Merge branch 'master' into feat/topk_splitter

2026-07-22 20:36:08 +00:00 · 2025-07-23 16:37:27 +08:00
parent e986a0acaf 6754666845
commit d651d956d6
116 changed files with 2556 additions and 1333 deletions
@@ -9,7 +9,7 @@
 *请在方括号间写`x`以打勾 / Please tick the box with `x`*
- [ ] 阅读仓库[贡献指引](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)?
+- [ ] 阅读仓库[贡献指引](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)?
 - [ ] 与项目所有者沟通过了吗？ / Have you communicated with the project maintainer?
 - [ ] 我确定已自行测试所作的更改，确保功能符合预期。 / I have tested the changes and ensured they work as expected.
@@ -1,50 +1,38 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
 </a>
 <div align="center">
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+简体中文 / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 <a href="https://langbot.app">项目主页</a> ｜
 <a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a> ｜
 <a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">插件介绍</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
 <div align="center">
 😎高稳定、🧩支持扩展、🦄多模态 - 大模型原生即时通信机器人平台🤖  
 </div>
 <br/>
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 简体中文 / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
 </div>
 </p>
-## ✨ 特性
+LangBot 是一个开源的大语言模型原生即时通信机器人开发平台，旨在提供开箱即用的 IM 机器人开发体验，具有 Agent、RAG、MCP 等多种 LLM 应用功能，适配全球主流即时通信平台，并提供丰富的 API 接口，支持自定义开发。
 - 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态能力，并深度适配 [Dify](https://dify.ai)。目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
 - 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。
 - 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
 - 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
 ## 📦 开始使用
 #### Docker Compose 部署
 ```bash
-git clone https://github.com/RockChinQ/LangBot
+git clone https://github.com/langbot-app/LangBot
 cd LangBot
 docker compose up -d
 ```
@@ -71,23 +59,25 @@ docker compose up -d
 直接使用发行版运行，查看文档[手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
-## 📸 效果展示
+## 😎 保持更新
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="450px"/>
+点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="450px"/>
+![star gif](https://docs.langbot.app/star.gif)
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="450px"/>
+## ✨ 特性
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="450px"/>
+- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态能力，自带 RAG（知识库）实现，并深度适配 [Dify](https://dify.ai)。
 - 🤖 多平台支持：目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
 - 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。
 - 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
 - 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
-<img alt="回复效果（带有联网插件）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
- WebUI Demo: https://demo.langbot.dev/
+或访问 demo 环境：https://demo.langbot.dev/  
-    - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
+  - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
-    - 注意：仅展示webui效果，公开环境，请不要在其中填入您的任何敏感信息。
+  - 注意：仅展示 WebUI 效果，公开环境，请不要在其中填入您的任何敏感信息。
 ## 🔌 组件兼容性
 ### 消息平台
@@ -104,10 +94,6 @@ docker compose up -d
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | 🚧 |  |
 | WhatsApp | 🚧 |  |
 🚧: 正在开发中
 ### 大模型能力
@@ -149,14 +135,8 @@ docker compose up -d
 ## 😘 社区贡献
-感谢以下[代码贡献者](https://github.com/RockChinQ/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
+感谢以下[代码贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
 ## 😎 保持更新
 点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
 ![star gif](https://docs.langbot.app/star.gif)
@@ -1,48 +1,34 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
 </a>
 <div align="center">
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+[简体中文](README.md) / English / [日本語](README_JP.md) / (PR for your language)
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 <a href="https://langbot.app">Home</a> ｜
 <a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a> ｜
 <a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
 <div align="center">
 😎High Stability, 🧩Extension Supported, 🦄Multi-modal - LLM Native Instant Messaging Bot Platform🤖  
 </div>
 <br/>
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 [简体中文](README.md) / English / [日本語](README_JP.md) / (PR for your language)
 </div>
 </p>
-## ✨ Features
+LangBot is an open-source LLM native instant messaging robot development platform, aiming to provide out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, adapting to global instant messaging platforms, and providing rich API interfaces, supporting custom development.
 - 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, and multi-modal capabilities. Deeply integrates with [Dify](https://dify.ai). Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
 - 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
 - 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
 - 😻 [New] Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
 ## 📦 Getting Started
 #### Docker Compose Deployment
 ```bash
-git clone https://github.com/RockChinQ/LangBot
+git clone https://github.com/langbot-app/LangBot
 cd LangBot
 docker compose up -d
 ```
@@ -69,23 +55,25 @@ Community contributed Zeabur template.
 Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
-## 📸 Demo
+## 😎 Stay Ahead
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
+Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
+![star gif](https://docs.langbot.app/star.gif)
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
+## ✨ Features
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
+- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, and multi-modal capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai).
 - 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
 - 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
 - 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
 - 😻 Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
-<img alt="Reply Effect (with Internet Plugin)" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
- WebUI Demo: https://demo.langbot.dev/
+Or visit the demo environment: https://demo.langbot.dev/
-    - Login information: Email: `demo@langbot.app` Password: `langbot123456`
+  - Login information: Email: `demo@langbot.app` Password: `langbot123456`
-    - Note: Only the WebUI effect is shown, please do not fill in any sensitive information in the public environment.
+  - Note: For WebUI demo only, please do not fill in any sensitive information in the public environment.
 ## 🔌 Component Compatibility
 ### Message Platform
@@ -101,10 +89,6 @@ Directly use the released version to run, see the [Manual Deployment](https://do
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | 🚧 |  |
 | WhatsApp | 🚧 |  |
 🚧: In development
 ### LLMs
@@ -132,14 +116,8 @@ Directly use the released version to run, see the [Manual Deployment](https://do
 ## 🤝 Community Contribution
-Thank you for the following [code contributors](https://github.com/RockChinQ/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
+Thank you for the following [code contributors](https://github.com/langbot-app/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
 ## 😎 Stay Ahead
 Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
 ![star gif](https://docs.langbot.app/star.gif)
@@ -1,47 +1,34 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
 </a>
 <div align="center">
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+[简体中文](README.md) / [English](README_EN.md) / 日本語 / (PR for your language)
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 <a href="https://langbot.app">ホーム</a> ｜
 <a href="https://docs.langbot.app/en/insight/guide.html">デプロイ</a> ｜
 <a href="https://docs.langbot.app/en/plugin/plugin-intro.html">プラグイン</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
 <div align="center">
 😎高い安定性、🧩拡張サポート、🦄マルチモーダル - LLMネイティブインスタントメッセージングボットプラットフォーム🤖  
 </div>
 <br/>
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 [简体中文](README_CN.md) / [English](README.md) / [日本語](README_JP.md) / (PR for your language)
 </div>
 </p>
-## ✨ 機能
+LangBot は、エージェント、RAG、MCP などの LLM アプリケーション機能を備えた、オープンソースの LLM ネイティブのインスタントメッセージングロボット開発プラットフォームです。世界中のインスタントメッセージングプラットフォームに適応し、豊富な API インターフェースを提供し、カスタム開発をサポートします。
 - 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル機能をサポート。 [Dify](https://dify.ai) と深く統合。現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
 - 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
 - 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
 - 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
 ## 📦 始め方
 #### Docker Compose デプロイ
 ```bash
-git clone https://github.com/RockChinQ/LangBot
+git clone https://github.com/langbot-app/LangBot
 cd LangBot
 docker compose up -d
 ```
@@ -50,7 +37,7 @@ http://localhost:5300 にアクセスして使用を開始します。
 詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
-#### BTPanelでのワンクリックデプロイ
+#### Panelでのワンクリックデプロイ
 LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
@@ -68,23 +55,25 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 リリースバージョンを直接使用して実行します。[手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html)のドキュメントを参照してください。
-## 📸 デモ
+## 😎 最新情報を入手
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
+リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
+![star gif](https://docs.langbot.app/star.gif)
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
+## ✨ 機能
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
+- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル機能をサポート、RAG（知識ベース）を組み込み、[Dify](https://dify.ai) と深く統合。
 - 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
 - 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
 - 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
 - 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
-<img alt="返信効果（インターネットプラグイン付き）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+詳細な仕様については、[ドキュメント](https://docs.langbot.app/en/insight/features.html)を参照してください。
- WebUIデモ: https://demo.langbot.dev/
+または、デモ環境にアクセスしてください: https://demo.langbot.dev/
-    - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
+  - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
-    - 注意: WebUIの効果のみを示しています。公開環境では、機密情報を入力しないでください。
+  - 注意: WebUI のデモンストレーションのみの場合、公開環境では機密情報を入力しないでください。
 ## 🔌 コンポーネントの互換性
 ### メッセージプラットフォーム
@@ -100,10 +89,6 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | 🚧 |  |
 | WhatsApp | 🚧 |  |
 🚧: 開発中
 ### LLMs
@@ -131,14 +116,8 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 ## 🤝 コミュニティ貢献
-LangBot への貢献に対して、以下の [コード貢献者](https://github.com/RockChinQ/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
+LangBot への貢献に対して、以下の [コード貢献者](https://github.com/langbot-app/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
 ## 😎 最新情報を入手
 リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
 ![star gif](https://docs.langbot.app/star.gif)
@@ -11,7 +11,7 @@ asciiart = r"""
 |____\__,_|_||_\__, |___/\___/\__|
               |___/              
-⭐️ Open Source 开源地址: https://github.com/RockChinQ/LangBot
+⭐️ Open Source 开源地址: https://github.com/langbot-app/LangBot
 📖 Documentation 文档地址: https://docs.langbot.app
 """
@@ -11,7 +11,7 @@ from ....core import app
 preregistered_groups: list[type[RouterGroup]] = []
-"""RouterGroup 的预注册列表"""
+"""Pre-registered list of RouterGroup"""
 def group_class(name: str, path: str) -> typing.Callable[[typing.Type[RouterGroup]], typing.Type[RouterGroup]]:
@@ -27,7 +27,7 @@ def group_class(name: str, path: str) -> typing.Callable[[typing.Type[RouterGrou
 class AuthType(enum.Enum):
-    """认证类型"""
+    """Authentication type"""
    NONE = 'none'
    USER_TOKEN = 'user-token'
@@ -56,7 +56,7 @@ class RouterGroup(abc.ABC):
        auth_type: AuthType = AuthType.USER_TOKEN,
        **options: typing.Any,
    ) -> typing.Callable[[RouteCallable], RouteCallable]:  # decorator
-        """注册一个路由"""
+        """Register a route"""
        def decorator(f: RouteCallable) -> RouteCallable:
            nonlocal rule
@@ -64,11 +64,11 @@ class RouterGroup(abc.ABC):
            async def handler_error(*args, **kwargs):
                if auth_type == AuthType.USER_TOKEN:
-                    # 从Authorization头中获取token
+                    # get token from Authorization header
                    token = quart.request.headers.get('Authorization', '').replace('Bearer ', '')
                    if not token:
-                        return self.http_status(401, -1, '未提供有效的用户令牌')
+                        return self.http_status(401, -1, 'No valid user token provided')
                    try:
                        user_email = await self.ap.user_service.verify_jwt_token(token)
@@ -76,9 +76,9 @@ class RouterGroup(abc.ABC):
                        # check if this account exists
                        user = await self.ap.user_service.get_user_by_email(user_email)
                        if not user:
-                            return self.http_status(401, -1, '用户不存在')
+                            return self.http_status(401, -1, 'User not found')
-                        # 检查f是否接受user_email参数
+                        # check if f accepts user_email parameter
                        if 'user_email' in f.__code__.co_varnames:
                            kwargs['user_email'] = user_email
                    except Exception as e:
@@ -86,10 +86,11 @@ class RouterGroup(abc.ABC):
                try:
                    return await f(*args, **kwargs)
-                except Exception:  # 自动 500
+
                except Exception as e:  # 自动 500
                    traceback.print_exc()
                    # return self.http_status(500, -2, str(e))
-                    return self.http_status(500, -2, 'internal server error')
+                    return self.http_status(500, -2, str(e))
            new_f = handler_error
            new_f.__name__ = (self.name + rule).replace('/', '__')
@@ -101,7 +102,7 @@ class RouterGroup(abc.ABC):
        return decorator
    def success(self, data: typing.Any = None) -> quart.Response:
-        """返回一个 200 响应"""
+        """Return a 200 response"""
        return quart.jsonify(
            {
                'code': 0,
@@ -111,7 +112,7 @@ class RouterGroup(abc.ABC):
        )
    def fail(self, code: int, msg: str) -> quart.Response:
-        """返回一个异常响应"""
+        """Return an error response"""
        return quart.jsonify(
            {
@@ -122,4 +123,4 @@ class RouterGroup(abc.ABC):
    def http_status(self, status: int, code: int, msg: str) -> typing.Tuple[quart.Response, int]:
        """返回一个指定状态码的响应"""
-        return (self.fail(code, msg), status)
+        return (self.fail(code, msg), status)
@@ -34,8 +34,9 @@ class FilesRouterGroup(group.RouterGroup):
            file_bytes = await asyncio.to_thread(file.stream.read)
            extension = file.filename.split('.')[-1]
            file_name = file.filename.split('.')[0]
-            file_key = str(uuid.uuid4()) + '.' + extension
+            file_key = file_name + '_' + str(uuid.uuid4())[:8] + '.' + extension
            # save file to storage
            await self.ap.storage_mgr.storage_provider.save(file_key, file_bytes)
            return self.success(
@@ -20,7 +20,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
        @self.route(
            '/<knowledge_base_uuid>',
-            methods=['GET', 'DELETE'],
+            methods=['GET', 'DELETE', 'PUT'],
        )
        async def handle_specific_knowledge_base(knowledge_base_uuid: str) -> quart.Response:
            if quart.request.method == 'GET':
@@ -34,6 +34,12 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
                        'base': knowledge_base,
                    }
                )
            elif quart.request.method == 'PUT':
                json_data = await quart.request.json
                await self.ap.knowledge_service.update_knowledge_base(knowledge_base_uuid, json_data)
                return self.success({})
            elif quart.request.method == 'DELETE':
                await self.ap.knowledge_service.delete_knowledge_base(knowledge_base_uuid)
                return self.success({})
@@ -72,3 +78,13 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
        async def delete_specific_file_in_kb(file_id: str, knowledge_base_uuid: str) -> str:
            await self.ap.knowledge_service.delete_file(knowledge_base_uuid, file_id)
            return self.success({})
        @self.route(
            '/<knowledge_base_uuid>/retrieve',
            methods=['POST'],
        )
        async def retrieve_knowledge_base(knowledge_base_uuid: str) -> str:
            json_data = await quart.request.json
            query = json_data.get('query')
            results = await self.ap.knowledge_service.retrieve_knowledge_base(knowledge_base_uuid, query)
            return self.success(data={'results': results})
@@ -11,7 +11,9 @@ class PipelinesRouterGroup(group.RouterGroup):
        @self.route('', methods=['GET', 'POST'])
        async def _() -> str:
            if quart.request.method == 'GET':
-                return self.success(data={'pipelines': await self.ap.pipeline_service.get_pipelines()})
+                sort_by = quart.request.args.get('sort_by', 'created_at')
                sort_order = quart.request.args.get('sort_order', 'DESC')
                return self.success(data={'pipelines': await self.ap.pipeline_service.get_pipelines(sort_by, sort_order)})
            elif quart.request.method == 'POST':
                json_data = await quart.request.json
@@ -8,7 +8,7 @@ class WebChatDebugRouterGroup(group.RouterGroup):
    async def initialize(self) -> None:
        @self.route('/send', methods=['POST'])
        async def send_message(pipeline_uuid: str) -> str:
-            """发送调试消息到流水线"""
+            """Send a message to the pipeline for debugging"""
            try:
                data = await quart.request.get_json()
                session_type = data.get('session_type', 'person')
@@ -38,7 +38,7 @@ class WebChatDebugRouterGroup(group.RouterGroup):
        @self.route('/messages/<session_type>', methods=['GET'])
        async def get_messages(pipeline_uuid: str, session_type: str) -> str:
-            """获取调试消息历史"""
+            """Get the message history of the pipeline for debugging"""
            try:
                if session_type not in ['person', 'group']:
                    return self.http_status(400, -1, 'session_type must be person or group')
@@ -57,7 +57,7 @@ class WebChatDebugRouterGroup(group.RouterGroup):
        @self.route('/reset/<session_type>', methods=['POST'])
        async def reset_session(session_type: str) -> str:
-            """重置调试会话"""
+            """Reset the debug session"""
            try:
                if session_type not in ['person', 'group']:
                    return self.http_status(400, -1, 'session_type must be person or group')
@@ -40,7 +40,7 @@ class PluginsRouterGroup(group.RouterGroup):
                self.ap.plugin_mgr.update_plugin(plugin_name, task_context=ctx),
                kind='plugin-operation',
                name=f'plugin-update-{plugin_name}',
-                label=f'更新插件 {plugin_name}',
+                label=f'Updating plugin {plugin_name}',
                context=ctx,
            )
            return self.success(data={'task_id': wrapper.id})
@@ -62,7 +62,7 @@ class PluginsRouterGroup(group.RouterGroup):
                    self.ap.plugin_mgr.uninstall_plugin(plugin_name, task_context=ctx),
                    kind='plugin-operation',
                    name=f'plugin-remove-{plugin_name}',
-                    label=f'删除插件 {plugin_name}',
+                    label=f'Removing plugin {plugin_name}',
                    context=ctx,
                )
@@ -102,7 +102,7 @@ class PluginsRouterGroup(group.RouterGroup):
                self.ap.plugin_mgr.install_plugin(data['source'], task_context=ctx),
                kind='plugin-operation',
                name='plugin-install-github',
-                label=f'安装插件 ...{short_source_str}',
+                label=f'Installing plugin ...{short_source_str}',
                context=ctx,
            )
@@ -14,7 +14,7 @@ class UserRouterGroup(group.RouterGroup):
                return self.success(data={'initialized': await self.ap.user_service.is_initialized()})
            if await self.ap.user_service.is_initialized():
-                return self.fail(1, '系统已初始化')
+                return self.fail(1, 'System already initialized')
            json_data = await quart.request.json
@@ -32,7 +32,7 @@ class UserRouterGroup(group.RouterGroup):
            try:
                token = await self.ap.user_service.authenticate(json_data['user'], json_data['password'])
            except argon2.exceptions.VerifyMismatchError:
-                return self.fail(1, '用户名或密码错误')
+                return self.fail(1, 'Invalid username or password')
            return self.success(data={'token': token})
@@ -54,15 +54,15 @@ class UserRouterGroup(group.RouterGroup):
            await asyncio.sleep(3)
            if not await self.ap.user_service.is_initialized():
-                return self.http_status(400, -1, 'system not initialized')
+                return self.http_status(400, -1, 'System not initialized')
            user_obj = await self.ap.user_service.get_user_by_email(user_email)
            if user_obj is None:
