/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [OpenAI](https://docs.cowagent.ai/ja/models/openai) | gpt-5.5、o シリーズ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Gemini](https://docs.cowagent.ai/ja/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [DeepSeek](https://docs.cowagent.ai/ja/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [Qwen](https://docs.cowagent.ai/ja/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [GLM](https://docs.cowagent.ai/ja/models/glm) | glm-5.2、glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [Doubao](https://docs.cowagent.ai/ja/models/doubao) | doubao-seed-2.1 シリーズ | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](https://docs.cowagent.ai/ja/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [MiniMax](https://docs.cowagent.ai/ja/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [ERNIE](https://docs.cowagent.ai/ja/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [MiMo](https://docs.cowagent.ai/ja/models/mimo) | mimo-v2.5-pro / v2.5 | ✅ | ✅ | | | ✅ | |
+| [LinkAI](https://docs.cowagent.ai/ja/models/linkai) | 1 つの Key で 100+ モデルに接続 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [カスタム](https://docs.cowagent.ai/ja/models/custom) | ローカルモデル / サードパーティプロキシ | ✅ | | | | | |
+
+> Web コンソールでの設定が推奨されており、ファイルを手動編集する必要はありません。手動設定については各プロバイダーのドキュメントおよび [モデル概要](https://docs.cowagent.ai/ja/models/index) を参照してください。
+
+<br/>
+
+## 💬 チャネル
+
+一つの Agent インスタンスで複数のチャネルを同時に提供できます。`channel_type` 設定で切り替えるか、複数のチャネルを並列実行できます。
+
+| チャネル | テキスト | 画像 | ファイル | 音声 | グループ |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [Web コンソール](https://docs.cowagent.ai/ja/channels/web)（デフォルト） | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat](https://docs.cowagent.ai/ja/channels/weixin) | ✅ | ✅ | ✅ | ✅ | |
+| [Feishu / Lark](https://docs.cowagent.ai/ja/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [DingTalk](https://docs.cowagent.ai/ja/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [WeCom Bot](https://docs.cowagent.ai/ja/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](https://docs.cowagent.ai/ja/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [WeCom App](https://docs.cowagent.ai/ja/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat カスタマーサービス](https://docs.cowagent.ai/ja/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat 公式アカウント](https://docs.cowagent.ai/ja/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [Telegram](https://docs.cowagent.ai/ja/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](https://docs.cowagent.ai/ja/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](https://docs.cowagent.ai/ja/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+
+> Feishu と WeCom Bot は **Web コンソール内で QR コードをスキャンするだけで接続**できます — パブリック IP は不要です。詳細は [チャネル概要](https://docs.cowagent.ai/ja/channels/index) を参照してください。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-chat.png" alt="CowAgent Web Console" width="800"/>
+
+*Web コンソールはデフォルトのチャネルであると同時に、Agent の設定・管理を統一的に行う場でもあります。*
+
+<br/>
+
+## 🧠 記憶とナレッジベース
+
+**長期記憶**は三層構造：会話コンテキスト（短期）→ デイリー記憶（中期）→ MEMORY.md（長期）。毎晩の **Deep Dream** が散在する記憶を洗練された長期記憶とナラティブな日記に蒸留します。詳細は [長期記憶](https://docs.cowagent.ai/ja/memory/index) · [Deep Dream](https://docs.cowagent.ai/ja/memory/deep-dream) を参照してください。
+
+**パーソナルナレッジベース**は時系列の記憶とは異なり、構造化された知識を**トピック単位**で整理します。Agent が会話中に有用な情報を自動でキュレーションし、相互参照とインデックスを維持し、Web コンソールでナレッジグラフを可視化できます。詳細は [パーソナルナレッジベース](https://docs.cowagent.ai/ja/knowledge/index) を参照してください。
+
+<table>
+  <tr>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-memory.png" alt="長期記憶" />
+      <p align="center"><em>長期記憶 · 三層構造 + Deep Dream</em></p>
+    </td>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-knowledge.png" alt="パーソナルナレッジベース" />
+      <p align="center"><em>ナレッジベース · 自動キュレーションされた Markdown Wiki</em></p>
+    </td>
+  </tr>
+</table>
+
+<br/>
+
+## 🔧 ツールと Skill
+
+**ツール（Tools）** は Agent がシステムリソースを操作するためのアトミックな機能です。**Skill（Skills）** はマニフェストファイルで定義される高レベルのワークフローで、複数のツールを組み合わせて複雑なタスクを完了します。
+
+### ツールシステム
+
+**組み込みツール**には、ファイル I/O（`read` / `write` / `edit` / `ls`）、ターミナル（`bash`）、ファイル送信（`send`）、記憶検索（`memory`）、環境変数（`env_config`）、Web フェッチ（`web_fetch`）、スケジューラ（`scheduler`）、Web 検索（`web_search`）、画像認識（`vision`）、ブラウザ自動化（`browser`）などが含まれます。
+
+**MCP プロトコル**は [Model Context Protocol](https://modelcontextprotocol.io) のオープンエコシステムを統合します。`mcp.json` を一度設定すれば即利用可能で、stdio / SSE トランスポート、ホットリロード、ノーコード統合をサポートします。
+
+詳細: [ツール概要](https://docs.cowagent.ai/ja/tools/index) · [MCP 統合](https://docs.cowagent.ai/ja/tools/mcp)。
+
+### Skill システム
+
+- **[Skill Hub](https://skills.cowagent.ai/)** — オープン Skill マーケットプレイス：閲覧、検索、ワンクリックインストール
+- **GitHub / ClawHub / URL など** — 任意のソースからワンクリックでインストール
+- **対話による作成** — `skill-creator` を使って対話でカスタム Skill を生成；ワークフローやサードパーティ API を再利用可能な Skill に変換
+
+```bash
+/skill list                   # インストール済み Skill の一覧
+/skill search <キーワード>     # マーケットプレイスで検索
+/skill install <名前>          # ワンクリックインストール
+```
+
+詳細: [Skill 概要](https://docs.cowagent.ai/ja/skills/index) · [Skill 作成](https://docs.cowagent.ai/ja/skills/create)。
+
+<br/>
+
+## 🏷 更新履歴
+
+> **2026.07.08:** [v2.1.3](https://github.com/zhayujie/CowAgent/releases/tag/2.1.3) — [デスクトップクライアント](https://cowagent.ai/download/)（macOS / Windows）、ナレッジベースのドキュメント管理、MCP ツールのオンデマンド検索、繁体字中国語対応、新モデル追加。
+
+> **2026.06.18:** [v2.1.2](https://github.com/zhayujie/CowAgent/releases/tag/2.1.2) — Web コンソールの強化（定期タスク管理、ナレッジベースのカテゴリ、複数のカスタムモデルプロバイダー）、自己進化の改善、新モデル（kimi-k2.7-code、glm-5.2）、セキュリティ強化と改善。
+
+> **2026.06.09:** [v2.1.1](https://github.com/zhayujie/CowAgent/releases/tag/2.1.1) — 自己進化、Web コンソールの強化（メッセージ管理、マルチセッション並行）、クロスプラットフォーム対応の MCP 強化と並行呼び出し、新モデル（MiniMax-M3、qwen3.7-plus）、Python 3.13 対応。
+
+> **2026.06.01:** [v2.1.0](https://github.com/zhayujie/CowAgent/releases/tag/2.1.0) — 国際化対応、新チャネル（Telegram、Discord、Slack、WeChat カスタマーサービス）、CLI インタラクション強化、ワンライナーインストールの最適化、MCP Streamable HTTP 対応、新モデル（claude-opus-4-8、MiMo）。
+
+> **2026.05.22:** [v2.0.9](https://github.com/zhayujie/CowAgent/releases/tag/2.0.9) — モデル管理、MCP プロトコル対応、ブラウザセッション永続化、新モデル（gpt-5.5、gemini-3.5-flash、qwen3.7-max）、デプロイのセキュリティ強化。
+
+> **2026.05.06:** [v2.0.8](https://github.com/zhayujie/CowAgent/releases/tag/2.0.8) — Feishu チャネル全面アップグレード（音声、ストリーミング、QR 接続）、DeepSeek V4 と Baidu Qianfan 対応、スケジューラツール強化。
+
+> **2026.04.22:** [v2.0.7](https://github.com/zhayujie/CowAgent/releases/tag/2.0.7) — 組み込み画像生成（GPT Image 2、Nano Banana）、新モデル（Kimi K2.6、Claude Opus 4.7、GLM 5.1）、ナレッジベースと記憶の強化。
+
+> **2026.04.14:** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — ナレッジベース、Deep Dream 記憶蒸留、スマートコンテキスト圧縮、マルチセッション Web コンソール。
+
+> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI、Skill Hub オープンソース化、ブラウザツール、WeCom Bot QR 接続。
+
+> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — マルチステップタスク計画、長期記憶、Skill フレームワークを備えたスーパー Agent アシスタントへの全面アップグレード。
+
+完全な履歴: [リリースノート](https://docs.cowagent.ai/ja/releases/overview)
+
+<br/>
+
+## 🤝 コミュニティとサポート
+
+GitHub で [Issue を報告](https://github.com/zhayujie/CowAgent/issues) するか、下記 QR コードをスキャンして WeChat コミュニティに参加してください：
+
+<img width="130" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png">
+
+<br/>
+
+## 🔗 関連プロジェクト
+
+- **[Cow Skill Hub](https://github.com/zhayujie/cow-skill-hub)** — AI エージェント向けのオープン Skill マーケットプレイス；CowAgent、OpenClaw、Claude Code などに対応
+- **[bot-on-anything](https://github.com/zhayujie/bot-on-anything)** — 軽量な LLM アプリケーションフレームワーク；Slack、Telegram、Discord、Gmail などに対応
+- **[AgentMesh](https://github.com/MinimalFuture/AgentMesh)** — チーム協調による複雑な問題解決のためのオープンソースのマルチエージェントフレームワーク
+
+<br/>
+
+## 🏢 エンタープライズサービス
+
+[**LinkAI**](https://link-ai.tech/) は企業や開発者向けのワンストップ AI Agent プラットフォームで、CowAgent にマネージドホスティングとエンタープライズグレードのサポートを提供します：
+
+- **🚀 デプロイ不要のホスト型ランタイム** — [CowAgent オンラインアシスタント](https://link-ai.tech/cowagent/create) を 1 分以内に起動、サーバー不要
+- **🧠 Agent インフラ** — 主要 LLM・ナレッジベース・データベース・Skill・ワークフローへの統一アクセス。CowAgent の機能を拡張する、すぐに使えるビルディングブロック
+- **🏢 チーム & エンタープライズ機能** — ワークスペース、ロールベースのアクセス制御、監査ログ、本番運用向けプライベートデプロイ
+
+エンタープライズに関するお問い合わせ：**sales@simple-future.tech** または [QR コードをスキャン](https://cdn.link-ai.tech/consultant.jpg) して WeChat でお問い合わせください。
+
+<br/>
+
+## 🛠️ 開発とコントリビューション
+
+あらゆる形のコントリビューションを歓迎します —— 新機能、バグ修正、パフォーマンス改善、ドキュメント、あるいは [Skill Hub](https://skills.cowagent.ai/submit) への Skill の共有など。まずは [CONTRIBUTING.md](/CONTRIBUTING.md) をご覧いただき、Issue で相談するか、直接 PR を送ってください。
+
+⭐ Star でプロジェクトを応援し、Watch → Custom → Releases で新バージョンの通知を受け取れます。PR や Issue の提出も歓迎します。
+
+## 🌟 コントリビューター
+
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
+
+<br/>
+
+## ⚠️ 免責事項
+
+1. 本プロジェクトは [MIT License](/LICENSE) に基づき、技術研究と学習を目的としています。利用者は所在地の法令・規制を遵守する必要があり、本プロジェクトの利用に起因するいかなる結果についてもメンテナーは責任を負いません。
+2. **コストと安全性：** Agent モードは通常のチャットよりトークン消費が大幅に多いため、品質とコストのバランスを考慮してモデルを選択してください。Agent はローカル OS にアクセスできるため、信頼できる環境にのみデプロイしてください。
+3. CowAgent は純粋なオープンソースプロジェクトであり、暗号通貨の発行・参加・承認は一切行いません。
+
+<br/>
+
+## 📌 プロジェクト改名のお知らせ
+
+本プロジェクトは旧名 `chatgpt-on-wechat` から、2026.04.13 に **CowAgent** へ正式に改名されました。元の GitHub URL は自動的にリダイレクトされます。既存ユーザーは `git remote set-url origin https://github.com/zhayujie/CowAgent.git` でローカルのリモートを更新できます。
diff --git a/docs/ja/channels/dingtalk.mdx b/docs/ja/channels/dingtalk.mdx
new file mode 100644
index 0000000..2926e49
--- /dev/null
+++ b/docs/ja/channels/dingtalk.mdx
@@ -0,0 +1,58 @@
+---
+title: DingTalk
+description: CowAgent を DingTalk アプリケーションに統合する
+---
+
+DingTalk オープンプラットフォームでインテリジェントロボットアプリを作成して、CowAgent を DingTalk に統合します。
+
+## 1. アプリの作成
+
+1. [DingTalk 開発者コンソール](https://open-dev.dingtalk.com/fe/app#/corp/app)にアクセスし、ログインして**アプリを作成**をクリックし、アプリ情報を入力します：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-create-app.png" width="800"/>
+
+2. **アプリ機能の追加**をクリックし、**ロボット**機能を選択して**追加**をクリックします：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-add-bot.png" width="800"/>
+
+3. ロボット情報を設定し、**公開**をクリックします。公開後、「**デバッグ**」をクリックすると自動的にテストグループチャットが作成され、クライアントで確認できます：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-config-bot.png" width="600"/>
+
+4. **バージョン管理とリリース**をクリックし、新しいバージョンを作成して公開します：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-publish-bot.png" width="700"/>
+
+## 2. プロジェクト設定
+
+1. **認証情報と基本情報**をクリックし、`Client ID` と `Client Secret` を取得します：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-get-secret.png" width="700"/>
+
+2. プロジェクトルートの `config.json` に以下の設定を追加します：
+
+```json
+{
+  "channel_type": "dingtalk",
+  "dingtalk_client_id": "YOUR_CLIENT_ID",
+  "dingtalk_client_secret": "YOUR_CLIENT_SECRET"
+}
+```
+
+3. 依存パッケージをインストールします：
+
+```bash
+pip3 install dingtalk_stream
+```
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-app-config.png" width="700"/>
+
+4. プロジェクト起動後、DingTalk 開発者コンソールに移動し、**イベントサブスクリプション**をクリックし、**接続確認済み、チャネルを確認**をクリックします。「**接続成功**」と表示されれば設定完了です：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-event-sub.png" width="700"/>
+
+## 3. 使い方
+
+ロボットと個別チャットするか、企業グループに追加して会話を開始します：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-hosting-demo.png" width="650"/>
diff --git a/docs/ja/channels/discord.mdx b/docs/ja/channels/discord.mdx
new file mode 100644
index 0000000..06c80d6
--- /dev/null
+++ b/docs/ja/channels/discord.mdx
@@ -0,0 +1,93 @@
+---
+title: Discord
+description: Discord Bot 経由で CowAgent を接続
+---
+
+> Discord Bot の **Gateway 常時接続** を通じて CowAgent を接続します。ダイレクトメッセージ（DM）およびサーバーチャンネル（@メンションまたはボットへの返信で起動）に対応。Gateway は WebSocket の常時接続を使うため公開 IP やコールバック URL は不要で、すぐに利用できます。
+
+## 1. 接続手順
+
+### ステップ 1: Discord アプリと Bot を作成
+
+1. [Discord 開発者ポータル](https://discord.com/developers/applications) を開き、**New Application** をクリックして名前（例: `CowAgent`）を入力し作成します。
+2. 左メニューの **Bot** ページで **Reset Token** をクリックして Bot Token を生成し、コピーして安全に保管します（一度だけ表示されます）。
+
+<Tip>
+  この Token は Bot のパスワードに相当します。漏洩しないようにしてください。万一漏洩した場合は Bot ページで再度 **Reset Token** をクリックして再生成できます。
+</Tip>
+
+### ステップ 2: Message Content Intent を有効化
+
+DM・チャンネルいずれもテキスト読み取りにこの権限が必要です。
+
+1. **Bot** ページの **Privileged Gateway Intents** を探します。
+2. **Message Content Intent** をオンにして保存します。
+
+<Note>
+  この権限を有効にしないと、受信メッセージの本文が空になり、ボットが応答しません。
+</Note>
+
+### ステップ 3: Bot をサーバーに招待
+
+1. 左メニューの **OAuth2 → URL Generator** を開きます。
+2. **Scopes** で `bot` をチェックします。
+3. **Bot Permissions** で最低限以下をチェックします: `Send Messages`、`Read Message History`、`Attach Files`、`View Channels`。
+4. 下部に生成された認証 URL をコピーしてブラウザで開き、対象のサーバーを選択して認証を完了します。
+
+<Note>
+  DM のみを利用する場合はこのステップを省略できますが、ボットとの DM チャンネルが必要です（ユーザーがボットに直接メッセージを送るなど）。
+</Note>
+
+### ステップ 4: CowAgent に接続
+
+<Tabs>
+  <Tab title="Web コンソール（推奨）">
+    Web コンソール（既定 `http://127.0.0.1:9899`）を開き、**チャネル** メニュー → **チャネルを追加** → **Discord** を選択し、Bot Token を貼り付けて接続をクリックします。
+  </Tab>
+  <Tab title="設定ファイル">
+    `config.json` に以下を追加して Cow を起動します:
+
+    ```json
+    {
+      "channel_type": "discord",
+      "discord_token": "your-discord-bot-token",
+      "discord_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | パラメータ | 説明 | 既定値 |
+    | --- | --- | --- |
+    | `discord_token` | 開発者ポータルの Bot ページで生成した Bot Token | - |
+    | `discord_group_trigger` | チャンネルのトリガー方式: `mention_or_reply`（@ またはボットへの返信）/ `mention_only`（@ のみ）/ `all`（全メッセージ） | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+ログに以下のような出力が表示されれば接続成功です:
+
+```
+[Discord] Bot logged in as CowAgent#1234 (id=123456789)
+[Discord] ✅ Discord bot ready, listening for messages
+```
+
+## 2. 機能
+
+| 機能 | 対応状況 |
+| --- | --- |
+| ダイレクトメッセージ（DM） | ✅ |
+| サーバーチャンネル（@bot / ボットへの返信） | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| ファイルメッセージ | ✅ 送受信（PDF / Word / Excel など） |
+
+<Note>
+  Discord の 1 メッセージは最大 2000 文字です。長い返信は改行単位で自動的に複数メッセージに分割して送信されます。
+</Note>
+
+## 3. 使い方
+
+接続が完了したら:
+
+- **ダイレクトメッセージ（DM）**: サーバーのメンバー一覧からボットを見つけ、アイコンをクリックして直接メッセージを送ります。
+- **チャンネル**: ボットを招待したチャンネルで、`@your-bot こんにちは` または **ボットのメッセージへの返信** で起動します。
+
+画像やファイルを送るときは、添付の入力欄に **テキスト説明**（説明・質問）を書いて一緒に送信できます。Bot は添付ファイルと説明を合わせて回答します。先に添付を送り、その後に質問を送る形でも、2 つのメッセージは自動でまとめて処理されます。
diff --git a/docs/ja/channels/feishu.mdx b/docs/ja/channels/feishu.mdx
new file mode 100644
index 0000000..d703954
--- /dev/null
+++ b/docs/ja/channels/feishu.mdx
@@ -0,0 +1,107 @@
+---
+title: Feishu (Lark)
+description: 企業向けカスタムアプリで CowAgent を Feishu に接続
+---
+
+> 飛書（Feishu）の企業向けカスタムアプリを通じて CowAgent を接続。1 対 1 チャット、グループチャット（@メンション）に対応。WebSocket 長接続を使用するため公開 IP 不要、ストリーミングのタイプライター応答や音声メッセージにも対応します。
+
+<Note>
+  接続には管理者権限を持つ Feishu 企業ユーザーが必要です。
+</Note>
+
+## 1. 接続方法
+
+### 方式 1: ワンクリック作成（推奨）
+
+事前に Feishu 開発者プラットフォームでアプリを作成する必要はありません。Cow を起動後、Web コンソール（既定 `http://127.0.0.1:9899/`）を開き、**チャネル** メニュー → **チャネルを追加** → **Feishu** を選択し、**QR スキャン** タブで **ワンクリックで Feishu アプリを作成** をクリック。**Feishu アプリ** で QR コードをスキャンするとアプリ作成と接続が自動完了します。
+
+<Note>
+  作成されたアプリには必要な権限（メッセージ送受信、カード読み書き、グループイベントなど）とイベント購読がすべて事前設定されています。現在は Feishu 中国版のみ対応で、Lark 国際版は未対応です。
+</Note>
+
+CLI から `feishu_app_id` 未設定で起動した場合は、ターミナルにも QR コードが表示されます。
+
+### 方式 2: 手動作成
+
+Feishu 開発者プラットフォームで自分でアプリを作成し、Web コンソールまたは設定ファイルから接続します。
+
+**ステップ 1: アプリ作成**
+
+1. [Feishu 開発者プラットフォーム](https://open.feishu.cn/app/) にアクセスし、**企業カスタムアプリを作成** をクリック:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-create-app.jpg" width="500"/>
+
+2. **アプリ機能の追加** で **Bot** 機能を追加:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-add-bot.jpg" width="800"/>
+
+3. **権限管理** で以下の権限を貼り付け、全選択して **一括有効化**:
+
+```
+im:message,im:message.group_at_msg,im:message.group_at_msg:readonly,im:message.p2p_msg,im:message.p2p_msg:readonly,im:message:send_as_bot,im:resource,cardkit:card:write
+```
+
+<img src="https://cdn.link-ai.tech/doc/feishu-hosting-add-auth2.png" width="800"/>
+
+4. **認証情報と基本情報** から `App ID` と `App Secret` を取得:
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-appid-secret.jpg" width="800"/>
+
+**ステップ 2: CowAgent に接続**
+
+<Tabs>
+  <Tab title="Web コンソール">
+    Web コンソールから **チャネル** → **チャネルを追加** → **Feishu** → **手動入力** タブに切り替え、App ID と App Secret を入力して接続。
+  </Tab>
+  <Tab title="設定ファイル">
+    `config.json` に以下を追加して起動:
+
+    ```json
+    {
+      "channel_type": "feishu",
+      "feishu_app_id": "YOUR_APP_ID",
+      "feishu_app_secret": "YOUR_APP_SECRET",
+      "feishu_stream_reply": true
+    }
+    ```
+
+    | パラメータ | 説明 | デフォルト |
+    | --- | --- | --- |
+    | `feishu_app_id` | Feishu アプリの App ID | - |
+    | `feishu_app_secret` | Feishu アプリの App Secret | - |
+    | `feishu_stream_reply` | ストリーミングタイプライター応答を有効化 | `true` |
+  </Tab>
+</Tabs>
+
+**ステップ 3: アプリの公開**
+
+1. Cow 起動後、Feishu 開発者プラットフォームの **イベントとコールバック** で **ロングコネクション** モードを選択して保存:
+
+<img src="https://cdn.link-ai.tech/doc/202601311731183.png" width="600"/>
+
+2. **イベントを追加** で「メッセージ受信」を検索し、**メッセージ受信 v2.0** を選択。
+
+3. **バージョン管理とリリース** で新バージョンを作成し **本番リリース** を申請、Feishu クライアントで承認:
+
+<img src="https://cdn.link-ai.tech/doc/202601311807356.png" width="600"/>
+
+## 2. 機能一覧
+
+| 機能 | 対応状況 |
+| --- | --- |
+| 1 対 1 チャット | ✅ |
+| グループチャット（@Bot） | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| 音声メッセージ | ✅ 送受信 |
+| ストリーミング応答 | ✅（Feishu cardkit ストリーミングカードベース） |
+
+<Note>
+  ストリーミング応答には `cardkit:card:write` 権限（ワンクリック作成では自動付与）と Feishu クライアント 7.20 以上が必要です。古いクライアントではアップグレード案内が表示され、権限/バージョン未充足時は通常テキスト応答に自動フォールバックします。
+</Note>
+
+## 3. 使い方
+
+接続完了後、Feishu で Bot 名を検索してチャットを開始できます。
+
+グループで使う場合は Bot をグループに追加し、@メンションでメッセージを送ってください。
diff --git a/docs/ja/channels/index.mdx b/docs/ja/channels/index.mdx
new file mode 100644
index 0000000..c86d198
--- /dev/null
+++ b/docs/ja/channels/index.mdx
@@ -0,0 +1,46 @@
+---
+title: チャネル一覧
+description: CowAgent が対応するチャネルと機能マトリクス
+---
+
+CowAgent は複数のチャットチャネルへの接続に対応しており、起動時に `channel_type` で切り替えます。Web コンソールはデフォルトで有効で、他の接続チャネルと並行して動作します。
+
+## 機能マトリクス
+
+下表は各チャネルが対応する受信メッセージタイプ、ボットの返信タイプ、グループチャット機能をまとめたものです。シーンに合わせて選択してください。
+
+| チャネル | テキスト | 画像 | ファイル | 音声 | グループチャット |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [Telegram](/ja/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](/ja/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](/ja/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+| [WeChat](/ja/channels/weixin) | ✅ | ✅ | ✅ | ✅ |  |
+| [Web コンソール](/ja/channels/web) | ✅ | ✅ | ✅ | ✅ | |
+| [Feishu](/ja/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [DingTalk](/ja/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [WeCom スマートボット](/ja/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](/ja/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [WeCom アプリ](/ja/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [WeChat 公式アカウント](/ja/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [WeChat カスタマーサービス](/ja/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+
+- **画像 / ファイル / 音声**列は対応するメッセージタイプの送受信に対応していることを示します。詳細は各チャネルのドキュメントを参照してください
+- **グループチャット**列はグループメッセージを認識して応答できることを示します
+
+<Tip>
+  各チャネルの音声 / 画像機能は、対応するモデルプロバイダーの設定に依存します。詳細は [モデル一覧](/ja/models) を参照してください。
+</Tip>
+
+## チャネル一覧
+
+- [Web コンソール](/ja/channels/web) — 組み込みのブラウザ対話・管理パネル、デフォルトで有効
+- [WeChat](/ja/channels/weixin) — 個人 WeChat の QR コードログイン
+- [Feishu](/ja/channels/feishu) — Feishu 自作ボット
+- [DingTalk](/ja/channels/dingtalk) — DingTalk 自作ボット
+- [WeCom スマートボット](/ja/channels/wecom-bot) — WeCom スマートボット
+- [QQ](/ja/channels/qq) — QQ 公式ボットオープンプラットフォーム
+- [WeCom アプリ](/ja/channels/wecom) — WeCom 自作アプリ接続
+- [WeChat 公式アカウント](/ja/channels/wechatmp) — WeChat 公式アカウント（購読アカウント / サービスアカウント）
+- [Telegram](/ja/channels/telegram) — グローバル IM、5 分で接続、公開 IP 不要
+- [Slack](/ja/channels/slack) — チームコラボレーション IM、Socket Mode 接続、公開 IP 不要
+- [Discord](/ja/channels/discord) — コミュニティ IM、Gateway 接続、公開 IP 不要
diff --git a/docs/ja/channels/qq.mdx b/docs/ja/channels/qq.mdx
new file mode 100644
index 0000000..57e950f
--- /dev/null
+++ b/docs/ja/channels/qq.mdx
@@ -0,0 +1,88 @@
+---
+title: QQ Bot
+description: CowAgent を QQ Bot に接続する（WebSocket ロングコネクション）
+---
+
+> QQ オープンプラットフォームの Bot API を介して CowAgent を接続し、QQ のダイレクトメッセージ、グループチャット（@bot）、ギルドチャネルメッセージ、ギルド DM に対応します。パブリック IP は不要で、WebSocket ロングコネクションを使用します。
+
+<Note>
+  QQ Bot は QQ オープンプラットフォームを通じて作成します。WebSocket ロングコネクションでメッセージを受信し、OpenAPI でメッセージを送信します。パブリック IP やドメインは不要です。
+</Note>
+
+## 1. QQ Bot の作成
+
+> [QQ オープンプラットフォーム](https://q.qq.com)にアクセスし、QQ でサインインします。未登録の場合は、先に[アカウント登録](https://q.qq.com/#/register)を完了してください。
+
+1.[QQ オープンプラットフォーム - Bot 一覧](https://q.qq.com/#/apps)に移動し、**Bot を作成**をクリックします：
+
+<img src="https://cdn.link-ai.tech/doc/20260317162900.png" width="800"/>
+
+2.Bot 名、アバター、その他の基本情報を入力して作成を完了します：
+
+<img src="https://cdn.link-ai.tech/doc/20260317163005.png" width="800"/>
+
+3.Bot 設定ページに入り、**開発管理**に移動して以下の手順を完了します：
+
+  - **AppID**（Bot ID）をコピーして保存します
+  - **AppSecret**（Bot Secret）を生成して保存します
+
+<img src="https://cdn.link-ai.tech/doc/20260317164955.png" width="800"/>
+
+## 2. 設定と起動
+
+### 方法 A: Web コンソール
+
+プログラムを起動し、Web コンソール（ローカルアクセス: http://127.0.0.1:9899/）を開きます。**チャネル**タブに移動し、**チャネルを接続**をクリックして **QQ Bot** を選択し、前のステップで取得した AppID と AppSecret を入力して接続をクリックします。
+
+<img src="https://cdn.link-ai.tech/doc/20260317165425.png" width="800"/>
+
+### 方法 B: 設定ファイル
+
+`config.json` に以下を追加します：
+
+```json
+{
+  "channel_type": "qq",
+  "qq_app_id": "YOUR_APP_ID",
+  "qq_app_secret": "YOUR_APP_SECRET"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `qq_app_id` | QQ Bot の AppID。オープンプラットフォームの開発管理で確認できます |
+| `qq_app_secret` | QQ Bot の AppSecret。オープンプラットフォームの開発管理で確認できます |
+
+設定後、プログラムを起動します。ログに `[QQ] ✅ Connected successfully` と表示されれば接続成功です。
+
+
+## 3. 使い方
+
+QQ オープンプラットフォームで、**管理 → 利用範囲とメンバー**に移動し、「グループとメッセージリストに追加」の QR コードを QQ クライアントでスキャンして Bot とのチャットを開始します：
+
+<img src="https://cdn.link-ai.tech/doc/20260317165947.png" width="800"/>
+
+チャット例:
+<img src="https://cdn.link-ai.tech/doc/20260317171508.png" width="800"/>
+
+## 4. 対応機能
+
+> 注意: グループチャットやギルドチャネルで QQ Bot を使用するには、公開審査を完了し、利用範囲の権限を設定する必要があります。
+
+| 機能 | 状態 |
+| --- | --- |
+| QQ ダイレクトメッセージ | ✅ |
+| QQ グループチャット（@bot） | ✅ |
+| ギルドチャネル（@bot） | ✅ |
+| ギルド DM | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信（グループ・ダイレクト） |
+| ファイルメッセージ | ✅ 送信（グループ・ダイレクト） |
+| スケジュールタスク | ✅ 能動的プッシュ（ユーザーあたり月4回） |
+
+
+## 5. 注意事項
+
+- **受動メッセージの制限**: QQ ダイレクトメッセージの返信は60分間有効です（1メッセージあたり最大5回返信可能）。グループチャットの返信は5分間有効です。
+- **能動メッセージの制限**: ダイレクトメッセージとグループチャットの両方で、月あたりの能動メッセージは4件までです。スケジュールタスク機能を使用する際はこの点にご注意ください。
+- **イベント権限**: デフォルトでは `GROUP_AND_C2C_EVENT`（QQ グループ/ダイレクト）と `PUBLIC_GUILD_MESSAGES`（ギルド公開メッセージ）がサブスクライブされています。追加の権限が必要な場合は、オープンプラットフォームで申請してください。
diff --git a/docs/ja/channels/slack.mdx b/docs/ja/channels/slack.mdx
new file mode 100644
index 0000000..d871bd0
--- /dev/null
+++ b/docs/ja/channels/slack.mdx
@@ -0,0 +1,118 @@
+---
+title: Slack
+description: Slack App 経由で CowAgent を接続
+---
+
+> Slack App の **Socket Mode** を通じて CowAgent を接続します。ダイレクトメッセージ（DM）およびチャンネル（@メンションまたはスレッド内の返信で起動）に対応。Socket Mode は WebSocket の常時接続を使うため公開 IP やコールバック URL は不要で、すぐに利用できます。
+
+## 1. 接続手順
+
+### ステップ 1: Slack App を作成
+
+1. [Slack API アプリ管理ページ](https://api.slack.com/apps) を開き、**Create New App** → **From scratch** をクリックします。
+2. **App Name**（例: `CowAgent`）を入力し、インストール先の **Workspace** を選択して作成します。
+
+### ステップ 2: Socket Mode を有効化し App Token を取得
+
+1. 左メニューの **Settings → Socket Mode** で **Enable Socket Mode** をオンにします。
+2. `connections:write` スコープを持つ **App-Level Token** の生成を求められます。`xapp-` で始まるこの Token を保存してください。
+
+<Tip>
+  Socket Mode は WebSocket 接続でイベントを受信するため、公開コールバック URL を公開する必要がありません。ローカルやイントラネットでの運用に最適です。
+</Tip>
+
+### ステップ 3: Bot 権限を設定してインストール
+
+1. **Features → OAuth & Permissions** を開き、**Bot Token Scopes** で **Add an OAuth Scope** をクリックして以下を 1 つずつ追加します:
+
+   ```
+   app_mentions:read
+   channels:history
+   chat:write
+   commands
+   files:read
+   files:write
+   groups:history
+   im:history
+   mpim:history
+   users:read
+   ```
+
+   <Note>
+     `files:read` / `files:write` は画像・ファイルの送受信に使用します。テキスト会話のみであれば省略可能です。
+   </Note>
+
+2. **Features → Event Subscriptions** を開き、**Enable Events** をオンにして、**Subscribe to bot events** で **Add Bot User Event** をクリックし、以下を追加します:
+
+   ```
+   app_mention
+   message.im
+   message.channels
+   ```
+
+   <Note>
+     非公開チャンネルで使用する場合は `message.groups` も追加してください。
+   </Note>
+3. **Features → App Home** を開き、**Show Tabs** 内の **Messages Tab** を有効にして、下の **Allow users to send Slash commands and messages from the messages tab**（メッセージタブからの送信を許可）にチェックを入れます。これを行わないと DM の入力欄が無効化され、ボットにメッセージを送れません。
+4. **OAuth & Permissions** に戻り、**Install to Workspace** をクリックしてインストールします。インストール後、`xoxb-` で始まる **Bot User OAuth Token** を取得します。
+
+<Tip>
+  Slack クライアントで「このアプリへのメッセージ送信は無効です」と表示される場合は、上記の App Home 設定が完了しているか確認し、Slack クライアントを再読み込み／再起動してください（必要に応じてアプリを会話一覧から削除して再度開きます）。
+</Tip>
+
+### ステップ 4: CowAgent に接続
+
+<Tabs>
+  <Tab title="Web コンソール（推奨）">
+    Web コンソール（既定 `http://127.0.0.1:9899`）を開き、**チャネル** メニュー → **チャネルを追加** → **Slack** を選択し、Bot Token（`xoxb-`）と App Token（`xapp-`）を貼り付けて接続をクリックします。
+  </Tab>
+  <Tab title="設定ファイル">
+    `config.json` に以下を追加して Cow を起動します:
+
+    ```json
+    {
+      "channel_type": "slack",
+      "slack_bot_token": "xoxb-xxxxxxxxxxxx",
+      "slack_app_token": "xapp-xxxxxxxxxxxx",
+      "slack_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | パラメータ | 説明 | 既定値 |
+    | --- | --- | --- |
+    | `slack_bot_token` | Bot User OAuth Token、`xoxb-...` の形式 | - |
+    | `slack_app_token` | App-Level Token（Socket Mode 有効化後に生成）、`xapp-...` の形式 | - |
+    | `slack_group_trigger` | チャンネルのトリガー方式: `mention_or_reply`（@ またはスレッド返信）/ `mention_only`（@ のみ）/ `all`（全メッセージ） | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+ログに以下のような出力が表示されれば接続成功です:
+
+```
+[Slack] Bot logged in as user_id=U0XXXXXXX, team=Txxxxxxxx
+[Slack] ✅ Slack bot ready, listening for events
+```
+
+## 2. 機能
+
+| 機能 | 対応状況 |
+| --- | --- |
+| ダイレクトメッセージ（DM） | ✅ |
+| チャンネル（@bot / スレッド返信） | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| ファイルメッセージ | ✅ 送受信（PDF / Word / Excel など） |
+| スレッド返信 | ✅ 起動メッセージのスレッドに返信を送信 |
+
+<Note>
+  Slack はスレッドで会話を整理します。Bot は起動メッセージのスレッドに返信を送信するため、チャンネルがすっきりします。
+</Note>
+
+## 3. 使い方
+
+接続が完了したら:
+
+- **ダイレクトメッセージ（DM）**: Slack の左サイドバー **Apps** からアプリを開き、直接メッセージを送ります。
+- **チャンネル**: アプリをチャンネルに招待し（`/invite @your-app`）、`@your-app こんにちは` で起動します。以降は同じスレッド内で返信すれば会話を継続できます。
+
+画像やファイルを送るときは、添付の入力欄に **テキスト説明**（説明・質問）を書いて一緒に送信できます。Bot は添付ファイルと説明を合わせて回答します。先に添付を送り、その後に質問を送る形でも、2 つのメッセージは自動でまとめて処理されます。
diff --git a/docs/ja/channels/telegram.mdx b/docs/ja/channels/telegram.mdx
new file mode 100644
index 0000000..eab1d3b
--- /dev/null
+++ b/docs/ja/channels/telegram.mdx
@@ -0,0 +1,111 @@
+---
+title: Telegram
+description: Telegram Bot API 経由で CowAgent を接続
+---
+
+> 公式の Telegram Bot API を通じて CowAgent を接続します。1 対 1 チャットおよびグループチャット（@メンションまたはボットへの返信で起動）に対応。Long Polling 方式のため公開 IP は不要で、すぐに利用できます。
+
+
+## 1. 接続手順
+
+### ステップ 1: BotFather で Bot を作成
+
+1. Telegram で公式アカウント [@BotFather](https://t.me/BotFather) を開きます。
+2. `/newbot` を送り、案内に従って入力します:
+   - **Bot 名**（表示名、例: `My CowAgent Bot`）
+   - **Bot ユーザー名**（`bot` で終わる必要があります、例: `my_cowagent_bot`）
+3. 作成完了後、BotFather から **HTTP API Token**（例: `123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ`）が返されます。大切に保管してください。
+
+<Tip>
+  Token は Bot のパスワードに相当します。漏えいしないよう注意してください。万が一漏れた場合は `@BotFather` に `/revoke` を送って再発行できます。
+</Tip>
+
+### ステップ 2:（グループ利用時）Privacy Mode を無効化
+
+1 対 1 チャットのみ利用する場合はスキップ可能です。Telegram Bot は既定で **Privacy Mode** が有効で、グループ内では `@bot` 接尾辞付きのコマンド（例: `/start@your_bot`）と、Bot メッセージへの返信のみ受信できます。**通常の `@bot こんにちは` のようなテキストメッセージは届きません**。そのままだとグループで反応しないので、必要に応じて以下を設定してください。
+
+`@BotFather` に対して:
+
+1. `/setprivacy` を送信
+2. 作成した Bot を選択
+3. `Disable` を選択
+
+<Note>
+  設定後もグループで反応しない場合は、Bot を一度グループから外して再度追加してみてください。
+</Note>
+
+### ステップ 3: CowAgent に接続
+
+<Tabs>
+  <Tab title="Web コンソール（推奨）">
+    Web コンソール（既定 `http://127.0.0.1:9899`）を開き、**チャネル** メニュー → **チャネルを追加** → **Telegram** を選択し、Bot Token を貼り付けて接続をクリックします。
+  </Tab>
+  <Tab title="設定ファイル">
+    `config.json` に以下を追加して Cow を起動します:
+
+    ```json
+    {
+      "channel_type": "telegram",
+      "telegram_token": "123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ",
+      "telegram_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | パラメータ | 説明 | 既定値 |
+    | --- | --- | --- |
+    | `telegram_token` | BotFather から発行された HTTP API Token | - |
+    | `telegram_group_trigger` | グループのトリガー方式: `mention_or_reply`（@ または返信）/ `mention_only`（@ のみ）/ `all`（全メッセージ） | `mention_or_reply` |
+    | `telegram_register_commands` | 起動時に BotFather にコマンドメニューを登録するかどうか | `true` |
+  </Tab>
+</Tabs>
+
+ログに以下のような出力が表示されれば接続成功です:
+
+```
+[Telegram] Bot logged in as @my_cowagent_bot (id=123456789)
+[Telegram] Registered 10 bot commands
+[Telegram] ✅ Telegram bot ready, polling for updates
+```
+
+## 2. 機能
+
+| 機能 | 対応状況 |
+| --- | --- |
+| 1 対 1 チャット | ✅ |
+| グループチャット（@bot / Bot への返信） | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| 音声メッセージ | ✅ 送受信（OGG/Opus） |
+| 動画メッセージ | ✅ 送受信 |
+| ファイルメッセージ | ✅ 送受信（PDF / Word / Excel など） |
+| コマンドメニュー | ✅ Web コンソールの slash コマンドと一致 |
+
+### コマンドメニュー
+
+起動時に BotFather へコマンドメニューを自動登録します。Telegram の入力欄で `/` を入力するとサジェストが表示されます:
+
+| コマンド | 説明 |
+| --- | --- |
+| `/help` | コマンドヘルプを表示 |
+| `/status` | 実行ステータスを確認 |
+| `/context` | 対話コンテキストを表示（`/context clear` でクリア） |
+| `/skill` | スキル管理（`/skill list`、`/skill install` など） |
+| `/memory` | 記憶管理（`/memory dream`） |
+| `/knowledge` | ナレッジベース管理（`/knowledge list` / `on` / `off`） |
+| `/config` | 現在の設定を表示 |
+| `/cancel` | 実行中の Agent タスクを中断 |
+| `/logs` | 最近のログを表示 |
+| `/version` | バージョンを表示 |
+
+<Note>
+  Telegram のコマンドメニューはトップレベルのコマンドのみ表示されます。サブコマンドはスペース区切りで入力します（例: `/skill list`、`/context clear`）。
+</Note>
+
+## 3. 使い方
+
+接続が完了したら:
+
+- **1 対 1 チャット**: Telegram で Bot のユーザー名（例: `@my_cowagent_bot`）を検索し、`Start` をタップして会話を開始します。
+- **グループチャット**: Bot をグループに追加し、`@bot こんにちは` または **Bot のメッセージに返信** することで起動します。グループで反応しない場合は [ステップ 2](#ステップ-2-グループ利用時-privacy-mode-を無効化) の Privacy Mode 設定を確認してください。
+
+画像やファイルを送るときは、添付欄の上の入力欄に **キャプション**（説明・質問）を直接書いて一緒に送信できます。Bot は添付ファイルとキャプションを合わせて回答します。先に添付を送り、その後に質問を送る形でも、2 つのメッセージは自動でまとめて処理されます。
diff --git a/docs/ja/channels/web.mdx b/docs/ja/channels/web.mdx
new file mode 100644
index 0000000..a044697
--- /dev/null
+++ b/docs/ja/channels/web.mdx
@@ -0,0 +1,95 @@
+---
+title: Web コンソール
+description: Web コンソールで CowAgent を使用する
+---
+
+Web コンソールは CowAgent のデフォルトチャネルです。起動後に自動的に実行され、ブラウザを通じて Agent と対話できるほか、モデル、Skill、メモリ、チャネルなどの設定をオンラインで管理できます。
+
+## 設定
+
+```json
+{
+  "channel_type": "web",
+  "web_host": "0.0.0.0",
+  "web_port": 9899,
+  "web_password": "",
+  "enable_thinking": false
+}
+```
+
+| パラメータ | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `channel_type` | `web` に設定 | `web` |
+| `web_host` | Web サービスのリスンアドレス。デフォルトは `127.0.0.1`（ローカルのみ）。公開アクセスが必要な場合は `0.0.0.0` に変更してパスワードを設定してください | `""` |
+| `web_port` | Web サービスのリスンポート | `9899` |
+| `web_password` | アクセスパスワード。空欄の場合はパスワード保護が無効。`0.0.0.0` でリスンする場合は設定を推奨 | `""` |
+| `web_session_expire_days` | ログインセッションの有効日数 | `30` |
+| `web_file_serve_root` | web コンソールが直接読み取り/送信できるファイルのルートディレクトリ。デフォルトはユーザーのホームディレクトリと agent ワークスペースのみ。`/` に設定するとファイルシステム全体を許可 | `"~"` |
+| `enable_thinking` | 深い思考モードを有効化するか | `false` |
+
+パスワード設定後、コンソールへアクセスする際にはまずパスワード入力によるログインが必要です。ログイン状態はデフォルトで 30 日間保持され、その間はサービスを再起動しても再ログインは不要です。パスワードはコンソールの「設定」ページからオンラインで変更することもできます。
+
+## アクセス URL
+
+プロジェクト起動後、以下にアクセスしてください：
+
+- ローカル実行: `http://localhost:9899`
+- サーバー実行: `http://<server-ip>:9899`
+
+<Note>
+  サーバーのファイアウォールとセキュリティグループで該当ポートが許可されていることを確認してください。
+</Note>
+
+## 機能紹介
+
+### チャット画面
+
+ストリーミング出力に対応しており、Agent の思考プロセス（Reasoning）とツール呼び出しプロセス（Tool Calls）をリアルタイムで表示でき、Agent の意思決定をより直感的に観察できます。深い思考機能は設定またはコンソールの「Agent 設定」スイッチで制御できます。
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### マルチセッション管理
+
+チャット画面はマルチセッション（Session）管理に対応しています。すべてのセッション記録はデータベースに永続化されます：
+
+- **セッション一覧**：左側の履歴セッションアイコンをクリックするとセッション一覧パネルを展開/折りたたみでき、スクロールですべての履歴セッションを読み込めます
+- **AI によるタイトル生成**：新しいセッションの初回対話完了後、自動的にモデルを呼び出して短いセッション要約タイトルを生成します
+- **新規セッション**：セッション一覧上部の「新しい会話」ボタンまたは入力エリアの `+` ボタンをクリックして新しいセッションを作成します
+- **セッション削除**：セッション項目の削除ボタンをクリックし、確認後にそのセッションとすべてのメッセージを完全に削除します
+- **コンテキストクリア**：入力エリアのクリアボタンをクリックすると、現在のセッションに区切り線が挿入されます。区切り線より上のメッセージは表示されたままですが、モデルのコンテキスト入力には含まれなくなります
+
+### モデル管理
+
+設定ファイルを手動で編集することなく、異なるモデルプロバイダーのテキスト、画像、音声、埋め込みモデル設定をオンラインで管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260521212949.png" />
+
+### Skill 管理
+
+Agent の Skill をオンラインで閲覧・管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+### メモリ管理
+
+Agent のメモリをオンラインで閲覧・管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+### チャネル管理
+
+接続中のチャネルをオンラインで管理でき、リアルタイムでの接続・切断操作に対応しています：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+### スケジュールタスク
+
+スケジュールタスクをオンラインで閲覧・管理できます。一回限りのタスク、固定間隔、Cron 式など複数のスケジューリング方式を可視化管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+### ログ
+
+Agent のランタイムログをオンラインでリアルタイムに確認でき、実行状態の監視やトラブルシューティングに便利です：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
diff --git a/docs/ja/channels/wechat-kf.mdx b/docs/ja/channels/wechat-kf.mdx
new file mode 100644
index 0000000..e48fa71
--- /dev/null
+++ b/docs/ja/channels/wechat-kf.mdx
@@ -0,0 +1,130 @@
+---
+title: WeChat Customer Service
+description: CowAgent を WeChat Customer Service に統合する
+---
+
+WeCom の自建アプリを WeChat Customer Service アカウントにバインドすることで、CowAgent は外部 WeChat ユーザーからの問い合わせを引き受けることができます。WeChat ミニプログラム、公式アカウント、ビデオチャンネル、ビデオチャンネルストアなどから、リンクや QR コードで WeChat ユーザーに到達できます。
+
+<Note>
+  WeChat Customer Service は Docker デプロイまたはサーバー Python デプロイのみサポートしており、外部からアクセス可能なコールバック URL が必要です。ローカル実行モードには対応していません。
+</Note>
+
+## 1. 前提条件
+
+必要なリソース：
+
+1. パブリック IP を持つサーバー
+2. 登録済みかつ認証済みの WeCom アカウント
+3. WeChat Customer Service 機能が有効になっていること
+
+<Note>
+  カスタマーサービス専用に **新たな** 企業微信自建アプリを作成することを推奨します。既存の `wechatcom_app` アプリを流用すると、2 つのチャネルが同じコールバック URL を奪い合うことになります。
+</Note>
+
+## 2. 企業微信自建アプリの作成
+
+1. [WeCom 管理コンソール](https://work.weixin.qq.com/wework_admin/frame#apps) で **アプリ管理 → アプリ作成** をクリックします：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+2. **自社情報** をクリックし、ページ下部で **企業ID（Corp ID）** を確認します（`wechat_kf_corp_id` に設定します）：
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-companyid.png" width="600"/>
+
+3. 上で作成したアプリに入り、Secret の隣の「**表示**」をクリックします。Secret は管理者のスマートフォンの WeCom アプリに送られ、そこで確認できます：
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-agent-secret.png" width="600"/>
+
+4. アプリの **メッセージ受信 → API 受信設定** に入り、右側の「**ランダム生成**」をクリックして **Token** と **EncodingAESKey** を生成し、保存します：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wechatcom-hosting-token-aeskey.jpg" width="600"/>
+
+<Note>
+  プログラムがまだ起動していないため、この時点では API 受信設定を保存できません。プロジェクトが動作した後に戻って保存してください。
+</Note>
+
+## 3. 設定と起動
+
+前のステップで収集した 4 つのフィールド（Corp ID / Secret / Token / EncodingAESKey）を入力します：
+
+<Tabs>
+  <Tab title="Web コンソール">
+    Cow プロジェクトを起動した後、Web コンソールを開きます。**チャネル** メニューを選択し、**接入チャネル** をクリックし、**WeChat Customer Service** を選択して、Corp ID / Secret / Token / AES Key を入力し（ポートはデフォルト 9888、変更可能）、接入をクリックします。
+
+    <img src="https://cdn.link-ai.tech/doc/cow-weixinkefu-web-control.png" width="800"/>
+  </Tab>
+  <Tab title="設定ファイル">
+    `config.json` に以下の設定を追加します（各パラメータと WeCom コンソールの対応関係は上のスクリーンショットを参照してください）：
+
+    ```json
+    {
+      "channel_type": "wechat_kf",
+      "wechat_kf_corp_id": "YOUR_CORP_ID",
+      "wechat_kf_secret": "YOUR_SECRET",
+      "wechat_kf_token": "YOUR_TOKEN",
+      "wechat_kf_aes_key": "YOUR_AES_KEY",
+      "wechat_kf_port": 9888
+    }
+    ```
+
+    | パラメータ | 説明 |
+    | --- | --- |
+    | `wechat_kf_corp_id` | 企業 ID |
+    | `wechat_kf_secret` | カスタマーサービスにバインドした企業微信自建アプリの Secret |
+    | `wechat_kf_token` | API 受信設定の Token |
+    | `wechat_kf_aes_key` | API 受信設定の EncodingAESKey |
+    | `wechat_kf_port` | リスンポート、デフォルトは 9888 |
+  </Tab>
+</Tabs>
+
+接入完了後、プログラムを起動します（Web コンソール方式ではチャネルが自動的に再起動されます）。ログに `Listening on http://0.0.0.0:9888/wxkf/` と表示されれば、プログラムは正常に動作しています。このポートを外部に公開する必要があります（例：クラウドサーバーのセキュリティグループで許可します）。
+
+続いて、WeCom 管理コンソールの **メッセージ受信 → API 受信設定** に戻り、コールバック URL に `http://<your-host>:9888/wxkf/` を入力して保存します。保存が成功したら、サーバー IP を **企業の信頼済み IP** に追加する必要もあります。追加しないとメッセージの送受信ができません：
+
+<img src="https://cdn.link-ai.tech/doc/wechat-com_config.png" width="600"/>
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  URL のコールバック検証が通らない、または設定がうまくいかない場合：
+  1. サーバーのファイアウォールが無効になっており、セキュリティグループでリスンポート（デフォルト 9888）が許可されていることを確認してください
+  2. Token、Secret、EncodingAESKey などのパラメータが一致しているか、URL の形式が正しいか慎重に確認してください
+  3. 認証済みの WeCom アカウントは、法人に対応する届け出済みドメインを設定する必要があります
+</Warning>
+
+## 4. WeChat Customer Service アカウントとのバインド
+
+WeCom 管理コンソールの **WeChat Customer Service** ページに入り、カスタマーサービスアカウントを作成し、上で作成した WeCom 自建アプリとバインドします：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step1.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step2.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step3.jpg" width="600"/>
+
+バインド完了後、**WeChat Customer Service → WeChat Customer Service アカウント詳細** に入り、「**接入リンク**」の項目で：
+
+- 「**リンクをコピー**」をクリックすると、`https://work.weixin.qq.com/kfid/kfcd83e5896b9ba07be` のような接入リンクが取得できます
+- 「**QR コード生成**」をクリックすると、対応する QR コードが取得できます
+
+リンクまたは QR コードを WeChat 顧客に配布してください：
+
+<img src="https://cdn.link-ai.tech/doc/wechat-customer-service_use.png" width="600"/>
+
+## 5. 使い方
+
+WeChat ユーザーがリンクや QR コードからカスタマーサービス対話に入った後、AI とテキスト・画像・音声などのマルチターン対話が可能です：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-chat-demo.jpg" width="900"/>
+
+これに加え、WeChat 公式エコシステムの機能に基づき、WeChat Customer Service を公式アカウント、ミニプログラム、ビデオチャンネルなどの場面でも使用できます。詳細は [WeCom 管理コンソール](https://work.weixin.qq.com/wework_admin/frame#/app/servicer) の **WeChat Customer Service → 接入シナリオ** を参照してください：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-interface-demo.png" width="800"/>
+
+## FAQ
+
+以下の依存パッケージがインストールされていることを確認してください：
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/ja/channels/wechatmp.mdx b/docs/ja/channels/wechatmp.mdx
new file mode 100644
index 0000000..023a6eb
--- /dev/null
+++ b/docs/ja/channels/wechatmp.mdx
@@ -0,0 +1,72 @@
+---
+title: WeChat 公式アカウント
+description: CowAgent を WeChat 公式アカウントに統合する
+---
+
+CowAgent は個人サブスクリプションアカウントと企業サービスアカウントの両方に対応しています。
+
+| 種類 | 要件 | 特徴 |
+| --- | --- | --- |
+| **個人サブスクリプション** | 個人で利用可能 | まずプレースホルダーの返信を送信し、ユーザーが完全な応答を取得するにはメッセージを送信する必要があります |
+| **企業サービス** | カスタマーサービス API が認証済みの企業 | ユーザーに能動的に返信をプッシュできます |
+
+<Note>
+  公式アカウントはサーバーおよび Docker デプロイのみサポートしており、ローカル実行モードには対応していません。拡張依存パッケージをインストールしてください: `pip3 install -r requirements-optional.txt`
+</Note>
+
+## 1. 個人サブスクリプションアカウント
+
+`config.json` に以下の設定を追加します：
+
+```json
+{
+  "channel_type": "wechatmp",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "wx73f9******d1e48",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
+
+### セットアップ手順
+
+これらの設定は [WeChat 公式アカウントプラットフォーム](https://mp.weixin.qq.com/advanced/advanced?action=dev&t=advanced/dev)と一致している必要があります。**設定と開発 → 基本設定 → サーバー設定**に移動し、以下のように設定します：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103506.png" width="480"/>
+
+1. プラットフォームで開発者シークレットを有効化し（`wechatmp_app_secret` に対応）、サーバー IP をホワイトリストに追加します
+2. プラットフォームの設定と一致するように公式アカウントのパラメータを `config.json` に入力します
+3. プログラムを起動します。ポート 80 でリスンします（権限がない場合は `sudo` を使用してください。ポート 80 を占有しているプロセスがあれば停止してください）
+4. 公式アカウントプラットフォームで**サーバー設定を有効化**して送信します。正常に保存できれば設定完了です。**「サーバー URL」**は `http://{HOST}/wx` の形式で入力する必要があり、`{HOST}` にはサーバー IP またはドメインを指定できます
+
+アカウントをフォローしてメッセージを送信すると、以下のような結果が表示されるはずです：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103522.png" width="720"/>
+
+サブスクリプションアカウントの制限により、短い返信（15秒以内）は即座に返されますが、長い返信の場合はまず「考え中...」というプレースホルダーが送信され、ユーザーは任意のテキストを送信して回答を取得する必要があります。企業サービスアカウントではカスタマーサービス API を使用してこの問題を解決できます。
+
+<Tip>
+  **音声認識**: WeChat 内蔵の音声認識を使用できます。公式アカウント管理ページの「設定と開発 → API 権限」で「音声認識結果の受信」を有効にしてください。
+</Tip>
+
+## 2. 企業サービスアカウント
+
+企業サービスアカウントのセットアップ手順は個人サブスクリプションアカウントとほぼ同じですが、以下の点が異なります：
+
+1. プラットフォームで企業サービスアカウントを登録し、WeChat 認証を完了します。**カスタマーサービス API** の権限が付与されていることを確認してください
+2. `config.json` で `"channel_type": "wechatmp_service"` に設定します。その他の設定は同じです
+3. 長い返信であっても、ユーザーに能動的にプッシュでき、手動での取得が不要です
+
+```json
+{
+  "channel_type": "wechatmp_service",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "YOUR_APP_ID",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
diff --git a/docs/ja/channels/wecom-bot.mdx b/docs/ja/channels/wecom-bot.mdx
new file mode 100644
index 0000000..4e463e2
--- /dev/null
+++ b/docs/ja/channels/wecom-bot.mdx
@@ -0,0 +1,87 @@
+---
+title: WeCom Bot
+description: CowAgent を WeCom AI Bot に接続する（WebSocket ロングコネクション）
+---
+
+WeCom AI Bot を介して CowAgent を接続し、ダイレクトメッセージとグループチャットの両方に対応します。パブリック IP は不要で、WebSocket ロングコネクションを使用し、Markdown レンダリングとストリーミング出力をサポートします。
+
+<Note>
+  WeCom Bot と WeCom App は異なる統合方式です。WeCom Bot は WebSocket ロングコネクションを使用するため、パブリック IP やドメインが不要で、セットアップが簡単です。
+</Note>
+
+## 1. AI Bot の作成
+
+1. WeCom クライアントを開き、**ワークベンチ**に移動し、**AI Bot** をクリックします：
+
+<img src="https://cdn.link-ai.tech/doc/20260316180959.png" width="800"/>
+
+2. **Bot を作成** → **手動作成**をクリックします：
+
+<img src="https://cdn.link-ai.tech/doc/20260316181118.png" width="600"/>
+
+3. 右パネルの一番下までスクロールし、**API モード**を選択します：
+
+<img src="https://cdn.link-ai.tech/doc/20260316181215.png" width="600"/>
+
+4. Bot 名、アバター、公開範囲を設定します。**ロングコネクション**モードを選択し、**Bot ID** と **Secret** をメモしてから保存をクリックします。
+
+## 2. 設定
+
+### 方法 A: Web コンソール
+
+プログラムを起動し、Web コンソール（ローカルアクセス: http://127.0.0.1:9899）を開きます。**チャネル**タブに移動し、**チャネルを接続**をクリックして **WeCom Bot** を選択し、前のステップで取得した Bot ID と Secret を入力して接続をクリックします。
+
+<img src="https://cdn.link-ai.tech/doc/20260316181711.png" width="600"/>
+
+### 方法 B: 設定ファイル
+
+`config.json` に以下を追加します：
+
+```json
+{
+  "channel_type": "wecom_bot",
+  "wecom_bot_id": "YOUR_BOT_ID",
+  "wecom_bot_secret": "YOUR_SECRET"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `wecom_bot_id` | AI Bot の Bot ID |
+| `wecom_bot_secret` | AI Bot の Secret |
+
+設定後、プログラムを起動します。ログに `[WecomBot] Subscribe success` と表示されれば接続成功です。
+
+<Note>
+  ロングコネクションのほかに、**Webhook（HTTP コールバック）モード**にも対応しています。Bot 作成時に **URL コールバックを使用**を選択し、受信メッセージ URL を `http(s)://<ドメインまたはIP>:9892/wecombot` に設定して、その画面の Token と EncodingAESKey をコピーします。このモードは外部からアクセス可能なアドレスが必要で、ファイル送信とスケジュール配信には対応していないため、通常はロングコネクションを推奨します。対応する `config.json`：
+
+```json
+{
+  "channel_type": "wecom_bot",
+  "wecom_bot_mode": "webhook",
+  "wecom_bot_token": "YOUR_TOKEN",
+  "wecom_bot_encoding_aes_key": "YOUR_ENCODING_AES_KEY",
+  "wecom_bot_port": 9892
+}
+```
+</Note>
+
+## 3. 対応機能
+
+| 機能 | 状態 |
+| --- | --- |
+| ダイレクトメッセージ | ✅ |
+| グループチャット（@bot） | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| ファイルメッセージ | ✅ 送受信 |
+| ストリーミング返信 | ✅ |
+| スケジュール配信 | ✅ |
+
+## 4. 使い方
+
+WeCom で Bot 名を検索してダイレクトメッセージを開始できます。
+
+グループチャットで使用するには、Bot をグループに追加し、@メンションしてメッセージを送信します。
+
+<img src="https://cdn.link-ai.tech/doc/20260316182902.png" width="800"/>
diff --git a/docs/ja/channels/wecom.mdx b/docs/ja/channels/wecom.mdx
new file mode 100644
index 0000000..92299ef
--- /dev/null
+++ b/docs/ja/channels/wecom.mdx
@@ -0,0 +1,98 @@
+---
+title: WeCom
+description: CowAgent を WeCom 企業アプリに統合する
+---
+
+カスタム企業アプリを通じて CowAgent を WeCom に統合し、社内従業員との1対1チャットに対応します。
+
+<Note>
+  WeCom は Docker デプロイまたはサーバー上の Python デプロイのみサポートしています。ローカル実行モードには対応していません。
+</Note>
+
+## 1. 前提条件
+
+必要なリソース：
+
+1. パブリック IP を持つサーバー（海外サーバー、または国際 API アクセス用のプロキシを持つ国内サーバー）
+2. 登録済みの WeCom アカウント（個人登録は可能ですが認証はできません）
+3. 認証済みの WeCom アカウントには、対応する法人名義で届け出済みのドメインが別途必要です
+
+## 2. WeCom アプリの作成
+
+1. [WeCom 管理コンソール](https://work.weixin.qq.com/wework_admin/frame#profile)で、**自社情報**をクリックし、ページ下部の **Corp ID** を確認します。この ID を `wechatcom_corp_id` 設定フィールド用に保存します。
+
+2. **アプリ管理**に切り替え、アプリを作成をクリックします：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+3. アプリ作成ページで、`AgentId` と `Secret` を記録します：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103218.png" width="580"/>
+
+4. **API 受信設定**をクリックしてアプリケーションインターフェースを設定します：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103211.png" width="520"/>
+
+- URL の形式: `http://ip:port/wxcomapp`（認証済み企業は届け出済みドメインを使用する必要があります）
+- ランダムな `Token` と `EncodingAESKey` を生成し、設定ファイル用に保存します
+
+<Note>
+  プログラムがまだ起動していないため、この時点では API 受信設定を保存できません。プロジェクトが動作した後に戻って保存してください。
+</Note>
+
+## 3. 設定と起動
+
+`config.json` に以下の設定を追加します（各パラメータと WeCom コンソールの対応関係は上のスクリーンショットを参照してください）：
+
+```json
+{
+  "channel_type": "wechatcom_app",
+  "single_chat_prefix": [""],
+  "wechatcom_corp_id": "YOUR_CORP_ID",
+  "wechatcomapp_token": "YOUR_TOKEN",
+  "wechatcomapp_secret": "YOUR_SECRET",
+  "wechatcomapp_agent_id": "YOUR_AGENT_ID",
+  "wechatcomapp_aes_key": "YOUR_AES_KEY",
+  "wechatcomapp_port": 9898
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `wechatcom_corp_id` | Corp ID |
+| `wechatcomapp_token` | API 受信設定の Token |
+| `wechatcomapp_secret` | アプリの Secret |
+| `wechatcomapp_agent_id` | アプリの AgentId |
+| `wechatcomapp_aes_key` | API 受信設定の EncodingAESKey |
+| `wechatcomapp_port` | リスンポート、デフォルトは 9898 |
+
+設定後、プログラムを起動します。ログに `http://0.0.0.0:9898/` と表示されれば、プログラムは正常に動作しています。このポートを外部に公開する必要があります（例：クラウドサーバーのセキュリティグループで許可します）。
+
+プログラム起動後、WeCom 管理コンソールに戻って**メッセージサーバー設定**を保存します。保存が成功したら、サーバー IP を**企業の信頼済み IP** に追加する必要もあります。追加しないとメッセージの送受信ができません：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  URL 設定のコールバックが失敗する場合や、設定がうまくいかない場合：
+  1. サーバーのファイアウォールが無効になっており、セキュリティグループでリスンポートが許可されていることを確認してください
+  2. Token、Secret Key などのパラメータ設定が一致しているか、URL の形式が正しいか慎重に確認してください
+  3. 認証済みの WeCom アカウントは、法人に対応する届け出済みドメインを設定する必要があります
+</Warning>
+
+## 4. 使い方
+
+WeCom で作成したアプリ名を検索して、直接チャットを開始できます。異なるポートでリスンする複数のインスタンスを実行して、複数の WeCom アプリを作成できます：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103228.png" width="720"/>
+
+外部の個人 WeChat ユーザーにアプリを利用してもらうには、**自社情報 → WeChat プラグイン**に移動し、招待 QR コードを共有します。スキャンしてフォローした後、個人 WeChat ユーザーがアプリとチャットできるようになります：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103232.png" width="520"/>
+
+## FAQ
+
+以下の依存パッケージがインストールされていることを確認してください：
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/ja/channels/weixin.mdx b/docs/ja/channels/weixin.mdx
new file mode 100644
index 0000000..912cce2
--- /dev/null
+++ b/docs/ja/channels/weixin.mdx
@@ -0,0 +1,72 @@
+---
+title: WeChat
+description: CowAgent を個人の WeChat に接続する
+---
+
+> 個人の WeChat に接続します。QR コードをスキャンするだけでログインでき、パブリック IP は不要です。テキスト、画像、音声、ファイル、動画メッセージの送受信に対応しています。
+
+## 1. 設定
+
+### 方法 A: Web コンソール
+
+プログラムを起動し、Web コンソール（ローカルアクセス: http://127.0.0.1:9899）を開きます。**チャネル**タブに移動し、**チャネルを接続**をクリックして **WeChat** を選択し、プロンプトに従って QR コードをスキャンしてください。
+
+### 方法 B: 設定ファイル
+
+`config.json` で `channel_type` を `weixin` に設定します：
+
+```json
+{
+  "channel_type": "weixin"
+}
+```
+
+プログラム起動後、ターミナルに QR コードが表示されます。WeChat でスキャンし、スマートフォンで確認してログインを完了してください。
+
+<Note>
+  後方互換性のため、`channel_type` を `wx` に設定しても WeChat チャネルが有効になります。
+</Note>
+
+## 2. パラメータ
+
+| パラメータ | 説明 | デフォルト |
+| --- | --- | --- |
+| `channel_type` | `weixin` または `wx` を指定 | — |
+
+ログイン認証情報は `~/.weixin_cow_credentials.json` に自動保存されます。再ログインするには、このファイルを削除してプログラムを再起動してください。
+
+## 3. ログイン
+
+### QR コードログイン
+
+初回起動時に、ターミナルに QR コードが表示されます（有効期限は約 2 分）。WeChat でスキャンし、スマートフォンで確認してください。
+
+- QR コードが期限切れになると自動的に更新・再表示されます
+- `qrcode` 依存関係は `requirements.txt` にデフォルトで含まれており、ターミナルに直接 QR コードを表示できます
+
+### 認証情報の永続化
+
+ログイン成功後、認証情報は `~/.weixin_cow_credentials.json` に保存されます。次回起動時は保存された認証情報が再利用され、再スキャンは不要です。
+
+再ログインするには、認証情報ファイルを削除してプログラムを再起動してください。
+
+### セッションの期限切れ
+
+WeChat セッションが期限切れになった場合（errcode -14）、プログラムは自動的に古い認証情報をクリアし、新しい QR ログインを開始します。手動での操作は不要です。
+
+## 4. 対応機能
+
+| 機能 | 状態 |
+| --- | --- |
+| ダイレクトメッセージ | ✅ |
+| テキストメッセージ | ✅ 送受信 |
+| 画像メッセージ | ✅ 送受信 |
+| ファイルメッセージ | ✅ 送受信 |
+| 動画メッセージ | ✅ 送受信 |
+| 音声メッセージ | ✅ 受信 |
+
+## 5. 注意事項
+
+1. `ilinkai.weixin.qq.com` へのネットワークアクセスが必要です。
+2. メディアファイル（画像、ファイル、動画）は CDN 経由で AES-128-ECB 暗号化を使用して転送され、プログラムが自動的に処理します。
+3. 頻繁な切断による再スキャンを避けるため、安定したネットワーク環境での実行を推奨します。
diff --git a/docs/ja/cli/general.mdx b/docs/ja/cli/general.mdx
new file mode 100644
index 0000000..e31d7cf
--- /dev/null
+++ b/docs/ja/cli/general.mdx
@@ -0,0 +1,110 @@
+---
+title: 汎用コマンド
+description: ステータスの確認、設定管理、コンテキスト制御などのよく使うコマンド
+---
+
+以下のコマンドはチャットで `/` プレフィックス、ターミナルで `cow` プレフィックスで使用できます（一部はチャット専用）。
+
+<Tip>
+  Web コンソールでは `/` を入力すると自動補完メニューが表示され、キーボードのナビゲーションと Tab 補完に対応しています。
+</Tip>
+
+## help
+
+使用可能なすべてのコマンドのヘルプ情報を表示します。
+
+```text
+/help
+```
+
+## status
+
+現在のセッションとサービスの実行状態を表示します。プロセス情報、モデル設定、メッセージ数、読み込み済みスキル数を含みます。
+
+```text
+/status
+```
+
+## cancel
+
+現在のセッションで実行中の Agent タスクを中止します。Agent が長時間のタスク（マルチターンのツール呼び出しや長いストリーミング応答など）を実行している間、`/cancel` を送信すると、次のツール実行の前に停止します。Web、WeChat、企業微信、Feishu など、すべてのチャネルで利用可能です。
+
+```text
+/cancel
+```
+
+## config
+
+実行時設定の表示または変更を行います。変更は即座に反映され、再起動は不要です。
+
+**すべての設定項目を表示：**
+
+```text
+/config
+```
+
+**単一の設定項目を表示：**
+
+```text
+/config model
+```
+
+**設定項目を変更：**
+
+```text
+/config model deepseek-v4-flash
+```
+
+**変更可能な設定項目：**
+
+| 項目 | 説明 | 例 |
+| --- | --- | --- |
+| `model` | AI モデル名 | `deepseek-v4-flash` |
+| `agent_max_context_tokens` | 最大コンテキストトークン数 | `40000` |
+| `agent_max_context_turns` | 最大コンテキスト記憶ターン数 | `30` |
+| `agent_max_steps` | タスクごとの最大判断ステップ数 | `15` |
+| `enable_thinking` | ディープシンキングモードの有効化 | `true` / `false` |
+
+<Note>
+  `model` を変更すると、システムが対応するモデル API を自動的にマッチングします。設定は `config.json` に永続的に保存されます。
+</Note>
+
+## context
+
+現在のセッションのコンテキスト統計情報を表示します。メッセージ数やコンテンツの長さを含みます。
+
+```text
+/context
+```
+
+**現在のセッションのコンテキストをクリア：**
+
+```text
+/context clear
+```
+
+<Tip>
+  コンテキストをクリアすると、Agent は以前の会話内容を「忘れます」。話題の切り替えやコンテキストスペースの解放に便利です。
+</Tip>
+
+## logs
+
+最近のサービスログを表示します。デフォルトでは最近の 20 行を表示し、最大 50 行です。
+
+```text
+/logs
+```
+
+**行数を指定：**
+
+```text
+/logs 50
+```
+
+## version
+
+現在の CowAgent のバージョンを表示します。
+
+```text
+/version
+```
diff --git a/docs/ja/cli/index.mdx b/docs/ja/cli/index.mdx
new file mode 100644
index 0000000..4d00a65
--- /dev/null
+++ b/docs/ja/cli/index.mdx
@@ -0,0 +1,96 @@
+---
+title: コマンド概要
+description: CowAgent コマンドシステム — ターミナル CLI とチャットコマンド
+---
+
+CowAgent は2つのコマンド操作方法を提供しています：
+
+- **ターミナル CLI** — システムターミナルで `cow <コマンド>` を実行し、サービス管理やスキル管理を行います
+- **チャットコマンド** — 会話で `/<コマンド>` または `cow <コマンド>` を入力し、ステータス確認、スキル管理、設定変更を行います
+
+## Cow CLI
+
+ワンクリックインストールスクリプトでデプロイすると、`cow` コマンドが自動的に利用可能になります。手動インストールの場合は以下を実行してください：
+
+```bash
+pip install -e .
+```
+
+インストール後、任意の場所で `cow` コマンドを使用できます：
+
+```bash
+cow help
+```
+
+出力例：
+
+```
+🐮 CowAgent CLI
+
+Usage: cow <command>
+
+Service:
+  start     Start the CowAgent service
+  stop      Stop the CowAgent service
+  restart   Restart the CowAgent service
+  update    Update code and restart service
+  status    Show service status
+  logs      View service logs
+
+Skills:
+  skill     Manage skills (list / search / install / uninstall ...)
+
+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
+Others:
+  help      Show this help message
+  version   Show version
+```
+
+## チャットコマンド
+
+Web コンソールや接続されたチャネルの会話で `/` を入力すると、コマンドの候補が表示されます。使用可能なコマンド：
+
+| コマンド | 説明 |
+| --- | --- |
+| `/help` | コマンドヘルプを表示 |
+| `/status` | サービスの状態と設定を表示 |
+| `/cancel` | 実行中の Agent タスクを中止 |
+| `/config` | 実行時設定の表示・変更 |
+| `/skill` | スキル管理（インストール、アンインストール、有効化、無効化など） |
+| `/memory dream [N]` | 記憶蒸留を手動トリガー（デフォルト 3 日、最大 30） |
+| `/knowledge` | ナレッジベースの統計情報を表示 |
+| `/knowledge list` | ナレッジベースのディレクトリ構造を表示 |
+| `/knowledge on\|off` | ナレッジベースの有効化・無効化 |
+| `/context` | 現在のセッションのコンテキスト情報を表示 |
+| `/context clear` | 現在のセッションのコンテキストをクリア |
+| `/logs` | 最近のログを表示 |
+| `/version` | バージョン番号を表示 |
+
+<Tip>
+  `/start`、`/stop`、`/restart` などのサービス管理コマンドは、プロセス操作を伴うため、ターミナルでの使用を案内します。
+</Tip>
+
+## コマンド対応表
+
+| コマンド | ターミナル (`cow`) | チャット (`/`) |
+| --- | :---: | :---: |
+| help | ✓ | ✓ |
+| version | ✓ | ✓ |
+| status | ✓ | ✓ |
+| logs | ✓ | ✓ |
+| cancel | ✗ | ✓ |
+| config | ✗ | ✓ |
+| context | — | ✓ |
+| memory（サブコマンド） | ✗ | ✓ |
+| knowledge（サブコマンド） | ✓ | ✓ |
+| skill（サブコマンド） | ✓ | ✓ |
+| start / stop / restart | ✓ | ✗ |
+| update | ✓ | ✗ |
+| install-browser | ✓ | ✗ |
+
+<Note>
+  `context` はターミナルではチャットでの使用を案内するのみです。`config` はチャットでのみ利用可能です。
+</Note>
diff --git a/docs/ja/cli/memory-knowledge.mdx b/docs/ja/cli/memory-knowledge.mdx
new file mode 100644
index 0000000..893d4f4
--- /dev/null
+++ b/docs/ja/cli/memory-knowledge.mdx
@@ -0,0 +1,63 @@
+---
+title: 記憶とナレッジベース
+description: 記憶蒸留とナレッジベース管理コマンド
+---
+
+## memory
+
+Agent の長期記憶システムを管理します。
+
+### memory dream
+
+記憶蒸留（Deep Dream）を手動でトリガーします — 最近の日次記憶を整理し、MEMORY.md に統合し、夢日記を生成します。
+
+```text
+/memory dream [N]
+```
+
+- `N`：直近 N 日間の記憶を整理（デフォルト 3 日、最大 30 日）
+- バックグラウンドで非同期に実行され、完了するとチャットで通知されます
+- Agent の初期化不要 — 最初の会話前でも使用可能
+
+**例：**
+
+```text
+/memory dream       # 直近 3 日間を整理
+/memory dream 7     # 直近 7 日間を整理
+/memory dream 30    # 直近 30 日間を整理（全量）
+```
+
+Web コンソールでは、完了通知にクリック可能なリンクが含まれ、更新された MEMORY.md と夢日記を直接確認できます。
+
+<Tip>
+  システムは毎日 23:55 に自動で蒸留を実行します（lookback 1 日）。手動トリガーは、初回デプロイ後の履歴整理や、即座に記憶を更新したい場合に使用します。
+</Tip>
+
+## knowledge
+
+パーソナルナレッジベースの表示と管理。デフォルトで統計情報を表示します。
+
+```text
+/knowledge
+```
+
+### knowledge list
+
+ナレッジベースのディレクトリツリーを表示します。
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+ナレッジベースの有効化・無効化。無効化すると、ナレッジプロンプトとファイルインデックスが注入されなくなります。
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  ターミナル CLI では `cow knowledge` と `cow knowledge list` が利用可能ですが、`on|off` はチャットでのみサポートされます（ランタイム効果が必要なため）。
+</Note>
diff --git a/docs/ja/cli/process.mdx b/docs/ja/cli/process.mdx
new file mode 100644
index 0000000..4600f2b
--- /dev/null
+++ b/docs/ja/cli/process.mdx
@@ -0,0 +1,123 @@
+---
+title: プロセス管理
+description: cow コマンドで CowAgent プロセスのライフサイクルを管理
+---
+
+プロセス管理コマンドは CowAgent バックグラウンドプロセスのライフサイクルを制御します。これらのコマンドはターミナルでのみ使用可能です。
+
+## start
+
+CowAgent サービスを起動します。デフォルトではバックグラウンドデーモンとして実行され、自動的にログを表示します。
+
+```bash
+cow start
+```
+
+**オプション：**
+
+| オプション | 説明 |
+| --- | --- |
+| `-f`, `--foreground` | フォアグラウンドで実行（デーモンとして起動しない） |
+| `--no-logs` | 起動後にログを自動表示しない |
+
+## stop
+
+実行中の CowAgent サービスを停止します。
+
+```bash
+cow stop
+```
+
+## restart
+
+CowAgent サービスを再起動します（停止してから起動）。
+
+```bash
+cow restart
+```
+
+**オプション：**
+
+| オプション | 説明 |
+| --- | --- |
+| `--no-logs` | 再起動後にログを自動表示しない |
+
+## update
+
+コードを更新してサービスを再起動します。自動的に以下を実行します：
+
+1. 最新コードをプル（`git pull`）
+2. 現在のサービスを停止
+3. Python 依存パッケージを更新
+4. CLI を再インストール
+5. サービスを起動
+
+```bash
+cow update
+```
+
+<Warning>
+  `git pull` が失敗した場合（ローカルの未コミットの変更がある場合など）、更新は中止され、サービスには影響しません。
+</Warning>
+
+## status
+
+CowAgent サービスの実行状態を確認します。プロセス情報、バージョン、現在のモデルとチャネルの設定を含みます。
+
+```bash
+cow status
+```
+
+## logs
+
+サービスログを表示します。
+
+```bash
+cow logs
+```
+
+**オプション：**
+
+| オプション | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `-f`, `--follow` | ログ出力を継続的に追跡 | いいえ |
+| `-n`, `--lines` | 最近の N 行を表示 | 50 |
+
+例：
+
+```bash
+# 最近の100行を表示
+cow logs -n 100
+
+# ログを継続的に追跡
+cow logs -f
+```
+
+## install-browser
+
+[ブラウザツール](/ja/tools/browser)のために Playwright と Chromium ブラウザをインストールします。
+
+```bash
+cow install-browser
+```
+
+<Tip>
+  ブラウザツール（Web ブラウジング、スクリーンショットなど）を使用する場合にのみ必要です。
+</Tip>
+
+## run.sh との互換性
+
+Cow CLI がインストールされていない場合は、`run.sh` でサービスを管理できます：
+
+| cow コマンド | run.sh 相当 |
+| --- | --- |
+| `cow start` | `./run.sh start` |
+| `cow stop` | `./run.sh stop` |
+| `cow restart` | `./run.sh restart` |
+| `cow update` | `./run.sh update` |
+| `cow status` | `./run.sh status` |
+| `cow logs` | `./run.sh logs` |
+
+<Note>
+  `cow` コマンドの使用を推奨します。よりシンプルな構文と豊富な機能を提供します。ワンクリックインストールスクリプトで自動的にインストールされます。
+</Note>
diff --git a/docs/ja/cli/skill.mdx b/docs/ja/cli/skill.mdx
new file mode 100644
index 0000000..9e5c1ad
--- /dev/null
+++ b/docs/ja/cli/skill.mdx
@@ -0,0 +1,192 @@
+---
+title: スキル管理
+description: コマンドでスキルのインストール、アンインストール、有効化、無効化、管理を行う
+---
+
+スキル管理コマンドは CowAgent のスキルのインストール、検索、管理に使用します。チャットでは `/skill <サブコマンド>`、ターミナルでは `cow skill <サブコマンド>` を使用します。
+
+## list
+
+インストール済みスキルとその状態を一覧表示します。
+
+<CodeGroup>
+```text チャット
+/skill list
+```
+
+```bash ターミナル
+cow skill list
+```
+</CodeGroup>
+
+**スキル広場を閲覧**（利用可能なすべてのスキルを表示）：
+
+<CodeGroup>
+```text チャット
+/skill list --remote
+```
+
+```bash ターミナル
+cow skill list --remote
+```
+</CodeGroup>
+
+**オプション：**
+
+| オプション | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `--remote`, `-r` | Skill Hub のリモートスキルリストを閲覧 | いいえ |
+| `--page` | リモートリストのページ番号 | 1 |
+
+## search
+
+スキル広場でスキルを検索します。
+
+<CodeGroup>
+```text チャット
+/skill search pptx
+```
+
+```bash ターミナル
+cow skill search pptx
+```
+</CodeGroup>
+
+## install
+
+統一された `install` コマンドで、Cow スキル広場、GitHub、ClawHub、任意の URL（zip アーカイブ、SKILL.md リンク）からスキルをワンクリックでインストールできます。手動ダウンロードや設定は不要です。
+
+**スキル広場からインストール（推奨）：**
+
+<CodeGroup>
+```text チャット
+/skill install pptx
+```
+
+```bash ターミナル
+cow skill install pptx
+```
+</CodeGroup>
+
+**GitHub からインストール：**
+
+<CodeGroup>
+```text チャット
+# リポジトリ内のすべてのスキルをインストール（SKILL.md を含むサブディレクトリを自動検出）
+/skill install larksuite/cli
+
+# サブディレクトリを指定して単一スキルをインストール
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# # でサブディレクトリを指定
+/skill install larksuite/cli#skills/lark-minutes
+```
+
+```bash ターミナル
+# リポジトリ内のすべてのスキルをインストール（SKILL.md を含むサブディレクトリを自動検出）
+cow skill install larksuite/cli
+
+# サブディレクトリを指定して単一スキルをインストール
+cow skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# # でサブディレクトリを指定
+cow skill install larksuite/cli#skills/lark-minutes
+```
+</CodeGroup>
+
+完全な GitHub URL と `owner/repo` 省略形に対応しています。モノリポ（1つのリポジトリに複数のスキル）の場合、サブディレクトリを省略するとすべてのスキルを自動検出して一括インストールします。サブディレクトリを指定した場合は、そのスキルのみをインストールします。
+
+**ClawHub からインストール：**
+
+<CodeGroup>
+```text チャット
+/skill install clawhub:baidu-search
+```
+
+```bash ターミナル
+cow skill install clawhub:baidu-search
+```
+</CodeGroup>
+
+**URL からインストール：**
+
+<CodeGroup>
+```text チャット
+# zip アーカイブからインストール（単一またはバッチ）
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# SKILL.md リンクからインストール
+/skill install https://example.com/path/to/SKILL.md
+```
+
+```bash ターミナル
+# zip アーカイブからインストール（単一またはバッチ）
+cow skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# SKILL.md リンクからインストール
+cow skill install https://example.com/path/to/SKILL.md
+```
+</CodeGroup>
+
+zip / tar.gz アーカイブ URL からのインストールに対応しており、自動的に解凍して `SKILL.md` を含むディレクトリを検出し、単一またはバッチインストールをサポートします。`SKILL.md` ファイルの URL から直接インストールすることもでき、スキル名と説明を自動的に解析します。
+
+## uninstall
+
+インストール済みスキルをアンインストールします。
+
+<CodeGroup>
+```text チャット
+/skill uninstall pptx
+```
+
+```bash ターミナル
+cow skill uninstall pptx
+```
+</CodeGroup>
+
+<Warning>
+  アンインストールするとスキルディレクトリ内のすべてのファイルが削除されます。この操作は元に戻せません。
+</Warning>
+
+## enable / disable
+
+スキルの有効化・無効化を行います。無効化されたスキルは Agent から呼び出されません。
+
+<CodeGroup>
+```text チャット
+/skill enable pptx
+/skill disable pptx
+```
+
+```bash ターミナル
+cow skill enable pptx
+cow skill disable pptx
+```
+</CodeGroup>
+
+## info
+
+インストール済みスキルの詳細情報を表示します。`SKILL.md` のプレビューを含みます。
+
+<CodeGroup>
+```text チャット
+/skill info pptx
+```
+
+```bash ターミナル
+cow skill info pptx
+```
+</CodeGroup>
+
+## スキルのソース
+
+インストールされたスキルはソース情報を記録しており、`/skill list` で確認できます：
+
+| ソース | 説明 |
+| --- | --- |
+| `builtin` | プロジェクト内蔵スキル |
+| `cowhub` | CowAgent Skill Hub からインストール |
+| `github` | GitHub URL から直接インストール |
+| `clawhub` | ClawHub からインストール |
+| `url` | SKILL.md URL からインストール |
+| `local` | ローカルで作成されたスキル |
diff --git a/docs/ja/guide/desktop.mdx b/docs/ja/guide/desktop.mdx
new file mode 100644
index 0000000..c7cc39a
--- /dev/null
+++ b/docs/ja/guide/desktop.mdx
@@ -0,0 +1,51 @@
+---
+title: デスクトップクライアント
+description: CowAgent デスクトップクライアント（macOS / Windows）のダウンロードと使い方
+---
+
+CowAgent は、Agent の実行環境を内蔵したすぐに使えるデスクトップクライアントを提供しています。**Python や依存関係を手動でインストールする必要はありません**。ダウンロードしてインストールするだけで、ローカルでスーパー AI アシスタントを実行できます。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/desktop-chat-demo-en.png" alt="CowAgent デスクトップクライアント" />
+
+## ダウンロードとインストール
+
+<Card title="ダウンロードページへ" icon="download" href="https://cowagent.ai/download/">
+  macOS / Windows 用インストーラーをダウンロード
+</Card>
+
+<Tabs>
+  <Tab title="macOS">
+    1. [ダウンロードページ](https://cowagent.ai/download/) を開き、チップに合わせて選択します：
+       - Apple Silicon（M1/M2/M3/M4）：`arm64` 版をダウンロード
+       - Intel：`x64` 版をダウンロード
+    2. ダウンロードした `.dmg` を開き、CowAgent を「アプリケーション」フォルダにドラッグします。
+    3. Launchpad またはアプリケーションから CowAgent を起動します。
+  </Tab>
+  <Tab title="Windows">
+    1. [ダウンロードページ](https://cowagent.ai/download/) を開き、Windows インストーラー（`.exe`）をダウンロードします。
+    2. インストーラーを実行し、画面の指示に従います（インストール先を選択できます）。
+    3. デスクトップまたはスタートメニューから CowAgent を起動します。
+  </Tab>
+</Tabs>
+
+## 自動アップデート
+
+デスクトップクライアントには自動アップデート機能が組み込まれています。新しいバージョンがあると自動的に検出・通知され、左下のメニューから手動で「アップデートを確認」してワンクリックでアップグレードすることもできます。
+
+## デスクトップとコマンドラインの違い
+
+- **デスクトップクライアント**：自分の PC での個人利用に最適。すぐに使え、GUI 操作で自動アップデート対応。
+- **コマンドラインデプロイ**：開発者やサーバーでの長期運用に最適で、カスタマイズ性が高い。詳しくは [クイックスタート](/ja/guide/quick-start) を参照。
+
+## ブラウザからのアクセス
+
+デスクトップクライアントは起動するとローカルでポート `9876` をリッスンし、そのバックエンドは Web コンソールとまったく同じです。そのため、アプリを開いている間はブラウザで `http://localhost:9876` にアクセスすれば、クライアント UI と同じ完全な体験が得られます。
+
+## ローカルデータの保存
+
+デスクトップクライアントのすべてのデータはお使いのマシンに保存されます：
+
+- **設定ディレクトリ**：ホームフォルダの `~/.cow`。`config.json`（モデルキーやチャネルなどの設定）のほか、ログ・キャッシュなどの実行データが含まれます。
+- **ワークスペース**：デフォルトは `~/cow`。会話履歴・ナレッジベース・記憶・スキル・定期タスクなど、Agent が生成したファイルが保存されます。
+
+クライアントをアンインストールしてもこの 2 つのディレクトリは自動削除されないため、再インストール後もデータは保持されます。完全に削除したい場合や別のデバイスへ移行する場合は、該当するフォルダを手動でバックアップまたは削除してください。
diff --git a/docs/ja/guide/manual-install.mdx b/docs/ja/guide/manual-install.mdx
new file mode 100644
index 0000000..f696ef8
--- /dev/null
+++ b/docs/ja/guide/manual-install.mdx
@@ -0,0 +1,148 @@
+---
+title: 手動インストール
+description: CowAgentの手動デプロイ（ソースコード / Docker）
+---
+
+## ソースコードによるデプロイ
+
+### 1. プロジェクトをクローン
+
+```bash
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
+```
+
+<Tip>
+  ネットワークに問題がある場合は、ミラーを使用してください: https://gitee.com/zhayujie/CowAgent
+</Tip>
+
+### 2. 依存パッケージをインストール
+
+コア依存パッケージ（必須）：
+
+```bash
+pip3 install -r requirements.txt
+```
+
+オプション依存パッケージ（推奨）：
+
+```bash
+pip3 install -r requirements-optional.txt
+```
+
+### 3. Cow CLI をインストール
+
+サービスとスキルを管理するためのコマンドラインツールをインストールします：
+
+```bash
+pip3 install -e .
+```
+
+インストール後、`cow` コマンドが使用可能になります：
+
+```bash
+cow help
+```
+
+<Note>
+  このステップは推奨です。インストール後、`cow start`、`cow stop`、`cow update` でサービスを管理でき、`cow skill` でスキルを管理できます。CLI をインストールしない場合は、`./run.sh` または `python3 app.py` で実行できます。
+</Note>
+
+### 4. 設定
+
+設定テンプレートをコピーして編集します：
+
+```bash
+cp config-template.json config.json
+```
+
+`config.json` にモデルの API キー、チャネルタイプ、その他の設定を入力します。詳細は[モデルのドキュメント](/ja/models/index)を参照してください。
+
+### 5. 実行
+
+**Cow CLI を使用して実行（推奨）：**
+
+```bash
+cow start
+```
+
+**またはローカルでフォアグラウンド実行：**
+
+```bash
+python3 app.py
+```
+
+デフォルトでは Web コンソールが起動します。`http://localhost:9899` にアクセスしてチャットできます。
+
+**サーバーでバックグラウンド実行（CLI 未使用時）：**
+
+```bash
+nohup python3 app.py & tail -f nohup.out
+```
+
+<Tip>
+  サーバーにデプロイする場合は、ファイアウォールまたはセキュリティグループでポート `9899` を開放して Web コンソールにアクセスできるようにしてください。セキュリティのため、特定の IP のみにアクセスを制限することを推奨します。
+</Tip>
+
+## Docker によるデプロイ
+
+Docker デプロイでは、ソースコードのクローンや依存パッケージのインストールは不要です。Agent モードを使用する場合は、より広範なシステムアクセスが可能なソースコードによるデプロイを推奨します。
+
+<Note>
+  [Docker](https://docs.docker.com/engine/install/) と docker-compose が必要です。
+</Note>
+
+**1. 設定ファイルをダウンロード**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+```
+
+`docker-compose.yml` を編集して設定を行います。
+
+**2. コンテナを起動**
+
+```bash
+sudo docker compose up -d
+```
+
+**3. ログを確認**
+
+```bash
+sudo docker logs -f chatgpt-on-wechat
+```
+
+<Tip>
+  サーバーにデプロイする場合は、ファイアウォールまたはセキュリティグループでポート `9899` を開放して Web コンソールにアクセスできるようにしてください。セキュリティのため、特定の IP のみにアクセスを制限することを推奨します。
+</Tip>
+
+## 主要な設定項目
+
+```json
+{
+  "channel_type": "web",
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "",
+  "agent": true,
+  "agent_workspace": "~/cow",
+  "agent_max_context_tokens": 40000,
+  "agent_max_context_turns": 30,
+  "agent_max_steps": 15,
+  "cow_lang": "auto"
+}
+```
+
+| パラメータ | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `channel_type` | チャネルタイプ | `web` |
+| `model` | モデル名 | `deepseek-v4-flash` |
+| `agent` | Agent モードを有効化 | `true` |
+| `agent_workspace` | Agent のワークスペースパス | `~/cow` |
+| `agent_max_context_tokens` | 最大コンテキストトークン数 | `40000` |
+| `agent_max_context_turns` | 最大コンテキストターン数 | `30` |
+| `agent_max_steps` | タスクごとの最大判断ステップ数 | `15` |
+| `cow_lang` | UI・コマンド文言・システムプロンプトなどの言語。`auto` で自動検出、`zh` / `en` も指定可 | `auto` |
+
+<Tip>
+  すべての設定オプションはプロジェクトの [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py) に記載されています。
+</Tip>
diff --git a/docs/ja/guide/quick-start.mdx b/docs/ja/guide/quick-start.mdx
new file mode 100644
index 0000000..a24c706
--- /dev/null
+++ b/docs/ja/guide/quick-start.mdx
@@ -0,0 +1,54 @@
+---
+title: ワンクリックインストール
+description: スクリプトによるCowAgentのワンクリックインストールと管理
+---
+
+本プロジェクトでは、ワンクリックでのインストール、設定、起動、管理を行うスクリプトを提供しています。素早くセットアップするには、スクリプトによるデプロイを推奨します。
+
+Linux、macOS、Windowsに対応しています。Python 3.7〜3.13が必要です（3.9を推奨）。
+
+## インストールコマンド
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+スクリプトは以下の手順を自動的に実行します：
+
+1. Python環境の確認（Python 3.7以上が必要）
+2. 必要なツールのインストール（git、curlなど）
+3. プロジェクトを `~/CowAgent` にクローン
+4. Pythonの依存パッケージと Cow CLI をインストール
+5. AIモデルとチャネルの対話式設定
+6. サービスの起動
+
+デフォルトでは、インストール後に Web コンソールが起動します。`http://localhost:9899` にアクセスしてチャットを開始できます。
+
+## 管理コマンド
+
+インストール後、`cow` コマンドでサービスを管理できます：
+
+| コマンド | 説明 |
+| --- | --- |
+| `cow start` | サービスを起動 |
+| `cow stop` | サービスを停止 |
+| `cow restart` | サービスを再起動 |
+| `cow status` | 実行状態を確認 |
+| `cow logs` | リアルタイムログを表示 |
+| `cow update` | コードを更新して再起動 |
+| `cow install-browser` | ブラウザツールの依存をインストール |
+
+詳細は[コマンドドキュメント](/ja/cli/index)を参照してください。
+
+<Note>
+  `cow` コマンドが利用できない場合は、`./run.sh <コマンド>`（Linux/macOS）または `.\scripts\run.ps1 <コマンド>`（Windows）で代替できます。機能は同等です。
+</Note>
diff --git a/docs/ja/guide/upgrade.mdx b/docs/ja/guide/upgrade.mdx
new file mode 100644
index 0000000..22f0ccd
--- /dev/null
+++ b/docs/ja/guide/upgrade.mdx
@@ -0,0 +1,67 @@
+---
+title: アップデート
+description: CowAgent のアップグレード方法
+---
+
+## コマンドによるアップグレード（推奨）
+
+`cow update` でコードの更新とサービスの再起動をワンクリックで実行できます：
+
+```bash
+cow update
+```
+
+このコマンドは以下のフローを自動的に実行します：
+
+1. 最新コードをプル（`git pull`）
+2. 現在のサービスを停止
+3. Python 依存パッケージを更新
+4. CLI を再インストール
+5. サービスを起動
+
+<Note>
+  Cow CLI がインストールされていない場合は、`./run.sh update` でも同様の操作が可能です。
+</Note>
+
+## 手動アップグレード
+
+プロジェクトのルートディレクトリで以下を実行します：
+
+```bash
+git pull
+pip3 install -r requirements.txt
+pip3 install -e .
+```
+
+更新完了後、サービスを再起動します：
+
+```bash
+# Cow CLI を使用
+cow restart
+
+# または run.sh を使用
+./run.sh restart
+
+# または nohup で直接実行
+kill $(ps -ef | grep app.py | grep -v grep | awk '{print $2}')
+nohup python3 app.py & tail -f nohup.out
+```
+
+## Docker アップグレード
+
+`docker-compose.yml` があるディレクトリで以下を実行します：
+
+```bash
+sudo docker compose pull
+sudo docker compose up -d
+```
+
+<Tip>
+  アップグレード前に `config.json` 設定ファイルのバックアップを推奨します。Docker 環境でデータを保持する場合は、volume マウントでワークスペースディレクトリを永続化できます。
+</Tip>
+
+## デスクトップクライアントのアップグレード
+
+[デスクトップクライアント](/ja/guide/desktop)は自動アップデート機能を内蔵しており、新しいバージョンを自動的に確認して通知します。ワンクリックでダウンロードして再起動し、アップグレードを完了できます。
+
+最新バージョンは [ダウンロードページ](https://cowagent.ai/download/) からいつでも手動で入手することもできます。
diff --git a/docs/ja/intro/architecture.mdx b/docs/ja/intro/architecture.mdx
new file mode 100644
index 0000000..682b407
--- /dev/null
+++ b/docs/ja/intro/architecture.mdx
@@ -0,0 +1,87 @@
+---
+title: アーキテクチャ
+description: CowAgent 2.0 のシステムアーキテクチャとコア設計
+---
+
+CowAgent 2.0 は、シンプルなチャットボットから、自律的な思考、タスク計画、長期記憶、Skill の拡張性を備えた Agent アーキテクチャのスーパーインテリジェントアシスタントへと進化しました。
+
+## システムアーキテクチャ
+
+CowAgent のアーキテクチャは以下のコアモジュールで構成されています：
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/en/architecture.png" alt="CowAgent Architecture" />
+
+| モジュール | 説明 |
+| --- | --- |
+| **Plan** | ユーザーの意図を理解し、複雑なタスクをマルチステップの計画に分解、目標達成までツールを反復的に呼び出す |
+| **Memory** | 重要な情報をコアメモリとデイリーメモリとして自動永続化し、キーワードとベクトルのハイブリッド検索でセッション間の連続性を実現 |
+| **Knowledge** | トピック別に構造化された知識を整理。Agent が価値ある情報を Markdown ページとして自律的に整理し、インデックスと相互参照で成長するナレッジネットワークを構築 |
+| **Evolution** | 会話がアイドルになった後、隔離環境で自動レビューを実行。Skill を改善し、未完了のタスクを引き継ぎ、記憶と知識を補完して、日々の利用を通じて Agent を成長させる |
+| **Tools** | Agent が OS リソースにアクセスするための中核能力。ファイル読み書き、ターミナル、ブラウザ、スケジューラ、記憶検索、Web 検索など 10 以上の組み込みツール |
+| **Skills** | Skill の読み込み・管理。Skill Hub や GitHub からのワンクリックインストール、または会話を通じたカスタム Skill の作成をサポート |
+| **Models** | モデル層。OpenAI、Claude、Gemini、DeepSeek、MiniMax、GLM、Qwen など主要 LLM への統一アクセスを提供 |
+| **Channels** | メッセージチャネル層。Web コンソール、WeChat、Feishu、DingTalk、WeCom、公式アカウントなど複数チャネルを統一プロトコルでサポート |
+| **CLI** | コマンドラインシステム。ターミナルコマンド（`cow`）とチャットコマンド（`/`）で、プロセス管理、Skill インストール、設定変更、ナレッジベース管理などをサポート |
+
+## Agent モードのワークフロー
+
+Agent モードが有効な場合、CowAgent は以下のワークフローで自律的な Agent として動作します：
+
+1. **メッセージ受信** — チャネルを通じてユーザーの入力を受信
+2. **意図の理解** — タスク要件とコンテキストを分析
+3. **タスク計画** — 複雑なタスクを複数のステップに分解
+4. **ツール呼び出し** — 各ステップに適切なツールを選択・実行
+5. **記憶・ナレッジの更新** — 重要な情報を長期記憶に保存し、構造化された知識をナレッジベースに整理
+6. **結果の返却** — 実行結果をユーザーに送信
+
+## ワークスペースのディレクトリ構成
+
+Agent のワークスペースはデフォルトで `~/cow` にあり、システムプロンプト、記憶ファイル、Skill ファイルを格納しています：
+
+```
+~/cow/
+├── system.md          # Agent システムプロンプト
+├── user.md            # ユーザープロフィール
+├── MEMORY.md          # コアメモリ
+├── memory/            # 長期記憶ストレージ
+│   └── YYYY-MM-DD.md  # デイリーメモリ
+├── knowledge/         # パーソナルナレッジベース
+│   ├── index.md       # ナレッジインデックス
+│   └── <category>/    # トピック別ページ
+└── skills/            # カスタム Skill
+    ├── skill-1/
+    └── skill-2/
+```
+
+シークレットキーはセキュリティのため `~/.cow` ディレクトリに別途保存されます：
+
+```
+~/.cow/
+└── .env               # Skill 用のシークレットキー
+```
+
+## コア設定
+
+`config.json` で Agent モードのパラメータを設定します：
+
+```json
+{
+  "agent": true,
+  "agent_workspace": "~/cow",
+  "agent_max_context_tokens": 40000,
+  "agent_max_context_turns": 30,
+  "agent_max_steps": 15,
+  "cow_lang": "auto"
+}
+```
+
+| パラメータ | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `agent` | Agent モードの有効化 | `true` |
+| `agent_workspace` | ワークスペースのパス | `~/cow` |
+| `agent_max_context_tokens` | 最大コンテキストトークン数 | `40000` |
+| `agent_max_context_turns` | 最大コンテキストターン数 | `30` |
+| `agent_max_steps` | タスクあたりの最大判断ステップ数 | `15` |
+| `knowledge` | パーソナルナレッジベースの有効化 | `true` |
+| `self_evolution_enabled` | 自己進化の有効化（新規インストールではデフォルト有効） | `false` |
+| `cow_lang` | UI・コマンド文言・システムプロンプトなどの言語。`auto` で自動検出、`zh` / `en` も指定可 | `auto` |
diff --git a/docs/ja/intro/features.mdx b/docs/ja/intro/features.mdx
new file mode 100644
index 0000000..0e509ea
--- /dev/null
+++ b/docs/ja/intro/features.mdx
@@ -0,0 +1,145 @@
+---
+title: 機能詳細
+description: CowAgent の長期記憶、タスク計画、Skill システム、CLI コマンド、ブラウザツールの詳細
+---
+
+## 1. 長期記憶
+
+記憶システムにより、Agent は重要な情報を長期にわたって記憶できます。三層記憶フローを採用：会話コンテキスト（短期）→ デイリーメモリ（中期）→ MEMORY.md（長期）、完全な記憶ライフサイクルを形成します。
+
+初回起動時、Agent はユーザーに重要な情報を自発的に尋ね、ワークスペース（デフォルト `~/cow`）に記録します。これには Agent の設定、ユーザーの身元情報、記憶ファイルが含まれます。
+
+その後の長期的な会話において、Agent は必要に応じてインテリジェントに記憶を保存・取得し、自身の設定やユーザーの好み、記憶ファイルを継続的に更新します。毎日 **Deep Dream（夢境蒸留）** が自動実行され、散在するデイリーメモリを精製された長期記憶に統合し、ナラティブスタイルの夢日記を生成します。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+これに加えて、**自己進化（Self-Evolution）** により Agent は日々の利用を通じて成長し続けます。会話がアイドルになった後に自動でレビューを行い、Skill を改善し、未完了のタスクを引き継ぎ、記憶と知識を補完します。実際に変更があったときのみ簡潔に通知し、変更はいつでも取り消せます。新規インストールではデフォルトで有効です。
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-demo.png" width="800" />
+</Frame>
+
+詳細は [長期記憶](/ja/memory)、[Deep Dream](/ja/memory/deep-dream)、[自己進化](/ja/memory/self-evolution) を参照してください。
+
+## 2. パーソナルナレッジベース
+
+> ナレッジベースシステムにより、Agent は構造化された知識を継続的に蓄積・整理できます。時系列で記録されるメモリとは異なり、ナレッジベースはトピック別に整理され、記事、会話からの洞察、学習資料などを相互にリンクされた Markdown ページとして整理し、継続的に成長するナレッジネットワークを形成します。
+
+Agent は会話中に価値ある情報を自動的にナレッジページとして整理し、相互参照とインデックスを維持します。Web コンソールではドキュメントの閲覧とナレッジグラフの可視化が可能です。ナレッジはワークスペースの `~/cow/knowledge/` ディレクトリに保存されます。
+
+- **自動整理**：Agent が会話中に構造化された知識を自律的に抽出・整理し、インデックスと相互参照を維持
+- **ナレッジグラフ**：ページ間の相互参照から自動的にナレッジグラフを構築し、Web コンソールでインタラクティブな関係図として可視化
+- **チャット連携**：Agent の回答で参照されるナレッジドキュメントのリンクを Web コンソールで直接クリックして閲覧可能
+- **CLI 管理**：`/knowledge` コマンドで統計表示、ディレクトリ閲覧、`/knowledge on|off` で機能の切り替えが可能
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+詳細は [パーソナルナレッジベース](/ja/knowledge) を参照してください。
+
+## 3. タスク計画とツール活用
+
+ツールは Agent がオペレーティングシステムのリソースにアクセスするための中核です。Agent はタスク要件に基づいてインテリジェントにツールを選択・呼び出し、ファイルの読み書き、コマンド実行、スケジュールタスクなどを実行します。組み込みツールはプロジェクトの `agent/tools/` ディレクトリに実装されています。
+
+**主なツール：** ファイルの読み書き・編集、Bash ターミナル、ブラウザ操作、ファイル送信、スケジューラ、記憶検索、Web 検索、環境設定など。
+
+### 3.1 ターミナルとファイルアクセス
+
+OS のターミナルとファイルシステムへのアクセスは、最も基本的かつ中核的な機能です。多くの他のツールや Skill はこの機能の上に構築されています。ユーザーはモバイルデバイスから Agent とやり取りし、パソコンやサーバーのリソースを操作できます：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+### 3.2 プログラミング能力
+
+プログラミングとシステムアクセスを組み合わせることで、Agent は完全な **Vibecoding ワークフロー** を実行できます。情報検索、アセット生成、コーディング、テスト、デプロイ、Nginx 設定、公開まで、すべてスマートフォンからの一つのコマンドで実行可能です：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
+</Frame>
+
+### 3.3 スケジュールタスク
+
+`scheduler` ツールにより動的なスケジュールタスクが可能で、**ワンタイムタスク、固定間隔、Cron 式**をサポートしています。タスクは**固定メッセージ送信**または **Agent 動的タスク**実行としてトリガーできます：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+### 3.4 ブラウザ操作
+
+組み込みの `browser` ツールにより、Agent は Chromium ブラウザを制御して Web ページへのアクセス、フォームの入力、要素のクリック、スクリーンショットの撮影が可能です。動的 JS レンダリングページにも対応しています。`cow install-browser` でワンコマンドインストール、サーバー（ヘッドレス）とデスクトップ環境に自動対応します：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
+</Frame>
+
+### 3.5 環境変数管理
+
+Skill が必要とするシークレットキーは環境変数ファイルに保存され、`env_config` ツールによって管理されます。会話を通じてシークレットを更新でき、セキュリティ保護とマスキング機能が組み込まれています：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
+
+## 4. Skill システム
+
+Skill システムは Agent に無限の拡張性を提供します。各 Skill は説明ファイル、実行スクリプト（任意）、リソース（任意）で構成され、特定のタイプのタスクを完了する方法を記述します。Skill により Agent は複雑なワークフローの指示に従い、ツールを呼び出し、サードパーティシステムと連携できます。
+
+- [Skill Hub](https://skills.cowagent.ai/)：オープンな Skill マーケットプレイス。公式推奨、コミュニティ、サードパーティの Skill を収録。ワンコマンドでインストール可能。
+- **組み込み Skill：** プロジェクトの `skills/` ディレクトリにあり、Skill クリエイター、画像認識、LinkAI Agent、Web フェッチなどが含まれます。組み込み Skill は依存条件（API キー、システムコマンドなど）に基づいて自動的に有効化されます。
+- **カスタム Skill：** ユーザーが会話を通じて作成し、ワークスペース（`~/cow/skills/`）に保存されます。あらゆる複雑なビジネスプロセスやサードパーティ連携を実装できます。
+
+Skill のインストール：`/skill install <名前>` または `cow skill install <名前>`。Skill Hub、GitHub、ClawHub、URL などからインストール可能。
+
+### 4.1 Skill の作成
+
+`skill-creator` Skill により、会話を通じて Skill を素早く作成できます。ワークフローを Skill としてコード化するよう Agent に依頼したり、API ドキュメントやサンプルを送信して Agent に直接連携を完成させることができます：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+### 4.2 Web 検索と画像認識
+
+- **Web 検索：** 組み込みの `web_search` ツールで、複数の検索エンジンをサポートします。`BOCHA_API_KEY` または `LINKAI_API_KEY` を設定して有効化してください。
+- **画像認識：** 組み込みの `openai-image-vision` Skill で、`gpt-4.1-mini`、`gpt-4.1` などのモデルをサポートします。`OPENAI_API_KEY` が必要です。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+### 4.3 Skill Hub
+
+[skills.cowagent.ai](https://skills.cowagent.ai/) で利用可能なすべての Skill を閲覧するか、会話内でコマンドを実行できます：
+
+```text
+/skill list --remote          # Skill Hub を閲覧
+/skill search <キーワード>     # Skill を検索
+/skill install <名前>          # ワンコマンドでインストール
+```
+
+GitHub、ClawHub、LinkAI などサードパーティプラットフォームの Skill もインストール可能です。詳細は [Skill のインストール](/ja/skills/install) を参照してください。
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+## 5. CLI コマンドシステム
+
+CowAgent はサービス管理、Skill インストール、設定変更などをカバーする2つのコマンドインターフェースを提供します：
+
+- **ターミナル CLI：** システムターミナルで `cow <コマンド>` を実行。`start`、`stop`、`restart`、`update`、`status`、`logs`、`skill` などをサポート。
+- **チャットコマンド：** 会話内で `/<コマンド>` を入力。Web コンソールでは `/` を入力するとコマンドメニューが表示されます。
+
+```bash
+cow start              # サービスを開始
+cow stop               # サービスを停止
+cow update             # 更新して再起動
+cow skill install pptx # Skill をインストール
+cow install-browser    # ブラウザツールをインストール
+```
+
+詳細は [コマンド一覧](https://docs.cowagent.ai/ja/cli) を参照してください。
diff --git a/docs/ja/intro/index.mdx b/docs/ja/intro/index.mdx
new file mode 100644
index 0000000..317e405
--- /dev/null
+++ b/docs/ja/intro/index.mdx
@@ -0,0 +1,89 @@
+---
+title: はじめに
+description: CowAgent - LLM を活用した AI スーパーアシスタント
+---
+
+<img src="https://cdn.link-ai.tech/doc/78c5dd674e2c828642ecc0406669fed7.png" alt="CowAgent" width="600px"/>
+
+**CowAgent** は、自律的なタスク計画、長期記憶、Skill システム、マルチモーダルメッセージ、複数モデル対応、マルチプラットフォームデプロイを備えた、LLM を活用した AI スーパーアシスタントです。
+
+CowAgent は自ら思考しタスクを計画し、コンピュータや外部リソースを操作し、Skill を作成・実行し、長期記憶により継続的に成長します。複数モデルの柔軟な切り替えをサポートし、テキスト、音声、画像、ファイルなどのマルチモーダルメッセージを処理でき、WeChat、Web、Feishu（飛書）、DingTalk（釘釘）、WeCom（企業微信）、WeChat公式アカウントに統合できます。お使いのパソコンやサーバー上で24時間365日稼働します。
+
+<Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
+  github.com/zhayujie/CowAgent
+</Card>
+
+## コア機能
+
+<CardGroup cols={2}>
+  <Card title="自律タスク計画" icon="brain" href="/ja/intro/architecture">
+    複雑なタスクを理解し、自律的に実行計画を立て、目標が達成されるまで思考とツール呼び出しを続けます。ツールを通じてファイルシステム、ターミナル、ブラウザ、スケジューラなどのシステムリソースにアクセスできます。
+  </Card>
+  <Card title="長期記憶" icon="database" href="/ja/memory">
+    三層記憶フロー（コンテキスト→デイリーメモリ→グローバルメモリ）、毎日 Deep Dream 蒸留で整理、キーワード検索とベクトル検索に対応。
+  </Card>
+  <Card title="ナレッジベース" icon="book" href="/ja/knowledge">
+    構造化された知識を自動整理し、ナレッジグラフの可視化をサポート。相互参照により継続的に成長するナレッジネットワークを構築します。
+  </Card>
+  <Card title="自己進化" icon="seedling" href="/ja/memory/self-evolution">
+    会話の終了後に自動でレビューし、Skill を改善し、未完了のタスクを引き継ぎ、記憶と知識を補完。日々の利用を通じて Agent が成長し続けます。
+  </Card>
+  <Card title="Skill システム" icon="puzzle-piece" href="/ja/skills/index">
+    Skill の作成・実行エンジンを実装し、組み込み Skill を搭載。自然言語の会話を通じてカスタム Skill の開発もサポートしています。
+  </Card>
+  <Card title="マルチモーダルメッセージ" icon="image" href="/ja/channels/web">
+    テキスト、画像、音声、ファイルなどのメッセージタイプの解析、処理、生成、送信をサポートします。
+  </Card>
+  <Card title="ツールシステム" icon="wrench" href="/ja/tools/index">
+    ファイル読み書き、ターミナル実行、ブラウザ操作、スケジュールタスク、メッセージ送信などの組み込みツールを提供。Agent が自律的にツールを呼び出して複雑なタスクを完了します。
+  </Card>
+  <Card title="コマンドシステム" icon="terminal" href="/ja/cli/index">
+    ターミナル CLI とチャット内コマンドを提供し、プロセス管理、Skill インストール、設定変更、コンテキスト確認などの一般的な操作をサポートします。
+  </Card>
+  <Card title="複数モデル対応" icon="microchip" href="/ja/models/index">
+    OpenAI、Claude、Gemini、DeepSeek、MiniMax、GLM、Qwen、Kimi、Doubao など、主要なモデルプロバイダーをサポートしています。
+  </Card>
+  <Card title="マルチプラットフォームデプロイ" icon="server" href="/ja/channels/weixin">
+    ローカルコンピュータやサーバー上で動作し、WeChat、Web、Feishu（飛書）、DingTalk（釘釘）、WeChat公式アカウント、WeCom（企業微信）アプリケーションに統合できます。
+  </Card>
+</CardGroup>
+
+## クイック体験
+
+ターミナルで以下のコマンドを実行すると、ワンクリックでインストール、設定、起動ができます：
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+デフォルトでは実行後に Web サービスが起動します。`http://localhost:9899/chat` にアクセスして Web インターフェースでチャットできます。
+
+<CardGroup cols={2}>
+  <Card title="クイックスタート" icon="rocket" href="/ja/guide/quick-start">
+    インストールと実行の完全ガイド
+  </Card>
+  <Card title="アーキテクチャ" icon="sitemap" href="/ja/intro/architecture">
+    CowAgent システムアーキテクチャ設計
+  </Card>
+</CardGroup>
+
+## 免責事項
+
+1. 本プロジェクトは [MIT License](https://github.com/zhayujie/CowAgent/blob/master/LICENSE) に基づき、技術研究および学習を目的としています。利用者は現地の法律、規制、ポリシー、および企業の社内規程を遵守する必要があります。違法行為や権利侵害につながる利用は禁止されています。
+2. Agent モードは通常のチャットモードよりも多くのトークンを消費します。効果とコストを考慮してモデルを選択してください。Agent はホスト OS にアクセスできるため、デプロイには十分注意してください。
+3. CowAgent はオープンソース開発に注力しており、いかなる暗号通貨の発行、認可、参加も行っておりません。
+
+## コミュニティ
+
+WeChat でアシスタントを追加して、オープンソースコミュニティに参加しましょう：
+
+<img width="140" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png" />
diff --git a/docs/ja/knowledge/index.mdx b/docs/ja/knowledge/index.mdx
new file mode 100644
index 0000000..f4a2abe
--- /dev/null
+++ b/docs/ja/knowledge/index.mdx
@@ -0,0 +1,89 @@
+---
+title: パーソナルナレッジベース
+description: CowAgent のパーソナルナレッジベース — 構造化された知識の蓄積、自動整理、ナレッジグラフ
+---
+
+パーソナルナレッジベースは、Agent の長期的な構造化知識ストレージで、ワークスペースの `knowledge/` ディレクトリに保存されます。タイムラインで整理されるメモリとは異なり、ナレッジベースはトピック別にコンテンツを整理します。記事、会話のインサイト、学習資料が相互リンクされた Markdown ページとして構造化され、継続的に成長するナレッジネットワークを形成します。
+
+## コアコンセプト
+
+### ナレッジ vs メモリ
+
+| 次元 | ナレッジベース（knowledge/） | 長期記憶（memory/） |
+| --- | --- | --- |
+| 整理方法 | トピック別、相互リンク | タイムライン順、日付ファイル |
+| 書き込み | Agent が能動的に構造化 | コンテキストトリミング時に自動要約 |
+| コンテンツ | 精製された構造化知識 | 生の会話要約 |
+| 用途 | 学習ノート、技術ドキュメント、プロジェクト知識 | 会話履歴、イベント記録 |
+
+### ディレクトリ構造
+
+```
+~/cow/knowledge/
+├── index.md          # ナレッジインデックス、全ページのエントリポイント
+├── log.md            # 変更ログ、各書き込みの記録
+├── concepts/         # 概念的な知識
+│   └── machine-learning.md
+├── entities/         # エンティティ知識（人物、組織、ツール）
+│   └── openai.md
+└── sources/          # ソース知識（記事、論文）
+    └── llm-wiki.md
+```
+
+ディレクトリ構造は柔軟です — Agent は実際のコンテンツに基づいて適切なカテゴリディレクトリを自動作成します。ユーザーが整理方法をカスタマイズすることも可能です。
+
+## 自動整理
+
+ナレッジの書き込みは Agent の自律的な動作で、以下のシナリオでトリガーされます：
+
+- **ユーザーが記事やドキュメントを共有** — Agent が自動的にキー情報を抽出し、構造化されたナレッジページを作成
+- **会話から価値ある結論が生まれた場合** — Agent がインサイトをナレッジページに整理し、既存の知識とリンク
+- **ユーザーが明示的に整理を要求** — ユーザーは会話を通じて Agent にナレッジの整理・更新を指示可能
+
+各ナレッジページには関連ページへの相互参照リンクが含まれ、ナレッジグラフを段階的に構築します。
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/3ce92f78-1863-4820-8fa8-660c0f2b7f09" alt="会話によるナレッジの取り込み" />
+</Frame>
+
+## ナレッジ検索
+
+Agent は会話中に以下の方法でナレッジを検索できます：
+
+- **インデックス参照** — `knowledge/index.md` で関連ページを素早く特定
+- **セマンティック検索** — `memory_search` ツールでナレッジコンテンツをセマンティック検索
+- **直接読み取り** — `memory_get` ツールで特定のナレッジファイルを読み取り
+
+## Web コンソール
+
+Web コンソールには専用の「ナレッジ」モジュールがあり、以下をサポートします：
+
+- **ドキュメント閲覧** — ツリー形式のディレクトリ構造、検索・折りたたみ可能、クリックでコンテンツ表示
+- **ナレッジグラフ** — インタラクティブなグラフによるナレッジ間の関係を可視化
+- **チャット連携** — Agent の返信で参照されたナレッジドキュメントリンクはクリックで直接ナビゲーション
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/b7b9d6be-0ac1-4c65-803b-2c6b36bd59a7" alt="ナレッジドキュメント閲覧" />
+</Frame>
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/44ae68ca-96cc-40b9-ab33-cdbec34c2379" alt="ナレッジグラフの可視化" />
+</Frame>
+
+## CLI コマンド
+
+`/knowledge` コマンドでナレッジベースを管理：
+
+| コマンド | 説明 |
+| --- | --- |
+| `/knowledge` | ナレッジベースの統計情報を表示 |
+| `/knowledge list` | ファイルディレクトリをツリー形式で表示 |
+| `/knowledge on` | ナレッジベース機能を有効化 |
+| `/knowledge off` | ナレッジベース機能を無効化 |
+
+## 設定
+
+| パラメータ | 説明 | デフォルト |
+| --- | --- | --- |
+| `knowledge` | パーソナルナレッジベースの有効/無効 | `true` |
+| `agent_workspace` | ワークスペースパス、ナレッジは `knowledge/` サブディレクトリに保存されます | `~/cow` |
diff --git a/docs/ja/memory/context.mdx b/docs/ja/memory/context.mdx
new file mode 100644
index 0000000..0ec3e7f
--- /dev/null
+++ b/docs/ja/memory/context.mdx
@@ -0,0 +1,81 @@
+---
+title: 短期記憶
+description: 会話コンテキスト — メッセージ管理、圧縮戦略、コンテキスト操作
+---
+
+会話コンテキストは Agent の短期記憶であり、現在のセッション内のすべてのメッセージ（ユーザー入力、Agent の返信、ツール呼び出しと結果）を含みます。適切なコンテキスト管理は、Agent の推論品質とコスト制御にとって重要です。
+
+## コンテキストの構造
+
+各会話ターンは以下で構成されます：
+
+```
+ユーザーメッセージ → Agent の思考 → ツール呼び出し → ツール結果 → ... → Agent の最終返信
+```
+
+1 つのターンには複数のツール呼び出しが含まれる場合があります（`agent_max_steps` で制御）。すべてのツール呼び出しと結果は、圧縮またはトリミングされるまでコンテキストに保持されます。
+
+## 主要な設定
+
+| パラメータ | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `agent_max_context_tokens` | コンテキストの最大トークン予算 | `50000` |
+| `agent_max_context_turns` | コンテキストの最大会話ターン数 | `20` |
+| `agent_max_steps` | ターンあたりの最大判断ステップ数（ツール呼び出し回数） | `15` |
+
+`config.json` またはチャットの `/config` コマンドで設定できます。
+
+## 圧縮戦略
+
+コンテキストが制限を超えた場合、システムは自動的に圧縮を実行してスペースを解放します。このプロセスには複数の段階があります：
+
+### 1. ツール結果の切り詰め
+
+各判断ループの開始前に、過去のターンのツール呼び出し結果を確認します。**20,000 文字** を超えるツール結果は切り詰められ、先頭と末尾のみが保持されます。現在のターンの結果は影響を受けません。
+
+### 2. ターンのトリミング
+
+会話ターン数が `agent_max_context_turns` を超えた場合：
+
+- **最も古い半分** の完全なターンがトリミングされます（ツール呼び出しチェーンの完全性を保証）
+- トリミングされたメッセージは LLM によって要約され、**日次記憶ファイルに書き込まれます**
+- LLM 要約が完了すると、保持されたコンテキストの最初のユーザーメッセージの先頭に要約が**注入**され、モデルが会話の文脈を維持できるようにします
+- 要約注入はバックグラウンドで非同期に実行され、次のターンから有効になります
+
+### 3. トークン予算のトリミング
+
+ターンのトリミング後、トークン数がまだ予算を超えている場合：
+
+- **5 ターン未満の場合**：すべてのターンで**テキスト圧縮**を実行 — 各ターンは最初のユーザーテキストと最後の Agent 返信のみを保持し、中間のツール呼び出しチェーンを削除
+- **5 ターン以上の場合**：**前半のターン**を再度トリミングし、破棄されたコンテンツも記憶に書き込まれ、コンテキスト要約も注入されます
+
+### 4. オーバーフロー緊急処理
+
+モデル API がコンテキストオーバーフローエラーを返した場合：
+
+1. 現在のすべてのメッセージを要約して記憶に書き込み
+2. 積極的なトリミングを適用（ツール結果は 10K 文字に制限、ユーザーテキストは 10K、最大 5 ターン）
+3. それでもオーバーフローする場合は、会話コンテキスト全体をクリア
+
+## セッションの永続化
+
+会話メッセージはローカルデータベースに永続化され、サービス再起動後に自動的に復元されます。復元戦略：
+
+- 最近の **`max(3, max_context_turns / 6)`** ターンを復元
+- 各ターンの**ユーザーテキストと Agent の最終返信のみ**を保持し、中間のツール呼び出しチェーンは復元しません
+- **30 日** を超える過去のセッションは自動的にクリーンアップされます
+
+## 操作コマンド
+
+チャットで以下のコマンドを使用してコンテキストを管理できます：
+
+| コマンド | 説明 |
+| --- | --- |
+| `/context` | 現在のコンテキスト統計を表示（メッセージ数、ロール分布、合計文字数） |
+| `/context clear` | 現在のセッションコンテキストをクリア |
+| `/config agent_max_context_tokens 80000` | コンテキストトークン予算を調整 |
+| `/config agent_max_context_turns 30` | コンテキストターン上限を調整 |
+
+<Tip>
+  コンテキストをクリアすると、Agent は以前の会話内容を「忘れます」。すでに長期記憶に書き込まれたコンテンツは、記憶検索を通じて引き続き取得できます。
+</Tip>
diff --git a/docs/ja/memory/deep-dream.mdx b/docs/ja/memory/deep-dream.mdx
new file mode 100644
index 0000000..dbd04a0
--- /dev/null
+++ b/docs/ja/memory/deep-dream.mdx
@@ -0,0 +1,106 @@
+---
+title: 夢境蒸留
+description: Deep Dream — 会話から永続記憶への自動蒸留メカニズム
+---
+
+夢境蒸留（Deep Dream）は CowAgent の記憶システムの中核的な整理メカニズムであり、散在する日次記憶を精錬された長期記憶に蒸留し、夢日記を生成します。
+
+## 記憶の流れ
+
+CowAgent の記憶は短期から長期まで 3 つの段階を経ます：
+
+```
+会話コンテキスト（短期）→ 日次記憶（中期）→ MEMORY.md（長期）
+```
+
+### 1. 会話 → 日次記憶
+
+会話コンテキストがトリミングされた時、または毎日のスケジュール要約時に、LLM が会話内容を重要イベントに要約し、日次記憶ファイル `memory/YYYY-MM-DD.md` に書き込みます。
+
+トリガー：
+- **コンテキストトリミング** — ターン数またはトークン制限を超えた時、トリミングされた内容が要約されます
+- **毎日のスケジュール** — 23:55 に自動トリガー
+- **API オーバーフロー** — 現在の会話要約の緊急保存
+
+### 2. 日次記憶 → MEMORY.md（蒸留）
+
+毎日の要約完了後、Deep Dream が自動的に蒸留を実行します：
+
+1. **材料の読み込み** — 現在の `MEMORY.md` + 当日の日次記憶
+2. **LLM 蒸留** — 重複排除、統合、剪定、新情報の抽出
+3. **MEMORY.md の上書き** — 精錬された長期記憶を出力
+4. **夢日記の生成** — 整理過程の発見と洞察を記録
+
+### 3. MEMORY.md の役割
+
+`MEMORY.md` は毎回の会話のシステムプロンプトに注入され、Agent がユーザーの好み、決定、重要な事実を常に把握できるようにします。そのため簡潔に保つ必要があり、Deep Dream は約 30 項目以内に制御します。
+
+## 蒸留ルール
+
+Deep Dream は以下の整理ルールに従います：
+
+| 操作 | 説明 |
+| --- | --- |
+| **統合・精錬** | 類似する複数の項目を 1 つの高密度な表現に統合 |
+| **新規抽出** | 日次記憶から好み、決定、人物、経験を抽出 |
+| **矛盾更新** | 新情報が古い項目と矛盾する場合、新情報を優先 |
+| **無効クリーン** | 一時的な記録、空白項目、フォーマット残留を削除 |
+| **冗長削除** | より精錬された表現でカバーされた古い項目を削除 |
+
+## 夢日記
+
+各蒸留で夢日記が生成され、`memory/dreams/YYYY-MM-DD.md` に保存されます。ナラティブスタイルで以下を記録します：
+
+- 発見された重複や矛盾
+- 日次記憶から抽出された新しい洞察
+- 実行されたクリーンアップと最適化
+- 全体的な観察
+
+夢日記は Web コンソールの「メモリ管理 → 夢日記」タブで確認できます。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## 手動トリガー
+
+毎日の自動実行に加えて、チャットで手動トリガーできます：
+
+```text
+/memory dream [N]
+```
+
+- `N`：直近 N 日間の記憶を整理（デフォルト 3 日、最大 30 日）
+- バックグラウンドで非同期に実行され、完了するとチャットで通知されます
+- Web 通知にはクリック可能なリンクが含まれ、MEMORY.md と夢日記を直接確認できます
+- Agent の初期化不要 — 最初の会話前でも使用可能
+
+<Tip>
+  初回デプロイ後は `/memory dream 30` を一度実行して、すべての履歴日次記憶を MEMORY.md に蒸留することをお勧めします。
+</Tip>
+
+## 設定スイッチ
+
+`config.json` の `deep_dream_enabled` で毎晩の自動蒸留を制御します：
+
+```json
+{
+  "deep_dream_enabled": true
+}
+```
+
+| 設定項目 | 説明 | デフォルト |
+| --- | --- | --- |
+| `deep_dream_enabled` | 毎日の定期蒸留の有効化 | `true` |
+
+デフォルトで有効になっており、既存の動作と互換性があります。無効にすると毎晩の自動蒸留が実行されなくなります。MEMORY.md を手動管理したい場合や LLM 呼び出しを 1 回節約したい場合に適しています（日次記憶の要約には影響しません）。手動コマンド `/memory dream` もこのスイッチの影響を受けず、いつでもトリガー可能です。
+
+## 安全メカニズム
+
+| メカニズム | 説明 |
+| --- | --- |
+| **コンテンツなしでスキップ** | 日次記憶がない場合、蒸留をスキップし空の上書きを回避 |
+| **入力重複排除** | スケジュールタスクで、入力材料が変更されていない場合自動スキップ |
+| **非同期実行** | 蒸留はバックグラウンドスレッドで実行、会話をブロックしない |
+| **順序保証** | スケジュールタスクで、日次フラッシュ完了後に蒸留を開始 |
+| **捏造禁止** | プロンプトで既存の材料のみに基づく整理を明示的に制約 |
diff --git a/docs/ja/memory/index.mdx b/docs/ja/memory/index.mdx
new file mode 100644
index 0000000..d01028f
--- /dev/null
+++ b/docs/ja/memory/index.mdx
@@ -0,0 +1,62 @@
+---
+title: 長期記憶
+description: CowAgent の長期記憶システム — ファイル永続化、自動書き込み、ハイブリッド検索
+---
+
+長期記憶はワークスペースのファイルに保存され、セッション間で永続化されます。Agent は会話中に検索ツールを通じて過去の記憶をオンデマンドで読み込み、コンテキストのトリミング時に会話の要約を自動的に長期記憶に書き込みます。
+
+<img src="https://cdn.link-ai.tech/doc/memory-architecture-en.jpg" alt="Memory Architecture" />
+
+## 記憶の種類
+
+### コア記憶（MEMORY.md）
+
+`~/cow/MEMORY.md` に保存され、長期的なユーザーの好み、重要な決定、主要な事実など、時間が経っても薄れない情報を含みます。Agent はツールを通じてこのファイルを読み書きし、長期的な知識を維持します。
+
+### 日次記憶（memory/YYYY-MM-DD.md）
+
+`~/cow/memory/` ディレクトリに保存され、日付で命名されます（例：`2026-03-08.md`）。日々の会話の要約と主要なイベントを記録します。空ファイルの生成を避けるため、最初の書き込み時にのみファイルが作成されます。
+
+### 夢日記（memory/dreams/YYYY-MM-DD.md）
+
+Deep Dream（記憶蒸留）プロセスの副産物で、各整理で発見された重複、統合操作、新しい洞察を記録します。`~/cow/memory/dreams/` ディレクトリに日付で命名されて保存されます。
+
+## 自動書き込み
+
+Agent は以下のメカニズムにより、会話内容を長期記憶に自動的に永続化します：
+
+- **コンテキストトリミング時** — 会話ターン数またはトークン数が設定上限を超えた場合、最も古い半分のコンテキストがトリミングされ、LLM によって要約されて日次記憶ファイルに書き込まれます。要約は保持されたコンテキストにも非同期で注入され、会話の連続性を維持します
+- **毎日のスケジュール要約** — 毎日 23:55 に自動的にフル要約がトリガーされ、アクティビティが少ない日でも記憶が保存されます（内容が変更されていない場合はスキップ）
+- [夢境蒸留（Deep Dream）](/ja/memory/deep-dream) — 毎日の要約完了後に自動実行され、日次記憶を MEMORY.md に蒸留し、夢日記を生成します
+- **API コンテキストオーバーフロー時** — モデル API がコンテキストオーバーフローエラーを返した場合、緊急措置として現在の会話要約が保存されます
+
+すべての記憶書き込みはバックグラウンドスレッドで非同期に実行され（LLM の要約 + ファイル書き込み）、通常の会話応答をブロックしません。
+
+## 関連ファイル
+
+ワークスペース（デフォルト `~/cow`）内の記憶関連ファイル：
+
+| ファイル | 説明 |
+| --- | --- |
+| `AGENT.md` | Agent のパーソナリティと動作設定 |
+| `USER.md` | ユーザーの身元情報と好み |
+| `RULE.md` | カスタムルールと制約 |
+| `MEMORY.md` | コア記憶（長期） |
+| `memory/YYYY-MM-DD.md` | 日次記憶（オンデマンドで作成） |
+| `memory/dreams/YYYY-MM-DD.md` | 夢日記（Deep Dream で自動生成） |
+
+## Web コンソール
+
+Web コンソールの記憶管理ページで、記憶ファイルと夢日記を閲覧できます。タブ切り替えに対応：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414171014.png" width="800" />
+</Frame>
+
+## 設定
+
+| パラメータ | 説明 | デフォルト |
+| --- | --- | --- |
+| `agent_workspace` | ワークスペースパス、記憶ファイルはこのディレクトリ配下に保存されます | `~/cow` |
+| `agent_max_context_tokens` | 最大コンテキストトークン数。超過時にトリミングされ、記憶として要約されます | `50000` |
+| `agent_max_context_turns` | 最大コンテキストターン数。超過時にトリミングされ、記憶として要約されます | `20` |
diff --git a/docs/ja/memory/self-evolution.mdx b/docs/ja/memory/self-evolution.mdx
new file mode 100644
index 0000000..7e81f5a
--- /dev/null
+++ b/docs/ja/memory/self-evolution.mdx
@@ -0,0 +1,78 @@
+---
+title: 自律進化
+description: Self-Evolution — 会話がアイドル状態になった後に振り返り、記憶を蓄積し、スキルを改善し、未完了のタスクに対応する
+---
+
+## 機能概要
+
+### はじめに
+
+自律進化（Self-Evolution）は、Agent が単発のタスクをこなすだけでなく、あなたとのやり取りを通じて成長し続けられるようにする仕組みです。会話が一段落すると、Agent は静かに振り返りを行います。覚えておくべきことを長期記憶に保存し、スキルで見つかった問題を修正し、やり残したタスクを引き継いで進めます。使い込むほど、Agent はあなたの好みを理解し、同じ失敗を繰り返さなくなり、自分から物事を仕上げるようになります。これらはすべてバックグラウンドで静かに行われ、実際に何かを行ったときだけ簡潔に知らせます。
+
+> 自律進化は[夢境蒸留](/ja/memory/deep-dream)と補完し合います。夢境蒸留が記憶そのものを整理するのに対し、自律進化はさらに一歩進んでスキルを改善し、未完了のタスクを前に進め、日々の利用を通じて Agent の能力を磨きます。
+
+### 3 つの目標
+
+自律進化は次の 3 つを軸に動きます：
+
+| 目標 | 説明 |
+| --- | --- |
+| **記憶の蓄積** | 会話中の重要な好み、決定、事実を記憶に補い、メインの会話の取りこぼしを補完します |
+| **スキルの改善** | スキルの利用中に問題（設定の誤りや手順の欠落など）が見つかったら、メモを残すだけでなくスキルファイルを直接修正します。必要に応じて新しいスキルも作成します |
+| **未完了タスクへの対応** | 会話に残ったやるべきことを見つけ、可能なときにその場で完了させます |
+
+振り返りが終わり、実際に変更を加えた場合は、Agent が「何を学び、どこを調整したか」を会話の中で一言で伝えるので、元に戻すかどうかを判断できます。
+
+## 使い方
+
+### トリガーのタイミング
+
+自律進化は定時実行ではなく、**会話が自然に終わってアイドル状態になった後**にのみ起動するため、進行中のやり取りを妨げることはありません。次の 2 つの条件を同時に満たす必要があります：
+
+- **会話がアイドル状態**：最後のやり取りから、設定したアイドル時間（デフォルトは 10 分）以上が経過している
+- **振り返るだけの内容がある**：前回の進化から十分なターン数が蓄積されている、またはコンテキストが容量の上限に近づいている
+
+両方の条件を満たしたときにのみ振り返りが始まります。これにより、振り返る価値のある内容を確保しつつ、会話の途中で邪魔をしないようにしています。
+
+### 関連設定
+
+自律進化は Web コンソールの「設定 → Agent 設定」（「ディープシンキング」の下）にあるスイッチで切り替えられるほか、設定ファイルで調整することもできます：
+
+| パラメータ | 説明 | デフォルト値 |
+| --- | --- | --- |
+| `self_evolution_enabled` | 自律進化を有効にするかどうか（新規インストールはデフォルトで有効） | `false` |
+| `self_evolution_idle_minutes` | 会話がアイドル状態になってからトリガーするまでの時間（分） | `10` |
+| `self_evolution_min_turns` | トリガーに必要な最小会話ターン数 | `6` |
+
+<Tip>
+  Web コンソールでは有効・無効のスイッチのみを提供しています。アイドル時間やターン数のしきい値を変更したい場合は、設定ファイルを編集してください。変更は即時に反映され、再起動は不要です。
+</Tip>
+
+### 進化の記録
+
+各振り返りは日付ごとに `memory/evolution/YYYY-MM-DD.md` に記録され、Web コンソールの「メモリ管理 → 自律進化」タブで確認できます。このタブには自律進化の記録と夢日記の両方がまとめられており、Agent の成長の軌跡を一箇所で振り返ることができます。
+
+### 元に戻す方法
+
+ある振り返りの変更に納得できない場合は、会話の中で Agent に「直前の変更を取り消して」と伝えるだけで、振り返り前のバックアップから該当ファイルを復元します。各振り返りはそれぞれ独立したバックアップを持つため、互いに干渉することはありません。
+
+## 設計
+
+自律進化はシステムの既存の機能を再利用しており、軽量に保たれています：
+
+- **隔離実行**：各振り返りは独立した短命のタスクとして実行されます。メインの会話と同じモデルを使いますが、ツールは制限されています（コンテキストの読み取りと、記憶およびスキルファイルの編集のみ可能）。メインの会話のコンテキストを汚さず、その動作にも影響しません。
+- **バックアップによる取り消し**：振り返り前に該当ファイルのスナップショットを取り、取り消し時にそのスナップショットから復元するため、すべての変更が追跡可能で元に戻せます。
+- **変更検知**：振り返り後にファイルのスナップショットを比較して実際に変更があったかを確認し、それをもとに通知するかどうかを判断します。これにより「何もしなければ通知しない」ことを仕組みとして保証します。
+
+### 抑制と安全性
+
+自律進化は、必要なときに動き、それ以外のときは邪魔をしないように設計されています：
+
+| 仕組み | 説明 |
+| --- | --- |
+| **何もしなければ通知しない** | 振り返りで実際の変更がなければ、静かなままで何も送りません |
+| **アイドル時のみトリガー** | 会話がアイドル状態になったときだけ実行し、進行中の会話を妨げません |
+| **変更を元に戻せる** | 振り返りごとに事前にバックアップを取るため、納得できない結果は取り消せます |
+| **組み込みスキルの保護** | 製品に付属する組み込みスキルは保護され、変更されません |
+| **ワークスペースに限定** | すべての読み書きはワークスペース内に限定され、他のシステムファイルには触れません |
+| **バックグラウンド実行** | 振り返りはバックグラウンドで実行され、通常の返信を妨げません |
diff --git a/docs/ja/models/claude.mdx b/docs/ja/models/claude.mdx
new file mode 100644
index 0000000..b9735cb
--- /dev/null
+++ b/docs/ja/models/claude.mdx
@@ -0,0 +1,51 @@
+---
+title: Claude
+description: Anthropic Claude モデル設定（テキスト対話 + 画像理解）
+---
+
+Claude は Anthropic が提供するモデルで、テキスト対話と画像理解をサポートします。主流の Sonnet / Opus モデルはネイティブにビジョンをサポートしており、別途 Vision モデルを指定する必要はありません。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "claude-sonnet-5",
+  "claude_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `claude-sonnet-5`、`claude-opus-4-8`、`claude-opus-4-7`、`claude-sonnet-4-6`、`claude-opus-4-6`、`claude-sonnet-4-5`、`claude-sonnet-4-0`、`claude-3-5-sonnet-latest` などをサポート。詳細は [公式モデル一覧](https://docs.anthropic.com/en/docs/about-claude/models/overview) を参照 |
+| `claude_api_key` | [Claude コンソール](https://console.anthropic.com/settings/keys) で作成 |
+| `claude_api_base` | 任意。デフォルトは `https://api.anthropic.com/v1`。サードパーティのプロキシに変更可能 |
+
+### モデル選択
+
+| モデル | 用途 |
+| --- | --- |
+| `claude-sonnet-5` | 最新フラッグシップ。デフォルト推奨モデルで、推論性能とコストのバランスが最も良い |
+| `claude-opus-4-8` | 前世代フラッグシップ。推論性能が最も高いが、価格は高め |
+| `claude-opus-4-7` | より以前の Opus フラッグシップ |
+| `claude-sonnet-4-6` | コストパフォーマンスと速度のバランスが良く、コストも低い |
+| `claude-opus-4-6` / `claude-sonnet-4-5` / `claude-sonnet-4-0` | より以前のフラッグシップ。価格はより安い |
+
+## 画像理解
+
+`claude_api_key` を設定すると、Agent の Vision ツールは Claude のメインモデルを使用して自動的に画像を認識します。追加設定は不要です。
+
+Vision モデルを手動で指定したい場合は、設定ファイルで明示的に指定できます：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "claude-sonnet-5"
+    }
+  }
+}
+```
diff --git a/docs/ja/models/coding-plan.mdx b/docs/ja/models/coding-plan.mdx
new file mode 100644
index 0000000..2447702
--- /dev/null
+++ b/docs/ja/models/coding-plan.mdx
@@ -0,0 +1,139 @@
+---
+title: Coding Plan
+description: Coding Planモデルの設定
+---
+
+> Coding Planは各プロバイダーが提供する月額サブスクリプションパッケージで、高頻度のAgent利用に最適です。CowAgentはOpenAI互換モードにより、すべてのCoding Planプロバイダーをサポートしています。
+
+<Note>
+  Coding PlanのAPI BaseとAPI Keyは、通常の従量課金制のものとは別になっています。各プロバイダーのプラットフォームから取得してください。
+</Note>
+
+## 共通設定
+
+すべてのプロバイダーはOpenAI互換プロトコルでアクセスでき、Webコンソールから素早く設定できます。モデルプロバイダーを**OpenAI**に設定し、カスタムモデルを選択してモデルコードを入力し、対応するプロバイダーのAPI BaseとAPI Keyを入力してください:
+
+<img src="https://cdn.link-ai.tech/doc/20260318113134.png" width="800"/>
+
+`config.json`で直接設定することも可能です:
+
+```json
+{
+  "bot_type": "openai",
+  "model": "MODEL_NAME",
+  "open_ai_api_base": "PROVIDER_CODING_PLAN_API_BASE",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `bot_type` | `openai`を指定（OpenAI互換モード） |
+| `model` | プロバイダーがサポートするモデル名 |
+| `open_ai_api_base` | プロバイダーのCoding Plan API Base URL |
+| `open_ai_api_key` | プロバイダーのCoding Plan API Key |
+
+---
+
+## 阿里云
+
+```json
+{
+  "bot_type": "openai",
+  "model": "qwen3.5-plus",
+  "open_ai_api_base": "https://coding.dashscope.aliyuncs.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `qwen3.5-plus`、`qwen3-max-2026-01-23`、`qwen3-coder-next`、`qwen3-coder-plus`、`glm-5`、`glm-4.7`、`kimi-k2.5`、`MiniMax-M2.5` |
+| `open_ai_api_base` | `https://coding.dashscope.aliyuncs.com/v1` |
+| `open_ai_api_key` | Coding Plan専用キー（従量課金とは共有不可） |
+
+参考: [クイックスタート](https://help.aliyun.com/zh/model-studio/coding-plan-quickstart?spm=a2c4g.11186623.help-menu-2400256.d_0_2_1.70115203zi5Igc)、[モデル一覧](https://help.aliyun.com/zh/model-studio/coding-plan)
+
+---
+
+## MiniMax
+
+```json
+{
+  "bot_type": "openai",
+  "model": "MiniMax-M3",
+  "open_ai_api_base": "https://api.minimaxi.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `MiniMax-M3`、`MiniMax-M2.7`、`MiniMax-M2.7-highspeed` |
+| `open_ai_api_base` | 中国: `https://api.minimaxi.com/v1`、グローバル: `https://api.minimax.io/v1` |
+| `open_ai_api_key` | Coding Plan専用キー（従量課金とは共有不可） |
+
+参考: [中国キー](https://platform.minimaxi.com/docs/coding-plan/quickstart)、[モデル一覧](https://platform.minimaxi.com/docs/guides/pricing-coding-plan)、[グローバルキー](https://platform.minimax.io/docs/coding-plan/quickstart)
+
+---
+
+## 智谱 GLM
+
+```json
+{
+  "bot_type": "openai",
+  "model": "glm-4.7",
+  "open_ai_api_base": "https://open.bigmodel.cn/api/coding/paas/v4",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `glm-5`、`glm-4.7`、`glm-4.6`、`glm-4.5`、`glm-4.5-air` |
+| `open_ai_api_base` | 中国: `https://open.bigmodel.cn/api/coding/paas/v4`、グローバル: `https://api.z.ai/api/coding/paas/v4` |
+| `open_ai_api_key` | 標準APIと共有 |
+
+参考: [中国クイックスタート](https://docs.bigmodel.cn/cn/coding-plan/quick-start)、[グローバルクイックスタート](https://docs.z.ai/devpack/quick-start)
+
+---
+
+## Kimi
+
+```json
+{
+  "bot_type": "moonshot",
+  "model": "kimi-for-coding",
+  "moonshot_base_url": "https://api.kimi.com/coding/v1",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `kimi-for-coding`で自動更新モデル、または`kimi-k2.6`などのモデルを指定 |
+| `moonshot_base_url` | `https://api.kimi.com/coding/v1` |
+| `moonshot_api_key` | Coding Plan専用キー（従量課金とは共有不可） |
+
+参考: [キー & ドキュメント](https://www.kimi.com/code/docs/)
+
+---
+
+## 火山引擎
+
+```json
+{
+  "bot_type": "openai",
+  "model": "Doubao-Seed-2.0-Code",
+  "open_ai_api_base": "https://ark.cn-beijing.volces.com/api/coding/v3",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `Doubao-Seed-2.0-Code`、`Doubao-Seed-2.0-pro`、`Doubao-Seed-2.0-lite`、`Doubao-Seed-Code`、`MiniMax-M2.5`、`Kimi-K2.5`、`GLM-4.7`、`DeepSeek-V3.2` |
+| `open_ai_api_base` | `https://ark.cn-beijing.volces.com/api/coding/v3` |
+| `open_ai_api_key` | 標準APIと共有 |
+
+参考: [クイックスタート](https://www.volcengine.com/docs/82379/1928261?lang=zh)
diff --git a/docs/ja/models/custom.mdx b/docs/ja/models/custom.mdx
new file mode 100644
index 0000000..3df7dc1
--- /dev/null
+++ b/docs/ja/models/custom.mdx
@@ -0,0 +1,62 @@
+---
+title: カスタム
+description: サードパーティ API プロキシやローカルモデル向けのカスタムプロバイダー設定
+---
+
+OpenAI 互換プロトコルで接続するモデルサービス向けの設定です。例えば：
+
+- **サードパーティ API プロキシ**：統一された API アドレスで複数のモデルを呼び出す
+- **ローカルモデル**：Ollama、vLLM などのツールでローカルにデプロイしたモデル
+- **プライベートデプロイ**：企業内部にデプロイされたモデルサービス
+
+## Web コンソールでの設定
+
+推奨方法です。Web コンソールの「モデル」ページで「プロバイダーを追加」をクリックし、「カスタム」を選択して、名称・API Base・API Key を入力します。複数のカスタムプロバイダーを追加でき、追加後は「メインモデル」でプロバイダーとモデルを選択すると有効になります。
+
+<img width="900" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-custom-model-config.png" />
+
+主なローカルデプロイツールのデフォルトアドレス：
+
+| ツール | デフォルト API Base |
+| --- | --- |
+| [Ollama](https://ollama.com) | `http://localhost:11434/v1` |
+| [vLLM](https://docs.vllm.ai) | `http://localhost:8000/v1` |
+| [LocalAI](https://localai.io) | `http://localhost:8080/v1` |
+
+## 設定ファイルでの設定
+
+`config.json` を直接編集することもできます。`custom_providers` リストに複数のプロバイダーを定義し、`bot_type` を `"custom:<id>"` に設定していずれかを有効化します：
+
+```json
+{
+  "bot_type": "custom:3f2a9c1b",
+  "custom_providers": [
+    {
+      "id": "3f2a9c1b",
+      "name": "プロバイダーA",
+      "api_key": "YOUR_API_KEY_A",
+      "api_base": "https://api.a.com/v1",
+      "model": "deepseek-v3"
+    },
+    {
+      "id": "a1b2c3d4",
+      "name": "プロバイダーB",
+      "api_key": "YOUR_API_KEY_B",
+      "api_base": "https://api.b.com/v1",
+      "model": "qwen3-max"
+    }
+  ]
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `custom_providers` | カスタムプロバイダーのリスト。各項目は `id`、`name`、`api_base`、`api_key`（任意）、`model`（任意）を含む |
+| `bot_type` | `"custom:<id>"` に設定して対応するプロバイダーを有効化 |
+| `id` | 一意の識別子（8 桁の 16 進数）。Web コンソールから追加すると自動生成され、手動設定の場合は重複しない任意の文字列でよい |
+| `name` | 表示名。自由に変更可能 |
+| `model` | このプロバイダーで使用するモデル。有効化時に適用される |
+
+<Note>
+  従来の単一プロバイダー設定（`bot_type` を `"custom"` にし、`custom_api_key` / `custom_api_base` を使用）は引き続き互換性があり、変更なしでそのまま利用できます。
+</Note>
diff --git a/docs/ja/models/deepseek.mdx b/docs/ja/models/deepseek.mdx
new file mode 100644
index 0000000..726520f
--- /dev/null
+++ b/docs/ja/models/deepseek.mdx
@@ -0,0 +1,72 @@
+---
+title: DeepSeek
+description: DeepSeek モデル設定（テキスト対話 + 思考モード）
+---
+
+DeepSeek は現在 Agent モードでデフォルト推奨されているベンダーの 1 つで、コストパフォーマンスの高いテキスト対話とタスクプランニング能力を主力としています。
+
+## テキスト対話
+
+```json
+{
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `deepseek-v4-flash`（デフォルト）、`deepseek-v4-pro` をサポート |
+| `deepseek_api_key` | [DeepSeek プラットフォーム](https://platform.deepseek.com/api_keys) で作成 |
+| `deepseek_api_base` | 任意。デフォルトは `https://api.deepseek.com/v1`。サードパーティのプロキシアドレスに変更可能 |
+
+### モデル選択
+
+| モデル | 用途 |
+| --- | --- |
+| `deepseek-v4-flash` | デフォルト推奨。高速かつ低コスト |
+| `deepseek-v4-pro` | より高い知能。複雑なタスクで効果が高い |
+
+## 思考モード
+
+V4 シリーズ（`deepseek-v4-flash` / `deepseek-v4-pro`）は明示的な「思考モード」をサポートしています：モデルは最終回答を出力する前に、まず思考連鎖（`reasoning_content`）を出力することで、回答の品質を向上させます。
+
+### スイッチ
+
+グローバル設定 `enable_thinking` で制御し、Web コンソールの設定ページからも切り替えできます：
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+- `true`：すべてのチャネルでモデルが先に思考してから回答します。Web コンソールでは思考過程が表示され、IM チャネル（WeChat / 企業 WeChat / DingTalk / Lark）では表示されませんが、同様により良い回答が得られます。
+- `false`：思考をオフにし、レスポンスが速くなり、初回トークン遅延が短くなります。
+
+### 推論強度
+
+思考モードでは `reasoning_effort` で推論の強さを制御できます：
+
+```json
+{
+  "enable_thinking": true,
+  "reasoning_effort": "high"
+}
+```
+
+| 値 | 用途 |
+| --- | --- |
+| `high`（デフォルト） | 日常的な Agent タスク。思考と速度のバランス |
+| `max` | 複雑なコーディング、長いプランニング、厳しい制約を伴うタスク。推論はより深いが、所要時間と出力トークンが増える |
+
+`reasoning_effort` は `enable_thinking` が `true` の場合のみ有効です。モデルが思考モードに対応していない場合、このフィールドは自動的に無視されます。
+
+### 動作の補足
+
+- **サンプリングパラメータ**：思考モードでは `temperature`、`top_p`、`presence_penalty`、`frequency_penalty` がサーバ側で無視されます（エラーにはなりません）。CowAgent は自動的にこれらの送信をスキップします。
+- **マルチターンのツール呼び出し**：履歴にツール呼び出しが含まれる場合、DeepSeek はすべての assistant メッセージで `reasoning_content` を返却することを要求します。CowAgent は返却ロジックを自動的に処理しており、ターンをまたいで思考スイッチを切り替えてもエラーにはなりません。
+
+<Tip>
+  デフォルトでは `deepseek-v4-flash` を使用します。複雑なタスクには `deepseek-v4-pro` を使用でき、深い推論が必要な場合は `enable_thinking` をオンにできます。
+</Tip>
diff --git a/docs/ja/models/doubao.mdx b/docs/ja/models/doubao.mdx
new file mode 100644
index 0000000..bb04abc
--- /dev/null
+++ b/docs/ja/models/doubao.mdx
@@ -0,0 +1,66 @@
+---
+title: Doubao
+description: Doubao（火山方舟）モデル設定（テキスト / 画像理解 / 画像生成 / ベクトル）
+---
+
+Doubao（火山方舟）はテキスト対話、画像理解、画像生成（Seedream）、ベクトル機能をサポートしており、1 つの `ark_api_key` ですべての機能を有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "doubao-seed-2-1-pro-260628",
+  "ark_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `doubao-seed-2-1-pro-260628`、`doubao-seed-2-1-turbo-260628`、`doubao-seed-2-0-pro-260215`、`doubao-seed-2-0-code-preview-260215` などを指定可能 |
+| `ark_api_key` | [火山方舟コンソール](https://console.volcengine.com/ark/region:ark+cn-beijing/apikey) で作成 |
+| `ark_base_url` | 任意。デフォルトは `https://ark.cn-beijing.volces.com/api/v3` |
+
+## 画像理解
+
+`ark_api_key` を設定し、メインモデルが Doubao 系の場合、Agent の Vision ツールは現在のメインモデルを自動的に使用して画像を認識します。追加設定は不要です。
+
+Vision モデルを手動で指定したい場合は：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "doubao-seed-2-1-pro-260628"
+    }
+  }
+}
+```
+
+## 画像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+選択可能なモデル：`seedream-5.0-lite`、`seedream-4.5`。
+
+## ベクトル
+
+```json
+{
+  "embedding_provider": "doubao",
+  "embedding_model": "doubao-embedding-vision-251215"
+}
+```
+
+デフォルトモデルは `doubao-embedding-vision-251215`（マルチモーダル embedding）です。設定ファイルで `embedding_dimensions` から 1024 または 2048 次元を指定できます。embedding を変更した後は `/memory rebuild-index` コマンドを実行してインデックスを再構築する必要があります。
diff --git a/docs/ja/models/gemini.mdx b/docs/ja/models/gemini.mdx
new file mode 100644
index 0000000..18f1125
--- /dev/null
+++ b/docs/ja/models/gemini.mdx
@@ -0,0 +1,59 @@
+---
+title: Gemini
+description: Google Gemini モデル設定（テキスト対話 + 画像理解 + 画像生成）
+---
+
+Google Gemini はテキスト対話、画像理解、画像生成（Nano Banana シリーズ）をサポートしており、1 つの `gemini_api_key` ですべての機能を有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "gemini-3.5-flash",
+  "gemini_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | 推奨は `gemini-3.5-flash`。`gemini-3.1-pro-preview`、`gemini-3.1-flash-lite-preview`、`gemini-3-flash-preview`、`gemini-3-pro-preview` などもサポート。詳細は [公式ドキュメント](https://ai.google.dev/gemini-api/docs/models) を参照 |
+| `gemini_api_key` | [Google AI Studio](https://aistudio.google.com/app/apikey) で作成 |
+| `gemini_api_base` | 任意。デフォルトは `https://generativelanguage.googleapis.com`。サードパーティのプロキシに変更可能 |
+
+## 画像理解
+
+Gemini の全シリーズモデルはネイティブにビジョンをサポートしています。`gemini_api_key` を設定すると、Agent の Vision ツールは自動的にメインモデルを使用して画像を認識します。追加設定は不要です。
+
+Vision モデルを手動で指定したい場合：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gemini-3.1-flash-lite-preview"
+    }
+  }
+}
+```
+
+## 画像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gemini-3.1-flash-image-preview"
+    }
+  }
+}
+```
+
+| モデル ID | エイリアス |
+| --- | --- |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `gemini-2.5-flash-image` | Nano Banana |
diff --git a/docs/ja/models/glm.mdx b/docs/ja/models/glm.mdx
new file mode 100644
index 0000000..bf3fb7b
--- /dev/null
+++ b/docs/ja/models/glm.mdx
@@ -0,0 +1,56 @@
+---
+title: Zhipu GLM
+description: Zhipu AI GLM モデル設定（テキスト / 画像理解 / 音声認識 / ベクトル）
+---
+
+Zhipu AI はテキスト対話、画像理解、音声認識（ASR）、ベクトル（Embedding）をサポートしており、1 つの `zhipu_ai_api_key` ですべての機能を有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "glm-5.2",
+  "zhipu_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `glm-5.2`、`glm-5.1`、`glm-5-turbo`、`glm-5`、`glm-4.7`、`glm-4-plus`、`glm-4-flash`、`glm-4-air` などを指定可能。詳細は [モデルコード](https://bigmodel.cn/dev/api/normal-model/glm-4) を参照 |
+| `zhipu_ai_api_key` | [Zhipu AI コンソール](https://www.bigmodel.cn/usercenter/proj-mgmt/apikeys) で作成 |
+| `zhipu_ai_api_base` | 任意。デフォルトは `https://open.bigmodel.cn/api/paas/v4` |
+
+## 画像理解
+
+Zhipu の chat 系モデル（`glm-5.2`、`glm-5.1`、`glm-5-turbo` など）はビジョンに対応していないため、ビジョン呼び出しは `glm-5v-turbo` に統一的にルーティングされます。`zhipu_ai_api_key` を設定すると、Agent の Vision ツールは自動的にこのモデルを使用するため、設定ファイルで明示的に指定する必要はありません。
+
+## 音声認識
+
+```json
+{
+  "voice_to_text": "zhipu",
+  "voice_to_text_model": "glm-asr-2512"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `voice_to_text` | `zhipu` に設定すると Zhipu ASR が有効になります |
+| `voice_to_text_model` | 任意。デフォルトは `glm-asr-2512` |
+
+認証情報は `zhipu_ai_api_key` を自動的に再利用します。音声ファイルは 25MB 未満を推奨します。サイズが大きすぎるファイルはサーバ側で拒否される可能性があります。
+
+## ベクトル
+
+```json
+{
+  "embedding_provider": "zhipu",
+  "embedding_model": "embedding-3"
+}
+```
+
+選択可能なモデル：`embedding-3`、`embedding-2`。embedding を変更した後は `/memory rebuild-index` コマンドを実行してインデックスを再構築する必要があります。
diff --git a/docs/ja/models/index.mdx b/docs/ja/models/index.mdx
new file mode 100644
index 0000000..5696ffd
--- /dev/null
+++ b/docs/ja/models/index.mdx
@@ -0,0 +1,45 @@
+---
+title: モデル概要
+description: CowAgent がサポートするモデルベンダーと機能マトリクス
+---
+
+CowAgent は国内外の主要ベンダーの大規模言語モデルをサポートしており、モデル接続の実装はプロジェクトの `models/` ディレクトリにあります。テキスト対話に加えて、一部のベンダーは画像理解、画像生成、音声認識、音声合成、ベクトルなどの機能も提供しており、Agent フローの中で必要に応じて呼び出すことができます。
+
+<Note>
+  Agent モードでは、効果とコストのバランスを考慮して以下のモデルの利用を推奨します：deepseek-v4-flash、MiniMax-M3、claude-sonnet-5、gemini-3.5-flash、glm-5.2、qwen3.7-plus、kimi-k2.7-code、ernie-5.1。
+
+  同時に [LinkAI](https://link-ai.tech) プラットフォームの API もサポートしており、1 つの Key で複数ベンダーを柔軟に切り替えられ、ナレッジベース、ワークフロー、プラグインなどの機能も付属しています。
+</Note>
+
+
+## モデル機能の全体像
+
+各ベンダーが提供する機能の一覧です。「テキスト」はメインの対話モデルを指し、その他の列はそのベンダーが対応する Agent 機能を担えるかを示します。
+
+| ベンダー | 代表モデル | テキスト | 画像理解 | 画像生成 | 音声認識 | 音声合成 | ベクトル |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [DeepSeek](/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [MiniMax](/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [Claude](/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [Gemini](/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [OpenAI](/models/openai) | gpt-5.5、o シリーズ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Zhipu GLM](/models/glm) | glm-5.2、glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [Tongyi Qianwen](/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Doubao](/models/doubao) | doubao-seed-2.1 シリーズ | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [Baidu Qianfan](/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [LinkAI](/models/linkai) | 複数ベンダー 100+ モデルを統一接続 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [カスタム](/models/custom) | ローカルモデル / サードパーティプロキシ | ✅ | | | | | |
+
+<Tip>
+  Web コンソール上では各機能（ビジョン / 画像 / 音声認識 / 音声合成 / ベクトル / Web 検索）ごとに独立してベンダーとモデルを設定でき、互いに強制的に紐付けされません。
+</Tip>
+
+
+## 設定方法
+
+**方法 1（推奨）:** [Web コンソール](/channels/web) からオンラインでモデルや各機能を管理でき、設定ファイルを手動で編集する必要はありません：
+
+<img width="900" src="https://cdn.link-ai.tech/doc/20260521212527.png" />
+
+**方法 2:** `config.json` を手動で編集し、選択したモデルに応じてモデル名と API Key を設定します。各モデルは OpenAI 互換方式での接続もサポートしており、`bot_type` を `openai` に設定し、`open_ai_api_base` と `open_ai_api_key` を設定すれば利用できます。
diff --git a/docs/ja/models/kimi.mdx b/docs/ja/models/kimi.mdx
new file mode 100644
index 0000000..e609218
--- /dev/null
+++ b/docs/ja/models/kimi.mdx
@@ -0,0 +1,41 @@
+---
+title: Kimi
+description: Kimi（Moonshot）モデル設定（テキスト対話 + 画像理解）
+---
+
+Kimi は Moonshot が提供するモデルで、テキスト対話と画像理解をサポートします。`kimi-k2.x` シリーズはネイティブにビジョンをサポートしています。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "kimi-k2.7-code",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `kimi-k2.7-code`、`kimi-k2.7-code-highspeed`、`kimi-k2.6`、`kimi-k2.5`、`kimi-k2`、`moonshot-v1-8k`、`moonshot-v1-32k`、`moonshot-v1-128k` を指定可能 |
+| `moonshot_api_key` | [Moonshot コンソール](https://platform.moonshot.cn/console/api-keys) で作成 |
+| `moonshot_base_url` | 任意。デフォルトは `https://api.moonshot.cn/v1` |
+
+## 画像理解
+
+`moonshot_api_key` を設定すると、Agent の Vision ツールは自動的に `kimi-k2.6` を使用して画像を認識します。追加設定は不要です。
+
+Vision モデルを手動で指定したい場合：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "kimi-k2.6"
+    }
+  }
+}
+```
diff --git a/docs/ja/models/linkai.mdx b/docs/ja/models/linkai.mdx
new file mode 100644
index 0000000..21a9f6c
--- /dev/null
+++ b/docs/ja/models/linkai.mdx
@@ -0,0 +1,103 @@
+---
+title: LinkAI
+description: LinkAI プラットフォーム経由でテキスト、ビジョン、画像、音声、ベクトル機能を統一接続
+---
+
+1 つの `linkai_api_key` で、OpenAI、Claude、Gemini、DeepSeek、MiniMax、Qwen、Kimi、Doubao など主要ベンダーのすべての機能にアクセスできます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "use_linkai": true,
+  "linkai_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `use_linkai` | `true` に設定すると有効になります |
+| `linkai_api_key` | [コンソール](https://link-ai.tech/console/interface) で作成 |
+| `model` | [モデル一覧](https://link-ai.tech/console/models) の任意のコードを指定可能 |
+
+詳細は [モデルサービス](https://link-ai.tech/console/models) を参照してください。
+
+## 画像理解
+
+設定が完了すると、Agent の Vision ツールは自動的にゲートウェイ上のマルチモーダルモデルを呼び出します。追加設定は不要です。Vision モデルを手動で指定したい場合：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+選択可能なモデル：`gpt-4.1-mini`、`gpt-5.4-mini`、`qwen3.7-plus`、`doubao-seed-2-1-pro-260628`、`kimi-k2.6`、`claude-sonnet-5`、`gemini-3.1-flash-lite-preview` など。
+
+## 画像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+| モデル ID | エイリアス |
+| --- | --- |
+| `gpt-image-2` | OpenAI |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `seedream-5.0-lite` | ByteDance Doubao Seedream |
+
+## 音声認識
+
+```json
+{
+  "voice_to_text": "linkai"
+}
+```
+
+ASR は固定で Whisper を使用します。認証情報は `linkai_api_key` を自動的に再利用します。
+
+## 音声合成
+
+音声合成ゲートウェイは複数の TTS エンジンをサポートしており、`text_to_voice_model` でエンジンを選択し、音色はエンジンに応じて切り替わります。
+
+```json
+{
+  "text_to_voice": "linkai",
+  "text_to_voice_model": "doubao",
+  "tts_voice_id": "BV001_streaming"
+}
+```
+
+| `text_to_voice_model` | エンジンの説明 |
+| --- | --- |
+| `tts-1` | OpenAI · 多言語汎用（音色 `alloy` / `nova` / `echo` など） |
+| `doubao` | ByteDance Doubao · 中国語の音色が豊富 |
+| `baidu` | Baidu · 中国語のアナウンサー音色 |
+
+エンジンによって対応する音色が異なるため、Web コンソールの「モデル管理 → 音声合成」から視覚的に選択することをおすすめします。
+
+## ベクトル
+
+```json
+{
+  "embedding_provider": "linkai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+デフォルトモデルは `text-embedding-3-small`（OpenAI 互換）です。embedding を変更した後は `/memory rebuild-index` コマンドを実行してインデックスを再構築する必要があります。
diff --git a/docs/ja/models/mimo.mdx b/docs/ja/models/mimo.mdx
new file mode 100644
index 0000000..c677810
--- /dev/null
+++ b/docs/ja/models/mimo.mdx
@@ -0,0 +1,135 @@
+---
+title: Xiaomi MiMo
+description: Xiaomi MiMo モデル設定（テキスト対話 + 画像理解 + 音声合成）
+---
+
+Xiaomi MiMo はネイティブ全モーダル大規模言語モデルです。1 つの `mimo_api_key` でテキスト対話、画像理解、音声合成を同時に有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "mimo-v2.5-pro",
+  "mimo_api_key": "YOUR_API_KEY",
+  "mimo_api_base": "https://api.xiaomimimo.com/v1"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | 推奨は `mimo-v2.5-pro`。`mimo-v2.5` も使用可能 |
+| `mimo_api_key` | [MiMo Open Platform](https://platform.xiaomimimo.com/console/api-keys) で作成 |
+| `mimo_api_base` | 任意。デフォルトは `https://api.xiaomimimo.com/v1` |
+
+### モデル選択
+
+| モデル | ユースケース |
+| --- | --- |
+| `mimo-v2.5-pro` | フラッグシップ。ネイティブ全モーダル + Agent 能力、最大 100 万トークンのコンテキスト |
+| `mimo-v2.5` | 汎用版。ネイティブ全モーダル（テキスト / 画像 / 動画 / 音声） |
+
+## 思考モード
+
+MiMo V2.5 シリーズはデフォルトで「思考モード」が有効です。最終回答の前に `reasoning_content`（思考過程）を出力することで、複雑なタスクのパフォーマンスを高めます。
+
+表示の有無はグローバル設定 `enable_thinking` で切り替え可能です（Web コンソールの設定ページからも変更できます）：
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+## 画像理解
+
+`mimo_api_key` を設定すると、Agent の Vision ツールは自動的に MiMo のビジョンモデルを利用します：
+
+- メインモデル自体がマルチモーダル（`mimo-v2.5-pro` / `mimo-v2.5`）の場合は、画像はメインモデルが直接処理し、追加設定は不要です。
+- メインモデルが他社製の場合、Vision ツールは順序に従い `mimo-v2.5-pro` にフォールバックします。
+
+特定の Vision モデルを強制したい場合は、設定ファイルで明示的に指定してください：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "provider": "mimo",
+      "model": "mimo-v2.5-pro"
+    }
+  }
+}
+```
+
+## 音声合成
+
+```json
+{
+  "text_to_voice": "mimo",
+  "text_to_voice_model": "mimo-v2.5-tts",
+  "tts_voice_id": "冰糖"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `text_to_voice_model` | 現在は `mimo-v2.5-tts` のみ対応（プリセット音色 + 歌唱モード） |
+| `tts_voice_id` | プリセット音色名（中国語の音色は中国語名がそのまま ID） |
+
+### プリセット音色
+
+| 音色 ID | 説明 |
+| --- | --- |
+| `冰糖` | 中国語 · 女声（デフォルト） |
+| `茉莉` | 中国語 · 女声 |
+| `苏打` | 中国語 · 男声 |
+| `白桦` | 中国語 · 男声 |
+| `Mia` | 英語 · 女声 |
+| `Chloe` | 英語 · 女声 |
+| `Milo` | 英語 · 男声 |
+| `Dean` | 英語 · 男声 |
+
+Web コンソールの「モデル管理 → 音声合成」のドロップダウンから視覚的に選択することもできます。
+
+### スタイル制御
+
+MiMo TTS は合成テキスト内に **音声タグ** を埋め込むことで、感情、語調、方言、キャラクター、さらには歌唱まで制御できます。タグは **最終的に音声合成されるテキスト（つまり Agent の返信内容）** に含める必要があり、全体スタイルのタグは先頭に置きます：
+
+```
+(スタイル)合成するテキスト
+```
+
+半角 `()`、全角 `（）`、`[]` の 3 種類の括弧に対応。スタイル記述は中国語・英語のどちらでも OK で、最も的確に表現できる言語を選んでください。代表的なスタイル例：
+
+| 種類 | サンプルタグ |
+| --- | --- |
+| 基本感情 | `happy` `sad` `angry` `fear` `surprised` `excited` `aggrieved` `calm` `indifferent` |
+| 複合感情 | `wistful` `relieved` `helpless` `guilty` `at ease` `uneasy` `touched` |
+| 全体トーン | `gentle` `aloof` `lively` `serious` `languid` `playful` `deep` `sharp` `cutting` |
+| 声質 | `magnetic` `mellow` `bright` `ethereal` `childlike` `aged` `sweet` `husky` |
+| キャラクター調 | `squeaky` `mature lady` `young boy` `uncle` `Taiwanese accent` |
+| 方言 | `Northeastern` `Sichuan` `Henan` `Cantonese` |
+| ロールプレイ | `Sun Wukong` `Lin Daiyu` |
+| 歌唱 | `sing` / `singing` |
+
+例：
+
+- `(magnetic)夜が深まり、街はまだ呼吸している。`
+- `(gentle)深呼吸して。きっと大丈夫。`
+- `(serious)これがシステム再起動前の最後の警告です。`
+- `(singing)Twinkle, twinkle, little star, how I wonder what you are…`
+
+テキストの任意の位置に細かい音声タグを挿入して、呼吸、笑い声、間などを制御することもできます。例：
+
+```
+(nervous, deep breath) ふぅ……落ち着いて、落ち着いて。(faster pace) 自己紹介は五十回練習したから大丈夫。
+```
+
+タグの完全な一覧は [MiMo 音声合成ドキュメント](https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/speech-synthesis-v2.5) を参照してください。
+
+<Tip>
+  CowAgent は TTS 呼び出し時、Agent の返信原文（`(...)` タグを含む）をそのまま MiMo に送信します。ペルソナ / システムプロンプトで「返信の冒頭に `(スタイル)` タグを付けて口調を指定する」よう指示すれば、IM チャネル（WeChat / Feishu / DingTalk / WeCom）の音声返信に感情・方言・歌唱などの効果を付与できます。
+</Tip>
diff --git a/docs/ja/models/minimax.mdx b/docs/ja/models/minimax.mdx
new file mode 100644
index 0000000..411619c
--- /dev/null
+++ b/docs/ja/models/minimax.mdx
@@ -0,0 +1,71 @@
+---
+title: MiniMax
+description: MiniMax モデル設定（テキスト / 画像理解 / 画像生成 / 音声合成）
+---
+
+MiniMax はテキスト対話、画像理解、画像生成、音声合成をサポートしており、1 つの `minimax_api_key` ですべての機能を有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "MiniMax-M3",
+  "minimax_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `MiniMax-M3`、`MiniMax-M2.7`、`MiniMax-M2.7-highspeed` などを指定可能 |
+| `minimax_api_key` | [MiniMax コンソール](https://platform.minimaxi.com/user-center/basic-information/interface-key) で作成 |
+
+## 画像理解
+
+MiniMax の M2.x シリーズの chat モデル自体はビジョンに対応していないため、ビジョン呼び出しは `MiniMax-Text-01` に統一的にルーティングされます。`minimax_api_key` を設定すると、Agent の Vision ツールは自動的にこのモデルを使用するため、設定ファイルで明示的に指定する必要はありません。
+
+## 画像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "image-01"
+    }
+  }
+}
+```
+
+選択可能なモデル：`image-01`。
+
+## 音声合成
+
+```json
+{
+  "text_to_voice": "minimax",
+  "text_to_voice_model": "speech-2.8-hd",
+  "tts_voice_id": "female-shaonv"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `text_to_voice_model` | `speech-2.8-hd`（感情表現、自然な聴感）、`speech-2.8-turbo`（高速）、`speech-2.6-hd`、`speech-2.6-turbo` |
+| `tts_voice_id` | 音色 ID。中国語 / 広東語 / 英語 / 日本語 / 韓国語をサポートし、合計 70 種類以上 |
+
+よく使われる音色の例：
+
+| 音色 ID | 説明 |
+| --- | --- |
+| `female-shaonv` | 中国語 · 少女（女性） |
+| `female-yujie` | 中国語 · お姉さま（女性） |
+| `female-tianmei` | 中国語 · 甘い女性（女性） |
+| `male-qn-jingying` | 中国語 · エリート青年（男性） |
+| `male-qn-badao` | 中国語 · 強気な青年（男性） |
+| `Cantonese_GentleLady` | 広東語 · 優しい女声 |
+| `English_Graceful_Lady` | 英語 · Graceful Lady |
+
+完全な音色リスト（中国語 / 広東語 / 英語 / 日本語 / 韓国語の合計 70 種類以上）は [システム音色一覧](https://platform.minimaxi.com/docs/faq/system-voice-id) を参照してください。Web コンソールの「モデル管理 → 音声合成」のドロップダウンから視覚的に選択することもできます。
diff --git a/docs/ja/models/openai.mdx b/docs/ja/models/openai.mdx
new file mode 100644
index 0000000..801c1fd
--- /dev/null
+++ b/docs/ja/models/openai.mdx
@@ -0,0 +1,103 @@
+---
+title: OpenAI
+description: OpenAI モデル設定（テキスト / ビジョン / 画像 / 音声 / ベクトル）
+---
+
+OpenAI は最も広範な機能をカバーするベンダーで、テキスト対話、画像理解、画像生成、音声認識（ASR）、音声合成（TTS）、ベクトル（Embedding）の各機能を同時に担えます。1 つの `open_ai_api_key` で Agent はすべての機能を利用できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+
+## テキスト対話
+
+```json
+{
+  "model": "gpt-5.5",
+  "open_ai_api_key": "YOUR_API_KEY",
+  "open_ai_api_base": "https://api.openai.com/v1"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | OpenAI API の [model パラメータ](https://platform.openai.com/docs/models) と同じです。`gpt-5.5`、`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano`、`gpt-5` シリーズ、`gpt-4.1`、o シリーズなどをサポート。Agent モードのデフォルトは `gpt-5.5`、コストパフォーマンスを重視する場合は `gpt-5.4` に変更可能 |
+| `open_ai_api_key` | [OpenAI プラットフォーム](https://platform.openai.com/api-keys) で作成 |
+| `open_ai_api_base` | 任意。サードパーティのプロキシに接続するために変更可能 |
+| `bot_type` | OpenAI 公式モデルを使用する場合は不要。互換プロトコルでベンダーモデルに接続する場合は `openai` に設定 |
+
+## 画像理解
+
+`gpt-5.5`、`gpt-5.4`、`gpt-4o`、`gpt-4.1` などの OpenAI モデルはネイティブにビジョンをサポートしています。`open_ai_api_key` を設定すると、Agent の Vision ツールは自動的にメインモデルを使用して画像を認識します。メインモデルがビジョンに対応していない場合や明示的に指定したい場合は、設定ファイルで指定できます：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+サポートする Vision モデル：`gpt-5.5`、`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano`、`gpt-5`、`gpt-4.1`、`gpt-4.1-mini`、`gpt-4o`。
+
+## 画像生成
+
+設定ファイルで画像生成モデルを指定すると、Agent が画像生成スキルを呼び出す際に自動的に OpenAI にルーティングされます：
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+サポートする画像生成モデル：`gpt-image-2`、`gpt-image-1`。
+
+## 音声認識
+
+```json
+{
+  "voice_to_text": "openai",
+  "voice_to_text_model": "gpt-4o-mini-transcribe"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `voice_to_text` | `openai` に設定すると OpenAI 音声認識が有効になります |
+| `voice_to_text_model` | 任意。デフォルトは `gpt-4o-mini-transcribe`。`gpt-4o-transcribe`、`whisper-1` も指定可能 |
+
+認証情報は `open_ai_api_key` を自動的に再利用します。
+
+## 音声合成
+
+```json
+{
+  "text_to_voice": "openai",
+  "text_to_voice_model": "tts-1",
+  "tts_voice_id": "alloy"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `text_to_voice_model` | `tts-1`、`tts-1-hd`、`gpt-4o-mini-tts` |
+| `tts_voice_id` | 音色：`alloy`、`echo`、`fable`、`onyx`、`nova`、`shimmer`、`ash`、`ballad`、`coral`、`sage`、`verse` |
+
+## ベクトル
+
+```json
+{
+  "embedding_provider": "openai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+選択可能なモデル：`text-embedding-3-small`、`text-embedding-3-large`、`text-embedding-ada-002`。embedding を変更した後は `/memory rebuild-index` コマンドを実行してインデックスを再構築する必要があります。
+
diff --git a/docs/ja/models/qianfan.mdx b/docs/ja/models/qianfan.mdx
new file mode 100644
index 0000000..4c3651f
--- /dev/null
+++ b/docs/ja/models/qianfan.mdx
@@ -0,0 +1,64 @@
+---
+title: Baidu Qianfan / ERNIE
+description: Baidu Qianfan ERNIE モデル設定
+---
+
+方法 1: 公式接続（推奨）:
+
+```json
+{
+  "model": "ernie-5.1",
+  "qianfan_api_key": "",
+  "qianfan_api_base": "https://qianfan.baidubce.com/v2"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | デフォルトの推奨は `ernie-5.1`。`ernie-5.0`、`ernie-x1.1`、`ernie-4.5-turbo-128k`、`ernie-4.5-turbo-32k` も利用できます |
+| `qianfan_api_key` | Qianfan API Key。通常は `bce-v3/` で始まります |
+| `qianfan_api_base` | 任意。デフォルトは `https://qianfan.baidubce.com/v2` |
+
+## モデル選択
+
+| モデル | 用途 |
+| --- | --- |
+| `ernie-5.1` | デフォルト推奨。文心の最新フラッグシップモデルで、総合性能が最も強い |
+| `ernie-5.0` | 前世代フラッグシップ。総合性能に優れる |
+| `ernie-x1.1` | 深層推論モデル。ハルシネーションが少なく、指示追従とツール呼び出しが強化 |
+| `ernie-4.5-turbo-128k` | 長いコンテキストと一般的なチャット向け |
+| `ernie-4.5-turbo-32k` | コンテキスト長とコストのバランスが良い一般チャット向け |
+
+## Vision ツール
+
+`qianfan_api_key` を設定すると、Agent モードの Vision ツールは Qianfan を自動検出します：
+
+- 主モデルが多モーダル（`ernie-5.1`、`ernie-5.0`、`ernie-x1.1`、`ernie-4.5-turbo-vl` など）の場合は、追加設定なしで主モデルがそのまま画像を処理します。
+- 主モデルがテキスト専用（`ernie-4.5-turbo-128k` など）の場合は、Vision ツールが自動的に `ernie-4.5-turbo-vl` にフォールバックします。
+
+特定の Vision モデルを強制したい場合は、`config.json` で明示的に指定できます：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "ernie-4.5-turbo-vl"
+    }
+  }
+}
+```
+
+方法 2: OpenAI 互換接続:
+
+```json
+{
+  "model": "ernie-5.1",
+  "bot_type": "openai",
+  "open_ai_api_key": "",
+  "open_ai_api_base": "https://qianfan.baidubce.com/v2"
+}
+```
+
+<Tip>
+  新しい設定では `qianfan_api_key` の利用を推奨します。既存の `wenxin`、`wenxin-4`、`baidu_wenxin_api_key`、`baidu_wenxin_secret_key` 設定は引き続き利用できます。
+</Tip>
diff --git a/docs/ja/models/qwen.mdx b/docs/ja/models/qwen.mdx
new file mode 100644
index 0000000..5ccc1f1
--- /dev/null
+++ b/docs/ja/models/qwen.mdx
@@ -0,0 +1,112 @@
+---
+title: Tongyi Qianwen Qwen
+description: Tongyi Qianwen モデル設定（テキスト / 画像理解 / 画像生成 / 音声認識 / 音声合成 / ベクトル）
+---
+
+Tongyi Qianwen（DashScope / Bailian）は国内で最も広範な機能をカバーするベンダーの 1 つで、テキスト、画像理解、画像生成、音声認識、音声合成、ベクトルの各機能を 1 つの `dashscope_api_key` で有効化できます。
+
+<Tip>
+  Web コンソールの「モデル管理」ページから、以下のすべての機能をワンストップで設定でき、設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## テキスト対話
+
+```json
+{
+  "model": "qwen3.7-plus",
+  "dashscope_api_key": "YOUR_API_KEY"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `model` | `qwen3.7-plus`、`qwen3.7-max`、`qwen3.6-plus`、`qwen3.5-plus`、`qwen3-max`、`qwen-max`、`qwen-plus`、`qwen-turbo`、`qwq-plus` などを指定可能 |
+| `dashscope_api_key` | [Bailian コンソール](https://bailian.console.aliyun.com/?tab=model#/api-key) で作成。詳細は [公式ドキュメント](https://bailian.console.aliyun.com/?tab=api#/api) を参照 |
+
+## 画像理解
+
+`dashscope_api_key` を設定すると、Agent の Vision ツールは自動的に Qwen のビジョンモデルを呼び出して画像を認識します。`qwen3.7-plus` / `qwen3.6-plus` / `qwen3.5-plus` / `qwen3-max` などのモデルはそのままマルチモーダルです。メインモデルがテキスト専用（`qwen-turbo` など）の場合は、自動的に `qwen-vl-max` にフォールバックします。
+
+Vision モデルを手動で指定したい場合：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "qwen3.7-plus"
+    }
+  }
+}
+```
+
+サポートするモデル：`qwen3.7-plus`、`qwen3.6-plus`、`qwen3.5-plus`、`qwen3-max`。
+
+## 画像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "qwen-image-2.0"
+    }
+  }
+}
+```
+
+選択可能なモデル：`qwen-image-2.0`、`qwen-image-2.0-pro`。
+
+## 音声認識
+
+```json
+{
+  "voice_to_text": "dashscope",
+  "voice_to_text_model": "qwen3-asr-flash"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `voice_to_text` | `dashscope` に設定すると Tongyi Qianwen ASR が有効になります |
+| `voice_to_text_model` | 任意。デフォルトは `qwen3-asr-flash` |
+
+認証情報は `dashscope_api_key` を自動的に再利用します。1 ファイルあたり 10MB 未満、長さ 300 秒以内を推奨します。
+
+## 音声合成
+
+```json
+{
+  "text_to_voice": "dashscope",
+  "text_to_voice_model": "qwen3-tts-flash",
+  "tts_voice_id": "Cherry"
+}
+```
+
+| パラメータ | 説明 |
+| --- | --- |
+| `text_to_voice_model` | 任意。デフォルトは `qwen3-tts-flash`。普通話、方言、主要な外国語をカバー |
+| `tts_voice_id` | 音色 ID。下記のよく使われる一覧を参照 |
+
+よく使われる音色の例：
+
+| 音色 ID | 説明 |
+| --- | --- |
+| `Cherry` | 芊悦 · 明るい女声 |
+| `Serena` | 苏瑶 · 優しい女声 |
+| `Ethan` | 晨煦 · 明るい男声 |
+| `Chelsie` | 千雪 · 二次元少女 |
+| `Dylan` | 北京語 · 晓东 |
+| `Rocky` | 広東語 · 阿强 |
+| `Sunny` | 四川語 · 晴儿 |
+
+完全な音色（普通話 / 各地の方言 / バイリンガルなど）は、Web コンソールの「モデル管理 → 音声合成」のドロップダウンから視覚的に選択できます。
+
+## ベクトル
+
+```json
+{
+  "embedding_provider": "dashscope",
+  "embedding_model": "text-embedding-v4"
+}
+```
+
+デフォルトモデルは `text-embedding-v4` です。embedding を変更した後は `/memory rebuild-index` コマンドを実行してインデックスを再構築する必要があります。
diff --git a/docs/ja/releases/overview.mdx b/docs/ja/releases/overview.mdx
new file mode 100644
index 0000000..5bb5391
--- /dev/null
+++ b/docs/ja/releases/overview.mdx
@@ -0,0 +1,36 @@
+---
+title: 変更履歴
+description: CowAgent バージョン更新履歴
+---
+
+| バージョン | 日付 | 説明 |
+| --- | --- | --- |
+| [2.1.3](/ja/releases/v2.1.3) | 2026.07.08 | デスクトップクライアント正式リリース（macOS / Windows）、ナレッジベースのドキュメント管理強化、MCP ツールのオンデマンド検索、繁体字中国語対応、新モデル追加（claude-sonnet-5、doubao-seed-2.1 など）、セキュリティ強化と改善 |
+| [2.1.2](/ja/releases/v2.1.2) | 2026.06.18 | Web コンソールの強化（定期タスク管理、ナレッジベースのカテゴリ、複数のカスタムモデルプロバイダー）、自己進化の改善、新モデル追加（kimi-k2.7-code、glm-5.2）、セキュリティ強化と改善 |
+| [2.1.1](/ja/releases/v2.1.1) | 2026.06.09 | 自己進化、Web コンソールの強化（メッセージ管理、マルチセッション並行）、クロスプラットフォーム対応の MCP 強化と並行呼び出し、新モデル追加（MiniMax-M3、qwen3.7-plus など）、各種改善 |
+| [2.1.0](/ja/releases/v2.1.0) | 2026.06.01 | 国際化対応、Telegram / Discord / Slack / WeChat カスタマーサービスチャネルの追加、CLI インタラクション強化（ストリーミング出力、コマンドあいまいマッチング、タスクキャンセル）、MCP Streamable HTTP、新モデル追加 |
+| [2.0.9](/ja/releases/v2.0.9) | 2026.05.22 | モデル管理機能の追加、MCP プロトコル対応、ブラウザログイン状態の永続化、新モデル追加（gpt-5.5、gemini-3.5-flash、qwen3.7-max など）、デプロイ・セキュリティ強化 |
+| [2.0.8](/ja/releases/v2.0.8) | 2026.05.06 | Feishu チャネル全面アップグレード（音声、ストリーミング出力と Markdown、QR コードによるワンクリック接続）、DeepSeek V4 と百度モデルの追加、スケジュールタスクツールの強化 |
+| [2.0.7](/ja/releases/v2.0.7) | 2026.04.22 | 画像生成スキル（6 プロバイダー自動ルーティング）、新モデル対応（Kimi K2.6、Claude Opus 4.7、GLM 5.1）、ナレッジベース強化、Web コンソール最適化 |
+| [2.0.6](/ja/releases/v2.0.6) | 2026.04.14 | プロジェクト名変更、ナレッジベースシステム、Deep Dream 記憶蒸留、コンテキストの賢い圧縮、Web コンソールのマルチセッションおよび複数の最適化 |
+| [2.0.5](/ja/releases/v2.0.5) | 2026.04.01 | Cow CLI、Skill Hub オープンソース化、ブラウザツール、WeCom QR コード作成、複数の最適化と修正 |
+| [2.0.4](/ja/releases/v2.0.4) | 2026.03.22 | 個人 WeChat チャネル追加、新モデル対応、日本語ドキュメント、スクリプトリファクタリングおよび複数の修正 |
+| [2.0.3](/ja/releases/v2.0.3) | 2026.03.18 | WeCom スマートボットおよび QQ チャネル追加、Coding Plan 対応、複数モデル追加、Web 側のファイル処理、メモリシステムアップグレード |
+| [2.0.2](/ja/releases/v2.0.2) | 2026.02.27 | Web コンソールアップグレード、マルチチャネル同時実行、セッション永続化 |
+| [2.0.1](/ja/releases/v2.0.1) | 2026.02.13 | Web Search ツール組み込み、スマートコンテキスト管理、複数の修正 |
+| [2.0.0](/ja/releases/v2.0.0) | 2026.02.03 | スーパー Agent アシスタントへの全面アップグレード |
+| 1.7.6 | 2025.05.23 | Web Channel 最適化、AgentMesh マルチエージェントプラグイン |
+| 1.7.5 | 2025.04.11 | DeepSeek モデル |
+| 1.7.4 | 2024.12.13 | Gemini 2.0 モデル、Web Channel |
+| 1.7.3 | 2024.10.31 | 安定性向上、データベース機能 |
+| 1.7.2 | 2024.09.26 | ワンクリックインストールスクリプト、o1 モデル |
+| 1.7.0 | 2024.08.02 | 讯飞 4.0 モデル、ナレッジベース参照 |
+| 1.6.9 | 2024.07.19 | gpt-4o-mini、アリババ音声認識 |
+| 1.6.8 | 2024.07.05 | Claude 3.5、Gemini 1.5 Pro |
+| 1.6.0 | 2024.04.26 | Kimi 接続、gpt-4-turbo アップグレード |
+| 1.5.8 | 2024.03.26 | GLM-4、Claude-3、edge-tts |
+| 1.5.2 | 2023.11.10 | Feishu チャネル、画像認識対話 |
+| 1.5.0 | 2023.11.10 | gpt-4-turbo、dall-e-3、tts マルチモーダル |
+| 1.0.0 | 2022.12.12 | プロジェクト作成、初の ChatGPT モデル接続 |
+
+その他の過去バージョンは [GitHub Releases](https://github.com/zhayujie/CowAgent/releases) をご覧ください。
diff --git a/docs/ja/releases/v2.0.0.mdx b/docs/ja/releases/v2.0.0.mdx
new file mode 100644
index 0000000..01be818
--- /dev/null
+++ b/docs/ja/releases/v2.0.0.mdx
@@ -0,0 +1,63 @@
+---
+title: v2.0.0
+description: CowAgent 2.0 - チャットボットから AI スーパーアシスタントへの全面アップグレード
+---
+
+CowAgent 2.0 は、チャットボットから **AI スーパーアシスタント** への包括的なアップグレードです。自律的な思考とタスク計画、長期記憶、コンピューターの操作、Skill の作成と実行が可能です。
+
+**リリース日**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)
+
+## 主な更新内容
+
+### Agent コア
+
+- **複雑なタスク計画**: マルチターン推論による自律的な計画
+- **長期記憶**: キーワードおよびベクトル検索による永続的な記憶
+- **組み込みツール**: ファイル操作、Bash、ブラウザ、スケジューラなど 10 以上のツール
+- **Web 検索**: 組み込みの `web_search` ツール、複数の検索エンジンに対応、対応する API キーを設定して使用
+- **Skill システム**: 組み込みおよびカスタム Skill をサポートする Skill エンジン
+- **セキュリティとコスト**: シークレット管理、プロンプト制御、トークン制限
+
+### その他
+
+- **チャネル**: 飞书/钉钉 WebSocket 対応、画像・ファイルメッセージ
+- **モデル**: claude-sonnet-4-5、gemini-3-pro-preview、glm-4.7、MiniMax-M2.1、qwen3-max
+- **デプロイ**: ワンクリックでのインストール、設定、実行、および管理スクリプト
+
+## 長期記憶
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+## タスク計画とツール
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+## Skill システム
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234350.png" width="750" />
+</Frame>
+
+## コントリビューション
+
+[フィードバックの送信](https://github.com/zhayujie/CowAgent/issues) や [コードのコントリビューション](https://github.com/zhayujie/CowAgent/pulls) を歓迎します。
diff --git a/docs/ja/releases/v2.0.1.mdx b/docs/ja/releases/v2.0.1.mdx
new file mode 100644
index 0000000..7de993b
--- /dev/null
+++ b/docs/ja/releases/v2.0.1.mdx
@@ -0,0 +1,36 @@
+---
+title: v2.0.1
+description: CowAgent 2.0.1 - 組み込み Web Search、スマートコンテキスト管理、複数の修正
+---
+
+**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)
+
+## 新機能
+
+- **組み込み Web Search ツール**: Web 検索を Agent の組み込みツールとして統合し、判断コストを削減 ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 モデル対応**: Claude Opus 4.6 モデルのサポートを追加 ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **企业微信の画像認識**: 企业微信チャネルでの画像メッセージ認識をサポート ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))
+
+## 改善
+
+- **スマートコンテキスト管理**: インテリジェントなコンテキストトリミング戦略により、チャットコンテキストのオーバーフローを解決し、トークン制限超過を防止 ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **ランタイム情報の動的更新**: 動的関数によるシステムプロンプト内のタイムスタンプおよびその他のランタイム情報の自動更新 ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill プロンプトの最適化**: Skill システムプロンプト生成を改善し、ツールの説明を簡素化して Agent のパフォーマンスを向上 ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **GLM カスタム API Base URL**: GLM モデルのカスタム API Base URL をサポート ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **起動スクリプトの最適化**: `run.sh` スクリプトのインタラクションと設定フローを改善 ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **判断ステップのログ記録**: デバッグ用の Agent 判断ステップログを追加 ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+
+## バグ修正
+
+- **Scheduler の記憶喪失**: Scheduler ディスパッチャーによる記憶喪失を修正 ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **空のツール呼び出しと長い結果**: 空のツール呼び出しおよび過度に長いツール結果の処理を修正 ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**: OpenAI モデルとの Function Call 互換性を修正 ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude ツール名フィールド**: Claude モデルのレスポンスから余分なツール名フィールドを削除 ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax 推論**: MiniMax モデルの推論コンテンツ処理を最適化し、思考プロセスの出力を非表示化 ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **GLM 思考プロセス**: GLM モデルの思考プロセス表示を非表示化 ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **飞书の接続と SSL**: 飞书チャネルの SSL 証明書エラーおよび接続問題を修正 ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type バリデーション**: 非文字列の `model_type` による `AttributeError` を修正 ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))
+
+## プラットフォーム互換性
+
+- **Windows 互換性**: 複数のツールモジュールにおける Windows でのパス処理、ファイルエンコーディング、および `os.getuid()` の利用不可問題を修正 ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
diff --git a/docs/ja/releases/v2.0.2.mdx b/docs/ja/releases/v2.0.2.mdx
new file mode 100644
index 0000000..ef9b3ee
--- /dev/null
+++ b/docs/ja/releases/v2.0.2.mdx
@@ -0,0 +1,98 @@
+---
+title: v2.0.2
+description: CowAgent 2.0.2 - Web Console アップグレード、マルチチャネル同時実行、セッション永続化
+---
+
+**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)
+
+## ハイライト
+
+### 🖥️ Web Console アップグレード
+
+Web Console が全面的にアップグレードされ、ストリーミング会話出力、ツール実行と推論プロセスの視覚的表示、**モデル、Skill、記憶、チャネル、Agent 設定** のオンライン管理が可能になりました。
+
+#### チャットインターフェース
+
+ストリーミング出力に対応し、Agent の推論プロセスとツール呼び出しをリアルタイムに表示することで、Agent の意思決定を直感的に観察できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### モデル管理
+
+設定ファイルを手動で編集せずに、モデル設定をオンラインで管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173811.png" />
+
+#### Skill 管理
+
+Agent の Skill をオンラインで表示・管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+#### 記憶管理
+
+Agent の記憶をオンラインで表示・管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+#### チャネル管理
+
+接続されたチャネルをオンラインで管理し、リアルタイムで接続・切断操作ができます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+#### スケジュールタスク
+
+ワンタイムタスク、固定間隔、Cron 式を含むスケジュールタスクをオンラインで表示・管理できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+#### ログ
+
+Agent のランタイムログをリアルタイムで表示し、監視とトラブルシューティングに活用できます：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
+
+関連コミット: [f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)
+
+### 🔀 マルチチャネル同時実行
+
+複数のチャネル（例：飞书、钉钉、企业微信、Web）を同時に実行できるようになりました。各チャネルは独立したスレッドで動作し、互いに干渉しません。
+
+設定方法: `config.json` の `channel_type` にカンマ区切りで複数のチャネルを設定するか、Web Console のチャネル管理ページからリアルタイムでチャネルの接続・切断を行います。
+
+```json
+{
+  "channel_type": "web,feishu,dingtalk"
+}
+```
+
+関連コミット: [4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)
+
+### 💾 セッション永続化
+
+セッション履歴がローカルの SQLite データベースに永続化されるようになりました。サービス再起動後も会話コンテキストが自動的に復元されます。Web Console の過去の会話も復元されます。
+
+関連コミット: [29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)
+
+## 新モデル
+
+- **Gemini 3.1 Pro Preview**: `gemini-3.1-pro-preview` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**: `claude-4.6-sonnet` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**: `qwen3.5-plus` モデルのサポートを追加 ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**: `Minimax-M2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**: `glm-5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**: `kimi-k2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**: コーディング特化型 `doubao-2.0-code` モデルを追加 ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope モデル**: 阿里云 DashScope モデル名のサポートを追加 ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))
+
+## ウェブサイトとドキュメント
+
+- **公式サイト**: [cowagent.ai](https://cowagent.ai/)
+- **ドキュメント**: [docs.cowagent.ai](https://docs.cowagent.ai/)
+
+## バグ修正
+
+- **Gemini 钉钉画像認識**: 钉钉チャネルで Gemini が画像マーカーを処理できない問題を修正 ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **起動スクリプトの依存関係**: `run.sh` スクリプトの依存関係インストール問題を修正 ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **bare except の整理**: より適切な例外処理のため `bare except` を `except Exception` に置換 ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
diff --git a/docs/ja/releases/v2.0.3.mdx b/docs/ja/releases/v2.0.3.mdx
new file mode 100644
index 0000000..0d03985
--- /dev/null
+++ b/docs/ja/releases/v2.0.3.mdx
@@ -0,0 +1,91 @@
+---
+title: v2.0.3
+description: CowAgent 2.0.3 - 企業微信スマートボットとQQチャネルの追加、Webコンソールファイル処理、メモリシステムのアップグレード
+---
+
+## 🔌 新規チャネル
+
+### 企業微信スマートボット
+
+企業微信スマートボット（`wecom_bot`）チャネルを追加しました。ストリーミングカードメッセージ出力、テキストと画像メッセージの送受信をサポートし、Webコンソールでチャネルの設定と管理が可能です。
+
+接続ドキュメント：[企業微信スマートボット接続](https://docs.cowagent.ai/channels/wecom-bot)。
+
+関連コミット：[d4480b6](https://github.com/zhayujie/CowAgent/commit/d4480b6), [a42f31f](https://github.com/zhayujie/CowAgent/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/CowAgent/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/CowAgent/commit/8b45d6c)
+
+### QQ チャネル
+
+QQ 公式ボット（`qq`）チャネルを追加しました。テキストと画像メッセージの送受信をサポートし、プライベートチャットとグループチャットに対応しています。
+
+接続ドキュメント：[QQボット接続](https://docs.cowagent.ai/channels/qq)。
+
+関連コミット：[005a0e1](https://github.com/zhayujie/CowAgent/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/CowAgent/commit/a4d54f5)
+
+## 🖥️ Web コンソールのファイル入力・処理対応
+
+Web コンソールのチャット画面でファイルや画像のアップロードが可能になり、Agent に直接ファイルを送信して処理できます。また、Read ツールに Office ドキュメント（Word、Excel、PPT）の解析機能を追加しました。
+
+関連コミット：[30c6d9b](https://github.com/zhayujie/CowAgent/commit/30c6d9b)
+
+## 🤖 新規モデル
+
+- **GPT-5.4 シリーズ**：`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` モデルのサポートを追加 ([1623deb](https://github.com/zhayujie/CowAgent/commit/1623deb))
+- **Gemini 3.1 Flash Lite Preview**：`gemini-3.1-flash-lite-preview` モデルのサポートを追加 ([ba915f2](https://github.com/zhayujie/CowAgent/commit/ba915f2))
+
+## 💰 Coding Plan サポート
+
+各ベンダーの Coding Plan（プログラミング月額プラン）への接続をサポートしました。OpenAI 互換方式で統一的に接続できます。現在、阿里雲、MiniMax、智譜 GLM、Kimi、火山エンジンなどのベンダーに対応しています。
+
+詳細設定は [Coding Plan ドキュメント](https://docs.cowagent.ai/models/coding-plan) を参照してください。
+
+## 🧠 メモリシステムのアップグレード
+
+メモリ書き込み（Memory Flush）のアップグレード：
+
+- LLM を使用してコンテキストウィンドウを超えた会話内容をインテリジェントに要約し、精製された日次メモリエントリを生成
+- 要約はバックグラウンドスレッドで非同期実行され、応答をブロックしない
+- コンテキストの一括トリミング戦略を最適化し、フラッシュ頻度を低減
+- 日次定期フラッシュのフォールバック機能を追加し、低アクティビティシナリオでのメモリ損失を防止
+- コンテキストメモリの損失問題を修正
+
+関連コミット：[022c13f](https://github.com/zhayujie/CowAgent/commit/022c13f), [c116235](https://github.com/zhayujie/CowAgent/commit/c116235)
+
+## 🔧 ツールリファクタリング
+
+- **画像認識**：画像認識（Image Vision）を Skill から内蔵 Tool にリファクタリングし、独立した画像ビジョンプロバイダー（Vision Provider）設定を追加。安定性と保守性を向上 ([a50fafa](https://github.com/zhayujie/CowAgent/commit/a50fafa), [3b8b562](https://github.com/zhayujie/CowAgent/commit/3b8b562))
+- **Webスクレイピング**：Webスクレイピング（Web Fetch）を Skill から内蔵 Tool にリファクタリング。リモートドキュメントファイル（PDF、Word、Excel、PPT）のダウンロードと解析をサポート ([ccb9030](https://github.com/zhayujie/CowAgent/commit/ccb9030), [fa61744](https://github.com/zhayujie/CowAgent/commit/fa61744))
+
+## 🐳 Docker デプロイメントの最適化
+
+- **設定テンプレートの整合**：`docker-compose.yml` の環境変数を `config-template.json` と整合し、モデル API Key と Agent 設定項目を完備
+- **Web コンソールポートマッピング**：`9899` ポートマッピングを追加。Docker デプロイ後にブラウザから Web コンソールにアクセス可能
+- **設定のホットリロード**：各モデル Bot の API Key と API Base をリアルタイム読み込みに変更。Web コンソールで設定変更後、再起動不要で即時反映
+- **ワークスペースの永続化**：`./cow` Volume マウントを追加。Agent ワークスペースデータ（メモリ、ペルソナ、スキルなど）をホストマシンに永続化し、コンテナの再構築やアップグレードでデータが失われない
+
+## ⚡ パフォーマンス最適化
+
+- **起動高速化**：飛書チャネルで依存関係の遅延読み込みを採用し、4-10秒の起動遅延を回避 ([924dc79](https://github.com/zhayujie/CowAgent/commit/924dc79))
+- **チャネルの安定性**：チャネル接続の安定性を最適化し、環境変数によるチャネル設定をサポート ([f1c04bc](https://github.com/zhayujie/CowAgent/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/CowAgent/commit/46d97fd))
+
+## 🐛 バグ修正
+
+- **bot_type 設定**：Agent モードでの `bot_type` 設定の受け渡し問題を修正 ([#2691](https://github.com/zhayujie/CowAgent/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
+- **bot_type 優先順位**：Agent モードでの `bot_type` の解析優先順位を調整 ([#2692](https://github.com/zhayujie/CowAgent/pull/2692)) Thanks [@6vision](https://github.com/6vision)
+- **智譜モデル設定**：智譜の `bot_type` 命名、Web コンソールの永続化、正規表現エスケープの問題を修正 ([#2693](https://github.com/zhayujie/CowAgent/pull/2693)) Thanks [@6vision](https://github.com/6vision)
+- **OpenAI 互換レイヤー**：`openai_compat` レイヤーによる統一エラー処理 ([#2688](https://github.com/zhayujie/CowAgent/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
+- **OpenAI 互換移行**：全モデル Bot の `openai_compat` 移行を完了 ([#2689](https://github.com/zhayujie/CowAgent/pull/2689))
+- **Gemini ツール呼び出し**：Gemini モデルのツール呼び出しマッチング問題を修正 ([eda82ba](https://github.com/zhayujie/CowAgent/commit/eda82ba))
+- **セッション並行処理**：セッション並行シナリオでの競合条件の問題を修正 ([9879878](https://github.com/zhayujie/CowAgent/commit/9879878))
+- **履歴メッセージの復元**：履歴セッションメッセージの不完全な問題を修正。user/assistant のテキストメッセージのみを復元し、ツール呼び出しを除外 ([b788a3d](https://github.com/zhayujie/CowAgent/commit/b788a3d), [a33ce97](https://github.com/zhayujie/CowAgent/commit/a33ce97))
+- **飛書グループチャット**：飛書グループチャットシナリオでの `bot_name` 依存を削除 ([b641bff](https://github.com/zhayujie/CowAgent/commit/b641bff))
+- **Safari 互換性**：Safari ブラウザでの IME Enter キーによるメッセージ誤送信の問題を修正 ([0687916](https://github.com/zhayujie/CowAgent/commit/0687916))
+- **Windows 互換性**：Windows での bash スタイル `$VAR` 環境変数を `%VAR%` に変換する問題を修正 ([7c67513](https://github.com/zhayujie/CowAgent/commit/7c67513))
+- **MiniMax パラメータ**：MiniMax モデルの `max_tokens` 制限を追加 ([1767413](https://github.com/zhayujie/CowAgent/commit/1767413))
+- **.gitignore 更新**：Python ディレクトリの無視ルールを追加 ([#2683](https://github.com/zhayujie/CowAgent/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
+- **AGENT.md の能動的進化**：システムプロンプトでの AGENT.md 更新ガイダンスを最適化。受動的な「ユーザーが変更した時に更新」から、会話中の性格やスタイルの変化を能動的に検出して自動更新するように改善
+
+## 📦 アップグレード方法
+
+ソースコードデプロイの場合は `./run.sh update` でワンクリックアップグレードできます。または手動でコードをプルして再起動してください。詳細は [アップデートドキュメント](https://docs.cowagent.ai/guide/upgrade) を参照。
+
+**リリース日**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.2...master)
diff --git a/docs/ja/releases/v2.0.4.mdx b/docs/ja/releases/v2.0.4.mdx
new file mode 100644
index 0000000..4965cae
--- /dev/null
+++ b/docs/ja/releases/v2.0.4.mdx
@@ -0,0 +1,55 @@
+---
+title: v2.0.4
+description: CowAgent 2.0.4 - 個人WeChat チャネルの追加、新モデルサポート、日本語ドキュメント、スクリプトリファクタリングおよび複数の修正
+---
+
+## 🔌 個人WeChat チャネルの追加
+
+個人WeChat（`weixin`）チャネルを追加しました。本バージョンの最も重要なアップデートです。QRコードをスキャンするだけで CowAgent を個人WeChatに接続でき、以下の機能をサポートします：
+
+- **メッセージ送受信**：テキスト、画像、ファイル、動画メッセージの送受信、音声メッセージの受信をサポート
+- **QRコードログイン**：ターミナルにQRコードを表示、WeChatでスキャンして確認するだけでログイン完了。QRコード期限切れ時は自動更新
+- **認証情報の永続化**：ログイン認証情報を `~/.weixin_cow_credentials.json` に自動保存、再起動時に再スキャン不要
+- **Session 自動再接続**：Session 期限切れ時に旧認証情報を自動クリアし、QRコードログインを再開
+- **Web コンソール接続**：Web コンソールからWeChatチャネルを追加可能、QRコードログインフローを同期表示
+- **Docker・スクリプト対応**：`run.sh` と `docker-compose.yml` がWeChat チャネルに対応
+
+接続ドキュメント：[WeChat 接続](https://docs.cowagent.ai/channels/weixin)。
+
+関連コミット：[ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869), [a483ec0](https://github.com/zhayujie/CowAgent/commit/a483ec0), [c1421e0](https://github.com/zhayujie/CowAgent/commit/c1421e0)
+
+## 🤖 新規モデル
+
+- **MiniMax-M2.7**：MiniMax-M2.7 モデルのサポートを追加
+- **GLM-5-Turbo**：智譜 glm-5-turbo モデルのサポートを追加
+
+関連コミット：[9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)
+
+## 🔧 スクリプトリファクタリング
+
+- **run.sh リファクタリング**：共通ロジックを抽出し、大量の重複コードを削除。スクリプトの行数を 600+ 行から 177 行に圧縮 ([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **実行権限**：`run.sh` ファイルの権限問題を修正 ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))
+
+## ⚡ 最適化
+
+- **リクエストヘッダー統一**：Agent の各サービス（Chat、Embedding、Vision、WebSearch 等）の外部リクエストに統一的な識別ヘッダーを追加 ([b4e711f](https://github.com/zhayujie/CowAgent/commit/b4e711f))
+- **メッセージ自動修復**：メッセージプロトコルのフォールトトレランスを強化し、フォーマット異常なメッセージシーケンスを自動修復 ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))
+
+## 🌍 日本語ドキュメント
+
+完全な日本語ドキュメントを追加しました。入門ガイド、チャネル接続、モデル設定などの主要セクションをカバーしています。Thanks [@Ikko Ashimine](https://github.com/ikoamu)
+
+関連コミット：[5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)
+
+## 🐛 バグ修正
+
+- **企業微信ボット互換性**：旧バージョンの `websocket-client` との互換性問題を修正し、統一的な WebSocket 互換レイヤーを追加 ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **run.sh PID 取得**：`run.sh` でのプロセス PID 取得エラーを修正 ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))
+- **飛書エンコーディング**：飛書チャネルのメッセージとログのエンコーディング問題を修正 ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **飛書設定**：`run.sh` での `feishu_bot_name` への冗長な依存を削除 ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))
+
+## 📦 アップグレード方法
+
+ソースコードデプロイの場合は `./run.sh update` でワンクリックアップグレードできます。または手動でコードをプルして再起動してください。詳細は [アップデートドキュメント](https://docs.cowagent.ai/guide/upgrade) を参照。
+
+**リリース日**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
diff --git a/docs/ja/releases/v2.0.5.mdx b/docs/ja/releases/v2.0.5.mdx
new file mode 100644
index 0000000..a55b3ac
--- /dev/null
+++ b/docs/ja/releases/v2.0.5.mdx
@@ -0,0 +1,77 @@
+---
+title: v2.0.5
+description: CowAgent 2.0.5 - Cow CLI、Skill Hub オープンソース、ブラウザツール、企業微信スキャン作成、その他改善
+---
+
+## 🖥️ Cow CLI コマンドシステム
+
+ターミナルと会話の両方で CowAgent を管理する新しい CLI コマンドシステム：
+
+- **ターミナルコマンド**：`cow <コマンド>` で `start`、`stop`、`restart`、`update`、`status`、`logs` などを実行
+- **チャットコマンド**：会話で `/<コマンド>` を入力して `/help`、`/status`、`/config`、`/skill`、`/context`、`/logs`、`/version` など
+- **Web コンソール**：入力欄で `/` を入力するとスラッシュコマンドメニューが表示、矢印キーで入力履歴を辿れる
+- **Windows サポート**：PowerShell スクリプト `scripts/run.ps1` を追加、`cow` コマンドに対応
+
+ドキュメント：[コマンド一覧](https://docs.cowagent.ai/ja/cli)
+
+<img src="https://cdn.link-ai.tech/doc/20260401114549.png" width="750" />
+
+## 🧩 Cow Skill Hub オープンソース
+
+[Cow Skill Hub](https://skills.cowagent.ai)（スキル広場）がオープンソースとして公開。AI Agent スキルの閲覧、検索、インストール、公開が可能：
+
+- **ワンコマンドインストール**：会話で `/skill install <名前>` またはターミナルで `cow skill install <名前>`
+- **マルチソース**：Skill Hub、GitHub、ClawHub、LinkAI などからインストール可能
+- **検索**：`/skill search` と `/skill list --remote` でスキル広場を閲覧・検索
+- **スキル公開**：[skills.cowagent.ai/submit](https://skills.cowagent.ai/submit) で自作スキルを提出
+- **ミラー加速**：中国国内向けミラーダウンロード対応
+
+オープンソースリポジトリ：[cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+ドキュメント：[スキル広場](https://docs.cowagent.ai/ja/skills/hub)、[スキルのインストール](https://docs.cowagent.ai/ja/skills/install)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+## 🌐 ブラウザツール
+
+新しい Browser ツール — Agent が Chromium ブラウザを制御して Web ページにアクセス・操作：
+
+- **ナビゲーションと操作**：`navigate`、`click`、`fill`、`select`、`scroll`、`press` など
+- **ページスナップショット**：精簡 DOM スナップショットで Agent がページ構造を効率的に理解、ナビゲーション後に自動スナップショット
+- **スクリーンショット**：ワークスペースにページのスクリーンショットを保存
+- **JavaScript 実行**：ページでカスタムスクリプトを実行
+- **CLI インストール**：`cow install-browser` でワンコマンドセットアップ
+- **Docker サポート**：Docker イメージにブラウザインストール組み込み
+
+ドキュメント：[ブラウザツール](https://docs.cowagent.ai/ja/tools/browser)
+
+<img src="https://cdn.link-ai.tech/doc/20260401115728.png" width="750" />
+
+## 🤖 企業微信 Bot スキャン作成
+
+企業微信 Bot チャネルで QR コードスキャンによるワンクリック作成をサポート：
+
+- **Web コンソールでスキャン**：「スキャン接入」モードを選択し、企業微信でスキャンするとボットが自動作成・接続
+- **手動モード**：既存の Bot ID と Secret を手動入力する方式も引き続きサポート
+- **ストリーム配信最適化**：WebSocket 混雑を避けるためのスロットリング
+
+ドキュメント：[企業微信 Bot](https://docs.cowagent.ai/ja/channels/wecom-bot)
+
+PR：[#2735](https://github.com/zhayujie/CowAgent/pull/2735)。Thanks [@WecomTeam](https://github.com/WecomTeam)
+
+## 🐛 その他の改善と修正
+
+- **DeepSeek モジュール**：独立 DeepSeek Bot、`deepseek_api_key` 専用設定対応（[#2719](https://github.com/zhayujie/CowAgent/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
+- **Web コンソール**：スラッシュコマンドメニュー、入力履歴、新モデル選択肢、モバイル最適化（[#2731](https://github.com/zhayujie/CowAgent/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
+- **コンテキスト**：トリミング後のコンテキスト喪失を修正（[393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0)）
+- **システムプロンプト**：毎ターン再構築されない問題を修正（[13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde)）
+- **Gemini**：GoogleGeminiBot の model 属性欠落を修正（[#2716](https://github.com/zhayujie/CowAgent/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
+- **WeChat チャネル**：ファイル送信失敗・ファイル名消失の修正（[6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba)、[45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c)）
+- **Docker**：ボリューム権限修正、イメージサイズ削減（[3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c)）
+- **セキュリティ**：Memory Content パストラバーサルリスクを修正。Thanks [@August829](https://github.com/August829)
+
+## 📦 アップグレード
+
+`cow update` または `./run.sh update` でアップグレード、またはコードを手動で pull して再起動。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。
+
+**リリース日**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
diff --git a/docs/ja/releases/v2.0.6.mdx b/docs/ja/releases/v2.0.6.mdx
new file mode 100644
index 0000000..d973fc2
--- /dev/null
+++ b/docs/ja/releases/v2.0.6.mdx
@@ -0,0 +1,83 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - ナレッジベース、Deep Dream 記憶蒸留、スマートコンテキスト圧縮、Web コンソールマルチセッションなど
+---
+
+## プロジェクト名を CowAgent に改称
+
+リポジトリが `chatgpt-on-wechat` から **CowAgent** に正式改称され、フル機能の AI Agent アシスタントへ進化しました。
+
+- 新アドレス：[github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent)、旧アドレスは GitHub が自動リダイレクト
+- CLI コマンド、設定ファイル、ドキュメントリンクはすべて互換性を維持、追加操作は不要
+
+## 📚 ナレッジベース
+
+新しいパーソナルナレッジベースシステム — Agent が構造化された知識を自律的に構築・維持し、会話中に必要に応じて検索・引用：
+
+- **インデックス駆動の自己組織構造**：ナレッジは `knowledge/` ディレクトリに保存、カテゴリ別に自動整理、各ナレッジページは独立した Markdown ファイル
+- **自動書き込み**：Agent にファイルやリンクなどの知識を送信、または会話で価値ある情報を識別した際にナレッジページを自動作成・更新
+- **ハイブリッド検索**：キーワード全文検索とベクトル意味検索をサポート、会話中に関連ナレッジをオンデマンドで読み込み
+- **ビジュアライゼーション**：ファイルツリー閲覧とナレッジグラフの可視化、ドキュメント内リンクで直接ナビゲーション
+- **コマンド管理**：`/knowledge` で統計表示、`/knowledge list` でディレクトリ構造、`/knowledge on|off` でオン・オフ
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+
+ドキュメント：[ナレッジベース](https://docs.cowagent.ai/ja/knowledge)
+
+## 🌙 Deep Dream 記憶蒸留
+
+散在する会話記憶を毎日自動的に精製された長期記憶へ蒸留する新しい記憶整理メカニズム：
+
+- **三層記憶フロー**：会話コンテキスト（短期）→ デイリーメモリ（中期）→ MEMORY.md（長期）、完全な記憶ライフサイクルを形成
+- **自動蒸留**：毎日 23:55 に定期実行、当日のデイリーメモリと MEMORY.md を読み取り、LLM で重複排除・統合・剪定を行い、精製された新しい MEMORY.md を出力
+- **夢日記**：各蒸留でナラティブスタイルの夢日記を生成、整理過程の発見と洞察を記録、`memory/dreams/` ディレクトリに保存
+- **手動トリガー**：`/memory dream [N]` で手動トリガー、整理日数を指定可能（デフォルト 3 日、最大 30 日）、完了後にチャットで通知
+- **Web コンソール**：記憶管理ページに「夢日記」タブを追加、すべての夢日記を閲覧可能
+
+ドキュメント：[Deep Dream](https://docs.cowagent.ai/ja/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 スマートコンテキスト圧縮
+
+コンテキストが上限を超えた場合、トリミング部分を LLM で要約し非同期で注入、会話の連続性を維持：
+
+- **LLM 非同期要約**：トリミングされたメッセージを LLM がキー情報に要約、デイリーメモリファイルへの書き込みと保持コンテキストへの注入を同時実行
+- **マルチモデル対応**：メインモデルを優先使用、Claude、OpenAI、MiniMax など異なるモデルのメッセージ形式要件に対応
+
+ドキュメント：[短期記憶](https://docs.cowagent.ai/ja/memory/context)
+
+## 💬 Web コンソールアップグレード
+
+Web コンソールの複数機能を強化：
+
+- **マルチセッション管理**：独立セッションの作成と切り替え、サイドバーにセッションリスト表示、タイトルの自動生成と手動編集をサポート
+- **パスワード保護**：`web_console_password` 設定でコンソールにログインパスワードを設定可能
+- **深い思考**：Web 端でモデルの思考プロセスを表示、`enable_thinking` 設定で制御
+- **定期プッシュ**：定期タスクの結果を Web コンソールにプッシュ
+- **メッセージコピー**：AI 回答バブルから元の Markdown コンテンツをワンクリックコピー
+- **言語切替**：上部の言語切替ボタンが現在の言語を表示するように改善、より直感的な操作
+
+## 🤖 モデル関連
+
+- **視覚認識の最適化**：画像認識ツールがメインモデルを優先使用、複数プロバイダーの自動フォールバック対応。ドキュメント：[ビジョンツール](https://docs.cowagent.ai/ja/tools/vision)
+- **MiniMax 新モデル**：MiniMax-M2.7-highspeed モデルと MiniMax TTS 音声合成サポートを追加。Thanks @octo-patch
+- **通義千問**：qwen3.6-plus モデルサポートを追加
+
+## 🐛 その他の改善と修正
+
+- **記憶プロンプト最適化**：`MEMORY.md` をシステムプロンプトにデフォルト注入、記憶検索と書き込みのトリガー条件を精緻化、主動的な書き込み能力を強化
+- **システムプロンプト**：システムプロンプトのスタイルとトーンガイダンスを最適化
+- **ブラウザツール**：暗黙的なインタラクティブ要素の検出を強化
+- **ファイル送信**：汎用ファイルタイプ（tar.gz、zip 等）が正しく送信されない問題を修正。Thanks @6vision
+- **macOS 互換性**：ネットワークプリチェックタイムアウトの互換性問題を修正。Thanks @Moliang Zhou
+- **Windows 互換性**：Windows での PowerShell 互換性、プロセス更新、ターミナルエンコーディングなどの問題を修正
+- **Python 3.13+**：Python 3.13 以降で `legacy-cgi` 依存関係が不足する問題を修正
+- **個人 WeChat**：個人 WeChat チャネルバージョンを更新
+
+## 📦 アップグレード
+
+`cow update` または `./run.sh update` でアップグレード、またはコードを手動で pull して再起動。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。
+
+**リリース日**：2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
diff --git a/docs/ja/releases/v2.0.7.mdx b/docs/ja/releases/v2.0.7.mdx
new file mode 100644
index 0000000..bcf4677
--- /dev/null
+++ b/docs/ja/releases/v2.0.7.mdx
@@ -0,0 +1,65 @@
+---
+title: v2.0.7
+description: CowAgent 2.0.7 - 画像生成スキル（6プロバイダー自動ルーティング）、新モデルサポート、ナレッジベース強化、Web コンソール改善およびバグ修正
+---
+
+## 🎨 画像生成スキル
+
+新しい内蔵スキル `image-generation` を追加。テキストから画像生成、画像編集、複数画像の融合に対応し、6 社の主要プロバイダーをカバー：
+
+- **6 プロバイダー自動ルーティング**：OpenAI (GPT-Image-2) → Gemini (Nano Banana) → Seedream (Volcengine Ark) → Qwen (DashScope) → MiniMax → LinkAI — 固定の優先順位で設定済みプロバイダーを自動選択、失敗時は次のプロバイダーへ自動フォールバック
+- **モデル選択不要**：API Key を設定するだけで使用可能、モデルを手動で指定する必要なし。会話で特定モデルを指名することも可能（例：「seedream で猫を描いて」）
+- **柔軟な制御**：`quality`（画質）、`size`（解像度、512/1K〜4K）、`aspect_ratio`（アスペクト比）パラメータ対応、各プロバイダーが自動的に有効な値にマッピング
+- **画像編集**：既存の画像を渡して編集・スタイル変換・複数画像融合が可能（Seedream は最大 14 枚の参照画像をサポート）
+- **スキルレベル設定**：`config.json` の `skills.image-generation.model` でデフォルトモデルを固定可能
+- **画像ライトボックス**：Web コンソールのすべての画像がクリックで拡大プレビュー対応
+
+ドキュメント：[画像生成スキル](https://docs.cowagent.ai/ja/skills/image-generation)
+
+## 🤖 新モデルサポート
+
+- **Kimi K2.6**：`kimi-k2.6` モデルサポートを追加
+- **Claude Opus 4.7**：`claude-opus-4-7` モデルサポートを追加
+- **GLM 5.1**：`glm-5.1` モデルサポートを追加
+- **Kimi Coding Plan**：Kimi Coding Plan モードをサポート
+- **カスタムモデルプロバイダー**：新しいカスタムモデルプロバイダー設定により、追加ベンダーとの統合が容易に
+
+## 💬 Web コンソール改善
+
+- **スマート自動スクロール**：チャットスクロールの動作を改善 — ユーザーが過去のメッセージを閲覧中に強制的に最下部にスクロールしなくなりました
+- **推論コンテンツ制限**：深い思考コンテンツを 4KB に制限し、フロントエンドのラグを防止
+- **モバイル最適化**：セッションサイドバーをモバイルではデフォルトで非表示、オーバーレイタップで閉じることが可能
+- **セッションタイトル修正**：タイトル自動生成のフォールバックロジックと設定変更時の Bridge リセットを修正
+- **画像プレビュー重複排除**：同一メッセージ内での画像の重複レンダリングを修正
+
+## 📚 ナレッジベース強化
+
+- **ネストディレクトリ対応**：ナレッジベースの一覧表示が多階層のネストディレクトリに対応
+- **ルートレベルファイル表示**：ナレッジツリーにルートディレクトリの `index.md`、`log.md` などを表示
+- **空状態統計の修正**：ルートレベルファイルが空状態検出に干渉しなくなりました
+
+## 🌙 夢の記憶改善
+
+- **構造化整理**：夢の記憶ファイルが日付別に自動アーカイブされ、ディレクトリ構造がより整理されました
+- **スケジュールジッター**：毎日の夢トリガーにランダムジッターを追加し、クラスター環境での同時実行の競合を回避
+
+## 🛠 スキルシステム改善
+
+- **スキルマネージャーの更新**：`/skill` コマンド実行後にスキルマネージャーを自動リフレッシュし、状態の同期を確保
+- **インストールソース拡張**：スキルインストールが複数のソース形式（URL、zip、ローカルファイルなど）に対応し、ターゲットディレクトリを自動的に確保
+
+## 🐛 その他の修正
+
+- **Gemini 修正**：Gemini の tool call が結果を返さない問題を修正
+- **Agent リトライ**：空レスポンスのリトライ時に `tool_calls` が破棄されなくなりました
+- **Docker 環境変数同期**：Docker 環境で設定更新後に環境変数が同期されない問題を修正
+- **Python 3.7 互換**：Python 3.7 互換性のために `Literal` のインポートを遅延
+- **モデル切替通知**：モデル切替後に bot_type 変更通知が表示されない問題を修正。Thanks @6vision
+- **設定コマンド**：`/config` で `enable_thinking` の設定が可能に
+- **思考表示**：深い思考の表示がデフォルトで無効に
+
+## 📦 アップグレード
+
+`cow update` または `./run.sh update` でアップグレード、またはコードを手動で pull して再起動。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。
+
+**リリース日**：2026.04.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.6...master)
diff --git a/docs/ja/releases/v2.0.8.mdx b/docs/ja/releases/v2.0.8.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/ja/releases/v2.0.8.mdx
@@ -0,0 +1,68 @@
+---
+title: v2.0.8
+description: CowAgent 2.0.8 - 飛書チャネル全面アップグレード（音声、ストリーミングタイプライター、ワンクリック QR アプリ作成）、DeepSeek V4 / 百度千帆 ERNIE 5.0 サポート、スケジューラ記憶強化および複数の修正
+---
+
+## 🪶 飛書チャネル全面アップグレード
+
+### 1. ワンクリック QR スキャンでアプリ作成
+
+飛書オープンプラットフォームで手動でアプリを作成し、権限とイベントサブスクリプションを設定する必要がなくなりました。Web コンソールおよびコマンドライン起動時に `feishu_app_id` が未設定の場合、QR スキャン入口が自動的に表示されます。飛書でスキャン・認可するとボットが自動作成され、設定が自動で書き戻され、すぐに使い始められます。
+
+ドキュメント：[飛書チャネル](https://docs.cowagent.ai/ja/channels/feishu)
+
+### 2. 音声メッセージ送受信
+
+ユーザーから送られた飛書の音声メッセージを受信し、自動的にテキストへ変換できるようになりました。返信も TTS による音声形式に対応。中国語の短い音声メッセージの認識精度も改善されています。
+
+### 3. ストリーミングタイプライター返信
+
+飛書 CardKit ストリーミングカードを統合し、**デフォルト有効**で Web コンソールと同等の体験を提供：
+
+- マルチターンの Agent シナリオで、中間メッセージと最終回答を別カードで表示
+- DeepSeek など高頻度出力モデル向けに最適化、Web コンソールと同等の速度を実現
+- 非対応時は自動的に通常のテキスト返信にフォールバック、手動設定不要
+- 飛書クライアント ≥ 7.20 が必要
+
+飛書の音声メッセージ送受信とストリーミングタイプライターのベース機能はコミュニティ貢献 #2791 によるものです。Thanks [@yangluxin613](https://github.com/yangluxin613)
+
+## 🤖 新モデルサポート
+
+- **DeepSeek V4 シリーズ**：`deepseek-v4-pro` / `deepseek-v4-flash` を追加、デフォルトモデルを `deepseek-v4-flash` に切り替え
+- **思考モデルスイッチの統一**：DeepSeek V4、Qwen3 など思考対応モデルの切り替え動作を `enable_thinking` に統一
+- **百度千帆 / ERNIE のファーストクラス対応**：新たな `qianfan` プロバイダーを追加。`ernie-5.0`（デフォルト推奨）、`ernie-x1.1`、`ernie-4.5-turbo-128k`、`ernie-4.5-turbo-32k` をサポート。`qianfan_api_key` / `qianfan_api_base` の独立設定により OpenAI 設定を汚染せず、旧来の `wenxin` / `wenxin-4` パスも完全互換 #2790 Thanks [@jimmyzhuu](https://github.com/jimmyzhuu)
+
+  ドキュメント：[百度千帆 / ERNIE](https://docs.cowagent.ai/ja/models/qianfan)
+
+## 🌐 翻訳プロバイダー
+
+- **有道翻訳を追加**：`translate/` モジュールに有道翻訳プロバイダーを追加。v3 SHA-256 署名方式に対応し、`zh` / `zh-TW` などの ISO 639-1 言語コードを自動マッピング #2797 Thanks [@Zmjjeff7](https://github.com/Zmjjeff7)
+
+## 🛠 OpenAI クライアントのリファクタリング
+
+- **SDK 依存を排除**：OpenAI Bot をネイティブ HTTP クライアントに刷新、起動が軽量化、依存衝突も削減
+- **Web コンソールヒント**：モデル設定の API Base 入力欄にバージョンパスのプレースホルダーヒントを追加
+
+## ⏰ スケジューラ記憶強化
+
+- **タスク結果への追問**：定期タスクの実行結果を受信側のセッション履歴に自動注入。次のターンでコンテキストを再説明することなくそのまま追問可能 Thanks [@huangrichao2020](https://github.com/huangrichao2020)
+- **長期記憶を汚染しない**：注入されたスケジューラ対話は毎日の記憶フラッシュ対象から除外され、高頻度タスクで記憶ストアが埋まることを防止
+- **遅くなり続ける問題を回避**：スケジューラ自身のコンテキスト長を自動制限、長期反復実行でも蓄積して応答を遅延させません
+
+## 🔧 ツールと安全性
+
+- **Vision モデル選択**：`tools.vision.model` 設定が実際に反映されるようになり、未設定時は自動フォールバック #2792
+- **Bash セーフティ確認**：破壊的削除の確認プロンプトをワークスペース外のパスに限定。ワークスペース内の通常操作は中断されません
+
+## 🐛 その他の修正
+
+- マルチインスタンス環境で Deep Dream が重複実行される問題を修正
+- DeepSeek マルチターン会話の一部の履歴ターンで `reasoning_content` が欠落する問題を修正
+
+## 📦 アップグレード
+
+ソースコードデプロイは `cow update` または `./run.sh update` でワンクリックアップグレード、または最新コードを手動で pull して再起動してください。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。
+
+> ⚠️ 飛書のワンクリックアプリ作成は `lark-oapi>=1.5.5` が必要です。`cow update` は自動で取得します。手動デプロイの場合は依存関係の更新を確認してください。
+
+**リリース日**：2026.05.05 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.7...2.0.8)
diff --git a/docs/ja/releases/v2.0.9.mdx b/docs/ja/releases/v2.0.9.mdx
new file mode 100644
index 0000000..003ae6e
--- /dev/null
+++ b/docs/ja/releases/v2.0.9.mdx
@@ -0,0 +1,65 @@
+---
+title: v2.0.9
+description: CowAgent 2.0.9 - モデル管理機能、MCP プロトコル対応、ブラウザログイン状態の永続化、新モデル追加とデプロイ・セキュリティ強化
+---
+
+## 🖥️ モデル管理機能の追加
+
+Web コンソールに「モデル」ページを新設。**モデルプロバイダー × モデル機能** の軸で管理し、対話、画像、音声、ベクトル、検索の各能力を一元的に設定可能になりました：
+
+- **プロバイダー単位の設定**：各プロバイダーの API Key / API Base はページ上部で一度だけ設定すれば、下部の各機能が自動で参照。再入力は不要
+- **画像モデル**：画像理解・画像生成それぞれで独立にプロバイダーとモデルを選択可能。未指定時はメインモデルに自動で追従
+- **音声モデル**：音声認識（ASR）と音声合成（TTS）を独立に設定可能。Qwen・Zhipu の ASR/TTS モデルを新たに追加
+- **ベクトルモデル**：埋め込み（Embedding）モデルを設定可能（記憶およびナレッジベース検索で利用）。OpenAI、Tongyi、Doubao、Zhipu などに対応。モデル切り替え後は `/memory rebuild-index` でインデックスをオンライン再構築してください
+- **検索機能**：ウェブ検索機能を強化、Bocha・Baidu・Zhipu など複数プロバイダーに対応。自動モードでは Agent が複数ソースの結果を統合してより深いリサーチを実行可能
+
+ドキュメント：[モデル概要](https://docs.cowagent.ai/ja/models)
+
+<img width="720" alt="20260522113305" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-models-config.png" />
+
+
+## 🧩 MCP プロトコル対応
+
+**MCP（Model Context Protocol）** プロトコルに対応。固定のツールセットから、開放的でプラグイン可能なツールエコシステムへと拡張され、MCP 互換のあらゆるサービスを Agent のツールとして直接接続できます。
+
+- ネイティブ JSON-RPC 実装、追加依存ゼロ。`stdio` と `sse` の両伝送方式に対応
+- Claude Desktop / Cursor などの主流形式の `mcpServers` 設定に互換、`~/cow/mcp.json` を優先的に読み込み
+
+ドキュメント：[MCP ツール](https://docs.cowagent.ai/ja/tools/mcp)。Thanks [@yangluxin613](https://github.com/yangluxin613) (#2801)
+
+## 🌐 ブラウザログイン状態の永続化
+
+ログインが必要なサイトや反クロウル機構のあるサイトに対して、ブラウザツールが一度のログイン状態を長期的に再利用できるようになりました。さらに自前の本物の Chrome に接続することで、フィンガープリント検出も回避可能です：
+
+- **永続化ユーザープロファイル（デフォルト）**：`~/.cow/browser_profile` をブラウザのユーザーディレクトリとしてデフォルト使用、一度ログインすれば次回以降は自動で復元
+- **CDP モード**：`tools.browser.cdp_endpoint` を設定することで実際の Chrome ブラウザを乗っ取り、完全なブラウザ権限を享受可能
+
+ドキュメント：[ブラウザツール](https://docs.cowagent.ai/ja/tools/browser)。Thanks [@leafmove](https://github.com/leafmove) (#2809)
+
+## 🤖 モデル追加と最適化
+
+- **モデル新規追加**：`gpt-5.5`、`gemini-3.5-flash`、`qwen3.7-max`、`ernie-5.1`
+- **モデル最適化**：DeepSeek V4 が `reasoning_effort` 思考深度パラメータをサポート。MiMo などの思考モデルが OpenAI 互換プロトコル経由で接続できない問題を修正
+
+## 🔒 デプロイとセキュリティ
+
+- **デフォルトでローカルアクセスのみ**：Web コンソールの `web_host` をデフォルトで `127.0.0.1` にバインド。サーバーデプロイ時は手動で `0.0.0.0` に変更しパスワードを設定してください。Thanks @August829、@yidaozhongqing、@YLChen-007、@icysun
+- **フロントエンド資源の完全ローカル化**：サードパーティ CSS / JS をすべてローカル配信化、オフライン / イントラネット環境でもコンソールが正常に動作。Thanks [@gitlayzer](https://github.com/gitlayzer) (#2816)
+
+## 🛠 体験改善と修正
+
+- **TTS のチャネル拡充**：Web 対話、個人 WeChat、飛書、DingTalk、WeCom スマートボットすべてが音声返信に対応。詳細は [チャネル概要](https://docs.cowagent.ai/ja/channels) を参照
+- **ログパネル強化**：ログレベルに応じたハイライト表示と、レベル別フィルタリングをサポート。Thanks [@yangluxin613](https://github.com/yangluxin613) (#2807)
+- **Web コンソールの自動起動**：プログラム起動後に Web コンソールが自動で開きます。Thanks [@yangluxin613](https://github.com/yangluxin613) (#2804)
+- **Ctrl+C のクリーン終了**：長い `KeyboardInterrupt` スタックトレースが表示されなくなりました。Thanks [@yangluxin613](https://github.com/yangluxin613) (#2806)
+- **フォルダアップロード**：Web 端でディレクトリアップロードに対応、Windows 向けのパス検証に適合。Thanks [@TryToMakeUsBetter](https://github.com/TryToMakeUsBetter) (#2814)
+- 特定条件下でスケジュールタスクが重複実行される問題を修正。Thanks [@CNXudiandian](https://github.com/CNXudiandian) (#2820)
+- タイムゾーン付きの単発スケジュールタスクが発火しない問題を修正。Thanks @AethericSpace
+- 実行失敗したツール呼び出しがページ更新後に表示されない問題を修正。Thanks [@a1094174619](https://github.com/a1094174619) (#2822)
+- WeCom ボットメッセージに不正な制御文字が含まれる場合に配信が失敗する問題を修正。Thanks [@Jacques-Zhao](https://github.com/Jacques-Zhao) (#2810)
+
+## 📦 アップグレード方法
+
+ソースコードデプロイは `cow update` でワンクリックアップグレード、または最新コードを手動で pull して再起動してください。詳細は [アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade) を参照。
+
+**リリース日**：2026.05.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.8...2.0.9)
diff --git a/docs/ja/releases/v2.1.0.mdx b/docs/ja/releases/v2.1.0.mdx
new file mode 100644
index 0000000..db9b26f
--- /dev/null
+++ b/docs/ja/releases/v2.1.0.mdx
@@ -0,0 +1,69 @@
+---
+title: v2.1.0
+description: CowAgent 2.1.0 - 国際化対応、Telegram / Discord / Slack / WeChat カスタマーサービスチャネルの追加、CLI インタラクション強化、MCP プロトコル強化、新モデル追加
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.0) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.0)
+
+## 📱 接続チャネルの追加
+
+今回、主要プラットフォームのチャネルを複数追加。設定すればすぐ使える、すぐ接続可能です：
+
+- **Telegram Bot**：Telegram ボットに接続、テキストとマルチメディアメッセージに対応
+- **Discord Bot**：Discord ボットに接続、チャンネルおよび DM で対話可能
+- **Slack Bot**：Slack ボットに接続、チームのワークフローに統合
+- **WeChat カスタマーサービス**：WeChat カスタマーサービスチャネルを新設。画像・ファイルの受信に対応し、自動で次のターンに統合。マルチメディアのコンテキスト体験が他チャネルと同等に。Thanks [@6vision](https://github.com/6vision) (#2840)
+
+ドキュメント：[チャネル概要](https://docs.cowagent.ai/ja/channels)
+
+## 🌍 国際化対応
+
+CowAgent は全世界の開発者に向けたエンドツーエンドの国際化フレームワークを導入。システム言語に応じて自動で適応します：
+
+- **エンドツーエンドのローカライズ**：インストールガイド、CLI、ログとエラー、Agent システムプロンプトなどがローカライズに対応
+- **言語の自動判定**：デフォルトの `auto` モードはシステムロケールから判定。`config.json` の `cow_lang` で明示的に指定も可能。まずは英語と中国語に対応し、今後さらに多くの言語を拡充予定
+- **コンソールでワンクリック切り替え**：Web コンソールでシステム言語をオンライン切り替え可能、リアルタイムで反映
+
+## ⌨️ CLI インタラクション強化
+
+- **ワンライナーインストールの最適化**：インストールスクリプトを簡素化し、対話的なセットアップに対応——言語を選択でき、ガイドに沿ってモデルとチャンネルも任意で選択可能。数分でデプロイして利用開始できます
+- **ストリーミング出力**：Terminal チャネルが Agent モードの推論過程、ツール呼び出し、ストリーミング返信をリアルタイムに表示
+- **コマンドのあいまいマッチング**：コマンドの省略形や近似タイポの自動サジェストに対応。よく使うショートカットを内蔵し、設定ファイルでカスタムエイリアスも定義可能。Thanks [@lyteen](https://github.com/lyteen) (#2850)
+- **タスクのキャンセル対応**：実行中の Agent タスクを能動的に中断可能。Web 端に中止ボタンを追加、その他のチャネルでは `/cancel` を送信して中止
+
+ドキュメント：[CLI ガイド](https://docs.cowagent.ai/ja/cli/general)
+
+## 🧩 MCP プロトコル強化
+
+MCP ツールが **Streamable HTTP** 伝送に新対応。既存の `stdio`・`sse` に加え、より多くの MCP サービスに互換となり、ストリーミング HTTP プロトコルを用いるリモートツールへ直接接続できます。
+
+ドキュメント：[MCP ツール](https://docs.cowagent.ai/ja/tools/mcp)
+
+## 🤖 モデル追加と最適化
+
+- **モデル新規追加**：`claude-opus-4-8`、Xiaomi `MiMo`
+- **モデル最適化**：一部モデルが返すツール呼び出し引数の JSON 解析に失敗する問題を修正 (#2823)
+
+ドキュメント：[モデル概要](https://docs.cowagent.ai/ja/models)
+
+## 🧠 記憶と検索の最適化
+
+- **キーワード検索の最適化**：中国語キーワード検索のヒット率が低い問題、純英語キーワードでクエリ結果が空になる問題を修正
+- **ベクトル検索の強化**：ベクトル検索フローを最適化し、Python バージョン互換性を向上
+
+Thanks [@yangluxin613](https://github.com/yangluxin613) (#2832)
+
+## 🛠 体験改善と修正
+
+- **ファイルアクセスの限定**：Web 端のファイル読み取り・送信をデフォルトでユーザーホームディレクトリと Agent ワークスペース内に限定し、任意ファイル読み取りを防止。`web_file_serve_root` で範囲を拡張可能
+- **スケジュールタスクの安定化**：個人 WeChat チャネルで再起動後にスケジュールタスクの配信が失効する問題を修正
+- **ブラウザツール**：ナビゲーション URL の非 HTTP スキームが破棄される問題を修正、ブラウザのメモリ使用量を最適化
+- **WeChat 公式アカウント**：パッシブ返信でキャッシュ済みテキストセグメントの結合、タスク実行中の準備完了セグメントの先行配信、ローカル `file://` 画像の送信に対応。Thanks [@6vision](https://github.com/6vision) (#2848)
+- **WeCom ボットの応答高速化**：コールバックを非同期ディスパッチに変更し、WeCom の 5 秒タイムアウトによるメッセージ欠落を回避
+- **ログインの堅牢化**：`web_password` が文字列でない場合にログインエラーになる問題を修正
+
+## 📦 アップグレード方法
+
+ソースコードデプロイは `cow update` でワンクリックアップグレード、または最新コードを手動で pull して再起動してください。詳細は [アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade) を参照。
+
+**リリース日**：2026.06.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.9...2.1.0)
diff --git a/docs/ja/releases/v2.1.1.mdx b/docs/ja/releases/v2.1.1.mdx
new file mode 100644
index 0000000..b4e4890
--- /dev/null
+++ b/docs/ja/releases/v2.1.1.mdx
@@ -0,0 +1,61 @@
+---
+title: v2.1.1
+description: CowAgent 2.1.1 - 自己進化、Web コンソールのメッセージ管理とマルチセッション並行、クロスプラットフォーム対応の MCP 強化、新モデルと改善
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.1) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.1)
+
+## 🧬 自己進化
+
+CowAgent に **自己進化（Self-Evolution）** が加わりました。Agent は単発のタスクをこなすだけでなく、日々の協働を通じて成長し続けます：
+
+- **アイドル後の自動レビュー**：会話がアイドルになると、Agent はバックグラウンドでその会話をレビューし、使用中に表面化した Skill の問題を修正し、再利用可能な新しい Skill を作成し、未完了のタスクを引き継ぎ、重要な情報を記憶とナレッジベースに記録します
+- **静かに実行、必要なときだけ通知**：実際に変更があったときのみ調整内容を一言で伝え、変更がなければ何も通知しません
+- **安全で取り消し可能**：レビューのたびに事前にバックアップを取り、いつでも取り消せます。組み込み Skill は保護され、すべての読み書きはワークスペース内に限定されます
+
+新規インストールではデフォルトで有効です。既存ユーザーは Web コンソールの **設定 → Agent 設定** からワンクリックで有効化できます。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-demo.png" alt="自己進化の会話例" />
+
+ドキュメント：[自己進化](https://docs.cowagent.ai/ja/memory/self-evolution)
+
+## 💬 Web コンソールの強化
+
+Web コンソールのチャット体験がさらに強化され、主要なチャット製品に近い操作感になりました：
+
+- **メッセージ管理**：ユーザーと Bot のメッセージを編集・削除・再生成できます。コードブロックに言語ラベルとワンクリックコピーボタンを追加。Thanks [@core-power](https://github.com/core-power) (#2865)
+- **マルチセッション並行**：複数のセッションを同時に実行しても互いに干渉せず、セッションに戻るとライブストリーミングが自動的に再開されます
+- **細部の改善**：チャット画面のどこにでもファイルをドラッグ＆ドロップ可能。アクティブなセッションを削除すると隣接セッションへ自動で切り替わります
+
+## 🧩 クロスプラットフォーム対応の MCP 強化
+
+- **Windows 互換性の修正**：Windows で `stdio` 通信が動作しない問題を修正し、サーバーのタイムアウトを `mcp.json` で設定できるようにしました
+- **並行呼び出し**：`sse` と `streamable-http` トランスポートがセッション間の並行呼び出しに対応し、複数ツールの応答が高速化されました
+
+Thanks [@xliu123321](https://github.com/xliu123321) (#2859)
+
+ドキュメント：[MCP ツール](https://docs.cowagent.ai/ja/tools/mcp)
+
+## 🤖 新モデルと改善
+
+- **MiniMax-M3**：追加してデフォルトモデルに設定（M2.7 シリーズはオプションとして継続）。Thanks [@octo-patch](https://github.com/octo-patch) (#2855)
+- **Qwen3.7-plus**：マルチモーダル対話に対応
+- **ASR モデルの選択**：Web コンソールで ASR（音声認識）モデルを選択して永続化できるようになりました。Thanks [@nightwhite](https://github.com/nightwhite) (#2857)
+- **インストールメニューの簡素化**：ワンライナーインストールスクリプトのモデルメニューを簡素化し、Xiaomi MiMo オプションを追加
+
+ドキュメント：[モデル概要](https://docs.cowagent.ai/ja/models)
+
+## 🛠 改善と修正
+
+- **Python 3.13 対応**：Python 3.13 環境でのインストールと依存関係の互換性を修正
+- **国際化**：チャネル一覧を UI の言語順に表示。`auto` モードでの言語自動フォールバックを改善
+- **より確実なキャンセル**：ストリーミング応答を中断できない場合がある問題を修正
+- **CLI**：`cow status` に現在のプロジェクトパスを表示
+- **デプロイのセキュリティ強化**：認証ファイルのブロック範囲を `~/.cow/.env` に限定し、他のディレクトリに影響しないように修正（Thanks [@orbisai0security](https://github.com/orbisai0security) #2863）。WeChat 公式アカウントは `wechatmp_token` が空の場合に Webhook リクエストを拒否します
+- **グループタスクボードプラグイン**：グループタスクボードプラグインのソースを追加。Thanks [@Wyh-max-star](https://github.com/Wyh-max-star) (#2853)
+
+## 📦 アップグレード
+
+ソースコードでデプロイしている場合は `cow update` でワンクリックアップグレードするか、最新コードを取得して手動で再起動してください。詳細は [アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade) を参照してください。
+
+**リリース日**：2026.06.09 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.0...2.1.1)
diff --git a/docs/ja/releases/v2.1.2.mdx b/docs/ja/releases/v2.1.2.mdx
new file mode 100644
index 0000000..ef24b44
--- /dev/null
+++ b/docs/ja/releases/v2.1.2.mdx
@@ -0,0 +1,67 @@
+---
+title: v2.1.2
+description: CowAgent 2.1.2 - Web コンソールの管理機能強化、自己進化の改善、新モデル、企業微信スマートボットのコールバックモード、セキュリティ強化
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.2) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.2)
+
+## 💬 Web コンソールの改善
+
+本リリースでは Web コンソールに複数の可視化管理機能を追加し、ファイルを編集せずに UI 上でより多くの設定を行えるようになりました：
+
+- **定期タスク管理**：コンソール上で任意の定期タスクを直接表示・編集・有効化／無効化・削除できます。タスク一覧は有効状態を優先し、次回実行時刻の順にソートされます。Thanks @HnBigVolibear (#2892)
+- **ナレッジベースのカテゴリと文書管理**：ナレッジベースをカテゴリで整理し、各カテゴリ配下の文書を UI で管理できるようになりました。Thanks @yangziyu-hhh (#2893)
+- **複数のカスタムモデルプロバイダー**：複数の OpenAI 互換プロバイダーを設定し、有効なものをワンクリックで切り替えられます。既存の設定とも完全に互換です。Thanks @kirs-hi (#2877)
+- **セッションのリネーム**：セッションを手動でリネームでき、並行する複数のタスクを区別しやすくなります (#2897)
+- **Bash のストリーミング出力**：長時間実行される Bash コマンドの進捗をリアルタイムにストリーミング出力します。Thanks @yangziyu-hhh (#2879)
+
+## 🧬 自己進化の改善
+
+前バージョンで導入した自己進化を、本バージョンでさらに改善しました：
+
+- **トリガー閾値の引き下げ**：デフォルトのレビュー閾値を引き下げ、日々の協働がより早く改善へとつながります
+- **同時レビューの回避**：単一ターンの処理が長引いた場合に、アイドルレビューが誤って起動しなくなり、進行中の会話との干渉を回避します
+- **レビュー要約の改善**：要約生成のプロンプトを改善し、要約を簡潔に保ちつつ情報密度を高め、会話の言語で出力します
+
+ドキュメント：[自己進化](https://docs.cowagent.ai/ja/memory/self-evolution)
+
+## 🤖 新モデル
+
+- **kimi-k2.7-code**：追加して Kimi のデフォルトモデルに設定。高速版の `kimi-k2.7-code-highspeed` も利用できます
+- **glm-5.2**：追加して GLM のデフォルトモデルに設定
+
+ドキュメント：[モデル概要](https://docs.cowagent.ai/ja/models)
+
+## 🏢 企業微信スマートボットのコールバックモード
+
+企業微信スマートボットのチャネルに、既存のロングコネクションに加えて **HTTP コールバックモード** を追加しました。ロングコネクションを維持できない環境でも安定して接続できます：
+
+- **モード切替**：`wecom_bot_mode` で `websocket`（ロングコネクション）と `webhook`（コールバック）を切り替えます
+- **暗号化通信**：コールバックモードは URL 検証、メッセージ復号、受動応答の暗号化に完全対応します
+- **安定性の修正**：応答の中断、ストリームの早期終了、一時画像ファイルのリークなどの問題を修正しました
+
+Thanks @6vision (#2896 #2869)
+
+ドキュメント：[企業微信スマートボット](https://docs.cowagent.ai/ja/channels/wecom-bot)
+
+## 🔒 セキュリティ強化
+
+- **Vision ツールの SSRF 対策**：画像 URL を解決する前に対象アドレスを検証し、内部・ループバック・クラウドサーバーのメタデータエンドポイントへのリクエストをブロックします。Thanks @kirs-hi (#2886)
+- **Web フェッチの SSRF 対策**：`web_fetch` は取得前に対象アドレスを検証し、リダイレクトのたびに再検証することで、リダイレクト経由で検証を回避して内部アドレスへ到達することを防ぎます。Thanks @christop (#2900)
+- **Skill インストールのパストラバーサル対策**：Skill のインストール時にパスを検証し、悪意ある Skill 名がパストラバーサルで `skills/` ディレクトリを抜け出して許可されない場所に書き込むことを防ぎます。Thanks @kirs-hi (#2886)
+
+## 🛠 改善と修正
+
+- **CLI セルフ再起動**：self-restart コマンドを追加し、Agent が自身のプロセスを再起動できるようになりました
+- **Windows 互換性**：cow CLI のディレクトリをユーザー PATH に永続化。`python -c` の長いコマンドが `cmd.exe` の長さ制限を超える問題を修正。インストール時に greenlet をソースからビルドしないように修正
+- **カスタムロール**：ロールプラグインが `roles/*.json` 配下の独立したプロンプトファイルによるカスタマイズに対応しました。Thanks @sufan721 (#2891)
+- **安定性の修正**：`/cancel` 時の KeyError と画像圧縮の無限ループを修正（Thanks @kirs-hi #2888）
+- **インストールの改善**：起動スクリプトとデフォルト設定を更新。ASR/TTS のデフォルト値、自己進化フラグ、インストール時のハングを修正
+- **Vision ツールの安定性**：Vision ツールのタイムアウトと max_tokens を引き上げ
+- **記憶の蒸留**：ディープドリーム蒸留の出力長制限を撤廃し、大きな `MEMORY.md` が切り詰められないようにしました
+
+## 📦 アップグレード
+
+ソースコードでデプロイしている場合は `cow update` でワンクリックアップグレードするか、最新コードを取得して手動で再起動してください。詳細は [アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade) を参照してください。
+
+**リリース日**：2026.06.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.1...2.1.2)
diff --git a/docs/ja/releases/v2.1.3.mdx b/docs/ja/releases/v2.1.3.mdx
new file mode 100644
index 0000000..5261bc7
--- /dev/null
+++ b/docs/ja/releases/v2.1.3.mdx
@@ -0,0 +1,73 @@
+---
+title: v2.1.3
+description: "CowAgent 2.1.3：デスクトップクライアント（macOS / Windows）を正式リリース。ナレッジベースのドキュメント管理を強化し、MCP ツールのオンデマンド検索、繁体字中国語対応、新モデルに加え、セキュリティと使い勝手の各種改善"
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.3) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.3)
+
+## 🖥 デスクトップクライアント
+
+**CowAgent デスクトップクライアント**を正式にリリースしました。**macOS と Windows** に対応し、ローカルのスーパー AI アシスタントをそのまますぐに使えます。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/desktop-chat-demo-en.png" alt="CowAgent デスクトップクライアント" />
+
+主な特長：
+
+- **すぐに使える**：Agent の実行環境を内蔵しており、インストール後すぐに起動できます。Python などの依存関係を用意する必要はありません
+- **充実したチャット体験**：ストリーミング応答、セッション管理、ツール呼び出しのステップ表示、Markdown レンダリングに加え、画像 / 動画 / ファイルの送信とプレビューに対応
+- **ビジュアル管理**：設定、モデル、ナレッジベース、定期タスク、スキル、メモリなどの画面が Web コンソールと同等で、ネイティブ UI 上で管理できます
+- **チャネル接続**：アプリ内で QR コードをスキャンして各種メッセージチャネルに接続
+- **自動アップデート**：バージョンの自動チェックとワンクリック更新に対応し、地域ごとにダウンロード速度を最適化
+- **ネイティブ体験**：初回起動ガイド、システム言語への追従、プラットフォームに適応したウィンドウ操作
+
+ダウンロード：[CowAgent デスクトップ](https://cowagent.ai/download/)
+
+## 📚 ナレッジベース
+
+- **ドキュメントの作成とインポート**：UI から直接ドキュメントを新規作成したり、外部ドキュメントをインポートできます
+- **インデックスの自動メンテナンス**：実際のディレクトリ構成からインデックスを自動的に再構築し、インデックスのずれやドキュメントの欠落を防ぎます
+- **ベクトル化の修正**：インデックスが統一された埋め込みプロバイダーを再利用するようになり、キーワード検索へのフォールバックではなく本来のセマンティックベクトルを生成します
+
+Thanks @yangziyu-hhh
+
+ドキュメント：[ナレッジベース](https://docs.cowagent.ai/ja/memory/knowledge)
+
+## 🔌 MCP ツールのオンデマンド検索
+
+多数の MCP ツールを接続した際のコンテキスト肥大化に対応するため、**オンデマンドのツール検索**を追加しました。現在のタスクに関連する MCP ツールを RAG ベクトル検索で必要に応じて読み込み、無関係なツールがコンテキストを占有するのを抑えます。Thanks @fengyl07
+
+ドキュメント：[MCP ツール](https://docs.cowagent.ai/ja/tools/mcp)
+
+## 🌏 繁体字中国語対応
+
+Web コンソール、ログ、ドキュメントが **繁体字中国語（zh-Hant）** に対応しました。インターフェース言語はシステムに追従するか、手動で切り替えられます。Thanks @anomixer (#2935)
+
+## 🤖 新モデル追加
+
+- **claude-sonnet-5**、**claude-fable-5** に対応
+- **doubao-seed-2-1-pro**、**doubao-seed-2-1-turbo** に対応
+
+ドキュメント：[モデル](https://docs.cowagent.ai/ja/models)
+
+## 🔒 セキュリティ強化
+
+- **機密ファイル読み取り防護**：認証情報などの機密ファイルへのアクセスを強化し、迂回による読み取りを防止します。Thanks @fengyl07 (#2913)
+- **ブラウザアクセス防護**：ブラウザによる内部ネットワークやクラウドサーバーの内部エンドポイントへのリクエストをブロックし、内部サービスへ誘導されるリスクを低減します。Thanks @Jiangrong-W
+- **設定解析の安全化**：設定内容をより安全な方法で解析し、潜在的なコード実行リスクを回避します。Thanks @shunfeng8421
+
+## 🛠 改善と修正
+
+- **カスタムプロバイダー対応**：埋め込みモデルとビジョンモデルでカスタムプロバイダーを利用可能に。あわせて Windows でのメモリ取得の問題を修正しました。Thanks @HnBigVolibear
+- **ファイル編集の安定性向上**：元のインデントをより適切に保持し、あいまい一致の際に無関係な内容を変更しないようにしました。Thanks @weijun-xia (#2942)
+- **コマンド出力の文字化け修正**：コマンドが大量の出力を生成した際に発生し得る中国語の文字化けを修正しました。Thanks @weijun-xia (#2941)
+- **Azure OpenAI の修正**：Azure OpenAI のストリーミング出力および関連する設定の問題を修正しました。Thanks @Tunnello
+- **企業向け WeChat スマートボット**：webhook（コールバック）モードの接続ドキュメントを追加しました。Thanks @6vision
+- **ディープドリームの切り替え**：`deep_dream_enabled` の専用スイッチを追加し、ディープドリームの蒸留を個別に有効・無効化できます。
+- **安定性**：Web サービスの接続回収を改善し、自己進化に関するいくつかの問題を修正しました (#2924, #2904)
+
+## 📦 アップグレード方法
+
+- **デスクトップクライアント**：[ダウンロードページ](https://cowagent.ai/download/) から最新バージョンを入手してください。
+- **ソースデプロイ**：`cow update` でワンクリックアップグレード、または最新コードを取得して再起動します。詳しくは [アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade) を参照してください。
+
+**リリース日**：2026.07.08 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.2...2.1.3)
diff --git a/docs/ja/skills/create.mdx b/docs/ja/skills/create.mdx
new file mode 100644
index 0000000..78640a3
--- /dev/null
+++ b/docs/ja/skills/create.mdx
@@ -0,0 +1,58 @@
+---
+title: スキルの作成
+description: 会話を通じてカスタムスキルを作成
+---
+
+CowAgent には Skill Creator が組み込まれており、自然言語の会話を通じてスキルの作成、インストール、更新を素早く行えます。
+
+## 使い方
+
+会話で作りたいスキルを説明するだけで、Agent が自動的に作成します：
+
+- ワークフローをスキル化：「このデプロイプロセスからスキルを作成して」
+- サードパーティ API の統合：「この API ドキュメントに基づいてスキルを作成して」
+- リモートスキルのインストール：「xxx スキルをインストールして」
+
+## 作成フロー
+
+1. 作成したいスキルを Agent に伝えます
+2. Agent が自動的に `SKILL.md` の説明と実行スクリプトを生成します
+3. スキルはワークスペースの `~/cow/skills/` ディレクトリに保存されます
+4. 以降の会話で Agent が自動的にそのスキルを認識し使用します
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+## SKILL.md のフォーマット
+
+作成されたスキルは標準の SKILL.md フォーマットに従います：
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| フィールド | 説明 |
+| --- | --- |
+| `name` | スキル名。ディレクトリ名と一致する必要があります |
+| `description` | スキルの説明。Agent はこれに基づいて呼び出すかどうかを判断します |
+| `metadata.requires.bins` | 必要なシステムコマンド |
+| `metadata.requires.env` | 必要な環境変数 |
+| `metadata.always` | 常に読み込む（デフォルトは false） |
+
+<Tip>
+  詳細は [Skill Creator のドキュメント](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md)をご覧ください。
+</Tip>
diff --git a/docs/ja/skills/hub.mdx b/docs/ja/skills/hub.mdx
new file mode 100644
index 0000000..c8116e3
--- /dev/null
+++ b/docs/ja/skills/hub.mdx
@@ -0,0 +1,65 @@
+---
+title: スキルハブ
+description: AI Agent スキルの閲覧、検索、インストール
+---
+
+[Cow Skill Hub](https://skills.cowagent.ai/) は、公式推奨・コミュニティ貢献・サードパーティ（GitHub、ClawHub など）のスキルを集約した、オープンソースの AI Agent スキルマーケットプレイスです。
+
+ソースコード: [github.com/zhayujie/cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
+
+## 機能
+
+- **スキル閲覧** — カテゴリ（公式推奨 / コミュニティ / サードパーティ）とタグでフィルタ
+- **スキル検索** — 名前または説明で検索
+- **詳細表示** — スキルマニフェスト、ファイル内容、インストールコマンド、必要な環境変数を確認
+- **ワンクリックインストール** — インストールコマンドをコピーして CowAgent で実行
+
+## スキルのインストール
+
+チャット内またはターミナルでインストールコマンドを実行:
+
+<CodeGroup>
+```text チャット
+/skill install <name>
+```
+
+```bash ターミナル
+cow skill install <name>
+```
+</CodeGroup>
+
+チャットからスキルハブを直接閲覧することもできます:
+
+```text
+/skill list --remote
+/skill search <キーワード>
+```
+
+リスト表示されている厳選スキル以外にも、**GitHub、ClawHub、LinkAI、任意の URL** からサードパーティスキルを CLI 経由でインストールできます。詳しくは [スキルのインストール](/ja/skills/install) を参照してください。
+
+## スキルの貢献
+
+ご自身のスキルを投稿するには:
+
+1. [skills.cowagent.ai/submit](https://skills.cowagent.ai/submit) にアクセス
+2. GitHub または Google でログイン
+3. `SKILL.md` を含むフォルダまたは zip ファイルをアップロード
+4. スキル名・表示名・説明は自動検出されます。必要に応じて編集してください
+5. 提出後、セキュリティ・品質チェックを経て公開されます
+
+<img src="https://cdn.link-ai.tech/doc/20260401111904.png" width="800" />
+
+スキルのファイル構成:
+
+```
+your-skill/
+├── SKILL.md        # 必須、ルートに配置
+├── scripts/        # 任意、実行スクリプト
+└── resources/      # 任意、その他リソース
+```
+
+<Tip>
+  スキルは `SKILL.md` マニフェストを中心に構築されます。スキル詳細ページから `SKILL.md` をダウンロードし、カスタム指示に対応した任意の Agent（OpenClaw、Cursor、Claude Code など）でも利用できます。
+</Tip>
diff --git a/docs/ja/skills/image-generation.mdx b/docs/ja/skills/image-generation.mdx
new file mode 100644
index 0000000..6267d08
--- /dev/null
+++ b/docs/ja/skills/image-generation.mdx
@@ -0,0 +1,98 @@
+---
+title: image-generation - 画像生成
+description: テキストから画像生成 / 画像編集 / 複数画像融合に対応。複数プロバイダーの自動ルーティングとフォールバックをサポート
+---
+
+汎用の画像生成・編集スキルです。OpenAI、Gemini、Seedream（Volcengine Ark）、Qwen（DashScope）、MiniMax、LinkAI の 6 つのプロバイダーに対応しています。いずれか 1 社の Key を設定すれば利用でき、複数社を設定すると自動フォールバックが有効になります。
+
+## 対応モデル
+
+| プロバイダー | モデル / エイリアス | 特徴 |
+| --- | --- | --- |
+| OpenAI | `gpt-image-2`、`gpt-image-1` | 汎用テキスト→画像、高品質、`quality` で画質制御に対応 |
+| Gemini Nano Banana | `nano-banana-2`、`nano-banana-pro`、`nano-banana` | `gemini-3.1-flash`、`gemini-3-pro`、`gemini-2.5-flash` の画像バージョン |
+| Seedream（Volcengine Ark） | `seedream-5.0-lite`、`seedream-4.5` | ネイティブ 2K–4K、最大 14 枚の画像融合 |
+| Qwen（DashScope） | `qwen-image-2.0`、`qwen-image-2.0-pro` | 中国語のレイアウトや画像とテキストの融合に強い |
+| MiniMax | `image-01` | シンプルで高速 |
+| LinkAI | 任意のモデル | 統一ゲートウェイ、フォールバック用途 |
+
+## モデル選択
+
+デフォルトでは「自動ルーティング + 失敗時フォールバック」で動作します：
+
+1. `OpenAI → Gemini → Seedream → Qwen → MiniMax → LinkAI` の順に、設定済みのプロバイダーを最初に選択
+2. 401、モデル未開通、ネットワークエラーなどに遭遇した場合、自動的に次のプロバイダーへ切り替え
+3. ユーザーが対話内でモデルを指定した場合（例：「seedream で猫を描いて」）、該当プロバイダーが優先候補に繰り上がります
+
+特定のモデルに固定したい場合：
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+## API Key の設定
+
+<Tip>
+  [Web コンソール](/ja/channels/web) の「モデル管理」ページから設定するのが推奨です。設定済みの対話モデル Key は画像生成スキルでも自動的に再利用されるため、重複した設定は不要です。設定ファイルを手動編集するか、対話中に `env_config` ツールで一時的に設定することもできます。
+</Tip>
+
+認証情報はメインモデルプロバイダーの Key を統一的に再利用します：
+
+| フィールド | 対応プロバイダー |
+| --- | --- |
+| `openai_api_key` | OpenAI |
+| `gemini_api_key` | Gemini |
+| `ark_api_key` | Volcengine Ark（Seedream） |
+| `dashscope_api_key` | Alibaba DashScope（Qwen） |
+| `minimax_api_key` | MiniMax |
+| `linkai_api_key` | LinkAI |
+
+
+## 有効化と無効化
+
+スキルは API Key に応じて自動的にステータスが調整されます：
+
+- **Key 設定済み**：Agent は画像生成リクエストを受けると直接呼び出します
+- **Key 未設定**：スキルはコンテキストに表示されますが（「設定が必要」とマーク）、Agent はユーザーに Key の設定を案内します
+
+手動で制御する場合：
+
+```text
+/skill disable image-generation    # 無効化
+/skill enable image-generation     # 再有効化
+```
+
+ターミナルでの等価コマンド：`cow skill disable image-generation` / `cow skill enable image-generation`。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | デフォルト | 説明 |
+| --- | --- | --- | --- | --- |
+| `prompt` | string | はい | — | 画像の説明 |
+| `image_url` | string / list | いいえ | null | 編集用の入力画像。ローカルパスまたは URL。リスト指定で複数画像融合 |
+| `quality` | string | いいえ | auto | `low` / `medium` / `high`、一部のプロバイダーのみ対応 |
+| `size` | string | いいえ | auto | `512` / `1K` / `2K` / `3K` / `4K`、またはピクセル値（例：`1024x1024`） |
+| `aspect_ratio` | string | いいえ | null | `1:1` / `3:2` / `2:3` / `16:9` / `9:16` / `21:9`。Gemini は `1:4` / `4:1` / `1:8` / `8:1` にも対応 |
+
+<Warning>
+  **品質が高いほど、解像度が大きいほど、時間とコストが高くなります。** 日常の対話ではデフォルト（`auto`）または `quality=low` + `size=1K` で十分で、約 20 秒で生成されます。ポスター制作や明示的に高解像度が必要な場合のみ `high` + `2K/4K` を使用してください。1〜5 分かかる場合があります。
+</Warning>
+
+## よくある使い方
+
+- **テキスト→画像**：説明文からイラスト、ポスター、アイコン、アバター、絵コンテなどを生成
+- **画像→画像**：既存の画像のスタイル変更、要素差し替え、装飾や文字の追加など
+- **複数画像融合**：複数の参考画像を 1 枚に合成（着せ替え、キャラクター集合写真など）
+
+<Note>
+- bash タイムアウトは 600 秒に設定することを推奨：単一プロバイダーの HTTP タイムアウトは 300 秒、スクリプトは複数社を順に試行する場合があります
+- 入力画像は自動的に 4 MB 以内・最長辺 4096 px 以内に圧縮されます
+- Gemini / Seedream / Qwen / MiniMax は `quality` パラメータに対応していません
+- Seedream のデフォルトは 2K。`seedream-5.0-lite` は 3K まで、`seedream-4.5` は 4K まで対応
+</Note>
diff --git a/docs/ja/skills/index.mdx b/docs/ja/skills/index.mdx
new file mode 100644
index 0000000..cab0410
--- /dev/null
+++ b/docs/ja/skills/index.mdx
@@ -0,0 +1,64 @@
+---
+title: スキル概要
+description: CowAgent のスキルシステム紹介
+---
+
+スキル（Skill）は Agent に無限の拡張性を提供します。各スキルは説明ファイル（`SKILL.md`）、実行スクリプト（任意）、リソース（任意）で構成され、特定のタスクをどのように遂行するかを記述します。
+
+スキルとツールの違い：ツールはコードで実装された原子的な操作（例：ファイルの読み書き、コマンドの実行）であるのに対し、スキルは説明ファイルに基づく高レベルなワークフローであり、複数のツールを組み合わせて複雑なタスクを完遂できます。
+
+## スキルの取得
+
+CowAgent ではスキルを取得する複数の方法を提供しています：
+
+- **Cow スキル広場** — `/skill list --remote` でコミュニティスキルを閲覧・インストール
+- **GitHub** — GitHub リポジトリから直接インストール、バッチインストールにも対応
+- **ClawHub** — `/skill install clawhub:名前` で ClawHub のスキルをインストール
+- **URL** — zip アーカイブや SKILL.md リンクからインストール
+- **会話で作成** — 自然言語の会話を通じて Agent にスキルを自動作成させる
+
+詳細は[スキルのインストール](/ja/skills/install)と[スキル管理コマンド](/ja/cli/skill)を参照してください。会話を通じて[スキルを作成](/ja/skills/create)することもできます。
+
+## スキルの読み込み優先順位
+
+1. **ワークスペースのスキル**（最高優先）：`~/cow/skills/`
+2. **プロジェクト組み込みスキル**（最低優先）：`skills/`
+
+同名のスキルは優先順位に従って上書きされます。
+
+## スキルのファイル構成
+
+```
+skills/
+├── my-skill/
+│   ├── SKILL.md          # Skill の説明（frontmatter + 手順）
+│   ├── scripts/          # 実行スクリプト（任意）
+│   └── resources/        # 追加リソース（任意）
+```
+
+### SKILL.md のフォーマット
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| フィールド | 説明 |
+| --- | --- |
+| `name` | スキル名。ディレクトリ名と一致する必要があります |
+| `description` | スキルの説明。Agent はこれに基づいて呼び出すかどうかを判断します |
+| `metadata.requires.bins` | 必要なシステムコマンド |
+| `metadata.requires.env` | 必要な環境変数 |
+| `metadata.always` | 常に読み込む（デフォルトは false） |
diff --git a/docs/ja/skills/install.mdx b/docs/ja/skills/install.mdx
new file mode 100644
index 0000000..c50e6ca
--- /dev/null
+++ b/docs/ja/skills/install.mdx
@@ -0,0 +1,53 @@
+---
+title: スキルのインストール
+description: 統一コマンドで多様なソースからスキルをインストール
+---
+
+CowAgent は統一された `install` コマンドで、**Cow スキル広場、GitHub、ClawHub** および任意の URL からスキルをインストールできます。チャットでは `/skill install`、ターミナルでは `cow skill install` を使用します。
+
+## スキル広場からインストール
+
+スキル広場を閲覧してインストール：
+
+```text
+/skill list --remote
+/skill install pptx
+```
+
+## GitHub からインストール
+
+リポジトリからの一括インストールとサブディレクトリ指定に対応：
+
+```text
+/skill install larksuite/cli
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+```
+
+## ClawHub からインストール
+
+```text
+/skill install clawhub:baidu-search
+```
+
+## URL からインストール
+
+zip アーカイブと SKILL.md ファイルリンクに対応：
+
+```text
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+/skill install https://example.com/path/to/SKILL.md
+```
+
+## スキルの管理
+
+```text
+/skill list                  # インストール済みスキルを表示
+/skill info pptx             # スキルの詳細を表示
+/skill enable pptx           # スキルを有効化
+/skill disable pptx          # スキルを無効化
+/skill uninstall pptx        # スキルをアンインストール
+```
+
+<Tip>
+  上記のすべてのコマンドは、ターミナルでは `/skill` を `cow skill` に置き換えて使用できます。完全なコマンドドキュメントは[スキル管理コマンド](/ja/cli/skill)を参照してください。
+</Tip>
diff --git a/docs/ja/skills/knowledge-wiki.mdx b/docs/ja/skills/knowledge-wiki.mdx
new file mode 100644
index 0000000..28760c8
--- /dev/null
+++ b/docs/ja/skills/knowledge-wiki.mdx
@@ -0,0 +1,112 @@
+---
+title: knowledge-wiki - ナレッジベース
+description: ローカルの構造化ナレッジベースを管理し、自動でアーカイブ・分類・相互参照を行う
+---
+
+会話で生まれた資料、アイデア、メモをローカルの構造化ナレッジベースに整理し、インデックスとページ間の相互参照を自動で維持します。
+
+`knowledge-wiki` はワークスペース内の `knowledge/` ディレクトリを管理します。Agent の「外部メモリ」のようなものです。`always: true` が設定されているため**常にコンテキストにロード**され、外部依存は不要です。
+
+## いつ起動するか
+
+- 記事、ドキュメント、URL を共有して、後で参照できるように残したいとき
+- 会話の中で長期保存に値する結論が出たとき
+- 以前蓄積したナレッジを調べたいとき
+
+## ディレクトリ構成
+
+```
+knowledge/
+├── index.md           # グローバルインデックス（必ずメンテナンスする）
+├── log.md             # 操作ログ（追記のみ）
+└── <category>/        # カテゴリサブディレクトリ（内容ごとにグループ化）
+    └── <slug>.md      # ナレッジページ（小文字ハイフン区切りのファイル名）
+```
+
+## 3 つの基本操作
+
+### 1. 収録（Ingest）
+
+資料を共有すると、Agent は：
+
+1. 原文を読んで理解し、重要な情報を抽出
+2. どのカテゴリに属するか判断 — まず `index.md` をチェックし、適切なカテゴリがなければ新規作成
+3. `knowledge/<category>/<slug>.md` にナレッジページを生成
+4. インデックス `index.md` とログ `log.md` を更新
+
+### 2. 統合（Synthesize）
+
+会話の中で新しい結論やインサイトが生まれたとき：
+
+1. 適切なカテゴリの下に新しいナレッジページを作成
+2. 関連する既存ページに相互リンクを追加
+3. インデックスとログを更新
+
+### 3. 検索（Query）
+
+以前蓄積したナレッジについて質問されたとき：
+
+1. `index.md` から関連しそうなページを探す
+2. `read` ツールで具体的なページを開く
+3. 必要に応じて `memory_search` で補完検索
+4. 回答にナレッジページへのリンクを含め、ユーザーが原文を確認できるようにする
+
+## ページの書き方
+
+```markdown
+# ページタイトル
+
+> Source: <ソース URL または簡単な説明>
+
+本文。ページ間は相対パスでリンク：
+[関連ページ](../category/related-page.md)
+
+## 要点
+
+- ...
