Implement googleSearch tool in openai_source.py for Gemini(OpenAI Compatible) provider

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

.github/ISSUE_TEMPLATE/PLUGIN_PUBLISH.yml

@@ -16,7 +16,7 @@ body:
 
         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 ？可以从 [此处](https://plugins.astrbot.app/submit) 生成 JSON ，生成后记得复制粘贴过来.
+        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
@@ -26,13 +26,12 @@ body:
       value: |
         ```json
         {
-          "name": "插件名，请以 astrbot_plugin_ 开头",
-          "display_name": "用于展示的插件名，方便人类阅读",
-          "desc": "插件的简短介绍",
+          "name": "插件名",
+          "desc": "插件介绍",
           "author": "作者名",
           "repo": "插件仓库链接",
           "tags": [],
-          "social_link": "",
+          "social_link": ""
         }
         ```
     validations:

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -6,13 +6,13 @@ body:
   - type: markdown
     attributes:
       value: |
-        感谢您抽出时间报告问题！请准确解释您的问题。如果可能，请提供一个可复现的片段（这有助于更快地解决问题）。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        感谢您抽出时间报告问题！请准确解释您的问题。如果可能，请提供一个可复现的片段（这有助于更快地解决问题）。
   - type: textarea
     attributes:
       label: 发生了什么
       description: 描述你遇到的异常
       placeholder: >
-        一个清晰且具体的描述这个异常是什么。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        一个清晰且具体的描述这个异常是什么。
     validations:
       required: true
 
@@ -55,7 +55,7 @@ body:
     attributes:
       label: 报错日志
       description: >
-        如报错日志、截图等。请提供完整的 Debug 级别的日志，不要介意它很长！请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        如报错日志、截图等。请提供完整的 Debug 级别的日志，不要介意它很长！
       placeholder: >
         请提供完整的报错日志或截图。
     validations:

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,46 +1,19 @@
-<!-- 如果有的话，请指定此 PR 旨在解决的 ISSUE 编号。 -->
-<!-- If applicable, please specify the ISSUE number this PR aims to resolve. -->
+<!-- 如果有的话，指定这个 PR 要解决的 ISSUE -->
+解决了 #XYZ
 
-fixes #XYZ
+### Motivation
 
----
+<!--解释为什么要改动-->
 
-### Motivation / 动机
+### Modifications
 
-<!--请描述此项更改的动机：它解决了什么问题？（例如：修复了 XX 错误，添加了 YY 功能）-->
-<!--Please describe the motivation for this change: What problem does it solve? (e.g., Fixes XX bug, adds YY feature)-->
+<!--简单解释你的改动-->
 
-### Modifications / 改动点
+### Check
 
-<!--请总结你的改动：哪些核心文件被修改了？实现了什么功能？-->
-<!--Please summarize your changes: What core files were modified? What functionality was implemented?-->
+<!--如果分支被合并，您的代码将服务于数万名用户！在提交前，请核查一下几点内容-->
 
-### Verification Steps / 验证步骤
-
-<!--请为审查者 (Reviewer) 提供清晰、可复现的验证步骤（例如：1. 导航到... 2. 点击...）。-->
-<!--Please provide clear and reproducible verification steps for the Reviewer (e.g., 1. Navigate to... 2. Click...).-->
-
-### Screenshots or Test Results / 运行截图或测试结果
-
-<!--请粘贴截图、GIF 或测试日志，作为执行“验证步骤”的证据，证明此改动有效。-->
-<!--Please paste screenshots, GIFs, or test logs here as evidence of executing the "Verification Steps" to prove this change is effective.-->
-
-### Compatibility & Breaking Changes / 兼容性与破坏性变更
-
-<!--请说明此变更的兼容性：哪些是破坏性变更？哪些地方做了向后兼容处理？是否提供了数据迁移方法？-->
-<!--Please explain the compatibility of this change: What are the breaking changes? What backward-compatible measures were taken? Are data migration paths provided?-->
-
-- [ ] 这是一个破坏性变更 (Breaking Change)。/ This is a breaking change.
-- [ ] 这不是一个破坏性变更。/ This is NOT a breaking change.
-
----
-
-### Checklist / 检查清单
-
-<!--如果分支被合并，您的代码将服务于数万名用户！在提交前，请核查一下几点内容。-->
-<!--If merged, your code will serve tens of thousands of users! Please double-check the following items before submitting.-->
-
-- [ ] 😊 如果 PR 中有新加入的功能，已经通过 Issue / 邮件等方式和作者讨论过。/ If there are new features added in the PR, I have discussed it with the authors through issues/emails, etc.
-- [ ] 👀 我的更改经过了良好的测试，**并已在上方提供了“验证步骤”和“运行截图”**。/ My changes have been well-tested, **and "Verification Steps" and "Screenshots" have been provided above**.
-- [ ] 🤓 我确保没有引入新依赖库，或者引入了新依赖库的同时将其添加到了 `requirements.txt` 和 `pyproject.toml` 文件相应位置。/ I have ensured that no new dependencies are introduced, OR if new dependencies are introduced, they have been added to the appropriate locations in `requirements.txt` and `pyproject.toml`.
-- [ ] 😮 我的更改没有引入恶意代码。/ My changes do not introduce malicious code.
+- [ ] 😊 我的 Commit Message 符合良好的[规范](https://www.conventionalcommits.org/en/v1.0.0/#summary)
+- [ ] 👀 我的更改经过良好的测试
+- [ ] 🤓 我确保没有引入新依赖库，或者引入了新依赖库的同时将其添加到了 `requirements.txt` 和 `pyproject.toml` 文件相应位置。
+- [ ] 😮 我的更改没有引入恶意代码

.github/auto_assign.yml

@@ -1,38 +0,0 @@
-# Set to true to add reviewers to pull requests
-addReviewers: true
-
-# Set to true to add assignees to pull requests
-addAssignees: false
-
-# A list of reviewers to be added to pull requests (GitHub user name)
-reviewers:
-  - Soulter
-  - Raven95676
-  - Larch-C
-  - anka-afk
-  - advent259141
-  - Fridemn
-  - LIghtJUNction
-  # - zouyonghe
-
-# A number of reviewers added to the pull request
-# Set 0 to add all the reviewers (default: 0)
-numberOfReviewers: 2
-
-# A list of assignees, overrides reviewers if set
-# assignees:
-#   - assigneeA
-
-# A number of assignees to add to the pull request
-# Set to 0 to add all of the assignees.
-# Uses numberOfReviewers if unset.
-# numberOfAssignees: 2
-
-# A list of keywords to be skipped the process that add reviewers if pull requests include it
-skipKeywords:
-  - wip
-  - draft
-
-# A list of users to be skipped by both the add reviewers and add assignees processes
-# skipUsers:
-#   - dependabot[bot]

.github/workflows/auto_release.yml

@@ -73,7 +73,7 @@ jobs:
         uses: actions/checkout@v5
 
       - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
         with:
           python-version: '3.10'
 

.github/workflows/code-format.yml

@@ -1,34 +0,0 @@
-name: Code Format Check
-
-on:
-  pull_request:
-    branches: [ master ]
-  push:
-    branches: [ master ]
-
-jobs:
-  format-check:
-    runs-on: ubuntu-latest
-    
-    steps:
-    - name: Checkout code
-      uses: actions/checkout@v5
-      
-    - name: Set up Python
-      uses: actions/setup-python@v6
-      with:
-        python-version: '3.10'
-        
-    - name: Install UV
-      run: pip install uv
-      
-    - name: Install dependencies
-      run: uv sync
-      
-    - name: Check code formatting with ruff
-      run: |
-        uv run ruff format --check .
-        
-    - name: Check code style with ruff
-      run: |
-        uv run ruff check .

.github/workflows/codeql.yml

@@ -60,7 +60,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v4
+      uses: github/codeql-action/init@v3
       with:
         languages: ${{ matrix.language }}
         build-mode: ${{ matrix.build-mode }}
@@ -88,6 +88,6 @@ jobs:
         exit 1
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v4
+      uses: github/codeql-action/analyze@v3
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/coverage_test.yml

@@ -22,7 +22,7 @@ jobs:
           fetch-depth: 0
 
       - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
       
       - name: Install dependencies
         run: |

.github/workflows/dashboard_ci.yml

@@ -13,18 +13,11 @@ jobs:
       - name: Checkout repository
         uses: actions/checkout@v5
 
-      - name: Setup Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: 'latest'
-
       - name: npm install, build
         run: |
           cd dashboard
-          npm install pnpm -g
-          pnpm install
-          pnpm i --save-dev @types/markdown-it
-          pnpm run build
+          npm install
+          npm run build
 
       - name: Inject Commit SHA
         id: get_sha
@@ -32,24 +25,11 @@ 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@v5
+        uses: actions/upload-artifact@v4
         with:
           name: dist-without-markdown
           path: |
             dashboard/dist
             !dist/**/*.md
-
-      - name: Create GitHub Release
-        if: github.event_name == 'push'
-        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

@@ -27,33 +27,6 @@ jobs:
         if: github.event_name == 'workflow_dispatch'
         run: git checkout ${{ steps.get-latest-tag.outputs.latest_tag }}
 
-      - name: Check if version is pre-release
-        id: check-prerelease
-        run: |
-          if [ "${{ github.event_name }}" == "workflow_dispatch" ]; then
-            version="${{ steps.get-latest-tag.outputs.latest_tag }}"
-          else
-            version="${{ github.ref_name }}"
-          fi
-          if [[ "$version" == *"beta"* ]] || [[ "$version" == *"alpha"* ]]; then
-            echo "is_prerelease=true" >> $GITHUB_OUTPUT
-            echo "Version $version is a pre-release, will not push latest tag"
-          else
-            echo "is_prerelease=false" >> $GITHUB_OUTPUT
-            echo "Version $version is a stable release, will push latest tag"
-          fi
-
-      - name: Build Dashboard
-        run: |
-          cd dashboard
-          npm install
-          npm run build
-          mkdir -p dist/assets
-          echo $(git rev-parse HEAD) > dist/assets/version
-          cd ..
-          mkdir -p data
-          cp -r dashboard/dist data/
-
       - name: Set QEMU
         uses: docker/setup-qemu-action@v3
 
@@ -80,9 +53,9 @@ jobs:
           platforms: linux/amd64,linux/arm64
           push: true
           tags: |
-            ${{ steps.check-prerelease.outputs.is_prerelease == 'false' && format('{0}/astrbot:latest', secrets.DOCKER_HUB_USERNAME) || '' }}
+            ${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:latest
             ${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
-            ${{ steps.check-prerelease.outputs.is_prerelease == 'false' && 'ghcr.io/soulter/astrbot:latest' || '' }}
+            ghcr.io/soulter/astrbot:latest
             ghcr.io/soulter/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
 
       - name: Post build notifications

.github/workflows/stale.yml

@@ -18,7 +18,7 @@ jobs:
       pull-requests: write
 
     steps:
-    - uses: actions/stale@v10
+    - uses: actions/stale@v9
       with:
         repo-token: ${{ secrets.GITHUB_TOKEN }}
         stale-issue-message: 'Stale issue message'

.gitignore

@@ -30,6 +30,4 @@ packages/python_interpreter/workplace
 .conda/
 .idea
 pytest.ini
-.astrbot
-
-uv.lock
+.astrbot

.pre-commit-config.yaml

@@ -6,20 +6,8 @@ ci:
   autoupdate_schedule: weekly
   autoupdate_commit_msg: ":balloon: pre-commit autoupdate"
 repos:
-- repo: https://github.com/astral-sh/ruff-pre-commit
-  # Ruff version.
-  rev: v0.14.1
-  hooks:
-    # Run the linter.
-    - id: ruff-check
-      types_or: [ python, pyi ]
-      args: [ --fix ]
-    # Run the formatter.
-    - id: ruff-format
-      types_or: [ python, pyi ]
-      
-- repo: https://github.com/asottile/pyupgrade
-  rev: v3.21.0
-  hooks:
-    - id: pyupgrade
-      args: [--py310-plus]
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.11.2
+    hooks:
+      - id: ruff
+      - id: ruff-format

Dockerfile

@@ -4,6 +4,8 @@ WORKDIR /AstrBot
 COPY . /AstrBot/
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
+    nodejs \
+    npm \
     gcc \
     build-essential \
     python3-dev \
@@ -11,20 +13,23 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     libssl-dev \
     ca-certificates \
     bash \
-    ffmpeg \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
-RUN apt-get update && apt-get install -y curl gnupg && \
-    curl -fsSL https://deb.nodesource.com/setup_lts.x | bash - && \
-    apt-get install -y nodejs && \
-    rm -rf /var/lib/apt/lists/*
-
 RUN python -m pip install uv
 RUN uv pip install -r requirements.txt --no-cache-dir --system
-RUN uv pip install socksio uv pilk --no-cache-dir --system
+RUN uv pip install socksio uv pyffmpeg pilk --no-cache-dir --system
 
-EXPOSE 6185
+# 释出 ffmpeg
+RUN python -c "from pyffmpeg import FFmpeg; ff = FFmpeg();"
+
+# add /root/.pyffmpeg/bin/ffmpeg to PATH, inorder to use ffmpeg
+RUN echo 'export PATH=$PATH:/root/.pyffmpeg/bin' >> ~/.bashrc
+
+EXPOSE 6185 
 EXPOSE 6186
 
 CMD [ "python", "main.py" ]
+
+
+

README.md

@@ -1,40 +1,33 @@
+<p align="center">
+ 
 ![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 
 </p>
 
 <div align="center">
 
-<br>
+_✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 
-<div>
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=1" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
-</div>
 
-<br>
-
-<div>
-<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?style=for-the-badge&color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/Soulter/AstrBot?style=for-the-badge&color=76bad9)](https://github.com/Soulter/AstrBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&color=76bad9" alt="python">
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?style=for-the-badge&color=76bad9"/></a>
-<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>
-<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600">
+<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> ｜
+<a href="https://github.com/Soulter/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://astrbot.app/">查看文档</a> ｜
+<a href="https://github.com/Soulter/AstrBot/issues">问题提交</a>
 </div>
 
-<br>
+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。
 
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
-<a href="https://astrbot.app/">文档</a> ｜
-<a href="https://blog.astrbot.app/">Blog</a> ｜
-<a href="https://astrbot.featurebase.app/roadmap">路线图</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">问题提交</a>
-</div>
-
-AstrBot 是一个开源的一站式 Agent 聊天机器人平台及开发框架。
-
-## 主要功能
+## ✨ 主要功能
 
 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。
@@ -42,9 +35,9 @@ AstrBot 是一个开源的一站式 Agent 聊天机器人平台及开发框架
 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。
 
-## 部署方式
+## ✨ 使用方式
 
-#### Docker 部署(推荐 🥳)
+#### Docker 部署
 
 推荐使用 Docker / Docker Compose 方式部署 AstrBot。
 
@@ -72,7 +65,7 @@ AstrBot 已由雨云官方上架至云应用平台，可一键部署。
 
 社区贡献的部署方式。
 
-[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+[![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
 
@@ -86,7 +79,9 @@ AstrBot 已由雨云官方上架至云应用平台，可一键部署。
 
 #### 手动部署
 
-首先安装 uv：
+> 推荐使用 `uv`。
+
+首先，安装 uv：
 
 ```bash
 pip install uv
@@ -101,101 +96,53 @@ uv run main.py
 
 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
 
-## 🌍 社区
-
-### QQ 群组
-
-- 1 群：322154837
-- 3 群：630166526
-- 5 群：822130018
-- 6 群：753075035
-- 开发者群：975206796
-
-### Telegram 群组
-
-<a href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
-
-### Discord 群组
-
-<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
-
 ## ⚡ 消息平台支持情况
 
-**官方维护**
-
 | 平台    | 支持性 |
 | -------- | ------- |
-| QQ(官方平台) | ✔    |
+| QQ(官方机器人接口) | ✔    |
 | QQ(OneBot)      | ✔    |
 | Telegram   | ✔    |
-| 企微应用    | ✔    |
-| 企微智能机器人 | ✔ |
+| 企业微信    | ✔    |
 | 微信客服    | ✔    |
 | 微信公众号    | ✔    |
 | 飞书   | ✔    |
 | 钉钉   | ✔    |
 | Slack   | ✔    |
 | Discord   | ✔    |
-| Satori   | ✔    |
-| Misskey   | ✔    |
-| Whatsapp | 将支持 |
-| LINE | 将支持 |
-
-**社区维护**
-
-| 平台    | 支持性 |
-| -------- | ------- |
 | [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)   | ✔    |
 | [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)   | ✔    |
-| [Bilibili 私信](https://github.com/Hina-Chat/astrbot_plugin_bilibili_adapter)   | ✔    |
-| [wxauto](https://github.com/luosheng520qaq/wxauto-repost-onebotv11)   | ✔    |
+| 微信对话开放平台 | 🚧    |
+| WhatsApp   | 🚧    |
+| 小爱音响   | 🚧    |
 
 ## ⚡ 提供商支持情况
 
-**大模型服务**
+| 名称    | 支持性 | 类型 | 备注 |
+| -------- | ------- | ------- | ------- |
+| 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 |  |
+| 阿里云百炼应用 | ✔    | LLMOps |  |
+| 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 |  |
+| Whisper | ✔    | 语音转文本 | 支持 API、本地部署 |
+| SenseVoice | ✔    | 语音转文本 | 本地部署 |
+| OpenAI TTS API | ✔    | 文本转语音 |  |
+| GSVI | ✔    | 文本转语音 | GPT-Sovits-Inference |
+| GPT-SoVITs | ✔    | 文本转语音 | GPT-Sovits-Inference |
+| FishAudio | ✔    | 文本转语音 | GPT-Sovits 作者参与的项目 |
+| Edge TTS | ✔    | 文本转语音 | Edge 浏览器的免费 TTS |
+| 阿里云百炼 TTS | ✔    | 文本转语音 |  |
+| Azure TTS | ✔    | 文本转语音 | Microsoft Azure TTS |
 
-| 名称  | 支持性 | 备注 |
-| -------- | ------- | ------- |
-| OpenAI | ✔    | 支持任何兼容 OpenAI API 的服务 |
-| Anthropic | ✔    |  |
-| Google Gemini | ✔   |  |
-| Moonshot AI | ✔   |  |
-| 智谱 AI | ✔   |  |
-| DeepSeek | ✔   |  |
-| Ollama | ✔     | 本地部署 DeepSeek 等开源语言模型 |
-| LM Studio | ✔    | 本地部署 DeepSeek 等开源语言模型 |
-| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | ✔  |  |
-| [302.AI](https://share.302.ai/rr1M3l) | ✔   |  |
-| [小马算力](https://www.tokenpony.cn/3YPyf) | ✔   |  |
-| 硅基流动 | ✔    |  |
-| PPIO 派欧云 | ✔    |  |
-| ModelScope | ✔    |  |
-| OneAPI | ✔    |  |
-| Dify | ✔    |  |
-| 阿里云百炼应用 | ✔    |  |
-| Coze | ✔    |  |
-
-**语音转文本服务**
-
-| 名称  | 支持性 | 备注 |
-| -------- | ------- | ------- |
-| Whisper | ✔    | 支持 API、本地部署 |
-| SenseVoice | ✔   | 本地部署 |
-
-**文本转语音服务**
-
-| 名称  | 支持性 | 备注 |
-| -------- | ------- | ------- |
-| OpenAI TTS | ✔    |  |
-| Gemini TTS | ✔    |  |
-| GSVI | ✔    | GPT-Sovits-Inference |
-| GPT-SoVITs | ✔     | GPT-Sovits |
-| FishAudio | ✔    | |
-| Edge TTS | ✔    | Edge 浏览器的免费 TTS |
-| 阿里云百炼 TTS | ✔    |  |
-| Azure TTS | ✔   | |
-| Minimax TTS | ✔   | |
-| 火山引擎 TTS | ✔   | |
 
 ## ❤️ 贡献
 
@@ -210,11 +157,44 @@ uv run main.py
 AstrBot 使用 `ruff` 进行代码格式化和检查。
 