-                return self.http_status(400, -1, 'user not found')
+                return self.http_status(400, -1, 'User not found')
            if recovery_key != self.ap.instance_config.data['system']['recovery_key']:
-                return self.http_status(403, -1, 'invalid recovery key')
+                return self.http_status(403, -1, 'Invalid recovery key')
            await self.ap.user_service.reset_password(user_email, new_password)
@@ -47,7 +47,7 @@ class HTTPController:
                try:
                    await self.quart_app.run_task(*args, **kwargs)
                except Exception as e:
-                    self.ap.logger.error(f'启动 HTTP 服务失败： {e}')
+                    self.ap.logger.error(f'Failed to start HTTP service: {e}')
            self.ap.task_mgr.create_task(
                exception_handler(
@@ -10,7 +10,7 @@ from ....entity.persistence import pipeline as persistence_pipeline
 class BotService:
-    """机器人服务"""
+    """Bot service"""
    ap: app.Application
@@ -18,7 +18,7 @@ class BotService:
        self.ap = ap
    async def get_bots(self) -> list[dict]:
-        """获取所有机器人"""
+        """Get all bots"""
        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_bot.Bot))
        bots = result.all()
@@ -26,7 +26,7 @@ class BotService:
        return [self.ap.persistence_mgr.serialize_model(persistence_bot.Bot, bot) for bot in bots]
    async def get_bot(self, bot_uuid: str) -> dict | None:
-        """获取机器人"""
+        """Get bot"""
        result = await self.ap.persistence_mgr.execute_async(
            sqlalchemy.select(persistence_bot.Bot).where(persistence_bot.Bot.uuid == bot_uuid)
        )
@@ -39,7 +39,7 @@ class BotService:
        return self.ap.persistence_mgr.serialize_model(persistence_bot.Bot, bot)
    async def create_bot(self, bot_data: dict) -> str:
-        """创建机器人"""
+        """Create bot"""
        # TODO: 检查配置信息格式
        bot_data['uuid'] = str(uuid.uuid4())
@@ -63,7 +63,7 @@ class BotService:
        return bot_data['uuid']
    async def update_bot(self, bot_uuid: str, bot_data: dict) -> None:
-        """更新机器人"""
+        """Update bot"""
        if 'uuid' in bot_data:
            del bot_data['uuid']
@@ -99,7 +99,7 @@ class BotService:
                session.using_conversation = None
    async def delete_bot(self, bot_uuid: str) -> None:
-        """删除机器人"""
+        """Delete bot"""
        await self.ap.platform_mgr.remove_bot(bot_uuid)
        await self.ap.persistence_mgr.execute_async(
            sqlalchemy.delete(persistence_bot.Bot).where(persistence_bot.Bot.uuid == bot_uuid)
@@ -47,12 +47,18 @@ class KnowledgeService:
    async def update_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
        """更新知识库"""
        if 'uuid' in kb_data:
            del kb_data['uuid']
        if 'embedding_model_uuid' in kb_data:
            del kb_data['embedding_model_uuid']
        await self.ap.persistence_mgr.execute_async(
            sqlalchemy.update(persistence_rag.KnowledgeBase)
            .values(kb_data)
            .where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
        )
-        await self.ap.rag_mgr.remove_knowledge_base(kb_uuid)
+        await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
        kb = await self.get_knowledge_base(kb_uuid)
@@ -67,6 +73,13 @@ class KnowledgeService:
            raise Exception('Knowledge base not found')
        return await runtime_kb.store_file(file_id)
    async def retrieve_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
        """检索知识库"""
        runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
        if runtime_kb is None:
            raise Exception('Knowledge base not found')
        return [result.model_dump() for result in await runtime_kb.retrieve(query)]
    async def get_files_by_knowledge_base(self, kb_uuid: str) -> list[dict]:
        """获取知识库文件"""
        result = await self.ap.persistence_mgr.execute_async(
@@ -77,14 +90,29 @@ class KnowledgeService:
    async def delete_file(self, kb_uuid: str, file_id: str) -> None:
        """删除文件"""
-        await self.ap.persistence_mgr.execute_async(
+        runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
-            sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file_id)
+        if runtime_kb is None:
-        )
+            raise Exception('Knowledge base not found')
-        # TODO: remove from memory
+        await runtime_kb.delete_file(file_id)
    async def delete_knowledge_base(self, kb_uuid: str) -> None:
        """删除知识库"""
        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
        await self.ap.persistence_mgr.execute_async(
            sqlalchemy.delete(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
        )
-        # TODO: remove from memory
+
        # delete files
        files = await self.ap.persistence_mgr.execute_async(
            sqlalchemy.select(persistence_rag.File).where(persistence_rag.File.kb_id == kb_uuid)
        )
        for file in files:
            # delete chunks
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.delete(persistence_rag.Chunk).where(persistence_rag.Chunk.file_id == file.uuid)
            )
            # delete file
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file.uuid)
            )
@@ -186,6 +186,6 @@ class EmbeddingModelsService:
        await runtime_embedding_model.requester.invoke_embedding(
            model=runtime_embedding_model,
-            input_text='Hello, world!',
+            input_text=['Hello, world!'],
            extra_args={},
        )
@@ -38,9 +38,21 @@ class PipelineService:
            self.ap.pipeline_config_meta_output.data,
        ]
-    async def get_pipelines(self) -> list[dict]:
+    async def get_pipelines(self, sort_by: str = 'created_at', sort_order: str = 'DESC') -> list[dict]:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
+        query = sqlalchemy.select(persistence_pipeline.LegacyPipeline)
-
+        
        if sort_by == 'created_at':
            if sort_order == 'DESC':
                query = query.order_by(persistence_pipeline.LegacyPipeline.created_at.desc())
            else:
                query = query.order_by(persistence_pipeline.LegacyPipeline.created_at.asc())
        elif sort_by == 'updated_at':
            if sort_order == 'DESC':
                query = query.order_by(persistence_pipeline.LegacyPipeline.updated_at.desc())
            else:
                query = query.order_by(persistence_pipeline.LegacyPipeline.updated_at.asc())
        result = await self.ap.persistence_mgr.execute_async(query)
        pipelines = result.all()
        return [
            self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
@@ -6,7 +6,7 @@ from .. import model as file_model
 class JSONConfigFile(file_model.ConfigFile):
-    """JSON配置文件"""
+    """JSON config file"""
    def __init__(
        self,
@@ -42,7 +42,7 @@ class JSONConfigFile(file_model.ConfigFile):
            try:
                cfg = json.load(f)
            except json.JSONDecodeError as e:
-                raise Exception(f'配置文件 {self.config_file_name} 语法错误: {e}')
+                raise Exception(f'Syntax error in config file {self.config_file_name}: {e}')
        if completion:
            for key in self.template_data:
@@ -7,13 +7,13 @@ from .. import model as file_model
 class PythonModuleConfigFile(file_model.ConfigFile):
-    """Python模块配置文件"""
+    """Python module config file"""
    config_file_name: str = None
-    """配置文件名"""
+    """Config file name"""
    template_file_name: str = None
-    """模板文件名"""
+    """Template file name"""
    def __init__(self, config_file_name: str, template_file_name: str) -> None:
        self.config_file_name = config_file_name
@@ -42,7 +42,7 @@ class PythonModuleConfigFile(file_model.ConfigFile):
            cfg[key] = getattr(module, key)
-        # 从模板模块文件中进行补全
+        # complete from template module file
        if completion:
            module_name = os.path.splitext(os.path.basename(self.template_file_name))[0]
            module = importlib.import_module(module_name)
@@ -60,7 +60,7 @@ class PythonModuleConfigFile(file_model.ConfigFile):
        return cfg
    async def save(self, data: dict):
-        logging.warning('Python模块配置文件不支持保存')
+        logging.warning('Python module config file does not support saving')
    def save_sync(self, data: dict):
-        logging.warning('Python模块配置文件不支持保存')
+        logging.warning('Python module config file does not support saving')
@@ -6,7 +6,7 @@ from .. import model as file_model
 class YAMLConfigFile(file_model.ConfigFile):
-    """YAML配置文件"""
+    """YAML config file"""
    def __init__(
        self,
@@ -42,7 +42,7 @@ class YAMLConfigFile(file_model.ConfigFile):
            try:
                cfg = yaml.load(f, Loader=yaml.FullLoader)
            except yaml.YAMLError as e:
-                raise Exception(f'配置文件 {self.config_file_name} 语法错误: {e}')
+                raise Exception(f'Syntax error in config file {self.config_file_name}: {e}')
        if completion:
            for key in self.template_data:
@@ -5,27 +5,27 @@ from .impls import pymodule, json as json_file, yaml as yaml_file
 class ConfigManager:
-    """配置文件管理器"""
+    """Config file manager"""
    name: str = None
-    """配置管理器名"""
+    """Config manager name"""
    description: str = None
-    """配置管理器描述"""
+    """Config manager description"""
    schema: dict = None
-    """配置文件 schema
+    """Config file schema
-    需要符合 JSON Schema Draft 7 规范
+    Must conform to JSON Schema Draft 7 specification
    """
    file: file_model.ConfigFile = None
-    """配置文件实例"""
+    """Config file instance"""
    data: dict = None
-    """配置数据"""
+    """Config data"""
    doc_link: str = None
-    """配置文件文档链接"""
+    """Config file documentation link"""
    def __init__(self, cfg_file: file_model.ConfigFile) -> None:
        self.file = cfg_file
@@ -42,15 +42,15 @@ class ConfigManager:
 async def load_python_module_config(config_name: str, template_name: str, completion: bool = True) -> ConfigManager:
-    """加载Python模块配置文件
+    """Load Python module config file
    Args:
-        config_name (str): 配置文件名
+        config_name (str): Config file name
-        template_name (str): 模板文件名
+        template_name (str): Template file name
-        completion (bool): 是否自动补全内存中的配置文件
+        completion (bool): Whether to automatically complete the config file in memory
    Returns:
-        ConfigManager: 配置文件管理器
+        ConfigManager: Config file manager
    """
    cfg_inst = pymodule.PythonModuleConfigFile(config_name, template_name)
@@ -66,13 +66,13 @@ async def load_json_config(
    template_data: dict = None,
    completion: bool = True,
 ) -> ConfigManager:
-    """加载JSON配置文件
+    """Load JSON config file
    Args:
-        config_name (str): 配置文件名
+        config_name (str): Config file name
-        template_name (str): 模板文件名
+        template_name (str): Template file name
-        template_data (dict): 模板数据
+        template_data (dict): Template data
-        completion (bool): 是否自动补全内存中的配置文件
+        completion (bool): Whether to automatically complete the config file in memory
    """
    cfg_inst = json_file.JSONConfigFile(config_name, template_name, template_data)
@@ -88,16 +88,16 @@ async def load_yaml_config(
    template_data: dict = None,
    completion: bool = True,
 ) -> ConfigManager:
-    """加载YAML配置文件
+    """Load YAML config file
    Args:
-        config_name (str): 配置文件名
+        config_name (str): Config file name
-        template_name (str): 模板文件名
+        template_name (str): Template file name
-        template_data (dict): 模板数据
+        template_data (dict): Template data
-        completion (bool): 是否自动补全内存中的配置文件
+        completion (bool): Whether to automatically complete the config file in memory
    Returns:
-        ConfigManager: 配置文件管理器
+        ConfigManager: Config file manager
    """
    cfg_inst = yaml_file.YAMLConfigFile(config_name, template_name, template_data)
@@ -2,16 +2,16 @@ import abc
 class ConfigFile(metaclass=abc.ABCMeta):
-    """配置文件抽象类"""
+    """Config file abstract class"""
    config_file_name: str = None
-    """配置文件名"""
+    """Config file name"""
    template_file_name: str = None
-    """模板文件名"""
+    """Template file name"""
    template_data: dict = None
-    """模板数据"""
+    """Template data"""
    @abc.abstractmethod
    def exists(self) -> bool:
@@ -28,11 +28,12 @@ from ..storage import mgr as storagemgr
 from ..utils import logcache
 from . import taskmgr
 from . import entities as core_entities
-from ..rag.knowledge import mgr as rag_mgr
+from ..rag.knowledge import kbmgr as rag_mgr
 from ..vector import mgr as vectordb_mgr
 class Application:
-    """运行时应用对象和上下文"""
+    """Runtime application object and context"""
    event_loop: asyncio.AbstractEventLoop = None
@@ -51,10 +52,10 @@ class Application:
    rag_mgr: rag_mgr.RAGManager = None
-    # TODO 移动到 pipeline 里
+    # TODO move to pipeline
    tool_mgr: llm_tool_mgr.ToolManager = None
-    # ======= 配置管理器 =======
+    # ======= Config manager =======
    command_cfg: config_mgr.ConfigManager = None  # deprecated
@@ -68,7 +69,7 @@ class Application:
    instance_config: config_mgr.ConfigManager = None
-    # ======= 元数据配置管理器 =======
+    # ======= Metadata config manager =======
    sensitive_meta: config_mgr.ConfigManager = None
@@ -97,6 +98,8 @@ class Application:
    persistence_mgr: persistencemgr.PersistenceManager = None
    vector_db_mgr: vectordb_mgr.VectorDBManager = None
    http_ctrl: http_controller.HTTPController = None
    log_cache: logcache.LogCache = None
@@ -163,11 +166,11 @@ class Application:
        except asyncio.CancelledError:
            pass
        except Exception as e:
-            self.logger.error(f'应用运行致命异常: {e}')
+            self.logger.error(f'Application runtime fatal exception: {e}')
            self.logger.debug(f'Traceback: {traceback.format_exc()}')
    async def print_web_access_info(self):
-        """打印访问 webui 的提示"""
+        """Print access webui tips"""
        if not os.path.exists(os.path.join('.', 'web/out')):
            self.logger.warning('WebUI 文件缺失，请根据文档部署：https://docs.langbot.app/zh')
@@ -199,7 +202,7 @@ class Application:
    ):
        match scope:
            case core_entities.LifecycleControlScope.PLATFORM.value:
-                self.logger.info('执行热重载 scope=' + scope)
+                self.logger.info('Hot reload scope=' + scope)
                await self.platform_mgr.shutdown()
                self.platform_mgr = im_mgr.PlatformManager(self)
@@ -215,7 +218,7 @@ class Application:
                    ],
                )
            case core_entities.LifecycleControlScope.PLUGIN.value:
-                self.logger.info('执行热重载 scope=' + scope)
+                self.logger.info('Hot reload scope=' + scope)
                await self.plugin_mgr.destroy_plugins()
                # 删除 sys.module 中所有的 plugins/* 下的模块
@@ -231,7 +234,7 @@ class Application:
                await self.plugin_mgr.load_plugins()
                await self.plugin_mgr.initialize_plugins()
            case core_entities.LifecycleControlScope.PROVIDER.value:
-                self.logger.info('执行热重载 scope=' + scope)
+                self.logger.info('Hot reload scope=' + scope)
                await self.tool_mgr.shutdown()
@@ -8,7 +8,7 @@ from . import app
 from . import stage
 from ..utils import constants, importutil
-# 引入启动阶段实现以便注册
+# Import startup stage implementation to register
 from . import stages
 importutil.import_modules_in_pkg(stages)
@@ -25,7 +25,7 @@ stage_order = [
 async def make_app(loop: asyncio.AbstractEventLoop) -> app.Application:
-    # 确定是否为调试模式
+    # Determine if it is debug mode
    if 'DEBUG' in os.environ and os.environ['DEBUG'] in ['true', '1']:
        constants.debug_mode = True
@@ -33,7 +33,7 @@ async def make_app(loop: asyncio.AbstractEventLoop) -> app.Application:
    ap.event_loop = loop
-    # 执行启动阶段
+    # Execute startup stage
    for stage_name in stage_order:
        stage_cls = stage.preregistered_stages[stage_name]
        stage_inst = stage_cls()
@@ -47,11 +47,11 @@ async def make_app(loop: asyncio.AbstractEventLoop) -> app.Application:
 async def main(loop: asyncio.AbstractEventLoop):
    try:
-        # 挂系统信号处理
+        # Hang system signal processing
        import signal
        def signal_handler(sig, frame):
-            print('[Signal] 程序退出.')
+            print('[Signal] Program exit.')
            # ap.shutdown()
            os._exit(0)
@@ -2,8 +2,8 @@ import pip
 import os
 from ...utils import pkgmgr
-# 检查依赖，防止用户未安装
+# Check dependencies to prevent users from not installing
-# 左边为引入名称，右边为依赖名称
+# Left is the import name, right is the dependency name
 required_deps = {
    'requests': 'requests',
    'openai': 'openai',
@@ -65,7 +65,7 @@ async def install_deps(deps: list[str]):
 async def precheck_plugin_deps():
    print('[Startup] Prechecking plugin dependencies...')
-    # 只有在plugins目录存在时才执行插件依赖安装
+    # Only execute plugin dependency installation when the plugins directory exists
    if os.path.exists('plugins'):
        for dir in os.listdir('plugins'):
            subdir = os.path.join('plugins', dir)
@@ -17,7 +17,7 @@ log_colors_config = {
 async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.Logger:
-    # 删除所有现有的logger
+    # Remove all existing loggers
    for handler in logging.root.handlers[:]:
        logging.root.removeHandler(handler)
@@ -54,13 +54,13 @@ async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.
        handler.setFormatter(color_formatter)
        qcg_logger.addHandler(handler)
-    qcg_logger.debug('日志初始化完成，日志级别：%s' % level)
+    qcg_logger.debug('Logging initialized, log level: %s' % level)
    logging.basicConfig(
-        level=logging.CRITICAL,  # 设置日志输出格式
+        level=logging.CRITICAL,  # Set log output format
        format='[DEPR][%(asctime)s.%(msecs)03d] %(pathname)s (%(lineno)d) - [%(levelname)s] :\n%(message)s',
-        # 日志输出的格式
+        # Log output format
-        # -8表示占位符，让输出左对齐，输出长度都为8位
+        # -8 is a placeholder, left-align the output, and output length is 8
-        datefmt='%Y-%m-%d %H:%M:%S',  # 时间输出的格式
+        datefmt='%Y-%m-%d %H:%M:%S',  # Time output format
        handlers=[logging.NullHandler()],
    )
@@ -7,11 +7,11 @@ from . import app
 preregistered_migrations: list[typing.Type[Migration]] = []
-"""当前阶段暂不支持扩展"""
+"""Currently not supported for extension"""
 def migration_class(name: str, number: int):
-    """注册一个迁移"""
+    """Register a migration"""
    def decorator(cls: typing.Type[Migration]) -> typing.Type[Migration]:
        cls.name = name
@@ -23,7 +23,7 @@ def migration_class(name: str, number: int):
 class Migration(abc.ABC):
-    """一个版本的迁移"""
+    """A version migration"""
    name: str
@@ -36,10 +36,10 @@ class Migration(abc.ABC):
    @abc.abstractmethod
    async def need_migrate(self) -> bool:
-        """判断当前环境是否需要运行此迁移"""
+        """Determine if the current environment needs to run this migration"""
        pass
    @abc.abstractmethod
    async def run(self):
-        """执行迁移"""
+        """Run migration"""
        pass
@@ -9,7 +9,7 @@ preregistered_notes: list[typing.Type[LaunchNote]] = []
 def note_class(name: str, number: int):
-    """注册一个启动信息"""
+    """Register a launch information"""
    def decorator(cls: typing.Type[LaunchNote]) -> typing.Type[LaunchNote]:
        cls.name = name
@@ -21,7 +21,7 @@ def note_class(name: str, number: int):
 class LaunchNote(abc.ABC):
-    """启动信息"""
+    """Launch information"""
    name: str
@@ -34,10 +34,10 @@ class LaunchNote(abc.ABC):
    @abc.abstractmethod
    async def need_show(self) -> bool:
-        """判断当前环境是否需要显示此启动信息"""
+        """Determine if the current environment needs to display this launch information"""
        pass
    @abc.abstractmethod
    async def yield_note(self) -> typing.AsyncGenerator[typing.Tuple[str, int], None]:
-        """生成启动信息"""
+        """Generate launch information"""
        pass
@@ -7,7 +7,7 @@ from .. import note
@note.note_class('ClassicNotes', 1)
 class ClassicNotes(note.LaunchNote):
-    """经典启动信息"""
+    """Classic launch information"""
    async def need_show(self) -> bool:
        return True
@@ -9,7 +9,7 @@ from .. import note
@note.note_class('SelectionModeOnWindows', 2)
 class SelectionModeOnWindows(note.LaunchNote):
-    """Windows 上的选择模式提示信息"""
+    """Selection mode prompt information on Windows"""
    async def need_show(self) -> bool:
        return os.name == 'nt'
@@ -19,3 +19,8 @@ class SelectionModeOnWindows(note.LaunchNote):
            """您正在使用 Windows 系统，若窗口左上角显示处于”选择“模式，程序将被暂停运行，此时请右键窗口中空白区域退出选择模式。""",
            logging.INFO,
        )
        yield (
            """You are using Windows system, if the top left corner of the window displays "Selection" mode, the program will be paused running, please right-click on the blank area in the window to exit the selection mode.""",
            logging.INFO,
        )
@@ -7,9 +7,9 @@ from . import app
 preregistered_stages: dict[str, typing.Type[BootingStage]] = {}
-"""预注册的请求处理阶段。在初始化时，所有请求处理阶段类会被注册到此字典中。
+"""Pre-registered request processing stages. All request processing stage classes are registered in this dictionary during initialization.
