diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index f3389c25..71ef28fc 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -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. diff --git a/.gitignore b/.gitignore index 2869b7cc..db62bdca 100644 --- a/.gitignore +++ b/.gitignore @@ -42,4 +42,5 @@ botpy.log* test.py /web_ui .venv/ -uv.lock \ No newline at end of file +uv.lock +/test \ No newline at end of file diff --git a/README.md b/README.md index ba6bbf90..c9341668 100644 --- a/README.md +++ b/README.md @@ -1,50 +1,40 @@

-LangBot +LangBot

-RockChinQ%2FLangBot | Trendshift +Featured｜HelloGitHub + +[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.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) +python +[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot) 项目主页 ｜ 部署文档 ｜ 插件介绍 ｜ -提交插件 +提交插件 -
-😎高稳定、🧩支持扩展、🦄多模态 - 大模型原生即时通信机器人平台🤖 -
- -
- -[![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) -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)

-## ✨ 特性 - -- 💬 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。 +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。 ## 📦 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 +61,25 @@ 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 -bots +点击仓库右上角 Star 和 Watch 按钮，获取最新动态。 -bots +![star gif](https://docs.langbot.app/star.gif) -bots +## ✨ 特性 -bots +- 💬 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、流式输出能力，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。 -回复效果（带有联网插件） +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/ - - 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。 - -## 🔌 组件兼容性 +或访问 demo 环境：https://demo.langbot.dev/ + - 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。 ### 消息平台 @@ -104,10 +96,6 @@ docker compose up -d | Discord | ✅ | | | Telegram | ✅ | | | Slack | ✅ | | -| LINE | 🚧 | | -| WhatsApp | 🚧 | | - -🚧: 正在开发中 ### 大模型能力 @@ -119,8 +107,10 @@ docker compose up -d | [Anthropic](https://www.anthropic.com/) | ✅ | | | [xAI](https://x.ai/) | ✅ | | | [智谱AI](https://open.bigmodel.cn/) | ✅ | | +| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 | | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 | -| [302 AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 | +| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 资源平台 | +| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 | | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | | | [Dify](https://dify.ai) | ✅ | LLMOps 平台 | | [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 | @@ -148,14 +138,8 @@ 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： - - + + - -## 😎 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) diff --git a/README_EN.md b/README_EN.md index 0542f16d..8977f8f1 100644 --- a/README_EN.md +++ b/README_EN.md @@ -1,48 +1,34 @@

-LangBot +LangBot

-RockChinQ%2FLangBot | Trendshift +English / [简体中文](README.md) / [繁體中文](README_TW.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) +[![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) +python Home ｜ Deployment ｜ Plugin ｜ -Submit Plugin - -
-😎High Stability, 🧩Extension Supported, 🦄Multi-modal - LLM Native Instant Messaging Bot Platform🤖 -
- -
- - -[![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) -python - -[简体中文](README.md) / English / [日本語](README_JP.md) / (PR for your language) +Submit Plugin

-## ✨ Features - -- 💬 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. +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. ## 📦 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 -bots +Click the Star and Watch button in the upper right corner of the repository to get the latest updates. -bots +![star gif](https://docs.langbot.app/star.gif) -bots +## ✨ Features -bots +- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output 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. -Reply Effect (with Internet Plugin) +For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html). -- WebUI Demo: https://demo.langbot.dev/ - - 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. - -## 🔌 Component Compatibility +Or visit the demo environment: https://demo.langbot.dev/ + - Login information: Email: `demo@langbot.app` Password: `langbot123456` + - Note: For WebUI demo only, please do not fill in any sensitive information in the public environment. ### 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 @@ -116,9 +100,11 @@ Directly use the released version to run, see the [Manual Deployment](https://do | [Anthropic](https://www.anthropic.com/) | ✅ | | | [xAI](https://x.ai/) | ✅ | | | [Zhipu AI](https://open.bigmodel.cn/) | ✅ | | +| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform | | [Dify](https://dify.ai) | ✅ | LLMOps platform | | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform | -| [302 AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) | +| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform | +| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) | | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | | | [Ollama](https://ollama.com/) | ✅ | Local LLM running platform | | [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform | @@ -131,14 +117,8 @@ 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: - - + + - -## 😎 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) \ No newline at end of file diff --git a/README_JP.md b/README_JP.md index 7a3a16dd..bc5e5e5d 100644 --- a/README_JP.md +++ b/README_JP.md @@ -1,47 +1,34 @@

-LangBot +LangBot

-RockChinQ%2FLangBot | Trendshift +[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.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) +python ホーム ｜ デプロイ ｜ プラグイン ｜ -プラグインの提出 - -
-😎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🤖 -
- -
- -[![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) -python - -[简体中文](README_CN.md) / [English](README.md) / [日本語](README_JP.md) / (PR for your language) +プラグインの提出

-## ✨ 機能 - -- 💬 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。 +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。 ## 📦 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 -bots +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。 -bots +![star gif](https://docs.langbot.app/star.gif) -bots +## ✨ 機能 -bots +- 💬 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、ストリーミング出力機能をサポート、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。 -返信効果（インターネットプラグイン付き） +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/ - - 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。 - -## 🔌 コンポーネントの互換性 +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` + - 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。 ### 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 @@ -115,8 +100,10 @@ LangBotはBTPanelにリストされています。BTPanelをインストール | [Anthropic](https://www.anthropic.com/) | ✅ | | | [xAI](https://x.ai/) | ✅ | | | [Zhipu AI](https://open.bigmodel.cn/) | ✅ | | +| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム | | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム | -| [302 AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) | +| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム | +| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) | | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | | | [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム | | [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム | @@ -130,14 +117,8 @@ 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。 - - + + - -## 😎 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) \ No newline at end of file diff --git a/README_TW.md b/README_TW.md new file mode 100644 index 00000000..0c52152d --- /dev/null +++ b/README_TW.md @@ -0,0 +1,140 @@ +

+ +LangBot + + +

Featured｜HelloGitHub + +[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [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) +python +[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot) + +主頁 ｜ +部署文件 ｜ +外掛介紹 ｜ +提交外掛 + +
+ +

