fix: complete requirements.txt

Release: v4.0.0-beta.1

.github/ISSUE_TEMPLATE/PLUGIN_PUBLISH.yml

@@ -1,40 +1,56 @@
-name: '🥳 发布插件'
-title: "[Plugin] 插件名"
+name: 🥳 发布插件
 description: 提交插件到插件市场
-labels: [ "plugin-publish" ]
+title: "[Plugin] 插件名"
+labels: ["plugin-publish"]
+assignees: []
 body:
   - type: markdown
     attributes:
       value: |
-        欢迎发布插件到插件市场！请确保您的插件经过**完整的**测试。
-  
-  - type: textarea
-    attributes:
-      label: 插件仓库
-      description: 插件的 GitHub 仓库链接
-      placeholder: >
-        如 https://github.com/Soulter/astrbot-github-cards
-
-  - type: textarea
-    attributes:
-      label: 描述
-      value: |
-        插件名: 
-        插件作者: 
-        插件简介: 
-        支持的消息平台:(必填，如 QQ、微信、飞书)
-        标签:(可选)
-        社交链接:(可选, 将会在插件市场作者名称上作为可点击的链接)
-      description: 必填。请以列表的字段按顺序将插件名、插件作者、插件简介放在这里。如果您不知道支持哪些消息平台，请填写测试过的消息平台。
-
-  - type: checkboxes
-    attributes:
-      label: Code of Conduct
-      options:
-        - label: >
-            我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
-          required: true
+        欢迎发布插件到插件市场！
 
   - type: markdown
     attributes:
-      value: "❤️"
+      value: |
+        ## 插件基本信息
+
+        请将插件信息填写到下方的 JSON 代码块中。其中 `tags`（插件标签）和 `social_link`（社交链接）选填。
+
+        不熟悉 JSON ？现在可以从 [这里](https://plugins.astrbot.app/#/submit) 获取你的 JSON 啦！获取到了记得复制粘贴过来哦！
+
+  - type: textarea
+    id: plugin-info
+    attributes:
+      label: 插件信息
+      description: 请在下方代码块中填写您的插件信息，确保反引号包裹了JSON
+      value: |
+        ```json
+        {
+          "name": "插件名",
+          "desc": "插件介绍",
+          "author": "作者名",
+          "repo": "插件仓库链接",
+          "tags": [],
+          "social_link": ""
+        }
+        ```
+    validations:
+      required: true
+
+  - type: markdown
+    attributes:
+      value: |
+        ## 检查
+
+  - type: checkboxes
+    id: checks
+    attributes:
+      label: 插件检查清单
+      description: 请确认以下所有项目
+      options:
+        - label: 我的插件经过完整的测试
+          required: true
+        - label: 我的插件不包含恶意代码
+          required: true
+        - label: 我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
+          required: true

.github/copilot-instructions.md

@@ -0,0 +1,63 @@
+# AstrBot Development Instructions
+
+AstrBot is a multi-platform LLM chatbot and development framework written in Python with a Vue.js dashboard. It supports multiple messaging platforms (QQ, Telegram, Discord, etc.) and various LLM providers (OpenAI, Anthropic, Google Gemini, etc.).
+
+Always reference these instructions first and fallback to search or bash commands only when you encounter unexpected information that does not match the info here.
+
+## Working Effectively
+
+### Bootstrap and Install Dependencies
+- **Python 3.10+ required** - Check `.python-version` file
+- Install UV package manager: `pip install uv`
+- Install project dependencies: `uv sync` -- takes 6-7 minutes. NEVER CANCEL. Set timeout to 10+ minutes.
+- Create required directories: `mkdir -p data/plugins data/config data/temp`
+
+### Running the Application
+- Run main application: `uv run main.py` -- starts in ~3 seconds
+- Application creates WebUI on http://localhost:6185 (default credentials: `astrbot`/`astrbot`)
+- Application loads plugins automatically from `packages/` and `data/plugins/` directories
+
+### Dashboard Build (Vue.js/Node.js)
+- **Prerequisites**: Node.js 20+ and npm 10+ required
+- Navigate to dashboard: `cd dashboard`
+- Install dashboard dependencies: `npm install` -- takes 2-3 minutes. NEVER CANCEL. Set timeout to 5+ minutes.
+- Build dashboard: `npm run build` -- takes 25-30 seconds. NEVER CANCEL.
+- Dashboard creates optimized production build in `dashboard/dist/`
+
+### Testing
+- Do not generate test files for now.
+
+### Code Quality and Linting
+- Install ruff linter: `uv add --dev ruff`
+- Check code style: `uv run ruff check .` -- takes <1 second
+- Check formatting: `uv run ruff format --check .` -- takes <1 second
+- Fix formatting: `uv run ruff format .`
+- **ALWAYS** run `uv run ruff check .` and `uv run ruff format .` before committing changes
+
+### Plugin Development
+- Plugins load from `packages/` (built-in) and `data/plugins/` (user-installed)
+- Plugin system supports function tools and message handlers
+- Key plugins: python_interpreter, web_searcher, astrbot, reminder, session_controller
+
+### Common Issues and Workarounds
+- **Dashboard download fails**: Known issue with "division by zero" error - application still works
+- **Import errors in tests**: Ensure `uv run` is used to run tests in proper environment
+=- **Build timeouts**: Always set appropriate timeouts (10+ minutes for uv sync, 5+ minutes for npm install)
+
+## CI/CD Integration
+- GitHub Actions workflows in `.github/workflows/`
+- Docker builds supported via `Dockerfile`
+- Pre-commit hooks enforce ruff formatting and linting
+
+## Docker Support
+- Primary deployment method: `docker run soulter/astrbot:latest`
+- Compose file available: `compose.yml`
+- Exposes ports: 6185 (WebUI), 6195 (WeChat), 6199 (QQ), etc.
+- Volume mount required: `./data:/AstrBot/data`
+
+## Multi-language Support
+- Documentation in Chinese (README.md), English (README_en.md), Japanese (README_ja.md)
+- UI supports internationalization
+- Default language is Chinese
+
+Remember: This is a production chatbot framework with real users. Always test thoroughly and ensure changes don't break existing functionality.

.github/dependabot.yml

@@ -0,0 +1,13 @@
+# Keep GitHub Actions up to date with GitHub's Dependabot...
+# https://docs.github.com/en/code-security/dependabot/working-with-dependabot/keeping-your-actions-up-to-date-with-dependabot
+# https://docs.github.com/en/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file#package-ecosystem
+version: 2
+updates:
+  - package-ecosystem: github-actions
+    directory: /
+    groups:
+      github-actions:
+        patterns:
+          - "*"  # Group all Actions updates into a single larger pull request
+    schedule:
+      interval: weekly

.github/workflows/auto_release.yml

@@ -13,7 +13,7 @@ jobs:
       contents: write
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Dashboard Build
         run: |
@@ -70,10 +70,10 @@ jobs:
     needs: build-and-publish-to-github-release
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: '3.10'
 

.github/workflows/codeql.yml

@@ -56,7 +56,7 @@ jobs:
         # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@v5
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL

.github/workflows/coverage_test.yml

@@ -1,6 +1,6 @@
 name: Run tests and upload coverage
 
-on: 
+on:
   push:
     branches:
       - master
@@ -8,6 +8,7 @@ on:
       - 'README.md'
       - 'changelogs/**'
       - 'dashboard/**'
+  pull_request:
   workflow_dispatch:
 
 jobs:
@@ -16,30 +17,29 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
       
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -r requirements.txt
-          pip install pytest pytest-cov pytest-asyncio
+          pip install pytest pytest-asyncio pytest-cov
+          pip install --editable .
 
       - name: Run tests
         run: |
-          mkdir data
-          mkdir data/plugins
-          mkdir data/config
-          mkdir data/temp
+          mkdir -p data/plugins
+          mkdir -p data/config
+          mkdir -p data/temp
           export TESTING=true
           export ZHIPU_API_KEY=${{ secrets.OPENAI_API_KEY }}
-          PYTHONPATH=./ pytest --cov=. tests/ -v -o log_cli=true -o log_level=DEBUG
+          pytest --cov=. -v -o log_cli=true -o log_level=DEBUG
 
       - name: Upload results to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
-          token: ${{ secrets.CODECOV_TOKEN }}
+          token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/dashboard_ci.yml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: npm install, build
         run: |
@@ -25,6 +25,8 @@ jobs:
           echo "COMMIT_SHA=$(git rev-parse HEAD)" >> $GITHUB_ENV
           mkdir -p dashboard/dist/assets
           echo $COMMIT_SHA > dashboard/dist/assets/version
+          cd dashboard
+          zip -r dist.zip dist
 
       - name: Archive production artifacts
         uses: actions/upload-artifact@v4
@@ -33,3 +35,13 @@ jobs:
           path: |
             dashboard/dist
             !dist/**/*.md
+
+      - name: Create GitHub Release
+        uses: ncipollo/release-action@v1
+        with:
+          tag: release-${{ github.sha }}
+          owner: AstrBotDevs
+          repo: astrbot-release-harbour
+          body: "Automated release from commit ${{ github.sha }}"
+          token: ${{ secrets.ASTRBOT_HARBOUR_TOKEN }}
+          artifacts: "dashboard/dist.zip"

.github/workflows/docker-image.yml

@@ -12,7 +12,7 @@ jobs:
 
     steps:
       - name: Pull The Codes
-        uses: actions/checkout@v3
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0  # Must be 0 so we can fetch tags
 

.github/workflows/stale.yml

@@ -18,7 +18,7 @@ jobs:
       pull-requests: write
 
     steps:
-    - uses: actions/stale@v5
+    - uses: actions/stale@v9
       with:
         repo-token: ${{ secrets.GITHUB_TOKEN }}
         stale-issue-message: 'Stale issue message'

README.md

@@ -1,4 +1,4 @@
-<p align="center">
+<img width="430" height="31" alt="image" src="https://github.com/user-attachments/assets/474c822c-fab7-41be-8c23-6dae252823ed" /><p align="center">
  
 ![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 
@@ -16,7 +16,7 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 <a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="QQ_community" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
 <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>
 [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg?style=for-the-badge&color=76bad9)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=3600&style=for-the-badge&color=3b618e)
+![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7日消息量&cacheSeconds=3600&style=for-the-badge&color=3b618e)
 ![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600)
 
 <a href="https://github.com/Soulter/AstrBot/blob/master/README_en.md">English</a> ｜
@@ -25,59 +25,52 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 <a href="https://github.com/Soulter/AstrBot/issues">问题提交</a>
 </div>
 
-AstrBot 是一个松耦合、异步、支持多消息平台部署、具有易用的插件系统和完善的大语言模型（LLM）接入功能的聊天机器人及开发框架。
-
-
-<!-- [![codecov](https://img.shields.io/codecov/c/github/soulter/astrbot?style=for-the-badge)](https://codecov.io/gh/Soulter/AstrBot)
- -->
-
-> [!WARNING]
-> 
-> 请务必修改默认密码以及保证 AstrBot 版本 >= 3.5.13。
-
-## ✨ 近期更新
-
-<details><summary>1. AstrBot 现已自带知识库能力</summary>
-
- 📚 详见[文档](https://astrbot.app/use/knowledge-base.html)
-
- ![image](https://github.com/user-attachments/assets/28b639b0-bb5c-4958-8e94-92ae8cfd1ab4)
-
-</details>
-
-2. AstrBot 现已支持接入 [MCP](https://modelcontextprotocol.io/) 服务器！
+AstrBot 是一个开源的一站式 Agentic 聊天机器人平台及开发框架。
 
 ## ✨ 主要功能
 
-> [!NOTE]
-> 🪧 我们正基于前沿科研成果，设计并实现适用于角色扮演和情感陪伴的长短期记忆模型及情绪控制模型，旨在提升对话的真实性与情感表达能力。敬请期待 `v3.6.0` 版本！
-
-1. **大语言模型对话**。支持各种大语言模型，包括 OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM 等，支持接入本地部署的大模型，通过 Ollama、LLMTuner。具有多轮对话、人格情境、多模态能力，支持图片理解、语音转文字（Whisper）。
-2. **多消息平台接入**。支持接入 QQ（OneBot、QQ 官方机器人平台）、QQ 频道、微信、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK、VoceChat。支持速率限制、白名单、关键词过滤、百度内容审核。
-3. **Agent**。原生支持部分 Agent 能力，如代码执行器、自然语言待办、网页搜索。对接 [Dify 平台](https://dify.ai/)，便捷接入 Dify 智能助手、知识库和 Dify 工作流。
-4. **插件扩展**。深度优化的插件机制，支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能，极简开发。已支持安装多个插件。
-5. **可视化管理面板**。支持可视化修改配置、插件管理、日志查看等功能，降低配置难度。集成 WebChat，可在面板上与大模型对话。
-6. **高稳定性、高模块化**。基于事件总线和流水线的架构设计，高度模块化，低耦合。
-
-> [!TIP]
-> WebUI 在线体验 Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)
-> 
-> 用户名: `astrbot`, 密码: `astrbot`。
+1. **大模型对话**。支持接入多种大模型服务。支持多模态、工具调用、MCP、原生知识库、人设等功能。
+2. **多消息平台支持**。支持接入 QQ、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK 等平台。支持速率限制、白名单、百度内容审核。
+3. **Agent**。完善适配的 Agentic 能力。支持多轮工具调用、内置沙盒代码执行器、网页搜索等功能。
+4. **插件扩展**。深度优化的插件机制，支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能，社区插件生态丰富。
+5. **WebUI**。可视化配置和管理机器人，功能齐全。
 
 ## ✨ 使用方式
 
 #### 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) 。
 
+#### 宝塔面板部署
+
+AstrBot 与宝塔面板合作，已上架至宝塔面板。
+
+请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
+
+#### 1Panel 部署
+
+AstrBot 已由 1Panel 官方上架至 1Panel 面板。
+
+请参阅官方文档 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html) 。
+
+#### 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)
+
+#### 在 Replit 上部署
+
+社区贡献的部署方式。
+
+[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
+
 #### Windows 一键安装器部署
 
 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) 。
 
-#### 宝塔面板部署
-
-请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
-
 #### CasaOS 部署
 