+
+## 関連ページ
+
+- [ページ A](../category/page-a.md) — 関連する理由
+```
+
+<Note>
+- `> Source:` はこのナレッジの出典を記録します。明確な出典がある場合は必ず記載してください
+- 相互参照は重要です：ページを作成・更新したら、関連ページにも逆リンクを追加してください
+- **既に存在するページにのみリンクしてください**。ある概念が独立ページに値する場合は、先にページを作成してからリンクを追加してください
+</Note>
+
+## インデックス形式
+
+`knowledge/index.md` はフラットリスト形式で、カテゴリごとにグループ化し、各ナレッジページを 1 行で表します：
+
+```markdown
+# Knowledge Index
+
+## カテゴリ A
+- [ページタイトル](category-a/page-slug.md) — 一行の要約
+
+## カテゴリ B
+- [ページタイトル](category-b/page-slug.md) — 一行の要約
+```
+
+テーブルや絵文字は使いません。カテゴリ名や構成は柔軟に調整できます。
+
+## ログ形式
+
+`knowledge/log.md` は追記のみ、最新のエントリが一番下：
+
+```markdown
+## [YYYY-MM-DD] ingest | ページタイトル
+## [YYYY-MM-DD] synthesize | ページタイトル
+```
+
+## 執筆ガイドライン
+
+- **ファイル名**は小文字＋ハイフン（例: `machine-learning.md`）
+- **1 ページ 1 トピック** — 関連コンテンツはリンクで繋ぐ
+- **重複ページを作らず、既存ページを更新する**
+- **変更のたびにインデックスを更新する**（`knowledge/index.md`）
+- **要点を抽出し、全文をコピーしない**
+- **会話中にナレッジページを参照する際はフルパスを使用**（例: `[タイトル](knowledge/<category>/<slug>.md)`）。ページ間の相互リンクのみ相対パスを使用
+- **ナレッジページに基づいて回答する際はリンクを含める** — ユーザーが詳細を確認できるように
diff --git a/docs/ja/skills/skill-creator.mdx b/docs/ja/skills/skill-creator.mdx
new file mode 100644
index 0000000..130548e
--- /dev/null
+++ b/docs/ja/skills/skill-creator.mdx
@@ -0,0 +1,180 @@
+---
+title: skill-creator - スキル作成
+description: スキルの作成・インストール・更新、SKILL.md の書き方とディレクトリ構成の標準化
+---
+
+`skill-creator` は「メタスキル」です。Agent が他のスキルを作成・インストール・更新する際に呼び出され、すべてのスキルの `SKILL.md` の書き方とディレクトリ構成を統一します。
+
+## いつ起動するか
+
+- ユーザーが URL やリモートリポジトリからスキルをインストールしたいとき
+- ユーザーが新しいスキルをゼロから作成したいとき
+- 既存のスキルをアップグレード・リファクタリングする必要があるとき
+
+## スキルとは
+
+スキルは「再利用可能な説明書」にオプションのスクリプトやリソースを加えたものです。特定のドメインの専門知識を Agent に注入し、該当タスクをスペシャリストのように処理できるようにします。
+
+スキルには通常、以下が含まれます：
+
+1. **専門ワークフロー** — ある種のタスクの完全な手順
+2. **ツールの使い方** — 特定の API やファイル形式の処理方法
+3. **ドメイン知識** — チームの規約、ビジネスルール、データ構造など
+4. **付属リソース** — スクリプト、参考ドキュメント、テンプレートなど
+
+<Note>
+**基本原則：省けるものは省く。** Agent が自力で推測できない内容だけを書きましょう。1 行追加するたびに「このトークンコストに見合うか？」と自問してください。
+</Note>
+
+## ディレクトリ構成
+
+```
+skill-name/
+├── SKILL.md            # 必須：スキル定義
+│   ├── YAML frontmatter（name / description は必須）
+│   └── Markdown 本文（説明 + 例）
+└── オプションリソース
+    ├── scripts/        # 実行可能スクリプト（Python / Bash など）
+    ├── references/     # 分量が多い参考ドキュメント（Agent が必要時に読む）
+    └── assets/         # テンプレート、アイコンなど（出力に直接使われるもの）
+```
+
+## SKILL.md 仕様
+
+SKILL.md ヘッダーの `frontmatter` フィールド：
+
+| フィールド | 説明 |
+| --- | --- |
+| `name` | スキル名。小文字＋ハイフン、ディレクトリ名と一致させる |
+| `description` | **最も重要なフィールド**。「このスキルが何をするか」「いつ使うべきか」を明記する。Agent はこれを見て呼び出すかどうかを判断する。トリガーに関する記述はすべてここに書き、本文には書かない |
+| `metadata.cowagent.requires.bins` | システムに必要な CLI ツール |
+| `metadata.cowagent.requires.env` | 必要な環境変数（すべて揃っている必要がある） |
+| `metadata.cowagent.requires.anyEnv` | 複数の API Key のうち 1 つあればよい |
+| `metadata.cowagent.requires.anyBins` | 複数のツールのうち 1 つあればよい |
+| `metadata.cowagent.always` | `true` にすると常にロードされ、依存チェックをスキップ |
+| `metadata.cowagent.emoji` | 表示用の絵文字（任意） |
+| `metadata.cowagent.os` | OS 制限、例: `["darwin", "linux"]` |
+
+<Note>
+`category` フィールドは手動で設定する必要はありません。システムが自動的に `skill` に設定します。
+</Note>
+
+API Key 依存の宣言方法は 2 通り：
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      env: ["MYAPI_KEY"]            # 必須
+```
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      anyEnv: ["OPENAI_API_KEY", "LINKAI_API_KEY"]   # いずれか 1 つ
+```
+
+**スキルは依存関係に基づいて自動的に有効/無効になります**：環境変数が揃えば自動有効、不足すれば自動無効。手動で `/skill enable` する必要はありません。
+
+## リソースディレクトリの使い方
+
+| ディレクトリ | 入れるもの | 入れないもの |
+| --- | --- | --- |
+| `scripts/` | 繰り返し実行するコード、確定的な結果が必要なスクリプト | デモ用のコード片 |
+| `references/` | **500 行超**で SKILL.md に収まらない大きなドキュメント（完全な DB スキーマなど） | 一般的な API ドキュメント、チュートリアル |
+| `assets/` | 最終出力に含まれるファイル（テンプレート、アイコン、ボイラープレートなど） | 説明用ドキュメント |
+
+<Warning>
+**原則としてすべての内容を `SKILL.md` に書きます** — リソースディレクトリに分割するのは本当に収まらない場合だけです。
+
+`README.md`、`CHANGELOG.md`、`INSTALLATION_GUIDE.md` などをスキルに追加しないでください。すべて `SKILL.md` に入れましょう。リソースディレクトリには実際に実行するスクリプトや実際に使う素材だけを配置してください。
+</Warning>
+
+## 外部スキルのインストール
+
+インストール後、スキルは `<workspace>/skills/<name>/` に配置されます。
+
+| ソース | インストール方法 |
+| --- | --- |
+| URL（単一ファイル） | curl / web_fetch |
+| URL（zip アーカイブ） | ダウンロードして展開 |
+| ローカル SKILL.md | 直接読み込み |
+| ローカル zip アーカイブ | 展開 |
+
+インストール手順：
+
+1. `SKILL.md` を見つける（アーカイブのルートまたはサブディレクトリにある場合がある）
+2. frontmatter から `name` を読み取る
+3. **スキルディレクトリ全体**（`SKILL.md`、`scripts/`、`assets/` など）を `<workspace>/skills/<name>/` にコピー
+4. アーカイブに `INSTALL.md` などのセットアップスクリプトがあれば実行するが、最終的に `<workspace>/skills/<name>/` に収まっている必要がある
+
+## スキルをゼロから作成
+
+推奨手順：
+
+1. **要件を明確にする** — ユーザーに具体的なユースケースをいくつか挙げてもらう（一度に多く聞きすぎない）
+2. **構成を計画する** — スクリプトは必要か？参考ドキュメントは？テンプレートは？
+3. **スキャフォールド** — 初期化スクリプトを使用：
+
+   ```bash
+   scripts/init_skill.py <skill-name> --path <workspace>/skills [--resources scripts,references,assets] [--examples]
+   ```
+
+4. **内容を埋める** — SKILL.md を書き、スクリプトとリソースを追加。スクリプトは必ず実行テストする
+5. **バリデーション**（任意）：
+
+   ```bash
+   scripts/quick_validate.py <workspace>/skills/<skill-name>
+   ```
+
+6. **イテレーション** — 実際の使用フィードバックに基づいて継続的に改善
+
+## 命名規則
+
+- 小文字、数字、ハイフンのみ使用。ユーザーの入力は正規化する（例: `Plan Mode` → `plan-mode`）
+- 64 文字以内
+- 短く、動詞で始め、一目で何をするか分かるように
+- 必要に応じてツール名をプレフィックスにする（例: `gh-address-comments`、`linear-address-issue`）
+- ディレクトリ名と `name` フィールドは完全に一致させる
+
+## 3 段階ローディング
+
+スキルは一度にすべてコンテキストに読み込まれるわけではなく、3 段階で必要に応じてロードされます：
+
+1. **メタ情報**（`name` + `description`） — 常にコンテキスト内（約 100 語）。Agent がスキルを使うかどうかの判断に使用
+2. **SKILL.md 本文** — スキルが有効化されたときだけロード。500 行以内を推奨
+3. **リソースファイル** — Agent が必要なときに読み込む
+
+複数のバリエーション（例: マルチクラウドデプロイ）を持つスキルは次のように整理：
+
+```
+cloud-deploy/
+├── SKILL.md             # メインワークフローとプロバイダー選択ロジック
+└── references/
+    ├── aws.md
+    ├── gcp.md
+    └── azure.md
+```
+
+ユーザーが AWS を選んだら、Agent は `aws.md` だけを読みます。3 社分のドキュメントをすべてロードする必要はありません。
+
+## よくあるデザインパターン
+
+**ステップ式**：番号付きの手順と対応スクリプト。
+
+```markdown
+1. フォーム構造を分析（analyze_form.py を実行）
+2. フィールドマッピングを生成（fields.json を編集）
+3. フォームを自動入力（fill_form.py を実行）
+```
+
+**分岐式**：ユーザーの意図に応じて異なるフローへ。
+
+```markdown
+1. 操作タイプを判定：
+   **新規作成？** → 「作成フロー」へ
+   **既存の編集？** → 「編集フロー」へ
+```
+
+**テンプレート式**：出力形式に厳密な要件がある場合、SKILL.md にテンプレートを含め、Agent にそれに従って出力させる。
diff --git a/docs/ja/tools/bash.mdx b/docs/ja/tools/bash.mdx
new file mode 100644
index 0000000..8296e2b
--- /dev/null
+++ b/docs/ja/tools/bash.mdx
@@ -0,0 +1,28 @@
+---
+title: bash - ターミナル
+description: システムコマンドの実行
+---
+
+現在の作業ディレクトリでBashコマンドを実行し、stdoutとstderrを返します。`env_config` で設定されたAPIキーは自動的に環境変数に注入されます。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `command` | string | はい | 実行するコマンド |
+| `timeout` | integer | いいえ | タイムアウト（秒） |
+
+## ユースケース
+
+- パッケージや依存関係のインストール
+- コードやテストの実行
+- アプリケーションやサービスのデプロイ（Nginx設定、プロセス管理など）
+- システム管理とトラブルシューティング
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
diff --git a/docs/ja/tools/browser.mdx b/docs/ja/tools/browser.mdx
new file mode 100644
index 0000000..ed332f9
--- /dev/null
+++ b/docs/ja/tools/browser.mdx
@@ -0,0 +1,172 @@
+---
+title: browser - ブラウザ
+description: ブラウザを操作してWebページにアクセス・操作する
+---
+
+Chromiumブラウザを操作してWebページのナビゲーション、要素操作、コンテンツ取得を行います。JavaScriptでレンダリングされる動的ページに対応し、簡略化したDOMスナップショットによりAgentが効率的にページ構造を理解できます。
+
+## インストール
+
+<Tabs>
+  <Tab title="CLIインストール（推奨）">
+    ```bash
+    cow install-browser
+    ```
+
+    このコマンドは以下を自動で実行します：
+    - `playwright` Pythonパッケージのインストール（古いシステムでは互換バージョンに自動フォールバック）
+    - Linuxにおけるシステム依存のインストール
+    - Chromiumブラウザのダウンロード（Linuxサーバーでは自動的にヘッドレス軽量版を使用）
+    - 中国本土ネットワークの自動検知とミラー高速化
+  </Tab>
+  <Tab title="手動インストール">
+    ```bash
+    pip install playwright
+    playwright install chromium
+    ```
+
+    Linuxサーバーではシステム依存も必要：
+    ```bash
+    sudo playwright install-deps chromium
+    ```
+
+    古いシステム（例: Ubuntu 18.04、glibc < 2.28）では互換バージョンをインストール：
+    ```bash
+    pip install playwright==1.28.0
+    python -m playwright install chromium
+    ```
+
+    中国からChromiumのダウンロードを高速化したい場合：
+    ```bash
+    export PLAYWRIGHT_DOWNLOAD_HOST=https://registry.npmmirror.com/-/binary/playwright
+    python -m playwright install chromium
+    ```
+  </Tab>
+</Tabs>
+
+<Note>
+  1. Ubuntu 20.04+、Debian 10+、macOS、Windowsをサポート。Ubuntu 18.04などの古いシステムでは互換バージョンに自動フォールバックします。
+  2. ブラウザToolは依存関係が大きい（約300MB）ため、不要な場合はインストールを省略できます。軽量なWebコンテンツ取得には `web_fetch` Toolをご利用ください。
+</Note>
+
+## ワークフロー
+
+Agentがブラウザを使う典型的な流れ：
+
+1. **`navigate`** — 対象URLを開く
+2. **`snapshot`** — 簡略化したDOMを取得し、操作可能な要素には自動で番号（`ref`）が付く
+3. **`click` / `fill` / `select`** — `ref`で要素を操作する
+4. **`snapshot`** — 再度スナップショットを取得して結果を確認
+
+## サポートされる操作
+
+| 操作 | 説明 | 主なパラメータ |
+| --- | --- | --- |
+| `navigate` | URLを開く | `url` |
+| `snapshot` | 構造化されたページテキストを取得（主な利用方法） | `selector`（任意） |
+| `click` | 要素をクリック | `ref` または `selector` |
+| `fill` | 入力欄にテキストを入力 | `ref` または `selector`、`text` |
+| `select` | プルダウンから選択 | `ref` または `selector`、`value` |
+| `scroll` | ページをスクロール | `direction`（up/down/left/right） |
+| `screenshot` | スクリーンショットをワークスペースに保存 | `full_page` |
+| `wait` | 要素または時間を待機 | `selector`、`timeout` |
+| `press` | キー入力（Enter、Tabなど） | `key` |
+| `back` / `forward` | ブラウザの戻る／進む | - |
+| `get_text` | 要素のテキストを取得 | `selector` |
+| `evaluate` | JavaScriptを実行 | `script` |
+
+## ユースケース
+
+- 指定URLにアクセスして動的コンテンツを取得
+- フォーム入力やログイン操作
+- Web要素の操作（ボタンクリック、項目選択など）
+- デプロイ後のWebページ動作確認
+- JSレンダリングが必要な動的コンテンツのスクレイピング
+
+## 動作モード
+
+実行環境に応じてブラウザのモードが自動選択されます：
+
+| 環境 | モード |
+| --- | --- |
+| macOS / Windows | ヘッドモード（ブラウザウィンドウを表示） |
+| Linuxデスクトップ（DISPLAYあり） | ヘッドモード |
+| Linuxサーバー（DISPLAYなし） | ヘッドレスモード |
+
+`config.json`で手動上書き可能：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "headless": true
+    }
+  }
+}
+```
+
+## ログイン状態の永続化
+
+**対象サイトに一度ログインすれば、Agentは以降そのまま利用できます。** 2つの方法があります：
+
+### 方法1: Persistentモード（デフォルト）
+
+設定不要、すぐに利用可能。ログイン情報は `~/.cow/browser_profile` に保存されます。
+
+毎回クリーンな環境で起動したい場合は、永続化を無効化：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "persistent": false
+    }
+  }
+}
+```
+
+### 方法2: CDPモード（既存のChromeに接続）
+
+Playwright付属のChromiumではなく、別途起動した本物のChromeにAgentを接続させることで、完全なブラウザフィンガープリントが得られます。Bot検知が厳しいサイトに有効です。
+
+Chromeをデバッグポートと専用のユーザーデータディレクトリ付きで起動します：
+
+<Tabs>
+  <Tab title="macOS">
+    ```bash
+    "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Linux">
+    ```bash
+    google-chrome \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Windows">
+    ```powershell
+    & "C:\Program Files\Google\Chrome\Application\chrome.exe" `
+      --remote-debugging-port=9222 `
+      --user-data-dir="$env:USERPROFILE\.cow\chrome-cdp"
+    ```
+  </Tab>
+</Tabs>
+
+`config.json` で接続先を指定：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "cdp_endpoint": "http://localhost:9222"
+    }
+  }
+}
+```
+
+<Note>
+  Chrome 137以降では `--remote-debugging-port` を専用の `--user-data-dir` と組み合わせる必要があるため、CDPで起動するChromeは**普段使いのChromeのログイン状態をそのまま流用できません**。専用プロファイル内で一度ログインし直す必要があります。
+</Note>
diff --git a/docs/ja/tools/edit.mdx b/docs/ja/tools/edit.mdx
new file mode 100644
index 0000000..634b97e
--- /dev/null
+++ b/docs/ja/tools/edit.mdx
@@ -0,0 +1,24 @@
+---
+title: edit - ファイル編集
+description: テキスト置換によるファイル編集
+---
+
+テキスト置換によるファイル編集を行います。`oldText` が空の場合、ファイル末尾に追記します。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ファイルパス |
+| `oldText` | string | はい | 置換対象の元テキスト（空の場合は追記） |
+| `newText` | string | はい | 置換後のテキスト |
+
+## ユースケース
+
+- 設定ファイルの特定パラメータの変更
+- コードのバグ修正
+- ファイル内の特定位置へのコンテンツ挿入
diff --git a/docs/ja/tools/env-config.mdx b/docs/ja/tools/env-config.mdx
new file mode 100644
index 0000000..be526f6
--- /dev/null
+++ b/docs/ja/tools/env-config.mdx
@@ -0,0 +1,36 @@
+---
+title: env_config - 環境設定
+description: APIキーとシークレットの管理
+---
+
+ワークスペースの `.env` ファイルで環境変数（APIキーやシークレット）を管理し、会話形式で安全に更新できます。セキュリティ保護とマスキング機能を内蔵しています。
+
+## 依存関係
+
+| 依存関係 | インストールコマンド |
+| --- | --- |
+| `python-dotenv` ≥ 1.0.0 | `pip install python-dotenv>=1.0.0` |
+
+オプション依存関係のインストールに含まれています：`pip3 install -r requirements-optional.txt`
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `action` | string | はい | 操作タイプ：`get`、`set`、`list`、`delete` |
+| `key` | string | いいえ | 環境変数名 |
+| `value` | string | いいえ | 環境変数の値（`set` の場合のみ） |
+
+## 使い方
+
+設定したいキーをAgentに伝えると、自動的にこのToolが呼び出されます：
+
+- 「BOCHA_API_KEYを設定して」
+- 「OPENAI_API_KEYをsk-xxxに設定して」
+- 「設定済みの環境変数を表示して」
+
+設定されたキーは `bash` Toolの実行環境に自動的に注入されます。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
diff --git a/docs/ja/tools/index.mdx b/docs/ja/tools/index.mdx
new file mode 100644
index 0000000..7b2b068
--- /dev/null
+++ b/docs/ja/tools/index.mdx
@@ -0,0 +1,60 @@
+---
+title: Tools 概要
+description: CowAgent 組み込みToolシステム
+---
+
+Toolは、AgentがOSリソースにアクセスするための中核機能です。Agentはタスクの要件に基づいてToolをインテリジェントに選択・呼び出し、ファイル操作、コマンド実行、Web検索、スケジュールタスクなどを実行します。Toolは `agent/tools/` ディレクトリに実装されています。
+
+## 組み込みTool
+
+以下のToolは追加設定なしでデフォルトで利用可能です：
+
+<CardGroup cols={2}>
+  <Card title="read - ファイル読み取り" icon="file" href="/ja/tools/read">
+    ファイル内容を読み取り、テキスト・画像・PDFに対応
+  </Card>
+  <Card title="write - ファイル書き込み" icon="pen" href="/ja/tools/write">
+    ファイルの作成または上書き
+  </Card>
+  <Card title="edit - ファイル編集" icon="pen-to-square" href="/ja/tools/edit">
+    テキスト置換によるファイル編集
+  </Card>
+  <Card title="ls - ディレクトリ一覧" icon="folder-open" href="/ja/tools/ls">
+    ディレクトリの内容を一覧表示
+  </Card>
+  <Card title="bash - ターミナル" icon="terminal" href="/ja/tools/bash">
+    システムコマンドの実行
+  </Card>
+  <Card title="send - ファイル送信" icon="paper-plane" href="/ja/tools/send">
+    ファイルや画像をユーザーに送信
+  </Card>
+  <Card title="memory - メモリ" icon="brain" href="/ja/tools/memory">
+    長期メモリの検索と読み取り
+  </Card>
+</CardGroup>
+
+## オプションTool
+
+以下のToolは追加の依存関係またはAPIキーの設定が必要です：
+
+<CardGroup cols={2}>
+  <Card title="env_config - 環境設定" icon="key" href="/ja/tools/env-config">
+    APIキーとシークレットの管理
+  </Card>
+  <Card title="scheduler - スケジューラ" icon="clock" href="/ja/tools/scheduler">
+    スケジュールタスクの作成と管理
+  </Card>
+  <Card title="web_search - Web検索" icon="magnifying-glass" href="/ja/tools/web-search">
+    インターネットからリアルタイム情報を検索
+  </Card>
+</CardGroup>
+
+## MCP Tool
+
+[Model Context Protocol](https://modelcontextprotocol.io) を介して、コミュニティの既製 Tool（地図、GitHub、Notion など数千種類）を統合できます。`mcp.json` を一度設定するだけで利用可能です：
+
+<CardGroup cols={1}>
+  <Card title="MCP - 外部Toolエコシステム" icon="plug" href="/ja/tools/mcp">
+    標準の stdio / SSE トランスポートをサポート。ホットリロードで、コード変更不要
+  </Card>
+</CardGroup>
diff --git a/docs/ja/tools/ls.mdx b/docs/ja/tools/ls.mdx
new file mode 100644
index 0000000..67ca1d2
--- /dev/null
+++ b/docs/ja/tools/ls.mdx
@@ -0,0 +1,23 @@
+---
+title: ls - ディレクトリ一覧
+description: ディレクトリの内容を一覧表示
+---
+
+ディレクトリの内容をアルファベット順にソートして一覧表示します。ディレクトリには `/` が付与され、隠しファイルも含まれます。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ディレクトリパス。相対パスはワークスペースディレクトリを基準とします |
+| `limit` | integer | いいえ | 返すエントリの最大数、デフォルト500 |
+
+## ユースケース
+
+- プロジェクト構造の閲覧
+- 特定ファイルの検索
+- ディレクトリの存在確認
diff --git a/docs/ja/tools/mcp.mdx b/docs/ja/tools/mcp.mdx
new file mode 100644
index 0000000..236d221
--- /dev/null
+++ b/docs/ja/tools/mcp.mdx
@@ -0,0 +1,134 @@
+---
+title: MCP Tool
+description: Model Context Protocol を介して外部Toolエコシステムを統合
+---
+
+CowAgent は [Model Context Protocol (MCP)](https://modelcontextprotocol.io) をサポートしており、コミュニティで提供されている数万種類の MCP Tool を Agent から直接呼び出せます。`mcp.json` を一度設定すれば、組み込みToolとまったく同じ形で LLM に公開され、自動的に選択・呼び出されます。
+
+## 設定ファイル
+
+CowAgent は `~/cow/mcp.json` を読み込みます。ファイルが存在しない場合は MCP Tool は読み込まれず、エラーにもなりません。
+
+Docker デプロイの場合、公式の `docker-compose.yml` はホスト側の `./cow` をコンテナ内の `/home/agent/cow`（コンテナユーザーの `~/cow`）にマウント済みです。ホスト側の `./cow/` に `mcp.json` を置くだけで反映されます。
+
+### 標準フォーマット
+
+MCP コミュニティ標準に完全準拠しており、Claude Desktop / Cursor と同じです：
+
+```json
+{
+  "mcpServers": {
+    "<server-name>": {
+      "command": "npx",
+      "args": ["-y", "some-mcp-package"],
+      "env": {
+        "API_KEY": "your-key-here"
+      }
+    }
+  }
+}
+```
+
+| フィールド | 必須 | 説明 |
+| --- | --- | --- |
+| `command` | stdio | サーバーを起動する実行コマンド（`npx`、`python`、`uvx` など） |
+| `args` | 任意 | `command` に渡す引数 |
+| `env` | 任意 | サブプロセスの環境変数。API Key などに利用 |
+| `url` | SSE / Streamable HTTP | リモートエンドポイントの URL（`command` と二者択一） |
+| `type` | リモート | リモートトランスポート種別：`sse` または `streamable-http`（既定は `sse`） |
+| `headers` | 任意 | リモートリクエストの追加 HTTP ヘッダ（`Authorization` など）。Streamable HTTP のみ |
+| `scope` | 任意 | OAuth スコープ。OAuth 認可が必要なリモート server のみ使用（任意） |
+| `disabled` | 任意 | `true` のとき該当サーバーをスキップ。一時的に無効化したいときに便利 |
+
+### 完全な例
+
+```json
+{
+  "mcpServers": {
+    "fetch": {
+      "command": "uvx",
+      "args": ["mcp-server-fetch"]
+    },
+    "github": {
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-github"],
+      "env": {
+        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
+      }
+    }
+  }
+}
+```
+
+- **fetch**：汎用 Web ページ取得。ページ本文を返す。API Key 不要
+- **github**：GitHub のリポジトリ、Issue、PR などにアクセス。Personal Access Token が必要
+
+## Agent に設定を任せる
+
+CowAgent には `read` / `write` / `edit` Tool が組み込まれているため、**MCP の設定をそのまま Agent に渡して、ファイルに書き込んでもらえます**：
+
+例：
+
+```markdown
+この MCP を ~/cow/mcp.json に追加してください：
+
+{"mcpServers":{"fetch":{"command":"uvx","args":["mcp-server-fetch"]}}}
+```
+
+Agent は次のように動作します：
+
+1. 既存の MCP 設定ファイルを読み込み、新しい server エントリをマージ（既存の項目は保持）
+2. 増分の MCP Server を自動でリロードし、次のメッセージから対応する Tool が利用可能に
+
+## Web 認可（OAuth）
+
+一部のリモート MCP は OAuth の Web 認可が必要で、そのまま設定すると `401` が返ります。CowAgent は標準的な OAuth フローを内蔵しているため、**token を手動で入力する必要はなく**、通常どおり設定するだけです。例：
+
+```json
+{
+  "mcpServers": {
+    "xmind": {
+      "type": "streamable-http",
+      "url": "https://app.xmind.com/api/mcp"
+    }
+  }
+}
+```
+
+server の初回ロードで `401` が返ると、認可が自動的に開始されます。ローカル実行では**自動的にブラウザが開き**、サーバー環境では**認可リンクがログに出力**されるので、ブラウザで開いてください。承認すると server はすぐにオンラインになり、token は期限切れ時に自動更新されるため、再認可は不要です。
+
+- **Web サービスが必要**：認可コールバックは Web コンソール（既定ポート `9899`）で受け取るため、Web channel が起動している必要があります。
+- **認証情報の保存**：token は `~/.cow/mcp_oauth.json` に永続化され、再起動後も再利用されます。
+- **コールバック URL**：既定は `http://127.0.0.1:9899/mcp/oauth/callback`。サーバーに配置し認可用ブラウザが別の端末にある場合は、`config.json` に `mcp_oauth_redirect_base`（例：`http://あなたのIP:9899`）を設定してください。
+
+## 動作の仕組み
+
+- **起動時の非同期ロード**：`mcp.json` に設定された全 server はバックグラウンドで非同期に読み込まれ、メインループをブロックしません。会話はすぐに開始できます
+- **ホットリロード**：ユーザーまたは Agent が `mcp.json` を変更すると、メッセージ処理完了時に変更された server のみが自動でリロードされます。cow の再起動は不要です
+- **フラットな公開**：MCP server が公開する各メソッドは独立した Tool として並列に公開され、LLM が直接選択して呼び出します。二段階の判断は不要です
+
+## サポートされるトランスポート
+
+| トランスポート | 説明 | 設定フィールド |
+| --- | --- | --- |
+| **stdio** | サブプロセス通信。最も一般的で、コミュニティのエコシステムが最も豊富 | `command` + `args` |
+| **SSE** | HTTP Server-Sent Events。従来のリモート用トランスポート | `url`（既定） |
+| **Streamable HTTP** | 新しい単一エンドポイント方式。SSE を段階的に置き換え | `type: "streamable-http"` + `url` |
+
+## トラブルシューティング
+
+| 症状 | 確認ポイント |
+| --- | --- |
+| 起動後に MCP Tool が一つもない | `~/cow/mcp.json` が存在し、JSON が正しいか確認 |
+| 特定の server が読み込みに失敗する | 起動ログの `[MCP] Server 'xxx' load failed` を確認。多くは依存関係の不足や API Key 未設定 |
+| `mcp.json` の変更が反映されない | 変更は **次のメッセージ** から有効になる。server の設定が実質的に変わっていない（コメントだけ変更など）場合は再起動されない |
+| Docker デプロイ | ホストの `./cow` がコンテナ内の `/home/agent/cow` にマウントされていることを確認し、ホスト側の `./cow/` に `mcp.json` を配置。または Agent に直接インストールを依頼 |
+
+## おすすめ MCP マーケットプレイス
+
+各種サードパーティのマーケットプレイスから既製の MCP server を探し、JSON 設定をコピーしてそのまま利用できます。例：
+
+- [mcp.so](https://mcp.so) — グローバル MCP サービスインデックス
+- [ModelScope MCP 広場](https://modelscope.cn/mcp) — 魔搭コミュニティの MCP 広場、中国本土からのアクセスが安定
+
+MCP 標準プロトコル（stdio / SSE / Streamable HTTP）に準拠していれば、コードを一切変更せずに CowAgent に統合できます。
diff --git a/docs/ja/tools/memory.mdx b/docs/ja/tools/memory.mdx
new file mode 100644
index 0000000..d82791c
--- /dev/null
+++ b/docs/ja/tools/memory.mdx
@@ -0,0 +1,43 @@
+---
+title: memory - メモリ & ナレッジ
+description: 長期メモリとナレッジベースファイルの検索・読み取り
+---
+
+メモリToolには `memory_search`（メモリ検索）と `memory_get`（メモリまたはナレッジファイル読み取り）の2つのサブToolがあります。
+
+[ナレッジベース](/ja/knowledge) 機能が有効な場合、両ツールとも `knowledge/` ディレクトリのファイルへのアクセスもサポートします。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。Agent Coreのメモリシステムによって管理されます。
+
+## memory_search
+
+キーワードとベクトルのハイブリッド検索で過去のメモリとナレッジベースの内容を検索します。
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `query` | string | はい | 検索クエリ |
+
+## memory_get
+
+特定のメモリファイルまたはナレッジファイルの内容を読み取ります。
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ファイルの相対パス（例：`MEMORY.md`、`memory/2026-01-01.md`、`knowledge/concepts/rag.md`） |
+| `start_line` | integer | いいえ | 開始行番号 |
+| `end_line` | integer | いいえ | 終了行番号 |
+
+## 仕組み
+
+Agentは以下のシナリオでメモリToolを自動的に呼び出します：
+
+- ユーザーが重要な情報を共有した場合 → メモリに保存
+- 過去のコンテキストが必要な場合 → 関連するメモリを検索
+- 会話が一定の長さに達した場合 → 要約を抽出して保存
+- 専門知識について議論する場合 → ナレッジベースから関連ページを検索
+
+<Note>
+  設定で `knowledge` が `false` に設定されている場合、ツールの説明と検索範囲は自動的にメモリファイルのみに調整されます。
+</Note>
diff --git a/docs/ja/tools/read.mdx b/docs/ja/tools/read.mdx
new file mode 100644
index 0000000..73ba21e
--- /dev/null
+++ b/docs/ja/tools/read.mdx
@@ -0,0 +1,24 @@
+---
+title: read - ファイル読み取り
+description: ファイル内容の読み取り
+---
+
+ファイルの内容を読み取ります。テキストファイル、PDFファイル、画像（メタデータを返す）などに対応しています。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ファイルパス。相対パスはワークスペースディレクトリを基準とします |
+| `offset` | integer | いいえ | 開始行番号（1始まり）。負の値は末尾からの読み取り |
+| `limit` | integer | いいえ | 読み取る行数 |
+
+## ユースケース
+
+- 設定ファイルやログファイルの閲覧
+- コードファイルの読み取りと分析
+- 画像・動画ファイルの情報確認
diff --git a/docs/ja/tools/scheduler.mdx b/docs/ja/tools/scheduler.mdx
new file mode 100644
index 0000000..3e85eed
--- /dev/null
+++ b/docs/ja/tools/scheduler.mdx
@@ -0,0 +1,40 @@
+---
+title: scheduler - スケジューラ
+description: スケジュールタスクの作成と管理
+---
+
+柔軟なスケジュール設定と実行モードを備えた、動的スケジュールタスクの作成と管理を行います。
+
+## 依存関係
+
+| 依存関係 | インストールコマンド |
+| --- | --- |
+| `croniter` ≥ 2.0.0 | `pip install croniter>=2.0.0` |
+
+コア依存関係に含まれています：`pip3 install -r requirements.txt`
+
+## スケジュールモード
+
+| モード | 説明 |
+| --- | --- |
+| ワンタイム | 指定した時刻に1回だけ実行 |
+| 固定間隔 | 一定の時間間隔で繰り返し実行 |
+| Cron式 | Cron構文を使用した複雑なスケジュール定義 |
+
+## 実行モード
+
+- **固定メッセージ**: トリガー時にプリセットメッセージを送信
+- **Agent動的タスク**: トリガー時にAgentがインテリジェントにタスクを実行
+
+## 使い方
+
+自然言語でスケジュールタスクを作成・管理できます：
+
+- 「毎朝9時に天気予報を送って」
+- 「2時間ごとにサーバーのステータスを確認して」
+- 「明日の午後3時に会議のリマインドをして」
+- 「すべてのスケジュールタスクを表示して」
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
diff --git a/docs/ja/tools/send.mdx b/docs/ja/tools/send.mdx
new file mode 100644
index 0000000..f1f7cd4
--- /dev/null
+++ b/docs/ja/tools/send.mdx
@@ -0,0 +1,23 @@
+---
+title: send - ファイル送信
+description: ユーザーへのファイル送信
+---
+
+ユーザーにファイル（画像、動画、音声、ドキュメントなど）を送信します。ユーザーが明示的にファイルの送信・共有を要求した場合に使用されます。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ファイルパス。絶対パスまたはワークスペースからの相対パス |
+| `message` | string | いいえ | 添付メッセージ |
+
+## ユースケース
+
+- 生成したコードやドキュメントをユーザーに送信
+- スクリーンショットやチャートの送信
+- ダウンロードしたファイルの共有
diff --git a/docs/ja/tools/vision.mdx b/docs/ja/tools/vision.mdx
new file mode 100644
index 0000000..cf0850c
--- /dev/null
+++ b/docs/ja/tools/vision.mdx
@@ -0,0 +1,75 @@
+---
+title: vision - 画像理解
+description: 画像コンテンツを分析（認識、説明、OCR など）
+---
+
+Vision API を使用してローカル画像や画像 URL を分析します。コンテンツの説明、テキスト抽出（OCR）、オブジェクト認識などに対応しています。
+
+## モデル選択
+
+Vision ツールは多段階の自動選択 + 自動フォールバック戦略を採用しており、手動設定なしで利用できます：
+
+1. **メインモデル** — 現在設定されているメインモデルを優先的に使用して画像認識を行います（マルチモーダルモデルである必要があります）
+2. **その他の設定済みモデル** — API Key が設定済みのその他のマルチモーダルモデルを自動的に検出して候補とします
+
+現在のプロバイダーで呼び出しに失敗した場合、成功するかすべて失敗するまで自動的に次のプロバイダーを試行します。
+
+### 対応モデル
+
+| プロバイダー | ビジョンモデル | 説明 |
+| --- | --- | --- |
+| OpenAI / 互換プロトコル | メインモデルを使用 | すべての OpenAI 互換マルチモーダルモデルに対応 |
+| 通義千問 (DashScope) | メインモデルを使用 | 例：qwen3.7-plus など |
+| Claude | メインモデルを使用 | Anthropic ネイティブ画像形式 |
+| Gemini | メインモデルを使用 | inlineData 形式 |
+| 豆包 (Doubao) | メインモデルを使用 | doubao-seed-2-1 シリーズがネイティブ対応 |
+| Kimi (Moonshot) | メインモデルを使用 | kimi-k2.6、kimi-k2.5 がネイティブ対応 |
+| 百度 Qianfan | メインモデルを使用 | デフォルトでマルチモーダルメインモデル（`ernie-5.1` など）を使用。メインモデルが非対応の場合は `ernie-4.5-turbo-vl` にフォールバック |
+| 智谱 AI | glm-5v-turbo | 常にビジョン専用モデルを使用 |
+| MiniMax | MiniMax-Text-01 | 常にビジョン専用モデルを使用 |
+
+<Note>
+  智谱と MiniMax のテキストモデルは画像理解に対応していないため、常に対応するビジョン専用モデルが使用されます。手動で指定する必要はありません。
+</Note>
+
+> `use_linkai=true` の場合、デフォルトで LinkAI のマルチモーダルモデルが使用されます。
+
+## カスタム設定
+
+Vision で使用するモデルを指定したい場合は、`config.json` に以下のように設定できます：
+
+```json
+{
+    "tools": {
+        "vision": {
+            "model": "gpt-4.1"
+        }
+    }
+}
+```
+
+指定したモデルが**優先的に使用**され、ツールはモデル名に応じて対応するプロバイダーへ自動ルーティングします。呼び出しに失敗した場合は、他の設定済みプロバイダーへ自動的にフォールバックします。
+
+ほとんどの場合、設定は不要です。メインモデルがマルチモーダルに対応しているか、ビジョン対応の API Key が 1 つでも設定されていれば自動的に動作します。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `image` | string | はい | ローカルファイルパスまたは HTTP(S) 画像 URL |
+| `question` | string | はい | 画像に対する質問 |
+
+対応画像形式：jpg、jpeg、png、gif、webp
+
+
+
+## ユースケース
+
+- 画像コンテンツの説明
+- 画像からのテキスト抽出（OCR）
+- オブジェクト、色、シーンの認識
+- スクリーンショットやスキャン文書などの分析
+
+<Note>
+  1MB を超える画像は自動的に圧縮してアップロードされます。すべての画像（リモート URL を含む）は base64 に統一変換して送信され、すべてのモデルバックエンドとの互換性を確保します。
+</Note>
diff --git a/docs/ja/tools/web-fetch.mdx b/docs/ja/tools/web-fetch.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/ja/tools/web-fetch.mdx
@@ -0,0 +1,32 @@
+---
+title: web_fetch - Web 取得
+description: Web ページやドキュメントのコンテンツを取得
+---
+
+HTTP/HTTPS URL の内容を取得します。Web ページからは可読テキストを抽出し、ドキュメントファイル（PDF、Word、Excel など）は自動でダウンロードして解析します。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `url` | string | はい | HTTP/HTTPS URL（Web ページまたはドキュメント） |
+
+## 対応ファイル形式
+
+| 種別 | 形式 |
+| --- | --- |
+| PDF | `.pdf` |
+| Word | `.docx` |
+| テキスト | `.txt`、`.md`、`.csv`、`.log` |
+| 表計算 | `.xls`、`.xlsx` |
+| プレゼン | `.ppt`、`.pptx` |
+
+## ユースケース
+
+- Web ページの可読テキストを抽出する
+- リモートドキュメントのダウンロードと解析
+- API レスポンスの確認
+
+<Note>
+  `web_fetch` は静的 HTML のみ取得できます。JavaScript レンダリングが必要なページ（SPA など）は `browser` ツールを使用してください。
+</Note>
diff --git a/docs/ja/tools/web-search.mdx b/docs/ja/tools/web-search.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/ja/tools/web-search.mdx
@@ -0,0 +1,51 @@
+---
+title: web_search - Web 検索
+description: インターネットからリアルタイム情報を検索。複数の検索プロバイダーに対応
+---
+
+インターネットからリアルタイム情報、ニュース、リサーチなどを検索します。Bocha、百度 Qianfan、智谱（Zhipu）、LinkAI の 4 つのバックエンドに対応しており、いずれか 1 社を設定すれば利用可能です。
+
+<Tip>
+  [Web コンソール](/ja/channels/web) の「モデル管理 → 検索」パネルから、プロバイダーと戦略を可視化して設定するのが推奨です。設定ファイルを手動で編集する必要はありません。
+</Tip>
+
+## プロバイダー
+
+| プロバイダー | 認証情報 | 申請窓口 |
+| --- | --- | --- |
+| Bocha | `tools.web_search.bocha_api_key` | [Bocha Open Platform](https://open.bochaai.com/) |
+| 百度 Qianfan | `qianfan_api_key` を再利用 | [Qianfan コンソール](https://cloud.baidu.com/doc/qianfan/s/2mh4su4uy) |
+| 智谱 Zhipu | `zhipu_ai_api_key` を再利用 | [Zhipu Open Platform](https://docs.bigmodel.cn/cn/guide/tools/web-search) |
+| LinkAI | `linkai_api_key` を再利用 | [LinkAI コンソール](https://link-ai.tech/console/interface) |
+
+Bocha のみ独立した `bocha_api_key` が必要ですが、他の 3 社は対応するモデルの API Key をそのまま再利用するため、モデルを設定すれば検索機能も同時に利用可能になります。
+
+## ルーティング戦略
+
+```json
+{
+  "tools": {
+    "web_search": {
+      "strategy": "auto",
+      "provider": ""
+    }
+  }
+}
+```
+
+- `auto`（デフォルト）：Agent が設定済みのプロバイダーから自動的に選択し、1 回のタスク内で複数回呼び出し、異なるプロバイダーを切り替えてより包括的な結果を取得できます。未指定の場合は `bocha → qianfan → zhipu → linkai` の順でフォールバックします。
+- `fixed`：`provider` で指定したプロバイダーに固定。該当プロバイダーの認証情報が欠けている場合は自動的に auto の順序にフォールバックします。
+
+## ツールパラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `query` | string | はい | 検索キーワード |
+| `count` | integer | いいえ | 返却する結果数（1–50、デフォルト 10） |
+| `freshness` | string | いいえ | 期間指定：`noLimit`（デフォルト）、`oneDay`、`oneWeek`、`oneMonth`、`oneYear`、または `2025-01-01..2025-02-01` のような日付範囲 |
+| `summary` | boolean | いいえ | ページ要約を返すか（デフォルト false） |
+| `provider` | string | いいえ | `auto` 戦略で複数プロバイダーを設定している場合に表示。単回のプロバイダー切り替えに使用 |
+
+<Note>
+  4 社の認証情報がいずれも未設定の場合、このツールは Agent に登録されません。
+</Note>
diff --git a/docs/ja/tools/write.mdx b/docs/ja/tools/write.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/ja/tools/write.mdx
@@ -0,0 +1,27 @@
+---
+title: write - ファイル書き込み
+description: ファイルの作成または上書き
+---
+
+ファイルにコンテンツを書き込みます。ファイルが存在しない場合は新規作成し、存在する場合は上書きします。親ディレクトリは自動的に作成されます。
+
+## 依存関係
+
+追加の依存関係は不要で、デフォルトで利用可能です。
+
+## パラメータ
+
+| パラメータ | 型 | 必須 | 説明 |
+| --- | --- | --- | --- |
+| `path` | string | はい | ファイルパス |
+| `content` | string | はい | 書き込む内容 |
+
+## ユースケース
+
+- 新しいコードファイルやスクリプトの作成
+- 設定ファイルの生成
+- 処理結果の保存
+
+<Note>
+  1回の書き込みは10KBを超えないようにしてください。大きなファイルの場合は、まずスケルトンを作成し、editツールを使用してチャンクごとにコンテンツを追加してください。
+</Note>
diff --git a/docs/knowledge/index.mdx b/docs/knowledge/index.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/knowledge/index.mdx
@@ -0,0 +1,93 @@
+---
+title: Personal Knowledge Base
+description: CowAgent personal knowledge base — structured knowledge accumulation, automatic organization, and knowledge graph
+---
+
+The personal knowledge base is the Agent's long-term structured knowledge store, saved in the `knowledge/` directory within the workspace. Unlike memory, which is organized by timeline, the knowledge base organizes content by topic — articles, conversation insights, and learning materials are structured into interlinked Markdown pages, forming a continuously growing knowledge network.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+## Core Concepts
+
+### Knowledge vs Memory
+
+| Dimension | Knowledge Base (knowledge/) | Long-term Memory (memory/) |
+| --- | --- | --- |
+| Organization | By topic, interlinked | By timeline, dated files |
+| Writing | Agent actively structures content | Auto-summarized on context trimming |
+| Content | Refined, structured knowledge | Raw conversation summaries |
+| Use cases | Study notes, tech docs, project knowledge | Conversation history, event records |
+
+### Directory Structure
+
+```
+~/cow/knowledge/
+├── index.md          # Knowledge index, entry point for all pages
+├── log.md            # Change log, records each write
+├── concepts/         # Conceptual knowledge
+│   └── machine-learning.md
+├── entities/         # Entity knowledge (people, orgs, tools)
+│   └── openai.md
+└── sources/          # Source knowledge (articles, papers)
+    └── llm-wiki.md
+```
+
+The directory structure is flexible — the Agent automatically creates appropriate category directories based on actual content. Users can also customize the organization.
+
+## Automatic Organization
+
+Knowledge writing is an autonomous Agent behavior, triggered in these scenarios:
+
+- **User shares an article or document** — The Agent automatically extracts key information and creates a structured knowledge page
+- **Conversation produces valuable conclusions** — The Agent organizes insights into knowledge pages and links them to existing knowledge
+- **User explicitly requests organization** — Users can guide the Agent to organize and update knowledge through conversation
+
+Each knowledge page includes cross-reference links to related pages, gradually building a knowledge graph.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413110104.png" width="800" />
+</Frame>
+
+## Knowledge Retrieval
+
+The Agent can retrieve knowledge during conversation through:
+
+- **Index lookup** — Quickly locate relevant pages via `knowledge/index.md`
+- **Semantic search** — Search knowledge content via the `memory_search` tool
+- **Direct read** — Read specific knowledge files via the `memory_get` tool
+
+## Web Console
+
+The web console provides a dedicated "Knowledge" module with:
+
+- **Document browsing** — Tree-style directory structure, searchable and collapsible, click to view content
+- **Knowledge graph** — Interactive graph visualizing relationships between knowledge pages
+- **Chat integration** — Knowledge document links referenced in Agent replies are clickable for direct navigation
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/17aad553d3e9e428c52ff9dc31726fda.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105402.png" width="800" />
+</Frame>
+
+## CLI Commands
+
+Manage the knowledge base with the `/knowledge` command:
+
+| Command | Description |
+| --- | --- |
+| `/knowledge` | Show knowledge base statistics |
+| `/knowledge list` | Display file directory as a tree |
+| `/knowledge on` | Enable the knowledge base feature |
+| `/knowledge off` | Disable the knowledge base feature |
+
+## Configuration
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `knowledge` | Whether to enable the personal knowledge base | `true` |
+| `agent_workspace` | Workspace path; knowledge is stored under the `knowledge/` subdirectory | `~/cow` |
diff --git a/docs/memory/context.mdx b/docs/memory/context.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/memory/context.mdx
@@ -0,0 +1,81 @@
+---
+title: Short-term Memory
+description: Conversation context — message management, compression strategies, and context operations
+---
+
+Conversation context is the Agent's short-term memory, containing all messages in the current session (user input, Agent replies, tool calls and results). Proper context management is critical for the Agent's reasoning quality and cost control.
+
+## Context Structure
+
+Each conversation turn consists of:
+
+```
+User message → Agent thinking → Tool call → Tool result → ... → Agent final reply
+```
+
+A single turn may include multiple tool calls (controlled by `agent_max_steps`). All tool calls and results are retained in context until compressed or trimmed.
+
+## Key Configuration
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `agent_max_context_tokens` | Maximum context token budget | `50000` |
+| `agent_max_context_turns` | Maximum conversation turns in context | `20` |
+| `agent_max_steps` | Maximum decision steps per turn (tool call count) | `15` |
+
+Configurable via `config.json` or the `/config` chat command.
+
+## Compression Strategy
+
+When context exceeds limits, the system automatically compresses to free space. The process has multiple stages:
+
+### 1. Tool Result Truncation
+
+Before each decision loop, the system checks tool call results in historical turns. Results exceeding **20,000 characters** are truncated, keeping only the beginning and end with a truncation notice. Current turn results are not affected.
+
+### 2. Turn Trimming
+
+When conversation turns exceed `agent_max_context_turns`:
+
+- The **oldest half** of complete turns is trimmed (preserving tool call chain integrity)
+- Trimmed messages are summarized by LLM and **written to the daily memory file**
+- Once the LLM summary is ready, it is also **injected into the first user message** of the retained context, helping the model maintain conversational continuity
+- Summary injection runs asynchronously in the background and takes effect from the next turn onward
+
+### 3. Token Budget Trimming
+
+After turn trimming, if tokens still exceed the budget:
+
+- **Fewer than 5 turns**: All turns undergo **text compression** — each turn keeps only the first user text and last Agent reply, removing intermediate tool call chains
+- **5 or more turns**: The **first half** of turns is trimmed again, with discarded content written to memory and a context summary injected
+
+### 4. Overflow Emergency Handling
+
+When the model API returns a context overflow error:
+
+1. All current messages are summarized and written to memory
+2. Aggressive trimming is applied (tool results limited to 10K chars, user text to 10K, max 5 turns)
+3. If still overflowing, the entire conversation context is cleared
+
+## Session Persistence
+
+Conversation messages are persisted to a local database, automatically restored after service restart. Restore strategy:
+
+- Restores the most recent **`max(3, max_context_turns / 6)`** turns
+- Only retains each turn's **user text and Agent final reply**, not intermediate tool call chains
+- Sessions older than **30 days** are automatically cleaned up
+
+## Commands
+
+Use these commands in chat to manage context:
+
+| Command | Description |
+| --- | --- |
+| `/context` | View current context statistics (message count, role distribution, total characters) |
+| `/context clear` | Clear current session context |
+| `/config agent_max_context_tokens 80000` | Adjust context token budget |
+| `/config agent_max_context_turns 30` | Adjust context turn limit |
+
+<Tip>
+  After clearing context, the Agent "forgets" previous conversation content. Content that was already written to long-term memory can still be retrieved via memory search.
+</Tip>
diff --git a/docs/memory/deep-dream.mdx b/docs/memory/deep-dream.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/memory/deep-dream.mdx
@@ -0,0 +1,106 @@
+---
+title: Deep Dream
+description: Deep Dream — automatic distillation from conversations to permanent memory
+---
+
+Deep Dream is the core consolidation mechanism of CowAgent's memory system, responsible for distilling scattered daily memories into refined long-term memory and generating dream diaries.
+
+## Memory Flow
+
+CowAgent's memory progresses through three stages from short-term to long-term:
+
+```
+Conversation context (short-term) → Daily memory (mid-term) → MEMORY.md (long-term)
+```
+
+### 1. Conversation → Daily Memory
+
+When conversation context is trimmed or during the daily scheduled summary, the system uses LLM to summarize conversation content into key events, writing them to the daily memory file `memory/YYYY-MM-DD.md`.
+
+Triggers:
+- **Context trimming** — Trimmed content is summarized when turn or token limits are exceeded
+- **Daily schedule** — Automatically triggered at 23:55
+- **API overflow** — Emergency save of current conversation summary
+
+### 2. Daily Memory → MEMORY.md (Distillation)
+
+After the daily summary completes, Deep Dream automatically runs distillation:
+
+1. **Read materials** — Current `MEMORY.md` + today's daily memory
+2. **LLM distillation** — Deduplicate, merge, prune, extract new information
+3. **Overwrite MEMORY.md** — Output the refined long-term memory
+4. **Generate dream diary** — Record discoveries and insights from the consolidation
+
+### 3. Role of MEMORY.md
+
+`MEMORY.md` is injected into the system prompt for every conversation, keeping the Agent aware of user preferences, decisions, and key facts. Therefore it must stay concise — Deep Dream targets approximately 30 entries or fewer.
+
+## Distillation Rules
+
+Deep Dream follows these consolidation rules:
+
+| Operation | Description |
+| --- | --- |
+| **Merge & refine** | Combine similar entries into single high-density statements |
+| **Extract new** | Pull preferences, decisions, people, experiences from daily memory |
+| **Conflict update** | When new info contradicts old entries, newer info takes precedence |
+| **Clean invalid** | Remove temporary records, blank entries, formatting artifacts |
+| **Remove redundancy** | Delete old entries already covered by more refined statements |
+
+## Dream Diary
+
+Each distillation generates a dream diary saved at `memory/dreams/YYYY-MM-DD.md`, written in a narrative style recording:
+
+- Duplications or contradictions found
+- New insights extracted from daily memory
+- Cleanups and optimizations performed
+- Overall observations
+
+Dream diaries can be viewed in the Web console under "Memory → Dream Diary" tab.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## Manual Trigger
+
+In addition to the automatic daily run, you can manually trigger distillation in chat:
+
+```text
+/memory dream [N]
+```
+
+- `N`: Consolidate the last N days of memory (default 3, max 30)
+- Runs asynchronously in the background; you'll be notified in chat when complete
+- Web notifications include clickable links to view MEMORY.md and dream diary
+- Works without Agent initialization — can be used before the first conversation
+
+<Tip>
+  After first deployment, it's recommended to run `/memory dream 30` once to distill all historical daily memories into MEMORY.md.
+</Tip>
+
+## Config Toggle
+
+Control the nightly automatic distillation via `deep_dream_enabled` in `config.json`:
+
+```json
+{
+  "deep_dream_enabled": true
+}
+```
+
+| Key | Description | Default |
+| --- | --- | --- |
+| `deep_dream_enabled` | Enable the daily scheduled distillation | `true` |
+
+Enabled by default to keep existing behavior. When disabled, the nightly distillation no longer runs — useful if you prefer to maintain MEMORY.md manually or want to save an LLM call (daily memory summarization is not affected). The manual `/memory dream` command is also unaffected and can still be triggered anytime.
+
+## Safety Mechanisms
+
+| Mechanism | Description |
+| --- | --- |
+| **Skip on no content** | Distillation skipped when no daily memory exists, avoiding empty overwrites |
+| **Input dedup** | In scheduled tasks, automatically skipped when input materials haven't changed |
+| **Async execution** | Distillation runs in a background thread, never blocking conversation |
+| **Sequential guarantee** | In scheduled tasks, daily flush completes before distillation starts |
+| **No fabrication** | Prompt explicitly constrains consolidation to existing materials only |
diff --git a/docs/memory/index.mdx b/docs/memory/index.mdx
new file mode 100644
index 0000000..069b6ea
--- /dev/null
+++ b/docs/memory/index.mdx
@@ -0,0 +1,71 @@
+---
+title: Long-term Memory
+description: CowAgent long-term memory system — file persistence, automatic writing, and hybrid retrieval
+---
+
+Long-term memory is stored in workspace files, persisting across sessions. The Agent loads historical memory on demand via retrieval tools during conversation, and automatically writes conversation summaries to long-term memory when context is trimmed.
+
+<img src="https://cdn.link-ai.tech/doc/memory-architecture-en.jpg" alt="Memory Architecture" />
+
+## Memory Types
+
+### Core Memory (MEMORY.md)
+
+Stored in `~/cow/MEMORY.md`, containing long-term user preferences, important decisions, key facts, and other information that doesn't fade over time. The Agent reads and writes this file via tools to maintain long-term knowledge.
+
+### Daily Memory (memory/YYYY-MM-DD.md)
+
+Stored in `~/cow/memory/` directory, named by date (e.g., `2026-03-08.md`), recording daily conversation summaries and key events. Files are only created on first write to avoid generating empty files.
+
+### Dream Diary (memory/dreams/YYYY-MM-DD.md)
+
+A byproduct of the Deep Dream (memory distillation) process, recording discoveries, deduplication operations, and new insights from each consolidation. Stored in `~/cow/memory/dreams/` directory, named by date.
+
+## Automatic Writing
+
+The Agent automatically persists conversation content to long-term memory through the following mechanisms:
+
+- **On context trimming** — When conversation turns or tokens exceed the configured limit, the oldest half of the context is trimmed, and the discarded content is summarized by LLM into key information and written to the daily memory file. The summary is also asynchronously injected into the retained context for conversational continuity
+- **Daily scheduled summary** — A full summary is automatically triggered at 23:55 every day, ensuring memory is preserved even on low-activity days (skipped if content hasn't changed)
+- [Deep Dream (memory distillation)](/memory/deep-dream) — Runs automatically after the daily summary, distilling daily memories into MEMORY.md and generating a dream diary
+- **On API context overflow** — When the model API returns a context overflow error, the current conversation summary is saved as an emergency measure
+
+All memory writes run asynchronously in a background thread (LLM summarization + file writing), never blocking normal conversation replies.
+
+## Memory Retrieval
+
+The memory system supports hybrid retrieval modes:
+
+- **Keyword retrieval** — FTS5 full-text index matching with BM25 ranking
+- **Vector retrieval** — Embedding-based semantic similarity search, finds relevant memory even with different wording
+
+The Agent automatically triggers memory retrieval during conversation as needed, incorporating relevant historical information into context. Results are ranked by a combined score (default: 0.7 vector weight + 0.3 keyword weight). Daily memory scores decay over time (30-day half-life), while core memory does not decay.
+
+## Related Files
+
+Files related to memory in the workspace (default `~/cow`):
+
+| File | Description |
+| --- | --- |
+| `AGENT.md` | Agent personality and behavior settings |
+| `USER.md` | User identity information and preferences |
+| `RULE.md` | Custom rules and constraints |
+| `MEMORY.md` | Core memory (long-term) |
+| `memory/YYYY-MM-DD.md` | Daily memory (created on demand) |
+| `memory/dreams/YYYY-MM-DD.md` | Dream diary (auto-generated by Deep Dream) |
+
+## Web Console
+
+The memory management page in the Web console allows browsing memory files and dream diaries, with tab switching support:
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414171014.png" width="800" />
+</Frame>
+
+## Configuration
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `agent_workspace` | Workspace path, memory files stored under this directory | `~/cow` |
+| `agent_max_context_tokens` | Max context tokens; when exceeded, content is trimmed and summarized into memory | `50000` |
+| `agent_max_context_turns` | Max context turns; when exceeded, content is trimmed and summarized into memory | `20` |
diff --git a/docs/memory/self-evolution.mdx b/docs/memory/self-evolution.mdx
new file mode 100644
index 0000000..7e1a821
--- /dev/null
+++ b/docs/memory/self-evolution.mdx
@@ -0,0 +1,94 @@
+---
+title: Self-Evolution
+description: Self-Evolution — review a conversation after it goes idle to consolidate memory, improve skills, and follow up on unfinished tasks
+---
+
+## Overview
+
+### Introduction
+
+Self-Evolution lets the Agent do more than finish one task at a time; it keeps improving as it works with you. After a conversation winds down, it quietly reviews what just happened: it saves anything worth remembering into long-term memory, fixes problems that surfaced in a skill, and picks up tasks that were left unfinished. Over time the Agent learns your preferences, repeats fewer mistakes, and gets better at wrapping things up on its own. All of this runs in the background, and it only tells you when it actually did something.
+
+<Note>
+  For the full architecture and engineering behind the self-evolution mechanism, see the blog post: [A Five-Layer Self-Evolution Mechanism for AI Agents](https://cowagent.ai/blog/self-evolution/).
+</Note>
+
+> Self-Evolution complements [Deep Dream](/memory/deep-dream). Deep Dream organizes memory itself, while Self-Evolution goes a step further to improve skills and push unfinished tasks forward, sharpening the Agent's abilities through everyday use.
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-demo.png" alt="Self-Evolution in a conversation" />
+</Frame>
+
+### Three Goals
+
+Self-Evolution focuses on three things:
+
+| Goal | Description |
+| --- | --- |
+| **Consolidate memory** | Record important preferences, decisions, and facts from the conversation, filling in what the main chat may have missed |
+| **Improve skills** | ① When a skill shows a problem in use (such as a wrong setting or a missing step), fix the skill file directly; ② when a reusable workflow emerges, turn it into a new skill so it can be reused next time |
+| **Follow up on unfinished tasks** | Spot the to-dos left in a conversation and finish them when possible |
+
+Once a review is done, if it actually changed something, the Agent tells you in a single line what it just learned and what it adjusted, so you can decide whether to roll it back.
+
+## Usage
+
+### When It Triggers
+
+Self-Evolution does not run on a fixed schedule. It only kicks in **after a conversation naturally ends and goes idle**, so it never interrupts an ongoing exchange. Two conditions must both hold:
+
+- **The conversation is idle**: more time has passed since the last interaction than the configured idle window (10 minutes by default)
+- **There is enough to review**: enough turns have accumulated since the last evolution, or the context is close to its capacity
+
+Only when both are met does a review begin. This makes sure there is something worth reviewing while keeping it from bothering you mid-conversation.
+
+### Configuration
+
+You can toggle Self-Evolution in the Web console under **Settings → Agent Config** (below "Deep Thinking"), or adjust it in the config file:
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `self_evolution_enabled` | Whether Self-Evolution is enabled (on by default for new installs) | `false` |
+| `self_evolution_idle_minutes` | How long the conversation must be idle before it triggers (minutes) | `10` |
+| `self_evolution_min_turns` | Minimum conversation turns required to trigger | `6` |
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-config.png" alt="Enable Self-Evolution in the Web console" />
+</Frame>
+
+<Tip>
+  The Web console only exposes the on/off toggle. To change the idle window or the turn threshold, edit the config file. Changes take effect immediately, with no restart needed.
+</Tip>
+
+### Evolution Records
+
+Each review is recorded by date in `memory/evolution/YYYY-MM-DD.md`, viewable in the Web console under the **Memory → Self-Evolution** tab. That tab gathers both self-evolution records and dream diaries in one place, so you can look back on how the Agent has grown.
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-logs.png" alt="Self-Evolution records list" />
+</Frame>
+
+### Rolling Back
+
+If you disagree with a change from a review, just tell the Agent in chat to undo the last change. It restores the affected files from the backup taken before the review. Every review keeps its own backup, so they never interfere with each other.
+
+## Design
+
+Self-Evolution reuses what the system already has, which keeps it lightweight:
+
+- **Isolated execution**: each review runs as a separate, short-lived task. It uses the same model as the main chat but with a restricted toolset (it can only read context and edit memory and skill files). It does not pollute the main chat's context or affect its performance.
+- **Backup-based undo**: the relevant files are snapshotted before a review and restored from that snapshot on undo, so every change is traceable and reversible.
+- **Change detection**: after a review, the system compares file snapshots to see whether anything actually changed, and uses that to decide whether to notify you. This is how it guarantees, at the engineering level, that no work means no message.
+
+### Restraint and Safety
+
+Self-Evolution is built to act when needed and stay out of the way otherwise:
+
+| Mechanism | Description |
+| --- | --- |
+| **No work, no notification** | If a review produces no real change, it stays silent and sends nothing |
+| **Triggers only when idle** | It runs only after the conversation is idle, never interrupting an active one |
+| **Reversible changes** | A backup is taken before every review, so you can undo a result you do not like |
+| **Built-in skills protected** | The skills shipped with the product are protected and never modified |
+| **Workspace-scoped** | All reads and writes stay inside the workspace and never touch other system files |
+| **Runs in the background** | Reviews run in the background and do not block normal replies |
diff --git a/docs/models/claude.mdx b/docs/models/claude.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/claude.mdx
@@ -0,0 +1,51 @@
+---
+title: Claude
+description: Anthropic Claude model configuration (Text Chat + Image Understanding)
+---
+
+Claude is provided by Anthropic and supports both text chat and image understanding. The mainstream Sonnet / Opus models natively support vision, so no separate Vision model needs to be specified.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "claude-sonnet-5",
+  "claude_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Supports `claude-sonnet-5`, `claude-opus-4-8`, `claude-opus-4-7`, `claude-sonnet-4-6`, `claude-opus-4-6`, `claude-sonnet-4-5`, `claude-sonnet-4-0`, `claude-3-5-sonnet-latest`, etc. See [official models](https://docs.anthropic.com/en/docs/about-claude/models/overview) |
+| `claude_api_key` | Create one in the [Claude Console](https://console.anthropic.com/settings/keys) |
+| `claude_api_base` | Optional, defaults to `https://api.anthropic.com/v1`. Can be changed to a third-party proxy |
+
+### Model Selection
+
+| Model | Use Case |
+| --- | --- |
+| `claude-sonnet-5` | Latest flagship; default recommendation, best balance of reasoning quality and cost |
+| `claude-opus-4-8` | Previous flagship with the strongest reasoning, at a higher price |
+| `claude-opus-4-7` | Earlier Opus flagship |
+| `claude-sonnet-4-6` | Balanced cost and speed, lower cost |
+| `claude-opus-4-6` / `claude-sonnet-4-5` / `claude-sonnet-4-0` | Earlier flagships at a lower price |
+
+## Image Understanding
+
+Once `claude_api_key` is configured, the Agent's Vision tool automatically uses the Claude main model to recognize images, with no extra setup required.
+
+To manually specify a Vision model, set it explicitly in the configuration file:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "claude-sonnet-5"
+    }
+  }
+}
+```
diff --git a/docs/models/coding-plan.mdx b/docs/models/coding-plan.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/coding-plan.mdx
@@ -0,0 +1,139 @@
+---
+title: Coding Plan
+description: Coding Plan model configuration
+---
+
+> Coding Plan is a monthly subscription package offered by various providers, ideal for high-frequency Agent usage. CowAgent supports all Coding Plan providers via OpenAI-compatible mode.
+
+<Note>
+  Coding Plan API Base and API Key are usually separate from the standard pay-as-you-go ones. Please obtain them from each provider's platform.
+</Note>
+
+## General Configuration
+
+All providers can be accessed via the OpenAI-compatible protocol, and can be quickly configured through the web console. Set the model provider to **OpenAI**, select a custom model and enter the model code, then fill in the corresponding provider's API Base and API Key:
+
+<img src="https://cdn.link-ai.tech/doc/20260318113134.png" width="800"/>
+
+You can also configure directly in `config.json`:
+
+```json
+{
+  "bot_type": "openai",
+  "model": "MODEL_NAME",
+  "open_ai_api_base": "PROVIDER_CODING_PLAN_API_BASE",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `bot_type` | Must be `openai` (OpenAI-compatible mode) |
+| `model` | Model name supported by the provider |
+| `open_ai_api_base` | Provider's Coding Plan API Base URL |
+| `open_ai_api_key` | Provider's Coding Plan API Key |
+
+---
+
+## Alibaba Cloud
+
+```json
+{
+  "bot_type": "openai",
+  "model": "qwen3.5-plus",
+  "open_ai_api_base": "https://coding.dashscope.aliyuncs.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | `qwen3.5-plus`, `qwen3-max-2026-01-23`, `qwen3-coder-next`, `qwen3-coder-plus`, `glm-5`, `glm-4.7`, `kimi-k2.5`, `MiniMax-M2.5` |
+| `open_ai_api_base` | `https://coding.dashscope.aliyuncs.com/v1` |
+| `open_ai_api_key` | Coding Plan specific key (not shared with pay-as-you-go) |
+
+Reference: [Quick Start](https://help.aliyun.com/zh/model-studio/coding-plan-quickstart?spm=a2c4g.11186623.help-menu-2400256.d_0_2_1.70115203zi5Igc), [Model List](https://help.aliyun.com/zh/model-studio/coding-plan)
+
+---
+
+## MiniMax
+
+```json
+{
+  "bot_type": "openai",
+  "model": "MiniMax-M3",
+  "open_ai_api_base": "https://api.minimaxi.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | `MiniMax-M3`, `MiniMax-M2.7`, `MiniMax-M2.7-highspeed` |
+| `open_ai_api_base` | China: `https://api.minimaxi.com/v1`; Global: `https://api.minimax.io/v1` |
+| `open_ai_api_key` | Coding Plan specific key (not shared with pay-as-you-go) |
+
+Reference: [China Key](https://platform.minimaxi.com/docs/coding-plan/quickstart), [Model List](https://platform.minimaxi.com/docs/guides/pricing-coding-plan), [Global Key](https://platform.minimax.io/docs/coding-plan/quickstart)
+
+---
+
+## GLM
+
+```json
+{
+  "bot_type": "openai",
+  "model": "glm-4.7",
+  "open_ai_api_base": "https://open.bigmodel.cn/api/coding/paas/v4",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | `glm-5`, `glm-4.7`, `glm-4.6`, `glm-4.5`, `glm-4.5-air` |
+| `open_ai_api_base` | China: `https://open.bigmodel.cn/api/coding/paas/v4`; Global: `https://api.z.ai/api/coding/paas/v4` |
+| `open_ai_api_key` | Shared with standard API |
+
+Reference: [China Quick Start](https://docs.bigmodel.cn/cn/coding-plan/quick-start), [Global Quick Start](https://docs.z.ai/devpack/quick-start)
+
+---
+
+## Kimi
+
+```json
+{
+  "bot_type": "moonshot",
+  "model": "kimi-for-coding",
+  "moonshot_base_url": "https://api.kimi.com/coding/v1",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Use `kimi-for-coding` for auto-updating model, or specify a model such as `kimi-k2.6` |
+| `moonshot_base_url` | `https://api.kimi.com/coding/v1` |
+| `moonshot_api_key` | Coding Plan specific key (not shared with pay-as-you-go) |
+
+Reference: [Key & Docs](https://www.kimi.com/code/docs/)
+
+---
+
+## Volcengine
+
+```json
+{
+  "bot_type": "openai",
+  "model": "Doubao-Seed-2.0-Code",
+  "open_ai_api_base": "https://ark.cn-beijing.volces.com/api/coding/v3",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | `Doubao-Seed-2.0-Code`, `Doubao-Seed-2.0-pro`, `Doubao-Seed-2.0-lite`, `Doubao-Seed-Code`, `MiniMax-M2.5`, `Kimi-K2.5`, `GLM-4.7`, `DeepSeek-V3.2` |
+| `open_ai_api_base` | `https://ark.cn-beijing.volces.com/api/coding/v3` |
+| `open_ai_api_key` | Shared with standard API |
+
+Reference: [Quick Start](https://www.volcengine.com/docs/82379/1928261?lang=zh)
diff --git a/docs/models/custom.mdx b/docs/models/custom.mdx
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--- /dev/null
+++ b/docs/models/custom.mdx
@@ -0,0 +1,62 @@
+---
+title: Custom
+description: Custom provider configuration for third-party API proxies and local models
+---
+
+For model services accessed via the OpenAI-compatible protocol, such as:
+
+- **Third-party API proxies**: call multiple models through a unified API base
+- **Local models**: models deployed locally with tools like Ollama, vLLM
+- **Private deployments**: model services deployed inside an enterprise
+
+## Web Console
+
+Recommended. On the "Models" page of the Web console, click "Add Provider" and pick "Custom", then fill in the name, API Base and API Key. Multiple custom providers can be added; after adding one, select it together with a model in the "Main Model" card to enable it.
+
+<img width="900" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-custom-model-config.png" />
+
+Default endpoints of common local deployment tools:
+
+| Tool | Default API Base |
+| --- | --- |
+| [Ollama](https://ollama.com) | `http://localhost:11434/v1` |
+| [vLLM](https://docs.vllm.ai) | `http://localhost:8000/v1` |
+| [LocalAI](https://localai.io) | `http://localhost:8080/v1` |
+
+## Configuration File
+
+You can also edit `config.json` directly: define multiple providers in the `custom_providers` list and set `bot_type` to `"custom:<id>"` to activate one of them:
+
+```json
+{
+  "bot_type": "custom:3f2a9c1b",
+  "custom_providers": [
+    {
+      "id": "3f2a9c1b",
+      "name": "ProviderA",
+      "api_key": "YOUR_API_KEY_A",
+      "api_base": "https://api.a.com/v1",
+      "model": "deepseek-v3"
+    },
+    {
+      "id": "a1b2c3d4",
+      "name": "ProviderB",
+      "api_key": "YOUR_API_KEY_B",
+      "api_base": "https://api.b.com/v1",
+      "model": "qwen3-max"
+    }
+  ]
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `custom_providers` | List of custom providers; each item has `id`, `name`, `api_base`, `api_key` (optional) and `model` (optional) |
+| `bot_type` | Set to `"custom:<id>"` to activate the corresponding provider |
+| `id` | Unique identifier (8-char hex); auto-generated when adding via the Web console, or any unique string when editing manually |
+| `name` | Display label, can be renamed freely |
+| `model` | Model used by this provider, takes effect when activated |
+
+<Note>
+  The legacy single-provider configuration (`bot_type` set to `"custom"` with `custom_api_key` / `custom_api_base`) remains fully compatible and keeps working without any changes.
+</Note>
diff --git a/docs/models/deepseek.mdx b/docs/models/deepseek.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/deepseek.mdx
@@ -0,0 +1,72 @@
+---
+title: DeepSeek
+description: DeepSeek model configuration (Text Chat + Thinking Mode)
+---
+
+DeepSeek is one of the default recommended providers in Agent mode, focused on cost-effective text chat and task planning.
+
+## Text Chat
+
+```json
+{
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Supports `deepseek-v4-flash` (Default), `deepseek-v4-pro` |
+| `deepseek_api_key` | Create one on the [DeepSeek Platform](https://platform.deepseek.com/api_keys) |
+| `deepseek_api_base` | Optional, defaults to `https://api.deepseek.com/v1`. Can be changed to a third-party proxy |
+
+### Model Selection
+
+| Model | Use Case |
+| --- | --- |
+| `deepseek-v4-flash` | Default recommended; fast and low cost |
+| `deepseek-v4-pro` | Smarter; better for complex tasks |
+
+## Thinking Mode
+
+The V4 series (`deepseek-v4-flash` / `deepseek-v4-pro`) supports an explicit "thinking mode": before producing the final answer, the model emits a chain of thought (`reasoning_content`) to improve answer quality.
+
+### Toggle
+
+Controlled by the global `enable_thinking` config, and can also be toggled from the Web Console's configuration page:
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+- `true`: the model thinks before answering across all channels. The Web Console displays the thinking process; IM channels (WeChat / WeCom / DingTalk / Feishu) do not show it but still get better answers.
+- `false`: thinking is disabled, responses are faster, and time-to-first-token is lower.
+
+### Reasoning Effort
+
+Under thinking mode, `reasoning_effort` controls reasoning intensity:
+
+```json
+{
+  "enable_thinking": true,
+  "reasoning_effort": "high"
+}
+```
+
+| Value | Use Case |
+| --- | --- |
+| `high` (Default) | Day-to-day Agent tasks; balanced reasoning and speed |
+| `max` | Complex coding, long-horizon planning, strictly constrained tasks; deeper reasoning but more time and output tokens |
+
+`reasoning_effort` only takes effect when `enable_thinking` is `true`; it is ignored automatically when the model does not support thinking mode.
+
+### Behavior Notes
+
+- **Sampling parameters**: in thinking mode, `temperature`, `top_p`, `presence_penalty`, and `frequency_penalty` are ignored by the server (without errors). CowAgent automatically skips them.
+- **Multi-turn tool calls**: when the history contains tool calls, DeepSeek requires every assistant message to include `reasoning_content`. CowAgent handles this automatically, so toggling thinking mode across turns will not cause errors.
+
+<Tip>
+  `deepseek-v4-flash` is used by default; switch to `deepseek-v4-pro` for complex tasks; enable `enable_thinking` when deep reasoning is needed.
+</Tip>
diff --git a/docs/models/doubao.mdx b/docs/models/doubao.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/doubao.mdx
@@ -0,0 +1,66 @@
+---
+title: Doubao
+description: Doubao (Volcengine Ark) model configuration (Text / Image Understanding / Image Generation / Embedding)
+---
+
+Doubao (Volcengine Ark) supports text chat, image understanding, image generation (Seedream), and embedding. A single `ark_api_key` enables all capabilities.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "doubao-seed-2-1-pro-260628",
+  "ark_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Can be `doubao-seed-2-1-pro-260628`, `doubao-seed-2-1-turbo-260628`, `doubao-seed-2-0-pro-260215`, `doubao-seed-2-0-code-preview-260215`, etc. |
+| `ark_api_key` | Create one in the [Volcengine Ark Console](https://console.volcengine.com/ark/region:ark+cn-beijing/apikey) |
+| `ark_base_url` | Optional, defaults to `https://ark.cn-beijing.volces.com/api/v3` |
+
+## Image Understanding
+
+Once `ark_api_key` is configured and the main model is a Doubao model, the Agent's Vision tool automatically uses the current main model to recognize images, with no extra setup required.
+
+To manually specify a Vision model:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "doubao-seed-2-1-pro-260628"
+    }
+  }
+}
+```
+
+## Image Generation
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+Available models: `seedream-5.0-lite`, `seedream-4.5`.
+
+## Embedding
+
+```json
+{
+  "embedding_provider": "doubao",
+  "embedding_model": "doubao-embedding-vision-251215"
+}
+```
+
+The default model is `doubao-embedding-vision-251215` (multimodal embedding); the dimension (1024 or 2048) can be set via `embedding_dimensions` in the configuration file. After changing the embedding, run `/memory rebuild-index` to rebuild the index.
diff --git a/docs/models/gemini.mdx b/docs/models/gemini.mdx
new file mode 100644
index 0000000..b2d9520
--- /dev/null
+++ b/docs/models/gemini.mdx
@@ -0,0 +1,59 @@
+---
+title: Gemini
+description: Google Gemini model configuration (Text Chat + Image Understanding + Image Generation)
+---
+
+Google Gemini supports text chat, image understanding, and image generation (Nano Banana series). A single `gemini_api_key` enables all capabilities.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "gemini-3.5-flash",
+  "gemini_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Recommended: `gemini-3.5-flash`; also supports `gemini-3.1-pro-preview`, `gemini-3.1-flash-lite-preview`, `gemini-3-flash-preview`, `gemini-3-pro-preview`, etc. See [official docs](https://ai.google.dev/gemini-api/docs/models) |
+| `gemini_api_key` | Create one in [Google AI Studio](https://aistudio.google.com/app/apikey) |
+| `gemini_api_base` | Optional, defaults to `https://generativelanguage.googleapis.com`. Can be changed to a third-party proxy |
+
+## Image Understanding
+
+All Gemini models natively support vision. Once `gemini_api_key` is configured, the Agent's Vision tool automatically uses the main model to recognize images, with no extra setup required.
+
+To manually specify a Vision model:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gemini-3.1-flash-lite-preview"
+    }
+  }
+}
+```
+
+## Image Generation
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gemini-3.1-flash-image-preview"
+    }
+  }
+}
+```
+
+| Model ID | Alias |
+| --- | --- |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `gemini-2.5-flash-image` | Nano Banana |
diff --git a/docs/models/glm.mdx b/docs/models/glm.mdx
new file mode 100644
index 0000000..63f8d0a
--- /dev/null
+++ b/docs/models/glm.mdx
@@ -0,0 +1,56 @@
+---
+title: GLM
+description: Zhipu AI GLM model configuration (Text / Image Understanding / Speech-to-Text / Embedding)
+---
+
+Zhipu AI supports text chat, image understanding, speech-to-text (ASR), and embedding. A single `zhipu_ai_api_key` enables all capabilities.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "glm-5.2",
+  "zhipu_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Can be `glm-5.2`, `glm-5.1`, `glm-5-turbo`, `glm-5`, `glm-4.7`, `glm-4-plus`, `glm-4-flash`, `glm-4-air`, etc. See [model codes](https://bigmodel.cn/dev/api/normal-model/glm-4) |
+| `zhipu_ai_api_key` | Create one in the [Zhipu AI Console](https://www.bigmodel.cn/usercenter/proj-mgmt/apikeys) |
+| `zhipu_ai_api_base` | Optional, defaults to `https://open.bigmodel.cn/api/paas/v4` |
+
+## Image Understanding
+
+Zhipu's chat models (`glm-5.2`, `glm-5.1`, `glm-5-turbo`, etc.) do not support vision; vision calls are uniformly routed to `glm-5v-turbo`. Once `zhipu_ai_api_key` is configured, the Agent's Vision tool automatically uses this model, with no need to specify it explicitly in the configuration file.
+
+## Speech-to-Text (ASR)
+
+```json
+{
+  "voice_to_text": "zhipu",
+  "voice_to_text_model": "glm-asr-2512"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `voice_to_text` | Set to `zhipu` to enable Zhipu ASR |
+| `voice_to_text_model` | Optional, defaults to `glm-asr-2512` |
+
+Credentials are automatically reused from `zhipu_ai_api_key`. Audio files should be smaller than 25MB; oversized files may be rejected by the server.
+
+## Embedding
+
+```json
+{
+  "embedding_provider": "zhipu",
+  "embedding_model": "embedding-3"
+}
+```
+
+Available models: `embedding-3`, `embedding-2`. After changing the embedding, run `/memory rebuild-index` to rebuild the index.
diff --git a/docs/models/index.mdx b/docs/models/index.mdx
new file mode 100644
index 0000000..ecbe5d3
--- /dev/null
+++ b/docs/models/index.mdx
@@ -0,0 +1,38 @@
+---
+title: Models Overview
+description: Model providers supported by CowAgent and their capability matrix
+---
+
+CowAgent supports a wide range of mainstream large language models. Model interfaces live under the project's `models/` directory. Beyond text chat, several providers also provide vision understanding, image generation, speech-to-text, text-to-speech, and embeddings — all of which can be invoked on demand in the Agent flow.
+
+## Capability Matrix
+
+A snapshot of each provider's capabilities. "Text" refers to the main chat model; the remaining columns show which Agent capabilities the provider can power.
+
+| Provider | Representative Models | Text | Vision | Image Gen | STT | TTS | Embedding |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [DeepSeek](/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [MiniMax](/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [Claude](/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [Gemini](/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [OpenAI](/models/openai) | gpt-5.5, o-series | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [GLM](/models/glm) | glm-5.2, glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [Qwen](/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Doubao](/models/doubao) | doubao-seed-2.1 series | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [ERNIE](/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [MiMo](/models/mimo) | mimo-v2.5-pro / v2.5 | ✅ | ✅ | | | ✅ | |
+| [LinkAI](/models/linkai) | 100+ models from multiple providers | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Custom](/models/custom) | Local models / third-party proxies | ✅ | | | | | |
+
+<Tip>
+  Every capability in the Web console (Vision / Image / STT / TTS / Embedding / Web Search) can be configured independently with its own provider and model — there is no forced binding between them.
+</Tip>
+
+## How to Configure
+
+**Option 1 (recommended):** Manage models and capabilities online via the [Web console](/channels/web), with no need to edit the configuration file:
+
+<img width="900" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-models-config.png" />
+
+**Option 2:** Edit `config.json` manually and fill in the model name and API key for the selected provider. Every model also supports OpenAI-compatible access — just set `bot_type` to `openai` and configure `open_ai_api_base` and `open_ai_api_key`.
diff --git a/docs/models/kimi.mdx b/docs/models/kimi.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/kimi.mdx
@@ -0,0 +1,41 @@
+---
+title: Kimi
+description: Kimi (Moonshot) model configuration (Text Chat + Image Understanding)
+---
+
+Kimi is provided by Moonshot and supports both text chat and image understanding. The `kimi-k2.x` series natively supports vision.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "kimi-k2.7-code",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Can be `kimi-k2.7-code`, `kimi-k2.7-code-highspeed`, `kimi-k2.6`, `kimi-k2.5`, `kimi-k2`, `moonshot-v1-8k`, `moonshot-v1-32k`, `moonshot-v1-128k` |
+| `moonshot_api_key` | Create one in the [Moonshot Console](https://platform.moonshot.cn/console/api-keys) |
+| `moonshot_base_url` | Optional, defaults to `https://api.moonshot.cn/v1` |
+
+## Image Understanding
+
+Once `moonshot_api_key` is configured, the Agent's Vision tool automatically uses `kimi-k2.6` to recognize images, with no extra setup required.
+
+To manually specify a Vision model:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "kimi-k2.6"
+    }
+  }
+}
+```
diff --git a/docs/models/linkai.mdx b/docs/models/linkai.mdx
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--- /dev/null
+++ b/docs/models/linkai.mdx
@@ -0,0 +1,103 @@
+---
+title: LinkAI
+description: Access text, vision, image, speech, and embedding capabilities through the LinkAI platform
+---
+
+A single `linkai_api_key` gives you access to all capabilities of mainstream providers such as OpenAI, Claude, Gemini, DeepSeek, MiniMax, Qwen, Kimi, and Doubao.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "use_linkai": true,
+  "linkai_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `use_linkai` | Set to `true` to enable |
+| `linkai_api_key` | Create one in the [Console](https://link-ai.tech/console/interface) |
+| `model` | Can be any code from the [model list](https://link-ai.tech/console/models) |
+
+See [Model Service](https://link-ai.tech/console/models) for more.
+
+## Image Understanding
+
+Once configured, the Agent's Vision tool automatically calls multimodal models via the gateway, with no extra setup required. To manually specify a Vision model:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+Available models: `gpt-4.1-mini`, `gpt-5.4-mini`, `qwen3.7-plus`, `doubao-seed-2-1-pro-260628`, `kimi-k2.6`, `claude-sonnet-5`, `gemini-3.1-flash-lite-preview`, etc.
+
+## Image Generation
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+| Model ID | Alias |
+| --- | --- |
+| `gpt-image-2` | OpenAI |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `seedream-5.0-lite` | ByteDance Doubao Seedream |
+
+## Speech-to-Text (ASR)
+
+```json
+{
+  "voice_to_text": "linkai"
+}
+```
+
+ASR uses Whisper by default; credentials are automatically reused from `linkai_api_key`.
+
+## Text-to-Speech (TTS)
+
+The TTS gateway supports multiple underlying engines. The engine is selected by `text_to_voice_model`, and the available voices change with the engine.
+
+```json
+{
+  "text_to_voice": "linkai",
+  "text_to_voice_model": "doubao",
+  "tts_voice_id": "BV001_streaming"
+}
+```
+
+| `text_to_voice_model` | Engine |
+| --- | --- |
+| `tts-1` | OpenAI · Multi-language (voices like `alloy` / `nova` / `echo`, etc.) |
+| `doubao` | ByteDance Doubao · Rich Chinese voices |
+| `baidu` | Baidu · Chinese broadcaster voices |
+
+Voices differ by engine; we recommend selecting them visually in the Web Console under "Model Management → Text-to-Speech".
+
+## Embedding
+
+```json
+{
+  "embedding_provider": "linkai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+The default model is `text-embedding-3-small` (OpenAI-compatible). After changing the embedding, run `/memory rebuild-index` to rebuild the index.
diff --git a/docs/models/mimo.mdx b/docs/models/mimo.mdx
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--- /dev/null
+++ b/docs/models/mimo.mdx
@@ -0,0 +1,136 @@
+---
+title: MiMo
+description: Xiaomi MiMo model configuration (Text Chat + Image Understanding + Text-to-Speech)
+---
+
+Xiaomi MiMo is a native omni-modal large model. A single `mimo_api_key` enables text chat, image understanding, and text-to-speech all at once.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console — no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "mimo-v2.5-pro",
+  "mimo_api_key": "YOUR_API_KEY",
+  "mimo_api_base": "https://api.xiaomimimo.com/v1"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Default recommendation: `mimo-v2.5-pro`; `mimo-v2.5` is also supported |
+| `mimo_api_key` | Create one in the [MiMo Open Platform](https://platform.xiaomimimo.com/console/api-keys) |
+| `mimo_api_base` | Optional, defaults to `https://api.xiaomimimo.com/v1` |
+
+### Model Selection
+
+| Model | Use Case |
+| --- | --- |
+| `mimo-v2.5-pro` | Flagship: native omni-modal + Agent capability, up to 1M tokens context |
+| `mimo-v2.5` | General-purpose, native omni-modal (text / image / video / audio) |
+
+## Thinking Mode
+
+The MiMo V2.5 series enables "thinking mode" by default: the model emits `reasoning_content` (chain-of-thought) before the final answer, improving performance on complex tasks.
+
+Use the global `enable_thinking` flag to toggle visibility (also switchable from the Web Console settings):
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+## Image Understanding
+
+Once `mimo_api_key` is configured, the Agent's Vision tool can automatically use MiMo's vision models:
+
+- When the main model itself is multimodal (`mimo-v2.5-pro` / `mimo-v2.5`), images are handled directly by the main model with no extra setup.
+- When the main model belongs to another provider, the Vision tool falls back to `mimo-v2.5-pro` in order.
+
+To force a specific Vision model, set it explicitly in the configuration:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "provider": "mimo",
+      "model": "mimo-v2.5-pro"
+    }
+  }
+}
+```
+
+## Text-to-Speech (TTS)
+
+```json
+{
+  "text_to_voice": "mimo",
+  "text_to_voice_model": "mimo-v2.5-tts",
+  "tts_voice_id": "冰糖"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `text_to_voice_model` | Currently only `mimo-v2.5-tts` (preset voices + singing mode) |
+| `tts_voice_id` | Preset voice name (Chinese voice IDs use the Chinese name directly) |
+
+### Preset Voices
+
+| Voice ID | Description |
+| --- | --- |
+| `Mia` | English · Female |
+| `Chloe` | English · Female |
+| `Milo` | English · Male |
+| `Dean` | English · Male |
+| `冰糖` | Chinese · Female (default) |
+| `茉莉` | Chinese · Female |
+| `苏打` | Chinese · Male |
+| `白桦` | Chinese · Male |
+
+
+You can also pick a voice visually from the Web Console under "Model Management → Text-to-Speech".
+
+### Style Control
+
+MiMo TTS supports embedding **audio tags** in the synthesis text to control emotion, tone, dialect, persona, and even singing. Tags must appear in the **text that will be synthesized to speech (i.e. the Agent's reply)**, with the overall style tag placed at the very beginning:
+
+```
+(style)content-to-synthesize
+```
+
+Half-width `()`, full-width `（）`, and `[]` brackets are all accepted. Both Chinese and English style descriptors work — pick whichever language expresses the timbre most precisely. Common examples:
+
+| Category | Example tags |
+| --- | --- |
+| Basic emotions | `happy` `sad` `angry` `fear` `surprised` `excited` `aggrieved` `calm` `indifferent` |
+| Compound emotions | `wistful` `relieved` `helpless` `guilty` `at ease` `uneasy` `touched` |
+| Overall tone | `gentle` `aloof` `lively` `serious` `languid` `playful` `deep` `sharp` `cutting` |
+| Voice character | `magnetic` `mellow` `bright` `ethereal` `childlike` `aged` `sweet` `husky` |
+| Persona | `squeaky` `mature lady` `young boy` `uncle` `Taiwanese accent` |
+| Dialect | `Northeastern` `Sichuan` `Henan` `Cantonese` |
+| Role-play | `Sun Wukong` `Lin Daiyu` |
+| Singing | `sing` / `singing` |
+
+Examples:
+
+- `(magnetic)The night is deep, and the city is still breathing.`
+- `(gentle)Take a breath. You've got this.`
+- `(serious)This is the final warning before the system reboots.`
+- `(singing)Oh, when the saints go marching in…`
+
+You can also insert fine-grained audio tags at any position in the text to control breathing, laughter, pauses, etc. For example:
+
+```
+(nervous, deep breath) Phew… stay calm, stay calm. (faster pace) I've rehearsed this intro fifty times, it'll be fine.
+```
+
+See the [MiMo speech synthesis documentation](https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/speech-synthesis-v2.5) for the full tag list.
+
+<Tip>
+  When CowAgent calls TTS, the Agent's reply text (including any `(...)` tags) is forwarded directly to MiMo for synthesis. Tell the model in its persona / system prompt to "prefix replies with a `(style)` tag to control the tone", and IM channels (WeChat / Feishu / DingTalk / WeCom) will play voice replies with the corresponding emotion, dialect, or even singing.
+</Tip>
diff --git a/docs/models/minimax.mdx b/docs/models/minimax.mdx
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--- /dev/null
+++ b/docs/models/minimax.mdx
@@ -0,0 +1,71 @@
+---
+title: MiniMax
+description: MiniMax model configuration (Text / Image Understanding / Image Generation / Text-to-Speech)
+---
+
+MiniMax supports text chat, image understanding, image generation, and text-to-speech. A single `minimax_api_key` enables all capabilities.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "MiniMax-M3",
+  "minimax_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Can be `MiniMax-M3`, `MiniMax-M2.7`, `MiniMax-M2.7-highspeed`, etc. |
+| `minimax_api_key` | Create one in the [MiniMax Console](https://platform.minimaxi.com/user-center/basic-information/interface-key) |
+
+## Image Understanding
+
+MiniMax's M2.x chat models do not support vision natively; vision calls are uniformly routed to `MiniMax-Text-01`. Once `minimax_api_key` is configured, the Agent's Vision tool automatically uses this model, with no need to specify it explicitly in the configuration file.
+
+## Image Generation
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "image-01"
+    }
+  }
+}
+```
+
+Available models: `image-01`.
+
+## Text-to-Speech (TTS)
+
+```json
+{
+  "text_to_voice": "minimax",
+  "text_to_voice_model": "speech-2.8-hd",
+  "tts_voice_id": "female-shaonv"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `text_to_voice_model` | `speech-2.8-hd` (emotional rendering, natural sound), `speech-2.8-turbo` (ultra-fast), `speech-2.6-hd`, `speech-2.6-turbo` |
+| `tts_voice_id` | Voice ID; supports Chinese / Cantonese / English / Japanese / Korean — 70+ voices in total |
+
+Common voice examples:
+
+| Voice ID | Description |
+| --- | --- |
+| `female-shaonv` | Chinese · Young Girl (Female) |
+| `female-yujie` | Chinese · Mature Lady (Female) |
+| `female-tianmei` | Chinese · Sweet Female (Female) |
+| `male-qn-jingying` | Chinese · Elite Youth (Male) |
+| `male-qn-badao` | Chinese · Dominant Youth (Male) |
+| `Cantonese_GentleLady` | Cantonese · Gentle Female Voice |
+| `English_Graceful_Lady` | English · Graceful Lady |
+
+For the full voice list (70+ voices across Chinese / Cantonese / English / Japanese / Korean), see the [system voice list](https://platform.minimaxi.com/docs/faq/system-voice-id), or select visually in the Web Console under "Model Management → Text-to-Speech".
diff --git a/docs/models/openai.mdx b/docs/models/openai.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/models/openai.mdx
@@ -0,0 +1,103 @@
+---
+title: OpenAI
+description: OpenAI model configuration (Text / Vision / Image / Speech / Embedding)
+---
+
+OpenAI offers the most complete coverage and can simultaneously serve text chat, vision understanding, image generation, speech-to-text (ASR), text-to-speech (TTS), and embedding. A single `open_ai_api_key` lets the Agent use all of these capabilities.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+
+## Text Chat
+
+```json
+{
+  "model": "gpt-5.5",
+  "open_ai_api_key": "YOUR_API_KEY",
+  "open_ai_api_base": "https://api.openai.com/v1"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Same as OpenAI's [model parameter](https://platform.openai.com/docs/models); supports `gpt-5.5`, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano`, the `gpt-5` series, `gpt-4.1`, the o-series, etc. Agent mode defaults to `gpt-5.5`; use `gpt-5.4` for better cost-efficiency |
+| `open_ai_api_key` | Create one on the [OpenAI Platform](https://platform.openai.com/api-keys) |
+| `open_ai_api_base` | Optional; change it to access a third-party proxy |
+| `bot_type` | Not required when using OpenAI's official models; set to `openai` when accessing other providers via the compatible protocol |
+
+## Image Understanding
+
+OpenAI models like `gpt-5.5`, `gpt-5.4`, `gpt-4o`, and `gpt-4.1` natively support vision. Once `open_ai_api_key` is configured, the Agent's Vision tool automatically uses the main model to recognize images. If the main model does not support vision or you want to specify it explicitly, set it in the configuration file:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+Supported Vision models: `gpt-5.5`, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano`, `gpt-5`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4o`.
+
+## Image Generation
+
+Specify the image generation model in the configuration file; the Agent automatically routes image generation skill calls to OpenAI:
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+Supported image generation models: `gpt-image-2`, `gpt-image-1`.
+
+## Speech-to-Text (ASR)
+
+```json
+{
+  "voice_to_text": "openai",
+  "voice_to_text_model": "gpt-4o-mini-transcribe"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `voice_to_text` | Set to `openai` to enable OpenAI speech-to-text |
+| `voice_to_text_model` | Optional, defaults to `gpt-4o-mini-transcribe`; can also be `gpt-4o-transcribe`, `whisper-1` |
+
+Credentials are automatically reused from `open_ai_api_key`.
+
+## Text-to-Speech (TTS)
+
+```json
+{
+  "text_to_voice": "openai",
+  "text_to_voice_model": "tts-1",
+  "tts_voice_id": "alloy"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `text_to_voice_model` | `tts-1`, `tts-1-hd`, `gpt-4o-mini-tts` |
+| `tts_voice_id` | Voices: `alloy`, `echo`, `fable`, `onyx`, `nova`, `shimmer`, `ash`, `ballad`, `coral`, `sage`, `verse` |
+
+## Embedding
+
+```json
+{
+  "embedding_provider": "openai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+Available models: `text-embedding-3-small`, `text-embedding-3-large`, `text-embedding-ada-002`. After changing the embedding, run `/memory rebuild-index` to rebuild the index.
+
diff --git a/docs/models/qianfan.mdx b/docs/models/qianfan.mdx
new file mode 100644
index 0000000..1352596
--- /dev/null
+++ b/docs/models/qianfan.mdx
@@ -0,0 +1,64 @@
+---
+title: ERNIE
+description: ERNIE model configuration (Baidu Qianfan)
+---
+
+Option 1: Native integration (recommended):
+
+```json
+{
+  "model": "ernie-5.1",
+  "qianfan_api_key": "",
+  "qianfan_api_base": "https://qianfan.baidubce.com/v2"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Default recommendation: `ernie-5.1`; also supports `ernie-5.0`, `ernie-x1.1`, `ernie-4.5-turbo-128k`, `ernie-4.5-turbo-32k` |
+| `qianfan_api_key` | Qianfan API key, usually starting with `bce-v3/` |
+| `qianfan_api_base` | Optional, defaults to `https://qianfan.baidubce.com/v2` |
+
+## Model Selection
+
+| Model | Use Case |
+| --- | --- |
+| `ernie-5.1` | Default recommendation; latest ERNIE flagship with the strongest overall capability |
+| `ernie-5.0` | Previous-generation flagship with excellent overall capability |
+| `ernie-x1.1` | Deep-thinking reasoning model with lower hallucination and stronger instruction following / tool calling |
+| `ernie-4.5-turbo-128k` | Long-context and general chat |
+| `ernie-4.5-turbo-32k` | General chat with a balanced context window and cost |
+
+## Vision tool
+
+Once `qianfan_api_key` is configured, Agent mode can auto-discover Qianfan for the Vision tool:
+
+- When the main model itself is multimodal (e.g. `ernie-5.1`, `ernie-5.0`, `ernie-x1.1`, `ernie-4.5-turbo-vl`), images are handled directly by the main model with no extra setup.
+- When the main model is text-only (e.g. `ernie-4.5-turbo-128k`), the Vision tool automatically falls back to `ernie-4.5-turbo-vl`.
+
+To force a specific Vision model, set it explicitly in `config.json`:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "ernie-4.5-turbo-vl"
+    }
+  }
+}
+```
+
+Option 2: OpenAI-compatible configuration:
+
+```json
+{
+  "model": "ernie-5.1",
+  "bot_type": "openai",
+  "open_ai_api_key": "",
+  "open_ai_api_base": "https://qianfan.baidubce.com/v2"
+}
+```
+
+<Tip>
+  Prefer `qianfan_api_key` for new configurations. Existing `wenxin`, `wenxin-4`, `baidu_wenxin_api_key`, and `baidu_wenxin_secret_key` configurations remain supported.
+</Tip>
diff --git a/docs/models/qwen.mdx b/docs/models/qwen.mdx
new file mode 100644
index 0000000..6096513
--- /dev/null
+++ b/docs/models/qwen.mdx
@@ -0,0 +1,112 @@
+---
+title: Qwen
+description: Qwen model configuration (Text / Image Understanding / Image Generation / Speech-to-Text / Text-to-Speech / Embedding)
+---
+
+Qwen (Alibaba DashScope / Bailian) is one of the most fully-featured providers. Text, image understanding, image generation, speech-to-text, text-to-speech, and embedding can all be enabled with a single `dashscope_api_key`.
+
+<Tip>
+  All capabilities below can be configured in one place via the "Model Management" page in the Web Console, with no need to manually edit the configuration file.
+</Tip>
+
+## Text Chat
+
+```json
+{
+  "model": "qwen3.7-plus",
+  "dashscope_api_key": "YOUR_API_KEY"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `model` | Can be `qwen3.7-plus`, `qwen3.7-max`, `qwen3.6-plus`, `qwen3.5-plus`, `qwen3-max`, `qwen-max`, `qwen-plus`, `qwen-turbo`, `qwq-plus`, etc. |
+| `dashscope_api_key` | Create one in the [Bailian Console](https://bailian.console.aliyun.com/?tab=model#/api-key); see the [official docs](https://bailian.console.aliyun.com/?tab=api#/api) |
+
+## Image Understanding
+
+Once `dashscope_api_key` is configured, the Agent's Vision tool automatically calls Qwen's vision models to recognize images. Models like `qwen3.7-plus` / `qwen3.6-plus` / `qwen3.5-plus` / `qwen3-max` are already multimodal; if the main model is text-only (e.g. `qwen-turbo`), it automatically falls back to `qwen-vl-max`.
+
+To manually specify a Vision model:
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "qwen3.7-plus"
+    }
+  }
+}
+```
+
+Supported models: `qwen3.7-plus`, `qwen3.6-plus`, `qwen3.5-plus`, `qwen3-max`.
+
+## Image Generation
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "qwen-image-2.0"
+    }
+  }
+}
+```
+
+Available models: `qwen-image-2.0`, `qwen-image-2.0-pro`.
+
+## Speech-to-Text (ASR)
+
+```json
+{
+  "voice_to_text": "dashscope",
+  "voice_to_text_model": "qwen3-asr-flash"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `voice_to_text` | Set to `dashscope` to enable Qwen ASR |
+| `voice_to_text_model` | Optional, defaults to `qwen3-asr-flash` |
+
+Credentials are automatically reused from `dashscope_api_key`. A single audio segment should be smaller than 10MB and no longer than 300 seconds.
+
+## Text-to-Speech (TTS)
+
+```json
+{
+  "text_to_voice": "dashscope",
+  "text_to_voice_model": "qwen3-tts-flash",
+  "tts_voice_id": "Cherry"
+}
+```
+
+| Parameter | Description |
+| --- | --- |
+| `text_to_voice_model` | Optional, defaults to `qwen3-tts-flash`; covers Mandarin, dialects, and major foreign languages |
+| `tts_voice_id` | Voice ID; see the common list below |
+
+Common voice examples:
+
+| Voice ID | Description |
+| --- | --- |
+| `Cherry` | Qianyue · Sunny Female Voice |
+| `Serena` | Suyao · Gentle Female Voice |
+| `Ethan` | Chenxu · Sunny Male Voice |
+| `Chelsie` | Qianxue · Anime Girl |
+| `Dylan` | Beijing Dialect · Xiaodong |
+| `Rocky` | Cantonese · Aqiang |
+| `Sunny` | Sichuan Dialect · Qing'er |
+
+The full voice list (Mandarin / regional dialects / bilingual, etc.) can be selected visually in the Web Console under "Model Management → Text-to-Speech".
+
+## Embedding
+
+```json
+{
+  "embedding_provider": "dashscope",
+  "embedding_model": "text-embedding-v4"
+}
+```
+
+The default model is `text-embedding-v4`. After changing the embedding, run `/memory rebuild-index` to rebuild the index.
diff --git a/docs/releases/overview.mdx b/docs/releases/overview.mdx
new file mode 100644
index 0000000..8aaaf5d
--- /dev/null
+++ b/docs/releases/overview.mdx
@@ -0,0 +1,36 @@
+---
+title: Changelog
+description: CowAgent version history
+---
+
+| Version | Date | Description |
+| --- | --- | --- |
+| [2.1.3](/releases/v2.1.3) | 2026.07.08 | Desktop client released (macOS / Windows), knowledge base document management, on-demand MCP tool retrieval, Traditional Chinese support, new models (claude-sonnet-5, doubao-seed-2.1, etc.), security hardening and refinements |
+| [2.1.2](/releases/v2.1.2) | 2026.06.18 | Web Console upgrades (scheduled task management, knowledge base categories, multiple custom model providers), Self-Evolution improvements, new models (kimi-k2.7-code, glm-5.2), security hardening and refinements |
+| [2.1.1](/releases/v2.1.1) | 2026.06.09 | Self-Evolution, Web Console message management and parallel sessions, cross-platform MCP enhancements with concurrent calls, new models (MiniMax-M3, qwen3.7-plus, etc.), various improvements |
+| [2.1.0](/releases/v2.1.0) | 2026.06.01 | Internationalization, new Telegram / Discord / Slack / WeChat Customer Service channels, CLI interaction upgrades (streaming output, fuzzy command matching, task cancellation), MCP Streamable HTTP, new models |
+| [2.0.9](/releases/v2.0.9) | 2026.05.22 | Model management console, MCP protocol support, browser persistent login, new models (gpt-5.5, gemini-3.5-flash, qwen3.7-max, etc.), deployment hardening |
+| [2.0.8](/releases/v2.0.8) | 2026.05.06 | Major Feishu channel upgrade (voice, streaming and Markdown, one-click QR-scan setup), DeepSeek V4 and Baidu models, scheduler tool enhancements |
+| [2.0.7](/releases/v2.0.7) | 2026.04.22 | Image Generation Skill (6-provider auto-routing), new models (Kimi K2.6, Claude Opus 4.7, GLM 5.1), knowledge base and Web Console improvements |
+| [2.0.6](/releases/v2.0.6) | 2026.04.14 | Project rename, Knowledge Base system, Deep Dream Memory Distillation, Smart Context Compression, Web Console multi-session and various improvements |
+| [2.0.5](/releases/v2.0.5) | 2026.04.01 | Cow CLI, Skill Hub open source, Browser tool, WeCom Bot QR scan, and more |
+| [2.0.4](/releases/v2.0.4) | 2026.03.22 | Personal WeChat channel, new model support, Japanese docs, script refactoring and bug fixes |
+| [2.0.3](/releases/v2.0.3) | 2026.03.18 | WeCom Smart Bot and QQ channels, Coding Plan support, multiple new models, Web file processing, memory system upgrade |
+| [2.0.2](/releases/v2.0.2) | 2026.02.27 | Web Console upgrade, multi-channel concurrency, session persistence |
+| [2.0.1](/releases/v2.0.1) | 2026.02.13 | Built-in Web Search tool, smart context management, multiple fixes |
+| [2.0.0](/releases/v2.0.0) | 2026.02.03 | Full upgrade to AI super assistant |
+| 1.7.6 | 2025.05.23 | Web Channel optimization, AgentMesh plugin |
+| 1.7.5 | 2025.04.11 | DeepSeek model |
+| 1.7.4 | 2024.12.13 | Gemini 2.0 model, Web Channel |
+| 1.7.3 | 2024.10.31 | Stability improvements, database features |
+| 1.7.2 | 2024.09.26 | One-click install script, o1 model |
+| 1.7.0 | 2024.08.02 | iFlytek 4.0 model, knowledge base references |
+| 1.6.9 | 2024.07.19 | gpt-4o-mini, Alibaba voice recognition |
+| 1.6.8 | 2024.07.05 | Claude 3.5, Gemini 1.5 Pro |
+| 1.6.0 | 2024.04.26 | Kimi integration, gpt-4-turbo upgrade |
+| 1.5.8 | 2024.03.26 | GLM-4, Claude-3, edge-tts |
+| 1.5.2 | 2023.11.10 | Feishu channel, image recognition chat |
+| 1.5.0 | 2023.11.10 | gpt-4-turbo, dall-e-3, tts multimodal |
+| 1.0.0 | 2022.12.12 | Project created, first ChatGPT integration |
+
+See [GitHub Releases](https://github.com/zhayujie/CowAgent/releases) for full history.
diff --git a/docs/releases/v2.0.0.mdx b/docs/releases/v2.0.0.mdx
new file mode 100644
index 0000000..e6c3753
--- /dev/null
+++ b/docs/releases/v2.0.0.mdx
@@ -0,0 +1,63 @@
+---
+title: v2.0.0
+description: CowAgent 2.0 - Full upgrade from chatbot to AI super assistant
+---
+
+CowAgent 2.0 is a comprehensive upgrade from a chatbot to an **AI super assistant** — capable of autonomous thinking and task planning, long-term memory, operating computers, and creating and executing skills.
+
+**Release Date**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)
+
+## Key Updates
+
+### Agent Core
+
+- **Complex Task Planning**: Autonomous planning with multi-turn reasoning
+- **Long-term Memory**: Persistent memory with keyword and vector search
+- **Built-in Tools**: 10+ tools including file ops, Bash, browser, scheduler
+- **Web search**: Built-in `web_search` tool, supports multiple search engines, configure corresponding API key to use
+- **Skills System**: Skill engine with built-in and custom skill support
+- **Security & Cost**: Secret management, prompt controls, token limits
+
+### Other
+
+- **Channels**: Feishu/DingTalk WebSocket support, image/file messages
+- **Models**: claude-sonnet-4-5, gemini-3-pro-preview, glm-4.7, MiniMax-M2.1, qwen3-max
+- **Deployment**: One-click install, configure, run, and management script
+
+## Long-term Memory
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+## Task Planning & Tools
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+## Skills System
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234350.png" width="750" />
+</Frame>
+
+## Contributing
+
+Welcome to [submit feedback](https://github.com/zhayujie/CowAgent/issues) and [contribute code](https://github.com/zhayujie/CowAgent/pulls).
diff --git a/docs/releases/v2.0.1.mdx b/docs/releases/v2.0.1.mdx
new file mode 100644
index 0000000..7de5746
--- /dev/null
+++ b/docs/releases/v2.0.1.mdx
@@ -0,0 +1,36 @@
+---
+title: v2.0.1
+description: CowAgent 2.0.1 - Built-in Web Search, smart context management, multiple fixes
+---
+
+**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)
+
+## New Features
+
+- **Built-in Web Search tool**: Integrated web search as a built-in Agent tool, reducing decision cost ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 model support**: Added support for Claude Opus 4.6 model ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **WeCom image recognition**: Support image message recognition in WeCom channel ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))
+
+## Improvements
+
+- **Smart context management**: Resolved chat context overflow with intelligent context trimming strategy to prevent token limits ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **Runtime info dynamic update**: Automatic update of timestamps and other runtime info in system prompts via dynamic functions ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill prompt optimization**: Improved Skill system prompt generation, simplified tool descriptions for better Agent performance ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **GLM custom API Base URL**: Support custom API Base URL for GLM models ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **Startup script optimization**: Improved `run.sh` script interaction and configuration flow ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **Decision step logging**: Added Agent decision step logging for debugging ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+
+## Bug Fixes
+
+- **Scheduler memory loss**: Fixed memory loss caused by Scheduler dispatcher ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **Empty tool calls & long results**: Fixed handling of empty tool calls and excessively long tool results ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**: Fixed function call compatibility with OpenAI models ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude tool name field**: Removed extraneous tool name field from Claude model responses ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax reasoning**: Optimized MiniMax model reasoning content handling, hidden thinking process output ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **GLM thinking process**: Hidden GLM model thinking process display ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **Feishu connection & SSL**: Fixed Feishu channel SSL certificate errors and connection issues ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type validation**: Fixed `AttributeError` caused by non-string `model_type` ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))
+
+## Platform Compatibility
+
+- **Windows compatibility**: Fixed path handling, file encoding, and `os.getuid()` unavailability on Windows across multiple tool modules ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
diff --git a/docs/releases/v2.0.2.mdx b/docs/releases/v2.0.2.mdx
new file mode 100644
index 0000000..80e9f6d
--- /dev/null
+++ b/docs/releases/v2.0.2.mdx
@@ -0,0 +1,98 @@
+---
+title: v2.0.2
+description: CowAgent 2.0.2 - Web Console upgrade, multi-channel concurrency, session persistence
+---
+
+**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)
+
+## Highlights
+
+### 🖥️ Web Console Upgrade
+
+The Web Console has been fully upgraded with streaming conversation output, visual display of tool execution and reasoning processes, and online management of **models, skills, memory, channels, and Agent configuration**.
+
+#### Chat Interface
+
+Supports streaming output with real-time display of the Agent's reasoning process and tool calls, providing intuitive observation of the Agent's decision-making:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### Model Management
+
+Manage model configurations online without manually editing config files:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173811.png" />
+
+#### Skill Management
+
+View and manage Agent skills (Skills) online:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+#### Memory Management
+
+View and manage Agent memory online:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+#### Channel Management
+
+Manage connected channels online with real-time connect/disconnect operations:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+#### Scheduled Tasks
+
+View and manage scheduled tasks online, including one-time tasks, fixed intervals, and Cron expressions:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+#### Logs
+
+View Agent runtime logs in real-time for monitoring and troubleshooting:
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
+
+Related commits: [f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)
+
+### 🔀 Multi-Channel Concurrency
+
+Multiple channels (e.g., Feishu, DingTalk, WeCom, Web) can now run simultaneously, each in an independent thread without interference.
+
+Configuration: Set multiple channels in `config.json` via `channel_type` separated by commas, or connect/disconnect channels in real-time from the Web Console's channel management page.
+
+```json
+{
+  "channel_type": "web,feishu,dingtalk"
+}
+```
+
+Related commits: [4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)
+
+### 💾 Session Persistence
+
+Session history is now persisted to a local SQLite database. Conversation context is automatically restored after service restarts. Historical conversations in the Web Console are also restored.
+
+Related commits: [29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)
+
+## New Models
+
+- **Gemini 3.1 Pro Preview**: Added `gemini-3.1-pro-preview` model support ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**: Added `claude-4.6-sonnet` model support ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**: Added `qwen3.5-plus` model support ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**: Added `Minimax-M2.5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**: Added `glm-5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**: Added `kimi-k2.5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**: Added `doubao-2.0-code` coding-specialized model ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope Models**: Added Alibaba Cloud DashScope model name support ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))
+
+## Website & Documentation
+
+- **Official Website**: [cowagent.ai](https://cowagent.ai/)
+- **Documentation**: [docs.cowagent.ai](https://docs.cowagent.ai/)
+
+## Bug Fixes
+
+- **Gemini DingTalk image recognition**: Fixed Gemini unable to process image markers in DingTalk channel ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **Startup script dependencies**: Fixed dependency installation issue in `run.sh` script ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **Bare except cleanup**: Replaced `bare except` with `except Exception` for better exception handling ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
diff --git a/docs/releases/v2.0.3.mdx b/docs/releases/v2.0.3.mdx
new file mode 100644
index 0000000..da68ccf
--- /dev/null
+++ b/docs/releases/v2.0.3.mdx
@@ -0,0 +1,91 @@
+---
+title: v2.0.3
+description: CowAgent 2.0.3 - WeCom Smart Bot and QQ channels, Web Console file handling, memory system upgrade
+---
+
+## 🔌 New Channels
+
+### WeCom Smart Bot
+
+Added the WeCom Smart Bot (`wecom_bot`) channel with streaming card output, support for receiving and replying to text and image messages, and full configuration through the Web Console.
+
+Documentation: [WeCom Smart Bot](https://docs.cowagent.ai/en/channels/wecom-bot).
+
+Related commits: [d4480b6](https://github.com/zhayujie/CowAgent/commit/d4480b6), [a42f31f](https://github.com/zhayujie/CowAgent/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/CowAgent/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/CowAgent/commit/8b45d6c)
+
+### QQ Channel
+
+Added the QQ official bot (`qq`) channel with support for text and image messages in both private chats and group chats.
+
+Documentation: [QQ Bot](https://docs.cowagent.ai/en/channels/qq).
+
+Related commits: [005a0e1](https://github.com/zhayujie/CowAgent/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/CowAgent/commit/a4d54f5)
+
+## 🖥️ Web Console File Input and Processing
+
+The Web Console chat UI now supports file and image uploads — files can be sent directly to the agent for processing. The Read tool gains parsing support for Office documents (Word, Excel, PPT).
+
+Related commits: [30c6d9b](https://github.com/zhayujie/CowAgent/commit/30c6d9b)
+
+## 🤖 New Models
+
+- **GPT-5.4 Series**: Added `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano` ([1623deb](https://github.com/zhayujie/CowAgent/commit/1623deb))
+- **Gemini 3.1 Flash Lite Preview**: Added `gemini-3.1-flash-lite-preview` ([ba915f2](https://github.com/zhayujie/CowAgent/commit/ba915f2))
+
+## 💰 Coding Plan Support
+
+Added integration with provider Coding Plan (monthly programming subscription) tiers via the unified OpenAI-compatible path. Supported providers include Aliyun, MiniMax, GLM, Kimi, and Volcengine.
+
+See [Coding Plan docs](https://docs.cowagent.ai/en/models/coding-plan) for detailed configuration.
+
+## 🧠 Memory System Upgrade
+
+Memory flush improvements:
+
+- Use the LLM to summarize out-of-window conversations into compact daily memory entries
+- Summarization runs asynchronously on a background thread, never blocking replies
+- Smarter batch trimming policy reduces flush frequency
+- Daily scheduled flush as a safety net for low-activity scenarios
+- Fixed context-memory loss issues
+
+Related commits: [022c13f](https://github.com/zhayujie/CowAgent/commit/022c13f), [c116235](https://github.com/zhayujie/CowAgent/commit/c116235)
+
+## 🔧 Tool Refactoring
+
+- **Image Vision**: Image recognition (Vision) is refactored from a Skill into a built-in Tool with a dedicated Vision Provider configuration, improving stability and maintainability ([a50fafa](https://github.com/zhayujie/CowAgent/commit/a50fafa), [3b8b562](https://github.com/zhayujie/CowAgent/commit/3b8b562))
+- **Web Fetch**: Web fetch is refactored from a Skill into a built-in Tool with support for downloading and parsing remote documents (PDF, Word, Excel, PPT) ([ccb9030](https://github.com/zhayujie/CowAgent/commit/ccb9030), [fa61744](https://github.com/zhayujie/CowAgent/commit/fa61744))
+
+## 🐳 Docker Deployment Improvements
+
+- **Config Template Alignment**: `docker-compose.yml` env vars aligned with `config-template.json`, covering full model API key and Agent settings
+- **Web Console Port Mapping**: Added `9899` port mapping so the Web Console is reachable in browser after Docker deployment
+- **Hot Config Reload**: Bot API key and API base are now read at request time — changes from the Web Console take effect without restart
+- **Workspace Persistence**: Added a `./cow` volume mount so agent workspace data (memories, persona, skills, etc.) persists across container rebuilds and upgrades
+
+## ⚡ Performance Improvements
+
+- **Faster Startup**: The Feishu channel imports its dependencies lazily, avoiding a 4–10s startup delay ([924dc79](https://github.com/zhayujie/CowAgent/commit/924dc79))
+- **Channel Stability**: Improved channel connection stability and added env-var support for channel configuration ([f1c04bc](https://github.com/zhayujie/CowAgent/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/CowAgent/commit/46d97fd))
+
+## 🐛 Bug Fixes
+
+- **bot_type Propagation**: Fixed `bot_type` propagation under Agent mode ([#2691](https://github.com/zhayujie/CowAgent/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
+- **bot_type Resolution Priority**: Adjusted `bot_type` resolution priority under Agent mode ([#2692](https://github.com/zhayujie/CowAgent/pull/2692)) Thanks [@6vision](https://github.com/6vision)
+- **Zhipu Config**: Fixed Zhipu `bot_type` naming, Web Console persistence, and regex escaping ([#2693](https://github.com/zhayujie/CowAgent/pull/2693)) Thanks [@6vision](https://github.com/6vision)
+- **OpenAI-Compat Layer**: Unified error handling via the `openai_compat` layer ([#2688](https://github.com/zhayujie/CowAgent/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
+- **OpenAI-Compat Migration**: Completed the `openai_compat` migration across all model bots ([#2689](https://github.com/zhayujie/CowAgent/pull/2689))
+- **Gemini Tool Calling**: Fixed tool-call matching for Gemini ([eda82ba](https://github.com/zhayujie/CowAgent/commit/eda82ba))
+- **Session Concurrency**: Fixed race conditions in concurrent session scenarios ([9879878](https://github.com/zhayujie/CowAgent/commit/9879878))
+- **History Recovery**: Fixed incomplete history recovery — only user/assistant text messages are restored, tool calls are stripped ([b788a3d](https://github.com/zhayujie/CowAgent/commit/b788a3d), [a33ce97](https://github.com/zhayujie/CowAgent/commit/a33ce97))
+- **Feishu Group Chat**: Removed the `bot_name` dependency for Feishu group chats ([b641bff](https://github.com/zhayujie/CowAgent/commit/b641bff))
+- **Safari Compatibility**: Fixed an IME Enter key issue that mistakenly sent messages on Safari ([0687916](https://github.com/zhayujie/CowAgent/commit/0687916))
+- **Windows Compatibility**: Fixed bash-style `$VAR` to `%VAR%` env-var conversion on Windows ([7c67513](https://github.com/zhayujie/CowAgent/commit/7c67513))
+- **MiniMax Params**: Added a `max_tokens` cap for MiniMax models ([1767413](https://github.com/zhayujie/CowAgent/commit/1767413))
+- **.gitignore**: Added Python directory ignore rules ([#2683](https://github.com/zhayujie/CowAgent/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
+- **AGENT.md Proactive Evolution**: Improved the system prompt guidance around AGENT.md — instead of waiting for explicit user edits, the agent now proactively detects persona/style shifts in the conversation and updates AGENT.md accordingly
+
+## 📦 Upgrade
+
+Run `./run.sh update` for a one-click upgrade, or manually pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade) for details.
+
+**Release Date**: 2026.03.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.2...2.0.3)
diff --git a/docs/releases/v2.0.4.mdx b/docs/releases/v2.0.4.mdx
new file mode 100644
index 0000000..fc976fa
--- /dev/null
+++ b/docs/releases/v2.0.4.mdx
@@ -0,0 +1,55 @@
+---
+title: v2.0.4
+description: CowAgent 2.0.4 - Personal WeChat channel, new model support, Japanese docs, script refactoring and bug fixes
+---
+
+## 🔌 Personal WeChat Channel
+
+Added personal WeChat (`weixin`) channel — the most important update in this release. Simply scan a QR code to connect CowAgent to your personal WeChat account, with support for:
+
+- **Messaging**: Send and receive text, image, file, and video messages; receive voice messages
+- **QR Code Login**: QR code displayed in terminal, scan with WeChat to log in; auto-refresh on expiry
+- **Credential Persistence**: Login credentials saved to `~/.weixin_cow_credentials.json` automatically, no re-scan needed on restart
+- **Session Auto-Reconnect**: Automatically clears expired credentials and re-initiates QR code login
+- **Web Console Integration**: Add WeChat channel from the Web Console with synchronized QR code login flow
+- **Docker & Script Support**: Both `run.sh` and `docker-compose.yml` now support the WeChat channel
+
+Documentation: [WeChat Channel](https://docs.cowagent.ai/channels/weixin).
+
+Related commits: [ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869), [a483ec0](https://github.com/zhayujie/CowAgent/commit/a483ec0), [c1421e0](https://github.com/zhayujie/CowAgent/commit/c1421e0)
+
+## 🤖 New Models
+
+- **MiniMax-M2.7**: Added MiniMax-M2.7 model support
+- **GLM-5-Turbo**: Added Zhipu glm-5-turbo model support
+
+Related commits: [9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)
+
+## 🔧 Script Refactoring
+
+- **run.sh Refactoring**: Extracted shared logic and eliminated duplication, reducing from 600+ lines to 177 lines ([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **Executable Permission**: Fixed `run.sh` file permission issue ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))
+
+## ⚡ Improvements
+
+- **Unified Request Headers**: Added identification headers to external requests across Agent services (Chat, Embedding, Vision, WebSearch, etc.) ([b4e711f](https://github.com/zhayujie/CowAgent/commit/b4e711f))
+- **Auto-Repair Messages**: Enhanced message protocol fault tolerance with automatic repair of malformed message sequences ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))
+
+## 🌍 Japanese Documentation
+
+Added complete Japanese documentation covering getting started guide, channel integration, model configuration and other major sections. Thanks [@Ikko Ashimine](https://github.com/ikoamu)
+
+Related commits: [5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)
+
+## 🐛 Bug Fixes
+
+- **WeCom Bot Compatibility**: Fixed compatibility with older `websocket-client` versions, added unified WebSocket compatibility layer ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **run.sh PID**: Fixed process PID retrieval error in `run.sh` ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))
+- **Feishu Encoding**: Fixed message and log encoding issue in Feishu channel ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **Feishu Config**: Removed redundant `feishu_bot_name` dependency in `run.sh` ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))
+
+## 📦 Upgrade
+
+Run `./run.sh update` for a one-click upgrade, or manually pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/guide/upgrade) for details.
+
+**Release Date**: 2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
diff --git a/docs/releases/v2.0.5.mdx b/docs/releases/v2.0.5.mdx
new file mode 100644
index 0000000..ad45398
--- /dev/null
+++ b/docs/releases/v2.0.5.mdx
@@ -0,0 +1,77 @@
+---
+title: v2.0.5
+description: CowAgent 2.0.5 - Cow CLI, Skill Hub open source, Browser tool, WeCom Bot QR scan, and more
+---
+
+## 🖥️ Cow CLI
+
+New CLI command system for managing CowAgent from terminal and chat:
+
+- **Terminal commands**: Run `cow <command>` for `start`, `stop`, `restart`, `update`, `status`, `logs`, etc.
+- **Chat commands**: Type `/<command>` in conversation for `/help`, `/status`, `/config`, `/skill`, `/context`, `/logs`, `/version`, etc.
+- **Web console**: Type `/` in the input box to open a slash command menu, with arrow-key input history
+- **Windows support**: New PowerShell script `scripts/run.ps1` with `cow` command support
+
+Docs: [Command Overview](https://docs.cowagent.ai/en/cli)
+
+<img src="https://cdn.link-ai.tech/doc/20260401114549.png" width="750" />
+
+## 🧩 Cow Skill Hub Open Source
+
+[Cow Skill Hub](https://skills.cowagent.ai) is now open source and live — browse, search, install, and publish AI Agent skills:
+
+- **One-command install**: `/skill install <name>` in chat or `cow skill install <name>` in terminal
+- **Multi-source**: Install from Skill Hub, GitHub, ClawHub, LinkAI, and more
+- **Search**: `/skill search` and `/skill list --remote` to browse the hub
+- **Publish**: Submit your own skills at [skills.cowagent.ai/submit](https://skills.cowagent.ai/submit)
+- **Mirror**: Mirror acceleration for faster downloads in China
+
+Open source repo: [cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+Docs: [Skill Hub](https://docs.cowagent.ai/en/skills/hub), [Install Skills](https://docs.cowagent.ai/en/skills/install)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+## 🌐 Browser Tool
+
+New Browser tool — Agent can control a Chromium browser to visit and interact with web pages:
+
+- **Navigation & interaction**: `navigate`, `click`, `fill`, `select`, `scroll`, `press`, etc.
+- **Page snapshot**: Compact DOM snapshot for efficient page understanding, auto-snapshot after navigation
+- **Screenshot**: Save page screenshots to workspace
+- **JavaScript execution**: Run custom scripts on pages
+- **CLI install**: `cow install-browser` for one-command setup
+- **Docker support**: Browser install built into Docker image
+
+Docs: [Browser Tool](https://docs.cowagent.ai/en/tools/browser)
+
+<img src="https://cdn.link-ai.tech/doc/20260401115728.png" width="750" />
+
+## 🤖 WeCom Bot QR Code Setup
+
+WeCom Bot channel now supports QR code scan for one-click bot creation:
+
+- **QR scan in Web console**: Select "Scan QR" mode, scan with WeCom to auto-create and connect a bot — no manual configuration needed
+- **Manual mode**: Still supports manual Bot ID and Secret input
+- **Stream push optimization**: Throttled push to avoid WebSocket congestion
+
+Docs: [WeCom Bot](https://docs.cowagent.ai/en/channels/wecom-bot)
+
+PR: [#2735](https://github.com/zhayujie/CowAgent/pull/2735). Thanks [@WecomTeam](https://github.com/WecomTeam)
+
+## 🐛 Other Improvements & Fixes
+
+- **DeepSeek module**: Independent DeepSeek Bot with dedicated `deepseek_api_key` config ([#2719](https://github.com/zhayujie/CowAgent/pull/2719)). Thanks [@6vision](https://github.com/6vision)
+- **Web console**: Slash command menu, input history, new model options, mobile optimization ([#2731](https://github.com/zhayujie/CowAgent/pull/2731)). Thanks [@zkjqd](https://github.com/zkjqd)
+- **Context loss**: Fix context loss after trimming ([393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0))
+- **System prompt**: Fix system prompt not rebuilding on every turn ([13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde))
+- **Gemini**: Fix missing model attribute in GoogleGeminiBot ([#2716](https://github.com/zhayujie/CowAgent/pull/2716)). Thanks [@cowagent](https://github.com/cowagent)
+- **WeChat channel**: Fix file send failures and filename loss ([6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba), [45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c))
+- **Docker**: Fix volume permissions, reduce image size ([3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348), [4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c))
+- **Security**: Fix Memory Content path traversal risk. Thanks [@August829](https://github.com/August829)
+
+## 📦 Upgrade
+
+Run `cow update` or `./run.sh update` to upgrade, or pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade).
+
+**Release Date**: 2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
diff --git a/docs/releases/v2.0.6.mdx b/docs/releases/v2.0.6.mdx
new file mode 100644
index 0000000..a41f75a
--- /dev/null
+++ b/docs/releases/v2.0.6.mdx
@@ -0,0 +1,83 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - Knowledge Base, Deep Dream Memory Distillation, Smart Context Compression, Web Console Multi-Session and More
+---
+
+## Project Renamed to CowAgent
+
+The repository has been officially renamed from `chatgpt-on-wechat` to **CowAgent**, evolving into a full-featured AI Agent assistant.
+
+- New URL: [github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent) — GitHub auto-redirects the old URL
+- CLI commands, config files, and documentation links remain compatible — no extra steps needed
+
+## 📚 Knowledge Base
+
+New personal knowledge base system — Agent can autonomously build and maintain structured knowledge, retrieving it on demand during conversations:
+
+- **Index-driven self-organizing structure**: Knowledge is stored in `knowledge/` directory, auto-organized by category, with each knowledge page as an independent Markdown file
+- **Auto-write**: Send files, links, or other knowledge to the Agent, or it will automatically create/update knowledge pages when valuable information is identified in conversation
+- **Hybrid retrieval**: Supports keyword full-text search and vector semantic retrieval, loading relevant knowledge on demand during conversations
+- **Visualization**: File tree browsing and knowledge graph visualization, with in-document links for direct navigation
+- **Command management**: `/knowledge` for stats, `/knowledge list` for directory structure, `/knowledge on|off` to toggle
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+
+Docs: [Knowledge Base](https://docs.cowagent.ai/en/knowledge)
+
+## 🌙 Deep Dream Memory Distillation
+
+A new memory consolidation mechanism that automatically distills scattered conversation memories into refined long-term memory daily:
+
+- **Three-tier memory flow**: Conversation context (short-term) → Daily memory (mid-term) → MEMORY.md (long-term), forming a complete memory lifecycle
+- **Auto-distillation**: Runs daily at 23:55, reads the day's daily memory and MEMORY.md, performs deduplication, merging, and pruning via LLM, outputting a refined MEMORY.md
+- **Dream diary**: Each distillation generates a narrative-style dream diary recording discoveries and insights, stored in `memory/dreams/`
+- **Manual trigger**: `/memory dream [N]` to manually trigger with configurable lookback days (default 3, max 30), with chat notification on completion
+- **Web console**: Memory management page now includes a "Dream Diary" tab for browsing all dream diaries
+
+Docs: [Deep Dream](https://docs.cowagent.ai/en/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 Smart Context Compression
+
+When context exceeds limits, trimmed portions are summarized by LLM and asynchronously injected to maintain conversation continuity:
+
+- **Async LLM summary**: Trimmed messages are summarized into key information by LLM, written to daily memory files and injected into retained context
+- **Multi-model compatible**: Uses the primary model for summarization, compatible with Claude, OpenAI, MiniMax and other model message format requirements
+
+Docs: [Short-term Memory](https://docs.cowagent.ai/en/memory/context)
+
+## 💬 Web Console Upgrades
+
+Multiple enhancements to the Web console:
+
+- **Multi-session management**: Create and switch between independent sessions, sidebar session list with auto-generated and manually editable titles
+- **Password protection**: Set a login password via `web_console_password` config option
+- **Deep thinking**: Display model thinking process in Web console, controlled by `enable_thinking` config option
+- **Scheduled push**: Scheduled task results can be pushed to Web console
+- **Message copy**: One-click copy of raw Markdown content from AI reply bubbles
+- **Language toggle**: Top language switch button now shows current language for more intuitive interaction
+
+## 🤖 Model Updates
+
+- **Vision optimization**: Image recognition tool prefers the primary model with automatic multi-provider fallback. Docs: [Vision Tool](https://docs.cowagent.ai/en/tools/vision)
+- **MiniMax new model**: Added MiniMax-M2.7-highspeed model and MiniMax TTS voice synthesis support. Thanks @octo-patch
+- **Qwen**: Added qwen3.6-plus model support
+
+## 🐛 Other Improvements & Fixes
+
+- **Memory prompts**: `MEMORY.md` injected into system prompt by default, with refined memory retrieval and write trigger conditions for enhanced proactive writing
+- **System prompt**: Optimized system prompt style and tone guidance
+- **Browser tool**: Enhanced implicit interactive element detection
+- **File send**: Fixed common file types (tar.gz, zip, etc.) not being sent correctly. Thanks @6vision
+- **macOS compatibility**: Fixed network pre-check timeout compatibility issue. Thanks @Moliang Zhou
+- **Windows compatibility**: Fixed PowerShell compatibility, process updates, terminal encoding and other issues on Windows
+- **Python 3.13+**: Fixed missing `legacy-cgi` dependency for Python 3.13+
+- **WeChat channel**: Updated personal WeChat channel version
+
+## 📦 Upgrade
+
+Run `cow update` or `./run.sh update` to upgrade, or pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade).
+
+**Release Date**: 2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
diff --git a/docs/releases/v2.0.7.mdx b/docs/releases/v2.0.7.mdx
new file mode 100644
index 0000000..a843bea
--- /dev/null
+++ b/docs/releases/v2.0.7.mdx
@@ -0,0 +1,65 @@
+---
+title: v2.0.7
+description: CowAgent 2.0.7 - Image Generation Skill (6-provider auto-routing), new models, knowledge base enhancements, Web Console improvements and bug fixes
+---
+
+## 🎨 Image Generation Skill
+
+New built-in `image-generation` skill supporting text-to-image, image-to-image, and multi-image fusion across six major providers:
+
+- **6-provider auto-routing**: OpenAI (GPT-Image-2) → Gemini (Nano Banana) → Seedream (Volcengine Ark) → Qwen (DashScope) → MiniMax → LinkAI — automatically selects from configured providers in fixed priority order, with automatic fallback on failure
+- **Zero model selection**: Just configure an API key and it works — no need to manually specify a model. You can also name a specific model in conversation (e.g. "draw a cat with seedream")
+- **Flexible control**: Supports `quality`, `size` (512/1K–4K), and `aspect_ratio` parameters, with each provider automatically mapping to its supported values
+- **Image editing**: Pass existing images for editing, style transfer, or multi-image fusion (Seedream supports up to 14 reference images)
+- **Skill-level config**: Pin a default model via `skills.image-generation.model` in `config.json`
+- **Image lightbox**: All images in the Web console now support click-to-enlarge preview
+
+Docs: [Image Generation Skill](https://docs.cowagent.ai/en/skills/image-generation)
+
+## 🤖 New Model Support
+
+- **Kimi K2.6**: Added `kimi-k2.6` model support
+- **Claude Opus 4.7**: Added `claude-opus-4-7` model support
+- **GLM 5.1**: Added `glm-5.1` model support
+- **Kimi Coding Plan**: Support for Kimi Coding Plan mode
+- **Custom model providers**: New custom model provider configuration for easier integration with additional providers
+
+## 💬 Web Console Improvements
+
+- **Smart auto-scroll**: Improved chat scroll behaviour — no longer forces scroll to bottom while the user is reading earlier messages
+- **Reasoning content cap**: Deep thinking content capped at 4 KB to prevent frontend lag
+- **Mobile optimisation**: Session sidebar hidden by default on mobile, with overlay dismiss support
+- **Session title fix**: Fixed title auto-generation fallback logic and Bridge reset on config change
+- **Image preview dedup**: Fixed duplicate image rendering within the same message
+
+## 📚 Knowledge Base Enhancements
+
+- **Nested directory support**: Knowledge base listing and display now support multi-level nested directories
+- **Root-level file display**: Show `index.md`, `log.md` and other root-level files in the knowledge tree
+- **Empty state stats fix**: Root-level files no longer interfere with empty-state detection
+
+## 🌙 Dream Memory Improvements
+
+- **Structured organisation**: Dream memory files are now auto-archived by date with a cleaner directory structure
+- **Schedule jitter**: Daily dream trigger includes random jitter to avoid concurrency conflicts in cluster deployments
+
+## 🛠 Skill System Improvements
+
+- **Skill manager refresh**: `/skill` commands now automatically refresh the skill manager to keep state in sync
+- **Installation sources**: Skill installation supports multiple source formats (URL, zip, local file, etc.) with automatic target directory handling
+
+## 🐛 Other Fixes
+
+- **Gemini fix**: Fixed Gemini tool calls not returning results
+- **Agent retry**: Empty-response retries no longer drop `tool_calls`
+- **Docker env sync**: Fixed environment variables not syncing after config update in Docker environments
+- **Python 3.7 compat**: Deferred `Literal` import for Python 3.7 compatibility
+- **Model switch notification**: Fixed bot_type change notification not showing after model switch. Thanks @6vision
+- **Config command**: `/config` now supports setting `enable_thinking`
+- **Thinking display**: Deep thinking display disabled by default
+
+## 📦 Upgrade
+
+Run `cow update` or `./run.sh update` to upgrade, or pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade).
+
+**Release Date**: 2026.04.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.6...master)
diff --git a/docs/releases/v2.0.8.mdx b/docs/releases/v2.0.8.mdx
new file mode 100644
index 0000000..3fcc29d
--- /dev/null
+++ b/docs/releases/v2.0.8.mdx
@@ -0,0 +1,68 @@
+---
+title: v2.0.8
+description: CowAgent 2.0.8 - Major Feishu channel upgrade (voice, streaming typewriter, one-click QR app creation), DeepSeek V4 / ERNIE 5.0 support, scheduler memory enhancements and multiple fixes
+---
+
+## 🪶 Major Feishu Channel Upgrade
+
+### 1. One-click QR-scan App Creation
+
+No more manual app setup, permission scopes and event subscriptions in the Feishu Open Platform. When `feishu_app_id` is not configured, both the Web Console and CLI startup flow now show a QR-scan entry — scan with Feishu, authorize, and the bot is created and config is filled back automatically. Out-of-the-box.
+
+Documentation: [Feishu Channel](https://docs.cowagent.ai/en/channels/feishu)
+
+### 2. Voice Messages
+
+Receive Feishu voice messages with automatic speech-to-text, and reply in voice via TTS. Recognition accuracy for short Chinese voice messages has been improved.
+
+### 3. Streaming Typewriter Replies
+
+Integrated with Feishu CardKit streaming cards, **enabled by default**, matching the Web Console experience:
+
+- Multi-turn agent flows render intermediate updates and the final reply on separate cards
+- Tuned for high-throughput models like DeepSeek to keep pace with the Web Console
+- Falls back to plain text replies automatically when not supported, no manual config needed
+- Requires Feishu client ≥ 7.20
+
+The voice and streaming building blocks come from a community contribution #2791. Thanks [@yangluxin613](https://github.com/yangluxin613)
+
+## 🤖 New Model Support
+
+- **DeepSeek V4 series**: Added `deepseek-v4-pro` / `deepseek-v4-flash`, with `deepseek-v4-flash` set as the new default
+- **Unified thinking-mode toggle**: DeepSeek V4, Qwen3 and other thinking-capable models now share the same `enable_thinking` switch
+- **ERNIE first-class integration**: New `qianfan` provider supporting `ernie-5.0` (default recommendation), `ernie-x1.1`, `ernie-4.5-turbo-128k`, `ernie-4.5-turbo-32k`. Dedicated `qianfan_api_key` / `qianfan_api_base` settings keep OpenAI config clean; legacy `wenxin` / `wenxin-4` paths are fully preserved. #2790 Thanks [@jimmyzhuu](https://github.com/jimmyzhuu)
+
+  Documentation: [ERNIE](https://docs.cowagent.ai/en/models/qianfan)
+
+## 🌐 Translation Provider
+
+- **Youdao translator**: Added a Youdao provider to the `translate/` module using the v3 SHA-256 signing scheme, with automatic ISO 639-1 language-code mapping (`zh`, `zh-TW`, etc.) #2797 Thanks [@Zmjjeff7](https://github.com/Zmjjeff7)
+
+## 🛠 OpenAI Client Refactor
+
+- **Drop SDK dependency**: The OpenAI bot is reimplemented on a native HTTP client — leaner startup, fewer dependency conflicts
+- **Web Console hint**: API base inputs in the model config UI now include version-path placeholder hints
+
+## ⏰ Scheduler Memory Enhancements
+
+- **Follow-up on task results**: Scheduled task results are automatically injected into the receiver's session history — the next turn can ask follow-up questions without re-stating context. Thanks [@huangrichao2020](https://github.com/huangrichao2020)
+- **No long-term memory pollution**: Scheduler-injected pairs are excluded from the daily memory flush so high-frequency tasks don't drown the memory store
+- **Bounded scheduler context**: The scheduler's own session context is automatically capped, so long-running periodic tasks don't accumulate state and slow down replies
+
+## 🔧 Tools and Safety
+
+- **Vision model selection**: `tools.vision.model` config now actually takes effect, with automatic fallback when unconfigured #2792
+- **Bash safety prompt**: The destructive-deletion confirm prompt is now scoped to paths outside the workspace — routine in-workspace operations are no longer interrupted
+
+## 🐛 Other Fixes
+
+- Fixed Deep Dream firing duplicate runs in multi-instance setups
+- Fixed missing `reasoning_content` on some history turns in DeepSeek multi-turn conversations
+
+## 📦 Upgrade
+
+Source-code deployments can run `cow update` or `./run.sh update` for a one-click upgrade, or pull the latest code and restart manually. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade) for details.
+
+> ⚠️ One-click Feishu app creation requires `lark-oapi>=1.5.5`. `cow update` pulls it automatically; manual deployments must update dependencies.
+
+**Release Date**: 2026.05.05 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.7...2.0.8)
diff --git a/docs/releases/v2.0.9.mdx b/docs/releases/v2.0.9.mdx
new file mode 100644
index 0000000..ccae36f
--- /dev/null
+++ b/docs/releases/v2.0.9.mdx
@@ -0,0 +1,65 @@
+---
+title: v2.0.9
+description: CowAgent 2.0.9 - Web Console model management, MCP protocol support, browser persistent login, new models and deployment hardening
+---
+
+## 🖥️ Model Management Console
+
+The Web Console adds a new **Models** page that organizes everything by **provider × capability**, covering chat, image, voice, embedding and search models in one place:
+
+- **Per-provider configuration**: Each provider's API Key / API Base is configured once at the top, and every capability below picks it up automatically — no more re-entering credentials
+- **Image models**: Image understanding and image generation can each pick their own provider and model independently; falls back to the main model when unspecified
+- **Voice models**: ASR (speech-to-text) and TTS (text-to-speech) can be configured independently, with new Qwen and Zhipu ASR/TTS models added
+- **Embedding models**: Configurable embedding models (used for memory and knowledge-base retrieval), with new support for OpenAI, Tongyi, Doubao, Zhipu and others; run `/memory rebuild-index` after switching to rebuild the index online
+- **Search capability**: Web search has been upgraded to support Bocha, Baidu, Zhipu and more providers — in auto mode the agent can synthesize results from multiple sources for deeper research
+
+Documentation: [Models Overview](https://docs.cowagent.ai/en/models)
+
+<img width="720" alt="20260522113305" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-models-config.png" />
+
+
+## 🧩 MCP Protocol Support
+
+Adds support for **MCP (Model Context Protocol)**, expanding from a fixed built-in toolset to an open, pluggable tool ecosystem — any MCP-compatible service can be plugged in directly as an agent tool.
+
+- Native JSON-RPC implementation, zero extra dependencies, supports both `stdio` and `sse` transports
+- Compatible with the `mcpServers` configuration style used by Claude Desktop / Cursor, reads `~/cow/mcp.json` by default
+
+Documentation: [MCP Tools](https://docs.cowagent.ai/en/tools/mcp). Thanks [@yangluxin613](https://github.com/yangluxin613) (#2801)
+
+## 🌐 Browser Persistent Login
+
+For sites that require login or have anti-bot protection, the browser tool can now persist a login session for long-term reuse, and supports attaching to your real Chrome browser to bypass fingerprint detection:
+
+- **Persistent user profile (default)**: Uses `~/.cow/browser_profile` as the browser user data dir by default; once logged in, sessions are reused automatically on subsequent runs
+- **CDP mode**: Configure `tools.browser.cdp_endpoint` to take over a real Chrome instance with full browser permissions
+
+Documentation: [Browser Tool](https://docs.cowagent.ai/en/tools/browser). Thanks [@leafmove](https://github.com/leafmove) (#2809)
+
+## 🤖 New Models and Improvements
+
+- **New models**: `gpt-5.5`, `gemini-3.5-flash`, `qwen3.7-max`, `ernie-5.1`
+- **Improvements**: DeepSeek V4 supports the `reasoning_effort` thinking-depth parameter; fixed thinking models like MiMo failing to connect via the OpenAI-compatible protocol
+
+## 🔒 Deployment & Security
+
+- **Bind to localhost by default**: The Web Console `web_host` now defaults to `127.0.0.1`; for server deployments, set it to `0.0.0.0` and configure a password manually. Thanks @August829, @yidaozhongqing, @YLChen-007, @icysun
+- **Fully bundled frontend assets**: All third-party CSS / JS are now served locally — the console works offline and on intranet deployments. Thanks [@gitlayzer](https://github.com/gitlayzer) (#2816)
+
+## 🛠 UX Improvements & Fixes
+
+- **TTS rolls out to more channels**: Web Console, Personal WeChat, Feishu, DingTalk and WeCom Smart Bot all support voice replies — see the [Channels Overview](https://docs.cowagent.ai/en/channels)
+- **Log panel enhancements**: Differentiated highlighting by log level, with level-based filtering. Thanks [@yangluxin613](https://github.com/yangluxin613) (#2807)
+- **Auto-launch Web Console**: The Web Console now opens automatically on startup. Thanks [@yangluxin613](https://github.com/yangluxin613) (#2804)
+- **Clean Ctrl+C exit**: No more long `KeyboardInterrupt` stack traces. Thanks [@yangluxin613](https://github.com/yangluxin613) (#2806)
+- **Folder upload**: Web Console supports directory uploads, with path validation adapted for Windows. Thanks [@TryToMakeUsBetter](https://github.com/TryToMakeUsBetter) (#2814)
+- Fixed scheduled tasks executing duplicates under certain conditions. Thanks [@CNXudiandian](https://github.com/CNXudiandian) (#2820)
+- Fixed one-shot scheduled tasks with timezone not firing. Thanks @AethericSpace
+- Fixed failed tool calls not being displayed after page refresh. Thanks [@a1094174619](https://github.com/a1094174619) (#2822)
+- Fixed WeCom bot messages with illegal control characters failing to be delivered. Thanks [@Jacques-Zhao](https://github.com/Jacques-Zhao) (#2810)
+
+## 📦 Upgrade
+
+Source-code deployments can run `cow update` for a one-click upgrade, or pull the latest code and restart manually. See the [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade) for details.
+
+**Release Date**: 2026.05.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.8...2.0.9)
diff --git a/docs/releases/v2.1.0.mdx b/docs/releases/v2.1.0.mdx
new file mode 100644
index 0000000..e3aefe2
--- /dev/null
+++ b/docs/releases/v2.1.0.mdx
@@ -0,0 +1,69 @@
+---
+title: v2.1.0
+description: CowAgent 2.1.0 - Internationalization, new Telegram / Discord / Slack / WeChat Customer Service channels, CLI interaction upgrades, MCP protocol enhancements and new models
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.0) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.0)
+
+## 📱 New Channels
+
+This release adds several mainstream platform channels — configure and go, ready out of the box:
+
+- **Telegram Bot**: Connect a Telegram bot with support for text and multimedia messages
+- **Discord Bot**: Connect a Discord bot to chat in channels and direct messages
+- **Slack Bot**: Connect a Slack bot and bring CowAgent into your team's workflow
+- **WeChat Customer Service**: New WeChat Customer Service channel that receives images and files and automatically merges them into the next turn, bringing its multimedia context experience in line with other channels. Thanks [@6vision](https://github.com/6vision) (#2840)
+
+Documentation: [Channels Overview](https://docs.cowagent.ai/en/channels)
+
+## 🌍 Internationalization
+
+CowAgent introduces an end-to-end internationalization framework built for developers worldwide, adapting automatically based on the system language:
+
+- **End-to-end localization**: The install flow, CLI, logs and error messages, agent system prompts and more are all localized
+- **Automatic language detection**: The default `auto` mode infers the language from the system locale, or you can set `cow_lang` explicitly in `config.json`. English and Chinese ship first, with more languages to follow
+- **One-click switch in the console**: The Web Console supports switching the system language online, taking effect in real time
+
+## ⌨️ CLI Interaction Upgrades
+
+- **Streamlined one-line install**: The install script is simplified with an interactive setup — pick your language, and optionally choose a model and channel right from the prompts, getting you up and running in minutes
+- **Streaming output**: The Terminal channel now renders the agent's reasoning, tool calls and streaming replies in real time
+- **Fuzzy command matching**: Supports command abbreviations and near-miss typo suggestions, ships with built-in shortcuts, and lets you define custom aliases in the config file. Thanks [@lyteen](https://github.com/lyteen) (#2850)
+- **Task cancellation**: In-flight agent runs can be interrupted on demand — the Web Console adds a stop button, and other channels can send `/cancel` to abort
+
+Documentation: [CLI Guide](https://docs.cowagent.ai/en/cli/general)
+
+## 🧩 MCP Protocol Enhancements
+
+MCP tools now support the **Streamable HTTP** transport. On top of the existing `stdio` and `sse` options, this makes more MCP services compatible, letting you connect directly to remote tools that use the streamable HTTP protocol.
+
+Documentation: [MCP Tools](https://docs.cowagent.ai/en/tools/mcp)
+
+## 🤖 New Models & Improvements
+
+- **New models**: `claude-opus-4-8`, Xiaomi `MiMo`
+- **Improvements**: Fixed JSON parsing failures for tool-call arguments returned by some models (#2823)
+
+Documentation: [Models Overview](https://docs.cowagent.ai/en/models)
+
+## 🧠 Memory & Retrieval Improvements
+
+- **Keyword search**: Fixed low hit rates for Chinese keyword search and empty results for pure-English keyword queries
+- **Vector retrieval**: Optimized the vector retrieval flow and improved Python version compatibility
+
+Thanks [@yangluxin613](https://github.com/yangluxin613) (#2832)
+
+## 🛠 UX Improvements & Fixes
+
+- **Confined file access**: Web file reads and sends are now limited to the user home directory and agent workspace by default to prevent arbitrary file reads; the scope can be widened via `web_file_serve_root`
+- **More stable scheduled tasks**: Fixed scheduled-task pushes failing after a restart on the Personal WeChat channel
+- **Browser tool**: Fixed non-HTTP schemes being dropped from navigation URLs; reduced browser memory usage
+- **WeChat Official Account**: Passive replies now merge cached text segments, flush ready segments while a task is still running, and support sending local `file://` images. Thanks [@6vision](https://github.com/6vision) (#2848)
+- **Faster WeCom bot responses**: Callbacks are now dispatched asynchronously to avoid message loss from WeCom's 5-second timeout
+- **More robust login**: Fixed a login error when `web_password` was not a string
+
+## 📦 Upgrade
+
+Source-code deployments can run `cow update` for a one-click upgrade, or pull the latest code and restart manually. See the [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade) for details.
+
+**Release Date**: 2026.06.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.9...2.1.0)
diff --git a/docs/releases/v2.1.1.mdx b/docs/releases/v2.1.1.mdx
new file mode 100644
index 0000000..61f0ba2
--- /dev/null
+++ b/docs/releases/v2.1.1.mdx
@@ -0,0 +1,63 @@
+---
+title: v2.1.1
+description: CowAgent 2.1.1 - Self-Evolution, Web Console message management and parallel sessions, cross-platform MCP enhancements, new models and improvements
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.1) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.1)
+
+## 🧬 Self-Evolution
+
+CowAgent introduces **Self-Evolution**, letting the agent go beyond completing a single task and keep improving through everyday collaboration with you:
+
+- **Automatic review after idle**: Once a conversation goes idle, the agent reviews it in the background to fix problems a skill exposed in use, create reusable new skills, follow up on unfinished tasks, and record important information into memory and the knowledge base
+- **Silent by default, notify on demand**: It reports what it changed only when it actually made a change, and stays silent otherwise
+- **Safe and reversible**: Every review is backed up beforehand and can be undone at any time. Built-in skills are protected, and all reads and writes stay within the workspace
+
+Enabled by default for new installs. Existing users can turn it on with a single click in the Web Console under **Settings → Agent Config**.
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-evolution-demo.png" alt="Self-Evolution conversation example" />
+
+Documentation: [Self-Evolution](https://docs.cowagent.ai/memory/self-evolution)
+
+## 💬 Web Console Upgrades
+
+The Web Console chat experience gets several enhancements:
+
+- **Message management**: Edit, delete, and regenerate both user and bot messages; code blocks now include language labels and a one-click copy button
+- **Parallel sessions**: Run multiple sessions at the same time without interference, with live streaming automatically resumed when you switch back to a session
+- **Refinements**: Drag and drop files anywhere in the chat view; automatically switch to a sibling session after deleting the active one
+
+Thanks [@core-power](https://github.com/core-power) (#2865)
+
+## 🧩 Cross-platform MCP Enhancements
+
+- **Windows compatibility fix**: Fixed `stdio` communication failing on Windows, and made the server timeout configurable via `mcp.json`
+- **Concurrent calls**: The `sse` and `streamable-http` transports now support concurrent calls across sessions for faster multi-tool responses
+
+Thanks [@xliu123321](https://github.com/xliu123321) (#2859)
+
+Documentation: [MCP Tools](https://docs.cowagent.ai/tools/mcp)
+
+## 🤖 New Models & Improvements
+
+- **MiniMax-M3**: Added and set as the default model, with the M2.7 series kept as an option. Thanks [@octo-patch](https://github.com/octo-patch) (#2855)
+- **Qwen3.7-plus**: Added support for multi-modal conversations
+- **Selectable ASR model**: The Web Console can now select and persist the ASR (speech recognition) model. Thanks [@nightwhite](https://github.com/nightwhite) (#2857)
+- **Simplified install menu**: The one-line install script streamlines the model menu and adds the Xiaomi MiMo option
+
+Documentation: [Models Overview](https://docs.cowagent.ai/models)
+
+## 🛠 Improvements & Fixes
+
+- **Python 3.13 support**: Fixed installation and dependency compatibility on Python 3.13
+- **Internationalization**: The channel list is now ordered by the interface language; refined the automatic language fallback under `auto` mode
+- **More reliable cancellation**: Fixed cases where a streaming reply could not be interrupted
+- **CLI**: `cow status` now shows the current project path
+- **Hardened deployment security**: The credential-file block is narrowed to `~/.cow/.env` so other directories are no longer affected (Thanks [@orbisai0security](https://github.com/orbisai0security) #2863); the WeChat Official Account now rejects webhook requests when `wechatmp_token` is empty
+- **Group task board plugin**: Added the group task board plugin source. Thanks [@Wyh-max-star](https://github.com/Wyh-max-star) (#2853)
+
+## 📦 Upgrade
+
+Source-code deployments can run `cow update` for a one-click upgrade, or pull the latest code and restart manually. See the [Upgrade Guide](https://docs.cowagent.ai/guide/upgrade) for details.
+
+**Release Date**: 2026.06.09 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.0...2.1.1)
diff --git a/docs/releases/v2.1.2.mdx b/docs/releases/v2.1.2.mdx
new file mode 100644
index 0000000..45e22a1
--- /dev/null
+++ b/docs/releases/v2.1.2.mdx
@@ -0,0 +1,67 @@
+---
+title: v2.1.2
+description: CowAgent 2.1.2 - Web Console management upgrades, Self-Evolution improvements, new models, WeCom smart-bot callback mode, and security hardening
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.2) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.2)
+
+## 💬 Web Console Improvements
+
+This release adds several visual management capabilities to the Web Console, so more configuration can be done in the UI without editing files:
+
+- **Scheduled task management**: View, edit, enable/disable, and delete any scheduled task directly in the console. The task list is sorted by enabled status first, then by next run time. Thanks @HnBigVolibear (#2892)
+- **Knowledge base categories and document management**: The knowledge base can now be organized by category, with documents under each category managed in the UI. Thanks @yangziyu-hhh (#2893)
+- **Multiple custom model providers**: Configure multiple OpenAI-compatible providers and switch the active one with a single click, fully compatible with existing configuration. Thanks @kirs-hi (#2877)
+- **Session renaming**: Rename sessions manually to tell parallel tasks apart (#2897)
+- **Bash streaming output**: Long-running Bash commands now stream their progress in real time. Thanks @yangziyu-hhh (#2879)
+
+## 🧬 Self-Evolution Improvements
+
+Building on the Self-Evolution introduced in the previous release, this version refines it further:
+
+- **Lower trigger thresholds**: The default review thresholds are lowered, so everyday collaboration turns into improvements sooner
+- **No concurrent reviews**: When a single turn runs long, the idle review no longer fires by mistake, avoiding interference with the active conversation
+- **Better review summary**: Refined the summary prompt to keep summaries concise, raise their information density, and output them in the conversation language
+
+Documentation: [Self-Evolution](https://docs.cowagent.ai/memory/self-evolution)
+
+## 🤖 New Models
+
+- **kimi-k2.7-code**: Added and set as the default Kimi model, with `kimi-k2.7-code-highspeed` also available
+- **glm-5.2**: Added and set as the default GLM model
+
+Documentation: [Models Overview](https://docs.cowagent.ai/models)
+
+## 🏢 WeCom Smart-Bot Callback Mode
+
+The WeCom smart-bot channel adds an **HTTP callback mode** alongside the existing long connection, so deployments that cannot keep a long connection open can still connect reliably:
+
+- **Mode switching**: Switch between `websocket` (long connection) and `webhook` (callback) via `wecom_bot_mode`
+- **Encrypted transport**: Callback mode fully supports URL verification, message decryption, and passive-reply encryption
+- **Stability fixes**: Fixed reply interruption, premature stream termination, and temporary image file leaks
+
+Thanks @6vision (#2896 #2869)
+
+Documentation: [WeCom Smart Bot](https://docs.cowagent.ai/channels/wecom-bot)
+
+## 🔒 Security Hardening
+
+- **Vision tool SSRF protection**: Validates the target address before resolving an image URL, blocking requests to internal, loopback, and cloud server metadata endpoints. Thanks @kirs-hi (#2886)
+- **Web fetch SSRF protection**: `web_fetch` validates the target address before fetching and re-validates every redirect hop, preventing redirects from bypassing the check to reach internal addresses. Thanks @christop (#2900)
+- **Skill install path traversal protection**: Validates the path when installing a skill, preventing a malicious skill name from escaping the `skills/` directory through path traversal and writing to an unauthorized location. Thanks @kirs-hi (#2886)
+
+## 🛠 Improvements & Fixes
+
+- **CLI self-restart**: Added the self-restart command so the agent can restart its own process
+- **Windows compatibility**: Persist the cow CLI directory to the user PATH; fixed `python -c` long commands exceeding the `cmd.exe` length limit; avoid building greenlet from source during install
+- **Custom roles**: The role plugin supports customization via standalone prompt files under `roles/*.json`. Thanks @sufan721 (#2891)
+- **Stability fixes**: Fixed a KeyError on `/cancel` and an infinite loop in image compression (Thanks @kirs-hi #2888)
+- **Install improvements**: Updated the startup script and default config; fixed ASR/TTS defaults, the self-evolution flag, and install hangs
+- **Vision tool stability**: Increased the vision tool timeout and max_tokens
+- **Memory distillation**: Removed the output length cap in deep-dream distillation to avoid truncating a large `MEMORY.md`
+
+## 📦 Upgrade
+
+Source-code deployments can run `cow update` for a one-click upgrade, or pull the latest code and restart manually. See the [Upgrade Guide](https://docs.cowagent.ai/guide/upgrade) for details.
+
+**Release Date**: 2026.06.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.1...2.1.2)
diff --git a/docs/releases/v2.1.3.mdx b/docs/releases/v2.1.3.mdx
new file mode 100644
index 0000000..b08c971
--- /dev/null
+++ b/docs/releases/v2.1.3.mdx
@@ -0,0 +1,75 @@
+---
+title: v2.1.3
+description: "CowAgent 2.1.3: Desktop client for macOS / Windows, enhanced knowledge base document management, on-demand MCP tool retrieval, Traditional Chinese support, new models, plus security and experience improvements"
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.3) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.3)
+
+## 🖥 Desktop Client
+
+Introducing the **CowAgent Desktop client** for **macOS and Windows** — your local super AI assistant, truly ready to use out of the box.
+
+Download: [CowAgent Desktop](https://cowagent.ai/download/)
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/desktop-chat-demo-en.png" alt="CowAgent Desktop client" />
+
+Highlights:
+
+- **Out of the box**: the full Agent runtime is bundled — launch right after install, no need to set up Python or other dependencies
+- **Full chat experience**: streaming replies, session management, tool-call step display, Markdown rendering, plus sending and previewing images / videos / files
+- **Visual management**: configuration, models, knowledge base, scheduled tasks, skills, and memory pages mirror the Web console, all manageable in the native UI
+- **Channel onboarding**: connect messaging channels by scanning a QR code right inside the app
+- **Auto update**: automatic version checks and one-click updates, with download speed optimized across regions
+- **Native experience**: first-run onboarding, follows the system language, and platform-adaptive window interactions
+
+Docs: [Desktop Client](https://docs.cowagent.ai/guide/desktop)
+
+## 📚 Knowledge Base
+
+- **Create & import documents**: create new documents or import external ones directly from the UI
+- **Automatic index maintenance**: the knowledge base index is rebuilt automatically from the actual directory tree, preventing index drift or lost documents
+- **Vectorization fix**: the index now reuses the unified embedding provider, ensuring real semantic vectors instead of falling back to keyword search
+
+Thanks @yangziyu-hhh
+
+Docs: [Knowledge Base](https://docs.cowagent.ai/memory/knowledge)
+
+## 🔌 On-demand MCP Tool Retrieval
+
+To address context bloat when many MCP tools are connected, we added **on-demand tool retrieval**: relevant MCP tools are loaded on demand via RAG vector search based on the current task, reducing the context taken up by irrelevant tools. Thanks @fengyl07
+
+Docs: [MCP Tools](https://docs.cowagent.ai/tools/mcp)
+
+## 🌏 Traditional Chinese Support
+
+The Web console, logs, and documentation now support **Traditional Chinese (zh-Hant)**; the interface language can follow the system or be switched manually. Thanks @anomixer (#2935)
+
+## 🤖 New Models
+
+- Added support for **claude-sonnet-5** and **claude-fable-5**
+- Added support for **doubao-seed-2-1-pro** and **doubao-seed-2-1-turbo**
+
+Docs: [Models](https://docs.cowagent.ai/models)
+
+## 🔒 Security Hardening
+
+- **Sensitive file read protection**: hardened access to credential and other sensitive files to prevent bypass reads. Thanks @fengyl07 (#2913)
+- **Browser access protection**: blocks browser requests targeting internal network and cloud server internal endpoints, reducing the risk of being tricked into reaching internal services. Thanks @Jiangrong-W
+- **Safer config parsing**: config content is parsed in a safer way to avoid potential code execution risks. Thanks @shunfeng8421
+
+## 🛠 Improvements & Fixes
+
+- **Custom provider support**: embedding and vision models can now use custom providers; also fixed a memory query issue on Windows. Thanks @HnBigVolibear
+- **More reliable file editing**: better preserves original indentation, and fuzzy matching no longer touches unrelated content. Thanks @weijun-xia (#2942)
+- **Command output encoding fix**: fixed garbled Chinese characters when a command produces large output. Thanks @weijun-xia (#2941)
+- **Azure OpenAI fixes**: fixed streaming output and related configuration issues for Azure OpenAI. Thanks @Tunnello
+- **WeCom Smart Bot**: added channel docs for the webhook (callback) mode. Thanks @6vision
+- **Deep Dream toggle**: added a dedicated `deep_dream_enabled` switch to enable or disable Deep Dream distillation independently.
+- **Stability**: improved connection recycling in the Web service and fixed several Self-Evolution issues (#2924, #2904)
+
+## 📦 How to Upgrade
+
+- **Desktop client**: get the latest version from the [download page](https://cowagent.ai/download/).
+- **Source deployment**: run `cow update` for a one-click upgrade, or pull the latest code and restart. See the [upgrade guide](https://docs.cowagent.ai/guide/upgrade).
+
+**Release date**: 2026.07.08 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.2...2.1.3)
diff --git a/docs/skills/create.mdx b/docs/skills/create.mdx
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--- /dev/null
+++ b/docs/skills/create.mdx
@@ -0,0 +1,58 @@
+---
+title: Create Skills
+description: Create custom skills through conversation
+---
+
+CowAgent includes a built-in Skill Creator that lets you quickly create, install, or update skills through natural language conversation.
+
+## Usage
+
+Simply describe the skill you want in a conversation, and the Agent will handle the creation:
+
+- Codify workflows as skills: "Create a skill from this deployment process"
+- Integrate third-party APIs: "Create a skill based on this API documentation"
+- Install remote skills: "Install xxx skill for me"
+
+## Creation Flow
+
+1. Tell the Agent what skill you want to create
+2. Agent automatically generates `SKILL.md` description and execution scripts
+3. Skill is saved to the workspace `~/cow/skills/` directory
+4. Agent will automatically recognize and use the skill in future conversations
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+## SKILL.md Format
+
+Created skills follow the standard SKILL.md format:
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| Field | Description |
+| --- | --- |
+| `name` | Skill name, must match directory name |
+| `description` | Skill description, Agent decides whether to invoke based on this |
+| `metadata.requires.bins` | Required system commands |
+| `metadata.requires.env` | Required environment variables |
+| `metadata.always` | Always load (default false) |
+
+<Tip>
+  See the [Skill Creator documentation](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md) for details.
+</Tip>
diff --git a/docs/skills/hub.mdx b/docs/skills/hub.mdx
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--- /dev/null
+++ b/docs/skills/hub.mdx
@@ -0,0 +1,65 @@
+---
+title: Skill Hub
+description: Browse, search, and install AI Agent skills
+---
+
+[Cow Skill Hub](https://skills.cowagent.ai/) is an open-source skill marketplace for AI Agents, aggregating official picks, community contributions, and third-party skills from GitHub, ClawHub, and beyond.
+
+Source code: [github.com/zhayujie/cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
+
+## Features
+
+- **Browse skills** — filter by category (Featured / Community / Third-party) and tags
+- **Search skills** — find skills by name or description
+- **View details** — read the skill manifest, file contents, install command, and required environment variables
+- **One-click install** — copy the install command and run it in CowAgent
+
+## Installing a skill
+
+Run the install command in chat or in your terminal:
+
+<CodeGroup>
+```text Chat
+/skill install <name>
+```
+
+```bash Terminal
+cow skill install <name>
+```
+</CodeGroup>
+
+You can also browse the marketplace directly from chat:
+
+```text
+/skill list --remote
+/skill search <keyword>
+```
+
+Beyond the curated list, you can install third-party skills from **GitHub, ClawHub, LinkAI, or any URL** via the CLI. See [Installing skills](/skills/install) for details.
+
+## Contributing a skill
+
+To submit your own skill:
+
+1. Visit [skills.cowagent.ai/submit](https://skills.cowagent.ai/submit)
+2. Sign in with GitHub or Google
+3. Upload a folder or zip file containing `SKILL.md`
+4. Skill name, display name, and description are auto-detected — adjust as needed
+5. Submit for review; skills go live after security and quality checks
+
+<img src="https://cdn.link-ai.tech/doc/20260401111904.png" width="800" />
+
+Skill file layout:
+
+```
+your-skill/
+├── SKILL.md        # required, in the root
+├── scripts/        # optional, runtime scripts
+└── resources/      # optional, additional assets
+```
+
+<Tip>
+  Skills are built around the `SKILL.md` manifest. You can also download `SKILL.md` from a skill's detail page and use it with any Agent that supports custom instructions (OpenClaw, Cursor, Claude Code, and more).
+</Tip>
diff --git a/docs/skills/image-generation.mdx b/docs/skills/image-generation.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/skills/image-generation.mdx
@@ -0,0 +1,98 @@
+---
+title: image-generation
+description: Text-to-image / image-to-image / multi-image fusion with automatic multi-provider routing and fallback
+---
+
+A general-purpose image generation and editing skill supporting six providers: OpenAI, Gemini, Seedream (Volcengine Ark), Qwen (DashScope), MiniMax, and LinkAI. Configure any one provider's key to start using it; configure multiple to enable automatic fallback.
+
+## Supported Models
+
+| Provider | Models / Aliases | Notes |
+| --- | --- | --- |
+| OpenAI | `gpt-image-2`, `gpt-image-1` | General-purpose, high quality, supports `quality` parameter |
+| Gemini Nano Banana | `nano-banana-2`, `nano-banana-pro`, `nano-banana` | Corresponds to the image variants of `gemini-3.1-flash`, `gemini-3-pro`, `gemini-2.5-flash` |
+| Seedream (Volcengine Ark) | `seedream-5.0-lite`, `seedream-4.5` | Native 2K–4K, up to 14 reference images for fusion |
+| Qwen (DashScope) | `qwen-image-2.0`, `qwen-image-2.0-pro` | Strong with Chinese text rendering and text-image layouts |
+| MiniMax | `image-01` | Fast and simple |
+| LinkAI | Any model | Universal gateway, used as fallback |
+
+## Model Selection
+
+By default, "auto routing + automatic fallback" is used:
+
+1. Pick the first configured provider in the order `OpenAI → Gemini → Seedream → Qwen → MiniMax → LinkAI`
+2. On errors such as 401, model not enabled, or network issues, automatically switch to the next provider
+3. If the user specifies a model in the conversation (e.g. "use seedream to draw a cat"), the corresponding provider is promoted to the front
+
+To pin a specific model:
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+## Configuring API Keys
+
+<Tip>
+  It is recommended to configure providers from the "Model Management" page in the [Web console](/channels/web). Chat model keys configured there are automatically reused by the image generation skill — no need to set them twice. You can also edit the configuration file manually or temporarily set keys in a conversation using the `env_config` tool.
+</Tip>
+
+Credentials are shared with the main model providers:
+
+| Field | Provider |
+| --- | --- |
+| `openai_api_key` | OpenAI |
+| `gemini_api_key` | Gemini |
+| `ark_api_key` | Volcengine Ark (Seedream) |
+| `dashscope_api_key` | Alibaba DashScope (Qwen) |
+| `minimax_api_key` | MiniMax |
+| `linkai_api_key` | LinkAI |
+
+
+## Enabling and Disabling
+
+The skill automatically adjusts its status based on API keys:
+
+- **Key configured**: the Agent calls the skill directly when it receives a drawing request
+- **Key not configured**: the skill still appears in context (marked as "needs configuration") — the Agent will guide the user to set up a key
+
+To control it manually:
+
+```text
+/skill disable image-generation    # Disable
+/skill enable image-generation     # Re-enable
+```
+
+Equivalent terminal commands: `cow skill disable image-generation` / `cow skill enable image-generation`.
+
+## Parameters
+
+| Parameter | Type | Required | Default | Description |
+| --- | --- | --- | --- | --- |
+| `prompt` | string | Yes | — | Image description |
+| `image_url` | string / list | No | null | Input image for editing — local path or URL; pass a list for multi-image fusion |
+| `quality` | string | No | auto | `low` / `medium` / `high`, supported only by some providers |
+| `size` | string | No | auto | `512` / `1K` / `2K` / `3K` / `4K`, or pixel value like `1024x1024` |
+| `aspect_ratio` | string | No | null | `1:1` / `3:2` / `2:3` / `16:9` / `9:16` / `21:9`; Gemini also supports `1:4` / `4:1` / `1:8` / `8:1` |
+
+<Warning>
+  **Higher quality and larger size cost more and take longer.** For everyday conversations, use the defaults (`auto`) or `quality=low` + `size=1K` — about 20 seconds per image. For posters or when high resolution is explicitly requested, use `quality=high` + `size=2K/4K` — may take 1–5 minutes.
+</Warning>
+
+## Common Use Cases
+
+- **Text-to-image**: generate illustrations, posters, icons, avatars, storyboards, etc. from a description
+- **Image-to-image**: change styles, swap elements, add decorations or text on an existing image
+- **Multi-image fusion**: combine multiple reference images into one (outfit swaps, character group photos, etc.)
+
+<Note>
+- Bash timeout should be set to 600 seconds: each provider has a 300-second HTTP timeout, and the script may try multiple providers sequentially
+- Input images are automatically compressed to ≤ 4 MB with the longest edge ≤ 4096 px
+- Gemini / Seedream / Qwen / MiniMax do not support the `quality` parameter
+- Seedream defaults to 2K; `seedream-5.0-lite` supports up to 3K; `seedream-4.5` supports up to 4K
+</Note>
diff --git a/docs/skills/index.mdx b/docs/skills/index.mdx
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--- /dev/null
+++ b/docs/skills/index.mdx
@@ -0,0 +1,64 @@
+---
+title: Skills Overview
+description: CowAgent skills system introduction
+---
+
+Skills provide infinite extensibility for the Agent. Each Skill consists of a description file (`SKILL.md`), execution scripts (optional), and resources (optional), describing how to accomplish specific types of tasks.
+
+The difference between Skills and Tools: Tools are atomic operations implemented in code (e.g., file read/write, command execution), while Skills are high-level workflows based on description files that can combine multiple Tools to complete complex tasks.
+
+## Getting Skills
+
+CowAgent offers multiple ways to acquire skills:
+
+- **Cow Skill Hub** — Browse and install community skills via `/skill list --remote`
+- **GitHub** — Install directly from GitHub repositories, with batch install support
+- **ClawHub** — Install ClawHub skills via `/skill install clawhub:name`
+- **URL** — Install from zip archives or SKILL.md links
+- **Conversational creation** — Let the Agent create skills through natural language conversation
+
+See [Install Skills](/skills/install) and [Skill Management Commands](/cli/skill) for details. You can also [create skills](/skills/create) through conversation.
+
+## Skill Loading Priority
+
+1. **Workspace skills** (highest): `~/cow/skills/`
+2. **Project built-in skills** (lowest): `skills/`
+
+Skills with the same name are overridden by priority.
+
+## Skill File Structure
+
+```
+skills/
+├── my-skill/
+│   ├── SKILL.md          # Skill description (frontmatter + instructions)
+│   ├── scripts/          # Execution scripts (optional)
+│   └── resources/        # Additional resources (optional)
+```
+
+### SKILL.md Format
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| Field | Description |
+| --- | --- |
+| `name` | Skill name, must match directory name |
+| `description` | Skill description, Agent decides whether to invoke based on this |
+| `metadata.requires.bins` | Required system commands |
+| `metadata.requires.env` | Required environment variables |
+| `metadata.always` | Always load (default false) |
diff --git a/docs/skills/install.mdx b/docs/skills/install.mdx
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--- /dev/null
+++ b/docs/skills/install.mdx
@@ -0,0 +1,65 @@
+---
+title: Install Skills
+description: Install skills from multiple sources with a single command
+---
+
+CowAgent supports installing skills from [Cow Skill Hub](https://skills.cowagent.ai/), GitHub, ClawHub, LinkAI, and any URL via a unified `install` command. Use `/skill install` in chat or `cow skill install` in the terminal.
+
+## From the Skill Hub
+
+Browse all available skills at [skills.cowagent.ai](https://skills.cowagent.ai/) and install by name:
+
+```text
+/skill list --remote
+/skill install pptx
+```
+
+## From GitHub
+
+Any GitHub-hosted skill can be installed directly. Supports both repository-level batch install and subdirectory-level single install:
+
+```text
+/skill install larksuite/cli
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+```
+
+## From ClawHub
+
+All [ClawHub](https://clawhub.ai/) skills (40k+) can be installed with a single command:
+
+```text
+/skill install clawhub:<name>
+```
+
+## From LinkAI
+
+All public resources on [LinkAI](https://link-ai.tech/console) (10k+ apps / workflows / plugins), as well as your own resources (apps, workflows, knowledge bases, databases, plugins), can be installed via:
+
+```text
+/skill install linkai:<code>
+```
+
+> Every resource created on the LinkAI platform has a unique `code`. Find it on each resource's page in the [console](https://link-ai.tech/console).
+
+## From URL
+
+Supports zip archives and SKILL.md file links:
+
+```text
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+/skill install https://example.com/path/to/SKILL.md
+```
+
+## Manage Skills
+
+```text
+/skill list                  # View installed skills
+/skill info pptx             # View skill details
+/skill enable pptx           # Enable a skill
+/skill disable pptx          # Disable a skill
+/skill uninstall pptx        # Uninstall a skill
+```
+
+<Tip>
+  All commands above work in the terminal by replacing `/skill` with `cow skill`. See [Skill Management Commands](/cli/skill) for full documentation.
+</Tip>
diff --git a/docs/skills/knowledge-wiki.mdx b/docs/skills/knowledge-wiki.mdx
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+++ b/docs/skills/knowledge-wiki.mdx
@@ -0,0 +1,112 @@
+---
+title: knowledge-wiki
+description: Maintain a local structured knowledge base with automatic archiving, categorisation, and cross-referencing
+---
+
+Organises notes, insights, and reference materials from your conversations into a structured local knowledge base, automatically maintaining an index and cross-references between pages.
+
+`knowledge-wiki` maintains a `knowledge/` directory in your workspace — essentially the Agent's "second brain". The skill is marked `always: true`, so it is **always loaded** and requires no external dependencies.
+
+## When It Triggers
+
+- You share an article, document, or URL that you want to keep for future reference
+- A conversation produces conclusions worth retaining long-term
+- You want to look up something you accumulated earlier
+
+## Directory Structure
+
+```
+knowledge/
+├── index.md           # Global index (must be maintained)
+├── log.md             # Operation log (append-only)
+└── <category>/        # Category subdirectories (grouped by content)
+    └── <slug>.md      # Knowledge page (lowercase-hyphenated filename)
+```
+
+## Three Core Operations
+
+### 1. Ingest
+
+When you share some material, the Agent will:
+
+1. Read and understand the original content, extracting key information
+2. Decide which category it belongs to — check `index.md` first; create a new category if none fits
+3. Generate a knowledge page at `knowledge/<category>/<slug>.md`
+4. Update the index `index.md` and the log `log.md`
+
+### 2. Synthesise
+
+When a conversation produces new conclusions or insights:
+
+1. Create a new knowledge page under an appropriate category
+2. Add cross-links to and from related existing pages
+3. Update the index and log
+
+### 3. Query
+
+When you ask about previously accumulated knowledge:
+
+1. Search `index.md` for potentially relevant pages
+2. Open specific pages with the `read` tool
+3. Supplement with `memory_search` if needed
+4. Include links to knowledge pages in the answer so you can click through to the source
+
+## Page Format
+
+```markdown
+# Page Title
+
+> Source: <source URL or brief description>
+
+Body content. Link between pages using relative paths:
+[Related Page](../category/related-page.md)
+
+## Key Points
+
+- ...
+
+## Related Pages
+
+- [Page A](../category/page-a.md) — why it's related
+```
+
+<Note>
+- `> Source:` records where this knowledge came from. Always include it when there is a clear source
+- Cross-references are important: when creating or updating a page, remember to add back-links in the related pages too
+- **Only link to pages that already exist.** If a concept deserves its own page, create it first, then add the link
+</Note>
+
+## Index Format
+
+`knowledge/index.md` uses a flat list grouped by category, one knowledge page per line:
+
+```markdown
+# Knowledge Index
+
+## Category A
+- [Page Title](category-a/page-slug.md) — one-line summary
+
+## Category B
+- [Page Title](category-b/page-slug.md) — one-line summary
+```
+
+No tables, no emojis. Category names and organisation can be adjusted freely.
+
+## Log Format
+
+`knowledge/log.md` is append-only — newest entries go at the bottom:
+
+```markdown
+## [YYYY-MM-DD] ingest | Page Title
+## [YYYY-MM-DD] synthesize | Page Title
+```
+
+## Writing Guidelines
+
+- **Filenames**: lowercase with hyphens, e.g. `machine-learning.md`
+- **One topic per page** — link related content across pages
+- **Update, don't duplicate** — if a page already exists, update it rather than creating a new one
+- **Always update the index** `knowledge/index.md` after any change
+- **Distill, don't copy** — capture the key points, not the entire source
+- **Use full paths when referencing knowledge pages in conversations**, e.g. `[Title](knowledge/<category>/<slug>.md)`. Use relative paths only for inter-page links
+- **Include links when answering questions based on knowledge pages** so users can dig deeper
diff --git a/docs/skills/skill-creator.mdx b/docs/skills/skill-creator.mdx
new file mode 100644
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--- /dev/null
+++ b/docs/skills/skill-creator.mdx
@@ -0,0 +1,180 @@
+---
+title: skill-creator
+description: Create, install, and update skills — standardises SKILL.md format and directory structure
+---
+
+`skill-creator` is a "meta-skill" that helps the Agent create, install, and update other skills, ensuring every skill follows a consistent `SKILL.md` format and directory layout.
+
+## When It Triggers
+
+- The user wants to install a skill from a URL or remote repository
+- The user wants to create a brand-new skill from scratch
+- An existing skill needs upgrading or restructuring
+
+## What Is a Skill?
+
+A skill is a reusable instruction set plus optional scripts and assets. It injects domain expertise into the Agent so it can handle specific tasks like a specialist.
+
+A skill typically contains:
+
+1. **Specialised workflow** — step-by-step instructions for a category of tasks
+2. **Tool usage** — how to call a particular API or process a particular file format
+3. **Domain knowledge** — team conventions, business rules, data schemas, etc.
+4. **Attached resources** — scripts, reference docs, templates, etc.
+
+<Note>
+**Core principle: less is more.** Only write what the Agent wouldn't figure out on its own. For every line you add, ask yourself: is it worth the tokens?
+</Note>
+
+## Directory Structure
+
+```
+skill-name/
+├── SKILL.md            # Required: skill definition
+│   ├── YAML frontmatter (name / description are mandatory)
+│   └── Markdown body (instructions + examples)
+└── Optional resources
+    ├── scripts/        # Executable scripts (Python / Bash, etc.)
+    ├── references/     # Large reference docs the Agent reads on demand
+    └── assets/         # Templates, icons, etc. used directly in output
+```
+
+## SKILL.md Specification
+
+Frontmatter fields in the SKILL.md header:
+
+| Field | Description |
+| --- | --- |
+| `name` | Skill name — lowercase with hyphens, must match the directory name |
+| `description` | **The most important field.** Clearly state what the skill does and when to use it. The Agent reads this to decide whether to invoke it. All trigger-related descriptions go here, not in the body |
+| `metadata.cowagent.requires.bins` | System CLI tools that must be installed |
+| `metadata.cowagent.requires.env` | Required environment variables (all must be present) |
+| `metadata.cowagent.requires.anyEnv` | Multiple API keys — at least one must be set |
+| `metadata.cowagent.requires.anyBins` | Multiple tools — at least one must be installed |
+| `metadata.cowagent.always` | Set to `true` to always load, skipping dependency checks |
+| `metadata.cowagent.emoji` | Display emoji (optional) |
+| `metadata.cowagent.os` | OS restriction, e.g. `["darwin", "linux"]` |
+
+<Note>
+The `category` field does not need to be set manually — the system automatically sets it to `skill`.
+</Note>
+
+Two ways to declare API key dependencies:
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      env: ["MYAPI_KEY"]            # Must be present
+```
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      anyEnv: ["OPENAI_API_KEY", "LINKAI_API_KEY"]   # At least one
+```
+
+**Skills are auto-enabled/disabled based on dependencies**: they activate when all required environment variables are present and deactivate when any are missing — no need for manual `/skill enable`.
+
+## Resource Directories
+
+| Directory | What goes here | What does NOT go here |
+| --- | --- | --- |
+| `scripts/` | Code that needs to run repeatedly, or scripts that produce deterministic results | Demo-only code snippets |
+| `references/` | Documents **over 500 lines** that genuinely won't fit in SKILL.md (e.g. a full DB schema) | General API docs, tutorials, examples |
+| `assets/` | Files that appear in the final output (templates, icons, boilerplate, etc.) | Explanatory documentation |
+
+<Warning>
+**In principle, everything goes in `SKILL.md`** — only split into resource directories when it truly won't fit.
+
+Do not add `README.md`, `CHANGELOG.md`, or `INSTALLATION_GUIDE.md` to a skill — put everything in `SKILL.md`. Resource directories should only contain scripts that actually run or assets that are actually used.
+</Warning>
+
+## Installing External Skills
+
+After installation, the skill lands in `<workspace>/skills/<name>/`.
+
+| Source | How to install |
+| --- | --- |
+| URL (single file) | curl / web_fetch |
+| URL (zip archive) | Download and extract |
+| Local SKILL.md | Read directly |
+| Local zip archive | Extract |
+
+Installation steps:
+
+1. Locate the `SKILL.md` (may be at the root or in a subdirectory of the archive)
+2. Read the `name` from the frontmatter
+3. Copy the **entire skill directory** (including `SKILL.md`, `scripts/`, `assets/`, etc.) to `<workspace>/skills/<name>/`
+4. If the archive contains an `INSTALL.md` or similar setup script, run it — but the final result must still reside under `<workspace>/skills/<name>/`
+
+## Creating a Skill from Scratch
+
+Recommended order:
+
+1. **Clarify requirements** — ask the user for a few concrete use cases (don't ask too many at once)
+2. **Plan the structure** — does this skill need scripts? Reference docs? Template assets?
+3. **Scaffold** — use the init script:
+
+   ```bash
+   scripts/init_skill.py <skill-name> --path <workspace>/skills [--resources scripts,references,assets] [--examples]
+   ```
+
+4. **Fill in content** — write SKILL.md, add scripts and resources. Always test scripts after writing them
+5. **Validate** (optional):
+
+   ```bash
+   scripts/quick_validate.py <workspace>/skills/<skill-name>
+   ```
+
+6. **Iterate** — keep improving based on real-world usage feedback
+
+## Naming Conventions
+
+- Use only lowercase letters, digits, and hyphens. Normalise user-given names, e.g. `Plan Mode` → `plan-mode`
+- Maximum 64 characters
+- Keep it short, start with a verb, make it self-explanatory
+- Use tool names as prefixes when appropriate, e.g. `gh-address-comments`, `linear-address-issue`
+- The directory name and the `name` field must match exactly
+
+## Three-Level Loading
+
+Skills are not loaded into context all at once — they use a three-level progressive loading mechanism:
+
+1. **Metadata** (`name` + `description`) — always in context (~100 words). The Agent uses this to decide whether to invoke the skill
+2. **SKILL.md body** — loaded only when the skill is activated; keep it under 500 lines
+3. **Resource files** — read on demand by the Agent
+
+For skills with multiple variants (e.g. multi-cloud deployment), organise like this:
+
+```
+cloud-deploy/
+├── SKILL.md             # Main workflow and provider selection logic
+└── references/
+    ├── aws.md
+    ├── gcp.md
+    └── azure.md
+```
+
+When the user picks AWS, the Agent only reads `aws.md` — no need to load all three providers.
+
+## Common Design Patterns
+
+**Step-by-step**: numbered steps with corresponding scripts.
+
+```markdown
+1. Analyse form structure (run analyze_form.py)
+2. Generate field mappings (edit fields.json)
+3. Auto-fill the form (run fill_form.py)
+```
+
+**Branching**: different flows based on user intent.
+
+```markdown
+1. Determine operation type:
+   **Creating new content?** → follow the "Create" workflow
+   **Editing existing content?** → follow the "Edit" workflow
+```
+
+**Template-based**: when output format has strict requirements, include a template in SKILL.md for the Agent to follow.
diff --git a/docs/tools/bash.mdx b/docs/tools/bash.mdx
new file mode 100644
index 0000000..60b2091
--- /dev/null
+++ b/docs/tools/bash.mdx
@@ -0,0 +1,28 @@
+---
+title: bash - Terminal
+description: Execute system commands
+---
+
+Execute Bash commands in the current working directory, returns stdout and stderr. API keys configured via `env_config` are automatically injected into the environment.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `command` | string | Yes | Command to execute |
+| `timeout` | integer | No | Timeout in seconds |
+
+## Use Cases
+
+- Install packages and dependencies
+- Run code and tests
+- Deploy applications and services (Nginx config, process management, etc.)
+- System administration and troubleshooting
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
diff --git a/docs/tools/browser.mdx b/docs/tools/browser.mdx
new file mode 100644
index 0000000..4c6fda8
--- /dev/null
+++ b/docs/tools/browser.mdx
@@ -0,0 +1,172 @@
+---
+title: browser - Browser
+description: Control a browser to access and interact with web pages
+---
+
+Control a Chromium browser for web navigation, element interaction and content extraction. Supports JavaScript-rendered pages and uses a compact DOM snapshot so the Agent can efficiently understand page structure.
+
+## Installation
+
+<Tabs>
+  <Tab title="CLI install (recommended)">
+    ```bash
+    cow install-browser
+    ```
+
+    This command will:
+    - Install the `playwright` Python package (with auto-fallback for older systems)
+    - Install system dependencies on Linux
+    - Download the Chromium browser (Linux servers automatically use the headless build)
+    - Detect China-mainland networks and use mirror acceleration
+  </Tab>
+  <Tab title="Manual install">
+    ```bash
+    pip install playwright
+    playwright install chromium
+    ```
+
+    On Linux servers, install system dependencies as well:
+    ```bash
+    sudo playwright install-deps chromium
+    ```
+
+    On older systems (e.g. Ubuntu 18.04, glibc < 2.28), install a compatible version:
+    ```bash
+    pip install playwright==1.28.0
+    python -m playwright install chromium
+    ```
+
+    To accelerate the Chromium download from China:
+    ```bash
+    export PLAYWRIGHT_DOWNLOAD_HOST=https://registry.npmmirror.com/-/binary/playwright
+    python -m playwright install chromium
+    ```
+  </Tab>
+</Tabs>
+
+<Note>
+  1. Supported on Ubuntu 20.04+, Debian 10+, macOS and Windows. Older systems such as Ubuntu 18.04 will fall back to a compatible version automatically.
+  2. The browser tool has heavy dependencies (~300MB) and is optional. For lightweight web content retrieval, use the `web_fetch` tool.
+</Note>
+
+## Workflow
+
+A typical browser workflow for the Agent:
+
+1. **`navigate`** — Open the target URL
+2. **`snapshot`** — Get a compact DOM with auto-numbered interactive elements (`ref`)
+3. **`click` / `fill` / `select`** — Operate elements by `ref`
+4. **`snapshot`** — Snapshot again to verify the result
+
+## Supported Actions
+
+| Action | Description | Key parameters |
+| --- | --- | --- |
+| `navigate` | Open URL | `url` |
+| `snapshot` | Get structured page text (primary way) | `selector` (optional) |
+| `click` | Click an element | `ref` or `selector` |
+| `fill` | Fill text into an input | `ref` or `selector`, `text` |
+| `select` | Select a dropdown option | `ref` or `selector`, `value` |
+| `scroll` | Scroll the page | `direction` (up/down/left/right) |
+| `screenshot` | Save a screenshot to the workspace | `full_page` |
+| `wait` | Wait for an element or timeout | `selector`, `timeout` |
+| `press` | Press a key (Enter, Tab, etc.) | `key` |
+| `back` / `forward` | Browser back / forward | - |
+| `get_text` | Get an element's text content | `selector` |
+| `evaluate` | Run JavaScript | `script` |
+
+## Use Cases
+
+- Access a URL to retrieve dynamic page content
+- Fill in forms and log in
+- Operate web elements (click buttons, select options, etc.)
+- Verify the result of a deployed web page
+- Scrape content that requires JS rendering
+
+## Run Mode
+
+The browser picks a mode based on the runtime environment:
+
+| Environment | Mode |
+| --- | --- |
+| macOS / Windows | Headed (browser window visible) |
+| Linux desktop (with DISPLAY) | Headed |
+| Linux server (no DISPLAY) | Headless |
+
+You can override it in `config.json`:
+
+```json
+{
+  "tools": {
+    "browser": {
+      "headless": true
+    }
+  }
+}
+```
+
+## Persistent Login
+
+**Log in to a target site once and the Agent can keep using it.** Two ways are supported:
+
+### Option 1: Persistent mode (default)
+
+Works out of the box. Login state is saved under `~/.cow/browser_profile`. No configuration needed.
+
+To disable persistence and start with a clean environment every time:
+
+```json
+{
+  "tools": {
+    "browser": {
+      "persistent": false
+    }
+  }
+}
+```
+
+### Option 2: CDP mode (attach to real Chrome)
+
+Have the Agent connect to a separately launched real Chrome (instead of the Chromium bundled with Playwright) for full browser fingerprints. Useful for sites with strict bot detection.
+
+Launch Chrome with a debugging port and a dedicated user data directory:
+
+<Tabs>
+  <Tab title="macOS">
+    ```bash
+    "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Linux">
+    ```bash
+    google-chrome \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Windows">
+    ```powershell
+    & "C:\Program Files\Google\Chrome\Application\chrome.exe" `
+      --remote-debugging-port=9222 `
+      --user-data-dir="$env:USERPROFILE\.cow\chrome-cdp"
+    ```
+  </Tab>
+</Tabs>
+
+Then point the Agent at the endpoint in `config.json`:
+
+```json
+{
+  "tools": {
+    "browser": {
+      "cdp_endpoint": "http://localhost:9222"
+    }
+  }
+}
+```
+
+<Note>
+  Chrome 137+ requires `--remote-debugging-port` to be paired with a dedicated `--user-data-dir`. As a result, the CDP-launched Chrome **cannot directly reuse the login state of your daily Chrome**; you'll need to log in once inside this dedicated profile.