+ +LangBot 是一個開源的大語言模型原生即時通訊機器人開發平台，旨在提供開箱即用的 IM 機器人開發體驗，具有 Agent、RAG、MCP 等多種 LLM 應用功能，適配全球主流即時通訊平台，並提供豐富的 API 介面，支援自定義開發。 + +## 📦 開始使用 + +#### Docker Compose 部署 + +```bash +git clone https://github.com/langbot-app/LangBot +cd LangBot +docker compose up -d +``` + +訪問 http://localhost:5300 即可開始使用。 + +詳細文件[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。 + +#### 寶塔面板部署 + +已上架寶塔面板，若您已安裝寶塔面板，可以根據[文件](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。 + +#### Zeabur 雲端部署 + +社群貢獻的 Zeabur 模板。 + +[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH) + +#### Railway 雲端部署 + +[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF) + +#### 手動部署 + +直接使用發行版運行，查看文件[手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。 + +## 😎 保持更新 + +點擊倉庫右上角 Star 和 Watch 按鈕，獲取最新動態。 + +![star gif](https://docs.langbot.app/star.gif) + +## ✨ 特性 + +- 💬 大模型對話、Agent：支援多種大模型，適配群聊和私聊；具有多輪對話、工具調用、多模態、流式輸出能力，自帶 RAG（知識庫）實現，並深度適配 [Dify](https://dify.ai)。 +- 🤖 多平台支援：目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram 等平台。 +- 🛠️ 高穩定性、功能完備：原生支援訪問控制、限速、敏感詞過濾等機制；配置簡單，支援多種部署方式。支援多流水線配置，不同機器人用於不同應用場景。 +- 🧩 外掛擴展、活躍社群：支援事件驅動、組件擴展等外掛機制；適配 Anthropic [MCP 協議](https://modelcontextprotocol.io/)；目前已有數百個外掛。 +- 😻 Web 管理面板：支援通過瀏覽器管理 LangBot 實例，不再需要手動編寫配置文件。 + +詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。 + +或訪問 demo 環境：https://demo.langbot.dev/ + - 登入資訊：郵箱：`demo@langbot.app` 密碼：`langbot123456` + - 注意：僅展示 WebUI 效果，公開環境，請不要在其中填入您的任何敏感資訊。 + +### 訊息平台 + +| 平台 | 狀態 | 備註 | +| --- | --- | --- | +| QQ 個人號 | ✅ | QQ 個人號私聊、群聊 | +| QQ 官方機器人 | ✅ | QQ 官方機器人，支援頻道、私聊、群聊 | +| 微信 | ✅ | | +| 企微對外客服 | ✅ | | +| 微信公眾號 | ✅ | | +| Lark | ✅ | | +| DingTalk | ✅ | | +| Discord | ✅ | | +| Telegram | ✅ | | +| Slack | ✅ | | + +### 大模型能力 + +| 模型 | 狀態 | 備註 | +| --- | --- | --- | +| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 介面格式模型 | +| [DeepSeek](https://www.deepseek.com/) | ✅ | | +| [Moonshot](https://www.moonshot.cn/) | ✅ | | +| [Anthropic](https://www.anthropic.com/) | ✅ | | +| [xAI](https://x.ai/) | ✅ | | +| [智譜AI](https://open.bigmodel.cn/) | ✅ | | +| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 | +| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 | +| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 | +| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 | +| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | | +| [Dify](https://dify.ai) | ✅ | LLMOps 平台 | +| [Ollama](https://ollama.com/) | ✅ | 本地大模型運行平台 | +| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型運行平台 | +| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型介面聚合平台 | +| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 | +| [阿里雲百煉](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 | +| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 | +| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 | +| [MCP](https://modelcontextprotocol.io/) | ✅ | 支援通過 MCP 協議獲取工具 | + +### TTS + +| 平台/模型 | 備註 | +| --- | --- | +| [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) | +| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) | +| [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) | + +### 文生圖 + +| 平台/模型 | 備註 | +| --- | --- | +| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) + +## 😘 社群貢獻 + +感謝以下[程式碼貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)和社群裡其他成員對 LangBot 的貢獻： + + + + \ No newline at end of file diff --git a/libs/dingtalk_api/api.py b/libs/dingtalk_api/api.py index d323df1e..3d483a3a 100644 --- a/libs/dingtalk_api/api.py +++ b/libs/dingtalk_api/api.py @@ -253,6 +253,43 @@ class DingTalkClient: await self.logger.error(f'failed to send proactive massage to group: {traceback.format_exc()}') raise Exception(f'failed to send proactive massage to group: {traceback.format_exc()}') + async def create_and_card( + self, temp_card_id: str, incoming_message: dingtalk_stream.ChatbotMessage, quote_origin: bool = False + ): + content_key = 'content' + card_data = {content_key: ''} + + card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message) + # print(card_instance) + # 先投放卡片: https://open.dingtalk.com/document/orgapp/create-and-deliver-cards + card_instance_id = await card_instance.async_create_and_deliver_card( + temp_card_id, + card_data, + ) + return card_instance, card_instance_id + + async def send_card_message(self, card_instance, card_instance_id: str, content: str, is_final: bool): + content_key = 'content' + try: + await card_instance.async_streaming( + card_instance_id, + content_key=content_key, + content_value=content, + append=False, + finished=is_final, + failed=False, + ) + except Exception as e: + self.logger.exception(e) + await card_instance.async_streaming( + card_instance_id, + content_key=content_key, + content_value='', + append=False, + finished=is_final, + failed=True, + ) + async def start(self): """启动 WebSocket 连接，监听消息""" await self.client.start() diff --git a/libs/wechatpad_api/__init__.py b/libs/wechatpad_api/__init__.py index ff27058b..9ac533f7 100644 --- a/libs/wechatpad_api/__init__.py +++ b/libs/wechatpad_api/__init__.py @@ -1,4 +1 @@ -from .client import WeChatPadClient - - -__all__ = ['WeChatPadClient'] +from .client import WeChatPadClient as WeChatPadClient diff --git a/main.py b/main.py index d02d527e..bf6cd39a 100644 --- a/main.py +++ b/main.py @@ -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 """ diff --git a/pkg/api/http/controller/group.py b/pkg/api/http/controller/group.py index ce366539..8ab4f4d9 100644 --- a/pkg/api/http/controller/group.py +++ b/pkg/api/http/controller/group.py @@ -11,10 +11,10 @@ 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) -> None: +def group_class(name: str, path: str) -> typing.Callable[[typing.Type[RouterGroup]], typing.Type[RouterGroup]]: """注册一个 RouterGroup""" def decorator(cls: typing.Type[RouterGroup]) -> typing.Type[RouterGroup]: @@ -27,7 +27,7 @@ def group_class(name: str, path: str) -> None: 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( { @@ -120,6 +121,6 @@ class RouterGroup(abc.ABC): } ) - def http_status(self, status: int, code: int, msg: str) -> quart.Response: + 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) diff --git a/pkg/api/http/controller/groups/files.py b/pkg/api/http/controller/groups/files.py index 0a8b2210..b3c1a3f1 100644 --- a/pkg/api/http/controller/groups/files.py +++ b/pkg/api/http/controller/groups/files.py @@ -2,6 +2,10 @@ from __future__ import annotations import quart import mimetypes +import uuid +import asyncio + +import quart.datastructures from .. import group @@ -20,3 +24,23 @@ class FilesRouterGroup(group.RouterGroup): mime_type = 'image/jpeg' return quart.Response(image_bytes, mimetype=mime_type) + + @self.route('/documents', methods=['POST'], auth_type=group.AuthType.USER_TOKEN) + async def _() -> quart.Response: + request = quart.request + # get file bytes from 'file' + file = (await request.files)['file'] + assert isinstance(file, quart.datastructures.FileStorage) + + file_bytes = await asyncio.to_thread(file.stream.read) + extension = file.filename.split('.')[-1] + file_name = file.filename.split('.')[0] + + 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( + data={ + 'file_id': file_key, + } + ) diff --git a/pkg/api/http/controller/groups/knowledge/__init__.py b/pkg/api/http/controller/groups/knowledge/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pkg/api/http/controller/groups/knowledge/base.py b/pkg/api/http/controller/groups/knowledge/base.py new file mode 100644 index 00000000..a5bed5df --- /dev/null +++ b/pkg/api/http/controller/groups/knowledge/base.py @@ -0,0 +1,90 @@ +import quart +from ... import group + + +@group.group_class('knowledge_base', '/api/v1/knowledge/bases') +class KnowledgeBaseRouterGroup(group.RouterGroup): + async def initialize(self) -> None: + @self.route('', methods=['POST', 'GET']) + async def handle_knowledge_bases() -> quart.Response: + if quart.request.method == 'GET': + knowledge_bases = await self.ap.knowledge_service.get_knowledge_bases() + return self.success(data={'bases': knowledge_bases}) + + elif quart.request.method == 'POST': + json_data = await quart.request.json + knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data) + return self.success(data={'uuid': knowledge_base_uuid}) + + return self.http_status(405, -1, 'Method not allowed') + + @self.route( + '/', + methods=['GET', 'DELETE', 'PUT'], + ) + async def handle_specific_knowledge_base(knowledge_base_uuid: str) -> quart.Response: + if quart.request.method == 'GET': + knowledge_base = await self.ap.knowledge_service.get_knowledge_base(knowledge_base_uuid) + + if knowledge_base is None: + return self.http_status(404, -1, 'knowledge base not found') + + return self.success( + data={ + '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({}) + + @self.route( + '//files', + methods=['GET', 'POST'], + ) + async def get_knowledge_base_files(knowledge_base_uuid: str) -> str: + if quart.request.method == 'GET': + files = await self.ap.knowledge_service.get_files_by_knowledge_base(knowledge_base_uuid) + return self.success( + data={ + 'files': files, + } + ) + + elif quart.request.method == 'POST': + json_data = await quart.request.json + file_id = json_data.get('file_id') + if not file_id: + return self.http_status(400, -1, 'File ID is required') + + # 调用服务层方法将文件与知识库关联 + task_id = await self.ap.knowledge_service.store_file(knowledge_base_uuid, file_id) + return self.success( + { + 'task_id': task_id, + } + ) + + @self.route( + '//files/', + methods=['DELETE'], + ) + 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( + '//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}) diff --git a/pkg/api/http/controller/groups/pipelines/pipelines.py b/pkg/api/http/controller/groups/pipelines/pipelines.py index 96ca239a..e3d08e28 100644 --- a/pkg/api/http/controller/groups/pipelines/pipelines.py +++ b/pkg/api/http/controller/groups/pipelines/pipelines.py @@ -11,7 +11,11 @@ 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 diff --git a/pkg/api/http/controller/groups/pipelines/webchat.py b/pkg/api/http/controller/groups/pipelines/webchat.py index 005738db..13f955d8 100644 --- a/pkg/api/http/controller/groups/pipelines/webchat.py +++ b/pkg/api/http/controller/groups/pipelines/webchat.py @@ -1,3 +1,5 @@ +import json + import quart from ... import group @@ -8,11 +10,19 @@ 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""" + + async def stream_generator(generator): + yield 'data: {"type": "start"}\n\n' + async for message in generator: + yield f'data: {json.dumps({"message": message})}\n\n' + yield 'data: {"type": "end"}\n\n' + try: data = await quart.request.get_json() session_type = data.get('session_type', 'person') message_chain_obj = data.get('message', []) + is_stream = data.get('is_stream', False) if not message_chain_obj: return self.http_status(400, -1, 'message is required') @@ -25,20 +35,40 @@ class WebChatDebugRouterGroup(group.RouterGroup): if not webchat_adapter: return self.http_status(404, -1, 'WebChat adapter not found') - result = await webchat_adapter.send_webchat_message(pipeline_uuid, session_type, message_chain_obj) - - return self.success( - data={ - 'message': result, + if is_stream: + generator = webchat_adapter.send_webchat_message( + pipeline_uuid, session_type, message_chain_obj, is_stream + ) + # 设置正确的响应头 + headers = { + 'Content-Type': 'text/event-stream', + 'Transfer-Encoding': 'chunked', + 'Cache-Control': 'no-cache', + 'Connection': 'keep-alive', } - ) + return quart.Response(stream_generator(generator), mimetype='text/event-stream', headers=headers) + + else: # non-stream + result = None + async for message in webchat_adapter.send_webchat_message( + pipeline_uuid, session_type, message_chain_obj + ): + result = message + if result is not None: + return self.success( + data={ + 'message': result, + } + ) + else: + return self.http_status(400, -1, 'message is required') except Exception as e: return self.http_status(500, -1, f'Internal server error: {str(e)}') @self.route('/messages/', 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 +87,7 @@ class WebChatDebugRouterGroup(group.RouterGroup): @self.route('/reset/', 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') diff --git a/pkg/api/http/controller/groups/provider/models.py b/pkg/api/http/controller/groups/provider/models.py index bb77986c..0de0c922 100644 --- a/pkg/api/http/controller/groups/provider/models.py +++ b/pkg/api/http/controller/groups/provider/models.py @@ -9,18 +9,18 @@ class LLMModelsRouterGroup(group.RouterGroup): @self.route('', methods=['GET', 'POST']) async def _() -> str: if quart.request.method == 'GET': - return self.success(data={'models': await self.ap.model_service.get_llm_models()}) + return self.success(data={'models': await self.ap.llm_model_service.get_llm_models()}) elif quart.request.method == 'POST': json_data = await quart.request.json - model_uuid = await self.ap.model_service.create_llm_model(json_data) + model_uuid = await self.ap.llm_model_service.create_llm_model(json_data) return self.success(data={'uuid': model_uuid}) @self.route('/', methods=['GET', 'PUT', 'DELETE']) async def _(model_uuid: str) -> str: if quart.request.method == 'GET': - model = await self.ap.model_service.get_llm_model(model_uuid) + model = await self.ap.llm_model_service.get_llm_model(model_uuid) if model is None: return self.http_status(404, -1, 'model not found') @@ -29,11 +29,11 @@ class LLMModelsRouterGroup(group.RouterGroup): elif quart.request.method == 'PUT': json_data = await quart.request.json - await self.ap.model_service.update_llm_model(model_uuid, json_data) + await self.ap.llm_model_service.update_llm_model(model_uuid, json_data) return self.success() elif quart.request.method == 'DELETE': - await self.ap.model_service.delete_llm_model(model_uuid) + await self.ap.llm_model_service.delete_llm_model(model_uuid) return self.success() @@ -41,6 +41,49 @@ class LLMModelsRouterGroup(group.RouterGroup): async def _(model_uuid: str) -> str: json_data = await quart.request.json - await self.ap.model_service.test_llm_model(model_uuid, json_data) + await self.ap.llm_model_service.test_llm_model(model_uuid, json_data) + + return self.success() + + +@group.group_class('models/embedding', '/api/v1/provider/models/embedding') +class EmbeddingModelsRouterGroup(group.RouterGroup): + async def initialize(self) -> None: + @self.route('', methods=['GET', 'POST']) + async def _() -> str: + if quart.request.method == 'GET': + return self.success(data={'models': await self.ap.embedding_models_service.get_embedding_models()}) + elif quart.request.method == 'POST': + json_data = await quart.request.json + + model_uuid = await self.ap.embedding_models_service.create_embedding_model(json_data) + + return self.success(data={'uuid': model_uuid}) + + @self.route('/', methods=['GET', 'PUT', 'DELETE']) + async def _(model_uuid: str) -> str: + if quart.request.method == 'GET': + model = await self.ap.embedding_models_service.get_embedding_model(model_uuid) + + if model is None: + return self.http_status(404, -1, 'model not found') + + return self.success(data={'model': model}) + elif quart.request.method == 'PUT': + json_data = await quart.request.json + + await self.ap.embedding_models_service.update_embedding_model(model_uuid, json_data) + + return self.success() + elif quart.request.method == 'DELETE': + await self.ap.embedding_models_service.delete_embedding_model(model_uuid) + + return self.success() + + @self.route('//test', methods=['POST']) + async def _(model_uuid: str) -> str: + json_data = await quart.request.json + + await self.ap.embedding_models_service.test_embedding_model(model_uuid, json_data) return self.success() diff --git a/pkg/api/http/controller/groups/provider/requesters.py b/pkg/api/http/controller/groups/provider/requesters.py index 0f999288..af9e1540 100644 --- a/pkg/api/http/controller/groups/provider/requesters.py +++ b/pkg/api/http/controller/groups/provider/requesters.py @@ -8,7 +8,8 @@ class RequestersRouterGroup(group.RouterGroup): async def initialize(self) -> None: @self.route('', methods=['GET']) async def _() -> quart.Response: - return self.success(data={'requesters': self.ap.model_mgr.get_available_requesters_info()}) + model_type = quart.request.args.get('type', '') + return self.success(data={'requesters': self.ap.model_mgr.get_available_requesters_info(model_type)}) @self.route('/', methods=['GET']) async def _(requester_name: str) -> quart.Response: diff --git a/pkg/api/http/controller/groups/user.py b/pkg/api/http/controller/groups/user.py index 498efaa4..f1525a6b 100644 --- a/pkg/api/http/controller/groups/user.py +++ b/pkg/api/http/controller/groups/user.py @@ -1,5 +1,6 @@ import quart import argon2 +import asyncio from .. import group @@ -13,7 +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 @@ -31,7 +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}) @@ -40,3 +41,45 @@ class UserRouterGroup(group.RouterGroup): token = await self.ap.user_service.generate_jwt_token(user_email) return self.success(data={'token': token}) + + @self.route('/reset-password', methods=['POST'], auth_type=group.AuthType.NONE) + async def _() -> str: + json_data = await quart.request.json + + user_email = json_data['user'] + recovery_key = json_data['recovery_key'] + new_password = json_data['new_password'] + + # hard sleep 3s for security + await asyncio.sleep(3) + + if not await self.ap.user_service.is_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') + + if recovery_key != self.ap.instance_config.data['system']['recovery_key']: + return self.http_status(403, -1, 'Invalid recovery key') + + await self.ap.user_service.reset_password(user_email, new_password) + + return self.success(data={'user': user_email}) + + @self.route('/change-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN) + async def _(user_email: str) -> str: + json_data = await quart.request.json + + current_password = json_data['current_password'] + new_password = json_data['new_password'] + + try: + await self.ap.user_service.change_password(user_email, current_password, new_password) + except argon2.exceptions.VerifyMismatchError: + return self.http_status(400, -1, 'Current password is incorrect') + except ValueError as e: + return self.http_status(400, -1, str(e)) + + return self.success(data={'user': user_email}) diff --git a/pkg/api/http/controller/main.py b/pkg/api/http/controller/main.py index eb434d88..e45b461d 100644 --- a/pkg/api/http/controller/main.py +++ b/pkg/api/http/controller/main.py @@ -14,11 +14,13 @@ from . import group from .groups import provider as groups_provider from .groups import platform as groups_platform from .groups import pipelines as groups_pipelines +from .groups import knowledge as groups_knowledge importutil.import_modules_in_pkg(groups) importutil.import_modules_in_pkg(groups_provider) importutil.import_modules_in_pkg(groups_platform) importutil.import_modules_in_pkg(groups_pipelines) +importutil.import_modules_in_pkg(groups_knowledge) class HTTPController: @@ -45,7 +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( diff --git a/pkg/api/http/service/bot.py b/pkg/api/http/service/bot.py index 8d43965f..3ced0e51 100644 --- a/pkg/api/http/service/bot.py +++ b/pkg/api/http/service/bot.py @@ -10,7 +10,7 @@ from ....entity.persistence import pipeline as persistence_pipeline class BotService: - """机器人服务""" + """Bot service""" ap: app.Application @@ -63,7 +63,7 @@ class BotService: return persistence_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()) @@ -87,7 +87,7 @@ 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'] @@ -123,7 +123,7 @@ 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) diff --git a/pkg/api/http/service/knowledge.py b/pkg/api/http/service/knowledge.py new file mode 100644 index 00000000..7b748bc6 --- /dev/null +++ b/pkg/api/http/service/knowledge.py @@ -0,0 +1,120 @@ +from __future__ import annotations + +import uuid +import sqlalchemy + +from ....core import app +from ....entity.persistence import rag as persistence_rag + + +class KnowledgeService: + """知识库服务""" + + ap: app.Application + + def __init__(self, ap: app.Application) -> None: + self.ap = ap + + async def get_knowledge_bases(self) -> list[dict]: + """获取所有知识库""" + result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase)) + knowledge_bases = result.all() + return [ + self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base) + for knowledge_base in knowledge_bases + ] + + async def get_knowledge_base(self, kb_uuid: str) -> dict | None: + """获取知识库""" + result = await self.ap.persistence_mgr.execute_async( + sqlalchemy.select(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid) + ) + knowledge_base = result.first() + if knowledge_base is None: + return None + return self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base) + + async def create_knowledge_base(self, kb_data: dict) -> str: + """创建知识库""" + kb_data['uuid'] = str(uuid.uuid4()) + await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.KnowledgeBase).values(kb_data)) + + kb = await self.get_knowledge_base(kb_data['uuid']) + + await self.ap.rag_mgr.load_knowledge_base(kb) + + return kb_data['uuid'] + + 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_from_runtime(kb_uuid) + + kb = await self.get_knowledge_base(kb_uuid) + + await self.ap.rag_mgr.load_knowledge_base(kb) + + async def store_file(self, kb_uuid: str, file_id: str) -> int: + """存储文件""" + # await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(kb_id=kb_uuid, file_id=file_id)) + # await self.ap.rag_mgr.store_file(file_id) + 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 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, runtime_kb.knowledge_base_entity.top_k) + ] + + 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( + sqlalchemy.select(persistence_rag.File).where(persistence_rag.File.kb_id == kb_uuid) + ) + files = result.all() + return [self.ap.persistence_mgr.serialize_model(persistence_rag.File, file) for file in files] + + async def delete_file(self, kb_uuid: str, file_id: str) -> None: + """删除文件""" + 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') + 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) + ) + + # 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) + ) diff --git a/pkg/api/http/service/model.py b/pkg/api/http/service/model.py index e04a50b2..036c1b9c 100644 --- a/pkg/api/http/service/model.py +++ b/pkg/api/http/service/model.py @@ -10,7 +10,7 @@ from ....provider.modelmgr import requester as model_requester from langbot_plugin.api.entities.builtin.provider import message as provider_message -class ModelsService: +class LLMModelsService: ap: app.Application def __init__(self, ap: app.Application) -> None: @@ -109,5 +109,91 @@ class ModelsService: model=runtime_llm_model, messages=[provider_message.Message(role='user', content='Hello, world!')], funcs=[], + extra_args=model_data.get('extra_args', {}), + ) + + +class EmbeddingModelsService: + ap: app.Application + + def __init__(self, ap: app.Application) -> None: + self.ap = ap + + async def get_embedding_models(self) -> list[dict]: + result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel)) + + models = result.all() + return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model) for model in models] + + async def create_embedding_model(self, model_data: dict) -> str: + model_data['uuid'] = str(uuid.uuid4()) + + await self.ap.persistence_mgr.execute_async( + sqlalchemy.insert(persistence_model.EmbeddingModel).values(**model_data) + ) + + embedding_model = await self.get_embedding_model(model_data['uuid']) + + await self.ap.model_mgr.load_embedding_model(embedding_model) + + return model_data['uuid'] + + async def get_embedding_model(self, model_uuid: str) -> dict | None: + result = await self.ap.persistence_mgr.execute_async( + sqlalchemy.select(persistence_model.EmbeddingModel).where( + persistence_model.EmbeddingModel.uuid == model_uuid + ) + ) + + model = result.first() + + if model is None: + return None + + return self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model) + + async def update_embedding_model(self, model_uuid: str, model_data: dict) -> None: + if 'uuid' in model_data: + del model_data['uuid'] + + await self.ap.persistence_mgr.execute_async( + sqlalchemy.update(persistence_model.EmbeddingModel) + .where(persistence_model.EmbeddingModel.uuid == model_uuid) + .values(**model_data) + ) + + await self.ap.model_mgr.remove_embedding_model(model_uuid) + + embedding_model = await self.get_embedding_model(model_uuid) + + await self.ap.model_mgr.load_embedding_model(embedding_model) + + async def delete_embedding_model(self, model_uuid: str) -> None: + await self.ap.persistence_mgr.execute_async( + sqlalchemy.delete(persistence_model.EmbeddingModel).where( + persistence_model.EmbeddingModel.uuid == model_uuid + ) + ) + + await self.ap.model_mgr.remove_embedding_model(model_uuid) + + async def test_embedding_model(self, model_uuid: str, model_data: dict) -> None: + runtime_embedding_model: model_requester.RuntimeEmbeddingModel | None = None + + if model_uuid != '_': + for model in self.ap.model_mgr.embedding_models: + if model.model_entity.uuid == model_uuid: + runtime_embedding_model = model + break + + if runtime_embedding_model is None: + raise Exception('model not found') + + else: + runtime_embedding_model = await self.ap.model_mgr.init_runtime_embedding_model(model_data) + + await runtime_embedding_model.requester.invoke_embedding( + model=runtime_embedding_model, + input_text=['Hello, world!'], extra_args={}, ) diff --git a/pkg/api/http/service/pipeline.py b/pkg/api/http/service/pipeline.py index f0f6c083..d3d0bfa7 100644 --- a/pkg/api/http/service/pipeline.py +++ b/pkg/api/http/service/pipeline.py @@ -38,9 +38,21 @@ class PipelineService: self.ap.pipeline_config_meta_output.data, ] - async def get_pipelines(self) -> list[dict]: - result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline)) + async def get_pipelines(self, sort_by: str = 'created_at', sort_order: str = 'DESC') -> list[dict]: + 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) diff --git a/pkg/api/http/service/user.py b/pkg/api/http/service/user.py index 782aad75..b2403d15 100644 --- a/pkg/api/http/service/user.py +++ b/pkg/api/http/service/user.py @@ -73,3 +73,27 @@ class UserService: jwt_secret = self.ap.instance_config.data['system']['jwt']['secret'] return jwt.decode(token, jwt_secret, algorithms=['HS256'])['user'] + + async def reset_password(self, user_email: str, new_password: str) -> None: + ph = argon2.PasswordHasher() + + hashed_password = ph.hash(new_password) + + await self.ap.persistence_mgr.execute_async( + sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password) + ) + + async def change_password(self, user_email: str, current_password: str, new_password: str) -> None: + ph = argon2.PasswordHasher() + + user_obj = await self.get_user_by_email(user_email) + if user_obj is None: + raise ValueError('User not found') + + ph.verify(user_obj.password, current_password) + + hashed_password = ph.hash(new_password) + + await self.ap.persistence_mgr.execute_async( + sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password) + ) diff --git a/pkg/config/impls/json.py b/pkg/config/impls/json.py index 07fc533c..44b4843c 100644 --- a/pkg/config/impls/json.py +++ b/pkg/config/impls/json.py @@ -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: diff --git a/pkg/config/impls/pymodule.py b/pkg/config/impls/pymodule.py index 2311992e..c3d04bc8 100644 --- a/pkg/config/impls/pymodule.py +++ b/pkg/config/impls/pymodule.py @@ -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') diff --git a/pkg/config/impls/yaml.py b/pkg/config/impls/yaml.py index 55045186..0d69ef9e 100644 --- a/pkg/config/impls/yaml.py +++ b/pkg/config/impls/yaml.py @@ -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: diff --git a/pkg/config/manager.py b/pkg/config/manager.py index c2e6bdf4..d552b038 100644 --- a/pkg/config/manager.py +++ b/pkg/config/manager.py @@ -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 - 需要符合 JSON Schema Draft 7 规范 + """Config file schema + 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 - template_name (str): 模板文件名 - completion (bool): 是否自动补全内存中的配置文件 + config_name (str): Config file name + template_name (str): Template file name + 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 - template_name (str): 模板文件名 - template_data (dict): 模板数据 - completion (bool): 是否自动补全内存中的配置文件 + config_name (str): Config file name + template_name (str): Template file name + template_data (dict): Template data + 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 - template_name (str): 模板文件名 - template_data (dict): 模板数据 - completion (bool): 是否自动补全内存中的配置文件 + config_name (str): Config file name + template_name (str): Template file name + template_data (dict): Template data + 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) diff --git a/pkg/config/model.py b/pkg/config/model.py index f3536804..8b040f05 100644 --- a/pkg/config/model.py +++ b/pkg/config/model.py @@ -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: diff --git a/pkg/core/app.py b/pkg/core/app.py index cd140413..27b780f6 100644 --- a/pkg/core/app.py +++ b/pkg/core/app.py @@ -21,15 +21,18 @@ from ..api.http.service import user as user_service from ..api.http.service import model as model_service from ..api.http.service import pipeline as pipeline_service from ..api.http.service import bot as bot_service +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 . import taskmgr from . import entities as core_entities +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 @@ -46,10 +49,12 @@ class Application: model_mgr: llm_model_mgr.ModelManager = None - # TODO 移动到 pipeline 里 + rag_mgr: rag_mgr.RAGManager = None + + # 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 @@ -63,7 +68,7 @@ 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 @@ -92,6 +97,8 @@ 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 @@ -102,12 +109,16 @@ class Application: user_service: user_service.UserService = None - model_service: model_service.ModelsService = None + llm_model_service: model_service.LLMModelsService = None + + embedding_models_service: model_service.EmbeddingModelsService = None pipeline_service: pipeline_service.PipelineService = None bot_service: bot_service.BotService = None + knowledge_service: knowledge_service.KnowledgeService = None + def __init__(self): pass @@ -142,6 +153,7 @@ class Application: name='http-api-controller', scopes=[core_entities.LifecycleControlScope.APPLICATION], ) + self.task_mgr.create_task( never_ending(), name='never-ending-task', @@ -153,14 +165,14 @@ 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()}') def dispose(self): self.plugin_connector.dispose() 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') diff --git a/pkg/core/boot.py b/pkg/core/boot.py index 8aa403ad..11a2d5e2 100644 --- a/pkg/core/boot.py +++ b/pkg/core/boot.py @@ -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() @@ -47,12 +47,12 @@ 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): app_inst.dispose() - print('[Signal] 程序退出.') + print('[Signal] Program exit.') os._exit(0) signal.signal(signal.SIGINT, signal_handler) diff --git a/pkg/core/bootutils/deps.py b/pkg/core/bootutils/deps.py index b403bf8d..1a439af8 100644 --- a/pkg/core/bootutils/deps.py +++ b/pkg/core/bootutils/deps.py @@ -2,8 +2,8 @@ import pip import os from ...utils import pkgmgr -# 检查依赖，防止用户未安装 -# 左边为引入名称，右边为依赖名称 +# Check dependencies to prevent users from not installing +# 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) diff --git a/pkg/core/bootutils/log.py b/pkg/core/bootutils/log.py index eb6806fa..631b05e2 100644 --- a/pkg/core/bootutils/log.py +++ b/pkg/core/bootutils/log.py @@ -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 - # -8表示占位符，让输出左对齐，输出长度都为8位 - datefmt='%Y-%m-%d %H:%M:%S', # 时间输出的格式 + # Log output format + # -8 is a placeholder, left-align the output, and output length is 8 + datefmt='%Y-%m-%d %H:%M:%S', # Time output format handlers=[logging.NullHandler()], ) diff --git a/pkg/core/migration.py b/pkg/core/migration.py index e97c0cf3..a921e6c7 100644 --- a/pkg/core/migration.py +++ b/pkg/core/migration.py @@ -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 diff --git a/pkg/core/note.py b/pkg/core/note.py index 07171581..b4c37ce1 100644 --- a/pkg/core/note.py +++ b/pkg/core/note.py @@ -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 diff --git a/pkg/core/notes/n001_classic_msgs.py b/pkg/core/notes/n001_classic_msgs.py index 3f3bd8e0..265ddbe9 100644 --- a/pkg/core/notes/n001_classic_msgs.py +++ b/pkg/core/notes/n001_classic_msgs.py @@ -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 diff --git a/pkg/core/notes/n002_selection_mode_on_windows.py b/pkg/core/notes/n002_selection_mode_on_windows.py index 23bff24a..16028de1 100644 --- a/pkg/core/notes/n002_selection_mode_on_windows.py +++ b/pkg/core/notes/n002_selection_mode_on_windows.py @@ -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, + ) diff --git a/pkg/core/stage.py b/pkg/core/stage.py index 220c474d..1483e23a 100644 --- a/pkg/core/stage.py +++ b/pkg/core/stage.py @@ -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 diff --git a/pkg/core/stages/build_app.py b/pkg/core/stages/build_app.py index f4361008..54a64ae8 100644 --- a/pkg/core/stages/build_app.py +++ b/pkg/core/stages/build_app.py @@ -10,6 +10,7 @@ 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 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 @@ -17,18 +18,20 @@ from ...api.http.service import user as user_service from ...api.http.service import model as model_service from ...api.http.service import pipeline as pipeline_service from ...api.http.service import bot as bot_service +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) @@ -43,7 +46,7 @@ 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 @@ -92,6 +95,15 @@ class BuildAppStage(stage.BootingStage): await pipeline_mgr.initialize() ap.pipeline_mgr = pipeline_mgr + rag_mgr_inst = rag_mgr.RAGManager(ap) + 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 @@ -99,8 +111,11 @@ class BuildAppStage(stage.BootingStage): user_service_inst = user_service.UserService(ap) ap.user_service = user_service_inst - model_service_inst = model_service.ModelsService(ap) - ap.model_service = model_service_inst + llm_model_service_inst = model_service.LLMModelsService(ap) + ap.llm_model_service = llm_model_service_inst + + embedding_models_service_inst = model_service.EmbeddingModelsService(ap) + ap.embedding_models_service = embedding_models_service_inst pipeline_service_inst = pipeline_service.PipelineService(ap) ap.pipeline_service = pipeline_service_inst @@ -108,5 +123,8 @@ class BuildAppStage(stage.BootingStage): bot_service_inst = bot_service.BotService(ap) ap.bot_service = bot_service_inst + knowledge_service_inst = knowledge_service.KnowledgeService(ap) + ap.knowledge_service = knowledge_service_inst + ctrl = controller.Controller(ap) ap.ctrl = ctrl diff --git a/pkg/core/stages/genkeys.py b/pkg/core/stages/genkeys.py index c24ebd70..f0412b9d 100644 --- a/pkg/core/stages/genkeys.py +++ b/pkg/core/stages/genkeys.py @@ -7,11 +7,18 @@ 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) await ap.instance_config.dump_config() + + if 'recovery_key' not in ap.instance_config.data['system']: + ap.instance_config.data['system']['recovery_key'] = '' + + if not ap.instance_config.data['system']['recovery_key']: + ap.instance_config.data['system']['recovery_key'] = secrets.token_hex(3).upper() + await ap.instance_config.dump_config() diff --git a/pkg/core/stages/load_config.py b/pkg/core/stages/load_config.py index ef5f611b..0474b33a 100644 --- a/pkg/core/stages/load_config.py +++ b/pkg/core/stages/load_config.py @@ -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'): diff --git a/pkg/core/stages/migrate.py b/pkg/core/stages/migrate.py index 02b03256..229e0060 100644 --- a/pkg/core/stages/migrate.py +++ b/pkg/core/stages/migrate.py @@ -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') diff --git a/pkg/core/stages/setup_logger.py b/pkg/core/stages/setup_logger.py index 0c630175..1f7c81ac 100644 --- a/pkg/core/stages/setup_logger.py +++ b/pkg/core/stages/setup_logger.py @@ -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 = [] diff --git a/pkg/core/stages/show_notes.py b/pkg/core/stages/show_notes.py index 5fa7ff08..d0f861ba 100644 --- a/pkg/core/stages/show_notes.py +++ b/pkg/core/stages/show_notes.py @@ -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: diff --git a/pkg/core/taskmgr.py b/pkg/core/taskmgr.py index 0f756118..ca6eb029 100644 --- a/pkg/core/taskmgr.py +++ b/pkg/core/taskmgr.py @@ -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 - """任务类型""" + task_type: str = 'system' # Task type: system or user + """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 - """任务种类""" + kind: str = 'system_task' # Task type determined by the initiator, usually the same task type + """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 - 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""" + """Save all asynchronous tasks in the app + 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 diff --git a/pkg/entity/persistence/bot.py b/pkg/entity/persistence/bot.py index 3c08f4ec..08eda478 100644 --- a/pkg/entity/persistence/bot.py +++ b/pkg/entity/persistence/bot.py @@ -4,7 +4,7 @@ from .base import Base class Bot(Base): - """机器人""" + """Bot""" __tablename__ = 'bots' diff --git a/pkg/entity/persistence/metadata.py b/pkg/entity/persistence/metadata.py index d9e03663..4db732b9 100644 --- a/pkg/entity/persistence/metadata.py +++ b/pkg/entity/persistence/metadata.py @@ -12,7 +12,7 @@ initial_metadata = [ class Metadata(Base): - """数据库元数据""" + """Database metadata""" __tablename__ = 'metadata' diff --git a/pkg/entity/persistence/model.py b/pkg/entity/persistence/model.py index 9eb2ccef..e9a104c4 100644 --- a/pkg/entity/persistence/model.py +++ b/pkg/entity/persistence/model.py @@ -4,7 +4,7 @@ from .base import Base class LLMModel(Base): - """LLM 模型""" + """LLM model""" __tablename__ = 'llm_models' @@ -23,3 +23,24 @@ class LLMModel(Base): server_default=sqlalchemy.func.now(), onupdate=sqlalchemy.func.now(), ) + + +class EmbeddingModel(Base): + """Embedding 模型""" + + __tablename__ = 'embedding_models' + + uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True) + name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) + description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) + requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) + requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={}) + api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False) + extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={}) + created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now()) + updated_at = sqlalchemy.Column( + sqlalchemy.DateTime, + nullable=False, + server_default=sqlalchemy.func.now(), + onupdate=sqlalchemy.func.now(), + ) diff --git a/pkg/entity/persistence/pipeline.py b/pkg/entity/persistence/pipeline.py index 56e2cae9..3a21dbf2 100644 --- a/pkg/entity/persistence/pipeline.py +++ b/pkg/entity/persistence/pipeline.py @@ -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) diff --git a/pkg/entity/persistence/plugin.py b/pkg/entity/persistence/plugin.py index aebed2f0..61629586 100644 --- a/pkg/entity/persistence/plugin.py +++ b/pkg/entity/persistence/plugin.py @@ -4,7 +4,7 @@ from .base import Base class PluginSetting(Base): - """插件配置""" + """Plugin setting""" __tablename__ = 'plugin_settings' diff --git a/pkg/entity/persistence/rag.py b/pkg/entity/persistence/rag.py new file mode 100644 index 00000000..0ff93d28 --- /dev/null +++ b/pkg/entity/persistence/rag.py @@ -0,0 +1,50 @@ +import sqlalchemy +from .base import Base + +# Base = declarative_base() +# DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./rag_knowledge.db') +# print("Using database URL:", DATABASE_URL) + + +# engine = create_engine(DATABASE_URL, connect_args={'check_same_thread': False}) + +# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) + +# def create_db_and_tables(): +# """Creates all database tables defined in the Base.""" +# Base.metadata.create_all(bind=engine) +# print('Database tables created or already exist.') + + +class KnowledgeBase(Base): + __tablename__ = 'knowledge_bases' + uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True) + name = sqlalchemy.Column(sqlalchemy.String, index=True) + description = sqlalchemy.Column(sqlalchemy.Text) + created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now()) + embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='') + top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5) + + +class File(Base): + __tablename__ = 'knowledge_base_files' + uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True) + kb_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) + file_name = sqlalchemy.Column(sqlalchemy.String) + extension = sqlalchemy.Column(sqlalchemy.String) + created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now()) + status = sqlalchemy.Column(sqlalchemy.String, default='pending') # pending, processing, completed, failed + + +class Chunk(Base): + __tablename__ = 'knowledge_base_chunks' + uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True) + file_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) + text = sqlalchemy.Column(sqlalchemy.Text) + + +# class Vector(Base): +# __tablename__ = 'knowledge_base_vectors' +# uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True) +# chunk_id = sqlalchemy.Column(sqlalchemy.String, nullable=True) +# embedding = sqlalchemy.Column(sqlalchemy.LargeBinary) diff --git a/pkg/entity/persistence/vector.py b/pkg/entity/persistence/vector.py new file mode 100644 index 00000000..465125f5 --- /dev/null +++ b/pkg/entity/persistence/vector.py @@ -0,0 +1,13 @@ +from sqlalchemy import Column, Integer, ForeignKey, LargeBinary +from sqlalchemy.orm import declarative_base, relationship + +Base = declarative_base() + + +class Vector(Base): + __tablename__ = 'vectors' + id = Column(Integer, primary_key=True, index=True) + chunk_id = Column(Integer, ForeignKey('chunks.id'), unique=True) + embedding = Column(LargeBinary) # Store embeddings as binary + + chunk = relationship('Chunk', back_populates='vector') diff --git a/pkg/entity/rag/__init__.py b/pkg/entity/rag/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pkg/entity/rag/retriever.py b/pkg/entity/rag/retriever.py new file mode 100644 index 00000000..becaf8db --- /dev/null +++ b/pkg/entity/rag/retriever.py @@ -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 diff --git a/pkg/persistence/database.py b/pkg/persistence/database.py index 528c6a34..4debb03d 100644 --- a/pkg/persistence/database.py +++ b/pkg/persistence/database.py @@ -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 diff --git a/pkg/persistence/databases/sqlite.py b/pkg/persistence/databases/sqlite.py index 7b095e61..c1337459 100644 --- a/pkg/persistence/databases/sqlite.py +++ b/pkg/persistence/databases/sqlite.py @@ -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' diff --git a/pkg/persistence/mgr.py b/pkg/persistence/mgr.py index 33f71769..9b926733 100644 --- a/pkg/persistence/mgr.py +++ b/pkg/persistence/mgr.py @@ -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 @@ -111,7 +111,7 @@ 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, } diff --git a/pkg/persistence/migration.py b/pkg/persistence/migration.py index c191b686..294e30ca 100644 --- a/pkg/persistence/migration.py +++ b/pkg/persistence/migration.py @@ -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 diff --git a/pkg/persistence/migrations/dbm001_migrate_v3_config.py b/pkg/persistence/migrations/dbm001_migrate_v3_config.py index a1145527..58f05e04 100644 --- a/pkg/persistence/migrations/dbm001_migrate_v3_config.py +++ b/pkg/persistence/migrations/dbm001_migrate_v3_config.py @@ -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。 - 迁移后，之前的配置文件都保存到 data/legacy/config 下。 - 迁移后，data/metadata/ 下的所有配置文件都保存到 data/legacy/metadata 下。 + Migrate all config files under data/config. + After migration, all previous config files are saved under data/legacy/config. + 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 ======= - # 只迁移当前选中的模型 + # ======= Migrate model ======= + # 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 ======= - # 修改到默认流水线 + # ======= Migrate pipeline config ======= + # 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 ======= - # 只迁移启用的机器人 + # ======= Migrate bot ======= + # 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""" diff --git a/pkg/persistence/migrations/dbm002_combine_quote_msg_config.py b/pkg/persistence/migrations/dbm002_combine_quote_msg_config.py index cebf403b..349bb0c2 100644 --- a/pkg/persistence/migrations/dbm002_combine_quote_msg_config.py +++ b/pkg/persistence/migrations/dbm002_combine_quote_msg_config.py @@ -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 diff --git a/pkg/persistence/migrations/dbm003_n8n_config.py b/pkg/persistence/migrations/dbm003_n8n_config.py index 8705040b..15484f22 100644 --- a/pkg/persistence/migrations/dbm003_n8n_config.py +++ b/pkg/persistence/migrations/dbm003_n8n_config.py @@ -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 diff --git a/pkg/persistence/migrations/dbm004_rag_kb_uuid.py b/pkg/persistence/migrations/dbm004_rag_kb_uuid.py new file mode 100644 index 00000000..b45cfa78 --- /dev/null +++ b/pkg/persistence/migrations/dbm004_rag_kb_uuid.py @@ -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 diff --git a/pkg/persistence/migrations/dbm005_pipeline_remove_cot_config.py b/pkg/persistence/migrations/dbm005_pipeline_remove_cot_config.py new file mode 100644 index 00000000..8e4d544d --- /dev/null +++ b/pkg/persistence/migrations/dbm005_pipeline_remove_cot_config.py @@ -0,0 +1,38 @@ +from .. import migration + +import sqlalchemy + +from ...entity.persistence import pipeline as persistence_pipeline + + +@migration.migration_class(5) +class DBMigratePipelineRemoveCotConfig(migration.DBMigration): + """Pipeline remove cot config""" + + async def upgrade(self): + """Upgrade""" + # 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 'remove-think' not in config['output']['misc']: + config['output']['misc']['remove-think'] = False + + 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): + """Downgrade""" + pass diff --git a/pkg/pipeline/bansess/bansess.py b/pkg/pipeline/bansess/bansess.py index 0cd498f6..15b68b08 100644 --- a/pkg/pipeline/bansess/bansess.py +++ b/pkg/pipeline/bansess/bansess.py @@ -6,9 +6,9 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @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 '', ) diff --git a/pkg/pipeline/cntfilter/filter.py b/pkg/pipeline/cntfilter/filter.py index dafc539a..58804fd8 100644 --- a/pkg/pipeline/cntfilter/filter.py +++ b/pkg/pipeline/cntfilter/filter.py @@ -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.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.PRE: Before message request to AI, the content to check is the user's input message. + 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: pipeline_query.Query, message: str = None, image_url=None) -> entities.FilterResult: """处理消息 - 分为前后阶段，具体取决于 enable_stages 的值。 - 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。 + It is divided into two stages, depending on the value of enable_stages. + 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 - image_url (str): 要检查的图片的 URL + message (str): Content to check + 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 diff --git a/pkg/pipeline/cntfilter/filters/banwords.py b/pkg/pipeline/cntfilter/filters/banwords.py index e04de8c4..05b25013 100644 --- a/pkg/pipeline/cntfilter/filters/banwords.py +++ b/pkg/pipeline/cntfilter/filters/banwords.py @@ -8,7 +8,7 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @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 diff --git a/pkg/pipeline/cntfilter/filters/cntignore.py b/pkg/pipeline/cntfilter/filters/cntignore.py index 0a3ef709..731ab392 100644 --- a/pkg/pipeline/cntfilter/filters/cntignore.py +++ b/pkg/pipeline/cntfilter/filters/cntignore.py @@ -8,7 +8,7 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @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( diff --git a/pkg/pipeline/longtext/longtext.py b/pkg/pipeline/longtext/longtext.py index 097c166a..4b461bd6 100644 --- a/pkg/pipeline/longtext/longtext.py +++ b/pkg/pipeline/longtext/longtext.py @@ -15,9 +15,9 @@ 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 """ @@ -35,22 +35,22 @@ 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 ) ) @@ -62,7 +62,7 @@ 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() @@ -76,7 +76,7 @@ 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'] diff --git a/pkg/pipeline/longtext/strategies/forward.py b/pkg/pipeline/longtext/strategies/forward.py index 8040efff..201622ce 100644 --- a/pkg/pipeline/longtext/strategies/forward.py +++ b/pkg/pipeline/longtext/strategies/forward.py @@ -15,17 +15,17 @@ Forward = platform_message.Forward class ForwardComponentStrategy(strategy_model.LongTextStrategy): async def process(self, message: str, query: pipeline_query.Query) -> list[platform_message.MessageComponent]: display = ForwardMessageDiaplay( - title='群聊的聊天记录', - brief='[聊天记录]', - source='聊天记录', - preview=['QQ用户: ' + message], - summary='查看1条转发消息', + title='Group chat history', + brief='[Chat history]', + source='Chat history', + preview=['User: ' + message], + 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]), ) ] diff --git a/pkg/pipeline/longtext/strategy.py b/pkg/pipeline/longtext/strategy.py index 018fb991..cb8ce7e1 100644 --- a/pkg/pipeline/longtext/strategy.py +++ b/pkg/pipeline/longtext/strategy.py @@ -15,13 +15,13 @@ 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]: @@ -37,7 +37,7 @@ 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 @@ -53,13 +53,13 @@ class LongTextStrategy(metaclass=abc.ABCMeta): async def process(self, message: str, query: pipeline_query.Query) -> list[platform_message.MessageComponent]: """处理长文本 - 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 - query (core_entities.Query): 此次请求的上下文对象 + message (str): Message + 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 [] diff --git a/pkg/pipeline/msgtrun/msgtrun.py b/pkg/pipeline/msgtrun/msgtrun.py index 3acd7e5c..00a9bfbf 100644 --- a/pkg/pipeline/msgtrun/msgtrun.py +++ b/pkg/pipeline/msgtrun/msgtrun.py @@ -11,9 +11,9 @@ 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 @@ -26,7 +26,7 @@ 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: pipeline_query.Query, stage_inst_name: str) -> entities.StageProcessResult: """处理""" diff --git a/pkg/pipeline/msgtrun/truncators/round.py b/pkg/pipeline/msgtrun/truncators/round.py index c6b1fba4..400706b6 100644 --- a/pkg/pipeline/msgtrun/truncators/round.py +++ b/pkg/pipeline/msgtrun/truncators/round.py @@ -6,7 +6,7 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @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: pipeline_query.Query) -> pipeline_query.Query: """截断""" @@ -16,7 +16,7 @@ class RoundTruncator(truncator.Truncator): 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) diff --git a/pkg/pipeline/pipelinemgr.py b/pkg/pipeline/pipelinemgr.py index e71ff0dc..3e126314 100644 --- a/pkg/pipeline/pipelinemgr.py +++ b/pkg/pipeline/pipelinemgr.py @@ -97,12 +97,20 @@ class RuntimePipeline: query.message_event, platform_events.GroupMessage ): result.user_notice.insert(0, platform_message.At(query.message_event.sender.id)) - - await query.adapter.reply_message( - message_source=query.message_event, - message=result.user_notice, - quote_origin=query.pipeline_config['output']['misc']['quote-origin'], - ) + if await query.adapter.is_stream_output_supported(): + await query.adapter.reply_message_chunk( + message_source=query.message_event, + bot_message=query.resp_messages[-1], + message=result.user_notice, + quote_origin=query.pipeline_config['output']['misc']['quote-origin'], + is_final=[msg.is_final for msg in query.resp_messages][0], + ) + else: + await query.adapter.reply_message( + message_source=query.message_event, + message=result.user_notice, + quote_origin=query.pipeline_config['output']['misc']['quote-origin'], + ) if result.debug_notice: self.ap.logger.debug(result.debug_notice) if result.console_notice: @@ -148,23 +156,27 @@ 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 @@ -196,7 +208,7 @@ 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: @@ -204,7 +216,7 @@ 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') del self.ap.query_pool.cached_queries[query.query_id] diff --git a/pkg/pipeline/preproc/preproc.py b/pkg/pipeline/preproc/preproc.py index 8cbcf8c7..bd150998 100644 --- a/pkg/pipeline/preproc/preproc.py +++ b/pkg/pipeline/preproc/preproc.py @@ -11,11 +11,11 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @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: pipeline_query.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' @@ -80,7 +80,7 @@ class PreProcessor(stage.PipelineStage): if me.type == 'image_url': msg.content.remove(me) - content_list = [] + content_list: list[provider_message.ContentElement] = [] plain_text = '' qoute_msg = query.pipeline_config['trigger'].get('misc', '').get('combine-quote-message') diff --git a/pkg/pipeline/process/handler.py b/pkg/pipeline/process/handler.py index 181d257d..b70a8e04 100644 --- a/pkg/pipeline/process/handler.py +++ b/pkg/pipeline/process/handler.py @@ -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: diff --git a/pkg/pipeline/process/handlers/chat.py b/pkg/pipeline/process/handlers/chat.py index 5bb5f07b..ed5380f6 100644 --- a/pkg/pipeline/process/handlers/chat.py +++ b/pkg/pipeline/process/handlers/chat.py @@ -1,5 +1,6 @@ from __future__ import annotations +import uuid import typing import traceback @@ -48,7 +49,6 @@ class ChatMessageHandler(handler.MessageHandler): if event_ctx.is_prevented_default(): if event_ctx.event.reply is not None: mc = platform_message.MessageChain(event_ctx.event.reply) - query.resp_messages.append(mc) yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) @@ -60,6 +60,10 @@ class ChatMessageHandler(handler.MessageHandler): query.user_message.content = event_ctx.event.alter text_length = 0 + try: + is_stream = await query.adapter.is_stream_output_supported() + except AttributeError: + is_stream = False try: for r in runner_module.preregistered_runners: @@ -68,21 +72,41 @@ class ChatMessageHandler(handler.MessageHandler): break else: raise ValueError(f'未找到请求运行器: {query.pipeline_config["ai"]["runner"]["runner"]}') + if is_stream: + resp_message_id = uuid.uuid4() + await query.adapter.create_message_card(str(resp_message_id), query.message_event) + async for result in runner.run(query): + result.resp_message_id = str(resp_message_id) + if query.resp_messages: + query.resp_messages.pop() + if query.resp_message_chain: + query.resp_message_chain.pop() - async for result in runner.run(query): - query.resp_messages.append(result) + query.resp_messages.append(result) + self.ap.logger.info(f'对话({query.query_id})流式响应: {self.cut_str(result.readable_str())}') - self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}') + if result.content is not None: + text_length += len(result.content) - if result.content is not None: - text_length += len(result.content) + yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) - yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) + else: + 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())}') + + if result.content is not None: + text_length += len(result.content) + + yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) 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)}') + traceback.print_exc() hide_exception_info = query.pipeline_config['output']['misc']['hide-exception'] diff --git a/pkg/pipeline/process/handlers/command.py b/pkg/pipeline/process/handlers/command.py index 7a2ec08f..db2187e3 100644 --- a/pkg/pipeline/process/handlers/command.py +++ b/pkg/pipeline/process/handlers/command.py @@ -16,7 +16,7 @@ class CommandHandler(handler.MessageHandler): self, query: pipeline_query.Query, ) -> typing.AsyncGenerator[entities.StageProcessResult, None]: - """处理""" + """Process""" command_text = str(query.message_chain).strip()[1:] @@ -71,7 +71,7 @@ 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: @@ -90,7 +90,7 @@ 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: diff --git a/pkg/pipeline/process/process.py b/pkg/pipeline/process/process.py index 704af5fd..c1f258d8 100644 --- a/pkg/pipeline/process/process.py +++ b/pkg/pipeline/process/process.py @@ -33,11 +33,11 @@ class Processor(stage.PipelineStage): query: pipeline_query.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(): diff --git a/pkg/pipeline/respback/respback.py b/pkg/pipeline/respback/respback.py index 4ffc9ca4..331a36aa 100644 --- a/pkg/pipeline/respback/respback.py +++ b/pkg/pipeline/respback/respback.py @@ -6,6 +6,7 @@ import asyncio import langbot_plugin.api.entities.builtin.platform.events as platform_events import langbot_plugin.api.entities.builtin.platform.message as platform_message +import langbot_plugin.api.entities.builtin.provider.message as provider_message from .. import stage, entities import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query @@ -36,10 +37,22 @@ class SendResponseBackStage(stage.PipelineStage): quote_origin = query.pipeline_config['output']['misc']['quote-origin'] - await query.adapter.reply_message( - message_source=query.message_event, - message=query.resp_message_chain[-1], - quote_origin=quote_origin, - ) + has_chunks = any(isinstance(msg, provider_message.MessageChunk) for msg in query.resp_messages) + # TODO 命令与流式的兼容性问题 + if await query.adapter.is_stream_output_supported() and has_chunks: + is_final = [msg.is_final for msg in query.resp_messages][0] + await query.adapter.reply_message_chunk( + message_source=query.message_event, + bot_message=query.resp_messages[-1], + message=query.resp_message_chain[-1], + quote_origin=quote_origin, + is_final=is_final, + ) + else: + await query.adapter.reply_message( + message_source=query.message_event, + message=query.resp_message_chain[-1], + quote_origin=quote_origin, + ) return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query) diff --git a/pkg/platform/botmgr.py b/pkg/platform/botmgr.py index 59341493..ee9bd040 100644 --- a/pkg/platform/botmgr.py +++ b/pkg/platform/botmgr.py @@ -115,8 +115,10 @@ class RuntimeBot: if isinstance(e, asyncio.CancelledError): self.task_context.set_current_action('Exited.') return + + traceback_str = traceback.format_exc() self.task_context.set_current_action('Exited with error.') - await self.logger.error(f'平台适配器运行出错:\n{e}\n{traceback.format_exc()}') + await self.logger.error(f'平台适配器运行出错:\n{e}\n{traceback_str}') self.task_wrapper = self.ap.task_mgr.create_task( exception_wrapper(), @@ -169,8 +171,8 @@ class PlatformManager: {}, webchat_logger, ap=self.ap, + is_stream=False, ) - webchat_adapter_inst.ap = self.ap self.webchat_proxy_bot = RuntimeBot( ap=self.ap, diff --git a/pkg/platform/logger.py b/pkg/platform/logger.py index cedaeb50..05fce394 100644 --- a/pkg/platform/logger.py +++ b/pkg/platform/logger.py @@ -120,7 +120,7 @@ class EventLogger(abstract_platform_event_logger.AbstractEventLogger): async def _truncate_logs(self): if len(self.logs) > MAX_LOG_COUNT: for i in range(DELETE_COUNT_PER_TIME): - for image_key in self.logs[i].images: + for image_key in self.logs[i].images: # type: ignore await self.ap.storage_mgr.storage_provider.delete(image_key) self.logs = self.logs[DELETE_COUNT_PER_TIME:] diff --git a/pkg/platform/sources/aiocqhttp.py b/pkg/platform/sources/aiocqhttp.py index ccfd3e53..ba673796 100644 --- a/pkg/platform/sources/aiocqhttp.py +++ b/pkg/platform/sources/aiocqhttp.py @@ -61,13 +61,13 @@ class AiocqhttpMessageConverter(abstract_platform_adapter.AbstractMessageConvert for node in msg.node_list: msg_list.extend((await AiocqhttpMessageConverter.yiri2target(node.message_chain))[0]) elif isinstance(msg, platform_message.File): - msg_list.append({"type":"file", "data":{'file': msg.url, "name": msg.name}}) + msg_list.append({'type': 'file', 'data': {'file': msg.url, 'name': msg.name}}) elif isinstance(msg, platform_message.Face): - if msg.face_type=='face': + if msg.face_type == 'face': msg_list.append(aiocqhttp.MessageSegment.face(msg.face_id)) - elif msg.face_type=='rps': + elif msg.face_type == 'rps': msg_list.append(aiocqhttp.MessageSegment.rps()) - elif msg.face_type=='dice': + elif msg.face_type == 'dice': msg_list.append(aiocqhttp.MessageSegment.dice()) else: @@ -76,44 +76,130 @@ class AiocqhttpMessageConverter(abstract_platform_adapter.AbstractMessageConvert 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): message = aiocqhttp.Message(message) def get_face_name(face_id): face_code_dict = { - "2": '好色', - "4": "得意", "5": "流泪", "8": "睡", "9": "大哭", "10": "尴尬", "12": "调皮", "14": "微笑", "16": "酷", - "21": "可爱", - "23": "傲慢", "24": "饥饿", "25": "困", "26": "惊恐", "27": "流汗", "28": "憨笑", "29": "悠闲", - "30": "奋斗", - "32": "疑问", "33": "嘘", "34": "晕", "38": "敲打", "39": "再见", "41": "发抖", "42": "爱情", - "43": "跳跳", - "49": "拥抱", "53": "蛋糕", "60": "咖啡", "63": "玫瑰", "66": "爱心", "74": "太阳", "75": "月亮", - "76": "赞", - "78": "握手", "79": "胜利", "85": "飞吻", "89": "西瓜", "96": "冷汗", "97": "擦汗", "98": "抠鼻", - "99": "鼓掌", - "100": "糗大了", "101": "坏笑", "102": "左哼哼", "103": "右哼哼", "104": "哈欠", "106": "委屈", - "109": "左亲亲", - "111": "可怜", "116": "示爱", "118": "抱拳", "120": "拳头", "122": "爱你", "123": "NO", "124": "OK", - "125": "转圈", - "129": "挥手", "144": "喝彩", "147": "棒棒糖", "171": "茶", "173": "泪奔", "174": "无奈", "175": "卖萌", - "176": "小纠结", "179": "doge", "180": "惊喜", "181": "骚扰", "182": "笑哭", "183": "我最美", - "201": "点赞", - "203": "托脸", "212": "托腮", "214": "啵啵", "219": "蹭一蹭", "222": "抱抱", "227": "拍手", - "232": "佛系", - "240": "喷脸", "243": "甩头", "246": "加油抱抱", "262": "脑阔疼", "264": "捂脸", "265": "辣眼睛", - "266": "哦哟", - "267": "头秃", "268": "问号脸", "269": "暗中观察", "270": "emm", "271": "吃瓜", "272": "呵呵哒", - "273": "我酸了", - "277": "汪汪", "278": "汗", "281": "无眼笑", "282": "敬礼", "284": "面无表情", "285": "摸鱼", - "287": "哦", - "289": "睁眼", "290": "敲开心", "293": "摸锦鲤", "294": "期待", "297": "拜谢", "298": "元宝", - "299": "牛啊", - "305": "右亲亲", "306": "牛气冲天", "307": "喵喵", "314": "仔细分析", "315": "加油", "318": "崇拜", - "319": "比心", - "320": "庆祝", "322": "拒绝", "324": "吃糖", "326": "生气" + '2': '好色', + '4': '得意', + '5': '流泪', + '8': '睡', + '9': '大哭', + '10': '尴尬', + '12': '调皮', + '14': '微笑', + '16': '酷', + '21': '可爱', + '23': '傲慢', + '24': '饥饿', + '25': '困', + '26': '惊恐', + '27': '流汗', + '28': '憨笑', + '29': '悠闲', + '30': '奋斗', + '32': '疑问', + '33': '嘘', + '34': '晕', + '38': '敲打', + '39': '再见', + '41': '发抖', + '42': '爱情', + '43': '跳跳', + '49': '拥抱', + '53': '蛋糕', + '60': '咖啡', + '63': '玫瑰', + '66': '爱心', + '74': '太阳', + '75': '月亮', + '76': '赞', + '78': '握手', + '79': '胜利', + '85': '飞吻', + '89': '西瓜', + '96': '冷汗', + '97': '擦汗', + '98': '抠鼻', + '99': '鼓掌', + '100': '糗大了', + '101': '坏笑', + '102': '左哼哼', + '103': '右哼哼', + '104': '哈欠', + '106': '委屈', + '109': '左亲亲', + '111': '可怜', + '116': '示爱', + '118': '抱拳', + '120': '拳头', + '122': '爱你', + '123': 'NO', + '124': 'OK', + '125': '转圈', + '129': '挥手', + '144': '喝彩', + '147': '棒棒糖', + '171': '茶', + '173': '泪奔', + '174': '无奈', + '175': '卖萌', + '176': '小纠结', + '179': 'doge', + '180': '惊喜', + '181': '骚扰', + '182': '笑哭', + '183': '我最美', + '201': '点赞', + '203': '托脸', + '212': '托腮', + '214': '啵啵', + '219': '蹭一蹭', + '222': '抱抱', + '227': '拍手', + '232': '佛系', + '240': '喷脸', + '243': '甩头', + '246': '加油抱抱', + '262': '脑阔疼', + '264': '捂脸', + '265': '辣眼睛', + '266': '哦哟', + '267': '头秃', + '268': '问号脸', + '269': '暗中观察', + '270': 'emm', + '271': '吃瓜', + '272': '呵呵哒', + '273': '我酸了', + '277': '汪汪', + '278': '汗', + '281': '无眼笑', + '282': '敬礼', + '284': '面无表情', + '285': '摸鱼', + '287': '哦', + '289': '睁眼', + '290': '敲开心', + '293': '摸锦鲤', + '294': '期待', + '297': '拜谢', + '298': '元宝', + '299': '牛啊', + '305': '右亲亲', + '306': '牛气冲天', + '307': '喵喵', + '314': '仔细分析', + '315': '加油', + '318': '崇拜', + '319': '比心', + '320': '庆祝', + '322': '拒绝', + '324': '吃糖', + '326': '生气', } - return face_code_dict.get(face_id,'') + return face_code_dict.get(face_id, '') async def process_message_data(msg_data, reply_list): if msg_data['type'] == 'image': @@ -156,10 +242,10 @@ class AiocqhttpMessageConverter(abstract_platform_adapter.AbstractMessageConvert elif msg.type == 'text': yiri_msg_list.append(platform_message.Plain(text=msg.data['text'])) elif msg.type == 'image': - emoji_id = msg.data.get("emoji_package_id", None) + emoji_id = msg.data.get('emoji_package_id', None) if emoji_id: face_id = emoji_id - face_name = msg.data.get("summary", '') + face_name = msg.data.get('summary', '') image_msg = platform_message.Face(face_id=face_id, face_name=face_name) else: image_base64, image_format = await image.qq_image_url_to_base64(msg.data['url']) @@ -185,27 +271,28 @@ class AiocqhttpMessageConverter(abstract_platform_adapter.AbstractMessageConvert yiri_msg_list.append(reply_msg) elif msg.type == 'file': + pass # file_name = msg.data['file'] - file_id = msg.data['file_id'] - file_data = await bot.get_file(file_id=file_id) - file_name = file_data.get('file_name') - file_path = file_data.get('file') - _ = file_path - file_url = file_data.get('file_url') - 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)) + # file_id = msg.data['file_id'] + # file_data = await bot.get_file(file_id=file_id) + # file_name = file_data.get('file_name') + # file_path = file_data.get('file') + # _ = file_path + # file_url = file_data.get('file_url') + # 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)) elif msg.type == 'face': face_id = msg.data['id'] face_name = msg.data['raw']['faceText'] if not face_name: face_name = get_face_name(face_id) - yiri_msg_list.append(platform_message.Face(face_id=int(face_id),face_name=face_name.replace('/',''))) + yiri_msg_list.append(platform_message.Face(face_id=int(face_id), face_name=face_name.replace('/', ''))) elif msg.type == 'rps': face_id = msg.data['result'] - yiri_msg_list.append(platform_message.Face(face_type="rps",face_id=int(face_id),face_name='猜拳')) + yiri_msg_list.append(platform_message.Face(face_type='rps', face_id=int(face_id), face_name='猜拳')) elif msg.type == 'dice': face_id = msg.data['result'] - yiri_msg_list.append(platform_message.Face(face_type='dice',face_id=int(face_id),face_name='骰子')) + yiri_msg_list.append(platform_message.Face(face_type='dice', face_id=int(face_id), face_name='骰子')) chain = platform_message.MessageChain(yiri_msg_list) @@ -221,7 +308,6 @@ class AiocqhttpEventConverter(abstract_platform_adapter.AbstractEventConverter): async def target2yiri(event: aiocqhttp.Event, bot=None): yiri_chain = await AiocqhttpMessageConverter.target2yiri(event.message, event.message_id, bot) - if event.message_type == 'group': permission = 'MEMBER' diff --git a/pkg/platform/sources/dingtalk.py b/pkg/platform/sources/dingtalk.py index 2a76c219..892808cd 100644 --- a/pkg/platform/sources/dingtalk.py +++ b/pkg/platform/sources/dingtalk.py @@ -96,10 +96,16 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): message_converter: DingTalkMessageConverter = DingTalkMessageConverter() event_converter: DingTalkEventConverter = DingTalkEventConverter() config: dict + card_instance_id_dict: ( + dict # 回复卡片消息字典，key为消息id，value为回复卡片实例id，用于在流式消息时判断是否发送到指定卡片 + ) + seq: int # 消息顺序，直接以seq作为标识 def __init__(self, config: dict, logger: EventLogger): self.config = config self.logger = logger + self.card_instance_id_dict = {} + # self.seq = 1 required_keys = [ 'client_id', 'client_secret', @@ -112,6 +118,15 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): 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, @@ -126,6 +141,33 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): content, at = await DingTalkMessageConverter.yiri2target(message) await self.bot.send_message(content, incoming_message, at) + async def reply_message_chunk( + self, + message_source: platform_events.MessageEvent, + bot_message, + message: platform_message.MessageChain, + quote_origin: bool = False, + is_final: bool = False, + ): + # event = await DingTalkEventConverter.yiri2target( + # message_source, + # ) + # incoming_message = event.incoming_message + + # msg_id = incoming_message.message_id + message_id = bot_message.resp_message_id + msg_seq = bot_message.msg_sequence + + if (msg_seq - 1) % 8 == 0 or is_final: + content, at = await DingTalkMessageConverter.yiri2target(message) + + card_instance, card_instance_id = self.card_instance_id_dict[message_id] + # print(card_instance_id) + await self.bot.send_card_message(card_instance, card_instance_id, content, is_final) + if is_final and bot_message.tool_calls is None: + # self.seq = 1 # 消息回复结束之后重置seq + self.card_instance_id_dict.pop(message_id) # 消息回复结束之后删除卡片实例id + async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain): content = await DingTalkMessageConverter.yiri2target(message) if target_type == 'person': @@ -133,6 +175,20 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): if target_type == 'group': await self.bot.send_proactive_message_to_group(target_id, content) + async def is_stream_output_supported(self) -> bool: + is_stream = False + if self.config.get('enable-stream-reply', None): + is_stream = True + return is_stream + + async def create_message_card(self, message_id, event): + card_template_id = self.config['card_template_id'] + incoming_message = event.source_platform_object.incoming_message + # message_id = incoming_message.message_id + card_instance, card_instance_id = await self.bot.create_and_card(card_template_id, incoming_message) + self.card_instance_id_dict[message_id] = (card_instance, card_instance_id) + return True + def register_listener( self, event_type: typing.Type[platform_events.Event], @@ -155,15 +211,6 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): 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: diff --git a/pkg/platform/sources/dingtalk.yaml b/pkg/platform/sources/dingtalk.yaml index fac2d6ff..70855c2b 100644 --- a/pkg/platform/sources/dingtalk.yaml +++ b/pkg/platform/sources/dingtalk.yaml @@ -46,6 +46,23 @@ spec: type: boolean required: false default: true + - name: enable-stream-reply + label: + en_US: Enable Stream Reply Mode + zh_Hans: 启用钉钉卡片流式回复模式 + description: + en_US: If enabled, the bot will use the stream of lark reply mode + zh_Hans: 如果启用，将使用钉钉卡片流式方式来回复内容 + type: boolean + required: true + default: false + - name: card_template_id + label: + en_US: card template id + zh_Hans: 卡片模板ID + type: string + required: true + default: "填写你的卡片template_id" execution: python: path: ./dingtalk.py diff --git a/pkg/platform/sources/discord.py b/pkg/platform/sources/discord.py index 5d24c77b..75ad287e 100644 --- a/pkg/platform/sources/discord.py +++ b/pkg/platform/sources/discord.py @@ -8,6 +8,8 @@ import base64 import uuid import os import datetime +import asyncio +from enum import Enum import aiohttp import pydantic @@ -17,6 +19,568 @@ import langbot_plugin.api.entities.builtin.platform.message as platform_message import langbot_plugin.api.entities.builtin.platform.events as platform_events import langbot_plugin.api.entities.builtin.platform.entities as platform_entities import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger +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(abstract_platform_adapter.AbstractMessageConverter): @@ -35,28 +599,89 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter for ele in message_chain: if isinstance(ele, platform_message.Image): image_bytes = None + filename = f'{uuid.uuid4()}.png' # 默认文件名 if ele.base64: - image_bytes = base64.b64decode(ele.base64) + # 处理base64编码的图片 + if ele.base64.startswith('data:'): + # 从data URL中提取文件类型 + data_header = ele.base64.split(',')[0] + if 'jpeg' in data_header or 'jpg' in data_header: + filename = f'{uuid.uuid4()}.jpg' + elif 'gif' in data_header: + filename = f'{uuid.uuid4()}.gif' + elif 'webp' in data_header: + filename = f'{uuid.uuid4()}.webp' + # 去掉data:image/xxx;base64,前缀 + base64_data = ele.base64.split(',')[1] + else: + base64_data = ele.base64 + image_bytes = base64.b64decode(base64_data) elif ele.url: + # 从URL下载图片 async with aiohttp.ClientSession() as session: async with session.get(ele.url) as response: image_bytes = await response.read() + # 从URL或Content-Type推断文件类型 + content_type = response.headers.get('Content-Type', '') + if 'jpeg' in content_type or 'jpg' in content_type: + filename = f'{uuid.uuid4()}.jpg' + elif 'gif' in content_type: + filename = f'{uuid.uuid4()}.gif' + elif 'webp' in content_type: + filename = f'{uuid.uuid4()}.webp' + elif ele.url.lower().endswith(('.jpg', '.jpeg')): + filename = f'{uuid.uuid4()}.jpg' + elif ele.url.lower().endswith('.gif'): + filename = f'{uuid.uuid4()}.gif' + elif ele.url.lower().endswith('.webp'): + filename = f'{uuid.uuid4()}.webp' elif ele.path: - with open(ele.path, 'rb') as f: - image_bytes = f.read() + # 从文件路径读取图片 + # 确保路径没有空字节 + clean_path = ele.path.replace('\x00', '') + clean_path = os.path.abspath(clean_path) - image_files.append(discord.File(fp=image_bytes, filename=f'{uuid.uuid4()}.png')) + if not os.path.exists(clean_path): + continue # 跳过不存在的文件 + + try: + with open(clean_path, 'rb') as f: + image_bytes = f.read() + # 从文件路径获取文件名，保持原始扩展名 + original_filename = os.path.basename(clean_path) + if original_filename and '.' in original_filename: + # 保持原始文件名的扩展名 + ext = original_filename.split('.')[-1].lower() + filename = f'{uuid.uuid4()}.{ext}' + else: + # 如果没有扩展名，尝试从文件内容检测 + if image_bytes.startswith(b'\xff\xd8\xff'): + filename = f'{uuid.uuid4()}.jpg' + elif image_bytes.startswith(b'GIF'): + filename = f'{uuid.uuid4()}.gif' + elif image_bytes.startswith(b'RIFF') and b'WEBP' in image_bytes[:20]: + filename = f'{uuid.uuid4()}.webp' + # 默认保持PNG + except Exception as e: + print(f'Error reading image file {clean_path}: {e}') + continue # 跳过读取失败的文件 + + if image_bytes: + # 使用BytesIO创建文件对象，避免路径问题 + import io + + image_files.append(discord.File(fp=io.BytesIO(image_bytes), filename=filename)) elif isinstance(ele, platform_message.Plain): text_string += ele.text elif isinstance(ele, platform_message.Forward): for node in ele.node_list: ( - text_string, - image_files, + node_text, + node_images, ) = await DiscordMessageConverter.yiri2target(node.message_chain) - text_string += text_string - image_files.extend(image_files) + text_string += node_text + image_files.extend(node_images) return text_string, image_files @@ -165,11 +790,16 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None], ] = {} - def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger): + voice_manager: VoiceConnectionManager | None = pydantic.Field(exclude=True, default=None) + + def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs): bot_account_id = config['client_id'] listeners = {} + # 初始化语音连接管理器 + # self.voice_manager: VoiceConnectionManager = None + adapter_self = self class MyClient(discord.Client): @@ -196,10 +826,194 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): bot_account_id=bot_account_id, listeners=listeners, bot=bot, + voice_manager=None, + **kwargs, ) + # 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): - pass + msg_to_send, image_files = await self.message_converter.yiri2target(message) + + try: + # 获取频道对象 + channel = self.bot.get_channel(int(target_id)) + if channel is None: + # 如果本地缓存中没有，尝试从API获取 + channel = await self.bot.fetch_channel(int(target_id)) + + args = { + 'content': msg_to_send, + } + + if len(image_files) > 0: + args['files'] = image_files + + await channel.send(**args) + + except Exception as e: + await self.logger.error(f'Discord send_message failed: {e}') + raise e async def reply_message( self, @@ -247,9 +1061,31 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): 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 diff --git a/pkg/platform/sources/lark.py b/pkg/platform/sources/lark.py index 7c8ae2eb..6d04bd94 100644 --- a/pkg/platform/sources/lark.py +++ b/pkg/platform/sources/lark.py @@ -18,6 +18,7 @@ import lark_oapi.ws.exception import quart from lark_oapi.api.im.v1 import * import pydantic +from lark_oapi.api.cardkit.v1 import * import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter import langbot_plugin.api.entities.builtin.platform.message as platform_message @@ -320,10 +321,17 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter): ) +CARD_ID_CACHE_SIZE = 500 +CARD_ID_CACHE_MAX_LIFETIME = 20 * 60 # 20分钟 + + class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): bot: lark_oapi.ws.Client = pydantic.Field(exclude=True) api_client: lark_oapi.Client = pydantic.Field(exclude=True) + bot_account_id: str # 用于在流水线中识别at是否是本bot，直接以bot_name作为标识 + lark_tenant_key: str = pydantic.Field(exclude=True, default='') # 飞书企业key + message_converter: LarkMessageConverter = LarkMessageConverter() event_converter: LarkEventConverter = LarkEventConverter() @@ -334,7 +342,11 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): quart_app: quart.Quart = pydantic.Field(exclude=True) - def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger): + card_id_dict: dict[str, str] # 消息id到卡片id的映射，便于创建卡片后的发送消息到指定卡片 + + seq: int # 用于在发送卡片消息中识别消息顺序，直接以seq作为标识 + + def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs): quart_app = quart.Quart(__name__) @quart_app.route('/lark/callback', methods=['POST']) @@ -343,7 +355,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): data = await quart.request.json if 'encrypt' in data: - cipher = AESCipher(self.config['encrypt-key']) + cipher = AESCipher(config['encrypt-key']) data = cipher.decrypt_string(data['encrypt']) data = json.loads(data) @@ -398,16 +410,256 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): super().__init__( config=config, logger=logger, + lark_tenant_key=config.get('lark_tenant_key', ''), + card_id_dict={}, + seq=1, listeners={}, quart_app=quart_app, bot=bot, api_client=api_client, bot_account_id=bot_account_id, + **kwargs, ) async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain): pass + async def is_stream_output_supported(self) -> bool: + is_stream = False + if self.config.get('enable-stream-reply', None): + is_stream = True + return is_stream + + async def create_card_id(self, message_id): + try: + # self.logger.debug('飞书支持stream输出,创建卡片......') + + card_data = { + 'schema': '2.0', + 'config': { + 'update_multi': True, + 'streaming_mode': True, + 'streaming_config': { + 'print_step': {'default': 1}, + 'print_frequency_ms': {'default': 70}, + 'print_strategy': 'fast', + }, + }, + 'body': { + 'direction': 'vertical', + 'padding': '12px 12px 12px 12px', + 'elements': [ + { + 'tag': 'div', + 'text': { + 'tag': 'plain_text', + 'content': 'LangBot', + 'text_size': 'normal', + 'text_align': 'left', + 'text_color': 'default', + }, + 'icon': { + 'tag': 'custom_icon', + 'img_key': 'img_v3_02p3_05c65d5d-9bad-440a-a2fb-c89571bfd5bg', + }, + }, + { + 'tag': 'markdown', + 'content': '', + 'text_align': 'left', + 'text_size': 'normal', + 'margin': '0px 0px 0px 0px', + 'element_id': 'streaming_txt', + }, + { + 'tag': 'markdown', + 'content': '', + 'text_align': 'left', + 'text_size': 'normal', + 'margin': '0px 0px 0px 0px', + }, + { + 'tag': 'column_set', + 'horizontal_spacing': '8px', + 'horizontal_align': 'left', + 'columns': [ + { + 'tag': 'column', + 'width': 'weighted', + 'elements': [ + { + 'tag': 'markdown', + 'content': '', + 'text_align': 'left', + 'text_size': 'normal', + 'margin': '0px 0px 0px 0px', + }, + { + 'tag': 'markdown', + 'content': '', + 'text_align': 'left', + 'text_size': 'normal', + 'margin': '0px 0px 0px 0px', + }, + { + 'tag': 'markdown', + 'content': '', + 'text_align': 'left', + 'text_size': 'normal', + 'margin': '0px 0px 0px 0px', + }, + ], + 'padding': '0px 0px 0px 0px', + 'direction': 'vertical', + 'horizontal_spacing': '8px', + 'vertical_spacing': '2px', + 'horizontal_align': 'left', + 'vertical_align': 'top', + 'margin': '0px 0px 0px 0px', + 'weight': 1, + } + ], + 'margin': '0px 0px 0px 0px', + }, + {'tag': 'hr', 'margin': '0px 0px 0px 0px'}, + { + 'tag': 'column_set', + 'horizontal_spacing': '12px', + 'horizontal_align': 'right', + 'columns': [ + { + 'tag': 'column', + 'width': 'weighted', + 'elements': [ + { + 'tag': 'markdown', + 'content': '以上内容由 AI 生成，仅供参考。更多详细、准确信息可点击引用链接查看', + 'text_align': 'left', + 'text_size': 'notation', + 'margin': '4px 0px 0px 0px', + 'icon': { + 'tag': 'standard_icon', + 'token': 'robot_outlined', + 'color': 'grey', + }, + } + ], + 'padding': '0px 0px 0px 0px', + 'direction': 'vertical', + 'horizontal_spacing': '8px', + 'vertical_spacing': '8px', + 'horizontal_align': 'left', + 'vertical_align': 'top', + 'margin': '0px 0px 0px 0px', + 'weight': 1, + }, + { + 'tag': 'column', + 'width': '20px', + 'elements': [ + { + 'tag': 'button', + 'text': {'tag': 'plain_text', 'content': ''}, + 'type': 'text', + 'width': 'fill', + 'size': 'medium', + 'icon': {'tag': 'standard_icon', 'token': 'thumbsup_outlined'}, + 'hover_tips': {'tag': 'plain_text', 'content': '有帮助'}, + 'margin': '0px 0px 0px 0px', + } + ], + 'padding': '0px 0px 0px 0px', + 'direction': 'vertical', + 'horizontal_spacing': '8px', + 'vertical_spacing': '8px', + 'horizontal_align': 'left', + 'vertical_align': 'top', + 'margin': '0px 0px 0px 0px', + }, + { + 'tag': 'column', + 'width': '30px', + 'elements': [ + { + 'tag': 'button', + 'text': {'tag': 'plain_text', 'content': ''}, + 'type': 'text', + 'width': 'default', + 'size': 'medium', + 'icon': {'tag': 'standard_icon', 'token': 'thumbdown_outlined'}, + 'hover_tips': {'tag': 'plain_text', 'content': '无帮助'}, + 'margin': '0px 0px 0px 0px', + } + ], + 'padding': '0px 0px 0px 0px', + 'vertical_spacing': '8px', + 'horizontal_align': 'left', + 'vertical_align': 'top', + 'margin': '0px 0px 0px 0px', + }, + ], + 'margin': '0px 0px 4px 0px', + }, + ], + }, + } + # delay / fast 创建卡片模板，delay 延迟打印，fast 实时打印，可以自定义更好看的消息模板 + + request: CreateCardRequest = ( + CreateCardRequest.builder() + .request_body(CreateCardRequestBody.builder().type('card_json').data(json.dumps(card_data)).build()) + .build() + ) + + # 发起请求 + response: CreateCardResponse = self.api_client.cardkit.v1.card.create(request) + + # 处理失败返回 + if not response.success(): + raise Exception( + f'client.cardkit.v1.card.create failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}' + ) + + self.ap.logger.debug(f'飞书卡片创建成功,卡片ID: {response.data.card_id}') + self.card_id_dict[message_id] = response.data.card_id + + card_id = response.data.card_id + return card_id + + except Exception as e: + self.ap.logger.error(f'飞书卡片创建失败,错误信息: {e}') + + async def create_message_card(self, message_id, event) -> str: + """ + 创建卡片消息。 + 使用卡片消息是因为普通消息更新次数有限制，而大模型流式返回结果可能很多而超过限制，而飞书卡片没有这个限制（api免费次数有限） + """ + # message_id = event.message_chain.message_id + + card_id = await self.create_card_id(message_id) + content = { + 'type': 'card', + 'data': {'card_id': card_id, 'template_variable': {'content': 'Thinking...'}}, + } # 当收到消息时发送消息模板，可添加模板变量，详情查看飞书中接口文档 + request: ReplyMessageRequest = ( + ReplyMessageRequest.builder() + .message_id(event.message_chain.message_id) + .request_body( + ReplyMessageRequestBody.builder().content(json.dumps(content)).msg_type('interactive').build() + ) + .build() + ) + + # 发起请求 + response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request) + + # 处理失败返回 + if not response.success(): + raise Exception( + f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}' + ) + return True + async def reply_message( self, message_source: platform_events.MessageEvent, @@ -446,6 +698,62 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}' ) + async def reply_message_chunk( + self, + message_source: platform_events.MessageEvent, + bot_message, + message: platform_message.MessageChain, + quote_origin: bool = False, + is_final: bool = False, + ): + """ + 回复消息变成更新卡片消息 + """ + # self.seq += 1 + message_id = bot_message.resp_message_id + msg_seq = bot_message.msg_sequence + if msg_seq % 8 == 0 or is_final: + lark_message = await self.message_converter.yiri2target(message, self.api_client) + + text_message = '' + for ele in lark_message[0]: + if ele['tag'] == 'text': + text_message += ele['text'] + elif ele['tag'] == 'md': + text_message += ele['text'] + + # content = { + # 'type': 'card_json', + # 'data': {'card_id': self.card_id_dict[message_id], 'elements': {'content': text_message}}, + # } + + request: ContentCardElementRequest = ( + ContentCardElementRequest.builder() + .card_id(self.card_id_dict[message_id]) + .element_id('streaming_txt') + .request_body( + ContentCardElementRequestBody.builder() + # .uuid("a0d69e20-1dd1-458b-k525-dfeca4015204") + .content(text_message) + .sequence(msg_seq) + .build() + ) + .build() + ) + + if is_final and bot_message.tool_calls is None: + # self.seq = 1 # 消息回复结束之后重置seq + self.card_id_dict.pop(message_id) # 清理已经使用过的卡片 + # 发起请求 + response: ContentCardElementResponse = self.api_client.cardkit.v1.card_element.content(request) + + # 处理失败返回 + if not response.success(): + raise Exception( + f'client.im.v1.message.patch failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}' + ) + return + async def is_muted(self, group_id: int) -> bool: return False @@ -495,4 +803,9 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): ) async def kill(self) -> bool: + # 需要断开连接，不然旧的连接会继续运行，导致飞书消息来时会随机选择一个连接 + # 断开时lark.ws.Client的_receive_message_loop会打印error日志: receive message loop exit。然后进行重连， + # 所以要设置_auto_reconnect=False,让其不重连。 + self.bot._auto_reconnect = False + await self.bot._disconnect() return False diff --git a/pkg/platform/sources/lark.yaml b/pkg/platform/sources/lark.yaml index f51bab76..94414b2e 100644 --- a/pkg/platform/sources/lark.yaml +++ b/pkg/platform/sources/lark.yaml @@ -65,6 +65,16 @@ spec: type: string required: true default: "" + - name: enable-stream-reply + label: + en_US: Enable Stream Reply Mode + zh_Hans: 启用飞书流式回复模式 + description: + en_US: If enabled, the bot will use the stream of lark reply mode + zh_Hans: 如果启用，将使用飞书流式方式来回复内容 + type: boolean + required: true + default: false execution: python: path: ./lark.py diff --git a/pkg/platform/sources/telegram.py b/pkg/platform/sources/telegram.py index 69e781ef..458d8094 100644 --- a/pkg/platform/sources/telegram.py +++ b/pkg/platform/sources/telegram.py @@ -1,5 +1,6 @@ from __future__ import annotations + import telegram import telegram.ext from telegram import Update @@ -136,6 +137,12 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): message_converter: TelegramMessageConverter = TelegramMessageConverter() event_converter: TelegramEventConverter = TelegramEventConverter() + config: dict + + msg_stream_id: dict # 流式消息id字典，key为流式消息id，value为首次消息源id，用于在流式消息时判断编辑那条消息 + + seq: int # 消息中识别消息顺序，直接以seq作为标识 + listeners: typing.Dict[ typing.Type[platform_events.Event], typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None], @@ -149,6 +156,7 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): try: lb_event = await self.event_converter.target2yiri(update, self.bot, self.bot_account_id) await self.listeners[type(lb_event)](lb_event, self) + await self.is_stream_output_supported() except Exception: await self.logger.error(f'Error in telegram callback: {traceback.format_exc()}') @@ -158,6 +166,8 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): super().