 社区贡献的部署方式。
@@ -101,27 +94,14 @@ git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
 uv run main.py
 ```
 
-或者，直接通过 uvx 安装 AstrBot：
-
-```bash
-mkdir astrbot && cd astrbot
-uvx astrbot init
-# uvx astrbot run
-```
-
 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
 
-#### Replit 部署
-
-[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
-
 ## ⚡ 消息平台支持情况
 
 | 平台    | 支持性 |
 | -------- | ------- |
 | QQ(官方机器人接口) | ✔    |
 | QQ(OneBot)      | ✔    |
-| 微信个人号    | ✔    |
 | Telegram   | ✔    |
 | 企业微信    | ✔    |
 | 微信客服    | ✔    |
@@ -140,7 +120,7 @@ uvx astrbot init
 
 | 名称    | 支持性 | 类型 | 备注 |
 | -------- | ------- | ------- | ------- |
-| OpenAI API | ✔    | 文本生成 | 也支持 DeepSeek、Google Gemini、GLM、Kimi、xAI 等兼容 OpenAI API 的服务 |
+| OpenAI API | ✔    | 文本生成 | 也支持 DeepSeek、Gemini、Kimi、xAI 等兼容 OpenAI API 的服务 |
 | Claude API | ✔    | 文本生成 |  |
 | Google Gemini API | ✔    | 文本生成 |  |
 | Dify | ✔    | LLMOps |  |
@@ -148,6 +128,8 @@ uvx astrbot init
 | Ollama | ✔    | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
 | LM Studio | ✔    | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
 | LLMTuner | ✔    | 模型加载器 | 本地加载 lora 等微调模型 |
+| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | ✔    | 模型 API 及算力服务平台 |  |
+| [302.AI](https://share.302.ai/rr1M3l) | ✔    | 模型 API 服务平台 |  |
 | 硅基流动 | ✔    | 模型 API 服务平台 |  |
 | PPIO 派欧云 | ✔    | 模型 API 服务平台 |  |
 | OneAPI | ✔    | LLM 分发系统 |  |
@@ -223,7 +205,7 @@ _✨ WebUI ✨_
 
 此外，本项目的诞生离不开以下开源项目：
 
-- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ)
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
 - [wechatpy/wechatpy](https://github.com/wechatpy/wechatpy)
 
 ## ⭐ Star History
@@ -237,11 +219,8 @@ _✨ WebUI ✨_
 
 </div>
 
-## Disclaimer
+![10k-star-banner-credit-by-kevin](https://github.com/user-attachments/assets/c97fc5fb-20b9-4bc8-9998-c20b930ab097)
 
-1. The project is protected under the `AGPL-v3` opensource license.
-2. The deployment of WeChat (personal account) utilizes [Gewechat](https://github.com/Devo919/Gewechat) service. AstrBot only guarantees connectivity with Gewechat and recommends using a WeChat account that is not frequently used. In the event of account risk control, the author of this project shall not bear any responsibility.
-3. Please ensure compliance with local laws and regulations when using this project.
 
 _私は、高性能ですから!_
 

README_ja.md

@@ -1,5 +1,5 @@
 <p align="center">
-    
+
 ![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
 
 </p>
@@ -27,7 +27,7 @@ AstrBot は、疎結合、非同期、複数のメッセージプラットフォ
 ## ✨ 主な機能
 
 1. **大規模言語モデルの対話**。OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM など、さまざまな大規模言語モデルをサポートし、Ollama、LLMTuner を介してローカルにデプロイされた大規模モデルをサポートします。多輪対話、人格シナリオ、多モーダル機能を備え、画像理解、音声からテキストへの変換（Whisper）をサポートします。
-2. **複数のメッセージプラットフォームの接続**。QQ（OneBot）、QQ チャンネル、WeChat（Gewechat）、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
+2. **複数のメッセージプラットフォームの接続**。QQ（OneBot）、QQ チャンネル、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
 3. **エージェント**。一部のエージェント機能をネイティブにサポートし、コードエグゼキューター、自然言語タスク、ウェブ検索などを提供します。[Dify プラットフォーム](https://dify.ai/)と連携し、Dify スマートアシスタント、ナレッジベース、Dify ワークフローを簡単に接続できます。
 4. **プラグインの拡張**。深く最適化されたプラグインメカニズムを備え、[プラグインの開発](https://astrbot.app/dev/plugin.html)をサポートし、機能を拡張できます。複数のプラグインのインストールをサポートします。
 5. **ビジュアル管理パネル**。設定の視覚的な変更、プラグイン管理、ログの表示などをサポートし、設定の難易度を低減します。WebChat を統合し、パネル上で大規模モデルと対話できます。
@@ -35,7 +35,7 @@ AstrBot は、疎結合、非同期、複数のメッセージプラットフォ
 
 > [!TIP]
 > 管理パネルのオンラインデモを体験する: [https://demo.astrbot.app/](https://demo.astrbot.app/)
-> 
+>
 > ユーザー名: `astrbot`, パスワード: `astrbot`。LLM が設定されていないため、チャットページで大規模モデルを使用することはできません。（デモのログインパスワードを変更しないでください 😭）
 
 ## ✨ 使用方法
@@ -136,11 +136,11 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
 
 ## ⭐ Star History
 
-> [!TIP] 
+> [!TIP]
 > このプロジェクトがあなたの生活や仕事に役立った場合、またはこのプロジェクトの将来の発展に関心がある場合は、プロジェクトに Star を付けてください。これはこのオープンソースプロジェクトを維持するためのモチベーションです <3
 
 <div align="center">
-    
+
 [![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
 
 </div>
@@ -152,8 +152,7 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
 ## 免責事項
 
 1. このプロジェクトは `AGPL-v3` オープンソースライセンスの下で保護されています。
-2. WeChat（個人アカウント）のデプロイメントには [Gewechat](https://github.com/Devo919/Gewechat) サービスを利用しています。AstrBot は Gewechat との接続を保証するだけであり、アカウントのリスク管理に関しては、このプロジェクトの著者は一切の責任を負いません。
-3. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
+2. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
 
 <!-- ## ✨ ATRI [ベータテスト]
 
@@ -165,6 +164,4 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
 4. TTS
     -->
 
-
 _私は、高性能ですから!_
-

astrbot/api/__init__.py

@@ -3,5 +3,18 @@ from astrbot import logger
 from astrbot.core import html_renderer
 from astrbot.core import sp
 from astrbot.core.star.register import register_llm_tool as llm_tool
+from astrbot.core.star.register import register_agent as agent
+from astrbot.core.agent.tool import ToolSet, FunctionTool
+from astrbot.core.agent.tool_executor import BaseFunctionToolExecutor
 
-__all__ = ["AstrBotConfig", "logger", "html_renderer", "llm_tool", "sp"]
+__all__ = [
+    "AstrBotConfig",
+    "logger",
+    "html_renderer",
+    "llm_tool",
+    "agent",
+    "sp",
+    "ToolSet",
+    "FunctionTool",
+    "BaseFunctionToolExecutor",
+]

astrbot/cli/__init__.py

@@ -1 +1 @@
-__version__ = "3.5.8"
+__version__ = "3.5.23"

astrbot/cli/utils/plugin.py

@@ -117,6 +117,9 @@ def build_plug_list(plugins_dir: Path) -> list:
             # 从 metadata.yaml 加载元数据
             metadata = load_yaml_metadata(plugin_dir)
 
+            if "desc" not in metadata and "description" in metadata:
+                metadata["desc"] = metadata["description"]
+
             # 如果成功加载元数据，添加到结果列表
             if metadata and all(
                 k in metadata for k in ["name", "desc", "version", "author", "repo"]

astrbot/core/__init__.py

@@ -1,5 +1,4 @@
 import os
-import asyncio
 from .log import LogManager, LogBroker  # noqa
 from astrbot.core.utils.t2i.renderer import HtmlRenderer
 from astrbot.core.utils.shared_preferences import SharedPreferences
@@ -13,7 +12,6 @@ from .utils.astrbot_path import get_astrbot_data_path
 # 初始化数据存储文件夹
 os.makedirs(get_astrbot_data_path(), exist_ok=True)
 
-WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"
 DEMO_MODE = os.getenv("DEMO_MODE", False)
 
 astrbot_config = AstrBotConfig()
@@ -22,13 +20,10 @@ html_renderer = HtmlRenderer(t2i_base_url)
 logger = LogManager.GetLogger(log_name="astrbot")
 db_helper = SQLiteDatabase(DB_PATH)
 # 简单的偏好设置存储, 这里后续应该存储到数据库中, 一些部分可以存储到配置中
-sp = SharedPreferences()
+sp = SharedPreferences(db_helper=db_helper)
 # 文件令牌服务
 file_token_service = FileTokenService()
 pip_installer = PipInstaller(
     astrbot_config.get("pip_install_arg", ""),
     astrbot_config.get("pypi_index_url", None),
 )
-web_chat_queue = asyncio.Queue(maxsize=32)
-web_chat_back_queue = asyncio.Queue(maxsize=32)
-

astrbot/core/agent/agent.py

@@ -0,0 +1,13 @@
+from dataclasses import dataclass
+from .tool import FunctionTool
+from typing import Generic
+from .run_context import TContext
+from .hooks import BaseAgentRunHooks
+
+
+@dataclass
+class Agent(Generic[TContext]):
+    name: str
+    instructions: str | None = None
+    tools: list[str, FunctionTool] | None = None
+    run_hooks: BaseAgentRunHooks[TContext] | None = None

astrbot/core/agent/handoff.py

@@ -0,0 +1,34 @@
+from typing import Generic
+from .tool import FunctionTool
+from .agent import Agent
+from .run_context import TContext
+
+
+class HandoffTool(FunctionTool, Generic[TContext]):
+    """Handoff tool for delegating tasks to another agent."""
+
+    def __init__(
+        self, agent: Agent[TContext], parameters: dict | None = None, **kwargs
+    ):
+        self.agent = agent
+        super().__init__(
+            name=f"transfer_to_{agent.name}",
+            parameters=parameters or self.default_parameters(),
+            description=agent.instructions or self.default_description(agent.name),
+            **kwargs,
+        )
+
+    def default_parameters(self) -> dict:
+        return {
+            "type": "object",
+            "properties": {
+                "input": {
+                    "type": "string",
+                    "description": "The input to be handed off to another agent. This should be a clear and concise request or task.",
+                },
+            },
+        }
+
+    def default_description(self, agent_name: str | None) -> str:
+        agent_name = agent_name or "another"
+        return f"Delegate tasks to {self.name} agent to handle the request."

astrbot/core/agent/hooks.py

@@ -0,0 +1,27 @@
+import mcp
+from dataclasses import dataclass
+from .run_context import ContextWrapper, TContext
+from typing import Generic
+from astrbot.core.provider.entities import LLMResponse
+from astrbot.core.agent.tool import FunctionTool
+
+
+@dataclass
+class BaseAgentRunHooks(Generic[TContext]):
+    async def on_agent_begin(self, run_context: ContextWrapper[TContext]): ...
+    async def on_tool_start(
+        self,
+        run_context: ContextWrapper[TContext],
+        tool: FunctionTool,
+        tool_args: dict | None,
+    ): ...
+    async def on_tool_end(
+        self,
+        run_context: ContextWrapper[TContext],
+        tool: FunctionTool,
+        tool_args: dict | None,
+        tool_result: mcp.types.CallToolResult | None,
+    ): ...
+    async def on_agent_done(
+        self, run_context: ContextWrapper[TContext], llm_response: LLMResponse
+    ): ...

astrbot/core/agent/mcp_client.py

@@ -0,0 +1,208 @@
+import asyncio
+import logging
+from datetime import timedelta
+from typing import Optional
+from contextlib import AsyncExitStack
+from astrbot import logger
+from astrbot.core.utils.log_pipe import LogPipe
+
+try:
+    import mcp
+    from mcp.client.sse import sse_client
+except (ModuleNotFoundError, ImportError):
+    logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
+
+try:
+    from mcp.client.streamable_http import streamablehttp_client
+except (ModuleNotFoundError, ImportError):
+    logger.warning(
+        "警告: 缺少依赖库 'mcp' 或者 mcp 库版本过低，无法使用 Streamable HTTP 连接方式。"
+    )
+
+
+def _prepare_config(config: dict) -> dict:
+    """准备配置，处理嵌套格式"""
+    if "mcpServers" in config and config["mcpServers"]:
+        first_key = next(iter(config["mcpServers"]))
+        config = config["mcpServers"][first_key]
+    config.pop("active", None)
+    return config
+
+
+async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
+    """快速测试 MCP 服务器可达性"""
+    import aiohttp
+
+    cfg = _prepare_config(config.copy())
+
+    url = cfg["url"]
+    headers = cfg.get("headers", {})
+    timeout = cfg.get("timeout", 10)
+
+    try:
+        async with aiohttp.ClientSession() as session:
+            if cfg.get("transport") == "streamable_http":
+                test_payload = {
+                    "jsonrpc": "2.0",
+                    "method": "initialize",
+                    "id": 0,
+                    "params": {
+                        "protocolVersion": "2024-11-05",
+                        "capabilities": {},
+                        "clientInfo": {"name": "test-client", "version": "1.2.3"},
+                    },
+                }
+                async with session.post(
+                    url,
+                    headers={
+                        **headers,
+                        "Content-Type": "application/json",
+                        "Accept": "application/json, text/event-stream",
+                    },
+                    json=test_payload,
+                    timeout=aiohttp.ClientTimeout(total=timeout),
+                ) as response:
+                    if response.status == 200:
+                        return True, ""
+                    else:
+                        return False, f"HTTP {response.status}: {response.reason}"
+            else:
+                async with session.get(
+                    url,
+                    headers={
+                        **headers,
+                        "Accept": "application/json, text/event-stream",
+                    },
+                    timeout=aiohttp.ClientTimeout(total=timeout),
+                ) as response:
+                    if response.status == 200:
+                        return True, ""
+                    else:
+                        return False, f"HTTP {response.status}: {response.reason}"
+
+    except asyncio.TimeoutError:
+        return False, f"连接超时: {timeout}秒"
+    except Exception as e:
+        return False, f"{e!s}"
+
+
+class MCPClient:
+    def __init__(self):
+        # Initialize session and client objects
+        self.session: Optional[mcp.ClientSession] = None
+        self.exit_stack = AsyncExitStack()
+
+        self.name = None
+        self.active: bool = True
+        self.tools: list[mcp.Tool] = []
+        self.server_errlogs: list[str] = []
+        self.running_event = asyncio.Event()
+
+    async def connect_to_server(self, mcp_server_config: dict, name: str):
+        """连接到 MCP 服务器
+
+        如果 `url` 参数存在：
+            1. 当 transport 指定为 `streamable_http` 时，使用 Streamable HTTP 连接方式。
+            1. 当 transport 指定为 `sse` 时，使用 SSE 连接方式。
+            2. 如果没有指定，默认使用 SSE 的方式连接到 MCP 服务。
+
+        Args:
+            mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server
+        """
+        cfg = _prepare_config(mcp_server_config.copy())
+
+        def logging_callback(msg: str):
+            # 处理 MCP 服务的错误日志
+            print(f"MCP Server {name} Error: {msg}")
+            self.server_errlogs.append(msg)
+
+        if "url" in cfg:
+            success, error_msg = await _quick_test_mcp_connection(cfg)
+            if not success:
+                raise Exception(error_msg)
+
+            if cfg.get("transport") != "streamable_http":
+                # SSE transport method
+                self._streams_context = sse_client(
+                    url=cfg["url"],
+                    headers=cfg.get("headers", {}),
+                    timeout=cfg.get("timeout", 5),
+                    sse_read_timeout=cfg.get("sse_read_timeout", 60 * 5),
+                )
+                streams = await self.exit_stack.enter_async_context(
+                    self._streams_context
+                )
+
+                # Create a new client session
+                read_timeout = timedelta(seconds=cfg.get("session_read_timeout", 20))
+                self.session = await self.exit_stack.enter_async_context(
+                    mcp.ClientSession(
+                        *streams,
+                        read_timeout_seconds=read_timeout,
+                        logging_callback=logging_callback,  # type: ignore
+                    )
+                )
+            else:
+                timeout = timedelta(seconds=cfg.get("timeout", 30))
+                sse_read_timeout = timedelta(
+                    seconds=cfg.get("sse_read_timeout", 60 * 5)
+                )
+                self._streams_context = streamablehttp_client(
+                    url=cfg["url"],
+                    headers=cfg.get("headers", {}),
+                    timeout=timeout,
+                    sse_read_timeout=sse_read_timeout,
+                    terminate_on_close=cfg.get("terminate_on_close", True),
+                )
+                read_s, write_s, _ = await self.exit_stack.enter_async_context(
+                    self._streams_context
+                )
+
+                # Create a new client session
+                read_timeout = timedelta(seconds=cfg.get("session_read_timeout", 20))
+                self.session = await self.exit_stack.enter_async_context(
+                    mcp.ClientSession(
+                        read_stream=read_s,
+                        write_stream=write_s,
+                        read_timeout_seconds=read_timeout,
+                        logging_callback=logging_callback,  # type: ignore
+                    )
+                )
+
+        else:
+            server_params = mcp.StdioServerParameters(
+                **cfg,
+            )
+
+            def callback(msg: str):
+                # 处理 MCP 服务的错误日志
+                self.server_errlogs.append(msg)
+
+            stdio_transport = await self.exit_stack.enter_async_context(
+                mcp.stdio_client(
+                    server_params,
+                    errlog=LogPipe(
+                        level=logging.ERROR,
+                        logger=logger,
+                        identifier=f"MCPServer-{name}",
+                        callback=callback,
+                    ),  # type: ignore
+                ),
+            )
+
+            # Create a new client session
+            self.session = await self.exit_stack.enter_async_context(
+                mcp.ClientSession(*stdio_transport)
+            )
+        await self.session.initialize()
+
+    async def list_tools_and_save(self) -> mcp.ListToolsResult:
+        """List all tools from the server and save them to self.tools"""
+        response = await self.session.list_tools()
+        self.tools = response.tools
+        return response
+
+    async def cleanup(self):
+        """Clean up resources"""
+        await self.exit_stack.aclose()
+        self.running_event.set()  # Set the running event to indicate cleanup is done

astrbot/core/agent/response.py

@@ -0,0 +1,12 @@
+from dataclasses import dataclass
+import typing as T
+from astrbot.core.message.message_event_result import MessageChain
+
+class AgentResponseData(T.TypedDict):
+    chain: MessageChain
+
+
+@dataclass
+class AgentResponse:
+    type: str
+    data: AgentResponseData

astrbot/core/agent/run_context.py

@@ -0,0 +1,17 @@
+from dataclasses import dataclass
+from typing import Any, Generic
+from typing_extensions import TypeVar
+
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+
+TContext = TypeVar("TContext", default=Any)
+
+
+@dataclass
+class ContextWrapper(Generic[TContext]):
+    """A context for running an agent, which can be used to pass additional data or state."""
+
+    context: TContext
+    event: AstrMessageEvent
+
+NoContext = ContextWrapper[None]

astrbot/core/agent/runners/__init__.py

@@ -0,0 +1,3 @@
+from .base import BaseAgentRunner
+
+__all__ = ["BaseAgentRunner"]

astrbot/core/agent/runners/base.py

@@ -0,0 +1,58 @@
+import abc
+import typing as T
+from enum import Enum, auto
+from ..run_context import ContextWrapper, TContext
+from ..response import AgentResponse
+from ..hooks import BaseAgentRunHooks
+from ..tool_executor import BaseFunctionToolExecutor
+from astrbot.core.provider import Provider
+from astrbot.core.provider.entities import LLMResponse
+
+
+class AgentState(Enum):
+    """Defines the state of the agent."""
+
+    IDLE = auto()  # Initial state
+    RUNNING = auto()  # Currently processing
+    DONE = auto()  # Completed
+    ERROR = auto()  # Error state
+
+
+class BaseAgentRunner(T.Generic[TContext]):
+    @abc.abstractmethod
+    async def reset(
+        self,
+        provider: Provider,
+        run_context: ContextWrapper[TContext],
+        tool_executor: BaseFunctionToolExecutor[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        **kwargs: T.Any,
+    ) -> None:
+        """
+        Reset the agent to its initial state.
+        This method should be called before starting a new run.
+        """
+        ...
+
+    @abc.abstractmethod
+    async def step(self) -> T.AsyncGenerator[AgentResponse, None]:
+        """
+        Process a single step of the agent.
+        """
+        ...
+
+    @abc.abstractmethod
+    def done(self) -> bool:
+        """
+        Check if the agent has completed its task.
+        Returns True if the agent is done, False otherwise.
+        """
+        ...
+
+    @abc.abstractmethod
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        """
+        Get the final observation from the agent.
+        This method should be called after the agent is done.
+        """
+        ...

astrbot/core/agent/runners/tool_loop_agent_runner.py

@@ -0,0 +1,334 @@
+import sys
+import traceback
+import typing as T
+from .base import BaseAgentRunner, AgentResponse, AgentState
+from ..hooks import BaseAgentRunHooks
+from ..tool_executor import BaseFunctionToolExecutor
+from ..run_context import ContextWrapper, TContext
+from ..response import AgentResponseData
+from astrbot.core.provider.provider import Provider
+from astrbot.core.message.message_event_result import (
+    MessageChain,
+)
+from astrbot.core.provider.entities import (
+    ProviderRequest,
+    LLMResponse,
+    ToolCallMessageSegment,
+    AssistantMessageSegment,
+    ToolCallsResult,
+)
+from mcp.types import (
+    TextContent,
+    ImageContent,
+    EmbeddedResource,
+    TextResourceContents,
+    BlobResourceContents,
+    CallToolResult,
+)
+from astrbot import logger
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
+    @override
+    async def reset(
+        self,
+        provider: Provider,
+        request: ProviderRequest,
+        run_context: ContextWrapper[TContext],
+        tool_executor: BaseFunctionToolExecutor[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        **kwargs: T.Any,
+    ) -> None:
+        self.req = request
+        self.streaming = kwargs.get("streaming", False)
+        self.provider = provider
+        self.final_llm_resp = None
+        self._state = AgentState.IDLE
+        self.tool_executor = tool_executor
+        self.agent_hooks = agent_hooks
+        self.run_context = run_context
+
+    def _transition_state(self, new_state: AgentState) -> None:
+        """转换 Agent 状态"""
+        if self._state != new_state:
+            logger.debug(f"Agent state transition: {self._state} -> {new_state}")
+            self._state = new_state
+
+    async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]:
+        """Yields chunks *and* a final LLMResponse."""
+        if self.streaming:
+            stream = self.provider.text_chat_stream(**self.req.__dict__)
+            async for resp in stream:  # type: ignore
+                yield resp
+        else:
+            yield await self.provider.text_chat(**self.req.__dict__)
+
+    @override
+    async def step(self):
+        """
+        Process a single step of the agent.
+        This method should return the result of the step.
+        """
+        if not self.req:
+            raise ValueError("Request is not set. Please call reset() first.")
+
+        if self._state == AgentState.IDLE:
+            try:
+                await self.agent_hooks.on_agent_begin(self.run_context)
+            except Exception as e:
+                logger.error(f"Error in on_agent_begin hook: {e}", exc_info=True)
+
+        # 开始处理，转换到运行状态
+        self._transition_state(AgentState.RUNNING)
+        llm_resp_result = None
+
+        async for llm_response in self._iter_llm_responses():
+            assert isinstance(llm_response, LLMResponse)
+            if llm_response.is_chunk:
+                if llm_response.result_chain:
+                    yield AgentResponse(
+                        type="streaming_delta",
+                        data=AgentResponseData(chain=llm_response.result_chain),
+                    )
+                else:
+                    yield AgentResponse(
+                        type="streaming_delta",
+                        data=AgentResponseData(
+                            chain=MessageChain().message(llm_response.completion_text)
+                        ),
+                    )
+                continue
+            llm_resp_result = llm_response
+            break  # got final response
+
+        if not llm_resp_result:
+            return
+
+        # 处理 LLM 响应
+        llm_resp = llm_resp_result
+
+        if llm_resp.role == "err":
+            # 如果 LLM 响应错误，转换到错误状态
+            self.final_llm_resp = llm_resp
+            self._transition_state(AgentState.ERROR)
+            yield AgentResponse(
+                type="err",
+                data=AgentResponseData(
+                    chain=MessageChain().message(
+                        f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}"
+                    )
+                ),
+            )
+
+        if not llm_resp.tools_call_name:
+            # 如果没有工具调用，转换到完成状态
+            self.final_llm_resp = llm_resp
+            self._transition_state(AgentState.DONE)
+            try:
+                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)
+
+        # 返回 LLM 结果
+        if llm_resp.result_chain:
+            yield AgentResponse(
+                type="llm_result",
+                data=AgentResponseData(chain=llm_resp.result_chain),
+            )
+        elif llm_resp.completion_text:
+            yield AgentResponse(
+                type="llm_result",
+                data=AgentResponseData(
+                    chain=MessageChain().message(llm_resp.completion_text)
+                ),
+            )
+
+        # 如果有工具调用，还需处理工具调用
+        if llm_resp.tools_call_name:
+            tool_call_result_blocks = []
+            for tool_call_name in llm_resp.tools_call_name:
+                yield AgentResponse(
+                    type="tool_call",
+                    data=AgentResponseData(
+                        chain=MessageChain().message(f"🔨 调用工具: {tool_call_name}")
+                    ),
+                )
+            async for result in self._handle_function_tools(self.req, llm_resp):
+                if isinstance(result, list):
+                    tool_call_result_blocks = result
+                elif isinstance(result, MessageChain):
+                    yield AgentResponse(
+                        type="tool_call_result",
+                        data=AgentResponseData(chain=result),
+                    )
+            # 将结果添加到上下文中
+            tool_calls_result = ToolCallsResult(
+                tool_calls_info=AssistantMessageSegment(
+                    role="assistant",
+                    tool_calls=llm_resp.to_openai_tool_calls(),
+                    content=llm_resp.completion_text,
+                ),
+                tool_calls_result=tool_call_result_blocks,
+            )
+            self.req.append_tool_calls_result(tool_calls_result)
+
+    async def _handle_function_tools(
+        self,
+        req: ProviderRequest,
+        llm_response: LLMResponse,
+    ) -> T.AsyncGenerator[MessageChain | list[ToolCallMessageSegment], None]:
+        """处理函数工具调用。"""
+        tool_call_result_blocks: list[ToolCallMessageSegment] = []
+        logger.info(f"Agent 使用工具: {llm_response.tools_call_name}")
+
+        # 执行函数调用
+        for func_tool_name, func_tool_args, func_tool_id in zip(
+            llm_response.tools_call_name,
+            llm_response.tools_call_args,
+            llm_response.tools_call_ids,
+        ):
+            try:
+                if not req.func_tool:
+                    return
+                func_tool = req.func_tool.get_func(func_tool_name)
+                logger.info(f"使用工具：{func_tool_name}，参数：{func_tool_args}")
+
+                try:
+                    await self.agent_hooks.on_tool_start(
+                        self.run_context, func_tool, func_tool_args
+                    )
+                except Exception as e:
+                    logger.error(f"Error in on_tool_start hook: {e}", exc_info=True)
+
+                executor = self.tool_executor.execute(
+                    tool=func_tool,
+                    run_context=self.run_context,
+                    **func_tool_args,
+                )
+                async for resp in executor:
+                    if isinstance(resp, CallToolResult):
+                        res = resp
+                        if isinstance(res.content[0], TextContent):
+                            tool_call_result_blocks.append(
+                                ToolCallMessageSegment(
+                                    role="tool",
+                                    tool_call_id=func_tool_id,
+                                    content=res.content[0].text,
+                                )
+                            )
+                            yield MessageChain().message(res.content[0].text)
+                        elif isinstance(res.content[0], ImageContent):
+                            tool_call_result_blocks.append(
+                                ToolCallMessageSegment(
+                                    role="tool",
+                                    tool_call_id=func_tool_id,
+                                    content="返回了图片(已直接发送给用户)",
+                                )
+                            )
+                            yield MessageChain(type="tool_direct_result").base64_image(
+                                res.content[0].data
+                            )
+                        elif isinstance(res.content[0], EmbeddedResource):
+                            resource = res.content[0].resource
+                            if isinstance(resource, TextResourceContents):
+                                tool_call_result_blocks.append(
+                                    ToolCallMessageSegment(
+                                        role="tool",
+                                        tool_call_id=func_tool_id,
+                                        content=resource.text,
+                                    )
+                                )
+                                yield MessageChain().message(resource.text)
+                            elif (
+                                isinstance(resource, BlobResourceContents)
+                                and resource.mimeType
+                                and resource.mimeType.startswith("image/")
+                            ):
+                                tool_call_result_blocks.append(
+                                    ToolCallMessageSegment(
+                                        role="tool",
+                                        tool_call_id=func_tool_id,
+                                        content="返回了图片(已直接发送给用户)",
+                                    )
+                                )
+                                yield MessageChain(
+                                    type="tool_direct_result"
+                                ).base64_image(res.content[0].data)
+                            else:
+                                tool_call_result_blocks.append(
+                                    ToolCallMessageSegment(
+                                        role="tool",
+                                        tool_call_id=func_tool_id,
+                                        content="返回的数据类型不受支持",
+                                    )
+                                )
+                                yield MessageChain().message("返回的数据类型不受支持。")
+
+                            try:
+                                await self.agent_hooks.on_tool_end(
+                                    self.run_context,
+                                    func_tool_name,
+                                    func_tool_args,
+                                    resp,
+                                )
+                            except Exception as e:
+                                logger.error(
+                                    f"Error in on_tool_end hook: {e}", exc_info=True
+                                )
+                    elif resp is None:
+                        # Tool 直接请求发送消息给用户
+                        # 这里我们将直接结束 Agent Loop。
+                        self._transition_state(AgentState.DONE)
+                        if res := self.run_context.event.get_result():
+                            if res.chain:
+                                yield MessageChain(
+                                    chain=res.chain, type="tool_direct_result"
+                                )
+                        try:
+                            await self.agent_hooks.on_tool_end(
+                                self.run_context, func_tool_name, func_tool_args, None
+                            )
+                        except Exception as e:
+                            logger.error(
+                                f"Error in on_tool_end hook: {e}", exc_info=True
+                            )
+                    else:
+                        logger.warning(
+                            f"Tool 返回了不支持的类型: {type(resp)}，将忽略。"
+                        )
+
+                        try:
+                            await self.agent_hooks.on_tool_end(
+                                self.run_context, func_tool_name, func_tool_args, None
+                            )
+                        except Exception as e:
+                            logger.error(
+                                f"Error in on_tool_end hook: {e}", exc_info=True
+                            )
+
+                self.run_context.event.clear_result()
+            except Exception as e:
+                logger.warning(traceback.format_exc())
+                tool_call_result_blocks.append(
+                    ToolCallMessageSegment(
+                        role="tool",
+                        tool_call_id=func_tool_id,
+                        content=f"error: {str(e)}",
+                    )
+                )
+
+        # 处理函数调用响应
+        if tool_call_result_blocks:
+            yield tool_call_result_blocks
+
+    def done(self) -> bool:
+        """检查 Agent 是否已完成工作"""
+        return self._state in (AgentState.DONE, AgentState.ERROR)
+
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        return self.final_llm_resp

astrbot/core/agent/tool.py

@@ -0,0 +1,256 @@
+from dataclasses import dataclass
+from deprecated import deprecated
+from typing import Awaitable, Literal, Any, Optional
+from .mcp_client import MCPClient
+
+
+@dataclass
+class FunctionTool:
+    """A class representing a function tool that can be used in function calling."""
+
+    name: str | None = None
+    parameters: dict | None = None
+    description: str | None = None
+    handler: Awaitable | None = None
+    """处理函数, 当 origin 为 mcp 时，这个为空"""
+    handler_module_path: str | None = None
+    """处理函数的模块路径，当 origin 为 mcp 时，这个为空
+
+    必须要保留这个字段, handler 在初始化会被 functools.partial 包装，导致 handler 的 __module__ 为 functools
+    """
+    active: bool = True
+    """是否激活"""
+
+    origin: Literal["local", "mcp"] = "local"
+    """函数工具的来源, local 为本地函数工具, mcp 为 MCP 服务"""
+
+    # MCP 相关字段
+    mcp_server_name: str | None = None
+    """MCP 服务名称，当 origin 为 mcp 时有效"""
+    mcp_client: MCPClient | None = None
+    """MCP 客户端，当 origin 为 mcp 时有效"""
+
+    def __repr__(self):
+        return f"FuncTool(name={self.name}, parameters={self.parameters}, description={self.description}, active={self.active}, origin={self.origin})"
+
+    def __dict__(self) -> dict[str, Any]:
+        """将 FunctionTool 转换为字典格式"""
+        return {
+            "name": self.name,
+            "parameters": self.parameters,
+            "description": self.description,
+            "active": self.active,
+            "origin": self.origin,
+            "mcp_server_name": self.mcp_server_name,
+        }
+
+
+class ToolSet:
+    """A set of function tools that can be used in function calling.
+
+    This class provides methods to add, remove, and retrieve tools, as well as
+    convert the tools to different API formats (OpenAI, Anthropic, Google GenAI)."""
+
+    def __init__(self, tools: list[FunctionTool] = None):
+        self.tools: list[FunctionTool] = tools or []
+
+    def empty(self) -> bool:
+        """Check if the tool set is empty."""
+        return len(self.tools) == 0
+
+    def add_tool(self, tool: FunctionTool):
+        """Add a tool to the set."""
+        # 检查是否已存在同名工具
+        for i, existing_tool in enumerate(self.tools):
+            if existing_tool.name == tool.name:
+                self.tools[i] = tool
+                return
+        self.tools.append(tool)
+
+    def remove_tool(self, name: str):
+        """Remove a tool by its name."""
+        self.tools = [tool for tool in self.tools if tool.name != name]
+
+    def get_tool(self, name: str) -> Optional[FunctionTool]:
+        """Get a tool by its name."""
+        for tool in self.tools:
+            if tool.name == name:
+                return tool
+        return None
+
+    @deprecated(reason="Use add_tool() instead", version="4.0.0")
+    def add_func(self, name: str, func_args: list, desc: str, handler: Awaitable):
+        """Add a function tool to the set."""
+        params = {
+            "type": "object",  # hard-coded here
+            "properties": {},
+        }
+        for param in func_args:
+            params["properties"][param["name"]] = {
+                "type": param["type"],
+                "description": param["description"],
+            }
+        _func = FunctionTool(
+            name=name,
+            parameters=params,
+            description=desc,
+            handler=handler,
+        )
+        self.add_tool(_func)
+
+    @deprecated(reason="Use remove_tool() instead", version="4.0.0")
+    def remove_func(self, name: str):
+        """Remove a function tool by its name."""
+        self.remove_tool(name)
+
+    @deprecated(reason="Use get_tool() instead", version="4.0.0")
+    def get_func(self, name: str) -> list[FunctionTool]:
+        """Get all function tools."""
+        return self.get_tool(name)
+
+    @property
+    def func_list(self) -> list[FunctionTool]:
+        """Get the list of function tools."""
+        return self.tools
+
+    def openai_schema(self, omit_empty_parameter_field: bool = False) -> list[dict]:
+        """Convert tools to OpenAI API function calling schema format."""
+        result = []
+        for tool in self.tools:
+            func_def = {
+                "type": "function",
+                "function": {
+                    "name": tool.name,
+                    "description": tool.description,
+                },
+            }
+
+            if tool.parameters.get("properties") or not omit_empty_parameter_field:
+                func_def["function"]["parameters"] = tool.parameters
+
+            result.append(func_def)
+        return result
+
+    def anthropic_schema(self) -> list[dict]:
+        """Convert tools to Anthropic API format."""
+        result = []
+        for tool in self.tools:
+            tool_def = {
+                "name": tool.name,
+                "description": tool.description,
+                "input_schema": {
+                    "type": "object",
+                    "properties": tool.parameters.get("properties", {}),
+                    "required": tool.parameters.get("required", []),
+                },
+            }
+            result.append(tool_def)
+        return result
+
+    def google_schema(self) -> dict:
+        """Convert tools to Google GenAI API format."""
+
+        def convert_schema(schema: dict) -> dict:
+            """Convert schema to Gemini API format."""
+            supported_types = {
+                "string",
+                "number",
+                "integer",
+                "boolean",
+                "array",
+                "object",
+                "null",
+            }
+            supported_formats = {
+                "string": {"enum", "date-time"},
+                "integer": {"int32", "int64"},
+                "number": {"float", "double"},
+            }
+
+            if "anyOf" in schema:
+                return {"anyOf": [convert_schema(s) for s in schema["anyOf"]]}
+
+            result = {}
+
+            if "type" in schema and schema["type"] in supported_types:
+                result["type"] = schema["type"]
+                if "format" in schema and schema["format"] in supported_formats.get(
+                    result["type"], set()
+                ):
+                    result["format"] = schema["format"]
+            else:
+                result["type"] = "null"
+
+            support_fields = {
+                "title",
+                "description",
+                "enum",
+                "minimum",
+                "maximum",
+                "maxItems",
+                "minItems",
+                "nullable",
+                "required",
+            }
+            result.update({k: schema[k] for k in support_fields if k in schema})
+
+            if "properties" in schema:
+                properties = {}
+                for key, value in schema["properties"].items():
+                    prop_value = convert_schema(value)
+                    if "default" in prop_value:
+                        del prop_value["default"]
+                    properties[key] = prop_value
+
+                if properties:
+                    result["properties"] = properties
+
+            if "items" in schema:
+                result["items"] = convert_schema(schema["items"])
+
+            return result
+
+        tools = [
+            {
+                "name": tool.name,
+                "description": tool.description,
+                "parameters": convert_schema(tool.parameters),
+            }
+            for tool in self.tools
+        ]
+
+        declarations = {}
+        if tools:
+            declarations["function_declarations"] = tools
+        return declarations
+
+    @deprecated(reason="Use openai_schema() instead", version="4.0.0")
+    def get_func_desc_openai_style(self, omit_empty_parameter_field: bool = False):
+        return self.openai_schema(omit_empty_parameter_field)
+
+    @deprecated(reason="Use anthropic_schema() instead", version="4.0.0")
+    def get_func_desc_anthropic_style(self):
+        return self.anthropic_schema()
+
+    @deprecated(reason="Use google_schema() instead", version="4.0.0")
+    def get_func_desc_google_genai_style(self):
+        return self.google_schema()
+
+    def names(self) -> list[str]:
+        """获取所有工具的名称列表"""
+        return [tool.name for tool in self.tools]
+
+    def __len__(self):
+        return len(self.tools)
+
+    def __bool__(self):
+        return len(self.tools) > 0
+
+    def __iter__(self):
+        return iter(self.tools)
+
+    def __repr__(self):
+        return f"ToolSet(tools={self.tools})"
+
+    def __str__(self):
+        return f"ToolSet(tools={self.tools})"

astrbot/core/agent/tool_executor.py

@@ -0,0 +1,11 @@
+import mcp
+from typing import Any, Generic, AsyncGenerator
+from .run_context import TContext, ContextWrapper
+from .tool import FunctionTool
+
+
+class BaseFunctionToolExecutor(Generic[TContext]):
+    @classmethod
+    async def execute(
+        cls, tool: FunctionTool, run_context: ContextWrapper[TContext], **tool_args
+    ) -> AsyncGenerator[Any | mcp.types.CallToolResult, None]: ...

astrbot/core/astr_agent_context.py

@@ -0,0 +1,11 @@
+from dataclasses import dataclass
+from astrbot.core.provider import Provider
+from astrbot.core.provider.entities import ProviderRequest
+
+
+@dataclass
+class AstrAgentContext:
+    provider: Provider
+    first_provider_request: ProviderRequest
+    curr_provider_request: ProviderRequest
+    streaming: bool

astrbot/core/astrbot_config_mgr.py

@@ -0,0 +1,276 @@
+import os
+import uuid
+from astrbot.core import AstrBotConfig, logger
+from astrbot.core.utils.shared_preferences import SharedPreferences
+from astrbot.core.config.astrbot_config import ASTRBOT_CONFIG_PATH
+from astrbot.core.config.default import DEFAULT_CONFIG
+from astrbot.core.platform.message_session import MessageSession
+from astrbot.core.utils.astrbot_path import get_astrbot_config_path
+from typing import TypeVar, TypedDict
+
+_VT = TypeVar("_VT")
+
+
+class ConfInfo(TypedDict):
+    """Configuration information for a specific session or platform."""
+
+    id: str  # UUID of the configuration or "default"
+    umop: list[str]  # Unified Message Origin Pattern
+    name: str
+    path: str  # File name to the configuration file
+
+
+DEFAULT_CONFIG_CONF_INFO = ConfInfo(
+    id="default",
+    umop=["::"],
+    name="default",
+    path=ASTRBOT_CONFIG_PATH,
+)
+
+
+class AstrBotConfigManager:
+    """A class to manage the system configuration of AstrBot, aka ACM"""
+
+    def __init__(self, default_config: AstrBotConfig, sp: SharedPreferences):
+        self.sp = sp
+        self.confs: dict[str, AstrBotConfig] = {}
+        """uuid / "default" -> AstrBotConfig"""
+        self.confs["default"] = default_config
+        self._load_all_configs()
+
+    def _load_all_configs(self):
+        """Load all configurations from the shared preferences."""
+        abconf_data = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        for uuid_, meta in abconf_data.items():
+            filename = meta["path"]
+            conf_path = os.path.join(get_astrbot_config_path(), filename)
+            if os.path.exists(conf_path):
+                conf = AstrBotConfig(config_path=conf_path)
+                self.confs[uuid_] = conf
+            else:
+                logger.warning(
+                    f"Config file {conf_path} for UUID {uuid_} does not exist, skipping."
+                )
+                continue
+
+    def _is_umo_match(self, p1: str, p2: str) -> bool:
+        """判断 p2 umo 是否逻辑包含于 p1 umo"""
+        p1_ls = p1.split(":")
+        p2_ls = p2.split(":")
+
+        if len(p1_ls) != 3 or len(p2_ls) != 3:
+            return False  # 非法格式
+
+        return all(p == "" or p == "*" or p == t for p, t in zip(p1_ls, p2_ls))
+
+    def _load_conf_mapping(self, umo: str | MessageSession) -> ConfInfo:
+        """获取指定 umo 的配置文件 uuid, 如果不存在则返回默认配置(返回 "default")
+
+        Returns:
+            ConfInfo: 包含配置文件的 uuid, 路径和名称等信息, 是一个 dict 类型
+        """
+        # uuid -> { "umop": list, "path": str, "name": str }
+        abconf_data = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        if isinstance(umo, MessageSession):
+            umo = str(umo)
+        else:
+            try:
+                umo = str(MessageSession.from_str(umo))  # validate
+            except Exception:
+                return DEFAULT_CONFIG_CONF_INFO
+
+        for uuid_, meta in abconf_data.items():
+            for pattern in meta["umop"]:
+                if self._is_umo_match(pattern, umo):
+                    return ConfInfo(**meta, id=uuid_)
+
+        return DEFAULT_CONFIG_CONF_INFO
+
+    def _save_conf_mapping(
+        self,
+        abconf_path: str,
+        abconf_id: str,
+        umo_parts: list[str] | list[MessageSession],
+        abconf_name: str | None = None,
+    ) -> None:
+        """保存配置文件的映射关系"""
+        for part in umo_parts:
+            if isinstance(part, MessageSession):
+                part = str(part)
+            elif not isinstance(part, str):
+                raise ValueError(
+                    "umo_parts must be a list of strings or MessageSession instances"
+                )
+        abconf_data = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        random_word = abconf_name or uuid.uuid4().hex[:8]
+        abconf_data[abconf_id] = {
+            "umop": umo_parts,
+            "path": abconf_path,
+            "name": random_word,
+        }
+        self.sp.put("abconf_mapping", abconf_data, scope="global", scope_id="global")
+
+    def get_conf(self, umo: str | MessageSession | None) -> AstrBotConfig:
+        """获取指定 umo 的配置文件。如果不存在，则 fallback 到默认配置文件。"""
+        if not umo:
+            return self.confs["default"]
+        if isinstance(umo, MessageSession):
+            umo = f"{umo.platform_id}:{umo.message_type}:{umo.session_id}"
+
+        uuid_ = self._load_conf_mapping(umo)["id"]
+
+        conf = self.confs.get(uuid_)
+        if not conf:
+            conf = self.confs["default"]  # default MUST exists
+
+        return conf
+
+    @property
+    def default_conf(self) -> AstrBotConfig:
+        """获取默认配置文件"""
+        return self.confs["default"]
+
+    def get_conf_info(self, umo: str | MessageSession) -> ConfInfo:
+        """获取指定 umo 的配置文件元数据"""
+        if isinstance(umo, MessageSession):
+            umo = f"{umo.platform_id}:{umo.message_type}:{umo.session_id}"
+
+        return self._load_conf_mapping(umo)
+
+    def get_conf_list(self) -> list[ConfInfo]:
+        """获取所有配置文件的元数据列表"""
+        conf_list = []
+        conf_list.append(DEFAULT_CONFIG_CONF_INFO)
+        abconf_mapping = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        for uuid_, meta in abconf_mapping.items():
+            conf_list.append(ConfInfo(**meta, id=uuid_))
+        return conf_list
+
+    def create_conf(
+        self,
+        umo_parts: list[str] | list[MessageSession],
+        config: dict = DEFAULT_CONFIG,
+        name: str | None = None,
+    ) -> str:
+        """
+        umo 由三个部分组成 [platform_id]:[message_type]:[session_id]。
+
+        umo_parts 可以是 "::" (代表所有), 可以是 "[platform_id]::" (代表指定平台下的所有类型消息和会话)。
+        """
+        conf_uuid = str(uuid.uuid4())
+        conf_file_name = f"abconf_{conf_uuid}.json"
+        conf_path = os.path.join(get_astrbot_config_path(), conf_file_name)
+        conf = AstrBotConfig(config_path=conf_path, default_config=config)
+        conf.save_config()
+        self._save_conf_mapping(conf_file_name, conf_uuid, umo_parts, abconf_name=name)
+        self.confs[conf_uuid] = conf
+        return conf_uuid
+
+    def delete_conf(self, conf_id: str) -> bool:
+        """删除指定配置文件
+
+        Args:
+            conf_id: 配置文件的 UUID
+
+        Returns:
+            bool: 删除是否成功
+
+        Raises:
+            ValueError: 如果试图删除默认配置文件
+        """
+        if conf_id == "default":
+            raise ValueError("不能删除默认配置文件")
+
+        # 从映射中移除
+        abconf_data = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        if conf_id not in abconf_data:
+            logger.warning(f"配置文件 {conf_id} 不存在于映射中")
+            return False
+
+        # 获取配置文件路径
+        conf_path = os.path.join(
+            get_astrbot_config_path(), abconf_data[conf_id]["path"]
+        )
+
+        # 删除配置文件
+        try:
+            if os.path.exists(conf_path):
+                os.remove(conf_path)
+                logger.info(f"已删除配置文件: {conf_path}")
+        except Exception as e:
+            logger.error(f"删除配置文件 {conf_path} 失败: {e}")
+            return False
+
+        # 从内存中移除
+        if conf_id in self.confs:
+            del self.confs[conf_id]
+
+        # 从映射中移除
+        del abconf_data[conf_id]
+        self.sp.put("abconf_mapping", abconf_data, scope="global", scope_id="global")
+
+        logger.info(f"成功删除配置文件 {conf_id}")
+        return True
+
+    def update_conf_info(
+        self, conf_id: str, name: str | None = None, umo_parts: list[str] | None = None
+    ) -> bool:
+        """更新配置文件信息
+
+        Args:
+            conf_id: 配置文件的 UUID
+            name: 新的配置文件名称 (可选)
+            umo_parts: 新的 UMO 部分列表 (可选)
+
+        Returns:
+            bool: 更新是否成功
+        """
+        if conf_id == "default":
+            raise ValueError("不能更新默认配置文件的信息")
+
+        abconf_data = self.sp.get(
+            "abconf_mapping", {}, scope="global", scope_id="global"
+        )
+        if conf_id not in abconf_data:
+            logger.warning(f"配置文件 {conf_id} 不存在于映射中")
+            return False
+
+        # 更新名称
+        if name is not None:
+            abconf_data[conf_id]["name"] = name
+
+        # 更新 UMO 部分
+        if umo_parts is not None:
+            # 验证 UMO 部分格式
+            for part in umo_parts:
+                if isinstance(part, MessageSession):
+                    part = str(part)
+                elif not isinstance(part, str):
+                    raise ValueError(
+                        "umo_parts must be a list of strings or MessageSession instances"
+                    )
+            abconf_data[conf_id]["umop"] = umo_parts
+
+        # 保存更新
+        self.sp.put("abconf_mapping", abconf_data, scope="global", scope_id="global")
+        logger.info(f"成功更新配置文件 {conf_id} 的信息")
+        return True
+
+    def g(
+        self, umo: str | None = None, key: str | None = None, default: _VT = None
+    ) -> _VT:
+        """获取配置项。umo 为 None 时使用默认配置"""
+        if umo is None:
+            return self.confs["default"].get(key, default)
+        conf = self.get_conf(umo)
+        return conf.get(key, default)

astrbot/core/conversation_mgr.py

@@ -5,40 +5,44 @@ AstrBot 会话-对话管理器, 维护两个本地存储, 其中一个是 json
 在一个会话中可以建立多个对话, 并且支持对话的切换和删除
 """
 
-import uuid
 import json
-import asyncio
 from astrbot.core import sp
 from typing import Dict, List
 from astrbot.core.db import BaseDatabase
-from astrbot.core.db.po import Conversation
+from astrbot.core.db.po import Conversation, ConversationV2
 
 
 class ConversationManager:
     """负责管理会话与 LLM 的对话，某个会话当前正在用哪个对话。"""
 
     def __init__(self, db_helper: BaseDatabase):
-        # session_conversations 字典记录会话ID-对话ID 映射关系
-        self.session_conversations: Dict[str, str] = sp.get("session_conversation", {})
+        self.session_conversations: Dict[str, str] = {}
         self.db = db_helper
         self.save_interval = 60  # 每 60 秒保存一次
-        self._start_periodic_save()
 
-    def _start_periodic_save(self):
-        """启动定时保存任务"""
-        asyncio.create_task(self._periodic_save())
+    def _convert_conv_from_v2_to_v1(self, conv_v2: ConversationV2) -> Conversation:
+        """将 ConversationV2 对象转换为 Conversation 对象"""
+        created_at = int(conv_v2.created_at.timestamp())
+        updated_at = int(conv_v2.updated_at.timestamp())
+        return Conversation(
+            platform_id=conv_v2.platform_id,
+            user_id=conv_v2.user_id,
+            cid=conv_v2.conversation_id,
+            history=json.dumps(conv_v2.content or []),
+            title=conv_v2.title,
+            persona_id=conv_v2.persona_id,
+            created_at=created_at,
+            updated_at=updated_at,
+        )
 
-    async def _periodic_save(self):
-        """定时保存会话对话映射关系到存储中"""
-        while True:
-            await asyncio.sleep(self.save_interval)
-            self._save_to_storage()
-
-    def _save_to_storage(self):
-        """保存会话对话映射关系到存储中"""
-        sp.put("session_conversation", self.session_conversations)
-
-    async def new_conversation(self, unified_msg_origin: str) -> str:
+    async def new_conversation(
+        self,
+        unified_msg_origin: str,
+        platform_id: str | None = None,
+        content: list[dict] | None = None,
+        title: str | None = None,
+        persona_id: str | None = None,
+    ) -> str:
         """新建对话，并将当前会话的对话转移到新对话
 
         Args:
@@ -46,11 +50,23 @@ class ConversationManager:
         Returns:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
-        conversation_id = str(uuid.uuid4())
-        self.db.new_conversation(user_id=unified_msg_origin, cid=conversation_id)
-        self.session_conversations[unified_msg_origin] = conversation_id
-        sp.put("session_conversation", self.session_conversations)
-        return conversation_id
+        if not platform_id:
+            # 如果没有提供 platform_id，则从 unified_msg_origin 中解析
+            parts = unified_msg_origin.split(":")
+            if len(parts) >= 3:
+                platform_id = parts[0]
+        if not platform_id:
+            platform_id = "unknown"
+        conv = await self.db.create_conversation(
+            user_id=unified_msg_origin,
+            platform_id=platform_id,
+            content=content,
+            title=title,
+            persona_id=persona_id,
+        )
+        self.session_conversations[unified_msg_origin] = conv.conversation_id
+        await sp.session_put(unified_msg_origin, "sel_conv_id", conv.conversation_id)
+        return conv.conversation_id
 
     async def switch_conversation(self, unified_msg_origin: str, conversation_id: str):
         """切换会话的对话
@@ -60,10 +76,10 @@ class ConversationManager:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
         self.session_conversations[unified_msg_origin] = conversation_id
-        sp.put("session_conversation", self.session_conversations)
+        await sp.session_put(unified_msg_origin, "sel_conv_id", conversation_id)
 
     async def delete_conversation(
-        self, unified_msg_origin: str, conversation_id: str = None
+        self, unified_msg_origin: str, conversation_id: str | None = None
     ):
         """删除会话的对话，当 conversation_id 为 None 时删除会话当前的对话
 
@@ -71,13 +87,18 @@ class ConversationManager:
             unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
-        conversation_id = self.session_conversations.get(unified_msg_origin)
+        f = False
+        if not conversation_id:
+            conversation_id = self.session_conversations.get(unified_msg_origin)
+            if conversation_id:
+                f = True
         if conversation_id:
-            self.db.delete_conversation(user_id=unified_msg_origin, cid=conversation_id)
-            del self.session_conversations[unified_msg_origin]
-            sp.put("session_conversation", self.session_conversations)
+            await self.db.delete_conversation(cid=conversation_id)
+            if f:
+                self.session_conversations.pop(unified_msg_origin, None)
+                await sp.session_remove(unified_msg_origin, "sel_conv_id")
 
-    async def get_curr_conversation_id(self, unified_msg_origin: str) -> str:
+    async def get_curr_conversation_id(self, unified_msg_origin: str) -> str | None:
         """获取会话当前的对话 ID
 
         Args:
@@ -85,11 +106,19 @@ class ConversationManager:
         Returns:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
-        return self.session_conversations.get(unified_msg_origin, None)
+        ret = self.session_conversations.get(unified_msg_origin, None)
+        if not ret:
+            ret = await sp.session_get(unified_msg_origin, "sel_conv_id", None)
+            if ret:
+                self.session_conversations[unified_msg_origin] = ret
+        return ret
 
     async def get_conversation(
-        self, unified_msg_origin: str, conversation_id: str
-    ) -> Conversation:
+        self,
+        unified_msg_origin: str,
+        conversation_id: str,
+        create_if_not_exists: bool = False,
+    ) -> Conversation | None:
         """获取会话的对话
 
         Args:
@@ -98,20 +127,74 @@ class ConversationManager:
         Returns:
             conversation (Conversation): 对话对象
         """
-        return self.db.get_conversation_by_user_id(unified_msg_origin, conversation_id)
+        conv = await self.db.get_conversation_by_id(cid=conversation_id)
+        if not conv and create_if_not_exists:
+            # 如果对话不存在且需要创建，则新建一个对话
+            conversation_id = await self.new_conversation(unified_msg_origin)
+            conv = await self.db.get_conversation_by_id(cid=conversation_id)
+        conv_res = None
+        if conv:
+            conv_res = self._convert_conv_from_v2_to_v1(conv)
+        return conv_res
 
-    async def get_conversations(self, unified_msg_origin: str) -> List[Conversation]:
-        """获取会话的所有对话
+    async def get_conversations(
+        self, unified_msg_origin: str | None = None, platform_id: str | None = None
+    ) -> List[Conversation]:
+        """获取对话列表
 
         Args:
-            unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
+            unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id，可选
+            platform_id (str): 平台 ID, 可选参数, 用于过滤对话
         Returns:
             conversations (List[Conversation]): 对话对象列表
         """
-        return self.db.get_conversations(unified_msg_origin)
+        convs = await self.db.get_conversations(
+            user_id=unified_msg_origin, platform_id=platform_id
+        )
+        convs_res = []
+        for conv in convs:
+            conv_res = self._convert_conv_from_v2_to_v1(conv)
+            convs_res.append(conv_res)
+        return convs_res
+
+    async def get_filtered_conversations(
+        self,
+        page: int = 1,
+        page_size: int = 20,
+        platform_ids: list[str] | None = None,
+        search_query: str = "",
+        **kwargs,
+    ) -> tuple[list[Conversation], int]:
+        """获取过滤后的对话列表
+
+        Args:
+            page (int): 页码, 默认为 1
+            page_size (int): 每页大小, 默认为 20
+            platform_ids (list[str]): 平台 ID 列表, 可选
+            search_query (str): 搜索查询字符串, 可选
+        Returns:
+            conversations (list[Conversation]): 对话对象列表
+        """
+        convs, cnt = await self.db.get_filtered_conversations(
+            page=page,
+            page_size=page_size,
+            platform_ids=platform_ids,
+            search_query=search_query,
+            **kwargs,
+        )
+        convs_res = []
+        for conv in convs:
+            conv_res = self._convert_conv_from_v2_to_v1(conv)
+            convs_res.append(conv_res)
+        return convs_res, cnt
 
     async def update_conversation(
-        self, unified_msg_origin: str, conversation_id: str, history: List[Dict]
+        self,
+        unified_msg_origin: str,
+        conversation_id: str | None = None,
+        history: list[dict] | None = None,
+        title: str | None = None,
+        persona_id: str | None = None,
     ):
         """更新会话的对话
 
@@ -120,40 +203,55 @@ class ConversationManager:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
             history (List[Dict]): 对话历史记录, 是一个字典列表, 每个字典包含 role 和 content 字段
         """
+        if not conversation_id:
+            # 如果没有提供 conversation_id，则获取当前的
+            conversation_id = await self.get_curr_conversation_id(unified_msg_origin)
         if conversation_id:
-            self.db.update_conversation(
-                user_id=unified_msg_origin,
+            await self.db.update_conversation(
                 cid=conversation_id,
-                history=json.dumps(history),
+                title=title,
+                persona_id=persona_id,
+                content=history,
             )
 
-    async def update_conversation_title(self, unified_msg_origin: str, title: str):
+    async def update_conversation_title(
+        self, unified_msg_origin: str, title: str, conversation_id: str | None = None
+    ):
         """更新会话的对话标题
 
         Args:
             unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
             title (str): 对话标题
+
+        Deprecated:
+            Use `update_conversation` with `title` parameter instead.
         """
-        conversation_id = self.session_conversations.get(unified_msg_origin)
-        if conversation_id:
-            self.db.update_conversation_title(
-                user_id=unified_msg_origin, cid=conversation_id, title=title
-            )
+        await self.update_conversation(
+            unified_msg_origin=unified_msg_origin,
+            conversation_id=conversation_id,
+            title=title,
+        )
 
     async def update_conversation_persona_id(
-        self, unified_msg_origin: str, persona_id: str
+        self,
+        unified_msg_origin: str,
+        persona_id: str,
+        conversation_id: str | None = None,
     ):
         """更新会话的对话 Persona ID
 
         Args:
             unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
             persona_id (str): 对话 Persona ID
+
+        Deprecated:
+            Use `update_conversation` with `persona_id` parameter instead.
         """
-        conversation_id = self.session_conversations.get(unified_msg_origin)
-        if conversation_id:
-            self.db.update_conversation_persona_id(
-                user_id=unified_msg_origin, cid=conversation_id, persona_id=persona_id
-            )
+        await self.update_conversation(
+            unified_msg_origin=unified_msg_origin,
+            conversation_id=conversation_id,
+            persona_id=persona_id,
+        )
 
     async def get_human_readable_context(
         self, unified_msg_origin, conversation_id, page=1, page_size=10

astrbot/core/core_lifecycle.py

@@ -15,20 +15,23 @@ import time
 import threading
 import os
 from .event_bus import EventBus
-from . import astrbot_config
+from . import astrbot_config, html_renderer
 from asyncio import Queue
 from typing import List
 from astrbot.core.pipeline.scheduler import PipelineScheduler, PipelineContext
 from astrbot.core.star import PluginManager
 from astrbot.core.platform.manager import PlatformManager
 from astrbot.core.star.context import Context
+from astrbot.core.persona_mgr import PersonaManager
 from astrbot.core.provider.manager import ProviderManager
 from astrbot.core import LogBroker
 from astrbot.core.db import BaseDatabase
 from astrbot.core.updator import AstrBotUpdator
-from astrbot.core import logger
+from astrbot.core import logger, sp
 from astrbot.core.config.default import VERSION
 from astrbot.core.conversation_mgr import ConversationManager
+from astrbot.core.platform_message_history_mgr import PlatformMessageHistoryManager
+from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star_handler import star_map
 
@@ -46,10 +49,24 @@ class AstrBotCoreLifecycle:
         self.astrbot_config = astrbot_config  # 初始化配置
         self.db = db  # 初始化数据库
 
-        # 根据环境变量设置代理
-        os.environ["https_proxy"] = self.astrbot_config["http_proxy"]
-        os.environ["http_proxy"] = self.astrbot_config["http_proxy"]
-        os.environ["no_proxy"] = "localhost"
+        # 设置代理
+        proxy_config = self.astrbot_config.get("http_proxy", "")
+        if proxy_config != "":
+            os.environ["https_proxy"] = proxy_config
+            os.environ["http_proxy"] = proxy_config
+            logger.debug(f"Using proxy: {proxy_config}")
+            # 设置 no_proxy
+            no_proxy_list = self.astrbot_config.get("no_proxy", [])
+            os.environ["no_proxy"] = ",".join(no_proxy_list)
+        else:
+            # 清空代理环境变量
+            if "https_proxy" in os.environ:
+                del os.environ["https_proxy"]
+            if "http_proxy" in os.environ:
+                del os.environ["http_proxy"]
+            if "no_proxy" in os.environ:
+                del os.environ["no_proxy"]
+            logger.debug("HTTP proxy cleared")
 
     async def initialize(self):
         """
@@ -63,11 +80,26 @@ class AstrBotCoreLifecycle:
         else:
             logger.setLevel(self.astrbot_config["log_level"])  # 设置日志级别
 
+        await self.db.initialize()
+
+        await html_renderer.initialize()
+
+        # 初始化 AstrBot 配置管理器
+        self.astrbot_config_mgr = AstrBotConfigManager(
+            default_config=self.astrbot_config, sp=sp
+        )
+
         # 初始化事件队列
         self.event_queue = Queue()
 
+        # 初始化人格管理器
+        self.persona_mgr = PersonaManager(self.db, self.astrbot_config_mgr)
+        await self.persona_mgr.initialize()
+
         # 初始化供应商管理器
-        self.provider_manager = ProviderManager(self.astrbot_config, self.db)
+        self.provider_manager = ProviderManager(
+            self.astrbot_config_mgr, self.db, self.persona_mgr
+        )
 
         # 初始化平台管理器
         self.platform_manager = PlatformManager(self.astrbot_config, self.event_queue)
@@ -75,6 +107,9 @@ class AstrBotCoreLifecycle:
         # 初始化对话管理器
         self.conversation_manager = ConversationManager(self.db)
 
+        # 初始化平台消息历史管理器
+        self.platform_message_history_manager = PlatformMessageHistoryManager(self.db)
+
         # 初始化提供给插件的上下文
         self.star_context = Context(
             self.event_queue,
@@ -83,6 +118,9 @@ class AstrBotCoreLifecycle:
             self.provider_manager,
             self.platform_manager,
             self.conversation_manager,
+            self.platform_message_history_manager,
+            self.persona_mgr,
+            self.astrbot_config_mgr,
         )
 
         # 初始化插件管理器
@@ -95,16 +133,16 @@ class AstrBotCoreLifecycle:
         await self.provider_manager.initialize()
 
         # 初始化消息事件流水线调度器
-        self.pipeline_scheduler = PipelineScheduler(
-            PipelineContext(self.astrbot_config, self.plugin_manager)
-        )
-        await self.pipeline_scheduler.initialize()
+
+        self.pipeline_scheduler_mapping = await self.load_pipeline_scheduler()
 
         # 初始化更新器
         self.astrbot_updator = AstrBotUpdator()
 
         # 初始化事件总线
-        self.event_bus = EventBus(self.event_queue, self.pipeline_scheduler)
+        self.event_bus = EventBus(
+            self.event_queue, self.pipeline_scheduler_mapping, self.astrbot_config_mgr
+        )
 
         # 记录启动时间
         self.start_time = int(time.time())
@@ -221,6 +259,39 @@ class AstrBotCoreLifecycle:
         platform_insts = self.platform_manager.get_insts()
         for platform_inst in platform_insts:
             tasks.append(
-                asyncio.create_task(platform_inst.run(), name=platform_inst.meta().name)
+                asyncio.create_task(
+                    platform_inst.run(),
+                    name=f"{platform_inst.meta().id}({platform_inst.meta().name})",
+                )
             )
         return tasks
+
+    async def load_pipeline_scheduler(self) -> dict[str, PipelineScheduler]:
+        """加载消息事件流水线调度器
+
+        Returns:
+            dict[str, PipelineScheduler]: 平台 ID 到流水线调度器的映射
+        """
+        mapping = {}
+        for conf_id, ab_config in self.astrbot_config_mgr.confs.items():
+            scheduler = PipelineScheduler(
+                PipelineContext(ab_config, self.plugin_manager, conf_id)
+            )
+            await scheduler.initialize()
+            mapping[conf_id] = scheduler
+        return mapping
+
+    async def reload_pipeline_scheduler(self, conf_id: str):
+        """重新加载消息事件流水线调度器
+
+        Returns:
+            dict[str, PipelineScheduler]: 平台 ID 到流水线调度器的映射
+        """
+        ab_config = self.astrbot_config_mgr.confs.get(conf_id)
+        if not ab_config:
+            raise ValueError(f"配置文件 {conf_id} 不存在")
+        scheduler = PipelineScheduler(
+            PipelineContext(ab_config, self.plugin_manager, conf_id)
+        )
+        await scheduler.initialize()
+        self.pipeline_scheduler_mapping[conf_id] = scheduler

astrbot/core/db/__init__.py

@@ -1,7 +1,20 @@
 import abc
+import datetime
+import typing as T
+from deprecated import deprecated
 from dataclasses import dataclass
-from typing import List, Dict, Any, Tuple
-from astrbot.core.db.po import Stats, LLMHistory, ATRIVision, Conversation
+from astrbot.core.db.po import (
+    Stats,
+    PlatformStat,
+    ConversationV2,
+    PlatformMessageHistory,
+    Attachment,
+    Persona,
+    Preference,
+)
+from contextlib import asynccontextmanager
+from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
+from sqlalchemy.orm import sessionmaker
 
 
 @dataclass
@@ -10,152 +23,262 @@ class BaseDatabase(abc.ABC):
     数据库基类
     """
 
+    DATABASE_URL = ""
+
     def __init__(self) -> None:
+        self.engine = create_async_engine(
+            self.DATABASE_URL,
+            echo=False,
+            future=True,
+        )
+        self.AsyncSessionLocal = sessionmaker(
+            self.engine, class_=AsyncSession, expire_on_commit=False
+        )
+
+    async def initialize(self):
+        """初始化数据库连接"""
         pass
 
-    def insert_base_metrics(self, metrics: dict):
-        """插入基础指标数据"""
-        self.insert_platform_metrics(metrics["platform_stats"])
-        self.insert_plugin_metrics(metrics["plugin_stats"])
-        self.insert_command_metrics(metrics["command_stats"])
-        self.insert_llm_metrics(metrics["llm_stats"])
-
-    @abc.abstractmethod
-    def insert_platform_metrics(self, metrics: dict):
-        """插入平台指标数据"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def insert_plugin_metrics(self, metrics: dict):
-        """插入插件指标数据"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def insert_command_metrics(self, metrics: dict):
-        """插入指令指标数据"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def insert_llm_metrics(self, metrics: dict):
-        """插入 LLM 指标数据"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def update_llm_history(self, session_id: str, content: str, provider_type: str):
-        """更新 LLM 历史记录。当不存在 session_id 时插入"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def get_llm_history(
-        self, session_id: str = None, provider_type: str = None
-    ) -> List[LLMHistory]:
-        """获取 LLM 历史记录, 如果 session_id 为 None, 返回所有"""
-        raise NotImplementedError
+    @asynccontextmanager
+    async def get_db(self) -> T.AsyncGenerator[AsyncSession, None]:
+        """Get a database session."""
+        if not self.inited:
+            await self.initialize()
+            self.inited = True
+        async with self.AsyncSessionLocal() as session:
+            yield session
 
+    @deprecated(version="4.0.0", reason="Use get_platform_stats instead")
     @abc.abstractmethod
     def get_base_stats(self, offset_sec: int = 86400) -> Stats:
         """获取基础统计数据"""
         raise NotImplementedError
 
+    @deprecated(version="4.0.0", reason="Use get_platform_stats instead")
     @abc.abstractmethod
     def get_total_message_count(self) -> int:
         """获取总消息数"""
         raise NotImplementedError
 
+    @deprecated(version="4.0.0", reason="Use get_platform_stats instead")
     @abc.abstractmethod
     def get_grouped_base_stats(self, offset_sec: int = 86400) -> Stats:
         """获取基础统计数据(合并)"""
         raise NotImplementedError
 
-    @abc.abstractmethod
-    def insert_atri_vision_data(self, vision_data: ATRIVision):
-        """插入 ATRI 视觉数据"""
-        raise NotImplementedError
+    # New methods in v4.0.0
 
     @abc.abstractmethod
-    def get_atri_vision_data(self) -> List[ATRIVision]:
-        """获取 ATRI 视觉数据"""
-        raise NotImplementedError
+    async def insert_platform_stats(
+        self,
+        platform_id: str,
+        platform_type: str,
+        count: int = 1,
+        timestamp: datetime.datetime | None = None,
+    ) -> None:
+        """Insert a new platform statistic record."""
+        ...
 
     @abc.abstractmethod
-    def get_atri_vision_data_by_path_or_id(
-        self, url_or_path: str, id: str
-    ) -> ATRIVision:
-        """通过 url 或 path 获取 ATRI 视觉数据"""
-        raise NotImplementedError
+    async def count_platform_stats(self) -> int:
+        """Count the number of platform statistics records."""
+        ...
 
     @abc.abstractmethod
-    def get_conversation_by_user_id(self, user_id: str, cid: str) -> Conversation:
-        """通过 user_id 和 cid 获取 Conversation"""
-        raise NotImplementedError
+    async def get_platform_stats(self, offset_sec: int = 86400) -> list[PlatformStat]:
+        """Get platform statistics within the specified offset in seconds and group by platform_id."""
+        ...
 
     @abc.abstractmethod
-    def new_conversation(self, user_id: str, cid: str):
-        """新建 Conversation"""
-        raise NotImplementedError
+    async def get_conversations(
+        self, user_id: str | None = None, platform_id: str | None = None
+    ) -> list[ConversationV2]:
+        """Get all conversations for a specific user and platform_id(optional).
 
-    @abc.abstractmethod
-    def get_conversations(self, user_id: str) -> List[Conversation]:
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def update_conversation(self, user_id: str, cid: str, history: str):
-        """更新 Conversation"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def delete_conversation(self, user_id: str, cid: str):
-        """删除 Conversation"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def update_conversation_title(self, user_id: str, cid: str, title: str):
-        """更新 Conversation 标题"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def update_conversation_persona_id(self, user_id: str, cid: str, persona_id: str):
-        """更新 Conversation Persona ID"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def get_all_conversations(
-        self, page: int = 1, page_size: int = 20
-    ) -> Tuple[List[Dict[str, Any]], int]:
-        """获取所有对话，支持分页
-
-        Args:
-            page: 页码，从1开始
-            page_size: 每页数量
-
-        Returns:
-            Tuple[List[Dict[str, Any]], int]: 返回一个元组，包含对话列表和总对话数
+        content is not included in the result.
         """
-        raise NotImplementedError
+        ...
 
     @abc.abstractmethod
-    def get_filtered_conversations(
+    async def get_conversation_by_id(self, cid: str) -> ConversationV2:
+        """Get a specific conversation by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def get_all_conversations(
+        self, page: int = 1, page_size: int = 20
+    ) -> list[ConversationV2]:
+        """Get all conversations with pagination."""
+        ...
+
+    @abc.abstractmethod
+    async def get_filtered_conversations(
         self,
         page: int = 1,
         page_size: int = 20,
-        platforms: List[str] = None,
-        message_types: List[str] = None,
-        search_query: str = None,
-        exclude_ids: List[str] = None,
-        exclude_platforms: List[str] = None,
-    ) -> Tuple[List[Dict[str, Any]], int]:
-        """获取筛选后的对话列表
+        platform_ids: list[str] | None = None,
+        search_query: str = "",
+        **kwargs,
+    ) -> tuple[list[ConversationV2], int]:
+        """Get conversations filtered by platform IDs and search query."""
+        ...
 
-        Args:
-            page: 页码
-            page_size: 每页数量
-            platforms: 平台筛选列表
-            message_types: 消息类型筛选列表
-            search_query: 搜索关键词
-            exclude_ids: 排除的用户ID列表
-            exclude_platforms: 排除的平台列表
+    @abc.abstractmethod
+    async def create_conversation(
+        self,
+        user_id: str,
+        platform_id: str,
+        content: list[dict] | None = None,
+        title: str | None = None,
+        persona_id: str | None = None,
+        cid: str | None = None,
+        created_at: datetime.datetime | None = None,
+        updated_at: datetime.datetime | None = None,
+    ) -> ConversationV2:
+        """Create a new conversation."""
+        ...
 
-        Returns:
-            Tuple[List[Dict[str, Any]], int]: 返回一个元组，包含对话列表和总对话数
-        """
-        raise NotImplementedError
+    @abc.abstractmethod
+    async def update_conversation(
+        self,
+        cid: str,
+        title: str | None = None,
+        persona_id: str | None = None,
+        content: list[dict] | None = None,
+    ) -> None:
+        """Update a conversation's history."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_conversation(self, cid: str) -> None:
+        """Delete a conversation by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def insert_platform_message_history(
+        self,
+        platform_id: str,
+        user_id: str,
+        content: list[dict],
+        sender_id: str | None = None,
+        sender_name: str | None = None,
+    ) -> None:
+        """Insert a new platform message history record."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_platform_message_offset(
+        self, platform_id: str, user_id: str, offset_sec: int = 86400
+    ) -> None:
+        """Delete platform message history records older than the specified offset."""
+        ...
+
+    @abc.abstractmethod
+    async def get_platform_message_history(
+        self,
+        platform_id: str,
+        user_id: str,
+        page: int = 1,
+        page_size: int = 20,
+    ) -> list[PlatformMessageHistory]:
+        """Get platform message history for a specific user."""
+        ...
+
+    @abc.abstractmethod
+    async def insert_attachment(
+        self,
+        path: str,
+        type: str,
+        mime_type: str,
+    ):
+        """Insert a new attachment record."""
+        ...
+
+    @abc.abstractmethod
+    async def get_attachment_by_id(self, attachment_id: str) -> Attachment:
+        """Get an attachment by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def insert_persona(
+        self,
+        persona_id: str,
+        system_prompt: str,
+        begin_dialogs: list[str] | None = None,
+        tools: list[str] | None = None,
+    ) -> Persona:
+        """Insert a new persona record."""
+        ...
+
+    @abc.abstractmethod
+    async def get_persona_by_id(self, persona_id: str) -> Persona:
+        """Get a persona by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def get_personas(self) -> list[Persona]:
+        """Get all personas for a specific bot."""
+        ...
+
+    @abc.abstractmethod
+    async def update_persona(
+        self,
+        persona_id: str,
+        system_prompt: str | None = None,
+        begin_dialogs: list[str] | None = None,
+        tools: list[str] | None = None,
+    ) -> Persona | None:
+        """Update a persona's system prompt or begin dialogs."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_persona(self, persona_id: str) -> None:
+        """Delete a persona by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def insert_preference_or_update(
+        self, scope: str, scope_id: str, key: str, value: dict
+    ) -> Preference:
+        """Insert a new preference record."""
+        ...
+
+    @abc.abstractmethod
+    async def get_preference(self, scope: str, scope_id: str, key: str) -> Preference:
+        """Get a preference by scope ID and key."""
+        ...
+
+    @abc.abstractmethod
+    async def get_preferences(
+        self, scope: str, scope_id: str | None = None, key: str | None = None
+    ) -> list[Preference]:
+        """Get all preferences for a specific scope ID or key."""
+        ...
+
+    @abc.abstractmethod
+    async def remove_preference(self, scope: str, scope_id: str, key: str) -> None:
+        """Remove a preference by scope ID and key."""
+        ...
+
+    @abc.abstractmethod
+    async def clear_preferences(self, scope: str, scope_id: str) -> None:
+        """Clear all preferences for a specific scope ID."""
+        ...
+
+    # @abc.abstractmethod
+    # async def insert_llm_message(
+    #     self,
+    #     cid: str,
+    #     role: str,
+    #     content: list,
+    #     tool_calls: list = None,
+    #     tool_call_id: str = None,
+    #     parent_id: str = None,
+    # ) -> LLMMessage:
+    #     """Insert a new LLM message into the conversation."""
+    #     ...
+
+    # @abc.abstractmethod
+    # async def get_llm_messages(self, cid: str) -> list[LLMMessage]:
+    #     """Get all LLM messages for a specific conversation."""
+    #     ...

astrbot/core/db/migration/helper.py

@@ -0,0 +1,64 @@
+import os
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from astrbot.core.db import BaseDatabase
+from astrbot.core.config import AstrBotConfig
+from astrbot.api import logger, sp
+from .migra_3_to_4 import (
+    migration_conversation_table,
+    migration_platform_table,
+    migration_webchat_data,
+    migration_persona_data,
+    migration_preferences,
+)
+
+
+async def check_migration_needed_v4(db_helper: BaseDatabase) -> bool:
+    """
+    检查是否需要进行数据库迁移
+    如果存在 data_v3.db 并且 preference 中没有 migration_done_v4，则需要进行迁移。
+    """
+    data_v3_exists = os.path.exists(get_astrbot_data_path())
+    if not data_v3_exists:
+        return False
+    migration_done = await db_helper.get_preference(
+        "global", "global", "migration_done_v4"
+    )
+    if migration_done:
+        return False
+    return True
+
+
+async def do_migration_v4(
+    db_helper: BaseDatabase,
+    platform_id_map: dict[str, dict[str, str]],
+    astrbot_config: AstrBotConfig,
+):
+    """
+    执行数据库迁移
+    迁移旧的 webchat_conversation 表到新的 conversation 表。
+    迁移旧的 platform 到新的 platform_stats 表。
+    """
+    if not await check_migration_needed_v4(db_helper):
+        return
+
+    logger.info("开始执行数据库迁移...")
+
+    # 执行会话表迁移
+    await migration_conversation_table(db_helper, platform_id_map)
+
+    # 执行人格数据迁移
+    await migration_persona_data(db_helper, astrbot_config)
+
+    # 执行 WebChat 数据迁移
+    await migration_webchat_data(db_helper, platform_id_map)
+
+    # 执行偏好设置迁移
+    await migration_preferences(db_helper,platform_id_map)
+
+    # 执行平台统计表迁移
+    await migration_platform_table(db_helper, platform_id_map)
+
+    # 标记迁移完成
+    await sp.put_async("global", "global", "migration_done_v4", True)
+
+    logger.info("数据库迁移完成。")

astrbot/core/db/migration/migra_3_to_4.py

@@ -0,0 +1,338 @@
+import json
+import datetime
+from .. import BaseDatabase
+from .sqlite_v3 import SQLiteDatabase as SQLiteV3DatabaseV3
+from .shared_preferences_v3 import sp as sp_v3
+from astrbot.core.config.default import DB_PATH
+from astrbot.api import logger, sp
+from astrbot.core.config import AstrBotConfig
+from astrbot.core.platform.astr_message_event import MessageSesion
+from sqlalchemy.ext.asyncio import AsyncSession
+from astrbot.core.db.po import ConversationV2, PlatformMessageHistory
+from sqlalchemy import text
+
+"""
+1. 迁移旧的 webchat_conversation 表到新的 conversation 表。
+2. 迁移旧的 platform 到新的 platform_stats 表。
+"""
+
+
+def get_platform_id(
+    platform_id_map: dict[str, dict[str, str]], old_platform_name: str
+) -> str:
+    return platform_id_map.get(
+        old_platform_name,
+        {"platform_id": old_platform_name, "platform_type": old_platform_name},
+    ).get("platform_id", old_platform_name)
+
+
+def get_platform_type(
+    platform_id_map: dict[str, dict[str, str]], old_platform_name: str
+) -> str:
+    return platform_id_map.get(
+        old_platform_name,
+        {"platform_id": old_platform_name, "platform_type": old_platform_name},
+    ).get("platform_type", old_platform_name)
+
+
+async def migration_conversation_table(
+    db_helper: BaseDatabase, platform_id_map: dict[str, dict[str, str]]
+):
+    db_helper_v3 = SQLiteV3DatabaseV3(
+        db_path=DB_PATH.replace("data_v4.db", "data_v3.db")
+    )
+    conversations, total_cnt = db_helper_v3.get_all_conversations(
+        page=1, page_size=10000000
+    )
+    logger.info(f"迁移 {total_cnt} 条旧的会话数据到新的表中...")
+
+    async with db_helper.get_db() as dbsession:
+        dbsession: AsyncSession
+        async with dbsession.begin():
+            for idx, conversation in enumerate(conversations):
+                if total_cnt > 0 and (idx + 1) % max(1, total_cnt // 10) == 0:
+                    progress = int((idx + 1) / total_cnt * 100)
+                    if progress % 10 == 0:
+                        logger.info(f"进度: {progress}% ({idx + 1}/{total_cnt})")
+                try:
+                    conv = db_helper_v3.get_conversation_by_user_id(
+                        user_id=conversation.get("user_id", "unknown"),
+                        cid=conversation.get("cid", "unknown"),
+                    )
+                    if not conv:
+                        logger.info(
+                            f"未找到该条旧会话对应的具体数据: {conversation}, 跳过。"
+                        )
+                    if ":" not in conv.user_id:
+                        continue
+                    session = MessageSesion.from_str(session_str=conv.user_id)
+                    platform_id = get_platform_id(
+                        platform_id_map, session.platform_name
+                    )
+                    session.platform_id = platform_id  # 更新平台名称为新的 ID
+                    conv_v2 = ConversationV2(
+                        user_id=str(session),
+                        content=json.loads(conv.history) if conv.history else [],
+                        platform_id=platform_id,
+                        title=conv.title,
+                        persona_id=conv.persona_id,
+                        conversation_id=conv.cid,
+                        created_at=datetime.datetime.fromtimestamp(conv.created_at),
+                        updated_at=datetime.datetime.fromtimestamp(conv.updated_at),
+                    )
+                    dbsession.add(conv_v2)
+                except Exception as e:
+                    logger.error(
+                        f"迁移旧会话 {conversation.get('cid', 'unknown')} 失败: {e}",
+                        exc_info=True,
+                    )
+    logger.info(f"成功迁移 {total_cnt} 条旧的会话数据到新表。")
+
+
+async def migration_platform_table(
+    db_helper: BaseDatabase, platform_id_map: dict[str, dict[str, str]]
+):
+    db_helper_v3 = SQLiteV3DatabaseV3(
+        db_path=DB_PATH.replace("data_v4.db", "data_v3.db")
+    )
+    secs_from_2023_4_10_to_now = (
+        datetime.datetime.now(datetime.timezone.utc)
+        - datetime.datetime(2023, 4, 10, tzinfo=datetime.timezone.utc)
+    ).total_seconds()
+    offset_sec = int(secs_from_2023_4_10_to_now)
+    logger.info(f"迁移旧平台数据，offset_sec: {offset_sec} 秒。")
+    stats = db_helper_v3.get_base_stats(offset_sec=offset_sec)
+    logger.info(f"迁移 {len(stats.platform)} 条旧的平台数据到新的表中...")
+    platform_stats_v3 = stats.platform
+
+    if not platform_stats_v3:
+        logger.info("没有找到旧平台数据，跳过迁移。")
+        return
+
+    first_time_stamp = platform_stats_v3[0].timestamp
+    end_time_stamp = platform_stats_v3[-1].timestamp
+    start_time = first_time_stamp - (first_time_stamp % 3600)  # 向下取整到小时
+    end_time = end_time_stamp + (3600 - (end_time_stamp % 3600))  # 向上取整到小时
+
+    idx = 0
+
+    async with db_helper.get_db() as dbsession:
+        dbsession: AsyncSession
+        async with dbsession.begin():
+            total_buckets = (end_time - start_time) // 3600
+            for bucket_idx, bucket_end in enumerate(range(start_time, end_time, 3600)):
+                if bucket_idx % 500 == 0:
+                    progress = int((bucket_idx + 1) / total_buckets * 100)
+                    logger.info(f"进度: {progress}% ({bucket_idx + 1}/{total_buckets})")
+                cnt = 0
+                while (
+                    idx < len(platform_stats_v3)
+                    and platform_stats_v3[idx].timestamp < bucket_end
+                ):
+                    cnt += platform_stats_v3[idx].count
+                    idx += 1
+                if cnt == 0:
+                    continue
+                platform_id = get_platform_id(
+                    platform_id_map, platform_stats_v3[idx].name
+                )
+                platform_type = get_platform_type(
+                    platform_id_map, platform_stats_v3[idx].name
+                )
+                try:
+                    await dbsession.execute(
+                        text("""
+                        INSERT INTO platform_stats (timestamp, platform_id, platform_type, count)
+                        VALUES (:timestamp, :platform_id, :platform_type, :count)
+                        ON CONFLICT(timestamp, platform_id, platform_type) DO UPDATE SET
+                            count = platform_stats.count + EXCLUDED.count
+                        """),
+                        {
+                            "timestamp": datetime.datetime.fromtimestamp(
+                                bucket_end, tz=datetime.timezone.utc
+                            ),
+                            "platform_id": platform_id,
+                            "platform_type": platform_type,
+                            "count": cnt,
+                        },
+                    )
+                except Exception:
+                    logger.error(
+                        f"迁移平台统计数据失败: {platform_id}, {platform_type}, 时间戳: {bucket_end}",
+                        exc_info=True,
+                    )
+    logger.info(f"成功迁移 {len(platform_stats_v3)} 条旧的平台数据到新表。")
+
+
+async def migration_webchat_data(
+    db_helper: BaseDatabase, platform_id_map: dict[str, dict[str, str]]
+):
+    """迁移 WebChat 的历史记录到新的 PlatformMessageHistory 表中"""
+    db_helper_v3 = SQLiteV3DatabaseV3(
+        db_path=DB_PATH.replace("data_v4.db", "data_v3.db")
+    )
+    conversations, total_cnt = db_helper_v3.get_all_conversations(
+        page=1, page_size=10000000
+    )
+    logger.info(f"迁移 {total_cnt} 条旧的 WebChat 会话数据到新的表中...")
+
+    async with db_helper.get_db() as dbsession:
+        dbsession: AsyncSession
+        async with dbsession.begin():
+            for idx, conversation in enumerate(conversations):
+                if total_cnt > 0 and (idx + 1) % max(1, total_cnt // 10) == 0:
+                    progress = int((idx + 1) / total_cnt * 100)
+                    if progress % 10 == 0:
+                        logger.info(f"进度: {progress}% ({idx + 1}/{total_cnt})")
+                try:
+                    conv = db_helper_v3.get_conversation_by_user_id(
+                        user_id=conversation.get("user_id", "unknown"),
+                        cid=conversation.get("cid", "unknown"),
+                    )
+                    if not conv:
+                        logger.info(
+                            f"未找到该条旧会话对应的具体数据: {conversation}, 跳过。"
+                        )
+                    if ":" in conv.user_id:
+                        continue
+                    platform_id = "webchat"
+                    history = json.loads(conv.history) if conv.history else []
+                    for msg in history:
+                        type_ = msg.get("type")  # user type, "bot" or "user"
+                        new_history = PlatformMessageHistory(
+                            platform_id=platform_id,
+                            user_id=conv.cid,  # we use conv.cid as user_id for webchat
+                            content=msg,
+                            sender_id=type_,
+                            sender_name=type_,
+                        )
+                        dbsession.add(new_history)
+
+                except Exception:
+                    logger.error(
+                        f"迁移旧 WebChat 会话 {conversation.get('cid', 'unknown')} 失败",
+                        exc_info=True,
+                    )
+
+    logger.info(f"成功迁移 {total_cnt} 条旧的 WebChat 会话数据到新表。")
+
+
+async def migration_persona_data(
+    db_helper: BaseDatabase, astrbot_config: AstrBotConfig
+):
+    """
+    迁移 Persona 数据到新的表中。
+    旧的 Persona 数据存储在 preference 中，新的 Persona 数据存储在 persona 表中。
+    """
+    v3_persona_config: list[dict] = astrbot_config.get("persona", [])
+    total_personas = len(v3_persona_config)
+    logger.info(f"迁移 {total_personas} 个 Persona 配置到新表中...")
+
+    for idx, persona in enumerate(v3_persona_config):
+        if total_personas > 0 and (idx + 1) % max(1, total_personas // 10) == 0:
+            progress = int((idx + 1) / total_personas * 100)
+            if progress % 10 == 0:
+                logger.info(f"进度: {progress}% ({idx + 1}/{total_personas})")
+        try:
+            begin_dialogs = persona.get("begin_dialogs", [])
+            mood_imitation_dialogs = persona.get("mood_imitation_dialogs", [])
+            mood_prompt = ""
+            user_turn = True
+            for mood_dialog in mood_imitation_dialogs:
+                if user_turn:
+                    mood_prompt += f"A: {mood_dialog}\n"
+                else:
+                    mood_prompt += f"B: {mood_dialog}\n"
+                user_turn = not user_turn
+            system_prompt = persona.get("prompt", "")
+            if mood_prompt:
+                system_prompt += f"Here are few shots of dialogs, you need to imitate the tone of 'B' in the following dialogs to respond:\n {mood_prompt}"
+            persona_new = await db_helper.insert_persona(
+                persona_id=persona["name"],
+                system_prompt=system_prompt,
+                begin_dialogs=begin_dialogs,
+            )
+            logger.info(
+                f"迁移 Persona {persona['name']}({persona_new.system_prompt[:30]}...) 到新表成功。"
+            )
+        except Exception as e:
+            logger.error(f"解析 Persona 配置失败：{e}")
+
+
+async def migration_preferences(
+    db_helper: BaseDatabase, platform_id_map: dict[str, dict[str, str]]
+):
+    # 1. global scope migration
+    keys = [
+        "inactivated_llm_tools",
+        "inactivated_plugins",
+        "curr_provider",
+        "curr_provider_tts",
+        "curr_provider_stt",
+        "alter_cmd",
+    ]
+    for key in keys:
+        value = sp_v3.get(key)
+        if value is not None:
+            await sp.put_async("global", "global", key, value)
+            logger.info(f"迁移全局偏好设置 {key} 成功，值: {value}")
+
+    # 2. umo scope migration
+    session_conversation = sp_v3.get("session_conversation", default={})
+    for umo, conversation_id in session_conversation.items():
+        if not umo or not conversation_id:
+            continue
+        try:
+            session = MessageSesion.from_str(session_str=umo)
+            platform_id = get_platform_id(platform_id_map, session.platform_name)
+            session.platform_id = platform_id
+            await sp.put_async("umo", str(session), "sel_conv_id", conversation_id)
+            logger.info(f"迁移会话 {umo} 的对话数据到新表成功，平台 ID: {platform_id}")
+        except Exception as e:
+            logger.error(f"迁移会话 {umo} 的对话数据失败: {e}", exc_info=True)
+
+    session_service_config = sp_v3.get("session_service_config", default={})
+    for umo, config in session_service_config.items():
+        if not umo or not config:
+            continue
+        try:
+            session = MessageSesion.from_str(session_str=umo)
+            platform_id = get_platform_id(platform_id_map, session.platform_name)
+            session.platform_id = platform_id
+
+            await sp.put_async("umo", str(session), "session_service_config", config)
+
+            logger.info(f"迁移会话 {umo} 的服务配置到新表成功，平台 ID: {platform_id}")
+        except Exception as e:
+            logger.error(f"迁移会话 {umo} 的服务配置失败: {e}", exc_info=True)
+
+    session_variables = sp_v3.get("session_variables", default={})
+    for umo, variables in session_variables.items():
+        if not umo or not variables:
+            continue
+        try:
+            session = MessageSesion.from_str(session_str=umo)
+            platform_id = get_platform_id(platform_id_map, session.platform_name)
+            session.platform_id = platform_id
+            await sp.put_async("umo", str(session), "session_variables", variables)
+        except Exception as e:
+            logger.error(f"迁移会话 {umo} 的变量失败: {e}", exc_info=True)
+
+    session_provider_perf = sp_v3.get("session_provider_perf", default={})
+    for umo, perf in session_provider_perf.items():
+        if not umo or not perf:
+            continue
+        try:
+            session = MessageSesion.from_str(session_str=umo)
+            platform_id = get_platform_id(platform_id_map, session.platform_name)
+            session.platform_id = platform_id
+
+            for provider_type, provider_id in perf.items():
+                await sp.put_async(
+                    "umo", str(session), f"provider_perf_{provider_type}", provider_id
+                )
+            logger.info(
+                f"迁移会话 {umo} 的提供商偏好到新表成功，平台 ID: {platform_id}"
+            )
+        except Exception as e:
+            logger.error(f"迁移会话 {umo} 的提供商偏好失败: {e}", exc_info=True)

astrbot/core/db/migration/shared_preferences_v3.py

@@ -0,0 +1,45 @@
+import json
+import os
+from typing import TypeVar
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+
+_VT = TypeVar("_VT")
+
+class SharedPreferences:
+    def __init__(self, path=None):
+        if path is None:
+            path = os.path.join(get_astrbot_data_path(), "shared_preferences.json")
+        self.path = path
+        self._data = self._load_preferences()
+
+    def _load_preferences(self):
+        if os.path.exists(self.path):
+            try:
+                with open(self.path, "r") as f:
+                    return json.load(f)
+            except json.JSONDecodeError:
+                os.remove(self.path)
+        return {}
+
+    def _save_preferences(self):
+        with open(self.path, "w") as f:
+            json.dump(self._data, f, indent=4, ensure_ascii=False)
+            f.flush()
+
+    def get(self, key, default: _VT = None) -> _VT:
+        return self._data.get(key, default)
+
+    def put(self, key, value):
+        self._data[key] = value
+        self._save_preferences()
+
+    def remove(self, key):
+        if key in self._data:
+            del self._data[key]
+            self._save_preferences()
+
+    def clear(self):
+        self._data.clear()
+        self._save_preferences()
+
+sp = SharedPreferences()

astrbot/core/db/migration/sqlite_v3.py

@@ -0,0 +1,493 @@
+import sqlite3
+import time
+from astrbot.core.db.po import Platform, Stats
+from typing import Tuple, List, Dict, Any
+from dataclasses import dataclass
+
+@dataclass
+class Conversation:
+    """LLM 对话存储
+
+    对于网页聊天，history 存储了包括指令、回复、图片等在内的所有消息。
+    对于其他平台的聊天，不存储非 LLM 的回复（因为考虑到已经存储在各自的平台上）。
+    """
+
+    user_id: str
+    cid: str
+    history: str = ""
+    """字符串格式的列表。"""
+    created_at: int = 0
+    updated_at: int = 0
+    title: str = ""
+    persona_id: str = ""
+
+
+INIT_SQL = """
+CREATE TABLE IF NOT EXISTS platform(
+    name VARCHAR(32),
+    count INTEGER,
+    timestamp INTEGER
+);
+CREATE TABLE IF NOT EXISTS llm(
+    name VARCHAR(32),
+    count INTEGER,
+    timestamp INTEGER
+);
+CREATE TABLE IF NOT EXISTS plugin(
+    name VARCHAR(32),
+    count INTEGER,
+    timestamp INTEGER
+);
+CREATE TABLE IF NOT EXISTS command(
+    name VARCHAR(32),
+    count INTEGER,
+    timestamp INTEGER
+);
+CREATE TABLE IF NOT EXISTS llm_history(
+    provider_type VARCHAR(32),
+    session_id VARCHAR(32),
+    content TEXT
+);
+
+-- ATRI
+CREATE TABLE IF NOT EXISTS atri_vision(
+    id TEXT,
+    url_or_path TEXT,
+    caption TEXT,
+    is_meme BOOLEAN,
+    keywords TEXT,
+    platform_name VARCHAR(32),
+    session_id VARCHAR(32),
+    sender_nickname VARCHAR(32),
+    timestamp INTEGER
+);
+
+CREATE TABLE IF NOT EXISTS webchat_conversation(
+    user_id TEXT, -- 会话 id
+    cid TEXT, -- 对话 id
+    history TEXT,
+    created_at INTEGER,
+    updated_at INTEGER,
+    title TEXT,
+    persona_id TEXT
+);
+
+PRAGMA encoding = 'UTF-8';
+"""
+
+
+class SQLiteDatabase():
+    def __init__(self, db_path: str) -> None:
+        super().__init__()
+        self.db_path = db_path
+
+        sql = INIT_SQL
+
+        # 初始化数据库
+        self.conn = self._get_conn(self.db_path)
+        c = self.conn.cursor()
+        c.executescript(sql)
+        self.conn.commit()
+
+        # 检查 webchat_conversation 的 title 字段是否存在
+        c.execute(
+            """
+            PRAGMA table_info(webchat_conversation)
+            """
+        )
+        res = c.fetchall()
+        has_title = False
+        has_persona_id = False
+        for row in res:
+            if row[1] == "title":
+                has_title = True
+            if row[1] == "persona_id":
+                has_persona_id = True
+        if not has_title:
+            c.execute(
+                """
+                ALTER TABLE webchat_conversation ADD COLUMN title TEXT;
+                """
+            )
+            self.conn.commit()
+        if not has_persona_id:
+            c.execute(
+                """
+                ALTER TABLE webchat_conversation ADD COLUMN persona_id TEXT;
+                """
+            )
+            self.conn.commit()
+
+        c.close()
+
+    def _get_conn(self, db_path: str) -> sqlite3.Connection:
+        conn = sqlite3.connect(self.db_path)
+        conn.text_factory = str
+        return conn
+
+    def _exec_sql(self, sql: str, params: Tuple = None):
+        conn = self.conn
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            conn = self._get_conn(self.db_path)
+            c = conn.cursor()
+
+        if params:
+            c.execute(sql, params)
+            c.close()
+        else:
+            c.execute(sql)
+            c.close()
+
+        conn.commit()
+
+    def insert_platform_metrics(self, metrics: dict):
+        for k, v in metrics.items():
+            self._exec_sql(
+                """
+                INSERT INTO platform(name, count, timestamp) VALUES (?, ?, ?)
+                """,
+                (k, v, int(time.time())),
+            )
+
+    def insert_llm_metrics(self, metrics: dict):
+        for k, v in metrics.items():
+            self._exec_sql(
+                """
+                INSERT INTO llm(name, count, timestamp) VALUES (?, ?, ?)
+                """,
+                (k, v, int(time.time())),
+            )
+
+    def get_base_stats(self, offset_sec: int = 86400) -> Stats:
+        """获取 offset_sec 秒前到现在的基础统计数据"""
+        where_clause = f" WHERE timestamp >= {int(time.time()) - offset_sec}"
+
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        c.execute(
+            """
+            SELECT * FROM platform
+            """
+            + where_clause
+        )
+
+        platform = []
+        for row in c.fetchall():
+            platform.append(Platform(*row))
+
+        c.close()
+
+        return Stats(platform=platform)
+
+    def get_total_message_count(self) -> int:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        c.execute(
+            """
+            SELECT SUM(count) FROM platform
+            """
+        )
+        res = c.fetchone()
+        c.close()
+        return res[0]
+
+    def get_grouped_base_stats(self, offset_sec: int = 86400) -> Stats:
+        """获取 offset_sec 秒前到现在的基础统计数据(合并)"""
+        where_clause = f" WHERE timestamp >= {int(time.time()) - offset_sec}"
+
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        c.execute(
+            """
+            SELECT name, SUM(count), timestamp FROM platform
+            """
+            + where_clause
+            + " GROUP BY name"
+        )
+
+        platform = []
+        for row in c.fetchall():
+            platform.append(Platform(*row))
+
+        c.close()
+
+        return Stats(platform, [], [])
+
+    def get_conversation_by_user_id(self, user_id: str, cid: str) -> Conversation:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        c.execute(
+            """
+            SELECT * FROM webchat_conversation WHERE user_id = ? AND cid = ?
+            """,
+            (user_id, cid),
+        )
+
+        res = c.fetchone()
+        c.close()
+
+        if not res:
+            return
+
+        return Conversation(*res)
+
+    def new_conversation(self, user_id: str, cid: str):
+        history = "[]"
+        updated_at = int(time.time())
+        created_at = updated_at
+        self._exec_sql(
+            """
+            INSERT INTO webchat_conversation(user_id, cid, history, updated_at, created_at) VALUES (?, ?, ?, ?, ?)
+            """,
+            (user_id, cid, history, updated_at, created_at),
+        )
+
+    def get_conversations(self, user_id: str) -> Tuple:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        c.execute(
+            """
+            SELECT cid, created_at, updated_at, title, persona_id FROM webchat_conversation WHERE user_id = ? ORDER BY updated_at DESC
+            """,
+            (user_id,),
+        )
+
+        res = c.fetchall()
+        c.close()
+        conversations = []
+        for row in res:
+            cid = row[0]
+            created_at = row[1]
+            updated_at = row[2]
+            title = row[3]
+            persona_id = row[4]
+            conversations.append(
+                Conversation("", cid, "[]", created_at, updated_at, title, persona_id)
+            )
+        return conversations
+
+    def update_conversation(self, user_id: str, cid: str, history: str):
+        """更新对话，并且同时更新时间"""
+        updated_at = int(time.time())
+        self._exec_sql(
+            """
+            UPDATE webchat_conversation SET history = ?, updated_at = ? WHERE user_id = ? AND cid = ?
+            """,
+            (history, updated_at, user_id, cid),
+        )
+
+    def update_conversation_title(self, user_id: str, cid: str, title: str):
+        self._exec_sql(
+            """
+            UPDATE webchat_conversation SET title = ? WHERE user_id = ? AND cid = ?
+            """,
+            (title, user_id, cid),
+        )
+
+    def update_conversation_persona_id(self, user_id: str, cid: str, persona_id: str):
+        self._exec_sql(
+            """
+            UPDATE webchat_conversation SET persona_id = ? WHERE user_id = ? AND cid = ?
+            """,
+            (persona_id, user_id, cid),
+        )
+
+    def delete_conversation(self, user_id: str, cid: str):
+        self._exec_sql(
+            """
+            DELETE FROM webchat_conversation WHERE user_id = ? AND cid = ?
+            """,
+            (user_id, cid),
+        )
+
+    def get_all_conversations(
+        self, page: int = 1, page_size: int = 20
+    ) -> Tuple[List[Dict[str, Any]], int]:
+        """获取所有对话，支持分页，按更新时间降序排序"""
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        try:
+            # 获取总记录数
+            c.execute("""
+                SELECT COUNT(*) FROM webchat_conversation
+            """)
+            total_count = c.fetchone()[0]
+
+            # 计算偏移量
+            offset = (page - 1) * page_size
+
+            # 获取分页数据，按更新时间降序排序
+            c.execute(
+                """
+                SELECT user_id, cid, created_at, updated_at, title, persona_id
+                FROM webchat_conversation
+                ORDER BY updated_at DESC
+                LIMIT ? OFFSET ?
+            """,
+                (page_size, offset),
+            )
+
+            rows = c.fetchall()
+
+            conversations = []
+
+            for row in rows:
+                user_id, cid, created_at, updated_at, title, persona_id = row
+                # 确保 cid 是字符串类型且至少有8个字符，否则使用一个默认值
+                safe_cid = str(cid) if cid else "unknown"
+                display_cid = safe_cid[:8] if len(safe_cid) >= 8 else safe_cid
+
+                conversations.append(
+                    {
+                        "user_id": user_id or "",
+                        "cid": safe_cid,
+                        "title": title or f"对话 {display_cid}",
+                        "persona_id": persona_id or "",
+                        "created_at": created_at or 0,
+                        "updated_at": updated_at or 0,
+                    }
+                )
+
+            return conversations, total_count
+
+        except Exception as _:
+            # 返回空列表和0，确保即使出错也有有效的返回值
+            return [], 0
+        finally:
+            c.close()
+
+    def get_filtered_conversations(
+        self,
+        page: int = 1,
+        page_size: int = 20,
+        platforms: List[str] = None,
+        message_types: List[str] = None,
+        search_query: str = None,
+        exclude_ids: List[str] = None,
+        exclude_platforms: List[str] = None,
+    ) -> Tuple[List[Dict[str, Any]], int]:
+        """获取筛选后的对话列表"""
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+
+        try:
+            # 构建查询条件
+            where_clauses = []
+            params = []
+
+            # 平台筛选
+            if platforms and len(platforms) > 0:
+                platform_conditions = []
+                for platform in platforms:
+                    platform_conditions.append("user_id LIKE ?")
+                    params.append(f"{platform}:%")
+
+                if platform_conditions:
+                    where_clauses.append(f"({' OR '.join(platform_conditions)})")
+
+            # 消息类型筛选
+            if message_types and len(message_types) > 0:
+                message_type_conditions = []
+                for msg_type in message_types:
+                    message_type_conditions.append("user_id LIKE ?")
+                    params.append(f"%:{msg_type}:%")
+
+                if message_type_conditions:
+                    where_clauses.append(f"({' OR '.join(message_type_conditions)})")
+
+            # 搜索关键词
+            if search_query:
+                search_query = search_query.encode("unicode_escape").decode("utf-8")
+                where_clauses.append(
+                    "(title LIKE ? OR user_id LIKE ? OR cid LIKE ? OR history LIKE ?)"
+                )
+                search_param = f"%{search_query}%"
+                params.extend([search_param, search_param, search_param, search_param])
+
+            # 排除特定用户ID
+            if exclude_ids and len(exclude_ids) > 0:
+                for exclude_id in exclude_ids:
+                    where_clauses.append("user_id NOT LIKE ?")
+                    params.append(f"{exclude_id}%")
+
+            # 排除特定平台
+            if exclude_platforms and len(exclude_platforms) > 0:
+                for exclude_platform in exclude_platforms:
+                    where_clauses.append("user_id NOT LIKE ?")
+                    params.append(f"{exclude_platform}:%")
+
+            # 构建完整的 WHERE 子句
+            where_sql = " WHERE " + " AND ".join(where_clauses) if where_clauses else ""
+
+            # 构建计数查询
+            count_sql = f"SELECT COUNT(*) FROM webchat_conversation{where_sql}"
+
+            # 获取总记录数
+            c.execute(count_sql, params)
