docs: make Chinese README the default

README.md

@@ -1,4 +1,10 @@
-<a href="https://www.surfsense.com/"><img width="1584" height="396" alt="SurfSense, the open-source competitive intelligence platform for AI agents" src="https://github.com/user-attachments/assets/9361ef58-1753-4b6e-b275-5020d8847261" /></a>
+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/MODSetter/SurfSense) · [上游 README](https://github.com/MODSetter/SurfSense/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
+<a href="https://www.surfsense.com/"><img width="1584" height="396" alt="SurfSense，面向 AI 智能体的开源竞争情报平台" src="https://github.com/user-attachments/assets/9361ef58-1753-4b6e-b275-5020d8847261" /></a>
 
 
 
@@ -20,101 +26,101 @@
 <a href="https://trendshift.io/repositories/13606" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13606" alt="MODSetter%2FSurfSense | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 </div>
 
-# SurfSense: Give Your AI Agents Competitive Intelligence
+# SurfSense：为你的 AI 智能体注入竞争情报能力
 
-SurfSense is the **open-source competitive intelligence platform for AI agents**. Your agents monitor competitors, track rankings, and listen to your market with live data from **Reddit, YouTube, Google Maps, Google Search, and the open web**, through one **REST API** or **MCP server**. Scheduled and event-triggered agents turn what they find into briefs and alerts, and a built-in knowledge base keeps every finding searchable with citations.
+SurfSense 是**面向 AI 智能体的开源竞争情报平台**。你的智能体可以通过一个 **REST API** 或 **MCP 服务器**，利用来自 **Reddit、YouTube、Google Maps、Google Search 和开放网络**的实时数据，监控竞争对手、追踪排名、倾听市场动态。定时和事件触发的智能体会把发现的内容转化为简报和预警，内置的知识库则让每一条发现都可搜索、可引用。
 
 > [!NOTE]
-> **📢 A note for our NotebookLM-alternative users**
+> **📢 致我们的 NotebookLM 替代品用户**
 >
-> For the past couple of months we built SurfSense as the best general research agent for your own knowledge, and that chapter earned us a community we are genuinely proud of. Agentic tools like Claude, OpenCode, Hermes, and OpenClaw have now proven that agents are the future, and general research is becoming something every capable agent does out of the box. What agents still lack is **live market data and the workflows around it**, so that is where we are pointing all of our energy: becoming the definitive open-source competitive intelligence agent platform.
+> 在过去几个月里，我们把 SurfSense 打造成了针对个人知识的最佳通用研究智能体，这段旅程为我们赢得了一个令我们由衷自豪的社区。如今，Claude、OpenCode、Hermes、OpenClaw 等智能体工具已经证明智能体就是未来，通用研究正在成为每个有能力的智能体开箱即用的功能。而智能体仍然缺少的是**实时市场数据以及围绕它的工作流**，所以这正是我们全力投入的方向：成为标杆级的开源竞争情报智能体平台。
 >
-> **Nothing you rely on is going away.** Your knowledge base, chat with citations, reports, podcasts, presentations, automations, and collaborative chats all keep working, and self-hosting stays free and open source. Read the full announcement on [our changelog](https://www.surfsense.com/changelog).
+> **你所依赖的一切功能都不会消失。**你的知识库、带引用的对话、报告、播客、演示文稿、自动化以及协作聊天都会继续可用，自托管也依然免费且开源。完整公告请阅读[我们的更新日志](https://www.surfsense.com/changelog)。
 
-## Table of contents
+## 目录
 
-- [Why agents need SurfSense](#why-agents-need-surfsense)
-- [What can you do with SurfSense?](#what-can-you-do-with-surfsense)
-- [Live data connectors](#live-data-connectors)
-- [Quick start](#quick-start)
-- [Everything else in the box](#everything-else-in-the-box)
-- [SurfSense vs Google NotebookLM](#surfsense-vs-google-notebooklm)
-- [Roadmap](#roadmap)
-- [Contribute](#contribute)
+- [为什么智能体需要 SurfSense](#为什么智能体需要-surfsense)
+- [你可以用 SurfSense 做什么？](#你可以用-surfsense-做什么)
+- [实时数据连接器](#实时数据连接器)
+- [快速开始](#快速开始)
+- [开箱即用的其他能力](#开箱即用的其他能力)
+- [SurfSense 对比 Google NotebookLM](#surfsense-对比-google-notebooklm)
+- [路线图](#路线图)
+- [参与贡献](#参与贡献)
 
