chore: update readme

docs: update readme
- Updated links in Japanese, Russian, and Traditional Chinese README files to include a new Simplified Chinese README. - Enhanced the description and features of AstrBot across all language versions. - Improved formatting of supported messaging platforms and model services in Japanese, Russian, and Traditional Chinese README files. - Added a new README file in Simplified Chinese with comprehensive details about AstrBot, including features, deployment methods, and community contributions.
2026-02-27 22:47:10 +08:00 · 2026-02-27 22:40:38 +08:00 · 2026-02-27 22:02:37 +08:00 · 2026-02-27 21:53:56 +08:00 · 2026-02-27 14:02:10 +08:00 · 2026-02-26 21:38:47 +08:00
25 changed files with 3536 additions and 1235 deletions
@@ -2,12 +2,14 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
 <br>
 <div>
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 <a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
@@ -21,42 +23,42 @@
 <img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
 <a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
-<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600">
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%20plugins&label=Marketplace&cacheSeconds=3600">
 <img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
 </div>
 <br>
-<a href="https://astrbot.app/">文档</a> ｜
+<a href="https://astrbot.app/">Documentation</a> ｜
 <a href="https://blog.astrbot.app/">Blog</a> ｜
-<a href="https://astrbot.featurebase.app/roadmap">路线图</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">Roadmap</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">问题提交</a>
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue Tracker</a>
 </div>
-AstrBot 是一个开源的一站式 Agentic 个人和群聊助手，可在 QQ、Telegram、企业微信、飞书、钉钉、Slack、等数十款主流即时通讯软件上部署，此外还内置类似 OpenWebUI 的轻量化 ChatUI，为个人、开发者和团队打造可靠、可扩展的对话式智能基础设施。无论是个人 AI 伙伴、智能客服、自动化助手，还是企业知识库，AstrBot 都能在你的即时通讯软件平台的工作流中快速构建 AI 应用。
+AstrBot is an open-source all-in-one Agent chatbot platform that integrates with mainstream instant messaging apps. It provides reliable and scalable conversational AI infrastructure for individuals, developers, and teams. Whether you're building a personal AI companion, intelligent customer service, automation assistant, or enterprise knowledge base, AstrBot enables you to quickly build production-ready AI applications within your IM platform workflows.
-![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)
-## 主要功能
+## Key Features
-1. 💯 免费 & 开源。
+1. 💯 Free & Open Source.
-2. ✨ AI 大模型对话，多模态，Agent，MCP，Skills，知识库，人格设定，自动压缩对话。
+2. ✨ AI LLM Conversations, Multimodal, Agent, MCP, Skills, Knowledge Base, Persona Settings, Auto Context Compression.
-3. 🤖 支持接入 Dify、阿里云百炼、Coze 等智能体平台。
+3. 🤖 Supports integration with Dify, Alibaba Cloud Bailian, Coze, and other agent platforms.
-4. 🌐 多平台，支持 QQ、企业微信、飞书、钉钉、微信公众号、Telegram、Slack 以及[更多](#支持的消息平台)。
+4. 🌐 Multi-Platform: QQ, WeChat Work, Feishu, DingTalk, WeChat Official Accounts, Telegram, Slack, and [more](#supported-messaging-platforms).
-5. 📦 插件扩展，已有 1000+ 个插件可一键安装。
+5. 📦 Plugin Extensions with 1000+ plugins available for one-click installation.
-6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) 隔离化环境，安全地执行任何代码、调用 Shell、会话级资源复用。
+6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) for isolated, safe execution of code, shell calls, and session-level resource reuse.
-7. 💻 WebUI 支持。
+7. 💻 WebUI Support.
-8. 🌈 Web ChatUI 支持，ChatUI 内置代理沙盒、网页搜索等。
+8. 🌈 Web ChatUI Support with built-in agent sandbox and web search.
-9. 🌐 国际化（i18n）支持。
+9. 🌐 Internationalization (i18n) Support.
 <br>
 <table align="center">
  <tr align="center">
-    <th>💙 角色扮演 & 情感陪伴</th>
+    <th>💙 Role-playing & Emotional Companionship</th>
-    <th>✨ 主动式 Agent</th>
+    <th>✨ Proactive Agent</th>
-    <th>🚀 通用 Agentic 能力</th>
+    <th>🚀 General Agentic Capabilities</th>
-    <th>🧩 1000+ 社区插件</th>
+    <th>🧩 1000+ Community Plugins</th>
  </tr>
  <tr>
    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
@@ -66,172 +68,163 @@ AstrBot 是一个开源的一站式 Agentic 个人和群聊助手，可在 QQ、
  </tr>
 </table>
-## 快速开始
+## Quick Start
-#### Docker 部署(推荐 🥳)
+#### Docker Deployment (Recommended 🥳)
-推荐使用 Docker / Docker Compose 方式部署 AstrBot。
+We recommend deploying AstrBot using Docker or Docker Compose.
-请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
+Please refer to the official documentation: [Deploy AstrBot with Docker](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot).
-#### uv 部署
+#### uv Deployment
 ```bash
 uv tool install astrbot
 astrbot
 ```
-#### 桌面应用部署（Tauri）
+#### System Package Manager Installation
-桌面应用仓库 [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop)。
+##### Arch Linux
-支持多系统架构，安装包直接安装，开箱即用，最适合新手和懒人的一键桌面部署方案，不推荐服务器场景。
+```bash
 yay -S astrbot-git
 # or use paru
 paru -S astrbot-git
 ```
-#### 启动器一键部署（AstrBot Launcher）
+#### Desktop Application (Tauri)
-快速部署和多开方案，实现环境隔离，进入 [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) 仓库，在 Releases 页最新版本下找到对应的系统安装包安装即可。
+Desktop repository: [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop).
-#### 宝塔面板部署
+Supports multiple system architectures, direct installation, out-of-the-box experience. Ideal for beginners.
-AstrBot 与宝塔面板合作，已上架至宝塔面板。
+#### AstrBot Launcher
-请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
+Quick deployment and multi-instance solution. Visit the [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) repository and find the latest release for your system.
-#### 1Panel 部署
+#### BT-Panel Deployment
-AstrBot 已由 1Panel 官方上架至 1Panel 面板。
+AstrBot has partnered with BT-Panel and is now available in their marketplace.
-请参阅官方文档 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html) 。
+Please refer to the official documentation: [BT-Panel Deployment](https://astrbot.app/deploy/astrbot/btpanel.html).
-#### 在 雨云 上部署
+#### 1Panel Deployment
-AstrBot 已由雨云官方上架至云应用平台，可一键部署。
+AstrBot has been officially listed on the 1Panel marketplace.
 Please refer to the official documentation: [1Panel Deployment](https://astrbot.app/deploy/astrbot/1panel.html).
 #### Deploy on RainYun
 For Chinese users:
 AstrBot has been officially listed on RainYun's cloud application platform with one-click deployment.
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
-#### 在 Replit 上部署
+#### Deploy on Replit
-社区贡献的部署方式。
+Community-contributed deployment method.
 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
-#### Windows 一键安装器部署
+#### Windows One-Click Installer
-请参阅官方文档 [使用 Windows 一键安装器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html) 。
+Please refer to the official documentation: [Deploy AstrBot with Windows One-Click Installer](https://astrbot.app/deploy/astrbot/windows.html).
-#### CasaOS 部署
+#### CasaOS Deployment
-社区贡献的部署方式。
+Community-contributed deployment method.
-请参阅官方文档 [CasaOS 部署](https://astrbot.app/deploy/astrbot/casaos.html) 。
+Please refer to the official documentation: [CasaOS Deployment](https://astrbot.app/deploy/astrbot/casaos.html).
-#### 手动部署
+#### Manual Deployment
-首先安装 uv：
+First, install uv:
 ```bash
 pip install uv
 ```
-通过 Git Clone 安装 AstrBot：
+Install AstrBot via Git Clone:
 ```bash
 git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
 uv run main.py
 ```
-或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
+Or refer to the official documentation: [Deploy AstrBot from Source](https://astrbot.app/deploy/astrbot/cli.html).
-#### 系统包管理器安装
+## Supported Messaging Platforms
-##### Arch Linux
+Connect AstrBot to your favorite chat platform.
-```bash
+| Platform | Maintainer |
-yay -S astrbot-git
+|---------|---------------|
-# 或者使用 paru
+| QQ | Official |
-paru -S astrbot-git
+| OneBot v11 protocol implementation | Official |
-```
+| Telegram | Official |
 | WeChat Work Application & WeChat Work Intelligent Bot | Official |
 | WeChat Customer Service & WeChat Official Accounts | Official |
 | Feishu (Lark) | Official |
 | DingTalk | Official |
 | Slack | Official |
 | Discord | Official |
 | LINE | Official |
 | Satori | Official |
 | Misskey | Official |
 | WhatsApp (Coming Soon) | Official |
 | [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Community |
 | [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Community |
 | [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Community |
-## 支持的消息平台
+## Supported Model Services
-**官方维护**
+| Service | Type |
 |---------|---------------|
 | OpenAI and Compatible Services | LLM Services |
 | Anthropic | LLM Services |
 | Google Gemini | LLM Services |
 | Moonshot AI | LLM Services |
 | Zhipu AI | LLM Services |
 | DeepSeek | LLM Services |
 | Ollama (Self-hosted) | LLM Services |
 | LM Studio (Self-hosted) | LLM Services |
 | [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | LLM Services |
 | [302.AI](https://share.302.ai/rr1M3l) | LLM Services |
 | [TokenPony](https://www.tokenpony.cn/3YPyf) | LLM Services |
 | [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | LLM Services |
 | [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | LLM Services |
 | ModelScope | LLM Services |
 | OneAPI | LLM Services |
 | Dify | LLMOps Platforms |
 | Alibaba Cloud Bailian Applications | LLMOps Platforms |
 | Coze | LLMOps Platforms |
 | OpenAI Whisper | Speech-to-Text Services |
 | SenseVoice | Speech-to-Text Services |
 | OpenAI TTS | Text-to-Speech Services |
 | Gemini TTS | Text-to-Speech Services |
 | GPT-Sovits-Inference | Text-to-Speech Services |
 | GPT-Sovits | Text-to-Speech Services |
 | FishAudio | Text-to-Speech Services |
 | Edge TTS | Text-to-Speech Services |
 | Alibaba Cloud Bailian TTS | Text-to-Speech Services |
 | Azure TTS | Text-to-Speech Services |
 | Minimax TTS | Text-to-Speech Services |
 | Volcano Engine TTS | Text-to-Speech Services |
- QQ
+## ❤️ Contributing
 - OneBot v11 协议实现
 - Telegram
 - 企微应用 & 企微智能机器人
 - 微信客服 & 微信公众号
 - 飞书
 - 钉钉
 - Slack
 - Discord
 - LINE
 - Satori
 - Misskey
 - Whatsapp (将支持)
-**社区维护**
+Issues and Pull Requests are always welcome! Feel free to submit your changes to this project :)
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+### How to Contribute
 - [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
 - [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
-## 支持的模型服务
+You can contribute by reviewing issues or helping with pull request reviews. Any issues or PRs are welcome to encourage community participation. Of course, these are just suggestions—you can contribute in any way you like. For adding new features, please discuss through an Issue first.
-**大模型服务**
+### Development Environment
- OpenAI 及兼容服务
+AstrBot uses `ruff` for code formatting and linting.
 - Anthropic
 - Google Gemini
 - Moonshot AI
 - 智谱 AI
 - DeepSeek
 - Ollama (本地部署)
 - LM Studio (本地部署)
 - [AIHubMix](https://aihubmix.com/?aff=4bfH)
 - [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
 - [302.AI](https://share.302.ai/rr1M3l)
 - [小马算力](https://www.tokenpony.cn/3YPyf)
 - [硅基流动](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
 - [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE)
 - ModelScope
 - OneAPI
 **LLMOps 平台**
 - Dify
 - 阿里云百炼应用
 - Coze
 **语音转文本服务**
 - OpenAI Whisper
 - SenseVoice
 **文本转语音服务**
 - OpenAI TTS
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - 阿里云百炼 TTS
 - Azure TTS
 - Minimax TTS
 - 火山引擎 TTS
 ## ❤️ 贡献
 欢迎任何 Issues/Pull Requests！只需要将你的更改提交到此项目 ：)
 ### 如何贡献
 你可以通过查看问题或帮助审核 PR（拉取请求）来贡献。任何问题或 PR 都欢迎参与，以促进社区贡献。当然，这些只是建议，你可以以任何方式进行贡献。对于新功能的添加，请先通过 Issue 讨论。
 ### 开发环境
 AstrBot 使用 `ruff` 进行代码格式化和检查。
 ```bash
 git clone https://github.com/AstrBotDevs/AstrBot
@@ -239,52 +232,42 @@ pip install pre-commit
 pre-commit install
 ```
-## 🌍 社区
+## 🌍 Community
-### QQ 群组
+### QQ Groups
- 1 群：322154837
+- Group 1: 322154837
- 3 群：630166526
+- Group 3: 630166526
- 5 群：822130018
+- Group 5: 822130018
- 6 群：753075035
+- Group 6: 753075035
- 7 群：743746109
+- Group 7: 743746109
- 8 群：1030353265
+- Group 8: 1030353265
- 开发者群：975206796
+- Developer Group: 975206796
-### Telegram 群组
+### Telegram Group
 <a href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
-### Discord 群组
+### Discord Server
 <a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
 ## ❤️ Special Thanks
-特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
+Special thanks to all Contributors and plugin developers for their contributions to AstrBot ❤️
 <a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
 </a>
-此外，本项目的诞生离不开以下开源项目的帮助：
+Additionally, the birth of this project would not have been possible without the help of the following open-source projects:
- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - The amazing cat framework
 开源项目友情链接：
 - [NoneBot2](https://github.com/nonebot/nonebot2) - 优秀的 Python 异步 ChatBot 框架
 - [Koishi](https://github.com/koishijs/koishi) - 优秀的 Node.js ChatBot 框架
 - [MaiBot](https://github.com/Mai-with-u/MaiBot) - 优秀的拟人化 AI ChatBot
 - [nekro-agent](https://github.com/KroMiose/nekro-agent) - 优秀的 Agent ChatBot
 - [LangBot](https://github.com/langbot-app/LangBot) - 优秀的多平台 AI ChatBot
 - [ChatLuna](https://github.com/ChatLunaLab/chatluna) - 优秀的多平台 AI ChatBot Koishi 插件
 - [Operit AI](https://github.com/AAswordman/Operit) - 优秀的 AI 智能助手 Android APP
 ## ⭐ Star History
 > [!TIP]
-> 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我们维护这个开源项目的动力 <3
+> If this project has helped you in your life or work, or if you're interested in its future development, please give the project a Star. It's the driving force behind maintaining this open-source project <3
 <div align="center">
@@ -294,10 +277,9 @@ pre-commit install
 <div align="center">
-_陪伴与能力从来不应该是对立面。我们希望创造的是一个既能理解情绪、给予陪伴，也能可靠完成工作的机器人。_
+_Companionship and capability should never be at odds. What we aim to create is a robot that can understand emotions, provide genuine companionship, and reliably accomplish tasks._
 _私は、高性能ですから!_
 <img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
 </div>
@@ -2,7 +2,7 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
@@ -37,7 +37,7 @@
 AstrBot is an open-source all-in-one Agent chatbot platform that integrates with mainstream instant messaging apps. It provides reliable and scalable conversational AI infrastructure for individuals, developers, and teams. Whether you're building a personal AI companion, intelligent customer service, automation assistant, or enterprise knowledge base, AstrBot enables you to quickly build production-ready AI applications within your IM platform workflows.
-![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)
 ## Key Features
@@ -117,6 +117,8 @@ Please refer to the official documentation: [1Panel Deployment](https://astrbot.
 #### Deploy on RainYun
 For Chinese users:
 AstrBot has been officially listed on RainYun's cloud application platform with one-click deployment.
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
@@ -156,70 +158,61 @@ Or refer to the official documentation: [Deploy AstrBot from Source](https://ast
 ## Supported Messaging Platforms
-**Officially Maintained**
+Connect AstrBot to your favorite chat platform.
- QQ (Official Platform & OneBot)
+| Platform | Maintainer |
- Telegram
+|---------|---------------|
- WeChat Work Application & WeChat Work Intelligent Bot
+| QQ | Official |
- WeChat Customer Service & WeChat Official Accounts
+| OneBot v11 protocol implementation | Official |
- Feishu (Lark)
+| Telegram | Official |
- DingTalk
+| WeChat Work Application & WeChat Work Intelligent Bot | Official |
- Slack
+| WeChat Customer Service & WeChat Official Accounts | Official |
- Discord
+| Feishu (Lark) | Official |
- Satori
+| DingTalk | Official |
- Misskey
+| Slack | Official |
- LINE
+| Discord | Official |
- WhatsApp (Coming Soon)
+| LINE | Official |
-
+| Satori | Official |
-**Community Maintained**
+| Misskey | Official |
-
+| WhatsApp (Coming Soon) | Official |
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Community |
- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Community |
- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Community |
 ## Supported Model Services
-**LLM Services**
+| Service | Type |
-
+|---------|---------------|
- OpenAI and Compatible Services
+| OpenAI and Compatible Services | LLM Services |
- Anthropic
+| Anthropic | LLM Services |
- Google Gemini
+| Google Gemini | LLM Services |
- Moonshot AI
+| Moonshot AI | LLM Services |
- Zhipu AI
+| Zhipu AI | LLM Services |
- DeepSeek
+| DeepSeek | LLM Services |
- Ollama (Self-hosted)
+| Ollama (Self-hosted) | LLM Services |
- LM Studio (Self-hosted)
+| LM Studio (Self-hosted) | LLM Services |
- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | LLM Services |
- [302.AI](https://share.302.ai/rr1M3l)
+| [302.AI](https://share.302.ai/rr1M3l) | LLM Services |
- [TokenPony](https://www.tokenpony.cn/3YPyf)
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | LLM Services |
- [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | LLM Services |
- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | LLM Services |
- ModelScope
+| ModelScope | LLM Services |
- OneAPI
+| OneAPI | LLM Services |
-
+| Dify | LLMOps Platforms |
-**LLMOps Platforms**
+| Alibaba Cloud Bailian Applications | LLMOps Platforms |
-
+| Coze | LLMOps Platforms |
- Dify
+| OpenAI Whisper | Speech-to-Text Services |
- Alibaba Cloud Bailian Applications
+| SenseVoice | Speech-to-Text Services |
- Coze
+| OpenAI TTS | Text-to-Speech Services |
-
+| Gemini TTS | Text-to-Speech Services |
-**Speech-to-Text Services**
+| GPT-Sovits-Inference | Text-to-Speech Services |
-
+| GPT-Sovits | Text-to-Speech Services |
- OpenAI Whisper
+| FishAudio | Text-to-Speech Services |
- SenseVoice
+| Edge TTS | Text-to-Speech Services |
-
+| Alibaba Cloud Bailian TTS | Text-to-Speech Services |
-**Text-to-Speech Services**
+| Azure TTS | Text-to-Speech Services |
-
+| Minimax TTS | Text-to-Speech Services |
- OpenAI TTS
+| Volcano Engine TTS | Text-to-Speech Services |
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - Alibaba Cloud Bailian TTS
 - Azure TTS
 - Minimax TTS
 - Volcano Engine TTS
 ## ❤️ Contributing
@@ -2,8 +2,8 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">中文</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
@@ -107,6 +107,8 @@ Veuillez consulter la documentation officielle : [Déploiement 1Panel](https://a
 #### Déployer sur RainYun
 For Chinese users:
 AstrBot a été officiellement listé sur la plateforme d'applications cloud de RainYun avec un déploiement en un clic.