+            total_count = c.fetchone()[0]
+
+            # 计算偏移量
+            offset = (page - 1) * page_size
+
+            # 构建分页数据查询
+            data_sql = f"""
+                SELECT user_id, cid, created_at, updated_at, title, persona_id
+                FROM webchat_conversation
+                {where_sql}
+                ORDER BY updated_at DESC
+                LIMIT ? OFFSET ?
+            """
+            query_params = params + [page_size, offset]
+
+            # 获取分页数据
+            c.execute(data_sql, query_params)
+            rows = c.fetchall()
+
+            conversations = []
+
+            for row in rows:
+                user_id, cid, created_at, updated_at, title, persona_id = row
+                # 确保 cid 是字符串类型，否则使用一个默认值
+                safe_cid = str(cid) if cid else "unknown"
+                display_cid = safe_cid[:8] if len(safe_cid) >= 8 else safe_cid
+
+                conversations.append(
+                    {
+                        "user_id": user_id or "",
+                        "cid": safe_cid,
+                        "title": title or f"对话 {display_cid}",
+                        "persona_id": persona_id or "",
+                        "created_at": created_at or 0,
+                        "updated_at": updated_at or 0,
+                    }
+                )
+
+            return conversations, total_count
+
+        except Exception as _:
+            # 返回空列表和0，确保即使出错也有有效的返回值
+            return [], 0
+        finally:
+            c.close()

astrbot/core/db/po.py

@@ -1,7 +1,233 @@
-"""指标数据"""
+import uuid
 
+from datetime import datetime, timezone
 from dataclasses import dataclass, field
-from typing import List
+from sqlmodel import (
+    SQLModel,
+    Text,
+    JSON,
+    UniqueConstraint,
+    Field,
+)
+from typing import Optional, TypedDict
+
+
+class PlatformStat(SQLModel, table=True):
+    """This class represents the statistics of bot usage across different platforms.
+
+    Note: In astrbot v4, we moved `platform` table to here.
+    """
+
+    __tablename__ = "platform_stats"
+
+    id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
+    timestamp: datetime = Field(nullable=False)
+    platform_id: str = Field(nullable=False)
+    platform_type: str = Field(nullable=False)  # such as "aiocqhttp", "slack", etc.
+    count: int = Field(default=0, nullable=False)
+
+    __table_args__ = (
+        UniqueConstraint(
+            "timestamp",
+            "platform_id",
+            "platform_type",
+            name="uix_platform_stats",
+        ),
+    )
+
+
+class ConversationV2(SQLModel, table=True):
+    __tablename__ = "conversations"
+
+    inner_conversation_id: int = Field(
+        primary_key=True, sa_column_kwargs={"autoincrement": True}
+    )
+    conversation_id: str = Field(
+        max_length=36,
+        nullable=False,
+        unique=True,
+        default_factory=lambda: str(uuid.uuid4()),
+    )
+    platform_id: str = Field(nullable=False)
+    user_id: str = Field(nullable=False)
+    content: Optional[list] = Field(default=None, sa_type=JSON)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+    title: Optional[str] = Field(default=None, max_length=255)
+    persona_id: Optional[str] = Field(default=None)
+
+    __table_args__ = (
+        UniqueConstraint(
+            "conversation_id",
+            name="uix_conversation_id",
+        ),
+    )
+
+
+class Persona(SQLModel, table=True):
+    """Persona is a set of instructions for LLMs to follow.
+
+    It can be used to customize the behavior of LLMs.
+    """
+
+    __tablename__ = "personas"
+
+    id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
+    persona_id: str = Field(max_length=255, nullable=False)
+    system_prompt: str = Field(sa_type=Text, nullable=False)
+    begin_dialogs: Optional[list] = Field(default=None, sa_type=JSON)
+    """a list of strings, each representing a dialog to start with"""
+    tools: Optional[list] = Field(default=None, sa_type=JSON)
+    """None means use ALL tools for default, empty list means no tools, otherwise a list of tool names."""
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "persona_id",
+            name="uix_persona_id",
+        ),
+    )
+
+
+class Preference(SQLModel, table=True):
+    """This class represents preferences for bots."""
+
+    __tablename__ = "preferences"
+
+    id: int | None = Field(
+        default=None, primary_key=True, sa_column_kwargs={"autoincrement": True}
+    )
+    scope: str = Field(nullable=False)
+    """Scope of the preference, such as 'global', 'umo', 'plugin'."""
+    scope_id: str = Field(nullable=False)
+    """ID of the scope, such as 'global', 'umo', 'plugin_name'."""
+    key: str = Field(nullable=False)
+    value: dict = Field(sa_type=JSON, nullable=False)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "scope",
+            "scope_id",
+            "key",
+            name="uix_preference_scope_scope_id_key",
+        ),
+    )
+
+
+class PlatformMessageHistory(SQLModel, table=True):
+    """This class represents the message history for a specific platform.
+
+    It is used to store messages that are not LLM-generated, such as user messages
+    or platform-specific messages.
+    """
+
+    __tablename__ = "platform_message_history"
+
+    id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
+    platform_id: str = Field(nullable=False)
+    user_id: str = Field(nullable=False)  # An id of group, user in platform
+    sender_id: Optional[str] = Field(default=None)  # ID of the sender in the platform
+    sender_name: Optional[str] = Field(
+        default=None
+    )  # Name of the sender in the platform
+    content: dict = Field(sa_type=JSON, nullable=False)  # a message chain list
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+
+class Attachment(SQLModel, table=True):
+    """This class represents attachments for messages in AstrBot.
+
+    Attachments can be images, files, or other media types.
+    """
+
+    __tablename__ = "attachments"
+
+    inner_attachment_id: int = Field(
+        primary_key=True, sa_column_kwargs={"autoincrement": True}
+    )
+    attachment_id: str = Field(
+        max_length=36,
+        nullable=False,
+        unique=True,
+        default_factory=lambda: str(uuid.uuid4()),
+    )
+    path: str = Field(nullable=False)  # Path to the file on disk
+    type: str = Field(nullable=False)  # Type of the file (e.g., 'image', 'file')
+    mime_type: str = Field(nullable=False)  # MIME type of the file
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "attachment_id",
+            name="uix_attachment_id",
+        ),
+    )
+
+
+@dataclass
+class Conversation:
+    """LLM 对话类
+
+    对于 WebChat，history 存储了包括指令、回复、图片等在内的所有消息。
+    对于其他平台的聊天，不存储非 LLM 的回复（因为考虑到已经存储在各自的平台上）。
+
+    在 v4.0.0 版本及之后，WebChat 的历史记录被迁移至 `PlatformMessageHistory` 表中，
+    """
+
+    platform_id: str
+    user_id: str
+    cid: str
+    """对话 ID, 是 uuid 格式的字符串"""
+    history: str = ""
+    """字符串格式的对话列表。"""
+    title: str | None = ""
+    persona_id: str | None = ""
+    created_at: int = 0
+    updated_at: int = 0
+
+
+class Personality(TypedDict):
+    """LLM 人格类。
+
+    在 v4.0.0 版本及之后，推荐使用上面的 Persona 类。并且， mood_imitation_dialogs 字段已被废弃。
+    """
+
+    prompt: str = ""
+    name: str = ""
+    begin_dialogs: list[str] = []
+    mood_imitation_dialogs: list[str] = []
+    """情感模拟对话预设。在 v4.0.0 版本及之后，已被废弃。"""
+    tools: list[str] | None = None
+    """工具列表。None 表示使用所有工具，空列表表示不使用任何工具"""
+
+    # cache
+    _begin_dialogs_processed: list[dict] = []
+    _mood_imitation_dialogs_processed: str = ""
+
+
+# ====
+# Deprecated, and will be removed in future versions.
+# ====
 
 
 @dataclass
@@ -13,77 +239,6 @@ class Platform:
     timestamp: int
 
 
-@dataclass
-class Provider:
-    """供应商使用统计数据"""
-
-    name: str
-    count: int
-    timestamp: int
-
-
-@dataclass
-class Plugin:
-    """插件使用统计数据"""
-
-    name: str
-    count: int
-    timestamp: int
-
-
-@dataclass
-class Command:
-    """命令使用统计数据"""
-
-    name: str
-    count: int
-    timestamp: int
-
-
 @dataclass
 class Stats:
-    platform: List[Platform] = field(default_factory=list)
-    command: List[Command] = field(default_factory=list)
-    llm: List[Provider] = field(default_factory=list)
-
-
-@dataclass
-class LLMHistory:
-    """LLM 聊天时持久化的信息"""
-
-    provider_type: str
-    session_id: str
-    content: str
-
-
-@dataclass
-class ATRIVision:
-    """Deprecated"""
-
-    id: str
-    url_or_path: str
-    caption: str
-    is_meme: bool
-    keywords: List[str]
-    platform_name: str
-    session_id: str
-    sender_nickname: str
-    timestamp: int = -1
-
-
-@dataclass
-class Conversation:
-    """LLM 对话存储
-
-    对于网页聊天，history 存储了包括指令、回复、图片等在内的所有消息。
-    对于其他平台的聊天，不存储非 LLM 的回复（因为考虑到已经存储在各自的平台上）。
-    """
-
-    user_id: str
-    cid: str
-    history: str = ""
-    """字符串格式的列表。"""
-    created_at: int = 0
-    updated_at: int = 0
-    title: str = ""
-    persona_id: str = ""
+    platform: list[Platform] = field(default_factory=list)

astrbot/core/db/sqlite_init.sql

@@ -1,50 +0,0 @@
-CREATE TABLE IF NOT EXISTS platform(
-    name VARCHAR(32),
-    count INTEGER,
-    timestamp INTEGER
-);
-CREATE TABLE IF NOT EXISTS llm(
-    name VARCHAR(32),
-    count INTEGER,
-    timestamp INTEGER
-);
-CREATE TABLE IF NOT EXISTS plugin(
-    name VARCHAR(32),
-    count INTEGER,
-    timestamp INTEGER
-);
-CREATE TABLE IF NOT EXISTS command(
-    name VARCHAR(32),
-    count INTEGER,
-    timestamp INTEGER
-);
-CREATE TABLE IF NOT EXISTS llm_history(
-    provider_type VARCHAR(32),
-    session_id VARCHAR(32),
-    content TEXT
-);
-
--- ATRI
-CREATE TABLE IF NOT EXISTS atri_vision(
-    id TEXT,
-    url_or_path TEXT,
-    caption TEXT,
-    is_meme BOOLEAN,
-    keywords TEXT,
-    platform_name VARCHAR(32),
-    session_id VARCHAR(32),
-    sender_nickname VARCHAR(32),
-    timestamp INTEGER
-);
-
-CREATE TABLE IF NOT EXISTS webchat_conversation(
-    user_id TEXT, -- 会话 id
-    cid TEXT, -- 对话 id
-    history TEXT,
-    created_at INTEGER,
-    updated_at INTEGER,
-    title TEXT,
-    persona_id TEXT
-);
-
-PRAGMA encoding = 'UTF-8';

astrbot/core/db/vec_db/faiss_impl/vec_db.py

@@ -5,6 +5,7 @@ from .document_storage import DocumentStorage
 from .embedding_storage import EmbeddingStorage
 from ..base import Result, BaseVecDB
 from astrbot.core.provider.provider import EmbeddingProvider
+from astrbot.core.provider.provider import RerankProvider
 
 
 class FaissVecDB(BaseVecDB):
@@ -17,6 +18,7 @@ class FaissVecDB(BaseVecDB):
         doc_store_path: str,
         index_store_path: str,
         embedding_provider: EmbeddingProvider,
+        rerank_provider: RerankProvider | None = None,
     ):
         self.doc_store_path = doc_store_path
         self.index_store_path = index_store_path
@@ -26,11 +28,14 @@ class FaissVecDB(BaseVecDB):
             embedding_provider.get_dim(), index_store_path
         )
         self.embedding_provider = embedding_provider
+        self.rerank_provider = rerank_provider
 
     async def initialize(self):
         await self.document_storage.initialize()
 
-    async def insert(self, content: str, metadata: dict = None, id: str = None) -> int:
+    async def insert(
+        self, content: str, metadata: dict | None = None, id: str | None = None
+    ) -> int:
         """
         插入一条文本和其对应向量，自动生成 ID 并保持一致性。
         """
@@ -53,7 +58,12 @@ class FaissVecDB(BaseVecDB):
             return int_id
 
     async def retrieve(
-        self, query: str, k: int = 5, fetch_k: int = 20, metadata_filters: dict = None
+        self,
+        query: str,
+        k: int = 5,
+        fetch_k: int = 20,
+        rerank: bool = False,
+        metadata_filters: dict | None = None,
     ) -> list[Result]:
         """
         搜索最相似的文档。
@@ -62,6 +72,7 @@ class FaissVecDB(BaseVecDB):
             query (str): 查询文本
             k (int): 返回的最相似文档的数量
             fetch_k (int): 在根据 metadata 过滤前从 FAISS 中获取的数量
+            rerank (bool): 是否使用重排序。这需要在实例化时提供 rerank_provider, 如果未提供并且 rerank 为 True, 不会抛出异常。
             metadata_filters (dict): 元数据过滤器
 
         Returns:
@@ -72,7 +83,6 @@ class FaissVecDB(BaseVecDB):
             vector=np.array([embedding]).astype("float32"),
             k=fetch_k if metadata_filters else k,
         )
-        # TODO: rerank
         if len(indices[0]) == 0 or indices[0][0] == -1:
             return []
         # normalize scores
@@ -83,7 +93,7 @@ class FaissVecDB(BaseVecDB):
         )
         if not fetched_docs:
             return []
-        result_docs = []
+        result_docs: list[Result] = []
 
         idx_pos = {fetch_doc["id"]: idx for idx, fetch_doc in enumerate(fetched_docs)}
         for i, indice_idx in enumerate(indices[0]):
@@ -93,7 +103,20 @@ class FaissVecDB(BaseVecDB):
             fetch_doc = fetched_docs[pos]
             score = scores[0][i]
             result_docs.append(Result(similarity=float(score), data=fetch_doc))
-        return result_docs[:k]
+
+        top_k_results = result_docs[:k]
+
+        if rerank and self.rerank_provider:
+            documents = [doc.data["text"] for doc in top_k_results]
+            reranked_results = await self.rerank_provider.rerank(query, documents)
+            reranked_results = sorted(
+                reranked_results, key=lambda x: x.relevance_score, reverse=True
+            )
+            top_k_results = [
+                top_k_results[reranked_result.index] for reranked_result in reranked_results
+            ]
+
+        return top_k_results
 
     async def delete(self, doc_id: int):
         """

astrbot/core/event_bus.py

@@ -16,30 +16,32 @@ from asyncio import Queue
 from astrbot.core.pipeline.scheduler import PipelineScheduler
 from astrbot.core import logger
 from .platform import AstrMessageEvent
+from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
 
 
 class EventBus:
-    """事件总线: 用于处理事件的分发和处理
+    """用于处理事件的分发和处理"""
 
-    维护一个异步队列, 来接受各种消息事件
-    """
-
-    def __init__(self, event_queue: Queue, pipeline_scheduler: PipelineScheduler):
+    def __init__(
+        self,
+        event_queue: Queue,
+        pipeline_scheduler_mapping: dict[str, PipelineScheduler],
+        astrbot_config_mgr: AstrBotConfigManager = None,
+    ):
         self.event_queue = event_queue  # 事件队列
-        self.pipeline_scheduler = pipeline_scheduler  # 管道调度器
+        # abconf uuid -> scheduler
+        self.pipeline_scheduler_mapping = pipeline_scheduler_mapping
+        self.astrbot_config_mgr = astrbot_config_mgr
 
     async def dispatch(self):
-        """无限循环的调度函数, 从事件队列中获取新的事件, 打印日志并创建一个新的异步任务来执行管道调度器的处理逻辑"""
         while True:
-            event: AstrMessageEvent = (
-                await self.event_queue.get()
-            )  # 从事件队列中获取新的事件
-            self._print_event(event)  # 打印日志
-            asyncio.create_task(
-                self.pipeline_scheduler.execute(event)
-            )  # 创建新的异步任务来执行管道调度器的处理逻辑
+            event: AstrMessageEvent = await self.event_queue.get()
+            conf_info = self.astrbot_config_mgr.get_conf_info(event.unified_msg_origin)
+            self._print_event(event, conf_info["name"])
+            scheduler = self.pipeline_scheduler_mapping.get(conf_info["id"])
+            asyncio.create_task(scheduler.execute(event))
 
-    def _print_event(self, event: AstrMessageEvent):
+    def _print_event(self, event: AstrMessageEvent, conf_name: str):
         """用于记录事件信息
 
         Args:
@@ -48,10 +50,10 @@ class EventBus:
         # 如果有发送者名称: [平台名] 发送者名称/发送者ID: 消息概要
         if event.get_sender_name():
             logger.info(
-                f"[{event.get_platform_name()}] {event.get_sender_name()}/{event.get_sender_id()}: {event.get_message_outline()}"
+                f"[{conf_name}] [{event.get_platform_id()}({event.get_platform_name()})] {event.get_sender_name()}/{event.get_sender_id()}: {event.get_message_outline()}"
             )
         # 没有发送者名称: [平台名] 发送者ID: 消息概要
         else:
             logger.info(
-                f"[{event.get_platform_name()}] {event.get_sender_id()}: {event.get_message_outline()}"
+                f"[{conf_name}] [{event.get_platform_id()}({event.get_platform_name()})] {event.get_sender_id()}: {event.get_message_outline()}"
             )

astrbot/core/file_token_service.py

@@ -2,6 +2,8 @@ import asyncio
 import os
 import uuid
 import time
+from urllib.parse import urlparse, unquote
+import platform
 
 
 class FileTokenService:
@@ -15,7 +17,9 @@ class FileTokenService:
     async def _cleanup_expired_tokens(self):
         """清理过期的令牌"""
         now = time.time()
-        expired_tokens = [token for token, (_, expire) in self.staged_files.items() if expire < now]
+        expired_tokens = [
+            token for token, (_, expire) in self.staged_files.items() if expire < now
+        ]
         for token in expired_tokens:
             self.staged_files.pop(token, None)
 
@@ -32,15 +36,35 @@ class FileTokenService:
         Raises:
             FileNotFoundError: 当路径不存在时抛出
         """
+
+        # 处理 file:///
+        try:
+            parsed_uri = urlparse(file_path)
+            if parsed_uri.scheme == "file":
+                local_path = unquote(parsed_uri.path)
+                if platform.system() == "Windows" and local_path.startswith("/"):
+                    local_path = local_path[1:]
+            else:
+                # 如果没有 file:/// 前缀，则认为是普通路径
+                local_path = file_path
+        except Exception:
+            # 解析失败时，按原路径处理
+            local_path = file_path
+
         async with self.lock:
             await self._cleanup_expired_tokens()
 
-            if not os.path.exists(file_path):
-                raise FileNotFoundError(f"文件不存在: {file_path}")
+            if not os.path.exists(local_path):
+                raise FileNotFoundError(
+                    f"文件不存在: {local_path} (原始输入: {file_path})"
+                )
 
             file_token = str(uuid.uuid4())
-            expire_time = time.time() + (timeout if timeout is not None else self.default_timeout)
-            self.staged_files[file_token] = (file_path, expire_time)
+            expire_time = time.time() + (
+                timeout if timeout is not None else self.default_timeout
+            )
+            # 存储转换后的真实路径
+            self.staged_files[file_token] = (local_path, expire_time)
             return file_token
 
     async def handle_file(self, file_token: str) -> str:

astrbot/core/log.py

@@ -96,8 +96,6 @@ class LogBroker:
             Queue: 订阅者的队列, 可用于接收日志消息
         """
         q = Queue(maxsize=CACHED_SIZE + 10)
-        for log in self.log_cache:
-            q.put_nowait(log)
         self.subscribers.append(q)
         return q
 

astrbot/core/message/components.py

@@ -125,6 +125,8 @@ class Plain(BaseMessageComponent):
     def toDict(self):
         return {"type": "text", "data": {"text": self.text.strip()}}
 
+    async def to_dict(self):
+        return {"type": "text", "data": {"text": self.text}}
 
 class Face(BaseMessageComponent):
     type: ComponentType = "Face"
@@ -610,6 +612,10 @@ class Node(BaseMessageComponent):
                         "data": {"file": f"base64://{bs64}"},
                     }
                 )
+            elif isinstance(comp, Plain):
+                # For Plain segments, we need to handle the plain differently
+                d = await comp.to_dict()
+                data_content.append(d)
             elif isinstance(comp, File):
                 # For File segments, we need to handle the file differently
                 d = await comp.to_dict()

astrbot/core/message/message_event_result.py

@@ -24,6 +24,8 @@ class MessageChain:
 
     chain: List[BaseMessageComponent] = field(default_factory=list)
     use_t2i_: Optional[bool] = None  # None 为跟随用户设置
+    type: Optional[str] = None
+    """消息链承载的消息的类型。可选，用于让消息平台区分不同业务场景的消息链。"""
 
     def message(self, message: str):
         """添加一条文本消息到消息链 `chain` 中。
@@ -98,6 +100,15 @@ class MessageChain:
         self.chain.append(Image.fromFileSystem(path))
         return self
 
+    def base64_image(self, base64_str: str):
+        """添加一条图片消息（base64 编码字符串）到消息链 `chain` 中。
+        Example:
+
+            CommandResult().base64_image("iVBORw0KGgoAAAANSUhEUgAAAAUA...")
+        """
+        self.chain.append(Image.fromBase64(base64_str))
+        return self
+
     def use_t2i(self, use_t2i: bool):
         """设置是否使用文本转图片服务。
 
@@ -157,7 +168,7 @@ class ResultContentType(enum.Enum):
     """普通的消息结果"""
     STREAMING_RESULT = enum.auto()
     """调用 LLM 产生的流式结果"""
-    STREAMING_FINISH= enum.auto()
+    STREAMING_FINISH = enum.auto()
     """流式输出完成"""
 
 

astrbot/core/persona_mgr.py

@@ -0,0 +1,183 @@
+from astrbot.core.db import BaseDatabase
+from astrbot.core.db.po import Persona, Personality
+from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
+from astrbot.core.platform.message_session import MessageSession
+from astrbot import logger
+
+DEFAULT_PERSONALITY = Personality(
+    prompt="You are a helpful and friendly assistant.",
+    name="default",
+    begin_dialogs=[],
+    mood_imitation_dialogs=[],
+    tools=None,
+    _begin_dialogs_processed=[],
+    _mood_imitation_dialogs_processed="",
+)
+
+
+class PersonaManager:
+    def __init__(self, db_helper: BaseDatabase, acm: AstrBotConfigManager):
+        self.db = db_helper
+        self.acm = acm
+        default_ps = acm.default_conf.get("provider_settings", {})
+        self.default_persona: str = default_ps.get("default_personality", "default")
+        self.personas: list[Persona] = []
+        self.selected_default_persona: Persona | None = None
+
+        self.personas_v3: list[Personality] = []
+        self.selected_default_persona_v3: Personality | None = None
+        self.persona_v3_config: list[dict] = []
+
+    async def initialize(self):
+        self.personas = await self.get_all_personas()
+        self.get_v3_persona_data()
+        logger.info(f"已加载 {len(self.personas)} 个人格。")
+
+    async def get_persona(self, persona_id: str):
+        """获取指定 persona 的信息"""
+        persona = await self.db.get_persona_by_id(persona_id)
+        if not persona:
+            raise ValueError(f"Persona with ID {persona_id} does not exist.")
+        return persona
+
+    async def get_default_persona_v3(
+        self, umo: str | MessageSession | None = None
+    ) -> Personality:
+        """获取默认 persona"""
+        cfg = self.acm.get_conf(umo)
+        default_persona_id = cfg.get("provider_settings", {}).get(
+            "default_personality", "default"
+        )
+        if not default_persona_id or default_persona_id == "default":
+            return DEFAULT_PERSONALITY
+        try:
+            return next(p for p in self.personas_v3 if p["name"] == default_persona_id)
+        except Exception:
+            return DEFAULT_PERSONALITY
+
+    async def delete_persona(self, persona_id: str):
+        """删除指定 persona"""
+        if not await self.db.get_persona_by_id(persona_id):
+            raise ValueError(f"Persona with ID {persona_id} does not exist.")
+        await self.db.delete_persona(persona_id)
+        self.personas = [p for p in self.personas if p.persona_id != persona_id]
+        self.get_v3_persona_data()
+
+    async def update_persona(
+        self,
+        persona_id: str,
+        system_prompt: str = None,
+        begin_dialogs: list[str] = None,
+        tools: list[str] = None,
+    ):
+        """更新指定 persona 的信息。tools 参数为 None 时表示使用所有工具，空列表表示不使用任何工具"""
+        existing_persona = await self.db.get_persona_by_id(persona_id)
+        if not existing_persona:
+            raise ValueError(f"Persona with ID {persona_id} does not exist.")
+        persona = await self.db.update_persona(
+            persona_id, system_prompt, begin_dialogs, tools=tools
+        )
+        if persona:
+            for i, p in enumerate(self.personas):
+                if p.persona_id == persona_id:
+                    self.personas[i] = persona
+                    break
+        self.get_v3_persona_data()
+        return persona
+
+    async def get_all_personas(self) -> list[Persona]:
+        """获取所有 personas"""
+        return await self.db.get_personas()
+
+    async def create_persona(
+        self,
+        persona_id: str,
+        system_prompt: str,
+        begin_dialogs: list[str] = None,
+        tools: list[str] = None,
+    ) -> Persona:
+        """创建新的 persona。tools 参数为 None 时表示使用所有工具，空列表表示不使用任何工具"""
+        if await self.db.get_persona_by_id(persona_id):
+            raise ValueError(f"Persona with ID {persona_id} already exists.")
+        new_persona = await self.db.insert_persona(
+            persona_id, system_prompt, begin_dialogs, tools=tools
+        )
+        self.personas.append(new_persona)
+        self.get_v3_persona_data()
+        return new_persona
+
+    def get_v3_persona_data(
+        self,
+    ) -> tuple[list[dict], list[Personality], Personality]:
+        """获取 AstrBot <4.0.0 版本的 persona 数据。
+
+        Returns:
+            - list[dict]: 包含 persona 配置的字典列表。
+            - list[Personality]: 包含 Personality 对象的列表。
+            - Personality: 默认选择的 Personality 对象。
+        """
+        v3_persona_config = [
+            {
+                "prompt": persona.system_prompt,
+                "name": persona.persona_id,
+                "begin_dialogs": persona.begin_dialogs or [],
+                "mood_imitation_dialogs": [],  # deprecated
+                "tools": persona.tools,
+            }
+            for persona in self.personas
+        ]
+
+        personas_v3: list[Personality] = []
+        selected_default_persona: Personality | None = None
+
+        for persona_cfg in v3_persona_config:
+            begin_dialogs = persona_cfg.get("begin_dialogs", [])
+            bd_processed = []
+            if begin_dialogs:
+                if len(begin_dialogs) % 2 != 0:
+                    logger.error(
+                        f"{persona_cfg['name']} 人格情景预设对话格式不对，条数应该为偶数。"
+                    )
+                    begin_dialogs = []
+                user_turn = True
+                for dialog in begin_dialogs:
+                    bd_processed.append(
+                        {
+                            "role": "user" if user_turn else "assistant",
+                            "content": dialog,
+                            "_no_save": None,  # 不持久化到 db
+                        }
+                    )
+                    user_turn = not user_turn
+
+            try:
+                persona = Personality(
+                    **persona_cfg,
+                    _begin_dialogs_processed=bd_processed,
+                    _mood_imitation_dialogs_processed="",  # deprecated
+                )
+                if persona["name"] == self.default_persona:
+                    selected_default_persona = persona
+                personas_v3.append(persona)
+            except Exception as e:
+                logger.error(f"解析 Persona 配置失败：{e}")
+
+        if not selected_default_persona and len(personas_v3) > 0:
+            # 默认选择第一个
+            selected_default_persona = personas_v3[0]
+
+        if not selected_default_persona:
+            selected_default_persona = DEFAULT_PERSONALITY
+            personas_v3.append(selected_default_persona)
+
+        self.personas_v3 = personas_v3
+        self.selected_default_persona_v3 = selected_default_persona
+        self.persona_v3_config = v3_persona_config
+        self.selected_default_persona = Persona(
+            persona_id=selected_default_persona["name"],
+            system_prompt=selected_default_persona["prompt"],
+            begin_dialogs=selected_default_persona["begin_dialogs"],
+            tools=selected_default_persona["tools"] or None,
+        )
+
+        return v3_persona_config, personas_v3, selected_default_persona

astrbot/core/pipeline/__init__.py

@@ -1,25 +1,25 @@
 from astrbot.core.message.message_event_result import (
-    MessageEventResult,
     EventResultType,
+    MessageEventResult,
 )
 
-from .waking_check.stage import WakingCheckStage
-from .whitelist_check.stage import WhitelistCheckStage
-from .rate_limit_check.stage import RateLimitStage
 from .content_safety_check.stage import ContentSafetyCheckStage
-from .platform_compatibility.stage import PlatformCompatibilityStage
 from .preprocess_stage.stage import PreProcessStage
 from .process_stage.stage import ProcessStage
-from .result_decorate.stage import ResultDecorateStage
+from .rate_limit_check.stage import RateLimitStage
 from .respond.stage import RespondStage
+from .result_decorate.stage import ResultDecorateStage
+from .session_status_check.stage import SessionStatusCheckStage
+from .waking_check.stage import WakingCheckStage
+from .whitelist_check.stage import WhitelistCheckStage
 
 # 管道阶段顺序
 STAGES_ORDER = [
     "WakingCheckStage",  # 检查是否需要唤醒
     "WhitelistCheckStage",  # 检查是否在群聊/私聊白名单
+    "SessionStatusCheckStage",  # 检查会话是否整体启用
     "RateLimitStage",  # 检查会话是否超过频率限制
     "ContentSafetyCheckStage",  # 检查内容安全
-    "PlatformCompatibilityStage",  # 检查所有处理器的平台兼容性
     "PreProcessStage",  # 预处理
     "ProcessStage",  # 交由 Stars 处理（a.k.a 插件），或者 LLM 调用
     "ResultDecorateStage",  # 处理结果，比如添加回复前缀、t2i、转换为语音 等
@@ -29,9 +29,9 @@ STAGES_ORDER = [
 __all__ = [
     "WakingCheckStage",
     "WhitelistCheckStage",
+    "SessionStatusCheckStage",
     "RateLimitStage",
     "ContentSafetyCheckStage",
-    "PlatformCompatibilityStage",
     "PreProcessStage",
     "ProcessStage",
     "ResultDecorateStage",

astrbot/core/pipeline/context.py

@@ -1,6 +1,7 @@
 from dataclasses import dataclass
-from astrbot.core.config.astrbot_config import AstrBotConfig
+from astrbot.core.config import AstrBotConfig
 from astrbot.core.star import PluginManager
+from .context_utils import call_handler, call_event_hook
 
 
 @dataclass
@@ -9,3 +10,6 @@ class PipelineContext:
 
     astrbot_config: AstrBotConfig  # AstrBot 配置对象
     plugin_manager: PluginManager  # 插件管理器对象
+    astrbot_config_id: str
+    call_handler = call_handler
+    call_event_hook = call_event_hook

astrbot/core/pipeline/context_utils.py

@@ -0,0 +1,98 @@
+import inspect
+import traceback
+import typing as T
+from astrbot import logger
+from astrbot.core.star.star_handler import star_handlers_registry, EventType
+from astrbot.core.star.star import star_map
+from astrbot.core.message.message_event_result import MessageEventResult, CommandResult
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+
+
+async def call_handler(
+    event: AstrMessageEvent,
+    handler: T.Awaitable,
+    *args,
+    **kwargs,
+) -> T.AsyncGenerator[T.Any, None]:
+    """执行事件处理函数并处理其返回结果
+
+    该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数:
+    1. 异步生成器: 实现洋葱模型，每次 yield 都会将控制权交回上层
+    2. 协程: 执行一次并处理返回值
+
+    Args:
+        event (AstrMessageEvent): 事件对象
+        handler (Awaitable): 事件处理函数
+
+    Returns:
+        AsyncGenerator[None, None]: 异步生成器，用于在管道中传递控制流
+    """
+    ready_to_call = None  # 一个协程或者异步生成器
+
+    trace_ = None
+
+    try:
+        ready_to_call = handler(event, *args, **kwargs)
+    except TypeError:
+        logger.error("处理函数参数不匹配，请检查 handler 的定义。", exc_info=True)
+
+    if inspect.isasyncgen(ready_to_call):
+        _has_yielded = False
+        try:
+            async for ret in ready_to_call:
+                # 这里逐步执行异步生成器, 对于每个 yield 返回的 ret, 执行下面的代码
+                # 返回值只能是 MessageEventResult 或者 None（无返回值）
+                _has_yielded = True
+                if isinstance(ret, (MessageEventResult, CommandResult)):
+                    # 如果返回值是 MessageEventResult, 设置结果并继续
+                    event.set_result(ret)
+                    yield
+                else:
+                    # 如果返回值是 None, 则不设置结果并继续
+                    # 继续执行后续阶段
+                    yield ret
+            if not _has_yielded:
+                # 如果这个异步生成器没有执行到 yield 分支
+                yield
+        except Exception as e:
+            logger.error(f"Previous Error: {trace_}")
+            raise e
+    elif inspect.iscoroutine(ready_to_call):
+        # 如果只是一个协程, 直接执行
+        ret = await ready_to_call
+        if isinstance(ret, (MessageEventResult, CommandResult)):
+            event.set_result(ret)
+            yield
+        else:
+            yield ret
+
+
+async def call_event_hook(
+    event: AstrMessageEvent,
+    hook_type: EventType,
+    *args,
+    **kwargs,
+) -> bool:
+    """调用事件钩子函数
+
+    Returns:
+        bool: 如果事件被终止，返回 True
+    # """
+    handlers = star_handlers_registry.get_handlers_by_event_type(
+        hook_type, plugins_name=event.plugins_name
+    )
+    for handler in handlers:
+        try:
+            logger.debug(
+                f"hook({hook_type.name}) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
+            )
+            await handler.handler(event, *args, **kwargs)
+        except BaseException:
+            logger.error(traceback.format_exc())
+
+        if event.is_stopped():
+            logger.info(
+                f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
+            )
+
+    return event.is_stopped()

astrbot/core/pipeline/platform_compatibility/stage.py

@@ -1,56 +0,0 @@
-from ..stage import Stage, register_stage
-from ..context import PipelineContext
-from typing import Union, AsyncGenerator
-from astrbot.core.platform.astr_message_event import AstrMessageEvent
-from astrbot.core.star.star import star_map
-from astrbot.core.star.star_handler import StarHandlerMetadata
-from astrbot.core import logger
-
-
-@register_stage
-class PlatformCompatibilityStage(Stage):
-    """检查所有处理器的平台兼容性。
-
-    这个阶段会检查所有处理器是否在当前平台启用，如果未启用则设置platform_compatible属性为False。
-    """
-
-    async def initialize(self, ctx: PipelineContext) -> None:
-        """初始化平台兼容性检查阶段
-
-        Args:
-            ctx (PipelineContext): 消息管道上下文对象, 包括配置和插件管理器
-        """
-        self.ctx = ctx
-
-    async def process(
-        self, event: AstrMessageEvent
-    ) -> Union[None, AsyncGenerator[None, None]]:
-        # 获取当前平台ID
-        platform_id = event.get_platform_id()
-
-        # 获取已激活的处理器
-        activated_handlers = event.get_extra("activated_handlers")
-        if activated_handlers is None:
-            activated_handlers = []
-
-        # 标记不兼容的处理器
-        for handler in activated_handlers:
-            if not isinstance(handler, StarHandlerMetadata):
-                continue
-            # 检查处理器是否在当前平台启用
-            enabled = handler.is_enabled_for_platform(platform_id)
-            if not enabled:
-                if handler.handler_module_path in star_map:
-                    plugin_name = star_map[handler.handler_module_path].name
-                logger.debug(
-                    f"[PlatformCompatibilityStage] 插件 {plugin_name} 在平台 {platform_id} 未启用，标记处理器 {handler.handler_name} 为平台不兼容"
-                )
-                # 设置处理器为平台不兼容状态
-                # TODO: 更好的标记方式
-                handler.platform_compatible = False
-            else:
-                # 确保处理器为平台兼容状态
-                handler.platform_compatible = True
-
-        # 更新已激活的处理器列表
-        event.set_extra("activated_handlers", activated_handlers)

astrbot/core/pipeline/process_stage/method/star_request.py

@@ -2,7 +2,7 @@
 本地 Agent 模式的 AstrBot 插件调用 Stage
 """
 
-from ...context import PipelineContext
+from ...context import PipelineContext, call_handler
 from ..stage import Stage
 from typing import Dict, Any, List, AsyncGenerator, Union
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
@@ -33,16 +33,6 @@ class StarRequestSubStage(Stage):
             handlers_parsed_params = {}
 
         for handler in activated_handlers:
-            # 检查处理器是否在当前平台兼容
-            if (
-                hasattr(handler, "platform_compatible")
-                and handler.platform_compatible is False
-            ):
-                logger.debug(
-                    f"处理器 {handler.handler_name} 在当前平台不兼容，跳过执行"
-                )
-                continue
-
             params = handlers_parsed_params.get(handler.handler_full_name, {})
             try:
                 if handler.handler_module_path not in star_map:
@@ -50,7 +40,7 @@ class StarRequestSubStage(Stage):
                 logger.debug(
                     f"plugin -> {star_map.get(handler.handler_module_path).name} - {handler.handler_name}"
                 )
-                wrapper = self._call_handler(self.ctx, event, handler.handler, **params)
+                wrapper = call_handler(event, handler.handler, **params)
                 async for ret in wrapper:
                     yield ret
                 event.clear_result()  # 清除上一个 handler 的结果

astrbot/core/pipeline/respond/stage.py

@@ -13,6 +13,7 @@ from astrbot.core.message.message_event_result import BaseMessageComponent
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star import star_map
 from astrbot.core.utils.path_util import path_Mapping
+from astrbot.core.utils.session_lock import session_lock_manager
 
 
 @register_stage
@@ -127,10 +128,8 @@ class RespondStage(Stage):
             use_fallback = self.config.get("provider_settings", {}).get(
                 "streaming_segmented", False
             )
-            logger.info(f"应用流式输出({event.get_platform_name()})")
-            await event._pre_send()
+            logger.info(f"应用流式输出({event.get_platform_id()})")
             await event.send_streaming(result.async_stream, use_fallback)
-            await event._post_send()
             return
         elif len(result.chain) > 0:
             # 检查路径映射
@@ -141,14 +140,10 @@ class RespondStage(Stage):
                         component.file = path_Mapping(mappings, component.file)
                         event.get_result().chain[idx] = component
 
-            await event._pre_send()
-
             # 检查消息链是否为空
             try:
                 if await self._is_empty_message_chain(result.chain):
                     logger.info("消息为空，跳过发送阶段")
-                    event.clear_result()
-                    event.stop_event()
                     return
             except Exception as e:
                 logger.warning(f"空内容检查异常: {e}")
@@ -158,9 +153,14 @@ class RespondStage(Stage):
                 c for c in result.chain if not isinstance(c, Comp.Record)
             ]
 
-            if self.enable_seg and (
-                (self.only_llm_result and result.is_llm_result())
-                or not self.only_llm_result
+            if (
+                self.enable_seg
+                and (
+                    (self.only_llm_result and result.is_llm_result())
+                    or not self.only_llm_result
+                )
+                and event.get_platform_name()
+                not in ["qq_official", "weixin_official_account", "dingtalk"]
             ):
                 decorated_comps = []
                 if self.reply_with_mention:
@@ -176,25 +176,26 @@ class RespondStage(Stage):
                             result.chain.remove(comp)
                             break
 
-                for rcomp in record_comps:
-                    i = await self._calc_comp_interval(rcomp)
-                    await asyncio.sleep(i)
-                    try:
-                        await event.send(MessageChain([rcomp]))
-                    except Exception as e:
-                        logger.error(f"发送消息失败: {e} chain: {result.chain}")
-                        break
-
-                # 分段回复
-                for comp in non_record_comps:
-                    i = await self._calc_comp_interval(comp)
-                    await asyncio.sleep(i)
-                    try:
-                        await event.send(MessageChain([*decorated_comps, comp]))
-                        decorated_comps = []  # 清空已发送的装饰组件
-                    except Exception as e:
-                        logger.error(f"发送消息失败: {e} chain: {result.chain}")
-                        break
+                # leverage lock to guarentee the order of message sending among different events
+                async with session_lock_manager.acquire_lock(event.unified_msg_origin):
+                    for rcomp in record_comps:
+                        i = await self._calc_comp_interval(rcomp)
+                        await asyncio.sleep(i)
+                        try:
+                            await event.send(MessageChain([rcomp]))
+                        except Exception as e:
+                            logger.error(f"发送消息失败: {e} chain: {result.chain}")
+                            break
+                    # 分段回复
+                    for comp in non_record_comps:
+                        i = await self._calc_comp_interval(comp)
+                        await asyncio.sleep(i)
+                        try:
+                            await event.send(MessageChain([*decorated_comps, comp]))
+                            decorated_comps = []  # 清空已发送的装饰组件
+                        except Exception as e:
+                            logger.error(f"发送消息失败: {e} chain: {result.chain}")
+                            break
             else:
                 for rcomp in record_comps:
                     try:
@@ -208,13 +209,12 @@ class RespondStage(Stage):
                     logger.error(traceback.format_exc())
                     logger.error(f"发送消息失败: {e} chain: {result.chain}")
 
-            await event._post_send()
             logger.info(
                 f"AstrBot -> {event.get_sender_name()}/{event.get_sender_id()}: {event._outline_chain(result.chain)}"
             )
 
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnAfterMessageSentEvent, platform_id=event.get_platform_id()
+            EventType.OnAfterMessageSentEvent, plugins_name=event.plugins_name
         )
         for handler in handlers:
             try:

astrbot/core/pipeline/result_decorate/stage.py

@@ -3,11 +3,12 @@ import time
 import traceback
 from typing import AsyncGenerator, Union
 
-from astrbot.core import html_renderer, logger, file_token_service
+from astrbot.core import file_token_service, html_renderer, logger
 from astrbot.core.message.components import At, File, Image, Node, Plain, Record, Reply
 from astrbot.core.message.message_event_result import ResultContentType
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.platform.message_type import MessageType
+from astrbot.core.star.session_llm_manager import SessionServiceManager
 from astrbot.core.star.star import star_map
 from astrbot.core.star.star_handler import EventType, star_handlers_registry
 
@@ -63,9 +64,10 @@ class ResultDecorateStage(Stage):
         ]
         self.content_safe_check_stage = None
         if self.content_safe_check_reply:
-            for stage in registered_stages:
-                if stage.__class__.__name__ == "ContentSafetyCheckStage":
-                    self.content_safe_check_stage = stage
+            for stage_cls in registered_stages:
+                if stage_cls.__name__ == "ContentSafetyCheckStage":
+                    self.content_safe_check_stage = stage_cls()
+                    await self.content_safe_check_stage.initialize(ctx)
 
     async def process(
         self, event: AstrMessageEvent
@@ -97,7 +99,7 @@ class ResultDecorateStage(Stage):
 
         # 发送消息前事件钩子
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnDecoratingResultEvent, platform_id=event.get_platform_id()
+            EventType.OnDecoratingResultEvent, plugins_name=event.plugins_name
         )
         for handler in handlers:
             try:
@@ -141,7 +143,11 @@ class ResultDecorateStage(Stage):
                         break
 
             # 分段回复
-            if self.enable_segmented_reply:
+            if self.enable_segmented_reply and event.get_platform_name() not in [
+                "qq_official",
+                "weixin_official_account",
+                "dingtalk",
+            ]:
                 if (
                     self.only_llm_result and result.is_llm_result()
                 ) or not self.only_llm_result:
@@ -172,10 +178,12 @@ class ResultDecorateStage(Stage):
             tts_provider = self.ctx.plugin_manager.context.get_using_tts_provider(
                 event.unified_msg_origin
             )
+
             if (
                 self.ctx.astrbot_config["provider_tts_settings"]["enable"]
                 and result.is_llm_result()
                 and tts_provider
+                and SessionServiceManager.should_process_tts_request(event)
             ):
                 new_chain = []
                 for comp in result.chain:

astrbot/core/pipeline/scheduler.py

@@ -11,16 +11,17 @@ class PipelineScheduler:
 
     def __init__(self, context: PipelineContext):
         registered_stages.sort(
-            key=lambda x: STAGES_ORDER.index(x.__class__.__name__)
+            key=lambda x: STAGES_ORDER.index(x.__name__)
         )  # 按照顺序排序
         self.ctx = context  # 上下文对象
+        self.stages = []  # 存储阶段实例
 
     async def initialize(self):
         """初始化管道调度器时, 初始化所有阶段"""
-        for stage in registered_stages:
-            # logger.debug(f"初始化阶段 {stage.__class__ .__name__}")
-
-            await stage.initialize(self.ctx)
+        for stage_cls in registered_stages:
+            stage_instance = stage_cls()  # 创建实例
+            await stage_instance.initialize(self.ctx)
+            self.stages.append(stage_instance)
 
     async def _process_stages(self, event: AstrMessageEvent, from_stage=0):
         """依次执行各个阶段
@@ -29,9 +30,9 @@ class PipelineScheduler:
             event (AstrMessageEvent): 事件对象
             from_stage (int): 从第几个阶段开始执行, 默认从0开始
         """
-        for i in range(from_stage, len(registered_stages)):
-            stage = registered_stages[i]  # 获取当前要执行的阶段
-            # logger.debug(f"执行阶段 {stage.__class__ .__name__}")
+        for i in range(from_stage, len(self.stages)):
+            stage = self.stages[i]  # 获取当前要执行的阶段
+            # logger.debug(f"执行阶段 {stage.__class__.__name__}")
             coroutine = stage.process(
                 event
             )  # 调用阶段的process方法, 返回协程或者异步生成器
@@ -73,7 +74,7 @@ class PipelineScheduler:
         await self._process_stages(event)
 
         # 如果没有发送操作, 则发送一个空消息, 以便于后续的处理
-        if not event._has_send_oper and event.get_platform_name() == "webchat":
+        if event.get_platform_name() == "webchat":
             await event.send(None)
 
         logger.debug("pipeline 执行完毕。")

astrbot/core/pipeline/session_status_check/stage.py

@@ -0,0 +1,22 @@
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from typing import AsyncGenerator, Union
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.star.session_llm_manager import SessionServiceManager
+from astrbot.core import logger
+
+
+@register_stage
+class SessionStatusCheckStage(Stage):
+    """检查会话是否整体启用"""
+
+    async def initialize(self, ctx: PipelineContext) -> None:
+        pass
+
+    async def process(
+        self, event: AstrMessageEvent
+    ) -> Union[None, AsyncGenerator[None, None]]:
+        # 检查会话是否整体启用
+        if not SessionServiceManager.is_session_enabled(event.unified_msg_origin):
+            logger.debug(f"会话 {event.unified_msg_origin} 已被关闭，已终止事件传播。")
+            event.stop_event()

astrbot/core/pipeline/stage.py

@@ -1,19 +1,15 @@
 from __future__ import annotations
 import abc
-import inspect
-import traceback
-from astrbot.api import logger
-from typing import List, AsyncGenerator, Union, Awaitable
+from typing import List, AsyncGenerator, Union, Type
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from .context import PipelineContext
-from astrbot.core.message.message_event_result import MessageEventResult, CommandResult
 
-registered_stages: List[Stage] = []  # 维护了所有已注册的 Stage 实现类
+registered_stages: List[Type[Stage]] = []  # 维护了所有已注册的 Stage 实现类类型
 
 
 def register_stage(cls):
     """一个简单的装饰器，用于注册 pipeline 包下的 Stage 实现类"""
-    registered_stages.append(cls())
+    registered_stages.append(cls)
     return cls
 
 
@@ -41,70 +37,3 @@ class Stage(abc.ABC):
             Union[None, AsyncGenerator[None, None]]: 处理结果，可能是 None 或者异步生成器, 如果为 None 则表示不需要继续处理, 如果为异步生成器则表示需要继续处理(进入下一个阶段)
         """
         raise NotImplementedError
-
-    async def _call_handler(
-        self,
-        ctx: PipelineContext,
-        event: AstrMessageEvent,
-        handler: Awaitable,
-        *args,
-        **kwargs,
-    ) -> AsyncGenerator[None, None]:
-        """执行事件处理函数并处理其返回结果
-
-        该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数:
-        1. 异步生成器: 实现洋葱模型，每次yield都会将控制权交回上层
-        2. 协程: 执行一次并处理返回值
-
-        Args:
-            ctx (PipelineContext): 消息管道上下文对象
-            event (AstrMessageEvent): 待处理的事件对象
-            handler (Awaitable): 事件处理函数
-            *args: 传递给handler的位置参数
-            **kwargs: 传递给handler的关键字参数
-
-        Returns:
-            AsyncGenerator[None, None]: 异步生成器，用于在管道中传递控制流
-        """
-        ready_to_call = None  # 一个协程或者异步生成器(async def)
-
-        trace_ = None
-
-        try:
-            ready_to_call = handler(event, *args, **kwargs)
-        except TypeError as _:
-            # 向下兼容
-            trace_ = traceback.format_exc()
-            # 以前的handler会额外传入一个参数, 但是context对象实际上在插件实例中有一份
-            ready_to_call = handler(event, ctx.plugin_manager.context, *args, **kwargs)
-
-        if isinstance(ready_to_call, AsyncGenerator):
-            # 如果是一个异步生成器, 进入洋葱模型
-            _has_yielded = False  # 是否返回过值
-            try:
-                async for ret in ready_to_call:
-                    # 这里逐步执行异步生成器, 对于每个yield返回的ret, 执行下面的代码
-                    # 返回值只能是 MessageEventResult 或者 None（无返回值）
-                    _has_yielded = True
-                    if isinstance(ret, (MessageEventResult, CommandResult)):
-                        # 如果返回值是 MessageEventResult, 设置结果并继续
-                        event.set_result(ret)
-                        yield  # 传递控制权给上一层的process函数
-                    else:
-                        # 如果返回值是 None, 则不设置结果并继续
-                        # 继续执行后续阶段
-                        yield ret  # 传递控制权给上一层的process函数
-                if not _has_yielded:
-                    # 如果这个异步生成器没有执行到yield分支
-                    yield
-            except Exception as e:
-                logger.error(f"Previous Error: {trace_}")
-                raise e
-        elif inspect.iscoroutine(ready_to_call):
-            # 如果只是一个协程, 直接执行
-            ret = await ready_to_call
-            if isinstance(ret, (MessageEventResult, CommandResult)):
-                event.set_result(ret)
-                yield  # 传递控制权给上一层的process函数
-            else:
-                yield ret  # 传递控制权给上一层的process函数

astrbot/core/pipeline/waking_check/stage.py

@@ -1,13 +1,16 @@
-from ..stage import Stage, register_stage
-from ..context import PipelineContext
+from typing import AsyncGenerator, Union
+
 from astrbot import logger
-from typing import Union, AsyncGenerator
-from astrbot.core.platform.astr_message_event import AstrMessageEvent
-from astrbot.core.message.message_event_result import MessageEventResult, MessageChain
 from astrbot.core.message.components import At, AtAll, Reply
-from astrbot.core.star.star_handler import star_handlers_registry, EventType
-from astrbot.core.star.star import star_map
+from astrbot.core.message.message_event_result import MessageChain, MessageEventResult
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.star.filter.permission import PermissionTypeFilter
+from astrbot.core.star.session_plugin_manager import SessionPluginManager
+from astrbot.core.star.star import star_map
+from astrbot.core.star.star_handler import EventType, star_handlers_registry
+
+from ..context import PipelineContext
+from ..stage import Stage, register_stage
 
 
 @register_stage
@@ -109,8 +112,17 @@ class WakingCheckStage(Stage):
         activated_handlers = []
         handlers_parsed_params = {}  # 注册了指令的 handler
 
+        # 将 plugins_name 设置到 event 中
+        enabled_plugins_name = self.ctx.astrbot_config.get("plugin_set", ["*"])
+        if enabled_plugins_name == ["*"]:
+            # 如果是 *，则表示所有插件都启用
+            event.plugins_name = None
+        else:
+            event.plugins_name = enabled_plugins_name
+        logger.debug(f"enabled_plugins_name: {enabled_plugins_name}")
+
         for handler in star_handlers_registry.get_handlers_by_event_type(
-            EventType.AdapterMessageEvent
+            EventType.AdapterMessageEvent, plugins_name=event.plugins_name
         ):
             # filter 需满足 AND 逻辑关系
             passed = True
@@ -135,7 +147,6 @@ class WakingCheckStage(Stage):
                             f"插件 {star_map[handler.handler_module_path].name}: {e}"
                         )
                     )
-                    await event._post_send()
                     event.stop_event()
                     passed = False
                     break
@@ -150,7 +161,6 @@ class WakingCheckStage(Stage):
                                 f"您(ID: {event.get_sender_id()})的权限不足以使用此指令。通过 /sid 获取 ID 并请管理员添加。"
                             )
                         )
-                        await event._post_send()
                     logger.info(
                         f"触发 {star_map[handler.handler_module_path].name} 时, 用户(ID={event.get_sender_id()}) 权限不足。"
                     )
@@ -166,7 +176,12 @@ class WakingCheckStage(Stage):
                         "parsed_params"
                     )
 
-            event.clear_extra()
+            event._extras.pop("parsed_params", None)
+
+        # 根据会话配置过滤插件处理器
+        activated_handlers = SessionPluginManager.filter_handlers_by_session(
+            event, activated_handlers
+        )
 
         event.set_extra("activated_handlers", activated_handlers)
         event.set_extra("handlers_parsed_params", handlers_parsed_params)

astrbot/core/platform/astr_message_event.py

@@ -3,9 +3,10 @@ import asyncio
 import re
 import hashlib
 import uuid
-from dataclasses import dataclass
+
 from typing import List, Union, Optional, AsyncGenerator
 
+from astrbot import logger
 from astrbot.core.db.po import Conversation
 from astrbot.core.message.components import (
     Plain,
@@ -23,21 +24,7 @@ from astrbot.core.provider.entities import ProviderRequest
 from astrbot.core.utils.metrics import Metric
 from .astrbot_message import AstrBotMessage, Group
 from .platform_metadata import PlatformMetadata
-
-
-@dataclass
-class MessageSesion:
-    platform_name: str
-    message_type: MessageType
-    session_id: str
-
-    def __str__(self):
-        return f"{self.platform_name}:{self.message_type.value}:{self.session_id}"
-
-    @staticmethod
-    def from_str(session_str: str):
-        platform_name, message_type, session_id = session_str.split(":")
-        return MessageSesion(platform_name, MessageType(message_type), session_id)
+from .message_session import MessageSession, MessageSesion # noqa
 
 
 class AstrMessageEvent(abc.ABC):
@@ -64,7 +51,7 @@ class AstrMessageEvent(abc.ABC):
         """是否是 At 机器人或者带有唤醒词或者是私聊(插件注册的事件监听器会让 is_wake 设为 True, 但是不会让这个属性置为 True)"""
         self._extras = {}
         self.session = MessageSesion(
-            platform_name=platform_meta.name,
+            platform_name=platform_meta.id,
             message_type=message_obj.type,
             session_id=session_id,
         )
@@ -78,13 +65,23 @@ class AstrMessageEvent(abc.ABC):
         self.call_llm = False
         """是否在此消息事件中禁止默认的 LLM 请求"""
 
+        self.plugins_name: list[str] | None = None
+        """该事件启用的插件名称列表。None 表示所有插件都启用。空列表表示没有启用任何插件。"""
+
         # back_compability
         self.platform = platform_meta
 
     def get_platform_name(self):
+        """获取这个事件所属的平台的类型（如 aiocqhttp, slack, discord 等）。
+
+        NOTE: 用户可能会同时运行多个相同类型的平台适配器。"""
         return self.platform_meta.name
 
     def get_platform_id(self):
+        """获取这个事件所属的平台的 ID。
+
+        NOTE: 用户可能会同时运行多个相同类型的平台适配器，但能确定的是 ID 是唯一的。
+        """
         return self.platform_meta.id
 
     def get_message_str(self) -> str:
@@ -188,6 +185,7 @@ class AstrMessageEvent(abc.ABC):
         """
         清除额外的信息。
         """
+        logger.info(f"清除 {self.get_platform_name()} 的额外信息: {self._extras}")
         self._extras.clear()
 
     def is_private_chat(self) -> bool:
@@ -227,7 +225,7 @@ class AstrMessageEvent(abc.ABC):
     ):
         """发送流式消息到消息平台，使用异步生成器。
         目前仅支持: telegram，qq official 私聊。
