✨ feat: 初步实现可视化编辑 object 配置项

支持阿里云百炼应用智能体、工作流

.codecov.yml

@@ -0,0 +1,3 @@
+comment:
+    layout: "condensed_header, condensed_files, condensed_footer"
+    hide_project_coverage: TRUE

.coveragerc

@@ -0,0 +1,5 @@
+[run]
+omit =
+    */site-packages/*
+    */dist-packages/*
+    your_package_name/tests/*

.dockerignore

@@ -0,0 +1,20 @@
+# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and WebStorm
+# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
+# github acions
+.github/
+.*ignore
+.git/
+# User-specific stuff
+.idea/
+# Byte-compiled / optimized / DLL files
+__pycache__/
+# Environments
+.env
+.venv
+env/
+venv*/
+ENV/
+.conda/
+README*.md
+dashboard/
+data/

.github/ISSUE_TEMPLATE/bug-report.yml

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+name: '🐛 报告 Bug'
+title: '[Bug]'
+description: 提交报告帮助我们改进。
+labels: [ 'bug' ]
+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）。
+  - 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。
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: 如何复现？
+      description: >
+        复现该问题的步骤
+      placeholder: >
+        如: 1. 打开 '...'
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: AstrBot 版本与部署方式
+      description: >
+        请提供您的 AstrBot 版本和部署方式。
+      placeholder: >
+        如: 3.1.8 Docker, 3.1.7 Windows启动器
+    validations:
+      required: true
+
+  - type: dropdown
+    attributes:
+      label: 操作系统
+      description: |
+        你在哪个操作系统上遇到了这个问题？
+      multiple: false
+      options:
+        - 'Windows'
+        - 'macOS'
+        - 'Linux'
+        - 'Other'
+        - 'Not sure'
+    validations:
+      required: true
+
+  - type: textarea
+    attributes:
+      label: 额外信息
+      description: >
+        任何额外信息，如报错日志、截图等。
+      placeholder: >
+        请提供完整的报错日志或截图。
+    validations:
+      required: true
+
+  - type: checkboxes
+    attributes:
+      label: 你愿意提交 PR 吗？
+      description: >
+        这绝对不是必需的，但我们很乐意在贡献过程中为您提供指导特别是如果你已经很好地理解了如何实现修复。
+      options:
+        - label: 是的，我愿意提交 PR!
+
+  - type: checkboxes
+    attributes:
+      label: Code of Conduct
+      options:
+        - label: >
+            我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
+          required: true
+
+  - type: markdown
+    attributes:
+      value: "感谢您填写我们的表单！"

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -0,0 +1,42 @@
+
+name: '🎉 功能建议'
+title: "[Feature]"
+description: 提交建议帮助我们改进。
+labels: [ "enhancement" ]
+body:
+  - type: markdown
+    attributes:
+      value: |
+        感谢您抽出时间提出新功能建议，请准确解释您的想法。
+
+  - type: textarea
+    attributes:
+      label: 描述
+      description: 简短描述您的功能建议。
+
+  - type: textarea
+    attributes:
+      label: 使用场景
+      description: 你想要发生什么？
+      placeholder: >
+        一个清晰且具体的描述这个功能的使用场景。
+
+  - type: checkboxes
+    attributes:
+      label: 你愿意提交PR吗?
+      description: >
+        这不是必须的，但我们欢迎您的贡献。
+      options:
+        - label: 是的, 我愿意提交PR!
+
+  - type: checkboxes
+    attributes:
+      label: Code of Conduct
+      options:
+        - label: >
+            我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
+          required: true
+
+  - type: markdown
+    attributes:
+      value: "感谢您填写我们的表单！"

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,10 @@
+<!-- 如果有的话，指定这个 PR 要解决的 ISSUE -->
+修复了 #XYZ
+
+### Motivation
+
+<!--解释为什么要改动-->
+
+### Modifications
+
+<!--简单解释你的改动-->

.github/workflows/auto_release.yml

@@ -0,0 +1,35 @@
+on:
+  push:
+    tags:
+      - 'v*'
+  workflow_dispatch:
+
+name: Auto Release
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Dashboard Build
+        run: |
+          cd dashboard
+          npm install
+          npm run build
+          echo "COMMIT_SHA=$(git rev-parse HEAD)" >> $GITHUB_ENV
+          echo ${{ github.ref_name }} > dist/assets/version
+          zip -r dist.zip dist
+
+      - name: Fetch Changelog
+        run: |
+          echo "changelog=changelogs/${{github.ref_name}}.md" >> "$GITHUB_ENV"
+
+      - name: Create Release
+        uses: ncipollo/release-action@v1
+        with:
+          bodyFile: ${{ env.changelog }}
+          artifacts: "dashboard/dist.zip"

.github/workflows/codeql.yml

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+# For most projects, this workflow file will not need changing; you simply need
+# to commit it to your repository.
+#
+# You may wish to alter this file to override the set of languages analyzed,
+# or to provide custom queries or build logic.
+#
+# ******** NOTE ********
+# We have attempted to detect the languages in your repository. Please check
+# the `language` matrix defined below to confirm you have the correct set of
+# supported CodeQL languages.
+#
+name: "CodeQL"
+
+on:
+  push:
+    branches: [ "master" ]
+  pull_request:
+    branches: [ "master" ]
+  schedule:
+    - cron: '21 15 * * 5'
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    # Runner size impacts CodeQL analysis time. To learn more, please see:
+    #   - https://gh.io/recommended-hardware-resources-for-running-codeql
+    #   - https://gh.io/supported-runners-and-hardware-resources
+    #   - https://gh.io/using-larger-runners (GitHub.com only)
+    # Consider using larger runners or machines with greater resources for possible analysis time improvements.
+    runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
+    timeout-minutes: ${{ (matrix.language == 'swift' && 120) || 360 }}
+    permissions:
+      # required for all workflows
+      security-events: write
+
+      # required to fetch internal or private CodeQL packs
+      packages: read
+
+      # only required for workflows in private repositories
+      actions: read
+      contents: read
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+        - language: python
+          build-mode: none
+        # CodeQL supports the following values keywords for 'language': 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'swift'
+        # Use `c-cpp` to analyze code written in C, C++ or both
+        # Use 'java-kotlin' to analyze code written in Java, Kotlin or both
+        # Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
+        # To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
+        # see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
+        # If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
+        # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+
+    # Initializes the CodeQL tools for scanning.
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@v3
+      with:
+        languages: ${{ matrix.language }}
+        build-mode: ${{ matrix.build-mode }}
+        # If you wish to specify custom queries, you can do so here or in a config file.
+        # By default, queries listed here will override any specified in a config file.
+        # Prefix the list here with "+" to use these queries and those in the config file.
+
+        # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
+        # queries: security-extended,security-and-quality
+
+    # If the analyze step fails for one of the languages you are analyzing with
+    # "We were unable to automatically build your code", modify the matrix above
+    # to set the build mode to "manual" for that language. Then modify this step
+    # to build your code.
+    # ℹ️ Command-line programs to run using the OS shell.
+    # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
+    - if: matrix.build-mode == 'manual'
+      shell: bash
+      run: |
+        echo 'If you are using a "manual" build mode for one or more of the' \
+          'languages you are analyzing, replace this with the commands to build' \
+          'your code, for example:'
+        echo '  make bootstrap'
+        echo '  make release'
+        exit 1
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@v3
+      with:
+        category: "/language:${{matrix.language}}"

.github/workflows/coverage_test.yml

@@ -0,0 +1,45 @@
+name: Run tests and upload coverage
+
+on: 
+  push:
+    branches:
+      - master
+    paths-ignore:
+      - 'README.md'
+      - 'changelogs/**'
+      - 'dashboard/**'
+  workflow_dispatch:
+
+jobs:
+  test:
+    name: Run tests and collect coverage
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+      
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+          pip install pytest pytest-cov pytest-asyncio
+
+      - name: Run tests
+        run: |
+          mkdir data
+          mkdir data/plugins
+          mkdir data/config
+          mkdir data/temp
+          export TESTING=true
+          export ZHIPU_API_KEY=${{ secrets.OPENAI_API_KEY }}
+          PYTHONPATH=./ pytest --cov=. tests/ -v -o log_cli=true -o log_level=DEBUG
+
+      - name: Upload results to Codecov
+        uses: codecov/codecov-action@v4
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/docker-image.yml

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+name: Docker Image CI/CD
+
+on:
+  push:
+    tags:
+      - 'v*'
+  workflow_dispatch:
+
+jobs:
+  publish-docker:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: 拉取源码
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 1
+
+      - name: 设置 QEMU
+        uses: docker/setup-qemu-action@v3
+
+      - name: 设置 Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: 登录到 DockerHub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_HUB_USERNAME }}
+          password: ${{ secrets.DOCKER_HUB_PASSWORD }}
+
+      - name: 构建和推送 Docker hub
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: |
+            ${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:latest
+            ${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:${{ github.ref_name }}
+
+      - name: Post build notifications
+        run: echo "Docker image has been built and pushed successfully"
+

.github/workflows/stale.yml

@@ -0,0 +1,27 @@
+# This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
+#
+# You can adjust the behavior by modifying this file.
+# For more information, see:
+# https://github.com/actions/stale
+name: Mark stale issues and pull requests
+
+on:
+  schedule:
+  - cron: '21 23 * * *'
+
+jobs:
+  stale:
+
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+
+    steps:
+    - uses: actions/stale@v5
+      with:
+        repo-token: ${{ secrets.GITHUB_TOKEN }}
+        stale-issue-message: 'Stale issue message'
+        stale-pr-message: 'Stale pull request message'
+        stale-issue-label: 'no-issue-activity'
+        stale-pr-label: 'no-pr-activity'

.gitignore

@@ -1,3 +1,28 @@
 __pycache__
 botpy.log
 .vscode
+data_v2.db
+data_v3.db
+configs/session
+configs/config.yaml
+**/.DS_Store
+temp
+cmd_config.json
+data
+cookies.json
+logs/
+addons/plugins
+.coverage
+
+
+tests/astrbot_plugin_openai
+chroma
+node_modules/
+.DS_Store
+package-lock.json
+package.json
+venv/*
+packages/python_interpreter/workplace
+.venv/*
+
+.conda/

Dockerfile

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+FROM python:3.10-slim
+WORKDIR /AstrBot
+
+COPY . /AstrBot/
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    gcc \
+    build-essential \
+    python3-dev \
+    libffi-dev \
+    libssl-dev \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN python -m pip install -r requirements.txt --no-cache-dir
+
+RUN python -m pip install socksio wechatpy cryptography --no-cache-dir
+
+EXPOSE 6185 
+EXPOSE 6186
+
+CMD [ "python", "main.py" ]

README.md

@@ -1,318 +1,169 @@
+<p align="center">
+    
+![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
+
+</p>
+
 <div align="center">
 
-<img src="https://socialify.git.ci/Soulter/QQChannelChatGPT/image?description=1&forks=1&issues=1&language=1&name=1&owner=1&pattern=Circuit%20Board&stargazers=1&theme=Light" alt="QQChannelChatGPT" width="600" height="300" />
+_✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 
-<!-- [![Language](https://img.shields.io/badge/language-python-green.svg?style=plastic)](https://www.python.org/)
-[![License](https://img.shields.io/badge/license-AGPL3-orange.svg?style=plastic)](https://github.com/Soulter/QQChannelChatGPT/blob/master/LICENSE)
-![Python](https://img.shields.io/badge/python-3.9+-blue) -->
- 
-基于go-cq和官方QQ频道SDK的机器人项目。支持ChatGPT、NewBing等大模型。一次部署，同时使用
+<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>
 
-部署文档：https://github.com/Soulter/QQChannelChatGPT/wiki
- 
-插件文档：https://github.com/Soulter/QQChannelChatGPT/wiki/%E5%9B%9B%E3%80%81%E5%BC%80%E5%8F%91%E6%8F%92%E4%BB%B6
+[![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/Soulter/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/Soulter/AstrBot)
 
-欢迎体验 | **QQ群号：322154837**
+<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>
 
-<!-- <img src="https://user-images.githubusercontent.com/37870767/230417115-9dd3c9d5-6b6b-4928-8fe3-82f559208aab.JPG" width="300"></img> -->
+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。
+
+## ✨ 主要功能
+
+1. **大语言模型对话**。支持各种大语言模型，包括 OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM 等，支持接入本地部署的大模型，通过 Ollama、LLMTuner。具有多轮对话、人格情境、多模态能力，支持图片理解、语音转文字（Whisper）。
+2. **多消息平台接入**。支持接入 QQ（OneBot）、QQ 频道、微信（Gewechat）、飞书、Telegram。后续将支持钉钉、Discord、WhatsApp、小爱音响。支持速率限制、白名单、关键词过滤、百度内容审核。
+3. **Agent**。原生支持部分 Agent 能力，如代码执行器、自然语言待办、网页搜索。对接 [Dify 平台](https://astrbot.app/others/dify.html)，便捷接入 Dify 智能助手、知识库和 Dify 工作流。
+4. **插件扩展**。深度优化的插件机制，支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能，极简开发。已支持安装多个插件。
+5. **可视化管理面板**。支持可视化修改配置、插件管理、日志查看等功能，降低配置难度。集成 WebChat，可在面板上与大模型对话。
+6. **高稳定性、高模块化**。基于事件总线和流水线的架构设计，高度模块化，低耦合。
+
+> [!TIP]
+> 管理面板在线体验 Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)
+> 
+> 用户名: `astrbot`, 密码: `astrbot`。未配置 LLM，无法在聊天页使用大模型。（不要再修改 demo 的登录密码了 😭）
+
+## ✨ 使用方式
+
+#### Docker 部署
+
+请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
+
+#### Windows 一键安装器部署
+
+需要电脑上安装有 Python（>3.10）。请参阅官方文档 [使用 Windows 一键安装器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html) 。
+
+#### Replit 部署
+
+[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
+
+#### CasaOS 部署
+
+社区贡献的部署方式。
+
+请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/casaos.html) 。
+
+#### 手动部署
+
+请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
+
+
+## ⚡ 消息平台支持情况
+
+| 平台    | 支持性 | 详情 | 消息类型 |
+| -------- | ------- | ------- | ------ |
+| QQ(官方机器人接口) | ✔    | 私聊、群聊，QQ 频道私聊、群聊 | 文字、图片 |
+| QQ(OneBot)      | ✔    | 私聊、群聊 | 文字、图片、语音 |
+| 微信(个人号)    | ✔    | 微信个人号私聊、群聊 | 文字、图片、语音 |
+| [Telegram](https://github.com/Soulter/astrbot_plugin_telegram)   | ✔    | 私聊、群聊 | 文字、图片 |
+| [微信(企业微信)](https://github.com/Soulter/astrbot_plugin_wecom)    | ✔    | 私聊 | 文字、图片、语音 |
+| 飞书   | ✔    | 群聊 | 文字、图片 |
+| 微信对话开放平台 | 🚧    | 计划内 | - |
+| Discord   | 🚧    | 计划内 | - |
+| WhatsApp   | 🚧    | 计划内 | - |
+| 小爱音响   | 🚧    | 计划内 | - |
+
+# 🦌 接下来的路线图
+
+> [!TIP]
+> 欢迎在 Issue 提出更多建议 <3
+
+- [ ] 完善并保证目前所有平台适配器的功能一致性
+- [ ] 优化插件接口
+- [ ] 默认支持更多 TTS 服务，如 GPT-Sovits
+- [ ] 完善“聊天增强”部分，支持持久化记忆
+- [ ] 规划 i18n
+
+
+## ❤️ 贡献
+
+欢迎任何 Issues/Pull Requests！只需要将你的更改提交到此项目 ：)
+
+对于新功能的添加，请先通过 Issue 讨论。
+
+## 🌟 支持
+
+- Star 这个项目！
+- 在[爱发电](https://afdian.com/a/soulter)支持我！
+- 在[微信](https://drive.soulter.top/f/pYfA/d903f4fa49a496fda3f16d2be9e023b5.png)支持我~
+
+## ✨ Demo
+
+> [!NOTE]
+> 代码执行器的文件输入/输出目前仅测试了 Napcat(QQ), Lagrange(QQ)
+
+<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 测试中）✨_
+
+<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/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
+
+_✨ 自然语言待办事项 ✨_
+
+<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/592a8630-14c7-4e06-b496-9c0386e4f36c" width=600>
+
+_✨ 管理面板 ✨_
+
+![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
+
+_✨ 内置 Web Chat，在线与机器人交互 ✨_
 
 </div>
 
-## 🧩功能：
+## ⭐ Star History
 
-近期新功能：
-- Markdown渲染支持：回复消息支持图片。
-- 支持插件。https://github.com/Soulter/QQChannelChatGPT/wiki/%E5%9B%9B%E3%80%81%E5%BC%80%E5%8F%91%E6%8F%92%E4%BB%B6
-- 热更新
-- 接入QQ，支持在QQ上和QQ频道上同时聊天！https://github.com/Soulter/QQChannelChatGPT/issues/82
-- Windows启动器。链接：https://github.com/Soulter/QQChatGPTLauncher/releases/latest
+> [!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，这是我维护这个开源项目的动力 <3
 