-## Why agents need SurfSense
+## 为什么智能体需要 SurfSense
 
-Ask any capable agent "what are competitors charging this week?" or "what is Reddit saying about us since the launch?" and it has nowhere trustworthy to look. Official platform APIs are rate-limited, priced for enterprises, or missing entirely, and scraping plumbing is brittle. SurfSense closes that gap:
+问任何一个有能力的智能体"竞争对手这周的定价是多少？"或者"自发布以来 Reddit 上对我们的评价如何？"，它都找不到可信赖的数据来源。官方平台 API 要么有速率限制，要么按企业级定价，要么根本不存在，而自建抓取管线又非常脆弱。SurfSense 正是为填补这一空白而生：
 
-- **Platform-native connectors**, each a typed REST endpoint returning structured JSON. No rate-limit roulette, no HTML parsing.
-- **An MCP server** that exposes every connector as a native tool (`surfsense_reddit_scrape`, `surfsense_google_search`, and more) to Claude, Cursor, or any agent framework.
-- **An agent harness**, not just raw data: retries, structured output, and credit metering are built in, so agents go from a question to a brief without you building the plumbing.
-- **Open source and self-hostable**, so your competitive research stays on your own infrastructure.
+- **平台原生连接器**，每个都是返回结构化 JSON 的强类型 REST 端点。不用赌速率限制，也不用解析 HTML。
+- **一个 MCP 服务器**，把每个连接器都作为原生工具（`surfsense_reddit_scrape`、`surfsense_google_search` 等）暴露给 Claude、Cursor 或任何智能体框架。
+- **一套智能体运行框架**，而不只是原始数据：重试、结构化输出和额度计量都已内置，智能体可以从一个问题直达一份简报，无需你自己搭建管线。
+- **开源且可自托管**，你的竞争研究数据始终留在你自己的基础设施上。
 
-## What can you do with SurfSense?
+## 你可以用 SurfSense 做什么？
 
-Every use case below is a real task the SurfSense agent runs end-to-end today, in one prompt or on a schedule.
+下面的每个用例都是 SurfSense 智能体如今能够端到端完成的真实任务，一条提示语或一个定时计划即可触发。
 
-### Multi-connector workflows
+### 多连接器工作流
 
-Chain several connectors in a single agent run and get one cited brief back.
+在一次智能体运行中串联多个连接器，最终得到一份带引用的简报。
 
-- **Launch impact, across every platform** — "Our competitor launched v2 yesterday. Measure the reaction across search, Reddit, and YouTube." The agent scrapes SERPs, Reddit threads, and YouTube comments, then merges all three signals into one launch-impact brief.
-- **Local competitor teardown** — Google Maps finds the players, the web crawler reads their pricing pages, and Google Search shows who wins the query, in one run.
-- **Competitor 360, on a schedule** — an automation chains four connectors every week: site changes, rank movements, Reddit sentiment, and YouTube reaction.
+- **发布影响力分析，覆盖所有平台** — "我们的竞争对手昨天发布了 v2。评估搜索、Reddit 和 YouTube 上的反应。"智能体会抓取搜索结果页、Reddit 帖子和 YouTube 评论，然后把三路信号汇总成一份发布影响力简报。
+- **本地竞争对手拆解** — Google Maps 找到本地玩家，网页爬虫读取他们的定价页面，Google Search 展示谁在搜索中胜出，全部在一次运行中完成。
+- **定时执行的竞争对手 360 全景** — 一条自动化每周串联四个连接器：网站变更、排名变动、Reddit 舆情和 YouTube 反应。
 
-### Competitor monitoring
+### 竞争对手监控
 
-- **Pricing watch** — extract every plan, price, and limit from competitors' pricing pages into one table, then re-check daily and alert on any change.
-- **Product & changelog tracking** — crawl rivals' changelog, product, and careers pages every Monday and get a brief on what they shipped.
-- **Rank & ad monitoring** — track the Google rankings, paid ads, and AI Overview citations your market actually sees, and flag movements day over day.
+- **定价监控** — 从竞争对手的定价页面提取每个套餐、价格和限制，汇总到一张表格，然后每天复查，任何变动即时预警。
+- **产品与更新日志追踪** — 每周一爬取对手的更新日志、产品页和招聘页面，收到一份他们发布了什么的简报。
+- **排名与广告监控** — 追踪你的市场真正看到的 Google 排名、付费广告和 AI Overview 引用，并逐日标记变动。
 