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
@@ -156,70 +158,61 @@ paru -S astrbot-git
 ## Plateformes de messagerie prises en charge
-**Maintenues officiellement**
+Connectez AstrBot à vos plateformes de chat préférées.
- QQ (Plateforme officielle & OneBot)
+| Plateforme | Maintenance |
- Telegram
+|---------|---------------|
- Application WeChat Work & Bot intelligent WeChat Work
+| QQ | Officielle |
- Service client WeChat & Comptes officiels WeChat
+| Implémentation du protocole OneBot v11 | Officielle |
- Feishu (Lark)
+| Telegram | Officielle |
- DingTalk
+| Application WeChat Work & Bot intelligent WeChat Work | Officielle |
- Slack
+| Service client WeChat & Comptes officiels WeChat | Officielle |
- Discord
+| Feishu (Lark) | Officielle |
- Satori
+| DingTalk | Officielle |
- Misskey
+| Slack | Officielle |
- LINE
+| Discord | Officielle |
- WhatsApp (Bientôt disponible)
+| LINE | Officielle |
-
+| Satori | Officielle |
-**Maintenues par la communauté**
+| Misskey | Officielle |
-
+| WhatsApp (Bientôt disponible) | Officielle |
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Communauté |
- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Communauté |
- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Communauté |
 ## Services de modèles pris en charge
-**Services LLM**
+| Service | Type |
-
+|---------|---------------|
- OpenAI et services compatibles
+| OpenAI et services compatibles | Services LLM |
- Anthropic
+| Anthropic | Services LLM |
- Google Gemini
+| Google Gemini | Services LLM |
- Moonshot AI
+| Moonshot AI | Services LLM |
- Zhipu AI
+| Zhipu AI | Services LLM |
- DeepSeek
+| DeepSeek | Services LLM |
- Ollama (Auto-hébergé)
+| Ollama (Auto-hébergé) | Services LLM |
- LM Studio (Auto-hébergé)
+| LM Studio (Auto-hébergé) | Services LLM |
- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | Services LLM |
- [302.AI](https://share.302.ai/rr1M3l)
+| [302.AI](https://share.302.ai/rr1M3l) | Services LLM |
- [TokenPony](https://www.tokenpony.cn/3YPyf)
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | Services LLM |
- [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | Services LLM |
- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | Services LLM |
- ModelScope
+| ModelScope | Services LLM |
- OneAPI
+| OneAPI | Services LLM |
-
+| Dify | Plateformes LLMOps |
-**Plateformes LLMOps**
+| Applications Alibaba Cloud Bailian | Plateformes LLMOps |
-
+| Coze | Plateformes LLMOps |
- Dify
+| OpenAI Whisper | Services de reconnaissance vocale |
- Applications Alibaba Cloud Bailian
+| SenseVoice | Services de reconnaissance vocale |
- Coze
+| OpenAI TTS | Services de synthèse vocale |
-
+| Gemini TTS | Services de synthèse vocale |
-**Services de reconnaissance vocale**
+| GPT-Sovits-Inference | Services de synthèse vocale |
-
+| GPT-Sovits | Services de synthèse vocale |
- OpenAI Whisper
+| FishAudio | Services de synthèse vocale |
- SenseVoice
+| Edge TTS | Services de synthèse vocale |
-
+| Alibaba Cloud Bailian TTS | Services de synthèse vocale |
-**Services de synthèse vocale**
+| Azure TTS | Services de synthèse vocale |
-
+| Minimax TTS | Services de synthèse vocale |
- OpenAI TTS
+| Volcano Engine TTS | Services de synthèse vocale |
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - Alibaba Cloud Bailian TTS
 - Azure TTS
 - Minimax TTS
 - Volcano Engine TTS
 ## ❤️ Contribuer
@@ -2,8 +2,8 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">中文</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
@@ -37,7 +37,7 @@
 AstrBot は、主要なインスタントメッセージングアプリと統合できるオープンソースのオールインワン Agent チャットボットプラットフォームです。個人、開発者、チームに信頼性が高くスケーラブルな会話型 AI インフラストラクチャを提供します。パーソナル AI コンパニオン、インテリジェントカスタマーサービス、オートメーションアシスタント、エンタープライズナレッジベースなど、AstrBot を使用すると、IM プラットフォームのワークフロー内で本番環境対応の AI アプリケーションを迅速に構築できます。
-![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)
 ## 主な機能
@@ -107,6 +107,8 @@ AstrBot は 1Panel 公式により 1Panel パネルに公開されています
 #### 雨云でのデプロイ
 For Chinese users:
 AstrBot は雨云公式によりクラウドアプリケーションプラットフォームに公開され、ワンクリックでデプロイ可能です。
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
@@ -156,71 +158,62 @@ paru -S astrbot-git
 ## サポートされているメッセージプラットフォーム
-**公式メンテナンス**
+AstrBot をよく使うチャットプラットフォームに接続できます。
- QQ (公式プラットフォーム & OneBot)
+| プラットフォーム | 保守 |
- Telegram
+|---------|---------------|
- WeChat Work アプリケーション & WeChat Work インテリジェントボット
+| QQ | 公式 |
- WeChat カスタマーサービス & WeChat 公式アカウント
+| OneBot v11 プロトコル実装 | 公式 |
- Feishu (Lark)
+| Telegram | 公式 |
- DingTalk
+| WeChat Work アプリケーション & WeChat Work インテリジェントボット | 公式 |
- Slack
+| WeChat カスタマーサービス & WeChat 公式アカウント | 公式 |
- Discord
+| Feishu (Lark) | 公式 |
- Satori
+| DingTalk | 公式 |
- Misskey
+| Slack | 公式 |
- LINE
+| Discord | 公式 |
- WhatsApp (近日対応予定)
+| LINE | 公式 |
-
+| Satori | 公式 |
-**コミュニティメンテナンス**
+| Misskey | 公式 |
-
+| WhatsApp (近日対応予定) | 公式 |
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | コミュニティ |
- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | コミュニティ |
- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | コミュニティ |
 ## サポートされているモデルサービス
-**大規模言語モデルサービス**
+| サービス | 種類 |
-
+|---------|---------------|
- OpenAI および互換サービス
+| OpenAI および互換サービス | 大規模言語モデルサービス |
- Anthropic
+| Anthropic | 大規模言語モデルサービス |
- Google Gemini
+| Google Gemini | 大規模言語モデルサービス |
- Moonshot AI
+| Moonshot AI | 大規模言語モデルサービス |
- 智谱 AI
+| 智谱 AI | 大規模言語モデルサービス |
- DeepSeek
+| DeepSeek | 大規模言語モデルサービス |
- Ollama (セルフホスト)
+| Ollama (セルフホスト) | 大規模言語モデルサービス |
- LM Studio (セルフホスト)
+| LM Studio (セルフホスト) | 大規模言語モデルサービス |
- [優云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+| [優云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | 大規模言語モデルサービス |
- [302.AI](https://share.302.ai/rr1M3l)
+| [302.AI](https://share.302.ai/rr1M3l) | 大規模言語モデルサービス |
- [小馬算力](https://www.tokenpony.cn/3YPyf)
+| [小馬算力](https://www.tokenpony.cn/3YPyf) | 大規模言語モデルサービス |
- [硅基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+| [硅基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | 大規模言語モデルサービス |
- [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE)
+| [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE) | 大規模言語モデルサービス |
- ModelScope
+| ModelScope | 大規模言語モデルサービス |
- OneAPI
+| OneAPI | 大規模言語モデルサービス |
-
+| Dify | LLMOps プラットフォーム |
-**LLMOps プラットフォーム**
+| Alibaba Cloud 百炼アプリケーション | LLMOps プラットフォーム |
-
+| Coze | LLMOps プラットフォーム |
- Dify
+| OpenAI Whisper | 音声認識サービス |
- Alibaba Cloud 百炼アプリケーション
+| SenseVoice | 音声認識サービス |
- Coze
+| OpenAI TTS | 音声合成サービス |
-
+| Gemini TTS | 音声合成サービス |
-**音声認識サービス**
+| GPT-Sovits-Inference | 音声合成サービス |
-
+| GPT-Sovits | 音声合成サービス |
- OpenAI Whisper
+| FishAudio | 音声合成サービス |
- SenseVoice
+| Edge TTS | 音声合成サービス |
-
+| Alibaba Cloud 百炼 TTS | 音声合成サービス |
-**音声合成サービス**
+| Azure TTS | 音声合成サービス |
-
+| Minimax TTS | 音声合成サービス |
- OpenAI TTS
+| Volcano Engine TTS | 音声合成サービス |
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - Alibaba Cloud 百炼 TTS
 - Azure TTS
 - Minimax TTS
 - Volcano Engine TTS
 ## ❤️ コントリビューション
@@ -2,8 +2,8 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">中文</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a>
@@ -107,6 +107,8 @@ AstrBot официально размещён на маркетплейсе 1Pan
 #### Развёртывание на RainYun
 For Chinese users:
 AstrBot официально размещён на облачной платформе приложений RainYun с развёртыванием в один клик.
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
@@ -156,71 +158,61 @@ paru -S astrbot-git
 ## Поддерживаемые платформы обмена сообщениями
-**Официально поддерживаемые**
+Подключите AstrBot к вашим любимым чат-платформам.
- QQ (Официальная платформа и OneBot)
+| Платформа | Поддержка |
- Telegram
+|---------|---------------|
- Приложение WeChat Work и интеллектуальный бот WeChat Work
+| QQ | Официальная |
- Служба поддержки WeChat и официальные аккаунты WeChat
+| Реализация протокола OneBot v11 | Официальная |
- Feishu (Lark)
+| Telegram | Официальная |
- DingTalk
+| Приложение WeChat Work и интеллектуальный бот WeChat Work | Официальная |
- Slack
+| Служба поддержки WeChat и официальные аккаунты WeChat | Официальная |
- Discord
+| Feishu (Lark) | Официальная |
- Satori
+| DingTalk | Официальная |
- Misskey
+| Slack | Официальная |
- LINE
+| Discord | Официальная |
- WhatsApp (Скоро)
+| LINE | Официальная |
-
+| Satori | Официальная |
-
+| Misskey | Официальная |
-**Поддерживаемые сообществом**
+| WhatsApp (Скоро) | Официальная |
-
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Сообщество |
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Сообщество |
- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Сообщество |
 - [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
 ## Поддерживаемые сервисы моделей
-**Сервисы LLM**
+| Сервис | Тип |
-
+|---------|---------------|
- OpenAI и совместимые сервисы
+| OpenAI и совместимые сервисы | Сервисы LLM |
- Anthropic
+| Anthropic | Сервисы LLM |
- Google Gemini
+| Google Gemini | Сервисы LLM |
- Moonshot AI
+| Moonshot AI | Сервисы LLM |
- Zhipu AI
+| Zhipu AI | Сервисы LLM |
- DeepSeek
+| DeepSeek | Сервисы LLM |
- Ollama (Самостоятельное размещение)
+| Ollama (Самостоятельное размещение) | Сервисы LLM |
- LM Studio (Самостоятельное размещение)
+| LM Studio (Самостоятельное размещение) | Сервисы LLM |
- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | Сервисы LLM |
- [302.AI](https://share.302.ai/rr1M3l)
+| [302.AI](https://share.302.ai/rr1M3l) | Сервисы LLM |
- [TokenPony](https://www.tokenpony.cn/3YPyf)
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | Сервисы LLM |
- [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | Сервисы LLM |
- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | Сервисы LLM |
- ModelScope
+| ModelScope | Сервисы LLM |
- OneAPI
+| OneAPI | Сервисы LLM |
-
+| Dify | Платформы LLMOps |
-**Платформы LLMOps**
+| Приложения Alibaba Cloud Bailian | Платформы LLMOps |
-
+| Coze | Платформы LLMOps |
- Dify
+| OpenAI Whisper | Сервисы распознавания речи |
- Приложения Alibaba Cloud Bailian
+| SenseVoice | Сервисы распознавания речи |
- Coze
+| OpenAI TTS | Сервисы синтеза речи |
-
+| Gemini TTS | Сервисы синтеза речи |
-**Сервисы распознавания речи**
+| GPT-Sovits-Inference | Сервисы синтеза речи |
-
+| GPT-Sovits | Сервисы синтеза речи |
- OpenAI Whisper
+| FishAudio | Сервисы синтеза речи |
- SenseVoice
+| Edge TTS | Сервисы синтеза речи |
-
+| Alibaba Cloud Bailian TTS | Сервисы синтеза речи |
-**Сервисы синтеза речи**
+| Azure TTS | Сервисы синтеза речи |
-
+| Minimax TTS | Сервисы синтеза речи |
- OpenAI TTS
+| Volcano Engine TTS | Сервисы синтеза речи |
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - Alibaba Cloud Bailian TTS
 - Azure TTS
 - Minimax TTS
 - Volcano Engine TTS
 ## ❤️ Вклад в проект
@@ -2,8 +2,8 @@
 <div align="center">
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
@@ -37,7 +37,7 @@
 AstrBot 是一個開源的一站式 Agent 聊天機器人平台，可接入主流即時通訊軟體，為個人、開發者和團隊打造可靠、可擴展的對話式智慧基礎設施。無論是個人 AI 夥伴、智慧客服、自動化助手，還是企業知識庫，AstrBot 都能在您的即時通訊軟體平台的工作流程中快速構建生產可用的 AI 應用程式。
-![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)
 ## 主要功能
@@ -107,6 +107,8 @@ AstrBot 已由 1Panel 官方上架至 1Panel 面板。
 #### 在雨雲上部署
 For Chinese users:
 AstrBot 已由雨雲官方上架至雲端應用程式平台，可一鍵部署。
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
@@ -156,71 +158,61 @@ paru -S astrbot-git
 ## 支援的訊息平台
-**官方維護**
+將 AstrBot 連接到你常用的聊天平台。
- QQ（官方平台 & OneBot）
+| 平台 | 維護方 |
- Telegram
+|---------|---------------|
- 企微應用 & 企微智慧機器人
+| QQ | 官方維護 |
- 微信客服 & 微信公眾號
+| OneBot v11 協議實作 | 官方維護 |
- 飛書
+| Telegram | 官方維護 |
- 釘釘
+| 企微應用 & 企微智慧機器人 | 官方維護 |
- Slack
+| 微信客服 & 微信公眾號 | 官方維護 |
- Discord
+| 飛書 | 官方維護 |
- Satori
+| 釘釘 | 官方維護 |
- Misskey
+| Slack | 官方維護 |
- LINE
+| Discord | 官方維護 |
- Whatsapp（即將支援）
+| LINE | 官方維護 |
-
+| Satori | 官方維護 |
-
+| Misskey | 官方維護 |
-**社群維護**
+| Whatsapp（即將支援） | 官方維護 |
-
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | 社群維護 |
- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | 社群維護 |
- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | 社群維護 |
 - [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
 ## 支援的模型服務
-**大型模型服務**
+| 服務 | 類型 |
-
+|---------|---------------|
- OpenAI 及相容服務
+| OpenAI 及相容服務 | 大型模型服務 |
- Anthropic
+| Anthropic | 大型模型服務 |
- Google Gemini
+| Google Gemini | 大型模型服務 |
- Moonshot AI
+| Moonshot AI | 大型模型服務 |
- 智譜 AI
+| 智譜 AI | 大型模型服務 |
- DeepSeek
+| DeepSeek | 大型模型服務 |
- Ollama（本機部署）
+| Ollama（本機部署） | 大型模型服務 |
- LM Studio（本機部署）
+| LM Studio（本機部署） | 大型模型服務 |
- [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | 大型模型服務 |
- [302.AI](https://share.302.ai/rr1M3l)
+| [302.AI](https://share.302.ai/rr1M3l) | 大型模型服務 |
- [小馬算力](https://www.tokenpony.cn/3YPyf)
+| [小馬算力](https://www.tokenpony.cn/3YPyf) | 大型模型服務 |
- [矽基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+| [矽基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | 大型模型服務 |
- [PPIO 派歐雲](https://ppio.com/user/register?invited_by=AIOONE)
+| [PPIO 派歐雲](https://ppio.com/user/register?invited_by=AIOONE) | 大型模型服務 |
- ModelScope
+| ModelScope | 大型模型服務 |
- OneAPI
+| OneAPI | 大型模型服務 |
-
+| Dify | LLMOps 平台 |
-**LLMOps 平台**
+| 阿里雲百煉應用 | LLMOps 平台 |
-
+| Coze | LLMOps 平台 |
- Dify
+| OpenAI Whisper | 語音轉文字服務 |
- 阿里雲百煉應用
+| SenseVoice | 語音轉文字服務 |
- Coze
+| OpenAI TTS | 文字轉語音服務 |
-
+| Gemini TTS | 文字轉語音服務 |
-**語音轉文字服務**
+| GPT-Sovits-Inference | 文字轉語音服務 |
-
+| GPT-Sovits | 文字轉語音服務 |
- OpenAI Whisper
+| FishAudio | 文字轉語音服務 |
- SenseVoice
+| Edge TTS | 文字轉語音服務 |
-
+| 阿里雲百煉 TTS | 文字轉語音服務 |
-**文字轉語音服務**
+| Azure TTS | 文字轉語音服務 |
-
+| Minimax TTS | 文字轉語音服務 |
- OpenAI TTS
+| 火山引擎 TTS | 文字轉語音服務 |
 - Gemini TTS
 - GPT-Sovits-Inference
 - GPT-Sovits
 - FishAudio
 - Edge TTS
 - 阿里雲百煉 TTS
 - Azure TTS
 - Minimax TTS
 - 火山引擎 TTS
 ## ❤️ 貢獻
@@ -0,0 +1,252 @@
 ![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 <div align="center">
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
 <div>
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 <a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 </div>
 <br>
 <div>
 <img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
 <img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
 <a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
 <img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600">
 <img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
 </div>
 <br>
 <a href="https://astrbot.app/">主页</a> ｜
 <a href="https://astrbot.app/">文档</a> ｜
 <a href="https://blog.astrbot.app/">博客</a> ｜
 <a href="https://astrbot.featurebase.app/roadmap">路线图</a> ｜
 <a href="https://github.com/AstrBotDevs/AstrBot/issues">问题提交</a>
 </div>
 AstrBot 是一个开源的一站式 Agentic 个人和群聊助手，可在 QQ、Telegram、企业微信、飞书、钉钉、Slack、等数十款主流即时通讯软件上部署，此外还内置类似 OpenWebUI 的轻量化 ChatUI，为个人、开发者和团队打造可靠、可扩展的对话式智能基础设施。无论是个人 AI 伙伴、智能客服、自动化助手，还是企业知识库，AstrBot 都能在你的即时通讯软件平台的工作流中快速构建 AI 应用。
 ![landingpage](https://github.com/user-attachments/assets/45fc5699-cddf-4e21-af35-13040706f6c0)
 ## 主要功能
 1. 💯 免费 & 开源。
 2. ✨ AI 大模型对话，多模态，Agent，MCP，Skills，知识库，人格设定，自动压缩对话。
 3. 🤖 支持接入 Dify、阿里云百炼、Coze 等智能体平台。
 4. 🌐 多平台，支持 QQ、企业微信、飞书、钉钉、微信公众号、Telegram、Slack 以及[更多](#支持的消息平台)。
 5. 📦 插件扩展，已有 1000+ 个插件可一键安装。
 6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) 隔离化环境，安全地执行任何代码、调用 Shell、会话级资源复用。
 7. 💻 WebUI 支持。
 8. 🌈 Web ChatUI 支持，ChatUI 内置代理沙盒、网页搜索等。
 9. 🌐 国际化（i18n）支持。
 <br>
 <table align="center">
  <tr align="center">
    <th>💙 角色扮演 & 情感陪伴</th>
    <th>✨ 主动式 Agent</th>
    <th>🚀 通用 Agentic 能力</th>
    <th>🧩 1000+ 社区插件</th>
  </tr>
  <tr>
    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
  </tr>
 </table>
 ## 快速开始
 ### 一键部署
 ```bash
 uv tool install astrbot
 astrbot
 ```
 > 需要安装 [uv](https://docs.astral.sh/uv/)。
 ### Docker 部署
 推荐使用 Docker / Docker Compose 方式部署 AstrBot。
 请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
 ### 在 雨云 上部署
 AstrBot 已由雨云官方上架至云应用平台，可一键部署。
 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
 ### 桌面客户端（Tauri）
 桌面应用仓库 [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop)。
 支持多系统架构，安装包直接安装，开箱即用，最适合新手和懒人的一键桌面部署方案，不推荐服务器场景。
 ### 启动器一键部署（AstrBot Launcher）
 快速部署和多开方案，实现环境隔离，进入 [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) 仓库，在 Releases 页最新版本下找到对应的系统安装包安装即可。
 ### 在 Replit 上部署
 社区贡献的部署方式。
 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
 ### AUR
 ```bash
 yay -S astrbot-git
 ```
 **更多部署方式**：[宝塔面板](https://astrbot.app/deploy/astrbot/btpanel.html) | [1Panel](https://astrbot.app/deploy/astrbot/1panel.html) | [CasaOS](https://astrbot.app/deploy/astrbot/casaos.html) | [手动部署](https://astrbot.app/deploy/astrbot/cli.html)
 ## 支持的消息平台
 将 AstrBot 连接到你常用的聊天平台。
 | 平台 | 维护方 |
 |---------|---------------|
 | **QQ** | 官方维护 |
 | **OneBot v11** | 官方维护 |
 | **Telegram** | 官方维护 |
 | **企微应用 & 企微智能机器人** | 官方维护 |
 | **微信客服 & 微信公众号** | 官方维护 |
 | **飞书** | 官方维护 |
 | **钉钉** | 官方维护 |
 | **Slack** | 官方维护 |
 | **Discord** | 官方维护 |
 | **LINE** | 官方维护 |
 | **Satori** | 官方维护 |
 | **Misskey** | 官方维护 |
 | **Whatsapp (将支持)** | 官方维护 |