-        Fallback仅支持 aiocqhttp, gewechat。
+        Fallback仅支持 aiocqhttp。
         """
         asyncio.create_task(
             Metric.upload(msg_event_tick=1, adapter_name=self.platform_meta.name)
@@ -235,10 +233,10 @@ class AstrMessageEvent(abc.ABC):
         self._has_send_oper = True
 
     async def _pre_send(self):
-        """调度器会在执行 send() 前调用该方法"""
+        """调度器会在执行 send() 前调用该方法 deprecated in v3.5.18"""
 
     async def _post_send(self):
-        """调度器会在执行 send() 后调用该方法"""
+        """调度器会在执行 send() 后调用该方法 deprecated in v3.5.18"""
 
     def set_result(self, result: Union[MessageEventResult, str]):
         """设置消息事件的结果。
@@ -419,7 +417,6 @@ class AstrMessageEvent(abc.ABC):
 
         适配情况:
 
-        - gewechat
         - aiocqhttp(OneBotv11)
         """
         ...

astrbot/core/platform/manager.py

@@ -18,6 +18,9 @@ class PlatformManager:
 
         self.platforms_config = config["platform"]
         self.settings = config["platform_settings"]
+        """NOTE: 这里是 default 的配置文件，以保证最大的兼容性；
+        这个配置中的 unique_session 需要特殊处理，
+        约定整个项目中对 unique_session 的引用都从 default 的配置中获取"""
         self.event_queue = event_queue
 
     async def initialize(self):
@@ -58,10 +61,6 @@ class PlatformManager:
                     from .sources.qqofficial_webhook.qo_webhook_adapter import (
                         QQOfficialWebhookPlatformAdapter,  # noqa: F401
                     )
-                case "gewechat":
-                    from .sources.gewechat.gewechat_platform_adapter import (
-                        GewechatPlatformAdapter,  # noqa: F401
-                    )
                 case "wechatpadpro":
                     from .sources.wechatpadpro.wechatpadpro_adapter import (
                         WeChatPadProAdapter,  # noqa: F401

astrbot/core/platform/message_session.py

@@ -0,0 +1,28 @@
+from astrbot.core.platform.message_type import MessageType
+from dataclasses import dataclass
+
+
+@dataclass
+class MessageSession:
+    """描述一条消息在 AstrBot 中对应的会话的唯一标识。
+    如果您需要实例化 MessageSession，请不要给 platform_id 赋值（或者同时给 platform_name 和 platform_id 赋值相同值）。它会在 __post_init__ 中自动设置为 platform_name 的值。"""
+
+    platform_name: str
+    """平台适配器实例的唯一标识符。自 AstrBot v4.0.0 起，该字段实际为 platform_id。"""
+    message_type: MessageType
+    session_id: str
+    platform_id: str = None
+
+    def __str__(self):
+        return f"{self.platform_id}:{self.message_type.value}:{self.session_id}"
+
+    def __post_init__(self):
+        self.platform_id = self.platform_name
+
+    @staticmethod
+    def from_str(session_str: str):
+        platform_id, message_type, session_id = session_str.split(":")
+        return MessageSession(platform_id, MessageType(message_type), session_id)
+
+
+MessageSesion = MessageSession  # back compatibility

astrbot/core/platform/platform.py

@@ -5,7 +5,7 @@ from asyncio import Queue
 from .platform_metadata import PlatformMetadata
 from .astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import MessageChain
-from .astr_message_event import MessageSesion
+from .message_session import MessageSesion
 from astrbot.core.utils.metrics import Metric
 
 

astrbot/core/platform/platform_metadata.py

@@ -4,7 +4,7 @@ from dataclasses import dataclass
 @dataclass
 class PlatformMetadata:
     name: str
-    """平台的名称"""
+    """平台的名称，即平台的类型，如 aiocqhttp, discord, slack"""
     description: str
     """平台的描述"""
     id: str = None

astrbot/core/platform/sources/aiocqhttp/aiocqhttp_message_event.py

@@ -1,7 +1,7 @@
 import asyncio
 import re
 from typing import AsyncGenerator, Dict, List
-from aiocqhttp import CQHttp
+from aiocqhttp import CQHttp, Event
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.message_components import (
     Image,
@@ -58,50 +58,85 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
             ret.append(d)
         return ret
 
-    async def send(self, message: MessageChain):
+    @classmethod
+    async def _dispatch_send(
+        cls,
+        bot: CQHttp,
+        event: Event | None,
+        is_group: bool,
+        session_id: str,
+        messages: list[dict],
+    ):
+        if event:
+            await bot.send(event=event, message=messages)
+        elif is_group:
+            await bot.send_group_msg(group_id=session_id, message=messages)
+        else:
+            await bot.send_private_msg(user_id=session_id, message=messages)
+
+    @classmethod
+    async def send_message(
+        cls,
+        bot: CQHttp,
+        message_chain: MessageChain,
+        event: Event | None = None,
+        is_group: bool = False,
+        session_id: str = None,
+    ):
+        """发送消息"""
+
         # 转发消息、文件消息不能和普通消息混在一起发送
         send_one_by_one = any(
-            isinstance(seg, (Node, Nodes, File)) for seg in message.chain
+            isinstance(seg, (Node, Nodes, File)) for seg in message_chain.chain
         )
-        if send_one_by_one:
-            for seg in message.chain:
-                if isinstance(seg, (Node, Nodes)):
-                    # 合并转发消息
-
-                    if isinstance(seg, Node):
-                        nodes = Nodes([seg])
-                        seg = nodes
-
-                    payload = await seg.to_dict()
-
-                    if self.get_group_id():
-                        payload["group_id"] = self.get_group_id()
-                        await self.bot.call_action("send_group_forward_msg", **payload)
-                    else:
-                        payload["user_id"] = self.get_sender_id()
-                        await self.bot.call_action(
-                            "send_private_forward_msg", **payload
-                        )
-                elif isinstance(seg, File):
-                    d = await AiocqhttpMessageEvent._from_segment_to_dict(seg)
-                    await self.bot.send(
-                        self.message_obj.raw_message,
-                        [d],
-                    )
-                else:
-                    await self.bot.send(
-                        self.message_obj.raw_message,
-                        await AiocqhttpMessageEvent._parse_onebot_json(
-                            MessageChain([seg])
-                        ),
-                    )
-                    await asyncio.sleep(0.5)
-        else:
-            ret = await AiocqhttpMessageEvent._parse_onebot_json(message)
+        if not send_one_by_one:
+            ret = await cls._parse_onebot_json(message_chain)
             if not ret:
                 return
-            await self.bot.send(self.message_obj.raw_message, ret)
+            await cls._dispatch_send(bot, event, is_group, session_id, ret)
+            return
+        for seg in message_chain.chain:
+            if isinstance(seg, (Node, Nodes)):
+                # 合并转发消息
+                if isinstance(seg, Node):
+                    nodes = Nodes([seg])
+                    seg = nodes
 
+                payload = await seg.to_dict()
+
+                if is_group:
+                    payload["group_id"] = session_id
+                    await bot.call_action("send_group_forward_msg", **payload)
+                else:
+                    payload["user_id"] = session_id
+                    await bot.call_action("send_private_forward_msg", **payload)
+            elif isinstance(seg, File):
+                d = await cls._from_segment_to_dict(seg)
+                await cls._dispatch_send(bot, event, is_group, session_id, [d])
+            else:
+                messages = await cls._parse_onebot_json(MessageChain([seg]))
+                if not messages:
+                    continue
+                await cls._dispatch_send(bot, event, is_group, session_id, messages)
+                await asyncio.sleep(0.5)
+
+    async def send(self, message: MessageChain):
+        """发送消息"""
+        event = self.message_obj.raw_message
+        assert isinstance(event, Event), "Event must be an instance of aiocqhttp.Event"
+        is_group = False
+        if self.get_group_id():
+            is_group = True
+            session_id = self.get_group_id()
+        else:
+            session_id = self.get_sender_id()
+        await self.send_message(
+            bot=self.bot,
+            message_chain=message,
+            event=event,
+            is_group=is_group,
+            session_id=session_id,
+        )
         await super().send(message)
 
     async def send_streaming(

astrbot/core/platform/sources/aiocqhttp/aiocqhttp_platform_adapter.py

@@ -83,19 +83,18 @@ class AiocqhttpAdapter(Platform):
     async def send_by_session(
         self, session: MessageSesion, message_chain: MessageChain
     ):
-        ret = await AiocqhttpMessageEvent._parse_onebot_json(message_chain)
-        match session.message_type.value:
-            case MessageType.GROUP_MESSAGE.value:
-                if "_" in session.session_id:
-                    # 独立会话
-                    _, group_id = session.session_id.split("_")
-                    await self.bot.send_group_msg(group_id=group_id, message=ret)
-                else:
-                    await self.bot.send_group_msg(
-                        group_id=session.session_id, message=ret
-                    )
-            case MessageType.FRIEND_MESSAGE.value:
-                await self.bot.send_private_msg(user_id=session.session_id, message=ret)
+        is_group = session.message_type == MessageType.GROUP_MESSAGE
+        if is_group:
+            session_id = session.session_id.split("_")[-1]
+        else:
+            session_id = session.session_id
+        await AiocqhttpMessageEvent.send_message(
+            bot=self.bot,
+            message_chain=message_chain,
+            event=None,  # 这里不需要 event，因为是通过 session 发送的
+            is_group=is_group,
+            session_id=session_id,
+        )
         await super().send_by_session(session, message_chain)
 
     async def convert_message(self, event: Event) -> AstrBotMessage:
@@ -168,9 +167,7 @@ class AiocqhttpAdapter(Platform):
 
         if "sub_type" in event:
             if event["sub_type"] == "poke" and "target_id" in event:
-                abm.message.append(
-                    Poke(qq=str(event["target_id"]), type="poke")
-                )  # noqa: F405
+                abm.message.append(Poke(qq=str(event["target_id"]), type="poke"))  # noqa: F405
 
         return abm
 
@@ -273,8 +270,16 @@ class AiocqhttpAdapter(Platform):
                                 action="get_msg",
                                 message_id=int(m["data"]["id"]),
                             )
+                            # 添加必要的 post_type 字段，防止 Event.from_payload 报错
+                            reply_event_data["post_type"] = "message"
+                            new_event = Event.from_payload(reply_event_data)
+                            if not new_event:
+                                logger.error(
+                                    f"无法从回复消息数据构造 Event 对象: {reply_event_data}"
+                                )
+                                continue
                             abm_reply = await self._convert_handle_message_event(
-                                Event.from_payload(reply_event_data), get_reply=False
+                                new_event, get_reply=False
                             )
 
                             reply_seg = Reply(
@@ -307,7 +312,9 @@ class AiocqhttpAdapter(Platform):
                             user_id=int(m["data"]["qq"]),
                         )
                         if at_info:
-                            nickname = at_info.get("nick", "")
+                            nickname = at_info.get("nick", "") or at_info.get(
+                                "nickname", ""
+                            )
                             is_at_self = str(m["data"]["qq"]) in {abm.self_id, "all"}
 
                             abm.message.append(
@@ -322,7 +329,7 @@ class AiocqhttpAdapter(Platform):
                                 first_at_self_processed = True
                             else:
                                 # 非第一个@机器人或@其他用户，添加到message_str
-                                message_str += f" @{nickname} "
+                                message_str += f" @{nickname}({m['data']['qq']}) "
                         else:
                             abm.message.append(At(qq=str(m["data"]["qq"]), name=""))
                     except ActionFailed as e:

astrbot/core/platform/sources/dingtalk/dingtalk_event.py

@@ -26,7 +26,7 @@ class DingtalkMessageEvent(AstrMessageEvent):
                 await asyncio.get_event_loop().run_in_executor(
                     None,
                     client.reply_markdown,
-                    "AstrBot",
+                    segment.text,
                     segment.text,
                     self.message_obj.raw_message,
                 )

astrbot/core/platform/sources/discord/discord_platform_adapter.py

@@ -46,6 +46,8 @@ class DiscordPlatformAdapter(Platform):
         self.enable_command_register = self.config.get("discord_command_register", True)
         self.guild_id = self.config.get("discord_guild_id_for_debug", None)
         self.activity_name = self.config.get("discord_activity_name", None)
+        self.shutdown_event = asyncio.Event()
+        self._polling_task = None
 
     @override
     async def send_by_session(
@@ -137,7 +139,8 @@ class DiscordPlatformAdapter(Platform):
         self.client.on_ready_once_callback = callback
 
         try:
-            await self.client.start_polling()
+            self._polling_task = asyncio.create_task(self.client.start_polling())
+            await self.shutdown_event.wait()
         except discord.errors.LoginFailure:
             logger.error("[Discord] 登录失败。请检查你的 Bot Token 是否正确。")
         except discord.errors.ConnectionClosed:
@@ -162,42 +165,47 @@ class DiscordPlatformAdapter(Platform):
     def _convert_message_to_abm(self, data: dict) -> AstrBotMessage:
         """将普通消息转换为 AstrBotMessage"""
         message: discord.Message = data["message"]
-        is_mentioned = data.get("is_mentioned", False)
 
         content = message.content
 
         # 如果机器人被@，移除@部分
-        if (
-            is_mentioned
-            and self.client
-            and self.client.user
-            and self.client.user in message.mentions
-        ):
-            # 构建机器人的@字符串，格式为 <@USER_ID> 或 <@!USER_ID>
+        # 剥离 User Mention (<@id>, <@!id>)
+        if self.client and self.client.user:
             mention_str = f"<@{self.client.user.id}>"
-            mention_str_nickname = (
-                f"<@!{self.client.user.id}>"  # 有些客户端会使用带!的格式
-            )
-
+            mention_str_nickname = f"<@!{self.client.user.id}>"
             if content.startswith(mention_str):
                 content = content[len(mention_str) :].lstrip()
             elif content.startswith(mention_str_nickname):
                 content = content[len(mention_str_nickname) :].lstrip()
 
-        abm = AstrBotMessage()
+        # 剥离 Role Mention（bot 拥有的任一角色被提及，<@&role_id>）
+        if (
+            hasattr(message, "role_mentions")
+            and hasattr(message, "guild")
+            and message.guild
+        ):
+            bot_member = (
+                message.guild.get_member(self.client.user.id)
+                if self.client and self.client.user
+                else None
+            )
+            if bot_member and hasattr(bot_member, "roles"):
+                for role in bot_member.roles:
+                    role_mention_str = f"<@&{role.id}>"
+                    if content.startswith(role_mention_str):
+                        content = content[len(role_mention_str) :].lstrip()
+                        break  # 只剥离第一个匹配的角色 mention
 
+        abm = AstrBotMessage()
         abm.type = self._get_message_type(message.channel)
         abm.group_id = self._get_channel_id(message.channel)
-
         abm.message_str = content
         abm.sender = MessageMember(
             user_id=str(message.author.id), nickname=message.author.display_name
         )
-
         message_chain = []
         if abm.message_str:
             message_chain.append(Plain(text=abm.message_str))
-
         if message.attachments:
             for attachment in message.attachments:
                 if attachment.content_type and attachment.content_type.startswith(
@@ -210,7 +218,6 @@ class DiscordPlatformAdapter(Platform):
                     message_chain.append(
                         File(name=attachment.filename, url=attachment.url)
                     )
-
         abm.message = message_chain
         abm.raw_message = message
         abm.self_id = self.client_self_id
@@ -237,13 +244,35 @@ class DiscordPlatformAdapter(Platform):
         # 检查是否为斜杠指令
         is_slash_command = message_event.interaction_followup_webhook is not None
 
-        # 检查是否被@
-        is_mention = (
+        # 检查是否被@（User Mention 或 Bot 拥有的 Role Mention）
+        is_mention = False
+        # User Mention
+        if (
             self.client
             and self.client.user
             and hasattr(message.raw_message, "mentions")
-            and self.client.user in message.raw_message.mentions
-        )
+        ):
+            if self.client.user in message.raw_message.mentions:
+                is_mention = True
+        # Role Mention（Bot 拥有的角色被提及）
+        if not is_mention and hasattr(message.raw_message, "role_mentions"):
+            bot_member = None
+            if hasattr(message.raw_message, "guild") and message.raw_message.guild:
+                try:
+                    bot_member = message.raw_message.guild.get_member(
+                        self.client.user.id
+                    )
+                except Exception:
+                    bot_member = None
+            if bot_member and hasattr(bot_member, "roles"):
+                bot_roles = set(bot_member.roles)
+                mentioned_roles = set(message.raw_message.role_mentions)
+                if (
+                    bot_roles
+                    and mentioned_roles
+                    and bot_roles.intersection(mentioned_roles)
+                ):
+                    is_mention = True
 
         # 如果是斜杠指令或被@的消息，设置为唤醒状态
         if is_slash_command or is_mention:
@@ -255,23 +284,37 @@ class DiscordPlatformAdapter(Platform):
     @override
     async def terminate(self):
         """终止适配器"""
-        logger.info("[Discord] 正在终止适配器...")
-
+        logger.info("[Discord] 正在终止适配器... (step 1: cancel polling task)")
+        self.shutdown_event.set()
+        # 优先 cancel polling_task
+        if self._polling_task:
+            self._polling_task.cancel()
+            try:
+                await asyncio.wait_for(self._polling_task, timeout=10)
+            except asyncio.CancelledError:
+                logger.info("[Discord] polling_task 已取消。")
+            except Exception as e:
+                logger.warning(f"[Discord] polling_task 取消异常: {e}")
+        logger.info("[Discord] 正在清理已注册的斜杠指令... (step 2)")
         # 清理指令
         if self.enable_command_register and self.client:
-            logger.info("[Discord] 正在清理已注册的斜杠指令...")
             try:
-                # 传入空的列表来清除所有全局指令
-                # 如果指定了 guild_id，则只清除该服务器的指令
-                await self.client.sync_commands(
-                    commands=[], guild_ids=[self.guild_id] if self.guild_id else None
+                await asyncio.wait_for(
+                    self.client.sync_commands(
+                        commands=[],
+                        guild_ids=[self.guild_id] if self.guild_id else None,
+                    ),
+                    timeout=10,
                 )
                 logger.info("[Discord] 指令清理完成。")
             except Exception as e:
                 logger.error(f"[Discord] 清理指令时发生错误: {e}", exc_info=True)
-
+        logger.info("[Discord] 正在关闭 Discord 客户端... (step 3)")
         if self.client and hasattr(self.client, "close"):
-            await self.client.close()
+            try:
+                await asyncio.wait_for(self.client.close(), timeout=10)
+            except Exception as e:
+                logger.warning(f"[Discord] 客户端关闭异常: {e}")
         logger.info("[Discord] 适配器已终止。")
 
     def register_handler(self, handler_info):

astrbot/core/platform/sources/gewechat/client.py

@@ -1,812 +0,0 @@
-import asyncio
-import base64
-import datetime
-import os
-import re
-import uuid
-import threading
-
-import aiohttp
-import anyio
-import quart
-
-from astrbot.api import logger, sp
-from astrbot.api.message_components import Plain, Image, At, Record, Video
-from astrbot.api.platform import AstrBotMessage, MessageMember, MessageType
-from astrbot.core.utils.io import download_image_by_url
-from .downloader import GeweDownloader
-from astrbot.core.utils.astrbot_path import get_astrbot_data_path
-
-try:
-    from .xml_data_parser import GeweDataParser
-except (ImportError, ModuleNotFoundError) as e:
-    logger.warning(
-        f"警告: 可能未安装 defusedxml 依赖库，将导致无法解析微信的 表情包、引用 类型的消息: {str(e)}"
-    )
-
-
-class SimpleGewechatClient:
-    """针对 Gewechat 的简单实现。
-
-    @author: Soulter
-    @website: https://github.com/Soulter
-    """
-
-    def __init__(
-        self,
-        base_url: str,
-        nickname: str,
-        host: str,
-        port: int,
-        event_queue: asyncio.Queue,
-    ):
-        self.base_url = base_url
-        if self.base_url.endswith("/"):
-            self.base_url = self.base_url[:-1]
-
-        self.download_base_url = self.base_url.split(":")[:-1]  # 去掉端口
-        self.download_base_url = ":".join(self.download_base_url) + ":2532/download/"
-
-        self.base_url += "/v2/api"
-
-        logger.info(f"Gewechat API: {self.base_url}")
-        logger.info(f"Gewechat 下载 API: {self.download_base_url}")
-
-        if isinstance(port, str):
-            port = int(port)
-
-        self.token = None
-        self.headers = {}
-        self.nickname = nickname
-        self.appid = sp.get(f"gewechat-appid-{nickname}", "")
-
-        self.server = quart.Quart(__name__)
-        self.server.add_url_rule(
-            "/astrbot-gewechat/callback", view_func=self._callback, methods=["POST"]
-        )
-        self.server.add_url_rule(
-            "/astrbot-gewechat/file/<file_token>",
-            view_func=self._handle_file,
-            methods=["GET"],
-        )
-
-        self.host = host
-        self.port = port
-        self.callback_url = f"http://{self.host}:{self.port}/astrbot-gewechat/callback"
-        self.file_server_url = f"http://{self.host}:{self.port}/astrbot-gewechat/file"
-
-        self.event_queue = event_queue
-
-        self.multimedia_downloader = None
-
-        self.userrealnames = {}
-
-        self.shutdown_event = asyncio.Event()
-
-        self.staged_files = {}
-        """存储了允许外部访问的文件列表。auth_token: file_path。通过 register_file 方法注册。"""
-
-        self.lock = asyncio.Lock()
-
-    async def get_token_id(self):
-        """获取 Gewechat Token。"""
-        async with aiohttp.ClientSession() as session:
-            async with session.post(f"{self.base_url}/tools/getTokenId") as resp:
-                json_blob = await resp.json()
-                self.token = json_blob["data"]
-                logger.info(f"获取到 Gewechat Token: {self.token}")
-                self.headers = {"X-GEWE-TOKEN": self.token}
-
-    async def _convert(self, data: dict) -> AstrBotMessage:
-        if "TypeName" in data:
-            type_name = data["TypeName"]
-        elif "type_name" in data:
-            type_name = data["type_name"]
-        else:
-            raise Exception("无法识别的消息类型")
-
-        # 以下没有业务处理，只是避免控制台打印太多的日志
-        if type_name == "ModContacts":
-            logger.info("gewechat下发：ModContacts消息通知。")
-            return
-        if type_name == "DelContacts":
-            logger.info("gewechat下发：DelContacts消息通知。")
-            return
-
-        if type_name == "Offline":
-            logger.critical("收到 gewechat 下线通知。")
-            return
-
-        d = None
-        if "Data" in data:
-            d = data["Data"]
-        elif "data" in data:
-            d = data["data"]
-
-        if not d:
-            logger.warning(f"消息不含 data 字段: {data}")
-            return
-
-        if "CreateTime" in d:
-            # 得到系统 UTF+8 的 ts
-            tz_offset = datetime.timedelta(hours=8)
-            tz = datetime.timezone(tz_offset)
-            ts = datetime.datetime.now(tz).timestamp()
-            create_time = d["CreateTime"]
-            if create_time < ts - 30:
-                logger.warning(f"消息时间戳过旧: {create_time}，当前时间戳: {ts}")
-                return
-
-        abm = AstrBotMessage()
-
-        from_user_name = d["FromUserName"]["string"]  # 消息来源
-        d["to_wxid"] = from_user_name  # 用于发信息
-
-        abm.message_id = str(d.get("MsgId"))
-        abm.session_id = from_user_name
-        abm.self_id = data["Wxid"]  # 机器人的 wxid
-
-        user_id = ""  # 发送人 wxid
-        content = d["Content"]["string"]  # 消息内容
-
-        at_me = False
-        at_wxids = []
-        if "@chatroom" in from_user_name:
-            abm.type = MessageType.GROUP_MESSAGE
-            _t = content.split(":\n")
-            user_id = _t[0]
-            content = _t[1]
-            # at
-            msg_source = d["MsgSource"]
-            if "\u2005" in content:
-                # at
-                # content = content.split('\u2005')[1]
-                content = re.sub(r"@[^\u2005]*\u2005", "", content)
-                at_wxids = re.findall(
-                    r"<atuserlist><!\[CDATA\[.*?(?:,|\b)([^,]+?)(?=,|\]\]></atuserlist>)",
-                    msg_source,
-                )
-
-            abm.group_id = from_user_name
-
-            if (
-                f"<atuserlist><![CDATA[,{abm.self_id}]]>" in msg_source
-                or f"<atuserlist><![CDATA[{abm.self_id}]]>" in msg_source
-            ):
-                at_me = True
-            if "在群聊中@了你" in d.get("PushContent", ""):
-                at_me = True
-        else:
-            abm.type = MessageType.FRIEND_MESSAGE
-            user_id = from_user_name
-
-        # 检查消息是否由自己发送，若是则忽略
-        # 已经有可配置项专门配置是否需要响应自己的消息，因此这里注释掉。
-        # if user_id == abm.self_id:
-        #     logger.info("忽略自己发送的消息")
-        #     return None
-
-        abm.message = []
-
-        # 解析用户真实名字
-        user_real_name = "unknown"
-        if abm.group_id:
-            if (
-                abm.group_id not in self.userrealnames
-                or user_id not in self.userrealnames[abm.group_id]
-            ):
-                # 获取群成员列表，并且缓存
-                if abm.group_id not in self.userrealnames:
-                    self.userrealnames[abm.group_id] = {}
-                member_list = await self.get_chatroom_member_list(abm.group_id)
-                logger.debug(f"获取到 {abm.group_id} 的群成员列表。")
-                if member_list and "memberList" in member_list:
-                    for member in member_list["memberList"]:
-                        self.userrealnames[abm.group_id][member["wxid"]] = member[
-                            "nickName"
-                        ]
-                if user_id in self.userrealnames[abm.group_id]:
-                    user_real_name = self.userrealnames[abm.group_id][user_id]
-            else:
-                user_real_name = self.userrealnames[abm.group_id][user_id]
-        else:
-            try:
-                info = (await self.get_user_or_group_info(user_id))["data"][0]
-                user_real_name = info["nickName"]
-            except Exception as e:
-                logger.debug(f"获取用户 {user_id} 昵称失败: {e}")
-                user_real_name = user_id
-
-        if at_me:
-            abm.message.insert(0, At(qq=abm.self_id, name=self.nickname))
-        for wxid in at_wxids:
-            # 群聊里 At 其他人的列表
-            _username = self.userrealnames.get(abm.group_id, {}).get(wxid, wxid)
-            abm.message.append(At(qq=wxid, name=_username))
-
-        abm.sender = MessageMember(user_id, user_real_name)
-        abm.raw_message = d
-        abm.message_str = ""
-
-        if user_id == "weixin":
-            # 忽略微信团队消息
-            return
-
-        # 不同消息类型
-        match d["MsgType"]:
-            case 1:
-                # 文本消息
-                abm.message.append(Plain(content))
-                abm.message_str = content
-            case 3:
-                # 图片消息
-                file_url = await self.multimedia_downloader.download_image(
-                    self.appid, content
-                )
-                logger.debug(f"下载图片: {file_url}")
-                file_path = await download_image_by_url(file_url)
-                abm.message.append(Image(file=file_path, url=file_path))
-
-            case 34:
-                # 语音消息
-                if "ImgBuf" in d and "buffer" in d["ImgBuf"]:
-                    voice_data = base64.b64decode(d["ImgBuf"]["buffer"])
-                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-                    file_path = os.path.join(
-                        temp_dir, f"gewe_voice_{abm.message_id}.silk"
-                    )
-
-                    async with await anyio.open_file(file_path, "wb") as f:
-                        await f.write(voice_data)
-                    abm.message.append(Record(file=file_path, url=file_path))
-
-            # 以下已知消息类型，没有业务处理，只是避免控制台打印太多的日志
-            case 37:  # 好友申请
-                logger.info("消息类型(37)：好友申请")
-            case 42:  # 名片
-                logger.info("消息类型(42)：名片")
-            case 43:  # 视频
-                video = Video(file="", cover=content)
-                abm.message.append(video)
-            case 47:  # emoji
-                data_parser = GeweDataParser(content, abm.group_id == "")
-                emoji = data_parser.parse_emoji()
-                abm.message.append(emoji)
-            case 48:  # 地理位置
-                logger.info("消息类型(48)：地理位置")
-            case 49:  # 公众号/文件/小程序/引用/转账/红包/视频号/群聊邀请
-                data_parser = GeweDataParser(content, abm.group_id == "")
-                segments = data_parser.parse_mutil_49()
-                if segments:
-                    abm.message.extend(segments)
-                    for seg in segments:
-                        if isinstance(seg, Plain):
-                            abm.message_str += seg.text
-            case 51:  # 帐号消息同步?
-                logger.info("消息类型(51)：帐号消息同步？")
-            case 10000:  # 被踢出群聊/更换群主/修改群名称
-                logger.info("消息类型(10000)：被踢出群聊/更换群主/修改群名称")
-            case 10002:  # 撤回/拍一拍/成员邀请/被移出群聊/解散群聊/群公告/群待办
-                logger.info(
-                    "消息类型(10002)：撤回/拍一拍/成员邀请/被移出群聊/解散群聊/群公告/群待办"
-                )
-
-            case _:
-                logger.info(f"未实现的消息类型: {d['MsgType']}")
-                abm.raw_message = d
-
-        logger.debug(f"abm: {abm}")
-        return abm
-
-    async def _callback(self):
-        data = await quart.request.json
-        logger.debug(f"收到 gewechat 回调: {data}")
-
-        if data.get("testMsg", None):
-            return quart.jsonify({"r": "AstrBot ACK"})
-
-        abm = None
-        try:
-            abm = await self._convert(data)
-        except BaseException as e:
-            logger.warning(
-                f"尝试解析 GeweChat 下发的消息时遇到问题: {e}。下发消息内容: {data}。"
-            )
-
-        if abm:
-            coro = getattr(self, "on_event_received")
-            if coro:
-                await coro(abm)
-
-        return quart.jsonify({"r": "AstrBot ACK"})
-
-    async def _register_file(self, file_path: str) -> str:
-        """向 AstrBot 回调服务器 注册一个允许外部访问的文件。
-
-        Args:
-            file_path (str): 文件路径。
-        Returns:
-            str: 返回一个 auth_token，文件路径为 file_path。通过 /astrbot-gewechat/file/auth_token 得到文件。
-        """
-        async with self.lock:
-            if not os.path.exists(file_path):
-                raise Exception(f"文件不存在: {file_path}")
-
-            file_token = str(uuid.uuid4())
-            self.staged_files[file_token] = file_path
-            return file_token
-
-    async def _handle_file(self, file_token):
-        async with self.lock:
-            if file_token not in self.staged_files:
-                logger.warning(f"请求的文件 {file_token} 不存在。")
-                return quart.abort(404)
-            if not os.path.exists(self.staged_files[file_token]):
-                logger.warning(f"请求的文件 {self.staged_files[file_token]} 不存在。")
-                return quart.abort(404)
-            file_path = self.staged_files[file_token]
-            self.staged_files.pop(file_token, None)
-            return await quart.send_file(file_path)
-
-    async def _set_callback_url(self):
-        logger.info("设置回调，请等待...")
-        await asyncio.sleep(3)
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/tools/setCallback",
-                headers=self.headers,
-                json={"token": self.token, "callbackUrl": self.callback_url},
-            ) as resp:
-                json_blob = await resp.json()
-                logger.info(f"设置回调结果: {json_blob}")
-                if json_blob["ret"] != 200:
-                    raise Exception(f"设置回调失败: {json_blob}")
-                logger.info(
-                    f"将在 {self.callback_url} 上接收 gewechat 下发的消息。如果一直没收到消息请先尝试重启 AstrBot。如果仍没收到请到管理面板聊天页输入 /gewe_logout 重新登录。"
-                )
-
-    async def start_polling(self):
-        threading.Thread(target=asyncio.run, args=(self._set_callback_url(),)).start()
-        await self.server.run_task(
-            host="0.0.0.0",
-            port=self.port,
-            shutdown_trigger=self.shutdown_trigger,
-        )
-
-    async def shutdown_trigger(self):
-        await self.shutdown_event.wait()
-
-    async def check_online(self, appid: str):
-        """检查 APPID 对应的设备是否在线。"""
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/login/checkOnline",
-                headers=self.headers,
-                json={"appId": appid},
-            ) as resp:
-                json_blob = await resp.json()
-                return json_blob["data"]
-
-    async def logout(self):
-        """登出 gewechat。"""
-        if self.appid:
-            online = await self.check_online(self.appid)
-            if online:
-                async with aiohttp.ClientSession() as session:
-                    async with session.post(
-                        f"{self.base_url}/login/logout",
-                        headers=self.headers,
-                        json={"appId": self.appid},
-                    ) as resp:
-                        json_blob = await resp.json()
-                        logger.info(f"登出结果: {json_blob}")
-
-    async def login(self):
-        """登录 gewechat。一般来说插件用不到这个方法。"""
-        if self.token is None:
-            await self.get_token_id()
-
-        self.multimedia_downloader = GeweDownloader(
-            self.base_url, self.download_base_url, self.token
-        )
-
-        if self.appid:
-            try:
-                online = await self.check_online(self.appid)
-                if online:
-                    logger.info(f"APPID: {self.appid} 已在线")
-                    return
-            except Exception as e:
-                logger.error(f"检查在线状态失败: {e}")
-                sp.put(f"gewechat-appid-{self.nickname}", "")
-                self.appid = None
-
-        payload = {"appId": self.appid}
-
-        if self.appid:
-            logger.info(f"使用 APPID: {self.appid}, {self.nickname}")
-
-        try:
-            async with aiohttp.ClientSession() as session:
-                async with session.post(
-                    f"{self.base_url}/login/getLoginQrCode",
-                    headers=self.headers,
-                    json=payload,
-                ) as resp:
-                    json_blob = await resp.json()
-                    if json_blob["ret"] != 200:
-                        error_msg = json_blob.get("data", {}).get("msg", "")
-                        if "设备不存在" in error_msg:
-                            logger.error(
-                                f"检测到无效的appid: {self.appid}，将清除并重新登录。"
-                            )
-                            sp.put(f"gewechat-appid-{self.nickname}", "")
-                            self.appid = None
-                            return await self.login()
-                        else:
-                            raise Exception(f"获取二维码失败: {json_blob}")
-                    qr_data = json_blob["data"]["qrData"]
-                    qr_uuid = json_blob["data"]["uuid"]
-                    appid = json_blob["data"]["appId"]
-                    logger.info(f"APPID: {appid}")
-                    logger.warning(
-                        f"请打开该网址，然后使用微信扫描二维码登录: https://api.cl2wm.cn/api/qrcode/code?text={qr_data}"
-                    )
-        except Exception as e:
-            raise e
-
-        # 执行登录
-        retry_cnt = 64
-        payload.update({"uuid": qr_uuid, "appId": appid})
-        while retry_cnt > 0:
-            retry_cnt -= 1
-
-            # 需要验证码
-            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-            code_file_path = os.path.join(temp_dir, "gewe_code")
-            if os.path.exists(code_file_path):
-                with open(code_file_path, "r") as f:
-                    code = f.read().strip()
-                    if not code:
-                        logger.warning(
-                            "未找到验证码，请在管理面板聊天页输入 /gewe_code 验证码 来验证，如 /gewe_code 123456"
-                        )
-                        await asyncio.sleep(5)
-                        continue
-                    payload["captchCode"] = code
-                    logger.info(f"使用验证码: {code}")
-                    try:
-                        os.remove(code_file_path)
-                    except Exception:
-                        logger.warning(f"删除验证码文件 {code_file_path} 失败。")
-
-            async with aiohttp.ClientSession() as session:
-                async with session.post(
-                    f"{self.base_url}/login/checkLogin",
-                    headers=self.headers,
-                    json=payload,
-                ) as resp:
-                    json_blob = await resp.json()
-                    logger.info(f"检查登录状态: {json_blob}")
-
-                    ret = json_blob["ret"]
-                    msg = ""
-                    if json_blob["data"] and "msg" in json_blob["data"]:
-                        msg = json_blob["data"]["msg"]
-                    if ret == 500 and "安全验证码" in msg:
-                        logger.warning(
-                            "此次登录需要安全验证码，请在管理面板聊天页输入 /gewe_code 验证码 来验证，如 /gewe_code 123456"
-                        )
-                    else:
-                        if "status" in json_blob["data"]:
-                            status = json_blob["data"]["status"]
-                            nickname = json_blob["data"].get("nickName", "")
-                            if status == 1:
-                                logger.info(f"等待确认...{nickname}")
-                            elif status == 2:
-                                logger.info(f"绿泡泡平台登录成功: {nickname}")
-                                break
-                            elif status == 0:
-                                logger.info("等待扫码...")
-                            else:
-                                logger.warning(f"未知状态: {status}")
-            await asyncio.sleep(5)
-
-        if appid:
-            sp.put(f"gewechat-appid-{self.nickname}", appid)
-            self.appid = appid
-            logger.info(f"已保存 APPID: {appid}")
-
-    """API 部分。Gewechat 的 API 文档请参考: https://apifox.com/apidoc/shared/69ba62ca-cb7d-437e-85e4-6f3d3df271b1
-    """
-
-    async def get_chatroom_member_list(self, chatroom_wxid: str) -> dict:
-        """获取群成员列表。
-
-        Args:
-            chatroom_wxid (str): 微信群聊的id。可以通过 event.get_group_id() 获取。
-
-        Returns:
-            dict: 返回群成员列表字典。其中键为 memberList 的值为群成员列表。
-        """
-        payload = {"appId": self.appid, "chatroomId": chatroom_wxid}
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/group/getChatroomMemberList",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                return json_blob["data"]
-
-    async def post_text(self, to_wxid, content: str, ats: str = ""):
-        """发送纯文本消息"""
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "content": content,
-        }
-        if ats:
-            payload["ats"] = ats
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/postText", headers=self.headers, json=payload
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"发送消息结果: {json_blob}")
-
-    async def post_image(self, to_wxid, image_url: str):
-        """发送图片消息"""
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "imgUrl": image_url,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/postImage", headers=self.headers, json=payload
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"发送图片结果: {json_blob}")
-
-    async def post_emoji(self, to_wxid, emoji_md5, emoji_size, cdnurl=""):
-        """发送emoji消息"""
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "emojiMd5": emoji_md5,
-            "emojiSize": emoji_size,
-        }
-
-        # 优先表情包，若拿不到表情包的md5，就用当作图片发
-        try:
-            if emoji_md5 != "" and emoji_size != "":
-                async with aiohttp.ClientSession() as session:
-                    async with session.post(
-                        f"{self.base_url}/message/postEmoji",
-                        headers=self.headers,
-                        json=payload,
-                    ) as resp:
-                        json_blob = await resp.json()
-                        logger.info(
-                            f"发送emoji消息结果: {json_blob.get('msg', '操作失败')}"
-                        )
-            else:
-                await self.post_image(to_wxid, cdnurl)
-
-        except Exception as e:
-            logger.error(e)
-
-    async def post_video(
-        self, to_wxid, video_url: str, thumb_url: str, video_duration: int
-    ):
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "videoUrl": video_url,
-            "thumbUrl": thumb_url,
-            "videoDuration": video_duration,
-        }
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/postVideo", headers=self.headers, json=payload
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"发送视频结果: {json_blob}")
-
-    async def forward_video(self, to_wxid, cnd_xml: str):
-        """转发视频
-
-        Args:
-            to_wxid (str): 发送给谁
-            cnd_xml (str): 视频消息的cdn信息
-        """
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "xml": cnd_xml,
-        }
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/forwardVideo",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"转发视频结果: {json_blob}")
-
-    async def post_voice(self, to_wxid, voice_url: str, voice_duration: int):
-        """发送语音信息
-
-        Args:
-            voice_url (str): 语音文件的网络链接
-            voice_duration (int): 语音时长，毫秒
-        """
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "voiceUrl": voice_url,
-            "voiceDuration": voice_duration,
-        }
-
-        logger.debug(f"发送语音: {payload}")
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/postVoice", headers=self.headers, json=payload
-            ) as resp:
-                json_blob = await resp.json()
-                logger.info(f"发送语音结果: {json_blob.get('msg', '操作失败')}")
-
-    async def post_file(self, to_wxid, file_url: str, file_name: str):
-        """发送文件
-
-        Args:
-            to_wxid (string): 微信ID
-            file_url (str): 文件的网络链接
-            file_name (str): 文件名
-        """
-        payload = {
-            "appId": self.appid,
-            "toWxid": to_wxid,
-            "fileUrl": file_url,
-            "fileName": file_name,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/message/postFile", headers=self.headers, json=payload
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"发送文件结果: {json_blob}")
-
-    async def add_friend(self, v3: str, v4: str, content: str):
-        """申请添加好友"""
-        payload = {
-            "appId": self.appid,
-            "scene": 3,
-            "content": content,
-            "v4": v4,
-            "v3": v3,
-            "option": 2,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/contacts/addContacts",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"申请添加好友结果: {json_blob}")
-                return json_blob
-
-    async def get_group(self, group_id: str):
-        payload = {
-            "appId": self.appid,
-            "chatroomId": group_id,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/group/getChatroomInfo",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取群信息结果: {json_blob}")
-                return json_blob
-
-    async def get_group_member(self, group_id: str):
-        payload = {
-            "appId": self.appid,
-            "chatroomId": group_id,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/group/getChatroomMemberList",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取群信息结果: {json_blob}")
-                return json_blob
-
-    async def accept_group_invite(self, url: str):
-        """同意进群"""
-        payload = {"appId": self.appid, "url": url}
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/group/agreeJoinRoom",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取群信息结果: {json_blob}")
-                return json_blob
-
-    async def add_group_member_to_friend(
-        self, group_id: str, to_wxid: str, content: str
-    ):
-        payload = {
-            "appId": self.appid,
-            "chatroomId": group_id,
-            "content": content,
-            "memberWxid": to_wxid,
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/group/addGroupMemberAsFriend",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取群信息结果: {json_blob}")
-                return json_blob
-
-    async def get_user_or_group_info(self, *ids):
-        """
-        获取用户或群组信息。
-
-        :param ids: 可变数量的 wxid 参数
-        """
-
-        wxids_str = list(ids)
-
-        payload = {
-            "appId": self.appid,
-            "wxids": wxids_str,  # 使用逗号分隔的字符串
-        }
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/contacts/getDetailInfo",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取群信息结果: {json_blob}")
-                return json_blob
-
-    async def get_contacts_list(self):
-        """
-        获取通讯录列表
-        见 https://apifox.com/apidoc/shared/69ba62ca-cb7d-437e-85e4-6f3d3df271b1/api-196794504
-        """
-        payload = {"appId": self.appid}
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{self.base_url}/contacts/fetchContactsList",
-                headers=self.headers,
-                json=payload,
-            ) as resp:
-                json_blob = await resp.json()
-                logger.debug(f"获取通讯录列表结果: {json_blob}")
-                return json_blob

astrbot/core/platform/sources/gewechat/downloader.py

@@ -1,55 +0,0 @@
-from astrbot import logger
-import aiohttp
-import json
-
-
-class GeweDownloader:
-    def __init__(self, base_url: str, download_base_url: str, token: str):
-        self.base_url = base_url
-        self.download_base_url = download_base_url
-        self.headers = {"Content-Type": "application/json", "X-GEWE-TOKEN": token}
-
-    async def _post_json(self, baseurl: str, route: str, payload: dict):
-        async with aiohttp.ClientSession() as session:
-            async with session.post(
-                f"{baseurl}{route}", headers=self.headers, json=payload
-            ) as resp:
-                return await resp.read()
-
-    async def download_voice(self, appid: str, xml: str, msg_id: str):
-        payload = {"appId": appid, "xml": xml, "msgId": msg_id}
-        return await self._post_json(self.base_url, "/message/downloadVoice", payload)
-
-    async def download_image(self, appid: str, xml: str) -> str:
-        """返回一个可下载的 URL"""
-        choices = [2, 3]  #  2:常规图片 3:缩略图
-
-        for choice in choices:
-            try:
-                payload = {"appId": appid, "xml": xml, "type": choice}
-                data = await self._post_json(
-                    self.base_url, "/message/downloadImage", payload
-                )
-                json_blob = json.loads(data)
-                if "fileUrl" in json_blob["data"]:
-                    return self.download_base_url + json_blob["data"]["fileUrl"]
-
-            except BaseException as e:
-                logger.error(f"gewe download image: {e}")
-                continue
-
-        raise Exception("无法下载图片")
-
-    async def download_emoji_md5(self, app_id, emoji_md5):
-        """下载emoji"""
-        try:
-            payload = {"appId": app_id, "emojiMd5": emoji_md5}
-
-            # gewe 计划中的接口，暂时没有实现。返回代码404
-            data = await self._post_json(
-                self.base_url, "/message/downloadEmojiMd5", payload
-            )
-            json_blob = json.loads(data)
-            return json_blob
-        except BaseException as e:
-            logger.error(f"gewe download emoji: {e}")

astrbot/core/platform/sources/gewechat/gewechat_event.py

@@ -1,264 +0,0 @@
-import asyncio
-import re
-import wave
-import uuid
-import traceback
-import os
-
-from typing import AsyncGenerator
-from astrbot.core.utils.io import download_file
-from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk
-from astrbot.api import logger
-from astrbot.api.event import AstrMessageEvent, MessageChain
-from astrbot.api.platform import AstrBotMessage, PlatformMetadata, Group, MessageMember
-from astrbot.api.message_components import (
-    Plain,
-    Image,
-    Record,
-    At,
-    File,
-    Video,
-    WechatEmoji as Emoji,
-)
-from .client import SimpleGewechatClient
-from astrbot.core.utils.astrbot_path import get_astrbot_data_path
-
-
-def get_wav_duration(file_path):
-    with wave.open(file_path, "rb") as wav_file:
-        file_size = os.path.getsize(file_path)
-        n_channels, sampwidth, framerate, n_frames = wav_file.getparams()[:4]
-        if n_frames == 2147483647:
-            duration = (file_size - 44) / (n_channels * sampwidth * framerate)
-        elif n_frames == 0:
-            duration = (file_size - 44) / (n_channels * sampwidth * framerate)
-        else:
-            duration = n_frames / float(framerate)
-        return duration
-
-
-class GewechatPlatformEvent(AstrMessageEvent):
-    def __init__(
-        self,
-        message_str: str,
-        message_obj: AstrBotMessage,
-        platform_meta: PlatformMetadata,
-        session_id: str,
-        client: SimpleGewechatClient,
-    ):
-        super().__init__(message_str, message_obj, platform_meta, session_id)
-        self.client = client
-
-    @staticmethod
-    async def send_with_client(
-        message: MessageChain, to_wxid: str, client: SimpleGewechatClient
-    ):
-        if not to_wxid:
-            logger.error("无法获取到 to_wxid。")
-            return
-
-        #  检查@
-        ats = []
-        ats_names = []
-        for comp in message.chain:
-            if isinstance(comp, At):
-                ats.append(comp.qq)
-                ats_names.append(comp.name)
-        has_at = False
-
-        for comp in message.chain:
-            if isinstance(comp, Plain):
-                text = comp.text
-                payload = {
-                    "to_wxid": to_wxid,
-                    "content": text,
-                }
-                if not has_at and ats:
-                    ats = f"{','.join(ats)}"
-                    ats_names = f"@{' @'.join(ats_names)}"
-                    text = f"{ats_names} {text}"
-                    payload["content"] = text
-                    payload["ats"] = ats
-                    has_at = True
-                await client.post_text(**payload)
-
-            elif isinstance(comp, Image):
-                img_path = await comp.convert_to_file_path()
-                # 为了安全，向 AstrBot 回调服务注册可被 gewechat 访问的文件，并获得文件 token
-                token = await client._register_file(img_path)
-                img_url = f"{client.file_server_url}/{token}"
-                logger.debug(f"gewe callback img url: {img_url}")
-                await client.post_image(to_wxid, img_url)
-            elif isinstance(comp, Video):
-                if comp.cover != "":
-                    await client.forward_video(to_wxid, comp.cover)
-                else:
-                    try:
-                        from pyffmpeg import FFmpeg
-                    except (ImportError, ModuleNotFoundError):
-                        logger.error(
-                            "需要安装 pyffmpeg 库才能发送视频: pip install pyffmpeg"
-                        )
-                        raise ModuleNotFoundError(
-                            "需要安装 pyffmpeg 库才能发送视频: pip install pyffmpeg"
-                        )
-
-                    video_url = comp.file
-                    # 根据 url 下载视频
-                    if video_url.startswith("http"):
-                        video_filename = f"{uuid.uuid4()}.mp4"
-                        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-                        video_path = os.path.join(temp_dir, video_filename)
-                        await download_file(video_url, video_path)
-                    else:
-                        video_path = video_url
-
-                    video_token = await client._register_file(video_path)
-                    video_callback_url = f"{client.file_server_url}/{video_token}"
-
-                    # 获取视频第一帧
-                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-                    thumb_path = os.path.join(
-                        temp_dir, f"gewechat_video_thumb_{uuid.uuid4()}.jpg"
-                    )
-
-                    video_path = video_path.replace(" ", "\\ ")
-                    try:
-                        ff = FFmpeg()
-                        command = f"-i {video_path} -ss 0 -vframes 1 {thumb_path}"
-                        ff.options(command)
-                        thumb_token = await client._register_file(thumb_path)
-                        thumb_url = f"{client.file_server_url}/{thumb_token}"
-                    except Exception as e:
-                        logger.error(f"获取视频第一帧失败: {e}")
-
-                    # 获取视频时长
-                    try:
-                        from pyffmpeg import FFprobe
-
-                        # 创建 FFprobe 实例
-                        ffprobe = FFprobe(video_url)
-                        # 获取时长字符串
-                        duration_str = ffprobe.duration
-                        # 处理时长字符串
-                        video_duration = float(duration_str.replace(":", ""))
-                    except Exception as e:
-                        logger.error(f"获取时长失败: {e}")
-                        video_duration = 10
-
-                    # 发送视频
-                    await client.post_video(
-                        to_wxid, video_callback_url, thumb_url, video_duration
-                    )
-
-                    # 删除临时缩略图文件
-                    if os.path.exists(thumb_path):
-                        os.remove(thumb_path)
-            elif isinstance(comp, Record):
-                # 默认已经存在 data/temp 中
-                record_url = comp.file
-                record_path = await comp.convert_to_file_path()
-
-                temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-                silk_path = os.path.join(temp_dir, f"{uuid.uuid4()}.silk")
-                try:
-                    duration = await wav_to_tencent_silk(record_path, silk_path)
-                except Exception as e:
-                    logger.error(traceback.format_exc())
-                    await client.post_text(to_wxid, f"语音文件转换失败。{str(e)}")
-                logger.info("Silk 语音文件格式转换至: " + record_path)
-                if duration == 0:
-                    duration = get_wav_duration(record_path)
-                token = await client._register_file(silk_path)
-                record_url = f"{client.file_server_url}/{token}"
-                logger.debug(f"gewe callback record url: {record_url}")
-                await client.post_voice(to_wxid, record_url, duration * 1000)
-            elif isinstance(comp, File):
-                file_path = comp.file
-                file_name = comp.name