-### B2B lead generation
+### B2B 潜在客户开发
 
-- **Local business leads** — turn a category and a territory ("burger places in San Jose") into a lead list with phones, websites, ratings, and decision-maker contacts pulled from their sites.
-- **Team rosters & contacts** — spider any company site and pull the full team with emails, socials, and source provenance, exported to CSV.
-- **Portfolio & market mapping** — map an investor's portfolio or a whole category, then enrich every company with pricing and contacts.
+- **本地商户线索** — 把一个品类加一个地区（"圣何塞的汉堡店"）变成一份线索清单，包含电话、网站、评分，以及从他们网站上提取的决策人联系方式。
+- **团队名录与联系方式** — 爬取任意公司网站，提取完整团队名单，附带邮箱、社交账号和数据来源，导出为 CSV。
+- **投资组合与市场地图** — 绘制一家投资机构的投资组合或整个品类的全景图，再为每家公司补充定价和联系方式。
 
-### Brand & market listening
+### 品牌与市场舆情监听
 
-- **Reddit brand monitoring** — hear what your market says about you, your competitors, and your category in the threads where buyers speak candidly.
-- **YouTube audience sentiment** — pull videos, transcripts, and comments at scale, then cluster what audiences praise and complain about.
-- **Switcher & intent mining** — find the people actively asking for an alternative to a competitor, ranked by how ready they are to move.
+- **Reddit 品牌监控** — 在买家坦诚发言的帖子里，倾听你的市场对你、你的竞争对手和你所在品类的真实评价。
+- **YouTube 观众情绪分析** — 大规模拉取视频、字幕转录和评论，然后聚类分析观众在称赞什么、抱怨什么。
+- **换用意向挖掘** — 找到正在积极寻找某竞争对手替代品的人群，并按他们的换用意愿排序。
 
-### Market research
+### 市场调研
 
-- **Deep research on the live web** — the agent crawls dozens of live sources on a question and synthesizes a cited answer, not a stale index.
-- **AI Overview & GEO tracking** — capture when Google's AI Overviews answer your market's queries, and exactly which sources they cite.
-- **Cited briefs & alerts** — everything the agents gather lands in your workspace as briefs and alerts with sources you can check.
+- **实时网络深度研究** — 智能体针对一个问题爬取数十个实时来源，并综合出一份带引用的答案，而不是过时的索引。
+- **AI Overview 与 GEO 追踪** — 捕捉 Google 的 AI Overviews 何时回答了你市场的搜索，以及它们究竟引用了哪些来源。
+- **带引用的简报与预警** — 智能体收集到的一切都会以简报和预警的形式汇入你的工作区，每条结论都附带可核查的来源。
 
-### Automate any of it, no code
+### 把以上任何任务自动化，无需代码
 
-Automations run full agent turns on a schedule or in response to events, then write results back to Notion, Slack, Linear, and Jira. Describe the workflow in plain English and SurfSense builds it. Try prompts like:
+自动化功能可以按计划或响应事件运行完整的智能体回合，然后把结果写回 Notion、Slack、Linear 和 Jira。用自然语言描述工作流，SurfSense 就会替你构建。可以试试这些提示语：
 
-- "Watch our top 3 competitors' pricing pages and alert me in Slack when a plan or price changes."
-- "Track every mention of our brand on Reddit and YouTube and send me a daily digest."
-- "Monitor our Google ranking for our top 10 keywords and flag drops week over week."
-- "Pull new Google Maps reviews for our locations and our competitors' every Monday."
-- "Run a monthly competitor analysis report and save it to my workspace."
+- "盯住我们前 3 名竞争对手的定价页面，一旦套餐或价格变动就在 Slack 上提醒我。"
+- "追踪 Reddit 和 YouTube 上对我们品牌的每一次提及，每天给我发一份摘要。"
+- "监控我们前 10 个关键词的 Google 排名，按周标记下滑情况。"
+- "每周一拉取我们门店以及竞争对手门店的最新 Google Maps 评论。"
+- "每月生成一份竞争对手分析报告并保存到我的工作区。"
 