-支持的AI语言模型（请在`configs/config.yaml`下配置）：
-- 逆向ChatGPT
-- 官方ChatGPT API
-- Bing
-- ...
-<!-- 
-### 基本功能
-<details> 
- <summary>✅ 回复符合上下文</summary>
-
-   -  程序向API发送近多次对话内容，模型根据上下文生成回复
-
-   -  你可在`configs/config.yaml`中修改`total_token_limit`来近似控制缓存大小。
- </details> 
-
-<details> 
- <summary>✅ 超额自动切换</summary>
-
-   -  超额时，程序自动切换openai的key，方便快捷
-   
-</details>
-
-<details> 
-
- <summary>✅ 支持统计频道、消息数量等信息</summary> 
-
-   -  实现了简单的统计功能
-
- </details>
-
-<details> 
- <summary>✅ 多并发处理，回复速度快</summary> 
-  
-   -  使用了协程，理论最高可以支持每个子频道每秒回复5条信息
-  
- </details>
-
-<details>
- <summary>✅ 持久化转储历史记录，重启不丢失</summary> 
-
-   -  使用内置的sqlite数据库存储历史记录到本地
-
-   -  方式为定时转储，可在`config.yaml`下修改`dump_history_interval`来修改间隔时间，单位为分钟。
-  
- </details>
-
-<details> 
- <summary>✅ 支持多种指令控制</summary> 
-  
-   -  详见下方`指令功能`
-  
- </details>
-
-<details>
-<summary>✅ 官方API，稳定</summary>
-
-   -  不使用ChatGPT逆向接口，而使用官方API接口，稳定方便。
-
-   -  QQ频道机器人框架为QQ官方开源的框架，稳定。
-
-</details> -->
-
-<!-- > 关于token：token就相当于是AI中的单词数（但是不等于单词数），`text-davinci-003`模型中最大可以支持`4097`个token。在发送信息时，这个机器人会将用户的历史聊天记录打包发送给ChatGPT，因此，`token`也会相应的累加，为了保证聊天的上下文的逻辑性，就有了缓存token。 -->
-
-### 🛠️ 插件支持
-
-本项目支持接入插件。
-
-> 使用`plugin i 插件GitHub链接`即可安装。
-
-插件开发教程：https://github.com/Soulter/QQChannelChatGPT/wiki/%E5%9B%9B%E3%80%81%E5%BC%80%E5%8F%91%E6%8F%92%E4%BB%B6
-
-部分好用的插件：
-
-- `HuggingChat`: https://github.com/Soulter/HuggingChatForQQBot | HuggingChat模型接入
-
-- `GoodPlugins`: https://github.com/Soulter/goodplugins | 随机动漫图片、搜番、喜报生成器等等
-
-- `sysstat`: https://github.com/Soulter/sysstatqcbot | 查看系统状态
-
-- `BiliMonitor`: https://github.com/Soulter/BiliMonitor | 订阅B站动态！
-
-<!-- 
-### 指令
-
-#### OpenAI官方API
-在频道内需要先`@`机器人之后再输入指令；在QQ中暂时需要在消息前加上`ai `，不需要@
-- `/reset`重置prompt
-- `/his`查看历史记录（每个用户都有独立的会话）
-- `/his [页码数]`查看不同页码的历史记录。例如`/his 2`查看第2页
-- `/token`查看当前缓存的总token数
-- `/count` 查看统计
-- `/status` 查看chatGPT的配置
-- `/help` 查看帮助
-- `/key` 动态添加key
-- `/set` 人格设置面板
-- `/keyword nihao 你好` 设置关键词回复。nihao->你好
-- `/bing` 切换为bing
-- `/revgpt` 切换为ChatGPT逆向库
-- `/画` 画画
-
-#### Bing语言模型
-- `/reset`重置prompt
-- `/gpt` 切换为OpenAI官方API
-- `/revgpt` 切换为ChatGPT逆向库
-
-#### 逆向ChatGPT库语言模型
-- `/gpt` 切换为OpenAI官方API
-- `/bing` 切换为bing
-
-* 切换模型指令支持临时回复。如`/bing 你好`将会临时使用一次bing模型 -->
-
-## 📰使用方法：
-
-使用文档：https://github.com/Soulter/QQChannelChatGPT/wiki
-
-**Windows用户可以使用启动器一键安装，请前往Release下载最新版本（Beta）**
-<!-- 
-### 安装第三方库
-
-```shell
-pip install -r requirements.txt
-```
-> ⚠Python版本应>=3.9
-
-### 配置
-
-**详细部署教程链接：**https://github.com/Soulter/QQChannelChatGPT/wiki
-
-### 启动
-- 启动main.py -->
-
-## 🙇‍感谢
-本项目使用了一下项目:
-
-[ChatGPT by acheong08](https://github.com/acheong08/ChatGPT)
-
-[EdgeGPT by acheong08](https://github.com/acheong08/EdgeGPT)
-
-[go-cqhttp by Mrs4s](https://github.com/Mrs4s/go-cqhttp)
-
-[nakuru-project by Lxns-Network](https://github.com/Lxns-Network/nakuru-project)
-
-<!-- ## 👀部分演示截图
-
-帮助中心（`help`指令）
-![)F%2VQA`O)`4BHTXZ653(~9](https://github.com/Soulter/QQChannelChatGPT/assets/37870767/57eaa8c6-6962-4940-823c-2e26b5206cf5)
-
- -->
-## ⚙配置文件说明：
-```yaml
-# 如果你不知道怎么部署，请查看https://github.com/Soulter/QQChannelChatGPT/wiki
-# 不一定需要key了，如果你没有key但有openAI账号或者必应账号，可以考虑使用下面的逆向库
-
-
-###############平台设置#################
-
-# QQ频道机器人
-# QQ开放平台的appid和令牌
-# q.qq.com
-# enable为true则启用，false则不启用
-qqbot:
-  enable: true
-  appid: 
-  token: 
-
-# QQ机器人
-# enable为true则启用，false则不启用
-# 需要安装GO-CQHTTP配合使用。
-# 文档：https://docs.go-cqhttp.org/
-# 请将go-cqhttp的配置文件的sever部分粘贴为以下内容，否则无法使用
-# 请先启动go-cqhttp再启动本程序
-# 
-# servers:
-#   - http:
-#       host: 127.0.0.1
-#       version: 0
-#       port: 5700
-#       timeout: 5
-#   - ws:
-#       address: 127.0.0.1:6700
-#       middlewares:
-#         <<: *default
-gocqbot:
-  enable: false
-
-# 设置是否一个人一个会话
-uniqueSessionMode: false
-# QChannelBot 的版本，请勿修改此字段，否则可能产生一些bug
-version: 3.0
-# [Beta] 转储历史记录时间间隔(分钟)
-dump_history_interval: 10
-# 一个用户只能在time秒内发送count条消息
-limit:
-  time: 60
-  count: 5
-# 公告
-notice: "此机器人由Github项目QQChannelChatGPT驱动。"
-# 是否打开私信功能
-# 设置为true则频道成员可以私聊机器人。
-# 设置为false则频道成员不能私聊机器人。
-direct_message_mode: true
-
-# 系统代理
-# http_proxy: http://localhost:7890
-# https_proxy: http://localhost:7890
-
-# 自定义回复前缀，如[Rev]或其他，务必加引号以防止不必要的bug。
-reply_prefix:
-  openai_official: "[GPT]"
-  rev_chatgpt: "[Rev]"
-  rev_edgegpt: "[RevBing]"
-
-# 百度内容审核服务
-# 新用户免费5万次调用。https://cloud.baidu.com/doc/ANTIPORN/index.html
-baidu_aip:
-  enable: false
-  app_id: 
-  api_key: 
-  secret_key: 
-
-
-
-
-###############语言模型设置#################
-
-
-# OpenAI官方API
-# 注意：已支持多key自动切换，方法：
-# key:
-#   - sk-xxxxxx
-#   - sk-xxxxxx
-# 在下方非注释的地方使用以上格式
-# 关于api_base：可以使用一些云函数（如腾讯、阿里）来避免国内被墙的问题。
-# 详见：
-# https://github.com/Ice-Hazymoon/openai-scf-proxy
-# https://github.com/Soulter/QQChannelChatGPT/issues/42
-# 设置为none则表示使用官方默认api地址
-openai:
-  key: 
-    - 
-  api_base: none
-  # 这里是GPT配置，语言模型默认使用gpt-3.5-turbo
-  chatGPTConfigs:
-    model: gpt-3.5-turbo
-    max_tokens: 3000
-    temperature: 0.9
-    top_p: 1
-    frequency_penalty: 0
-    presence_penalty: 0
+<div align="center">
     
-  total_tokens_limit: 5000
+[![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
 
-# 逆向文心一言【暂时不可用，请勿使用】
-rev_ernie:
-  enable: false
+</div>
 
-# 逆向New Bing
-# 需要在项目根目录下创建cookies.json并粘贴cookies进去。
-# 详见：https://soulter.top/posts/qpdg.html
-rev_edgegpt:
-  enable: false
+## Disclaimer
+
+1. The project is protected under the `AGPL-v3` opensource license.
+2. The deployment of WeChat (personal account) utilizes [Gewechat](https://github.com/Devo919/Gewechat) service. AstrBot only guarantees connectivity with Gewechat and recommends using a WeChat account that is not frequently used. In the event of account risk control, the author of this project shall not bear any responsibility.
+3. Please ensure compliance with local laws and regulations when using this project.
+
+<!-- ## ✨ ATRI [Beta 测试]
+
+该功能作为插件载入。插件仓库地址：[astrbot_plugin_atri](https://github.com/Soulter/astrbot_plugin_atri)
+
+1. 基于《ATRI ~ My Dear Moments》主角 ATRI 角色台词作为微调数据集的 `Qwen1.5-7B-Chat Lora` 微调模型。
+2. 长期记忆
+3. 表情包理解与回复
+4. TTS
+    -->
+
+
+_私は、高性能ですから!_
 
-# 逆向ChatGPT库
-# https://github.com/acheong08/ChatGPT
-# 优点：免费（无免费额度限制）；
-# 缺点：速度相对慢。OpenAI 速率限制：免费帐户每小时 50 个请求。您可以通过多帐户循环来绕过它
-# enable设置为true后，将会停止使用上面正常的官方API调用而使用本逆向项目
-#
-# 多账户可以保证每个请求都能得到及时的回复。
-# 关于account的格式
-# account:
-#   - email: 第1个账户
-#     password: 第1个账户密码
-#   - email: 第2个账户
-#     password: 第2个账户密码
-#   - ....
-# 支持使用access_token登录
-# 例：
-# - session_token: xxxxx
-# - access_token: xxxx
-# 请严格按照上面这个格式填写。
-# 逆向ChatGPT库的email-password登录方式不工作，建议使用access_token登录
-# 获取access_token的方法，详见：https://soulter.top/posts/qpdg.html
-rev_ChatGPT:
-  enable: false
-  account:
-    - access_token: 
-```

README_ja.md

@@ -0,0 +1,170 @@
+<p align="center">
+    
+![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
+
+</p>
+
+<div align="center">
+
+_✨ 簡単に使えるマルチプラットフォーム LLM チャットボットおよび開発フレームワーク ✨_
+
+<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/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/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/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。
+
+## ✨ 主な機能
+
+1. **大規模言語モデルの対話**。OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM など、さまざまな大規模言語モデルをサポートし、Ollama、LLMTuner を介してローカルにデプロイされた大規模モデルをサポートします。多輪対話、人格シナリオ、多モーダル機能を備え、画像理解、音声からテキストへの変換（Whisper）をサポートします。
+2. **複数のメッセージプラットフォームの接続**。QQ（OneBot）、QQ チャンネル、WeChat（Gewechat）、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
+3. **エージェント**。一部のエージェント機能をネイティブにサポートし、コードエグゼキューター、自然言語タスク、ウェブ検索などを提供します。[Dify プラットフォーム](https://astrbot.app/others/dify.html)と連携し、Dify スマートアシスタント、ナレッジベース、Dify ワークフローを簡単に接続できます。
+4. **プラグインの拡張**。深く最適化されたプラグインメカニズムを備え、[プラグインの開発](https://astrbot.app/dev/plugin.html)をサポートし、機能を拡張できます。複数のプラグインのインストールをサポートします。
+5. **ビジュアル管理パネル**。設定の視覚的な変更、プラグイン管理、ログの表示などをサポートし、設定の難易度を低減します。WebChat を統合し、パネル上で大規模モデルと対話できます。
+6. **高い安定性と高いモジュール性**。イベントバスとパイプラインに基づくアーキテクチャ設計により、高度にモジュール化され、低結合です。
+
+> [!TIP]
+> 管理パネルのオンラインデモを体験する: [https://demo.astrbot.app/](https://demo.astrbot.app/)
+> 
+> ユーザー名: `astrbot`, パスワード: `astrbot`。LLM が設定されていないため、チャットページで大規模モデルを使用することはできません。（デモのログインパスワードを変更しないでください 😭）
+
+## ✨ 使用方法
+
+#### Docker デプロイ
+
+公式ドキュメント [Docker を使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) を参照してください。
+
+#### Windows ワンクリックインストーラーのデプロイ
+
+コンピュータに Python（>3.10）がインストールされている必要があります。公式ドキュメント [Windows ワンクリックインストーラーを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/windows.html) を参照してください。
+
+#### Replit デプロイ
+
+[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
+
+#### CasaOS デプロイ
+
+コミュニティが提供するデプロイ方法です。
+
+公式ドキュメント [ソースコードを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/casaos.html) を参照してください。
+
+#### 手動デプロイ
+
+公式ドキュメント [ソースコードを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/cli.html) を参照してください。
+
+## ⚡ メッセージプラットフォームのサポート状況
+
+| プラットフォーム    | サポート状況 | 詳細 | メッセージタイプ |
+| -------- | ------- | ------- | ------ |
+| QQ(公式ロボットインターフェース) | ✔    | プライベートチャット、グループチャット、QQ チャンネルプライベートチャット、グループチャット | テキスト、画像 |
+| QQ(OneBot)      | ✔    | プライベートチャット、グループチャット | テキスト、画像、音声 |
+| WeChat(個人アカウント)    | ✔    | WeChat 個人アカウントのプライベートチャット、グループチャット | テキスト、画像、音声 |
+| [Telegram](https://github.com/Soulter/astrbot_plugin_telegram)   | ✔    | プライベートチャット、グループチャット | テキスト、画像 |
+| [WeChat(企業 WeChat)](https://github.com/Soulter/astrbot_plugin_wecom)    | ✔    | プライベートチャット | テキスト、画像、音声 |
+| Feishu   | ✔    | グループチャット | テキスト、画像 |
+| WeChat 対話オープンプラットフォーム | 🚧    | 計画中 | - |
+| Discord   | 🚧    | 計画中 | - |
+| WhatsApp   | 🚧    | 計画中 | - |
+| Xiaoai 音響   | 🚧    | 計画中 | - |
+
+# 🦌 今後のロードマップ
+
+> [!TIP]
+> Issue でさらに多くの提案を歓迎します <3
+
+- [ ] 現在のすべてのプラットフォームアダプターの機能の一貫性を確保し、改善する
+- [ ] プラグインインターフェースの最適化
+- [ ] GPT-Sovits などの TTS サービスをデフォルトでサポート
+- [ ] "チャット強化" 部分を完成させ、永続的な記憶をサポート
+- [ ] i18n の計画
+
+## ❤️ 貢献
+
+Issue や Pull Request を歓迎します！このプロジェクトに変更を加えるだけです :)
+
+新機能の追加については、まず Issue で議論してください。
+
+## 🌟 サポート
+
+- このプロジェクトに Star を付けてください！
+- [愛発電](https://afdian.com/a/soulter)で私をサポートしてください！
+- [WeChat](https://drive.soulter.top/f/pYfA/d903f4fa49a496fda3f16d2be9e023b5.png)で私をサポートしてください~
+
+## ✨ デモ
+
+> [!NOTE]
+> コードエグゼキューターのファイル入力/出力は現在 Napcat(QQ)、Lagrange(QQ) でのみテストされています
+
+<div align='center'>
+
+<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
+
+_✨ Docker ベースのサンドボックス化されたコードエグゼキューター（ベータテスト中）✨_
+
+<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
+
+_✨ 多モーダル、ウェブ検索、長文の画像変換（設定可能）✨_
+
+<img src="https://github.com/user-attachments/assets/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
+
+_✨ 自然言語タスク ✨_
+
+<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>
+
+_✨ プラグインシステム - 一部のプラグインの展示 ✨_
+
+<img src="https://github.com/user-attachments/assets/592a8630-14c7-4e06-b496-9c0386e4f36c" width="600">
+
+_✨ 管理パネル ✨_
+
+![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
+
+_✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
+
+</div>
+
+## ⭐ Star History
+
+> [!TIP] 
+> このプロジェクトがあなたの生活や仕事に役立った場合、またはこのプロジェクトの将来の発展に関心がある場合は、プロジェクトに Star を付けてください。これはこのオープンソースプロジェクトを維持するためのモチベーションです <3
+
+<div align="center">
+    
+[![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
+
+</div>
+
+## スポンサー
+
+[<img src="https://api.gitsponsors.com/api/badge/img?id=575865240" height="20">](https://api.gitsponsors.com/api/badge/link?p=XEpbdGxlitw/RbcwiTX93UMzNK/jgDYC8NiSzamIPMoKvG2lBFmyXhSS/b0hFoWlBBMX2L5X5CxTDsUdyvcIEHTOfnkXz47UNOZvMwyt5CzbYpq0SEzsSV1OJF1cCo90qC/ZyYKYOWedal3MhZ3ikw==)
+
+## 免責事項
+
+1. このプロジェクトは `AGPL-v3` オープンソースライセンスの下で保護されています。
+2. WeChat（個人アカウント）のデプロイメントには [Gewechat](https://github.com/Devo919/Gewechat) サービスを利用しています。AstrBot は Gewechat との接続を保証するだけであり、アカウントのリスク管理に関しては、このプロジェクトの著者は一切の責任を負いません。
+3. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
+
+<!-- ## ✨ ATRI [ベータテスト]
+
+この機能はプラグインとしてロードされます。プラグインリポジトリのアドレス：[astrbot_plugin_atri](https://github.com/Soulter/astrbot_plugin_atri)
+
+1. 《ATRI ~ My Dear Moments》の主人公 ATRI のキャラクターセリフを微調整データセットとして使用した `Qwen1.5-7B-Chat Lora` 微調整モデル。
+2. 長期記憶
+3. ミームの理解と返信
+4. TTS
+    -->
+
+
+_私は、高性能ですから!_
+

addons/baidu_aip_judge.py

@@ -1,26 +0,0 @@
-from aip import AipContentCensor
-
-class BaiduJudge:
-    def __init__(self, baidu_configs) -> None:
-        if 'app_id' in baidu_configs and 'api_key' in baidu_configs and 'secret_key' in baidu_configs:
-            self.app_id = str(baidu_configs['app_id'])
-            self.api_key = baidu_configs['api_key']
-            self.secret_key = baidu_configs['secret_key']
-            self.client = AipContentCensor(self.app_id, self.api_key, self.secret_key)
-        else:
-            raise ValueError("Baidu configs error! 请填写百度内容审核服务相关配置！")
-    def judge(self, text):
-        res = self.client.textCensorUserDefined(text)
-        if 'conclusionType' not in res:
-            return False, "百度审核服务未知错误"
-        if res['conclusionType'] == 1:
-            return True, "合规"
-        else:
-            if 'data' not in res:
-                return False, "百度审核服务未知错误"
-            count = len(res['data'])
-            info = f"百度审核服务发现 {count} 处违规：\n"
-            for i in res['data']:
-                info += f"{i['msg']}；\n"
-            info += "\n判断结果："+res['conclusion']
-            return False, info

addons/plugins/helloworld/README.md

@@ -1,5 +0,0 @@
-# helloworld
-
-QQChannelChatGPT项目的测试插件
-
-A test plugin for QQChannelChatGPT plugin feature

addons/plugins/helloworld/helloworld.py

@@ -1,79 +0,0 @@
-from nakuru.entities.components import *
-from nakuru import (
-    GroupMessage,
-    FriendMessage
-)
-from botpy.message import Message, DirectMessage
-from model.platform.qq import QQ
-import time
-import threading
-
-class HelloWorldPlugin:
-    """
-    初始化函数, 可以选择直接pass
-    """
-    def __init__(self) -> None:
-        self.myThread = None # 线程对象，如果要使用线程，需要在此处定义。在run处定义会被释放掉
-        print("这是HelloWorld测试插件, 发送 helloworld 即可触发此插件。")
-
-    """
-    入口函数，机器人会调用此函数。
-    参数规范: message: 消息文本; role: 身份; platform: 消息平台; message_obj: 消息对象; qq_platform: QQ平台对象，可以通过调用qq_platform.send()直接发送消息。详见Helloworld插件示例
-    参数详情: role为admin或者member; platform为qqchan或者gocq; message_obj为nakuru的GroupMessage对象或者FriendMessage对象或者频道的Message, DirectMessage对象。
-    返回规范: bool: 是否hit到此插件(所有的消息均会调用每一个载入的插件, 如果没有hit到, 则应返回False)
-             Tuple: None或者长度为3的元组。当没有hit到时, 返回None. hit到时, 第1个参数为指令是否调用成功, 第2个参数为返回的消息文本或者gocq的消息链列表, 第3个参数为指令名称
-    例子：做一个名为"yuanshen"的插件；当接收到消息为“原神 可莉”, 如果不想要处理此消息，则返回False, None；如果想要处理，但是执行失败了，返回True, tuple([False, "请求失败啦~", "yuanshen"])
-          ；执行成功了，返回True, tuple([True, "结果文本", "yuanshen"])
-    """
-    def run(self, message: str, role: str, platform: str, message_obj, qq_platform: QQ):
-
-        if platform == "gocq":
-            """
-            QQ平台指令处理逻辑
-            """
-            img_url = "https://gchat.qpic.cn/gchatpic_new/905617992/720871955-2246763964-C6EE1A52CC668EC982453065C4FA8747/0?term=2&is_origin=0"
-            if message == "helloworld":
-                return True, tuple([True, [Plain("Hello World!!"), Image.fromURL(url=img_url)], "helloworld"])
-            elif message == "hiloop":
-                if self.myThread is None:
-                    self.myThread = threading.Thread(target=self.helloworldThread, args=(message_obj, qq_platform))
-                    self.myThread.start()
-                return True, tuple([True, [Plain("A lot of Helloworlds!!"), Image.fromURL(url=img_url)], "helloworld"]) 
-            else:
-                return False, None
-        elif platform == "qqchan":
-            """
-            频道处理逻辑(频道暂时只支持回复字符串类型的信息，返回的信息都会被转成字符串，如果不想处理某一个平台的信息，直接返回False, None就行)
-            """
-            if message == "helloworld":
-                return True, tuple([True, "Hello World!!", "helloworld"])
-            else:
-                return False, None
-    """
-    帮助函数，当用户输入 plugin v 插件名称 时，会调用此函数，返回帮助信息
-    返回参数要求(必填)：dict{
-        "name": str, # 插件名称
-        "desc": str, # 插件简短描述
-        "help": str, # 插件帮助信息
-        "version": str, # 插件版本
-        "author": str, # 插件作者
-    }
-    """        
-    def info(self):
-        return {
-            "name": "helloworld",
-            "desc": "测试插件",
-            "help": "测试插件, 回复helloworld即可触发",
-            "version": "v1.0.1 beta",
-            "author": "Soulter"
-        }
-    
-    def helloworldThread(self, meseage_obj, qq_platform: QQ):
-        while True:
-            qq_platform.send(meseage_obj, [Plain("Hello World!!")]) # 第一个参数可以是message_obj, 也可以是qq群号
-            time.sleep(3) # 睡眠3秒。 用while True一定要记得sleep，不然会卡死
-        
-
-        # 热知识：检测消息开头指令，使用以下方法
-        # if message.startswith("原神"):
-        #     pass

astrbot/__init__.py

@@ -0,0 +1,2 @@
+from .core.log import LogManager
+logger = LogManager.GetLogger(log_name='astrbot')

astrbot/api/__init__.py

@@ -0,0 +1,13 @@
+from astrbot.core.config.astrbot_config import AstrBotConfig
+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
+
+__all__ = [
+    "AstrBotConfig",
+    "logger",
+    "html_renderer",
+    "llm_tool",
+    "sp"
+]

astrbot/api/all.py

@@ -0,0 +1,40 @@
+
+from astrbot.core.config.astrbot_config import AstrBotConfig
+from astrbot import logger
+from astrbot.core import html_renderer
+from astrbot.core.star.register import register_llm_tool as llm_tool
+
+# event
+from astrbot.core.message.message_event_result import (
+    MessageEventResult, MessageChain, CommandResult, EventResultType
+) 
+from astrbot.core.platform import AstrMessageEvent
+
+# star register
+from astrbot.core.star.register import (
+    register_command as command,
+    register_command_group as command_group,
+    register_event_message_type as event_message_type,
+    register_regex as regex,
+    register_platform_adapter_type as platform_adapter_type,
+)
+from astrbot.core.star.filter.event_message_type import EventMessageTypeFilter, EventMessageType
+from astrbot.core.star.filter.platform_adapter_type import PlatformAdapterTypeFilter, PlatformAdapterType
+from astrbot.core.star.register import (
+    register_star as register # 注册插件（Star）
+)
+from astrbot.core.star import Context, Star
+from astrbot.core.star.config import *
+
+
+# provider
+from astrbot.core.provider import Provider, Personality, ProviderMetaData
+
+# platform
+from astrbot.core.platform import (
+    AstrMessageEvent, Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+)
+
+from astrbot.core.platform.register import register_platform_adapter
+
+from .message_components import *