 ```bash
-git clone https://github.com/AstrBotDevs/AstrBot
+git clone https://github.com/Soulter/AstrBot
 pip install pre-commit
 pre-commit install
 ```
 
+## 🌟 支持
+
+- Star 这个项目！
+- 在[爱发电](https://afdian.com/a/soulter)支持我！
+
+## ✨ Demo
+
+<details><summary>👉 点击展开多张 Demo 截图 👈</summary>
+
+<div align='center'>
+
+<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
+
+_✨基于 Docker 的沙箱化代码执行器（Beta 测试）✨_
+
+<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
+
+_✨ 多模态、网页搜索、长文本转图片（可配置） ✨_
+
+<img src="https://github.com/user-attachments/assets/e137a9e1-340a-4bf2-bb2b-771132780735" height=150>
+<img src="https://github.com/user-attachments/assets/480f5e82-cf6a-4955-a869-0d73137aa6e1" height=150>
+
+_✨ 插件系统——部分插件展示 ✨_
+
+<img src="https://github.com/user-attachments/assets/0cdbf564-2f59-4da5-b524-ce0e7ef3d978" width=600>
+
+_✨ WebUI ✨_
+
+</div>
+
+</details>
+
+
 ## ❤️ Special Thanks
 
 特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
@@ -223,21 +203,24 @@ pre-commit install
   <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot" />
 </a>
 
-此外，本项目的诞生离不开以下开源项目的帮助：
+此外，本项目的诞生离不开以下开源项目：
 
 - [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
+- [wechatpy/wechatpy](https://github.com/wechatpy/wechatpy)
 
 ## ⭐ Star History
 
 > [!TIP] 
-> 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我们维护这个开源项目的动力 <3
+> 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我维护这个开源项目的动力 <3
 
 <div align="center">
-
-[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
+    
+[![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
 
 </div>
 
-</details>
+![10k-star-banner-credit-by-kevin](https://github.com/user-attachments/assets/c97fc5fb-20b9-4bc8-9998-c20b930ab097)
+
 
 _私は、高性能ですから!_
+

README_en.md

@@ -10,16 +10,16 @@ _✨ Easy-to-use Multi-platform LLM Chatbot & Development Framework ✨_
 
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/AstrBotDevs/AstrBot)](https://github.com/AstrBotDevs/AstrBot/releases/latest)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/Soulter/AstrBot)](https://github.com/Soulter/AstrBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
-<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg"/></a>
 <a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="Static Badge" src="https://img.shields.io/badge/QQ群-630166526-purple"></a>
 [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg)](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%B6%88%E6%81%AF%E4%B8%8A%E8%A1%8C%E9%87%8F&cacheSeconds=3600)
-[![codecov](https://codecov.io/gh/AstrBotDevs/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/AstrBotDevs/AstrBot)
+[![codecov](https://codecov.io/gh/Soulter/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/Soulter/AstrBot)
 
 <a href="https://astrbot.app/">Documentation</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue Tracking</a>
+<a href="https://github.com/Soulter/AstrBot/issues">Issue Tracking</a>
 </div>
 
 AstrBot is a loosely coupled, asynchronous chatbot and development framework that supports multi-platform deployment, featuring an easy-to-use plugin system and comprehensive Large Language Model (LLM) integration capabilities.
@@ -49,7 +49,7 @@ Requires Python (>3.10). See docs: [Windows Installer Guide](https://astrbot.app
 
 #### Replit Deployment
 
-[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
 
 #### CasaOS Deployment
 
@@ -67,8 +67,8 @@ See docs: [Source Code Deployment](https://astrbot.app/deploy/astrbot/cli.html)
 | QQ (Official Bot)                                              | ✔      | Private/Group chats | Text, Images        |
 | QQ (OneBot)                                                    | ✔      | Private/Group chats | Text, Images, Voice |
 | WeChat (Personal)                                              | ✔      | Private/Group chats | Text, Images, Voice |
-| [Telegram](https://github.com/AstrBotDevs/AstrBot_plugin_telegram) | ✔      | Private/Group chats | Text, Images        |
-| [WeChat Work](https://github.com/AstrBotDevs/AstrBot_plugin_wecom) | ✔      | Private chats       | Text, Images, Voice |
+| [Telegram](https://github.com/Soulter/astrbot_plugin_telegram) | ✔      | Private/Group chats | Text, Images        |
+| [WeChat Work](https://github.com/Soulter/astrbot_plugin_wecom) | ✔      | Private chats       | Text, Images, Voice |
 | Feishu                                                         | ✔      | Group chats         | Text, Images        |
 | WeChat Open Platform                                           | 🚧      | Planned             | -                   |
 | Discord                                                        | 🚧      | Planned             | -                   |
@@ -157,7 +157,7 @@ _✨ Built-in Web Chat Interface ✨_
 
 <div align="center">
     
-[![Star History Chart](https://api.star-history.com/svg?repos=AstrBotDevs/AstrBot&type=Date)](https://star-history.com/#AstrBotDevs/AstrBot&Date)
+[![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
 
 </div>
 
@@ -169,7 +169,7 @@ _✨ Built-in Web Chat Interface ✨_
 
 <!-- ## ✨ ATRI [Beta]
 
-Available as plugin: [astrbot_plugin_atri](https://github.com/AstrBotDevs/AstrBot_plugin_atri)
+Available as plugin: [astrbot_plugin_atri](https://github.com/Soulter/astrbot_plugin_atri)
 
 1. Qwen1.5-7B-Chat Lora model fine-tuned with ATRI character data
 2. Long-term memory

README_ja.md

@@ -10,16 +10,16 @@ _✨ 簡単に使えるマルチプラットフォーム LLM チャットボッ
 
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/AstrBotDevs/AstrBot)](https://github.com/AstrBotDevs/AstrBot/releases/latest)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/Soulter/AstrBot)](https://github.com/Soulter/AstrBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg"/></a>
 <img alt="Static Badge" src="https://img.shields.io/badge/QQ群-630166526-purple">
 [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg)](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%B6%88%E6%81%AF%E4%B8%8A%E8%A1%8C%E9%87%8F&cacheSeconds=3600)
-[![codecov](https://codecov.io/gh/AstrBotDevs/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/AstrBotDevs/AstrBot)
+[![codecov](https://codecov.io/gh/Soulter/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/Soulter/AstrBot)
 
 <a href="https://astrbot.app/">ドキュメントを見る</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">問題を報告する</a>
+<a href="https://github.com/Soulter/AstrBot/issues">問題を報告する</a>
 </div>
 
 AstrBot は、疎結合、非同期、複数のメッセージプラットフォームに対応したデプロイ、使いやすいプラグインシステム、および包括的な大規模言語モデル（LLM）接続機能を備えたチャットボットおよび開発フレームワークです。
@@ -50,7 +50,7 @@ AstrBot は、疎結合、非同期、複数のメッセージプラットフォ
 
 #### Replit デプロイ
 
-[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
 
 #### CasaOS デプロイ
 

astrbot/api/__init__.py

@@ -3,18 +3,5 @@ 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",
-    "agent",
-    "sp",
-    "ToolSet",
-    "FunctionTool",
-    "BaseFunctionToolExecutor",
-]
+__all__ = ["AstrBotConfig", "logger", "html_renderer", "llm_tool", "sp"]

astrbot/api/event/filter/__init__.py

@@ -7,7 +7,6 @@ from astrbot.core.star.register import (
     register_permission_type as permission_type,
     register_custom_filter as custom_filter,
     register_on_astrbot_loaded as on_astrbot_loaded,
-    register_on_platform_loaded as on_platform_loaded,
     register_on_llm_request as on_llm_request,
     register_on_llm_response as on_llm_response,
     register_llm_tool as llm_tool,
@@ -42,7 +41,6 @@ __all__ = [
     "custom_filter",
     "PermissionType",
     "on_astrbot_loaded",
-    "on_platform_loaded",
     "on_llm_request",
     "llm_tool",
     "on_decorating_result",

astrbot/cli/utils/basic.py

@@ -37,10 +37,7 @@ async def check_dashboard(astrbot_root: Path) -> None:
                 ):
                     click.echo("正在安装管理面板...")
                     await download_dashboard(
-                        path="data/dashboard.zip",
-                        extract_path=str(astrbot_root),
-                        version=f"v{VERSION}",
-                        latest=False,
+                        path="data/dashboard.zip", extract_path=str(astrbot_root)
                     )
                     click.echo("管理面板安装完成")
 
@@ -53,10 +50,7 @@ async def check_dashboard(astrbot_root: Path) -> None:
                         version = dashboard_version.split("v")[1]
                         click.echo(f"管理面板版本: {version}")
                         await download_dashboard(
-                            path="data/dashboard.zip",
-                            extract_path=str(astrbot_root),
-                            version=f"v{VERSION}",
-                            latest=False,
+                            path="data/dashboard.zip", extract_path=str(astrbot_root)
                         )
                     except Exception as e:
                         click.echo(f"下载管理面板失败: {e}")
@@ -65,10 +59,7 @@ async def check_dashboard(astrbot_root: Path) -> None:
         click.echo("初始化管理面板目录...")
         try:
             await download_dashboard(
-                path=str(astrbot_root / "dashboard.zip"),
-                extract_path=str(astrbot_root),
-                version=f"v{VERSION}",
-                latest=False,
+                path=str(astrbot_root / "dashboard.zip"), extract_path=str(astrbot_root)
             )
             click.echo("管理面板初始化完成")
         except Exception as e:

astrbot/core/__init__.py

@@ -1,4 +1,5 @@
 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
@@ -20,7 +21,7 @@ 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(db_helper=db_helper)
+sp = SharedPreferences()
 # 文件令牌服务
 file_token_service = FileTokenService()
 pip_installer = PipInstaller(

astrbot/core/agent/agent.py

@@ -1,13 +0,0 @@
-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

@@ -1,34 +0,0 @@
-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

@@ -1,27 +0,0 @@
-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

@@ -1,224 +0,0 @@
-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:
-        if "transport" in cfg:
-            transport_type = cfg["transport"]
-        elif "type" in cfg:
-            transport_type = cfg["type"]
-        else:
-            raise Exception("MCP 连接配置缺少 transport 或 type 字段")
-
-        async with aiohttp.ClientSession() as session:
-            if transport_type == "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: str | None = 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 "transport" in cfg:
-                transport_type = cfg["transport"]
-            elif "type" in cfg:
-                transport_type = cfg["type"]
-            else:
-                raise Exception("MCP 连接配置缺少 transport 或 type 字段")
-
-            if transport_type != "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", 60))
-                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", 60))
-                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"""
-        if not self.session:
-            raise Exception("MCP Client is not initialized")
-        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

@@ -1,13 +0,0 @@
-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

@@ -1,18 +0,0 @@
-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

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

astrbot/core/agent/tool.py

@@ -1,267 +0,0 @@
-from dataclasses import dataclass
-from deprecated import deprecated
-from typing import Awaitable, Callable, 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
-    parameters: dict | None = None
-    description: str | None = None
-    handler: Callable[..., Awaitable[Any]] | 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 = 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: Callable[..., Awaitable[Any]],
-    ):
-        """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) -> FunctionTool | None:
-        """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
-                and 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:
-            input_schema = {"type": "object"}
-            if tool.parameters:
-                input_schema["properties"] = tool.parameters.get("properties", {})
-                input_schema["required"] = tool.parameters.get("required", [])
-            tool_def = {
-                "name": tool.name,
-                "description": tool.description,
-                "input_schema": input_schema,
-            }
-            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 = []
-        for tool in self.tools:
-            d = {
-                "name": tool.name,
-                "description": tool.description,
-            }
-            if tool.parameters:
-                d["parameters"] = convert_schema(tool.parameters)
-            tools.append(d)
-
-        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

@@ -1,11 +0,0 @@
-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

@@ -1,12 +0,0 @@
-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
-    tool_call_timeout: int = 60  # Default tool call timeout in seconds

astrbot/core/astrbot_config_mgr.py

@@ -1,255 +0,0 @@
-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.umop_config_router import UmopConfigRouter
-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"
-    name: str
-    path: str  # File name to the configuration file
-
-
-DEFAULT_CONFIG_CONF_INFO = ConfInfo(
-    id="default",
-    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,
-        ucr: UmopConfigRouter,
-        sp: SharedPreferences,
-    ):
-        self.sp = sp
-        self.ucr = ucr
-        self.confs: dict[str, AstrBotConfig] = {}
-        """uuid / "default" -> AstrBotConfig"""
-        self.confs["default"] = default_config
-        self.abconf_data = None
-        self._load_all_configs()
-
-    def _get_abconf_data(self) -> dict:
-        """获取所有的 abconf 数据"""
-        if self.abconf_data is None:
-            self.abconf_data = self.sp.get(
-                "abconf_mapping", {}, scope="global", scope_id="global"
-            )
-        return self.abconf_data
-
-    def _load_all_configs(self):
-        """Load all configurations from the shared preferences."""
-        abconf_data = self._get_abconf_data()
-        self.abconf_data = abconf_data
-        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 _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 -> { "path": str, "name": str }
-        abconf_data = self._get_abconf_data()
-
-        if isinstance(umo, MessageSession):
-            umo = str(umo)
-        else:
-            try:
-                umo = str(MessageSession.from_str(umo))  # validate
-            except Exception:
-                return DEFAULT_CONFIG_CONF_INFO
-
-        conf_id = self.ucr.get_conf_id_for_umop(umo)
-        if conf_id:
-            meta = abconf_data.get(conf_id)
-            if meta and isinstance(meta, dict):
-                # the bind relation between umo and conf is defined in ucr now, so we remove "umop" here
-                meta.pop("umop", None)
-                return ConfInfo(**meta, id=conf_id)
-
-        return DEFAULT_CONFIG_CONF_INFO
-
-    def _save_conf_mapping(
-        self,
-        abconf_path: str,
-        abconf_id: str,
-        abconf_name: str | None = None,
-    ) -> None:
-        """保存配置文件的映射关系"""
-        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] = {
-            "path": abconf_path,
-            "name": random_word,
-        }
-        self.sp.put("abconf_mapping", abconf_data, scope="global", scope_id="global")
-        self.abconf_data = abconf_data
-
-    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 = []
-        abconf_mapping = self._get_abconf_data()
-        for uuid_, meta in abconf_mapping.items():
-            if not isinstance(meta, dict):
-                continue
-            meta.pop("umop", None)
-            conf_list.append(ConfInfo(**meta, id=uuid_))
-        conf_list.append(DEFAULT_CONFIG_CONF_INFO)
-        return conf_list
-
-    def create_conf(
-        self,
-        config: dict = DEFAULT_CONFIG,
-        name: str | None = None,
-    ) -> str:
-        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, 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")
-        self.abconf_data = abconf_data
-
-        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) -> 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)
-
-        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
-
-        # 保存更新
-        self.sp.put("abconf_mapping", abconf_data, scope="global", scope_id="global")
-        self.abconf_data = abconf_data
-        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

@@ -5,76 +5,40 @@ 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, Callable, Awaitable
+from typing import Dict, List
 from astrbot.core.db import BaseDatabase
-from astrbot.core.db.po import Conversation, ConversationV2
+from astrbot.core.db.po import Conversation
 
 
 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):
-        self.session_conversations: Dict[str, str] = {}
+        # 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.db = db_helper
         self.save_interval = 60  # 每 60 秒保存一次
+        self._start_periodic_save()
 
-        # 会话删除回调函数列表（用于级联清理，如知识库配置）
-        self._on_session_deleted_callbacks: List[Callable[[str], Awaitable[None]]] = []
+    def _start_periodic_save(self):
+        """启动定时保存任务"""
+        asyncio.create_task(self._periodic_save())
 
-    def register_on_session_deleted(
-        self, callback: Callable[[str], Awaitable[None]]
-    ) -> None:
-        """注册会话删除回调函数
+    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()
 
-        其他模块可以注册回调来响应会话删除事件，实现级联清理。
-        例如：知识库模块可以注册回调来清理会话的知识库配置。
+    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)
 
-        Args:
-            callback: 回调函数，接收会话ID (unified_msg_origin) 作为参数
-        """
-        self._on_session_deleted_callbacks.append(callback)
-
-    async def _trigger_session_deleted(self, unified_msg_origin: str) -> None:
-        """触发会话删除回调
-
-        Args:
-            unified_msg_origin: 会话ID
-        """
-        for callback in self._on_session_deleted_callbacks:
-            try:
-                await callback(unified_msg_origin)
-            except Exception as e:
-                from astrbot.core import logger
-
-                logger.error(
-                    f"会话删除回调执行失败 (session: {unified_msg_origin}): {e}"
-                )
-
-    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 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:
+    async def new_conversation(self, unified_msg_origin: str) -> str:
         """新建对话，并将当前会话的对话转移到新对话
 
         Args:
@@ -82,23 +46,11 @@ class ConversationManager:
         Returns:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
-        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
+        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
 
     async def switch_conversation(self, unified_msg_origin: str, conversation_id: str):
         """切换会话的对话
@@ -108,10 +60,10 @@ class ConversationManager:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
         self.session_conversations[unified_msg_origin] = conversation_id
-        await sp.session_put(unified_msg_origin, "sel_conv_id", conversation_id)
+        sp.put("session_conversation", self.session_conversations)
 
     async def delete_conversation(
-        self, unified_msg_origin: str, conversation_id: str | None = None
+        self, unified_msg_origin: str, conversation_id: str = None
     ):
         """删除会话的对话，当 conversation_id 为 None 时删除会话当前的对话
 
@@ -119,29 +71,13 @@ 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
         """
-        if not conversation_id:
-            conversation_id = self.session_conversations.get(unified_msg_origin)
+        conversation_id = self.session_conversations.get(unified_msg_origin)
         if conversation_id:
-            await self.db.delete_conversation(cid=conversation_id)
-            curr_cid = await self.get_curr_conversation_id(unified_msg_origin)
-            if curr_cid == conversation_id:
-                self.session_conversations.pop(unified_msg_origin, None)
-                await sp.session_remove(unified_msg_origin, "sel_conv_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)
 
-    async def delete_conversations_by_user_id(self, unified_msg_origin: str):
-        """删除会话的所有对话
-
-        Args:
-            unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
-        """
-        await self.db.delete_conversations_by_user_id(user_id=unified_msg_origin)
-        self.session_conversations.pop(unified_msg_origin, None)
-        await sp.session_remove(unified_msg_origin, "sel_conv_id")
-
-        # 触发会话删除回调（级联清理）
-        await self._trigger_session_deleted(unified_msg_origin)
-
-    async def get_curr_conversation_id(self, unified_msg_origin: str) -> str | None:
+    async def get_curr_conversation_id(self, unified_msg_origin: str) -> str:
         """获取会话当前的对话 ID
 
         Args:
@@ -149,19 +85,14 @@ class ConversationManager:
         Returns:
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
         """
-        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
+        return self.session_conversations.get(unified_msg_origin, None)
 
     async def get_conversation(
         self,
         unified_msg_origin: str,
         conversation_id: str,
         create_if_not_exists: bool = False,
-    ) -> Conversation | None:
+    ) -> Conversation:
         """获取会话的对话
 
         Args:
@@ -170,74 +101,27 @@ class ConversationManager:
         Returns:
             conversation (Conversation): 对话对象
         """
-        conv = await self.db.get_conversation_by_id(cid=conversation_id)
+        conv = self.db.get_conversation_by_user_id(unified_msg_origin, 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
+            return self.db.get_conversation_by_user_id(
+                unified_msg_origin, conversation_id
+            )
+        return self.db.get_conversation_by_user_id(unified_msg_origin, conversation_id)
 
-    async def get_conversations(
-        self, unified_msg_origin: str | None = None, platform_id: str | None = None
-    ) -> List[Conversation]:
-        """获取对话列表
+    async def get_conversations(self, unified_msg_origin: str) -> List[Conversation]:
+        """获取会话的所有对话
 
         Args:
-            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
+            unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
         Returns:
             conversations (List[Conversation]): 对话对象列表
         """
-        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
+        return self.db.get_conversations(unified_msg_origin)
 
     async def update_conversation(
-        self,
-        unified_msg_origin: str,
-        conversation_id: str | None = None,
-        history: list[dict] | None = None,
-        title: str | None = None,
-        persona_id: str | None = None,
+        self, unified_msg_origin: str, conversation_id: str, history: List[Dict]
     ):
         """更新会话的对话
 
@@ -246,55 +130,40 @@ 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:
-            await self.db.update_conversation(
+            self.db.update_conversation(
+                user_id=unified_msg_origin,
                 cid=conversation_id,
-                title=title,
-                persona_id=persona_id,
-                content=history,
+                history=json.dumps(history),
             )
 
-    async def update_conversation_title(
-        self, unified_msg_origin: str, title: str, conversation_id: str | None = None
-    ):
+    async def update_conversation_title(self, unified_msg_origin: str, title: str):
         """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.
         """
-        await self.update_conversation(
-            unified_msg_origin=unified_msg_origin,
-            conversation_id=conversation_id,
-            title=title,
-        )
+        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
+            )
 
     async def update_conversation_persona_id(
-        self,
-        unified_msg_origin: str,
-        persona_id: str,
-        conversation_id: str | None = None,
+        self, unified_msg_origin: str, persona_id: str
     ):
         """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.
         """
-        await self.update_conversation(
-            unified_msg_origin=unified_msg_origin,
-            conversation_id=conversation_id,
-            persona_id=persona_id,
-        )
+        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
+            )
 
     async def get_human_readable_context(
         self, unified_msg_origin, conversation_id, page=1, page_size=10

astrbot/core/core_lifecycle.py

@@ -15,27 +15,22 @@ import time
 import threading
 import os
 from .event_bus import EventBus
-from . import astrbot_config, html_renderer
+from . import astrbot_config
 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.db.migration.migra_45_to_46 import migrate_45_to_46
 from astrbot.core.updator import AstrBotUpdator
-from astrbot.core import logger, sp
+from astrbot.core import logger
 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.umop_config_router import UmopConfigRouter
-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
-from astrbot.core.knowledge_base.kb_mgr import KnowledgeBaseManager
 
 
 class AstrBotCoreLifecycle:
@@ -52,23 +47,12 @@ class AstrBotCoreLifecycle:
         self.db = db  # 初始化数据库
 
         # 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")
+        if self.astrbot_config.get("http_proxy", ""):
+            os.environ["https_proxy"] = self.astrbot_config["http_proxy"]
+            os.environ["http_proxy"] = self.astrbot_config["http_proxy"]
+        if proxy := os.environ.get("https_proxy"):
+            logger.debug(f"Using proxy: {proxy}")
+        os.environ["no_proxy"] = "localhost"
 
     async def initialize(self):
         """
@@ -82,36 +66,11 @@ 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 UMOP 配置路由器
-        self.umop_config_router = UmopConfigRouter(sp=sp)
-
-        # 初始化 AstrBot 配置管理器
-        self.astrbot_config_mgr = AstrBotConfigManager(
-            default_config=self.astrbot_config, ucr=self.umop_config_router, sp=sp
-        )
-
-        # 4.5 to 4.6 migration for umop_config_router
-        try:
-            await migrate_45_to_46(self.astrbot_config_mgr, self.umop_config_router)
-        except Exception as e:
-            logger.error(f"Migration from version 4.5 to 4.6 failed: {e!s}")
-            logger.error(traceback.format_exc())
-
         # 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_mgr, self.db, self.persona_mgr
-        )
+        self.provider_manager = ProviderManager(self.astrbot_config, self.db)
 
         # 初始化平台管理器
         self.platform_manager = PlatformManager(self.astrbot_config, self.event_queue)
@@ -119,12 +78,6 @@ 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)
-
-        # 初始化知识库管理器
-        self.kb_manager = KnowledgeBaseManager(self.provider_manager)
-
         # 初始化提供给插件的上下文
         self.star_context = Context(
             self.event_queue,
@@ -133,10 +86,6 @@ class AstrBotCoreLifecycle:
             self.provider_manager,
             self.platform_manager,
             self.conversation_manager,
-            self.platform_message_history_manager,
-            self.persona_mgr,
-            self.astrbot_config_mgr,
-            self.kb_manager,
         )
 
         # 初始化插件管理器
@@ -148,24 +97,23 @@ class AstrBotCoreLifecycle:
         # 根据配置实例化各个 Provider
         await self.provider_manager.initialize()
 
-        await self.kb_manager.initialize()
-
         # 初始化消息事件流水线调度器
-        self.pipeline_scheduler_mapping = await self.load_pipeline_scheduler()
+        self.pipeline_scheduler = PipelineScheduler(
+            PipelineContext(self.astrbot_config, self.plugin_manager)
+        )
+        await self.pipeline_scheduler.initialize()
 
         # 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_mapping, self.astrbot_config_mgr
-        )
+        self.event_bus = EventBus(self.event_queue, self.pipeline_scheduler)
 
         # 记录启动时间
         self.start_time = int(time.time())
 
         # 初始化当前任务列表
-        self.curr_tasks: list[asyncio.Task] = []
+        self.curr_tasks: List[asyncio.Task] = []
 
         # 根据配置实例化各个平台适配器
         await self.platform_manager.initialize()
@@ -250,7 +198,6 @@ class AstrBotCoreLifecycle:
 
         await self.provider_manager.terminate()
         await self.platform_manager.terminate()
-        await self.kb_manager.terminate()
         self.dashboard_shutdown_event.set()
 
         # 再次遍历curr_tasks等待每个任务真正结束
@@ -266,51 +213,17 @@ class AstrBotCoreLifecycle:
         """重启 AstrBot 核心生命周期管理类, 终止各个管理器并重新加载平台实例"""
         await self.provider_manager.terminate()
         await self.platform_manager.terminate()
-        await self.kb_manager.terminate()
         self.dashboard_shutdown_event.set()
         threading.Thread(
             target=self.astrbot_updator._reboot, name="restart", daemon=True
         ).start()
 
-    def load_platform(self) -> list[asyncio.Task]:
+    def load_platform(self) -> List[asyncio.Task]:
         """加载平台实例并返回所有平台实例的异步任务列表"""
         tasks = []
         platform_insts = self.platform_manager.get_insts()
         for platform_inst in platform_insts:
             tasks.append(
-                asyncio.create_task(
-                    platform_inst.run(),
-                    name=f"{platform_inst.meta().id}({platform_inst.meta().name})",
-                )
+                asyncio.create_task(platform_inst.run(), name=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

@@ -1,20 +1,7 @@
 import abc
-import datetime
-import typing as T
-from deprecated import deprecated
 from dataclasses import dataclass
-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
+from typing import List, Dict, Any, Tuple
+from astrbot.core.db.po import Stats, LLMHistory, ATRIVision, Conversation
 
 
 @dataclass
@@ -23,278 +10,152 @@ 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
 
-    @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
+    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
 
-    @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
 
-    # New methods in v4.0.0
+    @abc.abstractmethod
+    def insert_atri_vision_data(self, vision_data: ATRIVision):
+        """插入 ATRI 视觉数据"""
+        raise NotImplementedError
 
     @abc.abstractmethod
-    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."""
-        ...
+    def get_atri_vision_data(self) -> List[ATRIVision]:
+        """获取 ATRI 视觉数据"""
+        raise NotImplementedError
 
     @abc.abstractmethod
-    async def count_platform_stats(self) -> int:
-        """Count the number of platform statistics records."""
-        ...
+    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
 
     @abc.abstractmethod
-    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."""
-        ...
+    def get_conversation_by_user_id(self, user_id: str, cid: str) -> Conversation:
+        """通过 user_id 和 cid 获取 Conversation"""
+        raise NotImplementedError
 
     @abc.abstractmethod
-    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).
-
-        content is not included in the result.
-        """
-        ...
+    def new_conversation(self, user_id: str, cid: str):
+        """新建 Conversation"""
+        raise NotImplementedError
 
     @abc.abstractmethod
-    async def get_conversation_by_id(self, cid: str) -> ConversationV2:
-        """Get a specific conversation by its ID."""
-        ...
+    def get_conversations(self, user_id: str) -> List[Conversation]:
+        raise NotImplementedError
 
     @abc.abstractmethod
-    async def get_all_conversations(
+    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
-    ) -> list[ConversationV2]:
-        """Get all conversations with pagination."""
-        ...
+    ) -> 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
+        """
+        raise NotImplementedError
 
     @abc.abstractmethod
-    async def get_filtered_conversations(
+    def get_filtered_conversations(
         self,
         page: int = 1,
         page_size: int = 20,
-        platform_ids: list[str] | None = None,
-        search_query: str = "",
-        **kwargs,
-    ) -> tuple[list[ConversationV2], int]:
-        """Get conversations filtered by platform IDs and search query."""
-        ...
+        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
 
-    @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."""
-        ...
+        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 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 delete_conversations_by_user_id(self, user_id: str) -> None:
-        """Delete all conversations for a specific user."""
-        ...
-
-    @abc.abstractmethod
-    async def insert_platform_message_history(
-        self,
-        platform_id: str,
-        user_id: str,
-        content: 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."""
-    #     ...
-
-    @abc.abstractmethod
-    async def get_session_conversations(
-        self,
-        page: int = 1,
-        page_size: int = 20,
-        search_query: str | None = None,
-        platform: str | None = None,
-    ) -> tuple[list[dict], int]:
-        """Get paginated session conversations with joined conversation and persona details, support search and platform filter."""
-        ...
+        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

astrbot/core/db/migration/helper.py

@@ -1,67 +0,0 @@
-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。
-    """
-    # 仅当 data 目录下存在旧版本数据（data_v3.db 文件）时才考虑迁移
-    data_dir = get_astrbot_data_path()
-    data_v3_db = os.path.join(data_dir, "data_v3.db")
-
-    if not os.path.exists(data_v3_db):
-        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,
-) -> None:
-    """
-    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

@@ -1,338 +0,0 @@
-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/migra_45_to_46.py

@@ -1,44 +0,0 @@
-from astrbot.api import logger, sp
-from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
-from astrbot.core.umop_config_router import UmopConfigRouter
-
-
-async def migrate_45_to_46(acm: AstrBotConfigManager, ucr: UmopConfigRouter):
-    abconf_data = acm.abconf_data
-
-    if not isinstance(abconf_data, dict):
-        # should be unreachable
-        logger.warning(
-            f"migrate_45_to_46: abconf_data is not a dict (type={type(abconf_data)}). Value: {abconf_data!r}"
-        )
-        return
-
-    # 如果任何一项带有 umop，则说明需要迁移
-    need_migration = False
-    for conf_id, conf_info in abconf_data.items():
-        if isinstance(conf_info, dict) and "umop" in conf_info:
-            need_migration = True
-            break
-
-    if not need_migration:
-        return
-
-    logger.info("Starting migration from version 4.5 to 4.6")
-
-    # extract umo->conf_id mapping
-    umo_to_conf_id = {}
-    for conf_id, conf_info in abconf_data.items():
-        if isinstance(conf_info, dict) and "umop" in conf_info:
-            umop_ls = conf_info.pop("umop")
-            if not isinstance(umop_ls, list):
-                continue
-            for umo in umop_ls:
-                if isinstance(umo, str) and umo not in umo_to_conf_id:
-                    umo_to_conf_id[umo] = conf_id
-
-    # update the abconf data
-    await sp.global_put("abconf_mapping", abconf_data)
-    # update the umop config router
-    await ucr.update_routing_data(umo_to_conf_id)
-
-    logger.info("Migration from version 45 to 46 completed successfully")

astrbot/core/db/migration/shared_preferences_v3.py

@@ -1,47 +0,0 @@
-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

@@ -1,494 +0,0 @@
-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

@@ -1,237 +1,7 @@
-import uuid
+"""指标数据"""
 
-from datetime import datetime, timezone
 from dataclasses import dataclass, field
-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 | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    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 | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    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 | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    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.
-# ====
+from typing import List
 
 
 @dataclass
@@ -243,6 +13,77 @@ 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)
+    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 = ""

astrbot/core/db/sqlite_init.sql

@@ -0,0 +1,50 @@
+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/base.py

@@ -16,42 +16,14 @@ class BaseVecDB:
         pass
 
     @abc.abstractmethod
-    async def insert(
-        self, content: str, metadata: dict | None = None, id: str | None = None
-    ) -> int:
+    async def insert(self, content: str, metadata: dict = None, id: str = 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。
         """
         ...
 
     @abc.abstractmethod
-    async def insert_batch(
-        self,
-        contents: list[str],
-        metadatas: list[dict] | None = None,
-        ids: list[str] | None = None,
-        batch_size: int = 32,
-        tasks_limit: int = 3,
-        max_retries: int = 3,
-        progress_callback=None,
-    ) -> int:
-        """
-        批量插入文本和其对应向量，自动生成 ID 并保持一致性。
-
-        Args:
-            progress_callback: 进度回调函数，接收参数 (current, total)
-        """
-        ...
-
-    @abc.abstractmethod
-    async def retrieve(
-        self,
-        query: str,
-        top_k: int = 5,
-        fetch_k: int = 20,
-        rerank: bool = False,
-        metadata_filters: dict | None = None,
-    ) -> list[Result]:
+    async def retrieve(self, query: str, top_k: int = 5) -> list[Result]:
         """
         搜索最相似的文档。
         Args:
@@ -72,6 +44,3 @@ class BaseVecDB:
             bool: 删除是否成功
         """
         ...
-
-    @abc.abstractmethod
-    async def close(self): ...

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

@@ -1,224 +1,59 @@
+import aiosqlite
 import os
-import json
-from datetime import datetime
-from contextlib import asynccontextmanager
-
-from sqlalchemy import Text, Column
-from sqlalchemy.ext.asyncio import AsyncEngine, AsyncSession, create_async_engine
-from sqlalchemy.orm import sessionmaker
-from sqlmodel import Field, SQLModel, select, col, func, text, MetaData
-from astrbot.core import logger
-
-
-class BaseDocModel(SQLModel, table=False):
-    metadata = MetaData()
-
-
-class Document(BaseDocModel, table=True):
-    """SQLModel for documents table."""
-
-    __tablename__ = "documents"  # type: ignore
-
-    id: int | None = Field(
-        default=None, primary_key=True, sa_column_kwargs={"autoincrement": True}
-    )
-    doc_id: str = Field(nullable=False)
-    text: str = Field(nullable=False)
-    metadata_: str | None = Field(default=None, sa_column=Column("metadata", Text))
-    created_at: datetime | None = Field(default=None)
-    updated_at: datetime | None = Field(default=None)
 
 
 class DocumentStorage:
     def __init__(self, db_path: str):
         self.db_path = db_path
-        self.DATABASE_URL = f"sqlite+aiosqlite:///{db_path}"
-        self.engine: AsyncEngine | None = None
-        self.async_session_maker: sessionmaker | None = None
+        self.connection = None
         self.sqlite_init_path = os.path.join(
             os.path.dirname(__file__), "sqlite_init.sql"
         )
 
     async def initialize(self):
         """Initialize the SQLite database and create the documents table if it doesn't exist."""
-        await self.connect()
-        async with self.engine.begin() as conn:  # type: ignore
-            # Create tables using SQLModel
-            await conn.run_sync(BaseDocModel.metadata.create_all)
-
-            try:
-                await conn.execute(
-                    text(
-                        "ALTER TABLE documents ADD COLUMN kb_doc_id TEXT "
-                        "GENERATED ALWAYS AS (json_extract(metadata, '$.kb_doc_id')) STORED"
-                    )
-                )
-                await conn.execute(
-                    text(
-                        "ALTER TABLE documents ADD COLUMN user_id TEXT "
-                        "GENERATED ALWAYS AS (json_extract(metadata, '$.user_id')) STORED"
-                    )
-                )
-
-                # Create indexes
-                await conn.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_documents_kb_doc_id ON documents(kb_doc_id)"
-                    )
-                )
-                await conn.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_documents_user_id ON documents(user_id)"
-                    )
-                )
-            except BaseException:
-                pass
-
-            await conn.commit()
+        if not os.path.exists(self.db_path):
+            await self.connect()
+            async with self.connection.cursor() as cursor:
+                with open(self.sqlite_init_path, "r", encoding="utf-8") as f:
+                    sql_script = f.read()
+                await cursor.executescript(sql_script)
+            await self.connection.commit()
+        else:
+            await self.connect()
 
     async def connect(self):
         """Connect to the SQLite database."""
-        if self.engine is None:
-            self.engine = create_async_engine(
-                self.DATABASE_URL,
-                echo=False,
-                future=True,
-            )
-            self.async_session_maker = sessionmaker(
-                self.engine,  # type: ignore
-                class_=AsyncSession,
-                expire_on_commit=False,
-            )  # type: ignore
+        self.connection = await aiosqlite.connect(self.db_path)
 
-    @asynccontextmanager
-    async def get_session(self):
-        """Context manager for database sessions."""
-        async with self.async_session_maker() as session:  # type: ignore
-            yield session
-
-    async def get_documents(
-        self,
-        metadata_filters: dict,
-        ids: list | None = None,
-        offset: int | None = 0,
-        limit: int | None = 100,
-    ) -> list[dict]:
+    async def get_documents(self, metadata_filters: dict, ids: list = None):
         """Retrieve documents by metadata filters and ids.
 
         Args:
             metadata_filters (dict): The metadata filters to apply.
-            ids (list | None): Optional list of document IDs to filter.
-            offset (int | None): Offset for pagination.
-            limit (int | None): Limit for pagination.
 
         Returns:
-            list: The list of documents that match the filters.
+            list: The list of document IDs(primary key, not doc_id) that match the filters.
         """
-        if self.engine is None:
-            logger.warning(
-                "Database connection is not initialized, returning empty result"
-            )
-            return []
+        # metadata filter -> SQL WHERE clause
+        where_clauses = []
+        values = []
+        for key, val in metadata_filters.items():
+            where_clauses.append(f"json_extract(metadata, '$.{key}') = ?")
+            values.append(val)
+        if ids is not None and len(ids) > 0:
+            ids = [str(i) for i in ids if i != -1]
+            where_clauses.append("id IN ({})".format(",".join("?" * len(ids))))
+            values.extend(ids)
+        where_sql = " AND ".join(where_clauses) or "1=1"
 
-        async with self.get_session() as session:
-            query = select(Document)
-
-            for key, val in metadata_filters.items():
-                query = query.where(
-                    text(f"json_extract(metadata, '$.{key}') = :filter_{key}")
-                ).params(**{f"filter_{key}": val})
-
-            if ids is not None and len(ids) > 0:
-                valid_ids = [int(i) for i in ids if i != -1]
-                if valid_ids:
-                    query = query.where(col(Document.id).in_(valid_ids))
-
-            if limit is not None:
-                query = query.limit(limit)
-            if offset is not None:
-                query = query.offset(offset)
-
-            result = await session.execute(query)
-            documents = result.scalars().all()
-
-            return [self._document_to_dict(doc) for doc in documents]
-
-    async def insert_document(self, doc_id: str, text: str, metadata: dict) -> int:
-        """Insert a single document and return its integer ID.
-
-        Args:
-            doc_id (str): The document ID (UUID string).
-            text (str): The document text.
-            metadata (dict): The document metadata.
-
-        Returns:
-            int: The integer ID of the inserted document.
-        """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            async with session.begin():
-                document = Document(
-                    doc_id=doc_id,
-                    text=text,
-                    metadata_=json.dumps(metadata),
-                    created_at=datetime.now(),
-                    updated_at=datetime.now(),
-                )
-                session.add(document)
-                await session.flush()  # Flush to get the ID
-                return document.id  # type: ignore
-
-    async def insert_documents_batch(
-        self, doc_ids: list[str], texts: list[str], metadatas: list[dict]
-    ) -> list[int]:
-        """Batch insert documents and return their integer IDs.
-
-        Args:
-            doc_ids (list[str]): List of document IDs (UUID strings).
-            texts (list[str]): List of document texts.
-            metadatas (list[dict]): List of document metadata.
-
-        Returns:
-            list[int]: List of integer IDs of the inserted documents.
-        """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            async with session.begin():
-                import json
-
-                documents = []
-                for doc_id, text, metadata in zip(doc_ids, texts, metadatas):
-                    document = Document(
-                        doc_id=doc_id,
-                        text=text,
-                        metadata_=json.dumps(metadata),
-                        created_at=datetime.now(),
-                        updated_at=datetime.now(),
-                    )
-                    documents.append(document)
-                    session.add(document)
-
-                await session.flush()  # Flush to get all IDs
-                return [doc.id for doc in documents]  # type: ignore
-
-    async def delete_document_by_doc_id(self, doc_id: str):
-        """Delete a document by its doc_id.
-
-        Args:
-            doc_id (str): The doc_id of the document to delete.
-        """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            async with session.begin():
-                query = select(Document).where(col(Document.doc_id) == doc_id)
-                result = await session.execute(query)
-                document = result.scalar_one_or_none()
-
-                if document:
-                    await session.delete(document)
+        result = []
+        async with self.connection.cursor() as cursor:
+            sql = "SELECT * FROM documents WHERE " + where_sql
+            await cursor.execute(sql, values)
+            for row in await cursor.fetchall():
+                result.append(await self.tuple_to_dict(row))
+        return result
 
     async def get_document_by_doc_id(self, doc_id: str):
         """Retrieve a document by its doc_id.
@@ -227,91 +62,28 @@ class DocumentStorage:
             doc_id (str): The doc_id of the document to retrieve.
 
         Returns:
-            dict: The document data or None if not found.
+            dict: The document data.
         """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            query = select(Document).where(col(Document.doc_id) == doc_id)
-            result = await session.execute(query)
-            document = result.scalar_one_or_none()
-
-            if document:
-                return self._document_to_dict(document)
-            return None
+        async with self.connection.cursor() as cursor:
+            await cursor.execute("SELECT * FROM documents WHERE doc_id = ?", (doc_id,))
+            row = await cursor.fetchone()
+            if row:
+                return await self.tuple_to_dict(row)
+            else:
+                return None
 
     async def update_document_by_doc_id(self, doc_id: str, new_text: str):
-        """Update a document by its doc_id.
+        """Retrieve a document by its doc_id.
 
         Args:
             doc_id (str): The doc_id.
             new_text (str): The new text to update the document with.
         """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            async with session.begin():
-                query = select(Document).where(col(Document.doc_id) == doc_id)
-                result = await session.execute(query)
-                document = result.scalar_one_or_none()
-
-                if document:
-                    document.text = new_text
-                    document.updated_at = datetime.now()
-                    session.add(document)
-
-    async def delete_documents(self, metadata_filters: dict):
-        """Delete documents by their metadata filters.
-
-        Args:
-            metadata_filters (dict): The metadata filters to apply.
-        """
-        if self.engine is None:
-            logger.warning(
-                "Database connection is not initialized, skipping delete operation"
+        async with self.connection.cursor() as cursor:
+            await cursor.execute(
+                "UPDATE documents SET text = ? WHERE doc_id = ?", (new_text, doc_id)
             )
-            return
-
-        async with self.get_session() as session:
-            async with session.begin():
-                query = select(Document)
-
-                for key, val in metadata_filters.items():
-                    query = query.where(
-                        text(f"json_extract(metadata, '$.{key}') = :filter_{key}")
-                    ).params(**{f"filter_{key}": val})
-
-                result = await session.execute(query)
-                documents = result.scalars().all()
-
-                for doc in documents:
-                    await session.delete(doc)
-
-    async def count_documents(self, metadata_filters: dict | None = None) -> int:
-        """Count documents in the database.
-
-        Args:
-            metadata_filters (dict | None): Metadata filters to apply.
-
-        Returns:
-            int: The count of documents.
-        """
-        if self.engine is None:
-            logger.warning("Database connection is not initialized, returning 0")
-            return 0
-
-        async with self.get_session() as session:
-            query = select(func.count(col(Document.id)))
-
-            if metadata_filters:
-                for key, val in metadata_filters.items():
-                    query = query.where(
-                        text(f"json_extract(metadata, '$.{key}') = :filter_{key}")
-                    ).params(**{f"filter_{key}": val})
-
-            result = await session.execute(query)
-            count = result.scalar_one_or_none()
-            return count if count is not None else 0
+            await self.connection.commit()
 
     async def get_user_ids(self) -> list[str]:
         """Retrieve all user IDs from the documents table.
@@ -319,38 +91,11 @@ class DocumentStorage:
         Returns:
             list: A list of user IDs.
         """
-        assert self.engine is not None, "Database connection is not initialized."
-
-        async with self.get_session() as session:
-            query = text(
-                "SELECT DISTINCT user_id FROM documents WHERE user_id IS NOT NULL"
-            )
-            result = await session.execute(query)
-            rows = result.fetchall()
+        async with self.connection.cursor() as cursor:
+            await cursor.execute("SELECT DISTINCT user_id FROM documents")
+            rows = await cursor.fetchall()
             return [row[0] for row in rows]
 
-    def _document_to_dict(self, document: Document) -> dict:
-        """Convert a Document model to a dictionary.
-
-        Args:
-            document (Document): The document to convert.
-
-        Returns:
-            dict: The converted dictionary.
-        """
-        return {
-            "id": document.id,
-            "doc_id": document.doc_id,
-            "text": document.text,
-            "metadata": document.metadata_,
-            "created_at": document.created_at.isoformat()
-            if isinstance(document.created_at, datetime)
-            else document.created_at,
-            "updated_at": document.updated_at.isoformat()
-            if isinstance(document.updated_at, datetime)
-            else document.updated_at,
-        }
-
     async def tuple_to_dict(self, row):
         """Convert a tuple to a dictionary.
 
@@ -359,8 +104,6 @@ class DocumentStorage:
 
         Returns:
             dict: The converted dictionary.
-
-        Note: This method is kept for backward compatibility but is no longer used internally.
         """
         return {
             "id": row[0],
@@ -373,7 +116,6 @@ class DocumentStorage:
 
     async def close(self):
         """Close the connection to the SQLite database."""
-        if self.engine:
-            await self.engine.dispose()
-            self.engine = None
-            self.async_session_maker = None
+        if self.connection:
+            await self.connection.close()
+            self.connection = None

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

@@ -9,7 +9,7 @@ import numpy as np
 
 
 class EmbeddingStorage:
-    def __init__(self, dimension: int, path: str | None = None):
+    def __init__(self, dimension: int, path: str = None):
         self.dimension = dimension
         self.path = path
         self.index = None
@@ -18,6 +18,7 @@ class EmbeddingStorage:
         else:
             base_index = faiss.IndexFlatL2(dimension)
             self.index = faiss.IndexIDMap(base_index)
+        self.storage = {}
 
     async def insert(self, vector: np.ndarray, id: int):
         """插入向量
@@ -28,29 +29,12 @@ class EmbeddingStorage:
         Raises:
             ValueError: 如果向量的维度与存储的维度不匹配
         """
-        assert self.index is not None, "FAISS index is not initialized."
         if vector.shape[0] != self.dimension:
             raise ValueError(
                 f"向量维度不匹配, 期望: {self.dimension}, 实际: {vector.shape[0]}"
             )
         self.index.add_with_ids(vector.reshape(1, -1), np.array([id]))
-        await self.save_index()
-
-    async def insert_batch(self, vectors: np.ndarray, ids: list[int]):
-        """批量插入向量
-
-        Args:
-            vectors (np.ndarray): 要插入的向量数组
-            ids (list[int]): 向量的ID列表
-        Raises:
-            ValueError: 如果向量的维度与存储的维度不匹配
-        """
-        assert self.index is not None, "FAISS index is not initialized."
-        if vectors.shape[1] != self.dimension:
-            raise ValueError(
-                f"向量维度不匹配, 期望: {self.dimension}, 实际: {vectors.shape[1]}"
-            )
-        self.index.add_with_ids(vectors, np.array(ids))
+        self.storage[id] = vector
         await self.save_index()
 
     async def search(self, vector: np.ndarray, k: int) -> tuple:
@@ -62,22 +46,10 @@ class EmbeddingStorage:
         Returns:
             tuple: (距离, 索引)
         """
-        assert self.index is not None, "FAISS index is not initialized."
         faiss.normalize_L2(vector)
         distances, indices = self.index.search(vector, k)
         return distances, indices
 
-    async def delete(self, ids: list[int]):
-        """删除向量
-
-        Args:
-            ids (list[int]): 要删除的向量ID列表
-        """
-        assert self.index is not None, "FAISS index is not initialized."
-        id_array = np.array(ids, dtype=np.int64)
-        self.index.remove_ids(id_array)
-        await self.save_index()
-
     async def save_index(self):
         """保存索引
 

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

@@ -1,12 +1,10 @@
 import uuid
-import time
+import json
 import numpy as np
 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
-from astrbot import logger
 
 
 class FaissVecDB(BaseVecDB):
@@ -19,7 +17,6 @@ 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
@@ -29,14 +26,11 @@ 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 = None, id: str | None = None
-    ) -> int:
+    async def insert(self, content: str, metadata: dict = None, id: str = 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。
         """
@@ -45,64 +39,21 @@ class FaissVecDB(BaseVecDB):
 
         vector = await self.embedding_provider.get_embedding(content)
         vector = np.array(vector, dtype=np.float32)
+        async with self.document_storage.connection.cursor() as cursor:
+            await cursor.execute(
+                "INSERT INTO documents (doc_id, text, metadata) VALUES (?, ?, ?)",
+                (str_id, content, json.dumps(metadata)),
+            )
+            await self.document_storage.connection.commit()
+            result = await self.document_storage.get_document_by_doc_id(str_id)
+            int_id = result["id"]
 
-        # 使用 DocumentStorage 的方法插入文档
-        int_id = await self.document_storage.insert_document(str_id, content, metadata)
-
-        # 插入向量到 FAISS
-        await self.embedding_storage.insert(vector, int_id)
-        return int_id
-
-    async def insert_batch(
-        self,
-        contents: list[str],
-        metadatas: list[dict] | None = None,
-        ids: list[str] | None = None,
-        batch_size: int = 32,
-        tasks_limit: int = 3,
-        max_retries: int = 3,
-        progress_callback=None,
-    ) -> list[int]:
-        """
-        批量插入文本和其对应向量，自动生成 ID 并保持一致性。
-
-        Args:
-            progress_callback: 进度回调函数，接收参数 (current, total)
-        """
-        metadatas = metadatas or [{} for _ in contents]
-        ids = ids or [str(uuid.uuid4()) for _ in contents]
-
-        start = time.time()
-        logger.debug(f"Generating embeddings for {len(contents)} contents...")
-        vectors = await self.embedding_provider.get_embeddings_batch(
-            contents,
-            batch_size=batch_size,
-            tasks_limit=tasks_limit,
-            max_retries=max_retries,
-            progress_callback=progress_callback,
-        )
-        end = time.time()
-        logger.debug(
-            f"Generated embeddings for {len(contents)} contents in {end - start:.2f} seconds."
-        )
-
-        # 使用 DocumentStorage 的批量插入方法
-        int_ids = await self.document_storage.insert_documents_batch(
-            ids, contents, metadatas
-        )
-
-        # 批量插入向量到 FAISS
-        vectors_array = np.array(vectors).astype("float32")
-        await self.embedding_storage.insert_batch(vectors_array, int_ids)
-        return int_ids
+            # 插入向量到 FAISS
+            await self.embedding_storage.insert(vector, int_id)
+            return int_id
 
     async def retrieve(
-        self,
-        query: str,
-        k: int = 5,
-        fetch_k: int = 20,
-        rerank: bool = False,
-        metadata_filters: dict | None = None,
+        self, query: str, k: int = 5, fetch_k: int = 20, metadata_filters: dict = None
     ) -> list[Result]:
         """
         搜索最相似的文档。
@@ -111,7 +62,6 @@ 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:
@@ -122,6 +72,7 @@ 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
@@ -132,7 +83,7 @@ class FaissVecDB(BaseVecDB):
         )
         if not fetched_docs:
             return []
-        result_docs: list[Result] = []
+        result_docs = []
 
         idx_pos = {fetch_doc["id"]: idx for idx, fetch_doc in enumerate(fetched_docs)}
         for i, indice_idx in enumerate(indices[0]):
@@ -142,58 +93,25 @@ 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: str):
+    async def delete(self, doc_id: int):
         """
-        删除一条文档块（chunk）
+        删除一条文档
         """
-        # 获得对应的 int id
-        result = await self.document_storage.get_document_by_doc_id(doc_id)
-        int_id = result["id"] if result else None
-        if int_id is None:
-            return
-
-        # 使用 DocumentStorage 的删除方法
-        await self.document_storage.delete_document_by_doc_id(doc_id)
-        await self.embedding_storage.delete([int_id])
+        await self.document_storage.connection.execute(
+            "DELETE FROM documents WHERE doc_id = ?", (doc_id,)
+        )
+        await self.document_storage.connection.commit()
 
     async def close(self):
         await self.document_storage.close()
 
-    async def count_documents(self, metadata_filter: dict | None = None) -> int:
+    async def count_documents(self) -> int:
         """
         计算文档数量
-
-        Args:
-            metadata_filter (dict | None): 元数据过滤器
         """
-        count = await self.document_storage.count_documents(
-            metadata_filters=metadata_filter or {}
-        )
-        return count
-
-    async def delete_documents(self, metadata_filters: dict):
-        """
-        根据元数据过滤器删除文档
-        """
-        docs = await self.document_storage.get_documents(
-            metadata_filters=metadata_filters, offset=None, limit=None
-        )
-        doc_ids: list[int] = [doc["id"] for doc in docs]
-        await self.embedding_storage.delete(doc_ids)
-        await self.document_storage.delete_documents(metadata_filters=metadata_filters)
+        async with self.document_storage.connection.cursor() as cursor:
+            await cursor.execute("SELECT COUNT(*) FROM documents")
+            count = await cursor.fetchone()
+            return count[0] if count else 0

astrbot/core/event_bus.py

@@ -16,32 +16,30 @@ 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:
-    """用于处理事件的分发和处理"""
+    """事件总线: 用于处理事件的分发和处理
 
-    def __init__(
-        self,
-        event_queue: Queue,
-        pipeline_scheduler_mapping: dict[str, PipelineScheduler],
-        astrbot_config_mgr: AstrBotConfigManager = None,
-    ):
+    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):
         self.event_queue = event_queue  # 事件队列
-        # abconf uuid -> scheduler
-        self.pipeline_scheduler_mapping = pipeline_scheduler_mapping
-        self.astrbot_config_mgr = astrbot_config_mgr
+        self.pipeline_scheduler = pipeline_scheduler  # 管道调度器
 
     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()
-            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))
+            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
 
-    def _print_event(self, event: AstrMessageEvent, conf_name: str):
+    def _print_event(self, event: AstrMessageEvent):
         """用于记录事件信息
 
         Args:
@@ -50,10 +48,10 @@ 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"[{conf_name}] [{event.get_platform_id()}({event.get_platform_name()})] {event.get_sender_name()}/{event.get_sender_id()}: {event.get_message_outline()}"
+                f"[{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"[{conf_name}] [{event.get_platform_id()}({event.get_platform_name()})] {event.get_sender_id()}: {event.get_message_outline()}"
+                f"[{event.get_platform_name()}] {event.get_sender_id()}: {event.get_message_outline()}"
             )

astrbot/core/file_token_service.py

@@ -23,12 +23,7 @@ class FileTokenService:
         for token in expired_tokens:
             self.staged_files.pop(token, None)
 