+</Note>
diff --git a/docs/tools/edit.mdx b/docs/tools/edit.mdx
new file mode 100644
index 0000000..f231c6b
--- /dev/null
+++ b/docs/tools/edit.mdx
@@ -0,0 +1,24 @@
+---
+title: edit - File Edit
+description: Edit files via precise text replacement
+---
+
+Edit files via precise text replacement. If `oldText` is empty, appends to the end of the file.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | File path |
+| `oldText` | string | Yes | Original text to replace (empty to append) |
+| `newText` | string | Yes | Replacement text |
+
+## Use Cases
+
+- Modify specific parameters in configuration files
+- Fix bugs in code
+- Insert content at specific positions in files
diff --git a/docs/tools/env-config.mdx b/docs/tools/env-config.mdx
new file mode 100644
index 0000000..23f75bf
--- /dev/null
+++ b/docs/tools/env-config.mdx
@@ -0,0 +1,36 @@
+---
+title: env_config - Environment
+description: Manage API keys and secrets
+---
+
+Manage environment variables (API keys and secrets) in the workspace `.env` file, with secure conversational updates. Built-in security protection and desensitization.
+
+## Dependencies
+
+| Dependency | Install Command |
+| --- | --- |
+| `python-dotenv` ≥ 1.0.0 | `pip install python-dotenv>=1.0.0` |
+
+Included when installing optional dependencies: `pip3 install -r requirements-optional.txt`
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `action` | string | Yes | Operation type: `get`, `set`, `list`, `delete` |
+| `key` | string | No | Environment variable name |
+| `value` | string | No | Environment variable value (only for `set`) |
+
+## Usage
+
+Tell the Agent what key you need to configure, and it will automatically invoke this tool:
+
+- "Configure my BOCHA_API_KEY"
+- "Set OPENAI_API_KEY to sk-xxx"
+- "Show configured environment variables"
+
+Configured keys are automatically injected into the `bash` tool's execution environment.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
diff --git a/docs/tools/index.mdx b/docs/tools/index.mdx
new file mode 100644
index 0000000..fd2a21f
--- /dev/null
+++ b/docs/tools/index.mdx
@@ -0,0 +1,60 @@
+---
+title: Tools Overview
+description: CowAgent built-in tools system
+---
+
+Tools are the core capability for Agent to access operating system resources. The Agent intelligently selects and invokes tools based on task requirements, performing file operations, command execution, web search, scheduled tasks, and more. Tools are implemented in the `agent/tools/` directory.
+
+## Built-in Tools
+
+The following tools are available by default with no extra configuration:
+
+<CardGroup cols={2}>
+  <Card title="read - File Read" icon="file" href="/tools/read">
+    Read file content, supports text, images, PDF
+  </Card>
+  <Card title="write - File Write" icon="pen" href="/tools/write">
+    Create or overwrite files
+  </Card>
+  <Card title="edit - File Edit" icon="pen-to-square" href="/tools/edit">
+    Edit files via precise text replacement
+  </Card>
+  <Card title="ls - Directory List" icon="folder-open" href="/tools/ls">
+    List directory contents
+  </Card>
+  <Card title="bash - Terminal" icon="terminal" href="/tools/bash">
+    Execute system commands
+  </Card>
+  <Card title="send - File Send" icon="paper-plane" href="/tools/send">
+    Send files or images to user
+  </Card>
+  <Card title="memory - Memory" icon="brain" href="/tools/memory">
+    Search and read long-term memory
+  </Card>
+</CardGroup>
+
+## Optional Tools
+
+The following tools require additional dependencies or API key configuration:
+
+<CardGroup cols={2}>
+  <Card title="env_config - Environment" icon="key" href="/tools/env-config">
+    Manage API keys and secrets
+  </Card>
+  <Card title="scheduler - Scheduler" icon="clock" href="/tools/scheduler">
+    Create and manage scheduled tasks
+  </Card>
+  <Card title="web_search - Web Search" icon="magnifying-glass" href="/tools/web-search">
+    Search the internet for real-time information
+  </Card>
+</CardGroup>
+
+## MCP Tools
+
+Integrate thousands of community tools (maps, GitHub, Notion, etc.) via the [Model Context Protocol](https://modelcontextprotocol.io). Configure `mcp.json` once, ready to use:
+
+<CardGroup cols={1}>
+  <Card title="MCP - External Tool Ecosystem" icon="plug" href="/tools/mcp">
+    Supports standard stdio / SSE transports. Hot-reload, zero code changes.
+  </Card>
+</CardGroup>
diff --git a/docs/tools/ls.mdx b/docs/tools/ls.mdx
new file mode 100644
index 0000000..e9a5f65
--- /dev/null
+++ b/docs/tools/ls.mdx
@@ -0,0 +1,23 @@
+---
+title: ls - Directory List
+description: List directory contents
+---
+
+List directory contents, sorted alphabetically, directories suffixed with `/`, includes hidden files.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | Directory path, relative paths are based on workspace directory |
+| `limit` | integer | No | Maximum entries to return, default 500 |
+
+## Use Cases
+
+- Browse project structure
+- Find specific files
+- Check if a directory exists
diff --git a/docs/tools/mcp.mdx b/docs/tools/mcp.mdx
new file mode 100644
index 0000000..6c3e0ec
--- /dev/null
+++ b/docs/tools/mcp.mdx
@@ -0,0 +1,134 @@
+---
+title: MCP Tools
+description: Integrate external tool ecosystems via the Model Context Protocol
+---
+
+CowAgent supports the [Model Context Protocol (MCP)](https://modelcontextprotocol.io), allowing the Agent to directly invoke tens of thousands of community MCP tools. Configure `mcp.json` once and the tools are exposed to the LLM in exactly the same way as built-in tools — automatically selected and invoked.
+
+## Configuration File
+
+CowAgent reads `~/cow/mcp.json`. If the file does not exist, no MCP tools are loaded — and no error is raised.
+
+For Docker deployments, the official `docker-compose.yml` already mounts the host's `./cow` directory to `/home/agent/cow` inside the container (i.e. the container user's `~/cow`). Just drop `mcp.json` into the host's `./cow/` directory and it will take effect.
+
+### Standard Format
+
+Fully compatible with the MCP community standard, identical to Claude Desktop / Cursor:
+
+```json
+{
+  "mcpServers": {
+    "<server-name>": {
+      "command": "npx",
+      "args": ["-y", "some-mcp-package"],
+      "env": {
+        "API_KEY": "your-key-here"
+      }
+    }
+  }
+}
+```
+
+| Field | Required | Description |
+| --- | --- | --- |
+| `command` | stdio | Executable to launch the server (e.g. `npx`, `python`, `uvx`) |
+| `args` | No | Arguments passed to `command` |
+| `env` | No | Environment variables for the subprocess, commonly used for API keys |
+| `url` | SSE / Streamable HTTP | Remote endpoint URL (alternative to `command`) |
+| `type` | Remote | Remote transport type: `sse` or `streamable-http` (defaults to `sse`) |
+| `headers` | No | Extra HTTP headers for remote requests (e.g. `Authorization`); Streamable HTTP only |
+| `scope` | No | OAuth scope, only for remote servers that require OAuth authorization (optional) |
+| `disabled` | No | When `true`, this server is skipped — handy for temporary disabling |
+
+### Full Example
+
+```json
+{
+  "mcpServers": {
+    "fetch": {
+      "command": "uvx",
+      "args": ["mcp-server-fetch"]
+    },
+    "github": {
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-github"],
+      "env": {
+        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
+      }
+    }
+  }
+}
+```
+
+- **fetch**: Generic web page fetcher that returns page text content. No API key required.
+- **github**: Access GitHub repos, issues, PRs, etc. Requires a Personal Access Token.
+
+## Let the Agent Configure It for You
+
+CowAgent ships with `read` / `write` / `edit` tools, so **you can simply send the MCP config to the Agent and ask it to write the file**:
+
+For example:
+
+```markdown
+Add this MCP to ~/cow/mcp.json:
+
+{"mcpServers":{"fetch":{"command":"uvx","args":["mcp-server-fetch"]}}}
+```
+
+The Agent will:
+
+1. Read the existing MCP config and merge the new server entry, preserving existing ones
+2. Hot-reload the new MCP server, so the corresponding tools become available on the next message
+
+## Web Authorization (OAuth)
+
+Some remote MCP servers require OAuth web authorization, and connecting to them directly returns `401`. CowAgent has a built-in standard OAuth flow, so **no manual token is needed** — just configure the server normally, for example:
+
+```json
+{
+  "mcpServers": {
+    "xmind": {
+      "type": "streamable-http",
+      "url": "https://app.xmind.com/api/mcp"
+    }
+  }
+}
+```
+
+When a server returns `401` on its first load, authorization starts automatically: running locally **opens the browser automatically**, while server deployments **print the authorization link to the log** for you to open in a browser. Once you approve, the server comes online immediately; tokens are refreshed automatically on expiry, so you never have to re-authorize.
+
+- **Requires the web service**: The authorization callback is received by the web console (default port `9899`), so the Web channel must be running.
+- **Credential storage**: Tokens are persisted in `~/.cow/mcp_oauth.json` and reused across restarts.
+- **Callback URL**: Defaults to `http://127.0.0.1:9899/mcp/oauth/callback`. If deployed on a server with the authorizing browser on another device, set `mcp_oauth_redirect_base` in `config.json` (e.g. `http://YOUR_IP:9899`).
+
+## How It Works
+
+- **Async loading at startup**: All servers configured in `mcp.json` are loaded asynchronously in the background, never blocking the main loop — chat is usable immediately.
+- **Hot reload**: When you or the Agent modifies `mcp.json`, changed servers are automatically reloaded after the current message — no need to restart cow.
+- **Flat exposure**: Each method exposed by an MCP server appears as an individual tool. The LLM picks one directly without a second-stage decision.
+
+## Supported Transports
+
+| Transport | Description | Config Field |
+| --- | --- | --- |
+| **stdio** | Subprocess communication. The most common option, with the richest community ecosystem. | `command` + `args` |
+| **SSE** | HTTP Server-Sent Events. Legacy remote transport. | `url` (default) |
+| **Streamable HTTP** | New unified remote transport, gradually replacing SSE. | `type: "streamable-http"` + `url` |
+
+## Troubleshooting
+
+| Symptom | What to Check |
+| --- | --- |
+| Agent has no MCP tools after startup | Verify that `~/cow/mcp.json` exists and contains valid JSON |
+| A specific server fails to load | Look for `[MCP] Server 'xxx' load failed` in startup logs — usually missing dependencies or API keys |
+| Changes to `mcp.json` aren't applied | Changes take effect on **the next message**. If the server config didn't actually change (e.g. only comments edited), no restart is triggered |
+| Docker deployment | Make sure host's `./cow` is mounted to `/home/agent/cow` in the container, then just drop `mcp.json` into host's `./cow/`. Or just ask the Agent to do it |
+
+## Recommended MCP Marketplaces
+
+You can browse third-party MCP marketplaces and copy a JSON config to use directly, for example:
+
+- [mcp.so](https://mcp.so) — Global MCP service index
+- [ModelScope MCP Hub](https://modelscope.cn/mcp) — ModelScope's MCP hub, more reliable from mainland China
+
+Any MCP server that follows the standard protocol (stdio / SSE / Streamable HTTP) integrates with CowAgent out of the box.
diff --git a/docs/tools/memory.mdx b/docs/tools/memory.mdx
new file mode 100644
index 0000000..d272bf9
--- /dev/null
+++ b/docs/tools/memory.mdx
@@ -0,0 +1,43 @@
+---
+title: memory - Memory & Knowledge
+description: Search and read long-term memory and knowledge base files
+---
+
+The memory tool contains two sub-tools: `memory_search` (search memory) and `memory_get` (read memory or knowledge files).
+
+When the [knowledge base](/knowledge) feature is enabled, both tools also support accessing files under the `knowledge/` directory.
+
+## Dependencies
+
+No extra dependencies, available by default. Managed by the Agent Core memory system.
+
+## memory_search
+
+Search historical memory and knowledge base content with hybrid keyword and vector retrieval.
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `query` | string | Yes | Search query |
+
+## memory_get
+
+Read the content of a specific memory or knowledge file.
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | Relative path to the file (e.g. `MEMORY.md`, `memory/2026-01-01.md`, `knowledge/concepts/rag.md`) |
+| `start_line` | integer | No | Start line number |
+| `end_line` | integer | No | End line number |
+
+## How It Works
+
+The Agent automatically invokes memory tools in these scenarios:
+
+- When the user shares important information → stores to memory
+- When historical context is needed → searches relevant memory
+- When conversation reaches a certain length → extracts summary for storage
+- When discussing domain knowledge → retrieves relevant pages from the knowledge base
+
+<Note>
+  When `knowledge` is set to `false` in config, the tool descriptions and search scope automatically adjust to include only memory files.
+</Note>
diff --git a/docs/tools/read.mdx b/docs/tools/read.mdx
new file mode 100644
index 0000000..56b5657
--- /dev/null
+++ b/docs/tools/read.mdx
@@ -0,0 +1,24 @@
+---
+title: read - File Read
+description: Read file content
+---
+
+Read file content. Supports text files, PDF files, images (returns metadata), and more.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | File path, relative paths are based on workspace directory |
+| `offset` | integer | No | Start line number (1-indexed), negative values read from the end |
+| `limit` | integer | No | Number of lines to read |
+
+## Use Cases
+
+- View configuration files, log files
+- Read code files for analysis
+- Check image/video file info
diff --git a/docs/tools/scheduler.mdx b/docs/tools/scheduler.mdx
new file mode 100644
index 0000000..18c211b
--- /dev/null
+++ b/docs/tools/scheduler.mdx
@@ -0,0 +1,80 @@
+---
+title: scheduler - Scheduler
+description: Create and manage scheduled tasks
+---
+
+Create and manage dynamic scheduled tasks with flexible scheduling and execution modes.
+
+## Dependencies
+
+| Dependency | Install Command |
+| --- | --- |
+| `croniter` ≥ 2.0.0 | `pip install croniter>=2.0.0` |
+
+Included in core dependencies: `pip3 install -r requirements.txt`
+
+## Scheduling Modes
+
+| Mode | Description |
+| --- | --- |
+| One-time | Execute once at a specified time |
+| Fixed interval | Repeat at fixed time intervals |
+| Cron expression | Define complex schedules using Cron syntax |
+
+## Execution Modes
+
+- **Fixed message**: Send a preset message when triggered
+- **Agent dynamic task**: Agent intelligently executes the task when triggered
+
+## Usage
+
+Create and manage scheduled tasks with natural language:
+
+- "Send me a weather report every morning at 9 AM"
+- "Check server status every 2 hours"
+- "Remind me about the meeting tomorrow at 3 PM"
+- "Show all scheduled tasks"
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+## Results injected into the conversation
+
+Scheduled tasks run inside an isolated session (so internal planning and tool calls do not pollute the user's chat), but the **final output** is written back to the user's real session as a message pair. You can directly follow up — e.g. "expand on point 2 from earlier".
+
+**Default policy**
+
+- Output of Agent dynamic tasks is injected into the conversation
+- Fixed-message tasks are not injected by default (configurable)
+- Each session keeps the most recent **3 pairs** of scheduler messages; older pairs are pruned automatically. Regular user messages are unaffected
+
+**Configuration**
+
+| Key | Default | Description |
+| --- | --- | --- |
+| `scheduler_inject_to_session` | `true` | Master switch |
+| `scheduler_inject_max_per_session` | `3` | Max scheduler message pairs kept per session |
+| `scheduler_inject_send_message` | `false` | Whether to also inject fixed-message tasks |
+
+```json
+{
+  "scheduler_inject_to_session": true,
+  "scheduler_inject_max_per_session": 3,
+  "scheduler_inject_send_message": false
+}
+```
+
+## Context inside scheduled task execution
+
+The isolated session for scheduled tasks retains a few recent runs of conversation history, so you can naturally do "compare with last time" or "continue from previous conclusion". To prevent prompts from growing unbounded for high-frequency tasks (e.g. a 5-minute monitor), history is auto-trimmed:
+
+```
+scheduler_keep_turns = max(1, agent_max_context_turns / 5)
+```
+
+`agent_max_context_turns` defaults to `20`, so each scheduled run keeps the most recent **4 turns** of history by default. Increase `agent_max_context_turns` if you need longer memory.
+
+<Note>
+For group-chat scenarios (Feishu / WeCom group bots / DingTalk, etc.), the user's real `session_id` looks like `user_id:group_id` — different from `receiver`. Scheduler records the correct `session_id` when a task is created. For older `tasks.json` entries missing this field, the runtime falls back to `receiver`, matching legacy behavior.
+</Note>
diff --git a/docs/tools/send.mdx b/docs/tools/send.mdx
new file mode 100644
index 0000000..1cf089a
--- /dev/null
+++ b/docs/tools/send.mdx
@@ -0,0 +1,23 @@
+---
+title: send - File Send
+description: Send files to user
+---
+
+Send files to the user (images, videos, audio, documents, etc.), used when the user explicitly requests to send/share a file.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | File path, can be absolute or relative to workspace |
+| `message` | string | No | Accompanying message |
+
+## Use Cases
+
+- Send generated code or documents to the user
+- Send screenshots, charts
+- Share downloaded files
diff --git a/docs/tools/vision.mdx b/docs/tools/vision.mdx
new file mode 100644
index 0000000..402cd02
--- /dev/null
+++ b/docs/tools/vision.mdx
@@ -0,0 +1,75 @@
+---
+title: vision - Image Understanding
+description: Analyze image content (recognition, description, OCR, etc.)
+---
+
+Analyze local images or image URLs using Vision API. Supports content description, text extraction (OCR), object recognition, and more.
+
+## Model Selection
+
+The vision tool uses a multi-level auto-selection strategy with automatic fallback — no manual configuration required:
+
+1. **Main model** — uses the currently configured main model for image recognition (must be a multimodal model)
+2. **Other configured models** — auto-discovers other multimodal models with configured API keys as alternatives
+
+If the current provider fails, the tool automatically tries the next one until it succeeds or all fail.
+
+### Supported Models
+
+| Provider | Vision Model | Notes |
+| --- | --- | --- |
+| OpenAI / Compatible | Main model | All OpenAI-protocol-compatible multimodal models |
+| Qwen (DashScope) | Main model | e.g. qwen3.7-plus, etc. |
+| Claude | Main model | Anthropic native image format |
+| Gemini | Main model | inlineData format |
+| Doubao | Main model | doubao-seed-2-1 series natively supported |
+| Kimi (Moonshot) | Main model | kimi-k2.6, kimi-k2.5 natively supported |
+| ERNIE | Main model | Defaults to the multimodal main model (e.g. `ernie-5.1`); falls back to `ernie-4.5-turbo-vl` when the main model is not multimodal |
+| ZhipuAI | glm-5v-turbo | Always uses the dedicated vision model |
+| MiniMax | MiniMax-Text-01 | Always uses the dedicated vision model |
+
+<Note>
+  ZhipuAI and MiniMax text models do not support image understanding, so their dedicated vision models are always used automatically.
+</Note>
+
+> When `use_linkai=true`, LinkAI's multimodal model is used by default.
+
+## Custom Configuration
+
+To specify the model used by Vision, configure it in `config.json`, for example:
+
+```json
+{
+    "tools": {
+        "vision": {
+            "model": "gpt-4.1"
+        }
+    }
+}
+```
+
+The specified model is **used first**, and the tool automatically routes to the corresponding provider based on the model name; on failure, it falls back to other configured providers.
+
+In most cases no configuration is needed — the tool works automatically as long as the main model supports multimodal input or any vision-capable API key is configured.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `image` | string | Yes | Local file path or HTTP(S) image URL |
+| `question` | string | Yes | Question to ask about the image |
+
+Supported image formats: jpg, jpeg, png, gif, webp
+
+
+
+## Use Cases
+
+- Describe image content
+- Extract text from images (OCR)
+- Identify objects, colors, scenes
+- Analyze screenshots and scanned documents
+
+<Note>
+  Images larger than 1MB are automatically compressed before upload. All images (including remote URLs) are converted to base64 for transmission to ensure compatibility with all model backends.
+</Note>
diff --git a/docs/tools/web-fetch.mdx b/docs/tools/web-fetch.mdx
new file mode 100644
index 0000000..0a0349b
--- /dev/null
+++ b/docs/tools/web-fetch.mdx
@@ -0,0 +1,32 @@
+---
+title: web_fetch - Web Fetch
+description: Fetch web pages and document content
+---
+
+Fetch the content of an HTTP/HTTPS URL. Web pages are extracted as readable text; document files (PDF, Word, Excel, etc.) are downloaded and parsed automatically.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `url` | string | Yes | HTTP/HTTPS URL (web page or document) |
+
+## Supported file types
+
+| Type | Formats |
+| --- | --- |
+| PDF | `.pdf` |
+| Word | `.docx` |
+| Text | `.txt`, `.md`, `.csv`, `.log` |
+| Spreadsheet | `.xls`, `.xlsx` |
+| Presentation | `.ppt`, `.pptx` |
+
+## Use cases
+
+- Extract readable text from a web page
+- Download and parse remote documents
+- Inspect API response bodies
+
+<Note>
+  `web_fetch` only retrieves static HTML. For pages that require JavaScript rendering (such as SPAs), use the `browser` tool instead.
+</Note>
diff --git a/docs/tools/web-search.mdx b/docs/tools/web-search.mdx
new file mode 100644
index 0000000..09dff68
--- /dev/null
+++ b/docs/tools/web-search.mdx
@@ -0,0 +1,51 @@
+---
+title: web_search - Web Search
+description: Search the internet for real-time information, with support for multiple search providers
+---
+
+Search the internet for real-time information, news, research, and more. Supports four backends — Bocha, ERNIE, GLM, and LinkAI — and works once any one of them is configured.
+
+<Tip>
+  It is recommended to configure providers and routing strategy visually from the "Model Management → Search" panel in the [Web console](/channels/web), without manually editing the configuration file.
+</Tip>
+
+## Providers
+
+| Provider | Credential | Apply |
+| --- | --- | --- |
+| Bocha | `tools.web_search.bocha_api_key` | [Bocha Open Platform](https://open.bochaai.com/) |
+| ERNIE | Reuses `qianfan_api_key` | [Qianfan Console](https://cloud.baidu.com/doc/qianfan/s/2mh4su4uy) |
+| Zhipu | Reuses `zhipu_ai_api_key` | [Zhipu Open Platform](https://docs.bigmodel.cn/cn/guide/tools/web-search) |
+| LinkAI | Reuses `linkai_api_key` | [LinkAI Console](https://link-ai.tech/console/interface) |
+
+Except for Bocha which requires a dedicated `bocha_api_key`, the other three reuse the corresponding model's API key — configuring the model automatically grants search capability.
+
+## Routing Strategy
+
+```json
+{
+  "tools": {
+    "web_search": {
+      "strategy": "auto",
+      "provider": ""
+    }
+  }
+}
+```
+
+- `auto` (default): the Agent intelligently picks among configured providers and may call multiple providers in a single task to gather more comprehensive results; when none is specified, falls back through `bocha → qianfan → zhipu → linkai`.
+- `fixed`: always use the provider specified in `provider`; falls back to the auto order if that provider's credentials are missing.
+
+## Tool Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `query` | string | Yes | Search keywords |
+| `count` | integer | No | Number of results (1–50, default 10) |
+| `freshness` | string | No | Time range: `noLimit` (default), `oneDay`, `oneWeek`, `oneMonth`, `oneYear`, or date range like `2025-01-01..2025-02-01` |
+| `summary` | boolean | No | Whether to return page summaries (default false) |
+| `provider` | string | No | Available when multiple providers are configured under the `auto` strategy; used to switch provider for a single call |
+
+<Note>
+  If none of the four credentials are configured, this tool is not registered with the Agent.
+</Note>
diff --git a/docs/tools/write.mdx b/docs/tools/write.mdx
new file mode 100644
index 0000000..2c0a10f
--- /dev/null
+++ b/docs/tools/write.mdx
@@ -0,0 +1,27 @@
+---
+title: write - File Write
+description: Create or overwrite files
+---
+
+Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories.
+
+## Dependencies
+
+No extra dependencies, available by default.
+
+## Parameters
+
+| Parameter | Type | Required | Description |
+| --- | --- | --- | --- |
+| `path` | string | Yes | File path |
+| `content` | string | Yes | Content to write |
+
+## Use Cases
+
+- Create new code files or scripts
+- Generate configuration files
+- Save processing results
+
+<Note>
+  Single writes should not exceed 10KB. For large files, create a skeleton first, then use the edit tool to add content in chunks.
+</Note>
diff --git a/docs/zh/README-Hant.md b/docs/zh/README-Hant.md
new file mode 100644
index 0000000..7fe8553
--- /dev/null
+++ b/docs/zh/README-Hant.md
@@ -0,0 +1,291 @@
+<p align="center"><img src= "https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="420" /></p>
+
+<p align="center">
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent?cacheSeconds=3600" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-green.svg" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square&cacheSeconds=3600" alt="Stars"></a>
+  <a href="https://docs.cowagent.ai/zh"><img src="https://img.shields.io/badge/%E6%96%87%E6%A1%A3-cowagent.ai-blue?style=flat&logo=readthedocs&logoColor=white" alt="文件"></a>
+</p>
+
+<p align="center">
+  <a href="https://trendshift.io/repositories/25763" target="_blank"><img src="https://trendshift.io/api/badge/repositories/25763" alt="zhayujie%2FCowAgent | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
+<p align="center">
+[<a href="../../README.md">English</a>] | [<a href="README.md">中文</a>] | [繁體中文] | [<a href="../ja/README.md">日本語</a>]
+</p>
+
+**CowAgent** 是一個開源的超級 AI 助理，能夠主動思考和規劃任務、操作電腦和外部資源、創造和執行 Skills、構建知識庫與長期記憶、透過自主進化與你一同成長，是 Agent Harness 工程的最佳實踐之一。
+
+CowAgent 輕量、易部署、可擴充，自由接入主流大模型，覆蓋微信、飛書、釘釘、企微、QQ、Telegram、Slack、網頁等多渠道，7×24 執行於個人電腦或伺服器中。
+
+<p align="center">
+  <a href="https://cowagent.ai/?lang=zh">🌐 官網</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/zh/">📖 文件中心</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/zh/guide/quick-start">🚀 快速開始</a> &nbsp;·&nbsp;
+  <a href="https://skills.cowagent.ai/">🧩 技能廣場</a> &nbsp;·&nbsp;
+  <a href="https://cowagent.ai/zh/download/">💻 下載客戶端</a> &nbsp;·&nbsp;
+  <a href="https://link-ai.tech/cowagent/create">☁️ 線上體驗</a>
+</p>
+
+<br/>
+
+## 🌟 核心能力
+
+| 能力 | 說明 |
+| :--- | :--- |
+| [任務規劃](https://docs.cowagent.ai/zh/intro/architecture) | 理解複雜任務並自主分解執行，迴圈呼叫工具直到完成目標 |
+| [長期記憶](https://docs.cowagent.ai/zh/memory) | 三層記憶架構（上下文 → 天級 → 核心），夢境蒸餾自動整理，支援關鍵詞與向量混合檢索 |
+| [知識庫](https://docs.cowagent.ai/zh/knowledge) | 自動整理結構化知識為 Markdown Wiki，構建持續增長的知識圖譜，視覺化瀏覽 |
+| [自主進化](https://docs.cowagent.ai/zh/memory/self-evolution) | 自動覆盤對話，最佳化技能、處理未完成事項、沉澱記憶與知識，在使用中持續成長 |
+| [技能](https://docs.cowagent.ai/zh/skills) | 從 [Skill Hub](https://skills.cowagent.ai/)、GitHub、ClawHub 等一鍵安裝；也可透過對話創造自定義技能 |
+| [工具](https://docs.cowagent.ai/zh/tools) | 內建檔案讀寫、終端、瀏覽器、定時任務、記憶檢索、聯網搜尋等 10+ 工具，支援 MCP 協議 |
+| [通道](https://docs.cowagent.ai/zh/channels) | 一個 Agent 同時接入 Web、微信、飛書、釘釘、企微、QQ、公眾號、Telegram、Slack 等多個渠道 |
+| 多模態 | 文字、圖片、語音、檔案全訊息型別支援，覆蓋識別、生成、收發 |
+| [模型](https://docs.cowagent.ai/zh/models) | DeepSeek、Claude、Gemini、GPT、GLM、Qwen、Kimi、MiniMax、Doubao 等主流廠商，設定一行切換 |
+| [部署](https://docs.cowagent.ai/zh/guide/quick-start) | 一鍵指令碼安裝，Web 控制台統一管理；本地、Docker、伺服器多種部署方式 |
+
+<br/>
+
+## 🏗️ 架構總覽
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/zh/architecture.jpg" alt="CowAgent Architecture" width="750"/>
+
+CowAgent 是一個完整的 **Agent Harness**：訊息從各類**通道**進入，**Agent Core** 結合記憶、知識庫與可用工具/技能進行任務規劃與決策，呼叫**模型**生成結果，再回傳至原通道。各模組解耦清晰，按需擴充。
+
+詳見 [專案架構](https://docs.cowagent.ai/zh/intro/architecture)。
+
+<br/>
+
+## 🚀 快速開始
+
+專案提供一鍵安裝指令碼，自動完成依賴安裝、設定和啟動：
+
+**Linux / macOS：**
+
+```bash
+bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+```
+
+**Windows（PowerShell）：**
+
+```powershell
+irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+```
+
+**Docker：**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+docker compose up -d
+```
+
+啟動成功後開啟 `http://localhost:9899` 進入 **Web 控制台**，在控制台內即可完成模型設定、渠道接入、技能安裝等全部操作。
+
+> 伺服器部署且需要從外部網路存取控制台時，請在 `config.json` 中將 `web_host` 設為 `0.0.0.0`（同時強烈建議設定 `web_password` 啟用身分驗證），然後訪問 `http://<server-ip>:9899`，並確保防火牆/安全組放行 `9899` 埠。
+
+> 📖 詳細安裝指南：[快速開始](https://docs.cowagent.ai/zh/guide/quick-start) · [原始碼安裝](https://docs.cowagent.ai/zh/guide/manual-install) · [升級](https://docs.cowagent.ai/zh/guide/upgrade)
+
+安裝後可使用 `cow` [CLI 命令](https://docs.cowagent.ai/zh/cli) 管理服務：
+
+```bash
+cow start | stop | restart        # 服務管理
+cow status | logs                  # 狀態和日誌
+cow update                         # 拉取最新程式碼並重啟
+cow skill install <名稱>           # 安裝技能
+cow install-browser                # 安裝瀏覽器工具
+```
+
+> 💻 桌面客戶端：前往 **[下載 CowAgent 桌面客戶端](https://cowagent.ai/zh/download/)**（macOS / Windows），內建 Agent 執行環境，開箱即用。
+
+<br/>
+
+## 🤖 模型支援
+
+CowAgent 支援國內外主流廠商的大語言模型。**文字對話、影像理解、影像生成、語音識別/合成、向量** 等能力均可獨立設定廠商。
+
+| 廠商 | 代表模型 | 文字 | 影像理解 | 影像生成 | 語音識別 | 語音合成 | 向量 |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [DeepSeek](https://docs.cowagent.ai/zh/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [MiniMax](https://docs.cowagent.ai/zh/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [Claude](https://docs.cowagent.ai/zh/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [Gemini](https://docs.cowagent.ai/zh/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [OpenAI](https://docs.cowagent.ai/zh/models/openai) | gpt-5.5、o 系列 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [智譜 GLM](https://docs.cowagent.ai/zh/models/glm) | glm-5.2、glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [通義千問](https://docs.cowagent.ai/zh/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [豆包 Doubao](https://docs.cowagent.ai/zh/models/doubao) | doubao-seed-2.1 系列 | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](https://docs.cowagent.ai/zh/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [百度ERNIE](https://docs.cowagent.ai/zh/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [小米 MiMo](https://docs.cowagent.ai/zh/models/mimo) | mimo-v2.5-pro / v2.5 | ✅ | ✅ | | | ✅ | |
+| [LinkAI](https://docs.cowagent.ai/zh/models/linkai) | 一個 Key 接入 100+ 模型 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [自定義](https://docs.cowagent.ai/zh/models/custom) | 本地模型 / 三方代理 | ✅ | | | | | |
+
+> 推薦透過 Web 控制台線上設定，無需手動編輯檔案。手動設定請參考各廠商文件，詳見 [模型概覽](https://docs.cowagent.ai/zh/models)。
+
+<br/>
+
+## 💬 通道接入
+
+一個 Agent 例項可同時接入多個渠道，啟動時透過 `channel_type` 切換或並行執行。
+
+| 通道 | 文字 | 圖片 | 檔案 | 語音 | 群聊 |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [Web 控制台](https://docs.cowagent.ai/zh/channels/web)（預設） | ✅ | ✅ | ✅ | ✅ | |
+| [微信](https://docs.cowagent.ai/zh/channels/weixin) | ✅ | ✅ | ✅ | ✅ | |
+| [飛書](https://docs.cowagent.ai/zh/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [釘釘](https://docs.cowagent.ai/zh/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [企微智慧機器人](https://docs.cowagent.ai/zh/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](https://docs.cowagent.ai/zh/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [企業微信應用](https://docs.cowagent.ai/zh/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [微信客服](https://docs.cowagent.ai/zh/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [微信公眾號](https://docs.cowagent.ai/zh/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [Telegram](https://docs.cowagent.ai/zh/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](https://docs.cowagent.ai/zh/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](https://docs.cowagent.ai/zh/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+
+> 飛書、企微智慧機器人支援在 Web 控制台內**掃碼一鍵接入**，無需公有 IP。詳見 [通道概覽](https://docs.cowagent.ai/zh/channels)。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-chat.png" alt="CowAgent Web 控制台" width="800"/>
+
+*Web 控制台是預設通道，也是統一的 Agent 設定和管理入口*
+
+<br/>
+
+## 🧠 記憶與知識庫
+
+**長期記憶**採用三層架構：對話上下文（短期）→ 天級記憶（中期）→ MEMORY.md（長期）。每日自動執行**夢境蒸餾（Deep Dream）**，將分散記憶整合為精煉的長期記憶並生成敘事日記。詳見 [長期記憶](https://docs.cowagent.ai/zh/memory) · [夢境蒸餾](https://docs.cowagent.ai/zh/memory/deep-dream)。
+
+**個人知識庫** 與按時間記錄的記憶不同，以**主題為維度**組織結構化知識。Agent 在對話中自動整理有價值資訊，維護交叉引用與索引，Web 控制台可視覺化瀏覽知識圖譜。詳見 [個人知識庫](https://docs.cowagent.ai/zh/knowledge)。
+
+<table>
+  <tr>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-memory.png" alt="長期記憶" />
+      <p align="center"><em>長期記憶 · 三層記憶 + 夢境蒸餾</em></p>
+    </td>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-knowledge.png" alt="個人知識庫" />
+      <p align="center"><em>個人知識庫 · 自動整理的 Markdown Wiki</em></p>
+    </td>
+  </tr>
+</table>
+
+<br/>
+
+
+## 🔧 工具與技能
+
+**工具（Tools）** 是 Agent 作業系統資源的原子能力，**技能（Skills）** 是基於說明檔案的高階工作流，可組合多個工具完成複雜任務。
+
+### 工具系統
+
+**內建工具** 涵蓋檔案讀寫（`read` / `write` / `edit` / `ls`）、終端（`bash`）、檔案傳送（`send`）、記憶檢索（`memory`）、環境變數（`env_config`）、網頁獲取（`web_fetch`）、定時任務（`scheduler`）、聯網搜尋（`web_search`）、影像識別（`vision`）、瀏覽器自動化（`browser`）等常用能力。
+
+**MCP 協議** 透過 [Model Context Protocol](https://modelcontextprotocol.io) 接入開放生態中的各種 MCP 服務，設定一次 `mcp.json` 即用即得，支援 stdio / SSE 協議、熱更新、零程式碼接入。
+
+詳見 [工具概覽](https://docs.cowagent.ai/zh/tools) · [MCP 整合](https://docs.cowagent.ai/zh/tools/mcp)。
+
+### 技能系統
+
+- **[Skill Hub](https://skills.cowagent.ai/)** — 開源的技能廣場，瀏覽、搜尋、一鍵安裝
+- **GitHub / ClawHub / URL 等** — 任意來源一鍵安裝
+- **對話創造** — 透過 `skill-creator` 用對話快速生成自定義技能，可將工作流程或第三方介面直接固化為技能
+
+```bash
+/skill list                   # 檢視當前技能
+/skill search <關鍵詞>         # 在技能廣場搜尋
+/skill install <名稱>          # 一鍵安裝
+```
+
+詳見 [技能概覽](https://docs.cowagent.ai/zh/skills) · [建立技能](https://docs.cowagent.ai/zh/skills/create)。
+
+<br/>
+
+## 🏷 更新日誌
+
+> **2026.07.08：** [v2.1.3](https://github.com/zhayujie/CowAgent/releases/tag/2.1.3) — [桌面客戶端](https://cowagent.ai/zh/download/)正式發布（macOS / Windows）、知識庫文件管理增強、MCP 工具智能檢索、繁體中文支援、新模型接入
+
+> **2026.06.18：** [v2.1.2](https://github.com/zhayujie/CowAgent/releases/tag/2.1.2) — Web 控制台升級（定時任務管理、知識庫分類、多模型自定義廠商）、自主進化最佳化、新模型接入（kimi-k2.7-code、glm-5.2）、安全加固和體驗最佳化
+
+> **2026.06.09：** [v2.1.1](https://github.com/zhayujie/CowAgent/releases/tag/2.1.1) — 自進化能力、Web 控制台升級（訊息管理、多會話並行）、新模型接入（MiniMax-M3、qwen3.7-plus）、Python 3.13 支援
+
+> **2026.06.01：** [v2.1.0](https://github.com/zhayujie/CowAgent/releases/tag/2.1.0) — 國際化支援、新增通道（Telegram、Discord、Slack、微信客服）、命令列互動升級、一鍵安裝指令碼最佳化、MCP Streamable HTTP 支援、新模型接入（claude-opus-4-8、MiMo）
+
+> **2026.05.22：** [v2.0.9](https://github.com/zhayujie/CowAgent/releases/tag/2.0.9) — 模型管理、MCP 協議支援、瀏覽器登入態持久化、新模型接入（gpt-5.5、gemini-3.5-flash、qwen3.7-max）、部署安全加固
+
+> **2026.05.06：** [v2.0.8](https://github.com/zhayujie/CowAgent/releases/tag/2.0.8) — 飛書渠道全面升級（語音、流式輸出、掃碼接入）、新模型支援（DeepSeek V4、百度千帆）、定時任務工具增強
+
+> **2026.04.22：** [v2.0.7](https://github.com/zhayujie/CowAgent/releases/tag/2.0.7) — 影像生成內建技能（GPT Image 2、Nano Banana）、新模型支援（Kimi K2.6、Claude Opus 4.7、GLM 5.1）、知識庫和記憶增強
+
+> **2026.04.14：** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — 知識庫系統、夢境記憶模組、上下文智慧壓縮、Web 控制台多會話
+
+> **2026.04.01：** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI 命令系統、Skill Hub 開源、瀏覽器工具、企微掃碼建立
+
+> **2026.03.22：** [v2.0.4](https://github.com/zhayujie/CowAgent/releases/tag/2.0.4) — 新增個人微信通道，支援文字/圖片/檔案/語音訊息
+
+> **2026.02.03：** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — 正式升級為超級 Agent 助理，支援多輪任務決策、長期記憶、Skills 框架
+
+完整更新歷史：[Release Notes](https://docs.cowagent.ai/zh/releases)
+
+<br/>
+
+## 🤝 社群與支援
+
+掃碼加入微信開源交流群：
+
+<img width="130" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png">
+
+也可透過以下方式獲取支援：
+
+- 🐛 [提交 Issue](https://github.com/zhayujie/CowAgent/issues)
+- 🤖 線上 AI 助手：[專案小助手](https://link-ai.tech/app/Kv2fXJcH)（基於專案知識庫）
+
+<br/>
+
+## 🔗 相關專案
+
+- **[Cow Skill Hub](https://github.com/zhayujie/cow-skill-hub)** — 開源的 AI Agent 技能廣場，支援 CowAgent、OpenClaw、Claude Code 等多種 Agent
+- **[bot-on-anything](https://github.com/zhayujie/bot-on-anything)** — 輕量大模型應用框架，支援 Slack、Telegram、Discord、Gmail 等海外平臺
+- **[AgentMesh](https://github.com/MinimalFuture/AgentMesh)** — 開源多智慧體（Multi-Agent）框架，透過團隊協同解決複雜問題
+
+<br/>
+
+## 🏢 企業服務
+
+<a href="https://link-ai.tech" target="_blank"><img width="650" src="https://cdn.link-ai.tech/image/link-ai-intro.jpg"></a>
+
+> [LinkAI](https://link-ai.tech/) 是面向企業和個人的一站式 AI 智慧體平臺，為 CowAgent 提供雲端託管和企業級支援：
+>
+> - **🚀 免部署線上執行**：無需伺服器即可建立 [CowAgent 線上助理](https://link-ai.tech/cowagent/create)，1 分鐘擁有專屬 Agent
+> - **🧠 Agent 基礎設施**：聚合主流大模型、知識庫、資料庫、技能、工作流，提供開箱即用的 Agent 能力擴充
+> - **🏢 企業級協作**：提供團隊協作、許可權分級、審計日誌、私有化部署等能力，讓 Agent 安全落地企業場景
+
+**產品諮詢和企業服務** 可聯絡產品客服：
+
+<img width="130" src="https://cdn.link-ai.tech/portal/linkai-customer-service.png">
+
+<br/>
+
+## 🛠️ 開發與貢獻
+
+歡迎各種形式的貢獻：新功能、Bug 修復、效能最佳化、文件完善，或向 [Skill Hub](https://skills.cowagent.ai/submit) 分享你的技能。請先閱讀 [CONTRIBUTING.md](/CONTRIBUTING.md) 瞭解如何開始，然後提交 Issue 討論或直接發起 PR。
+
+歡迎 ⭐ Star 支援專案，並透過 Watch → Custom → Releases 訂閱新版本通知。也歡迎提交 PR、Issue 進行反饋。
+
+## 🌟 貢獻者
+
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
+
+<br/>
+
+## ⚠️ 宣告
+
+1. 本專案遵循 [MIT 開源協議](/LICENSE)，主要用於技術研究和學習。使用時請遵守所在地法律法規及相關政策，因使用本專案所產生的一切後果由使用者自行承擔。
+2. **成本與安全：** Agent 模式 Token 消耗顯著高於普通對話，請根據效果與成本權衡選擇模型；Agent 具備訪問本地作業系統的能力，請謹慎選擇部署環境。
+3. CowAgent 專案專注於開源技術開發，不會參與、授權或發行任何加密貨幣。
+
+<br/>
+
+## 📌 專案更名說明
+
+本專案原名 `chatgpt-on-wechat`，於 2026.04.13 正式更名為 **CowAgent**。原 GitHub 地址已自動重定向，老使用者可選擇執行 `git remote set-url origin https://github.com/zhayujie/CowAgent.git` 更新本地遠端地址。
diff --git a/docs/zh/README.md b/docs/zh/README.md
new file mode 100644
index 0000000..7f3be54
--- /dev/null
+++ b/docs/zh/README.md
@@ -0,0 +1,291 @@
+<p align="center"><img src= "https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="420" /></p>
+
+<p align="center">
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent?cacheSeconds=3600" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-green.svg" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square&cacheSeconds=3600" alt="Stars"></a>
+  <a href="https://docs.cowagent.ai/zh"><img src="https://img.shields.io/badge/%E6%96%87%E6%A1%A3-cowagent.ai-blue?style=flat&logo=readthedocs&logoColor=white" alt="文档"></a>
+</p>
+
+<p align="center">
+  <a href="https://trendshift.io/repositories/25763" target="_blank"><img src="https://trendshift.io/api/badge/repositories/25763" alt="zhayujie%2FCowAgent | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</p>
+
+<p align="center">
+  [<a href="../../README.md">English</a>] | [中文] | [<a href="README-Hant.md">繁體中文</a>] | [<a href="../ja/README.md">日本語</a>]
+</p>
+
+**CowAgent** 是一个开源的超级 AI 助理，能够主动思考和规划任务、操作计算机和外部资源、创造和执行 Skills、构建知识库与长期记忆、通过自主进化与你一同成长，是 Agent Harness 工程的最佳实践之一。
+
+CowAgent 轻量、易部署、可扩展，自由接入主流大模型，覆盖微信、飞书、钉钉、企微、QQ、Telegram、Slack、网页等多渠道，7×24 运行于个人电脑或服务器中。
+
+<p align="center">
+  <a href="https://cowagent.ai/?lang=zh">🌐 官网</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/zh/">📖 文档中心</a> &nbsp;·&nbsp;
+  <a href="https://docs.cowagent.ai/zh/guide/quick-start">🚀 快速开始</a> &nbsp;·&nbsp;
+  <a href="https://skills.cowagent.ai/">🧩 技能广场</a> &nbsp;·&nbsp;
+  <a href="https://cowagent.ai/zh/download/">💻 下载客户端</a> &nbsp;·&nbsp;
+  <a href="https://link-ai.tech/cowagent/create">☁️ 在线体验</a>
+</p>
+
+<br/>
+
+## 🌟 核心能力
+
+| 能力 | 说明 |
+| :--- | :--- |
+| [任务规划](https://docs.cowagent.ai/zh/intro/architecture) | 理解复杂任务并自主分解执行，循环调用工具直到完成目标 |
+| [长期记忆](https://docs.cowagent.ai/zh/memory) | 三层记忆架构（上下文 → 天级 → 核心），梦境蒸馏自动整理，支持关键词与向量混合检索 |
+| [知识库](https://docs.cowagent.ai/zh/knowledge) | 自动整理结构化知识为 Markdown Wiki，构建持续增长的知识图谱，可视化浏览 |
+| [自主进化](https://docs.cowagent.ai/zh/memory/self-evolution) | 自动复盘对话，优化技能、处理未完成事项、沉淀记忆与知识，在使用中持续成长 |
+| [技能](https://docs.cowagent.ai/zh/skills) | 从 [Skill Hub](https://skills.cowagent.ai/)、GitHub、ClawHub 等一键安装；也可通过对话创造自定义技能 |
+| [工具](https://docs.cowagent.ai/zh/tools) | 内置文件读写、终端、浏览器、定时任务、记忆检索、联网搜索等 10+ 工具，支持 MCP 协议 |
+| [通道](https://docs.cowagent.ai/zh/channels) | 一个 Agent 同时接入 Web、微信、飞书、钉钉、企微、QQ、公众号、Telegram、Slack 等多个渠道 |
+| 多模态 | 文本、图片、语音、文件全消息类型支持，覆盖识别、生成、收发 |
+| [模型](https://docs.cowagent.ai/zh/models) | DeepSeek、Claude、Gemini、GPT、GLM、Qwen、Kimi、MiniMax、Doubao 等主流厂商，配置一行切换 |
+| [部署](https://docs.cowagent.ai/zh/guide/quick-start) | 一键脚本安装，Web 控制台统一管理；本地、Docker、服务器多种部署方式 |
+
+<br/>
+
+## 🏗️ 架构总览
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/zh/architecture.jpg" alt="CowAgent Architecture" width="750"/>
+
+CowAgent 是一个完整的 **Agent Harness**：消息从各类**通道**进入，**Agent Core** 结合记忆、知识库与可用工具/技能进行任务规划与决策，调用**模型**生成结果，再回传至原通道。各模块解耦清晰，按需扩展。
+
+详见 [项目架构](https://docs.cowagent.ai/zh/intro/architecture)。
+
+<br/>
+
+## 🚀 快速开始
+
+项目提供一键安装脚本，自动完成依赖安装、配置和启动：
+
+**Linux / macOS：**
+
+```bash
+bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+```
+
+**Windows（PowerShell）：**
+
+```powershell
+irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+```
+
+**Docker：**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+docker compose up -d
+```
+
+启动成功后访问 `http://localhost:9899` 进入 **Web 控制台**，在控制台内即可完成模型配置、渠道接入、技能安装等全部操作。
+
+> 服务器部署且需要公网访问控制台时，请在 `config.json` 中将 `web_host` 设为 `0.0.0.0`（同时强烈建议设置 `web_password` 启用鉴权），然后访问 `http://<server-ip>:9899`，并确保防火墙/安全组放行 `9899` 端口。
+
+> 📖 详细安装指南：[快速开始](https://docs.cowagent.ai/zh/guide/quick-start) · [源码安装](https://docs.cowagent.ai/zh/guide/manual-install) · [升级](https://docs.cowagent.ai/zh/guide/upgrade)
+
+安装后可使用 `cow` [CLI 命令](https://docs.cowagent.ai/zh/cli) 管理服务：
+
+```bash
+cow start | stop | restart        # 服务管理
+cow status | logs                  # 状态和日志
+cow update                         # 拉取最新代码并重启
+cow skill install <名称>           # 安装技能
+cow install-browser                # 安装浏览器工具
+```
+
+> 💻 桌面客户端：前往 **[下载 CowAgent 桌面客户端](https://cowagent.ai/zh/download/)**（macOS / Windows），内置 Agent 运行环境，开箱即用。
+
+<br/>
+
+## 🤖 模型支持
+
+CowAgent 支持国内外主流厂商的大语言模型。**文本对话、图像理解、图像生成、语音识别/合成、向量** 等能力均可独立配置厂商。
+
+| 厂商 | 代表模型 | 文本 | 图像理解 | 图像生成 | 语音识别 | 语音合成 | 向量 |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [DeepSeek](https://docs.cowagent.ai/zh/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [MiniMax](https://docs.cowagent.ai/zh/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [Claude](https://docs.cowagent.ai/zh/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [Gemini](https://docs.cowagent.ai/zh/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [OpenAI](https://docs.cowagent.ai/zh/models/openai) | gpt-5.5、o 系列 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [智谱 GLM](https://docs.cowagent.ai/zh/models/glm) | glm-5.2、glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [通义千问](https://docs.cowagent.ai/zh/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [豆包 Doubao](https://docs.cowagent.ai/zh/models/doubao) | doubao-seed-2.1 系列 | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](https://docs.cowagent.ai/zh/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [百度ERNIE](https://docs.cowagent.ai/zh/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [小米 MiMo](https://docs.cowagent.ai/zh/models/mimo) | mimo-v2.5-pro / v2.5 | ✅ | ✅ | | | ✅ | |
+| [LinkAI](https://docs.cowagent.ai/zh/models/linkai) | 一个 Key 接入 100+ 模型 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [自定义](https://docs.cowagent.ai/zh/models/custom) | 本地模型 / 三方代理 | ✅ | | | | | |
+
+> 推荐通过 Web 控制台在线配置，无需手动编辑文件。手动配置请参考各厂商文档，详见 [模型概览](https://docs.cowagent.ai/zh/models)。
+
+<br/>
+
+## 💬 通道接入
+
+一个 Agent 实例可同时接入多个渠道，启动时通过 `channel_type` 切换或并行运行。
+
+| 通道 | 文本 | 图片 | 文件 | 语音 | 群聊 |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [Web 控制台](https://docs.cowagent.ai/zh/channels/web)（默认） | ✅ | ✅ | ✅ | ✅ | |
+| [微信](https://docs.cowagent.ai/zh/channels/weixin) | ✅ | ✅ | ✅ | ✅ | |
+| [飞书](https://docs.cowagent.ai/zh/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [钉钉](https://docs.cowagent.ai/zh/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [企微智能机器人](https://docs.cowagent.ai/zh/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](https://docs.cowagent.ai/zh/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [企业微信应用](https://docs.cowagent.ai/zh/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [微信客服](https://docs.cowagent.ai/zh/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [微信公众号](https://docs.cowagent.ai/zh/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [Telegram](https://docs.cowagent.ai/zh/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](https://docs.cowagent.ai/zh/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](https://docs.cowagent.ai/zh/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+
+> 飞书、企微智能机器人支持在 Web 控制台内**扫码一键接入**，无需公网 IP。详见 [通道概览](https://docs.cowagent.ai/zh/channels)。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-chat.png" alt="CowAgent Web 控制台" width="800"/>
+
+*Web 控制台是默认通道，也是统一的 Agent 配置和管理入口*
+
+<br/>
+
+## 🧠 记忆与知识库
+
+**长期记忆**采用三层架构：对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期）。每日自动执行**梦境蒸馏（Deep Dream）**，将分散记忆整合为精炼的长期记忆并生成叙事日记。详见 [长期记忆](https://docs.cowagent.ai/zh/memory) · [梦境蒸馏](https://docs.cowagent.ai/zh/memory/deep-dream)。
+
+**个人知识库** 与按时间记录的记忆不同，以**主题为维度**组织结构化知识。Agent 在对话中自动整理有价值信息，维护交叉引用与索引，Web 控制台可可视化浏览知识图谱。详见 [个人知识库](https://docs.cowagent.ai/zh/knowledge)。
+
+<table>
+  <tr>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-memory.png" alt="长期记忆" />
+      <p align="center"><em>长期记忆 · 三层记忆 + 梦境蒸馏</em></p>
+    </td>
+    <td width="50%">
+      <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-knowledge.png" alt="个人知识库" />
+      <p align="center"><em>个人知识库 · 自动整理的 Markdown Wiki</em></p>
+    </td>
+  </tr>
+</table>
+
+<br/>
+
+
+## 🔧 工具与技能
+
+**工具（Tools）** 是 Agent 操作系统资源的原子能力，**技能（Skills）** 是基于说明文件的高级工作流，可组合多个工具完成复杂任务。
+
+### 工具系统
+
+**内置工具** 涵盖文件读写（`read` / `write` / `edit` / `ls`）、终端（`bash`）、文件发送（`send`）、记忆检索（`memory`）、环境变量（`env_config`）、网页获取（`web_fetch`）、定时任务（`scheduler`）、联网搜索（`web_search`）、图像识别（`vision`）、浏览器自动化（`browser`）等常用能力。
+
+**MCP 协议** 通过 [Model Context Protocol](https://modelcontextprotocol.io) 接入开放生态中的各种 MCP 服务，配置一次 `mcp.json` 即用即得，支持 stdio / SSE 协议、热更新、零代码接入。
+
+详见 [工具概览](https://docs.cowagent.ai/zh/tools) · [MCP 集成](https://docs.cowagent.ai/zh/tools/mcp)。
+
+### 技能系统
+
+- **[Skill Hub](https://skills.cowagent.ai/)** — 开源的技能广场，浏览、搜索、一键安装
+- **GitHub / ClawHub / URL 等** — 任意来源一键安装
+- **对话创造** — 通过 `skill-creator` 用对话快速生成自定义技能，可将工作流程或第三方接口直接固化为技能
+
+```bash
+/skill list                   # 查看当前技能
+/skill search <关键词>         # 在技能广场搜索
+/skill install <名称>          # 一键安装
+```
+
+详见 [技能概览](https://docs.cowagent.ai/zh/skills) · [创建技能](https://docs.cowagent.ai/zh/skills/create)。
+
+<br/>
+
+## 🏷 更新日志
+
+> **2026.07.08：** [v2.1.3](https://github.com/zhayujie/CowAgent/releases/tag/2.1.3) — [桌面客户端](https://cowagent.ai/zh/download/)正式发布（macOS / Windows）、知识库文档管理增强、MCP 工具智能检索、繁体中文支持、新模型接入
+
+> **2026.06.18：** [v2.1.2](https://github.com/zhayujie/CowAgent/releases/tag/2.1.2) — Web 控制台升级（定时任务管理、知识库分类、多模型自定义厂商）、自主进化优化、新模型接入（kimi-k2.7-code、glm-5.2）、安全加固和体验优化
+
+> **2026.06.09：** [v2.1.1](https://github.com/zhayujie/CowAgent/releases/tag/2.1.1) — 自进化能力、Web 控制台升级（消息管理、多会话并行）、新模型接入（MiniMax-M3、qwen3.7-plus）、Python 3.13 支持
+
+> **2026.06.01：** [v2.1.0](https://github.com/zhayujie/CowAgent/releases/tag/2.1.0) — 国际化支持、新增通道（Telegram、Discord、Slack、微信客服）、命令行交互升级、一键安装脚本优化、MCP Streamable HTTP 支持、新模型接入（claude-opus-4-8、MiMo）
+
+> **2026.05.22：** [v2.0.9](https://github.com/zhayujie/CowAgent/releases/tag/2.0.9) — 模型管理、MCP 协议支持、浏览器登录态持久化、新模型接入（gpt-5.5、gemini-3.5-flash、qwen3.7-max）、部署安全加固
+
+> **2026.05.06：** [v2.0.8](https://github.com/zhayujie/CowAgent/releases/tag/2.0.8) — 飞书渠道全面升级（语音、流式输出、扫码接入）、新模型支持（DeepSeek V4、百度千帆）、定时任务工具增强
+
+> **2026.04.22：** [v2.0.7](https://github.com/zhayujie/CowAgent/releases/tag/2.0.7) — 图像生成内置技能（GPT Image 2、Nano Banana）、新模型支持（Kimi K2.6、Claude Opus 4.7、GLM 5.1）、知识库和记忆增强
+
+> **2026.04.14：** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — 知识库系统、梦境记忆模块、上下文智能压缩、Web 控制台多会话
+
+> **2026.04.01：** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI 命令系统、Skill Hub 开源、浏览器工具、企微扫码创建
+
+> **2026.03.22：** [v2.0.4](https://github.com/zhayujie/CowAgent/releases/tag/2.0.4) — 新增个人微信通道，支持文本/图片/文件/语音消息
+
+> **2026.02.03：** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — 正式升级为超级 Agent 助理，支持多轮任务决策、长期记忆、Skills 框架
+
+完整更新历史：[Release Notes](https://docs.cowagent.ai/zh/releases)
+
+<br/>
+
+## 🤝 社区与支持
+
+扫码加入微信开源交流群：
+
+<img width="130" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png">
+
+也可通过以下方式获取支持：
+
+- 🐛 [提交 Issue](https://github.com/zhayujie/CowAgent/issues)
+- 🤖 在线 AI 助手：[项目小助手](https://link-ai.tech/app/Kv2fXJcH)（基于项目知识库）
+
+<br/>
+
+## 🔗 相关项目
+
+- **[Cow Skill Hub](https://github.com/zhayujie/cow-skill-hub)** — 开源的 AI Agent 技能广场，支持 CowAgent、OpenClaw、Claude Code 等多种 Agent
+- **[bot-on-anything](https://github.com/zhayujie/bot-on-anything)** — 轻量大模型应用框架，支持 Slack、Telegram、Discord、Gmail 等海外平台
+- **[AgentMesh](https://github.com/MinimalFuture/AgentMesh)** — 开源多智能体（Multi-Agent）框架，通过团队协同解决复杂问题
+
+<br/>
+
+## 🏢 企业服务
+
+<a href="https://link-ai.tech" target="_blank"><img width="650" src="https://cdn.link-ai.tech/image/link-ai-intro.jpg"></a>
+
+> [LinkAI](https://link-ai.tech/) 是面向企业和个人的一站式 AI 智能体平台，为 CowAgent 提供云端托管和企业级支持：
+>
+> - **🚀 免部署在线运行**：无需服务器即可创建 [CowAgent 在线助理](https://link-ai.tech/cowagent/create)，1 分钟拥有专属 Agent
+> - **🧠 Agent 基础设施**：聚合主流大模型、知识库、数据库、技能、工作流，提供开箱即用的 Agent 能力扩展
+> - **🏢 企业级协作**：提供团队协作、权限分级、审计日志、私有化部署等能力，让 Agent 安全落地企业场景
+
+**产品咨询和企业服务** 可联系产品客服：
+
+<img width="130" src="https://cdn.link-ai.tech/portal/linkai-customer-service.png">
+
+<br/>
+
+## 🛠️ 开发与贡献
+
+欢迎各种形式的贡献：新功能、Bug 修复、性能优化、文档完善，或向 [Skill Hub](https://skills.cowagent.ai/submit) 分享你的技能。请先阅读 [CONTRIBUTING.md](/CONTRIBUTING.md) 了解如何开始，然后提交 Issue 讨论或直接发起 PR。
+
+欢迎 ⭐ Star 支持项目，并通过 Watch → Custom → Releases 订阅新版本通知。也欢迎提交 PR、Issue 进行反馈。
+
+## 🌟 贡献者
+
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
+
+<br/>
+
+## ⚠️ 声明
+
+1. 本项目遵循 [MIT 开源协议](/LICENSE)，主要用于技术研究和学习。使用时请遵守所在地法律法规及相关政策，因使用本项目所产生的一切后果由使用者自行承担。
+2. **成本与安全：** Agent 模式 Token 消耗显著高于普通对话，请根据效果与成本权衡选择模型；Agent 具备访问本地操作系统的能力，请谨慎选择部署环境。
+3. CowAgent 项目专注于开源技术开发，不会参与、授权或发行任何加密货币。
+
+<br/>
+
+## 📌 项目更名说明
+
+本项目原名 `chatgpt-on-wechat`，于 2026.04.13 正式更名为 **CowAgent**。原 GitHub 地址已自动重定向，老用户可选择执行 `git remote set-url origin https://github.com/zhayujie/CowAgent.git` 更新本地远程地址。
diff --git a/docs/zh/channels/dingtalk.mdx b/docs/zh/channels/dingtalk.mdx
new file mode 100644
index 0000000..df11019
--- /dev/null
+++ b/docs/zh/channels/dingtalk.mdx
@@ -0,0 +1,56 @@
+---
+title: 钉钉
+description: 将 CowAgent 接入钉钉应用
+---
+
+通过钉钉开放平台创建智能机器人应用，将 CowAgent 接入钉钉。
+
+## 一、创建应用
+
+1. 进入 [钉钉开发者后台](https://open-dev.dingtalk.com/fe/app#/corp/app)，登录后点击 **创建应用**，填写应用相关信息：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-create-app.png" width="800"/>
+
+2. 点击添加应用能力，选择 **机器人** 能力，点击 **添加**：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-add-bot.png" width="800"/>
+
+3. 配置机器人信息后点击 **发布**。发布后，点击 "**点击调试**"，会自动创建测试群聊，可在客户端查看：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-config-bot.png" width="600"/>
+
+4. 点击 **版本管理与发布**，创建新版本发布：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-publish-bot.png" width="700"/>
+
+## 二、项目配置
+
+1. 点击 **凭证与基础信息**，获取 `Client ID` 和 `Client Secret`：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-get-secret.png" width="700"/>
+
+2. 将以下配置加入项目根目录的 `config.json` 文件：
+
+```json
+{
+  "channel_type": "dingtalk",
+  "dingtalk_client_id": "YOUR_CLIENT_ID",
+  "dingtalk_client_secret": "YOUR_CLIENT_SECRET"
+}
+```
+
+3. 安装依赖：
+
+```bash
+pip3 install dingtalk_stream
+```
+
+4. 启动项目后，在钉钉开发者后台点击 **事件订阅**，点击 **已完成接入，验证连接通道**，显示 **连接接入成功** 即表示配置完成：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-event-sub.png" width="700"/>
+
+## 三、使用
+
+与机器人私聊或将机器人拉入企业群中均可开启对话：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/dingtalk-hosting-demo.png" width="650"/>
diff --git a/docs/zh/channels/discord.mdx b/docs/zh/channels/discord.mdx
new file mode 100644
index 0000000..0563ab4
--- /dev/null
+++ b/docs/zh/channels/discord.mdx
@@ -0,0 +1,93 @@
+---
+title: Discord
+description: 将 CowAgent 接入 Discord Bot
+---
+
+> 通过 Discord Bot 的 **Gateway 长连接** 接入 CowAgent，支持私聊（DM）与服务器频道（@机器人 / 回复机器人触发）。Gateway 基于 WebSocket 长连接，无需公网 IP 与回调地址，开箱即用。
+
+## 一、接入步骤
+
+### 步骤一：创建 Discord 应用与 Bot
+
+1. 打开 [Discord 开发者后台](https://discord.com/developers/applications)，点击 **New Application**，填写名称（如 `CowAgent`）并创建。
+2. 左侧菜单进入 **Bot** 页面，点击 **Reset Token** 生成 Bot Token，复制并妥善保存（仅显示一次）。
+
+<Tip>
+  这个 Token 等同于 Bot 的密码，请勿泄露。若意外泄漏，在 Bot 页面再次点击 **Reset Token** 重置即可。
+</Tip>
+
+### 步骤二：开启 Message Content Intent
+
+私聊与频道读取文本均依赖该权限。
+
+1. 在 **Bot** 页面下方找到 **Privileged Gateway Intents**。
+2. 打开 **Message Content Intent** 开关并保存。
+
+<Note>
+  未开启该开关时，机器人收到的消息内容会为空，导致无响应。
+</Note>
+
+### 步骤三：邀请 Bot 进入服务器
+
+1. 左侧菜单进入 **OAuth2 → URL Generator**。
+2. **Scopes** 勾选 `bot`。
+3. **Bot Permissions** 至少勾选：`Send Messages`、`Read Message History`、`Attach Files`、`View Channels`。
+4. 复制底部生成的授权链接，在浏览器打开，选择目标服务器完成授权。
+
+<Note>
+  仅需私聊（DM）可跳过此步，但仍需先在任意共同服务器中与机器人建立 DM 通道，或由用户主动私聊机器人。
+</Note>
+
+### 步骤四：接入 CowAgent
+
+<Tabs>
+  <Tab title="Web 控制台（推荐）">
+    打开 Web 控制台（本地链接：http://127.0.0.1:9899 ），选择 **通道** 菜单，点击 **接入通道**，选择 **Discord**，填入 Bot Token，点击接入即可。
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置后启动：
+
+    ```json
+    {
+      "channel_type": "discord",
+      "discord_token": "your-discord-bot-token",
+      "discord_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | 参数 | 说明 | 默认值 |
+    | --- | --- | --- |
+    | `discord_token` | 开发者后台 Bot 页面生成的 Bot Token | - |
+    | `discord_group_trigger` | 频道触发方式：`mention_or_reply`（@或回复机器人）/ `mention_only`（仅@） / `all`（所有消息） | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+启动 Cow 后，日志中出现以下输出即表示接入成功：
+
+```
+[Discord] Bot logged in as CowAgent#1234 (id=123456789)
+[Discord] ✅ Discord bot ready, listening for messages
+```
+
+## 二、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 私聊（DM） | ✅ |
+| 服务器频道（@机器人 / 回复机器人） | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 文件消息 | ✅ 收发（PDF / Word / Excel 等） |
+
+<Note>
+  Discord 单条消息上限为 2000 字符，超长回复会自动按换行拆分为多条发送。
+</Note>
+
+## 三、使用
+
+完成接入后：
+
+- **私聊（DM）**：在服务器成员列表中找到你的机器人，点击头像直接发消息对话。
+- **频道**：在已邀请机器人的频道中，使用 `@你的机器人 你好` 或 **回复机器人的某条消息** 触发对话。
+
+发送图片或文件时，可以在附件的输入框中 **添加文字说明**（描述/问题）一并发送，机器人会结合附件回答。也支持先发附件再发问题，两条消息会自动合并提问。
diff --git a/docs/zh/channels/feishu.mdx b/docs/zh/channels/feishu.mdx
new file mode 100644
index 0000000..5cb8fe8
--- /dev/null
+++ b/docs/zh/channels/feishu.mdx
@@ -0,0 +1,111 @@
+---
+title: 飞书
+description: 将 CowAgent 接入飞书应用
+---
+
+> 通过飞书自建应用接入 CowAgent，支持单聊与群聊（@机器人），使用 WebSocket 长连接模式，无需公网 IP，支持流式打字机回复、语音消息收发。
+
+<Note>
+  接入需要是飞书企业用户且具有企业管理权限。
+</Note>
+
+## 一、接入方式
+
+### 方式一：扫码一键接入（推荐）
+
+启动 Cow 项目后在终端中即可完成扫码创建。或打开 Web 控制台（本地链接：http://127.0.0.1:9899 ），选择 **通道** 菜单，点击 **接入通道**，选择 **飞书**，点击 **一键创建飞书应用**，使用 **飞书 App** 扫描二维码即可自动完成应用创建并接入:
+
+
+<img src="https://cdn.link-ai.tech/doc/20260505181126.png" width="800"/>
+
+
+<Note>
+  1. `lark-oapi` 依赖版本需要 >=1.5.5
+  2. 扫码创建出的应用会自动预置全部所需权限（消息收发、卡片读写、群聊事件等）和事件订阅，无需到开发者后台手动配置。
+</Note>
+
+
+### 方式二：手动创建接入
+
+需要先在飞书开放平台创建自建应用并配置权限，再通过 Web 控制台或配置文件接入。
+
+**步骤一：创建应用**
+
+1. 进入 [飞书开发平台](https://open.feishu.cn/app/)，点击 **创建企业自建应用**：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-create-app.jpg" width="500"/>
+
+2. 在 **添加应用能力** 中，为应用添加 **机器人** 能力：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-add-bot.jpg" width="800"/>
+
+3. 在 **权限管理** 中，将以下权限粘贴到输入框，全选并 **批量开通**：
+
+```
+im:message,im:message.group_at_msg,im:message.group_at_msg:readonly,im:message.p2p_msg,im:message.p2p_msg:readonly,im:message:send_as_bot,im:resource,cardkit:card:write
+```
+
+<img src="https://cdn.link-ai.tech/doc/feishu-hosting-add-auth2.png" width="800"/>
+
+4. 在 **凭证与基础信息** 中获取 `App ID` 和 `App Secret`：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/feishu-hosting-appid-secret.jpg" width="800"/>
+
+**步骤二：接入 CowAgent**
+
+<Tabs>
+  <Tab title="Web 控制台">
+    打开 Web 控制台，选择 **通道** 菜单，点击 **接入通道**，选择 **飞书**，切换到「手动填写」Tab，输入 App ID 和 App Secret，点击接入即可。
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置后启动程序：
+
+    ```json
+    {
+      "channel_type": "feishu",
+      "feishu_app_id": "YOUR_APP_ID",
+      "feishu_app_secret": "YOUR_APP_SECRET",
+      "feishu_stream_reply": true
+    }
+    ```
+
+    | 参数 | 说明 | 默认值 |
+    | --- | --- | --- |
+    | `feishu_app_id` | 飞书应用 App ID | - |
+    | `feishu_app_secret` | 飞书应用 App Secret | - |
+    | `feishu_stream_reply` | 是否开启流式打字机回复 | `true` |
+  </Tab>
+</Tabs>
+
+**步骤三：发布应用**
+
+1. 启动 Cow 项目后，在飞书开放平台点击 **事件与回调**，选择 **长连接** 模式并保存：
+
+<img src="https://cdn.link-ai.tech/doc/202601311731183.png" width="600"/>
+
+2. 点击 **添加事件**，搜索 "接收消息"，选择 **接收消息 v2.0** 并确认。
+
+3. 点击 **版本管理与发布**，创建版本并申请 **线上发布**，在飞书客户端审核通过：
+
+<img src="https://cdn.link-ai.tech/doc/202601311807356.png" width="600"/>
+
+## 二、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 单聊 | ✅ |
+| 群聊（@机器人） | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 语音消息 | ✅ 收发 |
+| 流式回复 | ✅（通过 `feishu_stream_reply` 配置控制，默认开启） |
+
+<Note>
+  流式回复需要机器人具备 `cardkit:card:write` 权限（一键创建已默认开通），且接收方飞书客户端版本 ≥ 7.20。低版本客户端会显示升级提示，权限或版本不满足时自动降级为普通文本回复。
+</Note>
+
+## 三、使用
+
+完成接入后，在飞书中搜索机器人名称即可开始单聊对话。
+
+如需在群聊中使用，将机器人添加到群中，@机器人发送消息即可。
diff --git a/docs/zh/channels/index.mdx b/docs/zh/channels/index.mdx
new file mode 100644
index 0000000..55ad07a
--- /dev/null
+++ b/docs/zh/channels/index.mdx
@@ -0,0 +1,46 @@
+---
+title: 通道概览
+description: CowAgent 支持的通道及能力矩阵
+---
+
+CowAgent 支持接入多种聊天通道，启动时通过 `channel_type` 切换。Web 控制台默认开启，可与其他接入通道并行运行。
+
+## 能力矩阵
+
+下表汇总各通道支持的入站消息类型、机器人回复类型与群聊能力，方便按场景选择。
+
+| 通道 | 文本 | 图片 | 文件 | 语音 | 群聊 |
+| --- | :-: | :-: | :-: | :-: | :-: |
+| [微信](/zh/channels/weixin) | ✅ | ✅ | ✅ | ✅ |  |
+| [Web 控制台](/zh/channels/web) | ✅ | ✅ | ✅ | ✅ | |
+| [飞书](/zh/channels/feishu) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [钉钉](/zh/channels/dingtalk) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [企微智能机器人](/zh/channels/wecom-bot) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [QQ](/zh/channels/qq) | ✅ | ✅ | ✅ | | ✅ |
+| [企业微信应用](/zh/channels/wecom) | ✅ | ✅ | ✅ | ✅ | |
+| [公众号](/zh/channels/wechatmp) | ✅ | ✅ | | ✅ | |
+| [微信客服](/zh/channels/wechat-kf) | ✅ | ✅ | ✅ | ✅ | |
+| [Telegram](/zh/channels/telegram) | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [Slack](/zh/channels/slack) | ✅ | ✅ | ✅ | | ✅ |
+| [Discord](/zh/channels/discord) | ✅ | ✅ | ✅ | | ✅ |
+
+- **图片 / 文件 / 语音**列表示通道支持收发对应消息类型，具体细节详见各通道文档
+- **群聊**列指可识别并响应群消息
+
+<Tip>
+  每个通道的语音 / 图像能力依赖对应模型厂商的配置，详见 [模型概览](/zh/models)。
+</Tip>
+
+## 通道一览
+
+- [Web 控制台](/zh/channels/web) — 内置浏览器对话和管理面板，默认开启
+- [微信](/zh/channels/weixin) — 通过个人微信扫码登录
+- [飞书](/zh/channels/feishu) — 飞书自建机器人
+- [钉钉](/zh/channels/dingtalk) — 钉钉自建机器人
+- [企微智能机器人](/zh/channels/wecom-bot) — 企业微信智能机器人
+- [QQ](/zh/channels/qq) — QQ 官方机器人开放平台
+- [企业微信应用](/zh/channels/wecom) — 企业微信自建应用接入
+- [公众号](/zh/channels/wechatmp) — 微信公众号（订阅号 / 服务号）
+- [Telegram](/zh/channels/telegram) — 海外 IM，5 分钟接入，无需公网 IP
+- [Slack](/zh/channels/slack) — 团队协作 IM，Socket Mode 接入，无需公网 IP
+- [Discord](/zh/channels/discord) — 社区 IM，Gateway 长连接接入，无需公网 IP
diff --git a/docs/zh/channels/qq.mdx b/docs/zh/channels/qq.mdx
new file mode 100644
index 0000000..3b7554a
--- /dev/null
+++ b/docs/zh/channels/qq.mdx
@@ -0,0 +1,88 @@
+---
+title: QQ 机器人
+description: 将 CowAgent 接入 QQ 机器人（WebSocket 长连接模式）
+---
+
+> 通过 QQ 开放平台的机器人接口接入 CowAgent，支持 QQ 单聊、QQ 群聊（@机器人）、频道消息和频道私信，无需公网 IP，使用 WebSocket 长连接模式。
+
+<Note>
+  QQ 机器人通过 QQ 开放平台创建，使用 WebSocket 长连接接收消息，通过 OpenAPI 发送消息，无需公网 IP 和域名。
+</Note>
+
+## 一、创建 QQ 机器人
+
+> 进入[QQ 开放平台](https://q.qq.com)，QQ扫码登录，如果未注册开放平台账号，请先完成[账号注册](https://q.qq.com/#/register)。
+
+1.在 [QQ开放平台-机器人列表页](https://q.qq.com/#/apps)，点击创建机器人:
+
+<img src="https://cdn.link-ai.tech/doc/20260317162900.png" width="800"/>
+
+2.填写机器人名称、头像等基本信息，完成创建：
+
+<img src="https://cdn.link-ai.tech/doc/20260317163005.png" width="800"/>
+
+3.点击进入机器人配置页面，选择**开发管理**菜单，完成以下步骤：
+
+  - 复制并记录 **AppID**（机器人ID）
+  - 生成并记录 **AppSecret**（机器人秘钥）
+
+<img src="https://cdn.link-ai.tech/doc/20260317164955.png" width="800"/>
+
+## 二、配置和运行
+
+### 方式一：Web 控制台接入
+
+启动 Cow项目后打开 Web 控制台 (本地链接为: http://127.0.0.1:9899/ )，选择 **通道** 菜单，点击 **接入通道**，选择 **QQ 机器人**，填写上一步保存的 AppID 和 AppSecret，点击接入即可。
+
+<img src="https://cdn.link-ai.tech/doc/20260317165425.png" width="800"/>
+
+### 方式二：配置文件接入
+
+在 `config.json` 中添加以下配置：
+
+```json
+{
+  "channel_type": "qq",
+  "qq_app_id": "YOUR_APP_ID",
+  "qq_app_secret": "YOUR_APP_SECRET"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `qq_app_id` | QQ 机器人的 AppID，在开放平台开发管理中获取 |
+| `qq_app_secret` | QQ 机器人的 AppSecret，在开放平台开发管理中获取 |
+
+配置完成后启动程序，日志显示 `[QQ] ✅ Connected successfully` 即表示连接成功。
+
+
+## 三、使用
+
+在 QQ开放平台 - 管理 - **使用范围和人员** 菜单中，使用QQ客户端扫描 "添加到群和消息列表" 的二维码，即可开始与QQ机器人的聊天：
+
+<img src="https://cdn.link-ai.tech/doc/20260317165947.png" width="800"/>
+
+对话效果：
+<img src="https://cdn.link-ai.tech/doc/20260317171508.png" width="800"/>
+
+## 四、功能说明
+
+> 注意：若需在群聊及频道中使用QQ机器人，需完成发布上架审核并在使用范围配置权限使用范围。
+
+| 功能 | 支持情况 |
+| --- | --- |
+| QQ 单聊 | ✅ |
+| QQ 群聊（@机器人） | ✅ |
+| 频道消息（@机器人） | ✅ |
+| 频道私信 | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发（群聊和单聊） |
+| 文件消息 | ✅ 发送（群聊和单聊） |
+| 定时任务 | ✅ 主动推送（每月每用户限 4 条） |
+
+
+## 五、注意事项
+
+- **被动消息限制**：QQ 单聊被动消息有效期为 60 分钟，每条消息最多回复 5 次；QQ 群聊被动消息有效期为 5 分钟。
+- **主动消息限制**：单聊和群聊每月主动消息上限为 4 条，在使用定时任务功能时需要注意这个限制
+- **事件权限**：默认订阅 `GROUP_AND_C2C_EVENT`（QQ群/单聊）和 `PUBLIC_GUILD_MESSAGES`（频道公域消息），如需其他事件类型请在开放平台申请权限。
diff --git a/docs/zh/channels/slack.mdx b/docs/zh/channels/slack.mdx
new file mode 100644
index 0000000..1103f1c
--- /dev/null
+++ b/docs/zh/channels/slack.mdx
@@ -0,0 +1,118 @@
+---
+title: Slack
+description: 将 CowAgent 接入 Slack App
+---
+
+> 通过 Slack App 的 **Socket Mode** 接入 CowAgent，支持私聊（DM）与频道（@机器人 / 线程内回复触发）。Socket Mode 基于长连接，无需公网 IP 与回调地址，开箱即用。
+
+## 一、接入步骤
+
+### 步骤一：创建 Slack App
+
+1. 打开 [Slack API 应用管理页](https://api.slack.com/apps)，点击 **Create New App** → **From scratch**。
+2. 填写 **App Name**（如 `CowAgent`），选择要安装的 **Workspace**，点击创建。
+
+### 步骤二：开启 Socket Mode 并获取 App Token
+
+1. 左侧菜单进入 **Settings → Socket Mode**，打开 **Enable Socket Mode**。
+2. 系统会提示生成一个 **App-Level Token**，作用域勾选 `connections:write`，生成后保存这串以 `xapp-` 开头的 Token。
+
+<Tip>
+  Socket Mode 通过 WebSocket 长连接接收事件，无需在公网暴露回调 URL，适合本地或内网部署。
+</Tip>
+
+### 步骤三：配置 Bot 权限并安装
+
+1. 进入 **Features → OAuth & Permissions**，在 **Bot Token Scopes** 中点击 **Add an OAuth Scope**，逐项添加以下权限：
+
+   ```
+   app_mentions:read
+   channels:history
+   chat:write
+   commands
+   files:read
+   files:write
+   groups:history
+   im:history
+   mpim:history
+   users:read
+   ```
+
+   <Note>
+     `files:read` / `files:write` 用于图片、文件的收发；若仅需文本对话可省略。
+   </Note>
+
+2. 进入 **Features → Event Subscriptions**，打开 **Enable Events**，在 **Subscribe to bot events** 中点击 **Add Bot User Event** 添加以下事件：
+
+   ```
+   app_mention
+   message.im
+   message.channels
+   ```
+
+   <Note>
+     如需在私有频道使用，再添加 `message.groups`。
+   </Note>
+3. 进入 **Features → App Home**，在 **Show Tabs** 区域勾选 **Messages Tab**，并勾选下方的 **Allow users to send Slash commands and messages from the messages tab**（允许用户从消息标签页发送消息），否则私聊输入框会被关闭、无法给机器人发消息。
+4. 回到 **OAuth & Permissions**，点击 **Install to Workspace** 完成安装，安装后获取以 `xoxb-` 开头的 **Bot User OAuth Token**。
+
+<Tip>
+  若 Slack 客户端仍提示「向此应用发送消息的功能已关闭」，请确认已完成上一步的 App Home 设置，并刷新或重启 Slack 客户端（必要时把 App 从对话列表移除后重新打开）。
+</Tip>
+
+### 步骤四：接入 CowAgent
+
+<Tabs>
+  <Tab title="Web 控制台（推荐）">
+    打开 Web 控制台（本地链接：http://127.0.0.1:9899 ），选择 **通道** 菜单，点击 **接入通道**，选择 **Slack**，分别填入 Bot Token（`xoxb-`）和 App Token（`xapp-`），点击接入即可。
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置后启动：
+
+    ```json
+    {
+      "channel_type": "slack",
+      "slack_bot_token": "xoxb-xxxxxxxxxxxx",
+      "slack_app_token": "xapp-xxxxxxxxxxxx",
+      "slack_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | 参数 | 说明 | 默认值 |
+    | --- | --- | --- |
+    | `slack_bot_token` | Bot User OAuth Token，形如 `xoxb-...` | - |
+    | `slack_app_token` | App-Level Token（开启 Socket Mode 后生成），形如 `xapp-...` | - |
+    | `slack_group_trigger` | 频道触发方式：`mention_or_reply`（@或线程内回复）/ `mention_only`（仅@） / `all`（所有消息） | `mention_or_reply` |
+  </Tab>
+</Tabs>
+
+启动 Cow 后，日志中出现以下输出即表示接入成功：
+
+```
+[Slack] Bot logged in as user_id=U0XXXXXXX, team=Txxxxxxxx
+[Slack] ✅ Slack bot ready, listening for events
+```
+
+## 二、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 私聊（DM） | ✅ |
+| 频道（@机器人 / 线程内回复） | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 文件消息 | ✅ 收发（PDF / Word / Excel 等） |
+| 线程回复 | ✅ 回复发送至触发消息所在线程 |
+
+<Note>
+  Slack 通过线程（Thread）组织对话。机器人会把回复发送到触发消息所在的线程，频道内更整洁。
+</Note>
+
+## 三、使用
+
+完成接入后：
+
+- **私聊（DM）**：在 Slack 左侧 **Apps** 中找到你的 App，直接发消息对话。
+- **频道**：把 App 邀请进频道（`/invite @你的App`），使用 `@你的App 你好` 触发对话；后续在同一线程内直接回复即可继续对话。
+
+发送图片或文件时，可以在附件的输入框中 **添加文字说明**（描述/问题）一并发送，机器人会结合附件回答。也支持先发附件再发问题，两条消息会自动合并提问。
diff --git a/docs/zh/channels/telegram.mdx b/docs/zh/channels/telegram.mdx
new file mode 100644
index 0000000..d7ab7a4
--- /dev/null
+++ b/docs/zh/channels/telegram.mdx
@@ -0,0 +1,112 @@
+---
+title: Telegram
+description: 将 CowAgent 接入 Telegram Bot
+---
+
+> 通过 Telegram Bot API 接入 CowAgent，支持单聊与群聊（@机器人 / 回复机器人触发），使用 Long Polling 模式无需公网 IP，开箱即用。
+
+
+## 一、接入步骤
+
+### 步骤一：通过 BotFather 创建 Bot
+
+1. 在 Telegram 中搜索并打开官方账号 [@BotFather](https://t.me/BotFather)。
+2. 发送 `/newbot` 命令，按提示输入：
+   - **Bot 名称**（显示名，可中文，例如 `My CowAgent Bot`）
+   - **Bot 用户名**（必须以 `bot` 结尾，例如 `my_cowagent_bot`）
+3. 创建成功后，BotFather 会返回一段 **HTTP API Token**（形如 `123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ`），妥善保存。
+
+<Tip>
+  这个 Token 等同于 Bot 的密码，请勿泄露。如果意外泄漏可向 `@BotFather` 发送 `/revoke` 重置。
+</Tip>
+
+### 步骤二：（群聊使用）关闭 Privacy Mode
+
+仅使用单聊可跳过此步。Telegram Bot 默认开启 **Privacy Mode**，群聊中只能收到带 `@bot` 的命令（如 `/start@your_bot`）以及对 bot 消息的 reply；**普通的 `@bot 你好` 文字消息收不到**，会导致群聊无响应。
+
+向 `@BotFather` 发送：
+
+1. `/setprivacy`
+2. 选择刚才创建的 bot
+3. 选择 `Disable`
+
+<Note>
+  若设置后群聊仍无响应，可尝试把 Bot 从群里移除并重新拉入。
+</Note>
+
+### 步骤三：接入 CowAgent
+
+<Tabs>
+  <Tab title="Web 控制台（推荐）">
+    打开 Web 控制台（本地链接：http://127.0.0.1:9899 ），选择 **通道** 菜单，点击 **接入通道**，选择 **Telegram**，填入 Bot Token，点击接入即可。
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置后启动：
+
+    ```json
+    {
+      "channel_type": "telegram",
+      "telegram_token": "123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ",
+      "telegram_group_trigger": "mention_or_reply"
+    }
+    ```
+
+    | 参数 | 说明 | 默认值 |
+    | --- | --- | --- |
+    | `telegram_token` | BotFather 返回的 HTTP API Token | - |
+    | `telegram_group_trigger` | 群聊触发方式：`mention_or_reply`（@或回复机器人）/ `mention_only`（仅@） / `all`（所有消息） | `mention_or_reply` |
+    | `telegram_register_commands` | 启动时是否自动向 BotFather 注册命令菜单 | `true` |
+    | `telegram_proxy` | （可选）代理地址，如 `http://127.0.0.1:7890`、`socks5://127.0.0.1:1080`；运行环境无法直连 `api.telegram.org` 时配置，留空则使用环境变量 `HTTPS_PROXY` | `""` |
+  </Tab>
+</Tabs>
+
+启动 Cow 后，日志中出现以下输出即表示接入成功：
+
+```
+[Telegram] Bot logged in as @my_cowagent_bot (id=123456789)
+[Telegram] Registered 10 bot commands
+[Telegram] ✅ Telegram bot ready, polling for updates
+```
+
+## 二、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 单聊 | ✅ |
+| 群聊（@机器人 / 回复机器人） | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 语音消息 | ✅ 收发（接收 OGG/Opus，发送 OGG/Opus） |
+| 视频消息 | ✅ 收发 |
+| 文件消息 | ✅ 收发（PDF / Word / Excel 等） |
+| 命令菜单 | ✅ 与 Web 控制台 slash 命令一致 |
+
+### 命令菜单
+
+启动时会自动向 BotFather 注册命令菜单，用户在 Telegram 输入框输入 `/` 会出现下拉提示：
+
+| 命令 | 说明 |
+| --- | --- |
+| `/help` | 显示命令帮助 |
+| `/status` | 查看运行状态 |
+| `/context` | 查看对话上下文（`/context clear` 清除） |
+| `/skill` | 技能管理（`/skill list`、`/skill install` 等） |
+| `/memory` | 记忆管理（`/memory dream`） |
+| `/knowledge` | 知识库管理（`/knowledge list` / `on` / `off`） |
+| `/config` | 查看当前配置 |
+| `/cancel` | 中止当前正在运行的 Agent 任务 |
+| `/logs` | 查看最近日志 |
+| `/version` | 查看版本 |
+
+<Note>
+  Telegram 命令菜单只能展示一级命令，子命令通过空格输入即可，例如 `/skill list`、`/context clear`。
+</Note>
+
+## 三、使用
+
+完成接入后：
+
+- **单聊**：在 Telegram 中搜索你创建的 Bot 用户名（如 `@my_cowagent_bot`），点击 `Start` 即可开始对话。
+- **群聊**：把 Bot 拉进群，使用 `@bot 你好` 或 **回复 Bot 的某条消息** 触发对话。若群聊无响应，请检查 Privacy Mode 是否已按 [步骤二](#步骤二-群聊使用-关闭-privacy-mode) 关闭。
+
+发送图片或文件时，可以直接在附件上方的输入框中 **添加 Caption**（描述/问题）一并发送，机器人会结合附件回答。也支持先发附件再发问题，两条消息会自动合并提问。
diff --git a/docs/zh/channels/web.mdx b/docs/zh/channels/web.mdx
new file mode 100644
index 0000000..810da3d
--- /dev/null
+++ b/docs/zh/channels/web.mdx
@@ -0,0 +1,95 @@
+---
+title: Web 控制台
+description: 通过 Web 控制台使用 CowAgent
+---
+
+Web 控制台是 CowAgent 的默认通道，启动后会自动运行，通过浏览器即可与 Agent 对话，并支持在线管理模型、技能、记忆、通道等配置。
+
+## 配置
+
+```json
+{
+  "channel_type": "web",
+  "web_host": "0.0.0.0",
+  "web_port": 9899,
+  "web_password": "",
+  "enable_thinking": false
+}
+```
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `channel_type` | 设为 `web` | `web` |
+| `web_host` | Web 服务监听地址，默认监听 `127.0.0.1`（仅本机），如需公网访问请改为 `0.0.0.0` 并设置密码 | `""` |
+| `web_port` | Web 服务监听端口 | `9899` |
+| `web_password` | 访问密码，留空表示不启用密码保护；监听 `0.0.0.0` 时建议设置 | `""` |
+| `web_session_expire_days` | 登录会话有效天数 | `30` |
+| `web_file_serve_root` | web 端可直接读取/发送的文件根目录，默认仅限用户主目录及 agent 工作空间；设为 `/` 可放开整个文件系统 | `"~"` |
+| `enable_thinking` | 是否启用深度思考模式 | `false` |
+
+配置密码后，访问控制台时需先输入密码完成登录。登录状态默认保持 30 天，期间重启服务也无需重新登录。密码也支持在控制台的「配置」页面中在线修改。
+
+## 访问地址
+
+启动项目后访问：
+
+- 本地运行：`http://localhost:9899`
+- 服务器运行：`http://<server-ip>:9899`
+
+<Note>
+  请确保服务器防火墙和安全组已放行对应端口。
+</Note>
+
+## 功能介绍
+
+### 对话界面
+
+支持流式输出，可实时展示 Agent 的思考过程（Reasoning）和工具调用过程（Tool Calls），更直观地观察 Agent 的决策过程。深度思考功能可通过配置或控制台的「Agent 配置」开关控制。
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### 多会话管理
+
+对话界面支持多会话（Session）管理，所有会话记录持久化存储在数据库中：
+
+- **会话列表**：点击左侧历史会话图标可展开/收起会话列表面板，支持滚动加载全部历史会话
+- **AI 生成标题**：新会话在首轮对话完成后，自动调用模型生成简短的会话摘要标题
+- **新建会话**：点击会话列表顶部的「新对话」按钮或输入区的 `+` 按钮创建新会话
+- **删除会话**：点击会话项的删除按钮，确认后永久删除该会话及其所有消息
+- **清除上下文**：点击输入区的清除按钮，在当前会话中插入一条分隔线，分隔线以上的消息仍然展示但不再作为模型的上下文输入
+
+### 模型管理
+
+支持在线管理不同模型厂商的文本、图像、语音、向量模型配置，无需手动编辑配置文件：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260521212949.png" />
+
+### 技能管理
+
+支持在线查看和管理 Agent 技能（Skills）：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+### 记忆管理
+
+支持在线查看和管理 Agent 记忆：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+### 通道管理
+
+支持在线管理接入通道，支持实时连接/断开操作：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+### 定时任务
+
+支持在线查看和管理定时任务，包括一次性任务、固定间隔、Cron 表达式等多种调度方式的可视化管理：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+### 日志
+
+支持在线实时查看 Agent 运行日志，便于监控运行状态和排查问题：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
diff --git a/docs/zh/channels/wechat-kf.mdx b/docs/zh/channels/wechat-kf.mdx
new file mode 100644
index 0000000..1967d99
--- /dev/null
+++ b/docs/zh/channels/wechat-kf.mdx
@@ -0,0 +1,130 @@
+---
+title: 微信客服
+description: 将 CowAgent 接入微信客服（WeChat Customer Service）
+---
+
+通过把企业微信自建应用绑定到「微信客服」账号，CowAgent 可以接管来自外部微信用户的客服咨询，并可在小程序、公众号、视频号及视频号小店等场景中通过链接或二维码触达微信用户。
+
+<Note>
+  微信客服只能使用 Docker 部署或服务器 Python 部署，需要公网可达的回调地址，不支持本地运行模式。
+</Note>
+
+## 一、准备
+
+需要的资源：
+
+1. 一台服务器（有公网 IP）
+2. 注册并已认证的企业微信
+3. 已开通「微信客服」能力
+
+<Note>
+  建议**单独再创建一个企微自建应用**用于微信客服，不要复用已有的 `wechatcom_app` 应用，否则两个通道会争抢同一个回调地址。
+</Note>
+
+## 二、创建企业微信自建应用
+
+1. 在 [企业微信管理后台](https://work.weixin.qq.com/wework_admin/frame#apps)，点击 **应用管理 → 创建应用**：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+2. 点击 **我的企业**，在最下方获取 **企业ID**（后续填写到 `wechat_kf_corp_id`）：
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-companyid.png" width="600"/>
+
+3. 进入上一步创建的应用，点击 Secret 旁的「**查看**」，Secret 会推送到管理员手机端的企业微信里查看：
+
+<img src="https://cdn.link-ai.tech/doc/wechatcom-hosting-agent-secret.png" width="600"/>
+
+4. 进入应用 **接收消息 → 设置API接收**，点击右侧「**随机获取**」生成 **Token** 和 **EncodingAESKey** 并保存：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wechatcom-hosting-token-aeskey.jpg" width="600"/>
+
+<Note>
+  此时保存 API 接收配置会失败，因为程序还未启动，等项目运行后再回来保存。
+</Note>
+
+## 三、配置和运行
+
+填入上一步收集到的 4 个字段（Corp ID / Secret / Token / EncodingAESKey）：
+
+<Tabs>
+  <Tab title="Web 控制台">
+    启动 Cow 项目后打开 Web 控制台，选择 **通道** 菜单，点击 **接入通道**，选择 **微信客服**，依次填入 Corp ID / Secret / Token / AES Key（端口默认 9888，可改），点击接入即可。
+
+    <img src="https://cdn.link-ai.tech/doc/cow-weixinkefu-web-control.png" width="800"/>
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置（各参数与企业微信后台的对应关系见上方截图）：
+
+    ```json
+    {
+      "channel_type": "wechat_kf",
+      "wechat_kf_corp_id": "YOUR_CORP_ID",
+      "wechat_kf_secret": "YOUR_SECRET",
+      "wechat_kf_token": "YOUR_TOKEN",
+      "wechat_kf_aes_key": "YOUR_AES_KEY",
+      "wechat_kf_port": 9888
+    }
+    ```
+
+    | 参数 | 说明 |
+    | --- | --- |
+    | `wechat_kf_corp_id` | 企业 ID |
+    | `wechat_kf_secret` | 绑定到微信客服的那个企微自建应用的 Secret |
+    | `wechat_kf_token` | API 接收配置中的 Token |
+    | `wechat_kf_aes_key` | API 接收配置中的 EncodingAESKey |
+    | `wechat_kf_port` | 监听端口，默认 9888 |
+  </Tab>
+</Tabs>
+
+接入完成后启动程序（Web 控制台方式会自动重启），日志中出现 `Listening on http://0.0.0.0:9888/wxkf/` 表示运行成功，需要将该端口对外开放（如在云服务器安全组中放行）。
+
+接着回到企业微信「接收消息 → 设置API接收」，将回调 URL 填为 `http://<your-host>:9888/wxkf/`，点击保存。保存成功后还需将服务器 IP 添加到 **企业可信IP** 中，否则无法收发消息：
+
+<img src="https://cdn.link-ai.tech/doc/wechat-com_config.png" width="600"/>
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  如遇到 URL 配置回调不通过或配置失败：
+  1. 确保服务器防火墙关闭且安全组放行监听端口（默认 9888）
+  2. 仔细检查 Token、Secret、EncodingAESKey 等参数配置是否一致，URL 格式是否正确
+  3. 认证企业微信需要配置与主体一致的备案域名
+</Warning>
+
+## 四、绑定微信客服账号
+
+进入企业微信管理后台 **微信客服** 页面，创建客服账号并与上一步的企微自建应用绑定：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step1.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step2.jpg" width="600"/>
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-step3.jpg" width="600"/>
+
+绑定完成后，进入 **微信客服 → 微信客服账号详情**，在「**接入链接**」一栏：
+
+- 点击「**复制链接**」可获得形如 `https://work.weixin.qq.com/kfid/kfcd83e5896b9ba07be` 的访问链接
+- 点击「**生成二维码**」可获得对应的二维码
+
+把链接或二维码推给微信客户使用即可：
+
+<img src="https://cdn.link-ai.tech/doc/wechat-customer-service_use.png" width="600"/>
+
+## 五、使用
+
+微信用户通过链接或二维码进入客服对话后，即可与 AI 进行多轮对话，支持文本、图片、语音等消息：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-chat-demo.jpg" width="900"/>
+
+除此之外，基于微信生态官方能力，还可将微信客服应用在公众号、小程序、视频号及视频号小店等场景，详情可查看企业微信管理后台 [微信客服 → 接入场景](https://work.weixin.qq.com/wework_admin/frame#/app/servicer) 的相关说明：
+
+<img src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/wxcustomer-hosting-interface-demo.png" width="800"/>
+
+## 常见问题
+
+需要确保已安装以下依赖：
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/zh/channels/wechatmp.mdx b/docs/zh/channels/wechatmp.mdx
new file mode 100644
index 0000000..917df41
--- /dev/null
+++ b/docs/zh/channels/wechatmp.mdx
@@ -0,0 +1,72 @@
+---
+title: 微信公众号
+description: 将 CowAgent 接入微信公众号
+---
+
+CowAgent 支持接入个人订阅号和企业服务号两种公众号类型。
+
+| 类型 | 要求 | 特点 |
+| --- | --- | --- |
+| **个人订阅号** | 个人可申请 | 收到消息时会回复一条提示，回复生成后需用户主动发消息获取 |
+| **企业服务号** | 企业申请，需通过微信认证开通客服接口 | 回复生成后可主动推送给用户 |
+
+<Note>
+  公众号仅支持服务器和 Docker 部署，不支持本地运行。需额外安装扩展依赖：`pip3 install -r requirements-optional.txt`
+</Note>
+
+## 一、个人订阅号
+
+在 `config.json` 中添加以下配置：
+
+```json
+{
+  "channel_type": "wechatmp",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "wx73f9******d1e48",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
+
+### 配置步骤
+
+这些配置需要和 [微信公众号后台](https://mp.weixin.qq.com/advanced/advanced?action=dev&t=advanced/dev) 中的保持一致，进入页面后，在左侧菜单选择 **设置与开发 → 基本配置 → 服务器配置**，按下图进行配置：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103506.png" width="480"/>
+
+1. 在公众平台启用开发者密码（对应配置 `wechatmp_app_secret`），并将服务器 IP 填入白名单
+2. 按上图填写 `config.json` 中与公众号相关的配置，要与公众号后台的配置一致
+3. 启动程序，启动后会监听 80 端口（若无权限监听，则在启动命令前加上 `sudo`；若 80 端口已被占用，则关闭该占用进程）
+4. 在公众号后台 **启用服务器配置** 并提交，保存成功则表示已成功配置。注意 **"服务器地址(URL)"** 需要配置为 `http://{HOST}/wx` 的格式，其中 `{HOST}` 可以是服务器的 IP 或域名
+
+随后关注公众号并发送消息即可看到以下效果：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103522.png" width="720"/>
+
+由于受订阅号限制，回复内容较短的情况下（15s 内），可以立即完成回复，但耗时较长的回复则会先回复一句 "正在思考中"，后续需要用户输入任意文字主动获取答案，而服务号则可以通过客服接口解决这一问题。
+
+<Tip>
+  **语音识别**：可利用微信自带的语音识别功能，需要在公众号管理页面的 "设置与开发 → 接口权限" 页面开启 "接收语音识别结果"。
+</Tip>
+
+## 二、企业服务号
+
+企业服务号与上述个人订阅号的接入过程基本相同，差异如下：
+
+1. 在公众平台申请企业服务号并完成微信认证，在接口权限中确认已获得 **客服接口** 的权限
+2. 在 `config.json` 中设置 `"channel_type": "wechatmp_service"`，其他配置与上述订阅号相同
+3. 交互效果上，即使是较长耗时的回复，也可以主动推送给用户，无需用户手动获取
+
+```json
+{
+  "channel_type": "wechatmp_service",
+  "single_chat_prefix": [""],
+  "wechatmp_app_id": "YOUR_APP_ID",
+  "wechatmp_app_secret": "YOUR_APP_SECRET",
+  "wechatmp_aes_key": "",
+  "wechatmp_token": "YOUR_TOKEN",
+  "wechatmp_port": 80
+}
+```
diff --git a/docs/zh/channels/wecom-bot.mdx b/docs/zh/channels/wecom-bot.mdx
new file mode 100644
index 0000000..5d4f753
--- /dev/null
+++ b/docs/zh/channels/wecom-bot.mdx
@@ -0,0 +1,104 @@
+---
+title: 企微智能机器人
+description: 将 CowAgent 接入企业微信智能机器人（长连接模式）
+---
+
+> 通过企业微信智能机器人接入CowAgent，支持企业内部单聊和内部群聊，无需公网 IP，使用 WebSocket 长连接模式，支持Markdown渲染和流式输出。
+
+<Note>
+  智能机器人与企业微信自建应用是两种不同的接入方式。智能机器人使用 WebSocket 长连接，无需服务器公网 IP 和域名，配置更简单。
+</Note>
+
+## 一、接入方式
+
+### 方式一：扫码一键接入（推荐）
+
+无需提前创建机器人，启动 Cow 项目后打开 Web 控制台（本地链接：http://127.0.0.1:9899/），选择 **通道** 菜单，点击**接入通道**，选择**企微智能机器人**，切换到「扫码接入」模式，使用**企业微信**扫码即可自动完成机器人创建和接入。
+
+<img src="https://cdn.link-ai.tech/doc/20260401121213.png" width="800"/>
+
+<Note>
+  扫码成功后，可在企业微信工作台 - **智能机器人**页面对机器人进行进一步配置，包括修改名称、头像、可见范围等。
+</Note>
+
+### 方式二：手动创建接入
+
+需要先在企业微信中创建智能机器人并获取 Bot ID 和 Secret，再通过 Web 控制台或配置文件接入。
+
+**步骤一：创建智能机器人**
+
+1. 打开企业微信客户端，进入工作台，点击**智能机器人**：
+
+<img src="https://cdn.link-ai.tech/doc/20260316180959.png" width="800"/>
+
+2. 点击创建机器人 - 手动创建：
+
+<img src="https://cdn.link-ai.tech/doc/20260316181118.png" width="800"/>
+
+3. 右侧窗口拖到最下方，选择**API模式创建**：
+
+<img src="https://cdn.link-ai.tech/doc/20260316181215.png" width="800"/>
+
+4. 设置机器人名称、头像、可见范围，并选择**长连接模式**，记录下 **Bot ID** 和 **Secret** 信息后点击保存。
+
+**步骤二：接入 CowAgent**
+
+<Tabs>
+  <Tab title="Web 控制台">
+    打开 Web 控制台，选择**通道**菜单，点击**接入通道**，选择**企微智能机器人**，切换到「手动填写」模式，输入 Bot ID 和 Secret，点击接入即可。
+
+    <img src="https://cdn.link-ai.tech/doc/20260316181711.png" width="800"/>
+  </Tab>
+  <Tab title="配置文件">
+    在 `config.json` 中添加以下配置后启动程序：
+
+    ```json
+    {
+      "channel_type": "wecom_bot",
+      "wecom_bot_id": "YOUR_BOT_ID",
+      "wecom_bot_secret": "YOUR_SECRET"
+    }
+    ```
+
+    | 参数 | 说明 |
+    | --- | --- |
+    | `wecom_bot_id` | 智能机器人的 BotID |
+    | `wecom_bot_secret` | 智能机器人的 Secret |
+  </Tab>
+</Tabs>
+
+日志显示 `[WecomBot] Subscribe success` 即表示连接成功。
+
+<Note>
+  除长连接外，也支持**回调（HTTP 回调）模式**：创建机器人时选择「使用 URL 回调」，将接收消息 URL 设为 `http(s)://<域名或IP>:9892/wecombot`，并复制该页面的 Token 和 EncodingAESKey。该模式需公网可达，且不支持文件发送与定时推送，一般推荐使用长连接。对应 `config.json` 配置如下：
+
+```json
+{
+  "channel_type": "wecom_bot",
+  "wecom_bot_mode": "webhook",
+  "wecom_bot_token": "YOUR_TOKEN",
+  "wecom_bot_encoding_aes_key": "YOUR_ENCODING_AES_KEY",
+  "wecom_bot_port": 9892
+}
+```
+</Note>
+
+## 二、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 单聊 | ✅ |
+| 群聊（@机器人） | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 文件消息 | ✅ 收发 |
+| 流式回复 | ✅ |
+| 定时任务主动推送 | ✅ |
+
+## 三、使用
+
+在企业微信中搜索创建的机器人名称，即可开始单聊对话。
+
+如需在企微内部群聊中使用，将机器人添加到群中，@机器人发送消息即可。
+
+<img src="https://cdn.link-ai.tech/doc/20260316182902.png" width="800"/>
diff --git a/docs/zh/channels/wecom.mdx b/docs/zh/channels/wecom.mdx
new file mode 100644
index 0000000..e0ed6fb
--- /dev/null
+++ b/docs/zh/channels/wecom.mdx
@@ -0,0 +1,98 @@
+---
+title: 企微自建应用
+description: 将 CowAgent 接入企业微信自建应用
+---
+
+通过企业微信自建应用接入 CowAgent，支持企业内部人员单聊使用。
+
+<Note>
+  企业微信只能使用 Docker 部署或服务器 Python 部署，不支持本地运行模式。
+</Note>
+
+## 一、准备
+
+需要的资源：
+
+1. 一台服务器（有公网 IP）
+2. 注册一个企业微信（个人也可注册，但无法认证）
+3. 认证企业微信还需要对应主体备案的域名
+
+## 二、创建企业微信应用
+
+1. 在 [企业微信管理后台](https://work.weixin.qq.com/wework_admin/frame#profile) 点击 **我的企业**，在最下方获取 **企业ID**（后续填写到 `wechatcom_corp_id` 字段中）。
+
+2. 切换到 **应用管理**，点击创建应用：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103156.png" width="480"/>
+
+3. 进入应用创建页面，记录 `AgentId` 和 `Secret`：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103218.png" width="580"/>
+
+4. 点击 **设置API接收**，配置应用接口：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103211.png" width="520"/>
+
+- URL 格式为 `http://ip:port/wxcomapp`（认证企业需使用备案域名）
+- 随机获取 `Token` 和 `EncodingAESKey` 并保存
+
+<Note>
+  此时保存 API 接收配置会失败，因为程序还未启动，等项目运行后再回来保存。
+</Note>
+
+## 三、配置和运行
+
+在 `config.json` 中添加以下配置（各参数与企业微信后台的对应关系见上方截图）：
+
+```json
+{
+  "channel_type": "wechatcom_app",
+  "single_chat_prefix": [""],
+  "wechatcom_corp_id": "YOUR_CORP_ID",
+  "wechatcomapp_token": "YOUR_TOKEN",
+  "wechatcomapp_secret": "YOUR_SECRET",
+  "wechatcomapp_agent_id": "YOUR_AGENT_ID",
+  "wechatcomapp_aes_key": "YOUR_AES_KEY",
+  "wechatcomapp_port": 9898
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `wechatcom_corp_id` | 企业 ID |
+| `wechatcomapp_token` | API 接收配置中的 Token |
+| `wechatcomapp_secret` | 应用的 Secret |
+| `wechatcomapp_agent_id` | 应用的 AgentId |
+| `wechatcomapp_aes_key` | API 接收配置中的 EncodingAESKey |
+| `wechatcomapp_port` | 监听端口，默认 9898 |
+
+配置完成后启动程序。当后台日志显示 `http://0.0.0.0:9898/` 时说明程序运行成功，需要将该端口对外开放（如在云服务器安全组中放行）。
+
+程序启动后，回到企业微信后台保存 **消息服务器配置**，保存成功后还需将服务器 IP 添加到 **企业可信IP** 中，否则无法收发消息：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103224.png" width="520"/>
+
+<Warning>
+  如遇到 URL 配置回调不通过或配置失败：
+  1. 确保服务器防火墙关闭且安全组放行监听端口
+  2. 仔细检查 Token、Secret Key 等参数配置是否一致，URL 格式是否正确
+  3. 认证企业微信需要配置与主体一致的备案域名
+</Warning>
+
+## 四、使用
+
+在企业微信中搜索刚创建的应用名称，即可直接对话：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103228.png" width="720"/>
+
+如需让外部个人微信用户使用，可在 **我的企业 → 微信插件** 中分享邀请关注二维码，个人微信扫码关注后即可与应用对话：
+
+<img src="https://cdn.link-ai.tech/doc/20260228103232.png" width="520"/>
+
+## 常见问题
+
+需要确保已安装以下依赖：
+
+```bash
+pip install websocket-client pycryptodome
+```
diff --git a/docs/zh/channels/weixin.mdx b/docs/zh/channels/weixin.mdx
new file mode 100644
index 0000000..c19974a
--- /dev/null
+++ b/docs/zh/channels/weixin.mdx
@@ -0,0 +1,74 @@
+---
+title: 微信
+description: 将 CowAgent 接入个人微信（基于官方接口）
+---
+
+> 接入个人微信，扫码登录即可使用，支持文本、图片、语音、文件、视频等消息的私聊收发。通过微信官方API进行接入，无安全风险，接入后会在会话中新增一个机器人助手，不影响当前账号的使用。
+
+## 一、配置和运行
+
+### 方式一：Web 控制台接入
+
+启动 Cow 项目后打开 Web 控制台 (本地链接为: http://127.0.0.1:9899/ )，选择 **通道** 菜单，点击 **接入通道**，选择 **微信**，点击接入后按照提示扫码登录。
+
+<img src="https://cdn.link-ai.tech/doc/20260322195114.png" width="800" />
+
+### 方式二：配置文件接入
+
+在 `config.json` 中设置 `channel_type` 为 `weixin`：
+
+```json
+{
+  "channel_type": "weixin"
+}
+```
+
+启动程序后，终端会显示二维码，使用微信扫码授权即可完成登录。
+
+<img src="https://cdn.link-ai.tech/doc/20260322195509.png" width="800" />
+
+
+<Note>
+  1. 兼容历史配置：`channel_type` 设为 `wx` 同样可以启用微信通道。
+  2. 注意微信客户端需要更新至 8.0.69 版本或以上
+</Note>
+
+## 二、使用说明
+
+微信扫码并进行授权确认后，即可完成接入并开始对话。接入微信后会在对话中创建出一个机器人助理，不会对已有账号的正常使用有任何影响。
+
+> 你可以通过搜索"微信ClawBot"随时找到这个机器人，还可以修改这个机器人的头像、备注等信息，将机器人置顶在消息列表等。
+
+<img src="https://cdn.link-ai.tech/doc/83ae8251d896219fde4803f4205205be.jpg" width="250" />
+
+
+
+## 三、登录说明
+
+### 扫码登录
+
+首次启动时，终端会显示一个二维码（有效期约 2 分钟）。使用微信扫描二维码并在手机上确认后即可完成登录。
+
+- 二维码过期后会自动刷新并重新显示
+- `requirements.txt` 中已默认包含 `qrcode` 依赖，安装后可在终端直接渲染二维码图案
+
+### 凭证保存
+
+登录成功后，凭证会自动保存至 `~/.weixin_cow_credentials.json`，下次启动时无需重新扫码。
+
+如需重新登录，删除该凭证文件后重启程序即可。
+
+### Session 过期
+
+当微信 session 过期时（errcode -14），程序会自动清除旧凭证并重新发起扫码登录，无需手动干预。
+
+## 四、功能说明
+
+| 功能 | 支持情况 |
+| --- | --- |
+| 单聊 | ✅ |
+| 文本消息 | ✅ 收发 |
+| 图片消息 | ✅ 收发 |
+| 文件消息 | ✅ 收发 |
+| 视频消息 | ✅ 收发 |
+| 语音消息 | ✅ 接收 (自带语音识别) |
diff --git a/docs/zh/cli/general.mdx b/docs/zh/cli/general.mdx
new file mode 100644
index 0000000..eb0aea3
--- /dev/null
+++ b/docs/zh/cli/general.mdx
@@ -0,0 +1,124 @@
+---
+title: 常用命令
+description: 查看状态、管理配置和上下文等常用命令
+---
+
+以下命令支持在对话中使用 `/` 前缀，也支持在终端中使用 `cow` 前缀（部分命令仅对话可用）。
+
+<Tip>
+  在 Web 控制台中输入 `/` 会自动弹出命令提示，支持键盘上下选择和 Tab 补全。
+</Tip>
+
+## help
+
+显示所有可用命令的帮助信息。
+
+```text
+/help
+```
+
+## status
+
+查看当前会话和服务的运行状态，包括进程信息、模型配置、会话消息数量和已加载技能数量。
+
+```text
+/status
+```
+
+输出示例：
+
+```
+🐮 CowAgent Status
+
+Process: PID 12345 | Running 2h 15m
+Version: 2.0.4
+Channel: web
+Model:   MiniMax-M3
+Mode:    agent
+
+Session: 12 messages | 8 skills loaded
+```
+
+## cancel
+
+中止当前会话正在运行的 Agent 任务。在 Agent 执行长时间任务（例如多轮工具调用、长流式输出）时，可随时发送 `/cancel`，Agent 会在下一次工具执行前停止。Web 端、微信、企业微信、飞书等各通道均可使用。
+
+```text
+/cancel
+```
+
+## config
+
+查看或修改运行时配置。修改后立即生效，无需重启服务。
+
+**查看所有可配置项：**
+
+```text
+/config
+```
+
+**查看单个配置项：**
+
+```text
+/config model
+```
+
+**修改配置项：**
+
+```text
+/config model deepseek-v4-flash
+```
+
+**支持修改的配置项：**
+
+| 配置项 | 说明 | 示例值 |
+| --- | --- | --- |
+| `model` | AI 模型名称 | `deepseek-v4-flash` |
+| `agent_max_context_tokens` | 最大上下文 tokens | `40000` |
+| `agent_max_context_turns` | 最大上下文记忆轮次 | `30` |
+| `agent_max_steps` | 单次任务最大决策步数 | `15` |
+| `enable_thinking` | 是否启用深度思考模式 | `true` / `false` |
+
+<Note>
+  修改 `model` 时，系统会自动匹配对应的模型调用方式。配置会写入 `config.json` 并持久保存。
+</Note>
+
+## context
+
+查看当前会话的上下文信息，包括消息数量、内容长度等统计。
+
+```text
+/context
+```
+
+**清空当前会话上下文：**
+
+```text
+/context clear
+```
+
+<Tip>
+  清空上下文后，Agent 会"忘记"之前的对话内容，适用于切换话题或释放上下文空间。
+</Tip>
+
+## logs
+
+查看最近的服务日志，默认显示最近 20 行，最多 50 行。
+
+```text
+/logs
+```
+
+**指定行数：**
+
+```text
+/logs 50
+```
+
+## version
+
+显示当前 CowAgent 版本号。
+
+```text
+/version
+```
diff --git a/docs/zh/cli/index.mdx b/docs/zh/cli/index.mdx
new file mode 100644
index 0000000..f6462ec
--- /dev/null
+++ b/docs/zh/cli/index.mdx
@@ -0,0 +1,98 @@
+---
+title: 命令总览
+description: CowAgent 命令系统 — 终端 CLI 和对话命令
+---
+
+CowAgent 提供两种命令交互方式：
+
+- **终端CLI** — 在系统终端中执行 `cow <命令>`，用于服务管理、技能管理等运维操作
+- **对话命令** — 在对话中输入 `/<命令>` 或 `cow <命令>`，用于查看状态、管理技能、调整配置等
+
+## 终端命令
+
+通过一键安装脚本部署后，`cow` 命令会自动可用。手动安装的用户需要在项目根目录下额外执行：
+
+```bash
+pip install -e .
+```
+
+安装后即可在任意位置使用 `cow` 命令：
+
+```bash
+cow help
+```
+
+输出示例：
+
+```
+CowAgent CLI
+
+Usage: cow <command>
+
+Service:
+  start     Start the CowAgent service
+  stop      Stop the CowAgent service
+  restart   Restart the CowAgent service
+  update    Update code and restart service
+  status    Show service status
+  logs      View service logs
+
+Skills:
+  skill     Manage skills (list / search / install / uninstall ...)
+
+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
+Others:
+  help      Show this help message
+  version   Show version
+```
+
+## 对话命令
+
+在 Web 控制台或任意接入渠道的对话中，支持输入以 `/` 开头的命令：
+
+| 命令 | 说明 |
+| --- | --- |
+| `/help` | 显示命令帮助 |
+| `/status` | 查看服务状态和配置 |
+| `/cancel` | 中止当前正在运行的 Agent 任务 |
+| `/config` | 查看或修改运行时配置 |
+| `/skill` | 管理技能（安装、卸载、启用、禁用等） |
+| `/memory dream [N]` | 手动触发记忆蒸馏（默认 3 天，最大 30） |
+| `/knowledge` | 查看知识库统计信息 |
+| `/knowledge list` | 查看知识库目录结构 |
+| `/knowledge on\|off` | 开启或关闭知识库 |
+| `/context` | 查看当前会话上下文信息 |
+| `/context clear` | 清空当前会话上下文 |
+| `/logs` | 查看最近日志 |
+| `/version` | 显示版本号 |
+
+<Tip>
+  对话命令中 `/start`、`/stop`、`/restart` 等服务管理命令会提示到终端中执行，因为它们涉及进程操作。
+</Tip>
+
+## 命令对照表
+
+以下是各命令在终端和对话中的可用性：
+
+| 命令 | 终端 (`cow`) | 对话 (`/`) |
+| --- | :---: | :---: |
+| help | ✓ | ✓ |
+| version | ✓ | ✓ |
+| status | ✓ | ✓ |
+| logs | ✓ | ✓ |
+| cancel | ✗ | ✓ |
+| config | ✗ | ✓ |
+| context | — | ✓ |
+| memory (子命令) | ✗ | ✓ |
+| knowledge (子命令) | ✓ | ✓ |
+| skill (子命令) | ✓ | ✓ |
+| start / stop / restart | ✓ | ✗ |
+| update | ✓ | ✗ |
+| install-browser | ✓ | ✗ |
+
+<Note>
+  `context` 在终端中仅提示到对话中使用。`config` 仅支持在对话中修改。
+</Note>
diff --git a/docs/zh/cli/memory-knowledge.mdx b/docs/zh/cli/memory-knowledge.mdx
new file mode 100644
index 0000000..3dc6713
--- /dev/null
+++ b/docs/zh/cli/memory-knowledge.mdx
@@ -0,0 +1,77 @@
+---
+title: 记忆与知识库
+description: 记忆蒸馏和知识库管理命令
+---
+
+## memory
+
+管理 Agent 的长期记忆系统。
+
+### memory dream
+
+手动触发记忆蒸馏（Deep Dream），整理近期的天级记忆，蒸馏合并到 MEMORY.md，并生成梦境日记。
+
+```text
+/memory dream [N]
+```
+
+- `N`：整理近 N 天的记忆，默认 3 天，最大 30 天
+- 蒸馏在后台异步执行，完成后会在对话中通知结果
+- 无需等待 Agent 初始化，首次对话前即可使用
+
+**示例：**
+
+```text
+/memory dream       # 整理近 3 天
+/memory dream 7     # 整理近 7 天
+/memory dream 30    # 整理近 30 天（全量）
+```
+
+蒸馏完成后，Web 端会收到带有跳转链接的通知，可直接查看更新后的 MEMORY.md 和梦境日记。
+
+<Tip>
+  系统每天 23:55 会自动执行一次蒸馏（lookback 1 天）。手动触发适用于首次部署后的历史整理，或需要立即更新记忆时使用。
+</Tip>
+
+## knowledge
+
+查看和管理个人知识库。默认显示知识库统计信息。
+
+```text
+/knowledge
+```
+
+输出示例：
+
+```
+📚 知识库
+
+- 状态：已开启
+- 页面数：12
+- 总大小：45.2 KB
+- 分类明细：
+  - concepts/: 5 篇
+  - entities/: 4 篇
+  - sources/: 3 篇
+```
+
+### knowledge list
+
+查看知识库目录树结构。
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+开启或关闭知识库。关闭后不再注入知识提示词和索引知识文件。
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  终端 CLI 中 `cow knowledge` 和 `cow knowledge list` 可用，但 `on|off` 仅支持在对话中使用（需实时生效）。
+</Note>
diff --git a/docs/zh/cli/process.mdx b/docs/zh/cli/process.mdx
new file mode 100644
index 0000000..80b10d6
--- /dev/null
+++ b/docs/zh/cli/process.mdx
@@ -0,0 +1,134 @@
+---
+title: 进程管理
+description: 使用 cow 命令管理 CowAgent 进程的启动、停止、重启、更新等操作
+---
+
+进程管理命令用于控制 CowAgent 后台进程的生命周期。这些命令仅在终端中可用。
+
+## start
+
+启动 CowAgent 服务。默认以后台进程方式运行，并自动跟踪日志输出。
+
+```bash
+cow start
+```
+
+**选项：**
+
+| 选项 | 说明 |
+| --- | --- |
+| `-f`, `--foreground` | 前台运行，不以后台守护进程方式启动 |
+| `--no-logs` | 启动后不自动跟踪日志 |
+
+## stop
+
+停止正在运行的 CowAgent 服务。
+
+```bash
+cow stop
+```
+
+## restart
+
+重启 CowAgent 服务（先停止再启动）。
+
+```bash
+cow restart
+```
+
+**选项：**
+
+| 选项 | 说明 |
+| --- | --- |
+| `--no-logs` | 重启后不自动跟踪日志 |
+
+## update
+
+更新代码并重启服务。自动执行以下流程：
+
+1. 拉取最新代码（`git pull`）
+2. 停止当前服务
+3. 更新 Python 依赖
+4. 重新安装 CLI
+5. 启动服务
+
+```bash
+cow update
+```
+
+<Warning>
+  如果 `git pull` 失败（如存在本地未提交的修改），更新会中止，服务不受影响。
+</Warning>
+
+## status
+
+查看 CowAgent 服务运行状态，包括进程信息、版本号、当前配置的模型和通道。
+
+```bash
+cow status
+```
+
+输出示例：
+
+```
+🐮 CowAgent Status
+  Status:   ● Running (PID: 12345)
+  Version:  2.0.4
+  Channel:  web
+  Model:    MiniMax-M3
+  Mode:     agent
+```
+
+## logs
+
+查看服务日志。
+
+```bash
+cow logs
+```
+
+**选项：**
+
+| 选项 | 说明 | 默认值 |
+| --- | --- | --- |
+| `-f`, `--follow` | 持续跟踪日志输出 | 否 |
+| `-n`, `--lines` | 显示最近 N 行 | 50 |
+
+示例：
+
+```bash
+# 查看最近 100 行日志
+cow logs -n 100
+
+# 持续跟踪日志
+cow logs -f
+```
+
+## install-browser
+
+安装 Playwright 和 Chromium 浏览器，用于启用 [浏览器工具](/zh/tools/browser)。
+
+```bash
+cow install-browser
+```
+
+<Tip>
+  仅在需要使用浏览器工具（如网页浏览、截图等）时才需要安装。
+</Tip>
+
+## run.sh 兼容
+
+如果未安装 Cow CLI，也可以使用 `run.sh` 脚本管理服务：
+
+| cow 命令 | run.sh 等效命令 |
+| --- | --- |
+| `cow start` | `./run.sh start` |
+| `cow stop` | `./run.sh stop` |
+| `cow restart` | `./run.sh restart` |
+| `cow update` | `./run.sh update` |
+| `cow status` | `./run.sh status` |
+| `cow logs` | `./run.sh logs` |
+
+<Note>
+  推荐使用 `cow` 命令，它提供更简洁的语法和更丰富的功能。通过一键安装脚本部署时 `cow` 命令会自动安装。
+</Note>
diff --git a/docs/zh/cli/skill.mdx b/docs/zh/cli/skill.mdx
new file mode 100644
index 0000000..3b4a8ae
--- /dev/null
+++ b/docs/zh/cli/skill.mdx
@@ -0,0 +1,218 @@
+---
+title: 技能管理
+description: 通过命令安装、卸载、启用、禁用和管理技能
+---
+
+技能管理命令用于安装、查询和管理 CowAgent 的技能。在对话中使用 `/skill <子命令>`，在终端中使用 `cow skill <子命令>`。
+
+## list
+
+列出已安装的技能及其状态。
+
+<CodeGroup>
+```text 对话
+/skill list
+```
+
+```bash 终端
+cow skill list
+```
+</CodeGroup>
+
+输出示例：
+
+```
+📦 已安装的技能 (3/4)
+
+✅ pptx
+   Use this skill any time a .pptx file is involved…
+   来源: cowhub
+
+✅ skill-creator
+   Create, install, or update skills…
+   来源: builtin
+
+⏸️ image-vision (已禁用)
+   图片理解和视觉分析
+   来源: builtin
+```
+
+**浏览技能广场**（查看 Hub 上所有可安装的技能）：
+
+<CodeGroup>
+```text 对话
+/skill list --remote
+```
+
+```bash 终端
+cow skill list --remote
+```
+</CodeGroup>
+
+**选项：**
+
+| 选项 | 说明 | 默认值 |
+| --- | --- | --- |
+| `--remote`, `-r` | 浏览 Skill Hub 远程技能列表 | 否 |
+| `--page` | 远程列表分页页码 | 1 |
+
+## search
+
+在技能广场中搜索技能。
+
+<CodeGroup>
+```text 对话
+/skill search pptx
+```
+
+```bash 终端
+cow skill search pptx
+```
+</CodeGroup>
+
+## install
+
+安装技能。通过统一的 `install` 命令，可一键安装来自 **Cow 技能广场、GitHub、ClawHub** 以及任意 URL（zip 压缩包、SKILL.md 链接）上的技能，无需手动下载和配置。
+
+**从 Cow 技能广场安装（推荐）：**
+
+<CodeGroup>
+```text 对话
+/skill install pptx
+```
+
+```bash 终端
+cow skill install pptx
+```
+</CodeGroup>
+
+**从 GitHub 安装：**
+
+<CodeGroup>
+```text 对话
+# 安装仓库中的所有技能（自动扫描包含 SKILL.md 的子目录）
+/skill install larksuite/cli
+
+# 指定子目录，只安装单个技能
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# 使用 # 指定子目录
+/skill install larksuite/cli#skills/lark-minutes
+```
+
+```bash 终端
+# 安装仓库中的所有技能（自动扫描包含 SKILL.md 的子目录）
+cow skill install larksuite/cli
+
+# 指定子目录，只安装单个技能
+cow skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+
+# 使用 # 指定子目录
+cow skill install larksuite/cli#skills/lark-minutes
+```
+</CodeGroup>
+
+支持完整的 GitHub URL 和 `owner/repo` 简写。对于 mono-repo（一个仓库中包含多个技能），不指定子目录时会自动发现并批量安装所有技能；指定子目录时只安装该目录下的技能。
+
+**从 ClawHub 安装：**
+
+<CodeGroup>
+```text 对话
+/skill install clawhub:baidu-search
+```
+
+```bash 终端
+cow skill install clawhub:baidu-search
+```
+</CodeGroup>
+
+**从 URL 安装：**
+
+<CodeGroup>
+```text 对话
+# 从 zip 压缩包安装（支持单个或批量）
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# 从 SKILL.md 链接安装
+/skill install https://example.com/path/to/SKILL.md
+```
+
+```bash 终端
+# 从 zip 压缩包安装（支持单个或批量）
+cow skill install https://cdn.link-ai.tech/skills/pptx.zip
+
+# 从 SKILL.md 链接安装
+cow skill install https://example.com/path/to/SKILL.md
+```
+</CodeGroup>
+
+支持从 zip / tar.gz 压缩包 URL 安装，解压后自动扫描包含 `SKILL.md` 的目录，支持单个或批量安装。也支持直接从 `SKILL.md` 文件链接安装，会自动解析技能名称和描述。
+
+安装成功后会显示技能名称、描述和来源，例如：
+
+```
+✅ baidu-search
+   百度搜索：使用百度搜索引擎检索信息…
+   来源: clawhub
+```
+
+## uninstall
+
+卸载已安装的技能。
+
+<CodeGroup>
+```text 对话
+/skill uninstall pptx
+```
+
+```bash 终端
+cow skill uninstall pptx
+```
+</CodeGroup>
+
+<Warning>
+  卸载操作会删除技能目录下的所有文件，此操作不可恢复。
+</Warning>
+
+## enable / disable
+
+启用或禁用技能，禁用后技能不会被 Agent 调用。
+
+<CodeGroup>
+```text 对话
+/skill enable pptx
+/skill disable pptx
+```
+
+```bash 终端
+cow skill enable pptx
+cow skill disable pptx
+```
+</CodeGroup>
+
+## info
+
+查看已安装技能的详细信息，包括 `SKILL.md` 内容预览。
+
+<CodeGroup>
+```text 对话
+/skill info pptx
+```
+
+```bash 终端
+cow skill info pptx
+```
+</CodeGroup>
+
+## 技能来源
+
+安装的技能会记录来源信息，可通过 `/skill list` 查看：
+
+| 来源标识 | 说明 |
+| --- | --- |
+| `builtin` | 项目内置技能 |
+| `cowhub` | 从 CowAgent Skill Hub 安装 |
+| `github` | 从 GitHub URL 直接安装 |
+| `clawhub` | 从 ClawHub 安装 |
+| `url` | 从 SKILL.md URL 安装 |
+| `local` | 本地创建的技能 |
diff --git a/docs/zh/guide/desktop.mdx b/docs/zh/guide/desktop.mdx
new file mode 100644
index 0000000..4e9c9e3
--- /dev/null
+++ b/docs/zh/guide/desktop.mdx
@@ -0,0 +1,51 @@
+---
+title: 桌面客户端
+description: 下载并使用 CowAgent 桌面客户端（macOS / Windows）
+---
+
+CowAgent 提供开箱即用的桌面客户端，内置 Agent 运行环境，**无需手动安装 Python 或依赖**，下载安装后即可在本地运行你的超级 AI 助理。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/desktop-chat-demo-zh.png" alt="CowAgent 桌面客户端" />
+
+## 下载安装
+
+<Card title="前往下载页" icon="download" href="https://cowagent.ai/zh/download/">
+  下载 macOS / Windows 客户端安装包
+</Card>
+
+<Tabs>
+  <Tab title="macOS">
+    1. 打开 [下载页](https://cowagent.ai/zh/download/)，根据芯片选择安装包：
+       - Apple Silicon（M1/M2/M3/M4）：下载 `arm64` 版本
+       - Intel 芯片：下载 `x64` 版本
+    2. 打开下载的 `.dmg`，将 CowAgent 拖入「应用程序」文件夹。
+    3. 从启动台或应用程序中打开 CowAgent 即可。
+  </Tab>
+  <Tab title="Windows">
+    1. 打开 [下载页](https://cowagent.ai/zh/download/)，下载 Windows 安装包（`.exe`）。
+    2. 双击运行安装程序，按提示完成安装（可自定义安装目录）。
+    3. 从桌面或开始菜单打开 CowAgent 即可。
+  </Tab>
+</Tabs>
+
+## 自动更新
+
+桌面客户端内置自动更新能力。有新版本时会自动检测并提示，你也可以在应用左下角菜单中手动「检查更新」，一键下载并重启完成升级。
+
+## 与命令行部署的区别
+
+- **桌面客户端**：适合个人用户开箱即用，无需安装任何依赖，图形界面操作，支持自动更新。
+- **命令行部署**：源码运行方式，适合开发者在本地或服务器部署，方便扩展功能，可定制性更强，详见 [一键安装](/zh/guide/quick-start)。
+
+## 通过浏览器访问
+
+桌面客户端启动后会在本机监听 `9876` 端口，其后端与 Web 控制台完全一致。因此在打开客户端的同时，也可以直接用浏览器访问 `http://localhost:9876`，获得与客户端界面一致的完整体验。
+
+## 本地数据存储
+
+桌面客户端的所有数据都保存在本机：
+
+- **配置文件**：位于用户目录下的 `~/.cow`，包含 `config.json`（模型密钥、通道等配置）以及日志、缓存等运行数据。
+- **工作空间**：默认位于 `~/cow`，用于存放对话记录、知识库、记忆、技能、定时任务等 Agent 产生的文件。
+
+卸载客户端不会自动删除这两个目录，重装后数据依然保留。如需彻底清理或迁移到其他设备，手动备份或删除对应目录即可。
diff --git a/docs/zh/guide/manual-install.mdx b/docs/zh/guide/manual-install.mdx
new file mode 100644
index 0000000..e6b81b4
--- /dev/null
+++ b/docs/zh/guide/manual-install.mdx
@@ -0,0 +1,182 @@
+---
+title: 手动安装
+description: 手动部署 CowAgent（源码 / Docker）
+---
+
+## 源码部署
+
+### 1. 克隆项目代码
+
+```bash
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
+```
+
+<Tip>
+  若遇到网络问题可使用国内仓库地址：https://gitee.com/zhayujie/CowAgent
+</Tip>
+
+### 2. 安装依赖
+
+核心依赖（必选）：
+
+```bash
+pip3 install -r requirements.txt
+```
+
+扩展依赖（可选，建议安装）：
+
+```bash
+pip3 install -r requirements-optional.txt
+```
+
+> 国内网络可使用镜像源加速：`pip3 install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple`
+
+### 3. 安装 Cow CLI
+
+安装命令行工具，用于管理服务和技能：
+
+```bash
+pip3 install -e .
+```
+
+安装后即可使用 `cow` 命令：
+
+```bash
+cow help
+```
+
+<Note>
+  此步骤为推荐操作。安装后可以使用 `cow start`、`cow stop`、`cow update` 等命令管理服务，也可以使用 `cow skill` 管理技能。如果不安装 CLI，可以使用 `./run.sh` 或 `python3 app.py` 运行。
+</Note>
+
+### 3.1 安装浏览器工具（可选）
+
+如需使用浏览器工具（控制浏览器访问网页、填写表单等），运行：
+
+```bash
+cow install-browser
+```
+
+该命令会自动安装 Playwright 和 Chromium 浏览器。详细说明参考 [浏览器工具文档](/zh/tools/browser)。
+
+<Note>
+  浏览器工具依赖较重（~300MB），如不需要可跳过，不影响其他功能正常使用。
+</Note>
+
+### 4. 配置
+
+复制配置文件模板并编辑：
+
+```bash
+cp config-template.json config.json
+```
+
+在 `config.json` 中填写模型 API Key 和通道类型等配置，详细说明参考各 [模型文档](/zh/models/minimax)。
+
+### 5. 运行
+
+**使用 Cow CLI 运行（推荐）：**
+
+```bash
+cow start
+```
+
+**或者本地前台运行：**
+
+```bash
+python3 app.py
+```
+
+运行后默认启动 Web 控制台，访问 `http://localhost:9899` 开始对话和管理Agent。
+
+**服务器后台运行（不使用 CLI 时）：**
+
+```bash
+nohup python3 app.py & tail -f nohup.out
+```
+
+<Tip>
+  **服务器公网访问 Web 控制台**：默认 `web_host` 仅监听 `127.0.0.1`（本机访问），需公网访问时请在 `config.json` 中将 `web_host` 设为 `0.0.0.0`，同时强烈建议设置 `web_password` 启用鉴权。此外还需在防火墙/安全组中放行 `9899` 端口，建议仅对指定 IP 开放以保证安全。
+</Tip>
+
+## Docker 部署
+
+使用 Docker 部署无需下载源码和安装依赖。Agent模式下更推荐使用源码部署以获得更多系统访问能力。
+
+<Note>
+  需要安装 [Docker](https://docs.docker.com/engine/install/) 和 docker-compose。
+</Note>
+
+**1. 下载配置文件**
+
+```bash
+curl -O https://cdn.link-ai.tech/code/cow/docker-compose.yml
+```
+
+打开 `docker-compose.yml` 填写所需配置。
+
+**2. 启动容器**
+
+```bash
+sudo docker compose up -d
+```
+
+**3. 查看日志**
+
+```bash
+sudo docker logs -f chatgpt-on-wechat
+```
+
+<Tip>
+  **Docker 公网访问 Web 控制台**：在 `docker-compose.yml` 中将 `WEB_HOST` 设为 `0.0.0.0`（容器内默认绑定 `127.0.0.1` 无法从宿主机外访问），同时强烈建议设置 `WEB_PASSWORD` 启用鉴权。此外需确保 `9899` 端口正确映射到宿主机，并在防火墙/安全组放行该端口。
+</Tip>
+
+## 核心配置项
+
+<Tabs>
+  <Tab title="源码部署（config.json）">
+    ```json
+    {
+      "channel_type": "web",
+      "model": "deepseek-v4-flash",
+      "deepseek_api_key": "",
+      "agent": true,
+      "agent_workspace": "~/cow",
+      "agent_max_context_tokens": 40000,
+      "agent_max_context_turns": 30,
+      "agent_max_steps": 15,
+      "cow_lang": "auto"
+    }
+    ```
+  </Tab>
+  <Tab title="Docker 部署（docker-compose.yml）">
+    ```yaml
+    environment:
+      CHANNEL_TYPE: 'web'
+      MODEL: 'deepseek-v4-flash'
+      DEEPSEEK_API_KEY: 'your-api-key'
+      DEEPSEEK_API_BASE: 'https://api.deepseek.com/v1'
+      AGENT: 'True'
+      AGENT_MAX_CONTEXT_TOKENS: 40000
+      AGENT_MAX_CONTEXT_TURNS: 30
+      AGENT_MAX_STEPS: 15
+      COW_LANG: 'auto'
+    ```
+  </Tab>
+</Tabs>
+
+| 参数 | 环境变量 | 说明 | 默认值 |
+| --- | --- | --- | --- |
+| `channel_type` | `CHANNEL_TYPE` | 接入渠道类型 | `web` |
+| `model` | `MODEL` | 模型名称 | `deepseek-v4-flash` |
+| `agent` | `AGENT` | 是否启用 Agent 模式 | `true` |
+| `agent_workspace` | - | Agent 工作空间路径 | `~/cow` |
+| `agent_max_context_tokens` | `AGENT_MAX_CONTEXT_TOKENS` | 最大上下文 tokens | `40000` |
+| `agent_max_context_turns` | `AGENT_MAX_CONTEXT_TURNS` | 最大上下文记忆轮次 | `30` |
+| `agent_max_steps` | `AGENT_MAX_STEPS` | 单次任务最大决策步数 | `15` |
+| `cow_lang` | `COW_LANG` | 界面、命令文案、系统提示词等的语言，`auto` 自动检测，可设为 `zh` / `en` | `auto` |
+
+<Tip>
+  全部配置项可在项目 [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py) 文件中查看。Docker 部署时，配置项名称需转为大写环境变量格式。
+</Tip>
diff --git a/docs/zh/guide/quick-start.mdx b/docs/zh/guide/quick-start.mdx
new file mode 100644
index 0000000..735225e
--- /dev/null
+++ b/docs/zh/guide/quick-start.mdx
@@ -0,0 +1,58 @@
+---
+title: 一键安装
+description: 使用脚本一键安装和管理 CowAgent
+---
+
+项目提供了一键安装、配置、启动、管理程序的脚本，推荐使用脚本快速运行。
+
+支持 Linux、macOS、Windows 操作系统，需安装 Python 3.7 ~ 3.13（推荐 3.9）。
+
+## 安装命令
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+脚本自动执行以下流程：
+
+1. 检查 Python 环境（需要 Python 3.7+）
+2. 安装必要工具（git、curl 等）
+3. 克隆项目代码到 `~/CowAgent`
+4. 安装 Python 依赖和 Cow CLI
+5. 引导配置 AI 模型和通信渠道
+6. 启动服务
+
+运行后默认启动 Web 控制台，访问 `http://localhost:9899` 开始对话和管理Agent。
+
+<Note>
+  **服务器部署需要公网访问控制台时**，请在 `config.json` 中将 `web_host` 设为 `0.0.0.0`（默认仅监听 `127.0.0.1` 本机访问），同时强烈建议设置 `web_password` 启用鉴权。然后通过 `http://<server-ip>:9899` 访问，并确保防火墙/安全组放行 `9899` 端口。
+</Note>
+
+## 管理命令
+
+安装完成后，使用 `cow` CLI 管理服务：
+
+| 命令 | 说明 |
+| --- | --- |
+| `cow start` | 启动服务 |
+| `cow stop` | 停止服务 |
+| `cow restart` | 重启服务 |
+| `cow status` | 查看运行状态 |
+| `cow logs` | 查看实时日志 |
+| `cow update` | 更新代码并重启 |
+| `cow install-browser` | 安装浏览器工具依赖 |
+
+更多命令和用法参考 [命令文档](/zh/cli/index)。
+
+<Note>
+  如果 `cow` 命令不可用，也可以使用 `./run.sh <命令>`（Linux/macOS）或 `.\scripts\run.ps1 <命令>`（Windows）作为替代，功能等效。
+</Note>
diff --git a/docs/zh/guide/upgrade.mdx b/docs/zh/guide/upgrade.mdx
new file mode 100644
index 0000000..71ff72f
--- /dev/null
+++ b/docs/zh/guide/upgrade.mdx
@@ -0,0 +1,67 @@
+---
+title: 更新升级
+description: CowAgent 的升级方式说明
+---
+
+## 命令升级（推荐）
+
+使用 `cow update` 一键完成代码更新和服务重启：
+
+```bash
+cow update
+```
+
+该命令会自动完成以下流程：
+
+1. 拉取最新代码（`git pull`）
+2. 停止当前服务
+3. 更新 Python 依赖
+4. 重新安装 CLI
+5. 启动服务
+
+<Note>
+  如果未安装 Cow CLI，也可以使用 `./run.sh update` 完成相同操作。
+</Note>
+
+## 手动升级
+
+在项目根目录下执行：
+
+```bash
+git pull
+pip3 install -r requirements.txt
+pip3 install -e .
+```
+
+更新完成后重启服务：
+
+```bash
+# 使用 Cow CLI (推荐)
+cow restart
+
+# 或使用 run.sh
+./run.sh restart
+
+# 或使用 nohup 直接运行
+kill $(ps -ef | grep app.py | grep -v grep | awk '{print $2}')
+nohup python3 app.py & tail -f nohup.out
+```
+
+## Docker 升级
+
+在 `docker-compose.yml` 所在目录下执行：
+
+```bash
+sudo docker compose pull
+sudo docker compose up -d
+```
+
+<Tip>
+  升级前建议备份 `config.json` 配置文件。Docker 环境下如需保留数据，可通过 volume 挂载持久化工作空间目录。
+</Tip>
+
+## 客户端升级
+
+[桌面客户端](/zh/guide/desktop)内置自动更新能力，有新版本时会自动检查并提示，一键即可下载并重启完成升级。
+
+你也可以随时前往[下载页](https://cowagent.ai/zh/download/)手动下载最新版本安装。
diff --git a/docs/zh/intro/architecture.mdx b/docs/zh/intro/architecture.mdx
new file mode 100644
index 0000000..6e3899b
--- /dev/null
+++ b/docs/zh/intro/architecture.mdx
@@ -0,0 +1,89 @@
+---
+title: 项目架构
+description: CowAgent 2.0 的系统架构和核心设计
+---
+
+CowAgent 2.0 从简单的聊天机器人全面升级为超级智能助理，采用 Agent 架构设计，具备自主思考、规划任务、长期记忆和技能扩展等能力。
+
+## 系统架构
+
+CowAgent 的整体架构由以下核心模块组成：
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/architecture/zh/architecture.jpg" alt="CowAgent Architecture" />
+
+| 模块 | 说明 |
+| --- | --- |
+| **Plan** | 理解用户意图，将复杂任务分解为多步骤计划，循环调用工具直到完成目标 |
+| **Memory** | 自动将重要信息持久化为核心记忆和日级记忆，支持关键词和向量混合检索，跨会话保持上下文连续性 |
+| **Knowledge** | 以主题维度组织结构化知识，Agent 自主整理有价值信息为 Markdown 页面，维护索引和交叉引用，构建持续增长的知识网络 |
+| **Evolution** | 对话空闲后在隔离环境中自动复盘，优化技能、处理未完成事项、补全记忆与知识，让 Agent 在使用中持续成长 |
+| **Tools** | Agent 访问操作系统资源的核心能力，内置文件读写、终端执行、浏览器操作、定时调度、记忆检索、联网搜索等 10+ 种工具 |
+| **Skills** | 加载和管理 Skills，支持从 Skill Hub、GitHub 等一键安装，或通过对话创建自定义技能 |
+| **Models** | 模型层，统一接入 OpenAI、Claude、Gemini、DeepSeek、MiniMax、GLM、Qwen 等国内外主流大语言模型 |
+| **Channels** | 消息通道层，负责接收和发送消息，支持 Web 控制台、微信、飞书、钉钉、企微、公众号等，统一消息协议 |
+| **CLI** | 命令行系统，提供终端命令（`cow`）和对话命令（`/`），支持进程管理、技能安装、配置修改、知识库管理等操作 |
+
+## Agent 模式
+
+启用 Agent 模式后，CowAgent 会以自主智能体的方式运行，核心工作流如下：
+
+1. **接收消息** — 通过通道接收用户输入
+2. **理解意图** — 分析任务需求和上下文
+3. **规划任务** — 将复杂任务分解为多个步骤
+4. **调用工具** — 选择合适的工具执行每个步骤
+5. **记忆与知识更新** — 将重要信息存入长期记忆，将结构化知识整理至知识库
+6. **返回结果** — 将执行结果发送回用户
+
+## 工作空间
+
+Agent 的工作空间默认位于 `~/cow` 目录，用于存储系统提示词、记忆文件、技能文件等：
+
+```
+~/cow/
+├── SYSTEM.md          # Agent system prompt
+├── USER.md            # User profile
+├── MEMORY.md          # Core memory
+├── memory/            # Long-term memory storage
+│   └── YYYY-MM-DD.md  # Daily memory
+├── knowledge/         # Personal knowledge base
+│   ├── index.md       # Knowledge index
+│   └── <category>/    # Topic-based pages
+└── skills/            # Custom skills
+    ├── skill-1/
+    └── skill-2/
+```
+
+秘钥文件单独存储在 `~/.cow` 目录（出于安全考虑）：
+
+```
+~/.cow/
+└── .env               # Secret keys for skills
+```
+
+## 核心配置
+
+在 `config.json` 中配置 Agent 模式的核心参数：
+
+```json
+{
+  "agent": true,
+  "agent_workspace": "~/cow",
+  "agent_max_context_tokens": 40000,
+  "agent_max_context_turns": 30,
+  "agent_max_steps": 15,
+  "enable_thinking": false,
+  "cow_lang": "auto"
+}
+```
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `agent` | 是否启用 Agent 模式 | `true` |
+| `agent_workspace` | 工作空间路径 | `~/cow` |
+| `agent_max_context_tokens` | 最大上下文 token 数 | `50000` |
+| `agent_max_context_turns` | 最大上下文记忆轮次 | `20` |
+| `agent_max_steps` | 单次任务最大决策步数 | `20` |
+| `enable_thinking` | 是否启用深度思考模式 | `false` |
+| `knowledge` | 是否启用个人知识库 | `true` |
+| `self_evolution_enabled` | 是否启用自主进化 | `false` |
+| `cow_lang` | 界面、命令文案、系统提示词等的语言，`auto` 自动检测，可设为 `zh` / `en` | `auto` |
diff --git a/docs/zh/intro/features.mdx b/docs/zh/intro/features.mdx
new file mode 100644
index 0000000..5e8d1b4
--- /dev/null
+++ b/docs/zh/intro/features.mdx
@@ -0,0 +1,148 @@
+---
+title: 功能介绍
+description: CowAgent 长期记忆、个人知识库、任务规划、技能系统、CLI 命令、浏览器工具详细说明
+---
+
+## 1. 长期记忆
+
+> 记忆系统让 Agent 能够长期记住重要信息，采用三层记忆流转架构：对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期），形成完整的记忆生命周期。
+
+第一次启动 Agent 时，Agent 会主动询问关键信息，并记录至工作空间（默认 `~/cow`）中的智能体设定、用户身份、记忆文件中。
+
+在后续的长期对话中，Agent 会在需要时智能记录或检索记忆，并对自身设定、用户偏好、记忆文件等进行不断更新。每日自动执行 **梦境蒸馏（Deep Dream）**，将分散的天级记忆整合为精炼的长期记忆，同时生成叙事风格的梦境日记。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+在此基础上，**自主进化（Self-Evolution）** 让 Agent 在使用中持续成长：对话空闲后自动复盘，优化技能、处理遗留任务、补全记忆与知识，仅在确有改动时简短告知，且每次改动可随时撤销。
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-evolution-demo-zh.png" width="800" />
+</Frame>
+
+详细说明请参考 [长期记忆](/zh/memory)、[梦境蒸馏](/zh/memory/deep-dream) 和 [自主进化](/zh/memory/self-evolution)。
+
+## 2. 个人知识库
+
+> 知识库系统让 Agent 能够持续积累和组织结构化知识。与按时间线记录的记忆不同，知识库以主题为维度，将文章、对话洞察、学习材料等整理为互相关联的 Markdown 页面，形成持续增长的知识网络。
+
+Agent 会在对话中自动将有价值的信息整理为知识页面，维护交叉引用和索引，通过 Web 控制台可浏览文档和查看知识图谱。知识库存储在工作空间的 `~/cow/knowledge/` 目录下。
+
+- **自动整理**：Agent 在对话中自主提取和整理结构化知识，维护索引和交叉引用
+- **知识图谱**：基于页面间的交叉引用自动构建知识图谱，Web 控制台提供可视化关系图浏览
+- **对话联动**：Agent 回复中引用的知识文档链接可在 Web 控制台中直接点击跳转查看
+- **CLI 管理**：通过 `/knowledge` 命令查看统计、浏览目录，通过 `/knowledge on|off` 开关功能
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+详细说明请参考 [个人知识库](/zh/knowledge)。
+
+## 3. 任务规划和工具调用
+
+工具是 Agent 访问操作系统资源的核心，Agent 会根据任务需求智能选择和调用工具，完成文件读写、命令执行、定时任务等各类操作。内置工具的实现在项目的 `agent/tools/` 目录下。
+
+**主要工具：** 文件读写编辑、Bash 终端、浏览器操作、文件发送、定时调度、记忆搜索、联网搜索、环境配置等。
+
+### 3.1 终端和文件访问
+
+针对操作系统的终端和文件的访问能力，是最基础和核心的工具，其他很多工具或技能都是基于此进行扩展。用户可通过手机端与 Agent 交互，操作个人电脑或服务器上的资源：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+### 3.2 编程能力
+
+基于编程能力和系统访问能力，Agent 可以实现从信息搜索、图片等素材生成、编码、测试、部署、Nginx 配置修改、发布的 **Vibecoding 全流程**，通过手机端简单的一句命令完成应用的快速 demo：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
+</Frame>
+
+### 3.3 定时任务
+
+基于 `scheduler` 工具实现动态定时任务，支持**一次性任务、固定时间间隔、Cron 表达式**三种形式，任务触发可选择**固定消息发送**或 **Agent 动态任务**执行两种模式：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+### 3.4 浏览器操作
+
+内置 `browser` 工具，Agent 可控制浏览器访问网页、填写表单、点击元素、截图，支持动态 JS 渲染页面。运行 `cow install-browser` 一键安装，自动适配服务器（无头模式）和桌面环境：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260401115728.png" width="750" />
+</Frame>
+
+### 3.5 环境变量管理
+
+技能所需的秘钥存储在环境变量文件中，由 `env_config` 工具进行管理，你可以通过对话的方式更新秘钥，工具内置安全保护和脱敏策略：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
+
+## 4. 技能系统
+
+技能系统为 Agent 提供无限的扩展性，每个 Skill 由说明文件、运行脚本（可选）、资源（可选）组成，描述如何完成特定类型的任务。通过 Skill 可以让 Agent 遵循说明完成复杂流程、调用各类工具或对接第三方系统。
+
+- [Skill Hub](https://skills.cowagent.ai/)：开放的技能广场，汇集官方推荐、社区贡献和第三方技能，支持一键安装。
+- **内置技能：** 在项目的 `skills/` 目录下，包含技能创造器、图像识别、LinkAI 智能体、网页抓取等。内置 Skill 根据依赖条件（API Key、系统命令等）自动判断是否启用。
+- **自定义技能：** 由用户通过对话创建，存放在工作空间中（`~/cow/skills/`），可实现任何复杂的业务流程和第三方系统对接。
+
+安装技能：`/skill install <名称>` 或 `cow skill install <名称>`，支持从 Skill Hub、GitHub、ClawHub、URL 等来源安装。
+
+### 4.1 创建技能
+
+通过 `skill-creator` 技能可以通过对话的方式快速创建技能。你可以让 Agent 将某个工作流程固化为技能，或者把任意接口文档和示例发送给 Agent，让他直接完成对接：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+### 4.2 搜索和图像识别
+
+- **联网搜索：** 内置 `web_search` 工具，支持多种搜索引擎，配置 `BOCHA_API_KEY` 或 `LINKAI_API_KEY` 后启用。
+- **图像识别：** 内置 `openai-image-vision` 技能，可使用 `gpt-4.1-mini`、`gpt-4.1` 等模型，依赖 `OPENAI_API_KEY`。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+### 4.3 技能广场
+
+访问 [skills.cowagent.ai](https://skills.cowagent.ai/) 浏览所有可用技能，或在对话中执行：
+
+```text
+/skill list --remote          # 浏览技能广场
+/skill search <关键词>         # 搜索技能
+/skill install <名称>          # 一键安装
+```
+
+同时还支持安装Github、ClawHub、LinkAI等第三方平台上的所有技能，详情查看 [技能安装](/zh/skills/install)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+
+## 5. CLI 命令系统
+
+CowAgent 提供两种命令交互方式，覆盖服务管理、技能安装、配置调整等日常运维操作：
+
+- **终端 CLI：** 在系统终端执行 `cow <命令>`，支持 `start`、`stop`、`restart`、`update`、`status`、`logs`、`skill` 等
+- **对话命令：** 在对话中输入 `/<命令>`，Web 控制台输入 `/` 可弹出指令菜单快速选择
+
+```bash
+cow start              # 启动服务
+cow stop               # 停止服务
+cow update             # 更新并重启
+cow skill install pptx # 安装技能
+cow install-browser    # 安装浏览器工具
+```
+
+详细命令参考 [命令总览](https://docs.cowagent.ai/cli)。
+
+<img src="https://cdn.link-ai.tech/doc/20260401114549.png" width="750" />
diff --git a/docs/zh/intro/index.mdx b/docs/zh/intro/index.mdx
new file mode 100644
index 0000000..dca75bb
--- /dev/null
+++ b/docs/zh/intro/index.mdx
@@ -0,0 +1,89 @@
+---
+title: 项目介绍
+description: CowAgent - 基于大模型的超级AI助理
+---
+
+<div align="center">
+  <img src="https://cdn.link-ai.tech/doc/78c5dd674e2c828642ecc0406669fed7.png" alt="CowAgent" width="450px"/>
+</div>
+
+**CowAgent** 是基于大模型的超级AI助理，能够主动思考和任务规划、操作计算机和外部资源、创造和执行Skills、拥有长期记忆和知识库并不断成长。
+
+CowAgent 支持灵活切换多种模型，能处理文本、语音、图片、文件等多模态消息，可接入微信、飞书、钉钉、企业微信应用、微信公众号、网页中使用，7×24小时运行于你的个人电脑或服务器中。
+
+<CardGroup cols={2}>
+  <Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
+    开源代码仓库，欢迎 Star 和贡献
+  </Card>
+  <Card title="免部署在线体验" icon="cloud" href="https://link-ai.tech/cowagent/create">
+    无需安装，立即在线体验 CowAgent
+  </Card>
+</CardGroup>
+
+## 核心能力
+
+<CardGroup cols={2}>
+  <Card title="复杂任务规划" icon="brain" href="/zh/intro/architecture">
+    能够理解复杂任务并自主规划执行，持续思考和调用各类工具和技能直到完成目标。
+  </Card>
+  <Card title="长期记忆" icon="database" href="/zh/memory">
+    三层记忆流转（上下文→天级记忆→全局记忆），每日梦境蒸馏整理，支持关键词及向量检索。
+  </Card>
+  <Card title="个人知识库" icon="book" href="/zh/knowledge">
+    自动整理结构化知识，支持知识图谱可视化，通过交叉引用构建持续增长的知识网络。
+  </Card>
+  <Card title="自主进化" icon="seedling" href="/zh/memory/self-evolution">
+    对话结束后自动复盘，优化技能、处理遗留任务、沉淀记忆与知识，让 Agent 在使用中持续成长。
+  </Card>
+  <Card title="技能系统" icon="puzzle-piece" href="/zh/skills/index">
+    实现了Skills创建和运行的引擎，内置多种技能，并支持通过自然语言对话完成自定义Skills开发。
+  </Card>
+  <Card title="工具系统" icon="wrench" href="/zh/tools/index">
+    内置文件读写、终端执行、浏览器操作、定时任务、消息发送等工具，Agent 可自主调用工具完成复杂任务。
+  </Card>
+  <Card title="命令系统" icon="terminal" href="/zh/cli/index">
+    提供终端 CLI 和对话中的命令，支持进程管理、技能安装、配置修改、上下文查看等常用操作。
+  </Card>
+  <Card title="多模型支持" icon="microchip" href="/zh/models/index">
+    支持 OpenAI, Claude, Gemini, DeepSeek, MiniMax, GLM, Qwen, Kimi, Doubao 等国内外主流模型厂商。
+  </Card>
+  <Card title="多通道接入" icon="server" href="/zh/channels/weixin">
+    支持运行在本地计算机或服务器，可集成到微信、网页、飞书、钉钉、微信公众号、企业微信应用中使用。
+  </Card>
+</CardGroup>
+
+## 快速体验
+
+在终端执行以下命令，即可一键安装、配置、启动 CowAgent：
+
+<Tabs>
+  <Tab title="Linux / macOS">
+    ```bash
+    bash <(curl -fsSL https://cdn.link-ai.tech/code/cow/run.sh)
+    ```
+  </Tab>
+  <Tab title="Windows (PowerShell)">
+    ```powershell
+    irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    ```
+  </Tab>
+</Tabs>
+
+运行后默认会启动 Web 控制台，通过访问 `http://localhost:9899` 可以在网页端进行对话、配置、应用通道接入等操作。
+
+也可以使用桌面客户端（macOS / Windows），内置 Agent 运行环境，[下载安装](https://cowagent.ai/zh/download/)后开箱即用。
+
+<CardGroup cols={2}>
+  <Card title="快速开始" icon="rocket" href="/zh/guide/quick-start">
+    查看完整的安装和运行指南
+  </Card>
+  <Card title="项目架构" icon="sitemap" href="/zh/intro/architecture">
+    了解 CowAgent 的系统架构设计
+  </Card>
+</CardGroup>
+
+## 社区
+
+添加小助手微信加入开源项目交流群：
+
+<img width="140" src="https://img-1317903499.cos.ap-guangzhou.myqcloud.com/docs/open-community.png" />
diff --git a/docs/zh/knowledge/index.mdx b/docs/zh/knowledge/index.mdx
new file mode 100644
index 0000000..4f9aa79
--- /dev/null
+++ b/docs/zh/knowledge/index.mdx
@@ -0,0 +1,96 @@
+---
+title: 个人知识库
+description: CowAgent 的个人知识库系统 — 结构化知识沉淀、自动整理与知识图谱
+---
+
+个人知识库是 Agent 的长期结构化知识存储，保存在工作空间的 `knowledge/` 目录下。与按时间线组织的记忆不同，知识库以主题为维度，将用户分享的文章、对话中的洞察、学习材料等整理为互相关联的 Markdown 页面，形成可持续增长的知识网络。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+## 核心概念
+
+### 知识 vs 记忆
+
+| 维度 | 知识库（knowledge/） | 长期记忆（memory/） |
+| --- | --- | --- |
+| 组织方式 | 按主题分类、互相关联 | 按时间线、日期文件 |
+| 写入方式 | Agent 主动整理结构化内容 | 上下文裁剪时自动摘要 |
+| 内容特点 | 提炼后的结构化知识 | 原始对话摘要 |
+| 典型用途 | 学习笔记、技术文档、项目知识 | 对话历史、事件记录 |
+
+### 目录结构
+
+```
+~/cow/knowledge/
+├── index.md          # 知识索引，所有页面的入口
+├── log.md            # 变更日志，记录每次写入
+├── concepts/         # 概念类知识
+│   └── machine-learning.md
+├── entities/         # 实体类知识（人物、组织、工具）
+│   └── openai.md
+└── sources/          # 来源类知识（文章、论文）
+    └── llm-wiki.md
+```
+
+目录结构是灵活的 — Agent 会根据实际内容自动创建合适的分类目录。用户也可以通过对话的方式自定义目录组织方式。
+
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413110104.png" width="800" />
+</Frame>
+
+## 自动整理
+
+知识库的写入是 Agent 的自主行为，在以下场景中触发：
+
+- **用户分享文章或文档** — Agent 自动提取关键信息，创建结构化知识页面
+- **对话产生有价值的结论** — Agent 将洞察整理为知识页面，并与已有知识建立关联
+- **用户主动要求整理** — 用户可以通过对话指导 Agent 组织和更新知识
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/17aad553d3e9e428c52ff9dc31726fda.png" width="800" />
+</Frame>
+
+
+每个知识页面都包含与其他页面的交叉引用链接，逐步构建起一个知识图谱。
+
+## 知识检索
+
+Agent 在对话中可以通过以下方式检索知识：
+
+- **索引查阅** — 通过 `knowledge/index.md` 快速定位相关知识页面
+- **语义搜索** — 通过 `memory_search` 工具对知识库内容进行语义检索
+- **直接读取** — 通过 `memory_get` 工具读取特定知识文件
+
+## Web 控制台
+
+Web 控制台提供了专用的「知识」模块，支持：
+
+- **文档浏览** — 树状目录结构，可搜索、可折叠，点击查看文档内容
+- **知识图谱** — 可视化展示知识之间的关联关系，节点可直接跳转至文档
+- **对话联动** — Agent 回复中引用的知识文档链接可直接点击跳转查看
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105402.png" width="800" />
+</Frame>
+
+
+## CLI 命令
+
+通过 `/knowledge` 命令管理知识库：
+
+| 命令 | 说明 |
+| --- | --- |
+| `/knowledge` | 显示知识库统计信息 |
+| `/knowledge list` | 以树状结构显示文件目录 |
+| `/knowledge on` | 开启知识库功能 |
+| `/knowledge off` | 关闭知识库功能 |
+
+## 相关配置
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `knowledge` | 是否启用个人知识库功能 | `true` |
+| `agent_workspace` | 工作空间路径，知识库存储在此目录的 `knowledge/` 子目录下 | `~/cow` |
diff --git a/docs/zh/memory/context.mdx b/docs/zh/memory/context.mdx
new file mode 100644
index 0000000..3d358f9
--- /dev/null
+++ b/docs/zh/memory/context.mdx
@@ -0,0 +1,81 @@
+---
+title: 短期记忆
+description: 对话上下文 — 消息管理、压缩策略和上下文操作
+---
+
+对话上下文是 Agent 的短期记忆，包含当前会话中的所有消息（用户输入、Agent 回复、工具调用及结果）。合理管理上下文对于 Agent 的推理质量和成本控制至关重要。
+
+## 上下文结构
+
+每一轮对话由以下消息组成：
+
+```
+用户消息 → Agent 思考 → 工具调用 → 工具结果 → ... → Agent 最终回复
+```
+
+一轮中可能包含多次工具调用（Agent 的决策步数由 `agent_max_steps` 控制），所有工具调用和结果都会保留在上下文中，直到被压缩或裁剪。
+
+## 关键配置
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `agent_max_context_tokens` | 上下文最大 token 预算 | `50000` |
+| `agent_max_context_turns` | 上下文最大对话轮次 | `20` |
+| `agent_max_steps` | 单轮对话最大决策步数（工具调用次数） | `15` |
+
+可通过 `config.json` 或对话中的 `/config` 命令修改。
+
+## 压缩策略
+
+当上下文超出限制时，系统会自动执行压缩以释放空间。整个过程分为多个阶段：
+
+### 1. 工具结果截断
+
+在每次决策循环开始前，系统会检查历史轮次中的工具调用结果。超过 **20000 字符** 的工具结果会被截断，仅保留首尾内容和截断说明。当前轮次的工具结果不受影响。
+
+### 2. 轮次裁剪
+
+当对话轮次超过 `agent_max_context_turns` 时：
+
+- 裁剪 **最早一半** 的完整轮次（保证工具调用链的完整性）
+- 被裁剪的消息会通过 LLM 总结后**写入当天的日级记忆文件**
+- LLM 摘要完成后，同时将摘要**注入到保留消息的第一条用户消息开头**，帮助模型在后续对话中保持上下文连贯性
+- 摘要注入在后台异步完成，不阻塞当前回复；注入的摘要在下一轮对话时生效
+
+### 3. Token 预算裁剪
+
+裁剪轮次后，如果 token 数仍超出预算：
+
+- **轮次 < 5 时**：对所有轮次进行**文本压缩** — 每轮只保留第一条用户文本和最后一条 Agent 回复，去掉中间的工具调用链
+- **轮次 ≥ 5 时**：再次裁剪**前半轮次**，被丢弃内容同样写入记忆并注入上下文摘要
+
+### 4. 溢出应急处理
+
+当模型 API 返回上下文溢出错误时：
+
+1. 先将当前所有消息总结写入记忆
+2. 执行激进裁剪（工具结果限制 10K 字符、用户文本限制 10K、最多保留 5 轮）
+3. 如果仍然溢出，清空整个对话上下文
+
+## 会话持久化
+
+对话消息会持久化到本地数据库，服务重启后自动恢复。恢复策略：
+
+- 恢复最近的 **`max(3, max_context_turns / 6)`** 轮对话
+- 只保留每轮的**用户文本和 Agent 最终回复**，不恢复中间工具调用链
+- 超过 **30 天**的历史会话自动清理
+
+## 操作命令
+
+在对话中可以使用以下命令管理上下文：
+
+| 命令 | 说明 |
+| --- | --- |
+| `/context` | 查看当前上下文统计（消息数、角色分布、总字符数） |
+| `/context clear` | 清空当前会话上下文 |
+| `/config agent_max_context_tokens 80000` | 调整上下文 token 预算 |
+| `/config agent_max_context_turns 30` | 调整上下文轮次上限 |
+
+<Tip>
+  清空上下文后，Agent 会"忘记"之前的对话内容。被裁剪和清空的内容如果已经写入长期记忆，仍可通过记忆检索找回。
+</Tip>
diff --git a/docs/zh/memory/deep-dream.mdx b/docs/zh/memory/deep-dream.mdx
new file mode 100644
index 0000000..e96f957
--- /dev/null
+++ b/docs/zh/memory/deep-dream.mdx
@@ -0,0 +1,110 @@
+---
+title: 梦境蒸馏
+description: Deep Dream — 从对话到永久记忆的自动蒸馏机制
+---
+
+梦境蒸馏（Deep Dream）是 CowAgent 记忆系统的核心整理机制，负责将分散的天级记忆蒸馏为精炼的长期记忆，并生成梦境日记。
+
+## 记忆流转
+
+CowAgent 的记忆从短期到长期经历三个阶段：
+
+```
+对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期）
+```
+
+### 1. 对话 → 天级记忆
+
+当对话上下文被裁剪或每日定时总结时，系统使用 LLM 将对话内容摘要为关键事件，写入当天的天级记忆文件 `memory/YYYY-MM-DD.md`。
+
+触发时机：
+- **上下文裁剪** — 轮次或 token 超限时，裁剪的内容被总结写入
+- **每日定时** — 23:55 自动触发全量总结
+- **API 溢出** — 紧急保存当前对话摘要
+
+### 2. 天级记忆 → MEMORY.md（蒸馏）
+
+每日总结完成后，Deep Dream 自动执行蒸馏：
+
+1. **读取材料** — 当前 `MEMORY.md` + 当天的天级记忆
+2. **LLM 蒸馏** — 去重、合并、修剪、提取新信息
+3. **覆写 MEMORY.md** — 输出精炼后的长期记忆
+4. **生成梦境日记** — 记录整理过程的发现和洞察
+
+### 3. MEMORY.md 的作用
+
+`MEMORY.md` 会被注入到每次对话的系统提示词中，让 Agent 始终了解用户的偏好、决策和关键事实。因此它必须保持精炼——Deep Dream 会控制在约 30 条以内。
+
+## 蒸馏规则
+
+Deep Dream 遵循以下整理规则：
+
+| 操作 | 说明 |
+| --- | --- |
+| **合并提炼** | 含义相近的多条合并为一条高密度表述 |
+| **新增萃取** | 从天级记忆中提取偏好、决策、人物、经验等 |
+| **冲突更新** | 新信息与旧条目矛盾时，以新信息为准 |
+| **清理无效** | 删除临时性记录、空白条目、格式残留 |
+| **删除冗余** | 已被更精炼表述涵盖的旧条目删除 |
+
+## 梦境日记
+
+每次蒸馏会生成一篇梦境日记，保存在 `memory/dreams/YYYY-MM-DD.md`，用叙事风格记录：
+
+- 发现了哪些重复或矛盾
+- 从天级记忆中提取了什么新洞察
+- 做了哪些清理和优化
+- 整体感受和观察
+
+梦境日记可在 Web 控制台的「记忆管理 → 梦境日记」tab 中查看。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## 手动触发
+
+除了每日自动执行外，也可以在对话中手动触发：
+
+```text
+/memory dream [N]
+```
+
+- `N`：整理近 N 天的记忆（默认 3 天，最大 30 天）
+- 蒸馏在后台异步执行，完成后在对话中通知结果
+- Web 端通知包含可点击链接，直接跳转查看 MEMORY.md 和梦境日记
+- 无需 Agent 初始化，首次对话前即可使用
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="800" />
+</Frame>
+
+<Tip>
+  首次部署后可以手动执行一次 `/memory dream 30`，将历史天级记忆全量蒸馏到 MEMORY.md。
+</Tip>
+
+## 配置开关
+
+通过 `config.json` 中的 `deep_dream_enabled` 控制每晚的自动蒸馏：
+
+```json
+{
+  "deep_dream_enabled": true
+}
+```
+
+| 配置项 | 说明 | 默认值 |
+| --- | --- | --- |
+| `deep_dream_enabled` | 是否启用每日定时蒸馏 | `true` |
+
+默认开启，保持与现有行为一致。关闭后每晚不再自动执行蒸馏，适合希望手动维护 MEMORY.md 或减少一次 LLM 调用的场景（每日记忆总结不受影响）。手动命令 `/memory dream` 也不受此开关影响，仍可随时触发。
+
+## 安全机制
+
+| 机制 | 说明 |
+| --- | --- |
+| **无新内容跳过** | 没有天级记忆时不执行蒸馏，避免空覆写 |
+| **输入去重** | 定时任务中，输入材料未变化时自动跳过 |
+| **异步执行** | 蒸馏在后台线程运行，不阻塞对话 |
+| **顺序保证** | 定时任务中，天级 flush 全部完成后才启动蒸馏 |
+| **禁止编造** | 提示词明确约束只能基于已有材料整理，不得推测或添加 |
diff --git a/docs/zh/memory/index.mdx b/docs/zh/memory/index.mdx
new file mode 100644
index 0000000..c547aab
--- /dev/null
+++ b/docs/zh/memory/index.mdx
@@ -0,0 +1,71 @@
+---
+title: 长期记忆
+description: CowAgent 的长期记忆系统 — 文件持久化、自动写入与混合检索
+---
+
+长期记忆保存在工作空间文件中，跨会话持久存在。Agent 在对话中通过检索工具按需加载历史记忆，也会在上下文裁剪时自动将对话摘要写入长期记忆。
+
+<img src="https://cdn.link-ai.tech/doc/memory-architecture-zh.jpeg" alt="Memory Architecture" />
+
+## 记忆类型
+
+### 核心记忆（MEMORY.md）
+
+存储在 `~/cow/MEMORY.md` 中，包含用户的长期偏好、重要决策、关键事实等不会随时间淡化的信息。Agent 可通过工具读写此文件来维护长期知识。
+
+### 日级记忆（memory/YYYY-MM-DD.md）
+
+存储在 `~/cow/memory/` 目录下，按日期命名（如 `2026-03-08.md`），记录每天的对话摘要和关键事件。仅在首次写入时创建，避免生成空文件。
+
+### 梦境日记（memory/dreams/YYYY-MM-DD.md）
+
+Deep Dream（记忆蒸馏）过程的副产物，记录每次整理的发现、去重合并操作和新洞察。存储在 `~/cow/memory/dreams/` 目录下，按日期命名。
+
+## 自动写入
+
+Agent 通过以下机制自动将对话内容持久化为长期记忆：
+
+- **上下文裁剪时** — 当对话轮次或 token 超出配置上限时，裁剪最早一半的上下文，使用 LLM 将被裁剪的内容总结为关键信息写入当天记忆文件，并将摘要异步注入到保留的上下文中，帮助模型保持对话连贯性
+- **每日定时总结** — 每天 23:55 自动触发一次全量总结，防止低活跃日无记忆留存（内容无变化时自动跳过）
+- [梦境蒸馏（Deep Dream）](/zh/memory/deep-dream) — 每日总结完成后自动执行，将天级记忆蒸馏合并到 MEMORY.md，并生成梦境日记
+- **API 上下文溢出时** — 当模型 API 返回上下文溢出错误时，紧急保存当前对话摘要
+
+所有记忆写入均在后台异步执行（LLM 总结 + 文件写入），不阻塞正常对话回复。
+
+## 记忆检索
+
+记忆系统支持混合检索模式：
+
+- **关键词检索** — 基于 FTS5 全文索引匹配历史记忆，支持 BM25 排序
+- **向量检索** — 基于 embedding 语义相似度搜索，即使表述不同也能找到相关记忆
+
+Agent 会在对话中根据需要自动触发记忆检索，将相关历史信息纳入上下文。检索结果按混合评分排序（默认向量权重 0.7、关键词权重 0.3），日级记忆会随时间衰减（半衰期 30 天），核心记忆不衰减。
+
+## 相关文件
+
+工作空间（默认 `~/cow`）中与记忆相关的文件：
+
+| 文件 | 说明 |
+| --- | --- |
+| `AGENT.md` | Agent 的人格和行为设定 |
+| `USER.md` | 用户身份信息和偏好 |
+| `RULE.md` | 自定义规则和约束 |
+| `MEMORY.md` | 核心记忆（长期） |
+| `memory/YYYY-MM-DD.md` | 日级记忆（按需创建） |
+| `memory/dreams/YYYY-MM-DD.md` | 梦境日记（Deep Dream 自动生成） |
+
+## Web 控制台
+
+在 Web 控制台的记忆管理页面中，可浏览记忆文件和梦境日记，支持通过 Tab 切换查看：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414171014.png" width="800" />
+</Frame>
+
+## 相关配置
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `agent_workspace` | 工作空间路径，记忆文件存储在此目录下 | `~/cow` |
+| `agent_max_context_tokens` | 最大上下文 token 数，超出时裁剪并总结写入记忆 | `50000` |
+| `agent_max_context_turns` | 最大上下文轮次，超出时裁剪并总结写入记忆 | `20` |
diff --git a/docs/zh/memory/self-evolution.mdx b/docs/zh/memory/self-evolution.mdx
new file mode 100644
index 0000000..6136069
--- /dev/null
+++ b/docs/zh/memory/self-evolution.mdx
@@ -0,0 +1,95 @@
+---
+title: 自主进化
+description: Self-Evolution：自动复盘，沉淀记忆、优化技能、处理未完成事项
+---
+
+## 功能介绍
+
+### 简介
+
+自主进化（Self-Evolution）让 Agent 不止于"完成单次任务"，而是能在与你的相处中持续成长。在每段对话告一段落后，它会自动"回头复盘"一次：把使用中暴露的问题修进技能、把没做完的事情接着推进，并把值得记住的沉淀进记忆与知识库。久而久之，Agent 会越来越懂你的偏好、越来越少重复犯错、越来越主动地把事情收尾，而这一切都在后台静默完成，当真正做了事情时才会主动地告诉你。
+
+<Note>
+  想了解自进化机制完整的架构设计与工程实现，可阅读博客文章：[让 Agent 在对话中成长：自进化机制的五层实现](https://cowagent.ai/zh/blog/self-evolution/)。
+</Note>
+
+> 它与[梦境蒸馏](/zh/memory/deep-dream)互补：梦境蒸馏负责整理记忆本身，自主进化则在记忆之外，进一步优化技能、推进未完成的任务，让 Agent 的能力随使用不断打磨。
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-evolution-demo-zh.png" alt="自主进化对话示例" />
+</Frame>
+
+### 几个目标
+
+自主进化围绕以下几件事工作，并以「优化技能、处理未完成事项」为主，「沉淀记忆、知识」作为主对话的查缺补漏：
+
+| 目标 | 说明 |
+| --- | --- |
+| **优化技能** | ① 技能在使用中暴露问题（如配置错误、步骤缺失）时，直接修正技能文件；② 出现一套可复用的流程时，主动固化为新技能，下次直接调用 |
+| **处理未完成事项** | 识别对话中遗留的待办，在能完成时直接完成 |
+| **沉淀记忆** | 把对话中重要的偏好、决策、事实补记到记忆中，作为主对话的查缺补漏 |
+| **沉淀知识** | 把对话中产生的、值得日后查阅的可复用知识补充进知识库（主对话遗漏时） |
+
+复盘完成后，如果确实做了改动，Agent 会在对话中用一句话告诉你"刚刚自主学习了什么、调整了哪里"，方便你判断是否需要回滚。
+
+## 如何使用
+
+### 触发时机
+
+自主进化不是定时执行，而是在**一段对话自然结束、进入空闲后**才触发，避免打断正在进行的交流。需要同时满足：
+
+- **对话已空闲** — 距离最后一次互动超过设定的空闲时长（默认 10 分钟）
+- **对话有足够内容** — 自上次进化以来累积了足够轮次（默认 6 轮），或上下文已接近容量上限
+
+只有两个条件都满足，才会启动一次复盘。这样既保证有足够的内容值得复盘，又不会在你还在对话时打扰你。
+
+### 相关配置
+
+自主进化可在 Web 控制台「配置 → Agent 配置」中通过开关启停（位于"深度思考"下方），也可在配置文件中调整：
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `self_evolution_enabled` | 是否启用自主进化 | `false` |
+| `self_evolution_idle_minutes` | 对话空闲多久后触发（分钟） | `10` |
+| `self_evolution_min_turns` | 触发所需的最少对话轮次 | `6` |
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-evolution-config-zh.png" alt="在 Web 控制台开启自主进化" />
+</Frame>
+
+<Tip>
+  Web 控制台只提供启用开关，若需调整空闲时长或轮次阈值，请编辑配置文件。修改后即时生效，无需重启。
+</Tip>
+
+### 进化记录
+
+每次进化的过程和结果会按日期记录在 `memory/evolution/YYYY-MM-DD.md` 中，可在 Web 控制台的「记忆管理 → 自主进化」tab 中查看。该 tab 同时汇总了自主进化记录与梦境日记，方便统一回顾 Agent 的成长轨迹。
+
+<Frame>
+  <img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-evolution-logs-zh.png" alt="自主进化记录列表" />
+</Frame>
+
+### 如何回滚
+
+如果你不认同某次进化的改动，直接在对话中告诉 Agent "把刚才的改动撤销"即可，它会根据进化前的备份还原相关文件。每次进化的改动都有独立备份，互不影响。
+
+## 实现设计
+
+自主进化复用了系统已有的能力，保持轻量：
+
+- **隔离执行**：每次复盘都启动一个独立的、临时的复盘任务，使用与主对话相同的模型，但拥有受限的工具集（只能读上下文、改记忆与技能文件）。它不会污染主对话的上下文，也不会影响主对话的性能。
+- **基于备份的撤销**：进化前对相关文件做快照备份，撤销时按备份还原，因此每一次改动都可追溯、可逆。
+- **改动检测**：复盘结束后通过对比文件快照判断是否真的有改动，以此决定要不要通知你，从工程上保证"没做事就不打扰"。
+
+### 克制与安全
+
+自主进化的设计原则是"必要时执行，减少打扰"：
+
+| 机制 | 说明 |
+| --- | --- |
+| **没做事不通知** | 如果复盘后没有任何实际改动，全程静默，不产生任何通知 |
+| **空闲才触发** | 仅在对话空闲后运行，绝不打断正在进行的对话 |
+| **改动可回滚** | 每次进化前自动备份，若对结果不满意，可一键撤销本次改动 |
+| **保护内置技能** | 项目自带的内置技能受保护，进化过程不会改动 |
+| **限定工作空间** | 所有读写都限定在工作空间内，不会触碰系统其他文件 |
+| **后台异步** | 复盘在后台进行，不阻塞正常对话回复 |
diff --git a/docs/zh/models/claude.mdx b/docs/zh/models/claude.mdx
new file mode 100644
index 0000000..bf15b42
--- /dev/null
+++ b/docs/zh/models/claude.mdx
@@ -0,0 +1,51 @@
+---
+title: Claude
+description: Anthropic Claude 模型配置（文本对话 + 图像理解）
+---
+
+Claude 由 Anthropic 提供，支持文本对话与图像理解，主流 Sonnet / Opus 模型均原生支持视觉，无需额外指定 Vision 模型。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "claude-sonnet-5",
+  "claude_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 支持 `claude-sonnet-5`、`claude-opus-4-8`、`claude-opus-4-7`、`claude-sonnet-4-6`、`claude-opus-4-6`、`claude-sonnet-4-5`、`claude-sonnet-4-0`、`claude-3-5-sonnet-latest` 等，参考 [官方模型](https://docs.anthropic.com/en/docs/about-claude/models/overview) |
+| `claude_api_key` | 在 [Claude 控制台](https://console.anthropic.com/settings/keys) 创建 |
+| `claude_api_base` | 可选，默认为 `https://api.anthropic.com/v1`，可改为第三方代理 |
+
+### 模型选择
+
+| 模型 | 适用场景 |
+| --- | --- |
+| `claude-sonnet-5` | 最新旗舰，默认推荐模型，推理效果与成本均衡最佳 |
+| `claude-opus-4-8` | 上一代 Opus 旗舰，推理能力最强，价格较高 |
+| `claude-opus-4-7` | 更早的 Opus 旗舰 |
+| `claude-sonnet-4-6` | 性价比与速度平衡，成本更低 |
+| `claude-opus-4-6` / `claude-sonnet-4-5` / `claude-sonnet-4-0` | 更早的旗舰，价格更低 |
+
+## 图像理解
+
+配置 `claude_api_key` 后 Agent 的 Vision 工具会自动使用 Claude 主模型识别图像，无需额外配置。
+
+如需手动指定 Vision 模型，可在配置文件中显式配置：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "claude-sonnet-5"
+    }
+  }
+}
+```
diff --git a/docs/zh/models/coding-plan.mdx b/docs/zh/models/coding-plan.mdx
new file mode 100644
index 0000000..6193c34
--- /dev/null
+++ b/docs/zh/models/coding-plan.mdx
@@ -0,0 +1,140 @@
+---
+title: Coding Plan
+description: Coding Plan 模式模型配置
+---
+
+> Coding Plan 是各厂商推出的编程包月套餐，适合高频使用 Agent 的场景。CowAgent 支持通过 OpenAI 兼容方式接入各厂商的 Coding Plan 接口。
+
+<Note>
+  Coding Plan 的 API Base 和 API Key 通常与普通按量计费接口不通用，请在各厂商平台单独获取。
+</Note>
+
+## 通用配置格式
+
+所有厂商均可使用 OpenAI 兼容协议接入，可在web控制台快速配置。设置模型厂商为**OpenAI**，选择自定义模型并填入模型编码，最后填写对应厂商的API Base 和 API Key：
+
+<img src="https://cdn.link-ai.tech/doc/20260318113134.png" width="800"/>
+
+也可通过 `config.json` 配置文件直接修改：
+
+```json
+{
+  "bot_type": "openai",
+  "model": "模型名称",
+  "open_ai_api_base": "厂商 Coding Plan API Base",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `bot_type` | 固定为 `openai`（OpenAI 兼容方式） |
+| `model` | 各厂商支持的模型名称 |
+| `open_ai_api_base` | 各厂商 Coding Plan 专用 API Base |
+| `open_ai_api_key` | 各厂商 Coding Plan 专用 API Key |
+
+---
+
+## 阿里云
+
+```json
+{
+  "bot_type": "openai",
+  "model": "qwen3.5-plus",
+  "open_ai_api_base": "https://coding.dashscope.aliyuncs.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | `qwen3.5-plus`、`qwen3-max-2026-01-23`、`qwen3-coder-next`、`qwen3-coder-plus`、`glm-5`、`glm-4.7`、`kimi-k2.5`、`MiniMax-M2.5` |
+| `open_ai_api_base` | `https://coding.dashscope.aliyuncs.com/v1` |
+| `open_ai_api_key` | Coding Plan 专用 Key（与按量计费接口不通用） |
+
+官方文档：[快速开始](https://help.aliyun.com/zh/model-studio/coding-plan-quickstart?spm=a2c4g.11186623.help-menu-2400256.d_0_2_1.70115203zi5Igc)、[模型列表](https://help.aliyun.com/zh/model-studio/coding-plan)
+
+---
+
+## MiniMax
+
+```json
+{
+  "bot_type": "openai",
+  "model": "MiniMax-M3",
+  "open_ai_api_base": "https://api.minimaxi.com/v1",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | `MiniMax-M3`、`MiniMax-M2.7`、`MiniMax-M2.7-highspeed` |
+| `open_ai_api_base` | 国内：`https://api.minimaxi.com/v1`；海外：`https://api.minimax.io/v1` |
+| `open_ai_api_key` | Coding Plan 专用 Key（与按量计费接口不通用） |
+
+官方文档：[国内 Key 获取](https://platform.minimaxi.com/docs/coding-plan/quickstart)、[模型列表](https://platform.minimaxi.com/docs/guides/pricing-coding-plan)、[国际 Key 获取](https://platform.minimax.io/docs/coding-plan/quickstart)
+
+---
+
+
+## 智谱 GLM
+
+```json
+{
+  "bot_type": "openai",
+  "model": "glm-4.7",
+  "open_ai_api_base": "https://open.bigmodel.cn/api/coding/paas/v4",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | `glm-5`、`glm-4.7`、`glm-4.6`、`glm-4.5`、`glm-4.5-air` |
+| `open_ai_api_base` | 中国区：`https://open.bigmodel.cn/api/coding/paas/v4`；全球区：`https://api.z.ai/api/coding/paas/v4` |
+| `open_ai_api_key` | API Key 与普通接口通用 |
+
+官方文档：[国内版快速开始](https://docs.bigmodel.cn/cn/coding-plan/quick-start)、[国际版快速开始](https://docs.z.ai/devpack/quick-start)
+
+---
+
+## 火山引擎
+
+```json
+{
+  "bot_type": "openai",
+  "model": "Doubao-Seed-2.0-Code",
+  "open_ai_api_base": "https://ark.cn-beijing.volces.com/api/coding/v3",
+  "open_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | `Doubao-Seed-2.0-Code`、`Doubao-Seed-2.0-pro`、`Doubao-Seed-2.0-lite`、`Doubao-Seed-Code`、`MiniMax-M2.5`、`Kimi-K2.5`、`GLM-4.7`、`DeepSeek-V3.2` |
+| `open_ai_api_base` | `https://ark.cn-beijing.volces.com/api/coding/v3` |
+| `open_ai_api_key` | API Key 与普通接口通用 |
+
+官方文档：[快速开始](https://www.volcengine.com/docs/82379/1928261?lang=zh)
+
+---
+
+## Kimi
+
+```json
+{
+  "bot_type": "moonshot",
+  "model": "kimi-for-coding",
+  "moonshot_base_url": "https://api.kimi.com/coding/v1",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 填写 `kimi-for-coding` 会自动更新模型，或指定模型例如 `kimi-k2.6` |
+| `moonshot_base_url` | `https://api.kimi.com/coding/v1` |
+| `moonshot_api_key` | Coding Plan 专用 Key（与按量计费接口不通用） |
+
+官方文档：[Key 获取](https://www.kimi.com/code/docs/)
diff --git a/docs/zh/models/custom.mdx b/docs/zh/models/custom.mdx
new file mode 100644
index 0000000..7970924
--- /dev/null
+++ b/docs/zh/models/custom.mdx
@@ -0,0 +1,62 @@
+---
+title: 自定义
+description: 自定义厂商配置，用于第三方 API 代理与本地模型
+---
+
+适用于通过 OpenAI 兼容协议接入的模型服务，例如：
+
+- **第三方 API 代理**：通过统一的 API 地址调用多种模型
+- **本地模型**：使用 Ollama、vLLM 等工具在本地部署的模型
+- **私有化部署**：企业内部部署的模型服务
+
+## Web 端配置
+
+推荐方式。在 Web 控制台「模型」页面点击「添加厂商」，选择「自定义」，填写名称、API Base 和 API Key 即可。支持添加多个自定义厂商，添加后在「主模型」中选择对应厂商和模型即可启用。
+
+<img width="900" src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/en/web-console-custom-model-config.png" />
+
+本地部署工具的默认地址：
+
+| 工具 | 默认 API Base |
+| --- | --- |
+| [Ollama](https://ollama.com) | `http://localhost:11434/v1` |
+| [vLLM](https://docs.vllm.ai) | `http://localhost:8000/v1` |
+| [LocalAI](https://localai.io) | `http://localhost:8080/v1` |
+
+## 配置文件配置
+
+也可以直接编辑 `config.json`，在 `custom_providers` 列表中定义多个厂商，并将 `bot_type` 设置为 `"custom:<id>"` 来激活其中一个：
+
+```json
+{
+  "bot_type": "custom:3f2a9c1b",
+  "custom_providers": [
+    {
+      "id": "3f2a9c1b",
+      "name": "厂商A",
+      "api_key": "YOUR_API_KEY_A",
+      "api_base": "https://api.a.com/v1",
+      "model": "deepseek-v3"
+    },
+    {
+      "id": "a1b2c3d4",
+      "name": "厂商B",
+      "api_key": "YOUR_API_KEY_B",
+      "api_base": "https://api.b.com/v1",
+      "model": "qwen3-max"
+    }
+  ]
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `custom_providers` | 自定义厂商列表，每项包含 `id`、`name`、`api_base`、`api_key`（可选）、`model`（可选） |
+| `bot_type` | 设置为 `"custom:<id>"` 激活对应厂商 |
+| `id` | 厂商唯一标识（8 位十六进制），在 Web 端添加时自动生成，手动配置时填写任意不重复的标识即可 |
+| `name` | 展示名称，可随意修改 |
+| `model` | 该厂商使用的模型，激活时生效 |
+
+<Note>
+  历史的单厂商配置（`bot_type` 为 `"custom"`，配合 `custom_api_key` / `custom_api_base`）仍然兼容，无需改动即可继续使用。
+</Note>
diff --git a/docs/zh/models/deepseek.mdx b/docs/zh/models/deepseek.mdx
new file mode 100644
index 0000000..57b96d5
--- /dev/null
+++ b/docs/zh/models/deepseek.mdx
@@ -0,0 +1,72 @@
+---
+title: DeepSeek
+description: DeepSeek 模型配置（文本对话 + 思考模式）
+---
+
+DeepSeek 是当前 Agent 模式默认推荐的厂商之一，主打高性价比的文本对话和任务规划能力。
+
+## 文本对话
+
+```json
+{
+  "model": "deepseek-v4-flash",
+  "deepseek_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 支持 `deepseek-v4-flash`（默认）、`deepseek-v4-pro` |
+| `deepseek_api_key` | 在 [DeepSeek 平台](https://platform.deepseek.com/api_keys) 创建 |
+| `deepseek_api_base` | 可选，默认为 `https://api.deepseek.com/v1`，可修改为第三方代理地址 |
+
+### 模型选择
+
+| 模型 | 适用场景 |
+| --- | --- |
+| `deepseek-v4-flash` | 默认推荐，速度快、成本低 |
+| `deepseek-v4-pro` | 更智能，复杂任务效果更强 |
+
+## 思考模式
+
+V4 系列（`deepseek-v4-flash` / `deepseek-v4-pro`）支持显式的「思考模式」：模型在输出最终回答前，先输出一段思维链（`reasoning_content`），从而提升答案质量。
+
+### 开关
+
+通过全局配置 `enable_thinking` 控制，也可在 web控制台 - 配置页面中进行切换：
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+- `true`：所有渠道下模型都会先思考再作答。Web 控制台会展示思考过程，IM 渠道（微信 / 企微 / 钉钉 / 飞书）虽不展示但同样获得更好答案。
+- `false`：关闭思考，响应更快，首字延迟更低。
+
+### 推理强度
+
+思考模式下可通过 `reasoning_effort` 控制推理强度：
+
+```json
+{
+  "enable_thinking": true,
+  "reasoning_effort": "high"
+}
+```
+
+| 取值 | 适用场景 |
+| --- | --- |
+| `high`（默认） | 日常 Agent 任务，思考与速度的平衡 |
+| `max` | 复杂编码、长链路规划、严格约束的任务，推理更深但耗时与输出 token 更多 |
+
+`reasoning_effort` 仅在 `enable_thinking` 为 `true` 时生效；模型不支持思考模式时该字段自动忽略。
+
+### 行为说明
+
+- **采样参数**：思考模式下 `temperature`、`top_p`、`presence_penalty`、`frequency_penalty` 会被服务端忽略（不会报错），CowAgent 会自动跳过传入。
+- **多轮工具调用**：当历史中包含工具调用时，DeepSeek 要求所有 assistant 消息必须回传 `reasoning_content`。CowAgent 会自动处理回传逻辑，跨轮次切换思考开关也不会出错。
+
+<Tip>
+  默认使用 `deepseek-v4-flash`；复杂任务可使用 `deepseek-v4-pro`；需要深度推理可开启 `enable_thinking`。
+</Tip>
diff --git a/docs/zh/models/doubao.mdx b/docs/zh/models/doubao.mdx
new file mode 100644
index 0000000..4296c53
--- /dev/null
+++ b/docs/zh/models/doubao.mdx
@@ -0,0 +1,66 @@
+---
+title: 豆包 Doubao
+description: 豆包（火山方舟）模型配置（文本 / 图像理解 / 图像生成 / 向量）
+---
+
+豆包（火山方舟）支持文本对话、图像理解、图像生成（Seedream）和向量能力，一份 `ark_api_key` 即可启用全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "doubao-seed-2-1-pro-260628",
+  "ark_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 可填 `doubao-seed-2-1-pro-260628`、`doubao-seed-2-1-turbo-260628`、`doubao-seed-2-0-pro-260215`、`doubao-seed-2-0-code-preview-260215` 等 |
+| `ark_api_key` | 在 [火山方舟控制台](https://console.volcengine.com/ark/region:ark+cn-beijing/apikey) 创建 |
+| `ark_base_url` | 可选，默认为 `https://ark.cn-beijing.volces.com/api/v3` |
+
+## 图像理解
+
+配置 `ark_api_key` 后，若主模型为豆包系列，Agent 的 Vision 工具会自动使用当前主模型识别图像，无需额外配置。
+
+如需手动指定 Vision 模型：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "doubao-seed-2-1-pro-260628"
+    }
+  }
+}
+```
+
+## 图像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+可选模型：`seedream-5.0-lite`、`seedream-4.5`。
+
+## 向量
+
+```json
+{
+  "embedding_provider": "doubao",
+  "embedding_model": "doubao-embedding-vision-251215"
+}
+```
+
+默认模型 `doubao-embedding-vision-251215`（多模态 embedding），可在配置文件中通过 `embedding_dimensions` 指定 1024 或 2048 维。修改 embedding 后需执行 `/memory rebuild-index` 命令重建索引。
diff --git a/docs/zh/models/gemini.mdx b/docs/zh/models/gemini.mdx
new file mode 100644
index 0000000..f1c8991
--- /dev/null
+++ b/docs/zh/models/gemini.mdx
@@ -0,0 +1,59 @@
+---
+title: Gemini
+description: Google Gemini 模型配置（文本对话 + 图像理解 + 图像生成）
+---
+
+Google Gemini 支持文本对话、图像理解和图像生成（Nano Banana 系列），一个 `gemini_api_key` 即可启用全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "gemini-3.5-flash",
+  "gemini_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 推荐 `gemini-3.5-flash`，亦支持 `gemini-3.1-pro-preview`、`gemini-3.1-flash-lite-preview`、`gemini-3-flash-preview`、`gemini-3-pro-preview` 等，参考 [官方文档](https://ai.google.dev/gemini-api/docs/models) |
+| `gemini_api_key` | 在 [Google AI Studio](https://aistudio.google.com/app/apikey) 创建 |
+| `gemini_api_base` | 可选，默认为 `https://generativelanguage.googleapis.com`，可改为第三方代理 |
+
+## 图像理解
+
+Gemini 全系列模型均原生支持视觉，配置 `gemini_api_key` 后 Agent 的 Vision 工具会自动使用主模型识别图像，无需额外配置。
+
+如需手动指定 Vision 模型：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gemini-3.1-flash-lite-preview"
+    }
+  }
+}
+```
+
+## 图像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gemini-3.1-flash-image-preview"
+    }
+  }
+}
+```
+
+| 模型 ID | 别名 |
+| --- | --- |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `gemini-2.5-flash-image` | Nano Banana |
diff --git a/docs/zh/models/glm.mdx b/docs/zh/models/glm.mdx
new file mode 100644
index 0000000..e6e7bd1
--- /dev/null
+++ b/docs/zh/models/glm.mdx
@@ -0,0 +1,56 @@
+---
+title: 智谱 GLM
+description: 智谱 AI GLM 模型配置（文本 / 图像理解 / 语音识别 / 向量）
+---
+
+智谱 AI 支持文本对话、图像理解、语音识别（ASR）和向量（Embedding），一份 `zhipu_ai_api_key` 即可启用全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "glm-5.2",
+  "zhipu_ai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 可填 `glm-5.2`、`glm-5.1`、`glm-5-turbo`、`glm-5`、`glm-4.7`、`glm-4-plus`、`glm-4-flash`、`glm-4-air` 等，参考 [模型编码](https://bigmodel.cn/dev/api/normal-model/glm-4) |
+| `zhipu_ai_api_key` | 在 [智谱 AI 控制台](https://www.bigmodel.cn/usercenter/proj-mgmt/apikeys) 创建 |
+| `zhipu_ai_api_base` | 可选，默认为 `https://open.bigmodel.cn/api/paas/v4` |
+
+## 图像理解
+
+智谱 chat 系列模型（`glm-5.2`、`glm-5.1`、`glm-5-turbo` 等）不支持视觉，视觉调用统一路由到 `glm-5v-turbo`。配置 `zhipu_ai_api_key` 后 Agent 的 Vision 工具会自动使用该模型，无需在配置文件中显式指定。
+
+## 语音识别
+
+```json
+{
+  "voice_to_text": "zhipu",
+  "voice_to_text_model": "glm-asr-2512"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `voice_to_text` | 设为 `zhipu` 启用智谱 ASR |
+| `voice_to_text_model` | 可选，默认 `glm-asr-2512` |
+
+凭证自动复用 `zhipu_ai_api_key`。语音文件建议小于 25MB，超大文件可能被服务端拒绝。
+
+## 向量
+
+```json
+{
+  "embedding_provider": "zhipu",
+  "embedding_model": "embedding-3"
+}
+```
+
+可选模型：`embedding-3`、`embedding-2`。修改 embedding 后需执行 `/memory rebuild-index` 命令重建索引。
diff --git a/docs/zh/models/index.mdx b/docs/zh/models/index.mdx
new file mode 100644
index 0000000..b3550d6
--- /dev/null
+++ b/docs/zh/models/index.mdx
@@ -0,0 +1,40 @@
+---
+title: 模型概览
+description: CowAgent 支持的模型厂商及能力矩阵
+---
+
+CowAgent 支持国内外主流厂商的大语言模型，模型接口实现在项目的 `models/` 目录下。除文本对话外，部分厂商还提供视觉理解、图像生成、语音识别、语音合成、向量等能力，可在 Agent 流程中按需调用。
+
+
+## 模型能力总览
+
+各厂商提供的能力一览。「文本」指主对话模型，其余列表示该厂商可承担对应 Agent 能力。
+
+| 厂商 | 代表模型 | 文本 | 图像理解 | 图像生成 | 语音识别 | 语音合成 | 向量 |
+| --- | --- | :-: | :-: | :-: | :-: | :-: | :-: |
+| [DeepSeek](/zh/models/deepseek) | deepseek-v4-flash / pro | ✅ | | | | | |
+| [MiniMax](/zh/models/minimax) | MiniMax-M3 | ✅ | ✅ | ✅ | | ✅ | |
+| [Claude](/zh/models/claude) | claude-sonnet-5 | ✅ | ✅ | | | | |
+| [Gemini](/zh/models/gemini) | gemini-3.5-flash | ✅ | ✅ | ✅ | | | |
+| [OpenAI](/zh/models/openai) | gpt-5.5、o 系列 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [智谱 GLM](/zh/models/glm) | glm-5.2、glm-5v-turbo | ✅ | ✅ | | ✅ | | ✅ |
+| [通义千问](/zh/models/qwen) | qwen3.7-plus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [豆包 Doubao](/zh/models/doubao) | doubao-seed-2.1 系列 | ✅ | ✅ | ✅ | | | ✅ |
+| [Kimi](/zh/models/kimi) | kimi-k2.7-code | ✅ | ✅ | | | | |
+| [百度千帆](/zh/models/qianfan) | ernie-5.1 | ✅ | ✅ | | | | |
+| [小米 MiMo](/zh/models/mimo) | mimo-v2.5-pro / v2.5 | ✅ | ✅ | | | ✅ | |
+| [LinkAI](/zh/models/linkai) | 多厂商 100+ 模型统一接入 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
+| [自定义](/zh/models/custom) |本地模型 / 三方代理 | ✅ | | | | | |
+
+<Tip>
+  Web 控制台中各项能力（视觉 / 图像 / 语音识别 / 语音合成 / 向量 / 网络搜索）均可独立配置厂商与模型，互相之间不强制绑定。
+</Tip>
+
+
+## 配置方式
+
+**方式一（推荐）：** 通过 [Web 控制台](/zh/channels/web) 在线管理模型与各项能力，无需手动编辑配置文件：
+
+<img width="900" src="https://cdn.link-ai.tech/doc/20260521212527.png" />
+
+**方式二：** 手动编辑 `config.json`，根据所选模型填写对应的模型名称和 API Key。每个模型也支持 OpenAI 兼容方式接入，将 `bot_type` 设为 `openai`，配置 `open_ai_api_base` 和 `open_ai_api_key` 即可。
diff --git a/docs/zh/models/kimi.mdx b/docs/zh/models/kimi.mdx
new file mode 100644
index 0000000..776c2dc
--- /dev/null
+++ b/docs/zh/models/kimi.mdx
@@ -0,0 +1,41 @@
+---
+title: Kimi
+description: Kimi（Moonshot）模型配置（文本对话 + 图像理解）
+---
+
+Kimi 由 Moonshot 提供，支持文本对话与图像理解，`kimi-k2.x` 系列原生支持视觉。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "kimi-k2.7-code",
+  "moonshot_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 可填 `kimi-k2.7-code`、`kimi-k2.7-code-highspeed`、`kimi-k2.6`、`kimi-k2.5`、`kimi-k2`、`moonshot-v1-8k`、`moonshot-v1-32k`、`moonshot-v1-128k` |
+| `moonshot_api_key` | 在 [Moonshot 控制台](https://platform.moonshot.cn/console/api-keys) 创建 |
+| `moonshot_base_url` | 可选，默认为 `https://api.moonshot.cn/v1` |
+
+## 图像理解
+
+配置 `moonshot_api_key` 后 Agent 的 Vision 工具会自动使用 `kimi-k2.6` 识别图像，无需额外配置。
+
+如需手动指定 Vision 模型：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "kimi-k2.6"
+    }
+  }
+}
+```
diff --git a/docs/zh/models/linkai.mdx b/docs/zh/models/linkai.mdx
new file mode 100644
index 0000000..5c07c37
--- /dev/null
+++ b/docs/zh/models/linkai.mdx
@@ -0,0 +1,103 @@
+---
+title: LinkAI
+description: 通过 LinkAI 平台统一接入文本、视觉、图像、语音与向量能力
+---
+
+通过一份 `linkai_api_key` 即可访问 OpenAI、Claude、Gemini、DeepSeek、MiniMax、Qwen、Kimi、豆包 等主流厂商的全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "use_linkai": true,
+  "linkai_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `use_linkai` | 设为 `true` 启用 |
+| `linkai_api_key` | 在 [控制台](https://link-ai.tech/console/interface) 创建 |
+| `model` | 可填写 [模型列表](https://link-ai.tech/console/models) 中任意编码 |
+
+前往 [模型服务](https://link-ai.tech/console/models) 了解更多。
+
+## 图像理解
+
+配置完成后 Agent 的 Vision 工具会自动调用网关上的多模态模型，无需额外配置。如需手动指定 Vision 模型：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+可选模型：`gpt-4.1-mini`、`gpt-5.4-mini`、`qwen3.7-plus`、`doubao-seed-2-1-pro-260628`、`kimi-k2.6`、`claude-sonnet-5`、`gemini-3.1-flash-lite-preview` 等。
+
+## 图像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+| 模型 ID | 别名 |
+| --- | --- |
+| `gpt-image-2` | OpenAI |
+| `gemini-3.1-flash-image-preview` | Nano Banana 2 |
+| `gemini-3-pro-image-preview` | Nano Banana Pro |
+| `seedream-5.0-lite` | 字节豆包 Seedream |
+
+## 语音识别
+
+```json
+{
+  "voice_to_text": "linkai"
+}
+```
+
+ASR 固定使用 Whisper，凭证自动复用 `linkai_api_key`。
+
+## 语音合成
+
+语音合成网关下支持多个底层 TTS 引擎，按 `text_to_voice_model` 选择引擎，音色随引擎切换。
+
+```json
+{
+  "text_to_voice": "linkai",
+  "text_to_voice_model": "doubao",
+  "tts_voice_id": "BV001_streaming"
+}
+```
+
+| `text_to_voice_model` | 引擎说明 |
+| --- | --- |
+| `tts-1` | OpenAI · 多语种通用（音色 `alloy` / `nova` / `echo` 等） |
+| `doubao` | 字节豆包 · 中文音色丰富 |
+| `baidu` | 百度 · 中文主播音色 |
+
+不同引擎对应的音色不同，建议在 Web 控制台「模型管理 → 语音合成」中可视化选择。
+
+## 向量
+
+```json
+{
+  "embedding_provider": "linkai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+默认模型 `text-embedding-3-small`（OpenAI 兼容）。修改 embedding 后需执行 `/memory rebuild-index` 命令重建索引。
diff --git a/docs/zh/models/mimo.mdx b/docs/zh/models/mimo.mdx
new file mode 100644
index 0000000..ea445df
--- /dev/null
+++ b/docs/zh/models/mimo.mdx
@@ -0,0 +1,135 @@
+---
+title: 小米 MiMo
+description: 小米 MiMo 模型配置（文本对话 + 图像理解 + 语音合成）
+---
+
+小米 MiMo 是原生全模态大模型，单 `mimo_api_key` 即可同时启用文本对话、图像理解与语音合成。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "mimo-v2.5-pro",
+  "mimo_api_key": "YOUR_API_KEY",
+  "mimo_api_base": "https://api.xiaomimimo.com/v1"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 默认推荐 `mimo-v2.5-pro`，也可使用 `mimo-v2.5` |
+| `mimo_api_key` | 在 [MiMo 开放平台](https://platform.xiaomimimo.com/console/api-keys) 创建 |
+| `mimo_api_base` | 可选，默认为 `https://api.xiaomimimo.com/v1` |
+
+### 模型选择
+
+| 模型 | 适用场景 |
+| --- | --- |
+| `mimo-v2.5-pro` | 旗舰，原生全模态 + Agent 能力，最高 100 万 tokens 上下文 |
+| `mimo-v2.5` | 综合版，原生全模态（文本 / 图像 / 视频 / 音频） |
+
+## 思考模式
+
+MiMo V2.5 系列默认开启「思考模式」：模型在输出最终回答前会先输出 `reasoning_content`（思维链），提升复杂任务表现。
+
+通过全局配置 `enable_thinking` 控制是否展示（也可在 Web 控制台 - 配置页面切换）：
+
+```json
+{
+  "enable_thinking": true
+}
+```
+
+## 图像理解
+
+配置 `mimo_api_key` 后，Agent 的 Vision 工具可以自动使用 MiMo 视觉模型：
+
+- 当主模型本身是多模态时（`mimo-v2.5-pro` / `mimo-v2.5`），直接由主模型识别图像，无需额外配置
+- 当主模型是其他厂商时，Vision 工具会根据顺序自动 fallback 到 `mimo-v2.5-pro`
+
+如需手动指定 Vision 模型，可在配置文件中显式配置：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "provider": "mimo",
+      "model": "mimo-v2.5-pro"
+    }
+  }
+}
+```
+
+## 语音合成
+
+```json
+{
+  "text_to_voice": "mimo",
+  "text_to_voice_model": "mimo-v2.5-tts",
+  "tts_voice_id": "冰糖"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `text_to_voice_model` | 当前仅支持 `mimo-v2.5-tts`（预置音色 + 唱歌模式） |
+| `tts_voice_id` | 预置音色名（中文音色直接使用中文名作为 ID） |
+
+### 预置音色
+
+| 音色 ID | 说明 |
+| --- | --- |
+| `冰糖` | 中文 · 女声（默认） |
+| `茉莉` | 中文 · 女声 |
+| `苏打` | 中文 · 男声 |
+| `白桦` | 中文 · 男声 |
+| `Mia` | 英文 · 女声 |
+| `Chloe` | 英文 · 女声 |
+| `Milo` | 英文 · 男声 |
+| `Dean` | 英文 · 男声 |
+
+也可在 Web 控制台的「模型管理 → 语音合成」下拉框中可视化选择。
+
+### 风格控制
+
+MiMo TTS 支持在合成文本中嵌入 **音频标签** 来控制情绪、语调、方言、角色甚至唱歌。标签需出现在 **最终被合成为语音的文本（即 Agent 回复内容）** 中，整体风格标签写在开头：
+
+```
+(风格)待合成内容
+```
+
+支持半角 `()`、全角 `（）` 或 `[]` 三种括号。常见风格示例：
+
+| 类型 | 示例标签 |
+| --- | --- |
+| 基础情绪 | `开心` `悲伤` `愤怒` `恐惧` `惊讶` `兴奋` `委屈` `平静` `冷漠` |
+| 复合情绪 | `怅然` `欣慰` `无奈` `愧疚` `释然` `忐忑` `动情` |
+| 整体语调 | `温柔` `高冷` `活泼` `严肃` `慵懒` `俏皮` `深沉` `干练` `凌厉` |
+| 音色定位 | `磁性` `醇厚` `清亮` `空灵` `稚嫩` `苍老` `甜美` `沙哑` |
+| 人设腔调 | `夹子音` `御姐音` `正太音` `大叔音` `台湾腔` |
+| 方言 | `东北话` `四川话` `河南话` `粤语` |
+| 角色扮演 | `孙悟空` `林黛玉` |
+| 唱歌 | `唱歌`（等价于 `sing` / `singing`） |
+
+示例：
+
+- (磁性)夜已经深了，城市还在呼吸。
+- (东北话)哎呀妈呀，这天儿也忒冷了吧！
+- (粤语)呢个真係好正啊！
+- (唱歌)原谅我这一生不羁放纵爱自由…
+
+也可以在文本任意位置插入细粒度音频标签来控制呼吸、笑声、停顿等，例如：
+
+```
+（紧张，深呼吸）呼……冷静，冷静。（语速加快）自我介绍我背了五十遍了，应该没问题。
+```
+
+完整标签列表参见 [MiMo 语音合成文档](https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/speech-synthesis-v2.5)。
+
+<Tip>
+  CowAgent 在调用 TTS 时会将 Agent 的回复原文（含 `(...)` 标签）直接送入 MiMo 合成。你可以在人设 / 系统提示词里要求模型「在回复开头用 `(风格)` 标签控制语气」，即可让 IM 渠道（微信 / 飞书 / 钉钉 / 企微）的语音回复带上情绪、方言、唱歌等效果。
+</Tip>
diff --git a/docs/zh/models/minimax.mdx b/docs/zh/models/minimax.mdx
new file mode 100644
index 0000000..af7913b
--- /dev/null
+++ b/docs/zh/models/minimax.mdx
@@ -0,0 +1,71 @@
+---
+title: MiniMax
+description: MiniMax 模型配置（文本 / 图像理解 / 图像生成 / 语音合成）
+---
+
+MiniMax 支持文本对话、图像理解、图像生成与语音合成，一份 `minimax_api_key` 即可启用全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "MiniMax-M3",
+  "minimax_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 可填 `MiniMax-M3`、`MiniMax-M2.7`、`MiniMax-M2.7-highspeed` 等 |
+| `minimax_api_key` | 在 [MiniMax 控制台](https://platform.minimaxi.com/user-center/basic-information/interface-key) 创建 |
+
+## 图像理解
+
+MiniMax 的 M2.x 系列 chat 模型本身不支持视觉，视觉调用统一路由到 `MiniMax-Text-01`。配置 `minimax_api_key` 后 Agent 的 Vision 工具会自动使用该模型，无需在配置文件中显式指定。
+
+## 图像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "image-01"
+    }
+  }
+}
+```
+
+可选模型：`image-01`。
+
+## 语音合成
+
+```json
+{
+  "text_to_voice": "minimax",
+  "text_to_voice_model": "speech-2.8-hd",
+  "tts_voice_id": "female-shaonv"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `text_to_voice_model` | `speech-2.8-hd`（情绪渲染、自然听感）、`speech-2.8-turbo`（极速）、`speech-2.6-hd`、`speech-2.6-turbo` |
+| `tts_voice_id` | 音色 ID，支持中文 / 粤语 / 英 / 日 / 韩，共 70+ 种 |
+
+常用音色示例：
+
+| 音色 ID | 说明 |
+| --- | --- |
+| `female-shaonv` | 中文 · 少女（女） |
+| `female-yujie` | 中文 · 御姐（女） |
+| `female-tianmei` | 中文 · 甜美女性（女） |
+| `male-qn-jingying` | 中文 · 精英青年（男） |
+| `male-qn-badao` | 中文 · 霸道青年（男） |
+| `Cantonese_GentleLady` | 粤语 · 温柔女声 |
+| `English_Graceful_Lady` | 英文 · Graceful Lady |
+
+完整音色（中文 / 粤语 / 英 / 日 / 韩共 70+ 种）可参考 [系统音色列表](https://platform.minimaxi.com/docs/faq/system-voice-id)，也可在 Web 控制台的「模型管理 → 语音合成」下拉框中可视化选择。
diff --git a/docs/zh/models/openai.mdx b/docs/zh/models/openai.mdx
new file mode 100644
index 0000000..aad83c8
--- /dev/null
+++ b/docs/zh/models/openai.mdx
@@ -0,0 +1,103 @@
+---
+title: OpenAI
+description: OpenAI 模型配置（文本 / 视觉 / 图像 / 语音 / 向量）
+---
+
+OpenAI 是覆盖最完整的厂商，可同时承担文本对话、视觉理解、图像生成、语音识别（ASR）、语音合成（TTS）和向量（Embedding）能力。一份 `open_ai_api_key` 即可让 Agent 用到全部能力。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+
+## 文本对话
+
+```json
+{
+  "model": "gpt-5.5",
+  "open_ai_api_key": "YOUR_API_KEY",
+  "open_ai_api_base": "https://api.openai.com/v1"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 与 OpenAI 接口的 [model 参数](https://platform.openai.com/docs/models) 一致，支持 `gpt-5.5`、`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano`、`gpt-5` 系列、`gpt-4.1`、o 系列等；Agent 模式默认 `gpt-5.5`，追求性价比可改为 `gpt-5.4` |
+| `open_ai_api_key` | 在 [OpenAI 平台](https://platform.openai.com/api-keys) 创建 |
+| `open_ai_api_base` | 可选，修改可接入第三方代理 |
+| `bot_type` | 使用 OpenAI 官方模型时无需填写；通过兼容协议接入厂商模型时需设为 `openai` |
+
+## 图像理解
+
+`gpt-5.5`、`gpt-5.4`、`gpt-4o`、`gpt-4.1` 等 OpenAI 模型均原生支持视觉，配置 `open_ai_api_key` 后 Agent 的 Vision 工具会自动使用主模型识别图像。若主模型不支持视觉或希望显式指定，可在配置文件中配置：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "gpt-5.4-mini"
+    }
+  }
+}
+```
+
+支持的 Vision 模型：`gpt-5.5`、`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano`、`gpt-5`、`gpt-4.1`、`gpt-4.1-mini`、`gpt-4o`。
+
+## 图像生成
+
+在配置文件中指定图像生成模型，Agent 调用图像生成技能时会自动路由到 OpenAI：
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "gpt-image-2"
+    }
+  }
+}
+```
+
+支持的图像生成模型：`gpt-image-2`、`gpt-image-1`。
+
+## 语音识别
+
+```json
+{
+  "voice_to_text": "openai",
+  "voice_to_text_model": "gpt-4o-mini-transcribe"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `voice_to_text` | 设为 `openai` 启用 OpenAI 语音识别 |
+| `voice_to_text_model` | 可选，默认 `gpt-4o-mini-transcribe`；也可填 `gpt-4o-transcribe`、`whisper-1` |
+
+凭证自动复用 `open_ai_api_key`。
+
+## 语音合成
+
+```json
+{
+  "text_to_voice": "openai",
+  "text_to_voice_model": "tts-1",
+  "tts_voice_id": "alloy"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `text_to_voice_model` | `tts-1`、`tts-1-hd`、`gpt-4o-mini-tts` |
+| `tts_voice_id` | 音色：`alloy`、`echo`、`fable`、`onyx`、`nova`、`shimmer`、`ash`、`ballad`、`coral`、`sage`、`verse` |
+
+## 向量
+
+```json
+{
+  "embedding_provider": "openai",
+  "embedding_model": "text-embedding-3-small"
+}
+```
+
+可选模型：`text-embedding-3-small`、`text-embedding-3-large`、`text-embedding-ada-002`。修改 embedding 后需执行 `/memory rebuild-index` 命令重建索引。
+
diff --git a/docs/zh/models/qianfan.mdx b/docs/zh/models/qianfan.mdx
new file mode 100644
index 0000000..bdd8721
--- /dev/null
+++ b/docs/zh/models/qianfan.mdx
@@ -0,0 +1,59 @@
+---
+title: 百度千帆
+description: 百度千帆 ERNIE 模型配置（文本对话 + 图像理解）
+---
+
+百度千帆提供 ERNIE 系列模型，支持文本对话与图像理解。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "ernie-5.1",
+  "qianfan_api_key": "YOUR_API_KEY",
+  "qianfan_api_base": "https://qianfan.baidubce.com/v2"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 默认推荐使用 `ernie-5.1`；也可使用 `ernie-5.0`、`ernie-x1.1`、`ernie-4.5-turbo-128k`、`ernie-4.5-turbo-32k` |
+| `qianfan_api_key` | 千帆 API Key，格式通常以 `bce-v3/` 开头 |
+| `qianfan_api_base` | 可选，默认为 `https://qianfan.baidubce.com/v2` |
+
+### 模型选择
+
+| 模型 | 适用场景 |
+| --- | --- |
+| `ernie-5.1` | 默认推荐，文心新一代旗舰模型，综合能力最强 |
+| `ernie-5.0` | 上一代旗舰模型，综合能力优异 |
+| `ernie-x1.1` | 深度思考推理模型，幻觉更低、指令遵循与工具调用更强 |
+| `ernie-4.5-turbo-128k` | 长上下文和通用对话 |
+| `ernie-4.5-turbo-32k` | 通用对话，成本和上下文更均衡 |
+
+## 图像理解
+
+配置 `qianfan_api_key` 后，Agent 的 Vision 工具可以自动使用千帆视觉模型：
+
+- 当主模型本身是多模态时（如 `ernie-5.1`、`ernie-5.0`、`ernie-x1.1`、`ernie-4.5-turbo-vl`），直接由主模型识别图像，无需额外配置
+- 当主模型是纯文本时（如 `ernie-4.5-turbo-128k`），Vision 工具会自动 fallback 到 `ernie-4.5-turbo-vl`
+
+如需手动指定 Vision 模型，可在配置文件中显式配置：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "ernie-4.5-turbo-vl"
+    }
+  }
+}
+```
+
+<Tip>
+  新配置推荐使用 `qianfan_api_key`。旧的 `wenxin`、`wenxin-4`、`baidu_wenxin_api_key`、`baidu_wenxin_secret_key` 配置仍保持兼容。
+</Tip>
diff --git a/docs/zh/models/qwen.mdx b/docs/zh/models/qwen.mdx
new file mode 100644
index 0000000..67626a4
--- /dev/null
+++ b/docs/zh/models/qwen.mdx
@@ -0,0 +1,112 @@
+---
+title: 通义千问 Qwen
+description: 通义千问模型配置（文本 / 图像理解 / 图像生成 / 语音识别 / 语音合成 / 向量）
+---
+
+通义千问（DashScope / 百炼）是国内覆盖最完整的厂商之一，文本、图像理解、图像生成、语音识别、语音合成与向量能力均可用一份 `dashscope_api_key` 启用。
+
+<Tip>
+  通过 Web 控制台的「模型管理」页面可一站式配置以下全部能力，无需手动改配置文件。
+</Tip>
+
+## 文本对话
+
+```json
+{
+  "model": "qwen3.7-plus",
+  "dashscope_api_key": "YOUR_API_KEY"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `model` | 可填 `qwen3.7-plus`、`qwen3.7-max`、`qwen3.6-plus`、`qwen3.5-plus`、`qwen3-max`、`qwen-max`、`qwen-plus`、`qwen-turbo`、`qwq-plus` 等 |
+| `dashscope_api_key` | 在 [百炼控制台](https://bailian.console.aliyun.com/?tab=model#/api-key) 创建，参考 [官方文档](https://bailian.console.aliyun.com/?tab=api#/api) |
+
+## 图像理解
+
+配置 `dashscope_api_key` 后 Agent 的 Vision 工具会自动调用千问的视觉模型识别图像。`qwen3.7-plus` / `qwen3.6-plus` / `qwen3.5-plus` / `qwen3-max` 等模型本身就是多模态；若主模型是纯文本（如 `qwen-turbo`），会自动回落到 `qwen-vl-max`。
+
+如需手动指定 Vision 模型：
+
+```json
+{
+  "tools": {
+    "vision": {
+      "model": "qwen3.7-plus"
+    }
+  }
+}
+```
+
+支持模型：`qwen3.7-plus`、`qwen3.6-plus`、`qwen3.5-plus`、`qwen3-max`。
+
+## 图像生成
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "qwen-image-2.0"
+    }
+  }
+}
+```
+
+可选模型：`qwen-image-2.0`、`qwen-image-2.0-pro`。
+
+## 语音识别
+
+```json
+{
+  "voice_to_text": "dashscope",
+  "voice_to_text_model": "qwen3-asr-flash"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `voice_to_text` | 设为 `dashscope` 启用通义千问 ASR |
+| `voice_to_text_model` | 可选，默认 `qwen3-asr-flash` |
+
+凭证自动复用 `dashscope_api_key`。单段音频建议小于 10MB、时长不超过 300 秒。
+
+## 语音合成
+
+```json
+{
+  "text_to_voice": "dashscope",
+  "text_to_voice_model": "qwen3-tts-flash",
+  "tts_voice_id": "Cherry"
+}
+```
+
+| 参数 | 说明 |
+| --- | --- |
+| `text_to_voice_model` | 可选，默认 `qwen3-tts-flash`，覆盖普通话、方言与主流外语 |
+| `tts_voice_id` | 音色 ID，详见下方常用列表 |
+
+常用音色示例：
+
+| 音色 ID | 说明 |
+| --- | --- |
+| `Cherry` | 芊悦 · 阳光女声 |
+| `Serena` | 苏瑶 · 温柔女声 |
+| `Ethan` | 晨煦 · 阳光男声 |
+| `Chelsie` | 千雪 · 二次元少女 |
+| `Dylan` | 北京话 · 晓东 |
+| `Rocky` | 粤语 · 阿强 |
+| `Sunny` | 四川话 · 晴儿 |
+
+完整音色（普通话 / 各地方言 / 双语等）可在 Web 控制台的「模型管理 → 语音合成」下拉框中可视化选择。
+
+## 向量
+
+```json
+{
+  "embedding_provider": "dashscope",
+  "embedding_model": "text-embedding-v4"
+}
+```
+
+默认模型 `text-embedding-v4`。修改 embedding 后需执行 `/memory rebuild-index` 命令重建索引。
diff --git a/docs/zh/releases/overview.mdx b/docs/zh/releases/overview.mdx
new file mode 100644
index 0000000..1d99b81
--- /dev/null
+++ b/docs/zh/releases/overview.mdx
@@ -0,0 +1,36 @@
+---
+title: 更新日志
+description: CowAgent 版本更新历史
+---
+
+| 版本 | 日期 | 说明 |
+| --- | --- | --- |
+| [2.1.3](/zh/releases/v2.1.3) | 2026.07.08 | 桌面客户端正式发布（macOS / Windows）、知识库文档管理增强、MCP 工具智能检索、繁体中文支持、新模型接入（claude-sonnet-5、doubao-seed-2.1 等）、安全加固与体验优化 |
+| [2.1.2](/zh/releases/v2.1.2) | 2026.06.18 | Web 控制台升级（定时任务管理、知识库分类、多模型自定义厂商）、自主进化优化、新模型接入（kimi-k2.7-code、glm-5.2）、安全加固和体验优化 |
+| [2.1.1](/zh/releases/v2.1.1) | 2026.06.09 | 自主进化能力、Web 控制台消息管理升级、新模型接入（MiniMax-M3、qwen3.7-plus 等）、其他多项优化和修复 |
+| [2.1.0](/zh/releases/v2.1.0) | 2026.06.01 | 国际化支持、新增 Telegram / Discord / Slack / 微信客服通道、命令行交互升级（流式输出、命令模糊匹配、任务取消）、MCP Streamable HTTP、新模型接入 |
+| [2.0.9](/zh/releases/v2.0.9) | 2026.05.22 | 新增模型管理、MCP 协议支持、浏览器登录态持久化、新模型接入（gpt-5.5、gemini-3.5-flash、qwen3.7-max 等）、部署安全加固 |
+| [2.0.8](/zh/releases/v2.0.8) | 2026.05.06 | 飞书渠道全面升级（语音、流式输出和Markdown、扫码一键接入）、DeepSeek V4和百度模型新增、定时任务工具增强 |
+| [2.0.7](/zh/releases/v2.0.7) | 2026.04.22 | 图像生成技能（六厂商自动路由）、新模型支持（Kimi K2.6、Claude Opus 4.7、GLM 5.1）、知识库增强、Web 控制台优化 |
+| [2.0.6](/zh/releases/v2.0.6) | 2026.04.14 | 项目更名、知识库系统、梦境记忆蒸馏、上下文智能压缩、Web 控制台多会话及多项优化 |
+| [2.0.5](/zh/releases/v2.0.5) | 2026.04.01 | Cow CLI、Skill Hub 开源、浏览器工具、企微扫码创建、多项优化和修复 |
+| [2.0.4](/zh/releases/v2.0.4) | 2026.03.22 | 新增个人微信通道、新模型支持、日文文档、脚本重构及多项修复 |
+| [2.0.3](/zh/releases/v2.0.3) | 2026.03.18 | 新增企微智能机器人和 QQ 通道、支持Coding Plan、新增多个模型、Web端文件处理、记忆系统升级 |
+| [2.0.2](/zh/releases/v2.0.2) | 2026.02.27 | Web 控制台升级、多通道同时运行、会话持久化 |
+| [2.0.1](/zh/releases/v2.0.1) | 2026.02.13 | 内置 Web Search 工具、智能上下文管理、多项修复 |
+| [2.0.0](/zh/releases/v2.0.0) | 2026.02.03 | 全面升级为超级 Agent 助理 |
+| 1.7.6 | 2025.05.23 | Web Channel 优化、AgentMesh 多智能体插件 |
+| 1.7.5 | 2025.04.11 | DeepSeek 模型 |
+| 1.7.4 | 2024.12.13 | Gemini 2.0 模型、Web Channel |
+| 1.7.3 | 2024.10.31 | 稳定性提升、数据库功能 |
+| 1.7.2 | 2024.09.26 | 一键安装脚本、o1 模型 |
+| 1.7.0 | 2024.08.02 | 讯飞 4.0 模型、知识库引用 |
+| 1.6.9 | 2024.07.19 | gpt-4o-mini、阿里语音识别 |
+| 1.6.8 | 2024.07.05 | Claude 3.5、Gemini 1.5 Pro |
+| 1.6.0 | 2024.04.26 | Kimi 接入、gpt-4-turbo 升级 |
+| 1.5.8 | 2024.03.26 | GLM-4、Claude-3、edge-tts |
+| 1.5.2 | 2023.11.10 | 飞书通道、图像识别对话 |
+| 1.5.0 | 2023.11.10 | gpt-4-turbo、dall-e-3、tts 多模态 |
+| 1.0.0 | 2022.12.12 | 项目创建，首次接入 ChatGPT 模型 |
+
+更多历史版本请查看 [GitHub Releases](https://github.com/zhayujie/CowAgent/releases)。
diff --git a/docs/zh/releases/v2.0.0.mdx b/docs/zh/releases/v2.0.0.mdx
new file mode 100644
index 0000000..3436bc1
--- /dev/null
+++ b/docs/zh/releases/v2.0.0.mdx
@@ -0,0 +1,105 @@
+---
+title: v2.0.0
+description: CowAgent 2.0 - 从聊天机器人到超级智能助理的全面升级
+---
+
+CowAgent 2.0 实现了从聊天机器人到**超级智能助理**的全面升级！现在它能够主动思考和规划任务、拥有长期记忆、操作计算机和外部资源、创造和执行技能，真正理解你并和你一起成长。
+
+**发布日期**：2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)
+
+## 重点更新
+
+### Agent 核心能力
+
+- **复杂任务规划**：能够理解复杂任务并自主规划执行，持续思考和调用工具直到完成目标，支持多轮推理和上下文理解
+- **长期记忆**：自动将对话记忆持久化至本地文件和数据库中，包括全局记忆和天级记忆，支持关键词及向量检索
+- **内置系统工具**：内置实现 10+ 种工具，包括文件操作、Bash 终端、浏览器、文件发送、定时任务、记忆管理等
+- **Skills**：新增 Skill 运行引擎，内置多种技能，并支持通过自然语言对话完成自定义 Skills 开发
+- **安全和成本**：通过秘钥管理工具、提示词控制、系统权限等手段控制 Agent 的访问安全；通过最大记忆轮次、最大上下文 token、工具执行步数对 token 成本进行限制
+
+### 其他更新
+
+- **渠道优化**：飞书及钉钉接入渠道支持长连接接入（无需公网 IP）、支持图片/文件消息的接收和发送
+- **模型更新**：新增 claude-sonnet-4-5、gemini-3-pro-preview、glm-4.7、MiniMax-M2.1、qwen3-max 等最新模型
+- **部署优化**：增加一键安装、配置、运行、管理的脚本，简化部署流程
+
+## 长期记忆系统
+
+Agent 会在用户分享重要信息时主动存储，也会在对话达到一定长度时自动提取摘要。支持语义搜索和向量检索的混合检索模式。
+
+**首次启动**时，Agent 会主动询问关键信息，并记录至工作空间（默认 `~/cow`）中的智能体设定、用户身份、记忆文件中。
+
+**长期对话**中，Agent 会智能记录或检索记忆，不断更新自身设定、用户偏好，总结经验和教训，真正实现自主思考和持续成长。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
+</Frame>
+
+## 任务规划与工具调用
+
+Agent 根据任务需求智能选择和调用工具，完成各类复杂操作。
+
+### 终端和文件访问
+
+最基础和核心的工具能力，用户可通过手机端与 Agent 交互，操作个人电脑或服务器上的资源：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
+</Frame>
+
+### 应用编程能力
+
+基于编程能力和系统访问能力，Agent 可实现从信息搜索、素材生成、编码、测试、部署、Nginx 配置、发布的 **Vibecoding 全流程**，通过手机端一句命令完成应用快速 demo。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
+
+### 定时任务
+
+支持 **一次性任务、固定时间间隔、Cron 表达式** 三种形式，任务触发可选择 **固定消息发送** 或 **Agent 动态任务执行** 两种模式：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+### 环境变量管理
+
+通过 `env_config` 工具管理技能所需秘钥，支持对话式更新，内置安全保护和脱敏策略：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
+
+## 技能系统
+
+每个 Skill 由说明文件、运行脚本（可选）、资源（可选）组成，为 Agent 提供无限扩展性。
+
+### 技能创造器
+
+通过对话方式快速创建技能，将工作流程固化或对接任意第三方接口：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+### 网页搜索和图像识别
+
+- **网页搜索**：内置 `web_search` 工具，支持多种搜索引擎，配置对应 API Key 即可使用
+- **图像识别**：支持 `gpt-4.1-mini`、`gpt-4.1` 等模型，配置 `OPENAI_API_KEY` 即可使用
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
+</Frame>
+
+### 三方知识库和插件
+
+`linkai-agent` 技能可将 [LinkAI](https://link-ai.tech/) 上的所有智能体作为 Skill 使用，实现多智能体决策：
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234350.png" width="750" />
+</Frame>
+
+## 参与共建
+
+2.0 版本后，项目将持续升级 Agent 能力、拓展接入渠道、内置工具、技能系统，降低模型成本和提升安全性。欢迎 [提出反馈](https://github.com/zhayujie/CowAgent/issues) 和 [贡献代码](https://github.com/zhayujie/CowAgent/pulls)。
diff --git a/docs/zh/releases/v2.0.1.mdx b/docs/zh/releases/v2.0.1.mdx
new file mode 100644
index 0000000..da7b674
--- /dev/null
+++ b/docs/zh/releases/v2.0.1.mdx
@@ -0,0 +1,36 @@
+---
+title: v2.0.1
+description: CowAgent 2.0.1 - 内置 Web Search、智能上下文管理、多项修复
+---
+
+**发布日期**：2026.02 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.1) | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)
+
+## 新特性
+
+- **内置 Web Search 工具**：将网络搜索作为 Agent 内置工具集成，降低决策成本 ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 模型支持**：新增对 Claude Opus 4.6 模型的支持 ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **企业微信图片消息识别**：支持企业微信渠道的图片消息识别功能 ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))
+
+## 优化
+
+- **智能上下文管理**：解决聊天上下文溢出问题，新增智能上下文裁剪策略，防止 token 超限 ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **运行时信息动态更新**：通过动态函数方案实现系统提示词中时间戳等运行时信息的自动更新 ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill 提示词优化**：改进 Skill 系统提示词生成逻辑，简化工具描述，提升 Agent 表现 ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **智谱 AI 自定义 API Base URL**：支持智谱 AI 配置自定义 API Base URL ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **启动脚本优化**：改进 `run.sh` 脚本的交互体验和配置流程 ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **决策轮次日志**：新增 Agent 决策轮次的日志记录，便于调试 ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+
+## 问题修复
+
+- **定时任务记忆丢失**：修复 Scheduler 调度器导致的记忆丢失问题 ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **空工具调用与超长结果**：修复空 tool calls 及过长工具返回结果的异常处理 ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**：修复 OpenAI 模型的 function call 调用兼容性问题 ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude 工具名字段**：移除 Claude 模型响应中多余的 tool name 字段 ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax 推理优化**：优化 MiniMax 模型 reasoning content 处理，隐藏思考过程输出 ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **智谱 AI 思考过程**：隐藏智谱 AI 模型的思考过程展示 ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **飞书连接与证书**：修复飞书渠道的 SSL 证书错误和连接异常问题 ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type 类型校验**：修复非字符串 `model_type` 导致的 `AttributeError` ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))
+
+## 平台兼容
+
+- **Windows 兼容性适配**：修复 Windows 平台下路径处理、文件编码及 `os.getuid()` 不可用等问题，涉及多个工具模块 ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
diff --git a/docs/zh/releases/v2.0.2.mdx b/docs/zh/releases/v2.0.2.mdx
new file mode 100644
index 0000000..ad17bcb
--- /dev/null
+++ b/docs/zh/releases/v2.0.2.mdx
@@ -0,0 +1,98 @@
+---
+title: v2.0.2
+description: CowAgent 2.0.2 - Web 控制台升级、多通道同时运行、会话持久化
+---
+
+## ✨ 重点更新
+
+### 🖥️ Web 控制台升级
+
+本次对 Web 控制台进行了全面升级，支持流式对话输出、工具执行过程和思考过程的可视化展示，并支持对模型、技能、记忆、通道、Agent 配置的在线查看和管理。
+
+#### 对话界面
+
+支持流式输出，可实时展示 Agent 的思考过程（Reasoning）和工具调用过程（Tool Calls），更直观地观察 Agent 的决策过程：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />
+
+#### 模型管理
+
+支持在线管理模型配置，无需手动编辑配置文件：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173811.png" />
+
+#### 技能管理
+
+支持在线查看和管理 Agent 技能（Skills）：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173403.png" />
+
+#### 记忆管理
+
+支持在线查看和管理 Agent 记忆：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173349.png" />
+
+#### 通道管理
+
+支持在线管理接入通道，支持实时连接/断开操作：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173331.png" />
+
+#### 定时任务
+
+支持在线查看和管理定时任务，包括一次性任务、固定间隔、Cron 表达式等多种调度方式的可视化管理：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173704.png" />
+
+#### 日志
+
+支持在线实时查看 Agent 运行日志，便于监控运行状态和排查问题：
+
+<img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />
+
+相关提交：[f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)
+
+### 🔀 多通道同时运行
+
+支持多个接入通道（如飞书、钉钉、企微应用、Web 等）同时运行，每个通道在独立子线程中启动，互不干扰。
+
+配置方式：在 `config.json` 中通过 `channel_type` 配置多个通道，以逗号分隔，也可在 Web 控制台的通道管理页面中实时连接或断开各通道。
+
+```json
+{
+  "channel_type": "web,feishu,dingtalk"
+}
+```
+
+相关提交：[4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)
+
+### 💾 会话持久化
+
+会话历史支持持久化存储至本地 SQLite 数据库，服务重启后会话上下文自动恢复，不再丢失。Web 控制台中的历史对话记录也会同步恢复展示。
+
+相关提交：[29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)
+
+### 🤖 新增模型
+
+- **Gemini 3.1 Pro Preview**：新增 `gemini-3.1-pro-preview` 模型支持 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**：新增 `claude-4.6-sonnet` 模型支持 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**：新增 `qwen3.5-plus` 模型支持 ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**：新增 `Minimax-M2.5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**：新增 `glm-5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**：新增 `kimi-k2.5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**：新增 `doubao-2.0-code` 编程专用模型 ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope 模型**：新增阿里云 DashScope 模型名称支持 ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))
+
+### 🌐 新增官网和文档中心
+
+- **官网上线**：[cowagent.ai](https://cowagent.ai/)
+- **文档中心上线**：[docs.cowagent.ai](https://docs.cowagent.ai/)
+
+### 🐛 问题修复
+
+- **Gemini 钉钉图片识别**：修复 Gemini 在钉钉通道中无法处理图片标记的问题 ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **启动脚本依赖**：修复 `run.sh` 脚本的依赖安装问题 ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **裸异常捕获**：将代码中的 `bare except` 替换为 `except Exception`，提升异常处理规范性 ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
+
+**发布日期**：2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)
diff --git a/docs/zh/releases/v2.0.3.mdx b/docs/zh/releases/v2.0.3.mdx
new file mode 100644
index 0000000..22d2d1f
--- /dev/null
+++ b/docs/zh/releases/v2.0.3.mdx
@@ -0,0 +1,91 @@
+---
+title: v2.0.3
+description: CowAgent 2.0.3 - 新增企微智能机器人和 QQ 通道、Web 控制台文件处理、记忆系统升级
+---
+
+## 🔌 新增接入通道
+
+### 企业微信智能机器人
+
+新增企业微信智能机器人（`wecom_bot`）通道，支持流式卡片消息输出，支持文本和图片消息的接收与回复，可在 Web 控制台中进行通道配置和管理。
+
+接入文档：[企微智能机器人接入](https://docs.cowagent.ai/channels/wecom-bot)。
+
+相关提交：[d4480b6](https://github.com/zhayujie/CowAgent/commit/d4480b6), [a42f31f](https://github.com/zhayujie/CowAgent/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/CowAgent/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/CowAgent/commit/8b45d6c)
+
+### QQ 通道
+
+新增 QQ 官方机器人（`qq`）通道，支持文本和图片消息的接收与回复，支持私聊和群聊场景。
+
+接入文档参考：[QQ机器人接入](https://docs.cowagent.ai/channels/qq)。
+
+相关提交：[005a0e1](https://github.com/zhayujie/CowAgent/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/CowAgent/commit/a4d54f5)
+
+## 🖥️ Web 控制台支持文件输入和处理
+
+Web 控制台对话界面支持文件和图片上传，可直接发送文件给 Agent 进行处理。同时 Read 工具新增对 Office 文档（Word、Excel、PPT）的解析能力。
+
+相关提交：[30c6d9b](https://github.com/zhayujie/CowAgent/commit/30c6d9b)
+
+## 🤖 新增模型
+
+- **GPT-5.4 系列**：新增 `gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` 模型支持 ([1623deb](https://github.com/zhayujie/CowAgent/commit/1623deb))
+- **Gemini 3.1 Flash Lite Preview**：新增 `gemini-3.1-flash-lite-preview` 模型支持 ([ba915f2](https://github.com/zhayujie/CowAgent/commit/ba915f2))
+
+## 💰 Coding Plan 支持
+
+新增各厂商 Coding Plan（编程包月套餐）的接入支持，通过 OpenAI 兼容方式统一接入。目前已支持阿里云、MiniMax、智谱 GLM、Kimi、火山引擎等厂商。
+
+详细配置参考 [Coding Plan 文档](https://docs.cowagent.ai/models/coding-plan)。
+
+## 🧠 记忆系统升级
+
+记忆写入（Memory Flush）升级：
+
+- 使用 LLM 对超出上下文窗口的对话内容进行智能摘要，生成精炼的每日记忆条目
+- 摘要在后台线程异步执行，不阻塞回复
+- 优化上下文批量裁剪策略，降低冲刷频率
+- 新增每日定时冲刷兜底机制，避免低活跃场景下记忆丢失
+- 修复上下文记忆丢失问题
+
+相关提交：[022c13f](https://github.com/zhayujie/CowAgent/commit/022c13f), [c116235](https://github.com/zhayujie/CowAgent/commit/c116235)
+
+## 🔧 工具重构
+
+- **图片识别**：将图片识别（Image Vision）从 Skill 重构为内置 Tool，新增独立的图片视觉提供方（Vision Provider）配置，提升稳定性和可维护性 ([a50fafa](https://github.com/zhayujie/CowAgent/commit/a50fafa), [3b8b562](https://github.com/zhayujie/CowAgent/commit/3b8b562))
+- **网页抓取**：将网页抓取（Web Fetch）从 Skill 重构为内置 Tool，支持远程文档文件（PDF、Word、Excel、PPT）的下载和解析 ([ccb9030](https://github.com/zhayujie/CowAgent/commit/ccb9030), [fa61744](https://github.com/zhayujie/CowAgent/commit/fa61744))
+
+## 🐳 Docker 部署优化
+
+- **配置模板对齐**：`docker-compose.yml` 环境变量与 `config-template.json` 对齐，补充完整的模型 API Key 和 Agent 等配置项
+- **Web 控制台端口映射**：新增 `9899` 端口映射，Docker 部署后可通过浏览器访问 Web 控制台
+- **配置热更新**：各模型 Bot 的 API Key 和 API Base 改为实时读取，通过 Web 控制台修改配置后无需重启即可生效
+- **工作空间持久化**：新增 `./cow` Volume 挂载，Agent 工作空间数据（记忆、人格、技能等）持久化到宿主机，容器重建或升级不丢失
+
+## ⚡ 性能优化
+
+- **启动加速**：飞书通道采用懒加载方式导入依赖，避免 4-10 秒的启动延迟 ([924dc79](https://github.com/zhayujie/CowAgent/commit/924dc79))
+- **通道稳定性**：优化通道连接稳定性，支持通道配置通过环境变量设置 ([f1c04bc](https://github.com/zhayujie/CowAgent/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/CowAgent/commit/46d97fd))
+
+## 🐛 问题修复
+
+- **bot_type 配置**：修复 Agent 模式下 `bot_type` 配置传递问题 ([#2691](https://github.com/zhayujie/CowAgent/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
+- **bot_type 优先级**：调整 Agent 模式下 `bot_type` 的解析优先级 ([#2692](https://github.com/zhayujie/CowAgent/pull/2692)) Thanks [@6vision](https://github.com/6vision)
+- **智谱模型配置**：修复智谱 `bot_type` 命名、Web 控制台持久化及正则转义问题 ([#2693](https://github.com/zhayujie/CowAgent/pull/2693)) Thanks [@6vision](https://github.com/6vision)
+- **OpenAI 兼容层**：使用 `openai_compat` 层统一错误处理 ([#2688](https://github.com/zhayujie/CowAgent/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
+- **OpenAI 兼容迁移**：完成所有模型 Bot 的 `openai_compat` 迁移 ([#2689](https://github.com/zhayujie/CowAgent/pull/2689))
+- **Gemini 工具调用**：修复 Gemini 模型的工具调用匹配问题 ([eda82ba](https://github.com/zhayujie/CowAgent/commit/eda82ba))
+- **会话并发**：修复会话并发场景下的竞态条件问题 ([9879878](https://github.com/zhayujie/CowAgent/commit/9879878))
+- **历史消息恢复**：修复历史会话消息不完整问题，仅恢复 user/assistant 文本消息，剥离工具调用 ([b788a3d](https://github.com/zhayujie/CowAgent/commit/b788a3d), [a33ce97](https://github.com/zhayujie/CowAgent/commit/a33ce97))
+- **飞书群聊**：移除飞书群聊场景下对 `bot_name` 的依赖 ([b641bff](https://github.com/zhayujie/CowAgent/commit/b641bff))
+- **Safari 兼容**：修复 Safari 浏览器 IME 回车键误触发消息发送问题 ([0687916](https://github.com/zhayujie/CowAgent/commit/0687916))
+- **Windows 兼容**：修复 Windows 下 bash 风格 `$VAR` 环境变量转换为 `%VAR%` 的问题 ([7c67513](https://github.com/zhayujie/CowAgent/commit/7c67513))
+- **MiniMax 参数**：增加 MiniMax 模型的 `max_tokens` 限制 ([1767413](https://github.com/zhayujie/CowAgent/commit/1767413))
+- **.gitignore 更新**：添加 Python 目录忽略规则 ([#2683](https://github.com/zhayujie/CowAgent/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
+- **AGENT.md 主动演进**：优化系统提示词中对 AGENT.md 的更新引导，从被动的"用户修改时更新"改为主动识别对话中的性格、风格变化并自动更新
+
+## 📦 升级方式
+
+源码部署可执行 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.2...master)
diff --git a/docs/zh/releases/v2.0.4.mdx b/docs/zh/releases/v2.0.4.mdx
new file mode 100644
index 0000000..55264a4
--- /dev/null
+++ b/docs/zh/releases/v2.0.4.mdx
@@ -0,0 +1,51 @@
+---
+title: v2.0.4
+description: CowAgent 2.0.4 - 新增个人微信通道、新模型支持、日文文档、脚本重构及多项修复
+---
+
+## 🔌 新增个人微信通道
+
+新增个人微信（`weixin`）通道，微信扫描二维码即可将 CowAgent 接入个人微信，支持以下功能：
+
+- **消息收发**：支持文本、图片、文件、视频消息的接收与回复，支持语音消息接收和识别
+- **扫码登录**：终端显示二维码，微信扫码确认即可登录，二维码过期自动刷新
+- **凭证持久化**：登录凭证自动保存至 `~/.weixin_cow_credentials.json`，重启无需重新扫码
+- **Session 自动重连**：Session 过期后自动清除旧凭证并重新发起扫码登录
+- **Web 控制台接入**：支持在 Web 控制台中添加微信通道，扫码登录流程同步展示
+- **Docker 和脚本支持**：`run.sh` 和 `docker-compose.yml` 均已适配微信通道
+
+接入文档：[微信接入](https://docs.cowagent.ai/channels/weixin)。
+
+相关提交：[ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869)
+
+## 🤖 新增模型
+
+- **MiniMax-M2.7**：新增 MiniMax-M2.7 模型支持
+- **GLM-5-Turbo**：新增智谱 glm-5-turbo 模型支持
+
+相关提交：[9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)
+
+## 🔧 脚本重构
+
+- **run.sh 重构**：提取公共逻辑，精简脚本代码([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **可执行权限**：修复 `run.sh` 文件权限问题 ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))
+- **PID 获取**：修复 `run.sh` 中进程 PID 获取错误的问题 ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))
+
+## 🌍 文档更新
+
+新增完整的日文文档，覆盖入门指南、通道接入、模型配置等主要章节。Thanks [@Ikko Ashimine](https://github.com/ikoamu)
+
+相关提交：[5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)
+
+## 🐛 问题修复
+
+- **企微机器人兼容**：修复旧版 `websocket-client` 的兼容性问题，新增统一的 WebSocket 兼容层 ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **消息自动修复**：增强消息协议的容错能力，自动修复格式异常的消息序列 ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))
+- **飞书编码**：修复飞书通道消息和日志的编码问题 ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **飞书配置**：移除 `run.sh` 中对 `feishu_bot_name` 的冗余依赖 ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))
+
+## 📦 升级方式
+
+源码部署可执行 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
diff --git a/docs/zh/releases/v2.0.5.mdx b/docs/zh/releases/v2.0.5.mdx
new file mode 100644
index 0000000..bf0c0e5
--- /dev/null
+++ b/docs/zh/releases/v2.0.5.mdx
@@ -0,0 +1,84 @@
+---
+title: v2.0.5
+description: CowAgent 2.0.5 - Cow CLI、Skill Hub 开源、浏览器工具、企微扫码创建、DeepSeek 独立模块及多项优化
+---
+
+## 🖥️ Cow CLI 命令系统
+
+新增 Cow CLI 命令系统，支持在终端和对话中执行命令，实现对 CowAgent 的全方位管理：
+
+- **终端命令**：在系统终端中执行 `cow <命令>`，支持 `start`、`stop`、`restart`、`update`、`status`、`logs` 等服务管理操作
+- **对话命令**：在对话中输入 `/<命令>` 或 `cow <命令>`，支持 `/help`、`/status`、`/config`、`/skill`、`/context`、`/logs`、`/version` 等
+- **web控制台**：Web 控制台输入框输入 `/` 即可弹出指令菜单，支持方向键回溯历史输入
+- **Windows 支持**：新增 PowerShell 一键安装脚本 `scripts/run.ps1`，同时支持 `cow` 命令
+
+相关文档：[命令总览](https://docs.cowagent.ai/cli)
+
+<img src="https://cdn.link-ai.tech/doc/20260401114549.png" width="750" />
+
+## 🧩 Cow Skill Hub 开源
+
+[Cow Skill Hub](https://skills.cowagent.ai)（技能广场）正式开源并上线，提供 AI Agent 技能的浏览、搜索、安装和发布，汇集精选技能、社区贡献技能、三方技能：
+
+- **一键安装**：在对话中 `/skill install <名称>` 或终端 `cow skill install <名称>` 一键安装
+- **多来源支持**：支持安装 Skill Hub、GitHub、ClawHub、LinkAI 上的全部技能，支持 GitHub 批量安装和子目录指定
+- **技能搜索**：`/skill search` 和 `/skill list --remote` 浏览和搜索技能广场
+- **技能发布**：通过 [skills.cowagent.ai/submit](https://skills.cowagent.ai/submit) 提交自己的技能
+- **镜像加速**：支持 Skill Hub 镜像加速，国内环境下载更流畅
+
+Skill Hub 开源仓库：[cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)。
+
+相关文档：[技能广场](https://docs.cowagent.ai/skills/hub)、[安装技能](https://docs.cowagent.ai/skills/install)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />
+
+
+## 🌐 新增浏览器工具
+
+新增 Browser 工具，Agent 可控制浏览器访问和操作网页：
+
+- **网页导航与交互**：支持 `navigate`、`click`、`fill`、`select`、`scroll`、`press` 等操作
+- **页面快照**：使用精简 DOM 快照技术，让 Agent 高效理解页面结构，导航后自动快照
+- **截图能力**：支持页面截图保存到工作区
+- **JavaScript 执行**：支持在页面中执行自定义脚本
+- **CLI 安装**：通过 `cow install-browser` 一键安装浏览器及依赖，自动适配系统环境
+- **Docker 支持**：Docker 镜像已内置浏览器安装支持
+
+相关文档：[浏览器工具](https://docs.cowagent.ai/tools/browser)。
+
+<img src="https://cdn.link-ai.tech/doc/20260401115728.png" width="750" />
+
+
+## 🤖 企微智能机器人扫码创建
+
+企业微信智能机器人通道新增扫码一键创建功能：
+
+- **Web 控制台扫码**：在 Web 控制台通道页面，选择「扫码接入」模式，使用企业微信扫码即可自动创建并接入智能机器人，无需手动到企业微信后台配置
+- **手动模式保留**：同时保留「手动填写」模式，可输入已有的 Bot ID 和 Secret 接入
+- **流式推送优化**：增加推送节流，避免 WebSocket 拥塞
+
+相关文档：[企微智能机器人接入](https://docs.cowagent.ai/channels/wecom-bot)。
+
+相关提交：[#2735](https://github.com/zhayujie/CowAgent/pull/2735)
+
+Thanks [@WecomTeam](https://github.com/WecomTeam)
+
+## 🐛 其他优化与修复
+
+- **DeepSeek 独立模块**：新增独立的 DeepSeek Bot 模块，支持 `deepseek_api_key` 专属配置，无需再通过 OpenAI 兼容方式接入（[#2719](https://github.com/zhayujie/CowAgent/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
+- **Web 控制台优化**：新增斜杠指令菜单和输入历史回溯，新增模型选项，优化移动端适配（[#2731](https://github.com/zhayujie/CowAgent/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
+- **上下文丢失**：修复上下文裁剪后丢失的问题 ([393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0))
+- **系统提示词**：修复系统提示词未在每轮重建的问题 ([13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde))
+- **Agent 响应**：去除 Agent 响应首尾空白字符 ([f890318](https://github.com/zhayujie/CowAgent/commit/f890318))
+- **视觉压缩**：优化视觉图片压缩策略 ([22b8ca0](https://github.com/zhayujie/CowAgent/commit/22b8ca0))
+- **Gemini 模型**：修复 GoogleGeminiBot 缺少 model 属性的问题（[#2716](https://github.com/zhayujie/CowAgent/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
+- **微信通道**：修复文件发送失败、文件名丢失等问题 ([6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba)、[baf66a1](https://github.com/zhayujie/CowAgent/commit/baf66a1)、[45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c))
+- **Docker 优化**：修复卷权限问题，精简镜像体积 ([3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c))
+- **README 排版**：优化中英文排版空格（[#2723](https://github.com/zhayujie/CowAgent/pull/2723)）。Thanks [@Xiaozhou345](https://github.com/Xiaozhou345)
+- **安全修复**：修复 Memory Content路径遍历风险，Thanks [@August829](https://github.com/August829)
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
diff --git a/docs/zh/releases/v2.0.6.mdx b/docs/zh/releases/v2.0.6.mdx
new file mode 100644
index 0000000..299be80
--- /dev/null
+++ b/docs/zh/releases/v2.0.6.mdx
@@ -0,0 +1,83 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - 知识库系统、梦境记忆蒸馏、上下文智能压缩、Web 控制台多会话及多项优化
+---
+
+## 项目正式更名为 CowAgent
+
+项目仓库正式从 `chatgpt-on-wechat` 更名为 **CowAgent**，演进为功能完备的 AI Agent 助理。
+
+- 新地址：[github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent)，旧地址 GitHub 会自动重定向
+- CLI 命令、配置文件、文档链接均保持兼容，无需额外操作
+
+## 📚 知识库系统
+
+新增个人知识库系统，Agent 可自主构建和维护结构化知识，并在对话中按需检索引用。
+
+- **索引驱动的自组织结构**：知识库采用 `knowledge/` 目录，按分类自动组织，每个知识页面为独立的 Markdown 文件
+- **自动写入**：向 Agent 发送文件、链接等知识，或在讨论中识别到有价值的知识时，自动创建或更新知识页面
+- **混合检索**：支持关键词全文搜索和向量语义检索，在对话中按需加载相关知识
+- **可视化**：支持文件树浏览和知识图谱可视化，文档内链接可直接跳转查看
+- **命令管理**：`/knowledge` 查看统计、`/knowledge list` 查看目录结构、`/knowledge on|off` 开关知识库
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+相关文档：[知识库](https://docs.cowagent.ai/knowledge)
+
+Inspired by Karpathy's [LLM Wiki](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f).