astrbot/api/event/__init__.py

@@ -0,0 +1,18 @@
+from astrbot.core.message.message_event_result import (
+    MessageEventResult,
+    MessageChain,
+    CommandResult,
+    EventResultType,
+    ResultContentType,
+)
+
+from astrbot.core.platform import AstrMessageEvent
+
+__all__ = [
+    "MessageEventResult",
+    "MessageChain",
+    "CommandResult",
+    "EventResultType",
+    "AstrMessageEvent",
+    "ResultContentType",
+]

astrbot/api/event/filter/__init__.py

@@ -0,0 +1,41 @@
+from astrbot.core.star.register import (
+    register_command as command,
+    register_command_group as command_group,
+    register_event_message_type as event_message_type,
+    register_regex as regex,
+    register_platform_adapter_type as platform_adapter_type,
+    register_permission_type as permission_type,
+    register_custom_filter as custom_filter,
+    register_on_llm_request as on_llm_request,
+    register_on_llm_response as on_llm_response,
+    register_llm_tool as llm_tool,
+    register_on_decorating_result as on_decorating_result,
+    register_after_message_sent as after_message_sent
+)
+
+from astrbot.core.star.filter.event_message_type import EventMessageTypeFilter, EventMessageType
+from astrbot.core.star.filter.platform_adapter_type import PlatformAdapterTypeFilter, PlatformAdapterType
+from astrbot.core.star.filter.permission import PermissionTypeFilter, PermissionType
+from astrbot.core.star.filter.custom_filter import CustomFilter
+
+__all__ = [
+    'command',
+    'command_group',
+    'event_message_type',
+    'regex',
+    'platform_adapter_type',
+    'permission_type',
+    'EventMessageTypeFilter',
+    'EventMessageType',
+    'PlatformAdapterTypeFilter',
+    'PlatformAdapterType',
+    'PermissionTypeFilter',
+    'CustomFilter',
+    'custom_filter',
+    'PermissionType',
+    'on_llm_request',
+    'llm_tool',
+    'on_decorating_result',
+    'after_message_sent',
+    'on_llm_response'
+]

astrbot/api/message_components.py

@@ -0,0 +1 @@
+from astrbot.core.message.components import *

astrbot/api/platform/__init__.py

@@ -0,0 +1,6 @@
+from astrbot.core.platform import (
+    AstrMessageEvent, Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+)
+
+from astrbot.core.platform.register import register_platform_adapter
+from astrbot.core.message.components import *

astrbot/api/provider/__init__.py

@@ -0,0 +1,2 @@
+from astrbot.core.provider import Provider, STTProvider, Personality
+from astrbot.core.provider.entites import ProviderRequest, ProviderType, ProviderMetaData, LLMResponse

astrbot/api/star/__init__.py

@@ -0,0 +1,6 @@
+from astrbot.core.star.register import (
+    register_star as register # 注册插件（Star）
+)
+
+from astrbot.core.star import Context, Star
+from astrbot.core.star.config import *

astrbot/core/__init__.py

@@ -0,0 +1,26 @@
+import os
+import asyncio
+from .log import LogManager, LogBroker
+from astrbot.core.utils.t2i.renderer import HtmlRenderer
+from astrbot.core.utils.shared_preferences import SharedPreferences
+from astrbot.core.utils.pip_installer import PipInstaller
+from astrbot.core.db.sqlite import SQLiteDatabase
+from astrbot.core.config.default import DB_PATH
+from astrbot.core.config import AstrBotConfig
+
+os.makedirs("data", exist_ok=True)
+
+astrbot_config = AstrBotConfig()
+t2i_base_url = astrbot_config.get('t2i_endpoint', 'https://t2i.soulter.top/text2img')
+html_renderer = HtmlRenderer(t2i_base_url)
+logger = LogManager.GetLogger(log_name='astrbot')
+
+if os.environ.get('TESTING', ""):
+    logger.setLevel('DEBUG')
+    
+db_helper = SQLiteDatabase(DB_PATH)
+sp = SharedPreferences() # 简单的偏好设置存储
+pip_installer = PipInstaller(astrbot_config.get('pip_install_arg', ''))
+web_chat_queue = asyncio.Queue(maxsize=32)
+web_chat_back_queue = asyncio.Queue(maxsize=32)
+WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"

astrbot/core/config/__init__.py

@@ -0,0 +1,2 @@
+from .default import DEFAULT_CONFIG, VERSION, DB_PATH
+from .astrbot_config import *

astrbot/core/config/astrbot_config.py

@@ -0,0 +1,127 @@
+import os
+import json
+import logging
+import enum
+from .default import DEFAULT_CONFIG, DEFAULT_VALUE_MAP
+from typing import Dict
+
+ASTRBOT_CONFIG_PATH = "data/cmd_config.json"
+logger = logging.getLogger("astrbot")
+
+class RateLimitStrategy(enum.Enum):
+    STALL = "stall"
+    DISCARD = "discard"
+
+class AstrBotConfig(dict):
+    '''从配置文件中加载的配置，支持直接通过点号操作符访问根配置项。
+    
+    - 初始化时会将传入的 default_config 与配置文件进行比对，如果配置文件中缺少配置项则会自动插入默认值并进行一次写入操作。会递归检查配置项。
+    - 如果配置文件路径对应的文件不存在，则会自动创建并写入默认配置。
+    - 如果传入了 schema，将会通过 schema 解析出 default_config，此时传入的 default_config 会被忽略。
+    '''
+    
+    def __init__(
+        self, 
+        config_path: str = ASTRBOT_CONFIG_PATH, 
+        default_config: dict = DEFAULT_CONFIG,
+        schema: dict = None
+    ):
+        super().__init__()
+        
+        # 调用父类的 __setattr__ 方法，防止保存配置时将此属性写入配置文件
+        object.__setattr__(self, 'config_path', config_path)
+        object.__setattr__(self, 'default_config', default_config)
+        object.__setattr__(self, 'schema', schema)
+        
+        if schema:
+            default_config = self._config_schema_to_default_config(schema)
+        
+        if not self.check_exist():
+            '''不存在时载入默认配置'''
+            with open(config_path, "w", encoding="utf-8-sig") as f:
+                json.dump(default_config, f, indent=4, ensure_ascii=False)
+
+        with open(config_path, "r", encoding="utf-8-sig") as f:
+            conf_str = f.read()
+            if conf_str.startswith(u'/ufeff'): # remove BOM
+                conf_str = conf_str.encode('utf8')[3:].decode('utf8')
+            conf = json.loads(conf_str)
+        
+        # 检查配置完整性，并插入
+        has_new = self.check_config_integrity(default_config, conf)
+        self.update(conf)
+        if has_new:
+            self.save_config()
+            
+        self.update(conf)
+
+    def _config_schema_to_default_config(self, schema: dict) -> dict:
+        '''将 Schema 转换成 Config'''
+        conf = {}
+        
+        def _parse_schema(schema: dict, conf: dict):
+            for k, v in schema.items():
+                if v['type'] not in DEFAULT_VALUE_MAP:
+                    raise TypeError(f"不受支持的配置类型 {v['type']}。支持的类型有：{DEFAULT_VALUE_MAP.keys()}")
+                if 'default' in v:
+                    default = v['default']
+                else:
+                    default = DEFAULT_VALUE_MAP[v['type']]
+                
+                if v['type'] == 'object':
+                    conf[k] = {}
+                    _parse_schema(v['items'], conf[k])
+                else:
+                    conf[k] = default
+                    
+        _parse_schema(schema, conf)
+
+        return conf
+
+
+    def check_config_integrity(self, refer_conf: Dict, conf: Dict, path=""):
+        '''检查配置完整性，如果有新的配置项则返回 True'''
+        has_new = False
+        for key, value in refer_conf.items():
+            if key not in conf:
+                # logger.info(f"检查到配置项 {path + "." + key if path else key} 不存在，已插入默认值 {value}")
+                path_ = path + "." + key if path else key
+                logger.info(f"检查到配置项 {path_} 不存在，已插入默认值 {value}")
+                conf[key] = value
+                has_new = True
+            else:
+                if conf[key] is None:
+                    conf[key] = value
+                    has_new = True
+                elif isinstance(value, dict):
+                    has_new |= self.check_config_integrity(value, conf[key], path + "." + key if path else key)
+        return has_new
+            
+    def save_config(self, replace_config: Dict = None):
+        '''将配置写入文件
+        
+        如果传入 replace_config，则将配置替换为 replace_config
+        '''
+        if replace_config:
+            self.update(replace_config)
+        with open(self.config_path, "w", encoding="utf-8-sig") as f:
+            json.dump(self, f, indent=2, ensure_ascii=False)
+            
+    def __getattr__(self, item):
+        try:
+            return self[item]
+        except KeyError:
+            return None
+        
+    def __delattr__(self, key):
+        try:
+            del self[key]
+            self.save_config()
+        except KeyError:
+            raise AttributeError(f"没有找到 Key: '{key}'")
+
+    def __setattr__(self, key, value):
+        self[key] = value
+
+    def check_exist(self) -> bool:
+        return os.path.exists(self.config_path)

astrbot/core/conversation_mgr.py

@@ -0,0 +1,119 @@
+import uuid
+import json
+import asyncio
+from astrbot.core import sp
+from typing import Dict, List
+from astrbot.core.db import BaseDatabase
+from astrbot.core.db.po import Conversation
+
+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] = sp.get("session_conversation", {})
+        self.db = db_helper
+        self.save_interval = 60  # 每 60 秒保存一次
+        self._start_periodic_save()
+                
+    def _start_periodic_save(self):
+        asyncio.create_task(self._periodic_save())
+
+    async def _periodic_save(self):
+        while True:
+            await asyncio.sleep(self.save_interval)
+            self._save_to_storage()
+
+    def _save_to_storage(self):
+        sp.put("session_conversation", self.session_conversations)
+
+    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'''
+        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'''
+        self.session_conversations[unified_msg_origin] = conversation_id
+        sp.put("session_conversation", self.session_conversations)
+        
+    async def delete_conversation(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'''
+        conversation_id = self.session_conversations.get(unified_msg_origin)
+        if conversation_id:
+            self.db.delete_conversation(
+                user_id=unified_msg_origin,
+                cid=conversation_id
+            )
+            del self.session_conversations[unified_msg_origin]
+            sp.put("session_conversation", self.session_conversations)
+            
+    async def get_curr_conversation_id(self, unified_msg_origin: str) -> str:
+        '''获取会话当前的对话 ID'''
+        return self.session_conversations.get(unified_msg_origin, None)
+    
+    async def get_conversation(self, unified_msg_origin: str, conversation_id: str) -> Conversation:
+        '''获取会话的对话'''
+        return self.db.get_conversation_by_user_id(unified_msg_origin, conversation_id)
+    
+    async def get_conversations(self, unified_msg_origin: str) -> List[Conversation]:
+        '''获取会话的所有对话'''
+        return self.db.get_conversations(unified_msg_origin)
+    
+    async def update_conversation(self, unified_msg_origin: str, conversation_id: str, history: List[Dict]):
+        '''更新会话的对话'''
+        if conversation_id:
+            self.db.update_conversation(
+                user_id=unified_msg_origin,
+                cid=conversation_id,
+                history=json.dumps(history)
+            )
+            
+    async def update_conversation_title(self, unified_msg_origin: str, title: str):
+        '''更新会话的对话标题'''
+        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):
+        '''更新会话的对话 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):
+        conversation = await self.get_conversation(unified_msg_origin, conversation_id)
+        history = json.loads(conversation.history)
+
+        contexts = []
+        temp_contexts = []
+        for record in history:
+            if record['role'] == "user":
+                temp_contexts.append(f"User: {record['content']}")
+            elif record['role'] == "assistant":
+                temp_contexts.append(f"Assistant: {record['content']}")
+                contexts.insert(0, temp_contexts)
+                temp_contexts = []
+
+        # 展平 contexts 列表
+        contexts = [item for sublist in contexts for item in sublist]
+
+        # 计算分页
+        paged_contexts = contexts[(page-1)*page_size:page*page_size]
+        total_pages = len(contexts) // page_size
+        if len(contexts) % page_size != 0:
+            total_pages += 1
+        
+        return paged_contexts, total_pages

astrbot/core/core_lifecycle.py

@@ -0,0 +1,137 @@
+import traceback
+import asyncio
+import time
+import threading
+import os
+from .event_bus import EventBus
+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.provider.manager import ProviderManager
+from astrbot.core import LogBroker
+from astrbot.core.db import BaseDatabase
+from astrbot.core.updator import AstrBotUpdator
+from astrbot.core import logger
+from astrbot.core.config.default import VERSION
+from astrbot.core.rag.knowledge_db_mgr import KnowledgeDBManager
+from astrbot.core.conversation_mgr import ConversationManager
+class AstrBotCoreLifecycle:
+    def __init__(self, log_broker: LogBroker, db: BaseDatabase):
+        self.log_broker = log_broker
+        self.astrbot_config = astrbot_config
+        self.db = db
+        
+        os.environ['https_proxy'] = self.astrbot_config['http_proxy']
+        os.environ['http_proxy'] = self.astrbot_config['http_proxy']
+        os.environ['no_proxy'] = 'localhost,127.0.0.1'
+        
+    async def initialize(self):
+        logger.info("AstrBot v"+ VERSION)
+        if os.environ.get("TESTING", ""):
+            logger.setLevel("DEBUG")
+        else:
+            logger.setLevel(self.astrbot_config['log_level'])
+        self.event_queue = Queue()
+        self.event_queue.closed = False
+        
+        self.provider_manager = ProviderManager(self.astrbot_config, self.db)
+        
+        self.platform_manager = PlatformManager(self.astrbot_config, self.event_queue)
+        
+        self.knowledge_db_manager = KnowledgeDBManager(self.astrbot_config)
+        
+        self.conversation_manager = ConversationManager(self.db)
+        
+        self.star_context = Context(
+            self.event_queue, 
+            self.astrbot_config, 
+            self.db,
+            self.provider_manager,
+            self.platform_manager,
+            self.conversation_manager,
+            self.knowledge_db_manager
+        )
+        self.plugin_manager = PluginManager(self.star_context, self.astrbot_config)
+        
+        await self.plugin_manager.reload()
+        '''扫描、注册插件、实例化插件类'''
+        
+        await self.provider_manager.initialize()
+        '''根据配置实例化各个 Provider'''
+        
+        await self.platform_manager.initialize()
+        '''根据配置实例化各个平台适配器'''
+
+        self.pipeline_scheduler = PipelineScheduler(PipelineContext(self.astrbot_config, self.plugin_manager))
+        await self.pipeline_scheduler.initialize()
+        '''初始化消息事件流水线调度器'''
+        
+        self.astrbot_updator = AstrBotUpdator(self.astrbot_config['plugin_repo_mirror'])
+        self.event_bus = EventBus(self.event_queue, self.pipeline_scheduler)
+        self.start_time = int(time.time())
+        self.curr_tasks: List[asyncio.Task] = []
+
+    def _load(self):
+
+        platform_tasks = self.load_platform()
+        event_bus_task = asyncio.create_task(self.event_bus.dispatch(), name="event_bus")
+        
+        extra_tasks = []
+        for task in self.star_context._register_tasks:
+            extra_tasks.append(asyncio.create_task(task, name=task.__name__))
+        
+        # self.curr_tasks = [event_bus_task, *platform_tasks, *extra_tasks]
+        
+        tasks_ = [event_bus_task, *platform_tasks, *extra_tasks]
+        for task in tasks_:
+            self.curr_tasks.append(asyncio.create_task(self._task_wrapper(task), name=task.get_name()))
+        
+        self.start_time = int(time.time())
+        
+    async def _task_wrapper(self, task: asyncio.Task):
+        try:
+            await task
+        except asyncio.CancelledError:
+            pass
+        except Exception as e:
+            
+            logger.error(f"------- 任务 {task.get_name()} 发生错误: {e}")
+            for line in traceback.format_exc().split("\n"):
+                logger.error(f"|    {line}")
+            logger.error("-------")
+    
+    async def start(self):
+        self._load()
+        logger.info("AstrBot 启动完成。")
+        
+        await asyncio.gather(*self.curr_tasks, return_exceptions=True)
+        
+    async def stop(self):
+        self.event_queue.closed = True
+        for task in self.curr_tasks:
+            task.cancel()
+            
+        await self.provider_manager.terminate()
+        
+        for task in self.curr_tasks:
+            try:
+                await task
+            except asyncio.CancelledError:
+                pass
+            except Exception as e:
+                logger.error(f"任务 {task.get_name()} 发生错误: {e}")
+        
+    def restart(self):
+        self.event_queue.closed = True
+        threading.Thread(target=self.astrbot_updator._reboot, name="restart", daemon=True).start()
+        
+    def load_platform(self) -> List[asyncio.Task]:
+        tasks = []
+        platform_insts = self.platform_manager.get_insts()
+        for platform_inst in platform_insts:
+            tasks.append(asyncio.create_task(platform_inst.run(), name=platform_inst.meta().name))
+        return tasks

astrbot/core/db/__init__.py

@@ -0,0 +1,113 @@
+import abc
+from dataclasses import dataclass
+from typing import List
+from astrbot.core.db.po import Stats, LLMHistory, ATRIVision, Conversation
+
+@dataclass
+class BaseDatabase(abc.ABC):
+    '''
+    数据库基类
+    '''
+    def __init__(self) -> None:
+        pass
+    
+    def insert_base_metrics(self, metrics: dict):
+        '''插入基础指标数据'''
+        self.insert_platform_metrics(metrics['platform_stats'])
+        self.insert_plugin_metrics(metrics['plugin_stats'])
+        self.insert_command_metrics(metrics['command_stats'])
+        self.insert_llm_metrics(metrics['llm_stats'])
+    
+    @abc.abstractmethod
+    def insert_platform_metrics(self, metrics: dict):
+        '''插入平台指标数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def insert_plugin_metrics(self, metrics: dict):
+        '''插入插件指标数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def insert_command_metrics(self, metrics: dict):
+        '''插入指令指标数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def insert_llm_metrics(self, metrics: dict):
+        '''插入 LLM 指标数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def update_llm_history(self, session_id: str, content: str, provider_type: str):
+        '''更新 LLM 历史记录。当不存在 session_id 时插入'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_llm_history(self, session_id: str = None, provider_type: str = None) -> List[LLMHistory]:
+        '''获取 LLM 历史记录, 如果 session_id 为 None, 返回所有'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_base_stats(self, offset_sec: int = 86400) -> Stats:
+        '''获取基础统计数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_total_message_count(self) -> int:
+        '''获取总消息数'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_grouped_base_stats(self, offset_sec: int = 86400) -> Stats:
+        '''获取基础统计数据(合并)'''
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def insert_atri_vision_data(self, vision_data: ATRIVision):
+        '''插入 ATRI 视觉数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_atri_vision_data(self) -> List[ATRIVision]:
+        '''获取 ATRI 视觉数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_atri_vision_data_by_path_or_id(self, url_or_path: str, id: str) -> ATRIVision:
+        '''通过 url 或 path 获取 ATRI 视觉数据'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_conversation_by_user_id(self, user_id: str, cid: str) -> Conversation:
+        '''通过 user_id 和 cid 获取 Conversation'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def new_conversation(self, user_id: str, cid: str):
+        '''新建 Conversation'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def get_conversations(self, user_id: str) -> List[Conversation]:
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def update_conversation(self, user_id: str, cid: str, history: str):
+        '''更新 Conversation'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def delete_conversation(self, user_id: str, cid: str):
+        '''删除 Conversation'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def update_conversation_title(self, user_id: str, cid: str, title: str):
+        '''更新 Conversation 标题'''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def update_conversation_persona_id(self, user_id: str, cid: str, persona_id: str):
+        '''更新 Conversation Persona ID'''
+        raise NotImplementedError

astrbot/core/db/po.py

@@ -0,0 +1,70 @@
+'''指标数据'''
+
+from dataclasses import dataclass, field
+from typing import List
+
+@dataclass
+class Platform():
+    name: str
+    count: int
+    timestamp: int
+    
+@dataclass
+class Provider():
+    name: str
+    count: int
+    timestamp: int
+    
+@dataclass
+class Plugin():
+    name: str
+    count: int
+    timestamp: int
+    
+@dataclass
+class Command():
+    name: str
+    count: int
+    timestamp: int
+
+@dataclass
+class Stats():
+    platform: List[Platform] = field(default_factory=list)
+    command: List[Command] = field(default_factory=list)
+    llm: List[Provider] = field(default_factory=list)
+    
+@dataclass
+class LLMHistory():
+    '''LLM 聊天时持久化的信息'''
+    provider_type: str
+    session_id: str
+    content: str
+    
+@dataclass
+class ATRIVision():
+    '''Deprecated'''
+    id: str
+    url_or_path: str
+    caption: str
+    is_meme: bool
+    keywords: List[str]
+    platform_name: str
+    session_id: str
+    sender_nickname: str
+    timestamp: int = -1
+    
+@dataclass
+class Conversation():
+    '''LLM 对话存储
+    
+    对于网页聊天，history 存储了包括指令、回复、图片等在内的所有消息。
+    对于其他平台的聊天，不存储非 LLM 的回复（因为考虑到已经存储在各自的平台上）。
+    '''
+    user_id: str
+    cid: str
+    history: str = ""
+    '''字符串格式的列表。'''
+    created_at: int = 0
+    updated_at: int = 0
+    title: str = ""
+    persona_id: str = ""