-## Live data connectors
+## 实时数据连接器
 
-| Connector | What your agents get | Learn more |
+| 连接器 | 你的智能体能获得什么 | 了解更多 |
 |---|---|---|
-| **Reddit** | Posts, comments, and subreddit streams without the official API's rate limits | [Reddit Scraper API](https://www.surfsense.com/reddit) |
-| **YouTube** | Videos, transcripts, and comment threads for brand and product listening | [YouTube Scraper API](https://www.surfsense.com/youtube) |
-| **Google Maps** | Places, ratings, and reviews for local competitor and lead research | [Google Maps Scraper API](https://www.surfsense.com/google-maps) |
-| **Google Search** | Live SERPs for rank tracking and market monitoring | [Google Search API](https://www.surfsense.com/google-search) |
-| **Web Crawl** | Any page on the open web as clean, structured content | [Web Crawling API](https://www.surfsense.com/web-crawl) |
-| **External MCP Connectors** | Bring any MCP server to your agents, with one-click OAuth for Notion, Slack, Jira, and more | [External MCP Connectors](https://www.surfsense.com/external-mcp-connectors) |
+| **Reddit** | 帖子、评论和子版块信息流，不受官方 API 速率限制 | [Reddit Scraper API](https://www.surfsense.com/reddit) |
+| **YouTube** | 视频、字幕转录和评论串，用于品牌和产品舆情监听 | [YouTube Scraper API](https://www.surfsense.com/youtube) |
+| **Google Maps** | 地点、评分和评论，用于本地竞争对手和潜在客户调研 | [Google Maps Scraper API](https://www.surfsense.com/google-maps) |
+| **Google Search** | 实时搜索结果页，用于排名追踪和市场监控 | [Google Search API](https://www.surfsense.com/google-search) |
+| **Web Crawl** | 把开放网络上的任意页面转为干净、结构化的内容 | [Web Crawling API](https://www.surfsense.com/web-crawl) |
+| **外部 MCP 连接器** | 将任意 MCP 服务器接入你的智能体，Notion、Slack、Jira 等支持一键 OAuth | [External MCP Connectors](https://www.surfsense.com/external-mcp-connectors) |
 
-Billing is pay as you go: connectors bill per item actually returned, crawls per page successfully fetched, and failed calls are never billed. Self-hosted installs run with billing off. See [pricing](https://www.surfsense.com/pricing).
+计费采用按量付费：连接器按实际返回的条目计费，爬取按成功抓取的页面计费，失败的调用永不计费。自托管部署默认关闭计费。详见[定价](https://www.surfsense.com/pricing)。
 
-## Quick start
+## 快速开始
 
-### Call a connector from code
+### 在代码中调用连接器
 
-Every connector is a REST endpoint you can call from any language with your SurfSense API key:
+每个连接器都是一个 REST 端点，你可以用任何语言、凭借你的 SurfSense API 密钥来调用：
 
 ```bash
 curl -X POST "$SURFSENSE_API_URL/workspaces/$WORKSPACE_ID/scrapers/reddit/scrape" \
@@ -128,11 +134,11 @@ curl -X POST "$SURFSENSE_API_URL/workspaces/$WORKSPACE_ID/scrapers/reddit/scrape
   }'
 ```
 
-Each [connector page](https://www.surfsense.com/connectors) has copy-paste examples in Python, JavaScript, Go, PHP, Ruby, Java, and C#.
+每个[连接器页面](https://www.surfsense.com/connectors)都提供 Python、JavaScript、Go、PHP、Ruby、Java 和 C# 的可直接复制粘贴的示例。
 
-### Give the tools to your agents over MCP
+### 通过 MCP 把工具交给你的智能体
 
-Add the SurfSense MCP server to Claude, Cursor, or your own agent framework:
+把 SurfSense MCP 服务器添加到 Claude、Cursor 或你自己的智能体框架：
 
 ```json
 {
@@ -145,152 +151,153 @@ Add the SurfSense MCP server to Claude, Cursor, or your own agent framework:
 }
 ```
 