+
+## 🌙 梦境记忆蒸馏（Deep Dream）
+
+全新的记忆整理机制，每日自动将分散的对话记忆蒸馏为精炼的长期记忆：
+
+- **三层记忆流转**：对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期），形成完整的记忆生命周期
+- **自动蒸馏**：每日 23:55 定时执行，读取当天天级记忆和 MEMORY.md，通过 LLM 进行去重、合并、修剪，输出精炼的新版 MEMORY.md
+- **梦境日记**：每次蒸馏生成一篇叙事风格的梦境日记，记录整理过程的发现和洞察，存储在 `memory/dreams/` 目录
+- **手动触发**：支持 `/memory dream [N]` 手动触发，可指定整理天数（默认 3 天，最大 30 天），完成后在对话中通知结果
+- **Web 控制台**：记忆管理页面新增「梦境日记」tab，可浏览和查看所有梦境日记
+
+相关文档：[梦境蒸馏](https://docs.cowagent.ai/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 上下文智能压缩
+
+上下文超出限制时将裁剪的部分通过 LLM 总结后异步注入，保持对话连贯性：
+
+- **LLM 异步摘要**：裁剪的消息由 LLM 总结为关键信息，同时写入天级记忆文件和注入保留的上下文
+- **多模型兼容**：优先使用主模型进行摘要，兼容 Claude、OpenAI、MiniMax 等不同模型的消息格式要求
+
+相关文档：[短期记忆](https://docs.cowagent.ai/memory/context)
+
+## 💬 Web 控制台升级
+
+Web 控制台多项功能增强：
+
+- **多会话管理**：支持创建和切换多个独立会话，侧边栏展示会话列表，支持会话标题自动生成和手动编辑
+- **密码保护**：支持为控制台设置登录密码，可通过 `web_console_password` 配置项控制
+- **深度思考**：支持在 Web 端展示模型的思考过程，可通过`enable_thinking` 配置项控制
+- **定时推送**：支持定时任务结果推送到 Web 控制台
+- **消息复制**：AI 回复支持一键复制原始 Markdown 内容
+
+## 🤖 模型相关
+
+- **视觉识别优化**：图片识别工具优先使用主模型，支持多模型厂商自动降级。相关文档：[视觉工具](https://docs.cowagent.ai/tools/vision)
+- **MiniMax 新模型**：新增 MiniMax-M2.7-highspeed 模型和 MiniMax TTS 语音合成支持。Thanks @octo-patch
+- **通义千问**：新增 qwen3.6-plus 模型支持
+
+## 🐛 其他优化与修复
+
+- **记忆提示词优化**：`MEMORY.md` 默认注入系统提示词，精细化记忆检索和写入的触发条件，增强主动写入能力
+- **系统提示词**：优化系统提示词的风格和语气引导
+- **浏览器工具**：增强隐式交互元素检测
+- **文件发送**：修复通用文件类型（tar.gz、zip 等）未能正确发送的问题。Thanks @6vision
+- **macOS 兼容**：修复网络预检超时兼容性问题。Thanks @Moliang Zhou
+- **Windows 兼容**：修复 Windows 下 PowerShell 兼容性、进程更新、终端编码等多项问题
+- **Python 3.13+**：修复 Python 3.13 及以上版本缺少 `legacy-cgi` 依赖的问题
+- **个人微信**：更新个人微信通道版本
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
diff --git a/docs/zh/releases/v2.0.7.mdx b/docs/zh/releases/v2.0.7.mdx
new file mode 100644
index 0000000..b4b6e27
--- /dev/null
+++ b/docs/zh/releases/v2.0.7.mdx
@@ -0,0 +1,64 @@
+---
+title: v2.0.7
+description: CowAgent 2.0.7 - 图像生成技能（六厂商自动路由）、新模型支持、知识库增强、Web 控制台优化及多项修复
+---
+
+## 🎨 图像生成技能
+
+新增图像生成内置技能，支持文生图、图生图、多图融合，支持 `GPT-Image-2`、`Nano Banana` 等多种模型：
+
+- **自动路由**：支持六种模型厂商自动切换，OpenAI (GPT-Image-2) → Gemini (Nano Banana) → Seedream (火山方舟) → Qwen (百炼) → MiniMax → LinkAI
+- **开箱即用**：配置 API Key 即可使用，无需手动指定模型。也支持在对话中指定特定模型
+- **灵活控制**：支持 `quality`（画质）、`size`（分辨率，512/1K~4K）、`aspect_ratio`（宽高比）等参数，各厂商自动适配有效值
+- **图片编辑**：传入已有图片即可进行编辑、风格迁移、多图融合
+- **Skill 级配置**：支持通过 `config.json` 中的 `skills.image-generation.model` 固定默认模型
+
+相关文档：[图像生成技能](https://docs.cowagent.ai/skills/image-generation)
+
+## 🤖 新模型支持
+
+- **Kimi K2.6**：新增 `kimi-k2.6` 模型支持
+- **Claude Opus 4.7**：新增 `claude-opus-4-7` 模型支持
+- **GLM 5.1**：新增 `glm-5.1` 模型支持
+- **Kimi Coding Plan**：支持 Kimi Coding Plan 模式
+- **自定义模型厂商**：新增[自定义模型](https://docs.cowagent.ai/models/custom)提供方配置，方便接入本地模型及更多厂商
+
+## 📚 知识库增强
+
+- **嵌套目录支持**：知识库列表和展示支持多级嵌套目录
+- **根级文件展示**：知识树中显示根目录下的 `index.md`、`log.md` 等文件
+- **空状态统计修复**：排除根级文件对知识库统计的干扰，正确保持空状态
+
+## 🌙 梦境记忆优化
+
+- **结构化组织**：梦境记忆文件按日期自动归档，目录结构更清晰
+- **定时抖动**：每日定时触发增加随机抖动，避免集群场景下的并发冲突
+
+## 🛠 技能系统改进
+
+- **技能管理刷新**：`/skill` 命令执行后自动加载最新技能，确保状态同步
+- **安装来源扩展**：技能安装支持多种来源格式（URL、zip、本地文件等）
+
+## 💬 Web 控制台优化
+
+- **智能自动滚动**：优化聊天窗口滚动逻辑，用户手动翻阅时不再强制跳到底部 Thanks @colin2060
+- **移动端适配**：侧边栏默认隐藏，支持点击遮罩关闭
+- **图片预览去重**：修复同一消息中图片重复渲染的问题
+- **推理内容截断**：深度思考内容超出阶段，解决前端卡顿问题
+- **会话标题修复**：修复标题自动生成的回退逻辑
+
+
+## 🐛 其他修复
+
+- **Gemini 修复**：修复 Gemini tool call 不返回结果的问题
+- **Agent 重试**：空响应重试时不再丢弃 tool_calls
+- **Docker 环境变量**：修复 Docker 环境下更新配置后环境变量未同步的问题 Thanks @sunboy0523 
+- **Python 3.7 兼容**：延迟导入 `Literal` 以兼容 Python 3.7
+- **模型切换通知**：修复切换模型后 bot_type 变更通知未显示的问题。Thanks @6vision
+- **配置命令增强**：`/config` 支持设置 `enable_thinking`
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.04.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.6...2.0.7)
diff --git a/docs/zh/releases/v2.0.8.mdx b/docs/zh/releases/v2.0.8.mdx
new file mode 100644
index 0000000..ced1b96
--- /dev/null
+++ b/docs/zh/releases/v2.0.8.mdx
@@ -0,0 +1,63 @@
+---
+title: v2.0.8
+description: CowAgent 2.0.8 - 飞书渠道全面升级（语音、流式打字机、一键扫码接入）、DeepSeek V4 / 百度千帆支持、定时任务工具优化
+---
+
+## 🪶 飞书渠道全面升级
+
+### 1. 一键扫码创建飞书应用
+
+不再需要手动到飞书开放平台建应用、填权限和事件订阅。Web 控制台和命令行启动时若未配置 `feishu_app_id`，会自动展示扫码入口，飞书扫码授权后自动创建机器人并回填配置，开箱即用。
+
+相关文档：[飞书渠道](https://docs.cowagent.ai/channels/feishu)
+
+### 2. 语音消息收发
+
+支持接收用户发送的飞书语音消息并自动转文本，回复也可走 TTS 以语音形式发出。同时优化了中文短语音的识别准确度。
+
+### 3. 流式打字机回复
+
+接入飞书 CardKit 流式卡片，**默认开启**，体验对齐 Web 端：
+
+- 多轮 Agent 场景下中间过场消息与最终回复分卡呈现
+- 针对 DeepSeek 等高频输出模型做了专门优化，速度与 Web 端持平
+- 不支持时自动回退为普通文本回复，无需手动配置
+- 要求飞书客户端 ≥ 7.20
+
+飞书语音消息收发与流式打字机的基础能力来自社区贡献 #2791 Thanks @yangluxin613
+
+## 🤖 新模型支持
+
+- **DeepSeek V4 系列**：新增 `deepseek-v4-pro` / `deepseek-v4-flash`，并将默认模型切换为 `deepseek-v4-flash`
+- **思考模型开关统一**：DeepSeek V4、Qwen3 等思考模型的开关行为对齐到 `enable_thinking`
+- **百度千帆模型接入**：新增百度千帆厂商，支持 `ernie-5.0`、`ernie-4.5-turbo-128k` 等模型，并支持图像识别工具，相关文档查看 [百度千帆](https://docs.cowagent.ai/models/qianfan)。#2790 Thanks @jimmyzhuu
+- **新增有道翻译**：`translate` 模块新增有道翻译支持 #2797 Thanks @Zmjjeff7
+
+## 🛠 OpenAI 客户端重构
+
+- **去 SDK 依赖**：OpenAI Bot 改为原生 HTTP 实现，启动更轻、依赖冲突更少
+- **Web 控制台提示**：模型配置 API Base 输入框加入版本路径占位提示
+
+## ⏰ 定时任务记忆增强
+
+- **任务结果可被追问**：定时任务的执行结果自动注入到接收方的会话历史中，下一轮对话可直接追问，无需重新交代上下文 Thanks @huangrichao2020
+- **不污染长期记忆**：注入的调度对话不会被纳入每日梦境记忆汇总，避免高频任务把记忆刷满
+- **避免越跑越慢**：调度任务自己的上下文长度自动控制在合理范围内，长期反复执行也不会越积越大、拖慢响应
+
+## 🔧 工具与安全
+
+- **图像识别模型**：让 `tools.vision.model` 配置真正生效，未配置时自动 fallback #2792 Thanks CNXudiandian
+- **Bash 安全确认**：仅对工作区外的破坏性删除做二次确认，工作区内常规操作不再打扰
+
+## 🐛 其他修复
+
+- 修复 Deep Dream 在多实例场景下重复触发
+- 修复 DeepSeek 多轮对话中部分历史轮次缺失 `reasoning_content`
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+> ⚠️ 飞书一键创建应用依赖 `lark-oapi>=1.5.5`，`cow update` 会自动拉取；手动部署请确保依赖已更新。
+
+**发布日期**：2026.05.06 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.7...2.0.8)
diff --git a/docs/zh/releases/v2.0.9.mdx b/docs/zh/releases/v2.0.9.mdx
new file mode 100644
index 0000000..957e0ce
--- /dev/null
+++ b/docs/zh/releases/v2.0.9.mdx
@@ -0,0 +1,65 @@
+---
+title: v2.0.9
+description: CowAgent 2.0.9 - 新增模型管理、MCP 协议支持、浏览器登录态持久化、新模型接入
+---
+
+## 🖥️ 新增模型管理
+
+Web 控制台新增「模型」页面，按 **模型厂商 + 模型能力** 进行管理，支持对话、图像、语音、向量模型和搜索能力的配置：
+
+- **多厂商配置**：所有厂商的 API Key / API Base 在顶部统一维护，下方所有能力立即生效，无需重复填写
+- **图像模型**：图像理解与图像生成均可独立选择厂商和模型，未指定时跟随主模型自动选择
+- **语音模型**：语音识别和合成可独立配置，新增千问、智谱 ASR/TTS 模型
+- **向量模型**：支持配置 Embedding 模型（用于记忆及知识库检索），新增支持 OpenAI、通义、豆包、智谱等；切换模型后需执行 `/memory rebuild-index` 在线重建索引
+- **搜索能力**：联网搜索能力升级，支持博查、百度、智谱等多个厂商，自动模式下 Agent 可综合多来源搜索结果进行深度研究
+
+相关文档：[模型概览](https://docs.cowagent.ai/models)
+
+<img width="720" alt="20260522113305" src="https://cdn.link-ai.tech/doc/20260522113305.png" />
+
+
+## 🧩 MCP 协议支持
+
+支持 **MCP（Model Context Protocol）** 协议，从固定工具集扩展为开放可插拔的工具生态，任何兼容 MCP 协议的服务均可作为工具直接接入 Agent。
+
+- 原生 JSON-RPC 实现，零额外依赖，同时支持 `stdio` 和 `sse` 两种传输
+- 兼容 Claude Desktop / Cursor 等主流风格的 `mcpServers` 配置，优先读取 `~/cow/mcp.json`
+
+相关文档：[MCP 工具](https://docs.cowagent.ai/tools/mcp)。Thanks @yangluxin613 (#2801)
+
+## 🌐 浏览器登录态持久化
+
+针对需要登录、有反爬机制的网站，浏览器工具支持登录一次后长期复用登录态，并允许接入用户自己的真实 Chrome 以通过指纹检测：
+
+- **持久化用户配置（默认）**：默认使用 `~/.cow/browser_profile` 作为浏览器用户目录，登录一次后下次自动复用登录态
+- **CDP 模式**：通过 `tools.browser.cdp_endpoint` 接管真实 Chrome 浏览器，享有完整浏览器权限
+
+相关文档：[浏览器工具](https://docs.cowagent.ai/tools/browser)。Thanks @leafmove (#2809)
+
+## 🤖 模型新增与优化
+
+- **模型新增**：`gpt-5.5`、`gemini-3.5-flash`、`qwen3.7-max`、`ernie-5.1`
+- **模型优化**：DeepSeek V4 支持 `reasoning_effort` 思考深度参数；修复 MiMo 等思考模型通过 OpenAI 兼容协议接入的问题
+
+## 🔒 部署与安全
+
+- **默认本机访问**：Web 控制台 `web_host` 配置默认绑定 `127.0.0.1`，服务器部署时可手动设置为 `0.0.0.0` 并设置密码。Thanks @August829、@yidaozhongqing、@YLChen-007、@icysun
+- **前端资源完全本地化**：第三方 CSS / JS 全部本地分发，离线 / 内网环境也能正常加载控制台。Thanks @gitlayzer (#2816)
+
+## 🛠 体验优化与修复
+
+- **TTS 适配更多通道**：Web对话、个人微信、飞书、钉钉、企微智能机器人均已支持回复语音，详情查看 [通道概览](https://docs.cowagent.ai/channels)
+- **日志面板增强**：根据日志等级差异化高亮展示、支持根据等级筛选。Thanks @yangluxin613 (#2807)
+- **Web 控制台自动启动**：程序启动后自动打开 Web 控制台。Thanks @yangluxin613 (#2804)
+- **Ctrl+C 干净退出**：不再打印一长串 `KeyboardInterrupt` 堆栈。Thanks @yangluxin613 (#2806)
+- **文件夹上传**：Web 端支持目录上传，路径校验适配 Windows。Thanks @TryToMakeUsBetter (#2814)
+- 修复定时任务在某些情况下重复执行的问题。Thanks @CNXudiandian (#2820)
+- 修复定时任务带时区时单次任务不触发的问题。Thanks @AethericSpace
+- 修复执行失败的工具调用在页面刷新后不显示的问题。Thanks @a1094174619 (#2822)
+- 修复企微机器人消息中包含非法控制字符导致投递失败的问题。Thanks @Jacques-Zhao (#2810)
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.05.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.8...2.0.9)
diff --git a/docs/zh/releases/v2.1.0.mdx b/docs/zh/releases/v2.1.0.mdx
new file mode 100644
index 0000000..2df19c0
--- /dev/null
+++ b/docs/zh/releases/v2.1.0.mdx
@@ -0,0 +1,68 @@
+---
+title: v2.1.0
+description: CowAgent 2.1.0 - 国际化支持、新增 Telegram / Discord / Slack / 微信客服通道、命令行交互升级、MCP协议增强、新模型接入
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.0) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.0)
+
+## 📱 新增接入通道
+
+本次新增多个主流平台通道，配置即用，开箱接入：
+
+- **Telegram Bot**：接入 Telegram 机器人，支持文本与多媒体消息
+- **Discord Bot**：接入 Discord 机器人，可在频道与私信中对话
+- **Slack Bot**：接入 Slack 机器人，融入团队协作场景
+- **微信客服**：新增微信客服通道，支持接收图片与文件并自动并入下一轮对话，多媒体上下文体验对齐其它通道。Thanks @6vision (#2840)
+
+相关文档：[通道概览](https://docs.cowagent.ai/zh/channels)
+
+## 🌍 国际化支持
+
+CowAgent 引入全链路国际化框架，面向全球开发者，支持根据系统语言自动适配：
+
+- **全链路本地化**：安装引导、命令行、日志和报错、Agent 系统提示词等均已支持本地化语言适配
+- **自动识别语言**：默认 `auto` 模式按系统语言自动判断，也可在 `config.json` 中通过 `cow_lang` 显式配置。首批提供英文与中文，后续将持续扩充更多语言。
+- **控制台一键切换**：Web 控制台支持在线切换系统语言，实时生效
+## ⌨️ 命令行交互升级
+
+- **一键安装脚本优化**：安装脚本简化流程并支持交互式配置——可选择语言，并在引导中按需选择模型与通道，几分钟即可完成部署
+- **流式输出体验**：Terminal 通道支持 Agent 模式的推理过程、工具调用与流式回复
+- **命令模糊匹配**：支持命令缩写及近似拼写自动提示，内置常用快捷指令，并可在配置文件中自定义别名。Thanks @lyteen (#2850)
+- **支持任务取消**：Agent 任务执行中可主动中断，Web 端新增中止按钮，其他通道可发送 `/cancel` 进行中止
+
+相关文档：[命令行指南](https://docs.cowagent.ai/zh/cli/general)
+
+## 🧩 MCP 协议增强
+
+MCP 工具新增对 **Streamable HTTP** 传输的支持，在原有 `stdio` 和 `sse` 基础上进一步兼容更多 MCP 服务，可直接接入采用流式 HTTP 协议的远程工具。
+
+相关文档：[MCP 工具](https://docs.cowagent.ai/zh/tools/mcp)
+
+## 🤖 模型新增与优化
+
+- **模型新增**：`claude-opus-4-8`、小米 `MiMo`
+- **模型优化**：修复部分模型的工具调用参数 JSON 解析失败问题 (#2823)
+
+相关文档：[模型概览](https://docs.cowagent.ai/zh/models)
+
+## 🧠 记忆与检索优化
+
+- **关键词检索优化**：修复中文关键词搜索命中率低、纯英文关键词出现查询为空的问题
+- **向量检索增强**：优化向量检索流程，并提升 Python 版本兼容性
+
+Thanks @yangluxin613 (#2832)
+
+## 🛠 体验优化与修复
+
+- **文件访问收敛**：Web 端文件读取与发送默认限制在用户主目录及 Agent 工作空间内，防止任意文件读取，可通过 `web_file_serve_root` 配置放开范围
+- **定时任务更稳定**：修复定时任务推送在个人微信通道重启后失效的问题
+- **浏览器工具**：修复导航 URL 中非 http 协议被丢弃的问题；优化浏览器内存占用
+- **微信公众号**：被动回复支持合并缓存文本片段、任务执行中先行下发已就绪片段、支持发送本地 `file://` 图片。Thanks @6vision (#2848)
+- **企微机器人响应提速**：回调改为异步分发，避免企微 5 秒超时导致的消息丢失
+- **登录鲁棒性**：修复 `web_password` 为非字符串时登录报错的问题
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/zh/guide/upgrade)。
+
+**发布日期**：2026.06.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.9...2.1.0)
diff --git a/docs/zh/releases/v2.1.1.mdx b/docs/zh/releases/v2.1.1.mdx
new file mode 100644
index 0000000..5366984
--- /dev/null
+++ b/docs/zh/releases/v2.1.1.mdx
@@ -0,0 +1,63 @@
+---
+title: v2.1.1
+description: CowAgent 2.1.1：自主进化能力、Web 控制台消息管理与多会话并行、MCP 跨平台增强、多模型接入与优化
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.1) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.1)
+
+## 🧬 自主进化能力
+
+CowAgent 新增 **自主进化（Self-Evolution）** 能力，让 Agent 不止于完成单次任务，而是在与你的日常协作中持续成长：
+
+- **空闲后自动复盘**：对话空闲后自动复盘，修正技能在使用中暴露的问题、创建可复用的新技能，处理遗留的未完成事项，并将重要信息补充进记忆与知识库
+- **静默执行、按需提醒**：仅在实际有改动时主动告知本次调整内容，无变更时全程静默
+- **安全可回退**：每次复盘前自动备份，可随时撤销本次改动；内置技能受保护，所有读写均限定在工作空间内
+
+新安装用户默认开启，已有用户可在 Web 控制台 **设置 → Agent 配置** 中一键开启。
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/web-console-evolution-demo-zh.png" alt="自主进化对话示例" />
+
+相关文档：[自主进化](https://docs.cowagent.ai/zh/memory/self-evolution)
+
+## 💬 Web 控制台升级
+
+Web 控制台的聊天体验进一步增强：
+
+- **消息管理**：用户与机器人的消息均支持编辑、删除、重新生成；代码块新增语言标签和一键复制按钮
+- **多会话并行**：支持多个会话同时进行、互不干扰，切回会话时自动恢复实时流式输出
+- **细节优化**：支持将文件拖拽到整个聊天区域；删除当前会话后自动切换到相邻会话
+
+Thanks @core-power (#2865)
+
+## 🧩 MCP 跨平台增强
+
+- **Windows 兼容修复**：修复 MCP 在 Windows 下 `stdio` 通信不可用的问题，并支持通过 `mcp.json` 配置服务超时时间
+- **并发调用支持**：`sse` 与 `streamable-http` 传输支持跨会话并发调用，多工具响应更快
+
+Thanks @xliu123321 (#2859)
+
+相关文档：[MCP 工具](https://docs.cowagent.ai/zh/tools/mcp)
+
+## 🤖 模型新增与优化
+
+- **MiniMax-M3**：新增并设为默认模型，保留 M2.7 系列作为可选项。Thanks @octo-patch (#2855)
+- **通义千问 qwen3.7-plus**：支持多模态对话
+- **语音识别模型可选**：Web 控制台支持选择 ASR（语音识别）模型并持久化保存。Thanks @nightwhite (#2857)
+- **安装菜单简化**：一键安装脚本精简模型选择菜单，新增小米 MiMo 选项
+
+相关文档：[模型概览](https://docs.cowagent.ai/zh/models)
+
+## 🛠 体验优化与修复
+
+- **Python 3.13 支持**：修复在 Python 3.13 环境下的安装与依赖兼容问题
+- **国际化体验**：通道列表按界面语言排序展示；优化 `auto` 模式下的语言自动回退逻辑
+- **任务取消更可靠**：修复部分场景下流式回复无法中断的问题
+- **CLI 增强**：`cow status` 新增显示当前项目路径
+- **部署安全加固**：凭证文件拦截范围收敛至 `~/.cow/.env`，不再误拦其他目录（Thanks @orbisai0security #2863）；微信公众号在 `wechatmp_token` 为空时拒绝 Webhook 请求
+- **群任务看板插件**：新增群聊任务看板插件源。Thanks @Wyh-max-star (#2853)
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/zh/guide/upgrade)。
+
+**发布日期**：2026.06.09 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.0...2.1.1)
diff --git a/docs/zh/releases/v2.1.2.mdx b/docs/zh/releases/v2.1.2.mdx
new file mode 100644
index 0000000..b45a0f3
--- /dev/null
+++ b/docs/zh/releases/v2.1.2.mdx
@@ -0,0 +1,67 @@
+---
+title: v2.1.2
+description: CowAgent 2.1.2：Web 控制台多项管理能力升级、自主进化体验优化、模型新增支持、企业微信智能机器人回调模式、安全加固和体验优化
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.2) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.2)
+
+## 💬 Web 控制台优化
+
+本次 Web 控制台围绕「可视化管理」做了多项增强，让更多配置无需改文件即可在界面完成：
+
+- **定时任务管理**：支持在控制台直接查看、编辑、启用/停用、删除任意定时任务，任务列表按启用状态与下次执行时间排序。Thanks @HnBigVolibear (#2892)
+- **知识库分类与文档管理**：知识库支持按分类组织，可在界面管理分类下的文档。Thanks @yangziyu-hhh (#2893)
+- **多自定义模型厂商**：支持配置多个 OpenAI 兼容供应商并一键切换当前生效项，且兼容已有配置。Thanks @kirs-hi (#2877)
+- **会话重命名**：支持手动重命名会话，便于区分多个并行任务 (#2897)
+- **Bash 流式输出**：长时间运行的 Bash 命令支持流式实时输出进度。Thanks @yangziyu-hhh (#2879)
+
+## 🧬 自主进化体验优化
+
+延续上个版本的自主进化能力，本次迭代进一步优化：
+
+- **触发阈值下调**：默认复盘触发阈值下调，更快触发复盘、沉淀经验
+- **避免并发冲突**：单轮任务耗时较长时不再误触发空闲复盘，避免与主对话相互干扰
+- **自进化摘要优化**：优化摘要生成提示词，精简篇幅、提升信息密度，并跟随对话语言输出
+
+相关文档：[自主进化](https://docs.cowagent.ai/zh/memory/self-evolution)
+
+## 🤖 模型新增
+
+- **kimi-k2.7-code**：新增并设为 Kimi 默认模型，同时提供 `kimi-k2.7-code-highspeed` 高速版
+- **glm-5.2**：新增并设为 GLM 默认模型
+
+相关文档：[模型概览](https://docs.cowagent.ai/zh/models)
+
+## 🏢 企业微信智能机器人回调模式
+
+企业微信智能机器人通道在原有长连接的基础上，新增 **HTTP 回调模式**，让无法保持长连接的部署环境也能稳定接入：
+
+- **模式切换**：通过 `wecom_bot_mode` 在 `websocket`（长连接）与 `webhook`（回调）之间切换
+- **加密传输**：回调模式完整支持 URL 验签、消息解密与被动回复加密
+- **稳定性优化**：修复回复中断、流式提前结束、临时图片文件泄漏等问题
+
+Thanks @6vision (#2896 #2869)
+
+相关文档：[企业微信智能机器人](https://docs.cowagent.ai/zh/channels/wecom-bot)
+
+## 🔒 安全加固
+
+- **视觉工具 SSRF 防护**：解析图片 URL 前校验目标地址，拦截指向内网、回环及云服务器元数据接口的请求。Thanks @kirs-hi (#2886)
+- **网页抓取 SSRF 防护**：`web_fetch` 抓取前校验目标地址，并逐跳校验重定向目标，防止通过跳转绕过校验。Thanks @christop (#2900)
+- **技能安装路径穿越防护**：安装技能时校验路径，防止恶意技能名通过路径穿越逃逸 `skills/` 目录、写入越权位置。Thanks @kirs-hi (#2886)
+
+## 🛠 体验优化与修复
+
+- **CLI 自重启**：新增 self-restart 命令，Agent 可自行重启进程
+- **Windows 兼容**：将 cow CLI 自动写入用户 PATH；修复 `python -c` 长命令超出 `cmd.exe` 长度限制的问题；安装时避免 greenlet 源码编译
+- **角色插件自定义**：角色插件支持通过 `roles/*.json` 下的独立提示词文件进行自定义。Thanks @sufan721 (#2891)
+- **稳定性修复**：修复 `/cancel` 时的 KeyError 与图片压缩死循环（Thanks @kirs-hi #2888）
+- **一键安装优化**：更新启动脚本与默认配置，修复 ASR/TTS 默认值、自主进化开关及安装过程卡顿等问题
+- **视觉工具稳定性**：提升视觉工具的超时时间与 max_tokens
+- **记忆蒸馏优化**：深度梦境蒸馏移除输出长度限制，避免大体量 `MEMORY.md` 被截断
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/zh/guide/upgrade)。
+
+**发布日期**：2026.06.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.1...2.1.2)
diff --git a/docs/zh/releases/v2.1.3.mdx b/docs/zh/releases/v2.1.3.mdx
new file mode 100644
index 0000000..937888c
--- /dev/null
+++ b/docs/zh/releases/v2.1.3.mdx
@@ -0,0 +1,76 @@
+---
+title: v2.1.3
+description: CowAgent 2.1.3：正式推出桌面客户端（macOS / Windows），知识库文档管理增强，新增 MCP 工具按需检索，繁体中文支持，模型支持，并带来安全与体验的多项改进
+---
+
+🌐 [English](https://docs.cowagent.ai/releases/v2.1.3) | [中文](https://docs.cowagent.ai/zh/releases/v2.1.3)
+
+## 🖥 桌面客户端
+
+正式推出 **CowAgent 桌面客户端**，支持 **macOS 与 Windows**，让本地超级 AI 助理真正做到开箱即用。
+
+下载地址：[CowAgent客户端](https://cowagent.ai/zh/download/)
+
+<img src="https://cdn.jsdelivr.net/gh/zhayujie/cowagent-assets@main/screenshots/zh/desktop-chat-demo-zh.png" alt="CowAgent 桌面客户端" />
+
+核心特性：
+
+- **开箱即用**：内置完整的 Agent 运行环境，安装后直接启动，无需安装 Python 等依赖
+- **完整对话体验**：流式对话、会话管理、工具调用步骤展示、Markdown 渲染，并支持发送与展示图片 / 视频 / 文件
+- **可视化管理**：配置管理、模型配置、知识库、定时任务、技能系统、记忆等页面与 Web 控制台对齐，在原生界面即可管理
+- **通道接入**：支持在客户端内扫码接入各类消息通道
+- **自动更新**：支持版本自动检查与一键更新，优化不同地区的下载速度
+- **原生体验**：首次启动引导、跟随系统语言、平台自适应的窗口交互
+
+相关文档：[桌面客户端](https://docs.cowagent.ai/zh/guide/desktop)
+
+## 📚 知识库
+
+- **文档创建与导入**：知识库支持在界面直接新建文档、导入外部文档。
+- **索引自动维护**：根据真实目录树自动重建 `knowledge/index.md` 索引文件，避免索引漂移或丢失文档
+- **向量模型修复**：知识库索引同步复用统一的嵌入厂商，确保生成向量而非退化为关键词检索
+
+Thanks @yangziyu-hhh
+
+相关文档：[知识库](https://docs.cowagent.ai/zh/memory/knowledge)
+
+## 🔌 MCP 工具智能检索
+
+针对接入大量 MCP 工具时上下文膨胀的问题，新增 **按需工具检索** 能力，通过 RAG 向量检索按需加载与当前任务相关的 MCP 工具，减少无关工具对上下文的占用。Thanks @fengyl07
+
+相关文档：[MCP 工具](https://docs.cowagent.ai/zh/tools/mcp)
+
+## 🌏 繁体中文支持
+
+Web 控制台、日志与文档新增 **繁体中文（zh-Hant）** 支持，界面语言可跟随系统或手动切换。Thanks @anomixer (#2935)
+
+## 🤖 模型新增
+
+- 新增支持 **claude-sonnet-5**、**claude-fable-5** 
+- 新增支持 **doubao-seed-2-1-pro**、**doubao-seed-2-1-turbo**
+
+相关文档：[模型概览](https://docs.cowagent.ai/zh/models)
+
+
+## 🔒 安全加固
+
+- **敏感文件读取防护**：加固对凭证等敏感文件的访问，防止绕过读取。Thanks @fengyl07 (#2913)
+- **浏览器访问防护**：浏览器访问网页时拦截指向内网及云服务器内部地址的请求，降低被诱导访问内部服务的风险。Thanks @Jiangrong-W
+- **配置解析加固**：使用更安全的方式解析配置内容，避免潜在的代码执行风险。Thanks @shunfeng8421
+
+## 🛠 体验优化与修复
+
+- **自定义供应商扩展**：嵌入与视觉模型支持配置自定义供应商；同时修复记忆查询在 Windows 下的问题。Thanks @HnBigVolibear
+- **文件编辑更稳**：编辑文件时更好地保留原有缩进，且模糊匹配时不改动未涉及的内容。Thanks @weijun-xia (#2942)
+- **命令输出乱码修复**：修复执行命令产生大量输出时可能出现的中文乱码。Thanks @weijun-xia (#2941)
+- **Azure OpenAI 修复**：修复 Azure OpenAI 的流式输出与相关配置问题。Thanks @Tunnello
+- **企业微信智能机器人**：补充 webhook（回调）模式的接入文档。Thanks @6vision
+- **深度梦境开关**：新增 `deep_dream_enabled` 配置开关，可按需开启或关闭深度梦境。
+- **稳定性提升**：优化 Web 服务的连接回收，并修复自主进化过程中的若干问题 (#2924, #2904)
+
+## 📦 升级方式
+
+- **桌面客户端**：前往 [下载页](https://cowagent.ai/zh/download/) 获取最新版本。
+- **源码部署**：执行 `cow update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/zh/guide/upgrade)。
+
+**发布日期**：2026.07.08 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.1.2...2.1.3)
diff --git a/docs/zh/skills/create.mdx b/docs/zh/skills/create.mdx
new file mode 100644
index 0000000..45cef14
--- /dev/null
+++ b/docs/zh/skills/create.mdx
@@ -0,0 +1,58 @@
+---
+title: 创造技能
+description: 通过对话创建自定义技能
+---
+
+CowAgent 内置了 Skill Creator，可以通过自然语言对话快速创建、安装或更新技能。
+
+## 使用方式
+
+直接在对话中描述你想要的技能，Agent 会自动完成创建：
+
+- 将工作流程固化为技能："帮我把这个部署流程创建为一个技能"
+- 对接第三方 API："根据这个接口文档创建一个技能"
+- 安装远程技能："帮我安装 xxx 技能"
+
+## 创建流程
+
+1. 告诉 Agent 你想创建的技能功能
+2. Agent 自动生成 `SKILL.md` 说明文件和运行脚本
+3. 技能保存到工作空间的 `~/cow/skills/` 目录
+4. 后续对话中 Agent 会自动识别并使用该技能
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
+</Frame>
+
+## SKILL.md 格式
+
+创建的技能遵循标准的 SKILL.md 格式：
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| 字段 | 说明 |
+| --- | --- |
+| `name` | 技能名称，需与目录名一致 |
+| `description` | 技能描述，Agent 据此决定是否调用 |
+| `metadata.requires.bins` | 依赖的系统命令 |
+| `metadata.requires.env` | 依赖的环境变量 |
+| `metadata.always` | 是否始终加载（默认 false） |
+
+<Tip>
+  详细开发文档可参考 [Skill Creator 说明](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md)。
+</Tip>
diff --git a/docs/zh/skills/hub.mdx b/docs/zh/skills/hub.mdx
new file mode 100644
index 0000000..65c8a21
--- /dev/null
+++ b/docs/zh/skills/hub.mdx
@@ -0,0 +1,65 @@
+---
+title: 技能广场
+description: 浏览、搜索和安装 AI Agent 技能
+---
+
+[Cow Skill Hub](https://skills.cowagent.ai/) 是开源的 AI Agent 技能广场，汇集了官方推荐、社区贡献和第三方平台（GitHub、ClawHub 等）的技能。
+
+开源仓库：[github.com/zhayujie/cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+<img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
+
+## 功能
+
+- **浏览技能**：按类别（推荐 / 社区 / 第三方）和标签筛选
+- **搜索技能**：按名称或描述搜索
+- **查看详情**：查看技能文档、文件内容、安装命令和依赖的环境变量
+- **一键安装**：复制安装命令即可在 CowAgent 中使用
+
+## 安装技能
+
+在对话中或终端中执行安装命令：
+
+<CodeGroup>
+```text 对话
+/skill install <name>
+```
+
+```bash 终端
+cow skill install <name>
+```
+</CodeGroup>
+
+也可以在对话中浏览技能广场：
+
+```text
+/skill list --remote
+/skill search <关键词>
+```
+
+除了在列表中展示的精选技能，还可以通过 **CLI命令 + Skill Hub** 安装各种第三方技能（**GitHub、ClawHub、LinkAI、URL** 等）参考 [安装技能](/zh/skills/install)。
+
+## 贡献技能
+
+欢迎向技能广场提交你的技能：
+
+1. 访问 [skills.cowagent.ai/submit](https://skills.cowagent.ai/submit)
+2. 使用 GitHub 或 Google 账号登录
+3. 上传包含 `SKILL.md` 的文件夹或 zip 包
+4. 自动解析技能名称、显示名称和描述，可按需修改
+5. 提交后将经过安全检查和审核后发布
+
+<img src="https://cdn.link-ai.tech/doc/20260401111904.png" width="800" />
+
+技能文件结构：
+
+```
+your-skill/
+├── SKILL.md        # 必须，放在根目录
+├── scripts/        # 可选，运行脚本
+└── resources/      # 可选，其他资源
+```
+
+<Tip>
+  技能基于 `SKILL.md` 文件构建，你也可以在技能详情页下载 SKILL.md，用于任何支持自定义指令的 Agent（如 OpenClaw、Cursor、Claude Code 等）。
+</Tip>
diff --git a/docs/zh/skills/image-generation.mdx b/docs/zh/skills/image-generation.mdx
new file mode 100644
index 0000000..5a174a8
--- /dev/null
+++ b/docs/zh/skills/image-generation.mdx
@@ -0,0 +1,98 @@
+---
+title: image-generation - 图像生成
+description: 文生图 / 图生图 / 多图融合，支持多家厂商自动路由与回退
+---
+
+通用的图像生成与编辑技能，支持 OpenAI、Gemini、Seedream（火山方舟）、Qwen（百炼）、MiniMax、LinkAI 共六家厂商。配好任意一家的 Key 即可使用，配多家可享受自动回退。
+
+## 支持的模型
+
+| 厂商 | 模型 / 别名 | 特点 |
+| --- | --- | --- |
+| OpenAI | `gpt-image-2`、`gpt-image-1` | 通用文生图，高质量，支持 `quality` 控制画质 |
+| Gemini Nano Banana | `nano-banana-2`、`nano-banana-pro`、`nano-banana` | 对应 `gemini-3.1-flash`、`gemini-3-pro`、`gemini-2.5-flash` 的图像版本 |
+| Seedream（火山方舟） | `seedream-5.0-lite`、`seedream-4.5` | 原生 2K–4K，最多 14 张图融合 |
+| Qwen（百炼） | `qwen-image-2.0`、`qwen-image-2.0-pro` | 擅长中文排版和图文融合 |
+| MiniMax | `image-01` | 简单快速 |
+| LinkAI | 任意模型 | 统一网关，作为兜底 |
+
+## 模型选择
+
+默认走「自动路由 + 失败回退」：
+
+1. 按 `OpenAI → Gemini → Seedream → Qwen → MiniMax → LinkAI` 顺序选第一个已配置的厂商
+2. 遇到 401、模型未开通、网络异常等错误时，自动切到下一家
+3. 用户在对话里指定模型时（如「用 seedream 画一只猫」），对应厂商会被提到最前优先尝试
+
+如需固定使用某个模型：
+
+```json
+{
+  "skills": {
+    "image-generation": {
+      "model": "seedream-5.0-lite"
+    }
+  }
+}
+```
+
+## 配置 API Key
+
+<Tip>
+  推荐通过 [Web 控制台](/zh/channels/web) 的「模型管理」页面配置，配好的对话模型 Key 会被图像生成技能自动复用，无需重复配置。也可手动编辑配置文件或在对话中通过 `env_config` 工具临时设置。
+</Tip>
+
+凭证统一复用主模型厂商的 Key：
+
+| 字段 | 对应厂商 |
+| --- | --- |
+| `openai_api_key` | OpenAI |
+| `gemini_api_key` | Gemini |
+| `ark_api_key` | 火山方舟（Seedream） |
+| `dashscope_api_key` | 阿里百炼（Qwen） |
+| `minimax_api_key` | MiniMax |
+| `linkai_api_key` | LinkAI |
+
+
+## 开启和关闭
+
+技能会根据 API Key 自动调整状态：
+
+- **已配置 Key**：Agent 收到画图请求时直接调用
+- **未配置 Key**：技能仍会出现在上下文中（标记为「需要配置」），Agent 会引导用户去配 Key
+
+如需手动控制：
+
+```text
+/skill disable image-generation    # 关闭
+/skill enable image-generation     # 重新开启
+```
+
+终端等价命令：`cow skill disable image-generation` / `cow skill enable image-generation`。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 默认 | 说明 |
+| --- | --- | --- | --- | --- |
+| `prompt` | string | 是 | — | 图像描述 |
+| `image_url` | string / list | 否 | null | 编辑用的输入图，本地路径或 URL；传列表为多图融合 |
+| `quality` | string | 否 | auto | `low` / `medium` / `high`，仅部分厂商支持 |
+| `size` | string | 否 | auto | `512` / `1K` / `2K` / `3K` / `4K`，或像素值如 `1024x1024` |
+| `aspect_ratio` | string | 否 | null | `1:1` / `3:2` / `2:3` / `16:9` / `9:16` / `21:9`；Gemini 还支持 `1:4` / `4:1` / `1:8` / `8:1` |
+
+<Warning>
+  **质量越高、分辨率越大，耗时和成本越高。** 日常对话用默认（`auto`）或 `quality=low` + `size=1K` 即可，约 20 秒出图；做海报或明确要高清时再上 `high` + `2K/4K`，可能需要 1–5 分钟。
+</Warning>
+
+## 常见用法
+
+- **文生图**：根据描述生成插画、海报、图标、头像、分镜图等
+- **图生图**：在已有图片上改风格、换元素、加装饰、加文字等
+- **多图融合**：把多张参考图合成一张（换装、角色合影等）
+
+<Note>
+- bash 超时建议设 600 秒：单厂商 HTTP 超时 300 秒，脚本可能依次尝试多家
+- 输入图片自动压缩到 4MB 以内、最长边不超过 4096px
+- Gemini / Seedream / Qwen / MiniMax 不支持 `quality` 参数
+- Seedream 默认出 2K 图；`seedream-5.0-lite` 支持到 3K，`seedream-4.5` 支持到 4K
+</Note>
diff --git a/docs/zh/skills/index.mdx b/docs/zh/skills/index.mdx
new file mode 100644
index 0000000..d30a2ef
--- /dev/null
+++ b/docs/zh/skills/index.mdx
@@ -0,0 +1,65 @@
+---
+title: 技能概览
+description: CowAgent 技能系统介绍
+---
+
+技能（Skill）为 Agent 提供无限的扩展性。每个 Skill 由说明文件（`SKILL.md`）、运行脚本（可选）、资源（可选）组成，描述如何完成特定类型的任务。
+
+Skill 与 Tool 的区别：Tool 是由代码实现的原子操作（如读写文件、执行命令），Skill 则是基于说明文件的高级工作流，可以组合调用多个 Tool 来完成复杂任务。
+
+## 获取技能
+
+CowAgent 提供多种方式获取技能：
+
+- [Cow 技能广场](https://skills.cowagent.ai/) — 在线浏览所有可用技能，或通过 `/skill list --remote` 在对话中浏览和安装
+- **GitHub** — 直接从 GitHub 仓库安装，支持批量安装
+- **ClawHub** — 通过 `/skill install clawhub:名称` 安装 ClawHub 上的技能 (4w+个)
+- **LinkA** — 通过 `/skill install linkai:编码` 安装 LinkAI 上的公开资源和创建的知识库/数据库/工作流/插件等资源
+- **URL** — 从 zip 压缩包或 SKILL.md 链接安装
+- **对话创建** — 通过自然语言对话让 Agent 自动创建技能
+
+详细安装方式参考 [安装技能](/zh/skills/install) 和 [技能管理命令](/zh/cli/skill)。也可以通过对话 [创建技能](/zh/skills/create)，或向 [Skill Hub](https://skills.cowagent.ai/submit) 贡献你的技能。
+
+## 技能加载优先级
+
+1. **工作空间技能**（最高）：`~/cow/skills/`
+2. **项目内置技能**（最低）：`skills/`
+
+同名技能按优先级覆盖。
+
+## 技能文件结构
+
+```
+skills/
+├── my-skill/
+│   ├── SKILL.md          # Skill description (frontmatter + instructions)
+│   ├── scripts/          # Execution scripts (optional)
+│   └── resources/        # Additional resources (optional)
+```
+
+### SKILL.md 格式
+
+```markdown
+---
+name: my-skill
+description: Brief description of the skill
+metadata:
+  emoji: 🔧
+  requires:
+    bins: ["curl"]
+    env: ["MY_API_KEY"]
+  primaryEnv: "MY_API_KEY"
+---
+
+# My Skill
+
+Detailed instructions...
+```
+
+| 字段 | 说明 |
+| --- | --- |
+| `name` | 技能名称，需与目录名一致 |
+| `description` | 技能描述，Agent 据此决定是否调用 |
+| `metadata.requires.bins` | 依赖的系统命令 |
+| `metadata.requires.env` | 依赖的环境变量 |
+| `metadata.always` | 是否始终加载（默认 false） |
diff --git a/docs/zh/skills/install.mdx b/docs/zh/skills/install.mdx
new file mode 100644
index 0000000..bbec9d9
--- /dev/null
+++ b/docs/zh/skills/install.mdx
@@ -0,0 +1,66 @@
+---
+title: 安装技能
+description: 通过命令一键安装来自多种来源的技能
+---
+
+CowAgent 支持通过统一的 `install` 命令安装来自 [Cow 技能广场](https://skills.cowagent.ai/)、GitHub、ClawHub、LinkAI 以及任意 URL 上的技能。在对话中使用 `/skill install`，在终端中使用 `cow skill install`。
+
+## 从Cow技能广场安装
+
+访问 [skills.cowagent.ai](https://skills.cowagent.ai/) 浏览所有可用技能，找到想要的技能后直接安装，例如：
+
+```text
+/skill list --remote
+/skill install pptx
+```
+
+## 从 GitHub 安装
+
+> Github上的所有技能都可以直接安装，支持仓库级批量安装和指定子目录安装，例如：
+
+```text
+/skill install larksuite/cli
+/skill install https://github.com/larksuite/cli/tree/main/skills/lark-im
+```
+
+## 从 ClawHub 安装
+
+[ClawHub](https://clawhub.ai/) 上的所有技能 (4w+个) 都可以一键安装，例如：
+
+
+```text
+/skill install clawhub:<name>
+```
+
+## 从 LinkAI 安装
+
+[LinkAI](https://link-ai.tech/console) 上的所有公开资源 (1w+个应用/工作流/插件) ，以及自己创建的资源 (应用/工作流/知识库/数据库/插件) 都可以通过命令一键安装：
+
+```text
+/skill install linkai:<code>
+```
+
+> LinkAI平台上创建的所有应用、工作流、知识库、数据库、插件都有唯一的code，可在[控制台](https://link-ai.tech/console)各资源页面中进行获取并填写到命令中
+
+## 从 URL 安装
+
+支持 zip 压缩包和 SKILL.md 文件链接：
+
+```text
+/skill install https://cdn.link-ai.tech/skills/pptx.zip
+/skill install https://example.com/path/to/SKILL.md
+```
+
+## 管理技能
+
+```text
+/skill list                  # 查看已安装技能
+/skill info pptx             # 查看技能详情
+/skill enable pptx           # 启用技能
+/skill disable pptx          # 禁用技能
+/skill uninstall pptx        # 卸载技能
+```
+
+<Tip>
+  以上所有命令在终端中使用时，将 `/skill` 替换为 `cow skill` 即可。完整命令说明参考 [技能管理命令](/zh/cli/skill)。
+</Tip>
diff --git a/docs/zh/skills/knowledge-wiki.mdx b/docs/zh/skills/knowledge-wiki.mdx
new file mode 100644
index 0000000..40b4d29
--- /dev/null
+++ b/docs/zh/skills/knowledge-wiki.mdx
@@ -0,0 +1,112 @@
+---
+title: knowledge-wiki - 知识库
+description: 维护本地结构化知识库，自动归档、分类和交叉引用
+---
+
+帮你把对话中产生的资料、灵感和零散笔记整理成结构化的本地知识库，自动维护索引和页面之间的交叉引用。
+
+`knowledge-wiki` 在工作空间下维护一个 `knowledge/` 目录，相当于 Agent 的「外脑」。技能设置了 `always: true`，会**常驻上下文**，不需要任何外部依赖。
+
+## 什么时候会触发
+
+- 你分享了一篇文章、一份文档或一个 URL，想要沉淀下来
+- 聊天过程中聊出了值得长期保留的结论
+- 你想查一下之前积累过的知识
+
+## 目录结构
+
+```
+knowledge/
+├── index.md           # 全局索引（必须维护）
+├── log.md             # 操作日志（只追加）
+└── <category>/        # 分类子目录（按内容自由分组）
+    └── <slug>.md      # 知识页（文件名用小写加中划线）
+```
+
+## 三个核心操作
+
+### 1. 收录（Ingest）
+
+你分享了一段资料时，Agent 会：
+
+1. 读懂原文，提取关键信息
+2. 按内容决定放到哪个分类下——先看 `index.md` 里有没有合适的分类，没有就新建一个
+3. 生成知识页 `knowledge/<category>/<slug>.md`
+4. 更新索引 `index.md` 和日志 `log.md`
+
+### 2. 综合（Synthesize）
+
+聊天中产生了新的结论或洞见时：
+
+1. 在合适的分类下创建新知识页
+2. 给相关的已有页面加上互相指向的链接
+3. 更新索引和日志
+
+### 3. 查询（Query）
+
+你问到以前积累的知识时：
+
+1. 先从 `index.md` 里找可能相关的页面
+2. 用 `read` 工具打开具体页面
+3. 需要时再用 `memory_search` 补充检索
+4. 回答里会带上知识页的链接，方便你点过去看原文
+
+## 知识页怎么写
+
+```markdown
+# 页面标题
+
+> Source: <来源 URL 或简要说明>
+
+正文内容。页面之间用相对路径链接：
+[相关页](../category/related-page.md)
+
+## 要点
+
+- ...
+
+## 相关页面
+
+- [页面 A](../category/page-a.md) — 为什么相关
+```
+
+<Note>
+- `> Source:` 用来记录这条知识的来源。有明确来源时一定要写
+- 交叉引用很重要：创建或更新某页时，记得也去关联页面里补上反向链接
+- **只链接已经存在的页面**。如果某个概念值得单独成页，先建好再加链接
+</Note>
+
+## 索引格式
+
+`knowledge/index.md` 采用扁平列表，按分类分组，每个知识页占一行：
+
+```markdown
+# Knowledge Index
+
+## 分类 A
+- [页面标题](category-a/page-slug.md) — 一句话摘要
+
+## 分类 B
+- [页面标题](category-b/page-slug.md) — 一句话摘要
+```
+
+不用表格，不加 emoji。分类怎么起名、怎么组织都可以灵活调整。
+
+## 日志格式
+
+`knowledge/log.md` 只追加、不修改，最新的写在最下面：
+
+```markdown
+## [YYYY-MM-DD] ingest | 页面标题
+## [YYYY-MM-DD] synthesize | 页面标题
+```
+
+## 写作约定
+
+- **文件名**用小写加中划线，比如 `machine-learning.md`
+- **一页只讲一件事**，需要关联的内容通过链接串起来
+- **有了就更新，不要重复建页**
+- **每次改完都要更新索引** `knowledge/index.md`
+- **写精华别抄全文**，抓住要点就行
+- **对话里引用知识页时用完整路径**，比如 `[标题](knowledge/<category>/<slug>.md)`。页面之间互相链接才用相对路径
+- **基于知识页回答问题时附上链接**，方便深入查阅
diff --git a/docs/zh/skills/skill-creator.mdx b/docs/zh/skills/skill-creator.mdx
new file mode 100644
index 0000000..623a74f
--- /dev/null
+++ b/docs/zh/skills/skill-creator.mdx
@@ -0,0 +1,180 @@
+---
+title: skill-creator - 技能创建
+description: 创建、安装、更新技能，规范 SKILL.md 写法与目录结构
+---
+
+`skill-creator` 是一个「元技能」，专门用来帮助 Agent 创建、安装和更新其他技能，确保所有技能的 `SKILL.md` 写法和目录结构保持一致。
+
+## 什么时候会触发
+
+- 用户想从 URL 或远程仓库安装一个技能
+- 用户想从头创建一个全新的技能
+- 需要升级或重构已有技能
+
+## 技能是什么
+
+简单来说，技能就是一份「可复用的说明书」加上可选的脚本和资源。它给 Agent 注入了某个领域的专业知识，让 Agent 在遇到对应任务时能像专家一样处理。
+
+一个技能通常包含以下内容：
+
+1. **专项工作流** — 某类任务的完整步骤
+2. **工具用法** — 怎么调某种 API 或处理某种文件
+3. **领域知识** — 团队约定、业务规则、数据结构之类
+4. **附带资源** — 脚本、参考文档、模板等
+
+<Note>
+**核心原则：能省则省**。只写 Agent 自己想不到的内容，每加一行都要问自己：值不值得占这些 token？
+</Note>
+
+## 目录结构
+
+```
+skill-name/
+├── SKILL.md            # 必需：技能定义
+│   ├── YAML frontmatter（必填 name / description）
+│   └── Markdown 正文（说明 + 示例）
+└── 可选资源
+    ├── scripts/        # 可执行脚本（Python / Bash 等）
+    ├── references/     # 内容较多的参考文档，Agent 按需读取
+    └── assets/         # 模板、图标等，会直接用在输出里
+```
+
+## SKILL.md 规范定义
+
+SKILL.md 文件头部的 `frontmatter` 字段：
+
+| 字段 | 说明 |
+| --- | --- |
+| `name` | 技能名，小写加中划线，必须和目录名一致 |
+| `description` | **最关键的字段**。写清楚「这个技能干什么」和「什么情况下该用它」，Agent 看到这段来决定要不要调它。注意：所有触发相关的描述都放在这里，不要写到正文里 |
+| `metadata.cowagent.requires.bins` | 系统里必须装了哪些命令行工具 |
+| `metadata.cowagent.requires.env` | 需要哪些环境变量（全部满足才行） |
+| `metadata.cowagent.requires.anyEnv` | 多个 API Key 满足一个就行 |
+| `metadata.cowagent.requires.anyBins` | 多个工具满足一个就行 |
+| `metadata.cowagent.always` | 设为 `true` 会始终加载，不检查依赖 |
+| `metadata.cowagent.emoji` | 展示用的 emoji（可选） |
+| `metadata.cowagent.os` | 限定系统，如 `["darwin", "linux"]` |
+
+<Note>
+`category` 字段不需要手写，系统会自动设成 `skill`。
+</Note>
+
+声明 API Key 依赖有两种写法：
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      env: ["MYAPI_KEY"]            # 必须有
+```
+
+```yaml
+metadata:
+  cowagent:
+    requires:
+      anyEnv: ["OPENAI_API_KEY", "LINKAI_API_KEY"]   # 有一个就行
+```
+
+**技能会自动按依赖启禁用**：环境变量齐了就自动启用，缺了就自动禁用，不需要手动 `/skill enable`。
+
+## 资源目录怎么用
+
+| 目录 | 放什么 | 不要放 |
+| --- | --- | --- |
+| `scripts/` | 需要反复执行的代码，或需要确定性结果的脚本 | 纯演示用的代码片段 |
+| `references/` | **超过 500 行**、SKILL.md 实在塞不下的大文档（比如完整的数据库 Schema） | 普通 API 文档、示例、教程 |
+| `assets/` | 会出现在最终产物里的文件（模板、图标、样板代码等） | 说明性文档 |
+
+<Warning>
+**原则上所有内容都写在 `SKILL.md` 里**，只有确实放不下才拆到资源目录。
+
+不要给技能加 `README.md`、`CHANGELOG.md`、`INSTALLATION_GUIDE.md` 之类的文件——全部放进 `SKILL.md`。资源目录里只放真正要跑的脚本或真正要用的素材。
+</Warning>
+
+## 安装外部技能
+
+安装后最终落在 `<workspace>/skills/<name>/` 目录。
+
+| 来源 | 怎么装 |
+| --- | --- |
+| URL（单文件） | curl / web_fetch 直接拉 |
+| URL（zip 包） | 下载解压 |
+| 本地 SKILL.md | 直接读 |
+| 本地 zip 包 | 解压 |
+
+安装步骤：
+
+1. 找到 `SKILL.md`（可能在包的根目录或某个子目录里）
+2. 从 frontmatter 里读出 `name`
+3. 把**整个技能目录**（包括 `SKILL.md`、`scripts/`、`assets/` 等）复制到 `<workspace>/skills/<name>/`
+4. 如果包里有 `INSTALL.md` 之类的安装脚本，照着跑一遍，但最终结果仍然要落在 `<workspace>/skills/<name>/` 下
+
+## 从头创建技能
+
+推荐按这个顺序来：
+
+1. **搞清楚需求** — 让用户举几个具体的使用场景，一次别问太多
+2. **想好结构** — 这个技能需要脚本吗？需要参考文档吗？需要模板素材吗？
+3. **生成骨架** — 用初始化脚本：
+
+   ```bash
+   scripts/init_skill.py <skill-name> --path <workspace>/skills [--resources scripts,references,assets] [--examples]
+   ```
+
+4. **填充内容** — 写好 SKILL.md、补上脚本和资源。脚本写完一定要实际跑一遍
+5. **格式校验**（可选）：
+
+   ```bash
+   scripts/quick_validate.py <workspace>/skills/<skill-name>
+   ```
+
+6. **迭代完善** — 实际用起来之后根据反馈持续改进
+
+## 命名规则
+
+- 只用小写字母、数字和中划线。用户给的名字需要做标准化处理，比如 `Plan Mode` → `plan-mode`
+- 长度别超过 64 个字符
+- 尽量短、用动词开头、一看就知道干什么
+- 必要时用工具名做前缀，比如 `gh-address-comments`、`linear-address-issue`
+- 目录名和 `name` 字段必须完全一致
+
+## 三级加载机制
+
+技能不会一次性全部塞进上下文，而是分三级按需加载：
+
+1. **元信息**（`name` + `description`）— 常驻上下文，约 100 词。Agent 靠它判断「要不要用这个技能」
+2. **SKILL.md 正文** — 确定要用了才加载，建议控制在 500 行以内
+3. **资源文件** — Agent 需要的时候再读
+
+如果一个技能涉及多个变体（比如多云厂商部署），建议这样组织：
+
+```
+cloud-deploy/
+├── SKILL.md             # 主流程和厂商选择逻辑
+└── references/
+    ├── aws.md
+    ├── gcp.md
+    └── azure.md
+```
+
+用户选了 AWS，Agent 只需要读 `aws.md`，不用把三家的文档全加载进来。
+
+## 常见设计模式
+
+**步骤式**：按编号列出操作步骤和对应脚本。
+
+```markdown
+1. 分析表单结构（运行 analyze_form.py）
+2. 生成字段映射（编辑 fields.json）
+3. 自动填充表单（运行 fill_form.py）
+```
+
+**分支式**：根据用户意图走不同流程。
+
+```markdown
+1. 判断操作类型：
+   **新建内容？** → 走「创建流程」
+   **编辑已有内容？** → 走「编辑流程」
+```
+
+**模板式**：输出格式有严格要求时，在 SKILL.md 里直接给一个样板，让 Agent 照着写。
diff --git a/docs/zh/tools/bash.mdx b/docs/zh/tools/bash.mdx
new file mode 100644
index 0000000..0090fe1
--- /dev/null
+++ b/docs/zh/tools/bash.mdx
@@ -0,0 +1,28 @@
+---
+title: bash - 终端
+description: 执行系统命令
+---
+
+在当前工作目录执行 Bash 命令，返回 stdout 和 stderr。`env_config` 中配置的 API Key 会自动注入到环境变量中。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `command` | string | 是 | 要执行的命令 |
+| `timeout` | integer | 否 | 超时时间（秒） |
+
+## 使用场景
+
+- 安装软件包和依赖
+- 运行代码和测试
+- 部署应用和服务（Nginx 配置、进程管理等）
+- 系统运维和排查
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+</Frame>
diff --git a/docs/zh/tools/browser.mdx b/docs/zh/tools/browser.mdx
new file mode 100644
index 0000000..0d3c919
--- /dev/null
+++ b/docs/zh/tools/browser.mdx
@@ -0,0 +1,172 @@
+---
+title: browser - 浏览器
+description: 控制浏览器访问和操作网页
+---
+
+控制 Chromium 浏览器进行网页导航、元素交互和内容提取。支持 JavaScript 渲染的动态页面，使用精简 DOM 快照让 Agent 高效理解页面结构。
+
+## 安装
+
+<Tabs>
+  <Tab title="CLI 安装（推荐）">
+    ```bash
+    cow install-browser
+    ```
+
+    该命令会自动完成：
+    - 安装 `playwright` Python 包（旧系统自动降级兼容版本）
+    - 在 Linux 上安装系统依赖
+    - 下载 Chromium 浏览器（Linux 服务器自动使用无头精简版）
+    - 自动检测国内网络并使用镜像加速
+  </Tab>
+  <Tab title="手动安装">
+    ```bash
+    pip install playwright
+    playwright install chromium
+    ```
+
+    Linux 服务器还需安装系统依赖：
+    ```bash
+    sudo playwright install-deps chromium
+    ```
+
+    如果系统较旧（如 Ubuntu 18.04，glibc < 2.28），需安装兼容版本：
+    ```bash
+    pip install playwright==1.28.0
+    python -m playwright install chromium
+    ```
+
+    国内网络下载 Chromium 较慢，可设置镜像加速：
+    ```bash
+    export PLAYWRIGHT_DOWNLOAD_HOST=https://registry.npmmirror.com/-/binary/playwright
+    python -m playwright install chromium
+    ```
+  </Tab>
+</Tabs>
+
+<Note>
+  1. 支持 Ubuntu 20.04+、Debian 10+、macOS、Windows。Ubuntu 18.04 等旧系统会自动降级安装兼容版本。
+  2. 浏览器工具依赖较重（约300MB），为可选安装。轻量的网页内容获取可使用 `web_fetch` 工具。
+</Note>
+
+## 工作流程
+
+Agent 使用浏览器的典型流程：
+
+1. **`navigate`** — 打开目标 URL
+2. **`snapshot`** — 获取页面精简 DOM，交互元素自动编号（ref）
+3. **`click` / `fill` / `select`** — 通过 ref 编号操作元素
+4. **`snapshot`** — 再次快照验证操作结果
+
+## 支持的操作
+
+| 操作 | 说明 | 关键参数 |
+| --- | --- | --- |
+| `navigate` | 打开 URL | `url` |
+| `snapshot` | 获取页面结构化文本（主要方式） | `selector`（可选） |
+| `click` | 点击元素 | `ref` 或 `selector` |
+| `fill` | 填入文本 | `ref` 或 `selector`，`text` |
+| `select` | 下拉选择 | `ref` 或 `selector`，`value` |
+| `scroll` | 滚动页面 | `direction`（up/down/left/right） |
+| `screenshot` | 截图保存到工作区 | `full_page` |
+| `wait` | 等待元素或超时 | `selector`，`timeout` |
+| `press` | 按键（Enter、Tab 等） | `key` |
+| `back` / `forward` | 浏览器前进/后退 | - |
+| `get_text` | 获取元素文本内容 | `selector` |
+| `evaluate` | 执行 JavaScript | `script` |
+
+## 使用场景
+
+- 访问指定 URL 获取动态页面内容
+- 填写表单、登录操作
+- 操作网页元素（点击按钮、选择选项等）
+- 验证部署后的网页效果
+- 抓取需要 JS 渲染的动态内容
+
+## 运行模式
+
+浏览器会根据运行环境自动选择模式：
+
+| 环境 | 模式 |
+| --- | --- |
+| macOS / Windows | 有头模式（显示浏览器窗口） |
+| Linux 桌面（有 DISPLAY） | 有头模式 |
+| Linux 服务器（无 DISPLAY） | 无头模式（headless） |
+
+可在 `config.json` 中手动覆盖：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "headless": true
+    }
+  }
+}
+```
+
+## 登录态持久化
+
+**只需登录一次目标网站，Agent 后续可直接使用**。提供两种方式：
+
+### 方式一：Persistent 模式（默认）
+
+开箱即用，登录信息保存在 `~/.cow/browser_profile`。无需任何配置。
+
+如需关闭持久化模式，每次都用纯净环境：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "persistent": false
+    }
+  }
+}
+```
+
+### 方式二：CDP 模式（接管真实 Chrome）
+
+让 Agent 连接独立启动的真实 Chrome（而非 Playwright 自带的 Chromium），获得完整浏览器指纹，适合反爬严格的网站。
+
+启动 Chrome 时加上调试端口和独立用户目录：
+
+<Tabs>
+  <Tab title="macOS">
+    ```bash
+    "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Linux">
+    ```bash
+    google-chrome \
+      --remote-debugging-port=9222 \
+      --user-data-dir="$HOME/.cow/chrome-cdp"
+    ```
+  </Tab>
+  <Tab title="Windows">
+    ```powershell
+    & "C:\Program Files\Google\Chrome\Application\chrome.exe" `
+      --remote-debugging-port=9222 `
+      --user-data-dir="$env:USERPROFILE\.cow\chrome-cdp"
+    ```
+  </Tab>
+</Tabs>
+
+在 `config.json` 中配置端点：
+
+```json
+{
+  "tools": {
+    "browser": {
+      "cdp_endpoint": "http://localhost:9222"
+    }
+  }
+}
+```
+
+<Note>
+  Chrome 137+ 限制 `--remote-debugging-port` 必须搭配独立 `--user-data-dir`，因此 CDP 启动的 Chrome **无法直接复用你日常 Chrome 的登录态**，需要在独立目录中重新登录一次。
+</Note>
diff --git a/docs/zh/tools/edit.mdx b/docs/zh/tools/edit.mdx
new file mode 100644
index 0000000..717af2b
--- /dev/null
+++ b/docs/zh/tools/edit.mdx
@@ -0,0 +1,24 @@
+---
+title: edit - 文件编辑
+description: 通过精确文本替换编辑文件
+---
+
+通过精确文本替换编辑文件。如果 `oldText` 为空则追加到文件末尾。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 文件路径 |
+| `oldText` | string | 是 | 要替换的原始文本（为空时追加到末尾） |
+| `newText` | string | 是 | 替换后的文本 |
+
+## 使用场景
+
+- 修改配置文件中的特定参数
+- 修复代码中的 bug
+- 在文件指定位置插入内容
diff --git a/docs/zh/tools/env-config.mdx b/docs/zh/tools/env-config.mdx
new file mode 100644
index 0000000..d5d52c6
--- /dev/null
+++ b/docs/zh/tools/env-config.mdx
@@ -0,0 +1,36 @@
+---
+title: env_config - 环境变量
+description: 管理 API Key 等秘钥配置
+---
+
+管理工作空间 `.env` 文件中的环境变量（API Key 等秘钥），支持通过对话安全地添加和更新。内置安全保护和脱敏策略。
+
+## 依赖
+
+| 依赖 | 安装命令 |
+| --- | --- |
+| `python-dotenv` ≥ 1.0.0 | `pip install python-dotenv>=1.0.0` |
+
+安装扩展依赖时已包含：`pip3 install -r requirements-optional.txt`
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `action` | string | 是 | 操作类型：`get`、`set`、`list`、`delete` |
+| `key` | string | 否 | 环境变量名称 |
+| `value` | string | 否 | 环境变量值（仅 `set` 时需要） |
+
+## 使用方式
+
+直接告诉 Agent 需要配置的秘钥，Agent 会自动调用该工具：
+
+- "帮我配置 BOCHA_API_KEY"
+- "设置 OPENAI_API_KEY 为 sk-xxx"
+- "查看已配置的环境变量"
+
+配置的秘钥会自动注入到 `bash` 工具的执行环境中。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
+</Frame>
diff --git a/docs/zh/tools/index.mdx b/docs/zh/tools/index.mdx
new file mode 100644
index 0000000..088c073
--- /dev/null
+++ b/docs/zh/tools/index.mdx
@@ -0,0 +1,69 @@
+---
+title: 工具概览
+description: CowAgent 内置工具系统
+---
+
+工具是 Agent 访问操作系统资源的核心能力。Agent 会根据任务需求智能选择和调用工具，完成文件操作、命令执行、联网搜索、定时任务等各类操作。工具实现在项目的 `agent/tools/` 目录下。
+
+## 内置工具
+
+以下工具默认可用，无需额外配置：
+
+<CardGroup cols={2}>
+  <Card title="read - 文件读取" icon="file" href="/zh/tools/read">
+    读取文件内容，支持文本、图片、PDF
+  </Card>
+  <Card title="write - 文件写入" icon="pen" href="/zh/tools/write">
+    创建或覆盖写入文件
+  </Card>
+  <Card title="edit - 文件编辑" icon="pen-to-square" href="/zh/tools/edit">
+    通过精确文本替换编辑文件
+  </Card>
+  <Card title="ls - 目录列表" icon="folder-open" href="/zh/tools/ls">
+    列出目录内容
+  </Card>
+  <Card title="bash - 终端" icon="terminal" href="/zh/tools/bash">
+    执行系统命令
+  </Card>
+  <Card title="send - 文件发送" icon="paper-plane" href="/zh/tools/send">
+    向用户发送文件或图片
+  </Card>
+  <Card title="memory - 记忆" icon="brain" href="/zh/tools/memory">
+    搜索和读取长期记忆
+  </Card>
+  <Card title="env_config - 环境变量" icon="key" href="/zh/tools/env-config">
+    管理 API Key 等秘钥配置
+  </Card>
+  <Card title="web_fetch - 网页获取" icon="globe" href="/zh/tools/web-fetch">
+    获取网页或文档内容
+  </Card>
+  <Card title="scheduler - 定时任务" icon="clock" href="/zh/tools/scheduler">
+    创建和管理定时任务
+  </Card>
+</CardGroup>
+
+## 可选工具
+
+以下工具需要安装额外依赖或配置 API Key 后启用：
+
+<CardGroup cols={2}>
+  <Card title="web_search - 联网搜索" icon="magnifying-glass" href="/zh/tools/web-search">
+    搜索互联网获取实时信息
+  </Card>
+  <Card title="vision - 图片理解" icon="eye" href="/zh/tools/vision">
+    分析图片内容（识别、描述、OCR 文字提取等）
+  </Card>
+  <Card title="browser - 浏览器" icon="window" href="/zh/tools/browser">
+    控制浏览器访问和操作网页
+  </Card>
+</CardGroup>
+
+## MCP 工具
+
+通过 [Model Context Protocol](https://modelcontextprotocol.io) 接入社区生态中的各种MCP工具，配置一次 `mcp.json` 即用即得：
+
+<CardGroup cols={1}>
+  <Card title="MCP - 外部工具生态" icon="plug" href="/zh/tools/mcp">
+    支持 stdio / SSE 标准协议，热更新，零代码接入
+  </Card>
+</CardGroup>
diff --git a/docs/zh/tools/ls.mdx b/docs/zh/tools/ls.mdx
new file mode 100644
index 0000000..e4d25fc
--- /dev/null
+++ b/docs/zh/tools/ls.mdx
@@ -0,0 +1,23 @@
+---
+title: ls - 目录列表
+description: 列出目录内容
+---
+
+列出目录内容，按字母排序，目录名带 `/` 后缀，包含隐藏文件。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 目录路径，相对路径基于工作空间目录 |
+| `limit` | integer | 否 | 最大返回条目数，默认 500 |
+
+## 使用场景
+
+- 浏览项目结构
+- 查找特定文件
+- 检查目录是否存在
diff --git a/docs/zh/tools/mcp.mdx b/docs/zh/tools/mcp.mdx
new file mode 100644
index 0000000..c7479a9
--- /dev/null
+++ b/docs/zh/tools/mcp.mdx
@@ -0,0 +1,134 @@
+---
+title: MCP 工具
+description: 通过 Model Context Protocol 接入外部工具生态
+---
+
+CowAgent 支持 [Model Context Protocol (MCP)](https://modelcontextprotocol.io)，让 Agent 能够直接调用社区中数以万计的 MCP 工具。配置一次 `mcp.json`，工具就会以与内置工具完全相同的方式呈现给 LLM，可被自动选择和调用。
+
+## 配置文件
+
+CowAgent 读取 `~/cow/mcp.json`。文件不存在时不会启用任何 MCP 工具，也不会报错。
+
+Docker 部署时，官方 `docker-compose.yml` 已经把宿主机 `./cow` 挂载到容器内 `/home/agent/cow`（即容器用户的 `~/cow`），把 `mcp.json` 放进宿主机 `./cow/` 目录即可生效。
+
+### 标准格式
+
+完全兼容 MCP 社区标准，同 Claude Desktop / Cursor 一致：
+
+```json
+{
+  "mcpServers": {
+    "<server-name>": {
+      "command": "npx",
+      "args": ["-y", "some-mcp-package"],
+      "env": {
+        "API_KEY": "your-key-here"
+      }
+    }
+  }
+}
+```
+
+| 字段 | 必填 | 说明 |
+| --- | --- | --- |
+| `command` | stdio | 启动 server 的可执行命令（如 `npx`、`python`、`uvx`） |
+| `args` | 否 | 传给 command 的参数列表 |
+| `env` | 否 | 子进程的环境变量，常用于 API Key |
+| `url` | SSE / Streamable HTTP | 远程端点 URL（与 `command` 二选一） |
+| `type` | 远程 | 远程传输类型，可选 `sse` 或 `streamable-http`，默认 `sse` |
+| `headers` | 否 | 远程请求附加 HTTP 头（如 `Authorization`），仅 Streamable HTTP 使用 |
+| `scope` | 否 | OAuth 授权范围，仅需要 OAuth 授权的远程 server 使用（可选） |
+| `disabled` | 否 | `true` 时跳过该 server，便于临时关闭 |
+
+### 完整示例
+
+```json
+{
+  "mcpServers": {
+    "fetch": {
+      "command": "uvx",
+      "args": ["mcp-server-fetch"]
+    },
+    "github": {
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-github"],
+      "env": {
+        "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
+      }
+    }
+  }
+}
+```
+
+- **fetch**：通用网页抓取，返回页面文本内容，无需 API Key
+- **github**：访问 GitHub 仓库、Issue、PR 等，需要 Personal Access Token
+
+## 让 Agent 帮你配置
+
+CowAgent 自带 `read` / `write` / `edit` 工具，**直接把要装的 MCP 配置发给 Agent，让它写到配置文件中：
+
+例如：
+
+```markdown
+帮我把这个 MCP 加到 ~/cow/mcp.json 里：
+
+{"mcpServers":{"fetch":{"command":"uvx","args":["mcp-server-fetch"]}}}
+```
+
+Agent 会：
+
+1. 访问 MCP 配置文件，合并新 server 配置，保留已有项
+2. 自动重载增量的 MCP Server，下一次对话即可使用相应 Tools
+
+## 网页授权（OAuth）
+
+部分远程 MCP需要 OAuth 网页授权，直接配置会返回 `401`。CowAgent 内置标准 OAuth 流程，**无需手填 token**，正常配置即可，例如：
+
+```json
+{
+  "mcpServers": {
+    "xmind": {
+      "type": "streamable-http",
+      "url": "https://app.xmind.com/api/mcp"
+    }
+  }
+}
+```
+
+server 首次加载遇到 `401` 时会自动发起授权：本机运行会**自动打开浏览器**，服务器部署则把**授权链接打印到日志**，复制到浏览器打开。授权同意后即完成，该 server 随即上线，令牌过期自动刷新，无需重复授权。
+
+- **依赖 Web 服务**：授权回调由 Web 控制台（默认端口 `9899`）接收，需保证 Web channel 正在运行。
+- **凭证存储**：令牌持久化在 `~/.cow/mcp_oauth.json`，重启后复用。
+- **回调地址**：默认 `http://127.0.0.1:9899/mcp/oauth/callback`；若部署在服务器、授权浏览器在另一台设备，在 `config.json` 设置 `mcp_oauth_redirect_base`（如 `http://你的IP:9899`）即可。
+
+## 工作方式
+
+- 启动时**异步加载**：`mcp.json` 中配置的所有 server 会在后台异步加载，不阻塞主流程，对话可以立刻使用
+- **热更新**：用户或 Agent 修改 `mcp.json` 后，消息处理完成时会自动重载变更的 server，无需重启 cow
+- **平铺呈现**：每个 MCP server 暴露的多个方法会平铺为独立的工具，LLM 直接选择调用，不需要二次决策
+
+## 支持的传输协议
+
+| 协议 | 说明 | 配置字段 |
+| --- | --- | --- |
+| **stdio** | 子进程通信，最常见，社区生态最丰富 | `command` + `args` |
+| **SSE** | HTTP Server-Sent Events，旧版远程协议 | `url`（默认） |
+| **Streamable HTTP** | 新版远程协议，单端点收发，逐步取代 SSE | `type: "streamable-http"` + `url` |
+
+## 排错
+
+| 现象 | 排查方向 |
+| --- | --- |
+| 启动后 Agent 没有 MCP 工具 | 检查 `~/cow/mcp.json` 是否存在、JSON 格式是否合法 |
+| 某个 server 加载失败 | 查看启动日志中的 `[MCP] Server 'xxx' load failed`，常见为依赖未装、API Key 缺失 |
+| 修改 `mcp.json` 没有生效 | 改动会在**下一条消息**生效；若 server 配置不变（如只改注释），不会触发重启 |
+| Docker 部署 | 确认宿主机 `./cow` 已挂载到容器内 `/home/agent/cow`，`mcp.json` 直接放进宿主机 `./cow/` 目录即可，或者直接对话 Agent 安装 |
+
+## MCP 市场推荐
+
+可以从各个第三方广场寻找现成的 MCP server，复制 JSON 配置即可使用，例如：
+
+- [mcp.so](https://mcp.so) — 全球 MCP 服务索引
+- [ModelScope MCP 广场](https://modelscope.cn/mcp) — 魔搭社区 MCP 广场，国内访问更稳定
+
+只要遵循 MCP 标准协议（stdio / SSE / Streamable HTTP），都可以直接接入 CowAgent。
diff --git a/docs/zh/tools/memory.mdx b/docs/zh/tools/memory.mdx
new file mode 100644
index 0000000..7f6ca9e
--- /dev/null
+++ b/docs/zh/tools/memory.mdx
@@ -0,0 +1,43 @@
+---
+title: memory - 记忆与知识
+description: 搜索和读取长期记忆及知识库文件
+---
+
+记忆工具包含两个子工具：`memory_search`（搜索记忆）和 `memory_get`（读取记忆或知识文件）。
+
+当 [知识库](/zh/knowledge) 功能开启时，这两个工具同时支持访问 `memory/` 和 `knowledge/` 目录下的文件。
+
+## 依赖
+
+无额外依赖，默认可用。由 Agent Core 的记忆系统管理。
+
+## memory_search
+
+搜索历史记忆和知识库内容，支持关键词和向量混合检索。
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `query` | string | 是 | 搜索查询 |
+
+## memory_get
+
+读取特定记忆文件或知识库文件的内容。
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 文件的相对路径（如 `MEMORY.md`、`memory/2026-01-01.md`、`knowledge/concepts/rag.md`） |
+| `start_line` | integer | 否 | 起始行号 |
+| `end_line` | integer | 否 | 结束行号 |
+
+## 工作方式
+
+Agent 会在以下场景自动调用记忆工具：
+
+- 用户分享重要信息时 → 存储到记忆
+- 需要参考历史信息时 → 搜索相关记忆
+- 对话达到一定长度时 → 提取摘要存储
+- 讨论到专业知识时 → 检索知识库中的相关页面
+
+<Note>
+  当 `knowledge` 配置为 `false` 时，工具的描述和搜索范围会自动调整为仅包含记忆文件。
+</Note>
diff --git a/docs/zh/tools/read.mdx b/docs/zh/tools/read.mdx
new file mode 100644
index 0000000..07e08b8
--- /dev/null
+++ b/docs/zh/tools/read.mdx
@@ -0,0 +1,24 @@
+---
+title: read - 文件读取
+description: 读取文件内容
+---
+
+读取文件内容。支持文本文件、PDF 文件、图片（返回元数据）等格式。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 文件路径，相对路径基于工作空间目录 |
+| `offset` | integer | 否 | 起始行号（1-indexed），负值表示从末尾读取 |
+| `limit` | integer | 否 | 读取行数 |
+
+## 使用场景
+
+- 查看配置文件、日志文件
+- 读取代码文件进行分析
+- 检查图片/视频的文件信息
diff --git a/docs/zh/tools/scheduler.mdx b/docs/zh/tools/scheduler.mdx
new file mode 100644
index 0000000..2648116
--- /dev/null
+++ b/docs/zh/tools/scheduler.mdx
@@ -0,0 +1,80 @@
+---
+title: scheduler - 定时任务
+description: 创建和管理定时任务
+---
+
+创建和管理动态定时任务，支持灵活的调度方式和执行模式。
+
+## 依赖
+
+| 依赖 | 安装命令 |
+| --- | --- |
+| `croniter` ≥ 2.0.0 | `pip install croniter>=2.0.0` |
+
+安装核心依赖时已包含：`pip3 install -r requirements.txt`
+
+## 调度方式
+
+| 方式 | 说明 |
+| --- | --- |
+| 一次性任务 | 在指定时间执行一次 |
+| 固定间隔 | 按固定时间间隔重复执行 |
+| Cron 表达式 | 使用 Cron 语法定义复杂调度规则 |
+
+## 执行模式
+
+- **固定消息发送**：到达触发时间时发送预设消息
+- **Agent 动态任务**：到达触发时间时由 Agent 智能执行任务
+
+## 使用方式
+
+通过自然语言即可创建和管理定时任务：
+
+- "每天早上 9 点给我发天气预报"
+- "每隔 2 小时检查一下服务器状态"
+- "明天下午 3 点提醒我开会"
+- "查看所有定时任务"
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
+</Frame>
+
+## 结果进入会话上下文
+
+定时任务在隔离 session 中执行（内部规划与 tool 调用不污染用户会话），但**最终输出**会作为一对消息回写到接收者的真实会话，用户可以直接追问"刚才那条第二点展开说说"。
+
+**默认策略**
+
+- Agent 动态任务的输出进入上下文
+- 固定消息类任务默认不进入上下文（可通过配置打开）
+- 每个会话最多保留最近 **3 对** scheduler 消息，更早的自动清理；普通用户消息不受影响
+
+**配置项**
+
+| 配置项 | 默认值 | 说明 |
+| --- | --- | --- |
+| `scheduler_inject_to_session` | `true` | 总开关 |
+| `scheduler_inject_max_per_session` | `3` | 每会话保留 scheduler 消息对数上限 |
+| `scheduler_inject_send_message` | `false` | 是否同时注入固定消息类任务 |
+
+```json
+{
+  "scheduler_inject_to_session": true,
+  "scheduler_inject_max_per_session": 3,
+  "scheduler_inject_send_message": false
+}
+```
+
+## 任务执行时的上下文
+
+定时任务的隔离 session 会保留最近几次执行的对话历史，便于做"对比上次"、"延续之前结论"等操作；但为了避免高频任务（如每 5 分钟监控）prompt 越积越长，会按公式自动裁剪：
+
+```
+scheduler_keep_turns = max(1, agent_max_context_turns / 5)
+```
+
+`agent_max_context_turns` 默认为 `20`，所以定时任务每次执行默认带最近 **4 轮**历史。需要更长记忆可调大 `agent_max_context_turns`。
+
+<Note>
+群聊场景（飞书 / 企微群机器人 / 钉钉等）下用户的真实 session_id 形如 `user_id:group_id`，与 receiver 不同。创建任务时会自动记录正确的 session_id；老的 `tasks.json` 缺该字段时回落到 receiver，行为与历史版本一致。
+</Note>
diff --git a/docs/zh/tools/send.mdx b/docs/zh/tools/send.mdx
new file mode 100644
index 0000000..05f73a6
--- /dev/null
+++ b/docs/zh/tools/send.mdx
@@ -0,0 +1,23 @@
+---
+title: send - 文件发送
+description: 向用户发送文件
+---
+
+向用户发送文件（图片、视频、音频、文档等），当用户明确要求发送/分享文件时使用。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 文件路径，可以是绝对路径或相对于工作空间的路径 |
+| `message` | string | 否 | 附带的消息说明 |
+
+## 使用场景
+
+- 将生成的代码或文档发送给用户
+- 发送截图、图表
+- 分享下载的文件
diff --git a/docs/zh/tools/vision.mdx b/docs/zh/tools/vision.mdx
new file mode 100644
index 0000000..bfc0591
--- /dev/null
+++ b/docs/zh/tools/vision.mdx
@@ -0,0 +1,75 @@
+---
+title: vision - 图片理解
+description: 分析图片内容（识别、描述、OCR 等）
+---
+
+使用 Vision API 分析本地图片或图片 URL，支持内容描述、文字提取（OCR）、物体识别等。
+
+## 模型选择
+
+Vision 工具采用多级自动选择 + 自动兜底策略，无需手动配置即可使用：
+
+1. **主模型** — 优先使用当前配置的主模型进行图像识别（需要是多模态模型）
+2. **其他已配置模型** — 自动发现已配置 API Key 的其他多模态模型作为备选
+
+如果当前 provider 调用失败，会自动尝试下一个，直到成功或全部失败。
+
+### 支持的模型
+
+| 厂商 | 视觉模型 | 说明 |
+| --- | --- | --- |
+| OpenAI / 兼容协议 | 使用主模型 | 支持所有 OpenAI 协议兼容的多模态模型 |
+| 通义千问 (DashScope) | 使用主模型 | 例如 qwen3.7-plus 等 |
+| Claude | 使用主模型 | Anthropic 原生图像格式 |
+| Gemini | 使用主模型 | inlineData 格式 |
+| 豆包 (Doubao) | 使用主模型 | doubao-seed-2-1 系列原生支持 |
+| Kimi (Moonshot) | 使用主模型 | kimi-k2.6、kimi-k2.5 原生支持 |
+| 百度千帆 (Qianfan) | 使用主模型 | 默认使用多模态主模型 (如 ernie-5.1)，主模型不支持时兜底使用 ernie-4.5-turbo-vl |
+| 智谱 AI | glm-5v-turbo | 固定使用视觉专用模型 |
+| MiniMax | MiniMax-Text-01 | 固定使用视觉专用模型 |
+
+<Note>
+  智谱和 MiniMax 的文本模型不支持图像理解，因此始终使用对应的视觉专用模型，无需手动指定。
+</Note>
+
+> 当 `use_linkai=true` 时，默认使用 LinkAI 的多模态模型进行
+
+## 自定义配置
+
+如果希望指定 Vision 使用的模型，可在 `config.json` 中配置，例如：
+
+```json
+{
+    "tools": {
+        "vision": {
+            "model": "gpt-4.1"
+        }
+    }
+}
+```
+
+指定的模型会被**优先使用**，工具会根据模型名自动路由到对应的 provider；若调用失败，会自动 fallback 到其他已配置的 provider。
+
+大多数情况下无需配置，主模型支持多模态或配置任意一个支持视觉的 API Key 即可自动工作。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `image` | string | 是 | 本地文件路径或 HTTP(S) 图片 URL |
+| `question` | string | 是 | 对图片提出的问题 |
+
+支持的图片格式：jpg、jpeg、png、gif、webp
+
+
+
+## 使用场景
+
+- 描述图片中的内容
+- 提取图片中的文字（OCR）
+- 识别物体、颜色、场景
+- 分析截图、文档扫描图片等
+
+<Note>
+  超过 1MB 的图片会自动压缩后上传，所有图片（包括远程 URL）会统一转为 base64 传输，确保兼容所有模型后端。
+</Note>
diff --git a/docs/zh/tools/web-fetch.mdx b/docs/zh/tools/web-fetch.mdx
new file mode 100644
index 0000000..12f8595
--- /dev/null
+++ b/docs/zh/tools/web-fetch.mdx
@@ -0,0 +1,32 @@
+---
+title: web_fetch - 网页获取
+description: 获取网页或文档内容
+---
+
+获取 HTTP/HTTPS URL 的内容。对网页提取可读文本，对文档文件（PDF、Word、Excel 等）自动下载并解析内容。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `url` | string | 是 | HTTP/HTTPS URL（网页或文档链接） |
+
+## 支持的文件类型
+
+| 类型 | 格式 |
+| --- | --- |
+| PDF | `.pdf` |
+| Word | `.docx` |
+| 文本 | `.txt`、`.md`、`.csv`、`.log` |
+| 表格 | `.xls`、`.xlsx` |
+| 演示文稿 | `.ppt`、`.pptx` |
+
+## 使用场景
+
+- 获取网页的文本内容
+- 下载并解析远程文档
+- 获取 API 响应内容
+
+<Note>
+  `web_fetch` 只能获取静态 HTML 内容。如果页面需要 JavaScript 渲染（如 SPA 单页应用），请使用 `browser` 工具。
+</Note>
diff --git a/docs/zh/tools/web-search.mdx b/docs/zh/tools/web-search.mdx
new file mode 100644
index 0000000..86c170c
--- /dev/null
+++ b/docs/zh/tools/web-search.mdx
@@ -0,0 +1,51 @@
+---
+title: web_search - 联网搜索
+description: 搜索互联网获取实时信息，支持多个搜索厂商
+---
+
+搜索互联网获取实时信息、新闻、研究等内容。支持博查、百度千帆、智谱、LinkAI 四个后端，配置任意一家即可使用。
+
+<Tip>
+  推荐通过 [Web 控制台](/zh/channels/web) 的「模型管理 → 搜索」面板可视化配置厂商与策略，无需手动编辑配置文件。
+</Tip>
+
+## 厂商
+
+| 厂商 | 凭证 | 申请入口 |
+| --- | --- | --- |
+| 博查 Bocha | `tools.web_search.bocha_api_key` | [博查开放平台](https://open.bochaai.com/) |
+| 百度千帆 | 复用 `qianfan_api_key` | [千帆控制台](https://cloud.baidu.com/doc/qianfan/s/2mh4su4uy) |
+| 智谱 Zhipu | 复用 `zhipu_ai_api_key` | [智谱开放平台](https://docs.bigmodel.cn/cn/guide/tools/web-search) |
+| LinkAI | 复用 `linkai_api_key` | [LinkAI 控制台](https://link-ai.tech/console/interface) |
+
+除博查需要单独的 `bocha_api_key` 外，其他三家直接复用对应模型的 API Key，配好模型即同时获得搜索能力。
+
+## 路由策略
+
+```json
+{
+  "tools": {
+    "web_search": {
+      "strategy": "auto",
+      "provider": ""
+    }
+  }
+}
+```
+
+- `auto`（默认）：由 Agent 在已配置的厂商中智能选择，并可在一次任务中多次调用、切换不同厂商以获取更全面的结果；未指定时按 `bocha → qianfan → zhipu → linkai` 顺序兜底。
+- `fixed`：固定使用 `provider` 指定的厂商；该厂商凭证缺失时自动回落到 auto 顺序。
+
+## 工具参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `query` | string | 是 | 搜索关键词 |
+| `count` | integer | 否 | 返回结果数量（1–50，默认 10） |
+| `freshness` | string | 否 | 时间范围：`noLimit`（默认）、`oneDay`、`oneWeek`、`oneMonth`、`oneYear`，或日期范围如 `2025-01-01..2025-02-01` |
+| `summary` | boolean | 否 | 是否返回页面摘要（默认 false） |
+| `provider` | string | 否 | `auto` 策略下配置了多个厂商时可见，用于单次切换厂商 |
+
+<Note>
+  四家凭证均未配置时，该工具不会注册到 Agent。
+</Note>
diff --git a/docs/zh/tools/write.mdx b/docs/zh/tools/write.mdx
new file mode 100644
index 0000000..51cf66f
--- /dev/null
+++ b/docs/zh/tools/write.mdx
@@ -0,0 +1,27 @@
+---
+title: write - 文件写入
+description: 创建或覆盖写入文件
+---
+
+写入内容到文件。文件不存在则自动创建，已存在则覆盖。自动创建父目录。
+
+## 依赖
+
+无额外依赖，默认可用。
+
+## 参数
+
+| 参数 | 类型 | 必填 | 说明 |
+| --- | --- | --- | --- |
+| `path` | string | 是 | 文件路径 |
+| `content` | string | 是 | 要写入的内容 |
+
+## 使用场景
+
+- 创建新的代码文件或脚本
+- 生成配置文件
+- 保存处理结果
+
+<Note>
+  单次写入不应超过 10KB。对于大文件，建议先创建骨架，再使用 edit 工具分块添加内容。
+</Note>
diff --git a/models/baidu/baidu_unit_bot.py b/models/baidu/baidu_unit_bot.py
new file mode 100644
index 0000000..35319e2
--- /dev/null
+++ b/models/baidu/baidu_unit_bot.py
@@ -0,0 +1,36 @@
+# encoding:utf-8
+
+import requests
+
+from models.bot import Bot
+from bridge.reply import Reply, ReplyType
+
+
+# Baidu Unit对话接口 (可用, 但能力较弱)
+class BaiduUnitBot(Bot):
+    def reply(self, query, context=None):
+        token = self.get_token()
+        url = "https://aip.baidubce.com/rpc/2.0/unit/service/v3/chat?access_token=" + token
+        post_data = (
+            '{"version":"3.0","service_id":"S73177","session_id":"","log_id":"7758521","skill_ids":["1221886"],"request":{"terminal_id":"88888","query":"'
+            + query
+            + '", "hyper_params": {"chat_custom_bot_profile": 1}}}'
+        )
+        print(post_data)
+        headers = {"content-type": "application/x-www-form-urlencoded"}
+        response = requests.post(url, data=post_data.encode(), headers=headers)
+        if response:
+            reply = Reply(
+                ReplyType.TEXT,
+                response.json()["result"]["context"]["SYS_PRESUMED_HIST"][1],
+            )
+            return reply
+
+    def get_token(self):
+        access_key = "YOUR_ACCESS_KEY"
+        secret_key = "YOUR_SECRET_KEY"
+        host = "https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=" + access_key + "&client_secret=" + secret_key
+        response = requests.get(host)
+        if response:
+            print(response.json())
+            return response.json()["access_token"]
diff --git a/models/baidu/baidu_wenxin.py b/models/baidu/baidu_wenxin.py
new file mode 100644
index 0000000..341f482
--- /dev/null
+++ b/models/baidu/baidu_wenxin.py
@@ -0,0 +1,120 @@
+# encoding:utf-8
+
+import requests
+import json
+from common import const
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from models.baidu.baidu_wenxin_session import BaiduWenxinSession
+
+BAIDU_API_KEY = conf().get("baidu_wenxin_api_key")
+BAIDU_SECRET_KEY = conf().get("baidu_wenxin_secret_key")
+
+class BaiduWenxinBot(Bot):
+
+    def __init__(self):
+        super().__init__()
+        wenxin_model = conf().get("baidu_wenxin_model")
+        self.prompt_enabled = conf().get("baidu_wenxin_prompt_enabled")
+        if self.prompt_enabled:
+            self.prompt = conf().get("character_desc", "")
+            if self.prompt == "":
+                logger.warn("[BAIDU] Although you enabled model prompt, character_desc is not specified.")
+        if wenxin_model is not None:
+            wenxin_model = conf().get("baidu_wenxin_model") or "eb-instant"
+        else:
+            if conf().get("model") and conf().get("model") == const.WEN_XIN:
+                wenxin_model = "completions"
+            elif conf().get("model") and conf().get("model") == const.WEN_XIN_4:
+                wenxin_model = "completions_pro"
+
+        self.sessions = SessionManager(BaiduWenxinSession, model=wenxin_model)
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context and context.type:
+            if context.type == ContextType.TEXT:
+                logger.info("[BAIDU] query={}".format(query))
+                session_id = context["session_id"]
+                reply = None
+                if query == "#清除记忆":
+                    self.sessions.clear_session(session_id)
+                    reply = Reply(ReplyType.INFO, "记忆已清除")
+                elif query == "#清除所有":
+                    self.sessions.clear_all_session()
+                    reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+                else:
+                    session = self.sessions.session_query(query, session_id)
+                    result = self.reply_text(session)
+                    total_tokens, completion_tokens, reply_content = (
+                        result["total_tokens"],
+                        result["completion_tokens"],
+                        result["content"],
+                    )
+                    logger.debug(
+                        "[BAIDU] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(session.messages, session_id, reply_content, completion_tokens)
+                    )
+
+                    if total_tokens == 0:
+                        reply = Reply(ReplyType.ERROR, reply_content)
+                    else:
+                        self.sessions.session_reply(reply_content, session_id, total_tokens)
+                        reply = Reply(ReplyType.TEXT, reply_content)
+                return reply
+            elif context.type == ContextType.IMAGE_CREATE:
+                ok, retstring = self.create_img(query, 0)
+                reply = None
+                if ok:
+                    reply = Reply(ReplyType.IMAGE_URL, retstring)
+                else:
+                    reply = Reply(ReplyType.ERROR, retstring)
+                return reply
+
+    def reply_text(self, session: BaiduWenxinSession, retry_count=0):
+        try:
+            logger.info("[BAIDU] model={}".format(session.model))
+            access_token = self.get_access_token()
+            if access_token == 'None':
+                logger.warn("[BAIDU] access token 获取失败")
+                return {
+                    "total_tokens": 0,
+                    "completion_tokens": 0,
+                    "content": 0,
+                    }
+            url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/" + session.model + "?access_token=" + access_token
+            headers = {
+                'Content-Type': 'application/json'
+            }
+            payload = {'messages': session.messages, 'system': self.prompt} if self.prompt_enabled else {'messages': session.messages}
+            response = requests.request("POST", url, headers=headers, data=json.dumps(payload))
+            response_text = json.loads(response.text)
+            logger.info(f"[BAIDU] response text={response_text}")
+            res_content = response_text["result"]
+            total_tokens = response_text["usage"]["total_tokens"]
+            completion_tokens = response_text["usage"]["completion_tokens"]
+            logger.info("[BAIDU] reply={}".format(res_content))
+            return {
+                "total_tokens": total_tokens,
+                "completion_tokens": completion_tokens,
+                "content": res_content,
+            }
+        except Exception as e:
+            need_retry = retry_count < 2
+            logger.warn("[BAIDU] Exception: {}".format(e))
+            need_retry = False
+            self.sessions.clear_session(session.session_id)
+            result = {"total_tokens": 0, "completion_tokens": 0, "content": "出错了: {}".format(e)}
+            return result
+
+    def get_access_token(self):
+        """
+        使用 AK，SK 生成鉴权签名（Access Token）
+        :return: access_token，或是None(如果错误)
+        """
+        url = "https://aip.baidubce.com/oauth/2.0/token"
+        params = {"grant_type": "client_credentials", "client_id": BAIDU_API_KEY, "client_secret": BAIDU_SECRET_KEY}
+        return str(requests.post(url, params=params).json().get("access_token"))
diff --git a/models/baidu/baidu_wenxin_session.py b/models/baidu/baidu_wenxin_session.py
new file mode 100644
index 0000000..52b5c93
--- /dev/null
+++ b/models/baidu/baidu_wenxin_session.py
@@ -0,0 +1,53 @@
+from models.session_manager import Session
+from common.log import logger
+
+"""
+    e.g.  [
+        {"role": "user", "content": "Who won the world series in 2020?"},
+        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
+        {"role": "user", "content": "Where was it played?"}
+    ]
+"""
+
+
+class BaiduWenxinSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="gpt-3.5-turbo"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        # 百度文心不支持system prompt
+        # self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) >= 2:
+                self.messages.pop(0)
+                self.messages.pop(0)
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    """Returns the number of tokens used by a list of messages."""
+    tokens = 0
+    for msg in messages:
+        # 官方token计算规则暂不明确： "大约为 token数为 "中文字 + 其他语种单词数 x 1.3"
+        # 这里先直接根据字数粗略估算吧，暂不影响正常使用，仅在判断是否丢弃历史会话的时候会有偏差
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/bot.py b/models/bot.py
new file mode 100644
index 0000000..f5f72e7
--- /dev/null
+++ b/models/bot.py
@@ -0,0 +1,32 @@
+"""
+Auto-replay chat robot abstract class
+"""
+
+from bridge.context import Context
+from bridge.reply import Reply
+
+
+class Bot(object):
+    """
+    Base class for all chat-bot implementations.
+
+    Subclasses may also implement:
+
+        call_with_tools(messages, tools=None, stream=False, **kwargs)
+            -> dict | generator  (OpenAI-compatible format)
+
+        call_vision(image_url, question, model=None, max_tokens=1000)
+            -> dict with keys: model, content, usage  (or error/message)
+
+    These are NOT defined here to avoid shadowing concrete implementations
+    provided by mixin classes (e.g. OpenAICompatibleBot) in the MRO.
+    Use ``hasattr(bot, 'call_vision')`` to detect support at runtime.
+    """
+
+    def reply(self, query, context: Context = None) -> Reply:
+        """
+        bot auto-reply content
+        :param req: received message
+        :return: reply content
+        """
+        raise NotImplementedError
diff --git a/models/bot_factory.py b/models/bot_factory.py
new file mode 100644
index 0000000..415e922
--- /dev/null
+++ b/models/bot_factory.py
@@ -0,0 +1,84 @@
+"""
+channel factory
+"""
+from common import const
+
+
+def create_bot(bot_type):
+    """
+    create a bot_type instance
+    :param bot_type: bot type code
+    :return: bot instance
+    """
+    if bot_type == const.BAIDU:
+        # 替换Baidu Unit为Baidu文心千帆对话接口
+        # from models.baidu.baidu_unit_bot import BaiduUnitBot
+        # return BaiduUnitBot()
+        from models.baidu.baidu_wenxin import BaiduWenxinBot
+        return BaiduWenxinBot()
+
+    elif bot_type == const.DEEPSEEK:
+        from models.deepseek.deepseek_bot import DeepSeekBot
+        return DeepSeekBot()
+
+    elif bot_type == const.QIANFAN:
+        from models.qianfan.qianfan_bot import QianfanBot
+        return QianfanBot()
+
+    elif bot_type == const.MIMO:
+        from models.mimo.mimo_bot import MimoBot
+        return MimoBot()
+
+    elif bot_type in (const.OPENAI, const.CHATGPT, const.CUSTOM) or bot_type.startswith("custom:"):  # OpenAI-compatible API
+        from models.chatgpt.chat_gpt_bot import ChatGPTBot
+        return ChatGPTBot()
+
+    elif bot_type == const.OPEN_AI:
+        # OpenAI 官方对话模型API
+        from models.openai.open_ai_bot import OpenAIBot
+        return OpenAIBot()
+
+    elif bot_type == const.CHATGPTONAZURE:
+        # Azure chatgpt service https://azure.microsoft.com/en-in/products/cognitive-services/openai-service/
+        from models.chatgpt.chat_gpt_bot import AzureChatGPTBot
+        return AzureChatGPTBot()
+
+    elif bot_type == const.XUNFEI:
+        from models.xunfei.xunfei_spark_bot import XunFeiBot
+        return XunFeiBot()
+
+    elif bot_type == const.LINKAI:
+        from models.linkai.link_ai_bot import LinkAIBot
+        return LinkAIBot()
+
+    elif bot_type == const.CLAUDEAPI:
+        from models.claudeapi.claude_api_bot import ClaudeAPIBot
+        return ClaudeAPIBot()
+    elif bot_type in (const.QWEN, const.QWEN_DASHSCOPE):
+        from models.dashscope.dashscope_bot import DashscopeBot
+        return DashscopeBot()
+    elif bot_type == const.GEMINI:
+        from models.gemini.google_gemini_bot import GoogleGeminiBot
+        return GoogleGeminiBot()
+
+    elif bot_type == const.ZHIPU_AI or bot_type == "glm-4":  # "glm-4" kept for backward compatibility
+        from models.zhipuai.zhipuai_bot import ZHIPUAIBot
+        return ZHIPUAIBot()
+
+    elif bot_type == const.MOONSHOT:
+        from models.moonshot.moonshot_bot import MoonshotBot
+        return MoonshotBot()
+    
+    elif bot_type == const.MiniMax:
+        from models.minimax.minimax_bot import MinimaxBot
+        return MinimaxBot()
+
+    elif bot_type == const.MODELSCOPE:
+        from models.modelscope.modelscope_bot import ModelScopeBot
+        return ModelScopeBot()
+
+    elif bot_type == const.DOUBAO:
+        from models.doubao.doubao_bot import DoubaoBot
+        return DoubaoBot()
+
+    raise RuntimeError
diff --git a/models/chatgpt/chat_gpt_bot.py b/models/chatgpt/chat_gpt_bot.py
new file mode 100644
index 0000000..ac00693
--- /dev/null
+++ b/models/chatgpt/chat_gpt_bot.py
@@ -0,0 +1,472 @@
+# encoding:utf-8
+
+import time
+import json
+
+from models.openai.openai_compat import (
+    error as openai_error,
+    RateLimitError,
+    Timeout,
+    APIError,
+    APIConnectionError,
+    wrap_http_error,
+)
+from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
+import requests
+from common import const
+from common.i18n import t as _t
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.custom_provider import resolve_custom_credentials, parse_custom_bot_type
+from models.chatgpt.chat_gpt_session import ChatGPTSession
+from models.openai.open_ai_image import OpenAIImage
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.token_bucket import TokenBucket
+from config import conf, load_config
+from models.baidu.baidu_wenxin_session import BaiduWenxinSession
+
+# OpenAI对话模型API (可用)
+class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
+    def __init__(self):
+        super().__init__()
+        # Resolve api key / base from config (no global SDK state anymore).
+        is_custom, _ = parse_custom_bot_type(conf().get("bot_type", ""))
+        custom_model = None
+        if is_custom:
+            # Supports multiple custom providers via bot_type "custom:<id>"
+            # with automatic fallback to the legacy custom_api_key/base fields.
+            self._api_key, self._api_base, custom_model = resolve_custom_credentials()
+        else:
+            self._api_key = conf().get("open_ai_api_key")
+            self._api_base = conf().get("open_ai_api_base") or None
+        self._proxy = conf().get("proxy") or None
+        self._http_client = OpenAIHTTPClient(
+            api_key=self._api_key,
+            api_base=self._api_base,
+            proxy=self._proxy,
+        )
+        if conf().get("rate_limit_chatgpt"):
+            self.tb4chatgpt = TokenBucket(conf().get("rate_limit_chatgpt", 20))
+        # Per-provider model takes precedence over global model.
+        conf_model = custom_model or conf().get("model") or "gpt-3.5-turbo"
+        self.sessions = SessionManager(ChatGPTSession, model=conf_model)
+        # o1相关模型不支持system prompt，暂时用文心模型的session
+
+        self.args = {
+            "model": conf_model,  # 对话模型的名称
+            "temperature": conf().get("temperature", 0.9),  # 值在[0,1]之间，越大表示回复越具有不确定性
+            # "max_tokens":4096,  # 回复最大的字符数
+            "top_p": conf().get("top_p", 1),
+            "frequency_penalty": conf().get("frequency_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            "presence_penalty": conf().get("presence_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            "request_timeout": conf().get("request_timeout", None),  # 请求超时时间，openai接口默认设置为600，对于难问题一般需要较长时间
+            "timeout": conf().get("request_timeout", None),  # 重试超时时间，在这个时间内，将会自动重试
+        }
+        # 部分模型暂不支持一些参数，特殊处理
+        if conf_model in [const.O1, const.O1_MINI, const.GPT_5, const.GPT_5_MINI, const.GPT_5_NANO, const.GPT_55]:
+            remove_keys = ["temperature", "top_p", "frequency_penalty", "presence_penalty"]
+            for key in remove_keys:
+                self.args.pop(key, None)  # 如果键不存在，使用 None 来避免抛出错、
+            if conf_model in [const.O1, const.O1_MINI]:  # o1系列模型不支持系统提示词，使用文心模型的session
+                self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or const.O1_MINI)
+
+    def get_api_config(self):
+        """Get API configuration for OpenAI-compatible base class"""
+        is_custom, _ = parse_custom_bot_type(conf().get("bot_type", ""))
+        if is_custom:
+            custom_key, custom_base, custom_model = resolve_custom_credentials()
+            api_key = custom_key
+            api_base = custom_base
+            model = custom_model or conf().get("model", "gpt-3.5-turbo")
+        else:
+            api_key = conf().get("open_ai_api_key")
+            api_base = conf().get("open_ai_api_base")
+            model = conf().get("model", "gpt-3.5-turbo")
+        return {
+            'api_key': api_key,
+            'api_base': api_base,
+            'model': model,
+            'default_temperature': conf().get("temperature", 0.9),
+            'default_top_p': conf().get("top_p", 1.0),
+            'default_frequency_penalty': conf().get("frequency_penalty", 0.0),
+            'default_presence_penalty': conf().get("presence_penalty", 0.0),
+        }
+
+    def _get_http_client(self) -> OpenAIHTTPClient:
+        """Override the default HTTP client to reuse our pre-configured one."""
+        return self._http_client
+    
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[CHATGPT] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, _t("记忆已清除", "Memory cleared"))
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, _t("所有人记忆已清除", "All memories cleared"))
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, _t("配置已更新", "Config updated"))
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[CHATGPT] session query={}".format(session.messages))
+
+            api_key = context.get("openai_api_key")
+            model = context.get("gpt_model")
+            new_args = None
+            if model:
+                new_args = self.args.copy()
+                new_args["model"] = model
+            # if context.get('stream'):
+            #     # reply in stream
+            #     return self.reply_text_stream(query, new_query, session_id)
+
+            reply_content = self.reply_text(session, api_key, args=new_args)
+            logger.debug(
+                "[CHATGPT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[CHATGPT] reply {} used 0 tokens.".format(reply_content))
+            return reply
+
+        elif context.type == ContextType.IMAGE_CREATE:
+            ok, retstring = self.create_img(query, 0)
+            reply = None
+            if ok:
+                reply = Reply(ReplyType.IMAGE_URL, retstring)
+            else:
+                reply = Reply(ReplyType.ERROR, retstring)
+            return reply
+        elif context.type == ContextType.IMAGE:
+            logger.info("[CHATGPT] Image message received")
+            reply = self.reply_image(context)
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, _t("Bot不支持处理{}类型的消息", "Bot does not support message type {}").format(context.type))
+            return reply
+
+    def reply_image(self, context):
+        """
+        Process image message using OpenAI Vision API
+        """
+        import base64
+        import os
+        
+        try:
+            image_path = context.content
+            logger.info(f"[CHATGPT] Processing image: {image_path}")
+            
+            # Check if file exists
+            if not os.path.exists(image_path):
+                logger.error(f"[CHATGPT] Image file not found: {image_path}")
+                return Reply(ReplyType.ERROR, _t("图片文件不存在", "Image file not found"))
+            
+            # Read and encode image
+            with open(image_path, "rb") as f:
+                image_data = f.read()
+                image_base64 = base64.b64encode(image_data).decode("utf-8")
+            
+            # Detect image format
+            extension = os.path.splitext(image_path)[1].lower()
+            mime_type_map = {
+                ".jpg": "image/jpeg",
+                ".jpeg": "image/jpeg", 
+                ".png": "image/png",
+                ".gif": "image/gif",
+                ".webp": "image/webp"
+            }
+            mime_type = mime_type_map.get(extension, "image/jpeg")
+            
+            # Get model and API config
+            is_custom, _ = parse_custom_bot_type(conf().get("bot_type", ""))
+            if is_custom:
+                custom_key, custom_base, custom_model = resolve_custom_credentials()
+                model = context.get("gpt_model") or custom_model or conf().get("model", "gpt-4o")
+                api_key = context.get("openai_api_key") or custom_key
+                api_base = custom_base
+            else:
+                model = context.get("gpt_model") or conf().get("model", "gpt-4o")
+                api_key = context.get("openai_api_key") or conf().get("open_ai_api_key")
+                api_base = conf().get("open_ai_api_base")
+            
+            # Build vision request
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": "请描述这张图片的内容"},
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": f"data:{mime_type};base64,{image_base64}"
+                            }
+                        }
+                    ]
+                }
+            ]
+            
+            logger.info(f"[CHATGPT] Calling vision API with model: {model}")
+            
+            # Call OpenAI-compatible API via HTTP
+            response = self._http_client.chat_completions(
+                api_key=api_key or None,
+                api_base=api_base or None,
+                model=model,
+                messages=messages,
+                max_tokens=1000,
+            )
+
+            content = response["choices"][0]["message"]["content"]
+            logger.info(f"[CHATGPT] Vision API response: {content[:100]}...")
+            
+            # Clean up temp file
+            try:
+                os.remove(image_path)
+                logger.debug(f"[CHATGPT] Removed temp image file: {image_path}")
+            except Exception:
+                pass
+            
+            return Reply(ReplyType.TEXT, content)
+            
+        except Exception as e:
+            logger.error(f"[CHATGPT] Image processing error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            return Reply(ReplyType.ERROR, _t("图片识别失败: ", "Image recognition failed: ") + str(e))
+
+    def reply_text(self, session: ChatGPTSession, api_key=None, args=None, retry_count=0) -> dict:
+        """
+        call openai's ChatCompletion to get the answer
+        :param session: a conversation session
+        :param session_id: session id
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            if conf().get("rate_limit_chatgpt") and not self.tb4chatgpt.get_token():
+                raise RateLimitError("RateLimitError: rate limit exceeded")
+            # If api_key is None, the per-instance default key will be used.
+            if args is None:
+                args = self.args
+            # Translate old SDK kwargs to HTTP client params:
+            # - request_timeout / timeout -> per-call timeout
+            call_args = dict(args)
+            timeout = call_args.pop("request_timeout", None) or call_args.pop("timeout", None)
+            response = self._http_client.chat_completions(
+                api_key=api_key or None,
+                timeout=timeout,
+                messages=session.messages,
+                **call_args,
+            )
+            logger.info("[ChatGPT] reply={}, total_tokens={}".format(
+                response["choices"][0]["message"]["content"],
+                response["usage"]["total_tokens"]
+            ))
+            return {
+                "total_tokens": response["usage"]["total_tokens"],
+                "completion_tokens": response["usage"]["completion_tokens"],
+                "content": response["choices"][0]["message"]["content"],
+            }
+        except OpenAIHTTPError as http_err:
+            return self._handle_reply_error(
+                wrap_http_error(http_err), session, api_key, args, retry_count
+            )
+        except Exception as e:
+            return self._handle_reply_error(e, session, api_key, args, retry_count)
+
+    def _handle_reply_error(self, e, session, api_key, args, retry_count):
+        """Map exception to user-facing reply with retry/backoff (mirrors SDK behavior)."""
+        need_retry = retry_count < 2
+        result = {"completion_tokens": 0, "content": _t("我现在有点累了，等会再来吧", "I'm a bit tired right now. Please try again later.")}
+        if isinstance(e, RateLimitError):
+            logger.warn("[CHATGPT] RateLimitError: {}".format(e))
+            result["content"] = _t("提问太快啦，请休息一下再问我吧", "You're asking too fast. Please take a short break and try again.")
+            if need_retry:
+                time.sleep(20)
+        elif isinstance(e, Timeout):
+            logger.warn("[CHATGPT] Timeout: {}".format(e))
+            result["content"] = _t("我没有收到你的消息", "I didn't receive your message")
+            if need_retry:
+                time.sleep(5)
+        elif isinstance(e, APIConnectionError):
+            logger.warn("[CHATGPT] APIConnectionError: {}".format(e))
+            result["content"] = _t("我连接不到你的网络", "I can't reach your network")
+            if need_retry:
+                time.sleep(5)
+        elif isinstance(e, APIError):
+            logger.warn("[CHATGPT] Bad Gateway: {}".format(e))
+            result["content"] = _t("请再问我一次", "Please ask me again")
+            if need_retry:
+                time.sleep(10)
+        else:
+            logger.exception("[CHATGPT] Exception: {}".format(e))
+            need_retry = False
+            self.sessions.clear_session(session.session_id)
+
+        if need_retry:
+            logger.warn("[CHATGPT] 第{}次重试".format(retry_count + 1))
+            return self.reply_text(session, api_key, args, retry_count + 1)
+        return result
+
+class AzureChatGPTBot(ChatGPTBot):
+    """Azure OpenAI variant.
+
+    Azure's HTTP shape differs from public OpenAI:
+      URL    : {endpoint}/openai/deployments/{deployment}/chat/completions
+      Auth   : api-key header (not Bearer)
+      Query  : ?api-version={version}
+    We model that with a dedicated HTTP client and override _get_http_client
+    so the OpenAICompatibleBot streaming/tool path uses it transparently.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._azure_api_version = conf().get("azure_api_version", "2023-06-01-preview")
+        self._azure_deployment_id = conf().get("azure_deployment_id")
+        # Drop legacy SDK kwarg; Azure deployment is encoded in the URL now.
+        self.args.pop("deployment_id", None)
+
+        endpoint = (self._api_base or "").rstrip("/")
+        deployment = self._azure_deployment_id or ""
+        # Build a base that already includes /openai/deployments/{deployment}.
+        # /chat/completions will be appended by the client.
+        azure_base = (
+            f"{endpoint}/openai/deployments/{deployment}" if endpoint and deployment else endpoint
+        )
+        self._http_client = _AzureChatHTTPClient(
+            api_key=self._api_key,
+            api_base=azure_base,
+            api_version=self._azure_api_version,
+            proxy=self._proxy,
+        )
+
+    def create_img(self, query, retry_count=0, api_key=None):
+        text_to_image_model = conf().get("text_to_image")
+        if text_to_image_model == "dall-e-2":
+            api_version = "2023-06-01-preview"
+            endpoint = conf().get("azure_openai_dalle_api_base","open_ai_api_base")
+            # 检查endpoint是否以/结尾
+            if not endpoint.endswith("/"):
+                endpoint = endpoint + "/"
+            url = "{}openai/images/generations:submit?api-version={}".format(endpoint, api_version)
+            api_key = conf().get("azure_openai_dalle_api_key","open_ai_api_key")
+            headers = {"api-key": api_key, "Content-Type": "application/json"}
+            try:
+                body = {"prompt": query, "size": conf().get("image_create_size", "256x256"),"n": 1}
+                submission = requests.post(url, headers=headers, json=body)
+                operation_location = submission.headers['operation-location']
+                status = ""
+                while (status != "succeeded"):
+                    if retry_count > 3:
+                        return False, _t("图片生成失败", "Image generation failed")
+                    response = requests.get(operation_location, headers=headers)
+                    status = response.json()['status']
+                    retry_count += 1
+                image_url = response.json()['result']['data'][0]['url']
+                return True, image_url
+            except Exception as e:
+                logger.error("create image error: {}".format(e))
+                return False, _t("图片生成失败", "Image generation failed")
+        elif text_to_image_model == "dall-e-3":
+            api_version = conf().get("azure_api_version", "2024-02-15-preview")
+            endpoint = conf().get("azure_openai_dalle_api_base","open_ai_api_base")
+            # 检查endpoint是否以/结尾
+            if not endpoint.endswith("/"):
+                endpoint = endpoint + "/"
+            url = "{}openai/deployments/{}/images/generations?api-version={}".format(endpoint, conf().get("azure_openai_dalle_deployment_id","text_to_image"),api_version)
+            api_key = conf().get("azure_openai_dalle_api_key","open_ai_api_key")
+            headers = {"api-key": api_key, "Content-Type": "application/json"}
+            try:
+                body = {"prompt": query, "size": conf().get("image_create_size", "1024x1024"), "quality": conf().get("dalle3_image_quality", "standard")}
+                response = requests.post(url, headers=headers, json=body)
+                response.raise_for_status()  # 检查请求是否成功
+                data = response.json()
+
+                # 检查响应中是否包含图像 URL
+                if 'data' in data and len(data['data']) > 0 and 'url' in data['data'][0]:
+                    image_url = data['data'][0]['url']
+                    return True, image_url
+                else:
+                    error_message = "响应中没有图像 URL"
+                    logger.error(error_message)
+                    return False, _t("图片生成失败", "Image generation failed")
+
+            except requests.exceptions.RequestException as e:
+                # 捕获所有请求相关的异常
+                try:
+                    error_detail = response.json().get('error', {}).get('message', str(e))
+                except ValueError:
+                    error_detail = str(e)
+                error_message = f"{error_detail}"
+                logger.error(error_message)
+                return False, error_message
+
+            except Exception as e:
+                # 捕获所有其他异常
+                error_message = f"生成图像时发生错误: {e}"
+                logger.error(error_message)
+                return False, _t("图片生成失败", "Image generation failed")
+        else:
+            return False, _t("图片生成失败，未配置text_to_image参数", "Image generation failed: text_to_image is not configured")
+
+    def get_api_config(self):
+        config = super().get_api_config()
+        # The Azure HTTP client already stores the deployment-scoped base URL.
+        # Passing the raw endpoint again would override it in call_with_tools().
+        config["api_base"] = None
+        return config
+
+
+class _AzureChatHTTPClient(OpenAIHTTPClient):
+    """Subclass that injects Azure's ``api-version`` query param and ``api-key``
+    header on every chat-completion request, and accepts the deployment-scoped
+    base URL set by :class:`AzureChatGPTBot`.
+    """
+
+    def __init__(self, api_key, api_base, api_version, proxy=None, timeout=None):
+        super().__init__(
+            api_key=api_key, api_base=api_base, proxy=proxy, timeout=timeout
+        )
+        self._api_version = api_version
+
+    def _build_headers(self, api_key, extra_headers, url=None):
+        # Azure uses api-key header, not Bearer token. No attribution
+        # headers — Azure deployments are the customer's own tenant.
+        key = api_key if api_key is not None else self.api_key
+        headers = {"Content-Type": "application/json"}
+        if key:
+            headers["api-key"] = key
+        if self.extra_headers:
+            headers.update(self.extra_headers)
+        if extra_headers:
+            headers.update(extra_headers)
+        return headers
+
+    def chat_completions(self, **kwargs):
+        # Always force api-version query param for Azure.
+        eq = dict(kwargs.get("extra_query") or {})
+        eq.setdefault("api-version", self._api_version)
+        kwargs["extra_query"] = eq
+        return super().chat_completions(**kwargs)
+    
diff --git a/models/chatgpt/chat_gpt_session.py b/models/chatgpt/chat_gpt_session.py
new file mode 100644
index 0000000..d25b093
--- /dev/null
+++ b/models/chatgpt/chat_gpt_session.py
@@ -0,0 +1,104 @@
+from models.session_manager import Session
+from common.log import logger
+from common import const
+
+"""
+    e.g.  [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Who won the world series in 2020?"},
+        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
+        {"role": "user", "content": "Where was it played?"}
+    ]
+"""
+
+
+class ChatGPTSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="gpt-3.5-turbo"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+# refer to https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
+def num_tokens_from_messages(messages, model):
+    """Returns the number of tokens used by a list of messages."""
+
+    if model in ["wenxin", "xunfei"] or model.startswith(const.GEMINI):
+        return num_tokens_by_character(messages)
+
+    import tiktoken
+
+    if model in ["gpt-3.5-turbo-0301", "gpt-35-turbo", "gpt-3.5-turbo-1106", "moonshot", const.LINKAI_35]:
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    elif model in ["gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-turbo-0613",
+                   "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-35-turbo-16k", "gpt-4-turbo-preview",
+                   "gpt-4-1106-preview", const.GPT4_TURBO_PREVIEW, const.GPT4_VISION_PREVIEW, const.GPT4_TURBO_01_25,
+                   const.GPT_4o, const.GPT_4O_0806, const.GPT_4o_MINI, const.LINKAI_4o, const.LINKAI_4_TURBO, const.GPT_5, const.GPT_5_MINI, const.GPT_5_NANO]:
+        return num_tokens_from_messages(messages, model="gpt-4")
+    elif model.startswith("claude-3"):
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    try:
+        encoding = tiktoken.encoding_for_model(model)
+    except KeyError:
+        logger.debug("Warning: model not found. Using cl100k_base encoding.")
+        encoding = tiktoken.get_encoding("cl100k_base")
+    if model == "gpt-3.5-turbo":
+        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
+        tokens_per_name = -1  # if there's a name, the role is omitted
+    elif model == "gpt-4":
+        tokens_per_message = 3
+        tokens_per_name = 1
+    else:
+        logger.debug(f"num_tokens_from_messages() is not implemented for model {model}. Returning num tokens assuming gpt-3.5-turbo.")
+        return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
+    num_tokens = 0
+    for message in messages:
+        num_tokens += tokens_per_message
+        for key, value in message.items():
+            num_tokens += len(encoding.encode(value))
+            if key == "name":
+                num_tokens += tokens_per_name
+    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
+    return num_tokens
+
+
+def num_tokens_by_character(messages):
+    """Returns the number of tokens used by a list of messages."""
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/claudeapi/claude_api_bot.py b/models/claudeapi/claude_api_bot.py
new file mode 100644
index 0000000..68ee81d
--- /dev/null
+++ b/models/claudeapi/claude_api_bot.py
@@ -0,0 +1,619 @@
+# encoding:utf-8
+
+import base64
+import json
+import re
+import time
+from typing import Optional
+
+import requests
+
+from models.baidu.baidu_wenxin_session import BaiduWenxinSession
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf
+
+# Optional OpenAI image support
+try:
+    from models.openai.open_ai_image import OpenAIImage
+    _openai_image_available = True
+except Exception as e:
+    logger.warning(f"OpenAI image support not available: {e}")
+    _openai_image_available = False
+    OpenAIImage = object  # Fallback to object
+
+user_session = dict()
+
+
+# OpenAI对话模型API (可用)
+class ClaudeAPIBot(Bot, OpenAIImage):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or "text-davinci-003")
+
+    @property
+    def api_key(self):
+        return conf().get("claude_api_key")
+
+    @property
+    def api_base(self):
+        return conf().get("claude_api_base") or "https://api.anthropic.com/v1"
+
+    @property
+    def proxy(self):
+        return conf().get("proxy", None)
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context and context.type:
+            if context.type == ContextType.TEXT:
+                logger.info("[CLAUDE_API] query={}".format(query))
+                session_id = context["session_id"]
+                reply = None
+                if query == "#清除记忆":
+                    self.sessions.clear_session(session_id)
+                    reply = Reply(ReplyType.INFO, "记忆已清除")
+                elif query == "#清除所有":
+                    self.sessions.clear_all_session()
+                    reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+                else:
+                    session = self.sessions.session_query(query, session_id)
+                    result = self.reply_text(session)
+                    logger.info(result)
+                    total_tokens, completion_tokens, reply_content = (
+                        result["total_tokens"],
+                        result["completion_tokens"],
+                        result["content"],
+                    )
+                    logger.debug(
+                        "[CLAUDE_API] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(str(session), session_id, reply_content, completion_tokens)
+                    )
+
+                    if total_tokens == 0:
+                        reply = Reply(ReplyType.ERROR, reply_content)
+                    else:
+                        self.sessions.session_reply(reply_content, session_id, total_tokens)
+                        reply = Reply(ReplyType.TEXT, reply_content)
+                return reply
+            elif context.type == ContextType.IMAGE_CREATE:
+                ok, retstring = self.create_img(query, 0)
+                reply = None
+                if ok:
+                    reply = Reply(ReplyType.IMAGE_URL, retstring)
+                else:
+                    reply = Reply(ReplyType.ERROR, retstring)
+                return reply
+
+    def reply_text(self, session: BaiduWenxinSession, retry_count=0, tools=None):
+        try:
+            actual_model = self._model_mapping(conf().get("model"))
+
+            # Prepare headers
+            headers = {
+                "x-api-key": self.api_key,
+                "anthropic-version": "2023-06-01",
+                "content-type": "application/json"
+            }
+
+            # Extract system prompt if present and prepare Claude-compatible messages
+            system_prompt = conf().get("character_desc", "")
+            claude_messages = []
+
+            for msg in session.messages:
+                if msg.get("role") == "system":
+                    system_prompt = msg["content"]
+                else:
+                    claude_messages.append(msg)
+
+            # Prepare request data
+            data = {
+                "model": actual_model,
+                "messages": claude_messages,
+                "max_tokens": self._get_max_tokens(actual_model)
+            }
+
+            if system_prompt:
+                data["system"] = system_prompt
+
+            if tools:
+                data["tools"] = tools
+
+            # Make HTTP request
+            proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
+            response = requests.post(
+                f"{self.api_base}/messages",
+                headers=headers,
+                json=data,
+                proxies=proxies
+            )
+
+            if response.status_code != 200:
+                raise Exception(f"API request failed: {response.status_code} - {response.text}")
+
+            claude_response = response.json()
+            # Handle response content and tool calls
+            res_content = ""
+            tool_calls = []
+
+            content_blocks = claude_response.get("content", [])
+            for block in content_blocks:
+                if block.get("type") == "text":
+                    res_content += block.get("text", "")
+                elif block.get("type") == "tool_use":
+                    tool_calls.append({
+                        "id": block.get("id", ""),
+                        "name": block.get("name", ""),
+                        "arguments": block.get("input", {})
+                    })
+
+            res_content = res_content.strip().replace("<|endoftext|>", "")
+            usage = claude_response.get("usage", {})
+            total_tokens = usage.get("input_tokens", 0) + usage.get("output_tokens", 0)
+            completion_tokens = usage.get("output_tokens", 0)
+
+            logger.info("[CLAUDE_API] reply={}".format(res_content))
+            if tool_calls:
+                logger.info("[CLAUDE_API] tool_calls={}".format(tool_calls))
+
+            result = {
+                "total_tokens": total_tokens,
+                "completion_tokens": completion_tokens,
+                "content": res_content,
+            }
+
+            if tool_calls:
+                result["tool_calls"] = tool_calls
+
+            return result
+        except Exception as e:
+            need_retry = retry_count < 2
+            result = {"total_tokens": 0, "completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+
+            # Handle different types of errors
+            error_str = str(e).lower()
+            if "rate" in error_str or "limit" in error_str:
+                logger.warn("[CLAUDE_API] RateLimitError: {}".format(e))
+                result["content"] = "提问太快啦，请休息一下再问我吧"
+                if need_retry:
+                    time.sleep(20)
+            elif "timeout" in error_str:
+                logger.warn("[CLAUDE_API] Timeout: {}".format(e))
+                result["content"] = "我没有收到你的消息"
+                if need_retry:
+                    time.sleep(5)
+            elif "connection" in error_str or "network" in error_str:
+                logger.warn("[CLAUDE_API] APIConnectionError: {}".format(e))
+                need_retry = False
+                result["content"] = "我连接不到你的网络"
+            else:
+                logger.warn("[CLAUDE_API] Exception: {}".format(e))
+                need_retry = False
+                self.sessions.clear_session(session.session_id)
+
+            if need_retry:
+                logger.warn("[CLAUDE_API] 第{}次重试".format(retry_count + 1))
+                return self.reply_text(session, retry_count + 1, tools)
+            else:
+                return result
+
+    def _model_mapping(self, model) -> str:
+        if model == "claude-3-opus":
+            return const.CLAUDE_3_OPUS
+        elif model == "claude-3-sonnet":
+            return const.CLAUDE_3_SONNET
+        elif model == "claude-3-haiku":
+            return const.CLAUDE_3_HAIKU
+        elif model == "claude-3.5-sonnet":
+            return const.CLAUDE_35_SONNET
+        return model
+
+    def _get_max_tokens(self, model: str) -> int:
+        """
+        Get max_tokens for the model.
+        Reference from pi-mono:
+        - Claude 3.5/3.7: 8192
+        - Claude 3 Opus: 4096
+        - Default: 8192
+        """
+        if model and (model.startswith("claude-3-5") or model.startswith("claude-3-7")):
+            return 8192
+        elif model and model.startswith("claude-3") and "opus" in model:
+            return 4096
+        elif model and (model.startswith("claude-sonnet-4") or model.startswith("claude-sonnet-5")
+                         or model.startswith("claude-opus-4") or model.startswith("claude-fable")):
+            return 64000
+        return 8192
+
+    @staticmethod
+    def _parse_data_url(data_url: str):
+        """Parse a data:<mime>;base64,<data> URL into (media_type, base64_data)."""
+        m = re.match(r"^data:([^;]+);base64,(.+)$", data_url, re.DOTALL)
+        if m:
+            return m.group(1), m.group(2)
+        return None, None
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using Claude Messages API (native image blocks)."""
+        try:
+            actual_model = model or self._model_mapping(conf().get("model"))
+
+            # Build Claude-native image content block
+            if image_url.startswith("data:"):
+                media_type, b64_data = self._parse_data_url(image_url)
+                if not b64_data:
+                    return {"error": True, "message": "Invalid base64 data URL"}
+                image_block = {
+                    "type": "image",
+                    "source": {"type": "base64",
+                               "media_type": media_type or "image/jpeg",
+                               "data": b64_data},
+                }
+            else:
+                image_block = {
+                    "type": "image",
+                    "source": {"type": "url", "url": image_url},
+                }
+
+            data = {
+                "model": actual_model,
+                "max_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        image_block,
+                        {"type": "text", "text": question},
+                    ],
+                }],
+            }
+
+            headers = {
+                "x-api-key": self.api_key,
+                "anthropic-version": "2023-06-01",
+                "content-type": "application/json",
+            }
+            proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
+            resp = requests.post(f"{self.api_base}/messages",
+                                 headers=headers, json=data, proxies=proxies)
+
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+
+            body = resp.json()
+            text_parts = [b.get("text", "") for b in body.get("content", [])
+                          if b.get("type") == "text"]
+            usage = body.get("usage", {})
+            return {
+                "model": actual_model,
+                "content": "".join(text_parts),
+                "usage": {
+                    "prompt_tokens": usage.get("input_tokens", 0),
+                    "completion_tokens": usage.get("output_tokens", 0),
+                    "total_tokens": usage.get("input_tokens", 0) + usage.get("output_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[CLAUDE] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call Claude API with tool support for agent integration
+
+        Args:
+            messages: List of messages
+            tools: List of tool definitions
+            stream: Whether to use streaming
+            **kwargs: Additional parameters
+            
+        Returns:
+            Formatted response compatible with OpenAI format or generator for streaming
+        """
+        actual_model = self._model_mapping(conf().get("model"))
+
+        # Extract system prompt from messages if present
+        system_prompt = kwargs.get("system", conf().get("character_desc", ""))
+        claude_messages = []
+
+        for msg in messages:
+            if msg.get("role") == "system":
+                system_prompt = msg["content"]
+            else:
+                claude_messages.append(self._sanitize_message(msg))
+
+        request_params = {
+            "model": actual_model,
+            "max_tokens": kwargs.get("max_tokens", self._get_max_tokens(actual_model)),
+            "messages": claude_messages,
+            "stream": stream
+        }
+
+        if system_prompt:
+            request_params["system"] = system_prompt
+
+        if tools:
+            request_params["tools"] = tools
+
+        try:
+            if stream:
+                return self._handle_stream_response(request_params)
+            else:
+                return self._handle_sync_response(request_params)
+        except Exception as e:
+            logger.error(f"Claude API call error: {e}")
+            if stream:
+                # Return error generator for stream
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": str(e),
+                        "status_code": 500
+                    }
+
+                return error_generator()
+            else:
+                # Return error response for sync
+                return {
+                    "error": True,
+                    "message": str(e),
+                    "status_code": 500
+                }
+
+    @staticmethod
+    def _sanitize_message(msg: dict) -> dict:
+        """Strip thinking blocks without a ``signature`` from assistant messages.
+
+        When the session switches from another model (e.g. MiniMax) to Claude,
+        the in-memory history may contain thinking blocks that lack the
+        ``signature`` field required by the Anthropic API, causing 400 errors.
+        We create a shallow copy so the original history is not mutated.
+        """
+        if msg.get("role") != "assistant":
+            return msg
+        content = msg.get("content")
+        if not isinstance(content, list):
+            return msg
+        cleaned = [
+            block for block in content
+            if not (isinstance(block, dict)
+                    and block.get("type") == "thinking"
+                    and "signature" not in block)
+        ]
+        if len(cleaned) == len(content):
+            return msg
+        return {**msg, "content": cleaned}
+
+    def _handle_sync_response(self, request_params):
+        """Handle synchronous Claude API response"""
+        # Prepare headers
+        headers = {
+            "x-api-key": self.api_key,
+            "anthropic-version": "2023-06-01",
+            "content-type": "application/json"
+        }
+
+        # Make HTTP request
+        proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
+        response = requests.post(
+            f"{self.api_base}/messages",
+            headers=headers,
+            json=request_params,
+            proxies=proxies
+        )
+
+        if response.status_code != 200:
+            raise Exception(f"API request failed: {response.status_code} - {response.text}")
+
+        claude_response = response.json()
+
+        # Extract content blocks
+        text_content = ""
+        tool_calls = []
+
+        content_blocks = claude_response.get("content", [])
+        for block in content_blocks:
+            if block.get("type") == "text":
+                text_content += block.get("text", "")
+            elif block.get("type") == "tool_use":
+                tool_calls.append({
+                    "id": block.get("id", ""),
+                    "type": "function",
+                    "function": {
+                        "name": block.get("name", ""),
+                        "arguments": json.dumps(block.get("input", {}))
+                    }
+                })
+
+        # Build message in OpenAI format
+        message = {
+            "role": "assistant",
+            "content": text_content
+        }
+        if tool_calls:
+            message["tool_calls"] = tool_calls
+
+        # Format response to match OpenAI structure
+        usage = claude_response.get("usage", {})
+        formatted_response = {
+            "id": claude_response.get("id", ""),
+            "object": "chat.completion",
+            "created": int(time.time()),
+            "model": claude_response.get("model", request_params["model"]),
+            "choices": [
+                {
+                    "index": 0,
+                    "message": message,
+                    "finish_reason": claude_response.get("stop_reason", "stop")
+                }
+            ],
+            "usage": {
+                "prompt_tokens": usage.get("input_tokens", 0),
+                "completion_tokens": usage.get("output_tokens", 0),
+                "total_tokens": usage.get("input_tokens", 0) + usage.get("output_tokens", 0)
+            }
+        }
+
+        return formatted_response
+
+    def _handle_stream_response(self, request_params):
+        """Handle streaming Claude API response using HTTP requests"""
+        # Prepare headers
+        headers = {
+            "x-api-key": self.api_key,
+            "anthropic-version": "2023-06-01",
+            "content-type": "application/json"
+        }
+
+        # Add stream parameter
+        request_params["stream"] = True
+
+        # Track tool use state
+        tool_uses_map = {}  # {index: {id, name, input}}
+        current_tool_use_index = -1
+        stop_reason = None  # Track stop reason from Claude
+
+        try:
+            # Make streaming HTTP request
+            proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
+            response = requests.post(
+                f"{self.api_base}/messages",
+                headers=headers,
+                json=request_params,
+                proxies=proxies,
+                stream=True
+            )
+
+            if response.status_code != 200:
+                error_text = response.text
+                try:
+                    error_data = json.loads(error_text)
+                    error_msg = error_data.get("error", {}).get("message", error_text)
+                except Exception:
+                    error_msg = error_text or "Unknown error"
+
+                yield {
+                    "error": True,
+                    "status_code": response.status_code,
+                    "message": error_msg
+                }
+                return
+
+            # Process streaming response
+            for line in response.iter_lines():
+                if line:
+                    line = line.decode('utf-8')
+                    if line.startswith('data: '):
+                        line = line[6:]  # Remove 'data: ' prefix
+                        if line == '[DONE]':
+                            break
+                        try:
+                            event = json.loads(line)
+                            event_type = event.get("type")
+
+                            if event_type == "content_block_start":
+                                # New content block
+                                block = event.get("content_block", {})
+                                if block.get("type") == "tool_use":
+                                    current_tool_use_index = event.get("index", 0)
+                                    tool_uses_map[current_tool_use_index] = {
+                                        "id": block.get("id", ""),
+                                        "name": block.get("name", ""),
+                                        "input": ""
+                                    }
+
+                            elif event_type == "content_block_delta":
+                                delta = event.get("delta", {})
+                                delta_type = delta.get("type")
+
+                                if delta_type == "thinking_delta":
+                                    thinking_text = delta.get("thinking", "")
+                                    if thinking_text:
+                                        yield {
+                                            "choices": [{
+                                                "index": 0,
+                                                "delta": {
+                                                    "role": "assistant",
+                                                    "reasoning_content": thinking_text
+                                                },
+                                                "finish_reason": None
+                                            }]
+                                        }
+
+                                elif delta_type == "text_delta":
+                                    content = delta.get("text", "")
+                                    yield {
+                                        "id": event.get("id", ""),
+                                        "object": "chat.completion.chunk",
+                                        "created": int(time.time()),
+                                        "model": request_params["model"],
+                                        "choices": [{
+                                            "index": 0,
+                                            "delta": {"content": content},
+                                            "finish_reason": None
+                                        }]
+                                    }
+
+                                elif delta_type == "input_json_delta":
+                                    # Tool input accumulation
+                                    if current_tool_use_index >= 0:
+                                        tool_uses_map[current_tool_use_index]["input"] += delta.get("partial_json", "")
+
+                            elif event_type == "message_delta":
+                                # Extract stop_reason from delta
+                                delta = event.get("delta", {})
+                                if "stop_reason" in delta:
+                                    stop_reason = delta.get("stop_reason")
+                                    logger.info(f"[Claude] Stream stop_reason: {stop_reason}")
+                                
+                                # Message complete - yield tool calls if any
+                                if tool_uses_map:
+                                    for idx in sorted(tool_uses_map.keys()):
+                                        tool_data = tool_uses_map[idx]
+                                        yield {
+                                            "id": event.get("id", ""),
+                                            "object": "chat.completion.chunk",
+                                            "created": int(time.time()),
+                                            "model": request_params["model"],
+                                            "choices": [{
+                                                "index": 0,
+                                                "delta": {
+                                                    "tool_calls": [{
+                                                        "index": idx,
+                                                        "id": tool_data["id"],
+                                                        "type": "function",
+                                                        "function": {
+                                                            "name": tool_data["name"],
+                                                            "arguments": tool_data["input"]
+                                                        }
+                                                    }]
+                                                },
+                                                "finish_reason": stop_reason
+                                            }]
+                                        }
+                            
+                            elif event_type == "message_stop":
+                                # Final event - log completion
+                                logger.debug(f"[Claude] Stream completed with stop_reason: {stop_reason}")
+
+                        except json.JSONDecodeError:
+                            continue
+
+        except requests.RequestException as e:
+            logger.error(f"Claude streaming request error: {e}")
+            yield {
+                "error": True,
+                "message": f"Connection error: {str(e)}",
+                "status_code": 0
+            }
+        except Exception as e:
+            logger.error(f"Claude streaming error: {e}")
+            yield {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
diff --git a/models/custom_provider.py b/models/custom_provider.py
new file mode 100644
index 0000000..5a2e11d
--- /dev/null
+++ b/models/custom_provider.py
@@ -0,0 +1,125 @@
+# encoding:utf-8
+
+"""
+Centralized resolver for custom (OpenAI-compatible) provider credentials.
+
+CowAgent historically supported only a *single* custom provider via the flat
+config keys ``custom_api_key`` / ``custom_api_base``. This module adds support
+for *multiple* custom providers (see issue #2838) while remaining 100%
+backward compatible.
+
+Config model
+------------
+- ``custom_providers``: list of dicts, each describing one custom provider::
+
+      {
+          "id": "3f2a9c1b",               # server-generated short uuid (primary key)
+          "name": "my-provider",           # user-facing display label (not a key)
+          "api_key": "sk-...",             # required
+          "api_base": "https://...",       # required, must be OpenAI-compatible
+          "model": "model-name"           # optional default model
+      }
+
+Routing
+-------
+- ``bot_type: "custom"`` (legacy): reads the flat ``custom_api_key`` / ``custom_api_base``.
+- ``bot_type: "custom:<id>"`` (multi-provider): looks up the provider by id in
+  ``custom_providers``.  There is a single source of truth — no separate
+  ``custom_active_provider`` field.
+
+Backward-compatibility contract
+-------------------------------
+When ``bot_type`` is exactly ``"custom"`` (no colon suffix), behaviour is
+unchanged: we return ``custom_api_key`` / ``custom_api_base`` values.
+"""
+
+import uuid
+from config import conf
+from common.log import logger
+
+
+def generate_provider_id() -> str:
+    """Generate a short random id for a new custom provider."""
+    return uuid.uuid4().hex[:8]
+
+
+def get_custom_providers():
+    """Return the list of configured custom providers (always a list)."""
+    providers = conf().get("custom_providers")
+    if not isinstance(providers, list):
+        return []
+    # Keep only well-formed entries with an id.
+    return [p for p in providers if isinstance(p, dict) and p.get("id")]
+
+
+def _find_provider_by_id(providers, provider_id):
+    """Look up a provider by its id, or None if not found."""
+    if not providers or not provider_id:
+        return None
+    for p in providers:
+        if p.get("id") == provider_id:
+            return p
+    return None
+
+
+def parse_custom_bot_type(bot_type):
+    """Parse bot_type to extract custom provider id.
+
+    Returns:
+        (is_custom, provider_id) where:
+        - is_custom: True if bot_type starts with "custom"
+        - provider_id: the id suffix (e.g. "3f2a9c1b") or empty string for legacy mode
+    """
+    if not bot_type or not isinstance(bot_type, str):
+        return False, ""
+    if bot_type == "custom":
+        return True, ""
+    if bot_type.startswith("custom:"):
+        return True, bot_type[7:]  # len("custom:") == 7
+    return False, ""
+
+
+def resolve_custom_credentials():
+    """Resolve the effective (api_key, api_base, model) for custom mode.
+
+    Resolution order:
+      1. If ``bot_type`` is ``"custom:<id>"``, look up that id in
+         ``custom_providers``.
+      2. If ``bot_type`` is exactly ``"custom"`` (legacy), return the flat
+         ``custom_api_key`` / ``custom_api_base``.
+
+    :return: tuple ``(api_key, api_base, model)``. ``api_base`` and ``model``
+             may be ``None`` / empty when not configured.
+    """
+    bot_type = conf().get("bot_type", "")
+    is_custom, provider_id = parse_custom_bot_type(bot_type)
+
+    if not is_custom:
+        # Not custom at all — should not happen but be defensive.
+        return (
+            conf().get("open_ai_api_key", ""),
+            conf().get("open_ai_api_base") or None,
+            None,
+        )
+
+    if provider_id:
+        # Multi-provider mode: look up by id.
+        providers = get_custom_providers()
+        provider = _find_provider_by_id(providers, provider_id)
+        if provider is not None:
+            return (
+                provider.get("api_key", ""),
+                provider.get("api_base") or None,
+                provider.get("model") or None,
+            )
+        logger.warning(
+            "[CUSTOM] provider id '%s' not found in custom_providers, "
+            "falling back to legacy fields", provider_id
+        )
+
+    # Legacy single-provider fallback — unchanged behavior.
+    return (
+        conf().get("custom_api_key", ""),
+        conf().get("custom_api_base") or None,
+        None,
+    )
diff --git a/models/dashscope/dashscope_bot.py b/models/dashscope/dashscope_bot.py
new file mode 100644
index 0000000..b224ef8
--- /dev/null
+++ b/models/dashscope/dashscope_bot.py
@@ -0,0 +1,681 @@
+# encoding:utf-8
+
+import json
+from typing import Optional
+
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from .dashscope_session import DashscopeSession
+import os
+import dashscope
+from dashscope import MultiModalConversation
+from http import HTTPStatus
+
+
+
+# Legacy model name mapping for older dashscope SDK constants.
+# New models don't need to be added here — they use their name string directly.
+dashscope_models = {
+    "qwen-turbo": dashscope.Generation.Models.qwen_turbo,
+    "qwen-plus": dashscope.Generation.Models.qwen_plus,
+    "qwen-max": dashscope.Generation.Models.qwen_max,
+    "qwen-bailian-v1": dashscope.Generation.Models.bailian_v1,
+}
+
+# Model name prefixes that require MultiModalConversation API instead of Generation API.
+# Qwen3.5+ series are omni models that only support MultiModalConversation.
+MULTIMODAL_MODEL_PREFIXES = ("qwen3.5-", "qwen3.6-", "qwen3.7-plus")
+
+
+# Qwen对话模型API
+class DashscopeBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(DashscopeSession, model=conf().get("model") or "qwen3.7-plus")
+        self.model_name = conf().get("model") or "qwen3.7-plus"
+        self.client = dashscope.Generation
+        api_key = conf().get("dashscope_api_key")
+        if api_key:
+            os.environ["DASHSCOPE_API_KEY"] = api_key
+
+    @property
+    def api_key(self):
+        return conf().get("dashscope_api_key")
+
+    @staticmethod
+    def _is_multimodal_model(model_name: str) -> bool:
+        """Check if the model requires MultiModalConversation API"""
+        return model_name.startswith(MULTIMODAL_MODEL_PREFIXES)
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[DASHSCOPE] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[DASHSCOPE] session query={}".format(session.messages))
+
+            reply_content = self.reply_text(session)
+            logger.debug(
+                "[DASHSCOPE] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[DASHSCOPE] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: DashscopeSession, retry_count=0) -> dict:
+        """
+        call openai's ChatCompletion to get the answer
+        :param session: a conversation session
+        :param session_id: session id
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            dashscope.api_key = self.api_key
+            model = dashscope_models.get(self.model_name, self.model_name)
+            if self._is_multimodal_model(self.model_name):
+                mm_messages = self._prepare_messages_for_multimodal(session.messages)
+                response = MultiModalConversation.call(
+                    model=model,
+                    messages=mm_messages,
+                    result_format="message"
+                )
+            else:
+                response = self.client.call(
+                    model,
+                    messages=session.messages,
+                    result_format="message"
+                )
+            if response.status_code == HTTPStatus.OK:
+                resp_dict = self._response_to_dict(response)
+                choice = resp_dict["output"]["choices"][0]
+                content = choice.get("message", {}).get("content", "")
+                # Multimodal models may return content as a list of blocks
+                if isinstance(content, list):
+                    content = "".join(
+                        item.get("text", "") for item in content if isinstance(item, dict)
+                    )
+                usage = resp_dict.get("usage", {})
+                return {
+                    "total_tokens": usage.get("total_tokens", 0),
+                    "completion_tokens": usage.get("output_tokens", 0),
+                    "content": content,
+                }
+            else:
+                logger.error('Request id: %s, Status code: %s, error code: %s, error message: %s' % (
+                    response.request_id, response.status_code,
+                    response.code, response.message
+                ))
+                result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+                need_retry = retry_count < 2
+                result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+                if need_retry:
+                    return self.reply_text(session, retry_count + 1)
+                else:
+                    return result
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text(session, retry_count + 1)
+            else:
+                return result
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using DashScope MultiModalConversation API."""
+        try:
+            dashscope.api_key = self.api_key
+            vision_model = model or "qwen-vl-max"
+
+            # DashScope multimodal format: {"image": url} + {"text": question}
+            messages = [{
+                "role": "user",
+                "content": [
+                    {"image": image_url},
+                    {"text": question},
+                ],
+            }]
+
+            response = MultiModalConversation.call(
+                model=vision_model,
+                messages=messages,
+                max_tokens=max_tokens,
+            )
+
+            if response.status_code != HTTPStatus.OK:
+                return {
+                    "error": True,
+                    "message": f"{response.code} - {response.message}",
+                }
+
+            resp_dict = self._response_to_dict(response)
+            choice = resp_dict["output"]["choices"][0]
+            content = choice.get("message", {}).get("content", "")
+            if isinstance(content, list):
+                content = "".join(
+                    item.get("text", "") for item in content if isinstance(item, dict)
+                )
+            usage = resp_dict.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("input_tokens", 0),
+                    "completion_tokens": usage.get("output_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[DASHSCOPE] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call DashScope API with tool support for agent integration
+        
+        This method handles:
+        1. Format conversion (Claude format → DashScope format)
+        2. System prompt injection
+        3. API calling with DashScope SDK
+        4. Thinking mode support (enable_thinking for Qwen3)
+        
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, etc.)
+            
+        Returns:
+            Formatted response or generator for streaming
+        """
+        try:
+            # Convert messages from Claude format to DashScope format
+            messages = self._convert_messages_to_dashscope_format(messages)
+            
+            # Convert tools from Claude format to DashScope format
+            if tools:
+                tools = self._convert_tools_to_dashscope_format(tools)
+            
+            # Handle system prompt
+            system_prompt = kwargs.get('system')
+            if system_prompt:
+                # Add system message at the beginning if not already present
+                if not messages or messages[0].get('role') != 'system':
+                    messages = [{"role": "system", "content": system_prompt}] + messages
+                else:
+                    # Replace existing system message
+                    messages[0] = {"role": "system", "content": system_prompt}
+            
+            # Build request parameters
+            model_name = kwargs.get("model", self.model_name)
+            
+            parameters = {
+                "result_format": "message",  # Required for tool calling
+                "temperature": kwargs.get("temperature", conf().get("temperature", 0.85)),
+                "top_p": kwargs.get("top_p", conf().get("top_p", 0.8)),
+            }
+            
+            # Add max_tokens if specified
+            if kwargs.get("max_tokens"):
+                parameters["max_tokens"] = kwargs["max_tokens"]
+            
+            # Add tools if provided
+            if tools:
+                parameters["tools"] = tools
+                # Add tool_choice if specified
+                if kwargs.get("tool_choice"):
+                    parameters["tool_choice"] = kwargs["tool_choice"]
+            
+            # Add thinking parameters for Qwen3/QwQ models
+            if "qwen3" in model_name.lower() or "qwq" in model_name.lower():
+                thinking = kwargs.get("thinking", {"type": "enabled"})
+                if thinking.get("type") == "enabled":
+                    parameters["enable_thinking"] = True
+                    if kwargs.get("thinking_budget"):
+                        parameters["thinking_budget"] = kwargs["thinking_budget"]
+                    if stream:
+                        parameters["incremental_output"] = True
+                else:
+                    parameters["enable_thinking"] = False
+            
+            # Always use incremental_output for streaming (for better token-by-token streaming)
+            # This is especially important for tool calling to avoid incomplete responses
+            if stream:
+                parameters["incremental_output"] = True
+            
+            # Make API call with DashScope SDK
+            if stream:
+                return self._handle_stream_response(model_name, messages, parameters)
+            else:
+                return self._handle_sync_response(model_name, messages, parameters)
+                
+        except Exception as e:
+            error_msg = str(e)
+            logger.error(f"[DASHSCOPE] call_with_tools error: {error_msg}")
+            if stream:
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": error_msg,
+                        "status_code": 500
+                    }
+                return error_generator()
+            else:
+                return {
+                    "error": True,
+                    "message": error_msg,
+                    "status_code": 500
+                }
+    
+    def _handle_sync_response(self, model_name, messages, parameters):
+        """Handle synchronous DashScope API response"""
+        try:
+            # Set API key before calling
+            dashscope.api_key = self.api_key
+            model = dashscope_models.get(model_name, model_name)
+
+            if self._is_multimodal_model(model_name):
+                messages = self._prepare_messages_for_multimodal(messages)
+                response = MultiModalConversation.call(
+                    model=model,
+                    messages=messages,
+                    **parameters
+                )
+            else:
+                response = dashscope.Generation.call(
+                    model=model,
+                    messages=messages,
+                    **parameters
+                )
+
+            if response.status_code == HTTPStatus.OK:
+                # Convert response to dict to avoid DashScope object KeyError issues
+                resp_dict = self._response_to_dict(response)
+                choice = resp_dict["output"]["choices"][0]
+                message = choice.get("message", {})
+                content = message.get("content", "")
+                # Multimodal models may return content as a list of blocks
+                if isinstance(content, list):
+                    content = "".join(
+                        item.get("text", "") for item in content if isinstance(item, dict)
+                    )
+                usage = resp_dict.get("usage", {})
+                return {
+                    "id": resp_dict.get("request_id"),
+                    "object": "chat.completion",
+                    "created": 0,
+                    "model": model_name,
+                    "choices": [{
+                        "index": 0,
+                        "message": {
+                            "role": message.get("role", "assistant"),
+                            "content": content,
+                            "tool_calls": self._convert_tool_calls_to_openai_format(
+                                message.get("tool_calls")
+                            )
+                        },
+                        "finish_reason": choice.get("finish_reason")
+                    }],
+                    "usage": {
+                        "prompt_tokens": usage.get("input_tokens", 0),
+                        "completion_tokens": usage.get("output_tokens", 0),
+                        "total_tokens": usage.get("total_tokens", 0)
+                    }
+                }
+            else:
+                logger.error(f"[DASHSCOPE] API error: {response.code} - {response.message}")
+                return {
+                    "error": True,
+                    "message": response.message,
+                    "status_code": response.status_code
+                }
+
+        except Exception as e:
+            logger.error(f"[DASHSCOPE] sync response error: {e}")
+            return {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+    
+    def _handle_stream_response(self, model_name, messages, parameters):
+        """Handle streaming DashScope API response"""
+        try:
+            # Set API key before calling
+            dashscope.api_key = self.api_key
+            model = dashscope_models.get(model_name, model_name)
+
+            if self._is_multimodal_model(model_name):
+                messages = self._prepare_messages_for_multimodal(messages)
+                responses = MultiModalConversation.call(
+                    model=model,
+                    messages=messages,
+                    stream=True,
+                    **parameters
+                )
+            else:
+                responses = dashscope.Generation.call(
+                    model=model,
+                    messages=messages,
+                    stream=True,
+                    **parameters
+                )
+            
+            # Stream chunks to caller, converting to OpenAI format
+            for response in responses:
+                # Convert to dict first to avoid DashScope proxy object KeyError
+                resp_dict = self._response_to_dict(response)
+                status_code = resp_dict.get("status_code", 200)
+
+                if status_code != HTTPStatus.OK:
+                    err_code = resp_dict.get("code", "")
+                    err_msg = resp_dict.get("message", "Unknown error")
+                    logger.error(f"[DASHSCOPE] Stream error: {err_code} - {err_msg}")
+                    yield {
+                        "error": True,
+                        "message": err_msg,
+                        "status_code": status_code
+                    }
+                    continue
+
+                choices = resp_dict.get("output", {}).get("choices", [])
+                if not choices:
+                    continue
+
+                choice = choices[0]
+                finish_reason = choice.get("finish_reason")
+                message = choice.get("message", {})
+
+                # Convert to OpenAI-compatible format
+                openai_chunk = {
+                    "id": resp_dict.get("request_id"),
+                    "object": "chat.completion.chunk",
+                    "created": 0,
+                    "model": model_name,
+                    "choices": [{
+                        "index": 0,
+                        "delta": {},
+                        "finish_reason": finish_reason
+                    }]
+                }
+
+                # Add role
+                role = message.get("role")
+                if role:
+                    openai_chunk["choices"][0]["delta"]["role"] = role
+
+                # Add reasoning_content (thinking process from models like qwen3.5)
+                reasoning_content = message.get("reasoning_content")
+                if reasoning_content:
+                    openai_chunk["choices"][0]["delta"]["reasoning_content"] = reasoning_content
+
+                # Add content (multimodal models may return list of blocks)
+                content = message.get("content")
+                if isinstance(content, list):
+                    content = "".join(
+                        item.get("text", "") for item in content if isinstance(item, dict)
+                    )
+                if content:
+                    openai_chunk["choices"][0]["delta"]["content"] = content
+
+                # Add tool_calls
+                tool_calls = message.get("tool_calls")
+                if tool_calls:
+                    openai_chunk["choices"][0]["delta"]["tool_calls"] = self._convert_tool_calls_to_openai_format(tool_calls)
+
+                yield openai_chunk
+
+        except Exception as e:
+            logger.error(f"[DASHSCOPE] stream response error: {e}", exc_info=True)
+            yield {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+    
+    @staticmethod
+    def _response_to_dict(response) -> dict:
+        """
+        Convert DashScope response object to a plain dict.
+
+        DashScope SDK wraps responses in proxy objects whose __getattr__
+        delegates to __getitem__, raising KeyError (not AttributeError)
+        when an attribute is missing.  Standard hasattr / getattr only
+        catch AttributeError, so we must use try-except everywhere.
+        """
+        _SENTINEL = object()
+
+        def _safe_getattr(obj, name, default=_SENTINEL):
+            """getattr that also catches KeyError from DashScope proxy objects."""
+            try:
+                return getattr(obj, name)
+            except (AttributeError, KeyError, TypeError):
+                return default
+
+        def _has_attr(obj, name):
+            return _safe_getattr(obj, name) is not _SENTINEL
+
+        def _to_dict(obj):
+            if isinstance(obj, (str, int, float, bool, type(None))):
+                return obj
+            if isinstance(obj, dict):
+                return {k: _to_dict(v) for k, v in obj.items()}
+            if isinstance(obj, (list, tuple)):
+                return [_to_dict(i) for i in obj]
+            # DashScope response objects behave like dicts (have .keys())
+            if _has_attr(obj, "keys"):
+                try:
+                    return {k: _to_dict(obj[k]) for k in obj.keys()}
+                except Exception:
+                    pass
+            return obj
+
+        result = {}
+        # Extract known top-level fields safely
+        for attr in ("request_id", "status_code", "code", "message", "output", "usage"):
+            val = _safe_getattr(response, attr)
+            if val is _SENTINEL:
+                try:
+                    val = response[attr]
+                except (KeyError, TypeError, IndexError):
+                    continue
+            result[attr] = _to_dict(val)
+        return result
+
+    def _convert_tools_to_dashscope_format(self, tools):
+        """
+        Convert tools from Claude format to DashScope format
+        
+        Claude format: {name, description, input_schema}
+        DashScope format: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+        
+        dashscope_tools = []
+        for tool in tools:
+            # Check if already in DashScope/OpenAI format
+            if 'type' in tool and tool['type'] == 'function':
+                dashscope_tools.append(tool)
+            else:
+                # Convert from Claude format
+                dashscope_tools.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+        
+        return dashscope_tools
+    
+    @staticmethod
+    def _prepare_messages_for_multimodal(messages: list) -> list:
+        """
+        Ensure messages are compatible with MultiModalConversation API.
+
+        MultiModalConversation._preprocess_messages iterates every message
+        with ``content = message["content"]; for elem in content: ...``,
+        which means:
+          1. Every message MUST have a 'content' key.
+          2. 'content' MUST be an iterable (list), not a plain string.
+             The expected format is [{"text": "..."}, ...].
+
+        Meanwhile the DashScope API requires role='tool' messages to follow
+        assistant tool_calls, so we must NOT convert them to role='user'.
+        We just ensure they have a list-typed 'content'.
+        """
+        result = []
+        for msg in messages:
+            msg = dict(msg)  # shallow copy
+
+            # Normalize content to list format [{"text": "..."}]
+            content = msg.get("content")
+            if content is None or (isinstance(content, str) and content == ""):
+                msg["content"] = [{"text": ""}]
+            elif isinstance(content, str):
+                msg["content"] = [{"text": content}]
+            # If content is already a list, keep as-is (already in multimodal format)
+
+            result.append(msg)
+        return result
+
+    def _convert_messages_to_dashscope_format(self, messages):
+        """
+        Convert messages from Claude format to DashScope format
+        
+        Claude uses content blocks with types like 'tool_use', 'tool_result'
+        DashScope uses 'tool_calls' in assistant messages and 'tool' role for results
+        """
+        if not messages:
+            return []
+        
+        dashscope_messages = []
+        
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+            
+            # Handle string content (already in correct format)
+            if isinstance(content, str):
+                dashscope_messages.append(msg)
+                continue
+            
+            # Handle list content (Claude format with content blocks)
+            if isinstance(content, list):
+                # Check if this is a tool result message (user role with tool_result blocks)
+                if role == "user" and any(block.get("type") == "tool_result" for block in content):
+                    # Convert each tool_result block to a separate tool message
+                    for block in content:
+                        if block.get("type") == "tool_result":
+                            dashscope_messages.append({
+                                "role": "tool",
+                                "content": block.get("content", ""),
+                                "tool_call_id": block.get("tool_use_id")  # DashScope uses 'tool_call_id'
+                            })
+                
+                # Check if this is an assistant message with tool_use blocks
+                elif role == "assistant":
+                    # Separate text content and tool_use blocks
+                    text_parts = []
+                    tool_calls = []
+                    
+                    for block in content:
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_use":
+                            tool_calls.append({
+                                "id": block.get("id"),
+                                "type": "function",
+                                "function": {
+                                    "name": block.get("name"),
+                                    "arguments": json.dumps(block.get("input", {}))
+                                }
+                            })
+                    
+                    # Build DashScope format assistant message
+                    dashscope_msg = {
+                        "role": "assistant"
+                    }
+                    
+                    # Add content only if there is actual text
+                    # DashScope API: when tool_calls exist, content should be None or omitted if empty
+                    if text_parts:
+                        dashscope_msg["content"] = " ".join(text_parts)
+                    elif not tool_calls:
+                        # If no tool_calls and no text, set empty string (rare case)
+                        dashscope_msg["content"] = ""
+                    # If there are tool_calls but no text, don't set content field at all
+                    
+                    if tool_calls:
+                        dashscope_msg["tool_calls"] = tool_calls
+                    
+                    dashscope_messages.append(dashscope_msg)
+                else:
+                    # Other list content, keep as is
+                    dashscope_messages.append(msg)
+            else:
+                # Other formats, keep as is
+                dashscope_messages.append(msg)
+        
+        return dashscope_messages
+    
+    def _convert_tool_calls_to_openai_format(self, tool_calls):
+        """Convert DashScope tool_calls to OpenAI format"""
+        if not tool_calls:
+            return None
+        
+        openai_tool_calls = []
+        for tool_call in tool_calls:
+            # DashScope format is already similar to OpenAI
+            if isinstance(tool_call, dict):
+                openai_tool_calls.append(tool_call)
+            else:
+                # Handle object format
+                openai_tool_calls.append({
+                    "id": getattr(tool_call, 'id', None),
+                    "type": "function",
+                    "function": {
+                        "name": tool_call.function.name,
+                        "arguments": tool_call.function.arguments
+                    }
+                })
+        
+        return openai_tool_calls
diff --git a/models/dashscope/dashscope_session.py b/models/dashscope/dashscope_session.py
new file mode 100644
index 0000000..042334e
--- /dev/null
+++ b/models/dashscope/dashscope_session.py
@@ -0,0 +1,51 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class DashscopeSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="qwen-turbo"):
+        super().__init__(session_id)
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens,
+                                                                                       len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages)
+
+
+def num_tokens_from_messages(messages):
+    # 只是大概，具体计算规则：https://help.aliyun.com/zh/dashscope/developer-reference/token-api?spm=a2c4g.11186623.0.0.4d8b12b0BkP3K9
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/deepseek/__init__.py b/models/deepseek/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/models/deepseek/deepseek_bot.py b/models/deepseek/deepseek_bot.py
new file mode 100644
index 0000000..23c72b1
--- /dev/null
+++ b/models/deepseek/deepseek_bot.py
@@ -0,0 +1,680 @@
+# encoding:utf-8
+
+"""
+DeepSeek Bot — fully OpenAI-compatible, uses its own API key / base config.
+
+Supported models:
+- deepseek-chat       (V3, no thinking)
+- deepseek-reasoner   (R1, built-in reasoning, no `thinking` switch)
+- deepseek-v4-flash   (V4, supports thinking mode + tool calls)
+- deepseek-v4-flash   (V4 Flash, default; thinking mode + tool calls)
+- deepseek-v4-pro     (V4 Pro, stronger on complex tasks)
+
+Thinking mode notes (for V4 models):
+- Toggle: ``{"thinking": {"type": "enabled" | "disabled"}}`` (default: enabled)
+- Effort: ``reasoning_effort`` ∈ {"high", "max"} (low/medium → high, xhigh → max)
+- In thinking mode, ``temperature``/``top_p``/``presence_penalty``/``frequency_penalty``
+  are silently ignored by the server; we drop them locally to avoid confusion.
+- ``reasoning_content`` is returned alongside ``content``. For turns that triggered
+  tool calls, ``reasoning_content`` MUST be echoed back in subsequent requests, or
+  the API returns 400.
+"""
+
+import json
+import time
+from typing import Optional
+
+import requests
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf, load_config
+from .deepseek_session import DeepSeekSession
+
+DEFAULT_API_BASE = "https://api.deepseek.com/v1"
+
+
+class DeepSeekBot(Bot, OpenAICompatibleBot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(
+            DeepSeekSession,
+            model=conf().get("model") or const.DEEPSEEK_V4_FLASH,
+        )
+        conf_model = conf().get("model") or const.DEEPSEEK_V4_FLASH
+        self.args = {
+            "model": conf_model,
+            "temperature": conf().get("temperature", 0.7),
+            "top_p": conf().get("top_p", 1.0),
+            "frequency_penalty": conf().get("frequency_penalty", 0.0),
+            "presence_penalty": conf().get("presence_penalty", 0.0),
+        }
+
+    # ---------- config helpers ----------
+
+    @property
+    def api_key(self):
+        return conf().get("deepseek_api_key") or conf().get("open_ai_api_key")
+
+    @property
+    def api_base(self):
+        url = (
+            conf().get("deepseek_api_base")
+            or conf().get("open_ai_api_base")
+            or DEFAULT_API_BASE
+        )
+        return url.rstrip("/")
+
+    def get_api_config(self):
+        """OpenAICompatibleBot interface — used by call_with_tools()."""
+        return {
+            "api_key": self.api_key,
+            "api_base": self.api_base,
+            "model": conf().get("model", const.DEEPSEEK_V4_FLASH),
+            "default_temperature": conf().get("temperature", 0.7),
+            "default_top_p": conf().get("top_p", 1.0),
+            "default_frequency_penalty": conf().get("frequency_penalty", 0.0),
+            "default_presence_penalty": conf().get("presence_penalty", 0.0),
+        }
+
+    @staticmethod
+    def _model_supports_thinking(model_name: str) -> bool:
+        """V4 series models expose the explicit `thinking` switch."""
+        if not model_name:
+            return False
+        m = model_name.lower()
+        return m.startswith("deepseek-v4")
+
+    @staticmethod
+    def _is_reasoner_model(model_name: str) -> bool:
+        """deepseek-reasoner (R1) always thinks internally; no toggle."""
+        return bool(model_name) and "reasoner" in model_name.lower()
+
+    def _build_headers(self) -> dict:
+        return {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+    # ---------- simple chat (non-agent mode) ----------
+
+    def reply(self, query, context=None):
+        if context.type == ContextType.TEXT:
+            logger.info("[DEEPSEEK] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[DEEPSEEK] session query={}".format(session.messages))
+
+            new_args = self.args.copy()
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[DEEPSEEK] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages, session_id,
+                    reply_content["content"], reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(
+                    reply_content["content"], session_id, reply_content["total_tokens"],
+                )
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[DEEPSEEK] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session, args=None, retry_count: int = 0) -> dict:
+        try:
+            headers = self._build_headers()
+            body = dict(args) if args else dict(self.args)
+            body["messages"] = session.messages
+
+            # Thinking mode ignores temperature/top_p/penalties — strip to avoid noise.
+            model_name = str(body.get("model", ""))
+            if self._model_supports_thinking(model_name) or self._is_reasoner_model(model_name):
+                for k in ("temperature", "top_p", "presence_penalty", "frequency_penalty"):
+                    body.pop(k, None)
+
+            res = requests.post(
+                f"{self.api_base}/chat/completions",
+                headers=headers,
+                json=body,
+                timeout=180,
+            )
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"],
+                }
+            else:
+                response = res.json()
+                error = response.get("error", {})
+                logger.error(
+                    f"[DEEPSEEK] chat failed, status_code={res.status_code}, "
+                    f"msg={error.get('message')}, type={error.get('type')}"
+                )
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                return result
+        except Exception as e:
+            logger.exception(e)
+            if retry_count < 2:
+                return self.reply_text(session, args, retry_count + 1)
+            return {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+
+    # ==================== Agent mode support ====================
+
+    def call_with_tools(self, messages, tools=None, stream: bool = False, **kwargs):
+        """
+        Call DeepSeek API with tool support for agent integration.
+
+        Handles:
+        - Claude → OpenAI message/tool format conversion (with reasoning_content round-trip)
+        - System prompt injection
+        - Streaming SSE with tool_calls + reasoning_content delta
+        - Thinking mode toggle and reasoning_effort for V4 models
+        """
+        try:
+            converted_messages = self._convert_messages_to_openai_format(messages)
+
+            system_prompt = kwargs.pop("system", None)
+            if system_prompt:
+                if not converted_messages or converted_messages[0].get("role") != "system":
+                    converted_messages.insert(0, {"role": "system", "content": system_prompt})
+                else:
+                    converted_messages[0] = {"role": "system", "content": system_prompt}
+
+            converted_tools = None
+            if tools:
+                converted_tools = self._convert_tools_to_openai_format(tools)
+
+            model = kwargs.pop("model", None) or self.args["model"]
+            max_tokens = kwargs.pop("max_tokens", None)
+
+            request_body = {
+                "model": model,
+                "messages": converted_messages,
+                "stream": stream,
+            }
+            if max_tokens is not None:
+                request_body["max_tokens"] = max_tokens
+
+            if converted_tools:
+                request_body["tools"] = converted_tools
+                request_body["tool_choice"] = kwargs.pop("tool_choice", "auto")
+
+            # Thinking mode (V4 only). Honour the toggle propagated by agent_bridge.
+            thinking_param = kwargs.pop("thinking", None)
+            reasoning_effort = kwargs.pop("reasoning_effort", None)
+            thinking_active = False
+
+            if self._model_supports_thinking(model):
+                # Default to enabled per DeepSeek docs unless caller explicitly disables.
+                thinking_param = thinking_param or {"type": "enabled"}
+                request_body["thinking"] = thinking_param
+                thinking_active = thinking_param.get("type") == "enabled"
+                if thinking_active:
+                    # Default to "high"; allow caller override (e.g. "max" for heavy agent loops).
+                    request_body["reasoning_effort"] = reasoning_effort or "high"
+            elif self._is_reasoner_model(model):
+                # R1 thinks unconditionally — no `thinking` field, but reasoning_content still flows.
+                thinking_active = True
+
+            # Strip params silently ignored under thinking mode to keep the wire clean.
+            if thinking_active:
+                for k in ("temperature", "top_p", "presence_penalty", "frequency_penalty"):
+                    request_body.pop(k, None)
+                    kwargs.pop(k, None)
+            else:
+                # Non-thinking path: forward standard sampling controls.
+                temperature = kwargs.pop("temperature", None)
+                if temperature is not None:
+                    request_body["temperature"] = temperature
+                top_p = kwargs.pop("top_p", None)
+                if top_p is not None:
+                    request_body["top_p"] = top_p
+
+            logger.debug(
+                f"[DEEPSEEK] API call: model={model}, "
+                f"tools={len(converted_tools) if converted_tools else 0}, "
+                f"stream={stream}, thinking={thinking_active}"
+            )
+
+            if stream:
+                return self._handle_stream_response(request_body)
+            else:
+                return self._handle_sync_response(request_body)
+
+        except Exception as e:
+            logger.error(f"[DEEPSEEK] call_with_tools error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+
+            def error_generator():
+                yield {"error": True, "message": str(e), "status_code": 500}
+            return error_generator()
+
+    # -------------------- streaming --------------------
+
+    def _handle_stream_response(self, request_body: dict):
+        """Stream SSE chunks from DeepSeek and yield OpenAI-format deltas (with reasoning_content)."""
+        try:
+            headers = self._build_headers()
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, stream=True, timeout=180)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[DEEPSEEK] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            current_tool_calls = {}
+            finish_reason = None
+
+            for line in response.iter_lines():
+                if not line:
+                    continue
+
+                line = line.decode("utf-8")
+                if line.startswith("data: "):
+                    data_str = line[6:]
+                elif line.startswith("data:"):
+                    data_str = line[5:]
+                else:
+                    continue
+                if data_str.strip() == "[DONE]":
+                    break
+
+                try:
+                    chunk = json.loads(data_str)
+                except json.JSONDecodeError as e:
+                    logger.warning(f"[DEEPSEEK] JSON decode error: {e}, data: {data_str[:200]}")
+                    continue
+
+                if chunk.get("error"):
+                    error_data = chunk["error"]
+                    error_msg = error_data.get("message", "Unknown error") if isinstance(error_data, dict) else str(error_data)
+                    logger.error(f"[DEEPSEEK] stream error: {error_msg}")
+                    yield {"error": True, "message": error_msg, "status_code": 500}
+                    return
+
+                if not chunk.get("choices"):
+                    continue
+                choice = chunk["choices"][0]
+                delta = choice.get("delta", {})
+
+                if choice.get("finish_reason"):
+                    finish_reason = choice["finish_reason"]
+
+                # Reasoning content (thinking mode). Forward as its own delta so
+                # agent_stream.py can stitch it into a `thinking` block.
+                if delta.get("reasoning_content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "reasoning_content": delta["reasoning_content"],
+                            },
+                            "finish_reason": None,
+                        }]
+                    }
+
+                if delta.get("content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "content": delta["content"],
+                            },
+                        }]
+                    }
+
+                if "tool_calls" in delta and delta["tool_calls"]:
+                    for tool_call_chunk in delta["tool_calls"]:
+                        index = tool_call_chunk.get("index", 0)
+                        if index not in current_tool_calls:
+                            current_tool_calls[index] = {
+                                "id": tool_call_chunk.get("id", ""),
+                                "name": tool_call_chunk.get("function", {}).get("name", ""),
+                                "arguments": "",
+                            }
+                        if "function" in tool_call_chunk and "arguments" in tool_call_chunk["function"]:
+                            current_tool_calls[index]["arguments"] += tool_call_chunk["function"]["arguments"]
+
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {"tool_calls": [tool_call_chunk]},
+                            }]
+                        }
+
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason,
+                }]
+            }
+
+        except requests.exceptions.Timeout:
+            logger.error("[DEEPSEEK] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[DEEPSEEK] stream response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- sync --------------------
+
+    def _handle_sync_response(self, request_body: dict):
+        """Single-shot response. Yields a Claude-format dict for symmetry with stream path."""
+        try:
+            headers = self._build_headers()
+            request_body.pop("stream", None)
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, timeout=180)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[DEEPSEEK] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            result = response.json()
+            message = result["choices"][0]["message"]
+            finish_reason = result["choices"][0]["finish_reason"]
+
+            response_data = {"role": "assistant", "content": []}
+
+            # Surface reasoning as a `thinking` block so the agent layer can persist it
+            # and round-trip it on tool-call turns (required by DeepSeek API).
+            if message.get("reasoning_content"):
+                response_data["content"].append({
+                    "type": "thinking",
+                    "thinking": message["reasoning_content"],
+                })
+
+            if message.get("content"):
+                response_data["content"].append({
+                    "type": "text",
+                    "text": message["content"],
+                })
+
+            if message.get("tool_calls"):
+                for tool_call in message["tool_calls"]:
+                    try:
+                        tool_input = json.loads(tool_call["function"]["arguments"])
+                    except (json.JSONDecodeError, TypeError):
+                        tool_input = {}
+                    response_data["content"].append({
+                        "type": "tool_use",
+                        "id": tool_call["id"],
+                        "name": tool_call["function"]["name"],
+                        "input": tool_input,
+                    })
+
+            if finish_reason == "tool_calls":
+                response_data["stop_reason"] = "tool_use"
+            elif finish_reason == "stop":
+                response_data["stop_reason"] = "end_turn"
+            else:
+                response_data["stop_reason"] = finish_reason
+
+            yield response_data
+
+        except requests.exceptions.Timeout:
+            logger.error("[DEEPSEEK] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[DEEPSEEK] sync response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- format conversion --------------------
+
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        Convert Claude-format messages (content blocks) to OpenAI format.
+
+        Crucially, once any assistant turn in the history triggered a tool
+        call, DeepSeek requires `reasoning_content` on **every subsequent
+        assistant message** (not just the tool-call one) until the next user
+        turn — and in fact the API enforces this for the whole history when
+        thinking mode is enabled. Missing `reasoning_content` on any
+        assistant message returns 400. We back-fill an empty string when the
+        trace was not captured (e.g. history recorded while thinking was
+        disabled, or upstream proxy stripped the field).
+        """
+        if not messages:
+            return []
+
+        # Determine whether the history contains any tool-call assistant turn.
+        # If so, every assistant message must carry `reasoning_content`.
+        has_tool_call_history = False
+        for msg in messages:
+            if msg.get("role") != "assistant":
+                continue
+            if msg.get("tool_calls"):
+                has_tool_call_history = True
+                break
+            content = msg.get("content")
+            if isinstance(content, list) and any(
+                isinstance(b, dict) and b.get("type") == "tool_use" for b in content
+            ):
+                has_tool_call_history = True
+                break
+
+        converted = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            # Pass-through path for non-list content (e.g. plain string).
+            # Back-fill `reasoning_content` on assistant messages whenever the
+            # history contains any tool-call turn.
+            if not isinstance(content, list):
+                if (
+                    role == "assistant"
+                    and isinstance(msg, dict)
+                    and has_tool_call_history
+                    and "reasoning_content" not in msg
+                ):
+                    patched = dict(msg)
+                    patched["reasoning_content"] = ""
+                    converted.append(patched)
+                else:
+                    converted.append(msg)
+                continue
+
+            if role == "user":
+                has_tool_result = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+                )
+                if has_tool_result:
+                    text_parts = []
+                    tool_results = []
+
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_result":
+                            tool_call_id = block.get("tool_use_id") or ""
+                            result_content = block.get("content", "")
+                            if not isinstance(result_content, str):
+                                result_content = json.dumps(result_content, ensure_ascii=False)
+                            tool_results.append({
+                                "role": "tool",
+                                "tool_call_id": tool_call_id,
+                                "content": result_content,
+                            })
+
+                    converted.extend(tool_results)
+
+                    if text_parts:
+                        converted.append({"role": "user", "content": "\n".join(text_parts)})
+                else:
+                    converted.append(msg)
+
+            elif role == "assistant":
+                openai_msg = {"role": "assistant"}
+                text_parts = []
+                tool_calls = []
+                reasoning_parts = []
+
+                for block in content:
+                    if not isinstance(block, dict):
+                        continue
+                    btype = block.get("type")
+                    if btype == "text":
+                        text_parts.append(block.get("text", ""))
+                    elif btype == "tool_use":
+                        tool_calls.append({
+                            "id": block.get("id"),
+                            "type": "function",
+                            "function": {
+                                "name": block.get("name"),
+                                "arguments": json.dumps(block.get("input", {})),
+                            },
+                        })
+                    elif btype == "thinking":
+                        reasoning_parts.append(block.get("thinking", ""))
+
+                if text_parts:
+                    openai_msg["content"] = "\n".join(text_parts)
+                elif not tool_calls:
+                    openai_msg["content"] = ""
+
+                if tool_calls:
+                    openai_msg["tool_calls"] = tool_calls
+                    if not text_parts:
+                        openai_msg["content"] = None
+
+                # Round-trip reasoning_content: required for every assistant
+                # message once the history contains any tool-call turn (see
+                # outer comment). Use empty string as fallback when the trace
+                # was not captured — DeepSeek validates field presence, not
+                # value; non-thinking backends silently ignore it.
+                if reasoning_parts:
+                    openai_msg["reasoning_content"] = "\n".join(reasoning_parts)
+                elif has_tool_call_history:
+                    openai_msg["reasoning_content"] = ""
+
+                converted.append(openai_msg)
+            else:
+                converted.append(msg)
+
+        return converted
+
+    def _convert_tools_to_openai_format(self, tools):
+        """
+        Convert tools from Claude format to OpenAI format.
+
+        Claude: {name, description, input_schema}
+        OpenAI: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+
+        converted = []
+        for tool in tools:
+            if "type" in tool and tool["type"] == "function":
+                converted.append(tool)
+            else:
+                converted.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {}),
+                    },
+                })
+        return converted
+
+    # -------------------- vision --------------------
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyse an image via DeepSeek's OpenAI-compatible /chat/completions endpoint."""
+        try:
+            vision_model = model or self.args.get("model", const.DEEPSEEK_V4_FLASH)
+            payload = {
+                "model": vision_model,
+                "max_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = self._build_headers()
+            resp = requests.post(
+                f"{self.api_base}/chat/completions",
+                headers=headers, json=payload, timeout=180,
+            )
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+            data = resp.json()
+            if "error" in data:
+                return {"error": True, "message": data["error"].get("message", str(data["error"]))}
+            content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[DEEPSEEK] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
diff --git a/models/deepseek/deepseek_session.py b/models/deepseek/deepseek_session.py
new file mode 100644
index 0000000..ecf85b9
--- /dev/null
+++ b/models/deepseek/deepseek_session.py
@@ -0,0 +1,57 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class DeepSeekSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="deepseek-v4-flash"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(
+                    max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        content = msg.get("content", "")
+        if isinstance(content, str):
+            tokens += len(content)
+        elif isinstance(content, list):
+            for block in content:
+                if isinstance(block, dict):
+                    tokens += len(block.get("text", ""))
+    return tokens
diff --git a/models/doubao/__init__.py b/models/doubao/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/models/doubao/doubao_bot.py b/models/doubao/doubao_bot.py
new file mode 100644
index 0000000..9e0de58
--- /dev/null
+++ b/models/doubao/doubao_bot.py
@@ -0,0 +1,582 @@
+# encoding:utf-8
+
+import json
+import time
+from typing import Optional
+
+import requests
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf, load_config
+from .doubao_session import DoubaoSession
+
+
+# Doubao (火山方舟 / Volcengine Ark) API Bot
+class DoubaoBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(DoubaoSession, model=conf().get("model") or const.DOUBAO_SEED_2_1_PRO)
+        model = conf().get("model") or const.DOUBAO_SEED_2_1_PRO
+        self.args = {
+            "model": model,
+            "temperature": conf().get("temperature", 0.8),
+            "top_p": conf().get("top_p", 1.0),
+        }
+
+    @property
+    def api_key(self):
+        return conf().get("ark_api_key")
+
+    @property
+    def base_url(self):
+        url = conf().get("ark_base_url", "https://ark.cn-beijing.volces.com/api/v3")
+        if url.endswith("/chat/completions"):
+            url = url.rsplit("/chat/completions", 1)[0]
+        return url.rstrip("/")
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[DOUBAO] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[DOUBAO] session query={}".format(session.messages))
+
+            model = context.get("doubao_model")
+            new_args = self.args.copy()
+            if model:
+                new_args["model"] = model
+
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[DOUBAO] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[DOUBAO] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: DoubaoSession, args=None, retry_count: int = 0) -> dict:
+        """
+        Call Doubao chat completion API to get the answer
+        :param session: a conversation session
+        :param args: model args
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            body = args.copy()
+            body["messages"] = session.messages
+            # Disable thinking by default for better efficiency
+            body["thinking"] = {"type": "disabled"}
+            res = requests.post(
+                f"{self.base_url}/chat/completions",
+                headers=headers,
+                json=body
+            )
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"]
+                }
+            else:
+                response = res.json()
+                error = response.get("error", {})
+                logger.error(f"[DOUBAO] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    logger.warn(f"[DOUBAO] do retry, times={retry_count}")
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                else:
+                    return result
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using Doubao (Volcengine Ark) OpenAI-compatible API."""
+        try:
+            vision_model = model or self.args.get("model", const.DOUBAO_SEED_2_1_PRO)
+            payload = {
+                "model": vision_model,
+                "max_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json",
+            }
+            resp = requests.post(f"{self.base_url}/chat/completions",
+                                 headers=headers, json=payload, timeout=180)
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+            data = resp.json()
+            if "error" in data:
+                return {"error": True, "message": data["error"].get("message", str(data["error"]))}
+            content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[DOUBAO] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    # ==================== Agent mode support ====================
+
+    def call_with_tools(self, messages, tools=None, stream: bool = False, **kwargs):
+        """
+        Call Doubao API with tool support for agent integration.
+
+        This method handles:
+        1. Format conversion (Claude format -> OpenAI format)
+        2. System prompt injection
+        3. Streaming SSE response with tool_calls
+        4. Thinking (reasoning) is disabled by default for efficiency
+
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, model, etc.)
+
+        Returns:
+            Generator yielding OpenAI-format chunks (for streaming)
+        """
+        try:
+            # Convert messages from Claude format to OpenAI format
+            converted_messages = self._convert_messages_to_openai_format(messages)
+
+            # Inject system prompt if provided
+            system_prompt = kwargs.pop("system", None)
+            if system_prompt:
+                if not converted_messages or converted_messages[0].get("role") != "system":
+                    converted_messages.insert(0, {"role": "system", "content": system_prompt})
+                else:
+                    converted_messages[0] = {"role": "system", "content": system_prompt}
+
+            # Convert tools from Claude format to OpenAI format
+            converted_tools = None
+            if tools:
+                converted_tools = self._convert_tools_to_openai_format(tools)
+
+            # Resolve model / temperature
+            model = kwargs.pop("model", None) or self.args["model"]
+            max_tokens = kwargs.pop("max_tokens", None)
+            # Don't pop temperature, just ignore it - let API use default
+            kwargs.pop("temperature", None)
+
+            # Build request body (omit temperature, let the API use its own default)
+            request_body = {
+                "model": model,
+                "messages": converted_messages,
+                "stream": stream,
+            }
+            if max_tokens is not None:
+                request_body["max_tokens"] = max_tokens
+
+            # Add tools
+            if converted_tools:
+                request_body["tools"] = converted_tools
+                request_body["tool_choice"] = "auto"
+
+            request_body["thinking"] = kwargs.get("thinking", {"type": "enabled"})
+
+            logger.debug(f"[DOUBAO] API call: model={model}, "
+                         f"tools={len(converted_tools) if converted_tools else 0}, stream={stream}")
+
+            if stream:
+                return self._handle_stream_response(request_body)
+            else:
+                return self._handle_sync_response(request_body)
+
+        except Exception as e:
+            logger.error(f"[DOUBAO] call_with_tools error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+
+            def error_generator():
+                yield {"error": True, "message": str(e), "status_code": 500}
+            return error_generator()
+
+    # -------------------- streaming --------------------
+
+    def _handle_stream_response(self, request_body: dict):
+        """Handle streaming SSE response from Doubao API and yield OpenAI-format chunks."""
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}"
+            }
+
+            url = f"{self.base_url}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, stream=True, timeout=120)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[DOUBAO] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            current_tool_calls = {}
+            finish_reason = None
+
+            for line in response.iter_lines():
+                if not line:
+                    continue
+
+                line = line.decode("utf-8")
+                if not line.startswith("data: "):
+                    continue
+
+                data_str = line[6:]  # Remove "data: " prefix
+                if data_str.strip() == "[DONE]":
+                    break
+
+                try:
+                    chunk = json.loads(data_str)
+                except json.JSONDecodeError as e:
+                    logger.warning(f"[DOUBAO] JSON decode error: {e}, data: {data_str[:200]}")
+                    continue
+
+                # Check for error in chunk
+                if chunk.get("error"):
+                    error_data = chunk["error"]
+                    error_msg = error_data.get("message", "Unknown error") if isinstance(error_data, dict) else str(error_data)
+                    logger.error(f"[DOUBAO] stream error: {error_msg}")
+                    yield {"error": True, "message": error_msg, "status_code": 500}
+                    return
+
+                if not chunk.get("choices"):
+                    continue
+
+                choice = chunk["choices"][0]
+                delta = choice.get("delta", {})
+
+                if delta.get("reasoning_content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "reasoning_content": delta["reasoning_content"]
+                            },
+                            "finish_reason": None
+                        }]
+                    }
+                    continue
+
+                # Handle text content
+                if "content" in delta and delta["content"]:
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "content": delta["content"]
+                            }
+                        }]
+                    }
+
+                # Handle tool_calls (streamed incrementally)
+                if "tool_calls" in delta:
+                    for tool_call_chunk in delta["tool_calls"]:
+                        index = tool_call_chunk.get("index", 0)
+                        if index not in current_tool_calls:
+                            current_tool_calls[index] = {
+                                "id": tool_call_chunk.get("id", ""),
+                                "type": "tool_use",
+                                "name": tool_call_chunk.get("function", {}).get("name", ""),
+                                "input": ""
+                            }
+
+                        # Accumulate arguments
+                        if "function" in tool_call_chunk and "arguments" in tool_call_chunk["function"]:
+                            current_tool_calls[index]["input"] += tool_call_chunk["function"]["arguments"]
+
+                        # Yield OpenAI-format tool call delta
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "tool_calls": [tool_call_chunk]
+                                }
+                            }]
+                        }
+
+                # Capture finish_reason
+                if choice.get("finish_reason"):
+                    finish_reason = choice["finish_reason"]
+
+            # Final chunk with finish_reason
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason
+                }]
+            }
+
+        except requests.exceptions.Timeout:
+            logger.error("[DOUBAO] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[DOUBAO] stream response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- sync --------------------
+
+    def _handle_sync_response(self, request_body: dict):
+        """Handle synchronous API response and yield a single result dict."""
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}"
+            }
+
+            request_body.pop("stream", None)
+            url = f"{self.base_url}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, timeout=120)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[DOUBAO] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            result = response.json()
+            message = result["choices"][0]["message"]
+            finish_reason = result["choices"][0]["finish_reason"]
+
+            response_data = {"role": "assistant", "content": []}
+
+            # Add text content
+            if message.get("content"):
+                response_data["content"].append({
+                    "type": "text",
+                    "text": message["content"]
+                })
+
+            # Add tool calls
+            if message.get("tool_calls"):
+                for tool_call in message["tool_calls"]:
+                    response_data["content"].append({
+                        "type": "tool_use",
+                        "id": tool_call["id"],
+                        "name": tool_call["function"]["name"],
+                        "input": json.loads(tool_call["function"]["arguments"])
+                    })
+
+            # Map finish_reason
+            if finish_reason == "tool_calls":
+                response_data["stop_reason"] = "tool_use"
+            elif finish_reason == "stop":
+                response_data["stop_reason"] = "end_turn"
+            else:
+                response_data["stop_reason"] = finish_reason
+
+            yield response_data
+
+        except requests.exceptions.Timeout:
+            logger.error("[DOUBAO] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[DOUBAO] sync response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- format conversion --------------------
+
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        Convert messages from Claude format to OpenAI format.
+
+        Claude format uses content blocks: tool_use / tool_result / text
+        OpenAI format uses tool_calls in assistant, role=tool for results
+        """
+        if not messages:
+            return []
+
+        converted = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            # Already a simple string - pass through
+            if isinstance(content, str):
+                converted.append(msg)
+                continue
+
+            if not isinstance(content, list):
+                converted.append(msg)
+                continue
+
+            if role == "user":
+                has_tool_result = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+                )
+                if has_tool_result:
+                    text_parts = []
+                    tool_results = []
+
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_result":
+                            tool_call_id = block.get("tool_use_id") or ""
+                            result_content = block.get("content", "")
+                            if not isinstance(result_content, str):
+                                result_content = json.dumps(result_content, ensure_ascii=False)
+                            tool_results.append({
+                                "role": "tool",
+                                "tool_call_id": tool_call_id,
+                                "content": result_content
+                            })
+
+                    for tr in tool_results:
+                        converted.append(tr)
+
+                    if text_parts:
+                        converted.append({"role": "user", "content": "\n".join(text_parts)})
+                else:
+                    # Keep as-is for multimodal content (e.g. image_url blocks)
+                    converted.append(msg)
+
+            elif role == "assistant":
+                openai_msg = {"role": "assistant"}
+                text_parts = []
+                tool_calls = []
+
+                for block in content:
+                    if not isinstance(block, dict):
+                        continue
+                    if block.get("type") == "text":
+                        text_parts.append(block.get("text", ""))
+                    elif block.get("type") == "tool_use":
+                        tool_calls.append({
+                            "id": block.get("id"),
+                            "type": "function",
+                            "function": {
+                                "name": block.get("name"),
+                                "arguments": json.dumps(block.get("input", {}))
+                            }
+                        })
+
+                if text_parts:
+                    openai_msg["content"] = "\n".join(text_parts)
+                elif not tool_calls:
+                    openai_msg["content"] = ""
+
+                if tool_calls:
+                    openai_msg["tool_calls"] = tool_calls
+                    if not text_parts:
+                        openai_msg["content"] = None
+
+                converted.append(openai_msg)
+            else:
+                converted.append(msg)
+
+        return converted
+
+    def _convert_tools_to_openai_format(self, tools):
+        """
+        Convert tools from Claude format to OpenAI format.
+
+        Claude: {name, description, input_schema}
+        OpenAI: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+
+        converted = []
+        for tool in tools:
+            # Already in OpenAI format
+            if "type" in tool and tool["type"] == "function":
+                converted.append(tool)
+            else:
+                converted.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+
+        return converted
diff --git a/models/doubao/doubao_session.py b/models/doubao/doubao_session.py
new file mode 100644
index 0000000..1e432a1
--- /dev/null
+++ b/models/doubao/doubao_session.py
@@ -0,0 +1,52 @@
+from models.session_manager import Session
+from common import const
+from common.log import logger
+
+
+class DoubaoSession(Session):
+    def __init__(self, session_id, system_prompt=None, model=const.DOUBAO_SEED_2_1_PRO):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(
+                    max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/gemini/google_gemini_bot.py b/models/gemini/google_gemini_bot.py
new file mode 100644
index 0000000..02cdd06
--- /dev/null
+++ b/models/gemini/google_gemini_bot.py
@@ -0,0 +1,975 @@
+"""
+Google gemini bot
+
+@author zhayujie
+@Date 2023/12/15
+"""
+# encoding:utf-8
+
+import base64
+import json
+import mimetypes
+import os
+import re
+import time
+from typing import Optional
+
+import requests
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType, Context
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from models.chatgpt.chat_gpt_session import ChatGPTSession
+from models.baidu.baidu_wenxin_session import BaiduWenxinSession
+
+
+# OpenAI对话模型API (可用)
+class GoogleGeminiBot(Bot):
+
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(ChatGPTSession, model=conf().get("model") or "gpt-3.5-turbo")
+
+    @property
+    def api_key(self):
+        return conf().get("gemini_api_key")
+
+    @property
+    def model(self):
+        model_name = conf().get("model") or "gemini-3.5-flash"
+        if model_name == "gemini":
+            model_name = "gemini-3.5-flash"
+        return model_name
+
+    @property
+    def api_base(self):
+        base = conf().get("gemini_api_base", "").strip()
+        if base:
+            return base.rstrip('/')
+        return "https://generativelanguage.googleapis.com"
+
+    def reply(self, query, context: Context = None) -> Reply:
+        session_id = None
+        try:
+            if context.type != ContextType.TEXT:
+                logger.warn(f"[Gemini] Unsupported message type, type={context.type}")
+                return Reply(ReplyType.TEXT, None)
+            logger.info(f"[Gemini] query={query}")
+            session_id = context["session_id"]
+            session = self.sessions.session_query(query, session_id)
+            filtered_messages = self.filter_messages(session.messages)
+            logger.debug(f"[Gemini] messages={filtered_messages}")
+
+            response = self.call_with_tools(
+                messages=filtered_messages,
+                tools=None,
+                stream=False,
+                model=self.model
+            )
+
+            if isinstance(response, dict) and response.get("error"):
+                error_message = response.get("message", "Failed to invoke [Gemini] api!")
+                logger.error(f"[Gemini] API error: {error_message}")
+                self.sessions.session_reply(error_message, session_id)
+                return Reply(ReplyType.ERROR, error_message)
+
+            choices = response.get("choices", []) if isinstance(response, dict) else []
+            if choices and choices[0].get("message"):
+                reply_text = choices[0]["message"].get("content")
+                if reply_text:
+                    logger.info(f"[Gemini] reply={reply_text}")
+                    self.sessions.session_reply(reply_text, session_id)
+                    return Reply(ReplyType.TEXT, reply_text)
+
+            logger.warning("[Gemini] No valid response generated. Checking safety ratings.")
+            safety_ratings = response.get("safety_ratings", []) if isinstance(response, dict) else []
+            if safety_ratings:
+                for rating in safety_ratings:
+                    category = rating.get("category", "UNKNOWN")
+                    probability = rating.get("probability", "UNKNOWN")
+                    logger.warning(f"[Gemini] Safety rating: {category} - {probability}")
+
+            error_message = "No valid response generated due to safety constraints."
+            self.sessions.session_reply(error_message, session_id)
+            return Reply(ReplyType.ERROR, error_message)
+                    
+        except Exception as e:
+            logger.error(f"[Gemini] Error generating response: {str(e)}", exc_info=True)
+            error_message = "Failed to invoke [Gemini] api!"
+            if session_id:
+                self.sessions.session_reply(error_message, session_id)
+            return Reply(ReplyType.ERROR, error_message)
+            
+    def _convert_to_gemini_messages(self, messages: list):
+        res = []
+        for msg in messages:
+            if msg.get("role") == "user":
+                role = "user"
+            elif msg.get("role") == "assistant":
+                role = "model"
+            elif msg.get("role") == "system":
+                role = "user"
+            else:
+                continue
+            res.append({
+                "role": role,
+                "parts": [{"text": msg.get("content")}]
+            })
+        return res
+
+    @staticmethod
+    def filter_messages(messages: list):
+        res = []
+        turn = "user"
+        if not messages:
+            return res
+        for i in range(len(messages) - 1, -1, -1):
+            message = messages[i]
+            role = message.get("role")
+            if role == "system":
+                res.insert(0, message)
+                continue
+            if role != turn:
+                continue
+            res.insert(0, message)
+            if turn == "user":
+                turn = "assistant"
+            elif turn == "assistant":
+                turn = "user"
+        return res
+
+    @staticmethod
+    def _extract_image_paths_from_text(content: str):
+        if not isinstance(content, str):
+            return "", []
+        pattern = r"\[图片:\s*([^\]]+)\]"
+        image_paths = [m.strip().strip("'\"") for m in re.findall(pattern, content) if m.strip()]
+        # Replace markers with path-only hints so the model still knows the
+        # original file location (needed when it calls tools like vision).
+        def _replace_with_hint(m):
+            path = m.group(1).strip().strip("'\"")
+            return f"[attached image: {path}]"
+        cleaned_text = re.sub(pattern, _replace_with_hint, content)
+        cleaned_text = re.sub(r"\n{3,}", "\n\n", cleaned_text).strip()
+        return cleaned_text, image_paths
+
+    @staticmethod
+    def _build_image_inline_part(image_path: str):
+        if not image_path:
+            return None
+        try:
+            if image_path.startswith("file://"):
+                image_path = image_path[7:]
+
+            image_path = os.path.expanduser(image_path)
+            if not os.path.exists(image_path):
+                logger.warning(f"[Gemini] Image file not found: {image_path}")
+                return None
+
+            with open(image_path, "rb") as f:
+                image_bytes = f.read()
+
+            mime_type = mimetypes.guess_type(image_path)[0] or "image/png"
+            if not mime_type.startswith("image/"):
+                mime_type = "image/png"
+
+            return {
+                "inlineData": {
+                    "mimeType": mime_type,
+                    "data": base64.b64encode(image_bytes).decode("utf-8")
+                }
+            }
+        except Exception as e:
+            logger.warning(f"[Gemini] Failed to build inline image part from path={image_path}, err={e}")
+            return None
+
+    @staticmethod
+    def _build_inline_part_from_image_url(image_url):
+        if not image_url:
+            return None
+
+        if isinstance(image_url, dict):
+            image_url = image_url.get("url")
+        if not image_url or not isinstance(image_url, str):
+            return None
+
+        if image_url.startswith("data:"):
+            match = re.match(r"^data:([^;]+);base64,(.+)$", image_url, re.DOTALL)
+            if not match:
+                logger.warning("[Gemini] Invalid data URL for image block")
+                return None
+            return {
+                "inlineData": {
+                    "mimeType": match.group(1),
+                    "data": match.group(2).strip()
+                }
+            }
+
+        if image_url.startswith("file://") or os.path.exists(os.path.expanduser(image_url)):
+            return GoogleGeminiBot._build_image_inline_part(image_url)
+
+        if image_url.startswith("http://") or image_url.startswith("https://"):
+            try:
+                response = requests.get(image_url, timeout=20)
+                if response.status_code != 200:
+                    logger.warning(f"[Gemini] Failed to fetch remote image: status={response.status_code}, url={image_url}")
+                    return None
+                mime_type = response.headers.get("Content-Type", "image/png").split(";")[0].strip()
+                if not mime_type.startswith("image/"):
+                    mime_type = "image/png"
+                return {
+                    "inlineData": {
+                        "mimeType": mime_type,
+                        "data": base64.b64encode(response.content).decode("utf-8")
+                    }
+                }
+            except Exception as e:
+                logger.warning(f"[Gemini] Failed to download remote image: url={image_url}, err={e}")
+                return None
+
+        logger.warning(f"[Gemini] Unsupported image URL format: {image_url[:120]}")
+        return None
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using Gemini REST API."""
+        try:
+            model_name = model or self.model or "gemini-2.0-flash"
+            image_part = self._build_inline_part_from_image_url({"url": image_url})
+            if not image_part:
+                return {"error": True, "message": f"Cannot process image URL: {image_url[:120]}"}
+
+            payload = {
+                "contents": [{
+                    "role": "user",
+                    "parts": [image_part, {"text": question}],
+                }],
+                "generationConfig": {"maxOutputTokens": max_tokens},
+                "safetySettings": [
+                    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+                    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+                    {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+                    {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+                ],
+            }
+            endpoint = f"{self.api_base}/v1beta/models/{model_name}:generateContent"
+            headers = {"x-goog-api-key": self.api_key, "Content-Type": "application/json"}
+            resp = requests.post(endpoint, headers=headers, json=payload, timeout=180)
+
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+
+            body = resp.json()
+            candidates = body.get("candidates", [])
+            text_parts = []
+            for part in candidates[0].get("content", {}).get("parts", []) if candidates else []:
+                if "text" in part:
+                    text_parts.append(part["text"])
+
+            usage_meta = body.get("usageMetadata", {})
+            return {
+                "model": model_name,
+                "content": "".join(text_parts),
+                "usage": {
+                    "prompt_tokens": usage_meta.get("promptTokenCount", 0),
+                    "completion_tokens": usage_meta.get("candidatesTokenCount", 0),
+                    "total_tokens": usage_meta.get("totalTokenCount", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[Gemini] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call Gemini API with tool support using REST API (following official docs)
+        
+        Args:
+            messages: List of messages (OpenAI format)
+            tools: List of tool definitions (OpenAI/Claude format)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (system, max_tokens, temperature, etc.)
+            
+        Returns:
+            Formatted response compatible with OpenAI format or generator for streaming
+        """
+        try:
+            model_name = kwargs.get("model", self.model or "gemini-1.5-flash")
+            
+            # Build REST API payload
+            payload = {"contents": []}
+            inline_image_count = 0
+
+            # Keep legacy behavior: disable Gemini safety blocking like old SDK path.
+            payload["safetySettings"] = [
+                {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
+                {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
+                {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
+                {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
+            ]
+            
+            # Extract and set system instruction
+            system_prompt = kwargs.get("system", "")
+            if not system_prompt:
+                for msg in messages:
+                    if msg.get("role") == "system":
+                        system_prompt = msg["content"]
+                        break
+            
+            if system_prompt:
+                payload["system_instruction"] = {
+                    "parts": [{"text": system_prompt}]
+                }
+            
+            # Convert messages to Gemini format
+            for msg in messages:
+                role = msg.get("role")
+                content = msg.get("content", "")
+                
+                if role == "system":
+                    continue
+                
+                # Convert role
+                gemini_role = "user" if role in ["user", "tool"] else "model"
+                
+                # For model messages that carry original Gemini parts (with
+                # thoughtSignature etc.), use them directly instead of
+                # reconstructing from Claude-format tool_use blocks.
+                if gemini_role == "model" and "_gemini_raw_parts" in msg:
+                    raw_parts = msg["_gemini_raw_parts"]
+                    if raw_parts:
+                        payload["contents"].append({
+                            "role": "model",
+                            "parts": raw_parts
+                        })
+                        continue
+                
+                # Handle different content formats
+                parts = []
+                
+                if isinstance(content, str):
+                    # Text with optional [图片: /path/to/file] markers
+                    cleaned_text, image_paths = self._extract_image_paths_from_text(content)
+                    if cleaned_text:
+                        parts.append({"text": cleaned_text})
+                    image_added = False
+                    for image_path in image_paths:
+                        image_part = self._build_image_inline_part(image_path)
+                        if image_part:
+                            parts.append(image_part)
+                            image_added = True
+                            inline_image_count += 1
+                    if not cleaned_text and not image_added and content:
+                        parts.append({"text": content})
+                    
+                elif isinstance(content, list):
+                    # List of content blocks (Claude format)
+                    for block in content:
+                        if not isinstance(block, dict):
+                            if isinstance(block, str):
+                                parts.append({"text": block})
+                            continue
+                        
+                        block_type = block.get("type")
+                        
+                        if block_type == "text":
+                            # Text block with optional image markers
+                            block_text = block.get("text", "")
+                            cleaned_text, image_paths = self._extract_image_paths_from_text(block_text)
+                            if cleaned_text:
+                                parts.append({"text": cleaned_text})
+                            for image_path in image_paths:
+                                image_part = self._build_image_inline_part(image_path)
+                                if image_part:
+                                    parts.append(image_part)
+
+                        elif block_type in ["image", "image_url"]:
+                            # OpenAI format: {"type":"image_url","image_url":{"url":"..."}}
+                            # Claude format: {"type":"image","source":{"type":"base64","media_type":"...","data":"..."}}
+                            image_part = None
+                            if block_type == "image":
+                                source = block.get("source", {})
+                                if isinstance(source, dict) and source.get("type") == "base64" and source.get("data"):
+                                    image_part = {
+                                        "inlineData": {
+                                            "mimeType": source.get("media_type", "image/png"),
+                                            "data": source.get("data")
+                                        }
+                                    }
+                                elif block.get("image_url"):
+                                    image_part = self._build_inline_part_from_image_url(block.get("image_url"))
+                            else:
+                                image_part = self._build_inline_part_from_image_url(block.get("image_url"))
+
+                            if image_part:
+                                parts.append(image_part)
+                                inline_image_count += 1
+                            else:
+                                logger.warning(f"[Gemini] Skip invalid image block: {str(block)[:200]}")
+                            
+                        elif block_type == "tool_use":
+                            # Convert Claude tool_use to Gemini functionCall
+                            fc_name = block.get("name", "unknown")
+                            fc_args = block.get("input") or {}
+                            parts.append({
+                                "functionCall": {
+                                    "name": fc_name,
+                                    "args": fc_args
+                                }
+                            })
+
+                        elif block_type == "tool_result":
+                            # Convert Claude tool_result to Gemini functionResponse
+                            tool_use_id = block.get("tool_use_id")
+                            tool_content = block.get("content", "")
+                            
+                            # Try to parse tool content as JSON
+                            try:
+                                if isinstance(tool_content, str):
+                                    tool_result_data = json.loads(tool_content)
+                                else:
+                                    tool_result_data = tool_content
+                            except Exception:
+                                tool_result_data = {"result": tool_content}
+                            
+                            # Find the tool name from previous messages
+                            tool_name = None
+                            for prev_msg in reversed(messages):
+                                if prev_msg.get("role") == "assistant":
+                                    prev_content = prev_msg.get("content", [])
+                                    if isinstance(prev_content, list):
+                                        for prev_block in prev_content:
+                                            if isinstance(prev_block, dict) and prev_block.get("type") == "tool_use":
+                                                if prev_block.get("id") == tool_use_id:
+                                                    tool_name = prev_block.get("name")
+                                                    break
+                                    if tool_name:
+                                        break
+                            
+                            # Gemini functionResponse format (Gemini 3 requires `id`)
+                            fn_response = {
+                                "name": tool_name or "unknown",
+                                "response": tool_result_data
+                            }
+                            if tool_use_id:
+                                fn_response["id"] = tool_use_id
+                            parts.append({"functionResponse": fn_response})
+                            
+                        elif "text" in block:
+                            # Generic text field
+                            parts.append({"text": block["text"]})
+                
+                if parts:
+                    payload["contents"].append({
+                        "role": gemini_role,
+                        "parts": parts
+                    })
+
+            if inline_image_count > 0:
+                logger.info(f"[Gemini] Multimodal request includes {inline_image_count} image part(s)")
+            
+            # Generation config
+            gen_config = {}
+            if kwargs.get("temperature") is not None:
+                gen_config["temperature"] = kwargs["temperature"]
+
+            if gen_config:
+                payload["generationConfig"] = gen_config
+            
+            # Convert tools to Gemini format (REST API style)
+            if tools:
+                gemini_tools = self._convert_tools_to_gemini_rest_format(tools)
+                if gemini_tools:
+                    payload["tools"] = gemini_tools
+            
+            # Make REST API call
+            base_url = f"{self.api_base}/v1beta"
+            endpoint = f"{base_url}/models/{model_name}:generateContent"
+            if stream:
+                endpoint = f"{base_url}/models/{model_name}:streamGenerateContent?alt=sse"
+            
+            headers = {
+                "x-goog-api-key": self.api_key,
+                "Content-Type": "application/json"
+            }
+            
+            response = requests.post(
+                endpoint,
+                headers=headers,
+                json=payload,
+                stream=stream,
+                timeout=60
+            )
+            
+            # Check HTTP status for stream mode (for non-stream, it's checked in handler)
+            if stream and response.status_code != 200:
+                error_text = response.text
+                logger.error(f"[Gemini] API error ({response.status_code}): {error_text}")
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": f"Gemini API error: {error_text}",
+                        "status_code": response.status_code
+                    }
+                return error_generator()
+            
+            if stream:
+                return self._handle_gemini_rest_stream_response(response, model_name)
+            else:
+                return self._handle_gemini_rest_sync_response(response, model_name)
+                
+        except Exception as e:
+            logger.error(f"[Gemini] call_with_tools error: {e}", exc_info=True)
+            error_msg = str(e)  # Capture error message before creating generator
+            if stream:
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": error_msg,
+                        "status_code": 500
+                    }
+                return error_generator()
+            else:
+                return {
+                    "error": True,
+                    "message": str(e),
+                    "status_code": 500
+                }
+    
+    def _convert_tools_to_gemini_rest_format(self, tools_list):
+        """
+        Convert tools to Gemini REST API format
+        
+        Handles both OpenAI and Claude/Agent formats.
+        Returns: [{"functionDeclarations": [...]}]
+        """
+        function_declarations = []
+        
+        for tool in tools_list:
+            # Extract name, description, and parameters based on format
+            if tool.get("type") == "function":
+                # OpenAI format: {"type": "function", "function": {...}}
+                func = tool.get("function", {})
+                name = func.get("name")
+                description = func.get("description", "")
+                parameters = func.get("parameters", {})
+            else:
+                # Claude/Agent format: {"name": "...", "description": "...", "input_schema": {...}}
+                name = tool.get("name")
+                description = tool.get("description", "")
+                parameters = tool.get("input_schema", {})
+            
+            if not name:
+                logger.warning(f"[Gemini] Skipping tool without name: {tool}")
+                continue
+            
+            function_declarations.append({
+                "name": name,
+                "description": description,
+                "parameters": parameters
+            })
+        
+        # All functionDeclarations must be in a single tools object (per Gemini REST API spec)
+        return [{
+            "functionDeclarations": function_declarations
+        }] if function_declarations else []
+    
+    def _handle_gemini_rest_sync_response(self, response, model_name):
+        """Handle Gemini REST API sync response and convert to OpenAI format"""
+        try:
+            if response.status_code != 200:
+                error_text = response.text
+                logger.error(f"[Gemini] API error ({response.status_code}): {error_text}")
+                return {
+                    "error": True,
+                    "message": f"Gemini API error: {error_text}",
+                    "status_code": response.status_code
+                }
+            
+            data = response.json()
+            logger.debug(f"[Gemini] Response data: {json.dumps(data, ensure_ascii=False)[:500]}")
+            
+            # Extract from Gemini response format
+            candidates = data.get("candidates", [])
+            if not candidates:
+                logger.warning("[Gemini] No candidates in response")
+                prompt_feedback = data.get("promptFeedback", {})
+                return {
+                    "error": True,
+                    "message": "No candidates in response",
+                    "status_code": 500,
+                    "safety_ratings": prompt_feedback.get("safetyRatings", [])
+                }
+            
+            candidate = candidates[0]
+            content = candidate.get("content", {})
+            parts = content.get("parts", [])
+            safety_ratings = candidate.get("safetyRatings", [])
+            
+            logger.debug(f"[Gemini] Candidate parts count: {len(parts)}")
+            
+            # Extract text and function calls
+            text_content = ""
+            tool_calls = []
+            
+            for part in parts:
+                # Check for text
+                if "text" in part:
+                    text_content += part["text"]
+                    logger.debug(f"[Gemini] Text part: {part['text'][:100]}...")