__init__( config=config, logger=logger, + msg_stream_id={}, + seq=1, bot=bot, application=application, bot_account_id='', @@ -195,6 +205,70 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): await self.bot.send_message(**args) + async def reply_message_chunk( + self, + message_source: platform_events.MessageEvent, + bot_message, + message: platform_message.MessageChain, + quote_origin: bool = False, + is_final: bool = False, + ): + msg_seq = bot_message.msg_sequence + if (msg_seq - 1) % 8 == 0 or is_final: + assert isinstance(message_source.source_platform_object, Update) + components = await TelegramMessageConverter.yiri2target(message, self.bot) + args = {} + message_id = message_source.source_platform_object.message.id + if quote_origin: + args['reply_to_message_id'] = message_source.source_platform_object.message.id + + component = components[0] + if message_id not in self.msg_stream_id: # 当消息回复第一次时，发送新消息 + # time.sleep(0.6) + if component['type'] == 'text': + if self.config['markdown_card'] is True: + content = telegramify_markdown.markdownify( + content=component['text'], + ) + else: + content = component['text'] + args = { + 'chat_id': message_source.source_platform_object.effective_chat.id, + 'text': content, + } + if self.config['markdown_card'] is True: + args['parse_mode'] = 'MarkdownV2' + + send_msg = await self.bot.send_message(**args) + send_msg_id = send_msg.message_id + self.msg_stream_id[message_id] = send_msg_id + else: # 存在消息的时候直接编辑消息1 + if component['type'] == 'text': + if self.config['markdown_card'] is True: + content = telegramify_markdown.markdownify( + content=component['text'], + ) + else: + content = component['text'] + args = { + 'message_id': self.msg_stream_id[message_id], + 'chat_id': message_source.source_platform_object.effective_chat.id, + 'text': content, + } + if self.config['markdown_card'] is True: + args['parse_mode'] = 'MarkdownV2' + + await self.bot.edit_message_text(**args) + if is_final and bot_message.tool_calls is None: + # self.seq = 1 # 消息回复结束之后重置seq + self.msg_stream_id.pop(message_id) # 消息回复结束之后删除流式消息id + + async def is_stream_output_supported(self) -> bool: + is_stream = False + if self.config.get('enable-stream-reply', None): + is_stream = True + return is_stream + async def is_muted(self, group_id: int) -> bool: return False @@ -221,8 +295,12 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): self.bot_account_id = (await self.bot.get_me()).username await self.application.updater.start_polling(allowed_updates=Update.ALL_TYPES) await self.application.start() + await self.logger.info('Telegram adapter running') async def kill(self) -> bool: if self.application.running: await self.application.stop() + if self.application.updater: + await self.application.updater.stop() + await self.logger.info('Telegram adapter stopped') return True diff --git a/pkg/platform/sources/telegram.yaml b/pkg/platform/sources/telegram.yaml index 43b9284b..d29c359e 100644 --- a/pkg/platform/sources/telegram.yaml +++ b/pkg/platform/sources/telegram.yaml @@ -25,6 +25,16 @@ spec: type: boolean required: false default: true + - name: enable-stream-reply + label: + en_US: Enable Stream Reply Mode + zh_Hans: 启用电报流式回复模式 + description: + en_US: If enabled, the bot will use the stream of telegram reply mode + zh_Hans: 如果启用，将使用电报流式方式来回复内容 + type: boolean + required: true + default: false execution: python: path: ./telegram.py diff --git a/pkg/platform/sources/webchat.py b/pkg/platform/sources/webchat.py index 0b5fc0ff..6c148614 100644 --- a/pkg/platform/sources/webchat.py +++ b/pkg/platform/sources/webchat.py @@ -9,8 +9,8 @@ import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platf import langbot_plugin.api.entities.builtin.platform.message as platform_message import langbot_plugin.api.entities.builtin.platform.events as platform_events import langbot_plugin.api.entities.builtin.platform.entities as platform_entities -from ...core import app import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger +from ...core import app logger = logging.getLogger(__name__) @@ -21,17 +21,20 @@ class WebChatMessage(pydantic.BaseModel): content: str message_chain: list[dict] timestamp: str + is_final: bool = False class WebChatSession: id: str message_lists: dict[str, list[WebChatMessage]] = {} resp_waiters: dict[int, asyncio.Future[WebChatMessage]] + resp_queues: dict[int, asyncio.Queue[WebChatMessage]] def __init__(self, id: str): self.id = id self.message_lists = {} self.resp_waiters = {} + self.resp_queues = {} def get_message_list(self, pipeline_uuid: str) -> list[WebChatMessage]: if pipeline_uuid not in self.message_lists: @@ -46,20 +49,21 @@ class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): webchat_person_session: WebChatSession = pydantic.Field(exclude=True, default_factory=WebChatSession) webchat_group_session: WebChatSession = pydantic.Field(exclude=True, default_factory=WebChatSession) - ap: app.Application = pydantic.Field(exclude=True) # set by bot manager - listeners: dict[ typing.Type[platform_events.Event], typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None], ] = pydantic.Field(default_factory=dict, exclude=True) + is_stream: bool = pydantic.Field(exclude=True) debug_messages: dict[str, list[dict]] = pydantic.Field(default_factory=dict, exclude=True) - def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, ap: app.Application): + ap: app.Application = pydantic.Field(exclude=True) + + def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs): super().__init__( config=config, logger=logger, - ap=ap, + **kwargs, ) self.webchat_person_session = WebChatSession(id='webchatperson') @@ -112,12 +116,53 @@ class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): # notify waiter if isinstance(message_source, platform_events.FriendMessage): - self.webchat_person_session.resp_waiters[message_source.message_chain.message_id].set_result(message_data) + await self.webchat_person_session.resp_queues[message_source.message_chain.message_id].put(message_data) elif isinstance(message_source, platform_events.GroupMessage): - self.webchat_group_session.resp_waiters[message_source.message_chain.message_id].set_result(message_data) + await self.webchat_group_session.resp_queues[message_source.message_chain.message_id].put(message_data) return message_data.model_dump() + async def reply_message_chunk( + self, + message_source: platform_events.MessageEvent, + bot_message, + message: platform_message.MessageChain, + quote_origin: bool = False, + is_final: bool = False, + ) -> dict: + """回复消息""" + message_data = WebChatMessage( + id=-1, + role='assistant', + content=str(message), + message_chain=[component.__dict__ for component in message], + timestamp=datetime.now().isoformat(), + ) + + # notify waiter + session = ( + self.webchat_group_session + if isinstance(message_source, platform_events.GroupMessage) + else self.webchat_person_session + ) + if message_source.message_chain.message_id not in session.resp_waiters: + # session.resp_waiters[message_source.message_chain.message_id] = asyncio.Queue() + queue = session.resp_queues[message_source.message_chain.message_id] + + # if isinstance(message_source, platform_events.FriendMessage): + # queue = self.webchat_person_session.resp_queues[message_source.message_chain.message_id] + # elif isinstance(message_source, platform_events.GroupMessage): + # queue = self.webchat_group_session.resp_queues[message_source.message_chain.message_id] + if is_final and bot_message.tool_calls is None: + message_data.is_final = True + # print(message_data) + await queue.put(message_data) + + return message_data.model_dump() + + async def is_stream_output_supported(self) -> bool: + return self.is_stream + def register_listener( self, event_type: typing.Type[platform_events.Event], @@ -157,8 +202,13 @@ class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): await self.logger.info('WebChat调试适配器正在停止') async def send_webchat_message( - self, pipeline_uuid: str, session_type: str, message_chain_obj: typing.List[dict] + self, + pipeline_uuid: str, + session_type: str, + message_chain_obj: typing.List[dict], + is_stream: bool = False, ) -> dict: + self.is_stream = is_stream """发送调试消息到流水线""" if session_type == 'person': use_session = self.webchat_person_session @@ -169,6 +219,9 @@ class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): message_id = len(use_session.get_message_list(pipeline_uuid)) + 1 + use_session.resp_queues[message_id] = asyncio.Queue() + logger.debug(f'Initialized queue for message_id: {message_id}') + use_session.get_message_list(pipeline_uuid).append( WebChatMessage( id=message_id, @@ -202,21 +255,46 @@ class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): self.ap.platform_mgr.webchat_proxy_bot.bot_entity.use_pipeline_uuid = pipeline_uuid + # trigger pipeline if event.__class__ in self.listeners: await self.listeners[event.__class__](event, self) - # set waiter - waiter = asyncio.Future[WebChatMessage]() - use_session.resp_waiters[message_id] = waiter - waiter.add_done_callback(lambda future: use_session.resp_waiters.pop(message_id)) + if is_stream: + queue = use_session.resp_queues[message_id] + msg_id = len(use_session.get_message_list(pipeline_uuid)) + 1 + while True: + resp_message = await queue.get() + resp_message.id = msg_id + if resp_message.is_final: + resp_message.id = msg_id + use_session.get_message_list(pipeline_uuid).append(resp_message) + yield resp_message.model_dump() + break + yield resp_message.model_dump() + use_session.resp_queues.pop(message_id) - resp_message = await waiter + else: # non-stream + # set waiter + # waiter = asyncio.Future[WebChatMessage]() + # use_session.resp_waiters[message_id] = waiter + # # waiter.add_done_callback(lambda future: use_session.resp_waiters.pop(message_id)) + # + # resp_message = await waiter + # + # resp_message.id = len(use_session.get_message_list(pipeline_uuid)) + 1 + # + # use_session.get_message_list(pipeline_uuid).append(resp_message) + # + # yield resp_message.model_dump() + msg_id = len(use_session.get_message_list(pipeline_uuid)) + 1 - resp_message.id = len(use_session.get_message_list(pipeline_uuid)) + 1 + queue = use_session.resp_queues[message_id] + resp_message = await queue.get() + use_session.get_message_list(pipeline_uuid).append(resp_message) + resp_message.id = msg_id + resp_message.is_final = True - use_session.get_message_list(pipeline_uuid).append(resp_message) - - return resp_message.model_dump() + yield resp_message.model_dump() def get_webchat_messages(self, pipeline_uuid: str, session_type: str) -> list[dict]: """获取调试消息历史""" diff --git a/pkg/platform/sources/webchat.yaml b/pkg/platform/sources/webchat.yaml index 4e8cc38e..748dfc8c 100644 --- a/pkg/platform/sources/webchat.yaml +++ b/pkg/platform/sources/webchat.yaml @@ -9,7 +9,8 @@ metadata: en_US: "WebChat adapter for pipeline debugging" zh_Hans: "用于流水线调试的网页聊天适配器" icon: "" -spec: {} +spec: + config: [] execution: python: path: "webchat.py" diff --git a/pkg/platform/sources/wechatpad.py b/pkg/platform/sources/wechatpad.py index 53d7a952..e719b7aa 100644 --- a/pkg/platform/sources/wechatpad.py +++ b/pkg/platform/sources/wechatpad.py @@ -11,13 +11,11 @@ import asyncio import traceback import re import base64 -import os import copy import threading import quart -from ...core import app from ..logger import EventLogger import xml.etree.ElementTree as ET from typing import Optional, Tuple @@ -27,21 +25,23 @@ import langbot_plugin.api.entities.builtin.platform.message as platform_message import langbot_plugin.api.entities.builtin.platform.events as platform_events import langbot_plugin.api.entities.builtin.platform.entities as platform_entities import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter +import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConverter): - def __init__(self, config: dict): + def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger): self.config = config 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 = [] - _ = os.path.abspath(__file__) for component in message_chain: - if isinstance(component, platform_message.At): + if isinstance(component, platform_message.AtAll): + 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}) @@ -75,20 +75,34 @@ class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConvert 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) + + 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'] @@ -226,8 +240,8 @@ class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConvert # self.logger.info("_handler_compound_quote", ET.tostring(xml_data, encoding='unicode')) appmsg_data = xml_data.find('.//appmsg') quote_data = '' # 引用原文 - quote_id = None # 引用消息的原发送者 - tousername = None # 接收方: 所属微信的wxid + # quote_id = None # 引用消息的原发送者 + # tousername = None # 接收方: 所属微信的wxid user_data = '' # 用户消息 sender_id = xml_data.findtext('.//fromusername') # 发送方：单聊用户/群member @@ -235,13 +249,10 @@ class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConvert if appmsg_data: user_data = appmsg_data.findtext('.//title') or '' quote_data = appmsg_data.find('.//refermsg').findtext('.//content') - quote_id = appmsg_data.find('.//refermsg').findtext('.//chatusr') + # quote_id = appmsg_data.find('.//refermsg').findtext('.//chatusr') message_list.append(platform_message.WeChatAppMsg(app_msg=ET.tostring(appmsg_data, encoding='unicode'))) - if message: - tousername = message['to_user_name']['str'] - - _ = tousername - _ = quote_id + # if message: + # tousername = message['to_user_name']['str'] if quote_data: quote_data_message_list = platform_message.MessageChain() @@ -397,6 +408,23 @@ class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConvert 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: @@ -420,16 +448,20 @@ class WeChatPadMessageConverter(abstract_platform_adapter.AbstractMessageConvert class WeChatPadEventConverter(abstract_platform_adapter.AbstractEventConverter): - def __init__(self, config: dict): + def __init__(self, config: dict, logger: logging.Logger): self.config = config - self.message_converter = WeChatPadMessageConverter(config) - self.logger = logging.getLogger('WeChatPadEventConverter') + 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_') @@ -489,8 +521,6 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) config: dict - ap: app.Application - logger: EventLogger message_converter: WeChatPadMessageConverter @@ -501,14 +531,13 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None], ] = {} - def __init__(self, config: dict, ap: app.Application, logger: EventLogger): + def __init__(self, config: dict, logger: EventLogger): self.config = config - self.ap = ap self.logger = logger self.quart_app = quart.Quart(__name__) - self.message_converter = WeChatPadMessageConverter(config) - self.event_converter = WeChatPadEventConverter(config) + self.message_converter = WeChatPadMessageConverter(config, logger) + self.event_converter = WeChatPadEventConverter(config, logger) async def ws_message(self, data): """处理接收到的消息""" @@ -541,19 +570,22 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) for msg in content_list: # 文本消息处理@ if msg['type'] == 'text' and at_targets: - at_nick_name_list = [] - 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"]}' + if 'all' in at_targets: + msg['content'] = f'@所有人 {msg["content"]}' + else: + at_nick_name_list = [] + 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'] @@ -575,7 +607,7 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) if handler := handler_map.get(msg['type']): handler(msg) else: - print(f'未处理的消息类型: {msg["type"]}') + self.logger.warning(f'未处理的消息类型: {msg["type"]}') continue async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain): @@ -650,7 +682,7 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) # url = login_data['Data']["QrCodeUrl"] profile = self.bot.get_profile() - self.logger.info(profile) + # self.logger.info(profile) self.bot_account_id = profile['Data']['userInfo']['nickName']['str'] self.config['wxid'] = profile['Data']['userInfo']['userName']['str'] @@ -670,18 +702,18 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter) # 这里需要确保ws_message是同步的，或者使用asyncio.run调用异步方法 asyncio.run(self.ws_message(data)) except json.JSONDecodeError: - print(f'Non-JSON message: {message[:100]}...') + self.logger.error(f'Non-JSON message: {message[:100]}...') def on_error(ws, error): - print(f'WebSocket error: {str(error)[:200]}') + self.logger.error(f'WebSocket error: {str(error)[:200]}') def on_close(ws, close_status_code, close_msg): - print('WebSocket closed, reconnecting...') + self.logger.info('WebSocket closed, reconnecting...') time.sleep(5) connect_websocket_sync() # 自动重连 def on_open(ws): - print('WebSocket connected successfully!') + self.logger.info('WebSocket connected successfully!') ws = websocket.WebSocketApp( uri, on_message=on_message, on_error=on_error, on_close=on_close, on_open=on_open diff --git a/pkg/platform/sources/wecomcs.py b/pkg/platform/sources/wecomcs.py index a0c24c08..7ce3a064 100644 --- a/pkg/platform/sources/wecomcs.py +++ b/pkg/platform/sources/wecomcs.py @@ -144,9 +144,9 @@ class WecomCSAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter): super().__init__( config=config, logger=logger, - bot=bot, bot_account_id='', listeners={}, + bot=bot, ) async def reply_message( diff --git a/pkg/provider/modelmgr/entities.py b/pkg/provider/modelmgr/entities.py index 91d1d6e9..efe9c112 100644 --- a/pkg/provider/modelmgr/entities.py +++ b/pkg/provider/modelmgr/entities.py @@ -17,7 +17,7 @@ class LLMModelInfo(pydantic.BaseModel): token_mgr: token.TokenManager - requester: requester.LLMAPIRequester + requester: requester.ProviderAPIRequester tool_call_supported: typing.Optional[bool] = False diff --git a/pkg/provider/modelmgr/modelmgr.py b/pkg/provider/modelmgr/modelmgr.py index 27621e6d..d649b41e 100644 --- a/pkg/provider/modelmgr/modelmgr.py +++ b/pkg/provider/modelmgr/modelmgr.py @@ -20,13 +20,16 @@ class ModelManager: llm_models: list[requester.RuntimeLLMModel] + embedding_models: list[requester.RuntimeEmbeddingModel] + requester_components: list[engine.Component] - requester_dict: dict[str, type[requester.LLMAPIRequester]] # cache + requester_dict: dict[str, type[requester.ProviderAPIRequester]] # cache def __init__(self, ap: app.Application): self.ap = ap self.llm_models = [] + self.embedding_models = [] self.requester_components = [] self.requester_dict = {} @@ -34,7 +37,7 @@ class ModelManager: self.requester_components = self.ap.discover.get_components_by_kind('LLMAPIRequester') # forge requester class dict - requester_dict: dict[str, type[requester.LLMAPIRequester]] = {} + requester_dict: dict[str, type[requester.ProviderAPIRequester]] = {} for component in self.requester_components: requester_dict[component.metadata.name] = component.get_python_component_class() @@ -47,13 +50,11 @@ class ModelManager: self.ap.logger.info('Loading models from db...') self.llm_models = [] + self.embedding_models = [] # llm models result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel)) - llm_models = result.all() - - # load models for llm_model in llm_models: try: await self.load_llm_model(llm_model) @@ -62,11 +63,17 @@ class ModelManager: except Exception as e: self.ap.logger.error(f'Failed to load model {llm_model.uuid}: {e}\n{traceback.format_exc()}') + # embedding models + result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel)) + embedding_models = result.all() + for embedding_model in embedding_models: + await self.load_embedding_model(embedding_model) + async def init_runtime_llm_model( self, model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict, ): - """初始化运行时模型""" + """初始化运行时 LLM 模型""" if isinstance(model_info, sqlalchemy.Row): model_info = persistence_model.LLMModel(**model_info._mapping) elif isinstance(model_info, dict): @@ -90,31 +97,85 @@ class ModelManager: return runtime_llm_model + async def init_runtime_embedding_model( + self, + model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict, + ): + """初始化运行时 Embedding 模型""" + if isinstance(model_info, sqlalchemy.Row): + model_info = persistence_model.EmbeddingModel(**model_info._mapping) + elif isinstance(model_info, dict): + model_info = persistence_model.EmbeddingModel(**model_info) + + requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config) + + await requester_inst.initialize() + + runtime_embedding_model = requester.RuntimeEmbeddingModel( + model_entity=model_info, + token_mgr=token.TokenManager( + name=model_info.uuid, + tokens=model_info.api_keys, + ), + requester=requester_inst, + ) + + return runtime_embedding_model + async def load_llm_model( self, model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict, ): - """加载模型""" + """加载 LLM 模型""" runtime_llm_model = await self.init_runtime_llm_model(model_info) self.llm_models.append(runtime_llm_model) + async def load_embedding_model( + self, + model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict, + ): + """加载 Embedding 模型""" + runtime_embedding_model = await self.init_runtime_embedding_model(model_info) + self.embedding_models.append(runtime_embedding_model) + async def get_model_by_uuid(self, uuid: str) -> requester.RuntimeLLMModel: - """通过uuid获取模型""" + """通过uuid获取 LLM 模型""" for model in self.llm_models: if model.model_entity.uuid == uuid: return model - raise ValueError(f'model {uuid} not found') + raise ValueError(f'LLM model {uuid} not found') + + async def get_embedding_model_by_uuid(self, uuid: str) -> requester.RuntimeEmbeddingModel: + """通过uuid获取 Embedding 模型""" + for model in self.embedding_models: + if model.model_entity.uuid == uuid: + return model + raise ValueError(f'Embedding model {uuid} not found') async def remove_llm_model(self, model_uuid: str): - """移除模型""" + """移除 LLM 模型""" for model in self.llm_models: if model.model_entity.uuid == model_uuid: self.llm_models.remove(model) return - def get_available_requesters_info(self) -> list[dict]: + async def remove_embedding_model(self, model_uuid: str): + """移除 Embedding 模型""" + for model in self.embedding_models: + if model.model_entity.uuid == model_uuid: + self.embedding_models.remove(model) + return + + def get_available_requesters_info(self, model_type: str) -> list[dict]: """获取所有可用的请求器""" - return [component.to_plain_dict() for component in self.requester_components] + if model_type != '': + return [ + component.to_plain_dict() + for component in self.requester_components + if model_type in component.spec['support_type'] + ] + else: + return [component.to_plain_dict() for component in self.requester_components] def get_available_requester_info_by_name(self, name: str) -> dict | None: """通过名称获取请求器信息""" diff --git a/pkg/provider/modelmgr/requester.py b/pkg/provider/modelmgr/requester.py index 1620dac7..52d73eea 100644 --- a/pkg/provider/modelmgr/requester.py +++ b/pkg/provider/modelmgr/requester.py @@ -20,22 +20,45 @@ class RuntimeLLMModel: token_mgr: token.TokenManager """api key管理器""" - requester: LLMAPIRequester + requester: ProviderAPIRequester """请求器实例""" def __init__( self, model_entity: persistence_model.LLMModel, token_mgr: token.TokenManager, - requester: LLMAPIRequester, + requester: ProviderAPIRequester, ): self.model_entity = model_entity self.token_mgr = token_mgr self.requester = requester -class LLMAPIRequester(metaclass=abc.ABCMeta): - """LLM API请求器""" +class RuntimeEmbeddingModel: + """运行时 Embedding 模型""" + + model_entity: persistence_model.EmbeddingModel + """模型数据""" + + token_mgr: token.TokenManager + """api key管理器""" + + requester: ProviderAPIRequester + """请求器实例""" + + def __init__( + self, + model_entity: persistence_model.EmbeddingModel, + token_mgr: token.TokenManager, + requester: ProviderAPIRequester, + ): + self.model_entity = model_entity + self.token_mgr = token_mgr + self.requester = requester + + +class ProviderAPIRequester(metaclass=abc.ABCMeta): + """Provider API请求器""" name: str = None @@ -61,6 +84,7 @@ class LLMAPIRequester(metaclass=abc.ABCMeta): messages: typing.List[provider_message.Message], funcs: typing.List[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: """调用API @@ -69,8 +93,50 @@ class LLMAPIRequester(metaclass=abc.ABCMeta): messages (typing.List[llm_entities.Message]): 消息对象列表 funcs (typing.List[tools_entities.LLMFunction], optional): 使用的工具函数列表. Defaults to None. extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}. + remove_think (bool, optional): 是否移思考中的消息. Defaults to False. Returns: llm_entities.Message: 返回消息对象 """ pass + + async def invoke_llm_stream( + self, + query: pipeline_query.Query, + model: RuntimeLLMModel, + messages: typing.List[provider_message.Message], + funcs: typing.List[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.MessageChunk: + """调用API + + Args: + model (RuntimeLLMModel): 使用的模型信息 + messages (typing.List[provider_message.Message]): 消息对象列表 + funcs (typing.List[resource_tool.LLMTool], optional): 使用的工具函数列表. Defaults to None. + extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}. + remove_think (bool, optional): 是否移除思考中的消息. Defaults to False. + + Returns: + typing.AsyncGenerator[provider_message.MessageChunk]: 返回消息对象 + """ + pass + + async def invoke_embedding( + self, + model: RuntimeEmbeddingModel, + input_text: typing.List[str], + extra_args: dict[str, typing.Any] = {}, + ) -> typing.List[typing.List[float]]: + """调用 Embedding API + + Args: + model (RuntimeEmbeddingModel): 使用的模型信息 + input_text (typing.List[str]): 输入文本 + extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}. + + Returns: + typing.List[typing.List[float]]: 返回的 embedding 向量 + """ + pass diff --git a/pkg/provider/modelmgr/requesters/302aichatcmpl.py b/pkg/provider/modelmgr/requesters/302aichatcmpl.py index bd9aaccd..40a41718 100644 --- a/pkg/provider/modelmgr/requesters/302aichatcmpl.py +++ b/pkg/provider/modelmgr/requesters/302aichatcmpl.py @@ -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 diff --git a/pkg/provider/modelmgr/requesters/302aichatcmpl.yaml b/pkg/provider/modelmgr/requesters/302aichatcmpl.yaml index 9d8ce9ea..5128f61d 100644 --- a/pkg/provider/modelmgr/requesters/302aichatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/302aichatcmpl.yaml @@ -3,8 +3,8 @@ kind: LLMAPIRequester metadata: name: 302-ai-chat-completions label: - en_US: 302 AI - zh_Hans: 302 AI + en_US: 302.AI + zh_Hans: 302.AI icon: 302ai.png spec: config: @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./302aichatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/anthropicmsgs.py b/pkg/provider/modelmgr/requesters/anthropicmsgs.py index 880c61bd..3a1b9384 100644 --- a/pkg/provider/modelmgr/requesters/anthropicmsgs.py +++ b/pkg/provider/modelmgr/requesters/anthropicmsgs.py @@ -15,13 +15,13 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query import langbot_plugin.api.entities.builtin.provider.message as provider_message -class AnthropicMessages(requester.LLMAPIRequester): +class AnthropicMessages(requester.ProviderAPIRequester): """Anthropic Messages API 请求器""" client: anthropic.AsyncAnthropic default_config: dict[str, typing.Any] = { - 'base_url': 'https://api.anthropic.com/v1', + 'base_url': 'https://api.anthropic.com', 'timeout': 120, } @@ -44,6 +44,7 @@ class AnthropicMessages(requester.LLMAPIRequester): self.client = anthropic.AsyncAnthropic( api_key='', http_client=httpx_client, + base_url=self.requester_cfg['base_url'], ) async def invoke_llm( @@ -53,6 +54,7 @@ class AnthropicMessages(requester.LLMAPIRequester): messages: typing.List[provider_message.Message], funcs: typing.List[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: self.client.api_key = model.token_mgr.get_token() @@ -89,7 +91,8 @@ class AnthropicMessages(requester.LLMAPIRequester): { 'type': 'tool_result', 'tool_use_id': tool_call_id, - 'content': m.content, + 'is_error': False, + 'content': [{'type': 'text', 'text': m.content}], } ], } @@ -133,6 +136,9 @@ class AnthropicMessages(requester.LLMAPIRequester): args['messages'] = req_messages + if 'thinking' in args: + args['thinking'] = {'type': 'enabled', 'budget_tokens': 10000} + if funcs: tools = await self.ap.tool_mgr.generate_tools_for_anthropic(funcs) @@ -140,19 +146,17 @@ class AnthropicMessages(requester.LLMAPIRequester): args['tools'] = tools try: - # print(json.dumps(args, indent=4, ensure_ascii=False)) resp = await self.client.messages.create(**args) args = { 'content': '', 'role': resp.role, } - assert type(resp) is anthropic.types.message.Message for block in resp.content: - if block.type == 'thinking': - args['content'] = '' + block.thinking + '\n' + args['content'] + if not remove_think and block.type == 'thinking': + args['content'] = '\n' + block.thinking + '\n\n' + args['content'] elif block.type == 'text': args['content'] += block.text elif block.type == 'tool_use': @@ -176,3 +180,191 @@ class AnthropicMessages(requester.LLMAPIRequester): raise errors.RequesterError(f'模型无效: {e.message}') else: raise errors.RequesterError(f'请求地址无效: {e.message}') + + async def invoke_llm_stream( + self, + query: pipeline_query.Query, + model: requester.RuntimeLLMModel, + messages: typing.List[provider_message.Message], + funcs: typing.List[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.Message: + self.client.api_key = model.token_mgr.get_token() + + args = extra_args.copy() + args['model'] = model.model_entity.name + args['stream'] = True + + # 处理消息 + + # system + system_role_message = None + + for i, m in enumerate(messages): + if m.role == 'system': + system_role_message = m + + break + + if system_role_message: + messages.pop(i) + + if isinstance(system_role_message, provider_message.Message) and isinstance(system_role_message.content, str): + args['system'] = system_role_message.content + + req_messages = [] + + for m in messages: + if m.role == 'tool': + tool_call_id = m.tool_call_id + + req_messages.append( + { + 'role': 'user', + 'content': [ + { + 'type': 'tool_result', + 'tool_use_id': tool_call_id, + 'is_error': False, # 暂时直接写false + 'content': [ + {'type': 'text', 'text': m.content} + ], # 这里要是list包裹，应该是多个返回的情况？type类型好像也可以填其他的，暂时只写text + } + ], + } + ) + + continue + + msg_dict = m.dict(exclude_none=True) + + if isinstance(m.content, str) and m.content.strip() != '': + msg_dict['content'] = [{'type': 'text', 'text': m.content}] + elif isinstance(m.content, list): + for i, ce in enumerate(m.content): + if ce.type == 'image_base64': + image_b64, image_format = await image.extract_b64_and_format(ce.image_base64) + + alter_image_ele = { + 'type': 'image', + 'source': { + 'type': 'base64', + 'media_type': f'image/{image_format}', + 'data': image_b64, + }, + } + msg_dict['content'][i] = alter_image_ele + if isinstance(msg_dict['content'], str) and msg_dict['content'] == '': + msg_dict['content'] = [] # 这里不知道为什么会莫名有个空导致content为字符 + if m.tool_calls: + for tool_call in m.tool_calls: + msg_dict['content'].append( + { + 'type': 'tool_use', + 'id': tool_call.id, + 'name': tool_call.function.name, + 'input': json.loads(tool_call.function.arguments), + } + ) + + del msg_dict['tool_calls'] + + req_messages.append(msg_dict) + if 'thinking' in args: + args['thinking'] = {'type': 'enabled', 'budget_tokens': 10000} + + args['messages'] = req_messages + + if funcs: + tools = await self.ap.tool_mgr.generate_tools_for_anthropic(funcs) + + if tools: + args['tools'] = tools + + try: + role = 'assistant' # 默认角色 + # chunk_idx = 0 + think_started = False + think_ended = False + finish_reason = False + content = '' + tool_name = '' + tool_id = '' + async for chunk in await self.client.messages.create(**args): + tool_call = {'id': None, 'function': {'name': None, 'arguments': None}, 'type': 'function'} + if isinstance( + chunk, anthropic.types.raw_content_block_start_event.RawContentBlockStartEvent + ): # 记录开始 + if chunk.content_block.type == 'tool_use': + if chunk.content_block.name is not None: + tool_name = chunk.content_block.name + if chunk.content_block.id is not None: + tool_id = chunk.content_block.id + + tool_call['function']['name'] = tool_name + tool_call['function']['arguments'] = '' + tool_call['id'] = tool_id + + if not remove_think: + if chunk.content_block.type == 'thinking' and not remove_think: + think_started = True + elif chunk.content_block.type == 'text' and chunk.index != 0 and not remove_think: + think_ended = True + continue + elif isinstance(chunk, anthropic.types.raw_content_block_delta_event.RawContentBlockDeltaEvent): + if chunk.delta.type == 'thinking_delta': + if think_started: + think_started = False + content = '\n' + chunk.delta.thinking + elif remove_think: + continue + else: + content = chunk.delta.thinking + elif chunk.delta.type == 'text_delta': + if think_ended: + think_ended = False + content = '\n\n' + chunk.delta.text + else: + content = chunk.delta.text + elif chunk.delta.type == 'input_json_delta': + tool_call['function']['arguments'] = chunk.delta.partial_json + tool_call['function']['name'] = tool_name + tool_call['id'] = tool_id + elif isinstance(chunk, anthropic.types.raw_content_block_stop_event.RawContentBlockStopEvent): + continue # 记录raw_content_block结束的 + + elif isinstance(chunk, anthropic.types.raw_message_delta_event.RawMessageDeltaEvent): + if chunk.delta.stop_reason == 'end_turn': + finish_reason = True + elif isinstance(chunk, anthropic.types.raw_message_stop_event.RawMessageStopEvent): + continue # 这个好像是完全结束 + else: + # print(chunk) + self.ap.logger.debug(f'anthropic chunk: {chunk}') + continue + + args = { + 'content': content, + 'role': role, + 'is_final': finish_reason, + 'tool_calls': None if tool_call['id'] is None else [tool_call], + } + # if chunk_idx == 0: + # chunk_idx += 1 + # continue + + # assert type(chunk) is anthropic.types.message.Chunk + + yield provider_message.MessageChunk(**args) + + # return llm_entities.Message(**args) + except anthropic.AuthenticationError as e: + raise errors.RequesterError(f'api-key 无效: {e.message}') + except anthropic.BadRequestError as e: + raise errors.RequesterError(str(e.message)) + except anthropic.NotFoundError as e: + if 'model: ' in str(e): + raise errors.RequesterError(f'模型无效: {e.message}') + else: + raise errors.RequesterError(f'请求地址无效: {e.message}') diff --git a/pkg/provider/modelmgr/requesters/anthropicmsgs.yaml b/pkg/provider/modelmgr/requesters/anthropicmsgs.yaml index c124fed9..e3f745fb 100644 --- a/pkg/provider/modelmgr/requesters/anthropicmsgs.yaml +++ b/pkg/provider/modelmgr/requesters/anthropicmsgs.yaml @@ -14,7 +14,7 @@ spec: zh_Hans: 基础 URL type: string required: true - default: "https://api.anthropic.com/v1" + default: "https://api.anthropic.com" - name: timeout label: en_US: Timeout @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./anthropicmsgs.py diff --git a/pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml b/pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml index 24beb915..10aae30f 100644 --- a/pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./bailianchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/chatcmpl.py b/pkg/provider/modelmgr/requesters/chatcmpl.py index 78f427b8..b940859e 100644 --- a/pkg/provider/modelmgr/requesters/chatcmpl.py +++ b/pkg/provider/modelmgr/requesters/chatcmpl.py @@ -13,7 +13,7 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query import langbot_plugin.api.entities.builtin.provider.message as provider_message -class OpenAIChatCompletions(requester.LLMAPIRequester): +class OpenAIChatCompletions(requester.ProviderAPIRequester): """OpenAI ChatCompletion API 请求器""" client: openai.AsyncClient @@ -38,9 +38,18 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): ) -> chat_completion.ChatCompletion: return await self.client.chat.completions.create(**args, extra_body=extra_body) + async def _req_stream( + self, + args: dict, + extra_body: dict = {}, + ): + async for chunk in await self.client.chat.completions.create(**args, extra_body=extra_body): + yield chunk + async def _make_msg( self, chat_completion: chat_completion.ChatCompletion, + remove_think: bool = False, ) -> provider_message.Message: chatcmpl_message = chat_completion.choices[0].message.model_dump() @@ -48,16 +57,191 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None: chatcmpl_message['role'] = 'assistant' - reasoning_content = chatcmpl_message['reasoning_content'] if 'reasoning_content' in chatcmpl_message else None + # 处理思维链 + content = chatcmpl_message.get('content', '') + reasoning_content = chatcmpl_message.get('reasoning_content', None) - # deepseek的reasoner模型 - if reasoning_content is not None: - chatcmpl_message['content'] = '\n' + reasoning_content + '\n\n' + chatcmpl_message['content'] + processed_content, _ = await self._process_thinking_content( + content=content, reasoning_content=reasoning_content, remove_think=remove_think + ) + + chatcmpl_message['content'] = processed_content + + # 移除 reasoning_content 字段，避免传递给 Message + if 'reasoning_content' in chatcmpl_message: + del chatcmpl_message['reasoning_content'] message = provider_message.Message(**chatcmpl_message) return message + async def _process_thinking_content( + self, + content: str, + reasoning_content: str = None, + remove_think: bool = False, + ) -> tuple[str, str]: + """处理思维链内容 + + Args: + content: 原始内容 + reasoning_content: reasoning_content 字段内容 + remove_think: 是否移除思维链 + + Returns: + (处理后的内容, 提取的思维链内容) + """ + thinking_content = '' + + # 1. 从 reasoning_content 提取思维链 + if reasoning_content: + thinking_content = reasoning_content + + # 2. 从 content 中提取 标签内容 + if content and '' in content and '' in content: + import re + + think_pattern = r'(.*?)' + think_matches = re.findall(think_pattern, content, re.DOTALL) + if think_matches: + # 如果已有 reasoning_content，则追加 + if thinking_content: + thinking_content += '\n' + '\n'.join(think_matches) + else: + thinking_content = '\n'.join(think_matches) + # 移除 content 中的 标签 + content = re.sub(think_pattern, '', content, flags=re.DOTALL).strip() + + # 3. 根据 remove_think 参数决定是否保留思维链 + if remove_think: + return content, '' + else: + # 如果有思维链内容，将其以 格式添加到 content 开头 + if thinking_content: + content = f'\n{thinking_content}\n\n{content}'.strip() + return content, thinking_content + + async def _closure_stream( + self, + query: pipeline_query.Query, + req_messages: list[dict], + use_model: requester.RuntimeLLMModel, + use_funcs: list[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.MessageChunk: + self.client.api_key = use_model.token_mgr.get_token() + + args = {} + args['model'] = use_model.model_entity.name + + if use_funcs: + tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs) + if tools: + args['tools'] = tools + + # 设置此次请求中的messages + messages = req_messages.copy() + + # 检查vision + for msg in messages: + if 'content' in msg and isinstance(msg['content'], list): + for me in msg['content']: + if me['type'] == 'image_base64': + me['image_url'] = {'url': me['image_base64']} + me['type'] = 'image_url' + del me['image_base64'] + + args['messages'] = messages + args['stream'] = True + + # 流式处理状态 + # tool_calls_map: dict[str, provider_message.ToolCall] = {} + chunk_idx = 0 + thinking_started = False + thinking_ended = False + role = 'assistant' # 默认角色 + tool_id = '' + tool_name = '' + # accumulated_reasoning = '' # 仅用于判断何时结束思维链 + + async for chunk in self._req_stream(args, extra_body=extra_args): + # 解析 chunk 数据 + + if hasattr(chunk, 'choices') and chunk.choices: + choice = chunk.choices[0] + delta = choice.delta.model_dump() if hasattr(choice, 'delta') else {} + + finish_reason = getattr(choice, 'finish_reason', None) + else: + delta = {} + finish_reason = None + # 从第一个 chunk 获取 role，后续使用这个 role + if 'role' in delta and delta['role']: + role = delta['role'] + + # 获取增量内容 + delta_content = delta.get('content', '') + reasoning_content = delta.get('reasoning_content', '') + + # 处理 reasoning_content + if reasoning_content: + # accumulated_reasoning += reasoning_content + # 如果设置了 remove_think，跳过 reasoning_content + if remove_think: + chunk_idx += 1 + continue + + # 第一次出现 reasoning_content，添加 开始标签 + if not thinking_started: + thinking_started = True + delta_content = '\n' + reasoning_content + else: + # 继续输出 reasoning_content + delta_content = reasoning_content + elif thinking_started and not thinking_ended and delta_content: + # reasoning_content 结束，normal content 开始，添加 结束标签 + thinking_ended = True + delta_content = '\n\n' + delta_content + + # 处理 content 中已有的 标签（如果需要移除） + # if delta_content and remove_think and '' in delta_content: + # import re + # + # # 移除 标签及其内容 + # delta_content = re.sub(r'.*?', '', delta_content, flags=re.DOTALL) + + # 处理工具调用增量 + # delta_tool_calls = None + if delta.get('tool_calls'): + for tool_call in delta['tool_calls']: + if tool_call['id'] and tool_call['function']['name']: + tool_id = tool_call['id'] + tool_name = tool_call['function']['name'] + else: + tool_call['id'] = tool_id + tool_call['function']['name'] = tool_name + if tool_call['type'] is None: + tool_call['type'] = 'function' + + # 跳过空的第一个 chunk（只有 role 没有内容） + if chunk_idx == 0 and not delta_content and not reasoning_content and not delta.get('tool_calls'): + chunk_idx += 1 + continue + # 构建 MessageChunk - 只包含增量内容 + chunk_data = { + 'role': role, + 'content': delta_content if delta_content else None, + 'tool_calls': delta.get('tool_calls'), + 'is_final': bool(finish_reason), + } + + # 移除 None 值 + chunk_data = {k: v for k, v in chunk_data.items() if v is not None} + + yield provider_message.MessageChunk(**chunk_data) + chunk_idx += 1 + async def _closure( self, query: pipeline_query.Query, @@ -65,6 +249,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): use_model: requester.RuntimeLLMModel, use_funcs: list[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: self.client.api_key = use_model.token_mgr.get_token() @@ -92,10 +277,10 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): args['messages'] = messages # 发送请求 - resp = await self._req(args, extra_body=extra_args) + resp = await self._req(args, extra_body=extra_args) # 处理请求结果 - message = await self._make_msg(resp) + message = await self._make_msg(resp, remove_think) return message @@ -106,6 +291,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): messages: typing.List[provider_message.Message], funcs: typing.List[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行 for m in messages: @@ -119,13 +305,90 @@ class OpenAIChatCompletions(requester.LLMAPIRequester): req_messages.append(msg_dict) try: - return await self._closure( + msg = await self._closure( query=query, req_messages=req_messages, use_model=model, use_funcs=funcs, extra_args=extra_args, + remove_think=remove_think, ) + return msg + except asyncio.TimeoutError: + raise errors.RequesterError('请求超时') + except openai.BadRequestError as e: + if 'context_length_exceeded' in e.message: + raise errors.RequesterError(f'上文过长，请重置会话: {e.message}') + else: + raise errors.RequesterError(f'请求参数错误: {e.message}') + except openai.AuthenticationError as e: + raise errors.RequesterError(f'无效的 api-key: {e.message}') + except openai.NotFoundError as e: + raise errors.RequesterError(f'请求路径错误: {e.message}') + except openai.RateLimitError as e: + raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}') + except openai.APIError as e: + raise errors.RequesterError(f'请求错误: {e.message}') + + async def invoke_embedding( + self, + model: requester.RuntimeEmbeddingModel, + input_text: list[str], + extra_args: dict[str, typing.Any] = {}, + ) -> list[list[float]]: + """调用 Embedding API""" + self.client.api_key = model.token_mgr.get_token() + + args = { + 'model': model.model_entity.name, + 'input': input_text, + } + + if model.model_entity.extra_args: + args.update(model.model_entity.extra_args) + + args.update(extra_args) + + try: + resp = await self.client.embeddings.create(**args) + + return [d.embedding for d in resp.data] + except asyncio.TimeoutError: + raise errors.RequesterError('请求超时') + except openai.BadRequestError as e: + raise errors.RequesterError(f'请求参数错误: {e.message}') + + async def invoke_llm_stream( + self, + query: pipeline_query.Query, + model: requester.RuntimeLLMModel, + messages: typing.List[provider_message.Message], + funcs: typing.List[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.MessageChunk: + req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行 + for m in messages: + msg_dict = m.dict(exclude_none=True) + content = msg_dict.get('content') + if isinstance(content, list): + # 检查 content 列表中是否每个部分都是文本 + if all(isinstance(part, dict) and part.get('type') == 'text' for part in content): + # 将所有文本部分合并为一个字符串 + msg_dict['content'] = '\n'.join(part['text'] for part in content) + req_messages.append(msg_dict) + + try: + async for item in self._closure_stream( + query=query, + req_messages=req_messages, + use_model=model, + use_funcs=funcs, + extra_args=extra_args, + remove_think=remove_think, + ): + yield item + except asyncio.TimeoutError: raise errors.RequesterError('请求超时') except openai.BadRequestError as e: diff --git a/pkg/provider/modelmgr/requesters/chatcmpl.yaml b/pkg/provider/modelmgr/requesters/chatcmpl.yaml index 908b30ac..ff0de6f9 100644 --- a/pkg/provider/modelmgr/requesters/chatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/chatcmpl.