-Your agent can now call every connector as a native tool. See the [SurfSense MCP server](https://www.surfsense.com/mcp-server) page for the full tool list, or run the server locally from [`surfsense_mcp`](./surfsense_mcp).
+现在，你的智能体就可以把每个连接器当作原生工具来调用。完整工具列表请查看 [SurfSense MCP 服务器](https://www.surfsense.com/mcp-server) 页面，也可以通过 [`surfsense_mcp`](./surfsense_mcp) 在本地运行该服务器。
 
-### Use the cloud
+### 使用云端服务
 
-Go to [surfsense.com](https://www.surfsense.com), log in, and ask the agent for live market data in plain English. New accounts start with $5 of free credit and no subscription.
+访问 [surfsense.com](https://www.surfsense.com)，登录后用自然语言向智能体索取实时市场数据。新账户自带 5 美元免费额度，无需订阅。
 
-### Self-host for free
 
-Run the entire platform, connectors, agents, automations, and the MCP server on your own infrastructure. Self-hosted installs ship with billing off, so scraping, crawling, and agent runs are limited only by your hardware and the model keys you bring.
+### 免费自托管
 
-**Prerequisites:** [Docker Desktop](https://www.docker.com/products/docker-desktop/) must be installed and running.
+在你自己的基础设施上运行整个平台，包括连接器、智能体、自动化和 MCP 服务器。自托管部署默认关闭计费，抓取、爬取和智能体运行只受你的硬件和你自带的模型密钥限制。
 
-For Linux/macOS:
+**前置条件：**必须已安装并运行 [Docker Desktop](https://www.docker.com/products/docker-desktop/)。
+
+Linux/macOS：
 
 ```bash
 curl -fsSL https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.sh | bash
 ```
 
-For Windows:
+Windows：
 
 ```bash
 irm https://raw.githubusercontent.com/MODSetter/SurfSense/main/docker/scripts/install.ps1 | iex
 ```
 
-The install script sets up [Watchtower](https://github.com/nicholas-fedor/watchtower) automatically for daily auto-updates. To skip it, add the `--no-watchtower` flag. For Docker Compose, manual installation, and other deployment options, see the [docs](https://www.surfsense.com/docs/).
+安装脚本会自动配置 [Watchtower](https://github.com/nicholas-fedor/watchtower) 以实现每日自动更新。如需跳过，请加上 `--no-watchtower` 参数。关于 Docker Compose、手动安装及其他部署方式，请参阅[文档](https://www.surfsense.com/docs/)。
 
-## Everything else in the box
+## 开箱即用的其他能力
 
-The research workspace that made SurfSense the leading open-source NotebookLM alternative is still here, and everything your agents gather lands in it.
+让 SurfSense 成为领先的开源 NotebookLM 替代品的那套研究工作区依然都在，而且你的智能体收集到的一切都会汇入其中。
 
-**Knowledge base**
+**知识库**
 
-- Upload PDFs, Office docs, images, and audio, or sync **Google Drive, OneDrive, and Dropbox**. 50+ file formats supported.
-- Hybrid semantic and full-text search with cited, Perplexity-style answers.
-- AI file sorting auto-organizes documents by source, date, and topic.
+- 上传 PDF、Office 文档、图片和音频，或同步 **Google Drive、OneDrive 和 Dropbox**。支持 50 多种文件格式。
+- 混合语义与全文搜索，提供 Perplexity 风格的带引用回答。
+- AI 文件整理功能按来源、日期和主题自动归类文档。
 
-<p align="center"><img src="surfsense_web/public/homepage/hero_tutorial/BQnaGif_compressed.gif" alt="Chat With Your PDFs and Docs" /></p>
+<p align="center"><img src="surfsense_web/public/homepage/hero_tutorial/BQnaGif_compressed.gif" alt="与你的 PDF 和文档对话" /></p>
 
-**Deliverable studio**
+**成果工作室**
 
-- AI report generator with export to PDF, DOCX, HTML, LaTeX, EPUB, ODT, or plain text.
-- Two-host AI podcasts from any document or folder in under 20 seconds.
-- Editable slide decks, narrated video overviews, and AI image generation.
+- AI 报告生成器，可导出为 PDF、DOCX、HTML、LaTeX、EPUB、ODT 或纯文本。
+- 20 秒内基于任意文档或文件夹生成双主持人 AI 播客。
+- 可编辑的幻灯片、带旁白的视频概览以及 AI 图像生成。
 