-当前阶段暂不支持扩展
+Currently not supported for extension
 """
@@ -22,11 +22,11 @@ def stage_class(name: str):
 class BootingStage(abc.ABC):
-    """启动阶段"""
+    """Booting stage"""
    name: str = None
    @abc.abstractmethod
    async def run(self, ap: app.Application):
-        """启动"""
+        """Run"""
        pass
@@ -9,7 +9,7 @@ from ...command import cmdmgr
 from ...provider.session import sessionmgr as llm_session_mgr
 from ...provider.modelmgr import modelmgr as llm_model_mgr
 from ...provider.tools import toolmgr as llm_tool_mgr
-from ...rag.knowledge import mgr as rag_mgr
+from ...rag.knowledge import kbmgr as rag_mgr
 from ...platform import botmgr as im_mgr
 from ...persistence import mgr as persistencemgr
 from ...api.http.controller import main as http_controller
@@ -21,15 +21,16 @@ from ...api.http.service import knowledge as knowledge_service
 from ...discover import engine as discover_engine
 from ...storage import mgr as storagemgr
 from ...utils import logcache
 from ...vector import mgr as vectordb_mgr
 from .. import taskmgr
@stage.stage_class('BuildAppStage')
 class BuildAppStage(stage.BootingStage):
-    """构建应用阶段"""
+    """Build LangBot application"""
    async def run(self, ap: app.Application):
-        """构建app对象的各个组件对象并初始化"""
+        """Build LangBot application"""
        ap.task_mgr = taskmgr.AsyncTaskManager(ap)
        discover = discover_engine.ComponentDiscoveryEngine(ap)
@@ -44,7 +45,7 @@ class BuildAppStage(stage.BootingStage):
        await ver_mgr.initialize()
        ap.ver_mgr = ver_mgr
-        # 发送公告
+        # Send announcement
        ann_mgr = announce.AnnouncementManager(ap)
        ap.ann_mgr = ann_mgr
@@ -91,9 +92,14 @@ class BuildAppStage(stage.BootingStage):
        ap.pipeline_mgr = pipeline_mgr
        rag_mgr_inst = rag_mgr.RAGManager(ap)
-        await rag_mgr_inst.initialize_rag_system()
+        await rag_mgr_inst.initialize()
        ap.rag_mgr = rag_mgr_inst
        # 初始化向量数据库管理器
        vectordb_mgr_inst = vectordb_mgr.VectorDBManager(ap)
        await vectordb_mgr_inst.initialize()
        ap.vector_db_mgr = vectordb_mgr_inst
        http_ctrl = http_controller.HTTPController(ap)
        await http_ctrl.initialize()
        ap.http_ctrl = http_ctrl
@@ -7,10 +7,10 @@ from .. import stage, app
@stage.stage_class('GenKeysStage')
 class GenKeysStage(stage.BootingStage):
-    """生成密钥阶段"""
+    """Generate keys stage"""
    async def run(self, ap: app.Application):
-        """启动"""
+        """Generate keys"""
        if not ap.instance_config.data['system']['jwt']['secret']:
            ap.instance_config.data['system']['jwt']['secret'] = secrets.token_hex(16)
@@ -8,10 +8,10 @@ from ..bootutils import config
@stage.stage_class('LoadConfigStage')
 class LoadConfigStage(stage.BootingStage):
-    """加载配置文件阶段"""
+    """Load config file stage"""
    async def run(self, ap: app.Application):
-        """启动"""
+        """Load config file"""
        # ======= deprecated =======
        if os.path.exists('data/config/command.json'):
@@ -11,10 +11,13 @@ importutil.import_modules_in_pkg(migrations)
@stage.stage_class('MigrationStage')
 class MigrationStage(stage.BootingStage):
-    """迁移阶段"""
+    """Migration stage
    These migrations are legacy, only performed in version 3.x
    """
    async def run(self, ap: app.Application):
-        """启动"""
+        """Run migration"""
        if any(
            [
@@ -29,7 +32,7 @@ class MigrationStage(stage.BootingStage):
        migrations = migration.preregistered_migrations
-        # 按照迁移号排序
+        # Sort by migration number
        migrations.sort(key=lambda x: x.number)
        for migration_cls in migrations:
@@ -37,4 +40,4 @@ class MigrationStage(stage.BootingStage):
            if await migration_instance.need_migrate():
                await migration_instance.run()
-                print(f'已执行迁移 {migration_instance.name}')
+                print(f'Migration {migration_instance.name} executed')
@@ -8,7 +8,7 @@ from ..bootutils import log
 class PersistenceHandler(logging.Handler, object):
    """
-    保存日志到数据库
+    Save logs to database
    """
    ap: app.Application
@@ -19,9 +19,9 @@ class PersistenceHandler(logging.Handler, object):
    def emit(self, record):
        """
-        emit函数为自定义handler类时必重写的函数，这里可以根据需要对日志消息做一些处理，比如发送日志到服务器
+        emit function is a required function for custom handler classes, here you can process the log messages as needed, such as sending logs to the server
-        发出记录(Emit a record)
+        Emit a record
        """
        try:
            msg = self.format(record)
@@ -34,10 +34,10 @@ class PersistenceHandler(logging.Handler, object):
@stage.stage_class('SetupLoggerStage')
 class SetupLoggerStage(stage.BootingStage):
-    """设置日志器阶段"""
+    """Setup logger stage"""
    async def run(self, ap: app.Application):
-        """启动"""
+        """Setup logger"""
        persistence_handler = PersistenceHandler('LoggerHandler', ap)
        extra_handlers = []
@@ -12,10 +12,10 @@ importutil.import_modules_in_pkg(notes)
@stage.stage_class('ShowNotesStage')
 class ShowNotesStage(stage.BootingStage):
-    """显示启动信息阶段"""
+    """Show notes stage"""
    async def run(self, ap: app.Application):
-        # 排序
+        # Sort
        note.preregistered_notes.sort(key=lambda x: x.number)
        for note_cls in note.preregistered_notes:
@@ -9,13 +9,13 @@ from . import entities as core_entities
 class TaskContext:
-    """任务跟踪上下文"""
+    """Task tracking context"""
    current_action: str
-    """当前正在执行的动作"""
+    """Current action being executed"""
    log: str
-    """记录日志"""
+    """Log"""
    def __init__(self):
        self.current_action = 'default'
@@ -58,40 +58,40 @@ placeholder_context: TaskContext | None = None
 class TaskWrapper:
-    """任务包装器"""
+    """Task wrapper"""
    _id_index: int = 0
-    """任务ID索引"""
+    """Task ID index"""
    id: int
-    """任务ID"""
+    """Task ID"""
-    task_type: str = 'system'  # 任务类型: system 或 user
+    task_type: str = 'system'  # Task type: system or user
-    """任务类型"""
+    """Task type"""
-    kind: str = 'system_task'  # 由发起者确定任务种类，通常同质化的任务种类相同
+    kind: str = 'system_task'  # Task type determined by the initiator, usually the same task type
-    """任务种类"""
+    """Task type"""
    name: str = ''
-    """任务唯一名称"""
+    """Task unique name"""
    label: str = ''
-    """任务显示名称"""
+    """Task display name"""
    task_context: TaskContext
-    """任务上下文"""
+    """Task context"""
    task: asyncio.Task
-    """任务"""
+    """Task"""
    task_stack: list = None
-    """任务堆栈"""
+    """Task stack"""
    ap: app.Application
-    """应用实例"""
+    """Application instance"""
    scopes: list[core_entities.LifecycleControlScope]
-    """任务所属生命周期控制范围"""
+    """Task scope"""
    def __init__(
        self,
@@ -165,13 +165,13 @@ class TaskWrapper:
 class AsyncTaskManager:
-    """保存app中的所有异步任务
+    """Save all asynchronous tasks in the app
-    包含系统级的和用户级（插件安装、更新等由用户直接发起的）的"""
+    Include system-level and user-level (plugin installation, update, etc. initiated by users directly)"""
    ap: app.Application
    tasks: list[TaskWrapper]
-    """所有任务"""
+    """All tasks"""
    def __init__(self, ap: app.Application):
        self.ap = ap
@@ -4,7 +4,7 @@ from .base import Base
 class Bot(Base):
-    """机器人"""
+    """Bot"""
    __tablename__ = 'bots'
@@ -12,7 +12,7 @@ initial_metadata = [
 class Metadata(Base):
-    """数据库元数据"""
+    """Database metadata"""
    __tablename__ = 'metadata'
@@ -4,7 +4,7 @@ from .base import Base
 class LLMModel(Base):
-    """LLM 模型"""
+    """LLM model"""
    __tablename__ = 'llm_models'
@@ -4,7 +4,7 @@ from .base import Base
 class LegacyPipeline(Base):
-    """旧版流水线"""
+    """Legacy pipeline"""
    __tablename__ = 'legacy_pipelines'
@@ -20,13 +20,12 @@ class LegacyPipeline(Base):
    )
    for_version = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
    is_default = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
    stages = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
    config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
 class PipelineRunRecord(Base):
-    """流水线运行记录"""
+    """Pipeline run record"""
    __tablename__ = 'pipeline_run_records'
@@ -43,3 +42,4 @@ class PipelineRunRecord(Base):
    started_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False)
    finished_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False)
    result = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
    knowledge_base_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
@@ -4,7 +4,7 @@ from .base import Base
 class PluginSetting(Base):
-    """插件配置"""
+    """Plugin setting"""
    __tablename__ = 'plugin_settings'
@@ -0,0 +1,13 @@
 from __future__ import annotations
 import pydantic
 from typing import Any
 class RetrieveResultEntry(pydantic.BaseModel):
    id: str
    metadata: dict[str, Any]
    distance: float
@@ -11,7 +11,7 @@ preregistered_managers: list[type[BaseDatabaseManager]] = []
 def manager_class(name: str) -> None:
-    """注册一个数据库管理类"""
+    """Register a database manager class"""
    def decorator(cls: type[BaseDatabaseManager]) -> type[BaseDatabaseManager]:
        cls.name = name
@@ -22,7 +22,7 @@ def manager_class(name: str) -> None:
 class BaseDatabaseManager(abc.ABC):
-    """基础数据库管理类"""
+    """Base database manager class"""
    name: str
@@ -7,7 +7,7 @@ from .. import database
@database.manager_class('sqlite')
 class SQLiteDatabaseManager(database.BaseDatabaseManager):
-    """SQLite 数据库管理类"""
+    """SQLite database manager"""
    async def initialize(self) -> None:
        sqlite_path = 'data/langbot.db'
@@ -22,12 +22,12 @@ importutil.import_modules_in_pkg(persistence)
 class PersistenceManager:
-    """持久化模块管理器"""
+    """Persistence module manager"""
    ap: app.Application
    db: database.BaseDatabaseManager
-    """数据库管理器"""
+    """Database manager"""
    meta: sqlalchemy.MetaData
@@ -79,7 +79,7 @@ class PersistenceManager:
                'stages': pipeline_service.default_stage_order,
                'is_default': True,
                'name': 'ChatPipeline',
-                'description': '默认提供的流水线，您配置的机器人、第一个模型将自动绑定到此流水线',
+                'description': 'Default pipeline, new bots will be bound to this pipeline | 默认提供的流水线，您配置的机器人将自动绑定到此流水线',
                'config': pipeline_config,
            }
@@ -10,7 +10,7 @@ preregistered_db_migrations: list[typing.Type[DBMigration]] = []
 def migration_class(number: int):
-    """迁移类装饰器"""
+    """Migration class decorator"""
    def wrapper(cls: typing.Type[DBMigration]) -> typing.Type[DBMigration]:
        cls.number = number
@@ -21,20 +21,20 @@ def migration_class(number: int):
 class DBMigration(abc.ABC):
-    """数据库迁移"""
+    """Database migration"""
    number: int
-    """迁移号"""
+    """Migration number"""
    def __init__(self, ap: app.Application):
        self.ap = ap
    @abc.abstractmethod
    async def upgrade(self):
-        """升级"""
+        """Upgrade"""
        pass
    @abc.abstractmethod
    async def downgrade(self):
-        """降级"""
+        """Downgrade"""
        pass
@@ -15,21 +15,21 @@ from ...entity.persistence import (
@migration.migration_class(1)
 class DBMigrateV3Config(migration.DBMigration):
-    """从 v3 的配置迁移到 v4 的数据库"""
+    """Migrate v3 config to v4 database"""
    async def upgrade(self):
-        """升级"""
+        """Upgrade"""
        """
-        将 data/config 下的所有配置文件进行迁移。
+        Migrate all config files under data/config.
-        迁移后，之前的配置文件都保存到 data/legacy/config 下。
+        After migration, all previous config files are saved under data/legacy/config.
-        迁移后，data/metadata/ 下的所有配置文件都保存到 data/legacy/metadata 下。
+        After migration, all config files under data/metadata/ are saved under data/legacy/metadata.
        """
        if self.ap.provider_cfg is None:
            return
-        # ======= 迁移模型 =======
+        # ======= Migrate model =======
-        # 只迁移当前选中的模型
+        # Only migrate the currently selected model
        model_name = self.ap.provider_cfg.data.get('model', 'gpt-4o')
        model_requester = 'openai-chat-completions'
@@ -91,8 +91,8 @@ class DBMigrateV3Config(migration.DBMigration):
            sqlalchemy.insert(persistence_model.LLMModel).values(**llm_model_data)
        )
-        # ======= 迁移流水线配置 =======
+        # ======= Migrate pipeline config =======
-        # 修改到默认流水线
+        # Modify to default pipeline
        default_pipeline = [
            self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
            for pipeline in (
@@ -184,8 +184,8 @@ class DBMigrateV3Config(migration.DBMigration):
                .where(persistence_pipeline.LegacyPipeline.uuid == default_pipeline['uuid'])
            )
-        # ======= 迁移机器人 =======
+        # ======= Migrate bot =======
-        # 只迁移启用的机器人
+        # Only migrate enabled bots
        for adapter in self.ap.platform_cfg.data.get('platform-adapters', []):
            if not adapter.get('enable'):
                continue
@@ -207,7 +207,7 @@ class DBMigrateV3Config(migration.DBMigration):
            await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_bot.Bot).values(**bot_data))
-        # ======= 迁移系统设置 =======
+        # ======= Migrate system settings =======
        self.ap.instance_config.data['admins'] = self.ap.system_cfg.data['admin-sessions']
        self.ap.instance_config.data['api']['port'] = self.ap.system_cfg.data['http-api']['port']
        self.ap.instance_config.data['command'] = {
@@ -223,7 +223,7 @@ class DBMigrateV3Config(migration.DBMigration):
        await self.ap.instance_config.dump_config()
        # ======= move files =======
-        # 迁移 data/config 下的所有配置文件
+        # Migrate all config files under data/config
        all_legacy_dir_name = [
            'config',
            # 'metadata',
@@ -246,4 +246,4 @@ class DBMigrateV3Config(migration.DBMigration):
            move_legacy_files(dir_name)
    async def downgrade(self):
-        """降级"""
+        """Downgrade"""
@@ -7,10 +7,10 @@ from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(2)
 class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
-    """引用消息合并配置"""
+    """Combine quote message config"""
    async def upgrade(self):
-        """升级"""
+        """Upgrade"""
        # read all pipelines
        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
@@ -37,5 +37,5 @@ class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
            )
    async def downgrade(self):
-        """降级"""
+        """Downgrade"""
        pass
@@ -7,10 +7,10 @@ from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(3)
 class DBMigrateN8nConfig(migration.DBMigration):
-    """N8n配置"""
+    """N8n config"""
    async def upgrade(self):
-        """升级"""
+        """Upgrade"""
        # read all pipelines
        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
@@ -45,5 +45,5 @@ class DBMigrateN8nConfig(migration.DBMigration):
            )
    async def downgrade(self):
-        """降级"""
+        """Downgrade"""
        pass
@@ -0,0 +1,38 @@
 from .. import migration
 import sqlalchemy
 from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(4)
 class DBMigrateRAGKBUUID(migration.DBMigration):
    """RAG知识库UUID"""
    async def upgrade(self):
        """升级"""
        # read all pipelines
        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
        for pipeline in pipelines:
            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
            config = serialized_pipeline['config']
            if 'knowledge-base' not in config['ai']['local-agent']:
                config['ai']['local-agent']['knowledge-base'] = ''
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
                .values(
                    {
                        'config': config,
                        'for_version': self.ap.ver_mgr.get_current_version(),
                    }
                )
            )
    async def downgrade(self):
        """降级"""
        pass
@@ -6,9 +6,9 @@ from ...core import entities as core_entities
@stage.stage_class('BanSessionCheckStage')
 class BanSessionCheckStage(stage.PipelineStage):
-    """访问控制处理阶段
+    """Access control processing stage
-    仅检查query中群号或个人号是否在访问控制列表中。
+    Only check if the group or personal number in the query is in the access control list.
    """
    async def initialize(self, pipeline_config: dict):
@@ -41,5 +41,7 @@ class BanSessionCheckStage(stage.PipelineStage):
        return entities.StageProcessResult(
            result_type=entities.ResultType.CONTINUE if ctn else entities.ResultType.INTERRUPT,
            new_query=query,
-            console_notice=f'根据访问控制忽略消息: {query.launcher_type.value}_{query.launcher_id}' if not ctn else '',
+            console_notice=f'Ignore message according to access control: {query.launcher_type.value}_{query.launcher_id}'
            if not ctn
            else '',
        )
@@ -13,13 +13,13 @@ preregistered_filters: list[typing.Type[ContentFilter]] = []
 def filter_class(
    name: str,
 ) -> typing.Callable[[typing.Type[ContentFilter]], typing.Type[ContentFilter]]:
-    """内容过滤器类装饰器
+    """Content filter class decorator
    Args:
-        name (str): 过滤器名称
+        name (str): Filter name
    Returns:
-        typing.Callable[[typing.Type[ContentFilter]], typing.Type[ContentFilter]]: 装饰器
+        typing.Callable[[typing.Type[ContentFilter]], typing.Type[ContentFilter]]: Decorator
    """
    def decorator(cls: typing.Type[ContentFilter]) -> typing.Type[ContentFilter]:
@@ -35,7 +35,7 @@ def filter_class(
 class ContentFilter(metaclass=abc.ABCMeta):
-    """内容过滤器抽象类"""
+    """Content filter abstract class"""
    name: str
@@ -46,31 +46,31 @@ class ContentFilter(metaclass=abc.ABCMeta):
    @property
    def enable_stages(self):
-        """启用的阶段
+        """Enabled stages
-        默认为消息请求AI前后的两个阶段。
+        Default is the two stages before and after the message request to AI.
-        entity.EnableStage.PRE: 消息请求AI前，此时需要检查的内容是用户的输入消息。
+        entity.EnableStage.PRE: Before message request to AI, the content to check is the user's input message.
-        entity.EnableStage.POST: 消息请求AI后，此时需要检查的内容是AI的回复消息。
+        entity.EnableStage.POST: After message request to AI, the content to check is the AI's reply message.
        """
        return [entities.EnableStage.PRE, entities.EnableStage.POST]
    async def initialize(self):
-        """初始化过滤器"""
+        """Initialize filter"""
        pass
    @abc.abstractmethod
    async def process(self, query: core_entities.Query, message: str = None, image_url=None) -> entities.FilterResult:
-        """处理消息
+        """Process message
-        分为前后阶段，具体取决于 enable_stages 的值。
+        It is divided into two stages, depending on the value of enable_stages.
-        对于内容过滤器来说，不需要考虑消息所处的阶段，只需要检查消息内容即可。
+        For content filters, you do not need to consider the stage of the message, you only need to check the message content.
        Args:
-            message (str): 需要检查的内容
+            message (str): Content to check
-            image_url (str): 要检查的图片的 URL
+            image_url (str): URL of the image to check
        Returns:
-            entities.FilterResult: 过滤结果，具体内容请查看 entities.FilterResult 类的文档
+            entities.FilterResult: Filter result, please refer to the documentation of entities.FilterResult class
        """
        raise NotImplementedError
@@ -8,7 +8,7 @@ from ....core import entities as core_entities
@filter_model.filter_class('ban-word-filter')
 class BanWordFilter(filter_model.ContentFilter):
-    """根据内容过滤"""
+    """Filter content"""
    async def initialize(self):
        pass
@@ -8,7 +8,7 @@ from ....core import entities as core_entities
@filter_model.filter_class('content-ignore')
 class ContentIgnore(filter_model.ContentFilter):
-    """根据内容忽略消息"""
+    """Ignore message according to content"""
    @property
    def enable_stages(self):
@@ -24,7 +24,7 @@ class ContentIgnore(filter_model.ContentFilter):
                        level=entities.ResultLevel.BLOCK,
                        replacement='',
                        user_notice='',
-                        console_notice='根据 ignore_rules 中的 prefix 规则，忽略消息',
+                        console_notice='Ignore message according to prefix rule in ignore_rules',
                    )
        if 'regexp' in query.pipeline_config['trigger']['ignore-rules']:
@@ -34,7 +34,7 @@ class ContentIgnore(filter_model.ContentFilter):
                        level=entities.ResultLevel.BLOCK,
                        replacement='',
                        user_notice='',
-                        console_notice='根据 ignore_rules 中的 regexp 规则，忽略消息',
+                        console_notice='Ignore message according to regexp rule in ignore_rules',
                    )
        return entities.FilterResult(
@@ -16,9 +16,9 @@ importutil.import_modules_in_pkg(strategies)
@stage.stage_class('LongTextProcessStage')
 class LongTextProcessStage(stage.PipelineStage):
-    """长消息处理阶段
+    """Long message processing stage
-    改写：
+    Rewrite:
        - resp_message_chain
    """
@@ -36,22 +36,22 @@ class LongTextProcessStage(stage.PipelineStage):
                        use_font = 'C:/Windows/Fonts/msyh.ttc'
                        if not os.path.exists(use_font):
                            self.ap.logger.warn(
-                                '未找到字体文件，且无法使用Windows自带字体，更换为转发消息组件以发送长消息，您可以在配置文件中调整相关设置。'
+                                'Font file not found, and Windows system font cannot be used, switch to forward message component to send long messages, you can adjust the related settings in the configuration file.'