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./chatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/compshare.png b/pkg/provider/modelmgr/requesters/compshare.png new file mode 100644 index 00000000..3ef1709c Binary files /dev/null and b/pkg/provider/modelmgr/requesters/compshare.png differ diff --git a/pkg/provider/modelmgr/requesters/compsharechatcmpl.py b/pkg/provider/modelmgr/requesters/compsharechatcmpl.py new file mode 100644 index 00000000..d272e721 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/compsharechatcmpl.py @@ -0,0 +1,17 @@ +from __future__ import annotations + +import typing +import openai + +from . import chatcmpl + + +class CompShareChatCompletions(chatcmpl.OpenAIChatCompletions): + """CompShare ChatCompletion API 请求器""" + + client: openai.AsyncClient + + default_config: dict[str, typing.Any] = { + 'base_url': 'https://api.modelverse.cn/v1', + 'timeout': 120, + } diff --git a/pkg/provider/modelmgr/requesters/compsharechatcmpl.yaml b/pkg/provider/modelmgr/requesters/compsharechatcmpl.yaml new file mode 100644 index 00000000..2b7f9a70 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/compsharechatcmpl.yaml @@ -0,0 +1,30 @@ +apiVersion: v1 +kind: LLMAPIRequester +metadata: + name: compshare-chat-completions + label: + en_US: CompShare + zh_Hans: 优云智算 + icon: compshare.png +spec: + config: + - name: base_url + label: + en_US: Base URL + zh_Hans: 基础 URL + type: string + required: true + default: "https://api.modelverse.cn/v1" + - name: timeout + label: + en_US: Timeout + zh_Hans: 超时时间 + type: integer + required: true + default: 120 + support_type: + - llm +execution: + python: + path: ./compsharechatcmpl.py + attr: CompShareChatCompletions \ No newline at end of file diff --git a/pkg/provider/modelmgr/requesters/deepseekchatcmpl.py b/pkg/provider/modelmgr/requesters/deepseekchatcmpl.py index 95c9fbe2..83b2bfa4 100644 --- a/pkg/provider/modelmgr/requesters/deepseekchatcmpl.py +++ b/pkg/provider/modelmgr/requesters/deepseekchatcmpl.py @@ -24,6 +24,7 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions): use_model: requester.RuntimeLLMModel, use_funcs: list[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: self.client.api_key = use_model.token_mgr.get_token() @@ -49,10 +50,11 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions): # 发送请求 resp = await self._req(args, extra_body=extra_args) + # print(resp) + if resp is None: raise errors.RequesterError('接口返回为空，请确定模型提供商服务是否正常') - # 处理请求结果 - message = await self._make_msg(resp) + message = await self._make_msg(resp, remove_think) return message diff --git a/pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml b/pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml index ea2c7eea..9a22c5d9 100644 --- a/pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml @@ -4,7 +4,7 @@ metadata: name: deepseek-chat-completions label: en_US: DeepSeek - zh_Hans: 深度求索 + zh_Hans: DeepSeek icon: deepseek.svg spec: config: @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./deepseekchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/geminichatcmpl.py b/pkg/provider/modelmgr/requesters/geminichatcmpl.py index 85395f91..9741e6b3 100644 --- a/pkg/provider/modelmgr/requesters/geminichatcmpl.py +++ b/pkg/provider/modelmgr/requesters/geminichatcmpl.py @@ -4,6 +4,13 @@ import typing from . import chatcmpl +import uuid + +from .. import requester +import langbot_plugin.api.entities.builtin.provider.message as provider_message +import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query +import langbot_plugin.api.entities.builtin.resource.tool as resource_tool + class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions): """Google Gemini API 请求器""" @@ -12,3 +19,124 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions): 'base_url': 'https://generativelanguage.googleapis.com/v1beta/openai', 'timeout': 120, } + + async def _closure_stream( + self, + query: pipeline_query.Query, + req_messages: list[dict], + use_model: requester.RuntimeLLMModel, + use_funcs: list[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.MessageChunk: + self.client.api_key = use_model.token_mgr.get_token() + + args = {} + args['model'] = use_model.model_entity.name + + if use_funcs: + tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs) + if tools: + args['tools'] = tools + + # 设置此次请求中的messages + messages = req_messages.copy() + + # 检查vision + for msg in messages: + if 'content' in msg and isinstance(msg['content'], list): + for me in msg['content']: + if me['type'] == 'image_base64': + me['image_url'] = {'url': me['image_base64']} + me['type'] = 'image_url' + del me['image_base64'] + + args['messages'] = messages + args['stream'] = True + + # 流式处理状态 + # tool_calls_map: dict[str, provider_message.ToolCall] = {} + chunk_idx = 0 + thinking_started = False + thinking_ended = False + role = 'assistant' # 默认角色 + tool_id = '' + tool_name = '' + # accumulated_reasoning = '' # 仅用于判断何时结束思维链 + + async for chunk in self._req_stream(args, extra_body=extra_args): + # 解析 chunk 数据 + + if hasattr(chunk, 'choices') and chunk.choices: + choice = chunk.choices[0] + delta = choice.delta.model_dump() if hasattr(choice, 'delta') else {} + + finish_reason = getattr(choice, 'finish_reason', None) + else: + delta = {} + finish_reason = None + # 从第一个 chunk 获取 role，后续使用这个 role + if 'role' in delta and delta['role']: + role = delta['role'] + + # 获取增量内容 + delta_content = delta.get('content', '') + reasoning_content = delta.get('reasoning_content', '') + + # 处理 reasoning_content + if reasoning_content: + # accumulated_reasoning += reasoning_content + # 如果设置了 remove_think，跳过 reasoning_content + if remove_think: + chunk_idx += 1 + continue + + # 第一次出现 reasoning_content，添加 开始标签 + if not thinking_started: + thinking_started = True + delta_content = '\n' + reasoning_content + else: + # 继续输出 reasoning_content + delta_content = reasoning_content + elif thinking_started and not thinking_ended and delta_content: + # reasoning_content 结束，normal content 开始，添加 结束标签 + thinking_ended = True + delta_content = '\n\n' + delta_content + + # 处理 content 中已有的 标签（如果需要移除） + # if delta_content and remove_think and '' in delta_content: + # import re + # + # # 移除 标签及其内容 + # delta_content = re.sub(r'.*?', '', delta_content, flags=re.DOTALL) + + # 处理工具调用增量 + # delta_tool_calls = None + if delta.get('tool_calls'): + for tool_call in delta['tool_calls']: + if tool_call['id'] == '' and tool_id == '': + tool_id = str(uuid.uuid4()) + if tool_call['function']['name']: + tool_name = tool_call['function']['name'] + tool_call['id'] = tool_id + tool_call['function']['name'] = tool_name + if tool_call['type'] is None: + tool_call['type'] = 'function' + + # 跳过空的第一个 chunk（只有 role 没有内容） + if chunk_idx == 0 and not delta_content and not reasoning_content and not delta.get('tool_calls'): + chunk_idx += 1 + continue + # 构建 MessageChunk - 只包含增量内容 + chunk_data = { + 'role': role, + 'content': delta_content if delta_content else None, + 'tool_calls': delta.get('tool_calls'), + 'is_final': bool(finish_reason), + } + + # 移除 None 值 + chunk_data = {k: v for k, v in chunk_data.items() if v is not None} + + yield provider_message.MessageChunk(**chunk_data) + chunk_idx += 1 diff --git a/pkg/provider/modelmgr/requesters/geminichatcmpl.yaml b/pkg/provider/modelmgr/requesters/geminichatcmpl.yaml index 6bfc085e..73fca19c 100644 --- a/pkg/provider/modelmgr/requesters/geminichatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/geminichatcmpl.yaml @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./geminichatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/giteeaichatcmpl.py b/pkg/provider/modelmgr/requesters/giteeaichatcmpl.py index 38d8931e..4e295e9f 100644 --- a/pkg/provider/modelmgr/requesters/giteeaichatcmpl.py +++ b/pkg/provider/modelmgr/requesters/giteeaichatcmpl.py @@ -3,49 +3,13 @@ from __future__ import annotations import typing -from . import chatcmpl -from .. import requester -import langbot_plugin.api.entities.builtin.resource.tool as resource_tool -import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query -import langbot_plugin.api.entities.builtin.provider.message as provider_message +from . import ppiochatcmpl -class GiteeAIChatCompletions(chatcmpl.OpenAIChatCompletions): +class GiteeAIChatCompletions(ppiochatcmpl.PPIOChatCompletions): """Gitee AI ChatCompletions API 请求器""" default_config: dict[str, typing.Any] = { 'base_url': 'https://ai.gitee.com/v1', 'timeout': 120, } - - async def _closure( - self, - query: pipeline_query.Query, - req_messages: list[dict], - use_model: requester.RuntimeLLMModel, - use_funcs: list[resource_tool.LLMTool] = None, - extra_args: dict[str, typing.Any] = {}, - ) -> provider_message.Message: - self.client.api_key = use_model.token_mgr.get_token() - - args = {} - args['model'] = use_model.model_entity.name - - if use_funcs: - tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs) - - if tools: - args['tools'] = tools - - # gitee 不支持多模态，把content都转换成纯文字 - for m in req_messages: - if 'content' in m and isinstance(m['content'], list): - m['content'] = ' '.join([c['text'] for c in m['content']]) - - args['messages'] = req_messages - - resp = await self._req(args, extra_body=extra_args) - - message = await self._make_msg(resp) - - return message diff --git a/pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml b/pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml index a18675a1..d1aec26b 100644 --- a/pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./giteeaichatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml b/pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml index 893235b2..8c44ab39 100644 --- a/pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./lmstudiochatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py b/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py index 657d2ab8..8684a677 100644 --- a/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py +++ b/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py @@ -5,7 +5,6 @@ import typing import openai import openai.types.chat.chat_completion as chat_completion -import openai.types.chat.chat_completion_message_tool_call as chat_completion_message_tool_call import httpx from .. import entities, errors, requester @@ -14,7 +13,7 @@ import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query import langbot_plugin.api.entities.builtin.provider.message as provider_message -class ModelScopeChatCompletions(requester.LLMAPIRequester): +class ModelScopeChatCompletions(requester.ProviderAPIRequester): """ModelScope ChatCompletion API 请求器""" client: openai.AsyncClient @@ -34,9 +33,11 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): async def _req( self, + query: pipeline_query.Query, args: dict, extra_body: dict = {}, - ) -> chat_completion.ChatCompletion: + remove_think: bool = False, + ) -> list[dict[str, typing.Any]]: args['stream'] = True chunk = None @@ -47,73 +48,71 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): resp_gen: openai.AsyncStream = await self.client.chat.completions.create(**args, extra_body=extra_body) + chunk_idx = 0 + thinking_started = False + thinking_ended = False + tool_id = '' + tool_name = '' + message_delta = {} async for chunk in resp_gen: - # print(chunk) if not chunk or not chunk.id or not chunk.choices or not chunk.choices[0] or not chunk.choices[0].delta: continue - if chunk.choices[0].delta.content is not None: - pending_content += chunk.choices[0].delta.content + delta = chunk.choices[0].delta.model_dump() if hasattr(chunk.choices[0], 'delta') else {} + reasoning_content = delta.get('reasoning_content') + # 处理 reasoning_content + if reasoning_content: + # accumulated_reasoning += reasoning_content + # 如果设置了 remove_think，跳过 reasoning_content + if remove_think: + chunk_idx += 1 + continue - if chunk.choices[0].delta.tool_calls is not None: - for tool_call in chunk.choices[0].delta.tool_calls: - if tool_call.function.arguments is None: + # 第一次出现 reasoning_content，添加 开始标签 + if not thinking_started: + thinking_started = True + pending_content += '\n' + reasoning_content + else: + # 继续输出 reasoning_content + pending_content += reasoning_content + elif thinking_started and not thinking_ended and delta.get('content'): + # reasoning_content 结束，normal content 开始，添加 结束标签 + thinking_ended = True + pending_content += '\n\n' + delta.get('content') + + if delta.get('content') is not None: + pending_content += delta.get('content') + + if delta.get('tool_calls') is not None: + for tool_call in delta.get('tool_calls'): + if tool_call['id'] != '': + tool_id = tool_call['id'] + if tool_call['function']['name'] is not None: + tool_name = tool_call['function']['name'] + if tool_call['function']['arguments'] is None: continue + tool_call['id'] = tool_id + tool_call['name'] = tool_name for tc in tool_calls: - if tc.index == tool_call.index: - tc.function.arguments += tool_call.function.arguments + if tc['index'] == tool_call['index']: + tc['function']['arguments'] += tool_call['function']['arguments'] break else: tool_calls.append(tool_call) if chunk.choices[0].finish_reason is not None: break + message_delta['content'] = pending_content + message_delta['role'] = 'assistant' - real_tool_calls = [] - - for tc in tool_calls: - function = chat_completion_message_tool_call.Function( - name=tc.function.name, arguments=tc.function.arguments - ) - real_tool_calls.append( - chat_completion_message_tool_call.ChatCompletionMessageToolCall( - id=tc.id, function=function, type='function' - ) - ) - - return ( - chat_completion.ChatCompletion( - id=chunk.id, - object='chat.completion', - created=chunk.created, - choices=[ - chat_completion.Choice( - index=0, - message=chat_completion.ChatCompletionMessage( - role='assistant', - content=pending_content, - tool_calls=real_tool_calls if len(real_tool_calls) > 0 else None, - ), - finish_reason=chunk.choices[0].finish_reason - if hasattr(chunk.choices[0], 'finish_reason') and chunk.choices[0].finish_reason is not None - else 'stop', - logprobs=chunk.choices[0].logprobs, - ) - ], - model=chunk.model, - service_tier=chunk.service_tier if hasattr(chunk, 'service_tier') else None, - system_fingerprint=chunk.system_fingerprint if hasattr(chunk, 'system_fingerprint') else None, - usage=chunk.usage if hasattr(chunk, 'usage') else None, - ) - if chunk - else None - ) + message_delta['tool_calls'] = tool_calls if tool_calls else None + return [message_delta] async def _make_msg( self, - chat_completion: chat_completion.ChatCompletion, + chat_completion: list[dict[str, typing.Any]], ) -> provider_message.Message: - chatcmpl_message = chat_completion.choices[0].message.dict() + chatcmpl_message = chat_completion[0] # 确保 role 字段存在且不为 None if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None: @@ -130,6 +129,7 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): use_model: requester.RuntimeLLMModel, use_funcs: list[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: self.client.api_key = use_model.token_mgr.get_token() @@ -157,13 +157,145 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): args['messages'] = messages # 发送请求 - resp = await self._req(args, extra_body=extra_args) + resp = await self._req(query, args, extra_body=extra_args, remove_think=remove_think) # 处理请求结果 message = await self._make_msg(resp) return message + async def _req_stream( + self, + args: dict, + extra_body: dict = {}, + ) -> chat_completion.ChatCompletion: + async for chunk in await self.client.chat.completions.create(**args, extra_body=extra_body): + yield chunk + + async def _closure_stream( + self, + query: pipeline_query.Query, + req_messages: list[dict], + use_model: requester.RuntimeLLMModel, + use_funcs: list[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.Message | typing.AsyncGenerator[provider_message.MessageChunk, None]: + self.client.api_key = use_model.token_mgr.get_token() + + args = {} + args['model'] = use_model.model_entity.name + + if use_funcs: + tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs) + + if tools: + args['tools'] = tools + + # 设置此次请求中的messages + messages = req_messages.copy() + + # 检查vision + for msg in messages: + if 'content' in msg and isinstance(msg['content'], list): + for me in msg['content']: + if me['type'] == 'image_base64': + me['image_url'] = {'url': me['image_base64']} + me['type'] = 'image_url' + del me['image_base64'] + + args['messages'] = messages + args['stream'] = True + + # 流式处理状态 + # tool_calls_map: dict[str, provider_message.ToolCall] = {} + chunk_idx = 0 + thinking_started = False + thinking_ended = False + role = 'assistant' # 默认角色 + # accumulated_reasoning = '' # 仅用于判断何时结束思维链 + + async for chunk in self._req_stream(args, extra_body=extra_args): + # 解析 chunk 数据 + if hasattr(chunk, 'choices') and chunk.choices: + choice = chunk.choices[0] + delta = choice.delta.model_dump() if hasattr(choice, 'delta') else {} + finish_reason = getattr(choice, 'finish_reason', None) + else: + delta = {} + finish_reason = None + + # 从第一个 chunk 获取 role，后续使用这个 role + if 'role' in delta and delta['role']: + role = delta['role'] + + # 获取增量内容 + delta_content = delta.get('content', '') + reasoning_content = delta.get('reasoning_content', '') + + # 处理 reasoning_content + if reasoning_content: + # accumulated_reasoning += reasoning_content + # 如果设置了 remove_think，跳过 reasoning_content + if remove_think: + chunk_idx += 1 + continue + + # 第一次出现 reasoning_content，添加 开始标签 + if not thinking_started: + thinking_started = True + delta_content = '\n' + reasoning_content + else: + # 继续输出 reasoning_content + delta_content = reasoning_content + elif thinking_started and not thinking_ended and delta_content: + # reasoning_content 结束，normal content 开始，添加 结束标签 + thinking_ended = True + delta_content = '\n\n' + delta_content + + # 处理 content 中已有的 标签（如果需要移除） + # if delta_content and remove_think and '' in delta_content: + # import re + # + # # 移除 标签及其内容 + # delta_content = re.sub(r'.*?', '', delta_content, flags=re.DOTALL) + + # 处理工具调用增量 + if delta.get('tool_calls'): + for tool_call in delta['tool_calls']: + if tool_call['id'] != '': + tool_id = tool_call['id'] + if tool_call['function']['name'] is not None: + tool_name = tool_call['function']['name'] + + if tool_call['type'] is None: + tool_call['type'] = 'function' + tool_call['id'] = tool_id + tool_call['function']['name'] = tool_name + tool_call['function']['arguments'] = ( + '' if tool_call['function']['arguments'] is None else tool_call['function']['arguments'] + ) + + # 跳过空的第一个 chunk（只有 role 没有内容） + if chunk_idx == 0 and not delta_content and not reasoning_content and not delta.get('tool_calls'): + chunk_idx += 1 + continue + + # 构建 MessageChunk - 只包含增量内容 + chunk_data = { + 'role': role, + 'content': delta_content if delta_content else None, + 'tool_calls': delta.get('tool_calls'), + 'is_final': bool(finish_reason), + } + + # 移除 None 值 + chunk_data = {k: v for k, v in chunk_data.items() if v is not None} + + yield provider_message.MessageChunk(**chunk_data) + chunk_idx += 1 + # return + async def invoke_llm( self, query: pipeline_query.Query, @@ -171,6 +303,7 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): messages: typing.List[provider_message.Message], funcs: typing.List[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行 for m in messages: @@ -185,7 +318,12 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): try: return await self._closure( - query=query, req_messages=req_messages, use_model=model, use_funcs=funcs, extra_args=extra_args + query=query, + req_messages=req_messages, + use_model=model, + use_funcs=funcs, + extra_args=extra_args, + remove_think=remove_think, ) except asyncio.TimeoutError: raise errors.RequesterError('请求超时') @@ -202,3 +340,50 @@ class ModelScopeChatCompletions(requester.LLMAPIRequester): raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}') except openai.APIError as e: raise errors.RequesterError(f'请求错误: {e.message}') + + async def invoke_llm_stream( + self, + query: pipeline_query.Query, + model: requester.RuntimeLLMModel, + messages: typing.List[provider_message.Message], + funcs: typing.List[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.MessageChunk: + req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行 + for m in messages: + msg_dict = m.dict(exclude_none=True) + content = msg_dict.get('content') + if isinstance(content, list): + # 检查 content 列表中是否每个部分都是文本 + if all(isinstance(part, dict) and part.get('type') == 'text' for part in content): + # 将所有文本部分合并为一个字符串 + msg_dict['content'] = '\n'.join(part['text'] for part in content) + req_messages.append(msg_dict) + + try: + async for item in self._closure_stream( + query=query, + req_messages=req_messages, + use_model=model, + use_funcs=funcs, + extra_args=extra_args, + remove_think=remove_think, + ): + yield item + + except asyncio.TimeoutError: + raise errors.RequesterError('请求超时') + except openai.BadRequestError as e: + if 'context_length_exceeded' in e.message: + raise errors.RequesterError(f'上文过长，请重置会话: {e.message}') + else: + raise errors.RequesterError(f'请求参数错误: {e.message}') + except openai.AuthenticationError as e: + raise errors.RequesterError(f'无效的 api-key: {e.message}') + except openai.NotFoundError as e: + raise errors.RequesterError(f'请求路径错误: {e.message}') + except openai.RateLimitError as e: + raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}') + except openai.APIError as e: + raise errors.RequesterError(f'请求错误: {e.message}') diff --git a/pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml b/pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml index a641a672..a926d889 100644 --- a/pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml @@ -29,6 +29,8 @@ spec: type: int required: true default: 120 + support_type: + - llm execution: python: path: ./modelscopechatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/moonshotchatcmpl.py b/pkg/provider/modelmgr/requesters/moonshotchatcmpl.py index 1f67fb1e..aa3d0f4f 100644 --- a/pkg/provider/modelmgr/requesters/moonshotchatcmpl.py +++ b/pkg/provider/modelmgr/requesters/moonshotchatcmpl.py @@ -25,6 +25,7 @@ class MoonshotChatCompletions(chatcmpl.OpenAIChatCompletions): use_model: requester.RuntimeLLMModel, use_funcs: list[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: self.client.api_key = use_model.token_mgr.get_token() @@ -54,6 +55,6 @@ class MoonshotChatCompletions(chatcmpl.OpenAIChatCompletions): resp = await self._req(args, extra_body=extra_args) # 处理请求结果 - message = await self._make_msg(resp) + message = await self._make_msg(resp, remove_think) return message diff --git a/pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml b/pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml index f3ae73c8..e51fdfa5 100644 --- a/pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml @@ -14,7 +14,7 @@ spec: zh_Hans: 基础 URL type: string required: true - default: "https://api.moonshot.com/v1" + default: "https://api.moonshot.ai/v1" - name: timeout label: en_US: Timeout @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./moonshotchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/newapi.png b/pkg/provider/modelmgr/requesters/newapi.png new file mode 100644 index 00000000..851556f6 Binary files /dev/null and b/pkg/provider/modelmgr/requesters/newapi.png differ diff --git a/pkg/provider/modelmgr/requesters/newapichatcmpl.py b/pkg/provider/modelmgr/requesters/newapichatcmpl.py new file mode 100644 index 00000000..3c2bd3fb --- /dev/null +++ b/pkg/provider/modelmgr/requesters/newapichatcmpl.py @@ -0,0 +1,17 @@ +from __future__ import annotations + +import typing +import openai + +from . import chatcmpl + + +class NewAPIChatCompletions(chatcmpl.OpenAIChatCompletions): + """New API ChatCompletion API 请求器""" + + client: openai.AsyncClient + + default_config: dict[str, typing.Any] = { + 'base_url': 'http://localhost:3000/v1', + 'timeout': 120, + } diff --git a/pkg/provider/modelmgr/requesters/newapichatcmpl.yaml b/pkg/provider/modelmgr/requesters/newapichatcmpl.yaml new file mode 100644 index 00000000..33573df5 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/newapichatcmpl.yaml @@ -0,0 +1,31 @@ +apiVersion: v1 +kind: LLMAPIRequester +metadata: + name: new-api-chat-completions + label: + en_US: New API + zh_Hans: New API + icon: newapi.png +spec: + config: + - name: base_url + label: + en_US: Base URL + zh_Hans: 基础 URL + type: string + required: true + default: "http://localhost:3000/v1" + - name: timeout + label: + en_US: Timeout + zh_Hans: 超时时间 + type: integer + required: true + default: 120 + support_type: + - llm + - text-embedding +execution: + python: + path: ./newapichatcmpl.py + attr: NewAPIChatCompletions \ No newline at end of file diff --git a/pkg/provider/modelmgr/requesters/ollamachat.py b/pkg/provider/modelmgr/requesters/ollamachat.py index 20ba3ebf..97361f89 100644 --- a/pkg/provider/modelmgr/requesters/ollamachat.py +++ b/pkg/provider/modelmgr/requesters/ollamachat.py @@ -17,7 +17,7 @@ import langbot_plugin.api.entities.builtin.provider.message as provider_message REQUESTER_NAME: str = 'ollama-chat' -class OllamaChatCompletions(requester.LLMAPIRequester): +class OllamaChatCompletions(requester.ProviderAPIRequester): """Ollama平台 ChatCompletion API请求器""" client: ollama.AsyncClient @@ -44,6 +44,7 @@ class OllamaChatCompletions(requester.LLMAPIRequester): use_model: requester.RuntimeLLMModel, use_funcs: list[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: args = extra_args.copy() args['model'] = use_model.model_entity.name @@ -110,6 +111,7 @@ class OllamaChatCompletions(requester.LLMAPIRequester): messages: typing.List[provider_message.Message], funcs: typing.List[resource_tool.LLMTool] = None, extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, ) -> provider_message.Message: req_messages: list = [] for m in messages: @@ -126,6 +128,21 @@ class OllamaChatCompletions(requester.LLMAPIRequester): use_model=model, use_funcs=funcs, extra_args=extra_args, + remove_think=remove_think, ) except asyncio.TimeoutError: raise errors.RequesterError('请求超时') + + async def invoke_embedding( + self, + model: requester.RuntimeEmbeddingModel, + input_text: list[str], + extra_args: dict[str, typing.Any] = {}, + ) -> list[list[float]]: + return ( + await self.client.embed( + model=model.model_entity.name, + input=input_text, + **extra_args, + ) + ).embeddings diff --git a/pkg/provider/modelmgr/requesters/ollamachat.yaml b/pkg/provider/modelmgr/requesters/ollamachat.yaml index 01435775..f7cdeeba 100644 --- a/pkg/provider/modelmgr/requesters/ollamachat.yaml +++ b/pkg/provider/modelmgr/requesters/ollamachat.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./ollamachat.py diff --git a/pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml b/pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml index 2ecee6cc..8c957dba 100644 --- a/pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./openrouterchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/ppiochatcmpl.py b/pkg/provider/modelmgr/requesters/ppiochatcmpl.py index 7e78ddb8..9658312b 100644 --- a/pkg/provider/modelmgr/requesters/ppiochatcmpl.py +++ b/pkg/provider/modelmgr/requesters/ppiochatcmpl.py @@ -4,6 +4,12 @@ import openai import typing from . import chatcmpl +from .. import requester +import openai.types.chat.chat_completion as chat_completion +import re +import langbot_plugin.api.entities.builtin.provider.message as provider_message +import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query +import langbot_plugin.api.entities.builtin.resource.tool as resource_tool class PPIOChatCompletions(chatcmpl.OpenAIChatCompletions): @@ -15,3 +21,188 @@ class PPIOChatCompletions(chatcmpl.OpenAIChatCompletions): 'base_url': 'https://api.ppinfra.com/v3/openai', 'timeout': 120, } + + is_think: bool = False + + async def _make_msg( + self, + chat_completion: chat_completion.ChatCompletion, + remove_think: bool, + ) -> provider_message.Message: + chatcmpl_message = chat_completion.choices[0].message.model_dump() + # print(chatcmpl_message.keys(), chatcmpl_message.values()) + + # 确保 role 字段存在且不为 None + if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None: + chatcmpl_message['role'] = 'assistant' + + reasoning_content = chatcmpl_message['reasoning_content'] if 'reasoning_content' in chatcmpl_message else None + + # deepseek的reasoner模型 + chatcmpl_message['content'] = await self._process_thinking_content( + chatcmpl_message['content'], reasoning_content, remove_think + ) + + # 移除 reasoning_content 字段，避免传递给 Message + if 'reasoning_content' in chatcmpl_message: + del chatcmpl_message['reasoning_content'] + + message = provider_message.Message(**chatcmpl_message) + + return message + + async def _process_thinking_content( + self, + content: str, + reasoning_content: str = None, + remove_think: bool = False, + ) -> tuple[str, str]: + """处理思维链内容 + + Args: + content: 原始内容 + reasoning_content: reasoning_content 字段内容 + remove_think: 是否移除思维链 + + Returns: + 处理后的内容 + """ + if remove_think: + content = re.sub(r'.*?', '', content, flags=re.DOTALL) + else: + if reasoning_content is not None: + content = '\n' + reasoning_content + '\n\n' + content + return content + + async def _make_msg_chunk( + self, + delta: dict[str, typing.Any], + idx: int, + ) -> provider_message.MessageChunk: + # 处理流式chunk和完整响应的差异 + # print(chat_completion.choices[0]) + + # 确保 role 字段存在且不为 None + if 'role' not in delta or delta['role'] is None: + delta['role'] = 'assistant' + + reasoning_content = delta['reasoning_content'] if 'reasoning_content' in delta else None + + delta['content'] = '' if delta['content'] is None else delta['content'] + # print(reasoning_content) + + # deepseek的reasoner模型 + + if reasoning_content is not None: + delta['content'] += reasoning_content + + message = provider_message.MessageChunk(**delta) + + return message + + async def _closure_stream( + self, + query: pipeline_query.Query, + req_messages: list[dict], + use_model: requester.RuntimeLLMModel, + use_funcs: list[resource_tool.LLMTool] = None, + extra_args: dict[str, typing.Any] = {}, + remove_think: bool = False, + ) -> provider_message.Message | typing.AsyncGenerator[provider_message.MessageChunk, None]: + self.client.api_key = use_model.token_mgr.get_token() + + args = {} + args['model'] = use_model.model_entity.name + + if use_funcs: + tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs) + + if tools: + args['tools'] = tools + + # 设置此次请求中的messages + messages = req_messages.copy() + + # 检查vision + for msg in messages: + if 'content' in msg and isinstance(msg['content'], list): + for me in msg['content']: + if me['type'] == 'image_base64': + me['image_url'] = {'url': me['image_base64']} + me['type'] = 'image_url' + del me['image_base64'] + + args['messages'] = messages + args['stream'] = True + + # tool_calls_map: dict[str, provider_message.ToolCall] = {} + chunk_idx = 0 + thinking_started = False + thinking_ended = False + role = 'assistant' # 默认角色 + async for chunk in self._req_stream(args, extra_body=extra_args): + # 解析 chunk 数据 + if hasattr(chunk, 'choices') and chunk.choices: + choice = chunk.choices[0] + delta = choice.delta.model_dump() if hasattr(choice, 'delta') else {} + finish_reason = getattr(choice, 'finish_reason', None) + else: + delta = {} + finish_reason = None + + # 从第一个 chunk 获取 role，后续使用这个 role + if 'role' in delta and delta['role']: + role = delta['role'] + + # 获取增量内容 + delta_content = delta.get('content', '') + # reasoning_content = delta.get('reasoning_content', '') + + if remove_think: + if delta['content'] is not None: + if '' in delta['content'] and not thinking_started and not thinking_ended: + thinking_started = True + continue + elif delta['content'] == r'' and not thinking_ended: + thinking_ended = True + continue + elif thinking_ended and delta['content'] == '\n\n' and thinking_started: + thinking_started = False + continue + elif thinking_started and not thinking_ended: + continue + + # delta_tool_calls = None + if delta.get('tool_calls'): + for tool_call in delta['tool_calls']: + if tool_call['id'] and tool_call['function']['name']: + tool_id = tool_call['id'] + tool_name = tool_call['function']['name'] + + if tool_call['id'] is None: + tool_call['id'] = tool_id + if tool_call['function']['name'] is None: + tool_call['function']['name'] = tool_name + if tool_call['function']['arguments'] is None: + tool_call['function']['arguments'] = '' + if tool_call['type'] is None: + tool_call['type'] = 'function' + + # 跳过空的第一个 chunk（只有 role 没有内容） + if chunk_idx == 0 and not delta_content and not delta.get('tool_calls'): + chunk_idx += 1 + continue + + # 构建 MessageChunk - 只包含增量内容 + chunk_data = { + 'role': role, + 'content': delta_content if delta_content else None, + 'tool_calls': delta.get('tool_calls'), + 'is_final': bool(finish_reason), + } + + # 移除 None 值 + chunk_data = {k: v for k, v in chunk_data.items() if v is not None} + + yield provider_message.MessageChunk(**chunk_data) + chunk_idx += 1 diff --git a/pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml b/pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml index 9f201aa9..90a81614 100644 --- a/pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml @@ -29,6 +29,9 @@ spec: type: int required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./ppiochatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/qhaigc.png b/pkg/provider/modelmgr/requesters/qhaigc.png new file mode 100644 index 00000000..53400713 Binary files /dev/null and b/pkg/provider/modelmgr/requesters/qhaigc.png differ diff --git a/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.py b/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.py new file mode 100644 index 00000000..a68b6896 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.py @@ -0,0 +1,17 @@ +from __future__ import annotations + +import openai +import typing + +from . import chatcmpl + + +class QHAIGCChatCompletions(chatcmpl.OpenAIChatCompletions): + """启航 AI ChatCompletion API 请求器""" + + client: openai.AsyncClient + + default_config: dict[str, typing.Any] = { + 'base_url': 'https://api.qhaigc.com/v1', + 'timeout': 120, + } diff --git a/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.yaml b/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.yaml new file mode 100644 index 00000000..2cd777d0 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/qhaigcchatcmpl.yaml @@ -0,0 +1,38 @@ +apiVersion: v1 +kind: LLMAPIRequester +metadata: + name: qhaigc-chat-completions + label: + en_US: QH AI + zh_Hans: 启航 AI + icon: qhaigc.png +spec: + config: + - name: base_url + label: + en_US: Base URL + zh_Hans: 基础 URL + type: string + required: true + default: "https://api.qhaigc.net/v1" + - name: args + label: + en_US: Args + zh_Hans: 附加参数 + type: object + required: true + default: {} + - name: timeout + label: + en_US: Timeout + zh_Hans: 超时时间 + type: int + required: true + default: 120 + support_type: + - llm + - text-embedding +execution: + python: + path: ./qhaigcchatcmpl.py + attr: QHAIGCChatCompletions \ No newline at end of file diff --git a/pkg/provider/modelmgr/requesters/shengsuanyun.py b/pkg/provider/modelmgr/requesters/shengsuanyun.py new file mode 100644 index 00000000..122eaf7d --- /dev/null +++ b/pkg/provider/modelmgr/requesters/shengsuanyun.py @@ -0,0 +1,32 @@ +from __future__ import annotations + +import openai +import typing + +from . import chatcmpl +import openai.types.chat.chat_completion as chat_completion + + +class ShengSuanYunChatCompletions(chatcmpl.OpenAIChatCompletions): + """胜算云(ModelSpot.AI) ChatCompletion API 请求器""" + + client: openai.AsyncClient + + default_config: dict[str, typing.Any] = { + 'base_url': 'https://router.shengsuanyun.com/api/v1', + 'timeout': 120, + } + + async def _req( + self, + args: dict, + extra_body: dict = {}, + ) -> chat_completion.ChatCompletion: + return await self.client.chat.completions.create( + **args, + extra_body=extra_body, + extra_headers={ + 'HTTP-Referer': 'https://langbot.app', + 'X-Title': 'LangBot', + }, + ) diff --git a/pkg/provider/modelmgr/requesters/shengsuanyun.svg b/pkg/provider/modelmgr/requesters/shengsuanyun.svg new file mode 100644 index 00000000..d3f672aa --- /dev/null +++ b/pkg/provider/modelmgr/requesters/shengsuanyun.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/pkg/provider/modelmgr/requesters/shengsuanyun.yaml b/pkg/provider/modelmgr/requesters/shengsuanyun.yaml new file mode 100644 index 00000000..6668b677 --- /dev/null +++ b/pkg/provider/modelmgr/requesters/shengsuanyun.yaml @@ -0,0 +1,38 @@ +apiVersion: v1 +kind: LLMAPIRequester +metadata: + name: shengsuanyun-chat-completions + label: + en_US: ShengSuanYun + zh_Hans: 胜算云 + icon: shengsuanyun.svg +spec: + config: + - name: base_url + label: + en_US: Base URL + zh_Hans: 基础 URL + type: string + required: true + default: "https://router.shengsuanyun.com/api/v1" + - name: args + label: + en_US: Args + zh_Hans: 附加参数 + type: object + required: true + default: {} + - name: timeout + label: + en_US: Timeout + zh_Hans: 超时时间 + type: int + required: true + default: 120 + support_type: + - llm + - text-embedding +execution: + python: + path: ./shengsuanyun.py + attr: ShengSuanYunChatCompletions \ No newline at end of file diff --git a/pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml b/pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml index 19b3dcc3..25a20653 100644 --- a/pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml @@ -22,6 +22,9 @@ spec: type: integer required: true default: 120 + support_type: + - llm + - text-embedding execution: python: path: ./siliconflowchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml b/pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml index 402f04e7..c711ef2d 100644 --- a/pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./volcarkchatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/xaichatcmpl.yaml b/pkg/provider/modelmgr/requesters/xaichatcmpl.yaml index 29db4eb3..2769a402 100644 --- a/pkg/provider/modelmgr/requesters/xaichatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/xaichatcmpl.yaml @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./xaichatcmpl.py diff --git a/pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml b/pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml index a05184ef..34539d95 100644 --- a/pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml +++ b/pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml @@ -22,6 +22,8 @@ spec: type: integer required: true default: 120 + support_type: + - llm execution: python: path: ./zhipuaichatcmpl.py diff --git a/pkg/provider/runners/dashscopeapi.py b/pkg/provider/runners/dashscopeapi.py index 98d504e2..d9cf25a5 100644 --- a/pkg/provider/runners/dashscopeapi.py +++ b/pkg/provider/runners/dashscopeapi.py @@ -102,8 +102,14 @@ class DashScopeAPIRunner(runner.RequestRunner): plain_text = '' # 用户输入的纯文本信息 image_ids = [] # 用户输入的图片ID列表 （暂不支持） - plain_text, image_ids = await self._preprocess_user_message(query) + think_start = False + think_end = False + plain_text, image_ids = await self._preprocess_user_message(query) + has_thoughts = True # 获取思考过程 + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + if remove_think: + has_thoughts = False # 发送对话请求 response = dashscope.Application.call( api_key=self.api_key, # 智能体应用的API Key @@ -112,43 +118,108 @@ class DashScopeAPIRunner(runner.RequestRunner): stream=True, # 流式输出 incremental_output=True, # 增量输出，使用流式输出需要开启增量输出 session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话 + has_thoughts=has_thoughts, # rag_options={ # 主要用于文件交互，暂不支持 # "session_file_ids": ["FILE_ID1"], # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个 # } ) + idx_chunk = 0 + try: + is_stream = await query.adapter.is_stream_output_supported() - for chunk in response: - if chunk.get('status_code') != 200: - raise DashscopeAPIError( - f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' - ) - if not chunk: - continue + except AttributeError: + is_stream = False + if is_stream: + for chunk in response: + if chunk.get('status_code') != 200: + raise DashscopeAPIError( + f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' + ) + if not chunk: + continue + idx_chunk += 1 + # 获取流式传输的output + stream_output = chunk.get('output', {}) + stream_think = stream_output.get('thoughts', []) + if stream_think[0].get('thought'): + if not think_start: + think_start = True + pending_content += f'\n{stream_think[0].get("thought")}' + else: + # 继续输出 reasoning_content + pending_content += stream_think[0].get('thought') + elif stream_think[0].get('thought') == '' and not think_end: + think_end = True + pending_content += '\n\n' + if stream_output.get('text') is not None: + pending_content += stream_output.get('text') + # 是否是流式最后一个chunk + is_final = False if stream_output.get('finish_reason', False) == 'null' else True - # 获取流式传输的output - stream_output = chunk.get('output', {}) - if stream_output.get('text') is not None: - pending_content += stream_output.get('text') + # 获取模型传出的参考资料列表 + references_dict_list = stream_output.get('doc_references', []) - # 保存当前会话的session_id用于下次对话的语境 - query.session.using_conversation.uuid = stream_output.get('session_id') + # 从模型传出的参考资料信息中提取用于替换的字典 + if references_dict_list is not None: + for doc in references_dict_list: + if doc.get('index_id') is not None: + references_dict[doc.get('index_id')] = doc.get('doc_name') - # 获取模型传出的参考资料列表 - references_dict_list = stream_output.get('doc_references', []) + # 将参考资料替换到文本中 + pending_content = self._replace_references(pending_content, references_dict) - # 从模型传出的参考资料信息中提取用于替换的字典 - if references_dict_list is not None: - for doc in references_dict_list: - if doc.get('index_id') is not None: - references_dict[doc.get('index_id')] = doc.get('doc_name') + if idx_chunk % 8 == 0 or is_final: + yield provider_message.MessageChunk( + role='assistant', + content=pending_content, + is_final=is_final, + ) + # 保存当前会话的session_id用于下次对话的语境 + query.session.using_conversation.uuid = stream_output.get('session_id') + else: + for chunk in response: + if chunk.get('status_code') != 200: + raise DashscopeAPIError( + f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' + ) + if not chunk: + continue + idx_chunk += 1 + # 获取流式传输的output + stream_output = chunk.get('output', {}) + stream_think = stream_output.get('thoughts', []) + if stream_think[0].get('thought'): + if not think_start: + think_start = True + pending_content += f'\n{stream_think[0].get("thought")}' + else: + # 继续输出 reasoning_content + pending_content += stream_think[0].get('thought') + elif stream_think[0].get('thought') == '' and not think_end: + think_end = True + pending_content += '\n\n' + if stream_output.get('text') is not None: + pending_content += stream_output.get('text') - # 将参考资料替换到文本中 - pending_content = self._replace_references(pending_content, references_dict) + # 保存当前会话的session_id用于下次对话的语境 + query.session.using_conversation.uuid = stream_output.get('session_id') - yield provider_message.Message( - role='assistant', - content=pending_content, - ) + # 获取模型传出的参考资料列表 + references_dict_list = stream_output.get('doc_references', []) + + # 从模型传出的参考资料信息中提取用于替换的字典 + if references_dict_list is not None: + for doc in references_dict_list: + if doc.get('index_id') is not None: + references_dict[doc.get('index_id')] = doc.get('doc_name') + + # 将参考资料替换到文本中 + pending_content = self._replace_references(pending_content, references_dict) + + yield provider_message.Message( + role='assistant', + content=pending_content, + ) async def _workflow_messages( self, query: pipeline_query.Query @@ -176,52 +247,108 @@ class DashScopeAPIRunner(runner.RequestRunner): incremental_output=True, # 增量输出，使用流式输出需要开启增量输出 session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话 biz_params=biz_params, # 工作流应用的自定义输入参数传递 + flow_stream_mode='message_format', # 消息模式，输出/结束节点的流式结果 # rag_options={ # 主要用于文件交互，暂不支持 # "session_file_ids": ["FILE_ID1"], # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个 # } ) # 处理API返回的流式输出 - for chunk in response: - if chunk.get('status_code') != 200: - raise DashscopeAPIError( - f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' - ) - if not chunk: - continue + try: + is_stream = await query.adapter.is_stream_output_supported() - # 获取流式传输的output - stream_output = chunk.get('output', {}) - if stream_output.get('text') is not None: - pending_content += stream_output.get('text') + except AttributeError: + is_stream = False + idx_chunk = 0 + if is_stream: + for chunk in response: + if chunk.get('status_code') != 200: + raise DashscopeAPIError( + f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' + ) + if not chunk: + continue + idx_chunk += 1 + # 获取流式传输的output + stream_output = chunk.get('output', {}) + if stream_output.get('workflow_message') is not None: + pending_content += stream_output.get('workflow_message').get('message').get('content') + # if stream_output.get('text') is not None: + # pending_content += stream_output.get('text') - # 保存当前会话的session_id用于下次对话的语境 - query.session.using_conversation.uuid = stream_output.get('session_id') + is_final = False if stream_output.get('finish_reason', False) == 'null' else True - # 获取模型传出的参考资料列表 - references_dict_list = stream_output.get('doc_references', []) + # 获取模型传出的参考资料列表 + references_dict_list = stream_output.get('doc_references', []) - # 从模型传出的参考资料信息中提取用于替换的字典 - if references_dict_list is not None: - for doc in references_dict_list: - if doc.get('index_id') is not None: - references_dict[doc.get('index_id')] = doc.get('doc_name') + # 从模型传出的参考资料信息中提取用于替换的字典 + if references_dict_list is not None: + for doc in references_dict_list: + if doc.get('index_id') is not None: + references_dict[doc.get('index_id')] = doc.get('doc_name') - # 将参考资料替换到文本中 - pending_content = self._replace_references(pending_content, references_dict) + # 将参考资料替换到文本中 + pending_content = self._replace_references(pending_content, references_dict) + if idx_chunk % 8 == 0 or is_final: + yield provider_message.MessageChunk( + role='assistant', + content=pending_content, + is_final=is_final, + ) - yield provider_message.Message( - role='assistant', - content=pending_content, - ) + # 保存当前会话的session_id用于下次对话的语境 + query.session.using_conversation.uuid = stream_output.get('session_id') + + else: + for chunk in response: + if chunk.get('status_code') != 200: + raise DashscopeAPIError( + f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} ' + ) + if not chunk: + continue + + # 获取流式传输的output + stream_output = chunk.get('output', {}) + if stream_output.get('text') is not None: + pending_content += stream_output.get('text') + + is_final = False if stream_output.get('finish_reason', False) == 'null' else True + + # 保存当前会话的session_id用于下次对话的语境 + query.session.using_conversation.uuid = stream_output.get('session_id') + + # 获取模型传出的参考资料列表 + references_dict_list = stream_output.get('doc_references', []) + + # 从模型传出的参考资料信息中提取用于替换的字典 + if references_dict_list is not None: + for doc in references_dict_list: + if doc.get('index_id') is not None: + references_dict[doc.get('index_id')] = doc.get('doc_name') + + # 将参考资料替换到文本中 + pending_content = self._replace_references(pending_content, references_dict) + + yield provider_message.Message( + role='assistant', + content=pending_content, + ) async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]: """运行""" + msg_seq = 0 if self.app_type == 'agent': async for msg in self._agent_messages(query): + if isinstance(msg, provider_message.MessageChunk): + msg_seq += 1 + msg.msg_sequence = msg_seq yield msg elif self.app_type == 'workflow': async for msg in self._workflow_messages(query): + if isinstance(msg, provider_message.MessageChunk): + msg_seq += 1 + msg.msg_sequence = msg_seq yield msg else: raise DashscopeAPIError(f'不支持的 Dashscope 应用类型: {self.app_type}') diff --git a/pkg/provider/runners/difysvapi.py b/pkg/provider/runners/difysvapi.py index 779f2ef6..b98a9bc3 100644 --- a/pkg/provider/runners/difysvapi.py +++ b/pkg/provider/runners/difysvapi.py @@ -3,7 +3,6 @@ from __future__ import annotations import typing import json import uuid -import re import base64 @@ -38,29 +37,38 @@ class DifyServiceAPIRunner(runner.RequestRunner): base_url=self.pipeline_config['ai']['dify-service-api']['base-url'], ) - def _try_convert_thinking(self, resp_text: str) -> str: - """尝试转换 Dify 的思考提示""" - if not resp_text.startswith( - '