astrbot/core/db/sqlite.py

@@ -0,0 +1,365 @@
+import sqlite3
+import os
+import time
+from astrbot.core.db.po import (
+    Platform, 
+    Stats,
+    LLMHistory,
+    ATRIVision,
+    Conversation
+)
+from . import BaseDatabase
+from typing import Tuple
+
+
+class SQLiteDatabase(BaseDatabase):
+    def __init__(self, db_path: str) -> None:
+        super().__init__()
+        self.db_path = db_path
+        
+        with open(os.path.dirname(__file__) + "/sqlite_init.sql", "r") as f:
+            sql = f.read()
+        
+        # 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_plugin_metrics(self, metrics: dict):
+        pass
+
+    def insert_command_metrics(self, metrics: dict):
+        for k, v in metrics.items():
+            self._exec_sql(
+                '''
+                INSERT INTO command(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 update_llm_history(self, session_id: str, content: str, provider_type: str):
+        res = self.get_llm_history(session_id, provider_type)
+        if res:
+            self._exec_sql(
+                '''
+                UPDATE llm_history SET content = ? WHERE session_id = ? AND provider_type = ?
+                ''', (content, session_id, provider_type)
+            )
+        else:
+            self._exec_sql(
+                '''
+                INSERT INTO llm_history(provider_type, session_id, content) VALUES (?, ?, ?)
+                ''', (provider_type, session_id, content)
+            )
+
+    def get_llm_history(self, session_id: str = None, provider_type: str = None) -> Tuple:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+        
+        where_clause = ""
+        if session_id or provider_type:
+            where_clause += " WHERE "
+            has = False
+            if session_id:
+                where_clause += f"session_id = '{session_id}'"
+                has = True
+            if provider_type:
+                if has:
+                    where_clause += " AND "
+                where_clause += f"provider_type = '{provider_type}'"
+        
+        c.execute(
+            '''
+            SELECT * FROM llm_history
+            ''' + where_clause
+        )
+        res = c.fetchall()
+        histories = []
+        for row in res:
+            histories.append(LLMHistory(*row))
+        c.close()
+        return histories
+
+    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.execute(
+        #     '''
+        #     SELECT * FROM command
+        #     ''' + where_clause
+        # )
+        
+        # command = []
+        # for row in c.fetchall():
+        #     command.append(Command(*row))
+            
+        # c.execute(
+        #     '''
+        #     SELECT * FROM llm
+        #     ''' + where_clause
+        # )
+        
+        # llm = []
+        # for row in c.fetchall():
+        #     llm.append(Provider(*row))
+            
+        c.close()
+            
+        return Stats(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 insert_atri_vision_data(self, vision: ATRIVision):
+        ts = int(time.time())
+        keywords = ",".join(vision.keywords)
+        self._exec_sql(
+            '''
+            INSERT INTO atri_vision(id, url_or_path, caption, is_meme, keywords, platform_name, session_id, sender_nickname, timestamp) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
+            ''', (vision.id, vision.url_or_path, vision.caption, vision.is_meme, keywords, vision.platform_name, vision.session_id, vision.sender_nickname, ts)
+        )
+        
+    def get_atri_vision_data(self) -> Tuple:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+            
+        c.execute(
+            '''
+            SELECT * FROM atri_vision
+            '''
+        )
+        
+        res = c.fetchall()
+        visions = []
+        for row in res:
+            visions.append(ATRIVision(*row))
+        c.close()
+        return visions
+    
+    def get_atri_vision_data_by_path_or_id(self, url_or_path: str, id: str) -> ATRIVision:
+        try:
+            c = self.conn.cursor()
+        except sqlite3.ProgrammingError:
+            c = self._get_conn(self.db_path).cursor()
+            
+        c.execute(
+            '''
+            SELECT * FROM atri_vision WHERE url_or_path = ? OR id = ?
+            ''', (url_or_path, id)
+        )
+        
+        res = c.fetchone()
+        c.close()
+        if res:
+            return ATRIVision(*res)
+        return None

astrbot/core/db/sqlite_init.sql

@@ -0,0 +1,48 @@
+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,
+    cid TEXT,
+    history TEXT,
+    created_at INTEGER,
+    updated_at INTEGER,
+    title TEXT,
+    persona_id TEXT
+);

astrbot/core/event_bus.py

@@ -0,0 +1,23 @@
+import asyncio
+from asyncio import Queue
+from astrbot.core.pipeline.scheduler import PipelineScheduler
+from astrbot.core import logger
+from .platform import AstrMessageEvent
+
+class EventBus:
+    def __init__(self, event_queue: Queue, pipeline_scheduler: PipelineScheduler):
+        self.event_queue = event_queue
+        self.pipeline_scheduler = pipeline_scheduler
+
+    async def dispatch(self):
+        logger.info("事件总线已打开。")
+        while True:
+            event: AstrMessageEvent = await self.event_queue.get()
+            self._print_event(event)
+            asyncio.create_task(self.pipeline_scheduler.execute(event))
+            
+    def _print_event(self, event: AstrMessageEvent):        
+        if event.get_sender_name():
+            logger.info(f"[{event.get_platform_name()}] {event.get_sender_name()}/{event.get_sender_id()}: {event.get_message_outline()}")
+        else:
+            logger.info(f"[{event.get_platform_name()}] {event.get_sender_id()}: {event.get_message_outline()}")

astrbot/core/log.py

@@ -0,0 +1,79 @@
+import logging
+import colorlog
+import asyncio
+from collections import deque
+from asyncio import Queue
+from typing import List
+
+CACHED_SIZE = 200
+log_color_config = {
+    'DEBUG': 'bold_blue', 'INFO': 'bold_cyan',
+    'WARNING': 'bold_yellow', 'ERROR': 'red',
+    'CRITICAL': 'bold_red', 'RESET': 'reset',
+    'asctime': 'green'
+}
+
+class LogBroker:
+    def __init__(self):
+        self.log_cache = deque(maxlen=CACHED_SIZE)
+        self.subscribers: List[Queue] = []
+    
+    def register(self) -> Queue:
+        '''给每个订阅者返回一个带有日志缓存的队列'''
+        q = Queue(maxsize=CACHED_SIZE + 10)
+        for log in self.log_cache:
+            q.put_nowait(log)
+        self.subscribers.append(q)
+        return q
+    
+    def unregister(self, q: Queue):
+        '''取消订阅'''
+        self.subscribers.remove(q)
+        
+    def publish(self, log_entry: str):
+        '''发布消息'''
+        self.log_cache.append(log_entry)
+        for q in self.subscribers:
+            try:
+                q.put_nowait(log_entry)
+            except asyncio.QueueFull:
+                pass
+
+class LogQueueHandler(logging.Handler):
+    def __init__(self, log_broker: LogBroker):
+        super().__init__()
+        self.log_broker = log_broker
+
+    def emit(self, record):
+        log_entry = self.format(record)
+        self.log_broker.publish(log_entry)
+
+class LogManager:
+
+    @classmethod
+    def GetLogger(cls, log_name: str = 'default'):
+        logger = logging.getLogger(log_name)
+        if logger.hasHandlers():
+            return logger
+        console_handler = logging.StreamHandler()
+        console_handler.setLevel(logging.DEBUG)
+        console_formatter = colorlog.ColoredFormatter(
+            fmt='%(log_color)s [%(asctime)s| %(levelname)s] [%(filename)s:%(lineno)d]: %(message)s %(reset)s',
+            datefmt='%H:%M:%S',
+            log_colors=log_color_config
+        )
+        console_handler.setFormatter(console_formatter)
+        logger.setLevel(logging.DEBUG)
+        logger.addHandler(console_handler)
+        
+        return logger
+    
+    @classmethod
+    def set_queue_handler(cls, logger: logging.Logger, log_broker: LogBroker):
+        handler = LogQueueHandler(log_broker)
+        handler.setLevel(logging.DEBUG)
+        if logger.handlers:
+            handler.setFormatter(logger.handlers[0].formatter)
+        else:
+            handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
+        logger.addHandler(handler)

astrbot/core/message/components.py

@@ -0,0 +1,460 @@
+'''
+MIT License
+
+Copyright (c) 2021 Lxns-Network
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+'''
+
+import base64
+import json
+import os
+import typing as T
+from enum import Enum
+from pydantic.v1 import BaseModel
+
+class ComponentType(Enum):
+    Plain = "Plain"
+    Face = "Face"
+    Record = "Record"
+    Video = "Video"
+    At = "At"
+    RPS = "RPS"  # TODO
+    Dice = "Dice"  # TODO
+    Shake = "Shake"  # TODO
+    Anonymous = "Anonymous"  # TODO
+    Share = "Share"
+    Contact = "Contact"  # TODO
+    Location = "Location"  # TODO
+    Music = "Music"
+    Image = "Image"
+    Reply = "Reply"
+    RedBag = "RedBag"
+    Poke = "Poke"
+    Forward = "Forward"
+    Node = "Node"
+    Xml = "Xml"
+    Json = "Json"
+    CardImage = "CardImage"
+    TTS = "TTS"
+    Unknown = "Unknown"
+    File = "File"
+
+
+class BaseMessageComponent(BaseModel):
+    type: ComponentType
+
+    def toString(self):
+        output = f"[CQ:{self.type.lower()}"
+        for k, v in self.__dict__.items():
+            if k == "type" or v is None:
+                continue
+            if k == "_type":
+                k = "type"
+            if isinstance(v, bool):
+                v = 1 if v else 0
+            output += ",%s=%s" % (k, str(v).replace("&", "&") \
+                                  .replace(",", ",") \
+                                  .replace("[", "[") \
+                                  .replace("]", "]"))
+        output += "]"
+        return output
+
+    def toDict(self):
+        data = dict()
+        for k, v in self.__dict__.items():
+            if k == "type" or v is None:
+                continue
+            if k == "_type":
+                k = "type"
+            data[k] = v
+        return {
+            "type": self.type.lower(),
+            "data": data
+        }
+
+
+class Plain(BaseMessageComponent):
+    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
+
+    def __init__(self, text: str, convert: bool = True, **_):
+        super().__init__(text=text, convert=convert, **_)
+
+    def toString(self):  # 没有 [CQ:plain] 这种东西，所以直接导出纯文本
+        if not self.convert:
+            return self.text
+        return self.text.replace("&", "&") \
+            .replace("[", "[") \
+            .replace("]", "]")
+
+
+class Face(BaseMessageComponent):
+    type: ComponentType = "Face"
+    id: int
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Record(BaseMessageComponent):
+    type: ComponentType = "Record"
+    file: T.Optional[str] = ""
+    magic: T.Optional[bool] = False
+    url: T.Optional[str] = ""
+    cache: T.Optional[bool] = True
+    proxy: T.Optional[bool] = True
+    timeout: T.Optional[int] = 0
+    # 额外
+    path: T.Optional[str]
+
+    def __init__(self, file: T.Optional[str], **_):
+        for k in _.keys():
+            if k == "url":
+                pass
+                # Protocol.warn(f"go-cqhttp doesn't support send {self.type} by {k}")
+        super().__init__(file=file, **_)
+
+    @staticmethod
+    def fromFileSystem(path, **_):
+        return Record(file=f"file:///{os.path.abspath(path)}", path=path, **_)
+
+    @staticmethod
+    def fromURL(url: str, **_):
+        if url.startswith("http://") or url.startswith("https://"):
+            return Record(file=url, **_)
+        raise Exception("not a valid url")
+
+
+class Video(BaseMessageComponent):
+    type: ComponentType = "Video"
+    file: str
+    cover: T.Optional[str] = ""
+    c: T.Optional[int] = 2
+    # 额外
+    path: T.Optional[str] = ""
+
+    def __init__(self, file: str, **_):
+        # for k in _.keys():
+        #     if k == "c" and _[k] not in [2, 3]:
+        #         logger.warn(f"Protocol: {k}={_[k]} doesn't match values")
+        super().__init__(file=file, **_)
+
+    @staticmethod
+    def fromFileSystem(path, **_):
+        return Video(file=f"file:///{os.path.abspath(path)}", path=path, **_)
+
+    @staticmethod
+    def fromURL(url: str, **_):
+        if url.startswith("http://") or url.startswith("https://"):
+            return Video(file=url, **_)
+        raise Exception("not a valid url")
+
+
+class At(BaseMessageComponent):
+    type: ComponentType = "At"
+    qq: T.Union[int, str]  # 此处str为all时代表所有人
+    name: T.Optional[str] = ""
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class AtAll(At):
+    qq: str = "all"
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class RPS(BaseMessageComponent):  # TODO
+    type: ComponentType = "RPS"
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Dice(BaseMessageComponent):  # TODO
+    type: ComponentType = "Dice"
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Shake(BaseMessageComponent):  # TODO
+    type: ComponentType = "Shake"
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Anonymous(BaseMessageComponent):  # TODO
+    type: ComponentType = "Anonymous"
+    ignore: T.Optional[bool] = False
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Share(BaseMessageComponent):
+    type: ComponentType = "Share"
+    url: str
+    title: str
+    content: T.Optional[str] = ""
+    image: T.Optional[str] = ""
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Contact(BaseMessageComponent):  # TODO
+    type: ComponentType = "Contact"
+    _type: str  # type 字段冲突
+    id: T.Optional[int] = 0
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Location(BaseMessageComponent):  # TODO
+    type: ComponentType = "Location"
+    lat: float
+    lon: float
+    title: T.Optional[str] = ""
+    content: T.Optional[str] = ""
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Music(BaseMessageComponent):
+    type: ComponentType = "Music"
+    _type: str
+    id: T.Optional[int] = 0
+    url: T.Optional[str] = ""
+    audio: T.Optional[str] = ""
+    title: T.Optional[str] = ""
+    content: T.Optional[str] = ""
+    image: T.Optional[str] = ""
+
+    def __init__(self, **_):
+        # for k in _.keys():
+        #     if k == "_type" and _[k] not in ["qq", "163", "xm", "custom"]:
+        #         logger.warn(f"Protocol: {k}={_[k]} doesn't match values")
+        super().__init__(**_)
+
+
+class Image(BaseMessageComponent):
+    type: ComponentType = "Image"
+    file: T.Optional[str] = ""
+    _type: T.Optional[str] = ""
+    subType: T.Optional[int] = 0
+    url: T.Optional[str] = ""
+    cache: T.Optional[bool] = True
+    id: T.Optional[int] = 40000
+    c: T.Optional[int] = 2
+    # 额外
+    path: T.Optional[str] = ""
+    file_unique: T.Optional[str] = "" # 某些平台可能有图片缓存的唯一标识
+
+    def __init__(self, file: T.Optional[str], **_):
+        # for k in _.keys():
+        #     if (k == "_type" and _[k] not in ["flash", "show", None]) or \
+        #             (k == "c" and _[k] not in [2, 3]):
+        #         logger.warn(f"Protocol: {k}={_[k]} doesn't match values")
+        super().__init__(file=file, **_)
+
+    @staticmethod
+    def fromURL(url: str, **_):
+        if url.startswith("http://") or url.startswith("https://"):
+            return Image(file=url, **_)
+        raise Exception("not a valid url")
+
+    @staticmethod
+    def fromFileSystem(path, **_):
+        return Image(file=f"file:///{os.path.abspath(path)}", path=path, **_)
+
+    @staticmethod
+    def fromBase64(base64: str, **_):
+        return Image(f"base64://{base64}", **_)
+
+    @staticmethod
+    def fromBytes(byte: bytes):
+        return Image.fromBase64(base64.b64encode(byte).decode())
+
+    @staticmethod
+    def fromIO(IO):
+        return Image.fromBytes(IO.read())
+
+
+class Reply(BaseMessageComponent):
+    type: ComponentType = "Reply"
+    id: T.Union[str, int]
+    text: T.Optional[str] = ""
+    qq: T.Optional[int] = 0
+    time: T.Optional[int] = 0
+    seq: T.Optional[int] = 0
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class RedBag(BaseMessageComponent):
+    type: ComponentType = "RedBag"
+    title: str
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Poke(BaseMessageComponent):
+    type: str = ""
+    id: T.Optional[int] = 0
+    qq: T.Optional[int] = 0
+
+    def __init__(self, type: str, **_):
+        type = f"Poke:{type}"
+        super().__init__(type=type, **_)
+
+
+class Forward(BaseMessageComponent):
+    type: ComponentType = "Forward"
+    id: str
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+class Node(BaseMessageComponent):
+    '''群合并转发消息'''
+    type: ComponentType = "Node"
+    id: T.Optional[int] = 0 # 忽略
+    name: T.Optional[str] = "" # qq昵称
+    uin: T.Optional[int] = 0 # qq号
+    content: T.Optional[T.Union[str, list]] = "" # 子消息段列表
+    seq: T.Optional[T.Union[str, list]] = "" # 忽略
+    time: T.Optional[int] = 0
+
+    def __init__(self, content: T.Union[str, list], **_):
+        if isinstance(content, list):
+            _content = ""
+            for chain in content:
+                _content += chain.toString()
+            content = _content
+        super().__init__(content=content, **_)
+
+    def toString(self):
+        # logger.warn("Protocol: node doesn't support stringify")
+        return ""
+
+
+class Xml(BaseMessageComponent):
+    type: ComponentType = "Xml"
+    data: str
+    resid: T.Optional[int] = 0
+ 
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Json(BaseMessageComponent):
+    type: ComponentType = "Json"
+    data: T.Union[str, dict]
+    resid: T.Optional[int] = 0
+
+    def __init__(self, data, **_):
+        if isinstance(data, dict):
+            data = json.dumps(data)
+        super().__init__(data=data, **_)
+
+
+class CardImage(BaseMessageComponent):
+    type: ComponentType = "CardImage"
+    file: str
+    cache: T.Optional[bool] = True
+    minwidth: T.Optional[int] = 400
+    minheight: T.Optional[int] = 400
+    maxwidth: T.Optional[int] = 500
+    maxheight: T.Optional[int] = 500
+    source: T.Optional[str] = ""
+    icon: T.Optional[str] = ""
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+    @staticmethod
+    def fromFileSystem(path, **_):
+        return CardImage(file=f"file:///{os.path.abspath(path)}", **_)
+
+
+class TTS(BaseMessageComponent):
+    type: ComponentType = "TTS"
+    text: str
+
+    def __init__(self, **_):
+        super().__init__(**_)
+
+
+class Unknown(BaseMessageComponent):
+    type: ComponentType = "Unknown"
+    text: str
+
+    def toString(self):
+        return ""
+
+class File(BaseMessageComponent):
+    '''
+    目前此消息段只适配了 Napcat。
+    '''
+    type: ComponentType = "File"
+    name: T.Optional[str] = "" # 名字
+    file: T.Optional[str] = "" # url（本地路径）
+    
+    def __init__(self, name: str, file: str):
+        super().__init__(name=name, file=file)
+
+
+ComponentTypes = {
+    "plain": Plain,
+    "text": Plain,
+    "face": Face,
+    "record": Record,
+    "video": Video,
+    "at": At,
+    "rps": RPS,
+    "dice": Dice,
+    "shake": Shake,
+    "anonymous": Anonymous,
+    "share": Share,
+    "contact": Contact,
+    "location": Location,
+    "music": Music,
+    "image": Image,
+    "reply": Reply,
+    "redbag": RedBag,
+    "poke": Poke,
+    "forward": Forward,
+    "node": Node,
+    "xml": Xml,
+    "json": Json,
+    "cardimage": CardImage,
+    "tts": TTS,
+    "unknown": Unknown,
+    'file': File,
+}