-    async def check_token_expired(self, file_token: str) -> bool:
-        async with self.lock:
-            await self._cleanup_expired_tokens()
-            return file_token not in self.staged_files
-
-    async def register_file(self, file_path: str, timeout: float | None = None) -> str:
+    async def register_file(self, file_path: str, timeout: float = None) -> str:
         """向令牌服务注册一个文件。
 
         Args:

astrbot/core/initial_loader.py

@@ -22,7 +22,6 @@ class InitialLoader:
         self.db = db
         self.logger = logger
         self.log_broker = log_broker
-        self.webui_dir: str | None = None
 
     async def start(self):
         core_lifecycle = AstrBotCoreLifecycle(self.log_broker, self.db)
@@ -36,18 +35,13 @@ class InitialLoader:
 
         core_task = core_lifecycle.start()
 
-        webui_dir = self.webui_dir
-
         self.dashboard_server = AstrBotDashboard(
-            core_lifecycle, self.db, core_lifecycle.dashboard_shutdown_event, webui_dir
+            core_lifecycle, self.db, core_lifecycle.dashboard_shutdown_event
         )
+        task = asyncio.gather(
+            core_task, self.dashboard_server.run()
+        )  # 启动核心任务和仪表板服务器
 
-        coro = self.dashboard_server.run()
-        if coro:
-            # 启动核心任务和仪表板服务器
-            task = asyncio.gather(core_task, coro)
-        else:
-            task = core_task
         try:
             await task  # 整个AstrBot在这里运行
         except asyncio.CancelledError:

astrbot/core/knowledge_base/chunking/__init__.py

@@ -1,11 +0,0 @@
-"""
-文档分块模块
-"""
-
-from .base import BaseChunker
-from .fixed_size import FixedSizeChunker
-
-__all__ = [
-    "BaseChunker",
-    "FixedSizeChunker",
-]

astrbot/core/knowledge_base/chunking/base.py

@@ -1,24 +0,0 @@
-"""文档分块器基类
-
-定义了文档分块处理的抽象接口。
-"""
-
-from abc import ABC, abstractmethod
-
-
-class BaseChunker(ABC):
-    """分块器基类
-
-    所有分块器都应该继承此类并实现 chunk 方法。
-    """
-
-    @abstractmethod
-    async def chunk(self, text: str, **kwargs) -> list[str]:
-        """将文本分块
-
-        Args:
-            text: 输入文本
-
-        Returns:
-            list[str]: 分块后的文本列表
-        """

astrbot/core/knowledge_base/chunking/fixed_size.py

@@ -1,57 +0,0 @@
-"""固定大小分块器
-
-按照固定的字符数将文本分块,支持重叠区域。
-"""
-
-from .base import BaseChunker
-
-
-class FixedSizeChunker(BaseChunker):
-    """固定大小分块器
-
-    按照固定的字符数分块,并支持块之间的重叠。
-    """
-
-    def __init__(self, chunk_size: int = 512, chunk_overlap: int = 50):
-        """初始化分块器
-
-        Args:
-            chunk_size: 块的大小(字符数)
-            chunk_overlap: 块之间的重叠字符数
-        """
-        self.chunk_size = chunk_size
-        self.chunk_overlap = chunk_overlap
-
-    async def chunk(self, text: str, **kwargs) -> list[str]:
-        """固定大小分块
-
-        Args:
-            text: 输入文本
-            chunk_size: 每个文本块的最大大小
-            chunk_overlap: 每个文本块之间的重叠部分大小
-
-        Returns:
-            list[str]: 分块后的文本列表
-        """
-        chunk_size = kwargs.get("chunk_size", self.chunk_size)
-        chunk_overlap = kwargs.get("chunk_overlap", self.chunk_overlap)
-
-        chunks = []
-        start = 0
-        text_len = len(text)
-
-        while start < text_len:
-            end = start + chunk_size
-            chunk = text[start:end]
-
-            if chunk:
-                chunks.append(chunk)
-
-            # 移动窗口,保留重叠部分
-            start = end - chunk_overlap
-
-            # 防止无限循环: 如果重叠过大,直接移到end
-            if start >= end or chunk_overlap >= chunk_size:
-                start = end
-
-        return chunks

astrbot/core/knowledge_base/chunking/recursive.py

@@ -1,155 +0,0 @@
-from collections.abc import Callable
-from .base import BaseChunker
-
-
-class RecursiveCharacterChunker(BaseChunker):
-    def __init__(
-        self,
-        chunk_size: int = 500,
-        chunk_overlap: int = 100,
-        length_function: Callable[[str], int] = len,
-        is_separator_regex: bool = False,
-        separators: list[str] | None = None,
-    ):
-        """
-        初始化递归字符文本分割器
-
-        Args:
-            chunk_size: 每个文本块的最大大小
-            chunk_overlap: 每个文本块之间的重叠部分大小
-            length_function: 计算文本长度的函数
-            is_separator_regex: 分隔符是否为正则表达式
-            separators: 用于分割文本的分隔符列表，按优先级排序
-        """
-        self.chunk_size = chunk_size
-        self.chunk_overlap = chunk_overlap
-        self.length_function = length_function
-        self.is_separator_regex = is_separator_regex
-
-        # 默认分隔符列表，按优先级从高到低
-        self.separators = separators or [
-            "\n\n",  # 段落
-            "\n",  # 换行
-            "。",  # 中文句子
-            "，",  # 中文逗号
-            ". ",  # 句子
-            ", ",  # 逗号分隔
-            " ",  # 单词
-            "",  # 字符
-        ]
-
-    async def chunk(self, text: str, **kwargs) -> list[str]:
-        """
-        递归地将文本分割成块
-
-        Args:
-            text: 要分割的文本
-            chunk_size: 每个文本块的最大大小
-            chunk_overlap: 每个文本块之间的重叠部分大小
-
-        Returns:
-            分割后的文本块列表
-        """
-        if not text:
-            return []
-
-        overlap = kwargs.get("chunk_overlap", self.chunk_overlap)
-        chunk_size = kwargs.get("chunk_size", self.chunk_size)
-
-        text_length = self.length_function(text)
-        if text_length <= chunk_size:
-            return [text]
-
-        for separator in self.separators:
-            if separator == "":
-                return self._split_by_character(text, chunk_size, overlap)
-
-            if separator in text:
-                splits = text.split(separator)
-                # 重新添加分隔符（除了最后一个片段）
-                splits = [s + separator for s in splits[:-1]] + [splits[-1]]
-                splits = [s for s in splits if s]
-                if len(splits) == 1:
-                    continue
-
-                # 递归合并分割后的文本块
-                final_chunks = []
-                current_chunk = []
-                current_chunk_length = 0
-
-                for split in splits:
-                    split_length = self.length_function(split)
-
-                    # 如果单个分割部分已经超过了chunk_size，需要递归分割
-                    if split_length > chunk_size:
-                        # 先处理当前积累的块
-                        if current_chunk:
-                            combined_text = "".join(current_chunk)
-                            final_chunks.extend(
-                                await self.chunk(
-                                    combined_text,
-                                    chunk_size=chunk_size,
-                                    chunk_overlap=overlap,
-                                )
-                            )
-                            current_chunk = []
-                            current_chunk_length = 0
-
-                        # 递归分割过大的部分
-                        final_chunks.extend(
-                            await self.chunk(
-                                split, chunk_size=chunk_size, chunk_overlap=overlap
-                            )
-                        )
-                    # 如果添加这部分会使当前块超过chunk_size
-                    elif current_chunk_length + split_length > chunk_size:
-                        # 合并当前块并添加到结果中
-                        combined_text = "".join(current_chunk)
-                        final_chunks.append(combined_text)
-
-                        # 处理重叠部分
-                        overlap_start = max(0, len(combined_text) - overlap)
-                        if overlap_start > 0:
-                            overlap_text = combined_text[overlap_start:]
-                            current_chunk = [overlap_text, split]
-                            current_chunk_length = (
-                                self.length_function(overlap_text) + split_length
-                            )
-                        else:
-                            current_chunk = [split]
-                            current_chunk_length = split_length
-                    else:
-                        # 添加到当前块
-                        current_chunk.append(split)
-                        current_chunk_length += split_length
-
-                # 处理剩余的块
-                if current_chunk:
-                    final_chunks.append("".join(current_chunk))
-
-                return final_chunks
-
-        return [text]
-
-    def _split_by_character(
-        self, text: str, chunk_size: int | None = None, overlap: int | None = None
-    ) -> list[str]:
-        """
-        按字符级别分割文本
-
-        Args:
-            text: 要分割的文本
-
-        Returns:
-            分割后的文本块列表
-        """
-        chunk_size = chunk_size or self.chunk_size
-        overlap = overlap or self.chunk_overlap
-        result = []
-        for i in range(0, len(text), chunk_size - overlap):
-            end = min(i + chunk_size, len(text))
-            result.append(text[i:end])
-            if end == len(text):
-                break
-
-        return result

astrbot/core/knowledge_base/kb_db_sqlite.py

@@ -1,299 +0,0 @@
-from contextlib import asynccontextmanager
-from pathlib import Path
-
-from sqlmodel import col, desc
-from sqlalchemy import text, func, select, update, delete
-from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
-
-from astrbot.core import logger
-from astrbot.core.knowledge_base.models import (
-    BaseKBModel,
-    KBDocument,
-    KBMedia,
-    KnowledgeBase,
-)
-from astrbot.core.db.vec_db.faiss_impl import FaissVecDB
-
-
-class KBSQLiteDatabase:
-    def __init__(self, db_path: str = "data/knowledge_base/kb.db") -> None:
-        """初始化知识库数据库
-
-        Args:
-            db_path: 数据库文件路径, 默认为 data/knowledge_base/kb.db
-        """
-        self.db_path = db_path
-        self.DATABASE_URL = f"sqlite+aiosqlite:///{db_path}"
-        self.inited = False
-
-        # 确保目录存在
-        Path(db_path).parent.mkdir(parents=True, exist_ok=True)
-
-        # 创建异步引擎
-        self.engine = create_async_engine(
-            self.DATABASE_URL,
-            echo=False,
-            pool_pre_ping=True,
-            pool_recycle=3600,
-        )
-
-        # 创建会话工厂
-        self.async_session = async_sessionmaker(
-            self.engine,
-            class_=AsyncSession,
-            expire_on_commit=False,
-        )
-
-    @asynccontextmanager
-    async def get_db(self):
-        """获取数据库会话
-
-        用法:
-            async with kb_db.get_db() as session:
-                # 执行数据库操作
-                result = await session.execute(stmt)
-        """
-        async with self.async_session() as session:
-            yield session
-
-    async def initialize(self) -> None:
-        """初始化数据库,创建表并配置 SQLite 参数"""
-        async with self.engine.begin() as conn:
-            # 创建所有知识库相关表
-            await conn.run_sync(BaseKBModel.metadata.create_all)
-
-            # 配置 SQLite 性能优化参数
-            await conn.execute(text("PRAGMA journal_mode=WAL"))
-            await conn.execute(text("PRAGMA synchronous=NORMAL"))
-            await conn.execute(text("PRAGMA cache_size=20000"))
-            await conn.execute(text("PRAGMA temp_store=MEMORY"))
-            await conn.execute(text("PRAGMA mmap_size=134217728"))
-            await conn.execute(text("PRAGMA optimize"))
-            await conn.commit()
-
-        self.inited = True
-
-    async def migrate_to_v1(self) -> None:
-        """执行知识库数据库 v1 迁移
-
-        创建所有必要的索引以优化查询性能
-        """
-        async with self.get_db() as session:
-            session: AsyncSession
-            async with session.begin():
-                # 创建知识库表索引
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_kb_kb_id "
-                        "ON knowledge_bases(kb_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_kb_name "
-                        "ON knowledge_bases(kb_name)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_kb_created_at "
-                        "ON knowledge_bases(created_at)"
-                    )
-                )
-
-                # 创建文档表索引
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_doc_doc_id "
-                        "ON kb_documents(doc_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_doc_kb_id "
-                        "ON kb_documents(kb_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_doc_name "
-                        "ON kb_documents(doc_name)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_doc_type "
-                        "ON kb_documents(file_type)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_doc_created_at "
-                        "ON kb_documents(created_at)"
-                    )
-                )
-
-                # 创建多媒体表索引
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_media_media_id "
-                        "ON kb_media(media_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_media_doc_id "
-                        "ON kb_media(doc_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_media_kb_id ON kb_media(kb_id)"
-                    )
-                )
-                await session.execute(
-                    text(
-                        "CREATE INDEX IF NOT EXISTS idx_media_type "
-                        "ON kb_media(media_type)"
-                    )
-                )
-
-                await session.commit()
-
-    async def close(self) -> None:
-        """关闭数据库连接"""
-        await self.engine.dispose()
-        logger.info(f"知识库数据库已关闭: {self.db_path}")
-
-    async def get_kb_by_id(self, kb_id: str) -> KnowledgeBase | None:
-        """根据 ID 获取知识库"""
-        async with self.get_db() as session:
-            stmt = select(KnowledgeBase).where(col(KnowledgeBase.kb_id) == kb_id)
-            result = await session.execute(stmt)
-            return result.scalar_one_or_none()
-
-    async def get_kb_by_name(self, kb_name: str) -> KnowledgeBase | None:
-        """根据名称获取知识库"""
-        async with self.get_db() as session:
-            stmt = select(KnowledgeBase).where(col(KnowledgeBase.kb_name) == kb_name)
-            result = await session.execute(stmt)
-            return result.scalar_one_or_none()
-
-    async def list_kbs(self, offset: int = 0, limit: int = 100) -> list[KnowledgeBase]:
-        """列出所有知识库"""
-        async with self.get_db() as session:
-            stmt = (
-                select(KnowledgeBase)
-                .offset(offset)
-                .limit(limit)
-                .order_by(desc(KnowledgeBase.created_at))
-            )
-            result = await session.execute(stmt)
-            return list(result.scalars().all())
-
-    async def count_kbs(self) -> int:
-        """统计知识库数量"""
-        async with self.get_db() as session:
-            stmt = select(func.count(col(KnowledgeBase.id)))
-            result = await session.execute(stmt)
-            return result.scalar() or 0
-
-    # ===== 文档查询 =====
-
-    async def get_document_by_id(self, doc_id: str) -> KBDocument | None:
-        """根据 ID 获取文档"""
-        async with self.get_db() as session:
-            stmt = select(KBDocument).where(col(KBDocument.doc_id) == doc_id)
-            result = await session.execute(stmt)
-            return result.scalar_one_or_none()
-
-    async def list_documents_by_kb(
-        self, kb_id: str, offset: int = 0, limit: int = 100
-    ) -> list[KBDocument]:
-        """列出知识库的所有文档"""
-        async with self.get_db() as session:
-            stmt = (
-                select(KBDocument)
-                .where(col(KBDocument.kb_id) == kb_id)
-                .offset(offset)
-                .limit(limit)
-                .order_by(desc(KBDocument.created_at))
-            )
-            result = await session.execute(stmt)
-            return list(result.scalars().all())
-
-    async def count_documents_by_kb(self, kb_id: str) -> int:
-        """统计知识库的文档数量"""
-        async with self.get_db() as session:
-            stmt = select(func.count(col(KBDocument.id))).where(
-                col(KBDocument.kb_id) == kb_id
-            )
-            result = await session.execute(stmt)
-            return result.scalar() or 0
-
-    async def get_document_with_metadata(self, doc_id: str) -> dict | None:
-        async with self.get_db() as session:
-            stmt = (
-                select(KBDocument, KnowledgeBase)
-                .join(KnowledgeBase, col(KBDocument.kb_id) == col(KnowledgeBase.kb_id))
-                .where(col(KBDocument.doc_id) == doc_id)
-            )
-            result = await session.execute(stmt)
-            row = result.first()
-
-            if not row:
-                return None
-
-            return {
-                "document": row[0],
-                "knowledge_base": row[1],
-            }
-
-    async def delete_document_by_id(self, doc_id: str, vec_db: FaissVecDB):
-        """删除单个文档及其相关数据"""
-        # 在知识库表中删除
-        async with self.get_db() as session:
-            async with session.begin():
-                # 删除文档记录
-                delete_stmt = delete(KBDocument).where(col(KBDocument.doc_id) == doc_id)
-                await session.execute(delete_stmt)
-                await session.commit()
-
-        # 在 vec db 中删除相关向量
-        await vec_db.delete_documents(metadata_filters={"kb_doc_id": doc_id})
-
-    # ===== 多媒体查询 =====
-
-    async def list_media_by_doc(self, doc_id: str) -> list[KBMedia]:
-        """列出文档的所有多媒体资源"""
-        async with self.get_db() as session:
-            stmt = select(KBMedia).where(col(KBMedia.doc_id) == doc_id)
-            result = await session.execute(stmt)
-            return list(result.scalars().all())
-
-    async def get_media_by_id(self, media_id: str) -> KBMedia | None:
-        """根据 ID 获取多媒体资源"""
-        async with self.get_db() as session:
-            stmt = select(KBMedia).where(col(KBMedia.media_id) == media_id)
-            result = await session.execute(stmt)
-            return result.scalar_one_or_none()
-
-    async def update_kb_stats(self, kb_id: str, vec_db: FaissVecDB) -> None:
-        """更新知识库统计信息"""
-        chunk_cnt = await vec_db.count_documents()
-
-        async with self.get_db() as session:
-            async with session.begin():
-                update_stmt = (
-                    update(KnowledgeBase)
-                    .where(col(KnowledgeBase.kb_id) == kb_id)
-                    .values(
-                        doc_count=select(func.count(col(KBDocument.id)))
-                        .where(col(KBDocument.kb_id) == kb_id)
-                        .scalar_subquery(),
-                        chunk_count=chunk_cnt,
-                    )
-                )
-
-                await session.execute(update_stmt)
-                await session.commit()

astrbot/core/knowledge_base/kb_helper.py

@@ -1,348 +0,0 @@
-import uuid
-import aiofiles
-import json
-from pathlib import Path
-from .models import KnowledgeBase, KBDocument, KBMedia
-from .kb_db_sqlite import KBSQLiteDatabase
-from astrbot.core.db.vec_db.base import BaseVecDB
-from astrbot.core.db.vec_db.faiss_impl.vec_db import FaissVecDB
-from astrbot.core.provider.provider import EmbeddingProvider, RerankProvider
-from astrbot.core.provider.manager import ProviderManager
-from .parsers.util import select_parser
-from .chunking.base import BaseChunker
-from astrbot.core import logger
-
-
-class KBHelper:
-    vec_db: BaseVecDB
-    kb: KnowledgeBase
-
-    def __init__(
-        self,
-        kb_db: KBSQLiteDatabase,
-        kb: KnowledgeBase,
-        provider_manager: ProviderManager,
-        kb_root_dir: str,
-        chunker: BaseChunker,
-    ):
-        self.kb_db = kb_db
-        self.kb = kb
-        self.prov_mgr = provider_manager
-        self.kb_root_dir = kb_root_dir
-        self.chunker = chunker
-
-        self.kb_dir = Path(self.kb_root_dir) / self.kb.kb_id
-        self.kb_medias_dir = Path(self.kb_dir) / "medias" / self.kb.kb_id
-        self.kb_files_dir = Path(self.kb_dir) / "files" / self.kb.kb_id
-
-        self.kb_medias_dir.mkdir(parents=True, exist_ok=True)
-        self.kb_files_dir.mkdir(parents=True, exist_ok=True)
-
-    async def initialize(self):
-        await self._ensure_vec_db()
-
-    async def get_ep(self) -> EmbeddingProvider:
-        if not self.kb.embedding_provider_id:
-            raise ValueError(f"知识库 {self.kb.kb_name} 未配置 Embedding Provider")
-        ep: EmbeddingProvider = await self.prov_mgr.get_provider_by_id(
-            self.kb.embedding_provider_id
-        )  # type: ignore
-        if not ep:
-            raise ValueError(
-                f"无法找到 ID 为 {self.kb.embedding_provider_id} 的 Embedding Provider"
-            )
-        return ep
-
-    async def get_rp(self) -> RerankProvider | None:
-        if not self.kb.rerank_provider_id:
-            return None
-        rp: RerankProvider = await self.prov_mgr.get_provider_by_id(
-            self.kb.rerank_provider_id
-        )  # type: ignore
-        if not rp:
-            raise ValueError(
-                f"无法找到 ID 为 {self.kb.rerank_provider_id} 的 Rerank Provider"
-            )
-        return rp
-
-    async def _ensure_vec_db(self) -> FaissVecDB:
-        if not self.kb.embedding_provider_id:
-            raise ValueError(f"知识库 {self.kb.kb_name} 未配置 Embedding Provider")
-
-        ep = await self.get_ep()
-        rp = await self.get_rp()
-
-        vec_db = FaissVecDB(
-            doc_store_path=str(self.kb_dir / "doc.db"),
-            index_store_path=str(self.kb_dir / "index.faiss"),
-            embedding_provider=ep,
-            rerank_provider=rp,
-        )
-        await vec_db.initialize()
-        self.vec_db = vec_db
-        return vec_db
-
-    async def delete_vec_db(self):
-        """删除知识库的向量数据库和所有相关文件"""
-        import shutil
-
-        await self.terminate()
-        if self.kb_dir.exists():
-            shutil.rmtree(self.kb_dir)
-
-    async def terminate(self):
-        if self.vec_db:
-            await self.vec_db.close()
-
-    async def upload_document(
-        self,
-        file_name: str,
-        file_content: bytes,
-        file_type: str,
-        chunk_size: int = 512,
-        chunk_overlap: int = 50,
-        batch_size: int = 32,
-        tasks_limit: int = 3,
-        max_retries: int = 3,
-        progress_callback=None,
-    ) -> KBDocument:
-        """上传并处理文档（带原子性保证和失败清理）
-
-        流程:
-        1. 保存原始文件
-        2. 解析文档内容
-        3. 提取多媒体资源
-        4. 分块处理
-        5. 生成向量并存储
-        6. 保存元数据（事务）
-        7. 更新统计
-
-        Args:
-            progress_callback: 进度回调函数，接收参数 (stage, current, total)
-                - stage: 当前阶段 ('parsing', 'chunking', 'embedding')
-                - current: 当前进度
-                - total: 总数
-        """
-        await self._ensure_vec_db()
-        doc_id = str(uuid.uuid4())
-        media_paths: list[Path] = []
-
-        # file_path = self.kb_files_dir / f"{doc_id}.{file_type}"
-        # async with aiofiles.open(file_path, "wb") as f:
-        #     await f.write(file_content)
-
-        try:
-            # 阶段1: 解析文档
-            if progress_callback:
-                await progress_callback("parsing", 0, 100)
-
-            parser = await select_parser(f".{file_type}")
-            parse_result = await parser.parse(file_content, file_name)
-            text_content = parse_result.text
-            media_items = parse_result.media
-
-            if progress_callback:
-                await progress_callback("parsing", 100, 100)
-
-            # 保存媒体文件
-            saved_media = []
-            for media_item in media_items:
-                media = await self._save_media(
-                    doc_id=doc_id,
-                    media_type=media_item.media_type,
-                    file_name=media_item.file_name,
-                    content=media_item.content,
-                    mime_type=media_item.mime_type,
-                )
-                saved_media.append(media)
-                media_paths.append(Path(media.file_path))
-
-            # 阶段2: 分块
-            if progress_callback:
-                await progress_callback("chunking", 0, 100)
-
-            chunks_text = await self.chunker.chunk(
-                text_content, chunk_size=chunk_size, chunk_overlap=chunk_overlap
-            )
-            contents = []
-            metadatas = []
-            for idx, chunk_text in enumerate(chunks_text):
-                contents.append(chunk_text)
-                metadatas.append(
-                    {
-                        "kb_id": self.kb.kb_id,
-                        "kb_doc_id": doc_id,
-                        "chunk_index": idx,
-                    }
-                )
-
-            if progress_callback:
-                await progress_callback("chunking", 100, 100)
-
-            # 阶段3: 生成向量（带进度回调）
-            async def embedding_progress_callback(current, total):
-                if progress_callback:
-                    await progress_callback("embedding", current, total)
-
-            await self.vec_db.insert_batch(
-                contents=contents,
-                metadatas=metadatas,
-                batch_size=batch_size,
-                tasks_limit=tasks_limit,
-                max_retries=max_retries,
-                progress_callback=embedding_progress_callback,
-            )
-
-            # 保存文档的元数据
-            doc = KBDocument(
-                doc_id=doc_id,
-                kb_id=self.kb.kb_id,
-                doc_name=file_name,
-                file_type=file_type,
-                file_size=len(file_content),
-                # file_path=str(file_path),
-                file_path="",
-                chunk_count=len(chunks_text),
-                media_count=0,
-            )
-            async with self.kb_db.get_db() as session:
-                async with session.begin():
-                    session.add(doc)
-                    for media in saved_media:
-                        session.add(media)
-                    await session.commit()
-
-                await session.refresh(doc)
-
-            vec_db: FaissVecDB = self.vec_db  # type: ignore
-            await self.kb_db.update_kb_stats(kb_id=self.kb.kb_id, vec_db=vec_db)
-            await self.refresh_kb()
-            await self.refresh_document(doc_id)
-            return doc
-        except Exception as e:
-            logger.error(f"上传文档失败: {e}")
-            # if file_path.exists():
-            #     file_path.unlink()
-
-            for media_path in media_paths:
-                try:
-                    if media_path.exists():
-                        media_path.unlink()
-                except Exception as me:
-                    logger.warning(f"清理多媒体文件失败 {media_path}: {me}")
-
-            raise e
-
-    async def list_documents(
-        self, offset: int = 0, limit: int = 100
-    ) -> list[KBDocument]:
-        """列出知识库的所有文档"""
-        docs = await self.kb_db.list_documents_by_kb(self.kb.kb_id, offset, limit)
-        return docs
-
-    async def get_document(self, doc_id: str) -> KBDocument | None:
-        """获取单个文档"""
-        doc = await self.kb_db.get_document_by_id(doc_id)
-        return doc
-
-    async def delete_document(self, doc_id: str):
-        """删除单个文档及其相关数据"""
-        await self.kb_db.delete_document_by_id(
-            doc_id=doc_id,
-            vec_db=self.vec_db,  # type: ignore
-        )
-        await self.kb_db.update_kb_stats(
-            kb_id=self.kb.kb_id,
-            vec_db=self.vec_db,  # type: ignore
-        )
-        await self.refresh_kb()
-
-    async def delete_chunk(self, chunk_id: str, doc_id: str):
-        """删除单个文本块及其相关数据"""
-        vec_db: FaissVecDB = self.vec_db  # type: ignore
-        await vec_db.delete(chunk_id)
-        await self.kb_db.update_kb_stats(
-            kb_id=self.kb.kb_id,
-            vec_db=self.vec_db,  # type: ignore
-        )
-        await self.refresh_kb()
-        await self.refresh_document(doc_id)
-
-    async def refresh_kb(self):
-        if self.kb:
-            kb = await self.kb_db.get_kb_by_id(self.kb.kb_id)
-            if kb:
-                self.kb = kb
-
-    async def refresh_document(self, doc_id: str) -> None:
-        """更新文档的元数据"""
-        doc = await self.get_document(doc_id)
-        if not doc:
-            raise ValueError(f"无法找到 ID 为 {doc_id} 的文档")
-        chunk_count = await self.get_chunk_count_by_doc_id(doc_id)
-        doc.chunk_count = chunk_count
-        async with self.kb_db.get_db() as session:
-            async with session.begin():
-                session.add(doc)
-                await session.commit()
-            await session.refresh(doc)
-
-    async def get_chunks_by_doc_id(
-        self, doc_id: str, offset: int = 0, limit: int = 100
-    ) -> list[dict]:
-        """获取文档的所有块及其元数据"""
-        vec_db: FaissVecDB = self.vec_db  # type: ignore
-        chunks = await vec_db.document_storage.get_documents(
-            metadata_filters={"kb_doc_id": doc_id}, offset=offset, limit=limit
-        )
-        result = []
-        for chunk in chunks:
-            chunk_md = json.loads(chunk["metadata"])
-            result.append(
-                {
-                    "chunk_id": chunk["doc_id"],
-                    "doc_id": chunk_md["kb_doc_id"],
-                    "kb_id": chunk_md["kb_id"],
-                    "chunk_index": chunk_md["chunk_index"],
-                    "content": chunk["text"],
-                    "char_count": len(chunk["text"]),
-                }
-            )
-        return result
-
-    async def get_chunk_count_by_doc_id(self, doc_id: str) -> int:
-        """获取文档的块数量"""
-        vec_db: FaissVecDB = self.vec_db  # type: ignore
-        count = await vec_db.count_documents(metadata_filter={"kb_doc_id": doc_id})
-        return count
-
-    async def _save_media(
-        self,
-        doc_id: str,
-        media_type: str,
-        file_name: str,
-        content: bytes,
-        mime_type: str,
-    ) -> KBMedia:
-        """保存多媒体资源"""
-        media_id = str(uuid.uuid4())
-        ext = Path(file_name).suffix
-
-        # 保存文件
-        file_path = self.kb_medias_dir / doc_id / f"{media_id}{ext}"
-        file_path.parent.mkdir(parents=True, exist_ok=True)
-        async with aiofiles.open(file_path, "wb") as f:
-            await f.write(content)
-
-        media = KBMedia(
-            media_id=media_id,
-            doc_id=doc_id,
-            kb_id=self.kb.kb_id,
-            media_type=media_type,
-            file_name=file_name,
-            file_path=str(file_path),
-            file_size=len(content),
-            mime_type=mime_type,
-        )
-
-        return media

astrbot/core/knowledge_base/kb_mgr.py

@@ -1,287 +0,0 @@
-import traceback
-from pathlib import Path
-from astrbot.core import logger
-from astrbot.core.provider.manager import ProviderManager
-
-from .retrieval.manager import RetrievalManager, RetrievalResult
-from .retrieval.sparse_retriever import SparseRetriever
-from .retrieval.rank_fusion import RankFusion
-from .kb_db_sqlite import KBSQLiteDatabase
-
-# from .chunking.fixed_size import FixedSizeChunker
-from .chunking.recursive import RecursiveCharacterChunker
-from .kb_helper import KBHelper
-
-from .models import KnowledgeBase
-
-
-FILES_PATH = "data/knowledge_base"
-DB_PATH = Path(FILES_PATH) / "kb.db"
-"""Knowledge Base storage root directory"""
-CHUNKER = RecursiveCharacterChunker()
-
-
-class KnowledgeBaseManager:
-    kb_db: KBSQLiteDatabase
-    retrieval_manager: RetrievalManager
-
-    def __init__(
-        self,
-        provider_manager: ProviderManager,
-    ):
-        Path(DB_PATH).parent.mkdir(parents=True, exist_ok=True)
-        self.provider_manager = provider_manager
-        self._session_deleted_callback_registered = False
-
-        self.kb_insts: dict[str, KBHelper] = {}
-
-    async def initialize(self):
-        """初始化知识库模块"""
-        try:
-            logger.info("正在初始化知识库模块...")
-
-            # 初始化数据库
-            await self._init_kb_database()
-
-            # 初始化检索管理器
-            sparse_retriever = SparseRetriever(self.kb_db)