Thinking... ' - ): - return resp_text + def _process_thinking_content( + self, + content: str, + ) -> tuple[str, str]: + """处理思维链内容 - if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'original': - return resp_text + Args: + content: 原始内容 + Returns: + (处理后的内容, 提取的思维链内容) + """ + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + thinking_content = '' + # 从 content 中提取 标签内容 + if content and '' in content and '' in content: + import re - if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'remove': - return re.sub( - r'
Thinking... .*?
', - '', - resp_text, - flags=re.DOTALL, - ) + think_pattern = r'(.*?)' + think_matches = re.findall(think_pattern, content, re.DOTALL) + if think_matches: + thinking_content = '\n'.join(think_matches) + # 移除 content 中的 标签 + content = re.sub(think_pattern, '', content, flags=re.DOTALL).strip() - if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'plain': - pattern = r'
Thinking... (.*?)
' - thinking_text = re.search(pattern, resp_text, flags=re.DOTALL) - content_text = re.sub(pattern, '', resp_text, flags=re.DOTALL) - return f'{thinking_text.group(1)}\n{content_text}' + # 3. 根据 remove_think 参数决定是否保留思维链 + if remove_think: + return content, '' + else: + # 如果有思维链内容，将其以 格式添加到 content 开头 + if thinking_content: + content = f'\n{thinking_content}\n\n{content}'.strip() + return content, thinking_content async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[str]]: """预处理用户消息，提取纯文本，并将图片上传到 Dify 服务 @@ -134,17 +142,20 @@ class DifyServiceAPIRunner(runner.RequestRunner): if mode == 'workflow': if chunk['event'] == 'node_finished': if chunk['data']['node_type'] == 'answer': + content, _ = self._process_thinking_content(chunk['data']['outputs']['answer']) + yield provider_message.Message( role='assistant', - content=self._try_convert_thinking(chunk['data']['outputs']['answer']), + content=content, ) elif mode == 'basic': if chunk['event'] == 'message': basic_mode_pending_chunk += chunk['answer'] elif chunk['event'] == 'message_end': + content, _ = self._process_thinking_content(basic_mode_pending_chunk) yield provider_message.Message( role='assistant', - content=self._try_convert_thinking(basic_mode_pending_chunk), + content=content, ) basic_mode_pending_chunk = '' @@ -195,14 +206,15 @@ class DifyServiceAPIRunner(runner.RequestRunner): if chunk['event'] in ignored_events: continue - if chunk['event'] == 'agent_message': + if chunk['event'] == 'agent_message' or chunk['event'] == 'message': pending_agent_message += chunk['answer'] else: if pending_agent_message.strip() != '': pending_agent_message = pending_agent_message.replace('
Action:', '') + content, _ = self._process_thinking_content(pending_agent_message) yield provider_message.Message( role='assistant', - content=self._try_convert_thinking(pending_agent_message), + content=content, ) pending_agent_message = '' @@ -312,26 +324,352 @@ class DifyServiceAPIRunner(runner.RequestRunner): elif chunk['event'] == 'workflow_finished': if chunk['data']['error']: raise errors.DifyAPIError(chunk['data']['error']) + content, _ = self._process_thinking_content(chunk['data']['outputs']['summary']) msg = provider_message.Message( role='assistant', - content=chunk['data']['outputs']['summary'], + content=content, ) yield msg + async def _chat_messages_chunk( + self, query: pipeline_query.Query + ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]: + """调用聊天助手""" + cov_id = query.session.using_conversation.uuid or '' + query.variables['conversation_id'] = cov_id + + plain_text, image_ids = await self._preprocess_user_message(query) + + files = [ + { + 'type': 'image', + 'transfer_method': 'local_file', + 'upload_file_id': image_id, + } + for image_id in image_ids + ] + + basic_mode_pending_chunk = '' + + inputs = {} + + inputs.update(query.variables) + message_idx = 0 + + chunk = None # 初始化chunk变量，防止在没有响应时引用错误 + + is_final = False + think_start = False + think_end = False + + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + + async for chunk in self.dify_client.chat_messages( + inputs=inputs, + query=plain_text, + user=f'{query.session.launcher_type.value}_{query.session.launcher_id}', + conversation_id=cov_id, + files=files, + timeout=120, + ): + self.ap.logger.debug('dify-chat-chunk: ' + str(chunk)) + + # if chunk['event'] == 'workflow_started': + # mode = 'workflow' + # if mode == 'workflow': + # elif mode == 'basic': + # 因为都只是返回的 message也没有工具调用什么的，暂时不分类 + if chunk['event'] == 'message': + message_idx += 1 + if remove_think: + if '' in chunk['answer'] and not think_start: + think_start = True + continue + if '' in chunk['answer'] and not think_end: + import re + + content = re.sub(r'^\n', '', chunk['answer']) + basic_mode_pending_chunk += content + think_end = True + elif think_end: + basic_mode_pending_chunk += chunk['answer'] + if think_start: + continue + + else: + basic_mode_pending_chunk += chunk['answer'] + + if chunk['event'] == 'message_end': + is_final = True + + if is_final or message_idx % 8 == 0: + # content, _ = self._process_thinking_content(basic_mode_pending_chunk) + yield provider_message.MessageChunk( + role='assistant', + content=basic_mode_pending_chunk, + is_final=is_final, + ) + + if chunk is None: + raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置') + + query.session.using_conversation.uuid = chunk['conversation_id'] + + async def _agent_chat_messages_chunk( + self, query: pipeline_query.Query + ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]: + """调用聊天助手""" + cov_id = query.session.using_conversation.uuid or '' + query.variables['conversation_id'] = cov_id + + plain_text, image_ids = await self._preprocess_user_message(query) + + files = [ + { + 'type': 'image', + 'transfer_method': 'local_file', + 'upload_file_id': image_id, + } + for image_id in image_ids + ] + + ignored_events = [] + + inputs = {} + + inputs.update(query.variables) + + pending_agent_message = '' + + chunk = None # 初始化chunk变量，防止在没有响应时引用错误 + message_idx = 0 + is_final = False + think_start = False + think_end = False + + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + + async for chunk in self.dify_client.chat_messages( + inputs=inputs, + query=plain_text, + user=f'{query.session.launcher_type.value}_{query.session.launcher_id}', + response_mode='streaming', + conversation_id=cov_id, + files=files, + timeout=120, + ): + self.ap.logger.debug('dify-agent-chunk: ' + str(chunk)) + + if chunk['event'] in ignored_events: + continue + + if chunk['event'] == 'agent_message': + message_idx += 1 + if remove_think: + if '' in chunk['answer'] and not think_start: + think_start = True + continue + if '' in chunk['answer'] and not think_end: + import re + + content = re.sub(r'^\n', '', chunk['answer']) + pending_agent_message += content + think_end = True + elif think_end or not think_start: + pending_agent_message += chunk['answer'] + if think_start: + continue + + else: + pending_agent_message += chunk['answer'] + elif chunk['event'] == 'message_end': + is_final = True + else: + if chunk['event'] == 'agent_thought': + if chunk['tool'] != '' and chunk['observation'] != '': # 工具调用结果，跳过 + continue + message_idx += 1 + if chunk['tool']: + msg = provider_message.MessageChunk( + role='assistant', + tool_calls=[ + provider_message.ToolCall( + id=chunk['id'], + type='function', + function=provider_message.FunctionCall( + name=chunk['tool'], + arguments=json.dumps({}), + ), + ) + ], + ) + yield msg + if chunk['event'] == 'message_file': + message_idx += 1 + if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant': + base_url = self.dify_client.base_url + + if base_url.endswith('/v1'): + base_url = base_url[:-3] + + image_url = base_url + chunk['url'] + + yield provider_message.MessageChunk( + role='assistant', + content=[provider_message.ContentElement.from_image_url(image_url)], + is_final=is_final, + ) + + if chunk['event'] == 'error': + raise errors.DifyAPIError('dify 服务错误: ' + chunk['message']) + if message_idx % 8 == 0 or is_final: + yield provider_message.MessageChunk( + role='assistant', + content=pending_agent_message, + is_final=is_final, + ) + + if chunk is None: + raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置') + + query.session.using_conversation.uuid = chunk['conversation_id'] + + async def _workflow_messages_chunk( + self, query: pipeline_query.Query + ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]: + """调用工作流""" + + if not query.session.using_conversation.uuid: + query.session.using_conversation.uuid = str(uuid.uuid4()) + + query.variables['conversation_id'] = query.session.using_conversation.uuid + + plain_text, image_ids = await self._preprocess_user_message(query) + + files = [ + { + 'type': 'image', + 'transfer_method': 'local_file', + 'upload_file_id': image_id, + } + for image_id in image_ids + ] + + ignored_events = ['workflow_started'] + + inputs = { # these variables are legacy variables, we need to keep them for compatibility + 'langbot_user_message_text': plain_text, + 'langbot_session_id': query.variables['session_id'], + 'langbot_conversation_id': query.variables['conversation_id'], + 'langbot_msg_create_time': query.variables['msg_create_time'], + } + + inputs.update(query.variables) + messsage_idx = 0 + is_final = False + think_start = False + think_end = False + workflow_contents = '' + + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + async for chunk in self.dify_client.workflow_run( + inputs=inputs, + user=f'{query.session.launcher_type.value}_{query.session.launcher_id}', + files=files, + timeout=120, + ): + self.ap.logger.debug('dify-workflow-chunk: ' + str(chunk)) + if chunk['event'] in ignored_events: + continue + if chunk['event'] == 'workflow_finished': + is_final = True + if chunk['data']['error']: + raise errors.DifyAPIError(chunk['data']['error']) + + if chunk['event'] == 'text_chunk': + messsage_idx += 1 + if remove_think: + if '' in chunk['data']['text'] and not think_start: + think_start = True + continue + if '' in chunk['data']['text'] and not think_end: + import re + + content = re.sub(r'^\n', '', chunk['data']['text']) + workflow_contents += content + think_end = True + elif think_end: + workflow_contents += chunk['data']['text'] + if think_start: + continue + + else: + workflow_contents += chunk['data']['text'] + + if chunk['event'] == 'node_started': + if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end': + continue + messsage_idx += 1 + msg = provider_message.MessageChunk( + role='assistant', + content=None, + tool_calls=[ + provider_message.ToolCall( + id=chunk['data']['node_id'], + type='function', + function=provider_message.FunctionCall( + name=chunk['data']['title'], + arguments=json.dumps({}), + ), + ) + ], + ) + + yield msg + + if messsage_idx % 8 == 0 or is_final: + yield provider_message.MessageChunk( + role='assistant', + content=workflow_contents, + is_final=is_final, + ) + async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]: """运行请求""" - if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat': - async for msg in self._chat_messages(query): - yield msg - elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent': - async for msg in self._agent_chat_messages(query): - yield msg - elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow': - async for msg in self._workflow_messages(query): - yield msg + if await query.adapter.is_stream_output_supported(): + msg_idx = 0 + if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat': + async for msg in self._chat_messages_chunk(query): + msg_idx += 1 + msg.msg_sequence = msg_idx + yield msg + elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent': + async for msg in self._agent_chat_messages_chunk(query): + msg_idx += 1 + msg.msg_sequence = msg_idx + yield msg + elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow': + async for msg in self._workflow_messages_chunk(query): + msg_idx += 1 + msg.msg_sequence = msg_idx + yield msg + else: + raise errors.DifyAPIError( + f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}' + ) else: - raise errors.DifyAPIError( - f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}' - ) + if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat': + async for msg in self._chat_messages(query): + yield msg + elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent': + async for msg in self._agent_chat_messages(query): + yield msg + elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow': + async for msg in self._workflow_messages(query): + yield msg + else: + raise errors.DifyAPIError( + f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}' + ) diff --git a/pkg/provider/runners/localagent.py b/pkg/provider/runners/localagent.py index da88d490..f91a145c 100644 --- a/pkg/provider/runners/localagent.py +++ b/pkg/provider/runners/localagent.py @@ -1,39 +1,179 @@ from __future__ import annotations import json +import copy import typing - from .. import runner import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query import langbot_plugin.api.entities.builtin.provider.message as provider_message +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. + + +{rag_context} + + + +{user_message} + +""" + + @runner.runner_class('local-agent') class LocalAgentRunner(runner.RequestRunner): """本地Agent请求运行器""" - async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]: + class ToolCallTracker: + """工具调用追踪器""" + + def __init__(self): + self.active_calls: dict[str, dict] = {} + self.completed_calls: list[provider_message.ToolCall] = [] + + async def run( + self, query: pipeline_query.Query + ) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]: """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'] - use_llm_model = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid) + if kb_uuid == '__none__': + kb_uuid = None - # 首次请求 - msg = await use_llm_model.requester.invoke_llm( - query, - use_llm_model, - req_messages, - query.use_funcs, - extra_args=use_llm_model.model_entity.extra_args, - ) + user_message = copy.deepcopy(query.user_message) - yield msg + user_message_text = '' - pending_tool_calls = msg.tool_calls + 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 - req_messages.append(msg) + 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, kb.knowledge_base_entity.top_k) + + 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] + + try: + is_stream = await query.adapter.is_stream_output_supported() + except AttributeError: + is_stream = False + + remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think') + + if not is_stream: + # 非流式输出，直接请求 + + msg = await query.use_llm_model.requester.invoke_llm( + query, + query.use_llm_model, + req_messages, + query.use_funcs, + extra_args=query.use_llm_model.model_entity.extra_args, + remove_think=remove_think, + ) + yield msg + final_msg = msg + else: + # 流式输出，需要处理工具调用 + tool_calls_map: dict[str, provider_message.ToolCall] = {} + msg_idx = 0 + accumulated_content = '' # 从开始累积的所有内容 + last_role = 'assistant' + msg_sequence = 1 + async for msg in query.use_llm_model.requester.invoke_llm_stream( + query, + query.use_llm_model, + req_messages, + query.use_funcs, + extra_args=query.use_llm_model.model_entity.extra_args, + remove_think=remove_think, + ): + msg_idx = msg_idx + 1 + + # 记录角色 + if msg.role: + last_role = msg.role + + # 累积内容 + if msg.content: + accumulated_content += msg.content + + # 处理工具调用 + if msg.tool_calls: + for tool_call in msg.tool_calls: + if tool_call.id not in tool_calls_map: + tool_calls_map[tool_call.id] = provider_message.ToolCall( + id=tool_call.id, + type=tool_call.type, + function=provider_message.FunctionCall( + name=tool_call.function.name if tool_call.function else '', arguments='' + ), + ) + if tool_call.function and tool_call.function.arguments: + # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖 + tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments + # continue + # 每8个chunk或最后一个chunk时，输出所有累积的内容 + if msg_idx % 8 == 0 or msg.is_final: + msg_sequence += 1 + yield provider_message.MessageChunk( + role=last_role, + content=accumulated_content, # 输出所有累积内容 + tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None, + is_final=msg.is_final, + msg_sequence=msg_sequence, + ) + + # 创建最终消息用于后续处理 + final_msg = provider_message.MessageChunk( + role=last_role, + content=accumulated_content, + tool_calls=list(tool_calls_map.values()) if tool_calls_map else None, + msg_sequence=msg_sequence, + ) + + pending_tool_calls = final_msg.tool_calls + first_content = final_msg.content + if isinstance(final_msg, provider_message.MessageChunk): + first_end_sequence = final_msg.msg_sequence + + req_messages.append(final_msg) # 持续请求，只要还有待处理的工具调用就继续处理调用 while pending_tool_calls: @@ -43,13 +183,19 @@ class LocalAgentRunner(runner.RequestRunner): parameters = json.loads(func.arguments) - func_ret = await self.ap.tool_mgr.execute_func_call(func.name, parameters) - - msg = provider_message.Message( - role='tool', - content=json.dumps(func_ret, ensure_ascii=False), - tool_call_id=tool_call.id, - ) + func_ret = await self.ap.tool_mgr.execute_func_call(query, func.name, parameters) + if is_stream: + msg = provider_message.MessageChunk( + role='tool', + content=json.dumps(func_ret, ensure_ascii=False), + tool_call_id=tool_call.id, + ) + else: + msg = provider_message.Message( + role='tool', + content=json.dumps(func_ret, ensure_ascii=False), + tool_call_id=tool_call.id, + ) yield msg @@ -62,17 +208,81 @@ class LocalAgentRunner(runner.RequestRunner): req_messages.append(err_msg) - # 处理完所有调用，再次请求 - msg = await use_llm_model.requester.invoke_llm( - query, - use_llm_model, - req_messages, - query.use_funcs, - extra_args=use_llm_model.model_entity.extra_args, - ) + if is_stream: + tool_calls_map = {} + msg_idx = 0 + accumulated_content = '' # 从开始累积的所有内容 + last_role = 'assistant' + msg_sequence = first_end_sequence - yield msg + async for msg in query.use_llm_model.requester.invoke_llm_stream( + query, + query.use_llm_model, + req_messages, + query.use_funcs, + extra_args=query.use_llm_model.model_entity.extra_args, + remove_think=remove_think, + ): + msg_idx += 1 - pending_tool_calls = msg.tool_calls + # 记录角色 + if msg.role: + last_role = msg.role - req_messages.append(msg) + # 第一次请求工具调用时的内容 + if msg_idx == 1: + accumulated_content = first_content if first_content is not None else accumulated_content + + # 累积内容 + if msg.content: + accumulated_content += msg.content + + # 处理工具调用 + if msg.tool_calls: + for tool_call in msg.tool_calls: + if tool_call.id not in tool_calls_map: + tool_calls_map[tool_call.id] = provider_message.ToolCall( + id=tool_call.id, + type=tool_call.type, + function=provider_message.FunctionCall( + name=tool_call.function.name if tool_call.function else '', arguments='' + ), + ) + if tool_call.function and tool_call.function.arguments: + # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖 + tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments + + # 每8个chunk或最后一个chunk时，输出所有累积的内容 + if msg_idx % 8 == 0 or msg.is_final: + msg_sequence += 1 + yield provider_message.MessageChunk( + role=last_role, + content=accumulated_content, # 输出所有累积内容 + tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None, + is_final=msg.is_final, + msg_sequence=msg_sequence, + ) + + final_msg = provider_message.MessageChunk( + role=last_role, + content=accumulated_content, + tool_calls=list(tool_calls_map.values()) if tool_calls_map else None, + msg_sequence=msg_sequence, + ) + else: + # 处理完所有调用，再次请求 + msg = await query.use_llm_model.requester.invoke_llm( + query, + query.use_llm_model, + req_messages, + query.use_funcs, + extra_args=query.use_llm_model.model_entity.extra_args, + remove_think=remove_think, + ) + + yield msg + final_msg = msg + + pending_tool_calls = final_msg.tool_calls + + req_messages.append(final_msg) diff --git a/pkg/rag/knowledge/kbmgr.py b/pkg/rag/knowledge/kbmgr.py new file mode 100644 index 00000000..ed242696 --- /dev/null +++ b/pkg/rag/knowledge/kbmgr.py @@ -0,0 +1,276 @@ +from __future__ import annotations +import traceback +import uuid +import zipfile +import io +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 + finally: + # delete file from storage + await self.ap.storage_mgr.storage_provider.delete(file.file_name) + + 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_name = file_id + extension = file_name.split('.')[-1].lower() + + if extension == 'zip': + return await self._store_zip_file(file_id) + + file_uuid = str(uuid.uuid4()) + kb_id = self.knowledge_base_entity.uuid + + 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 _store_zip_file(self, zip_file_id: str) -> str: + """Handle ZIP file by extracting each document and storing them separately.""" + self.ap.logger.info(f'Processing ZIP file: {zip_file_id}') + + zip_bytes = await self.ap.storage_mgr.storage_provider.load(zip_file_id) + + supported_extensions = {'txt', 'pdf', 'docx', 'md', 'html'} + stored_file_tasks = [] + + # use utf-8 encoding + with zipfile.ZipFile(io.BytesIO(zip_bytes), 'r', metadata_encoding='utf-8') as zip_ref: + for file_info in zip_ref.filelist: + # skip directories and hidden files + if file_info.is_dir() or file_info.filename.startswith('.'): + continue + + file_extension = file_info.filename.split('.')[-1].lower() + if file_extension not in supported_extensions: + self.ap.logger.debug(f'Skipping unsupported file in ZIP: {file_info.filename}') + continue + + try: + file_content = zip_ref.read(file_info.filename) + + base_name = file_info.filename.replace('/', '_').replace('\\', '_') + extension = base_name.split('.')[-1] + file_name = base_name.split('.')[0] + + if file_name.startswith('__MACOSX'): + continue + + extracted_file_id = file_name + '_' + str(uuid.uuid4())[:8] + '.' + extension + # save file to storage + + await self.ap.storage_mgr.storage_provider.save(extracted_file_id, file_content) + + task_id = await self.store_file(extracted_file_id) + stored_file_tasks.append(task_id) + + self.ap.logger.info( + f'Extracted and stored file from ZIP: {file_info.filename} -> {extracted_file_id}' + ) + + except Exception as e: + self.ap.logger.warning(f'Failed to extract file {file_info.filename} from ZIP: {e}') + continue + + if not stored_file_tasks: + raise Exception('No supported files found in ZIP archive') + + self.ap.logger.info(f'Successfully processed ZIP file {zip_file_id}, extracted {len(stored_file_tasks)} files') + await self.ap.storage_mgr.storage_provider.delete(zip_file_id) + + return stored_file_tasks[0] if stored_file_tasks else '' + + async def retrieve(self, query: str, top_k: int) -> 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, top_k) + + 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 diff --git a/pkg/rag/knowledge/services/__init__.py b/pkg/rag/knowledge/services/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pkg/rag/knowledge/services/base_service.py b/pkg/rag/knowledge/services/base_service.py new file mode 100644 index 00000000..0f71a508 --- /dev/null +++ b/pkg/rag/knowledge/services/base_service.py @@ -0,0 +1,15 @@ +# 封装异步操作 +import asyncio + + +class BaseService: + def __init__(self): + pass + + 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。 + """ + + return await asyncio.to_thread(func, *args, **kwargs) diff --git a/pkg/rag/knowledge/services/chunker.py b/pkg/rag/knowledge/services/chunker.py new file mode 100644 index 00000000..f169d5f1 --- /dev/null +++ b/pkg/rag/knowledge/services/chunker.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +import json +from typing import List +from pkg.rag.knowledge.services import base_service +from pkg.core import app + + +class Chunker(base_service.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): + self.ap = ap + self.chunk_size = chunk_size + self.chunk_overlap = chunk_overlap + if self.chunk_overlap >= self.chunk_size: + self.ap.logger.warning( + 'Chunk overlap is greater than or equal to chunk size. This may lead to empty or malformed chunks.' + ) + + def _split_text_sync(self, text: str) -> List[str]: + """ + Synchronously splits a long text into chunks with specified overlap. + This is a CPU-bound operation, intended to be run in a separate thread. + """ + if not text: + return [] + # words = text.split() + # chunks = [] + # current_chunk = [] + + # for word in words: + # current_chunk.append(word) + # if len(current_chunk) > self.chunk_size: + # chunks.append(" ".join(current_chunk[:self.chunk_size])) + # current_chunk = current_chunk[self.chunk_size - self.chunk_overlap:] + + # if current_chunk: + # chunks.append(" ".join(current_chunk)) + + # A more robust chunking strategy (e.g., using recursive character text splitter) + from langchain.text_splitter import RecursiveCharacterTextSplitter + + text_splitter = RecursiveCharacterTextSplitter( + chunk_size=self.chunk_size, + chunk_overlap=self.chunk_overlap, + length_function=len, + is_separator_regex=False, + ) + return text_splitter.split_text(text) + + async def chunk(self, text: str) -> List[str]: + """ + Asynchronously chunks a given text into smaller pieces. + """ + self.ap.logger.info(f'Chunking text (length: {len(text)})...') + # 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 diff --git a/pkg/rag/knowledge/services/embedder.py b/pkg/rag/knowledge/services/embedder.py new file mode 100644 index 00000000..a0ae3d49 --- /dev/null +++ b/pkg/rag/knowledge/services/embedder.py @@ -0,0 +1,47 @@ +from __future__ import annotations +import uuid +from typing import List +from pkg.rag.knowledge.services.base_service import BaseService +from ....entity.persistence import rag as persistence_rag +from ....core import app +from ....provider.modelmgr.requester import RuntimeEmbeddingModel +import sqlalchemy + + +class Embedder(BaseService): + def __init__(self, ap: app.Application) -> None: + super().__init__() + self.ap = ap + + async def embed_and_store( + self, kb_id: str, file_id: str, chunks: List[str], embedding_model: RuntimeEmbeddingModel + ) -> list[persistence_rag.Chunk]: + # save chunk to db + chunk_entities: list[persistence_rag.Chunk] = [] + chunk_ids: list[str] = [] + + for chunk_text in chunks: + chunk_uuid = str(uuid.uuid4()) + chunk_ids.append(chunk_uuid) + chunk_entity = persistence_rag.Chunk(uuid=chunk_uuid, file_id=file_id, text=chunk_text) + chunk_entities.append(chunk_entity) + + chunk_dicts = [ + self.ap.persistence_mgr.serialize_model(persistence_rag.Chunk, chunk) for chunk in chunk_entities + ] + + await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.Chunk).values(chunk_dicts)) + + # get embeddings + embeddings_list: list[list[float]] = await embedding_model.requester.invoke_embedding( + model=embedding_model, + input_text=chunks, + extra_args={}, # TODO: add extra args + ) + + # save embeddings to vdb + await self.ap.vector_db_mgr.vector_db.add_embeddings(kb_id, chunk_ids, embeddings_list, chunk_dicts) + + self.ap.logger.info(f'Successfully saved {len(chunk_entities)} embeddings to Knowledge Base.') + + return chunk_entities diff --git a/pkg/rag/knowledge/services/parser.py b/pkg/rag/knowledge/services/parser.py new file mode 100644 index 00000000..004dbdaa --- /dev/null +++ b/pkg/rag/knowledge/services/parser.py @@ -0,0 +1,291 @@ +from __future__ import annotations + +import PyPDF2 +import io +from docx import Document +import chardet +from typing import Union, Callable, Any +import markdown +from bs4 import BeautifulSoup +import re +import asyncio # Import asyncio for async operations +from pkg.core import app + + +class FileParser: + """ + A robust file parser class to extract text content from various document formats. + It supports TXT, PDF, DOCX, XLSX, CSV, Markdown, HTML, and EPUB files. + All core file reading operations are designed to be run synchronously in a thread pool + to avoid blocking the asyncio event loop. + """ + + def __init__(self, ap: app.Application): + self.ap = ap + + async def _run_sync(self, sync_func: Callable, *args: Any, **kwargs: Any) -> Any: + """ + Runs a synchronous function in a separate thread to prevent blocking the event loop. + This is a general utility method for wrapping blocking I/O operations. + """ + try: + return await asyncio.to_thread(sync_func, *args, **kwargs) + except Exception as e: + self.ap.logger.error(f'Error running synchronous function {sync_func.__name__}: {e}') + raise + + async def parse(self, file_name: str, extension: str) -> Union[str, None]: + """ + Parses the file based on its extension and returns the extracted text content. + This is the main asynchronous entry point for parsing. + + Args: + file_name (str): The name of the file to be parsed, get from ap.storage_mgr + + Returns: + Union[str, None]: The extracted text content as a single string, or None if parsing fails. + """ + + file_extension = extension.lower() + parser_method = getattr(self, f'_parse_{file_extension}', None) + + if parser_method is None: + self.ap.logger.error(f'Unsupported file format: {file_extension} for file {file_name}') + return None + + try: + # Pass file_path to the specific parser methods + return await parser_method(file_name) + except Exception as e: + self.ap.logger.error(f'Failed to parse {file_extension} file {file_name}: {e}') + return None + + # --- Helper for reading files with encoding detection --- + async def _read_file_content(self, file_name: str) -> Union[str, bytes]: + """ + Reads a file with automatic encoding detection, ensuring the synchronous + file read operation runs in a separate thread. + """ + + # def _read_sync(): + # with open(file_path, 'rb') as file: + # raw_data = file.read() + # detected = chardet.detect(raw_data) + # encoding = detected['encoding'] or 'utf-8' + + # if mode == 'r': + # return raw_data.decode(encoding, errors='ignore') + # return raw_data # For binary mode + + # return await self._run_sync(_read_sync) + file_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + detected = chardet.detect(file_bytes) + encoding = detected['encoding'] or 'utf-8' + + return file_bytes.decode(encoding, errors='ignore') + + # --- Specific Parser Methods --- + + async def _parse_txt(self, file_name: str) -> str: + """Parses a TXT file and returns its content.""" + self.ap.logger.info(f'Parsing TXT file: {file_name}') + return await self._read_file_content(file_name) + + async def _parse_pdf(self, file_name: str) -> str: + """Parses a PDF file and returns its text content.""" + self.ap.logger.info(f'Parsing PDF file: {file_name}') + + # def _parse_pdf_sync(): + # text_content = [] + # with open(file_name, 'rb') as file: + # pdf_reader = PyPDF2.PdfReader(file) + # for page in pdf_reader.pages: + # text = page.extract_text() + # if text: + # text_content.append(text) + # return '\n'.join(text_content) + + # return await self._run_sync(_parse_pdf_sync) + + pdf_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + def _parse_pdf_sync(): + pdf_reader = PyPDF2.PdfReader(io.BytesIO(pdf_bytes)) + text_content = [] + for page in pdf_reader.pages: + text = page.extract_text() + if text: + text_content.append(text) + return '\n'.join(text_content) + + return await self._run_sync(_parse_pdf_sync) + + async def _parse_docx(self, file_name: str) -> str: + """Parses a DOCX file and returns its text content.""" + self.ap.logger.info(f'Parsing DOCX file: {file_name}') + + docx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + def _parse_docx_sync(): + doc = Document(io.BytesIO(docx_bytes)) + text_content = [paragraph.text for paragraph in doc.paragraphs if paragraph.text.strip()] + return '\n'.join(text_content) + + return await self._run_sync(_parse_docx_sync) + + async def _parse_doc(self, file_name: str) -> str: + """Handles .doc files, explicitly stating lack of direct support.""" + 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: + # """Parses an XLSX file, returning text from all sheets.""" + # self.ap.logger.info(f'Parsing XLSX file: {file_name}') + + # xlsx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + # def _parse_xlsx_sync(): + # excel_file = pd.ExcelFile(io.BytesIO(xlsx_bytes)) + # all_sheet_content = [] + # for sheet_name in excel_file.sheet_names: + # 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' + # all_sheet_content.append(sheet_text) + # return '\n'.join(all_sheet_content) + + # return await self._run_sync(_parse_xlsx_sync) + + # async def _parse_csv(self, file_name: str) -> str: + # """Parses a CSV file and returns its content as a string.""" + # self.ap.logger.info(f'Parsing CSV file: {file_name}') + + # csv_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + # def _parse_csv_sync(): + # # pd.read_csv can often detect encoding, but explicit detection is safer + # # raw_data = self._read_file_content( + # # file_name, mode='rb' + # # ) # Note: this will need to be await outside this sync function + # # _ = raw_data + # # 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. + # detected = chardet.detect(io.BytesIO(csv_bytes)) + # encoding = detected['encoding'] or 'utf-8' + # df = pd.read_csv(io.BytesIO(csv_bytes), encoding=encoding) + # return df.to_string(index=False) + + # return await self._run_sync(_parse_csv_sync) + + 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}') + + md_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + def _parse_markdown_sync(): + md_content = io.BytesIO(md_bytes).read().decode('utf-8', errors='ignore') + html_content = markdown.markdown( + md_content, extensions=['extra', 'codehilite', 'tables', 'toc', 'fenced_code'] + ) + soup = BeautifulSoup(html_content, 'html.parser') + text_parts = [] + for element in soup.children: + if element.name in ['h1', 'h2', 'h3', 'h4', 'h5', 'h6']: + level = int(element.name[1]) + text_parts.append('#' * level + ' ' + element.get_text().strip()) + elif element.name == 'p': + text = element.get_text().strip() + if text: + text_parts.append(text) + elif element.name in ['ul', 'ol']: + for li in element.find_all('li'): + text_parts.append(f'* {li.get_text().strip()}') + elif element.name == 'pre': + code_block = element.get_text().strip() + if code_block: + text_parts.append(f'```\n{code_block}\n```') + elif element.name == 'table': + table_str = self._extract_table_to_markdown_sync(element) # Call sync helper + if table_str: + text_parts.append(table_str) + elif element.name: + text = element.get_text(separator=' ', strip=True) + if text: + text_parts.append(text) + cleaned_text = re.sub(r'\n\s*\n', '\n\n', '\n'.join(text_parts)) + return cleaned_text.strip() + + return await self._run_sync(_parse_markdown_sync) + + async def _parse_html(self, file_name: str) -> str: + """Parses an HTML file, extracting structured plain text.""" + self.ap.logger.info(f'Parsing HTML file: {file_name}') + + html_bytes = await self.ap.storage_mgr.storage_provider.load(file_name) + + def _parse_html_sync(): + html_content = io.BytesIO(html_bytes).read().decode('utf-8', errors='ignore') + soup = BeautifulSoup(html_content, 'html.parser') + for script_or_style in soup(['script', 'style']): + script_or_style.decompose() + text_parts = [] + for element in soup.body.children if soup.body else soup.children: + if element.name in ['h1', 'h2', 'h3', 'h4', 'h5', 'h6']: + level = int(element.name[1]) + text_parts.append('#' * level + ' ' + element.get_text().strip()) + elif element.name == 'p': + text = element.get_text().strip() + if text: + text_parts.append(text) + elif element.name in ['ul', 'ol']: + for li in element.find_all('li'): + text = li.get_text().strip() + if text: + text_parts.append(f'* {text}') + elif element.name == 'table': + table_str = self._extract_table_to_markdown_sync(element) # Call sync helper + if table_str: + text_parts.append(table_str) + elif element.name: + text = element.get_text(separator=' ', strip=True) + if text: + text_parts.append(text) + cleaned_text = re.sub(r'\n\s*\n', '\n\n', '\n'.join(text_parts)) + return cleaned_text.strip() + + return await self._run_sync(_parse_html_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 + for item in toc_list: + if isinstance(item, tuple): + chapter, subchapters = item + text_content.append(f'{indent}- {chapter.title}') + self._add_toc_items_sync(subchapters, text_content, level + 1) + else: + text_content.append(f'{indent}- {item.title}') + + def _extract_table_to_markdown_sync(self, table_element: BeautifulSoup) -> str: + """Helper to convert a BeautifulSoup table element into a Markdown table string (synchronous).""" + headers = [th.get_text().strip() for th in table_element.find_all('th')] + rows = [] + for tr in table_element.find_all('tr'): + cells = [td.get_text().strip() for td in tr.find_all('td')] + if cells: + rows.append(cells) + + if not headers and not rows: + return '' + + table_lines = [] + if headers: + table_lines.append(' | '.join(headers)) + table_lines.append(' | '.join(['---'] * len(headers))) + + for row_cells in rows: + padded_cells = row_cells + [''] * (len(headers) - len(row_cells)) if headers else row_cells + table_lines.append(' | '.join(padded_cells)) + + return '\n'.join(table_lines) diff --git a/pkg/rag/knowledge/services/retriever.py b/pkg/rag/knowledge/services/retriever.py new file mode 100644 index 00000000..73c7edaa --- /dev/null +++ b/pkg/rag/knowledge/services/retriever.py @@ -0,0 +1,48 @@ +from __future__ import annotations + +from . import base_service +from ....core import app +from ....provider.modelmgr.requester import RuntimeEmbeddingModel +from ....entity.rag import retriever as retriever_entities + + +class Retriever(base_service.BaseService): + def __init__(self, ap: app.Application): + super().__init__() + self.ap = ap + + async def retrieve( + self, kb_id: str, query: str, embedding_model: RuntimeEmbeddingModel, k: int = 5 + ) -> list[retriever_entities.RetrieveResultEntry]: + self.ap.logger.info( + f"Retrieving for query: '{query[:10]}' with k={k} using {embedding_model.model_entity.uuid}" + ) + + query_embedding: list[float] = await embedding_model.requester.invoke_embedding( + model=embedding_model, + input_text=[query], + extra_args={}, # TODO: add extra args + ) + + chroma_results = await self.ap.vector_db_mgr.vector_db.search(kb_id, query_embedding[0], 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] + + if not matched_chroma_ids: + self.ap.logger.info('No relevant chunks found in Chroma.') + return [] + + result: list[retriever_entities.RetrieveResultEntry] = [] + + for i, id in enumerate(matched_chroma_ids): + entry = retriever_entities.RetrieveResultEntry( + id=id, + metadata=chroma_metadatas[i], + distance=distances[i], + ) + result.append(entry) + + return result diff --git a/pkg/utils/announce.py b/pkg/utils/announce.py index 56de579d..64e4ba88 100644 --- a/pkg/utils/announce.py +++ b/pkg/utils/announce.py @@ -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, ) diff --git a/pkg/utils/version.py b/pkg/utils/version.py index ec0683c3..b26b1e33 100644 --- a/pkg/utils/version.py +++ b/pkg/utils/version.py @@ -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, ) diff --git a/pkg/vector/__init__.py b/pkg/vector/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pkg/vector/mgr.py b/pkg/vector/mgr.py new file mode 100644 index 00000000..ea198ac2 --- /dev/null +++ b/pkg/vector/mgr.py @@ -0,0 +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): + # 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) diff --git a/pkg/vector/vdb.py b/pkg/vector/vdb.py new file mode 100644 index 00000000..73a3cc0e --- /dev/null +++ b/pkg/vector/vdb.py @@ -0,0 +1,37 @@ +from __future__ import annotations +import abc +from typing import Any, Dict +import numpy as np + + +class VectorDatabase(abc.ABC): + @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 diff --git a/pkg/vector/vdbs/__init__.py b/pkg/vector/vdbs/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pkg/vector/vdbs/chroma.py b/pkg/vector/vdbs/chroma.py new file mode 100644 index 00000000..41ab7d36 --- /dev/null +++ b/pkg/vector/vdbs/chroma.py @@ -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.") diff --git a/pyproject.toml b/pyproject.toml index d06f0643..9e847da9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -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", @@ -50,7 +51,17 @@ dependencies = [ "pre-commit>=4.2.0", "uv>=0.7.11", "mypy>=1.16.0", - "langbot-plugin==0.1.1b3", + "PyPDF2>=3.0.1", + "python-docx>=1.1.0", + "pandas>=2.2.2", + "chardet>=5.2.0", + "markdown>=3.6", + "beautifulsoup4>=4.12.3", + "ebooklib>=0.18", + "html2text>=2024.2.26", + "langchain>=0.2.0", + "chromadb>=0.4.24", + "langbot-plugin==0.1.1b4", ] keywords = [ "bot", @@ -81,11 +92,13 @@ 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", ] diff --git a/templates/config.yaml b/templates/config.yaml index c26c86df..5e9448c8 100644 --- a/templates/config.yaml +++ b/templates/config.yaml @@ -15,6 +15,7 @@ proxy: http: '' https: '' system: + recovery_key: '' jwt: expire: 604800 secret: '' diff --git a/templates/default-pipeline-config.json b/templates/default-pipeline-config.json index 796c6356..2184f982 100644 --- a/templates/default-pipeline-config.json +++ b/templates/default-pipeline-config.json @@ -44,13 +44,13 @@ "role": "system", "content": "You are a helpful assistant." } - ] + ], + "knowledge-base": "" }, "dify-service-api": { "base-url": "https://api.dify.ai/v1", "app-type": "chat", "api-key": "your-api-key", - "thinking-convert": "plain", "timeout": 30 }, "dashscope-app-api": { @@ -86,7 +86,8 @@ "hide-exception": true, "at-sender": true, "quote-origin": true, - "track-function-calls": false + "track-function-calls": false, + "remove-think": false } } } \ No newline at end of file diff --git a/templates/metadata/pipeline/ai.yaml b/templates/metadata/pipeline/ai.yaml index 90732dc8..4564f097 100644 --- a/templates/metadata/pipeline/ai.yaml +++ b/templates/metadata/pipeline/ai.yaml @@ -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 @@ -108,26 +118,6 @@ stages: zh_Hans: API 密钥 type: string required: true - - name: thinking-convert - label: - en_US: CoT Convert - zh_Hans: 思维链转换策略 - type: select - required: true - default: plain - options: - - name: plain - label: - en_US: Convert to ... - zh_Hans: 转换成 ... - - name: original - label: - en_US: Original - zh_Hans: 原始 - - name: remove - label: - en_US: Remove - zh_Hans: 移除 - name: dashscope-app-api label: en_US: Aliyun Dashscope App API @@ -298,3 +288,4 @@ stages: type: string required: false default: 'response' + diff --git a/templates/metadata/pipeline/output.yaml b/templates/metadata/pipeline/output.yaml index 9fe0cd25..8d571e91 100644 --- a/templates/metadata/pipeline/output.yaml +++ b/templates/metadata/pipeline/output.yaml @@ -105,3 +105,13 @@ stages: type: boolean required: true default: false + - name: remove-think + label: + en_US: Remove CoT + zh_Hans: 删除思维链 + description: + en_US: 'If enabled, LangBot will remove the LLM thought content in response. Note: When using streaming response, removing CoT may cause the first token to wait for a long time.' + zh_Hans: '如果启用，将自动删除大模型回复中的模型思考内容。