astrbot/core/message/message_event_result.py

@@ -0,0 +1,149 @@
+import enum
+
+from typing import List, Optional
+from dataclasses import dataclass, field
+from astrbot.core.message.components import BaseMessageComponent, Plain, Image
+from typing_extensions import deprecated
+
+@dataclass
+class MessageChain():
+    '''MessageChain 描述了一整条消息中带有的所有组件。
+    现代消息平台的一条富文本消息中可能由多个组件构成，如文本、图片、At 等，并且保留了顺序。
+    
+    Attributes:
+        `chain` (list): 用于顺序存储各个组件。
+        `use_t2i_` (bool): 用于标记是否使用文本转图片服务。默认为 None，即跟随用户的设置。当设置为 True 时，将会使用文本转图片服务。
+    '''
+    
+    chain: List[BaseMessageComponent] = field(default_factory=list)
+    use_t2i_: Optional[bool] = None # None 为跟随用户设置
+    
+    def message(self, message: str):
+        '''添加一条文本消息到消息链 `chain` 中。
+        
+        Example:
+
+            CommandResult().message("Hello ").message("world!")
+            # 输出 Hello world!
+
+        '''
+        self.chain.append(Plain(message))
+        return self
+    
+    @deprecated("请使用 message 方法代替。")
+    def error(self, message: str):
+        '''添加一条错误消息到消息链 `chain` 中
+        
+        Example:
+            
+            CommandResult().error("解析失败")
+            
+        '''
+        self.chain.append(Plain(message))
+        return self
+    
+    def url_image(self, url: str):
+        '''添加一条图片消息（https 链接）到消息链 `chain` 中。
+        
+        Note:
+            如果需要发送本地图片，请使用 `file_image` 方法。
+        
+        Example:
+        
+            CommandResult().image("https://example.com/image.jpg")
+            
+        '''
+        self.chain.append(Image.fromURL(url))
+        return self
+    
+    def file_image(self, path: str):
+        '''添加一条图片消息（本地文件路径）到消息链 `chain` 中。
+        
+        Note:
+            如果需要发送网络图片，请使用 `url_image` 方法。
+        
+        CommandResult().image("image.jpg")
+        '''
+        self.chain.append(Image.fromFileSystem(path))
+        return self
+    
+    def use_t2i(self, use_t2i: bool):
+        '''设置是否使用文本转图片服务。
+        
+        Args:
+            use_t2i (bool): 是否使用文本转图片服务。默认为 None，即跟随用户的设置。当设置为 True 时，将会使用文本转图片服务。
+        '''
+        self.use_t2i_ = use_t2i
+        return self
+
+class EventResultType(enum.Enum):
+    '''用于描述事件处理的结果类型。
+    
+    Attributes:
+        CONTINUE: 事件将会继续传播
+        STOP: 事件将会终止传播
+    '''
+    CONTINUE = enum.auto()
+    STOP = enum.auto()
+    
+class ResultContentType(enum.Enum):
+    '''用于描述事件结果的内容的类型。
+    '''
+    LLM_RESULT = enum.auto()
+    '''调用 LLM 产生的结果'''
+    GENERAL_RESULT = enum.auto()
+    '''普通的消息结果'''
+@dataclass
+class MessageEventResult(MessageChain):
+    '''MessageEventResult 描述了一整条消息中带有的所有组件以及事件处理的结果。
+    现代消息平台的一条富文本消息中可能由多个组件构成，如文本、图片、At 等，并且保留了顺序。
+    
+    Attributes:
+        `chain` (list): 用于顺序存储各个组件。
+        `use_t2i_` (bool): 用于标记是否使用文本转图片服务。默认为 None，即跟随用户的设置。当设置为 True 时，将会使用文本转图片服务。
+        `result_type` (EventResultType): 事件处理的结果类型。
+    '''
+    
+    result_type: Optional[EventResultType] = field(default_factory=lambda: EventResultType.CONTINUE)
+    
+    result_content_type: Optional[ResultContentType] = field(default_factory=lambda: ResultContentType.GENERAL_RESULT)
+    
+    def stop_event(self) -> 'MessageEventResult':
+        '''终止事件传播。
+        '''
+        self.result_type = EventResultType.STOP
+        return self
+    
+    def continue_event(self) -> 'MessageEventResult':
+        '''继续事件传播。
+        '''
+        self.result_type = EventResultType.CONTINUE
+        return self
+        
+    def is_stopped(self) -> bool:
+        '''
+        是否终止事件传播。
+        '''
+        return self.result_type == EventResultType.STOP
+    
+    def set_result_content_type(self, typ: ResultContentType) -> 'MessageEventResult':
+        '''设置事件处理的结果类型。
+        
+        Args:
+            result_type (EventResultType): 事件处理的结果类型。
+        '''
+        self.result_content_type = typ
+        return self
+    
+    def is_llm_result(self) -> bool:
+        '''是否为 LLM 结果。
+        '''
+        return self.result_content_type == ResultContentType.LLM_RESULT
+    
+    def get_plain_text(self) -> str:
+        '''获取纯文本消息。这个方法将获取所有 Plain 组件的文本并拼接成一条消息。空格分隔。
+        '''
+        return " ".join([comp.text for comp in self.chain if isinstance(comp, Plain)])
+    
+    
+CommandResult = MessageEventResult

astrbot/core/pipeline/__init__.py

@@ -0,0 +1,34 @@
+from astrbot.core.message.message_event_result import MessageEventResult, EventResultType
+
+from .waking_check.stage import WakingCheckStage
+from .whitelist_check.stage import WhitelistCheckStage
+from .rate_limit_check.stage import RateLimitStage
+from .content_safety_check.stage import ContentSafetyCheckStage
+from .preprocess_stage.stage import PreProcessStage
+from .process_stage.stage import ProcessStage
+from .result_decorate.stage import ResultDecorateStage
+from .respond.stage import RespondStage
+
+STAGES_ORDER = [
+    "WakingCheckStage", # 检查是否需要唤醒
+    "WhitelistCheckStage", # 检查是否在群聊/私聊白名单
+    "RateLimitStage", # 检查会话是否超过频率限制
+    "ContentSafetyCheckStage", # 检查内容安全
+    "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
+    "RespondStage" # 发送消息
+]
+
+__all__ = [
+    "WakingCheckStage",
+    "WhitelistCheckStage",
+    "RateLimitStage",
+    "ContentSafetyCheckStage",
+    "PreProcessStage",
+    "ProcessStage",
+    "ResultDecorateStage",
+    "RespondStage",
+    "MessageEventResult",
+    "EventResultType"
+]

astrbot/core/pipeline/content_safety_check/stage.py

@@ -0,0 +1,31 @@
+from typing import Union, AsyncGenerator
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.message.message_event_result import MessageEventResult
+from astrbot.core import logger
+from .strategies.strategy import StrategySelector
+
+@register_stage
+class ContentSafetyCheckStage(Stage):
+    '''检查内容安全
+    
+    当前只会检查文本的。
+    '''
+
+    async def initialize(self, ctx: PipelineContext):
+        config = ctx.astrbot_config['content_safety']
+        self.strategy_selector = StrategySelector(config)
+
+    async def process(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()
+        ok, info = self.strategy_selector.check(text)
+        if not ok:
+            if event.is_at_or_wake_command:
+                event.set_result(MessageEventResult().message("你的消息或者大模型的响应中包含不适当的内容，已被屏蔽。"))
+                yield 
+            event.stop_event()
+            logger.info(f"内容安全检查不通过，原因：{info}")
+            return
+        event.continue_event()

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

@@ -0,0 +1,8 @@
+import abc
+from typing import Tuple
+
+class ContentSafetyStrategy(abc.ABC):
+        
+    @abc.abstractmethod
+    def check(self, content: str) -> Tuple[bool, str]:
+        raise NotImplementedError

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

@@ -0,0 +1,30 @@
+'''
+使用此功能应该先 pip install baidu-aip
+'''
+from . import ContentSafetyStrategy
+from aip import AipContentCensor
+
+class BaiduAipStrategy(ContentSafetyStrategy):
+    def __init__(self, appid: str, ak: str, sk: str) -> None:
+        self.app_id = appid
+        self.api_key = ak
+        self.secret_key = sk
+        self.client = AipContentCensor(self.app_id, 
+                                       self.api_key, 
+                                       self.secret_key)
+
+    def check(self, content: str):
+        res = self.client.textCensorUserDefined(content)
+        if 'conclusionType' not in res:
+            return False, ""
+        if res['conclusionType'] == 1:
+            return True, ""
+        else:
+            if 'data' not in res:
+                return False, ""
+            count = len(res['data'])
+            info = f"百度审核服务发现 {count} 处违规：\n"
+            for i in res['data']:
+                info += f"{i['msg']}；\n"
+            info += "\n判断结果："+res['conclusion']
+            return False, info

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

@@ -0,0 +1,23 @@
+import re
+import os
+import json
+import base64
+from . import ContentSafetyStrategy
+
+class KeywordsStrategy(ContentSafetyStrategy):
+    def __init__(self, extra_keywords: list) -> None:
+        self.keywords = []
+        if extra_keywords is None:
+            extra_keywords = []
+        self.keywords.extend(extra_keywords)
+        keywords_path = os.path.join(os.path.dirname(__file__), 'unfit_words')
+        # internal keywords
+        if os.path.exists(keywords_path):
+            with open(keywords_path, "r", encoding="utf-8") as f:
+                self.keywords.extend(json.loads(base64.b64decode(f.read()).decode("utf-8"))['keywords'])
+
+    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。"
+        return True, ""

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

@@ -0,0 +1,33 @@
+from . import ContentSafetyStrategy
+from typing import List, Tuple
+from astrbot import logger
+
+class StrategySelector:
+    def __init__(self, config: dict) -> None:
+        self.enabled_strategies: List[ContentSafetyStrategy] = []
+        if config["internal_keywords"]["enable"]:
+            from .keywords import KeywordsStrategy
+
+            self.enabled_strategies.append(
+                KeywordsStrategy(config["internal_keywords"]["extra_keywords"])
+            )
+        if config["baidu_aip"]["enable"]:
+            try:
+                from .baidu_aip import BaiduAipStrategy
+            except ImportError:
+                logger.warning("使用百度内容审核应该先 pip install baidu-aip")
+                return
+            self.enabled_strategies.append(
+                BaiduAipStrategy(
+                    config["baidu_aip"]["app_id"],
+                    config["baidu_aip"]["api_key"],
+                    config["baidu_aip"]["secret_key"],
+                )
+            )
+
+    def check(self, content: str) -> Tuple[bool, str]:
+        for strategy in self.enabled_strategies:
+            ok, info = strategy.check(content)
+            if not ok:
+                return False, info
+        return True, ""

astrbot/core/pipeline/content_safety_check/strategies/unfit_words

@@ -0,0 +1 @@
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

astrbot/core/pipeline/context.py

@@ -0,0 +1,8 @@
+from dataclasses import dataclass
+from astrbot.core.config.astrbot_config import AstrBotConfig
+from astrbot.core.star import PluginManager
+
+@dataclass
+class PipelineContext:
+    astrbot_config: AstrBotConfig
+    plugin_manager: PluginManager

astrbot/core/pipeline/preprocess_stage/stage.py

@@ -0,0 +1,70 @@
+import traceback
+import asyncio
+from typing import Union, AsyncGenerator
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core import logger
+from astrbot.core.message.components import Plain, Record, Image
+
+@register_stage
+class PreProcessStage(Stage):
+    
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.ctx = ctx
+        self.config = ctx.astrbot_config
+        self.plugin_manager = ctx.plugin_manager
+        
+        self.stt_settings: dict = self.config.get('provider_stt_settings', {})
+        self.platform_settings: dict = self.config.get('platform_settings', {})
+        
+
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        '''在处理事件之前的预处理'''
+        # 路径映射
+        if mappings := self.platform_settings.get('path_mapping', []):
+            # 支持 Record，Image 消息段的路径映射。
+            message_chain = event.get_messages()
+            
+            for idx, component in enumerate(message_chain):
+                if isinstance(component, (Record, Image)) and component.url:
+                    for mapping in mappings:
+                        from_, to_ = mapping.split(":")
+                        from_ = from_.removesuffix("/")
+                        to_ = to_.removesuffix("/")
+                        
+                        url = component.url.removeprefix("file://")
+                        if url.startswith(from_):
+                            component.url = url.replace(from_, to_, 1)
+                            logger.debug(f"路径映射: {url} -> {component.url}")
+                    message_chain[idx] = component
+        
+        # STT
+        if self.stt_settings.get('enable', False):
+            # TODO: 独立
+            stt_provider = self.plugin_manager.context.provider_manager.curr_stt_provider_inst
+            if stt_provider:
+                message_chain = event.get_messages()
+                for idx, component in enumerate(message_chain):
+                    if isinstance(component, Record) and component.url:
+                        path = component.url.removeprefix("file://")
+                        retry = 5
+                        for i in range(retry):
+                            try:
+                                result = await stt_provider.get_text(audio_url=path)
+                                if result:
+                                    logger.info("语音转文本结果: " + result)
+                                    message_chain[idx] = Plain(result)
+                                    event.message_str += result
+                                    event.message_obj.message_str += result
+                                break
+                            except FileNotFoundError as e:
+                                # napcat workaround
+                                logger.warning(e)
+                                logger.warning(f"重试中: {i + 1}/{retry}")
+                                await asyncio.sleep(0.5)
+                                continue
+                            except BaseException as e:
+                                logger.error(traceback.format_exc())
+                                logger.error(f"语音转文本失败: {e}")
+                                break

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

@@ -0,0 +1,159 @@
+'''
+本地 Agent 模式的 LLM 调用 Stage
+'''
+import traceback
+import json
+from typing import Union, AsyncGenerator
+from ...context import PipelineContext
+from ..stage import Stage
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.message.message_event_result import MessageEventResult, ResultContentType
+from astrbot.core.message.components import Image
+from astrbot.core import logger
+from astrbot.core.utils.metrics import Metric
+from astrbot.core.provider.entites import ProviderRequest, LLMResponse
+from astrbot.core.star.star_handler import star_handlers_registry, EventType
+
+class LLMRequestSubStage(Stage):
+    
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.ctx = ctx
+        self.bot_wake_prefixs = ctx.astrbot_config['wake_prefix'] # list
+        self.provider_wake_prefix = ctx.astrbot_config['provider_settings']['wake_prefix'] # str
+        
+        for bwp in self.bot_wake_prefixs:
+            if self.provider_wake_prefix.startswith(bwp):
+                logger.info(f"识别 LLM 聊天额外唤醒前缀 {self.provider_wake_prefix} 以机器人唤醒前缀 {bwp} 开头，已自动去除。")
+                self.provider_wake_prefix = self.provider_wake_prefix[len(bwp):]
+                
+        self.conv_manager = ctx.plugin_manager.context.conversation_manager
+        
+    async def process(self, event: AstrMessageEvent, _nested: bool = False) -> Union[None, AsyncGenerator[None, None]]:
+        req: ProviderRequest = None
+        
+        provider = self.ctx.plugin_manager.context.get_using_provider()
+        if provider is None:
+            return
+        
+        if event.get_extra("provider_request"):
+            req = event.get_extra("provider_request")
+            assert isinstance(req, ProviderRequest), "provider_request 必须是 ProviderRequest 类型。"
+        else:
+            req = ProviderRequest(prompt="", image_urls=[])
+            if self.provider_wake_prefix:
+                if not event.message_str.startswith(self.provider_wake_prefix):
+                    return
+            req.prompt = event.message_str[len(self.provider_wake_prefix):]
+            req.func_tool = self.ctx.plugin_manager.context.get_llm_tool_manager()
+            for comp in event.message_obj.message:
+                if isinstance(comp, Image):
+                    image_url = comp.url if comp.url else comp.file
+                    req.image_urls.append(image_url)
+            
+            # 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)
+            req.session_id = 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)
+
+            event.set_extra("provider_request", req)
+            
+        if not req.prompt and not req.image_urls:
+            return
+            
+        # 执行请求 LLM 前事件钩子。
+        # 装饰 system_prompt 等功能
+        handlers = star_handlers_registry.get_handlers_by_event_type(EventType.OnLLMRequestEvent)
+        for handler in handlers:
+            try:
+                await handler.handler(event, req)
+            except BaseException:
+                logger.error(traceback.format_exc())
+                
+        if isinstance(req.contexts, str):
+            req.contexts = json.loads(req.contexts)
+        
+        try:
+            logger.debug(f"提供商请求 Payload: {req}")
+            if _nested:
+                req.func_tool = None # 暂时不支持递归工具调用
+            llm_response = await provider.text_chat(**req.__dict__) # 请求 LLM
+            
+            # 执行 LLM 响应后的事件。
+            handlers = star_handlers_registry.get_handlers_by_event_type(EventType.OnLLMResponseEvent)
+            for handler in handlers:
+                try:
+                    await handler.handler(event, llm_response)
+                except BaseException:
+                    logger.error(traceback.format_exc())
+            
+            # 保存到历史记录
+            await self._save_to_history(event, req, llm_response)
+            
+            await Metric.upload(llm_tick=1, model_name=provider.get_model(), provider_type=provider.meta().type)
+
+            if llm_response.role == 'assistant':
+                # text completion
+                event.set_result(MessageEventResult().message(llm_response.completion_text)
+                                 .set_result_content_type(ResultContentType.LLM_RESULT))
+            elif llm_response.role == 'err':
+                event.set_result(MessageEventResult().message(f"AstrBot 请求失败。\n错误信息: {llm_response.completion_text}"))
+            elif llm_response.role == 'tool':
+                # function calling
+                function_calling_result = {}
+                for func_tool_name, func_tool_args in zip(llm_response.tools_call_name, llm_response.tools_call_args):
+                    func_tool = req.func_tool.get_func(func_tool_name)
+                    logger.info(f"调用工具函数：{func_tool_name}，参数：{func_tool_args}")
+                    try:
+                        # 尝试调用工具函数
+                        wrapper = self._call_handler(self.ctx, event, func_tool.handler, **func_tool_args)
+                        async for resp in wrapper:
+                            if resp is not None: # 有 return 返回
+                                function_calling_result[func_tool_name] = resp
+                            else:
+                                yield # 有生成器返回
+                        event.clear_result() # 清除上一个 handler 的结果
+                    except BaseException as e:
+                        logger.warning(traceback.format_exc())
+                        function_calling_result[func_tool_name] = "When calling the function, an error occurred: " + str(e)
+                if function_calling_result:
+                    # 工具返回 LLM 资源。比如 RAG、网页 得到的相关结果等。
+                    # 我们重新执行一遍这个 stage
+                    req.func_tool = None # 暂时不支持递归工具调用
+                    extra_prompt = "\n\nSystem executed some external tools for this task and here are the results:\n"
+                    for tool_name, tool_result in function_calling_result.items():
+                        extra_prompt += f"Tool: {tool_name}\nTool Result: {tool_result}\n"
+                    req.prompt += extra_prompt
+                    async for _ in self.process(event, _nested=True):
+                        yield
+                else:
+                    if llm_response.completion_text:
+                        event.set_result(MessageEventResult().message(llm_response.completion_text))
+
+        except BaseException 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)}"))
+            return
+        
+    async def _save_to_history(self, event: AstrMessageEvent, req: ProviderRequest, llm_response: LLMResponse):
+        if llm_response.role == "assistant":
+            # 文本回复
+            contexts = req.contexts
+            new_record = {
+                "role": "user",
+                "content": req.prompt
+            }
+            contexts.append(new_record)
+            contexts.append({
+                "role": "assistant",
+                "content": llm_response.completion_text
+            })
+            contexts_to_save = list(filter(lambda item: '_no_save' not in item, contexts))
+            await self.conv_manager.update_conversation(
+                event.unified_msg_origin, 
+                req.conversation.cid, 
+                history=contexts_to_save
+            )