-            rank_fusion = RankFusion(self.kb_db)
-            self.retrieval_manager = RetrievalManager(
-                sparse_retriever=sparse_retriever,
-                rank_fusion=rank_fusion,
-                kb_db=self.kb_db,
-            )
-            await self.load_kbs()
-
-        except ImportError as e:
-            logger.error(f"知识库模块导入失败: {e}")
-            logger.warning("请确保已安装所需依赖: pypdf, aiofiles, Pillow, rank-bm25")
-        except Exception as e:
-            logger.error(f"知识库模块初始化失败: {e}")
-            logger.error(traceback.format_exc())
-
-    async def _init_kb_database(self):
-        self.kb_db = KBSQLiteDatabase(DB_PATH.as_posix())
-        await self.kb_db.initialize()
-        await self.kb_db.migrate_to_v1()
-        logger.info(f"KnowledgeBase database initialized: {DB_PATH}")
-
-    async def load_kbs(self):
-        """加载所有知识库实例"""
-        kb_records = await self.kb_db.list_kbs()
-        for record in kb_records:
-            kb_helper = KBHelper(
-                kb_db=self.kb_db,
-                kb=record,
-                provider_manager=self.provider_manager,
-                kb_root_dir=FILES_PATH,
-                chunker=CHUNKER,
-            )
-            await kb_helper.initialize()
-            self.kb_insts[record.kb_id] = kb_helper
-
-    async def create_kb(
-        self,
-        kb_name: str,
-        description: str | None = None,
-        emoji: str | None = None,
-        embedding_provider_id: str | None = None,
-        rerank_provider_id: str | None = None,
-        chunk_size: int | None = None,
-        chunk_overlap: int | None = None,
-        top_k_dense: int | None = None,
-        top_k_sparse: int | None = None,
-        top_m_final: int | None = None,
-    ) -> KBHelper:
-        """创建新的知识库实例"""
-        kb = KnowledgeBase(
-            kb_name=kb_name,
-            description=description,
-            emoji=emoji or "📚",
-            embedding_provider_id=embedding_provider_id,
-            rerank_provider_id=rerank_provider_id,
-            chunk_size=chunk_size if chunk_size is not None else 512,
-            chunk_overlap=chunk_overlap if chunk_overlap is not None else 50,
-            top_k_dense=top_k_dense if top_k_dense is not None else 50,
-            top_k_sparse=top_k_sparse if top_k_sparse is not None else 50,
-            top_m_final=top_m_final if top_m_final is not None else 5,
-        )
-        async with self.kb_db.get_db() as session:
-            session.add(kb)
-            await session.commit()
-            await session.refresh(kb)
-
-            kb_helper = KBHelper(
-                kb_db=self.kb_db,
-                kb=kb,
-                provider_manager=self.provider_manager,
-                kb_root_dir=FILES_PATH,
-                chunker=CHUNKER,
-            )
-            await kb_helper.initialize()
-        self.kb_insts[kb.kb_id] = kb_helper
-        return kb_helper
-
-    async def get_kb(self, kb_id: str) -> KBHelper | None:
-        """获取知识库实例"""
-        if kb_id in self.kb_insts:
-            return self.kb_insts[kb_id]
-
-    async def get_kb_by_name(self, kb_name: str) -> KBHelper | None:
-        """通过名称获取知识库实例"""
-        for kb_helper in self.kb_insts.values():
-            if kb_helper.kb.kb_name == kb_name:
-                return kb_helper
-        return None
-
-    async def delete_kb(self, kb_id: str) -> bool:
-        """删除知识库实例"""
-        kb_helper = await self.get_kb(kb_id)
-        if not kb_helper:
-            return False
-
-        await kb_helper.delete_vec_db()
-        async with self.kb_db.get_db() as session:
-            await session.delete(kb_helper.kb)
-            await session.commit()
-
-        self.kb_insts.pop(kb_id, None)
-        return True
-
-    async def list_kbs(self) -> list[KnowledgeBase]:
-        """列出所有知识库实例"""
-        kbs = [kb_helper.kb for kb_helper in self.kb_insts.values()]
-        return kbs
-
-    async def update_kb(
-        self,
-        kb_id: str,
-        kb_name: str,
-        description: str | None = None,
-        emoji: str | None = None,
-        embedding_provider_id: str | None = None,
-        rerank_provider_id: str | None = None,
-        chunk_size: int | None = None,
-        chunk_overlap: int | None = None,
-        top_k_dense: int | None = None,
-        top_k_sparse: int | None = None,
-        top_m_final: int | None = None,
-    ) -> KBHelper | None:
-        """更新知识库实例"""
-        kb_helper = await self.get_kb(kb_id)
-        if not kb_helper:
-            return None
-
-        kb = kb_helper.kb
-        if kb_name is not None:
-            kb.kb_name = kb_name
-        if description is not None:
-            kb.description = description
-        if emoji is not None:
-            kb.emoji = emoji
-        if embedding_provider_id is not None:
-            kb.embedding_provider_id = embedding_provider_id
-        kb.rerank_provider_id = rerank_provider_id  # 允许设置为 None
-        if chunk_size is not None:
-            kb.chunk_size = chunk_size
-        if chunk_overlap is not None:
-            kb.chunk_overlap = chunk_overlap
-        if top_k_dense is not None:
-            kb.top_k_dense = top_k_dense
-        if top_k_sparse is not None:
-            kb.top_k_sparse = top_k_sparse
-        if top_m_final is not None:
-            kb.top_m_final = top_m_final
-        async with self.kb_db.get_db() as session:
-            session.add(kb)
-            await session.commit()
-            await session.refresh(kb)
-
-        return kb_helper
-
-    async def retrieve(
-        self,
-        query: str,
-        kb_names: list[str],
-        top_k_fusion: int = 20,
-        top_m_final: int = 5,
-    ) -> dict | None:
-        """从指定知识库中检索相关内容"""
-        kb_ids = []
-        kb_id_helper_map = {}
-        for kb_name in kb_names:
-            if kb_helper := await self.get_kb_by_name(kb_name):
-                kb_ids.append(kb_helper.kb.kb_id)
-                kb_id_helper_map[kb_helper.kb.kb_id] = kb_helper
-
-        if not kb_ids:
-            return {}
-
-        results = await self.retrieval_manager.retrieve(
-            query=query,
-            kb_ids=kb_ids,
-            kb_id_helper_map=kb_id_helper_map,
-            top_k_fusion=top_k_fusion,
-            top_m_final=top_m_final,
-        )
-        if not results:
-            return None
-
-        context_text = self._format_context(results)
-
-        results_dict = [
-            {
-                "chunk_id": r.chunk_id,
-                "doc_id": r.doc_id,
-                "kb_id": r.kb_id,
-                "kb_name": r.kb_name,
-                "doc_name": r.doc_name,
-                "chunk_index": r.metadata.get("chunk_index", 0),
-                "content": r.content,
-                "score": r.score,
-                "char_count": r.metadata.get("char_count", 0),
-            }
-            for r in results
-        ]
-
-        return {
-            "context_text": context_text,
-            "results": results_dict,
-        }
-
-    def _format_context(self, results: list[RetrievalResult]) -> str:
-        """格式化知识上下文
-
-        Args:
-            results: 检索结果列表
-
-        Returns:
-            str: 格式化的上下文文本
-        """
-        lines = ["以下是相关的知识库内容,请参考这些信息回答用户的问题:\n"]
-
-        for i, result in enumerate(results, 1):
-            lines.append(f"【知识 {i}】")
-            lines.append(f"来源: {result.kb_name} / {result.doc_name}")
-            lines.append(f"内容: {result.content}")
-            lines.append(f"相关度: {result.score:.2f}")
-            lines.append("")
-
-        return "\n".join(lines)
-
-    async def terminate(self):
-        """终止所有知识库实例,关闭数据库连接"""
-        for kb_id, kb_helper in self.kb_insts.items():
-            try:
-                await kb_helper.terminate()
-            except Exception as e:
-                logger.error(f"关闭知识库 {kb_id} 失败: {e}")
-
-        self.kb_insts.clear()
-
-        # 关闭元数据数据库
-        if hasattr(self, "kb_db") and self.kb_db:
-            try:
-                await self.kb_db.close()
-            except Exception as e:
-                logger.error(f"关闭知识库元数据数据库失败: {e}")

astrbot/core/knowledge_base/models.py

@@ -1,114 +0,0 @@
-import uuid
-from datetime import datetime, timezone
-
-from sqlmodel import Field, SQLModel, Text, UniqueConstraint, MetaData
-
-
-class BaseKBModel(SQLModel, table=False):
-    metadata = MetaData()
-
-
-class KnowledgeBase(BaseKBModel, table=True):
-    """知识库表
-
-    存储知识库的基本信息和统计数据。
-    """
-
-    __tablename__ = "knowledge_bases"  # type: ignore
-
-    id: int | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    kb_id: str = Field(
-        max_length=36,
-        nullable=False,
-        unique=True,
-        default_factory=lambda: str(uuid.uuid4()),
-        index=True,
-    )
-    kb_name: str = Field(max_length=100, nullable=False)
-    description: str | None = Field(default=None, sa_type=Text)
-    emoji: str | None = Field(default="📚", max_length=10)
-    embedding_provider_id: str | None = Field(default=None, max_length=100)
-    rerank_provider_id: str | None = Field(default=None, max_length=100)
-    # 分块配置参数
-    chunk_size: int | None = Field(default=512, nullable=True)
-    chunk_overlap: int | None = Field(default=50, nullable=True)
-    # 检索配置参数
-    top_k_dense: int | None = Field(default=50, nullable=True)
-    top_k_sparse: int | None = Field(default=50, nullable=True)
-    top_m_final: int | None = Field(default=5, nullable=True)
-    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)},
-    )
-    doc_count: int = Field(default=0, nullable=False)
-    chunk_count: int = Field(default=0, nullable=False)
-
-    __table_args__ = (
-        UniqueConstraint(
-            "kb_name",
-            name="uix_kb_name",
-        ),
-    )
-
-
-class KBDocument(BaseKBModel, table=True):
-    """文档表
-
-    存储上传到知识库的文档元数据。
-    """
-
-    __tablename__ = "kb_documents"  # type: ignore
-
-    id: int | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    doc_id: str = Field(
-        max_length=36,
-        nullable=False,
-        unique=True,
-        default_factory=lambda: str(uuid.uuid4()),
-        index=True,
-    )
-    kb_id: str = Field(max_length=36, nullable=False, index=True)
-    doc_name: str = Field(max_length=255, nullable=False)
-    file_type: str = Field(max_length=20, nullable=False)
-    file_size: int = Field(nullable=False)
-    file_path: str = Field(max_length=512, nullable=False)
-    chunk_count: int = Field(default=0, nullable=False)
-    media_count: int = Field(default=0, 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)},
-    )
-
-
-class KBMedia(BaseKBModel, table=True):
-    """多媒体资源表
-
-    存储从文档中提取的图片、视频等多媒体资源。
-    """
-
-    __tablename__ = "kb_media"  # type: ignore
-
-    id: int | None = Field(
-        primary_key=True, sa_column_kwargs={"autoincrement": True}, default=None
-    )
-    media_id: str = Field(
-        max_length=36,
-        nullable=False,
-        unique=True,
-        default_factory=lambda: str(uuid.uuid4()),
-        index=True,
-    )
-    doc_id: str = Field(max_length=36, nullable=False, index=True)
-    kb_id: str = Field(max_length=36, nullable=False, index=True)
-    media_type: str = Field(max_length=20, nullable=False)
-    file_name: str = Field(max_length=255, nullable=False)
-    file_path: str = Field(max_length=512, nullable=False)
-    file_size: int = Field(nullable=False)
-    mime_type: str = Field(max_length=100, nullable=False)
-    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))

astrbot/core/knowledge_base/parsers/__init__.py

@@ -1,15 +0,0 @@
-"""
-文档解析器模块
-"""
-
-from .base import BaseParser, MediaItem, ParseResult
-from .text_parser import TextParser
-from .pdf_parser import PDFParser
-
-__all__ = [
-    "BaseParser",
-    "MediaItem",
-    "ParseResult",
-    "TextParser",
-    "PDFParser",
-]

astrbot/core/knowledge_base/parsers/base.py

@@ -1,50 +0,0 @@
-"""文档解析器基类和数据结构
-
-定义了文档解析器的抽象接口和相关数据类。
-"""
-
-from abc import ABC, abstractmethod
-from dataclasses import dataclass
-
-
-@dataclass
-class MediaItem:
-    """多媒体项
-
-    表示从文档中提取的多媒体资源。
-    """
-
-    media_type: str  # image, video
-    file_name: str
-    content: bytes
-    mime_type: str
-
-
-@dataclass
-class ParseResult:
-    """解析结果
-
-    包含解析后的文本内容和提取的多媒体资源。
-    """
-
-    text: str
-    media: list[MediaItem]
-
-
-class BaseParser(ABC):
-    """文档解析器基类
-
-    所有文档解析器都应该继承此类并实现 parse 方法。
-    """
-
-    @abstractmethod
-    async def parse(self, file_content: bytes, file_name: str) -> ParseResult:
-        """解析文档
-
-        Args:
-            file_content: 文件内容
-            file_name: 文件名
-
-        Returns:
-            ParseResult: 解析结果
-        """

astrbot/core/knowledge_base/parsers/markitdown_parser.py

@@ -1,25 +0,0 @@
-import io
-import os
-
-from astrbot.core.knowledge_base.parsers.base import (
-    BaseParser,
-    ParseResult,
-)
-from markitdown_no_magika import MarkItDown, StreamInfo
-
-
-class MarkitdownParser(BaseParser):
-    """解析 docx, xls, xlsx 格式"""
-
-    async def parse(self, file_content: bytes, file_name: str) -> ParseResult:
-        md = MarkItDown(enable_plugins=False)
-        bio = io.BytesIO(file_content)
-        stream_info = StreamInfo(
-            extension=os.path.splitext(file_name)[1].lower(),
-            filename=file_name,
-        )
-        result = md.convert(bio, stream_info=stream_info)
-        return ParseResult(
-            text=result.markdown,
-            media=[],
-        )

astrbot/core/knowledge_base/parsers/pdf_parser.py

@@ -1,100 +0,0 @@
-"""PDF 文件解析器
-
-支持解析 PDF 文件中的文本和图片资源。
-"""
-
-import io
-
-from pypdf import PdfReader
-
-from astrbot.core.knowledge_base.parsers.base import (
-    BaseParser,
-    MediaItem,
-    ParseResult,
-)
-
-
-class PDFParser(BaseParser):
-    """PDF 文档解析器
-
-    提取 PDF 中的文本内容和嵌入的图片资源。
-    """
-
-    async def parse(self, file_content: bytes, file_name: str) -> ParseResult:
-        """解析 PDF 文件
-
-        Args:
-            file_content: 文件内容
-            file_name: 文件名
-
-        Returns:
-            ParseResult: 包含文本和图片的解析结果
-        """
-        pdf_file = io.BytesIO(file_content)
-        reader = PdfReader(pdf_file)
-
-        text_parts = []
-        media_items = []
-
-        # 提取文本
-        for page in reader.pages:
-            text = page.extract_text()
-            if text:
-                text_parts.append(text)
-
-        # 提取图片
-        image_counter = 0
-        for page_num, page in enumerate(reader.pages):
-            try:
-                # 安全检查 Resources
-                if "/Resources" not in page:
-                    continue
-
-                resources = page["/Resources"]
-                if not resources or "/XObject" not in resources:  # type: ignore
-                    continue
-
-                xobjects = resources["/XObject"].get_object()  # type: ignore
-                if not xobjects:
-                    continue
-
-                for obj_name in xobjects:
-                    try:
-                        obj = xobjects[obj_name]
-
-                        if obj.get("/Subtype") != "/Image":
-                            continue
-
-                        # 提取图片数据
-                        image_data = obj.get_data()
-
-                        # 确定格式
-                        filter_type = obj.get("/Filter", "")
-                        if filter_type == "/DCTDecode":
-                            ext = "jpg"
-                            mime_type = "image/jpeg"
-                        elif filter_type == "/FlateDecode":
-                            ext = "png"
-                            mime_type = "image/png"
-                        else:
-                            ext = "png"
-                            mime_type = "image/png"
-
-                        image_counter += 1
-                        media_items.append(
-                            MediaItem(
-                                media_type="image",
-                                file_name=f"page_{page_num}_img_{image_counter}.{ext}",
-                                content=image_data,
-                                mime_type=mime_type,
-                            )
-                        )
-                    except Exception:
-                        # 单个图片提取失败不影响整体
-                        continue
-            except Exception:
-                # 页面处理失败不影响其他页面
-                continue
-
-        full_text = "\n\n".join(text_parts)
-        return ParseResult(text=full_text, media=media_items)

astrbot/core/knowledge_base/parsers/text_parser.py

@@ -1,41 +0,0 @@
-"""文本文件解析器
-
-支持解析 TXT 和 Markdown 文件。
-"""
-
-from astrbot.core.knowledge_base.parsers.base import BaseParser, ParseResult
-
-
-class TextParser(BaseParser):
-    """TXT/MD 文本解析器
-
-    支持多种字符编码的自动检测。
-    """
-
-    async def parse(self, file_content: bytes, file_name: str) -> ParseResult:
-        """解析文本文件
-
-        尝试使用多种编码解析文件内容。
-
-        Args:
-            file_content: 文件内容
-            file_name: 文件名
-
-        Returns:
-            ParseResult: 解析结果,不包含多媒体资源
-
-        Raises:
-            ValueError: 如果无法解码文件
-        """
-        # 尝试多种编码
-        for encoding in ["utf-8", "gbk", "gb2312", "gb18030"]:
-            try:
-                text = file_content.decode(encoding)
-                break
-            except UnicodeDecodeError:
-                continue
-        else:
-            raise ValueError(f"无法解码文件: {file_name}")
-
-        # 文本文件无多媒体资源
-        return ParseResult(text=text, media=[])

astrbot/core/knowledge_base/parsers/util.py

@@ -1,13 +0,0 @@
-from .base import BaseParser
-
-
-async def select_parser(ext: str) -> BaseParser:
-    if ext in {".md", ".txt", ".markdown", ".xlsx", ".docx", ".xls"}:
-        from .markitdown_parser import MarkitdownParser
-
-        return MarkitdownParser()
-    elif ext == ".pdf":
-        from .pdf_parser import PDFParser
-
-        return PDFParser()
-    raise ValueError(f"暂时不支持的文件格式: {ext}")

astrbot/core/knowledge_base/retrieval/__init__.py

@@ -1,16 +0,0 @@
-"""
-检索模块
-"""
-
-from .manager import RetrievalManager, RetrievalResult
-from .sparse_retriever import SparseRetriever, SparseResult
-from .rank_fusion import RankFusion, FusedResult
-
-__all__ = [
-    "RetrievalManager",
-    "RetrievalResult",
-    "SparseRetriever",
-    "SparseResult",
-    "RankFusion",
-    "FusedResult",
-]

astrbot/core/knowledge_base/retrieval/hit_stopwords.txt

@@ -1,767 +0,0 @@
-———
-》），
-）÷（１－
-”，
-）、
-＝（
-:
-→
-℃ 
-&
-*
-一一
-~~~~
-’
-.
-『
-.一
-./
--- 
-』
-＝″
-【
-［＊］
-｝＞
-［⑤］］
-［①Ｄ］
-ｃ］
-ｎｇ昉
-＊
-//
-［
-］
-［②ｅ］
-［②ｇ］
-＝｛
-}
-，也 
-‘
-Ａ
-［①⑥］
-［②Ｂ］ 
-［①ａ］
-［④ａ］
-［①③］
-［③ｈ］
-③］
-１． 
-－－ 
-［②ｂ］
-’‘ 
-××× 
-［①⑧］
-０：２ 
-＝［
-［⑤ｂ］
-［②ｃ］ 
-［④ｂ］
-［②③］
-［③ａ］
-［④ｃ］
-［①⑤］
-［①⑦］
-［①ｇ］
-∈［ 
-［①⑨］
-［①④］
-［①ｃ］
-［②ｆ］
-［②⑧］
-［②①］
-［①Ｃ］
-［③ｃ］
-［③ｇ］
-［②⑤］
-［②②］
-一.
-［①ｈ］
-.数
-［］
-［①Ｂ］
-数/
-［①ｉ］
-［③ｅ］
-［①①］
-［④ｄ］
-［④ｅ］
-［③ｂ］
-［⑤ａ］
-［①Ａ］
-［②⑧］
-［②⑦］
-［①ｄ］
-［②ｊ］
-〕〔
-］［
-://
-′∈
-［②④
-［⑤ｅ］
-１２％
-ｂ］
-...
-...................
-…………………………………………………③
-ＺＸＦＩＴＬ
-［③Ｆ］
-」
-［①ｏ］
-］∧′＝［ 
-∪φ∈
-′｜
-｛－
-②ｃ
-｝
-［③①］
-Ｒ．Ｌ．
-［①Ｅ］
-Ψ
-－［＊］－
-↑
-.日 
-［②ｄ］
-［②
-［②⑦］
-［②②］
-［③ｅ］
-［①ｉ］
-［①Ｂ］
-［①ｈ］
-［①ｄ］
-［①ｇ］
-［①②］
-［②ａ］
-ｆ］
-［⑩］
-ａ］
-［①ｅ］
-［②ｈ］
-［②⑥］
-［③ｄ］
-［②⑩］
-ｅ］
-〉
-】
-元／吨
-［②⑩］
-２．３％
-５：０  
-［①］
-::
-［②］
-［③］
-［④］
-［⑤］
-［⑥］
-［⑦］
-［⑧］
-［⑨］ 
-……
-——
-?
-、
-。
-“
-”
-《
-》
-！
-，
-：
-；
-？
-．
-,
-．
-'
-? 
-·
-———
-──
-? 
-—
-<
->
-（
-）
-〔
-〕
-[
-]
-(
-)
--
-+
-～
-×
-／
-/
-①
-②
-③
-④
-⑤
-⑥
-⑦
-⑧
-⑨
-⑩
-Ⅲ
-В
-"
-;
-#
-@
-γ
-μ
-φ
-φ．
-× 
-Δ
-■
-▲
-sub
-exp 
-sup
-sub
-Lex 
-＃
-％
-＆
-＇
-＋
-＋ξ
-＋＋
-－
-－β
-＜
-＜±
-＜Δ
-＜λ
-＜φ
-＜＜
-=
-＝
-＝☆
-＝－
-＞
-＞λ
-＿
-～±
-～＋
-［⑤ｆ］
-［⑤ｄ］
-［②ｉ］
-≈ 
-［②Ｇ］
-［①ｆ］
-ＬＩ
-㈧ 
-［－
-......
-〉
-［③⑩］
-第二
-一番
-一直
-一个
-一些
-许多
-种
-有的是
-也就是说
-末##末
-啊
-阿
-哎
-哎呀
-哎哟
-唉
-俺
-俺们
-按
-按照
-吧
-吧哒
-把
-罢了
-被
-本
-本着
-比
-比方
-比如
-鄙人
-彼
-彼此
-边
-别
-别的
-别说
-并
-并且
-不比
-不成
-不单
-不但
-不独
-不管
-不光
-不过
-不仅
-不拘
-不论
-不怕
-不然
-不如
-不特
-不惟
-不问
-不只
-朝
-朝着
-趁
-趁着
-乘
-冲
-除
-除此之外
-除非
-除了
-此
-此间
-此外
-从
-从而
-打
-待
-但
-但是
-当
-当着
-到
-得
-的
-的话
-等
-等等
-地
-第
-叮咚
-对
-对于
-多
-多少
-而
-而况
-而且
-而是
-而外
-而言
-而已
-尔后
-反过来
-反过来说
-反之
-非但
-非徒
-否则
-嘎
-嘎登
-该
-赶
-个
-各
-各个
-各位
-各种
-各自
-给
-根据
-跟
-故
-故此
-固然
-关于
-管
-归
-果然
-果真
-过
-哈
-哈哈
-呵
-和
-何
-何处
-何况
-何时
-嘿
-哼
-哼唷
-呼哧
-乎
-哗
-还是
-还有
-换句话说
-换言之
-或
-或是
-或者
-极了
-及
-及其
-及至
-即
-即便
-即或
-即令
-即若
-即使
-几
-几时
-己
-既
-既然
-既是
-继而
-加之
-假如
-假若
-假使
-鉴于
-将
-较
-较之
-叫
-接着
-结果
-借
-紧接着
-进而
-尽
-尽管
-经
-经过
-就
-就是
-就是说
-据
-具体地说
-具体说来
-开始
-开外
-靠
-咳
-可
-可见
-可是
-可以
-况且
-啦
-来
-来着
-离
-例如
-哩
-连
-连同
-两者
-了
-临
-另
-另外
-另一方面
-论
-嘛
-吗
-慢说
-漫说
-冒
-么
-每
-每当
-们
-莫若
-某
-某个
-某些
-拿
-哪
-哪边
-哪儿
-哪个
-哪里
-哪年
-哪怕
-哪天
-哪些
-哪样
-那
-那边
-那儿
-那个
-那会儿
-那里
-那么
-那么些
-那么样
-那时
-那些
-那样
-乃
-乃至
-呢
-能
-你
-你们
-您
-宁
-宁可
-宁肯
-宁愿
-哦
-呕
-啪达
-旁人
-呸
-凭
-凭借
-其
-其次
-其二
-其他
-其它
-其一
-其余
-其中
-起
-起见
-起见
-岂但
-恰恰相反
-前后
-前者
-且
-然而
-然后
-然则
-让
-人家
-任
-任何
-任凭
-如
-如此
-如果
-如何
-如其
-如若
-如上所述
-若
-若非
-若是
-啥
-上下
-尚且
-设若
-设使
-甚而
-甚么
-甚至
-省得
-时候
-什么
-什么样
-使得
-是
-是的
-首先
-谁
-谁知
-顺
-顺着
-似的
-虽
-虽然
-虽说
-虽则
-随
-随着
-所
-所以
-他
-他们
-他人
-它
-它们
-她
-她们
-倘
-倘或
-倘然
-倘若
-倘使
-腾
-替
-通过
-同
-同时
-哇
-万一
-往
-望
-为
-为何
-为了
-为什么
-为着
-喂
-嗡嗡
-我
-我们
-呜
-呜呼
-乌乎
-无论
-无宁
-毋宁
-嘻
-吓
-相对而言
-像
-向
-向着
-嘘
-呀
-焉
-沿
-沿着
-要
-要不
-要不然
-要不是
-要么
-要是
-也
-也罢
-也好
-一
-一般
-一旦
-一方面
-一来
-一切
-一样
-一则
-依
-依照
-矣
-以
-以便
-以及
-以免
-以至
-以至于
-以致
-抑或
-因
-因此
-因而
-因为
-哟
-用
-由
-由此可见
-由于
-有
-有的
-有关
-有些
-又
-于
-于是
-于是乎
-与
-与此同时
-与否
-与其
-越是
-云云
-哉
-再说
-再者
-在
-在下
-咱
-咱们
-则
-怎
-怎么
-怎么办
-怎么样
-怎样
-咋
-照
-照着
-者
-这
-这边
-这儿
-这个
-这会儿
-这就是说
-这里
-这么
-这么点儿
-这么些
-这么样
-这时
-这些
-这样
-正如
-吱
-之
-之类
-之所以
-之一
-只是
-只限
-只要
-只有
-至
-至于
-诸位
-着
-着呢
-自
-自从
-自个儿
-自各儿
-自己
-自家
-自身
-综上所述
-总的来看
-总的来说
-总的说来
-总而言之
-总之
-纵
-纵令
-纵然
-纵使
-遵照
-作为
-兮
-呃
-呗
-咚
-咦
-喏
-啐
-喔唷
-嗬
-嗯
-嗳

astrbot/core/knowledge_base/retrieval/manager.py

@@ -1,273 +0,0 @@
-"""检索管理器
-
-协调稠密检索、稀疏检索和 Rerank,提供统一的检索接口
-"""
-
-import time
-
-from dataclasses import dataclass
-from typing import List
-
-from astrbot.core.knowledge_base.kb_db_sqlite import KBSQLiteDatabase
-from astrbot.core.knowledge_base.retrieval.rank_fusion import RankFusion
-from astrbot.core.knowledge_base.retrieval.sparse_retriever import SparseRetriever
-from astrbot.core.provider.provider import RerankProvider
-from astrbot.core.db.vec_db.base import Result
-from astrbot.core.db.vec_db.faiss_impl import FaissVecDB
-from ..kb_helper import KBHelper
-from astrbot import logger
-
-
-@dataclass
-class RetrievalResult:
-    """检索结果"""
-
-    chunk_id: str
-    doc_id: str
-    doc_name: str
-    kb_id: str
-    kb_name: str
-    content: str
-    score: float
-    metadata: dict
-
-
-class RetrievalManager:
-    """检索管理器
-
-    职责:
-    - 协调稠密检索、稀疏检索和 Rerank
-    - 结果融合和排序
-    """
-
-    def __init__(
-        self,
-        sparse_retriever: SparseRetriever,
-        rank_fusion: RankFusion,
-        kb_db: KBSQLiteDatabase,
-    ):
-        """初始化检索管理器
-
-        Args:
-            vec_db_factory: 向量数据库工厂
-            sparse_retriever: 稀疏检索器
-            rank_fusion: 结果融合器
-            kb_db: 知识库数据库实例
-        """
-        self.sparse_retriever = sparse_retriever
-        self.rank_fusion = rank_fusion
-        self.kb_db = kb_db
-
-    async def retrieve(
-        self,
-        query: str,
-        kb_ids: List[str],
-        kb_id_helper_map: dict[str, KBHelper],
-        top_k_fusion: int = 20,
-        top_m_final: int = 5,
-    ) -> List[RetrievalResult]:
-        """混合检索
-
-        流程:
-        1. 稠密检索 (向量相似度)
-        2. 稀疏检索 (BM25)
-        3. 结果融合 (RRF)
-        4. Rerank 重排序
-
-        Args:
-            query: 查询文本
-            kb_ids: 知识库 ID 列表
-            top_m_final: 最终返回数量
-            enable_rerank: 是否启用 Rerank
-
-        Returns:
-            List[RetrievalResult]: 检索结果列表
-        """
-        if not kb_ids:
-            return []
-
-        kb_options: dict = {}
-        new_kb_ids = []
-        for kb_id in kb_ids:
-            kb_helper = kb_id_helper_map.get(kb_id)
-            if kb_helper:
-                kb = kb_helper.kb
-                kb_options[kb_id] = {
-                    "top_k_dense": kb.top_k_dense or 50,
-                    "top_k_sparse": kb.top_k_sparse or 50,
-                    "top_m_final": kb.top_m_final or 5,
-                    "vec_db": kb_helper.vec_db,
-                    "rerank_provider_id": kb.rerank_provider_id,
-                }
-                new_kb_ids.append(kb_id)
-            else:
-                logger.warning(f"知识库 ID {kb_id} 实例未找到, 已跳过该知识库的检索")
-
-        kb_ids = new_kb_ids
-
-        # 1. 稠密检索
-        time_start = time.time()
-        dense_results = await self._dense_retrieve(
-            query=query,
-            kb_ids=kb_ids,
-            kb_options=kb_options,
-        )
-        time_end = time.time()
-        logger.debug(
-            f"Dense retrieval across {len(kb_ids)} bases took {time_end - time_start:.2f}s and returned {len(dense_results)} results."
-        )
-
-        # 2. 稀疏检索
-        time_start = time.time()
-        sparse_results = await self.sparse_retriever.retrieve(
-            query=query,
-            kb_ids=kb_ids,
-            kb_options=kb_options,
-        )
-        time_end = time.time()
-        logger.debug(
-            f"Sparse retrieval across {len(kb_ids)} bases took {time_end - time_start:.2f}s and returned {len(sparse_results)} results."
-        )
-
-        # 3. 结果融合
-        time_start = time.time()
-        fused_results = await self.rank_fusion.fuse(
-            dense_results=dense_results,
-            sparse_results=sparse_results,
-            top_k=top_k_fusion,
-        )
-        time_end = time.time()
-        logger.debug(
-            f"Rank fusion took {time_end - time_start:.2f}s and returned {len(fused_results)} results."
-        )
-
-        # 4. 转换为 RetrievalResult (获取元数据)
-        retrieval_results = []
-        for fr in fused_results:
-            metadata_dict = await self.kb_db.get_document_with_metadata(fr.doc_id)
-            if metadata_dict:
-                retrieval_results.append(
-                    RetrievalResult(
-                        chunk_id=fr.chunk_id,
-                        doc_id=fr.doc_id,
-                        doc_name=metadata_dict["document"].doc_name,
-                        kb_id=fr.kb_id,
-                        kb_name=metadata_dict["knowledge_base"].kb_name,
-                        content=fr.content,
-                        score=fr.score,
-                        metadata={
-                            "chunk_index": fr.chunk_index,
-                            "char_count": len(fr.content),
-                        },
-                    )
-                )
-
-        # 5. Rerank
-        first_rerank = None
-        for kb_id in kb_ids:
-            vec_db: FaissVecDB = kb_options[kb_id]["vec_db"]
-            rerank_pi = kb_options[kb_id]["rerank_provider_id"]
-            if (
-                vec_db
-                and vec_db.rerank_provider
-                and rerank_pi
-                and rerank_pi == vec_db.rerank_provider.meta().id
-            ):
-                first_rerank = vec_db.rerank_provider
-                break
-        if first_rerank and retrieval_results:
-            retrieval_results = await self._rerank(
-                query=query,
-                results=retrieval_results,
-                top_k=top_m_final,
-                rerank_provider=first_rerank,
-            )
-
-        return retrieval_results[:top_m_final]
-
-    async def _dense_retrieve(
-        self,
-        query: str,
-        kb_ids: List[str],
-        kb_options: dict,
-    ):
-        """稠密检索 (向量相似度)
-
-        为每个知识库使用独立的向量数据库进行检索,然后合并结果。
-
-        Args:
-            query: 查询文本
-            kb_ids: 知识库 ID 列表
-            top_k: 返回结果数量
-
-        Returns:
-            List[Result]: 检索结果列表
-        """
-        all_results: list[Result] = []
-        for kb_id in kb_ids:
-            if kb_id not in kb_options:
-                continue
-            try:
-                vec_db: FaissVecDB = kb_options[kb_id]["vec_db"]
-                dense_k = int(kb_options[kb_id]["top_k_dense"])
-                vec_results = await vec_db.retrieve(
-                    query=query,
-                    k=dense_k,
-                    fetch_k=dense_k * 2,
-                    rerank=False,  # 稠密检索阶段不进行 rerank
-                    metadata_filters={"kb_id": kb_id},
-                )
-
-                all_results.extend(vec_results)
-            except Exception as e:
-                from astrbot.core import logger
-
-                logger.warning(f"知识库 {kb_id} 稠密检索失败: {e}")
-                continue
-
-        # 按相似度排序并返回 top_k
-        all_results.sort(key=lambda x: x.similarity, reverse=True)
-        # return all_results[: len(all_results) // len(kb_ids)]
-        return all_results
-
-    async def _rerank(
-        self,
-        query: str,
-        results: List[RetrievalResult],
-        top_k: int,
-        rerank_provider: RerankProvider,
-    ) -> List[RetrievalResult]:
-        """Rerank 重排序
-
-        Args:
-            query: 查询文本
-            results: 检索结果列表
-            top_k: 返回结果数量
-
-        Returns:
-            List[RetrievalResult]: 重排序后的结果列表
-        """
-        if not results:
-            return []
-
-        # 准备文档列表
-        docs = [r.content for r in results]
-
-        # 调用 Rerank Provider
-        rerank_results = await rerank_provider.rerank(
-            query=query,
-            documents=docs,
-        )
-
-        # 更新分数并重新排序
-        reranked_list = []
-        for rerank_result in rerank_results:
-            idx = rerank_result.index
-            if idx < len(results):
-                result = results[idx]
-                result.score = rerank_result.relevance_score
-                reranked_list.append(result)
-
-        reranked_list.sort(key=lambda x: x.score, reverse=True)
-
-        return reranked_list[:top_k]

astrbot/core/knowledge_base/retrieval/rank_fusion.py

@@ -1,138 +0,0 @@
-"""检索结果融合器
-
-使用 Reciprocal Rank Fusion (RRF) 算法融合稠密检索和稀疏检索的结果
-"""
-
-import json
-from dataclasses import dataclass
-
-from astrbot.core.db.vec_db.base import Result
-from astrbot.core.knowledge_base.kb_db_sqlite import KBSQLiteDatabase
-from astrbot.core.knowledge_base.retrieval.sparse_retriever import SparseResult
-
-
-@dataclass
-class FusedResult:
-    """融合后的检索结果"""
-
-    chunk_id: str
-    chunk_index: int
-    doc_id: str
-    kb_id: str
-    content: str
-    score: float
-
-
-class RankFusion:
-    """检索结果融合器
-
-    职责:
-    - 融合稠密检索和稀疏检索的结果
-    - 使用 Reciprocal Rank Fusion (RRF) 算法
-    """
-
-    def __init__(self, kb_db: KBSQLiteDatabase, k: int = 60):
-        """初始化结果融合器
-
-        Args:
-            kb_db: 知识库数据库实例
-            k: RRF 参数,用于平滑排名
-        """
-        self.kb_db = kb_db
-        self.k = k
-
-    async def fuse(
-        self,
-        dense_results: list[Result],
-        sparse_results: list[SparseResult],
-        top_k: int = 20,
-    ) -> list[FusedResult]:
-        """融合稠密和稀疏检索结果
-
-        RRF 公式:
-        score(doc) = sum(1 / (k + rank_i))
-
-        Args:
-            dense_results: 稠密检索结果
-            sparse_results: 稀疏检索结果
-            top_k: 返回结果数量
-
-        Returns:
-            List[FusedResult]: 融合后的结果列表
-        """
-        # 1. 构建排名映射
-        dense_ranks = {
-            r.data["doc_id"]: (idx + 1) for idx, r in enumerate(dense_results)
-        }  # 这里的 doc_id 实际上是 chunk_id
-        sparse_ranks = {r.chunk_id: (idx + 1) for idx, r in enumerate(sparse_results)}
-
-        # 2. 收集所有唯一的 ID
-        # 需要统一为 chunk_id
-        all_chunk_ids = set()
-        vec_doc_id_to_dense: dict[str, Result] = {}  # vec_doc_id -> Result
-        chunk_id_to_sparse: dict[str, SparseResult] = {}  # chunk_id -> SparseResult
-
-        # 处理稀疏检索结果
-        for r in sparse_results:
-            all_chunk_ids.add(r.chunk_id)
-            chunk_id_to_sparse[r.chunk_id] = r
-
-        # 处理稠密检索结果 (需要转换 vec_doc_id 到 chunk_id)
-        for r in dense_results:
-            vec_doc_id = r.data["doc_id"]
-            all_chunk_ids.add(vec_doc_id)
-            vec_doc_id_to_dense[vec_doc_id] = r
-
-        # 3. 计算 RRF 分数
-        rrf_scores: dict[str, float] = {}
-
-        for identifier in all_chunk_ids:
-            score = 0.0
-
-            # 来自稠密检索的贡献
-            if identifier in dense_ranks:
-                score += 1.0 / (self.k + dense_ranks[identifier])
-
-            # 来自稀疏检索的贡献
-            if identifier in sparse_ranks:
-                score += 1.0 / (self.k + sparse_ranks[identifier])
-
-            rrf_scores[identifier] = score
-
-        # 4. 排序
-        sorted_ids = sorted(
-            rrf_scores.keys(), key=lambda cid: rrf_scores[cid], reverse=True
-        )[:top_k]
-
-        # 5. 构建融合结果
-        fused_results = []
-        for identifier in sorted_ids:
-            # 优先从稀疏检索获取完整信息
-            if identifier in chunk_id_to_sparse:
-                sr = chunk_id_to_sparse[identifier]
-                fused_results.append(
-                    FusedResult(
-                        chunk_id=sr.chunk_id,
-                        chunk_index=sr.chunk_index,
-                        doc_id=sr.doc_id,
-                        kb_id=sr.kb_id,
-                        content=sr.content,
-                        score=rrf_scores[identifier],
-                    )
-                )
-            elif identifier in vec_doc_id_to_dense:
-                # 从向量检索获取信息,需要从数据库获取块的详细信息
-                vec_result = vec_doc_id_to_dense[identifier]
-                chunk_md = json.loads(vec_result.data["metadata"])
-                fused_results.append(
-                    FusedResult(
-                        chunk_id=identifier,
-                        chunk_index=chunk_md["chunk_index"],
-                        doc_id=chunk_md["kb_doc_id"],
-                        kb_id=chunk_md["kb_id"],
-                        content=vec_result.data["text"],
-                        score=rrf_scores[identifier],
-                    )
-                )
-
-        return fused_results

astrbot/core/knowledge_base/retrieval/sparse_retriever.py

@@ -1,130 +0,0 @@
-"""稀疏检索器
-
-使用 BM25 算法进行基于关键词的文档检索
-"""
-
-import jieba
-import os
-import json
-from dataclasses import dataclass
-from rank_bm25 import BM25Okapi
-from astrbot.core.knowledge_base.kb_db_sqlite import KBSQLiteDatabase
-from astrbot.core.db.vec_db.faiss_impl import FaissVecDB
-
-
-@dataclass
-class SparseResult:
-    """稀疏检索结果"""
-
-    chunk_index: int
-    chunk_id: str
-    doc_id: str
-    kb_id: str
-    content: str
-    score: float
-
-
-class SparseRetriever:
-    """BM25 稀疏检索器
-
-    职责:
-    - 基于关键词的文档检索
-    - 使用 BM25 算法计算相关度
-    """
-
-    def __init__(self, kb_db: KBSQLiteDatabase):
-        """初始化稀疏检索器
-
-        Args:
-            kb_db: 知识库数据库实例
-        """
-        self.kb_db = kb_db
-        self._index_cache = {}  # 缓存 BM25 索引
-
-        with open(
-            os.path.join(os.path.dirname(__file__), "hit_stopwords.txt"),
-            encoding="utf-8",
-        ) as f:
-            self.hit_stopwords = {
-                word.strip() for word in set(f.read().splitlines()) if word.strip()
-            }
-
-    async def retrieve(
-        self,
-        query: str,
-        kb_ids: list[str],
-        kb_options: dict,
-    ) -> list[SparseResult]:
-        """执行稀疏检索
-
-        Args:
-            query: 查询文本
-            kb_ids: 知识库 ID 列表
-            kb_options: 每个知识库的检索选项
-
-        Returns:
-            List[SparseResult]: 检索结果列表
-        """
-        # 1. 获取所有相关块
-        top_k_sparse = 0
-        chunks = []
-        for kb_id in kb_ids:
-            vec_db: FaissVecDB = kb_options.get(kb_id, {}).get("vec_db")
-            if not vec_db:
-                continue
-            result = await vec_db.document_storage.get_documents(
-                metadata_filters={}, limit=None, offset=None
-            )
-            chunk_mds = [json.loads(doc["metadata"]) for doc in result]
-            result = [
-                {
-                    "chunk_id": doc["doc_id"],
-                    "chunk_index": chunk_md["chunk_index"],
-                    "doc_id": chunk_md["kb_doc_id"],
-                    "kb_id": kb_id,
-                    "text": doc["text"],
-                }
-                for doc, chunk_md in zip(result, chunk_mds)
-            ]
-            chunks.extend(result)
-            top_k_sparse += kb_options.get(kb_id, {}).get("top_k_sparse", 50)
-
-        if not chunks:
-            return []
-
-        # 2. 准备文档和索引
-        corpus = [chunk["text"] for chunk in chunks]
-        tokenized_corpus = [list(jieba.cut(doc)) for doc in corpus]
-        tokenized_corpus = [
-            [word for word in doc if word not in self.hit_stopwords]
-            for doc in tokenized_corpus
-        ]
-
-        # 3. 构建 BM25 索引
-        bm25 = BM25Okapi(tokenized_corpus)
-
-        # 4. 执行检索
-        tokenized_query = list(jieba.cut(query))
-        tokenized_query = [
-            word for word in tokenized_query if word not in self.hit_stopwords
-        ]
-        scores = bm25.get_scores(tokenized_query)
-
-        # 5. 排序并返回 Top-K
-        results = []
-        for idx, score in enumerate(scores):
-            chunk = chunks[idx]
-            results.append(
-                SparseResult(
-                    chunk_id=chunk["chunk_id"],
-                    chunk_index=chunk["chunk_index"],
-                    doc_id=chunk["doc_id"],
-                    kb_id=chunk["kb_id"],
-                    content=chunk["text"],
-                    score=float(score),
-                )
-            )
-
-        results.sort(key=lambda x: x.score, reverse=True)
-        # return results[: len(results) // len(kb_ids)]
-        return results[:top_k_sparse]

astrbot/core/message/components.py

@@ -37,7 +37,7 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 from astrbot.core.utils.io import download_file, download_image_by_url, file_to_base64
 
 
-class ComponentType(str, Enum):
+class ComponentType(Enum):
     Plain = "Plain"  # 纯文本消息
     Face = "Face"  # QQ表情
     Record = "Record"  # 语音
@@ -108,7 +108,7 @@ class BaseMessageComponent(BaseModel):
 
 
 class Plain(BaseMessageComponent):
-    type = ComponentType.Plain
+    type: ComponentType = "Plain"
     text: str
     convert: T.Optional[bool] = True  # 若为 False 则直接发送未转换 CQ 码的消息
 
@@ -130,7 +130,7 @@ class Plain(BaseMessageComponent):
 
 
 class Face(BaseMessageComponent):
-    type = ComponentType.Face
+    type: ComponentType = "Face"
     id: int
 
     def __init__(self, **_):
@@ -138,7 +138,7 @@ class Face(BaseMessageComponent):
 
 
 class Record(BaseMessageComponent):
-    type = ComponentType.Record
+    type: ComponentType = "Record"
     file: T.Optional[str] = ""
     magic: T.Optional[bool] = False
     url: T.Optional[str] = ""
@@ -165,24 +165,19 @@ class Record(BaseMessageComponent):
             return Record(file=url, **_)
         raise Exception("not a valid url")
 
-    @staticmethod
-    def fromBase64(bs64_data: str, **_):
-        return Record(file=f"base64://{bs64_data}", **_)
-
     async def convert_to_file_path(self) -> str:
         """将这个语音统一转换为本地文件路径。这个方法避免了手动判断语音数据类型，直接返回语音数据的本地路径（如果是网络 URL, 则会自动进行下载）。
 
         Returns:
             str: 语音的本地路径，以绝对路径表示。
         """
-        if not self.file:
-            raise Exception(f"not a valid file: {self.file}")
-        if self.file.startswith("file:///"):
-            return self.file[8:]
-        elif self.file.startswith("http"):
+        if self.file and self.file.startswith("file:///"):
+            file_path = self.file[8:]
+            return file_path
+        elif self.file and self.file.startswith("http"):
             file_path = await download_image_by_url(self.file)
             return os.path.abspath(file_path)
-        elif self.file.startswith("base64://"):
+        elif self.file and self.file.startswith("base64://"):
             bs64_data = self.file.removeprefix("base64://")
             image_bytes = base64.b64decode(bs64_data)
             temp_dir = os.path.join(get_astrbot_data_path(), "temp")
@@ -191,7 +186,8 @@ class Record(BaseMessageComponent):
                 f.write(image_bytes)
             return os.path.abspath(file_path)
         elif os.path.exists(self.file):
-            return os.path.abspath(self.file)
+            file_path = self.file
+            return os.path.abspath(file_path)
         else:
             raise Exception(f"not a valid file: {self.file}")
 
@@ -202,14 +198,12 @@ class Record(BaseMessageComponent):
             str: 语音的 base64 编码，不以 base64:// 或者 data:image/jpeg;base64, 开头。
         """
         # convert to base64
-        if not self.file:
-            raise Exception(f"not a valid file: {self.file}")
-        if self.file.startswith("file:///"):
+        if self.file and self.file.startswith("file:///"):
             bs64_data = file_to_base64(self.file[8:])
-        elif self.file.startswith("http"):
+        elif self.file and self.file.startswith("http"):
             file_path = await download_image_by_url(self.file)
             bs64_data = file_to_base64(file_path)
-        elif self.file.startswith("base64://"):
+        elif self.file and self.file.startswith("base64://"):
             bs64_data = self.file
         elif os.path.exists(self.file):
             bs64_data = file_to_base64(self.file)
@@ -243,7 +237,7 @@ class Record(BaseMessageComponent):
 
 
 class Video(BaseMessageComponent):
-    type = ComponentType.Video
+    type: ComponentType = "Video"
     file: str
     cover: T.Optional[str] = ""
     c: T.Optional[int] = 2
@@ -329,7 +323,7 @@ class Video(BaseMessageComponent):
 
 
 class At(BaseMessageComponent):
-    type = ComponentType.At
+    type: ComponentType = "At"
     qq: T.Union[int, str]  # 此处str为all时代表所有人
     name: T.Optional[str] = ""
 
@@ -351,28 +345,28 @@ class AtAll(At):
 
 
 class RPS(BaseMessageComponent):  # TODO
-    type = ComponentType.RPS
+    type: ComponentType = "RPS"
 
     def __init__(self, **_):
         super().__init__(**_)
 
 
 class Dice(BaseMessageComponent):  # TODO
-    type = ComponentType.Dice
+    type: ComponentType = "Dice"
 
     def __init__(self, **_):
         super().__init__(**_)
 
 
 class Shake(BaseMessageComponent):  # TODO
-    type = ComponentType.Shake
+    type: ComponentType = "Shake"
 
     def __init__(self, **_):
         super().__init__(**_)
 
 
 class Anonymous(BaseMessageComponent):  # TODO
-    type = ComponentType.Anonymous
+    type: ComponentType = "Anonymous"
     ignore: T.Optional[bool] = False
 
     def __init__(self, **_):
@@ -380,7 +374,7 @@ class Anonymous(BaseMessageComponent):  # TODO
 
 
 class Share(BaseMessageComponent):
-    type = ComponentType.Share
+    type: ComponentType = "Share"
     url: str
     title: str
     content: T.Optional[str] = ""
@@ -391,7 +385,7 @@ class Share(BaseMessageComponent):
 
 
 class Contact(BaseMessageComponent):  # TODO
-    type = ComponentType.Contact
+    type: ComponentType = "Contact"
     _type: str  # type 字段冲突
     id: T.Optional[int] = 0
 
@@ -400,7 +394,7 @@ class Contact(BaseMessageComponent):  # TODO
 
 
 class Location(BaseMessageComponent):  # TODO
-    type = ComponentType.Location
+    type: ComponentType = "Location"
     lat: float
     lon: float
     title: T.Optional[str] = ""
@@ -411,7 +405,7 @@ class Location(BaseMessageComponent):  # TODO
 
 
 class Music(BaseMessageComponent):
-    type = ComponentType.Music
+    type: ComponentType = "Music"
     _type: str
     id: T.Optional[int] = 0
     url: T.Optional[str] = ""
@@ -428,7 +422,7 @@ class Music(BaseMessageComponent):
 
 
 class Image(BaseMessageComponent):
-    type = ComponentType.Image
+    type: ComponentType = "Image"
     file: T.Optional[str] = ""
     _type: T.Optional[str] = ""
     subType: T.Optional[int] = 0
@@ -471,15 +465,14 @@ class Image(BaseMessageComponent):
         Returns:
             str: 图片的本地路径，以绝对路径表示。
         """
-        url = self.url or self.file
-        if not url:
-            raise ValueError("No valid file or URL provided")
-        if url.startswith("file:///"):
-            return url[8:]
-        elif url.startswith("http"):
+        url = self.url if self.url else self.file
+        if url and url.startswith("file:///"):
+            image_file_path = url[8:]
+            return image_file_path
+        elif url and url.startswith("http"):
             image_file_path = await download_image_by_url(url)
             return os.path.abspath(image_file_path)
-        elif url.startswith("base64://"):
+        elif url and url.startswith("base64://"):
             bs64_data = url.removeprefix("base64://")
             image_bytes = base64.b64decode(bs64_data)
             temp_dir = os.path.join(get_astrbot_data_path(), "temp")
@@ -488,7 +481,8 @@ class Image(BaseMessageComponent):
                 f.write(image_bytes)
             return os.path.abspath(image_file_path)
         elif os.path.exists(url):
-            return os.path.abspath(url)
+            image_file_path = url
+            return os.path.abspath(image_file_path)
         else:
             raise Exception(f"not a valid file: {url}")
 
@@ -499,15 +493,13 @@ class Image(BaseMessageComponent):
             str: 图片的 base64 编码，不以 base64:// 或者 data:image/jpeg;base64, 开头。
         """
         # convert to base64
-        url = self.url or self.file
-        if not url:
-            raise ValueError("No valid file or URL provided")
-        if url.startswith("file:///"):
+        url = self.url if self.url else self.file
+        if url and url.startswith("file:///"):
             bs64_data = file_to_base64(url[8:])
-        elif url.startswith("http"):
+        elif url and url.startswith("http"):
             image_file_path = await download_image_by_url(url)
             bs64_data = file_to_base64(image_file_path)
-        elif url.startswith("base64://"):
+        elif url and url.startswith("base64://"):
             bs64_data = url
         elif os.path.exists(url):
             bs64_data = file_to_base64(url)
@@ -541,7 +533,7 @@ class Image(BaseMessageComponent):
 
 
 class Reply(BaseMessageComponent):
-    type = ComponentType.Reply
+    type: ComponentType = "Reply"
     id: T.Union[str, int]
     """所引用的消息 ID"""
     chain: T.Optional[T.List["BaseMessageComponent"]] = []
@@ -567,7 +559,7 @@ class Reply(BaseMessageComponent):
 
 
 class RedBag(BaseMessageComponent):
-    type = ComponentType.RedBag
+    type: ComponentType = "RedBag"
     title: str
 
     def __init__(self, **_):
@@ -575,7 +567,7 @@ class RedBag(BaseMessageComponent):
 
 
 class Poke(BaseMessageComponent):
-    type: str = ComponentType.Poke
+    type: str = ""
     id: T.Optional[int] = 0
     qq: T.Optional[int] = 0
 
@@ -585,7 +577,7 @@ class Poke(BaseMessageComponent):
 
 
 class Forward(BaseMessageComponent):
-    type = ComponentType.Forward
+    type: ComponentType = "Forward"
     id: str
 
     def __init__(self, **_):
@@ -595,7 +587,7 @@ class Forward(BaseMessageComponent):
 class Node(BaseMessageComponent):
     """群合并转发消息"""
 
-    type = ComponentType.Node
+    type: ComponentType = "Node"
     id: T.Optional[int] = 0  # 忽略
     name: T.Optional[str] = ""  # qq昵称
     uin: T.Optional[str] = "0"  # qq号
@@ -647,7 +639,7 @@ class Node(BaseMessageComponent):
 
 
 class Nodes(BaseMessageComponent):
-    type = ComponentType.Nodes
+    type: ComponentType = "Nodes"
     nodes: T.List[Node]
 
     def __init__(self, nodes: T.List[Node], **_):
@@ -673,7 +665,7 @@ class Nodes(BaseMessageComponent):
 
 
 class Xml(BaseMessageComponent):
-    type = ComponentType.Xml
+    type: ComponentType = "Xml"
     data: str
     resid: T.Optional[int] = 0
 
@@ -682,7 +674,7 @@ class Xml(BaseMessageComponent):
 
 
 class Json(BaseMessageComponent):
-    type = ComponentType.Json
+    type: ComponentType = "Json"
     data: T.Union[str, dict]
     resid: T.Optional[int] = 0
 
@@ -693,7 +685,7 @@ class Json(BaseMessageComponent):
 
 
 class CardImage(BaseMessageComponent):
-    type = ComponentType.CardImage
+    type: ComponentType = "CardImage"
     file: str
     cache: T.Optional[bool] = True
     minwidth: T.Optional[int] = 400
@@ -712,7 +704,7 @@ class CardImage(BaseMessageComponent):
 
 
 class TTS(BaseMessageComponent):
-    type = ComponentType.TTS
+    type: ComponentType = "TTS"
     text: str
 
     def __init__(self, **_):
@@ -720,7 +712,7 @@ class TTS(BaseMessageComponent):
 
 
 class Unknown(BaseMessageComponent):
-    type = ComponentType.Unknown
+    type: ComponentType = "Unknown"
     text: str
 
     def toString(self):
@@ -732,7 +724,7 @@ class File(BaseMessageComponent):
     文件消息段
     """
 
-    type = ComponentType.File
+    type: ComponentType = "File"
     name: T.Optional[str] = ""  # 名字
     file_: T.Optional[str] = ""  # 本地路径
     url: T.Optional[str] = ""  # url
@@ -862,7 +854,7 @@ class File(BaseMessageComponent):
 
 
 class WechatEmoji(BaseMessageComponent):
-    type = ComponentType.WechatEmoji
+    type: ComponentType = "WechatEmoji"
     md5: T.Optional[str] = ""
     md5_len: T.Optional[int] = 0
     cdnurl: T.Optional[str] = ""

astrbot/core/persona_mgr.py

@@ -1,183 +0,0 @@
-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

@@ -4,6 +4,7 @@ from astrbot.core.message.message_event_result import (
 )
 
 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 .rate_limit_check.stage import RateLimitStage
@@ -20,6 +21,7 @@ STAGES_ORDER = [
     "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
@@ -32,6 +34,7 @@ __all__ = [
     "SessionStatusCheckStage",
     "RateLimitStage",
     "ContentSafetyCheckStage",
+    "PlatformCompatibilityStage",
     "PreProcessStage",
     "ProcessStage",
     "ResultDecorateStage",

astrbot/core/pipeline/content_safety_check/stage.py

@@ -19,7 +19,7 @@ class ContentSafetyCheckStage(Stage):
         self.strategy_selector = StrategySelector(config)
 
     async def process(
-        self, event: AstrMessageEvent, check_text: str | None = None
+        self, event: AstrMessageEvent, check_text: str = None
     ) -> Union[None, AsyncGenerator[None, None]]:
         """检查内容安全"""
         text = check_text if check_text else event.get_message_str()

astrbot/core/pipeline/content_safety_check/strategies/baidu_aip.py

@@ -13,7 +13,7 @@ class BaiduAipStrategy(ContentSafetyStrategy):
         self.secret_key = sk
         self.client = AipContentCensor(self.app_id, self.api_key, self.secret_key)
 
-    def check(self, content: str) -> tuple[bool, str]:
+    def check(self, content: str):
         res = self.client.textCensorUserDefined(content)
         if "conclusionType" not in res:
             return False, ""

astrbot/core/pipeline/content_safety_check/strategies/keywords.py

@@ -16,7 +16,7 @@ class KeywordsStrategy(ContentSafetyStrategy):
         #             json.loads(base64.b64decode(f.read()).decode("utf-8"))["keywords"]
         #         )
 
-    def check(self, content: str) -> tuple[bool, str]:
+    def check(self, content: str) -> bool:
         for keyword in self.keywords:
             if re.search(keyword, content):
                 return False, "内容安全检查不通过，匹配到敏感词。"

astrbot/core/pipeline/context.py

@@ -1,7 +1,14 @@
+import inspect
+import traceback
+import typing as T
 from dataclasses import dataclass
-from astrbot.core.config import AstrBotConfig
+from astrbot.core.config.astrbot_config import AstrBotConfig
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.star import PluginManager
-from .context_utils import call_handler, call_event_hook
+from astrbot.api 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
 
 
 @dataclass
@@ -10,6 +17,97 @@ 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
+
+    async def call_event_hook(
+        self,
+        event: AstrMessageEvent,
+        hook_type: EventType,
+        *args,
+    ) -> bool:
+        """调用事件钩子函数
+
+        Returns:
+            bool: 如果事件被终止，返回 True
+        """
+        platform_id = event.get_platform_id()
+        handlers = star_handlers_registry.get_handlers_by_event_type(
+            hook_type, platform_id=platform_id
+        )
+        for handler in handlers:
+            try:
+                logger.debug(
+                    f"hook(on_llm_request) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
+                )
+                await handler.handler(event, *args)
+            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()
+
+    async def call_handler(
+        self,
+        event: AstrMessageEvent,
+        handler: T.Awaitable,
+        *args,
+        **kwargs,
+    ) -> T.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): 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 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, self.plugin_manager.context, *args, **kwargs)
+
+        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

astrbot/core/pipeline/context_utils.py

@@ -1,102 +0,0 @@
-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.Callable[..., T.Awaitable[T.Any]],
-    *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 not ready_to_call:
-        return
-
-    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 True
-
-    return event.is_stopped()

astrbot/core/pipeline/platform_compatibility/stage.py

@@ -0,0 +1,56 @@
+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/preprocess_stage/stage.py

@@ -1,6 +1,5 @@
 import traceback
 import asyncio
-import random
 from typing import Union, AsyncGenerator
 from ..stage import Stage, register_stage
 from ..context import PipelineContext
@@ -23,26 +22,6 @@ class PreProcessStage(Stage):
         self, event: AstrMessageEvent
     ) -> Union[None, AsyncGenerator[None, None]]:
         """在处理事件之前的预处理"""
-        # 平台特异配置：platform_specific.<platform>.pre_ack_emoji
-        supported = {"telegram", "lark"}
-        platform = event.get_platform_name()
-        cfg = (
-            self.config.get("platform_specific", {})
-            .get(platform, {})
-            .get("pre_ack_emoji", {})
-        ) or {}
-        emojis = cfg.get("emojis") or []
-        if (
-            cfg.get("enable", False)
-            and platform in supported
-            and emojis
-            and event.is_at_or_wake_command
-        ):
-            try:
-                await event.react(random.choice(emojis))
-            except Exception as e:
-                logger.warning(f"{platform} 预回应表情发送失败: {e}")
-
         # 路径映射
         if mappings := self.platform_settings.get("path_mapping", []):
             # 支持 Record，Image 消息段的路径映射。
@@ -67,9 +46,6 @@ class PreProcessStage(Stage):
             ctx = self.plugin_manager.context
             stt_provider = ctx.get_using_stt_provider(event.unified_msg_origin)
             if not stt_provider:
-                logger.warning(
-                    f"会话 {event.unified_msg_origin} 未配置语音转文本模型。"
-                )
                 return
             message_chain = event.get_messages()
             for idx, component in enumerate(message_chain):

astrbot/core/pipeline/process_stage/agent_runner/base.py

@@ -1,33 +1,33 @@
 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 dataclasses import dataclass
 from astrbot.core.provider.entities import LLMResponse
+from ....message.message_event_result import MessageChain
+from enum import Enum, auto
 
 
 class AgentState(Enum):
-    """Defines the state of the agent."""
+    """Agent 状态枚举"""
 
-    IDLE = auto()  # Initial state
-    RUNNING = auto()  # Currently processing
-    DONE = auto()  # Completed
-    ERROR = auto()  # Error state
+    IDLE = auto()  # 初始状态
+    RUNNING = auto()  # 运行中
+    DONE = auto()  # 完成
+    ERROR = auto()  # 错误状态
 
 
-class BaseAgentRunner(T.Generic[TContext]):
+class AgentResponseData(T.TypedDict):
+    chain: MessageChain
+
+
+@dataclass
+class AgentResponse:
+    type: str
+    data: AgentResponseData
+
+
+class BaseAgentRunner:
     @abc.abstractmethod
-    async def reset(
-        self,
-        provider: Provider,
-        run_context: ContextWrapper[TContext],
-        tool_executor: BaseFunctionToolExecutor[TContext],
-        agent_hooks: BaseAgentRunHooks[TContext],
-        **kwargs: T.Any,
-    ) -> None:
+    async def reset(self) -> None:
         """
         Reset the agent to its initial state.
         This method should be called before starting a new run.

astrbot/core/pipeline/process_stage/agent_runner/tool_loop_agent.py

@@ -1,12 +1,10 @@
 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 .base import BaseAgentRunner, AgentResponse, AgentResponseData, AgentState
+from ...context import PipelineContext
 from astrbot.core.provider.provider import Provider
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import (
     MessageChain,
 )
@@ -23,8 +21,8 @@ from mcp.types import (
     EmbeddedResource,
     TextResourceContents,
     BlobResourceContents,
-    CallToolResult,
 )
+from astrbot.core.star.star_handler import EventType
 from astrbot import logger
 
 if sys.version_info >= (3, 12):
@@ -33,25 +31,28 @@ 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,
+# TODO:
+# 1. 处理平台不兼容的处理器
+
+
+class ToolLoopAgent(BaseAgentRunner):
+    def __init__(
+        self, provider: Provider, event: AstrMessageEvent, pipeline_ctx: PipelineContext
     ) -> None:
-        self.req = request
-        self.streaming = kwargs.get("streaming", False)
         self.provider = provider
+        self.req = None
+        self.event = event
+        self.pipeline_ctx = pipeline_ctx
+        self._state = AgentState.IDLE
+        self.final_llm_resp = None
+        self.streaming = False
+
+    @override
+    async def reset(self, req: ProviderRequest, streaming: bool) -> None:
+        self.req = req
+        self.streaming = streaming
         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"""
@@ -77,12 +78,6 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         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
@@ -129,10 +124,12 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             # 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)
+
+            # 执行事件钩子
+            if await self.pipeline_ctx.call_event_hook(
+                self.event, EventType.OnLLMResponseEvent, llm_resp
+            ):
+                return
 
         # 返回 LLM 结果
         if llm_resp.result_chain:
@@ -196,76 +193,50 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                 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}")
-
-                if not func_tool:
-                    logger.warning(f"未找到指定的工具: {func_tool_name}，将跳过。")
-                    tool_call_result_blocks.append(
-                        ToolCallMessageSegment(
-                            role="tool",
-                            tool_call_id=func_tool_id,
-                            content=f"error: 未找到工具 {func_tool_name}",
+                if func_tool.origin == "mcp":
+                    logger.info(
+                        f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数：{func_tool.name}，参数：{func_tool_args}"
+                    )
+                    client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name]
+                    res = await client.session.call_tool(func_tool.name, func_tool_args)
+                    if not res:
+                        continue
+                    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,
+                            )
                         )
-                    )
-                    continue
-
-                valid_params = {}  # 参数过滤：只传递函数实际需要的参数
-
-                # 获取实际的 handler 函数
-                if func_tool.handler:
-                    logger.debug(
-                        f"工具 {func_tool_name} 期望的参数: {func_tool.parameters}"
-                    )
-                    if func_tool.parameters and func_tool.parameters.get("properties"):
-                        expected_params = set(func_tool.parameters["properties"].keys())
-
-                        valid_params = {
-                            k: v
-                            for k, v in func_tool_args.items()
-                            if k in expected_params
-                        }
-
-                    # 记录被忽略的参数
-                    ignored_params = set(func_tool_args.keys()) - set(
-                        valid_params.keys()
-                    )
-                    if ignored_params:
-                        logger.warning(
-                            f"工具 {func_tool_name} 忽略非期望参数: {ignored_params}"
+                        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)",
+                            )
                         )
-                else:
-                    # 如果没有 handler（如 MCP 工具），使用所有参数
-                    valid_params = func_tool_args
-                    logger.warning(f"工具 {func_tool_name} 没有 handler，使用所有参数")
-
-                try:
-                    await self.agent_hooks.on_tool_start(
-                        self.run_context, func_tool, valid_params
-                    )
-                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,
-                    **valid_params,  # 只传递有效的参数
-                )
-
-                _final_resp: CallToolResult | None = None
-                async for resp in executor:  # type: ignore
-                    if isinstance(resp, CallToolResult):
-                        res = resp
-                        _final_resp = resp
-                        if isinstance(res.content[0], TextContent):
+                        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=res.content[0].text,
+                                    content=resource.text,
                                 )
                             )
-                            yield MessageChain().message(res.content[0].text)
-                        elif isinstance(res.content[0], ImageContent):
+                            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",
@@ -276,65 +247,43 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                             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,
-                                    )
+                        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(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(resource.blob)
-                            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。")
-
-                    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"
-                                )
-                    else:
-                        # 不应该出现其他类型
-                        logger.warning(
-                            f"Tool 返回了不支持的类型: {type(resp)}，将忽略。"
-                        )
-
-                try:
-                    await self.agent_hooks.on_tool_end(
-                        self.run_context, func_tool, func_tool_args, _final_resp
+                            )
+                            yield MessageChain().message("返回的数据类型不受支持。")
+                else:
+                    logger.info(f"使用工具：{func_tool_name}，参数：{func_tool_args}")
+                    # 尝试调用工具函数
+                    wrapper = self.pipeline_ctx.call_handler(
+                        self.event, func_tool.handler, **func_tool_args
                     )
-                except Exception as e:
-                    logger.error(f"Error in on_tool_end hook: {e}", exc_info=True)
+                    async for resp in wrapper:
+                        if resp is not None:
+                            # Tool 返回结果
+                            tool_call_result_blocks.append(
+                                ToolCallMessageSegment(
+                                    role="tool",
+                                    tool_call_id=func_tool_id,
+                                    content=resp,
+                                )