注意：当您使用流式响应时，删除思维链可能会导致首个 Token 的等待时间过长' + type: boolean + required: true + default: false diff --git a/web/.env.example b/web/.env.example new file mode 100644 index 00000000..963ad1c9 --- /dev/null +++ b/web/.env.example @@ -0,0 +1 @@ +NEXT_PUBLIC_API_BASE_URL=http://localhost:5300 diff --git a/web/.gitignore b/web/.gitignore index c77c37c5..9713d3c6 100644 --- a/web/.gitignore +++ b/web/.gitignore @@ -32,6 +32,7 @@ yarn-error.log* # env files (can opt-in for committing if needed) .env* +!.env.example # vercel .vercel diff --git a/web/README.md b/web/README.md index e215bc4c..ac69bf33 100644 --- a/web/README.md +++ b/web/README.md @@ -1,36 +1,3 @@ -This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). +# Debug LangBot Frontend -## Getting Started - -First, run the development server: - -```bash -npm run dev -# or -yarn dev -# or -pnpm dev -# or -bun dev -``` - -Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. - -You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. - -This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel. - -## Learn More - -To learn more about Next.js, take a look at the following resources: - -- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. -- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. - -You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome! - -## Deploy on Vercel - -The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. - -Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details. +Please refer to the [Development Guide](https://docs.langbot.app/en/develop/dev-config.html) for more information. diff --git a/web/package-lock.json b/web/package-lock.json index ee9b5767..3decfad8 100644 --- a/web/package-lock.json +++ b/web/package-lock.json @@ -10,25 +10,32 @@ "dependencies": { "@dnd-kit/core": "^6.3.1", "@dnd-kit/sortable": "^10.0.0", + "@dnd-kit/utilities": "^3.2.2", "@hookform/resolvers": "^5.0.1", "@radix-ui/react-checkbox": "^1.3.1", - "@radix-ui/react-dialog": "^1.1.13", + "@radix-ui/react-context-menu": "^2.2.15", + "@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", "@radix-ui/react-scroll-area": "^1.2.9", "@radix-ui/react-select": "^2.2.4", - "@radix-ui/react-slot": "^1.2.2", + "@radix-ui/react-separator": "^1.1.7", 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"MIT", + "optional": true, + "dependencies": { + "tslib": "^2.4.0" + } + }, + "node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@emnapi/wasi-threads": { + "version": "1.0.2", + "inBundle": true, + "license": "MIT", + "optional": true, + "dependencies": { + "tslib": "^2.4.0" + } + }, + "node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@napi-rs/wasm-runtime": { + "version": "0.2.9", + "inBundle": true, + "license": "MIT", + "optional": true, + "dependencies": { + "@emnapi/core": "^1.4.0", + "@emnapi/runtime": "^1.4.0", + "@tybys/wasm-util": "^0.9.0" + } + }, + "node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/@tybys/wasm-util": { + "version": "0.9.0", + "inBundle": true, + "license": "MIT", + "optional": true, + "dependencies": { + "tslib": "^2.4.0" + } + }, + "node_modules/@tailwindcss/oxide-wasm32-wasi/node_modules/tslib": { + "version": "2.8.0", + "inBundle": true, + "license": "0BSD", + "optional": true + }, "node_modules/@tailwindcss/oxide-win32-arm64-msvc": { "version": "4.1.5", "resolved": "https://registry.npmjs.org/@tailwindcss/oxide-win32-arm64-msvc/-/oxide-win32-arm64-msvc-4.1.5.tgz", @@ -2295,10 +3010,44 @@ "tailwindcss": "4.1.5" } }, + "node_modules/@tanstack/react-table": { + "version": "8.21.3", + "resolved": "https://registry.npmjs.org/@tanstack/react-table/-/react-table-8.21.3.tgz", + "integrity": "sha512-5nNMTSETP4ykGegmVkhjcS8tTLW6Vl4axfEGQN3v0zdHYbK4UfoqfPChclTrJ4EoK9QynqAu9oUf8VEmrpZ5Ww==", + "license": "MIT", + "dependencies": { + "@tanstack/table-core": "8.21.3" + }, + "engines": { + "node": ">=12" + }, + "funding": { + "type": "github", + "url": "https://github.com/sponsors/tannerlinsley" + }, + "peerDependencies": { + "react": ">=16.8", + "react-dom": ">=16.8" + } + }, + "node_modules/@tanstack/table-core": { + "version": "8.21.3", + "resolved": "https://registry.npmjs.org/@tanstack/table-core/-/table-core-8.21.3.tgz", + "integrity": 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"sha512-KrGhL9Q4zjj0kiUt5OO4Mr/A/jlI2jDYs5eHBpYHPcBEVSiipAvn2Ko2HnPe20rmcuuvMHNdZFp+4IlGTMF0Ow==", "license": "MIT", "dependencies": { "asynckit": "^0.4.0", "combined-stream": "^1.0.8", "es-set-tostringtag": "^2.1.0", + "hasown": "^2.0.2", "mime-types": "^2.1.12" }, "engines": { @@ -4763,6 +5513,16 @@ "node": ">=0.8.19" } }, + "node_modules/input-otp": { + "version": "1.4.2", + "resolved": "https://registry.npmjs.org/input-otp/-/input-otp-1.4.2.tgz", + "integrity": "sha512-l3jWwYNvrEa6NTCt7BECfCm48GvwuZzkoeG3gBL2w4CHeOXW3eKFmf9UNYkNfYc3mxMrthMnxjIE07MT0zLBQA==", + "license": "MIT", + "peerDependencies": { + "react": "^16.8 || ^17.0 || ^18.0 || ^19.0.0 || ^19.0.0-rc", + "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0.0 || ^19.0.0-rc" + } + }, "node_modules/internal-slot": { "version": "1.1.0", "resolved": "https://registry.npmjs.org/internal-slot/-/internal-slot-1.1.0.tgz", diff --git a/web/package.json b/web/package.json index 68486bce..8cce9538 100644 --- a/web/package.json +++ b/web/package.json @@ -4,8 +4,6 @@ "private": true, "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", @@ -17,12 +15,16 @@ "prettier --write" ] }, + "overrides": { + "@radix-ui/react-focus-scope": "1.1.7" + }, "dependencies": { "@dnd-kit/core": "^6.3.1", "@dnd-kit/sortable": "^10.0.0", "@dnd-kit/utilities": "^3.2.2", "@hookform/resolvers": "^5.0.1", "@radix-ui/react-checkbox": "^1.3.1", + "@radix-ui/react-context-menu": "^2.2.15", "@radix-ui/react-dialog": "^1.1.14", "@radix-ui/react-dropdown-menu": "^2.1.16", "@radix-ui/react-hover-card": "^1.1.13", @@ -38,11 +40,13 @@ "@radix-ui/react-toggle-group": "^1.1.9", "@radix-ui/react-tooltip": "^1.2.7", "@tailwindcss/postcss": "^4.1.5", + "@tanstack/react-table": "^8.21.3", "axios": "^1.8.4", "class-variance-authority": "^0.7.1", "clsx": "^2.1.1", "i18next": "^25.1.2", "i18next-browser-languagedetector": "^8.1.0", + "input-otp": "^1.4.2", "lodash": "^4.17.21", "lucide-react": "^0.507.0", "next": "15.2.4", diff --git a/web/src/app/global.css b/web/src/app/global.css index 079437e8..310d509a 100644 --- a/web/src/app/global.css +++ b/web/src/app/global.css @@ -56,6 +56,15 @@ background: rgba(0, 0, 0, 0.35); /* 悬停加深 */ } +/* 暗黑模式下的滚动条 */ +.dark ::-webkit-scrollbar-thumb { + background: rgba(255, 255, 255, 0.2); /* 半透明白色 */ +} + +.dark ::-webkit-scrollbar-thumb:hover { + background: rgba(255, 255, 255, 0.35); /* 悬停加深 */ +} + /* 兼容 Edge */ @supports (-ms-ime-align: auto) { body { @@ -108,36 +117,36 @@ } .dark { - --background: oklch(0.141 0.005 285.823); + --background: oklch(0.08 0.002 285.823); --foreground: oklch(0.985 0 0); - --card: oklch(0.21 0.006 285.885); + --card: oklch(0.12 0.004 285.885); --card-foreground: oklch(0.985 0 0); - --popover: oklch(0.21 0.006 285.885); + --popover: oklch(0.12 0.004 285.885); --popover-foreground: oklch(0.985 0 0); - --primary: oklch(0.92 0.004 286.32); - --primary-foreground: oklch(0.21 0.006 285.885); - --secondary: oklch(0.274 0.006 286.033); + --primary: oklch(0.62 0.2 255); + --primary-foreground: oklch(1 0 0); + --secondary: oklch(0.18 0.004 286.033); --secondary-foreground: oklch(0.985 0 0); - --muted: oklch(0.274 0.006 286.033); + --muted: oklch(0.18 0.004 286.033); --muted-foreground: oklch(0.705 0.015 286.067); - --accent: oklch(0.274 0.006 286.033); + --accent: oklch(0.18 0.004 286.033); --accent-foreground: oklch(0.985 0 0); --destructive: oklch(0.704 0.191 22.216); - --border: oklch(1 0 0 / 10%); - --input: oklch(1 0 0 / 15%); + --border: oklch(1 0 0 / 8%); + --input: oklch(1 0 0 / 10%); --ring: oklch(0.552 0.016 285.938); --chart-1: oklch(0.488 0.243 264.376); --chart-2: oklch(0.696 0.17 162.48); --chart-3: oklch(0.769 0.188 70.08); --chart-4: oklch(0.627 0.265 303.9); --chart-5: oklch(0.645 0.246 16.439); - --sidebar: oklch(0.21 0.006 285.885); + --sidebar: oklch(0.1 0.003 285.885); --sidebar-foreground: oklch(0.985 0 0); - --sidebar-primary: oklch(0.488 0.243 264.376); - --sidebar-primary-foreground: oklch(0.985 0 0); - --sidebar-accent: oklch(0.274 0.006 286.033); + --sidebar-primary: oklch(0.62 0.2 255); + --sidebar-primary-foreground: oklch(1 0 0); + --sidebar-accent: oklch(0.18 0.004 286.033); --sidebar-accent-foreground: oklch(0.985 0 0); - --sidebar-border: oklch(1 0 0 / 10%); + --sidebar-border: oklch(1 0 0 / 8%); --sidebar-ring: oklch(0.552 0.016 285.938); } diff --git a/web/src/app/home/bots/BotDetailDialog.tsx b/web/src/app/home/bots/BotDetailDialog.tsx index 1c4a2403..fbb8c359 100644 --- a/web/src/app/home/bots/BotDetailDialog.tsx +++ b/web/src/app/home/bots/BotDetailDialog.tsx @@ -127,10 +127,8 @@ export default function BotDetailDialog({ @@ -161,7 +159,7 @@ export default function BotDetailDialog({ @@ -199,10 +197,8 @@ export default function BotDetailDialog({ )} {activeMenu === 'logs' && botId && ( diff --git a/web/src/app/home/bots/components/bot-card/botCard.module.css b/web/src/app/home/bots/components/bot-card/botCard.module.css index 396b5831..d9b82b9b 100644 --- a/web/src/app/home/bots/components/bot-card/botCard.module.css +++ b/web/src/app/home/bots/components/bot-card/botCard.module.css @@ -6,12 +6,22 @@ box-shadow: 0px 2px 2px 0 rgba(0, 0, 0, 0.2); padding: 1.2rem; cursor: pointer; + transition: all 0.2s ease; +} + +:global(.dark) .cardContainer { + background-color: #1f1f22; + box-shadow: 0; } .cardContainer:hover { box-shadow: 0px 2px 8px 0 rgba(0, 0, 0, 0.1); } +:global(.dark) .cardContainer:hover { + box-shadow: 0; +} + .iconBasicInfoContainer { width: 100%; height: 100%; @@ -47,6 +57,11 @@ white-space: nowrap; overflow: hidden; text-overflow: ellipsis; + color: #1a1a1a; +} + +:global(.dark) .basicInfoName { + color: #f0f0f0; } .basicInfoDescription { @@ -58,6 +73,10 @@ text-overflow: ellipsis; } +:global(.dark) .basicInfoDescription { + color: #888888; +} + .basicInfoAdapterContainer { display: flex; flex-direction: row; @@ -71,12 +90,20 @@ color: #626262; } +:global(.dark) .basicInfoAdapterIcon { + color: #a0a0a0; +} + .basicInfoAdapterLabel { font-size: 1.2rem; font-weight: 500; color: #626262; } +:global(.dark) .basicInfoAdapterLabel { + color: #a0a0a0; +} + .basicInfoPipelineContainer { display: flex; flex-direction: row; @@ -90,12 +117,20 @@ margin-top: 0.2rem; } +:global(.dark) .basicInfoPipelineIcon { + color: #a0a0a0; +} + .basicInfoPipelineLabel { font-size: 1.2rem; font-weight: 500; color: #626262; } +:global(.dark) .basicInfoPipelineLabel { + color: #a0a0a0; +} + .bigText { white-space: nowrap; overflow: hidden; diff --git a/web/src/app/home/bots/components/bot-form/BotForm.tsx b/web/src/app/home/bots/components/bot-form/BotForm.tsx index de42e2ed..f6aa21c0 100644 --- a/web/src/app/home/bots/components/bot-form/BotForm.tsx +++ b/web/src/app/home/bots/components/bot-form/BotForm.tsx @@ -64,17 +64,13 @@ const getFormSchema = (t: (key: string) => string) => export default function BotForm({ initBotId, onFormSubmit, - onFormCancel, onBotDeleted, onNewBotCreated, - hideButtons = false, }: { initBotId?: string; onFormSubmit: (value: z.infer>) => void; - onFormCancel: () => void; onBotDeleted: () => void; onNewBotCreated: (botId: string) => void; - hideButtons?: boolean; }) { const { t } = useTranslation(); const formSchema = getFormSchema(t); @@ -214,6 +210,7 @@ export default function BotForm({ }); setAdapterNameToDynamicConfigMap(adapterNameToDynamicConfigMap); } + async function getBotConfig( botId: string, ): Promise> { @@ -397,7 +394,7 @@ export default function BotForm({ {t('bots.bindPipeline')} - + @@ -135,7 +151,7 @@ export default function DynamicFormItemComponent({ case DynamicFormItemType.LLM_MODEL_SELECTOR: return ( ); + case DynamicFormItemType.KNOWLEDGE_BASE_SELECTOR: + return ( + + ); + case DynamicFormItemType.PROMPT_EDITOR: return (
@@ -257,7 +292,7 @@ export default function DynamicFormItemComponent({
{/* 角色选择 */} {index === 0 ? ( -
+
system
) : ( @@ -269,7 +304,7 @@ export default function DynamicFormItemComponent({ field.onChange(newValue); }} > - + @@ -281,7 +316,7 @@ export default function DynamicFormItemComponent({ )} {/* 内容输入 */} - { diff --git a/web/src/app/home/components/empty-and-create-component/EmptyAndCreateComponent.tsx b/web/src/app/home/components/empty-and-create-component/EmptyAndCreateComponent.tsx deleted file mode 100644 index b55b4cee..00000000 --- a/web/src/app/home/components/empty-and-create-component/EmptyAndCreateComponent.tsx +++ /dev/null @@ -1,27 +0,0 @@ -import styles from './emptyAndCreate.module.css'; - -export default function EmptyAndCreateComponent({ - title, - subTitle, - buttonText, - onButtonClick, -}: { - title: string; - subTitle: string; - buttonText: string; - onButtonClick: () => void; -}) { - return ( -
-
-
-
{title}
-
{subTitle}
-
-
- {buttonText} -
-
-
- ); -} diff --git a/web/src/app/home/components/empty-and-create-component/emptyAndCreate.module.css b/web/src/app/home/components/empty-and-create-component/emptyAndCreate.module.css deleted file mode 100644 index 3504d7a3..00000000 --- a/web/src/app/home/components/empty-and-create-component/emptyAndCreate.module.css +++ /dev/null @@ -1,54 +0,0 @@ -.emptyPageContainer { - width: 100%; - height: 100%; - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; - background: #fff; - border: 1px solid #c5c5c5; - border-radius: 10px; -} - -.emptyContainer { - width: 100%; - height: 50%; - display: flex; - flex-direction: column; - align-items: center; - justify-content: space-evenly; -} - -.emptyCreateButton { - width: 200px; - height: 50px; - border-radius: 20px; - background-color: #2288ee; - color: #fff; - font-size: 20px; - font-weight: bold; - text-align: center; - line-height: 50px; - user-select: none; -} - -.emptyCreateButton:hover { - background-color: #1b77d2; -} - -.emptyInfoContainer { - width: 100%; - height: 60px; - display: flex; - flex-direction: column; - align-items: center; - color: #353535; -} - -.emptyInfoText { - font-size: 30px; -} - -.emptyInfoSubText { - font-size: 28px; -} diff --git a/web/src/app/home/components/home-sidebar/HomeSidebar.module.css b/web/src/app/home/components/home-sidebar/HomeSidebar.module.css index d525d495..4aeb96e3 100644 --- a/web/src/app/home/components/home-sidebar/HomeSidebar.module.css +++ b/web/src/app/home/components/home-sidebar/HomeSidebar.module.css @@ -13,6 +13,10 @@ /* box-shadow: 0 0 5px 0 rgba(0, 0, 0, 0.1); */ } +:global(.dark) .sidebarContainer { + background-color: #0a0a0b !important; +} + .langbotIconContainer { width: 200px; height: 70px; @@ -21,32 +25,49 @@ align-items: center; justify-content: center; gap: 0.8rem; +} - .langbotIcon { - width: 2.8rem; - height: 2.8rem; - box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.1); - border-radius: 8px; - } +.langbotIcon { + width: 2.8rem; + height: 2.8rem; + box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.1); + border-radius: 8px; +} - .langbotTextContainer { - display: flex; - flex-direction: column; - align-items: flex-start; - justify-content: flex-start; - gap: 0.1rem; - } +:global(.dark) .langbotIcon { + box-shadow: 0 0 10px 0 rgba(255, 255, 255, 0.1); +} - .langbotText { - font-size: 1.4rem; - font-weight: 500; - } +.langbotTextContainer { + display: flex; + flex-direction: column; + align-items: flex-start; + justify-content: flex-start; + gap: 0.1rem; +} - .langbotVersion { - font-size: 0.8rem; - font-weight: 700; - color: #6c6c6c; - } +.langbotText { + font-size: 1.4rem; + font-weight: 500; + color: #1a1a1a; +} + +:global(.dark) .langbotText { + font-size: 1.4rem; + font-weight: 500; + color: #f0f0f0 !important; +} + +.langbotVersion { + font-size: 0.8rem; + font-weight: 700; + color: #6c6c6c; +} + +:global(.dark) .langbotVersion { + font-size: 0.8rem; + font-weight: 700; + color: #a0a0a0 !important; } .sidebarTopContainer { @@ -76,6 +97,7 @@ justify-content: flex-start; cursor: pointer; gap: 0.5rem; + transition: all 0.2s ease; /* background-color: aqua; */ } @@ -85,16 +107,40 @@ box-shadow: 0 0 10px 0 rgba(0, 0, 0, 0.1); } +:global(.dark) .sidebarSelected { + background-color: #2288ee; + color: white; + box-shadow: 0 0 10px 0 rgba(34, 136, 238, 0.3); +} + .sidebarUnselected { color: #6c6c6c; } +:global(.dark) .sidebarUnselected { + color: #a0a0a0 !important; +} + +.sidebarUnselected:hover { + background-color: rgba(34, 136, 238, 0.1); + color: #2288ee; +} + +:global(.dark) .sidebarUnselected:hover { + background-color: rgba(34, 136, 238, 0.2); + color: #66baff; +} + .sidebarChildIcon { width: 20px; height: 20px; background-color: rgba(96, 149, 209, 0); } +.sidebarChildName { + color: inherit; +} + .sidebarBottomContainer { width: 100%; display: flex; diff --git a/web/src/app/home/components/home-sidebar/HomeSidebar.tsx b/web/src/app/home/components/home-sidebar/HomeSidebar.tsx index 876baf33..25b3b58f 100644 --- a/web/src/app/home/components/home-sidebar/HomeSidebar.tsx +++ b/web/src/app/home/components/home-sidebar/HomeSidebar.tsx @@ -11,6 +11,18 @@ import { sidebarConfigList } from '@/app/home/components/home-sidebar/sidbarConf import langbotIcon from '@/app/assets/langbot-logo.webp'; import { systemInfo } from '@/app/infra/http/HttpClient'; import { useTranslation } from 'react-i18next'; +import { Moon, Sun, Monitor } from 'lucide-react'; +import { useTheme } from 'next-themes'; + +import { + Popover, + PopoverContent, + PopoverTrigger, +} from '@/components/ui/popover'; +import { Button } from '@/components/ui/button'; +import { ToggleGroup, ToggleGroupItem } from '@/components/ui/toggle-group'; +import { LanguageSelector } from '@/components/ui/language-selector'; +import PasswordChangeDialog from '@/app/home/components/password-change-dialog/PasswordChangeDialog'; // TODO 侧边导航栏要加动画 export default function HomeSidebar({ @@ -27,8 +39,11 @@ export default function HomeSidebar({ }, [pathname]); const [selectedChild, setSelectedChild] = useState(); - + const { theme, setTheme } = useTheme(); const { t } = useTranslation(); + const [popoverOpen, setPopoverOpen] = useState(false); + const [passwordChangeOpen, setPasswordChangeOpen] = useState(false); + const [languageSelectorOpen, setLanguageSelectorOpen] = useState(false); useEffect(() => { initSelect(); @@ -144,6 +159,11 @@ export default function HomeSidebar({ 'https://docs.langbot.app/zh/insight/guide.html', '_blank', ); + } else if (language === 'zh-Hant') { + window.open( + 'https://docs.langbot.app/zh/insight/guide.html', + '_blank', + ); } else { window.open( 'https://docs.langbot.app/en/insight/guide.html', @@ -163,23 +183,113 @@ export default function HomeSidebar({ } name={t('common.helpDocs')} /> - { - handleLogout(); + + { + // 防止语言选择器打开时关闭popover + if (!open && languageSelectorOpen) return; + setPopoverOpen(open); }} - isSelected={false} - icon={ - - - - } - name={t('common.logout')} - /> + > + + {}} + isSelected={false} + icon={ + + + + } + name={t('common.accountOptions')} + /> + + +
+ {t('common.theme')} + { + if (value) setTheme(value); + }} + className="justify-start" + > + + + + + + + + + + +
+ +
+ + {t('common.language')} + + +
+ +
+ {t('common.account')} + + +
+ +
+
); } diff --git a/web/src/app/home/components/home-sidebar/sidbarConfigList.tsx b/web/src/app/home/components/home-sidebar/sidbarConfigList.tsx index e21317d6..b3edb98a 100644 --- a/web/src/app/home/components/home-sidebar/sidbarConfigList.tsx +++ b/web/src/app/home/components/home-sidebar/sidbarConfigList.tsx @@ -47,6 +47,7 @@ export const sidebarConfigList = [ zh_Hans: 'https://docs.langbot.app/zh/deploy/models/readme.html', }, }), + new SidebarChildVO({ id: 'pipelines', name: t('pipelines.title'), @@ -67,6 +68,25 @@ export const sidebarConfigList = [ zh_Hans: 'https://docs.langbot.app/zh/deploy/pipelines/readme.html', }, }), + new SidebarChildVO({ + id: 'knowledge', + name: t('knowledge.title'), + icon: ( + + + + ), + route: '/home/knowledge', + description: t('knowledge.description'), + helpLink: { + en_US: 'https://docs.langbot.app/en/deploy/knowledge/readme.html', + zh_Hans: 'https://docs.langbot.app/zh/deploy/knowledge/readme.html', + }, + }), new SidebarChildVO({ id: 'plugins', name: t('plugins.title'), diff --git a/web/src/app/home/components/home-titlebar/HomeTittleBar.module.css b/web/src/app/home/components/home-titlebar/HomeTittleBar.module.css index bc740231..73bb2242 100644 --- a/web/src/app/home/components/home-titlebar/HomeTittleBar.module.css +++ b/web/src/app/home/components/home-titlebar/HomeTittleBar.module.css @@ -17,6 +17,10 @@ color: #585858; } +:global(.dark) .titleText { + color: #e0e0e0; +} + .subtitleText { margin-left: 3.2rem; font-size: 0.8rem; @@ -25,8 +29,16 @@ align-items: center; } +:global(.dark) .subtitleText { + color: #b0b0b0; +} + .helpLink { margin-left: 0.2rem; font-size: 0.8rem; color: #8b8b8b; } + +:global(.dark) .helpLink { + color: #a0a0a0; +} diff --git a/web/src/app/home/components/password-change-dialog/PasswordChangeDialog.tsx b/web/src/app/home/components/password-change-dialog/PasswordChangeDialog.tsx new file mode 100644 index 00000000..03a302af --- /dev/null +++ b/web/src/app/home/components/password-change-dialog/PasswordChangeDialog.tsx @@ -0,0 +1,163 @@ +'use client'; + +import * as React from 'react'; +import { useState } from 'react'; +import { useForm } from 'react-hook-form'; +import { zodResolver } from '@hookform/resolvers/zod'; +import { z } from 'zod'; +import { toast } from 'sonner'; +import { useTranslation } from 'react-i18next'; +import { + Dialog, + DialogContent, + DialogHeader, + DialogTitle, + DialogFooter, +} from '@/components/ui/dialog'; +import { Button } from '@/components/ui/button'; +import { + Form, + FormControl, + FormField, + FormItem, + FormLabel, + FormMessage, +} from '@/components/ui/form'; +import { Input } from '@/components/ui/input'; +import { httpClient } from '@/app/infra/http/HttpClient'; + +const getFormSchema = (t: (key: string) => string) => + z + .object({ + currentPassword: z + .string() + .min(1, { message: t('common.currentPasswordRequired') }), + newPassword: z + .string() + .min(1, { message: t('common.newPasswordRequired') }), + confirmNewPassword: z + .string() + .min(1, { message: t('common.confirmPasswordRequired') }), + }) + .refine((data) => data.newPassword === data.confirmNewPassword, { + message: t('common.passwordsDoNotMatch'), + path: ['confirmNewPassword'], + }); + +interface PasswordChangeDialogProps { + open: boolean; + onOpenChange: (open: boolean) => void; +} + +export default function PasswordChangeDialog({ + open, + onOpenChange, +}: PasswordChangeDialogProps) { + const { t } = useTranslation(); + const [isSubmitting, setIsSubmitting] = useState(false); + const formSchema = getFormSchema(t); + + const form = useForm>({ + resolver: zodResolver(formSchema), + defaultValues: { + currentPassword: '', + newPassword: '', + confirmNewPassword: '', + }, + }); + + const onSubmit = async (values: z.infer) => { + setIsSubmitting(true); + try { + await httpClient.changePassword( + values.currentPassword, + values.newPassword, + ); + toast.success(t('common.changePasswordSuccess')); + form.reset(); + onOpenChange(false); + } catch { + toast.error(t('common.changePasswordFailed')); + } finally { + setIsSubmitting(false); + } + }; + + return ( + + + + {t('common.changePassword')} + +
+ + ( + + {t('common.currentPassword')} + + + + + + )} + /> + ( + + {t('common.newPassword')} + + + + + + )} + /> + ( + + {t('common.confirmNewPassword')} + + + + + + )} + /> + + + + + + +
+ + ); +} diff --git a/web/src/app/home/knowledge/KBDetailDialog.tsx b/web/src/app/home/knowledge/KBDetailDialog.tsx new file mode 100644 index 00000000..33a21267 --- /dev/null +++ b/web/src/app/home/knowledge/KBDetailDialog.tsx @@ -0,0 +1,253 @@ +'use client'; + +import { useEffect, useState } from 'react'; +import { + Dialog, + DialogContent, + DialogHeader, + DialogTitle, + DialogFooter, +} from '@/components/ui/dialog'; +import { + Sidebar, + SidebarContent, + SidebarGroup, + SidebarGroupContent, + SidebarMenu, + SidebarMenuButton, + SidebarMenuItem, + SidebarProvider, +} from '@/components/ui/sidebar'; +import { Button } from '@/components/ui/button'; +import { useTranslation } from 'react-i18next'; +import { httpClient } from '@/app/infra/http/HttpClient'; +// import { KnowledgeBase } from '@/app/infra/entities/api'; +import KBForm from '@/app/home/knowledge/components/kb-form/KBForm'; +import KBDoc from '@/app/home/knowledge/components/kb-docs/KBDoc'; +import KBRetrieve from '@/app/home/knowledge/components/kb-retrieve/KBRetrieve'; + +interface KBDetailDialogProps { + open: boolean; + onOpenChange: (open: boolean) => void; + kbId?: string; + onFormCancel: () => void; + onKbDeleted: () => void; + onNewKbCreated: (kbId: string) => void; + onKbUpdated: (kbId: string) => void; +} + +export default function KBDetailDialog({ + open, + onOpenChange, + kbId: propKbId, + onFormCancel, + onKbDeleted, + onNewKbCreated, + onKbUpdated, +}: KBDetailDialogProps) { + const { t } = useTranslation(); + const [kbId, setKbId] = useState(propKbId); + const [activeMenu, setActiveMenu] = useState('metadata'); + const [showDeleteConfirm, setShowDeleteConfirm] = useState(false); + + useEffect(() => { + setKbId(propKbId); + setActiveMenu('metadata'); + }, [propKbId, open]); + + const menu = [ + { + key: 'metadata', + label: t('knowledge.metadata'), + icon: ( + + + + ), + }, + { + key: 'documents', + label: t('knowledge.documents'), + icon: ( + + + + ), + }, + { + key: 'retrieve', + label: t('knowledge.retrieve'), + icon: ( + + + + ), + }, + ]; + + const confirmDelete = () => { + httpClient.deleteKnowledgeBase(kbId ?? '').then(() => { + onKbDeleted(); + }); + setShowDeleteConfirm(false); + }; + + if (!kbId) { + // new kb + return ( + + +
+ + {t('knowledge.createKnowledgeBase')} + +
+ {activeMenu === 'metadata' && ( + + )} + {activeMenu === 'documents' &&
documents
} +
+ {activeMenu === 'metadata' && ( + +
+ + +
+ + )} +
+ + + ); + } + + return ( + <> + + + + + + + + + {menu.map((item) => ( + + setActiveMenu(item.key)} + > + + {item.icon} + {item.label} + + + + ))} + + + + + +
+ + + {activeMenu === 'metadata' + ? t('knowledge.editKnowledgeBase') + : activeMenu === 'documents' + ? t('knowledge.editDocument') + : t('knowledge.retrieveTest')} + + +
+ {activeMenu === 'metadata' && ( + + )} + {activeMenu === 'documents' && } + {activeMenu === 'retrieve' && } +
+ {activeMenu === 'metadata' && ( + +
+ + + +
+ + )} +
+ + + + + {/* 删除确认对话框 */} + + + + {t('common.confirmDelete')} + +
+ {t('knowledge.deleteKnowledgeBaseConfirmation')} +
+ + + + + + + + ); +} diff --git a/web/src/app/home/knowledge/components/kb-card/KBCard.module.css b/web/src/app/home/knowledge/components/kb-card/KBCard.module.css new file mode 100644 index 00000000..d2bfebca --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-card/KBCard.module.css @@ -0,0 +1,144 @@ +.cardContainer { + width: 100%; + height: 10rem; + background-color: #fff; + border-radius: 10px; + box-shadow: 0px 2px 2px 0 rgba(0, 0, 0, 0.2); + padding: 1.2rem; + cursor: pointer; + display: flex; + flex-direction: row; + justify-content: space-between; + gap: 0.5rem; + transition: all 0.2s ease; +} + +:global(.dark) .cardContainer { + background-color: #1f1f22; + box-shadow: 0; +} + +.cardContainer:hover { + box-shadow: 0px 2px 8px 0 rgba(0, 0, 0, 0.1); +} + +:global(.dark) .cardContainer:hover { + box-shadow: 0; +} + +.basicInfoContainer { + width: 100%; + height: 100%; + display: flex; + flex-direction: column; + justify-content: space-between; + gap: 0.4rem; + min-width: 0; +} + +.basicInfoNameContainer { + display: flex; + flex-direction: column; + gap: 0.2rem; +} + +.basicInfoNameText { + font-size: 1.4rem; + font-weight: 500; + color: #1a1a1a; +} + +:global(.dark) .basicInfoNameText { + color: #f0f0f0; +} + +.basicInfoDescriptionText { + font-size: 0.9rem; + font-weight: 400; + display: -webkit-box; + -webkit-line-clamp: 3; + -webkit-box-orient: vertical; + overflow: hidden; + text-overflow: ellipsis; + color: #b1b1b1; +} + +:global(.dark) .basicInfoDescriptionText { + color: #888888; +} + +.basicInfoLastUpdatedTimeContainer { + display: flex; + flex-direction: row; + align-items: center; + gap: 0.5rem; +} + +.basicInfoUpdateTimeIcon { + width: 1.2rem; + height: 1.2rem; + color: #626262; +} + +:global(.dark) .basicInfoUpdateTimeIcon { + color: #a0a0a0; +} + +.basicInfoUpdateTimeText { + font-size: 1rem; + font-weight: 400; + color: #626262; +} + +:global(.dark) .basicInfoUpdateTimeText { + color: #a0a0a0; +} + +.operationContainer { + display: flex; + flex-direction: column; + align-items: flex-end; + justify-content: space-between; + gap: 0.5rem; + width: 8rem; +} + +.operationDefaultBadge { + display: flex; + flex-direction: row; + gap: 0.5rem; +} + +.operationDefaultBadgeIcon { + width: 1.2rem; + height: 1.2rem; + color: #ffcd27; +} + +:global(.dark) .operationDefaultBadgeIcon { + color: #fbbf24; +} + +.operationDefaultBadgeText { + font-size: 1rem; + font-weight: 400; + color: #ffcd27; +} + +:global(.dark) .operationDefaultBadgeText { + color: #fbbf24; +} + +.bigText { + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + font-size: 1.4rem; + font-weight: bold; + max-width: 100%; +} + +.debugButtonIcon { + width: 1.2rem; + height: 1.2rem; +} diff --git a/web/src/app/home/knowledge/components/kb-card/KBCard.tsx b/web/src/app/home/knowledge/components/kb-card/KBCard.tsx new file mode 100644 index 00000000..560b0497 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-card/KBCard.tsx @@ -0,0 +1,36 @@ +import { KnowledgeBaseVO } from '@/app/home/knowledge/components/kb-card/KBCardVO'; +import { useTranslation } from 'react-i18next'; +import styles from './KBCard.module.css'; + +export default function KBCard({ kbCardVO }: { kbCardVO: KnowledgeBaseVO }) { + const { t } = useTranslation(); + return ( +
+
+
+
+ {kbCardVO.name} +
+
+ {kbCardVO.description} +
+
+ +
+ + + +
+ {t('knowledge.updateTime')} + {kbCardVO.lastUpdatedTimeAgo} +
+
+
+
+ ); +} diff --git a/web/src/app/home/knowledge/components/kb-card/KBCardVO.ts b/web/src/app/home/knowledge/components/kb-card/KBCardVO.ts new file mode 100644 index 00000000..b13d2c24 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-card/KBCardVO.ts @@ -0,0 +1,26 @@ +export interface IKnowledgeBaseVO { + id: string; + name: string; + description: string; + embeddingModelUUID: string; + top_k: number; + lastUpdatedTimeAgo: string; +} + +export class KnowledgeBaseVO implements IKnowledgeBaseVO { + id: string; + name: string; + description: string; + embeddingModelUUID: string; + top_k: number; + lastUpdatedTimeAgo: string; + + constructor(props: IKnowledgeBaseVO) { + this.id = props.id; + this.name = props.name; + this.description = props.description; + this.embeddingModelUUID = props.embeddingModelUUID; + this.top_k = props.top_k; + this.lastUpdatedTimeAgo = props.lastUpdatedTimeAgo; + } +} diff --git a/web/src/app/home/knowledge/components/kb-docs/FileUploadZone.tsx b/web/src/app/home/knowledge/components/kb-docs/FileUploadZone.tsx new file mode 100644 index 00000000..ff61a5b4 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-docs/FileUploadZone.tsx @@ -0,0 +1,145 @@ +import React, { useCallback, useState } from 'react'; +import { Card, CardContent } from '@/components/ui/card'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { toast } from 'sonner'; +import { useTranslation } from 'react-i18next'; + +interface FileUploadZoneProps { + kbId: string; + onUploadSuccess: () => void; + onUploadError: (error: string) => void; +} + +export default function FileUploadZone({ + kbId, + onUploadSuccess, + onUploadError, +}: FileUploadZoneProps) { + const { t } = useTranslation(); + const [isDragOver, setIsDragOver] = useState(false); + const [isUploading, setIsUploading] = useState(false); + + const handleUpload = useCallback( + async (file: File) => { + if (isUploading) return; + + setIsUploading(true); + const toastId = toast.loading(t('knowledge.documentsTab.uploadingFile')); + + try { + // Step 1: Upload file to server + const uploadResult = await httpClient.uploadDocumentFile(file); + + // Step 2: Associate file with knowledge base + await httpClient.uploadKnowledgeBaseFile(kbId, uploadResult.file_id); + + toast.success(t('knowledge.documentsTab.uploadSuccess'), { + id: toastId, + }); + onUploadSuccess(); + } catch (error) { + console.error('File upload failed:', error); + const errorMessage = t('knowledge.documentsTab.uploadError'); + toast.error(errorMessage, { id: toastId }); + onUploadError(errorMessage); + } finally { + setIsUploading(false); + } + }, + [kbId, isUploading, onUploadSuccess, onUploadError], + ); + + const handleDragOver = useCallback((e: React.DragEvent) => { + e.preventDefault(); + setIsDragOver(true); + }, []); + + const handleDragLeave = useCallback((e: React.DragEvent) => { + e.preventDefault(); + setIsDragOver(false); + }, []); + + const handleDrop = useCallback( + (e: React.DragEvent) => { + e.preventDefault(); + setIsDragOver(false); + + const files = Array.from(e.dataTransfer.files); + if (files.length > 0) { + handleUpload(files[0]); + } + }, + [handleUpload], + ); + + const handleFileSelect = useCallback( + (e: React.ChangeEvent) => { + const files = e.target.files; + if (files && files.length > 0) { + handleUpload(files[0]); + } + }, + [handleUpload], + ); + + return ( + + +
+ + + +
+ + + ); +} diff --git a/web/src/app/home/knowledge/components/kb-docs/KBDoc.tsx b/web/src/app/home/knowledge/components/kb-docs/KBDoc.tsx new file mode 100644 index 00000000..fb94dace --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-docs/KBDoc.tsx @@ -0,0 +1,72 @@ +import { useEffect, useState } from 'react'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { KnowledgeBaseFile } from '@/app/infra/entities/api'; +import { columns, DocumentFile } from './documents/columns'; +import { DataTable } from './documents/data-table'; +import FileUploadZone from './FileUploadZone'; +import { toast } from 'sonner'; +import { useTranslation } from 'react-i18next'; + +export default function KBDoc({ kbId }: { kbId: string }) { + const [documentsList, setDocumentsList] = useState([]); + const { t } = useTranslation(); + + useEffect(() => { + getDocumentsList(); + + const intervalId = setInterval(() => { + getDocumentsList(); + }, 5000); + + return () => { + clearInterval(intervalId); + }; + }, [kbId]); + + async function getDocumentsList() { + const resp = await httpClient.getKnowledgeBaseFiles(kbId); + setDocumentsList( + resp.files.map((file: KnowledgeBaseFile) => { + return { + uuid: file.uuid, + name: file.file_name, + status: file.status, + }; + }), + ); + } + + const handleUploadSuccess = () => { + // Refresh document list after successful upload + getDocumentsList(); + }; + + const handleUploadError = (error: string) => { + // Error messages are already handled by toast in FileUploadZone component + console.error('Upload failed:', error); + }; + + const handleDelete = (id: string) => { + httpClient + .deleteKnowledgeBaseFile(kbId, id) + .then(() => { + getDocumentsList(); + toast.success(t('knowledge.documentsTab.fileDeleteSuccess')); + }) + .catch((error) => { + console.error('Delete failed:', error); + toast.error(t('knowledge.documentsTab.fileDeleteFailed')); + }); + }; + + return ( +
+ + +
+ ); +} diff --git a/web/src/app/home/knowledge/components/kb-docs/documents/columns.tsx b/web/src/app/home/knowledge/components/kb-docs/documents/columns.tsx new file mode 100644 index 00000000..2880c1ba --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-docs/documents/columns.tsx @@ -0,0 +1,97 @@ +'use client'; + +import { ColumnDef } from '@tanstack/react-table'; +import { MoreHorizontal } from 'lucide-react'; +import { Button } from '@/components/ui/button'; +import { + DropdownMenu, + DropdownMenuContent, + DropdownMenuItem, + DropdownMenuLabel, + DropdownMenuTrigger, +} from '@/components/ui/dropdown-menu'; +import { Badge } from '@/components/ui/badge'; +import { TFunction } from 'i18next'; + +export type DocumentFile = { + uuid: string; + name: string; + status: string; +}; + +export const columns = ( + onDelete: (id: string) => void, + t: TFunction, +): ColumnDef[] => { + return [ + { + accessorKey: 'name', + header: t('knowledge.documentsTab.name'), + }, + { + accessorKey: 'status', + header: t('knowledge.documentsTab.status'), + cell: ({ row }) => { + const document = row.original; + + switch (document.status) { + case 'processing': + return ( + + {t('knowledge.documentsTab.processing')} + + ); + case 'completed': + return ( + + {t('knowledge.documentsTab.completed')} + + ); + case 'failed': + return ( + + {t('knowledge.documentsTab.failed')} + + ); + default: + return ( + + {document.status} + + ); + } + }, + }, + { + id: 'actions', + cell: ({ row }) => { + const document = row.original; + + return ( + + + + + + + {t('knowledge.documentsTab.actions')} + + + onDelete(document.uuid)}> + {t('knowledge.documentsTab.delete')} + + + + ); + }, + }, + ]; +}; diff --git a/web/src/app/home/knowledge/components/kb-docs/documents/data-table.tsx b/web/src/app/home/knowledge/components/kb-docs/documents/data-table.tsx new file mode 100644 index 00000000..178ccad9 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-docs/documents/data-table.tsx @@ -0,0 +1,81 @@ +'use client'; + +import { + ColumnDef, + flexRender, + getCoreRowModel, + useReactTable, +} from '@tanstack/react-table'; +import { + Table, + TableBody, + TableCell, + TableHead, + TableHeader, + TableRow, +} from '@/components/ui/table'; +import { useTranslation } from 'react-i18next'; + +interface DataTableProps { + columns: ColumnDef[]; + data: TData[]; +} + +export function DataTable({ + columns, + data, +}: DataTableProps) { + const { t } = useTranslation(); + const table = useReactTable({ + data, + columns, + getCoreRowModel: getCoreRowModel(), + }); + + return ( +
+ + + {table.getHeaderGroups().map((headerGroup) => ( + + {headerGroup.headers.map((header) => { + return ( + + {header.isPlaceholder + ? null + : flexRender( + header.column.columnDef.header, + header.getContext(), + )} + + ); + })} + + ))} + + + {table.getRowModel().rows?.length ? ( + table.getRowModel().rows.map((row) => ( + + {row.getVisibleCells().map((cell) => ( + + {flexRender(cell.column.columnDef.cell, cell.getContext())} + + ))} + + )) + ) : ( + + + {t('knowledge.documentsTab.noResults')} + + + )} + +
+
+ ); +} diff --git a/web/src/app/home/knowledge/components/kb-form/ChooseEntity.ts b/web/src/app/home/knowledge/components/kb-form/ChooseEntity.ts new file mode 100644 index 00000000..54f983e4 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-form/ChooseEntity.ts @@ -0,0 +1,4 @@ +export interface IEmbeddingModelEntity { + label: string; + value: string; +} diff --git a/web/src/app/home/knowledge/components/kb-form/KBForm.tsx b/web/src/app/home/knowledge/components/kb-form/KBForm.tsx new file mode 100644 index 00000000..0804ee12 --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-form/KBForm.tsx @@ -0,0 +1,267 @@ +import { useEffect, useState } from 'react'; +import { useForm } from 'react-hook-form'; +import { zodResolver } from '@hookform/resolvers/zod'; +import { z } from 'zod'; +import { useTranslation } from 'react-i18next'; +import { Input } from '@/components/ui/input'; +import { + Form, + FormControl, + FormField, + FormItem, + FormLabel, + FormMessage, + FormDescription, +} from '@/components/ui/form'; +import { IEmbeddingModelEntity } from './ChooseEntity'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { + Select, + SelectContent, + SelectGroup, + SelectItem, + SelectTrigger, + SelectValue, +} from '@/components/ui/select'; +import { KnowledgeBase } from '@/app/infra/entities/api'; +import { toast } from 'sonner'; + +const getFormSchema = (t: (key: string) => string) => + z.object({ + name: z.string().min(1, { message: t('knowledge.kbNameRequired') }), + description: z + .string() + .min(1, { message: t('knowledge.kbDescriptionRequired') }), + embeddingModelUUID: z + .string() + .min(1, { message: t('knowledge.embeddingModelUUIDRequired') }), + top_k: z + .number() + .min(1, { message: t('knowledge.topKRequired') }) + .max(30, { message: t('knowledge.topKMax') }), + }); + +export default function KBForm({ + initKbId, + onNewKbCreated, + onKbUpdated, +}: { + initKbId?: string; + onNewKbCreated: (kbId: string) => void; + onKbUpdated: (kbId: string) => void; +}) { + const { t } = useTranslation(); + const formSchema = getFormSchema(t); + + const form = useForm>({ + resolver: zodResolver(formSchema), + defaultValues: { + name: '', + description: t('knowledge.defaultDescription'), + embeddingModelUUID: '', + top_k: 5, + }, + }); + + const [embeddingModelNameList, setEmbeddingModelNameList] = useState< + IEmbeddingModelEntity[] + >([]); + + useEffect(() => { + getEmbeddingModelNameList().then(() => { + if (initKbId) { + getKbConfig(initKbId).then((val) => { + form.setValue('name', val.name); + form.setValue('description', val.description); + form.setValue('embeddingModelUUID', val.embeddingModelUUID); + form.setValue('top_k', val.top_k || 5); + }); + } + }); + }, []); + + const getKbConfig = async ( + kbId: string, + ): Promise> => { + return new Promise((resolve) => { + httpClient.getKnowledgeBase(kbId).then((res) => { + resolve({ + name: res.base.name, + description: res.base.description, + embeddingModelUUID: res.base.embedding_model_uuid, + top_k: res.base.top_k || 5, + }); + }); + }); + }; + + const getEmbeddingModelNameList = async () => { + const resp = await httpClient.getProviderEmbeddingModels(); + setEmbeddingModelNameList( + resp.models.map((item) => { + return { + label: item.name, + value: item.uuid, + }; + }), + ); + }; + + const onSubmit = (data: z.infer) => { + console.log('data', data); + + if (initKbId) { + // update knowledge base + const updateKb: KnowledgeBase = { + name: data.name, + description: data.description, + embedding_model_uuid: data.embeddingModelUUID, + top_k: data.top_k, + }; + httpClient + .updateKnowledgeBase(initKbId, updateKb) + .then((res) => { + console.log('update knowledge base success', res); + onKbUpdated(res.uuid); + toast.success(t('knowledge.updateKnowledgeBaseSuccess')); + }) + .catch((err) => { + console.error('update knowledge base failed', err); + toast.error(t('knowledge.updateKnowledgeBaseFailed')); + }); + } else { + // create knowledge base + const newKb: KnowledgeBase = { + name: data.name, + description: data.description, + embedding_model_uuid: data.embeddingModelUUID, + top_k: data.top_k, + }; + httpClient + .createKnowledgeBase(newKb) + .then((res) => { + console.log('create knowledge base success', res); + onNewKbCreated(res.uuid); + }) + .catch((err) => { + console.error('create knowledge base failed', err); + }); + } + }; + + return ( + <> +
+ +
+ ( + + + {t('knowledge.kbName')} + * + + + + + + + )} + /> + ( + + + {t('knowledge.kbDescription')} + * + + + + + + + )} + /> + ( + + + {t('knowledge.embeddingModelUUID')} + * + + +
+ +
+ + + {initKbId + ? t('knowledge.cannotChangeEmbeddingModel') + : t('knowledge.embeddingModelDescription')} + + + + )} + /> + ( + + + {t('knowledge.topK')} + * + + + field.onChange(Number(e.target.value))} + className="w-[180px] h-10 text-base appearance-none" + /> + + + {t('knowledge.topKdescription')} + + + + )} + /> +
+
+ + + ); +} diff --git a/web/src/app/home/knowledge/components/kb-retrieve/KBRetrieve.tsx b/web/src/app/home/knowledge/components/kb-retrieve/KBRetrieve.tsx new file mode 100644 index 00000000..1db7d11d --- /dev/null +++ b/web/src/app/home/knowledge/components/kb-retrieve/KBRetrieve.tsx @@ -0,0 +1,99 @@ +'use client'; + +import React, { useState, useEffect } from 'react'; +import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'; +import { Button } from '@/components/ui/button'; +import { Input } from '@/components/ui/input'; +import { useTranslation } from 'react-i18next'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { RetrieveResult, KnowledgeBaseFile } from '@/app/infra/entities/api'; +import { toast } from 'sonner'; + +interface KBRetrieveProps { + kbId: string; +} + +export default function KBRetrieve({ kbId }: KBRetrieveProps) { + const { t } = useTranslation(); + const [query, setQuery] = useState(''); + const [results, setResults] = useState([]); + const [files, setFiles] = useState([]); + const [loading, setLoading] = useState(false); + + useEffect(() => { + const loadFiles = async () => { + try { + const response = await httpClient.getKnowledgeBaseFiles(kbId); + setFiles(response.files); + } catch (error) { + console.error('Failed to load files:', error); + } + }; + loadFiles(); + }, [kbId]); + + const handleRetrieve = async () => { + if (!query.trim()) return; + + setLoading(true); + try { + setResults([]); + const response = await httpClient.retrieveKnowledgeBase(kbId, query); + setResults(response.results); + } catch (error) { + console.error('Retrieve failed:', error); + toast.error(t('knowledge.retrieveError')); + } finally { + setLoading(false); + } + }; + + const getFileName = (fileId: string) => { + const file = files.find((f) => f.uuid === fileId); + return file?.file_name || fileId; + }; + + return ( +
+
+ setQuery(e.target.value)} + placeholder={t('knowledge.queryPlaceholder')} + onKeyPress={(e) => e.key === 'Enter' && handleRetrieve()} + /> + +
+ +
+ {results.length === 0 && !loading && ( +