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

@@ -0,0 +1,49 @@
+'''
+本地 Agent 模式的 AstrBot 插件调用 Stage
+'''
+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
+from astrbot.core.message.message_event_result import MessageEventResult
+from astrbot.core import logger
+from astrbot.core.star.star_handler import StarHandlerMetadata
+from astrbot.core.star.star import star_map
+import traceback
+
+class StarRequestSubStage(Stage):
+    
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.curr_provider = ctx.plugin_manager.context.get_using_provider()
+        self.prompt_prefix = ctx.astrbot_config['provider_settings']['prompt_prefix']
+        self.identifier = ctx.astrbot_config['provider_settings']['identifier']
+        self.ctx = ctx
+        
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        activated_handlers: List[StarHandlerMetadata] = event.get_extra("activated_handlers")
+        handlers_parsed_params: Dict[str, Dict[str, Any]] = event.get_extra("handlers_parsed_params")
+        if not handlers_parsed_params:
+            handlers_parsed_params = {}
+        for handler in activated_handlers:
+            params = handlers_parsed_params.get(handler.handler_full_name, {})
+            try:
+                if handler.handler_module_path not in star_map:
+                    # 孤立无援的 star handler 
+                    continue
+                
+                logger.debug(f"执行插件 handler {handler.handler_full_name}")
+                wrapper = self._call_handler(self.ctx, event, handler.handler, **params)
+                async for ret in wrapper:
+                    yield ret
+                event.clear_result() # 清除上一个 handler 的结果
+            except Exception as e:
+                logger.error(traceback.format_exc())
+                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 {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()
+                
+                event.stop_event()

astrbot/core/pipeline/process_stage/stage.py

@@ -0,0 +1,59 @@
+from typing import List, Union, AsyncGenerator
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from .method.llm_request import LLMRequestSubStage
+from .method.star_request import StarRequestSubStage
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.star.star_handler import StarHandlerMetadata
+from astrbot.core.provider.entites import ProviderRequest
+from astrbot.core import logger
+
+@register_stage
+class ProcessStage(Stage):
+    
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.ctx = ctx
+        self.config = ctx.astrbot_config
+        self.plugin_manager = ctx.plugin_manager
+        self.llm_request_sub_stage = LLMRequestSubStage()
+        await self.llm_request_sub_stage.initialize(ctx)
+        
+        self.star_request_sub_stage = StarRequestSubStage()
+        await self.star_request_sub_stage.initialize(ctx)
+
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        '''处理事件
+        '''
+        activated_handlers: List[StarHandlerMetadata] = event.get_extra("activated_handlers")
+        # 有插件 Handler 被激活
+        if activated_handlers:
+            async for resp in self.star_request_sub_stage.process(event):
+                # 生成器返回值处理
+                if isinstance(resp, ProviderRequest):
+                    # Handler 的 LLM 请求
+                    event.set_extra("provider_request", resp)
+                    _t = False
+                    async for _ in self.llm_request_sub_stage.process(event):
+                        _t = True
+                        yield
+                    if not _t:
+                        yield
+                else:
+                    yield
+        
+        # 调用 LLM 相关请求
+        if not self.ctx.astrbot_config['provider_settings'].get('enable', True):
+            return
+        
+        if not event._has_send_oper and event.is_at_or_wake_command:
+            # 是否有过发送操作 and 是否是被 @ 或者通过唤醒前缀
+            if (event.get_result() and not event.get_result().is_stopped()) or not event.get_result():
+                # 事件没有终止传播
+                provider = self.ctx.plugin_manager.context.get_using_provider()
+                
+                if not provider:
+                    logger.info("未找到可用的 LLM 提供商，请先前往配置服务提供商。")
+                    return
+                
+                async for _ in self.llm_request_sub_stage.process(event):
+                    yield

astrbot/core/pipeline/rate_limit_check/stage.py

@@ -0,0 +1,88 @@
+import asyncio
+from datetime import datetime, timedelta
+from collections import defaultdict, deque
+from typing import DefaultDict, Deque, Union, AsyncGenerator
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.message.message_event_result import MessageEventResult
+from astrbot.core import logger
+from astrbot.core.config.astrbot_config import RateLimitStrategy
+
+
+@register_stage
+class RateLimitStage(Stage):
+    """
+    检查是否需要限制消息发送的限流器。
+
+    使用 Fixed Window 算法。
+    如果触发限流，将 stall 流水线，直到下一个时间窗口来临时自动唤醒。
+    """
+
+    def __init__(self):
+        # 存储每个会话的请求时间队列
+        self.event_timestamps: DefaultDict[str, Deque[datetime]] = defaultdict(deque)
+        # 为每个会话设置一个锁，避免并发冲突
+        self.locks: DefaultDict[str, asyncio.Lock] = defaultdict(asyncio.Lock)
+        # 限流参数
+        self.rate_limit_count: int = 0
+        self.rate_limit_time: timedelta = timedelta(0)
+
+    async def initialize(self, ctx: PipelineContext) -> None:
+        """
+        初始化限流器，根据配置设置限流参数。
+        """
+        self.rate_limit_count = ctx.astrbot_config['platform_settings']['rate_limit']['count']
+        self.rate_limit_time = timedelta(seconds=ctx.astrbot_config['platform_settings']['rate_limit']['time'])
+        self.rl_strategy = ctx.astrbot_config['platform_settings']['rate_limit']['strategy'] # stall or discard
+
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        """
+        检查并处理限流逻辑。如果触发限流，流水线会 stall 并在窗口期后自动恢复。
+
+        Args:
+            event (AstrMessageEvent): 当前消息事件。
+            ctx (PipelineContext): 流水线上下文。
+
+        Returns:
+            MessageEventResult: 继续或停止事件处理的结果。
+        """
+        session_id = event.session_id
+        now = datetime.now()
+
+        async with self.locks[session_id]:  # 确保同一会话不会并发修改队列
+            timestamps = self.event_timestamps[session_id]
+
+            self._remove_expired_timestamps(timestamps, now)
+
+            if len(timestamps) >= self.rate_limit_count:
+                # 达到限流阈值，计算下一个窗口的时间
+                next_window_time = timestamps[0] + self.rate_limit_time
+                stall_duration = (next_window_time - now).total_seconds()
+                
+                match self.rl_strategy:
+                    case RateLimitStrategy.STALL.value:
+                        logger.info(f"会话 {session_id} 被限流。根据限流策略，此会话处理将被暂停 {stall_duration:.2f} 秒。")
+                        await asyncio.sleep(stall_duration)
+                    case RateLimitStrategy.DISCARD.value:
+                        # event.set_result(MessageEventResult().message(f"会话 {session_id} 被限流。根据限流策略，此请求已被丢弃，直到您的限额于 {stall_duration:.2f} 秒后重置。"))
+                        logger.info(f"会话 {session_id} 被限流。根据限流策略，此请求已被丢弃，直到限额于 {stall_duration:.2f} 秒后重置。")
+                        return event.stop_event()
+                
+                self._remove_expired_timestamps(timestamps, now + timedelta(seconds=stall_duration))
+
+            timestamps.append(now)
+
+        return event.continue_event()
+
+    def _remove_expired_timestamps(self, timestamps: Deque[datetime], now: datetime) -> None:
+        """
+        移除时间窗口外的时间戳。
+
+        Args:
+            timestamps (Deque[datetime]): 当前会话的时间戳队列。
+            now (datetime): 当前时间，用于计算过期时间。
+        """
+        expiry_threshold: datetime = now - self.rate_limit_time
+        while timestamps and timestamps[0] < expiry_threshold:
+            timestamps.popleft() 

astrbot/core/pipeline/respond/stage.py

@@ -0,0 +1,97 @@
+import random
+import asyncio
+import math
+import traceback
+from typing import Union, AsyncGenerator
+from ..stage import register_stage, Stage
+from ..context import PipelineContext
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core import logger
+from astrbot.core.message.message_event_result import BaseMessageComponent
+from astrbot.core.star.star_handler import star_handlers_registry, EventType
+from astrbot.core.message.components import Plain, Reply, At
+@register_stage
+class RespondStage(Stage):
+    async def initialize(self, ctx: PipelineContext):
+        self.ctx = ctx
+        
+        self.reply_with_mention = ctx.astrbot_config['platform_settings']['reply_with_mention']
+        self.reply_with_quote = ctx.astrbot_config['platform_settings']['reply_with_quote']
+        
+        # 分段回复
+        self.enable_seg: bool = ctx.astrbot_config['platform_settings']['segmented_reply']['enable']
+        self.only_llm_result = ctx.astrbot_config['platform_settings']['segmented_reply']['only_llm_result']
+        
+        self.interval_method = ctx.astrbot_config['platform_settings']['segmented_reply']['interval_method']
+        self.log_base = float(ctx.astrbot_config['platform_settings']['segmented_reply']['log_base'])
+        interval_str: str = ctx.astrbot_config['platform_settings']['segmented_reply']['interval']
+        interval_str_ls = interval_str.replace(" ", "").split(",")
+        try:
+            self.interval = [float(t) for t in interval_str_ls]
+        except BaseException as e:
+            logger.error(f'解析分段回复的间隔时间失败。{e}')
+            self.interval = [1.5, 3.5]
+        logger.info(f"分段回复间隔时间：{self.interval}")
+        
+    async def _word_cnt(self, text: str) -> int:
+        '''分段回复 统计字数'''
+        if all(ord(c) < 128 for c in text):
+            word_count = len(text.split())
+        else:
+            word_count = len([c for c in text if c.isalnum()])
+        return word_count
+    
+    async def _calc_comp_interval(self, comp: BaseMessageComponent) -> float:
+        '''分段回复 计算间隔时间'''
+        if self.interval_method == 'log':
+            if isinstance(comp, Plain):
+                wc = await self._word_cnt(comp.text)
+                i = math.log(wc + 1, self.log_base)
+                return random.uniform(i, i + 0.5)
+            else:
+                return random.uniform(1, 1.75)
+        else:
+            # random
+            return random.uniform(self.interval[0], self.interval[1])
+
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        result = event.get_result()
+        if result is None:
+            return
+
+        if len(result.chain) > 0:
+            await event._pre_send()
+            
+            if self.enable_seg and ((self.only_llm_result and result.is_llm_result()) or not self.only_llm_result):
+                decorated_comps = []
+                if self.reply_with_mention:
+                    for comp in result.chain:
+                        if isinstance(comp, At):
+                            decorated_comps.append(comp)
+                            result.chain.remove(comp)
+                            break
+                if self.reply_with_quote:
+                    for comp in result.chain:
+                        if isinstance(comp, Reply):
+                            decorated_comps.append(comp)
+                            result.chain.remove(comp)
+                            break
+                # 分段回复
+                for comp in result.chain:
+                    i = await self._calc_comp_interval(comp)
+                    await asyncio.sleep(i)
+                    await event.send(MessageChain([*decorated_comps, comp]))
+            else:
+                await event.send(result)
+            await event._post_send()
+            logger.info(f"AstrBot -> {event.get_sender_name()}/{event.get_sender_id()}: {event._outline_chain(result.chain)}")
+        
+        handlers = star_handlers_registry.get_handlers_by_event_type(EventType.OnAfterMessageSentEvent)
+        for handler in handlers:
+            try:
+                await handler.handler(event)
+            except BaseException:
+                logger.error(traceback.format_exc())
+            
+        event.clear_result()

astrbot/core/pipeline/result_decorate/stage.py

@@ -0,0 +1,180 @@
+import time
+import re
+import traceback
+from typing import Union, AsyncGenerator
+from ..stage import Stage, register_stage, registered_stages
+from ..context import PipelineContext
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.platform.message_type import MessageType
+from astrbot.core import logger
+from astrbot.core.message.components import Plain, Image, At, Reply, Record, File, Node
+from astrbot.core import html_renderer
+from astrbot.core.star.star_handler import star_handlers_registry, EventType
+
+@register_stage
+class ResultDecorateStage(Stage):
+    async def initialize(self, ctx: PipelineContext):
+        self.ctx = ctx
+        self.reply_prefix = ctx.astrbot_config['platform_settings']['reply_prefix']
+        self.reply_with_mention = ctx.astrbot_config['platform_settings']['reply_with_mention']
+        self.reply_with_quote = ctx.astrbot_config['platform_settings']['reply_with_quote']
+        self.t2i_word_threshold = ctx.astrbot_config['t2i_word_threshold']
+        try:
+            self.t2i_word_threshold = int(self.t2i_word_threshold)
+            if self.t2i_word_threshold < 50:
+                self.t2i_word_threshold = 50
+        except BaseException:
+            self.t2i_word_threshold = 150
+            
+        self.forward_threshold = ctx.astrbot_config['platform_settings']['forward_threshold']
+        
+        # 分段回复
+        self.words_count_threshold = int(ctx.astrbot_config['platform_settings']['segmented_reply']['words_count_threshold'])
+        self.enable_segmented_reply = ctx.astrbot_config['platform_settings']['segmented_reply']['enable']
+        self.only_llm_result = ctx.astrbot_config['platform_settings']['segmented_reply']['only_llm_result']
+        self.regex = ctx.astrbot_config['platform_settings']['segmented_reply']['regex']
+        self.content_cleanup_rule = ctx.astrbot_config['platform_settings']['segmented_reply']['content_cleanup_rule']
+
+        
+        # exception
+        self.content_safe_check_reply = ctx.astrbot_config['content_safety']['also_use_in_response']
+        self.content_safe_check_stage = None
+        if self.content_safe_check_reply:
+            for stage in registered_stages:
+                if stage.__class__.__name__ == "ContentSafetyCheckStage":
+                    self.content_safe_check_stage = stage
+                    
+            
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        result = event.get_result()
+        if result is None:
+            return
+        
+        # 回复时检查内容安全
+        if self.content_safe_check_reply and self.content_safe_check_stage and result.is_llm_result():
+            text = ""
+            for comp in result.chain:
+                if isinstance(comp, Plain):
+                    text += comp.text
+            async for _ in self.content_safe_check_stage.process(event, check_text=text):
+                yield
+        
+        # 发送消息前事件钩子
+        handlers = star_handlers_registry.get_handlers_by_event_type(EventType.OnDecoratingResultEvent)
+        for handler in handlers:
+            try:
+                await handler.handler(event)
+            except BaseException:
+                logger.error(traceback.format_exc())
+            
+        # 需要再获取一次。插件可能直接对 chain 进行了替换。
+        result = event.get_result()
+        if result is None:
+            return
+        
+        if len(result.chain) > 0:
+            # 回复前缀
+            if self.reply_prefix:
+                for comp in result.chain:
+                    if isinstance(comp, Plain):
+                        comp.text = self.reply_prefix + comp.text
+                        break
+            
+             # 分段回复 
+            if self.enable_segmented_reply:
+                if (self.only_llm_result and result.is_llm_result()) or not self.only_llm_result:
+                    new_chain = []
+                    for comp in result.chain:
+                        if isinstance(comp, Plain):
+                            if len(comp.text) > self.words_count_threshold:
+                                # 不分段回复
+                                new_chain.append(comp)
+                                continue
+                            split_response = []
+                            for line in comp.text.split("\n"):
+                                split_response.extend(re.findall(self.regex, line))
+                            if not split_response:
+                                new_chain.append(comp)
+                                continue
+                            for seg in split_response:
+                                if self.content_cleanup_rule:
+                                    seg = re.sub(self.content_cleanup_rule, "", seg)
+                                if seg.strip():
+                                    new_chain.append(Plain(seg))
+                        else:
+                            # 非 Plain 类型的消息段不分段
+                            new_chain.append(comp)
+                    result.chain = new_chain
+                
+            # TTS
+            if self.ctx.astrbot_config['provider_tts_settings']['enable'] and result.is_llm_result():
+                tts_provider = self.ctx.plugin_manager.context.provider_manager.curr_tts_provider_inst
+                new_chain = []
+                for comp in result.chain:
+                    if isinstance(comp, Plain) and len(comp.text) > 1:
+                        try:
+                            logger.info("TTS 请求: " + comp.text)
+                            audio_path = await tts_provider.get_audio(comp.text)
+                            logger.info("TTS 结果: " + audio_path)
+                            if audio_path:
+                                new_chain.append(Record(file=audio_path, url=audio_path))
+                            else:
+                                logger.error(f"由于 TTS 音频文件没找到，消息段转语音失败: {comp.text}")
+                                new_chain.append(comp)
+                        except BaseException:
+                            logger.error(traceback.format_exc())
+                            logger.error("TTS 失败，使用文本发送。")
+                            new_chain.append(comp)
+                    else:
+                        new_chain.append(comp)
+                result.chain = new_chain
+            
+            # 文本转图片
+            elif (result.use_t2i_ is None and self.ctx.astrbot_config['t2i']) or result.use_t2i_:
+                plain_str = ""
+                for comp in result.chain:
+                    if isinstance(comp, Plain):
+                        plain_str += "\n\n" + comp.text
+                    else:
+                        break
+                if plain_str and len(plain_str) > self.t2i_word_threshold:
+                    render_start = time.time()
+                    try:
+                        url = await html_renderer.render_t2i(plain_str, return_url=True)
+                    except BaseException:
+                        logger.error("文本转图片失败，使用文本发送。")
+                        return
+                    if time.time() - render_start > 3:
+                        logger.warning("文本转图片耗时超过了 3 秒，如果觉得很慢可以使用 /t2i 关闭文本转图片模式。")
+                    if url:
+                        result.chain = [Image.fromURL(url)]
+            
+            # 触发转发消息
+            has_forwarded = False
+            if event.get_platform_name() == 'aiocqhttp':
+                word_cnt = 0
+                for comp in result.chain:
+                    if isinstance(comp, Plain):
+                        word_cnt += len(comp.text)
+                if word_cnt > self.forward_threshold:
+                    node = Node(
+                        uin=event.get_self_id(),
+                        name="AstrBot",
+                        content=[
+                            *result.chain
+                        ]
+                    )
+                    result.chain = [node]
+                    has_forwarded = True
+            
+            if not has_forwarded:
+                # at 回复
+                if self.reply_with_mention and event.get_message_type() != MessageType.FRIEND_MESSAGE:
+                    result.chain.insert(0, At(qq=event.get_sender_id(), name=event.get_sender_name()))
+                    if len(result.chain) > 1 and isinstance(result.chain[1], Plain):
+                        result.chain[1].text = "\n" + result.chain[1].text
+                
+                # 引用回复
+                if self.reply_with_quote:
+                    if not any(isinstance(item, File) for item in result.chain):
+                        result.chain.insert(0, Reply(id=event.message_obj.message_id))

astrbot/core/pipeline/scheduler.py

@@ -0,0 +1,48 @@
+from . import STAGES_ORDER
+from .stage import registered_stages
+from .context import PipelineContext
+from typing import AsyncGenerator
+from astrbot.core.platform import AstrMessageEvent
+from astrbot.core import logger
+
+class PipelineScheduler():
+    def __init__(self, context: PipelineContext):
+        registered_stages.sort(key=lambda x: STAGES_ORDER.index(x.__class__ .__name__))
+        self.ctx = context
+        
+    async def initialize(self):
+        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):
+        for i in range(from_stage, len(registered_stages)):
+            stage = registered_stages[i]
+            # logger.debug(f"执行阶段 {stage.__class__ .__name__}")
+            coro = stage.process(event)
+            if isinstance(coro, AsyncGenerator):
+                async for _ in coro:
+                    if event.is_stopped():
+                        logger.debug(f"阶段 {stage.__class__ .__name__} 已终止事件传播。")
+                        break
+                    await self._process_stages(event, i + 1)
+            else:
+                await coro
+
+                if event.is_stopped():
+                    logger.debug(f"阶段 {stage.__class__ .__name__} 已终止事件传播。")
+                    break
+
+            if event.is_stopped():
+                logger.debug(f"阶段 {stage.__class__ .__name__} 已终止事件传播。")
+                break
+    
+    async def execute(self, event: AstrMessageEvent):
+        '''执行 pipeline'''
+        await self._process_stages(event)
+        
+        if not event._has_send_oper and event.get_platform_name() == "webchat":
+            await event.send(None)
+        
+        logger.debug("pipeline 执行完毕。")

astrbot/core/pipeline/stage.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+import abc
+import inspect
+from astrbot.api import logger
+from typing import List, AsyncGenerator, Union, Awaitable
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from .context import PipelineContext
+from astrbot.core.message.message_event_result import MessageEventResult, CommandResult
+
+registered_stages: List[Stage] = []
+'''维护了所有已注册的 Stage 实现类'''
+
+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())
+    return cls
+    
+class Stage(abc.ABC):
+    '''描述一个 Pipeline 的某个阶段
+    '''
+    
+    @abc.abstractmethod
+    async def initialize(self, ctx: PipelineContext) -> None:
+        '''初始化阶段
+        '''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        '''处理事件
+        '''
+        raise NotImplementedError
+    
+    async def _call_handler(
+        self, 
+        ctx: PipelineContext,
+        event: AstrMessageEvent, 
+        handler: Awaitable,
+        *args,
+        **kwargs,
+    ) -> AsyncGenerator[None, None]:
+        '''调用 Handler。'''
+        # 判断 handler 是否是类方法（通过装饰器注册的没有 __self__ 属性）
+        ready_to_call = None
+        try:
+            ready_to_call = handler(event, *args, **kwargs)
+        except TypeError as e:
+            # 向下兼容
+            logger.debug(str(e))
+            ready_to_call = handler(event, ctx.plugin_manager.context, *args, **kwargs)
+        
+        if isinstance(ready_to_call, AsyncGenerator):
+            async for ret in ready_to_call:
+                # 如果处理函数是生成器，返回值只能是 MessageEventResult 或者 None（无返回值）
+                if isinstance(ret, (MessageEventResult, CommandResult)):
+                    event.set_result(ret)
+                    yield
+                else:
+                    yield ret
+        elif inspect.iscoroutine(ready_to_call):
+            # 如果只是一个 coroutine
+            ret = await ready_to_call
+            if isinstance(ret, (MessageEventResult, CommandResult)):
+                event.set_result(ret)
+                yield
+            else:
+                yield ret