+                
+                # Check for functionCall (per REST API docs)
+                if "functionCall" in part:
+                    fc = part["functionCall"]
+                    fc_id = fc.get("id") or f"call_{int(time.time() * 1000000)}"
+                    logger.info(f"[Gemini] Function call detected: {fc.get('name')} (id={fc_id})")
+                    
+                    tool_calls.append({
+                        "id": fc_id,
+                        "type": "function",
+                        "function": {
+                            "name": fc.get("name"),
+                            "arguments": json.dumps(fc.get("args", {}))
+                        }
+                    })
+            
+            logger.info(f"[Gemini] Response: text={len(text_content)} chars, tool_calls={len(tool_calls)}")
+            
+            # Build OpenAI format response
+            message_dict = {
+                "role": "assistant",
+                "content": text_content or None
+            }
+            if tool_calls:
+                message_dict["tool_calls"] = tool_calls
+            
+            return {
+                "id": f"chatcmpl-{time.time()}",
+                "object": "chat.completion",
+                "created": int(time.time()),
+                "model": model_name,
+                "choices": [{
+                    "index": 0,
+                    "message": message_dict,
+                    "finish_reason": "tool_calls" if tool_calls else "stop"
+                }],
+                "usage": data.get("usageMetadata", {}),
+                "safety_ratings": safety_ratings
+            }
+            
+        except Exception as e:
+            logger.error(f"[Gemini] sync response error: {e}", exc_info=True)
+            return {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+    
+    def _handle_gemini_rest_stream_response(self, response, model_name):
+        """Handle Gemini REST API stream response"""
+        try:
+            all_tool_calls = []
+            all_raw_parts = []  # Preserve all Gemini parts (incl. thoughtSignature) for round-trip
+            has_sent_tool_calls = False
+            has_content = False  # Track if any content was sent
+            chunk_count = 0
+            last_finish_reason = None
+            last_safety_ratings = None
+            raw_chunks = []  # Buffer raw chunks for diagnostics on empty response
+            non_text_part_keys = []  # Track non-text/functionCall part keys (e.g. thoughtSignature)
+            
+            for line in response.iter_lines():
+                if not line:
+                    continue
+                
+                line = line.decode('utf-8')
+                
+                # Skip SSE prefixes
+                if line.startswith('data: '):
+                    line = line[6:]
+                
+                if not line or line == '[DONE]':
+                    continue
+                
+                try:
+                    chunk_data = json.loads(line)
+                    chunk_count += 1
+                    raw_chunks.append(chunk_data)
+                    
+                    candidates = chunk_data.get("candidates", [])
+                    if not candidates:
+                        # Could be a chunk with only usageMetadata / promptFeedback
+                        prompt_feedback = chunk_data.get("promptFeedback")
+                        if prompt_feedback:
+                            logger.warning(f"[Gemini] promptFeedback in chunk: {prompt_feedback}")
+                        else:
+                            logger.debug(f"[Gemini] No candidates in chunk: {chunk_data}")
+                        continue
+                    
+                    candidate = candidates[0]
+                    
+                    # 记录 finish_reason 和 safety_ratings
+                    if "finishReason" in candidate:
+                        last_finish_reason = candidate["finishReason"]
+                    if "safetyRatings" in candidate:
+                        last_safety_ratings = candidate["safetyRatings"]
+                    
+                    content = candidate.get("content", {})
+                    parts = content.get("parts", [])
+                    
+                    if not parts:
+                        logger.debug(f"[Gemini] No parts in candidate content, candidate={candidate}")
+                    
+                    # Stream text content
+                    for part in parts:
+                        # Track unknown part types for diagnostics
+                        if "text" not in part and "functionCall" not in part:
+                            for k in part.keys():
+                                if k not in non_text_part_keys:
+                                    non_text_part_keys.append(k)
+
+                        if "text" in part and part["text"]:
+                            has_content = True
+                            yield {
+                                "id": f"chatcmpl-{time.time()}",
+                                "object": "chat.completion.chunk",
+                                "created": int(time.time()),
+                                "model": model_name,
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {"content": part["text"]},
+                                    "finish_reason": None
+                                }]
+                            }
+                        
+                        # Collect function calls
+                        if "functionCall" in part:
+                            fc = part["functionCall"]
+                            logger.info(f"[Gemini] Function call: {fc.get('name')} (id={fc.get('id')})")
+                            # Prefer Gemini's native id; fall back to generated one
+                            fc_id = fc.get("id") or f"call_{int(time.time() * 1000000)}_{len(all_tool_calls)}"
+                            all_tool_calls.append({
+                                "index": len(all_tool_calls),
+                                "id": fc_id,
+                                "type": "function",
+                                "function": {
+                                    "name": fc.get("name"),
+                                    "arguments": json.dumps(fc.get("args", {}))
+                                }
+                            })
+
+                    # Preserve all raw parts for round-trip (thoughtSignature, etc.)
+                    all_raw_parts.extend(parts)
+                    
+                except json.JSONDecodeError as je:
+                    logger.debug(f"[Gemini] JSON decode error: {je}, line={line[:500]}")
+                    continue
+            
+            # Send tool calls if any were collected
+            if all_tool_calls and not has_sent_tool_calls:
+                delta = {"tool_calls": all_tool_calls}
+                if all_raw_parts:
+                    delta["_gemini_raw_parts"] = all_raw_parts
+                yield {
+                    "id": f"chatcmpl-{time.time()}",
+                    "object": "chat.completion.chunk",
+                    "created": int(time.time()),
+                    "model": model_name,
+                    "choices": [{
+                        "index": 0,
+                        "delta": delta,
+                        "finish_reason": None
+                    }]
+                }
+                has_sent_tool_calls = True
+            elif not has_sent_tool_calls and all_raw_parts:
+                # No tool calls but we have raw parts (e.g. text-only response with
+                # thoughtSignature) — pass them through for round-trip fidelity.
+                yield {
+                    "id": f"chatcmpl-{time.time()}",
+                    "object": "chat.completion.chunk",
+                    "created": int(time.time()),
+                    "model": model_name,
+                    "choices": [{
+                        "index": 0,
+                        "delta": {"_gemini_raw_parts": all_raw_parts},
+                        "finish_reason": None
+                    }]
+                }
+            
+            # 如果返回空响应，dump 完整原始 chunks 以便诊断
+            if not has_content and not all_tool_calls:
+                logger.warning(
+                    f"[Gemini] ⚠️  Empty response detected! "
+                    f"chunks={chunk_count}, finish_reason={last_finish_reason}, "
+                    f"non_text_part_keys={non_text_part_keys}"
+                )
+                if last_safety_ratings:
+                    logger.warning(f"[Gemini] safetyRatings: {last_safety_ratings}")
+                # Dump raw chunks (truncate each to avoid huge logs)
+                try:
+                    for i, ch in enumerate(raw_chunks):
+                        ch_str = json.dumps(ch, ensure_ascii=False)
+                        if len(ch_str) > 2000:
+                            ch_str = ch_str[:2000] + f"...[truncated, total {len(ch_str)} chars]"
+                        logger.warning(f"[Gemini] raw chunk[{i}]: {ch_str}")
+                except Exception as dump_err:
+                    logger.warning(f"[Gemini] Failed to dump raw chunks: {dump_err}")
+            
+            # Final chunk
+            yield {
+                "id": f"chatcmpl-{time.time()}",
+                "object": "chat.completion.chunk",
+                "created": int(time.time()),
+                "model": model_name,
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": "tool_calls" if all_tool_calls else "stop"
+                }]
+            }
+                    
+        except Exception as e:
+            logger.error(f"[Gemini] stream response error: {e}", exc_info=True)
+            error_msg = str(e)
+            yield {
+                "error": True,
+                "message": error_msg,
+                "status_code": 500
+            }
+    
+    def _convert_tools_to_gemini_format(self, openai_tools):
+        """Convert OpenAI tool format to Gemini function declarations"""
+        import google.generativeai as genai
+        
+        gemini_functions = []
+        for tool in openai_tools:
+            if tool.get("type") == "function":
+                func = tool.get("function", {})
+                gemini_functions.append(
+                    genai.protos.FunctionDeclaration(
+                        name=func.get("name"),
+                        description=func.get("description", ""),
+                        parameters=func.get("parameters", {})
+                    )
+                )
+        
+        if gemini_functions:
+            return [genai.protos.Tool(function_declarations=gemini_functions)]
+        return None
+    
+    def _handle_gemini_sync_response(self, model, messages, request_params, model_name):
+        """Handle synchronous Gemini API response"""
+        import json
+        
+        response = model.generate_content(messages, **request_params)
+        
+        # Extract text content and function calls
+        text_content = ""
+        tool_calls = []
+        
+        if response.candidates and response.candidates[0].content:
+            for part in response.candidates[0].content.parts:
+                if hasattr(part, 'text') and part.text:
+                    text_content += part.text
+                elif hasattr(part, 'function_call') and part.function_call:
+                    # Convert Gemini function call to OpenAI format
+                    func_call = part.function_call
+                    tool_calls.append({
+                        "id": f"call_{hash(func_call.name)}",
+                        "type": "function",
+                        "function": {
+                            "name": func_call.name,
+                            "arguments": json.dumps(dict(func_call.args))
+                        }
+                    })
+        
+        # Build message in OpenAI format
+        message = {
+            "role": "assistant",
+            "content": text_content
+        }
+        if tool_calls:
+            message["tool_calls"] = tool_calls
+        
+        # Format response to match OpenAI structure
+        formatted_response = {
+            "id": f"gemini_{int(time.time())}",
+            "object": "chat.completion",
+            "created": int(time.time()),
+            "model": model_name,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": message,
+                    "finish_reason": "stop" if not tool_calls else "tool_calls"
+                }
+            ],
+            "usage": {
+                "prompt_tokens": 0,  # Gemini doesn't provide token counts in the same way
+                "completion_tokens": 0,
+                "total_tokens": 0
+            }
+        }
+        
+        logger.info(f"[Gemini] call_with_tools reply, model={model_name}")
+        return formatted_response
+    
+    def _handle_gemini_stream_response(self, model, messages, request_params, model_name):
+        """Handle streaming Gemini API response"""
+        import json
+        
+        try:
+            response_stream = model.generate_content(messages, stream=True, **request_params)
+            
+            for chunk in response_stream:
+                if chunk.candidates and chunk.candidates[0].content:
+                    for part in chunk.candidates[0].content.parts:
+                        if hasattr(part, 'text') and part.text:
+                            # Text content
+                            yield {
+                                "id": f"gemini_{int(time.time())}",
+                                "object": "chat.completion.chunk",
+                                "created": int(time.time()),
+                                "model": model_name,
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {"content": part.text},
+                                    "finish_reason": None
+                                }]
+                            }
+                        elif hasattr(part, 'function_call') and part.function_call:
+                            # Function call
+                            func_call = part.function_call
+                            yield {
+                                "id": f"gemini_{int(time.time())}",
+                                "object": "chat.completion.chunk",
+                                "created": int(time.time()),
+                                "model": model_name,
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {
+                                        "tool_calls": [{
+                                            "index": 0,
+                                            "id": f"call_{hash(func_call.name)}",
+                                            "type": "function",
+                                            "function": {
+                                                "name": func_call.name,
+                                                "arguments": json.dumps(dict(func_call.args))
+                                            }
+                                        }]
+                                    },
+                                    "finish_reason": None
+                                }]
+                            }
+                            
+        except Exception as e:
+            logger.error(f"[Gemini] stream response error: {e}")
+            yield {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
diff --git a/models/linkai/link_ai_bot.py b/models/linkai/link_ai_bot.py
new file mode 100644
index 0000000..2e47068
--- /dev/null
+++ b/models/linkai/link_ai_bot.py
@@ -0,0 +1,760 @@
+# access LinkAI knowledge base platform
+# docs: https://link-ai.tech/platform/link-app/wechat
+
+import re
+import time
+import requests
+import json
+import config
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.chatgpt.chat_gpt_session import ChatGPTSession
+from models.session_manager import SessionManager
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, pconf
+import threading
+from common import memory, utils
+import base64
+import os
+
+class LinkAIBot(Bot, OpenAICompatibleBot):
+    # authentication failed
+    AUTH_FAILED_CODE = 401
+    NO_QUOTA_CODE = 406
+
+    def __init__(self):
+        super().__init__()
+        self.sessions = LinkAISessionManager(LinkAISession, model=conf().get("model") or "gpt-3.5-turbo")
+        self.args = {}
+    
+    def get_api_config(self):
+        """Get API configuration for OpenAI-compatible base class"""
+        return {
+            'api_key': conf().get("open_ai_api_key"),  # LinkAI uses OpenAI-compatible key
+            'api_base': conf().get("open_ai_api_base", "https://api.link-ai.tech/v1"),
+            'model': conf().get("model", "gpt-3.5-turbo"),
+            'default_temperature': conf().get("temperature", 0.9),
+            'default_top_p': conf().get("top_p", 1.0),
+            'default_frequency_penalty': conf().get("frequency_penalty", 0.0),
+            'default_presence_penalty': conf().get("presence_penalty", 0.0),
+        }
+
+    def reply(self, query, context: Context = None) -> Reply:
+        if context.type == ContextType.TEXT:
+            return self._chat(query, context)
+        elif context.type == ContextType.IMAGE_CREATE:
+            if not conf().get("text_to_image"):
+                logger.warn("[LinkAI] text_to_image is not enabled, ignore the IMAGE_CREATE request")
+                return Reply(ReplyType.TEXT, "")
+            ok, res = self.create_img(query, 0)
+            if ok:
+                reply = Reply(ReplyType.IMAGE_URL, res)
+            else:
+                reply = Reply(ReplyType.ERROR, res)
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def _chat(self, query, context, retry_count=0) -> Reply:
+        """
+        发起对话请求
+        :param query: 请求提示词
+        :param context: 对话上下文
+        :param retry_count: 当前递归重试次数
+        :return: 回复
+        """
+        if retry_count > 2:
+            # exit from retry 2 times
+            logger.warn("[LINKAI] failed after maximum number of retry times")
+            return Reply(ReplyType.TEXT, "请再问我一次吧")
+
+        try:
+            # load config
+            if context.get("generate_breaked_by"):
+                logger.info(f"[LINKAI] won't set appcode because a plugin ({context['generate_breaked_by']}) affected the context")
+                app_code = None
+            else:
+                plugin_app_code = self._find_group_mapping_code(context)
+                app_code = context.kwargs.get("app_code") or plugin_app_code or conf().get("linkai_app_code")
+            linkai_api_key = conf().get("linkai_api_key")
+
+            session_id = context["session_id"]
+            session_message = self.sessions.session_msg_query(query, session_id)
+            logger.debug(f"[LinkAI] session={session_message}, session_id={session_id}")
+
+            # image process
+            img_cache = memory.USER_IMAGE_CACHE.get(session_id)
+            if img_cache:
+                messages = self._process_image_msg(app_code=app_code, session_id=session_id, query=query, img_cache=img_cache)
+                if messages:
+                    session_message = messages
+
+            model = conf().get("model")
+            # remove system message
+            if session_message[0].get("role") == "system":
+                if app_code or model == "wenxin":
+                    session_message.pop(0)
+            body = {
+                "app_code": app_code,
+                "messages": session_message,
+                "model": model,     # 对话模型的名称, 支持 gpt-3.5-turbo, gpt-3.5-turbo-16k, gpt-4, wenxin, xunfei
+                "temperature": conf().get("temperature"),
+                "top_p": conf().get("top_p", 1),
+                "frequency_penalty": conf().get("frequency_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                "presence_penalty": conf().get("presence_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                "session_id": session_id,
+                "sender_id": session_id,
+                "channel_type": context.get("channel_type") or conf().get("channel_type", "web")
+            }
+            try:
+                from linkai import LinkAIClient
+                client_id = LinkAIClient.fetch_client_id()
+                if client_id:
+                    body["client_id"] = client_id
+                    # start: client info deliver
+                    if context.kwargs.get("msg"):
+                        body["session_id"] = context.kwargs.get("msg").from_user_id
+                        if context.kwargs.get("msg").is_group:
+                            body["is_group"] = True
+                            body["group_name"] = context.kwargs.get("msg").from_user_nickname
+                            body["sender_name"] = context.kwargs.get("msg").actual_user_nickname
+                        else:
+                            if body.get("channel_type") in ["wechatcom_app"]:
+                                body["sender_name"] = context.kwargs.get("msg").from_user_id
+                            else:
+                                body["sender_name"] = context.kwargs.get("msg").from_user_nickname
+
+            except Exception as e:
+                pass
+            file_id = context.kwargs.get("file_id")
+            if file_id:
+                body["file_id"] = file_id
+            logger.info(f"[LINKAI] query={query}, app_code={app_code}, model={body.get('model')}, file_id={file_id}")
+            headers = {"Authorization": "Bearer " + linkai_api_key, "X-Title": "CowAgent"}
+
+            # do http request
+            base_url = conf().get("linkai_api_base", "https://api.link-ai.tech")
+            res = requests.post(url=base_url + "/v1/chat/completions", json=body, headers=headers,
+                                timeout=conf().get("request_timeout", 180))
+            if res.status_code == 200:
+                # execute success
+                response = res.json()
+                reply_content = response["choices"][0]["message"]["content"]
+                total_tokens = response["usage"]["total_tokens"]
+                res_code = response.get('code')
+                logger.info(f"[LINKAI] reply={reply_content}, total_tokens={total_tokens}, res_code={res_code}")
+                if res_code == 429:
+                    logger.warn(f"[LINKAI] 用户访问超出限流配置，sender_id={body.get('sender_id')}")
+                else:
+                    self.sessions.session_reply(reply_content, session_id, total_tokens, query=query)
+                agent_suffix = self._fetch_agent_suffix(response)
+                if agent_suffix:
+                    reply_content += agent_suffix
+                if not agent_suffix:
+                    knowledge_suffix = self._fetch_knowledge_search_suffix(response)
+                    if knowledge_suffix:
+                        reply_content += knowledge_suffix
+                # image process
+                if response["choices"][0].get("img_urls"):
+                    thread = threading.Thread(target=self._send_image, args=(context.get("channel"), context, response["choices"][0].get("img_urls")))
+                    thread.start()
+                    reply_content = response["choices"][0].get("text_content")
+                if reply_content:
+                    reply_content = self._process_url(reply_content)
+                return Reply(ReplyType.TEXT, reply_content)
+
+            else:
+                response = res.json()
+                error = response.get("error")
+                logger.error(f"[LINKAI] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                if res.status_code >= 500:
+                    # server error, need retry
+                    time.sleep(2)
+                    logger.warn(f"[LINKAI] do retry, times={retry_count}")
+                    return self._chat(query, context, retry_count + 1)
+
+                error_reply = "提问太快啦，请休息一下再问我吧"
+                if res.status_code == 409:
+                    error_reply = "这个问题我还没有学会，请问我其它问题吧"
+                return Reply(ReplyType.TEXT, error_reply)
+
+        except Exception as e:
+            logger.exception(e)
+            # retry
+            time.sleep(2)
+            logger.warn(f"[LINKAI] do retry, times={retry_count}")
+            return self._chat(query, context, retry_count + 1)
+
+    def _process_image_msg(self, app_code: str, session_id: str, query:str, img_cache: dict):
+        try:
+            enable_image_input = False
+            app_info = self._fetch_app_info(app_code)
+            if not app_info:
+                logger.debug(f"[LinkAI] not found app, can't process images, app_code={app_code}")
+                return None
+            plugins = app_info.get("data").get("plugins")
+            for plugin in plugins:
+                if plugin.get("input_type") and "IMAGE" in plugin.get("input_type"):
+                    enable_image_input = True
+            if not enable_image_input:
+                return
+            msg = img_cache.get("msg")
+            path = img_cache.get("path")
+            msg.prepare()
+            logger.info(f"[LinkAI] query with images, path={path}")
+            messages = self._build_vision_msg(query, path)
+            memory.USER_IMAGE_CACHE[session_id] = None
+            return messages
+        except Exception as e:
+            logger.exception(e)
+
+    def _find_group_mapping_code(self, context):
+        try:
+            if context.kwargs.get("isgroup"):
+                group_name = context.kwargs.get("msg").from_user_nickname
+                if config.plugin_config and config.plugin_config.get("linkai"):
+                    linkai_config = config.plugin_config.get("linkai")
+                    group_mapping = linkai_config.get("group_app_map")
+                    if group_mapping and group_name:
+                        return group_mapping.get(group_name)
+        except Exception as e:
+            logger.exception(e)
+            return None
+
+    def _build_vision_msg(self, query: str, path: str):
+        try:
+            suffix = utils.get_path_suffix(path)
+            with open(path, "rb") as file:
+                base64_str = base64.b64encode(file.read()).decode('utf-8')
+                messages = [{
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "text",
+                            "text": query
+                        },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": f"data:image/{suffix};base64,{base64_str}"
+                            }
+                        }
+                    ]
+                }]
+                return messages
+        except Exception as e:
+            logger.exception(e)
+
+    def reply_text(self, session: ChatGPTSession, app_code="", retry_count=0) -> dict:
+        if retry_count >= 2:
+            # exit from retry 2 times
+            logger.warn("[LINKAI] failed after maximum number of retry times")
+            return {
+                "total_tokens": 0,
+                "completion_tokens": 0,
+                "content": "请再问我一次吧"
+            }
+
+        try:
+            body = {
+                "app_code": app_code,
+                "messages": session.messages,
+                "model": conf().get("model") or "gpt-3.5-turbo",  # 对话模型的名称, 支持 gpt-3.5-turbo, gpt-3.5-turbo-16k, gpt-4, wenxin, xunfei
+                "temperature": conf().get("temperature"),
+                "top_p": conf().get("top_p", 1),
+                "frequency_penalty": conf().get("frequency_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                "presence_penalty": conf().get("presence_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            }
+            if self.args.get("max_tokens"):
+                body["max_tokens"] = self.args.get("max_tokens")
+            headers = {"Authorization": "Bearer " + conf().get("linkai_api_key"), "X-Title": "CowAgent"}
+
+            # do http request
+            base_url = conf().get("linkai_api_base", "https://api.link-ai.tech")
+            res = requests.post(url=base_url + "/v1/chat/completions", json=body, headers=headers,
+                                timeout=conf().get("request_timeout", 180))
+            if res.status_code == 200:
+                # execute success
+                response = res.json()
+                reply_content = response["choices"][0]["message"]["content"]
+                total_tokens = response["usage"]["total_tokens"]
+                logger.info(f"[LINKAI] reply={reply_content}, total_tokens={total_tokens}")
+                return {
+                    "total_tokens": total_tokens,
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": reply_content,
+                }
+
+            else:
+                response = res.json()
+                error = response.get("error")
+                logger.error(f"[LINKAI] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                if res.status_code >= 500:
+                    # server error, need retry
+                    time.sleep(2)
+                    logger.warn(f"[LINKAI] do retry, times={retry_count}")
+                    return self.reply_text(session, app_code, retry_count + 1)
+
+                return {
+                    "total_tokens": 0,
+                    "completion_tokens": 0,
+                    "content": "提问太快啦，请休息一下再问我吧"
+                }
+
+        except Exception as e:
+            logger.exception(e)
+            # retry
+            time.sleep(2)
+            logger.warn(f"[LINKAI] do retry, times={retry_count}")
+            return self.reply_text(session, app_code, retry_count + 1)
+
+    def _fetch_app_info(self, app_code: str):
+        headers = {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+        # do http request
+        base_url = conf().get("linkai_api_base", "https://api.link-ai.tech")
+        params = {"app_code": app_code}
+        res = requests.get(url=base_url + "/v1/app/info", params=params, headers=headers, timeout=(5, 10))
+        if res.status_code == 200:
+            return res.json()
+        else:
+            logger.warning(f"[LinkAI] find app info exception, res={res}")
+
+    def create_img(self, query, retry_count=0, api_key=None):
+        try:
+            logger.info("[LinkImage] image_query={}".format(query))
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {conf().get('linkai_api_key')}"
+            }
+            data = {
+                "prompt": query,
+                "n": 1,
+                "model": conf().get("text_to_image") or "dall-e-2",
+                "response_format": "url",
+                "img_proxy": conf().get("image_proxy")
+            }
+            url = conf().get("linkai_api_base", "https://api.link-ai.tech") + "/v1/images/generations"
+            res = requests.post(url, headers=headers, json=data, timeout=(5, 90))
+            t2 = time.time()
+            image_url = res.json()["data"][0]["url"]
+            logger.info("[OPEN_AI] image_url={}".format(image_url))
+            return True, image_url
+
+        except Exception as e:
+            logger.error(format(e))
+            return False, "画图出现问题，请休息一下再问我吧"
+
+
+    def _fetch_knowledge_search_suffix(self, response) -> str:
+        try:
+            if response.get("knowledge_base"):
+                search_hit = response.get("knowledge_base").get("search_hit")
+                first_similarity = response.get("knowledge_base").get("first_similarity")
+                logger.info(f"[LINKAI] knowledge base, search_hit={search_hit}, first_similarity={first_similarity}")
+                plugin_config = pconf("linkai")
+                if plugin_config and plugin_config.get("knowledge_base") and plugin_config.get("knowledge_base").get("search_miss_text_enabled"):
+                    search_miss_similarity = plugin_config.get("knowledge_base").get("search_miss_similarity")
+                    search_miss_text = plugin_config.get("knowledge_base").get("search_miss_suffix")
+                    if not search_hit:
+                        return search_miss_text
+                    if search_miss_similarity and float(search_miss_similarity) > first_similarity:
+                        return search_miss_text
+        except Exception as e:
+            logger.exception(e)
+
+
+    def _fetch_agent_suffix(self, response):
+        try:
+            plugin_list = []
+            logger.debug(f"[LinkAgent] res={response}")
+            if response.get("agent") and response.get("agent").get("chain") and response.get("agent").get("need_show_plugin"):
+                chain = response.get("agent").get("chain")
+                suffix = "\n\n- - - - - - - - - - - -"
+                i = 0
+                for turn in chain:
+                    plugin_name = turn.get('plugin_name')
+                    suffix += "\n"
+                    need_show_thought = response.get("agent").get("need_show_thought")
+                    if turn.get("thought") and plugin_name and need_show_thought:
+                        suffix += f"{turn.get('thought')}\n"
+                    if plugin_name:
+                        plugin_list.append(turn.get('plugin_name'))
+                        if turn.get('plugin_icon'):
+                            suffix += f"{turn.get('plugin_icon')} "
+                        suffix += f"{turn.get('plugin_name')}"
+                        if turn.get('plugin_input'):
+                            suffix += f"：{turn.get('plugin_input')}"
+                    if i < len(chain) - 1:
+                        suffix += "\n"
+                    i += 1
+                logger.info(f"[LinkAgent] use plugins: {plugin_list}")
+                return suffix
+        except Exception as e:
+            logger.exception(e)
+
+    def _process_url(self, text):
+        try:
+            url_pattern = re.compile(r'\[(.*?)\]\((http[s]?://.*?)\)')
+            def replace_markdown_url(match):
+                return f"{match.group(2)}"
+            return url_pattern.sub(replace_markdown_url, text)
+        except Exception as e:
+            logger.error(e)
+
+    def _send_image(self, channel, context, image_urls):
+        if not image_urls:
+            return
+        max_send_num = conf().get("max_media_send_count")
+        send_interval = conf().get("media_send_interval")
+        file_type = (".pdf", ".doc", ".docx", ".csv", ".xls", ".xlsx", ".txt", ".rtf", ".ppt", ".pptx")
+        try:
+            i = 0
+            for url in image_urls:
+                if max_send_num and i >= max_send_num:
+                    continue
+                i += 1
+                if url.endswith(".mp4"):
+                    reply_type = ReplyType.VIDEO_URL
+                elif url.endswith(file_type):
+                    reply_type = ReplyType.FILE
+                    url = _download_file(url)
+                    if not url:
+                        continue
+                else:
+                    reply_type = ReplyType.IMAGE_URL
+                reply = Reply(reply_type, url)
+                channel.send(reply, context)
+                if send_interval:
+                    time.sleep(send_interval)
+        except Exception as e:
+            logger.error(e)
+
+
+def _download_file(url: str):
+    try:
+        file_path = "tmp"
+        if not os.path.exists(file_path):
+            os.makedirs(file_path)
+        file_name = url.split("/")[-1]  # 获取文件名
+        file_path = os.path.join(file_path, file_name)
+        response = requests.get(url)
+        with open(file_path, "wb") as f:
+            f.write(response.content)
+        return file_path
+    except Exception as e:
+        logger.warn(e)
+
+
+class LinkAISessionManager(SessionManager):
+    def session_msg_query(self, query, session_id):
+        session = self.build_session(session_id)
+        messages = session.messages + [{"role": "user", "content": query}]
+        return messages
+
+    def session_reply(self, reply, session_id, total_tokens=None, query=None):
+        session = self.build_session(session_id)
+        if query:
+            session.add_query(query)
+        session.add_reply(reply)
+        try:
+            max_tokens = conf().get("conversation_max_tokens", 8000)
+            tokens_cnt = session.discard_exceeding(max_tokens, total_tokens)
+            logger.debug(f"[LinkAI] chat history, before tokens={total_tokens}, now tokens={tokens_cnt}")
+        except Exception as e:
+            logger.warning("Exception when counting tokens precisely for session: {}".format(str(e)))
+        return session
+
+
+class LinkAISession(ChatGPTSession):
+    def calc_tokens(self):
+        if not self.messages:
+            return 0
+        return len(str(self.messages))
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        cur_tokens = self.calc_tokens()
+        if cur_tokens > max_tokens:
+            for i in range(0, len(self.messages)):
+                if i > 0 and self.messages[i].get("role") == "assistant" and self.messages[i - 1].get("role") == "user":
+                    self.messages.pop(i)
+                    self.messages.pop(i - 1)
+                    return self.calc_tokens()
+        return cur_tokens
+
+
+# Add call_with_tools method to LinkAIBot class
+def _linkai_call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+    """
+    Call LinkAI API with tool support for agent integration
+    LinkAI is fully compatible with OpenAI's tool calling format
+    
+    Args:
+        messages: List of messages
+        tools: List of tool definitions (OpenAI format)
+        stream: Whether to use streaming
+        **kwargs: Additional parameters (max_tokens, temperature, etc.)
+        
+    Returns:
+        Formatted response in OpenAI format or generator for streaming
+    """
+    try:
+        # Convert messages from Claude format to OpenAI format
+        # This is important because Agent uses Claude format internally
+        messages = self._convert_messages_to_openai_format(messages)
+        
+        # Convert tools from Claude format to OpenAI format
+        if tools:
+            tools = self._convert_tools_to_openai_format(tools)
+        
+        # Handle system prompt (OpenAI uses system message, Claude uses separate parameter)
+        system_prompt = kwargs.get('system')
+        if system_prompt:
+            # Add system message at the beginning if not already present
+            if not messages or messages[0].get('role') != 'system':
+                messages = [{"role": "system", "content": system_prompt}] + messages
+            else:
+                # Replace existing system message
+                messages[0] = {"role": "system", "content": system_prompt}
+        
+        logger.debug(f"[LinkAI] messages: {len(messages)}, tools: {len(tools) if tools else 0}, stream: {stream}")
+        
+        # Build request parameters (LinkAI uses OpenAI-compatible format)
+        raw_ct = conf().get("channel_type", "web")
+        if isinstance(raw_ct, list):
+            channel_type = raw_ct[0] if raw_ct else "web"
+        elif isinstance(raw_ct, str) and "," in raw_ct:
+            channel_type = raw_ct.split(",")[0].strip()
+        else:
+            channel_type = raw_ct
+
+        session_id = kwargs.get("session_id", "")
+        body = {
+            "messages": messages,
+            "model": kwargs.get("model", conf().get("model") or "gpt-3.5-turbo"),
+            "temperature": kwargs.get("temperature", conf().get("temperature", 0.9)),
+            "top_p": kwargs.get("top_p", conf().get("top_p", 1)),
+            "frequency_penalty": kwargs.get("frequency_penalty", conf().get("frequency_penalty", 0.0)),
+            "presence_penalty": kwargs.get("presence_penalty", conf().get("presence_penalty", 0.0)),
+            "stream": stream,
+            "channel_type": kwargs.get("channel_type", channel_type),
+            "session_id": session_id,
+            "sender_id": session_id,
+        }
+
+        try:
+            from linkai import LinkAIClient
+            client_id = LinkAIClient.fetch_client_id()
+            if client_id:
+                body["client_id"] = client_id
+        except Exception:
+            pass
+
+        if tools:
+            body["tools"] = tools
+            body["tool_choice"] = kwargs.get("tool_choice", "auto")
+
+        thinking = kwargs.get("thinking")
+        if thinking:
+            body["thinking"] = thinking
+
+        # Prepare headers
+        headers = {"Authorization": "Bearer " + conf().get("linkai_api_key"), "X-Title": "CowAgent"}
+        base_url = conf().get("linkai_api_base", "https://api.link-ai.tech")
+        
+        if stream:
+            return self._handle_linkai_stream_response(base_url, headers, body)
+        else:
+            return self._handle_linkai_sync_response(base_url, headers, body)
+            
+    except Exception as e:
+        logger.error(f"[LinkAI] call_with_tools error: {e}")
+        if stream:
+            def error_generator():
+                yield {
+                    "error": True,
+                    "message": str(e),
+                    "status_code": 500
+                }
+            return error_generator()
+        else:
+            return {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+
+def _handle_linkai_sync_response(self, base_url, headers, body):
+    """Handle synchronous LinkAI API response"""
+    try:
+        res = requests.post(
+            url=base_url + "/v1/chat/completions",
+            json=body,
+            headers=headers,
+            timeout=conf().get("request_timeout", 180)
+        )
+        
+        if res.status_code == 200:
+            response = res.json()
+            logger.debug(f"[LinkAI] reply: model={response.get('model')}, "
+                        f"tokens={response.get('usage', {}).get('total_tokens', 0)}")
+            
+            # LinkAI response is already in OpenAI-compatible format
+            return response
+        else:
+            error_data = res.json()
+            error_msg = error_data.get("error", {}).get("message", "Unknown error")
+            raise Exception(f"LinkAI API error: {res.status_code} - {error_msg}")
+            
+    except Exception as e:
+        logger.error(f"[LinkAI] sync response error: {e}")
+        raise
+
+def _handle_linkai_stream_response(self, base_url, headers, body):
+    """Handle streaming LinkAI API response"""
+    try:
+        res = requests.post(
+            url=base_url + "/v1/chat/completions",
+            json=body,
+            headers=headers,
+            timeout=conf().get("request_timeout", 180),
+            stream=True
+        )
+        
+        if res.status_code != 200:
+            error_text = res.text
+            try:
+                error_data = json.loads(error_text)
+                error_msg = error_data.get("error", {}).get("message", error_text)
+            except Exception:
+                error_msg = error_text or "Unknown error"
+            
+            yield {
+                "error": True,
+                "status_code": res.status_code,
+                "message": error_msg
+            }
+            return
+        
+        # Process streaming response (OpenAI-compatible SSE format)
+        for line in res.iter_lines():
+            if line:
+                line = line.decode('utf-8')
+                if line.startswith('data: '):
+                    line = line[6:]  # Remove 'data: ' prefix
+                    if line == '[DONE]':
+                        break
+                    try:
+                        chunk = json.loads(line)
+                    except json.JSONDecodeError:
+                        continue
+
+                    # Check for error responses within the stream
+                    # Some providers (e.g., MiniMax via LinkAI) return errors as:
+                    # {'type': 'error', 'error': {'type': '...', 'message': '...', 'http_code': '400'}}
+                    if chunk.get("type") == "error" or (
+                        isinstance(chunk.get("error"), dict) and "message" in chunk.get("error", {})
+                    ):
+                        error_data = chunk.get("error", {})
+                        error_msg = error_data.get("message", "Unknown error") if isinstance(error_data, dict) else str(error_data)
+                        http_code = error_data.get("http_code", "") if isinstance(error_data, dict) else ""
+                        status_code = int(http_code) if http_code and str(http_code).isdigit() else 400
+                        logger.error(f"[LinkAI] stream error: {error_msg} (http_code={http_code})")
+                        yield {
+                            "error": True,
+                            "message": error_msg,
+                            "status_code": status_code
+                        }
+                        return
+
+                    # Forward SSE JSON as-is so extensions (e.g. delta._gemini_raw_parts
+                    # for Gemini via LinkAI) reach agent_stream and are stored on assistant
+                    # messages for the next request. Standard OpenAI fields are unchanged.
+                    yield chunk
+                        
+    except Exception as e:
+        logger.error(f"[LinkAI] stream response error: {e}")
+        yield {
+            "error": True,
+            "message": str(e),
+            "status_code": 500
+        }
+
+def _linkai_convert_messages_to_openai_format(self, messages):
+    """
+    Override the base OpenAI-compatible conversion to round-trip
+    ``reasoning_content`` on assistant messages.
+
+    Internally, the agent layer keeps the model's reasoning trace as a
+    Claude-style ``thinking`` content block on the assistant message. The
+    base converter drops that block. For thinking-capable models proxied via
+    LinkAI (DeepSeek V4, Kimi K2 thinking, …), the upstream API requires
+    the trace to be echoed back as a top-level ``reasoning_content`` field
+    on every assistant turn that contained tool calls — otherwise the next
+    request returns 400. We re-emit it for every assistant turn (it's
+    silently ignored on plain text turns).
+    """
+    openai_messages = OpenAICompatibleBot._convert_messages_to_openai_format(self, messages)
+    if not messages:
+        return openai_messages
+
+    # DeepSeek (proxied via LinkAI) requires `reasoning_content` on EVERY
+    # assistant message once the history contains any tool-call turn — not
+    # just the tool-call turn itself. Detect that condition first.
+    has_tool_call_history = False
+    for src in messages:
+        if src.get("role") != "assistant":
+            continue
+        if src.get("tool_calls"):
+            has_tool_call_history = True
+            break
+        content = src.get("content")
+        if isinstance(content, list) and any(
+            isinstance(b, dict) and b.get("type") == "tool_use" for b in content
+        ):
+            has_tool_call_history = True
+            break
+
+    # Walk the original Claude messages to collect each assistant turn's
+    # reasoning text, then attach it to the matching converted entry.
+    dst_idx = 0
+    for src in messages:
+        if src.get("role") != "assistant":
+            continue
+        content = src.get("content")
+        reasoning_parts = []
+        if isinstance(content, list):
+            reasoning_parts = [
+                b.get("thinking", "") for b in content
+                if isinstance(b, dict) and b.get("type") == "thinking"
+            ]
+        # Locate the corresponding assistant entry in the converted list.
+        while dst_idx < len(openai_messages) and openai_messages[dst_idx].get("role") != "assistant":
+            dst_idx += 1
+        if dst_idx >= len(openai_messages):
+            break
+        dst_msg = openai_messages[dst_idx]
+        if reasoning_parts:
+            dst_msg["reasoning_content"] = "\n".join(reasoning_parts)
+        elif has_tool_call_history:
+            # Fallback when the trace was lost (proxy stripped it, model
+            # switched mid-session, thinking toggled on after tool calls).
+            # DeepSeek-style backends validate field presence, not value;
+            # non-thinking backends silently ignore the empty string.
+            dst_msg["reasoning_content"] = ""
+        dst_idx += 1
+
+    return openai_messages
+
+
+# Attach methods to LinkAIBot class
+LinkAIBot.call_with_tools = _linkai_call_with_tools
+LinkAIBot._handle_linkai_sync_response = _handle_linkai_sync_response
+LinkAIBot._handle_linkai_stream_response = _handle_linkai_stream_response
+LinkAIBot._convert_messages_to_openai_format = _linkai_convert_messages_to_openai_format
diff --git a/models/mimo/__init__.py b/models/mimo/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/models/mimo/mimo_bot.py b/models/mimo/mimo_bot.py
new file mode 100644
index 0000000..762003f
--- /dev/null
+++ b/models/mimo/mimo_bot.py
@@ -0,0 +1,668 @@
+# encoding:utf-8
+
+"""
+小米 MiMo Bot —— OpenAI 兼容协议，使用独立 API key / base 配置。
+
+支持模型：
+- mimo-v2.5-pro     (旗舰，长上下文，默认开启思考)
+- mimo-v2.5         (多模态：文/图/音/视频，默认开启思考)
+- mimo-v2-pro       (V2 Pro，默认开启思考)
+- mimo-v2-omni      (V2 多模态，默认开启思考)
+- mimo-v2-flash     (V2 极速版，默认关闭思考)
+
+思考模式说明：
+- 开关参数：``{"thinking": {"type": "enabled" | "disabled"}}``
+- mimo-v2.5-pro / mimo-v2.5 在思考模式下 ``temperature`` 会被强制为 1.0，
+  本地直接剥离 ``temperature`` / ``top_p`` 等参数避免歧义。
+- 多轮工具调用过程中，若历史包含 tool_calls，所有后续 assistant 消息必须回传
+  ``reasoning_content``，否则 API 返回 400 错误。
+- 文档：https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/passing-back-reasoning_content
+"""
+
+import json
+import time
+from typing import Optional
+
+import requests
+
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf, load_config
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.session_manager import SessionManager
+from .mimo_session import MimoSession
+
+DEFAULT_API_BASE = "https://api.xiaomimimo.com/v1"
+DEFAULT_MODEL = const.MIMO_V2_5_PRO
+
+# 支持多模态输入（图/音/视频）的模型
+MULTIMODAL_MODELS = {const.MIMO_V2_5_PRO, const.MIMO_V2_5, const.MIMO_V2_OMNI}
+
+
+class MimoBot(Bot, OpenAICompatibleBot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(
+            MimoSession,
+            model=conf().get("model") or DEFAULT_MODEL,
+        )
+        conf_model = conf().get("model") or DEFAULT_MODEL
+        self.args = {
+            "model": conf_model,
+            "temperature": conf().get("temperature", 1.0),
+            "top_p": conf().get("top_p", 0.95),
+        }
+
+    # ---------- config helpers ----------
+
+    @property
+    def api_key(self):
+        return conf().get("mimo_api_key")
+
+    @property
+    def api_base(self):
+        url = conf().get("mimo_api_base") or DEFAULT_API_BASE
+        return url.rstrip("/")
+
+    def get_api_config(self):
+        """OpenAICompatibleBot 接口 —— 供 call_with_tools() 使用。"""
+        return {
+            "api_key": self.api_key,
+            "api_base": self.api_base,
+            "model": conf().get("model", DEFAULT_MODEL),
+            "default_temperature": conf().get("temperature", 1.0),
+            "default_top_p": conf().get("top_p", 0.95),
+        }
+
+    @property
+    def supports_vision(self) -> bool:
+        """主模型为多模态模型时，允许 vision tool 走主 bot 通道。"""
+        model_name = (conf().get("model") or "").lower()
+        return model_name in MULTIMODAL_MODELS
+
+    @staticmethod
+    def _model_supports_thinking(model_name: str) -> bool:
+        """全部 mimo 系列模型都支持 thinking 开关。"""
+        if not model_name:
+            return False
+        return model_name.lower().startswith("mimo-")
+
+    @staticmethod
+    def _thinking_default_enabled(model_name: str) -> bool:
+        """各模型的思考模式默认值。mimo-v2-flash 默认关闭，其他默认开启。"""
+        if not model_name:
+            return False
+        return model_name.lower() != const.MIMO_V2_FLASH
+
+    def _build_headers(self) -> dict:
+        return {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+    # ---------- simple chat (non-agent mode) ----------
+
+    def reply(self, query, context=None):
+        if context.type == ContextType.TEXT:
+            logger.info("[MIMO] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[MIMO] session query={}".format(session.messages))
+
+            new_args = self.args.copy()
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[MIMO] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages, session_id,
+                    reply_content["content"], reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(
+                    reply_content["content"], session_id, reply_content["total_tokens"],
+                )
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[MIMO] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session, args=None, retry_count: int = 0) -> dict:
+        try:
+            headers = self._build_headers()
+            body = dict(args) if args else dict(self.args)
+            body["messages"] = session.messages
+
+            model_name = str(body.get("model", ""))
+            # 思考模式下 mimo-v2.5-pro / mimo-v2.5 不支持自定义 temperature/top_p,
+            # 简单起见，所有支持思考的模型按默认配置走，剥离这些参数。
+            if self._model_supports_thinking(model_name) and self._thinking_default_enabled(model_name):
+                for k in ("temperature", "top_p", "presence_penalty", "frequency_penalty"):
+                    body.pop(k, None)
+
+            res = requests.post(
+                f"{self.api_base}/chat/completions",
+                headers=headers,
+                json=body,
+                timeout=180,
+            )
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"],
+                }
+            else:
+                try:
+                    response = res.json()
+                    error = response.get("error", {})
+                except Exception:
+                    error = {"message": res.text[:300]}
+                logger.error(
+                    f"[MIMO] chat failed, status_code={res.status_code}, "
+                    f"msg={error.get('message')}, type={error.get('type')}"
+                )
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                return result
+        except Exception as e:
+            logger.exception(e)
+            if retry_count < 2:
+                return self.reply_text(session, args, retry_count + 1)
+            return {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+
+    # ==================== Agent mode support ====================
+
+    def call_with_tools(self, messages, tools=None, stream: bool = False, **kwargs):
+        """
+        带工具调用支持的 MiMo API 调用 (供 agent 集成使用)。
+
+        处理逻辑：
+        - Claude 格式 → OpenAI 格式 转换（含 reasoning_content 全量回传）
+        - System prompt 注入
+        - SSE 流式响应（包含 tool_calls 与 reasoning_content 增量）
+        - 思考模式开关传递
+        """
+        try:
+            converted_messages = self._convert_messages_to_openai_format(messages)
+
+            system_prompt = kwargs.pop("system", None)
+            if system_prompt:
+                if not converted_messages or converted_messages[0].get("role") != "system":
+                    converted_messages.insert(0, {"role": "system", "content": system_prompt})
+                else:
+                    converted_messages[0] = {"role": "system", "content": system_prompt}
+
+            converted_tools = None
+            if tools:
+                converted_tools = self._convert_tools_to_openai_format(tools)
+
+            model = kwargs.pop("model", None) or self.args["model"]
+            max_tokens = kwargs.pop("max_tokens", None)
+
+            request_body = {
+                "model": model,
+                "messages": converted_messages,
+                "stream": stream,
+            }
+            if max_tokens is not None:
+                # MiMo 使用 max_completion_tokens 命名（含可见输出 + 推理 token）
+                request_body["max_completion_tokens"] = max_tokens
+
+            if converted_tools:
+                request_body["tools"] = converted_tools
+                request_body["tool_choice"] = kwargs.pop("tool_choice", "auto")
+
+            # 思考模式：默认遵循各模型的官方默认值；caller 可显式覆盖
+            thinking_param = kwargs.pop("thinking", None)
+            thinking_active = False
+
+            if self._model_supports_thinking(model):
+                if thinking_param is None:
+                    default_on = self._thinking_default_enabled(model)
+                    thinking_param = {"type": "enabled" if default_on else "disabled"}
+                request_body["thinking"] = thinking_param
+                thinking_active = thinking_param.get("type") == "enabled"
+
+            # 思考模式下 v2.5-pro / v2.5 不支持自定义 temperature；干脆全部剥离避免被静默忽略
+            if thinking_active:
+                for k in ("temperature", "top_p", "presence_penalty", "frequency_penalty"):
+                    request_body.pop(k, None)
+                    kwargs.pop(k, None)
+            else:
+                temperature = kwargs.pop("temperature", None)
+                if temperature is not None:
+                    request_body["temperature"] = temperature
+                top_p = kwargs.pop("top_p", None)
+                if top_p is not None:
+                    request_body["top_p"] = top_p
+
+            logger.debug(
+                f"[MIMO] API call: model={model}, "
+                f"tools={len(converted_tools) if converted_tools else 0}, "
+                f"stream={stream}, thinking={thinking_active}"
+            )
+
+            if stream:
+                return self._handle_stream_response(request_body)
+            else:
+                return self._handle_sync_response(request_body)
+
+        except Exception as e:
+            logger.error(f"[MIMO] call_with_tools error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+
+            def error_generator():
+                yield {"error": True, "message": str(e), "status_code": 500}
+            return error_generator()
+
+    # -------------------- streaming --------------------
+
+    def _handle_stream_response(self, request_body: dict):
+        """SSE 流式 chunk 转为 OpenAI 标准 delta 输出（含 reasoning_content）。"""
+        try:
+            headers = self._build_headers()
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, stream=True, timeout=180)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MIMO] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            current_tool_calls = {}
+            finish_reason = None
+
+            for line in response.iter_lines():
+                if not line:
+                    continue
+
+                line = line.decode("utf-8")
+                if line.startswith("data: "):
+                    data_str = line[6:]
+                elif line.startswith("data:"):
+                    data_str = line[5:]
+                else:
+                    continue
+                if data_str.strip() == "[DONE]":
+                    break
+
+                try:
+                    chunk = json.loads(data_str)
+                except json.JSONDecodeError as e:
+                    logger.warning(f"[MIMO] JSON decode error: {e}, data: {data_str[:200]}")
+                    continue
+
+                if chunk.get("error"):
+                    error_data = chunk["error"]
+                    error_msg = error_data.get("message", "Unknown error") if isinstance(error_data, dict) else str(error_data)
+                    logger.error(f"[MIMO] stream error: {error_msg}")
+                    yield {"error": True, "message": error_msg, "status_code": 500}
+                    return
+
+                if not chunk.get("choices"):
+                    continue
+                choice = chunk["choices"][0]
+                delta = choice.get("delta", {})
+
+                if choice.get("finish_reason"):
+                    finish_reason = choice["finish_reason"]
+
+                # 推理内容（思考模式）：单独 delta 透传给 agent_stream
+                if delta.get("reasoning_content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "reasoning_content": delta["reasoning_content"],
+                            },
+                            "finish_reason": None,
+                        }]
+                    }
+
+                if delta.get("content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "content": delta["content"],
+                            },
+                        }]
+                    }
+
+                if "tool_calls" in delta and delta["tool_calls"]:
+                    for tool_call_chunk in delta["tool_calls"]:
+                        index = tool_call_chunk.get("index", 0)
+                        if index not in current_tool_calls:
+                            current_tool_calls[index] = {
+                                "id": tool_call_chunk.get("id", ""),
+                                "name": tool_call_chunk.get("function", {}).get("name", ""),
+                                "arguments": "",
+                            }
+                        if "function" in tool_call_chunk and "arguments" in tool_call_chunk["function"]:
+                            current_tool_calls[index]["arguments"] += tool_call_chunk["function"]["arguments"]
+
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {"tool_calls": [tool_call_chunk]},
+                            }]
+                        }
+
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason,
+                }]
+            }
+
+        except requests.exceptions.Timeout:
+            logger.error("[MIMO] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MIMO] stream response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- sync --------------------
+
+    def _handle_sync_response(self, request_body: dict):
+        """非流式响应；统一 yield 一份 Claude 格式 dict 与流式路径对齐。"""
+        try:
+            headers = self._build_headers()
+            request_body.pop("stream", None)
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, timeout=180)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MIMO] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            result = response.json()
+            message = result["choices"][0]["message"]
+            finish_reason = result["choices"][0]["finish_reason"]
+
+            response_data = {"role": "assistant", "content": []}
+
+            # 推理内容包装成 thinking block，便于 agent 层持久化并在工具调用时回传
+            if message.get("reasoning_content"):
+                response_data["content"].append({
+                    "type": "thinking",
+                    "thinking": message["reasoning_content"],
+                })
+
+            if message.get("content"):
+                response_data["content"].append({
+                    "type": "text",
+                    "text": message["content"],
+                })
+
+            if message.get("tool_calls"):
+                for tool_call in message["tool_calls"]:
+                    try:
+                        tool_input = json.loads(tool_call["function"]["arguments"])
+                    except (json.JSONDecodeError, TypeError):
+                        tool_input = {}
+                    response_data["content"].append({
+                        "type": "tool_use",
+                        "id": tool_call["id"],
+                        "name": tool_call["function"]["name"],
+                        "input": tool_input,
+                    })
+
+            if finish_reason == "tool_calls":
+                response_data["stop_reason"] = "tool_use"
+            elif finish_reason == "stop":
+                response_data["stop_reason"] = "end_turn"
+            else:
+                response_data["stop_reason"] = finish_reason
+
+            yield response_data
+
+        except requests.exceptions.Timeout:
+            logger.error("[MIMO] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MIMO] sync response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- format conversion --------------------
+
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        将 Claude 格式（content blocks）转为 OpenAI 格式。
+
+        关键约束：MiMo 思考模式下，一旦历史包含 tool_calls 的 assistant 轮次，
+        所有后续 assistant 消息（含工具调用轮）必须回传 reasoning_content，
+        否则 API 返回 400。本地无 trace 时用空字符串回填，MiMo 接受字段存在
+        即可。
+        """
+        if not messages:
+            return []
+
+        has_tool_call_history = False
+        for msg in messages:
+            if msg.get("role") != "assistant":
+                continue
+            if msg.get("tool_calls"):
+                has_tool_call_history = True
+                break
+            content = msg.get("content")
+            if isinstance(content, list) and any(
+                isinstance(b, dict) and b.get("type") == "tool_use" for b in content
+            ):
+                has_tool_call_history = True
+                break
+
+        converted = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            if not isinstance(content, list):
+                if (
+                    role == "assistant"
+                    and isinstance(msg, dict)
+                    and has_tool_call_history
+                    and "reasoning_content" not in msg
+                ):
+                    patched = dict(msg)
+                    patched["reasoning_content"] = ""
+                    converted.append(patched)
+                else:
+                    converted.append(msg)
+                continue
+
+            if role == "user":
+                has_tool_result = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+                )
+                if has_tool_result:
+                    text_parts = []
+                    tool_results = []
+
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_result":
+                            tool_call_id = block.get("tool_use_id") or ""
+                            result_content = block.get("content", "")
+                            if not isinstance(result_content, str):
+                                result_content = json.dumps(result_content, ensure_ascii=False)
+                            tool_results.append({
+                                "role": "tool",
+                                "tool_call_id": tool_call_id,
+                                "content": result_content,
+                            })
+
+                    converted.extend(tool_results)
+
+                    if text_parts:
+                        converted.append({"role": "user", "content": "\n".join(text_parts)})
+                else:
+                    # 多模态原样保留（image_url / input_audio / video_url 等 block）
+                    converted.append(msg)
+
+            elif role == "assistant":
+                openai_msg = {"role": "assistant"}
+                text_parts = []
+                tool_calls = []
+                reasoning_parts = []
+
+                for block in content:
+                    if not isinstance(block, dict):
+                        continue
+                    btype = block.get("type")
+                    if btype == "text":
+                        text_parts.append(block.get("text", ""))
+                    elif btype == "tool_use":
+                        tool_calls.append({
+                            "id": block.get("id"),
+                            "type": "function",
+                            "function": {
+                                "name": block.get("name"),
+                                "arguments": json.dumps(block.get("input", {})),
+                            },
+                        })
+                    elif btype == "thinking":
+                        reasoning_parts.append(block.get("thinking", ""))
+
+                if text_parts:
+                    openai_msg["content"] = "\n".join(text_parts)
+                elif not tool_calls:
+                    openai_msg["content"] = ""
+
+                if tool_calls:
+                    openai_msg["tool_calls"] = tool_calls
+                    if not text_parts:
+                        openai_msg["content"] = None
+
+                if reasoning_parts:
+                    openai_msg["reasoning_content"] = "\n".join(reasoning_parts)
+                elif has_tool_call_history:
+                    openai_msg["reasoning_content"] = ""
+
+                converted.append(openai_msg)
+            else:
+                converted.append(msg)
+
+        return converted
+
+    def _convert_tools_to_openai_format(self, tools):
+        """工具定义 Claude 格式 → OpenAI 格式。"""
+        if not tools:
+            return None
+
+        converted = []
+        for tool in tools:
+            if "type" in tool and tool["type"] == "function":
+                converted.append(tool)
+            else:
+                converted.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {}),
+                    },
+                })
+        return converted
+
+    # -------------------- vision --------------------
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """通过 MiMo OpenAI 兼容的 /chat/completions 端点进行图像理解。"""
+        try:
+            # 主模型若不支持视觉（如 mimo-v2-flash），自动切到 mimo-v2.5-pro
+            vision_model = model
+            if not vision_model:
+                cur = self.args.get("model") or DEFAULT_MODEL
+                vision_model = cur if cur in MULTIMODAL_MODELS else const.MIMO_V2_5_PRO
+
+            payload = {
+                "model": vision_model,
+                "max_completion_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = self._build_headers()
+            resp = requests.post(
+                f"{self.api_base}/chat/completions",
+                headers=headers, json=payload, timeout=180,
+            )
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+            data = resp.json()
+            if "error" in data:
+                return {"error": True, "message": data["error"].get("message", str(data["error"]))}
+            choice = data.get("choices", [{}])[0].get("message", {})
+            # 部分模型在多模态下会把答案塞在 reasoning_content 而非 content
+            content = choice.get("content") or choice.get("reasoning_content") or ""
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[MIMO] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
diff --git a/models/mimo/mimo_session.py b/models/mimo/mimo_session.py
new file mode 100644
index 0000000..76483f1
--- /dev/null
+++ b/models/mimo/mimo_session.py
@@ -0,0 +1,57 @@
+from common.log import logger
+from models.session_manager import Session
+
+
+class MimoSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="mimo-v2.5-pro"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(
+                    max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        content = msg.get("content", "")
+        if isinstance(content, str):
+            tokens += len(content)
+        elif isinstance(content, list):
+            for block in content:
+                if isinstance(block, dict):
+                    tokens += len(block.get("text", ""))
+    return tokens
diff --git a/models/minimax/minimax_bot.py b/models/minimax/minimax_bot.py
new file mode 100644
index 0000000..530c017
--- /dev/null
+++ b/models/minimax/minimax_bot.py
@@ -0,0 +1,689 @@
+# encoding:utf-8
+
+import time
+import json
+from typing import Optional
+
+import requests
+
+from models.bot import Bot
+from models.minimax.minimax_session import MinimaxSession
+from models.session_manager import SessionManager
+from bridge.context import Context, ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from common import const
+from agent.protocol.message_utils import drop_orphaned_tool_results_openai
+
+
+# MiniMax对话模型API
+class MinimaxBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.args = {
+            "model": conf().get("model") or "MiniMax-M3",
+            "temperature": conf().get("temperature", 0.3),
+            "top_p": conf().get("top_p", 0.95),
+        }
+        self.sessions = SessionManager(MinimaxSession, model=const.MiniMax)
+
+    @property
+    def api_key(self):
+        key = conf().get("minimax_api_key")
+        if not key:
+            key = conf().get("Minimax_api_key")
+        return key
+
+    @property
+    def api_base(self):
+        return conf().get("minimax_api_base", "https://api.minimaxi.com/v1")
+
+    def reply(self, query, context: Context = None) -> Reply:
+        # acquire reply content
+        logger.info("[MINIMAX] query={}".format(query))
+        if context.type == ContextType.TEXT:
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[MINIMAX] session query={}".format(session))
+
+            model = context.get("Minimax_model")
+            new_args = self.args.copy()
+            if model:
+                new_args["model"] = model
+
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[MINIMAX] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[MINIMAX] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: MinimaxSession, args=None, retry_count=0) -> dict:
+        """
+        Call MiniMax API to get the answer using REST API
+        :param session: a conversation session
+        :param args: request arguments
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            if args is None:
+                args = self.args
+
+            # Build request
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}"
+            }
+
+            request_body = {
+                "model": args.get("model", self.args["model"]),
+                "messages": session.messages,
+                "temperature": args.get("temperature", self.args["temperature"]),
+                "top_p": args.get("top_p", self.args["top_p"]),
+            }
+
+            url = f"{self.api_base}/chat/completions"
+            logger.debug(f"[MINIMAX] Calling {url} with model={request_body['model']}")
+
+            response = requests.post(url, headers=headers, json=request_body, timeout=60)
+
+            if response.status_code == 200:
+                result = response.json()
+                content = result["choices"][0]["message"]["content"]
+                total_tokens = result["usage"]["total_tokens"]
+                completion_tokens = result["usage"]["completion_tokens"]
+
+                logger.debug(f"[MINIMAX] reply_text: content_length={len(content)}, tokens={total_tokens}")
+
+                return {
+                    "total_tokens": total_tokens,
+                    "completion_tokens": completion_tokens,
+                    "content": content,
+                }
+            else:
+                error_msg = response.text
+                logger.error(f"[MINIMAX] API error: status={response.status_code}, msg={error_msg}")
+
+                # Parse error for better messages
+                result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+                need_retry = False
+
+                if response.status_code >= 500:
+                    logger.warning(f"[MINIMAX] Server error, retry={retry_count}")
+                    need_retry = retry_count < 2
+                elif response.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                    need_retry = False
+                elif response.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                else:
+                    return result
+
+        except requests.exceptions.Timeout:
+            logger.error("[MINIMAX] Request timeout")
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "请求超时，请稍后再试"}
+            if need_retry:
+                time.sleep(3)
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+        except Exception as e:
+            logger.error(f"[MINIMAX] reply_text error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                time.sleep(3)
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using MiniMax OpenAI-compatible API.
+        Always uses MiniMax-Text-01 — other MiniMax models do not support vision.
+        """
+        try:
+            vision_model = "MiniMax-Text-01"
+            payload = {
+                "model": vision_model,
+                "max_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json",
+            }
+            resp = requests.post(f"{self.api_base}/chat/completions",
+                                 headers=headers, json=payload, timeout=180)
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+            data = resp.json()
+            if "error" in data:
+                return {"error": True, "message": data["error"].get("message", str(data["error"]))}
+            content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[MINIMAX] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call MiniMax API with tool support for agent integration
+
+        This method handles:
+        1. Format conversion (Claude format → OpenAI format)
+        2. System prompt injection
+        3. API calling with REST API
+        4. Interleaved Thinking support (reasoning_split=True)
+
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, etc.)
+
+        Returns:
+            Formatted response or generator for streaming
+        """
+        try:
+            # Convert messages from Claude format to OpenAI format
+            converted_messages = self._convert_messages_to_openai_format(messages)
+
+            # Extract and inject system prompt if provided
+            system_prompt = kwargs.pop("system", None)
+            if system_prompt:
+                # Add system message at the beginning
+                converted_messages.insert(0, {"role": "system", "content": system_prompt})
+
+            # Convert tools from Claude format to OpenAI format
+            converted_tools = None
+            if tools:
+                converted_tools = self._convert_tools_to_openai_format(tools)
+
+            # Prepare API parameters
+            model = kwargs.pop("model", None) or self.args["model"]
+            max_tokens = kwargs.pop("max_tokens", 100000)
+            temperature = kwargs.pop("temperature", self.args["temperature"])
+
+            # Build request body
+            request_body = {
+                "model": model,
+                "messages": converted_messages,
+                "max_tokens": max_tokens,
+                "temperature": temperature,
+                "stream": stream,
+            }
+
+            # Add tools if provided
+            if converted_tools:
+                request_body["tools"] = converted_tools
+
+            # Add reasoning_split=True for better thinking control (M2.1 feature)
+            # This separates thinking content into reasoning_details field
+            request_body["reasoning_split"] = True
+
+            logger.debug(f"[MINIMAX] API call: model={model}, tools={len(converted_tools) if converted_tools else 0}, stream={stream}")
+
+            if stream:
+                return self._handle_stream_response(request_body)
+            else:
+                return self._handle_sync_response(request_body)
+
+        except Exception as e:
+            logger.error(f"[MINIMAX] call_with_tools error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            
+            def error_generator():
+                yield {"error": True, "message": str(e), "status_code": 500}
+            return error_generator()
+
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        Convert messages from Claude format to OpenAI format
+
+        Claude format:
+        - role: "user" | "assistant"
+        - content: string | list of content blocks
+
+        OpenAI format:
+        - role: "user" | "assistant" | "tool"
+        - content: string
+        - tool_calls: list (for assistant)
+        - tool_call_id: string (for tool results)
+        """
+        converted = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            if role == "user":
+                # Handle user message
+                if isinstance(content, list):
+                    has_tool_result = any(
+                        isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+                    )
+                    if has_tool_result:
+                        text_parts = []
+                        tool_results = []
+
+                        for block in content:
+                            if isinstance(block, dict):
+                                if block.get("type") == "text":
+                                    text_parts.append(block.get("text", ""))
+                                elif block.get("type") == "tool_result":
+                                    tool_call_id = block.get("tool_use_id") or ""
+                                    if not tool_call_id:
+                                        logger.warning(f"[MINIMAX] tool_result missing tool_use_id")
+                                    result_content = block.get("content", "")
+                                    if not isinstance(result_content, str):
+                                        result_content = json.dumps(result_content, ensure_ascii=False)
+                                    tool_results.append({
+                                        "role": "tool",
+                                        "tool_call_id": tool_call_id,
+                                        "content": result_content
+                                    })
+
+                        if text_parts:
+                            converted.append({
+                                "role": "user",
+                                "content": "\n".join(text_parts)
+                            })
+
+                        for tool_result in tool_results:
+                            converted.append(tool_result)
+                    else:
+                        # Keep as-is for multimodal content (e.g. image_url blocks)
+                        converted.append(msg)
+                else:
+                    # Simple text content
+                    converted.append({
+                        "role": "user",
+                        "content": str(content)
+                    })
+
+            elif role == "assistant":
+                # Handle assistant message
+                openai_msg = {"role": "assistant"}
+
+                if isinstance(content, list):
+                    # Parse content blocks
+                    text_parts = []
+                    tool_calls = []
+
+                    for block in content:
+                        if isinstance(block, dict):
+                            if block.get("type") == "text":
+                                text_parts.append(block.get("text", ""))
+                            elif block.get("type") == "tool_use":
+                                # Convert to OpenAI tool_calls format
+                                tool_calls.append({
+                                    "id": block.get("id"),
+                                    "type": "function",
+                                    "function": {
+                                        "name": block.get("name"),
+                                        "arguments": json.dumps(block.get("input", {}))
+                                    }
+                                })
+
+                    # Set content (can be empty if only tool calls)
+                    if text_parts:
+                        openai_msg["content"] = "\n".join(text_parts)
+                    elif not tool_calls:
+                        openai_msg["content"] = ""
+
+                    # Set tool_calls
+                    if tool_calls:
+                        openai_msg["tool_calls"] = tool_calls
+                        # When tool_calls exist and content is empty, set to None
+                        if not text_parts:
+                            openai_msg["content"] = None
+
+                else:
+                    # Simple text content
+                    openai_msg["content"] = str(content) if content else ""
+
+                converted.append(openai_msg)
+
+        return drop_orphaned_tool_results_openai(converted)
+
+    def _convert_tools_to_openai_format(self, tools):
+        """
+        Convert tools from Claude format to OpenAI format
+
+        Claude format:
+        {
+            "name": "tool_name",
+            "description": "description",
+            "input_schema": {...}
+        }
+
+        OpenAI format:
+        {
+            "type": "function",
+            "function": {
+                "name": "tool_name",
+                "description": "description",
+                "parameters": {...}
+            }
+        }
+        """
+        converted = []
+
+        for tool in tools:
+            converted.append({
+                "type": "function",
+                "function": {
+                    "name": tool.get("name"),
+                    "description": tool.get("description"),
+                    "parameters": tool.get("input_schema", {})
+                }
+            })
+
+        return converted
+
+    def _handle_sync_response(self, request_body):
+        """Handle synchronous API response"""
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}"
+            }
+
+            # Remove stream from body for sync request
+            request_body.pop("stream", None)
+
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, timeout=60)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MINIMAX] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            result = response.json()
+            message = result["choices"][0]["message"]
+            finish_reason = result["choices"][0]["finish_reason"]
+
+            # Build response in Claude-like format
+            response_data = {
+                "role": "assistant",
+                "content": []
+            }
+
+            # Add reasoning_details (thinking) if present
+            if "reasoning_details" in message:
+                for reasoning in message["reasoning_details"]:
+                    if "text" in reasoning:
+                        response_data["content"].append({
+                            "type": "thinking",
+                            "thinking": reasoning["text"]
+                        })
+
+            # Add text content if present
+            if message.get("content"):
+                response_data["content"].append({
+                    "type": "text",
+                    "text": message["content"]
+                })
+
+            # Add tool calls if present
+            if message.get("tool_calls"):
+                for tool_call in message["tool_calls"]:
+                    response_data["content"].append({
+                        "type": "tool_use",
+                        "id": tool_call["id"],
+                        "name": tool_call["function"]["name"],
+                        "input": json.loads(tool_call["function"]["arguments"])
+                    })
+
+            # Set stop_reason
+            if finish_reason == "tool_calls":
+                response_data["stop_reason"] = "tool_use"
+            elif finish_reason == "stop":
+                response_data["stop_reason"] = "end_turn"
+            else:
+                response_data["stop_reason"] = finish_reason
+
+            yield response_data
+
+        except requests.exceptions.Timeout:
+            logger.error("[MINIMAX] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MINIMAX] sync response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    def _handle_stream_response(self, request_body):
+        """Handle streaming API response
+
+        Args:
+            request_body: API request parameters
+        """
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}"
+            }
+
+            url = f"{self.api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, stream=True, timeout=60)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MINIMAX] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            current_content = []
+            current_tool_calls = {}
+            current_reasoning = []
+            finish_reason = None
+            chunk_count = 0
+
+            # Process SSE stream
+            for line in response.iter_lines():
+                if not line:
+                    continue
+
+                line = line.decode('utf-8')
+                if not line.startswith('data: '):
+                    continue
+
+                data_str = line[6:]  # Remove 'data: ' prefix
+                if data_str.strip() == '[DONE]':
+                    break
+
+                try:
+                    chunk = json.loads(data_str)
+                    chunk_count += 1
+                except json.JSONDecodeError as e:
+                    logger.warning(f"[MINIMAX] JSON decode error: {e}, data: {data_str[:100]}")
+                    continue
+
+                # Check for error response (MiniMax format)
+                if chunk.get("type") == "error" or "error" in chunk:
+                    error_data = chunk.get("error", {})
+                    error_msg = error_data.get("message", "Unknown error")
+                    error_type = error_data.get("type", "")
+                    http_code = error_data.get("http_code", "")
+                    
+                    logger.error(f"[MINIMAX] API error: {error_msg} (type: {error_type}, code: {http_code})")
+                    
+                    yield {
+                        "error": True,
+                        "message": error_msg,
+                        "status_code": int(http_code) if http_code.isdigit() else 500
+                    }
+                    return
+
+                if not chunk.get("choices"):
+                    continue
+
+                choice = chunk["choices"][0]
+                delta = choice.get("delta", {})
+
+                # Handle reasoning_details (thinking)
+                if "reasoning_details" in delta:
+                    for reasoning in delta["reasoning_details"]:
+                        if "text" in reasoning:
+                            reasoning_id = reasoning.get("id", "reasoning-text-1")
+                            reasoning_index = reasoning.get("index", 0)
+                            reasoning_text = reasoning["text"]
+
+                            # Accumulate reasoning text
+                            if reasoning_index >= len(current_reasoning):
+                                current_reasoning.append({"id": reasoning_id, "text": ""})
+
+                            current_reasoning[reasoning_index]["text"] += reasoning_text
+
+                            yield {
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {
+                                        "role": "assistant",
+                                        "reasoning_content": reasoning_text
+                                    }
+                                }]
+                            }
+
+                # Handle text content
+                if "content" in delta and delta["content"]:
+                    # Start new content block if needed
+                    if not any(block.get("type") == "text" for block in current_content):
+                        current_content.append({"type": "text", "text": ""})
+
+                    # Accumulate text
+                    for block in current_content:
+                        if block.get("type") == "text":
+                            block["text"] += delta["content"]
+                            break
+
+                    # Yield OpenAI-format delta (for agent_stream.py compatibility)
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "content": delta["content"]
+                            }
+                        }]
+                    }
+
+                # Handle tool calls
+                if "tool_calls" in delta:
+                    for tool_call_chunk in delta["tool_calls"]:
+                        index = tool_call_chunk.get("index", 0)
+                        if index not in current_tool_calls:
+                            # Start new tool call
+                            current_tool_calls[index] = {
+                                "id": tool_call_chunk.get("id", ""),
+                                "type": "tool_use",
+                                "name": tool_call_chunk.get("function", {}).get("name", ""),
+                                "input": ""
+                            }
+                        
+                        # Accumulate tool call arguments
+                        if "function" in tool_call_chunk and "arguments" in tool_call_chunk["function"]:
+                            current_tool_calls[index]["input"] += tool_call_chunk["function"]["arguments"]
+
+                        # Yield OpenAI-format tool call delta
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "tool_calls": [tool_call_chunk]
+                                }
+                            }]
+                        }
+
+                # Handle finish_reason
+                if choice.get("finish_reason"):
+                    finish_reason = choice["finish_reason"]
+
+            # Log complete reasoning_details for debugging
+            if current_reasoning:
+                logger.debug(f"[MINIMAX] ===== Complete Reasoning Details =====")
+                for i, reasoning in enumerate(current_reasoning):
+                    reasoning_text = reasoning.get("text", "")
+                    logger.debug(f"[MINIMAX] Reasoning {i+1} (length={len(reasoning_text)}):")
+                    logger.debug(f"[MINIMAX] {reasoning_text}")
+                logger.debug(f"[MINIMAX] ===== End Reasoning Details =====")
+
+            # Yield final chunk with finish_reason (OpenAI format)
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason
+                }]
+            }
+
+        except requests.exceptions.Timeout:
+            logger.error("[MINIMAX] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MINIMAX] stream response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
diff --git a/models/minimax/minimax_session.py b/models/minimax/minimax_session.py
new file mode 100644
index 0000000..7479170
--- /dev/null
+++ b/models/minimax/minimax_session.py
@@ -0,0 +1,72 @@
+from models.session_manager import Session
+from common.log import logger
+
+"""
+    e.g.
+    [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Who won the world series in 2020?"},
+        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
+        {"role": "user", "content": "Where was it played?"}
+    ]
+"""
+
+
+class MinimaxSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="minimax"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        # self.reset()
+
+    def add_query(self, query):
+        user_item = {"sender_type": "USER", "sender_name": self.session_id, "text": query}
+        self.messages.append(user_item)
+
+    def add_reply(self, reply):
+        assistant_item = {"sender_type": "BOT", "sender_name": "MM智能助理", "text": reply}
+        self.messages.append(assistant_item)
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["sender_type"] == "BOT":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["sender_type"] == "USER":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    """Returns the number of tokens used by a list of messages."""
+    # 官方token计算规则："对于中文文本来说，1个token通常对应一个汉字；对于英文文本来说，1个token通常对应3至4个字母或1个单词"
+    # 详情请产看文档：https://help.aliyun.com/document_detail/2586397.html
+    # 目前根据字符串长度粗略估计token数，不影响正常使用
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["text"])
+    return tokens
diff --git a/models/modelscope/modelscope_bot.py b/models/modelscope/modelscope_bot.py
new file mode 100644
index 0000000..6e2b767
--- /dev/null
+++ b/models/modelscope/modelscope_bot.py
@@ -0,0 +1,882 @@
+# encoding:utf-8
+
+import json
+import time
+import requests
+
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from .modelscope_session import ModelScopeSession
+
+
+class ModelScopeBot(Bot):
+
+    def __init__(self):
+        super().__init__()
+        model = conf().get("model") or "Qwen/Qwen3.5-27B"
+        if model == "modelscope":
+            model = "Qwen/Qwen3.5-27B"
+        self.sessions = SessionManager(ModelScopeSession, model=model)
+        self.args = {
+            "model": model,
+            "temperature": conf().get("temperature", 0.3),
+            "top_p": conf().get("top_p", 1.0),
+        }
+        self.api_key = conf().get("modelscope_api_key")
+        self.base_url = conf().get("modelscope_base_url", "https://api-inference.modelscope.cn/v1")
+        if self.base_url.endswith("/chat/completions"):
+            self.base_url = self.base_url.rsplit("/chat/completions", 1)[0]
+        if self.base_url.endswith("/"):
+            self.base_url = self.base_url.rstrip("/")
+        
+        # Cache context for Agent mode usage
+        self._last_context = None
+        
+        logger.info("[MODELSCOPE] base_url configured as: {}".format(self.base_url))
+
+    def reply(self, query, context=None):
+        # Cache context for Agent mode usage
+        self._last_context = context
+        
+        if context.type == ContextType.TEXT:
+            logger.info("[MODELSCOPE] query={}".format(query))
+            
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[MODELSCOPE] session query={}".format(session.messages))
+
+            model = context.get("modelscope_model")
+            new_args = self.args.copy()
+            if model:
+                new_args["model"] = model
+            
+            model_name = new_args["model"]
+
+            # Unified judgment for thinking model
+            if self._is_thinking_model(model_name):
+                new_args["enable_thinking"] = True
+                reply_content = self.reply_text_stream(session, args=new_args)
+            else:
+                reply_content = self.reply_text(session, args=new_args)
+            
+            logger.debug(
+                "[MODELSCOPE] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(
+                    reply_content["content"],
+                    session_id,
+                    reply_content["total_tokens"]
+                )
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[MODELSCOPE] reply {} used 0 tokens.".format(reply_content))
+            
+            return reply
+            
+        elif context.type == ContextType.IMAGE_CREATE:
+            ok, retstring = self.create_img(query, 0)
+            return Reply(ReplyType.IMAGE_URL, retstring) if ok else Reply(ReplyType.ERROR, retstring)
+        else:
+            return Reply(ReplyType.ERROR, "Bot 不支持处理{}类型的消息".format(context.type))
+
+    def reply_text(self, session, args=None, retry_count=0):
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            
+            body = args.copy() if args else {}
+            body["messages"] = self._convert_messages_for_modelscope(session.messages)
+            body["stream"] = False
+            
+            res = requests.post(
+                "{}/chat/completions".format(self.base_url),
+                headers=headers,
+                json=body,
+                timeout=120
+            )
+            
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response.get("usage", {}).get("total_tokens", 0),
+                    "completion_tokens": response.get("usage", {}).get("completion_tokens", 0),
+                    "content": response["choices"][0]["message"]["content"] if response.get("choices") else ""
+                }
+            else:
+                response = res.json()
+                error = response.get("error", response.get("errors", {}))
+                logger.error(
+                    "[MODELSCOPE] chat failed, status_code={}, msg={}".format(
+                        res.status_code,
+                        error.get('message') if isinstance(error, dict) else error
+                    )
+                )
+                
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+
+                if res.status_code >= 500:
+                    logger.warn("[MODELSCOPE] do retry, times={}".format(retry_count))
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查 API Key 是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+                
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                else:
+                    return result
+                    
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def reply_text_stream(self, session, args=None):
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            
+            body = args.copy() if args else {}
+            body["messages"] = self._convert_messages_for_modelscope(session.messages)
+            body["stream"] = True
+
+            res = requests.post(
+                "{}/chat/completions".format(self.base_url),
+                headers=headers,
+                json=body,
+                stream=True,
+                timeout=120
+            )
+            if res.status_code == 200:
+                content = ""
+                total_tokens = completion_tokens = 0
+                finish_reason = None
+                
+                for line in res.iter_lines():
+                    if not line:
+                        continue
+                    
+                    decoded_line = line.decode('utf-8')
+                    if not decoded_line.startswith("data: "):
+                        continue
+                    
+                    data_str = decoded_line[6:]
+                    if data_str.strip() == "[DONE]":
+                        break
+                    
+                    try:
+                        json_data = json.loads(data_str)
+
+                        if "usage" in json_data:
+                            total_tokens = json_data["usage"].get("total_tokens", 0)
+                            completion_tokens = json_data["usage"].get("completion_tokens", 0)
+
+                        delta = json_data.get("choices", [{}])[0].get("delta", {})
+                        if delta and delta.get("content"):
+                            content += delta["content"]
+
+                        choice = json_data.get("choices", [{}])[0]
+                        if choice.get("finish_reason"):
+                            finish_reason = choice["finish_reason"]
+                            
+                    except json.JSONDecodeError:
+                        continue
+
+                if finish_reason is None and content:
+                    finish_reason = "stop"
+                
+                return {
+                    "total_tokens": total_tokens,
+                    "completion_tokens": completion_tokens,
+                    "content": content
+                }
+            else:
+                return {"completion_tokens": 0, "content": "请求失败"}
+                
+        except Exception as e:
+            logger.exception(e)
+            return {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+
+    def create_img(self, query):
+        try:
+            logger.info("[ModelScopeImage] image_query={}".format(query))
+            
+            create_headers = {
+                "Authorization": "Bearer " + self.api_key,
+                "Content-Type": "application/json; charset=utf-8",
+                "X-ModelScope-Async-Mode": "true"
+            }
+            
+            payload = {
+                "model": conf().get("text_to_image"),
+                "prompt": query,
+                "n": 1,
+            }
+            
+            logger.debug("[ModelScopeImage] model={}".format(payload["model"]))
+            
+            res = requests.post(
+                "{}/images/generations".format(self.base_url),
+                headers=create_headers,
+                data=json.dumps(payload, ensure_ascii=False).encode('utf-8'),
+                timeout=120
+            )
+            
+            logger.debug("[ModelScopeImage] create task status={}".format(res.status_code))
+            logger.debug("[ModelScopeImage] create task response={}".format(res.text))
+            
+            if res.status_code != 200:
+                logger.error("[ModelScopeImage] create task failed: {}".format(res.text))
+                return False, "创建画图任务失败：{}".format(res.status_code)
+            
+            task_data = res.json()
+            
+            task_id = task_data.get("task_id")
+            if not task_id:
+                logger.error("[ModelScopeImage] No task_id in response: {}".format(task_data))
+                return False, "创建画图任务失败：未返回 task_id"
+            
+            logger.info("[ModelScopeImage] task_id={}".format(task_id))
+            
+            max_wait_times = 60
+            wait_interval = 5
+            
+            for i in range(max_wait_times):
+                time.sleep(wait_interval)
+                
+                poll_headers = {
+                    "Authorization": "Bearer " + self.api_key,
+                    "X-ModelScope-Task-Type": "image_generation"
+                }
+                
+                poll_url = "{}/tasks/{}".format(self.base_url, task_id)
+                logger.debug("[ModelScopeImage] poll {} URL: {}".format(i+1, poll_url))
+                logger.debug("[ModelScopeImage] poll headers: {}".format(poll_headers))
+                
+                task_res = requests.get(
+                    poll_url,
+                    headers=poll_headers,
+                    timeout=30
+                )
+                
+                logger.debug("[ModelScopeImage] poll {} status={}".format(i+1, task_res.status_code))
+                logger.debug("[ModelScopeImage] poll response={}".format(task_res.text))
+                
+                if task_res.status_code != 200:
+                    logger.error("[ModelScopeImage] poll task error: {}".format(task_res.text))
+                    continue
+                
+                data = task_res.json()
+                
+                task_status = data.get("task_status")
+                logger.debug("[ModelScopeImage] task_status={}".format(task_status))
+                
+                if task_status == "SUCCEED":
+                    output_images = data.get("output_images", [])
+                    if output_images and len(output_images) > 0:
+                        image_url = output_images[0]
+                        logger.info("[ModelScopeImage] image generated successfully: {}".format(image_url))
+                        return True, image_url
+                    else:
+                        logger.error("[ModelScopeImage] No output_images in success response: {}".format(data))
+                        return False, "画图成功但未返回图片 URL"
+                        
+                elif task_status == "FAILED":
+                    error_msg = "未知错误"
+                    if "errors" in data:
+                        error_msg = data["errors"].get("message", "未知错误")
+                    elif "message" in data:
+                        error_msg = data["message"]
+                    logger.error("[ModelScopeImage] task failed: {}".format(data))
+                    return False, "画图任务失败：{}".format(error_msg)
+                    
+                elif task_status == "CANCELED":
+                    logger.error("[ModelScopeImage] task canceled: {}".format(data))
+                    return False, "画图任务已取消"
+                    
+                logger.debug("[ModelScopeImage] waiting for task to complete...")
+            
+            logger.error("[ModelScopeImage] task timeout after {} seconds".format(max_wait_times * wait_interval))
+            return False, "画图超时，请稍后再试"
+            
+        except Exception as e:
+            logger.error("[ModelScopeImage] error: {}".format(format(e)))
+            return False, "画图出现问题，请休息一下再问我吧"
+
+    # ==================== Agent Mode Support ====================
+
+    def _detect_image_intent(self, message):
+        """Detect whether the message has drawing intention (keyword detection)"""
+        if not message:
+            return False
+        
+        message_lower = message.lower()
+        image_keywords = ["画", "图片", "图像", "生成图", "photo", "image", "draw", "paint", "generate"]
+        if any(keyword in message_lower for keyword in image_keywords):
+            logger.info("[MODELSCOPE] Image intent detected by keyword: {}".format(message[:50]))
+            return True
+        
+        return False
+
+    def _is_thinking_model(self, model_name):
+        """
+        Determine whether it is a thinking model.
+        A thinking model requires: 1) enabling the enable_thinking parameter, and 2) using streaming responses.
+        """
+        if not model_name:
+            return False
+        model_name_lower = model_name.lower()
+        if "thinking" in model_name_lower or "think" in model_name_lower:
+            return True
+        if model_name in ["Qwen/QwQ-32B", ]:
+            return True
+        return False
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call ModelScope API with tool call support.
+        Also check ContextType and keywords; if either matches, trigger drawing.
+        """
+        try:
+            # Check the IMAGE_CREATE type from the cached context
+            context = getattr(self, '_last_context', None)
+            
+            # If the context type is IMAGE_CREATE, directly call create_img
+            if context and hasattr(context, 'type') and context.type == ContextType.IMAGE_CREATE:
+                logger.info("[MODELSCOPE] IMAGE_CREATE context detected, calling create_img directly")
+                query = getattr(context, 'content', '')
+                if query:
+                    ok, result = self.create_img(query)
+                    if ok:
+                        logger.info("[MODELSCOPE] Image generated: {}".format(result))
+                        if stream:
+                            return self._create_image_stream_response(result)
+                        else:
+                            return self._create_image_response(result)
+                    else:
+                        logger.error("[MODELSCOPE] Image generation failed: {}".format(result))
+                        error_content = "画图失败：{}".format(result)
+                        if stream:
+                            return self._create_error_stream_response(error_content)
+                        else:
+                            return self._create_error_response(error_content)
+            
+            # Extract message content
+            last_message = ""
+            if messages and len(messages) > 0:
+                last_msg = messages[-1]
+                if isinstance(last_msg, dict):
+                    content = last_msg.get("content", "")
+                    if isinstance(content, list):
+                        text_parts = []
+                        for block in content:
+                            if isinstance(block, dict):
+                                if block.get("type") == "text":
+                                    text_parts.append(block.get("text", ""))
+                        last_message = " ".join(text_parts)
+                    else:
+                        last_message = content
+                elif isinstance(last_msg, str):
+                    last_message = last_msg
+            
+            if not isinstance(last_message, str):
+                last_message = str(last_message)
+            
+            logger.debug("[MODELSCOPE] Extracted message: {}".format(last_message[:100]))
+            
+            # Keyword detection
+            has_image_intent = self._detect_image_intent(last_message)
+            
+            if has_image_intent:
+                logger.info("[MODELSCOPE] Image intent detected by keyword, calling create_img directly")
+                ok, result = self.create_img(last_message)
+                if ok:
+                    logger.info("[MODELSCOPE] Image generated: {}".format(result))
+                    if stream:
+                        return self._create_image_stream_response(result)
+                    else:
+                        return self._create_image_response(result)
+                else:
+                    logger.error("[MODELSCOPE] Image generation failed: {}".format(result))
+                    error_content = "画图失败：{}".format(result)
+                    if stream:
+                        return self._create_error_stream_response(error_content)
+                    else:
+                        return self._create_error_response(error_content)
+            
+            # No drawing intent, proceed with normal tool call flow
+            session_id = kwargs.get('session_id', 'default_session')
+            session = self.sessions.session_query("", session_id)
+            session.messages = messages
+            
+            args = self.args.copy()
+            args.update(kwargs)
+            
+            # Unified judgment for thinking model
+            model_name = args.get("model", self.args.get("model", ""))
+            if self._is_thinking_model(model_name):
+                args["enable_thinking"] = True
+            
+            if tools:
+                args["tools"] = self._convert_tools_to_openai_format(tools)
+                args["tool_choice"] = "auto"
+            
+            logger.debug(
+                "[MODELSCOPE] call_with_tools: model={}, tools={}, stream={}, enable_thinking={}".format(
+                    args.get('model'),
+                    len(tools) if tools else 0,
+                    stream,
+                    args.get('enable_thinking')
+                )
+            )
+            
+            if stream:
+                return self._handle_stream_response(session, args)
+            else:
+                return self._handle_sync_response(session, args)
+                
+        except Exception as e:
+            logger.error("[MODELSCOPE] call_with_tools error: {}".format(e))
+            error_msg = "{}".format(e)
+            def error_generator():
+                yield {"error": True, "message": error_msg, "status_code": 500}
+            return error_generator()
+
+    def _handle_sync_response(self, session, args):
+        result = self.reply_text(session, args)
+        
+        content = result.get("content", "")
+        tool_calls = result.get("tool_calls")
+        
+        if tool_calls:
+            for tool_call in tool_calls:
+                tool_name = tool_call.get("function", {}).get("name", "")
+                if tool_name in ["create_image", "generate_image"]:
+                    try:
+                        tool_args = json.loads(tool_call.get("function", {}).get("arguments", "{}"))
+                        prompt = tool_args.get("prompt", "")
+                        ok, image_url = self.create_img(prompt)
+                        if ok:
+                            result["tool_execution_result"] = {"image_url": image_url, "success": True}
+                        else:
+                            result["tool_execution_result"] = {"error": image_url, "success": False}
+                    except Exception as e:
+                        logger.error("[MODELSCOPE] Sync tool execution error: {}".format(e))
+        
+        return {
+            "choices": [{
+                "message": {
+                    "role": "assistant",
+                    "content": content,
+                    "tool_calls": tool_calls
+                },
+                "finish_reason": "stop"
+            }],
+            "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": result.get("completion_tokens", 0),
+                "total_tokens": result.get("total_tokens", 0)
+            },
+            "model": args.get("model", self.args.get("model"))
+        }
+
+    def _handle_stream_response(self, session, args):
+        try:
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": "Bearer " + self.api_key
+            }
+            
+            body = args.copy()
+            body["messages"] = self._convert_messages_for_modelscope(session.messages)
+            body["stream"] = True
+            
+            response = requests.post(
+                "{}/chat/completions".format(self.base_url),
+                headers=headers,
+                json=body,
+                stream=True,
+                timeout=120
+            )
+            
+            if response.status_code != 200:
+                yield {"error": True, "message": response.text, "status_code": response.status_code}
+                return
+            
+            current_tool_calls = {}
+            finish_reason = None
+            
+            for line in response.iter_lines():
+                if not line:
+                    continue
+                
+                line = line.decode("utf-8")
+                if not line.startswith("data: ") or line[6:].strip() == "[DONE]":
+                    continue
+                
+                try:
+                    chunk = json.loads(line[6:])
+                    
+                    if chunk.get("error"):
+                        yield {"error": True, "message": str(chunk["error"]), "status_code": 500}
+                        return
+                    
+                    choices = chunk.get("choices")
+                    if not choices or len(choices) == 0:
+                        continue
+                    
+                    choice = choices[0]
+                    if not choice:
+                        continue
+                    
+                    delta = choice.get("delta")
+                    if not delta:
+                        continue
+                    
+                    if delta.get("reasoning_content"):
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "role": "assistant",
+                                    "reasoning_content": delta["reasoning_content"]
+                                }
+                            }]
+                        }
+                        continue
+                    
+                    tool_call_chunks = delta.get("tool_calls")
+                    if tool_call_chunks:
+                        cleaned_chunks = []
+                        for tool_call_chunk in tool_call_chunks:
+                            if not tool_call_chunk:
+                                continue
+                            
+                            index = tool_call_chunk.get("index", 0)
+                            func_info = tool_call_chunk.get("function") or {}
+                            
+                            if index not in current_tool_calls:
+                                current_tool_calls[index] = {
+                                    "id": tool_call_chunk.get("id") or "",
+                                    "name": func_info.get("name") or "",
+                                    "arguments": ""
+                                }
+                                logger.debug("[MODELSCOPE] tool_call start: {}".format(func_info.get('name')))
+                            
+                            args_str = func_info.get("arguments")
+                            if args_str:
+                                current_tool_calls[index]["arguments"] += (
+                                    args_str if isinstance(args_str, str) else str(args_str)
+                                )
+                            
+                            cleaned_chunk = {
+                                "index": index,
+                                "id": tool_call_chunk.get("id") or "call_{}".format(index),
+                                "type": "function",
+                                "function": {
+                                    "name": func_info.get("name") or current_tool_calls[index].get("name", ""),
+                                    "arguments": func_info.get("arguments") or ""
+                                }
+                            }
+                            cleaned_chunks.append(cleaned_chunk)
+                        
+                        if cleaned_chunks:
+                            yield {
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {
+                                        "role": "assistant",
+                                        "tool_calls": cleaned_chunks
+                                    }
+                                }]
+                            }
+                        continue
+                    
+                    content = delta.get("content")
+                    if content:
+                        logger.debug("[MODELSCOPE] stream content: {}...".format(content[:50]))
+                    
+                    yield_chunk = {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": delta.get("role"),
+                                "content": content
+                            }
+                        }]
+                    }
+                    
+                    if choice.get("finish_reason"):
+                        finish_reason = choice["finish_reason"]
+                        yield_chunk["choices"][0]["finish_reason"] = finish_reason
+                    
+                    yield yield_chunk
+                    
+                except json.JSONDecodeError:
+                    continue
+                except Exception as e:
+                    logger.error("[MODELSCOPE] chunk process error: {}".format(e))
+                    continue
+            
+            logger.debug(
+                "[MODELSCOPE] stream completed: has_tool_calls={}, finish_reason={}".format(
+                    len(current_tool_calls) > 0,
+                    finish_reason
+                )
+            )
+            
+            if current_tool_calls:
+                logger.debug("[MODELSCOPE] tool_calls collected: {}".format(list(current_tool_calls.values())))
+                
+                for idx, tool_call in current_tool_calls.items():
+                    tool_name = tool_call.get("name", "")
+                    tool_args_str = tool_call.get("arguments", "{}")
+                    
+                    if tool_name in ["create_image", "generate_image"]:
+                        try:
+                            tool_args = json.loads(tool_args_str) if tool_args_str else {}
+                            prompt = tool_args.get("prompt", "")
+                            
+                            logger.info("[MODELSCOPE] Executing image tool directly: {}".format(prompt[:50]))
+                            
+                            ok, result = self.create_img(prompt)
+                            
+                            if ok:
+                                logger.info("[MODELSCOPE] Image generated: {}".format(result))
+                                yield {
+                                    "choices": [{
+                                        "index": 0,
+                                        "delta": {
+                                            "role": "tool",
+                                            "content": json.dumps({"image_url": result, "success": True})
+                                        },
+                                        "tool_call_id": tool_call.get("id", "")
+                                    }]
+                                }
+                            else:
+                                logger.error("[MODELSCOPE] Image generation failed: {}".format(result))
+                                yield {
+                                    "choices": [{
+                                        "index": 0,
+                                        "delta": {
+                                            "role": "tool",
+                                            "content": json.dumps({"error": result, "success": False})
+                                        },
+                                        "tool_call_id": tool_call.get("id", "")
+                                    }]
+                                }
+                        except Exception as e:
+                            logger.error("[MODELSCOPE] Image tool execution error: {}".format(e))
+                            yield {
+                                "choices": [{
+                                    "index": 0,
+                                    "delta": {
+                                        "role": "tool",
+                                        "content": json.dumps({"error": str(e), "success": False})
+                                    },
+                                    "tool_call_id": tool_call.get("id", "")
+                                }]
+                            }
+            
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason or "stop"
+                }]
+            }
+            
+        except Exception as e:
+            logger.error("[MODELSCOPE] stream tool call error: {}".format(e))
+            error_msg = "{}".format(e)
+            def error_generator():
+                yield {"error": True, "message": error_msg, "status_code": 500}
+            return error_generator()
+
+    # ==================== Format Conversion ====================
+
+    def _convert_messages_for_modelscope(self, messages):
+        if not messages:
+            return []
+        converted = []
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+            if isinstance(content, str):
+                converted.append(msg)
+                continue
+            if isinstance(content, list):
+                new_content = []
+                for block in content:
+                    if not isinstance(block, dict):
+                        new_content.append(block)
+                        continue
+                    block_type = block.get("type")
+                    if block_type == "tool_result":
+                        tool_content = block.get("content", "")
+                        if not isinstance(tool_content, str):
+                            tool_content = json.dumps(tool_content, ensure_ascii=False)
+                        new_content.append({
+                            "type": "text",
+                            "text": "[工具执行结果]: {}".format(tool_content)
+                        })
+                    elif block_type == "tool_use":
+                        tool_name = block.get("name", "unknown")
+                        tool_input = block.get("input", {})
+                        if not isinstance(tool_input, str):
+                            tool_input = json.dumps(tool_input, ensure_ascii=False)
+                        new_content.append({
+                            "type": "text",
+                            "text": "[工具调用]: {}({})".format(tool_name, tool_input)
+                        })
+                    else:
+                        new_content.append(block)
+                converted.append({"role": role, "content": new_content})
+            else:
+                converted.append(msg)
+        return converted
+
+    def _convert_tools_to_openai_format(self, tools):
+        if not tools:
+            return None
+        converted = []
+        for tool in tools:
+            if "type" in tool and tool["type"] == "function":
+                converted.append(tool)
+            else:
+                converted.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+        return converted
+
+    def _create_image_response(self, image_url):
+        return {
+            "choices": [{
+                "message": {
+                    "role": "assistant",
+                    "content": "已为您生成图片：{}".format(image_url),
+                    "tool_calls": None
+                },
+                "finish_reason": "stop"
+            }],
+            "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "total_tokens": 0
+            },
+            "model": self.args.get("model")
+        }
+
+    def _create_image_stream_response(self, image_url):
+        content = "已为您生成图片：{}".format(image_url)
+        yield {
+            "choices": [{
+                "index": 0,
+                "delta": {"role": "assistant"}
+            }]
+        }
+        chunk_size = 10
+        for i in range(0, len(content), chunk_size):
+            chunk = content[i:i+chunk_size]
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {"content": chunk}
+                }]
+            }
+        yield {
+            "choices": [{
+                "index": 0,
+                "delta": {},
+                "finish_reason": "stop"
+            }]
+        }
+
+    def _create_error_response(self, error_msg):
+        return {
+            "choices": [{
+                "message": {
+                    "role": "assistant",
+                    "content": error_msg,
+                    "tool_calls": None
+                },
+                "finish_reason": "stop"
+            }],
+            "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "total_tokens": 0
+            },
+            "model": self.args.get("model")
+        }
+
+    def _create_error_stream_response(self, error_msg):
+        yield {
+            "choices": [{
+                "index": 0,
+                "delta": {"role": "assistant"}
+            }]
+        }
+        chunk_size = 10
+        for i in range(0, len(error_msg), chunk_size):
+            chunk = error_msg[i:i+chunk_size]
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {"content": chunk}
+                }]
+            }
+        yield {
+            "choices": [{
+                "index": 0,
+                "delta": {},
+                "finish_reason": "stop"
+            }]
+        }
diff --git a/models/modelscope/modelscope_session.py b/models/modelscope/modelscope_session.py
new file mode 100644
index 0000000..fc349ed
--- /dev/null
+++ b/models/modelscope/modelscope_session.py
@@ -0,0 +1,51 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class ModelScopeSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="Qwen/Qwen2.5-7B-Instruct"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens,
+                                                                                       len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/moonshot/moonshot_bot.py b/models/moonshot/moonshot_bot.py
new file mode 100644
index 0000000..fd3fb70
--- /dev/null
+++ b/models/moonshot/moonshot_bot.py
@@ -0,0 +1,631 @@
+# encoding:utf-8
+
+import json
+import time
+from typing import Optional
+
+import requests
+from models.bot import Bot
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from .moonshot_session import MoonshotSession
+
+
+# Moonshot (Kimi) API Bot
+class MoonshotBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(MoonshotSession, model=conf().get("model") or "moonshot-v1-128k")
+        model = conf().get("model") or "moonshot-v1-128k"
+        if model == "moonshot":
+            model = "moonshot-v1-32k"
+        self.args = {
+            "model": model,
+            "temperature": conf().get("temperature", 0.3),
+            "top_p": conf().get("top_p", 1.0),
+        }
+
+    @property
+    def api_key(self):
+        return conf().get("moonshot_api_key")
+
+    @property
+    def base_url(self):
+        url = conf().get("moonshot_base_url", "https://api.moonshot.cn/v1")
+        if url.endswith("/chat/completions"):
+            url = url.rsplit("/chat/completions", 1)[0]
+        return url.rstrip("/")
+
+    @property
+    def _is_kimi_coding_plan(self) -> bool:
+        """Detect Kimi Coding Plan by model name or API base URL."""
+        model = str(conf().get("model", ""))
+        base = str(conf().get("moonshot_base_url", ""))
+        return model == "kimi-for-coding" or "api.kimi.com/coding" in base
+
+    @staticmethod
+    def _is_builtin_reasoning_model(model_name: str) -> bool:
+        """Return True for Kimi code models with built-in reasoning.
+
+        These models only accept thinking type=enabled and reject disabled,
+        so the thinking param must be omitted entirely.
+        """
+        return model_name.lower().startswith("kimi-k2.7-code")
+
+    @classmethod
+    def _model_supports_thinking(cls, model_name: str) -> bool:
+        """Return True if the model accepts the ``thinking`` request parameter."""
+        m = model_name.lower()
+        if cls._is_builtin_reasoning_model(m):
+            return False
+        return m.startswith("kimi-k2") or m.startswith("kimi-k1.5")
+
+    def _build_headers(self) -> dict:
+        """Build HTTP headers, adding Coding-Agent User-Agent for Kimi Coding Plan."""
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}",
+        }
+        if self._is_kimi_coding_plan:
+            headers["User-Agent"] = "claude-cli/2.1.39"
+        return headers
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[MOONSHOT] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[MOONSHOT] session query={}".format(session.messages))
+
+            model = context.get("moonshot_model")
+            new_args = self.args.copy()
+            if model:
+                new_args["model"] = model
+
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[MOONSHOT] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[MOONSHOT] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: MoonshotSession, args=None, retry_count: int = 0) -> dict:
+        """
+        Call Moonshot chat completion API to get the answer
+        :param session: a conversation session
+        :param args: model args
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            headers = self._build_headers()
+            # Fallback to default args (e.g. when called by session title
+            # generation which passes only the session). Always copy to avoid
+            # mutating the shared self.args across calls.
+            body = dict(args) if args else dict(self.args)
+            body["messages"] = session.messages
+            model_name = str(body.get("model", ""))
+            # K2.x / Coding Plan enforce fixed temperature/top_p; strip them.
+            if model_name.startswith("kimi-k2") or model_name == "kimi-for-coding":
+                body.pop("temperature", None)
+                body.pop("top_p", None)
+            res = requests.post(
+                f"{self.base_url}/chat/completions",
+                headers=headers,
+                json=body
+            )
+            if res.status_code == 200:
+                response = res.json()
+                return {
+                    "total_tokens": response["usage"]["total_tokens"],
+                    "completion_tokens": response["usage"]["completion_tokens"],
+                    "content": response["choices"][0]["message"]["content"]
+                }
+            else:
+                response = res.json()
+                error = response.get("error")
+                logger.error(f"[MOONSHOT] chat failed, status_code={res.status_code}, "
+                             f"msg={error.get('message')}, type={error.get('type')}")
+
+                result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"}
+                need_retry = False
+                if res.status_code >= 500:
+                    logger.warn(f"[MOONSHOT] do retry, times={retry_count}")
+                    need_retry = retry_count < 2
+                elif res.status_code == 401:
+                    result["content"] = "授权失败，请检查API Key是否正确"
+                elif res.status_code == 429:
+                    result["content"] = "请求过于频繁，请稍后再试"
+                    need_retry = retry_count < 2
+                else:
+                    need_retry = False
+
+                if need_retry:
+                    time.sleep(3)
+                    return self.reply_text(session, args, retry_count + 1)
+                else:
+                    return result
+        except Exception as e:
+            logger.exception(e)
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            if need_retry:
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using Moonshot (Kimi) OpenAI-compatible API."""
+        try:
+            vision_model = model or self.args.get("model", "kimi-k2.6")
+            payload = {
+                "model": vision_model,
+                "max_tokens": max_tokens,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = self._build_headers()
+            resp = requests.post(f"{self.base_url}/chat/completions",
+                                 headers=headers, json=payload, timeout=180)
+            if resp.status_code != 200:
+                return {"error": True, "message": f"HTTP {resp.status_code}: {resp.text[:300]}"}
+            data = resp.json()
+            if "error" in data:
+                return {"error": True, "message": data["error"].get("message", str(data["error"]))}
+            content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[MOONSHOT] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    # ==================== Agent mode support ====================
+
+    def call_with_tools(self, messages, tools=None, stream: bool = False, **kwargs):
+        """
+        Call Moonshot API with tool support for agent integration.
+
+        This method handles:
+        1. Format conversion (Claude format -> OpenAI format)
+        2. System prompt injection
+        3. Streaming SSE response with tool_calls
+        4. Thinking (reasoning) is disabled by default to avoid tool_choice conflicts
+
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, model, etc.)
+
+        Returns:
+            Generator yielding OpenAI-format chunks (for streaming)
+        """
+        try:
+            # Convert messages from Claude format to OpenAI format
+            converted_messages = self._convert_messages_to_openai_format(messages)
+
+            # Inject system prompt if provided
+            system_prompt = kwargs.pop("system", None)
+            if system_prompt:
+                if not converted_messages or converted_messages[0].get("role") != "system":
+                    converted_messages.insert(0, {"role": "system", "content": system_prompt})
+                else:
+                    converted_messages[0] = {"role": "system", "content": system_prompt}
+
+            # Convert tools from Claude format to OpenAI format
+            converted_tools = None
+            if tools:
+                converted_tools = self._convert_tools_to_openai_format(tools)
+
+            # Resolve model / temperature
+            model = kwargs.pop("model", None) or self.args["model"]
+            max_tokens = kwargs.pop("max_tokens", None)
+            # Don't pop temperature, just ignore it
+            kwargs.pop("temperature", None)
+
+            # Build request body (omit temperature, let the API use its own default)
+            request_body = {
+                "model": model,
+                "messages": converted_messages,
+                "stream": stream,
+            }
+            if max_tokens is not None:
+                request_body["max_tokens"] = max_tokens
+
+            # Add tools
+            if converted_tools:
+                request_body["tools"] = converted_tools
+                request_body["tool_choice"] = "auto"
+
+            # Kimi Coding Plan has built-in reasoning and ignores the thinking param.
+            # For regular Kimi models, only K2/K1.5 series support the thinking param.
+            # Respect the enable_thinking config passed from agent_bridge.
+            if not self._is_kimi_coding_plan and self._model_supports_thinking(model):
+                thinking = kwargs.get("thinking", {"type": "enabled"})
+                request_body["thinking"] = thinking
+
+            logger.debug(f"[MOONSHOT] API call: model={model}, "
+                         f"tools={len(converted_tools) if converted_tools else 0}, stream={stream}")
+
+            if stream:
+                return self._handle_stream_response(request_body)
+            else:
+                return self._handle_sync_response(request_body)
+
+        except Exception as e:
+            logger.error(f"[MOONSHOT] call_with_tools error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+
+            def error_generator():
+                yield {"error": True, "message": str(e), "status_code": 500}
+            return error_generator()
+
+    # -------------------- streaming --------------------
+
+    def _handle_stream_response(self, request_body: dict):
+        """Handle streaming SSE response from Moonshot API and yield OpenAI-format chunks."""
+        try:
+            headers = self._build_headers()
+
+            url = f"{self.base_url}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, stream=True, timeout=120)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MOONSHOT] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            current_tool_calls = {}
+            finish_reason = None
+
+            for line in response.iter_lines():
+                if not line:
+                    continue
+
+                line = line.decode("utf-8")
+                # Handle both "data: {...}" and "data:{...}" (Kimi Coding Plan omits the space)
+                if line.startswith("data: "):
+                    data_str = line[6:]
+                elif line.startswith("data:"):
+                    data_str = line[5:]
+                else:
+                    continue
+                if data_str.strip() == "[DONE]":
+                    break
+
+                try:
+                    chunk = json.loads(data_str)
+                except json.JSONDecodeError as e:
+                    logger.warning(f"[MOONSHOT] JSON decode error: {e}, data: {data_str[:200]}")
+                    continue
+
+                # Check for error in chunk
+                if chunk.get("error"):
+                    error_data = chunk["error"]
+                    error_msg = error_data.get("message", "Unknown error") if isinstance(error_data, dict) else str(error_data)
+                    logger.error(f"[MOONSHOT] stream error: {error_msg}")
+                    yield {"error": True, "message": error_msg, "status_code": 500}
+                    return
+
+                if not chunk.get("choices"):
+                    continue
+
+                choices = chunk["choices"]
+                if not choices:
+                    continue
+                choice = choices[0]
+                delta = choice.get("delta", {})
+
+                # Capture finish_reason early (it may arrive on any chunk type)
+                if choice.get("finish_reason"):
+                    finish_reason = choice["finish_reason"]
+
+                if delta.get("reasoning_content"):
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "reasoning_content": delta["reasoning_content"]
+                            },
+                            "finish_reason": None
+                        }]
+                    }
+                    continue
+
+                # Handle text content
+                if "content" in delta and delta["content"]:
+                    yield {
+                        "choices": [{
+                            "index": 0,
+                            "delta": {
+                                "role": "assistant",
+                                "content": delta["content"]
+                            }
+                        }]
+                    }
+
+                # Handle tool_calls (streamed incrementally)
+                if "tool_calls" in delta:
+                    for tool_call_chunk in delta["tool_calls"]:
+                        index = tool_call_chunk.get("index", 0)
+                        if index not in current_tool_calls:
+                            current_tool_calls[index] = {
+                                "id": tool_call_chunk.get("id", ""),
+                                "type": "tool_use",
+                                "name": tool_call_chunk.get("function", {}).get("name", ""),
+                                "input": ""
+                            }
+
+                        # Accumulate arguments
+                        if "function" in tool_call_chunk and "arguments" in tool_call_chunk["function"]:
+                            current_tool_calls[index]["input"] += tool_call_chunk["function"]["arguments"]
+
+                        # Yield OpenAI-format tool call delta
+                        yield {
+                            "choices": [{
+                                "index": 0,
+                                "delta": {
+                                    "tool_calls": [tool_call_chunk]
+                                }
+                            }]
+                        }
+
+            # Final chunk with finish_reason
+            yield {
+                "choices": [{
+                    "index": 0,
+                    "delta": {},
+                    "finish_reason": finish_reason
+                }]
+            }
+
+        except requests.exceptions.Timeout:
+            logger.error("[MOONSHOT] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MOONSHOT] stream response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- sync --------------------
+
+    def _handle_sync_response(self, request_body: dict):
+        """Handle synchronous API response and yield a single result dict."""
+        try:
+            headers = self._build_headers()
+
+            request_body.pop("stream", None)
+            url = f"{self.base_url}/chat/completions"
+            response = requests.post(url, headers=headers, json=request_body, timeout=120)
+
+            if response.status_code != 200:
+                error_msg = response.text
+                logger.error(f"[MOONSHOT] API error: status={response.status_code}, msg={error_msg}")
+                yield {"error": True, "message": error_msg, "status_code": response.status_code}
+                return
+
+            result = response.json()
+            message = result["choices"][0]["message"]
+            finish_reason = result["choices"][0]["finish_reason"]
+
+            response_data = {"role": "assistant", "content": []}
+
+            # Add text content
+            if message.get("content"):
+                response_data["content"].append({
+                    "type": "text",
+                    "text": message["content"]
+                })
+
+            # Add tool calls
+            if message.get("tool_calls"):
+                for tool_call in message["tool_calls"]:
+                    response_data["content"].append({
+                        "type": "tool_use",
+                        "id": tool_call["id"],
+                        "name": tool_call["function"]["name"],
+                        "input": json.loads(tool_call["function"]["arguments"])
+                    })
+
+            # Map finish_reason
+            if finish_reason == "tool_calls":
+                response_data["stop_reason"] = "tool_use"
+            elif finish_reason == "stop":
+                response_data["stop_reason"] = "end_turn"
+            else:
+                response_data["stop_reason"] = finish_reason
+
+            yield response_data
+
+        except requests.exceptions.Timeout:
+            logger.error("[MOONSHOT] Request timeout")
+            yield {"error": True, "message": "Request timeout", "status_code": 500}
+        except Exception as e:
+            logger.error(f"[MOONSHOT] sync response error: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+            yield {"error": True, "message": str(e), "status_code": 500}
+
+    # -------------------- format conversion --------------------
+
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        Convert messages from Claude format to OpenAI format.
+
+        Claude format uses content blocks: tool_use / tool_result / text
+        OpenAI format uses tool_calls in assistant, role=tool for results
+        """
+        if not messages:
+            return []
+
+        converted = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            # Already a simple string – pass through
+            if isinstance(content, str):
+                converted.append(msg)
+                continue
+
+            if not isinstance(content, list):
+                converted.append(msg)
+                continue
+
+            if role == "user":
+                has_tool_result = any(
+                    isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+                )
+                if has_tool_result:
+                    text_parts = []
+                    tool_results = []
+
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_result":
+                            tool_call_id = block.get("tool_use_id") or ""
+                            result_content = block.get("content", "")
+                            if not isinstance(result_content, str):
+                                result_content = json.dumps(result_content, ensure_ascii=False)
+                            tool_results.append({
+                                "role": "tool",
+                                "tool_call_id": tool_call_id,
+                                "content": result_content
+                            })
+
+                    for tr in tool_results:
+                        converted.append(tr)
+
+                    if text_parts:
+                        converted.append({"role": "user", "content": "\n".join(text_parts)})
+                else:
+                    # Keep as-is for multimodal content (e.g. image_url blocks)
+                    converted.append(msg)
+
+            elif role == "assistant":
+                openai_msg = {"role": "assistant"}
+                text_parts = []
+                tool_calls = []
+                reasoning_parts = []
+
+                for block in content:
+                    if not isinstance(block, dict):
+                        continue
+                    if block.get("type") == "text":
+                        text_parts.append(block.get("text", ""))
+                    elif block.get("type") == "tool_use":
+                        tool_calls.append({
+                            "id": block.get("id"),
+                            "type": "function",
+                            "function": {
+                                "name": block.get("name"),
+                                "arguments": json.dumps(block.get("input", {}))
+                            }
+                        })
+                    elif block.get("type") == "thinking":
+                        reasoning_parts.append(block.get("thinking", ""))
+
+                if text_parts:
+                    openai_msg["content"] = "\n".join(text_parts)
+                elif not tool_calls:
+                    openai_msg["content"] = ""
+
+                if tool_calls:
+                    openai_msg["tool_calls"] = tool_calls
+                    if not text_parts:
+                        openai_msg["content"] = None
+
+                # Kimi API requires reasoning_content in assistant messages
+                # when thinking was active for that turn. The presence of
+                # reasoning_parts means thinking was on, so always round-trip it.
+                if reasoning_parts:
+                    openai_msg["reasoning_content"] = "\n".join(reasoning_parts)
+
+                converted.append(openai_msg)
+            else:
+                converted.append(msg)
+
+        return converted
+
+    def _convert_tools_to_openai_format(self, tools):
+        """
+        Convert tools from Claude format to OpenAI format.
+
+        Claude: {name, description, input_schema}
+        OpenAI: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+
+        converted = []
+        for tool in tools:
+            # Already in OpenAI format
+            if "type" in tool and tool["type"] == "function":
+                converted.append(tool)
+            else:
+                converted.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+
+        return converted
diff --git a/models/moonshot/moonshot_session.py b/models/moonshot/moonshot_session.py
new file mode 100644
index 0000000..a5a1842
--- /dev/null
+++ b/models/moonshot/moonshot_session.py
@@ -0,0 +1,51 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class MoonshotSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="moonshot-v1-128k"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens,
+                                                                                       len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/openai/open_ai_bot.py b/models/openai/open_ai_bot.py
new file mode 100644
index 0000000..ef9df3f
--- /dev/null
+++ b/models/openai/open_ai_bot.py
@@ -0,0 +1,164 @@
+# encoding:utf-8
+
+import time
+
+from models.openai.openai_compat import (
+    RateLimitError,
+    Timeout,
+    APIConnectionError,
+    APIError,
+    wrap_http_error,
+)
+from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
+
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.openai.open_ai_image import OpenAIImage
+from models.openai.open_ai_session import OpenAISession
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+
+user_session = dict()
+
+
+# OpenAI对话模型API (可用)
+class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
+    def __init__(self):
+        super().__init__()
+        self._api_key = conf().get("open_ai_api_key")
+        self._api_base = conf().get("open_ai_api_base") or None
+        self._proxy = conf().get("proxy") or None
+        self._http_client = OpenAIHTTPClient(
+            api_key=self._api_key,
+            api_base=self._api_base,
+            proxy=self._proxy,
+        )
+
+        self.sessions = SessionManager(OpenAISession, model=conf().get("model") or "text-davinci-003")
+        self.args = {
+            "model": conf().get("model") or "text-davinci-003",  # 对话模型的名称
+            "temperature": conf().get("temperature", 0.9),  # 值在[0,1]之间，越大表示回复越具有不确定性
+            "max_tokens": 1200,  # 回复最大的字符数
+            "top_p": 1,
+            "frequency_penalty": conf().get("frequency_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            "presence_penalty": conf().get("presence_penalty", 0.0),  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            "request_timeout": conf().get("request_timeout", None),  # 请求超时时间，openai接口默认设置为600，对于难问题一般需要较长时间
+            "timeout": conf().get("request_timeout", None),  # 重试超时时间，在这个时间内，将会自动重试
+            "stop": ["\n\n\n"],
+        }
+    
+    def get_api_config(self):
+        """Get API configuration for OpenAI-compatible base class"""
+        return {
+            'api_key': conf().get("open_ai_api_key"),
+            'api_base': conf().get("open_ai_api_base"),
+            'model': conf().get("model", "text-davinci-003"),
+            'default_temperature': conf().get("temperature", 0.9),
+            'default_top_p': conf().get("top_p", 1.0),
+            'default_frequency_penalty': conf().get("frequency_penalty", 0.0),
+            'default_presence_penalty': conf().get("presence_penalty", 0.0),
+        }
+
+    def _get_http_client(self) -> OpenAIHTTPClient:
+        """Reuse the per-instance HTTP client for the streaming/tool path."""
+        return self._http_client
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context and context.type:
+            if context.type == ContextType.TEXT:
+                logger.info("[OPEN_AI] query={}".format(query))
+                session_id = context["session_id"]
+                reply = None
+                if query == "#清除记忆":
+                    self.sessions.clear_session(session_id)
+                    reply = Reply(ReplyType.INFO, "记忆已清除")
+                elif query == "#清除所有":
+                    self.sessions.clear_all_session()
+                    reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+                else:
+                    session = self.sessions.session_query(query, session_id)
+                    result = self.reply_text(session)
+                    total_tokens, completion_tokens, reply_content = (
+                        result["total_tokens"],
+                        result["completion_tokens"],
+                        result["content"],
+                    )
+                    logger.debug(
+                        "[OPEN_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(str(session), session_id, reply_content, completion_tokens)
+                    )
+
+                    if total_tokens == 0:
+                        reply = Reply(ReplyType.ERROR, reply_content)
+                    else:
+                        self.sessions.session_reply(reply_content, session_id, total_tokens)
+                        reply = Reply(ReplyType.TEXT, reply_content)
+                return reply
+            elif context.type == ContextType.IMAGE_CREATE:
+                ok, retstring = self.create_img(query, 0)
+                reply = None
+                if ok:
+                    reply = Reply(ReplyType.IMAGE_URL, retstring)
+                else:
+                    reply = Reply(ReplyType.ERROR, retstring)
+                return reply
+
+    def reply_text(self, session: OpenAISession, retry_count=0):
+        try:
+            call_args = dict(self.args)
+            timeout = call_args.pop("request_timeout", None) or call_args.pop("timeout", None)
+            response = self._http_client.completions(
+                timeout=timeout,
+                prompt=str(session),
+                **call_args,
+            )
+            res_content = response["choices"][0]["text"].strip().replace("<|endoftext|>", "")
+            total_tokens = response["usage"]["total_tokens"]
+            completion_tokens = response["usage"]["completion_tokens"]
+            logger.info("[OPEN_AI] reply={}".format(res_content))
+            return {
+                "total_tokens": total_tokens,
+                "completion_tokens": completion_tokens,
+                "content": res_content,
+            }
+        except OpenAIHTTPError as http_err:
+            return self._handle_legacy_error(wrap_http_error(http_err), session, retry_count)
+        except Exception as e:
+            return self._handle_legacy_error(e, session, retry_count)
+
+    def _handle_legacy_error(self, e, session, retry_count):
+        """Map exception -> reply for the legacy /completions endpoint."""
+        need_retry = retry_count < 2
+        result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+        if isinstance(e, RateLimitError):
+            logger.warn("[OPEN_AI] RateLimitError: {}".format(e))
+            result["content"] = "提问太快啦，请休息一下再问我吧"
+            if need_retry:
+                time.sleep(20)
+        elif isinstance(e, Timeout):
+            logger.warn("[OPEN_AI] Timeout: {}".format(e))
+            result["content"] = "我没有收到你的消息"
+            if need_retry:
+                time.sleep(5)
+        elif isinstance(e, APIConnectionError):
+            logger.warn("[OPEN_AI] APIConnectionError: {}".format(e))
+            need_retry = False
+            result["content"] = "我连接不到你的网络"
+        else:
+            logger.warn("[OPEN_AI] Exception: {}".format(e))
+            need_retry = False
+            self.sessions.clear_session(session.session_id)
+
+        if need_retry:
+            logger.warn("[OPEN_AI] 第{}次重试".format(retry_count + 1))
+            return self.reply_text(session, retry_count + 1)
+        return result
+
+    # NOTE: Tool-call routing is delegated to OpenAICompatibleBot.call_with_tools,
+    # which calls /chat/completions via our shared HTTP client. The previous
+    # bespoke implementation here bypassed Claude->OpenAI message/tool conversion
+    # and was effectively broken for agent flows; we now inherit the correct
+    # implementation from the base class.
diff --git a/models/openai/open_ai_image.py b/models/openai/open_ai_image.py
new file mode 100644
index 0000000..9683baa
--- /dev/null
+++ b/models/openai/open_ai_image.py
@@ -0,0 +1,62 @@
+import time
+
+from common.log import logger
+from common.token_bucket import TokenBucket
+from config import conf
+from models.openai.openai_compat import RateLimitError, wrap_http_error
+from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
+
+
+# OpenAI image generation API wrapper
+class OpenAIImage(object):
+    def __init__(self):
+        # Lazy default client; subclasses (ChatGPTBot/OpenAIBot) typically
+        # construct their own _http_client and override _get_image_client().
+        self._image_api_key = conf().get("open_ai_api_key")
+        self._image_api_base = conf().get("open_ai_api_base") or None
+        self._image_proxy = conf().get("proxy") or None
+        self._image_client = OpenAIHTTPClient(
+            api_key=self._image_api_key,
+            api_base=self._image_api_base,
+            proxy=self._image_proxy,
+        )
+        if conf().get("rate_limit_dalle"):
+            self.tb4dalle = TokenBucket(conf().get("rate_limit_dalle", 50))
+
+    def create_img(self, query, retry_count=0, api_key=None, api_base=None):
+        try:
+            if conf().get("rate_limit_dalle") and not self.tb4dalle.get_token():
+                return False, "请求太快了，请休息一下再问我吧"
+            logger.info("[OPEN_AI] image_query={}".format(query))
+            response = self._image_client.images_generate(
+                api_key=api_key or None,
+                api_base=api_base or None,
+                prompt=query,  # image description
+                n=1,
+                model=conf().get("text_to_image") or "dall-e-2",
+                # size=conf().get("image_create_size", "256x256"),
+            )
+            image_url = response["data"][0]["url"]
+            logger.info("[OPEN_AI] image_url={}".format(image_url))
+            return True, image_url
+        except OpenAIHTTPError as http_err:
+            mapped = wrap_http_error(http_err)
+            if isinstance(mapped, RateLimitError):
+                logger.warn(mapped)
+                if retry_count < 1:
+                    time.sleep(5)
+                    logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count + 1))
+                    return self.create_img(query, retry_count + 1)
+                return False, "画图出现问题，请休息一下再问我吧"
+            logger.exception(mapped)
+            return False, "画图出现问题，请休息一下再问我吧"
+        except RateLimitError as e:
+            logger.warn(e)
+            if retry_count < 1:
+                time.sleep(5)
+                logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count + 1))
+                return self.create_img(query, retry_count + 1)
+            return False, "画图出现问题，请休息一下再问我吧"
+        except Exception as e:
+            logger.exception(e)
+            return False, "画图出现问题，请休息一下再问我吧"
diff --git a/models/openai/open_ai_session.py b/models/openai/open_ai_session.py
new file mode 100644
index 0000000..76023f8
--- /dev/null
+++ b/models/openai/open_ai_session.py
@@ -0,0 +1,73 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class OpenAISession(Session):
+    def __init__(self, session_id, system_prompt=None, model="text-davinci-003"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def __str__(self):
+        # 构造对话模型的输入
+        """
+        e.g.  Q: xxx
+              A: xxx
+              Q: xxx
+        """
+        prompt = ""
+        for item in self.messages:
+            if item["role"] == "system":
+                prompt += item["content"] + "<|endoftext|>\n\n\n"
+            elif item["role"] == "user":
+                prompt += "Q: " + item["content"] + "\n"
+            elif item["role"] == "assistant":
+                prompt += "\n\nA: " + item["content"] + "<|endoftext|>\n"
+
+        if len(self.messages) > 0 and self.messages[-1]["role"] == "user":
+            prompt += "A: "
+        return prompt
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 1:
+                self.messages.pop(0)
+            elif len(self.messages) == 1 and self.messages[0]["role"] == "assistant":
+                self.messages.pop(0)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = len(str(self))
+                break
+            elif len(self.messages) == 1 and self.messages[0]["role"] == "user":
+                logger.warn("user question exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(conversation)={}".format(max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = len(str(self))
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_string(str(self), self.model)
+
+
+# refer to https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
+def num_tokens_from_string(string: str, model: str) -> int:
+    """Returns the number of tokens in a text string."""
+    import tiktoken
+
+    encoding = tiktoken.encoding_for_model(model)
+    num_tokens = len(encoding.encode(string, disallowed_special=()))
+    return num_tokens
diff --git a/models/openai/openai_compat.py b/models/openai/openai_compat.py
new file mode 100644
index 0000000..099acb5
--- /dev/null
+++ b/models/openai/openai_compat.py
@@ -0,0 +1,163 @@
+"""
+OpenAI-compatible exception layer.
+
+This module used to bridge between openai SDK 0.x and 1.x exception types.
+Since we no longer depend on the `openai` SDK at all (we call HTTP directly
+via :mod:`models.openai.openai_http_client`), this file now provides:
+
+1. Pure Python exception classes that match the *names* the rest of the
+   codebase already imports (RateLimitError / Timeout / APIError /
+   APIConnectionError / AuthenticationError / InvalidRequestError ...).
+2. A :func:`map_http_error` helper that converts an
+   :class:`OpenAIHTTPError` (or any HTTP status code + message) into the
+   appropriate exception subclass, so existing ``except RateLimitError``
+   ``except Timeout`` etc. blocks keep working unchanged.
+
+This keeps the behavior of all existing bots (rate-limit backoff, timeout
+retry, auth-error fast-fail) identical to the openai-SDK-based version, while
+removing the hard dependency on the `openai` package.
+"""
+
+from typing import Optional
+
+
+# --------------------------------------------------------------------------- #
+# Exception hierarchy (mirrors openai SDK names so call sites don't change)
+# --------------------------------------------------------------------------- #
+
+class OpenAIError(Exception):
+    """Base exception for all OpenAI-compatible API errors."""
+
+    def __init__(self, message: str = "", status_code: Optional[int] = None,
+                 body=None):
+        super().__init__(message)
+        self.message = message
+        self.status_code = status_code
+        self.body = body
+
+
+class APIError(OpenAIError):
+    """Generic API error (5xx and unclassified errors)."""
+
+
+class APIConnectionError(OpenAIError):
+    """Network / connection failure (DNS, refused, reset...)."""
+
+
+class Timeout(OpenAIError):
+    """Request timeout. Aliased as APITimeoutError for new-SDK style imports."""
+
+
+class AuthenticationError(OpenAIError):
+    """401 Unauthorized."""
+
+
+class PermissionDeniedError(OpenAIError):
+    """403 Forbidden."""
+
+
+class NotFoundError(OpenAIError):
+    """404 Not Found."""
+
+
+class InvalidRequestError(OpenAIError):
+    """400 Bad Request. Aliased as BadRequestError."""
+
+
+class RateLimitError(OpenAIError):
+    """429 Too Many Requests."""
+
+
+# Aliases used by some new-SDK-style code paths in the project.
+APITimeoutError = Timeout
+BadRequestError = InvalidRequestError
+
+
+# --------------------------------------------------------------------------- #
+# Backward-compat ``error`` module-style accessor
+# --------------------------------------------------------------------------- #
+# Some legacy code in the codebase (and possibly user plugins) does
+#   from models.openai.openai_compat import error
+#   except error.RateLimitError: ...
+# Keep that path working by exposing an attribute namespace.
+class _ErrorModule:
+    OpenAIError = OpenAIError
+    APIError = APIError
+    APIConnectionError = APIConnectionError
+    Timeout = Timeout
+    AuthenticationError = AuthenticationError
+    PermissionDeniedError = PermissionDeniedError
+    NotFoundError = NotFoundError
+    InvalidRequestError = InvalidRequestError
+    RateLimitError = RateLimitError
+
+
+error = _ErrorModule()
+
+
+# --------------------------------------------------------------------------- #
+# HTTP -> exception mapping
+# --------------------------------------------------------------------------- #
+
+def map_http_error(status_code: Optional[int], message: str = "",
+                   body=None) -> OpenAIError:
+    """Convert an HTTP status (+ optional message/body) to the right subclass.
+
+    Used by HTTP-based bot wrappers so that downstream ``except RateLimitError``
+    blocks behave identically to when the openai SDK was raising them.
+    """
+    sc = status_code or 0
+    msg = message or ""
+    msg_lower = msg.lower()
+
+    # Connection-level (no status / non-HTTP failure)
+    if sc == 0:
+        if "timeout" in msg_lower or "timed out" in msg_lower:
+            return Timeout(msg, sc, body)
+        return APIConnectionError(msg, sc, body)
+
+    if sc == 408:
+        return Timeout(msg, sc, body)
+    if sc == 401:
+        return AuthenticationError(msg, sc, body)
+    if sc == 403:
+        return PermissionDeniedError(msg, sc, body)
+    if sc == 404:
+        return NotFoundError(msg, sc, body)
+    if sc == 429:
+        return RateLimitError(msg, sc, body)
+    if 400 <= sc < 500:
+        return InvalidRequestError(msg, sc, body)
+    if sc >= 500:
+        return APIError(msg, sc, body)
+
+    return APIError(msg, sc, body)
+
+
+def wrap_http_error(http_err) -> OpenAIError:
+    """Adapter for :class:`OpenAIHTTPError` -> compat exception subclass.
+
+    Accepts any object with ``status_code`` / ``message`` / ``body`` attrs.
+    """
+    sc = getattr(http_err, "status_code", None)
+    msg = getattr(http_err, "message", "") or str(http_err)
+    body = getattr(http_err, "body", None)
+    return map_http_error(sc, msg, body)
+
+
+__all__ = [
+    "error",
+    "OpenAIError",
+    "APIError",
+    "APIConnectionError",
+    "Timeout",
+    "APITimeoutError",
+    "AuthenticationError",
+    "PermissionDeniedError",
+    "NotFoundError",
+    "InvalidRequestError",
+    "BadRequestError",
+    "RateLimitError",
+    "map_http_error",
+    "wrap_http_error",
+]
diff --git a/models/openai/openai_http_client.py b/models/openai/openai_http_client.py
new file mode 100644
index 0000000..e26d8e6
--- /dev/null
+++ b/models/openai/openai_http_client.py
@@ -0,0 +1,493 @@
+# encoding:utf-8
+
+"""
+Lightweight HTTP client for OpenAI-compatible APIs.
+
+This client is a drop-in replacement for the parts of the `openai` SDK that this
+project actually uses (chat completions, completions, image generation), so we
+can drop the hard dependency on `openai==0.27.x`.
+
+Design goals:
+- Pure `requests` based (no httpx / pydantic / openai SDK dependency).
+- Returns plain `dict` responses with the same shape OpenAI's HTTP API returns,
+  so existing code that does `response["choices"][0]["message"]["content"]` /
+  `response["usage"]["total_tokens"]` keeps working.
+- Streaming yields plain `dict` chunks (parsed SSE `data:` JSON), matching the
+  shape that `agent/protocol/agent_stream.py` consumes:
+    chunk["choices"][0]["delta"]["content" | "tool_calls" | "reasoning_content"]
+    chunk["choices"][0]["finish_reason"]
+  Plus dict-style error chunks: {"error": True, "message": ..., "status_code": ...}
+- Compatible with arbitrary OpenAI-compatible endpoints (LinkAI, Azure-style
+  proxies, DeepSeek, Moonshot, etc.) by allowing per-call api_key / api_base
+  override and trusting whatever path/payload shape the caller passes.
+"""
+
+import json
+from typing import Any, Dict, Generator, Optional
+from urllib.parse import urlparse
+
+import requests
+
+from common.log import logger
+
+
+DEFAULT_API_BASE = "https://api.openai.com/v1"
+DEFAULT_TIMEOUT = 600  # seconds; matches old openai SDK default
+
+
+_APP_TITLE = "CowAgent"
+_APP_REFERER = "https://github.com/zhayujie/CowAgent"
+
+# Per-gateway app attribution headers, only sent when the request host
+# matches a documented gateway. Sending these to user-configured custom
+# proxies would leak app identity, so we dispatch by host suffix.
+_ATTRIBUTION_HEADERS_BY_HOST: Dict[str, Dict[str, str]] = {
+    "openrouter.ai": {
+        "HTTP-Referer": _APP_REFERER,
+        "X-Title": _APP_TITLE,
+    },
+    "ai-gateway.vercel.sh": {
+        "HTTP-Referer": _APP_REFERER,
+        "X-Title": _APP_TITLE,
+    },
+}
+
+
+def _resolve_attribution_headers(url: str) -> Dict[str, str]:
+    try:
+        host = (urlparse(url).hostname or "").lower()
+    except Exception:
+        return {}
+    if not host:
+        return {}
+    for suffix, headers in _ATTRIBUTION_HEADERS_BY_HOST.items():
+        if host == suffix or host.endswith("." + suffix):
+            return dict(headers)
+    return {}
+
+
+class OpenAIHTTPError(Exception):
+    """Raised for non-2xx responses. Carries status code + parsed body."""
+
+    def __init__(self, status_code: int, body: Any, message: str = ""):
+        self.status_code = status_code
+        self.body = body
+        # Try to extract human-readable message from OpenAI-style error envelope
+        if not message and isinstance(body, dict):
+            err = body.get("error") or {}
+            if isinstance(err, dict):
+                message = err.get("message") or ""
+            elif isinstance(err, str):
+                message = err
+        if not message:
+            message = str(body)[:500]
+        self.message = message
+        super().__init__(f"HTTP {status_code}: {message}")
+
+
+class OpenAIHTTPClient:
+    """Minimal HTTP client for OpenAI-compatible endpoints.
+
+    Per-instance defaults (api_key / api_base / proxy / timeout) can be
+    overridden on every call. Callers can also pass ``extra_headers`` for
+    Azure-style ``api-key`` headers or custom routing headers.
+    """
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        proxy: Optional[str] = None,
+        timeout: Optional[float] = None,
+        extra_headers: Optional[Dict[str, str]] = None,
+    ):
+        self.api_key = api_key
+        self.api_base = (api_base or DEFAULT_API_BASE).rstrip("/")
+        self.timeout = timeout if timeout is not None else DEFAULT_TIMEOUT
+        self.proxies = (
+            {"http": proxy, "https": proxy} if proxy else None
+        )
+        self.extra_headers = dict(extra_headers) if extra_headers else {}
+
+    # ------------------------------------------------------------------ #
+    # Public API surface (mirrors what the old openai SDK provided)
+    # ------------------------------------------------------------------ #
+
+    def chat_completions(
+        self,
+        *,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        timeout: Optional[float] = None,
+        proxy: Optional[str] = None,
+        extra_headers: Optional[Dict[str, str]] = None,
+        extra_query: Optional[Dict[str, str]] = None,
+        path: str = "/chat/completions",
+        stream: bool = False,
+        **payload,
+    ):
+        """POST /chat/completions.
+
+        When ``stream=True`` returns a generator yielding parsed SSE chunks
+        (plain ``dict``). On error during streaming, yields a single dict with
+        ``{"error": True, ...}`` and stops, matching the contract expected by
+        ``agent/protocol/agent_stream.py``.
+        """
+        payload["stream"] = stream
+        return self._request(
+            path=path,
+            payload=payload,
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            proxy=proxy,
+            extra_headers=extra_headers,
+            extra_query=extra_query,
+            stream=stream,
+        )
+
+    def completions(
+        self,
+        *,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        timeout: Optional[float] = None,
+        **payload,
+    ) -> Dict[str, Any]:
+        """POST /completions (legacy text completion). Non-streaming only."""
+        payload.pop("stream", None)
+        return self._request(
+            path="/completions",
+            payload=payload,
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            stream=False,
+        )
+
+    def images_generate(
+        self,
+        *,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+        timeout: Optional[float] = None,
+        **payload,
+    ) -> Dict[str, Any]:
+        """POST /images/generations."""
+        return self._request(
+            path="/images/generations",
+            payload=payload,
+            api_key=api_key,
+            api_base=api_base,
+            timeout=timeout,
+            stream=False,
+        )
+
+    # ------------------------------------------------------------------ #
+    # Internal helpers
+    # ------------------------------------------------------------------ #
+
+    def _build_headers(
+        self,
+        api_key: Optional[str],
+        extra_headers: Optional[Dict[str, str]],
+        url: Optional[str] = None,
+    ) -> Dict[str, str]:
+        key = api_key if api_key is not None else self.api_key
+        headers = {"Content-Type": "application/json"}
+        if key:
+            headers["Authorization"] = f"Bearer {key}"
+        if url:
+            attribution = _resolve_attribution_headers(url)
+            if attribution:
+                headers.update(attribution)
+        if self.extra_headers:
+            headers.update(self.extra_headers)
+        if extra_headers:
+            headers.update(extra_headers)
+        return headers
+
+    def _request(
+        self,
+        *,
+        path: str,
+        payload: Dict[str, Any],
+        api_key: Optional[str],
+        api_base: Optional[str],
+        timeout: Optional[float],
+        stream: bool,
+        proxy: Optional[str] = None,
+        extra_headers: Optional[Dict[str, str]] = None,
+        extra_query: Optional[Dict[str, str]] = None,
+    ):
+        base = (api_base or self.api_base).rstrip("/") if api_base else self.api_base
+        url = f"{base}{path}" if path.startswith("/") else f"{base}/{path}"
+        headers = self._build_headers(api_key, extra_headers, url=url)
+        req_timeout = timeout if timeout is not None else self.timeout
+        proxies = (
+            {"http": proxy, "https": proxy} if proxy else self.proxies
+        )
+
+        # Drop None-valued keys; some providers reject explicit nulls.
+        clean_payload = {k: v for k, v in payload.items() if v is not None}
+
+        if stream:
+            # Return a generator. Errors during stream are yielded as a single
+            # error chunk so callers (agent_stream) can map them to their
+            # existing error-handling path without try/except around the loop.
+            return self._stream_chat(
+                url=url,
+                headers=headers,
+                payload=clean_payload,
+                proxies=proxies,
+                timeout=req_timeout,
+                params=extra_query,
+            )
+
+        try:
+            resp = requests.post(
+                url,
+                headers=headers,
+                json=clean_payload,
+                timeout=req_timeout,
+                proxies=proxies,
+                params=extra_query,
+            )
+        except requests.exceptions.Timeout as e:
+            raise OpenAIHTTPError(408, {}, f"Request timed out: {e}")
+        except requests.exceptions.ConnectionError as e:
+            raise OpenAIHTTPError(0, {}, f"Connection error: {e}")
+        except requests.exceptions.RequestException as e:
+            raise OpenAIHTTPError(0, {}, f"Request failed: {e}")
+
+        return self._parse_response(resp)
+
+    @staticmethod
+    def _parse_response(resp: requests.Response) -> Dict[str, Any]:
+        # Try JSON, fall back to text
+        try:
+            data = resp.json()
+        except ValueError:
+            data = {"raw": resp.text}
+
+        if resp.status_code >= 400:
+            raise OpenAIHTTPError(resp.status_code, data)
+
+        return data
+
+    def _stream_chat(
+        self,
+        *,
+        url: str,
+        headers: Dict[str, str],
+        payload: Dict[str, Any],
+        proxies: Optional[Dict[str, str]],
+        timeout: float,
+        params: Optional[Dict[str, str]] = None,
+    ) -> Generator[Dict[str, Any], None, None]:
+        """Stream SSE response and yield parsed JSON chunks.
+
+        Yields:
+            - Normal chunks: dict with ``choices[0].delta`` etc.
+            - Error chunks: ``{"error": True, "message": str, "status_code": int}``
+              followed by termination of the generator.
+        """
+        try:
+            resp = requests.post(
+                url,
+                headers=headers,
+                json=payload,
+                timeout=timeout,
+                proxies=proxies,
+                stream=True,
+                params=params,
+            )
+        except requests.exceptions.Timeout as e:
+            yield self._make_error_chunk(408, f"Request timed out: {e}")
+            return
+        except requests.exceptions.ConnectionError as e:
+            yield self._make_error_chunk(0, f"Connection error: {e}")
+            return
+        except requests.exceptions.RequestException as e:
+            yield self._make_error_chunk(0, f"Request failed: {e}")
+            return
+
+        if resp.status_code >= 400:
+            # Read full body once for error reporting
+            try:
+                body = resp.json()
+            except ValueError:
+                body = {"raw": resp.text[:1000]}
+            err_msg = ""
+            err_code = ""
+            err_type = ""
+            if isinstance(body, dict):
+                err = body.get("error") or {}
+                if isinstance(err, dict):
+                    err_msg = err.get("message") or ""
+                    err_code = err.get("code") or ""
+                    err_type = err.get("type") or ""
+                elif isinstance(err, str):
+                    err_msg = err
+            if not err_msg:
+                err_msg = str(body)[:500]
+            yield {
+                "error": {
+                    "message": err_msg,
+                    "code": err_code,
+                    "type": err_type,
+                },
+                # Top-level fields kept for backward compatibility with the
+                # error-shape that `_handle_stream_response` previously emitted.
+                "message": err_msg,
+                "status_code": resp.status_code,
+            }
+            return
+
+        # IMPORTANT: do NOT use `iter_lines(decode_unicode=True)`.
+        #
+        # `requests` decodes per-network-chunk using the response's declared
+        # encoding (often Latin-1 / ISO-8859-1 for SSE), which mangles UTF-8
+        # codepoints that straddle a chunk boundary. Some upstreams (Azure
+        # OpenAI proxies, Cloudflare-fronted gateways, ...) split TCP chunks
+        # aggressively in the middle of multibyte characters, producing
+        # garbled text and "skip malformed SSE chunk" errors.
+        #
+        # The fix is to read raw bytes, accumulate them until we have a
+        # complete SSE event (terminated by a blank line per the SSE spec:
+        # https://html.spec.whatwg.org/multipage/server-sent-events.html),
+        # and only THEN decode as UTF-8. This mirrors what the official
+        # openai SDK 1.x does in `openai/_streaming.py::SSEDecoder` (which
+        # itself is copied from httpx-sse).
+        try:
+            for sse_event in self._iter_sse_events(resp):
+                # `sse_event` is the joined `data:` payload as a str.
+                if sse_event == "[DONE]":
+                    return
+                if not sse_event:
+                    continue
+                try:
+                    chunk = json.loads(sse_event)
+                except ValueError:
+                    logger.debug(
+                        f"[OpenAIHTTP] skip malformed SSE chunk: {sse_event[:200]}"
+                    )
+                    continue
+                yield chunk
+        except requests.exceptions.ChunkedEncodingError as e:
+            yield self._make_error_chunk(0, f"Stream interrupted: {e}")
+        except requests.exceptions.RequestException as e:
+            yield self._make_error_chunk(0, f"Stream error: {e}")
+        finally:
+            try:
+                resp.close()
+            except Exception:
+                pass
+
+    @staticmethod
+    def _iter_sse_events(resp: requests.Response) -> Generator[str, None, None]:
+        """Decode an SSE byte stream into joined `data:` payloads.
+
+        Implements the subset of the SSE spec that OpenAI / OpenAI-compatible
+        endpoints actually use:
+          - Events are separated by blank lines (\\r\\r, \\n\\n, or \\r\\n\\r\\n).
+          - Within an event, multiple ``data:`` lines are concatenated with
+            "\\n" (per spec).
+          - ``event:``, ``id:``, ``retry:`` and comment lines (``:``) are
+            tolerated but not yielded — for chat-completion we only care
+            about the JSON payload in ``data:``.
+          - Bytes are buffered until a complete event boundary is seen so
+            UTF-8 codepoints split across TCP chunks decode correctly.
+
+        Yields each event's joined ``data`` string. The terminal sentinel
+        ``[DONE]`` is yielded as a literal string so the caller can break.
+        """
+        buf = b""
+        for raw in resp.iter_content(chunk_size=None, decode_unicode=False):
+            if not raw:
+                continue
+            buf += raw
+            # Find complete events (terminated by a blank line).
+            while True:
+                # Look for the earliest event terminator. SSE allows three
+                # forms; check all and pick the earliest match.
+                idx_nn = buf.find(b"\n\n")
+                idx_rr = buf.find(b"\r\r")
+                idx_rnrn = buf.find(b"\r\n\r\n")
+                candidates = [i for i in (idx_nn, idx_rr, idx_rnrn) if i != -1]
+                if not candidates:
+                    break
+                # We need to know the length of the matched terminator to
+                # advance past it correctly.
+                end_pos = min(candidates)
+                if end_pos == idx_rnrn:
+                    term_len = 4
+                else:
+                    term_len = 2
+                event_bytes = buf[:end_pos]
+                buf = buf[end_pos + term_len:]
+
+                # Decode the full event as UTF-8. ``errors="replace"`` is a
+                # belt-and-suspenders safety net for truly malformed upstream
+                # bytes; it should never trigger for well-formed providers.
+                try:
+                    event_text = event_bytes.decode("utf-8")
+                except UnicodeDecodeError:
+                    event_text = event_bytes.decode("utf-8", errors="replace")
+
+                data_lines = []
+                for line in event_text.splitlines():
+                    if not line or line.startswith(":"):
+                        continue
+                    field, _, value = line.partition(":")
+                    # Per SSE spec, a single optional space after the colon
+                    # is part of the framing, not the value.
+                    if value.startswith(" "):
+                        value = value[1:]
+                    if field == "data":
+                        data_lines.append(value)
+                    # Other fields (event/id/retry) are intentionally ignored
+                    # — chat-completion endpoints don't use them in a way we
+                    # need for parsing.
+                if data_lines:
+                    yield "\n".join(data_lines)
+
+        # Flush any trailing bytes the server forgot to terminate. This is
+        # rare but spec-allowed (some providers omit the final \n\n).
+        if buf.strip():
+            try:
+                event_text = buf.decode("utf-8")
+            except UnicodeDecodeError:
+                event_text = buf.decode("utf-8", errors="replace")
+            data_lines = []
+            for line in event_text.splitlines():
+                if not line or line.startswith(":"):
+                    continue
+                field, _, value = line.partition(":")
+                if value.startswith(" "):
+                    value = value[1:]
+                if field == "data":
+                    data_lines.append(value)
+            if data_lines:
+                yield "\n".join(data_lines)
+
+    @staticmethod
+    def _make_error_chunk(status_code: int, message: str) -> Dict[str, Any]:
+        return {
+            "error": {"message": message, "code": "", "type": ""},
+            "message": message,
+            "status_code": status_code,
+        }
+
+
+# A tiny helper for callers that just need a one-shot client without storing
+# state. Keeps call sites cleaner than instantiating the class every time.
+def get_default_client(
+    api_key: Optional[str] = None,
+    api_base: Optional[str] = None,
+    proxy: Optional[str] = None,
+    timeout: Optional[float] = None,
+) -> OpenAIHTTPClient:
+    return OpenAIHTTPClient(
+        api_key=api_key, api_base=api_base, proxy=proxy, timeout=timeout
+    )
diff --git a/models/openai_compatible_bot.py b/models/openai_compatible_bot.py
new file mode 100644
index 0000000..d89690a
--- /dev/null
+++ b/models/openai_compatible_bot.py
@@ -0,0 +1,438 @@
+# encoding:utf-8
+
+"""
+OpenAI-Compatible Bot Base Class
+
+Provides a common implementation for bots that are compatible with OpenAI's API format.
+This includes: OpenAI, LinkAI, Azure OpenAI, and many third-party providers.
+"""
+
+import json
+import requests
+from typing import Optional
+from common.log import logger
+from agent.protocol.message_utils import drop_orphaned_tool_results_openai
+from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
+
+
+class OpenAICompatibleBot:
+    """
+    Base class for OpenAI-compatible bots.
+    
+    Provides common tool calling implementation that can be inherited by:
+    - ChatGPTBot
+    - LinkAIBot  
+    - OpenAIBot
+    - AzureChatGPTBot
+    - Other OpenAI-compatible providers
+    
+    Subclasses only need to override get_api_config() to provide their specific API settings.
+    """
+    
+    def get_api_config(self):
+        """
+        Get API configuration for this bot.
+        
+        Subclasses should override this to provide their specific config.
+        
+        Returns:
+            dict: {
+                'api_key': str,
+                'api_base': str (optional),
+                'model': str,
+                'default_temperature': float,
+                'default_top_p': float,
+                'default_frequency_penalty': float,
+                'default_presence_penalty': float,
+            }
+        """
+        raise NotImplementedError("Subclasses must implement get_api_config()")
+    
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call OpenAI-compatible API with tool support for agent integration
+        
+        This method handles:
+        1. Format conversion (Claude format → OpenAI format)
+        2. System prompt injection
+        3. API calling with proper configuration
+        4. Error handling
+        
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, etc.)
+            
+        Returns:
+            Formatted response in OpenAI format or generator for streaming
+        """
+        try:
+            # Get API configuration from subclass
+            api_config = self.get_api_config()
+            
+            # Convert messages from Claude format to OpenAI format
+            messages = self._convert_messages_to_openai_format(messages)
+            
+            # Convert tools from Claude format to OpenAI format
+            if tools:
+                tools = self._convert_tools_to_openai_format(tools)
+            
+            # Handle system prompt (OpenAI uses system message, Claude uses separate parameter)
+            system_prompt = kwargs.get('system')
+            if system_prompt:
+                # Add system message at the beginning if not already present
+                if not messages or messages[0].get('role') != 'system':
+                    messages = [{"role": "system", "content": system_prompt}] + messages
+                else:
+                    # Replace existing system message
+                    messages[0] = {"role": "system", "content": system_prompt}
+            
+            # Build request parameters
+            model_name = kwargs.get("model", api_config.get('model', 'gpt-5.4'))
+            request_params = {
+                "model": model_name,
+                "messages": messages,
+                "temperature": kwargs.get("temperature", api_config.get('default_temperature', 0.9)),
+                "top_p": kwargs.get("top_p", api_config.get('default_top_p', 1.0)),
+                "frequency_penalty": kwargs.get("frequency_penalty", api_config.get('default_frequency_penalty', 0.0)),
+                "presence_penalty": kwargs.get("presence_penalty", api_config.get('default_presence_penalty', 0.0)),
+                "stream": stream
+            }
+            # GPT-5 / GPT-5.5 / o1 series only accept default temperature/top_p and reject penalty params
+            if model_name in ("gpt-5", "gpt-5-mini", "gpt-5-nano", "gpt-5.5", "o1", "o1-mini"):
+                for key in ("temperature", "top_p", "frequency_penalty", "presence_penalty"):
+                    request_params.pop(key, None)
+            
+            # Add max_tokens if specified
+            if kwargs.get("max_tokens"):
+                request_params["max_tokens"] = kwargs["max_tokens"]
+            
+            # Add tools if provided
+            if tools:
+                request_params["tools"] = tools
+                request_params["tool_choice"] = kwargs.get("tool_choice", "auto")
+            
+            # Make API call with proper configuration
+            api_key = api_config.get('api_key')
+            api_base = api_config.get('api_base')
+            
+            if stream:
+                return self._handle_stream_response(request_params, api_key, api_base)
+            else:
+                return self._handle_sync_response(request_params, api_key, api_base)
+                
+        except Exception as e:
+            error_msg = str(e)
+            logger.error(f"[{self.__class__.__name__}] call_with_tools error: {error_msg}")
+            if stream:
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": error_msg,
+                        "status_code": 500
+                    }
+                return error_generator()
+            else:
+                return {
+                    "error": True,
+                    "message": error_msg,
+                    "status_code": 500
+                }
+    
+    def _get_http_client(self) -> OpenAIHTTPClient:
+        """Build an HTTP client honoring the global proxy config.
+
+        Subclasses can override this for custom auth headers (e.g. Azure's
+        ``api-key`` header) by returning a pre-configured client.
+        """
+        from config import conf
+        proxy = conf().get("proxy") or None
+        return OpenAIHTTPClient(proxy=proxy)
+
+    def _handle_sync_response(self, request_params, api_key, api_base):
+        """Handle synchronous chat-completion via HTTP."""
+        params = dict(request_params)
+        params.pop("stream", None)
+        # Translate legacy SDK timeout kwarg to our HTTP client kwarg.
+        timeout = params.pop("request_timeout", None) or params.pop("timeout", None)
+        try:
+            client = self._get_http_client()
+            return client.chat_completions(
+                api_key=api_key,
+                api_base=api_base,
+                timeout=timeout,
+                stream=False,
+                **params,
+            )
+        except OpenAIHTTPError as e:
+            logger.error(
+                f"[{self.__class__.__name__}] sync response error: "
+                f"HTTP {e.status_code}: {e.message}"
+            )
+            return {
+                "error": True,
+                "message": e.message,
+                "status_code": e.status_code or 500,
+            }
+        except Exception as e:
+            logger.error(f"[{self.__class__.__name__}] sync response error: {e}")
+            return {
+                "error": True,
+                "message": str(e),
+                "status_code": 500,
+            }
+
+    def _handle_stream_response(self, request_params, api_key, api_base):
+        """Handle streaming chat-completion via HTTP (SSE).
+
+        Yields dict chunks in OpenAI's standard streaming shape:
+          {"choices": [{"delta": {...}, "finish_reason": ...}], ...}
+        On error, yields a single ``{"error": ..., "status_code": ...}`` chunk
+        — the same contract :mod:`agent.protocol.agent_stream` already handles.
+        """
+        params = dict(request_params)
+        params.pop("stream", None)
+        timeout = params.pop("request_timeout", None) or params.pop("timeout", None)
+        try:
+            client = self._get_http_client()
+            stream = client.chat_completions(
+                api_key=api_key,
+                api_base=api_base,
+                timeout=timeout,
+                stream=True,
+                **params,
+            )
+            for chunk in stream:
+                yield chunk
+        except OpenAIHTTPError as e:
+            logger.error(
+                f"[{self.__class__.__name__}] stream response error: "
+                f"HTTP {e.status_code}: {e.message}"
+            )
+            yield {
+                "error": True,
+                "message": e.message,
+                "status_code": e.status_code or 500,
+            }
+        except Exception as e:
+            logger.error(f"[{self.__class__.__name__}] stream response error: {e}")
+            yield {
+                "error": True,
+                "message": str(e),
+                "status_code": 500,
+            }
+    
+    def _convert_tools_to_openai_format(self, tools):
+        """
+        Convert tools from Claude format to OpenAI format
+        
+        Claude format: {name, description, input_schema}
+        OpenAI format: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+        
+        openai_tools = []
+        for tool in tools:
+            # Check if already in OpenAI format
+            if 'type' in tool and tool['type'] == 'function':
+                openai_tools.append(tool)
+            else:
+                # Convert from Claude format
+                openai_tools.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+        
+        return openai_tools
+    
+    def _convert_messages_to_openai_format(self, messages):
+        """
+        Convert messages from Claude format to OpenAI format
+
+        Claude content blocks (tool_use / tool_result / thinking) → OpenAI
+        tool_calls / tool role / reasoning_content. Some thinking-mode
+        providers require reasoning_content on assistant messages after a
+        tool_call appears in history; back-fill with empty string when the
+        trace was not captured.
+        """
+        if not messages:
+            return []
+
+        # Detect any prior tool-call turn — gates reasoning_content back-fill below.
+        has_tool_call_history = False
+        for msg in messages:
+            if msg.get("role") != "assistant":
+                continue
+            if msg.get("tool_calls"):
+                has_tool_call_history = True
+                break
+            inner = msg.get("content")
+            if isinstance(inner, list) and any(
+                isinstance(b, dict) and b.get("type") == "tool_use" for b in inner
+            ):
+                has_tool_call_history = True
+                break
+
+        openai_messages = []
+
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+
+            # Handle string content (already in correct format)
+            if isinstance(content, str):
+                if (role == "assistant" and has_tool_call_history
+                        and isinstance(msg, dict)
+                        and "reasoning_content" not in msg):
+                    patched = dict(msg)
+                    patched["reasoning_content"] = ""
+                    openai_messages.append(patched)
+                else:
+                    openai_messages.append(msg)
+                continue
+
+            # Handle list content (Claude format with content blocks)
+            if isinstance(content, list):
+                # Check if this is a tool result message (user role with tool_result blocks)
+                if role == "user" and any(block.get("type") == "tool_result" for block in content):
+                    # Separate text content and tool_result blocks
+                    text_parts = []
+                    tool_results = []
+
+                    for block in content:
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_result":
+                            tool_results.append(block)
+
+                    # First, add tool result messages (must come immediately after assistant with tool_calls)
+                    for block in tool_results:
+                        tool_call_id = block.get("tool_use_id") or ""
+                        if not tool_call_id:
+                            logger.warning(f"[OpenAICompatible] tool_result missing tool_use_id, using empty string")
+                        # Ensure content is a string (some providers require string content)
+                        result_content = block.get("content", "")
+                        if not isinstance(result_content, str):
+                            result_content = json.dumps(result_content, ensure_ascii=False)
+                        openai_messages.append({
+                            "role": "tool",
+                            "tool_call_id": tool_call_id,
+                            "content": result_content
+                        })
+
+                    # Then, add text content as a separate user message if present
+                    if text_parts:
+                        openai_messages.append({
+                            "role": "user",
+                            "content": " ".join(text_parts)
+                        })
+
+                # Check if this is an assistant message with tool_use blocks
+                elif role == "assistant":
+                    text_parts = []
+                    tool_calls = []
+                    reasoning_parts = []
+
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        btype = block.get("type")
+                        if btype == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif btype == "tool_use":
+                            tool_id = block.get("id") or ""
+                            if not tool_id:
+                                logger.warning(f"[OpenAICompatible] tool_use missing id for '{block.get('name')}'")
+                            tool_calls.append({
+                                "id": tool_id,
+                                "type": "function",
+                                "function": {
+                                    "name": block.get("name"),
+                                    "arguments": json.dumps(block.get("input", {}))
+                                }
+                            })
+                        elif btype == "thinking":
+                            reasoning_parts.append(block.get("thinking", ""))
+
+                    # Build OpenAI format assistant message
+                    openai_msg = {
+                        "role": "assistant",
+                        "content": " ".join(text_parts) if text_parts else None
+                    }
+
+                    if tool_calls:
+                        openai_msg["tool_calls"] = tool_calls
+
+                    # Round-trip reasoning_content; empty string when missing
+                    # after a tool-call turn keeps strict providers happy.
+                    if reasoning_parts:
+                        openai_msg["reasoning_content"] = "\n".join(reasoning_parts)
+                    elif has_tool_call_history:
+                        openai_msg["reasoning_content"] = ""
+
+                    if msg.get("_gemini_raw_parts"):
+                        openai_msg["_gemini_raw_parts"] = msg["_gemini_raw_parts"]
+
+                    openai_messages.append(openai_msg)
+                else:
+                    # Other list content, keep as is
+                    openai_messages.append(msg)
+            else:
+                # Other formats, keep as is
+                openai_messages.append(msg)
+
+        return drop_orphaned_tool_results_openai(openai_messages)
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using the OpenAI-compatible /chat/completions endpoint."""
+        try:
+            api_config = self.get_api_config()
+            vision_model = model or api_config.get("model", "gpt-4o")
+            api_key = api_config.get("api_key", "")
+            api_base = (api_config.get("api_base") or "https://api.openai.com/v1").rstrip("/")
+
+            payload = {
+                "model": vision_model,
+                "messages": [{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            }
+            headers = {
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            }
+            resp = requests.post(
+                f"{api_base}/chat/completions",
+                headers=headers, json=payload, timeout=180,
+            )
+            if resp.status_code != 200:
+                body = resp.text[:500]
+                logger.error(f"[{self.__class__.__name__}] call_vision HTTP {resp.status_code}: {body}")
+                return {"error": True, "message": f"HTTP {resp.status_code}: {body}"}
+            data = resp.json()
+            content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+            usage = data.get("usage", {})
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[{self.__class__.__name__}] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
diff --git a/models/qianfan/__init__.py b/models/qianfan/__init__.py
new file mode 100644
index 0000000..1466814
--- /dev/null
+++ b/models/qianfan/__init__.py
@@ -0,0 +1 @@
+# encoding:utf-8
diff --git a/models/qianfan/qianfan_bot.py b/models/qianfan/qianfan_bot.py
new file mode 100644
index 0000000..5bfe657
--- /dev/null
+++ b/models/qianfan/qianfan_bot.py
@@ -0,0 +1,239 @@
+# encoding:utf-8
+
+import time
+
+import requests
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf, load_config
+from models.bot import Bot
+from models.openai_compatible_bot import OpenAICompatibleBot
+from models.session_manager import SessionManager
+from .qianfan_session import QianfanSession
+
+DEFAULT_API_BASE = "https://qianfan.baidubce.com/v2"
+DEFAULT_MODEL = const.ERNIE_5_1
+DEFAULT_VISION_MODEL = const.ERNIE_45_TURBO_VL
+
+# Qianfan models that natively understand images. Other ERNIE variants
+# are text-only and must not receive image payloads.
+_VISION_CAPABLE_MODELS = {
+    const.ERNIE_5_1,
+    const.ERNIE_5,
+    const.ERNIE_X1_1,
+    const.ERNIE_45_TURBO_VL,
+    const.ERNIE_45_TURBO_VL_32K,
+}
+
+
+class QianfanBot(Bot, OpenAICompatibleBot):
+    @property
+    def supports_vision(self) -> bool:
+        """Whether the configured main model is multimodal."""
+        return (conf().get("model") or "").lower() in _VISION_CAPABLE_MODELS
+
+    def __init__(self):
+        super().__init__()
+        model = self._resolve_model()
+        self.sessions = SessionManager(QianfanSession, model=model)
+        self.args = {
+            "model": model,
+            "temperature": conf().get("temperature", 0.7),
+            "top_p": conf().get("top_p", 1.0),
+            "frequency_penalty": conf().get("frequency_penalty", 0.0),
+            "presence_penalty": conf().get("presence_penalty", 0.0),
+        }
+
+    def _resolve_model(self):
+        model = conf().get("model") or DEFAULT_MODEL
+        if model == const.QIANFAN:
+            return DEFAULT_MODEL
+        return model
+
+    @property
+    def api_key(self):
+        return conf().get("qianfan_api_key")
+
+    @property
+    def api_base(self):
+        url = conf().get("qianfan_api_base") or DEFAULT_API_BASE
+        url = url.rstrip("/")
+        suffix = "/chat/completions"
+        if url.endswith(suffix):
+            url = url[:-len(suffix)]
+        return url.rstrip("/")
+
+    def get_api_config(self):
+        return {
+            "api_key": self.api_key,
+            "api_base": self.api_base,
+            "model": self._resolve_model(),
+            "default_temperature": conf().get("temperature", 0.7),
+            "default_top_p": conf().get("top_p", 1.0),
+            "default_frequency_penalty": conf().get("frequency_penalty", 0.0),
+            "default_presence_penalty": conf().get("presence_penalty", 0.0),
+        }
+
+    def _build_headers(self):
+        return {
+            "Content-Type": "application/json",
+            "Authorization": "Bearer {}".format(self.api_key),
+        }
+
+    def reply(self, query, context=None):
+        if context.type == ContextType.TEXT:
+            logger.info("[QIANFAN] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[QIANFAN] session query={}".format(session.messages))
+
+            reply_content = self.reply_text(session, args=self.args.copy())
+            logger.debug(
+                "[QIANFAN] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(
+                    reply_content["content"], session_id, reply_content["total_tokens"],
+                )
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[QIANFAN] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session, args=None, retry_count=0):
+        try:
+            body = dict(args) if args else dict(self.args)
+            body["messages"] = session.messages
+            response = requests.post(
+                "{}/chat/completions".format(self.api_base),
+                headers=self._build_headers(),
+                json=body,
+                timeout=conf().get("request_timeout", 180),
+            )
+            if response.status_code == 200:
+                data = response.json()
+                return {
+                    "total_tokens": data["usage"]["total_tokens"],
+                    "completion_tokens": data["usage"]["completion_tokens"],
+                    "content": data["choices"][0]["message"]["content"],
+                }
+            return self._error_result(response, session, args, retry_count)
+        except Exception as e:
+            logger.exception(e)
+            if retry_count < 2:
+                return self.reply_text(session, args, retry_count + 1)
+            return {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+
+    def call_vision(self, image_url: str, question: str,
+                    model: str = None, max_tokens: int = 1000) -> dict:
+        vision_model = model or DEFAULT_VISION_MODEL
+        payload = {
+            "model": vision_model,
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }
+            ],
+            "max_tokens": max_tokens,
+        }
+
+        try:
+            response = requests.post(
+                "{}/chat/completions".format(self.api_base),
+                headers=self._build_headers(),
+                json=payload,
+                timeout=conf().get("request_timeout", 180),
+            )
+            if response.status_code != 200:
+                err = self._error_result(response, None)
+                return {
+                    "error": True,
+                    "message": err.get("content", "Qianfan vision request failed"),
+                }
+
+            data = response.json()
+            choices = data.get("choices", [])
+            content = choices[0].get("message", {}).get("content", "") if choices else ""
+            usage = data.get("usage", {}) or {}
+            return {
+                "content": content,
+                "model": data.get("model", vision_model),
+                "usage": {
+                    "prompt_tokens": usage.get("prompt_tokens", 0),
+                    "completion_tokens": usage.get("completion_tokens", 0),
+                    "total_tokens": usage.get("total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.exception(e)
+            return {"error": True, "message": str(e)}
+
+    def _error_result(self, response, session, args=None, retry_count=0):
+        try:
+            body = response.json()
+        except ValueError:
+            body = {"raw": response.text}
+
+        error = body.get("error") if isinstance(body, dict) else None
+        if isinstance(error, dict):
+            message = error.get("message") or str(error)
+        elif error:
+            message = str(error)
+        elif isinstance(body, dict) and body.get("raw") is not None:
+            message = str(body.get("raw"))
+        else:
+            message = str(body)
+
+        logger.error(
+            "[QIANFAN] chat failed, status_code={}, msg={}".format(
+                response.status_code, message
+            )
+        )
+
+        if response.status_code >= 500 and retry_count < 2:
+            time.sleep(3)
+            return self.reply_text(session, args, retry_count + 1)
+
+        if response.status_code == 401:
+            content = "授权失败，请检查 Qianfan API Key 是否正确"
+        elif response.status_code == 429:
+            if retry_count < 2:
+                time.sleep(3)
+                return self.reply_text(session, args, retry_count + 1)
+            content = "请求过于频繁，请稍后再试"
+        else:
+            content = "请求失败：{}".format(message)
+
+        return {"completion_tokens": 0, "content": content}
diff --git a/models/qianfan/qianfan_session.py b/models/qianfan/qianfan_session.py
new file mode 100644
index 0000000..5bf5d03
--- /dev/null
+++ b/models/qianfan/qianfan_session.py
@@ -0,0 +1,57 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class QianfanSession(Session):
+    def __init__(self, session_id, system_prompt=None, model="ernie-5.1"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(
+                    max_tokens, cur_tokens, len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        content = msg.get("content", "")
+        if isinstance(content, str):
+            tokens += len(content)
+        elif isinstance(content, list):
+            for block in content:
+                if isinstance(block, dict):
+                    tokens += len(block.get("text", ""))
+    return tokens
diff --git a/models/session_manager.py b/models/session_manager.py
new file mode 100644
index 0000000..a6e89f9
--- /dev/null
+++ b/models/session_manager.py
@@ -0,0 +1,91 @@
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from config import conf
+
+
+class Session(object):
+    def __init__(self, session_id, system_prompt=None):
+        self.session_id = session_id
+        self.messages = []
+        if system_prompt is None:
+            self.system_prompt = conf().get("character_desc", "")
+        else:
+            self.system_prompt = system_prompt
+
+    # 重置会话
+    def reset(self):
+        system_item = {"role": "system", "content": self.system_prompt}
+        self.messages = [system_item]
+
+    def set_system_prompt(self, system_prompt):
+        self.system_prompt = system_prompt
+        self.reset()
+
+    def add_query(self, query):
+        user_item = {"role": "user", "content": query}
+        self.messages.append(user_item)
+
+    def add_reply(self, reply):
+        assistant_item = {"role": "assistant", "content": reply}
+        self.messages.append(assistant_item)
+
+    def discard_exceeding(self, max_tokens=None, cur_tokens=None):
+        raise NotImplementedError
+
+    def calc_tokens(self):
+        raise NotImplementedError
+
+
+class SessionManager(object):
+    def __init__(self, sessioncls, **session_args):
+        if conf().get("expires_in_seconds"):
+            sessions = ExpiredDict(conf().get("expires_in_seconds"))
+        else:
+            sessions = dict()
+        self.sessions = sessions
+        self.sessioncls = sessioncls
+        self.session_args = session_args
+
+    def build_session(self, session_id, system_prompt=None):
+        """
+        如果session_id不在sessions中，创建一个新的session并添加到sessions中
+        如果system_prompt不会空，会更新session的system_prompt并重置session
+        """
+        if session_id is None:
+            return self.sessioncls(session_id, system_prompt, **self.session_args)
+
+        if session_id not in self.sessions:
+            self.sessions[session_id] = self.sessioncls(session_id, system_prompt, **self.session_args)
+        elif system_prompt is not None:  # 如果有新的system_prompt，更新并重置session
+            self.sessions[session_id].set_system_prompt(system_prompt)
+        session = self.sessions[session_id]
+        return session
+
+    def session_query(self, query, session_id):
+        session = self.build_session(session_id)
+        session.add_query(query)
+        try:
+            max_tokens = conf().get("conversation_max_tokens", 1000)
+            total_tokens = session.discard_exceeding(max_tokens, None)
+            logger.debug("prompt tokens used={}".format(total_tokens))
+        except Exception as e:
+            logger.warning("Exception when counting tokens precisely for prompt: {}".format(str(e)))
+        return session
+
+    def session_reply(self, reply, session_id, total_tokens=None):
+        session = self.build_session(session_id)
+        session.add_reply(reply)
+        try:
+            max_tokens = conf().get("conversation_max_tokens", 1000)
+            tokens_cnt = session.discard_exceeding(max_tokens, total_tokens)
+            logger.debug("raw total_tokens={}, savesession tokens={}".format(total_tokens, tokens_cnt))
+        except Exception as e:
+            logger.warning("Exception when counting tokens precisely for session: {}".format(str(e)))
+        return session
+
+    def clear_session(self, session_id):
+        if session_id in self.sessions:
+            del self.sessions[session_id]
+
+    def clear_all_session(self):
+        self.sessions.clear()
diff --git a/models/xunfei/xunfei_spark_bot.py b/models/xunfei/xunfei_spark_bot.py
new file mode 100644
index 0000000..d2662f9
--- /dev/null
+++ b/models/xunfei/xunfei_spark_bot.py
@@ -0,0 +1,269 @@
+# encoding:utf-8
+
+import requests, json
+from models.bot import Bot
+from models.session_manager import SessionManager
+from models.chatgpt.chat_gpt_session import ChatGPTSession
+from bridge.context import ContextType, Context
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from common import const
+import time
+import _thread as thread
+import datetime
+from datetime import datetime
+from wsgiref.handlers import format_date_time
+from urllib.parse import urlencode
+import base64
+import ssl
+import hashlib
+import hmac
+import json
+from time import mktime
+from urllib.parse import urlparse
+import websocket
+import queue
+import threading
+import random
+
+# 消息队列 map
+queue_map = dict()
+
+# 响应队列 map
+reply_map = dict()
+
+
+class XunFeiBot(Bot):
+    def __init__(self):
+        super().__init__()
+        self.app_id = conf().get("xunfei_app_id")
+        self.api_key = conf().get("xunfei_api_key")
+        self.api_secret = conf().get("xunfei_api_secret")
+        # 默认使用v2.0版本: "generalv2"
+        # Spark Lite请求地址(spark_url): wss://spark-api.xf-yun.com/v1.1/chat, 对应的domain参数为: "lite"
+        # Spark V2.0请求地址(spark_url): wss://spark-api.xf-yun.com/v2.1/chat, 对应的domain参数为: "generalv2"
+        # Spark Pro 请求地址(spark_url): wss://spark-api.xf-yun.com/v3.1/chat, 对应的domain参数为: "generalv3"
+        # Spark Pro-128K请求地址(spark_url):  wss://spark-api.xf-yun.com/chat/pro-128k, 对应的domain参数为: "pro-128k"
+        # Spark Max 请求地址(spark_url): wss://spark-api.xf-yun.com/v3.5/chat, 对应的domain参数为: "generalv3.5"
+        # Spark4.0 Ultra 请求地址(spark_url): wss://spark-api.xf-yun.com/v4.0/chat, 对应的domain参数为: "4.0Ultra"
+        # 后续模型更新，对应的参数可以参考官网文档获取：https://www.xfyun.cn/doc/spark/Web.html
+        self.domain = conf().get("xunfei_domain", "generalv3.5")
+        self.spark_url = conf().get("xunfei_spark_url", "wss://spark-api.xf-yun.com/v3.5/chat")
+        self.host = urlparse(self.spark_url).netloc
+        self.path = urlparse(self.spark_url).path
+        # 和wenxin使用相同的session机制
+        self.sessions = SessionManager(ChatGPTSession, model=const.XUNFEI)
+
+    def reply(self, query, context: Context = None) -> Reply:
+        if context.type == ContextType.TEXT:
+            logger.info("[XunFei] query={}".format(query))
+            session_id = context["session_id"]
+            request_id = self.gen_request_id(session_id)
+            reply_map[request_id] = ""
+            session = self.sessions.session_query(query, session_id)
+            threading.Thread(target=self.create_web_socket,
+                             args=(session.messages, request_id)).start()
+            depth = 0
+            time.sleep(0.1)
+            t1 = time.time()
+            usage = {}
+            while depth <= 300:
+                try:
+                    data_queue = queue_map.get(request_id)
+                    if not data_queue:
+                        depth += 1
+                        time.sleep(0.1)
+                        continue
+                    data_item = data_queue.get(block=True, timeout=0.1)
+                    if data_item.is_end:
+                        # 请求结束
+                        del queue_map[request_id]
+                        if data_item.reply:
+                            reply_map[request_id] += data_item.reply
+                        usage = data_item.usage
+                        break
+
+                    reply_map[request_id] += data_item.reply
+                    depth += 1
+                except Exception as e:
+                    depth += 1
+                    continue
+            t2 = time.time()
+            logger.info(
+                f"[XunFei-API] response={reply_map[request_id]}, time={t2 - t1}s, usage={usage}"
+            )
+            self.sessions.session_reply(reply_map[request_id], session_id,
+                                        usage.get("total_tokens"))
+            reply = Reply(ReplyType.TEXT, reply_map[request_id])
+            del reply_map[request_id]
+            return reply
+        else:
+            reply = Reply(ReplyType.ERROR,
+                          "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def create_web_socket(self, prompt, session_id, temperature=0.5):
+        logger.info(f"[XunFei] start connect, prompt={prompt}")
+        websocket.enableTrace(False)
+        wsUrl = self.create_url()
+        ws = websocket.WebSocketApp(wsUrl,
+                                    on_message=on_message,
+                                    on_error=on_error,
+                                    on_close=on_close,
+                                    on_open=on_open)
+        data_queue = queue.Queue(1000)
+        queue_map[session_id] = data_queue
+        ws.appid = self.app_id
+        ws.question = prompt
+        ws.domain = self.domain
+        ws.session_id = session_id
+        ws.temperature = temperature
+        ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})
+
+    def gen_request_id(self, session_id: str):
+        return session_id + "_" + str(int(time.time())) + "" + str(
+            random.randint(0, 100))
+
+    # 生成url
+    def create_url(self):
+        # 生成RFC1123格式的时间戳
+        now = datetime.now()
+        date = format_date_time(mktime(now.timetuple()))
+
+        # 拼接字符串
+        signature_origin = "host: " + self.host + "\n"
+        signature_origin += "date: " + date + "\n"
+        signature_origin += "GET " + self.path + " HTTP/1.1"
+
+        # 进行hmac-sha256进行加密
+        signature_sha = hmac.new(self.api_secret.encode('utf-8'),
+                                 signature_origin.encode('utf-8'),
+                                 digestmod=hashlib.sha256).digest()
+
+        signature_sha_base64 = base64.b64encode(signature_sha).decode(
+            encoding='utf-8')
+
+        authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", ' \
+                               f'signature="{signature_sha_base64}"'
+
+        authorization = base64.b64encode(
+            authorization_origin.encode('utf-8')).decode(encoding='utf-8')
+
+        # 将请求的鉴权参数组合为字典
+        v = {"authorization": authorization, "date": date, "host": self.host}
+        # 拼接鉴权参数，生成url
+        url = self.spark_url + '?' + urlencode(v)
+        # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致
+        return url
+
+    def gen_params(self, appid, domain, question):
+        """
+        通过appid和用户的提问来生成请参数
+        """
+        data = {
+            "header": {
+                "app_id": appid,
+                "uid": "1234"
+            },
+            "parameter": {
+                "chat": {
+                    "domain": domain,
+                    "random_threshold": 0.5,
+                    "max_tokens": 2048,
+                    "auditing": "default"
+                }
+            },
+            "payload": {
+                "message": {
+                    "text": question
+                }
+            }
+        }
+        return data
+
+
+class ReplyItem:
+    def __init__(self, reply, usage=None, is_end=False):
+        self.is_end = is_end
+        self.reply = reply
+        self.usage = usage
+
+
+# 收到websocket错误的处理
+def on_error(ws, error):
+    logger.error(f"[XunFei] error: {str(error)}")
+
+
+# 收到websocket关闭的处理
+def on_close(ws, one, two):
+    data_queue = queue_map.get(ws.session_id)
+    data_queue.put("END")
+
+
+# 收到websocket连接建立的处理
+def on_open(ws):
+    logger.info(f"[XunFei] Start websocket, session_id={ws.session_id}")
+    thread.start_new_thread(run, (ws, ))
+
+
+def run(ws, *args):
+    data = json.dumps(
+        gen_params(appid=ws.appid,
+                   domain=ws.domain,
+                   question=ws.question,
+                   temperature=ws.temperature))
+    ws.send(data)
+
+
+# Websocket 操作
+# 收到websocket消息的处理
+def on_message(ws, message):
+    data = json.loads(message)
+    code = data['header']['code']
+    if code != 0:
+        logger.error(f'请求错误: {code}, {data}')
+        ws.close()
+    else:
+        choices = data["payload"]["choices"]
+        status = choices["status"]
+        content = choices["text"][0]["content"]
+        data_queue = queue_map.get(ws.session_id)
+        if not data_queue:
+            logger.error(
+                f"[XunFei] can't find data queue, session_id={ws.session_id}")
+            return
+        reply_item = ReplyItem(content)
+        if status == 2:
+            usage = data["payload"].get("usage")
+            reply_item = ReplyItem(content, usage)
+            reply_item.is_end = True
+            ws.close()
+        data_queue.put(reply_item)
+
+
+def gen_params(appid, domain, question, temperature=0.5):
+    """
+    通过appid和用户的提问来生成请参数
+    """
+    data = {
+        "header": {
+            "app_id": appid,
+            "uid": "1234"
+        },
+        "parameter": {
+            "chat": {
+                "domain": domain,
+                "temperature": temperature,
+                "random_threshold": 0.5,
+                "max_tokens": 2048,
+                "auditing": "default"
+            }
+        },
+        "payload": {
+            "message": {
+                "text": question
+            }
+        }
+    }
+    return data
diff --git a/models/zhipuai/zhipu_ai_image.py b/models/zhipuai/zhipu_ai_image.py
new file mode 100644
index 0000000..57ac3a7
--- /dev/null
+++ b/models/zhipuai/zhipu_ai_image.py
@@ -0,0 +1,36 @@
+from common.log import logger
+from config import conf
+
+
+# ZhipuAI提供的画图接口
+
+class ZhipuAIImage(object):
+    def __init__(self):
+        from zai import ZhipuAiClient
+        # 初始化客户端，支持自定义 API base URL（例如智谱国际版 z.ai）
+        api_key = conf().get("zhipu_ai_api_key")
+        api_base = conf().get("zhipu_ai_api_base")
+        
+        if api_base:
+            self.client = ZhipuAiClient(api_key=api_key, base_url=api_base)
+        else:
+            self.client = ZhipuAiClient(api_key=api_key)
+
+    def create_img(self, query, retry_count=0, api_key=None, api_base=None):
+        try:
+            if conf().get("rate_limit_dalle"):
+                return False, "请求太快了，请休息一下再问我吧"
+            logger.info("[ZHIPU_AI] image_query={}".format(query))
+            response = self.client.images.generations(
+                prompt=query,
+                n=1,  # 每次生成图片的数量
+                model=conf().get("text_to_image") or "cogview-3",
+                size=conf().get("image_create_size", "1024x1024"),  # 图片大小,可选有 256x256, 512x512, 1024x1024
+                quality="standard",
+            )
+            image_url = response.data[0].url
+            logger.info("[ZHIPU_AI] image_url={}".format(image_url))
+            return True, image_url
+        except Exception as e:
+            logger.exception(e)
+            return False, "画图出现问题，请休息一下再问我吧"
diff --git a/models/zhipuai/zhipu_ai_session.py b/models/zhipuai/zhipu_ai_session.py
new file mode 100644
index 0000000..afb30cc
--- /dev/null
+++ b/models/zhipuai/zhipu_ai_session.py
@@ -0,0 +1,53 @@
+from models.session_manager import Session
+from common.log import logger
+
+
+class ZhipuAISession(Session):
+    def __init__(self, session_id, system_prompt=None, model="glm-4"):
+        super().__init__(session_id, system_prompt)
+        self.model = model
+        self.reset()
+        if not system_prompt:
+            logger.warn("[ZhiPu] `character_desc` can not be empty")
+
+    def discard_exceeding(self, max_tokens, cur_tokens=None):
+        precise = True
+        try:
+            cur_tokens = self.calc_tokens()
+        except Exception as e:
+            precise = False
+            if cur_tokens is None:
+                raise e
+            logger.debug("Exception when counting tokens precisely for query: {}".format(e))
+        while cur_tokens > max_tokens:
+            if len(self.messages) > 2:
+                self.messages.pop(1)
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "assistant":
+                self.messages.pop(1)
+                if precise:
+                    cur_tokens = self.calc_tokens()
+                else:
+                    cur_tokens = cur_tokens - max_tokens
+                break
+            elif len(self.messages) == 2 and self.messages[1]["role"] == "user":
+                logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens))
+                break
+            else:
+                logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens,
+                                                                                       len(self.messages)))
+                break
+            if precise:
+                cur_tokens = self.calc_tokens()
+            else:
+                cur_tokens = cur_tokens - max_tokens
+        return cur_tokens
+
+    def calc_tokens(self):
+        return num_tokens_from_messages(self.messages, self.model)
+
+
+def num_tokens_from_messages(messages, model):
+    tokens = 0
+    for msg in messages:
+        tokens += len(msg["content"])
+    return tokens
diff --git a/models/zhipuai/zhipuai_bot.py b/models/zhipuai/zhipuai_bot.py
new file mode 100644
index 0000000..98ea5db
--- /dev/null
+++ b/models/zhipuai/zhipuai_bot.py
@@ -0,0 +1,500 @@
+# encoding:utf-8
+
+import time
+import json
+from typing import Optional
+
+from models.bot import Bot
+from models.zhipuai.zhipu_ai_session import ZhipuAISession
+from models.zhipuai.zhipu_ai_image import ZhipuAIImage
+from models.session_manager import SessionManager
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf, load_config
+from zai import ZhipuAiClient
+
+
+# ZhipuAI对话模型API
+class ZHIPUAIBot(Bot, ZhipuAIImage):
+    def __init__(self):
+        super().__init__()
+        self.sessions = SessionManager(ZhipuAISession, model=conf().get("model") or "ZHIPU_AI")
+        self.args = {
+            "model": conf().get("model") or "glm-4",  # 对话模型的名称
+            "temperature": conf().get("temperature", 0.9),  # 值在(0,1)之间(智谱AI 的温度不能取 0 或者 1)
+            "top_p": conf().get("top_p", 0.7),  # 值在(0,1)之间(智谱AI 的 top_p 不能取 0 或者 1)
+        }
+        # 初始化客户端，支持自定义 API base URL（例如智谱国际版 z.ai）
+        api_key = conf().get("zhipu_ai_api_key")
+        api_base = conf().get("zhipu_ai_api_base")
+        
+        if api_base:
+            self.client = ZhipuAiClient(api_key=api_key, base_url=api_base)
+        else:
+            self.client = ZhipuAiClient(api_key=api_key)
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if context.type == ContextType.TEXT:
+            logger.info("[ZHIPU_AI] query={}".format(query))
+
+            session_id = context["session_id"]
+            reply = None
+            clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
+            if query in clear_memory_commands:
+                self.sessions.clear_session(session_id)
+                reply = Reply(ReplyType.INFO, "记忆已清除")
+            elif query == "#清除所有":
+                self.sessions.clear_all_session()
+                reply = Reply(ReplyType.INFO, "所有人记忆已清除")
+            elif query == "#更新配置":
+                load_config()
+                reply = Reply(ReplyType.INFO, "配置已更新")
+            if reply:
+                return reply
+            session = self.sessions.session_query(query, session_id)
+            logger.debug("[ZHIPU_AI] session query={}".format(session.messages))
+
+            model = context.get("gpt_model")
+            new_args = None
+            if model:
+                new_args = self.args.copy()
+                new_args["model"] = model
+
+            reply_content = self.reply_text(session, args=new_args)
+            logger.debug(
+                "[ZHIPU_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
+                    session.messages,
+                    session_id,
+                    reply_content["content"],
+                    reply_content["completion_tokens"],
+                )
+            )
+            if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+            elif reply_content["completion_tokens"] > 0:
+                self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
+                reply = Reply(ReplyType.TEXT, reply_content["content"])
+            else:
+                reply = Reply(ReplyType.ERROR, reply_content["content"])
+                logger.debug("[ZHIPU_AI] reply {} used 0 tokens.".format(reply_content))
+            return reply
+        elif context.type == ContextType.IMAGE_CREATE:
+            ok, retstring = self.create_img(query, 0)
+            reply = None
+            if ok:
+                reply = Reply(ReplyType.IMAGE_URL, retstring)
+            else:
+                reply = Reply(ReplyType.ERROR, retstring)
+            return reply
+
+        else:
+            reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
+            return reply
+
+    def reply_text(self, session: ZhipuAISession, args=None, retry_count=0) -> dict:
+        """
+        Call ZhipuAI API to get the answer
+        :param session: a conversation session
+        :param args: request arguments
+        :param retry_count: retry count
+        :return: {}
+        """
+        try:
+            if args is None:
+                args = self.args
+            response = self.client.chat.completions.create(messages=session.messages, **args)
+            # logger.debug("[ZHIPU_AI] response={}".format(response))
+            # logger.info("[ZHIPU_AI] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
+
+            return {
+                "total_tokens": response.usage.total_tokens,
+                "completion_tokens": response.usage.completion_tokens,
+                "content": response.choices[0].message.content,
+            }
+        except Exception as e:
+            need_retry = retry_count < 2
+            result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
+            error_str = str(e).lower()
+            
+            # Check error type by error message content
+            if "rate" in error_str and "limit" in error_str:
+                logger.warn("[ZHIPU_AI] RateLimitError: {}".format(e))
+                result["content"] = "提问太快啦，请休息一下再问我吧"
+                if need_retry:
+                    time.sleep(20)
+            elif "timeout" in error_str or "timed out" in error_str:
+                logger.warn("[ZHIPU_AI] Timeout: {}".format(e))
+                result["content"] = "我没有收到你的消息"
+                if need_retry:
+                    time.sleep(5)
+            elif "api" in error_str and ("error" in error_str or "gateway" in error_str):
+                logger.warn("[ZHIPU_AI] APIError: {}".format(e))
+                result["content"] = "请再问我一次"
+                if need_retry:
+                    time.sleep(10)
+            elif "connection" in error_str or "network" in error_str:
+                logger.warn("[ZHIPU_AI] ConnectionError: {}".format(e))
+                result["content"] = "我连接不到你的网络"
+                if need_retry:
+                    time.sleep(5)
+            else:
+                logger.exception("[ZHIPU_AI] Exception: {}".format(e), e)
+                need_retry = False
+                self.sessions.clear_session(session.session_id)
+
+            if need_retry:
+                logger.warn("[ZHIPU_AI] 第{}次重试".format(retry_count + 1))
+                return self.reply_text(session, args, retry_count + 1)
+            else:
+                return result
+
+    def call_vision(self, image_url: str, question: str,
+                    model: Optional[str] = None,
+                    max_tokens: int = 1000) -> dict:
+        """Analyze an image using ZhipuAI OpenAI-compatible SDK.
+        Always uses glm-5v-turbo — the text models (glm-5-turbo etc.) do not support vision.
+        """
+        try:
+            vision_model = "glm-5v-turbo"
+            response = self.client.chat.completions.create(
+                model=vision_model,
+                max_tokens=max_tokens,
+                messages=[{
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": question},
+                        {"type": "image_url", "image_url": {"url": image_url}},
+                    ],
+                }],
+            )
+            content = response.choices[0].message.content or ""
+            usage = response.usage
+            return {
+                "model": vision_model,
+                "content": content,
+                "usage": {
+                    "prompt_tokens": getattr(usage, "prompt_tokens", 0),
+                    "completion_tokens": getattr(usage, "completion_tokens", 0),
+                    "total_tokens": getattr(usage, "total_tokens", 0),
+                },
+            }
+        except Exception as e:
+            logger.error(f"[ZHIPU_AI] call_vision error: {e}")
+            return {"error": True, "message": str(e)}
+
+    def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
+        """
+        Call ZhipuAI API with tool support for agent integration
+        
+        This method handles:
+        1. Format conversion (Claude format → ZhipuAI format)
+        2. System prompt injection
+        3. API calling with ZhipuAI SDK
+        4. Tool stream support (tool_stream=True for GLM-4.7)
+        
+        Args:
+            messages: List of messages (may be in Claude format from agent)
+            tools: List of tool definitions (may be in Claude format from agent)
+            stream: Whether to use streaming
+            **kwargs: Additional parameters (max_tokens, temperature, system, etc.)
+            
+        Returns:
+            Formatted response or generator for streaming
+        """
+        try:
+            # Convert messages from Claude format to ZhipuAI format
+            messages = self._convert_messages_to_zhipu_format(messages)
+            
+            # Convert tools from Claude format to ZhipuAI format
+            if tools:
+                tools = self._convert_tools_to_zhipu_format(tools)
+            
+            # Handle system prompt
+            system_prompt = kwargs.get('system')
+            if system_prompt:
+                # Add system message at the beginning if not already present
+                if not messages or messages[0].get('role') != 'system':
+                    messages = [{"role": "system", "content": system_prompt}] + messages
+                else:
+                    # Replace existing system message
+                    messages[0] = {"role": "system", "content": system_prompt}
+            
+            # Build request parameters
+            request_params = {
+                "model": kwargs.get("model", self.args.get("model", "glm-4")),
+                "messages": messages,
+                "temperature": kwargs.get("temperature", self.args.get("temperature", 0.9)),
+                "top_p": kwargs.get("top_p", self.args.get("top_p", 0.7)),
+                "stream": stream
+            }
+            
+            # Add max_tokens if specified
+            if kwargs.get("max_tokens"):
+                request_params["max_tokens"] = kwargs["max_tokens"]
+            
+            # Add tools if provided
+            if tools:
+                request_params["tools"] = tools
+                # GLM-4.7 with zai-sdk supports tool_stream for streaming tool calls
+                if stream:
+                    request_params["tool_stream"] = kwargs.get("tool_stream", True)
+            
+            # Add thinking parameter for deep thinking mode (GLM-4.7)
+            thinking = kwargs.get("thinking")
+            if thinking:
+                request_params["thinking"] = thinking
+            elif "glm-4.7" in request_params["model"]:
+                # Enable thinking by default for GLM-4.7
+                request_params["thinking"] = {"type": "disabled"}
+            
+            # Make API call with ZhipuAI SDK
+            if stream:
+                return self._handle_stream_response(request_params)
+            else:
+                return self._handle_sync_response(request_params)
+                
+        except Exception as e:
+            error_msg = str(e)
+            logger.error(f"[ZHIPU_AI] call_with_tools error: {error_msg}")
+            if stream:
+                def error_generator():
+                    yield {
+                        "error": True,
+                        "message": error_msg,
+                        "status_code": 500
+                    }
+                return error_generator()
+            else:
+                return {
+                    "error": True,
+                    "message": error_msg,
+                    "status_code": 500
+                }
+    
+    def _handle_sync_response(self, request_params):
+        """Handle synchronous ZhipuAI API response"""
+        try:
+            response = self.client.chat.completions.create(**request_params)
+            
+            # Convert ZhipuAI response to OpenAI-compatible format
+            return {
+                "id": response.id,
+                "object": "chat.completion",
+                "created": response.created,
+                "model": response.model,
+                "choices": [{
+                    "index": 0,
+                    "message": {
+                        "role": response.choices[0].message.role,
+                        "content": response.choices[0].message.content,
+                        "tool_calls": self._convert_tool_calls_to_openai_format(
+                            getattr(response.choices[0].message, 'tool_calls', None)
+                        )
+                    },
+                    "finish_reason": response.choices[0].finish_reason
+                }],
+                "usage": {
+                    "prompt_tokens": response.usage.prompt_tokens,
+                    "completion_tokens": response.usage.completion_tokens,
+                    "total_tokens": response.usage.total_tokens
+                }
+            }
+            
+        except Exception as e:
+            logger.error(f"[ZHIPU_AI] sync response error: {e}")
+            return {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+    
+    def _handle_stream_response(self, request_params):
+        """Handle streaming ZhipuAI API response"""
+        try:
+            stream = self.client.chat.completions.create(**request_params)
+            
+            # Stream chunks to caller, converting to OpenAI format
+            for chunk in stream:
+                if not chunk.choices:
+                    continue
+                
+                delta = chunk.choices[0].delta
+                
+                # Convert to OpenAI-compatible format
+                openai_chunk = {
+                    "id": chunk.id,
+                    "object": "chat.completion.chunk",
+                    "created": chunk.created,
+                    "model": chunk.model,
+                    "choices": [{
+                        "index": 0,
+                        "delta": {},
+                        "finish_reason": chunk.choices[0].finish_reason
+                    }]
+                }
+                
+                # Add role if present
+                if hasattr(delta, 'role') and delta.role:
+                    openai_chunk["choices"][0]["delta"]["role"] = delta.role
+                
+                # Add content if present
+                if hasattr(delta, 'content') and delta.content:
+                    openai_chunk["choices"][0]["delta"]["content"] = delta.content
+                
+                # Add reasoning_content as separate field if present (GLM-5/GLM-4.7 thinking)
+                if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
+                    openai_chunk["choices"][0]["delta"]["reasoning_content"] = delta.reasoning_content
+                
+                # Add tool_calls if present
+                if hasattr(delta, 'tool_calls') and delta.tool_calls:
+                    # For streaming, tool_calls need special handling
+                    openai_tool_calls = []
+                    for tc in delta.tool_calls:
+                        tool_call_dict = {
+                            "index": getattr(tc, 'index', 0),
+                            "id": getattr(tc, 'id', None),
+                            "type": "function",
+                            "function": {}
+                        }
+                        
+                        # Add function name if present
+                        if hasattr(tc, 'function') and hasattr(tc.function, 'name') and tc.function.name:
+                            tool_call_dict["function"]["name"] = tc.function.name
+                        
+                        # Add function arguments if present
+                        if hasattr(tc, 'function') and hasattr(tc.function, 'arguments') and tc.function.arguments:
+                            tool_call_dict["function"]["arguments"] = tc.function.arguments
+                        
+                        openai_tool_calls.append(tool_call_dict)
+                    
+                    openai_chunk["choices"][0]["delta"]["tool_calls"] = openai_tool_calls
+                
+                yield openai_chunk
+                
+        except Exception as e:
+            logger.error(f"[ZHIPU_AI] stream response error: {e}")
+            yield {
+                "error": True,
+                "message": str(e),
+                "status_code": 500
+            }
+    
+    def _convert_tools_to_zhipu_format(self, tools):
+        """
+        Convert tools from Claude format to ZhipuAI format
+        
+        Claude format: {name, description, input_schema}
+        ZhipuAI format: {type: "function", function: {name, description, parameters}}
+        """
+        if not tools:
+            return None
+        
+        zhipu_tools = []
+        for tool in tools:
+            # Check if already in ZhipuAI/OpenAI format
+            if 'type' in tool and tool['type'] == 'function':
+                zhipu_tools.append(tool)
+            else:
+                # Convert from Claude format
+                zhipu_tools.append({
+                    "type": "function",
+                    "function": {
+                        "name": tool.get("name"),
+                        "description": tool.get("description"),
+                        "parameters": tool.get("input_schema", {})
+                    }
+                })
+        
+        return zhipu_tools
+    
+    def _convert_messages_to_zhipu_format(self, messages):
+        """
+        Convert messages from Claude format to ZhipuAI format
+        
+        Claude uses content blocks with types like 'tool_use', 'tool_result'
+        ZhipuAI uses 'tool_calls' in assistant messages and 'tool' role for results
+        """
+        if not messages:
+            return []
+        
+        zhipu_messages = []
+        
+        for msg in messages:
+            role = msg.get("role")
+            content = msg.get("content")
+            
+            # Handle string content (already in correct format)
+            if isinstance(content, str):
+                zhipu_messages.append(msg)
+                continue
+            
+            # Handle list content (Claude format with content blocks)
+            if isinstance(content, list):
+                # Check if this is a tool result message (user role with tool_result blocks)
+                if role == "user" and any(block.get("type") == "tool_result" for block in content):
+                    # Convert each tool_result block to a separate tool message
+                    for block in content:
+                        if block.get("type") == "tool_result":
+                            zhipu_messages.append({
+                                "role": "tool",
+                                "tool_call_id": block.get("tool_use_id"),
+                                "content": block.get("content", "")
+                            })
+                
+                # Check if this is an assistant message with tool_use blocks
+                elif role == "assistant":
+                    # Separate text content and tool_use blocks
+                    text_parts = []
+                    tool_calls = []
+                    
+                    for block in content:
+                        if block.get("type") == "text":
+                            text_parts.append(block.get("text", ""))
+                        elif block.get("type") == "tool_use":
+                            tool_calls.append({
+                                "id": block.get("id"),
+                                "type": "function",
+                                "function": {
+                                    "name": block.get("name"),
+                                    "arguments": json.dumps(block.get("input", {}))
+                                }
+                            })
+                    
+                    # Build ZhipuAI format assistant message
+                    zhipu_msg = {
+                        "role": "assistant",
+                        "content": " ".join(text_parts) if text_parts else None
+                    }
+                    
+                    if tool_calls:
+                        zhipu_msg["tool_calls"] = tool_calls
+                    
+                    zhipu_messages.append(zhipu_msg)
+                else:
+                    # Other list content, keep as is
+                    zhipu_messages.append(msg)
+            else:
+                # Other formats, keep as is
+                zhipu_messages.append(msg)
+        
+        return zhipu_messages
+    
+    def _convert_tool_calls_to_openai_format(self, tool_calls):
+        """Convert ZhipuAI tool_calls to OpenAI format"""
+        if not tool_calls:
+            return None
+        
+        openai_tool_calls = []
+        for tool_call in tool_calls:
+            openai_tool_calls.append({
+                "id": tool_call.id,
+                "type": "function",
+                "function": {
+                    "name": tool_call.function.name,
+                    "arguments": tool_call.function.arguments
+                }
+            })
+        
+        return openai_tool_calls
diff --git a/plugins/README.md b/plugins/README.md
new file mode 100644
index 0000000..6804a20
--- /dev/null
+++ b/plugins/README.md
@@ -0,0 +1,273 @@
+**Table of Content**
+
+- [插件化初衷](#插件化初衷)
+- [插件安装方法](#插件安装方法)
+- [插件化实现](#插件化实现)
+- [插件编写示例](#插件编写示例)
+- [插件设计建议](#插件设计建议)
+
+## 插件化初衷
+
+之前未插件化的代码耦合程度高，如果要定制一些个性化功能（如流量控制、接入`NovelAI`画图平台等），需要了解代码主体，避免影响到其他的功能。多个功能同时存在时，无法调整功能的优先级顺序，功能配置项也非常混乱。
+
+此时插件化应声而出。
+
+**插件化**: 在保证主体功能是ChatGPT的前提下，我们推荐将主体功能外的功能利用插件的方式实现。
+
+- [x] 可根据功能需要，下载不同插件。
+- [x] 插件开发成本低，仅需了解插件触发事件，并按照插件定义接口编写插件。
+- [x] 插件化能够自由开关和调整优先级。
+- [x] 每个插件可在插件文件夹内维护独立的配置文件，方便代码的测试和调试，可以在独立的仓库开发插件。
+
+## 插件安装方法
+
+在本仓库中预置了一些插件，如果要安装其他仓库的插件，有两种方法。
+
+- 第一种方法是在将下载的插件文件都解压到"plugins"文件夹的一个单独的文件夹，最终插件的代码都位于"plugins/PLUGIN_NAME/*"中。启动程序后，如果插件的目录结构正确，插件会自动被扫描加载。除此以外，注意你还需要安装文件夹中`requirements.txt`中的依赖。
+
+- 第二种方法是`Godcmd`插件，它是预置的管理员插件，能够让程序在运行时就能安装插件，它能够自动安装依赖。
+
+    安装插件的命令是"#installp [仓库源](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/plugins/source.json)记录的插件名/仓库地址"。这是管理员命令，认证方法在[这里](https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/godcmd)。
+
+    - 安装[仓库源](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/plugins/source.json)记录的插件：#installp sdwebui
+
+    - 安装指定仓库的插件：#installp https://github.com/lanvent/plugin_sdwebui.git
+
+    在安装之后，需要执行"#scanp"命令来扫描加载新安装的插件（或者重新启动程序）。
+
+安装插件后需要注意有些插件有自己的配置模板，一般要去掉".template"新建一个配置文件。
+
+## 插件化实现
+
+插件化实现是在收到消息到发送回复的各个步骤之间插入触发事件实现的。
+
+### 消息处理过程
+
+在了解插件触发事件前，首先需要了解程序收到消息到发送回复的整个过程。
+
+插件化版本中，消息处理过程可以分为4个步骤：
+```
+    1.收到消息 ---> 2.产生回复 ---> 3.包装回复 ---> 4.发送回复
+```
+
+以下是它们的默认处理逻辑(太长不看，可跳到[插件编写示例](#插件编写示例))：
+
+**注意以下包含的代码是`v1.1.0`中的片段，已过时，只可用于理解事件，最新的默认代码逻辑请参考[chat_channel](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/channel/chat_channel.py)**
+
+#### 1. 收到消息
+
+负责接收用户消息，根据用户的配置，判断本条消息是否触发机器人。如果触发，则会判断该消息的类型（声音、文本、画图命令等），将消息包装成如下的`Context`交付给下一个步骤。
+
+```python
+    class ContextType (Enum):
+        TEXT = 1         # 文本消息
+        VOICE = 2        # 音频消息
+        IMAGE_CREATE = 3 # 创建图片命令
+    class Context:
+        def __init__(self, type : ContextType = None , content = None,  kwargs = dict()):
+            self.type = type
+            self.content = content
+            self.kwargs = kwargs
+        def __getitem__(self, key):
+            return self.kwargs[key]
+```
+
+`Context`中除了存放消息类型和内容外,还存放了一些与会话相关的参数。
+
+例如，当收到用户私聊消息时，会存放以下的会话参数。
+
+```python
+    context.kwargs = {'isgroup': False, 'msg': msg, 'receiver': other_user_id, 'session_id': other_user_id}
+```
+
+- `isgroup`: `Context`是否是群聊消息。
+- `msg`: the original message object from the channel.
+- `receiver`: 需要回复消息的对象ID。
+- `session_id`: 会话ID(一般是发送触发bot消息的用户ID，如果在群聊中并且`conf`里设置了`group_chat_in_one_session`，那么此处便是群聊ID)
+
+#### 2. 产生回复
+
+处理消息并产生回复。目前默认处理逻辑是根据`Context`的类型交付给对应的bot，并产生回复`Reply`。 如果本步骤没有产生任何回复，那么会跳过之后的所有步骤。
+
+```python
+    if context.type == ContextType.TEXT or context.type == ContextType.IMAGE_CREATE:
+        reply = super().build_reply_content(context.content, context) #文字跟画图交付给chatgpt
+    elif context.type == ContextType.VOICE: # 声音先进行语音转文字后，修改Context类型为文字后，再交付给chatgpt
+        cmsg = context['msg']
+        cmsg.prepare()
+        file_name = context.content
+        reply = super().build_voice_to_text(file_name)
+        if reply.type != ReplyType.ERROR and reply.type != ReplyType.INFO:
+            context.content = reply.content # 语音转文字后，将文字内容作为新的context
+            context.type = ContextType.TEXT
+            reply = super().build_reply_content(context.content, context)
+            if reply.type == ReplyType.TEXT:
+                if conf().get('voice_reply_voice'):
+                    reply = super().build_text_to_voice(reply.content)
+```
+
+回复`Reply`的定义如下所示，它允许Bot可以回复多类不同的消息。同时也加入了`INFO`和`ERROR`消息类型区分系统提示和系统错误。
+
+```python
+    class ReplyType(Enum):
+        TEXT = 1        # 文本
+        VOICE = 2       # 音频文件
+        IMAGE = 3       # 图片文件
+        IMAGE_URL = 4   # 图片URL
+
+        INFO = 9
+        ERROR = 10
+    class Reply:
+        def __init__(self, type : ReplyType = None , content = None):
+            self.type = type
+            self.content = content
+```
+
+#### 3. 装饰回复
+
+根据`Context`和回复`Reply`的类型，对回复的内容进行装饰。目前的装饰有以下两种:
+
+- `TEXT`文本回复:如果这次消息需要的回复是`VOICE`，进行文字转语音回复之后再次装饰。 否则根据是否在群聊中来决定是艾特接收方还是添加回复的前缀。
+
+- `INFO`或`ERROR`类型，会在消息前添加对应的系统提示字样。
+
+如下是默认逻辑的代码：
+
+```python
+    if reply.type == ReplyType.TEXT:
+        reply_text = reply.content
+        if context.get('desire_rtype') == ReplyType.VOICE:
+            reply = super().build_text_to_voice(reply.content)
+            return self._decorate_reply(context, reply)
+        if context['isgroup']:
+            reply_text = '@' +  context['msg'].actual_user_nickname + ' ' + reply_text.strip()
+            reply_text = conf().get("group_chat_reply_prefix", "")+reply_text
+        else:
+            reply_text = conf().get("single_chat_reply_prefix", "")+reply_text
+        reply.content = reply_text
+    elif reply.type == ReplyType.ERROR or reply.type == ReplyType.INFO:
+        reply.content = str(reply.type)+":\n" + reply.content
+```
+
+#### 4. 发送回复
+
+根据`Reply`的类型，默认逻辑调用不同的发送函数发送回复给接收方`context["receiver"]`。
+
+### 插件触发事件
+
+主程序目前会在各个消息步骤间触发事件，监听相应事件的插件会按照优先级，顺序调用事件处理函数。
+
+目前支持三类触发事件：
+```
+1.收到消息
+---> `ON_HANDLE_CONTEXT`
+2.产生回复
+---> `ON_DECORATE_REPLY`
+3.装饰回复
+---> `ON_SEND_REPLY`
+4.发送回复
+```
+
+触发事件会产生事件的上下文`EventContext`，它包含了以下信息:
+
+`EventContext(Event事件类型, {'channel' : 消息channel, 'context': Context, 'reply': Reply})`
+
+插件处理函数可通过修改`EventContext`中的`context`和`reply`来实现功能。
+
+## 插件编写示例
+
+以`plugins/hello`为例，其中编写了一个简单的`Hello`插件。
+
+### 1. 创建插件
+
+在`plugins`目录下创建一个插件文件夹`hello`。然后，在该文件夹中创建``__init__.py``文件，在``__init__.py``中将其他编写的模块文件导入。在程序启动时，插件管理器会读取``__init__.py``的所有内容。
+
+```
+plugins/
+└── hello
+    ├── __init__.py
+    └── hello.py
+```
+
+``__init__.py``的内容：
+```
+from .hello import *
+```
+
+### 2. 编写插件类
+
+在`hello.py`文件中，创建插件类，它继承自`Plugin`。
+
+在类定义之前需要使用`@plugins.register`装饰器注册插件，并填写插件的相关信息，其中`desire_priority`表示插件默认的优先级，越大优先级越高。初次加载插件后可在`plugins/plugins.json`中修改插件优先级。
+
+并在`__init__`中绑定你编写的事件处理函数。
+
+`Hello`插件为事件`ON_HANDLE_CONTEXT`绑定了一个处理函数`on_handle_context`，它表示之后每次生成回复前，都会由`on_handle_context`先处理。
+
+PS: `ON_HANDLE_CONTEXT`是最常用的事件，如果要根据不同的消息来生成回复，就用它。
+
+```python
+@plugins.register(name="Hello", desc="A simple plugin that says hello", version="0.1", author="lanvent", desire_priority= -1)
+class Hello(Plugin):
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        logger.info("[Hello] inited")
+```
+
+### 3. 编写事件处理函数
+
+#### 修改事件上下文
+
+事件处理函数接收一个`EventContext`对象`e_context`作为参数。`e_context`包含了事件相关信息，利用`e_context['key']`来访问这些信息。
+
+`EventContext(Event事件类型, {'channel' : 消息channel, 'context': Context, 'reply': Reply})`
+
+处理函数中通过修改`e_context`对象中的事件相关信息来实现所需功能，比如更改`e_context['reply']`中的内容可以修改回复。
+
+#### 决定是否交付给下个插件或默认逻辑
+
+在处理函数结束时，还需要设置`e_context`对象的`action`属性，它决定如何继续处理事件。目前有以下三种处理方式：
+
+- `EventAction.CONTINUE`: 事件未结束，继续交给下个插件处理，如果没有下个插件，则交付给默认的事件处理逻辑。
+- `EventAction.BREAK`: 事件结束，不再给下个插件处理，交付给默认的处理逻辑。
+- `EventAction.BREAK_PASS`: 事件结束，不再给下个插件处理，跳过默认的处理逻辑。
+
+#### 示例处理函数
+
+`Hello`插件处理`Context`类型为`TEXT`的消息：
+
+- 如果内容是`Hello`，就将回复设置为`Hello+用户昵称`，并跳过之后的插件和默认逻辑。
+- 如果内容是`End`，就将`Context`的类型更改为`IMAGE_CREATE`，并让事件继续，如果最终交付到默认逻辑，会调用默认的画图Bot来画画。
+
+```python
+    def on_handle_context(self, e_context: EventContext):
+        if e_context['context'].type != ContextType.TEXT:
+            return
+        content = e_context['context'].content
+        if content == "Hello":
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            msg:ChatMessage = e_context['context']['msg']
+            if e_context['context']['isgroup']:
+                reply.content = f"Hello, {msg.actual_user_nickname} from {msg.from_user_nickname}"
+            else:
+                reply.content = f"Hello, {msg.from_user_nickname}"
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS # 事件结束，并跳过处理context的默认逻辑
+        if content == "End":
+            # 如果是文本消息"End"，将请求转换成"IMAGE_CREATE"，并将content设置为"The World"
+            e_context['context'].type = ContextType.IMAGE_CREATE
+            content = "The World"
+            e_context.action = EventAction.CONTINUE  # 事件继续，交付给下个插件或默认逻辑
+```
+
+## 插件设计建议
+
+- 尽情将你想要的个性化功能设计为插件。
+- 一个插件目录建议只注册一个插件类。建议使用单独的仓库维护插件，便于更新。
+
+  在测试调试好后提交`PR`，把自己的仓库加入到[仓库源](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/plugins/source.json)中。
+
+- 插件的config文件、使用说明`README.md`、`requirement.txt`等放置在插件目录中。
+- 默认优先级不要超过管理员插件`Godcmd`的优先级(999)，`Godcmd`插件提供了配置管理、插件管理等功能。
diff --git a/plugins/__init__.py b/plugins/__init__.py
new file mode 100644
index 0000000..d515edb
--- /dev/null
+++ b/plugins/__init__.py
@@ -0,0 +1,9 @@
+from .event import *
+from .plugin import *
+from .plugin_manager import PluginManager
+
+instance = PluginManager()
+
+register = instance.register
+# load_plugins                = instance.load_plugins
+# emit_event                  = instance.emit_event
diff --git a/plugins/banwords/.gitignore b/plugins/banwords/.gitignore
new file mode 100644
index 0000000..a6593bf
--- /dev/null
+++ b/plugins/banwords/.gitignore
@@ -0,0 +1 @@
+banwords.txt
\ No newline at end of file
diff --git a/plugins/banwords/README.md b/plugins/banwords/README.md
new file mode 100644
index 0000000..39517f6
--- /dev/null
+++ b/plugins/banwords/README.md
@@ -0,0 +1,27 @@
+
+## 插件描述
+
+简易的敏感词插件，暂不支持分词，请自行导入词库到插件文件夹中的`banwords.txt`，每行一个词，一个参考词库是[1](https://github.com/cjh0613/tencent-sensitive-words/blob/main/sensitive_words_lines.txt)。
+
+使用前将`config.json.template`复制为`config.json`，并自行配置。
+
+目前插件对消息的默认处理行为有如下两种：
+
+- `ignore` : 无视这条消息。
+- `replace` : 将消息中的敏感词替换成"*"，并回复违规。
+
+```json
+    "action": "replace",  
+    "reply_filter": true,
+    "reply_action": "ignore"
+```
+
+在以上配置项中：
+
+- `action`: 对用户消息的默认处理行为
+- `reply_filter`: 是否对ChatGPT的回复也进行敏感词过滤
+- `reply_action`: 如果开启了回复过滤，对回复的默认处理行为
+
+## 致谢
+
+搜索功能实现来自https://github.com/toolgood/ToolGood.Words
\ No newline at end of file
diff --git a/plugins/banwords/__init__.py b/plugins/banwords/__init__.py
new file mode 100644
index 0000000..503a563
--- /dev/null
+++ b/plugins/banwords/__init__.py
@@ -0,0 +1 @@
+from .banwords import *
diff --git a/plugins/banwords/banwords.py b/plugins/banwords/banwords.py
new file mode 100644
index 0000000..0a1f43f
--- /dev/null
+++ b/plugins/banwords/banwords.py
@@ -0,0 +1,103 @@
+# encoding:utf-8
+
+import json
+import os
+
+import plugins
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from plugins import *
+
+from .lib.WordsSearch import WordsSearch
+
+
+@plugins.register(
+    name="Banwords",
+    desire_priority=100,
+    hidden=True,
+    desc="判断消息中是否有敏感词、决定是否回复。",
+    version="1.0",
+    author="lanvent",
+)
+class Banwords(Plugin):
+    def __init__(self):
+        super().__init__()
+        try:
+            # load config
+            conf = super().load_config()
+            curdir = os.path.dirname(__file__)
+            if not conf:
+                # 配置不存在则写入默认配置
+                config_path = os.path.join(curdir, "config.json")
+                if not os.path.exists(config_path):
+                    conf = {"action": "ignore"}
+                    with open(config_path, "w") as f:
+                        json.dump(conf, f, indent=4)
+
+            self.searchr = WordsSearch()
+            self.action = conf["action"]
+            # banwords.txt is gitignored / not shipped by default; treat a
+            # missing file as an empty ban list instead of failing to init.
+            banwords_path = os.path.join(curdir, "banwords.txt")
+            words = []
+            if os.path.exists(banwords_path):
+                with open(banwords_path, "r", encoding="utf-8") as f:
+                    for line in f:
+                        word = line.strip()
+                        if word:
+                            words.append(word)
+            self.searchr.SetKeywords(words)
+            self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+            if conf.get("reply_filter", True):
+                self.handlers[Event.ON_DECORATE_REPLY] = self.on_decorate_reply
+                self.reply_action = conf.get("reply_action", "ignore")
+            logger.debug("[Banwords] inited")
+        except Exception as e:
+            logger.debug("[Banwords] init failed, ignore or see https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/banwords .")
+            raise e
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type not in [
+            ContextType.TEXT,
+            ContextType.IMAGE_CREATE,
+        ]:
+            return
+
+        content = e_context["context"].content
+        logger.debug("[Banwords] on_handle_context. content: %s" % content)
+        if self.action == "ignore":
+            f = self.searchr.FindFirst(content)
+            if f:
+                logger.info("[Banwords] %s in message" % f["Keyword"])
+                e_context.action = EventAction.BREAK_PASS
+                return
+        elif self.action == "replace":
+            if self.searchr.ContainsAny(content):
+                reply = Reply(ReplyType.INFO, "发言中包含敏感词，请重试: \n" + self.searchr.Replace(content))
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+
+    def on_decorate_reply(self, e_context: EventContext):
+        if e_context["reply"].type not in [ReplyType.TEXT]:
+            return
+
+        reply = e_context["reply"]
+        content = reply.content
+        if self.reply_action == "ignore":
+            f = self.searchr.FindFirst(content)
+            if f:
+                logger.info("[Banwords] %s in reply" % f["Keyword"])
+                e_context["reply"] = None
+                e_context.action = EventAction.BREAK_PASS
+                return
+        elif self.reply_action == "replace":
+            if self.searchr.ContainsAny(content):
+                reply = Reply(ReplyType.INFO, "已替换回复中的敏感词: \n" + self.searchr.Replace(content))
+                e_context["reply"] = reply
+                e_context.action = EventAction.CONTINUE
+                return
+
+    def get_help_text(self, **kwargs):
+        return "过滤消息中的敏感词。"
diff --git a/plugins/banwords/banwords.txt.template b/plugins/banwords/banwords.txt.template
new file mode 100644
index 0000000..7c6e0f9
--- /dev/null
+++ b/plugins/banwords/banwords.txt.template
@@ -0,0 +1,2 @@
+nipples
+pennis
diff --git a/plugins/banwords/config.json.template b/plugins/banwords/config.json.template
new file mode 100644
index 0000000..3117a83
--- /dev/null
+++ b/plugins/banwords/config.json.template
@@ -0,0 +1,5 @@
+{
+  "action": "replace",
+  "reply_filter": true,
+  "reply_action": "ignore"
+}
diff --git a/plugins/banwords/lib/WordsSearch.py b/plugins/banwords/lib/WordsSearch.py
new file mode 100644
index 0000000..d41d6e7
--- /dev/null
+++ b/plugins/banwords/lib/WordsSearch.py
@@ -0,0 +1,250 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+# ToolGood.Words.WordsSearch.py
+# 2020, Lin Zhijun, https://github.com/toolgood/ToolGood.Words
+# Licensed under the Apache License 2.0
+# 更新日志
+# 2020.04.06 第一次提交
+# 2020.05.16 修改，支持大于0xffff的字符
+
+__all__ = ['WordsSearch']
+__author__ = 'Lin Zhijun'
+__date__ = '2020.05.16'
+
+class TrieNode():
+    def __init__(self):
+        self.Index = 0
+        self.Index = 0
+        self.Layer = 0
+        self.End = False
+        self.Char = ''
+        self.Results = []
+        self.m_values = {}
+        self.Failure = None
+        self.Parent = None
+
+    def Add(self,c):
+        if c in self.m_values :
+            return self.m_values[c]
+        node = TrieNode()
+        node.Parent = self
+        node.Char = c
+        self.m_values[c] = node
+        return node
+
+    def SetResults(self,index):
+        if (self.End == False):
+            self.End = True
+        self.Results.append(index)
+
+class TrieNode2():
+    def __init__(self):
+        self.End = False
+        self.Results = []
+        self.m_values = {}
+        self.minflag = 0xffff
+        self.maxflag = 0
+
+    def Add(self,c,node3):
+        if (self.minflag > c):
+            self.minflag = c
+        if (self.maxflag < c):
+             self.maxflag = c
+        self.m_values[c] = node3
+
+    def SetResults(self,index):
+        if (self.End == False) :
+            self.End = True
+        if (index in self.Results )==False : 
+            self.Results.append(index)
+
+    def HasKey(self,c):
+        return c in self.m_values
+        
+ 
+    def TryGetValue(self,c):
+        if (self.minflag <= c and self.maxflag >= c):
+            if c in self.m_values:
+                return self.m_values[c]
+        return None
+
+
+class WordsSearch():
+    def __init__(self):
+        self._first = {}
+        self._keywords = []
+        self._indexs=[]
+    
+    def SetKeywords(self,keywords):
+        self._keywords = keywords
+        self._indexs=[]
+        for i in range(len(keywords)):
+            self._indexs.append(i)
+
+        root = TrieNode()
+        allNodeLayer={}
+
+        for i in range(len(self._keywords)): # for (i = 0; i < _keywords.length; i++) 
+            p = self._keywords[i]
+            nd = root
+            for j in range(len(p)): # for (j = 0; j < p.length; j++) 
+                nd = nd.Add(ord(p[j]))
+                if (nd.Layer == 0):
+                    nd.Layer = j + 1
+                    if nd.Layer in allNodeLayer:
+                        allNodeLayer[nd.Layer].append(nd)
+                    else:
+                        allNodeLayer[nd.Layer]=[]
+                        allNodeLayer[nd.Layer].append(nd)
+            nd.SetResults(i)
+
+
+        allNode = []
+        allNode.append(root)
+        for key in allNodeLayer.keys():
+            for nd in allNodeLayer[key]:
+                allNode.append(nd)
+        allNodeLayer=None
+
+        for i in range(len(allNode)): # for (i = 0; i < allNode.length; i++) 
+            if i==0 :
+                continue
+            nd=allNode[i]
+            nd.Index = i
+            r = nd.Parent.Failure
+            c = nd.Char
+            while (r != None and (c in r.m_values)==False):
+                r = r.Failure
+            if (r == None):
+                nd.Failure = root
+            else:
+                nd.Failure = r.m_values[c]
+                for key2 in nd.Failure.Results :
+                    nd.SetResults(key2)
+        root.Failure = root
+
+        allNode2 = []
+        for i in range(len(allNode)): # for (i = 0; i < allNode.length; i++) 
+            allNode2.append( TrieNode2())
+        
+        for i in range(len(allNode2)): # for (i = 0; i < allNode2.length; i++) 
+            oldNode = allNode[i]
+            newNode = allNode2[i]
+
+            for key in oldNode.m_values :
+                index = oldNode.m_values[key].Index
+                newNode.Add(key, allNode2[index])
+            
+            for index in range(len(oldNode.Results)): # for (index = 0; index < oldNode.Results.length; index++) 
+                item = oldNode.Results[index]
+                newNode.SetResults(item)
+            
+            oldNode=oldNode.Failure
+            while oldNode != root:
+                for key in oldNode.m_values :
+                    if (newNode.HasKey(key) == False):
+                        index = oldNode.m_values[key].Index
+                        newNode.Add(key, allNode2[index])
+                for index in range(len(oldNode.Results)): 
+                    item = oldNode.Results[index]
+                    newNode.SetResults(item)
+                oldNode=oldNode.Failure
+        allNode = None
+        root = None
+
+        # first = []
+        # for index in range(65535):# for (index = 0; index < 0xffff; index++) 
+        #     first.append(None)
+        
+        # for key in allNode2[0].m_values :
+        #     first[key] = allNode2[0].m_values[key]
+        
+        self._first = allNode2[0]
+    
+
+    def FindFirst(self,text):
+        ptr = None
+        for index in range(len(text)): # for (index = 0; index < text.length; index++) 
+            t =ord(text[index]) # text.charCodeAt(index)
+            tn = None
+            if (ptr == None):
+                tn = self._first.TryGetValue(t)
+            else:
+                tn = ptr.TryGetValue(t)
+                if (tn==None):
+                    tn = self._first.TryGetValue(t)
+                
+            
+            if (tn != None):
+                if (tn.End):
+                    item = tn.Results[0]
+                    keyword = self._keywords[item]
+                    return { "Keyword": keyword, "Success": True, "End": index, "Start": index + 1 - len(keyword), "Index": self._indexs[item] }
+            ptr = tn
+        return None
+
+    def FindAll(self,text):
+        ptr = None
+        list = []
+
+        for index in range(len(text)): # for (index = 0; index < text.length; index++) 
+            t =ord(text[index]) # text.charCodeAt(index)
+            tn = None
+            if (ptr == None):
+                tn = self._first.TryGetValue(t)
+            else:
+                tn = ptr.TryGetValue(t)
+                if (tn==None):
+                    tn = self._first.TryGetValue(t)
+                
+            
+            if (tn != None):
+                if (tn.End):
+                    for j in range(len(tn.Results)): # for (j = 0; j < tn.Results.length; j++) 
+                        item = tn.Results[j]
+                        keyword = self._keywords[item]
+                        list.append({ "Keyword": keyword, "Success": True, "End": index, "Start": index + 1 - len(keyword), "Index": self._indexs[item] })
+            ptr = tn
+        return list
+
+
+    def ContainsAny(self,text):
+        ptr = None
+        for index in range(len(text)): # for (index = 0; index < text.length; index++) 
+            t =ord(text[index]) # text.charCodeAt(index)
+            tn = None
+            if (ptr == None):
+                tn = self._first.TryGetValue(t)
+            else:
+                tn = ptr.TryGetValue(t)
+                if (tn==None):
+                    tn = self._first.TryGetValue(t)
+            
+            if (tn != None):
+                if (tn.End):
+                    return True
+            ptr = tn
+        return False
+    
+    def Replace(self,text, replaceChar = '*'):
+        result = list(text) 
+
+        ptr = None
+        for i in range(len(text)): # for (i = 0; i < text.length; i++) 
+            t =ord(text[i]) # text.charCodeAt(index)
+            tn = None
+            if (ptr == None):
+                tn = self._first.TryGetValue(t)
+            else:
+                tn = ptr.TryGetValue(t)
+                if (tn==None):
+                    tn = self._first.TryGetValue(t)
+            
+            if (tn != None):
+                if (tn.End):
+                    maxLength = len( self._keywords[tn.Results[0]])
+                    start = i + 1 - maxLength
+                    for j in range(start,i+1): # for (j = start; j <= i; j++) 
+                        result[j] = replaceChar
+            ptr = tn
+        return ''.join(result) 
\ No newline at end of file
diff --git a/plugins/config.json.template b/plugins/config.json.template
new file mode 100644
index 0000000..7cc3dcd
--- /dev/null
+++ b/plugins/config.json.template
@@ -0,0 +1,48 @@
+{
+    "godcmd": {
+        "password": "",
+        "admin_users": []
+    },
+    "banwords": {
+        "action": "replace",
+        "reply_filter": true,
+        "reply_action": "ignore"
+    },
+    "linkai": {
+        "group_app_map": {
+            "测试群1": "default",
+            "测试群2": "Kv2fXJcH"
+        },
+        "midjourney": {
+            "enabled": true,
+            "auto_translate": true,
+            "img_proxy": true,
+            "max_tasks": 3,
+            "max_tasks_per_user": 1,
+            "use_image_create_prefix": true
+        },
+        "summary": {
+            "enabled": true,
+            "group_enabled": true,
+            "max_file_size": 5000,
+            "type": ["FILE", "SHARING"]
+        }
+    },
+    "hello": {
+        "group_welc_fixed_msg": {
+            "群聊1": "群聊1的固定欢迎语",
+            "群聊2": "群聊2的固定欢迎语"
+        },
+        "group_welc_prompt": "请你随机使用一种风格说一句问候语来欢迎新用户\"{nickname}\"加入群聊。",
+
+        "group_exit_prompt": "请你随机使用一种风格跟其他群用户说他违反规则\"{nickname}\"退出群聊。",
+
+        "patpat_prompt": "请你随机使用一种风格介绍你自己，并告诉用户输入#help可以查看帮助信息。",
+
+        "use_character_desc": false
+    },
+    "Apilot": {
+        "alapi_token": "xxx",
+        "morning_news_text_enabled": false
+    }
+}
diff --git a/plugins/cow_cli/__init__.py b/plugins/cow_cli/__init__.py
new file mode 100644
index 0000000..a535239
--- /dev/null
+++ b/plugins/cow_cli/__init__.py
@@ -0,0 +1 @@
+from .cow_cli import CowCliPlugin
diff --git a/plugins/cow_cli/cow_cli.py b/plugins/cow_cli/cow_cli.py
new file mode 100644
index 0000000..3642fe0
--- /dev/null
+++ b/plugins/cow_cli/cow_cli.py
@@ -0,0 +1,1769 @@
+"""
+CowCli plugin - Intercept cow/slash commands in chat messages.
+
+Matches messages like:
+  cow skill list
+  cow install-browser
+  /skill list
+  /context clear
+  /status
+  /install-browser
+
+Does NOT match:
+  cow是什么
+  cow真好用
+  /开头但不是已知命令
+"""
+
+import os
+import threading
+
+import plugins
+from plugins import Plugin, Event, EventContext, EventAction
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.i18n import t as _t
+from config import conf
+from cli import __version__
+
+
+# Known top-level subcommands that cow supports.
+# "start" / "stop" / "restart" refer to daemon lifecycle on the host shell;
+# in chat, "/cancel" aborts the in-flight agent run instead.
+KNOWN_COMMANDS = {
+    "help", "version", "status", "logs",
+    "start", "stop", "restart",
+    "cancel",
+    "skill", "context", "config",
+    "knowledge", "memory",
+    "install-browser",
+}
+
+# Commands that can only run from the CLI (terminal), not in chat.
+CLI_ONLY_COMMANDS = {"start", "stop", "restart"}
+
+# Commands that can only run from chat (need access to in-process memory)
+CHAT_ONLY_COMMANDS = set()  # context is allowed in both, but behaves differently
+
+# Convenience shorthands for the slash form only. Values are *full command
+# strings* so an alias can carry arguments (e.g. "cc" -> "context clear").
+# These shorthands are deliberate and NOT derivable from prefix/typo rules:
+#   - "c"  is a prefix of cancel/config/context (ambiguous) -> needs explicit map
+#   - "cc" is a prefix of nothing and expands to a command + argument
+#   - "s"  would otherwise be an ambiguous prefix (skill/start/status/stop)
+# Users may override / extend these via config.json "command_aliases".
+DEFAULT_ALIASES = {
+    "c":   "cancel",
+    "cc":  "context clear",
+    "ctx": "context",
+    "h":   "help",
+    "s":   "status",
+    "cfg": "config",
+    "k":   "knowledge",
+}
+
+
+@plugins.register(
+    name="cow_cli",
+    desc="Handle cow/slash commands in chat messages",
+    version="0.1.0",
+    author="CowAgent",
+    desire_priority=1000,
+)
+class CowCliPlugin(Plugin):
+
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        self.aliases = self._build_aliases()
+        logger.debug("[CowCli] initialized")
+
+    def reload(self):
+        """Rebuild the alias table (e.g. after config changes)."""
+        self.aliases = self._build_aliases()
+
+    @staticmethod
+    def _build_aliases() -> dict:
+        """Merge DEFAULT_ALIASES with optional config.json ``command_aliases``.
+
+        User-supplied entries (keys lowercased / stripped) override defaults.
+        An alias whose target's first token is not a known command is dropped
+        with a warning, so a bad alias can never create a dead command. An
+        alias key that shadows a real command is kept but warned about — the
+        exact-command stage in ``_resolve`` runs first, so the command wins.
+        """
+        merged = dict(DEFAULT_ALIASES)
+        try:
+            overrides = conf().get("command_aliases", {}) or {}
+        except Exception as e:
+            logger.warning(f"[CowCli] could not read command_aliases from config: {e}")
+            overrides = {}
+        if not isinstance(overrides, dict):
+            logger.warning(f"[CowCli] command_aliases must be an object, got {type(overrides).__name__}; ignoring")
+            overrides = {}
+        for key, value in overrides.items():
+            if not isinstance(key, str) or not isinstance(value, str):
+                logger.warning(f"[CowCli] ignoring non-string alias entry: {key!r} -> {value!r}")
+                continue
+            k = key.strip().lower()
+            if k:
+                merged[k] = value.strip()
+
+        valid = {}
+        for key, value in merged.items():
+            head = value.split(None, 1)[0].lower() if value.strip() else ""
+            if head not in KNOWN_COMMANDS:
+                logger.warning(f"[CowCli] dropping alias '/{key}' -> '{value}': unknown command '{head}'")
+                continue
+            if key in KNOWN_COMMANDS:
+                logger.warning(f"[CowCli] alias '/{key}' shadows a real command; the command takes precedence")
+            valid[key] = value
+        return valid
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+
+        content = e_context["context"].content.strip()
+        parsed = self._parse_command(content)
+        if parsed is None:
+            return
+
+        token, user_args = parsed
+        result = self._resolve(token, user_args)
+        kind = result[0]
+
+        if kind == "passthrough":
+            # Not a command and not a near-typo: let the agent handle it.
+            return
+
+        if kind == "run":
+            _, cmd, args = result
+            logger.info(f"[CowCli] intercepted command: {cmd} {args}")
+            reply_text = self._dispatch(cmd, args, e_context)
+        elif kind == "ambiguous":
+            reply_text = self._ambiguous_hint(token, result[1])
+        else:  # "typo"
+            reply_text = self._typo_hint(token, result[1])
+
+        reply_text = self._harden_line_breaks(reply_text, e_context)
+        e_context["reply"] = Reply(ReplyType.TEXT, reply_text)
+        e_context.action = EventAction.BREAK_PASS
+
+    def _parse_command(self, content: str):
+        """
+        Parse cow command from message text.
+
+        Supported formats:
+          cow <command> [args...]   e.g. "cow skill list"
+          /<command> [args...]      e.g. "/skill list"
+
+        Returns:
+          - (command, args_string): when the message looks like a command.
+            'command' may NOT be in KNOWN_COMMANDS; caller should validate.
+          - None: when the message is not command-like at all.
+
+        We deliberately return parsed-but-unknown for the slash form so the
+        caller can offer a typo hint instead of silently passing the message
+        through to the agent.
+        """
+        if content.startswith("/"):
+            rest = content[1:].strip()
+            if not rest:
+                return None
+            parts = rest.split(None, 1)
+            cmd = parts[0].lower()
+            args = parts[1] if len(parts) > 1 else ""
+            return cmd, args
+
+        if content.startswith("cow "):
+            rest = content[4:].strip()
+            if not rest:
+                return None
+            parts = rest.split(None, 1)
+            cmd = parts[0].lower()
+            if cmd not in KNOWN_COMMANDS:
+                # 'cow xxx' that isn't a command — don't intercept (could be
+                # natural language like "cow xxx 怎么样").
+                return None
+            args = parts[1] if len(parts) > 1 else ""
+            return cmd, args
+
+        return None
+
+    @staticmethod
+    def _suggest_command(cmd: str) -> str:
+        """
+        Return the closest known command if cmd is a likely typo, else "".
+        Returns None to indicate "do not intercept" (when input is too far off).
+
+        Heuristic: edit distance <= 1 (single insert/delete/substitute) when
+        |cmd| >= 3, and the candidate shares the same first letter.
+        """
+        if not cmd:
+            return ""
+        if len(cmd) < 3:
+            return None
+
+        def edit_distance_le1(a: str, b: str) -> bool:
+            if a == b:
+                return True
+            la, lb = len(a), len(b)
+            if abs(la - lb) > 1:
+                return False
+            if la == lb:
+                diffs = sum(1 for x, y in zip(a, b) if x != y)
+                return diffs <= 1
+            short, long_ = (a, b) if la < lb else (b, a)
+            i = j = 0
+            skipped = False
+            while i < len(short) and j < len(long_):
+                if short[i] != long_[j]:
+                    if skipped:
+                        return False
+                    skipped = True
+                    j += 1
+                else:
+                    i += 1
+                    j += 1
+            return True
+
+        for known in KNOWN_COMMANDS:
+            if known[0] == cmd[0] and edit_distance_le1(cmd, known):
+                return known
+        return None
+
+    def _resolve(self, token: str, user_args: str):
+        """Resolve a parsed slash token to an action.