-                if file_path.startswith("file:///"):
-                    file_path = file_path[8:]
-                elif file_path.startswith("http"):
-                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
-                    temp_file_path = os.path.join(temp_dir, file_name)
-                    await download_file(file_path, temp_file_path)
-                    file_path = temp_file_path
-                else:
-                    file_path = file_path
-
-                token = await client._register_file(file_path)
-                file_url = f"{client.file_server_url}/{token}"
-                logger.debug(f"gewe callback file url: {file_url}")
-                await client.post_file(to_wxid, file_url, file_name)
-            elif isinstance(comp, Emoji):
-                await client.post_emoji(to_wxid, comp.md5, comp.md5_len, comp.cdnurl)
-            elif isinstance(comp, At):
-                pass
-            else:
-                logger.debug(f"gewechat 忽略: {comp.type}")
-
-    async def send(self, message: MessageChain):
-        to_wxid = self.message_obj.raw_message.get("to_wxid", None)
-        await GewechatPlatformEvent.send_with_client(message, to_wxid, self.client)
-        await super().send(message)
-
-    async def get_group(self, group_id=None, **kwargs):
-        # 确定有效的 group_id
-        if group_id is None:
-            group_id = self.get_group_id()
-
-        if not group_id:
-            return None
-
-        res = await self.client.get_group(group_id)
-        data: dict = res["data"]
-
-        if not data["chatroomId"]:
-            return None
-
-        members = [
-            MessageMember(user_id=member["wxid"], nickname=member["nickName"])
-            for member in data.get("memberList", [])
-        ]
-
-        return Group(
-            group_id=data["chatroomId"],
-            group_name=data.get("nickName"),
-            group_avatar=data.get("smallHeadImgUrl"),
-            group_owner=data.get("chatRoomOwner"),
-            members=members,
-        )
-
-    async def send_streaming(
-        self, generator: AsyncGenerator, use_fallback: bool = False
-    ):
-        if not use_fallback:
-            buffer = None
-            async for chain in generator:
-                if not buffer:
-                    buffer = chain
-                else:
-                    buffer.chain.extend(chain.chain)
-            if not buffer:
-                return
-            buffer.squash_plain()
-            await self.send(buffer)
-            return await super().send_streaming(generator, use_fallback)
-
-        buffer = ""
-        pattern = re.compile(r"[^。？！~…]+[。？！~…]+")
-
-        async for chain in generator:
-            if isinstance(chain, MessageChain):
-                for comp in chain.chain:
-                    if isinstance(comp, Plain):
-                        buffer += comp.text
-                        if any(p in buffer for p in "。？！~…"):
-                            buffer = await self.process_buffer(buffer, pattern)
-                    else:
-                        await self.send(MessageChain(chain=[comp]))
-                        await asyncio.sleep(1.5)  # 限速
-
-        if buffer.strip():
-            await self.send(MessageChain([Plain(buffer)]))
-        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/gewechat/gewechat_platform_adapter.py

@@ -1,103 +0,0 @@
-import sys
-import asyncio
-import os
-
-from astrbot.api.platform import Platform, AstrBotMessage, MessageType, PlatformMetadata
-from astrbot.api.event import MessageChain
-from astrbot.core.platform.astr_message_event import MessageSesion
-from ...register import register_platform_adapter
-from .gewechat_event import GewechatPlatformEvent
-from .client import SimpleGewechatClient
-from astrbot import logger
-
-if sys.version_info >= (3, 12):
-    from typing import override
-else:
-    from typing_extensions import override
-
-
-@register_platform_adapter("gewechat", "基于 gewechat 的 Wechat 适配器")
-class GewechatPlatformAdapter(Platform):
-    def __init__(
-        self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue
-    ) -> None:
-        super().__init__(event_queue)
-        self.config = platform_config
-        self.settingss = platform_settings
-        self.test_mode = os.environ.get("TEST_MODE", "off") == "on"
-        self.client = None
-
-        self.client = SimpleGewechatClient(
-            self.config["base_url"],
-            self.config["nickname"],
-            self.config["host"],
-            self.config["port"],
-            self._event_queue,
-        )
-
-        async def on_event_received(abm: AstrBotMessage):
-            await self.handle_msg(abm)
-
-        self.client.on_event_received = on_event_received
-
-    @override
-    async def send_by_session(
-        self, session: MessageSesion, message_chain: MessageChain
-    ):
-        session_id = session.session_id
-        if "#" in session_id:
-            # unique session
-            to_wxid = session_id.split("#")[1]
-        else:
-            to_wxid = session_id
-
-        await GewechatPlatformEvent.send_with_client(
-            message_chain, to_wxid, self.client
-        )
-
-        await super().send_by_session(session, message_chain)
-
-    @override
-    def meta(self) -> PlatformMetadata:
-        return PlatformMetadata(
-            name="gewechat",
-            description="基于 gewechat 的 Wechat 适配器",
-            id=self.config.get("id"),
-        )
-
-    async def terminate(self):
-        self.client.shutdown_event.set()
-        try:
-            await self.client.server.shutdown()
-        except Exception as _:
-            pass
-        logger.info("Gewechat 适配器已被优雅地关闭。")
-
-    async def logout(self):
-        await self.client.logout()
-
-    @override
-    def run(self):
-        return self._run()
-
-    async def _run(self):
-        await self.client.login()
-        await self.client.start_polling()
-
-    async def handle_msg(self, message: AstrBotMessage):
-        if message.type == MessageType.GROUP_MESSAGE:
-            if self.settingss["unique_session"]:
-                message.session_id = message.sender.user_id + "#" + message.group_id
-
-        message_event = GewechatPlatformEvent(
-            message_str=message.message_str,
-            message_obj=message,
-            platform_meta=self.meta(),
-            session_id=message.session_id,
-            client=self.client,
-        )
-
-        self.commit_event(message_event)
-
-    def get_client(self) -> SimpleGewechatClient:
-        return self.client

astrbot/core/platform/sources/gewechat/xml_data_parser.py

@@ -1,110 +0,0 @@
-from defusedxml import ElementTree as eT
-from astrbot.api import logger
-from astrbot.api.message_components import (
-    WechatEmoji as Emoji,
-    Reply,
-    Plain,
-    BaseMessageComponent,
-)
-
-
-class GeweDataParser:
-    def __init__(self, data, is_private_chat):
-        self.data = data
-        self.is_private_chat = is_private_chat
-
-    def _format_to_xml(self):
-        return eT.fromstring(self.data)
-
-    def parse_mutil_49(self) -> list[BaseMessageComponent] | None:
-        appmsg_type = self._format_to_xml().find(".//appmsg/type")
-        if appmsg_type is None:
-            return
-
-        match appmsg_type.text:
-            case "57":
-                return self.parse_reply()
-
-    def parse_emoji(self) -> Emoji | None:
-        try:
-            emoji_element = self._format_to_xml().find(".//emoji")
-            # 提取 md5 和 len 属性
-            if emoji_element is not None:
-                md5_value = emoji_element.get("md5")
-                emoji_size = emoji_element.get("len")
-                cdnurl = emoji_element.get("cdnurl")
-
-                return Emoji(md5=md5_value, md5_len=emoji_size, cdnurl=cdnurl)
-
-        except Exception as e:
-            logger.error(f"gewechat: parse_emoji failed, {e}")
-
-    def parse_reply(self) -> list[Reply, Plain] | None:
-        """解析引用消息
-
-        Returns:
-            list[Reply, Plain]: 一个包含两个元素的列表。Reply 消息对象和引用者说的文本内容。微信平台下引用消息时只能发送文本消息。
-        """
-        try:
-            replied_id = -1
-            replied_uid = 0
-            replied_nickname = ""
-            replied_content = ""  # 被引用者说的内容
-            content = ""  # 引用者说的内容
-
-            root = self._format_to_xml()
-            refermsg = root.find(".//refermsg")
-            if refermsg is not None:
-                # 被引用的信息
-                svrid = refermsg.find("svrid")
-                fromusr = refermsg.find("fromusr")
-                displayname = refermsg.find("displayname")
-                refermsg_content = refermsg.find("content")
-                if svrid is not None:
-                    replied_id = svrid.text
-                if fromusr is not None:
-                    replied_uid = fromusr.text
-                if displayname is not None:
-                    replied_nickname = displayname.text
-                if refermsg_content is not None:
-                    # 处理引用嵌套，包括嵌套公众号消息
-                    if refermsg_content.text.startswith(
-                        "<msg>"
-                    ) or refermsg_content.text.startswith("<?xml"):
-                        try:
-                            logger.debug("gewechat: Reference message is nested")
-                            refer_root = eT.fromstring(refermsg_content.text)
-                            img = refer_root.find("img")
-                            if img is not None:
-                                replied_content = "[图片]"
-                            else:
-                                app_msg = refer_root.find("appmsg")
-                                refermsg_content_title = app_msg.find("title")
-                                logger.debug(
-                                    f"gewechat: Reference message nesting: {refermsg_content_title.text}"
-                                )
-                                replied_content = refermsg_content_title.text
-                        except Exception as e:
-                            logger.error(f"gewechat: nested failed, {e}")
-                            # 处理异常情况
-                            replied_content = refermsg_content.text
-                    else:
-                        replied_content = refermsg_content.text
-
-                # 提取引用者说的内容
-            title = root.find(".//appmsg/title")
-            if title is not None:
-                content = title.text
-
-            reply_seg = Reply(
-                id=replied_id,
-                chain=[Plain(replied_content)],
-                sender_id=replied_uid,
-                sender_nickname=replied_nickname,
-                message_str=replied_content,
-            )
-            plain_seg = Plain(content)
-            return [reply_seg, plain_seg]
-
-        except Exception as e:
-            logger.error(f"gewechat: parse_reply failed, {e}")

astrbot/core/platform/sources/qqofficial/qqofficial_message_event.py

@@ -3,15 +3,23 @@ import botpy.message
 import botpy.types
 import botpy.types.message
 import asyncio
+import base64
+import aiofiles
 from astrbot.core.utils.io import file_to_base64, download_image_by_url
+from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.platform import AstrBotMessage, PlatformMetadata
-from astrbot.api.message_components import Plain, Image
+from astrbot.api.message_components import Plain, Image, Record
 from botpy import Client
 from botpy.http import Route
 from astrbot.api import logger
+from botpy.types.message import Media
 from botpy.types import message
+from typing import Optional
 import random
+import uuid
+import os
 
 
 class QQOfficialMessageEvent(AstrMessageEvent):
@@ -28,16 +36,15 @@ class QQOfficialMessageEvent(AstrMessageEvent):
         self.send_buffer = None
 
     async def send(self, message: MessageChain):
-        if not self.send_buffer:
-            self.send_buffer = message
-        else:
-            self.send_buffer.chain.extend(message.chain)
+        self.send_buffer = message
+        await self._post_send()
 
     async def send_streaming(self, generator, use_fallback: bool = False):
         """流式输出仅支持消息列表私聊"""
         stream_payload = {"state": 1, "id": None, "index": 0, "reset": False}
         last_edit_time = 0  # 上次编辑消息的时间
         throttle_interval = 1  # 编辑消息的间隔时间 (秒)
+        ret = None
         try:
             async for chain in generator:
                 source = self.message_obj.raw_message
@@ -87,9 +94,10 @@ class QQOfficialMessageEvent(AstrMessageEvent):
             plain_text,
             image_base64,
             image_path,
+            record_file_path
         ) = await QQOfficialMessageEvent._parse_to_qqofficial(self.send_buffer)
 
-        if not plain_text and not image_base64 and not image_path:
+        if not plain_text and not image_base64 and not image_path and not record_file_path:
             return
 
         payload = {
@@ -100,6 +108,8 @@ class QQOfficialMessageEvent(AstrMessageEvent):
         if not isinstance(source, (botpy.message.Message, botpy.message.DirectMessage)):
             payload["msg_seq"] = random.randint(1, 10000)
 
+        ret = None
+
         match type(source):
             case botpy.message.GroupMessage:
                 if image_base64:
@@ -108,6 +118,12 @@ class QQOfficialMessageEvent(AstrMessageEvent):
                     )
                     payload["media"] = media
                     payload["msg_type"] = 7
+                if record_file_path: # group record msg
+                    media = await self.upload_group_and_c2c_record(
+                        record_file_path, 3, group_openid=source.group_openid
+                    )
+                    payload["media"] = media
+                    payload["msg_type"] = 7
                 ret = await self.bot.api.post_group_message(
                     group_openid=source.group_openid, **payload
                 )
@@ -118,6 +134,12 @@ class QQOfficialMessageEvent(AstrMessageEvent):
                     )
                     payload["media"] = media
                     payload["msg_type"] = 7
+                if record_file_path: # c2c record
+                    media = await self.upload_group_and_c2c_record(
+                        record_file_path, 3, openid = source.author.user_openid
+                    )
+                    payload["media"] = media
+                    payload["msg_type"] = 7
                 if stream:
                     ret = await self.post_c2c_message(
                         openid=source.author.user_openid,
@@ -167,6 +189,59 @@ class QQOfficialMessageEvent(AstrMessageEvent):
             )
             return await self.bot.api._http.request(route, json=payload)
 
+    async def upload_group_and_c2c_record(
+        self, 
+        file_source: str, 
+        file_type: int, 
+        srv_send_msg: bool = False,
+        **kwargs
+    ) -> Optional[Media]:
+        """
+        上传媒体文件
+        """
+        # 构建基础payload
+        payload = {
+            "file_type": file_type,
+            "srv_send_msg": srv_send_msg
+        }
+        
+        # 处理文件数据
+        if os.path.exists(file_source):
+            # 读取本地文件
+            async with aiofiles.open(file_source, 'rb') as f:
+                file_content = await f.read()
+                # use base64 encode
+                payload["file_data"] = base64.b64encode(file_content).decode('utf-8')
+        else:
+            # 使用URL
+            payload["url"] = file_source
+        
+        # 添加接收者信息和确定路由
+        if "openid" in kwargs:
+            payload["openid"] = kwargs["openid"]
+            route = Route("POST", "/v2/users/{openid}/files", openid=kwargs["openid"])
+        elif "group_openid" in kwargs:
+            payload["group_openid"] =kwargs["group_openid"]
+            route = Route("POST", "/v2/groups/{group_openid}/files", group_openid=kwargs["group_openid"])
+        else:
+            return None
+        
+        try:
+            # 使用底层HTTP请求
+            result = await self.bot.api._http.request(route, json=payload)
+            
+            if result:
+                return Media(
+                    file_uuid=result.get("file_uuid"),
+                    file_info=result.get("file_info"),
+                    ttl=result.get("ttl", 0),
+                    file_id=result.get("id", "")
+                )
+        except Exception as e:
+            logger.error(f"上传请求错误: {e}")
+        
+        return None
+    
     async def post_c2c_message(
         self,
         openid: str,
@@ -193,6 +268,7 @@ class QQOfficialMessageEvent(AstrMessageEvent):
         plain_text = ""
         image_base64 = None  # only one img supported
         image_file_path = None
+        record_file_path = None
         for i in message.chain:
             if isinstance(i, Plain):
                 plain_text += i.text
@@ -208,6 +284,21 @@ class QQOfficialMessageEvent(AstrMessageEvent):
                 else:
                     image_base64 = file_to_base64(i.file)
                 image_base64 = image_base64.removeprefix("base64://")
+            elif isinstance(i, Record):
+                if i.file:
+                    record_wav_path = await i.convert_to_file_path() # wav 路径
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    record_tecent_silk_path = os.path.join(temp_dir, f"{uuid.uuid4()}.silk")
+                    try:
+                        duration = await wav_to_tencent_silk(record_wav_path, record_tecent_silk_path)
+                        if duration > 0:
+                            record_file_path = record_tecent_silk_path
+                        else:
+                            record_file_path = None                                 
+                            logger.error("转换音频格式时出错：音频时长不大于0")
+                    except Exception as e:
+                        logger.error(f"处理语音时出错: {e}")
+                        record_file_path = None                                     
             else:
                 logger.debug(f"qq_official 忽略 {i.type}")
-        return plain_text, image_base64, image_file_path
+        return plain_text, image_base64, image_file_path, record_file_path

astrbot/core/platform/sources/telegram/tg_event.py

@@ -40,20 +40,21 @@ class TelegramPlatformEvent(AstrMessageEvent):
         super().__init__(message_str, message_obj, platform_meta, session_id)
         self.client = client
 
-    def _split_message(self, text: str) -> list[str]:
-        if len(text) <= self.MAX_MESSAGE_LENGTH:
+    @classmethod
+    def _split_message(cls, text: str) -> list[str]:
+        if len(text) <= cls.MAX_MESSAGE_LENGTH:
             return [text]
 
         chunks = []
         while text:
-            if len(text) <= self.MAX_MESSAGE_LENGTH:
+            if len(text) <= cls.MAX_MESSAGE_LENGTH:
                 chunks.append(text)
                 break
 
-            split_point = self.MAX_MESSAGE_LENGTH
-            segment = text[: self.MAX_MESSAGE_LENGTH]
+            split_point = cls.MAX_MESSAGE_LENGTH
+            segment = text[: cls.MAX_MESSAGE_LENGTH]
 
-            for _, pattern in self.SPLIT_PATTERNS.items():
+            for _, pattern in cls.SPLIT_PATTERNS.items():
                 if matches := list(pattern.finditer(segment)):
                     last_match = matches[-1]
                     split_point = last_match.end()
@@ -64,9 +65,8 @@ class TelegramPlatformEvent(AstrMessageEvent):
 
         return chunks
 
-    async def send_with_client(
-        self, client: ExtBot, message: MessageChain, user_name: str
-    ):
+    @classmethod
+    async def send_with_client(cls, client: ExtBot, message: MessageChain, user_name: str):
         image_path = None
 
         has_reply = False
@@ -97,7 +97,7 @@ class TelegramPlatformEvent(AstrMessageEvent):
                 if at_user_id and not at_flag:
                     i.text = f"@{at_user_id} {i.text}"
                     at_flag = True
-                chunks = self._split_message(i.text)
+                chunks = cls._split_message(i.text)
                 for chunk in chunks:
                     try:
                         md_text = telegramify_markdown.markdownify(
@@ -158,6 +158,12 @@ class TelegramPlatformEvent(AstrMessageEvent):
 
         async for chain in generator:
             if isinstance(chain, MessageChain):
+                if chain.type == "break":
+                    # 分割符
+                    message_id = None  # 重置消息 ID
+                    delta = ""  # 重置 delta
+                    continue
+
                 # 处理消息链中的每个组件
                 for i in chain.chain:
                     if isinstance(i, Plain):

astrbot/core/platform/sources/webchat/webchat_adapter.py

@@ -2,7 +2,7 @@ import time
 import asyncio
 import uuid
 import os
-from typing import Awaitable, Any
+from typing import Awaitable, Any, Callable
 from astrbot.core.platform import (
     Platform,
     AstrBotMessage,
@@ -13,7 +13,7 @@ from astrbot.core.platform import (
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.message.components import Plain, Image, Record  # noqa: F403
 from astrbot import logger
-from astrbot.core import web_chat_queue
+from .webchat_queue_mgr import webchat_queue_mgr, WebChatQueueMgr
 from .webchat_event import WebChatMessageEvent
 from astrbot.core.platform.astr_message_event import MessageSesion
 from ...register import register_platform_adapter
@@ -21,14 +21,46 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class QueueListener:
-    def __init__(self, queue: asyncio.Queue, callback: callable) -> None:
-        self.queue = queue
+    def __init__(self, webchat_queue_mgr: WebChatQueueMgr, callback: Callable) -> None:
+        self.webchat_queue_mgr = webchat_queue_mgr
         self.callback = callback
+        self.running_tasks = set()
+
+    async def listen_to_queue(self, conversation_id: str):
+        """Listen to a specific conversation queue"""
+        queue = self.webchat_queue_mgr.get_or_create_queue(conversation_id)
+        while True:
+            try:
+                data = await queue.get()
+                await self.callback(data)
+            except Exception as e:
+                logger.error(
+                    f"Error processing message from conversation {conversation_id}: {e}"
+                )
+                break
 
     async def run(self):
+        """Monitor for new conversation queues and start listeners"""
+        monitored_conversations = set()
+
         while True:
-            data = await self.queue.get()
-            await self.callback(data)
+            # Check for new conversations
+            current_conversations = set(self.webchat_queue_mgr.queues.keys())
+            new_conversations = current_conversations - monitored_conversations
+
+            # Start listeners for new conversations
+            for conversation_id in new_conversations:
+                task = asyncio.create_task(self.listen_to_queue(conversation_id))
+                self.running_tasks.add(task)
+                task.add_done_callback(self.running_tasks.discard)
+                monitored_conversations.add(conversation_id)
+                logger.debug(f"Started listener for conversation: {conversation_id}")
+
+            # Clean up monitored conversations that no longer exist
+            removed_conversations = monitored_conversations - current_conversations
+            monitored_conversations -= removed_conversations
+
+            await asyncio.sleep(1)  # Check for new conversations every second
 
 
 @register_platform_adapter("webchat", "webchat")
@@ -45,7 +77,7 @@ class WebChatAdapter(Platform):
         os.makedirs(self.imgs_dir, exist_ok=True)
 
         self.metadata = PlatformMetadata(
-            name="webchat", description="webchat", id=self.config.get("id")
+            name="webchat", description="webchat", id="webchat"
         )
 
     async def send_by_session(
@@ -105,7 +137,7 @@ class WebChatAdapter(Platform):
             abm = await self.convert_message(data)
             await self.handle_msg(abm)
 
-        bot = QueueListener(web_chat_queue, callback)
+        bot = QueueListener(webchat_queue_mgr, callback)
         return bot.run()
 
     def meta(self) -> PlatformMetadata:
@@ -119,6 +151,10 @@ class WebChatAdapter(Platform):
             session_id=message.session_id,
         )
 
+        _, _, payload = message.raw_message  # type: ignore
+        message_event.set_extra("selected_provider", payload.get("selected_provider"))
+        message_event.set_extra("selected_model", payload.get("selected_model"))
+
         self.commit_event(message_event)
 
     async def terminate(self):

astrbot/core/platform/sources/webchat/webchat_event.py

@@ -5,8 +5,8 @@ from astrbot.api import logger
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.message_components import Plain, Image, Record
 from astrbot.core.utils.io import download_image_by_url
-from astrbot.core import web_chat_back_queue
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from .webchat_queue_mgr import webchat_queue_mgr
 
 imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
 
@@ -18,13 +18,18 @@ class WebChatMessageEvent(AstrMessageEvent):
 
     @staticmethod
     async def _send(message: MessageChain, session_id: str, streaming: bool = False):
+        cid = session_id.split("!")[-1]
+        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
         if not message:
             await web_chat_back_queue.put(
-                {"type": "end", "data": "", "streaming": False}
+                {
+                    "type": "end",
+                    "data": "",
+                    "streaming": False,
+                }  # end means this request is finished
             )
             return ""
 
-        cid = session_id.split("!")[-1]
         data = ""
         for comp in message.chain:
             if isinstance(comp, Plain):
@@ -35,6 +40,7 @@ class WebChatMessageEvent(AstrMessageEvent):
                         "cid": cid,
                         "data": data,
                         "streaming": streaming,
+                        "chain_type": message.type,
                     }
                 )
             elif isinstance(comp, Image):
@@ -97,29 +103,35 @@ class WebChatMessageEvent(AstrMessageEvent):
 
     async def send(self, message: MessageChain):
         await WebChatMessageEvent._send(message, session_id=self.session_id)
-        await web_chat_back_queue.put(
-            {
-                "type": "end",
-                "data": "",
-                "streaming": False,
-                "cid": self.session_id.split("!")[-1],
-            }
-        )
         await super().send(message)
 
     async def send_streaming(self, generator, use_fallback: bool = False):
         final_data = ""
+        cid = self.session_id.split("!")[-1]
+        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
         async for chain in generator:
+            if chain.type == "break" and final_data:
+                # 分割符
+                await web_chat_back_queue.put(
+                    {
+                        "type": "break",  # break means a segment end
+                        "data": final_data,
+                        "streaming": True,
+                        "cid": cid,
+                    }
+                )
+                final_data = ""
+                continue
             final_data += await WebChatMessageEvent._send(
                 chain, session_id=self.session_id, streaming=True
             )
 
         await web_chat_back_queue.put(
             {
-                "type": "end",
+                "type": "complete",  # complete means we return the final result
                 "data": final_data,
                 "streaming": True,
-                "cid": self.session_id.split("!")[-1],
+                "cid": cid,
             }
         )
         await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/webchat/webchat_queue_mgr.py

@@ -0,0 +1,33 @@
+import asyncio
+
+class WebChatQueueMgr:
+    def __init__(self) -> None:
+        self.queues = {}
+        """Conversation ID to asyncio.Queue mapping"""
+        self.back_queues = {}
+        """Conversation ID to asyncio.Queue mapping for responses"""
+
+    def get_or_create_queue(self, conversation_id: str) -> asyncio.Queue:
+        """Get or create a queue for the given conversation ID"""
+        if conversation_id not in self.queues:
+            self.queues[conversation_id] = asyncio.Queue()
+        return self.queues[conversation_id]
+
+    def get_or_create_back_queue(self, conversation_id: str) -> asyncio.Queue:
+        """Get or create a back queue for the given conversation ID"""
+        if conversation_id not in self.back_queues:
+            self.back_queues[conversation_id] = asyncio.Queue()
+        return self.back_queues[conversation_id]
+
+    def remove_queues(self, conversation_id: str):
+        """Remove queues for the given conversation ID"""
+        if conversation_id in self.queues:
+            del self.queues[conversation_id]
+        if conversation_id in self.back_queues:
+            del self.back_queues[conversation_id]
+
+    def has_queue(self, conversation_id: str) -> bool:
+        """Check if a queue exists for the given conversation ID"""
+        return conversation_id in self.queues
+
+webchat_queue_mgr = WebChatQueueMgr()

astrbot/core/platform/sources/wechatpadpro/wechatpadpro_adapter.py

@@ -210,6 +210,16 @@ class WeChatPadProAdapter(Platform):
                 logger.error(traceback.format_exc())
                 return False
 
+    def _extract_auth_key(self, data):
+        """Helper method to extract auth_key from response data."""
+        if isinstance(data, dict):
+            auth_keys = data.get("authKeys") # 新接口
+            if isinstance(auth_keys, list) and auth_keys:
+                return auth_keys[0]
+        elif isinstance(data, list) and data: # 旧接口
+            return data[0]
+        return None
+
     async def generate_auth_key(self):
         """
         生成授权码。
@@ -218,28 +228,26 @@ class WeChatPadProAdapter(Platform):
         params = {"key": self.admin_key}
         payload = {"Count": 1, "Days": 365}  # 生成一个有效期365天的授权码
 
+        self.auth_key = None  # Reset auth_key before generating a new one
+
         async with aiohttp.ClientSession() as session:
             try:
                 async with session.post(url, params=params, json=payload) as response:
+                    if response.status != 200:
+                        logger.error(f"生成授权码失败: {response.status}, {await response.text()}")
+                        return
+
                     response_data = await response.json()
-                    # 修正成功判断条件和授权码提取路径
-                    if response.status == 200 and response_data.get("Code") == 200:
-                        # 授权码在 Data 字段的列表中
-                        if (
-                            response_data.get("Data")
-                            and isinstance(response_data["Data"], list)
-                            and len(response_data["Data"]) > 0
-                        ):
-                            self.auth_key = response_data["Data"][0]
-                            logger.info(f"成功获取授权码 {self.auth_key[:8]}...")
+                    if response_data.get("Code") == 200:
+                        if data := response_data.get("Data"):
+                            self.auth_key = self._extract_auth_key(data)
+
+                        if self.auth_key:
+                            logger.info("成功获取授权码")
                         else:
-                            logger.error(
-                                f"生成授权码成功但未找到授权码: {response_data}"
-                            )
+                            logger.error(f"生成授权码成功但未找到授权码: {response_data}")
                     else:
-                        logger.error(
-                            f"生成授权码失败: {response.status}, {response_data}"
-                        )
+                        logger.error(f"生成授权码失败: {response_data}")
             except aiohttp.ClientConnectorError as e:
                 logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
             except Exception as e:

astrbot/core/platform/sources/wechatpadpro/wechatpadpro_message_event.py

@@ -17,7 +17,7 @@ from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.platform.astrbot_message import AstrBotMessage, MessageType
 from astrbot.core.platform.platform_metadata import PlatformMetadata
-from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk_base64
+from astrbot.core.utils.tencent_record_helper import audio_to_tencent_silk_base64
 
 if TYPE_CHECKING:
     from .wechatpadpro_adapter import WeChatPadProAdapter
@@ -113,7 +113,7 @@ class WeChatPadProMessageEvent(AstrMessageEvent):
     async def _send_voice(self, session: aiohttp.ClientSession, comp: Record):
         record_path = await comp.convert_to_file_path()
         # 默认已经存在 data/temp 中
-        b64, duration = await wav_to_tencent_silk_base64(record_path)
+        b64, duration = await audio_to_tencent_silk_base64(record_path)
         payload = {
             "ToUserName": self.session_id,
             "VoiceData": b64,

astrbot/core/platform_message_history_mgr.py

@@ -0,0 +1,47 @@
+from astrbot.core.db import BaseDatabase
+from astrbot.core.db.po import PlatformMessageHistory
+
+
+class PlatformMessageHistoryManager:
+    def __init__(self, db_helper: BaseDatabase):
+        self.db = db_helper
+
+    async def insert(
+        self,
+        platform_id: str,
+        user_id: str,
+        content: list[dict],  # TODO: parse from message chain
+        sender_id: str = None,
+        sender_name: str = None,
+    ):
+        """Insert a new platform message history record."""
+        await self.db.insert_platform_message_history(
+            platform_id=platform_id,
+            user_id=user_id,
+            content=content,
+            sender_id=sender_id,
+            sender_name=sender_name,
+        )
+
+    async def get(
+        self,
+        platform_id: str,
+        user_id: str,
+        page: int = 1,
+        page_size: int = 200,
+    ) -> list[PlatformMessageHistory]:
+        """Get platform message history for a specific user."""
+        history = await self.db.get_platform_message_history(
+            platform_id=platform_id,
+            user_id=user_id,
+            page=page,
+            page_size=page_size,
+        )
+        history.reverse()
+        return history
+
+    async def delete(self, platform_id: str, user_id: str, offset_sec: int = 86400):
+        """Delete platform message history records older than the specified offset."""
+        await self.db.delete_platform_message_offset(
+            platform_id=platform_id, user_id=user_id, offset_sec=offset_sec
+        )

astrbot/core/provider/entities.py

@@ -5,7 +5,7 @@ from astrbot.core.utils.io import download_image_by_url
 from astrbot import logger
 from dataclasses import dataclass, field
 from typing import List, Dict, Type
-from .func_tool_manager import FuncCall
+from astrbot.core.agent.tool import ToolSet
 from openai.types.chat.chat_completion import ChatCompletion
 from openai.types.chat.chat_completion_message_tool_call import (
     ChatCompletionMessageToolCall,
@@ -20,6 +20,7 @@ class ProviderType(enum.Enum):
     SPEECH_TO_TEXT = "speech_to_text"
     TEXT_TO_SPEECH = "text_to_speech"
     EMBEDDING = "embedding"
+    RERANK = "rerank"
 
 
 @dataclass
@@ -58,7 +59,7 @@ class AssistantMessageSegment:
     """OpenAI 格式的上下文中 role 为 assistant 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
 
     content: str = None
-    tool_calls: List[ChatCompletionMessageToolCall | Dict] = None
+    tool_calls: List[ChatCompletionMessageToolCall | Dict] = field(default_factory=list)
     role: str = "assistant"
 
     def to_dict(self):
@@ -67,7 +68,7 @@ class AssistantMessageSegment:
         }
         if self.content:
             ret["content"] = self.content
-        elif self.tool_calls:
+        if self.tool_calls:
             ret["tool_calls"] = self.tool_calls
         return ret
 
@@ -95,27 +96,38 @@ class ProviderRequest:
     """提示词"""
     session_id: str = ""
     """会话 ID"""
-    image_urls: List[str] = None
+    image_urls: list[str] = field(default_factory=list)
     """图片 URL 列表"""
-    func_tool: FuncCall = None
+    func_tool: ToolSet | None = None
     """可用的函数工具"""
-    contexts: List = None
+    contexts: list[dict] = field(default_factory=list)
     """上下文。格式与 openai 的上下文格式一致：
     参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
     """
     system_prompt: str = ""
     """系统提示词"""
-    conversation: Conversation = None
+    conversation: Conversation | None = None
 
-    tool_calls_result: ToolCallsResult = None
+    tool_calls_result: list[ToolCallsResult] | ToolCallsResult | None = None
     """附加的上次请求后工具调用的结果。参考: https://platform.openai.com/docs/guides/function-calling#handling-function-calls"""
 
+    model: str | None = None
+    """模型名称，为 None 时使用提供商的默认模型"""
+
     def __repr__(self):
         return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self._print_friendly_context()}, system_prompt={self.system_prompt.strip()}, tool_calls_result={self.tool_calls_result})"
 
     def __str__(self):
         return self.__repr__()
 
+    def append_tool_calls_result(self, tool_calls_result: ToolCallsResult):
+        """添加工具调用结果到请求中"""
+        if not self.tool_calls_result:
+            self.tool_calls_result = []
+        if isinstance(self.tool_calls_result, ToolCallsResult):
+            self.tool_calls_result = [self.tool_calls_result]
+        self.tool_calls_result.append(tool_calls_result)
+
     def _print_friendly_context(self):
         """打印友好的消息上下文。将 image_url 的值替换为 <Image>"""
         if not self.contexts:
@@ -282,3 +294,10 @@ class LLMResponse:
                 }
             )
         return ret
+
+@dataclass
+class RerankResult:
+    index: int
+    """在候选列表中的索引位置"""
+    relevance_score: float
+    """相关性分数"""

astrbot/core/provider/func_tool_manager.py

@@ -1,32 +1,17 @@
 from __future__ import annotations
 import json
-import textwrap
 import os
 import asyncio
-import logging
-from datetime import timedelta
+import aiohttp
 
-from typing import Dict, List, Awaitable, Literal, Any
-from dataclasses import dataclass
-from typing import Optional
-from contextlib import AsyncExitStack
+from typing import Dict, List, Awaitable
 from astrbot import logger
-from astrbot.core.utils.log_pipe import LogPipe
+from astrbot.core import sp
 
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from astrbot.core.agent.mcp_client import MCPClient
+from astrbot.core.agent.tool import ToolSet, FunctionTool
 
-try:
-    import mcp
-    from mcp.client.sse import sse_client
-except (ModuleNotFoundError, ImportError):
-    logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
-
-try:
-    from mcp.client.streamable_http import streamablehttp_client
-except (ModuleNotFoundError, ImportError):
-    logger.warning(
-        "警告: 缺少依赖库 'mcp' 或者 mcp 库版本过低，无法使用 Streamable HTTP 连接方式。"
-    )
 
 DEFAULT_MCP_CONFIG = {"mcpServers": {}}
 
@@ -39,175 +24,109 @@ SUPPORTED_TYPES = [
 ]  # json schema 支持的数据类型
 
 
-@dataclass
-class FuncTool:
-    """
-    用于描述一个函数调用工具。
-    """
-
-    name: str
-    parameters: Dict
-    description: str
-    handler: Awaitable = None
-    """处理函数, 当 origin 为 mcp 时，这个为空"""
-    handler_module_path: str = None
-    """处理函数的模块路径，当 origin 为 mcp 时，这个为空
-
-    必须要保留这个字段, handler 在初始化会被 functools.partial 包装，导致 handler 的 __module__ 为 functools
-    """
-    active: bool = True
-    """是否激活"""
-
-    origin: Literal["local", "mcp"] = "local"
-    """函数工具的来源, local 为本地函数工具, mcp 为 MCP 服务"""
-
-    # MCP 相关字段
-    mcp_server_name: str = None
-    """MCP 服务名称，当 origin 为 mcp 时有效"""
-    mcp_client: MCPClient = None
-    """MCP 客户端，当 origin 为 mcp 时有效"""
-
-    def __repr__(self):
-        return f"FuncTool(name={self.name}, parameters={self.parameters}, description={self.description}, active={self.active}, origin={self.origin})"
-
-    async def execute(self, **args) -> Any:
-        """执行函数调用"""
-        if self.origin == "local":
-            if not self.handler:
-                raise Exception(f"Local function {self.name} has no handler")
-            return await self.handler(**args)
-        elif self.origin == "mcp":
-            if not self.mcp_client or not self.mcp_client.session:
-                raise Exception(f"MCP client for {self.name} is not available")
-            # 使用name属性而不是额外的mcp_tool_name
-            if ":" in self.name:
-                # 如果名字是格式为 mcp:server:tool_name，提取实际的工具名
-                actual_tool_name = self.name.split(":")[-1]
-                return await self.mcp_client.session.call_tool(actual_tool_name, args)
-            else:
-                return await self.mcp_client.session.call_tool(self.name, args)
-        else:
-            raise Exception(f"Unknown function origin: {self.origin}")
+# alias
+FuncTool = FunctionTool
 
 
-class MCPClient:
-    def __init__(self):
-        # Initialize session and client objects
-        self.session: Optional[mcp.ClientSession] = None
-        self.exit_stack = AsyncExitStack()
+def _prepare_config(config: dict) -> dict:
+    """准备配置，处理嵌套格式"""
+    if "mcpServers" in config and config["mcpServers"]:
+        first_key = next(iter(config["mcpServers"]))
+        config = config["mcpServers"][first_key]
+    config.pop("active", None)
+    return config
 
-        self.name = None
-        self.active: bool = True
-        self.tools: List[mcp.Tool] = []
-        self.server_errlogs: List[str] = []
 
-    async def connect_to_server(self, mcp_server_config: dict, name: str):
-        """连接到 MCP 服务器
+async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
+    """快速测试 MCP 服务器可达性"""
+    import aiohttp
 
-        如果 `url` 参数存在：
-            1. 当 transport 指定为 `streamable_http` 时，使用 Streamable HTTP 连接方式。
-            1. 当 transport 指定为 `sse` 时，使用 SSE 连接方式。
-            2. 如果没有指定，默认使用 SSE 的方式连接到 MCP 服务。
+    cfg = _prepare_config(config.copy())
 
-        Args:
-            mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server
-        """
-        cfg = mcp_server_config.copy()
-        if "mcpServers" in cfg and len(cfg["mcpServers"]) > 0:
-            key_0 = list(cfg["mcpServers"].keys())[0]
-            cfg = cfg["mcpServers"][key_0]
-        cfg.pop("active", None)  # Remove active flag from config
+    url = cfg["url"]
+    headers = cfg.get("headers", {})
+    timeout = cfg.get("timeout", 10)
 
-        if "url" in cfg:
-            is_sse = True
+    try:
+        async with aiohttp.ClientSession() as session:
             if cfg.get("transport") == "streamable_http":
-                is_sse = False
-            if is_sse:
-                # SSE transport method
-                self._streams_context = sse_client(
-                    url=cfg["url"],
-                    headers=cfg.get("headers", {}),
-                    timeout=cfg.get("timeout", 5),
-                    sse_read_timeout=cfg.get("sse_read_timeout", 60 * 5),
-                )
-                streams = await self._streams_context.__aenter__()
-
-                # Create a new client session
-                self.session = await self.exit_stack.enter_async_context(
-                    mcp.ClientSession(*streams)
-                )
+                test_payload = {
+                    "jsonrpc": "2.0",
+                    "method": "initialize",
+                    "id": 0,
+                    "params": {
+                        "protocolVersion": "2024-11-05",
+                        "capabilities": {},
+                        "clientInfo": {"name": "test-client", "version": "1.2.3"},
+                    },
+                }
+                async with session.post(
+                    url,
+                    headers={
+                        **headers,
+                        "Content-Type": "application/json",
+                        "Accept": "application/json, text/event-stream",
+                    },
+                    json=test_payload,
+                    timeout=aiohttp.ClientTimeout(total=timeout),
+                ) as response:
+                    if response.status == 200:
+                        return True, ""
+                    else:
+                        return False, f"HTTP {response.status}: {response.reason}"
             else:
-                timeout = timedelta(seconds=cfg.get("timeout", 30))
-                sse_read_timeout = timedelta(
-                    seconds=cfg.get("sse_read_timeout", 60 * 5)
-                )
-                self._streams_context = streamablehttp_client(
-                    url=cfg["url"],
-                    headers=cfg.get("headers", {}),
-                    timeout=timeout,
-                    sse_read_timeout=sse_read_timeout,
-                    terminate_on_close=cfg.get("terminate_on_close", True),
-                )
-                read_s, write_s, _ = await self._streams_context.__aenter__()
+                async with session.get(
+                    url,
+                    headers={
+                        **headers,
+                        "Accept": "application/json, text/event-stream",
+                    },
+                    timeout=aiohttp.ClientTimeout(total=timeout),
+                ) as response:
+                    if response.status == 200:
+                        return True, ""
+                    else:
+                        return False, f"HTTP {response.status}: {response.reason}"
 
-                # Create a new client session
-                self.session = await self.exit_stack.enter_async_context(
-                    mcp.ClientSession(read_stream=read_s, write_stream=write_s)
-                )
-
-        else:
-            server_params = mcp.StdioServerParameters(
-                **cfg,
-            )
-
-            def callback(msg: str):
-                # 处理 MCP 服务的错误日志
-                self.server_errlogs.append(msg)
-
-            stdio_transport = await self.exit_stack.enter_async_context(
-                mcp.stdio_client(
-                    server_params,
-                    errlog=LogPipe(
-                        level=logging.ERROR,
-                        logger=logger,
-                        identifier=f"MCPServer-{name}",
-                        callback=callback,
-                    ),
-                ),
-            )
-
-            # Create a new client session
-            self.session = await self.exit_stack.enter_async_context(
-                mcp.ClientSession(*stdio_transport)
-            )
-
-        await self.session.initialize()
-
-    async def list_tools_and_save(self) -> mcp.ListToolsResult:
-        """List all tools from the server and save them to self.tools"""
-        response = await self.session.list_tools()
-        logger.debug(f"MCP server {self.name} list tools response: {response}")
-        self.tools = response.tools
-        return response
-
-    async def cleanup(self):
-        """Clean up resources"""
-        await self.exit_stack.aclose()
+    except asyncio.TimeoutError:
+        return False, f"连接超时: {timeout}秒"
+    except Exception as e:
+        return False, f"{e!s}"
 
 
-class FuncCall:
+class FunctionToolManager:
     def __init__(self) -> None:
         self.func_list: List[FuncTool] = []
-        """内部加载的 func tools"""
         self.mcp_client_dict: Dict[str, MCPClient] = {}
         """MCP 服务列表"""
-        self.mcp_service_queue = asyncio.Queue()
-        """用于外部控制 MCP 服务的启停"""
         self.mcp_client_event: Dict[str, asyncio.Event] = {}
 
     def empty(self) -> bool:
         return len(self.func_list) == 0
 
+    def spec_to_func(
+        self,
+        name: str,
+        func_args: list,
+        desc: str,
+        handler: Awaitable,
+    ) -> FuncTool:
+        params = {
+            "type": "object",  # hard-coded here
+            "properties": {},
+        }
+        for param in func_args:
+            params["properties"][param["name"]] = {
+                "type": param["type"],
+                "description": param["description"],
+            }
+        return FuncTool(
+            name=name,
+            parameters=params,
+            description=desc,
+            handler=handler,
+        )
+
     def add_func(
         self,
         name: str,
@@ -225,22 +144,14 @@ class FuncCall:
         # check if the tool has been added before
         self.remove_func(name)
 
-        params = {
-            "type": "object",  # hard-coded here
-            "properties": {},
-        }
-        for param in func_args:
-            params["properties"][param["name"]] = {
-                "type": param["type"],
-                "description": param["description"],
-            }
-        _func = FuncTool(
-            name=name,
-            parameters=params,
-            description=desc,
-            handler=handler,
+        self.func_list.append(
+            self.spec_to_func(
+                name=name,
+                func_args=func_args,
+                desc=desc,
+                handler=handler,
+            )
         )
-        self.func_list.append(_func)
         logger.info(f"添加函数调用工具: {name}")
 
     def remove_func(self, name: str) -> None:
@@ -252,13 +163,17 @@ class FuncCall:
                 self.func_list.pop(i)
                 break
 
-    def get_func(self, name) -> FuncTool:
+    def get_func(self, name) -> FuncTool | None:
         for f in self.func_list:
             if f.name == name:
                 return f
-        return None
 
-    async def _init_mcp_clients(self) -> None:
+    def get_full_tool_set(self) -> ToolSet:
+        """获取完整工具集"""
+        tool_set = ToolSet(self.func_list.copy())
+        return tool_set
+
+    async def init_mcp_clients(self) -> None:
         """从项目根目录读取 mcp_server.json 文件，初始化 MCP 服务列表。文件格式如下：
         ```
         {
@@ -300,113 +215,64 @@ class FuncCall:
                 )
                 self.mcp_client_event[name] = event
 
-    async def mcp_service_selector(self):
-        """为了避免在不同异步任务中控制 MCP 服务导致的报错，整个项目统一通过这个 Task 来控制
-
-        使用 self.mcp_service_queue.put_nowait() 来控制 MCP 服务的启停，数据格式如下：
-
-        {"type": "init"} 初始化所有MCP客户端
-
-        {"type": "init", "name": "mcp_server_name", "cfg": {...}} 初始化指定的MCP客户端
-
-        {"type": "terminate"} 终止所有MCP客户端
-
-        {"type": "terminate", "name": "mcp_server_name"} 终止指定的MCP客户端
-        """
-        while True:
-            data = await self.mcp_service_queue.get()
-            if data["type"] == "init":
-                if "name" in data:
-                    event = asyncio.Event()
-                    asyncio.create_task(
-                        self._init_mcp_client_task_wrapper(
-                            data["name"], data["cfg"], event
-                        )
-                    )
-                    self.mcp_client_event[data["name"]] = event
-                else:
-                    await self._init_mcp_clients()
-            elif data["type"] == "terminate":
-                if "name" in data:
-                    # await self._terminate_mcp_client(data["name"])
-                    if data["name"] in self.mcp_client_event:
-                        self.mcp_client_event[data["name"]].set()
-                        self.mcp_client_event.pop(data["name"], None)
-                        self.func_list = [
-                            f
-                            for f in self.func_list
-                            if not (
-                                f.origin == "mcp" and f.mcp_server_name == data["name"]
-                            )
-                        ]
-                else:
-                    for name in self.mcp_client_dict.keys():
-                        # await self._terminate_mcp_client(name)
-                        # self.mcp_client_event[name].set()
-                        if name in self.mcp_client_event:
-                            self.mcp_client_event[name].set()
-                            self.mcp_client_event.pop(name, None)
-                    self.func_list = [f for f in self.func_list if f.origin != "mcp"]
-
     async def _init_mcp_client_task_wrapper(
-        self, name: str, cfg: dict, event: asyncio.Event
+        self,
+        name: str,
+        cfg: dict,
+        event: asyncio.Event,
+        ready_future: asyncio.Future = None,
     ) -> None:
         """初始化 MCP 客户端的包装函数，用于捕获异常"""
         try:
             await self._init_mcp_client(name, cfg)
+            tools = await self.mcp_client_dict[name].list_tools_and_save()
+            if ready_future and not ready_future.done():
+                # tell the caller we are ready
+                ready_future.set_result(tools)
             await event.wait()
             logger.info(f"收到 MCP 客户端 {name} 终止信号")
-            await self._terminate_mcp_client(name)
         except Exception as e:
-            import traceback
-
-            traceback.print_exc()
-            logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
+            logger.error(f"初始化 MCP 客户端 {name} 失败", exc_info=True)
+            if ready_future and not ready_future.done():
+                ready_future.set_exception(e)
+        finally:
+            # 无论如何都能清理
+            await self._terminate_mcp_client(name)
 
     async def _init_mcp_client(self, name: str, config: dict) -> None:
         """初始化单个MCP客户端"""
-        try:
-            # 先清理之前的客户端，如果存在
-            if name in self.mcp_client_dict:
-                await self._terminate_mcp_client(name)
+        # 先清理之前的客户端，如果存在
+        if name in self.mcp_client_dict:
+            await self._terminate_mcp_client(name)
 
-            mcp_client = MCPClient()
-            mcp_client.name = name
-            self.mcp_client_dict[name] = mcp_client
-            await mcp_client.connect_to_server(config, name)
-            tools_res = await mcp_client.list_tools_and_save()
-            tool_names = [tool.name for tool in tools_res.tools]
+        mcp_client = MCPClient()
+        mcp_client.name = name
+        self.mcp_client_dict[name] = mcp_client
+        await mcp_client.connect_to_server(config, name)
+        tools_res = await mcp_client.list_tools_and_save()
+        logger.debug(f"MCP server {name} list tools response: {tools_res}")
+        tool_names = [tool.name for tool in tools_res.tools]
 
-            # 移除该MCP服务之前的工具（如有）
-            self.func_list = [
-                f
-                for f in self.func_list
-                if not (f.origin == "mcp" and f.mcp_server_name == name)
-            ]
+        # 移除该MCP服务之前的工具（如有）
+        self.func_list = [
+            f
+            for f in self.func_list
+            if not (f.origin == "mcp" and f.mcp_server_name == name)
+        ]
 
-            # 将 MCP 工具转换为 FuncTool 并添加到 func_list
-            for tool in mcp_client.tools:
-                func_tool = FuncTool(
-                    name=tool.name,
-                    parameters=tool.inputSchema,
-                    description=tool.description,
-                    origin="mcp",
-                    mcp_server_name=name,
-                    mcp_client=mcp_client,
-                )
-                self.func_list.append(func_tool)
+        # 将 MCP 工具转换为 FuncTool 并添加到 func_list
+        for tool in mcp_client.tools:
+            func_tool = FuncTool(
+                name=tool.name,
+                parameters=tool.inputSchema,
+                description=tool.description,
+                origin="mcp",
+                mcp_server_name=name,
+                mcp_client=mcp_client,
+            )
+            self.func_list.append(func_tool)
 
-            logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
-            return
-        except Exception as e:
-            import traceback
-
-            logger.error(traceback.format_exc())
-            logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
-            # 发生错误时确保客户端被清理
-            if name in self.mcp_client_dict:
-                await self._terminate_mcp_client(name)
-            return