astrbot/core/pipeline/waking_check/stage.py

@@ -0,0 +1,128 @@
+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.message.message_event_result import MessageEventResult, MessageChain
+from astrbot.core.message.components import At, Reply
+from astrbot.core.star.star_handler import star_handlers_registry, EventType
+from astrbot.core.star.star import star_map
+from astrbot.core.star.filter.command_group import CommandGroupFilter
+from astrbot.core.star.filter.permission import PermissionTypeFilter
+
+@register_stage
+class WakingCheckStage(Stage):
+    """检查是否需要唤醒。唤醒机器人有如下几点条件：
+
+    1. 机器人被 @ 了
+    2. 机器人的消息被提到了
+    3. 以 wake_prefix 前缀开头，并且消息没有以 At 消息段开头
+    4. 插件（Star）的 handler filter 通过
+    5. 私聊情况下，位于 admins_id 列表中的管理员的消息（在白名单阶段中）
+    """
+
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.ctx = ctx
+        self.no_permission_reply = self.ctx.astrbot_config["platform_settings"].get(
+            "no_permission_reply", True
+        )
+
+    async def process(
+        self, event: AstrMessageEvent
+    ) -> Union[None, AsyncGenerator[None, None]]:
+        # 设置 sender 身份
+        event.message_str = event.message_str.strip()
+        for admin_id in self.ctx.astrbot_config["admins_id"]:
+            if event.get_sender_id() == admin_id:
+                event.role = "admin"
+                break
+
+        # 检查 wake
+        wake_prefixes = self.ctx.astrbot_config["wake_prefix"]
+        messages = event.get_messages()
+        is_wake = False
+        for wake_prefix in wake_prefixes:
+            if event.message_str.startswith(wake_prefix):
+                if (
+                    not event.is_private_chat()
+                    and isinstance(messages[0], At)
+                    and str(messages[0].qq) != str(event.get_self_id())
+                    and str(messages[0].qq) != "all"
+                ):
+                    # 如果是群聊，且第一个消息段是 At 消息，但不是 At 机器人或 At 全体成员，则不唤醒
+                    break
+                is_wake = True
+                event.is_at_or_wake_command = True
+                event.is_wake = True
+                event.message_str = event.message_str[len(wake_prefix) :].strip()
+                break
+        if not is_wake:
+            # 检查是否有 at 消息
+            for message in messages:
+                if isinstance(message, At) and (
+                    str(message.qq) == str(event.get_self_id())
+                    or str(message.qq) == "all"
+                ):
+                    is_wake = True
+                    event.is_wake = True
+                    wake_prefix = ""
+                    event.is_at_or_wake_command = True
+                    break
+            # 检查是否是私聊
+            if event.is_private_chat():
+                is_wake = True
+                event.is_wake = True
+                event.is_at_or_wake_command = True
+                wake_prefix = ""
+
+        # 检查插件的 handler filter
+        activated_handlers = []
+        handlers_parsed_params = {}  # 注册了指令的 handler
+        
+        for handler in star_handlers_registry.get_handlers_by_event_type(EventType.AdapterMessageEvent):
+            # filter 需满足 AND 逻辑关系
+            passed = True            
+            permission_not_pass = False
+            if len(handler.event_filters) == 0:
+                continue
+
+            for filter in handler.event_filters:
+                try:
+                    if isinstance(filter, PermissionTypeFilter):
+                        if not filter.filter(event, self.ctx.astrbot_config):
+                            permission_not_pass = True
+                    else:
+                        if not filter.filter(event, self.ctx.astrbot_config):
+                            passed = False
+                            break
+                except Exception as e:
+                    await event.send(
+                        MessageEventResult().message(
+                            f"插件 {star_map[handler.handler_module_path].name}: {e}"
+                        )
+                    )
+                    event.stop_event()
+                    passed = False
+                    break
+            if passed:
+                if permission_not_pass:
+                    if self.no_permission_reply:
+                        await event.send(MessageChain().message(f"ID {event.get_sender_id()} 权限不足。通过 /sid 获取 ID 并请管理员添加。"))
+                    event.stop_event()
+                    return
+                
+                is_wake = True
+                event.is_wake = True
+
+                activated_handlers.append(handler)
+                if "parsed_params" in event.get_extra():
+                    handlers_parsed_params[handler.handler_full_name] = event.get_extra(
+                        "parsed_params"
+                    )
+                    
+            event.clear_extra()
+
+        event.set_extra("activated_handlers", activated_handlers)
+        event.set_extra("handlers_parsed_params", handlers_parsed_params)
+
+        if not is_wake:
+            event.stop_event()

astrbot/core/pipeline/whitelist_check/stage.py

@@ -0,0 +1,42 @@
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from typing import AsyncGenerator, Union
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.platform.message_type import MessageType
+from astrbot.core import logger
+
+@register_stage
+class WhitelistCheckStage(Stage):
+    '''检查是否在群聊/私聊白名单
+    '''
+    async def initialize(self, ctx: PipelineContext) -> None:
+        self.enable_whitelist_check = ctx.astrbot_config['platform_settings']['enable_id_white_list']
+        self.whitelist = ctx.astrbot_config['platform_settings']['id_whitelist']
+        self.wl_ignore_admin_on_group = ctx.astrbot_config['platform_settings']['wl_ignore_admin_on_group']
+        self.wl_ignore_admin_on_friend = ctx.astrbot_config['platform_settings']['wl_ignore_admin_on_friend']    
+        self.wl_log = ctx.astrbot_config['platform_settings']['id_whitelist_log']
+        
+    async def process(self, event: AstrMessageEvent) -> Union[None, AsyncGenerator[None, None]]:
+        if not self.enable_whitelist_check:
+            # 白名单检查未启用
+            return
+        
+        if len(self.whitelist) == 0:
+            # 白名单为空，不检查
+            return
+        
+        if event.get_platform_name() == 'webchat':
+            # WebChat 豁免
+            return
+        
+        # 检查是否在白名单
+        if self.wl_ignore_admin_on_group:
+            if event.role == 'admin' and event.get_message_type() == MessageType.GROUP_MESSAGE:
+                return
+        if self.wl_ignore_admin_on_friend:
+            if event.role == 'admin' and event.get_message_type() == MessageType.FRIEND_MESSAGE:
+                return
+        if event.unified_msg_origin not in self.whitelist:
+            if self.wl_log:
+                logger.info(f"会话 ID {event.unified_msg_origin} 不在会话白名单中，已终止事件传播。请在配置文件中添加该会话 ID 到白名单。")
+            event.stop_event()

astrbot/core/platform/__init__.py

@@ -0,0 +1,4 @@
+from .platform import Platform
+from .astr_message_event import AstrMessageEvent
+from .platform_metadata import PlatformMetadata
+from .astrbot_message import AstrBotMessage, MessageMember, MessageType

astrbot/core/platform/astr_message_event.py

@@ -0,0 +1,335 @@
+import abc
+from dataclasses import dataclass
+from .astrbot_message import AstrBotMessage
+from .platform_metadata import PlatformMetadata
+from astrbot.core.message.message_event_result import MessageEventResult, MessageChain
+from astrbot.core.platform.message_type import MessageType
+from typing import List, Union
+from astrbot.core.message.components import Plain, Image, BaseMessageComponent, Face, At, AtAll, Forward
+from astrbot.core.utils.metrics import Metric
+from astrbot.core.provider.entites import ProviderRequest
+from astrbot.core.db.po import Conversation
+
+@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):
+    def __init__(self, 
+                message_str: str,
+                message_obj: AstrBotMessage,
+                platform_meta: PlatformMetadata,
+                session_id: str,):
+        self.message_str = message_str
+        '''纯文本的消息'''
+        self.message_obj = message_obj
+        '''消息对象，AstrBotMessage。带有完整的消息结构。'''
+        self.platform_meta = platform_meta
+        '''消息平台的信息, 其中 name 是平台的类型，如 aiocqhttp'''
+        self.session_id = session_id
+        '''用户的会话 ID。可以直接使用下面的 unified_msg_origin'''
+        self.role = "member"
+        '''用户是否是管理员。如果是管理员，这里是 admin'''
+        self.is_wake = False # 是否通过 WakingStage
+        '''是否唤醒'''
+        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（事件监听器会让 is_wake 设为 True，但是不会让这个属性置为 True）'''
+        self._extras = {}
+        self.session = MessageSesion(
+            platform_name=platform_meta.name,
+            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
+        '''消息事件的结果'''
+        
+        self._has_send_oper = False 
+        '''是否有过至少一次发送操作'''
+        
+        
+        # back_compability
+        self.platform = platform_meta
+    
+    def get_platform_name(self):
+        return self.platform_meta.name
+    
+    def get_message_str(self) -> str:
+        '''
+        获取消息字符串。
+        '''
+        return self.message_str
+    
+    def _outline_chain(self, chain: List[BaseMessageComponent]) -> str:
+        outline = ""
+        for i in chain:
+            if isinstance(i, Plain):
+                outline += i.text
+            elif isinstance(i, Image):
+                outline += "[图片]"
+            elif isinstance(i, Face):
+                outline += f"[表情:{i.id}]"
+            elif isinstance(i, At):
+                outline += f"[At:{i.qq}]"
+            elif isinstance(i, AtAll):
+                outline += "[At:全体成员]"
+            elif isinstance(i, Forward):
+                # 转发消息
+                outline += "[转发消息]"
+            else:
+                outline += f"[{i.type}]"
+        return outline
+    
+    def get_message_outline(self) -> str:
+        '''
+        获取消息概要。
+        
+        除了文本消息外，其他消息类型会被转换为对应的占位符。如图片消息会被转换为 [图片]。
+        '''
+        return self._outline_chain(self.message_obj.message)
+    
+    def get_messages(self) -> List[BaseMessageComponent]:
+        '''
+        获取消息链。
+        '''
+        return self.message_obj.message
+    
+    def get_message_type(self) -> MessageType:
+        '''
+        获取消息类型。
+        '''
+        return self.message_obj.type
+    
+    def get_session_id(self) -> str:
+        '''
+        获取会话id。
+        '''
+        return self.session_id
+    
+    def get_group_id(self) -> str:
+        '''
+        获取群组id。如果不是群组消息，返回空字符串。
+        '''
+        return self.message_obj.group_id
+    
+    def get_self_id(self) -> str:
+        '''
+        获取机器人自身的id。
+        '''
+        return self.message_obj.self_id
+    
+    def get_sender_id(self) -> str:
+        '''
+        获取消息发送者的id。
+        '''
+        return self.message_obj.sender.user_id
+    
+    def get_sender_name(self) -> str:
+        '''
+        获取消息发送者的名称。(可能会返回空字符串)
+        '''
+        return self.message_obj.sender.nickname
+        
+    def set_extra(self, key, value):
+        '''
+        设置额外的信息。
+        '''
+        self._extras[key] = value
+        
+    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, None)
+    
+    def clear_extra(self):
+        '''
+        清除额外的信息。
+        '''
+        self._extras.clear()
+        
+    def is_private_chat(self) -> bool:
+        '''
+        是否是私聊。
+        '''
+        return self.message_obj.type.value == (MessageType.FRIEND_MESSAGE).value
+    
+    def is_wake_up(self) -> bool:
+        '''
+        是否是唤醒机器人的事件。
+        '''
+        return self.is_wake
+    
+    def is_admin(self) -> bool:
+        '''
+        是否是管理员。
+        '''
+        return self.role == "admin"
+    
+    async def send(self, message: MessageChain):
+        '''
+        发送消息到消息平台。
+        '''
+        await Metric.upload(msg_event_tick = 1, adapter_name = self.platform_meta.name)
+        self._has_send_oper = True
+        
+    async def _pre_send(self):
+        '''调度器会在执行 send() 前调用该方法'''
+        pass
+    
+    async def _post_send(self):
+        '''调度器会在执行 send() 后调用该方法'''
+        pass
+        
+        
+    def set_result(self, result: Union[MessageEventResult, str]):
+        '''设置消息事件的结果。
+        
+        Note:
+            事件处理器可以通过设置结果来控制事件是否继续传播，并向消息适配器发送消息。
+            
+            如果没有设置 `MessageEventResult` 中的 result_type，默认为 CONTINUE。即事件将会继续向后面的 listener 或者 command 传播。
+        
+        Example:
+        ```
+        async def ban_handler(self, event: AstrMessageEvent):
+            if event.get_sender_id() in self.blacklist:
+                event.set_result(MessageEventResult().set_console_log("由于用户在黑名单，因此消息事件中断处理。")).set_result_type(EventResultType.STOP)
+                return
+            
+        async def check_count(self, event: AstrMessageEvent):
+            self.count += 1
+            event.set_result(MessageEventResult().set_console_log("数量已增加", logging.DEBUG).set_result_type(EventResultType.CONTINUE))
+            return
+        ```
+        '''
+        if isinstance(result, str):
+            result = MessageEventResult().message(result)
+        self._result = result
+        
+    def stop_event(self):
+        '''终止事件传播。
+        '''
+        if self._result is None:
+            self.set_result(MessageEventResult().stop_event())
+        else:
+            self._result.stop_event()
+        
+    def continue_event(self):
+        '''继续事件传播。
+        '''
+        if self._result is None:
+            self.set_result(MessageEventResult().continue_event())
+        else:
+            self._result.continue_event()
+            
+    def is_stopped(self) -> bool:
+        '''
+        是否终止事件传播。
+        '''
+        if self._result is None:
+            return False # 默认是继续传播
+        return self._result.is_stopped()        
+        
+    def get_result(self) -> MessageEventResult:
+        '''
+        获取消息事件的结果。
+        '''
+        return self._result
+    
+    def clear_result(self):
+        '''
+        清除消息事件的结果。
+        '''
+        self._result = None
+    
+    '''消息链相关'''
+    
+    def make_result(self) -> MessageEventResult:
+        '''
+        创建一个空的消息事件结果。
+        
+        Example:
+        
+        ```python
+        # 纯文本回复
+        yield event.make_result().message("Hi")
+        # 发送图片
+        yield event.make_result().url_image("https://example.com/image.jpg")
+        yield event.make_result().file_image("image.jpg")
+        ```
+        '''
+        return MessageEventResult()
+    
+    def plain_result(self, text: str) -> MessageEventResult:
+        '''
+        创建一个空的消息事件结果，只包含一条文本消息。
+        '''
+        return MessageEventResult().message(text)
+    
+    def image_result(self, url_or_path: str) -> MessageEventResult:
+        '''
+        创建一个空的消息事件结果，只包含一条图片消息。
+        
+        根据开头是否包含 http 来判断是网络图片还是本地图片。
+        '''
+        if url_or_path.startswith("http"):
+            return MessageEventResult().url_image(url_or_path)
+        return MessageEventResult().file_image(url_or_path)
+    
+    def chain_result(self, chain: List[BaseMessageComponent]) -> MessageEventResult:
+        '''
+        创建一个空的消息事件结果，包含指定的消息链。
+        '''
+        mer = MessageEventResult()
+        mer.chain = chain
+        return mer
+    
+    '''LLM 请求相关'''
+    
+    def request_llm(
+        self,
+        prompt: str,
+        func_tool_manager = None,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        contexts: List = [],
+        system_prompt: str = "",
+        conversation: Conversation = None
+    ) -> ProviderRequest:
+        '''
+        创建一个 LLM 请求。
+        
+        Examples:
+        ```py
+        yield event.request_llm(prompt="hi")
+        ```
+        prompt: 提示词
+        session_id: 已经过时，留空即可
+        image_urls: 可以是 base64:// 或者 http:// 开头的图片链接，也可以是本地图片路径。
+        contexts: 当指定 contexts 时，将会使用 contexts 作为上下文。
+        func_tool_manager: 函数工具管理器，用于调用函数工具。用 self.context.get_llm_tool_manager() 获取。
+        conversation: 可选。如果指定，将在指定的对话中进行 LLM 请求。对话的人格会被用于 LLM 请求，并且结果将会被记录到对话中。
+        '''
+        return ProviderRequest(
+            prompt = prompt,
+            session_id = session_id,
+            image_urls = image_urls,
+            func_tool = func_tool_manager,
+            contexts = contexts,
+            system_prompt = system_prompt,
+            conversation=conversation
+        )

astrbot/core/platform/astrbot_message.py

@@ -0,0 +1,31 @@
+import time
+from typing import List
+from dataclasses import dataclass
+from astrbot.core.message.components import BaseMessageComponent
+from .message_type import MessageType
+
+@dataclass
+class MessageMember():
+    user_id: str  # 发送者id
+    nickname: str = None
+
+class AstrBotMessage:
+    '''
+    AstrBot 的消息对象
+    '''
+    type: MessageType  # 消息类型
+    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_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
+    raw_message: object
+    timestamp: int  # 消息时间戳
+    
+    def __init__(self) -> None:
+        self.timestamp = int(time.time())
+
+    def __str__(self) -> str:
+        return str(self.__dict__)

astrbot/core/platform/manager.py

@@ -0,0 +1,53 @@
+from astrbot.core.config.astrbot_config import AstrBotConfig
+from .platform import Platform
+from typing import List
+from asyncio import Queue
+from .register import platform_cls_map
+from astrbot.core import logger
+from .sources.webchat.webchat_adapter import WebChatAdapter
+
+class PlatformManager():
+    def __init__(self, config: AstrBotConfig, event_queue: Queue):
+        self.platform_insts: List[Platform] = []
+        '''加载的 Platform 的实例'''
+        
+        self.platforms_config = config['platform']
+        self.settings = config['platform_settings']
+        self.event_queue = event_queue
+        
+        try:
+            for platform in self.platforms_config:
+                if not platform['enable']:
+                    continue
+                match platform['type']:
+                    case "aiocqhttp":
+                        from .sources.aiocqhttp.aiocqhttp_platform_adapter import AiocqhttpAdapter  # noqa: F401
+                    case "qq_official":
+                        from .sources.qqofficial.qqofficial_platform_adapter import QQOfficialPlatformAdapter # noqa: F401
+                    case "qq_official_webhook":
+                        from .sources.qqofficial_webhook.qo_webhook_adapter import QQOfficialWebhookPlatformAdapter # noqa: F401
+                    case "gewechat":
+                        from .sources.gewechat.gewechat_platform_adapter import GewechatPlatformAdapter # noqa: F401
+                    case "lark":
+                        from .sources.lark.lark_adapter import LarkPlatformAdapter # noqa: F401
+        except (ImportError, ModuleNotFoundError) as e:
+            logger.error(f"加载平台适配器 {platform['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。")
+        except Exception as e:
+            logger.error(f"加载平台适配器 {platform['type']} 失败，原因：{e}。")
+
+    async def initialize(self):
+        for platform in self.platforms_config:
+            if not platform['enable']:
+                continue
+            if platform['type'] not in platform_cls_map:
+                logger.error(f"未找到适用于 {platform['type']}({platform['id']}) 平台适配器，请检查是否已经安装或者名称填写错误。已跳过。")
+                continue
+            cls_type = platform_cls_map[platform['type']]
+            logger.debug(f"尝试实例化 {platform['type']}({platform['id']}) 平台适配器 ...")
+            inst = cls_type(platform, self.settings, self.event_queue)
+            self.platform_insts.append(inst)
+        
+        self.platform_insts.append(WebChatAdapter({}, self.settings, self.event_queue))
+                    
+    def get_insts(self):
+        return self.platform_insts

astrbot/core/platform/message_type.py

@@ -0,0 +1,6 @@
+from enum import Enum
+
+class MessageType(Enum):
+    GROUP_MESSAGE = 'GroupMessage'  # 群组形式的消息
+    FRIEND_MESSAGE = 'FriendMessage'  # 私聊、好友等单聊消息
+    OTHER_MESSAGE = 'OtherMessage'  # 其他类型的消息，如系统消息等

astrbot/core/platform/platform.py

@@ -0,0 +1,42 @@
+import abc
+from typing import Awaitable, Any
+from asyncio import Queue
+from .platform_metadata import PlatformMetadata
+from .astr_message_event import AstrMessageEvent
+from astrbot.core.message.message_event_result import MessageChain
+from .astr_message_event import MessageSesion
+from astrbot.core.utils.metrics import Metric
+
+class Platform(abc.ABC):
+    def __init__(self, event_queue: Queue):
+        super().__init__()
+        # 维护了消息平台的事件队列，EventBus 会从这里取出事件并处理。
+        self._event_queue = event_queue
+    
+    @abc.abstractmethod
+    def run(self) -> Awaitable[Any]:
+        '''
+        得到一个平台的运行实例，需要返回一个协程对象。
+        '''
+        raise NotImplementedError
+    
+    @abc.abstractmethod
+    def meta(self) -> PlatformMetadata:
+        '''
+        得到一个平台的元数据。
+        '''
+        raise NotImplementedError
+    
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain) -> Awaitable[Any]:
+        '''
+        通过会话发送消息。该方法旨在让插件能够直接通过**可持久化的会话数据**发送消息，而不需要保存 event 对象。
+        
+        异步方法。
+        '''            
+        await Metric.upload(msg_event_tick = 1, adapter_name = self.meta().name)
+    
+    def commit_event(self, event: AstrMessageEvent):
+        '''
+        提交一个事件到事件队列。
+        '''
+        self._event_queue.put_nowait(event)

astrbot/core/platform/platform_metadata.py

@@ -0,0 +1,12 @@
+from dataclasses import dataclass
+@dataclass
+class PlatformMetadata():
+    name: str
+    '''平台的名称'''
+    description: str
+    '''平台的描述'''
+    
+    default_config_tmpl: dict = None
+    '''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'''

astrbot/core/platform/register.py

@@ -0,0 +1,44 @@
+from typing import List, Dict, Type
+from .platform_metadata import PlatformMetadata
+from astrbot.core import logger
+
+platform_registry: List[PlatformMetadata] = []
+'''维护了通过装饰器注册的平台适配器'''
+platform_cls_map: Dict[str, Type] = {}
+'''维护了平台适配器名称和适配器类的映射'''
+
+def register_platform_adapter(
+    adapter_name: str, 
+    desc: str, 
+    default_config_tmpl: dict = None,
+    adapter_display_name: 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。 
+    '''
+    def decorator(cls):
+        if adapter_name in platform_cls_map:
+            raise ValueError(f"平台适配器 {adapter_name} 已经注册过了，可能发生了适配器命名冲突。")
+        
+        # 添加必备选项
+        if default_config_tmpl:
+            if 'type' not in default_config_tmpl:
+                default_config_tmpl['type'] = adapter_name
+            if 'enable' not in default_config_tmpl:
+                default_config_tmpl['enable'] = False
+            if 'id' not in default_config_tmpl:
+                default_config_tmpl['id'] = adapter_name
+
+        pm = PlatformMetadata(
+            name=adapter_name,
+            description=desc,
+            default_config_tmpl=default_config_tmpl,
+            adapter_display_name=adapter_display_name
+        )
+        platform_registry.append(pm)
+        platform_cls_map[adapter_name] = cls
+        logger.debug(f"平台适配器 {adapter_name} 已注册")
+        return cls
+    
+    return decorator