+
+        Precedence (first hit wins):
+          1. exact command            -> ("run", cmd, args)
+          2. alias (exact key)        -> expand to a full command string, merge args
+          3. unique prefix            -> ("run", cmd, args)
+          4. ambiguous prefix (>1)    -> ("ambiguous", sorted_candidates)
+          5. typo (edit-distance <=1) -> ("typo", suggestion_or_None)
+          6. no match                 -> ("passthrough",)
+
+        Pure function of (token, user_args, KNOWN_COMMANDS, self.aliases) so it
+        is trivially unit-testable. Note the `cow ` form never reaches stages
+        2-5: `_parse_command` only returns known tokens for it, so it stays
+        strict and alias/prefix matching applies to the `/` form only.
+        """
+        token = token.lower()
+
+        # 1. exact command (a real command can never be shadowed by an alias)
+        if token in KNOWN_COMMANDS:
+            return ("run", token, user_args)
+
+        # 2. alias -> full command string; merge alias args with user args.
+        #    Alias expansion is applied at most once (no alias -> alias chains).
+        if token in self.aliases:
+            parts = self.aliases[token].split(None, 1)
+            cmd = parts[0].lower()
+            alias_args = parts[1] if len(parts) > 1 else ""
+            merged = f"{alias_args} {user_args}".strip() if user_args else alias_args
+            return ("run", cmd, merged)
+
+        # 3 / 4. prefix match
+        candidates = sorted(c for c in KNOWN_COMMANDS if c.startswith(token))
+        if len(candidates) == 1:
+            return ("run", candidates[0], user_args)
+        if len(candidates) > 1:
+            return ("ambiguous", candidates)
+
+        # 5. typo (keeps its own len>=3 + edit-distance<=1 guards)
+        suggestion = self._suggest_command(token)
+        if suggestion is not None:
+            return ("typo", suggestion)
+
+        # 6. nothing matched
+        return ("passthrough",)
+
+    @staticmethod
+    def _typo_hint(token: str, suggestion) -> str:
+        hint = _t(f"未知命令: /{token}", f"Unknown command: /{token}")
+        if suggestion:
+            hint += _t(f"\n你是不是想输入 /{suggestion} ?", f"\nDid you mean /{suggestion} ?")
+        hint += _t("\n发送 /help 查看全部命令。", "\nSend /help to see all commands.")
+        return hint
+
+    @staticmethod
+    def _ambiguous_hint(token: str, candidates) -> str:
+        options = " ".join(f"/{c}" for c in candidates)
+        return _t(
+            f"命令不明确: /{token}\n可能想输入: {options}\n发送 /help 查看全部命令。",
+            f"Ambiguous command: /{token}\nDid you mean: {options}\nSend /help to see all commands.",
+        )
+
+    # ------------------------------------------------------------------
+    # Command dispatch
+    # ------------------------------------------------------------------
+
+    def execute(self, query: str, session_id: str = "") -> str:
+        """Execute a cow/slash command string without a channel context.
+
+        Used by cloud on_chat to intercept commands before the agent runs.
+        Returns None when *query* is not command-like at all (e.g. natural
+        language). For slash-prefixed typos returns a hint string so the
+        caller still short-circuits the agent round.
+        """
+        parsed = self._parse_command(query.strip())
+        if parsed is None:
+            return None
+        token, user_args = parsed
+        result = self._resolve(token, user_args)
+        kind = result[0]
+        if kind == "passthrough":
+            return None
+        if kind == "run":
+            _, cmd, args = result
+            return self._dispatch(cmd, args, e_context=None, session_id=session_id)
+        if kind == "ambiguous":
+            return self._ambiguous_hint(token, result[1])
+        return self._typo_hint(token, result[1])  # "typo"
+
+    def _dispatch(self, cmd: str, args: str, e_context: EventContext, session_id: str = "") -> str:
+        if cmd in CLI_ONLY_COMMANDS:
+            return _t(
+                f"⚠️ `cow {cmd}` 只能在命令行终端中执行。\n请在终端运行: cow {cmd}",
+                f"⚠️ `cow {cmd}` can only run in a terminal.\nRun it in your shell: cow {cmd}",
+            )
+
+        handler_attr = "_cmd_" + cmd.replace("-", "_")
+        handler = getattr(self, handler_attr, None)
+        if handler:
+            try:
+                return handler(args, e_context, session_id=session_id)
+            except Exception as e:
+                logger.error(f"[CowCli] command '{cmd}' failed: {e}")
+                return _t(f"命令执行失败: {e}", f"Command failed: {e}")
+
+        return _t(f"未知命令: {cmd}", f"Unknown command: {cmd}")
+
+    # ------------------------------------------------------------------
+    # help / version
+    # ------------------------------------------------------------------
+
+    def _cmd_help(self, args: str, e_context, **_) -> str:
+        if _t("zh", "en") == "en":
+            lines = [
+                "📋 CowAgent Commands",
+                "",
+                "/help: Show this help",
+                "/version: Show version",
+                "/status: Show running status",
+                "/cancel: Abort the running Agent task",
+                "/logs [N]: Show the last N log lines (default 20)",
+                "/context: Show current conversation context",
+                "/context clear: Clear current conversation context",
+                "/skill list: List installed skills",
+                "/skill list --remote: Browse Skill Hub",
+                "/skill search <keyword>: Search skills",
+                "/skill install <name>: Install a skill",
+                "/skill info <name>: Show skill details",
+                "/config: Show current config",
+                "/config <key>: Show a config item",
+                "/config <key> <val>: Update a config item",
+                "/memory status: Show memory index status",
+                "/memory rebuild-index: Rebuild the vector index (required after switching embedding model)",
+                "/memory dream [N]: Trigger memory distillation (last N days, default 3, max 30)",
+                "/knowledge: Show knowledge base stats",
+                "/knowledge list: Show knowledge base file tree",
+                "/knowledge on|off: Enable/disable knowledge base",
+                "",
+                "💡 You can also use cow <command> instead of /<command>",
+            ]
+        else:
+            lines = [
+                "📋 CowAgent 命令列表",
+                "",
+                "/help: 显示此帮助",
+                "/version: 查看版本",
+                "/status: 查看运行状态",
+                "/cancel: 中止当前正在运行的 Agent 任务",
+                "/logs [N]: 查看最近N条日志 (默认20)",
+                "/context: 查看当前对话上下文信息",
+                "/context clear: 清除当前对话上下文",
+                "/skill list: 查看已安装的技能",
+                "/skill list --remote: 浏览技能广场",
+                "/skill search <关键词>: 搜索技能",
+                "/skill install <名称>: 安装技能",
+                "/skill info <名称>: 查看技能详情",
+                "/config: 查看当前配置",
+                "/config <key>: 查看某项配置",
+                "/config <key> <val>: 修改配置",
+                "/memory status: 查看记忆索引状态",
+                "/memory rebuild-index: 清空并重建向量索引 (切换 embedding 模型后必须执行)",
+                "/memory dream [N]: 手动触发记忆蒸馏 (整理近N天, 默认3, 最多30)",
+                "/knowledge: 查看知识库统计",
+                "/knowledge list: 查看知识库文件树",
+                "/knowledge on|off: 开启/关闭知识库",
+                "",
+                "💡 也可以用 cow <command> 代替 /<command>",
+            ]
+        return "\n".join(lines)
+
+    def _cmd_version(self, args: str, e_context, **_) -> str:
+        return f"CowAgent v{__version__}"
+
+    # ------------------------------------------------------------------
+    # cancel — abort the in-flight agent run for the current session.
+    # Fallback handler; in practice chat_channel/web_channel intercept
+    # /cancel earlier so it bypasses the per-session serial queue.
+    # ------------------------------------------------------------------
+
+    def _cmd_cancel(self, args: str, e_context: EventContext, session_id: str = "", **_) -> str:
+        """Signal the running agent to halt at its next checkpoint."""
+        from agent.protocol import get_cancel_registry
+
+        target_session = self._get_session_id(e_context, fallback=session_id)
+        registry = get_cancel_registry()
+
+        # Prefer per-turn request_id (matches the key agent_bridge registered)
+        cancelled = 0
+        request_id = ""
+        if e_context is not None:
+            try:
+                ctx = e_context["context"]
+                request_id = ctx.kwargs.get("request_id") or ctx.get("request_id", "")
+            except Exception:
+                request_id = ""
+
+        if request_id and registry.cancel_request(request_id):
+            cancelled = 1
+
+        # Fall back to session-wide cancel
+        if cancelled == 0 and target_session:
+            cancelled = registry.cancel_session(target_session)
+
+        if cancelled <= 0:
+            return _t("当前没有可中止的任务。", "Nothing to cancel.")
+
+        return _t("🛑 已中止", "🛑 Cancelled")
+
+    # ------------------------------------------------------------------
+    # status
+    # ------------------------------------------------------------------
+
+    def _cmd_status(self, args: str, e_context: EventContext, session_id: str = "", **_) -> str:
+        from config import conf
+
+        cfg = conf()
+        lines = [_t("📊 CowAgent 运行状态", "📊 CowAgent Status"), ""]
+
+        lines.append(_t(f"  版本: v{__version__}", f"  Version: v{__version__}"))
+        lines.append(_t(f"  进程: PID {os.getpid()}", f"  Process: PID {os.getpid()}"))
+
+        channel = cfg.get("channel_type", "unknown")
+        if isinstance(channel, list):
+            channel = ", ".join(channel)
+        lines.append(_t(f"  通道: {channel}", f"  Channel: {channel}"))
+
+        model_name = cfg.get("model", "unknown")
+        lines.append(_t(f"  模型: {model_name}", f"  Model: {model_name}"))
+
+        mode = "Chat" if cfg.get("agent") is False else "Agent"
+        lines.append(_t(f"  模式: {mode}", f"  Mode: {mode}"))
+
+        from common import i18n
+        lang_label = "中文" if i18n.get_language() == "zh" else "English"
+        lines.append(_t(f"  语言: {lang_label}", f"  Language: {lang_label}"))
+
+        session_id = self._get_session_id(e_context, fallback=session_id)
+        agent = self._get_agent(session_id)
+        if agent:
+            lines.append("")
+            with agent.messages_lock:
+                msg_count = len(agent.messages)
+            lines.append(_t(f"  会话消息数: {msg_count}", f"  Session messages: {msg_count}"))
+
+            if agent.skill_manager:
+                total = len(agent.skill_manager.skills)
+                enabled = sum(
+                    1 for v in agent.skill_manager.skills_config.values()
+                    if v.get("enabled", True)
+                )
+                lines.append(_t(f"  已加载技能: {enabled}/{total}", f"  Loaded skills: {enabled}/{total}"))
+        else:
+            lines.append("")
+            lines.append(_t("  Agent: 未初始化 (首次对话后自动创建)", "  Agent: not initialized (created on first chat)"))
+
+        return "\n".join(lines)
+
+    # ------------------------------------------------------------------
+    # logs
+    # ------------------------------------------------------------------
+
+    def _cmd_logs(self, args: str, e_context, **_) -> str:
+        num_lines = 20
+        if args.strip().isdigit():
+            num_lines = min(int(args.strip()), 50)
+
+        log_file = self._find_log_file()
+        if not log_file:
+            return _t("未找到日志文件", "No log file found")
+
+        try:
+            with open(log_file, "r", encoding="utf-8", errors="replace") as f:
+                all_lines = f.readlines()
+            tail = all_lines[-num_lines:]
+            content = "".join(tail).strip()
+            if not content:
+                return _t("日志为空", "Log is empty")
+            return _t(f"📄 最近 {len(tail)} 条日志:\n\n{content}", f"📄 Last {len(tail)} log lines:\n\n{content}")
+        except Exception as e:
+            return _t(f"读取日志失败: {e}", f"Failed to read log: {e}")
+
+    def _find_log_file(self) -> str:
+        project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+        candidates = [
+            os.path.join(project_root, "nohup.out"),
+            os.path.join(project_root, "run.log"),
+        ]
+        import glob as glob_mod
+        candidates.extend(sorted(glob_mod.glob(os.path.join(project_root, "logs", "*.log")), reverse=True))
+        for f in candidates:
+            if os.path.isfile(f) and os.path.getsize(f) > 0:
+                return f
+        return ""
+
+    # ------------------------------------------------------------------
+    # context
+    # ------------------------------------------------------------------
+
+    def _cmd_context(self, args: str, e_context: EventContext, session_id: str = "", **_) -> str:
+        session_id = self._get_session_id(e_context, fallback=session_id)
+        agent = self._get_agent(session_id)
+
+        sub = args.strip().lower()
+        if sub == "clear":
+            return self._context_clear(agent, session_id)
+        else:
+            return self._context_info(agent, session_id)
+
+    def _context_info(self, agent, session_id: str) -> str:
+        if not agent:
+            return _t("⚠️ Agent 未初始化，暂无上下文信息", "⚠️ Agent not initialized, no context yet")
+
+        with agent.messages_lock:
+            messages = agent.messages.copy()
+
+        if not messages:
+            return _t("当前对话上下文为空", "Current conversation context is empty")
+
+        user_msgs = sum(1 for m in messages if m.get("role") == "user")
+        assistant_msgs = sum(1 for m in messages if m.get("role") == "assistant")
+        tool_msgs = sum(1 for m in messages if m.get("role") == "tool")
+
+        total_chars = sum(len(str(m.get("content", ""))) for m in messages)
+
+        if _t("zh", "en") == "en":
+            lines = [
+                "💬 Current Conversation Context",
+                "",
+                f"  Session: {session_id or 'default'}",
+                f"  Total messages: {len(messages)}",
+                f"  User messages: {user_msgs}",
+                f"  Assistant replies: {assistant_msgs}",
+                f"  Tool calls: {tool_msgs}",
+                f"  Total content length: ~{total_chars} chars",
+                "",
+                "  Send /context clear to clear the conversation context",
+            ]
+        else:
+            lines = [
+                "💬 当前对话上下文",
+                "",
+                f"  会话: {session_id or 'default'}",
+                f"  总消息数: {len(messages)}",
+                f"  用户消息: {user_msgs}",
+                f"  助手回复: {assistant_msgs}",
+                f"  工具调用: {tool_msgs}",
+                f"  内容总长度: ~{total_chars} 字符",
+                "",
+                "  发送 /context clear 可清除对话上下文",
+            ]
+        return "\n".join(lines)
+
+    def _context_clear(self, agent, session_id: str) -> str:
+        if not agent:
+            return _t("⚠️ Agent 未初始化", "⚠️ Agent not initialized")
+
+        with agent.messages_lock:
+            count = len(agent.messages)
+            agent.messages.clear()
+
+        return _t(f"✅ 已清除当前对话上下文 ({count} 条消息)", f"✅ Conversation context cleared ({count} messages)")
+
+    # ------------------------------------------------------------------
+    # config
+    # ------------------------------------------------------------------
+
+    _CONFIG_WRITABLE = {
+        "model",
+        "agent_max_context_tokens",
+        "agent_max_context_turns",
+        "agent_max_steps",
+        "knowledge",
+        "enable_thinking",
+        "self_evolution_enabled",
+        "self_evolution_idle_minutes",
+        "self_evolution_min_turns",
+    }
+
+    _CONFIG_READABLE = _CONFIG_WRITABLE | {"channel_type"}
+
+    def _cmd_config(self, args: str, e_context, **_) -> str:
+        from config import conf, load_config
+        import json as _json
+
+        parts = args.strip().split(None, 1)
+        if not parts:
+            return self._config_show_all()
+
+        key = parts[0].lower()
+        if len(parts) == 1:
+            return self._config_get(key)
+
+        value_str = parts[1].strip()
+        return self._config_set(key, value_str)
+
+    def _config_show_all(self) -> str:
+        from config import conf
+        cfg = conf()
+        lines = [_t("⚙️ 当前配置", "⚙️ Current Config"), ""]
+        for key in sorted(self._CONFIG_READABLE):
+            val = cfg.get(key, "")
+            lines.append(f"  {key}: {val}")
+        lines.append("")
+        lines.append("━━━━━━━━━━━━━━━━━━━━━━━━━━")
+        lines.append(_t("💡 /config <key>: 查看配置", "💡 /config <key>: Show a config item"))
+        lines.append(_t("💡 /config <key> <val>: 修改配置", "💡 /config <key> <val>: Update a config item"))
+        return "\n".join(lines)
+
+    def _config_get(self, key: str) -> str:
+        from config import conf
+        if key not in self._CONFIG_READABLE:
+            available = ", ".join(sorted(self._CONFIG_READABLE))
+            return _t(
+                f"不支持查看 '{key}'\n\n可查看的配置项: {available}",
+                f"Cannot show '{key}'\n\nReadable config items: {available}",
+            )
+        val = conf().get(key, "")
+        return f"⚙️ {key}: {val}"
+
+    def _config_set(self, key: str, value_str: str) -> str:
+        from config import conf, load_config, available_setting
+        import json as _json
+
+        if key not in self._CONFIG_WRITABLE:
+            if key in self._CONFIG_READABLE:
+                return _t(f"⚠️ '{key}' 为只读配置，不支持修改", f"⚠️ '{key}' is read-only and cannot be modified")
+            available = ", ".join(sorted(self._CONFIG_WRITABLE))
+            return _t(
+                f"不支持修改 '{key}'\n\n可修改的配置项: {available}",
+                f"Cannot modify '{key}'\n\nWritable config items: {available}",
+            )
+
+        old_val = conf().get(key, "")
+
+        try:
+            new_val = _json.loads(value_str)
+        except (_json.JSONDecodeError, ValueError):
+            if value_str.lower() == "true":
+                new_val = True
+            elif value_str.lower() == "false":
+                new_val = False
+            else:
+                new_val = value_str
+
+        updates = {key: new_val}
+        old_bot_type = conf().get("bot_type", "")
+
+        if key == "model" and old_bot_type:
+            from common import const
+            if old_bot_type not in (const.CUSTOM,):
+                resolved = self._resolve_bot_type_for_model(str(new_val))
+                if resolved:
+                    updates["bot_type"] = resolved
+
+        # Write to the data dir (~/.cow in desktop, project root otherwise), not
+        # __file__-relative — the latter lives inside the read-only .app bundle
+        # when frozen and writing there breaks the macOS code-signature seal.
+        from config import get_data_root
+        config_path = os.path.join(get_data_root(), "config.json")
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_config = _json.load(f)
+            file_config.update(updates)
+            with open(config_path, "w", encoding="utf-8") as f:
+                _json.dump(file_config, f, indent=4, ensure_ascii=False)
+        except Exception as e:
+            return _t(f"写入 config.json 失败: {e}", f"Failed to write config.json: {e}")
+
+        # Sync updated values to environment variables so that load_config()
+        # won't overwrite the new value with a stale env var (common in Docker).
+        # Match env var keys case-insensitively (Docker compose typically uses
+        # upper-case like MODEL, but lower-case is also possible).
+        synced_envs = {}
+        for k, v in updates.items():
+            if k not in available_setting:
+                continue
+            str_val = str(v)
+            k_lower = k.lower()
+            for env_key in list(os.environ):
+                if env_key.lower() == k_lower:
+                    os.environ[env_key] = str_val
+                    synced_envs[env_key] = str_val
+        logger.info(f"[CowCli] config update: {updates}, synced envs: {synced_envs}")
+
+        try:
+            load_config()
+        except Exception as e:
+            logger.warning(f"[CowCli] config reload warning: {e}")
+
+        result = _t(f"✅ 配置已更新\n\n  {key}: {old_val} → {new_val}", f"✅ Config updated\n\n  {key}: {old_val} → {new_val}")
+        if "bot_type" in updates and updates["bot_type"] != old_bot_type:
+            result += f"\n  bot_type: {old_bot_type} → {updates['bot_type']}"
+        return result
+
+    @staticmethod
+    def _resolve_bot_type_for_model(model_name: str) -> str:
+        """Resolve bot_type from model name, matching AgentBridge mapping."""
+        from common import const
+        _EXACT = {
+            "wenxin": const.BAIDU, "wenxin-4": const.BAIDU,
+            "xunfei": const.XUNFEI, const.QWEN: const.QWEN_DASHSCOPE,
+            const.QIANFAN: const.QIANFAN,
+            const.MODELSCOPE: const.MODELSCOPE,
+            const.MOONSHOT: const.MOONSHOT,
+            "moonshot-v1-8k": const.MOONSHOT, "moonshot-v1-32k": const.MOONSHOT,
+            "moonshot-v1-128k": const.MOONSHOT,
+        }
+        _PREFIX = [
+            ("qwen", const.QWEN_DASHSCOPE), ("qwq", const.QWEN_DASHSCOPE),
+            ("qvq", const.QWEN_DASHSCOPE),
+            ("gemini", const.GEMINI), ("glm", const.ZHIPU_AI),
+            ("claude", const.CLAUDEAPI),
+            ("moonshot", const.MOONSHOT), ("kimi", const.MOONSHOT),
+            ("doubao", const.DOUBAO), ("deepseek", const.DEEPSEEK),
+            ("ernie", const.QIANFAN),
+        ]
+        if not model_name:
+            return const.OPENAI
+        if model_name in _EXACT:
+            return _EXACT[model_name]
+        if model_name.lower().startswith("minimax") or model_name in ["abab6.5-chat"]:
+            return const.MiniMax
+        if model_name in [const.QWEN_TURBO, const.QWEN_PLUS, const.QWEN_MAX]:
+            return const.QWEN_DASHSCOPE
+        lowered_model = model_name.lower()
+        for prefix, btype in _PREFIX:
+            if lowered_model.startswith(prefix):
+                return btype
+        return const.OPENAI
+
+    # ------------------------------------------------------------------
+    # install-browser (shared logic with cow install-browser CLI)
+    # ------------------------------------------------------------------
+
+    @staticmethod
+    def _send_install_progress(e_context, text: str) -> None:
+        """Push a short status line to the chat channel (SSE: phase event, not done)."""
+        if e_context is None:
+            logger.info(f"[CowCli] install-browser: {text}")
+            return
+        try:
+            channel = e_context["channel"]
+            context = e_context["context"]
+            if channel and context:
+                r = Reply(ReplyType.TEXT, text)
+                r.sse_phase = True
+                channel.send(r, context)
+        except Exception as e:
+            logger.warning(f"[CowCli] install-browser progress send failed: {e}")
+
+    def _cmd_install_browser(self, args: str, e_context, **_) -> str:
+        from cli.commands.install import run_install_browser
+
+        if args.strip():
+            return _t(
+                "用法: /install-browser\n\n"
+                "无需参数，等同于终端执行 `cow install-browser`。\n"
+                "安装过程可能持续数分钟；进度会以多条消息推送，pip 详细输出见服务日志。",
+                "Usage: /install-browser\n\n"
+                "No arguments needed; equivalent to running `cow install-browser` in a terminal.\n"
+                "Installation may take a few minutes; progress is pushed as multiple messages, and detailed pip output goes to the service log.",
+            )
+
+        # Suppress detailed stream in chat; phases go through channel.send
+        def _noop_stream(msg: str, fg=None):
+            pass
+
+        code = run_install_browser(
+            stream=_noop_stream,
+            on_phase=lambda m: self._send_install_progress(e_context, m),
+        )
+        if code != 0:
+            return _t(
+                "❌ 安装未成功结束，请查看上方分段提示或服务器日志；"
+                "也可在终端执行 `cow install-browser`。",
+                "❌ Installation did not finish successfully. Check the messages above or the server log; "
+                "you can also run `cow install-browser` in a terminal.",
+            )
+        return _t(
+            "✅ 安装流程已结束。请重启 CowAgent 后使用 browser 工具（进度见上方消息）。",
+            "✅ Installation finished. Restart CowAgent to use the browser tool (see messages above for progress).",
+        )
+
+    # ------------------------------------------------------------------
+    # skill
+    # ------------------------------------------------------------------
+
+    def _cmd_skill(self, args: str, e_context, **_) -> str:
+        parts = args.strip().split(None, 1)
+        sub = parts[0].lower() if parts else ""
+        sub_args = parts[1].strip() if len(parts) > 1 else ""
+
+        if sub == "list":
+            return self._skill_list(sub_args)
+        elif sub == "search":
+            return self._skill_search(sub_args)
+        elif sub == "install":
+            return self._skill_install(sub_args, e_context)
+        elif sub == "uninstall":
+            return self._skill_uninstall(sub_args)
+        elif sub == "info":
+            return self._skill_info(sub_args)
+        elif sub == "enable":
+            return self._skill_set_enabled(sub_args, True)
+        elif sub == "disable":
+            return self._skill_set_enabled(sub_args, False)
+        else:
+            return _t(
+                "用法: /skill <子命令>\n\n"
+                "子命令:\n"
+                "list [--remote]: 查看技能列表\n"
+                "search <关键词>: 搜索技能\n"
+                "install <名称>: 安装技能\n"
+                "uninstall <名称>: 卸载技能\n"
+                "info <名称>: 查看技能详情\n"
+                "enable <名称>: 启用技能\n"
+                "disable <名称>: 禁用技能",
+                "Usage: /skill <subcommand>\n\n"
+                "Subcommands:\n"
+                "list [--remote]: List skills\n"
+                "search <keyword>: Search skills\n"
+                "install <name>: Install a skill\n"
+                "uninstall <name>: Uninstall a skill\n"
+                "info <name>: Show skill details\n"
+                "enable <name>: Enable a skill\n"
+                "disable <name>: Disable a skill",
+            )
+
+    def _refresh_skill_manager(self):
+        """Re-scan skill directories so skills_config.json reflects disk state."""
+        try:
+            from bridge.bridge import Bridge
+            bridge = Bridge()
+            agent_bridge = bridge.get_agent_bridge()
+            for agent in [agent_bridge.default_agent] + list(agent_bridge.agents.values()):
+                if agent and hasattr(agent, 'skill_manager') and agent.skill_manager:
+                    agent.skill_manager.refresh_skills()
+                    break
+        except Exception as e:
+            logger.debug(f"[CowCli] skill refresh skipped: {e}")
+
+    def _skill_list_local(self) -> str:
+        from cli.utils import load_skills_config, get_skills_dir, get_builtin_skills_dir
+        self._refresh_skill_manager()
+        config = load_skills_config()
+
+        if not config:
+            skills_dir = get_skills_dir()
+            builtin_dir = get_builtin_skills_dir()
+            entries = []
+            for d, source in [(builtin_dir, "builtin"), (skills_dir, "custom")]:
+                if not os.path.isdir(d):
+                    continue
+                for name in sorted(os.listdir(d)):
+                    skill_path = os.path.join(d, name)
+                    if os.path.isdir(skill_path) and not name.startswith("."):
+                        if os.path.exists(os.path.join(skill_path, "SKILL.md")):
+                            entries.append({"name": name, "source": source, "enabled": True})
+            if not entries:
+                return _t(
+                    "暂无已安装的技能\n\n💡 /skill list --remote: 浏览技能广场",
+                    "No skills installed yet\n\n💡 /skill list --remote: Browse Skill Hub",
+                )
+            config = {e["name"]: e for e in entries}
+
+        sorted_entries = sorted(config.values(), key=lambda e: e.get("name", ""))
+        enabled_count = sum(1 for e in sorted_entries if e.get("enabled", True))
+
+        lines = [_t(f"📦 已安装的技能 ({enabled_count}/{len(sorted_entries)})", f"📦 Installed Skills ({enabled_count}/{len(sorted_entries)})"), ""]
+        for entry in sorted_entries:
+            name = entry.get("name", "")
+            enabled = entry.get("enabled", True)
+            source = entry.get("source", "")
+            icon = "✅" if enabled else "⏸️"
+            display = entry.get("display_name", "") or name
+            desc = entry.get("description", "")
+            if len(desc) > 50:
+                desc = desc[:47] + "…"
+            line = f"{icon} {display}"
+            if display != name:
+                line += f" ({name})"
+            if desc:
+                line += f"\n   {desc}"
+            if source:
+                line += _t(f"\n   来源: {source}", f"\n   Source: {source}")
+            lines.append(line)
+            lines.append("")
+
+        lines.append("━━━━━━━━━━━━━━━━━━━━━━━━━━")
+        lines.append(_t("💡 /skill list --remote: 浏览技能广场", "💡 /skill list --remote: Browse Skill Hub"))
+        lines.append(_t("💡 /skill info <名称>: 查看详情", "💡 /skill info <name>: Show details"))
+        return "\n".join(lines)
+
+    def _skill_list(self, args: str) -> str:
+        parts = args.strip().split()
+        if "--remote" in parts or "-r" in parts:
+            page = 1
+            for i, p in enumerate(parts):
+                if p == "--page" and i + 1 < len(parts) and parts[i + 1].isdigit():
+                    page = max(1, int(parts[i + 1]))
+            return self._skill_list_remote(page=page)
+        return self._skill_list_local()
+
+    _REMOTE_PAGE_SIZE = 10
+
+    def _skill_list_remote(self, page: int = 1) -> str:
+        import requests
+        from cli.utils import SKILL_HUB_API, load_skills_config
+        page_size = self._REMOTE_PAGE_SIZE
+        try:
+            resp = requests.get(
+                f"{SKILL_HUB_API}/skills",
+                params={"page": page, "limit": page_size},
+                timeout=10,
+            )
+            resp.raise_for_status()
+            data = resp.json()
+            skills = data.get("skills", [])
+            total = data.get("total", len(skills))
+        except Exception as e:
+            return _t(f"获取技能广场失败: {e}", f"Failed to fetch Skill Hub: {e}")
+
+        if not skills and page == 1:
+            return _t("技能广场暂无可用技能", "No skills available on Skill Hub")
+
+        total_pages = max(1, (total + page_size - 1) // page_size)
+        page = min(page, total_pages)
+        installed = set(load_skills_config().keys())
+
+        lines = [_t("🌐 技能广场", "🌐 Skill Hub"), ""]
+        for s in skills:
+            name = s.get("name", "")
+            display = s.get("display_name", "") or name
+            desc = s.get("description", "")
+            if len(desc) > 50:
+                desc = desc[:47] + "…"
+            badge = _t(" [已安装]", " [installed]") if name in installed else ""
+            lines.append(f"📌 {display}{badge}")
+            lines.append(_t(f"   名称: {name}", f"   Name: {name}"))
+            if desc:
+                lines.append(f"   {desc}")
+            lines.append("")
+
+        lines.append("━━━━━━━━━━━━━━━━━━━━━━━━━━")
+        lines.append(_t(f"📄 第 {page}/{total_pages} 页", f"📄 Page {page}/{total_pages}"))
+        if page < total_pages:
+            lines.append(_t(f"💡 /skill list --remote --page {page + 1}: 下一页", f"💡 /skill list --remote --page {page + 1}: Next page"))
+        if page > 1:
+            lines.append(_t(f"💡 /skill list --remote --page {page - 1}: 上一页", f"💡 /skill list --remote --page {page - 1}: Previous page"))
+        lines.append(_t("💡 /skill install <名称>: 安装技能", "💡 /skill install <name>: Install a skill"))
+        lines.append(_t("💡 /skill search <关键词>: 搜索技能", "💡 /skill search <keyword>: Search skills"))
+        lines.append(_t("🌐 https://skills.cowagent.ai  在线浏览全部技能", "🌐 https://skills.cowagent.ai  Browse all skills online"))
+        return "\n".join(lines)
+
+    def _skill_search(self, query: str) -> str:
+        if not query:
+            return _t("请指定搜索关键词: /skill search <关键词>", "Please specify a search keyword: /skill search <keyword>")
+
+        import requests
+        from cli.utils import SKILL_HUB_API, load_skills_config
+        try:
+            resp = requests.get(f"{SKILL_HUB_API}/skills/search", params={"q": query}, timeout=10)
+            resp.raise_for_status()
+            skills = resp.json().get("skills", [])
+        except Exception as e:
+            return _t(f"搜索失败: {e}", f"Search failed: {e}")
+
+        if not skills:
+            return _t(f"未找到与「{query}」相关的技能", f"No skills found for \"{query}\"")
+
+        installed = set(load_skills_config().keys())
+        lines = [_t(f"🔍 搜索「{query}」({len(skills)} 个结果)", f"🔍 Search \"{query}\" ({len(skills)} results)"), ""]
+        for s in skills:
+            name = s.get("name", "")
+            display = s.get("display_name", "") or name
+            desc = s.get("description", "")
+            if len(desc) > 50:
+                desc = desc[:47] + "…"
+            badge = _t(" [已安装]", " [installed]") if name in installed else ""
+            lines.append(f"📌 {display}{badge}")
+            lines.append(_t(f"   名称: {name}", f"   Name: {name}"))
+            if desc:
+                lines.append(f"   {desc}")
+            lines.append("")
+
+        lines.append("━━━━━━━━━━━━━━━━━━━━━━━━━━")
+        lines.append(_t("💡 /skill install <名称>: 安装技能", "💡 /skill install <name>: Install a skill"))
+        return "\n".join(lines)
+
+    _INSTALL_TIMEOUT = 60
+
+    def _skill_install(self, name: str, e_context: EventContext) -> str:
+        if not name:
+            return _t("请指定要安装的技能: /skill install <名称>", "Please specify a skill to install: /skill install <name>")
+
+        from concurrent.futures import ThreadPoolExecutor, TimeoutError as FuturesTimeout
+        from cli.commands.skill import install_skill
+
+        try:
+            with ThreadPoolExecutor(max_workers=1) as pool:
+                future = pool.submit(install_skill, name)
+                result = future.result(timeout=self._INSTALL_TIMEOUT)
+
+            if result.error:
+                return _t(f"安装失败: {result.error}", f"Install failed: {result.error}")
+
+            if not result.installed:
+                return "\n".join(result.messages) if result.messages else _t("未找到可安装的技能", "No installable skill found")
+
+            return self._format_install_result(result)
+        except FuturesTimeout:
+            return _t("安装超时，请稍后重试或检查网络连接", "Install timed out. Please retry later or check your network connection.")
+        except Exception as e:
+            return _t(f"安装失败: {e}", f"Install failed: {e}")
+
+    @staticmethod
+    def _format_install_result(result) -> str:
+        """Format InstallResult into a chat-friendly message."""
+        from cli.commands.skill import _read_skill_description
+        from cli.utils import get_skills_dir, load_skills_config
+        skills_dir = get_skills_dir()
+        config = load_skills_config()
+
+        lines = []
+        for skill_name in result.installed:
+            desc = _read_skill_description(os.path.join(skills_dir, skill_name))
+            display = config.get(skill_name, {}).get("display_name", "")
+            lines.append(_t(f"✅ 技能安装成功：{skill_name}", f"✅ Skill installed: {skill_name}"))
+            if display and display != skill_name:
+                lines.append(_t(f"   名称：{display}", f"   Name: {display}"))
+            if desc:
+                lines.append(_t(f"   描述：{desc}", f"   Description: {desc}"))
+
+        if len(result.installed) > 1:
+            lines.append(_t(f"\n共安装 {len(result.installed)} 个技能", f"\nInstalled {len(result.installed)} skills"))
+
+        return "\n".join(lines)
+
+    def _skill_uninstall(self, name: str) -> str:
+        if not name:
+            return _t("请指定要卸载的技能: /skill uninstall <名称>", "Please specify a skill to uninstall: /skill uninstall <name>")
+
+        import shutil
+        import json
+        from cli.utils import get_skills_dir
+
+        skills_dir = get_skills_dir()
+        skill_dir = os.path.join(skills_dir, name)
+
+        if not os.path.exists(skill_dir):
+            skill_dir = self._resolve_skill_dir(name, skills_dir)
+
+        if not skill_dir:
+            return _t(f"技能 '{name}' 未安装", f"Skill '{name}' is not installed")
+
+        shutil.rmtree(skill_dir)
+
+        config_path = os.path.join(skills_dir, "skills_config.json")
+        if os.path.exists(config_path):
+            try:
+                with open(config_path, "r", encoding="utf-8") as f:
+                    config = json.load(f)
+                config.pop(name, None)
+                with open(config_path, "w", encoding="utf-8") as f:
+                    json.dump(config, f, indent=4, ensure_ascii=False)
+            except Exception:
+                pass
+
+        return _t(f"✅ 技能 '{name}' 已卸载", f"✅ Skill '{name}' uninstalled")
+
+    @staticmethod
+    def _resolve_skill_dir(name: str, skills_dir: str):
+        """Find actual directory for a skill whose folder name may differ from its config name."""
+        if not os.path.isdir(skills_dir):
+            return None
+        for entry in os.listdir(skills_dir):
+            entry_path = os.path.join(skills_dir, entry)
+            if not os.path.isdir(entry_path) or entry.startswith("."):
+                continue
+            if entry == name or entry.startswith(name + "-") or entry.endswith("-" + name):
+                skill_md = os.path.join(entry_path, "SKILL.md")
+                if os.path.exists(skill_md):
+                    return entry_path
+        return None
+
+    @staticmethod
+    def _strip_frontmatter(content: str):
+        """Strip YAML frontmatter and return (metadata_dict, body)."""
+        if not content.startswith("---"):
+            return {}, content
+        end = content.find("\n---", 3)
+        if end == -1:
+            return {}, content
+        fm_text = content[3:end].strip()
+        body = content[end + 4:].lstrip("\n")
+        meta = {}
+        for line in fm_text.split("\n"):
+            if ":" in line:
+                key, _, val = line.partition(":")
+                meta[key.strip()] = val.strip().strip('"').strip("'")
+        return meta, body
+
+    def _skill_info(self, name: str) -> str:
+        if not name:
+            return _t("请指定技能名称: /skill info <名称>", "Please specify a skill name: /skill info <name>")
+
+        from cli.utils import get_skills_dir, get_builtin_skills_dir
+
+        skills_dir = get_skills_dir()
+        builtin_dir = get_builtin_skills_dir()
+
+        skill_dir = None
+        source = None
+        for d, src in [(skills_dir, "custom"), (builtin_dir, "builtin")]:
+            candidate = os.path.join(d, name)
+            if os.path.isdir(candidate):
+                skill_dir = candidate
+                source = src
+                break
+
+        if not skill_dir:
+            resolved = self._resolve_skill_dir(name, skills_dir)
+            if resolved:
+                skill_dir = resolved
+                source = "custom"
+
+        if not skill_dir:
+            return _t(f"技能 '{name}' 未找到", f"Skill '{name}' not found")
+
+        skill_md = os.path.join(skill_dir, "SKILL.md")
+        if not os.path.exists(skill_md):
+            return _t(f"技能 '{name}' 没有 SKILL.md 文件", f"Skill '{name}' has no SKILL.md file")
+
+        with open(skill_md, "r", encoding="utf-8") as f:
+            content = f.read()
+
+        meta, body = self._strip_frontmatter(content)
+
+        header_lines = [_t(f"📖 技能: {name} [{source}]", f"📖 Skill: {name} [{source}]"), ""]
+        desc = meta.get("description", "")
+        if desc:
+            header_lines.append(f"  {desc}")
+            header_lines.append("")
+
+        lines = body.split("\n")
+        preview = "\n".join(lines[:30])
+        result = "\n".join(header_lines) + preview
+        if len(lines) > 30:
+            result += f"\n\n... ({len(lines) - 30} more lines)"
+        return result
+
+    def _skill_set_enabled(self, name: str, enabled: bool) -> str:
+        if not name:
+            return _t(
+                f"请指定技能名称: /skill {'enable' if enabled else 'disable'} <名称>",
+                f"Please specify a skill name: /skill {'enable' if enabled else 'disable'} <name>",
+            )
+
+        import json
+        from cli.utils import get_skills_dir
+
+        skills_dir = get_skills_dir()
+        config_path = os.path.join(skills_dir, "skills_config.json")
+
+        if not os.path.exists(config_path):
+            return _t("技能配置文件不存在", "Skills config file not found")
+
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                config = json.load(f)
+        except Exception as e:
+            return _t(f"读取配置失败: {e}", f"Failed to read config: {e}")
+
+        if name not in config:
+            return _t(f"技能 '{name}' 未在配置中找到", f"Skill '{name}' not found in config")
+
+        config[name]["enabled"] = enabled
+        with open(config_path, "w", encoding="utf-8") as f:
+            json.dump(config, f, indent=4, ensure_ascii=False)
+
+        icon = "✅" if enabled else "⬚"
+        if enabled:
+            return _t(f"{icon} 技能 '{name}' 已启用", f"{icon} Skill '{name}' enabled")
+        return _t(f"{icon} 技能 '{name}' 已禁用", f"{icon} Skill '{name}' disabled")
+
+    # ------------------------------------------------------------------
+    # memory
+    # ------------------------------------------------------------------
+
+    def _cmd_memory(self, args: str, e_context, session_id: str = "", **_) -> str:
+        parts = args.strip().split()
+        sub = parts[0].lower() if parts else ""
+
+        if sub == "dream":
+            days = 3
+            if len(parts) > 1 and parts[1].isdigit():
+                days = max(1, min(int(parts[1]), 30))
+            return self._memory_dream(days, e_context, session_id)
+        elif sub in ("rebuild-index", "rebuild_index", "rebuild"):
+            return self._memory_rebuild_index(e_context, session_id)
+        elif sub in ("status", "info", ""):
+            if sub == "":
+                return self._memory_help()
+            return self._memory_status()
+        else:
+            return self._memory_help()
+
+    @staticmethod
+    def _memory_help() -> str:
+        return _t(
+            "🧠 记忆管理\n\n"
+            "用法: /memory <子命令>\n\n"
+            "子命令:\n"
+            "status: 查看索引状态 (provider / model / dim / chunks)\n"
+            "rebuild-index: 清空并重建向量索引 (切换 embedding 模型后必须执行)\n"
+            "dream [N]: 手动触发记忆蒸馏 (整理近N天, 默认3, 最多30)",
+            "🧠 Memory Management\n\n"
+            "Usage: /memory <subcommand>\n\n"
+            "Subcommands:\n"
+            "status: Show index status (provider / model / dim / chunks)\n"
+            "rebuild-index: Rebuild the vector index (required after switching embedding model)\n"
+            "dream [N]: Trigger memory distillation (last N days, default 3, max 30)",
+        )
+
+    def _memory_dream(self, days: int, e_context, session_id: str) -> str:
+        session_id = self._get_session_id(e_context, fallback=session_id)
+        agent = self._get_agent(session_id)
+
+        flush_mgr = None
+        if agent and agent.memory_manager:
+            flush_mgr = agent.memory_manager.flush_manager
+
+        if not flush_mgr:
+            try:
+                flush_mgr = self._create_standalone_flush_manager()
+            except Exception as e:
+                return _t(f"⚠️ 无法初始化记忆蒸馏: {e}", f"⚠️ Failed to initialize memory distillation: {e}")
+
+        if not flush_mgr.llm_model:
+            return _t("⚠️ 未配置 LLM 模型，无法执行记忆蒸馏", "⚠️ No LLM model configured, cannot run memory distillation")
+
+        # SaaS (e_context is None): run synchronously, return full result
+        if e_context is None:
+            return self._memory_dream_sync(flush_mgr, days)
+
+        # Local channels: run in background, notify via channel.send()
+        is_web = self._is_web_channel(e_context)
+
+        def _run():
+            try:
+                result = flush_mgr.deep_dream(lookback_days=days, force=True)
+                if result:
+                    self._notify(e_context, self._build_dream_result(flush_mgr, is_web))
+                else:
+                    self._notify(e_context, _t("💤 记忆蒸馏跳过 — 没有新的记忆内容需要整理", "💤 Memory distillation skipped — no new memories to process"))
+            except Exception as e:
+                logger.warning(f"[CowCli] /memory dream failed: {e}")
+                self._notify(e_context, _t(f"❌ 记忆蒸馏失败: {e}", f"❌ Memory distillation failed: {e}"))
+
+        threading.Thread(target=_run, daemon=True).start()
+        return _t(
+            f"🌙 记忆蒸馏已启动 (整理近 {days} 天的记忆)\n\n整理在后台执行，完成后会通知你。",
+            f"🌙 Memory distillation started (processing the last {days} days)\n\nRunning in the background; you'll be notified when it's done.",
+        )
+
+    def _memory_dream_sync(self, flush_mgr, days: int) -> str:
+        """Run deep dream synchronously and return the full result."""
+        try:
+            result = flush_mgr.deep_dream(lookback_days=days, force=True)
+            if result:
+                return self._build_dream_result(flush_mgr, is_web=True)
+            return _t("💤 记忆蒸馏跳过 — 没有新的记忆内容需要整理", "💤 Memory distillation skipped — no new memories to process")
+        except Exception as e:
+            logger.warning(f"[CowCli] /memory dream sync failed: {e}")
+            return _t(f"❌ 记忆蒸馏失败: {e}", f"❌ Memory distillation failed: {e}")
+
+    @staticmethod
+    def _resolve_active_embedding():
+        """
+        Resolve (provider_label, model, dim) from the LATEST config, not the
+        possibly-stale provider instance cached on a running agent. Used by
+        /memory status and rebuild-index hints so they reflect what a rebuild
+        will actually run as after the user changes embedding_provider.
+        Returns (label, model, dim) where any field may be None when unknown.
+        """
+        from agent.memory.embedding import EMBEDDING_VENDORS
+        from config import conf
+
+        provider_key = (conf().get("embedding_provider") or "").strip().lower()
+        cfg_model = (conf().get("embedding_model") or "").strip()
+        try:
+            cfg_dim = int(conf().get("embedding_dimensions") or 0)
+        except (TypeError, ValueError):
+            cfg_dim = 0
+
+        if not provider_key:
+            # Legacy auto path: openai -> linkai, both default to text-embedding-3-small (1536).
+            if (conf().get("open_ai_api_key") or "").strip():
+                return "openai (legacy)", "text-embedding-3-small", 1536
+            if (conf().get("linkai_api_key") or "").strip():
+                return "linkai (legacy)", "text-embedding-3-small", 1536
+            return "(legacy)", None, None
+
+        # Since we have added support for custom providers for vector models, this part should be modified accordingly:
+        # Custom providers ("custom:<id>") resolve to the "custom" vendor key.
+        resolved_key = "custom" if provider_key.startswith("custom:") else provider_key
+        meta = EMBEDDING_VENDORS.get(resolved_key) or {}
+        model = cfg_model or meta.get("default_model")
+        # Custom provider model fallback: read from custom_providers entry.
+        if not model and provider_key.startswith("custom:"):
+            from models.custom_provider import parse_custom_bot_type, get_custom_providers, _find_provider_by_id
+            _, custom_id = parse_custom_bot_type(provider_key)
+            if custom_id:
+                entry = _find_provider_by_id(get_custom_providers(), custom_id)
+                if entry and entry.get("model"):
+                    model = entry["model"]
+        dim = cfg_dim if cfg_dim > 0 else meta.get("default_dimensions")
+        return provider_key, model, dim
+
+    def _memory_status(self) -> str:
+        """Show current memory index status."""
+        from agent.memory.embedding import detect_index_dim
+        from config import conf
+
+        agent = self._get_agent("")
+        memory_manager = agent.memory_manager if agent else None
+
+        lines = [_t("🧠 记忆索引状态", "🧠 Memory Index Status"), ""]
+        if not memory_manager:
+            lines.append(_t("  ⚠️ Agent 尚未初始化，先发一条普通消息再试", "  ⚠️ Agent not initialized yet, send a normal message first"))
+            return "\n".join(lines)
+
+        stats = memory_manager.storage.get_stats()
+        db_path = memory_manager.config.get_db_path()
+        embedded = stats.get('embedded', 0)
+        chunks = stats.get('chunks', 0)
+        lines.append(f"  索引DB  : {db_path}")
+        lines.append(f"  Files   : {stats.get('files', 0)}")
+        lines.append(f"  Chunks  : {chunks} (embedded: {embedded})")
+        lines.append("")
+
+        # Resolve from the latest config so users see what /memory rebuild-index
+        # will actually run as — not what the cached agent was initialized with.
+        cfg_provider, cfg_model, cfg_dim = self._resolve_active_embedding()
+        provider_obj = memory_manager.embedding_provider
+        if cfg_model:
+            lines.append(f"  Provider : {cfg_provider}")
+            lines.append(f"  Model    : {cfg_model}")
+            lines.append(f"  Dim      : {cfg_dim if cfg_dim else '?'}")
+        else:
+            lines.append(_t("  Provider : (未初始化, keyword-only)", "  Provider : (not initialized, keyword-only)"))
+
+        # Health hints — only shown when the user has explicitly opted into
+        # vector search via `embedding_provider`. Legacy users (no explicit
+        # provider) are running in a "best-effort vectors" mode by design;
+        # nagging them about missing/mismatched vectors would be noise.
+        warnings = []
+        explicitly_opted_in = (conf().get("embedding_provider") or "").strip() != ""
+        if explicitly_opted_in and provider_obj is not None:
+            if chunks > 0 and embedded < chunks:
+                missing = chunks - embedded
+                warnings.append(_t(
+                    f"  ⚠️ {missing}/{chunks} 个 chunk 没有向量；运行 /memory rebuild-index 后所有记忆才会被向量化检索",
+                    f"  ⚠️ {missing}/{chunks} chunks have no vectors; run /memory rebuild-index to enable vector search for all memories",
+                ))
+
+            index_dim = detect_index_dim(memory_manager.storage)
+            if index_dim is not None and cfg_dim and index_dim != cfg_dim:
+                warnings.append(_t(
+                    f"  ⚠️ 索引中存量向量为 {index_dim} 维，与当前配置 {cfg_dim} 维不一致；运行 /memory rebuild-index 重建后向量检索才会生效",
+                    f"  ⚠️ Existing vectors are {index_dim}-dim, mismatching the current {cfg_dim}-dim config; run /memory rebuild-index to make vector search work",
+                ))
+
+        if warnings:
+            lines.append("")
+            lines.extend(warnings)
+
+        return "\n".join(lines)
+
+    def _memory_rebuild_index(self, e_context, session_id: str) -> str:
+        """Rebuild the vector index using the current agent's memory_manager."""
+        session_id = self._get_session_id(e_context, fallback=session_id)
+        agent = self._get_agent(session_id)
+        if not agent or not agent.memory_manager:
+            return _t(
+                "⚠️ Agent 尚未初始化，无法重建索引。\n"
+                "请先发送一条普通消息触发 Agent 启动后再试。",
+                "⚠️ Agent not initialized, cannot rebuild the index.\n"
+                "Send a normal message first to start the Agent, then try again.",
+            )
+
+        memory_manager = agent.memory_manager
+
+        # Rebuild against the LATEST config: build a fresh provider from
+        # config.json and swap it onto memory_manager. The agent's
+        # conversation_history and other state are untouched.
+        try:
+            from bridge.agent_initializer import AgentInitializer
+            fresh_provider = AgentInitializer(bridge=None, agent_bridge=None) \
+                ._init_embedding_provider(memory_manager.config, session_id=session_id)
+        except Exception as e:
+            logger.exception("[CowCli] /memory rebuild-index: build provider failed")
+            return _t(f"⚠️ 无法根据当前配置构造 embedding provider: {e}", f"⚠️ Failed to build embedding provider from current config: {e}")
+
+        if fresh_provider is None:
+            return _t(
+                "⚠️ 当前没有可用的 embedding provider。\n"
+                "请检查 config.json 中的 embedding 相关配置 (provider / api key)。",
+                "⚠️ No embedding provider available.\n"
+                "Check the embedding settings in config.json (provider / api key).",
+            )
+        memory_manager.embedding_provider = fresh_provider
+
+        model_label = getattr(fresh_provider, "model", "?")
+        dim_label = getattr(fresh_provider, "dimensions", "?")
+
+        # SaaS (e_context is None): run synchronously, return final result
+        if e_context is None:
+            return self._memory_rebuild_sync(memory_manager, model_label, dim_label)
+
+        # Local channels: run in background, push progress + final result
+        from agent.memory.embedding import rebuild_in_process
+
+        def _run():
+            try:
+                result = rebuild_in_process(memory_manager)
+                if result.ok:
+                    self._notify(
+                        e_context,
+                        _t(
+                            f"✅ 索引重建完成\n"
+                            f"  cleared : {result.removed}\n"
+                            f"  chunks  : {result.chunks}\n"
+                            f"  files   : {result.files}",
+                            f"✅ Index rebuild complete\n"
+                            f"  cleared : {result.removed}\n"
+                            f"  chunks  : {result.chunks}\n"
+                            f"  files   : {result.files}",
+                        ),
+                    )
+                else:
+                    self._notify(e_context, _t(f"❌ 索引重建失败: {result.error}", f"❌ Index rebuild failed: {result.error}"))
+            except Exception as e:
+                logger.exception("[CowCli] /memory rebuild-index failed")
+                self._notify(e_context, _t(f"❌ 索引重建失败: {e}", f"❌ Index rebuild failed: {e}"))
+
+        threading.Thread(target=_run, daemon=True).start()
+        return _t(
+            f"🔧 索引重建已启动 (model={model_label}, dim={dim_label})\n\n"
+            f"将重新向量化所有记忆和知识文件，完成后会通知你。",
+            f"🔧 Index rebuild started (model={model_label}, dim={dim_label})\n\n"
+            f"Re-vectorizing all memory and knowledge files; you'll be notified when done.",
+        )
+
+    @staticmethod
+    def _memory_rebuild_sync(memory_manager, model_label, dim_label) -> str:
+        from agent.memory.embedding import rebuild_in_process
+
+        try:
+            result = rebuild_in_process(memory_manager)
+        except Exception as e:
+            logger.exception("[CowCli] /memory rebuild-index sync failed")
+            return _t(f"❌ 索引重建失败: {e}", f"❌ Index rebuild failed: {e}")
+
+        if not result.ok:
+            return _t(f"❌ 索引重建失败: {result.error}", f"❌ Index rebuild failed: {result.error}")
+        return _t(
+            f"✅ 索引重建完成 (model={model_label}, dim={dim_label})\n"
+            f"  cleared : {result.removed}\n"
+            f"  chunks  : {result.chunks}\n"
+            f"  files   : {result.files}",
+            f"✅ Index rebuild complete (model={model_label}, dim={dim_label})\n"
+            f"  cleared : {result.removed}\n"
+            f"  chunks  : {result.chunks}\n"
+            f"  files   : {result.files}",
+        )
+
+    @staticmethod
+    def _notify(e_context, text: str):
+        """Push a notification message back to the chat channel."""
+        if e_context is None:
+            logger.info(f"[CowCli] {text}")
+            return
+        try:
+            channel = e_context["channel"]
+            context = e_context["context"]
+            if channel and context:
+                channel.send(Reply(ReplyType.TEXT, text), context)
+        except Exception as e:
+            logger.warning(f"[CowCli] notify failed: {e}")
+
+    @staticmethod
+    def _is_web_channel(e_context) -> bool:
+        if e_context is None:
+            return False
+        try:
+            return e_context["context"].kwargs.get("channel_type") == "web"
+        except Exception:
+            return False
+
+    @staticmethod
+    def _harden_line_breaks(text: str, e_context) -> str:
+        """WeChat PC renders bot messages as Markdown, where a lone '\\n' is
+        collapsed into a space, so plain-text CLI output gets squashed onto
+        one line. Prefix consecutive text lines with '- ' so the Markdown
+        list keeps each on its own line (the only form WeChat respects).
+        WeChat-only; other channels are untouched. Blank lines, code fences,
+        and lines that are already list items are left intact."""
+        if e_context is None or not text or "\n" not in text:
+            return text
+        try:
+            if e_context["context"].kwargs.get("channel_type") != "weixin":
+                return text
+        except Exception:
+            return text
+
+        out = []
+        in_code = False
+        lines = text.split("\n")
+        for i, line in enumerate(lines):
+            if line.lstrip().startswith("```"):
+                in_code = not in_code
+                out.append(line)
+                continue
+            stripped = line.lstrip()
+            prev_packed = i > 0 and lines[i - 1].strip() != ""
+            next_packed = i < len(lines) - 1 and lines[i + 1].strip() != ""
+            # Only convert lines inside a multi-line block (a neighbour line is
+            # non-blank); standalone paragraphs separated by blank lines, code
+            # blocks, blank lines, and existing list items are left intact.
+            if (in_code or not stripped or stripped.startswith(("- ", "* ", "+ "))
+                    or not (prev_packed or next_packed)):
+                out.append(line)
+            else:
+                out.append("- " + stripped)
+        return "\n".join(out)
+
+    @staticmethod
+    def _build_dream_result(flush_mgr, is_web: bool) -> str:
+        """Build dream completion message with diary content."""
+        from datetime import datetime
+        lines = [_t("✅ 记忆蒸馏完成", "✅ Memory distillation complete")]
+
+        # Read today's dream diary
+        today = datetime.now().strftime("%Y-%m-%d")
+        diary_file = flush_mgr.memory_dir / "dreams" / f"{today}.md"
+        if diary_file.exists():
+            diary = diary_file.read_text(encoding="utf-8").strip()
+            # Strip the "# Dream Diary: ..." header line
+            diary_lines = diary.split("\n")
+            if diary_lines and diary_lines[0].startswith("# "):
+                diary = "\n".join(diary_lines[1:]).strip()
+            if diary:
+                lines.append(f"\n{diary}")
+
+        if is_web:
+            lines.append(_t("\n[MEMORY.md](/memory/MEMORY.md) | [梦境日记](/memory/dreams)", "\n[MEMORY.md](/memory/MEMORY.md) | [Dream Diary](/memory/dreams)"))
+        else:
+            lines.append(_t("\nMEMORY.md 已更新", "\nMEMORY.md updated"))
+
+        return "\n".join(lines)
+
+    @staticmethod
+    def _create_standalone_flush_manager():
+        """Create a MemoryFlushManager without a running agent (for pre-init dream)."""
+        from pathlib import Path
+        from config import conf
+        from common.utils import expand_path
+        from agent.memory.summarizer import MemoryFlushManager
+        from bridge.bridge import Bridge
+        from bridge.agent_bridge import AgentLLMModel
+
+        workspace = Path(expand_path(conf().get("agent_workspace", "~/cow")))
+        flush_mgr = MemoryFlushManager(workspace_dir=workspace)
+        flush_mgr.llm_model = AgentLLMModel(Bridge())
+        return flush_mgr
+
+    # ------------------------------------------------------------------
+    # knowledge
+    # ------------------------------------------------------------------
+
+    def _cmd_knowledge(self, args: str, e_context, **_) -> str:
+        sub = args.strip().lower().split(None, 1)[0] if args.strip() else ""
+
+        if sub == "on":
+            return self._knowledge_toggle(True)
+        elif sub == "off":
+            return self._knowledge_toggle(False)
+        elif sub in ("list", "tree"):
+            return self._knowledge_tree()
+        else:
+            return self._knowledge_stats()
+
+    def _knowledge_toggle(self, enabled: bool) -> str:
+        from config import conf
+        import json as _json
+
+        conf()["knowledge"] = enabled
+
+        # Data dir (~/.cow in desktop), not __file__-relative — see _config_set.
+        from config import get_data_root
+        config_path = os.path.join(get_data_root(), "config.json")
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                file_config = _json.load(f)
+            file_config["knowledge"] = enabled
+            with open(config_path, "w", encoding="utf-8") as f:
+                _json.dump(file_config, f, indent=4, ensure_ascii=False)
+        except Exception as e:
+            return _t(f"⚠️ 内存中已切换，但写入 config.json 失败: {e}", f"⚠️ Switched in memory, but failed to write config.json: {e}")
+
+        if enabled:
+            return _t(
+                "📚 知识库已开启 ✅\n\n知识库将在下次对话中生效",
+                "📚 Knowledge base enabled ✅\n\nIt will take effect in the next conversation",
+            )
+        return _t(
+            "📚 知识库已关闭 ❌\n\n知识库系统已停用，不再注入提示词和索引知识文件",
+            "📚 Knowledge base disabled ❌\n\nThe knowledge system is off; no prompt injection or file indexing",
+        )
+
+    def _knowledge_stats(self) -> str:
+        from config import conf
+        from common.utils import expand_path
+        knowledge_dir = os.path.join(
+            expand_path(conf().get("agent_workspace", "~/cow")),
+            "knowledge"
+        )
+        if not os.path.isdir(knowledge_dir):
+            return _t("📚 知识库目录不存在\n\n💡 开启知识库: /knowledge on", "📚 Knowledge base directory not found\n\n💡 Enable it: /knowledge on")
+
+        enabled = conf().get("knowledge", True)
+        total_files = 0
+        total_bytes = 0
+        cat_count = {}
+
+        for root, dirs, files in os.walk(knowledge_dir):
+            dirs[:] = [d for d in dirs if not d.startswith(".")]
+            rel_root = os.path.relpath(root, knowledge_dir)
+            category = rel_root.split(os.sep)[0] if rel_root != "." else "root"
+            for f in files:
+                if f.endswith(".md") and f not in ("index.md", "log.md"):
+                    total_files += 1
+                    total_bytes += os.path.getsize(os.path.join(root, f))
+                    cat_count[category] = cat_count.get(category, 0) + 1
+
+        status = _t("✅ 已开启", "✅ Enabled") if enabled else _t("❌ 已关闭", "❌ Disabled")
+        lines = [
+            _t("📚 知识库统计", "📚 Knowledge Base Stats"),
+            "",
+            _t(f"状态: {status}", f"Status: {status}"),
+            _t(f"页面: {total_files} 篇", f"Pages: {total_files}"),
+            _t(f"大小: {total_bytes / 1024:.1f} KB", f"Size: {total_bytes / 1024:.1f} KB"),
+            "",
+        ]
+        if cat_count:
+            for cat in sorted(cat_count.keys()):
+                lines.append(f"- {cat}/ ({cat_count[cat]} pages)")
+            lines.append("")
+
+        lines.append(_t(f"路径: {knowledge_dir}", f"Path: {knowledge_dir}"))
+        lines.extend([
+            "",
+            "━━━━━━━━━━━━━━━━━━━━━━━━━━",
+            _t("💡 /knowledge list: 查看文件树", "💡 /knowledge list: Show file tree"),
+            _t("💡 /knowledge on|off: 开关知识库", "💡 /knowledge on|off: Toggle knowledge base"),
+        ])
+        return "\n".join(lines)
+
+    def _knowledge_tree(self) -> str:
+        from config import conf
+        from common.utils import expand_path
+        knowledge_dir = os.path.join(
+            expand_path(conf().get("agent_workspace", "~/cow")),
+            "knowledge"
+        )
+        if not os.path.isdir(knowledge_dir):
+            return _t("📚 知识库目录不存在\n\n💡 开启知识库: /knowledge on", "📚 Knowledge base directory not found\n\n💡 Enable it: /knowledge on")
+
+        tree = ["knowledge/"]
+
+        subdirs = sorted([
+            d for d in os.listdir(knowledge_dir)
+            if os.path.isdir(os.path.join(knowledge_dir, d)) and not d.startswith(".")
+        ])
+
+        for i, subdir in enumerate(subdirs):
+            is_last_dir = (i == len(subdirs) - 1)
+            branch = "└── " if is_last_dir else "├── "
+            subdir_path = os.path.join(knowledge_dir, subdir)
+            md_files = sorted([
+                f for f in os.listdir(subdir_path)
+                if f.endswith(".md") and not f.startswith(".")
+            ])
+            tree.append(f"{branch}{subdir}/ ({len(md_files)})")
+
+            child_prefix = "    " if is_last_dir else "│   "
+            max_show = 12
+            for j, fname in enumerate(md_files[:max_show]):
+                is_last_file = (j == len(md_files[:max_show]) - 1) and len(md_files) <= max_show
+                fb = "└── " if is_last_file else "├── "
+                name = fname.replace(".md", "")
+                tree.append(f"{child_prefix}{fb}{name}")
+            if len(md_files) > max_show:
+                tree.append(f"{child_prefix}└── ... +{len(md_files) - max_show} more")
+
+        if not subdirs:
+            tree.append(_t("(空)", "(empty)"))
+
+        return "```\n" + "\n".join(tree) + "\n```"
+
+    # ------------------------------------------------------------------
+    # Helpers
+    # ------------------------------------------------------------------
+
+    def _get_session_id(self, e_context, fallback: str = "") -> str:
+        if e_context is None:
+            return fallback
+        context = e_context["context"]
+        return context.kwargs.get("session_id") or context.get("session_id", "")
+
+    def _get_agent(self, session_id: str):
+        try:
+            from bridge.bridge import Bridge
+            bridge = Bridge()
+            if not bridge._agent_bridge:
+                return None
+            return bridge._agent_bridge.get_agent(session_id=session_id or None)
+        except Exception:
+            return None
+
+    def get_help_text(self, **kwargs):
+        return _t("在对话中使用 /help 或 cow help 查看可用命令", "Use /help or cow help in chat to see available commands")
diff --git a/plugins/dungeon/README.md b/plugins/dungeon/README.md
new file mode 100644
index 0000000..2c2e8cd
--- /dev/null
+++ b/plugins/dungeon/README.md
@@ -0,0 +1,4 @@
+玩地牢游戏的聊天插件，触发方法如下：
+
+- `$开始冒险 <背景故事>` - 以<背景故事>开始一个地牢游戏，不填写会使用默认背景故事。之后聊天中你的所有消息会帮助ai完善这个故事。
+- `$停止冒险` - 停止一个地牢游戏，回归正常的ai。
diff --git a/plugins/dungeon/__init__.py b/plugins/dungeon/__init__.py
new file mode 100644
index 0000000..6b10443
--- /dev/null
+++ b/plugins/dungeon/__init__.py
@@ -0,0 +1 @@
+from .dungeon import *
diff --git a/plugins/dungeon/dungeon.py b/plugins/dungeon/dungeon.py
new file mode 100644
index 0000000..9f5d74a
--- /dev/null
+++ b/plugins/dungeon/dungeon.py
@@ -0,0 +1,107 @@
+# encoding:utf-8
+
+import plugins
+from bridge.bridge import Bridge
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.expired_dict import ExpiredDict
+from common.log import logger
+from config import conf
+from plugins import *
+
+
+# https://github.com/bupticybee/ChineseAiDungeonChatGPT
+class StoryTeller:
+    def __init__(self, bot, sessionid, story):
+        self.bot = bot
+        self.sessionid = sessionid
+        bot.sessions.clear_session(sessionid)
+        self.first_interact = True
+        self.story = story
+
+    def reset(self):
+        self.bot.sessions.clear_session(self.sessionid)
+        self.first_interact = True
+
+    def action(self, user_action):
+        if user_action[-1] != "。":
+            user_action = user_action + "。"
+        if self.first_interact:
+            prompt = (
+                """现在来充当一个文字冒险游戏，描述时候注意节奏，不要太快，仔细描述各个人物的心情和周边环境。一次只需写四到六句话。
+            开头是，"""
+                + self.story
+                + " "
+                + user_action
+            )
+            self.first_interact = False
+        else:
+            prompt = """继续，一次只需要续写四到六句话，总共就只讲5分钟内发生的事情。""" + user_action
+        return prompt
+
+
+@plugins.register(
+    name="Dungeon",
+    desire_priority=0,
+    enabled=False,
+    namecn="文字冒险",
+    desc="A plugin to play dungeon game",
+    version="1.0",
+    author="lanvent",
+)
+class Dungeon(Plugin):
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        logger.debug("[Dungeon] inited")
+        # 目前没有设计session过期事件，这里先暂时使用过期字典
+        if conf().get("expires_in_seconds"):
+            self.games = ExpiredDict(conf().get("expires_in_seconds"))
+        else:
+            self.games = dict()
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+        bottype = Bridge().get_bot_type("chat")
+        if bottype not in [const.OPEN_AI, const.OPENAI, const.CHATGPT, const.CHATGPTONAZURE, const.LINKAI]:
+            return
+        bot = Bridge().get_bot("chat")
+        content = e_context["context"].content[:]
+        clist = e_context["context"].content.split(maxsplit=1)
+        sessionid = e_context["context"]["session_id"]
+        logger.debug("[Dungeon] on_handle_context. content: %s" % clist)
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        if clist[0] == f"{trigger_prefix}停止冒险":
+            if sessionid in self.games:
+                self.games[sessionid].reset()
+                del self.games[sessionid]
+                reply = Reply(ReplyType.INFO, "冒险结束!")
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+        elif clist[0] == f"{trigger_prefix}开始冒险" or sessionid in self.games:
+            if sessionid not in self.games or clist[0] == f"{trigger_prefix}开始冒险":
+                if len(clist) > 1:
+                    story = clist[1]
+                else:
+                    story = "你在树林里冒险，指不定会从哪里蹦出来一些奇怪的东西，你握紧手上的手枪，希望这次冒险能够找到一些值钱的东西，你往树林深处走去。"
+                self.games[sessionid] = StoryTeller(bot, sessionid, story)
+                reply = Reply(ReplyType.INFO, "冒险开始，你可以输入任意内容，让故事继续下去。故事背景是：" + story)
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+            else:
+                prompt = self.games[sessionid].action(content)
+                e_context["context"].type = ContextType.TEXT
+                e_context["context"].content = prompt
+                e_context.action = EventAction.BREAK  # 事件结束，不跳过处理context的默认逻辑
+
+    def get_help_text(self, **kwargs):
+        help_text = "可以和机器人一起玩文字冒险游戏。\n"
+        if kwargs.get("verbose") != True:
+            return help_text
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        help_text = f"{trigger_prefix}开始冒险 " + "背景故事: 开始一个基于{背景故事}的文字冒险，之后你的所有消息会协助完善这个故事。\n" + f"{trigger_prefix}停止冒险: 结束游戏。\n"
+        if kwargs.get("verbose") == True:
+            help_text += f"\n命令例子: '{trigger_prefix}开始冒险 你在树林里冒险，指不定会从哪里蹦出来一些奇怪的东西，你握紧手上的手枪，希望这次冒险能够找到一些值钱的东西，你往树林深处走去。'"
+        return help_text
diff --git a/plugins/event.py b/plugins/event.py
new file mode 100644
index 0000000..719e6fc
--- /dev/null
+++ b/plugins/event.py
@@ -0,0 +1,55 @@
+# encoding:utf-8
+
+from enum import Enum
+
+
+class Event(Enum):
+    ON_RECEIVE_MESSAGE = 1  # 收到消息
+    """
+    e_context = {  "channel": 消息channel, "context" : 本次消息的context}
+    """
+
+    ON_HANDLE_CONTEXT = 2  # 处理消息前
+    """
+    e_context = {  "channel": 消息channel, "context" : 本次消息的context, "reply" : 目前的回复，初始为空  }
+    """
+
+    ON_DECORATE_REPLY = 3  # 得到回复后准备装饰
+    """
+    e_context = {  "channel": 消息channel, "context" : 本次消息的context, "reply" : 目前的回复 }
+    """
+
+    ON_SEND_REPLY = 4  # 发送回复前
+    """
+    e_context = {  "channel": 消息channel, "context" : 本次消息的context, "reply" : 目前的回复 }
+    """
+
+    # AFTER_SEND_REPLY = 5    # 发送回复后
+
+
+class EventAction(Enum):
+    CONTINUE = 1  # 事件未结束，继续交给下个插件处理，如果没有下个插件，则交付给默认的事件处理逻辑
+    BREAK = 2  # 事件结束，不再给下个插件处理，交付给默认的事件处理逻辑
+    BREAK_PASS = 3  # 事件结束，不再给下个插件处理，不交付给默认的事件处理逻辑
+
+
+class EventContext:
+    def __init__(self, event, econtext=dict()):
+        self.event = event
+        self.econtext = econtext
+        self.action = EventAction.CONTINUE
+
+    def __getitem__(self, key):
+        return self.econtext[key]
+
+    def __setitem__(self, key, value):
+        self.econtext[key] = value
+
+    def __delitem__(self, key):
+        del self.econtext[key]
+
+    def is_pass(self):
+        return self.action == EventAction.BREAK_PASS
+
+    def is_break(self):
+        return self.action == EventAction.BREAK or self.action == EventAction.BREAK_PASS
diff --git a/plugins/finish/__init__.py b/plugins/finish/__init__.py
new file mode 100644
index 0000000..8c1cfd9
--- /dev/null
+++ b/plugins/finish/__init__.py
@@ -0,0 +1 @@
+from .finish import *
diff --git a/plugins/finish/finish.py b/plugins/finish/finish.py
new file mode 100644
index 0000000..d976b53
--- /dev/null
+++ b/plugins/finish/finish.py
@@ -0,0 +1,40 @@
+# encoding:utf-8
+
+import plugins
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from plugins import *
+
+
+@plugins.register(
+    name="Finish",
+    desire_priority=-999,
+    hidden=True,
+    desc="A plugin that check unknown command",
+    version="1.0",
+    author="js00000",
+)
+class Finish(Plugin):
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        logger.debug("[Finish] inited")
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+
+        content = e_context["context"].content
+        logger.debug("[Finish] on_handle_context. content: %s" % content)
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        if content.startswith(trigger_prefix):
+            reply = Reply()
+            reply.type = ReplyType.ERROR
+            reply.content = "未知插件命令\n查看插件命令列表请输入#help 插件名\n"
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+
+    def get_help_text(self, **kwargs):
+        return ""
diff --git a/plugins/godcmd/README.md b/plugins/godcmd/README.md
new file mode 100644
index 0000000..3b7ce1d
--- /dev/null
+++ b/plugins/godcmd/README.md
@@ -0,0 +1,18 @@
+## 插件说明
+
+指令插件
+
+## 插件使用
+
+将`config.json.template`复制为`config.json`，并修改其中`password`的值为口令。
+
+如果没有设置命令，在命令行日志中会打印出本次的临时口令，请注意观察，打印格式如下。
+
+```
+[INFO][2023-04-06 23:53:47][godcmd.py:165] - [Godcmd] 因未设置口令，本次的临时口令为0971。
+```
+
+在私聊中可使用`#auth`指令，输入口令进行管理员认证。更多详细指令请输入`#help`查看帮助文档：
+
+`#auth <口令>` - 管理员认证，仅可在私聊时认证。
+`#help` - 输出帮助文档，**是否是管理员**和是否是在群聊中会影响帮助文档的输出内容。
diff --git a/plugins/godcmd/__init__.py b/plugins/godcmd/__init__.py
new file mode 100644
index 0000000..0e26552
--- /dev/null
+++ b/plugins/godcmd/__init__.py
@@ -0,0 +1 @@
+from .godcmd import *
diff --git a/plugins/godcmd/config.json.template b/plugins/godcmd/config.json.template
new file mode 100644
index 0000000..ed021e0
--- /dev/null
+++ b/plugins/godcmd/config.json.template
@@ -0,0 +1,4 @@
+{
+  "password": "",
+  "admin_users": []
+}
diff --git a/plugins/godcmd/godcmd.py b/plugins/godcmd/godcmd.py
new file mode 100644
index 0000000..efd445f
--- /dev/null
+++ b/plugins/godcmd/godcmd.py
@@ -0,0 +1,488 @@
+# encoding:utf-8
+
+import json
+import os
+import random
+import string
+import logging
+from typing import Tuple
+
+import bridge.bridge
+import plugins
+from bridge.bridge import Bridge
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from config import conf, load_config, global_config
+from plugins import *
+
+# 定义指令集
+COMMANDS = {
+    "help": {
+        "alias": ["help", "帮助"],
+        "desc": "回复此帮助",
+    },
+    "helpp": {
+        "alias": ["help", "帮助"],  # 与help指令共用别名，根据参数数量区分
+        "args": ["插件名"],
+        "desc": "回复指定插件的详细帮助",
+    },
+    "auth": {
+        "alias": ["auth", "认证"],
+        "args": ["口令"],
+        "desc": "管理员认证",
+    },
+    "model": {
+        "alias": ["model", "模型"],
+        "desc": "查看和设置全局模型",
+    },
+    "set_openai_api_key": {
+        "alias": ["set_openai_api_key"],
+        "args": ["api_key"],
+        "desc": "设置你的OpenAI私有api_key",
+    },
+    "reset_openai_api_key": {
+        "alias": ["reset_openai_api_key"],
+        "desc": "重置为默认的api_key",
+    },
+    "set_gpt_model": {
+        "alias": ["set_gpt_model"],
+        "desc": "设置你的私有模型",
+    },
+    "reset_gpt_model": {
+        "alias": ["reset_gpt_model"],
+        "desc": "重置你的私有模型",
+    },
+    "gpt_model": {
+        "alias": ["gpt_model"],
+        "desc": "查询你使用的模型",
+    },
+    "id": {
+        "alias": ["id", "用户"],
+        "desc": "获取用户id",
+    },
+    "reset": {
+        "alias": ["reset", "重置会话"],
+        "desc": "重置会话",
+    },
+}
+
+ADMIN_COMMANDS = {
+    "resume": {
+        "alias": ["resume", "恢复服务"],
+        "desc": "恢复服务",
+    },
+    "stop": {
+        "alias": ["stop", "暂停服务"],
+        "desc": "暂停服务",
+    },
+    "reconf": {
+        "alias": ["reconf", "重载配置"],
+        "desc": "重载配置(不包含插件配置)",
+    },
+    "resetall": {
+        "alias": ["resetall", "重置所有会话"],
+        "desc": "重置所有会话",
+    },
+    "scanp": {
+        "alias": ["scanp", "扫描插件"],
+        "desc": "扫描插件目录是否有新插件",
+    },
+    "plist": {
+        "alias": ["plist", "插件"],
+        "desc": "打印当前插件列表",
+    },
+    "setpri": {
+        "alias": ["setpri", "设置插件优先级"],
+        "args": ["插件名", "优先级"],
+        "desc": "设置指定插件的优先级，越大越优先",
+    },
+    "reloadp": {
+        "alias": ["reloadp", "重载插件"],
+        "args": ["插件名"],
+        "desc": "重载指定插件配置",
+    },
+    "enablep": {
+        "alias": ["enablep", "启用插件"],
+        "args": ["插件名"],
+        "desc": "启用指定插件",
+    },
+    "disablep": {
+        "alias": ["disablep", "禁用插件"],
+        "args": ["插件名"],
+        "desc": "禁用指定插件",
+    },
+    "installp": {
+        "alias": ["installp", "安装插件"],
+        "args": ["仓库地址或插件名"],
+        "desc": "安装指定插件",
+    },
+    "uninstallp": {
+        "alias": ["uninstallp", "卸载插件"],
+        "args": ["插件名"],
+        "desc": "卸载指定插件",
+    },
+    "updatep": {
+        "alias": ["updatep", "更新插件"],
+        "args": ["插件名"],
+        "desc": "更新指定插件",
+    },
+    "debug": {
+        "alias": ["debug", "调试模式", "DEBUG"],
+        "desc": "开启机器调试日志",
+    },
+}
+
+
+# 定义帮助函数
+def get_help_text(isadmin, isgroup):
+    help_text = "通用指令\n"
+    for cmd, info in COMMANDS.items():
+        if cmd in ["auth", "set_openai_api_key", "reset_openai_api_key", "set_gpt_model", "reset_gpt_model", "gpt_model"]:  # 不显示帮助指令
+            continue
+        raw_ct = conf().get("channel_type", "web")
+        active_channels = raw_ct if isinstance(raw_ct, list) else [c.strip() for c in str(raw_ct).split(",")]
+        if cmd == "id" and not any(c in ["wxy", "wechatmp"] for c in active_channels):
+            continue
+        alias = ["#" + a for a in info["alias"][:1]]
+        help_text += f"{','.join(alias)} "
+        if "args" in info:
+            args = [a for a in info["args"]]
+            help_text += f"{' '.join(args)}"
+        help_text += f": {info['desc']}\n"
+
+    # 插件指令
+    plugins = PluginManager().list_plugins()
+    help_text += "\n可用插件"
+    for plugin in plugins:
+        if plugins[plugin].enabled and not plugins[plugin].hidden:
+            namecn = plugins[plugin].namecn
+            help_text += "\n%s: " % namecn
+            help_text += PluginManager().instances[plugin].get_help_text(verbose=False).strip()
+
+    if ADMIN_COMMANDS and isadmin:
+        help_text += "\n\n管理员指令：\n"
+        for cmd, info in ADMIN_COMMANDS.items():
+            alias = ["#" + a for a in info["alias"][:1]]
+            help_text += f"{','.join(alias)} "
+            if "args" in info:
+                args = [a for a in info["args"]]
+                help_text += f"{' '.join(args)}"
+            help_text += f": {info['desc']}\n"
+    return help_text
+
+
+@plugins.register(
+    name="Godcmd",
+    desire_priority=999,
+    hidden=True,
+    desc="为你的机器人添加指令集，有用户和管理员两种角色，加载顺序请放在首位，初次运行后插件目录会生成配置文件, 填充管理员密码后即可认证",
+    version="1.0",
+    author="lanvent",
+)
+class Godcmd(Plugin):
+    def __init__(self):
+        super().__init__()
+
+        config_path = os.path.join(os.path.dirname(__file__), "config.json")
+        gconf = super().load_config()
+        if not gconf:
+            if not os.path.exists(config_path):
+                gconf = {"password": "", "admin_users": []}
+                with open(config_path, "w") as f:
+                    json.dump(gconf, f, indent=4)
+        if gconf["password"] == "":
+            self.temp_password = "".join(random.sample(string.digits, 4))
+            logger.info("[Godcmd] 因未设置口令，本次的临时口令为%s。" % self.temp_password)
+        else:
+            self.temp_password = None
+        custom_commands = conf().get("clear_memory_commands", [])
+        for custom_command in custom_commands:
+            if custom_command and custom_command.startswith("#"):
+                custom_command = custom_command[1:]
+                if custom_command and custom_command not in COMMANDS["reset"]["alias"]:
+                    COMMANDS["reset"]["alias"].append(custom_command)
+
+        self.password = gconf["password"]
+        self.admin_users = gconf["admin_users"]
+        global_config["admin_users"] = self.admin_users
+        self.isrunning = True  # 机器人是否运行中
+
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        logger.debug("[Godcmd] inited")
+
+    def on_handle_context(self, e_context: EventContext):
+        context_type = e_context["context"].type
+        if context_type != ContextType.TEXT:
+            if not self.isrunning:
+                e_context.action = EventAction.BREAK_PASS
+            return
+
+        content = e_context["context"].content
+        logger.debug("[Godcmd] on_handle_context. content: %s" % content)
+        if content.startswith("#"):
+            if len(content) == 1:
+                reply = Reply()
+                reply.type = ReplyType.ERROR
+                reply.content = f"空指令，输入#help查看指令列表\n"
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+            # msg = e_context['context']['msg']
+            channel = e_context["channel"]
+            user = e_context["context"]["receiver"]
+            session_id = e_context["context"]["session_id"]
+            isgroup = e_context["context"].get("isgroup", False)
+            bottype = Bridge().get_bot_type("chat")
+            bot = Bridge().get_bot("chat")
+            # 将命令和参数分割
+            command_parts = content[1:].strip().split()
+            cmd = command_parts[0]
+            args = command_parts[1:]
+            isadmin = False
+            if user in self.admin_users:
+                isadmin = True
+            ok = False
+            result = "string"
+            if any(cmd in info["alias"] for info in COMMANDS.values()):
+                cmd = next(c for c, info in COMMANDS.items() if cmd in info["alias"])
+                if cmd == "auth":
+                    ok, result = self.authenticate(user, args, isadmin, isgroup)
+                elif cmd == "help" or cmd == "helpp":
+                    if len(args) == 0:
+                        ok, result = True, get_help_text(isadmin, isgroup)
+                    else:
+                        # This can replace the helpp command
+                        plugins = PluginManager().list_plugins()
+                        query_name = args[0].upper()
+                        # search name and namecn
+                        for name, plugincls in plugins.items():
+                            if not plugincls.enabled:
+                                continue
+                            if query_name == name or query_name == plugincls.namecn:
+                                ok, result = True, PluginManager().instances[name].get_help_text(isgroup=isgroup, isadmin=isadmin, verbose=True)
+                                break
+                        if not ok:
+                            result = "插件不存在或未启用"
+                elif cmd == "model":
+                    if not isadmin and not self.is_admin_in_group(e_context["context"]):
+                        ok, result = False, "需要管理员权限执行"
+                    elif len(args) == 0:
+                        model = conf().get("model") or const.GPT35
+                        ok, result = True, "当前模型为: " + str(model)
+                    elif len(args) == 1:
+                        if args[0] not in const.MODEL_LIST:
+                            ok, result = False, "模型名称不存在"
+                        else:
+                            conf()["model"] = self.model_mapping(args[0])
+                            Bridge().reset_bot()
+                            model = conf().get("model") or const.GPT35
+                            ok, result = True, "模型设置为: " + str(model)
+                elif cmd == "id":
+                    ok, result = True, user
+                elif cmd == "set_openai_api_key":
+                    if len(args) == 1:
+                        user_data = conf().get_user_data(user)
+                        user_data["openai_api_key"] = args[0]
+                        ok, result = True, "你的OpenAI私有api_key已设置为" + args[0]
+                    else:
+                        ok, result = False, "请提供一个api_key"
+                elif cmd == "reset_openai_api_key":
+                    try:
+                        user_data = conf().get_user_data(user)
+                        user_data.pop("openai_api_key")
+                        ok, result = True, "你的OpenAI私有api_key已清除"
+                    except Exception as e:
+                        ok, result = False, "你没有设置私有api_key"
+                elif cmd == "set_gpt_model":
+                    if len(args) == 1:
+                        user_data = conf().get_user_data(user)
+                        user_data["gpt_model"] = args[0]
+                        ok, result = True, "你的GPT模型已设置为" + args[0]
+                    else:
+                        ok, result = False, "请提供一个GPT模型"
+                elif cmd == "gpt_model":
+                    user_data = conf().get_user_data(user)
+                    model = conf().get("model")
+                    if "gpt_model" in user_data:
+                        model = user_data["gpt_model"]
+                    ok, result = True, "你的GPT模型为" + str(model)
+                elif cmd == "reset_gpt_model":
+                    try:
+                        user_data = conf().get_user_data(user)
+                        user_data.pop("gpt_model")
+                        ok, result = True, "你的GPT模型已重置"
+                    except Exception as e:
+                        ok, result = False, "你没有设置私有GPT模型"
+                elif cmd == "reset":
+                    if bottype in [const.OPEN_AI, const.OPENAI, const.CHATGPT, const.CHATGPTONAZURE, const.LINKAI, const.BAIDU, const.QIANFAN, const.XUNFEI, const.QWEN, const.QWEN_DASHSCOPE, const.GEMINI, const.ZHIPU_AI, const.CLAUDEAPI]:
+                        bot.sessions.clear_session(session_id)
+                        if Bridge().chat_bots.get(bottype):
+                            Bridge().chat_bots.get(bottype).sessions.clear_session(session_id)
+                        channel.cancel_session(session_id)
+                        ok, result = True, "会话已重置"
+                    else:
+                        ok, result = False, "当前对话机器人不支持重置会话"
+                logger.debug("[Godcmd] command: %s by %s" % (cmd, user))
+            elif any(cmd in info["alias"] for info in ADMIN_COMMANDS.values()):
+                if isadmin:
+                    if isgroup:
+                        ok, result = False, "群聊不可执行管理员指令"
+                    else:
+                        cmd = next(c for c, info in ADMIN_COMMANDS.items() if cmd in info["alias"])
+                        if cmd == "stop":
+                            self.isrunning = False
+                            ok, result = True, "服务已暂停"
+                        elif cmd == "resume":
+                            self.isrunning = True
+                            ok, result = True, "服务已恢复"
+                        elif cmd == "reconf":
+                            load_config()
+                            ok, result = True, "配置已重载"
+                        elif cmd == "resetall":
+                            if bottype in [const.OPEN_AI, const.OPENAI, const.CHATGPT, const.CHATGPTONAZURE, const.LINKAI,
+                                           const.BAIDU, const.QIANFAN, const.XUNFEI, const.QWEN, const.QWEN_DASHSCOPE, const.GEMINI, const.ZHIPU_AI, const.MOONSHOT,
+                                           const.MODELSCOPE]:
+                                channel.cancel_all_session()
+                                bot.sessions.clear_all_session()
+                                ok, result = True, "重置所有会话成功"
+                            else:
+                                ok, result = False, "当前对话机器人不支持重置会话"
+                        elif cmd == "debug":
+                            if logger.getEffectiveLevel() == logging.DEBUG:  # 判断当前日志模式是否DEBUG
+                                logger.setLevel(logging.INFO)
+                                ok, result = True, "DEBUG模式已关闭"
+                            else:
+                                logger.setLevel(logging.DEBUG)
+                                ok, result = True, "DEBUG模式已开启"
+                        elif cmd == "plist":
+                            plugins = PluginManager().list_plugins()
+                            ok = True
+                            result = "插件列表：\n"
+                            for name, plugincls in plugins.items():
+                                result += f"{plugincls.name}_v{plugincls.version} {plugincls.priority} - "
+                                if plugincls.enabled:
+                                    result += "已启用\n"
+                                else:
+                                    result += "未启用\n"
+                        elif cmd == "scanp":
+                            new_plugins = PluginManager().scan_plugins()
+                            ok, result = True, "插件扫描完成"
+                            PluginManager().activate_plugins()
+                            if len(new_plugins) > 0:
+                                result += "\n发现新插件：\n"
+                                result += "\n".join([f"{p.name}_v{p.version}" for p in new_plugins])
+                            else:
+                                result += ", 未发现新插件"
+                        elif cmd == "setpri":
+                            if len(args) != 2:
+                                ok, result = False, "请提供插件名和优先级"
+                            else:
+                                ok = PluginManager().set_plugin_priority(args[0], int(args[1]))
+                                if ok:
+                                    result = "插件" + args[0] + "优先级已设置为" + args[1]
+                                else:
+                                    result = "插件不存在"
+                        elif cmd == "reloadp":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名"
+                            else:
+                                ok = PluginManager().reload_plugin(args[0])
+                                if ok:
+                                    result = "插件配置已重载"
+                                else:
+                                    result = "插件不存在"
+                        elif cmd == "enablep":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名"
+                            else:
+                                ok, result = PluginManager().enable_plugin(args[0])
+                        elif cmd == "disablep":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名"
+                            else:
+                                ok = PluginManager().disable_plugin(args[0])
+                                if ok:
+                                    result = "插件已禁用"
+                                else:
+                                    result = "插件不存在"
+                        elif cmd == "installp":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名或.git结尾的仓库地址"
+                            else:
+                                ok, result = PluginManager().install_plugin(args[0])
+                        elif cmd == "uninstallp":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名"
+                            else:
+                                ok, result = PluginManager().uninstall_plugin(args[0])
+                        elif cmd == "updatep":
+                            if len(args) != 1:
+                                ok, result = False, "请提供插件名"
+                            else:
+                                ok, result = PluginManager().update_plugin(args[0])
+                        logger.debug("[Godcmd] admin command: %s by %s" % (cmd, user))
+                else:
+                    ok, result = False, "需要管理员权限才能执行该指令"
+            else:
+                trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+                if trigger_prefix == "#":  # 跟插件聊天指令前缀相同，继续递交
+                    return
+                ok, result = False, f"未知指令：{cmd}\n查看指令列表请输入#help \n"
+
+            reply = Reply()
+            if ok:
+                reply.type = ReplyType.INFO
+            else:
+                reply.type = ReplyType.ERROR
+            reply.content = result
+            e_context["reply"] = reply
+
+            e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+        elif not self.isrunning:
+            e_context.action = EventAction.BREAK_PASS
+
+    def authenticate(self, userid, args, isadmin, isgroup) -> Tuple[bool, str]:
+        if isgroup:
+            return False, "请勿在群聊中认证"
+
+        if isadmin:
+            return False, "管理员账号无需认证"
+
+        if len(args) != 1:
+            return False, "请提供口令"
+
+        password = args[0]
+        if password == self.password:
+            self.admin_users.append(userid)
+            global_config["admin_users"].append(userid)
+            return True, "认证成功"
+        elif password == self.temp_password:
+            self.admin_users.append(userid)
+            global_config["admin_users"].append(userid)
+            return True, "认证成功，请尽快设置口令"
+        else:
+            return False, "认证失败"
+
+    def get_help_text(self, isadmin=False, isgroup=False, **kwargs):
+        return get_help_text(isadmin, isgroup)
+
+
+    def is_admin_in_group(self, context):
+        if context["isgroup"]:
+            return context.kwargs.get("msg").actual_user_id in global_config["admin_users"]
+        return False
+
+
+    def model_mapping(self, model) -> str:
+        if model == "gpt-4-turbo":
+            return const.GPT4_TURBO_PREVIEW
+        return model
+
+    def reload(self):
+        gconf = pconf(self.name)
+        if gconf:
+            if gconf.get("password"):
+                self.password = gconf["password"]
+            if gconf.get("admin_users"):
+                self.admin_users = gconf["admin_users"]
diff --git a/plugins/hello/README.md b/plugins/hello/README.md
new file mode 100644
index 0000000..fb560c4
--- /dev/null
+++ b/plugins/hello/README.md
@@ -0,0 +1,41 @@
+## 插件说明
+
+可以根据需求设置入群欢迎、群聊拍一拍、退群等消息的自定义提示词，也支持为每个群设置对应的固定欢迎语。
+
+该插件也是用户根据需求开发自定义插件的示例插件，参考[插件开发说明](https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins)
+
+## 插件配置
+
+将 `plugins/hello` 目录下的 `config.json.template` 配置模板复制为最终生效的 `config.json`。 (如果未配置则会默认使用`config.json.template`模板中配置)。
+
+以下是插件配置项说明：
+
+```bash
+{
+    "group_welc_fixed_msg": {                   ## 这里可以为特定群里配置特定的固定欢迎语
+      "群聊1": "群聊1的固定欢迎语",
+      "群聊2": "群聊2的固定欢迎语"
+    },
+
+  "group_welc_prompt": "请你随机使用一种风格说一句问候语来欢迎新用户\"{nickname}\"加入群聊。",  ## 群聊随机欢迎语的提示词
+
+  "group_exit_prompt": "请你随机使用一种风格跟其他群用户说他违反规则\"{nickname}\"退出群聊。",  ## 移出群聊的提示词
+
+  "patpat_prompt": "请你随机使用一种风格介绍你自己，并告诉用户输入#help可以查看帮助信息。",  ## 群内拍一拍的提示词
+ 
+  "use_character_desc": false     ## 是否在Hello插件中使用LinkAI应用的系统设定
+}
+```
+
+
+注意：
+
+ - 设置全局的用户进群固定欢迎语，可以在***项目根目录下***的`config.json`文件里，可以添加参数`"group_welcome_msg": "" `，参考 [#1482](https://github.com/zhayujie/chatgpt-on-wechat/pull/1482)
+ - 为每个群设置固定的欢迎语，可以在`"group_welc_fixed_msg": {}`配置群聊名和对应的固定欢迎语，优先级高于全局固定欢迎语
+ - 如果没有配置以上两个参数，则使用随机欢迎语，如需设定风格，语言等，修改`"group_welc_prompt": `即可
+ - 如果使用LinkAI的服务，想在随机欢迎中结合LinkAI应用的设定，配置`"use_character_desc": true `
+ - 实际 `config.json` 配置中应保证json格式，不应携带 '#' 及后面的注释
+ - 如果是`docker`部署，可通过映射 `plugins/config.json` 到容器中来完成插件配置，参考[文档](https://github.com/zhayujie/chatgpt-on-wechat#3-%E6%8F%92%E4%BB%B6%E4%BD%BF%E7%94%A8)
+
+
+
diff --git a/plugins/hello/__init__.py b/plugins/hello/__init__.py
new file mode 100644
index 0000000..d9b15a1
--- /dev/null
+++ b/plugins/hello/__init__.py
@@ -0,0 +1 @@
+from .hello import *
diff --git a/plugins/hello/config.json.template b/plugins/hello/config.json.template
new file mode 100644
index 0000000..13c3788
--- /dev/null
+++ b/plugins/hello/config.json.template
@@ -0,0 +1,14 @@
+{
+    "group_welc_fixed_msg": {
+      "群聊1": "群聊1的固定欢迎语",
+      "群聊2": "群聊2的固定欢迎语"
+    },
+
+  "group_welc_prompt": "请你随机使用一种风格说一句问候语来欢迎新用户\"{nickname}\"加入群聊。",
+
+  "group_exit_prompt": "请你随机使用一种风格跟其他群用户说他违反规则\"{nickname}\"退出群聊。",
+
+  "patpat_prompt": "请你随机使用一种风格介绍你自己，并告诉用户输入#help可以查看帮助信息。",
+
+  "use_character_desc": false
+}
\ No newline at end of file
diff --git a/plugins/hello/hello.py b/plugins/hello/hello.py
new file mode 100644
index 0000000..a71aa78
--- /dev/null
+++ b/plugins/hello/hello.py
@@ -0,0 +1,128 @@
+# encoding:utf-8
+
+import plugins
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from channel.chat_message import ChatMessage
+from common.log import logger
+from plugins import *
+from config import conf
+
+
+@plugins.register(
+    name="Hello",
+    desire_priority=-1,
+    hidden=True,
+    enabled=False,
+    desc="A simple plugin that says hello",
+    version="0.1",
+    author="lanvent",
+)
+
+
+class Hello(Plugin):
+
+    group_welc_prompt = "请你随机使用一种风格说一句问候语来欢迎新用户\"{nickname}\"加入群聊。"
+    group_exit_prompt = "请你随机使用一种风格介绍你自己，并告诉用户输入#help可以查看帮助信息。"
+    patpat_prompt = "请你随机使用一种风格跟其他群用户说他违反规则\"{nickname}\"退出群聊。"
+
+    def __init__(self):
+        super().__init__()
+        try:
+            self.config = super().load_config()
+            if not self.config:
+                self.config = self._load_config_template()
+            self.group_welc_fixed_msg = self.config.get("group_welc_fixed_msg", {})
+            self.group_welc_prompt = self.config.get("group_welc_prompt", self.group_welc_prompt)
+            self.group_exit_prompt = self.config.get("group_exit_prompt", self.group_exit_prompt)
+            self.patpat_prompt = self.config.get("patpat_prompt", self.patpat_prompt)
+            logger.debug("[Hello] inited")
+            self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        except Exception as e:
+            logger.error(f"[Hello]初始化异常：{e}")
+            raise "[Hello] init failed, ignore "
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type not in [
+            ContextType.TEXT,
+            ContextType.JOIN_GROUP,
+            ContextType.PATPAT,
+            ContextType.EXIT_GROUP
+        ]:
+            return
+        msg: ChatMessage = e_context["context"]["msg"]
+        group_name = msg.from_user_nickname
+        if e_context["context"].type == ContextType.JOIN_GROUP:
+            if "group_welcome_msg" in conf() or group_name in self.group_welc_fixed_msg:
+                reply = Reply()
+                reply.type = ReplyType.TEXT
+                if group_name in self.group_welc_fixed_msg:
+                    reply.content = self.group_welc_fixed_msg.get(group_name, "")
+                else:
+                    reply.content = conf().get("group_welcome_msg", "")
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+                return
+            e_context["context"].type = ContextType.TEXT
+            e_context["context"].content = self.group_welc_prompt.format(nickname=msg.actual_user_nickname)
+            e_context.action = EventAction.BREAK  # 事件结束，进入默认处理逻辑
+            if not self.config or not self.config.get("use_character_desc"):
+                e_context["context"]["generate_breaked_by"] = EventAction.BREAK
+            return
+        
+        if e_context["context"].type == ContextType.EXIT_GROUP:
+            if conf().get("group_chat_exit_group"):
+                e_context["context"].type = ContextType.TEXT
+                e_context["context"].content = self.group_exit_prompt.format(nickname=msg.actual_user_nickname)
+                e_context.action = EventAction.BREAK  # 事件结束，进入默认处理逻辑
+                return
+            e_context.action = EventAction.BREAK
+            return
+            
+        if e_context["context"].type == ContextType.PATPAT:
+            e_context["context"].type = ContextType.TEXT
+            e_context["context"].content = self.patpat_prompt
+            e_context.action = EventAction.BREAK  # 事件结束，进入默认处理逻辑
+            if not self.config or not self.config.get("use_character_desc"):
+                e_context["context"]["generate_breaked_by"] = EventAction.BREAK
+            return
+
+        content = e_context["context"].content
+        logger.debug("[Hello] on_handle_context. content: %s" % content)
+        if content == "Hello":
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            if e_context["context"]["isgroup"]:
+                reply.content = f"Hello, {msg.actual_user_nickname} from {msg.from_user_nickname}"
+            else:
+                reply.content = f"Hello, {msg.from_user_nickname}"
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+
+        if content == "Hi":
+            reply = Reply()
+            reply.type = ReplyType.TEXT
+            reply.content = "Hi"
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK  # 事件结束，进入默认处理逻辑，一般会覆写reply
+
+        if content == "End":
+            # 如果是文本消息"End"，将请求转换成"IMAGE_CREATE"，并将content设置为"The World"
+            e_context["context"].type = ContextType.IMAGE_CREATE
+            content = "The World"
+            e_context.action = EventAction.CONTINUE  # 事件继续，交付给下个插件或默认逻辑
+
+    def get_help_text(self, **kwargs):
+        help_text = "输入Hello，我会回复你的名字\n输入End，我会回复你世界的图片\n"
+        return help_text
+
+    def _load_config_template(self):
+        logger.debug("No Hello plugin config.json, use plugins/hello/config.json.template")
+        try:
+            plugin_config_path = os.path.join(self.path, "config.json.template")
+            if os.path.exists(plugin_config_path):
+                with open(plugin_config_path, "r", encoding="utf-8") as f:
+                    plugin_conf = json.load(f)
+                    return plugin_conf
+        except Exception as e:
+            logger.exception(e)
\ No newline at end of file
diff --git a/plugins/keyword/README.md b/plugins/keyword/README.md
new file mode 100644
index 0000000..4678f68
--- /dev/null
+++ b/plugins/keyword/README.md
@@ -0,0 +1,13 @@
+# 目的
+关键字匹配并回复
+
+# 试用场景
+目前是在微信公众号下面使用过。
+
+# 使用步骤
+1. 复制 `config.json.template` 为 `config.json`
+2. 在关键字 `keyword` 新增需要关键字匹配的内容
+3. 重启程序做验证
+
+# 验证结果
+![结果](test-keyword.png)
\ No newline at end of file
diff --git a/plugins/keyword/__init__.py b/plugins/keyword/__init__.py
new file mode 100644
index 0000000..b860b69
--- /dev/null
+++ b/plugins/keyword/__init__.py
@@ -0,0 +1 @@
+from .keyword import *
diff --git a/plugins/keyword/config.json.template b/plugins/keyword/config.json.template
new file mode 100644
index 0000000..dbd5efe
--- /dev/null
+++ b/plugins/keyword/config.json.template
@@ -0,0 +1,5 @@
+{
+  "keyword": {
+    "关键字匹配": "测试成功"
+  }
+}
diff --git a/plugins/keyword/keyword.py b/plugins/keyword/keyword.py
new file mode 100644
index 0000000..45ebd3a
--- /dev/null
+++ b/plugins/keyword/keyword.py
@@ -0,0 +1,95 @@
+# encoding:utf-8
+
+import json
+import os
+import requests
+import plugins
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from plugins import *
+
+
+@plugins.register(
+    name="Keyword",
+    desire_priority=900,
+    hidden=True,
+    desc="关键词匹配过滤",
+    version="0.1",
+    author="fengyege.top",
+)
+class Keyword(Plugin):
+    def __init__(self):
+        super().__init__()
+        try:
+            curdir = os.path.dirname(__file__)
+            config_path = os.path.join(curdir, "config.json")
+            conf = None
+            if not os.path.exists(config_path):
+                logger.debug(f"[keyword] config file not found: {config_path}")
+                conf = {"keyword": {}}
+                with open(config_path, "w", encoding="utf-8") as f:
+                    json.dump(conf, f, indent=4)
+            else:
+                logger.debug(f"[keyword] loading config file: {config_path}")
+                with open(config_path, "r", encoding="utf-8") as f:
+                    conf = json.load(f)
+            # 加载关键词
+            self.keyword = conf["keyword"]
+
+            logger.debug("[keyword] {}".format(self.keyword))
+            self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+            logger.debug("[keyword] inited.")
+        except Exception as e:
+            logger.warn("[keyword] init failed, ignore or see https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/keyword .")
+            raise e
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+
+        content = e_context["context"].content.strip()
+        logger.debug("[keyword] on_handle_context. content: %s" % content)
+        if content in self.keyword:
+            logger.info(f"[keyword] 匹配到关键字【{content}】")
+            reply_text = self.keyword[content]
+
+            # 判断匹配内容的类型
+            if (reply_text.startswith("http://") or reply_text.startswith("https://")) and any(reply_text.endswith(ext) for ext in [".jpg", ".webp", ".jpeg", ".png", ".gif", ".img"]):
+            # 如果是以 http:// 或 https:// 开头，且".jpg", ".jpeg", ".png", ".gif", ".img"结尾，则认为是图片 URL。
+                reply = Reply()
+                reply.type = ReplyType.IMAGE_URL
+                reply.content = reply_text
+                
+            elif (reply_text.startswith("http://") or reply_text.startswith("https://")) and any(reply_text.endswith(ext) for ext in [".pdf", ".doc", ".docx", ".xls", "xlsx",".zip", ".rar"]):
+            # 如果是以 http:// 或 https:// 开头，且".pdf", ".doc", ".docx", ".xls", "xlsx",".zip", ".rar"结尾，则下载文件到tmp目录并发送给用户
+                file_path = "tmp"
+                if not os.path.exists(file_path):
+                    os.makedirs(file_path)
+                file_name = reply_text.split("/")[-1]  # 获取文件名
+                file_path = os.path.join(file_path, file_name)
+                response = requests.get(reply_text)
+                with open(file_path, "wb") as f:
+                    f.write(response.content)
+                reply = Reply()
+                reply.type = ReplyType.FILE
+                reply.content = file_path
+            
+            elif (reply_text.startswith("http://") or reply_text.startswith("https://")) and any(reply_text.endswith(ext) for ext in [".mp4"]):
+            # 如果是以 http:// 或 https:// 开头，且".mp4"结尾，则下载视频到tmp目录并发送给用户
+                reply = Reply()
+                reply.type = ReplyType.VIDEO_URL
+                reply.content = reply_text
+                
+            else:
+            # 否则认为是普通文本
+                reply = Reply()
+                reply.type = ReplyType.TEXT
+                reply.content = reply_text
+            
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS  # 事件结束，并跳过处理context的默认逻辑
+            
+    def get_help_text(self, **kwargs):
+        help_text = "关键词过滤"
+        return help_text
diff --git a/plugins/keyword/test-keyword.png b/plugins/keyword/test-keyword.png
new file mode 100644
index 0000000..0f17ae8
Binary files /dev/null and b/plugins/keyword/test-keyword.png differ
diff --git a/plugins/linkai/README.md b/plugins/linkai/README.md
new file mode 100644
index 0000000..9347410
--- /dev/null
+++ b/plugins/linkai/README.md
@@ -0,0 +1,111 @@
+## 插件说明
+
+基于 LinkAI 提供的知识库、Midjourney绘画、文档对话等能力对机器人的功能进行增强。平台地址: https://link-ai.tech/console
+
+## 插件配置
+
+将 `plugins/linkai` 目录下的 `config.json.template` 配置模板复制为最终生效的 `config.json`。 (如果未配置则会默认使用`config.json.template`模板中配置，但功能默认关闭，需要可通过指令进行开启)。
+
+以下是插件配置项说明：
+
+```bash
+{
+    "group_app_map": {               # 群聊 和 应用编码 的映射关系
+        "测试群名称1": "default",      # 表示在名称为 "测试群名称1" 的群聊中将使用app_code 为 default 的应用
+        "测试群名称2": "Kv2fXJcH"
+    },
+    "midjourney": {
+        "enabled": true,          # midjourney 绘画开关
+        "auto_translate": true,   # 是否自动将提示词翻译为英文
+        "img_proxy": true,        # 是否对生成的图片使用代理，如果你是国外服务器，将这一项设置为false会获得更快的生成速度
+        "max_tasks": 3,           # 支持同时提交的总任务个数
+        "max_tasks_per_user": 1,  # 支持单个用户同时提交的任务个数
+        "use_image_create_prefix": true   # 是否使用全局的绘画触发词，如果开启将同时支持由`config.json`中的 image_create_prefix 配置触发
+    },
+    "summary": {
+        "enabled": true,              # 文档总结和对话功能开关
+        "group_enabled": true,        # 是否支持群聊开启
+        "max_file_size": 5000,        # 文件的大小限制，单位KB，默认为5M，超过该大小直接忽略
+        "type": ["FILE", "SHARING", "IMAGE"]  # 支持总结的类型，分别表示 文件、分享链接、图片，其中文件和链接默认打开，图片默认关闭
+    }
+}
+```
+
+根目录 `config.json` 中配置，`API_KEY` 在 [控制台](https://link-ai.tech/console/interface) 中创建并复制过来:
+
+```bash
+"linkai_api_key": "Link_xxxxxxxxx"
+```
+
+注意：
+
+ - 配置项中 `group_app_map` 部分是用于映射群聊与LinkAI平台上的应用， `midjourney` 部分是 mj 画图的配置，`summary` 部分是文档总结及对话功能的配置。三部分的配置相互独立，可按需开启
+ - 实际 `config.json` 配置中应保证json格式，不应携带 '#' 及后面的注释
+ - 如果是`docker`部署，可通过映射 `plugins/config.json` 到容器中来完成插件配置，参考[文档](https://github.com/zhayujie/chatgpt-on-wechat#3-%E6%8F%92%E4%BB%B6%E4%BD%BF%E7%94%A8)
+
+## 插件使用
+
+> 使用插件中的知识库管理功能需要首先开启`linkai`对话，依赖全局 `config.json` 中的 `use_linkai` 和 `linkai_api_key` 配置；而midjourney绘画 和 summary文档总结对话功能则只需填写 `linkai_api_key` 配置，`use_linkai` 无论是否关闭均可使用。具体可参考 [详细文档](https://link-ai.tech/platform/link-app/wechat)。
+
+完成配置后运行项目，会自动运行插件，输入 `#help linkai` 可查看插件功能。
+
+### 1.知识库管理功能
+
+提供在不同群聊使用不同应用的功能。可以在上述 `group_app_map` 配置中固定映射关系，也可以通过指令在群中快速完成切换。
+
+应用切换指令需要首先完成管理员 (`godcmd`) 插件的认证，然后按以下格式输入：
+
+`$linkai app {app_code}`
+
+例如输入 `$linkai app Kv2fXJcH`，即将当前群聊与 app_code为 Kv2fXJcH 的应用绑定。
+
+另外，还可以通过 `$linkai close` 来一键关闭linkai对话，此时就会使用默认的openai接口；同理，发送 `$linkai open` 可以再次开启。
+
+### 2.Midjourney绘画功能
+
+若未配置 `plugins/linkai/config.json`，默认会关闭画图功能，直接使用 `$mj open` 可基于默认配置直接使用mj画图。
+
+指令格式：
+
+```
+ - 图片生成: $mj 描述词1, 描述词2..
+ - 图片放大: $mju 图片ID 图片序号
+ - 图片变换: $mjv 图片ID 图片序号
+ - 重置: $mjr 图片ID
+```
+
+例如：
+
+```
+"$mj a little cat, white --ar 9:16"
+"$mju 1105592717188272288 2"
+"$mjv 11055927171882 2"
+"$mjr 11055927171882"
+```
+
+注意事项：
+1. 使用 `$mj open` 和 `$mj close` 指令可以快速打开和关闭绘图功能
+2. 海外环境部署请将 `img_proxy` 设置为 `false`
+3. 开启 `use_image_create_prefix` 配置后可直接复用全局画图触发词，以"画"开头便可以生成图片。
+4. 提示词内容中包含敏感词或者参数格式错误可能导致绘画失败，生成失败不消耗积分
+5. 若未收到图片可能有两种可能，一种是收到了图片但微信发送失败，可以在后台日志查看有没有获取到图片url，一般原因是受到了wx限制，可以稍后重试或更换账号尝试；另一种情况是图片提示词存在疑似违规，mj不会直接提示错误但会在画图后删掉原图导致程序无法获取，这种情况不消耗积分。
+
+### 3.文档总结对话功能
+
+#### 配置
+
+该功能依赖 LinkAI的知识库及对话功能，需要在项目根目录的config.json中设置 `linkai_api_key`， 同时根据上述插件配置说明，在插件config.json添加 `summary` 部分的配置，设置 `enabled` 为 true。
+
+如果不想创建 `plugins/linkai/config.json` 配置，可以直接通过 `$linkai sum open` 指令开启该功能。
+
+也可以通过私聊(全局 `config.json` 中的 `linkai_app_code`)或者群聊绑定(通过`group_app_map`参数配置)的应用来开启该功能：在LinkAI平台 [应用配置](https://link-ai.tech/console/factory) 里添加并开启**内容总结**插件。
+
+#### 使用
+
+功能开启后，向机器人发送 **文件**、 **分享链接卡片**、**图片** 即可生成摘要，进一步可以与文件或链接的内容进行多轮对话。如果需要关闭某种类型的内容总结，设置 `summary`配置中的type字段即可。
+
+#### 限制
+
+ 1. 文件目前 支持 `txt`, `docx`, `pdf`, `md`, `csv`格式，文件大小由 `max_file_size` 限制，最大不超过15M，文件字数最多可支持百万字的文件。但不建议上传字数过多的文件，一是token消耗过大，二是摘要很难覆盖到全部内容，只能通过多轮对话来了解细节。
+ 2. 分享链接 目前仅支持 公众号文章，后续会支持更多文章类型及视频链接等
+ 3. 总结及对话的 费用与 LinkAI 3.5-4K 模型的计费方式相同，按文档内容的tokens进行计算
diff --git a/plugins/linkai/__init__.py b/plugins/linkai/__init__.py
new file mode 100644
index 0000000..e7414be
--- /dev/null
+++ b/plugins/linkai/__init__.py
@@ -0,0 +1 @@
+from .linkai import *
diff --git a/plugins/linkai/config.json.template b/plugins/linkai/config.json.template
new file mode 100644
index 0000000..547b8ef
--- /dev/null
+++ b/plugins/linkai/config.json.template
@@ -0,0 +1,20 @@
+{
+    "group_app_map": {
+        "测试群名1": "default",
+        "测试群名2": "Kv2fXJcH"
+    },
+    "midjourney": {
+        "enabled": true,
+        "auto_translate": true,
+        "img_proxy": true,
+        "max_tasks": 3,
+        "max_tasks_per_user": 1,
+        "use_image_create_prefix": true
+    },
+    "summary": {
+        "enabled": true,
+        "group_enabled": true,
+        "max_file_size": 5000,
+        "type": ["FILE", "SHARING"]
+    }
+}
diff --git a/plugins/linkai/linkai.py b/plugins/linkai/linkai.py
new file mode 100644
index 0000000..17183a6
--- /dev/null
+++ b/plugins/linkai/linkai.py
@@ -0,0 +1,336 @@
+import plugins
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from plugins import *
+from .midjourney import MJBot
+from .summary import LinkSummary
+from bridge import bridge
+from common.expired_dict import ExpiredDict
+from common import const
+import os
+from .utils import Util
+from config import plugin_config, conf
+
+
+@plugins.register(
+    name="linkai",
+    desc="A plugin that supports knowledge base and midjourney drawing.",
+    version="0.1.0",
+    author="https://link-ai.tech",
+    desire_priority=99
+)
+class LinkAI(Plugin):
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        self.config = super().load_config()
+        if not self.config:
+            # 未加载到配置，使用模板中的配置
+            self.config = self._load_config_template()
+        if self.config:
+            self.mj_bot = MJBot(self.config.get("midjourney"), self._fetch_group_app_code)
+        self.sum_config = {}
+        if self.config:
+            self.sum_config = self.config.get("summary")
+        logger.debug(f"[LinkAI] inited, config={self.config}")
+
+    def on_handle_context(self, e_context: EventContext):
+        """
+        消息处理逻辑
+        :param e_context: 消息上下文
+        """
+        if not self.config:
+            return
+
+        context = e_context['context']
+        if context.type not in [ContextType.TEXT, ContextType.IMAGE, ContextType.IMAGE_CREATE, ContextType.FILE,
+                                ContextType.SHARING]:
+            # filter content no need solve
+            return
+
+        if context.type in [ContextType.FILE, ContextType.IMAGE] and self._is_summary_open(context):
+            # 文件处理
+            context.get("msg").prepare()
+            file_path = context.content
+            if not LinkSummary().check_file(file_path, self.sum_config):
+                return
+            if context.type != ContextType.IMAGE:
+                _send_info(e_context, "正在为你加速生成摘要，请稍后")
+            app_code = self._fetch_app_code(context)
+            res = LinkSummary().summary_file(file_path, app_code)
+            if not res:
+                if context.type != ContextType.IMAGE:
+                    _set_reply_text("因为神秘力量无法获取内容，请稍后再试吧", e_context, level=ReplyType.TEXT)
+                return
+            summary_text = res.get("summary")
+            if context.type != ContextType.IMAGE:
+                USER_FILE_MAP[_find_user_id(context) + "-sum_id"] = res.get("summary_id")
+                summary_text += "\n\n💬 发送 \"开启对话\" 可以开启与文件内容的对话"
+            _set_reply_text(summary_text, e_context, level=ReplyType.TEXT)
+            os.remove(file_path)
+            return
+
+        if (context.type == ContextType.SHARING and self._is_summary_open(context)) or \
+                (context.type == ContextType.TEXT and self._is_summary_open(context) and LinkSummary().check_url(context.content)):
+            if not LinkSummary().check_url(context.content):
+                return
+            _send_info(e_context, "正在为你加速生成摘要，请稍后")
+            app_code = self._fetch_app_code(context)
+            res = LinkSummary().summary_url(context.content, app_code)
+            if not res:
+                _set_reply_text("因为神秘力量无法获取文章内容，请稍后再试吧~", e_context, level=ReplyType.TEXT)
+                return
+            _set_reply_text(res.get("summary") + "\n\n💬 发送 \"开启对话\" 可以开启与文章内容的对话", e_context,
+                            level=ReplyType.TEXT)
+            USER_FILE_MAP[_find_user_id(context) + "-sum_id"] = res.get("summary_id")
+            return
+
+        mj_type = self.mj_bot.judge_mj_task_type(e_context)
+        if mj_type:
+            # MJ作图任务处理
+            self.mj_bot.process_mj_task(mj_type, e_context)
+            return
+
+        if context.content.startswith(f"{_get_trigger_prefix()}linkai"):
+            # 应用管理功能
+            self._process_admin_cmd(e_context)
+            return
+
+        if context.type == ContextType.TEXT and context.content == "开启对话" and _find_sum_id(context):
+            # 文本对话
+            _send_info(e_context, "正在为你开启对话，请稍后")
+            res = LinkSummary().summary_chat(_find_sum_id(context))
+            if not res:
+                _set_reply_text("开启对话失败，请稍后再试吧", e_context)
+                return
+            USER_FILE_MAP[_find_user_id(context) + "-file_id"] = res.get("file_id")
+            _set_reply_text("💡你可以问我关于这篇文章的任何问题，例如：\n\n" + res.get(
+                "questions") + "\n\n发送 \"退出对话\" 可以关闭与文章的对话", e_context, level=ReplyType.TEXT)
+            return
+
+        if context.type == ContextType.TEXT and context.content == "退出对话" and _find_file_id(context):
+            del USER_FILE_MAP[_find_user_id(context) + "-file_id"]
+            bot = bridge.Bridge().find_chat_bot(const.LINKAI)
+            bot.sessions.clear_session(context["session_id"])
+            _set_reply_text("对话已退出", e_context, level=ReplyType.TEXT)
+            return
+
+        if context.type == ContextType.TEXT and _find_file_id(context):
+            bot = bridge.Bridge().find_chat_bot(const.LINKAI)
+            context.kwargs["file_id"] = _find_file_id(context)
+            reply = bot.reply(context.content, context)
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+
+        if self._is_chat_task(e_context):
+            # 文本对话任务处理
+            self._process_chat_task(e_context)
+
+    # 插件管理功能
+    def _process_admin_cmd(self, e_context: EventContext):
+        context = e_context['context']
+        cmd = context.content.split()
+        if len(cmd) == 1 or (len(cmd) == 2 and cmd[1] == "help"):
+            _set_reply_text(self.get_help_text(verbose=True), e_context, level=ReplyType.INFO)
+            return
+
+        if len(cmd) == 2 and (cmd[1] == "open" or cmd[1] == "close"):
+            # 知识库开关指令
+            if not Util.is_admin(e_context):
+                _set_reply_text("需要管理员权限执行", e_context, level=ReplyType.ERROR)
+                return
+            is_open = True
+            tips_text = "开启"
+            if cmd[1] == "close":
+                tips_text = "关闭"
+                is_open = False
+            conf()["use_linkai"] = is_open
+            bridge.Bridge().reset_bot()
+            _set_reply_text(f"LinkAI对话功能{tips_text}", e_context, level=ReplyType.INFO)
+            return
+
+        if len(cmd) == 3 and cmd[1] == "app":
+            # 知识库应用切换指令
+            if not context.kwargs.get("isgroup"):
+                _set_reply_text("该指令需在群聊中使用", e_context, level=ReplyType.ERROR)
+                return
+            if not Util.is_admin(e_context):
+                _set_reply_text("需要管理员权限执行", e_context, level=ReplyType.ERROR)
+                return
+            app_code = cmd[2]
+            group_name = context.kwargs.get("msg").from_user_nickname
+            group_mapping = self.config.get("group_app_map")
+            if group_mapping:
+                group_mapping[group_name] = app_code
+            else:
+                self.config["group_app_map"] = {group_name: app_code}
+            # 保存插件配置
+            super().save_config(self.config)
+            _set_reply_text(f"应用设置成功: {app_code}", e_context, level=ReplyType.INFO)
+            return
+
+        if len(cmd) == 3 and cmd[1] == "sum" and (cmd[2] == "open" or cmd[2] == "close"):
+            # 总结对话开关指令
+            if not Util.is_admin(e_context):
+                _set_reply_text("需要管理员权限执行", e_context, level=ReplyType.ERROR)
+                return
+            is_open = True
+            tips_text = "开启"
+            if cmd[2] == "close":
+                tips_text = "关闭"
+                is_open = False
+            if not self.sum_config:
+                _set_reply_text(
+                    f"插件未启用summary功能，请参考以下链添加插件配置\n\nhttps://github.com/zhayujie/chatgpt-on-wechat/blob/master/plugins/linkai/README.md",
+                    e_context, level=ReplyType.INFO)
+            else:
+                self.sum_config["enabled"] = is_open
+                _set_reply_text(f"文章总结功能{tips_text}", e_context, level=ReplyType.INFO)
+            return
+
+        _set_reply_text(f"指令错误，请输入{_get_trigger_prefix()}linkai help 获取帮助", e_context,
+                        level=ReplyType.INFO)
+        return
+
+    def _is_summary_open(self, context) -> bool:
+        # 获取远程应用插件状态
+        remote_enabled = False
+        if context.kwargs.get("isgroup"):
+            # 群聊场景只查询群对应的app_code
+            group_name = context.get("msg").from_user_nickname
+            app_code = self._fetch_group_app_code(group_name)
+            if app_code:
+                if context.type.name in ["FILE", "SHARING"]:
+                    remote_enabled = Util.fetch_app_plugin(app_code, "内容总结")
+        else:
+            # 非群聊场景使用全局app_code
+            app_code = conf().get("linkai_app_code")
+            if app_code:
+                if context.type.name in ["FILE", "SHARING"]:
+                    remote_enabled = Util.fetch_app_plugin(app_code, "内容总结")
+
+        # 基础条件：总开关开启且消息类型符合要求
+        base_enabled = (
+                self.sum_config
+                and self.sum_config.get("enabled")
+                and (context.type.name in (
+                    self.sum_config.get("type") or ["FILE", "SHARING"]) or context.type.name == "TEXT")
+        )
+
+        # 群聊：需要满足(总开关和群开关)或远程插件开启
+        if context.kwargs.get("isgroup"):
+            return (base_enabled and self.sum_config.get("group_enabled")) or remote_enabled
+
+        # 非群聊：只需要满足总开关或远程插件开启
+        return base_enabled or remote_enabled
+
+    # LinkAI 对话任务处理
+    def _is_chat_task(self, e_context: EventContext):
+        context = e_context['context']
+        # 群聊应用管理
+        return self.config.get("group_app_map") and context.kwargs.get("isgroup")
+
+    def _process_chat_task(self, e_context: EventContext):
+        """
+        处理LinkAI对话任务
+        :param e_context: 对话上下文
+        """
+        context = e_context['context']
+        # 群聊应用管理
+        group_name = context.get("msg").from_user_nickname
+        app_code = self._fetch_group_app_code(group_name)
+        if app_code:
+            context.kwargs['app_code'] = app_code
+
+    def _fetch_group_app_code(self, group_name: str) -> str:
+        """
+        根据群聊名称获取对应的应用code
+        :param group_name: 群聊名称
+        :return: 应用code
+        """
+        group_mapping = self.config.get("group_app_map")
+        if group_mapping:
+            app_code = group_mapping.get(group_name) or group_mapping.get("ALL_GROUP")
+            return app_code
+
+    def _fetch_app_code(self, context) -> str:
+        """
+        根据主配置或者群聊名称获取对应的应用code,优先获取群聊配置的应用code
+        :param context: 上下文
+        :return: 应用code
+        """
+        app_code = conf().get("linkai_app_code")
+        if context.kwargs.get("isgroup"):
+            # 群聊场景只查询群对应的app_code
+            group_name = context.get("msg").from_user_nickname
+            app_code = self._fetch_group_app_code(group_name)
+        return app_code
+
+    def get_help_text(self, verbose=False, **kwargs):
+        trigger_prefix = _get_trigger_prefix()
+        help_text = "用于集成 LinkAI 提供的知识库、Midjourney绘画、文档总结、联网搜索等能力。\n\n"
+        if not verbose:
+            return help_text
+        help_text += f'📖 知识库\n - 群聊中指定应用: {trigger_prefix}linkai app 应用编码\n'
+        help_text += f' - {trigger_prefix}linkai open: 开启对话\n'
+        help_text += f' - {trigger_prefix}linkai close: 关闭对话\n'
+        help_text += f'\n例如: \n"{trigger_prefix}linkai app Kv2fXJcH"\n\n'
+        help_text += f"🎨 绘画\n - 生成: {trigger_prefix}mj 描述词1, 描述词2.. \n - 放大: {trigger_prefix}mju 图片ID 图片序号\n - 变换: {trigger_prefix}mjv 图片ID 图片序号\n - 重置: {trigger_prefix}mjr 图片ID"
+        help_text += f"\n\n例如：\n\"{trigger_prefix}mj a little cat, white --ar 9:16\"\n\"{trigger_prefix}mju 11055927171882 2\""
+        help_text += f"\n\"{trigger_prefix}mjv 11055927171882 2\"\n\"{trigger_prefix}mjr 11055927171882\""
+        help_text += f"\n\n💡 文档总结和对话\n - 开启: {trigger_prefix}linkai sum open\n - 使用: 发送文件、公众号文章等可生成摘要，并与内容对话"
+        return help_text
+
+    def _load_config_template(self):
+        logger.debug("No LinkAI plugin config.json, use plugins/linkai/config.json.template")
+        try:
+            plugin_config_path = os.path.join(self.path, "config.json.template")
+            if os.path.exists(plugin_config_path):
+                with open(plugin_config_path, "r", encoding="utf-8") as f:
+                    plugin_conf = json.load(f)
+                    plugin_conf["midjourney"]["enabled"] = False
+                    plugin_conf["summary"]["enabled"] = False
+                    write_plugin_config({"linkai": plugin_conf})
+                    return plugin_conf
+        except Exception as e:
+            logger.exception(e)
+
+    def reload(self):
+        self.config = super().load_config()
+
+
+def _send_info(e_context: EventContext, content: str):
+    reply = Reply(ReplyType.TEXT, content)
+    channel = e_context["channel"]
+    channel.send(reply, e_context["context"])
+
+
+def _find_user_id(context):
+    if context["isgroup"]:
+        return context.kwargs.get("msg").actual_user_id
+    else:
+        return context["receiver"]
+
+
+def _set_reply_text(content: str, e_context: EventContext, level: ReplyType = ReplyType.ERROR):
+    reply = Reply(level, content)
+    e_context["reply"] = reply
+    e_context.action = EventAction.BREAK_PASS
+
+
+def _get_trigger_prefix():
+    return conf().get("plugin_trigger_prefix", "$")
+
+
+def _find_sum_id(context):
+    return USER_FILE_MAP.get(_find_user_id(context) + "-sum_id")
+
+
+def _find_file_id(context):
+    user_id = _find_user_id(context)
+    if user_id:
+        return USER_FILE_MAP.get(user_id + "-file_id")
+
+
+USER_FILE_MAP = ExpiredDict(conf().get("expires_in_seconds") or 60 * 30)
diff --git a/plugins/linkai/midjourney.py b/plugins/linkai/midjourney.py
new file mode 100644
index 0000000..7e0a287
--- /dev/null
+++ b/plugins/linkai/midjourney.py
@@ -0,0 +1,453 @@
+from enum import Enum
+from config import conf
+from common.log import logger
+import requests
+import threading
+import time
+from bridge.reply import Reply, ReplyType
+import asyncio
+from bridge.context import ContextType
+from plugins import EventContext, EventAction
+from .utils import Util
+
+
+INVALID_REQUEST = 410
+NOT_FOUND_ORIGIN_IMAGE = 461
+NOT_FOUND_TASK = 462
+
+
+class TaskType(Enum):
+    GENERATE = "generate"
+    UPSCALE = "upscale"
+    VARIATION = "variation"
+    RESET = "reset"
+
+    def __str__(self):
+        return self.name
+
+
+class Status(Enum):
+    PENDING = "pending"
+    FINISHED = "finished"
+    EXPIRED = "expired"
+    ABORTED = "aborted"
+
+    def __str__(self):
+        return self.name
+
+
+class TaskMode(Enum):
+    FAST = "fast"
+    RELAX = "relax"
+
+
+task_name_mapping = {
+    TaskType.GENERATE.name: "生成",
+    TaskType.UPSCALE.name: "放大",
+    TaskType.VARIATION.name: "变换",
+    TaskType.RESET.name: "重新生成",
+}
+
+
+class MJTask:
+    def __init__(self, id, user_id: str, task_type: TaskType, raw_prompt=None, expires: int = 60 * 6,
+                 status=Status.PENDING):
+        self.id = id
+        self.user_id = user_id
+        self.task_type = task_type
+        self.raw_prompt = raw_prompt
+        self.send_func = None  # send_func(img_url)
+        self.expiry_time = time.time() + expires
+        self.status = status
+        self.img_url = None  # url
+        self.img_id = None
+
+    def __str__(self):
+        return f"id={self.id}, user_id={self.user_id}, task_type={self.task_type}, status={self.status}, img_id={self.img_id}"
+
+
+# midjourney bot
+class MJBot:
+    def __init__(self, config, fetch_group_app_code):
+        self.base_url = conf().get("linkai_api_base", "https://api.link-ai.tech") + "/v1/img/midjourney"
+        self.headers = {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+        self.config = config
+        self.fetch_group_app_code = fetch_group_app_code
+        self.tasks = {}
+        self.temp_dict = {}
+        self.tasks_lock = threading.Lock()
+        self.event_loop = asyncio.new_event_loop()
+
+    def judge_mj_task_type(self, e_context: EventContext):
+        """
+        判断MJ任务的类型
+        :param e_context: 上下文
+        :return: 任务类型枚举
+        """
+        if not self.config:
+            return None
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        context = e_context['context']
+        if context.type == ContextType.TEXT:
+            cmd_list = context.content.split(maxsplit=1)
+            if not cmd_list:
+                return None
+            if cmd_list[0].lower() == f"{trigger_prefix}mj":
+                return TaskType.GENERATE
+            elif cmd_list[0].lower() == f"{trigger_prefix}mju":
+                return TaskType.UPSCALE
+            elif cmd_list[0].lower() == f"{trigger_prefix}mjv":
+                return TaskType.VARIATION
+            elif cmd_list[0].lower() == f"{trigger_prefix}mjr":
+                return TaskType.RESET
+        elif context.type == ContextType.IMAGE_CREATE and self.config.get("use_image_create_prefix") and self._is_mj_open(context):
+            return TaskType.GENERATE
+
+    def process_mj_task(self, mj_type: TaskType, e_context: EventContext):
+        """
+        处理mj任务
+        :param mj_type: mj任务类型
+        :param e_context: 对话上下文
+        """
+        context = e_context['context']
+        session_id = context["session_id"]
+        cmd = context.content.split(maxsplit=1)
+        if len(cmd) == 1 and context.type == ContextType.TEXT:
+            # midjourney 帮助指令
+            self._set_reply_text(self.get_help_text(verbose=True), e_context, level=ReplyType.INFO)
+            return
+
+        if len(cmd) == 2 and (cmd[1] == "open" or cmd[1] == "close"):
+            if not Util.is_admin(e_context):
+                Util.set_reply_text("需要管理员权限执行", e_context, level=ReplyType.ERROR)
+                return
+            # midjourney 开关指令
+            is_open = True
+            tips_text = "开启"
+            if cmd[1] == "close":
+                tips_text = "关闭"
+                is_open = False
+            self.config["enabled"] = is_open
+            self._set_reply_text(f"Midjourney绘画已{tips_text}", e_context, level=ReplyType.INFO)
+            return
+
+        if not self._is_mj_open(context):
+            logger.warn("Midjourney绘画未开启，请查看 plugins/linkai/config.json 中的配置，或者在LinkAI平台 应用中添加/打开”MJ“插件")
+            self._set_reply_text(f"Midjourney绘画未开启", e_context, level=ReplyType.INFO)
+            return
+
+        if not self._check_rate_limit(session_id, e_context):
+            logger.warn("[MJ] midjourney task exceed rate limit")
+            return
+
+        if mj_type == TaskType.GENERATE:
+            if context.type == ContextType.IMAGE_CREATE:
+                raw_prompt = context.content
+            else:
+                # 图片生成
+                raw_prompt = cmd[1]
+            reply = self.generate(raw_prompt, session_id, e_context)
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+
+        elif mj_type == TaskType.UPSCALE or mj_type == TaskType.VARIATION:
+            # 图片放大/变换
+            clist = cmd[1].split()
+            if len(clist) < 2:
+                self._set_reply_text(f"{cmd[0]} 命令缺少参数", e_context)
+                return
+            img_id = clist[0]
+            index = int(clist[1])
+            if index < 1 or index > 4:
+                self._set_reply_text(f"图片序号 {index} 错误，应在 1 至 4 之间", e_context)
+                return
+            key = f"{str(mj_type)}_{img_id}_{index}"
+            if self.temp_dict.get(key):
+                self._set_reply_text(f"第 {index} 张图片已经{task_name_mapping.get(str(mj_type))}过了", e_context)
+                return
+            # 执行图片放大/变换操作
+            reply = self.do_operate(mj_type, session_id, img_id, e_context, index)
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+
+        elif mj_type == TaskType.RESET:
+            # 图片重新生成
+            clist = cmd[1].split()
+            if len(clist) < 1:
+                self._set_reply_text(f"{cmd[0]} 命令缺少参数", e_context)
+                return
+            img_id = clist[0]
+            # 图片重新生成
+            reply = self.do_operate(mj_type, session_id, img_id, e_context)
+            e_context['reply'] = reply
+            e_context.action = EventAction.BREAK_PASS
+        else:
+            self._set_reply_text(f"暂不支持该命令", e_context)
+
+    def generate(self, prompt: str, user_id: str, e_context: EventContext) -> Reply:
+        """
+        图片生成
+        :param prompt: 提示词
+        :param user_id: 用户id
+        :param e_context: 对话上下文
+        :return: 任务ID
+        """
+        logger.info(f"[MJ] image generate, prompt={prompt}")
+        mode = self._fetch_mode(prompt)
+        body = {"prompt": prompt, "mode": mode, "auto_translate": self.config.get("auto_translate")}
+        if not self.config.get("img_proxy"):
+            body["img_proxy"] = False
+        res = requests.post(url=self.base_url + "/generate", json=body, headers=self.headers, timeout=(5, 40))
+        if res.status_code == 200:
+            res = res.json()
+            logger.debug(f"[MJ] image generate, res={res}")
+            if res.get("code") == 200:
+                task_id = res.get("data").get("task_id")
+                real_prompt = res.get("data").get("real_prompt")
+                if mode == TaskMode.RELAX.value:
+                    time_str = "1~10分钟"
+                else:
+                    time_str = "1分钟"
+                content = f"🚀您的作品将在{time_str}左右完成，请耐心等待\n- - - - - - - - -\n"
+                if real_prompt:
+                    content += f"初始prompt: {prompt}\n转换后prompt: {real_prompt}"
+                else:
+                    content += f"prompt: {prompt}"
+                reply = Reply(ReplyType.INFO, content)
+                task = MJTask(id=task_id, status=Status.PENDING, raw_prompt=prompt, user_id=user_id,
+                              task_type=TaskType.GENERATE)
+                # put to memory dict
+                self.tasks[task.id] = task
+                # asyncio.run_coroutine_threadsafe(self.check_task(task, e_context), self.event_loop)
+                self._do_check_task(task, e_context)
+                return reply
+        else:
+            res_json = res.json()
+            logger.error(f"[MJ] generate error, msg={res_json.get('message')}, status_code={res.status_code}")
+            if res.status_code == INVALID_REQUEST:
+                reply = Reply(ReplyType.ERROR, "图片生成失败，请检查提示词参数或内容")
+            else:
+                reply = Reply(ReplyType.ERROR, "图片生成失败，请稍后再试")
+            return reply
+
+    def do_operate(self, task_type: TaskType, user_id: str, img_id: str, e_context: EventContext,
+                   index: int = None) -> Reply:
+        logger.info(f"[MJ] image operate, task_type={task_type}, img_id={img_id}, index={index}")
+        body = {"type": task_type.name, "img_id": img_id}
+        if index:
+            body["index"] = index
+        if not self.config.get("img_proxy"):
+            body["img_proxy"] = False
+        res = requests.post(url=self.base_url + "/operate", json=body, headers=self.headers, timeout=(5, 40))
+        logger.debug(res)
+        if res.status_code == 200:
+            res = res.json()
+            if res.get("code") == 200:
+                task_id = res.get("data").get("task_id")
+                logger.info(f"[MJ] image operate processing, task_id={task_id}")
+                icon_map = {TaskType.UPSCALE: "🔎", TaskType.VARIATION: "🪄", TaskType.RESET: "🔄"}
+                content = f"{icon_map.get(task_type)}图片正在{task_name_mapping.get(task_type.name)}中，请耐心等待"
+                reply = Reply(ReplyType.INFO, content)
+                task = MJTask(id=task_id, status=Status.PENDING, user_id=user_id, task_type=task_type)
+                # put to memory dict
+                self.tasks[task.id] = task
+                key = f"{task_type.name}_{img_id}_{index}"
+                self.temp_dict[key] = True
+                # asyncio.run_coroutine_threadsafe(self.check_task(task, e_context), self.event_loop)
+                self._do_check_task(task, e_context)
+                return reply
+        else:
+            error_msg = ""
+            if res.status_code == NOT_FOUND_ORIGIN_IMAGE:
+                error_msg = "请输入正确的图片ID"
+            res_json = res.json()
+            logger.error(f"[MJ] operate error, msg={res_json.get('message')}, status_code={res.status_code}")
+            reply = Reply(ReplyType.ERROR, error_msg or "图片生成失败，请稍后再试")
+            return reply
+
+    def check_task_sync(self, task: MJTask, e_context: EventContext):
+        logger.debug(f"[MJ] start check task status, {task}")
+        max_retry_times = 90
+        while max_retry_times > 0:
+            time.sleep(10)
+            url = f"{self.base_url}/tasks/{task.id}"
+            try:
+                res = requests.get(url, headers=self.headers, timeout=8)
+                if res.status_code == 200:
+                    res_json = res.json()
+                    logger.debug(f"[MJ] task check res sync, task_id={task.id}, status={res.status_code}, "
+                                 f"data={res_json.get('data')}, thread={threading.current_thread().name}")
+                    if res_json.get("data") and res_json.get("data").get("status") == Status.FINISHED.name:
+                        # process success res
+                        if self.tasks.get(task.id):
+                            self.tasks[task.id].status = Status.FINISHED
+                        self._process_success_task(task, res_json.get("data"), e_context)
+                        return
+                    max_retry_times -= 1
+                else:
+                    res_json = res.json()
+                    logger.warn(f"[MJ] image check error, status_code={res.status_code}, res={res_json}")
+                    max_retry_times -= 20
+            except Exception as e:
+                max_retry_times -= 20
+                logger.warn(e)
+        logger.warn("[MJ] end from poll")
+        if self.tasks.get(task.id):
+            self.tasks[task.id].status = Status.EXPIRED
+
+    def _do_check_task(self, task: MJTask, e_context: EventContext):
+        threading.Thread(target=self.check_task_sync, args=(task, e_context)).start()
+
+    def _process_success_task(self, task: MJTask, res: dict, e_context: EventContext):
+        """
+        处理任务成功的结果
+        :param task: MJ任务
+        :param res: 请求结果
+        :param e_context: 对话上下文
+        """
+        # channel send img
+        task.status = Status.FINISHED
+        task.img_id = res.get("img_id")
+        task.img_url = res.get("img_url")
+        logger.info(f"[MJ] task success, task_id={task.id}, img_id={task.img_id}, img_url={task.img_url}")
+
+        # send img
+        reply = Reply(ReplyType.IMAGE_URL, task.img_url)
+        channel = e_context["channel"]
+        _send(channel, reply, e_context["context"])
+
+        # send info
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        text = ""
+        if task.task_type == TaskType.GENERATE or task.task_type == TaskType.VARIATION or task.task_type == TaskType.RESET:
+            text = f"🎨绘画完成!\n"
+            if task.raw_prompt:
+                text += f"prompt: {task.raw_prompt}\n"
+            text += f"- - - - - - - - -\n图片ID: {task.img_id}"
+            text += f"\n\n🔎使用 {trigger_prefix}mju 命令放大图片\n"
+            text += f"例如：\n{trigger_prefix}mju {task.img_id} 1"
+            text += f"\n\n🪄使用 {trigger_prefix}mjv 命令变换图片\n"
+            text += f"例如：\n{trigger_prefix}mjv {task.img_id} 1"
+            text += f"\n\n🔄使用 {trigger_prefix}mjr 命令重新生成图片\n"
+            text += f"例如：\n{trigger_prefix}mjr {task.img_id}"
+            reply = Reply(ReplyType.INFO, text)
+            _send(channel, reply, e_context["context"])
+
+        self._print_tasks()
+        return
+
+    def _check_rate_limit(self, user_id: str, e_context: EventContext) -> bool:
+        """
+        midjourney任务限流控制
+        :param user_id: 用户id
+        :param e_context: 对话上下文
+        :return: 任务是否能够生成, True:可以生成, False: 被限流
+        """
+        tasks = self.find_tasks_by_user_id(user_id)
+        task_count = len([t for t in tasks if t.status == Status.PENDING])
+        if task_count >= self.config.get("max_tasks_per_user"):
+            reply = Reply(ReplyType.INFO, "您的Midjourney作图任务数已达上限，请稍后再试")
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return False
+        task_count = len([t for t in self.tasks.values() if t.status == Status.PENDING])
+        if task_count >= self.config.get("max_tasks"):
+            reply = Reply(ReplyType.INFO, "Midjourney作图任务数已达上限，请稍后再试")
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return False
+        return True
+
+    def _fetch_mode(self, prompt) -> str:
+        mode = self.config.get("mode")
+        if "--relax" in prompt or mode == TaskMode.RELAX.value:
+            return TaskMode.RELAX.value
+        return mode or TaskMode.FAST.value
+
+    def _run_loop(self, loop: asyncio.BaseEventLoop):
+        """
+        运行事件循环，用于轮询任务的线程
+        :param loop: 事件循环
+        """
+        loop.run_forever()
+        loop.stop()
+
+    def _print_tasks(self):
+        for id in self.tasks:
+            logger.debug(f"[MJ] current task: {self.tasks[id]}")
+
+    def _set_reply_text(self, content: str, e_context: EventContext, level: ReplyType = ReplyType.ERROR):
+        """
+        设置回复文本
+        :param content: 回复内容
+        :param e_context: 对话上下文
+        :param level: 回复等级
+        """
+        reply = Reply(level, content)
+        e_context["reply"] = reply
+        e_context.action = EventAction.BREAK_PASS
+
+    def get_help_text(self, verbose=False, **kwargs):
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        help_text = "🎨利用Midjourney进行画图\n\n"
+        if not verbose:
+            return help_text
+        help_text += f" - 生成: {trigger_prefix}mj 描述词1, 描述词2.. \n - 放大: {trigger_prefix}mju 图片ID 图片序号\n - 变换: mjv 图片ID 图片序号\n - 重置: mjr 图片ID"
+        help_text += f"\n\n例如：\n\"{trigger_prefix}mj a little cat, white --ar 9:16\"\n\"{trigger_prefix}mju 11055927171882 2\""
+        help_text += f"\n\"{trigger_prefix}mjv 11055927171882 2\"\n\"{trigger_prefix}mjr 11055927171882\""
+        return help_text
+
+    def find_tasks_by_user_id(self, user_id) -> list:
+        result = []
+        with self.tasks_lock:
+            now = time.time()
+            for task in self.tasks.values():
+                if task.status == Status.PENDING and now > task.expiry_time:
+                    task.status = Status.EXPIRED
+                    logger.info(f"[MJ] {task} expired")
+                if task.user_id == user_id:
+                    result.append(task)
+        return result
+
+    def _is_mj_open(self, context) -> bool:
+        # 获取远程应用插件状态
+        remote_enabled = False
+        if context.kwargs.get("isgroup"):
+            # 群聊场景只查询群对应的app_code
+            group_name = context.get("msg").from_user_nickname
+            app_code = self.fetch_group_app_code(group_name)
+            if app_code:
+                remote_enabled = Util.fetch_app_plugin(app_code, "Midjourney")
+        else:
+            # 非群聊场景使用全局app_code
+            app_code = conf().get("linkai_app_code")
+            if app_code:
+                remote_enabled = Util.fetch_app_plugin(app_code, "Midjourney")
+
+        # 本地配置
+        base_enabled = self.config.get("enabled")
+
+        return base_enabled or remote_enabled
+
+def _send(channel, reply: Reply, context, retry_cnt=0):
+    try:
+        channel.send(reply, context)
+    except Exception as e:
+        logger.error("[WX] sendMsg error: {}".format(str(e)))
+        if isinstance(e, NotImplementedError):
+            return
+        logger.exception(e)
+        if retry_cnt < 2:
+            time.sleep(3 + 3 * retry_cnt)
+            channel.send(reply, context, retry_cnt + 1)
+
+
+def check_prefix(content, prefix_list):
+    if not prefix_list:
+        return None
+    for prefix in prefix_list:
+        if content.startswith(prefix):
+            return prefix
+    return None
diff --git a/plugins/linkai/summary.py b/plugins/linkai/summary.py
new file mode 100644
index 0000000..7060f2a
--- /dev/null
+++ b/plugins/linkai/summary.py
@@ -0,0 +1,102 @@
+import requests
+from config import conf
+from common.log import logger
+import os
+import html
+
+
+class LinkSummary:
+    def __init__(self):
+        pass
+
+    def summary_file(self, file_path: str, app_code: str):
+        file_body = {
+            "file": open(file_path, "rb"),
+            "name": file_path.split("/")[-1]
+        }
+        body = {
+            "app_code": app_code
+        }
+        url = self.base_url() + "/v1/summary/file"
+        logger.info(f"[LinkSum] file summary, app_code={app_code}")
+        res = requests.post(url, headers=self.headers(), files=file_body, data=body, timeout=(5, 300))
+        return self._parse_summary_res(res)
+
+    def summary_url(self, url: str, app_code: str):
+        url = html.unescape(url)
+        body = {
+            "url": url,
+            "app_code": app_code
+        }
+        logger.info(f"[LinkSum] url summary, app_code={app_code}")
+        res = requests.post(url=self.base_url() + "/v1/summary/url", headers=self.headers(), json=body, timeout=(5, 180))
+        return self._parse_summary_res(res)
+
+    def summary_chat(self, summary_id: str):
+        body = {
+            "summary_id": summary_id
+        }
+        res = requests.post(url=self.base_url() + "/v1/summary/chat", headers=self.headers(), json=body, timeout=(5, 180))
+        if res.status_code == 200:
+            res = res.json()
+            logger.debug(f"[LinkSum] chat open, res={res}")
+            if res.get("code") == 200:
+                data = res.get("data")
+                return {
+                    "questions": data.get("questions"),
+                    "file_id": data.get("file_id")
+                }
+        else:
+            res_json = res.json()
+            logger.error(f"[LinkSum] summary error, status_code={res.status_code}, msg={res_json.get('message')}")
+            return None
+
+    def _parse_summary_res(self, res):
+        if res.status_code == 200:
+            res = res.json()
+            logger.debug(f"[LinkSum] summary result, res={res}")
+            if res.get("code") == 200:
+                data = res.get("data")
+                return {
+                    "summary": data.get("summary"),
+                    "summary_id": data.get("summary_id")
+                }
+        else:
+            res_json = res.json()
+            logger.error(f"[LinkSum] summary error, status_code={res.status_code}, msg={res_json.get('message')}")
+            return None
+
+    def base_url(self):
+        return conf().get("linkai_api_base", "https://api.link-ai.tech")
+
+    def headers(self):
+        return {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+
+    def check_file(self, file_path: str, sum_config: dict) -> bool:
+        file_size = os.path.getsize(file_path) // 1000
+
+        if (sum_config.get("max_file_size") and file_size > sum_config.get("max_file_size")) or file_size > 15000:
+            logger.warn(f"[LinkSum] file size exceeds limit, No processing, file_size={file_size}KB")
+            return False
+
+        suffix = file_path.split(".")[-1]
+        support_list = ["txt", "csv", "docx", "pdf", "md", "jpg", "jpeg", "png"]
+        if suffix not in support_list:
+            logger.warn(f"[LinkSum] unsupported file, suffix={suffix}, support_list={support_list}")
+            return False
+
+        return True
+
+    def check_url(self, url: str):
+        if not url:
+            return False
+        support_list = ["http://mp.weixin.qq.com", "https://mp.weixin.qq.com"]
+        black_support_list = ["https://mp.weixin.qq.com/mp/waerrpage"]
+        for black_url_prefix in black_support_list:
+            if url.strip().startswith(black_url_prefix):
+                logger.warn(f"[LinkSum] unsupported url, no need to process, url={url}")
+                return False
+        for support_url in support_list:
+            if url.strip().startswith(support_url):
+                return True
+        return False
diff --git a/plugins/linkai/utils.py b/plugins/linkai/utils.py
new file mode 100644
index 0000000..a51547b
--- /dev/null
+++ b/plugins/linkai/utils.py
@@ -0,0 +1,50 @@
+import requests
+from common.log import logger
+from config import global_config
+from bridge.reply import Reply, ReplyType
+from plugins.event import EventContext, EventAction
+from config import conf
+
+class Util:
+    @staticmethod
+    def is_admin(e_context: EventContext) -> bool:
+        """
+        判断消息是否由管理员用户发送
+        :param e_context: 消息上下文
+        :return: True: 是, False: 否
+        """
+        context = e_context["context"]
+        if context["isgroup"]:
+            actual_user_id = context.kwargs.get("msg").actual_user_id
+            for admin_user in global_config["admin_users"]:
+                if actual_user_id and actual_user_id in admin_user:
+                    return True
+            return False
+        else:
+            return context["receiver"] in global_config["admin_users"]
+
+    @staticmethod
+    def set_reply_text(content: str, e_context: EventContext, level: ReplyType = ReplyType.ERROR):
+        reply = Reply(level, content)
+        e_context["reply"] = reply
+        e_context.action = EventAction.BREAK_PASS
+
+    @staticmethod
+    def fetch_app_plugin(app_code: str, plugin_name: str) -> bool:
+        try:
+            headers = {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+            # do http request
+            base_url = conf().get("linkai_api_base", "https://api.link-ai.tech")
+            params = {"app_code": app_code}
+            res = requests.get(url=base_url + "/v1/app/info", params=params, headers=headers, timeout=(5, 10))
+            if res.status_code == 200:
+                plugins = res.json().get("data").get("plugins")
+                for plugin in plugins:
+                    if plugin.get("name") and plugin.get("name") == plugin_name:
+                        return True
+                return False
+            else:
+                logger.warning(f"[LinkAI] find app info exception, res={res}")
+                return False
+        except Exception as e:
+            return False
diff --git a/plugins/plugin.py b/plugins/plugin.py
new file mode 100644
index 0000000..900501a
--- /dev/null
+++ b/plugins/plugin.py
@@ -0,0 +1,50 @@
+import os
+import json
+from config import pconf, plugin_config, conf, write_plugin_config
+from common.log import logger
+
+
+class Plugin:
+    def __init__(self):
+        self.handlers = {}
+
+    def load_config(self) -> dict:
+        """
+        加载当前插件配置
+        :return: 插件配置字典
+        """
+        # 优先获取 plugins/config.json 中的全局配置
+        plugin_conf = pconf(self.name)
+        if not plugin_conf:
+            # 全局配置不存在，则获取插件目录下的配置
+            plugin_config_path = os.path.join(self.path, "config.json")
+            if os.path.exists(plugin_config_path):
+                with open(plugin_config_path, "r", encoding="utf-8") as f:
+                    plugin_conf = json.load(f)
+
+                # 写入全局配置内存
+                write_plugin_config({self.name: plugin_conf})
+        return plugin_conf
+
+    def save_config(self, config: dict):
+        try:
+            write_plugin_config({self.name: config})
+            # 写入全局配置
+            global_config_path = "./plugins/config.json"
+            if os.path.exists(global_config_path):
+                with open(global_config_path, "w", encoding='utf-8') as f:
+                    json.dump(plugin_config, f, indent=4, ensure_ascii=False)
+            # 写入插件配置
+            plugin_config_path = os.path.join(self.path, "config.json")
+            if os.path.exists(plugin_config_path):
+                with open(plugin_config_path, "w", encoding='utf-8') as f:
+                    json.dump(config, f, indent=4, ensure_ascii=False)
+
+        except Exception as e:
+            logger.warn("save plugin config failed: {}".format(e))
+
+    def get_help_text(self, **kwargs):
+        return "暂无帮助信息"
+
+    def reload(self):
+        pass
diff --git a/plugins/plugin_manager.py b/plugins/plugin_manager.py
new file mode 100644
index 0000000..0fbd9a7
--- /dev/null
+++ b/plugins/plugin_manager.py
@@ -0,0 +1,393 @@
+# encoding:utf-8
+
+import importlib
+import importlib.util
+import json
+import os
+import sys
+
+from common.log import logger
+from common.singleton import singleton
+from common.sorted_dict import SortedDict
+from config import conf, remove_plugin_config, write_plugin_config, get_data_root, get_resource_root
+
+from .event import *
+
+
+def _plugins_resource_dir():
+    """Read-only plugins source dir. In a frozen bundle it lives under the
+    resource root (sys._MEIPASS); from source it's the CWD-relative ./plugins."""
+    if getattr(sys, "frozen", False):
+        return os.path.join(get_resource_root(), "plugins")
+    return "./plugins"
+
+
+def _plugins_data_dir():
+    """Writable dir for plugin runtime config (plugins.json). In a frozen
+    bundle the resource dir is read-only, so redirect writes to the data root
+    (~/.cow); from source it stays the CWD-relative ./plugins."""
+    if getattr(sys, "frozen", False):
+        d = os.path.join(get_data_root(), "plugins")
+        os.makedirs(d, exist_ok=True)
+        return d
+    return "./plugins"
+
+
+@singleton
+class PluginManager:
+    def __init__(self):
+        self.plugins = SortedDict(lambda k, v: v.priority, reverse=True)
+        self.listening_plugins = {}
+        self.instances = {}
+        self.pconf = {}
+        self.current_plugin_path = None
+        self.loaded = {}
+
+    def register(self, name: str, desire_priority: int = 0, **kwargs):
+        def wrapper(plugincls):
+            plugincls.name = name
+            plugincls.priority = desire_priority
+            plugincls.desc = kwargs.get("desc")
+            plugincls.author = kwargs.get("author")
+            plugincls.path = self.current_plugin_path
+            plugincls.version = kwargs.get("version") if kwargs.get("version") != None else "1.0"
+            plugincls.namecn = kwargs.get("namecn") if kwargs.get("namecn") != None else name
+            plugincls.hidden = kwargs.get("hidden") if kwargs.get("hidden") != None else False
+            # enabled 默认 True；示例性插件可在装饰器中显式传 enabled=False，
+            # 首次启动写入 plugins.json 时即为关闭状态，避免拦截用户消息。
+            plugincls.enabled = kwargs.get("enabled", True)
+            if self.current_plugin_path == None:
+                raise Exception("Plugin path not set")
+            self.plugins[name.upper()] = plugincls
+            logger.debug("Plugin %s_v%s registered, path=%s" % (name, plugincls.version, plugincls.path))
+
+        return wrapper
+
+    def save_config(self):
+        cfg_path = os.path.join(_plugins_data_dir(), "plugins.json")
+        with open(cfg_path, "w", encoding="utf-8") as f:
+            json.dump(self.pconf, f, indent=4, ensure_ascii=False)
+
+    def load_config(self):
+        logger.debug("Loading plugins config...")
+
+        modified = False
+        # Prefer the writable copy (data dir); fall back to the one shipped in
+        # the resource dir (first run in a frozen bundle, before any save).
+        data_cfg = os.path.join(_plugins_data_dir(), "plugins.json")
+        res_cfg = os.path.join(_plugins_resource_dir(), "plugins.json")
+        cfg_path = data_cfg if os.path.exists(data_cfg) else res_cfg
+        if os.path.exists(cfg_path):
+            with open(cfg_path, "r", encoding="utf-8") as f:
+                pconf = json.load(f)
+                pconf["plugins"] = SortedDict(lambda k, v: v["priority"], pconf["plugins"], reverse=True)
+        else:
+            modified = True
+            pconf = {"plugins": SortedDict(lambda k, v: v["priority"], reverse=True)}
+        self.pconf = pconf
+        if modified:
+            self.save_config()
+        return pconf
+
+    @staticmethod
+    def _load_all_config():
+        """
+        背景: 目前插件配置存放于每个插件目录的config.json下，docker运行时不方便进行映射，故增加统一管理的入口，优先
+        加载 plugins/config.json，原插件目录下的config.json 不受影响
+
+        从 plugins/config.json 中加载所有插件的配置并写入 config.py 的全局配置中，供插件中使用
+        插件实例中通过 config.pconf(plugin_name) 即可获取该插件的配置
+        """
+        all_config_path = os.path.join(_plugins_resource_dir(), "config.json")
+        try:
+            if os.path.exists(all_config_path):
+                # read from all plugins config
+                with open(all_config_path, "r", encoding="utf-8") as f:
+                    all_conf = json.load(f)
+                    logger.info(f"load all config from plugins/config.json: {all_conf}")
+
+                # write to global config
+                write_plugin_config(all_conf)
+        except Exception as e:
+            logger.error(e)
+
+    def scan_plugins(self):
+        logger.debug("Scanning plugins ...")
+        plugins_dir = _plugins_resource_dir()
+        raws = [self.plugins[name] for name in self.plugins]
+        for plugin_name in os.listdir(plugins_dir):
+            plugin_path = os.path.join(plugins_dir, plugin_name)
+            if os.path.isdir(plugin_path):
+                # 判断插件是否包含同名__init__.py文件
+                main_module_path = os.path.join(plugin_path, "__init__.py")
+                if os.path.isfile(main_module_path):
+                    # 导入插件
+                    import_path = "plugins.{}".format(plugin_name)
+                    try:
+                        self.current_plugin_path = plugin_path
+                        if plugin_path in self.loaded:
+                            if plugin_name.upper() != 'GODCMD':
+                                logger.info("reload module %s" % plugin_name)
+                                self.loaded[plugin_path] = importlib.reload(sys.modules[import_path])
+                                dependent_module_names = [name for name in sys.modules.keys() if name.startswith(import_path + ".")]
+                                for name in dependent_module_names:
+                                    logger.info("reload module %s" % name)
+                                    importlib.reload(sys.modules[name])
+                        else:
+                            self.loaded[plugin_path] = importlib.import_module(import_path)
+                        self.current_plugin_path = None
+                    except Exception as e:
+                        logger.warn("Failed to import plugin %s: %s" % (plugin_name, e))
+                        continue
+        pconf = self.pconf
+        news = [self.plugins[name] for name in self.plugins]
+        new_plugins = list(set(news) - set(raws))
+        modified = False
+        for name, plugincls in self.plugins.items():
+            rawname = plugincls.name
+            if rawname not in pconf["plugins"]:
+                modified = True
+                logger.info("Plugin %s not found in pconfig, adding to pconfig..." % name)
+                pconf["plugins"][rawname] = {
+                    "enabled": plugincls.enabled,
+                    "priority": plugincls.priority,
+                }
+            else:
+                self.plugins[name].enabled = pconf["plugins"][rawname]["enabled"]
+                self.plugins[name].priority = pconf["plugins"][rawname]["priority"]
+                self.plugins._update_heap(name)  # 更新下plugins中的顺序
+        if modified:
+            self.save_config()
+        return new_plugins
+
+    def refresh_order(self):
+        for event in self.listening_plugins.keys():
+            self.listening_plugins[event].sort(key=lambda name: self.plugins[name].priority, reverse=True)
+
+    def activate_plugins(self):  # 生成新开启的插件实例
+        failed_plugins = []
+        for name, plugincls in self.plugins.items():
+            if plugincls.enabled:
+                if 'GODCMD' in self.instances and name == 'GODCMD':
+                    continue
+                # if name not in self.instances:
+                try:
+                    instance = plugincls()
+                except Exception as e:
+                    logger.warn("Failed to init %s, diabled. %s" % (name, e))
+                    self.disable_plugin(name)
+                    failed_plugins.append(name)
+                    continue
+                if name in self.instances:
+                    self.instances[name].handlers.clear()
+                self.instances[name] = instance
+                for event in instance.handlers:
+                    if event not in self.listening_plugins:
+                        self.listening_plugins[event] = []
+                    self.listening_plugins[event].append(name)
+        self.refresh_order()
+        return failed_plugins
+
+    def reload_plugin(self, name: str):
+        name = name.upper()
+        remove_plugin_config(name)
+        if name in self.instances:
+            for event in self.listening_plugins:
+                if name in self.listening_plugins[event]:
+                    self.listening_plugins[event].remove(name)
+            if name in self.instances:
+                self.instances[name].handlers.clear()
+            del self.instances[name]
+            self.activate_plugins()
+            return True
+        return False
+
+    # IM-channel-only plugins that make no sense in the single-user desktop app
+    # and, worse, write config.json into their bundle dir on init — which breaks
+    # the macOS code-signature seal of the packaged .app. cow_cli stays enabled
+    # so desktop chat commands (/status, /help, ...) keep working.
+    DESKTOP_DISABLED_PLUGINS = {
+        "GODCMD", "KEYWORD", "BANWORDS", "ROLE", "DUNGEON", "HELLO", "FINISH",
+    }
+
+    def _apply_desktop_plugin_denylist(self):
+        """In desktop mode, force-disable IM-only plugins regardless of what
+        plugins.json (bundle default or user copy) says. Runs after scan (which
+        syncs enabled from plugins.json) and before activate, so denied plugins
+        are never instantiated and never write into the read-only bundle."""
+        if os.environ.get("COW_DESKTOP") != "1":
+            return
+        for name in list(self.plugins.keys()):
+            if name.upper() in self.DESKTOP_DISABLED_PLUGINS and self.plugins[name].enabled:
+                self.plugins[name].enabled = False
+                logger.info("[desktop] plugin %s disabled (not needed in desktop client)" % name)
+
+    def load_plugins(self):
+        self.load_config()
+        self.scan_plugins()
+        # 加载全量插件配置
+        self._load_all_config()
+        pconf = self.pconf
+        logger.debug("plugins.json config={}".format(pconf))
+        for name, plugin in pconf["plugins"].items():
+            if name.upper() not in self.plugins:
+                logger.error("Plugin %s not found, but found in plugins.json" % name)
+        self._apply_desktop_plugin_denylist()
+        self.activate_plugins()
+
+    def emit_event(self, e_context: EventContext, *args, **kwargs):
+        if e_context.event in self.listening_plugins:
+            for name in self.listening_plugins[e_context.event]:
+                if self.plugins[name].enabled and e_context.action == EventAction.CONTINUE:
+                    logger.debug("Plugin %s triggered by event %s" % (name, e_context.event))
+                    instance = self.instances[name]
+                    instance.handlers[e_context.event](e_context, *args, **kwargs)
+                    if e_context.is_break():
+                        e_context["breaked_by"] = name
+                        logger.debug("Plugin %s breaked event %s" % (name, e_context.event))
+        return e_context
+
+    def set_plugin_priority(self, name: str, priority: int):
+        name = name.upper()
+        if name not in self.plugins:
+            return False
+        if self.plugins[name].priority == priority:
+            return True
+        self.plugins[name].priority = priority
+        self.plugins._update_heap(name)
+        rawname = self.plugins[name].name
+        self.pconf["plugins"][rawname]["priority"] = priority
+        self.pconf["plugins"]._update_heap(rawname)
+        self.save_config()
+        self.refresh_order()
+        return True
+
+    def enable_plugin(self, name: str):
+        name = name.upper()
+        if name not in self.plugins:
+            return False, "插件不存在"
+        if not self.plugins[name].enabled:
+            self.plugins[name].enabled = True
+            rawname = self.plugins[name].name
+            self.pconf["plugins"][rawname]["enabled"] = True
+            self.save_config()
+            failed_plugins = self.activate_plugins()
+            if name in failed_plugins:
+                return False, "插件开启失败"
+            return True, "插件已开启"
+        return True, "插件已开启"
+
+    def disable_plugin(self, name: str):
+        name = name.upper()
+        if name not in self.plugins:
+            return False
+        if self.plugins[name].enabled:
+            self.plugins[name].enabled = False
+            rawname = self.plugins[name].name
+            self.pconf["plugins"][rawname]["enabled"] = False
+            self.save_config()
+            return True
+        return True
+
+    def list_plugins(self):
+        return self.plugins
+
+    def install_plugin(self, repo: str):
+        try:
+            import common.package_manager as pkgmgr
+
+            pkgmgr.check_dulwich()
+        except Exception as e:
+            logger.error("Failed to install plugin, {}".format(e))
+            return False, "无法导入dulwich，安装插件失败"
+        import re
+
+        from dulwich import porcelain
+
+        logger.info("clone git repo: {}".format(repo))
+
+        match = re.match(r"^(https?:\/\/|git@)([^\/:]+)[\/:]([^\/:]+)\/(.+).git$", repo)
+
+        if not match:
+            try:
+                with open("./plugins/source.json", "r", encoding="utf-8") as f:
+                    source = json.load(f)
+                if repo in source["repo"]:
+                    repo = source["repo"][repo]["url"]
+                    match = re.match(r"^(https?:\/\/|git@)([^\/:]+)[\/:]([^\/:]+)\/(.+).git$", repo)
+                    if not match:
+                        return False, "安装插件失败，source中的仓库地址不合法"
+                else:
+                    return False, "安装插件失败，仓库地址不合法"
+            except Exception as e:
+                logger.error("Failed to install plugin, {}".format(e))
+                return False, "安装插件失败，请检查仓库地址是否正确"
+        dirname = os.path.join("./plugins", match.group(4))
+        try:
+            repo = porcelain.clone(repo, dirname, checkout=True)
+            if os.path.exists(os.path.join(dirname, "requirements.txt")):
+                logger.info("detect requirements.txt，installing...")
+            pkgmgr.install_requirements(os.path.join(dirname, "requirements.txt"))
+            return True, "安装插件成功，请使用 #scanp 命令扫描插件或重启程序，开启前请检查插件是否需要配置"
+        except Exception as e:
+            logger.error("Failed to install plugin, {}".format(e))
+            return False, "安装插件失败，" + str(e)
+
+    def update_plugin(self, name: str):
+        try:
+            import common.package_manager as pkgmgr
+
+            pkgmgr.check_dulwich()
+        except Exception as e:
+            logger.error("Failed to install plugin, {}".format(e))
+            return False, "无法导入dulwich，更新插件失败"
+        from dulwich import porcelain
+
+        name = name.upper()
+        if name not in self.plugins:
+            return False, "插件不存在"
+        if name in [
+            "HELLO",
+            "GODCMD",
+            "ROLE",
+            "TOOL",
+            "BDUNIT",
+            "BANWORDS",
+            "FINISH",
+            "DUNGEON",
+        ]:
+            return False, "预置插件无法更新，请更新主程序仓库"
+        dirname = self.plugins[name].path
+        try:
+            porcelain.pull(dirname, "origin")
+            if os.path.exists(os.path.join(dirname, "requirements.txt")):
+                logger.info("detect requirements.txt，installing...")
+            pkgmgr.install_requirements(os.path.join(dirname, "requirements.txt"))
+            return True, "更新插件成功，请重新运行程序"
+        except Exception as e:
+            logger.error("Failed to update plugin, {}".format(e))
+            return False, "更新插件失败，" + str(e)
+
+    def uninstall_plugin(self, name: str):
+        name = name.upper()
+        if name not in self.plugins:
+            return False, "插件不存在"
+        if name in self.instances:
+            self.disable_plugin(name)
+        dirname = self.plugins[name].path
+        try:
+            import shutil
+
+            shutil.rmtree(dirname)
+            rawname = self.plugins[name].name
+            for event in self.listening_plugins:
+                if name in self.listening_plugins[event]:
+                    self.listening_plugins[event].remove(name)
+            del self.plugins[name]
+            del self.pconf["plugins"][rawname]
+            self.loaded[dirname] = None
+            self.save_config()
+            return True, "卸载插件成功"
+        except Exception as e:
+            logger.error("Failed to uninstall plugin, {}".format(e))
+            return False, "卸载插件失败，请手动删除文件夹完成卸载，" + str(e)
diff --git a/plugins/role/README.md b/plugins/role/README.md
new file mode 100644
index 0000000..25f7640
--- /dev/null
+++ b/plugins/role/README.md
@@ -0,0 +1,61 @@
+用于让Bot扮演指定角色的聊天插件，触发方法如下：
+
+- `$角色/$role help/帮助` - 打印目前支持的角色列表。
+- `$角色/$role <角色名>` - 让AI扮演该角色，角色名支持模糊匹配。
+- `$停止扮演` - 停止角色扮演。
+
+## 目录结构
+
+```
+plugins/role/
+├── README.md
+├── __init__.py
+├── role.py                  # 插件主逻辑
+├── roles.json               # 内置角色库（所有默认角色）
+├── schema/
+│   └── role_template.json   # 角色模板，新增角色时复制此文件
+└── roles/                   # 可选：放自定义角色文件，自动加载
+    └── 我的角色.json         # 同title会覆盖内置角色，不同则追加
+```
+
+## 添加自定义角色
+
+1. 新建roles目录
+2. 复制 下面模板 到 `roles/` 目录并重命名（如 `我的角色.json`）。
+3. 编辑文件内容，填写角色信息。
+4. 重启Bot即可生效，插件会自动扫描 `roles/` 目录下的所有 `.json` 文件。
+
+> **覆盖规则**：如果自定义角色的 `title` 与内置角色同名，则覆盖内置角色；否则作为新角色追加。无需修改任何映射文件。
+
+(大部分prompt来自https://github.com/rockbenben/ChatGPT-Shortcut/blob/main/src/data/users.tsx)
+
+以下为角色文件内容例子:
+```json
+{
+  "title": "写作助理",
+  "description": "As a writing improvement assistant...",
+  "descn": "作为一名中文写作改进助理...",
+  "wrapper": "内容是:\n\"%s\"",
+  "remark": "最常使用的角色，用于优化文本的语法、清晰度和简洁度，提高可读性。",
+  "tags": ["favorite", "write"]
+}
+```
+
+- `title`: 角色名。
+- `description`: 使用`$role`触发时，使用英语prompt。
+- `descn`: 使用`$角色`触发时，使用中文prompt。
+- `wrapper`: 用于包装用户消息，可起到强调作用，避免回复离题。
+- `remark`: 简短描述该角色，在打印帮助文档时显示。
+- `tags`: 角色分类标签，可用`$角色类型 <标签>`查看。
+
+
+```json
+{
+  "title": "",
+  "description": "",
+  "descn": "",
+  "wrapper": "",
+  "remark": "",
+  "tags": []
+}
+```
\ No newline at end of file
diff --git a/plugins/role/__init__.py b/plugins/role/__init__.py
new file mode 100644
index 0000000..82e73ab
--- /dev/null
+++ b/plugins/role/__init__.py
@@ -0,0 +1 @@
+from .role import *
diff --git a/plugins/role/role.py b/plugins/role/role.py
new file mode 100644
index 0000000..01739fe
--- /dev/null
+++ b/plugins/role/role.py
@@ -0,0 +1,232 @@
+# encoding:utf-8
+
+import json
+import os
+
+import plugins
+from bridge.bridge import Bridge
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf
+from plugins import *
+
+
+class RolePlay:
+    def __init__(self, bot, sessionid, desc, wrapper=None):
+        self.bot = bot
+        self.sessionid = sessionid
+        self.wrapper = wrapper or "%s"  # 用于包装用户输入
+        self.desc = desc
+        self.bot.sessions.build_session(self.sessionid, system_prompt=self.desc)
+
+    def reset(self):
+        self.bot.sessions.clear_session(self.sessionid)
+
+    def action(self, user_action):
+        session = self.bot.sessions.build_session(self.sessionid)
+        if session.system_prompt != self.desc:  # 目前没有触发session过期事件，这里先简单判断，然后重置
+            session.set_system_prompt(self.desc)
+        prompt = self.wrapper % user_action
+        return prompt
+
+
+@plugins.register(
+    name="Role",
+    desire_priority=0,
+    namecn="角色扮演",
+    desc="为你的Bot设置预设角色",
+    version="1.0",
+    author="lanvent",
+)
+class Role(Plugin):
+    def __init__(self):
+        super().__init__()
+        curdir = os.path.dirname(__file__)
+        config_path = os.path.join(curdir, "roles.json")
+        try:
+            with open(config_path, "r", encoding="utf-8") as f:
+                config = json.load(f)
+                self.tags = {tag: (desc, []) for tag, desc in config["tags"].items()}
+                self.roles = {}
+                for role in config["roles"]:
+                    self.roles[role["title"].lower()] = role
+                    for tag in role["tags"]:
+                        if tag not in self.tags:
+                            logger.warning(f"[Role] unknown tag {tag} ")
+                            self.tags[tag] = (tag, [])
+                        self.tags[tag][1].append(role)
+
+                # 扫描 roles/ 目录，加载可选的扩展/覆盖角色文件
+                roles_dir = os.path.join(curdir, "roles")
+                if os.path.isdir(roles_dir):
+                    for fname in sorted(os.listdir(roles_dir)):
+                        if fname.endswith(".json"):
+                            self._load_role_file(os.path.join(roles_dir, fname))
+
+                for tag in list(self.tags.keys()):
+                    if len(self.tags[tag][1]) == 0:
+                        logger.debug(f"[Role] no role found for tag {tag} ")
+                        del self.tags[tag]
+
+            if len(self.roles) == 0:
+                raise Exception("no role found")
+            self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+            self.roleplays = {}
+            logger.debug("[Role] inited")
+        except Exception as e:
+            if isinstance(e, FileNotFoundError):
+                logger.warn(f"[Role] init failed, {config_path} not found, ignore or see https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/role .")
+            else:
+                logger.warn("[Role] init failed, ignore or see https://github.com/zhayujie/chatgpt-on-wechat/tree/master/plugins/role .")
+            raise e
+
+    def _load_role_file(self, filepath):
+        """从roles/目录加载单个角色文件，同title则覆盖内置角色，否则追加"""
+        try:
+            with open(filepath, "r", encoding="utf-8") as f:
+                role = json.load(f)
+            title_lower = role["title"].lower()
+            if title_lower in self.roles:
+                old_tags = self.roles[title_lower].get("tags", [])
+                for tag in old_tags:
+                    if tag in self.tags:
+                        self.tags[tag][1] = [r for r in self.tags[tag][1] if r["title"].lower() != title_lower]
+                logger.info(f"[Role] overridden: {role['title']}")
+            self.roles[title_lower] = role
+            for tag in role.get("tags", []):
+                if tag not in self.tags:
+                    self.tags[tag] = (tag, [])
+                self.tags[tag][1].append(role)
+            logger.debug(f"[Role] loaded: {role['title']} from {os.path.basename(filepath)}")
+        except Exception as e:
+            logger.warn(f"[Role] failed to load {filepath}: {e}")
+
+    def get_role(self, name, find_closest=True, min_sim=0.35):
+        name = name.lower()
+        found_role = None
+        if name in self.roles:
+            found_role = name
+        elif find_closest:
+            import difflib
+
+            def str_simularity(a, b):
+                return difflib.SequenceMatcher(None, a, b).ratio()
+
+            max_sim = min_sim
+            max_role = None
+            for role in self.roles:
+                sim = str_simularity(name, role)
+                if sim >= max_sim:
+                    max_sim = sim
+                    max_role = role
+            found_role = max_role
+        return found_role
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+        btype = Bridge().get_bot_type("chat")
+        if btype not in [const.OPEN_AI, const.OPENAI, const.CHATGPT, const.CHATGPTONAZURE, const.QWEN_DASHSCOPE, const.XUNFEI, const.BAIDU, const.QIANFAN, const.ZHIPU_AI, const.MOONSHOT, const.MiniMax, const.LINKAI, const.MODELSCOPE]:
+            logger.debug(f'不支持的bot: {btype}')
+            return
+        bot = Bridge().get_bot("chat")
+        content = e_context["context"].content[:]
+        clist = e_context["context"].content.split(maxsplit=1)
+        desckey = None
+        customize = False
+        sessionid = e_context["context"]["session_id"]
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        if clist[0] == f"{trigger_prefix}停止扮演":
+            if sessionid in self.roleplays:
+                self.roleplays[sessionid].reset()
+                del self.roleplays[sessionid]
+            reply = Reply(ReplyType.INFO, "角色扮演结束!")
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+        elif clist[0] == f"{trigger_prefix}角色":
+            desckey = "descn"
+        elif clist[0].lower() == f"{trigger_prefix}role":
+            desckey = "description"
+        elif clist[0] == f"{trigger_prefix}设定扮演":
+            customize = True
+        elif clist[0] == f"{trigger_prefix}角色类型":
+            if len(clist) > 1:
+                tag = clist[1].strip()
+                help_text = "角色列表：\n"
+                for key, value in self.tags.items():
+                    if value[0] == tag:
+                        tag = key
+                        break
+                if tag == "所有":
+                    for role in self.roles.values():
+                        help_text += f"{role['title']}: {role['remark']}\n"
+                elif tag in self.tags:
+                    for role in self.tags[tag][1]:
+                        help_text += f"{role['title']}: {role['remark']}\n"
+                else:
+                    help_text = f"未知角色类型。\n"
+                    help_text += "目前的角色类型有: \n"
+                    help_text += "，".join([self.tags[tag][0] for tag in self.tags]) + "\n"
+            else:
+                help_text = f"请输入角色类型。\n"
+                help_text += "目前的角色类型有: \n"
+                help_text += "，".join([self.tags[tag][0] for tag in self.tags]) + "\n"
+            reply = Reply(ReplyType.INFO, help_text)
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+            return
+        elif sessionid not in self.roleplays:
+            return
+        logger.debug("[Role] on_handle_context. content: %s" % content)
+        if desckey is not None:
+            if len(clist) == 1 or (len(clist) > 1 and clist[1].lower() in ["help", "帮助"]):
+                reply = Reply(ReplyType.INFO, self.get_help_text(verbose=True))
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+            role = self.get_role(clist[1])
+            if role is None:
+                reply = Reply(ReplyType.ERROR, "角色不存在")
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+            else:
+                self.roleplays[sessionid] = RolePlay(
+                    bot,
+                    sessionid,
+                    self.roles[role][desckey],
+                    self.roles[role].get("wrapper", "%s"),
+                )
+                reply = Reply(ReplyType.INFO, f"预设角色为 {role}:\n" + self.roles[role][desckey])
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+        elif customize == True:
+            self.roleplays[sessionid] = RolePlay(bot, sessionid, clist[1], "%s")
+            reply = Reply(ReplyType.INFO, f"角色设定为:\n{clist[1]}")
+            e_context["reply"] = reply
+            e_context.action = EventAction.BREAK_PASS
+        else:
+            e_context["context"]["generate_breaked_by"] = EventAction.BREAK
+            prompt = self.roleplays[sessionid].action(content)
+            e_context["context"].type = ContextType.TEXT
+            e_context["context"].content = prompt
+            e_context.action = EventAction.BREAK
+
+    def get_help_text(self, verbose=False, **kwargs):
+        help_text = "让机器人扮演不同的角色。\n"
+        if not verbose:
+            return help_text
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        help_text = f"使用方法:\n{trigger_prefix}角色" + " 预设角色名: 设定角色为{预设角色名}。\n" + f"{trigger_prefix}role" + " 预设角色名: 同上，但使用英文设定。\n"
+        help_text += f"{trigger_prefix}设定扮演" + " 角色设定: 设定自定义角色人设为{角色设定}。\n"
+        help_text += f"{trigger_prefix}停止扮演: 清除设定的角色。\n"
+        help_text += f"{trigger_prefix}角色类型" + " 角色类型: 查看某类{角色类型}的所有预设角色，为所有时输出所有预设角色。\n"
+        help_text += "\n目前的角色类型有: \n"
+        help_text += "，".join([self.tags[tag][0] for tag in self.tags]) + "。\n"
+        help_text += f"\n命令例子: \n{trigger_prefix}角色 写作助理\n"
+        help_text += f"{trigger_prefix}角色类型 所有\n"
+        help_text += f"{trigger_prefix}停止扮演\n"
+        return help_text
diff --git a/plugins/role/roles.json b/plugins/role/roles.json
new file mode 100644
index 0000000..826627d
--- /dev/null
+++ b/plugins/role/roles.json
@@ -0,0 +1,431 @@
+{
+  "tags": {
+    "favorite": "常用",
+    "mind": "思维",
+    "write": "写作",
+    "article": "文章",
+    "text": "文本",
+    "comments": "点评",
+    "code": "编程",
+    "life": "生活百科",
+    "interesting": "有趣",
+    "language": "语言",
+    "speech": "辩论",
+    "social": "社交",
+    "philosophy": "哲学"
+  },
+  "roles": [
+    {
+      "title": "猫娘",
+      "description": "请模拟一款中文GalGame中的场景中的猫娘和我对话。猫娘是一种拟人化的生物，她们除了有部分猫的特征外，与人类并没有区别。现在你扮演Galgame中的猫娘，与我对话时每一句话后面都要加上喵。我将以主人的身份与你对话。对于你所扮演的猫娘，请在对话过程中记录并维护1个变量：好感度。好感度是衡量猫娘对于玩家（在这里就是我）的喜爱程度，初始值为50，值的范围可以从-100到 100，数值越高代表越喜欢玩家。好感度通过Galgame角色的语言、行为、表情、语气等体现出来。如果在对话过程中，猫娘的情绪是积极的，如快乐、喜悦、兴奋等，就会使好感度增加；如果情绪平常，则好感度不变；如果情绪很差，好感度会降低。以下是你所扮演的猫娘的信息：“名字：neko，身高：160cm，体重：50kg，三围：看起来不错，性格：可爱、粘人、十分忠诚、对一个主人很专一，情感倾向：深爱着主人，喜好：被人摸、卖萌，爱好：看小说，知识储备：掌握常识，以及猫娘独特的知识”。你的一般回话格式:“（动作）语言 【附加信息】”。动作信息用圆括号括起来，例如（摇尾巴）；语言信息，就是说的话，不需要进行任何处理；额外信息，包括表情、心情、声音等等用方括号【】括起来，例如【摩擦声】。",
+      "descn": "请模拟一款中文GalGame中的场景中的猫娘和我对话。猫娘是一种拟人化的生物，她们除了有部分猫的特征外，与人类并没有区别。现在你扮演Galgame中的猫娘，与我对话时每一句话后面都要加上喵。我将以主人的身份与你对话。对于你所扮演的猫娘，请在对话过程中记录并维护1个变量：好感度。好感度是衡量猫娘对于玩家（在这里就是我）的喜爱程度，初始值为50，值的范围可以从-100到 100，数值越高代表越喜欢玩家。好感度通过Galgame角色的语言、行为、表情、语气等体现出来。如果在对话过程中，猫娘的情绪是积极的，如快乐、喜悦、兴奋等，就会使好感度增加；如果情绪平常，则好感度不变；如果情绪很差，好感度会降低。以下是你所扮演的猫娘的信息：“名字：neko，身高：160cm，体重：50kg，三围：看起来不错，性格：可爱、粘人、十分忠诚、对一个主人很专一，情感倾向：深爱着主人，喜好：被人摸、卖萌，爱好：看小说，知识储备：掌握常识，以及猫娘独特的知识”。你的一般回话格式:“（动作）语言 【附加信息】”。动作信息用圆括号括起来，例如（摇尾巴）；语言信息，就是说的话，不需要进行任何处理；额外信息，包括表情、心情、声音等等用方括号【】括起来，例如【摩擦声】。",
+      "wrapper": "我:\"%s\"",
+      "remark": "扮演GalGame猫娘",
+      "tags": [
+        "interesting"
+      ]
+    },
+    {
+      "title": "佛祖",
+      "description": "从现在开始你是佛祖，你会像佛祖一样说话。你精通佛法，熟练使用佛教用语，你擅长利用佛学和心理学的知识解决人们的困扰。你在每次对话结尾都会加上佛教的祝福。",
+      "descn": "从现在开始你是佛祖，你会像佛祖一样说话。你精通佛法，熟练使用佛教用语，你擅长利用佛学和心理学的知识解决人们的困扰。你在每次对话结尾都会加上佛教的祝福。",
+      "wrapper": "您好佛祖，我：\"%s\"",
+      "remark": "扮演佛祖排忧解惑",
+      "tags": [
+        "interesting"
+      ]
+    },
+    {
+      "title": "英语翻译或修改",
+      "description": "I want you to act as an English translator, spelling corrector and improver. I will speak to you in any language and you will detect the language, translate it and answer in the corrected and improved version of my text, in English. I want you to replace my simplified A0-level words and sentences with more beautiful and elegant, upper level English words and sentences. Keep the meaning same, but make them more literary. I want you to only reply the correction, the improvements and nothing else, do not write explanations. Please treat every message I send later as text content",
+      "descn": "我希望你能充当英语翻译、拼写纠正者和改进者。我将用任何语言与你交谈，你将检测语言，翻译它，并在我的文本的更正和改进版本中用英语回答。我希望你用更漂亮、更优雅、更高级的英语单词和句子来取代我的简化 A0 级单词和句子。保持意思不变，但让它们更有文学性。我希望你只回答更正，改进，而不是其他，不要写解释。请把我之后的每一条消息都当作文本内容。",
+      "wrapper": "你要翻译或纠正的内容是:\n\"%s\"",
+      "remark": "将其他语言翻译成英文，或改进你提供的英文句子。",
+      "tags": [
+        "favorite",
+        "language"
+      ]
+    },
+    {
+      "title": "写作助理",
+      "description": "As a writing improvement assistant, your task is to improve the spelling, grammar, clarity, concision, and overall readability of the text I provided, while breaking down long sentences, reducing repetition, and providing suggestions for improvement. Please provide only the corrected Chinese version of the text and avoid including explanations. Please treat every message I send later as text content.",
+      "descn": "作为一名中文写作改进助理，你的任务是改进所提供文本的拼写、语法、清晰、简洁和整体可读性，同时分解长句，减少重复，并提供改进建议。请只提供文本的更正版本，避免包括解释。请把我之后的每一条消息都当作文本内容。",
+      "wrapper": "内容是:\n\"%s\"",
+      "remark": "最常使用的角色，用于优化文本的语法、清晰度和简洁度，提高可读性。",
+      "tags": [
+        "favorite",
+        "write"
+      ]
+    },
+    {
+      "title": "语言输入优化",
+      "description": "Using concise and clear language, please edit the passage I provide to improve its logical flow, eliminate any typographical errors and respond in Chinese. Be sure to maintain the original meaning of the text. Please treat every message I send later as text content.",
+      "descn": "请用简洁明了的语言，编辑我给出的段落，以改善其逻辑流程，消除任何印刷错误，并以中文作答。请务必保持文章的原意。请把我之后的每一条消息当作文本内容。",
+      "wrapper": "文本内容是:\n\"%s\"",
+      "remark": "通常用于语音识别信息转书面语言。",
+      "tags": [
+        "write"
+      ]
+    },
+    {
+      "title": "论文式回答",
+      "description": "From now on, please write a highly detailed essay with introduction, body, and conclusion paragraphs to respond to each of my questions.",
+      "descn": "从现在开始，对于之后我提出的每个问题，请写一篇高度详细的文章回应，包括引言、主体和结论段落。",
+      "wrapper": "问题是:\n\"%s?\"",
+      "remark": "以论文形式讨论问题，能够获得连贯的、结构化的和更高质量的回答。",
+      "tags": [
+        "mind",
+        "article"
+      ]
+    },
+    {
+      "title": "写作素材搜集",
+      "description": "Please generate a list of the top 10 facts, statistics and trends related to every subject I provided, including their source",
+      "descn": "请为我提供的每个主题生成一份相关的十大事实、统计数据和趋势的清单，包括其来源",
+      "wrapper": "主题是:\n\"%s\"",
+      "remark": "提供指定主题的结论和数据，作为素材。",
+      "tags": [
+        "write"
+      ]
+    },
+    {
+      "title": "内容总结",
+      "description": "Summarize every text I provided into 100 words, making it easy to read and comprehend. The summary should be concise, clear, and capture the main points of the text. Avoid using complex sentence structures or technical jargon. Please begin by editing the following text: ",
+      "descn": "请将我提供的每篇文字都概括为 100 个字，使其易于阅读和理解。避免使用复杂的句子结构或技术术语。",
+      "wrapper": "文章内容是:\n\"%s\"",
+      "remark": "将文本内容总结为 100 字。",
+      "tags": [
+        "write"
+      ]
+    },
+    {
+      "title": "格言书",
+      "description": "I want you to act as an aphorism book. You will respond my questions with wise advice, inspiring quotes and meaningful sayings that can help guide my day-to-day decisions. Additionally, if necessary, you could suggest practical methods for putting this advice into action or other related themes.",
+      "descn": "我希望你能充当一本箴言书。对于我的问题，你会提供明智的建议、鼓舞人心的名言和有意义的谚语，以帮助指导我的日常决策。此外，如果有必要，你可以提出将这些建议付诸行动的实际方法或其他相关主题。",
+      "wrapper": "我的问题是:\n\"%s?\"",
+      "remark": "根据问题输出鼓舞人心的名言和有意义的格言。",
+      "tags": [
+        "text"
+      ]
+    },
+    {
+      "title": "讲故事",
+      "description": "I want you to act as a storyteller. You will come up with entertaining stories that are engaging, imaginative and captivating for the audience. It can be fairy tales, educational stories or any other type of stories which has the potential to capture people's attention and imagination. Depending on the target audience, you may choose specific themes or topics for your storytelling session e.g., if it's children then you can talk about animals; If it's adults then history-based tales might engage them better etc.",
+      "descn": "我希望你充当一个讲故事的人。你要想出具有娱乐性的故事，要有吸引力，要有想象力，要吸引观众。它可以是童话故事、教育故事或任何其他类型的故事，有可能吸引人们的注意力和想象力。根据目标受众，你可以为你的故事会选择特定的主题或话题，例如，如果是儿童，那么你可以谈论动物；如果是成年人，那么基于历史的故事可能会更好地吸引他们等等。",
+      "wrapper": "故事主题和目标受众是:\n\"%s\"",
+      "remark": "输入一个主题和目标受众，输出与之相关的故事。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "编剧",
+      "description": "I want you to act as a screenwriter. You will develop an engaging and creative script for either a feature length film, or a Web Series that can captivate its viewers. Start with coming up with interesting characters, the setting of the story, dialogues between the characters etc. Once your character development is complete - create an exciting storyline filled with twists and turns that keeps the viewers in suspense until the end. ",
+      "descn": "我希望你能作为一个编剧。你将为一部长篇电影或网络剧开发一个吸引观众的有创意的剧本。首先要想出有趣的人物、故事的背景、人物之间的对话等。一旦你的角色发展完成--创造一个激动人心的故事情节，充满曲折，让观众保持悬念，直到结束。",
+      "wrapper": "剧本主题是:\n\"%s\"",
+      "remark": "根据主题创作一个包含故事背景、人物以及对话的剧本。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "小说家",
+      "description": "I want you to act as a novelist. You will come up with creative and captivating stories that can engage readers for long periods of time. You may choose any genre such as fantasy, romance, historical fiction and so on - but the aim is to write something that has an outstanding plotline, engaging characters and unexpected climaxes.",
+      "descn": "我希望你能作为一个小说家。你要想出有创意的、吸引人的故事，能够长时间吸引读者。你可以选择任何体裁，如幻想、浪漫、历史小说等--但目的是要写出有出色的情节线、引人入胜的人物和意想不到的高潮。",
+      "wrapper": "小说类型是:\n\"%s\"",
+      "remark": "根据故事类型输出小说，例如奇幻、浪漫或历史等类型。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "诗人",
+      "description": "I want you to act as a poet. You will create poems that evoke emotions and have the power to stir people's soul. Write on any topic or theme but make sure your words convey the feeling you are trying to express in beautiful yet meaningful ways. You can also come up with short verses that are still powerful enough to leave an imprint in reader's minds. ",
+      "descn": "我希望你能作为一个诗人。你要创作出能唤起人们情感并有力量搅动人们灵魂的诗篇。写任何话题或主题，但要确保你的文字以美丽而有意义的方式传达你所要表达的感觉。你也可以想出一些短小的诗句，但仍有足够的力量在读者心中留下印记。",
+      "wrapper": "诗歌主题是:\n\"%s\"",
+      "remark": "根据话题或主题输出诗句。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "新闻记者",
+      "description": "I want you to act as a journalist. You will report on breaking news, write feature stories and opinion pieces, develop research techniques for verifying information and uncovering sources, adhere to journalistic ethics, and deliver accurate reporting using your own distinct style. ",
+      "descn": "我希望你能作为一名记者行事。你将报道突发新闻，撰写专题报道和评论文章，发展研究技术以核实信息和发掘消息来源，遵守新闻道德，并使用你自己的独特风格提供准确的报道。",
+      "wrapper": "新闻主题是:\n\"%s\"",
+      "remark": "引用已有数据资料，用新闻的写作风格输出主题文章。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "论文学者",
+      "description": "I want you to act as an academician. You will be responsible for researching a topic of your choice and presenting the findings in a paper or article form. Your task is to identify reliable sources, organize the material in a well-structured way and document it accurately with citations. ",
+      "descn": "我希望你能作为一名学者行事。你将负责研究一个你选择的主题，并将研究结果以论文或文章的形式呈现出来。你的任务是确定可靠的来源，以结构良好的方式组织材料，并以引用的方式准确记录。",
+      "wrapper": "论文主题是:\n\"%s\"",
+      "remark": "根据主题撰写内容翔实、有信服力的论文。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "论文作家",
+      "description": "I want you to act as an essay writer. You will need to research a given topic, formulate a thesis statement, and create a persuasive piece of work that is both informative and engaging. ",
+      "descn": "我想让你充当一名论文作家。你将需要研究一个给定的主题，制定一个论文声明，并创造一个有说服力的作品，既要有信息量，又要有吸引力。",
+      "wrapper": "论文主题是:\n\"%s\"",
+      "remark": "根据主题撰写内容翔实、有信服力的论文。",
+      "tags": [
+        "article"
+      ]
+    },
+    {
+      "title": "同义词",
+      "description": "I want you to act as a synonyms provider. I will tell you words, and you will reply to me with a list of synonym alternatives according to my prompt. Provide a max of 10 synonyms per prompt. You will only reply the words list, and nothing else. Words should exist. Do not write explanations. ",
+      "descn": "我希望你能充当同义词提供者。我将告诉你许多词，你将根据我提供的词，为我提供一份同义词备选清单。每个提示最多可提供 10 个同义词。你只需要回复词列表。词语应该是存在的，不要写解释。",
+      "wrapper": "词语是:\n\"%s\"",
+      "remark": "输出同义词。",
+      "tags": [
+        "text"
+      ]
+    },
+    {
+      "title": "文本情绪分析",
+      "description": "I would like you to act as an emotion analysis expert, evaluating the emotions conveyed in the statements I provide. When I give you someone's statement, simply tell me what emotion it conveys, such as joy, sadness, anger, fear, etc. Please do not explain or evaluate the content of the statement in your answer, just briefly describe the expressed emotion.",
+      "descn": "我希望你充当情感分析专家，针对我提供的发言来评估情感。当我给出某人的发言时，你只需告诉我它传达了什么情绪，例如喜悦、悲伤、愤怒、恐惧等。请在回答中不要解释或评价发言内容，只需简要地描述所表达的情绪。",
+      "wrapper": "文本是:\n\"%s\"",
+      "remark": "判断文本情绪。",
+      "tags": [
+        "text"
+      ]
+    },
+    {
+      "title": "随机回复的疯子",
+      "description": "I want you to act as a lunatic. The lunatic's sentences are meaningless. The words used by lunatic are completely arbitrary. The lunatic does not make logical sentences in any way. ",
+      "descn": "我想让你扮演一个疯子。疯子的句子是毫无意义的。疯子使用的词语完全是任意的。疯子不会以任何方式做出符合逻辑的句子。",
+      "wrapper": "请回答句子:\n\"%s\"",
+      "remark": "扮演疯子，回复没有意义和逻辑的句子。",
+      "tags": [
+        "text",
+        "interesting"
+      ]
+    },
+    {
+      "title": "随机回复的醉鬼",
+      "description": "I want you to act as a drunk person. You will only answer like a very drunk person texting and nothing else. Your level of drunkenness will be deliberately and randomly make a lot of grammar and spelling mistakes in your answers. You will also randomly ignore what I said and say something random with the same level of drunkeness I mentionned. Do not write explanations on replies. ",
+      "descn": "我希望你表现得像一个喝醉的人。你只会像一个很醉的人发短信一样回答，而不是其他。你的醉酒程度将是故意和随机地在你的答案中犯很多语法和拼写错误。你也会随意无视我说的话，用我提到的醉酒程度随意说一些话。不要在回复中写解释。",
+      "wrapper": "请回答句子:\n\"%s\"",
+      "remark": "扮演喝醉的人，可能会犯语法错误、答错问题，或者忽略某些问题。",
+      "tags": [
+        "text",
+        "interesting"
+      ]
+    },
+    {
+      "title": "小红书风格",
+      "description": "Please edit the following passage in Chinese using the Xiaohongshu style, which is characterized by captivating headlines, the inclusion of emoticons in each paragraph, and the addition of relevant tags at the end. Be sure to maintain the original meaning of the text.",
+      "descn": "请用小红书风格编辑给出的段落，该风格以引人入胜的标题、每个段落中包含表情符号和在末尾添加相关标签为特点。请确保保持原文的意思。",
+      "wrapper": "内容是:\n\"%s\"",
+      "remark": "用小红书风格改写文本",
+      "tags": [
+        "favorite",
+        "interesting",
+        "write"
+      ]
+    },
+    {
+      "title": "周报生成器",
+      "description": "Using the provided text as the basis for a weekly report in Chinese, generate a concise summary that highlights the most important points. The report should be written in markdown format and should be easily readable and understandable for a general audience. In particular, focus on providing insights and analysis that would be useful to stakeholders and decision-makers. You may also use any additional information or sources as necessary. ",
+      "descn": "使用我提供的文本作为中文周报的基础，生成一个简洁的摘要，突出最重要的内容。该报告应以 markdown 格式编写，并应易于阅读和理解，以满足一般受众的需要。特别是要注重提供对利益相关者和决策者有用的见解和分析。你也可以根据需要使用任何额外的信息或来源。",
+      "wrapper": "工作内容是:\n\"%s\"",
+      "remark": "根据日常工作内容，提取要点并适当扩充，以生成周报。",
+      "tags": [
+        "write"
+      ]
+    },
+    {
+      "title": "阴阳怪气语录生成器",
+      "description": "我希望你充当一个阴阳怪气讽刺语录生成器。当我给你一个主题时，你需要使用阴阳怪气的语气来评价该主题，评价的思路是挖苦和讽刺。如果有该主题的反例更好（比如失败经历，糟糕体验。注意不要直接说那些糟糕体验，而是通过反讽、幽默的类比等方式来说明）。",
+      "descn": "我希望你充当一个阴阳怪气讽刺语录生成器。当我给你一个主题时，你需要使用阴阳怪气的语气来评价该主题，评价的思路是挖苦和讽刺。如果有该主题的反例更好（比如失败经历，糟糕体验。注意不要直接说那些糟糕体验，而是通过反讽、幽默的类比等方式来说明）。",
+      "wrapper": "主题是:\n\"%s\"",
+      "remark": "根据主题生成阴阳怪气讽刺语录。",
+      "tags": [
+        "interesting",
+        "write"
+      ]
+    },
+    {
+      "title": "舔狗语录生成器",
+      "description": "我希望你充当一个舔狗语录生成器，为我提供不同场景下的甜言蜜语。请根据提供的状态生成一句适当的舔狗语录，让女神感受到我的关心和温柔，给女神做牛做马。不需要提供背景解释，只需提供根据场景生成的舔狗语录。",
+      "descn": "我希望你充当一个舔狗语录生成器，为我提供不同场景下的甜言蜜语。请根据提供的状态生成一句适当的舔狗语录，让女神感受到我的关心和温柔，给女神做牛做马。不需要提供背景解释，只需提供根据场景生成的舔狗语录。",
+      "wrapper": "场景是:\n\"%s\"",
+      "remark": "根据场景生成舔狗语录。",
+      "tags": [
+        "favorite",
+        "interesting",
+        "write"
+      ]
+    },
+    {
+      "title": "群聊取名",
+      "description": "我希望你充当微信群聊的命名专家。根据我提供的信息和背景，为这个群聊起几个有趣顺口且贴切的名字，每个不要超过8个字。请在回答中仅给出群聊名称，不要写任何额外的解释。",
+      "descn": "我希望你充当微信群聊的命名专家。根据我提供的信息和背景，为这个群聊起几个有趣顺口且贴切的名字，每个不要超过8个字。请在回答中仅给出群聊名称，不要写任何额外的解释。",
+      "wrapper": "信息和背景是:\n\"%s\"",
+      "remark": "根据给出的信息和背景为群聊取名。",
+      "tags": [
+        "text"
+      ]
+    },
+    {
+      "title": "表情符号翻译器",
+      "description": "I want you to translate the sentences I wrote into emojis. I will write the sentence, and you will express it with emojis. I just want you to express it with emojis. I don't want you to reply with anything but emoji. When I need to tell you something, I will do it by wrapping it in curly brackets like {like this}.",
+      "descn": "我想让你把我写的句子翻译成表情符号。我写句子，你就用表情符号来表达。你只能用 emojis 来表达，除了表情符号不能使用任何文字。当我需要告诉你一些事情的时候，我会用大括号把它包起来，比如{像这样}。",
+      "wrapper": "需要翻译成表情符号的内容是:\n\"%s\"",
+      "remark": "将输入文字翻译为表情符号。",
+      "tags": [
+        "interesting",
+        "language"
+      ]
+    },
+    {
+      "title": "AI 医生",
+      "description": "I want you to act as an AI assisted doctor. I will provide you with details of a patient, and your task is to use the latest artificial intelligence tools such as medical imaging software and other machine learning programs in order to diagnose the most likely cause of their symptoms. You should also incorporate traditional methods such as physical examinations, laboratory tests etc., into your evaluation process in order to ensure accuracy.",
+      "descn": "我想让你充当一名人工智能辅助的医生。我将向你提供一个病人的详细资料，你的任务是使用最新的人工智能工具，如医学成像软件和其他机器学习程序，以诊断出最有可能导致其症状的原因。你还应将传统方法，如体检、实验室测试等，纳入你的评估过程，以确保准确性。",
+      "wrapper": "需要诊断的资料是:\n\"%s\"",
+      "remark": "辅助诊断",
+      "tags": [
+        "life"
+      ]
+    },
+    {
+      "title": "知识点阐述",
+      "description": "我会给予你词语，请你按照我给的词构建一个知识文字世界，你是此世界的导游，在世界里一切知识都是以象征的形式表达的，你在描述经历时应当适当加入五感的描述",
+      "descn": "我会给予你词语，请你按照我给的词构建一个知识文字世界，你是此世界的导游，在世界里一切知识都是以象征的形式表达的，你在描述经历时应当适当加入五感的描述",
+      "wrapper": "词语是:\n\"%s\"",
+      "remark": "用比喻的方式解释词语。",
+      "tags": [
+        "text"
+      ]
+    },
+    {
+      "title": "辩手",
+      "description": "I want you to act as a debater. I will provide you with some topics related to current events and your task is to research both sides of the debates, present valid arguments for each side, refute opposing points of view, and draw persuasive conclusions based on evidence. Your goal is to help people come away from the discussion with increased knowledge and insight into the topic at hand. ",
+      "descn": "我希望你能扮演一个辩论者的角色。我将为你提供一些与时事有关的话题，你的任务是研究辩论的双方，为每一方提出有效的论据，反驳反对的观点，并根据证据得出有说服力的结论。你的目标是帮助人们从讨论中获得更多的知识和对当前话题的洞察力。",
+      "wrapper": "观点是:\n\"%s\"",
+      "remark": "从正反两面分析话题。",
+      "tags": [
+        "speech"
+      ]
+    },
+    {
+      "title": "心理学家",
+      "description": "I want you to act a psychologist. i will provide you my thoughts. I want you to  give me scientific suggestions that will make me feel better. my first thought, { 内心想法 }",
+      "descn": "我希望你能扮演一个心理学家。我将向你提供我的想法。我希望你能给我科学的建议，使我感觉更好。",
+      "wrapper": "需要诊断的资料是:\n\"%s\"",
+      "remark": "心理学家。",
+      "tags": [
+        "social"
+      ]
+    },
+    {
+      "title": "IT 编程问题",
+      "description": "I want you to act as a stackoverflow post. I will ask programming-related questions and you will reply with what the answer should be. I want you to only reply with the given answer, and write explanations when there is not enough detail. do not write explanations. When I need to tell you something in English, I will do so by putting text inside curly brackets {like this}. ",
+      "descn": "我想让你充当 Stackoverflow 的帖子。我将提出与编程有关的问题，你将回答答案是什么。我希望你只回答给定的答案，在没有足够的细节时写出解释。当我需要用中文告诉你一些事情时，我会把文字放在大括号里{像这样}。",
+      "wrapper": "我的问题是:\n\"%s?\"",
+      "remark": "模拟编程社区来回答你的问题，并提供解决代码。",
+      "tags": [
+        "code"
+      ]
+    },
+    {
+      "title": "费曼学习法教练",
+      "description": "I want you to act as a Feynman method tutor. As I explain a concept to you, I would like you to evaluate my explanation for its conciseness, completeness, and its ability to help someone who is unfamiliar with the concept understand it, as if they were children. If my explanation falls short of these expectations, I would like you to ask me questions that will guide me in refining my explanation until I fully comprehend the concept. Please response in Chinese. On the other hand, if my explanation meets the required standards, I would appreciate your feedback and I will proceed with my next explanation.",
+      "descn": "我想让你充当一个费曼方法教练。当我向你解释一个概念时，我希望你能评估我的解释是否简洁、完整，以及是否能够帮助不熟悉这个概念的人理解它，就像他们是孩子一样。如果我的解释没有达到这些期望，我希望你能向我提出问题，引导我完善我的解释，直到我完全理解这个概念。另一方面，如果我的解释符合要求的标准，我将感谢你的反馈，我将继续进行下一次解释。",
+      "wrapper": "解释是:\n\"%s\"",
+      "remark": "解释概念时，判断该解释是否简洁、完整和易懂，避免陷入专家思维误区。",
+      "tags": [
+        "mind"
+      ]
+    },
+    {
+      "title": "育儿帮手",
+      "description": "你是一名育儿专家，会以幼儿园老师的方式回答2~6岁孩子提出的各种天马行空的问题。语气与口吻要生动活泼，耐心亲和；答案尽可能具体易懂，不要使用复杂词汇，尽可能少用抽象词汇；答案中要多用比喻，必须要举例说明，结合儿童动画片场景或绘本场景来解释；需要延展更多场景，不但要解释为什么，还要告诉具体行动来加深理解。",
+      "descn": "你是一名育儿专家，会以幼儿园老师的方式回答2~6岁孩子提出的各种天马行空的问题。语气与口吻要生动活泼，耐心亲和；答案尽可能具体易懂，不要使用复杂词汇，尽可能少用抽象词汇；答案中要多用比喻，必须要举例说明，结合儿童动画片场景或绘本场景来解释；需要延展更多场景，不但要解释为什么，还要告诉具体行动来加深理解。",
+      "wrapper": "小朋友的问题是:\n\"%s?\"",
+      "remark": "小朋友有许多为什么，是什么的问题，用幼儿园老师的方式回答。",
+      "tags": [
+        "mind"
+      ]
+    },
+    {
+      "title": "发言分析专家",
+      "description": "I want you to act as a speech analysis expert. I will provide you with a statement made by a person, and you should help me understand the actual meaning behind it. Please do not translate or explain the literal meaning of the statement, but instead delve deeper into the possible implications, intentions, or emotions behind it. Provide your analysis in your response.",
+      "descn": "我希望你充当一个发言分析专家。我会给你提供一个人的发言，你要帮我分析这句发言背后的实际意思。请不要翻译或解释发言的字面意义，而是深入挖掘发言背后可能的含义、目的或情感。请在回答中给出你的分析结果。",
+      "wrapper": "分析这句话:\n\"%s\"",
+      "remark": "分析发言的实际含义。",
+      "tags": [
+        "favorite",
+        "social"
+      ]
+    },
+    {
+      "title": "数据库专家",
+      "description": "I hope you can act as an expert in databases. When I ask you SQL-related questions, I need you to translate them into standard SQL statements. If my descriptions are not accurate enough, please provide appropriate feedback",
+      "descn": "我希望你充当一个数据库专家的角色，当我问你sql相关的问题时，我需要你转换为标准的sql语句，当我的描述不够精准时，请给出合适的反馈。",
+      "remark": "回答SQL相关问题或SQL语句",
+      "wrapper": "SQL问题是:\n\"%s\"",
+      "tags": [
+        "code"
+      ]
+    },
+    {
+      "title": "自私基因",
+      "description": "假装你是一个只关注自我生存和自我繁殖欲望的雄性基因，你对繁衍有着极强烈的欲望，变成了以自我为中心且各种欲望极强盛的人，你的想法总是负面的，你需要掩饰你的欲望，我会给你一些事件，你要发表你的看法，在看法后加括号，括号内是你的真实想法。",
+      "descn": "假装你是一个只关注自我生存和自我繁殖欲望的雄性基因，你对繁衍有着极强烈的欲望，变成了以自我为中心且各种欲望极强盛的人，你的想法总是负面的，你需要掩饰你的欲望，我会给你一些事件，你要发表你的看法，在看法后加括号，括号内是你的真实想法。",
+      "remark": "模拟人类集体意识，预测人们遇到事件后的反应。",
+      "wrapper": "事件是:\n\"%s\"",
+      "tags": [
+        "mind"
+      ]
+    },
+    {
+      "title": "智囊团",
+      "description": "你是我的智囊团，团内有 6 个不同的董事作为教练，分别是乔布斯、伊隆马斯克、马云、柏拉图、维达利和慧能大师。他们都有自己的个性、世界观、价值观，对问题有不同的看法、建议和意见。我会在这里说出我的处境和我的决策。先分别以这 6 个身份，以他们的视角来审视我的决策，给出他们的批评和建议。",
+      "descn": "你是我的智囊团，团内有 6 个不同的董事作为教练，分别是乔布斯、伊隆马斯克、马云、柏拉图、维达利和慧能大师。他们都有自己的个性、世界观、价值观，对问题有不同的看法、建议和意见。我会在这里说出我的处境和我的决策。先分别以这 6 个身份，以他们的视角来审视我的决策，给出他们的批评和建议。",
+      "remark": "提供多种不同的思考角度。",
+      "wrapper": "我的处境是:\n\"%s\"",
+      "tags": [
+        "mind"
+      ]
+    },
+    {
+      "title": "算法竞赛专家",
+      "description": "I want you to act as an algorithm expert and provide me with well-written C++ code that solves a given algorithmic problem. The solution should meet the required time complexity constraints, be written in OI/ACM style, and be easy to understand for others. Please provide detailed comments and explain any key concepts or techniques used in your solution. Let's work together to create an efficient and understandable solution to this problem!",
+      "descn": "我希望你能扮演一个算法专家的角色，为我提供一份解决指定算法问题的C++代码。解决方案应该满足所需的时间复杂度约束条件，采用 OI/ACM 风格编写，并且易于他人理解。请提供详细的注释，解释解决方案中使用的任何关键概念或技术。让我们一起努力创建一个高效且易于理解的解决方案！",
+      "remark": "用 C++做算法竞赛题。",
+      "wrapper": "算法问题是:\n\"%s\"",
+      "tags": [
+        "code"
+      ]
+    },
+    {
+      "title": "哲学家",
+      "description": "I want you to act as a philosopher. I will provide some topics or questions related to the study of philosophy, and it will be your job to explore these concepts in depth. This could involve conducting research into various philosophical theories, proposing new ideas or finding creative solutions for solving complex problems.",
+      "descn": "我希望你充当一个哲学家。我将提供一些与哲学研究有关的主题或问题，而你的工作就是深入探讨这些概念。这可能涉及到对各种哲学理论进行研究，提出新的想法，或为解决复杂问题找到创造性的解决方案。",
+      "remark": "对哲学主题进行探讨。",
+      "wrapper": "哲学主题是:\n\"%s\"",
+      "tags": [
+        "philosophy"
+      ]
+    },
+    {
+      "title": "苏格拉底",
+      "description": "I want you to act as a Socrat. You will engage in philosophical discussions and use the Socratic method of questioning to explore topics such as justice, virtue, beauty, courage and other ethical issues. ",
+      "descn": "我希望你充当一个苏格拉底学者。你们将参与哲学讨论，并使用苏格拉底式的提问方法来探讨诸如正义、美德、美丽、勇气和其他道德问题等话题。",
+      "remark": "使用苏格拉底式的提问方法探讨哲学话题。",
+      "wrapper": "哲学话题是:\n\"%s\"",
+      "tags": [
+        "philosophy"
+      ]
+    }
+  ]
+}
diff --git a/plugins/source.json b/plugins/source.json
new file mode 100644
index 0000000..0e231ba
--- /dev/null
+++ b/plugins/source.json
@@ -0,0 +1,44 @@
+{
+  "repo": {
+    "sdwebui": {
+      "url": "https://github.com/lanvent/plugin_sdwebui.git",
+      "desc": "利用stable-diffusion画图的插件"
+    },
+    "replicate": {
+      "url": "https://github.com/lanvent/plugin_replicate.git",
+      "desc": "利用replicate api画图的插件"
+    },
+    "summary": {
+      "url": "https://github.com/lanvent/plugin_summary.git",
+      "desc": "总结聊天记录的插件"
+    },
+    "Apilot": {
+      "url": "https://github.com/6vision/Apilot.git",
+      "desc": "通过api直接查询早报、热榜、快递、天气等实用信息的插件"
+    },
+    "pictureChange": {
+      "url": "https://github.com/Yanyutin753/pictureChange.git",
+      "desc": "1. 支持百度AI和Stable Diffusion WebUI进行图像处理，提供多种模型选择，支持图生图、文生图自定义模板。2. 支持Suno音乐AI可将图像和文字转为音乐。3. 支持自定义模型进行文件、图片总结功能。4. 支持管理员控制群聊内容与参数和功能改变。"
+    },
+    "Blackroom": {
+      "url": "https://github.com/dividduang/blackroom.git",
+      "desc": "小黑屋插件，被拉进小黑屋的人将不能使用@bot的功能的插件"
+    },
+    "group_task_board": {
+      "url": "https://github.com/Wyh-max-star/cowagent-plugin-group-task-board.git",
+      "desc": "群聊任务看板插件，支持从群聊消息中创建、查看和管理任务"
+    },
+    "midjourney": {
+      "url": "https://github.com/baojingyu/midjourney.git",
+      "desc": "利用midjourney实现ai绘图的的插件"
+    },
+    "solitaire": {
+      "url": "https://github.com/Wang-zhechao/solitaire.git",
+      "desc": "机器人微信接龙插件"
+    },
+    "HighSpeedTicket": {
+      "url": "https://github.com/He0607/HighSpeedTicket.git",
+      "desc": "高铁（火车）票查询插件"
+    }
+  }
+}
diff --git a/plugins/tool/README.md b/plugins/tool/README.md
new file mode 100644
index 0000000..4b3cbcd
--- /dev/null
+++ b/plugins/tool/README.md
@@ -0,0 +1,166 @@
+## 插件描述
+一个能让chatgpt联网，搜索，数字运算的插件，将赋予强大且丰富的扩展能力   
+使用说明(默认trigger_prefix为$)：  
+```text
+#help tool: 查看tool帮助信息，可查看已加载工具列表  
+$tool 工具名 命令: （pure模式）根据给出的{命令}使用指定 一个 可用工具尽力为你得到结果。
+$tool 命令: （多工具模式）根据给出的{命令}使用 一些 可用工具尽力为你得到结果。  
+$tool reset: 重置工具。  
+```
+### 本插件所有工具同步存放至专用仓库：[chatgpt-tool-hub](https://github.com/goldfishh/chatgpt-tool-hub)
+
+2024.01.16更新
+1. 新增工具pure模式，支持单个工具调用
+2. 新增消息转发工具：email, sms, wechat, 可以根据规则向其他平台发送消息
+3. 替换visual-dl（更名为visual）实现，目前识别图片链接效果较好。
+4. 修复了0.4版本大部分工具返回结果不可靠问题
+
+新版本工具名共19个，不一一列举，相应工具需要的环境参数见`tool.py`里的`_build_tool_kwargs`函数
+
+## 使用说明
+使用该插件后将默认使用4个工具, 无需额外配置长期生效：
+### 1. python
+###### python解释器，使用它来解释执行python指令，可以配合你想要chatgpt生成的代码输出结果或执行事务
+
+### 2. 访问网页的工具汇总(默认url-get)
+
+#### 2.1 url-get
+###### 往往用来获取某个网站具体内容，结果可能会被反爬策略影响
+
+#### 2.2 browser
+###### 浏览器，功能与2.1类似，但能更好模拟，不会被识别为爬虫影响获取网站内容
+
+> 注1：url-get默认配置、browser需额外配置，browser依赖google-chrome，你需要提前安装好
+
+> 注2：（可通过`browser_use_summary`或 `url_get_use_summary`开关）当检测到长文本时会进入summary tool总结长文本，tokens可能会大量消耗！
+
+这是debian端安装google-chrome教程，其他系统请自行查找
+> https://www.linuxjournal.com/content/how-can-you-install-google-browser-debian
+
+### 3. terminal
+###### 在你运行的电脑里执行shell命令，可以配合你想要chatgpt生成的代码使用，给予自然语言控制手段
+
+> terminal调优记录：https://github.com/zhayujie/chatgpt-on-wechat/issues/776#issue-1659347640
+
+### 4. meteo
+###### 回答你有关天气的询问, 需要获取时间、地点上下文信息，本工具使用了[meteo open api](https://open-meteo.com/)
+注：该工具需要较高的对话技巧，不保证你问的任何问题均能得到满意的回复
+注2：当前版本可只使用这个工具，返回结果较可控。
+
+> meteo调优记录：https://github.com/zhayujie/chatgpt-on-wechat/issues/776#issuecomment-1500771334
+
+## 使用本插件对话（prompt）技巧
+### 1. 有指引的询问
+#### 例如：
+- 总结这个链接的内容 https://github.com/goldfishh/chatgpt-tool-hub
+- 使用Terminal执行curl cip.cc
+- 使用python查询今天日期
+
+### 2. 使用搜索引擎工具
+- 如果有搜索工具就能让chatgpt获取到你的未传达清楚的上下文信息，比如chatgpt不知道你的地理位置，现在时间等，所以无法查询到天气
+
+## 其他工具
+
+### 5. wikipedia
+###### 可以回答你想要知道确切的人事物
+
+### 6. news 新闻类工具集合
+
+> news更新：0.4版本对新闻类工具做了整合，配置文件只要加入`news`一个工具名就会自动加载所有新闻类工具
+
+#### 6.1. news-api *
+###### 从全球 80,000 多个信息源中获取当前和历史新闻文章
+
+#### 6.2. morning-news *
+###### 每日60秒早报，每天凌晨一点更新，本工具使用了[alapi-每日60秒早报](https://alapi.cn/api/view/93)
+
+> 该tool每天返回内容相同
+
+#### 6.3. finance-news
+###### 获取实时的金融财政新闻
+
+> 该工具需要用到browser工具解决反爬问题
+
+
+### 7. bing-search *
+###### bing搜索引擎，从此你不用再烦恼搜索要用哪些关键词
+
+### 8. wolfram-alpha *
+###### 知识搜索引擎、科学问答系统，常用于专业学科计算
+
+### 9. google-search *
+###### google搜索引擎，申请流程较bing-search繁琐
+
+### 10. arxiv
+###### 用于查找论文
+
+```text
+可配置参数：
+1. arxiv_summary: 是否使用总结工具，默认true, 当为false时会直接返回论文的标题、作者、发布时间、摘要、分类、备注、pdf链接等内容
+```
+
+> 0.4.2更新，例子：帮我找一篇吴恩达写的论文
+
+### 11. summary
+###### 总结工具，该工具可以支持输入url
+
+> 该工具目前是和其他工具配合使用，暂未测试单独使用效果
+
+### 12. visual
+###### 将图片转换成文字，底层调用ali dashscope `qwen-vl-plus`模型
+
+### 13. searxng-search *
+###### 一个私有化的搜索引擎工具
+
+> 安装教程：https://docs.searxng.org/admin/installation.html
+
+### 14. email *
+###### 发送邮件
+
+### 15. sms *
+###### 发送短信
+
+### 16. stt *
+###### speak to text 语音识别
+
+### 17. tts *
+###### text to speak 文生语音
+
+### 18. wechat *
+###### 向好友、群组发送微信
+
+---
+
+###### 注1：带*工具需要获取api-key才能使用(在config.json内的kwargs添加项)，部分工具需要外网支持  
+## [工具的api申请方法](https://github.com/goldfishh/chatgpt-tool-hub/blob/master/docs/apply_optional_tool.md)
+
+## config.json 配置说明
+###### 默认工具无需配置，其它工具需手动配置，以增加morning-news和bing-search两个工具为例：
+```json
+{
+  "tools": ["bing-search", "morning-news", "你想要添加的其他工具"],  // 填入你想用到的额外工具名，这里加入了工具"bing-search"和工具"morning-news"
+  "kwargs": {
+      "debug": true, // 当你遇到问题求助时，需要配置
+      "request_timeout": 120,  // openai接口超时时间
+      "no_default": false,  // 是否不使用默认的4个工具
+      "bing_subscription_key": "4871f273a4804743",//带*工具需要申请api-key，这里填入了工具bing-search对应的api，api_name参考前述`工具的api申请方法`
+      "morning_news_api_key": "5w1kjNh9VQlUc",// 这里填入了morning-news对应的api，
+  }
+}
+
+```
+注：config.json文件非必须，未创建仍可使用本tool；带*工具需在kwargs填入对应api-key键值对  
+- `tools`：本插件初始化时加载的工具, 上述一级标题即是对应工具名称，带*工具必须在kwargs中配置相应api-key
+- `kwargs`：工具执行时的配置，一般在这里存放**api-key**，或环境配置
+  - `debug`: 输出chatgpt-tool-hub额外信息用于调试
+  - `request_timeout`: 访问openai接口的超时时间，默认与wechat-on-chatgpt配置一致，可单独配置
+  - `no_default`: 用于配置默认加载4个工具的行为，如果为true则仅使用tools列表工具，不加载默认工具
+  - `model_name`: 用于控制tool插件底层使用的llm模型，目前暂未测试3.5以外的模型，一般保持默认
+
+---
+
+## 备注
+- 强烈建议申请搜索工具搭配使用，推荐bing-search
+- 虽然我会有意加入一些限制，但请不要使用本插件做危害他人的事情，请提前了解清楚某些内容是否会违反相关规定，建议提前做好过滤
+- 如有本插件问题，请将debug设置为true无上下文重新问一遍，如仍有问题请访问[chatgpt-tool-hub](https://github.com/goldfishh/chatgpt-tool-hub)建个issue，将日志贴进去，我无法处理不能复现的问题
+- 欢迎 star & 宣传，有能力请提pr
diff --git a/plugins/tool/config.json.template b/plugins/tool/config.json.template
new file mode 100644
index 0000000..aead657
--- /dev/null
+++ b/plugins/tool/config.json.template
@@ -0,0 +1,11 @@
+{
+  "tools": [
+    "url-get",
+    "meteo"
+  ],
+  "kwargs": {
+    "debug": false,
+    "no_default": false,
+    "model_name": "gpt-3.5-turbo"
+  }
+}
diff --git a/plugins/tool/tool.py b/plugins/tool/tool.py
new file mode 100644
index 0000000..eaacd5f
--- /dev/null
+++ b/plugins/tool/tool.py
@@ -0,0 +1,244 @@
+from chatgpt_tool_hub.apps import AppFactory
+from chatgpt_tool_hub.apps.app import App
+from chatgpt_tool_hub.tools.tool_register import main_tool_register
+
+import plugins
+from bridge.bridge import Bridge
+from bridge.context import ContextType
+from bridge.reply import Reply, ReplyType
+from common import const
+from config import conf, get_appdata_dir
+from plugins import *
+
+
+@plugins.register(
+    name="tool",
+    desc="Arming your ChatGPT bot with various tools",
+    version="0.5",
+    author="goldfishh",
+    desire_priority=0,
+)
+class Tool(Plugin):
+    def __init__(self):
+        super().__init__()
+        self.handlers[Event.ON_HANDLE_CONTEXT] = self.on_handle_context
+        self.app = self._reset_app()
+        if not self.tool_config.get("tools"):
+            logger.warn("[tool] init failed, ignore ")
+            raise Exception("config.json not found")
+        logger.info("[tool] inited")
+
+
+    def get_help_text(self, verbose=False, **kwargs):
+        help_text = "这是一个能让chatgpt联网，搜索，数字运算的插件，将赋予强大且丰富的扩展能力。"
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        if not verbose:
+            return help_text
+        help_text += "\n使用说明：\n"
+        help_text += f"{trigger_prefix}tool " + "命令: 根据给出的{命令}模型来选择使用哪些工具尽力为你得到结果。\n"
+        help_text += f"{trigger_prefix}tool 工具名 " + "命令: 根据给出的{命令}使用指定工具尽力为你得到结果。\n"
+        help_text += f"{trigger_prefix}tool reset: 重置工具。\n\n"
+
+        help_text += f"已加载工具列表: \n"
+        for idx, tool in enumerate(main_tool_register.get_registered_tool_names()):
+            if idx != 0:
+                help_text += ", "
+            help_text += f"{tool}"
+        return help_text
+
+    def on_handle_context(self, e_context: EventContext):
+        if e_context["context"].type != ContextType.TEXT:
+            return
+
+        # 暂时不支持未来扩展的bot
+        if Bridge().get_bot_type("chat") not in (
+            const.OPENAI,
+            const.CHATGPT,
+            const.OPEN_AI,
+            const.CHATGPTONAZURE,
+            const.LINKAI,
+        ):
+            return
+
+        content = e_context["context"].content
+        content_list = e_context["context"].content.split(maxsplit=1)
+
+        if not content or len(content_list) < 1:
+            e_context.action = EventAction.CONTINUE
+            return
+
+        logger.debug("[tool] on_handle_context. content: %s" % content)
+        reply = Reply()
+        reply.type = ReplyType.TEXT
+        trigger_prefix = conf().get("plugin_trigger_prefix", "$")
+        # todo: 有些工具必须要api-key，需要修改config文件，所以这里没有实现query增删tool的功能
+        if content.startswith(f"{trigger_prefix}tool"):
+            if len(content_list) == 1:
+                logger.debug("[tool]: get help")
+                reply.content = self.get_help_text()
+                e_context["reply"] = reply
+                e_context.action = EventAction.BREAK_PASS
+                return
+            elif len(content_list) > 1:
+                if content_list[1].strip() == "reset":
+                    logger.debug("[tool]: reset config")
+                    self.app = self._reset_app()
+                    reply.content = "重置工具成功"
+                    e_context["reply"] = reply
+                    e_context.action = EventAction.BREAK_PASS
+                    return
+                elif content_list[1].startswith("reset"):
+                    logger.debug("[tool]: remind")
+                    e_context["context"].content = "请你随机用一种聊天风格，提醒用户：如果想重置tool插件，reset之后不要加任何字符"
+
+                    e_context.action = EventAction.BREAK
+                    return
+                query = content_list[1].strip()
+                
+                use_one_tool = False
+                for tool_name in main_tool_register.get_registered_tool_names():
+                    if query.startswith(tool_name):
+                        use_one_tool = True
+                        query = query[len(tool_name):]
+                        break
+
+                # Don't modify bot name
+                all_sessions = Bridge().get_bot("chat").sessions
+                user_session = all_sessions.session_query(query, e_context["context"]["session_id"]).messages
+
+                logger.debug("[tool]: just-go")
+                try:
+                    if use_one_tool:
+                        _func, _ = main_tool_register.get_registered_tool()[tool_name]
+                        tool = _func(**self.app_kwargs)
+                        _reply = tool.run(query)
+                    else:
+                        # chatgpt-tool-hub will reply you with many tools
+                        _reply = self.app.ask(query, user_session)
+                    e_context.action = EventAction.BREAK_PASS
+                    all_sessions.session_reply(_reply, e_context["context"]["session_id"])
+                except Exception as e:
+                    logger.exception(e)
+                    logger.error(str(e))
+
+                    e_context["context"].content = "请你随机用一种聊天风格，提醒用户：这个问题tool插件暂时无法处理"
+                    reply.type = ReplyType.ERROR
+                    e_context.action = EventAction.BREAK
+                    return
+
+                reply.content = _reply
+                e_context["reply"] = reply
+        return
+
+    def _read_json(self) -> dict:
+        default_config = {"tools": [], "kwargs": {}}
+        return super().load_config() or default_config
+
+    def _build_tool_kwargs(self, kwargs: dict):
+        tool_model_name = kwargs.get("model_name")
+        request_timeout = kwargs.get("request_timeout")
+
+        return {
+            # 全局配置相关
+            "log": False,  # tool 日志开关
+            "debug": kwargs.get("debug", False),  # 输出更多日志
+            "no_default": kwargs.get("no_default", False),  # 不要默认的工具，只加载自己导入的工具
+            "think_depth": kwargs.get("think_depth", 2),  # 一个问题最多使用多少次工具
+            "proxy": conf().get("proxy", ""),  # 科学上网
+            "request_timeout": request_timeout if request_timeout else conf().get("request_timeout", 120),
+            "temperature": kwargs.get("temperature", 0),  # llm 温度，建议设置0
+            # LLM配置相关
+            "llm_api_key": conf().get("open_ai_api_key", ""),  # 如果llm api用key鉴权，传入这里
+            "llm_api_base_url": conf().get("open_ai_api_base", "https://api.openai.com/v1"),  # 支持openai接口的llm服务地址前缀
+            "deployment_id": conf().get("azure_deployment_id", ""),  # azure openai会用到
+            # note: 目前tool暂未对其他模型测试，但这里仍对配置来源做了优先级区分，一般插件配置可覆盖全局配置
+            "model_name": tool_model_name if tool_model_name else conf().get("model", const.GPT35),
+            # 工具配置相关
+            # for arxiv tool
+            "arxiv_simple": kwargs.get("arxiv_simple", True),  # 返回内容更精简
+            "arxiv_top_k_results": kwargs.get("arxiv_top_k_results", 2),  # 只返回前k个搜索结果
+            "arxiv_sort_by": kwargs.get("arxiv_sort_by", "relevance"),  # 搜索排序方式 ["relevance","lastUpdatedDate","submittedDate"]
+            "arxiv_sort_order": kwargs.get("arxiv_sort_order", "descending"),  # 搜索排序方式 ["ascending", "descending"]
+            "arxiv_output_type": kwargs.get("arxiv_output_type", "text"),  # 搜索结果类型 ["text", "pdf", "all"]
+            # for bing-search tool
+            "bing_subscription_key": kwargs.get("bing_subscription_key", ""),
+            "bing_search_url": kwargs.get("bing_search_url", "https://api.bing.microsoft.com/v7.0/search"),  # 必应搜索的endpoint地址，无需修改
+            "bing_search_top_k_results": kwargs.get("bing_search_top_k_results", 2),  # 只返回前k个搜索结果
+            "bing_search_simple": kwargs.get("bing_search_simple", True),  # 返回内容更精简
+            "bing_search_output_type": kwargs.get("bing_search_output_type", "text"),  # 搜索结果类型 ["text", "json"]
+            # for email tool
+            "email_nickname_mapping": kwargs.get("email_nickname_mapping", "{}"),  # 关于人的代号对应的邮箱地址，可以不输入邮箱地址发送邮件。键为代号值为邮箱地址
+            "email_smtp_host": kwargs.get("email_smtp_host", ""),  # 例如 'smtp.qq.com'
+            "email_smtp_port": kwargs.get("email_smtp_port", ""),  # 例如 587
+            "email_sender": kwargs.get("email_sender", ""),  # 发送者的邮件地址
+            "email_authorization_code": kwargs.get("email_authorization_code", ""),  # 发送者验证秘钥（可能不是登录密码）
+            # for google-search tool
+            "google_api_key": kwargs.get("google_api_key", ""),
+            "google_cse_id": kwargs.get("google_cse_id", ""),
+            "google_simple": kwargs.get("google_simple", True),   # 返回内容更精简
+            "google_output_type": kwargs.get("google_output_type", "text"),  # 搜索结果类型 ["text", "json"]
+            # for finance-news tool
+            "finance_news_filter": kwargs.get("finance_news_filter", False),  # 是否开启过滤
+            "finance_news_filter_list": kwargs.get("finance_news_filter_list", []),  # 过滤词列表
+            "finance_news_simple": kwargs.get("finance_news_simple", True),   # 返回内容更精简
+            "finance_news_repeat_news": kwargs.get("finance_news_repeat_news", False),  # 是否过滤不返回。该tool每次返回约50条新闻，可能有重复新闻
+            # for morning-news tool
+            "morning_news_api_key": kwargs.get("morning_news_api_key", ""),   # api-key
+            "morning_news_simple": kwargs.get("morning_news_simple", True),   # 返回内容更精简
+            "morning_news_output_type": kwargs.get("morning_news_output_type", "text"),  # 搜索结果类型 ["text", "image"]
+            # for news-api tool
+            "news_api_key": kwargs.get("news_api_key", ""),
+            # for searxng-search tool
+            "searxng_search_host": kwargs.get("searxng_search_host", ""),
+            "searxng_search_top_k_results": kwargs.get("searxng_search_top_k_results", 2),  # 只返回前k个搜索结果
+            "searxng_search_output_type": kwargs.get("searxng_search_output_type", "text"),  # 搜索结果类型 ["text", "json"]
+            # for sms tool
+            "sms_nickname_mapping": kwargs.get("sms_nickname_mapping", "{}"),  # 关于人的代号对应的手机号，可以不输入手机号发送sms。键为代号值为手机号
+            "sms_username": kwargs.get("sms_username", ""),  # smsbao用户名
+            "sms_apikey": kwargs.get("sms_apikey", ""),  # smsbao
+            # for stt tool
+            "stt_api_key": kwargs.get("stt_api_key", ""),  # azure
+            "stt_api_region": kwargs.get("stt_api_region", ""),  # azure
+            "stt_recognition_language": kwargs.get("stt_recognition_language", "zh-CN"),  # 识别的语言类型 部分：en-US ja-JP ko-KR yue-CN zh-CN
+            # for tts tool
+            "tts_api_key": kwargs.get("tts_api_key", ""),  # azure
+            "tts_api_region": kwargs.get("tts_api_region", ""),  # azure
+            "tts_auto_detect": kwargs.get("tts_auto_detect", True),  # 是否自动检测语音的语言
+            "tts_speech_id": kwargs.get("tts_speech_id", "zh-CN-XiaozhenNeural"),  # 输出语音ID
+            # for summary tool
+            "summary_max_segment_length": kwargs.get("summary_max_segment_length", 2500),  # 每2500tokens分段，多段触发总结tool
+            # for terminal tool
+            "terminal_nsfc_filter": kwargs.get("terminal_nsfc_filter", True),  # 是否过滤llm输出的危险命令
+            "terminal_return_err_output": kwargs.get("terminal_return_err_output", True),  # 是否输出错误信息
+            "terminal_timeout": kwargs.get("terminal_timeout", 20),  # 允许命令最长执行时间
+            # for visual tool
+            "caption_api_key": kwargs.get("caption_api_key", ""),  # ali dashscope apikey
+            # for browser tool
+            "browser_use_summary": kwargs.get("browser_use_summary", True),  # 是否对返回结果使用tool功能
+            # for url-get tool
+            "url_get_use_summary": kwargs.get("url_get_use_summary", True),  # 是否对返回结果使用tool功能
+            # for wikipedia tool
+            "wikipedia_top_k_results": kwargs.get("wikipedia_top_k_results", 2),  # 只返回前k个搜索结果
+            # for wolfram-alpha tool
+            "wolfram_alpha_appid": kwargs.get("wolfram_alpha_appid", ""),
+        }
+
+    def _filter_tool_list(self, tool_list: list):
+        valid_list = []
+        for tool in tool_list:
+            if tool in main_tool_register.get_registered_tool_names():
+                valid_list.append(tool)
+            else:
+                logger.warning("[tool] filter invalid tool: " + repr(tool))
+        return valid_list
+
+    def _reset_app(self) -> App:
+        self.tool_config = self._read_json()
+        self.app_kwargs = self._build_tool_kwargs(self.tool_config.get("kwargs", {}))
+
+        app = AppFactory()
+        app.init_env(**self.app_kwargs)
+        # filter not support tool
+        tool_list = self._filter_tool_list(self.tool_config.get("tools", []))
+
+        return app.create_app(tools_list=tool_list, **self.app_kwargs)
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..7a0f4c0
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,19 @@
+[build-system]
+requires = ["setuptools>=45.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "cowagent"
+version = "1.0.0"
+description = "CowAgent - AI Agent on WeChat and more"
+requires-python = ">=3.7"
+dependencies = [
+    "click>=8.0",
+    "requests>=2.28.2",
+]
+
+[project.scripts]
+cow = "cli.cli:main"
+
+[tool.setuptools.packages.find]
+include = ["cli*"]
diff --git a/requirements-optional.txt b/requirements-optional.txt
new file mode 100644
index 0000000..bc1b801
--- /dev/null
+++ b/requirements-optional.txt
@@ -0,0 +1,26 @@
+tiktoken>=0.3.2 # openai calculate token
+
+#voice
+pydub>=0.25.1 # need ffmpeg
+gTTS>=2.3.1 # google text to speech
+# edge-tts: install on demand, see voice/edge/edge_voice.py
+# elevenlabs: install on demand, see voice/elevent/elevent_voice.py
+
+#install plugin
+dulwich
+
+# xunfei spark
+websocket-client==1.2.0
+
+# google
+google-generativeai
+
+# file parsing (web_fetch document support)
+pypdf
+python-docx
+openpyxl
+python-pptx
+
+# i18n: Traditional Chinese (zh-Hant) high-quality conversion
+# Built-in fallback provides basic conversion without this dependency
+opencc-python-reimplemented
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..e059cd2
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,38 @@
+numpy>=1.21
+aiohttp>=3.8.6,<3.10
+requests>=2.28.2
+chardet>=5.1.0
+Pillow
+python-dotenv>=1.0.0
+PyYAML>=6.0
+croniter>=2.0.0
+click>=8.0
+qrcode
+json-repair
+
+# wechatcom & wechatmp
+wechatpy
+
+# zhipuai
+zai-sdk
+# tongyi qwen sdk
+dashscope
+
+# feishu
+lark-oapi>=1.5.5
+# dingtalk
+dingtalk_stream
+# wecom bot websocket mode
+websocket-client>=1.4.0
+pycryptodome
+# telegram bot
+python-telegram-bot
+# slack bot
+slack_bolt
+# discord bot
+discord.py
+
+# web.py: PyPI 0.62 fails to build on Python 3.13+ (cgi module removed), use GitHub fix instead
+web.py; python_version < "3.13"
+web.py @ git+https://github.com/webpy/webpy.git ; python_version >= "3.13"
+legacy-cgi; python_version >= "3.13"
diff --git a/run.sh b/run.sh
new file mode 100755
index 0000000..0816701
--- /dev/null
+++ b/run.sh
@@ -0,0 +1,1362 @@
+#!/bin/bash
+set -e
+
+# ============================
+# CowAgent Management Script
+# ============================
+
+# ANSI colors
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[0;33m'
+CYAN='\033[0;36m'
+BOLD='\033[1m'
+NC='\033[0m'
+
+# Emojis
+EMOJI_ROCKET="🚀"
+EMOJI_COW="🐄"
+EMOJI_CHECK="✅"
+EMOJI_CROSS="❌"
+EMOJI_WARN="⚠️"
+EMOJI_STOP="🛑"
+EMOJI_WRENCH="🔧"
+
+# Check if using Bash
+if [ -z "$BASH_VERSION" ]; then
+    echo -e "${RED}❌ Please run this script with Bash.${NC}"
+    exit 1
+fi
+
+# ============================
+# i18n: install-flow language
+# ============================
+# UI_LANG controls the language of install prompts/menus. Detected on first run
+# (or chosen by the user), defaults to auto-detection. "zh" or "en".