-<p align="center"><img src="surfsense_web/public/homepage/hero_tutorial/ReportGenGif_compressed.gif" alt="AI Report Generator" /></p>
+<p align="center"><img src="surfsense_web/public/homepage/hero_tutorial/ReportGenGif_compressed.gif" alt="AI 报告生成器" /></p>
 
-**Team collaboration**
+**团队协作**
 
-- Real-time collaborative AI chats with comments and mentions.
-- RBAC with Owner, Admin, Editor, and Viewer roles.
+- 支持评论和提及的实时协作 AI 聊天。
+- 基于角色的访问控制（RBAC），提供所有者、管理员、编辑者和查看者角色。
 
-<p align="center"><img src="surfsense_web/public/homepage/hero_realtime/RealTimeChatGif.gif" alt="Collaborative AI Chat" /></p>
+<p align="center"><img src="surfsense_web/public/homepage/hero_realtime/RealTimeChatGif.gif" alt="协作 AI 聊天" /></p>
 
-**Desktop app**
+**桌面应用**
 
-Native AI assistance in every application on your computer. Download from the [latest release](https://github.com/MODSetter/SurfSense/releases/latest).
+在电脑上的每个应用中获得原生 AI 辅助。从[最新版本](https://github.com/MODSetter/SurfSense/releases/latest)下载。
 
-- **General Assist**: launch SurfSense from any app with a global shortcut.
-- **Quick Assist**: select text anywhere, then ask AI to explain, rewrite, or act on it.
-- **Screenshot Assist**: capture any region of your screen and ask AI about it.
-- **Watch Local Folder**: auto-sync a local folder to your knowledge base. Point it at your Obsidian vault to keep your notes searchable.
+- **General Assist**：通过全局快捷键在任意应用中唤起 SurfSense。
+- **Quick Assist**：在任意位置选中文本，让 AI 解释、改写或据此执行操作。
+- **Screenshot Assist**：截取屏幕上任意区域，向 AI 提问。
+- **Watch Local Folder**：把本地文件夹自动同步到知识库。将它指向你的 Obsidian 仓库，让笔记随时可搜索。
 
 <p align="center"><img src="surfsense_web/public/homepage/hero_tutorial/quick_assist.gif" alt="Quick Assist" /></p>
 
-**No vendor lock-in**
+**无供应商锁定**
 
-- 100+ LLMs via the OpenAI spec and LiteLLM, including GPT-5.5, Claude Sonnet 5, and Gemini 3.1 Pro.
-- 6,000+ embedding models and all major rerankers.
-- Full local and private LLM support (vLLM, Ollama), so your data stays yours.
+- 通过 OpenAI 规范和 LiteLLM 支持 100 多种 LLM，包括 GPT-5.5、Claude Sonnet 5 和 Gemini 3.1 Pro。
+- 支持 6,000 多种嵌入模型和所有主流重排序器。
+- 完整支持本地和私有 LLM（vLLM、Ollama），你的数据始终属于你。
 
-## Video Agent Sample
+## 视频智能体示例
 
 https://github.com/user-attachments/assets/012a7ffa-6f76-4f06-9dda-7632b470057a
 
-## Podcast Agent Sample
+## 播客智能体示例
 
 https://github.com/user-attachments/assets/a0a16566-6967-4374-ac51-9b3e07fbecd7
 
-## How to collaborate in real time (Beta)
+## 如何进行实时协作（Beta）
 
-1. Go to the Manage Members page and create an invite.
+1. 进入成员管理页面并创建邀请。
 
-   <p align="center"><img src="https://github.com/user-attachments/assets/40ed7683-5aa6-48a0-a3df-00575528c392" alt="Invite Members" /></p>
+   <p align="center"><img src="https://github.com/user-attachments/assets/40ed7683-5aa6-48a0-a3df-00575528c392" alt="邀请成员" /></p>
 
-2. A teammate joins and that workspace becomes shared.
+2. 队友加入后，该工作区即变为共享。
 
-   <p align="center"><img src="https://github.com/user-attachments/assets/ea4e1057-4d2b-4fd2-9ca0-cd19286a285e" alt="Invite Join Flow" /></p>
+   <p align="center"><img src="https://github.com/user-attachments/assets/ea4e1057-4d2b-4fd2-9ca0-cd19286a285e" alt="邀请加入流程" /></p>
 