                            )
                            config['blob_message_strategy'] = 'forward'
                        else:
-                            self.ap.logger.info('使用Windows自带字体：' + use_font)
+                            self.ap.logger.info('Using Windows system font: ' + use_font)
                            config['font-path'] = use_font
                    else:
                        self.ap.logger.warn(
-                            '未找到字体文件，且无法使用系统自带字体，更换为转发消息组件以发送长消息，您可以在配置文件中调整相关设置。'
+                            'Font file not found, and system font cannot be used, switch to forward message component to send long messages, you can adjust the related settings in the configuration file.'
                        )
                        pipeline_config['output']['long-text-processing']['strategy'] = 'forward'
            except Exception:
                traceback.print_exc()
                self.ap.logger.error(
-                    '加载字体文件失败({})，更换为转发消息组件以发送长消息，您可以在配置文件中调整相关设置。'.format(
+                    'Failed to load font file ({}), switch to forward message component to send long messages, you can adjust the related settings in the configuration file.'.format(
                        use_font
                    )
                )
@@ -63,12 +63,12 @@ class LongTextProcessStage(stage.PipelineStage):
                self.strategy_impl = strategy_cls(self.ap)
                break
        else:
-            raise ValueError(f'未找到名为 {config["strategy"]} 的长消息处理策略')
+            raise ValueError(f'Long message processing strategy not found: {config["strategy"]}')
        await self.strategy_impl.initialize()
    async def process(self, query: core_entities.Query, stage_inst_name: str) -> entities.StageProcessResult:
-        # 检查是否包含非 Plain 组件
+        # Check if it contains non-Plain components
        contains_non_plain = False
        for msg in query.resp_message_chain[-1]:
@@ -77,7 +77,7 @@ class LongTextProcessStage(stage.PipelineStage):
                break
        if contains_non_plain:
-            self.ap.logger.debug('消息中包含非 Plain 组件，跳过长消息处理。')
+            self.ap.logger.debug('Message contains non-Plain components, skip long message processing.')
        elif (
            len(str(query.resp_message_chain[-1]))
            > query.pipeline_config['output']['long-text-processing']['threshold']
@@ -15,17 +15,17 @@ Forward = platform_message.Forward
 class ForwardComponentStrategy(strategy_model.LongTextStrategy):
    async def process(self, message: str, query: core_entities.Query) -> list[platform_message.MessageComponent]:
        display = ForwardMessageDiaplay(
-            title='群聊的聊天记录',
+            title='Group chat history',
-            brief='[聊天记录]',
+            brief='[Chat history]',
-            source='聊天记录',
+            source='Chat history',
-            preview=['QQ用户: ' + message],
+            preview=['User: ' + message],
-            summary='查看1条转发消息',
+            summary='View 1 forwarded message',
        )
        node_list = [
            platform_message.ForwardMessageNode(
                sender_id=query.adapter.bot_account_id,
-                sender_name='QQ用户',
+                sender_name='User',
                message_chain=platform_message.MessageChain([message]),
            )
        ]
@@ -14,13 +14,13 @@ preregistered_strategies: list[typing.Type[LongTextStrategy]] = []
 def strategy_class(
    name: str,
 ) -> typing.Callable[[typing.Type[LongTextStrategy]], typing.Type[LongTextStrategy]]:
-    """长文本处理策略类装饰器
+    """Long text processing strategy class decorator
    Args:
-        name (str): 策略名称
+        name (str): Strategy name
    Returns:
-        typing.Callable[[typing.Type[LongTextStrategy]], typing.Type[LongTextStrategy]]: 装饰器
+        typing.Callable[[typing.Type[LongTextStrategy]], typing.Type[LongTextStrategy]]: Decorator
    """
    def decorator(cls: typing.Type[LongTextStrategy]) -> typing.Type[LongTextStrategy]:
@@ -36,7 +36,7 @@ def strategy_class(
 class LongTextStrategy(metaclass=abc.ABCMeta):
-    """长文本处理策略抽象类"""
+    """Long text processing strategy abstract class"""
    name: str
@@ -50,15 +50,15 @@ class LongTextStrategy(metaclass=abc.ABCMeta):
    @abc.abstractmethod
    async def process(self, message: str, query: core_entities.Query) -> list[platform_message.MessageComponent]:
-        """处理长文本
+        """Process long text
-        在 platform.json 中配置 long-text-process 字段，只要 文本长度超过了 threshold 就会调用此方法
+        If the text length exceeds the threshold, this method will be called.
        Args:
-            message (str): 消息
+            message (str): Message
-            query (core_entities.Query): 此次请求的上下文对象
+            query (core_entities.Query): Query object
        Returns:
-            list[platform_message.MessageComponent]: 转换后的 平台 消息组件列表
+            list[platform_message.MessageComponent]: Converted platform message components
        """
        return []
@@ -12,9 +12,9 @@ importutil.import_modules_in_pkg(truncators)
@stage.stage_class('ConversationMessageTruncator')
 class ConversationMessageTruncator(stage.PipelineStage):
-    """会话消息截断器
+    """Conversation message truncator
-    用于截断会话消息链，以适应平台消息长度限制。
+    Used to truncate the conversation message chain to adapt to the LLM message length limit.
    """
    trun: truncator.Truncator
@@ -27,10 +27,10 @@ class ConversationMessageTruncator(stage.PipelineStage):
                self.trun = trun(self.ap)
                break
        else:
-            raise ValueError(f'未知的截断器: {use_method}')
+            raise ValueError(f'Unknown truncator: {use_method}')
    async def process(self, query: core_entities.Query, stage_inst_name: str) -> entities.StageProcessResult:
-        """处理"""
+        """Process"""
        query = await self.trun.truncate(query)
        return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
@@ -6,17 +6,17 @@ from ....core import entities as core_entities
@truncator.truncator_class('round')
 class RoundTruncator(truncator.Truncator):
-    """前文回合数阶段器"""
+    """Truncate the conversation message chain to adapt to the LLM message length limit."""
    async def truncate(self, query: core_entities.Query) -> core_entities.Query:
-        """截断"""
+        """Truncate"""
        max_round = query.pipeline_config['ai']['local-agent']['max-round']
        temp_messages = []
        current_round = 0
-        # 从后往前遍历
+        # Traverse from back to front
        for msg in query.messages[::-1]:
            if current_round < max_round:
                temp_messages.append(msg)
@@ -144,23 +144,27 @@ class RuntimePipeline:
                result = await result
            if isinstance(result, pipeline_entities.StageProcessResult):  # 直接返回结果
-                self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} res {result}')
+                self.ap.logger.debug(
                    f'Stage {stage_container.inst_name} processed query {query.query_id} res {result.result_type}'
                )
                await self._check_output(query, result)
                if result.result_type == pipeline_entities.ResultType.INTERRUPT:
-                    self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query}')
+                    self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query.query_id}')
                    break
                elif result.result_type == pipeline_entities.ResultType.CONTINUE:
                    query = result.new_query
            elif isinstance(result, typing.AsyncGenerator):  # 生成器
-                self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} gen')
+                self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query.query_id} gen')
                async for sub_result in result:
-                    self.ap.logger.debug(f'Stage {stage_container.inst_name} processed query {query} res {sub_result}')
+                    self.ap.logger.debug(
                        f'Stage {stage_container.inst_name} processed query {query.query_id} res {sub_result.result_type}'
                    )
                    await self._check_output(query, sub_result)
                    if sub_result.result_type == pipeline_entities.ResultType.INTERRUPT:
-                        self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query}')
+                        self.ap.logger.debug(f'Stage {stage_container.inst_name} interrupted query {query.query_id}')
                        break
                    elif sub_result.result_type == pipeline_entities.ResultType.CONTINUE:
                        query = sub_result.new_query
@@ -192,7 +196,7 @@ class RuntimePipeline:
            if event_ctx.is_prevented_default():
                return
-            self.ap.logger.debug(f'Processing query {query}')
+            self.ap.logger.debug(f'Processing query {query.query_id}')
            await self._execute_from_stage(0, query)
        except Exception as e:
@@ -200,7 +204,7 @@ class RuntimePipeline:
            self.ap.logger.error(f'处理请求时出错 query_id={query.query_id} stage={inst_name} : {e}')
            self.ap.logger.error(f'Traceback: {traceback.format_exc()}')
        finally:
-            self.ap.logger.debug(f'Query {query} processed')
+            self.ap.logger.debug(f'Query {query.query_id} processed')
 class PipelineManager:
@@ -11,11 +11,11 @@ from ...platform.types import message as platform_message
@stage.stage_class('PreProcessor')
 class PreProcessor(stage.PipelineStage):
-    """请求预处理阶段
+    """Request pre-processing stage
-    签出会话、prompt、上文、模型、内容函数。
+    Check out session, prompt, context, model, and content functions.
-    改写：
+    Rewrite:
        - session
        - prompt
        - messages
@@ -29,12 +29,12 @@ class PreProcessor(stage.PipelineStage):
        query: core_entities.Query,
        stage_inst_name: str,
    ) -> entities.StageProcessResult:
-        """处理"""
+        """Process"""
        selected_runner = query.pipeline_config['ai']['runner']['runner']
        session = await self.ap.sess_mgr.get_session(query)
-        # 非 local-agent 时，llm_model 为 None
+        # When not local-agent, llm_model is None
        llm_model = (
            await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
            if selected_runner == 'local-agent'
@@ -51,7 +51,7 @@ class PreProcessor(stage.PipelineStage):
        conversation.use_llm_model = llm_model
-        # 设置query
+        # Set query
        query.session = session
        query.prompt = conversation.prompt.copy()
        query.messages = conversation.messages.copy()
@@ -80,14 +80,15 @@ class PreProcessor(stage.PipelineStage):
                        if me.type == 'image_url':
                            msg.content.remove(me)
-        content_list = []
+        content_list: list[llm_entities.ContentElement] = []
        plain_text = ''
        qoute_msg = query.pipeline_config['trigger'].get('misc', '').get('combine-quote-message')
        # tidy the content_list
        # combine all text content into one, and put it in the first position
        for me in query.message_chain:
            if isinstance(me, platform_message.Plain):
                content_list.append(llm_entities.ContentElement.from_text(me.text))
                plain_text += me.text
            elif isinstance(me, platform_message.Image):
                if selected_runner != 'local-agent' or query.use_llm_model.model_entity.abilities.__contains__(
@@ -106,10 +107,12 @@ class PreProcessor(stage.PipelineStage):
                            if msg.base64 is not None:
                                content_list.append(llm_entities.ContentElement.from_image_base64(msg.base64))
        content_list.insert(0, llm_entities.ContentElement.from_text(plain_text))
        query.variables['user_message_text'] = plain_text
        query.user_message = llm_entities.Message(role='user', content=content_list)
-        # =========== 触发事件 PromptPreProcessing
+        # =========== Trigger event PromptPreProcessing
        event_ctx = await self.ap.plugin_mgr.emit_event(
            event=events.PromptPreProcessing(
@@ -25,7 +25,7 @@ class MessageHandler(metaclass=abc.ABCMeta):
    def cut_str(self, s: str) -> str:
        """
-        取字符串第一行，最多20个字符，若有多行，或超过20个字符，则加省略号
+        Take the first line of the string, up to 20 characters, if there are multiple lines, or more than 20 characters, add an ellipsis
        """
        s0 = s.split('\n')[0]
        if len(s0) > 20 or '\n' in s:
@@ -22,11 +22,11 @@ class ChatMessageHandler(handler.MessageHandler):
        self,
        query: core_entities.Query,
    ) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
-        """处理"""
+        """Process"""
-        # 调API
+        # Call API
-        #   生成器
+        #   generator
-        # 触发插件事件
+        # Trigger plugin event
        event_class = (
            events.PersonNormalMessageReceived
            if query.launcher_type == core_entities.LauncherTypes.PERSON
@@ -54,7 +54,7 @@ class ChatMessageHandler(handler.MessageHandler):
                yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
        else:
            if event_ctx.event.alter is not None:
-                # if isinstance(event_ctx.event, str):  # 现在暂时不考虑多模态alter
+                # if isinstance(event_ctx.event, str):  # Currently not considering multi-modal alter
                query.user_message.content = event_ctx.event.alter
            text_length = 0
@@ -65,12 +65,12 @@ class ChatMessageHandler(handler.MessageHandler):
                        runner = r(self.ap, query.pipeline_config)
                        break
                else:
-                    raise ValueError(f'未找到请求运行器: {query.pipeline_config["ai"]["runner"]["runner"]}')
+                    raise ValueError(f'Request runner not found: {query.pipeline_config["ai"]["runner"]["runner"]}')
                async for result in runner.run(query):
                    query.resp_messages.append(result)
-                    self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
+                    self.ap.logger.info(f'Response({query.query_id}): {self.cut_str(result.readable_str())}')
                    if result.content is not None:
                        text_length += len(result.content)
@@ -80,7 +80,7 @@ class ChatMessageHandler(handler.MessageHandler):
                query.session.using_conversation.messages.append(query.user_message)
                query.session.using_conversation.messages.extend(query.resp_messages)
            except Exception as e:
-                self.ap.logger.error(f'对话({query.query_id})请求失败: {type(e).__name__} {str(e)}')
+                self.ap.logger.error(f'Request failed({query.query_id}): {type(e).__name__} {str(e)}')
                hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
@@ -15,7 +15,7 @@ class CommandHandler(handler.MessageHandler):
        self,
        query: core_entities.Query,
    ) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
-        """处理"""
+        """Process"""
        command_text = str(query.message_chain).strip()[1:]
@@ -70,7 +70,7 @@ class CommandHandler(handler.MessageHandler):
                        )
                    )
-                    self.ap.logger.info(f'命令({query.query_id})报错: {self.cut_str(str(ret.error))}')
+                    self.ap.logger.info(f'Command({query.query_id}) error: {self.cut_str(str(ret.error))}')
                    yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
                elif ret.text is not None or ret.image_url is not None:
@@ -89,7 +89,7 @@ class CommandHandler(handler.MessageHandler):
                        )
                    )
-                    self.ap.logger.info(f'命令返回: {self.cut_str(str(content[0]))}')
+                    self.ap.logger.info(f'Command returned: {self.cut_str(str(content[0]))}')
                    yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
                else:
@@ -33,11 +33,11 @@ class Processor(stage.PipelineStage):
        query: core_entities.Query,
        stage_inst_name: str,
    ) -> entities.StageProcessResult:
-        """处理"""
+        """Process"""
        message_text = str(query.message_chain).strip()
        self.ap.logger.info(
-            f'处理 {query.launcher_type.value}_{query.launcher_id} 的请求({query.query_id}): {message_text}'
+            f'Processing request from {query.launcher_type.value}_{query.launcher_id} ({query.query_id}): {message_text}'
        )
        async def generator():
@@ -76,8 +76,7 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
        return msg_list, msg_id, msg_time
    @staticmethod
-    async def target2yiri(message: str, message_id: int = -1, bot=None):
+    async def target2yiri(message: str, message_id: int = -1, bot: aiocqhttp.CQHttp = None):
        print(message)
        message = aiocqhttp.Message(message)
        def get_face_name(face_id):
@@ -271,16 +270,16 @@ class AiocqhttpMessageConverter(adapter.MessageConverter):
                )
                yiri_msg_list.append(reply_msg)
-            elif msg.type == 'file':
+            # 这里下载所有文件会导致下载文件过多，暂时不下载
-                # file_name = msg.data['file']
+            # elif msg.type == 'file':
-                file_id = msg.data['file_id']
+            #     # file_name = msg.data['file']
-                file_data = await bot.get_file(file_id=file_id)
+            #     file_id = msg.data['file_id']
-                file_name = file_data.get('file_name')
+            #     file_data = await bot.get_file(file_id=file_id)
-                file_path = file_data.get('file')
+            #     file_name = file_data.get('file_name')
-                _ = file_path
+            #     file_path = file_data.get('file')
-                file_url = file_data.get('file_url')
+            #     file_url = file_data.get('file_url')
-                file_size = file_data.get('file_size')
+            #     file_size = file_data.get('file_size')
-                yiri_msg_list.append(platform_message.File(id=file_id, name=file_name, url=file_url, size=file_size))
+            #     yiri_msg_list.append(platform_message.File(id=file_id, name=file_name,url=file_url,size=file_size))
            elif msg.type == 'face':
                face_id = msg.data['id']
                face_name = msg.data['raw']['faceText']
@@ -116,6 +116,15 @@ class DingTalkAdapter(adapter.MessagePlatformAdapter):
        self.bot_account_id = self.config['robot_name']
        self.bot = DingTalkClient(
            client_id=config['client_id'],
            client_secret=config['client_secret'],
            robot_name=config['robot_name'],
            robot_code=config['robot_code'],
            markdown_card=config['markdown_card'],
            logger=self.logger,
        )
    async def reply_message(
        self,
        message_source: platform_events.MessageEvent,
@@ -157,15 +166,6 @@ class DingTalkAdapter(adapter.MessagePlatformAdapter):
            self.bot.on_message('GroupMessage')(on_message)
    async def run_async(self):
        config = self.config
        self.bot = DingTalkClient(
            client_id=config['client_id'],
            client_secret=config['client_secret'],
            robot_name=config['robot_name'],
            robot_code=config['robot_code'],
            markdown_card=config['markdown_card'],
            logger=self.logger,
        )
        await self.bot.start()
    async def kill(self) -> bool:
@@ -8,15 +8,592 @@ import base64
 import uuid
 import os
 import datetime
 import io
 import asyncio
 from enum import Enum
 import aiohttp
 from .. import adapter
 from ...core import app
 from ..logger import EventLogger
 from ..types import message as platform_message
 from ..types import events as platform_events
 from ..types import entities as platform_entities
-from ..logger import EventLogger
+
 # 语音功能相关异常定义
 class VoiceConnectionError(Exception):
    """语音连接基础异常"""
    def __init__(self, message: str, error_code: str = None, guild_id: int = None):
        super().__init__(message)
        self.error_code = error_code
        self.guild_id = guild_id
        self.timestamp = datetime.datetime.now()
 class VoicePermissionError(VoiceConnectionError):
    """语音权限异常"""
    def __init__(self, message: str, missing_permissions: list = None, user_id: int = None, channel_id: int = None):
        super().__init__(message, "PERMISSION_ERROR")
        self.missing_permissions = missing_permissions or []
        self.user_id = user_id
        self.channel_id = channel_id
 class VoiceNetworkError(VoiceConnectionError):
    """语音网络异常"""
    def __init__(self, message: str, retry_count: int = 0):
        super().__init__(message, "NETWORK_ERROR")
        self.retry_count = retry_count
        self.last_attempt = datetime.datetime.now()
 class VoiceConnectionStatus(Enum):
    """语音连接状态枚举"""
    IDLE = "idle"
    CONNECTING = "connecting"
    CONNECTED = "connected"
    PLAYING = "playing"
    RECONNECTING = "reconnecting"
    FAILED = "failed"
 class VoiceConnectionInfo:
    """
    语音连接信息类
    用于存储和管理单个语音连接的详细信息，包括连接状态、时间戳、
    频道信息等。提供连接信息的标准化数据结构。
    @author: @ydzat
    @version: 1.0
    @since: 2025-07-04
    """
    def __init__(self, guild_id: int, channel_id: int, channel_name: str = None):
        """
        初始化语音连接信息
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
            channel_id (int): 语音频道ID
            channel_name (str, optional): 语音频道名称
        """
        self.guild_id = guild_id
        self.channel_id = channel_id
        self.channel_name = channel_name or f"Channel-{channel_id}"
        self.connected = False
        self.connection_time: datetime.datetime = None
        self.last_activity = datetime.datetime.now()
        self.status = VoiceConnectionStatus.IDLE
        self.user_count = 0
        self.latency = 0.0
        self.connection_health = "unknown"
        self.voice_client = None
    def update_status(self, status: VoiceConnectionStatus):
        """
        更新连接状态
        @author: @ydzat
        Args:
            status (VoiceConnectionStatus): 新的连接状态
        """
        self.status = status
        self.last_activity = datetime.datetime.now()
        if status == VoiceConnectionStatus.CONNECTED:
            self.connected = True
            if self.connection_time is None:
                self.connection_time = datetime.datetime.now()
        elif status in [VoiceConnectionStatus.IDLE, VoiceConnectionStatus.FAILED]:
            self.connected = False
            self.connection_time = None
            self.voice_client = None
    def to_dict(self) -> dict:
        """
        转换为字典格式
        @author: @ydzat
        Returns:
            dict: 连接信息的字典表示
        """
        return {
            "guild_id": self.guild_id,
            "channel_id": self.channel_id,
            "channel_name": self.channel_name,
            "connected": self.connected,
            "connection_time": self.connection_time.isoformat() if self.connection_time else None,
            "last_activity": self.last_activity.isoformat(),
            "status": self.status.value,
            "user_count": self.user_count,
            "latency": self.latency,
            "connection_health": self.connection_health
        }
 class VoiceConnectionManager:
    """
    语音连接管理器
    负责管理多个服务器的语音连接，提供连接建立、断开、状态查询等功能。
    采用单例模式确保全局只有一个连接管理器实例。
    @author: @ydzat
    @version: 1.0
    @since: 2025-07-04
    """
    def __init__(self, bot: discord.Client, logger: EventLogger):
        """
        初始化语音连接管理器
        @author: @ydzat
        Args:
            bot (discord.Client): Discord 客户端实例
            logger (EventLogger): 事件日志记录器
        """
        self.bot = bot
        self.logger = logger
        self.connections: typing.Dict[int, VoiceConnectionInfo] = {}
        self._connection_lock = asyncio.Lock()
        self._cleanup_task = None
        self._monitoring_enabled = True
    async def join_voice_channel(self, guild_id: int, channel_id: int, 
                                user_id: int = None) -> discord.VoiceClient:
        """
        加入语音频道
        验证用户权限和频道状态后，建立到指定语音频道的连接。
        支持连接复用和自动重连机制。
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
            channel_id (int): 语音频道ID
            user_id (int, optional): 请求用户ID，用于权限验证
        Returns:
            discord.VoiceClient: 语音客户端实例
        Raises:
            VoicePermissionError: 权限不足时抛出
            VoiceNetworkError: 网络连接失败时抛出
            VoiceConnectionError: 其他连接错误时抛出
        """
        async with self._connection_lock:
            try:
                # 获取服务器和频道对象
                guild = self.bot.get_guild(guild_id)
                if not guild:
                    raise VoiceConnectionError(
                        f"无法找到服务器 {guild_id}",
                        "GUILD_NOT_FOUND",
                        guild_id
                    )
                channel = guild.get_channel(channel_id)
                if not channel or not isinstance(channel, discord.VoiceChannel):
                    raise VoiceConnectionError(
                        f"无法找到语音频道 {channel_id}",
                        "CHANNEL_NOT_FOUND",
                        guild_id
                    )
                # 验证用户是否在语音频道中（如果提供了用户ID）