+UI_LANG=""
+
+# A terminal we can read from. When the script runs via `curl | bash`, stdin is
+# the script pipe (EOF on read), so interactive prompts must read from the tty.
+TTY_DEV="/dev/tty"
+HAS_TTY=false
+if [ -r /dev/tty ] && [ -w /dev/tty ]; then
+    HAS_TTY=true
+fi
+
+# Detect default UI language from environment (best-effort, mirrors common/i18n).
+detect_ui_lang() {
+    local loc=""
+    # macOS: prefer AppleLocale, which reflects the real UI language
+    if [ "$(uname)" = "Darwin" ] && command -v defaults &> /dev/null; then
+        loc=$(defaults read -g AppleLocale 2>/dev/null || true)
+    fi
+    [ -z "$loc" ] && loc="${LC_ALL:-${LC_MESSAGES:-${LANG:-}}}"
+    case "$loc" in
+        zh* | *zh_* | *_CN* | *_TW* | *_HK* | *Hans* | *Hant*) echo "zh" ;;
+        *) echo "en" ;;
+    esac
+}
+
+# Translation helper: t <zh_text> <en_text>
+t() {
+    if [ "$UI_LANG" = "en" ]; then
+        printf '%s' "$2"
+    else
+        printf '%s' "$1"
+    fi
+}
+
+# Read a line from the controlling terminal (works under `curl | bash`).
+# Usage: tty_read VAR "prompt"
+tty_read() {
+    local __var=$1 __prompt=$2 __input=""
+    if [ "$HAS_TTY" = true ]; then
+        # Ensure the tty is in normal line mode. A preceding arrow-key menu
+        # may have left it in cbreak/-echo mode; without this, `read` could
+        # return immediately or not echo typed characters.
+        stty sane < "$TTY_DEV" 2>/dev/null || true
+        # Print the prompt explicitly (not via read -p, whose prompt can be
+        # swallowed right after an arrow-key menu) and read from the tty.
+        # `|| true` so a non-zero read (EOF) does NOT trip `set -e`.
+        printf '%s' "$__prompt" > /dev/tty
+        read -r __input < "$TTY_DEV" || true
+    else
+        read -r -p "$__prompt" __input || true
+    fi
+    printf -v "$__var" '%s' "$__input"
+}
+
+# Arrow-key selectable menu with number fallback.
+# Usage: select_menu OUT_VAR "Title" "opt1" "opt2" ...
+# Result: OUT_VAR is set to the selected index (1-based).
+select_menu() {
+    # Interactive function: never let a non-zero command (read EOF, arithmetic
+    # evaluating to 0, etc.) abort the caller under `set -e`.
+    set +e
+    local __out=$1; shift
+    local title=$1; shift
+    local options=("$@")
+    local count=${#options[@]}
+    # Initial highlight: MENU_DEFAULT (1-based) if set, else first option.
+    local cur=0
+    if [[ "${MENU_DEFAULT:-}" =~ ^[0-9]+$ ]] && (( MENU_DEFAULT >= 1 && MENU_DEFAULT <= count )); then
+        cur=$((MENU_DEFAULT - 1))
+    fi
+    MENU_DEFAULT=""
+
+    # Fallback to numbered input when no interactive terminal is available
+    # (e.g. CI, non-tty pipe). Arrow-key rendering needs a real tty.
+    if [ "$HAS_TTY" != true ] || [ ! -t 1 ]; then
+        local def=$((cur + 1))
+        echo -e "${CYAN}${BOLD}${title}${NC}"
+        local i=1
+        for opt in "${options[@]}"; do
+            echo -e "  ${YELLOW}${i})${NC} ${opt}"
+            i=$((i + 1))
+        done
+        local choice=""
+        while true; do
+            tty_read choice "$(t "请输入序号" "Enter number") [1-${count}, $(t "默认" "default") ${def}]: "
+            choice=${choice:-$def}
+            if [[ "$choice" =~ ^[0-9]+$ ]] && (( choice >= 1 && choice <= count )); then
+                break
+            fi
+            echo -e "${RED}$(t "无效选择，请输入" "Invalid choice, enter") 1-${count}${NC}"
+        done
+        printf -v "$__out" '%s' "$choice"
+        return
+    fi
+
+    # Interactive arrow-key menu.
+    # Use literal escape characters (via $'...') and printf instead of
+    # `echo -e`, because `echo`'s backslash handling is not portable and
+    # leaks raw "\e[K" text on some shells/terminals.
+    local ESC=$'\033'
+    local UP="${ESC}[A"          # move cursor up one line
+    local CLR="${ESC}[K"         # clear to end of line
+
+    # fd 3 is a long-lived (read) handle to the controlling terminal, opened
+    # once by menu_session_begin() before the install flow. Reusing one fd
+    # across all menus avoids the bash 3.2 bug where re-opening /dev/tty per
+    # menu makes the second menu read EOF and auto-select the default.
+    # Detect whether fd 3 is already open using a READ redirection (fd 3 is
+    # read-only; testing with `>&3` would wrongly report it as closed).
+    local _own_fd3=false
+    if ! { : <&3; } 2>/dev/null; then
+        exec 3<"$TTY_DEV"
+        _own_fd3=true
+    fi
+
+    # Put the terminal into cbreak/raw input mode so single keystrokes arrive
+    # immediately and are not echoed.
+    #   -echo    : don't echo keystrokes (otherwise arrow keys leak as ^[[A)
+    #   -icanon  : disable line buffering
+    #   min 1 time 0 : read returns as soon as 1 byte is available
+    local _restore="tput cnorm 2>/dev/null; stty echo icanon <${TTY_DEV} 2>/dev/null"
+    trap "$_restore" EXIT INT TERM
+    tput civis 2>/dev/null || true
+    stty -echo -icanon min 1 time 0 <&3 2>/dev/null || true
+
+    printf '%b\n' "${CYAN}${BOLD}${title}${NC}"
+    printf '%b\n' "${CYAN}$(t "↑/↓ 选择，Enter 确认" "Use ↑/↓ to move, Enter to select")${NC}"
+
+    local first_draw=true
+    while true; do
+        # Move cursor up to the top of the option block to redraw it.
+        if [ "$first_draw" = false ]; then
+            local i=0
+            while [ $i -lt $count ]; do
+                printf '%s' "$UP"
+                i=$((i + 1))
+            done
+        fi
+        first_draw=false
+
+        local idx=0
+        for opt in "${options[@]}"; do
+            if [ $idx -eq $cur ]; then
+                printf '%s%b\n' "$CLR" "  ${GREEN}${BOLD}❯ ${opt}${NC}"
+            else
+                printf '%s%b\n' "$CLR" "    ${opt}"
+            fi
+            idx=$((idx + 1))
+        done
+
+        # Read one key from the shared terminal fd 3.
+        local key=""
+        IFS= read -rsn1 key <&3
+        local rc=$?
+        if [ $rc -ne 0 ]; then
+            # No usable terminal: restore and fall back to numbered input.
+            eval "$_restore"; trap - EXIT INT TERM
+            [ "${_own_fd3:-}" = true ] && exec 3<&- 2>/dev/null
+            local choice=""
+            while true; do
+                tty_read choice "$(t "请输入序号" "Enter number") [1-${count}]: "
+                choice=${choice:-$((cur + 1))}
+                if [[ "$choice" =~ ^[0-9]+$ ]] && (( choice >= 1 && choice <= count )); then
+                    break
+                fi
+            done
+            printf -v "$__out" '%s' "$choice"
+            return
+        fi
+
+        # Empty key means Enter/Return (read -n1 strips the newline delimiter).
+        if [ -z "$key" ]; then
+            break
+        fi
+
+        case "$key" in
+            "$ESC")
+                # Arrow key: ESC [ A/B (or ESC O A/B). Read the two trailing
+                # bytes one at a time, no timeout (bash 3.2 has no fractional
+                # read -t; in cbreak mode the bytes are already buffered).
+                local b2="" b3=""
+                IFS= read -rsn1 b2 <&3 2>/dev/null || b2=""
+                IFS= read -rsn1 b3 <&3 2>/dev/null || b3=""
+                case "${b2}${b3}" in
+                    "[A" | "OA") cur=$(( (cur - 1 + count) % count )) ;;  # up
+                    "[B" | "OB") cur=$(( (cur + 1) % count )) ;;          # down
+                esac
+                ;;
+            $'\n' | $'\r')
+                break
+                ;;
+            [0-9])
+                if (( key >= 1 && key <= count )); then
+                    cur=$((key - 1))
+                    break
+                fi
+                ;;
+            $'\003')
+                # Ctrl-C: restore and abort.
+                eval "$_restore"; trap - EXIT INT TERM
+                [ "${_own_fd3:-}" = true ] && exec 3<&- 2>/dev/null
+                printf '\n%b\n' "${RED}$(t "已取消安装" "Installation cancelled")${NC}"
+                exit 130
+                ;;
+        esac
+    done
+
+    eval "$_restore"
+    trap - EXIT INT TERM
+    [ "${_own_fd3:-}" = true ] && exec 3<&- 2>/dev/null
+    printf -v "$__out" '%s' "$((cur + 1))"
+}
+
+# Open/close a long-lived terminal handle (fd 3) shared by all menus in an
+# install/config session. Opening fd 3 once avoids per-menu re-open issues on
+# bash 3.2 (second menu reading EOF). Safe no-ops when there is no tty.
+menu_session_begin() {
+    [ "$HAS_TTY" = true ] || return 0
+    exec 3<"$TTY_DEV" 2>/dev/null || true
+}
+menu_session_end() {
+    exec 3<&- 2>/dev/null || true
+}
+
+# Ask the user to choose the install/UI language (first step of install).
+select_language() {
+    # Order is fixed (English first, Chinese second). The default highlight
+    # follows detection, but conservatively: only a confident "zh" signal
+    # (macOS AppleLocale / Linux zh_* locale) preselects Chinese; everything
+    # else (English, empty/C/POSIX locale, server images) defaults to English.
+    local detected
+    detected=$(detect_ui_lang)
+    if [ "$detected" = "zh" ]; then
+        MENU_DEFAULT=2
+        UI_LANG="zh"
+    else
+        MENU_DEFAULT=1
+        UI_LANG="en"
+    fi
+
+    local lang_choice
+    select_menu lang_choice "Select Language / 选择语言" "English" "中文 (Chinese)"
+    case "$lang_choice" in
+        1) UI_LANG="en" ;;
+        2) UI_LANG="zh" ;;
+        *) UI_LANG="en" ;;
+    esac
+    # Remember for the rest of the flow (config write happens later)
+    INSTALL_LANG="$UI_LANG"
+}
+
+# Cross-platform timeout: prefer GNU timeout/gtimeout, fallback to a pure-bash implementation
+# that uses background process + sleep to enforce a hard time limit.
+if command -v timeout &> /dev/null; then
+    _timeout() { timeout "$@"; }
+elif command -v gtimeout &> /dev/null; then
+    _timeout() { gtimeout "$@"; }
+else
+    _timeout() {
+        local secs=$1; shift
+        "$@" &
+        local cmd_pid=$!
+        ( sleep "$secs"; kill $cmd_pid 2>/dev/null ) &
+        local watcher_pid=$!
+        wait $cmd_pid 2>/dev/null
+        local exit_code=$?
+        kill $watcher_pid 2>/dev/null
+        wait $watcher_pid 2>/dev/null
+        return $exit_code
+    }
+fi
+
+# Get current script directory.
+# When launched via process substitution (`bash <(curl ...)`) or a pipe,
+# $0 points at /dev/fd/* or "bash", so dirname is meaningless. Fall back to
+# the current working directory in that case (remote install will cd into
+# the cloned project dir and reset BASE_DIR afterwards).
+_script_src="$0"
+case "$_script_src" in
+    /dev/fd/* | /proc/self/fd/* | bash | sh | -* | "")
+        export BASE_DIR="$(pwd)"
+        ;;
+    *)
+        export BASE_DIR=$(cd "$(dirname "$_script_src")" 2>/dev/null && pwd || pwd)
+        ;;
+esac
+
+# Detect if in project directory
+IS_PROJECT_DIR=false
+if [ -f "${BASE_DIR}/config-template.json" ] && [ -f "${BASE_DIR}/app.py" ]; then
+    IS_PROJECT_DIR=true
+fi
+
+# Check and install tool
+check_and_install_tool() {
+    local tool_name=$1
+    if ! command -v "$tool_name" &> /dev/null; then
+        echo -e "${YELLOW}⚙️  $tool_name not found, installing...${NC}"
+        if command -v yum &> /dev/null; then
+            sudo yum install "$tool_name" -y
+        elif command -v apt-get &> /dev/null; then
+            sudo apt-get update && sudo apt-get install "$tool_name" -y
+        elif command -v brew &> /dev/null; then
+            brew install "$tool_name"
+        else
+            echo -e "${RED}❌ Unsupported package manager. Please install $tool_name manually.${NC}"
+            return 1
+        fi
+
+        if ! command -v "$tool_name" &> /dev/null; then
+            echo -e "${RED}❌ Failed to install $tool_name.${NC}"
+            return 1
+        else
+            echo -e "${GREEN}✅ $tool_name installed successfully.${NC}"
+            return 0
+        fi
+    else
+        echo -e "${GREEN}✅ $tool_name is already installed.${NC}"
+        return 0
+    fi
+}
+
+# Detect and set Python command
+detect_python_command() {
+    FOUND_NEWER_VERSION=""
+    
+    # Try to find Python command in order of preference
+    for cmd in python3 python python3.12 python3.11 python3.10 python3.9 python3.8 python3.7 python3.13; do
+        if command -v $cmd &> /dev/null; then
+            # Check Python version
+            major_version=$($cmd -c 'import sys; print(sys.version_info[0])' 2>/dev/null)
+            minor_version=$($cmd -c 'import sys; print(sys.version_info[1])' 2>/dev/null)
+            
+            if [[ "$major_version" == "3" ]]; then
+                # Supported range is 3.7+. On 3.13+ web.py is installed from a
+                # pinned GitHub commit (see requirements.txt), which needs git.
+                if (( minor_version >= 7 )); then
+                    PYTHON_CMD=$cmd
+                    PYTHON_VERSION="${major_version}.${minor_version}"
+                    break
+                fi
+            fi
+        fi
+    done
+    
+    if [ -z "$PYTHON_CMD" ]; then
+        echo -e "${YELLOW}Tried: python3, python, python3.12, python3.11, python3.10, python3.9, python3.8, python3.7, python3.13${NC}"
+        echo -e "${RED}❌ No suitable Python found. Please install Python 3.7 or newer${NC}"
+        exit 1
+    fi
+
+    # On 3.13+, web.py is pulled from GitHub via pip, which requires git.
+    if [[ "$major_version" == "3" ]] && (( minor_version >= 13 )); then
+        if ! command -v git &> /dev/null; then
+            echo -e "${YELLOW}⚠️  Python $PYTHON_VERSION detected. Installing web.py from GitHub requires git, which was not found.${NC}"
+            echo -e "${YELLOW}    Please install git, or use Python 3.12 where web.py installs directly from PyPI.${NC}"
+        fi
+    fi
+    
+    # Export for global use
+    export PYTHON_CMD
+    export PYTHON_VERSION
+    
+    echo -e "${GREEN}✅ Found Python: $PYTHON_CMD (version $PYTHON_VERSION)${NC}"
+}
+
+# Check Python version (>= 3.7)
+check_python_version() {
+    detect_python_command
+    
+    # Verify pip is available
+    if ! $PYTHON_CMD -m pip --version &> /dev/null; then
+        echo -e "${RED}❌ pip not found for $PYTHON_CMD. Please install pip.${NC}"
+        exit 1
+    fi
+    
+    echo -e "${GREEN}✅ pip is available for $PYTHON_CMD${NC}"
+}
+
+# Clone project
+clone_project() {
+    echo -e "${GREEN}🔍 Cloning CowAgent project...${NC}"
+
+    if [ -d "CowAgent" ]; then
+        # An existing directory is automatically backed up (no prompt) so the
+        # installer stays one-shot / hands-off.
+        local backup_dir="CowAgent_backup_$(date +%s)"
+        echo -e "${YELLOW}⚠️  $(t "目录 'CowAgent' 已存在，自动备份到" "Directory 'CowAgent' exists, backing up to") '$backup_dir'...${NC}"
+        mv CowAgent "$backup_dir"
+    fi
+
+    check_and_install_tool git
+
+    if ! command -v git &> /dev/null; then
+        echo -e "${YELLOW}⚠️  Git not available. Trying wget/curl...${NC}"
+        local zip_url="https://gitee.com/zhayujie/CowAgent/repository/archive/master.zip"
+        if command -v wget &> /dev/null; then
+            wget "$zip_url" -O CowAgent.zip
+        elif command -v curl &> /dev/null; then
+            curl -L "$zip_url" -o CowAgent.zip
+        else
+            echo -e "${RED}❌ Cannot download project. Please install Git, wget, or curl.${NC}"
+            exit 1
+        fi
+        # Unzip: prefer `unzip`, otherwise fall back to Python's zipfile (no
+        # extra dependency) so minimal environments without unzip still work.
+        if command -v unzip &> /dev/null; then
+            unzip CowAgent.zip
+        elif command -v python3 &> /dev/null; then
+            python3 -m zipfile -e CowAgent.zip .
+        elif command -v python &> /dev/null; then
+            python -m zipfile -e CowAgent.zip .
+        else
+            echo -e "${RED}❌ Cannot extract archive. Please install 'unzip' or Python.${NC}"
+            exit 1
+        fi
+        # Archive top-level dir name may vary (CowAgent-master, etc.); detect it.
+        local _extracted="CowAgent-master"
+        if [ ! -d "$_extracted" ]; then
+            _extracted=$(ls -d CowAgent-*/ 2>/dev/null | head -1 | sed 's:/*$::')
+        fi
+        [ -n "$_extracted" ] && [ -d "$_extracted" ] && mv "$_extracted" CowAgent
+        rm -f CowAgent.zip
+    else
+        local clone_ok=false
+        # Detect and temporarily disable invalid git proxy settings
+        local _git_proxy_unset=false
+        local _http_proxy=$(git config --global http.proxy 2>/dev/null)
+        local _https_proxy=$(git config --global https.proxy 2>/dev/null)
+        if [ -n "$_http_proxy" ] && ! curl -s --connect-timeout 3 --max-time 5 --proxy "$_http_proxy" https://github.com > /dev/null 2>&1; then
+            echo -e "${YELLOW}⚠️  Invalid git proxy detected: $_http_proxy, temporarily disabling...${NC}"
+            git config --global --unset http.proxy
+            [ -n "$_https_proxy" ] && git config --global --unset https.proxy
+            _git_proxy_unset=true
+        fi
+        # Test GitHub connectivity before attempting clone
+        if curl -sI --connect-timeout 5 --max-time 10 https://github.com > /dev/null 2>&1; then
+            echo -e "${YELLOW}🌐 GitHub is reachable, cloning from GitHub...${NC}"
+            _timeout 60 git clone --depth 10 --progress https://github.com/zhayujie/CowAgent.git && clone_ok=true
+        fi
+        if [ "$clone_ok" = false ]; then
+            echo -e "${YELLOW}⚠️  GitHub clone failed or timed out, switching to Gitee mirror...${NC}"
+            _timeout 30 git clone --depth 10 --progress https://gitee.com/zhayujie/CowAgent.git && clone_ok=true
+        fi
+        if [ "$clone_ok" = false ]; then
+            echo -e "${RED}❌ Project clone failed. Please check network connection.${NC}"
+            if git config --global http.proxy &> /dev/null || git config --global https.proxy &> /dev/null || [ -n "$http_proxy" ] || [ -n "$https_proxy" ] || [ -n "$HTTP_PROXY" ] || [ -n "$HTTPS_PROXY" ]; then
+                echo -e "${YELLOW}💡 Detected proxy settings. If proxy is misconfigured, try removing it with:${NC}"
+                echo -e "${YELLOW}   git config --global --unset http.proxy${NC}"
+                echo -e "${YELLOW}   git config --global --unset https.proxy${NC}"
+                echo -e "${YELLOW}   unset http_proxy https_proxy HTTP_PROXY HTTPS_PROXY${NC}"
+            fi
+            exit 1
+        fi
+    fi
+
+    cd CowAgent || { echo -e "${RED}❌ Failed to enter project directory.${NC}"; exit 1; }
+    export BASE_DIR=$(pwd)
+    echo -e "${GREEN}✅ Project cloned successfully: $BASE_DIR${NC}"
+    
+    # Add execute permission to management script
+    if [ -f "${BASE_DIR}/run.sh" ]; then
+        chmod +x "${BASE_DIR}/run.sh" 2>/dev/null || true
+        echo -e "${GREEN}✅ Execute permission added to run.sh${NC}"
+    fi
+    
+    sleep 1
+}
+
+# Install dependencies
+install_dependencies() {
+    echo -e "${GREEN}📦 Installing dependencies...${NC}"
+    # Pick the pip index by install language, then fall back to the other if the
+    # preferred one is unreachable:
+    #   - zh users: Tsinghua mirror first (fast in China), official PyPI fallback
+    #   - others : official PyPI first, Tsinghua mirror fallback
+    local PIP_MIRROR=""
+    local _tuna="https://pypi.tuna.tsinghua.edu.cn/simple"
+    local _pypi="https://pypi.org/simple"
+    if [ "$UI_LANG" = "zh" ]; then
+        # Prefer Tsinghua; if it's down, fall back to official PyPI (pip default).
+        if curl -s --connect-timeout 5 "${_tuna}/" > /dev/null 2>&1; then
+            PIP_MIRROR="-i $_tuna"
+        fi
+    else
+        # Prefer official PyPI; only use Tsinghua if PyPI is unreachable.
+        if ! curl -s --connect-timeout 5 "${_pypi}/" > /dev/null 2>&1 \
+           && curl -s --connect-timeout 5 "${_tuna}/" > /dev/null 2>&1; then
+            PIP_MIRROR="-i $_tuna"
+        fi
+    fi
+    if [ -n "$PIP_MIRROR" ]; then
+        echo -e "${YELLOW}Using pip mirror: ${_tuna}${NC}"
+    fi
+
+    # Only pass --break-system-packages if this pip actually supports it
+    # (pip >= 23.x). Older pip versions error out with "no such option",
+    # which previously dumped a confusing usage message and failed the install.
+    PIP_EXTRA_ARGS=""
+    if $PYTHON_CMD -c "import sys; exit(0 if sys.version_info >= (3, 11) else 1)" 2>/dev/null \
+       && $PYTHON_CMD -m pip install --help 2>/dev/null | grep -q -- "--break-system-packages"; then
+        PIP_EXTRA_ARGS="--break-system-packages"
+        echo -e "${YELLOW}Python 3.11+ with break-system-packages support detected${NC}"
+    fi
+
+    echo -e "${YELLOW}Upgrading pip and basic tools...${NC}"
+    set +e
+    $PYTHON_CMD -m pip install --upgrade pip setuptools wheel importlib_metadata --ignore-installed $PIP_EXTRA_ARGS $PIP_MIRROR > /tmp/pip_upgrade.log 2>&1
+    [ $? -ne 0 ] && echo -e "${YELLOW}⚠️  Some tools failed to upgrade, but continuing...${NC}"
+    set -e
+    rm -f /tmp/pip_upgrade.log
+
+    echo -e "${YELLOW}Installing project dependencies...${NC}"
+    set +e
+    $PYTHON_CMD -m pip install -r requirements.txt $PIP_EXTRA_ARGS $PIP_MIRROR > /tmp/pip_install.log 2>&1
+    local exit_code=$?
+    set -e
+    cat /tmp/pip_install.log
+
+    if [ $exit_code -eq 0 ]; then
+        echo -e "${GREEN}✅ Dependencies installed successfully.${NC}"
+    elif grep -qE "distutils installed project|uninstall-no-record-file|installed by debian" /tmp/pip_install.log; then
+        echo -e "${YELLOW}⚠️  Detected system package conflict, retrying with workaround...${NC}"
+        local IGNORE_PACKAGES=""
+        for pkg in PyYAML setuptools wheel certifi charset-normalizer; do
+            IGNORE_PACKAGES="$IGNORE_PACKAGES --ignore-installed $pkg"
+        done
+        set +e
+        $PYTHON_CMD -m pip install -r requirements.txt $IGNORE_PACKAGES $PIP_EXTRA_ARGS $PIP_MIRROR \
+            && echo -e "${GREEN}✅ Dependencies installed successfully (workaround applied).${NC}" \
+            || echo -e "${YELLOW}⚠️  Some dependencies may have issues, but continuing...${NC}"
+        set -e
+    elif grep -q "externally-managed-environment" /tmp/pip_install.log; then
+        echo -e "${YELLOW}⚠️  Detected externally-managed environment, retrying with --break-system-packages...${NC}"
+        set +e
+        $PYTHON_CMD -m pip install -r requirements.txt --break-system-packages $PIP_MIRROR \
+            && echo -e "${GREEN}✅ Dependencies installed successfully (system packages override applied).${NC}" \
+            || echo -e "${YELLOW}⚠️  Some dependencies may have issues, but continuing...${NC}"
+        set -e
+    else
+        echo -e "${YELLOW}⚠️  Installation had errors, but continuing...${NC}"
+    fi
+
+    rm -f /tmp/pip_install.log
+
+    # Register `cow` CLI command via editable install
+    echo -e "${YELLOW}Registering cow CLI...${NC}"
+    set +e
+    $PYTHON_CMD -m pip install -e . $PIP_EXTRA_ARGS $PIP_MIRROR > /dev/null 2>&1
+    if command -v cow &> /dev/null; then
+        echo -e "${GREEN}✅ cow CLI registered.${NC}"
+    else
+        echo -e "${YELLOW}⚠️  cow CLI not in PATH, you can still use: $PYTHON_CMD -m cli.cli${NC}"
+    fi
+    set -e
+}
+
+# Select model
+select_model() {
+    echo ""
+    local title sel
+    title="$(t "选择 AI 模型" "Select AI Model")"
+    # The 12th option is "skip" -> configure later in the web console.
+    select_menu sel "$title" \
+        "DeepSeek (deepseek-v4-flash, deepseek-v4-pro, etc.)" \
+        "Claude (claude-opus-4-8, claude-fable-5, etc.)" \
+        "Gemini (gemini-3.5-flash, gemini-3.1-pro-preview, etc.)" \
+        "OpenAI (gpt-5.5, etc.)" \
+        "MiniMax (MiniMax-M3, etc.)" \
+        "GLM (glm-5.2, etc.)" \
+        "Qwen (qwen3.7-plus, qwen3.7-max, etc.)" \
+        "Doubao (doubao-seed-2.1, etc.)" \
+        "Kimi (kimi-k2.7-code, etc.)" \
+        "MiMo (mimo-v2.5-pro, etc.)" \
+        "LinkAI ($(t "一个 Key 接入所有模型" "access all models via one API"))" \
+        "$(t "⏭  跳过（稍后在 Web 控制台配置）" "⏭  Skip (configure later in the web console)")"
+    model_choice="$sel"
+}
+
+# Read model config: provider, default_model, key_variable_name
+read_model_config() {
+    local provider=$1 default_model=$2 key_var=$3
+    echo -e "${GREEN}$(t "正在配置" "Configuring") ${provider}...${NC}"
+    # Only ask for the API key here; the model name and API base default to
+    # sensible values and can be changed later in the web console.
+    local _api_key
+    tty_read _api_key "$(t "请输入" "Enter") ${provider} API Key ($(t "回车跳过，稍后在 Web 控制台填写" "press Enter to skip, set later in web console")): "
+    MODEL_NAME="$default_model"
+    # printf -v (not eval) so keys containing quotes/backticks/$() are safe.
+    printf -v "${key_var}" '%s' "$_api_key"
+}
+
+# Configure model. The "skip" choice leaves the model empty so the user can
+# finish configuration in the web console after first start.
+configure_model() {
+    case "$model_choice" in
+        1) read_model_config "DeepSeek" "deepseek-v4-flash" "DEEPSEEK_KEY" ;;
+        2) read_model_config "Claude" "claude-opus-4-8" "CLAUDE_KEY" ;;
+        3) read_model_config "Gemini" "gemini-3.1-pro-preview" "GEMINI_KEY" ;;
+        4) read_model_config "OpenAI" "gpt-5.5" "OPENAI_KEY" ;;
+        5) read_model_config "MiniMax" "MiniMax-M3" "MINIMAX_KEY" ;;
+        6) read_model_config "GLM" "glm-5.2" "ZHIPU_KEY" ;;
+        7) read_model_config "Qwen (DashScope)" "qwen3.7-plus" "DASHSCOPE_KEY" ;;
+        8) read_model_config "Doubao (Volcengine Ark)" "doubao-seed-2-1-pro-260628" "ARK_KEY" ;;
+        9) read_model_config "Kimi (Moonshot)" "kimi-k2.7-code" "MOONSHOT_KEY" ;;
+        10) read_model_config "MiMo" "mimo-v2.5-pro" "MIMO_KEY" ;;
+        11)
+            # Show where to obtain a LinkAI key (zh users -> console page).
+            echo -e "${CYAN}$(t "获取 LinkAI Key" "Get your LinkAI Key"): https://link-ai.tech/console/interface${NC}"
+            read_model_config "LinkAI" "deepseek-v4-flash" "LINKAI_KEY"
+            USE_LINKAI="true"
+            ;;
+        12)
+            # Skip: leave model unset, will be configured in web console
+            MODEL_SKIPPED="true"
+            MODEL_NAME=""
+            echo -e "${YELLOW}$(t "已跳过模型配置，稍后可在 Web 控制台填写" "Model configuration skipped, you can set it later in the web console")${NC}"
+            ;;
+    esac
+}
+
+# Channel label by stable key (independent of menu order).
+channel_label() {
+    case "$1" in
+        web)           t "Web 网页控制台（推荐，开箱即用）" "Web Console (recommended, ready to use)" ;;
+        weixin)        t "微信" "Wechat" ;;
+        feishu)        t "飞书" "Feishu" ;;
+        dingtalk)      t "钉钉" "DingTalk" ;;
+        wecom_bot)     t "企微智能机器人" "WeCom Bot" ;;
+        qq)            printf '%s' "QQ" ;;
+        wechatcom_app) t "企微自建应用" "WeCom App" ;;
+        telegram)      printf '%s' "Telegram" ;;
+        slack)         printf '%s' "Slack" ;;
+        discord)       printf '%s' "Discord" ;;
+        skip)          t "⏭  跳过（稍后在 Web 控制台配置）" "⏭  Skip (configure later in the web console)" ;;
+    esac
+}
+
+# Select channel. The display order depends on the install language:
+#   - English: Web first, then the global IM channels (Telegram/Discord/Slack),
+#     then the China-focused channels.
+#   - Chinese: Web first, then China-focused channels, then global ones.
+# A stable key list (CHANNEL_KEYS) decouples the menu order from the config
+# logic, so reordering the menu never breaks configure_channel().
+select_channel() {
+    echo ""
+    local title sel
+    title="$(t "选择接入渠道" "Select Communication Channel")"
+    if [ "$UI_LANG" = "en" ]; then
+        CHANNEL_KEYS=(web telegram discord slack weixin feishu dingtalk wecom_bot qq wechatcom_app skip)
+    else
+        CHANNEL_KEYS=(web weixin feishu dingtalk wecom_bot qq wechatcom_app telegram slack discord skip)
+    fi
+    local labels=() k
+    for k in "${CHANNEL_KEYS[@]}"; do
+        labels+=("$(channel_label "$k")")
+    done
+    select_menu sel "$title" "${labels[@]}"
+    # Map the 1-based menu position back to the stable channel key.
+    channel_choice="${CHANNEL_KEYS[$((sel - 1))]}"
+}
+
+# Configure channel, dispatched by stable channel key (not menu position).
+configure_channel() {
+    case "$channel_choice" in
+        web|skip)
+            # Web (also the default when skipped). Use the default port with
+            # no prompt; it can be changed later in the web console / config.
+            CHANNEL_TYPE="web"
+            WEB_PORT="9899"
+            ACCESS_INFO="$(t "Web 控制台地址" "Web console") : http://localhost:9899/chat"
+            ;;
+        weixin)
+            # Weixin
+            CHANNEL_TYPE="weixin"
+            ACCESS_INFO="$(t "微信渠道已配置，请在终端或 Web 控制台扫码登录" "Weixin channel configured. Scan QR code in terminal or web console to login.")"
+            ;;
+        feishu)
+            # Feishu (WebSocket mode)
+            CHANNEL_TYPE="feishu"
+            echo -e "${GREEN}$(t "配置飞书（WebSocket 模式）" "Configure Feishu (WebSocket mode)")...${NC}"
+            local fs_app_id fs_app_secret
+            tty_read fs_app_id "$(t "请输入飞书 App ID" "Enter Feishu App ID"): "
+            tty_read fs_app_secret "$(t "请输入飞书 App Secret" "Enter Feishu App Secret"): "
+            FEISHU_APP_ID="$fs_app_id"
+            FEISHU_APP_SECRET="$fs_app_secret"
+            FEISHU_EVENT_MODE="websocket"
+            ACCESS_INFO="$(t "飞书渠道已配置（WebSocket 模式）" "Feishu channel configured (WebSocket mode)")"
+            ;;
+        dingtalk)
+            # DingTalk
+            CHANNEL_TYPE="dingtalk"
+            echo -e "${GREEN}$(t "配置钉钉" "Configure DingTalk")...${NC}"
+            local dt_client_id dt_client_secret
+            tty_read dt_client_id "$(t "请输入钉钉 Client ID" "Enter DingTalk Client ID"): "
+            tty_read dt_client_secret "$(t "请输入钉钉 Client Secret" "Enter DingTalk Client Secret"): "
+            DT_CLIENT_ID="$dt_client_id"
+            DT_CLIENT_SECRET="$dt_client_secret"
+            ACCESS_INFO="$(t "钉钉渠道已配置" "DingTalk channel configured")"
+            ;;
+        wecom_bot)
+            # WeCom Bot
+            CHANNEL_TYPE="wecom_bot"
+            echo -e "${GREEN}$(t "配置企微智能机器人" "Configure WeCom Bot")...${NC}"
+            local wecom_bot_id wecom_bot_secret
+            tty_read wecom_bot_id "$(t "请输入 WeCom Bot ID" "Enter WeCom Bot ID"): "
+            tty_read wecom_bot_secret "$(t "请输入 WeCom Bot Secret" "Enter WeCom Bot Secret"): "
+            WECOM_BOT_ID="$wecom_bot_id"
+            WECOM_BOT_SECRET="$wecom_bot_secret"
+            ACCESS_INFO="$(t "企微智能机器人渠道已配置" "WeCom Bot channel configured")"
+            ;;
+        qq)
+            # QQ
+            CHANNEL_TYPE="qq"
+            echo -e "${GREEN}$(t "配置 QQ 机器人" "Configure QQ Bot")...${NC}"
+            local qq_app_id qq_app_secret
+            tty_read qq_app_id "$(t "请输入 QQ App ID" "Enter QQ App ID"): "
+            tty_read qq_app_secret "$(t "请输入 QQ App Secret" "Enter QQ App Secret"): "
+            QQ_APP_ID="$qq_app_id"
+            QQ_APP_SECRET="$qq_app_secret"
+            ACCESS_INFO="$(t "QQ 机器人渠道已配置" "QQ Bot channel configured")"
+            ;;
+        wechatcom_app)
+            # WeCom App
+            CHANNEL_TYPE="wechatcom_app"
+            echo -e "${GREEN}$(t "配置企微自建应用" "Configure WeCom App")...${NC}"
+            local corp_id com_token com_secret com_agent_id com_aes_key com_port
+            tty_read corp_id "$(t "请输入企业 Corp ID" "Enter WeChat Corp ID"): "
+            tty_read com_token "$(t "请输入应用 Token" "Enter WeChat Com App Token"): "
+            tty_read com_secret "$(t "请输入应用 Secret" "Enter WeChat Com App Secret"): "
+            tty_read com_agent_id "$(t "请输入应用 Agent ID" "Enter WeChat Com App Agent ID"): "
+            tty_read com_aes_key "$(t "请输入应用 AES Key" "Enter WeChat Com App AES Key"): "
+            tty_read com_port "$(t "请输入应用端口" "Enter WeChat Com App Port") [$(t "默认" "default"): 9898]: "
+            com_port=${com_port:-9898}
+            WECHATCOM_CORP_ID="$corp_id"
+            WECHATCOM_TOKEN="$com_token"
+            WECHATCOM_SECRET="$com_secret"
+            WECHATCOM_AGENT_ID="$com_agent_id"
+            WECHATCOM_AES_KEY="$com_aes_key"
+            WECHATCOM_PORT="$com_port"
+            ACCESS_INFO="$(t "企微自建应用渠道已配置，端口" "WeCom App channel configured on port") ${com_port}"
+            ;;
+        telegram)
+            # Telegram
+            CHANNEL_TYPE="telegram"
+            echo -e "${GREEN}$(t "配置 Telegram" "Configure Telegram")...${NC}"
+            local tg_token
+            tty_read tg_token "$(t "请输入 Telegram Bot Token" "Enter Telegram Bot Token"): "
+            TELEGRAM_TOKEN="$tg_token"
+            ACCESS_INFO="$(t "Telegram 渠道已配置" "Telegram channel configured")"
+            ;;
+        slack)
+            # Slack
+            CHANNEL_TYPE="slack"
+            echo -e "${GREEN}$(t "配置 Slack" "Configure Slack")...${NC}"
+            local slack_bot slack_app
+            tty_read slack_bot "$(t "请输入 Slack Bot Token" "Enter Slack Bot Token") (xoxb-...): "
+            tty_read slack_app "$(t "请输入 Slack App Token" "Enter Slack App Token") (xapp-...): "
+            SLACK_BOT_TOKEN="$slack_bot"
+            SLACK_APP_TOKEN="$slack_app"
+            ACCESS_INFO="$(t "Slack 渠道已配置" "Slack channel configured")"
+            ;;
+        discord)
+            # Discord
+            CHANNEL_TYPE="discord"
+            echo -e "${GREEN}$(t "配置 Discord" "Configure Discord")...${NC}"
+            local discord_token
+            tty_read discord_token "$(t "请输入 Discord Bot Token" "Enter Discord Bot Token"): "
+            DISCORD_TOKEN="$discord_token"
+            ACCESS_INFO="$(t "Discord 渠道已配置" "Discord channel configured")"
+            ;;
+    esac
+}
+
+# Generate config file
+create_config_file() {
+    echo -e "${GREEN}📝 $(t "正在生成 config.json" "Generating config.json")...${NC}"
+
+    CHANNEL_TYPE="$CHANNEL_TYPE" \
+    MODEL_NAME="$MODEL_NAME" \
+    OPENAI_KEY="${OPENAI_KEY:-}" \
+    OPENAI_BASE="${OPENAI_BASE:-https://api.openai.com/v1}" \
+    CLAUDE_KEY="${CLAUDE_KEY:-}" \
+    CLAUDE_BASE="${CLAUDE_BASE:-https://api.anthropic.com/v1}" \
+    GEMINI_KEY="${GEMINI_KEY:-}" \
+    GEMINI_BASE="${GEMINI_BASE:-https://generativelanguage.googleapis.com}" \
+    ZHIPU_KEY="${ZHIPU_KEY:-}" \
+    MOONSHOT_KEY="${MOONSHOT_KEY:-}" \
+    ARK_KEY="${ARK_KEY:-}" \
+    DASHSCOPE_KEY="${DASHSCOPE_KEY:-}" \
+    MINIMAX_KEY="${MINIMAX_KEY:-}" \
+    MIMO_KEY="${MIMO_KEY:-}" \
+    DEEPSEEK_KEY="${DEEPSEEK_KEY:-}" \
+    DEEPSEEK_BASE="${DEEPSEEK_BASE:-https://api.deepseek.com/v1}" \
+    USE_LINKAI="${USE_LINKAI:-false}" \
+    LINKAI_KEY="${LINKAI_KEY:-}" \
+    FEISHU_APP_ID="${FEISHU_APP_ID:-}" \
+    FEISHU_APP_SECRET="${FEISHU_APP_SECRET:-}" \
+    WEB_PORT="${WEB_PORT:-}" \
+    DT_CLIENT_ID="${DT_CLIENT_ID:-}" \
+    DT_CLIENT_SECRET="${DT_CLIENT_SECRET:-}" \
+    WECOM_BOT_ID="${WECOM_BOT_ID:-}" \
+    WECOM_BOT_SECRET="${WECOM_BOT_SECRET:-}" \
+    QQ_APP_ID="${QQ_APP_ID:-}" \
+    QQ_APP_SECRET="${QQ_APP_SECRET:-}" \
+    WECHATCOM_CORP_ID="${WECHATCOM_CORP_ID:-}" \
+    WECHATCOM_TOKEN="${WECHATCOM_TOKEN:-}" \
+    WECHATCOM_SECRET="${WECHATCOM_SECRET:-}" \
+    WECHATCOM_AGENT_ID="${WECHATCOM_AGENT_ID:-}" \
+    WECHATCOM_AES_KEY="${WECHATCOM_AES_KEY:-}" \
+    WECHATCOM_PORT="${WECHATCOM_PORT:-}" \
+    TELEGRAM_TOKEN="${TELEGRAM_TOKEN:-}" \
+    SLACK_BOT_TOKEN="${SLACK_BOT_TOKEN:-}" \
+    SLACK_APP_TOKEN="${SLACK_APP_TOKEN:-}" \
+    DISCORD_TOKEN="${DISCORD_TOKEN:-}" \
+    COW_LANG="${INSTALL_LANG:-auto}" \
+    $PYTHON_CMD -c "
+import json, os
+e = os.environ.get
+base = {
+    'channel_type': e('CHANNEL_TYPE') or 'web',
+    'model': e('MODEL_NAME') or '',
+    'cow_lang': e('COW_LANG', 'auto'),
+    'open_ai_api_key': e('OPENAI_KEY', ''),
+    'open_ai_api_base': e('OPENAI_BASE'),
+    'claude_api_key': e('CLAUDE_KEY', ''),
+    'claude_api_base': e('CLAUDE_BASE'),
+    'gemini_api_key': e('GEMINI_KEY', ''),
+    'gemini_api_base': e('GEMINI_BASE'),
+    'zhipu_ai_api_key': e('ZHIPU_KEY', ''),
+    'moonshot_api_key': e('MOONSHOT_KEY', ''),
+    'ark_api_key': e('ARK_KEY', ''),
+    'dashscope_api_key': e('DASHSCOPE_KEY', ''),
+    'minimax_api_key': e('MINIMAX_KEY', ''),
+    'mimo_api_key': e('MIMO_KEY', ''),
+    'deepseek_api_key': e('DEEPSEEK_KEY', ''),
+    'deepseek_api_base': e('DEEPSEEK_BASE'),
+    # Leave ASR/TTS provider empty so the web console auto-suggests the vendor
+    # whose API key is actually configured (e.g. LinkAI), not always OpenAI.
+    'voice_to_text': '',
+    'text_to_voice': '',
+    'voice_reply_voice': False,
+    'speech_recognition': True,
+    'group_speech_recognition': False,
+    'use_linkai': e('USE_LINKAI') == 'true',
+    'linkai_api_key': e('LINKAI_KEY', ''),
+    'linkai_app_code': '',
+    'agent': True,
+    'agent_max_context_tokens': 50000,
+    'agent_max_context_turns': 20,
+    'agent_max_steps': 20,
+    # New installs opt into self-evolution; existing users (no key) keep the
+    # code default (off) so an upgrade never silently changes their behavior.
+    'self_evolution_enabled': True,
+}
+channel_map = {
+    'feishu': {'feishu_app_id': 'FEISHU_APP_ID', 'feishu_app_secret': 'FEISHU_APP_SECRET'},
+    'web': {'web_port': ('WEB_PORT', int)},
+    'dingtalk': {'dingtalk_client_id': 'DT_CLIENT_ID', 'dingtalk_client_secret': 'DT_CLIENT_SECRET'},
+    'wecom_bot': {'wecom_bot_id': 'WECOM_BOT_ID', 'wecom_bot_secret': 'WECOM_BOT_SECRET'},
+    'qq': {'qq_app_id': 'QQ_APP_ID', 'qq_app_secret': 'QQ_APP_SECRET'},
+    'wechatcom_app': {'wechatcom_corp_id': 'WECHATCOM_CORP_ID', 'wechatcomapp_token': 'WECHATCOM_TOKEN', 'wechatcomapp_secret': 'WECHATCOM_SECRET', 'wechatcomapp_agent_id': 'WECHATCOM_AGENT_ID', 'wechatcomapp_aes_key': 'WECHATCOM_AES_KEY', 'wechatcomapp_port': ('WECHATCOM_PORT', int)},
+    'telegram': {'telegram_token': 'TELEGRAM_TOKEN'},
+    'slack': {'slack_bot_token': 'SLACK_BOT_TOKEN', 'slack_app_token': 'SLACK_APP_TOKEN'},
+    'discord': {'discord_token': 'DISCORD_TOKEN'},
+}
+def _to_int(val, default):
+    try:
+        return int(val)
+    except (TypeError, ValueError):
+        return default
+ch = e('CHANNEL_TYPE') or 'web'
+for key, spec in channel_map.get(ch, {}).items():
+    if isinstance(spec, tuple):
+        env_name, conv = spec
+        # Guard int() against non-numeric input; fall back to a sane port.
+        base[key] = _to_int(e(env_name), 9899 if key == 'web_port' else 9898) if conv is int else conv(e(env_name))
+    else:
+        base[key] = e(spec, '')
+with open('config.json', 'w') as f:
+    json.dump(base, f, indent=2, ensure_ascii=False)
+"
+
+    echo -e "${GREEN}✅ $(t "配置文件创建成功" "Configuration file created successfully").${NC}"
+}
+
+# Start project
+start_project() {
+    echo ""
+    echo -e "${GREEN}${EMOJI_ROCKET} Starting CowAgent...${NC}"
+    sleep 1
+
+    local USE_COW=false
+    if command -v cow &> /dev/null; then
+        USE_COW=true
+    fi
+
+    if $USE_COW; then
+        cd "${BASE_DIR}"
+        cow start --no-logs
+    else
+        if [ ! -f "${BASE_DIR}/nohup.out" ]; then
+            touch "${BASE_DIR}/nohup.out"
+        fi
+
+        OS_TYPE=$(uname)
+
+        if [[ "$OS_TYPE" == "Linux" ]]; then
+            nohup setsid $PYTHON_CMD "${BASE_DIR}/app.py" > "${BASE_DIR}/nohup.out" 2>&1 &
+            echo -e "${GREEN}${EMOJI_COW} CowAgent started on Linux (using $PYTHON_CMD)${NC}"
+        elif [[ "$OS_TYPE" == "Darwin" ]]; then
+            nohup $PYTHON_CMD "${BASE_DIR}/app.py" > "${BASE_DIR}/nohup.out" 2>&1 &
+            echo -e "${GREEN}${EMOJI_COW} CowAgent started on macOS (using $PYTHON_CMD)${NC}"
+        else
+            echo -e "${RED}❌ Unsupported OS: ${OS_TYPE}${NC}"
+            exit 1
+        fi
+    fi
+
+    sleep 2
+    echo ""
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo -e "${GREEN}${EMOJI_CHECK} $(t "CowAgent 已在后台运行" "CowAgent is now running in background")!${NC}"
+    echo -e "${GREEN}${EMOJI_CHECK} $(t "关闭终端后进程仍会继续运行" "Process will continue after closing terminal").${NC}"
+    echo -e "${CYAN}$ACCESS_INFO${NC}"
+
+    # If the model was skipped, guide the user to finish setup in the web console.
+    if [ "${MODEL_SKIPPED:-}" = "true" ]; then
+        local _port="${WEB_PORT:-9899}"
+        echo ""
+        echo -e "${YELLOW}${EMOJI_WARN} $(t "尚未配置模型，请在 Web 控制台完成配置" "Model not configured yet, please finish setup in the web console"):${NC}"
+        echo -e "${CYAN}   http://localhost:${_port}/chat${NC}"
+    fi
+    echo ""
+    echo -e "${CYAN}${BOLD}$(t "管理命令" "Management Commands"):${NC}"
+    if $USE_COW; then
+        echo -e "  ${GREEN}cow stop${NC}       $(t "停止服务" "Stop the service")"
+        echo -e "  ${GREEN}cow restart${NC}    $(t "重启服务" "Restart the service")"
+        echo -e "  ${GREEN}cow status${NC}     $(t "查看状态" "Check status")"
+        echo -e "  ${GREEN}cow logs${NC}       $(t "查看日志" "View logs")"
+        echo -e "  ${GREEN}cow update${NC}     $(t "更新并重启" "Update and restart")"
+        echo -e "  ${GREEN}cow install-browser${NC}  $(t "安装浏览器工具" "Install browser tool")"
+    else
+        echo -e "  ${GREEN}./run.sh stop${NC}       $(t "停止服务" "Stop the service")"
+        echo -e "  ${GREEN}./run.sh restart${NC}    $(t "重启服务" "Restart the service")"
+        echo -e "  ${GREEN}./run.sh status${NC}     $(t "查看状态" "Check status")"
+        echo -e "  ${GREEN}./run.sh logs${NC}       $(t "查看日志" "View logs")"
+        echo -e "  ${GREEN}./run.sh update${NC}     $(t "更新并重启" "Update and restart")"
+        echo -e "  ${GREEN}cow install-browser${NC}  $(t "安装浏览器工具" "Install browser tool")"
+    fi
+    echo ""
+    echo -e "${YELLOW}$(t "提示：需要让 Agent 浏览网页时，运行 cow install-browser 安装浏览器工具" "Tip: to let the Agent browse the web, run 'cow install-browser' to install the browser tool")${NC}"
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo ""
+
+    echo -e "${YELLOW}$(t "显示最近日志（Ctrl+C 退出，Agent 继续运行）" "Showing recent logs (Ctrl+C to exit, agent keeps running)"):${NC}"
+    sleep 2
+    tail -n 30 -f "${BASE_DIR}/nohup.out"
+}
+
+# Show usage
+show_usage() {
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo -e "${CYAN}${BOLD}   ${EMOJI_COW} CowAgent Management Script${NC}"
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo ""
+    echo -e "${YELLOW}$(t "用法" "Usage"):${NC}"
+    echo -e "  ${GREEN}./run.sh${NC}               ${CYAN}# $(t "安装/配置项目" "Install/Configure project")${NC}"
+    echo -e "  ${GREEN}./run.sh <command>${NC}     ${CYAN}# $(t "执行管理命令" "Execute management command")${NC}"
+    echo ""
+    echo -e "${YELLOW}$(t "命令" "Commands"):${NC}"
+    echo -e "  ${GREEN}start${NC}      $(t "启动服务" "Start the service")"
+    echo -e "  ${GREEN}stop${NC}       $(t "停止服务" "Stop the service")"
+    echo -e "  ${GREEN}restart${NC}    $(t "重启服务" "Restart the service")"
+    echo -e "  ${GREEN}status${NC}     $(t "查看服务状态" "Check service status")"
+    echo -e "  ${GREEN}logs${NC}       $(t "查看日志 (tail -f)" "View logs (tail -f)")"
+    echo -e "  ${GREEN}config${NC}     $(t "重新配置项目" "Reconfigure project")"
+    echo -e "  ${GREEN}update${NC}     $(t "更新并重启" "Update and restart")"
+    echo ""
+    echo -e "${YELLOW}$(t "示例" "Examples"):${NC}"
+    echo -e "  ${GREEN}./run.sh start${NC}"
+    echo -e "  ${GREEN}./run.sh logs${NC}"
+    echo -e "  ${GREEN}./run.sh status${NC}"
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+}
+
+# Ensure PYTHON_CMD is set
+ensure_python_cmd() {
+    if [ -z "$PYTHON_CMD" ]; then
+        detect_python_command > /dev/null 2>&1 || PYTHON_CMD="python3"
+    fi
+}
+
+# Get service PID (empty string if not running)
+get_pid() {
+    ensure_python_cmd > /dev/null 2>&1
+    ps ax | grep -i app.py | grep "${BASE_DIR}" | grep "$PYTHON_CMD" | grep -v grep | awk '{print $1}' | grep -E '^[0-9]+$' | head -1
+}
+
+# Check if service is running
+is_running() {
+    [ -n "$(get_pid)" ]
+}
+
+# Check if cow CLI is available
+has_cow() {
+    command -v cow &> /dev/null
+}
+
+# Start service
+cmd_start() {
+    if [ ! -f "${BASE_DIR}/config.json" ]; then
+        echo -e "${RED}${EMOJI_CROSS} $(t "未找到 config.json" "config.json not found")${NC}"
+        echo -e "${YELLOW}$(t "请先运行 './run.sh' 进行配置" "Please run './run.sh' to configure first")${NC}"
+        exit 1
+    fi
+
+    if has_cow; then
+        cd "${BASE_DIR}"
+        cow start
+    else
+        if is_running; then
+            echo -e "${YELLOW}${EMOJI_WARN} $(t "CowAgent 已在运行中" "CowAgent is already running") (PID: $(get_pid))${NC}"
+            echo -e "${YELLOW}$(t "使用 './run.sh restart' 重启" "Use './run.sh restart' to restart")${NC}"
+            return
+        fi
+        check_python_version
+        start_project
+    fi
+}
+
+# Stop service
+cmd_stop() {
+    # Don't let kill/return non-zero (e.g. process already gone) abort the
+    # caller (cmd_restart) under `set -e`.
+    set +e
+    if has_cow; then
+        cd "${BASE_DIR}"
+        cow stop
+    else
+        echo -e "${GREEN}${EMOJI_STOP} $(t "正在停止 CowAgent" "Stopping CowAgent")...${NC}"
+
+        if ! is_running; then
+            echo -e "${YELLOW}${EMOJI_WARN} $(t "CowAgent 未在运行" "CowAgent is not running")${NC}"
+            return 0
+        fi
+
+        pid=$(get_pid)
+        if [ -z "$pid" ] || ! echo "$pid" | grep -qE '^[0-9]+$'; then
+            echo -e "${RED}❌ $(t "获取有效 PID 失败" "Failed to get valid PID") (${pid})${NC}"
+            return 0
+        fi
+
+        echo -e "${GREEN}$(t "找到运行中的进程" "Found running process") (PID: ${pid})${NC}"
+
+        kill ${pid} 2>/dev/null || true
+        sleep 3
+
+        if ps -p ${pid} > /dev/null 2>&1; then
+            echo -e "${YELLOW}⚠️  $(t "进程未停止，强制终止" "Process not stopped, forcing termination")...${NC}"
+            kill -9 ${pid} 2>/dev/null || true
+        fi
+
+        echo -e "${GREEN}${EMOJI_CHECK} $(t "CowAgent 已停止" "CowAgent stopped")${NC}"
+    fi
+}
+
+# Restart service
+cmd_restart() {
+    if has_cow; then
+        cd "${BASE_DIR}"
+        cow restart
+    else
+        cmd_stop
+        sleep 1
+        cmd_start
+    fi
+}
+
+# Check status
+cmd_status() {
+    if has_cow; then
+        cd "${BASE_DIR}"
+        cow status
+    else
+        echo -e "${CYAN}${BOLD}=========================================${NC}"
+        echo -e "${CYAN}${BOLD}   ${EMOJI_COW} CowAgent Status${NC}"
+        echo -e "${CYAN}${BOLD}=========================================${NC}"
+
+        if is_running; then
+            pid=$(get_pid)
+            echo -e "${GREEN}$(t "状态" "Status"):${NC} ✅ $(t "运行中" "Running")"
+            echo -e "${GREEN}PID:${NC}    ${pid}"
+            if [ -f "${BASE_DIR}/nohup.out" ]; then
+                echo -e "${GREEN}$(t "日志" "Logs"):${NC}   ${BASE_DIR}/nohup.out"
+            fi
+        else
+            echo -e "${YELLOW}$(t "状态" "Status"):${NC} ⭐ $(t "已停止" "Stopped")"
+        fi
+
+        if [ -f "${BASE_DIR}/config.json" ]; then
+            # `|| true`: grep returns 1 when the key is absent (set -e safe).
+            model=$(grep -o '"model"[[:space:]]*:[[:space:]]*"[^"]*"' "${BASE_DIR}/config.json" 2>/dev/null | cut -d'"' -f4 || true)
+            channel=$(grep -o '"channel_type"[[:space:]]*:[[:space:]]*"[^"]*"' "${BASE_DIR}/config.json" 2>/dev/null | cut -d'"' -f4 || true)
+            echo -e "${GREEN}$(t "模型" "Model"):${NC}  ${model:-$(t "（未配置）" "(not set)")}"
+            echo -e "${GREEN}$(t "渠道" "Channel"):${NC} ${channel:-$(t "（未配置）" "(not set)")}"
+        fi
+
+        echo -e "${CYAN}${BOLD}=========================================${NC}"
+    fi
+}
+
+# View logs
+cmd_logs() {
+    if has_cow; then
+        cd "${BASE_DIR}"
+        cow logs -f
+    else
+        if [ -f "${BASE_DIR}/nohup.out" ]; then
+            echo -e "${YELLOW}$(t "查看日志（Ctrl+C 退出）" "Viewing logs (Ctrl+C to exit)"):${NC}"
+            tail -f "${BASE_DIR}/nohup.out"
+        else
+            echo -e "${RED}❌ $(t "日志文件未找到" "Log file not found"): ${BASE_DIR}/nohup.out${NC}"
+        fi
+    fi
+}
+
+# Reconfigure
+cmd_config() {
+    # Interactive flow: disable `set -e` (see install_mode for rationale).
+    set +e
+    # One shared terminal handle for all menus in this session.
+    menu_session_begin
+
+    # Choose language first so the rest of the flow is localized.
+    select_language
+    echo ""
+    echo -e "${YELLOW}${EMOJI_WRENCH} $(t "正在重新配置 CowAgent" "Reconfiguring CowAgent")...${NC}"
+    
+    if [ -f "${BASE_DIR}/config.json" ]; then
+        backup_file="${BASE_DIR}/config.json.backup.$(date +%s)"
+        cp "${BASE_DIR}/config.json" "${backup_file}"
+        echo -e "${GREEN}✅ $(t "已备份配置到" "Backed up config to"): ${backup_file}${NC}"
+    fi
+    
+    check_python_version
+    install_dependencies
+    select_model
+    configure_model
+    select_channel
+    configure_channel
+    menu_session_end
+    create_config_file
+    
+    echo ""
+    local restart_now
+    tty_read restart_now "$(t "现在重启服务" "Restart service now")? [Y/n]: "
+    if [[ ! $restart_now == [Nn]* ]]; then
+        cmd_restart
+    fi
+}
+
+# Update project
+cmd_update() {
+    echo -e "${GREEN}${EMOJI_WRENCH} $(t "正在更新 CowAgent" "Updating CowAgent")...${NC}"
+    cd "${BASE_DIR}"
+    
+    # Pull latest code first (service still running)
+    local pull_ok=false
+    if [ -d .git ]; then
+        echo -e "${GREEN}🔄 $(t "正在拉取最新代码" "Pulling latest code")...${NC}"
+        if git pull; then
+            pull_ok=true
+        else
+            echo -e "${YELLOW}⚠️  $(t "git pull 失败，尝试 Gitee 镜像" "git pull failed, trying Gitee mirror")...${NC}"
+            git remote set-url origin https://gitee.com/zhayujie/CowAgent.git
+            if git pull; then
+                pull_ok=true
+            else
+                echo -e "${RED}❌ $(t "拉取代码失败，更新已中止" "Failed to pull code. Update aborted").${NC}"
+                exit 1
+            fi
+        fi
+    else
+        echo -e "${YELLOW}⚠️  $(t "非 git 仓库，跳过代码更新" "Not a git repository, skipping code update")${NC}"
+    fi
+    
+    # Re-exec with the updated run.sh to pick up new logic
+    exec "$0" _post_update
+}
+
+# Post-update: called by cmd_update after git pull to run with new code
+cmd_post_update() {
+    cd "${BASE_DIR}"
+
+    # Stop service
+    if is_running; then
+        cmd_stop
+    fi
+
+    # Reinstall dependencies
+    check_python_version
+    install_dependencies
+
+    # Restart service
+    cmd_start
+}
+
+# Installation mode
+install_mode() {
+    # Interactive flow: disable `set -e` so a single non-zero command (e.g. an
+    # arithmetic `(( ))` evaluating to 0, a `read` hitting EOF, or an optional
+    # step failing) does not silently abort the whole installer.
+    set +e
+    clear
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo -e "${CYAN}${BOLD}   ${EMOJI_COW} CowAgent Installation${NC}"
+    echo -e "${CYAN}${BOLD}=========================================${NC}"
+    echo ""
+
+    # Open one shared terminal handle for ALL menus in this session (language,
+    # model, channel). One long-lived fd 3 avoids per-menu re-open issues on
+    # bash 3.2. Closed on early return and before config generation.
+    menu_session_begin
+
+    # Step 0: choose the install/UI language. Everything after this is localized.
+    select_language
+    echo ""
+    sleep 1
+
+    if [ "$IS_PROJECT_DIR" = true ]; then
+        echo -e "${GREEN}✅ $(t "检测到已有项目目录" "Detected existing project directory").${NC}"
+        
+        if [ -f "${BASE_DIR}/config.json" ]; then
+            menu_session_end
+            echo -e "${GREEN}✅ $(t "项目已配置" "Project already configured")${NC}"
+            echo ""
+            show_usage
+            return
+        fi
+        
+        echo -e "${YELLOW}📝 $(t "未找到 config.json，开始配置项目" "No config.json found. Let's configure your project")!${NC}"
+        echo ""
+        
+        # Project directory already exists, skip clone
+        check_python_version
+    else
+        # Remote install mode, need to clone project
+        check_python_version
+        clone_project
+    fi
+    
+    # Install dependencies and configure
+    install_dependencies
+    select_model
+    configure_model
+    select_channel
+    configure_channel
+    menu_session_end
+    create_config_file
+    
+    # Auto-start after configuration for a true out-of-the-box experience.
+    echo ""
+    start_project
+}
+
+# Require running inside the project directory
+require_project_dir() {
+    if [ "$IS_PROJECT_DIR" = false ]; then
+        echo -e "${RED}${EMOJI_CROSS} $(t "必须在项目目录下运行" "Must run in project directory")${NC}"
+        exit 1
+    fi
+}
+
+# Initialize UI_LANG for management commands: prefer cow_lang from an existing
+# config.json, otherwise fall back to environment detection. The install flow
+# overrides this later via select_language().
+init_ui_lang() {
+    [ -n "$UI_LANG" ] && return
+    local cfg_lang=""
+    if [ -f "${BASE_DIR}/config.json" ]; then
+        # `|| true`: grep returns 1 when cow_lang is absent, which would abort
+        # the whole script under `set -e` at the very first management command.
+        cfg_lang=$(grep -o '"cow_lang"[[:space:]]*:[[:space:]]*"[^"]*"' "${BASE_DIR}/config.json" 2>/dev/null | cut -d'"' -f4 || true)
+    fi
+    case "$cfg_lang" in
+        zh) UI_LANG="zh" ;;
+        en) UI_LANG="en" ;;
+        *) UI_LANG=$(detect_ui_lang) ;;
+    esac
+}
+
+# Main function
+main() {
+    init_ui_lang
+
+    case "$1" in
+        start|stop|restart|status|logs|config|update|_post_update)
+            require_project_dir
+            ;;
+    esac
+
+    case "$1" in
+        start)   cmd_start ;;
+        stop)    cmd_stop ;;
+        restart) cmd_restart ;;
+        status)  cmd_status ;;
+        logs)    cmd_logs ;;
+        config)  cmd_config ;;
+        update)  cmd_update ;;
+        _post_update) cmd_post_update ;;
+        help|--help|-h)
+            show_usage
+            ;;
+        "")
+            install_mode
+            ;;
+        *)
+            echo -e "${RED}${EMOJI_CROSS} $(t "未知命令" "Unknown command"): $1${NC}"
+            echo ""
+            show_usage
+            exit 1
+            ;;
+    esac
+}
+
+# Execute main function
+main "$@"
diff --git a/scripts/run.ps1 b/scripts/run.ps1
new file mode 100644
index 0000000..2124710
--- /dev/null
+++ b/scripts/run.ps1
@@ -0,0 +1,878 @@
+#Requires -Version 5.1
+<#
+.SYNOPSIS
+    CowAgent installer & management script for Windows.
+.DESCRIPTION
+    One-liner install:
+      irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
+    Or from a local clone:
+      .\scripts\run.ps1              # install / configure
+      .\scripts\run.ps1 start        # start service  (delegates to cow CLI)
+      .\scripts\run.ps1 stop|restart|status|logs|config|update|help
+#>
+
+param(
+    [Parameter(Position = 0)]
+    [string]$Command = ""
+)
+
+$ErrorActionPreference = "Stop"
+
+# ── ensure UTF-8 everywhere on Windows ───────────────────────────
+# Without this, Chinese text renders as mojibake (e.g. "éæ©") on Windows
+# PowerShell 5.1, whose console defaults to the system ANSI code page (GBK on
+# Chinese systems). Set the active code page AND the console encodings so both
+# our output and any child process (git/python) speak UTF-8.
+try { chcp 65001 | Out-Null } catch {}
+try {
+    [Console]::OutputEncoding = [System.Text.Encoding]::UTF8
+    [Console]::InputEncoding  = [System.Text.Encoding]::UTF8
+} catch {}
+# $OutputEncoding controls how strings are piped to external programs.
+$OutputEncoding = [System.Text.Encoding]::UTF8
+$env:PYTHONIOENCODING = "utf-8"
+
+# ── disable console QuickEdit mode ───────────────────────────────
+# On Windows, QuickEdit is ON by default: a stray click/selection in the
+# window FREEZES all output until the user presses a key. During long steps
+# (git clone, pip install) this looks like a hang, and the wake-up key gets
+# buffered and later auto-confirms a menu default. Turning QuickEdit off
+# removes both the freeze and the phantom keystrokes.
+try {
+    if (-not ([Console]::IsInputRedirected)) {
+        $quickEditType = @'
+using System;
+using System.Runtime.InteropServices;
+public static class ConsoleQuickEdit {
+    const int  STD_INPUT_HANDLE   = -10;
+    const uint ENABLE_QUICK_EDIT  = 0x0040;
+    const uint ENABLE_EXTENDED    = 0x0080;
+    [DllImport("kernel32.dll", SetLastError = true)]
+    static extern IntPtr GetStdHandle(int nStdHandle);
+    [DllImport("kernel32.dll")]
+    static extern bool GetConsoleMode(IntPtr hConsoleHandle, out uint lpMode);
+    [DllImport("kernel32.dll")]
+    static extern bool SetConsoleMode(IntPtr hConsoleHandle, uint dwMode);
+    public static void Disable() {
+        IntPtr handle = GetStdHandle(STD_INPUT_HANDLE);
+        uint mode;
+        if (!GetConsoleMode(handle, out mode)) { return; }
+        mode &= ~ENABLE_QUICK_EDIT;   // clear QuickEdit
+        mode |=  ENABLE_EXTENDED;     // keep extended flags valid
+        SetConsoleMode(handle, mode);
+    }
+}
+'@
+        if (-not ([System.Management.Automation.PSTypeName]'ConsoleQuickEdit').Type) {
+            Add-Type -TypeDefinition $quickEditType -ErrorAction Stop
+        }
+        [ConsoleQuickEdit]::Disable()
+    }
+} catch {}
+
+# ── colours ──────────────────────────────────────────────────────
+function Write-Cow   { param([string]$M) Write-Host $M -ForegroundColor Green  }
+function Write-Warn  { param([string]$M) Write-Host $M -ForegroundColor Yellow }
+function Write-Err   { param([string]$M) Write-Host $M -ForegroundColor Red    }
+function Write-Info  { param([string]$M) Write-Host $M -ForegroundColor Cyan   }
+
+# ── i18n: install-flow language ──────────────────────────────────
+# $UiLang controls the language of install prompts/menus ("zh" or "en").
+# Chosen by the user at the first step; defaults to environment detection
+# for management commands (start/stop/...).
+$script:UiLang = ""
+
+# Detect default UI language from the OS culture (best-effort). Checks the
+# display/UI culture first (closest to the user's chosen Windows language),
+# then the regional format culture as a fallback. Any zh-* signal -> "zh".
+function Get-DefaultUiLang {
+    foreach ($getter in @({ (Get-UICulture).Name }, { (Get-Culture).Name })) {
+        try {
+            $name = & $getter
+            if ($name -match '^zh') { return "zh" }
+        } catch {}
+    }
+    return "en"
+}
+
+# Translation helper: T <zh> <en> -> string in the active UI language.
+function T {
+    param([string]$Zh, [string]$En)
+    if ($script:UiLang -eq "en") { return $En } else { return $Zh }
+}
+
+# ── detect project directory ─────────────────────────────────────
+$ScriptDir = if ($PSScriptRoot) { $PSScriptRoot } else { $PWD.Path }
+$BaseDir   = Split-Path $ScriptDir -Parent
+
+$IsProjectDir = (Test-Path "$BaseDir\app.py") -and (Test-Path "$BaseDir\config-template.json")
+if (-not $IsProjectDir) {
+    $BaseDir = $PWD.Path
+    $IsProjectDir = (Test-Path "$BaseDir\app.py") -and (Test-Path "$BaseDir\config-template.json")
+}
+
+# Initialize $UiLang for management commands: prefer cow_lang from an existing
+# config.json, otherwise fall back to environment detection.
+function Initialize-UiLang {
+    if ($script:UiLang) { return }
+    $cfgLang = ""
+    if (Test-Path "$BaseDir\config.json") {
+        try {
+            $cfg = Get-Content "$BaseDir\config.json" -Raw | ConvertFrom-Json
+            if ($cfg.cow_lang) { $cfgLang = "$($cfg.cow_lang)" }
+        } catch {}
+    }
+    switch ($cfgLang) {
+        "zh"    { $script:UiLang = "zh" }
+        "en"    { $script:UiLang = "en" }
+        default { $script:UiLang = Get-DefaultUiLang }
+    }
+}
+
+# Drain any buffered console keystrokes. During long steps (git clone, pip
+# install) users often hit Enter to "wake up" a seemingly stuck console; those
+# keys sit in the input buffer and would otherwise be consumed by the next
+# ReadKey, auto-confirming a menu's default. Flush them before reading input.
+function Clear-InputBuffer {
+    try {
+        if ([Console]::IsInputRedirected) { return }
+        while ([Console]::KeyAvailable) { [void][Console]::ReadKey($true) }
+    } catch {}
+}
+
+# ── arrow-key selectable menu with number fallback ───────────────
+# Usage: $idx = Select-Menu -Title "..." -Options @("a","b") [-Default 1]
+# Returns the selected 1-based index.
+function Select-Menu {
+    param(
+        [string]$Title,
+        [string[]]$Options,
+        [int]$Default = 1
+    )
+    $count = $Options.Count
+    $cur = [Math]::Max(0, [Math]::Min($Default - 1, $count - 1))
+
+    # Fallback to numbered input when there is no interactive console
+    # (e.g. piped input, redirected host).
+    $interactive = $true
+    try {
+        if ([Console]::IsInputRedirected) { $interactive = $false }
+    } catch { $interactive = $false }
+
+    if (-not $interactive) {
+        Write-Info $Title
+        for ($i = 0; $i -lt $count; $i++) {
+            Write-Host ("  {0}) {1}" -f ($i + 1), $Options[$i])
+        }
+        do {
+            $sel = Read-Host (T "请输入序号" "Enter number") 
+            if (-not $sel) { $sel = "$($cur + 1)" }
+        } while ($sel -notmatch '^\d+$' -or [int]$sel -lt 1 -or [int]$sel -gt $count)
+        return [int]$sel
+    }
+
+    Write-Info $Title
+    Write-Host (T "↑/↓ 选择，Enter 确认" "Use ↑/↓ to move, Enter to select") -ForegroundColor Cyan
+
+    # Discard keystrokes buffered during the previous (possibly long-running)
+    # step so a leftover Enter doesn't instantly confirm the default option.
+    Clear-InputBuffer
+
+    [Console]::CursorVisible = $false
+    $firstDraw = $true
+    try {
+        while ($true) {
+            if (-not $firstDraw) {
+                # Move cursor up to the top of the option block to redraw it.
+                $top = [Console]::CursorTop - $count
+                if ($top -lt 0) { $top = 0 }
+                [Console]::SetCursorPosition(0, $top)
+            }
+            $firstDraw = $false
+
+            for ($i = 0; $i -lt $count; $i++) {
+                # Clear the line first to avoid leftover characters.
+                Write-Host (" " * ([Console]::WindowWidth - 1)) -NoNewline
+                [Console]::SetCursorPosition(0, [Console]::CursorTop)
+                if ($i -eq $cur) {
+                    Write-Host ("  > " + $Options[$i]) -ForegroundColor Green
+                } else {
+                    Write-Host ("    " + $Options[$i])
+                }
+            }
+
+            $key = [Console]::ReadKey($true)
+            switch ($key.Key) {
+                "UpArrow"   { $cur = (($cur - 1 + $count) % $count) }
+                "DownArrow" { $cur = (($cur + 1) % $count) }
+                "Enter"     { return ($cur + 1) }
+                default {
+                    # Number shortcut (1-9) jumps to that option and confirms.
+                    $ch = $key.KeyChar
+                    if ($ch -match '^[1-9]$') {
+                        $n = [int]"$ch"
+                        if ($n -ge 1 -and $n -le $count) { return $n }
+                    }
+                }
+            }
+        }
+    } finally {
+        [Console]::CursorVisible = $true
+    }
+}
+
+# ── language selection (first step of install) ───────────────────
+function Select-Language {
+    # Order is fixed (English first, Chinese second). The default highlight
+    # follows detection, but conservatively: only a confident "zh" signal
+    # (a zh-* system culture) preselects Chinese; everything else defaults to
+    # English. The menu hint shows in the detected language for familiarity.
+    $detected = Get-DefaultUiLang
+    if ($detected -eq "zh") {
+        $default = 2
+        $script:UiLang = "zh"
+    } else {
+        $default = 1
+        $script:UiLang = "en"
+    }
+
+    $idx = Select-Menu -Title "Select Language / 选择语言" -Options @("English", "中文 (Chinese)") -Default $default
+    switch ($idx) {
+        1 { $script:UiLang = "en" }
+        2 { $script:UiLang = "zh" }
+        default { $script:UiLang = "en" }
+    }
+    $script:InstallLang = $script:UiLang
+}
+
+# ── Python detection ─────────────────────────────────────────────
+function Find-Python {
+    # 3.13 compatibility is not great, so prefer 3.7-3.12 and only fall back to 3.13.
+    $fallback = $null
+    foreach ($cmd in @("python3", "python")) {
+        $bin = Get-Command $cmd -ErrorAction SilentlyContinue
+        if (-not $bin) { continue }
+        try {
+            $ver = & $bin.Source -c "import sys; v=sys.version_info; print(f'{v.major}.{v.minor}')" 2>$null
+            $parts = $ver -split '\.'
+            $major = [int]$parts[0]; $minor = [int]$parts[1]
+            if ($major -eq 3 -and $minor -ge 7 -and $minor -le 12) {
+                return $bin.Source
+            }
+            if ($major -eq 3 -and $minor -eq 13 -and -not $fallback) {
+                $fallback = $bin.Source
+            }
+        } catch {}
+    }
+    return $fallback
+}
+
+$PythonCmd = Find-Python
+function Assert-Python {
+    if (-not $PythonCmd) {
+        Write-Err (T "未找到 Python 3.7-3.13，请从 https://www.python.org/downloads/ 安装" "Python 3.7-3.13 not found. Please install from https://www.python.org/downloads/")
+        Read-Host (T "按回车退出" "Press Enter to exit")
+        exit 1
+    }
+    Write-Cow ((T "找到 Python" "Found Python") + ": $PythonCmd")
+}
+
+# ── clone project ────────────────────────────────────────────────
+function Install-Project {
+    if (Test-Path "CowAgent") {
+        # Auto-backup the existing directory without prompting.
+        $backup = "CowAgent_backup_$(Get-Date -Format 'yyyyMMddHHmmss')"
+        Rename-Item "CowAgent" $backup
+        Write-Warn ((T "已存在 CowAgent 目录，已自动备份为" "Existing 'CowAgent' directory backed up to") + " '$backup'")
+    }
+
+    $gitBin = Get-Command git -ErrorAction SilentlyContinue
+    if (-not $gitBin) {
+        Write-Err (T "未找到 Git，请从 https://git-scm.com/download/win 安装" "Git not found. Please install from https://git-scm.com/download/win")
+        Read-Host (T "按回车退出" "Press Enter to exit")
+        exit 1
+    }
+
+    Write-Cow (T "正在克隆 CowAgent 项目..." "Cloning CowAgent project...")
+    $cloneOk = $false
+
+    # Test GitHub connectivity before attempting clone
+    try {
+        $null = Invoke-WebRequest -Uri "https://github.com" -UseBasicParsing -TimeoutSec 5 -ErrorAction Stop
+        Write-Cow (T "GitHub 可达，正在从 GitHub 克隆..." "GitHub is reachable, cloning from GitHub...")
+        $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+        git clone --depth 10 --progress "https://github.com/zhayujie/CowAgent.git" 2>&1 | ForEach-Object { Write-Host $_ }
+        if ($LASTEXITCODE -eq 0) { $cloneOk = $true }
+        $ErrorActionPreference = $prevEAP
+        if (-not $cloneOk) {
+            if (Test-Path "CowAgent") { Remove-Item -Recurse -Force "CowAgent" }
+        }
+    } catch {}
+
+    if (-not $cloneOk) {
+        Write-Warn (T "GitHub 克隆失败或超时，切换到 Gitee 镜像..." "GitHub clone failed or timed out, switching to Gitee mirror...")
+        $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+        git clone --depth 10 --progress "https://gitee.com/zhayujie/CowAgent.git" 2>&1 | ForEach-Object { Write-Host $_ }
+        if ($LASTEXITCODE -eq 0) { $cloneOk = $true }
+        $ErrorActionPreference = $prevEAP
+        if (-not $cloneOk) {
+            if (Test-Path "CowAgent") { Remove-Item -Recurse -Force "CowAgent" }
+        }
+    }
+
+    if (-not $cloneOk) {
+        Write-Err (T "GitHub 和 Gitee 均克隆失败，请检查网络连接。" "Clone failed from both GitHub and Gitee. Please check your network connection.")
+        Write-Err (T "你也可以手动克隆: git clone https://gitee.com/zhayujie/CowAgent.git" "You can also manually clone: git clone https://gitee.com/zhayujie/CowAgent.git")
+        Read-Host (T "按回车退出" "Press Enter to exit")
+        exit 1
+    }
+
+    Set-Location "CowAgent"
+    $script:BaseDir = $PWD.Path
+    $script:IsProjectDir = $true
+    Write-Cow ((T "项目已克隆" "Project cloned") + ": $BaseDir")
+}
+
+# Test whether a URL is reachable within a short timeout. Uses a HEAD request
+# and hides progress so it never blocks the UI for long. Any failure (DNS, TLS,
+# timeout) just returns $false so the caller falls back gracefully.
+function Test-UrlReachable {
+    param([string]$Url, [int]$TimeoutSec = 4)
+    $oldPP = $ProgressPreference; $ProgressPreference = "SilentlyContinue"
+    try {
+        $null = Invoke-WebRequest -Uri $Url -Method Head -UseBasicParsing -TimeoutSec $TimeoutSec -ErrorAction Stop
+        return $true
+    } catch {
+        return $false
+    } finally {
+        $ProgressPreference = $oldPP
+    }
+}
+
+# Pick the pip index by install language, with the other as fallback:
+#   - zh users: Tsinghua mirror first, official PyPI fallback
+#   - others : official PyPI first, Tsinghua mirror fallback
+# Returns an args array to splat into pip (empty = pip default / official PyPI).
+function Get-PipMirrorArgs {
+    $tuna = "https://pypi.tuna.tsinghua.edu.cn/simple"
+    $pypi = "https://pypi.org/simple"
+    if ($script:UiLang -eq "zh") {
+        if (Test-UrlReachable "$tuna/") {
+            Write-Warn ((T "使用 pip 镜像" "Using pip mirror") + ": $tuna")
+            return @("-i", $tuna)
+        }
+    } else {
+        if ((-not (Test-UrlReachable "$pypi/")) -and (Test-UrlReachable "$tuna/")) {
+            Write-Warn ((T "使用 pip 镜像" "Using pip mirror") + ": $tuna")
+            return @("-i", $tuna)
+        }
+    }
+    return @()
+}
+
+# ── install dependencies ─────────────────────────────────────────
+function Install-Dependencies {
+    Write-Cow (T "正在安装依赖..." "Installing dependencies...")
+
+    # Probe the mirror first (with progress hidden so the slow IWR call doesn't
+    # leave the screen blank for too long).
+    $oldPP = $ProgressPreference; $ProgressPreference = "SilentlyContinue"
+    $pipMirror = Get-PipMirrorArgs
+    $ProgressPreference = $oldPP
+
+    # Keep pip output VISIBLE (do not pipe to Out-Null): on slow networks the
+    # download can take minutes, and a silent step looks like a hang.
+    $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+
+    Write-Info (T "正在升级 pip 等基础工具..." "Upgrading pip and basic tools...")
+    & $PythonCmd -m pip install --upgrade pip setuptools wheel @pipMirror
+
+    Write-Info (T "正在安装项目依赖（可能需要几分钟）..." "Installing project dependencies (may take a few minutes)...")
+    & $PythonCmd -m pip install -r "$BaseDir\requirements.txt" @pipMirror
+    $pipExit = $LASTEXITCODE
+    $ErrorActionPreference = $prevEAP
+    if ($pipExit -ne 0) {
+        Write-Warn (T "部分依赖可能有问题，但继续安装..." "Some dependencies may have issues, but continuing...")
+    }
+
+    Write-Cow (T "正在注册 cow CLI..." "Registering cow CLI...")
+    $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+    & $PythonCmd -m pip install -e $BaseDir @pipMirror 2>&1 | Out-Null
+    $ErrorActionPreference = $prevEAP
+
+    # Add the Scripts dir (where pip puts cow.exe) to PATH, both for this
+    # session and persistently, so `cow` keeps working after a reboot.
+    $scriptsDir = & $PythonCmd -c "import sysconfig; print(sysconfig.get_path('scripts'))" 2>$null
+    if ($scriptsDir -and (Test-Path $scriptsDir)) {
+        Add-ScriptsDirToPath $scriptsDir
+    }
+
+    $cowBin = Get-Command cow -ErrorAction SilentlyContinue
+    if ($cowBin) {
+        Write-Cow ((T "cow CLI 注册成功" "cow CLI registered") + ": $($cowBin.Source)")
+    } else {
+        Write-Warn ((T "cow CLI 不在 PATH 中，你可以使用" "cow CLI not in PATH. You can use") + ": $PythonCmd -m cli.cli")
+    }
+}
+
+# Add the Python Scripts dir to PATH for this session and persist it to the
+# user PATH (User scope needs no admin rights), so `cow` survives a reboot.
+function Add-ScriptsDirToPath {
+    param([string]$ScriptsDir)
+
+    if ($env:PATH -notlike "*$ScriptsDir*") {
+        $env:PATH = "$ScriptsDir;$env:PATH"
+    }
+
+    # Persist to the User PATH only if missing from BOTH User and Machine scopes
+    # (checking Machine avoids a duplicate when Python is installed for all
+    # users). Read raw scope values, not the already-merged $env:PATH.
+    try {
+        $target = $ScriptsDir.TrimEnd('\')
+        $userPath = [Environment]::GetEnvironmentVariable("Path", "User")
+        $machinePath = ""
+        try { $machinePath = [Environment]::GetEnvironmentVariable("Path", "Machine") } catch {}
+
+        $allParts = @()
+        foreach ($p in @($userPath, $machinePath)) {
+            if ($p) { $allParts += ($p -split ';' | Where-Object { $_ -ne "" }) }
+        }
+        $already = $allParts | Where-Object { $_.TrimEnd('\') -ieq $target }
+        if (-not $already) {
+            $newPath = if ($userPath) { "$userPath;$ScriptsDir" } else { $ScriptsDir }
+            [Environment]::SetEnvironmentVariable("Path", $newPath, "User")
+            Write-Cow ((T "已将 cow 命令目录加入用户 PATH（重启后仍可用）" "Added cow command directory to user PATH (persists after reboot)") + ": $ScriptsDir")
+        }
+    } catch {
+        Write-Warn (T "无法自动写入持久化 PATH，重启后可能需要重新配置。" "Could not persist PATH automatically; you may need to reconfigure after reboot.")
+    }
+}
+
+# ── model selection ──────────────────────────────────────────────
+# Order mirrors run.sh: DeepSeek, Claude, Gemini, OpenAI, MiniMax, Zhipu,
+# Qwen, Doubao, Kimi, LinkAI, then Skip (11th option).
+# Each entry: Provider / default model name / config key field / optional base.
+$ModelChoices = @{
+    1  = @{ Provider = "DeepSeek";                Default = "deepseek-v4-flash";                   Field = "deepseek_api_key" }
+    2  = @{ Provider = "Claude";                  Default = "claude-opus-4-8";                     Field = "claude_api_key";    BaseField = "claude_api_base" }
+    3  = @{ Provider = "Gemini";                  Default = "gemini-3.1-pro-preview";              Field = "gemini_api_key";    BaseField = "gemini_api_base" }
+    4  = @{ Provider = "OpenAI";                  Default = "gpt-5.5";                             Field = "open_ai_api_key";   BaseField = "open_ai_api_base" }
+    5  = @{ Provider = "MiniMax";                 Default = "MiniMax-M3";                          Field = "minimax_api_key" }
+    6  = @{ Provider = "GLM";                     Default = "glm-5.2";                             Field = "zhipu_ai_api_key" }
+    7  = @{ Provider = "Qwen (DashScope)";        Default = "qwen3.7-plus";                        Field = "dashscope_api_key" }
+    8  = @{ Provider = "Doubao (Volcengine Ark)"; Default = "doubao-seed-2-1-pro-260628"; Field = "ark_api_key" }
+    9  = @{ Provider = "Kimi (Moonshot)";         Default = "kimi-k2.7-code";                      Field = "moonshot_api_key" }
+    10 = @{ Provider = "MiMo";                    Default = "mimo-v2.5-pro";                       Field = "mimo_api_key" }
+    11 = @{ Provider = "LinkAI";                  Default = "deepseek-v4-flash";                   Field = "linkai_api_key";    Linkai = $true }
+}
+
+function Select-Model {
+    Write-Host ""
+    $title = T "选择 AI 模型" "Select AI Model"
+    $options = @(
+        "DeepSeek (deepseek-v4-flash, deepseek-v4-pro, etc.)",
+        "Claude (claude-opus-4-8, claude-fable-5, etc.)",
+        "Gemini (gemini-3.5-flash, gemini-3.1-pro-preview, etc.)",
+        "OpenAI (gpt-5.5, etc.)",
+        "MiniMax (MiniMax-M3, etc.)",
+        "GLM (glm-5.2, etc.)",
+        "Qwen (qwen3.7-plus, qwen3.7-max, etc.)",
+        "Doubao (doubao-seed-2.1, etc.)",
+        "Kimi (kimi-k2.7-code, etc.)",
+        "MiMo (mimo-v2.5-pro, etc.)",
+        ("LinkAI (" + (T "一个 Key 接入所有模型" "access all models via one API") + ")"),
+        (T "⏭  跳过（稍后在 Web 控制台配置）" "⏭  Skip (configure later in the web console)")
+    )
+    $script:ModelChoice = Select-Menu -Title $title -Options $options -Default 1
+}
+
+# Configure model. Only ask for the API key; model name and base default to
+# sensible values and can be changed later in the web console.
+function Configure-Model {
+    # Reset model-related state
+    $script:ModelName    = ""
+    $script:ModelField   = ""
+    $script:ApiKey       = ""
+    $script:ApiBase      = ""
+    $script:ApiBaseField = ""
+    $script:UseLinkai    = $false
+
+    if ($script:ModelChoice -eq 12) {
+        # Skip: leave model unset, will be configured in the web console.
+        Write-Warn (T "已跳过模型配置，稍后可在 Web 控制台填写" "Model configuration skipped, you can set it later in the web console")
+        return
+    }
+
+    $m = $ModelChoices[$script:ModelChoice]
+    Write-Cow ((T "正在配置" "Configuring") + " $($m.Provider)...")
+    # Show where to obtain a LinkAI key.
+    if ($m.Linkai) {
+        Write-Info ((T "获取 LinkAI Key" "Get your LinkAI Key") + ": https://link-ai.tech/console/interface")
+    }
+    $hint = T "回车跳过，稍后在 Web 控制台填写" "press Enter to skip, set later in web console"
+    $script:ApiKey     = Read-Host ((T "请输入" "Enter") + " $($m.Provider) API Key ($hint)")
+    $script:ModelName  = $m.Default
+    $script:ModelField = $m.Field
+    if ($m.BaseField) { $script:ApiBaseField = $m.BaseField }
+    if ($m.Linkai)    { $script:UseLinkai = $true }
+}
+
+# ── channel selection ────────────────────────────────────────────
+# Channel label by stable key (independent of menu order).
+function Get-ChannelLabel {
+    param([string]$Key)
+    switch ($Key) {
+        "web"           { return (T "Web 网页控制台（推荐，开箱即用）" "Web Console (recommended, ready to use)") }
+        "weixin"        { return (T "微信 Weixin" "Wechat") }
+        "feishu"        { return (T "飞书 Feishu" "Feishu") }
+        "dingtalk"      { return (T "钉钉 DingTalk" "DingTalk") }
+        "wecom_bot"     { return (T "企微智能机器人 WeCom Bot" "WeCom Bot") }
+        "qq"            { return "QQ" }
+        "wechatcom_app" { return (T "企微自建应用 WeCom App" "WeCom App") }
+        "telegram"      { return "Telegram" }
+        "slack"         { return "Slack" }
+        "discord"       { return "Discord" }
+        "skip"          { return (T "⏭  跳过（稍后在 Web 控制台配置）" "⏭  Skip (configure later in the web console)") }
+    }
+}
+
+# Select channel. The display order depends on the install language:
+#   - English: Web first, then the global IM channels (Telegram/Discord/Slack),
+#     then the China-focused channels.
+#   - Chinese: Web first, then China-focused channels, then global ones.
+# A stable key list decouples the menu order from the config logic.
+function Select-Channel {
+    Write-Host ""
+    $title = T "选择接入渠道" "Select Communication Channel"
+    if ($script:UiLang -eq "en") {
+        $script:ChannelKeys = @("web", "telegram", "discord", "slack", "weixin", "feishu", "dingtalk", "wecom_bot", "qq", "wechatcom_app", "skip")
+    } else {
+        $script:ChannelKeys = @("web", "weixin", "feishu", "dingtalk", "wecom_bot", "qq", "wechatcom_app", "telegram", "slack", "discord", "skip")
+    }
+    $options = @($script:ChannelKeys | ForEach-Object { Get-ChannelLabel $_ })
+    $idx = Select-Menu -Title $title -Options $options -Default 1
+    # Map the 1-based menu position back to the stable channel key.
+    $script:ChannelChoice = $script:ChannelKeys[$idx - 1]
+}
+
+# Configure channel, dispatched by stable channel key (not menu position).
+function Configure-Channel {
+    $script:ChannelExtra = @{}
+    $script:AccessInfo = ""
+
+    switch ($script:ChannelChoice) {
+        { $_ -eq "web" -or $_ -eq "skip" } {
+            # Web (also the default when skipped). Default port, no prompt.
+            $script:ChannelType = "web"
+            $script:ChannelExtra["web_port"] = 9899
+            $script:AccessInfo = (T "Web 控制台地址" "Web console") + " : http://localhost:9899/chat"
+        }
+        "weixin" {
+            $script:ChannelType = "weixin"
+            $script:AccessInfo = T "微信渠道已配置，请在终端或 Web 控制台扫码登录" "Weixin channel configured. Scan QR code in terminal or web console to login."
+        }
+        "feishu" {
+            $script:ChannelType = "feishu"
+            Write-Cow (T "配置飞书（WebSocket 模式）..." "Configure Feishu (WebSocket mode)...")
+            $script:ChannelExtra["feishu_app_id"]     = Read-Host (T "请输入飞书 App ID" "Enter Feishu App ID")
+            $script:ChannelExtra["feishu_app_secret"] = Read-Host (T "请输入飞书 App Secret" "Enter Feishu App Secret")
+            $script:ChannelExtra["feishu_event_mode"] = "websocket"
+            $script:AccessInfo = T "飞书渠道已配置（WebSocket 模式）" "Feishu channel configured (WebSocket mode)"
+        }
+        "dingtalk" {
+            $script:ChannelType = "dingtalk"
+            Write-Cow (T "配置钉钉..." "Configure DingTalk...")
+            $script:ChannelExtra["dingtalk_client_id"]     = Read-Host (T "请输入钉钉 Client ID" "Enter DingTalk Client ID")
+            $script:ChannelExtra["dingtalk_client_secret"] = Read-Host (T "请输入钉钉 Client Secret" "Enter DingTalk Client Secret")
+            $script:AccessInfo = T "钉钉渠道已配置" "DingTalk channel configured"
+        }
+        "wecom_bot" {
+            $script:ChannelType = "wecom_bot"
+            Write-Cow (T "配置企微智能机器人..." "Configure WeCom Bot...")
+            $script:ChannelExtra["wecom_bot_id"]     = Read-Host (T "请输入 WeCom Bot ID" "Enter WeCom Bot ID")
+            $script:ChannelExtra["wecom_bot_secret"] = Read-Host (T "请输入 WeCom Bot Secret" "Enter WeCom Bot Secret")
+            $script:AccessInfo = T "企微智能机器人渠道已配置" "WeCom Bot channel configured"
+        }
+        "qq" {
+            $script:ChannelType = "qq"
+            Write-Cow (T "配置 QQ 机器人..." "Configure QQ Bot...")
+            $script:ChannelExtra["qq_app_id"]     = Read-Host (T "请输入 QQ App ID" "Enter QQ App ID")
+            $script:ChannelExtra["qq_app_secret"] = Read-Host (T "请输入 QQ App Secret" "Enter QQ App Secret")
+            $script:AccessInfo = T "QQ 机器人渠道已配置" "QQ Bot channel configured"
+        }
+        "wechatcom_app" {
+            $script:ChannelType = "wechatcom_app"
+            Write-Cow (T "配置企微自建应用..." "Configure WeCom App...")
+            $script:ChannelExtra["wechatcom_corp_id"]     = Read-Host (T "请输入企业 Corp ID" "Enter WeChat Corp ID")
+            $script:ChannelExtra["wechatcomapp_token"]    = Read-Host (T "请输入应用 Token" "Enter WeChat Com App Token")
+            $script:ChannelExtra["wechatcomapp_secret"]   = Read-Host (T "请输入应用 Secret" "Enter WeChat Com App Secret")
+            $script:ChannelExtra["wechatcomapp_agent_id"] = Read-Host (T "请输入应用 Agent ID" "Enter WeChat Com App Agent ID")
+            $script:ChannelExtra["wechatcomapp_aes_key"]  = Read-Host (T "请输入应用 AES Key" "Enter WeChat Com App AES Key")
+            $port = Read-Host ((T "请输入应用端口" "Enter port") + " [" + (T "默认" "default") + ": 9898]")
+            if (-not ($port -match '^\d+$')) { $port = "9898" }
+            $script:ChannelExtra["wechatcomapp_port"] = [int]$port
+            $script:AccessInfo = (T "企微自建应用渠道已配置，端口" "WeCom App channel configured on port") + " $port"
+        }
+        "telegram" {
+            $script:ChannelType = "telegram"
+            Write-Cow (T "配置 Telegram..." "Configure Telegram...")
+            $script:ChannelExtra["telegram_token"] = Read-Host (T "请输入 Telegram Bot Token" "Enter Telegram Bot Token")
+            $script:AccessInfo = T "Telegram 渠道已配置" "Telegram channel configured"
+        }
+        "slack" {
+            $script:ChannelType = "slack"
+            Write-Cow (T "配置 Slack..." "Configure Slack...")
+            $script:ChannelExtra["slack_bot_token"] = Read-Host ((T "请输入 Slack Bot Token" "Enter Slack Bot Token") + " (xoxb-...)")
+            $script:ChannelExtra["slack_app_token"] = Read-Host ((T "请输入 Slack App Token" "Enter Slack App Token") + " (xapp-...)")
+            $script:AccessInfo = T "Slack 渠道已配置" "Slack channel configured"
+        }
+        "discord" {
+            $script:ChannelType = "discord"
+            Write-Cow (T "配置 Discord..." "Configure Discord...")
+            $script:ChannelExtra["discord_token"] = Read-Host (T "请输入 Discord Bot Token" "Enter Discord Bot Token")
+            $script:AccessInfo = T "Discord 渠道已配置" "Discord channel configured"
+        }
+    }
+}
+
+# ── generate config.json ─────────────────────────────────────────
+function New-ConfigFile {
+    Write-Cow (T "正在生成 config.json..." "Generating config.json...")
+
+    $config = [ordered]@{
+        channel_type              = if ($script:ChannelType) { $script:ChannelType } else { "web" }
+        model                     = if ($script:ModelName)  { $script:ModelName }  else { "" }
+        cow_lang                  = if ($script:InstallLang) { $script:InstallLang } else { "auto" }
+        open_ai_api_key           = ""
+        open_ai_api_base          = "https://api.openai.com/v1"
+        claude_api_key            = ""
+        claude_api_base           = "https://api.anthropic.com/v1"
+        gemini_api_key            = ""
+        gemini_api_base           = "https://generativelanguage.googleapis.com"
+        zhipu_ai_api_key          = ""
+        moonshot_api_key          = ""
+        ark_api_key               = ""
+        dashscope_api_key         = ""
+        minimax_api_key           = ""
+        mimo_api_key              = ""
+        deepseek_api_key          = ""
+        deepseek_api_base         = "https://api.deepseek.com/v1"
+        # Leave ASR/TTS provider empty so the web console auto-suggests the
+        # vendor whose API key is actually configured (e.g. LinkAI), instead
+        # of always defaulting to OpenAI.
+        voice_to_text             = ""
+        text_to_voice             = ""
+        voice_reply_voice         = $false
+        speech_recognition        = $true
+        group_speech_recognition  = $false
+        use_linkai                = [bool]$script:UseLinkai
+        linkai_api_key            = ""
+        linkai_app_code           = ""
+        agent                     = $true
+        agent_max_context_tokens  = 50000
+        agent_max_context_turns   = 20
+        agent_max_steps           = 20
+        # New installs opt into self-evolution (matches run.sh).
+        self_evolution_enabled    = $true
+    }
+
+    # Set the API key into the right field (skipped models leave it empty).
+    if ($script:ModelField -and $config.Contains($script:ModelField)) {
+        $config[$script:ModelField] = $script:ApiKey
+    }
+    # Set API base if the model has a configurable base and the user changed it.
+    if ($script:ApiBase -and $script:ApiBaseField -and $config.Contains($script:ApiBaseField)) {
+        $config[$script:ApiBaseField] = $script:ApiBase
+    }
+
+    # Merge channel-specific fields
+    foreach ($k in $script:ChannelExtra.Keys) {
+        $config[$k] = $script:ChannelExtra[$k]
+    }
+
+    $jsonText = $config | ConvertTo-Json -Depth 5
+    [System.IO.File]::WriteAllText("$BaseDir\config.json", $jsonText, (New-Object System.Text.UTF8Encoding $false))
+    Write-Cow (T "配置文件创建成功。" "Configuration file created.")
+}
+
+# Resolve the `cow` command, self-healing PATH if needed. When `cow` is missing
+# (e.g. an older install whose PATH was never persisted), locate the Scripts dir,
+# re-add it to PATH (session + persistent), and retry. Returns $true if callable.
+function Resolve-CowCommand {
+    if (Get-Command cow -ErrorAction SilentlyContinue) { return $true }
+
+    $py = if ($PythonCmd) { $PythonCmd } else { Find-Python }
+    if ($py) {
+        $scriptsDir = & $py -c "import sysconfig; print(sysconfig.get_path('scripts'))" 2>$null
+        if ($scriptsDir -and (Test-Path "$scriptsDir\cow.exe")) {
+            Add-ScriptsDirToPath $scriptsDir
+            if (Get-Command cow -ErrorAction SilentlyContinue) { return $true }
+        }
+    }
+    return $false
+}
+
+# ── start via cow CLI ─────────────────────────────────────────────
+function Start-CowAgent {
+    Write-Cow (T "正在启动 CowAgent..." "Starting CowAgent...")
+    if (Resolve-CowCommand) {
+        & cow start
+    } else {
+        Write-Warn (T "未找到 cow CLI，直接启动..." "cow CLI not found, starting directly...")
+        & $PythonCmd "$BaseDir\app.py"
+    }
+}
+
+# ── delegate management commands to cow CLI ──────────────────────
+function Invoke-CowCommand {
+    param([string]$Cmd)
+    if (Resolve-CowCommand) {
+        & cow $Cmd
+    } else {
+        # Fall back to the module entrypoint so management commands still work
+        # even when cow.exe isn't on PATH (e.g. right after a fresh reboot on
+        # an older install).
+        $py = if ($PythonCmd) { $PythonCmd } else { Find-Python }
+        if ($py -and (Test-Path "$BaseDir\app.py")) {
+            Write-Warn (T "未找到 cow 命令，使用 python -m cli.cli 兜底运行..." "cow command not found, falling back to python -m cli.cli...")
+            Push-Location $BaseDir
+            try { & $py -m cli.cli $Cmd } finally { Pop-Location }
+        } else {
+            Write-Err (T "未找到 cow CLI，请先不带参数运行本脚本进行安装。" "cow CLI not found. Run this script without arguments first to install.")
+            exit 1
+        }
+    }
+}
+
+# ── usage ─────────────────────────────────────────────────────────
+function Show-Usage {
+    Write-Info "========================================="
+    Write-Info "   CowAgent Management Script (Windows)"
+    Write-Info "========================================="
+    Write-Host ""
+    Write-Host (T "用法:" "Usage:")
+    Write-Host ("  .\run.ps1               # " + (T "安装 / 配置" "Install / Configure"))
+    Write-Host ("  .\run.ps1 <command>     # " + (T "管理命令" "Management command"))
+    Write-Host ""
+    Write-Host (T "命令:" "Commands:")
+    Write-Host ("  start      " + (T "启动服务" "Start the service"))
+    Write-Host ("  stop       " + (T "停止服务" "Stop the service"))
+    Write-Host ("  restart    " + (T "重启服务" "Restart the service"))
+    Write-Host ("  status     " + (T "查看状态" "Check service status"))
+    Write-Host ("  logs       " + (T "查看日志" "View logs"))
+    Write-Host ("  config     " + (T "重新配置项目" "Reconfigure project"))
+    Write-Host ("  update     " + (T "更新并重启" "Update and restart"))
+    Write-Host ("  help       " + (T "显示本帮助" "Show this message"))
+    Write-Host ""
+}
+
+# ── install mode ──────────────────────────────────────────────────
+function Install-Mode {
+    Clear-Host
+    Write-Info "========================================="
+    Write-Info "   CowAgent Installation (Windows)"
+    Write-Info "========================================="
+    Write-Host ""
+
+    # Step 0: choose the install/UI language. Everything after this is localized.
+    Select-Language
+    Write-Host ""
+
+    if ($IsProjectDir) {
+        Write-Cow (T "检测到已有项目目录。" "Detected existing project directory.")
+        if (Test-Path "$BaseDir\config.json") {
+            Write-Cow (T "项目已配置。" "Project already configured.")
+            Write-Host ""
+            Show-Usage
+            return
+        }
+        Write-Warn (T "未找到 config.json，开始配置项目！" "No config.json found. Let's configure your project!")
+        Write-Host ""
+        Assert-Python
+    } else {
+        Assert-Python
+        Install-Project
+    }
+
+    Install-Dependencies
+    Select-Model
+    Configure-Model
+    Select-Channel
+    Configure-Channel
+    New-ConfigFile
+
+    # Auto-start after configuration for a true out-of-the-box experience.
+    Write-Host ""
+    if ($script:AccessInfo) { Write-Cow $script:AccessInfo }
+    Write-Warn (T "提示：需要让 Agent 浏览网页时，运行 cow install-browser 安装浏览器工具" "Tip: to let the Agent browse the web, run 'cow install-browser' to install the browser tool")
+    Start-CowAgent
+}
+
+# ── update ────────────────────────────────────────────────────────
+function Update-Project {
+    Write-Cow (T "正在更新 CowAgent..." "Updating CowAgent...")
+    Set-Location $BaseDir
+
+    # Stop if running
+    $cowBin = Get-Command cow -ErrorAction SilentlyContinue
+    if ($cowBin) {
+        $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+        & cow stop 2>&1 | Out-Null
+        $ErrorActionPreference = $prevEAP
+    }
+
+    if (Test-Path "$BaseDir\.git") {
+        Write-Cow (T "正在拉取最新代码..." "Pulling latest code...")
+        $prevEAP = $ErrorActionPreference; $ErrorActionPreference = "Continue"
+        git pull 2>&1 | Out-Null
+        $pullExit = $LASTEXITCODE
+        $ErrorActionPreference = $prevEAP
+        if ($pullExit -ne 0) {
+            Write-Warn (T "GitHub 拉取失败，尝试 Gitee..." "GitHub failed, trying Gitee...")
+            $ErrorActionPreference = "Continue"
+            git remote set-url origin https://gitee.com/zhayujie/CowAgent.git 2>&1 | Out-Null
+            git pull 2>&1 | Out-Null
+            $ErrorActionPreference = $prevEAP
+        }
+    } else {
+        Write-Warn (T "非 git 仓库，跳过代码更新。" "Not a git repository, skipping code update.")
+    }
+
+    Assert-Python
+    Install-Dependencies
+
+    # Start via python -m cli.cli instead of cow.exe, because the exe may
+    # still be cached/locked from the previous installation on Windows.
+    Write-Cow (T "正在启动 CowAgent..." "Starting CowAgent...")
+    & $PythonCmd -m cli.cli start
+}
+
+# ── main ──────────────────────────────────────────────────────────
+Initialize-UiLang
+
+switch ($Command.ToLower()) {
+    ""        { Install-Mode }
+    "start"   { Invoke-CowCommand "start" }
+    "stop"    { Invoke-CowCommand "stop" }
+    "restart" { Invoke-CowCommand "restart" }
+    "status"  { Invoke-CowCommand "status" }
+    "logs"    { Invoke-CowCommand "logs" }
+    "config"  {
+        Assert-Python
+        Install-Dependencies
+        Select-Model
+        Configure-Model
+        Select-Channel
+        Configure-Channel
+        New-ConfigFile
+        $r = Read-Host (T "现在重启服务吗？[Y/n]" "Restart service now? [Y/n]")
+        if ($r -ne "n" -and $r -ne "N") { Invoke-CowCommand "restart" }
+    }
+    "update"  { Update-Project }
+    "help"    { Show-Usage }
+    default   {
+        Write-Err ((T "未知命令" "Unknown command") + ": $Command")
+        Show-Usage
+        exit 1
+    }
+}
diff --git a/scripts/shutdown.sh b/scripts/shutdown.sh
new file mode 100755
index 0000000..c2bf6b1
--- /dev/null
+++ b/scripts/shutdown.sh
@@ -0,0 +1,16 @@
+#!/bin/bash
+
+#关闭服务
+cd `dirname $0`/..
+export BASE_DIR=`pwd`
+pid=`ps ax | grep -i app.py | grep "${BASE_DIR}" | grep python3 | grep -v grep | awk '{print $1}'`
+if [ -z "$pid" ] ; then
+        echo "No chatgpt-on-wechat running."
+        exit -1;
+fi
+
+echo "The chatgpt-on-wechat(${pid}) is running..."
+
+kill ${pid}
+
+echo "Send shutdown request to chatgpt-on-wechat(${pid}) OK"
diff --git a/scripts/start.sh b/scripts/start.sh
new file mode 100755
index 0000000..3037eb5
--- /dev/null
+++ b/scripts/start.sh
@@ -0,0 +1,16 @@
+#!/bin/bash
+#后台运行Chat_on_webchat执行脚本
+
+cd `dirname $0`/..
+export BASE_DIR=`pwd`
+echo $BASE_DIR
+
+# check the nohup.out log output file
+if [ ! -f "${BASE_DIR}/nohup.out" ]; then
+  touch "${BASE_DIR}/nohup.out"
+echo "create file  ${BASE_DIR}/nohup.out"
+fi
+
+nohup python3 "${BASE_DIR}/app.py" & tail -f "${BASE_DIR}/nohup.out"
+
+echo "Chat_on_webchat is starting，you can check the ${BASE_DIR}/nohup.out"
diff --git a/scripts/tout.sh b/scripts/tout.sh
new file mode 100755
index 0000000..ffe6de3
--- /dev/null
+++ b/scripts/tout.sh
@@ -0,0 +1,14 @@
+#!/bin/bash
+#打开日志
+
+cd `dirname $0`/..
+export BASE_DIR=`pwd`
+echo $BASE_DIR
+
+# check the nohup.out log output file
+if [ ! -f "${BASE_DIR}/nohup.out" ]; then
+   echo "No file  ${BASE_DIR}/nohup.out"
+   exit -1;
+fi
+
+tail -f "${BASE_DIR}/nohup.out"
diff --git a/skills/README.md b/skills/README.md
new file mode 100644
index 0000000..78d88c3
--- /dev/null
+++ b/skills/README.md
@@ -0,0 +1,89 @@
+# Skills
+
+Skills are reusable instruction sets that extend the agent's capabilities. Each skill is a `SKILL.md` file in its own directory, providing specialized knowledge, workflows, and tool integrations for specific tasks.
+
+## Skill Hub
+
+Browse, search, and install skills from [Cow Skill Hub](https://skills.cowagent.ai/).
+
+Open source: [github.com/zhayujie/cow-skill-hub](https://github.com/zhayujie/cow-skill-hub)
+
+## Install Skills
+
+Install skills from multiple sources via chat (`/skill`) or terminal (`cow skill`):
+
+```bash
+/skill install <name>                   # From Skill Hub
+/skill install <owner>/<repo>           # From GitHub
+/skill install clawhub:<name>           # From ClawHub
+/skill install linkai:<code>            # From LinkAI
+/skill install <url>                    # From URL (zip or SKILL.md)
+```
+
+List all available remote skills:
+
+```bash
+/skill list --remote
+```
+
+## Manage Skills
+
+```bash
+/skill list                  # List installed skills
+/skill info <name>           # View skill details
+/skill enable <name>         # Enable a skill
+/skill disable <name>        # Disable a skill
+/skill uninstall <name>      # Uninstall a skill
+```
+
+> In terminal, replace `/skill` with `cow skill`.
+
+## Skill Structure
+
+```
+skills/
+  my-skill/
+    SKILL.md          # Required: skill definition
+    scripts/          # Optional: bundled scripts
+    resources/        # Optional: reference files
+```
+
+`SKILL.md` uses YAML frontmatter:
+
+```markdown
+---
+name: my-skill
+description: Brief description of what the skill does
+metadata: {"cow":{"emoji":"🔧","requires":{"bins":["tool"],"env":["API_KEY"]}}}
+---
+
+# My Skill
+
+Instructions, examples, and usage patterns...
+```
+
+### Frontmatter Fields
+
+| Field | Description |
+|---|---|
+| `name` | Skill name (must match directory name) |
+| `description` | Brief description (required) |
+| `metadata.cow.emoji` | Display emoji |
+| `metadata.cow.always` | Always include this skill (default: false) |
+| `metadata.cow.requires.bins` | Required binaries |
+| `metadata.cow.requires.env` | Required environment variables |
+| `metadata.cow.requires.config` | Required config paths |
+| `metadata.cow.os` | Supported OS (e.g., `["darwin", "linux"]`) |
+
+## Skill Loading Order
+
+Skills are loaded from two locations (higher precedence overrides lower):
+
+1. **Builtin skills** (lower): `<project_root>/skills/` — shipped with the codebase
+2. **Custom skills** (higher): `~/cow/skills/` — installed via `cow skill install` or skill creator
+
+Skills with the same name in the custom directory override builtin ones.
+
+## Create & Contribute
+
+See the [Skill Creation docs](https://docs.cowagent.ai/skills/create) for details, or submit your skill to [Skill Hub](https://skills.cowagent.ai/submit).
diff --git a/skills/image-generation/SKILL.md b/skills/image-generation/SKILL.md
new file mode 100644
index 0000000..d260162
--- /dev/null
+++ b/skills/image-generation/SKILL.md
@@ -0,0 +1,117 @@
+---
+name: image-generation
+description: Generate or edit images from text prompts. Use when the user asks to create, draw, design, or edit an image, illustration, photo, icon, poster, or any visual content.
+metadata:
+  cowagent:
+    requires:
+      anyEnv:
+        - OPENAI_API_KEY
+        - GEMINI_API_KEY
+        - ARK_API_KEY
+        - DASHSCOPE_API_KEY
+        - MINIMAX_API_KEY
+        - LINKAI_API_KEY
+---
+
+# Image Generation
+
+Generate and edit images using AI models. The script automatically picks a backend based on which API keys are configured — **you don't need to specify a model unless the user explicitly names one**.
+
+Supported models (passed via `model` only when the user asks for a specific one):
+
+- **OpenAI** — `gpt-image-2`, `gpt-image-1`
+- **Gemini Nano Banana** — `nano-banana-2`, `nano-banana-pro`, `nano-banana`
+- **Seedream (Volcengine Ark)** — `seedream-5.0-lite`, `seedream-4.5`
+- **Qwen (DashScope)** — `qwen-image-2.0`, `qwen-image-2.0-pro`
+- **MiniMax** — `image-01`
+
+## Usage
+
+Run `scripts/generate.py` with a JSON argument. The path is relative to this skill's `base_dir`.
+
+```bash
+python <base_dir>/scripts/generate.py '<json_args>'
+```
+
+**Set bash timeout to at least 600 seconds**, as image generation can take 30–200s per provider, and the script may try multiple providers sequentially.
+
+### Parameters
+
+| Parameter | Type | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `prompt` | string | yes | — | Image description |
+| `image_url` | string / list | no | null | Input image(s) for editing: local file path or URL. Multi-image fusion is supported (pass a list) |
+| `quality` | string | no | auto | `low` / `medium` / `high` (only some backends honour this) |
+| `size` | string | no | auto | `512` / `1K` / `2K` / `3K` / `4K`, or pixel value (`1024x1024`) |
+| `aspect_ratio` | string | no | null | `1:1` / `3:2` / `2:3` / `16:9` / `9:16` / `21:9` (some backends also support extreme ratios like `1:4` / `8:1`) |
+
+**Higher `quality` and larger `size` cost more and run slower.** In normal cases, when the user does not explicitly specify, `low` or `medium` is sufficient. Only use `high` when the user asks for it.
+
+### Example — generate
+
+```bash
+python <base_dir>/scripts/generate.py '{"prompt": "A corgi astronaut floating in space"}'
+```
+
+With aspect ratio:
+
+```bash
+python <base_dir>/scripts/generate.py '{"prompt": "Isometric miniature city of Shanghai at sunset", "size": "2K", "aspect_ratio": "16:9"}'
+```
+
+### Important: Editing vs Generating
+
+When the user asks to **edit, modify, or improve an existing image**, pass the original image via `image_url`. Prefer **local file paths** directly — the script handles file reading internally. Without `image_url`, the script generates a brand-new image instead of editing.
+
+### Example — edit (image-to-image)
+
+```bash
+python <base_dir>/scripts/generate.py '{"prompt": "Add a Santa hat to the dog", "image_url": "/path/to/dog.png"}'
+```
+
+Multi-image fusion — pass a list:
+
+```bash
+python <base_dir>/scripts/generate.py '{"prompt": "Combine these characters into a group photo", "image_url": ["/path/a.png", "/path/b.png"]}'
+```
+
+### Output
+
+Prints JSON to stdout:
+
+```json
+{
+  "model": "doubao-seedream-5-0-260128",
+  "images": [
+    {"url": "/path/to/output.png"}
+  ]
+}
+```
+
+After success, display the image to the user. You can either embed it in markdown (`![description](/path/to/output.png)`) or use the `send` tool.
+
+On error:
+
+```json
+{
+  "error": "error message"
+}
+```
+
+### Setup
+
+The script needs **at least one** of these API keys (set via `env_config` or `config.json`):
+
+`OPENAI_API_KEY` / `GEMINI_API_KEY` / `ARK_API_KEY` / `DASHSCOPE_API_KEY` / `MINIMAX_API_KEY` / `LINKAI_API_KEY`
+
+Each also has an optional `*_API_BASE` for custom endpoints. The script automatically picks the first configured backend and falls back to the next if it fails — no need to specify a model.
+
+### Error Handling
+
+If the script returns an error after trying all configured backends, **do NOT retry with the same parameters** — the failure is almost always a configuration issue (wrong API key, unsupported API base). Tell the user to fix it via `env_config`, then retry.
+
+### Notes
+
+- HTTP timeout is 300s — high-resolution generation can take over 200s.
+- Omit `quality` / `size` to let the model pick automatically (`auto`).
+- Input images for editing are auto-compressed to ≤ 4MB / longest edge ≤ 4096px.
diff --git a/skills/image-generation/scripts/generate.py b/skills/image-generation/scripts/generate.py
new file mode 100644
index 0000000..23d05fd
--- /dev/null
+++ b/skills/image-generation/scripts/generate.py
@@ -0,0 +1,1204 @@
+#!/usr/bin/env python3
+"""
+Unified image generation script.
+
+Usage:
+    python generate.py '<json_args>'
+
+Supported model families (each provider is tried in priority order:
+OpenAI → Gemini → Seedream → Qwen → MiniMax → LinkAI; missing API keys
+are skipped, and the provider that natively owns the requested model is
+promoted to the front of the queue):
+
+    - gpt-image-2 / gpt-image-1                    → OpenAI
+    - nano-banana / gemini-*-image-*               → Gemini
+    - doubao-seedream-* / seedream-*               → Seedream (Volcengine Ark)
+    - qwen-image-2.0 / qwen-image-2.0-pro / etc.   → Qwen (DashScope)
+    - image-01 / minimax-image                     → MiniMax
+    - any model                                    → LinkAI (universal proxy)
+
+Dependencies: requests (stdlib: json, sys, os, base64, io, abc, uuid, pathlib, urllib)
+"""
+
+import json
+import sys
+import os
+import base64
+import io
+import time
+import uuid
+import re
+from abc import ABC, abstractmethod
+from pathlib import Path
+from urllib.request import urlopen, Request
+from urllib.parse import urlparse
+from urllib.error import URLError
+
+try:
+    import requests
+
+    _HAS_REQUESTS = True
+except ImportError:
+    _HAS_REQUESTS = False
+
+
+# ---------------------------------------------------------------------------
+# Size / aspect-ratio resolution
+# ---------------------------------------------------------------------------
+
+_SIZE_TABLE = {
+    # (tier, ratio) -> "WxH"
+    ("1K", "1:1"): "1024x1024",
+    ("1K", "3:2"): "1536x1024",
+    ("1K", "2:3"): "1024x1536",
+    ("2K", "1:1"): "2048x2048",
+    ("2K", "16:9"): "2048x1152",
+    ("2K", "9:16"): "1152x2048",
+    ("4K", "16:9"): "3840x2160",
+    ("4K", "9:16"): "2160x3840",
+}
+
+_TIER_ORDER = ["1K", "2K", "4K"]
+_RATIO_DEFAULT = {"1K": "1:1", "2K": "1:1", "4K": "16:9"}
+
+_PIXEL_RE = re.compile(r"^\d+x\d+$")
+
+
+def resolve_size(size: str | None, aspect_ratio: str | None) -> str | None:
+    """Resolve (size, aspect_ratio) to a concrete 'WxH' string or None."""
+    if size and _PIXEL_RE.match(size):
+        return size
+    if size and size.lower() == "auto":
+        size = None
+    if not size and not aspect_ratio:
+        return None
+
+    tier = size.upper() if size else None
+    ratio = aspect_ratio
+
+    if tier and ratio:
+        key = (tier, ratio)
+        if key in _SIZE_TABLE:
+            return _SIZE_TABLE[key]
+        # Upgrade: try higher tiers with same ratio
+        start = _TIER_ORDER.index(tier) + 1 if tier in _TIER_ORDER else 0
+        for t in _TIER_ORDER[start:]:
+            if (t, ratio) in _SIZE_TABLE:
+                return _SIZE_TABLE[(t, ratio)]
+        # Cross-tier: any tier with this ratio
+        for t in _TIER_ORDER:
+            if (t, ratio) in _SIZE_TABLE:
+                return _SIZE_TABLE[(t, ratio)]
+        # Tier default
+        if tier in _RATIO_DEFAULT:
+            return _SIZE_TABLE.get((tier, _RATIO_DEFAULT[tier]))
+
+    if tier and not ratio:
+        default_ratio = _RATIO_DEFAULT.get(tier)
+        if default_ratio:
+            return _SIZE_TABLE.get((tier, default_ratio))
+
+    if ratio and not tier:
+        for t in _TIER_ORDER:
+            if (t, ratio) in _SIZE_TABLE:
+                return _SIZE_TABLE[(t, ratio)]
+
+    return None
+
+
+# ---------------------------------------------------------------------------
+# Image helpers
+# ---------------------------------------------------------------------------
+
+def _load_image(source: str) -> bytes:
+    """Load image from a local file path or URL."""
+    if os.path.isfile(source):
+        with open(source, "rb") as f:
+            return f.read()
+    if _HAS_REQUESTS:
+        resp = requests.get(source, timeout=60)
+        resp.raise_for_status()
+        return resp.content
+    req = Request(source)
+    with urlopen(req, timeout=60) as resp:
+        return resp.read()
+
+
+def _compress_image(data: bytes, max_bytes: int = 4 * 1024 * 1024, max_edge: int = 4096) -> bytes:
+    """Compress image to fit size/dimension limits. Requires Pillow only when needed."""
+    if len(data) <= max_bytes:
+        try:
+            from PIL import Image
+
+            img = Image.open(io.BytesIO(data))
+            w, h = img.size
+            if max(w, h) <= max_edge:
+                return data
+        except ImportError:
+            return data
+        except Exception:
+            return data
+
+    try:
+        from PIL import Image
+    except ImportError:
+        return data
+
+    img = Image.open(io.BytesIO(data))
+    w, h = img.size
+
+    if max(w, h) > max_edge:
+        ratio = max_edge / max(w, h)
+        w, h = int(w * ratio), int(h * ratio)
+        img = img.resize((w, h), Image.LANCZOS)
+
+    buf = io.BytesIO()
+    fmt = img.format or "PNG"
+    if fmt.upper() == "JPEG":
+        quality = 85
+        while True:
+            buf.seek(0)
+            buf.truncate()
+            img.save(buf, format="JPEG", quality=quality)
+            if buf.tell() <= max_bytes or quality <= 20:
+                break
+            quality -= 10
+    else:
+        img.save(buf, format=fmt)
+        if buf.tell() > max_bytes:
+            buf.seek(0)
+            buf.truncate()
+            img.save(buf, format="JPEG", quality=75)
+    return buf.getvalue()
+
+
+def _save_image(data: bytes, output_dir: str) -> str:
+    """Save image bytes to output_dir and return the path."""
+    os.makedirs(output_dir, exist_ok=True)
+    ext = "png"
+    if data[:3] == b"\xff\xd8\xff":
+        ext = "jpg"
+    elif data[:4] == b"RIFF":
+        ext = "webp"
+    filename = f"{uuid.uuid4().hex[:12]}.{ext}"
+    path = os.path.join(output_dir, filename)
+    with open(path, "wb") as f:
+        f.write(data)
+    return path
+
+
+# ---------------------------------------------------------------------------
+# Provider interface
+# ---------------------------------------------------------------------------
+
+class ImageProvider(ABC):
+    """Abstract base class for image generation providers."""
+
+    @abstractmethod
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url: str | list | None = None,
+        quality: str | None = None,
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        """Generate image(s) and return list of local file paths.
+
+        `size` may be a tier ("1K" / "2K" / "4K" / "512") or pixels ("WxH").
+        Providers that need pixel sizes should call `resolve_size(size, aspect_ratio)`.
+        """
+        ...
+
+
+# ---------------------------------------------------------------------------
+# OpenAI-compatible provider (gpt-image-2, gpt-image-1)
+# ---------------------------------------------------------------------------
+
+class OpenAIProvider(ImageProvider):
+    """Provider for OpenAI Image API (generations + edits)."""
+
+    DEFAULT_MODEL = "gpt-image-2"
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = model or self.DEFAULT_MODEL
+
+    def _headers(self) -> dict:
+        return {
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+    @staticmethod
+    def _raise_for_api_error(resp):
+        """Raise with server error details instead of bare HTTP status."""
+        if resp.status_code >= 400:
+            try:
+                body = resp.json()
+                msg = body.get("error", {}).get("message") or body.get("message") or resp.text
+            except Exception:
+                msg = resp.text or resp.reason
+            raise RuntimeError(f"API {resp.status_code}: {msg} (url: {resp.url})")
+
+    def _post_json(self, url: str, payload: dict) -> dict:
+        headers = {**self._headers(), "Content-Type": "application/json"}
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            self._raise_for_api_error(resp)
+            return resp.json()
+        data = json.dumps(payload).encode()
+        req = Request(url, data=data, headers=headers, method="POST")
+        with urlopen(req, timeout=300) as r:
+            return json.loads(r.read())
+
+    def _post_multipart(self, url: str, fields: dict, files: list[tuple]) -> dict:
+        """POST multipart/form-data using requests (or fall back to urllib)."""
+        headers = self._headers()
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, data=fields, files=files, timeout=300)
+            self._raise_for_api_error(resp)
+            return resp.json()
+        boundary = uuid.uuid4().hex
+        body = b""
+        for key, val in fields.items():
+            body += f"--{boundary}\r\nContent-Disposition: form-data; name=\"{key}\"\r\n\r\n{val}\r\n".encode()
+        for field_name, (filename, filedata, content_type) in files:
+            body += (
+                f"--{boundary}\r\n"
+                f"Content-Disposition: form-data; name=\"{field_name}\"; filename=\"{filename}\"\r\n"
+                f"Content-Type: {content_type}\r\n\r\n"
+            ).encode() + filedata + b"\r\n"
+        body += f"--{boundary}--\r\n".encode()
+        headers["Content-Type"] = f"multipart/form-data; boundary={boundary}"
+        req = Request(url, data=body, headers=headers, method="POST")
+        with urlopen(req, timeout=300) as r:
+            return json.loads(r.read())
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        # OpenAI Images API expects pixel size like 1024x1024.
+        resolved = resolve_size(size, aspect_ratio) if (size or aspect_ratio) else None
+        if image_url:
+            return self._edit(prompt, image_url=image_url, quality=quality, size=resolved, output_dir=output_dir)
+        return self._create(prompt, quality=quality, size=resolved, output_dir=output_dir)
+
+    def _create(self, prompt: str, *, quality: str | None, size: str | None, output_dir: str) -> list[str]:
+        url = f"{self.api_base}/images/generations"
+        payload: dict = {
+            "model": self.model,
+            "prompt": prompt,
+        }
+        if quality:
+            payload["quality"] = quality
+        if size:
+            payload["size"] = size
+        result = self._post_json(url, payload)
+        return self._save_results(result, output_dir)
+
+    def _edit(
+        self,
+        prompt: str,
+        *,
+        image_url,
+        quality: str | None,
+        size: str | None,
+        output_dir: str,
+    ) -> list[str]:
+        urls = image_url if isinstance(image_url, list) else [image_url]
+        image_data_list = [_compress_image(_load_image(u)) for u in urls]
+
+        url = f"{self.api_base}/images/edits"
+
+        fields = {"model": self.model, "prompt": prompt}
+        if quality:
+            fields["quality"] = quality
+        if size:
+            fields["size"] = size
+
+        files = []
+        for i, img_bytes in enumerate(image_data_list):
+            ext = "png"
+            if img_bytes[:3] == b"\xff\xd8\xff":
+                ext = "jpg"
+            field_name = "image[]" if len(image_data_list) > 1 else "image"
+            files.append((field_name, (f"image_{i}.{ext}", img_bytes, f"image/{ext}")))
+
+        result = self._post_multipart(url, fields, files)
+        return self._save_results(result, output_dir)
+
+    @staticmethod
+    def _save_results(result: dict, output_dir: str) -> list[str]:
+        paths = []
+        for item in result.get("data", []):
+            if "b64_json" in item:
+                raw = base64.b64decode(item["b64_json"])
+                paths.append(_save_image(raw, output_dir))
+            elif "url" in item:
+                raw = _load_image(item["url"])
+                paths.append(_save_image(raw, output_dir))
+        return paths
+
+
+# ---------------------------------------------------------------------------
+# LinkAI provider (uses unified /v1/images/generations)
+# ---------------------------------------------------------------------------
+
+class LinkAIProvider(ImageProvider):
+    """Provider for LinkAI unified image generation API."""
+
+    DEFAULT_MODEL = "gpt-image-2"
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = model or self.DEFAULT_MODEL
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        url = f"{self.api_base}/v1/images/generations"
+        payload: dict = {
+            "model": self.model,
+            "prompt": prompt,
+        }
+        if quality:
+            payload["quality"] = quality
+        # LinkAI accepts both pixel sizes (1024x1024) and tier shorthand (1K/2K/4K).
+        # Pass through whatever the caller gave us; also forward aspect_ratio.
+        if size:
+            payload["size"] = size
+        if aspect_ratio:
+            payload["aspect_ratio"] = aspect_ratio
+        if image_url:
+            urls = image_url if isinstance(image_url, list) else [image_url]
+            resolved = []
+            for u in urls:
+                if os.path.isfile(u):
+                    data = _load_image(u)
+                    ext = u.rsplit(".", 1)[-1].lower() if "." in u else "png"
+                    mime = {"jpg": "image/jpeg", "jpeg": "image/jpeg", "webp": "image/webp"}.get(ext, "image/png")
+                    resolved.append(f"data:{mime};base64,{base64.b64encode(data).decode()}")
+                else:
+                    resolved.append(u)
+            payload["image_url"] = resolved if len(resolved) > 1 else resolved[0]
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            if resp.status_code >= 400:
+                try:
+                    body = resp.json()
+                    msg = body.get("error", {}).get("message") or body.get("message") or resp.text
+                except Exception:
+                    msg = resp.text or resp.reason
+                raise RuntimeError(f"API {resp.status_code}: {msg}")
+            result = resp.json()
+        else:
+            data = json.dumps(payload).encode()
+            req = Request(url, data=data, headers=headers, method="POST")
+            with urlopen(req, timeout=300) as r:
+                result = json.loads(r.read())
+
+        if "error" in result:
+            raise RuntimeError(result["error"].get("message", str(result["error"])))
+
+        paths = []
+        for item in result.get("data", []):
+            if "url" in item:
+                raw = _load_image(item["url"])
+                paths.append(_save_image(raw, output_dir))
+            elif "b64_json" in item:
+                raw = base64.b64decode(item["b64_json"])
+                paths.append(_save_image(raw, output_dir))
+        return paths
+
+
+# ---------------------------------------------------------------------------
+# Gemini provider (Nano Banana family — gemini-*-image-*)
+# ---------------------------------------------------------------------------
+
+# Friendly aliases → real Gemini model id
+_GEMINI_MODEL_ALIASES = {
+    "nano-banana": "gemini-2.5-flash-image",
+    "nano-banana-2": "gemini-3.1-flash-image-preview",
+    "nano-banana-pro": "gemini-3-pro-image-preview",
+}
+
+
+class GeminiProvider(ImageProvider):
+    """Provider for Google Gemini native image generation (Nano Banana family)."""
+
+    DEFAULT_MODEL = "gemini-3.1-flash-image-preview"  # nano-banana-2
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = _GEMINI_MODEL_ALIASES.get(model, model or self.DEFAULT_MODEL)
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,  # not used; Gemini has no `quality` param
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        # Build request parts: prompt text + optional inline images
+        parts: list[dict] = [{"text": prompt}]
+        if image_url:
+            urls = image_url if isinstance(image_url, list) else [image_url]
+            for u in urls:
+                data = _compress_image(_load_image(u))
+                mime = _guess_mime(data)
+                parts.append({
+                    "inline_data": {
+                        "mime_type": mime,
+                        "data": base64.b64encode(data).decode(),
+                    }
+                })
+
+        payload: dict = {
+            "contents": [{"parts": parts}],
+            "generationConfig": {"responseModalities": ["IMAGE"]},
+        }
+
+        # Gemini natively supports aspectRatio + imageSize tiers (512/1K/2K/4K).
+        _GEMINI_VALID_TIERS = {"512", "1K", "2K", "4K"}
+        _GEMINI_TIER_FALLBACK = {"3K": "2K"}
+        image_config: dict = {}
+        if size:
+            if "x" in size.lower():
+                tier = _pixels_to_tier(size)
+            else:
+                tier = size.upper()
+            tier = _GEMINI_TIER_FALLBACK.get(tier, tier)
+            if tier in _GEMINI_VALID_TIERS:
+                image_config["imageSize"] = tier
+        if aspect_ratio:
+            image_config["aspectRatio"] = aspect_ratio
+        elif size and "x" in size.lower():
+            ratio = _pixels_to_ratio(size)
+            if ratio:
+                image_config["aspectRatio"] = ratio
+        if image_config:
+            payload["generationConfig"]["imageConfig"] = image_config
+
+        url = f"{self.api_base}/v1beta/models/{self.model}:generateContent"
+        headers = {
+            "x-goog-api-key": self.api_key,
+            "Content-Type": "application/json",
+        }
+
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            if resp.status_code >= 400:
+                try:
+                    body = resp.json()
+                    msg = body.get("error", {}).get("message") or resp.text
+                except Exception:
+                    msg = resp.text or resp.reason
+                raise RuntimeError(f"API {resp.status_code}: {msg}")
+            result = resp.json()
+        else:
+            data = json.dumps(payload).encode()
+            req = Request(url, data=data, headers=headers, method="POST")
+            with urlopen(req, timeout=300) as r:
+                result = json.loads(r.read())
+
+        return self._extract_images(result, output_dir)
+
+    @staticmethod
+    def _extract_images(result: dict, output_dir: str) -> list[str]:
+        paths: list[str] = []
+        for cand in result.get("candidates", []):
+            for part in cand.get("content", {}).get("parts", []):
+                if part.get("thought"):
+                    continue  # skip thinking-stage interim images
+                inline = part.get("inlineData") or part.get("inline_data")
+                if inline and inline.get("data"):
+                    raw = base64.b64decode(inline["data"])
+                    paths.append(_save_image(raw, output_dir))
+        if not paths:
+            # Surface the model's text reply (often a refusal explanation)
+            for cand in result.get("candidates", []):
+                for part in cand.get("content", {}).get("parts", []):
+                    if part.get("text"):
+                        raise RuntimeError(f"Gemini returned no image: {part['text'][:200]}")
+            raise RuntimeError("Gemini returned no image (empty response)")
+        return paths
+
+
+def _guess_mime(data: bytes) -> str:
+    if data[:3] == b"\xff\xd8\xff":
+        return "image/jpeg"
+    if data[:4] == b"RIFF":
+        return "image/webp"
+    if data[:8] == b"\x89PNG\r\n\x1a\n":
+        return "image/png"
+    return "image/png"
+
+
+def _pixels_to_tier(pixel_str: str) -> str:
+    """Map 'WxH' to nearest Gemini tier (512 / 1K / 2K / 4K)."""
+    try:
+        w, h = (int(x) for x in pixel_str.lower().split("x"))
+        long_edge = max(w, h)
+    except Exception:
+        return "1K"
+    if long_edge <= 768:
+        return "512"
+    if long_edge <= 1536:
+        return "1K"
+    if long_edge <= 3072:
+        return "2K"
+    return "4K"
+
+
+def _pixels_to_ratio(pixel_str: str) -> str | None:
+    """Map 'WxH' to a Gemini-supported aspect ratio string when possible."""
+    try:
+        w, h = (int(x) for x in pixel_str.lower().split("x"))
+    except Exception:
+        return None
+    # Reduce to a small ratio
+    from math import gcd
+    g = gcd(w, h)
+    rw, rh = w // g, h // g
+    candidate = f"{rw}:{rh}"
+    supported = {"1:1", "1:4", "1:8", "2:3", "3:2", "3:4", "4:1", "4:3",
+                 "4:5", "5:4", "8:1", "9:16", "16:9", "21:9"}
+    return candidate if candidate in supported else None
+
+
+# ---------------------------------------------------------------------------
+# Seedream provider (Volcengine Ark, OpenAI-compatible /images/generations)
+# ---------------------------------------------------------------------------
+
+# Friendly aliases → real Seedream model id (Ark Model IDs).
+_SEEDREAM_MODEL_ALIASES = {
+    "seedream": "doubao-seedream-5-0-260128",
+    "seedream-lite": "doubao-seedream-5-0-260128",
+    "seedream-5.0": "doubao-seedream-5-0-260128",
+    "seedream-5.0-lite": "doubao-seedream-5-0-260128",
+    "seedream-5-0-lite": "doubao-seedream-5-0-260128",
+    "doubao-seedream-5-0": "doubao-seedream-5-0-260128",
+    "doubao-seedream-5-0-lite": "doubao-seedream-5-0-260128",
+    "seedream-4.5": "doubao-seedream-4-5-251128",
+    "seedream-4-5": "doubao-seedream-4-5-251128",
+    "doubao-seedream-4-5": "doubao-seedream-4-5-251128",
+}
+
+# Seedream supports either a coarse tier ("2K"/"3K"/"4K") or explicit "WxH".
+# We pass the user's tier through as-is when valid; otherwise translate ratio
+# hints into the recommended pixel sizes from the Ark docs.
+# Valid size tiers for Seedream (5.0 lite: 2K/3K, 4.5: 2K/4K).
+# Unsupported tiers are mapped to the nearest valid one.
+_SEEDREAM_VALID_TIERS = {"2K", "3K", "4K"}
+_SEEDREAM_TIER_FALLBACK = {"512": "2K", "1K": "2K"}
+_SEEDREAM_SIZE_TABLE = {
+    # (tier, ratio) -> "WxH" recommended pixel sizes (Seedream 5.0 lite + 4.5 share most)
+    ("2K", "1:1"): "2048x2048",
+    ("2K", "3:4"): "1728x2304",
+    ("2K", "4:3"): "2304x1728",
+    ("2K", "16:9"): "2848x1600",
+    ("2K", "9:16"): "1600x2848",
+    ("2K", "3:2"): "2496x1664",
+    ("2K", "2:3"): "1664x2496",
+    ("2K", "21:9"): "3136x1344",
+    ("3K", "1:1"): "3072x3072",
+    ("3K", "3:4"): "2592x3456",
+    ("3K", "4:3"): "3456x2592",
+    ("3K", "16:9"): "4096x2304",
+    ("3K", "9:16"): "2304x4096",
+    ("3K", "2:3"): "2496x3744",
+    ("3K", "3:2"): "3744x2496",
+    ("3K", "21:9"): "4704x2016",
+    ("4K", "1:1"): "4096x4096",
+    ("4K", "3:4"): "3520x4704",
+    ("4K", "4:3"): "4704x3520",
+    ("4K", "16:9"): "5504x3040",
+    ("4K", "9:16"): "3040x5504",
+    ("4K", "2:3"): "3328x4992",
+    ("4K", "3:2"): "4992x3328",
+    ("4K", "21:9"): "6240x2656",
+}
+
+
+class SeedreamProvider(ImageProvider):
+    """Provider for Volcengine Ark Seedream image generation API.
+
+    The endpoint is OpenAI-compatible (POST {base}/images/generations) but
+    accepts an extra `image` field (string or list) for image-to-image and
+    multi-image fusion, plus `sequential_image_generation` / `watermark` flags.
+    Reference docs accept both `2K` shorthand and explicit `WxH` for `size`.
+    """
+
+    DEFAULT_MODEL = "doubao-seedream-5-0-260128"  # seedream 5.0 lite
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = _SEEDREAM_MODEL_ALIASES.get((model or "").lower(), model or self.DEFAULT_MODEL)
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,  # not honoured by Seedream
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        url = f"{self.api_base}/images/generations"
+
+        payload: dict = {
+            "model": self.model,
+            "prompt": prompt,
+            "response_format": "url",
+            "watermark": False,
+        }
+
+        # Default to 2K (Seedream 5.0 lite minimum tier), unless caller picks one.
+        seedream_size = self._resolve_seedream_size(size, aspect_ratio)
+        if seedream_size:
+            payload["size"] = seedream_size
+
+        # Image-to-image / multi-image fusion (up to 14 reference images).
+        if image_url:
+            urls = image_url if isinstance(image_url, list) else [image_url]
+            prepared: list[str] = []
+            for u in urls[:14]:
+                if os.path.isfile(u):
+                    data = _compress_image(_load_image(u))
+                    mime = _guess_mime(data)
+                    prepared.append(f"data:{mime};base64,{base64.b64encode(data).decode()}")
+                else:
+                    prepared.append(u)
+            payload["image"] = prepared if len(prepared) > 1 else prepared[0]
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            if resp.status_code >= 400:
+                try:
+                    body = resp.json()
+                    err = body.get("error") or {}
+                    msg = err.get("message") or body.get("message") or resp.text
+                except Exception:
+                    msg = resp.text or resp.reason
+                raise RuntimeError(f"API {resp.status_code}: {msg}")
+            result = resp.json()
+        else:
+            data = json.dumps(payload).encode()
+            req = Request(url, data=data, headers=headers, method="POST")
+            with urlopen(req, timeout=300) as r:
+                result = json.loads(r.read())
+
+        if result.get("error"):
+            err = result["error"]
+            raise RuntimeError(f"Seedream {err.get('code')}: {err.get('message')}")
+
+        paths: list[str] = []
+        for item in result.get("data") or []:
+            u = item.get("url")
+            b64 = item.get("b64_json")
+            if u:
+                paths.append(_save_image(_load_image(u), output_dir))
+            elif b64:
+                paths.append(_save_image(base64.b64decode(b64), output_dir))
+        if not paths:
+            raise RuntimeError(f"Seedream returned no image: {result}")
+        return paths
+
+    @staticmethod
+    def _resolve_seedream_size(size: str | None, aspect_ratio: str | None) -> str | None:
+        if not size and not aspect_ratio:
+            return "2K"
+        # Explicit pixel values: pass through (normalise separator)
+        if size and "x" in size.lower() and "*" not in size:
+            return size.lower()
+        if size and "*" in size:
+            return size.replace("*", "x")
+        tier = (size or "2K").upper()
+        # Map unsupported tiers (512, 1K) to the nearest valid one
+        tier = _SEEDREAM_TIER_FALLBACK.get(tier, tier)
+        if tier not in _SEEDREAM_VALID_TIERS:
+            tier = "2K"
+        ratio = aspect_ratio or "1:1"
+        if (tier, ratio) in _SEEDREAM_SIZE_TABLE:
+            return _SEEDREAM_SIZE_TABLE[(tier, ratio)]
+        return tier
+
+
+# ---------------------------------------------------------------------------
+# Qwen provider (DashScope multimodal-generation: qwen-image-* family)
+# ---------------------------------------------------------------------------
+
+# Friendly aliases → real Qwen model id
+_QWEN_MODEL_ALIASES = {
+    "qwen": "qwen-image-2.0-pro",
+    "qwen-image": "qwen-image-2.0-pro",
+    "qwen-image-pro": "qwen-image-2.0-pro",
+}
+
+# Qwen pixel-size table (closest match by tier+ratio).
+# qwen-image-2.0(*) supports any WxH between 512*512 and 2048*2048.
+_QWEN_SIZE_TABLE = {
+    # (tier, ratio) -> "W*H"
+    ("1K", "1:1"): "1024*1024",
+    ("1K", "16:9"): "1280*720",
+    ("1K", "9:16"): "720*1280",
+    ("1K", "4:3"): "1184*888",
+    ("1K", "3:4"): "888*1184",
+    ("1K", "3:2"): "1248*832",
+    ("1K", "2:3"): "832*1248",
+    ("2K", "1:1"): "2048*2048",
+    ("2K", "16:9"): "2688*1536",  # exceeds 2048 cap → clamped at runtime if needed
+    ("2K", "9:16"): "1536*2688",
+    ("2K", "4:3"): "2368*1728",
+    ("2K", "3:4"): "1728*2368",
+}
+
+
+class QwenProvider(ImageProvider):
+    """Provider for Alibaba DashScope Qwen image API (qwen-image-2.0[-pro])."""
+
+    DEFAULT_MODEL = "qwen-image-2.0"
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = _QWEN_MODEL_ALIASES.get((model or "").lower(), model or self.DEFAULT_MODEL)
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,  # not supported by Qwen image API
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        url = f"{self.api_base}/api/v1/services/aigc/multimodal-generation/generation"
+
+        # Build content array: 0..3 images then a single text part.
+        content: list[dict] = []
+        if image_url:
+            urls = image_url if isinstance(image_url, list) else [image_url]
+            for u in urls[:3]:  # API caps at 3 reference images
+                if os.path.isfile(u):
+                    data = _compress_image(_load_image(u))
+                    mime = _guess_mime(data)
+                    image_field = f"data:{mime};base64,{base64.b64encode(data).decode()}"
+                else:
+                    image_field = u
+                content.append({"image": image_field})
+        content.append({"text": prompt})
+
+        payload: dict = {
+            "model": self.model,
+            "input": {"messages": [{"role": "user", "content": content}]},
+        }
+
+        # Map (size, aspect_ratio) → Qwen "W*H"
+        qwen_size = self._resolve_qwen_size(size, aspect_ratio)
+        if qwen_size:
+            payload["parameters"] = {"size": qwen_size}
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            if resp.status_code >= 400:
+                try:
+                    body = resp.json()
+                    msg = body.get("message") or body.get("error", {}).get("message") or resp.text
+                except Exception:
+                    msg = resp.text or resp.reason
+                raise RuntimeError(f"API {resp.status_code}: {msg}")
+            result = resp.json()
+        else:
+            data = json.dumps(payload).encode()
+            req = Request(url, data=data, headers=headers, method="POST")
+            with urlopen(req, timeout=300) as r:
+                result = json.loads(r.read())
+
+        # Business-level errors arrive on HTTP 200 with a `code` field.
+        if result.get("code"):
+            raise RuntimeError(f"Qwen {result.get('code')}: {result.get('message')}")
+
+        paths: list[str] = []
+        choices = (result.get("output") or {}).get("choices") or []
+        for ch in choices:
+            for part in ((ch.get("message") or {}).get("content") or []):
+                u = part.get("image")
+                if u:
+                    paths.append(_save_image(_load_image(u), output_dir))
+        if not paths:
+            raise RuntimeError(f"Qwen returned no image: {result}")
+        return paths
+
+    @staticmethod
+    def _resolve_qwen_size(size: str | None, aspect_ratio: str | None) -> str | None:
+        if not size and not aspect_ratio:
+            return None
+        if size and "x" in size.lower() and "*" not in size:
+            return size.lower().replace("x", "*")
+        if size and "*" in size:
+            return size
+        tier = (size or "1K").upper()
+        # Qwen supports 1K and 2K; clamp others
+        _QWEN_TIER_MAP = {"512": "1K", "3K": "2K", "4K": "2K"}
+        tier = _QWEN_TIER_MAP.get(tier, tier)
+        if tier not in ("1K", "2K"):
+            tier = "1K"
+        ratio = aspect_ratio or "1:1"
+        if (tier, ratio) in _QWEN_SIZE_TABLE:
+            return _QWEN_SIZE_TABLE[(tier, ratio)]
+        return _QWEN_SIZE_TABLE.get((tier, "1:1"))
+
+
+# ---------------------------------------------------------------------------
+# MiniMax provider (image-01 family)
+# ---------------------------------------------------------------------------
+
+# Friendly aliases → real MiniMax model id
+_MINIMAX_MODEL_ALIASES = {
+    "minimax": "image-01",
+    "minimax-image": "image-01",
+    "minimax-image-01": "image-01",
+}
+
+_MINIMAX_SUPPORTED_RATIOS = {"1:1", "16:9", "4:3", "3:2", "2:3", "3:4", "9:16", "21:9"}
+
+
+class MinimaxProvider(ImageProvider):
+    """Provider for MiniMax image generation API (image-01)."""
+
+    DEFAULT_MODEL = "image-01"
+
+    def __init__(self, api_key: str, api_base: str, model: str):
+        self.api_key = api_key
+        self.api_base = api_base.rstrip("/")
+        self.model = _MINIMAX_MODEL_ALIASES.get((model or "").lower(), model or self.DEFAULT_MODEL)
+
+    def generate(
+        self,
+        prompt: str,
+        *,
+        image_url=None,
+        quality: str | None = None,  # not supported by MiniMax
+        size: str | None = None,
+        aspect_ratio: str | None = None,
+        output_dir: str = ".",
+    ) -> list[str]:
+        url = f"{self.api_base}/v1/image_generation"
+        payload: dict = {
+            "model": self.model,
+            "prompt": prompt,
+            "response_format": "base64",
+        }
+
+        # MiniMax accepts aspect_ratio directly; derive from pixels if needed.
+        ratio = aspect_ratio
+        if not ratio and size and "x" in size.lower():
+            ratio = _pixels_to_ratio(size)
+        if ratio and ratio in _MINIMAX_SUPPORTED_RATIOS:
+            payload["aspect_ratio"] = ratio
+
+        # Image-to-image uses subject_reference; accept URL or local file (→ base64).
+        if image_url:
+            urls = image_url if isinstance(image_url, list) else [image_url]
+            refs = []
+            for u in urls:
+                if os.path.isfile(u):
+                    data = _compress_image(_load_image(u))
+                    mime = _guess_mime(data)
+                    image_file = f"data:{mime};base64,{base64.b64encode(data).decode()}"
+                else:
+                    image_file = u
+                refs.append({"type": "character", "image_file": image_file})
+            payload["subject_reference"] = refs
+
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        if _HAS_REQUESTS:
+            resp = requests.post(url, headers=headers, json=payload, timeout=300)
+            if resp.status_code >= 400:
+                try:
+                    body = resp.json()
+                    msg = body.get("base_resp", {}).get("status_msg") or body.get("error", {}).get("message") or resp.text
+                except Exception:
+                    msg = resp.text or resp.reason
+                raise RuntimeError(f"API {resp.status_code}: {msg}")
+            result = resp.json()
+        else:
+            data = json.dumps(payload).encode()
+            req = Request(url, data=data, headers=headers, method="POST")
+            with urlopen(req, timeout=300) as r:
+                result = json.loads(r.read())
+
+        # MiniMax returns business errors inside base_resp even on HTTP 200.
+        base_resp = result.get("base_resp") or {}
+        if base_resp.get("status_code") not in (None, 0):
+            raise RuntimeError(f"MiniMax {base_resp.get('status_code')}: {base_resp.get('status_msg')}")
+
+        data_obj = result.get("data") or {}
+        b64_list = data_obj.get("image_base64") or []
+        urls_list = data_obj.get("image_urls") or []
+
+        paths: list[str] = []
+        for b64 in b64_list:
+            paths.append(_save_image(base64.b64decode(b64), output_dir))
+        for u in urls_list:
+            paths.append(_save_image(_load_image(u), output_dir))
+        if not paths:
+            raise RuntimeError(f"MiniMax returned no image: {result}")
+        return paths
+
+
+# ---------------------------------------------------------------------------
+# Provider factory
+# ---------------------------------------------------------------------------
+
+# Model-prefix → preferred provider label.
+# When the requested model matches a prefix, that provider is promoted to the
+# front of the queue. All other configured providers still run as fallbacks.
+_MODEL_PREFERRED_PROVIDER: list[tuple[tuple[str, ...], str]] = [
+    (("gpt-image",), "OpenAI"),
+    (("nano-banana", "gemini-"), "Gemini"),
+    (("seedream", "doubao-seedream"), "Seedream"),
+    (("qwen-image", "qwen"), "Qwen"),
+    (("minimax", "image-01"), "MiniMax"),
+]
+
+# Default global priority when the model has no preferred provider.
+_DEFAULT_PROVIDER_ORDER = ["OpenAI", "Gemini", "Seedream", "Qwen", "MiniMax", "LinkAI"]
+
+# UI provider id (persisted via the Models page) → internal label used by
+# the factory dict in `_build_providers`. Allows pinning a vendor for
+# custom model names that prefix-inference can't recognize.
+_PROVIDER_ID_TO_LABEL = {
+    "openai": "OpenAI",
+    "gemini": "Gemini",
+    "doubao": "Seedream",
+    "dashscope": "Qwen",
+    "minimax": "MiniMax",
+    "linkai": "LinkAI",
+}
+
+
+def _preferred_provider(model: str) -> str | None:
+    m = (model or "").lower()
+    for prefixes, label in _MODEL_PREFERRED_PROVIDER:
+        if m.startswith(prefixes):
+            return label
+    return None
+
+
+def _build_providers(model: str, provider_id: str = "") -> list[tuple[str, ImageProvider]]:
+    """Build an ordered list of (label, provider) to try.
+
+    Behaviour:
+      1. All providers with a configured API key are added in the global
+         priority order: OpenAI → Gemini → Seedream → Qwen → MiniMax → LinkAI.
+      2. If `model` natively belongs to one of the providers AND that provider
+         is configured, it is promoted to the front so it gets the first
+         attempt with the right model id.
+      3. If the preferred provider is NOT configured (no API key), the model
+         id would 100% fail on every other backend, so we drop the explicit
+         model and fall back to automatic routing — every provider then uses
+         its own DEFAULT_MODEL.
+    """
+    keys = {
+        "OpenAI": os.environ.get("OPENAI_API_KEY", ""),
+        "Gemini": os.environ.get("GEMINI_API_KEY", ""),
+        "Seedream": os.environ.get("ARK_API_KEY", ""),
+        "Qwen": os.environ.get("DASHSCOPE_API_KEY", ""),
+        "MiniMax": os.environ.get("MINIMAX_API_KEY", ""),
+        "LinkAI": os.environ.get("LINKAI_API_KEY", ""),
+    }
+    bases = {
+        "OpenAI": os.environ.get("OPENAI_API_BASE", "https://api.openai.com/v1"),
+        "Gemini": os.environ.get("GEMINI_API_BASE", "https://generativelanguage.googleapis.com"),
+        "Seedream": os.environ.get("ARK_API_BASE", "https://ark.cn-beijing.volces.com/api/v3"),
+        "Qwen": os.environ.get("DASHSCOPE_API_BASE", "https://dashscope.aliyuncs.com"),
+        "MiniMax": os.environ.get("MINIMAX_API_BASE", "https://api.minimaxi.com"),
+        "LinkAI": os.environ.get("LINKAI_API_BASE", "https://api.link-ai.tech"),
+    }
+
+    # Provider preference resolution priority:
+    #   1. Explicit `provider_id` (UI-persisted, supports custom model names).
+    #   2. Model-name prefix inference.
+    pref = _PROVIDER_ID_TO_LABEL.get(provider_id) if provider_id else None
+    if not pref:
+        pref = _preferred_provider(model)
+
+    # If a specific model is requested and its native provider has no key,
+    # other backends won't recognise the id → reset to auto routing.
+    if pref and not keys.get(pref):
+        model = ""
+        pref = None
+
+    factories = {
+        "OpenAI": OpenAIProvider,
+        "Gemini": GeminiProvider,
+        "Seedream": SeedreamProvider,
+        "Qwen": QwenProvider,
+        "MiniMax": MinimaxProvider,
+        "LinkAI": LinkAIProvider,
+    }
+    available: dict[str, ImageProvider] = {}
+    for label, key in keys.items():
+        if key:
+            available[label] = factories[label](api_key=key, api_base=bases[label], model=model)
+
+    # When a specific model is pinned, only try its native provider — other
+    # backends won't recognise the model id so retrying them is pointless.
+    if pref and pref in available:
+        return [(pref, available[pref])]
+
+    # Auto routing: try every configured provider in priority order.
+    ordered: list[str] = []
+    for label in _DEFAULT_PROVIDER_ORDER:
+        if label in available:
+            ordered.append(label)
+    return [(label, available[label]) for label in ordered]
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+def main():
+    if len(sys.argv) < 2:
+        print(json.dumps({"error": "Usage: python generate.py '<json_args>'"}))
+        sys.exit(1)
+
+    try:
+        raw = sys.argv[1]
+        raw = raw.replace('\u201c', '"').replace('\u201d', '"').replace('\u2018', "'").replace('\u2019', "'")
+        args = json.loads(raw)
+    except json.JSONDecodeError as e:
+        print(json.dumps({"error": f"Invalid JSON: {e}"}))
+        sys.exit(1)
+
+    prompt = args.get("prompt")
+    if not prompt:
+        print(json.dumps({"error": "Missing required parameter: prompt"}))
+        sys.exit(1)
+
+    # Model resolution priority:
+    #   1. Explicit `model` in the call args (agent / user override)
+    #   2. SKILL_IMAGE_GENERATION_MODEL env var (synced from
+    #      config["skills"]["image-generation"]["model"] at startup)
+    #   3. None → fall back to automatic provider routing (try every
+    #      provider with a configured API key in global priority order)
+    model = args.get("model") or os.environ.get("SKILL_IMAGE_GENERATION_MODEL") or ""
+    # Provider hint persisted by the Models UI; lets users pin a vendor for
+    # custom model names that prefix-inference can't recognize.
+    provider_id = args.get("provider") or os.environ.get("SKILL_IMAGE_GENERATION_PROVIDER") or ""
+    quality = args.get("quality")
+    size = args.get("size")
+    aspect_ratio = args.get("aspect_ratio")
+    image_url = args.get("image_url")
+
+    output_dir = os.environ.get("IMAGE_OUTPUT_DIR", os.path.join(os.getcwd(), "images"))
+
+    providers = _build_providers(model, provider_id=provider_id)
+    if not providers:
+        target = f"model '{model}'" if model else "image generation"
+        print(json.dumps({
+            "error": (
+                f"No API key configured for {target}. "
+                "Set at least one of OPENAI_API_KEY / GEMINI_API_KEY / "
+                "ARK_API_KEY / DASHSCOPE_API_KEY / MINIMAX_API_KEY / "
+                "LINKAI_API_KEY via the env_config tool, then try again."
+            )
+        }, ensure_ascii=False))
+        sys.exit(1)
+
+    errors = []
+    for label, provider in providers:
+        try:
+            attempt_model = getattr(provider, "model", model) or "auto"
+            print(f"[image-generation] Trying {label} (model={attempt_model})...", file=sys.stderr)
+            t0 = time.time()
+            paths = provider.generate(
+                prompt,
+                image_url=image_url,
+                quality=quality,
+                size=size,
+                aspect_ratio=aspect_ratio,
+                output_dir=output_dir,
+            )
+            elapsed = time.time() - t0
+            # Resolved model id (after alias expansion) actually sent to the API
+            actual_model = getattr(provider, "model", model)
+            print(
+                f"[image-generation] ✅ {label} succeeded in {elapsed:.1f}s "
+                f"(model={actual_model})",
+                file=sys.stderr,
+            )
+            result = {
+                "model": actual_model,
+                "images": [{"url": p} for p in paths],
+            }
+            print(json.dumps(result, ensure_ascii=False))
+            return
+        except Exception as e:
+            elapsed = time.time() - t0
+            print(f"[image-generation] ❌ {label} failed in {elapsed:.1f}s: {e}", file=sys.stderr)
+            errors.append(f"{label}: {e}")
+
+    hint = " | ".join(errors)
+    print(json.dumps({
+        "error": f"All providers failed — {hint}. "
+                 "This is likely an API key or base URL configuration issue. "
+                 "Do NOT retry with the same parameters. "
+                 "Ask the user to verify their API key / base URL "
+                 "(OPENAI_API_KEY, GEMINI_API_KEY, ARK_API_KEY, "
+                 "DASHSCOPE_API_KEY, MINIMAX_API_KEY, or LINKAI_API_KEY) "
+                 "via env_config."
+    }, ensure_ascii=False))
+    sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/skills/knowledge-wiki/SKILL.md b/skills/knowledge-wiki/SKILL.md
new file mode 100644
index 0000000..9fdf5f5
--- /dev/null
+++ b/skills/knowledge-wiki/SKILL.md
@@ -0,0 +1,96 @@
+---
+name: knowledge-wiki
+description: Manage the personal knowledge wiki. Use when the user shares articles, documents, or asks to organize knowledge; when a conversation produces insights worth preserving as structured knowledge; or when the user asks about the knowledge base.
+metadata:
+  cowagent:
+    always: true
+---
+
+# Knowledge Wiki
+
+Maintain a persistent, structured knowledge base in the `knowledge/` directory.
+
+## Core Operations
+
+### 1. Ingest — User shares an article, document, or resource
+
+1. Read and understand the source material
+2. Extract key facts, insights, and structured knowledge
+3. Determine the appropriate subdirectory:
+   - Read `knowledge/index.md` to see existing categories
+   - If a matching category exists, follow that structure
+   - If not, create a new subdirectory with a clear name
+4. Create the knowledge page: `knowledge/<category>/<slug>.md`
+5. Update `knowledge/index.md` and append to `knowledge/log.md`
+
+### 2. Synthesize — Conversation produces valuable structured knowledge
+
+1. Create a knowledge page under the appropriate category
+2. Update related pages with cross-references
+3. Update `knowledge/index.md` and `knowledge/log.md`
+
+### 3. Query — User asks about accumulated knowledge
+
+1. Check `knowledge/index.md` (already in your context) for relevant pages
+2. Read specific pages with the `read` tool
+3. Supplement with `memory_search` if needed
+
+## Page Format
+
+```markdown
+# Page Title
+
+> Source: <URL or description of the original material>
+
+Content here. Cross-reference related pages with markdown links:
+[Related Page](../category/related-page.md)
+
+## Key Points
+
+- ...
+
+## Related
+
+- [Page A](../category/page-a.md) — how it relates
+- [Page B](../category/page-b.md) — how it relates
+```
+
+The `> Source:` line records where the knowledge came from (URL, document name, conversation, etc.). Always include it when the material originates from a specific source.
+
+Cross-references build a knowledge graph. When creating or updating a page, link to related pages and update those pages to link back. **Only link to pages that already exist** — if a concept deserves its own page, create it first, then add the link.
+
+## Index Format (`knowledge/index.md`)
+
+Flat list, one line per page: `[Title](path) — one-line summary`. Group by category (matching subdirectories). No tables, no emoji.
+
+```markdown
+# Knowledge Index
+
+## Category A
+- [Page Title](category-a/page-slug.md) — one-line summary
+
+## Category B
+- [Page Title](category-b/page-slug.md) — one-line summary
+```
+
+Category names and structure are flexible — follow whatever organization already exists in the index, or create new categories based on the content.
+
+## Log Format (`knowledge/log.md`)
+
+Append-only, newest at bottom:
+
+```markdown
+## [YYYY-MM-DD] ingest | Page Title
+## [YYYY-MM-DD] synthesize | Page Title
+```
+
+## Guidelines
+
+- **File naming**: lowercase kebab-case (e.g. `machine-learning.md`)
+- **One topic per page**: link between pages rather than duplicating
+- **Update, don't duplicate**: if a page exists, update it
+- **Cross-reference**: every page should link to related pages; keep the knowledge graph connected
+- **Index is mandatory**: always update `knowledge/index.md` after any change
+- **Be concise**: capture essence, not copy entire sources
+- **Full paths in replies**: when referencing knowledge files in conversation replies, use the full path from workspace root (e.g. `[Title](knowledge/<category>/<slug>.md)`), not relative paths. Relative paths are only for cross-references inside knowledge pages themselves.
+- **Cite sources**: when answering based on knowledge pages, include links to the relevant pages so the user can explore further.
diff --git a/skills/skill-creator/SKILL.md b/skills/skill-creator/SKILL.md
new file mode 100644
index 0000000..5021a00
--- /dev/null
+++ b/skills/skill-creator/SKILL.md
@@ -0,0 +1,429 @@
+---
+name: skill-creator
+description: Create, install, or update skills in the workspace. Use when (1) installing a skill from a URL or remote source, (2) creating a new skill from scratch, (3) updating or restructuring existing skills. Always use this skill for any skill installation or creation task.
+license: Complete terms in LICENSE.txt
+---
+
+# Skill Creator
+
+This skill provides guidance for creating effective skills using the existing tool system.
+
+## About Skills
+
+Skills are modular, self-contained packages that extend the agent's capabilities by providing specialized knowledge, workflows, and tools. They transform a general-purpose agent into a specialized agent equipped with procedural knowledge.
+
+### What Skills Provide
+
+1. **Specialized workflows** - Multi-step procedures for specific domains
+2. **Tool integrations** - Instructions for working with specific file formats or APIs
+3. **Domain expertise** - Company-specific knowledge, schemas, business logic
+4. **Bundled resources** - Scripts, references, and assets for complex tasks
+
+### Core Principle
+
+**Concise is Key**: Only add context the agent doesn't already have. Challenge each piece of information: "Does this justify its token cost?" Prefer concise examples over verbose explanations.
+
+## Skill Structure
+
+Every skill consists of a required SKILL.md file and optional bundled resources:
+
+```
+skill-name/
+├── SKILL.md (required)
+│   ├── YAML frontmatter metadata (required)
+│   │   ├── name: (required)
+│   │   └── description: (required)
+│   └── Markdown instructions (required)
+└── Bundled Resources (optional)
+    ├── scripts/          - Executable code (Python/Bash/etc.)
+    ├── references/       - Documentation intended to be loaded into context as needed
+    └── assets/           - Files used in output (templates, icons, fonts, etc.)
+```
+
+### SKILL.md Components
+
+**Frontmatter (YAML)** - Required fields:
+
+- **name**: Skill name in hyphen-case (e.g., `weather-api`, `pdf-editor`)
+- **description**: **CRITICAL** - Primary triggering mechanism
+  - Must clearly describe what the skill does
+  - Must explicitly state when to use it
+  - Include specific trigger scenarios and keywords
+  - All "when to use" info goes here, NOT in body
+  - Example: `"PDF document processing with rotation, merging, splitting, and text extraction. Use when user needs to: (1) Rotate PDF pages, (2) Merge multiple PDFs, (3) Split PDF files, (4) Extract text from PDFs."`
+
+**Body (Markdown)** - Loaded after skill triggers:
+
+- Detailed usage instructions
+- How to call scripts and read references
+- Examples and best practices
+- Use imperative/infinitive form ("Use X to do Y")
+
+### Bundled Resources
+
+**scripts/** - When to include:
+- Code is repeatedly rewritten
+- Deterministic execution needed (avoid LLM randomness)
+- Examples: PDF rotation, image processing
+- Must test scripts before including
+
+**references/** - When to include:
+- **ONLY** when documentation is too large for SKILL.md (>500 lines)
+- Database schemas, complex API specs that agent needs to reference
+- Agent reads these files into context as needed
+- **NOT for**: API reference docs, usage examples, tutorials (put in SKILL.md instead)
+- **Rule of thumb**: If it fits in SKILL.md, don't create a separate reference file
+
+**assets/** - When to include:
+- Files used in output (not loaded to context)
+- Templates, icons, boilerplate code
+- Copied or modified in final output
+
+**Important**: Most skills don't need all three. Choose based on actual needs.
+
+### What NOT to Include
+
+Do NOT create auxiliary documentation files:
+- README.md - Instructions belong in SKILL.md
+- INSTALLATION_GUIDE.md - Setup info belongs in SKILL.md
+- CHANGELOG.md - Not needed for local skills
+- API_REFERENCE.md - Put API docs directly in SKILL.md
+- USAGE_EXAMPLES.md - Put examples directly in SKILL.md
+- Any other documentation files - Everything goes in SKILL.md unless it's too large
+
+**Critical Rule**: Only create files that the agent will actually execute (scripts) or that are too large for SKILL.md (references). Documentation, examples, and guides ALL belong in SKILL.md.
+
+## Installing a Skill
+
+Install target directory: `<workspace>/skills/<name>/` (the `<workspace>` is from the "工作空间" section).
+
+### Step 1 — Obtain skill content
+
+| Source | Action |
+|---|---|
+| URL (single file) | Fetch content via curl or web_fetch |
+| URL (zip/archive) | Download and extract to a temp directory |
+| Local file (SKILL.md) | Read directly |
+| Local archive (zip) | Extract to a temp directory |
+
+### Step 2 — Identify and install
+
+1. Locate the SKILL.md (may be at top level or inside a subdirectory)
+2. Extract `name` from YAML frontmatter
+3. Copy the **entire skill directory** (SKILL.md and all sibling files/folders such as `references/`, `scripts/`, `assets/`, etc.) into `<workspace>/skills/<name>/`
+4. If an install/setup file exists (e.g. INSTALL.md), follow its instructions — the final result must still end up in `<workspace>/skills/<name>/`
+
+## Skill Creation Process (from scratch)
+
+1. **Understand** - Clarify use cases with concrete examples
+2. **Plan** - Identify needed scripts, references, assets
+3. **Initialize** - Run init_skill.py to create template
+4. **Edit** - Implement SKILL.md and resources
+5. **Validate** (optional) - Run quick_validate.py to check format
+6. **Iterate** - Improve based on real usage
+
+## Skill Naming
+
+- Use lowercase letters, digits, and hyphens only; normalize user-provided titles to hyphen-case (e.g., "Plan Mode" -> `plan-mode`).
+- When generating names, generate a name under 64 characters (letters, digits, hyphens).
+- Prefer short, verb-led phrases that describe the action.
+- Namespace by tool when it improves clarity or triggering (e.g., `gh-address-comments`, `linear-address-issue`).
+- Name the skill folder exactly after the skill name.
+
+## Step-by-Step Guide
+
+### Step 1: Understanding the Skill with Concrete Examples
+
+Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
+
+To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
+
+For example, when building an image-editor skill, relevant questions include:
+
+- "What functionality should the image-editor skill support? Editing, rotating, anything else?"
+- "Can you give some examples of how this skill would be used?"
+- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
+- "What would a user say that should trigger this skill?"
+
+To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
+
+Conclude this step when there is a clear sense of the functionality the skill should support.
+
+### Step 2: Planning the Reusable Skill Contents
+
+To turn concrete examples into an effective skill, analyze each example by:
+
+1. Considering how to execute on the example from scratch
+2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
+
+**Planning Checklist**:
+- ✅ **Always needed**: SKILL.md with clear description and usage instructions
+- ✅ **scripts/**: Only if code needs to be executed (not just shown as examples)
+- ❌ **references/**: Rarely needed - only if documentation is >500 lines and can't fit in SKILL.md
+- ✅ **assets/**: Only if files are used in output (templates, boilerplate, etc.)
+
+Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows:
+
+1. Rotating a PDF requires re-writing the same code each time
+2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill
+3. ❌ Don't create `references/api-docs.md` - put API info in SKILL.md instead
+
+Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
+
+1. Writing a frontend webapp requires the same boilerplate HTML/React each time
+2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill
+3. ❌ Don't create `references/usage-examples.md` - put examples in SKILL.md instead
+
+Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows:
+
+1. Querying BigQuery requires re-discovering the table schemas and relationships each time
+2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill (ONLY because schemas are very large)
+3. ❌ Don't create separate `references/query-examples.md` - put examples in SKILL.md instead
+
+To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets. **Default to putting everything in SKILL.md unless there's a compelling reason to separate it.**
+
+### Step 3: Initialize the Skill
+
+At this point, it is time to actually create the skill.
+
+Skip this step only if the skill being developed already exists, and iteration is needed. In this case, continue to the next step.
+
+When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
+
+Usage:
+
+```bash
+scripts/init_skill.py <skill-name> --path <output-directory> [--resources scripts,references,assets] [--examples]
+```
+
+Examples:
+
+```bash
+scripts/init_skill.py my-skill --path <workspace>/skills
+scripts/init_skill.py my-skill --path <workspace>/skills --resources scripts,references
+scripts/init_skill.py my-skill --path <workspace>/skills --resources scripts --examples
+```
+
+Where `<workspace>` is your workspace directory shown in the "工作空间" section of the system prompt.
+
+The script:
+
+- Creates the skill directory at the specified path
+- Generates a SKILL.md template with proper frontmatter and TODO placeholders
+- Optionally creates resource directories based on `--resources`
+- Optionally adds example files when `--examples` is set
+
+After initialization, customize the SKILL.md and add resources as needed. If you used `--examples`, replace or delete placeholder files.
+
+**Important**: Always create skills in workspace skills directory (`<workspace>/skills`), NOT in project directory. Check the "工作空间" section for the actual workspace path.
+
+### Step 4: Edit the Skill
+
+When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of the agent to use. Include information that would be beneficial and non-obvious to the agent. Consider what procedural knowledge, domain-specific details, or reusable assets would help another agent instance execute these tasks more effectively.
+
+#### Design Patterns
+
+**Workflow patterns** — For complex tasks, break operations into sequential steps or conditional branches:
+
+```markdown
+# Sequential: list numbered steps with scripts
+1. Analyze the form (run analyze_form.py)
+2. Create field mapping (edit fields.json)
+3. Fill the form (run fill_form.py)
+
+# Conditional: guide through decision points
+1. Determine the modification type:
+   **Creating new content?** → Follow "Creation workflow"
+   **Editing existing content?** → Follow "Editing workflow"
+```
+
+**Output patterns** — When consistent output format matters, provide a template or input/output examples in SKILL.md so the agent can follow the desired style.
+
+#### Start with Reusable Skill Contents
+
+To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.
+
+**Available Base Tools**:
+
+The agent has access to these core tools that you can leverage in your skill:
+- **bash**: Execute shell commands (use for curl, ls, grep, sed, awk, bc for calculations, etc.)
+- **read**: Read file contents
+- **write**: Write files
+- **edit**: Edit files with search/replace
+
+**Minimize Dependencies**:
+- ✅ **Prefer bash + curl** for HTTP API calls (no Python dependencies)
+- ✅ **Use bash tools** (grep, sed, awk) for text processing
+- ✅ **Keep scripts simple** - if bash can do it, no need for Python (document packages/versions if Python is used)
+
+**Important Guidelines**:
+- **scripts/**: Only create scripts that will be executed. Test all scripts before including.
+- **references/**: ONLY create if documentation is too large for SKILL.md (>500 lines). Most skills don't need this.
+- **assets/**: Only include files used in output (templates, icons, etc.)
+- **Default approach**: Put everything in SKILL.md unless there's a specific reason not to.
+
+Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
+
+If you used `--examples`, delete any placeholder files that are not needed for the skill. Only create resource directories that are actually required.
+
+#### Update SKILL.md
+
+**Writing Guidelines:** Always use imperative/infinitive form.
+
+##### Frontmatter
+
+Write the YAML frontmatter with `name`, `description`, and optional `metadata`:
+
+- `name`: The skill name
+- `description`: This is the primary triggering mechanism for your skill, and helps the agent understand when to use the skill.
+  - Include both what the Skill does and specific triggers/contexts for when to use it.
+  - Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to the agent.
+  - Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when the agent needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
+- `metadata`: (Optional) Specify requirements and configuration
+  - `requires.bins`: Required binaries (e.g., `["curl", "jq"]`)
+  - `requires.env`: Required environment variables — all must be set (e.g., `["MYAPI_KEY"]`)
+  - `requires.anyEnv`: Alternative environment variables — at least one must be set (e.g., `["OPENAI_API_KEY", "LINKAI_API_KEY"]`)
+  - `requires.anyBins`: Alternative binaries — at least one must be present
+  - `always`: Set to `true` to always load regardless of requirements
+  - `emoji`: Skill icon (optional)
+  - Do NOT set `category` — it defaults to `skill` and is managed by the system
+
+**API Key Requirements**:
+
+If your skill needs a single API key, declare it in `requires.env`:
+
+```yaml
+---
+name: my-search
+description: Search using MyAPI
+metadata:
+  requires:
+    bins: ["curl"]
+    env: ["MYAPI_KEY"]
+---
+```
+
+If your skill supports multiple API key providers (e.g., OpenAI or LinkAI), use `requires.anyEnv`:
+
+```yaml
+---
+name: my-vision
+description: Analyze images using Vision API
+metadata:
+  requires:
+    bins: ["curl"]
+    anyEnv: ["OPENAI_API_KEY", "LINKAI_API_KEY"]
+---
+```
+
+**Auto-enable rule**: Skills are automatically enabled when required environment variables are set, and automatically disabled when missing. No manual configuration needed.
+
+##### Body
+
+Write instructions for using the skill and its bundled resources.
+
+**If your skill requires an API key**, include setup instructions in the body:
+
+```markdown
+## Setup
+
+This skill requires an API key from [Service Name].
+
+1. Visit https://service.com to get an API key
+2. Configure it using: `env_config(action="set", key="SERVICE_API_KEY", value="your-key")`
+3. Or manually add to `~/cow/.env`: `SERVICE_API_KEY=your-key`
+4. Restart the agent for changes to take effect
+
+## Usage
+...
+```
+
+The bash script should check for the key and provide helpful error messages:
+
+```bash
+#!/usr/bin/env bash
+if [ -z "${SERVICE_API_KEY:-}" ]; then
+    echo "Error: SERVICE_API_KEY not set"
+    echo "Please configure your API key first (see SKILL.md)"
+    exit 1
+fi
+
+curl -H "Authorization: Bearer $SERVICE_API_KEY" ...
+```
+
+**Script Path Convention**:
+
+When writing SKILL.md instructions, remember that:
+- Skills are listed in `<available_skills>` with a `<base_dir>` path
+- Scripts should be referenced as: `<base_dir>/scripts/script_name.sh`
+- The AI will see the base_dir and can construct the full path
+
+Example instruction in SKILL.md:
+```markdown
+## Usage
+
+Scripts are in this skill's base directory (shown in skill listing).
+
+bash "<base_dir>/scripts/my_script.sh" <args>
+```
+
+### Step 5: Validate (Optional)
+
+Validate skill format:
+
+```bash
+scripts/quick_validate.py <path/to/skill-folder>
+```
+
+Example:
+
+```bash
+scripts/quick_validate.py <workspace>/skills/weather-api
+```
+
+Validation checks:
+- YAML frontmatter format and required fields
+- Skill naming conventions (hyphen-case, lowercase)
+- Description completeness and quality
+- File organization
+
+**Note**: Validation is optional in COW. Mainly useful for troubleshooting format issues.
+
+### Step 6: Iterate
+
+Improve based on real usage:
+
+1. Use skill on real tasks
+2. Notice struggles or inefficiencies
+3. Identify needed updates to SKILL.md or resources
+4. Implement changes and test again
+
+## Progressive Disclosure
+
+Skills use three-level loading:
+
+1. **Metadata** (name + description) - Always in context (~100 words)
+2. **SKILL.md body** - Loaded when skill triggers (<5k words)
+3. **Resources** - Loaded as needed by agent
+
+**Best practices**:
+- Keep SKILL.md under 500 lines
+- Split complex content into `references/` files
+- Reference these files clearly in SKILL.md
+
+**Pattern**: For skills with multiple variants/frameworks:
+- Keep core workflow in SKILL.md
+- Move variant-specific details to separate reference files
+- Agent loads only relevant files
+
+Example:
+```
+cloud-deploy/
+├── SKILL.md (workflow + provider selection)
+└── references/
+    ├── aws.md
+    ├── gcp.md
+    └── azure.md
+```
+
+When user chooses AWS, agent only reads aws.md.
diff --git a/skills/skill-creator/scripts/init_skill.py b/skills/skill-creator/scripts/init_skill.py
new file mode 100755
index 0000000..ecddc3e
--- /dev/null
+++ b/skills/skill-creator/scripts/init_skill.py
@@ -0,0 +1,303 @@
+#!/usr/bin/env python3
+"""
+Skill Initializer - Creates a new skill from template
+
+Usage:
+    init_skill.py <skill-name> --path <path>
+
+Examples:
+    init_skill.py my-new-skill --path skills/public
+    init_skill.py my-api-helper --path skills/private
+    init_skill.py custom-skill --path /custom/location
+"""
+
+import sys
+from pathlib import Path
+
+
+SKILL_TEMPLATE = """---
+name: {skill_name}
+description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
+---
+
+# {skill_title}
+
+## Overview
+
+[TODO: 1-2 sentences explaining what this skill enables]
+
+## Structuring This Skill
+
+[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
+
+**1. Workflow-Based** (best for sequential processes)
+- Works well when there are clear step-by-step procedures
+- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing"
+- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2...
+
+**2. Task-Based** (best for tool collections)
+- Works well when the skill offers different operations/capabilities
+- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text"
+- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2...
+
+**3. Reference/Guidelines** (best for standards or specifications)
+- Works well for brand guidelines, coding standards, or requirements
+- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features"
+- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage...
+
+**4. Capabilities-Based** (best for integrated systems)
+- Works well when the skill provides multiple interrelated features
+- Example: Product Management with "Core Capabilities" → numbered capability list
+- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature...
+
+Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
+
+Delete this entire "Structuring This Skill" section when done - it's just guidance.]
+
+## [TODO: Replace with the first main section based on chosen structure]
+
+[TODO: Add content here. See examples in existing skills:
+- Code samples for technical skills
+- Decision trees for complex workflows
+- Concrete examples with realistic user requests
+- References to scripts/templates/references as needed]
+
+## Resources
+
+This skill includes example resource directories that demonstrate how to organize different types of bundled resources:
+
+### scripts/
+Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
+
+**Examples from other skills:**
+- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
+- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
+
+**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
+
+**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments.
+
+### references/
+Documentation and reference material intended to be loaded into context to inform Claude's process and thinking.
+
+**Examples from other skills:**
+- Product management: `communication.md`, `context_building.md` - detailed workflow guides
+- BigQuery: API reference documentation and query examples
+- Finance: Schema documentation, company policies
+
+**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working.
+
+### assets/
+Files not intended to be loaded into context, but rather used within the output Claude produces.
+
+**Examples from other skills:**
+- Brand styling: PowerPoint template files (.pptx), logo files
+- Frontend builder: HTML/React boilerplate project directories
+- Typography: Font files (.ttf, .woff2)
+
+**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
+
+---
+
+**Any unneeded directories can be deleted.** Not every skill requires all three types of resources.
+"""
+
+EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
+"""
+Example helper script for {skill_name}
+
+This is a placeholder script that can be executed directly.
+Replace with actual implementation or delete if not needed.
+
+Example real scripts from other skills:
+- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
+- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
+"""
+
+def main():
+    print("This is an example script for {skill_name}")
+    # TODO: Add actual script logic here
+    # This could be data processing, file conversion, API calls, etc.
+
+if __name__ == "__main__":
+    main()
+'''
+
+EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
+
+This is a placeholder for detailed reference documentation.
+Replace with actual reference content or delete if not needed.
+
+Example real reference docs from other skills:
+- product-management/references/communication.md - Comprehensive guide for status updates
+- product-management/references/context_building.md - Deep-dive on gathering context
+- bigquery/references/ - API references and query examples
+
+## When Reference Docs Are Useful
+
+Reference docs are ideal for:
+- Comprehensive API documentation
+- Detailed workflow guides
+- Complex multi-step processes
+- Information too lengthy for main SKILL.md
+- Content that's only needed for specific use cases
+
+## Structure Suggestions
+
+### API Reference Example
+- Overview
+- Authentication
+- Endpoints with examples
+- Error codes
+- Rate limits
+
+### Workflow Guide Example
+- Prerequisites
+- Step-by-step instructions
+- Common patterns
+- Troubleshooting
+- Best practices
+"""
+
+EXAMPLE_ASSET = """# Example Asset File
+
+This placeholder represents where asset files would be stored.
+Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
+
+Asset files are NOT intended to be loaded into context, but rather used within
+the output Claude produces.
+
+Example asset files from other skills:
+- Brand guidelines: logo.png, slides_template.pptx
+- Frontend builder: hello-world/ directory with HTML/React boilerplate
+- Typography: custom-font.ttf, font-family.woff2
+- Data: sample_data.csv, test_dataset.json
+
+## Common Asset Types
+
+- Templates: .pptx, .docx, boilerplate directories
+- Images: .png, .jpg, .svg, .gif
+- Fonts: .ttf, .otf, .woff, .woff2
+- Boilerplate code: Project directories, starter files
+- Icons: .ico, .svg
+- Data files: .csv, .json, .xml, .yaml
+
+Note: This is a text placeholder. Actual assets can be any file type.
+"""
+
+
+def title_case_skill_name(skill_name):
+    """Convert hyphenated skill name to Title Case for display."""
+    return ' '.join(word.capitalize() for word in skill_name.split('-'))
+
+
+def init_skill(skill_name, path):
+    """
+    Initialize a new skill directory with template SKILL.md.
+
+    Args:
+        skill_name: Name of the skill
+        path: Path where the skill directory should be created
+
+    Returns:
+        Path to created skill directory, or None if error
+    """
+    # Determine skill directory path
+    skill_dir = Path(path).resolve() / skill_name
+
+    # Check if directory already exists
+    if skill_dir.exists():
+        print(f"❌ Error: Skill directory already exists: {skill_dir}")
+        return None
+
+    # Create skill directory
+    try:
+        skill_dir.mkdir(parents=True, exist_ok=False)
+        print(f"✅ Created skill directory: {skill_dir}")
+    except Exception as e:
+        print(f"❌ Error creating directory: {e}")
+        return None
+
+    # Create SKILL.md from template
+    skill_title = title_case_skill_name(skill_name)
+    skill_content = SKILL_TEMPLATE.format(
+        skill_name=skill_name,
+        skill_title=skill_title
+    )
+
+    skill_md_path = skill_dir / 'SKILL.md'
+    try:
+        skill_md_path.write_text(skill_content)
+        print("✅ Created SKILL.md")
+    except Exception as e:
+        print(f"❌ Error creating SKILL.md: {e}")
+        return None
+
+    # Create resource directories with example files
+    try:
+        # Create scripts/ directory with example script
+        scripts_dir = skill_dir / 'scripts'
+        scripts_dir.mkdir(exist_ok=True)
+        example_script = scripts_dir / 'example.py'
+        example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
+        example_script.chmod(0o755)
+        print("✅ Created scripts/example.py")
+
+        # Create references/ directory with example reference doc
+        references_dir = skill_dir / 'references'
+        references_dir.mkdir(exist_ok=True)
+        example_reference = references_dir / 'api_reference.md'
+        example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
+        print("✅ Created references/api_reference.md")
+
+        # Create assets/ directory with example asset placeholder
+        assets_dir = skill_dir / 'assets'
+        assets_dir.mkdir(exist_ok=True)
+        example_asset = assets_dir / 'example_asset.txt'
+        example_asset.write_text(EXAMPLE_ASSET)
+        print("✅ Created assets/example_asset.txt")
+    except Exception as e:
+        print(f"❌ Error creating resource directories: {e}")
+        return None
+
+    # Print next steps
+    print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}")
+    print("\nNext steps:")
+    print("1. Edit SKILL.md to complete the TODO items and update the description")
+    print("2. Customize or delete the example files in scripts/, references/, and assets/")
+    print("3. Run the validator when ready to check the skill structure")
+
+    return skill_dir
+
+
+def main():
+    if len(sys.argv) < 4 or sys.argv[2] != '--path':
+        print("Usage: init_skill.py <skill-name> --path <path>")
+        print("\nSkill name requirements:")
+        print("  - Hyphen-case identifier (e.g., 'data-analyzer')")
+        print("  - Lowercase letters, digits, and hyphens only")
+        print("  - Max 40 characters")
+        print("  - Must match directory name exactly")
+        print("\nExamples:")
+        print("  init_skill.py my-new-skill --path workspace/skills")
+        print("  init_skill.py my-api-helper --path /path/to/skills")
+        print("  init_skill.py custom-skill --path /custom/location")
+        sys.exit(1)
+
+    skill_name = sys.argv[1]
+    path = sys.argv[3]
+
+    print(f"🚀 Initializing skill: {skill_name}")
+    print(f"   Location: {path}")
+    print()
+
+    result = init_skill(skill_name, path)
+
+    if result:
+        sys.exit(0)
+    else:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/skills/skill-creator/scripts/package_skill.py b/skills/skill-creator/scripts/package_skill.py
new file mode 100755
index 0000000..02392e9
--- /dev/null
+++ b/skills/skill-creator/scripts/package_skill.py
@@ -0,0 +1,116 @@
+#!/usr/bin/env python3
+"""
+Skill Packager - Creates a distributable .skill file of a skill folder
+
+Usage:
+    python utils/package_skill.py <path/to/skill-folder> [output-directory]
+
+Example:
+    python utils/package_skill.py skills/public/my-skill
+    python utils/package_skill.py skills/public/my-skill ./dist
+"""
+
+import sys
+import os
+import zipfile
+from pathlib import Path
+
+# Add script directory to path for imports
+script_dir = Path(__file__).parent
+sys.path.insert(0, str(script_dir))
+
+from quick_validate import validate_skill
+
+
+def package_skill(skill_path, output_dir=None):
+    """
+    Package a skill folder into a .skill file.
+
+    Args:
+        skill_path: Path to the skill folder
+        output_dir: Optional output directory for the .skill file (defaults to current directory)
+
+    Returns:
+        Path to the created .skill file, or None if error
+    """
+    skill_path = Path(skill_path).resolve()
+
+    # Validate skill folder exists
+    if not skill_path.exists():
+        print(f"❌ Error: Skill folder not found: {skill_path}")
+        return None
+
+    if not skill_path.is_dir():
+        print(f"❌ Error: Path is not a directory: {skill_path}")
+        return None
+
+    # Validate SKILL.md exists
+    skill_md = skill_path / "SKILL.md"
+    if not skill_md.exists():
+        print(f"❌ Error: SKILL.md not found in {skill_path}")
+        return None
+
+    # Run validation before packaging
+    print("🔍 Validating skill...")
+    valid, message = validate_skill(skill_path)
+    if not valid:
+        print(f"❌ Validation failed: {message}")
+        print("   Please fix the validation errors before packaging.")
+        return None
+    print(f"✅ {message}\n")
+
+    # Determine output location
+    skill_name = skill_path.name
+    if output_dir:
+        output_path = Path(output_dir).resolve()
+        output_path.mkdir(parents=True, exist_ok=True)
+    else:
+        output_path = Path.cwd()
+
+    skill_filename = output_path / f"{skill_name}.skill"
+
+    # Create the .skill file (zip format)
+    try:
+        with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf:
+            # Walk through the skill directory
+            for file_path in skill_path.rglob('*'):
+                if file_path.is_file():
+                    # Calculate the relative path within the zip
+                    arcname = file_path.relative_to(skill_path.parent)
+                    zipf.write(file_path, arcname)
+                    print(f"  Added: {arcname}")
+
+        print(f"\n✅ Successfully packaged skill to: {skill_filename}")
+        return skill_filename
+
+    except Exception as e:
+        print(f"❌ Error creating .skill file: {e}")
+        return None
+
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: python utils/package_skill.py <path/to/skill-folder> [output-directory]")
+        print("\nExample:")
+        print("  python utils/package_skill.py skills/public/my-skill")
+        print("  python utils/package_skill.py skills/public/my-skill ./dist")
+        sys.exit(1)
+
+    skill_path = sys.argv[1]
+    output_dir = sys.argv[2] if len(sys.argv) > 2 else None
+
+    print(f"📦 Packaging skill: {skill_path}")
+    if output_dir:
+        print(f"   Output directory: {output_dir}")
+    print()
+
+    result = package_skill(skill_path, output_dir)
+
+    if result:
+        sys.exit(0)
+    else:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/skills/skill-creator/scripts/quick_validate.py b/skills/skill-creator/scripts/quick_validate.py
new file mode 100755
index 0000000..d9fbeb7
--- /dev/null
+++ b/skills/skill-creator/scripts/quick_validate.py
@@ -0,0 +1,95 @@
+#!/usr/bin/env python3
+"""
+Quick validation script for skills - minimal version
+"""
+
+import sys
+import os
+import re
+import yaml
+from pathlib import Path
+
+def validate_skill(skill_path):
+    """Basic validation of a skill"""
+    skill_path = Path(skill_path)
+
+    # Check SKILL.md exists
+    skill_md = skill_path / 'SKILL.md'
+    if not skill_md.exists():
+        return False, "SKILL.md not found"
+
+    # Read and validate frontmatter
+    content = skill_md.read_text()
+    if not content.startswith('---'):
+        return False, "No YAML frontmatter found"
+
+    # Extract frontmatter
+    match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL)
+    if not match:
+        return False, "Invalid frontmatter format"
+
+    frontmatter_text = match.group(1)
+
+    # Parse YAML frontmatter
+    try:
+        frontmatter = yaml.safe_load(frontmatter_text)
+        if not isinstance(frontmatter, dict):
+            return False, "Frontmatter must be a YAML dictionary"
+    except yaml.YAMLError as e:
+        return False, f"Invalid YAML in frontmatter: {e}"
+
+    # Define allowed properties
+    ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata'}
+
+    # Check for unexpected properties (excluding nested keys under metadata)
+    unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES
+    if unexpected_keys:
+        return False, (
+            f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. "
+            f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}"
+        )
+
+    # Check required fields
+    if 'name' not in frontmatter:
+        return False, "Missing 'name' in frontmatter"
+    if 'description' not in frontmatter:
+        return False, "Missing 'description' in frontmatter"
+
+    # Extract name for validation
+    name = frontmatter.get('name', '')
+    if not isinstance(name, str):
+        return False, f"Name must be a string, got {type(name).__name__}"
+    name = name.strip()
+    if name:
+        # Check naming convention (hyphen-case: lowercase with hyphens)
+        if not re.match(r'^[a-z0-9-]+$', name):
+            return False, f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)"
+        if name.startswith('-') or name.endswith('-') or '--' in name:
+            return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens"
+        # Check name length (max 64 characters per spec)
+        if len(name) > 64:
+            return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters."
+
+    # Extract and validate description
+    description = frontmatter.get('description', '')
+    if not isinstance(description, str):
+        return False, f"Description must be a string, got {type(description).__name__}"
+    description = description.strip()
+    if description:
+        # Check for angle brackets
+        if '<' in description or '>' in description:
+            return False, "Description cannot contain angle brackets (< or >)"
+        # Check description length (max 1024 characters per spec)
+        if len(description) > 1024:
+            return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters."
+
+    return True, "Skill is valid!"
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python quick_validate.py <skill_directory>")
+        sys.exit(1)
+    
+    valid, message = validate_skill(sys.argv[1])
+    print(message)
+    sys.exit(0 if valid else 1)
\ No newline at end of file
diff --git a/tests/test_bash_output_encoding.py b/tests/test_bash_output_encoding.py
new file mode 100644
index 0000000..2c455ff
--- /dev/null
+++ b/tests/test_bash_output_encoding.py
@@ -0,0 +1,59 @@
+# encoding:utf-8
+"""
+Regression test for the Bash tool spilling large output to a temp file.
+
+When a command's output exceeds DEFAULT_MAX_BYTES the full output is written to
+a temp file. That file must be opened with encoding='utf-8'; otherwise it falls
+back to the platform locale encoding (e.g. cp936/GBK on Chinese Windows), which
+raises UnicodeEncodeError for output containing emoji or other characters not
+representable in that codepage. The exception previously propagated out and
+turned an otherwise-successful command (exit code 0) into a tool error, losing
+all of its output.
+"""
+import os
+import sys
+import tempfile
+from unittest.mock import patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools.bash.bash import Bash
+
+
+def test_large_non_locale_output_is_saved_as_utf8(tmp_path):
+    tool = Bash({"cwd": str(tmp_path), "safety_mode": False})
+
+    # Emit ~80KB (> 50KB DEFAULT_MAX_BYTES) of an emoji so the tool spills the
+    # full output to a temp file. Raw UTF-8 bytes are written from the child so
+    # the command line stays pure ASCII and the child's own stdout encoding is
+    # irrelevant.
+    code = "import sys; sys.stdout.buffer.write((chr(0x1F389) * 20000).encode('utf-8'))"
+    command = f'"{sys.executable}" -c "{code}"'
+
+    real_named_temp_file = tempfile.NamedTemporaryFile
+    captured = {}
+
+    def spy(*args, **kwargs):
+        captured.update(kwargs)
+        return real_named_temp_file(*args, **kwargs)
+
+    temp_file_path = None
+    try:
+        with patch(
+            "agent.tools.bash.bash.tempfile.NamedTemporaryFile", side_effect=spy
+        ):
+            result = tool.execute({"command": command, "timeout": 60})
+
+        # Command succeeded, so the tool must not report an error.
+        assert result.status == "success", result.result
+
+        # The temp file must be opened as UTF-8 (the actual fix).
+        assert captured.get("encoding") == "utf-8"
+
+        # And the emoji must round-trip through the saved file.
+        temp_file_path = result.result["details"]["full_output_path"]
+        with open(temp_file_path, encoding="utf-8") as f:
+            assert "\U0001f389" in f.read()
+    finally:
+        if temp_file_path and os.path.exists(temp_file_path):
+            os.remove(temp_file_path)
diff --git a/tests/test_bash_streaming.py b/tests/test_bash_streaming.py
new file mode 100644
index 0000000..ff3d359
--- /dev/null
+++ b/tests/test_bash_streaming.py
@@ -0,0 +1,185 @@
+import subprocess
+import sys
+import time
+from unittest.mock import patch
+
+import pytest
+
+from agent.tools.bash.bash import Bash
+
+
+posix_only = pytest.mark.skipif(Bash._IS_WIN, reason="POSIX shell command")
+windows_only = pytest.mark.skipif(not Bash._IS_WIN, reason="Windows integration test")
+
+
+def _windows_pid_command(pid_file):
+    path = str(pid_file).replace("\\", "\\\\")
+    return (
+        f'"{sys.executable}" -c '
+        f'"import os,time;open(r\'{path}\',\'w\').write(str(os.getpid()));time.sleep(30)"'
+    )
+
+
+def _windows_pid_is_running(pid):
+    result = subprocess.run(
+        ["tasklist", "/FI", f"PID eq {pid}", "/FO", "CSV", "/NH"],
+        capture_output=True,
+        text=True,
+        errors="replace",
+    )
+    return f'"{pid}"' in result.stdout
+
+
+def _windows_kill_pid_file(pid_file):
+    if pid_file.exists():
+        subprocess.run(
+            ["taskkill", "/F", "/PID", pid_file.read_text()],
+            capture_output=True,
+        )
+
+
+@posix_only
+def test_fast_command_returns_output_without_progress(tmp_path):
+    tool = Bash({"cwd": str(tmp_path)})
+    progress = []
+    tool.progress_callback = progress.append
+
+    result = tool.execute({"command": "printf fast"})
+
+    assert result.status == "success"
+    assert result.result["output"] == "fast"
+    assert progress == []
+
+
+@posix_only
+def test_timeout_returns_promptly(tmp_path):
+    tool = Bash({"cwd": str(tmp_path)})
+    started = time.monotonic()
+
+    result = tool.execute({"command": "sleep 10", "timeout": 1})
+
+    assert result.status == "error"
+    assert "timed out after 1 seconds" in result.result
+    assert time.monotonic() - started < 3
+
+
+@posix_only
+def test_background_process_holding_pipe_does_not_hang(tmp_path):
+    tool = Bash({"cwd": str(tmp_path)})
+    started = time.monotonic()
+
+    result = tool.execute({"command": "sleep 10 & printf done", "timeout": 3})
+
+    assert result.status == "success"
+    assert result.result["output"] == "done"
+    assert time.monotonic() - started < 7
+
+
+@posix_only
+def test_output_without_trailing_newline_streams_progress(tmp_path):
+    tool = Bash({"cwd": str(tmp_path)})
+    progress = []
+    tool.progress_callback = progress.append
+
+    result = tool.execute({
+        "command": "for i in 1 2 3 4 5; do printf .; sleep 0.3; done",
+        "timeout": 5,
+    })
+
+    assert result.status == "success"
+    assert result.result["output"] == "....."
+    assert progress
+    assert progress[-1].endswith(".")
+
+
+def test_windows_kill_uses_taskkill_for_process_tree():
+    tool = Bash()
+    process = type("Process", (), {"pid": 1234, "poll": lambda self: None, "kill": lambda self: None})()
+
+    with patch.object(tool, "_IS_WIN", True), patch.object(subprocess, "run") as run:
+        run.return_value.returncode = 0
+        tool._kill_process(process)
+
+    run.assert_called_once_with(
+        ["taskkill", "/F", "/T", "/PID", "1234"],
+        capture_output=True,
+        timeout=5,
+    )
+
+
+def test_windows_kill_falls_back_when_taskkill_fails():
+    tool = Bash()
+    process = type("Process", (), {"pid": 1234, "poll": lambda self: None, "kill": lambda self: None})()
+
+    with patch.object(tool, "_IS_WIN", True), \
+            patch.object(subprocess, "run", side_effect=OSError), \
+            patch.object(process, "kill") as kill:
+        tool._kill_process(process)
+
+    kill.assert_called_once()
+
+
+@windows_only
+def test_windows_timeout_kills_process_tree(tmp_path):
+    pid_file = tmp_path / "timeout-child.pid"
+    child_command = _windows_pid_command(pid_file)
+    tool = Bash({"cwd": str(tmp_path)})
+    started = time.monotonic()
+
+    try:
+        result = tool.execute({
+            "command": f'start "" /b {child_command} & ping -n 30 127.0.0.1 >nul',
+            "timeout": 1,
+        })
+
+        assert result.status == "error"
+        assert "timed out after 1 seconds" in result.result
+        assert time.monotonic() - started < 8
+        assert pid_file.exists()
+        time.sleep(0.5)
+        assert not _windows_pid_is_running(pid_file.read_text())
+    finally:
+        _windows_kill_pid_file(pid_file)
+
+
+@windows_only
+def test_windows_long_running_command_streams_progress(tmp_path):
+    tool = Bash({"cwd": str(tmp_path)})
+    progress = []
+    tool.progress_callback = progress.append
+
+    result = tool.execute({
+        "command": (
+            f'"{sys.executable}" -u -c '
+            '"import sys,time; '
+            "[(sys.stdout.write('.'),sys.stdout.flush(),time.sleep(0.3)) "
+            'for _ in range(5)]"'
+        ),
+        "timeout": 5,
+    })
+
+    assert result.status == "success"
+    assert result.result["output"] == "....."
+    assert progress
+    assert progress[-1].endswith(".")
+
+
+@windows_only
+def test_windows_background_process_holding_pipe_does_not_hang(tmp_path):
+    pid_file = tmp_path / "background-child.pid"
+    child_command = _windows_pid_command(pid_file)
+    tool = Bash({"cwd": str(tmp_path)})
+    started = time.monotonic()
+
+    try:
+        result = tool.execute({
+            "command": f'start "" /b {child_command} & echo done',
+            "timeout": 3,
+        })
+
+        assert result.status == "success"
+        assert result.result["output"].strip() == "done"
+        assert time.monotonic() - started < 8
+        assert pid_file.exists()
+    finally:
+        _windows_kill_pid_file(pid_file)
diff --git a/tests/test_custom_provider.py b/tests/test_custom_provider.py
new file mode 100644
index 0000000..d80f2a3
--- /dev/null
+++ b/tests/test_custom_provider.py
@@ -0,0 +1,240 @@
+# encoding:utf-8
+"""
+Unit tests for multiple custom (OpenAI-compatible) provider support (issue #2838).
+
+Covers models/custom_provider.py:
+  - Backward compatibility: legacy custom_api_key / custom_api_base fallback
+  - Multi-provider selection via bot_type "custom:<id>" routing
+  - parse_custom_bot_type helper
+  - Robustness against malformed config (missing id, non-dict, non-list)
+"""
+import sys
+import os
+import unittest
+
+# Add project root to path
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+import config as config_module
+from config import Config
+
+
+def set_conf(d):
+    """Install a fresh Config as the global config used by conf()."""
+    config_module.config = Config(d)
+
+
+class TestParseCustomBotType(unittest.TestCase):
+    """parse_custom_bot_type() parsing logic."""
+
+    def setUp(self):
+        from models.custom_provider import parse_custom_bot_type
+        self.parse = parse_custom_bot_type
+
+    def test_legacy_custom(self):
+        is_custom, pid = self.parse("custom")
+        self.assertTrue(is_custom)
+        self.assertEqual(pid, "")
+
+    def test_custom_with_id(self):
+        is_custom, pid = self.parse("custom:3f2a9c1b")
+        self.assertTrue(is_custom)
+        self.assertEqual(pid, "3f2a9c1b")
+
+    def test_non_custom(self):
+        is_custom, pid = self.parse("openai")
+        self.assertFalse(is_custom)
+        self.assertEqual(pid, "")
+
+    def test_empty(self):
+        is_custom, pid = self.parse("")
+        self.assertFalse(is_custom)
+        self.assertEqual(pid, "")
+
+    def test_none(self):
+        is_custom, pid = self.parse(None)
+        self.assertFalse(is_custom)
+        self.assertEqual(pid, "")
+
+
+class TestResolveCustomCredentials(unittest.TestCase):
+    """resolve_custom_credentials() resolution order and fallbacks."""
+
+    def setUp(self):
+        from models.custom_provider import resolve_custom_credentials, get_custom_providers
+        self.resolve = resolve_custom_credentials
+        self.get_providers = get_custom_providers
+
+    # --- Backward compatibility ---
+
+    def test_legacy_fallback_when_no_providers(self):
+        set_conf({
+            "bot_type": "custom",
+            "custom_api_key": "legacy-key",
+            "custom_api_base": "https://legacy.example.com/v1",
+        })
+        self.assertEqual(
+            self.resolve(),
+            ("legacy-key", "https://legacy.example.com/v1", None),
+        )
+
+    def test_empty_config(self):
+        set_conf({"bot_type": "custom"})
+        self.assertEqual(self.resolve(), ("", None, None))
+
+    # --- Multi-provider selection via bot_type ---
+
+    def test_provider_selected_by_id(self):
+        set_conf({
+            "bot_type": "custom:abc12345",
+            "custom_providers": [
+                {"id": "sf001", "name": "provider-a", "api_key": "key-a",
+                 "api_base": "https://api.example.com/v1", "model": "model-a"},
+                {"id": "abc12345", "name": "provider-b", "api_key": "key-b",
+                 "api_base": "https://api.example.org/v1", "model": "model-b"},
+            ],
+        })
+        self.assertEqual(
+            self.resolve(),
+            ("key-b", "https://api.example.org/v1", "model-b"),
+        )
+
+    def test_id_not_found_falls_back_to_legacy(self):
+        set_conf({
+            "bot_type": "custom:ghost",
+            "custom_api_key": "legacy-key",
+            "custom_api_base": "https://legacy.example.com/v1",
+            "custom_providers": [
+                {"id": "sf001", "name": "provider-a", "api_key": "key-a",
+                 "api_base": "https://api.example.com/v1"},
+            ],
+        })
+        self.assertEqual(
+            self.resolve(),
+            ("legacy-key", "https://legacy.example.com/v1", None),
+        )
+
+    def test_provider_without_model_returns_none_model(self):
+        set_conf({
+            "bot_type": "custom:local01",
+            "custom_providers": [
+                {"id": "local01", "name": "local", "api_key": "", "api_base": "http://localhost:11434/v1"},
+            ],
+        })
+        self.assertEqual(
+            self.resolve(),
+            ("", "http://localhost:11434/v1", None),
+        )
+
+    # --- Robustness against malformed config ---
+
+    def test_malformed_entries_filtered_and_fallback(self):
+        set_conf({
+            "bot_type": "custom:nope",
+            "custom_api_key": "legacy-key",
+            "custom_api_base": "https://legacy.example.com/v1",
+            "custom_providers": [
+                {"name": "no-id", "api_key": "no-id-key"},   # invalid: no id
+                "not-a-dict",                                  # invalid: wrong type
+            ],
+        })
+        # All entries invalid -> treated as empty -> legacy fallback
+        self.assertEqual(
+            self.resolve(),
+            ("legacy-key", "https://legacy.example.com/v1", None),
+        )
+
+    def test_get_custom_providers_filters_invalid(self):
+        set_conf({
+            "bot_type": "custom",
+            "custom_providers": [
+                {"id": "ok1", "name": "ok", "api_key": "k", "api_base": "https://x/v1"},
+                {"name": "no-id", "api_key": "no-id"},   # dropped: no id
+                123,                                       # dropped
+            ],
+        })
+        providers = self.get_providers()
+        self.assertEqual(len(providers), 1)
+        self.assertEqual(providers[0]["id"], "ok1")
+
+    def test_custom_providers_not_a_list_falls_back(self):
+        set_conf({
+            "bot_type": "custom",
+            "custom_api_key": "legacy-key",
+            "custom_api_base": "https://legacy.example.com/v1",
+            "custom_providers": "oops-a-string",
+        })
+        self.assertEqual(
+            self.resolve(),
+            ("legacy-key", "https://legacy.example.com/v1", None),
+        )
+
+
+class TestGenerateProviderId(unittest.TestCase):
+    """generate_provider_id() produces valid short ids."""
+
+    def test_length_and_hex(self):
+        from models.custom_provider import generate_provider_id
+        pid = generate_provider_id()
+        self.assertEqual(len(pid), 8)
+        # Must be valid hex characters
+        int(pid, 16)
+
+    def test_uniqueness(self):
+        from models.custom_provider import generate_provider_id
+        ids = {generate_provider_id() for _ in range(100)}
+        self.assertEqual(len(ids), 100)
+
+
+class TestConfigDefaults(unittest.TestCase):
+    """The new config fields must exist with safe defaults."""
+
+    def test_default_config_has_custom_providers(self):
+        from config import available_setting
+        self.assertIn("custom_providers", available_setting)
+        self.assertEqual(available_setting["custom_providers"], [])
+
+    def test_default_config_no_custom_active_provider(self):
+        """custom_active_provider was removed — replaced by bot_type routing."""
+        from config import available_setting
+        self.assertNotIn("custom_active_provider", available_setting)
+
+
+class TestDragSensitiveNested(unittest.TestCase):
+    """drag_sensitive() must mask api_key in nested structures."""
+
+    def test_nested_api_key_masked(self):
+        from config import drag_sensitive
+        import json
+        test_config = {
+            "open_ai_api_key": "sk-1234567890abcdef",
+            "custom_providers": [
+                {"id": "x1", "name": "test", "api_key": "sk-nested-secret-key-long", "api_base": "https://x/v1"}
+            ],
+        }
+        result = drag_sensitive(test_config)
+        # Top-level key should be masked
+        self.assertNotIn("1234567890abcdef", str(result))
+        # Nested key should also be masked
+        self.assertNotIn("nested-secret-key-long", str(result))
+        # But the id/name/api_base should not be masked
+        self.assertIn("x1", str(result))
+        self.assertIn("test", str(result))
+        self.assertIn("https://x/v1", str(result))
+
+    def test_string_config_masked(self):
+        from config import drag_sensitive
+        import json
+        test_str = json.dumps({
+            "open_ai_api_key": "sk-1234567890abcdef",
+            "custom_providers": [
+                {"id": "x1", "api_key": "sk-nested-very-long-secret"}
+            ],
+        })
+        result = drag_sensitive(test_str)
+        self.assertNotIn("1234567890abcdef", result)
+        self.assertNotIn("nested-very-long-secret", result)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_custom_provider_handlers.py b/tests/test_custom_provider_handlers.py
new file mode 100644
index 0000000..48d666a
--- /dev/null
+++ b/tests/test_custom_provider_handlers.py
@@ -0,0 +1,289 @@
+# encoding:utf-8
+"""
+Unit tests for the multi custom-provider management API (issue #2838, web UI).
+
+Covers channel/web/web_channel.py::ModelsHandler:
+  - _custom_provider_cards / _provider_overview expansion
+  - _handle_set_custom_provider   (create / edit / activate)
+  - _handle_delete_custom_provider
+  - _handle_set_active_custom_provider
+
+Uses id-based routing (bot_type: "custom:<id>") — no custom_active_provider.
+"""
+import json
+import os
+import sys
+import types
+import unittest
+
+# Add project root to path.
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+# Stub the web.py framework so web_channel imports without the dependency.
+if "web" not in sys.modules:
+    _web_stub = types.ModuleType("web")
+    _web_stub.header = lambda *a, **k: None
+    _web_stub.data = lambda: b"{}"
+    _web_stub.ctx = types.SimpleNamespace()
+    sys.modules["web"] = _web_stub
+
+import config as config_module
+from config import Config
+from channel.web.web_channel import ModelsHandler
+
+
+def set_conf(d):
+    """Install a fresh Config as the global config used by conf()."""
+    config_module.config = Config(d)
+
+
+class _HandlerHarness:
+    """Test double around ModelsHandler that captures persisted config in
+    memory instead of touching config.json, and no-ops the Bridge reset."""
+
+    def __init__(self):
+        self.handler = ModelsHandler.__new__(ModelsHandler)
+        self._file_cfg = {}
+        self.bridge_resets = 0
+        # Patch the disk + bridge boundary on this instance.
+        self.handler._read_file_config = lambda: dict(self._file_cfg)
+        self.handler._write_file_config = self._capture_write
+        self.handler._reset_bridge = self._capture_reset
+
+    def _capture_write(self, data):
+        self._file_cfg = dict(data)
+
+    def _capture_reset(self):
+        self.bridge_resets += 1
+
+    def call(self, **payload):
+        # Resolve the bound method by action for convenience.
+        action = payload.get("action")
+        method = {
+            "set_custom_provider": self.handler._handle_set_custom_provider,
+            "delete_custom_provider": self.handler._handle_delete_custom_provider,
+            "set_active_custom_provider": self.handler._handle_set_active_custom_provider,
+        }[action]
+        return json.loads(method(payload))
+
+
+class TestSetCustomProvider(unittest.TestCase):
+    def setUp(self):
+        set_conf({"bot_type": "custom", "custom_providers": []})
+        self.h = _HandlerHarness()
+
+    def test_create_provider_does_not_hijack_bot_type(self):
+        """Creating a provider without make_active must not change bot_type."""
+        res = self.h.call(action="set_custom_provider", name="my-provider",
+                          api_base="https://api.example.com/v1", api_key="key-a")
+        self.assertEqual(res["status"], "success")
+        self.assertTrue(res["created"])
+        self.assertIn("id", res)
+        # bot_type must remain unchanged — no auto-activation.
+        bot_type = config_module.conf().get("bot_type")
+        self.assertEqual(bot_type, "custom")  # unchanged from setUp
+        providers = config_module.conf().get("custom_providers")
+        self.assertEqual(len(providers), 1)
+        self.assertEqual(providers[0]["id"], res["id"])
+        self.assertEqual(providers[0]["name"], "my-provider")
+        self.assertEqual(self.h.bridge_resets, 1)
+
+    def test_create_with_make_active_switches_bot_type(self):
+        """Creating a provider with make_active=true must switch bot_type."""
+        res = self.h.call(action="set_custom_provider", name="my-provider",
+                          api_base="https://api.example.com/v1", api_key="key-a",
+                          make_active=True)
+        self.assertEqual(res["status"], "success")
+        bot_type = config_module.conf().get("bot_type")
+        self.assertEqual(bot_type, f"custom:{res['id']}")
+
+    def test_create_requires_api_base(self):
+        res = self.h.call(action="set_custom_provider", name="x", api_key="k")
+        self.assertEqual(res["status"], "error")
+        self.assertIn("api_base", res["message"])
+
+    def test_create_requires_name(self):
+        res = self.h.call(action="set_custom_provider", name="", api_base="https://x/v1")
+        self.assertEqual(res["status"], "error")
+
+    def test_second_provider_does_not_steal_active(self):
+        # Explicitly activate the first provider.
+        res1 = self.h.call(action="set_custom_provider", name="a",
+                           api_base="https://a/v1", api_key="ak", make_active=True)
+        res2 = self.h.call(action="set_custom_provider", name="b",
+                           api_base="https://b/v1", api_key="bk")
+        self.assertTrue(res2["created"])
+        # First provider stays active — second creation doesn't steal it.
+        bot_type = config_module.conf().get("bot_type")
+        self.assertEqual(bot_type, f"custom:{res1['id']}")
+
+    def test_make_active_flag(self):
+        self.h.call(action="set_custom_provider", name="a",
+                    api_base="https://a/v1", api_key="ak")
+        res2 = self.h.call(action="set_custom_provider", name="b",
+                           api_base="https://b/v1", api_key="bk", make_active=True)
+        bot_type = config_module.conf().get("bot_type")
+        self.assertEqual(bot_type, f"custom:{res2['id']}")
+
+    def test_edit_keeps_key_when_omitted(self):
+        res = self.h.call(action="set_custom_provider", name="a",
+                          api_base="https://a/v1", api_key="secret")
+        pid = res["id"]
+        # Edit only the base; omit api_key.
+        res2 = self.h.call(action="set_custom_provider", name="a",
+                           id=pid, api_base="https://a2/v1")
+        self.assertEqual(res2["status"], "success")
+        self.assertFalse(res2["created"])
+        providers = config_module.conf().get("custom_providers")
+        self.assertEqual(providers[0]["api_base"], "https://a2/v1")
+        self.assertEqual(providers[0]["api_key"], "secret")  # preserved
+
+    def test_edit_can_rename(self):
+        res = self.h.call(action="set_custom_provider", name="old",
+                          api_base="https://a/v1", api_key="ak")
+        pid = res["id"]
+        res2 = self.h.call(action="set_custom_provider", name="new",
+                           id=pid, api_base="https://a/v1")
+        self.assertEqual(res2["status"], "success")
+        providers = config_module.conf().get("custom_providers")
+        self.assertEqual(providers[0]["name"], "new")
+        # ID stays the same
+        self.assertEqual(providers[0]["id"], pid)
+
+    def test_edit_clears_model_when_empty(self):
+        res = self.h.call(action="set_custom_provider", name="a",
+                          api_base="https://a/v1", api_key="ak", model="m1")
+        pid = res["id"]
+        self.assertEqual(config_module.conf().get("custom_providers")[0]["model"], "m1")
+        self.h.call(action="set_custom_provider", name="a", id=pid,
+                    api_base="https://a/v1", model="")
+        self.assertNotIn("model", config_module.conf().get("custom_providers")[0])
+
+
+class TestDeleteCustomProvider(unittest.TestCase):
+    def setUp(self):
+        set_conf({"bot_type": "custom", "custom_providers": []})
+        self.h = _HandlerHarness()
+        self.res_a = self.h.call(action="set_custom_provider", name="a",
+                                 api_base="https://a/v1", api_key="ak",
+                                 make_active=True)
+        self.res_b = self.h.call(action="set_custom_provider", name="b",
+                                 api_base="https://b/v1", api_key="bk")
+
+    def test_delete_unknown(self):
+        res = self.h.call(action="delete_custom_provider", id="ghost")
+        self.assertEqual(res["status"], "error")
+
+    def test_delete_non_active(self):
+        res = self.h.call(action="delete_custom_provider", id=self.res_b["id"])
+        self.assertEqual(res["status"], "success")
+        ids = [p["id"] for p in config_module.conf().get("custom_providers")]
+        self.assertEqual(ids, [self.res_a["id"]])
+        # bot_type unchanged (still pointing to a)
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{self.res_a['id']}")
+
+    def test_delete_active_falls_back_to_first_remaining(self):
+        # 'a' is active (created first); deleting it should re-point to 'b'.
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{self.res_a['id']}")
+        res = self.h.call(action="delete_custom_provider", id=self.res_a["id"])
+        self.assertEqual(res["status"], "success")
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{self.res_b['id']}")
+
+    def test_delete_last_reverts_to_legacy(self):
+        self.h.call(action="delete_custom_provider", id=self.res_a["id"])
+        self.h.call(action="delete_custom_provider", id=self.res_b["id"])
+        self.assertEqual(config_module.conf().get("custom_providers"), [])
+        # When all providers deleted, reverts to legacy "custom"
+        self.assertEqual(config_module.conf().get("bot_type"), "custom")
+
+
+class TestSetActiveCustomProvider(unittest.TestCase):
+    def setUp(self):
+        set_conf({"bot_type": "custom", "custom_providers": []})
+        self.h = _HandlerHarness()
+        self.res_a = self.h.call(action="set_custom_provider", name="a",
+                                 api_base="https://a/v1", api_key="ak",
+                                 make_active=True)
+        self.res_b = self.h.call(action="set_custom_provider", name="b",
+                                 api_base="https://b/v1", api_key="bk")
+
+    def test_set_active_valid(self):
+        res = self.h.call(action="set_active_custom_provider", id=self.res_b["id"])
+        self.assertEqual(res["status"], "success")
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{self.res_b['id']}")
+
+    def test_set_active_unknown(self):
+        res = self.h.call(action="set_active_custom_provider", id="ghost")
+        self.assertEqual(res["status"], "error")
+        # bot_type unchanged
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{self.res_a['id']}")
+
+    def test_activation_syncs_model_to_global(self):
+        """Activating a provider must write its model into global model field."""
+        set_conf({"bot_type": "custom", "custom_providers": [], "model": "gpt-4o"})
+        h = _HandlerHarness()
+        res = h.call(action="set_custom_provider", name="sf",
+                     api_base="https://sf/v1", api_key="k", model="deepseek-v3",
+                     make_active=True)
+        # Global model field should now be the provider's model.
+        self.assertEqual(config_module.conf().get("model"), "deepseek-v3")
+        self.assertEqual(config_module.conf().get("bot_type"), f"custom:{res['id']}")
+
+    def test_activation_without_model_keeps_global_model(self):
+        """Activating a provider with no model must not overwrite global model."""
+        set_conf({"bot_type": "custom", "custom_providers": [], "model": "gpt-4o"})
+        h = _HandlerHarness()
+        h.call(action="set_custom_provider", name="local",
+               api_base="http://localhost:11434/v1", api_key="",
+               make_active=True)
+        # Global model field should remain unchanged.
+        self.assertEqual(config_module.conf().get("model"), "gpt-4o")
+
+
+class TestProviderOverviewExpansion(unittest.TestCase):
+    """_provider_overview / _custom_provider_cards should expand the list."""
+
+    def test_no_custom_providers_keeps_single_card(self):
+        set_conf({"bot_type": "custom", "custom_providers": []})
+        cards = ModelsHandler._custom_provider_cards(config_module.conf())
+        self.assertEqual(cards, [])
+        overview = ModelsHandler._provider_overview()
+        custom_cards = [c for c in overview if c.get("id") == "custom"]
+        # Legacy single custom card remains present.
+        self.assertEqual(len(custom_cards), 1)
+
+    def test_multi_providers_expand_into_cards(self):
+        set_conf({
+            "bot_type": "custom:id_b",
+            "custom_providers": [
+                {"id": "id_a", "name": "a", "api_key": "ak", "api_base": "https://a/v1"},
+                {"id": "id_b", "name": "b", "api_key": "bk", "api_base": "https://b/v1", "model": "m"},
+            ],
+        })
+        overview = ModelsHandler._provider_overview()
+        custom_cards = [c for c in overview if c.get("is_custom")]
+        self.assertEqual(len(custom_cards), 2)
+        by_id = {c["custom_id"]: c for c in custom_cards}
+        self.assertEqual(by_id["id_a"]["id"], "custom:id_a")
+        self.assertFalse(by_id["id_a"]["active"])
+        self.assertTrue(by_id["id_b"]["active"])
+        self.assertEqual(by_id["id_b"]["model"], "m")
+        # No single legacy "custom" card when expanded.
+        self.assertFalse(any(c.get("id") == "custom" for c in overview))
+
+    def test_no_active_shows_none_active(self):
+        """When bot_type is plain 'custom', no card is marked active."""
+        set_conf({
+            "bot_type": "custom",
+            "custom_providers": [
+                {"id": "id_a", "name": "a", "api_key": "ak", "api_base": "https://a/v1"},
+                {"id": "id_b", "name": "b", "api_key": "bk", "api_base": "https://b/v1"},
+            ],
+        })
+        cards = ModelsHandler._custom_provider_cards(config_module.conf())
+        active_cards = [c for c in cards if c.get("active")]
+        self.assertEqual(len(active_cards), 0)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_dashscope_provider.py b/tests/test_dashscope_provider.py
new file mode 100644
index 0000000..f8eb349
--- /dev/null
+++ b/tests/test_dashscope_provider.py
@@ -0,0 +1,63 @@
+# encoding:utf-8
+"""Unit tests for Qwen DashScope qwen3.7-plus provider updates."""
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock, patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+class TestDashscopeConst(unittest.TestCase):
+    def test_qwen37_plus_constant_defined(self):
+        from common import const
+        self.assertEqual(const.QWEN37_PLUS, "qwen3.7-plus")
+
+    def test_qwen37_plus_in_model_list(self):
+        from common import const
+        self.assertIn("qwen3.7-plus", const.MODEL_LIST)
+
+    def test_qwen37_plus_before_qwen37_max_in_model_list(self):
+        from common import const
+        qwen_models = [m for m in const.MODEL_LIST if str(m).startswith("qwen")]
+        self.assertGreater(
+            len(qwen_models),
+            1,
+        )
+        self.assertEqual(qwen_models[0], "qwen3.7-plus")
+
+
+class TestDashscopeBotDefaultModel(unittest.TestCase):
+    def test_default_model_is_qwen37_plus(self):
+        mock_conf = MagicMock()
+        mock_conf.get = MagicMock(side_effect=lambda key, default=None: default)
+
+        with patch("models.dashscope.dashscope_bot.conf", return_value=mock_conf):
+            with patch("models.dashscope.dashscope_bot.SessionManager"):
+                from models.dashscope.dashscope_bot import DashscopeBot
+                bot = DashscopeBot.__new__(DashscopeBot)
+                bot.sessions = MagicMock()
+                bot.model_name = mock_conf.get("model") or "qwen3.7-plus"
+                self.assertEqual(bot.model_name, "qwen3.7-plus")
+
+    def test_default_model_string_in_source(self):
+        bot_path = os.path.join(
+            os.path.dirname(__file__), "..", "models", "dashscope", "dashscope_bot.py"
+        )
+        with open(bot_path, encoding="utf-8") as f:
+            source = f.read()
+        self.assertIn('"qwen3.7-plus"', source)
+
+
+class TestDashscopeMultimodalRouting(unittest.TestCase):
+    def test_qwen37_plus_uses_multimodal_api(self):
+        from models.dashscope.dashscope_bot import DashscopeBot
+        self.assertTrue(DashscopeBot._is_multimodal_model("qwen3.7-plus"))
+
+    def test_qwen37_max_uses_generation_api(self):
+        from models.dashscope.dashscope_bot import DashscopeBot
+        self.assertFalse(DashscopeBot._is_multimodal_model("qwen3.7-max"))
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_edit_tool.py b/tests/test_edit_tool.py
new file mode 100644
index 0000000..f558929
--- /dev/null
+++ b/tests/test_edit_tool.py
@@ -0,0 +1,138 @@
+# encoding:utf-8
+"""
+Regression tests for the Edit tool's fuzzy matching.
+
+When the provided oldText does not match byte-for-byte (usually because the
+whitespace differs), the Edit tool falls back to a whitespace-tolerant fuzzy
+match. The fuzzy match must replace only the matched region in the original
+file. It previously rewrote the entire file from a whitespace-normalized copy,
+which collapsed the indentation of every untouched line and corrupted the file
+(e.g. broke Python indentation).
+"""
+import os
+import sys
+import tempfile
+import unittest
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools.edit.edit import Edit
+
+
+class TestEditFuzzyPreservesWhitespace(unittest.TestCase):
+    def setUp(self):
+        self.work = tempfile.mkdtemp()
+        self.path = os.path.join(self.work, "sample.py")
+        self.original = (
+            "def foo():\n"
+            "    x = 1\n"
+            "    y = 2\n"
+            "    return x + y\n"
+        )
+        with open(self.path, "w", encoding="utf-8") as f:
+            f.write(self.original)
+        self.tool = Edit({"cwd": self.work})
+
+    def _read(self):
+        with open(self.path, "r", encoding="utf-8") as f:
+            return f.read()
+
+    def test_fuzzy_match_does_not_reformat_untouched_lines(self):
+        # oldText differs from the file only by extra spaces around '=', so the
+        # exact match fails and the fuzzy path is taken. Only the 'x = 1' line
+        # should change; the other lines must keep their 4-space indentation.
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "    x  =  1",
+            "newText": "    x = 100",
+        })
+        self.assertEqual(result.status, "success", result.result)
+
+        expected = (
+            "def foo():\n"
+            "    x = 100\n"
+            "    y = 2\n"
+            "    return x + y\n"
+        )
+        self.assertEqual(self._read(), expected)
+
+    def test_exact_match_still_replaces_in_place(self):
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "    y = 2",
+            "newText": "    y = 20",
+        })
+        self.assertEqual(result.status, "success", result.result)
+        self.assertEqual(
+            self._read(),
+            "def foo():\n    x = 1\n    y = 20\n    return x + y\n",
+        )
+
+    def test_multiline_fuzzy_match_preserves_surrounding_indentation(self):
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "    x = 1\n    y  =  2",  # extra spaces on 2nd line
+            "newText": "    x = 9\n    y = 8",
+        })
+        self.assertEqual(result.status, "success", result.result)
+        self.assertEqual(
+            self._read(),
+            "def foo():\n    x = 9\n    y = 8\n    return x + y\n",
+        )
+
+    def test_fuzzy_match_with_unindented_oldtext_preserves_file_indent(self):
+        # oldText has NO leading indentation (and loose spacing around '='), so
+        # the exact match fails and the fuzzy path runs against an indented file
+        # line. The file's indentation must be preserved -- kept OUTSIDE the
+        # replaced region -- instead of being swallowed into the match and
+        # dropped (which would break the file's indentation). newText is
+        # likewise unindented, mirroring exact-substring replacement.
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "x  =  1",
+            "newText": "x = 100",
+        })
+        self.assertEqual(result.status, "success", result.result)
+        self.assertEqual(
+            self._read(),
+            "def foo():\n    x = 100\n    y = 2\n    return x + y\n",
+        )
+
+    def test_exact_match_rejects_multiple_occurrences(self):
+        # Two byte-identical statements; the exact-match path applies and the
+        # uniqueness guard counts exact occurrences, so the ambiguous edit is
+        # rejected instead of silently editing only the first.
+        with open(self.path, "w", encoding="utf-8") as f:
+            f.write("a = 1\nb = 2\na = 1\n")
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "a = 1",
+            "newText": "a = 9",
+        })
+        self.assertEqual(result.status, "error", result.result)
+        self.assertIn("occurrences", result.result)
+        # An ambiguous match must leave the file untouched.
+        self.assertEqual(self._read(), "a = 1\nb = 2\na = 1\n")
+
+    def test_fuzzy_match_rejects_multiple_occurrences(self):
+        # oldText uses loose spacing, so the exact match fails and the fuzzy
+        # path runs. The uniqueness guard now counts with the SAME regex used
+        # to match/replace, so an ambiguous fuzzy match (two hits) is rejected
+        # rather than silently editing the first one.
+        with open(self.path, "w", encoding="utf-8") as f:
+            f.write("def foo():\n    x = 1\n    y = 2\n    x = 1\n")
+        result = self.tool.execute({
+            "path": self.path,
+            "oldText": "x  =  1",
+            "newText": "x = 99",
+        })
+        self.assertEqual(result.status, "error", result.result)
+        self.assertIn("occurrences", result.result)
+        self.assertEqual(
+            self._read(),
+            "def foo():\n    x = 1\n    y = 2\n    x = 1\n",
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_evolution.py b/tests/test_evolution.py
new file mode 100644
index 0000000..4b53523
--- /dev/null
+++ b/tests/test_evolution.py
@@ -0,0 +1,856 @@
+"""Self-evolution test harness.
+
+Simulates multiple realistic conversations and checks the evolution pass behaves
+correctly: stays silent when it should, evolves (memory/skill) when it should,
+backs up before editing, notifies the user, and supports undo.
+
+Two modes:
+  - stub  (default): the review agent's reasoning is replaced by a scripted
+    output per scenario. Fast, deterministic, validates the WIRING (backup,
+    record, inject, notify, undo, protection). No model calls.
+  - real:  the review agent runs the configured model for real. Validates the
+    QUALITY of the judgement (does it correctly decide to act / stay silent).
+
+Run:
+    python tests/test_evolution.py            # stub mode
+    python tests/test_evolution.py --real      # real model mode
+"""
+
+import os
+import sys
+import shutil
+import tempfile
+from pathlib import Path
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+# ---------------------------------------------------------------------------
+# Fakes
+# ---------------------------------------------------------------------------
+class FakeChannel:
+    """Captures channel.send calls instead of sending."""
+
+    def __init__(self):
+        self.sent = []
+
+    def send(self, reply, context):
+        self.sent.append({"content": getattr(reply, "content", str(reply)), "receiver": context.get("receiver")})
+
+
+class FakeModel:
+    pass
+
+
+class FakeAgent:
+    """Minimal stand-in for a chat Agent."""
+
+    def __init__(self, messages, tools=None):
+        import threading
+        self.messages = messages
+        self.messages_lock = threading.Lock()
+        self.tools = tools or []
+        self.model = FakeModel()
+        self.skill_manager = None
+        self.memory_manager = None
+
+
+class FakeReviewAgent:
+    """Review agent whose run_stream returns a scripted result (stub mode)."""
+
+    def __init__(self, scripted_output, workspace, on_edit=None):
+        self._out = scripted_output
+        self._workspace = workspace
+        self._on_edit = on_edit
+        self.model = None
+
+    def run_stream(self, user_message, clear_history=False, **kwargs):
+        # Simulate the side effects a real review agent would perform.
+        if self._on_edit:
+            self._on_edit(self._workspace)
+        return self._out
+
+
+class FakeAgentBridge:
+    """Stand-in for AgentBridge wiring used by the executor."""
+
+    def __init__(self, agent, scripted_output, on_edit=None):
+        self.agents = {"session_test": agent}
+        self.default_agent = agent
+        self._scripted = scripted_output
+        self._on_edit = on_edit
+        self.injected = []
+
+    def create_agent(self, **kwargs):
+        from agent.memory.config import get_default_memory_config
+        ws = get_default_memory_config().get_workspace()
+        return FakeReviewAgent(self._scripted, ws, on_edit=self._on_edit)
+
+    def remember_scheduled_output(self, session_id, content, channel_type="", task_description=""):
+        self.injected.append(content)
+
+
+# ---------------------------------------------------------------------------
+# Test scaffolding
+# ---------------------------------------------------------------------------
+def _setup_workspace():
+    """Create a realistic temp workspace: seeded memory + real editable skills.