 | [**Matrix**](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | 社区维护 |
 | [**KOOK**](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | 社区维护 |
 | [**VoceChat**](https://github.com/HikariFroya/astrbot_plugin_vocechat) | 社区维护 |
 ## 支持的模型提供商
 | 提供商 | 类型 |
 |---------|---------------|
 | 自定义 | 任何 OpenAI API 兼容的服务 |
 | OpenAI | LLM |
 | Anthropic | LLM |
 | Google Gemini | LLM |
 | Moonshot AI | LLM |
 | 智谱 AI | LLM |
 | DeepSeek | LLM |
 | Ollama (本地部署) | LLM |
 | LM Studio (本地部署) | LLM |
 | [AIHubMix](https://aihubmix.com/?aff=4bfH) | LLM (API 网关, 支持所有模型) |
 | [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | LLM (API 网关, 支持所有模型) |
 | [硅基流动](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | LLM (API 网关, 支持所有模型)  |
 | [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE) | LLM (API 网关, 支持所有模型) |
 | [302.AI](https://share.302.ai/rr1M3l) | LLM (API 网关, 支持所有模型)|
 | [小马算力](https://www.tokenpony.cn/3YPyf) | LLM (API 网关, 支持所有模型)|
 | ModelScope | LLM |
 | OneAPI | LLM |
 | Dify | LLMOps 平台 |
 | 阿里云百炼应用 | LLMOps 平台 |
 | Coze | LLMOps 平台 |
 | OpenAI Whisper | 语音转文本 |
 | SenseVoice | 语音转文本 |
 | OpenAI TTS | 文本转语音 |
 | Gemini TTS | 文本转语音 |
 | GPT-Sovits-Inference | 文本转语音 |
 | GPT-Sovits | 文本转语音 |
 | FishAudio | 文本转语音 |
 | Edge TTS | 文本转语音 |
 | 阿里云百炼 TTS | 文本转语音 |
 | Azure TTS | 文本转语音 |
 | Minimax TTS | 文本转语音 |
 | 火山引擎 TTS | 文本转语音 |
 ## ❤️ 贡献
 欢迎任何 Issues/Pull Requests！只需要将你的更改提交到此项目 ：)
 ### 如何贡献
 你可以通过查看问题或帮助审核 PR（拉取请求）来贡献。任何问题或 PR 都欢迎参与，以促进社区贡献。当然，这些只是建议，你可以以任何方式进行贡献。对于新功能的添加，请先通过 Issue 讨论。
 ### 开发环境
 AstrBot 使用 `ruff` 进行代码格式化和检查。
 ```bash
 git clone https://github.com/AstrBotDevs/AstrBot
 pip install pre-commit
 pre-commit install
 ```
 ## 🌍 社区
 ### QQ 群组
 - 1 群：322154837
 - 3 群：630166526
 - 5 群：822130018
 - 6 群：753075035
 - 7 群：743746109
 - 8 群：1030353265
 - 开发者群：975206796
 ### Discord 频道
 - [Discord](https://discord.gg/hAVk6tgV36)
 ## ❤️ Special Thanks
 特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
 <a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
 </a>
 此外，本项目的诞生离不开以下开源项目的帮助：
 - [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
 开源项目友情链接：
 - [NoneBot2](https://github.com/nonebot/nonebot2) - 优秀的 Python 异步 ChatBot 框架
 - [Koishi](https://github.com/koishijs/koishi) - 优秀的 Node.js ChatBot 框架
 - [MaiBot](https://github.com/Mai-with-u/MaiBot) - 优秀的拟人化 AI ChatBot
 - [nekro-agent](https://github.com/KroMiose/nekro-agent) - 优秀的 Agent ChatBot
 - [LangBot](https://github.com/langbot-app/LangBot) - 优秀的多平台 AI ChatBot
 - [ChatLuna](https://github.com/ChatLunaLab/chatluna) - 优秀的多平台 AI ChatBot Koishi 插件
 - [Operit AI](https://github.com/AAswordman/Operit) - 优秀的 AI 智能助手 Android APP
 ## ⭐ Star History
 > [!TIP]
 > 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我们维护这个开源项目的动力 <3
 <div align="center">
 [![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
 </div>
 <div align="center">
 _陪伴与能力从来不应该是对立面。我们希望创造的是一个既能理解情绪、给予陪伴，也能可靠完成工作的机器人。_
 _私は、高性能ですから!_
 <img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
 </div>
@@ -1,9 +1,10 @@
 import asyncio
 import copy
 import sys
 import time
 import traceback
 import typing as T
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from mcp.types import (
    BlobResourceContents,
@@ -68,6 +69,14 @@ class _HandleFunctionToolsResult:
        return cls(kind="cached_image", cached_image=image)
@dataclass(slots=True)
 class FollowUpTicket:
    seq: int
    text: str
    consumed: bool = False
    resolved: asyncio.Event = field(default_factory=asyncio.Event)
 class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
    @override
    async def reset(
@@ -139,6 +148,8 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        self.run_context = run_context
        self._stop_requested = False
        self._aborted = False
        self._pending_follow_ups: list[FollowUpTicket] = []
        self._follow_up_seq = 0
        # These two are used for tool schema mode handling
        # We now have two modes:
@@ -277,6 +288,55 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            roles.append(message.role)
        logger.debug(f"{tag} RunCtx.messages -> [{len(roles)}] {','.join(roles)}")
    def follow_up(
        self,
        *,
        message_text: str,
    ) -> FollowUpTicket | None:
        """Queue a follow-up message for the next tool result."""
        if self.done():
            return None
        text = (message_text or "").strip()
        if not text:
            return None
        ticket = FollowUpTicket(seq=self._follow_up_seq, text=text)
        self._follow_up_seq += 1
        self._pending_follow_ups.append(ticket)
        return ticket
    def _resolve_unconsumed_follow_ups(self) -> None:
        if not self._pending_follow_ups:
            return
        follow_ups = self._pending_follow_ups
        self._pending_follow_ups = []
        for ticket in follow_ups:
            ticket.resolved.set()
    def _consume_follow_up_notice(self) -> str:
        if not self._pending_follow_ups:
            return ""
        follow_ups = self._pending_follow_ups
        self._pending_follow_ups = []
        for ticket in follow_ups:
            ticket.consumed = True
            ticket.resolved.set()
        follow_up_lines = "\n".join(
            f"{idx}. {ticket.text}" for idx, ticket in enumerate(follow_ups, start=1)
        )
        return (
            "\n\n[SYSTEM NOTICE] User sent follow-up messages while tool execution "
            "was in progress. Prioritize these follow-up instructions in your next "
            "actions. In your very next action, briefly acknowledge to the user "
            "that their follow-up message(s) were received before continuing.\n"
            f"{follow_up_lines}"
        )
    def _merge_follow_up_notice(self, content: str) -> str:
        notice = self._consume_follow_up_notice()
        if not notice:
            return content
        return f"{content}{notice}"
    @override
    async def step(self):
        """Process a single step of the agent.
@@ -391,6 +451,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                type="aborted",
                data=AgentResponseData(chain=MessageChain(type="aborted")),
            )
            self._resolve_unconsumed_follow_ups()
            return
        # 处理 LLM 响应
@@ -401,6 +462,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            self.final_llm_resp = llm_resp
            self.stats.end_time = time.time()
            self._transition_state(AgentState.ERROR)
            self._resolve_unconsumed_follow_ups()
            yield AgentResponse(
                type="err",
                data=AgentResponseData(
@@ -439,6 +501,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                await self.agent_hooks.on_agent_done(self.run_context, llm_resp)
            except Exception as e:
                logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
            self._resolve_unconsumed_follow_ups()
        # 返回 LLM 结果
        if llm_resp.result_chain:
@@ -583,6 +646,15 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        tool_call_result_blocks: list[ToolCallMessageSegment] = []
        logger.info(f"Agent 使用工具: {llm_response.tools_call_name}")
        def _append_tool_call_result(tool_call_id: str, content: str) -> None:
            tool_call_result_blocks.append(
                ToolCallMessageSegment(
                    role="tool",
                    tool_call_id=tool_call_id,
                    content=self._merge_follow_up_notice(content),
                ),
            )
        # 执行函数调用
        for func_tool_name, func_tool_args, func_tool_id in zip(
            llm_response.tools_call_name,
@@ -622,12 +694,9 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                if not func_tool:
                    logger.warning(f"未找到指定的工具: {func_tool_name}，将跳过。")
-                    tool_call_result_blocks.append(
+                    _append_tool_call_result(
-                        ToolCallMessageSegment(
+                        func_tool_id,
-                            role="tool",
+                        f"error: Tool {func_tool_name} not found.",
                            tool_call_id=func_tool_id,
                            content=f"error: Tool {func_tool_name} not found.",
                        ),
                    )
                    continue
@@ -680,12 +749,9 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                        res = resp
                        _final_resp = resp
                        if isinstance(res.content[0], TextContent):
-                            tool_call_result_blocks.append(
+                            _append_tool_call_result(
-                                ToolCallMessageSegment(
+                                func_tool_id,
-                                    role="tool",
+                                res.content[0].text,
                                    tool_call_id=func_tool_id,
                                    content=res.content[0].text,
                                ),
                            )
                        elif isinstance(res.content[0], ImageContent):
                            # Cache the image instead of sending directly
@@ -696,15 +762,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                index=0,
                                mime_type=res.content[0].mimeType or "image/png",
                            )
-                            tool_call_result_blocks.append(
+                            _append_tool_call_result(
-                                ToolCallMessageSegment(
+                                func_tool_id,
-                                    role="tool",
+                                (
-                                    tool_call_id=func_tool_id,
+                                    f"Image returned and cached at path='{cached_img.file_path}'. "
-                                    content=(
+                                    f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
-                                        f"Image returned and cached at path='{cached_img.file_path}'. "
+                                    f"with type='image' and path='{cached_img.file_path}'."
                                        f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
                                        f"with type='image' and path='{cached_img.file_path}'."
                                    ),
                                ),
                            )
                            # Yield image info for LLM visibility (will be handled in step())
@@ -714,12 +777,9 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                        elif isinstance(res.content[0], EmbeddedResource):
                            resource = res.content[0].resource
                            if isinstance(resource, TextResourceContents):
-                                tool_call_result_blocks.append(
+                                _append_tool_call_result(
-                                    ToolCallMessageSegment(
+                                    func_tool_id,
-                                        role="tool",
+                                    resource.text,
                                        tool_call_id=func_tool_id,
                                        content=resource.text,
                                    ),
                                )
                            elif (
                                isinstance(resource, BlobResourceContents)
@@ -734,15 +794,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                    index=0,
                                    mime_type=resource.mimeType,
                                )
-                                tool_call_result_blocks.append(
+                                _append_tool_call_result(
-                                    ToolCallMessageSegment(
+                                    func_tool_id,
-                                        role="tool",
+                                    (
-                                        tool_call_id=func_tool_id,
+                                        f"Image returned and cached at path='{cached_img.file_path}'. "
-                                        content=(
+                                        f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
-                                            f"Image returned and cached at path='{cached_img.file_path}'. "
+                                        f"with type='image' and path='{cached_img.file_path}'."
                                            f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
                                            f"with type='image' and path='{cached_img.file_path}'."
                                        ),
                                    ),
                                )
                                # Yield image info for LLM visibility
@@ -750,12 +807,9 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                    cached_img
                                )
                            else:
-                                tool_call_result_blocks.append(
+                                _append_tool_call_result(
-                                    ToolCallMessageSegment(
+                                    func_tool_id,
-                                        role="tool",
+                                    "The tool has returned a data type that is not supported.",
                                        tool_call_id=func_tool_id,
                                        content="The tool has returned a data type that is not supported.",
                                    ),
                                )
                    elif resp is None:
@@ -767,24 +821,18 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                        )
                        self._transition_state(AgentState.DONE)
                        self.stats.end_time = time.time()
-                        tool_call_result_blocks.append(
+                        _append_tool_call_result(
-                            ToolCallMessageSegment(
+                            func_tool_id,
-                                role="tool",
+                            "The tool has no return value, or has sent the result directly to the user.",
                                tool_call_id=func_tool_id,
                                content="The tool has no return value, or has sent the result directly to the user.",
                            ),
                        )
                    else:
                        # 不应该出现其他类型
                        logger.warning(
                            f"Tool 返回了不支持的类型: {type(resp)}。",
                        )
-                        tool_call_result_blocks.append(
+                        _append_tool_call_result(
-                            ToolCallMessageSegment(
+                            func_tool_id,
-                                role="tool",
+                            "*The tool has returned an unsupported type. Please tell the user to check the definition and implementation of this tool.*",
                                tool_call_id=func_tool_id,
                                content="*The tool has returned an unsupported type. Please tell the user to check the definition and implementation of this tool.*",
                            ),
                        )
                try:
@@ -798,12 +846,9 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                    logger.error(f"Error in on_tool_end hook: {e}", exc_info=True)
            except Exception as e:
                logger.warning(traceback.format_exc())
-                tool_call_result_blocks.append(
+                _append_tool_call_result(
-                    ToolCallMessageSegment(
+                    func_tool_id,
-                        role="tool",
+                    f"error: {e!s}",
                        tool_call_id=func_tool_id,
                        content=f"error: {e!s}",
                    ),
                )
        # yield the last tool call result
@@ -0,0 +1,227 @@
 from __future__ import annotations
 import asyncio
 from dataclasses import dataclass
 from astrbot import logger
 from astrbot.core.agent.runners.tool_loop_agent_runner import FollowUpTicket
 from astrbot.core.astr_agent_run_util import AgentRunner
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 _ACTIVE_AGENT_RUNNERS: dict[str, AgentRunner] = {}
 _FOLLOW_UP_ORDER_STATE: dict[str, dict[str, object]] = {}
 """UMO-level follow-up order state.