                if user_id:
                    await self._validate_user_in_channel(guild, channel, user_id)
                # 验证机器人权限
                await self._validate_bot_permissions(channel)
                # 检查是否已有连接
                if guild_id in self.connections:
                    existing_conn = self.connections[guild_id]
                    if existing_conn.connected and existing_conn.voice_client:
                        if existing_conn.channel_id == channel_id:
                            # 已连接到相同频道，返回现有连接
                            await self.logger.info(f"复用现有语音连接: {guild.name} -> {channel.name}")
                            return existing_conn.voice_client
                        else:
                            # 连接到不同频道，先断开旧连接
                            await self._disconnect_internal(guild_id)
                # 建立新连接
                voice_client = await channel.connect()
                # 更新连接信息
                conn_info = VoiceConnectionInfo(guild_id, channel_id, channel.name)
                conn_info.voice_client = voice_client
                conn_info.update_status(VoiceConnectionStatus.CONNECTED)
                conn_info.user_count = len(channel.members)
                self.connections[guild_id] = conn_info
                await self.logger.info(f"成功连接到语音频道: {guild.name} -> {channel.name}")
                return voice_client
            except discord.ClientException as e:
                raise VoiceNetworkError(f"Discord 客户端错误: {str(e)}")
            except discord.opus.OpusNotLoaded as e:
                raise VoiceConnectionError(f"Opus 编码器未加载: {str(e)}", "OPUS_NOT_LOADED", guild_id)
            except Exception as e:
                await self.logger.error(f"连接语音频道时发生未知错误: {str(e)}")
                raise VoiceConnectionError(f"连接失败: {str(e)}", "UNKNOWN_ERROR", guild_id)
    async def leave_voice_channel(self, guild_id: int) -> bool:
        """
        离开语音频道
        断开指定服务器的语音连接，清理相关资源和状态信息。
        确保音频播放停止后再断开连接。
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
        Returns:
            bool: 断开是否成功
        """
        async with self._connection_lock:
            return await self._disconnect_internal(guild_id)
    async def _disconnect_internal(self, guild_id: int) -> bool:
        """
        内部断开连接方法
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
        Returns:
            bool: 断开是否成功
        """
        if guild_id not in self.connections:
            return True
        conn_info = self.connections[guild_id]
        try:
            if conn_info.voice_client and conn_info.voice_client.is_connected():
                # 停止当前播放
                if conn_info.voice_client.is_playing():
                    conn_info.voice_client.stop()
                # 等待播放完全停止
                await asyncio.sleep(0.1)
                # 断开连接
                await conn_info.voice_client.disconnect()
            conn_info.update_status(VoiceConnectionStatus.IDLE)
            del self.connections[guild_id]
            await self.logger.info(f"已断开语音连接: Guild {guild_id}")
            return True
        except Exception as e:
            await self.logger.error(f"断开语音连接时发生错误: {str(e)}")
            # 即使出错也要清理连接记录
            conn_info.update_status(VoiceConnectionStatus.FAILED)
            if guild_id in self.connections:
                del self.connections[guild_id]
            return False
    async def get_voice_client(self, guild_id: int) -> typing.Optional[discord.VoiceClient]:
        """
        获取语音客户端
        返回指定服务器的语音客户端实例，如果未连接则返回 None。
        会验证连接的有效性，自动清理无效连接。
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
        Returns:
            Optional[discord.VoiceClient]: 语音客户端实例或 None
        """
        if guild_id not in self.connections:
            return None
        conn_info = self.connections[guild_id]
        # 验证连接是否仍然有效
        if conn_info.voice_client and not conn_info.voice_client.is_connected():
            # 连接已失效，清理状态
            await self._disconnect_internal(guild_id)
            return None
        return conn_info.voice_client if conn_info.connected else None
    async def is_connected_to_voice(self, guild_id: int) -> bool:
        """
        检查是否连接到语音频道
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
        Returns:
            bool: 是否已连接
        """
        if guild_id not in self.connections:
            return False
        conn_info = self.connections[guild_id]
        # 检查实际连接状态
        if conn_info.voice_client and not conn_info.voice_client.is_connected():
            # 连接已失效，清理状态
            await self._disconnect_internal(guild_id)
            return False
        return conn_info.connected
    async def get_connection_status(self, guild_id: int) -> typing.Optional[dict]:
        """
        获取连接状态信息
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
        Returns:
            Optional[dict]: 连接状态信息字典或 None
        """
        if guild_id not in self.connections:
            return None
        conn_info = self.connections[guild_id]
        # 更新实时信息
        if conn_info.voice_client and conn_info.voice_client.is_connected():
            conn_info.latency = conn_info.voice_client.latency * 1000  # 转换为毫秒
            conn_info.connection_health = "good" if conn_info.latency < 100 else "poor"
            # 更新频道用户数
            guild = self.bot.get_guild(guild_id)
            if guild:
                channel = guild.get_channel(conn_info.channel_id)
                if channel and isinstance(channel, discord.VoiceChannel):
                    conn_info.user_count = len(channel.members)
        return conn_info.to_dict()
    async def list_active_connections(self) -> typing.List[dict]:
        """
        列出所有活跃连接
        @author: @ydzat
        Returns:
            List[dict]: 活跃连接列表
        """
        active_connections = []
        for guild_id, conn_info in self.connections.items():
            if conn_info.connected:
                status = await self.get_connection_status(guild_id)
                if status:
                    active_connections.append(status)
        return active_connections
    async def get_voice_channel_info(self, guild_id: int, channel_id: int) -> typing.Optional[dict]:
        """
        获取语音频道信息
        @author: @ydzat
        Args:
            guild_id (int): 服务器ID
            channel_id (int): 频道ID
        Returns:
            Optional[dict]: 频道信息字典或 None
        """
        guild = self.bot.get_guild(guild_id)
        if not guild:
            return None
        channel = guild.get_channel(channel_id)
        if not channel or not isinstance(channel, discord.VoiceChannel):
            return None
        # 获取用户信息
        users = []
        for member in channel.members:
            users.append({
                "id": member.id,
                "name": member.display_name,
                "status": str(member.status),
                "is_bot": member.bot
            })
        # 获取权限信息
        bot_member = guild.me
        permissions = channel.permissions_for(bot_member)
        return {
            "channel_id": channel_id,
            "channel_name": channel.name,
            "guild_id": guild_id,
            "guild_name": guild.name,
            "user_limit": channel.user_limit,
            "current_users": users,
            "user_count": len(users),
            "bitrate": channel.bitrate,
            "permissions": {
                "connect": permissions.connect,
                "speak": permissions.speak,
                "use_voice_activation": permissions.use_voice_activation,
                "priority_speaker": permissions.priority_speaker
            }
        }
    async def _validate_user_in_channel(self, guild: discord.Guild, 
                                       channel: discord.VoiceChannel, user_id: int):
        """
        验证用户是否在语音频道中
        @author: @ydzat
        Args:
            guild: Discord 服务器对象
            channel: 语音频道对象
            user_id: 用户ID
        Raises:
            VoicePermissionError: 用户不在频道中时抛出
        """
        member = guild.get_member(user_id)
        if not member:
            raise VoicePermissionError(
                f"无法找到用户 {user_id}",
                ["member_not_found"],
                user_id,
                channel.id
            )
        if not member.voice or member.voice.channel != channel:
            raise VoicePermissionError(
                f"用户 {member.display_name} 不在语音频道 {channel.name} 中",
                ["user_not_in_channel"],
                user_id,
                channel.id
            )
    async def _validate_bot_permissions(self, channel: discord.VoiceChannel):
        """
        验证机器人权限
        @author: @ydzat
        Args:
            channel: 语音频道对象
        Raises:
            VoicePermissionError: 权限不足时抛出
        """
        bot_member = channel.guild.me
        permissions = channel.permissions_for(bot_member)
        missing_permissions = []
        if not permissions.connect:
            missing_permissions.append("connect")
        if not permissions.speak:
            missing_permissions.append("speak")
        if missing_permissions:
            raise VoicePermissionError(
                f"机器人在频道 {channel.name} 中缺少权限: {', '.join(missing_permissions)}",
                missing_permissions,
                channel_id=channel.id
            )
    async def cleanup_inactive_connections(self):
        """
        清理无效连接
        定期检查并清理已断开或无效的语音连接，释放资源。
        @author: @ydzat
        """
        cleanup_guilds = []
        for guild_id, conn_info in self.connections.items():
            if not conn_info.voice_client or not conn_info.voice_client.is_connected():
                cleanup_guilds.append(guild_id)
        for guild_id in cleanup_guilds:
            await self._disconnect_internal(guild_id)
        if cleanup_guilds:
            await self.logger.info(f"清理了 {len(cleanup_guilds)} 个无效的语音连接")
    async def start_monitoring(self):
        """
        开始连接监控
        @author: @ydzat
        """
        if self._cleanup_task is None and self._monitoring_enabled:
            self._cleanup_task = asyncio.create_task(self._monitoring_loop())
    async def stop_monitoring(self):
        """
        停止连接监控
        @author: @ydzat
        """
        self._monitoring_enabled = False
        if self._cleanup_task:
            self._cleanup_task.cancel()
            try:
                await self._cleanup_task
            except asyncio.CancelledError:
                pass
            self._cleanup_task = None
    async def _monitoring_loop(self):
        """
        监控循环
        @author: @ydzat
        """
        try:
            while self._monitoring_enabled:
                await asyncio.sleep(60)  # 每分钟检查一次
                await self.cleanup_inactive_connections()
        except asyncio.CancelledError:
            pass
    async def disconnect_all(self):
        """
        断开所有连接
        @author: @ydzat
        """
        async with self._connection_lock:
            guild_ids = list(self.connections.keys())
            for guild_id in guild_ids:
                await self._disconnect_internal(guild_id)
        await self.stop_monitoring()
 class DiscordMessageConverter(adapter.MessageConverter):
@@ -238,6 +815,9 @@ class DiscordAdapter(adapter.MessagePlatformAdapter):
        self.logger = logger
        self.bot_account_id = self.config['client_id']
        # 初始化语音连接管理器
        self.voice_manager: VoiceConnectionManager = None
        adapter_self = self
@@ -258,6 +838,169 @@ class DiscordAdapter(adapter.MessagePlatformAdapter):
            args['proxy'] = os.getenv('http_proxy')
        self.bot = MyClient(intents=intents, **args)
    # Voice functionality methods
    async def join_voice_channel(self, guild_id: int, channel_id: int, 
                                user_id: int = None) -> discord.VoiceClient:
        """
        加入语音频道
        为指定服务器的语音频道建立连接，支持用户权限验证和连接复用。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
            channel_id (int): 语音频道ID
            user_id (int, optional): 请求用户ID，用于权限验证
        Returns:
            discord.VoiceClient: 语音客户端实例
        Raises:
            VoicePermissionError: 权限不足
            VoiceNetworkError: 网络连接失败
            VoiceConnectionError: 其他连接错误
        """
        if not self.voice_manager:
            raise VoiceConnectionError("语音管理器未初始化", "MANAGER_NOT_READY")
        return await self.voice_manager.join_voice_channel(guild_id, channel_id, user_id)
    async def leave_voice_channel(self, guild_id: int) -> bool:
        """
        离开语音频道
        断开指定服务器的语音连接，清理相关资源。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
        Returns:
            bool: 是否成功断开连接
        """
        if not self.voice_manager:
            return False
        return await self.voice_manager.leave_voice_channel(guild_id)
    async def get_voice_client(self, guild_id: int) -> typing.Optional[discord.VoiceClient]:
        """
        获取语音客户端
        返回指定服务器的语音客户端实例，用于音频播放控制。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
        Returns:
            Optional[discord.VoiceClient]: 语音客户端实例或 None
        """
        if not self.voice_manager:
            return None
        return await self.voice_manager.get_voice_client(guild_id)
    async def is_connected_to_voice(self, guild_id: int) -> bool:
        """
        检查语音连接状态
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
        Returns:
            bool: 是否已连接到语音频道
        """
        if not self.voice_manager:
            return False
        return await self.voice_manager.is_connected_to_voice(guild_id)
    async def get_voice_connection_status(self, guild_id: int) -> typing.Optional[dict]:
        """
        获取语音连接详细状态
        返回包含连接时间、延迟、用户数等详细信息的状态字典。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
        Returns:
            Optional[dict]: 连接状态信息或 None
        """
        if not self.voice_manager:
            return None
        return await self.voice_manager.get_connection_status(guild_id)
    async def list_active_voice_connections(self) -> typing.List[dict]:
        """
        列出所有活跃的语音连接
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Returns:
            List[dict]: 活跃语音连接列表
        """
        if not self.voice_manager:
            return []
        return await self.voice_manager.list_active_connections()
    async def get_voice_channel_info(self, guild_id: int, channel_id: int) -> typing.Optional[dict]:
        """
        获取语音频道详细信息
        包括频道名称、用户列表、权限信息等。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        Args:
            guild_id (int): Discord 服务器ID
            channel_id (int): 语音频道ID
        Returns:
            Optional[dict]: 频道信息字典或 None
        """
        if not self.voice_manager:
            return None
        return await self.voice_manager.get_voice_channel_info(guild_id, channel_id)
    async def cleanup_voice_connections(self):
        """
        清理无效的语音连接
        手动触发语音连接清理，移除已断开或无效的连接。
        @author: @ydzat
        @version: 1.0
        @since: 2025-07-04
        """
        if self.voice_manager:
            await self.voice_manager.cleanup_inactive_connections()
    async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
        msg_to_send, image_files = await self.message_converter.yiri2target(message)
@@ -324,9 +1067,32 @@ class DiscordAdapter(adapter.MessagePlatformAdapter):
        self.listeners.pop(event_type)
    async def run_async(self):
        """
        启动 Discord 适配器
        初始化语音管理器并启动 Discord 客户端连接。
        @author: @ydzat (修改)
        """
        async with self.bot:
            # 初始化语音管理器
            self.voice_manager = VoiceConnectionManager(self.bot, self.logger)
            await self.voice_manager.start_monitoring()
            await self.logger.info("Discord 适配器语音功能已启用")
            await self.bot.start(self.config['token'], reconnect=True)
    async def kill(self) -> bool:
        """
        关闭 Discord 适配器
        清理语音连接并关闭 Discord 客户端。
        @author: @ydzat (修改)
        """
        if self.voice_manager:
            await self.voice_manager.disconnect_all()
        await self.bot.close()
        return True
@@ -29,18 +29,21 @@ import logging
 class WeChatPadMessageConverter(adapter.MessageConverter):
-    def __init__(self, config: dict):
+
    def __init__(self, config: dict, logger: logging.Logger):
        self.config = config
-        self.bot = WeChatPadClient(self.config['wechatpad_url'], self.config['token'])
+        self.bot = WeChatPadClient(self.config["wechatpad_url"],self.config["token"])
-        self.logger = logging.getLogger('WeChatPadMessageConverter')
+        self.logger = logger
    @staticmethod
    async def yiri2target(message_chain: platform_message.MessageChain) -> list[dict]:
        content_list = []
        for component in message_chain:
-            if isinstance(component, platform_message.At):
+            if isinstance(component, platform_message.AtAll):
-                content_list.append({'type': 'at', 'target': component.target})
+                content_list.append({"type": "at", "target": "all"})
            elif isinstance(component, platform_message.At):
                content_list.append({"type": "at", "target": component.target})
            elif isinstance(component, platform_message.Plain):
                content_list.append({'type': 'text', 'content': component.text})
            elif isinstance(component, platform_message.Image):
@@ -73,20 +76,34 @@ class WeChatPadMessageConverter(adapter.MessageConverter):
        return content_list
-    async def target2yiri(self, message: dict, bot_account_id: str) -> platform_message.MessageChain:
+    async def target2yiri(
            self,
            message: dict,
            bot_account_id: str,
    ) -> platform_message.MessageChain:
        """外部消息转平台消息"""
        # 数据预处理
        message_list = []
        bot_wxid = self.config['wxid']
        ats_bot = False  # 是否被@
        content = message['content']['str']
        content_no_preifx = content  # 群消息则去掉前缀
        is_group_message = self._is_group_message(message)
        if is_group_message:
            ats_bot = self._ats_bot(message, bot_account_id)
-            if '@所有人' in content:
+
            self.logger.info(f"ats_bot: {ats_bot}; bot_account_id: {bot_account_id}; bot_wxid: {bot_wxid}")
            if "@所有人" in content:
                message_list.append(platform_message.AtAll())
-            elif ats_bot:
+            if ats_bot:
                message_list.append(platform_message.At(target=bot_account_id))
            # 解析@信息并生成At组件
            at_targets = self._extract_at_targets(message)
            for target_id in at_targets:
                if target_id != bot_wxid:  # 避免重复添加机器人的At
                    message_list.append(platform_message.At(target=target_id))
            content_no_preifx, _ = self._extract_content_and_sender(content)
        msg_type = message['msg_type']
@@ -395,6 +412,23 @@ class WeChatPadMessageConverter(adapter.MessageConverter):
        finally:
            return ats_bot
    # 提取一下at的wxid列表
    def _extract_at_targets(self, message: dict) -> list[str]:
        """从消息中提取被@用户的ID列表"""
        at_targets = []
        try:
            # 从msg_source中解析atuserlist
            msg_source = message.get('msg_source', '') or ''
            if len(msg_source) > 0:
                msg_source_data = ET.fromstring(msg_source)
                at_user_list = msg_source_data.findtext("atuserlist") or ""
                if at_user_list:
                    # atuserlist格式通常是逗号分隔的用户ID列表
                    at_targets = [user_id.strip() for user_id in at_user_list.split(',') if user_id.strip()]
        except Exception as e:
            self.logger.error(f"_extract_at_targets got except: {e}")
        return at_targets
    # 提取一下content前面的sender_id, 和去掉前缀的内容
    def _extract_content_and_sender(self, raw_content: str) -> Tuple[str, Optional[str]]:
        try:
@@ -418,16 +452,22 @@ class WeChatPadMessageConverter(adapter.MessageConverter):
 class WeChatPadEventConverter(adapter.EventConverter):
    def __init__(self, config: dict):
        self.config = config
        self.message_converter = WeChatPadMessageConverter(config)
        self.logger = logging.getLogger('WeChatPadEventConverter')
    def __init__(self, config: dict, logger: logging.Logger):
        self.config = config
        self.message_converter = WeChatPadMessageConverter(config, logger)
        self.logger = logger
    @staticmethod
    async def yiri2target(event: platform_events.MessageEvent) -> dict:
        pass
-    async def target2yiri(self, event: dict, bot_account_id: str) -> platform_events.MessageEvent:
+    async def target2yiri(
            self,
            event: dict,
            bot_account_id: str,
    ) -> platform_events.MessageEvent:
        # 排除公众号以及微信团队消息
        if (
            event['from_user_name']['str'].startswith('gh_')
@@ -503,8 +543,8 @@ class WeChatPadAdapter(adapter.MessagePlatformAdapter):
        self.logger = logger
        self.quart_app = quart.Quart(__name__)
-        self.message_converter = WeChatPadMessageConverter(config)
+        self.message_converter = WeChatPadMessageConverter(config, ap.logger)
-        self.event_converter = WeChatPadEventConverter(config)
+        self.event_converter = WeChatPadEventConverter(config, ap.logger)
    async def ws_message(self, data):
        """处理接收到的消息"""
@@ -539,19 +579,26 @@ class WeChatPadAdapter(adapter.MessagePlatformAdapter):
        for msg in content_list:
            # 文本消息处理@
            if msg['type'] == 'text' and at_targets:
-                at_nick_name_list = []
+                if "all" in at_targets:
-                for member in member_info:
+                    msg['content'] = f'@所有人 {msg["content"]}'
-                    if member['user_name'] in at_targets:
+                else:
-                        at_nick_name_list.append(f'@{member["nick_name"]}')
+                    at_nick_name_list = []
-                msg['content'] = f'{" ".join(at_nick_name_list)} {msg["content"]}'
+                    for member in member_info:
                        if member["user_name"] in at_targets:
                            at_nick_name_list.append(f'@{member["nick_name"]}')
                    msg['content'] = f'{" ".join(at_nick_name_list)} {msg["content"]}'
            # 统一消息派发
            handler_map = {
                'text': lambda msg: self.bot.send_text_message(
-                    to_wxid=target_id, message=msg['content'], ats=at_targets
+                    to_wxid=target_id,
                    message=msg['content'],
                    ats= ["notify@all"] if "all" in at_targets else at_targets
                ),
                'image': lambda msg: self.bot.send_image_message(
-                    to_wxid=target_id, img_url=msg['image'], ats=at_targets
+                    to_wxid=target_id,
                    img_url=msg["image"],
                    ats = ["notify@all"] if "all" in at_targets else at_targets
                ),
                'WeChatEmoji': lambda msg: self.bot.send_emoji_message(
                    to_wxid=target_id, emoji_md5=msg['emoji_md5'], emoji_size=msg['emoji_size']
@@ -101,18 +101,18 @@ class ProviderAPIRequester(metaclass=abc.ABCMeta):
    async def invoke_embedding(
        self,
        model: RuntimeEmbeddingModel,
-        input_text: str,
+        input_text: list[str],
        extra_args: dict[str, typing.Any] = {},
-    ) -> list[float]:
+    ) -> list[list[float]]:
        """调用 Embedding API
        Args:
            query (core_entities.Query): 请求上下文
            model (RuntimeEmbeddingModel): 使用的模型信息
-            input_text (str): 输入文本
+            input_text (list[str]): 输入文本
            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
        Returns:
-            list[float]: 返回的 embedding 向量
+            list[list[float]]: 返回的 embedding 向量
        """
        pass
@@ -7,7 +7,7 @@ from . import chatcmpl
 class AI302ChatCompletions(chatcmpl.OpenAIChatCompletions):
-    """302 AI ChatCompletion API 请求器"""
+    """302.AI ChatCompletion API 请求器"""
    client: openai.AsyncClient
@@ -145,9 +145,9 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
    async def invoke_embedding(
        self,
        model: requester.RuntimeEmbeddingModel,
-        input_text: str,
+        input_text: list[str],
        extra_args: dict[str, typing.Any] = {},
-    ) -> list[float]:
+    ) -> list[list[float]]:
        """调用 Embedding API"""
        self.client.api_key = model.token_mgr.get_token()
@@ -163,7 +163,8 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
        try:
            resp = await self.client.embeddings.create(**args)
-            return resp.data[0].embedding
+
            return [d.embedding for d in resp.data]
        except asyncio.TimeoutError:
            raise errors.RequesterError('请求超时')
        except openai.BadRequestError as e:
@@ -1,13 +1,28 @@
 from __future__ import annotations
 import json
 import copy
 import typing
 from .. import runner
 from ...core import entities as core_entities
 from .. import entities as llm_entities
 rag_combined_prompt_template = """
 The following are relevant context entries retrieved from the knowledge base. 