-3. Make a chat shared and work in it together in real time, with comments to tag teammates.
+3. 将聊天设为共享，即可与团队实时协作，并通过评论标记队友。
 
-   <p align="center"><img src="surfsense_web/public/homepage/hero_realtime/RealTimeCommentsFlow.gif" alt="Realtime Comments" /></p>
+   <p align="center"><img src="surfsense_web/public/homepage/hero_realtime/RealTimeCommentsFlow.gif" alt="实时评论" /></p>
 
-## SurfSense vs Google NotebookLM
+## SurfSense 对比 Google NotebookLM
 
-Still comparing us as a NotebookLM alternative? Here is the honest breakdown.
+还在把我们当作 NotebookLM 替代品来比较？这里是坦诚的对比。
 
-| Feature | Google NotebookLM | SurfSense |
+| 功能 | Google NotebookLM | SurfSense |
 |---------|-------------------|-----------|
-| **Live market data for agents** | No | Reddit, YouTube, Google Maps, Google Search, and web crawl connectors via REST API and MCP |
-| **MCP server** | No | Every connector exposed as a native agent tool, plus bring-your-own MCP servers with one-click OAuth apps |
-| **Sources per Notebook** | 50 (Free) to 600 (Ultra, $249.99/mo) | Unlimited |
-| **Number of Notebooks** | 100 (Free) to 500 (paid tiers) | Unlimited |
-| **Source Size Limit** | 500,000 words / 200MB per source | No limit |
-| **Pricing** | Free tier; Pro $19.99/mo, Ultra $249.99/mo | Free and open source to self-host; cloud is pay as you go with $5 free credit |
-| **LLM Support** | Google Gemini only | 100+ LLMs via OpenAI spec & LiteLLM |
-| **Embedding Models** | Google only | 6,000+ embedding models, all major rerankers |
-| **Local / Private LLMs** | Not available | Full support (vLLM, Ollama), your data stays yours |
-| **Self Hostable** | No | Yes, Docker one-liner or full Docker Compose |
-| **Open Source** | No | Yes |
-| **Knowledge Base Sources** | Google Drive, YouTube, websites | File uploads, Google Drive, OneDrive, Dropbox, local folder sync, and crawled pages |
-| **File Format Support** | PDFs, Docs, Slides, Sheets, CSV, Word, EPUB, images, web URLs, YouTube | 50+ formats: documents, images, videos via LlamaCloud, Unstructured, or Docling (local) |
-| **Search** | Semantic search | Hybrid semantic + full-text with hierarchical indices & reciprocal rank fusion |
-| **Cited Answers** | Yes | Yes, Perplexity-style cited responses |
-| **Agentic Architecture** | No | Yes, powered by [LangChain Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview) with planning, subagents, and file system access |
-| **AI Automations & Agents** | No | Scheduled workflows, event triggers, and chat-built no-code automations with write-back to Notion, Slack, Linear & Jira |
-| **Real-Time Multiplayer** | Shared notebooks with Viewer/Editor roles (no real-time chat) | RBAC with Owner / Admin / Editor / Viewer roles, real-time chat & comment threads |
-| **Video Generation** | Cinematic Video Overviews via Veo 3 (Ultra only) | Available (NotebookLM is better here, actively improving) |
-| **Presentation Generation** | Better looking slides but not editable | Editable, slide-based presentations |
-| **Podcast Generation** | Audio Overviews with customizable hosts and languages | Available with multiple TTS providers (NotebookLM is better here, actively improving) |
-| **Desktop App** | No | Native app with General Assist, Quick Assist, Screenshot Assist, and local folder sync |
+| **面向智能体的实时市场数据** | 无 | 通过 REST API 和 MCP 提供 Reddit、YouTube、Google Maps、Google Search 和网页爬取连接器 |
+| **MCP 服务器** | 无 | 每个连接器都作为原生智能体工具暴露，还可自带 MCP 服务器并使用一键 OAuth 应用 |
+| **每个笔记本的来源数** | 50 个（免费版）至 600 个（Ultra 版，249.99 美元/月） | 无限制 |
+| **笔记本数量** | 100 个（免费版）至 500 个（付费档位） | 无限制 |
+| **来源大小限制** | 每个来源 50 万字 / 200MB | 无限制 |
+| **定价** | 免费档；Pro 19.99 美元/月，Ultra 249.99 美元/月 | 自托管免费且开源；云端按量付费，附赠 5 美元免费额度 |
+| **LLM 支持** | 仅 Google Gemini | 通过 OpenAI 规范和 LiteLLM 支持 100 多种 LLM |
+| **嵌入模型** | 仅 Google | 6,000 多种嵌入模型，所有主流重排序器 |
+| **本地 / 私有 LLM** | 不支持 | 完整支持（vLLM、Ollama），你的数据始终属于你 |
+| **可自托管** | 否 | 是，Docker 一行命令或完整 Docker Compose |
+| **开源** | 否 | 是 |
+| **知识库来源** | Google Drive、YouTube、网站 | 文件上传、Google Drive、OneDrive、Dropbox、本地文件夹同步以及爬取的网页 |
+| **文件格式支持** | PDF、Docs、Slides、Sheets、CSV、Word、EPUB、图片、网页 URL、YouTube | 50 多种格式：文档、图片、视频，通过 LlamaCloud、Unstructured 或 Docling（本地）解析 |
+| **搜索** | 语义搜索 | 混合语义 + 全文搜索，带分层索引和倒数排名融合 |
+| **带引用的回答** | 有 | 有，Perplexity 风格的引用回答 |
+| **智能体架构** | 无 | 有，由 [LangChain Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview) 驱动，具备规划、子智能体和文件系统访问能力 |
+| **AI 自动化与智能体** | 无 | 定时工作流、事件触发以及通过聊天构建的无代码自动化，可写回 Notion、Slack、Linear 和 Jira |
+| **实时多人协作** | 共享笔记本，仅有查看者/编辑者角色（无实时聊天） | RBAC 提供所有者 / 管理员 / 编辑者 / 查看者角色，支持实时聊天和评论串 |
+| **视频生成** | 通过 Veo 3 生成电影级视频概览（仅 Ultra 版） | 已提供（此项 NotebookLM 更强，我们正在积极改进） |
+| **演示文稿生成** | 幻灯片更美观但不可编辑 | 可编辑的幻灯片式演示文稿 |
+| **播客生成** | 音频概览，支持自定义主持人和语言 | 已提供，支持多种 TTS 服务商（此项 NotebookLM 更强，我们正在积极改进） |
+| **桌面应用** | 无 | 原生应用，包含 General Assist、Quick Assist、Screenshot Assist 和本地文件夹同步 |
 