+        logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
 
     async def _terminate_mcp_client(self, name: str) -> None:
         """关闭并清理MCP客户端"""
@@ -414,9 +280,9 @@ class FuncCall:
             try:
                 # 关闭MCP连接
                 await self.mcp_client_dict[name].cleanup()
-                del self.mcp_client_dict[name]
+                self.mcp_client_dict.pop(name)
             except Exception as e:
-                logger.info(f"清空 MCP 客户端资源 {name}: {e}。")
+                logger.error(f"清空 MCP 客户端资源 {name}: {e}。")
             # 移除关联的FuncTool
             self.func_list = [
                 f
@@ -425,204 +291,273 @@ class FuncCall:
             ]
             logger.info(f"已关闭 MCP 服务 {name}")
 
+    @staticmethod
+    async def test_mcp_server_connection(config: dict) -> list[str]:
+        if "url" in config:
+            success, error_msg = await _quick_test_mcp_connection(config)
+            if not success:
+                raise Exception(error_msg)
+
+        mcp_client = MCPClient()
+        try:
+            logger.debug(f"testing MCP server connection with config: {config}")
+            await mcp_client.connect_to_server(config, "test")
+            tools_res = await mcp_client.list_tools_and_save()
+            tool_names = [tool.name for tool in tools_res.tools]
+        finally:
+            logger.debug("Cleaning up MCP client after testing connection.")
+            await mcp_client.cleanup()
+        return tool_names
+
+    async def enable_mcp_server(
+        self,
+        name: str,
+        config: dict,
+        event: asyncio.Event | None = None,
+        ready_future: asyncio.Future | None = None,
+        timeout: int = 30,
+    ) -> None:
+        """Enable_mcp_server a new MCP server to the manager and initialize it.
+
+        Args:
+            name (str): The name of the MCP server.
+            config (dict): Configuration for the MCP server.
+            event (asyncio.Event): Event to signal when the MCP client is ready.
+            ready_future (asyncio.Future): Future to signal when the MCP client is ready.
+            timeout (int): Timeout for the initialization.
+        Raises:
+            TimeoutError: If the initialization does not complete within the specified timeout.
+            Exception: If there is an error during initialization.
+        """
+        if not event:
+            event = asyncio.Event()
+        if not ready_future:
+            ready_future = asyncio.Future()
+        if name in self.mcp_client_dict:
+            return
+        asyncio.create_task(
+            self._init_mcp_client_task_wrapper(name, config, event, ready_future)
+        )
+        try:
+            await asyncio.wait_for(ready_future, timeout=timeout)
+        finally:
+            self.mcp_client_event[name] = event
+
+        if ready_future.done() and ready_future.exception():
+            exc = ready_future.exception()
+            if exc is not None:
+                raise exc
+
+    async def disable_mcp_server(
+        self, name: str | None = None, timeout: float = 10
+    ) -> None:
+        """Disable an MCP server by its name.
+
+        Args:
+            name (str): The name of the MCP server to disable. If None, ALL MCP servers will be disabled.
+            timeout (int): Timeout.
+        """
+        if name:
+            if name not in self.mcp_client_event:
+                return
+            client = self.mcp_client_dict.get(name)
+            self.mcp_client_event[name].set()
+            if not client:
+                return
+            client_running_event = client.running_event
+            try:
+                await asyncio.wait_for(client_running_event.wait(), timeout=timeout)
+            finally:
+                self.mcp_client_event.pop(name, None)
+                self.func_list = [
+                    f
+                    for f in self.func_list
+                    if f.origin != "mcp" or f.mcp_server_name != name
+                ]
+        else:
+            running_events = [
+                client.running_event.wait() for client in self.mcp_client_dict.values()
+            ]
+            for key, event in self.mcp_client_event.items():
+                event.set()
+            # waiting for all clients to finish
+            try:
+                await asyncio.wait_for(asyncio.gather(*running_events), timeout=timeout)
+            finally:
+                self.mcp_client_event.clear()
+                self.mcp_client_dict.clear()
+                self.func_list = [f for f in self.func_list if f.origin != "mcp"]
+
     def get_func_desc_openai_style(self, omit_empty_parameter_field=False) -> list:
         """
         获得 OpenAI API 风格的**已经激活**的工具描述
         """
-        _l = []
-        # 处理所有工具（包括本地和MCP工具）
-        for f in self.func_list:
-            if not f.active:
-                continue
-            func_ = {
-                "type": "function",
-                "function": {
-                    "name": f.name,
-                    # "parameters": f.parameters,
-                    "description": f.description,
-                },
-            }
-            func_["function"]["parameters"] = f.parameters
-            if not f.parameters.get("properties") and omit_empty_parameter_field:
-                # 如果 properties 为空，并且 omit_empty_parameter_field 为 True，则删除 parameters 字段
-                del func_["function"]["parameters"]
-            _l.append(func_)
-        return _l
+        tools = [f for f in self.func_list if f.active]
+        toolset = ToolSet(tools)
+        return toolset.openai_schema(
+            omit_empty_parameter_field=omit_empty_parameter_field
+        )
 
     def get_func_desc_anthropic_style(self) -> list:
         """
         获得 Anthropic API 风格的**已经激活**的工具描述
         """
-        tools = []
-        for f in self.func_list:
-            if not f.active:
-                continue
-
-            # Convert internal format to Anthropic style
-            tool = {
-                "name": f.name,
-                "description": f.description,
-                "input_schema": {
-                    "type": "object",
-                    "properties": f.parameters.get("properties", {}),
-                    # Keep the required field from the original parameters if it exists
-                    "required": f.parameters.get("required", []),
-                },
-            }
-            tools.append(tool)
-        return tools
+        tools = [f for f in self.func_list if f.active]
+        toolset = ToolSet(tools)
+        return toolset.anthropic_schema()
 
     def get_func_desc_google_genai_style(self) -> dict:
         """
         获得 Google GenAI API 风格的**已经激活**的工具描述
         """
+        tools = [f for f in self.func_list if f.active]
+        toolset = ToolSet(tools)
+        return toolset.google_schema()
 
-        # Gemini API 支持的数据类型和格式
-        supported_types = {
-            "string",
-            "number",
-            "integer",
-            "boolean",
-            "array",
-            "object",
-            "null",
-        }
-        supported_formats = {
-            "string": {"enum", "date-time"},
-            "integer": {"int32", "int64"},
-            "number": {"float", "double"},
-        }
+    def deactivate_llm_tool(self, name: str) -> bool:
+        """停用一个已经注册的函数调用工具。
 
-        def convert_schema(schema: dict) -> dict:
-            """转换 schema 为 Gemini API 格式"""
+        Returns:
+            如果没找到，会返回 False"""
+        func_tool = self.get_func(name)
+        if func_tool is not None:
+            func_tool.active = False
 
-            # 如果 schema 包含 anyOf，则只返回 anyOf 字段
-            if "anyOf" in schema:
-                return {"anyOf": [convert_schema(s) for s in schema["anyOf"]]}
-
-            result = {}
-
-            if "type" in schema and schema["type"] in supported_types:
-                result["type"] = schema["type"]
-                if "format" in schema and schema["format"] in supported_formats.get(
-                    result["type"], set()
-                ):
-                    result["format"] = schema["format"]
-            else:
-                # 暂时指定默认为null
-                result["type"] = "null"
-
-            support_fields = {
-                "title",
-                "description",
-                "enum",
-                "minimum",
-                "maximum",
-                "maxItems",
-                "minItems",
-                "nullable",
-                "required",
-            }
-            result.update({k: schema[k] for k in support_fields if k in schema})
-
-            if "properties" in schema:
-                properties = {}
-                for key, value in schema["properties"].items():
-                    prop_value = convert_schema(value)
-                    if "default" in prop_value:
-                        del prop_value["default"]
-                    properties[key] = prop_value
-
-                if properties:  # 只在有非空属性时添加
-                    result["properties"] = properties
-
-            if "items" in schema:
-                result["items"] = convert_schema(schema["items"])
-
-            return result
-
-        tools = [
-            {
-                "name": f.name,
-                "description": f.description,
-                **({"parameters": convert_schema(f.parameters)}),
-            }
-            for f in self.func_list
-            if f.active
-        ]
-
-        declarations = {}
-        if tools:
-            declarations["function_declarations"] = tools
-        return declarations
-
-    async def func_call(self, question: str, session_id: str, provider) -> tuple:
-        _l = []
-        for f in self.func_list:
-            if not f.active:
-                continue
-            _l.append(
-                {
-                    "name": f.name,
-                    "parameters": f.parameters,
-                    "description": f.description,
-                }
+            inactivated_llm_tools: list = sp.get(
+                "inactivated_llm_tools", [], scope="global", scope_id="global"
             )
-        func_definition = json.dumps(_l, ensure_ascii=False)
+            if name not in inactivated_llm_tools:
+                inactivated_llm_tools.append(name)
+                sp.put(
+                    "inactivated_llm_tools",
+                    inactivated_llm_tools,
+                    scope="global",
+                    scope_id="global",
+                )
 
-        prompt = textwrap.dedent(f"""
-            ROLE:
-            你是一个 Function calling AI Agent, 你的任务是将用户的提问转化为函数调用。
+            return True
+        return False
 
-            TOOLS:
-            可用的函数列表:
+    # 因为不想解决循环引用，所以这里直接传入 star_map 先了...
+    def activate_llm_tool(self, name: str, star_map: dict) -> bool:
+        func_tool = self.get_func(name)
+        if func_tool is not None:
+            if func_tool.handler_module_path in star_map:
+                if not star_map[func_tool.handler_module_path].activated:
+                    raise ValueError(
+                        f"此函数调用工具所属的插件 {star_map[func_tool.handler_module_path].name} 已被禁用，请先在管理面板启用再激活此工具。"
+                    )
 
-            {func_definition}
+            func_tool.active = True
 
-            LIMIT:
-            1. 你返回的内容应当能够被 Python 的 json 模块解析的 Json 格式字符串。
-            2. 你的 Json 返回的格式如下：`[{{"name": "<func_name>", "args": <arg_dict>}}, ...]`。参数根据上面提供的函数列表中的参数来填写。
-            3. 允许必要时返回多个函数调用，但需保证这些函数调用的顺序正确。
-            4. 如果用户的提问中不需要用到给定的函数，请直接返回 `{{"res": False}}`。
+            inactivated_llm_tools: list = sp.get(
+                "inactivated_llm_tools", [], scope="global", scope_id="global"
+            )
+            if name in inactivated_llm_tools:
+                inactivated_llm_tools.remove(name)
+                sp.put(
+                    "inactivated_llm_tools",
+                    inactivated_llm_tools,
+                    scope="global",
+                    scope_id="global",
+                )
 
-            EXAMPLE:
-            1. `用户提问`：请问一下天气怎么样？ `函数调用`：[{{"name": "get_weather", "args": {{"city": "北京"}}}}]
+            return True
+        return False
 
-            用户的提问是：{question}
-        """)
+    @property
+    def mcp_config_path(self):
+        data_dir = get_astrbot_data_path()
+        return os.path.join(data_dir, "mcp_server.json")
 
-        _c = 0
-        while _c < 3:
-            try:
-                res = await provider.text_chat(prompt, session_id)
-                if res.find("```") != -1:
-                    res = res[res.find("```json") + 7 : res.rfind("```")]
-                res = json.loads(res)
-                break
-            except Exception as e:
-                _c += 1
-                if _c == 3:
-                    raise e
-                if "The message you submitted was too long" in str(e):
-                    raise e
+    def load_mcp_config(self):
+        if not os.path.exists(self.mcp_config_path):
+            # 配置文件不存在，创建默认配置
+            os.makedirs(os.path.dirname(self.mcp_config_path), exist_ok=True)
+            with open(self.mcp_config_path, "w", encoding="utf-8") as f:
+                json.dump(DEFAULT_MCP_CONFIG, f, ensure_ascii=False, indent=4)
+            return DEFAULT_MCP_CONFIG
 
-        if "res" in res and not res["res"]:
-            return "", False
+        try:
+            with open(self.mcp_config_path, "r", encoding="utf-8") as f:
+                return json.load(f)
+        except Exception as e:
+            logger.error(f"加载 MCP 配置失败: {e}")
+            return DEFAULT_MCP_CONFIG
 
-        tool_call_result = []
-        for tool in res:
-            # 说明有函数调用
-            func_name = tool["name"]
-            args = tool["args"]
-            # 调用函数
-            func_tool = self.get_func(func_name)
-            if not func_tool:
-                raise Exception(f"Request function {func_name} not found.")
+    def save_mcp_config(self, config: dict):
+        try:
+            with open(self.mcp_config_path, "w", encoding="utf-8") as f:
+                json.dump(config, f, ensure_ascii=False, indent=4)
+            return True
+        except Exception as e:
+            logger.error(f"保存 MCP 配置失败: {e}")
+            return False
 
-            ret = await func_tool.execute(**args)
-            if ret:
-                tool_call_result.append(str(ret))
-        return tool_call_result, True
+    async def sync_modelscope_mcp_servers(self, access_token: str) -> None:
+        """从 ModelScope 平台同步 MCP 服务器配置"""
+        base_url = "https://www.modelscope.cn/openapi/v1"
+        url = f"{base_url}/mcp/servers/operational"
+        headers = {
+            "Authorization": f"Bearer {access_token.strip()}",
+            "Content-Type": "application/json",
+        }
+
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.get(url, headers=headers) as response:
+                    if response.status == 200:
+                        data = await response.json()
+                        mcp_server_list = data.get("data", {}).get(
+                            "mcp_server_list", []
+                        )
+                        local_mcp_config = self.load_mcp_config()
+
+                        synced_count = 0
+                        for server in mcp_server_list:
+                            server_name = server["name"]
+                            operational_urls = server.get("operational_urls", [])
+                            if not operational_urls:
+                                continue
+                            url_info = operational_urls[0]
+                            server_url = url_info.get("url")
+                            if not server_url:
+                                continue
+                            # 添加到配置中(同名会覆盖)
+                            local_mcp_config["mcpServers"][server_name] = {
+                                "url": server_url,
+                                "transport": "sse",
+                                "active": True,
+                                "provider": "modelscope",
+                            }
+                            synced_count += 1
+
+                        if synced_count > 0:
+                            self.save_mcp_config(local_mcp_config)
+                            tasks = []
+                            for server in mcp_server_list:
+                                name = server["name"]
+                                tasks.append(
+                                    self.enable_mcp_server(
+                                        name=name,
+                                        config=local_mcp_config["mcpServers"][name],
+                                    )
+                                )
+                            await asyncio.gather(*tasks)
+                            logger.info(
+                                f"从 ModelScope 同步了 {synced_count} 个 MCP 服务器"
+                            )
+                        else:
+                            logger.warning("没有找到可用的 ModelScope MCP 服务器")
+                    else:
+                        raise Exception(
+                            f"ModelScope API 请求失败: HTTP {response.status}"
+                        )
+
+        except aiohttp.ClientError as e:
+            raise Exception(f"网络连接错误: {str(e)}")
+        except Exception as e:
+            raise Exception(f"同步 ModelScope MCP 服务器时发生错误: {str(e)}")
 
     def __str__(self):
         return str(self.func_list)
@@ -630,7 +565,6 @@ class FuncCall:
     def __repr__(self):
         return str(self.func_list)
 
-    async def terminate(self):
-        for name in self.mcp_client_dict.keys():
-            await self._terminate_mcp_client(name)
-            logger.debug(f"清理 MCP 客户端 {name} 资源")
+
+# alias
+FuncCall = FunctionToolManager

astrbot/core/provider/manager.py

@@ -1,89 +1,34 @@
-import traceback
 import asyncio
-from astrbot.core.config.astrbot_config import AstrBotConfig
-from .provider import Provider, STTProvider, TTSProvider, Personality
-from .entities import ProviderType
+import traceback
 from typing import List
-from astrbot.core.db import BaseDatabase
-from .register import provider_cls_map, llm_tools
+
 from astrbot.core import logger, sp
+from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
+from astrbot.core.db import BaseDatabase
+
+from .entities import ProviderType
+from .provider import Provider, STTProvider, TTSProvider, EmbeddingProvider
+from .register import llm_tools, provider_cls_map
+from ..persona_mgr import PersonaManager
 
 
 class ProviderManager:
-    def __init__(self, config: AstrBotConfig, db_helper: BaseDatabase):
+    def __init__(
+        self,
+        acm: AstrBotConfigManager,
+        db_helper: BaseDatabase,
+        persona_mgr: PersonaManager,
+    ):
+        self.persona_mgr = persona_mgr
+        self.acm = acm
+        config = acm.confs["default"]
         self.providers_config: List = config["provider"]
         self.provider_settings: dict = config["provider_settings"]
         self.provider_stt_settings: dict = config.get("provider_stt_settings", {})
         self.provider_tts_settings: dict = config.get("provider_tts_settings", {})
-        self.persona_configs: list = config.get("persona", [])
-        self.astrbot_config = config
 
-        # 人格情景管理
-        # 目前没有拆成独立的模块
-        self.default_persona_name = self.provider_settings.get(
-            "default_personality", "default"
-        )
-        self.personas: List[Personality] = []
-        self.selected_default_persona = None
-        for persona in self.persona_configs:
-            begin_dialogs = persona.get("begin_dialogs", [])
-            mood_imitation_dialogs = persona.get("mood_imitation_dialogs", [])
-            bd_processed = []
-            mid_processed = ""
-            if begin_dialogs:
-                if len(begin_dialogs) % 2 != 0:
-                    logger.error(
-                        f"{persona['name']} 人格情景预设对话格式不对，条数应该为偶数。"
-                    )
-                    begin_dialogs = []
-                user_turn = True
-                for dialog in begin_dialogs:
-                    bd_processed.append(
-                        {
-                            "role": "user" if user_turn else "assistant",
-                            "content": dialog,
-                            "_no_save": None,  # 不持久化到 db
-                        }
-                    )
-                    user_turn = not user_turn
-            if mood_imitation_dialogs:
-                if len(mood_imitation_dialogs) % 2 != 0:
-                    logger.error(
-                        f"{persona['name']} 对话风格对话格式不对，条数应该为偶数。"
-                    )
-                    mood_imitation_dialogs = []
-                user_turn = True
-                for dialog in mood_imitation_dialogs:
-                    role = "A" if user_turn else "B"
-                    mid_processed += f"{role}: {dialog}\n"
-                    if not user_turn:
-                        mid_processed += "\n"
-                    user_turn = not user_turn
-
-            try:
-                persona = Personality(
-                    **persona,
-                    _begin_dialogs_processed=bd_processed,
-                    _mood_imitation_dialogs_processed=mid_processed,
-                )
-                if persona["name"] == self.default_persona_name:
-                    self.selected_default_persona = persona
-                self.personas.append(persona)
-            except Exception as e:
-                logger.error(f"解析 Persona 配置失败：{e}")
-
-        if not self.selected_default_persona and len(self.personas) > 0:
-            # 默认选择第一个
-            self.selected_default_persona = self.personas[0]
-
-        if not self.selected_default_persona:
-            self.selected_default_persona = Personality(
-                prompt="You are a helpful and friendly assistant.",
-                name="default",
-                _begin_dialogs_processed=[],
-                _mood_imitation_dialogs_processed="",
-            )
-            self.personas.append(self.selected_default_persona)
+        # 人格相关属性，v4.0.0 版本后被废弃，推荐使用 PersonaManager
+        self.default_persona_name = persona_mgr.default_persona
 
         self.provider_insts: List[Provider] = []
         """加载的 Provider 的实例"""
@@ -91,53 +36,118 @@ class ProviderManager:
         """加载的 Speech To Text Provider 的实例"""
         self.tts_provider_insts: List[TTSProvider] = []
         """加载的 Text To Speech Provider 的实例"""
-        self.embedding_provider_insts: List[Provider] = []
+        self.embedding_provider_insts: List[EmbeddingProvider] = []
         """加载的 Embedding Provider 的实例"""
-        self.inst_map = {}
+        self.inst_map: dict[str, Provider] = {}
         """Provider 实例映射. key: provider_id, value: Provider 实例"""
         self.llm_tools = llm_tools
 
-        self.curr_provider_inst: Provider = None
-        """默认的 Provider 实例"""
-        self.curr_stt_provider_inst: STTProvider = None
-        """默认的 Speech To Text Provider 实例"""
-        self.curr_tts_provider_inst: TTSProvider = None
-        """默认的 Text To Speech Provider 实例"""
+        self.curr_provider_inst: Provider | None = None
+        """默认的 Provider 实例。已弃用，请使用 get_using_provider() 方法获取当前使用的 Provider 实例。"""
+        self.curr_stt_provider_inst: STTProvider | None = None
+        """默认的 Speech To Text Provider 实例。已弃用，请使用 get_using_provider() 方法获取当前使用的 Provider 实例。"""
+        self.curr_tts_provider_inst: TTSProvider | None = None
+        """默认的 Text To Speech Provider 实例。已弃用，请使用 get_using_provider() 方法获取当前使用的 Provider 实例。"""
         self.db_helper = db_helper
 
-        # kdb(experimental)
-        self.curr_kdb_name = ""
-        kdb_cfg = config.get("knowledge_db", {})
-        if kdb_cfg and len(kdb_cfg):
-            self.curr_kdb_name = list(kdb_cfg.keys())[0]
+    @property
+    def persona_configs(self) -> list:
+        """动态获取最新的 persona 配置"""
+        return self.persona_mgr.persona_v3_config
+
+    @property
+    def personas(self) -> list:
+        """动态获取最新的 personas 列表"""
+        return self.persona_mgr.personas_v3
+
+    @property
+    def selected_default_persona(self):
+        """动态获取最新的默认选中 persona。已弃用，请使用 context.persona_mgr.get_default_persona_v3()"""
+        return self.persona_mgr.selected_default_persona_v3
 
     async def set_provider(
-        self, provider_id: str, provider_type: ProviderType, umo: str = None
+        self, provider_id: str, provider_type: ProviderType, umo: str | None = None
     ):
         """设置提供商。
 
         Args:
             provider_id (str): 提供商 ID。
             provider_type (ProviderType): 提供商类型。
-            umo (str, optional): 用户会话 ID，用于提供商会话隔离。当用户启用了提供商会话隔离时此参数才生效。
+            umo (str, optional): 用户会话 ID，用于提供商会话隔离。
+
+        Version 4.0.0: 这个版本下已经默认隔离提供商
         """
         if provider_id not in self.inst_map:
             raise ValueError(f"提供商 {provider_id} 不存在，无法设置。")
-        if umo and self.provider_settings["separate_provider"]:
-            perf = sp.get("session_provider_perf", {})
-            session_perf = perf.get(umo, {})
-            session_perf[provider_type.value] = provider_id
-            perf[umo] = session_perf
-            sp.put("session_provider_perf", perf)
+        if umo:
+            await sp.session_put(
+                umo,
+                f"provider_perf_{provider_type.value}",
+                provider_id,
+            )
             return
         # 不启用提供商会话隔离模式的情况
         self.curr_provider_inst = self.inst_map[provider_id]
         if provider_type == ProviderType.TEXT_TO_SPEECH:
-            sp.put("curr_provider_tts", provider_id)
+            sp.put("curr_provider_tts", provider_id, scope="global", scope_id="global")
         elif provider_type == ProviderType.SPEECH_TO_TEXT:
-            sp.put("curr_provider_stt", provider_id)
+            sp.put("curr_provider_stt", provider_id, scope="global", scope_id="global")
         elif provider_type == ProviderType.CHAT_COMPLETION:
-            sp.put("curr_provider", provider_id)
+            sp.put("curr_provider", provider_id, scope="global", scope_id="global")
+
+    async def get_provider_by_id(self, provider_id: str) -> Provider | None:
+        """根据提供商 ID 获取提供商实例"""
+        return self.inst_map.get(provider_id)
+
+    def get_using_provider(self, provider_type: ProviderType, umo=None):
+        """获取正在使用的提供商实例。
+
+        Args:
+            provider_type (ProviderType): 提供商类型。
+            umo (str, optional): 用户会话 ID，用于提供商会话隔离。
+
+        Returns:
+            Provider: 正在使用的提供商实例。
+        """
+        provider = None
+        if umo:
+            provider_id = sp.get(
+                f"provider_perf_{provider_type.value}",
+                None,
+                scope="umo",
+                scope_id=umo,
+            )
+            if provider_id:
+                provider = self.inst_map.get(provider_id)
+        if not provider:
+            # default setting
+            config = self.acm.get_conf(umo)
+            if provider_type == ProviderType.CHAT_COMPLETION:
+                provider_id = config["provider_settings"].get("default_provider_id")
+                provider = self.inst_map.get(provider_id)
+                if not provider:
+                    provider = self.provider_insts[0] if self.provider_insts else None
+            elif provider_type == ProviderType.SPEECH_TO_TEXT:
+                provider_id = config["provider_stt_settings"].get("provider_id")
+                if not provider_id:
+                    return None
+                provider = self.inst_map.get(provider_id)
+                if not provider:
+                    provider = (
+                        self.stt_provider_insts[0] if self.stt_provider_insts else None
+                    )
+            elif provider_type == ProviderType.TEXT_TO_SPEECH:
+                provider_id = config["provider_tts_settings"].get("provider_id")
+                if not provider_id:
+                    return None
+                provider = self.inst_map.get(provider_id)
+                if not provider:
+                    provider = (
+                        self.tts_provider_insts[0] if self.tts_provider_insts else None
+                    )
+            else:
+                raise ValueError(f"Unknown provider type: {provider_type}")
+        return provider
 
     async def initialize(self):
         # 逐个初始化提供商
@@ -145,29 +155,38 @@ class ProviderManager:
             await self.load_provider(provider_config)
 
         # 设置默认提供商
-        self.curr_provider_inst = self.inst_map.get(
-            self.provider_settings.get("default_provider_id")
+        selected_provider_id = sp.get(
+            "curr_provider",
+            self.provider_settings.get("default_provider_id"),
+            scope="global",
+            scope_id="global",
         )
+        selected_stt_provider_id = sp.get(
+            "curr_provider_stt",
+            self.provider_stt_settings.get("provider_id"),
+            scope="global",
+            scope_id="global",
+        )
+        selected_tts_provider_id = sp.get(
+            "curr_provider_tts",
+            self.provider_tts_settings.get("provider_id"),
+            scope="global",
+            scope_id="global",
+        )
+        self.curr_provider_inst = self.inst_map.get(selected_provider_id)
         if not self.curr_provider_inst and self.provider_insts:
             self.curr_provider_inst = self.provider_insts[0]
 
-        self.curr_stt_provider_inst = self.inst_map.get(
-            self.provider_stt_settings.get("provider_id")
-        )
+        self.curr_stt_provider_inst = self.inst_map.get(selected_stt_provider_id)
         if not self.curr_stt_provider_inst and self.stt_provider_insts:
             self.curr_stt_provider_inst = self.stt_provider_insts[0]
 
-        self.curr_tts_provider_inst = self.inst_map.get(
-            self.provider_tts_settings.get("provider_id")
-        )
+        self.curr_tts_provider_inst = self.inst_map.get(selected_tts_provider_id)
         if not self.curr_tts_provider_inst and self.tts_provider_insts:
             self.curr_tts_provider_inst = self.tts_provider_insts[0]
 
         # 初始化 MCP Client 连接
-        asyncio.create_task(
-            self.llm_tools.mcp_service_selector(), name="mcp-service-handler"
-        )
-        self.llm_tools.mcp_service_queue.put_nowait({"type": "init"})
+        asyncio.create_task(self.llm_tools.init_mcp_clients(), name="init_mcp_clients")
 
     async def load_provider(self, provider_config: dict):
         if not provider_config["enable"]:
@@ -190,11 +209,6 @@ class ProviderManager:
                     from .sources.anthropic_source import (
                         ProviderAnthropic as ProviderAnthropic,
                     )
-                case "llm_tuner":
-                    logger.info("加载 LLM Tuner 工具 ...")
-                    from .sources.llmtuner_source import (
-                        LLMTunerModelLoader as LLMTunerModelLoader,
-                    )
                 case "dify":
                     from .sources.dify_source import ProviderDify as ProviderDify
                 case "dashscope":
@@ -253,6 +267,10 @@ class ProviderManager:
                     from .sources.volcengine_tts import (
                         ProviderVolcengineTTS as ProviderVolcengineTTS,
                     )
+                case "gemini_tts":
+                    from .sources.gemini_tts_source import (
+                        ProviderGeminiTTSAPI as ProviderGeminiTTSAPI,
+                    )
                 case "openai_embedding":
                     from .sources.openai_embedding_source import (
                         OpenAIEmbeddingProvider as OpenAIEmbeddingProvider,
@@ -261,6 +279,10 @@ class ProviderManager:
                     from .sources.gemini_embedding_source import (
                         GeminiEmbeddingProvider as GeminiEmbeddingProvider,
                     )
+                case "vllm_rerank":
+                    from .sources.vllm_rerank_source import (
+                        VLLMRerankProvider as VLLMRerankProvider,
+                    )
         except (ImportError, ModuleNotFoundError) as e:
             logger.critical(
                 f"加载 {provider_config['type']}({provider_config['id']}) 提供商适配器失败：{e}。可能是因为有未安装的依赖。"
@@ -326,8 +348,6 @@ class ProviderManager:
                 inst = provider_metadata.cls_type(
                     provider_config,
                     self.provider_settings,
-                    self.db_helper,
-                    self.provider_settings.get("persistant_history", True),
                     self.selected_default_persona,
                 )
 
@@ -346,7 +366,7 @@ class ProviderManager:
                 if not self.curr_provider_inst:
                     self.curr_provider_inst = inst
 
-            elif provider_metadata.provider_type == ProviderType.EMBEDDING:
+            elif provider_metadata.provider_type in [ProviderType.EMBEDDING, ProviderType.RERANK]:
                 inst = provider_metadata.cls_type(
                     provider_config, self.provider_settings
                 )
@@ -420,7 +440,7 @@ class ProviderManager:
                 self.curr_tts_provider_inst = None
 
             if getattr(self.inst_map[provider_id], "terminate", None):
-                await self.inst_map[provider_id].terminate()
+                await self.inst_map[provider_id].terminate()  # type: ignore
 
             logger.info(
                 f"{provider_id} 提供商适配器已终止({len(self.provider_insts)}, {len(self.stt_provider_insts)}, {len(self.tts_provider_insts)})"
@@ -430,6 +450,8 @@ class ProviderManager:
     async def terminate(self):
         for provider_inst in self.provider_insts:
             if hasattr(provider_inst, "terminate"):
-                await provider_inst.terminate()
-        # 清理 MCP Client 连接
-        await self.llm_tools.mcp_service_queue.put({"type": "terminate"})
+                await provider_inst.terminate()  # type: ignore
+        try:
+            await self.llm_tools.disable_mcp_server()
+        except Exception:
+            logger.error("Error while disabling MCP servers", exc_info=True)

astrbot/core/provider/provider.py

@@ -1,28 +1,24 @@
 import abc
 from typing import List
-from astrbot.core.db import BaseDatabase
-from typing import TypedDict, AsyncGenerator
-from astrbot.core.provider.func_tool_manager import FuncCall
-from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
+from typing import AsyncGenerator
+from astrbot.core.agent.tool import ToolSet
+from astrbot.core.provider.entities import (
+    LLMResponse,
+    ToolCallsResult,
+    ProviderType,
+    RerankResult,
+)
+from astrbot.core.provider.register import provider_cls_map
+from astrbot.core.db.po import Personality
 from dataclasses import dataclass
 
 
-class Personality(TypedDict):
-    prompt: str = ""
-    name: str = ""
-    begin_dialogs: List[str] = []
-    mood_imitation_dialogs: List[str] = []
-
-    # cache
-    _begin_dialogs_processed: List[dict] = []
-    _mood_imitation_dialogs_processed: str = ""
-
-
 @dataclass
 class ProviderMeta:
     id: str
     model: str
     type: str
+    provider_type: ProviderType
 
 
 class AbstractProvider(abc.ABC):
@@ -41,10 +37,14 @@ class AbstractProvider(abc.ABC):
 
     def meta(self) -> ProviderMeta:
         """获取 Provider 的元数据"""
+        provider_type_name = self.provider_config["type"]
+        meta_data = provider_cls_map.get(provider_type_name)
+        provider_type = meta_data.provider_type if meta_data else None
         return ProviderMeta(
             id=self.provider_config["id"],
             model=self.get_model(),
-            type=self.provider_config["type"],
+            type=provider_type_name,
+            provider_type=provider_type,
         )
 
 
@@ -53,15 +53,13 @@ class Provider(AbstractProvider):
         self,
         provider_config: dict,
         provider_settings: dict,
-        persistant_history: bool = True,
-        db_helper: BaseDatabase = None,
-        default_persona: Personality = None,
+        default_persona: Personality | None = None,
     ) -> None:
         super().__init__(provider_config)
 
         self.provider_settings = provider_settings
 
-        self.curr_personality: Personality = default_persona
+        self.curr_personality = default_persona
         """维护了当前的使用的 persona，即人格。可能为 None"""
 
     @abc.abstractmethod
@@ -86,11 +84,12 @@ class Provider(AbstractProvider):
         self,
         prompt: str,
         session_id: str = None,
-        image_urls: List[str] = None,
-        func_tool: FuncCall = None,
-        contexts: List = None,
+        image_urls: list[str] = None,
+        func_tool: ToolSet = None,
+        contexts: list = None,
         system_prompt: str = None,
-        tool_calls_result: ToolCallsResult = None,
+        tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None,
+        model: str | None = None,
         **kwargs,
     ) -> LLMResponse:
         """获得 LLM 的文本对话结果。会使用当前的模型进行对话。
@@ -114,11 +113,12 @@ class Provider(AbstractProvider):
         self,
         prompt: str,
         session_id: str = None,
-        image_urls: List[str] = None,
-        func_tool: FuncCall = None,
-        contexts: List = None,
+        image_urls: list[str] = None,
+        func_tool: ToolSet = None,
+        contexts: list = None,
         system_prompt: str = None,
-        tool_calls_result: ToolCallsResult = None,
+        tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None,
+        model: str | None = None,
         **kwargs,
     ) -> AsyncGenerator[LLMResponse, None]:
         """获得 LLM 的流式文本对话结果。会使用当前的模型进行对话。在生成的最后会返回一次完整的结果。
@@ -201,3 +201,17 @@ class EmbeddingProvider(AbstractProvider):
     def get_dim(self) -> int:
         """获取向量的维度"""
         ...
+
+
+class RerankProvider(AbstractProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+
+    @abc.abstractmethod
+    async def rerank(
+        self, query: str, documents: list[str], top_n: int | None = None
+    ) -> list[RerankResult]:
+        """获取查询和文档的重排序分数"""
+        ...

astrbot/core/provider/sources/anthropic_source.py

@@ -1,3 +1,6 @@
+import json
+import anthropic
+import base64
 from typing import List
 from mimetypes import guess_type
 
@@ -5,41 +8,33 @@ from anthropic import AsyncAnthropic
 from anthropic.types import Message
 
 from astrbot.core.utils.io import download_image_by_url
-from astrbot.core.db import BaseDatabase
-from astrbot.api.provider import Provider, Personality
+from astrbot.api.provider import Provider
 from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
 from ..register import register_provider_adapter
-from astrbot.core.message.message_event_result import MessageChain
-from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
-from .openai_source import ProviderOpenAIOfficial
+from astrbot.core.provider.entities import LLMResponse
+from typing import AsyncGenerator
 
 
 @register_provider_adapter(
     "anthropic_chat_completion", "Anthropic Claude API 提供商适配器"
 )
-class ProviderAnthropic(ProviderOpenAIOfficial):
+class ProviderAnthropic(Provider):
     def __init__(
         self,
-        provider_config: dict,
-        provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=True,
-        default_persona: Personality = None,
+        provider_config,
+        provider_settings,
+        default_persona=None,
     ) -> None:
-        # Skip OpenAI's __init__ and call Provider's __init__ directly
-        Provider.__init__(
-            self,
+        super().__init__(
             provider_config,
             provider_settings,
-            persistant_history,
-            db_helper,
             default_persona,
         )
 
-        self.chosen_api_key = None
+        self.chosen_api_key: str = ""
         self.api_keys: List = provider_config.get("key", [])
-        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else ""
         self.base_url = provider_config.get("api_base", "https://api.anthropic.com")
         self.timeout = provider_config.get("timeout", 120)
         if isinstance(self.timeout, str):
@@ -51,10 +46,63 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
 
         self.set_model(provider_config["model_config"]["model"])
 
+    def _prepare_payload(self, messages: list[dict]):
+        """准备 Anthropic API 的请求 payload
+
+        Args:
+            messages: OpenAI 格式的消息列表，包含用户输入和系统提示等信息
+        Returns:
+            system_prompt: 系统提示内容
+            new_messages: 处理后的消息列表，去除系统提示
+        """
+        system_prompt = ""
+        new_messages = []
+        for message in messages:
+            if message["role"] == "system":
+                system_prompt = message["content"]
+            elif message["role"] == "assistant":
+                blocks = []
+                if isinstance(message["content"], str):
+                    blocks.append({"type": "text", "text": message["content"]})
+                if "tool_calls" in message:
+                    for tool_call in message["tool_calls"]:
+                        blocks.append(  # noqa: PERF401
+                            {
+                                "type": "tool_use",
+                                "name": tool_call["function"]["name"],
+                                "input": json.loads(tool_call["function"]["arguments"])
+                                if isinstance(tool_call["function"]["arguments"], str)
+                                else tool_call["function"]["arguments"],
+                                "id": tool_call["id"],
+                            }
+                        )
+                new_messages.append(
+                    {
+                        "role": "assistant",
+                        "content": blocks,
+                    }
+                )
+            elif message["role"] == "tool":
+                new_messages.append(
+                    {
+                        "role": "user",
+                        "content": [
+                            {
+                                "type": "tool_result",
+                                "tool_use_id": message["tool_call_id"],
+                                "content": message["content"],
+                            }
+                        ],
+                    }
+                )
+            else:
+                new_messages.append(message)
+
+        return system_prompt, new_messages
+
     async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
         if tools:
-            tool_list = tools.get_func_desc_anthropic_style()
-            if tool_list:
+            if tool_list := tools.get_func_desc_anthropic_style():
                 payloads["tools"] = tool_list
 
         completion = await self.client.messages.create(**payloads, stream=False)
@@ -64,70 +112,158 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
 
         if len(completion.content) == 0:
             raise Exception("API 返回的 completion 为空。")
-        # TODO: 如果进行函数调用，思维链被截断，用户可能需要思维链的内容
-        # 选最后一条消息，如果要进行函数调用，anthropic会先返回文本消息的思维链，然后再返回函数调用请求
-        content = completion.content[-1]
 
-        llm_response = LLMResponse("assistant")
+        llm_response = LLMResponse(role="assistant")
 
-        if content.type == "text":
-            # text completion
-            completion_text = str(content.text).strip()
-            # llm_response.completion_text = completion_text
-            llm_response.result_chain = MessageChain().message(completion_text)
-
-        # Anthropic每次只返回一个函数调用
-        if completion.stop_reason == "tool_use":
-            # tools call (function calling)
-            args_ls = []
-            func_name_ls = []
-            tool_use_ids = []
-            func_name_ls.append(content.name)
-            args_ls.append(content.input)
-            tool_use_ids.append(content.id)
-            llm_response.role = "tool"
-            llm_response.tools_call_args = args_ls
-            llm_response.tools_call_name = func_name_ls
-            llm_response.tools_call_ids = tool_use_ids
+        for content_block in completion.content:
+            if content_block.type == "text":
+                completion_text = str(content_block.text).strip()
+                llm_response.completion_text = completion_text
 
+            if content_block.type == "tool_use":
+                llm_response.tools_call_args.append(content_block.input)
+                llm_response.tools_call_name.append(content_block.name)
+                llm_response.tools_call_ids.append(content_block.id)
+        # TODO(Soulter): 处理 end_turn 情况
         if not llm_response.completion_text and not llm_response.tools_call_args:
-            logger.error(f"API 返回的 completion 无法解析：{completion}。")
-            raise Exception(f"API 返回的 completion 无法解析：{completion}。")
-
-        llm_response.raw_completion = completion
+            raise Exception(f"Anthropic API 返回的 completion 无法解析：{completion}。")
 
         return llm_response
 
+    async def _query_stream(
+        self, payloads: dict, tools: FuncCall
+    ) -> AsyncGenerator[LLMResponse, None]:
+        if tools:
+            if tool_list := tools.get_func_desc_anthropic_style():
+                payloads["tools"] = tool_list
+
+        # 用于累积工具调用信息
+        tool_use_buffer = {}
+        # 用于累积最终结果
+        final_text = ""
+        final_tool_calls = []
+
+        async with self.client.messages.stream(**payloads) as stream:
+            assert isinstance(stream, anthropic.AsyncMessageStream)
+            async for event in stream:
+                if event.type == "content_block_start":
+                    if event.content_block.type == "text":
+                        # 文本块开始
+                        yield LLMResponse(
+                            role="assistant", completion_text="", is_chunk=True
+                        )
+                    elif event.content_block.type == "tool_use":
+                        # 工具使用块开始，初始化缓冲区
+                        tool_use_buffer[event.index] = {
+                            "id": event.content_block.id,
+                            "name": event.content_block.name,
+                            "input": {},
+                        }
+
+                elif event.type == "content_block_delta":
+                    if event.delta.type == "text_delta":
+                        # 文本增量
+                        final_text += event.delta.text
+                        yield LLMResponse(
+                            role="assistant",
+                            completion_text=event.delta.text,
+                            is_chunk=True,
+                        )
+                    elif event.delta.type == "input_json_delta":
+                        # 工具调用参数增量
+                        if event.index in tool_use_buffer:
+                            # 累积 JSON 输入
+                            if "input_json" not in tool_use_buffer[event.index]:
+                                tool_use_buffer[event.index]["input_json"] = ""
+                            tool_use_buffer[event.index]["input_json"] += (
+                                event.delta.partial_json
+                            )
+
+                elif event.type == "content_block_stop":
+                    # 内容块结束
+                    if event.index in tool_use_buffer:
+                        # 解析完整的工具调用
+                        tool_info = tool_use_buffer[event.index]
+                        try:
+                            if "input_json" in tool_info:
+                                tool_info["input"] = json.loads(tool_info["input_json"])
+
+                            # 添加到最终结果
+                            final_tool_calls.append(
+                                {
+                                    "id": tool_info["id"],
+                                    "name": tool_info["name"],
+                                    "input": tool_info["input"],
+                                }
+                            )
+
+                            yield LLMResponse(
+                                role="tool",
+                                completion_text="",
+                                tools_call_args=[tool_info["input"]],
+                                tools_call_name=[tool_info["name"]],
+                                tools_call_ids=[tool_info["id"]],
+                                is_chunk=True,
+                            )
+                        except json.JSONDecodeError:
+                            # JSON 解析失败，跳过这个工具调用
+                            logger.warning(f"工具调用参数 JSON 解析失败: {tool_info}")
+
+                        # 清理缓冲区
+                        del tool_use_buffer[event.index]
+
+        # 返回最终的完整结果
+        final_response = LLMResponse(
+            role="assistant", completion_text=final_text, is_chunk=False
+        )
+
+        if final_tool_calls:
+            final_response.tools_call_args = [
+                call["input"] for call in final_tool_calls
+            ]
+            final_response.tools_call_name = [call["name"] for call in final_tool_calls]
+            final_response.tools_call_ids = [call["id"] for call in final_tool_calls]
+
+        yield final_response
+
     async def text_chat(
         self,
-        prompt: str,
-        session_id: str = None,
-        image_urls: List[str] = [],
-        func_tool: FuncCall = None,
+        prompt,
+        session_id=None,
+        image_urls=None,
+        func_tool=None,
         contexts=None,
         system_prompt=None,
-        tool_calls_result: ToolCallsResult = None,
+        tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
         if contexts is None:
             contexts = []
-        if not prompt:
-            prompt = "<image>"
-
         new_record = await self.assemble_context(prompt, image_urls)
         context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
 
         for part in context_query:
             if "_no_save" in part:
                 del part["_no_save"]
 
+        # tool calls result
         if tool_calls_result:
-            # 暂时这样写。
-            prompt += f"Here are the related results via using tools: {str(tool_calls_result.tool_calls_result)}"
+            if not isinstance(tool_calls_result, list):
+                context_query.extend(tool_calls_result.to_openai_messages())
+            else:
+                for tcr in tool_calls_result:
+                    context_query.extend(tcr.to_openai_messages())
+
+        system_prompt, new_messages = self._prepare_payload(context_query)
 
         model_config = self.provider_config.get("model_config", {})
+        model_config["model"] = model or self.get_model()
+
+        payloads = {"messages": new_messages, **model_config}
 
-        payloads = {"messages": context_query, **model_config}
         # Anthropic has a different way of handling system prompts
         if system_prompt:
             payloads["system"] = system_prompt
@@ -135,32 +271,9 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
         llm_response = None
         try:
             llm_response = await self._query(payloads, func_tool)
-
         except Exception as e:
-            if "maximum context length" in str(e):
-                retry_cnt = 20
-                while retry_cnt > 0:
-                    logger.warning(
-                        f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}"
-                    )
-                    try:
-                        await self.pop_record(context_query)
-                        response = await self.client.messages.create(
-                            messages=context_query, **model_config
-                        )
-                        llm_response = LLMResponse("assistant")
-                        llm_response.result_chain = MessageChain().message(response.content[0].text)
-                        llm_response.raw_completion = response
-                        return llm_response
-                    except Exception as e:
-                        if "maximum context length" in str(e):
-                            retry_cnt -= 1
-                        else:
-                            raise e
-                return LLMResponse("err", "err: 请尝试 /reset 清除会话记录。")
-            else:
-                logger.error(f"发生了错误。Provider 配置如下: {model_config}")
-                raise e
+            logger.error(f"发生了错误。Provider 配置如下: {model_config}")
+            raise e
 
         return llm_response
 
@@ -173,23 +286,41 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
         contexts=...,
         system_prompt=None,
         tool_calls_result=None,
+        model=None,
         **kwargs,
     ):
-        # raise NotImplementedError("This method is not implemented yet.")
-        # 调用 text_chat 模拟流式
-        llm_response = await self.text_chat(
-            prompt=prompt,
-            session_id=session_id,
-            image_urls=image_urls,
-            func_tool=func_tool,
-            contexts=contexts,
-            system_prompt=system_prompt,
-            tool_calls_result=tool_calls_result,
-        )
-        llm_response.is_chunk = True
-        yield llm_response
-        llm_response.is_chunk = False
-        yield llm_response
+        if contexts is None:
+            contexts = []
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+
+        for part in context_query:
+            if "_no_save" in part:
+                del part["_no_save"]
+
+        # tool calls result
+        if tool_calls_result:
+            if not isinstance(tool_calls_result, list):
+                context_query.extend(tool_calls_result.to_openai_messages())
+            else:
+                for tcr in tool_calls_result:
+                    context_query.extend(tcr.to_openai_messages())
+
+        system_prompt, new_messages = self._prepare_payload(context_query)
+
+        model_config = self.provider_config.get("model_config", {})
+        model_config["model"] = model or self.get_model()
+
+        payloads = {"messages": new_messages, **model_config}
+
+        # Anthropic has a different way of handling system prompts
+        if system_prompt:
+            payloads["system"] = system_prompt
+
+        async for llm_response in self._query_stream(payloads, func_tool):
+            yield llm_response
 
     async def assemble_context(self, text: str, image_urls: List[str] = None):
         """组装上下文，支持文本和图片"""
@@ -232,3 +363,28 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
             )
 
         return {"role": "user", "content": content}
+
+    async def encode_image_bs64(self, image_url: str) -> str:
+        """
+        将图片转换为 base64
+        """
+        if image_url.startswith("base64://"):
+            return image_url.replace("base64://", "data:image/jpeg;base64,")
+        with open(image_url, "rb") as f:
+            image_bs64 = base64.b64encode(f.read()).decode("utf-8")
+            return "data:image/jpeg;base64," + image_bs64
+        return ""
+
+    def get_current_key(self) -> str:
+        return self.chosen_api_key
+
+    async def get_models(self) -> List[str]:
+        models_str = []
+        models = await self.client.models.list()
+        models = sorted(models.data, key=lambda x: x.id)
+        for model in models:
+            models_str.append(model.id)
+        return models_str
+
+    def set_key(self, key: str):
+        self.chosen_api_key = key

astrbot/core/provider/sources/azure_tts_source.py

@@ -19,6 +19,7 @@ from ..register import register_provider_adapter
 TEMP_DIR = Path("data/temp/azure_tts")
 TEMP_DIR.mkdir(parents=True, exist_ok=True)
 
+
 class OTTSProvider:
     def __init__(self, config: Dict):
         self.skey = config["OTTS_SKEY"]
@@ -70,12 +71,12 @@ class OTTSProvider:
                         "style": voice_params["style"],
                         "role": voice_params["role"],
                         "rate": voice_params["rate"],
-                        "volume": voice_params["volume"]
+                        "volume": voice_params["volume"],
                     },