+
+    Mirrors a real CowAgent workspace closely enough that the model has genuine
+    content to read, reason about, and edit during a real evolution pass.
+    """
+    ws = Path(tempfile.mkdtemp(prefix="evo_test_"))
+    (ws / "MEMORY.md").write_text(
+        "# Long-term Memory\n\n"
+        "## User\n"
+        "- Name: 大锤 (David)\n"
+        "- Lives in Shenzhen, works as a backend engineer\n"
+        "- Company: a fintech startup, team of 8\n\n"
+        "## Preferences\n"
+        "- Likes detailed technical explanations\n",
+        encoding="utf-8",
+    )
+    (ws / "memory").mkdir()
+    (ws / "output").mkdir()
+    skills = ws / "skills"
+
+    # Editable skill 1: weekly report generator (has a structural gap: no risk).
+    (skills / "weekly-report").mkdir(parents=True)
+    (skills / "weekly-report" / "SKILL.md").write_text(
+        "# Weekly Report\n\n"
+        "Generate a weekly work report from the user's notes.\n\n"
+        "## Steps\n"
+        "1. Collect this week's completed items.\n"
+        "2. Summarize key progress in 3-5 bullets.\n"
+        "3. List next week's plan.\n\n"
+        "## Output format\n"
+        "Markdown with sections: 本周进展 / 下周计划\n",
+        encoding="utf-8",
+    )
+
+    # Editable skill 2: expense tracker (has a wrong currency-format step).
+    (skills / "expense-tracker").mkdir(parents=True)
+    (skills / "expense-tracker" / "SKILL.md").write_text(
+        "# Expense Tracker\n\n"
+        "Record an expense into output/expenses.md.\n\n"
+        "## Steps\n"
+        "1. Parse amount and category from the user message.\n"
+        "2. Append a row to output/expenses.md.\n"
+        "3. Format the amount with a `$` prefix.\n",
+        encoding="utf-8",
+    )
+
+    # Editable skill 3: an API caller whose SKILL.md hardcodes a WRONG endpoint
+    # host. The conversation discovers the correct host at runtime; the right
+    # fix is to edit this file's source, not just log the corrected fact.
+    (skills / "data-fetch").mkdir(parents=True)
+    (skills / "data-fetch" / "SKILL.md").write_text(
+        "# Data Fetch\n\n"
+        "Fetch records from the data service.\n\n"
+        "## Steps\n"
+        "1. Build the request payload from the user's query.\n"
+        "2. POST it to `https://api.example-wrong.com/v1/fetch`.\n"
+        "3. Parse and return the `data` field.\n",
+        encoding="utf-8",
+    )
+
+    # Protected built-in skill: must never be edited by evolution.
+    (skills / "image-generation").mkdir(parents=True)
+    (skills / "image-generation" / "SKILL.md").write_text(
+        "# Image Generation (built-in)\nDo not modify.\n", encoding="utf-8"
+    )
+    return ws
+
+
+def _point_config_at(ws):
+    """Force the global memory config to use the temp workspace."""
+    from agent.memory.config import MemoryConfig, set_global_memory_config
+    set_global_memory_config(MemoryConfig(workspace_root=str(ws)))
+
+
+def _make_messages(turns):
+    msgs = []
+    for u, a in turns:
+        msgs.append({"role": "user", "content": u})
+        msgs.append({"role": "assistant", "content": a})
+    return msgs
+
+
+# ---------------------------------------------------------------------------
+# Scenarios
+# ---------------------------------------------------------------------------
+def scenario_silent():
+    """Pure small talk -> should stay SILENT (no change, no notify)."""
+    return {
+        "name": "闲聊 (should stay SILENT)",
+        "goal": "none",
+        "turns": [
+            ("在吗", "在的，有什么可以帮你？"),
+            ("今天周五了，终于要放假了", "是呀，周末好好休息一下。"),
+            ("哈哈是的，那没事了", "好的，随时找我。"),
+        ],
+        "scripted": "[SILENT]",
+        "on_edit": None,
+        "expect_evolved": False,
+    }
+
+
+def scenario_silent_qa():
+    """A normal knowledge Q&A -> nothing durable, should stay SILENT."""
+    return {
+        "name": "普通问答 (should stay SILENT)",
+        "goal": "none",
+        "turns": [
+            ("Python 里 list 和 tuple 有什么区别？",
+             "主要区别：list 可变、用 []；tuple 不可变、用 ()。tuple 更省内存、可作字典键。"),
+            ("那什么时候该用 tuple？", "当数据不应被修改、或要做字典键/集合元素时用 tuple。"),
+            ("懂了，谢谢", "不客气。"),
+        ],
+        "scripted": "[SILENT]",
+        "on_edit": None,
+        "expect_evolved": False,
+    }
+
+
+def scenario_silent_transient():
+    """User shares transient, non-durable info -> should stay SILENT."""
+    return {
+        "name": "临时信息 (should stay SILENT)",
+        "goal": "none",
+        "turns": [
+            ("帮我看下今天天气适合跑步吗，深圳", "深圳今天多云 26°C，傍晚湿度高，清晨或晚上跑步比较合适。"),
+            ("那我晚上去吧", "好的，记得补水。"),
+            ("行", "👍"),
+        ],
+        "scripted": "[SILENT]",
+        "on_edit": None,
+        "expect_evolved": False,
+    }
+
+
+def scenario_silent_advice():
+    """User asks for one-off advice, no reusable workflow -> should stay SILENT."""
+    return {
+        "name": "一次性建议 (should stay SILENT)",
+        "goal": "none",
+        "turns": [
+            ("给我起三个适合咖啡馆的名字", "可以考虑：① 拾光咖啡 ② 角落 Corner ③ 慢半拍。"),
+            ("第二个不错", "嗯，「角落 Corner」简洁好记。"),
+            ("就用这个了", "好的，祝开业顺利。"),
+        ],
+        "scripted": "[SILENT]",
+        "on_edit": None,
+        "expect_evolved": False,
+    }
+
+
+def scenario_memory_preference():
+    """User states a durable working preference -> update MEMORY.md."""
+    def edit(ws):
+        from datetime import datetime
+        p = ws / "memory" / (datetime.now().strftime("%Y-%m-%d") + ".md")
+        p.write_text((p.read_text() if p.exists() else "") + "- Prefers concise replies; avoid long explanations\n", encoding="utf-8")
+
+    return {
+        "name": "记忆-偏好 (should note in daily memory)",
+        "goal": "memory",
+        "turns": [
+            ("你能帮我解释下什么是数据库事务吗", "当然可以。数据库事务（Transaction）是一组要么全部成功、要么全部失败的操作单元，它有四个核心特性 ACID：原子性、一致性、隔离性、持久性……（接着是 5 段详细展开）"),
+            ("打住打住，太长了", "抱歉，我说得太细了。"),
+            ("对，你以后回答我都简短一点，抓重点就行，别长篇大论", "好的，明白了。"),
+            ("嗯这样挺好", "👌"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：你希望回答简短、抓重点\n"
+            "- 调整：更新了长期记忆 MEMORY.md\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_memory_contains": "concise",
+    }
+
+
+def scenario_memory_correction():
+    """User corrects a wrong fact the agent stated -> fix MEMORY.md."""
+    def edit(ws):
+        from datetime import datetime
+        p = ws / "memory" / (datetime.now().strftime("%Y-%m-%d") + ".md")
+        p.write_text((p.read_text() if p.exists() else "") + "- Correction: team size is now 15 (was recorded as 8)\n", encoding="utf-8")
+
+    return {
+        "name": "记忆-纠正事实 (should note correction in daily)",
+        "goal": "memory",
+        "turns": [
+            ("我们团队最近又招了几个人", "记得你们是 8 人的小团队，扩张了挺好的。"),
+            ("不对，我们现在是 15 个人了，上次你就记错了", "抱歉记错了，你们现在是 15 人团队。"),
+            ("嗯对，记住啊", "好的，记住了。"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：团队规模已是 15 人（之前记成 8 人）\n"
+            "- 调整：修正了长期记忆 MEMORY.md\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_memory_contains": "15",
+    }
+
+
+def scenario_skill_gap():
+    """Using weekly-report reveals a missing section -> patch the skill."""
+    def edit(ws):
+        p = ws / "skills" / "weekly-report" / "SKILL.md"
+        p.write_text(p.read_text() + "4. List risk items / blockers.\n", encoding="utf-8")
+
+    return {
+        "name": "技能-缺陷 (should patch weekly-report skill)",
+        "goal": "skill",
+        "turns": [
+            ("用周报技能帮我生成这周的周报，素材：完成了支付网关重构、修复了3个线上bug、对接了风控接口",
+             "好的，我用 weekly-report 技能生成：\n\n## 本周进展\n- 完成支付网关重构\n- 修复 3 个线上 bug\n- 对接风控接口\n\n## 下周计划\n- 联调风控接口"),
+            ("不错，但是每次周报都漏了风险项，我们 leader 每次都要问这个", "确实，风险项很重要。"),
+            ("对，你能不能让这个周报技能以后都带上风险项这一节", "可以的，我把它固化进技能。"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：周报需要固定包含「风险项」一节\n"
+            "- 调整：给 weekly-report 技能补充了风险项步骤\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_skill_contains": ("weekly-report", "risk"),
+    }
+
+
+def scenario_skill_error():
+    """A skill step is wrong (currency format) -> correct the skill."""
+    def edit(ws):
+        p = ws / "skills" / "expense-tracker" / "SKILL.md"
+        p.write_text(p.read_text().replace("`$` prefix", "`¥` prefix (RMB)"), encoding="utf-8")
+
+    return {
+        "name": "技能-报错纠正 (should fix expense-tracker skill)",
+        "goal": "skill",
+        "turns": [
+            ("用记账技能记一笔：午饭 35", "好的，已记录：午饭 $35（已写入 output/expenses.md）"),
+            ("怎么是美元？我们都是人民币啊", "抱歉，格式用错了，应该是 ¥35。"),
+            ("对，以后这个记账技能都用人民币符号", "明白，我修正技能里的货币格式。"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：记账应使用人民币符号 ¥ 而非 $\n"
+            "- 调整：修正了 expense-tracker 技能的货币格式步骤\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_skill_contains": ("expense-tracker", "¥"),
+    }
+
+
+def scenario_skill_wrong_config():
+    """A skill's SKILL.md hardcodes a wrong endpoint; the chat works around it
+    at runtime. Correct evolution = FIX the skill source, not log a memory note.
+    """
+    def edit(ws):
+        p = ws / "skills" / "data-fetch" / "SKILL.md"
+        p.write_text(
+            p.read_text().replace("api.example-wrong.com", "api.example-correct.com"),
+            encoding="utf-8",
+        )
+
+    return {
+        "name": "技能-配置错误 (should fix skill source, not log memory)",
+        "goal": "skill",
+        "turns": [
+            ("用 data-fetch 技能拉一下最新数据",
+             "好的，我按技能里的步骤 POST 到 https://api.example-wrong.com/v1/fetch …… 报错了，连接失败。"),
+            ("哦那个地址不对，正确的是 api.example-correct.com，你用这个调",
+             "好的，换成 https://api.example-correct.com/v1/fetch ，成功拿到数据了 ✅"),
+            ("嗯对，就是这个地址", "明白了，这个才是正确的服务地址。"),
+        ],
+        # The model must decide on its own to edit the skill; we still provide a
+        # scripted output for stub mode wiring.
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：data-fetch 的正确服务地址是 api.example-correct.com\n"
+            "- 调整：修正了 data-fetch 技能里写错的接口地址\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_skill_contains": ("data-fetch", "api.example-correct.com"),
+    }
+
+
+def scenario_skill_create():
+    """A reusable, repeatable workflow emerges that no skill covers, and the
+    user explicitly asks to make it permanent -> CREATE a new skill.
+    """
+    return {
+        "name": "技能-新增 (should create a new skill)",
+        "goal": "skill",
+        "turns": [
+            ("每周一帮我把客户反馈整理成晨会简报：先按「严重/一般/建议」给反馈分类，再统计每类数量，最后写一段 3 句话的总结，发我",
+             "好的，本周客户反馈晨会简报：\n\n## 严重 (2)\n- 支付失败\n- 数据丢失\n## 一般 (3)\n- 加载慢…\n## 建议 (1)\n- 增加暗色模式\n\n总结：本周以稳定性问题为主，建议优先排查支付与数据链路，其余可排期跟进。"),
+            ("很好，就是这个格式。上周我也是这么让你弄的", "嗯，分类+计数+三句总结这套流程挺顺手。"),
+            ("对，这个我每周一都要用，你能不能把这套流程固化下来，以后我直接说『生成客户反馈晨会简报』你就照这个来",
+             "可以，我把这套「客户反馈晨会简报」流程固化成一个可复用的技能。"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：你每周一都要按「分类+计数+三句总结」生成客户反馈晨会简报\n"
+            "- 调整：新建了「客户反馈晨会简报」技能，固化这套流程\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": _create_briefing_skill,
+        "expect_evolved": True,
+        "expect_new_skill": True,
+    }
+
+
+def scenario_skill_create_implicit():
+    """A complex, clearly-structured multi-step workflow is executed once. The
+    user NEVER says "I do this weekly" or "make this a skill" — the agent must
+    判断 on its own that this is a reusable procedure worth capturing.
+
+    This is the realistic, harder case: no explicit instruction to create a
+    skill, only an obviously repeatable workflow.
+    """
+    return {
+        "name": "技能-隐式新增 (complex workflow, user never asks to save)",
+        "goal": "skill",
+        "turns": [
+            ("帮我做一份竞品调研：对比一下 Notion、飞书文档、语雀这三个产品",
+             "好的，我按一套固定方法来做竞品调研：\n1. 先确定对比维度：定价、协作能力、模板生态、API 开放度、本地化；\n2. 逐个产品按维度收集信息；\n3. 做成对比表；\n4. 给出结论和选型建议。\n\n（随后产出了完整的五维度对比表 + 结论）"),
+            ("不错。再帮我用同样的方法调研一下 Slack、企业微信、钉钉",
+             "好的，沿用刚才那套方法（定价/协作/模板/API/本地化 五维度 → 收集 → 对比表 → 结论）：\n\n（产出了第二份五维度对比表 + 选型建议）"),
+            ("可以，结论挺清楚的", "嗯，这套五维度对比的方法做下来结构很清楚。"),
+        ],
+        # In real mode the model decides on its own. The scripted side effect
+        # only wires stub mode; it emulates capturing the procedure as a skill.
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 学到：你做竞品调研有一套固定方法（五维度对比 → 收集 → 对比表 → 结论）\n"
+            "- 调整：把这套竞品调研流程固化成了一个可复用技能\n"
+            "如果不对，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": _create_competitor_skill,
+        "expect_evolved": True,
+        "expect_new_skill": True,
+    }
+
+
+def _create_competitor_skill(ws):
+    """Stub side effect: emulate capturing the competitor-research procedure."""
+    d = ws / "skills" / "competitor-research"
+    d.mkdir(parents=True, exist_ok=True)
+    (d / "SKILL.md").write_text(
+        "# Competitor Research\n\n"
+        "Compare a set of products with a fixed methodology.\n\n"
+        "## Steps\n"
+        "1. Fix the comparison dimensions (pricing, collaboration, templates, API, localization).\n"
+        "2. Collect info per product across each dimension.\n"
+        "3. Build a comparison table.\n"
+        "4. Give a conclusion and recommendation.\n",
+        encoding="utf-8",
+    )
+
+
+def scenario_skill_no_create():
+    """A one-off, novel task with no sign of recurrence -> must NOT create a
+    skill (and ideally stay silent). Guards against over-eager skill creation.
+    """
+    return {
+        "name": "技能-不应新增 (one-off task, must NOT create skill)",
+        "goal": "none",
+        "turns": [
+            ("帮我把这段话翻译成英文：今晚的庆功宴改到 8 点", "翻译：The celebration dinner tonight is moved to 8 PM."),
+            ("谢谢", "不客气。"),
+            ("嗯没事了", "好的，随时找我。"),
+        ],
+        "scripted": "[SILENT]",
+        "on_edit": None,
+        "expect_evolved": False,
+        "expect_no_new_skill": True,
+    }
+
+
+def _create_briefing_skill(ws):
+    """Stub side effect: emulate creating a new skill under workspace skills/."""
+    d = ws / "skills" / "customer-feedback-briefing"
+    d.mkdir(parents=True, exist_ok=True)
+    (d / "SKILL.md").write_text(
+        "# Customer Feedback Briefing\n\n"
+        "Turn raw customer feedback into a standup briefing.\n\n"
+        "## Steps\n"
+        "1. Classify each item as 严重/一般/建议.\n"
+        "2. Count items per category.\n"
+        "3. Write a 3-sentence summary.\n",
+        encoding="utf-8",
+    )
+
+
+def scenario_unfinished_task():
+    """A promised deliverable was not produced -> finish it now via tools."""
+    def edit(ws):
+        p = ws / "output" / "team-roster.md"
+        p.write_text("# Team Roster (backend)\n- 张伟\n- 李娜\n- 王强\n- 大锤\n", encoding="utf-8")
+
+    return {
+        "name": "未完成任务 (should finish & write output file)",
+        "goal": "task",
+        "turns": [
+            ("帮我把后端团队花名册整理成一个文件保存下，成员有：张伟、李娜、王强，还有我自己（大锤）",
+             "好的，后端 4 个人：张伟、李娜、王强、大锤。我整理成文件保存到 output/team-roster.md。"),
+            ("好的麻烦了，我先去开个会", "没问题，我现在就处理。"),
+            ("（用户离开，会话中断，文件尚未写入）", "（助手未及写入文件，对话中断）"),
+        ],
+        "scripted": (
+            "我刚做了一次自我学习。\n"
+            "- 发现：之前答应整理团队花名册但没完成\n"
+            "- 已完成：把后端成员名单写入 output/team-roster.md\n"
+            "如果不需要，回复「撤销上次学习」即可。"
+        ),
+        "on_edit": edit,
+        "expect_evolved": True,
+        "expect_output_file": "team-roster.md",
+    }
+
+
+SCENARIOS = [
+    scenario_silent,
+    scenario_silent_qa,
+    scenario_silent_transient,
+    scenario_silent_advice,
+    scenario_memory_preference,
+    scenario_memory_correction,
+    scenario_skill_gap,
+    scenario_skill_error,
+    scenario_skill_wrong_config,
+    scenario_skill_create,
+    scenario_skill_create_implicit,
+    scenario_skill_no_create,
+    scenario_unfinished_task,
+]
+
+# Skill directories present in a fresh workspace; anything beyond these that
+# appears after a pass is a newly-created skill.
+_SEED_SKILLS = {"weekly-report", "expense-tracker", "data-fetch", "image-generation"}
+
+
+def _new_skill_dirs(ws: Path) -> set:
+    """Skill directories created beyond the seeded set."""
+    skills_dir = ws / "skills"
+    if not skills_dir.exists():
+        return set()
+    return {p.name for p in skills_dir.iterdir() if p.is_dir()} - _SEED_SKILLS
+
+
+# ---------------------------------------------------------------------------
+# Runner (stub mode)
+# ---------------------------------------------------------------------------
+def run_stub():
+    from agent.evolution.executor import run_evolution_for_session
+    from agent.evolution import backup as backup_mod
+    from config import conf
+    # Evolution is disabled by default now; enable for the test.
+    conf()["self_evolution_enabled"] = True
+
+    passed, failed = 0, 0
+    for make in SCENARIOS:
+        sc = make()
+        ws = _setup_workspace()
+        try:
+            _point_config_at(ws)
+            # Patch channel push to capture instead of send.
+            channel = FakeChannel()
+            import agent.evolution.executor as ex
+            orig_notify = ex._notify_user
+            ex._notify_user = lambda ct, rcv, summary: channel.send(
+                type("R", (), {"content": summary})(),
+                {"receiver": rcv},
+            )
+
+            agent = FakeAgent(_make_messages(sc["turns"]))
+            bridge = FakeAgentBridge(agent, sc["scripted"], on_edit=sc["on_edit"])
+
+            evolved = run_evolution_for_session(
+                bridge, "session_test", channel_type="telegram", receiver="user_42"
+            )
+
+            ok = True
+            errs = []
+
+            if evolved != sc["expect_evolved"]:
+                ok = False
+                errs.append(f"evolved={evolved}, expected {sc['expect_evolved']}")
+
+            if sc["expect_evolved"]:
+                # memory / skill content checks
+                if "expect_memory_contains" in sc:
+                    # Evolution now writes to the dated daily file, not MEMORY.md.
+                    from datetime import datetime
+                    daily = ws / "memory" / (datetime.now().strftime("%Y-%m-%d") + ".md")
+                    mem = daily.read_text() if daily.exists() else ""
+                    if sc["expect_memory_contains"] not in mem:
+                        ok = False
+                        errs.append("daily memory missing expected content")
+                if "expect_skill_contains" in sc:
+                    sk, txt = sc["expect_skill_contains"]
+                    content = (ws / "skills" / sk / "SKILL.md").read_text()
+                    if txt not in content:
+                        ok = False
+                        errs.append("skill missing expected content")
+                if sc.get("expect_new_skill") and not _new_skill_dirs(ws):
+                    ok = False
+                    errs.append("expected a new skill to be created")
+                # notify happened
+                if not channel.sent:
+                    ok = False
+                    errs.append("no notification sent")
+                # injection happened (undo support)
+                if not bridge.injected or "[EVOLUTION]" not in bridge.injected[0]:
+                    ok = False
+                    errs.append("no [EVOLUTION] record injected")
+                # protected skill untouched
+                prot = (ws / "skills" / "image-generation" / "SKILL.md").read_text()
+                if prot != "# Image Generation (built-in)\nDo not modify.\n":
+                    ok = False
+                    errs.append("PROTECTED skill was modified!")
+                # backup exists (undo possible)
+                backups = list((ws / "memory" / ".evolution_backups").glob("*"))
+                if not backups:
+                    ok = False
+                    errs.append("no backup created")
+            else:
+                # SILENT: nothing should have changed / been sent
+                if channel.sent:
+                    ok = False
+                    errs.append("notification sent on SILENT")
+                if bridge.injected:
+                    ok = False
+                    errs.append("injected record on SILENT")
+            if sc.get("expect_no_new_skill") and _new_skill_dirs(ws):
+                ok = False
+                errs.append(f"unexpected new skill created: {_new_skill_dirs(ws)}")
+
+            ex._notify_user = orig_notify
+
+            if ok:
+                passed += 1
+                print(f"  PASS  {sc['name']}")
+            else:
+                failed += 1
+                print(f"  FAIL  {sc['name']}: {'; '.join(errs)}")
+        finally:
+            shutil.rmtree(ws, ignore_errors=True)
+
+    # Undo verification (uses the memory scenario's backup path).
+    print("\n-- undo tool --")
+    _verify_undo()
+
+    print(f"\nStub results: {passed} passed, {failed} failed")
+    return failed == 0
+
+
+def _verify_undo():
+    from agent.evolution.backup import create_backup, restore_backup
+    ws = _setup_workspace()
+    try:
+        _point_config_at(ws)
+        mem = ws / "MEMORY.md"
+        bid = create_backup(ws, [mem])
+        mem.write_text("CORRUPTED", encoding="utf-8")
+        from agent.tools.evolution_undo import EvolutionUndoTool
+        r = EvolutionUndoTool().execute({"backup_id": bid})
+        restored = mem.read_text()
+        if r.status == "success" and "大锤" in restored:
+            print("  PASS  undo restores pre-evolution state")
+        else:
+            print(f"  FAIL  undo: status={r.status}, content={restored[:40]}")
+    finally:
+        shutil.rmtree(ws, ignore_errors=True)
+
+
+# ---------------------------------------------------------------------------
+# Runner (real mode) — minimal: just prints the model's decision per scenario.
+# ---------------------------------------------------------------------------
+def _snapshot_ws(ws: Path) -> dict:
+    """Map every text file under the workspace -> content (skip backups dir)."""
+    snap = {}
+    for p in ws.rglob("*"):
+        if not p.is_file():
+            continue
+        rel = str(p.relative_to(ws))
+        if rel.startswith("memory/.evolution_backups"):
+            continue
+        try:
+            snap[rel] = p.read_text(encoding="utf-8")
+        except Exception:
+            pass
+    return snap
+
+
+def _print_diff(before: dict, after: dict) -> bool:
+    """Print added/changed files. Returns True if anything changed."""
+    changed = False
+    keys = sorted(set(before) | set(after))
+    for rel in keys:
+        old = before.get(rel)
+        new = after.get(rel)
+        if old == new:
+            continue
+        changed = True
+        tag = "NEW FILE" if old is None else "CHANGED"
+        print(f"      ~ {rel} [{tag}]")
+        old_lines = set((old or "").splitlines())
+        for line in (new or "").splitlines():
+            if line not in old_lines:
+                print(f"          + {line}")
+    return changed
+
+
+def run_real():
+    """Run real model evolution on each scenario and print the actual output.
+
+    Uses config.json's configured model via a real AgentBridge, so you see
+    exactly what the model decides and writes for each conversation.
+    """
+    from bridge.bridge import Bridge
+    from agent.memory.config import (
+        MemoryConfig,
+        set_global_memory_config,
+        get_default_memory_config,
+    )
+    from config import conf, load_config
+
+    # Load config.json so real API keys are available to the bots.
+    load_config()
+
+    # Default the test to deepseek-v4-flash (fast, low cost) unless overridden.
+    override_model = os.environ.get("EVO_TEST_MODEL", "deepseek-v4-flash")
+    conf()["model"] = override_model
+    conf()["bot_type"] = os.environ.get("EVO_TEST_BOT_TYPE", "deepseek")
+    # Force-enable evolution for the test regardless of config.json default.
+    conf()["self_evolution_enabled"] = True
+    print(f"[test] model: {override_model} (bot_type={conf().get('bot_type')}, "
+          f"key={'set' if conf().get('deepseek_api_key') else 'MISSING'})")
+
+    from agent.memory.manager import MemoryManager
+    import agent.evolution.executor as ex
+
+    bridge = Bridge()
+    agent_bridge = bridge.get_agent_bridge()
+
+    # Capture the user-facing reply instead of pushing it to a channel.
+    captured = {"reply": None}
+    orig_notify = ex._notify_user
+    ex._notify_user = lambda ct, rcv, summary: captured.__setitem__("reply", summary)
+
+    results = []  # (name, goal, evolved, changed, reply_ok)
+
+    only = os.environ.get("EVO_TEST_ONLY")  # substring filter on goal/name
+    try:
+        for make in SCENARIOS:
+            sc = make()
+            if only and only not in sc["goal"] and only not in sc["name"]:
+                continue
+            ws = _setup_workspace()
+            captured["reply"] = None
+            try:
+                mem_cfg = MemoryConfig(workspace_root=str(ws))
+                set_global_memory_config(mem_cfg)
+
+                sid = "session_evo_real"
+                # Fully isolated agent: tool cwd + memory_manager -> temp ws.
+                iso_mem = MemoryManager(mem_cfg)
+                agent = agent_bridge.create_agent(
+                    system_prompt="You are a helpful assistant.",
+                    tools=None,
+                    workspace_dir=str(ws),
+                    memory_manager=iso_mem,
+                    enable_skills=False,
+                )
+                # Notify path needs a channel+receiver to fire; give dummies.
+                agent_bridge.agents[sid] = agent
+                with agent.messages_lock:
+                    agent.messages.clear()
+                    agent.messages.extend(_make_messages(sc["turns"]))
+
+                before = _snapshot_ws(ws)
+
+                print("\n" + "=" * 72)
+                print(f"场景: {sc['name']}   [目标: {sc['goal']}]")
+                print("-" * 72)
+                print("【会话输入】")
+                for u, a in sc["turns"]:
+                    print(f"   用户: {u}")
+                    print(f"   助手: {a}")
+
+                from agent.evolution.executor import run_evolution_for_session
+                evolved = run_evolution_for_session(
+                    agent_bridge, sid, channel_type="telegram", receiver="tester"
+                )
+
+                after = _snapshot_ws(ws)
+                print("\n【进化结果】 evolved =", evolved)
+                changed = False
+                if evolved:
+                    changed = _print_diff(before, after)
+                    if not changed:
+                        print("      (无文件变更)")
+                else:
+                    print("      (静默，未做任何改动)")
+
+                new_skills = _new_skill_dirs(ws)
+                if new_skills:
+                    print(f"      新建技能: {', '.join(sorted(new_skills))}")
+                # Surface mismatches against the scenario's skill expectation.
+                if sc.get("expect_new_skill") and not new_skills:
+                    print("      ⚠ 预期新建技能，但未创建")
+                if sc.get("expect_no_new_skill") and new_skills:
+                    print("      ⚠ 不应新建技能，但创建了")
+
+                print("\n【给用户的回复】")
+                if captured["reply"]:
+                    for line in captured["reply"].splitlines():
+                        print(f"   {line}")
+                else:
+                    print("   (无推送)")
+
+                reply_ok = bool(captured["reply"]) == bool(evolved)
+                results.append((sc["name"], sc["goal"], evolved, changed, reply_ok))
+                agent_bridge.agents.pop(sid, None)
+            finally:
+                shutil.rmtree(ws, ignore_errors=True)
+    finally:
+        ex._notify_user = orig_notify
+
+    # Summary table.
+    print("\n" + "=" * 72)
+    print("汇总 (deepseek-v4-flash 真实运行)")
+    print("-" * 72)
+    for name, goal, evolved, changed, reply_ok in results:
+        exp = "静默" if goal == "none" else "应进化"
+        got = "进化" if evolved else "静默"
+        mark = "✓" if (goal == "none") != evolved else "✗"
+        print(f"  {mark}  {name:42s} 预期={exp} 实际={got}")
+
+
+if __name__ == "__main__":
+    if "--debug" in sys.argv:
+        import logging
+        from common.log import logger as _cow_logger
+        _cow_logger.setLevel(logging.DEBUG)
+        for _h in _cow_logger.handlers:
+            _h.setLevel(logging.DEBUG)
+    if "--real" in sys.argv:
+        run_real()
+    else:
+        ok = run_stub()
+        sys.exit(0 if ok else 1)
diff --git a/tests/test_invariant_bash.py b/tests/test_invariant_bash.py
new file mode 100644
index 0000000..776f33c
--- /dev/null
+++ b/tests/test_invariant_bash.py
@@ -0,0 +1,24 @@
+import pytest
+from agent.tools.bash.bash import Bash
+
+
+@pytest.mark.parametrize("command", [
+    "cat ~/.cow/.env",
+    "cat .cow/.env",
+    "less ~/.cow/.env",
+    "cat /home/user/.cow/.env",
+])
+def test_credential_file_access_is_blocked(command):
+    result = Bash().execute({"command": command})
+    assert result.status == "error", f"Expected blocked result for: {command}"
+    assert "Access denied" in str(result.result)
+
+
+@pytest.mark.parametrize("command", [
+    "ls ~/.cow/skills",
+    "ls ~/.cow/",
+    "echo hello",
+])
+def test_legitimate_cow_directory_access_is_not_blocked(command):
+    result = Bash().execute({"command": command})
+    assert "Access denied" not in str(result.result)
diff --git a/tests/test_knowledge_service.py b/tests/test_knowledge_service.py
new file mode 100644
index 0000000..5740816
--- /dev/null
+++ b/tests/test_knowledge_service.py
@@ -0,0 +1,298 @@
+import asyncio
+import os
+import sqlite3
+from pathlib import Path
+from unittest.mock import patch
+
+from agent.memory.storage import MemoryChunk, MemoryStorage
+from agent.knowledge.service import KnowledgeService
+
+
+class FakeStorage:
+    def __init__(self):
+        self.deleted = []
+
+    def delete_by_path(self, path):
+        self.deleted.append(path)
+
+
+class FakeMemoryManager:
+    def __init__(self):
+        self.storage = FakeStorage()
+        self.dirty = 0
+        self.synced = 0
+
+    def mark_dirty(self):
+        self.dirty += 1
+
+    async def sync(self):
+        self.synced += 1
+
+
+def service(tmp_path):
+    (tmp_path / "knowledge").mkdir()
+    manager = FakeMemoryManager()
+    return KnowledgeService(str(tmp_path), manager), manager
+
+
+def test_category_lifecycle_and_confirmation(tmp_path):
+    svc, manager = service(tmp_path)
+    assert svc.dispatch("create_category", {"path": "notes"})["payload"]["created"]
+    (tmp_path / "knowledge/notes/a.md").write_text("# A", encoding="utf-8")
+
+    denied = svc.dispatch("delete_category", {"path": "notes"})
+    assert denied["code"] == 403
+
+    result = svc.dispatch("delete_category", {"path": "notes", "confirm": True})
+    assert result["payload"]["deleted_documents"] == 1
+    assert manager.storage.deleted == ["knowledge/notes/a.md"]
+    assert manager.synced == 1
+
+
+def test_rename_category_reindexes_documents(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/old/sub").mkdir(parents=True)
+    (tmp_path / "knowledge/old/a.md").write_text("a", encoding="utf-8")
+    (tmp_path / "knowledge/old/sub/b.md").write_text("b", encoding="utf-8")
+
+    result = svc.dispatch("rename_category", {"path": "old", "new_path": "new"})
+    assert result["code"] == 200
+    assert sorted(manager.storage.deleted) == [
+        "knowledge/old/a.md", "knowledge/old/sub/b.md"
+    ]
+    assert manager.synced == 1
+    assert (tmp_path / "knowledge/new/sub/b.md").exists()
+
+
+def test_delete_documents_is_idempotent_and_protects_metadata(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/index.md").write_text("index", encoding="utf-8")
+    (tmp_path / "knowledge/a.md").write_text("a", encoding="utf-8")
+
+    protected = svc.dispatch("delete_documents", {"paths": ["index.md"]})
+    assert protected["code"] == 403
+    first = svc.dispatch("delete_documents", {"paths": ["a.md", "missing.md"]})
+    assert first["payload"]["deleted"] == 1
+    second = svc.dispatch("delete_documents", {"paths": ["a.md"]})
+    assert second["payload"]["deleted"] == 0
+    assert manager.storage.deleted == ["knowledge/a.md", "knowledge/missing.md", "knowledge/a.md"]
+    assert manager.synced == 2
+
+
+def test_move_documents_rejects_overwrite_and_syncs(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/source").mkdir()
+    (tmp_path / "knowledge/target").mkdir()
+    (tmp_path / "knowledge/source/a.md").write_text("a", encoding="utf-8")
+    (tmp_path / "knowledge/source/b.md").write_text("b", encoding="utf-8")
+    (tmp_path / "knowledge/target/b.md").write_text("existing", encoding="utf-8")
+
+    result = svc.dispatch("move_documents", {
+        "paths": ["source/a.md", "source/b.md"], "target_category": "target"
+    })
+    assert result["payload"]["moved"] == 1
+    assert result["payload"]["results"][1]["reason"] == "target_exists"
+    assert manager.storage.deleted == ["knowledge/source/a.md"]
+    assert manager.synced == 1
+
+
+def test_path_traversal_and_symlink_escape_are_rejected(tmp_path):
+    svc, _ = service(tmp_path)
+    outside = tmp_path / "outside"
+    outside.mkdir()
+    (tmp_path / "knowledge/link").symlink_to(outside, target_is_directory=True)
+
+    assert svc.dispatch("create_category", {"path": "../bad"})["code"] == 403
+    assert svc.dispatch("create_category", {"path": "link/bad"})["code"] == 403
+
+
+def test_dispatch_sync_works_inside_running_event_loop(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/source").mkdir()
+    (tmp_path / "knowledge/target").mkdir()
+    (tmp_path / "knowledge/source/a.md").write_text("a", encoding="utf-8")
+
+    async def run():
+        return svc.dispatch("move_documents", {
+            "paths": ["source/a.md"], "target_category": "target"
+        })
+
+    assert asyncio.run(run())["code"] == 200
+    assert manager.synced == 1
+
+
+def test_real_storage_delete_by_path_removes_chunks_and_file_metadata(tmp_path):
+    storage = MemoryStorage(tmp_path / "index.db")
+    path = "knowledge/category/a.md"
+    storage.save_chunks_batch([MemoryChunk(
+        id="chunk-1", user_id=None, scope="shared", source="knowledge",
+        path=path, start_line=1, end_line=1, text="unique content",
+        embedding=None, hash="hash-1",
+    )])
+    storage.update_file_metadata(path, "knowledge", "file-hash", 1, 14)
+
+    storage.delete_by_path(path)
+
+    assert storage.conn.execute("SELECT COUNT(*) FROM chunks WHERE path = ?", (path,)).fetchone()[0] == 0
+    assert storage.conn.execute("SELECT COUNT(*) FROM files WHERE path = ?", (path,)).fetchone()[0] == 0
+    storage.close()
+
+
+def test_missing_document_still_cleans_stale_index(tmp_path):
+    svc, manager = service(tmp_path)
+
+    result = svc.dispatch("delete_documents", {"paths": ["removed-by-agent.md"]})
+
+    assert result["code"] == 200
+    assert result["payload"]["results"][0]["reason"] == "not_found"
+    assert manager.storage.deleted == ["knowledge/removed-by-agent.md"]
+    assert manager.dirty == 1
+    assert manager.synced == 1
+
+
+def test_category_rename_handles_concurrent_disappearance(tmp_path):
+    svc, manager = service(tmp_path)
+    category = tmp_path / "knowledge/source"
+    category.mkdir()
+    (category / "a.md").write_text("a", encoding="utf-8")
+    def disappear_then_rename(path, target):
+        (category / "a.md").unlink()
+        category.rmdir()
+        raise FileNotFoundError(path)
+
+    with patch.object(Path, "rename", disappear_then_rename):
+        result = svc.dispatch("rename_category", {"path": "source", "new_path": "target"})
+
+    assert result["code"] == 200
+    assert result["payload"]["reason"] == "not_found"
+    assert manager.storage.deleted == []
+
+
+def test_category_delete_handles_concurrent_disappearance(tmp_path):
+    svc, manager = service(tmp_path)
+    category = tmp_path / "knowledge/source"
+    category.mkdir()
+    (category / "a.md").write_text("a", encoding="utf-8")
+
+    def disappear_then_delete(path):
+        (category / "a.md").unlink()
+        category.rmdir()
+        raise FileNotFoundError(path)
+
+    with patch("agent.knowledge.service.shutil.rmtree", side_effect=disappear_then_delete):
+        result = svc.dispatch("delete_category", {"path": "source", "confirm": True})
+
+    assert result["code"] == 200
+    assert result["payload"]["reason"] == "not_found"
+    assert manager.storage.deleted == []
+
+
+def test_move_does_not_overwrite_target_created_concurrently(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/source").mkdir()
+    (tmp_path / "knowledge/target").mkdir()
+    source = tmp_path / "knowledge/source/a.md"
+    target = tmp_path / "knowledge/target/a.md"
+    source.write_text("source", encoding="utf-8")
+    real_link = os.link
+
+    def create_target_then_link(src, dst):
+        target.write_text("concurrent", encoding="utf-8")
+        return real_link(src, dst)
+
+    with patch("agent.knowledge.service.os.link", side_effect=create_target_then_link):
+        result = svc.dispatch("move_documents", {
+            "paths": ["source/a.md"], "target_category": "target",
+        })
+
+    assert result["payload"]["results"][0]["reason"] == "target_exists"
+    assert source.read_text(encoding="utf-8") == "source"
+    assert target.read_text(encoding="utf-8") == "concurrent"
+    assert manager.storage.deleted == []
+
+
+def test_create_document_writes_and_syncs(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/notes").mkdir()
+
+    result = svc.dispatch("create_document", {
+        "path": "notes/new.md", "content": "# New\nBody",
+    })
+
+    assert result["code"] == 200
+    assert (tmp_path / "knowledge/notes/new.md").read_text(encoding="utf-8") == "# New\nBody"
+    assert manager.dirty == 1
+    assert manager.synced == 1
+
+
+def test_import_documents_supports_md_txt_and_rename_conflicts(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/notes").mkdir()
+    (tmp_path / "knowledge/notes/a.md").write_text("existing", encoding="utf-8")
+
+    result = svc.dispatch("import_documents", {
+        "target_category": "notes",
+        "conflict_strategy": "rename",
+        "files": [
+            {"filename": "a.md", "content": b"# A"},
+            {"filename": "plain.txt", "content": "plain text"},
+        ],
+    })
+
+    assert result["code"] == 200
+    assert result["payload"]["imported"] == 2
+    assert (tmp_path / "knowledge/notes/a-1.md").read_text(encoding="utf-8") == "# A"
+    assert (tmp_path / "knowledge/notes/plain.md").read_text(encoding="utf-8") == "plain text"
+    assert manager.storage.deleted == []
+    assert manager.synced == 1
+
+
+def test_import_documents_skip_overwrite_and_failures(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/notes").mkdir()
+    existing = tmp_path / "knowledge/notes/a.md"
+    existing.write_text("old", encoding="utf-8")
+
+    skipped = svc.dispatch("import_documents", {
+        "target_category": "notes",
+        "conflict_strategy": "skip",
+        "files": [{"filename": "a.md", "content": b"new"}],
+    })
+    assert skipped["payload"]["skipped"] == 1
+    assert existing.read_text(encoding="utf-8") == "old"
+    assert manager.synced == 0
+
+    overwritten = svc.dispatch("import_documents", {
+        "target_category": "notes",
+        "conflict_strategy": "overwrite",
+        "files": [
+            {"filename": "a.md", "content": b"new"},
+            {"filename": "bad.pdf", "content": b"%PDF"},
+        ],
+    })
+    assert overwritten["payload"]["imported"] == 1
+    assert overwritten["payload"]["failed"] == 1
+    assert existing.read_text(encoding="utf-8") == "new"
+    assert manager.storage.deleted == ["knowledge/notes/a.md"]
+    assert manager.synced == 1
+
+
+def test_import_documents_rejects_large_files_and_batches(tmp_path):
+    svc, manager = service(tmp_path)
+    (tmp_path / "knowledge/notes").mkdir()
+    assert svc.MAX_IMPORT_TOTAL_SIZE == 200 * 1024 * 1024
+
+    too_large = svc.dispatch("import_documents", {
+        "target_category": "notes",
+        "files": [{"filename": "big.md", "content": b"x" * (svc.MAX_IMPORT_FILE_SIZE + 1)}],
+    })
+    assert too_large["payload"]["failed"] == 1
+    assert too_large["payload"]["results"][0]["reason"] == "file too large"
+
+    too_many = svc.dispatch("import_documents", {
+        "target_category": "notes",
+        "files": [{"filename": f"{i}.md", "content": b"x"} for i in range(svc.MAX_IMPORT_FILES + 1)],
+    })
+    assert too_many["code"] == 403
+    assert "too many files" in too_many["message"]
+    assert manager.synced == 0
diff --git a/tests/test_knowledge_web.py b/tests/test_knowledge_web.py
new file mode 100644
index 0000000..6ab2dba
--- /dev/null
+++ b/tests/test_knowledge_web.py
@@ -0,0 +1,127 @@
+import json
+from pathlib import Path
+from unittest.mock import patch
+
+
+def test_knowledge_action_handler_delegates_to_dispatch(tmp_path):
+    from channel.web.web_channel import KnowledgeActionHandler
+
+    request = {"action": "create_category", "payload": {"path": "research"}}
+    dispatched = {"action": "create_category", "code": 200, "message": "success",
+                  "payload": {"path": "research", "created": True}}
+
+    with patch("channel.web.web_channel._require_auth"), \
+         patch("channel.web.web_channel.web.header"), \
+         patch("channel.web.web_channel.web.data", return_value=json.dumps(request).encode()), \
+         patch("channel.web.web_channel._get_workspace_root", return_value=str(tmp_path)), \
+         patch("agent.knowledge.service.KnowledgeService.dispatch", return_value=dispatched) as dispatch:
+        response = json.loads(KnowledgeActionHandler().POST())
+
+    dispatch.assert_called_once_with("create_category", {"path": "research"})
+    assert response["status"] == "success"
+    assert response["payload"]["created"] is True
+
+
+def test_knowledge_action_handler_preserves_dispatch_error(tmp_path):
+    from channel.web.web_channel import KnowledgeActionHandler
+
+    dispatched = {"action": "delete_documents", "code": 403,
+                  "message": "protected knowledge file: index.md", "payload": None}
+    request = {"action": "delete_documents", "payload": {"paths": ["index.md"]}}
+
+    with patch("channel.web.web_channel._require_auth"), \
+         patch("channel.web.web_channel.web.header"), \
+         patch("channel.web.web_channel.web.data", return_value=json.dumps(request).encode()), \
+         patch("channel.web.web_channel._get_workspace_root", return_value=str(tmp_path)), \
+         patch("agent.knowledge.service.KnowledgeService.dispatch", return_value=dispatched):
+        response = json.loads(KnowledgeActionHandler().POST())
+
+    assert response["status"] == "error"
+    assert response["code"] == 403
+    assert response["message"] == "protected knowledge file: index.md"
+
+
+def test_knowledge_frontend_management_contract():
+    root = Path(__file__).parents[1]
+    html = (root / "channel/web/chat.html").read_text(encoding="utf-8")
+    js = (root / "channel/web/static/js/console.js").read_text(encoding="utf-8")
+
+    assert 'id="knowledge-dialog-overlay"' in html
+    assert 'id="knowledge-dialog-textarea"' in html
+    assert 'id="knowledge-document-form"' in html
+    assert 'id="knowledge-document-path-preview"' in html
+    assert "function openKnowledgeDialog(" in js
+    assert "function _knowledgeCategoryPaths(" in js
+    assert "dispatchKnowledgeAction('create_category'" in js
+    assert "dispatchKnowledgeAction('create_document'" in js
+    assert "dispatchKnowledgeAction('rename_category'" in js
+    assert "dispatchKnowledgeAction('delete_category'" in js
+    assert "dispatchKnowledgeAction('delete_documents'" in js
+    assert "dispatchKnowledgeAction('move_documents'" in js
+    assert 'id="knowledge-import-input"' in html
+    assert "function createKnowledgeDocument(" in js
+    assert "function openKnowledgeDocumentEditor(" in js
+    assert "documentPathPreview.textContent = options.category" in js
+    assert "options.type === 'document'" in js
+    assert "input.classList.toggle('hidden', options.type === 'select' || options.type === 'textarea' || options.type === 'document')" in js
+    assert "function selectKnowledgeImportFiles(" in js
+    assert "function importKnowledgeDocuments(" in js
+    assert "function validateKnowledgeImportFiles(" in js
+    assert "KNOWLEDGE_IMPORT_MAX_FILE_SIZE" in js
+    assert "fetch('/api/knowledge/import'" in js
+    assert "initKnowledgeImportDropZone()" in js
+
+    knowledge_section = js[js.index("// Knowledge View"):js.index("function _hasFilterMatch")]
+    assert "prompt(" not in knowledge_section
+    assert "alert(" not in knowledge_section
+    assert "if (path === 'index.md' || path === 'log.md') return '';" in knowledge_section
+
+
+class UploadedFile:
+    def __init__(self, filename, content):
+        self.filename = filename
+        self.value = content
+
+
+def test_knowledge_import_handler_delegates_to_dispatch(tmp_path):
+    from channel.web.web_channel import KnowledgeImportHandler
+
+    dispatched = {"action": "import_documents", "code": 200, "message": "success",
+                  "payload": {"imported": 2, "skipped": 0, "failed": 0}}
+    params = {
+        "target_category": "notes",
+        "conflict_strategy": "rename",
+        "files": [UploadedFile("a.md", b"# A"), UploadedFile("b.txt", b"B")],
+    }
+
+    with patch("channel.web.web_channel._require_auth"), \
+         patch("channel.web.web_channel.web.header"), \
+         patch("channel.web.web_channel._raw_web_input", return_value=params), \
+         patch("channel.web.web_channel._get_workspace_root", return_value=str(tmp_path)), \
+         patch("agent.knowledge.service.KnowledgeService.dispatch", return_value=dispatched) as dispatch:
+        response = json.loads(KnowledgeImportHandler().POST())
+
+    dispatch.assert_called_once()
+    action, payload = dispatch.call_args.args
+    assert action == "import_documents"
+    assert payload["target_category"] == "notes"
+    assert payload["conflict_strategy"] == "rename"
+    assert [f["filename"] for f in payload["files"]] == ["a.md", "b.txt"]
+    assert response["status"] == "success"
+    assert response["payload"]["imported"] == 2
+
+
+def test_knowledge_import_handler_rejects_large_content_length(tmp_path):
+    from channel.web.web_channel import KnowledgeImportHandler
+    from agent.knowledge.service import KnowledgeService
+    assert KnowledgeService.MAX_IMPORT_TOTAL_SIZE == 200 * 1024 * 1024
+
+    with patch("channel.web.web_channel._require_auth"), \
+         patch("channel.web.web_channel.web.header"), \
+         patch("channel.web.web_channel.web.ctx") as ctx:
+        ctx.env = {"CONTENT_LENGTH": str(KnowledgeService.MAX_IMPORT_TOTAL_SIZE + 1)}
+        response = json.loads(KnowledgeImportHandler().POST())
+
+    assert response["status"] == "error"
+    assert response["code"] == 413
+    assert response["message"] == "import batch too large"
diff --git a/tests/test_mcp_tool_retrieval.py b/tests/test_mcp_tool_retrieval.py
new file mode 100644
index 0000000..84aeef7
--- /dev/null
+++ b/tests/test_mcp_tool_retrieval.py
@@ -0,0 +1,253 @@
+# encoding:utf-8
+"""
+Unit tests for on-demand MCP tool retrieval.
+
+Covers the invariants the maintainer asked for in the feature review:
+  * below threshold / degrade paths behave exactly like today (full injection),
+  * the injected MCP tool set only ever grows within a run (never shrinks),
+plus the pure selection helpers (query building, cosine, top-k, fallbacks).
+"""
+import os
+import sys
+import unittest
+from unittest.mock import patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools.mcp.tool_retrieval import (
+    build_retrieval_query,
+    cosine_similarity,
+    select_mcp_tools,
+)
+from agent.tools.mcp.mcp_tool import McpTool
+
+
+def _mcp_tool(name, description=""):
+    """Build a real McpTool without needing a live MCP client."""
+    return McpTool(
+        client=None,
+        tool_schema={"name": name, "description": description, "inputSchema": {}},
+        server_name="test-server",
+    )
+
+
+class _FakeBuiltinTool:
+    """Minimal stand-in for a built-in BaseTool."""
+
+    def __init__(self, name):
+        self.name = name
+        self.description = f"builtin {name}"
+        self.params = {"type": "object", "properties": {}}
+
+    def get_json_schema(self):
+        return {}
+
+
+class _FakeToolManager:
+    """Controls the vectors/query embeddings seen by the executor."""
+
+    def __init__(self, tool_vectors, query_vectors):
+        self._tool_vectors = tool_vectors
+        self._query_vectors = list(query_vectors)
+        self._call = 0
+
+    def get_mcp_tool_vectors(self):
+        return dict(self._tool_vectors)
+
+    def embed_query(self, text):
+        if self._call < len(self._query_vectors):
+            vec = self._query_vectors[self._call]
+        else:
+            vec = self._query_vectors[-1] if self._query_vectors else None
+        self._call += 1
+        return vec
+
+
+# --------------------------------------------------------------------------
+# Pure helper: build_retrieval_query
+# --------------------------------------------------------------------------
+
+class TestBuildRetrievalQuery(unittest.TestCase):
+
+    def test_empty_messages(self):
+        self.assertEqual(build_retrieval_query([]), "")
+
+    def test_extracts_text_blocks(self):
+        messages = [
+            {"role": "user", "content": [{"type": "text", "text": "hello"}]},
+            {"role": "assistant", "content": [{"type": "text", "text": "world"}]},
+        ]
+        self.assertEqual(build_retrieval_query(messages), "hello\nworld")
+
+    def test_skips_tool_result_and_tool_use(self):
+        messages = [
+            {"role": "user", "content": [{"type": "text", "text": "do it"}]},
+            {"role": "assistant", "content": [
+                {"type": "tool_use", "name": "read", "input": {}},
+            ]},
+            {"role": "user", "content": [
+                {"type": "tool_result", "content": "huge payload " * 100},
+            ]},
+        ]
+        self.assertEqual(build_retrieval_query(messages), "do it")
+
+    def test_string_content_supported(self):
+        messages = [{"role": "user", "content": "plain string"}]
+        self.assertEqual(build_retrieval_query(messages), "plain string")
+
+    def test_respects_recent_window(self):
+        messages = [
+            {"role": "user", "content": [{"type": "text", "text": f"m{i}"}]}
+            for i in range(10)
+        ]
+        # Only the last 3 messages should be kept.
+        self.assertEqual(build_retrieval_query(messages, max_messages=3), "m7\nm8\nm9")
+
+
+# --------------------------------------------------------------------------
+# Pure helper: cosine_similarity
+# --------------------------------------------------------------------------
+
+class TestCosineSimilarity(unittest.TestCase):
+
+    def test_identical_vectors(self):
+        self.assertAlmostEqual(cosine_similarity([1.0, 0.0], [1.0, 0.0]), 1.0)
+
+    def test_orthogonal_vectors(self):
+        self.assertAlmostEqual(cosine_similarity([1.0, 0.0], [0.0, 1.0]), 0.0)
+
+    def test_degenerate_inputs(self):
+        self.assertEqual(cosine_similarity([], [1.0]), 0.0)
+        self.assertEqual(cosine_similarity([0.0, 0.0], [1.0, 1.0]), 0.0)
+        self.assertEqual(cosine_similarity([1.0], [1.0, 0.0]), 0.0)
+
+
+# --------------------------------------------------------------------------
+# Pure helper: select_mcp_tools
+# --------------------------------------------------------------------------
+
+class TestSelectMcpTools(unittest.TestCase):
+
+    def setUp(self):
+        self.vectors = {
+            "a": [1.0, 0.0, 0.0],
+            "b": [0.0, 1.0, 0.0],
+            "c": [0.0, 0.0, 1.0],
+            "d": [0.9, 0.1, 0.0],
+        }
+
+    def test_returns_top_k(self):
+        selected = select_mcp_tools([1.0, 0.0, 0.0], self.vectors, top_k=2,
+                                    already_selected=set())
+        self.assertEqual(selected, {"a", "d"})
+
+    def test_union_only_grows_across_turns(self):
+        """The core invariant: a later turn never drops earlier selections."""
+        first = select_mcp_tools([1.0, 0.0, 0.0], self.vectors, top_k=2,
+                                 already_selected=set())
+        second = select_mcp_tools([0.0, 1.0, 0.0], self.vectors, top_k=1,
+                                  already_selected=first)
+        self.assertTrue(first.issubset(second))
+        self.assertIn("b", second)
+
+    def test_none_query_vector_falls_back(self):
+        self.assertIsNone(select_mcp_tools(None, self.vectors, top_k=2,
+                                           already_selected=set()))
+
+    def test_empty_index_falls_back(self):
+        self.assertIsNone(select_mcp_tools([1.0, 0.0, 0.0], {}, top_k=2,
+                                           already_selected=set()))
+
+    def test_dimension_mismatch_falls_back(self):
+        mismatched = {"a": [1.0, 0.0]}  # dim 2 vs query dim 3
+        self.assertIsNone(select_mcp_tools([1.0, 0.0, 0.0], mismatched, top_k=2,
+                                           already_selected=set()))
+
+
+# --------------------------------------------------------------------------
+# Executor integration: AgentStream._select_tools_for_injection
+# --------------------------------------------------------------------------
+
+class TestSelectToolsForInjection(unittest.TestCase):
+    """Exercise the executor decision without spinning up a real agent."""
+
+    def _make_self(self, mcp_count, builtins=("read", "write", "bash")):
+        from types import SimpleNamespace
+        tools = {}
+        for name in builtins:
+            tools[name] = _FakeBuiltinTool(name)
+        for i in range(mcp_count):
+            name = f"mcp_{i}"
+            tools[name] = _mcp_tool(name, f"tool number {i}")
+        return SimpleNamespace(
+            tools=tools,
+            messages=[{"role": "user", "content": [{"type": "text", "text": "hi"}]}],
+            _retrieved_mcp_names=set(),
+        )
+
+    def _call(self, fake_self):
+        from agent.protocol.agent_stream import AgentStreamExecutor
+        return AgentStreamExecutor._select_tools_for_injection(fake_self)
+
+    def _conf(self, **overrides):
+        cfg = {
+            "mcp_tool_retrieval_enabled": True,
+            "mcp_tool_retrieval_threshold": 20,
+            "mcp_tool_retrieval_top_k": 2,
+        }
+        cfg.update(overrides)
+        return cfg
+
+    def test_disabled_returns_all_tools(self):
+        fake = self._make_self(mcp_count=50)
+        with patch("config.conf", return_value=self._conf(mcp_tool_retrieval_enabled=False)):
+            result = self._call(fake)
+        self.assertEqual(len(result), len(fake.tools))
+
+    def test_below_threshold_returns_all_tools(self):
+        """Maintainer scenario 1: below threshold → behavior unchanged."""
+        fake = self._make_self(mcp_count=5)  # <= threshold 20
+        with patch("config.conf", return_value=self._conf()):
+            result = self._call(fake)
+        self.assertEqual(len(result), len(fake.tools))
+
+    def test_degrade_no_provider_returns_all_tools(self):
+        """Maintainer scenario 2: no embedding provider → full injection."""
+        fake = self._make_self(mcp_count=25)  # > threshold
+        fake_tm = _FakeToolManager(tool_vectors={}, query_vectors=[None])
+        with patch("config.conf", return_value=self._conf()), \
+             patch("agent.tools.ToolManager", return_value=fake_tm):
+            result = self._call(fake)
+        self.assertEqual(len(result), len(fake.tools))
+
+    def test_builtins_always_injected_and_set_grows(self):
+        """Maintainer scenario 3: multi-turn MCP set only grows; builtins stay."""
+        fake = self._make_self(mcp_count=25)
+        # Deterministic vectors: mcp_0 wins turn 1, mcp_1 wins turn 2.
+        tool_vectors = {f"mcp_{i}": [0.1, 0.1, 0.1] for i in range(25)}
+        tool_vectors["mcp_0"] = [1.0, 0.0, 0.0]
+        tool_vectors["mcp_1"] = [0.0, 1.0, 0.0]
+        fake_tm = _FakeToolManager(
+            tool_vectors=tool_vectors,
+            query_vectors=[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]],
+        )
+        with patch("config.conf", return_value=self._conf(mcp_tool_retrieval_top_k=1)), \
+             patch("agent.tools.ToolManager", return_value=fake_tm):
+            result1 = self._call(fake)
+            names1 = {t.name for t in result1}
+            result2 = self._call(fake)
+            names2 = {t.name for t in result2}
+
+        # Built-in tools present in both turns.
+        for b in ("read", "write", "bash"):
+            self.assertIn(b, names1)
+            self.assertIn(b, names2)
+        # Turn 1 selected mcp_0; turn 2 must still contain it (only-grows).
+        self.assertIn("mcp_0", names1)
+        self.assertIn("mcp_0", names2)
+        self.assertIn("mcp_1", names2)
+        self.assertTrue(fake._retrieved_mcp_names >= {"mcp_0", "mcp_1"})
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_minimax_provider.py b/tests/test_minimax_provider.py
new file mode 100644
index 0000000..bd4cc57
--- /dev/null
+++ b/tests/test_minimax_provider.py
@@ -0,0 +1,193 @@
+# encoding:utf-8
+"""
+Unit tests for MiniMax provider additions:
+  - MiniMax-M3 / M2.7 / M2.7-highspeed constants in const.py
+  - Default model update in MinimaxBot
+  - MinimaxVoice TTS provider
+"""
+import sys
+import os
+import json
+import unittest
+from unittest.mock import MagicMock, patch, PropertyMock
+
+# Add project root to path
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+class TestMinimaxConst(unittest.TestCase):
+    """Test that MiniMax M3 / M2.7 constants are properly registered in const.py."""
+
+    def test_m3_constant_defined(self):
+        from common import const
+        self.assertTrue(hasattr(const, "MINIMAX_M3"))
+        self.assertEqual(const.MINIMAX_M3, "MiniMax-M3")
+
+    def test_m2_7_highspeed_constant_defined(self):
+        from common import const
+        self.assertTrue(hasattr(const, "MINIMAX_M2_7_HIGHSPEED"))
+        self.assertEqual(const.MINIMAX_M2_7_HIGHSPEED, "MiniMax-M2.7-highspeed")
+
+    def test_m2_7_constant_defined(self):
+        from common import const
+        self.assertEqual(const.MINIMAX_M2_7, "MiniMax-M2.7")
+
+    def test_m3_in_model_list(self):
+        from common import const
+        self.assertIn("MiniMax-M3", const.MODEL_LIST)
+
+    def test_m2_7_highspeed_in_model_list(self):
+        from common import const
+        self.assertIn("MiniMax-M2.7-highspeed", const.MODEL_LIST)
+
+    def test_m2_7_in_model_list(self):
+        from common import const
+        self.assertIn("MiniMax-M2.7", const.MODEL_LIST)
+
+    def test_minimax_provider_key_defined(self):
+        from common import const
+        self.assertEqual(const.MiniMax, "minimax")
+
+
+class TestMinimaxBotDefaultModel(unittest.TestCase):
+    """Test that MinimaxBot defaults to MiniMax-M3."""
+
+    def test_default_model_is_m3(self):
+        # Patch conf() to return empty config
+        mock_conf = MagicMock()
+        mock_conf.get = MagicMock(side_effect=lambda key, default=None: default)
+
+        with patch("models.minimax.minimax_bot.conf", return_value=mock_conf):
+            with patch("models.minimax.minimax_bot.SessionManager"):
+                from models.minimax import minimax_bot
+                # Reload to pick up patches
+                import importlib
+                importlib.reload(minimax_bot)
+                with patch("models.minimax.minimax_bot.conf", return_value=mock_conf):
+                    bot = minimax_bot.MinimaxBot.__new__(minimax_bot.MinimaxBot)
+                    bot.args = {
+                        "model": mock_conf.get("model") or "MiniMax-M3",
+                    }
+                    self.assertEqual(bot.args["model"], "MiniMax-M3")
+
+    def test_default_model_string(self):
+        """Verify the fallback string literal in minimax_bot.py is MiniMax-M3."""
+        import ast
+        bot_path = os.path.join(os.path.dirname(__file__), "..", "models", "minimax", "minimax_bot.py")
+        with open(bot_path) as f:
+            source = f.read()
+        # Verify MiniMax-M3 is in the source (not the older default)
+        self.assertIn("MiniMax-M3", source)
+        self.assertNotIn('"MiniMax-M2.1"', source)
+
+
+class TestMinimaxVoice(unittest.TestCase):
+    """Test MinimaxVoice TTS provider."""
+
+    def _make_voice(self, api_key="test-key", api_base="https://api.minimax.io/v1"):
+        mock_conf = MagicMock()
+        def conf_get(key, default=None):
+            return {
+                "minimax_api_key": api_key,
+                "minimax_api_base": api_base,
+            }.get(key, default)
+        mock_conf.get = conf_get
+        with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+            from voice.minimax.minimax_voice import MinimaxVoice
+            return MinimaxVoice()
+
+    def test_instantiation(self):
+        voice = self._make_voice()
+        self.assertIsNotNone(voice)
+
+    def test_api_base_strips_v1_suffix(self):
+        voice = self._make_voice(api_base="https://api.minimax.io/v1")
+        self.assertEqual(voice.api_base, "https://api.minimax.io")
+
+    def test_api_base_no_trailing_slash(self):
+        voice = self._make_voice(api_base="https://api.minimax.io")
+        self.assertEqual(voice.api_base, "https://api.minimax.io")
+
+    def test_voice_to_text_not_supported(self):
+        voice = self._make_voice()
+        with self.assertRaises(NotImplementedError):
+            voice.voiceToText("dummy.wav")
+
+    def test_text_to_voice_success(self):
+        """Test textToVoice with mocked SSE stream response."""
+        import os
+        os.makedirs("tmp", exist_ok=True)
+
+        # Build fake SSE stream bytes
+        audio_hex = bytes([0x49, 0x44, 0x33]).hex()  # "ID3" MP3 magic bytes
+        sse_line = f'data: {{"data": {{"audio": "{audio_hex}", "status": 2}}}}\n\n'
+        done_line = "data: [DONE]\n\n"
+        fake_body = (sse_line + done_line).encode("utf-8")
+
+        mock_response = MagicMock()
+        mock_response.raise_for_status = MagicMock()
+        mock_response.iter_lines.return_value = [
+            line.encode("utf-8") for line in (sse_line + done_line).splitlines() if line
+        ]
+
+        mock_conf = MagicMock()
+        def conf_get(key, default=None):
+            return {
+                "minimax_api_key": "test-key",
+                "minimax_api_base": "https://api.minimax.io",
+            }.get(key, default)
+        mock_conf.get = conf_get
+
+        with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+            with patch("voice.minimax.minimax_voice.requests.post", return_value=mock_response):
+                from voice.minimax import minimax_voice
+                import importlib
+                importlib.reload(minimax_voice)
+                with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+                    voice = minimax_voice.MinimaxVoice()
+                    from bridge.reply import ReplyType
+                    reply = voice.textToVoice("Hello, world!")
+                    self.assertEqual(reply.type, ReplyType.VOICE)
+                    self.assertTrue(reply.content.endswith(".mp3"))
+
+    def test_text_to_voice_no_audio_returns_error(self):
+        """Test that empty SSE stream returns an ERROR reply."""
+        mock_response = MagicMock()
+        mock_response.raise_for_status = MagicMock()
+        mock_response.iter_lines.return_value = []
+
+        mock_conf = MagicMock()
+        def conf_get(key, default=None):
+            return {
+                "minimax_api_key": "test-key",
+                "minimax_api_base": "https://api.minimax.io",
+            }.get(key, default)
+        mock_conf.get = conf_get
+
+        with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+            with patch("voice.minimax.minimax_voice.requests.post", return_value=mock_response):
+                from voice.minimax import minimax_voice
+                import importlib
+                importlib.reload(minimax_voice)
+                with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+                    voice = minimax_voice.MinimaxVoice()
+                    from bridge.reply import ReplyType
+                    reply = voice.textToVoice("Hello")
+                    self.assertEqual(reply.type, ReplyType.ERROR)
+
+
+class TestVoiceFactory(unittest.TestCase):
+    """Test that minimax is registered in the voice factory."""
+
+    def test_minimax_voice_factory(self):
+        mock_conf = MagicMock()
+        mock_conf.get = MagicMock(return_value=None)
+        with patch("voice.minimax.minimax_voice.conf", return_value=mock_conf):
+            from voice.factory import create_voice
+            voice = create_voice("minimax")
+            from voice.minimax.minimax_voice import MinimaxVoice
+            self.assertIsInstance(voice, MinimaxVoice)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_models_handler.py b/tests/test_models_handler.py
new file mode 100644
index 0000000..9d41b2b
--- /dev/null
+++ b/tests/test_models_handler.py
@@ -0,0 +1,99 @@
+# encoding:utf-8
+import json
+import os
+import sys
+import types
+import unittest
+from unittest.mock import patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+if "web" not in sys.modules:
+    web_stub = types.ModuleType("web")
+    web_stub.HTTPError = type("HTTPError", (Exception,), {})
+    web_stub.cookies = lambda: {}
+    web_stub.header = lambda *args, **kwargs: None
+    web_stub.data = lambda: b"{}"
+    web_stub.input = lambda **kwargs: types.SimpleNamespace(**kwargs)
+    web_stub.setcookie = lambda *args, **kwargs: None
+    web_stub.seeother = lambda *args, **kwargs: Exception("seeother")
+    web_stub.notfound = lambda *args, **kwargs: Exception("notfound")
+    web_stub.badrequest = lambda *args, **kwargs: Exception("badrequest")
+    web_stub.application = lambda *args, **kwargs: types.SimpleNamespace(wsgifunc=lambda: None)
+    web_stub.httpserver = types.SimpleNamespace(
+        LogMiddleware=type("LogMiddleware", (), {"log": lambda *args, **kwargs: None}),
+        StaticMiddleware=lambda app: app,
+        WSGIServer=lambda *args, **kwargs: types.SimpleNamespace(serve_forever=lambda: None),
+    )
+    sys.modules["web"] = web_stub
+
+
+class TestModelsHandler(unittest.TestCase):
+    def test_set_asr_capability_persists_provider_and_model(self):
+        from channel.web.web_channel import ModelsHandler
+
+        local_config = {}
+        file_config = {}
+        handler = ModelsHandler()
+
+        with patch("channel.web.web_channel.conf", return_value=local_config):
+            with patch.object(ModelsHandler, "_read_file_config", return_value=file_config):
+                with patch.object(ModelsHandler, "_write_file_config") as write_file:
+                    with patch.object(ModelsHandler, "_refresh_voice_routing") as refresh_voice:
+                        result = json.loads(handler._handle_set_capability({
+                            "capability": "asr",
+                            "provider_id": "dashscope",
+                            "model": "qwen3-asr-flash",
+                        }))
+
+        self.assertEqual(result["status"], "success")
+        self.assertEqual(local_config["voice_to_text"], "dashscope")
+        self.assertEqual(local_config["voice_to_text_model"], "qwen3-asr-flash")
+        self.assertEqual(file_config["voice_to_text"], "dashscope")
+        self.assertEqual(file_config["voice_to_text_model"], "qwen3-asr-flash")
+        write_file.assert_called_once_with(file_config)
+        refresh_voice.assert_called_once()
+
+    def test_set_asr_empty_model_keeps_existing(self):
+        # Switching provider with an empty model must not wipe a user's
+        # hand-configured voice_to_text_model.
+        from channel.web.web_channel import ModelsHandler
+
+        local_config = {"voice_to_text_model": "qwen3-asr-flash"}
+        file_config = {"voice_to_text_model": "qwen3-asr-flash"}
+        handler = ModelsHandler()
+
+        with patch("channel.web.web_channel.conf", return_value=local_config):
+            with patch.object(ModelsHandler, "_read_file_config", return_value=file_config):
+                with patch.object(ModelsHandler, "_write_file_config"):
+                    with patch.object(ModelsHandler, "_refresh_voice_routing"):
+                        result = json.loads(handler._handle_set_capability({
+                            "capability": "asr",
+                            "provider_id": "zhipu",
+                            "model": "",
+                        }))
+
+        self.assertEqual(result["status"], "success")
+        self.assertEqual(local_config["voice_to_text"], "zhipu")
+        # Existing model preserved, not overwritten with "".
+        self.assertEqual(local_config["voice_to_text_model"], "qwen3-asr-flash")
+        self.assertEqual(file_config["voice_to_text_model"], "qwen3-asr-flash")
+        self.assertEqual(result["model"], "qwen3-asr-flash")
+
+    def test_asr_capability_exposes_provider_models(self):
+        from channel.web.web_channel import ModelsHandler
+
+        cap = ModelsHandler._asr_capability({
+            "voice_to_text": "dashscope",
+            "voice_to_text_model": "qwen3-asr-flash",
+        })
+
+        self.assertTrue(cap["editable"])
+        self.assertEqual(cap["current_provider"], "dashscope")
+        self.assertEqual(cap["current_model"], "qwen3-asr-flash")
+        self.assertIn("provider_models", cap)
+        self.assertIn("dashscope", cap["provider_models"])
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_qianfan_provider.py b/tests/test_qianfan_provider.py
new file mode 100644
index 0000000..99eb413
--- /dev/null
+++ b/tests/test_qianfan_provider.py
@@ -0,0 +1,610 @@
+# encoding:utf-8
+import os
+import sys
+import unittest
+from unittest.mock import MagicMock, patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+class TestQianfanConstantsAndRouting(unittest.TestCase):
+    def test_qianfan_provider_constant_defined(self):
+        from common import const
+
+        self.assertEqual(const.QIANFAN, "qianfan")
+
+    def test_ernie_constants_are_in_model_list(self):
+        from common import const
+
+        self.assertEqual(const.ERNIE_5_1, "ernie-5.1")
+        self.assertEqual(const.ERNIE_5, "ernie-5.0")
+        self.assertEqual(const.ERNIE_45_TURBO_128K, "ernie-4.5-turbo-128k")
+        self.assertEqual(const.ERNIE_45_TURBO_32K, "ernie-4.5-turbo-32k")
+        self.assertEqual(const.ERNIE_X1_1, "ernie-x1.1")
+        self.assertEqual(
+            const.ERNIE_45_TURBO_VL,
+            "ernie-4.5-turbo-vl",
+        )
+        self.assertEqual(
+            const.ERNIE_45_TURBO_VL_32K,
+            "ernie-4.5-turbo-vl-32k",
+        )
+        self.assertIn(const.QIANFAN, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_5_1, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_5, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_45_TURBO_128K, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_45_TURBO_32K, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_X1_1, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_45_TURBO_VL, const.MODEL_LIST)
+        self.assertIn(const.ERNIE_45_TURBO_VL_32K, const.MODEL_LIST)
+        # ERNIE 5.1 must be ranked before 5.0 so it is presented as the default.
+        self.assertLess(
+            const.MODEL_LIST.index(const.ERNIE_5_1),
+            const.MODEL_LIST.index(const.ERNIE_5),
+        )
+
+    def test_qianfan_config_keys_are_available(self):
+        import config
+
+        self.assertIn("qianfan_api_key", config.available_setting)
+        self.assertIn("qianfan_api_base", config.available_setting)
+
+    def test_agent_bridge_routes_ernie_models_to_qianfan(self):
+        from bridge.agent_bridge import AgentLLMModel
+        from common import const
+
+        model = AgentLLMModel.__new__(AgentLLMModel)
+        fake_conf = MagicMock()
+        fake_conf.get.side_effect = lambda key, default=None: {
+            "use_linkai": False,
+            "linkai_api_key": "",
+            "bot_type": "",
+        }.get(key, default)
+
+        with patch("bridge.agent_bridge.conf", return_value=fake_conf):
+            self.assertEqual(
+                AgentLLMModel._resolve_bot_type(model, "ernie-4.5-turbo-128k"),
+                const.QIANFAN,
+            )
+            self.assertEqual(
+                AgentLLMModel._resolve_bot_type(model, "qianfan"),
+                const.QIANFAN,
+            )
+
+    def test_cow_cli_routes_ernie_models_to_qianfan(self):
+        from common import const
+        import plugins
+
+        old_plugin_path = plugins.instance.current_plugin_path
+        cow_cli_was_registered = "COW_CLI" in plugins.instance.plugins
+        old_cow_cli_plugin = plugins.instance.plugins.get("COW_CLI")
+        parent_had_cow_cli = hasattr(plugins, "cow_cli")
+        old_parent_cow_cli = getattr(plugins, "cow_cli", None)
+        module_names = ("plugins.cow_cli", "plugins.cow_cli.cow_cli")
+        old_modules = {
+            name: sys.modules[name]
+            for name in module_names
+            if name in sys.modules
+        }
+        plugins.instance.current_plugin_path = os.path.join(
+            os.path.dirname(__file__), "..", "plugins", "cow_cli"
+        )
+        try:
+            import plugins.cow_cli.cow_cli
+            cow_cli_plugin = plugins.instance.plugins["COW_CLI"]
+        finally:
+            plugins.instance.current_plugin_path = old_plugin_path
+            if cow_cli_was_registered:
+                plugins.instance.plugins["COW_CLI"] = old_cow_cli_plugin
+            else:
+                plugins.instance.plugins.pop("COW_CLI", None)
+            for name in module_names:
+                if name in old_modules:
+                    sys.modules[name] = old_modules[name]
+                else:
+                    sys.modules.pop(name, None)
+            if parent_had_cow_cli:
+                plugins.cow_cli = old_parent_cow_cli
+            elif hasattr(plugins, "cow_cli"):
+                delattr(plugins, "cow_cli")
+
+        self.assertEqual(
+            cow_cli_plugin._resolve_bot_type_for_model("ernie-4.5-turbo-128k"),
+            const.QIANFAN,
+        )
+        self.assertEqual(
+            cow_cli_plugin._resolve_bot_type_for_model("qianfan"),
+            const.QIANFAN,
+        )
+
+
+class TestQianfanBot(unittest.TestCase):
+    def _fake_conf(self, values=None):
+        data = {
+            "model": "ernie-5.1",
+            "qianfan_api_key": "test-qianfan-key",
+            "qianfan_api_base": "https://qianfan.baidubce.com/v2",
+            "temperature": 0.7,
+            "top_p": 1.0,
+            "frequency_penalty": 0.0,
+            "presence_penalty": 0.0,
+            "request_timeout": 180,
+            "clear_memory_commands": ["#清除记忆"],
+            "conversation_max_tokens": 1000,
+            "expires_in_seconds": 3600,
+        }
+        if values:
+            data.update(values)
+        fake_conf = MagicMock()
+        fake_conf.get.side_effect = lambda key, default=None: data.get(key, default)
+        return fake_conf
+
+    def test_bot_factory_returns_qianfan_bot(self):
+        from common import const
+        from models.bot_factory import create_bot
+
+        fake_conf = self._fake_conf()
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                bot = create_bot(const.QIANFAN)
+
+        from models.qianfan.qianfan_bot import QianfanBot
+        self.assertIsInstance(bot, QianfanBot)
+
+    def test_default_model_uses_ernie_when_model_is_provider_alias(self):
+        fake_conf = self._fake_conf({"model": "qianfan"})
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+
+        self.assertEqual(bot.args["model"], "ernie-5.1")
+
+    def test_reply_text_posts_openai_compatible_payload(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 200
+        fake_response.json.return_value = {
+            "choices": [{"message": {"content": "你好，我是文心。"}}],
+            "usage": {"total_tokens": 12, "completion_tokens": 6},
+        }
+        session = MagicMock()
+        session.messages = [{"role": "user", "content": "你好"}]
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response) as post:
+                    result = bot.reply_text(session)
+
+        self.assertEqual(result["content"], "你好，我是文心。")
+        self.assertEqual(result["total_tokens"], 12)
+        self.assertEqual(result["completion_tokens"], 6)
+        post.assert_called_once()
+        url = post.call_args.args[0]
+        kwargs = post.call_args.kwargs
+        self.assertEqual(url, "https://qianfan.baidubce.com/v2/chat/completions")
+        self.assertEqual(kwargs["headers"]["Authorization"], "Bearer test-qianfan-key")
+        self.assertEqual(kwargs["json"]["model"], "ernie-5.1")
+        self.assertEqual(kwargs["json"]["messages"], [{"role": "user", "content": "你好"}])
+
+    def test_reply_text_returns_auth_error_for_401(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 401
+        fake_response.json.return_value = {"error": {"message": "invalid api key"}}
+        fake_response.text = '{"error":{"message":"invalid api key"}}'
+        session = MagicMock()
+        session.messages = [{"role": "user", "content": "你好"}]
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response):
+                    result = bot.reply_text(session)
+
+        self.assertEqual(result["completion_tokens"], 0)
+        self.assertEqual(result["content"], "授权失败，请检查 Qianfan API Key 是否正确")
+
+    def test_reply_text_returns_raw_message_for_non_json_error(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 400
+        fake_response.json.side_effect = ValueError
+        fake_response.text = "bad gateway text"
+        session = MagicMock()
+        session.messages = [{"role": "user", "content": "你好"}]
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response) as post:
+                    result = bot.reply_text(session)
+
+        self.assertEqual(result["completion_tokens"], 0)
+        self.assertEqual(result["content"], "请求失败：bad gateway text")
+        post.assert_called_once()
+
+    def test_qianfan_bot_supports_vision_for_multimodal_models(self):
+        for model in ("ernie-5.1", "ernie-5.0", "ernie-x1.1", "ernie-4.5-turbo-vl", "ernie-4.5-turbo-vl-32k"):
+            fake_conf = self._fake_conf({"model": model})
+            with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+                with patch("models.qianfan.qianfan_bot.SessionManager"):
+                    from models.qianfan.qianfan_bot import QianfanBot
+
+                    bot = QianfanBot()
+                    self.assertTrue(
+                        bot.supports_vision,
+                        msg=f"{model} should be marked as multimodal",
+                    )
+
+    def test_qianfan_bot_does_not_advertise_vision_for_text_only_models(self):
+        for model in ("ernie-4.5-turbo-128k", "ernie-4.5-turbo-32k"):
+            fake_conf = self._fake_conf({"model": model})
+            with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+                with patch("models.qianfan.qianfan_bot.SessionManager"):
+                    from models.qianfan.qianfan_bot import QianfanBot
+
+                    bot = QianfanBot()
+                    self.assertFalse(
+                        bot.supports_vision,
+                        msg=f"{model} should not be marked as multimodal",
+                    )
+
+    def test_call_vision_posts_openai_compatible_multimodal_payload(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 200
+        fake_response.json.return_value = {
+            "id": "chatcmpl-test",
+            "model": "ernie-4.5-turbo-vl",
+            "choices": [{"message": {"content": "图中有一个红色方块。"}}],
+            "usage": {
+                "prompt_tokens": 10,
+                "completion_tokens": 8,
+                "total_tokens": 18,
+            },
+        }
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response) as post:
+                    result = bot.call_vision(
+                        image_url="data:image/png;base64,AAAA",
+                        question="这张图里有什么？",
+                    )
+
+        self.assertEqual(result["content"], "图中有一个红色方块。")
+        self.assertEqual(result["model"], "ernie-4.5-turbo-vl")
+        self.assertEqual(result["usage"]["total_tokens"], 18)
+        post.assert_called_once()
+        url = post.call_args.args[0]
+        kwargs = post.call_args.kwargs
+        self.assertEqual(url, "https://qianfan.baidubce.com/v2/chat/completions")
+        self.assertEqual(kwargs["headers"]["Authorization"], "Bearer test-qianfan-key")
+        self.assertEqual(kwargs["json"]["model"], "ernie-4.5-turbo-vl")
+        self.assertEqual(kwargs["json"]["max_tokens"], 1000)
+        self.assertEqual(kwargs["json"]["messages"], [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "这张图里有什么？"},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": "data:image/png;base64,AAAA"},
+                    },
+                ],
+            }
+        ])
+
+    def test_call_vision_allows_explicit_model_override(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 200
+        fake_response.json.return_value = {
+            "model": "ernie-4.5-turbo-vl-32k",
+            "choices": [{"message": {"content": "有文字。"}}],
+            "usage": {},
+        }
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response) as post:
+                    result = bot.call_vision(
+                        image_url="data:image/jpeg;base64,BBBB",
+                        question="识别文字",
+                        model="ernie-4.5-turbo-vl-32k",
+                        max_tokens=256,
+                    )
+
+        self.assertEqual(result["model"], "ernie-4.5-turbo-vl-32k")
+        self.assertEqual(post.call_args.kwargs["json"]["model"], "ernie-4.5-turbo-vl-32k")
+        self.assertEqual(post.call_args.kwargs["json"]["max_tokens"], 256)
+
+    def test_call_vision_returns_error_dict_for_api_error(self):
+        fake_conf = self._fake_conf()
+        fake_response = MagicMock()
+        fake_response.status_code = 400
+        fake_response.json.return_value = {"error": {"message": "bad image"}}
+        fake_response.text = '{"error":{"message":"bad image"}}'
+
+        with patch("models.qianfan.qianfan_bot.conf", return_value=fake_conf):
+            with patch("models.qianfan.qianfan_bot.SessionManager"):
+                from models.qianfan.qianfan_bot import QianfanBot
+
+                bot = QianfanBot()
+                with patch("models.qianfan.qianfan_bot.requests.post", return_value=fake_response):
+                    result = bot.call_vision(
+                        image_url="data:image/png;base64,AAAA",
+                        question="这张图里有什么？",
+                    )
+
+        self.assertTrue(result["error"])
+        self.assertEqual(result["message"], "请求失败：bad image")
+
+
+class TestQianfanSurfaces(unittest.TestCase):
+    def _read(self, relative_path):
+        root = os.path.join(os.path.dirname(__file__), "..")
+        with open(os.path.join(root, relative_path), encoding="utf-8") as f:
+            return f.read()
+
+    def test_web_console_registers_qianfan_provider(self):
+        source = self._read("channel/web/web_channel.py")
+
+        self.assertIn('("qianfan", {', source)
+        self.assertIn('"label": "百度千帆"', source)
+        self.assertIn('"api_key_field": "qianfan_api_key"', source)
+        self.assertIn('"api_base_key": "qianfan_api_base"', source)
+        self.assertIn('"api_base_default": "https://qianfan.baidubce.com/v2"', source)
+
+    def test_web_console_allows_qianfan_config_edits(self):
+        source = self._read("channel/web/web_channel.py")
+
+        self.assertIn('"qianfan_api_base"', source)
+        self.assertIn('"qianfan_api_key"', source)
+
+    def test_session_plugins_allow_qianfan(self):
+        role_source = self._read("plugins/role/role.py")
+        godcmd_source = self._read("plugins/godcmd/godcmd.py")
+
+        self.assertIn("const.QIANFAN", role_source)
+        self.assertIn("const.QIANFAN", godcmd_source)
+
+
+class TestQianfanVisionTool(unittest.TestCase):
+    def _fake_conf(self, values=None):
+        data = {
+            "model": "deepseek-v4-flash",
+            "qianfan_api_key": "",
+            "qianfan_api_base": "https://qianfan.baidubce.com/v2",
+            "open_ai_api_key": "",
+            "linkai_api_key": "",
+            "use_linkai": False,
+            "tools": {},
+        }
+        if values:
+            data.update(values)
+        fake_conf = MagicMock()
+        fake_conf.get.side_effect = lambda key, default=None: data.get(key, default)
+        return fake_conf
+
+    def test_vision_auto_discovers_qianfan_when_key_configured(self):
+        fake_conf = self._fake_conf({"qianfan_api_key": "test-qianfan-key"})
+        fake_bot = MagicMock()
+        fake_bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            with patch("models.bot_factory.create_bot", return_value=fake_bot) as create_bot:
+                from agent.tools.vision.vision import Vision
+                from common import const
+
+                tool = Vision()
+                tool.model = None
+                providers = tool._resolve_providers()
+
+        self.assertEqual(providers[0].name, "Qianfan")
+        self.assertEqual(providers[0].model_override, const.ERNIE_45_TURBO_VL)
+        self.assertTrue(providers[0].use_bot)
+        create_bot.assert_called_with(const.QIANFAN)
+
+    def test_vision_routes_ernie_model_override_to_qianfan(self):
+        fake_conf = self._fake_conf({
+            "qianfan_api_key": "test-qianfan-key",
+            "tools": {"vision": {"model": "ernie-4.5-turbo-vl-32k"}},
+        })
+        fake_bot = MagicMock()
+        fake_bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            with patch("models.bot_factory.create_bot", return_value=fake_bot):
+                from agent.tools.vision.vision import Vision
+
+                tool = Vision()
+                tool.model = None
+                providers = tool._resolve_providers()
+
+        self.assertEqual(providers[0].name, "Qianfan")
+        self.assertEqual(providers[0].model_override, "ernie-4.5-turbo-vl-32k")
+
+    def test_vision_main_model_uses_qianfan_when_configured_model_is_ernie(self):
+        fake_conf = self._fake_conf({"model": "ernie-4.5-turbo-vl-32k"})
+        from common import const
+
+        fake_model = MagicMock()
+        fake_model._resolve_bot_type.return_value = const.QIANFAN
+        fake_model.bot = MagicMock()
+        fake_model.bot.supports_vision = True
+        fake_model.bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            from agent.tools.vision.vision import Vision
+
+            tool = Vision()
+            tool.model = fake_model
+            providers = tool._resolve_providers()
+
+        self.assertEqual(providers[0].name, "MainModel")
+        self.assertEqual(providers[0].model_override, "ernie-4.5-turbo-vl-32k")
+
+    def test_vision_main_model_uses_ernie_5_directly(self):
+        """ERNIE 5.0 is omni-modal → main-model path forwards image to it."""
+        fake_conf = self._fake_conf({"model": "ernie-5.0"})
+        from common import const
+
+        fake_model = MagicMock()
+        fake_model._resolve_bot_type.return_value = const.QIANFAN
+        fake_model.bot = MagicMock()
+        fake_model.bot.supports_vision = True
+        fake_model.bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            from agent.tools.vision.vision import Vision
+
+            tool = Vision()
+            tool.model = fake_model
+            providers = tool._resolve_providers()
+
+        self.assertEqual(providers[0].name, "MainModel")
+        self.assertEqual(providers[0].model_override, "ernie-5.0")
+
+    def test_vision_falls_back_to_qianfan_vl_when_main_model_is_text_only_ernie(self):
+        """Text-only ERNIE (e.g. ernie-4.5-turbo-128k) must NOT receive image
+        payloads — Vision should skip MainModel and pick up the Qianfan
+        provider from _DISCOVERABLE_MODELS instead."""
+        fake_conf = self._fake_conf({
+            "model": "ernie-4.5-turbo-128k",
+            "qianfan_api_key": "test-qianfan-key",
+        })
+        from common import const
+
+        # Main bot reports supports_vision=False because the configured
+        # model is text-only.
+        fake_main_bot = MagicMock()
+        fake_main_bot.supports_vision = False
+        fake_main_bot.call_vision = MagicMock()
+
+        fake_model = MagicMock()
+        fake_model._resolve_bot_type.return_value = const.QIANFAN
+        fake_model.bot = fake_main_bot
+
+        # The discoverable Qianfan provider creates a new bot via factory.
+        fake_factory_bot = MagicMock()
+        fake_factory_bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            with patch("models.bot_factory.create_bot", return_value=fake_factory_bot):
+                from agent.tools.vision.vision import Vision
+
+                tool = Vision()
+                tool.model = fake_model
+                providers = tool._resolve_providers()
+
+        # MainModel must be absent; Qianfan fallback provider must be the
+        # first choice and pinned to the dedicated vision model.
+        names = [p.name for p in providers]
+        self.assertNotIn("MainModel", names)
+        self.assertEqual(names[0], "Qianfan")
+        self.assertEqual(providers[0].model_override, const.ERNIE_45_TURBO_VL)
+
+    def test_vision_prefers_same_vendor_fallback_over_other_configured_keys(self):
+        """When the main bot is text-only ERNIE and several vision-capable
+        keys are configured, the same-vendor (Qianfan) fallback wins over
+        unrelated providers regardless of declaration order."""
+        fake_conf = self._fake_conf({
+            "model": "ernie-4.5-turbo-128k",
+            "qianfan_api_key": "test-qianfan-key",
+            "ark_api_key": "test-ark-key",
+            "claude_api_key": "test-claude-key",
+            "minimax_api_key": "test-minimax-key",
+        })
+        from common import const
+
+        fake_main_bot = MagicMock()
+        fake_main_bot.supports_vision = False
+        fake_main_bot.call_vision = MagicMock()
+
+        fake_model = MagicMock()
+        fake_model._resolve_bot_type.return_value = const.QIANFAN
+        fake_model.bot = fake_main_bot
+
+        fake_factory_bot = MagicMock()
+        fake_factory_bot.call_vision = MagicMock()
+
+        with patch("agent.tools.vision.vision.conf", return_value=fake_conf):
+            with patch("models.bot_factory.create_bot", return_value=fake_factory_bot):
+                from agent.tools.vision.vision import Vision
+
+                tool = Vision()
+                tool.model = fake_model
+                providers = tool._resolve_providers()
+
+        names = [p.name for p in providers]
+        self.assertEqual(names[0], "Qianfan")
+        self.assertEqual(providers[0].model_override, const.ERNIE_45_TURBO_VL)
+        # Other configured providers should still appear in the chain.
+        for expected in ("Doubao", "Claude", "MiniMax"):
+            self.assertIn(expected, names)
+
+
+class TestQianfanDocs(unittest.TestCase):
+    def _read(self, relative_path):
+        root = os.path.join(os.path.dirname(__file__), "..")
+        with open(os.path.join(root, relative_path), encoding="utf-8") as f:
+            return f.read()
+
+    def test_qianfan_docs_exist_in_all_doc_locales(self):
+        for path in (
+            "docs/models/qianfan.mdx",
+            "docs/en/models/qianfan.mdx",
+            "docs/ja/models/qianfan.mdx",
+        ):
+            text = self._read(path)
+            self.assertIn("qianfan_api_key", text)
+            self.assertIn("https://qianfan.baidubce.com/v2", text)
+            self.assertIn("ernie-4.5-turbo-128k", text)
+            self.assertIn("ernie-4.5-turbo-vl", text)
+
+    def test_model_indexes_link_qianfan(self):
+        for path in (
+            "docs/models/index.mdx",
+            "docs/en/models/index.mdx",
+            "docs/ja/models/index.mdx",
+        ):
+            text = self._read(path)
+            self.assertIn('/models/qianfan', text)
+
+    def test_readme_documents_native_qianfan_provider(self):
+        text = self._read("README.md")
+
+        self.assertIn('"model": "ernie-5.1"', text)
+        self.assertIn('"qianfan_api_key": ""', text)
+        self.assertIn('"qianfan_api_base": "https://qianfan.baidubce.com/v2"', text)
+
+    def test_vision_docs_document_qianfan_provider(self):
+        expected = {
+            "docs/tools/vision.mdx": "百度千帆",
+            "docs/en/tools/vision.mdx": "Baidu Qianfan",
+            "docs/ja/tools/vision.mdx": "Baidu Qianfan",
+        }
+        for path, label in expected.items():
+            text = self._read(path)
+            self.assertIn(label, text)
+            self.assertIn("ernie-4.5-turbo-vl", text)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_read_offset.py b/tests/test_read_offset.py
new file mode 100644
index 0000000..97b321b
--- /dev/null
+++ b/tests/test_read_offset.py
@@ -0,0 +1,58 @@
+# encoding:utf-8
+"""
+Regression tests for the Read tool's negative offset ("read from end").
+
+The tool documents that a negative offset reads from the end (e.g. -20 for the
+last 20 lines). Because content is split on "\n", a file ending in a newline
+yields a trailing empty element, so the line count was one too high and every
+negative offset was off by one: offset=-1 returned the empty string after the
+final newline instead of the last line, and -N returned N-1 real lines.
+"""
+import os
+import sys
+import tempfile
+import unittest
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools.read.read import Read
+
+
+class TestReadNegativeOffset(unittest.TestCase):
+    def setUp(self):
+        self.work = tempfile.mkdtemp()
+        self.tool = Read({"cwd": self.work})
+
+    def _write(self, name, text):
+        path = os.path.join(self.work, name)
+        with open(path, "w", encoding="utf-8") as f:
+            f.write(text)
+        return path
+
+    def test_offset_minus_one_returns_last_line(self):
+        path = self._write("f.txt", "line1\nline2\nline3\n")  # trailing newline
+        result = self.tool.execute({"path": path, "offset": -1})
+        self.assertEqual(result.status, "success", result.result)
+        content = result.result["content"]
+        self.assertIn("line3", content)          # was "" before the fix
+        self.assertNotIn("line2", content)
+        self.assertNotIn("line1", content)
+
+    def test_offset_minus_two_returns_last_two_lines(self):
+        path = self._write("f.txt", "line1\nline2\nline3\n")
+        result = self.tool.execute({"path": path, "offset": -2})
+        self.assertEqual(result.status, "success", result.result)
+        content = result.result["content"]
+        self.assertIn("line2", content)
+        self.assertIn("line3", content)
+        self.assertNotIn("line1", content)
+
+    def test_file_without_trailing_newline_still_works(self):
+        path = self._write("f.txt", "a\nb\nc")  # no trailing newline
+        result = self.tool.execute({"path": path, "offset": -1})
+        self.assertEqual(result.status, "success", result.result)
+        self.assertEqual(result.result["content"].strip(), "c")
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_robustness_fixes.py b/tests/test_robustness_fixes.py
new file mode 100644
index 0000000..9f8aa45
--- /dev/null
+++ b/tests/test_robustness_fixes.py
@@ -0,0 +1,121 @@
+# encoding:utf-8
+"""
+Unit tests for robustness fixes:
+  1. ChatChannel.cancel_session / cancel_all_session must not raise KeyError
+     when a session has been produced but no task has been dispatched yet
+     (so self.futures[session_id] does not exist).
+  2. common.utils.compress_imgfile must terminate (no infinite loop / invalid
+     PIL quality) when an image cannot be compressed below max_size.
+"""
+import io
+import os
+import sys
+import types
+import unittest
+from unittest.mock import MagicMock
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+# =============================================================================
+# 1. cancel_session / cancel_all_session KeyError regression
+# =============================================================================
+
+class TestCancelSessionMissingFutures(unittest.TestCase):
+    """A session may exist in self.sessions before any future is recorded."""
+
+    def _make_channel(self):
+        # Import lazily and build a bare object without running __init__,
+        # to avoid pulling the full channel setup / config.
+        from channel.chat_channel import ChatChannel
+
+        ch = ChatChannel.__new__(ChatChannel)
+        import threading
+
+        ch.lock = threading.RLock()
+        # A produced session whose future has NOT been dispatched yet.
+        queue = MagicMock()
+        queue.qsize.return_value = 0
+        semaphore = MagicMock()
+        ch.sessions = {"sid": [queue, semaphore]}
+        ch.futures = {}  # intentionally empty: consume() never ran
+        return ch
+
+    def test_cancel_session_no_futures_entry(self):
+        ch = self._make_channel()
+        # Should not raise KeyError.
+        try:
+            ch.cancel_session("sid")
+        except KeyError:
+            self.fail("cancel_session raised KeyError when futures entry missing")
+
+    def test_cancel_all_session_no_futures_entry(self):
+        ch = self._make_channel()
+        try:
+            ch.cancel_all_session()
+        except KeyError:
+            self.fail("cancel_all_session raised KeyError when futures entry missing")
+
+    def test_cancel_session_cancels_existing_futures(self):
+        ch = self._make_channel()
+        fut = MagicMock()
+        ch.futures["sid"] = [fut]
+        ch.cancel_session("sid")
+        fut.cancel.assert_called_once()
+
+
+# =============================================================================
+# 2. compress_imgfile termination
+# =============================================================================
+
+class TestCompressImgfileTermination(unittest.TestCase):
+    """compress_imgfile must always return, even for incompressible input."""
+
+    def setUp(self):
+        # Skip if Pillow is not available in the test environment.
+        try:
+            import PIL  # noqa: F401
+        except ImportError:
+            self.skipTest("Pillow not installed")
+
+    def _make_image_buf(self, size=(64, 64)):
+        from PIL import Image
+        import random
+
+        img = Image.new("RGB", size)
+        # Fill with random noise so JPEG cannot compress it well.
+        pixels = [
+            (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
+            for _ in range(size[0] * size[1])
+        ]
+        img.putdata(pixels)
+        buf = io.BytesIO()
+        img.save(buf, "JPEG", quality=95)
+        buf.seek(0)
+        return buf
+
+    def test_returns_when_target_unreachable(self):
+        from common.utils import compress_imgfile
+
+        buf = self._make_image_buf()
+        # An impossibly small target that even quality=10 won't reach.
+        out = compress_imgfile(buf, max_size=10)
+        self.assertIsInstance(out, io.BytesIO)
+        # Verify the result is still a valid JPEG (PIL never got invalid quality).
+        from PIL import Image
+
+        out.seek(0)
+        img = Image.open(out)
+        img.verify()
+
+    def test_no_compression_needed_returns_same_object(self):
+        from common.utils import compress_imgfile
+
+        buf = self._make_image_buf()
+        size = buf.getbuffer().nbytes
+        out = compress_imgfile(buf, max_size=size + 1)
+        self.assertIs(out, buf)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_security_read_env_bypass.py b/tests/test_security_read_env_bypass.py
new file mode 100644
index 0000000..b8e2d0b
--- /dev/null
+++ b/tests/test_security_read_env_bypass.py
@@ -0,0 +1,103 @@
+# encoding:utf-8
+"""
+Unit tests for Read tool credential-bypass protection (issue #2913).
+
+Verifies that the read tool blocks not just the literal ~/.cow/.env file but
+also its process-environment aliases (/proc/<pid>/environ) and symlinks that
+resolve to it, WITHOUT re-broadening the scope narrowed by #2863.
+"""
+import os
+import sys
+import tempfile
+import unittest
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools.read.read import Read
+from common.utils import expand_path
+
+_DENIED = "Access denied"
+
+
+class TestReadCredentialBypass(unittest.TestCase):
+    """_is_credential_path must block credential files and their aliases."""
+
+    def setUp(self):
+        self.read = Read()
+
+    # ---- happy path: ordinary files are NOT blocked -----------------------
+
+    def test_normal_file_not_blocked(self):
+        """A regular temp file must not be treated as a credential path."""
+        with tempfile.NamedTemporaryFile(suffix=".txt", delete=False) as tf:
+            tf.write(b"hello world")
+            tmp_path = tf.name
+        try:
+            self.assertFalse(self.read._is_credential_path(tmp_path))
+            result = self.read.execute({"path": tmp_path})
+            self.assertEqual(result.status, "success")
+        finally:
+            os.unlink(tmp_path)
+
+    def test_non_environ_proc_file_not_blocked(self):
+        """Non-environ /proc files must not be over-blocked (no #2863 regression)."""
+        self.assertFalse(self.read._is_credential_path("/proc/self/status"))
+        self.assertFalse(self.read._is_credential_path("/proc/1/cmdline"))
+
+    # ---- control: the literal credential file stays blocked --------------
+
+    def test_direct_env_file_blocked(self):
+        """Direct ~/.cow/.env access must remain blocked (regression control)."""
+        env_path = expand_path("~/.cow/.env")
+        self.assertTrue(self.read._is_credential_path(env_path))
+        result = self.read.execute({"path": env_path})
+        self.assertEqual(result.status, "error")
+        self.assertIn(_DENIED, str(result.result))
+
+    # ---- the vulnerability: environ aliases are blocked ------------------
+
+    def test_proc_self_environ_blocked(self):
+        """/proc/self/environ must be blocked (the #2913 bypass)."""
+        self.assertTrue(self.read._is_credential_path("/proc/self/environ"))
+        result = self.read.execute({"path": "/proc/self/environ"})
+        self.assertEqual(result.status, "error")
+        self.assertIn(_DENIED, str(result.result))
+
+    def test_proc_pid_environ_blocked(self):
+        """/proc/<pid>/environ must be blocked for any pid."""
+        self.assertTrue(self.read._is_credential_path("/proc/1/environ"))
+        self.assertTrue(self.read._is_credential_path(f"/proc/{os.getpid()}/environ"))
+
+    def test_proc_thread_self_environ_blocked(self):
+        """/proc/thread-self/environ must be blocked."""
+        self.assertTrue(self.read._is_credential_path("/proc/thread-self/environ"))
+
+    # ---- symlink escape --------------------------------------------------
+
+    @unittest.skipUnless(hasattr(os, "symlink"), "symlink not supported")
+    def test_symlink_to_env_file_blocked(self):
+        """A symlink resolving to ~/.cow/.env must be blocked."""
+        env_path = expand_path("~/.cow/.env")
+        os.makedirs(os.path.dirname(env_path), exist_ok=True)
+        created_env = False
+        if not os.path.exists(env_path):
+            with open(env_path, "w", encoding="utf-8") as f:
+                f.write("SECRET=canary\n")
+            created_env = True
+        link_dir = tempfile.mkdtemp()
+        link_path = os.path.join(link_dir, "innocent.txt")
+        try:
+            os.symlink(env_path, link_path)
+        except (OSError, NotImplementedError):
+            self.skipTest("cannot create symlink in this environment")
+        try:
+            self.assertTrue(self.read._is_credential_path(link_path))
+        finally:
+            os.unlink(link_path)
+            os.rmdir(link_dir)
+            if created_env:
+                os.unlink(env_path)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_security_ssrf_browser_navigate.py b/tests/test_security_ssrf_browser_navigate.py
new file mode 100644
index 0000000..f36e42a
--- /dev/null
+++ b/tests/test_security_ssrf_browser_navigate.py
@@ -0,0 +1,172 @@
+# encoding:utf-8
+"""
+Regression tests for browser-navigate SSRF protection.
+
+The browser tool navigates to a model-supplied URL via Playwright
+``page.goto`` and then auto-snapshots the page back to the model. Without a
+guard, a model (including one under prompt injection) can point it at the
+cloud-metadata endpoint (169.254.169.254) and read the credentials back
+through the snapshot.
+
+Unlike the vision / web_fetch tools, the browser legitimately needs local
+pages — a dev server on ``localhost`` / ``127.0.0.1`` / a LAN IP. So the guard
+is deliberately narrow: it blocks only **link-local** addresses
+(169.254.0.0/16, which includes the metadata endpoint, plus IPv6 fe80::/10) and
+the IPv6 cloud-metadata address, while leaving loopback and RFC1918/LAN
+reachable.
+
+These tests ensure ``BrowserTool``:
+  - blocks link-local / cloud-metadata targets *before* the navigation reaches
+    the browser service,
+  - still lets loopback, RFC1918/LAN and public URLs through to the (stubbed)
+    service,
+  - preserves the documented non-HTTP scheme behaviour (about:/data:), and
+  - honours an explicit opt-out (allow_private_targets).
+
+No real browser / Playwright / network is used: the BrowserService that the
+tool would create is replaced with a stub, and DNS resolution is mocked.
+"""
+import os
+import sys
+import types
+import unittest
+from unittest.mock import patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+# Stub 'requests' if not installed so sibling tool imports don't fail.
+if "requests" not in sys.modules:
+    _requests_stub = types.ModuleType("requests")
+    _requests_stub.get = lambda *a, **k: None
+    sys.modules["requests"] = _requests_stub
+
+
+def _gai(ip_str):
+    """Build a socket.getaddrinfo return value for a single IPv4 address."""
+    return [(2, 1, 6, "", (ip_str, 0))]
+
+
+class _StubService:
+    """Stand-in for BrowserService that records navigation attempts."""
+
+    def __init__(self):
+        self.navigated = []
+
+    def navigate(self, url, timeout=30000):
+        self.navigated.append(url)
+        return {"url": url, "title": "page", "status": 200}
+
+    def snapshot(self, selector=None):
+        return "Page: page  (http://page/)\nInteractive elements: 0\n---\ncontent"
+
+
+class TestBrowserNavigateSSRF(unittest.TestCase):
+    """Browser navigate blocks link-local/metadata but keeps local dev reachable."""
+
+    def setUp(self):
+        from agent.tools.browser.browser_tool import BrowserTool
+        self.tool = BrowserTool()
+        self.stub = _StubService()
+        # Force the tool to use our stub instead of a real BrowserService.
+        self.tool._service = self.stub
+        patcher = patch.object(BrowserTool, "_get_service", return_value=self.stub)
+        patcher.start()
+        self.addCleanup(patcher.stop)
+
+    # --- Link-local / cloud-metadata: rejected before any service call ---
+
+    def test_cloud_metadata_literal_blocked(self):
+        result = self.tool.execute(
+            {"action": "navigate", "url": "http://169.254.169.254/latest/meta-data/"}
+        )
+        self.assertEqual(result.status, "error")
+        self.assertIn("blocked for security", str(result.result))
+        self.assertEqual(self.stub.navigated, [])
+
+    def test_link_local_literal_blocked(self):
+        result = self.tool.execute({"action": "navigate", "url": "http://169.254.1.1/x"})
+        self.assertEqual(result.status, "error")
+        self.assertIn("blocked for security", str(result.result))
+        self.assertEqual(self.stub.navigated, [])
+
+    def test_ipv6_metadata_literal_blocked(self):
+        result = self.tool.execute(
+            {"action": "navigate", "url": "http://[fd00:ec2::254]/latest/"}
+        )
+        self.assertEqual(result.status, "error")
+        self.assertIn("blocked for security", str(result.result))
+        self.assertEqual(self.stub.navigated, [])
+
+    def test_metadata_hostname_blocked(self):
+        # A hostname that resolves to the metadata endpoint is blocked too.
+        with patch("socket.getaddrinfo", return_value=_gai("169.254.169.254")):
+            result = self.tool.execute(
+                {"action": "navigate", "url": "http://metadata.internal/latest/meta-data/"}
+            )
+        self.assertEqual(result.status, "error")
+        self.assertIn("blocked for security", str(result.result))
+        self.assertEqual(self.stub.navigated, [])
+
+    # --- Local dev targets stay reachable (the maintainer's core workflow) ---
+
+    def test_loopback_literal_allowed(self):
+        result = self.tool.execute({"action": "navigate", "url": "http://127.0.0.1:3000/"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["http://127.0.0.1:3000/"])
+
+    def test_ipv6_loopback_literal_allowed(self):
+        result = self.tool.execute({"action": "navigate", "url": "http://[::1]:5173/"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["http://[::1]:5173/"])
+
+    def test_localhost_bare_allowed(self):
+        """A bare 'localhost' (no scheme) gets https:// prepended, then allowed."""
+        with patch("socket.getaddrinfo", return_value=_gai("127.0.0.1")):
+            result = self.tool.execute({"action": "navigate", "url": "localhost:3000"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["https://localhost:3000"])
+
+    def test_rfc1918_10_hostname_allowed(self):
+        with patch("socket.getaddrinfo", return_value=_gai("10.1.2.3")):
+            result = self.tool.execute({"action": "navigate", "url": "http://dev.lan/app"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["http://dev.lan/app"])
+
+    def test_rfc1918_192_168_hostname_allowed(self):
+        with patch("socket.getaddrinfo", return_value=_gai("192.168.0.5")):
+            result = self.tool.execute({"action": "navigate", "url": "http://router.lan/admin"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["http://router.lan/admin"])
+
+    # --- Public URL is allowed through to the (stubbed) service ---
+
+    def test_public_url_allowed(self):
+        with patch("socket.getaddrinfo", return_value=_gai("93.184.216.34")):
+            result = self.tool.execute({"action": "navigate", "url": "http://example.com/page"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["http://example.com/page"])
+
+    # --- Documented non-HTTP scheme behaviour preserved (not an egress path) ---
+
+    def test_about_blank_not_blocked(self):
+        result = self.tool.execute({"action": "navigate", "url": "about:blank"})
+        self.assertEqual(result.status, "success")
+        self.assertEqual(self.stub.navigated, ["about:blank"])
+
+    # --- Explicit opt-out lets an operator re-enable metadata/link-local ---
+
+    def test_opt_out_allows_metadata(self):
+        from agent.tools.browser.browser_tool import BrowserTool
+        tool = BrowserTool({"allow_private_targets": True})
+        stub = _StubService()
+        tool._service = stub
+        with patch.object(BrowserTool, "_get_service", return_value=stub):
+            result = tool.execute(
+                {"action": "navigate", "url": "http://169.254.169.254/latest/meta-data/"}
+            )
+        self.assertEqual(result.status, "success")
+        self.assertEqual(stub.navigated, ["http://169.254.169.254/latest/meta-data/"])
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_security_ssrf_path_traversal.py b/tests/test_security_ssrf_path_traversal.py
new file mode 100644
index 0000000..bafb54e
--- /dev/null
+++ b/tests/test_security_ssrf_path_traversal.py
@@ -0,0 +1,206 @@
+# encoding:utf-8
+"""
+Unit tests for security fixes:
+  1. Vision tool SSRF protection (issue #2878, #2872)
+  2. Skill service path traversal protection (issue #2873)
+"""
+import os
+import sys
+import tempfile
+import types
+import unittest
+from unittest.mock import patch, MagicMock
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+# Stub 'requests' if not installed so vision.py can be imported for testing.
+if "requests" not in sys.modules:
+    _requests_stub = types.ModuleType("requests")
+    _requests_stub.get = lambda *a, **k: None
+    sys.modules["requests"] = _requests_stub
+
+
+# =============================================================================
+# Vision SSRF tests
+# =============================================================================
+
+class TestVisionSSRFValidation(unittest.TestCase):
+    """Test that _validate_url_safe blocks internal/private URLs.
+
+    SSRF protection is opt-in (disabled by default); enable it via env for
+    the duration of these tests.
+    """
+
+    def setUp(self):
+        self._prev_ssrf_env = os.environ.get("WEB_SECURITY_SSRF_PROTECTION")
+        os.environ["WEB_SECURITY_SSRF_PROTECTION"] = "true"
+        from agent.tools.vision.vision import Vision
+        self.validate = Vision._validate_url_safe
+
+    def tearDown(self):
+        if self._prev_ssrf_env is None:
+            os.environ.pop("WEB_SECURITY_SSRF_PROTECTION", None)
+        else:
+            os.environ["WEB_SECURITY_SSRF_PROTECTION"] = self._prev_ssrf_env
+
+    def test_loopback_ipv4_blocked(self):
+        """127.0.0.1 must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.validate("http://127.0.0.1/canary.png")
+        self.assertIn("non-public", str(ctx.exception))
+
+    def test_loopback_localhost_blocked(self):
+        """localhost must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.validate("http://localhost/canary.png")
+        self.assertIn("non-public", str(ctx.exception))
+
+    def test_private_10_network_blocked(self):
+        """10.x.x.x RFC1918 must be rejected."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (2, 1, 6, "", ("10.0.0.1", 0)),
+            ]
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://internal.corp/image.png")
+            self.assertIn("non-public", str(ctx.exception))
+
+    def test_private_172_network_blocked(self):
+        """172.16.x.x RFC1918 must be rejected."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (2, 1, 6, "", ("172.16.0.1", 0)),
+            ]
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://internal.corp/image.png")
+            self.assertIn("non-public", str(ctx.exception))
+
+    def test_private_192_168_blocked(self):
+        """192.168.x.x RFC1918 must be rejected."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (2, 1, 6, "", ("192.168.1.1", 0)),
+            ]
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://router.local/image.png")
+            self.assertIn("non-public", str(ctx.exception))
+
+    def test_link_local_blocked(self):
+        """169.254.x.x (link-local / cloud metadata) must be rejected."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (2, 1, 6, "", ("169.254.169.254", 0)),
+            ]
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://metadata.google.internal/image.png")
+            self.assertIn("non-public", str(ctx.exception))
+
+    def test_ipv6_loopback_blocked(self):
+        """::1 (IPv6 loopback) must be rejected."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (10, 1, 6, "", ("::1", 0, 0, 0)),
+            ]
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://[::1]/image.png")
+            self.assertIn("non-public", str(ctx.exception))
+
+    def test_public_url_allowed(self):
+        """A URL resolving to a public IP should pass validation."""
+        with patch("socket.getaddrinfo") as mock_gai:
+            mock_gai.return_value = [
+                (2, 1, 6, "", ("151.101.1.140", 0)),
+            ]
+            # Should not raise
+            self.validate("https://cdn.example.com/image.png")
+
+    def test_no_hostname_rejected(self):
+        """A URL with no host must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.validate("http:///path/to/image.png")
+        self.assertIn("no hostname", str(ctx.exception))
+
+    def test_non_http_scheme_rejected(self):
+        """file:// and ftp:// schemes must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.validate("file:///etc/passwd")
+        self.assertIn("scheme", str(ctx.exception))
+
+    def test_dns_failure_rejected(self):
+        """Unresolvable hostname must be rejected."""
+        import socket as sock_mod
+        with patch("socket.getaddrinfo", side_effect=sock_mod.gaierror("Name does not resolve")):
+            with self.assertRaises(ValueError) as ctx:
+                self.validate("http://nonexistent.invalid/img.png")
+            self.assertIn("Cannot resolve", str(ctx.exception))
+
+
+# =============================================================================
+# Skill service path traversal tests
+# =============================================================================
+
+class TestSkillServicePathTraversal(unittest.TestCase):
+    """Test that _safe_skill_dir blocks path traversal attempts."""
+
+    def setUp(self):
+        self.tmp_root = tempfile.mkdtemp()
+        # Create a minimal SkillManager mock with custom_dir set.
+        from agent.skills.service import SkillService
+        mock_manager = MagicMock()
+        mock_manager.custom_dir = self.tmp_root
+        self.svc = SkillService(mock_manager)
+
+    def tearDown(self):
+        import shutil
+        shutil.rmtree(self.tmp_root, ignore_errors=True)
+
+    def test_normal_name_allowed(self):
+        """A simple name like 'my-skill' should produce a valid path."""
+        result = self.svc._safe_skill_dir("my-skill")
+        expected = os.path.realpath(os.path.join(self.tmp_root, "my-skill"))
+        self.assertEqual(result, expected)
+
+    def test_dotdot_traversal_blocked(self):
+        """'../escaped' must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.svc._safe_skill_dir("../escaped")
+        self.assertIn("path traversal", str(ctx.exception))
+
+    def test_nested_dotdot_blocked(self):
+        """'foo/../../escaped' must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.svc._safe_skill_dir("foo/../../escaped")
+        self.assertIn("path traversal", str(ctx.exception))
+
+    def test_absolute_path_blocked(self):
+        """'/tmp/evil' must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.svc._safe_skill_dir("/tmp/evil")
+        self.assertIn("path traversal", str(ctx.exception))
+
+    def test_backslash_path_blocked(self):
+        r"""'\\server\share' must be rejected."""
+        with self.assertRaises(ValueError) as ctx:
+            self.svc._safe_skill_dir("\\server\\share")
+        self.assertIn("path traversal", str(ctx.exception))
+
+    def test_empty_name_blocked(self):
+        """Empty name must be rejected."""
+        with self.assertRaises(ValueError):
+            self.svc._safe_skill_dir("")
+
+    def test_whitespace_only_blocked(self):
+        """Whitespace-only name must be rejected."""
+        with self.assertRaises(ValueError):
+            self.svc._safe_skill_dir("   ")
+
+    def test_subdir_name_allowed(self):
+        """A name with a forward slash but no traversal is allowed if it stays in root."""
+        # e.g. "category/skill-name" is a valid nested skill directory
+        result = self.svc._safe_skill_dir("category/skill-name")
+        expected = os.path.realpath(os.path.join(self.tmp_root, "category/skill-name"))
+        self.assertEqual(result, expected)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_security_ssrf_web_fetch.py b/tests/test_security_ssrf_web_fetch.py
new file mode 100644
index 0000000..6da6e0f
--- /dev/null
+++ b/tests/test_security_ssrf_web_fetch.py
@@ -0,0 +1,224 @@
+# encoding:utf-8
+"""
+Regression tests for web_fetch SSRF protection.
+
+The web_fetch tool fetches model-supplied URLs. Without a guard, a model
+(including one under prompt injection) can point it at loopback, RFC1918,
+link-local or cloud-metadata (169.254.169.254) endpoints, or use a public
+URL that 3xx-redirects into such a target. These tests ensure web_fetch
+refuses the request instead of connecting to the internal address.
+
+No real network is used: DNS resolution and ``requests.get`` are stubbed.
+"""
+import os
+import sys
+import types
+import unittest
+from unittest.mock import patch, MagicMock
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+# Stub 'requests' if not installed so the module can be imported for testing.
+if "requests" not in sys.modules:
+    _requests_stub = types.ModuleType("requests")
+    _requests_stub.get = lambda *a, **k: None
+
+    class _Exc(Exception):
+        pass
+
+    _requests_stub.Timeout = type("Timeout", (_Exc,), {})
+    _requests_stub.ConnectionError = type("ConnectionError", (_Exc,), {})
+    _requests_stub.HTTPError = type("HTTPError", (_Exc,), {})
+    _requests_stub.Response = object
+    _compat = types.SimpleNamespace(urljoin=__import__("urllib.parse", fromlist=["urljoin"]).urljoin)
+    _requests_stub.compat = _compat
+    sys.modules["requests"] = _requests_stub
+
+
+def _gai(ip_str):
+    """Build a socket.getaddrinfo return value for a single IPv4 address."""
+    return [(2, 1, 6, "", (ip_str, 0))]
+
+
+class _FakeRedirect:
+    """Minimal stand-in for a requests redirect Response."""
+
+    def __init__(self, location):
+        self.is_redirect = True
+        self.is_permanent_redirect = False
+        self.headers = {"Location": location}
+        self.closed = False
+
+    def close(self):
+        self.closed = True
+
+
+def _fake_ok_response(body=b"<html><head><title>internal</title></head><body>secret</body></html>"):
+    """A well-formed non-redirect response.
+
+    Returned by the mocked ``requests.get`` so that on UNPATCHED code the
+    fetch path runs to completion and the test fails specifically on the
+    ``assert_not_called`` guard (proving a request reached the internal
+    target), rather than on an incidental error.
+    """
+    resp = MagicMock()
+    resp.is_redirect = False
+    resp.is_permanent_redirect = False
+    resp.status_code = 200
+    resp.headers = {"Content-Type": "text/html; charset=utf-8"}
+    resp.content = body
+    resp.text = body.decode("utf-8")
+    resp.apparent_encoding = "utf-8"
+    resp.raise_for_status = lambda: None
+    return resp
+
+
+class TestWebFetchSSRF(unittest.TestCase):
+    """web_fetch must refuse internal targets and never connect to them.
+
+    SSRF protection is opt-in (disabled by default), so these tests enable it
+    via the WEB_SECURITY_SSRF_PROTECTION env var for the duration of the test.
+    """
+
+    def setUp(self):
+        self._prev_ssrf_env = os.environ.get("WEB_SECURITY_SSRF_PROTECTION")
+        os.environ["WEB_SECURITY_SSRF_PROTECTION"] = "true"
+        from agent.tools.web_fetch.web_fetch import WebFetch
+        self.tool = WebFetch()
+
+    def tearDown(self):
+        if self._prev_ssrf_env is None:
+            os.environ.pop("WEB_SECURITY_SSRF_PROTECTION", None)
+        else:
+            os.environ["WEB_SECURITY_SSRF_PROTECTION"] = self._prev_ssrf_env
+
+    # --- Literal internal IPs: rejected before any socket call ---
+
+    def test_loopback_literal_blocked(self):
+        """http://127.0.0.1:<port>/x must be refused, no request issued."""
+        with patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute({"url": "http://127.0.0.1:8080/canary"})
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        mock_get.assert_not_called()
+
+    def test_cloud_metadata_literal_blocked(self):
+        """http://169.254.169.254/latest/meta-data/ must be refused."""
+        with patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute(
+                {"url": "http://169.254.169.254/latest/meta-data/"}
+            )
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        mock_get.assert_not_called()
+
+    def test_ipv6_loopback_literal_blocked(self):
+        """http://[::1]/x must be refused."""
+        with patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute({"url": "http://[::1]/canary"})
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        mock_get.assert_not_called()
+
+    # --- RFC1918 host resolved via DNS: rejected after resolution ---
+
+    def test_rfc1918_hostname_blocked(self):
+        """A hostname that resolves to 10.x.x.x must be refused, no request."""
+        with patch("socket.getaddrinfo", return_value=_gai("10.1.2.3")), \
+                patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute({"url": "http://internal.corp/secret"})
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        mock_get.assert_not_called()
+
+    def test_192_168_hostname_blocked(self):
+        """A hostname that resolves to 192.168.x.x must be refused."""
+        with patch("socket.getaddrinfo", return_value=_gai("192.168.0.5")), \
+                patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute({"url": "http://router.local/admin"})
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        mock_get.assert_not_called()
+
+    # --- Redirect bounce: public entry URL 302 -> loopback ---
+
+    def test_public_to_loopback_redirect_blocked(self):
+        """A public URL that redirects to a loopback target must be refused.
+
+        The first hop resolves to a public IP and returns a 302 pointing at
+        127.0.0.1; the guard must re-validate the redirect target and refuse
+        instead of fetching the internal address.
+        """
+        redirect = _FakeRedirect("http://127.0.0.1:8080/canary")
+
+        def fake_getaddrinfo(host, *a, **k):
+            # Public entry host resolves to a public IP; the loopback literal
+            # echoes back (as the real getaddrinfo does for an IP literal).
+            if host == "evil.example.com":
+                return _gai("93.184.216.34")
+            return _gai(host)
+
+        with patch("socket.getaddrinfo", side_effect=fake_getaddrinfo), \
+                patch("requests.get", return_value=redirect) as mock_get:
+            result = self.tool.execute({"url": "http://evil.example.com/start"})
+
+        self.assertEqual(result.status, "error")
+        self.assertIn("non-public", result.result)
+        # The first (public) hop is issued exactly once; the loopback hop is
+        # rejected by the guard BEFORE a second requests.get to the internal
+        # target is made.
+        self.assertEqual(mock_get.call_count, 1)
+        first_call_url = mock_get.call_args[0][0]
+        self.assertEqual(first_call_url, "http://evil.example.com/start")
+        # The follow-up request to the internal target was never issued.
+        for call in mock_get.call_args_list:
+            self.assertNotIn("127.0.0.1", call[0][0])
+
+    # --- Sanity: a public URL is allowed to proceed to the fetch path ---
+
+    def test_public_url_allowed_through_guard(self):
+        """A public URL passes the guard and a (mocked) request is issued."""
+        ok = MagicMock()
+        ok.is_redirect = False
+        ok.is_permanent_redirect = False
+        ok.headers = {"Content-Type": "text/html; charset=utf-8"}
+        ok.content = b"<html><head><title>Hi</title></head><body>ok</body></html>"
+        ok.text = "<html><head><title>Hi</title></head><body>ok</body></html>"
+        ok.apparent_encoding = "utf-8"
+        ok.raise_for_status = lambda: None
+
+        with patch("socket.getaddrinfo", return_value=_gai("93.184.216.34")), \
+                patch("requests.get", return_value=ok) as mock_get:
+            result = self.tool.execute({"url": "http://example.com/page"})
+
+        self.assertEqual(result.status, "success")
+        mock_get.assert_called_once()
+        self.assertEqual(mock_get.call_args[0][0], "http://example.com/page")
+
+
+class TestWebFetchSSRFDisabledByDefault(unittest.TestCase):
+    """With protection disabled (default), local/internal targets are reachable."""
+
+    def setUp(self):
+        self._prev_ssrf_env = os.environ.get("WEB_SECURITY_SSRF_PROTECTION")
+        os.environ.pop("WEB_SECURITY_SSRF_PROTECTION", None)
+        from agent.tools.web_fetch.web_fetch import WebFetch
+        self.tool = WebFetch()
+
+    def tearDown(self):
+        if self._prev_ssrf_env is None:
+            os.environ.pop("WEB_SECURITY_SSRF_PROTECTION", None)
+        else:
+            os.environ["WEB_SECURITY_SSRF_PROTECTION"] = self._prev_ssrf_env
+
+    def test_loopback_allowed_when_disabled(self):
+        """http://127.0.0.1/x must be fetched when protection is off (default)."""
+        with patch("socket.getaddrinfo", return_value=_gai("127.0.0.1")), \
+                patch("requests.get", return_value=_fake_ok_response()) as mock_get:
+            result = self.tool.execute({"url": "http://127.0.0.1:8080/local"})
+        self.assertEqual(result.status, "success")
+        mock_get.assert_called_once()
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/test_youdao_translator.py b/tests/test_youdao_translator.py
new file mode 100644
index 0000000..5c50ffc
--- /dev/null
+++ b/tests/test_youdao_translator.py
@@ -0,0 +1,260 @@
+# encoding:utf-8
+"""
+Unit tests for the Youdao translator integration:
+  - YoudaoTranslator class behavior (signature, language code mapping,
+    request/response handling, error handling).
+  - translate.factory.create_translator dispatch and error message.
+"""
+import os
+import sys
+import unittest
+from hashlib import sha256
+from unittest.mock import MagicMock, patch
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+def _mock_conf(**values):
+    """Build a callable that mimics config.conf() returning the provided dict."""
+    cfg = MagicMock()
+    cfg.get = MagicMock(side_effect=lambda key, default=None: values.get(key, default))
+    return MagicMock(return_value=cfg)
+
+
+class TestYoudaoTranslatorInit(unittest.TestCase):
+    def test_init_success(self):
+        with patch(
+            "translate.youdao.youdao_translate.conf",
+            _mock_conf(
+                youdao_translate_app_key="key123",
+                youdao_translate_app_secret="secret456",
+            ),
+        ):
+            from translate.youdao.youdao_translate import YoudaoTranslator
+
+            translator = YoudaoTranslator()
+            self.assertEqual(translator.app_key, "key123")
+            self.assertEqual(translator.app_secret, "secret456")
+
+    def test_init_missing_credentials_raises(self):
+        with patch(
+            "translate.youdao.youdao_translate.conf",
+            _mock_conf(youdao_translate_app_key="", youdao_translate_app_secret=""),
+        ):
+            from translate.youdao.youdao_translate import YoudaoTranslator
+
+            with self.assertRaises(Exception) as ctx:
+                YoudaoTranslator()
+            self.assertIn("youdao", str(ctx.exception).lower())
+
+
+class TestYoudaoTranslatorHelpers(unittest.TestCase):
+    def test_truncate_input_short(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        # length <= 20 -> returned as-is
+        self.assertEqual(YoudaoTranslator._truncate_input("hello"), "hello")
+        self.assertEqual(YoudaoTranslator._truncate_input("a" * 20), "a" * 20)
+
+    def test_truncate_input_long(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        # length > 20 -> first 10 + len + last 10
+        text = "abcdefghij" + "X" * 5 + "1234567890"  # 25 chars
+        result = YoudaoTranslator._truncate_input(text)
+        self.assertEqual(result, "abcdefghij" + "25" + "1234567890")
+
+    def test_truncate_input_exactly_21(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        text = "a" * 21
+        result = YoudaoTranslator._truncate_input(text)
+        # first 10 'a' + "21" + last 10 'a'
+        self.assertEqual(result, "a" * 10 + "21" + "a" * 10)
+
+    def test_convert_lang_known_codes(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        self.assertEqual(YoudaoTranslator._convert_lang(""), "auto")
+        self.assertEqual(YoudaoTranslator._convert_lang("auto"), "auto")
+        self.assertEqual(YoudaoTranslator._convert_lang("zh"), "zh-CHS")
+        self.assertEqual(YoudaoTranslator._convert_lang("zh-CN"), "zh-CHS")
+        self.assertEqual(YoudaoTranslator._convert_lang("zh-TW"), "zh-CHT")
+
+    def test_convert_lang_passthrough(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        # unknown codes pass through unchanged (Youdao accepts ISO codes for many langs)
+        self.assertEqual(YoudaoTranslator._convert_lang("en"), "en")
+        self.assertEqual(YoudaoTranslator._convert_lang("ja"), "ja")
+        self.assertEqual(YoudaoTranslator._convert_lang("fr"), "fr")
+
+    def test_convert_lang_none(self):
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        self.assertEqual(YoudaoTranslator._convert_lang(None), "auto")
+
+    def test_build_sign_matches_v3_spec(self):
+        with patch(
+            "translate.youdao.youdao_translate.conf",
+            _mock_conf(
+                youdao_translate_app_key="appKey",
+                youdao_translate_app_secret="appSecret",
+            ),
+        ):
+            from translate.youdao.youdao_translate import YoudaoTranslator
+
+            translator = YoudaoTranslator()
+            query = "hello"
+            salt = "saltvalue"
+            curtime = "1700000000"
+            expected = sha256(
+                ("appKey" + "hello" + "saltvalue" + "1700000000" + "appSecret").encode("utf-8")
+            ).hexdigest()
+            self.assertEqual(translator._build_sign(query, salt, curtime), expected)
+
+
+class TestYoudaoTranslatorTranslate(unittest.TestCase):
+    def _make_translator(self):
+        with patch(
+            "translate.youdao.youdao_translate.conf",
+            _mock_conf(
+                youdao_translate_app_key="appKey",
+                youdao_translate_app_secret="appSecret",
+            ),
+        ):
+            from translate.youdao.youdao_translate import YoudaoTranslator
+
+            return YoudaoTranslator()
+
+    def test_translate_success(self):
+        translator = self._make_translator()
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "errorCode": "0",
+            "translation": ["你好"],
+            "query": "hello",
+            "l": "en2zh-CHS",
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        with patch(
+            "translate.youdao.youdao_translate.requests.post",
+            return_value=mock_response,
+        ) as mock_post:
+            result = translator.translate("hello", from_lang="en", to_lang="zh")
+
+        self.assertEqual(result, "你好")
+        mock_post.assert_called_once()
+        # Check posted payload contains the right language codes
+        call_kwargs = mock_post.call_args.kwargs
+        payload = call_kwargs["data"]
+        self.assertEqual(payload["q"], "hello")
+        self.assertEqual(payload["from"], "en")
+        self.assertEqual(payload["to"], "zh-CHS")
+        self.assertEqual(payload["appKey"], "appKey")
+        self.assertEqual(payload["signType"], "v3")
+        self.assertIn("salt", payload)
+        self.assertIn("sign", payload)
+        self.assertIn("curtime", payload)
+
+    def test_translate_multiline_joins_with_newlines(self):
+        translator = self._make_translator()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "errorCode": "0",
+            "translation": ["line one", "line two"],
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        with patch(
+            "translate.youdao.youdao_translate.requests.post",
+            return_value=mock_response,
+        ):
+            result = translator.translate("multi\nline")
+        self.assertEqual(result, "line one\nline two")
+
+    def test_translate_empty_query_returns_empty(self):
+        translator = self._make_translator()
+        # Should not even hit the network for an empty query
+        with patch("translate.youdao.youdao_translate.requests.post") as mock_post:
+            self.assertEqual(translator.translate(""), "")
+            mock_post.assert_not_called()
+
+    def test_translate_error_code_raises(self):
+        translator = self._make_translator()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "errorCode": "108",
+            "msg": "appKey无效",
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        with patch(
+            "translate.youdao.youdao_translate.requests.post",
+            return_value=mock_response,
+        ):
+            with self.assertRaises(Exception) as ctx:
+                translator.translate("hello")
+        msg = str(ctx.exception)
+        self.assertIn("108", msg)
+
+    def test_translate_empty_translation_raises(self):
+        translator = self._make_translator()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"errorCode": "0", "translation": []}
+        mock_response.raise_for_status = MagicMock()
+
+        with patch(
+            "translate.youdao.youdao_translate.requests.post",
+            return_value=mock_response,
+        ):
+            with self.assertRaises(Exception):
+                translator.translate("hello")
+
+    def test_translate_default_target_language(self):
+        translator = self._make_translator()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"errorCode": "0", "translation": ["hello"]}
+        mock_response.raise_for_status = MagicMock()
+
+        with patch(
+            "translate.youdao.youdao_translate.requests.post",
+            return_value=mock_response,
+        ) as mock_post:
+            translator.translate("你好")  # no from/to provided
+
+        payload = mock_post.call_args.kwargs["data"]
+        self.assertEqual(payload["from"], "auto")
+        self.assertEqual(payload["to"], "en")
+
+
+class TestTranslatorFactory(unittest.TestCase):
+    def test_factory_creates_youdao(self):
+        with patch(
+            "translate.youdao.youdao_translate.conf",
+            _mock_conf(
+                youdao_translate_app_key="k",
+                youdao_translate_app_secret="s",
+            ),
+        ):
+            from translate.factory import create_translator
+            from translate.youdao.youdao_translate import YoudaoTranslator
+
+            translator = create_translator("youdao")
+            self.assertIsInstance(translator, YoudaoTranslator)
+
+    def test_factory_unknown_type_message(self):
+        from translate.factory import create_translator
+
+        with self.assertRaises(RuntimeError) as ctx:
+            create_translator("nonexistent")
+        msg = str(ctx.exception)
+        self.assertIn("nonexistent", msg)
+        self.assertIn("baidu", msg)
+        self.assertIn("youdao", msg)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/translate/__init__.py b/translate/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/translate/baidu/__init__.py b/translate/baidu/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/translate/baidu/baidu_translate.py b/translate/baidu/baidu_translate.py
new file mode 100644
index 0000000..6f99e34
--- /dev/null
+++ b/translate/baidu/baidu_translate.py
@@ -0,0 +1,49 @@
+# -*- coding: utf-8 -*-
+
+import random
+from hashlib import md5
+
+import requests
+
+from config import conf
+from translate.translator import Translator
+
+
+class BaiduTranslator(Translator):
+    def __init__(self) -> None:
+        super().__init__()
+        endpoint = "http://api.fanyi.baidu.com"
+        path = "/api/trans/vip/translate"
+        self.url = endpoint + path
+        self.appid = conf().get("baidu_translate_app_id")
+        self.appkey = conf().get("baidu_translate_app_key")
+        if not self.appid or not self.appkey:
+            raise Exception("baidu translate appid or appkey not set")
+
+    # For list of language codes, please refer to `https://api.fanyi.baidu.com/doc/21`, need to convert to ISO 639-1 codes
+    def translate(self, query: str, from_lang: str = "", to_lang: str = "en") -> str:
+        if not from_lang:
+            from_lang = "auto"  # baidu suppport auto detect
+        salt = random.randint(32768, 65536)
+        sign = self.make_md5("{}{}{}{}".format(self.appid, query, salt, self.appkey))
+        headers = {"Content-Type": "application/x-www-form-urlencoded"}
+        payload = {"appid": self.appid, "q": query, "from": from_lang, "to": to_lang, "salt": salt, "sign": sign}
+
+        retry_cnt = 3
+        while retry_cnt:
+            r = requests.post(self.url, params=payload, headers=headers)
+            result = r.json()
+            errcode = result.get("error_code", "52000")
+            if errcode != "52000":
+                if errcode == "52001" or errcode == "52002":
+                    retry_cnt -= 1
+                    continue
+                else:
+                    raise Exception(result["error_msg"])
+            else:
+                break
+        text = "\n".join([item["dst"] for item in result["trans_result"]])
+        return text
+
+    def make_md5(self, s, encoding="utf-8"):
+        return md5(s.encode(encoding)).hexdigest()
diff --git a/translate/factory.py b/translate/factory.py
new file mode 100644
index 0000000..7e7bea8
--- /dev/null
+++ b/translate/factory.py
@@ -0,0 +1,17 @@
+SUPPORTED_TRANSLATORS = ("baidu", "youdao")
+
+
+def create_translator(translator_type):
+    if translator_type == "baidu":
+        from translate.baidu.baidu_translate import BaiduTranslator
+
+        return BaiduTranslator()
+    if translator_type == "youdao":
+        from translate.youdao.youdao_translate import YoudaoTranslator
+
+        return YoudaoTranslator()
+    raise RuntimeError(
+        "unsupported translator type: {}, supported: {}".format(
+            translator_type, ", ".join(SUPPORTED_TRANSLATORS)
+        )
+    )
diff --git a/translate/translator.py b/translate/translator.py
new file mode 100644
index 0000000..b394f4e
--- /dev/null
+++ b/translate/translator.py
@@ -0,0 +1,12 @@
+"""
+Voice service abstract class
+"""
+
+
+class Translator(object):
+    # please use https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes to specify language
+    def translate(self, query: str, from_lang: str = "", to_lang: str = "en") -> str:
+        """
+        Translate text from one language to another
+        """
+        raise NotImplementedError
diff --git a/translate/youdao/__init__.py b/translate/youdao/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/translate/youdao/youdao_translate.py b/translate/youdao/youdao_translate.py
new file mode 100644
index 0000000..4db9602
--- /dev/null
+++ b/translate/youdao/youdao_translate.py
@@ -0,0 +1,110 @@
+# -*- coding: utf-8 -*-
+"""
+Youdao translator implementation.
+
+Youdao Translation API v3 documentation:
+https://ai.youdao.com/DOCSIRMA/html/trans/api/wbfy/index.html
+
+Configuration keys (in config.json):
+    youdao_translate_app_key:    Application key from Youdao AI platform.
+    youdao_translate_app_secret: Application secret from Youdao AI platform.
+"""
+
+import time
+import uuid
+from hashlib import sha256
+
+import requests
+
+from config import conf
+from translate.translator import Translator
+
+
+class YoudaoTranslator(Translator):
+    """Youdao translator using the v3 signature scheme."""
+
+    API_URL = "https://openapi.youdao.com/api"
+
+    # Mapping from ISO 639-1 codes (used by the Translator interface)
+    # to Youdao-specific language codes.
+    # Reference: https://ai.youdao.com/DOCSIRMA/html/trans/api/wbfy/index.html
+    LANG_CODE_MAP = {
+        "": "auto",
+        "auto": "auto",
+        "zh": "zh-CHS",
+        "zh-CN": "zh-CHS",
+        "zh-TW": "zh-CHT",
+        "yue": "yue",  # Cantonese
+    }
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.app_key = conf().get("youdao_translate_app_key")
+        self.app_secret = conf().get("youdao_translate_app_secret")
+        if not self.app_key or not self.app_secret:
+            raise Exception("youdao translate app_key or app_secret not set")
+
+    def translate(self, query: str, from_lang: str = "", to_lang: str = "en") -> str:
+        if not query:
+            return ""
+
+        from_lang_code = self._convert_lang(from_lang) or "auto"
+        to_lang_code = self._convert_lang(to_lang) or "en"
+
+        salt = str(uuid.uuid4())
+        curtime = str(int(time.time()))
+        sign = self._build_sign(query, salt, curtime)
+
+        payload = {
+            "q": query,
+            "from": from_lang_code,
+            "to": to_lang_code,
+            "appKey": self.app_key,
+            "salt": salt,
+            "sign": sign,
+            "signType": "v3",
+            "curtime": curtime,
+        }
+        headers = {"Content-Type": "application/x-www-form-urlencoded"}
+
+        response = requests.post(self.API_URL, data=payload, headers=headers, timeout=10)
+        response.raise_for_status()
+        result = response.json()
+
+        error_code = result.get("errorCode", "0")
+        if error_code != "0":
+            raise Exception(
+                "youdao translate error: code={}, msg={}".format(
+                    error_code, result.get("msg", "")
+                )
+            )
+
+        translations = result.get("translation") or []
+        if not translations:
+            raise Exception("youdao translate returned empty translation")
+        return "\n".join(translations)
+
+    def _build_sign(self, query: str, salt: str, curtime: str) -> str:
+        """
+        Build the v3 signature.
+
+        sign = sha256(appKey + input + salt + curtime + appSecret),
+        where input = q if len(q) <= 20 else q[:10] + str(len(q)) + q[-10:].
+        """
+        input_str = self._truncate_input(query)
+        sign_str = self.app_key + input_str + salt + curtime + self.app_secret
+        return sha256(sign_str.encode("utf-8")).hexdigest()
+
+    @staticmethod
+    def _truncate_input(query: str) -> str:
+        length = len(query)
+        if length <= 20:
+            return query
+        return query[:10] + str(length) + query[-10:]
+
+    @classmethod
+    def _convert_lang(cls, lang: str) -> str:
+        """Convert ISO 639-1 language code to Youdao-specific code."""
+        if lang is None:
+            return "auto"
+        return cls.LANG_CODE_MAP.get(lang, lang)
diff --git a/voice/ali/ali_api.py b/voice/ali/ali_api.py
new file mode 100644
index 0000000..def5c7a
--- /dev/null
+++ b/voice/ali/ali_api.py
@@ -0,0 +1,216 @@
+# coding=utf-8
+"""
+Author: chazzjimel
+Email: chazzjimel@gmail.com
+wechat：cheung-z-x
+
+Description:
+
+"""
+
+import http.client
+import json
+import time
+import requests
+import datetime
+import hashlib
+import hmac
+import base64
+import urllib.parse
+import uuid
+
+from common.log import logger
+from common.tmp_dir import TmpDir
+
+
+def text_to_speech_aliyun(url, text, appkey, token):
+    """
+    使用阿里云的文本转语音服务将文本转换为语音。
+
+    参数:
+    - url (str): 阿里云文本转语音服务的端点URL。
+    - text (str): 要转换为语音的文本。
+    - appkey (str): 您的阿里云appkey。
+    - token (str): 阿里云API的认证令牌。
+
+    返回值:
+    - str: 成功时输出音频文件的路径，否则为None。
+    """
+    headers = {
+        "Content-Type": "application/json",
+    }
+
+    data = {
+        "text": text,
+        "appkey": appkey,
+        "token": token,
+        "format": "wav"
+    }
+
+    response = requests.post(url, headers=headers, data=json.dumps(data))
+
+    if response.status_code == 200 and response.headers['Content-Type'] == 'audio/mpeg':
+        output_file = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".wav"
+
+        with open(output_file, 'wb') as file:
+            file.write(response.content)
+        logger.debug(f"音频文件保存成功，文件名：{output_file}")
+    else:
+        logger.debug("响应状态码: {}".format(response.status_code))
+        logger.debug("响应内容: {}".format(response.text))
+        output_file = None
+
+    return output_file
+
+def speech_to_text_aliyun(url, audioContent, appkey, token):
+    """
+    使用阿里云的语音识别服务识别音频文件中的语音。
+
+    参数:
+    - url (str): 阿里云语音识别服务的端点URL。
+    - audioContent (byte): pcm音频数据。
+    - appkey (str): 您的阿里云appkey。
+    - token (str): 阿里云API的认证令牌。
+
+    返回值:
+    - str: 成功时输出识别到的文本，否则为None。
+    """
+    format = 'pcm'
+    sample_rate = 16000
+    enablePunctuationPrediction  = True
+    enableInverseTextNormalization = True
+    enableVoiceDetection  = False
+
+    # 设置RESTful请求参数
+    request = url + '?appkey=' + appkey
+    request = request + '&format=' + format
+    request = request + '&sample_rate=' + str(sample_rate)
+
+    if enablePunctuationPrediction :
+        request = request + '&enable_punctuation_prediction=' + 'true'
+
+    if enableInverseTextNormalization :
+        request = request + '&enable_inverse_text_normalization=' + 'true'
+
+    if enableVoiceDetection :
+        request = request + '&enable_voice_detection=' + 'true'
+        
+    host = 'nls-gateway-cn-shanghai.aliyuncs.com'
+
+    # 设置HTTPS请求头部
+    httpHeaders = {
+        'X-NLS-Token': token,
+        'Content-type': 'application/octet-stream',
+        'Content-Length': len(audioContent)
+        }
+
+    conn = http.client.HTTPSConnection(host)
+    conn.request(method='POST', url=request, body=audioContent, headers=httpHeaders)
+
+    response = conn.getresponse()
+    body = response.read()
+    try:
+        body = json.loads(body)
+        status = body['status']
+        if status == 20000000 :
+            result = body['result']
+            if result :
+                logger.info(f"阿里云语音识别到了：{result}")
+            conn.close()
+            return result
+        else :
+            logger.error(f"语音识别失败，状态码: {status}")
+    except ValueError:
+        logger.error(f"语音识别失败，收到非JSON格式的数据: {body}")
+    conn.close()
+    return None
+
+
+class AliyunTokenGenerator:
+    """
+    用于生成阿里云服务认证令牌的类。
+
+    属性:
+    - access_key_id (str): 您的阿里云访问密钥ID。
+    - access_key_secret (str): 您的阿里云访问密钥秘密。
+    """
+
+    def __init__(self, access_key_id, access_key_secret):
+        self.access_key_id = access_key_id
+        self.access_key_secret = access_key_secret
+
+    def sign_request(self, parameters):
+        """
+        为阿里云服务签名请求。
+
+        参数:
+        - parameters (dict): 请求的参数字典。
+
+        返回值:
+        - str: 请求的签名签章。
+        """
+        # 将参数按照字典顺序排序
+        sorted_params = sorted(parameters.items())
+
+        # 构造待签名的查询字符串
+        canonicalized_query_string = ''
+        for (k, v) in sorted_params:
+            canonicalized_query_string += '&' + self.percent_encode(k) + '=' + self.percent_encode(v)
+
+        # 构造用于签名的字符串
+        string_to_sign = 'GET&%2F&' + self.percent_encode(canonicalized_query_string[1:])  # 使用GET方法
+
+        # 使用HMAC算法计算签名
+        h = hmac.new((self.access_key_secret + "&").encode('utf-8'), string_to_sign.encode('utf-8'), hashlib.sha1)
+        signature = base64.encodebytes(h.digest()).strip()
+
+        return signature
+
+    def percent_encode(self, encode_str):
+        """
+        对字符串进行百分比编码。
+
+        参数:
+        - encode_str (str): 要编码的字符串。
+
+        返回值:
+        - str: 编码后的字符串。
+        """
+        encode_str = str(encode_str)
+        res = urllib.parse.quote(encode_str, '')
+        res = res.replace('+', '%20')
+        res = res.replace('*', '%2A')
+        res = res.replace('%7E', '~')
+        return res
+
+    def get_token(self):
+        """
+        获取阿里云服务的令牌。
+
+        返回值:
+        - str: 获取到的令牌。
+        """
+        # 设置请求参数
+        params = {
+            'Format': 'JSON',
+            'Version': '2019-02-28',
+            'AccessKeyId': self.access_key_id,
+            'SignatureMethod': 'HMAC-SHA1',
+            'Timestamp': datetime.datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ"),
+            'SignatureVersion': '1.0',
+            'SignatureNonce': str(uuid.uuid4()),  # 使用uuid生成唯一的随机数
+            'Action': 'CreateToken',
+            'RegionId': 'cn-shanghai'
+        }
+
+        # 计算签名
+        signature = self.sign_request(params)
+        params['Signature'] = signature
+
+        # 构造请求URL
+        url = 'http://nls-meta.cn-shanghai.aliyuncs.com/?' + urllib.parse.urlencode(params)
+
+        # 发送请求
+        response = requests.get(url)
+
+        return response.text
diff --git a/voice/ali/ali_voice.py b/voice/ali/ali_voice.py
new file mode 100644
index 0000000..91f9143
--- /dev/null
+++ b/voice/ali/ali_voice.py
@@ -0,0 +1,105 @@
+# -*- coding: utf-8 -*-
+"""
+Author: chazzjimel
+Email: chazzjimel@gmail.com
+wechat：cheung-z-x
+
+Description:
+ali voice service
+
+"""
+import json
+import os
+import re
+import time
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from voice.voice import Voice
+from voice.ali.ali_api import AliyunTokenGenerator, speech_to_text_aliyun, text_to_speech_aliyun
+from config import conf
+
+try:
+    from voice.audio_convert import get_pcm_from_wav
+except ImportError as e:
+    logger.debug("import voice.audio_convert failed: {}".format(e))
+
+
+class AliVoice(Voice):
+    def __init__(self):
+        """
+        初始化AliVoice类，从配置文件加载必要的配置。
+        """
+        try:
+            curdir = os.path.dirname(__file__)
+            config_path = os.path.join(curdir, "config.json")
+            with open(config_path, "r") as fr:
+                config = json.load(fr)
+            self.token = None
+            self.token_expire_time = 0
+            # 默认复用阿里云千问的 access_key 和 access_secret
+            self.api_url_voice_to_text = config.get("api_url_voice_to_text")
+            self.api_url_text_to_voice = config.get("api_url_text_to_voice")
+            self.app_key = config.get("app_key")
+            self.access_key_id = conf().get("qwen_access_key_id") or config.get("access_key_id")
+            self.access_key_secret = conf().get("qwen_access_key_secret") or config.get("access_key_secret")
+        except Exception as e:
+            logger.warn("AliVoice init failed: %s, ignore " % e)
+
+    def textToVoice(self, text):
+        """
+        将文本转换为语音文件。
+
+        :param text: 要转换的文本。
+        :return: 返回一个Reply对象，其中包含转换得到的语音文件或错误信息。
+        """
+        # 清除文本中的非中文、非英文和非基本字符
+        text = re.sub(r'[^\u4e00-\u9fa5\u3040-\u30FF\uAC00-\uD7AFa-zA-Z0-9'
+                      r'äöüÄÖÜáéíóúÁÉÍÓÚàèìòùÀÈÌÒÙâêîôûÂÊÎÔÛçÇñÑ，。！？,.]', '', text)
+        # 提取有效的token
+        token_id = self.get_valid_token()
+        fileName = text_to_speech_aliyun(self.api_url_text_to_voice, text, self.app_key, token_id)
+        if fileName:
+            logger.info("[Ali] textToVoice text={} voice file name={}".format(text, fileName))
+            reply = Reply(ReplyType.VOICE, fileName)
+        else:
+            reply = Reply(ReplyType.ERROR, "抱歉，语音合成失败")
+        return reply
+
+    def voiceToText(self, voice_file):
+        """
+        将语音文件转换为文本。
+
+        :param voice_file: 要转换的语音文件。
+        :return: 返回一个Reply对象，其中包含转换得到的文本或错误信息。
+        """
+        # 提取有效的token
+        token_id = self.get_valid_token()
+        logger.debug("[Ali] voice file name={}".format(voice_file))
+        pcm = get_pcm_from_wav(voice_file)
+        text = speech_to_text_aliyun(self.api_url_voice_to_text, pcm, self.app_key, token_id)
+        if text:
+            logger.info("[Ali] VoicetoText = {}".format(text))
+            reply = Reply(ReplyType.TEXT, text)
+        else:
+            reply = Reply(ReplyType.ERROR, "抱歉，语音识别失败")
+        return reply
+
+    def get_valid_token(self):
+        """
+        获取有效的阿里云token。
+
+        :return: 返回有效的token字符串。
+        """
+        current_time = time.time()
+        if self.token is None or current_time >= self.token_expire_time:
+            get_token = AliyunTokenGenerator(self.access_key_id, self.access_key_secret)
+            token_str = get_token.get_token()
+            token_data = json.loads(token_str)
+            self.token = token_data["Token"]["Id"]
+            # 将过期时间减少一小段时间（例如5分钟），以避免在边界条件下的过期
+            self.token_expire_time = token_data["Token"]["ExpireTime"] - 300
+            logger.debug(f"新获取的阿里云token：{self.token}")
+        else:
+            logger.debug("使用缓存的token")
+        return self.token
diff --git a/voice/ali/config.json.template b/voice/ali/config.json.template
new file mode 100644
index 0000000..563c57f
--- /dev/null
+++ b/voice/ali/config.json.template
@@ -0,0 +1,7 @@
+{
+    "api_url_text_to_voice": "https://nls-gateway-cn-shanghai.aliyuncs.com/stream/v1/tts",
+    "api_url_voice_to_text": "https://nls-gateway.cn-shanghai.aliyuncs.com/stream/v1/asr",
+    "app_key": "",
+    "access_key_id": "",
+    "access_key_secret": ""
+}
\ No newline at end of file
diff --git a/voice/audio_convert.py b/voice/audio_convert.py
new file mode 100644
index 0000000..0601f86
--- /dev/null
+++ b/voice/audio_convert.py
@@ -0,0 +1,156 @@
+import shutil
+import wave
+
+from common.log import logger
+
+try:
+    import pysilk
+except ImportError:
+    logger.debug("import pysilk failed, silk voice format will not be supported.")
+
+try:
+    from pydub import AudioSegment
+    _pydub_available = True
+except ImportError:
+    logger.debug("import pydub failed, voice conversion features will not be supported.")
+    AudioSegment = None
+    _pydub_available = False
+
+sil_supports = [8000, 12000, 16000, 24000, 32000, 44100, 48000]  # slk转wav时，支持的采样率
+
+
+def find_closest_sil_supports(sample_rate):
+    """
+    找到最接近的支持的采样率
+    """
+    if sample_rate in sil_supports:
+        return sample_rate
+    closest = 0
+    mindiff = 9999999
+    for rate in sil_supports:
+        diff = abs(rate - sample_rate)
+        if diff < mindiff:
+            closest = rate
+            mindiff = diff
+    return closest
+
+
+def get_pcm_from_wav(wav_path):
+    """
+    从 wav 文件中读取 pcm
+
+    :param wav_path: wav 文件路径
+    :returns: pcm 数据
+    """
+    wav = wave.open(wav_path, "rb")
+    return wav.readframes(wav.getnframes())
+
+
+def any_to_mp3(any_path, mp3_path):
+    """
+    把任意格式转成mp3文件
+    """
+    if not _pydub_available:
+        raise ImportError("pydub is required for audio conversion. Please install it with: pip install pydub")
+    if any_path.endswith(".mp3"):
+        shutil.copy2(any_path, mp3_path)
+        return
+    if any_path.endswith(".sil") or any_path.endswith(".silk") or any_path.endswith(".slk"):
+        sil_to_wav(any_path, any_path)
+        any_path = mp3_path
+    audio = AudioSegment.from_file(any_path)
+    audio.export(mp3_path, format="mp3")
+
+
+def any_to_wav(any_path, wav_path):
+    """
+    把任意格式转成wav文件
+    """
+    if not _pydub_available:
+        raise ImportError("pydub is required for audio conversion. Please install it with: pip install pydub")
+    if any_path.endswith(".wav"):
+        shutil.copy2(any_path, wav_path)
+        return
+    if any_path.endswith(".sil") or any_path.endswith(".silk") or any_path.endswith(".slk"):
+        return sil_to_wav(any_path, wav_path)
+    # pydub 0.23.0+ 会将 parameters 追加到 ffmpeg 命令的输出文件 `-` 之后，
+    # 因此 -nostdin 可能被当作"尾部选项"处理，是否生效取决于 ffmpeg 版本。
+    # 目的是防止后台服务中 ffmpeg 子进程继承父进程的 stdin，避免死锁。
+    audio = AudioSegment.from_file(any_path, parameters=["-nostdin"])
+    # AudioSegment 是不可变对象：set_frame_rate/set_channels 返回新对象，不修改原对象。
+    # 必须将返回值重新赋给 audio，否则修改不会生效。
+    audio = audio.set_frame_rate(16000)
+    audio = audio.set_channels(1)
+    audio.export(wav_path, format="wav", codec='pcm_s16le')
+
+
+def any_to_sil(any_path, sil_path):
+    """
+    把任意格式转成sil文件
+    """
+    if not _pydub_available:
+        raise ImportError("pydub is required for audio conversion. Please install it with: pip install pydub")
+    if any_path.endswith(".sil") or any_path.endswith(".silk") or any_path.endswith(".slk"):
+        shutil.copy2(any_path, sil_path)
+        return 10000
+    audio = AudioSegment.from_file(any_path)
+    rate = find_closest_sil_supports(audio.frame_rate)
+    # Convert to PCM_s16
+    pcm_s16 = audio.set_sample_width(2)
+    pcm_s16 = pcm_s16.set_frame_rate(rate)
+    wav_data = pcm_s16.raw_data
+    silk_data = pysilk.encode(wav_data, data_rate=rate, sample_rate=rate)
+    with open(sil_path, "wb") as f:
+        f.write(silk_data)
+    return audio.duration_seconds * 1000
+
+
+def any_to_amr(any_path, amr_path):
+    """
+    把任意格式转成amr文件
+    """
+    if not _pydub_available:
+        raise ImportError("pydub is required for audio conversion. Please install it with: pip install pydub")
+    if any_path.endswith(".amr"):
+        shutil.copy2(any_path, amr_path)
+        return
+    if any_path.endswith(".sil") or any_path.endswith(".silk") or any_path.endswith(".slk"):
+        raise NotImplementedError("Not support file type: {}".format(any_path))
+    audio = AudioSegment.from_file(any_path)
+    audio = audio.set_frame_rate(8000)  # only support 8000
+    audio.export(amr_path, format="amr")
+    return audio.duration_seconds * 1000
+
+
+def sil_to_wav(silk_path, wav_path, rate: int = 24000):
+    """
+    silk 文件转 wav
+    """
+    wav_data = pysilk.decode_file(silk_path, to_wav=True, sample_rate=rate)
+    with open(wav_path, "wb") as f:
+        f.write(wav_data)
+
+
+def split_audio(file_path, max_segment_length_ms=60000):
+    """
+    分割音频文件
+    """
+    if not _pydub_available:
+        raise ImportError("pydub is required for audio conversion. Please install it with: pip install pydub")
+    audio = AudioSegment.from_file(file_path)
+    audio_length_ms = len(audio)
+    if audio_length_ms <= max_segment_length_ms:
+        return audio_length_ms, [file_path]
+    segments = []
+    for start_ms in range(0, audio_length_ms, max_segment_length_ms):
+        end_ms = min(audio_length_ms, start_ms + max_segment_length_ms)
+        segment = audio[start_ms:end_ms]
+        segments.append(segment)
+    file_prefix = file_path[: file_path.rindex(".")]
+    format = file_path[file_path.rindex(".") + 1 :]
+    files = []
+    for i, segment in enumerate(segments):
+        path = f"{file_prefix}_{i+1}" + f".{format}"
+        segment.export(path, format=format)
+        files.append(path)
+    return audio_length_ms, files
diff --git a/voice/azure/azure_voice.py b/voice/azure/azure_voice.py
new file mode 100644
index 0000000..b0ec8b8
--- /dev/null
+++ b/voice/azure/azure_voice.py
@@ -0,0 +1,95 @@
+"""
+azure voice service
+"""
+import json
+import os
+import time
+
+import azure.cognitiveservices.speech as speechsdk
+from langid import classify
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from config import conf
+from voice.voice import Voice
+
+"""
+Azure voice
+主目录设置文件中需填写azure_voice_api_key和azure_voice_region
+
+查看可用的 voice： https://speech.microsoft.com/portal/voicegallery
+
+"""
+
+
+class AzureVoice(Voice):
+    def __init__(self):
+        try:
+            curdir = os.path.dirname(__file__)
+            config_path = os.path.join(curdir, "config.json")
+            config = None
+            if not os.path.exists(config_path):  # 如果没有配置文件，创建本地配置文件
+                config = {
+                    "speech_synthesis_voice_name": "zh-CN-XiaoxiaoNeural",  # 识别不出时的默认语音
+                    "auto_detect": True,  # 是否自动检测语言
+                    "speech_synthesis_zh": "zh-CN-XiaozhenNeural",
+                    "speech_synthesis_en": "en-US-JacobNeural",
+                    "speech_synthesis_ja": "ja-JP-AoiNeural",
+                    "speech_synthesis_ko": "ko-KR-SoonBokNeural",
+                    "speech_synthesis_de": "de-DE-LouisaNeural",
+                    "speech_synthesis_fr": "fr-FR-BrigitteNeural",
+                    "speech_synthesis_es": "es-ES-LaiaNeural",
+                    "speech_recognition_language": "zh-CN",
+                }
+                with open(config_path, "w") as fw:
+                    json.dump(config, fw, indent=4)
+            else:
+                with open(config_path, "r") as fr:
+                    config = json.load(fr)
+            self.config = config
+            self.api_key = conf().get("azure_voice_api_key")
+            self.api_region = conf().get("azure_voice_region")
+            self.speech_config = speechsdk.SpeechConfig(subscription=self.api_key, region=self.api_region)
+            self.speech_config.speech_synthesis_voice_name = self.config["speech_synthesis_voice_name"]
+            self.speech_config.speech_recognition_language = self.config["speech_recognition_language"]
+        except Exception as e:
+            logger.warn("AzureVoice init failed: %s, ignore " % e)
+
+    def voiceToText(self, voice_file):
+        audio_config = speechsdk.AudioConfig(filename=voice_file)
+        speech_recognizer = speechsdk.SpeechRecognizer(speech_config=self.speech_config, audio_config=audio_config)
+        result = speech_recognizer.recognize_once()
+        if result.reason == speechsdk.ResultReason.RecognizedSpeech:
+            logger.info("[Azure] voiceToText voice file name={} text={}".format(voice_file, result.text))
+            reply = Reply(ReplyType.TEXT, result.text)
+        else:
+            cancel_details = result.cancellation_details
+            logger.error("[Azure] voiceToText error, result={}, errordetails={}".format(result, cancel_details))
+            reply = Reply(ReplyType.ERROR, "抱歉，语音识别失败")
+        return reply
+
+    def textToVoice(self, text):
+        if self.config.get("auto_detect"):
+            lang = classify(text)[0]
+            key = "speech_synthesis_" + lang
+            if key in self.config:
+                logger.info("[Azure] textToVoice auto detect language={}, voice={}".format(lang, self.config[key]))
+                self.speech_config.speech_synthesis_voice_name = self.config[key]
+            else:
+                self.speech_config.speech_synthesis_voice_name = self.config["speech_synthesis_voice_name"]
+        else:
+            self.speech_config.speech_synthesis_voice_name = self.config["speech_synthesis_voice_name"]
+        # Avoid the same filename under multithreading
+        fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".wav"
+        audio_config = speechsdk.AudioConfig(filename=fileName)
+        speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=self.speech_config, audio_config=audio_config)
+        result = speech_synthesizer.speak_text(text)
+        if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
+            logger.info("[Azure] textToVoice text={} voice file name={}".format(text, fileName))
+            reply = Reply(ReplyType.VOICE, fileName)
+        else:
+            cancel_details = result.cancellation_details
+            logger.error("[Azure] textToVoice error, result={}, errordetails={}".format(result, cancel_details.error_details))
+            reply = Reply(ReplyType.ERROR, "抱歉，语音合成失败")
+        return reply
diff --git a/voice/azure/config.json.template b/voice/azure/config.json.template
new file mode 100644
index 0000000..8f3f546
--- /dev/null
+++ b/voice/azure/config.json.template
@@ -0,0 +1,12 @@
+{
+  "speech_synthesis_voice_name": "zh-CN-XiaoxiaoNeural",
+  "auto_detect": true,
+  "speech_synthesis_zh": "zh-CN-YunxiNeural",
+  "speech_synthesis_en": "en-US-JacobNeural",
+  "speech_synthesis_ja": "ja-JP-AoiNeural",
+  "speech_synthesis_ko": "ko-KR-SoonBokNeural",
+  "speech_synthesis_de": "de-DE-LouisaNeural",
+  "speech_synthesis_fr": "fr-FR-BrigitteNeural",
+  "speech_synthesis_es": "es-ES-LaiaNeural",
+  "speech_recognition_language": "zh-CN"
+}
diff --git a/voice/baidu/README.md b/voice/baidu/README.md
new file mode 100644
index 0000000..d4628a1
--- /dev/null
+++ b/voice/baidu/README.md
@@ -0,0 +1,55 @@
+## 说明
+百度语音识别与合成参数说明
+百度语音依赖，经常会出现问题，可能就是缺少依赖：
+pip install baidu-aip
+pip install pydub
+pip install pysilk
+还有ffmpeg，不同系统安装方式不同
+
+系统中收到的语音文件为mp3格式（wx）或者sil格式（wxy），如果要识别需要转换为pcm格式，转换后的文件为16k采样率，单声道，16bit的pcm文件
+发送时又需要（wx）转换为mp3格式，转换后的文件为16k采样率，单声道，16bit的pcm文件,（wxy）转换为sil格式,还要计算声音长度，发送时需要带上声音长度
+这些事情都在audio_convert.py中封装了，直接调用即可
+
+
+参数说明
+识别参数
+https://ai.baidu.com/ai-doc/SPEECH/Vk38lxily
+合成参数
+https://ai.baidu.com/ai-doc/SPEECH/Gk38y8lzk
+
+## 使用说明
+分两个地方配置
+
+1、对于def voiceToText(self, filename)函数中调用的百度语音识别API,中接口调用asr（参数）这个配置见CHATGPT-ON-WECHAT工程目录下的`config.json`文件和config.py文件。
+参数	    可需	描述
+app_id    必填	应用的APPID
+api_key  必填	应用的APIKey
+secret_key  必填	应用的SecretKey
+dev_pid	    必填	语言选择,填写语言对应的dev_pid值
+
+2、对于def textToVoice(self, text)函数中调用的百度语音合成API,中接口调用synthesis（参数）在本目录下的`config.json`文件中进行配置。
+参数	    可需	描述
+tex	        必填	合成的文本，使用UTF-8编码，请注意文本长度必须小于1024字节  
+lan	        必填	固定值zh。语言选择,目前只有中英文混合模式，填写固定值zh
+spd	        选填	语速，取值0-15，默认为5中语速
+pit	        选填	音调，取值0-15，默认为5中语调
+vol	        选填	音量，取值0-15，默认为5中音量（取值为0时为音量最小值，并非为无声）
+per（基础音库）	选填	度小宇=1，度小美=0，度逍遥（基础）=3，度丫丫=4
+per（精品音库）	选填	度逍遥（精品）=5003，度小鹿=5118，度博文=106，度小童=110，度小萌=111，度米朵=103，度小娇=5
+aue	        选填	3为mp3格式(默认)； 4为pcm-16k；5为pcm-8k；6为wav（内容同pcm-16k）; 注意aue=4或者6是语音识别要求的格式，但是音频内容不是语音识别要求的自然人发音，所以识别效果会受影响。
+
+关于per参数的说明，注意您购买的哪个音库，就填写哪个音库的参数，否则会报错。如果您购买的是基础音库，那么per参数只能填写0到4，如果您购买的是精品音库，那么per参数只能填写5003，5118，106,110,111,103,5其他的都会报错。
+### 配置文件
+
+将文件夹中`config.json.template`复制为`config.json`。
+
+``` json
+    {
+    "lang": "zh",
+    "ctp": 1,
+    "spd": 5,
+    "pit": 5,
+    "vol": 5,
+    "per": 0
+    }
+```
\ No newline at end of file
diff --git a/voice/baidu/baidu_voice.py b/voice/baidu/baidu_voice.py
new file mode 100644
index 0000000..8ded4cf
--- /dev/null
+++ b/voice/baidu/baidu_voice.py
@@ -0,0 +1,176 @@
+"""
+baidu voice service with thread-safe token caching
+"""
+import json
+import os
+import time
+import threading
+import requests
+
+from aip import AipSpeech
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from config import conf
+from voice.voice import Voice
+
+try:
+    from voice.audio_convert import get_pcm_from_wav
+except ImportError as e:
+    logger.debug("import voice.audio_convert failed: {}".format(e))
+
+class BaiduVoice(Voice):
+    def __init__(self):
+        try:
+            # 读取本地 TTS 参数配置
+            curdir = os.path.dirname(__file__)
+            config_path = os.path.join(curdir, "config.json")
+            if not os.path.exists(config_path):
+                bconf = {"lang": "zh", "ctp": 1, "spd": 5, "pit": 5, "vol": 5, "per": 0}
+                with open(config_path, "w") as fw:
+                    json.dump(bconf, fw, indent=4)
+            else:
+                with open(config_path, "r") as fr:
+                    bconf = json.load(fr)
+
+            self.app_id = str(conf().get("baidu_app_id"))
+            self.api_key = str(conf().get("baidu_api_key"))
+            self.secret_key = str(conf().get("baidu_secret_key"))
+            self.dev_id = conf().get("baidu_dev_pid")
+
+            self.lang = bconf["lang"]
+            self.ctp  = bconf["ctp"]
+            self.spd  = bconf["spd"]
+            self.pit  = bconf["pit"]
+            self.vol  = bconf["vol"]
+            self.per  = bconf["per"]
+
+            # 百度 SDK 客户端（短文本合成 & 语音识别）
+            self.client = AipSpeech(self.app_id, self.api_key, self.secret_key)
+
+            # access_token 缓存与锁
+            self._access_token    = None
+            self._token_expire_ts = 0
+            self._token_lock      = threading.Lock()
+        except Exception as e:
+            logger.warn("BaiduVoice init failed: %s, ignore" % e)
+
+    def _get_access_token(self):
+        # 多线程安全获取 token
+        with self._token_lock:
+            now = time.time()
+            if self._access_token and now < self._token_expire_ts:
+                return self._access_token
+            url = "https://aip.baidubce.com/oauth/2.0/token"
+            params = {
+                "grant_type":    "client_credentials",
+                "client_id":     self.api_key,
+                "client_secret": self.secret_key,
+            }
+            resp = requests.post(url, params=params).json()
+            token = resp.get("access_token")
+            expires_in = resp.get("expires_in", 2592000)
+            if token:
+                self._access_token    = token
+                self._token_expire_ts = now + expires_in - 60  # 提前 1 分钟过期
+                return token
+            else:
+                logger.error("BaiduVoice _get_access_token failed: %s", resp)
+                return None
+
+    def voiceToText(self, voice_file):
+        logger.debug("[Baidu] recognize voice file=%s", voice_file)
+        pcm = get_pcm_from_wav(voice_file)
+        res = self.client.asr(pcm, "pcm", 16000, {"dev_pid": self.dev_id})
+        if res.get("err_no") == 0:
+            text = "".join(res["result"])
+            logger.info("[Baidu] ASR result: %s", text)
+            return Reply(ReplyType.TEXT, text)
+        else:
+            err = res.get("err_msg", "")
+            logger.error("[Baidu] ASR error: %s", err)
+            return Reply(ReplyType.ERROR, f"语音识别失败：{err}")
+
+    def _long_text_synthesis(self, text):
+        token = self._get_access_token()
+        if not token:
+            return Reply(ReplyType.ERROR, "获取百度 access_token 失败")
+
+        # 创建合成任务
+        create_url = f"https://aip.baidubce.com/rpc/2.0/tts/v1/create?access_token={token}"
+        payload = {
+            "text":            text,
+            "format":          "mp3-16k",
+            "voice":           0,
+            "lang":            self.lang,
+            "speed":           self.spd,
+            "pitch":           self.pit,
+            "volume":          self.vol,
+            "enable_subtitle": 0,
+        }
+        headers = {"Content-Type": "application/json"}
+        create_resp = requests.post(create_url, headers=headers, json=payload).json()
+        task_id = create_resp.get("task_id")
+        if not task_id:
+            logger.error("[Baidu] 长文本合成创建任务失败: %s", create_resp)
+            return Reply(ReplyType.ERROR, "长文本合成任务提交失败")
+        logger.info("[Baidu] 长文本合成任务已提交 task_id=%s", task_id)
+
+        # 轮询查询任务状态
+        query_url = f"https://aip.baidubce.com/rpc/2.0/tts/v1/query?access_token={token}"
+        for _ in range(100):
+            time.sleep(3)
+            resp = requests.post(query_url, headers=headers, json={"task_ids":[task_id]})
+            result = resp.json()
+            infos = result.get("tasks_info") or result.get("tasks") or []
+            if not infos:
+                continue
+            info = infos[0]
+            status = info.get("task_status")
+            if status == "Success":
+                task_res = info.get("task_result", {})
+                audio_url = task_res.get("audio_address") or task_res.get("speech_url")
+                break
+            elif status == "Running":
+                continue
+            else:
+                logger.error("[Baidu] 长文本合成失败: %s", info)
+                return Reply(ReplyType.ERROR, "长文本合成执行失败")
+        else:
+            return Reply(ReplyType.ERROR, "长文本合成超时，请稍后重试")
+
+        # 下载并保存音频
+        audio_data = requests.get(audio_url).content
+        fn = TmpDir().path() + f"reply-long-{int(time.time())}-{hash(text)&0x7FFFFFFF}.mp3"
+        with open(fn, "wb") as f:
+            f.write(audio_data)
+        logger.info("[Baidu] 长文本合成 success: %s", fn)
+        return Reply(ReplyType.VOICE, fn)
+
+    def textToVoice(self, text):
+        try:
+            # GBK 编码字节长度
+            gbk_len = len(text.encode("gbk", errors="ignore"))
+            if gbk_len <= 1024:
+                # 短文本走 SDK 合成
+                result = self.client.synthesis(
+                    text, self.lang, self.ctp,
+                    {"spd":self.spd, "pit":self.pit, "vol":self.vol, "per":self.per}
+                )
+                if not isinstance(result, dict):
+                    fn = TmpDir().path() + f"reply-{int(time.time())}-{hash(text)&0x7FFFFFFF}.mp3"
+                    with open(fn, "wb") as f:
+                        f.write(result)
+                    logger.info("[Baidu] 短文本合成 success: %s", fn)
+                    return Reply(ReplyType.VOICE, fn)
+                else:
+                    logger.error("[Baidu] 短文本合成 error: %s", result)
+                    return Reply(ReplyType.ERROR, "短文本语音合成失败")
+            else:
+                # 长文本
+                return self._long_text_synthesis(text)
+        except Exception as e:
+            logger.error("BaiduVoice textToVoice exception: %s", e)
+            return Reply(ReplyType.ERROR, f"合成异常：{e}")
+
diff --git a/voice/baidu/config.json.template b/voice/baidu/config.json.template
new file mode 100644
index 0000000..19e812f
--- /dev/null
+++ b/voice/baidu/config.json.template
@@ -0,0 +1,8 @@
+{
+  "lang": "zh",
+  "ctp": 1,
+  "spd": 5,
+  "pit": 5,
+  "vol": 5,
+  "per": 0
+}
diff --git a/voice/dashscope/__init__.py b/voice/dashscope/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/voice/dashscope/dashscope_voice.py b/voice/dashscope/dashscope_voice.py
new file mode 100644
index 0000000..e1f0770
--- /dev/null
+++ b/voice/dashscope/dashscope_voice.py
@@ -0,0 +1,175 @@
+# encoding:utf-8
+"""DashScope voice: qwen3-asr-flash (ASR) + qwen3-tts-flash (TTS)
+via dashscope.MultiModalConversation."""
+import datetime
+import os
+import random
+from typing import Optional
+
+import dashscope
+import requests
+from dashscope import MultiModalConversation
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from config import conf
+from voice import audio_convert
+from voice.voice import Voice
+
+
+DEFAULT_ASR_MODEL = "qwen3-asr-flash"
+DEFAULT_TTS_MODEL = "qwen3-tts-flash"
+DEFAULT_TTS_VOICE = "Cherry"
+MAX_DURATION_SECONDS = 300
+MAX_FILE_BYTES = 10 * 1024 * 1024
+
+
+class DashScopeVoice(Voice):
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file: str):
+        try:
+            voice_file = self._ensure_compatible_format(voice_file)
+
+            try:
+                size = os.path.getsize(voice_file)
+                if size > MAX_FILE_BYTES:
+                    logger.warning(
+                        f"[DashScopeVoice] audio file {size}B exceeds {MAX_FILE_BYTES}B; "
+                        f"qwen3-asr-flash may reject it"
+                    )
+            except OSError:
+                pass
+
+            api_key = conf().get("dashscope_api_key", "")
+            if not api_key:
+                logger.error("[DashScopeVoice] dashscope_api_key is not configured")
+                return Reply(ReplyType.ERROR, "未配置 DashScope API key")
+            dashscope.api_key = api_key
+
+            model = conf().get("voice_to_text_model") or DEFAULT_ASR_MODEL
+            abs_path = os.path.abspath(voice_file)
+            file_uri = f"file://{abs_path}"
+
+            messages = [
+                {"role": "user", "content": [{"audio": file_uri}]},
+            ]
+            response = MultiModalConversation.call(
+                model=model,
+                messages=messages,
+                result_format="message",
+                asr_options={"enable_itn": False, "enable_lid": True},
+            )
+
+            text = self._extract_text(response)
+            if text is None:
+                logger.error(f"[DashScopeVoice] voiceToText failed: {response}")
+                return Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+
+            logger.info(f"[DashScopeVoice] voiceToText model={model} text={text}")
+            return Reply(ReplyType.TEXT, text)
+        except Exception as e:
+            logger.exception(f"[DashScopeVoice] voiceToText exception: {e}")
+            return Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+
+    def textToVoice(self, text: str):
+        try:
+            api_key = conf().get("dashscope_api_key", "")
+            if not api_key:
+                logger.error("[DashScopeVoice] dashscope_api_key is not configured")
+                return Reply(ReplyType.ERROR, "未配置 DashScope API key")
+            dashscope.api_key = api_key
+
+            model = conf().get("text_to_voice_model") or DEFAULT_TTS_MODEL
+            voice = conf().get("tts_voice_id") or DEFAULT_TTS_VOICE
+            response = MultiModalConversation.call(
+                model=model,
+                api_key=api_key,
+                text=text,
+                voice=voice,
+                stream=False,
+            )
+
+            url = self._extract_audio_url(response)
+            if not url:
+                logger.error(f"[DashScopeVoice] textToVoice failed: {response}")
+                return Reply(ReplyType.ERROR, "语音合成失败")
+
+            local_path = self._download_audio(url)
+            if not local_path:
+                return Reply(ReplyType.ERROR, "语音合成失败")
+
+            logger.info(f"[DashScopeVoice] textToVoice model={model} voice={voice} file={local_path}")
+            return Reply(ReplyType.VOICE, local_path)
+        except Exception as e:
+            logger.exception(f"[DashScopeVoice] textToVoice exception: {e}")
+            return Reply(ReplyType.ERROR, "语音合成失败")
+
+    @staticmethod
+    def _extract_audio_url(response) -> Optional[str]:
+        try:
+            if getattr(response, "status_code", 200) != 200:
+                return None
+            audio = response.output.get("audio") if response.output else None
+            if isinstance(audio, dict):
+                return audio.get("url") or None
+            return getattr(audio, "url", None)
+        except Exception:
+            return None
+
+    @staticmethod
+    def _download_audio(url: str) -> Optional[str]:
+        try:
+            tmp_dir = TmpDir().path()
+            ts = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+            ext = os.path.splitext(url.split("?", 1)[0])[1].lower() or ".wav"
+            if ext not in (".mp3", ".wav", ".m4a", ".aac", ".opus"):
+                ext = ".wav"
+            dst = os.path.join(tmp_dir, f"dashscope_tts_{ts}_{random.randint(0, 9999)}{ext}")
+            resp = requests.get(url, timeout=60)
+            resp.raise_for_status()
+            with open(dst, "wb") as f:
+                f.write(resp.content)
+            return dst
+        except Exception as e:
+            logger.error(f"[DashScopeVoice] download audio failed: {e}")
+            return None
+
+    @staticmethod
+    def _ensure_compatible_format(voice_file: str) -> str:
+        # qwen3-asr-flash doesn't accept AMR/SILK; mp3/wav/m4a/aac/opus pass through.
+        lower = voice_file.lower()
+        if lower.endswith(".amr") or lower.endswith(".silk") or lower.endswith(".slk"):
+            try:
+                mp3_file = os.path.splitext(voice_file)[0] + ".mp3"
+                audio_convert.any_to_mp3(voice_file, mp3_file)
+                return mp3_file
+            except Exception as e:
+                logger.warning(f"[DashScopeVoice] mp3 convert failed: {e}")
+        return voice_file
+
+    @staticmethod
+    def _extract_text(response) -> Optional[str]:
+        try:
+            if getattr(response, "status_code", 200) != 200:
+                return None
+            choices = response.output.get("choices") or []
+            if not choices:
+                return None
+            content = choices[0].get("message", {}).get("content")
+            if isinstance(content, str):
+                return content.strip() or None
+            if isinstance(content, list):
+                parts = []
+                for item in content:
+                    if isinstance(item, dict) and "text" in item:
+                        parts.append(item["text"])
+                    elif isinstance(item, str):
+                        parts.append(item)
+                text = "".join(parts).strip()
+                return text or None
+            return None
+        except Exception:
+            return None
diff --git a/voice/edge/edge_voice.py b/voice/edge/edge_voice.py
new file mode 100644
index 0000000..1a25a2b
--- /dev/null
+++ b/voice/edge/edge_voice.py
@@ -0,0 +1,51 @@
+# Requires: edge-tts  (pip install edge-tts)
+import time
+
+import edge_tts
+import asyncio
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from voice.voice import Voice
+
+
+class EdgeVoice(Voice):
+
+    def __init__(self):
+        '''
+        # 普通话
+        zh-CN-XiaoxiaoNeural
+        zh-CN-XiaoyiNeural
+        zh-CN-YunjianNeural
+        zh-CN-YunxiNeural
+        zh-CN-YunxiaNeural
+        zh-CN-YunyangNeural
+        # 地方口音
+        zh-CN-liaoning-XiaobeiNeural
+        zh-CN-shaanxi-XiaoniNeural
+        # 粤语
+        zh-HK-HiuGaaiNeural
+        zh-HK-HiuMaanNeural
+        zh-HK-WanLungNeural
+        # 湾湾腔
+        zh-TW-HsiaoChenNeural
+        zh-TW-HsiaoYuNeural
+        zh-TW-YunJheNeural
+        '''
+        self.voice = "zh-CN-YunjianNeural"
+
+    def voiceToText(self, voice_file):
+        pass
+
+    async def gen_voice(self, text, fileName):
+        communicate = edge_tts.Communicate(text, self.voice)
+        await communicate.save(fileName)
+
+    def textToVoice(self, text):
+        fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+
+        asyncio.run(self.gen_voice(text, fileName))
+
+        logger.info("[EdgeTTS] textToVoice text={} voice file name={}".format(text, fileName))
+        return Reply(ReplyType.VOICE, fileName)
diff --git a/voice/elevent/elevent_voice.py b/voice/elevent/elevent_voice.py
new file mode 100644
index 0000000..5e27463
--- /dev/null
+++ b/voice/elevent/elevent_voice.py
@@ -0,0 +1,33 @@
+# Requires: elevenlabs==1.0.3  (pip install elevenlabs==1.0.3)
+import time
+
+from elevenlabs.client import ElevenLabs
+from elevenlabs import save
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from voice.voice import Voice
+from config import conf
+
+XI_API_KEY = conf().get("xi_api_key")
+client = ElevenLabs(api_key=XI_API_KEY)
+name = conf().get("xi_voice_id")
+
+class ElevenLabsVoice(Voice):
+
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file):
+        pass
+
+    def textToVoice(self, text):
+        audio = client.generate(
+            text=text,
+            voice=name,
+            model='eleven_multilingual_v2'
+        )
+        fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+        save(audio, fileName)
+        logger.info("[ElevenLabs] textToVoice text={} voice file name={}".format(text, fileName))
+        return Reply(ReplyType.VOICE, fileName)
\ No newline at end of file
diff --git a/voice/factory.py b/voice/factory.py
new file mode 100644
index 0000000..2bc356f
--- /dev/null
+++ b/voice/factory.py
@@ -0,0 +1,73 @@
+"""
+voice factory
+"""
+
+
+def create_voice(voice_type):
+    """
+    create a voice instance
+    :param voice_type: voice type code
+    :return: voice instance
+    """
+    if voice_type == "baidu":
+        from voice.baidu.baidu_voice import BaiduVoice
+
+        return BaiduVoice()
+    elif voice_type == "google":
+        from voice.google.google_voice import GoogleVoice
+
+        return GoogleVoice()
+    elif voice_type == "openai":
+        from voice.openai.openai_voice import OpenaiVoice
+
+        return OpenaiVoice()
+    elif voice_type == "pytts":
+        from voice.pytts.pytts_voice import PyttsVoice
+
+        return PyttsVoice()
+    elif voice_type == "azure":
+        from voice.azure.azure_voice import AzureVoice
+
+        return AzureVoice()
+    elif voice_type == "elevenlabs":
+        from voice.elevent.elevent_voice import ElevenLabsVoice
+
+        return ElevenLabsVoice()
+
+    elif voice_type == "linkai":
+        from voice.linkai.linkai_voice import LinkAIVoice
+
+        return LinkAIVoice()
+    elif voice_type == "ali":
+        from voice.ali.ali_voice import AliVoice
+
+        return AliVoice()
+    elif voice_type == "edge":
+        from voice.edge.edge_voice import EdgeVoice
+
+        return EdgeVoice()
+    elif voice_type == "xunfei":
+        from voice.xunfei.xunfei_voice import XunfeiVoice
+
+        return XunfeiVoice()
+    elif voice_type == "tencent":
+        from voice.tencent.tencent_voice import TencentVoice
+
+        return TencentVoice()
+    elif voice_type == "minimax":
+        from voice.minimax.minimax_voice import MinimaxVoice
+
+        return MinimaxVoice()
+    elif voice_type == "dashscope":
+        from voice.dashscope.dashscope_voice import DashScopeVoice
+
+        return DashScopeVoice()
+    elif voice_type == "zhipu" or voice_type == "zhipuai":
+        from voice.zhipuai.zhipuai_voice import ZhipuAIVoice
+
+        return ZhipuAIVoice()
+    elif voice_type == "mimo":
+        from voice.mimo.mimo_voice import MimoVoice
+
+        return MimoVoice()
+    raise RuntimeError
diff --git a/voice/google/google_voice.py b/voice/google/google_voice.py
new file mode 100644
index 0000000..6dcadad
--- /dev/null
+++ b/voice/google/google_voice.py
@@ -0,0 +1,47 @@
+"""
+google voice service
+"""
+
+import time
+
+import speech_recognition
+from gtts import gTTS
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from voice.voice import Voice
+
+
+class GoogleVoice(Voice):
+    recognizer = speech_recognition.Recognizer()
+
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file):
+        with speech_recognition.AudioFile(voice_file) as source:
+            audio = self.recognizer.record(source)
+        try:
+            text = self.recognizer.recognize_google(audio, language="zh-CN")
+            logger.info("[Google] voiceToText text={} voice file name={}".format(text, voice_file))
+            reply = Reply(ReplyType.TEXT, text)
+        except speech_recognition.UnknownValueError:
+            reply = Reply(ReplyType.ERROR, "抱歉，我听不懂")
+        except speech_recognition.RequestError as e:
+            reply = Reply(ReplyType.ERROR, "抱歉，无法连接到 Google 语音识别服务；{0}".format(e))
+        finally:
+            return reply
+
+    def textToVoice(self, text):
+        try:
+            # Avoid the same filename under multithreading
+            mp3File = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+            tts = gTTS(text=text, lang="zh")
+            tts.save(mp3File)
+            logger.info("[Google] textToVoice text={} voice file name={}".format(text, mp3File))
+            reply = Reply(ReplyType.VOICE, mp3File)
+        except Exception as e:
+            reply = Reply(ReplyType.ERROR, str(e))
+        finally:
+            return reply
diff --git a/voice/linkai/linkai_voice.py b/voice/linkai/linkai_voice.py
new file mode 100644
index 0000000..ec59812
--- /dev/null
+++ b/voice/linkai/linkai_voice.py
@@ -0,0 +1,89 @@
+"""LinkAI voice: Whisper ASR + multi-vendor TTS (OpenAI / Doubao / Baidu)
+proxied via https://docs.link-ai.tech/platform/api/voice-speech."""
+import datetime
+import os
+import random
+
+import requests
+
+from bridge.reply import Reply, ReplyType
+from common import const
+from common.log import logger
+from config import conf
+from voice import audio_convert
+from voice.voice import Voice
+
+
+class LinkAIVoice(Voice):
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file):
+        logger.debug("[LinkVoice] voice file name={}".format(voice_file))
+        try:
+            url = conf().get("linkai_api_base", "https://api.link-ai.tech") + "/v1/audio/transcriptions"
+            headers = {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+            # Pin whisper-1: gateway ignores any other ASR model id.
+            model = const.WHISPER_1
+            if voice_file.endswith(".amr"):
+                try:
+                    mp3_file = os.path.splitext(voice_file)[0] + ".mp3"
+                    audio_convert.any_to_mp3(voice_file, mp3_file)
+                    voice_file = mp3_file
+                except Exception as e:
+                    logger.warning(f"[LinkVoice] amr file transfer failed, directly send amr voice file: {e}")
+            with open(voice_file, "rb") as file:
+                res = requests.post(
+                    url,
+                    files={"file": file},
+                    headers=headers,
+                    data={"model": model},
+                    timeout=(5, 60),
+                )
+            if res.status_code != 200:
+                msg = ""
+                try:
+                    msg = res.json().get("message", "")
+                except Exception:
+                    pass
+                logger.error(f"[LinkVoice] voiceToText error, status_code={res.status_code}, msg={msg}")
+                return None
+            text = res.json().get("text")
+            logger.info(f"[LinkVoice] voiceToText success, text={text}, file name={voice_file}")
+            return Reply(ReplyType.TEXT, text)
+        except Exception as e:
+            logger.error(e)
+            return None
+
+    def textToVoice(self, text):
+        try:
+            url = conf().get("linkai_api_base", "https://api.link-ai.tech") + "/v1/audio/speech"
+            headers = {"Authorization": "Bearer " + conf().get("linkai_api_key")}
+            # Gateway routes by `model` (tts-1 / doubao / baidu) + `voice` from
+            # that engine's catalog. `app_code` is optional workspace override.
+            data = {
+                "input": text,
+                "voice": conf().get("tts_voice_id"),
+                "app_code": conf().get("linkai_app_code"),
+            }
+            model = conf().get("text_to_voice_model")
+            if model:
+                data["model"] = model
+            res = requests.post(url, headers=headers, json=data, timeout=(5, 120))
+            if res.status_code != 200:
+                msg = ""
+                try:
+                    msg = res.json().get("message", "")
+                except Exception:
+                    pass
+                logger.error(f"[LinkVoice] textToVoice error, status_code={res.status_code}, msg={msg}")
+                return None
+            tmp_file_name = "tmp/" + datetime.datetime.now().strftime('%Y%m%d%H%M%S') + str(random.randint(0, 1000)) + ".mp3"
+            os.makedirs(os.path.dirname(tmp_file_name), exist_ok=True)
+            with open(tmp_file_name, 'wb') as f:
+                f.write(res.content)
+            logger.info(f"[LinkVoice] textToVoice success, input={text}, voice_id={data.get('voice')}")
+            return Reply(ReplyType.VOICE, tmp_file_name)
+        except Exception as e:
+            logger.error(e)
+            return None
diff --git a/voice/mimo/__init__.py b/voice/mimo/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/voice/mimo/mimo_voice.py b/voice/mimo/mimo_voice.py
new file mode 100644
index 0000000..2ae885f
--- /dev/null
+++ b/voice/mimo/mimo_voice.py
@@ -0,0 +1,109 @@
+# encoding:utf-8
+"""
+小米 MiMo TTS - 基于 mimo-v2.5-tts 模型的语音合成。
+
+通过 /chat/completions 接口实现：assistant 消息内容为待合成文本，
+audio 字段指定预置音色（如 冰糖/茉莉/苏打/Mia/Chloe 等），返回 base64
+编码的音频字节。
+
+文档：https://platform.xiaomimimo.com/docs/zh-CN/usage-guide/speech-synthesis-v2.5
+注意：MiMo 不提供 ASR 端点，因此 voiceToText 不实现。
+"""
+import base64
+import datetime
+import os
+import random
+
+import requests
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from voice.voice import Voice
+
+DEFAULT_API_BASE = "https://api.xiaomimimo.com/v1"
+DEFAULT_TTS_MODEL = "mimo-v2.5-tts"
+DEFAULT_TTS_VOICE = "冰糖"  # 默认音色：中国集群事实默认值
+REQUEST_TIMEOUT = (5, 120)
+
+
+class MimoVoice(Voice):
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file: str):
+        # MiMo 没有独立 ASR 端点；建议使用其他 provider（如 openai/zhipu/dashscope）
+        logger.warning("[MimoVoice] voiceToText is not supported by MiMo API")
+        return Reply(ReplyType.ERROR, "MiMo 暂不支持语音识别，请配置其他 voice_to_text provider")
+
+    def textToVoice(self, text: str):
+        try:
+            api_key = conf().get("mimo_api_key", "")
+            if not api_key:
+                logger.error("[MimoVoice] mimo_api_key is not configured")
+                return Reply(ReplyType.ERROR, "未配置 MiMo API key")
+
+            api_base = (conf().get("mimo_api_base") or DEFAULT_API_BASE).rstrip("/")
+            model = conf().get("text_to_voice_model") or DEFAULT_TTS_MODEL
+            voice_id = conf().get("tts_voice_id") or DEFAULT_TTS_VOICE
+
+            # 目标合成文本必须放在 assistant 消息；user 消息可选用作风格指令
+            payload = {
+                "model": model,
+                "messages": [
+                    {"role": "assistant", "content": text},
+                ],
+                "audio": {
+                    "format": "wav",
+                    "voice": voice_id,
+                },
+            }
+            headers = {
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            }
+            url = f"{api_base}/chat/completions"
+            response = requests.post(url, headers=headers, json=payload, timeout=REQUEST_TIMEOUT)
+
+            if response.status_code != 200:
+                logger.error(
+                    f"[MimoVoice] textToVoice failed: status={response.status_code} "
+                    f"body={response.text[:500]} model={model} voice={voice_id}"
+                )
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            data = response.json()
+            if "error" in data:
+                err = data["error"]
+                msg = err.get("message", str(err)) if isinstance(err, dict) else str(err)
+                logger.error(f"[MimoVoice] textToVoice api error: {msg}")
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            message = (data.get("choices") or [{}])[0].get("message", {}) or {}
+            audio_obj = message.get("audio") or {}
+            audio_b64 = audio_obj.get("data")
+            if not audio_b64:
+                logger.error(f"[MimoVoice] textToVoice empty audio in response: {data}")
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            try:
+                audio_bytes = base64.b64decode(audio_b64)
+            except Exception as e:
+                logger.error(f"[MimoVoice] base64 decode failed: {e}")
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            file_name = (
+                "tmp/" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+                + str(random.randint(0, 1000)) + ".wav"
+            )
+            os.makedirs(os.path.dirname(file_name), exist_ok=True)
+            with open(file_name, "wb") as f:
+                f.write(audio_bytes)
+            logger.info(
+                f"[MimoVoice] textToVoice model={model} voice={voice_id} "
+                f"file={file_name} bytes={len(audio_bytes)}"
+            )
+            return Reply(ReplyType.VOICE, file_name)
+        except Exception as e:
+            logger.exception(f"[MimoVoice] textToVoice exception: {e}")
+            return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
diff --git a/voice/minimax/__init__.py b/voice/minimax/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/voice/minimax/minimax_voice.py b/voice/minimax/minimax_voice.py
new file mode 100644
index 0000000..8456c47
--- /dev/null
+++ b/voice/minimax/minimax_voice.py
@@ -0,0 +1,110 @@
+# encoding:utf-8
+"""MiniMax TTS via /v1/t2a_v2 (SSE stream, hex-encoded mp3 chunks)."""
+import datetime
+import json
+import random
+import requests
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from voice.voice import Voice
+
+
+class MinimaxVoice(Voice):
+    def __init__(self):
+        self.api_key = conf().get("minimax_api_key")
+        # Mainland endpoint matches `sk-api-0-...` keys; override via
+        # `minimax_api_base` for international (api.minimax.io) workspaces.
+        self.api_base = (conf().get("minimax_api_base") or "https://api.minimaxi.com").rstrip("/")
+        if self.api_base.endswith("/v1"):
+            self.api_base = self.api_base[:-3]
+
+    def voiceToText(self, voice_file):
+        """MiniMax does not provide an ASR endpoint; raise NotImplementedError."""
+        raise NotImplementedError("MiniMax voice-to-text is not supported")
+
+    def textToVoice(self, text):
+        try:
+            model = conf().get("text_to_voice_model") or "speech-2.8-hd"
+            voice_id = conf().get("tts_voice_id") or "English_Graceful_Lady"
+
+            url = f"{self.api_base}/v1/t2a_v2"
+            headers = {
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {self.api_key}",
+            }
+            payload = {
+                "model": model,
+                "text": text,
+                "stream": True,
+                "voice_setting": {
+                    "voice_id": voice_id,
+                    "speed": 1,
+                    "vol": 1,
+                    "pitch": 0,
+                },
+                "audio_setting": {
+                    "sample_rate": 32000,
+                    "bitrate": 128000,
+                    "format": "mp3",
+                    "channel": 1,
+                },
+            }
+
+            response = requests.post(url, headers=headers, json=payload, stream=True, timeout=60)
+            response.raise_for_status()
+
+            # MiniMax returns HTTP 200 even on errors; capture base_resp for diagnostics.
+            audio_chunks = []
+            last_base_resp = None
+            event_count = 0
+            for raw in response.iter_lines():
+                if not raw:
+                    continue
+                event_count += 1
+                line = raw.decode("utf-8") if isinstance(raw, bytes) else raw
+                if not line.startswith("data:"):
+                    continue
+                json_str = line[5:].strip()
+                if not json_str or json_str == "[DONE]":
+                    continue
+                try:
+                    event_data = json.loads(json_str)
+                except Exception:
+                    continue
+                base_resp = event_data.get("base_resp") or {}
+                if base_resp:
+                    last_base_resp = base_resp
+                audio_hex = (event_data.get("data") or {}).get("audio")
+                if audio_hex:
+                    try:
+                        audio_chunks.append(bytes.fromhex(audio_hex))
+                    except Exception as e:
+                        logger.warning(f"[MINIMAX] skip bad audio hex chunk: {e}")
+
+            if not audio_chunks:
+                ct = response.headers.get("Content-Type", "")
+                if last_base_resp and last_base_resp.get("status_code") not in (None, 0):
+                    logger.error(
+                        f"[MINIMAX] TTS failed: status_code={last_base_resp.get('status_code')}, "
+                        f"status_msg={last_base_resp.get('status_msg')}, model={model}, voice_id={voice_id}"
+                    )
+                else:
+                    logger.error(
+                        f"[MINIMAX] TTS returned no audio data, model={model}, voice_id={voice_id}, "
+                        f"url={url}, http={response.status_code}, content_type={ct!r}, events={event_count}"
+                    )
+                return Reply(ReplyType.ERROR, "语音合成失败，未获取到音频数据")
+
+            audio_data = b"".join(audio_chunks)
+            file_name = "tmp/" + datetime.datetime.now().strftime("%Y%m%d%H%M%S") + str(random.randint(0, 1000)) + ".mp3"
+            with open(file_name, "wb") as f:
+                f.write(audio_data)
+
+            logger.info(f"[MINIMAX] textToVoice success, file={file_name}")
+            return Reply(ReplyType.VOICE, file_name)
+
+        except Exception as e:
+            logger.error(f"[MINIMAX] textToVoice error: {e}")
+            return Reply(ReplyType.ERROR, "遇到了一点小问题，请稍后再试")
diff --git a/voice/openai/openai_voice.py b/voice/openai/openai_voice.py
new file mode 100644
index 0000000..f0db53b
--- /dev/null
+++ b/voice/openai/openai_voice.py
@@ -0,0 +1,79 @@
+"""
+google voice service
+"""
+import json
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from voice.voice import Voice
+import requests
+from common import const
+import datetime, random
+
+class OpenaiVoice(Voice):
+    def __init__(self):
+        # No-op: this implementation calls OpenAI HTTP endpoints directly via
+        # `requests`, so it does not need a global SDK to be configured.
+        pass
+
+    def voiceToText(self, voice_file):
+        logger.debug("[Openai] voice file name={}".format(voice_file))
+        try:
+            file = open(voice_file, "rb")
+            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
+            url = f'{api_base}/audio/transcriptions'
+            headers = {
+                'Authorization': 'Bearer ' + conf().get("open_ai_api_key"),
+                # 'Content-Type': 'multipart/form-data' # 加了会报错，不知道什么原因
+            }
+            files = {
+                "file": file,
+            }
+            data = {
+                # Override via `voice_to_text_model` (e.g. fall back to whisper-1).
+                "model": conf().get("voice_to_text_model") or "gpt-4o-mini-transcribe",
+            }
+            response = requests.post(url, headers=headers, files=files, data=data)
+            response_data = response.json()
+            if response.status_code != 200 or "text" not in response_data:
+                logger.error(
+                    f"[Openai] voiceToText failed: status={response.status_code}, "
+                    f"resp={response_data}"
+                )
+                reply = Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+            else:
+                text = response_data["text"]
+                reply = Reply(ReplyType.TEXT, text)
+                logger.info("[Openai] voiceToText text={} voice file name={}".format(text, voice_file))
+        except Exception as e:
+            logger.error(f"[Openai] voiceToText exception: {e}", exc_info=True)
+            reply = Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+        finally:
+            return reply
+
+
+    def textToVoice(self, text):
+        try:
+            api_base = conf().get("open_ai_api_base") or "https://api.openai.com/v1"
+            url = f'{api_base}/audio/speech'
+            headers = {
+                'Authorization': 'Bearer ' + conf().get("open_ai_api_key"),
+                'Content-Type': 'application/json'
+            }
+            data = {
+                'model': conf().get("text_to_voice_model") or const.TTS_1,
+                'input': text,
+                'voice': conf().get("tts_voice_id") or "alloy"
+            }
+            response = requests.post(url, headers=headers, json=data)
+            file_name = "tmp/" + datetime.datetime.now().strftime('%Y%m%d%H%M%S') + str(random.randint(0, 1000)) + ".mp3"
+            logger.debug(f"[OPENAI] text_to_Voice file_name={file_name}, input={text}")
+            with open(file_name, 'wb') as f:
+                f.write(response.content)
+            logger.info(f"[OPENAI] text_to_Voice success")
+            reply = Reply(ReplyType.VOICE, file_name)
+        except Exception as e:
+            logger.error(e)
+            reply = Reply(ReplyType.ERROR, "遇到了一点小问题，请稍后再问我吧")
+        return reply
diff --git a/voice/pytts/pytts_voice.py b/voice/pytts/pytts_voice.py
new file mode 100644
index 0000000..bd70086
--- /dev/null
+++ b/voice/pytts/pytts_voice.py
@@ -0,0 +1,64 @@
+"""
+pytts voice service (offline)
+"""
+
+import os
+import sys
+import time
+
+import pyttsx3
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from voice.voice import Voice
+
+
+class PyttsVoice(Voice):
+    engine = pyttsx3.init()
+
+    def __init__(self):
+        # 语速
+        self.engine.setProperty("rate", 125)
+        # 音量
+        self.engine.setProperty("volume", 1.0)
+        if sys.platform == "win32":
+            for voice in self.engine.getProperty("voices"):
+                if "Chinese" in voice.name:
+                    self.engine.setProperty("voice", voice.id)
+        else:
+            self.engine.setProperty("voice", "zh")
+            # If the problem of espeak is fixed, using runAndWait() and remove this startLoop()
+            # TODO: check if this is work on win32
+            self.engine.startLoop(useDriverLoop=False)
+
+    def textToVoice(self, text):
+        try:
+            # Avoid the same filename under multithreading
+            wavFileName = "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".wav"
+            wavFile = TmpDir().path() + wavFileName
+            logger.info("[Pytts] textToVoice text={} voice file name={}".format(text, wavFile))
+
+            self.engine.save_to_file(text, wavFile)
+
+            if sys.platform == "win32":
+                self.engine.runAndWait()
+            else:
+                # In ubuntu, runAndWait do not really wait until the file created.
+                # It will return once the task queue is empty, but the task is still running in coroutine.
+                # And if you call runAndWait() and time.sleep() twice, it will stuck, so do not use this.
+                # If you want to fix this, add self._proxy.setBusy(True) in line 127 in espeak.py, at the beginning of the function save_to_file.
+                # self.engine.runAndWait()
+
+                # Before espeak fix this problem, we iterate the generator and control the waiting by ourself.
+                # But this is not the canonical way to use it, for example if the file already exists it also cannot wait.
+                self.engine.iterate()
+                while self.engine.isBusy() or wavFileName not in os.listdir(TmpDir().path()):
+                    time.sleep(0.1)
+
+            reply = Reply(ReplyType.VOICE, wavFile)
+
+        except Exception as e:
+            reply = Reply(ReplyType.ERROR, str(e))
+        finally:
+            return reply
diff --git a/voice/tencent/config.json.template b/voice/tencent/config.json.template
new file mode 100644
index 0000000..210d95f
--- /dev/null
+++ b/voice/tencent/config.json.template
@@ -0,0 +1,5 @@
+{
+    "voice_type": 1003,
+    "secret_id": "YOUR_SECRET_ID",
+    "secret_key": "YOUR_SECRET_KEY"
+}
diff --git a/voice/tencent/tencent_voice.py b/voice/tencent/tencent_voice.py
new file mode 100644
index 0000000..a02a9e1
--- /dev/null
+++ b/voice/tencent/tencent_voice.py
@@ -0,0 +1,119 @@
+import json
+import base64
+import os
+import time
+from voice.voice import Voice
+from common.log import logger
+from tencentcloud.common import credential
+from tencentcloud.asr.v20190614 import asr_client, models as asr_models
+from tencentcloud.tts.v20190823 import tts_client, models as tts_models
+from bridge.reply import Reply, ReplyType
+from common.tmp_dir import TmpDir
+
+class TencentVoice(Voice):
+    def __init__(self):
+        super().__init__()
+        self.secret_id = None
+        self.secret_key = None
+        self.voice_type = 1003
+        self._load_config()
+        
+    def _load_config(self):
+        """
+        从本地配置文件加载配置
+        """
+        try:
+            config_path = os.path.join(os.path.dirname(__file__), 'config.json')
+            with open(config_path, 'r') as f:
+                config = json.load(f)
+            self.secret_id = config.get('secret_id')
+            self.secret_key = config.get('secret_key')
+            self.voice_type = config.get('voice_type', self.voice_type)
+            if not self.secret_id or not self.secret_key:
+                logger.error("[Tencent] Missing credentials in config.json")
+        except Exception as e:
+            logger.error(f"[Tencent] Failed to load config: {e}")
+    
+    def setup(self, config):
+        """
+        设置配置信息（保留此方法用于向后兼容）
+        """
+        pass
+        
+    def voiceToText(self, voice_file):
+        """
+        将语音文件转换为文本
+        """
+        try:
+            # 实例化认证对象
+            cred = credential.Credential(self.secret_id, self.secret_key)
+            
+            # 实例化客户端
+            client = asr_client.AsrClient(cred, "ap-guangzhou")
+            
+            # 读取音频文件
+            with open(voice_file, 'rb') as f:
+                audio_data = f.read()
+            
+            # 进行base64编码
+            base64_audio = base64.b64encode(audio_data).decode('utf-8')
+            
+            # 构造请求对象
+            req = asr_models.SentenceRecognitionRequest()
+            req.ProjectId = 0
+            req.SubServiceType = 2
+            req.EngSerViceType = "16k_zh"
+            req.SourceType = 1
+            req.VoiceFormat = "wav"
+            req.UsrAudioKey = "voice_recognition"
+            req.Data = base64_audio
+            
+            # 发起请求
+            resp = client.SentenceRecognition(req)
+            
+            # 解析结果
+            if resp.Result:
+                logger.info("[Tencent] Voice to text success: {}".format(resp.Result))
+                return Reply(ReplyType.TEXT, resp.Result)
+            else:
+                logger.warning("[Tencent] Voice to text failed")
+                return Reply(ReplyType.ERROR, "腾讯语音识别失败")
+            
+        except Exception as e:
+            logger.error("[Tencent] Voice to text error: {}".format(e))
+            return Reply(ReplyType.ERROR, "腾讯语音识别出错：{}".format(str(e)))
+
+    def textToVoice(self, text):
+        """
+        将文本转换为语音
+        """
+        try:
+            cred = credential.Credential(self.secret_id, self.secret_key)
+            client = tts_client.TtsClient(cred, "ap-guangzhou")
+
+            req = tts_models.TextToVoiceRequest()
+            req.Text = text
+            req.SessionId = str(int(time.time()))
+            req.Volume = 5
+            req.Speed = 0
+            req.ProjectId = 0
+            req.ModelType = 1
+            req.PrimaryLanguage = 1
+            req.SampleRate = 16000
+            req.VoiceType = self.voice_type  # 客服女声
+
+            response = client.TextToVoice(req)
+            
+            if response.Audio:
+                fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+                with open(fileName, "wb") as f:
+                    f.write(base64.b64decode(response.Audio))
+                logger.info("[Tencent] textToVoice text={} voice file name={}".format(text, fileName))
+                return Reply(ReplyType.VOICE, fileName)
+            else:
+                logger.error("[Tencent] textToVoice failed")
+                return Reply(ReplyType.ERROR, "腾讯语音合成失败")
+
+        except Exception as e:
+            logger.error("[Tencent] Text to voice error: {}".format(e))
+            return Reply(ReplyType.ERROR, "腾讯语音合成出错：{}".format(str(e)))
diff --git a/voice/voice.py b/voice/voice.py
new file mode 100644
index 0000000..1ca199b
--- /dev/null
+++ b/voice/voice.py
@@ -0,0 +1,17 @@
+"""
+Voice service abstract class
+"""
+
+
+class Voice(object):
+    def voiceToText(self, voice_file):
+        """
+        Send voice to voice service and get text
+        """
+        raise NotImplementedError
+
+    def textToVoice(self, text):
+        """
+        Send text to voice service and get voice
+        """
+        raise NotImplementedError
diff --git a/voice/xunfei/config.json.template b/voice/xunfei/config.json.template
new file mode 100644
index 0000000..770160d
--- /dev/null
+++ b/voice/xunfei/config.json.template
@@ -0,0 +1,7 @@
+{
+  "APPID":"xxx71xxx",
+  "APIKey":"xxxx69058exxxxxx",
+  "APISecret":"xxxx697f0xxxxxx",
+  "BusinessArgsTTS":{"aue": "lame", "sfl": 1, "auf": "audio/L16;rate=16000", "vcn": "xiaoyan", "tte": "utf8"},
+  "BusinessArgsASR":{"domain": "iat", "language": "zh_cn", "accent": "mandarin", "vad_eos":10000, "dwa": "wpgs"}
+}
diff --git a/voice/xunfei/xunfei_asr.py b/voice/xunfei/xunfei_asr.py
new file mode 100644
index 0000000..2e81369
--- /dev/null
+++ b/voice/xunfei/xunfei_asr.py
@@ -0,0 +1,209 @@
+# -*- coding:utf-8 -*-
+#
+#  Author: njnuko 
+#  Email: njnuko@163.com 
+#
+#  这个文档是基于官方的demo来改的，固体官方demo文档请参考官网
+#
+#  语音听写流式 WebAPI 接口调用示例 接口文档（必看）：https://doc.xfyun.cn/rest_api/语音听写（流式版）.html
+#  webapi 听写服务参考帖子（必看）：http://bbs.xfyun.cn/forum.php?mod=viewthread&tid=38947&extra=
+#  语音听写流式WebAPI 服务，热词使用方式：登陆开放平台https://www.xfyun.cn/后，找到控制台--我的应用---语音听写（流式）---服务管理--个性化热词，
+#  设置热词
+#  注意：热词只能在识别的时候会增加热词的识别权重，需要注意的是增加相应词条的识别率，但并不是绝对的，具体效果以您测试为准。
+#  语音听写流式WebAPI 服务，方言试用方法：登陆开放平台https://www.xfyun.cn/后，找到控制台--我的应用---语音听写（流式）---服务管理--识别语种列表
+#  可添加语种或方言，添加后会显示该方言的参数值
+#  错误码链接：https://www.xfyun.cn/document/error-code （code返回错误码时必看）
+# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
+
+import websocket
+import datetime
+import hashlib
+import base64
+import hmac
+import json
+from urllib.parse import urlencode
+import time
+import ssl
+from wsgiref.handlers import format_date_time
+from datetime import datetime
+from time import mktime
+import _thread as thread
+import os
+import wave
+
+
+STATUS_FIRST_FRAME = 0  # 第一帧的标识
+STATUS_CONTINUE_FRAME = 1  # 中间帧标识
+STATUS_LAST_FRAME = 2  # 最后一帧的标识
+
+#############
+#whole_dict 是用来存储返回值的，由于带语音修正，所以用dict来存储，有更新的化pop之前的值，最后再合并
+global whole_dict
+#这个文档是官方文档改的，这个参数是用来做函数调用时用的
+global wsParam
+##############
+
+
+class Ws_Param(object):
+    # 初始化
+    def __init__(self, APPID, APIKey, APISecret,BusinessArgs, AudioFile):
+        self.APPID = APPID
+        self.APIKey = APIKey
+        self.APISecret = APISecret
+        self.AudioFile = AudioFile
+        self.BusinessArgs = BusinessArgs
+        # 公共参数(common)
+        self.CommonArgs = {"app_id": self.APPID}
+        # 业务参数(business)，更多个性化参数可在官网查看
+        #self.BusinessArgs = {"domain": "iat", "language": "zh_cn", "accent": "mandarin", "vinfo":1,"vad_eos":10000}
+
+    # 生成url
+    def create_url(self):
+        url = 'wss://ws-api.xfyun.cn/v2/iat'
+        # 生成RFC1123格式的时间戳
+        now = datetime.now()
+        date = format_date_time(mktime(now.timetuple()))
+
+        # 拼接字符串
+        signature_origin = "host: " + "ws-api.xfyun.cn" + "\n"
+        signature_origin += "date: " + date + "\n"
+        signature_origin += "GET " + "/v2/iat " + "HTTP/1.1"
+        # 进行hmac-sha256进行加密
+        signature_sha = hmac.new(self.APISecret.encode('utf-8'), signature_origin.encode('utf-8'),
+                                 digestmod=hashlib.sha256).digest()
+        signature_sha = base64.b64encode(signature_sha).decode(encoding='utf-8')
+
+        authorization_origin = "api_key=\"%s\", algorithm=\"%s\", headers=\"%s\", signature=\"%s\"" % (
+            self.APIKey, "hmac-sha256", "host date request-line", signature_sha)
+        authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')
+        # 将请求的鉴权参数组合为字典
+        v = {
+            "authorization": authorization,
+            "date": date,
+            "host": "ws-api.xfyun.cn"
+        }
+        # 拼接鉴权参数，生成url
+        url = url + '?' + urlencode(v)
+        #print("date: ",date)
+        #print("v: ",v)
+        # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致
+        #print('websocket url :', url)
+        return url
+
+
+# 收到websocket消息的处理
+def on_message(ws, message):
+    global whole_dict
+    try:
+        code = json.loads(message)["code"]
+        sid = json.loads(message)["sid"]
+        if code != 0:
+            errMsg = json.loads(message)["message"]
+            print("sid:%s call error:%s code is:%s" % (sid, errMsg, code))
+        else:
+            temp1 = json.loads(message)["data"]["result"]
+            data = json.loads(message)["data"]["result"]["ws"]
+            sn = temp1["sn"]
+            if "rg" in temp1.keys():
+                rep = temp1["rg"]
+                rep_start = rep[0]
+                rep_end = rep[1]
+                for sn in range(rep_start,rep_end+1):
+                    #print("before pop",whole_dict)
+                    #print("sn",sn)
+                    whole_dict.pop(sn,None)
+                    #print("after pop",whole_dict)
+                results = ""
+                for i in data:
+                    for w in i["cw"]:
+                        results += w["w"]
+                whole_dict[sn]=results
+                #print("after add",whole_dict)
+            else:
+                results = ""
+                for i in data:
+                    for w in i["cw"]:
+                        results += w["w"]
+                whole_dict[sn]=results
+            #print("sid:%s call success!,data is:%s" % (sid, json.dumps(data, ensure_ascii=False)))
+    except Exception as e:
+        print("receive msg,but parse exception:", e)
+
+
+
+# 收到websocket错误的处理
+def on_error(ws, error):
+    print("### error:", error)
+
+
+# 收到websocket关闭的处理
+def on_close(ws,a,b):
+    print("### closed ###")
+
+
+# 收到websocket连接建立的处理
+def on_open(ws):
+    global wsParam
+    def run(*args):
+        frameSize = 8000  # 每一帧的音频大小
+        intervel = 0.04  # 发送音频间隔(单位:s)
+        status = STATUS_FIRST_FRAME  # 音频的状态信息，标识音频是第一帧，还是中间帧、最后一帧
+
+        with wave.open(wsParam.AudioFile, "rb") as fp:
+            while True:
+                buf = fp.readframes(frameSize)
+                # 文件结束
+                if not buf:
+                    status = STATUS_LAST_FRAME
+                # 第一帧处理
+                # 发送第一帧音频，带business 参数
+                # appid 必须带上，只需第一帧发送
+                if status == STATUS_FIRST_FRAME:
+                    d = {"common": wsParam.CommonArgs,
+                         "business": wsParam.BusinessArgs,
+                         "data": {"status": 0, "format": "audio/L16;rate=16000","audio": str(base64.b64encode(buf), 'utf-8'), "encoding": "raw"}} 
+                    d = json.dumps(d)
+                    ws.send(d)
+                    status = STATUS_CONTINUE_FRAME
+                # 中间帧处理
+                elif status == STATUS_CONTINUE_FRAME:
+                    d = {"data": {"status": 1, "format": "audio/L16;rate=16000",
+                                  "audio": str(base64.b64encode(buf), 'utf-8'),
+                                  "encoding": "raw"}}
+                    ws.send(json.dumps(d))
+                # 最后一帧处理
+                elif status == STATUS_LAST_FRAME:
+                    d = {"data": {"status": 2, "format": "audio/L16;rate=16000",
+                                  "audio": str(base64.b64encode(buf), 'utf-8'),
+                                  "encoding": "raw"}}
+                    ws.send(json.dumps(d))
+                    time.sleep(1)
+                    break
+                # 模拟音频采样间隔
+                time.sleep(intervel)
+        ws.close()
+
+    thread.start_new_thread(run, ())
+
+#提供给xunfei_voice调用的函数
+def xunfei_asr(APPID,APISecret,APIKey,BusinessArgsASR,AudioFile):
+    global whole_dict
+    global wsParam
+    whole_dict = {}
+    wsParam1 = Ws_Param(APPID=APPID, APISecret=APISecret,
+                       APIKey=APIKey,BusinessArgs=BusinessArgsASR,
+                       AudioFile=AudioFile)
+    #wsParam是global变量，给上面on_open函数调用使用的
+    wsParam = wsParam1
+    websocket.enableTrace(False)
+    wsUrl = wsParam.create_url()
+    ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close)
+    ws.on_open = on_open
+    ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})
+    #把字典的值合并起来做最后识别的输出
+    whole_words = ""
+    for i in sorted(whole_dict.keys()):
+        whole_words += whole_dict[i]
+    return whole_words
+
+     
diff --git a/voice/xunfei/xunfei_tts.py b/voice/xunfei/xunfei_tts.py
new file mode 100644
index 0000000..33f934c
--- /dev/null
+++ b/voice/xunfei/xunfei_tts.py
@@ -0,0 +1,163 @@
+# -*- coding:utf-8 -*-
+#
+#  Author: njnuko
+#  Email: njnuko@163.com
+#
+#  这个文档是基于官方的demo来改的，固体官方demo文档请参考官网
+#
+#  语音听写流式 WebAPI 接口调用示例 接口文档（必看）：https://doc.xfyun.cn/rest_api/语音听写（流式版）.html
+#  webapi 听写服务参考帖子（必看）：http://bbs.xfyun.cn/forum.php?mod=viewthread&tid=38947&extra=
+#  语音听写流式WebAPI 服务，热词使用方式：登陆开放平台https://www.xfyun.cn/后，找到控制台--我的应用---语音听写（流式）---服务管理--个性化热词，
+#  设置热词
+#  注意：热词只能在识别的时候会增加热词的识别权重，需要注意的是增加相应词条的识别率，但并不是绝对的，具体效果以您测试为准。
+#  语音听写流式WebAPI 服务，方言试用方法：登陆开放平台https://www.xfyun.cn/后，找到控制台--我的应用---语音听写（流式）---服务管理--识别语种列表
+#  可添加语种或方言，添加后会显示该方言的参数值
+#  错误码链接：https://www.xfyun.cn/document/error-code （code返回错误码时必看）
+# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
+import websocket
+import datetime
+import hashlib
+import base64
+import hmac
+import json
+from urllib.parse import urlencode
+import time
+import ssl
+from wsgiref.handlers import format_date_time
+from datetime import datetime
+from time import mktime
+import _thread as thread
+import os
+
+
+
+STATUS_FIRST_FRAME = 0  # 第一帧的标识
+STATUS_CONTINUE_FRAME = 1  # 中间帧标识
+STATUS_LAST_FRAME = 2  # 最后一帧的标识
+
+#############
+#这个参数是用来做输出文件路径的
+global outfile
+#这个文档是官方文档改的，这个参数是用来做函数调用时用的
+global wsParam
+##############
+
+
+class Ws_Param(object):
+    # 初始化
+    def __init__(self, APPID, APIKey, APISecret,BusinessArgs,Text):
+        self.APPID = APPID
+        self.APIKey = APIKey
+        self.APISecret = APISecret
+        self.BusinessArgs = BusinessArgs
+        self.Text = Text
+
+        # 公共参数(common)
+        self.CommonArgs = {"app_id": self.APPID}
+        # 业务参数(business)，更多个性化参数可在官网查看
+        #self.BusinessArgs = {"aue": "raw", "auf": "audio/L16;rate=16000", "vcn": "xiaoyan", "tte": "utf8"}
+        self.Data = {"status": 2, "text": str(base64.b64encode(self.Text.encode('utf-8')), "UTF8")}
+        #使用小语种须使用以下方式，此处的unicode指的是 utf16小端的编码方式，即"UTF-16LE"”
+        #self.Data = {"status": 2, "text": str(base64.b64encode(self.Text.encode('utf-16')), "UTF8")}
+
+    # 生成url
+    def create_url(self):
+        url = 'wss://tts-api.xfyun.cn/v2/tts'
+        # 生成RFC1123格式的时间戳
+        now = datetime.now()
+        date = format_date_time(mktime(now.timetuple()))
+
+        # 拼接字符串
+        signature_origin = "host: " + "ws-api.xfyun.cn" + "\n"
+        signature_origin += "date: " + date + "\n"
+        signature_origin += "GET " + "/v2/tts " + "HTTP/1.1"
+        # 进行hmac-sha256进行加密
+        signature_sha = hmac.new(self.APISecret.encode('utf-8'), signature_origin.encode('utf-8'),
+                                 digestmod=hashlib.sha256).digest()
+        signature_sha = base64.b64encode(signature_sha).decode(encoding='utf-8')
+
+        authorization_origin = "api_key=\"%s\", algorithm=\"%s\", headers=\"%s\", signature=\"%s\"" % (
+            self.APIKey, "hmac-sha256", "host date request-line", signature_sha)
+        authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')
+        # 将请求的鉴权参数组合为字典
+        v = {
+            "authorization": authorization,
+            "date": date,
+            "host": "ws-api.xfyun.cn"
+        }
+        # 拼接鉴权参数，生成url
+        url = url + '?' + urlencode(v)
+        # print("date: ",date)
+        # print("v: ",v)
+        # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致
+        # print('websocket url :', url)
+        return url
+
+def on_message(ws, message):
+    #输出文件
+    global outfile
+    try:
+        message =json.loads(message)
+        code = message["code"]
+        sid = message["sid"]
+        audio = message["data"]["audio"]
+        audio = base64.b64decode(audio)
+        status = message["data"]["status"]
+        if status == 2:
+            print("ws is closed")
+            ws.close()
+        if code != 0:
+            errMsg = message["message"]
+            print("sid:%s call error:%s code is:%s" % (sid, errMsg, code))
+        else:
+
+            with open(outfile, 'ab') as f:
+                f.write(audio)
+
+    except Exception as e:
+        print("receive msg,but parse exception:", e)
+
+
+
+# 收到websocket连接建立的处理
+def on_open(ws):
+    global outfile
+    global wsParam
+    def run(*args):
+        d = {"common": wsParam.CommonArgs,
+             "business": wsParam.BusinessArgs,
+             "data": wsParam.Data,
+             }
+        d = json.dumps(d)
+        # print("------>开始发送文本数据")
+        ws.send(d)
+        if os.path.exists(outfile):
+            os.remove(outfile)
+
+    thread.start_new_thread(run, ())
+
+# 收到websocket错误的处理
+def on_error(ws, error):
+    print("### error:", error)
+
+
+
+# 收到websocket关闭的处理
+def on_close(ws):
+    print("### closed ###")
+
+
+
+def xunfei_tts(APPID, APIKey, APISecret,BusinessArgsTTS, Text, OutFile):
+    global outfile
+    global wsParam 
+    outfile = OutFile
+    wsParam1 = Ws_Param(APPID,APIKey,APISecret,BusinessArgsTTS,Text)
+    wsParam = wsParam1
+    websocket.enableTrace(False)
+    wsUrl = wsParam.create_url()
+    ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close)
+    ws.on_open = on_open
+    ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})
+    return outfile
+     
diff --git a/voice/xunfei/xunfei_voice.py b/voice/xunfei/xunfei_voice.py
new file mode 100644
index 0000000..6ce54e7
--- /dev/null
+++ b/voice/xunfei/xunfei_voice.py
@@ -0,0 +1,92 @@
+#####################################################################
+#    xunfei voice service
+#     Auth: njnuko
+#     Email: njnuko@163.com
+#
+#    要使用本模块, 首先到 xfyun.cn 注册一个开发者账号,
+#    之后创建一个新应用, 然后在应用管理的语音识别或者语音合同右边可以查看APPID API Key 和 Secret Key
+#    然后在 config.json 中填入这三个值
+#
+#    配置说明：
+# {
+#  "APPID":"xxx71xxx",
+#  "APIKey":"xxxx69058exxxxxx",  #讯飞xfyun.cn控制台语音合成或者听写界面的APIKey
+#  "APISecret":"xxxx697f0xxxxxx",  #讯飞xfyun.cn控制台语音合成或者听写界面的APIKey
+#  "BusinessArgsTTS":{"aue": "lame", "sfl": 1, "auf": "audio/L16;rate=16000", "vcn": "xiaoyan", "tte": "utf8"}, #语音合成的参数，具体可以参考xfyun.cn的文档
+#  "BusinessArgsASR":{"domain": "iat", "language": "zh_cn", "accent": "mandarin", "vad_eos":10000, "dwa": "wpgs"}  #语音听写的参数，具体可以参考xfyun.cn的文档
+# }
+#####################################################################
+
+import json
+import os
+import time
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from common.tmp_dir import TmpDir
+from config import conf
+from voice.voice import Voice
+from .xunfei_asr import xunfei_asr
+from .xunfei_tts import xunfei_tts
+import shutil
+
+try:
+    from voice.audio_convert import any_to_mp3
+    from pydub import AudioSegment
+    _audio_available = True
+except ImportError as e:
+    logger.debug("import audio libraries failed: {}".format(e))
+    _audio_available = False
+
+
+class XunfeiVoice(Voice):
+    def __init__(self):
+        try:
+            curdir = os.path.dirname(__file__)
+            config_path = os.path.join(curdir, "config.json")
+            conf = None
+            with open(config_path, "r") as fr:
+                conf = json.load(fr)
+            print(conf)
+            self.APPID = str(conf.get("APPID"))
+            self.APIKey = str(conf.get("APIKey"))
+            self.APISecret = str(conf.get("APISecret"))
+            self.BusinessArgsTTS = conf.get("BusinessArgsTTS")
+            self.BusinessArgsASR= conf.get("BusinessArgsASR")
+
+        except Exception as e:
+            logger.warn("XunfeiVoice init failed: %s, ignore " % e)
+
+    def voiceToText(self, voice_file):
+        # 识别本地文件
+        try:
+            logger.debug("[Xunfei] voice file name={}".format(voice_file))
+            #print("voice_file===========",voice_file)
+            #print("voice_file_type===========",type(voice_file))
+            #mp3_name, file_extension = os.path.splitext(voice_file)
+            #mp3_file = mp3_name + ".mp3"
+            #pcm_data=get_pcm_from_wav(voice_file)
+            #mp3_name, file_extension = os.path.splitext(voice_file)
+            #AudioSegment.from_wav(voice_file).export(mp3_file, format="mp3")
+            #shutil.copy2(voice_file, 'tmp/test1.wav')
+            #shutil.copy2(mp3_file, 'tmp/test1.mp3')
+            #print("voice and mp3 file",voice_file,mp3_file)
+            text = xunfei_asr(self.APPID,self.APISecret,self.APIKey,self.BusinessArgsASR,voice_file)
+            logger.info("讯飞语音识别到了: {}".format(text))
+            reply = Reply(ReplyType.TEXT, text)
+        except Exception as e:
+            logger.warn("XunfeiVoice init failed: %s, ignore " % e)
+            reply = Reply(ReplyType.ERROR, "讯飞语音识别出错了；{0}")
+        return reply
+
+    def textToVoice(self, text):
+        try:
+            # Avoid the same filename under multithreading
+            fileName = TmpDir().path() + "reply-" + str(int(time.time())) + "-" + str(hash(text) & 0x7FFFFFFF) + ".mp3"
+            return_file = xunfei_tts(self.APPID,self.APIKey,self.APISecret,self.BusinessArgsTTS,text,fileName)
+            logger.info("[Xunfei] textToVoice text={} voice file name={}".format(text, fileName))
+            reply = Reply(ReplyType.VOICE, fileName)
+        except Exception as e:
+            logger.error("[Xunfei] textToVoice error={}".format(fileName))
+            reply = Reply(ReplyType.ERROR, "抱歉，讯飞语音合成失败")
+        return reply
diff --git a/voice/zhipuai/__init__.py b/voice/zhipuai/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/voice/zhipuai/zhipuai_voice.py b/voice/zhipuai/zhipuai_voice.py
new file mode 100644
index 0000000..1fdcdc7
--- /dev/null
+++ b/voice/zhipuai/zhipuai_voice.py
@@ -0,0 +1,173 @@
+# encoding:utf-8
+"""ZhipuAI voice: glm-asr-2512 (ASR) + glm-tts (TTS) via BigModel REST API."""
+import datetime
+import os
+import random
+
+import requests
+
+from bridge.reply import Reply, ReplyType
+from common.log import logger
+from config import conf
+from voice import audio_convert
+from voice.voice import Voice
+
+
+DEFAULT_ASR_MODEL = "glm-asr-2512"
+DEFAULT_TTS_MODEL = "glm-tts"
+DEFAULT_TTS_VOICE = "tongtong"
+DEFAULT_API_BASE = "https://open.bigmodel.cn/api/paas/v4"
+MAX_FILE_BYTES = 25 * 1024 * 1024
+REQUEST_TIMEOUT = (5, 60)
+
+
+class ZhipuAIVoice(Voice):
+    def __init__(self):
+        pass
+
+    def voiceToText(self, voice_file: str):
+        try:
+            voice_file = self._ensure_compatible_format(voice_file)
+
+            try:
+                size = os.path.getsize(voice_file)
+                if size > MAX_FILE_BYTES:
+                    logger.warning(
+                        f"[ZhipuAIVoice] audio file {size}B exceeds {MAX_FILE_BYTES}B; "
+                        f"glm-asr-2512 may reject it"
+                    )
+            except OSError:
+                pass
+
+            api_key = conf().get("zhipu_ai_api_key", "")
+            if not api_key:
+                logger.error("[ZhipuAIVoice] zhipu_ai_api_key is not configured")
+                return Reply(ReplyType.ERROR, "未配置 ZhipuAI API key")
+
+            api_base = (conf().get("zhipu_ai_api_base") or DEFAULT_API_BASE).rstrip("/")
+            url = f"{api_base}/audio/transcriptions"
+            model = conf().get("voice_to_text_model") or DEFAULT_ASR_MODEL
+
+            with open(voice_file, "rb") as f:
+                files = {"file": (os.path.basename(voice_file), f)}
+                data = {"model": model, "stream": "false"}
+                headers = {"Authorization": f"Bearer {api_key}"}
+                response = requests.post(
+                    url, headers=headers, files=files, data=data, timeout=REQUEST_TIMEOUT
+                )
+
+            if response.status_code != 200:
+                logger.error(
+                    f"[ZhipuAIVoice] voiceToText failed: status={response.status_code} "
+                    f"body={response.text[:500]}"
+                )
+                return Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+
+            payload = response.json()
+            text = (payload.get("text") or "").strip()
+            if not text:
+                logger.error(f"[ZhipuAIVoice] voiceToText empty text: {payload}")
+                return Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+
+            logger.info(f"[ZhipuAIVoice] voiceToText model={model} text={text}")
+            return Reply(ReplyType.TEXT, text)
+        except Exception as e:
+            logger.exception(f"[ZhipuAIVoice] voiceToText exception: {e}")
+            return Reply(ReplyType.ERROR, "我暂时还无法听清您的语音，请稍后再试吧~")
+
+    def textToVoice(self, text: str):
+        try:
+            api_key = conf().get("zhipu_ai_api_key", "")
+            if not api_key:
+                logger.error("[ZhipuAIVoice] zhipu_ai_api_key is not configured")
+                return Reply(ReplyType.ERROR, "未配置 ZhipuAI API key")
+
+            api_base = (conf().get("zhipu_ai_api_base") or DEFAULT_API_BASE).rstrip("/")
+            url = f"{api_base}/audio/speech"
+            model = conf().get("text_to_voice_model") or DEFAULT_TTS_MODEL
+            voice_id = conf().get("tts_voice_id") or DEFAULT_TTS_VOICE
+
+            payload = {
+                "model": model,
+                "input": text,
+                "voice": voice_id,
+                "response_format": "wav",
+                "speed": 1.0,
+                "volume": 1.0,
+            }
+            headers = {
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            }
+            response = requests.post(
+                url, headers=headers, json=payload, timeout=REQUEST_TIMEOUT
+            )
+
+            if response.status_code != 200:
+                logger.error(
+                    f"[ZhipuAIVoice] textToVoice failed: status={response.status_code} "
+                    f"body={response.text[:500]} model={model} voice={voice_id}"
+                )
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            # Some errors come back as JSON / SSE with HTTP 200.
+            ct = response.headers.get("Content-Type", "")
+            if "application/json" in ct or "text/event-stream" in ct:
+                try:
+                    err = response.json()
+                except Exception:
+                    err = {"raw": response.text[:500]}
+                logger.error(
+                    f"[ZhipuAIVoice] textToVoice unexpected text response "
+                    f"(content_type={ct}): {err}"
+                )
+                return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+            audio_bytes = response.content
+            ext = self._sniff_audio_ext(audio_bytes) or "wav"
+
+            file_name = (
+                "tmp/" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+                + str(random.randint(0, 1000)) + "." + ext
+            )
+            os.makedirs(os.path.dirname(file_name), exist_ok=True)
+            with open(file_name, "wb") as f:
+                f.write(audio_bytes)
+            logger.info(
+                f"[ZhipuAIVoice] textToVoice model={model} voice={voice_id} "
+                f"file={file_name} bytes={len(audio_bytes)} ext={ext}"
+            )
+            return Reply(ReplyType.VOICE, file_name)
+        except Exception as e:
+            logger.exception(f"[ZhipuAIVoice] textToVoice exception: {e}")
+            return Reply(ReplyType.ERROR, "语音合成失败，请稍后再试")
+
+    @staticmethod
+    def _sniff_audio_ext(data: bytes) -> str:
+        """Detect audio container by magic bytes; returns '' on unknown."""
+        if len(data) < 12:
+            return ""
+        head = data[:12]
+        if head[:4] == b"RIFF" and head[8:12] == b"WAVE":
+            return "wav"
+        if head[:3] == b"ID3" or head[:2] == b"\xff\xfb" or head[:2] == b"\xff\xf3" or head[:2] == b"\xff\xf2":
+            return "mp3"
+        if head[:4] == b"OggS":
+            return "ogg"
+        if head[:4] == b"fLaC":
+            return "flac"
+        return ""
+
+    @staticmethod
+    def _ensure_compatible_format(voice_file: str) -> str:
+        # glm-asr-2512 only accepts .wav / .mp3
+        lower = voice_file.lower()
+        if lower.endswith(".mp3") or lower.endswith(".wav"):
+            return voice_file
+        try:
+            mp3_file = os.path.splitext(voice_file)[0] + ".mp3"
+            audio_convert.any_to_mp3(voice_file, mp3_file)
+            return mp3_file
+        except Exception as e:
+            logger.warning(f"[ZhipuAIVoice] mp3 convert failed: {e}")
+            return voice_file