 State fields:
 - `statuses`: seq -> {"pending"|"active"|"consumed"|"finished"}
 - `next_order`: monotonically increasing sequence allocator
 - `next_turn`: next sequence allowed to proceed when not consumed
 """
@dataclass(slots=True)
 class FollowUpCapture:
    umo: str
    ticket: FollowUpTicket
    order_seq: int
    monitor_task: asyncio.Task[None]
 def _event_follow_up_text(event: AstrMessageEvent) -> str:
    text = (event.get_message_str() or "").strip()
    if text:
        return text
    return event.get_message_outline().strip()
 def register_active_runner(umo: str, runner: AgentRunner) -> None:
    _ACTIVE_AGENT_RUNNERS[umo] = runner
 def unregister_active_runner(umo: str, runner: AgentRunner) -> None:
    if _ACTIVE_AGENT_RUNNERS.get(umo) is runner:
        _ACTIVE_AGENT_RUNNERS.pop(umo, None)
 def _get_follow_up_order_state(umo: str) -> dict[str, object]:
    state = _FOLLOW_UP_ORDER_STATE.get(umo)
    if state is None:
        state = {
            "condition": asyncio.Condition(),
            # Sequence status map for strict in-order resume after unresolved follow-ups.
            "statuses": {},
            # Stable allocator for arrival order; never decreases for the same UMO state.
            "next_order": 0,
            # The sequence currently allowed to continue main internal flow.
            "next_turn": 0,
        }
        _FOLLOW_UP_ORDER_STATE[umo] = state
    return state
 def _advance_follow_up_turn_locked(state: dict[str, object]) -> None:
    # Skip slots that are already handled, and stop at the first unfinished slot.
    statuses = state["statuses"]
    assert isinstance(statuses, dict)
    next_turn = state["next_turn"]
    assert isinstance(next_turn, int)
    while True:
        curr = statuses.get(next_turn)
        if curr in ("consumed", "finished"):
            statuses.pop(next_turn, None)
            next_turn += 1
            continue
        break
    state["next_turn"] = next_turn
 def _allocate_follow_up_order(umo: str) -> int:
    state = _get_follow_up_order_state(umo)
    next_order = state["next_order"]
    assert isinstance(next_order, int)
    seq = next_order
    state["next_order"] = seq + 1
    statuses = state["statuses"]
    assert isinstance(statuses, dict)
    statuses[seq] = "pending"
    return seq
 async def _mark_follow_up_consumed(umo: str, seq: int) -> None:
    state = _FOLLOW_UP_ORDER_STATE.get(umo)
    if not state:
        return
    condition = state["condition"]
    assert isinstance(condition, asyncio.Condition)
    async with condition:
        statuses = state["statuses"]
        assert isinstance(statuses, dict)
        if seq in statuses and statuses[seq] != "finished":
            statuses[seq] = "consumed"
        _advance_follow_up_turn_locked(state)
        condition.notify_all()
        # Release state only when this UMO has no pending statuses and no active runner.
        if not statuses and _ACTIVE_AGENT_RUNNERS.get(umo) is None:
            _FOLLOW_UP_ORDER_STATE.pop(umo, None)
 async def _activate_and_wait_follow_up_turn(umo: str, seq: int) -> None:
    state = _FOLLOW_UP_ORDER_STATE.get(umo)
    if not state:
        return
    condition = state["condition"]
    assert isinstance(condition, asyncio.Condition)
    async with condition:
        statuses = state["statuses"]
        assert isinstance(statuses, dict)
        if seq in statuses:
            statuses[seq] = "active"
        # Strict ordering: only the head (`next_turn`) can continue.
        while True:
            next_turn = state["next_turn"]
            assert isinstance(next_turn, int)
            if next_turn == seq:
                break
            await condition.wait()
 async def _finish_follow_up_turn(umo: str, seq: int) -> None:
    state = _FOLLOW_UP_ORDER_STATE.get(umo)
    if not state:
        return
    condition = state["condition"]
    assert isinstance(condition, asyncio.Condition)
    async with condition:
        statuses = state["statuses"]
        assert isinstance(statuses, dict)
        if seq in statuses:
            statuses[seq] = "finished"
        _advance_follow_up_turn_locked(state)
        condition.notify_all()
        if not statuses and _ACTIVE_AGENT_RUNNERS.get(umo) is None:
            _FOLLOW_UP_ORDER_STATE.pop(umo, None)
 async def _monitor_follow_up_ticket(
    umo: str,
    ticket: FollowUpTicket,
    order_seq: int,
 ) -> None:
    """Advance consumed slots immediately on resolution to avoid wake-order drift."""
    await ticket.resolved.wait()
    if ticket.consumed:
        await _mark_follow_up_consumed(umo, order_seq)
 def try_capture_follow_up(event: AstrMessageEvent) -> FollowUpCapture | None:
    sender_id = event.get_sender_id()
    if not sender_id:
        return None
    runner = _ACTIVE_AGENT_RUNNERS.get(event.unified_msg_origin)
    if not runner:
        return None
    runner_event = getattr(getattr(runner.run_context, "context", None), "event", None)
    if runner_event is None:
        return None
    active_sender_id = runner_event.get_sender_id()
    if not active_sender_id or active_sender_id != sender_id:
        return None
    ticket = runner.follow_up(message_text=_event_follow_up_text(event))
    if not ticket:
        return None
    # Allocate strict order at capture time (arrival order), not at wake time.
    order_seq = _allocate_follow_up_order(event.unified_msg_origin)
    monitor_task = asyncio.create_task(
        _monitor_follow_up_ticket(
            event.unified_msg_origin,
            ticket,
            order_seq,
        )
    )
    logger.info(
        "Captured follow-up message for active agent run, umo=%s, order_seq=%s",
        event.unified_msg_origin,
        order_seq,
    )
    return FollowUpCapture(
        umo=event.unified_msg_origin,
        ticket=ticket,
        order_seq=order_seq,
        monitor_task=monitor_task,
    )
 async def prepare_follow_up_capture(capture: FollowUpCapture) -> tuple[bool, bool]:
    """Return `(consumed_marked, activated)` for internal stage branch handling."""
    await capture.ticket.resolved.wait()
    if capture.ticket.consumed:
        await _mark_follow_up_consumed(capture.umo, capture.order_seq)
        return True, False
    await _activate_and_wait_follow_up_turn(capture.umo, capture.order_seq)
    return False, True
 async def finalize_follow_up_capture(
    capture: FollowUpCapture,
    *,
    activated: bool,
    consumed_marked: bool,
 ) -> None:
    # Best-effort cancellation: monitor task is auxiliary and should not leak.
    if not capture.monitor_task.done():
        capture.monitor_task.cancel()
        try:
            await capture.monitor_task
        except asyncio.CancelledError:
            pass
    if activated:
        await _finish_follow_up_turn(capture.umo, capture.order_seq)
    elif not consumed_marked:
        await _mark_follow_up_consumed(capture.umo, capture.order_seq)
@@ -29,8 +29,16 @@ from astrbot.core.star.star_handler import EventType
 from astrbot.core.utils.metrics import Metric
 from astrbot.core.utils.session_lock import session_lock_manager
-from .....astr_agent_run_util import run_agent, run_live_agent
+from .....astr_agent_run_util import AgentRunner, run_agent, run_live_agent
 from ....context import PipelineContext, call_event_hook
 from ...follow_up import (
    FollowUpCapture,
    finalize_follow_up_capture,
    prepare_follow_up_capture,
    register_active_runner,
    try_capture_follow_up,
    unregister_active_runner,
 )
 class InternalAgentSubStage(Stage):
@@ -130,6 +138,9 @@ class InternalAgentSubStage(Stage):
    async def process(
        self, event: AstrMessageEvent, provider_wake_prefix: str
    ) -> AsyncGenerator[None, None]:
        follow_up_capture: FollowUpCapture | None = None
        follow_up_consumed_marked = False
        follow_up_activated = False
        try:
            streaming_response = self.streaming_response
            if (enable_streaming := event.get_extra("enable_streaming")) is not None:
@@ -150,188 +161,208 @@ class InternalAgentSubStage(Stage):
                return
            logger.debug("ready to request llm provider")
            follow_up_capture = try_capture_follow_up(event)
            if follow_up_capture:
                (
                    follow_up_consumed_marked,
                    follow_up_activated,
                ) = await prepare_follow_up_capture(follow_up_capture)
                if follow_up_consumed_marked:
                    logger.info(
                        "Follow-up ticket already consumed, stopping processing. umo=%s, seq=%s",
                        event.unified_msg_origin,
                        follow_up_capture.ticket.seq,
                    )
                    return
            await event.send_typing()
            await call_event_hook(event, EventType.OnWaitingLLMRequestEvent)
            async with session_lock_manager.acquire_lock(event.unified_msg_origin):
                logger.debug("acquired session lock for llm request")
                agent_runner: AgentRunner | None = None
                runner_registered = False
                try:
                    build_cfg = replace(
                        self.main_agent_cfg,
                        provider_wake_prefix=provider_wake_prefix,
                        streaming_response=streaming_response,
                    )
-                build_cfg = replace(
+                    build_result: MainAgentBuildResult | None = await build_main_agent(
-                    self.main_agent_cfg,
+                        event=event,
-                    provider_wake_prefix=provider_wake_prefix,
+                        plugin_context=self.ctx.plugin_manager.context,
-                    streaming_response=streaming_response,
+                        config=build_cfg,
-                )
+                        apply_reset=False,
                    )
-                build_result: MainAgentBuildResult | None = await build_main_agent(
+                    if build_result is None:
                    event=event,
                    plugin_context=self.ctx.plugin_manager.context,
                    config=build_cfg,
                    apply_reset=False,
                )
                if build_result is None:
                    return
                agent_runner = build_result.agent_runner
                req = build_result.provider_request
                provider = build_result.provider
                reset_coro = build_result.reset_coro
                api_base = provider.provider_config.get("api_base", "")
                for host in decoded_blocked:
                    if host in api_base:
                        logger.error(
                            "Provider API base %s is blocked due to security reasons. Please use another ai provider.",
                            api_base,
                        )
                        return
-                stream_to_general = (
+                    agent_runner = build_result.agent_runner
-                    self.unsupported_streaming_strategy == "turn_off"
+                    req = build_result.provider_request
-                    and not event.platform_meta.support_streaming_message
+                    provider = build_result.provider
-                )
+                    reset_coro = build_result.reset_coro
-                if await call_event_hook(event, EventType.OnLLMRequestEvent, req):
+                    api_base = provider.provider_config.get("api_base", "")
                    for host in decoded_blocked:
                        if host in api_base:
                            logger.error(
                                "Provider API base %s is blocked due to security reasons. Please use another ai provider.",
                                api_base,
                            )
                            return
                    stream_to_general = (
                        self.unsupported_streaming_strategy == "turn_off"
                        and not event.platform_meta.support_streaming_message
                    )
                    if await call_event_hook(event, EventType.OnLLMRequestEvent, req):
                        if reset_coro:
                            reset_coro.close()
                        return
                    # apply reset
                    if reset_coro:
-                        reset_coro.close()
+                        await reset_coro
                    return
-                # apply reset
+                    register_active_runner(event.unified_msg_origin, agent_runner)
-                if reset_coro:
+                    runner_registered = True
-                    await reset_coro
+                    action_type = event.get_extra("action_type")
-                action_type = event.get_extra("action_type")
+                    event.trace.record(
-
+                        "astr_agent_prepare",
-                event.trace.record(
+                        system_prompt=req.system_prompt,
-                    "astr_agent_prepare",
+                        tools=req.func_tool.names() if req.func_tool else [],
-                    system_prompt=req.system_prompt,
+                        stream=streaming_response,
-                    tools=req.func_tool.names() if req.func_tool else [],
+                        chat_provider={
-                    stream=streaming_response,
+                            "id": provider.provider_config.get("id", ""),
-                    chat_provider={
+                            "model": provider.get_model(),
-                        "id": provider.provider_config.get("id", ""),
+                        },
                        "model": provider.get_model(),
                    },
                )
                # 检测 Live Mode
                if action_type == "live":
                    # Live Mode: 使用 run_live_agent
                    logger.info("[Internal Agent] 检测到 Live Mode，启用 TTS 处理")
                    # 获取 TTS Provider
                    tts_provider = (
                        self.ctx.plugin_manager.context.get_using_tts_provider(
                            event.unified_msg_origin
                        )
                    )
-                    if not tts_provider:
+                    # 检测 Live Mode
-                        logger.warning(
+                    if action_type == "live":
-                            "[Live Mode] TTS Provider 未配置，将使用普通流式模式"
+                        # Live Mode: 使用 run_live_agent
                        logger.info("[Internal Agent] 检测到 Live Mode，启用 TTS 处理")
                        # 获取 TTS Provider
                        tts_provider = (
                            self.ctx.plugin_manager.context.get_using_tts_provider(
                                event.unified_msg_origin
                            )
                        )
-                    # 使用 run_live_agent，总是使用流式响应
+                        if not tts_provider:
-                    event.set_result(
+                            logger.warning(
-                        MessageEventResult()
+                                "[Live Mode] TTS Provider 未配置，将使用普通流式模式"
-                        .set_result_content_type(ResultContentType.STREAMING_RESULT)
+                            )
-                        .set_async_stream(
+
-                            run_live_agent(
+                        # 使用 run_live_agent，总是使用流式响应
-                                agent_runner,
+                        event.set_result(
-                                tts_provider,
+                            MessageEventResult()
-                                self.max_step,
+                            .set_result_content_type(ResultContentType.STREAMING_RESULT)
-                                self.show_tool_use,
+                            .set_async_stream(
-                                self.show_tool_call_result,
+                                run_live_agent(
-                                show_reasoning=self.show_reasoning,
+                                    agent_runner,
                                    tts_provider,
                                    self.max_step,
                                    self.show_tool_use,
                                    self.show_tool_call_result,
                                    show_reasoning=self.show_reasoning,
                                ),
                            ),
-                        ),
+                        )
-                    )
+                        yield
                    yield
-                    # 保存历史记录
+                        # 保存历史记录
-                    if agent_runner.done() and (
+                        if agent_runner.done() and (
-                        not event.is_stopped() or agent_runner.was_aborted()
+                            not event.is_stopped() or agent_runner.was_aborted()
-                    ):
+                        ):
                            await self._save_to_history(
                                event,
                                req,
                                agent_runner.get_final_llm_resp(),
                                agent_runner.run_context.messages,
                                agent_runner.stats,
                                user_aborted=agent_runner.was_aborted(),
                            )
                    elif streaming_response and not stream_to_general:
                        # 流式响应
                        event.set_result(
                            MessageEventResult()
                            .set_result_content_type(ResultContentType.STREAMING_RESULT)
                            .set_async_stream(
                                run_agent(
                                    agent_runner,
                                    self.max_step,
                                    self.show_tool_use,
                                    self.show_tool_call_result,
                                    show_reasoning=self.show_reasoning,
                                ),
                            ),
                        )
                        yield
                        if agent_runner.done():
                            if final_llm_resp := agent_runner.get_final_llm_resp():
                                if final_llm_resp.completion_text:
                                    chain = (
                                        MessageChain()
                                        .message(final_llm_resp.completion_text)
                                        .chain
                                    )
                                elif final_llm_resp.result_chain:
                                    chain = final_llm_resp.result_chain.chain
                                else:
                                    chain = MessageChain().chain
                                event.set_result(
                                    MessageEventResult(
                                        chain=chain,
                                        result_content_type=ResultContentType.STREAMING_FINISH,
                                    ),
                                )
                    else:
                        async for _ in run_agent(
                            agent_runner,
                            self.max_step,
                            self.show_tool_use,
                            self.show_tool_call_result,
                            stream_to_general,
                            show_reasoning=self.show_reasoning,
                        ):
                            yield
                    final_resp = agent_runner.get_final_llm_resp()
                    event.trace.record(
                        "astr_agent_complete",
                        stats=agent_runner.stats.to_dict(),
                        resp=final_resp.completion_text if final_resp else None,
                    )
                    # 检查事件是否被停止，如果被停止则不保存历史记录
                    if not event.is_stopped() or agent_runner.was_aborted():
                        await self._save_to_history(
                            event,
                            req,
-                            agent_runner.get_final_llm_resp(),
+                            final_resp,
                            agent_runner.run_context.messages,
                            agent_runner.stats,
                            user_aborted=agent_runner.was_aborted(),
                        )
-                elif streaming_response and not stream_to_general:
+                    asyncio.create_task(
-                    # 流式响应
+                        Metric.upload(
-                    event.set_result(
+                            llm_tick=1,
-                        MessageEventResult()
+                            model_name=agent_runner.provider.get_model(),
-                        .set_result_content_type(ResultContentType.STREAMING_RESULT)
+                            provider_type=agent_runner.provider.meta().type,
                        .set_async_stream(
                            run_agent(
                                agent_runner,
                                self.max_step,
                                self.show_tool_use,
                                self.show_tool_call_result,
                                show_reasoning=self.show_reasoning,
                            ),
                        ),
                    )
-                    yield
+                finally:
-                    if agent_runner.done():
+                    if runner_registered and agent_runner is not None:
-                        if final_llm_resp := agent_runner.get_final_llm_resp():
+                        unregister_active_runner(event.unified_msg_origin, agent_runner)
                            if final_llm_resp.completion_text:
                                chain = (
                                    MessageChain()
                                    .message(final_llm_resp.completion_text)
                                    .chain
                                )
                            elif final_llm_resp.result_chain:
                                chain = final_llm_resp.result_chain.chain
                            else:
                                chain = MessageChain().chain
                            event.set_result(
                                MessageEventResult(
                                    chain=chain,
                                    result_content_type=ResultContentType.STREAMING_FINISH,
                                ),
                            )
                else:
                    async for _ in run_agent(
                        agent_runner,
                        self.max_step,
                        self.show_tool_use,
                        self.show_tool_call_result,
                        stream_to_general,
                        show_reasoning=self.show_reasoning,
                    ):
                        yield
                final_resp = agent_runner.get_final_llm_resp()
                event.trace.record(
                    "astr_agent_complete",
                    stats=agent_runner.stats.to_dict(),
                    resp=final_resp.completion_text if final_resp else None,
                )
                # 检查事件是否被停止，如果被停止则不保存历史记录
                if not event.is_stopped() or agent_runner.was_aborted():
                    await self._save_to_history(
                        event,
                        req,
                        final_resp,
                        agent_runner.run_context.messages,
                        agent_runner.stats,
                        user_aborted=agent_runner.was_aborted(),
                    )
            asyncio.create_task(
                Metric.upload(
                    llm_tick=1,
                    model_name=agent_runner.provider.get_model(),
                    provider_type=agent_runner.provider.meta().type,
                ),
            )
        except Exception as e:
            logger.error(f"Error occurred while processing agent: {e}")
@@ -340,6 +371,13 @@ class InternalAgentSubStage(Stage):
                    f"Error occurred while processing agent request: {e}"
                )
            )
        finally:
            if follow_up_capture:
                await finalize_follow_up_capture(
                    follow_up_capture,
                    activated=follow_up_activated,
                    consumed_marked=follow_up_consumed_marked,
                )
    async def _save_to_history(
        self,
@@ -0,0 +1,465 @@
 import json
 import mimetypes
 import shutil
 import uuid
 from collections.abc import Awaitable, Callable, Sequence
 from pathlib import Path
 from typing import Any
 from astrbot.core.db.po import Attachment
 from astrbot.core.message.components import (
    File,
    Image,
    Json,
    Plain,
    Record,
    Reply,
    Video,
 )
 from astrbot.core.message.message_event_result import MessageChain
 AttachmentGetter = Callable[[str], Awaitable[Attachment | None]]
 AttachmentInserter = Callable[[str, str, str], Awaitable[Attachment | None]]
 ReplyHistoryGetter = Callable[
    [Any],
    Awaitable[tuple[list[dict], str | None, str | None] | None],
 ]
 MEDIA_PART_TYPES = {"image", "record", "file", "video"}
 def strip_message_parts_path_fields(message_parts: list[dict]) -> list[dict]:
    return [{k: v for k, v in part.items() if k != "path"} for part in message_parts]
 def webchat_message_parts_have_content(message_parts: list[dict]) -> bool:
    return any(
        part.get("type") in ("plain", "image", "record", "file", "video")
        and (part.get("text") or part.get("attachment_id") or part.get("filename"))
        for part in message_parts
    )
 async def parse_webchat_message_parts(
    message_parts: list,
    *,
    strict: bool = False,
    include_empty_plain: bool = False,
    verify_media_path_exists: bool = True,
    reply_history_getter: ReplyHistoryGetter | None = None,
    current_depth: int = 0,
    max_reply_depth: int = 0,
    cast_reply_id_to_str: bool = True,
 ) -> tuple[list, list[str], bool]:
    """Parse webchat message parts into components/text parts.