                     headers={
                         "User-Agent": f"AstrBot/{VERSION}",
-                        "UAK": "AstrBot/AzureTTS"
-                    }
+                        "UAK": "AstrBot/AzureTTS",
+                    },
                 )
                 response.raise_for_status()
                 file_path.parent.mkdir(parents=True, exist_ok=True)
@@ -88,14 +89,19 @@ class OTTSProvider:
                     raise RuntimeError(f"OTTS请求失败: {str(e)}") from e
                 await asyncio.sleep(0.5 * (attempt + 1))
 
+
 class AzureNativeProvider(TTSProvider):
     def __init__(self, provider_config: dict, provider_settings: dict):
         super().__init__(provider_config, provider_settings)
-        self.subscription_key = provider_config.get("azure_tts_subscription_key", "").strip()
+        self.subscription_key = provider_config.get(
+            "azure_tts_subscription_key", ""
+        ).strip()
         if not re.fullmatch(r"^[a-zA-Z0-9]{32}$", self.subscription_key):
             raise ValueError("无效的Azure订阅密钥")
         self.region = provider_config.get("azure_tts_region", "eastus").strip()
-        self.endpoint = f"https://{self.region}.tts.speech.microsoft.com/cognitiveservices/v1"
+        self.endpoint = (
+            f"https://{self.region}.tts.speech.microsoft.com/cognitiveservices/v1"
+        )
         self.client = None
         self.token = None
         self.token_expire = 0
@@ -104,15 +110,17 @@ class AzureNativeProvider(TTSProvider):
             "style": provider_config.get("azure_tts_style", "cheerful"),
             "role": provider_config.get("azure_tts_role", "Boy"),
             "rate": provider_config.get("azure_tts_rate", "1"),
-            "volume": provider_config.get("azure_tts_volume", "100")
+            "volume": provider_config.get("azure_tts_volume", "100"),
         }
 
     async def __aenter__(self):
-        self.client = AsyncClient(headers={
-            "User-Agent": f"AstrBot/{VERSION}",
-            "Content-Type": "application/ssml+xml",
-            "X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm"
-        })
+        self.client = AsyncClient(
+            headers={
+                "User-Agent": f"AstrBot/{VERSION}",
+                "Content-Type": "application/ssml+xml",
+                "X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm",
+            }
+        )
         return self
 
     async def __aexit__(self, exc_type, exc_val, exc_tb):
@@ -120,10 +128,11 @@ class AzureNativeProvider(TTSProvider):
             await self.client.aclose()
 
     async def _refresh_token(self):
-        token_url = f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
+        token_url = (
+            f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
+        )
         response = await self.client.post(
-            token_url,
-            headers={"Ocp-Apim-Subscription-Key": self.subscription_key}
+            token_url, headers={"Ocp-Apim-Subscription-Key": self.subscription_key}
         )
         response.raise_for_status()
         self.token = response.text
@@ -150,8 +159,8 @@ class AzureNativeProvider(TTSProvider):
             content=ssml,
             headers={
                 "Authorization": f"Bearer {self.token}",
-                "User-Agent": f"AstrBot/{VERSION}"
-            }
+                "User-Agent": f"AstrBot/{VERSION}",
+            },
         )
         response.raise_for_status()
         file_path.parent.mkdir(parents=True, exist_ok=True)
@@ -160,6 +169,7 @@ class AzureNativeProvider(TTSProvider):
                 f.write(chunk)
         return str(file_path.resolve())
 
+
 @register_provider_adapter("azure_tts", "Azure TTS", ProviderType.TEXT_TO_SPEECH)
 class AzureTTSProvider(TTSProvider):
     def __init__(self, provider_config: dict, provider_settings: dict):
@@ -183,7 +193,7 @@ class AzureTTSProvider(TTSProvider):
                 error_msg = (
                     f"JSON解析失败，请检查格式（错误位置：行 {e.lineno} 列 {e.colno}）\n"
                     f"错误详情: {e.msg}\n"
-                    f"错误上下文: {json_str[max(0, e.pos-30):e.pos+30]}"
+                    f"错误上下文: {json_str[max(0, e.pos - 30) : e.pos + 30]}"
                 )
                 raise ValueError(error_msg) from e
             except KeyError as e:
@@ -202,8 +212,8 @@ class AzureTTSProvider(TTSProvider):
                         "style": self.provider_config.get("azure_tts_style"),
                         "role": self.provider_config.get("azure_tts_role"),
                         "rate": self.provider_config.get("azure_tts_rate"),
-                        "volume": self.provider_config.get("azure_tts_volume")
-                    }
+                        "volume": self.provider_config.get("azure_tts_volume"),
+                    },
                 )
         else:
             async with self.provider as provider:

astrbot/core/provider/sources/dashscope_source.py

@@ -5,7 +5,6 @@ from typing import List
 from .. import Provider, Personality
 from ..entities import LLMResponse
 from ..func_tool_manager import FuncCall
-from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
 from astrbot.core.message.message_event_result import MessageChain
 from .openai_source import ProviderOpenAIOfficial
@@ -19,16 +18,12 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         self,
         provider_config: dict,
         provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=False,
-        default_persona: Personality = None,
+        default_persona: Personality | None = None,
     ) -> None:
         Provider.__init__(
             self,
             provider_config,
             provider_settings,
-            persistant_history,
-            db_helper,
             default_persona,
         )
         self.api_key = provider_config.get("dashscope_api_key", "")
@@ -72,6 +67,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         func_tool: FuncCall = None,
         contexts: List = None,
         system_prompt: str = None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
         if contexts is None:
@@ -79,8 +75,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         # 获得会话变量
         payload_vars = self.variables.copy()
         # 动态变量
-        session_vars = sp.get("session_variables", {})
-        session_var = session_vars.get(session_id, {})
+        session_var = await sp.session_get(session_id, "session_variables", default={})
         payload_vars.update(session_var)
 
         if (
@@ -168,6 +163,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         contexts=...,
         system_prompt=None,
         tool_calls_result=None,
+        model=None,
         **kwargs,
     ):
         # raise NotImplementedError("This method is not implemented yet.")

astrbot/core/provider/sources/dify_source.py

@@ -1,10 +1,9 @@
 import astrbot.core.message.components as Comp
 import os
 from typing import List
-from .. import Provider, Personality
+from .. import Provider
 from ..entities import LLMResponse
 from ..func_tool_manager import FuncCall
-from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
 from astrbot.core.utils.dify_api_client import DifyAPIClient
 from astrbot.core.utils.io import download_image_by_url, download_file
@@ -17,17 +16,13 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 class ProviderDify(Provider):
     def __init__(
         self,
-        provider_config: dict,
-        provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=False,
-        default_persona: Personality = None,
+        provider_config,
+        provider_settings,
+        default_persona=None,
     ) -> None:
         super().__init__(
             provider_config,
             provider_settings,
-            persistant_history,
-            db_helper,
             default_persona,
         )
         self.api_key = provider_config.get("dify_api_key", "")
@@ -65,12 +60,14 @@ class ProviderDify(Provider):
         func_tool: FuncCall = None,
         contexts: List = None,
         system_prompt: str = None,
+        tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
         if image_urls is None:
             image_urls = []
         result = ""
-        session_id = session_id or kwargs.get("user") # 1734
+        session_id = session_id or kwargs.get("user") or "unknown"  # 1734
         conversation_id = self.conversation_ids.get(session_id, "")
 
         files_payload = []
@@ -100,9 +97,9 @@ class ProviderDify(Provider):
         # 获得会话变量
         payload_vars = self.variables.copy()
         # 动态变量
-        session_vars = sp.get("session_variables", {})
-        session_var = session_vars.get(session_id, {})
+        session_var = await sp.session_get(session_id, "session_variables", default={})
         payload_vars.update(session_var)
+        payload_vars["system_prompt"] = system_prompt
 
         try:
             match self.api_type:
@@ -202,6 +199,7 @@ class ProviderDify(Provider):
         contexts=...,
         system_prompt=None,
         tool_calls_result=None,
+        model=None,
         **kwargs,
     ):
         # raise NotImplementedError("This method is not implemented yet.")

astrbot/core/provider/sources/fishaudio_tts_api_source.py

@@ -1,5 +1,6 @@
 import os
 import uuid
+import re
 import ormsgpack
 from pydantic import BaseModel, conint
 from httpx import AsyncClient
@@ -24,8 +25,8 @@ class ServeTTSRequest(BaseModel):
     # 参考音频
     references: list[ServeReferenceAudio] = []
     # 参考模型 ID
-    # 例如 https://fish.audio/m/7f92f8afb8ec43bf81429cc1c9199cb1/
-    # 其中reference_id为 7f92f8afb8ec43bf81429cc1c9199cb1
+    # 例如 https://fish.audio/m/626bb6d3f3364c9cbc3aa6a67300a664/
+    # 其中reference_id为 626bb6d3f3364c9cbc3aa6a67300a664
     reference_id: str | None = None
     # 对中英文文本进行标准化，这可以提高数字的稳定性
     normalize: bool = True
@@ -44,6 +45,7 @@ class ProviderFishAudioTTSAPI(TTSProvider):
     ) -> None:
         super().__init__(provider_config, provider_settings)
         self.chosen_api_key: str = provider_config.get("api_key", "")
+        self.reference_id: str = provider_config.get("fishaudio-tts-reference-id", "")
         self.character: str = provider_config.get("fishaudio-tts-character", "可莉")
         self.api_base: str = provider_config.get(
             "api_base", "https://api.fish-audio.cn/v1"
@@ -81,11 +83,43 @@ class ProviderFishAudioTTSAPI(TTSProvider):
                         return item["_id"]
             return None
 
+    def _validate_reference_id(self, reference_id: str) -> bool:
+        """
+        验证reference_id格式是否有效
+
+        Args:
+            reference_id: 参考模型ID
+
+        Returns:
+            bool: ID是否有效
+        """
+        if not reference_id or not reference_id.strip():
+            return False
+
+        # FishAudio的reference_id通常是32位十六进制字符串
+        # 例如: 626bb6d3f3364c9cbc3aa6a67300a664
+        pattern = r'^[a-fA-F0-9]{32}$'
+        return bool(re.match(pattern, reference_id.strip()))
+
     async def _generate_request(self, text: str) -> dict:
+        # 向前兼容逻辑：优先使用reference_id，如果没有则使用角色名称查询
+        if self.reference_id and self.reference_id.strip():
+            # 验证reference_id格式
+            if not self._validate_reference_id(self.reference_id):
+                raise ValueError(
+                    f"无效的FishAudio参考模型ID: '{self.reference_id}'. "
+                    f"请确保ID是32位十六进制字符串（例如: 626bb6d3f3364c9cbc3aa6a67300a664）。"
+                    f"您可以从 https://fish.audio/zh-CN/discovery 获取有效的模型ID。"
+                )
+            reference_id = self.reference_id.strip()
+        else:
+            # 回退到原来的角色名称查询逻辑
+            reference_id = await self._get_reference_id_by_character(self.character)
+
         return ServeTTSRequest(
             text=text,
             format="wav",
-            reference_id=await self._get_reference_id_by_character(self.character),
+            reference_id=reference_id,
         )
 
     async def get_audio(self, text: str) -> str:

astrbot/core/provider/sources/gemini_source.py

@@ -12,10 +12,9 @@ from google.genai.errors import APIError
 
 import astrbot.core.message.components as Comp
 from astrbot import logger
-from astrbot.api.provider import Personality, Provider
-from astrbot.core.db import BaseDatabase
+from astrbot.api.provider import Provider
 from astrbot.core.message.message_event_result import MessageChain
-from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
+from astrbot.core.provider.entities import LLMResponse
 from astrbot.core.provider.func_tool_manager import FuncCall
 from astrbot.core.utils.io import download_image_by_url
 
@@ -52,17 +51,13 @@ class ProviderGoogleGenAI(Provider):
 
     def __init__(
         self,
-        provider_config: dict,
-        provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=True,
-        default_persona: Personality = None,
+        provider_config,
+        provider_settings,
+        default_persona=None,
     ) -> None:
         super().__init__(
             provider_config,
             provider_settings,
-            persistant_history,
-            db_helper,
             default_persona,
         )
         self.api_keys: list = provider_config.get("key", [])
@@ -436,6 +431,7 @@ class ProviderGoogleGenAI(Provider):
                 continue
 
         llm_response = LLMResponse("assistant")
+        llm_response.raw_completion = result
         llm_response.result_chain = self._process_content_parts(result, llm_response)
         return llm_response
 
@@ -475,6 +471,10 @@ class ProviderGoogleGenAI(Provider):
                     raise
                 continue
 
+        # Accumulate the complete response text for the final response
+        accumulated_text = ""
+        final_response = None
+
         async for chunk in result:
             llm_response = LLMResponse("assistant", is_chunk=True)
 
@@ -482,36 +482,53 @@ class ProviderGoogleGenAI(Provider):
                 part.function_call for part in chunk.candidates[0].content.parts
             ):
                 llm_response = LLMResponse("assistant", is_chunk=False)
+                llm_response.raw_completion = chunk
                 llm_response.result_chain = self._process_content_parts(
                     chunk, llm_response
                 )
                 yield llm_response
-                break
+                return
 
             if chunk.text:
+                accumulated_text += chunk.text
                 llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)])
                 yield llm_response
 
             if chunk.candidates[0].finish_reason:
-                llm_response = LLMResponse("assistant", is_chunk=False)
-                if not chunk.candidates[0].content.parts:
-                    llm_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
-                else:
-                    llm_response.result_chain = self._process_content_parts(
-                        chunk, llm_response
+                # Process the final chunk for potential tool calls or other content
+                if chunk.candidates[0].content.parts:
+                    final_response = LLMResponse("assistant", is_chunk=False)
+                    final_response.raw_completion = chunk
+                    final_response.result_chain = self._process_content_parts(
+                        chunk, final_response
                     )
-                yield llm_response
                 break
 
+        # Yield final complete response with accumulated text
+        if not final_response:
+            final_response = LLMResponse("assistant", is_chunk=False)
+
+        # Set the complete accumulated text in the final response
+        if accumulated_text:
+            final_response.result_chain = MessageChain(
+                chain=[Comp.Plain(accumulated_text)]
+            )
+        elif not final_response.result_chain:
+            # If no text was accumulated and no final response was set, provide empty space
+            final_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
+
+        yield final_response
+
     async def text_chat(
         self,
         prompt: str,
-        session_id: str = None,
-        image_urls: list[str] = None,
-        func_tool: FuncCall = None,
-        contexts: list = None,
-        system_prompt: str = None,
-        tool_calls_result: ToolCallsResult = None,
+        session_id=None,
+        image_urls=None,
+        func_tool=None,
+        contexts=None,
+        system_prompt=None,
+        tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
         if contexts is None:
@@ -527,10 +544,14 @@ class ProviderGoogleGenAI(Provider):
 
         # tool calls result
         if tool_calls_result:
-            context_query.extend(tool_calls_result.to_openai_messages())
+            if not isinstance(tool_calls_result, list):
+                context_query.extend(tool_calls_result.to_openai_messages())
+            else:
+                for tcr in tool_calls_result:
+                    context_query.extend(tcr.to_openai_messages())
 
         model_config = self.provider_config.get("model_config", {})
-        model_config["model"] = self.get_model()
+        model_config["model"] = model or self.get_model()
 
         payloads = {"messages": context_query, **model_config}
 
@@ -547,13 +568,14 @@ class ProviderGoogleGenAI(Provider):
 
     async def text_chat_stream(
         self,
-        prompt: str,
-        session_id: str = None,
-        image_urls: list[str] = None,
-        func_tool: FuncCall = None,
-        contexts: str = None,
-        system_prompt: str = None,
-        tool_calls_result: ToolCallsResult = None,
+        prompt,
+        session_id=None,
+        image_urls=None,
+        func_tool=None,
+        contexts=None,
+        system_prompt=None,
+        tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> AsyncGenerator[LLMResponse, None]:
         if contexts is None:
@@ -569,10 +591,14 @@ class ProviderGoogleGenAI(Provider):
 
         # tool calls result
         if tool_calls_result:
-            context_query.extend(tool_calls_result.to_openai_messages())
+            if not isinstance(tool_calls_result, list):
+                context_query.extend(tool_calls_result.to_openai_messages())
+            else:
+                for tcr in tool_calls_result:
+                    context_query.extend(tcr.to_openai_messages())
 
         model_config = self.provider_config.get("model_config", {})
-        model_config["model"] = self.get_model()
+        model_config["model"] = model or self.get_model()
 
         payloads = {"messages": context_query, **model_config}
 
@@ -632,7 +658,10 @@ class ProviderGoogleGenAI(Provider):
                     logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
                     continue
                 user_content["content"].append(
-                    {"type": "image_url", "image_url": {"url": image_data}}
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": image_data},
+                    }
                 )
             return user_content
         else:

astrbot/core/provider/sources/gemini_tts_source.py

@@ -0,0 +1,79 @@
+import os
+import uuid
+import wave
+
+from google import genai
+from google.genai import types
+
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+
+from ..entities import ProviderType
+from ..provider import TTSProvider
+from ..register import register_provider_adapter
+
+
+@register_provider_adapter(
+    "gemini_tts", "Gemini TTS API", provider_type=ProviderType.TEXT_TO_SPEECH
+)
+class ProviderGeminiTTSAPI(TTSProvider):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        api_key: str = provider_config.get("gemini_tts_api_key", "")
+        api_base: str | None = provider_config.get("gemini_tts_api_base")
+        timeout: int = int(provider_config.get("gemini_tts_timeout", 20))
+        http_options = types.HttpOptions(timeout=timeout * 1000)
+
+        if api_base:
+            if api_base.endswith("/"):
+                api_base = api_base[:-1]
+            http_options.base_url = api_base
+
+        self.client = genai.Client(api_key=api_key, http_options=http_options).aio
+        self.model: str = provider_config.get(
+            "gemini_tts_model", "gemini-2.5-flash-preview-tts"
+        )
+        self.prefix: str | None = provider_config.get(
+            "gemini_tts_prefix",
+        )
+        self.voice_name: str = provider_config.get("gemini_tts_voice_name", "Leda")
+
+    async def get_audio(self, text: str) -> str:
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        path = os.path.join(temp_dir, f"gemini_tts_{uuid.uuid4()}.wav")
+        prompt = f"{self.prefix}: {text}" if self.prefix else text
+        response = await self.client.models.generate_content(
+            model=self.model,
+            contents=prompt,
+            config=types.GenerateContentConfig(
+                response_modalities=["AUDIO"],
+                speech_config=types.SpeechConfig(
+                    voice_config=types.VoiceConfig(
+                        prebuilt_voice_config=types.PrebuiltVoiceConfig(
+                            voice_name=self.voice_name,
+                        )
+                    )
+                ),
+            ),
+        )
+
+        # 不想看类型检查报错
+        if (
+            not response.candidates
+            or not response.candidates[0].content
+            or not response.candidates[0].content.parts
+            or not response.candidates[0].content.parts[0].inline_data
+            or not response.candidates[0].content.parts[0].inline_data.data
+        ):
+            raise Exception("No audio content returned from Gemini TTS API.")
+
+        with wave.open(path, "wb") as wf:
+            wf.setnchannels(1)
+            wf.setsampwidth(2)
+            wf.setframerate(24000)
+            wf.writeframes(response.candidates[0].content.parts[0].inline_data.data)
+
+        return path

astrbot/core/provider/sources/llmtuner_source.py

@@ -1,134 +0,0 @@
-import os
-from llmtuner.chat import ChatModel
-from typing import List
-from .. import Provider
-from ..entities import LLMResponse
-from ..func_tool_manager import FuncCall
-from astrbot.core.db import BaseDatabase
-from ..register import register_provider_adapter
-
-
-@register_provider_adapter(
-    "llm_tuner", "LLMTuner 适配器, 用于装载使用 LlamaFactory 微调后的模型"
-)
-class LLMTunerModelLoader(Provider):
-    def __init__(
-        self,
-        provider_config: dict,
-        provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=True,
-        default_persona=None,
-    ) -> None:
-        super().__init__(
-            provider_config,
-            provider_settings,
-            persistant_history,
-            db_helper,
-            default_persona,
-        )
-        if not os.path.exists(provider_config["base_model_path"]) or not os.path.exists(
-            provider_config["adapter_model_path"]
-        ):
-            raise FileNotFoundError("模型文件路径不存在。")
-        self.base_model_path = provider_config["base_model_path"]
-        self.adapter_model_path = provider_config["adapter_model_path"]
-        self.model = ChatModel(
-            {
-                "model_name_or_path": self.base_model_path,
-                "adapter_name_or_path": self.adapter_model_path,
-                "template": provider_config["llmtuner_template"],
-                "finetuning_type": provider_config["finetuning_type"],
-                "quantization_bit": provider_config["quantization_bit"],
-            }
-        )
-        self.set_model(
-            os.path.basename(self.base_model_path)
-            + "_"
-            + os.path.basename(self.adapter_model_path)
-        )
-
-    async def assemble_context(self, text: str, image_urls: List[str] = None):
-        """
-        组装上下文。
-        """
-        return {"role": "user", "content": text}
-
-    async def text_chat(
-        self,
-        prompt: str,
-        session_id: str = None,
-        image_urls: List[str] = None,
-        func_tool: FuncCall = None,
-        contexts: List = None,
-        system_prompt: str = None,
-        **kwargs,
-    ) -> LLMResponse:
-        if contexts is None:
-            contexts = []
-        system_prompt = ""
-        new_record = {"role": "user", "content": prompt}
-        query_context = [*contexts, new_record]
-
-        # 提取出系统提示
-        system_idxs = []
-        for idx, context in enumerate(query_context):
-            if context["role"] == "system":
-                system_idxs.append(idx)
-
-            if "_no_save" in context:
-                del context["_no_save"]
-
-        for idx in reversed(system_idxs):
-            system_prompt += " " + query_context.pop(idx)["content"]
-
-        conf = {
-            "messages": query_context,
-            "system": system_prompt,
-        }
-        if func_tool:
-            tool_list = func_tool.get_func_desc_openai_style()
-            if tool_list:
-                conf["tools"] = tool_list
-
-        responses = await self.model.achat(**conf)
-
-        llm_response = LLMResponse("assistant", responses[-1].response_text)
-
-        return llm_response
-
-    async def text_chat_stream(
-        self,
-        prompt,
-        session_id=None,
-        image_urls=...,
-        func_tool=None,
-        contexts=...,
-        system_prompt=None,
-        tool_calls_result=None,
-        **kwargs,
-    ):
-        # raise NotImplementedError("This method is not implemented yet.")
-        # 调用 text_chat 模拟流式
-        llm_response = await self.text_chat(
-            prompt=prompt,
-            session_id=session_id,
-            image_urls=image_urls,
-            func_tool=func_tool,
-            contexts=contexts,
-            system_prompt=system_prompt,
-            tool_calls_result=tool_calls_result,
-        )
-        llm_response.is_chunk = True
-        yield llm_response
-        llm_response.is_chunk = False
-        yield llm_response
-
-    async def get_current_key(self):
-        return "none"
-
-    async def set_key(self, key):
-        pass
-
-    async def get_models(self):
-        return [self.get_model()]

astrbot/core/provider/sources/openai_embedding_source.py

@@ -22,7 +22,7 @@ class OpenAIEmbeddingProvider(EmbeddingProvider):
             timeout=int(provider_config.get("timeout", 20)),
         )
         self.model = provider_config.get("embedding_model", "text-embedding-3-small")
-        self.dimension = provider_config.get("embedding_dimensions", 1536)
+        self.dimension = provider_config.get("embedding_dimensions", 1024)
 
     async def get_embedding(self, text: str) -> list[float]:
         """

astrbot/core/provider/sources/openai_source.py

@@ -9,14 +9,12 @@ import astrbot.core.message.components as Comp
 from openai import AsyncOpenAI, AsyncAzureOpenAI
 from openai.types.chat.chat_completion import ChatCompletion
 
-# from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
 from openai._exceptions import NotFoundError, UnprocessableEntityError
 from openai.lib.streaming.chat._completions import ChatCompletionStreamState
 from astrbot.core.utils.io import download_image_by_url
 from astrbot.core.message.message_event_result import MessageChain
 
-from astrbot.core.db import BaseDatabase
-from astrbot.api.provider import Provider, Personality
+from astrbot.api.provider import Provider
 from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
 from typing import List, AsyncGenerator
@@ -30,17 +28,13 @@ from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
 class ProviderOpenAIOfficial(Provider):
     def __init__(
         self,
-        provider_config: dict,
-        provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=True,
-        default_persona: Personality = None,
+        provider_config,
+        provider_settings,
+        default_persona=None,
     ) -> None:
         super().__init__(
             provider_config,
             provider_settings,
-            persistant_history,
-            db_helper,
             default_persona,
         )
         self.chosen_api_key = None
@@ -105,6 +99,14 @@ class ProviderOpenAIOfficial(Provider):
         for key in to_del:
             del payloads[key]
 
+        model = payloads.get("model", "")
+        # 针对 qwen3 模型的特殊处理：非流式调用必须设置 enable_thinking=false
+        if "qwen3" in model.lower():
+            extra_body["enable_thinking"] = False 
+        # 针对 deepseek 模型的特殊处理：deepseek-reasoner调用必须移除 tools ，否则将被切换至 deepseek-chat
+        elif model == "deepseek-reasoner" and "tools" in payloads:
+            del payloads["tools"]
+
         completion = await self.client.chat.completions.create(
             **payloads, stream=False, extra_body=extra_body
         )
@@ -182,7 +184,7 @@ class ProviderOpenAIOfficial(Provider):
             raise Exception("API 返回的 completion 为空。")
         choice = completion.choices[0]
 
-        if choice.message.content:
+        if choice.message.content is not None:
             # text completion
             completion_text = str(choice.message.content).strip()
             llm_response.result_chain = MessageChain().message(completion_text)
@@ -193,6 +195,9 @@ class ProviderOpenAIOfficial(Provider):
             func_name_ls = []
             tool_call_ids = []
             for tool_call in choice.message.tool_calls:
+                if isinstance(tool_call, str):
+                    # workaround for #1359
+                    tool_call = json.loads(tool_call)
                 for tool in tools.func_list:
                     if tool.name == tool_call.function.name:
                         # workaround for #1454
@@ -213,7 +218,7 @@ class ProviderOpenAIOfficial(Provider):
                 "API 返回的 completion 由于内容安全过滤被拒绝(非 AstrBot)。"
             )
 
-        if not llm_response.completion_text and not llm_response.tools_call_args:
+        if llm_response.completion_text is None and not llm_response.tools_call_args:
             logger.error(f"API 返回的 completion 无法解析：{completion}。")
             raise Exception(f"API 返回的 completion 无法解析：{completion}。")
 
@@ -224,12 +229,11 @@ class ProviderOpenAIOfficial(Provider):
     async def _prepare_chat_payload(
         self,
         prompt: str,
-        session_id: str = None,
-        image_urls: list[str] = None,
-        func_tool: FuncCall = None,
-        contexts: list = None,
-        system_prompt: str = None,
-        tool_calls_result: ToolCallsResult = None,
+        image_urls: list[str] | None = None,
+        contexts: list | None = None,
+        system_prompt: str | None = None,
+        tool_calls_result: ToolCallsResult | list[ToolCallsResult] | None = None,
+        model: str | None = None,
         **kwargs,
     ) -> tuple:
         """准备聊天所需的有效载荷和上下文"""
@@ -246,14 +250,18 @@ class ProviderOpenAIOfficial(Provider):
 
         # tool calls result
         if tool_calls_result:
-            context_query.extend(tool_calls_result.to_openai_messages())
+            if isinstance(tool_calls_result, ToolCallsResult):
+                context_query.extend(tool_calls_result.to_openai_messages())
+            else:
+                for tcr in tool_calls_result:
+                    context_query.extend(tcr.to_openai_messages())
 
         model_config = self.provider_config.get("model_config", {})
-        model_config["model"] = self.get_model()
+        model_config["model"] = model or self.get_model()
 
         payloads = {"messages": context_query, **model_config}
 
-        return payloads, context_query, func_tool
+        return payloads, context_query
 
     async def _handle_api_error(
         self,
@@ -350,16 +358,16 @@ class ProviderOpenAIOfficial(Provider):
         contexts=None,
         system_prompt=None,
         tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
-        payloads, context_query, func_tool = await self._prepare_chat_payload(
+        payloads, context_query = await self._prepare_chat_payload(
             prompt,
-            session_id,
             image_urls,
-            func_tool,
             contexts,
             system_prompt,
             tool_calls_result,
+            model=model,
             **kwargs,
         )
 
@@ -419,17 +427,17 @@ class ProviderOpenAIOfficial(Provider):
         contexts=[],
         system_prompt=None,
         tool_calls_result=None,
+        model=None,
         **kwargs,
     ) -> AsyncGenerator[LLMResponse, None]:
         """流式对话，与服务商交互并逐步返回结果"""
-        payloads, context_query, func_tool = await self._prepare_chat_payload(
+        payloads, context_query = await self._prepare_chat_payload(
             prompt,
-            session_id,
             image_urls,
-            func_tool,
             contexts,
             system_prompt,
             tool_calls_result,
+            model=model,
             **kwargs,
         )
 
@@ -485,13 +493,8 @@ class ProviderOpenAIOfficial(Provider):
         """
         new_contexts = []
 
-        flag = False
         for context in contexts:
-            if flag:
-                flag = False  # 删除 image 后，下一条（LLM 响应）也要删除
-                continue
-            if isinstance(context["content"], list):
-                flag = True
+            if "content" in context and isinstance(context["content"], list):
                 # continue
                 new_content = []
                 for item in context["content"]:
@@ -534,7 +537,10 @@ class ProviderOpenAIOfficial(Provider):
                     logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
                     continue
                 user_content["content"].append(
-                    {"type": "image_url", "image_url": {"url": image_data}}
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": image_data},
+                    }
                 )
             return user_content
         else:

astrbot/core/provider/sources/vllm_rerank_source.py

@@ -0,0 +1,59 @@
+import aiohttp
+from ..provider import RerankProvider
+from ..register import register_provider_adapter
+from ..entities import ProviderType, RerankResult
+
+
+@register_provider_adapter(
+    "vllm_rerank",
+    "VLLM Rerank 适配器",
+    provider_type=ProviderType.RERANK,
+)
+class VLLMRerankProvider(RerankProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+        self.auth_key = provider_config.get("rerank_api_key", "")
+        self.base_url = provider_config.get("rerank_api_base", "http://127.0.0.1:8000")
+        self.base_url = self.base_url.rstrip("/")
+        self.timeout = provider_config.get("timeout", 20)
+        self.model = provider_config.get("rerank_model", "BAAI/bge-reranker-base")
+
+        h = {}
+        if self.auth_key:
+            h["Authorization"] = f"Bearer {self.auth_key}"
+        self.client = aiohttp.ClientSession(
+            headers=h,
+            timeout=aiohttp.ClientTimeout(total=self.timeout),
+        )
+
+    async def rerank(
+        self, query: str, documents: list[str], top_n: int | None = None
+    ) -> list[RerankResult]:
+        payload = {
+            "query": query,
+            "documents": documents,
+            "model": self.model,
+        }
+        if top_n is not None:
+            payload["top_n"] = top_n
+        async with self.client.post(
+            f"{self.base_url}/v1/rerank", json=payload
+        ) as response:
+            response_data = await response.json()
+            results = response_data.get("results", [])
+
+            return [
+                RerankResult(
+                    index=result["index"],
+                    relevance_score=result["relevance_score"],
+                )
+                for result in results
+            ]
+
+    async def terminate(self) -> None:
+        """关闭客户端会话"""
+        if self.client:
+            await self.client.close()
+            self.client = None

astrbot/core/provider/sources/volcengine_tts.py

@@ -5,12 +5,12 @@ import os
 import traceback
 import asyncio
 import aiohttp
-import requests
 from ..provider import TTSProvider
 from ..entities import ProviderType
 from ..register import register_provider_adapter
 from astrbot import logger
 
+
 @register_provider_adapter(
     "volcengine_tts", "火山引擎 TTS", provider_type=ProviderType.TEXT_TO_SPEECH
 )
@@ -22,7 +22,9 @@ class ProviderVolcengineTTS(TTSProvider):
         self.cluster = provider_config.get("volcengine_cluster", "")
         self.voice_type = provider_config.get("volcengine_voice_type", "")
         self.speed_ratio = provider_config.get("volcengine_speed_ratio", 1.0)
-        self.api_base = provider_config.get("api_base", f"https://openspeech.bytedance.com/api/v1/tts")
+        self.api_base = provider_config.get(
+            "api_base", "https://openspeech.bytedance.com/api/v1/tts"
+        )
         self.timeout = provider_config.get("timeout", 20)
 
     def _build_request_payload(self, text: str) -> dict:
@@ -30,11 +32,9 @@ class ProviderVolcengineTTS(TTSProvider):
             "app": {
                 "appid": self.appid,
                 "token": self.api_key,
-                "cluster": self.cluster
-            },
-            "user": {
-                "uid": str(uuid.uuid4())  
+                "cluster": self.cluster,
             },
+            "user": {"uid": str(uuid.uuid4())},
             "audio": {
                 "voice_type": self.voice_type,
                 "encoding": "mp3",
@@ -48,60 +48,61 @@ class ProviderVolcengineTTS(TTSProvider):
                 "text_type": "plain",
                 "operation": "query",
                 "with_frontend": 1,
-                "frontend_type": "unitTson"
-            }
+                "frontend_type": "unitTson",
+            },
         }
 
     async def get_audio(self, text: str) -> str:
         """异步方法获取语音文件路径"""
         headers = {
             "Content-Type": "application/json",
-            "Authorization": f"Bearer; {self.api_key}"
+            "Authorization": f"Bearer; {self.api_key}",
         }
-        
+
         payload = self._build_request_payload(text)
-        
+
         logger.debug(f"请求头: {headers}")
         logger.debug(f"请求 URL: {self.api_base}")
         logger.debug(f"请求体: {json.dumps(payload, ensure_ascii=False)[:100]}...")
-        
+
         try:
             async with aiohttp.ClientSession() as session:
                 async with session.post(
                     self.api_base,
-                    data=json.dumps(payload), 
+                    data=json.dumps(payload),
                     headers=headers,
-                    timeout=self.timeout
+                    timeout=self.timeout,
                 ) as response:
                     logger.debug(f"响应状态码: {response.status}")
-                    
+
                     response_text = await response.text()
                     logger.debug(f"响应内容: {response_text[:200]}...")
-                    
+
                     if response.status == 200:
                         resp_data = json.loads(response_text)
-                        
+
                         if "data" in resp_data:
                             audio_data = base64.b64decode(resp_data["data"])
-                            
+
                             os.makedirs("data/temp", exist_ok=True)
-                            
+
                             file_path = f"data/temp/volcengine_tts_{uuid.uuid4()}.mp3"
-                            
+
                             loop = asyncio.get_running_loop()
                             await loop.run_in_executor(
-                                None, 
-                                lambda: open(file_path, "wb").write(audio_data)
+                                None, lambda: open(file_path, "wb").write(audio_data)
                             )
-                            
+
                             return file_path
                         else:
                             error_msg = resp_data.get("message", "未知错误")
                             raise Exception(f"火山引擎 TTS API 返回错误: {error_msg}")
                     else:
-                        raise Exception(f"火山引擎 TTS API 请求失败: {response.status}, {response_text}")
-        
+                        raise Exception(
+                            f"火山引擎 TTS API 请求失败: {response.status}, {response_text}"
+                        )
+
         except Exception as e:
             error_details = traceback.format_exc()
             logger.debug(f"火山引擎 TTS 异常详情: {error_details}")
-            raise Exception(f"火山引擎 TTS 异常: {str(e)}")
+            raise Exception(f"火山引擎 TTS 异常: {str(e)}")

astrbot/core/provider/sources/zhipu_source.py

@@ -1,4 +1,3 @@
-from astrbot.core.db import BaseDatabase
 from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
 from typing import List
@@ -13,15 +12,11 @@ class ProviderZhipu(ProviderOpenAIOfficial):
         self,
         provider_config: dict,
         provider_settings: dict,
-        db_helper: BaseDatabase,
-        persistant_history=True,
         default_persona=None,
     ) -> None:
         super().__init__(
             provider_config,
             provider_settings,
-            db_helper,
-            persistant_history,
             default_persona,
         )
 
@@ -33,6 +28,7 @@ class ProviderZhipu(ProviderOpenAIOfficial):
         func_tool: FuncCall = None,
         contexts=None,
         system_prompt=None,
+        model=None,
         **kwargs,
     ) -> LLMResponse:
         if contexts is None:
@@ -43,7 +39,7 @@ class ProviderZhipu(ProviderOpenAIOfficial):
         context_query = [*contexts, new_record]
 
         model_cfgs: dict = self.provider_config.get("model_config", {})
-        model = self.get_model()
+        model = model or self.get_model()
         # glm-4v-flash 只支持一张图片
         if model.lower() == "glm-4v-flash" and image_urls and len(context_query) > 1:
             logger.debug("glm-4v-flash 只支持一张图片，将只保留最后一张图片")

astrbot/core/star/__init__.py

@@ -1,4 +1,4 @@
-from .star import StarMetadata
+from .star import StarMetadata, star_map, star_registry
 from .star_manager import PluginManager
 from .context import Context
 from astrbot.core.provider import Provider
@@ -10,23 +10,48 @@ from astrbot.core.star.star_tools import StarTools
 class Star(CommandParserMixin):
     """所有插件（Star）的父类，所有插件都应该继承于这个类"""
 
-    def __init__(self, context: Context):
+    def __init__(self, context: Context, config: dict | None = None):
         StarTools.initialize(context)
         self.context = context
 
-    async def text_to_image(self, text: str, return_url=True) -> str:
+    def __init_subclass__(cls, **kwargs):
+        super().__init_subclass__(**kwargs)
+        if not star_map.get(cls.__module__):
+            metadata = StarMetadata(
+                star_cls_type=cls,
+                module_path=cls.__module__,
+            )
+            star_map[cls.__module__] = metadata
+            star_registry.append(metadata)
+        else:
+            star_map[cls.__module__].star_cls_type = cls
+            star_map[cls.__module__].module_path = cls.__module__
+
+    @staticmethod
+    async def text_to_image(text: str, return_url=True) -> str:
         """将文本转换为图片"""
         return await html_renderer.render_t2i(text, return_url=return_url)
 
-    async def html_render(self, tmpl: str, data: dict, return_url=True) -> str:
+    @staticmethod
+    async def html_render(
+        tmpl: str, data: dict, return_url=True, options: dict | None = None
+    ) -> str:
         """渲染 HTML"""
         return await html_renderer.render_custom_template(
-            tmpl, data, return_url=return_url
+            tmpl, data, return_url=return_url, options=options
         )
 
+    async def initialize(self):
+        """当插件被激活时会调用这个方法"""
+        pass
+
     async def terminate(self):
         """当插件被禁用、重载插件时会调用这个方法"""
         pass
 
+    def __del__(self):
+        """[Deprecated] 当插件被禁用、重载插件时会调用这个方法"""
+        pass
+
 
 __all__ = ["Star", "StarMetadata", "PluginManager", "Context", "Provider", "StarTools"]

astrbot/core/star/context.py

@@ -1,17 +1,24 @@
 from asyncio import Queue
 from typing import List, Union
 
-from astrbot.core import sp
-from astrbot.core.provider.provider import Provider, TTSProvider, STTProvider
+from astrbot.core.provider.provider import (
+    Provider,
+    TTSProvider,
+    STTProvider,
+    EmbeddingProvider,
+)
 from astrbot.core.provider.entities import ProviderType
 from astrbot.core.db import BaseDatabase
 from astrbot.core.config.astrbot_config import AstrBotConfig
-from astrbot.core.provider.func_tool_manager import FuncCall
+from astrbot.core.provider.func_tool_manager import FunctionToolManager
 from astrbot.core.platform.astr_message_event import MessageSesion
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.provider.manager import ProviderManager
 from astrbot.core.platform import Platform
 from astrbot.core.platform.manager import PlatformManager
+from astrbot.core.platform_message_history_mgr import PlatformMessageHistoryManager
+from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
+from astrbot.core.persona_mgr import PersonaManager
 from .star import star_registry, StarMetadata, star_map
 from .star_handler import star_handlers_registry, StarHandlerMetadata, EventType
 from .filter.command import CommandFilter
@@ -22,6 +29,7 @@ from astrbot.core.star.filter.platform_adapter_type import (
     PlatformAdapterType,
     ADAPTER_NAME_2_TYPE,
 )
+from deprecated import deprecated
 
 
 class Context:
@@ -29,19 +37,6 @@ class Context:
     暴露给插件的接口上下文。
     """
 
-    _event_queue: Queue = None
-    """事件队列。消息平台通过事件队列传递消息事件。"""
-
-    _config: AstrBotConfig = None
-    """AstrBot 配置信息"""
-
-    _db: BaseDatabase = None
-    """AstrBot 数据库"""
-
-    provider_manager: ProviderManager = None
-
-    platform_manager: PlatformManager = None
-
     registered_web_apis: list = []
 
     # back compatibility
@@ -53,18 +48,27 @@ class Context:
         event_queue: Queue,
         config: AstrBotConfig,
         db: BaseDatabase,
-        provider_manager: ProviderManager = None,
-        platform_manager: PlatformManager = None,
-        conversation_manager: ConversationManager = None,
+        provider_manager: ProviderManager,
+        platform_manager: PlatformManager,
+        conversation_manager: ConversationManager,
+        message_history_manager: PlatformMessageHistoryManager,
+        persona_manager: PersonaManager,
+        astrbot_config_mgr: AstrBotConfigManager,
     ):
         self._event_queue = event_queue
+        """事件队列。消息平台通过事件队列传递消息事件。"""
         self._config = config
+        """AstrBot 默认配置"""
         self._db = db
+        """AstrBot 数据库"""
         self.provider_manager = provider_manager
         self.platform_manager = platform_manager
         self.conversation_manager = conversation_manager
+        self.message_history_manager = message_history_manager
+        self.persona_manager = persona_manager
+        self.astrbot_config_mgr = astrbot_config_mgr
 
-    def get_registered_star(self, star_name: str) -> StarMetadata:
+    def get_registered_star(self, star_name: str) -> StarMetadata | None:
         """根据插件名获取插件的 Metadata"""
         for star in star_registry:
             if star.name == star_name:
@@ -74,7 +78,7 @@ class Context:
         """获取当前载入的所有插件 Metadata 的列表"""
         return star_registry
 
-    def get_llm_tool_manager(self) -> FuncCall:
+    def get_llm_tool_manager(self) -> FunctionToolManager:
         """获取 LLM Tool Manager，其用于管理注册的所有的 Function-calling tools"""
         return self.provider_manager.llm_tools
 
@@ -84,40 +88,14 @@ class Context:
         Returns:
             如果没找到，会返回 False
         """
-        func_tool = self.provider_manager.llm_tools.get_func(name)
-        if func_tool is not None:
-            if func_tool.handler_module_path in star_map:
-                if not star_map[func_tool.handler_module_path].activated:
-                    raise ValueError(
-                        f"此函数调用工具所属的插件 {star_map[func_tool.handler_module_path].name} 已被禁用，请先在管理面板启用再激活此工具。"
-                    )
-
-            func_tool.active = True
-
-            inactivated_llm_tools: list = sp.get("inactivated_llm_tools", [])
-            if name in inactivated_llm_tools:
-                inactivated_llm_tools.remove(name)
-                sp.put("inactivated_llm_tools", inactivated_llm_tools)
-
-            return True
-        return False
+        return self.provider_manager.llm_tools.activate_llm_tool(name, star_map)
 
     def deactivate_llm_tool(self, name: str) -> bool:
         """停用一个已经注册的函数调用工具。
 
         Returns:
             如果没找到，会返回 False"""
-        func_tool = self.provider_manager.llm_tools.get_func(name)
-        if func_tool is not None:
-            func_tool.active = False
-
-            inactivated_llm_tools: list = sp.get("inactivated_llm_tools", [])
-            if name not in inactivated_llm_tools:
-                inactivated_llm_tools.append(name)
-                sp.put("inactivated_llm_tools", inactivated_llm_tools)
-
-            return True
-        return False
+        return self.provider_manager.llm_tools.deactivate_llm_tool(name)
 
     def register_provider(self, provider: Provider):
         """
@@ -125,7 +103,7 @@ class Context:
         """
         self.provider_manager.provider_insts.append(provider)
 
-    def get_provider_by_id(self, provider_id: str) -> Provider:
+    def get_provider_by_id(self, provider_id: str) -> Provider | None:
         """通过 ID 获取对应的 LLM Provider(Chat_Completion 类型)。"""
         return self.provider_manager.inst_map.get(provider_id)
 
@@ -141,51 +119,53 @@ class Context:
         """获取所有用于 STT 任务的 Provider。"""
         return self.provider_manager.stt_provider_insts
 
-    def get_using_provider(self, umo: str = None) -> Provider:
+    def get_all_embedding_providers(self) -> List[EmbeddingProvider]:
+        """获取所有用于 Embedding 任务的 Provider。"""
+        return self.provider_manager.embedding_provider_insts
+
+    def get_using_provider(self, umo: str | None = None) -> Provider | None:
         """
         获取当前使用的用于文本生成任务的 LLM Provider(Chat_Completion 类型)。通过 /provider 指令切换。
 
         Args:
             umo(str): unified_message_origin 值，如果传入并且用户启用了提供商会话隔离，则使用该会话偏好的提供商。
         """
-        if umo and self._config["provider_settings"]["separate_provider"]:
-            perf = sp.get("session_provider_perf", {})
-            prov_id = perf.get(umo, {}).get(ProviderType.CHAT_COMPLETION.value, None)
-            if inst := self.provider_manager.inst_map.get(prov_id, None):
-                return inst
-        return self.provider_manager.curr_provider_inst
+        return self.provider_manager.get_using_provider(
+            provider_type=ProviderType.CHAT_COMPLETION,
+            umo=umo,
+        )
 
-    def get_using_tts_provider(self, umo: str = None) -> TTSProvider:
+    def get_using_tts_provider(self, umo: str | None = None) -> TTSProvider:
         """
         获取当前使用的用于 TTS 任务的 Provider。
 
         Args:
             umo(str): unified_message_origin 值，如果传入，则使用该会话偏好的提供商。
         """
-        if umo and self._config["provider_settings"]["separate_provider"]:
-            perf = sp.get("session_provider_perf", {})
-            prov_id = perf.get(umo, {}).get(ProviderType.TEXT_TO_SPEECH.value, None)
-            if inst := self.provider_manager.inst_map.get(prov_id, None):
-                return inst
-        return self.provider_manager.curr_tts_provider_inst
+        return self.provider_manager.get_using_provider(
+            provider_type=ProviderType.TEXT_TO_SPEECH,
+            umo=umo,
+        )
 
-    def get_using_stt_provider(self, umo: str = None) -> STTProvider:
+    def get_using_stt_provider(self, umo: str | None = None) -> STTProvider:
         """
         获取当前使用的用于 STT 任务的 Provider。
 
         Args:
             umo(str): unified_message_origin 值，如果传入，则使用该会话偏好的提供商。
         """
-        if umo and self._config["provider_settings"]["separate_provider"]:
-            perf = sp.get("session_provider_perf", {})
-            prov_id = perf.get(umo, {}).get(ProviderType.SPEECH_TO_TEXT.value, None)
-            if inst := self.provider_manager.inst_map.get(prov_id, None):
-                return inst
-        return self.provider_manager.curr_stt_provider_inst
+        return self.provider_manager.get_using_provider(
+            provider_type=ProviderType.SPEECH_TO_TEXT,
+            umo=umo,
+        )
 
-    def get_config(self) -> AstrBotConfig:
+    def get_config(self, umo: str | None = None) -> AstrBotConfig:
         """获取 AstrBot 的配置。"""
-        return self._config
+        if not umo:
+            # using default config
+            return self._config
+        else:
+            return self.astrbot_config_mgr.get_conf(umo)
 
     def get_db(self) -> BaseDatabase:
         """获取 AstrBot 数据库。"""
@@ -197,9 +177,14 @@ class Context:
         """
         return self._event_queue
 
-    def get_platform(self, platform_type: Union[PlatformAdapterType, str]) -> Platform:
+    @deprecated(version="4.0.0", reason="Use get_platform_inst instead")
+    def get_platform(
+        self, platform_type: Union[PlatformAdapterType, str]
+    ) -> Platform | None:
         """
         获取指定类型的平台适配器。
+
+        该方法已经过时，请使用 get_platform_inst 方法。(>= AstrBot v4.0.0)
         """
         for platform in self.platform_manager.platform_insts:
             name = platform.meta().name
@@ -213,6 +198,20 @@ class Context:
                 ):
                     return platform
 
+    def get_platform_inst(self, platform_id: str) -> Platform | None:
+        """
+        获取指定 ID 的平台适配器实例。
+
+        Args:
+            platform_id (str): 平台适配器的唯一标识符。你可以通过 event.get_platform_id() 获取。
+
+        Returns:
+            Platform: 平台适配器实例，如果未找到则返回 None。
+        """
+        for platform in self.platform_manager.platform_insts:
+            if platform.meta().id == platform_id:
+                return platform
+
     async def send_message(
         self, session: Union[str, MessageSesion], message_chain: MessageChain
     ) -> bool:
@@ -236,7 +235,7 @@ class Context:
                 raise ValueError("不合法的 session 字符串: " + str(e))
 
         for platform in self.platform_manager.platform_insts:
-            if platform.meta().name == session.platform_name:
+            if platform.meta().id == session.platform_name:
                 await platform.send_by_session(session, message_chain)
                 return True
         return False

astrbot/core/star/filter/command.py

@@ -7,10 +7,13 @@ from astrbot.core.config import AstrBotConfig
 from .custom_filter import CustomFilter
 from ..star_handler import StarHandlerMetadata
 
+
 class GreedyStr(str):
     """标记指令完成其他参数接收后的所有剩余文本。"""
+
     pass
 
+
 # 标准指令受到 wake_prefix 的制约。
 class CommandFilter(HandlerFilter):
     """标准指令过滤器"""
@@ -18,8 +21,8 @@ class CommandFilter(HandlerFilter):
     def __init__(
         self,
         command_name: str,
-        alias: set = None,
-        handler_md: StarHandlerMetadata = None,
+        alias: set | None = None,
+        handler_md: StarHandlerMetadata | None = None,
         parent_command_names: List[str] = [""],
     ):
         self.command_name = command_name
@@ -110,6 +113,17 @@ class CommandFilter(HandlerFilter):
                     elif isinstance(param_type_or_default_val, str):
                         # 如果 param_type_or_default_val 是字符串，直接赋值
                         result[param_name] = params[i]
+                    elif isinstance(param_type_or_default_val, bool):
+                        # 处理布尔类型
+                        lower_param = str(params[i]).lower()
+                        if lower_param in ["true", "yes", "1"]:
+                            result[param_name] = True
+                        elif lower_param in ["false", "no", "0"]:
+                            result[param_name] = False
+                        else:
+                            raise ValueError(
+                                f"参数 {param_name} 必须是布尔值（true/false, yes/no, 1/0）。"
+                            )
                     elif isinstance(param_type_or_default_val, int):
                         result[param_name] = int(params[i])
                     elif isinstance(param_type_or_default_val, float):