+                            )
+                            yield MessageChain().message(resp)
+                        else:
+                            # 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.event.get_result():
+                                if res.chain:
+                                    yield MessageChain(
+                                        chain=res.chain, type="tool_direct_result"
+                                    )
 
-                self.run_context.event.clear_result()
+                self.event.clear_result()
             except Exception as e:
                 logger.warning(traceback.format_exc())
                 tool_call_result_blocks.append(

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

@@ -6,9 +6,7 @@ import asyncio
 import copy
 import json
 import traceback
-from datetime import timedelta
-from collections.abc import AsyncGenerator
-from astrbot.core.conversation_mgr import Conversation
+from typing import AsyncGenerator, Union
 from astrbot.core import logger
 from astrbot.core.message.components import Image
 from astrbot.core.message.message_event_result import (
@@ -22,292 +20,12 @@ from astrbot.core.provider.entities import (
     LLMResponse,
     ProviderRequest,
 )
-from astrbot.core.agent.hooks import BaseAgentRunHooks
-from astrbot.core.agent.runners.tool_loop_agent_runner import ToolLoopAgentRunner
-from astrbot.core.agent.run_context import ContextWrapper
-from astrbot.core.agent.tool import ToolSet, FunctionTool
-from astrbot.core.agent.tool_executor import BaseFunctionToolExecutor
-from astrbot.core.agent.handoff import HandoffTool
 from astrbot.core.star.session_llm_manager import SessionServiceManager
 from astrbot.core.star.star_handler import EventType
 from astrbot.core.utils.metrics import Metric
-from ...context import PipelineContext, call_event_hook, call_handler
+from ...context import PipelineContext
+from ..agent_runner.tool_loop_agent import ToolLoopAgent
 from ..stage import Stage
-from ..utils import inject_kb_context
-from astrbot.core.provider.register import llm_tools
-from astrbot.core.star.star_handler import star_map
-from astrbot.core.astr_agent_context import AstrAgentContext
-
-try:
-    import mcp
-except (ModuleNotFoundError, ImportError):
-    logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
-
-
-AgentContextWrapper = ContextWrapper[AstrAgentContext]
-AgentRunner = ToolLoopAgentRunner[AstrAgentContext]
-
-
-class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
-    @classmethod
-    async def execute(cls, tool, run_context, **tool_args):
-        """执行函数调用。
-
-        Args:
-            event (AstrMessageEvent): 事件对象, 当 origin 为 local 时必须提供。
-            **kwargs: 函数调用的参数。
-
-        Returns:
-            AsyncGenerator[None | mcp.types.CallToolResult, None]
-        """
-        if isinstance(tool, HandoffTool):
-            async for r in cls._execute_handoff(tool, run_context, **tool_args):
-                yield r
-            return
-
-        if tool.origin == "local":
-            async for r in cls._execute_local(tool, run_context, **tool_args):
-                yield r
-            return
-
-        elif tool.origin == "mcp":
-            async for r in cls._execute_mcp(tool, run_context, **tool_args):
-                yield r
-            return
-
-        raise Exception(f"Unknown function origin: {tool.origin}")
-
-    @classmethod
-    async def _execute_handoff(
-        cls,
-        tool: HandoffTool,
-        run_context: ContextWrapper[AstrAgentContext],
-        **tool_args,
-    ):
-        input_ = tool_args.get("input", "agent")
-        agent_runner = AgentRunner()
-
-        # make toolset for the agent
-        tools = tool.agent.tools
-        if tools:
-            toolset = ToolSet()
-            for t in tools:
-                if isinstance(t, str):
-                    _t = llm_tools.get_func(t)
-                    if _t:
-                        toolset.add_tool(_t)
-                elif isinstance(t, FunctionTool):
-                    toolset.add_tool(t)
-        else:
-            toolset = None
-
-        request = ProviderRequest(
-            prompt=input_,
-            system_prompt=tool.description or "",
-            image_urls=[],  # 暂时不传递原始 agent 的上下文
-            contexts=[],  # 暂时不传递原始 agent 的上下文
-            func_tool=toolset,
-        )
-        astr_agent_ctx = AstrAgentContext(
-            provider=run_context.context.provider,
-            first_provider_request=run_context.context.first_provider_request,
-            curr_provider_request=request,
-            streaming=run_context.context.streaming,
-        )
-
-        logger.debug(f"正在将任务委托给 Agent: {tool.agent.name}, input: {input_}")
-        await run_context.event.send(
-            MessageChain().message("✨ 正在将任务委托给 Agent: " + tool.agent.name)
-        )
-
-        await agent_runner.reset(
-            provider=run_context.context.provider,
-            request=request,
-            run_context=AgentContextWrapper(
-                context=astr_agent_ctx, event=run_context.event
-            ),
-            tool_executor=FunctionToolExecutor(),
-            agent_hooks=tool.agent.run_hooks or BaseAgentRunHooks[AstrAgentContext](),
-            streaming=run_context.context.streaming,
-        )
-
-        async for _ in run_agent(agent_runner, 15, True):
-            pass
-
-        if agent_runner.done():
-            llm_response = agent_runner.get_final_llm_resp()
-
-            if not llm_response:
-                text_content = mcp.types.TextContent(
-                    type="text",
-                    text=f"error when deligate task to {tool.agent.name}",
-                )
-                yield mcp.types.CallToolResult(content=[text_content])
-                return
-
-            logger.debug(
-                f"Agent  {tool.agent.name} 任务完成, response: {llm_response.completion_text}"
-            )
-
-            result = (
-                f"Agent {tool.agent.name} respond with: {llm_response.completion_text}\n\n"
-                "Note: If the result is error or need user provide more information, please provide more information to the agent(you can ask user for more information first)."
-            )
-
-            text_content = mcp.types.TextContent(
-                type="text",
-                text=result,
-            )
-            yield mcp.types.CallToolResult(content=[text_content])
-        else:
-            text_content = mcp.types.TextContent(
-                type="text",
-                text=f"error when deligate task to {tool.agent.name}",
-            )
-            yield mcp.types.CallToolResult(content=[text_content])
-        return
-
-    @classmethod
-    async def _execute_local(
-        cls,
-        tool: FunctionTool,
-        run_context: ContextWrapper[AstrAgentContext],
-        **tool_args,
-    ):
-        if not run_context.event:
-            raise ValueError("Event must be provided for local function tools.")
-
-        # 检查 tool 下有没有 run 方法
-        if not tool.handler and not hasattr(tool, "run"):
-            raise ValueError("Tool must have a valid handler or 'run' method.")
-        awaitable = tool.handler or getattr(tool, "run")
-
-        wrapper = call_handler(
-            event=run_context.event,
-            handler=awaitable,
-            **tool_args,
-        )
-        # async for resp in wrapper:
-        while True:
-            try:
-                resp = await asyncio.wait_for(
-                    anext(wrapper),
-                    timeout=run_context.context.tool_call_timeout,
-                )
-                if resp is not None:
-                    if isinstance(resp, mcp.types.CallToolResult):
-                        yield resp
-                    else:
-                        text_content = mcp.types.TextContent(
-                            type="text",
-                            text=str(resp),
-                        )
-                        yield mcp.types.CallToolResult(content=[text_content])
-                else:
-                    # NOTE: Tool 在这里直接请求发送消息给用户
-                    # TODO: 是否需要判断 event.get_result() 是否为空?
-                    # 如果为空,则说明没有发送消息给用户,并且返回值为空,将返回一个特殊的 TextContent,其内容如"工具没有返回内容"
-                    yield None
-            except asyncio.TimeoutError:
-                raise Exception(
-                    f"tool {tool.name} execution timeout after {run_context.context.tool_call_timeout} seconds."
-                )
-            except StopAsyncIteration:
-                break
-
-    @classmethod
-    async def _execute_mcp(
-        cls,
-        tool: FunctionTool,
-        run_context: ContextWrapper[AstrAgentContext],
-        **tool_args,
-    ):
-        if not tool.mcp_client:
-            raise ValueError("MCP client is not available for MCP function tools.")
-
-        session = tool.mcp_client.session
-        if not session:
-            raise ValueError("MCP session is not available for MCP function tools.")
-        res = await session.call_tool(
-            name=tool.name,
-            arguments=tool_args,
-            read_timeout_seconds=timedelta(
-                seconds=run_context.context.tool_call_timeout
-            ),
-        )
-        if not res:
-            return
-        yield res
-
-
-class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
-    async def on_agent_done(self, run_context, llm_response):
-        # 执行事件钩子
-        await call_event_hook(
-            run_context.event, EventType.OnLLMResponseEvent, llm_response
-        )
-
-
-MAIN_AGENT_HOOKS = MainAgentHooks()
-
-
-async def run_agent(
-    agent_runner: AgentRunner, max_step: int = 30, show_tool_use: bool = True
-) -> AsyncGenerator[MessageChain, None]:
-    step_idx = 0
-    astr_event = agent_runner.run_context.event
-    while step_idx < max_step:
-        step_idx += 1
-        try:
-            async for resp in agent_runner.step():
-                if astr_event.is_stopped():
-                    return
-                if resp.type == "tool_call_result":
-                    msg_chain = resp.data["chain"]
-                    if msg_chain.type == "tool_direct_result":
-                        # tool_direct_result 用于标记 llm tool 需要直接发送给用户的内容
-                        resp.data["chain"].type = "tool_call_result"
-                        await astr_event.send(resp.data["chain"])
-                        continue
-                    # 对于其他情况，暂时先不处理
-                    continue
-                elif resp.type == "tool_call":
-                    if agent_runner.streaming:
-                        # 用来标记流式响应需要分节
-                        yield MessageChain(chain=[], type="break")
-                    if show_tool_use or astr_event.get_platform_name() == "webchat":
-                        resp.data["chain"].type = "tool_call"
-                        await astr_event.send(resp.data["chain"])
-                    continue
-
-                if not agent_runner.streaming:
-                    content_typ = (
-                        ResultContentType.LLM_RESULT
-                        if resp.type == "llm_result"
-                        else ResultContentType.GENERAL_RESULT
-                    )
-                    astr_event.set_result(
-                        MessageEventResult(
-                            chain=resp.data["chain"].chain,
-                            result_content_type=content_typ,
-                        )
-                    )
-                    yield
-                    astr_event.clear_result()
-                else:
-                    if resp.type == "streaming_delta":
-                        yield resp.data["chain"]  # MessageChain
-            if agent_runner.done():
-                break
-
-        except Exception as e:
-            logger.error(traceback.format_exc())
-            err_msg = f"\n\nAstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}\n\n请在控制台查看和分享错误详情。\n"
-            if agent_runner.streaming:
-                yield MessageChain().message(err_msg)
-            else:
-                astr_event.set_result(MessageEventResult().message(err_msg))
-            return
 
 
 class LLMRequestSubStage(Stage):
@@ -323,10 +41,7 @@ class LLMRequestSubStage(Stage):
             self.max_context_length - 1,
         )
         self.streaming_response: bool = settings["streaming_response"]
-        self.max_step: int = settings.get("max_agent_step", 30)
-        self.tool_call_timeout: int = settings.get("tool_call_timeout", 60)
-        if isinstance(self.max_step, bool):  # workaround: #2622
-            self.max_step = 30
+        self.max_step: int = settings.get("max_agent_step", 10)
         self.show_tool_use: bool = settings.get("show_tool_use_status", True)
 
         for bwp in self.bot_wake_prefixs:
@@ -338,7 +53,7 @@ class LLMRequestSubStage(Stage):
 
         self.conv_manager = ctx.plugin_manager.context.conversation_manager
 
-    def _select_provider(self, event: AstrMessageEvent):
+    def _select_provider(self, event: AstrMessageEvent) -> Provider | None:
         """选择使用的 LLM 提供商"""
         sel_provider = event.get_extra("selected_provider")
         _ctx = self.ctx.plugin_manager.context
@@ -350,25 +65,9 @@ class LLMRequestSubStage(Stage):
 
         return _ctx.get_using_provider(umo=event.unified_msg_origin)
 
-    async def _get_session_conv(self, event: AstrMessageEvent) -> Conversation:
-        umo = event.unified_msg_origin
-        conv_mgr = self.conv_manager
-
-        # 获取对话上下文
-        cid = await conv_mgr.get_curr_conversation_id(umo)
-        if not cid:
-            cid = await conv_mgr.new_conversation(umo, event.get_platform_id())
-        conversation = await conv_mgr.get_conversation(umo, cid)
-        if not conversation:
-            cid = await conv_mgr.new_conversation(umo, event.get_platform_id())
-            conversation = await conv_mgr.get_conversation(umo, cid)
-        if not conversation:
-            raise RuntimeError("无法创建新的对话。")
-        return conversation
-
     async def process(
         self, event: AstrMessageEvent, _nested: bool = False
-    ) -> None | AsyncGenerator[None, None]:
+    ) -> Union[None, AsyncGenerator[None, None]]:
         req: ProviderRequest | None = None
 
         if not self.ctx.astrbot_config["provider_settings"]["enable"]:
@@ -383,9 +82,6 @@ class LLMRequestSubStage(Stage):
         provider = self._select_provider(event)
         if provider is None:
             return
-        if not isinstance(provider, Provider):
-            logger.error(f"选择的提供商类型无效({type(provider)})，跳过 LLM 请求处理。")
-            return
 
         if event.get_extra("provider_request"):
             req = event.get_extra("provider_request")
@@ -404,14 +100,30 @@ class LLMRequestSubStage(Stage):
                 if not event.message_str.startswith(self.provider_wake_prefix):
                     return
             req.prompt = event.message_str[len(self.provider_wake_prefix) :]
-            # func_tool selection 现在已经转移到 packages/astrbot 插件中进行选择。
-            # req.func_tool = self.ctx.plugin_manager.context.get_llm_tool_manager()
+            req.func_tool = self.ctx.plugin_manager.context.get_llm_tool_manager()
             for comp in event.message_obj.message:
                 if isinstance(comp, Image):
                     image_path = await comp.convert_to_file_path()
                     req.image_urls.append(image_path)
 
-            conversation = await self._get_session_conv(event)
+            # 获取对话上下文
+            conversation_id = await self.conv_manager.get_curr_conversation_id(
+                event.unified_msg_origin
+            )
+            if not conversation_id:
+                conversation_id = await self.conv_manager.new_conversation(
+                    event.unified_msg_origin
+                )
+            conversation = await self.conv_manager.get_conversation(
+                event.unified_msg_origin, conversation_id
+            )
+            if not conversation:
+                conversation_id = await self.conv_manager.new_conversation(
+                    event.unified_msg_origin
+                )
+                conversation = await self.conv_manager.get_conversation(
+                    event.unified_msg_origin, conversation_id
+                )
             req.conversation = conversation
             req.contexts = json.loads(conversation.history)
 
@@ -420,16 +132,8 @@ class LLMRequestSubStage(Stage):
         if not req.prompt and not req.image_urls:
             return
 
-        # 应用知识库
-        try:
-            await inject_kb_context(
-                umo=event.unified_msg_origin, p_ctx=self.ctx, req=req
-            )
-        except Exception as e:
-            logger.error(f"调用知识库时遇到问题: {e}")
-
         # 执行请求 LLM 前事件钩子。
-        if await call_event_hook(event, EventType.OnLLMRequestEvent, req):
+        if await self.ctx.call_event_hook(event, EventType.OnLLMRequestEvent, req):
             return
 
         if isinstance(req.contexts, str):
@@ -463,79 +167,98 @@ class LLMRequestSubStage(Stage):
         # fix messages
         req.contexts = self.fix_messages(req.contexts)
 
-        # check provider modalities
-        # 如果提供商不支持图像/工具使用，但请求中包含图像/工具列表，则清空。图片转述等的检测和调用发生在这之前，因此这里可以这样处理。
-        if req.image_urls:
-            provider_cfg = provider.provider_config.get("modalities", ["image"])
-            if "image" not in provider_cfg:
-                logger.debug(f"用户设置提供商 {provider} 不支持图像，清空图像列表。")
-                req.image_urls = []
-        if req.func_tool:
-            provider_cfg = provider.provider_config.get("modalities", ["tool_use"])
-            # 如果模型不支持工具使用，但请求中包含工具列表，则清空。
-            if "tool_use" not in provider_cfg:
-                logger.debug(
-                    f"用户设置提供商 {provider} 不支持工具使用，清空工具列表。"
-                )
-                req.func_tool = None
-        # 插件可用性设置
-        if event.plugins_name is not None and req.func_tool:
-            new_tool_set = ToolSet()
-            for tool in req.func_tool.tools:
-                mp = tool.handler_module_path
-                if not mp:
-                    continue
-                plugin = star_map.get(mp)
-                if not plugin:
-                    continue
-                if plugin.name in event.plugins_name or plugin.reserved:
-                    new_tool_set.add_tool(tool)
-            req.func_tool = new_tool_set
-
-        # 备份 req.contexts
-        backup_contexts = copy.deepcopy(req.contexts)
-
-        # run agent
-        agent_runner = AgentRunner()
+        # Call Agent
+        tool_loop_agent = ToolLoopAgent(
+            provider=provider,
+            event=event,
+            pipeline_ctx=self.ctx,
+        )
         logger.debug(
             f"handle provider[id: {provider.provider_config['id']}] request: {req}"
         )
-        astr_agent_ctx = AstrAgentContext(
-            provider=provider,
-            first_provider_request=req,
-            curr_provider_request=req,
-            streaming=self.streaming_response,
-            tool_call_timeout=self.tool_call_timeout,
-        )
-        await agent_runner.reset(
-            provider=provider,
-            request=req,
-            run_context=AgentContextWrapper(context=astr_agent_ctx, event=event),
-            tool_executor=FunctionToolExecutor(),
-            agent_hooks=MAIN_AGENT_HOOKS,
-            streaming=self.streaming_response,
-        )
+        await tool_loop_agent.reset(req=req, streaming=self.streaming_response)
+
+        async def requesting():
+            step_idx = 0
+            while step_idx < self.max_step:
+                step_idx += 1
+                try:
+                    async for resp in tool_loop_agent.step():
+                        if event.is_stopped():
+                            return
+                        if resp.type == "tool_call_result":
+                            msg_chain = resp.data["chain"]
+                            if msg_chain.type == "tool_direct_result":
+                                # tool_direct_result 用于标记 llm tool 需要直接发送给用户的内容
+                                resp.data["chain"].type = "tool_call_result"
+                                await event.send(resp.data["chain"])
+                                continue
+                            # 对于其他情况，暂时先不处理
+                            continue
+                        elif resp.type == "tool_call":
+                            if self.streaming_response:
+                                # 用来标记流式响应需要分节
+                                yield MessageChain(chain=[], type="break")
+                            if (
+                                self.show_tool_use
+                                or event.get_platform_name() == "webchat"
+                            ):
+                                resp.data["chain"].type = "tool_call"
+                                await event.send(resp.data["chain"])
+                            continue
+
+                        if not self.streaming_response:
+                            content_typ = (
+                                ResultContentType.LLM_RESULT
+                                if resp.type == "llm_result"
+                                else ResultContentType.GENERAL_RESULT
+                            )
+                            event.set_result(
+                                MessageEventResult(
+                                    chain=resp.data["chain"].chain,
+                                    result_content_type=content_typ,
+                                )
+                            )
+                            yield
+                            event.clear_result()
+                        else:
+                            if resp.type == "streaming_delta":
+                                yield resp.data["chain"]  # MessageChain
+                    if tool_loop_agent.done():
+                        break
+
+                except Exception as e:
+                    logger.error(traceback.format_exc())
+                    event.set_result(
+                        MessageEventResult().message(
+                            f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}\n\n请在控制台查看和分享错误详情。\n"
+                        )
+                    )
+                    return
+                asyncio.create_task(
+                    Metric.upload(
+                        llm_tick=1,
+                        model_name=provider.get_model(),
+                        provider_type=provider.meta().type,
+                    )
+                )
 
         if self.streaming_response:
             # 流式响应
             event.set_result(
                 MessageEventResult()
                 .set_result_content_type(ResultContentType.STREAMING_RESULT)
-                .set_async_stream(
-                    run_agent(agent_runner, self.max_step, self.show_tool_use)
-                )
+                .set_async_stream(requesting())
             )
             yield
-            if agent_runner.done():
-                if final_llm_resp := agent_runner.get_final_llm_resp():
+            if tool_loop_agent.done():
+                if final_llm_resp := tool_loop_agent.get_final_llm_resp():
                     if final_llm_resp.completion_text:
                         chain = (
                             MessageChain().message(final_llm_resp.completion_text).chain
                         )
-                    elif final_llm_resp.result_chain:
-                        chain = final_llm_resp.result_chain.chain
                     else:
-                        chain = MessageChain().chain
+                        chain = final_llm_resp.result_chain.chain
                     event.set_result(
                         MessageEventResult(
                             chain=chain,
@@ -543,32 +266,19 @@ class LLMRequestSubStage(Stage):
                         )
                     )
         else:
-            async for _ in run_agent(agent_runner, self.max_step, self.show_tool_use):
+            async for _ in requesting():
                 yield
 
-        # 恢复备份的 contexts
-        req.contexts = backup_contexts
-
-        await self._save_to_history(event, req, agent_runner.get_final_llm_resp())
-
         # 异步处理 WebChat 特殊情况
         if event.get_platform_name() == "webchat":
             asyncio.create_task(self._handle_webchat(event, req, provider))
 
-        asyncio.create_task(
-            Metric.upload(
-                llm_tick=1,
-                model_name=agent_runner.provider.get_model(),
-                provider_type=agent_runner.provider.meta().type,
-            )
-        )
+        await self._save_to_history(event, req, tool_loop_agent.get_final_llm_resp())
 
     async def _handle_webchat(
         self, event: AstrMessageEvent, req: ProviderRequest, prov: Provider
     ):
         """处理 WebChat 平台的特殊情况，包括第一次 LLM 对话时总结对话内容生成 title"""
-        if not req.conversation:
-            return
         conversation = await self.conv_manager.get_conversation(
             event.unified_msg_origin, req.conversation.cid
         )
@@ -577,23 +287,7 @@ class LLMRequestSubStage(Stage):
             latest_pair = messages[-2:]
             if not latest_pair:
                 return
-            content = latest_pair[0].get("content", "")
-            if isinstance(content, list):
-                # 多模态
-                text_parts = []
-                for item in content:
-                    if isinstance(item, dict):
-                        if item.get("type") == "text":
-                            text_parts.append(item.get("text", ""))
-                        elif item.get("type") == "image":
-                            text_parts.append("[图片]")
-                    elif isinstance(item, str):
-                        text_parts.append(item)
-                cleaned_text = "User: " + " ".join(text_parts).strip()
-            elif isinstance(content, str):
-                cleaned_text = "User: " + content.strip()
-            else:
-                return
+            cleaned_text = "User: " + latest_pair[0].get("content", "").strip()
             logger.debug(f"WebChat 对话标题生成请求，清理后的文本: {cleaned_text}")
             llm_resp = await prov.text_chat(
                 system_prompt="You are expert in summarizing user's query.",
@@ -613,10 +307,19 @@ class LLMRequestSubStage(Stage):
                 if not title or "<None>" in title:
                     return
                 await self.conv_manager.update_conversation_title(
-                    unified_msg_origin=event.unified_msg_origin,
-                    title=title,
-                    conversation_id=req.conversation.cid,
+                    event.unified_msg_origin, title=title
                 )
+                # 由于 WebChat 平台特殊性，其有两个对话，因此我们要更新两个对话的标题
+                # webchat adapter 中，session_id 的格式是 f"webchat!{username}!{cid}"
+                # TODO: 优化 WebChat 适配器的对话管理
+                if event.session_id:
+                    username, cid = event.session_id.split("!")[1:3]
+                    db_helper = self.ctx.plugin_manager.context._db
+                    db_helper.update_conversation_title(
+                        user_id=username,
+                        cid=cid,
+                        title=title,
+                    )
 
     async def _save_to_history(
         self,
@@ -632,10 +335,6 @@ class LLMRequestSubStage(Stage):
         ):
             return
 
-        if not llm_response.completion_text and not req.tool_calls_result:
-            logger.debug("LLM 响应为空，不保存记录。")
-            return
-
         # 历史上下文
         messages = copy.deepcopy(req.contexts)
         # 这一轮对话请求的用户输入

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, call_handler
+from ...context import PipelineContext
 from ..stage import Stage
 from typing import Dict, Any, List, AsyncGenerator, Union
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
@@ -33,16 +33,24 @@ class StarRequestSubStage(Stage):
             handlers_parsed_params = {}
 
         for handler in activated_handlers:
-            params = handlers_parsed_params.get(handler.handler_full_name, {})
-            md = star_map.get(handler.handler_module_path)
-            if not md:
-                logger.warning(
-                    f"Cannot find plugin for given handler module path: {handler.handler_module_path}"
+            # 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
-            logger.debug(f"plugin -> {md.name} - {handler.handler_name}")
+
+            params = handlers_parsed_params.get(handler.handler_full_name, {})
             try:
-                wrapper = call_handler(event, handler.handler, **params)
+                if handler.handler_module_path not in star_map:
+                    continue
+                logger.debug(
+                    f"plugin -> {star_map.get(handler.handler_module_path).name} - {handler.handler_name}"
+                )
+                wrapper = self.ctx.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
@@ -51,7 +59,7 @@ class StarRequestSubStage(Stage):
                 logger.error(f"Star {handler.handler_full_name} handle error: {e}")
 
                 if event.is_at_or_wake_command:
-                    ret = f":(\n\n在调用插件 {md.name} 的处理函数 {handler.handler_name} 时出现异常：{e}"
+                    ret = f":(\n\n在调用插件 {star_map.get(handler.handler_module_path).name} 的处理函数 {handler.handler_name} 时出现异常：{e}"
                     event.set_result(MessageEventResult().message(ret))
                     yield
                     event.clear_result()

astrbot/core/pipeline/process_stage/utils.py

@@ -1,80 +0,0 @@
-from ..context import PipelineContext
-from astrbot.core.provider.entities import ProviderRequest
-from astrbot.api import logger, sp
-
-
-async def inject_kb_context(
-    umo: str,
-    p_ctx: PipelineContext,
-    req: ProviderRequest,
-) -> None:
-    """inject knowledge base context into the provider request
-
-    Args:
-        umo: Unique message object (session ID)
-        p_ctx: Pipeline context
-        req: Provider request
-    """
-
-    kb_mgr = p_ctx.plugin_manager.context.kb_manager
-
-    # 1. 优先读取会话级配置
-    session_config = await sp.session_get(umo, "kb_config", default={})
-
-    if session_config and "kb_ids" in session_config:
-        # 会话级配置
-        kb_ids = session_config.get("kb_ids", [])
-
-        # 如果配置为空列表，明确表示不使用知识库
-        if not kb_ids:
-            logger.info(f"[知识库] 会话 {umo} 已被配置为不使用知识库")
-            return
-
-        top_k = session_config.get("top_k", 5)
-
-        # 将 kb_ids 转换为 kb_names
-        kb_names = []
-        invalid_kb_ids = []
-        for kb_id in kb_ids:
-            kb_helper = await kb_mgr.get_kb(kb_id)
-            if kb_helper:
-                kb_names.append(kb_helper.kb.kb_name)
-            else:
-                logger.warning(f"[知识库] 知识库不存在或未加载: {kb_id}")
-                invalid_kb_ids.append(kb_id)
-
-        if invalid_kb_ids:
-            logger.warning(
-                f"[知识库] 会话 {umo} 配置的以下知识库无效: {invalid_kb_ids}"
-            )
-
-        if not kb_names:
-            return
-
-        logger.debug(f"[知识库] 使用会话级配置，知识库数量: {len(kb_names)}")
-    else:
-        kb_names = p_ctx.astrbot_config.get("kb_names", [])
-        top_k = p_ctx.astrbot_config.get("kb_final_top_k", 5)
-        logger.debug(f"[知识库] 使用全局配置，知识库数量: {len(kb_names)}")
-
-    top_k_fusion = p_ctx.astrbot_config.get("kb_fusion_top_k", 20)
-
-    if not kb_names:
-        return
-
-    logger.debug(f"[知识库] 开始检索知识库，数量: {len(kb_names)}, top_k={top_k}")
-    kb_context = await kb_mgr.retrieve(
-        query=req.prompt,
-        kb_names=kb_names,
-        top_k_fusion=top_k_fusion,
-        top_m_final=top_k,
-    )
-
-    if not kb_context:
-        return
-
-    formatted = kb_context.get("context_text", "")
-    if formatted:
-        results = kb_context.get("results", [])
-        logger.debug(f"[知识库] 为会话 {umo} 注入了 {len(results)} 条相关知识块")
-        req.system_prompt = f"{formatted}\n\n{req.system_prompt or ''}"

astrbot/core/pipeline/respond/stage.py

@@ -1,15 +1,17 @@
 import random
 import asyncio
 import math
+import traceback
 import astrbot.core.message.components as Comp
 from typing import Union, AsyncGenerator
 from ..stage import register_stage, Stage
-from ..context import PipelineContext, call_event_hook
+from ..context import PipelineContext
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import MessageChain, ResultContentType
 from astrbot.core import logger
-from astrbot.core.message.components import BaseMessageComponent, ComponentType
-from astrbot.core.star.star_handler import EventType
+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
 
@@ -112,43 +114,6 @@ class RespondStage(Stage):
         # 如果所有组件都为空
         return True
 
-    def is_seg_reply_required(self, event: AstrMessageEvent) -> bool:
-        """检查是否需要分段回复"""
-        if not self.enable_seg:
-            return False
-
-        if self.only_llm_result and not event.get_result().is_llm_result():
-            return False
-
-        if event.get_platform_name() in [
-            "qq_official",
-            "weixin_official_account",
-            "dingtalk",
-        ]:
-            return False
-
-        return True
-
-    def _extract_comp(
-        self,
-        raw_chain: list[BaseMessageComponent],
-        extract_types: set[ComponentType],
-        modify_raw_chain: bool = True,
-    ):
-        extracted = []
-        if modify_raw_chain:
-            remaining = []
-            for comp in raw_chain:
-                if comp.type in extract_types:
-                    extracted.append(comp)
-                else:
-                    remaining.append(comp)
-            raw_chain[:] = remaining
-        else:
-            extracted = [comp for comp in raw_chain if comp.type in extract_types]
-
-        return extracted
-
     async def process(
         self, event: AstrMessageEvent
     ) -> Union[None, AsyncGenerator[None, None]]:
@@ -158,19 +123,12 @@ class RespondStage(Stage):
         if result.result_content_type == ResultContentType.STREAMING_FINISH:
             return
 
-        logger.info(
-            f"Prepare to send - {event.get_sender_name()}/{event.get_sender_id()}: {event._outline_chain(result.chain)}"
-        )
-
         if result.result_content_type == ResultContentType.STREAMING_RESULT:
-            if result.async_stream is None:
-                logger.warning("async_stream 为空，跳过发送。")
-                return
             # 流式结果直接交付平台适配器处理
             use_fallback = self.config.get("provider_settings", {}).get(
                 "streaming_segmented", False
             )
-            logger.info(f"应用流式输出({event.get_platform_id()})")
+            logger.info(f"应用流式输出({event.get_platform_name()})")
             await event.send_streaming(result.async_stream, use_fallback)
             return
         elif len(result.chain) > 0:
@@ -186,85 +144,93 @@ class RespondStage(Stage):
             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}")
 
-            # 将 Plain 为空的消息段移除
-            result.chain = [
-                comp
-                for comp in result.chain
-                if not (
-                    isinstance(comp, Comp.Plain)
-                    and (not comp.text or not comp.text.strip())
-                )
+            record_comps = [c for c in result.chain if isinstance(c, Comp.Record)]
+            non_record_comps = [
+                c for c in result.chain if not isinstance(c, Comp.Record)
             ]
 
-            # 发送消息链
-            # Record 需要强制单独发送
-            need_separately = {ComponentType.Record}
-            if self.is_seg_reply_required(event):
-                header_comps = self._extract_comp(
-                    result.chain,
-                    {ComponentType.Reply, ComponentType.At},
-                    modify_raw_chain=True,
+            if (
+                self.enable_seg
+                and (
+                    (self.only_llm_result and result.is_llm_result())
+                    or not self.only_llm_result
                 )
-                if not result.chain or len(result.chain) == 0:
-                    # may fix #2670
-                    logger.warning(
-                        f"实际消息链为空, 跳过发送阶段。header_chain: {header_comps}, actual_chain: {result.chain}"
-                    )
-                    return
-                async with session_lock_manager.acquire_lock(event.unified_msg_origin):
+                and event.get_platform_name()
+                not in ["qq_official", "weixin_official_account", "dingtalk"]
+            ):
+                decorated_comps = []
+                if self.reply_with_mention:
                     for comp in result.chain:
+                        if isinstance(comp, Comp.At):
+                            decorated_comps.append(comp)
+                            result.chain.remove(comp)
+                            break
+                if self.reply_with_quote:
+                    for comp in result.chain:
+                        if isinstance(comp, Comp.Reply):
+                            decorated_comps.append(comp)
+                            result.chain.remove(comp)
+                            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:
-                            if comp.type in need_separately:
-                                await event.send(MessageChain([comp]))
-                            else:
-                                await event.send(MessageChain([*header_comps, comp]))
-                                header_comps.clear()
+                            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"发送消息链失败: chain = {MessageChain([comp])}, error = {e}",
-                                exc_info=True,
-                            )
+                            logger.error(f"发送消息失败: {e} chain: {result.chain}")
+                            break
             else:
-                if all(
-                    comp.type in {ComponentType.Reply, ComponentType.At}
-                    for comp in result.chain
-                ):
-                    # may fix #2670
-                    logger.warning(
-                        f"消息链全为 Reply 和 At 消息段, 跳过发送阶段。chain: {result.chain}"
-                    )
-                    return
-                sep_comps = self._extract_comp(
-                    result.chain,
-                    need_separately,
-                    modify_raw_chain=True,
-                )
-                for comp in sep_comps:
-                    chain = MessageChain([comp])
+                for rcomp in record_comps:
                     try:
-                        await event.send(chain)
+                        await event.send(MessageChain([rcomp]))
                     except Exception as e:
-                        logger.error(
-                            f"发送消息链失败: chain = {chain}, error = {e}",
-                            exc_info=True,
-                        )
-                chain = MessageChain(result.chain)
-                if result.chain and len(result.chain) > 0:
-                    try:
-                        await event.send(chain)
-                    except Exception as e:
-                        logger.error(
-                            f"发送消息链失败: chain = {chain}, error = {e}",
-                            exc_info=True,
-                        )
+                        logger.error(f"发送消息失败: {e} chain: {result.chain}")
 
-        if await call_event_hook(event, EventType.OnAfterMessageSentEvent):
-            return
+                try:
+                    await event.send(MessageChain(non_record_comps))
+                except Exception as e:
+                    logger.error(traceback.format_exc())
+                    logger.error(f"发送消息失败: {e} chain: {result.chain}")
+
+            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()
+        )
+        for handler in handlers:
+            try:
+                logger.debug(
+                    f"hook(on_after_message_sent) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
+                )
+                await handler.handler(event)
+            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.clear_result()

astrbot/core/pipeline/result_decorate/stage.py

@@ -36,7 +36,6 @@ class ResultDecorateStage(Stage):
             self.t2i_word_threshold = 150
         self.t2i_strategy = ctx.astrbot_config["t2i_strategy"]
         self.t2i_use_network = self.t2i_strategy == "remote"
-        self.t2i_active_template = ctx.astrbot_config["t2i_active_template"]
 
         self.forward_threshold = ctx.astrbot_config["platform_settings"][
             "forward_threshold"
@@ -65,10 +64,9 @@ class ResultDecorateStage(Stage):
         ]
         self.content_safe_check_stage = None
         if self.content_safe_check_reply:
-            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)
+            for stage in registered_stages:
+                if stage.__class__.__name__ == "ContentSafetyCheckStage":
+                    self.content_safe_check_stage = stage
 
     async def process(
         self, event: AstrMessageEvent
@@ -100,7 +98,7 @@ class ResultDecorateStage(Stage):
 
         # 发送消息前事件钩子
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnDecoratingResultEvent, plugins_name=event.plugins_name
+            EventType.OnDecoratingResultEvent, platform_id=event.get_platform_id()
         )
         for handler in handlers:
             try:
@@ -183,60 +181,56 @@ class ResultDecorateStage(Stage):
             if (
                 self.ctx.astrbot_config["provider_tts_settings"]["enable"]
                 and result.is_llm_result()
+                and tts_provider
                 and SessionServiceManager.should_process_tts_request(event)
             ):
-                if not tts_provider:
-                    logger.warning(
-                        f"会话 {event.unified_msg_origin} 未配置文本转语音模型。"
-                    )
-                else:
-                    new_chain = []
-                    for comp in result.chain:
-                        if isinstance(comp, Plain) and len(comp.text) > 1:
-                            try:
-                                logger.info(f"TTS 请求: {comp.text}")
-                                audio_path = await tts_provider.get_audio(comp.text)
-                                logger.info(f"TTS 结果: {audio_path}")
-                                if not audio_path:
-                                    logger.error(
-                                        f"由于 TTS 音频文件未找到，消息段转语音失败: {comp.text}"
-                                    )
-                                    new_chain.append(comp)
-                                    continue
-
-                                use_file_service = self.ctx.astrbot_config[
-                                    "provider_tts_settings"
-                                ]["use_file_service"]
-                                callback_api_base = self.ctx.astrbot_config[
-                                    "callback_api_base"
-                                ]
-                                dual_output = self.ctx.astrbot_config[
-                                    "provider_tts_settings"
-                                ]["dual_output"]
-
-                                url = None
-                                if use_file_service and callback_api_base:
-                                    token = await file_token_service.register_file(
-                                        audio_path
-                                    )
-                                    url = f"{callback_api_base}/api/file/{token}"
-                                    logger.debug(f"已注册：{url}")
-
-                                new_chain.append(
-                                    Record(
-                                        file=url or audio_path,
-                                        url=url or audio_path,
-                                    )
+                new_chain = []
+                for comp in result.chain:
+                    if isinstance(comp, Plain) and len(comp.text) > 1:
+                        try:
+                            logger.info(f"TTS 请求: {comp.text}")
+                            audio_path = await tts_provider.get_audio(comp.text)
+                            logger.info(f"TTS 结果: {audio_path}")
+                            if not audio_path:
+                                logger.error(
+                                    f"由于 TTS 音频文件未找到，消息段转语音失败: {comp.text}"
                                 )
-                                if dual_output:
-                                    new_chain.append(comp)
-                            except Exception:
-                                logger.error(traceback.format_exc())
-                                logger.error("TTS 失败，使用文本发送。")
                                 new_chain.append(comp)
-                        else:
+                                continue
+
+                            use_file_service = self.ctx.astrbot_config[
+                                "provider_tts_settings"
+                            ]["use_file_service"]
+                            callback_api_base = self.ctx.astrbot_config[
+                                "callback_api_base"
+                            ]
+                            dual_output = self.ctx.astrbot_config[
+                                "provider_tts_settings"
+                            ]["dual_output"]
+
+                            url = None
+                            if use_file_service and callback_api_base:
+                                token = await file_token_service.register_file(
+                                    audio_path
+                                )
+                                url = f"{callback_api_base}/api/file/{token}"
+                                logger.debug(f"已注册：{url}")
+
+                            new_chain.append(
+                                Record(
+                                    file=url or audio_path,
+                                    url=url or audio_path,
+                                )
+                            )
+                            if dual_output:
+                                new_chain.append(comp)
+                        except Exception:
+                            logger.error(traceback.format_exc())
+                            logger.error("TTS 失败，使用文本发送。")
                             new_chain.append(comp)
-                    result.chain = new_chain
+                    else:
+                        new_chain.append(comp)
+                result.chain = new_chain
 
             # 文本转图片
             elif (
@@ -252,10 +246,7 @@ class ResultDecorateStage(Stage):
                     render_start = time.time()
                     try:
                         url = await html_renderer.render_t2i(
-                            plain_str,
-                            return_url=True,
-                            use_network=self.t2i_use_network,
-                            template_name=self.t2i_active_template,
+                            plain_str, return_url=True, use_network=self.t2i_use_network
                         )
                     except BaseException:
                         logger.error("文本转图片失败，使用文本发送。")
@@ -279,6 +270,7 @@ class ResultDecorateStage(Stage):
                             result.chain = [Image.fromFileSystem(url)]
 
             # 触发转发消息
+            has_forwarded = False
             if event.get_platform_name() == "aiocqhttp":
                 word_cnt = 0
                 for comp in result.chain:
@@ -289,9 +281,9 @@ class ResultDecorateStage(Stage):
                         uin=event.get_self_id(), name="AstrBot", content=[*result.chain]
                     )
                     result.chain = [node]
+                    has_forwarded = True
 
-            has_plain = any(isinstance(item, Plain) for item in result.chain)
-            if has_plain:
+            if not has_forwarded:
                 # at 回复
                 if (
                     self.reply_with_mention

astrbot/core/pipeline/scheduler.py

@@ -11,17 +11,16 @@ class PipelineScheduler:
 
     def __init__(self, context: PipelineContext):
         registered_stages.sort(
-            key=lambda x: STAGES_ORDER.index(x.__name__)
+            key=lambda x: STAGES_ORDER.index(x.__class__.__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_cls in registered_stages:
-            stage_instance = stage_cls()  # 创建实例
-            await stage_instance.initialize(self.ctx)
-            self.stages.append(stage_instance)
+        for stage in registered_stages:
+            # logger.debug(f"初始化阶段 {stage.__class__ .__name__}")
+
+            await stage.initialize(self.ctx)
 
     async def _process_stages(self, event: AstrMessageEvent, from_stage=0):
         """依次执行各个阶段
@@ -30,9 +29,9 @@ 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(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__}")
+        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__}")
             coroutine = stage.process(
                 event
             )  # 调用阶段的process方法, 返回协程或者异步生成器
@@ -74,7 +73,7 @@ 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 event.get_platform_name() in ["webchat", "wecom_ai_bot"]:
+        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

@@ -11,8 +11,7 @@ class SessionStatusCheckStage(Stage):
     """检查会话是否整体启用"""
 
     async def initialize(self, ctx: PipelineContext) -> None:
-        self.ctx = ctx
-        self.conv_mgr = ctx.plugin_manager.context.conversation_manager
+        pass
 
     async def process(
         self, event: AstrMessageEvent
@@ -20,14 +19,4 @@ class SessionStatusCheckStage(Stage):
         # 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。")
-
-            # workaround for #2309
-            conv_id = await self.conv_mgr.get_curr_conversation_id(
-                event.unified_msg_origin
-            )
-            if not conv_id:
-                await self.conv_mgr.new_conversation(
-                    event.unified_msg_origin, platform_id=event.get_platform_id()
-                )
-
             event.stop_event()

astrbot/core/pipeline/stage.py

@@ -1,15 +1,15 @@
 from __future__ import annotations
 import abc
-from typing import List, AsyncGenerator, Union, Type
+from typing import List, AsyncGenerator, Union
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from .context import PipelineContext
 
-registered_stages: List[Type[Stage]] = []  # 维护了所有已注册的 Stage 实现类类型
+registered_stages: List[Stage] = []  # 维护了所有已注册的 Stage 实现类
 
 
 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
 
 

astrbot/core/pipeline/waking_check/stage.py

@@ -5,7 +5,6 @@ from astrbot.core.message.components import At, AtAll, Reply
 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.filter.command_group import CommandGroupFilter
 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
@@ -113,17 +112,8 @@ 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, plugins_name=event.plugins_name
+            EventType.AdapterMessageEvent
         ):
             # filter 需满足 AND 逻辑关系
             passed = True
@@ -171,15 +161,11 @@ class WakingCheckStage(Stage):
                 is_wake = True
                 event.is_wake = True
 
-                is_group_cmd_handler = any(
-                    isinstance(f, CommandGroupFilter) for f in handler.event_filters
-                )
-                if not is_group_cmd_handler:
-                    activated_handlers.append(handler)
-                    if "parsed_params" in event.get_extra(default={}):
-                        handlers_parsed_params[handler.handler_full_name] = (
-                            event.get_extra("parsed_params")
-                        )
+                activated_handlers.append(handler)
+                if "parsed_params" in event.get_extra():
+                    handlers_parsed_params[handler.handler_full_name] = event.get_extra(
+                        "parsed_params"
+                    )
 
             event._extras.pop("parsed_params", None)
 

astrbot/core/platform/astr_message_event.py

@@ -3,10 +3,9 @@ import asyncio
 import re
 import hashlib
 import uuid
+from dataclasses import dataclass
+from typing import List, Union, Optional, AsyncGenerator
 
-from typing import List, Union, Optional, AsyncGenerator, Any
-
-from astrbot import logger
 from astrbot.core.db.po import Conversation
 from astrbot.core.message.components import (
     Plain,
@@ -24,7 +23,21 @@ 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
-from .message_session import MessageSession, MessageSesion  # noqa
+
+
+@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)
 
 
 class AstrMessageEvent(abc.ABC):
@@ -49,15 +62,15 @@ class AstrMessageEvent(abc.ABC):
         """是否唤醒(是否通过 WakingStage)"""
         self.is_at_or_wake_command = False
         """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: dict[str, Any] = {}
+        self._extras = {}
         self.session = MessageSesion(
-            platform_name=platform_meta.id,
+            platform_name=platform_meta.name,
             message_type=message_obj.type,
             session_id=session_id,
         )
         self.unified_msg_origin = str(self.session)
         """统一的消息来源字符串。格式为 platform_name:message_type:session_id"""
-        self._result: MessageEventResult | None = None
+        self._result: MessageEventResult = None
         """消息事件的结果"""
 
         self._has_send_oper = False
@@ -65,23 +78,13 @@ 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:
@@ -90,10 +93,8 @@ class AstrMessageEvent(abc.ABC):
         """
         return self.message_str
 
-    def _outline_chain(self, chain: Optional[List[BaseMessageComponent]]) -> str:
+    def _outline_chain(self, chain: List[BaseMessageComponent]) -> str:
         outline = ""
-        if not chain:
-            return outline
         for i in chain:
             if isinstance(i, Plain):
                 outline += i.text
@@ -175,19 +176,18 @@ class AstrMessageEvent(abc.ABC):
         """
         self._extras[key] = value
 
-    def get_extra(self, key: str | None = None, default=None) -> Any:
+    def get_extra(self, key=None):
         """
         获取额外的信息。
         """
         if key is None:
             return self._extras
-        return self._extras.get(key, default)
+        return self._extras.get(key, None)
 
     def clear_extra(self):
         """
         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:
@@ -263,9 +263,6 @@ class AstrMessageEvent(abc.ABC):
         """
         if isinstance(result, str):
             result = MessageEventResult().message(result)
-        # 兼容外部插件或调用方传入的 chain=None 的情况，确保为可迭代列表
-        if isinstance(result, MessageEventResult) and result.chain is None:
-            result.chain = []
         self._result = result
 
     def stop_event(self):
@@ -417,16 +414,6 @@ class AstrMessageEvent(abc.ABC):
         )
         self._has_send_oper = True
 
-    async def react(self, emoji: str):
-        """
-        对消息添加表情回应。
-
-        默认实现为发送一条包含该表情的消息。
-        注意：此实现并不一定符合所有平台的原生“表情回应”行为。
-        如需支持平台原生的消息反应功能，请在对应平台的子类中重写本方法。
-        """
-        await self.send(MessageChain([Plain(emoji)]))
-
     async def get_group(self, group_id: str = None, **kwargs) -> Optional[Group]:
         """获取一个群聊的数据, 如果不填写 group_id: 如果是私聊消息，返回 None。如果是群聊消息，返回当前群聊的数据。
 

astrbot/core/platform/astrbot_message.py

@@ -55,7 +55,7 @@ class AstrBotMessage:
     self_id: str  # 机器人的识别id
     session_id: str  # 会话id。取决于 unique_session 的设置。
     message_id: str  # 消息id
-    group: Group  # 群组
+    group_id: str = ""  # 群组id，如果为私聊，则为空
     sender: MessageMember  # 发送者
     message: List[BaseMessageComponent]  # 消息链使用 Nakuru 的消息链格式
     message_str: str  # 最直观的纯文本消息字符串
@@ -64,28 +64,6 @@ class AstrBotMessage:
 
     def __init__(self) -> None:
         self.timestamp = int(time.time())
-        self.group = None
 
     def __str__(self) -> str:
         return str(self.__dict__)
-
-    @property
-    def group_id(self) -> str:
-        """
-        向后兼容的 group_id 属性
-        群组id，如果为私聊，则为空
-        """
-        if self.group:
-            return self.group.group_id
-        return ""
-
-    @group_id.setter
-    def group_id(self, value: str):
-        """设置 group_id"""
-        if value:
-            if self.group:
-                self.group.group_id = value
-            else:
-                self.group = Group(group_id=value)
-        else:
-            self.group = None

astrbot/core/platform/manager.py

@@ -6,7 +6,6 @@ from typing import List
 from asyncio import Queue
 from .register import platform_cls_map
 from astrbot.core import logger
-from astrbot.core.star.star_handler import star_handlers_registry, star_map, EventType
 from .sources.webchat.webchat_adapter import WebChatAdapter
 
 
@@ -19,9 +18,6 @@ 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):
@@ -67,43 +63,25 @@ class PlatformManager:
                         WeChatPadProAdapter,  # noqa: F401
                     )
                 case "lark":
-                    from .sources.lark.lark_adapter import (
-                        LarkPlatformAdapter,  # noqa: F401
-                    )
+                    from .sources.lark.lark_adapter import LarkPlatformAdapter  # noqa: F401
                 case "dingtalk":
                     from .sources.dingtalk.dingtalk_adapter import (
                         DingtalkPlatformAdapter,  # noqa: F401
                     )
                 case "telegram":
-                    from .sources.telegram.tg_adapter import (
-                        TelegramPlatformAdapter,  # noqa: F401
-                    )
+                    from .sources.telegram.tg_adapter import TelegramPlatformAdapter  # noqa: F401
                 case "wecom":
-                    from .sources.wecom.wecom_adapter import (
-                        WecomPlatformAdapter,  # noqa: F401
-                    )
-                case "wecom_ai_bot":
-                    from .sources.wecom_ai_bot.wecomai_adapter import (
-                        WecomAIBotAdapter,  # noqa: F401
-                    )
+                    from .sources.wecom.wecom_adapter import WecomPlatformAdapter  # noqa: F401
                 case "weixin_official_account":
                     from .sources.weixin_official_account.weixin_offacc_adapter import (
-                        WeixinOfficialAccountPlatformAdapter,  # noqa: F401
+                        WeixinOfficialAccountPlatformAdapter,  # noqa
                     )
                 case "discord":
                     from .sources.discord.discord_platform_adapter import (
                         DiscordPlatformAdapter,  # noqa: F401
                     )
-                case "misskey":
-                    from .sources.misskey.misskey_adapter import (
-                        MisskeyPlatformAdapter,  # noqa: F401
-                    )
                 case "slack":
                     from .sources.slack.slack_adapter import SlackAdapter  # noqa: F401
-                case "satori":
-                    from .sources.satori.satori_adapter import (
-                        SatoriPlatformAdapter,  # noqa: F401
-                    )
         except (ImportError, ModuleNotFoundError) as e:
             logger.error(
                 f"加载平台适配器 {platform_config['type']} 失败，原因：{e}。请检查依赖库是否安装。提示：可以在 管理面板->控制台->安装Pip库 中安装依赖库。"
@@ -132,17 +110,6 @@ class PlatformManager:
                 )
             )
         )
-        handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnPlatformLoadedEvent
-        )
-        for handler in handlers:
-            try:
-                logger.info(
-                    f"hook(on_platform_loaded) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
-                )
-                await handler.handler()
-            except Exception:
-                logger.error(traceback.format_exc())
 
     async def _task_wrapper(self, task: asyncio.Task):
         try:

astrbot/core/platform/message_session.py

@@ -1,28 +0,0 @@
-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 .message_session import MessageSesion
+from .astr_message_event 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，即平台的类型，如 aiocqhttp, discord, slack"""
+    """平台的名称"""
     description: str
     """平台的描述"""
     id: str = None
@@ -14,5 +14,3 @@ class PlatformMetadata:
     """平台的默认配置模板"""
     adapter_display_name: str = None
     """显示在 WebUI 配置页中的平台名称，如空则是 name"""
-    logo_path: str = None
-    """平台适配器的 logo 文件路径（相对于插件目录）"""

astrbot/core/platform/register.py

@@ -13,12 +13,10 @@ def register_platform_adapter(
     desc: str,
     default_config_tmpl: dict = None,
     adapter_display_name: str = None,
-    logo_path: str = None,
 ):
     """用于注册平台适配器的带参装饰器。
 
     default_config_tmpl 指定了平台适配器的默认配置模板。用户填写好后将会作为 platform_config 传入你的 Platform 类的实现类。
-    logo_path 指定了平台适配器的 logo 文件路径，是相对于插件目录的路径。
     """
 
     def decorator(cls):
@@ -41,7 +39,6 @@ def register_platform_adapter(
             description=desc,
             default_config_tmpl=default_config_tmpl,
             adapter_display_name=adapter_display_name,
-            logo_path=logo_path,
         )
         platform_registry.append(pm)
         platform_cls_map[adapter_name] = cls

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

@@ -67,19 +67,12 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
         session_id: str,
         messages: list[dict],
     ):
-        # session_id 必须是纯数字字符串
-        session_id = int(session_id) if session_id.isdigit() else None
-
-        if is_group and isinstance(session_id, int):
-            await bot.send_group_msg(group_id=session_id, message=messages)
-        elif not is_group and isinstance(session_id, int):
-            await bot.send_private_msg(user_id=session_id, message=messages)
-        elif isinstance(event, Event):  # 最后兜底
+        if event:
             await bot.send(event=event, message=messages)
+        elif is_group:
+            await bot.send_group_msg(group_id=session_id, message=messages)
         else:
-            raise ValueError(
-                f"无法发送消息：缺少有效的数字 session_id({session_id}) 或 event({event})"
-            )
+            await bot.send_private_msg(user_id=session_id, message=messages)
 
     @classmethod
     async def send_message(
@@ -90,15 +83,7 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
         is_group: bool = False,
         session_id: str = None,
     ):
-        """发送消息至 QQ 协议端（aiocqhttp）。
-
-        Args:
-            bot (CQHttp): aiocqhttp 机器人实例
-            message_chain (MessageChain): 要发送的消息链
-            event (Event | None, optional): aiocqhttp 事件对象.
-            is_group (bool, optional): 是否为群消息.
-            session_id (str | None, optional): 会话 ID（群号或 QQ 号
-        """
+        """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(
@@ -137,15 +122,18 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
 
     async def send(self, message: MessageChain):
         """发送消息"""
-        event = getattr(self.message_obj, "raw_message", None)
-
-        is_group = bool(self.get_group_id())
-        session_id = self.get_group_id() if is_group else self.get_sender_id()
-
+        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,  # 不强制要求一定是 Event
+            event=event,
             is_group=is_group,
             session_id=session_id,
         )