 Please use them to answer the user's message. 
 Respond in the same language as the user's input.
 <context>
 {rag_context}
 </context>
 <user_message>
 {user_message}
 </user_message>
 """
@runner.runner_class('local-agent')
 class LocalAgentRunner(runner.RequestRunner):
    """本地Agent请求运行器"""
@@ -16,7 +31,54 @@ class LocalAgentRunner(runner.RequestRunner):
        """运行请求"""
        pending_tool_calls = []
-        req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
+        kb_uuid = query.pipeline_config['ai']['local-agent']['knowledge-base']
        if kb_uuid == '__none__':
            kb_uuid = None
        user_message = copy.deepcopy(query.user_message)
        user_message_text = ''
        if isinstance(user_message.content, str):
            user_message_text = user_message.content
        elif isinstance(user_message.content, list):
            for ce in user_message.content:
                if ce.type == 'text':
                    user_message_text += ce.text
                    break
        if kb_uuid and user_message_text:
            # only support text for now
            kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
            if not kb:
                self.ap.logger.warning(f'Knowledge base {kb_uuid} not found')
                raise ValueError(f'Knowledge base {kb_uuid} not found')
            result = await kb.retrieve(user_message_text)
            final_user_message_text = ''
            if result:
                rag_context = '\n\n'.join(
                    f'[{i + 1}] {entry.metadata.get("text", "")}' for i, entry in enumerate(result)
                )
                final_user_message_text = rag_combined_prompt_template.format(
                    rag_context=rag_context, user_message=user_message_text
                )
            else:
                final_user_message_text = user_message_text
            self.ap.logger.debug(f'Final user message text: {final_user_message_text}')
            for ce in user_message.content:
                if ce.type == 'text':
                    ce.text = final_user_message_text
                    break
        req_messages = query.prompt.messages.copy() + query.messages.copy() + [user_message]
        # 首次请求
        msg = await query.use_llm_model.requester.invoke_llm(
@@ -0,0 +1,212 @@
 from __future__ import annotations
 import traceback
 import uuid
 from .services import parser, chunker
 from pkg.core import app
 from pkg.rag.knowledge.services.embedder import Embedder
 from pkg.rag.knowledge.services.retriever import Retriever
 import sqlalchemy
 from ...entity.persistence import rag as persistence_rag
 from pkg.core import taskmgr
 from ...entity.rag import retriever as retriever_entities
 class RuntimeKnowledgeBase:
    ap: app.Application
    knowledge_base_entity: persistence_rag.KnowledgeBase
    parser: parser.FileParser
    chunker: chunker.Chunker
    embedder: Embedder
    retriever: Retriever
    def __init__(self, ap: app.Application, knowledge_base_entity: persistence_rag.KnowledgeBase):
        self.ap = ap
        self.knowledge_base_entity = knowledge_base_entity
        self.parser = parser.FileParser(ap=self.ap)
        self.chunker = chunker.Chunker(ap=self.ap)
        self.embedder = Embedder(ap=self.ap)
        self.retriever = Retriever(ap=self.ap)
        # 传递kb_id给retriever
        self.retriever.kb_id = knowledge_base_entity.uuid
    async def initialize(self):
        pass
    async def _store_file_task(self, file: persistence_rag.File, task_context: taskmgr.TaskContext):
        try:
            # set file status to processing
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='processing')
            )
            task_context.set_current_action('Parsing file')
            # parse file
            text = await self.parser.parse(file.file_name, file.extension)
            if not text:
                raise Exception(f'No text extracted from file {file.file_name}')
            task_context.set_current_action('Chunking file')
            # chunk file
            chunks_texts = await self.chunker.chunk(text)
            if not chunks_texts:
                raise Exception(f'No chunks extracted from file {file.file_name}')
            task_context.set_current_action('Embedding chunks')
            embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(
                self.knowledge_base_entity.embedding_model_uuid
            )
            # embed chunks
            await self.embedder.embed_and_store(
                kb_id=self.knowledge_base_entity.uuid,
                file_id=file.uuid,
                chunks=chunks_texts,
                embedding_model=embedding_model,
            )
            # set file status to completed
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='completed')
            )
        except Exception as e:
            self.ap.logger.error(f'Error storing file {file.uuid}: {e}')
            traceback.print_exc()
            # set file status to failed
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='failed')
            )
            raise
    async def store_file(self, file_id: str) -> str:
        # pre checking
        if not await self.ap.storage_mgr.storage_provider.exists(file_id):
            raise Exception(f'File {file_id} not found')
        file_uuid = str(uuid.uuid4())
        kb_id = self.knowledge_base_entity.uuid
        file_name = file_id
        extension = file_name.split('.')[-1]
        file_obj_data = {
            'uuid': file_uuid,
            'kb_id': kb_id,
            'file_name': file_name,
            'extension': extension,
            'status': 'pending',
        }
        file_obj = persistence_rag.File(**file_obj_data)
        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(file_obj_data))
        # run background task asynchronously
        ctx = taskmgr.TaskContext.new()
        wrapper = self.ap.task_mgr.create_user_task(
            self._store_file_task(file_obj, task_context=ctx),
            kind='knowledge-operation',
            name=f'knowledge-store-file-{file_id}',
            label=f'Store file {file_id}',
            context=ctx,
        )
        return wrapper.id
    async def retrieve(self, query: str) -> list[retriever_entities.RetrieveResultEntry]:
        embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(
            self.knowledge_base_entity.embedding_model_uuid
        )
        return await self.retriever.retrieve(self.knowledge_base_entity.uuid, query, embedding_model)
    async def delete_file(self, file_id: str):
        # delete vector
        await self.ap.vector_db_mgr.vector_db.delete_by_file_id(self.knowledge_base_entity.uuid, file_id)
        # delete chunk
        await self.ap.persistence_mgr.execute_async(
            sqlalchemy.delete(persistence_rag.Chunk).where(persistence_rag.Chunk.file_id == file_id)
        )
        await self.ap.persistence_mgr.execute_async(
            sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file_id)
        )
    async def dispose(self):
        await self.ap.vector_db_mgr.vector_db.delete_collection(self.knowledge_base_entity.uuid)
 class RAGManager:
    ap: app.Application
    knowledge_bases: list[RuntimeKnowledgeBase]
    def __init__(self, ap: app.Application):
        self.ap = ap
        self.knowledge_bases = []
    async def initialize(self):
        await self.load_knowledge_bases_from_db()
    async def load_knowledge_bases_from_db(self):
        self.ap.logger.info('Loading knowledge bases from db...')
        self.knowledge_bases = []
        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
        knowledge_bases = result.all()
        for knowledge_base in knowledge_bases:
            try:
                await self.load_knowledge_base(knowledge_base)
            except Exception as e:
                self.ap.logger.error(
                    f'Error loading knowledge base {knowledge_base.uuid}: {e}\n{traceback.format_exc()}'
                )
    async def load_knowledge_base(
        self,
        knowledge_base_entity: persistence_rag.KnowledgeBase | sqlalchemy.Row | dict,
    ) -> RuntimeKnowledgeBase:
        if isinstance(knowledge_base_entity, sqlalchemy.Row):
            knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity._mapping)
        elif isinstance(knowledge_base_entity, dict):
            knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity)
        runtime_knowledge_base = RuntimeKnowledgeBase(ap=self.ap, knowledge_base_entity=knowledge_base_entity)
        await runtime_knowledge_base.initialize()
        self.knowledge_bases.append(runtime_knowledge_base)
        return runtime_knowledge_base
    async def get_knowledge_base_by_uuid(self, kb_uuid: str) -> RuntimeKnowledgeBase | None:
        for kb in self.knowledge_bases:
            if kb.knowledge_base_entity.uuid == kb_uuid:
                return kb
        return None
    async def remove_knowledge_base_from_runtime(self, kb_uuid: str):
        for kb in self.knowledge_bases:
            if kb.knowledge_base_entity.uuid == kb_uuid:
                self.knowledge_bases.remove(kb)
                return
    async def delete_knowledge_base(self, kb_uuid: str):
        for kb in self.knowledge_bases:
            if kb.knowledge_base_entity.uuid == kb_uuid:
                await kb.dispose()
                self.knowledge_bases.remove(kb)
                return
@@ -1,408 +0,0 @@
 from __future__ import annotations
 import os
 import asyncio
 import traceback
 import uuid
 from pkg.rag.knowledge.services.parser import FileParser
 from pkg.rag.knowledge.services.chunker import Chunker
 from pkg.rag.knowledge.services.database import (
    KnowledgeBase,
    File,
    Chunk,
 )
 from pkg.core import app
 from pkg.rag.knowledge.services.embedder import Embedder
 from pkg.rag.knowledge.services.retriever import Retriever
 from pkg.rag.knowledge.services.chroma_manager import ChromaIndexManager
 from pkg.core import taskmgr
 from ...entity.persistence import rag as persistence_rag
 import sqlalchemy
 class RuntimeKnowledgeBase:
    ap: app.Application
    knowledge_base_entity: persistence_rag.KnowledgeBase
    chroma_manager: ChromaIndexManager
    parser: FileParser
    chunker: Chunker
    embedder: Embedder
    retriever: Retriever
    def __init__(self, ap: app.Application, knowledge_base_entity: persistence_rag.KnowledgeBase):
        self.ap = ap
        self.knowledge_base_entity = knowledge_base_entity
        self.chroma_manager = ChromaIndexManager(ap=self.ap)
        self.parser = FileParser(ap=self.ap)
        self.chunker = Chunker(ap=self.ap)
        self.embedder = Embedder(ap=self.ap, chroma_manager=self.chroma_manager)
        self.retriever = Retriever(ap=self.ap, chroma_manager=self.chroma_manager)
    async def initialize(self):
        pass
    async def _store_file_task(self, file: persistence_rag.File, task_context: taskmgr.TaskContext):
        try:
            # set file status to processing
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='processing')
            )
            task_context.set_current_action('Parsing file')
            # parse file
            text = await self.parser.parse(file.file_name, file.extension)
            if not text:
                raise Exception(f'No text extracted from file {file.file_name}')
            task_context.set_current_action('Chunking file')
            # chunk file
            chunks_texts = await self.chunker.chunk(text)
            if not chunks_texts:
                raise Exception(f'No chunks extracted from file {file.file_name}')
            task_context.set_current_action('Embedding chunks')
            # embed chunks
            await self.embedder.embed_and_store(
                file_id=file.uuid, chunks=chunks_texts, embedding_model=self.knowledge_base_entity.embedding_model_uuid
            )
            # set file status to completed
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='completed')
            )
        except Exception as e:
            self.ap.logger.error(f'Error storing file {file.file_id}: {e}')
            # set file status to failed
            await self.ap.persistence_mgr.execute_async(
                sqlalchemy.update(persistence_rag.File)
                .where(persistence_rag.File.uuid == file.uuid)
                .values(status='failed')
            )
            raise
    async def store_file(self, file_id: str) -> int:
        # pre checking
        if not await self.ap.storage_mgr.storage_provider.exists(file_id):
            raise Exception(f'File {file_id} not found')
        file_uuid = str(uuid.uuid4())
        kb_id = self.knowledge_base_entity.uuid
        file_name = file_id
        extension = os.path.splitext(file_id)[1].lstrip('.')
        file = persistence_rag.File(
            uuid=file_uuid,
            kb_id=kb_id,
            file_name=file_name,
            extension=extension,
            status='pending',
        )
        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(**file.to_dict()))
        # run background task asynchronously
        ctx = taskmgr.TaskContext.new()
        wrapper = self.ap.task_mgr.create_user_task(
            self._store_file_task(file, task_context=ctx),
            kind='knowledge-operation',
            name=f'knowledge-store-file-{file_id}',
            label=f'Store file {file_id}',
            context=ctx,
        )
        return wrapper.id
    async def dispose(self):
        pass
 class RAGManager:
    ap: app.Application
    knowledge_bases: list[RuntimeKnowledgeBase]
    def __init__(self, ap: app.Application):
        self.ap = ap
        self.knowledge_bases = []
    async def initialize(self):
        pass
    async def load_knowledge_bases_from_db(self):
        self.ap.logger.info('Loading knowledge bases from db...')
        self.knowledge_bases = []
        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
        knowledge_bases = result.all()
        for knowledge_base in knowledge_bases:
            try:
                await self.load_knowledge_base(knowledge_base)
            except Exception as e:
                self.ap.logger.error(
                    f'Error loading knowledge base {knowledge_base.uuid}: {e}\n{traceback.format_exc()}'
                )
    async def load_knowledge_base(
        self,
        knowledge_base_entity: persistence_rag.KnowledgeBase | sqlalchemy.Row | dict,
    ) -> RuntimeKnowledgeBase:
        if isinstance(knowledge_base_entity, sqlalchemy.Row):
            knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity._mapping)
        elif isinstance(knowledge_base_entity, dict):
            knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity)
        runtime_knowledge_base = RuntimeKnowledgeBase(ap=self.ap, knowledge_base_entity=knowledge_base_entity)
        await runtime_knowledge_base.initialize()
        self.knowledge_bases.append(runtime_knowledge_base)
        return runtime_knowledge_base
    async def get_knowledge_base_by_uuid(self, kb_uuid: str) -> RuntimeKnowledgeBase | None:
        for kb in self.knowledge_bases:
            if kb.knowledge_base_entity.uuid == kb_uuid:
                return kb
        return None
    async def remove_knowledge_base(self, kb_uuid: str):
        for kb in self.knowledge_bases:
            if kb.knowledge_base_entity.uuid == kb_uuid:
                await kb.dispose()
                self.knowledge_bases.remove(kb)
                return
    async def store_data(self, file_path: str, kb_id: str, file_type: str, file_id: str = None):
        """
        Parses, chunks, embeds, and stores data from a given file into the RAG system.
        Associates the file with a knowledge base using kb_id in the File table.
        """
        self.ap.logger.info(f'Starting data storage process for file: {file_path}')
        session = SessionLocal()
        file_obj = None
        try:
            kb = session.query(KnowledgeBase).filter_by(id=kb_id).first()
            if not kb:
                self.ap.logger.info(f'Knowledge Base "{kb_id}" does not exist. ')
                return
            # get embedding model
            embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(kb.embedding_model_uuid)
            file_name = os.path.basename(file_path)
            text = await self.parser.parse(file_path)
            if not text:
                self.ap.logger.warning(f'No text extracted from file {file_path}. ')
                return
            chunks_texts = await self.chunker.chunk(text)
            self.ap.logger.info(f"Chunked file '{file_name}' into {len(chunks_texts)} chunks.")
            await self.embedder.embed_and_store(file_id=file_id, chunks=chunks_texts, embedding_model=embedding_model)
            self.ap.logger.info(f'Data storage process completed for file: {file_path}')
        except Exception as e:
            session.rollback()
            self.ap.logger.error(f'Error in store_data for file {file_path}: {str(e)}', exc_info=True)
            raise
        finally:
            if file_id:
                file_obj = session.query(File).filter_by(id=file_id).first()
            if file_obj:
                file_obj.status = 1
            session.close()
    async def retrieve_data(self, query: str):
        """
        Retrieves relevant data chunks based on a given query using the configured retriever.
        """
        self.ap.logger.info(f"Starting data retrieval process for query: '{query}'")
        try:
            retrieved_chunks = await self.retriever.retrieve(query)
            self.ap.logger.info(f'Successfully retrieved {len(retrieved_chunks)} chunks for query.')
            return retrieved_chunks
        except Exception as e:
            self.ap.logger.error(f"Error in retrieve_data for query '{query}': {str(e)}", exc_info=True)
            return []
    async def delete_data_by_file_id(self, file_id: str):
        """
        Deletes all data associated with a specific file ID, including its chunks and vectors,
        and the file record itself.
        """
        self.ap.logger.info(f'Starting data deletion process for file_id: {file_id}')
        session = SessionLocal()
        try:
            # delete vectors
            await asyncio.to_thread(self.chroma_manager.delete_by_file_id_sync, file_id)
            self.ap.logger.info(f'Deleted embeddings from ChromaDB for file_id: {file_id}')
            chunks_to_delete = session.query(Chunk).filter_by(file_id=file_id).all()
            for chunk in chunks_to_delete:
                session.delete(chunk)
            self.ap.logger.info(f'Deleted {len(chunks_to_delete)} chunk records for file_id: {file_id}')
            file_to_delete = session.query(File).filter_by(id=file_id).first()
            if file_to_delete:
                session.delete(file_to_delete)
                try:
                    await self.ap.storage_mgr.storage_provider.delete(file_id)
                except Exception as e:
                    self.ap.logger.error(
                        f'Error deleting file from storage for file_id {file_id}: {str(e)}',
                        exc_info=True,
                    )
                self.ap.logger.info(f'Deleted file record for file_id: {file_id}')
            else:
                self.ap.logger.warning(
                    f'File with ID {file_id} not found in database. Skipping deletion of file record.'