    Returns:
        tuple[list, list[str], bool]:
            (components, plain_text_parts, has_non_reply_content)
    """
    components = []
    text_parts: list[str] = []
    has_content = False
    for part in message_parts:
        if not isinstance(part, dict):
            if strict:
                raise ValueError("message part must be an object")
            continue
        part_type = str(part.get("type", "")).strip()
        if part_type == "plain":
            text = str(part.get("text", ""))
            if text or include_empty_plain:
                components.append(Plain(text=text))
                text_parts.append(text)
            if text:
                has_content = True
            continue
        if part_type == "reply":
            message_id = part.get("message_id")
            if message_id is None:
                if strict:
                    raise ValueError("reply part missing message_id")
                continue
            reply_chain = []
            reply_message_str = str(part.get("selected_text", ""))
            sender_id = None
            sender_name = None
            if reply_message_str:
                reply_chain = [Plain(text=reply_message_str)]
            elif (
                reply_history_getter
                and current_depth < max_reply_depth
                and message_id is not None
            ):
                reply_info = await reply_history_getter(message_id)
                if reply_info:
                    reply_parts, sender_id, sender_name = reply_info
                    (
                        reply_chain,
                        reply_text_parts,
                        _,
                    ) = await parse_webchat_message_parts(
                        reply_parts,
                        strict=strict,
                        include_empty_plain=include_empty_plain,
                        verify_media_path_exists=verify_media_path_exists,
                        reply_history_getter=reply_history_getter,
                        current_depth=current_depth + 1,
                        max_reply_depth=max_reply_depth,
                        cast_reply_id_to_str=cast_reply_id_to_str,
                    )
                    reply_message_str = "".join(reply_text_parts)
            reply_id = str(message_id) if cast_reply_id_to_str else message_id
            components.append(
                Reply(
                    id=reply_id,
                    message_str=reply_message_str,
                    chain=reply_chain,
                    sender_id=sender_id,
                    sender_nickname=sender_name,
                )
            )
            continue
        if part_type not in MEDIA_PART_TYPES:
            if strict:
                raise ValueError(f"unsupported message part type: {part_type}")
            continue
        path = part.get("path")
        if not path:
            if strict:
                raise ValueError(f"{part_type} part missing path")
            continue
        file_path = Path(str(path))
        if verify_media_path_exists and not file_path.exists():
            if strict:
                raise ValueError(f"file not found: {file_path!s}")
            continue
        file_path_str = (
            str(file_path.resolve()) if verify_media_path_exists else str(file_path)
        )
        has_content = True
        if part_type == "image":
            components.append(Image.fromFileSystem(file_path_str))
        elif part_type == "record":
            components.append(Record.fromFileSystem(file_path_str))
        elif part_type == "video":
            components.append(Video.fromFileSystem(file_path_str))
        else:
            filename = str(part.get("filename", "")).strip() or file_path.name
            components.append(File(name=filename, file=file_path_str))
    return components, text_parts, has_content
 async def build_webchat_message_parts(
    message_payload: str | list,
    *,
    get_attachment_by_id: AttachmentGetter,
    strict: bool = False,
 ) -> list[dict]:
    if isinstance(message_payload, str):
        text = message_payload.strip()
        return [{"type": "plain", "text": text}] if text else []
    if not isinstance(message_payload, list):
        if strict:
            raise ValueError("message must be a string or list")
        return []
    message_parts: list[dict] = []
    for part in message_payload:
        if not isinstance(part, dict):
            if strict:
                raise ValueError("message part must be an object")
            continue
        part_type = str(part.get("type", "")).strip()
        if part_type == "plain":
            text = str(part.get("text", ""))
            if text:
                message_parts.append({"type": "plain", "text": text})
            continue
        if part_type == "reply":
            message_id = part.get("message_id")
            if message_id is None:
                if strict:
                    raise ValueError("reply part missing message_id")
                continue
            message_parts.append(
                {
                    "type": "reply",
                    "message_id": message_id,
                    "selected_text": str(part.get("selected_text", "")),
                }
            )
            continue
        if part_type not in MEDIA_PART_TYPES:
            if strict:
                raise ValueError(f"unsupported message part type: {part_type}")
            continue
        attachment_id = part.get("attachment_id")
        if not attachment_id:
            if strict:
                raise ValueError(f"{part_type} part missing attachment_id")
            continue
        attachment = await get_attachment_by_id(str(attachment_id))
        if not attachment:
            if strict:
                raise ValueError(f"attachment not found: {attachment_id}")
            continue
        attachment_path = Path(attachment.path)
        message_parts.append(
            {
                "type": attachment.type,
                "attachment_id": attachment.attachment_id,
                "filename": attachment_path.name,
                "path": str(attachment_path),
            }
        )
    return message_parts
 def webchat_message_parts_to_message_chain(
    message_parts: list[dict],
    *,
    strict: bool = False,
 ) -> MessageChain:
    components = []
    has_content = False
    for part in message_parts:
        if not isinstance(part, dict):
            if strict:
                raise ValueError("message part must be an object")
            continue
        part_type = str(part.get("type", "")).strip()
        if part_type == "plain":
            text = str(part.get("text", ""))
            if text:
                components.append(Plain(text=text))
                has_content = True
            continue
        if part_type == "reply":
            message_id = part.get("message_id")
            if message_id is None:
                if strict:
                    raise ValueError("reply part missing message_id")
                continue
            components.append(
                Reply(
                    id=str(message_id),
                    message_str=str(part.get("selected_text", "")),
                    chain=[],
                )
            )
            continue
        if part_type not in MEDIA_PART_TYPES:
            if strict:
                raise ValueError(f"unsupported message part type: {part_type}")
            continue
        path = part.get("path")
        if not path:
            if strict:
                raise ValueError(f"{part_type} part missing path")
            continue
        file_path = Path(str(path))
        if not file_path.exists():
            if strict:
                raise ValueError(f"file not found: {file_path!s}")
            continue
        file_path_str = str(file_path.resolve())
        has_content = True
        if part_type == "image":
            components.append(Image.fromFileSystem(file_path_str))
        elif part_type == "record":
            components.append(Record.fromFileSystem(file_path_str))
        elif part_type == "video":
            components.append(Video.fromFileSystem(file_path_str))
        else:
            filename = str(part.get("filename", "")).strip() or file_path.name
            components.append(File(name=filename, file=file_path_str))
    if strict and (not components or not has_content):
        raise ValueError("Message content is empty (reply only is not allowed)")
    return MessageChain(chain=components)
 async def build_message_chain_from_payload(
    message_payload: str | list,
    *,
    get_attachment_by_id: AttachmentGetter,
    strict: bool = True,
 ) -> MessageChain:
    message_parts = await build_webchat_message_parts(
        message_payload,
        get_attachment_by_id=get_attachment_by_id,
        strict=strict,
    )
    components, _, has_content = await parse_webchat_message_parts(
        message_parts,
        strict=strict,
    )
    if strict and (not components or not has_content):
        raise ValueError("Message content is empty (reply only is not allowed)")
    return MessageChain(chain=components)
 async def create_attachment_part_from_existing_file(
    filename: str,
    *,
    attach_type: str,
    insert_attachment: AttachmentInserter,
    attachments_dir: str | Path,
    fallback_dirs: Sequence[str | Path] = (),
 ) -> dict | None:
    basename = Path(filename).name
    candidate_paths = [Path(attachments_dir) / basename]
    candidate_paths.extend(Path(p) / basename for p in fallback_dirs)
    file_path = next((path for path in candidate_paths if path.exists()), None)
    if not file_path:
        return None
    mime_type, _ = mimetypes.guess_type(str(file_path))
    attachment = await insert_attachment(
        str(file_path),
        attach_type,
        mime_type or "application/octet-stream",
    )
    if not attachment:
        return None
    return {
        "type": attach_type,
        "attachment_id": attachment.attachment_id,
        "filename": file_path.name,
    }
 async def message_chain_to_storage_message_parts(
    message_chain: MessageChain,
    *,
    insert_attachment: AttachmentInserter,
    attachments_dir: str | Path,
 ) -> list[dict]:
    target_dir = Path(attachments_dir)
    target_dir.mkdir(parents=True, exist_ok=True)
    parts: list[dict] = []
    for comp in message_chain.chain:
        if isinstance(comp, Plain):
            if comp.text:
                parts.append({"type": "plain", "text": comp.text})
            continue
        if isinstance(comp, Json):
            parts.append(
                {"type": "plain", "text": json.dumps(comp.data, ensure_ascii=False)}
            )
            continue
        if isinstance(comp, Image):
            file_path = await comp.convert_to_file_path()
            attachment_part = await _copy_file_to_attachment_part(
                file_path=file_path,
                attach_type="image",
                insert_attachment=insert_attachment,
                attachments_dir=target_dir,
            )
            if attachment_part:
                parts.append(attachment_part)
            continue
        if isinstance(comp, Record):
            file_path = await comp.convert_to_file_path()
            attachment_part = await _copy_file_to_attachment_part(
                file_path=file_path,
                attach_type="record",
                insert_attachment=insert_attachment,
                attachments_dir=target_dir,
            )
            if attachment_part:
                parts.append(attachment_part)
            continue
        if isinstance(comp, Video):
            file_path = await comp.convert_to_file_path()
            attachment_part = await _copy_file_to_attachment_part(
                file_path=file_path,
                attach_type="video",
                insert_attachment=insert_attachment,
                attachments_dir=target_dir,
            )
            if attachment_part:
                parts.append(attachment_part)
            continue
        if isinstance(comp, File):
            file_path = await comp.get_file()
            attachment_part = await _copy_file_to_attachment_part(
                file_path=file_path,
                attach_type="file",
                insert_attachment=insert_attachment,
                attachments_dir=target_dir,
                display_name=comp.name,
            )
            if attachment_part:
                parts.append(attachment_part)
            continue
    return parts
 async def _copy_file_to_attachment_part(
    *,
    file_path: str,
    attach_type: str,
    insert_attachment: AttachmentInserter,
    attachments_dir: Path,
    display_name: str | None = None,
 ) -> dict | None:
    src_path = Path(file_path)
    if not src_path.exists() or not src_path.is_file():
        return None
    suffix = src_path.suffix
    target_path = attachments_dir / f"{uuid.uuid4().hex}{suffix}"
    shutil.copy2(src_path, target_path)
    mime_type, _ = mimetypes.guess_type(target_path.name)
    attachment = await insert_attachment(
        str(target_path),
        attach_type,
        mime_type or "application/octet-stream",
    )
    if not attachment:
        return None
    return {
        "type": attach_type,
        "attachment_id": attachment.attachment_id,
        "filename": display_name or src_path.name,
    }
@@ -3,12 +3,12 @@ import os
 import time
 import uuid
 from collections.abc import Callable, Coroutine
 from pathlib import Path
 from typing import Any
 from astrbot import logger
 from astrbot.core import db_helper
 from astrbot.core.db.po import PlatformMessageHistory
 from astrbot.core.message.components import File, Image, Plain, Record, Reply, Video
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.platform import (
    AstrBotMessage,
@@ -21,10 +21,23 @@ from astrbot.core.platform.astr_message_event import MessageSesion
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 from ...register import register_platform_adapter
 from .message_parts_helper import (
    message_chain_to_storage_message_parts,
    parse_webchat_message_parts,
 )
 from .webchat_event import WebChatMessageEvent
 from .webchat_queue_mgr import WebChatQueueMgr, webchat_queue_mgr
 def _extract_conversation_id(session_id: str) -> str:
    """Extract raw webchat conversation id from event/session id."""