{t('knowledge.noResults')}

+ )} + + {loading ? ( +

{t('common.loading')}

+ ) : ( + results.map((result) => ( + + + + {getFileName(result.metadata.file_id)} + + {t('knowledge.distance')}: {result.distance.toFixed(4)} + + + + +

+ {result.metadata.text} +

+ + + )) + )} +
+
+ ); +} diff --git a/web/src/app/home/knowledge/knowledgeBase.module.css b/web/src/app/home/knowledge/knowledgeBase.module.css new file mode 100644 index 00000000..e811b521 --- /dev/null +++ b/web/src/app/home/knowledge/knowledgeBase.module.css @@ -0,0 +1,15 @@ +.configPageContainer { + width: 100%; + height: 100%; +} + +.knowledgeListContainer { + width: 100%; + padding-left: 0.8rem; + padding-right: 0.8rem; + display: grid; + grid-template-columns: repeat(auto-fill, minmax(24rem, 1fr)); + gap: 2rem; + justify-items: stretch; + align-items: start; +} diff --git a/web/src/app/home/knowledge/page.tsx b/web/src/app/home/knowledge/page.tsx new file mode 100644 index 00000000..85e99c56 --- /dev/null +++ b/web/src/app/home/knowledge/page.tsx @@ -0,0 +1,115 @@ +'use client'; + +import CreateCardComponent from '@/app/infra/basic-component/create-card-component/CreateCardComponent'; +import styles from './knowledgeBase.module.css'; +import { useTranslation } from 'react-i18next'; +import { useEffect, useState } from 'react'; +import { KnowledgeBaseVO } from '@/app/home/knowledge/components/kb-card/KBCardVO'; +import KBCard from '@/app/home/knowledge/components/kb-card/KBCard'; +import KBDetailDialog from '@/app/home/knowledge/KBDetailDialog'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { KnowledgeBase } from '@/app/infra/entities/api'; + +export default function KnowledgePage() { + const { t } = useTranslation(); + const [knowledgeBaseList, setKnowledgeBaseList] = useState( + [], + ); + const [selectedKbId, setSelectedKbId] = useState(''); + const [detailDialogOpen, setDetailDialogOpen] = useState(false); + + useEffect(() => { + getKnowledgeBaseList(); + }, []); + + async function getKnowledgeBaseList() { + const resp = await httpClient.getKnowledgeBases(); + setKnowledgeBaseList( + resp.bases.map((kb: KnowledgeBase) => { + const currentTime = new Date(); + const lastUpdatedTimeAgo = Math.floor( + (currentTime.getTime() - + new Date(kb.updated_at ?? currentTime.getTime()).getTime()) / + 1000 / + 60 / + 60 / + 24, + ); + + const lastUpdatedTimeAgoText = + lastUpdatedTimeAgo > 0 + ? ` ${lastUpdatedTimeAgo} ${t('knowledge.daysAgo')}` + : t('knowledge.today'); + + return new KnowledgeBaseVO({ + id: kb.uuid || '', + name: kb.name, + description: kb.description, + embeddingModelUUID: kb.embedding_model_uuid, + top_k: kb.top_k ?? 5, + lastUpdatedTimeAgo: lastUpdatedTimeAgoText, + }); + }), + ); + } + + const handleKBCardClick = (kbId: string) => { + setSelectedKbId(kbId); + setDetailDialogOpen(true); + }; + + const handleCreateKBClick = () => { + setSelectedKbId(''); + setDetailDialogOpen(true); + }; + + const handleFormCancel = () => { + setDetailDialogOpen(false); + }; + + const handleKbDeleted = () => { + getKnowledgeBaseList(); + setDetailDialogOpen(false); + }; + + const handleNewKbCreated = (newKbId: string) => { + getKnowledgeBaseList(); + setSelectedKbId(newKbId); + setDetailDialogOpen(true); + }; + + const handleKbUpdated = () => { + getKnowledgeBaseList(); + }; + + return ( +
+ + +
+ + + {knowledgeBaseList.map((kb) => { + return ( +
handleKBCardClick(kb.id)}> + +
+ ); + })} +
+
+ ); +} diff --git a/web/src/app/home/layout.module.css b/web/src/app/home/layout.module.css index 78a11beb..ad9725ca 100644 --- a/web/src/app/home/layout.module.css +++ b/web/src/app/home/layout.module.css @@ -7,6 +7,19 @@ background-color: #eee; } +:global(.dark) .homeLayoutContainer { + background-color: #0a0a0b; +} + +/* 侧边栏区域 */ +.sidebar { + background-color: #eee; +} + +:global(.dark) .sidebar { + background-color: #0a0a0b; +} + /* 主内容区域 */ .main { background-color: #fafafa; @@ -23,6 +36,11 @@ box-shadow: 0 0 6px 0 rgba(0, 0, 0, 0.05); } +:global(.dark) .main { + background-color: #151518; + box-shadow: 0 0 6px 0 rgba(255, 255, 255, 0.05); +} + .mainContent { padding: 1.5rem; padding-left: 2rem; @@ -30,3 +48,7 @@ overflow-y: auto; background-color: #fafafa; } + +:global(.dark) .mainContent { + background-color: #151518; +} diff --git a/web/src/app/home/models/component/llm-form/ChooseRequesterEntity.ts b/web/src/app/home/models/component/ChooseRequesterEntity.ts similarity index 100% rename from web/src/app/home/models/component/llm-form/ChooseRequesterEntity.ts rename to web/src/app/home/models/component/ChooseRequesterEntity.ts diff --git a/web/src/app/home/models/component/ICreateEmbeddingField.ts b/web/src/app/home/models/component/ICreateEmbeddingField.ts new file mode 100644 index 00000000..ea198f3f --- /dev/null +++ b/web/src/app/home/models/component/ICreateEmbeddingField.ts @@ -0,0 +1,7 @@ +export interface ICreateEmbeddingField { + name: string; + model_provider: string; + url: string; + api_key: string; + extra_args?: string[]; +} diff --git a/web/src/app/home/models/ICreateLLMField.ts b/web/src/app/home/models/component/ICreateLLMField.ts similarity index 100% rename from web/src/app/home/models/ICreateLLMField.ts rename to web/src/app/home/models/component/ICreateLLMField.ts diff --git a/web/src/app/home/models/component/embedding-card/EmbeddingCard.module.css b/web/src/app/home/models/component/embedding-card/EmbeddingCard.module.css new file mode 100644 index 00000000..9545619b --- /dev/null +++ b/web/src/app/home/models/component/embedding-card/EmbeddingCard.module.css @@ -0,0 +1,128 @@ +.cardContainer { + width: 100%; + height: 10rem; + background-color: #fff; + border-radius: 10px; + box-shadow: 0px 2px 2px 0 rgba(0, 0, 0, 0.2); + padding: 1.2rem; + cursor: pointer; + transition: all 0.2s ease; +} + +:global(.dark) .cardContainer { + background-color: #1f1f22; + box-shadow: 0; +} + +.cardContainer:hover { + box-shadow: 0px 2px 8px 0 rgba(0, 0, 0, 0.1); +} + +:global(.dark) .cardContainer:hover { + box-shadow: 0; +} + +.iconBasicInfoContainer { + width: 100%; + height: 100%; + display: flex; + flex-direction: row; + gap: 0.8rem; + user-select: none; +} + +.iconImage { + width: 3.8rem; + height: 3.8rem; + margin: 0.2rem; + border-radius: 50%; +} + +.basicInfoContainer { + display: flex; + flex-direction: column; + gap: 0.2rem; + min-width: 0; + width: 100%; +} + +.basicInfoText { + font-size: 1.4rem; + font-weight: bold; + color: #1a1a1a; +} + +:global(.dark) .basicInfoText { + color: #f0f0f0; +} + +.providerContainer { + display: flex; + flex-direction: row; + align-items: center; + justify-content: flex-start; + gap: 0.2rem; +} + +.providerIcon { + width: 1.2rem; + height: 1.2rem; + margin-top: 0.2rem; + color: #626262; +} + +:global(.dark) .providerIcon { + color: #a0a0a0; +} + +.providerLabel { + font-size: 1.2rem; + font-weight: 600; + color: #626262; +} + +:global(.dark) .providerLabel { + color: #a0a0a0; +} + +.baseURLContainer { + display: flex; + flex-direction: row; + align-items: center; + justify-content: flex-start; + gap: 0.2rem; + width: calc(100% - 3rem); +} + +.baseURLIcon { + width: 1.2rem; + height: 1.2rem; + color: #626262; +} + +:global(.dark) .baseURLIcon { + color: #a0a0a0; +} + +.baseURLText { + font-size: 1rem; + width: 100%; + color: #626262; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; + max-width: 100%; +} + +:global(.dark) .baseURLText { + color: #a0a0a0; +} + +.bigText { + white-space: nowrap; + overflow: hidden; + text-overflow: ellipsis; + font-size: 1.4rem; + font-weight: bold; + max-width: 100%; +} diff --git a/web/src/app/home/models/component/embedding-card/EmbeddingCard.tsx b/web/src/app/home/models/component/embedding-card/EmbeddingCard.tsx new file mode 100644 index 00000000..e3dfaf80 --- /dev/null +++ b/web/src/app/home/models/component/embedding-card/EmbeddingCard.tsx @@ -0,0 +1,53 @@ +import styles from './EmbeddingCard.module.css'; +import { EmbeddingCardVO } from '@/app/home/models/component/embedding-card/EmbeddingCardVO'; + +export default function EmbeddingCard({ cardVO }: { cardVO: EmbeddingCardVO }) { + return ( +
+
+ icon + +
+ {/* 名称 */} +
+ {cardVO.name} +
+ {/* 厂商 */} +
+ + + + + {cardVO.providerLabel} + +
+ {/* baseURL */} +
+ + + + {cardVO.baseURL} +
+
+
+
+ ); +} diff --git a/web/src/app/home/models/component/embedding-card/EmbeddingCardVO.ts b/web/src/app/home/models/component/embedding-card/EmbeddingCardVO.ts new file mode 100644 index 00000000..f6d960f6 --- /dev/null +++ b/web/src/app/home/models/component/embedding-card/EmbeddingCardVO.ts @@ -0,0 +1,23 @@ +export interface IEmbeddingCardVO { + id: string; + iconURL: string; + name: string; + providerLabel: string; + baseURL: string; +} + +export class EmbeddingCardVO implements IEmbeddingCardVO { + id: string; + iconURL: string; + providerLabel: string; + name: string; + baseURL: string; + + constructor(props: IEmbeddingCardVO) { + this.id = props.id; + this.iconURL = props.iconURL; + this.providerLabel = props.providerLabel; + this.name = props.name; + this.baseURL = props.baseURL; + } +} diff --git a/web/src/app/home/models/component/embedding-form/EmbeddingForm.tsx b/web/src/app/home/models/component/embedding-form/EmbeddingForm.tsx new file mode 100644 index 00000000..eee02b5a --- /dev/null +++ b/web/src/app/home/models/component/embedding-form/EmbeddingForm.tsx @@ -0,0 +1,579 @@ +import { ICreateEmbeddingField } from '@/app/home/models/component/ICreateEmbeddingField'; +import { useEffect, useState } from 'react'; +import { IChooseRequesterEntity } from '@/app/home/models/component/ChooseRequesterEntity'; +import { httpClient } from '@/app/infra/http/HttpClient'; +import { EmbeddingModel } from '@/app/infra/entities/api'; +import { UUID } from 'uuidjs'; + +import { zodResolver } from '@hookform/resolvers/zod'; +import { useForm } from 'react-hook-form'; +import { z } from 'zod'; +import { useTranslation } from 'react-i18next'; + +import { + Dialog, + DialogContent, + DialogDescription, + DialogHeader, + DialogTitle, + DialogFooter, +} from '@/components/ui/dialog'; +import { Button } from '@/components/ui/button'; +import { + Form, + FormControl, + FormDescription, + FormField, + FormItem, + FormLabel, + FormMessage, +} from '@/components/ui/form'; +import { Input } from '@/components/ui/input'; +import { + Select, + SelectContent, + SelectGroup, + SelectItem, + SelectTrigger, + SelectValue, +} from '@/components/ui/select'; +import { toast } from 'sonner'; +import { i18nObj } from '@/i18n/I18nProvider'; + +const getExtraArgSchema = (t: (key: string) => string) => + z + .object({ + key: z.string().min(1, { message: t('models.keyNameRequired') }), + type: z.enum(['string', 'number', 'boolean']), + value: z.string(), + }) + .superRefine((data, ctx) => { + if (data.type === 'number' && isNaN(Number(data.value))) { + ctx.addIssue({ + code: z.ZodIssueCode.custom, + message: t('models.mustBeValidNumber'), + path: ['value'], + }); + } + if ( + data.type === 'boolean' && + data.value !== 'true' && + data.value !== 'false' + ) { + ctx.addIssue({ + code: z.ZodIssueCode.custom, + message: t('models.mustBeTrueOrFalse'), + path: ['value'], + }); + } + }); + +const getFormSchema = (t: (key: string) => string) => + z.object({ + name: z.string().min(1, { message: t('models.modelNameRequired') }), + model_provider: z + .string() + .min(1, { message: t('models.modelProviderRequired') }), + url: z.string().min(1, { message: t('models.requestURLRequired') }), + api_key: z.string().min(1, { message: t('models.apiKeyRequired') }), + extra_args: z.array(getExtraArgSchema(t)).optional(), + }); + +export default function EmbeddingForm({ + editMode, + initEmbeddingId, + onFormSubmit, + onFormCancel, + onEmbeddingDeleted, +}: { + editMode: boolean; + initEmbeddingId?: string; + onFormSubmit: () => void; + onFormCancel: () => void; + onEmbeddingDeleted: () => void; +}) { + const { t } = useTranslation(); + const formSchema = getFormSchema(t); + + const form = useForm>({ + resolver: zodResolver(formSchema), + defaultValues: { + name: '', + model_provider: '', + url: '', + api_key: 'sk-xxxxx', + extra_args: [], + }, + }); + + const [extraArgs, setExtraArgs] = useState< + { key: string; type: 'string' | 'number' | 'boolean'; value: string }[] + >([]); + + const [showDeleteConfirmModal, setShowDeleteConfirmModal] = useState(false); + const [requesterNameList, setRequesterNameList] = useState< + IChooseRequesterEntity[] + >([]); + const [requesterDefaultURLList, setRequesterDefaultURLList] = useState< + string[] + >([]); + const [modelTesting, setModelTesting] = useState(false); + const [currentModelProvider, setCurrentModelProvider] = useState(''); + + useEffect(() => { + initEmbeddingModelFormComponent().then(() => { + if (editMode && initEmbeddingId) { + getEmbeddingConfig(initEmbeddingId).then((val) => { + form.setValue('name', val.name); + form.setValue('model_provider', val.model_provider); + setCurrentModelProvider(val.model_provider); + form.setValue('url', val.url); + form.setValue('api_key', val.api_key); + if (val.extra_args) { + const args = val.extra_args.map((arg) => { + const [key, value] = arg.split(':'); + let type: 'string' | 'number' | 'boolean' = 'string'; + if (!isNaN(Number(value))) { + type = 'number'; + } else if (value === 'true' || value === 'false') { + type = 'boolean'; + } + return { + key, + type, + value, + }; + }); + setExtraArgs(args); + form.setValue('extra_args', args); + } + }); + } else { + form.reset(); + } + }); + }, []); + + const addExtraArg = () => { + setExtraArgs([...extraArgs, { key: '', type: 'string', value: '' }]); + }; + + const updateExtraArg = ( + index: number, + field: 'key' | 'type' | 'value', + value: string, + ) => { + const newArgs = [...extraArgs]; + newArgs[index] = { + ...newArgs[index], + [field]: value, + }; + setExtraArgs(newArgs); + form.setValue('extra_args', newArgs); + }; + + const removeExtraArg = (index: number) => { + const newArgs = extraArgs.filter((_, i) => i !== index); + setExtraArgs(newArgs); + form.setValue('extra_args', newArgs); + }; + + async function initEmbeddingModelFormComponent() { + const requesterNameList = + await httpClient.getProviderRequesters('text-embedding'); + setRequesterNameList( + requesterNameList.requesters.map((item) => { + return { + label: i18nObj(item.label), + value: item.name, + }; + }), + ); + setRequesterDefaultURLList( + requesterNameList.requesters.map((item) => { + const config = item.spec.config; + for (let i = 0; i < config.length; i++) { + if (config[i].name == 'base_url') { + return config[i].default?.toString() || ''; + } + } + return ''; + }), + ); + } + + async function getEmbeddingConfig( + id: string, + ): Promise { + const embeddingModel = await httpClient.getProviderEmbeddingModel(id); + + const fakeExtraArgs = []; + const extraArgs = embeddingModel.model.extra_args as Record; + for (const key in extraArgs) { + fakeExtraArgs.push(`${key}:${extraArgs[key]}`); + } + return { + name: embeddingModel.model.name, + model_provider: embeddingModel.model.requester, + url: embeddingModel.model.requester_config?.base_url, + api_key: embeddingModel.model.api_keys[0], + extra_args: fakeExtraArgs, + }; + } + + function handleFormSubmit(value: z.infer) { + const extraArgsObj: Record = {}; + value.extra_args?.forEach( + (arg: { key: string; type: string; value: string }) => { + if (arg.type === 'number') { + extraArgsObj[arg.key] = Number(arg.value); + } else if (arg.type === 'boolean') { + extraArgsObj[arg.key] = arg.value === 'true'; + } else { + extraArgsObj[arg.key] = arg.value; + } + }, + ); + + const embeddingModel: EmbeddingModel = { + uuid: editMode ? initEmbeddingId || '' : UUID.generate(), + name: value.name, + description: '', + requester: value.model_provider, + requester_config: { + base_url: value.url, + timeout: 120, + }, + extra_args: extraArgsObj, + api_keys: [value.api_key], + }; + + if (editMode) { + onSaveEdit(embeddingModel).then(() => { + form.reset(); + }); + } else { + onCreateEmbedding(embeddingModel).then(() => { + form.reset(); + }); + } + } + + async function onCreateEmbedding(embeddingModel: EmbeddingModel) { + try { + await httpClient.createProviderEmbeddingModel(embeddingModel); + onFormSubmit(); + toast.success(t('models.createSuccess')); + } catch (err) { + toast.error(t('models.createError') + (err as Error).message); + } + } + + async function onSaveEdit(embeddingModel: EmbeddingModel) { + try { + await httpClient.updateProviderEmbeddingModel( + initEmbeddingId || '', + embeddingModel, + ); + onFormSubmit(); + toast.success(t('models.saveSuccess')); + } catch (err) { + toast.error(t('models.saveError') + (err as Error).message); + } + } + + function deleteModel() { + if (initEmbeddingId) { + httpClient + .deleteProviderEmbeddingModel(initEmbeddingId) + .then(() => { + onEmbeddingDeleted(); + toast.success(t('models.deleteSuccess')); + }) + .catch((err) => { + toast.error(t('models.deleteError') + err.message); + }); + } + } + + function testEmbeddingModelInForm() { + setModelTesting(true); + const extraArgsObj: Record = {}; + form + .getValues('extra_args') + ?.forEach((arg: { key: string; type: string; value: string }) => { + if (arg.type === 'number') { + extraArgsObj[arg.key] = Number(arg.value); + } else if (arg.type === 'boolean') { + extraArgsObj[arg.key] = arg.value === 'true'; + } else { + extraArgsObj[arg.key] = arg.value; + } + }); + httpClient + .testEmbeddingModel('_', { + uuid: '', + name: form.getValues('name'), + description: '', + requester: form.getValues('model_provider'), + requester_config: { + base_url: form.getValues('url'), + timeout: 120, + }, + api_keys: [form.getValues('api_key')], + extra_args: extraArgsObj, + }) + .then((res) => { + console.log(res); + toast.success(t('models.testSuccess')); + }) + .catch(() => { + toast.error(t('models.testError')); + }) + .finally(() => { + setModelTesting(false); + }); + } + + return ( +
+ + + + {t('common.confirmDelete')} + + + {t('models.deleteConfirmation')} + + + + + + + + +
+ +
+ ( + + + {t('models.modelName')} + * + + + + + + + {t('models.modelProviderDescription')} + + + )} + /> + + ( + + + {t('models.modelProvider')} + * + + + + + + + )} + /> + + ( + + + {t('models.requestURL')} + * + + + + + + + )} + /> + + {!['ollama-chat'].includes(currentModelProvider) && ( + ( + + + {t('models.apiKey')} + * + + + + + + + )} + /> + )} + + + {t('models.extraParameters')} +
+ {extraArgs.map((arg, index) => ( +
+ + updateExtraArg(index, 'key', e.target.value) + } + /> + + + updateExtraArg(index, 'value', e.target.value) + } + /> + +
+ ))} + +
+ + {t('embedding.extraParametersDescription')} + + + +
+ + {editMode && ( + + )} + + + + + + + +
+ +
+ ); +} diff --git a/web/src/app/home/models/component/llm-card/LLMCard.module.css b/web/src/app/home/models/component/llm-card/LLMCard.module.css index b6d1ac6f..aedbebde 100644 --- a/web/src/app/home/models/component/llm-card/LLMCard.module.css +++ b/web/src/app/home/models/component/llm-card/LLMCard.module.css @@ -6,12 +6,22 @@ box-shadow: 0px 2px 2px 0 rgba(0, 0, 0, 0.2); padding: 1.2rem; cursor: pointer; + transition: all 0.2s ease; +} + +:global(.dark) .cardContainer { + background-color: #1f1f22; + box-shadow: 0; } .cardContainer:hover { box-shadow: 0px 2px 8px 0 rgba(0, 0, 0, 0.1); } +:global(.dark) .cardContainer:hover { + box-shadow: 0; +} + .iconBasicInfoContainer { width: 100%; height: 100%; @@ -40,6 +50,11 @@ .basicInfoText { font-size: 1.4rem; font-weight: bold; + color: #1a1a1a; +} + +:global(.dark) .basicInfoText { + color: #f0f0f0; } .providerContainer { @@ -57,12 +72,20 @@ color: #626262; } +:global(.dark) .providerIcon { + color: #a0a0a0; +} + .providerLabel { font-size: 1.2rem; font-weight: 600; color: #626262; } +:global(.dark) .providerLabel { + color: #a0a0a0; +} + .baseURLContainer { display: flex; flex-direction: row; @@ -78,6 +101,10 @@ color: #626262; } +:global(.dark) .baseURLIcon { + color: #a0a0a0; +} + .baseURLText { font-size: 1rem; width: 100%; @@ -88,6 +115,10 @@ max-width: 100%; } +:global(.dark) .baseURLText { + color: #a0a0a0; +} + .abilitiesContainer { display: flex; flex-direction: row; @@ -108,18 +139,30 @@ background-color: #66baff80; } +:global(.dark) .abilityBadge { + background-color: rgba(34, 136, 238, 0.3); +} + .abilityIcon { width: 1rem; height: 1rem; color: #2288ee; } +:global(.dark) .abilityIcon { + color: #66baff; +} + .abilityLabel { font-size: 0.8rem; font-weight: 400; color: #2288ee; } +:global(.dark) .abilityLabel { + color: #66baff; +} + .bigText { white-space: nowrap; overflow: hidden; diff --git a/web/src/app/home/models/component/llm-form/LLMForm.tsx b/web/src/app/home/models/component/llm-form/LLMForm.tsx index 3f023336..6d46da6d 100644 --- a/web/src/app/home/models/component/llm-form/LLMForm.tsx +++ b/web/src/app/home/models/component/llm-form/LLMForm.tsx @@ -1,6 +1,6 @@ -import { ICreateLLMField } from '@/app/home/models/ICreateLLMField'; +import { ICreateLLMField } from '@/app/home/models/component/ICreateLLMField'; import { useEffect, useState } from 'react'; -import { IChooseRequesterEntity } from '@/app/home/models/component/llm-form/ChooseRequesterEntity'; +import { IChooseRequesterEntity } from '@/app/home/models/component/ChooseRequesterEntity'; import { httpClient } from '@/app/infra/http/HttpClient'; import { LLMModel } from '@/app/infra/entities/api'; import { UUID } from 'uuidjs'; @@ -197,7 +197,7 @@ export default function LLMForm({ }; async function initLLMModelFormComponent() { - const requesterNameList = await httpClient.getProviderRequesters(); + const requesterNameList = await httpClient.getProviderRequesters('llm'); setRequesterNameList( requesterNameList.requesters.map((item) => { return { @@ -312,6 +312,18 @@ export default function LLMForm({ function testLLMModelInForm() { setModelTesting(true); + const extraArgsObj: Record = {}; + form + .getValues('extra_args') + ?.forEach((arg: { key: string; type: string; value: string }) => { + if (arg.type === 'number') { + extraArgsObj[arg.key] = Number(arg.value); + } else if (arg.type === 'boolean') { + extraArgsObj[arg.key] = arg.value === 'true'; + } else { + extraArgsObj[arg.key] = arg.value; + } + }); httpClient .testLLMModel('_', { uuid: '', @@ -324,7 +336,7 @@ export default function LLMForm({ }, api_keys: [form.getValues('api_key')], abilities: form.getValues('abilities'), - extra_args: form.getValues('extra_args'), + extra_args: extraArgsObj, }) .then((res) => { console.log(res); @@ -420,7 +432,7 @@ export default function LLMForm({ }} value={field.value} > - + @@ -553,7 +565,7 @@ export default function LLMForm({ updateExtraArg(index, 'type', value) } > - + @@ -596,7 +608,7 @@ export default function LLMForm({
- {t('models.extraParametersDescription')} + {t('llm.extraParametersDescription')} diff --git a/web/src/app/home/models/page.tsx b/web/src/app/home/models/page.tsx index 5b23622d..9a3a1597 100644 --- a/web/src/app/home/models/page.tsx +++ b/web/src/app/home/models/page.tsx @@ -8,6 +8,7 @@ import LLMForm from '@/app/home/models/component/llm-form/LLMForm'; import CreateCardComponent from '@/app/infra/basic-component/create-card-component/CreateCardComponent'; import { httpClient } from '@/app/infra/http/HttpClient'; import { LLMModel } from '@/app/infra/entities/api'; +import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs'; import { Dialog, DialogContent, @@ -17,6 +18,9 @@ import { import { toast } from 'sonner'; import { useTranslation } from 'react-i18next'; import { extractI18nObject } from '@/i18n/I18nProvider'; +import { EmbeddingCardVO } from '@/app/home/models/component/embedding-card/EmbeddingCardVO'; +import EmbeddingCard from '@/app/home/models/component/embedding-card/EmbeddingCard'; +import EmbeddingForm from '@/app/home/models/component/embedding-form/EmbeddingForm'; export default function LLMConfigPage() { const { t } = useTranslation(); @@ -24,13 +28,21 @@ export default function LLMConfigPage() { const [modalOpen, setModalOpen] = useState(false); const [isEditForm, setIsEditForm] = useState(false); const [nowSelectedLLM, setNowSelectedLLM] = useState(null); + const [embeddingCardList, setEmbeddingCardList] = useState( + [], + ); + const [embeddingModalOpen, setEmbeddingModalOpen] = useState(false); + const [isEditEmbeddingForm, setIsEditEmbeddingForm] = useState(false); + const [nowSelectedEmbedding, setNowSelectedEmbedding] = + useState(null); useEffect(() => { getLLMModelList(); + getEmbeddingModelList(); }, []); async function getLLMModelList() { - const requesterNameListResp = await httpClient.getProviderRequesters(); + const requesterNameListResp = await httpClient.getProviderRequesters('llm'); const requesterNameList = requesterNameListResp.requesters.map((item) => { return { label: extractI18nObject(item.label), @@ -74,6 +86,55 @@ export default function LLMConfigPage() { setNowSelectedLLM(null); setModalOpen(true); } + function selectEmbedding(cardVO: EmbeddingCardVO) { + setIsEditEmbeddingForm(true); + setNowSelectedEmbedding(cardVO); + setEmbeddingModalOpen(true); + } + + function handleCreateEmbeddingModelClick() { + setIsEditEmbeddingForm(false); + setNowSelectedEmbedding(null); + setEmbeddingModalOpen(true); + } + async function getEmbeddingModelList() { + const requesterNameListResp = + await httpClient.getProviderRequesters('text-embedding'); + const requesterNameList = requesterNameListResp.requesters.map((item) => { + return { + label: extractI18nObject(item.label), + value: item.name, + }; + }); + + httpClient + .getProviderEmbeddingModels() + .then((resp) => { + const embeddingModelList: EmbeddingCardVO[] = resp.models.map( + (model: { + uuid: string; + requester: string; + name: string; + requester_config?: { base_url?: string }; + }) => { + return new EmbeddingCardVO({ + id: model.uuid, + iconURL: httpClient.getProviderRequesterIconURL(model.requester), + name: model.name, + providerLabel: + requesterNameList.find((item) => item.value === model.requester) + ?.label || model.requester.substring(0, 10), + baseURL: model.requester_config?.base_url || '', + }); + }, + ); + setEmbeddingCardList(embeddingModelList); + }) + .catch((err) => { + console.error('get Embedding model list error', err); + toast.error(t('embedding.getModelListError') + err.message); + }); + } return (
@@ -101,26 +162,110 @@ export default function LLMConfigPage() { /> -
- - {cardList.map((cardVO) => { - return ( -
{ - selectLLM(cardVO); - }} - > - + + + + + {isEditEmbeddingForm + ? t('embedding.editModel') + : t('embedding.createModel')} + + + { + setEmbeddingModalOpen(false); + getEmbeddingModelList(); + }} + onFormCancel={() => { + setEmbeddingModalOpen(false); + }} + onEmbeddingDeleted={() => { + setEmbeddingModalOpen(false); + getEmbeddingModelList(); + }} + /> + + + + +
+
+ + + {t('llm.llmModels')} + + + {t('embedding.embeddingModels')} + + +
+ +
+

+ {t('llm.description')} +

- ); - })} -
+ + +
+

+ {t('embedding.description')} +

+
+ +
+ + +
+ + {cardList.map((cardVO) => { + return ( +
{ + selectLLM(cardVO); + }} + > + +
+ ); + })} +
+ + + +
+ + {embeddingCardList.map((cardVO) => { + return ( +
{ + selectEmbedding(cardVO); + }} + > + +
+ ); + })} +
+ +
); } diff --git a/web/src/app/home/pipelines/PipelineDetailDialog.tsx b/web/src/app/home/pipelines/PipelineDetailDialog.tsx index 72b4ac76..91b8b192 100644 --- a/web/src/app/home/pipelines/PipelineDetailDialog.tsx +++ b/web/src/app/home/pipelines/PipelineDetailDialog.tsx @@ -18,7 +18,6 @@ import { } from '@/components/ui/sidebar'; import PipelineFormComponent from './components/pipeline-form/PipelineFormComponent'; import DebugDialog from './components/debug-dialog/DebugDialog'; -import { PipelineFormEntity } from '@/app/infra/entities/pipeline'; interface PipelineDialogProps { open: boolean; @@ -26,7 +25,6 @@ interface PipelineDialogProps { pipelineId?: string; isEditMode?: boolean; isDefaultPipeline?: boolean; - initValues?: PipelineFormEntity; onFinish: () => void; onNewPipelineCreated?: (pipelineId: string) => void; onDeletePipeline: () => void; @@ -41,7 +39,6 @@ export default function PipelineDialog({ pipelineId: propPipelineId, isEditMode = false, isDefaultPipeline = false, - initValues, onFinish, onNewPipelineCreated, onDeletePipeline, @@ -119,7 +116,6 @@ export default function PipelineDialog({
@@ -184,7 +180,6 @@ export default function PipelineDialog({ > {currentMode === 'config' && ( @{targetName} {!readonly && onRemove && ( diff --git a/web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx b/web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx index a84389e0..71e5b748 100644 --- a/web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx +++ b/web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx @@ -1,4 +1,4 @@ -import React, { useState, useEffect, useRef } from 'react'; +import React, { useState, useEffect, useRef, useCallback } from 'react'; import { useTranslation } from 'react-i18next'; import { httpClient } from '@/app/infra/http/HttpClient'; import { DialogContent } from '@/components/ui/dialog'; @@ -10,6 +10,7 @@ import { cn } from '@/lib/utils'; import { Message } from '@/app/infra/entities/message'; import { toast } from 'sonner'; import AtBadge from './AtBadge'; +import { Switch } from '@/components/ui/switch'; interface MessageComponent { type: 'At' | 'Plain'; @@ -36,17 +37,44 @@ export default function DebugDialog({ const [showAtPopover, setShowAtPopover] = useState(false); const [hasAt, setHasAt] = useState(false); const [isHovering, setIsHovering] = useState(false); + const [isStreaming, setIsStreaming] = useState(true); const messagesEndRef = useRef(null); const inputRef = useRef(null); const popoverRef = useRef(null); - const scrollToBottom = () => { - messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }); - }; + const scrollToBottom = useCallback(() => { + // 使用setTimeout确保在DOM更新后执行滚动 + setTimeout(() => { + const scrollArea = document.querySelector('.scroll-area') as HTMLElement; + if (scrollArea) { + scrollArea.scrollTo({ + top: scrollArea.scrollHeight, + behavior: 'smooth', + }); + } + // 同时确保messagesEndRef也滚动到视图 + messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }); + }, 0); + }, []); + const loadMessages = useCallback( + async (pipelineId: string) => { + try { + const response = await httpClient.getWebChatHistoryMessages( + pipelineId, + sessionType, + ); + setMessages(response.messages); + } catch (error) { + console.error('Failed to load messages:', error); + } + }, + [sessionType], + ); + // 在useEffect中监听messages变化时滚动 useEffect(() => { scrollToBottom(); - }, [messages]); + }, [messages, scrollToBottom]); useEffect(() => { if (open) { @@ -59,7 +87,7 @@ export default function DebugDialog({ if (open) { loadMessages(selectedPipelineId); } - }, [sessionType, selectedPipelineId]); + }, [sessionType, selectedPipelineId, open, loadMessages]); useEffect(() => { const handleClickOutside = (event: MouseEvent) => { @@ -84,18 +112,6 @@ export default function DebugDialog({ } }, [showAtPopover]); - const loadMessages = async (pipelineId: string) => { - try { - const response = await httpClient.getWebChatHistoryMessages( - pipelineId, - sessionType, - ); - setMessages(response.messages); - } catch (error) { - console.error('Failed to load messages:', error); - } - }; - const handleInputChange = (e: React.ChangeEvent) => { const value = e.target.value; if (sessionType === 'group') { @@ -165,19 +181,87 @@ export default function DebugDialog({ timestamp: new Date().toISOString(), message_chain: messageChain, }; + // 根据isStreaming状态决定使用哪种传输方式 + if (isStreaming) { + // streaming + // 创建初始bot消息 + const placeholderRandomId = Math.floor(Math.random() * 1000000); + const botMessagePlaceholder: Message = { + id: placeholderRandomId, + role: 'assistant', + content: 'Generating...', + timestamp: new Date().toISOString(), + message_chain: [{ type: 'Plain', text: 'Generating...' }], + }; - setMessages((prevMessages) => [...prevMessages, userMessage]); - setInputValue(''); - setHasAt(false); + // 添加用户消息和初始bot消息到状态 - const response = await httpClient.sendWebChatMessage( - sessionType, - messageChain, - selectedPipelineId, - 120000, - ); + setMessages((prevMessages) => [ + ...prevMessages, + userMessage, + botMessagePlaceholder, + ]); + setInputValue(''); + setHasAt(false); + try { + await httpClient.sendStreamingWebChatMessage( + sessionType, + messageChain, + selectedPipelineId, + (data) => { + // 处理流式响应数据 + console.log('data', data); + if (data.message) { + // 更新完整内容 - setMessages((prevMessages) => [...prevMessages, response.message]); + setMessages((prevMessages) => { + const updatedMessages = [...prevMessages]; + const botMessageIndex = updatedMessages.findIndex( + (message) => message.id === placeholderRandomId, + ); + if (botMessageIndex !== -1) { + updatedMessages[botMessageIndex] = { + ...updatedMessages[botMessageIndex], + content: data.message.content, + message_chain: [ + { type: 'Plain', text: data.message.content }, + ], + }; + } + return updatedMessages; + }); + } + }, + () => {}, + (error) => { + // 处理错误 + console.error('Streaming error:', error); + if (sessionType === 'person') { + toast.error(t('pipelines.debugDialog.sendFailed')); + } + }, + ); + } catch (error) { + console.error('Failed to send streaming message:', error); + if (sessionType === 'person') { + toast.error(t('pipelines.debugDialog.sendFailed')); + } + } + } else { + // non-streaming + setMessages((prevMessages) => [...prevMessages, userMessage]); + setInputValue(''); + setHasAt(false); + + const response = await httpClient.sendWebChatMessage( + sessionType, + messageChain, + selectedPipelineId, + 180000, + ); + + setMessages((prevMessages) => [...prevMessages, response.message]); + } } catch ( // eslint-disable-next-line @typescript-eslint/no-explicit-any error: any @@ -218,14 +302,14 @@ export default function DebugDialog({ const renderContent = () => (
-
+
- +
{messages.length === 0 ? (
@@ -281,7 +365,7 @@ export default function DebugDialog({ 'max-w-md px-5 py-3 rounded-2xl', message.role === 'user' ? 'bg-[#2288ee] text-white rounded-br-none' - : 'bg-gray-100 text-gray-900 rounded-bl-none', + : 'bg-gray-100 dark:bg-gray-800 text-gray-900 dark:text-gray-100 rounded-bl-none', )} > {renderMessageContent(message)} @@ -290,7 +374,7 @@ export default function DebugDialog({ 'text-xs mt-2', message.role === 'user' ? 'text-white/70' - : 'text-gray-500', + : 'text-gray-500 dark:text-gray-400', )} > {message.role === 'user' @@ -305,7 +389,13 @@ export default function DebugDialog({
-
+
+
+ + {t('pipelines.debugDialog.streaming')} + + +
{hasAt && ( @@ -322,23 +412,25 @@ export default function DebugDialog({ ? t('pipelines.debugDialog.privateChat') : t('pipelines.debugDialog.groupChat'), })} - className="flex-1 rounded-md px-3 py-2 border border-gray-300 focus:border-[#2288ee] transition-none text-base" + className="flex-1 rounded-md px-3 py-2 border border-gray-300 dark:border-gray-600 dark:bg-gray-800 dark:text-gray-100 focus:border-[#2288ee] transition-none text-base" /> {showAtPopover && (
setIsHovering(true)} onMouseLeave={() => setIsHovering(false)} > - + @webchatbot - {t('pipelines.debugDialog.atTips')}
@@ -369,7 +461,7 @@ export default function DebugDialog({ // 原有的Dialog包装 return ( - + {renderContent()} ); diff --git a/web/src/app/home/pipelines/components/pipeline-card/pipelineCard.module.css b/web/src/app/home/pipelines/components/pipeline-card/pipelineCard.module.css index 2ecbd44a..d2bfebca 100644 --- a/web/src/app/home/pipelines/components/pipeline-card/pipelineCard.module.css +++ b/web/src/app/home/pipelines/components/pipeline-card/pipelineCard.module.css @@ -10,12 +10,22 @@ flex-direction: row; justify-content: space-between; gap: 0.5rem; + transition: all 0.2s ease; +} + +:global(.dark) .cardContainer { + background-color: #1f1f22; + box-shadow: 0; } .cardContainer:hover { box-shadow: 0px 2px 8px 0 rgba(0, 0, 0, 0.1); } +:global(.dark) .cardContainer:hover { + box-shadow: 0; +} + .basicInfoContainer { width: 100%; height: 100%; @@ -35,6 +45,11 @@ .basicInfoNameText { font-size: 1.4rem; font-weight: 500; + color: #1a1a1a; +} + +:global(.dark) .basicInfoNameText { + color: #f0f0f0; } .basicInfoDescriptionText { @@ -48,6 +63,10 @@ color: #b1b1b1; } +:global(.dark) .basicInfoDescriptionText { + color: #888888; +} + .basicInfoLastUpdatedTimeContainer { display: flex; flex-direction: row; @@ -58,11 +77,21 @@ .basicInfoUpdateTimeIcon { width: 1.2rem; height: 1.2rem; + color: #626262; +} + +:global(.dark) .basicInfoUpdateTimeIcon { + color: #a0a0a0; } .basicInfoUpdateTimeText { font-size: 1rem; font-weight: 400; + color: #626262; +} + +:global(.dark) .basicInfoUpdateTimeText { + color: #a0a0a0; } .operationContainer { @@ -86,12 +115,20 @@ color: #ffcd27; } +:global(.dark) .operationDefaultBadgeIcon { + color: #fbbf24; +} + .operationDefaultBadgeText { font-size: 1rem; font-weight: 400; color: #ffcd27; } +:global(.dark) .operationDefaultBadgeText { + color: #fbbf24; +} + .bigText { white-space: nowrap; overflow: hidden; diff --git a/web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx b/web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx index d7dd4c07..0ff2a2cd 100644 --- a/web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx +++ b/web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx @@ -1,8 +1,7 @@ import { useEffect, useState } from 'react'; import { httpClient } from '@/app/infra/http/HttpClient'; -import { Pipeline } from '@/app/infra/entities/api'; +import { GetPipelineResponseData, Pipeline } from '@/app/infra/entities/api'; import { - PipelineFormEntity, PipelineConfigTab, PipelineConfigStage, } from '@/app/infra/entities/pipeline'; @@ -34,7 +33,6 @@ import { useTranslation } from 'react-i18next'; import { extractI18nObject } from '@/i18n/I18nProvider'; export default function PipelineFormComponent({ - initValues, isDefaultPipeline, onFinish, onNewPipelineCreated, @@ -49,8 +47,6 @@ export default function PipelineFormComponent({ isEditMode: boolean; disableForm: boolean; showButtons?: boolean; - // 这里的写法很不安全不规范，未来流水线需要重新整理 - initValues?: PipelineFormEntity; onFinish: () => void; onNewPipelineCreated: (pipelineId: string) => void; onDeletePipeline: () => void; @@ -132,13 +128,26 @@ export default function PipelineFormComponent({ } } }); + + if (isEditMode) { + httpClient + .getPipeline(pipelineId || '') + .then((resp: GetPipelineResponseData) => { + form.reset({ + basic: { + name: resp.pipeline.name, + description: resp.pipeline.description, + }, + ai: resp.pipeline.config.ai, + trigger: resp.pipeline.config.trigger, + safety: resp.pipeline.config.safety, + output: resp.pipeline.config.output, + }); + }); + } }, []); useEffect(() => { - if (initValues) { - form.reset(initValues); - } - if (!isEditMode) { form.reset({ basic: { @@ -147,7 +156,7 @@ export default function PipelineFormComponent({ }, }); } - }, [initValues, form, isEditMode]); + }, [form, isEditMode]); function handleFormSubmit(values: FormValues) { console.log('handleFormSubmit', values); @@ -339,7 +348,7 @@ export default function PipelineFormComponent({ return ( <> -
+
{/* 按钮栏移到 Tabs 外部，始终固定底部 */} {showButtons && ( -
+
{isEditMode && !isDefaultPipeline && (