                )
            session.commit()
            self.ap.logger.info(f'Successfully completed data deletion for file_id: {file_id}')
        except Exception as e:
            session.rollback()
            self.ap.logger.error(f'Error deleting data for file_id {file_id}: {str(e)}', exc_info=True)
            raise
        finally:
            session.close()
    async def delete_kb_by_id(self, kb_id: str):
        """
        Deletes a knowledge base and all associated files, chunks, and vectors.
        This involves querying for associated files and then deleting them.
        """
        self.ap.logger.info(f'Starting deletion of knowledge base with ID: {kb_id}')
        session = SessionLocal()
        try:
            kb_to_delete = session.query(KnowledgeBase).filter_by(id=kb_id).first()
            if not kb_to_delete:
                self.ap.logger.warning(f'Knowledge Base with ID {kb_id} not found.')
                return
            files_to_delete = session.query(File).filter_by(kb_id=kb_id).all()
            session.close()
            for file_obj in files_to_delete:
                try:
                    await self.delete_data_by_file_id(file_obj.id)
                except Exception as file_del_e:
                    self.ap.logger.error(f'Failed to delete file ID {file_obj.id} during KB deletion: {file_del_e}')
            session = SessionLocal()
            try:
                kb_final_delete = session.query(KnowledgeBase).filter_by(id=kb_id).first()
                if kb_final_delete:
                    session.delete(kb_final_delete)
                    session.commit()
                    self.ap.logger.info(f'Successfully deleted knowledge base with ID: {kb_id}')
                else:
                    self.ap.logger.warning(
                        f'Knowledge Base with ID {kb_id} not found after file deletion, skipping KB deletion.'
                    )
            except Exception as kb_del_e:
                session.rollback()
                self.ap.logger.error(
                    f'Error deleting KnowledgeBase record for ID {kb_id}: {kb_del_e}',
                    exc_info=True,
                )
                raise
            finally:
                session.close()
        except Exception as e:
            # 如果在最初获取 KB 或文件列表时出错
            if session.is_active:
                session.rollback()
            self.ap.logger.error(
                f'Error during overall knowledge base deletion for ID {kb_id}: {str(e)}',
                exc_info=True,
            )
            raise
        finally:
            if session.is_active:
                session.close()
    async def get_file_content_by_file_id(self, file_id: str) -> str:
        file_bytes = await self.ap.storage_mgr.storage_provider.load(file_id)
        _, ext = os.path.splitext(file_id.lower())
        ext = ext.lstrip('.')
        try:
            text = file_bytes.decode('utf-8')
        except UnicodeDecodeError:
            return '[非文本文件或编码无法识别]'
        if ext in ['txt', 'md', 'csv', 'log', 'py', 'html']:
            return text
        else:
            return f'[未知类型: .{ext}]'
    async def relate_file_id_with_kb(self, knowledge_base_uuid: str, file_id: str) -> None:
        """
        Associates a file with a knowledge base by updating the kb_id in the File table.
        """
        self.ap.logger.info(f'Associating file ID {file_id} with knowledge base UUID {knowledge_base_uuid}')
        session = SessionLocal()
        try:
            # 查询知识库是否存在
            kb = session.query(KnowledgeBase).filter_by(id=knowledge_base_uuid).first()
            if not kb:
                self.ap.logger.error(f'Knowledge Base with UUID {knowledge_base_uuid} not found.')
                return
            if not await self.ap.storage_mgr.storage_provider.exists(file_id):
                self.ap.logger.error(f'File with ID {file_id} does not exist.')
                return
            self.ap.logger.info(f'File with ID {file_id} exists, proceeding with association.')
            # add new file record
            file_to_update = File(
                id=file_id,
                kb_id=kb.id,
                file_name=file_id,
                path=os.path.join('data', 'storage', file_id),
                file_type=os.path.splitext(file_id)[1].lstrip('.'),
                status=0,
            )
            session.add(file_to_update)
            session.commit()
            self.ap.logger.info(
                f'Successfully associated file ID {file_id} with knowledge base UUID {knowledge_base_uuid}'
            )
        except Exception as e:
            session.rollback()
            self.ap.logger.error(
                f'Error associating file ID {file_id} with knowledge base UUID {knowledge_base_uuid}: {str(e)}',
                exc_info=True,
            )
        finally:
            # 进行文件解析
            try:
                await self.store_data(
                    file_path=os.path.join('data', 'storage', file_id),
                    kb_id=knowledge_base_uuid,
                    file_type=os.path.splitext(file_id)[1].lstrip('.'),
                    file_id=file_id,
                )
            except Exception:
                # 如果存储数据时出错，更新文件状态为失败
                file_obj = session.query(File).filter_by(id=file_id).first()
                if file_obj:
                    file_obj.status = 2
                session.commit()
                self.ap.logger.error(f'Error storing data for file ID {file_id}', exc_info=True)
            session.close()
@@ -1,26 +1,15 @@
 # 封装异步操作
 import asyncio
-import logging
+
 from pkg.rag.knowledge.services.database import SessionLocal 
 class BaseService:
    def __init__(self):
-        self.logger = logging.getLogger(self.__class__.__name__)
+        pass
        self.db_session_factory = SessionLocal
    async def _run_sync(self, func, *args, **kwargs):
        """
        在单独的线程中运行同步函数。
        如果第一个参数是 session，则在 to_thread 中获取新的 session。
        """
-        
+
-        if getattr(func, '__name__', '').startswith('_db_'): 
+        return await asyncio.to_thread(func, *args, **kwargs)
            session = await asyncio.to_thread(self.db_session_factory)
            try:
                result = await asyncio.to_thread(func, session, *args, **kwargs)
                return result
            finally:
                session.close()
        else:
            # 否则，直接运行同步函数
            return await asyncio.to_thread(func, *args, **kwargs)
@@ -1,67 +0,0 @@
 import numpy as np
 import logging
 from chromadb import PersistentClient
 from pkg.core import app
 logger = logging.getLogger(__name__)
 class ChromaIndexManager:
    def __init__(self, ap: app.Application, collection_name: str = 'default_collection'):
        self.ap = ap
        chroma_data_path = './data/chroma'
        self.client = PersistentClient(path=chroma_data_path)
        self._collection_name = collection_name
        self._collection = None
        self.ap.logger.info(f'ChromaIndexManager initialized. Collection name: {self._collection_name}')
    @property
    def collection(self):
        if self._collection is None:
            self._collection = self.client.get_or_create_collection(name=self._collection_name)
            self.ap.logger.info(f"Chroma collection '{self._collection_name}' accessed/created.")
        return self._collection
    def add_embeddings_sync(
        self, file_ids: list[int], chunk_ids: list[int], embeddings: np.ndarray, documents: list[str]
    ):
        if (
            embeddings.shape[0] != len(chunk_ids)
            or embeddings.shape[0] != len(file_ids)
            or embeddings.shape[0] != len(documents)
        ):
            raise ValueError('Embedding, file_id, chunk_id, and document count mismatch.')
        chroma_ids = [f'{file_id}_{chunk_id}' for file_id, chunk_id in zip(file_ids, chunk_ids)]
        metadatas = [{'file_id': fid, 'chunk_id': cid} for fid, cid in zip(file_ids, chunk_ids)]
        self.logger.debug(f"Adding {len(embeddings)} embeddings to Chroma collection '{self._collection_name}'.")
        self.collection.add(embeddings=embeddings.tolist(), ids=chroma_ids, metadatas=metadatas, documents=documents)
        self.logger.info(f"Added {len(embeddings)} embeddings to Chroma collection '{self._collection_name}'.")
    def search_sync(self, query_embedding: np.ndarray, k: int = 5):
        """
        Searches the Chroma collection for the top-k nearest neighbors.
        Args:
            query_embedding: A numpy array of the query embedding.
            k: The number of results to return.
        Returns:
            A dictionary containing query results from Chroma.
        """
        self.logger.debug(f"Searching Chroma collection '{self._collection_name}' with k={k}.")
        results = self.collection.query(
            query_embeddings=query_embedding.tolist(),
            n_results=k,
            # REMOVE 'ids' from the include list. It's returned by default.
            include=['metadatas', 'distances', 'documents'],
        )
        self.logger.debug(f'Chroma search returned {len(results.get("ids", [[]])[0])} results.')
        return results
    def delete_by_file_id_sync(self, file_id: int):
        self.logger.info(
            f"Deleting embeddings for file_id: {file_id} from Chroma collection '{self._collection_name}'."
        )
        self.collection.delete(where={'file_id': file_id})
        self.logger.info(f'Deleted embeddings for file_id: {file_id} from Chroma.')
@@ -1,24 +1,22 @@
-# services/chunker.py
+from __future__ import annotations
-import logging
+
 import json
 from typing import List
-from pkg.rag.knowledge.services.base_service import BaseService  # Assuming BaseService provides _run_sync
+from pkg.rag.knowledge.services import base_service
 from pkg.core import app
 logger = logging.getLogger(__name__)
-
+class Chunker(base_service.BaseService):
 class Chunker(BaseService):
    """
    A class for splitting long texts into smaller, overlapping chunks.
    """
    def __init__(self, ap: app.Application, chunk_size: int = 500, chunk_overlap: int = 50):
        super().__init__(ap)  # Initialize BaseService
        self.ap = ap
        self.chunk_size = chunk_size
        self.chunk_overlap = chunk_overlap
        if self.chunk_overlap >= self.chunk_size:
-            self.logger.warning(
+            self.ap.logger.warning(
                'Chunk overlap is greater than or equal to chunk size. This may lead to empty or malformed chunks.'
            )
@@ -61,4 +59,5 @@ class Chunker(BaseService):
        # Run the synchronous splitting logic in a separate thread
        chunks = await self._run_sync(self._split_text_sync, text)
        self.ap.logger.info(f'Text chunked into {len(chunks)} pieces.')
        self.ap.logger.debug(f'Chunks: {json.dumps(chunks, indent=4, ensure_ascii=False)}')
        return chunks
@@ -1,23 +0,0 @@
 # 全部迁移过去
 from pkg.entity.persistence.rag import (
    create_db_and_tables,
    SessionLocal,
    Base,
    engine,
    KnowledgeBase,
    File,
    Chunk,
    Vector,
 )
 __all__ = [
    "create_db_and_tables",
    "SessionLocal",
    "Base",
    "engine",
    "KnowledgeBase",
    "File",
    "Chunk",
    "Vector",
 ]
@@ -1,89 +1,47 @@
 from __future__ import annotations
-import asyncio
+import uuid
 import logging
 import numpy as np
 from typing import List
 from sqlalchemy.orm import Session
 from pkg.rag.knowledge.services.base_service import BaseService
-from pkg.rag.knowledge.services.database import Chunk, SessionLocal
+from ....entity.persistence import rag as persistence_rag
 from pkg.rag.knowledge.services.chroma_manager import ChromaIndexManager
 from ....core import app
 from ....provider.modelmgr.requester import RuntimeEmbeddingModel
 import sqlalchemy
 class Embedder(BaseService):
-    def __init__(self, ap: app.Application, chroma_manager: ChromaIndexManager = None) -> None:
+    def __init__(self, ap: app.Application) -> None:
        super().__init__()
        self.logger = logging.getLogger(self.__class__.__name__)
        self.chroma_manager = chroma_manager
        self.ap = ap
    def _db_save_chunks_sync(self, session: Session, file_id: int, chunks_texts: List[str]):
        """
        Saves chunks to the relational database and returns the created Chunk objects.
        This function assumes it's called within a context where the session
        will be committed/rolled back and closed by the caller.
        """
        self.logger.debug(f'Saving {len(chunks_texts)} chunks for file_id {file_id} to DB (sync).')
        chunk_objects = []
        for text in chunks_texts:
            chunk = Chunk(file_id=file_id, text=text)
            session.add(chunk)
            chunk_objects.append(chunk)
        session.flush()  # This populates the .id attribute for each new chunk object
        self.logger.debug(f'Successfully added {len(chunk_objects)} chunk entries to DB.')
        return chunk_objects
    async def embed_and_store(
-        self, file_id: int, chunks: List[str], embedding_model: RuntimeEmbeddingModel
+        self, kb_id: str, file_id: str, chunks: List[str], embedding_model: RuntimeEmbeddingModel
-    ) -> List[Chunk]:
+    ) -> list[persistence_rag.Chunk]:
-        if not embedding_model:
+        # save chunk to db
-            raise RuntimeError('Embedding model not loaded. Please check Embedder initialization.')
+        chunk_entities: list[persistence_rag.Chunk] = []
        chunk_ids: list[str] = []
-        session = SessionLocal()  # Start a session that will live for the whole operation
+        for chunk_text in chunks:
-        chunk_objects = []
+            chunk_uuid = str(uuid.uuid4())
-        try:
+            chunk_ids.append(chunk_uuid)
-            # 1. Save chunks to the relational database first to get their IDs
+            chunk_entity = persistence_rag.Chunk(uuid=chunk_uuid, file_id=file_id, text=chunk_text)
-            #    We call _db_save_chunks_sync directly without _run_sync's session management
+            chunk_entities.append(chunk_entity)
            #    because we manage the session here across multiple async calls.
            chunk_objects = await asyncio.to_thread(self._db_save_chunks_sync, session, file_id, chunks)
            session.commit()  # Commit chunks to make their IDs permanent and accessible
-            if not chunk_objects:
+        chunk_dicts = [
-                self.logger.warning(
+            self.ap.persistence_mgr.serialize_model(persistence_rag.Chunk, chunk) for chunk in chunk_entities
-                    f'No chunk objects created for file_id {file_id}. Skipping embedding and Chroma storage.'
+        ]
                )
                return []
-            # get the embeddings for the chunks
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.Chunk).values(chunk_dicts))
            embeddings: list[list[float]] = []
-            for chunk in chunks:
+        # get embeddings
-                result = await embedding_model.requester.invoke_embedding(
+        embeddings_list: list[list[float]] = await embedding_model.requester.invoke_embedding(
-                    model=embedding_model,
+            model=embedding_model,
-                    input_text=chunk,
+            input_text=chunks,
-                )
+            extra_args={},  # TODO: add extra args
-                embeddings.append(result)
+        )
-            embeddings_np = np.array(embeddings, dtype=np.float32)
+        # save embeddings to vdb
        await self.ap.vector_db_mgr.vector_db.add_embeddings(kb_id, chunk_ids, embeddings_list, chunk_dicts)
-            self.logger.info('Saving embeddings to Chroma...')
+        self.ap.logger.info(f'Successfully saved {len(chunk_entities)} embeddings to Knowledge Base.')
            chunk_ids = [c.id for c in chunk_objects]
            file_ids_for_chroma = [file_id] * len(chunk_ids)
-            await self._run_sync(  # Use _run_sync for the Chroma operation, as it's a sync call
+        return chunk_entities
                self.chroma_manager.add_embeddings_sync,
                file_ids_for_chroma,
                chunk_ids,
                embeddings_np,
                chunks,  # Pass original chunks texts for documents
            )
            self.logger.info(f'Successfully saved {len(chunk_objects)} embeddings to Chroma.')
            return chunk_objects
        except Exception as e:
            session.rollback()  # Rollback on any error
            self.logger.error(f'Failed to process and store data for file_id {file_id}: {e}', exc_info=True)
            raise  # Re-raise the exception to propagate it
        finally:
            session.close()  # Ensure the session is always closed
@@ -1,21 +1,16 @@
 from __future__ import annotations
 import PyPDF2
 import io
 from docx import Document
 import pandas as pd
 import chardet
 from typing import Union, Callable, Any
 import logging
 import markdown
 from bs4 import BeautifulSoup
 import ebooklib
 from ebooklib import epub
 import re
 import asyncio  # Import asyncio for async operations
 from pkg.core import app
 # Configure logging
 logger = logging.getLogger(__name__)
 class FileParser:
    """
@@ -144,45 +139,45 @@ class FileParser:
        self.ap.logger.warning(f'Direct .doc parsing is not supported for {file_name}. Please convert to .docx first.')
        raise NotImplementedError('Direct .doc parsing not supported. Please convert to .docx first.')
-    async def _parse_xlsx(self, file_name: str) -> str:
+    # async def _parse_xlsx(self, file_name: str) -> str:
-        """Parses an XLSX file, returning text from all sheets."""
+    #     """Parses an XLSX file, returning text from all sheets."""
-        self.ap.logger.info(f'Parsing XLSX file: {file_name}')
+    #     self.ap.logger.info(f'Parsing XLSX file: {file_name}')
-        xlsx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+    #     xlsx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
-        def _parse_xlsx_sync():
+    #     def _parse_xlsx_sync():
-            excel_file = pd.ExcelFile(io.BytesIO(xlsx_bytes))
+    #         excel_file = pd.ExcelFile(io.BytesIO(xlsx_bytes))
-            all_sheet_content = []
+    #         all_sheet_content = []
-            for sheet_name in excel_file.sheet_names:
+    #         for sheet_name in excel_file.sheet_names:
-                df = pd.read_excel(io.BytesIO(xlsx_bytes), sheet_name=sheet_name)
+    #             df = pd.read_excel(io.BytesIO(xlsx_bytes), sheet_name=sheet_name)
-                sheet_text = f'--- Sheet: {sheet_name} ---\n{df.to_string(index=False)}\n'
+    #             sheet_text = f'--- Sheet: {sheet_name} ---\n{df.to_string(index=False)}\n'
-                all_sheet_content.append(sheet_text)
+    #             all_sheet_content.append(sheet_text)
-            return '\n'.join(all_sheet_content)
+    #         return '\n'.join(all_sheet_content)
-        return await self._run_sync(_parse_xlsx_sync)
+    #     return await self._run_sync(_parse_xlsx_sync)
-    async def _parse_csv(self, file_name: str) -> str:
+    # async def _parse_csv(self, file_name: str) -> str:
-        """Parses a CSV file and returns its content as a string."""
+    #     """Parses a CSV file and returns its content as a string."""
-        self.ap.logger.info(f'Parsing CSV file: {file_name}')
+    #     self.ap.logger.info(f'Parsing CSV file: {file_name}')
-        csv_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+    #     csv_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
-        def _parse_csv_sync():
+    #     def _parse_csv_sync():
-            # pd.read_csv can often detect encoding, but explicit detection is safer
+    #         # pd.read_csv can often detect encoding, but explicit detection is safer
-            # raw_data = self._read_file_content(
+    #         # raw_data = self._read_file_content(
-            #     file_name, mode='rb'
+    #         #     file_name, mode='rb'
-            # )  # Note: this will need to be await outside this sync function
+    #         # )  # Note: this will need to be await outside this sync function
-            # _ = raw_data
+    #         # _ = raw_data
-            # For simplicity, we'll let pandas handle encoding internally after a raw read.
+    #         # For simplicity, we'll let pandas handle encoding internally after a raw read.
-            # A more robust solution might pass encoding directly to pd.read_csv after detection.
+    #         # A more robust solution might pass encoding directly to pd.read_csv after detection.