    if session_id.startswith("webchat!"):
        parts = session_id.split("!", 2)
        if len(parts) == 3:
            return parts[2]
    return session_id
 class QueueListener:
    def __init__(
        self,
@@ -57,13 +70,15 @@ class WebChatAdapter(Platform):
        self.settings = platform_settings
        self.imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
        self.attachments_dir = Path(get_astrbot_data_path()) / "attachments"
        os.makedirs(self.imgs_dir, exist_ok=True)
        self.attachments_dir.mkdir(parents=True, exist_ok=True)
        self.metadata = PlatformMetadata(
            name="webchat",
            description="webchat",
            id="webchat",
-            support_proactive_message=False,
+            support_proactive_message=True,
        )
        self._shutdown_event = asyncio.Event()
        self._webchat_queue_mgr = webchat_queue_mgr
@@ -73,10 +88,67 @@ class WebChatAdapter(Platform):
        session: MessageSesion,
        message_chain: MessageChain,
    ) -> None:
-        message_id = f"active_{str(uuid.uuid4())}"
+        conversation_id = _extract_conversation_id(session.session_id)
-        await WebChatMessageEvent._send(message_id, message_chain, session.session_id)
+        active_request_ids = self._webchat_queue_mgr.list_back_request_ids(
            conversation_id
        )
        subscription_request_ids = [
            req_id for req_id in active_request_ids if req_id.startswith("ws_sub_")
        ]
        target_request_ids = subscription_request_ids or active_request_ids
        if target_request_ids:
            for request_id in target_request_ids:
                await WebChatMessageEvent._send(
                    request_id,
                    message_chain,
                    session.session_id,
                )
        else:
            message_id = f"active_{uuid.uuid4()!s}"
            await WebChatMessageEvent._send(
                message_id,
                message_chain,
                session.session_id,
            )
        should_persist = (
            bool(subscription_request_ids)
            or not active_request_ids
            or all(req_id.startswith("active_") for req_id in active_request_ids)
        )
        if should_persist:
            try:
                await self._save_proactive_message(conversation_id, message_chain)
            except Exception as e:
                logger.error(
                    f"[WebChatAdapter] Failed to save proactive message: {e}",
                    exc_info=True,
                )
        await super().send_by_session(session, message_chain)
    async def _save_proactive_message(
        self,
        conversation_id: str,
        message_chain: MessageChain,
    ) -> None:
        message_parts = await message_chain_to_storage_message_parts(
            message_chain,
            insert_attachment=db_helper.insert_attachment,
            attachments_dir=self.attachments_dir,
        )
        if not message_parts:
            return
        await db_helper.insert_platform_message_history(
            platform_id="webchat",
            user_id=conversation_id,
            content={"type": "bot", "message": message_parts},
            sender_id="bot",
            sender_name="bot",
        )
    async def _get_message_history(
        self, message_id: int
    ) -> PlatformMessageHistory | None:
@@ -98,72 +170,30 @@ class WebChatAdapter(Platform):
        Returns:
            tuple[list, list[str]]: (消息组件列表, 纯文本列表)
        """
        components = []
        text_parts = []
-        for part in message_parts:
+        async def get_reply_parts(
-            part_type = part.get("type")
+            message_id: Any,
-            if part_type == "plain":
+        ) -> tuple[list[dict], str | None, str | None] | None:
-                text = part.get("text", "")
+            history = await self._get_message_history(message_id)
-                components.append(Plain(text=text))
+            if not history or not history.content:
-                text_parts.append(text)
+                return None
            elif part_type == "reply":
                message_id = part.get("message_id")
                reply_chain = []
                reply_message_str = part.get("selected_text", "")
                sender_id = None
                sender_name = None
-                if reply_message_str:
+            reply_parts = history.content.get("message", [])
-                    reply_chain = [Plain(text=reply_message_str)]
+            if not isinstance(reply_parts, list):
                return None
-                # recursively get the content of the referenced message, if selected_text is empty
+            return reply_parts, history.sender_id, history.sender_name
                if not reply_message_str and depth < max_depth and message_id:
                    history = await self._get_message_history(message_id)
                    if history and history.content:
                        reply_parts = history.content.get("message", [])
                        if isinstance(reply_parts, list):
                            (
                                reply_chain,
                                reply_text_parts,
                            ) = await self._parse_message_parts(
                                reply_parts,
                                depth=depth + 1,
                                max_depth=max_depth,
                            )
                            reply_message_str = "".join(reply_text_parts)
                        sender_id = history.sender_id
                        sender_name = history.sender_name
                components.append(
                    Reply(
                        id=message_id,
                        chain=reply_chain,
                        message_str=reply_message_str,
                        sender_id=sender_id,
                        sender_nickname=sender_name,
                    )
                )
            elif part_type == "image":
                path = part.get("path")
                if path:
                    components.append(Image.fromFileSystem(path))
            elif part_type == "record":
                path = part.get("path")
                if path:
                    components.append(Record.fromFileSystem(path))
            elif part_type == "file":
                path = part.get("path")
                if path:
                    filename = part.get("filename") or (
                        os.path.basename(path) if path else "file"
                    )
                    components.append(File(name=filename, file=path))
            elif part_type == "video":
                path = part.get("path")
                if path:
                    components.append(Video.fromFileSystem(path))
        components, text_parts, _ = await parse_webchat_message_parts(
            message_parts,
            strict=False,
            include_empty_plain=True,
            verify_media_path_exists=False,
            reply_history_getter=get_reply_parts,
            current_depth=depth,
            max_reply_depth=max_depth,
            cast_reply_id_to_str=False,
        )
        return components, text_parts
    async def convert_message(self, data: tuple) -> AstrBotMessage:
@@ -14,6 +14,15 @@ from .webchat_queue_mgr import webchat_queue_mgr
 attachments_dir = os.path.join(get_astrbot_data_path(), "attachments")
 def _extract_conversation_id(session_id: str) -> str:
    """Extract raw webchat conversation id from event/session id."""
    if session_id.startswith("webchat!"):
        parts = session_id.split("!", 2)
        if len(parts) == 3:
            return parts[2]
    return session_id
 class WebChatMessageEvent(AstrMessageEvent):
    def __init__(self, message_str, message_obj, platform_meta, session_id) -> None:
        super().__init__(message_str, message_obj, platform_meta, session_id)
@@ -27,7 +36,7 @@ class WebChatMessageEvent(AstrMessageEvent):
        streaming: bool = False,
    ) -> str | None:
        request_id = str(message_id)
-        conversation_id = session_id.split("!")[-1]
+        conversation_id = _extract_conversation_id(session_id)
        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(
            request_id,
            conversation_id,
@@ -130,7 +139,7 @@ class WebChatMessageEvent(AstrMessageEvent):
        reasoning_content = ""
        message_id = self.message_obj.message_id
        request_id = str(message_id)
-        conversation_id = self.session_id.split("!")[-1]
+        conversation_id = _extract_conversation_id(self.session_id)
        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(
            request_id,
            conversation_id,
@@ -75,6 +75,10 @@ class WebChatQueueMgr:
        if task is not None:
            task.cancel()
    def list_back_request_ids(self, conversation_id: str) -> list[str]:
        """List active back-queue request IDs for a conversation."""
        return list(self._conversation_back_requests.get(conversation_id, set()))
    def has_queue(self, conversation_id: str) -> bool:
        """Check if a queue exists for the given conversation ID"""
        return conversation_id in self.queues
@@ -1,6 +1,5 @@
 import asyncio
 import json
 import mimetypes
 import os
 import re
 import uuid
@@ -14,6 +13,12 @@ from astrbot.core import logger, sp
 from astrbot.core.core_lifecycle import AstrBotCoreLifecycle
 from astrbot.core.db import BaseDatabase
 from astrbot.core.platform.message_type import MessageType
 from astrbot.core.platform.sources.webchat.message_parts_helper import (
    build_webchat_message_parts,
    create_attachment_part_from_existing_file,
    strip_message_parts_path_fields,
    webchat_message_parts_have_content,
 )
 from astrbot.core.platform.sources.webchat.webchat_queue_mgr import webchat_queue_mgr
 from astrbot.core.utils.active_event_registry import active_event_registry
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
@@ -166,83 +171,24 @@ class ChatRoute(Route):
        )
    async def _build_user_message_parts(self, message: str | list) -> list[dict]:
-        """构建用户消息的部分列表
+        """构建用户消息的部分列表。"""
-
+        return await build_webchat_message_parts(
-        Args:
+            message,
-            message: 文本消息 (str) 或消息段列表 (list)
+            get_attachment_by_id=self.db.get_attachment_by_id,
-        """
+            strict=False,
-        parts = []
+        )
        if isinstance(message, list):
            for part in message:
                part_type = part.get("type")
                if part_type == "plain":
                    parts.append({"type": "plain", "text": part.get("text", "")})
                elif part_type == "reply":
                    parts.append(
                        {
                            "type": "reply",
                            "message_id": part.get("message_id"),
                            "selected_text": part.get("selected_text", ""),
                        }
                    )
                elif attachment_id := part.get("attachment_id"):
                    attachment = await self.db.get_attachment_by_id(attachment_id)
                    if attachment:
                        parts.append(
                            {
                                "type": attachment.type,
                                "attachment_id": attachment.attachment_id,
                                "filename": os.path.basename(attachment.path),
                                "path": attachment.path,  # will be deleted
                            }
                        )
            return parts
        if message:
            parts.append({"type": "plain", "text": message})
        return parts
    async def _create_attachment_from_file(
        self, filename: str, attach_type: str
    ) -> dict | None:
-        """从本地文件创建 attachment 并返回消息部分
+        """从本地文件创建 attachment 并返回消息部分。"""
-
+        return await create_attachment_part_from_existing_file(
-        用于处理 bot 回复中的媒体文件
+            filename,
-
+            attach_type=attach_type,
-        Args:
+            insert_attachment=self.db.insert_attachment,
-            filename: 存储的文件名
+            attachments_dir=self.attachments_dir,
-            attach_type: 附件类型 (image, record, file, video)
+            fallback_dirs=[self.legacy_img_dir],
        """
        basename = os.path.basename(filename)
        candidate_paths = [
            os.path.join(self.attachments_dir, basename),
            os.path.join(self.legacy_img_dir, basename),
        ]
        file_path = next((p for p in candidate_paths if os.path.exists(p)), None)
        if not file_path:
            return None
        # guess mime type
        mime_type, _ = mimetypes.guess_type(filename)
        if not mime_type:
            mime_type = "application/octet-stream"
        # insert attachment
        attachment = await self.db.insert_attachment(
            path=file_path,
            type=attach_type,
            mime_type=mime_type,
        )
        if not attachment:
            return None
        return {
            "type": attach_type,
            "attachment_id": attachment.attachment_id,
            "filename": os.path.basename(file_path),
        }
    def _extract_web_search_refs(
        self, accumulated_text: str, accumulated_parts: list
@@ -356,21 +302,6 @@ class ChatRoute(Route):
        selected_model = post_data.get("selected_model")
        enable_streaming = post_data.get("enable_streaming", True)
        # 检查消息是否为空
        if isinstance(message, list):
            has_content = any(
                part.get("type") in ("plain", "image", "record", "file", "video")
                for part in message
            )
            if not has_content:
                return (
                    Response()
                    .error("Message content is empty (reply only is not allowed)")
                    .__dict__
                )
        elif not message:
            return Response().error("Message are both empty").__dict__
        if not session_id:
            return Response().error("session_id is empty").__dict__
@@ -378,6 +309,12 @@ class ChatRoute(Route):
        # 构建用户消息段（包含 path 用于传递给 adapter）
        message_parts = await self._build_user_message_parts(message)
        if not webchat_message_parts_have_content(message_parts):
            return (
                Response()
                .error("Message content is empty (reply only is not allowed)")
                .__dict__
            )
        message_id = str(uuid.uuid4())
        back_queue = webchat_queue_mgr.get_or_create_back_queue(
@@ -583,10 +520,7 @@ class ChatRoute(Route):
            ),
        )
-        message_parts_for_storage = []
+        message_parts_for_storage = strip_message_parts_path_fields(message_parts)
        for part in message_parts:
            part_copy = {k: v for k, v in part.items() if k != "path"}
            message_parts_for_storage.append(part_copy)
        await self.platform_history_mgr.insert(
            platform_id="webchat",
@@ -1,6 +1,7 @@
 import asyncio
 import json
 import os
 import re
 import time
 import uuid
 import wave
@@ -10,9 +11,16 @@ import jwt
 from quart import websocket
 from astrbot import logger
 from astrbot.core import sp
 from astrbot.core.core_lifecycle import AstrBotCoreLifecycle
 from astrbot.core.platform.sources.webchat.message_parts_helper import (
    build_webchat_message_parts,
    create_attachment_part_from_existing_file,
    strip_message_parts_path_fields,
    webchat_message_parts_have_content,
 )
 from astrbot.core.platform.sources.webchat.webchat_queue_mgr import webchat_queue_mgr
-from astrbot.core.utils.astrbot_path import get_astrbot_temp_path
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path, get_astrbot_temp_path
 from .route import Route, RouteContext
@@ -30,6 +38,9 @@ class LiveChatSession:
        self.audio_frames: list[bytes] = []
        self.current_stamp: str | None = None
        self.temp_audio_path: str | None = None
        self.chat_subscriptions: dict[str, str] = {}
        self.chat_subscription_tasks: dict[str, asyncio.Task] = {}
        self.ws_send_lock = asyncio.Lock()
    def start_speaking(self, stamp: str) -> None:
        """开始说话"""
@@ -106,13 +117,26 @@ class LiveChatRoute(Route):
        self.core_lifecycle = core_lifecycle
        self.db = db
        self.plugin_manager = core_lifecycle.plugin_manager
        self.platform_history_mgr = core_lifecycle.platform_message_history_manager
        self.sessions: dict[str, LiveChatSession] = {}
        self.attachments_dir = os.path.join(get_astrbot_data_path(), "attachments")
        self.legacy_img_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
        os.makedirs(self.attachments_dir, exist_ok=True)
        # 注册 WebSocket 路由
        self.app.websocket("/api/live_chat/ws")(self.live_chat_ws)
        self.app.websocket("/api/unified_chat/ws")(self.unified_chat_ws)
    async def live_chat_ws(self) -> None:
-        """Live Chat WebSocket 处理器"""
+        """Legacy Live Chat WebSocket 处理器（默认 ct=live）"""
        await self._unified_ws_loop(force_ct="live")
    async def unified_chat_ws(self) -> None:
        """Unified Chat WebSocket 处理器（支持 ct=live/chat）"""
        await self._unified_ws_loop(force_ct=None)
    async def _unified_ws_loop(self, force_ct: str | None = None) -> None:
        """统一 WebSocket 循环"""
        # WebSocket 不能通过 header 传递 token，需要从 query 参数获取
        # 注意：WebSocket 上下文使用 websocket.args 而不是 request.args
        token = websocket.args.get("token")
@@ -140,7 +164,11 @@ class LiveChatRoute(Route):
        try:
            while True:
                message = await websocket.receive_json()
-                await self._handle_message(live_session, message)
+                ct = force_ct or message.get("ct", "live")
                if ct == "chat":
                    await self._handle_chat_message(live_session, message)
                else:
                    await self._handle_message(live_session, message)
        except Exception as e:
            logger.error(f"[Live Chat] WebSocket 错误: {e}", exc_info=True)
@@ -148,10 +176,488 @@ class LiveChatRoute(Route):
        finally:
            # 清理会话
            if session_id in self.sessions:
                await self._cleanup_chat_subscriptions(live_session)
                live_session.cleanup()
                del self.sessions[session_id]
            logger.info(f"[Live Chat] WebSocket 连接关闭: {username}")
    async def _create_attachment_from_file(
        self, filename: str, attach_type: str
    ) -> dict | None:
        """从本地文件创建 attachment 并返回消息部分。"""
        return await create_attachment_part_from_existing_file(
            filename,
            attach_type=attach_type,
            insert_attachment=self.db.insert_attachment,
            attachments_dir=self.attachments_dir,
            fallback_dirs=[self.legacy_img_dir],
        )
    def _extract_web_search_refs(
        self, accumulated_text: str, accumulated_parts: list
    ) -> dict:
        """从消息中提取 web_search 引用。"""
        supported = ["web_search_tavily", "web_search_bocha"]
        web_search_results = {}
        tool_call_parts = [
            p
            for p in accumulated_parts
            if p.get("type") == "tool_call" and p.get("tool_calls")
        ]
        for part in tool_call_parts:
            for tool_call in part["tool_calls"]:
                if tool_call.get("name") not in supported or not tool_call.get(
                    "result"
                ):
                    continue
                try:
                    result_data = json.loads(tool_call["result"])
                    for item in result_data.get("results", []):
                        if idx := item.get("index"):
                            web_search_results[idx] = {
                                "url": item.get("url"),
                                "title": item.get("title"),
                                "snippet": item.get("snippet"),
                            }
                except (json.JSONDecodeError, KeyError):
                    pass
        if not web_search_results:
            return {}
        ref_indices = {
            m.strip() for m in re.findall(r"<ref>(.*?)</ref>", accumulated_text)
        }
        used_refs = []
        for ref_index in ref_indices:
            if ref_index not in web_search_results:
                continue
            payload = {"index": ref_index, **web_search_results[ref_index]}
            if favicon := sp.temporary_cache.get("_ws_favicon", {}).get(payload["url"]):
                payload["favicon"] = favicon
            used_refs.append(payload)
        return {"used": used_refs} if used_refs else {}
    async def _save_bot_message(
        self,
        webchat_conv_id: str,
        text: str,
        media_parts: list,
        reasoning: str,
        agent_stats: dict,
        refs: dict,
    ):
        """保存 bot 消息到历史记录。"""
        bot_message_parts = []
        bot_message_parts.extend(media_parts)
        if text:
            bot_message_parts.append({"type": "plain", "text": text})
        new_his = {"type": "bot", "message": bot_message_parts}
        if reasoning:
            new_his["reasoning"] = reasoning
        if agent_stats:
            new_his["agent_stats"] = agent_stats
        if refs:
            new_his["refs"] = refs
        return await self.platform_history_mgr.insert(
            platform_id="webchat",
            user_id=webchat_conv_id,
            content=new_his,
            sender_id="bot",
            sender_name="bot",
        )
    async def _send_chat_payload(self, session: LiveChatSession, payload: dict) -> None:
        async with session.ws_send_lock:
            await websocket.send_json(payload)
    async def _forward_chat_subscription(
        self,
        session: LiveChatSession,
        chat_session_id: str,
        request_id: str,
    ) -> None:
        back_queue = webchat_queue_mgr.get_or_create_back_queue(
            request_id, chat_session_id
        )
        try:
            while True:
                result = await back_queue.get()
                if not result:
                    continue
                await self._send_chat_payload(session, {"ct": "chat", **result})
        except asyncio.CancelledError:
            pass
        except Exception as e:
            logger.error(
                f"[Live Chat] chat subscription forward failed ({chat_session_id}): {e}",
                exc_info=True,