-## Feature requests and future
+## 功能请求与未来规划
 
-**SurfSense is actively being developed.** While it's not yet production-ready, you can help us speed up the process.
+**SurfSense 正在积极开发中。**虽然它尚未达到生产就绪状态，但你可以帮助我们加快进度。
 
-Join the [SurfSense Discord](https://discord.gg/ejRNvftDp9) and help shape the future of SurfSense!
+加入 [SurfSense Discord](https://discord.gg/ejRNvftDp9)，一起塑造 SurfSense 的未来！
 
-## Roadmap
+## 路线图
 
-Stay up to date with our development progress and upcoming features. Check out our public roadmap and contribute your ideas or feedback:
+随时了解我们的开发进度和即将推出的功能。查看我们的公开路线图，贡献你的想法或反馈：
 
-**Roadmap Discussion:** [SurfSense 2026 Roadmap](https://github.com/MODSetter/SurfSense/discussions/565)
+**路线图讨论：**[SurfSense 2026 Roadmap](https://github.com/MODSetter/SurfSense/discussions/565)
 
-**Kanban Board:** [SurfSense Project Board](https://github.com/users/MODSetter/projects/3)
+**看板：**[SurfSense Project Board](https://github.com/users/MODSetter/projects/3)
 
-## Contribute
+## 参与贡献
 
-All contributions welcome, from stars and bug reports to backend improvements. See [CONTRIBUTING.md](CONTRIBUTING.md) to get started.
+欢迎一切形式的贡献，从点星标、报告缺陷到后端改进。请参阅 [CONTRIBUTING.md](CONTRIBUTING.md) 开始参与。
 
-Thanks to all our Surfers:
+感谢所有 Surfer：
 
 <a href="https://github.com/MODSetter/SurfSense/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=MODSetter/SurfSense" />
 </a>
 
-## Star History
+## Star 历史
 
 <a href="https://www.star-history.com/#MODSetter/SurfSense&Date">
  <picture>