-            detected = chardet.detect(io.BytesIO(csv_bytes))
+    #         detected = chardet.detect(io.BytesIO(csv_bytes))
-            encoding = detected['encoding'] or 'utf-8'
+    #         encoding = detected['encoding'] or 'utf-8'
-            df = pd.read_csv(io.BytesIO(csv_bytes), encoding=encoding)
+    #         df = pd.read_csv(io.BytesIO(csv_bytes), encoding=encoding)
-            return df.to_string(index=False)
+    #         return df.to_string(index=False)
-        return await self._run_sync(_parse_csv_sync)
+    #     return await self._run_sync(_parse_csv_sync)
-    async def _parse_markdown(self, file_name: str) -> str:
+    async def _parse_md(self, file_name: str) -> str:
        """Parses a Markdown file, converting it to structured plain text."""
        self.ap.logger.info(f'Parsing Markdown file: {file_name}')
@@ -261,43 +256,6 @@ class FileParser:
        return await self._run_sync(_parse_html_sync)
    async def _parse_epub(self, file_name: str) -> str:
        """Parses an EPUB file, extracting metadata and content."""
        self.ap.logger.info(f'Parsing EPUB file: {file_name}')
        epub_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
        def _parse_epub_sync():
            book = epub.read_epub(io.BytesIO(epub_bytes))
            text_content = []
            title_meta = book.get_metadata('DC', 'title')
            if title_meta:
                text_content.append(f'Title: {title_meta[0][0]}')
            creator_meta = book.get_metadata('DC', 'creator')
            if creator_meta:
                text_content.append(f'Author: {creator_meta[0][0]}')
            date_meta = book.get_metadata('DC', 'date')
            if date_meta:
                text_content.append(f'Publish Date: {date_meta[0][0]}')
            toc = book.get_toc()
            if toc:
                text_content.append('\n--- Table of Contents ---')
                self._add_toc_items_sync(toc, text_content, level=0)  # Call sync helper
                text_content.append('--- End of Table of Contents ---\n')
            for item in book.get_items():
                if item.get_type() == ebooklib.ITEM_DOCUMENT:
                    html_content = item.get_content().decode('utf-8', errors='ignore')
                    soup = BeautifulSoup(html_content, 'html.parser')
                    for junk in soup(['script', 'style', 'nav', 'header', 'footer']):
                        junk.decompose()
                    text = soup.get_text(separator='\n', strip=True)
                    text = re.sub(r'\n\s*\n', '\n\n', text)
                    if text:
                        text_content.append(text)
            return re.sub(r'\n\s*\n', '\n\n', '\n'.join(text_content)).strip()
        return await self._run_sync(_parse_epub_sync)
    def _add_toc_items_sync(self, toc_list: list, text_content: list, level: int):
        """Recursively adds TOC items to text_content (synchronous helper)."""
        indent = '  ' * level
@@ -1,94 +1,48 @@
 from __future__ import annotations
-import logging
+
-import numpy as np  # Make sure numpy is imported
+from . import base_service
 from typing import List, Dict, Any
 from sqlalchemy.orm import Session
 from pkg.rag.knowledge.services.base_service import BaseService
 from pkg.rag.knowledge.services.database import Chunk, SessionLocal
 from pkg.rag.knowledge.services.chroma_manager import ChromaIndexManager
 from ....core import app
-
+from ....provider.modelmgr.requester import RuntimeEmbeddingModel
-logger = logging.getLogger(__name__)
+from ....entity.rag import retriever as retriever_entities
-class Retriever(BaseService):
+class Retriever(base_service.BaseService):
-    def __init__(self, ap:app.Application, chroma_manager: ChromaIndexManager):
+    def __init__(self, ap: app.Application):
        super().__init__()
        self.logger = logging.getLogger(self.__class__.__name__)
        self.chroma_manager = chroma_manager
        self.ap = ap
-    async def retrieve(self, query: str, k: int = 5) -> List[Dict[str, Any]]:
+    async def retrieve(
-        if not self.embedding_model:
+        self, kb_id: str, query: str, embedding_model: RuntimeEmbeddingModel, k: int = 5
-            raise RuntimeError('Retriever embedding model not loaded. Please check Retriever initialization.')
+    ) -> list[retriever_entities.RetrieveResultEntry]:
        self.ap.logger.info(
            f"Retrieving for query: '{query[:10]}' with k={k} using {embedding_model.model_entity.uuid}"
        )
-        self.logger.info(f"Retrieving for query: '{query}' with k={k} using {self.model_name_key}")
+        query_embedding: list[float] = await embedding_model.requester.invoke_embedding(
            model=embedding_model,
            input_text=[query],
            extra_args={},  # TODO: add extra args
        )
-        query_embedding: List[float] = await self.embedding_model.embed_query(query)
+        chroma_results = await self.ap.vector_db_mgr.vector_db.search(kb_id, query_embedding[0], k)
        query_embedding_np = np.array([query_embedding], dtype=np.float32)
        chroma_results = await self._run_sync(self.chroma_manager.search_sync, query_embedding_np, k)
        # 'ids' is always returned by ChromaDB, even if not explicitly in 'include'
        matched_chroma_ids = chroma_results.get('ids', [[]])[0]
        distances = chroma_results.get('distances', [[]])[0]
        chroma_metadatas = chroma_results.get('metadatas', [[]])[0]
        chroma_documents = chroma_results.get('documents', [[]])[0]
        if not matched_chroma_ids:
-            self.logger.info('No relevant chunks found in Chroma.')
+            self.ap.logger.info('No relevant chunks found in Chroma.')
            return []
-        db_chunk_ids = []
+        result: list[retriever_entities.RetrieveResultEntry] = []
        for metadata in chroma_metadatas:
            if 'chunk_id' in metadata:
                db_chunk_ids.append(metadata['chunk_id'])
            else:
                self.logger.warning(f"Metadata missing 'chunk_id': {metadata}. Skipping this entry.")
-        if not db_chunk_ids:
+        for i, id in enumerate(matched_chroma_ids):
-            self.logger.warning('No valid chunk_ids extracted from Chroma results metadata.')
+            entry = retriever_entities.RetrieveResultEntry(
-            return []
+                id=id,
-
+                metadata=chroma_metadatas[i],
-        self.logger.info(f'Fetching {len(db_chunk_ids)} chunk details from relational database...')
+                distance=distances[i],
        chunks_from_db = await self._run_sync(
            lambda cids: self._db_get_chunks_sync(
                SessionLocal(), cids
            ),  # Ensure SessionLocal is passed correctly for _db_get_chunks_sync
            db_chunk_ids,
        )
        chunk_map = {chunk.id: chunk for chunk in chunks_from_db}
        results_list: List[Dict[str, Any]] = []
        for i, chroma_id in enumerate(matched_chroma_ids):
            try:
                # Ensure original_chunk_id is int for DB lookup
                original_chunk_id = int(chroma_id.split('_')[-1])
            except (ValueError, IndexError):
                self.logger.warning(f'Could not parse chunk_id from Chroma ID: {chroma_id}. Skipping.')
                continue
            chunk_text_from_chroma = chroma_documents[i]
            distance = float(distances[i])
            file_id_from_chroma = chroma_metadatas[i].get('file_id')
            chunk_from_db = chunk_map.get(original_chunk_id)
            results_list.append(
                {
                    'chunk_id': original_chunk_id,
                    'text': chunk_from_db.text if chunk_from_db else chunk_text_from_chroma,
                    'distance': distance,
                    'file_id': file_id_from_chroma,
                }
            )
            result.append(entry)
-        self.logger.info(f'Retrieved {len(results_list)} chunks.')
+        return result
        return results_list
    def _db_get_chunks_sync(self, session: Session, chunk_ids: List[int]) -> List[Chunk]:
        self.logger.debug(f'Fetching {len(chunk_ids)} chunk details from database (sync).')
        chunks = session.query(Chunk).filter(Chunk.id.in_(chunk_ids)).all()
        session.close()
        return chunks
@@ -46,7 +46,7 @@ class AnnouncementManager:
    async def fetch_all(self) -> list[Announcement]:
        """获取所有公告"""
        resp = requests.get(
-            url='https://api.github.com/repos/RockChinQ/LangBot/contents/res/announcement.json',
+            url='https://api.github.com/repos/langbot-app/LangBot/contents/res/announcement.json',
            proxies=self.ap.proxy_mgr.get_forward_proxies(),
            timeout=5,
        )
@@ -1,6 +1,6 @@
-semantic_version = 'v4.0.8'
+semantic_version = 'v4.1.0'
-required_database_version = 3
+required_database_version = 4
 """Tag the version of the database schema, used to check if the database needs to be migrated"""
 debug_mode = False
@@ -29,7 +29,7 @@ class VersionManager:
    async def get_release_list(self) -> list:
        """获取发行列表"""
        rls_list_resp = requests.get(
-            url='https://api.github.com/repos/RockChinQ/LangBot/releases',
+            url='https://api.github.com/repos/langbot-app/LangBot/releases',
            proxies=self.ap.proxy_mgr.get_forward_proxies(),
            timeout=5,
        )
@@ -1,13 +1,18 @@
 from __future__ import annotations
 from ..core import app
 from .vdb import VectorDatabase
 from .vdbs.chroma import ChromaVectorDatabase
 class VectorDBManager:
    ap: app.Application
    vector_db: VectorDatabase = None
    def __init__(self, ap: app.Application):
        self.ap = ap
    async def initialize(self):
-        pass
+        # 初始化 Chroma 向量数据库（可扩展为多种实现）
        if self.vector_db is None:
            self.vector_db = ChromaVectorDatabase(self.ap)
@@ -1,7 +1,37 @@
 from __future__ import annotations
 import abc
 from typing import Any, Dict
 import numpy as np
 class VectorDatabase(abc.ABC):
-    pass
+    @abc.abstractmethod
    async def add_embeddings(
        self,
        collection: str,
        ids: list[str],
        embeddings_list: list[list[float]],
        metadatas: list[dict[str, Any]],
        documents: list[str],
    ) -> None:
        """向指定 collection 添加向量数据。"""
        pass
    @abc.abstractmethod
    async def search(self, collection: str, query_embedding: np.ndarray, k: int = 5) -> Dict[str, Any]:
        """在指定 collection 中检索最相似的向量。"""
        pass
    @abc.abstractmethod
    async def delete_by_file_id(self, collection: str, file_id: str) -> None:
        """根据 file_id 删除指定 collection 中的向量。"""
        pass
    @abc.abstractmethod
    async def get_or_create_collection(self, collection: str):
        """获取或创建 collection。"""
        pass
    @abc.abstractmethod
    async def delete_collection(self, collection: str):
        pass
@@ -0,0 +1,61 @@
 from __future__ import annotations
 import asyncio
 from typing import Any
 from chromadb import PersistentClient
 from pkg.vector.vdb import VectorDatabase
 from pkg.core import app
 import chromadb
 import chromadb.errors
 class ChromaVectorDatabase(VectorDatabase):
    def __init__(self, ap: app.Application, base_path: str = './data/chroma'):
        self.ap = ap
        self.client = PersistentClient(path=base_path)
        self._collections = {}
    async def get_or_create_collection(self, collection: str) -> chromadb.Collection:
        if collection not in self._collections:
            self._collections[collection] = await asyncio.to_thread(
                self.client.get_or_create_collection, name=collection
            )
            self.ap.logger.info(f"Chroma collection '{collection}' accessed/created.")
        return self._collections[collection]
    async def add_embeddings(
        self,
        collection: str,
        ids: list[str],
        embeddings_list: list[list[float]],
        metadatas: list[dict[str, Any]],
    ) -> None:
        col = await self.get_or_create_collection(collection)
        await asyncio.to_thread(col.add, embeddings=embeddings_list, ids=ids, metadatas=metadatas)
        self.ap.logger.info(f"Added {len(ids)} embeddings to Chroma collection '{collection}'.")
    async def search(self, collection: str, query_embedding: list[float], k: int = 5) -> dict[str, Any]:
        col = await self.get_or_create_collection(collection)
        results = await asyncio.to_thread(
            col.query,
            query_embeddings=query_embedding,
            n_results=k,
            include=['metadatas', 'distances', 'documents'],
        )
        self.ap.logger.info(f"Chroma search in '{collection}' returned {len(results.get('ids', [[]])[0])} results.")
        return results
    async def delete_by_file_id(self, collection: str, file_id: str) -> None:
        col = await self.get_or_create_collection(collection)
        await asyncio.to_thread(col.delete, where={'file_id': file_id})
        self.ap.logger.info(f"Deleted embeddings from Chroma collection '{collection}' with file_id: {file_id}")
    async def delete_collection(self, collection: str):
        if collection in self._collections:
            del self._collections[collection]
        try:
            await asyncio.to_thread(self.client.delete_collection, name=collection)
        except chromadb.errors.NotFoundError:
            self.ap.logger.warning(f"Chroma collection '{collection}' not found.")
            return
        self.ap.logger.info(f"Chroma collection '{collection}' deleted.")
@@ -1,6 +1,6 @@
 [project]
 name = "langbot"
-version = "4.0.7"
+version = "4.1.0"
 description = "高稳定、支持扩展、多模态 - 大模型原生即时通信机器人平台"
 readme = "README.md"
 requires-python = ">=3.10.1"
@@ -19,6 +19,7 @@ dependencies = [
    "dashscope>=1.23.2",
    "dingtalk-stream>=0.24.0",
    "discord-py>=2.5.2",
    "pynacl>=1.5.0",  # Required for Discord voice support
    "gewechat-client>=0.1.5",
    "lark-oapi>=1.4.15",
    "mcp>=1.8.1",
@@ -59,7 +60,6 @@ dependencies = [
    "html2text>=2024.2.26",
    "langchain>=0.2.0",
    "chromadb>=0.4.24",
    "sentence-transformers>=2.6.1",
 ]
 keywords = [
    "bot",
@@ -90,11 +90,13 @@ classifiers = [
 [project.urls]
 Homepage = "https://langbot.app"
 Documentation = "https://docs.langbot.app"
-Repository = "https://github.com/RockChinQ/langbot"
+Repository = "https://github.com/langbot-app/LangBot"
 [dependency-groups]
 dev = [
    "pre-commit>=4.2.0",
    "pytest>=8.4.1",
    "pytest-asyncio>=1.0.0",
    "ruff>=0.11.9",
 ]
@@ -44,7 +44,8 @@
                    "role": "system",
                    "content": "You are a helpful assistant."
                }
-            ]
+            ],
            "knowledge-base": ""
        },
        "dify-service-api": {
            "base-url": "https://api.dify.ai/v1",
@@ -68,6 +68,16 @@ stages:
          zh_Hans: 除非您了解消息结构，否则请只使用 system 单提示词
        type: prompt-editor
        required: true
      - name: knowledge-base
        label:
          en_US: Knowledge Base
          zh_Hans: 知识库
        description:
          en_US: Configure the knowledge base to use for the agent, if not selected, the agent will directly use the LLM to reply
          zh_Hans: 配置用于提升回复质量的知识库，若不选择，则直接使用大模型回复
        type: knowledge-base-selector
        required: false
        default: ''
  - name: dify-service-api
    label:
      en_US: Dify Service API
@@ -298,3 +308,4 @@ stages:
        type: string
        required: false
        default: 'response'
@@ -13,6 +13,7 @@
        "@hookform/resolvers": "^5.0.1",
        "@radix-ui/react-checkbox": "^1.3.1",
        "@radix-ui/react-dialog": "^1.1.14",
        "@radix-ui/react-dropdown-menu": "^2.1.15",
        "@radix-ui/react-hover-card": "^1.1.13",
        "@radix-ui/react-label": "^2.1.6",
        "@radix-ui/react-popover": "^1.1.14",
@@ -1152,31 +1153,6 @@
        }
      }
    },
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@@ -1266,6 +1242,58 @@
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@@ -1282,13 +1310,13 @@
      }
    },
    "node_modules/@radix-ui/react-focus-scope": {
-      "version": "1.1.6",
+      "version": "1.1.7",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-focus-scope/-/react-focus-scope-1.1.6.tgz",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-focus-scope/-/react-focus-scope-1.1.7.tgz",
-      "integrity": "sha512-r9zpYNUQY+2jWHWZGyddQLL9YHkM/XvSFHVcWs7bdVuxMAnCwTAuy6Pf47Z4nw7dYcUou1vg/VgjjrrH03VeBw==",
+      "integrity": "sha512-t2ODlkXBQyn7jkl6TNaw/MtVEVvIGelJDCG41Okq/KwUsJBwQ4XVZsHAVUkK4mBv3ewiAS3PGuUWuY2BoK4ZUw==",
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-        "@radix-ui/react-primitive": "2.1.2",
+        "@radix-ui/react-primitive": "2.1.3",
        "@radix-ui/react-use-callback-ref": "1.1.1"
      },
      "peerDependencies": {
@@ -1306,6 +1334,29 @@
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@@ -1378,6 +1429,232 @@
        }
      }
    },
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      "resolved": "https://registry.npmjs.org/@radix-ui/react-menu/-/react-menu-2.1.15.tgz",
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        "@radix-ui/react-compose-refs": "1.1.2",
        "@radix-ui/react-context": "1.1.2",
        "@radix-ui/react-direction": "1.1.1",
        "@radix-ui/react-dismissable-layer": "1.1.10",
        "@radix-ui/react-focus-guards": "1.1.2",
        "@radix-ui/react-focus-scope": "1.1.7",
        "@radix-ui/react-id": "1.1.1",
        "@radix-ui/react-popper": "1.2.7",
        "@radix-ui/react-portal": "1.1.9",
        "@radix-ui/react-presence": "1.1.4",
        "@radix-ui/react-primitive": "2.1.3",
        "@radix-ui/react-roving-focus": "1.1.10",
        "@radix-ui/react-slot": "1.2.3",
        "@radix-ui/react-use-callback-ref": "1.1.1",
        "aria-hidden": "^1.2.4",
        "react-remove-scroll": "^2.6.3"
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    "node_modules/@radix-ui/react-menu/node_modules/@radix-ui/react-roving-focus": {
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      "resolved": "https://registry.npmjs.org/@radix-ui/react-roving-focus/-/react-roving-focus-1.1.10.tgz",
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      "dependencies": {
        "@radix-ui/primitive": "1.1.2",
        "@radix-ui/react-collection": "1.1.7",
        "@radix-ui/react-compose-refs": "1.1.2",
        "@radix-ui/react-context": "1.1.2",
        "@radix-ui/react-direction": "1.1.1",
        "@radix-ui/react-id": "1.1.1",
        "@radix-ui/react-primitive": "2.1.3",
        "@radix-ui/react-use-callback-ref": "1.1.1",
        "@radix-ui/react-use-controllable-state": "1.2.2"
      },
      "peerDependencies": {
        "@types/react": "*",
        "@types/react-dom": "*",
        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
      },
      "peerDependenciesMeta": {
        "@types/react": {
          "optional": true
        },
        "@types/react-dom": {
          "optional": true
        }
      }
    },
    "node_modules/@radix-ui/react-popover": {
      "version": "1.1.14",
      "resolved": "https://registry.npmjs.org/@radix-ui/react-popover/-/react-popover-1.1.14.tgz",
@@ -1465,31 +1742,6 @@
        }
      }
    },
    "node_modules/@radix-ui/react-popover/node_modules/@radix-ui/react-focus-scope": {
      "version": "1.1.7",
      "resolved": "https://registry.npmjs.org/@radix-ui/react-focus-scope/-/react-focus-scope-1.1.7.tgz",
      "integrity": "sha512-t2ODlkXBQyn7jkl6TNaw/MtVEVvIGelJDCG41Okq/KwUsJBwQ4XVZsHAVUkK4mBv3ewiAS3PGuUWuY2BoK4ZUw==",
      "license": "MIT",
      "dependencies": {
        "@radix-ui/react-compose-refs": "1.1.2",
        "@radix-ui/react-primitive": "2.1.3",
        "@radix-ui/react-use-callback-ref": "1.1.1"
      },
      "peerDependencies": {
        "@types/react": "*",
        "@types/react-dom": "*",
        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
      },
      "peerDependenciesMeta": {
        "@types/react": {
          "optional": true
        },
        "@types/react-dom": {
          "optional": true
        }
      }
    },
    "node_modules/@radix-ui/react-popover/node_modules/@radix-ui/react-popper": {
      "version": "1.2.7",
      "resolved": "https://registry.npmjs.org/@radix-ui/react-popper/-/react-popper-1.2.7.tgz",
@@ -5,6 +5,7 @@
  "scripts": {
    "dev": "next dev --turbopack",
    "dev:local": "NEXT_PUBLIC_API_BASE_URL=http://localhost:5300 next dev --turbopack",
    "dev:local:win": "set NEXT_PUBLIC_API_BASE_URL=http://localhost:5300&&next dev --turbopack",
    "build": "next build",
    "start": "next start",
    "lint": "next lint",
@@ -16,6 +17,9 @@
      "prettier --write"
    ]
  },
  "overrides": {
    "@radix-ui/react-focus-scope": "1.1.7"
  },
  "dependencies": {
    "@dnd-kit/core": "^6.3.1",
    "@dnd-kit/sortable": "^10.0.0",
@@ -127,7 +127,6 @@ export default function BotDetailDialog({
                <BotForm
                  initBotId={undefined}
                  onFormSubmit={handleFormSubmit}
                  onFormCancel={handleFormCancel}
                  onBotDeleted={handleBotDeleted}
                  onNewBotCreated={handleNewBotCreated}
                />
@@ -198,7 +197,6 @@ export default function BotDetailDialog({
                  <BotForm
                    initBotId={botId}
                    onFormSubmit={handleFormSubmit}
                    onFormCancel={handleFormCancel}
                    onBotDeleted={handleBotDeleted}
                    onNewBotCreated={handleNewBotCreated}
                  />
@@ -64,13 +64,11 @@ const getFormSchema = (t: (key: string) => string) =>
 export default function BotForm({
  initBotId,
  onFormSubmit,
  onFormCancel,
  onBotDeleted,
  onNewBotCreated,
 }: {
  initBotId?: string;
  onFormSubmit: (value: z.infer<ReturnType<typeof getFormSchema>>) => void;
  onFormCancel: () => void;
  onBotDeleted: () => void;
  onNewBotCreated: (botId: string) => void;
 }) {
@@ -50,6 +50,9 @@ export default function DynamicFormComponent({
          case 'llm-model-selector':
            fieldSchema = z.string();
            break;
          case 'knowledge-base-selector':
            fieldSchema = z.string();
            break;
          case 'prompt-editor':
            fieldSchema = z.array(
              z.object({
--- a/Show More
+++ b/Show More