            )
        finally:
            webchat_queue_mgr.remove_back_queue(request_id)
            if session.chat_subscriptions.get(chat_session_id) == request_id:
                session.chat_subscriptions.pop(chat_session_id, None)
            session.chat_subscription_tasks.pop(chat_session_id, None)
    async def _ensure_chat_subscription(
        self,
        session: LiveChatSession,
        chat_session_id: str,
    ) -> str:
        existing_request_id = session.chat_subscriptions.get(chat_session_id)
        existing_task = session.chat_subscription_tasks.get(chat_session_id)
        if existing_request_id and existing_task and not existing_task.done():
            return existing_request_id
        request_id = f"ws_sub_{uuid.uuid4().hex}"
        session.chat_subscriptions[chat_session_id] = request_id
        task = asyncio.create_task(
            self._forward_chat_subscription(session, chat_session_id, request_id),
            name=f"chat_ws_sub_{chat_session_id}",
        )
        session.chat_subscription_tasks[chat_session_id] = task
        return request_id
    async def _cleanup_chat_subscriptions(self, session: LiveChatSession) -> None:
        tasks = list(session.chat_subscription_tasks.values())
        for task in tasks:
            task.cancel()
        if tasks:
            await asyncio.gather(*tasks, return_exceptions=True)
        for request_id in list(session.chat_subscriptions.values()):
            webchat_queue_mgr.remove_back_queue(request_id)
        session.chat_subscriptions.clear()
        session.chat_subscription_tasks.clear()
    async def _handle_chat_message(
        self, session: LiveChatSession, message: dict
    ) -> None:
        """处理 Chat Mode 消息（ct=chat）"""
        msg_type = message.get("t")
        if msg_type == "bind":
            chat_session_id = message.get("session_id")
            if not isinstance(chat_session_id, str) or not chat_session_id:
                await self._send_chat_payload(
                    session,
                    {
                        "ct": "chat",
                        "t": "error",
                        "data": "session_id is required",
                        "code": "INVALID_MESSAGE_FORMAT",
                    },
                )
                return
            request_id = await self._ensure_chat_subscription(session, chat_session_id)
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "type": "session_bound",
                    "session_id": chat_session_id,
                    "message_id": request_id,
                },
            )
            return
        if msg_type == "interrupt":
            session.should_interrupt = True
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": "INTERRUPTED",
                    "code": "INTERRUPTED",
                },
            )
            return
        if msg_type != "send":
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": f"Unsupported message type: {msg_type}",
                    "code": "INVALID_MESSAGE_FORMAT",
                },
            )
            return
        if session.is_processing:
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": "Session is busy",
                    "code": "PROCESSING_ERROR",
                },
            )
            return
        payload = message.get("message")
        session_id = message.get("session_id") or session.session_id
        message_id = message.get("message_id") or str(uuid.uuid4())
        selected_provider = message.get("selected_provider")
        selected_model = message.get("selected_model")
        selected_stt_provider = message.get("selected_stt_provider")
        selected_tts_provider = message.get("selected_tts_provider")
        persona_prompt = message.get("persona_prompt")
        show_reasoning = message.get("show_reasoning")
        enable_streaming = message.get("enable_streaming", True)
        if not isinstance(payload, list):
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": "message must be list",
                    "code": "INVALID_MESSAGE_FORMAT",
                },
            )
            return
        message_parts = await self._build_chat_message_parts(payload)
        has_content = webchat_message_parts_have_content(message_parts)
        if not has_content:
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": "Message content is empty",
                    "code": "INVALID_MESSAGE_FORMAT",
                },
            )
            return
        await self._ensure_chat_subscription(session, session_id)
        session.is_processing = True
        session.should_interrupt = False
        back_queue = webchat_queue_mgr.get_or_create_back_queue(message_id, session_id)
        try:
            chat_queue = webchat_queue_mgr.get_or_create_queue(session_id)
            await chat_queue.put(
                (
                    session.username,
                    session_id,
                    {
                        "message": message_parts,
                        "selected_provider": selected_provider,
                        "selected_model": selected_model,
                        "selected_stt_provider": selected_stt_provider,
                        "selected_tts_provider": selected_tts_provider,
                        "persona_prompt": persona_prompt,
                        "show_reasoning": show_reasoning,
                        "enable_streaming": enable_streaming,
                        "message_id": message_id,
                    },
                ),
            )
            message_parts_for_storage = strip_message_parts_path_fields(message_parts)
            await self.platform_history_mgr.insert(
                platform_id="webchat",
                user_id=session_id,
                content={"type": "user", "message": message_parts_for_storage},
                sender_id=session.username,
                sender_name=session.username,
            )
            accumulated_parts = []
            accumulated_text = ""
            accumulated_reasoning = ""
            tool_calls = {}
            agent_stats = {}
            refs = {}
            while True:
                if session.should_interrupt:
                    session.should_interrupt = False
                    break
                try:
                    result = await asyncio.wait_for(back_queue.get(), timeout=1)
                except asyncio.TimeoutError:
                    continue
                if not result:
                    continue
                if result.get("message_id") and result.get("message_id") != message_id:
                    continue
                result_text = result.get("data", "")
                msg_type = result.get("type")
                streaming = result.get("streaming", False)
                chain_type = result.get("chain_type")
                if chain_type == "agent_stats":
                    try:
                        parsed_agent_stats = json.loads(result_text)
                        agent_stats = parsed_agent_stats
                        await self._send_chat_payload(
                            session,
                            {
                                "ct": "chat",
                                "type": "agent_stats",
                                "data": parsed_agent_stats,
                            },
                        )
                    except Exception:
                        pass
                    continue
                outgoing = {"ct": "chat", **result}
                await self._send_chat_payload(session, outgoing)
                if msg_type == "plain":
                    if chain_type == "tool_call":
                        try:
                            tool_call = json.loads(result_text)
                            tool_calls[tool_call.get("id")] = tool_call
                            if accumulated_text:
                                accumulated_parts.append(
                                    {"type": "plain", "text": accumulated_text}
                                )
                                accumulated_text = ""
                        except Exception:
                            pass
                    elif chain_type == "tool_call_result":
                        try:
                            tcr = json.loads(result_text)
                            tc_id = tcr.get("id")
                            if tc_id in tool_calls:
                                tool_calls[tc_id]["result"] = tcr.get("result")
                                tool_calls[tc_id]["finished_ts"] = tcr.get("ts")
                                accumulated_parts.append(
                                    {
                                        "type": "tool_call",
                                        "tool_calls": [tool_calls[tc_id]],
                                    }
                                )
                                tool_calls.pop(tc_id, None)
                        except Exception:
                            pass
                    elif chain_type == "reasoning":
                        accumulated_reasoning += result_text
                    elif streaming:
                        accumulated_text += result_text
                    else:
                        accumulated_text = result_text
                elif msg_type == "image":
                    filename = str(result_text).replace("[IMAGE]", "")
                    part = await self._create_attachment_from_file(filename, "image")
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "record":
                    filename = str(result_text).replace("[RECORD]", "")
                    part = await self._create_attachment_from_file(filename, "record")
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "file":
                    filename = str(result_text).replace("[FILE]", "").split("|", 1)[0]
                    part = await self._create_attachment_from_file(filename, "file")
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "video":
                    filename = str(result_text).replace("[VIDEO]", "").split("|", 1)[0]
                    part = await self._create_attachment_from_file(filename, "video")
                    if part:
                        accumulated_parts.append(part)
                should_save = False
                if msg_type == "end":
                    should_save = bool(
                        accumulated_parts
                        or accumulated_text
                        or accumulated_reasoning
                        or refs
                        or agent_stats
                    )
                elif (streaming and msg_type == "complete") or not streaming:
                    if chain_type not in (
                        "tool_call",
                        "tool_call_result",
                        "agent_stats",
                    ):
                        should_save = True
                if should_save:
                    try:
                        refs = self._extract_web_search_refs(
                            accumulated_text,
                            accumulated_parts,
                        )
                    except Exception as e:
                        logger.exception(
                            f"[Live Chat] Failed to extract web search refs: {e}",
                            exc_info=True,
                        )
                    saved_record = await self._save_bot_message(
                        session_id,
                        accumulated_text,
                        accumulated_parts,
                        accumulated_reasoning,
                        agent_stats,
                        refs,
                    )
                    if saved_record:
                        await self._send_chat_payload(
                            session,
                            {
                                "ct": "chat",
                                "type": "message_saved",
                                "data": {
                                    "id": saved_record.id,
                                    "created_at": saved_record.created_at.astimezone().isoformat(),
                                },
                            },
                        )
                    accumulated_parts = []
                    accumulated_text = ""
                    accumulated_reasoning = ""
                    agent_stats = {}
                    refs = {}
                if msg_type == "end":
                    break
        except Exception as e:
            logger.error(f"[Live Chat] 处理 chat 消息失败: {e}", exc_info=True)
            await self._send_chat_payload(
                session,
                {
                    "ct": "chat",
                    "t": "error",
                    "data": f"处理失败: {str(e)}",
                    "code": "PROCESSING_ERROR",
                },
            )
        finally:
            session.is_processing = False
            webchat_queue_mgr.remove_back_queue(message_id)
    async def _build_chat_message_parts(self, message: list[dict]) -> list[dict]:
        """构建 chat websocket 用户消息段（复用 webchat 逻辑）"""
        return await build_webchat_message_parts(
            message,
            get_attachment_by_id=self.db.get_attachment_by_id,
            strict=False,
        )
    async def _handle_message(self, session: LiveChatSession, message: dict) -> None:
        """处理 WebSocket 消息"""
        msg_type = message.get("t")  # 使用 t 代替 type
@@ -1,15 +1,22 @@
-from pathlib import Path
+import asyncio
 import hashlib
 import json
 from uuid import uuid4
-from quart import g, request
+from quart import g, request, websocket
 from astrbot.core import logger
 from astrbot.core.core_lifecycle import AstrBotCoreLifecycle
 from astrbot.core.db import BaseDatabase
 from astrbot.core.message.components import File, Image, Plain, Record, Reply, Video
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.platform.message_session import MessageSesion
 from astrbot.core.platform.sources.webchat.message_parts_helper import (
    build_message_chain_from_payload,
    strip_message_parts_path_fields,
    webchat_message_parts_have_content,
 )
 from astrbot.core.platform.sources.webchat.webchat_queue_mgr import webchat_queue_mgr
 from .api_key import ALL_OPEN_API_SCOPES
 from .chat import ChatRoute
 from .route import Response, Route, RouteContext
@@ -37,6 +44,7 @@ class OpenApiRoute(Route):
            "/v1/im/bots": ("GET", self.get_bots),
        }
        self.register_routes()
        self.app.websocket("/api/v1/chat/ws")(self.chat_ws)
    @staticmethod
    def _resolve_open_username(
@@ -181,6 +189,348 @@ class OpenApiRoute(Route):
        finally:
            g.username = original_username
    @staticmethod
    def _extract_ws_api_key() -> str | None:
        if key := websocket.args.get("api_key"):
            return key.strip()
        if key := websocket.args.get("key"):
            return key.strip()
        if key := websocket.headers.get("X-API-Key"):
            return key.strip()
        auth_header = websocket.headers.get("Authorization", "").strip()
        if auth_header.startswith("Bearer "):
            return auth_header.removeprefix("Bearer ").strip()
        if auth_header.startswith("ApiKey "):
            return auth_header.removeprefix("ApiKey ").strip()
        return None
    async def _authenticate_chat_ws_api_key(self) -> tuple[bool, str | None]:
        raw_key = self._extract_ws_api_key()
        if not raw_key:
            return False, "Missing API key"
        key_hash = hashlib.pbkdf2_hmac(
            "sha256",
            raw_key.encode("utf-8"),
            b"astrbot_api_key",
            100_000,
        ).hex()
        api_key = await self.db.get_active_api_key_by_hash(key_hash)
        if not api_key:
            return False, "Invalid API key"
        if isinstance(api_key.scopes, list):
            scopes = api_key.scopes
        else:
            scopes = list(ALL_OPEN_API_SCOPES)
        if "*" not in scopes and "chat" not in scopes:
            return False, "Insufficient API key scope"
        await self.db.touch_api_key(api_key.key_id)
        return True, None
    async def _send_chat_ws_error(self, message: str, code: str) -> None:
        await websocket.send_json(
            {
                "type": "error",
                "code": code,
                "data": message,
            }
        )
    async def _update_session_config_route(
        self,
        *,
        username: str,
        session_id: str,
        config_id: str | None,
    ) -> str | None:
        if not config_id:
            return None
        umo = f"webchat:FriendMessage:webchat!{username}!{session_id}"
        try:
            if config_id == "default":
                await self.core_lifecycle.umop_config_router.delete_route(umo)
            else:
                await self.core_lifecycle.umop_config_router.update_route(
                    umo, config_id
                )
        except Exception as e:
            logger.error(
                "Failed to update chat config route for %s with %s: %s",
                umo,
                config_id,
                e,
                exc_info=True,
            )
            return f"Failed to update chat config route: {e}"
        return None
    async def _handle_chat_ws_send(self, post_data: dict) -> None:
        effective_username, username_err = self._resolve_open_username(
            post_data.get("username")
        )
        if username_err or not effective_username:
            await self._send_chat_ws_error(
                username_err or "Invalid username", "BAD_USER"
            )
            return
        message = post_data.get("message")
        if message is None:
            await self._send_chat_ws_error("Missing key: message", "INVALID_MESSAGE")
            return
        raw_session_id = post_data.get("session_id", post_data.get("conversation_id"))
        session_id = str(raw_session_id).strip() if raw_session_id is not None else ""
        if not session_id:
            session_id = str(uuid4())
        ensure_session_err = await self._ensure_chat_session(
            effective_username,
            session_id,
        )
        if ensure_session_err:
            await self._send_chat_ws_error(ensure_session_err, "SESSION_ERROR")
            return
        config_id, resolve_err = self._resolve_chat_config_id(post_data)
        if resolve_err:
            await self._send_chat_ws_error(resolve_err, "CONFIG_ERROR")
            return
        config_err = await self._update_session_config_route(
            username=effective_username,
            session_id=session_id,
            config_id=config_id,
        )
        if config_err:
            await self._send_chat_ws_error(config_err, "CONFIG_ERROR")
            return
        message_parts = await self.chat_route._build_user_message_parts(message)
        if not webchat_message_parts_have_content(message_parts):
            await self._send_chat_ws_error(
                "Message content is empty (reply only is not allowed)",
                "INVALID_MESSAGE",
            )
            return
        message_id = str(post_data.get("message_id") or uuid4())
        selected_provider = post_data.get("selected_provider")
        selected_model = post_data.get("selected_model")
        enable_streaming = post_data.get("enable_streaming", True)
        back_queue = webchat_queue_mgr.get_or_create_back_queue(message_id, session_id)
        try:
            chat_queue = webchat_queue_mgr.get_or_create_queue(session_id)
            await chat_queue.put(
                (
                    effective_username,
                    session_id,
                    {
                        "message": message_parts,
                        "selected_provider": selected_provider,
                        "selected_model": selected_model,
                        "enable_streaming": enable_streaming,
                        "message_id": message_id,
                    },
                )
            )
            message_parts_for_storage = strip_message_parts_path_fields(message_parts)
            await self.chat_route.platform_history_mgr.insert(
                platform_id="webchat",
                user_id=session_id,
                content={"type": "user", "message": message_parts_for_storage},
                sender_id=effective_username,
                sender_name=effective_username,
            )
            await websocket.send_json(
                {
                    "type": "session_id",
                    "data": None,
                    "session_id": session_id,
                    "message_id": message_id,
                }
            )
            accumulated_parts = []
            accumulated_text = ""
            accumulated_reasoning = ""
            tool_calls = {}
            agent_stats = {}
            refs = {}
            while True:
                try:
                    result = await asyncio.wait_for(back_queue.get(), timeout=1)
                except asyncio.TimeoutError:
                    continue
                if not result:
                    continue
                if "message_id" in result and result["message_id"] != message_id:
                    logger.warning("openapi ws stream message_id mismatch")
                    continue
                result_text = result.get("data", "")
                msg_type = result.get("type")
                streaming = result.get("streaming", False)
                chain_type = result.get("chain_type")
                if chain_type == "agent_stats":
                    try:
                        stats_info = {
                            "type": "agent_stats",
                            "data": json.loads(result_text),
                        }
                        await websocket.send_json(stats_info)
                        agent_stats = stats_info["data"]
                    except Exception:
                        pass
                    continue
                await websocket.send_json(result)
                if msg_type == "plain":
                    if chain_type == "tool_call":
                        tool_call = json.loads(result_text)
                        tool_calls[tool_call.get("id")] = tool_call
                        if accumulated_text:
                            accumulated_parts.append(
                                {"type": "plain", "text": accumulated_text}
                            )
                            accumulated_text = ""
                    elif chain_type == "tool_call_result":
                        tcr = json.loads(result_text)
                        tc_id = tcr.get("id")
                        if tc_id in tool_calls:
                            tool_calls[tc_id]["result"] = tcr.get("result")
                            tool_calls[tc_id]["finished_ts"] = tcr.get("ts")
                            accumulated_parts.append(
                                {"type": "tool_call", "tool_calls": [tool_calls[tc_id]]}
                            )
                            tool_calls.pop(tc_id, None)
                    elif chain_type == "reasoning":
                        accumulated_reasoning += result_text
                    elif streaming:
                        accumulated_text += result_text
                    else:
                        accumulated_text = result_text
                elif msg_type == "image":
                    filename = str(result_text).replace("[IMAGE]", "")
                    part = await self.chat_route._create_attachment_from_file(
                        filename, "image"
                    )
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "record":
                    filename = str(result_text).replace("[RECORD]", "")
                    part = await self.chat_route._create_attachment_from_file(
                        filename, "record"
                    )
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "file":
                    filename = str(result_text).replace("[FILE]", "")
                    part = await self.chat_route._create_attachment_from_file(
                        filename, "file"
                    )
                    if part:
                        accumulated_parts.append(part)
                elif msg_type == "video":
                    filename = str(result_text).replace("[VIDEO]", "")
                    part = await self.chat_route._create_attachment_from_file(
                        filename, "video"
                    )
                    if part:
                        accumulated_parts.append(part)
                if msg_type == "end":
                    break
                if (streaming and msg_type == "complete") or not streaming:
                    if chain_type in ("tool_call", "tool_call_result"):
                        continue
                    try:
                        refs = self.chat_route._extract_web_search_refs(
                            accumulated_text,
                            accumulated_parts,
                        )
                    except Exception as e:
                        logger.exception(
                            f"Open API WS failed to extract web search refs: {e}",
                            exc_info=True,
                        )
                    saved_record = await self.chat_route._save_bot_message(
                        session_id,
                        accumulated_text,
                        accumulated_parts,
                        accumulated_reasoning,
                        agent_stats,
                        refs,
                    )
                    if saved_record:
                        await websocket.send_json(
                            {
                                "type": "message_saved",
                                "data": {
                                    "id": saved_record.id,
                                    "created_at": saved_record.created_at.astimezone().isoformat(),
                                },
                                "session_id": session_id,
                            }
                        )
                    accumulated_parts = []
                    accumulated_text = ""
                    accumulated_reasoning = ""
                    agent_stats = {}
                    refs = {}
        except Exception as e:
            logger.exception(f"Open API WS chat failed: {e}", exc_info=True)
            await self._send_chat_ws_error(
                f"Failed to process message: {e}", "PROCESSING_ERROR"
            )
        finally:
            webchat_queue_mgr.remove_back_queue(message_id)
    async def chat_ws(self) -> None:
        authed, auth_err = await self._authenticate_chat_ws_api_key()
        if not authed:
            await self._send_chat_ws_error(auth_err or "Unauthorized", "UNAUTHORIZED")
            await websocket.close(1008, auth_err or "Unauthorized")
            return
        try:
            while True:
                message = await websocket.receive_json()
                if not isinstance(message, dict):
                    await self._send_chat_ws_error(
                        "message must be an object",
                        "INVALID_MESSAGE",
                    )
                    continue
                msg_type = message.get("t", "send")
                if msg_type == "ping":
                    await websocket.send_json({"type": "pong"})
                    continue
                if msg_type != "send":
                    await self._send_chat_ws_error(
                        f"Unsupported message type: {msg_type}",
                        "INVALID_MESSAGE",
                    )
                    continue
                await self._handle_chat_ws_send(message)
        except Exception as e:
            logger.debug("Open API WS connection closed: %s", e)
    async def upload_file(self):
        return await self.chat_route.post_file()
@@ -254,83 +604,12 @@ class OpenApiRoute(Route):
    async def _build_message_chain_from_payload(
        self,
        message_payload: str | list,
-    ) -> MessageChain:
+    ):
-        if isinstance(message_payload, str):
+        return await build_message_chain_from_payload(
-            text = message_payload.strip()
+            message_payload,
-            if not text:
+            get_attachment_by_id=self.db.get_attachment_by_id,
-                raise ValueError("Message is empty")
+            strict=True,
-            return MessageChain(chain=[Plain(text=text)])
+        )
        if not isinstance(message_payload, list):
            raise ValueError("message must be a string or list")
        components = []
        has_content = False
        for part in message_payload:
            if not isinstance(part, dict):
                raise ValueError("message part must be an object")
            part_type = str(part.get("type", "")).strip()
            if part_type == "plain":
                text = str(part.get("text", ""))
                if text:
                    has_content = True
                    components.append(Plain(text=text))
                continue
            if part_type == "reply":
                message_id = part.get("message_id")
                if message_id is None:
                    raise ValueError("reply part missing message_id")
                components.append(
                    Reply(
                        id=str(message_id),
                        message_str=str(part.get("selected_text", "")),
                        chain=[],
                    )
                )
                continue
            if part_type not in {"image", "record", "file", "video"}:
                raise ValueError(f"unsupported message part type: {part_type}")
            has_content = True
            file_path: Path | None = None
            resolved_type = part_type
            filename = str(part.get("filename", "")).strip()
            attachment_id = part.get("attachment_id")
            if attachment_id:
                attachment = await self.db.get_attachment_by_id(str(attachment_id))
                if not attachment:
                    raise ValueError(f"attachment not found: {attachment_id}")
                file_path = Path(attachment.path)
                resolved_type = attachment.type
                if not filename:
                    filename = file_path.name
            else:
                raise ValueError(f"{part_type} part missing attachment_id")
            if not file_path.exists():
                raise ValueError(f"file not found: {file_path!s}")
            file_path_str = str(file_path.resolve())
            if resolved_type == "image":
                components.append(Image.fromFileSystem(file_path_str))
            elif resolved_type == "record":
                components.append(Record.fromFileSystem(file_path_str))
            elif resolved_type == "video":
                components.append(Video.fromFileSystem(file_path_str))
            else:
                components.append(
                    File(name=filename or file_path.name, file=file_path_str)
                )
        if not components or not has_content:
            raise ValueError("Message content is empty (reply only is not allowed)")
        return MessageChain(chain=components)
    async def send_message(self):
        post_data = await request.json or {}
@@ -204,6 +204,10 @@ class AstrBotDashboard:
    @staticmethod
    def _extract_raw_api_key() -> str | None:
        if key := request.args.get("api_key"):
            return key.strip()
        if key := request.args.get("key"):
            return key.strip()
        if key := request.headers.get("X-API-Key"):
            return key.strip()
        auth_header = request.headers.get("Authorization", "").strip()
@@ -217,6 +221,7 @@ class AstrBotDashboard:
    def _get_required_open_api_scope(path: str) -> str | None:
        scope_map = {
            "/api/v1/chat": "chat",
            "/api/v1/chat/ws": "chat",
            "/api/v1/chat/sessions": "chat",
            "/api/v1/configs": "config",
            "/api/v1/file": "file",
@@ -10,6 +10,7 @@
                    :selectedSessions="selectedSessions"
                    :currSessionId="currSessionId"
                    :selectedProjectId="selectedProjectId"
                    :transportMode="transportMode"
                    :isDark="isDark"
                    :chatboxMode="chatboxMode"
                    :isMobile="isMobile"
@@ -26,6 +27,7 @@
                    @createProject="showCreateProjectDialog"
                    @editProject="showEditProjectDialog"
                    @deleteProject="handleDeleteProject"
                    @updateTransportMode="setTransportMode"
                />
                <!-- 右侧聊天内容区域 -->
@@ -301,11 +303,14 @@ const {
    isStreaming,
    isConvRunning,
    enableStreaming,
    transportMode,
    currentSessionProject,
    getSessionMessages: getSessionMsg,
    sendMessage: sendMsg,
    stopMessage: stopMsg,
-    toggleStreaming
+    toggleStreaming,
    setTransportMode,
    cleanupTransport
 } = useMessages(currSessionId, getMediaFile, updateSessionTitle, getSessions);
 // 组件引用
@@ -695,6 +700,7 @@ onMounted(() => {
 onBeforeUnmount(() => {
    window.removeEventListener('resize', checkMobile);
    cleanupMediaCache();
    cleanupTransport();
 });
 </script>
@@ -117,6 +117,27 @@
                    <v-list-item-title>{{ isDark ? tm('modes.lightMode') : tm('modes.darkMode') }}</v-list-item-title>
                </v-list-item>
                <!-- 通信传输模式 -->
                <v-list-item class="styled-menu-item">
                    <template v-slot:prepend>
                        <v-icon>mdi-lan-connect</v-icon>
                    </template>
                    <v-list-item-title>{{ tm('transport.title') }}</v-list-item-title>
                    <template v-slot:append>
                        <v-select
                            :model-value="transportMode"
                            :items="transportOptions"
                            item-title="label"
                            item-value="value"
                            density="compact"
                            variant="underlined"
                            hide-details
                            class="transport-mode-select"
                            @update:model-value="handleTransportModeChange"
                        />
                    </template>
                </v-list-item>
                <!-- 全屏/退出全屏 -->
                <v-list-item class="styled-menu-item" @click="$emit('toggleFullscreen')">
                    <template v-slot:prepend>
@@ -156,6 +177,7 @@ interface Props {
    selectedSessions: string[];
    currSessionId: string;
    selectedProjectId?: string | null;
    transportMode: 'sse' | 'websocket';
    isDark: boolean;
    chatboxMode: boolean;
    isMobile: boolean;
@@ -179,6 +201,7 @@ const emit = defineEmits<{
    createProject: [];
    editProject: [project: Project];
    deleteProject: [projectId: string];
    updateTransportMode: [mode: 'sse' | 'websocket'];
 }>();
 const { t } = useI18n();
@@ -188,6 +211,10 @@ const confirmDialog = useConfirmDialog();
 const sidebarCollapsed = ref(true);
 const showProviderConfigDialog = ref(false);
 const transportOptions = [
    { label: tm('transport.sse'), value: 'sse' as const },
    { label: tm('transport.websocket'), value: 'websocket' as const }
 ];
 // 从 localStorage 读取侧边栏折叠状态
 const savedCollapsedState = localStorage.getItem('sidebarCollapsed');
@@ -209,6 +236,12 @@ async function handleDeleteConversation(session: Session) {
        emit('deleteConversation', session.session_id);
    }
 }
 function handleTransportModeChange(mode: string | null) {
    if (mode === 'sse' || mode === 'websocket') {
        emit('updateTransportMode', mode);
    }
 }
 </script>
 <style scoped>
@@ -361,4 +394,8 @@ async function handleDeleteConversation(session: Session) {
    display: flex;
    justify-content: center;
 }
 .transport-mode-select {
    min-width: 120px;
 }
 </style>
@@ -81,9 +81,16 @@
    "disabled": "Streaming disabled",
    "on": "Stream",
    "off": "Normal"
-  },  "config": {
+  },
  "transport": {
    "title": "Transport Mode",
    "sse": "SSE",
    "websocket": "WebSocket"
  },
  "config": {
    "title": "Config"
-  },  "reasoning": {
+  },
  "reasoning": {
    "thinking": "Thinking Process"
  },
  "reply": {
@@ -82,6 +82,11 @@
    "on": "流式",
    "off": "普通"
  },
  "transport": {
    "title": "通信传输模式",
    "sse": "SSE",
    "websocket": "WebSocket"
  },
  "config": {
    "title": "配置文件"
  },
@@ -43,6 +43,7 @@ export default defineConfig({
      '/api': {
        target: 'http://127.0.0.1:6185/',
        changeOrigin: true,
        ws: true
      }
    }
  }
@@ -149,6 +149,20 @@ class MockHooks(BaseAgentRunHooks):
        self.agent_done_called = True
 class MockEvent:
    def __init__(self, umo: str, sender_id: str):
        self.unified_msg_origin = umo
        self._sender_id = sender_id
    def get_sender_id(self):
        return self._sender_id
 class MockAgentContext:
    def __init__(self, event):
        self.event = event
@pytest.fixture
 def mock_provider():
    return MockProvider()
@@ -451,6 +465,76 @@ async def test_stop_signal_returns_aborted_and_persists_partial_message(
    assert runner.run_context.messages[-1].role == "assistant"
@pytest.mark.asyncio
 async def test_tool_result_injects_follow_up_notice(
    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
 ):
    mock_event = MockEvent("test:FriendMessage:follow_up", "u1")
    run_context = ContextWrapper(context=MockAgentContext(mock_event))
    await runner.reset(
        provider=mock_provider,
        request=provider_request,
        run_context=run_context,
        tool_executor=mock_tool_executor,
        agent_hooks=mock_hooks,
        streaming=False,
    )
    ticket1 = runner.follow_up(
        message_text="follow up 1",
    )
    ticket2 = runner.follow_up(
        message_text="follow up 2",
    )
    assert ticket1 is not None
    assert ticket2 is not None
    async for _ in runner.step():
        pass
    assert provider_request.tool_calls_result is not None
    assert isinstance(provider_request.tool_calls_result, list)
    assert provider_request.tool_calls_result
    tool_result = str(
        provider_request.tool_calls_result[0].tool_calls_result[0].content
    )
    assert "SYSTEM NOTICE" in tool_result
    assert "1. follow up 1" in tool_result
    assert "2. follow up 2" in tool_result
    assert ticket1.resolved.is_set() is True
    assert ticket2.resolved.is_set() is True
    assert ticket1.consumed is True
    assert ticket2.consumed is True
@pytest.mark.asyncio
 async def test_follow_up_ticket_not_consumed_when_no_next_tool_call(
    runner, mock_provider, provider_request, mock_tool_executor, mock_hooks
 ):
    mock_provider.should_call_tools = False
    mock_event = MockEvent("test:FriendMessage:follow_up_no_tool", "u1")
    run_context = ContextWrapper(context=MockAgentContext(mock_event))
    await runner.reset(
        provider=mock_provider,
        request=provider_request,
        run_context=run_context,
        tool_executor=mock_tool_executor,
        agent_hooks=mock_hooks,
        streaming=False,
    )
    ticket = runner.follow_up(message_text="follow up without tool")
    assert ticket is not None
    async for _ in runner.step():
        pass
    assert ticket.resolved.is_set() is True
    assert ticket.consumed is False
 if __name__ == "__main__":
    # 运行测试
    pytest.main([__file__, "-v"])
Author	SHA1	Message	Date
Soulter	a0656483b0	chore: update readme	2026-02-27 22:47:10 +08:00
Soulter	f6ac6b9007	docs: update readme - Updated links in Japanese, Russian, and Traditional Chinese README files to include a new Simplified Chinese README. - Enhanced the description and features of AstrBot across all language versions. - Improved formatting of supported messaging platforms and model services in Japanese, Russian, and Traditional Chinese README files. - Added a new README file in Simplified Chinese with comprehensive details about AstrBot, including features, deployment methods, and community contributions.	2026-02-27 22:40:38 +08:00
LIghtJUNction	b8c73430fb	Revert "可选后端，实现前后端分离" (#5536 )	2026-02-27 22:02:37 +08:00
LIghtJUNction	3141ed52bd	Merge branch 'feat/optional-backend' into master	2026-02-27 21:53:56 +08:00
Soulter	63ff234f10	feat: implement websockets transport mode selection for chat (#5410 ) * feat: implement websockets transport mode selection for chat - Added transport mode selection (SSE/WebSocket) in the chat component. - Updated conversation sidebar to include transport mode options. - Integrated transport mode handling in message sending logic. - Refactored message sending functions to support both SSE and WebSocket. - Enhanced WebSocket connection management and message handling. - Updated localization files for transport mode labels. - Configured Vite to support WebSocket proxying. * feat(webchat): refactor message parsing logic and integrate new parsing function * feat(chat): add websocket API key extraction and scope validation	2026-02-27 14:02:10 +08:00
Soulter	5219ba5c4e	feat: implement follow-up message handling in ToolLoopAgentRunner (#5484 ) * feat: implement follow-up message handling in ToolLoopAgentRunner * fix: correct import path for follow-up module in InternalAgentSubStage	2026-02-26 21:38:47 +08:00
LIghtJUNction	48c2d98dde	删除 bun.lock，让行数看起来没那么夸张	2026-02-09 00:22:46 +08:00
LIghtJUNction	af09b5cb16	Update astrbot/dashboard/server.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-02-09 00:21:37 +08:00
LIghtJUNction	31f46045d7	修正/修正一个错误	2026-02-07 20:17:44 +08:00
LIghtJUNction	d6455d774b	修正/一个导入问题	2026-02-07 20:02:44 +08:00
LIghtJUNction	3e928b9659	修正/CI工作流反馈的一些问题	2026-02-07 19:54:54 +08:00
LIghtJUNction	df1299b192	移除自定义的一个协议	2026-02-06 12:38:55 +08:00
LIghtJUNction	15ee17724d	Merge branch 'feat/optional-backend' of https://github.com/AstrBotDevs/AstrBot into feat/optional-backend	2026-02-06 12:37:58 +08:00
LIghtJUNction	437c186a66	类型标注	2026-02-06 12:37:41 +08:00
LIghtJUNction	3610a42ebf	Merge branch 'master' into feat/optional-backend	2026-02-06 04:22:49 +08:00
LIghtJUNction	bf1bde79ec	Update astrbot/core/utils/io.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-02-06 04:22:03 +08:00
LIghtJUNction	f309638192	Update astrbot/dashboard/server.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-02-06 04:21:40 +08:00
LIghtJUNction	6439e4e152	Update astrbot/cli/commands/cmd_run.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-02-06 04:21:02 +08:00
LIghtJUNction	4b1395b2c9	Update astrbot/dashboard/routes/route.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>	2026-02-06 04:19:41 +08:00
LIghtJUNction	1859206007	feat: 支持前后端分离部署与动态后端地址配置后端: - 支持通过 DASHBOARD_ENABLE 环境变量分离 WebUI 服务 - 修复 CORS 跨域预检请求(OPTIONS) 鉴权问题 - 优化 IPv6 地址过滤逻辑 - CLI 新增 --backend-only 模式支持前端: - 新增 API 地址动态配置与预设管理功能 (登录页/设置页) - 修复 WebSocket/SSE 连接地址适配非同源环境 - 修复 TypeScript 配置报错 - 完善新增功能的国际化支持	2026-02-06 04:06:52 +08:00
LIghtJUNction	3b93429353	新增cors配置项	2026-02-06 04:01:30 +08:00
LIghtJUNction	d68ccfcc96	1.前端的后端配置页面新增新增按钮，允许新增后端，自由切换后端。2.一些必要的改进，比如astrbot init初始化时候询问是否下载前端，可选择不下载，使用--backend-only选项时候，不再提示要下载前端	2026-02-06 03:47:53 +08:00
LIghtJUNction	68b8a1a01c	将enable变量含义释为：是否启用集成前端，如果为False,保留后端能力，而不是后端也关闭了	2026-02-06 03:13:46 +08:00
LIghtJUNction	75ee46715a	支持ipv6并完善astrbot run子命令 * 默认host修改为::，同时新增两个环境变量DASHBOARD_HOST，DASHBOARD_ENABLE，和DASHBOARD_PORT对齐 * feat: systemd support (#4880) * fix: pyright lint (#4874) * feat: 将 MessageSession 的 platform_id 改为 init=False，实例化时无需传入 Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * refactor: 将 isinstance 检查改为元组、将默认模型值设为空字符串、将类型注解改为 Any 并导入 * refactor: 为 _serialize_job 增加返回类型注解 dict * fix: 使用 cast 获取百度 AIP 的 msg 并对 psutil_addr 引入 type: ignore Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * refactor: 引入 _AddrWithPort 协议并替换 conn.laddr 的 cast Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * fix: 在构建 AstrBotMessage 时对 ctx.channel 可能为 None 进行兜底处理 Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> --------- Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * fix: TypeError when MCP schema type is a list (#4867) * Fix TypeError when MCP schema type is a list Fixes crash in Gemini native tools with VRChat MCP. * Refactor: avoid modifying schema in place per feedback * Fix formatting and cleanup comments * docs: update watashiwakoseinodesukara Removed duplicate text and added a new image. * 修复/跨平台一致性 * 琐事/类型标注和一些简单错误修正 * 修复/检查端口时候包含ipv6 * 修复/enable变量的赋值逻辑 --------- Co-authored-by: Dt8333 <25431943+Dt8333@users.noreply.github.com> Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> Co-authored-by: boushi1111 <95118141+boushi1111@users.noreply.github.com> Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>	2026-02-06 02:46:16 +08:00
LIghtJUNction	a8cad50f27	新功能/可选的分离前后端	2026-02-06 02:38:58 +08:00