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

@@ -0,0 +1,60 @@
+import asyncio
+
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.message_components import Plain, Image, Record, At, Node, Music, Video
+from aiocqhttp import CQHttp
+from astrbot.core.utils.io import file_to_base64, download_image_by_url
+
+class AiocqhttpMessageEvent(AstrMessageEvent):
+    def __init__(self, message_str, message_obj, platform_meta, session_id, bot: CQHttp):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.bot = bot
+    
+    @staticmethod
+    async def _parse_onebot_json(message_chain: MessageChain):
+        '''解析成 OneBot json 格式'''
+        ret = []
+        for segment in message_chain.chain:
+            d = segment.toDict()
+            if isinstance(segment, Plain):
+                d['type'] = 'text'
+            elif isinstance(segment, (Image, Record)):
+                # convert to base64
+                if segment.file and segment.file.startswith("file:///"):
+                    bs64_data = file_to_base64(segment.file[8:])
+                    image_file_path = segment.file[8:]
+                elif segment.file and segment.file.startswith("http"):
+                    image_file_path = await download_image_by_url(segment.file)
+                    bs64_data = file_to_base64(image_file_path)
+                elif segment.file and segment.file.startswith("base64://"):
+                    bs64_data = segment.file
+                else:
+                    bs64_data = file_to_base64(segment.file)
+                d['data'] = {
+                    'file': bs64_data,
+                }
+            elif isinstance(segment, At):
+                d['data'] = {
+                    'qq': str(segment.qq) # 转换为字符串
+                }
+            ret.append(d)
+        return ret
+
+    async def send(self, message: MessageChain):
+        ret = await AiocqhttpMessageEvent._parse_onebot_json(message)
+        
+        send_one_by_one = False
+        for seg in message.chain:
+            if isinstance(seg, (Node, Music)):
+                # 转发消息不能和普通消息混在一起发送
+                send_one_by_one = True
+                break
+        
+        if send_one_by_one:
+            for seg in message.chain:
+                await self.bot.send(self.message_obj.raw_message, await AiocqhttpMessageEvent._parse_onebot_json(MessageChain([seg])))
+                await asyncio.sleep(0.5)
+        else:
+            await self.bot.send(self.message_obj.raw_message, ret)
+        
+        await super().send(message)

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

@@ -0,0 +1,251 @@
+import os
+import time
+import asyncio
+import logging
+import uuid
+from typing import Awaitable, Any
+from aiocqhttp import CQHttp, Event
+from astrbot.api.platform import Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from .aiocqhttp_message_event import *  # noqa: F403
+from astrbot.api.message_components import *  # noqa: F403
+from astrbot.api import logger
+from .aiocqhttp_message_event import AiocqhttpMessageEvent
+from astrbot.core.platform.astr_message_event import MessageSesion
+from ...register import register_platform_adapter
+from aiocqhttp.exceptions import ActionFailed
+from astrbot.core.utils.io import download_file
+
+@register_platform_adapter("aiocqhttp", "适用于 OneBot 标准的消息平台适配器，支持反向 WebSockets。")
+class AiocqhttpAdapter(Platform):
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        
+        self.config = platform_config
+        self.settings = platform_settings
+        self.unique_session = platform_settings['unique_session']
+        self.host = platform_config['ws_reverse_host']
+        self.port = platform_config['ws_reverse_port']
+        
+        self.metadata = PlatformMetadata(
+            "aiocqhttp",
+            "适用于 OneBot 标准的消息平台适配器，支持反向 WebSockets。",
+        )
+        
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        ret = await AiocqhttpMessageEvent._parse_onebot_json(message_chain)
+        match session.message_type.value:
+            case MessageType.GROUP_MESSAGE.value:
+                if "_" in session.session_id:
+                    # 独立会话
+                    _, group_id = session.session_id.split("_")
+                    await self.bot.send_group_msg(group_id=group_id, message=ret)
+                else:
+                    await self.bot.send_group_msg(group_id=session.session_id, message=ret)
+            case MessageType.FRIEND_MESSAGE.value:
+                await self.bot.send_private_msg(user_id=session.session_id, message=ret)
+        await super().send_by_session(session, message_chain)
+        
+    async def convert_message(self, event: Event) -> AstrBotMessage:
+        logger.debug(f"[aiocqhttp] RawMessage {event}")
+        
+        if event['post_type'] == 'message':
+            abm = await self._convert_handle_message_event(event)
+        elif event['post_type'] == 'notice':
+            abm = await self._convert_handle_notice_event(event)
+        elif event['post_type'] == 'request':
+            abm = await self._convert_handle_request_event(event)
+        
+        return abm
+    
+    async def _convert_handle_request_event(self, event: Event) -> AstrBotMessage:
+        '''OneBot V11 请求类事件'''
+        abm = AstrBotMessage()
+        abm.self_id = str(event.self_id)
+        abm.sender = MessageMember(
+            user_id=event.user_id,
+            nickname=event.user_id
+        )
+        abm.type = MessageType.OTHER_MESSAGE
+        if 'group_id' in event and event['group_id']:
+            abm.type = MessageType.GROUP_MESSAGE
+            abm.group_id = str(event.group_id)
+        else:
+            abm.type = MessageType.FRIEND_MESSAGE
+        if self.unique_session and abm.type == MessageType.GROUP_MESSAGE:
+            abm.session_id = abm.sender.user_id + "_" + str(event.group_id)
+        abm.message_str = ''
+        abm.message = []
+        abm.timestamp = int(time.time())
+        abm.message_id = uuid.uuid4().hex
+        abm.raw_message = event
+        return abm
+    
+    async def _convert_handle_notice_event(self, event: Event) -> AstrBotMessage:
+        '''OneBot V11 通知类事件'''
+        abm = AstrBotMessage()
+        abm.self_id = str(event.self_id)
+        abm.sender = MessageMember(
+            user_id=event.user_id,
+            nickname=event.user_id
+        )
+        abm.type = MessageType.OTHER_MESSAGE
+        if 'group_id' in event and event['group_id']:
+            abm.group_id = str(event.group_id)
+            abm.type = MessageType.GROUP_MESSAGE
+        else:
+            abm.type = MessageType.FRIEND_MESSAGE    
+        if self.unique_session and abm.type == MessageType.GROUP_MESSAGE:
+            abm.session_id = abm.sender.user_id + "_" + str(event.group_id) # 也保留群组 id
+        else:
+            abm.session_id = str(event.group_id) if abm.type == MessageType.GROUP_MESSAGE else abm.sender.user_id
+        abm.message_str = ""
+        abm.message = []
+        abm.raw_message = event
+        abm.timestamp = int(time.time())
+        abm.message_id = uuid.uuid4().hex
+        
+        if 'sub_type' in event:
+            if event['sub_type'] == 'poke' and 'target_id' in event:
+                abm.message.append(Poke(qq=str(event['target_id']), type='poke')) # noqa: F405
+                
+        return abm
+    
+    
+    async def _convert_handle_message_event(self, event: Event) -> AstrBotMessage:
+        '''OneBot V11 消息类事件'''
+        abm = AstrBotMessage()
+        abm.self_id = str(event.self_id)
+        abm.sender = MessageMember(str(event.sender['user_id']), event.sender['nickname'])      
+        if event['message_type'] == 'group':
+            abm.type = MessageType.GROUP_MESSAGE
+            abm.group_id = str(event.group_id)
+        elif event['message_type'] == 'private':
+            abm.type = MessageType.FRIEND_MESSAGE
+        if self.unique_session and abm.type == MessageType.GROUP_MESSAGE:
+            abm.session_id = abm.sender.user_id + "_" + str(event.group_id) # 也保留群组 id
+        else:
+            abm.session_id = str(event.group_id) if abm.type == MessageType.GROUP_MESSAGE else abm.sender.user_id
+        
+        abm.message_id = str(event.message_id)
+        abm.message = []
+        
+        message_str = ""
+        if not isinstance(event.message, list):
+            err = f"aiocqhttp: 无法识别的消息类型: {str(event.message)}，此条消息将被忽略。如果您在使用 go-cqhttp，请将其配置文件中的 message.post-format 更改为 array。"
+            logger.critical(err)
+            try:
+                self.bot.send(event, err)
+            except BaseException as e:
+                logger.error(f"回复消息失败: {e}")
+            return
+        
+        # 按消息段类型类型适配
+        for m in event.message:
+            t = m['type']
+            a = None
+            if t == 'text':
+                message_str += m['data']['text'].strip()
+            elif t == 'file':
+                if m['data']['url'] and m['data']['url'].startswith("http"):
+                    # Lagrange
+                    logger.info("guessing lagrange")
+                    
+                    file_name = m['data'].get('file_name', "file")
+                    path = os.path.join("data/temp", file_name)
+                    await download_file(m['data']['url'], path)
+                    
+                    m['data'] = {
+                        "file": path,
+                        "name": file_name
+                    }
+                
+                else:
+                    try:
+                        # Napcat, LLBot
+                        ret = await self.bot.call_action(action="get_file", file_id=event.message[0]['data']['file_id'])
+                        if not ret.get('file', None):
+                            raise ValueError(f"无法解析文件响应: {ret}")
+                        if not os.path.exists(ret['file']):
+                            raise FileNotFoundError(f"文件不存在或者权限问题: {ret['file']}。如果您使用 Docker 部署了 AstrBot 或者消息协议端(Napcat等),请先映射路径。如果路径在 /root 目录下，请用 sudo 打开 AstrBot")
+                        
+                        m['data'] = {
+                            "file": ret['file'],
+                            "name": ret['file_name']
+                        }
+                    except ActionFailed as e:
+                        logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
+                    except BaseException as e:
+                        logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
+                    
+            a = ComponentTypes[t](**m['data'])  # noqa: F405
+            abm.message.append(a)
+        abm.timestamp = int(time.time())
+        abm.message_str = message_str
+        abm.raw_message = event
+        
+        return abm
+    
+    def run(self) -> Awaitable[Any]:
+        if not self.host or not self.port:
+            logger.warning("aiocqhttp: 未配置 ws_reverse_host 或 ws_reverse_port，将使用默认值：http://0.0.0.0:6199")
+            self.host = "0.0.0.0"
+            self.port = 6199
+            
+        self.bot = CQHttp(use_ws_reverse=True, import_name='aiocqhttp', api_timeout_sec=180)
+        
+        @self.bot.on_request()
+        async def request(event: Event):
+            abm = await self.convert_message(event)
+            if abm:
+                await self.handle_msg(abm)
+        
+        @self.bot.on_notice()
+        async def notice(event: Event):
+            abm = await self.convert_message(event)
+            if abm:
+                await self.handle_msg(abm)
+        
+        @self.bot.on_message('group')
+        async def group(event: Event):
+            abm = await self.convert_message(event)
+            if abm:
+                await self.handle_msg(abm)
+        
+        @self.bot.on_message('private')
+        async def private(event: Event):
+            abm = await self.convert_message(event)
+            if abm:
+                await self.handle_msg(abm)
+                
+        @self.bot.on_websocket_connection
+        def on_websocket_connection(_):
+            logger.info("aiocqhttp 适配器已连接。")
+        
+        bot = self.bot.run_task(host=self.host, port=int(self.port), shutdown_trigger=self.shutdown_trigger_placeholder)
+        
+        for handler in logging.root.handlers[:]:
+            logging.root.removeHandler(handler)
+        logging.getLogger('aiocqhttp').setLevel(logging.ERROR)
+        
+        return bot
+    
+    def meta(self) -> PlatformMetadata:
+        return self.metadata
+    
+    async def shutdown_trigger_placeholder(self):
+        while not self._event_queue.closed:
+            await asyncio.sleep(1)
+        logger.info("aiocqhttp 适配器已关闭。")
+
+    async def handle_msg(self, message: AstrBotMessage):
+        
+        message_event = AiocqhttpMessageEvent(
+            message_str=message.message_str,
+            message_obj=message,
+            platform_meta=self.meta(),
+            session_id=message.session_id,
+            bot=self.bot
+        )
+        
+        self.commit_event(message_event)

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

@@ -0,0 +1,445 @@
+import threading
+import asyncio
+import aiohttp
+import quart
+import base64
+import datetime
+import re
+import os
+from astrbot.api.platform import AstrBotMessage, MessageMember, MessageType
+from astrbot.api.message_components import Plain, Image, At, Record
+from astrbot.api import logger, sp
+from .downloader import GeweDownloader
+from astrbot.core.utils.io import download_image_by_url
+
+
+class SimpleGewechatClient():
+    '''针对 Gewechat 的简单实现。
+    
+    @author: Soulter
+    @website: https://github.com/Soulter
+    '''
+    def __init__(self, base_url: str, nickname: str, host: str, port: int, event_queue: asyncio.Queue):
+        self.base_url = base_url
+        if self.base_url.endswith('/'):
+            self.base_url = self.base_url[:-1]
+            
+        self.download_base_url = self.base_url.split(':')[:-1] # 去掉端口
+        self.download_base_url = ':'.join(self.download_base_url) + ":2532/download/"
+        
+        self.base_url += "/v2/api"
+        
+        logger.info(f"Gewechat API: {self.base_url}")
+        logger.info(f"Gewechat 下载 API: {self.download_base_url}")
+        
+        if isinstance(port, str):
+            port = int(port)
+            
+        self.token = None
+        self.headers = {}
+        self.nickname = nickname
+        self.appid = sp.get(f"gewechat-appid-{nickname}", "")
+        
+        self.server = quart.Quart(__name__)
+        self.server.add_url_rule('/astrbot-gewechat/callback', view_func=self.callback, methods=['POST'])
+        self.server.add_url_rule('/astrbot-gewechat/file/<file_id>', view_func=self.handle_file, methods=['GET'])
+        
+        self.host = host
+        self.port = port 
+        self.callback_url = f"http://{self.host}:{self.port}/astrbot-gewechat/callback"
+        self.file_server_url = f"http://{self.host}:{self.port}/astrbot-gewechat/file"
+        
+        self.event_queue = event_queue
+        
+        self.multimedia_downloader = None
+        
+        self.userrealnames = {}
+    
+    async def get_token_id(self):
+        async with aiohttp.ClientSession() as session:
+            async with session.post(f"{self.base_url}/tools/getTokenId") as resp:
+                json_blob = await resp.json()
+                self.token = json_blob['data']
+                logger.info(f"获取到 Gewechat Token: {self.token}")
+                self.headers = {
+                    "X-GEWE-TOKEN": self.token
+                }
+                
+    async def _convert(self, data: dict) -> AstrBotMessage:
+        type_name = data['TypeName']
+        if type_name == "Offline":
+            logger.critical("收到 gewechat 下线通知。")
+            return
+        
+        if 'Data' in data and 'CreateTime' in data['Data']:
+            # 得到系统 UTF+8 的 ts
+            tz_offset = datetime.timedelta(hours=8)
+            tz = datetime.timezone(tz_offset)
+            ts = datetime.datetime.now(tz).timestamp()
+            create_time = data['Data']['CreateTime']
+            if create_time < ts - 30:
+                logger.warning(f"消息时间戳过旧: {create_time}，当前时间戳: {ts}")
+                return
+
+        
+        abm = AstrBotMessage()
+        d = data['Data']
+    
+        from_user_name = d['FromUserName']['string'] # 消息来源
+        d['to_wxid'] = from_user_name # 用于发信息
+        
+        abm.message_id = str(d.get('MsgId'))
+        abm.session_id = from_user_name
+        abm.self_id = data['Wxid'] # 机器人的 wxid
+        
+        user_id = "" # 发送人 wxid
+        content = d['Content']['string'] # 消息内容
+        
+        at_me = False
+        if "@chatroom" in from_user_name:
+            abm.type = MessageType.GROUP_MESSAGE
+            _t = content.split(':\n')
+            user_id = _t[0]
+            content = _t[1]
+            if '\u2005' in content: 
+                # at
+                # content = content.split('\u2005')[1]
+                content = re.sub(r'@[^\u2005]*\u2005', '', content)
+            abm.group_id = from_user_name
+            # at
+            msg_source = d['MsgSource']
+            if f'<atuserlist><![CDATA[,{abm.self_id}]]>' in msg_source \
+                or f'<atuserlist><![CDATA[{abm.self_id}]]>' in msg_source:
+                at_me = True
+            if '在群聊中@了你' in d.get('PushContent', ''):
+                at_me = True
+        else:
+            abm.type = MessageType.FRIEND_MESSAGE
+            user_id = from_user_name
+            
+        abm.message = []
+        if at_me:
+            abm.message.insert(0, At(qq=abm.self_id))
+        
+        # 解析用户真实名字
+        user_real_name = "unknown"
+        if abm.group_id:
+            if abm.group_id not in self.userrealnames or user_id not in self.userrealnames[abm.group_id]:
+                # 获取群成员列表，并且缓存
+                if abm.group_id not in self.userrealnames:
+                    self.userrealnames[abm.group_id] = {}
+                member_list = await self.get_chatroom_member_list(abm.group_id)
+                logger.debug(f"获取到 {abm.group_id} 的群成员列表。")
+                if member_list and 'memberList' in member_list:
+                    for member in member_list['memberList']:
+                        self.userrealnames[abm.group_id][member['wxid']] = member['nickName']
+                if user_id in self.userrealnames[abm.group_id]:
+                    user_real_name = self.userrealnames[abm.group_id][user_id]
+            else:
+                user_real_name = self.userrealnames[abm.group_id][user_id]
+        else:
+            user_real_name = d.get('PushContent', 'unknown : ').split(' : ')[0]
+
+        abm.sender = MessageMember(user_id, user_real_name)
+        abm.raw_message = d
+        abm.message_str = ""
+        # 不同消息类型
+        match d['MsgType']:
+            case 1:
+                # 文本消息
+                abm.message.append(Plain(content))
+                abm.message_str = content
+            case 3:
+                # 图片消息
+                file_url = await self.multimedia_downloader.download_image(
+                    self.appid, 
+                    content
+                )
+                logger.debug(f"下载图片: {file_url}")
+                file_path = await download_image_by_url(file_url)
+                abm.message.append(Image(file=file_path, url=file_path))
+                
+            case 34:
+                # 语音消息
+                # data = await self.multimedia_downloader.download_voice(
+                #     self.appid, 
+                #     content, 
+                #     abm.message_id
+                # )
+                # print(data)
+                if 'ImgBuf' in d and 'buffer' in d['ImgBuf']:
+                    voice_data = base64.b64decode(d['ImgBuf']['buffer'])
+                    file_path = f"data/temp/gewe_voice_{abm.message_id}.silk"
+                    with open(file_path, "wb") as f:
+                        f.write(voice_data)
+                    abm.message.append(Record(file=file_path, url=file_path))
+            case _:
+                logger.info(f"未实现的消息类型: {d['MsgType']}")
+                abm.raw_message = d
+        
+        logger.debug(f"abm: {abm}")
+        return abm
+
+    async def callback(self):
+        data = await quart.request.json
+        logger.debug(f"收到 gewechat 回调: {data}")
+        
+        if data.get('testMsg', None):
+            return quart.jsonify({"r": "AstrBot ACK"})
+        
+        abm = None
+        try:
+            abm = await self._convert(data)
+        except BaseException as e:
+            logger.warning(f"尝试解析 GeweChat 下发的消息时遇到问题: {e}。下发消息内容: {data}。")
+            
+        if abm:
+            coro = getattr(self, "on_event_received")
+            if coro:
+                await coro(abm)
+        
+        return quart.jsonify({"r": "AstrBot ACK"})
+    
+    async def handle_file(self, file_id):
+        file_path = f"data/temp/{file_id}"
+        return await quart.send_file(file_path)
+        
+    async def _set_callback_url(self):
+        logger.info("设置回调，请等待...")
+        await asyncio.sleep(3)
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/tools/setCallback",
+                headers=self.headers,
+                json={
+                    "token": self.token,
+                    "callbackUrl": self.callback_url
+                }
+            ) as resp:
+                json_blob = await resp.json()
+                logger.info(f"设置回调结果: {json_blob}")
+                if json_blob['ret'] != 200:
+                    raise Exception(f"设置回调失败: {json_blob}")
+                logger.info(f"将在 {self.callback_url} 上接收 gewechat 下发的消息。如果一直没收到消息请先尝试重启 AstrBot。如果仍没收到请到管理面板聊天页输入 /gewe_logout 重新登录。")
+        
+    async def start_polling(self):
+        threading.Thread(target=asyncio.run, args=(self._set_callback_url(),)).start()
+        await self.server.run_task(
+            host='0.0.0.0', 
+            port=self.port, 
+            shutdown_trigger=self.shutdown_trigger_placeholder
+        )
+    
+    async def shutdown_trigger_placeholder(self):
+        while not self.event_queue.closed:
+            await asyncio.sleep(1)
+        logger.info("gewechat 适配器已关闭。")
+        
+    async def check_online(self, appid: str):
+        # /login/checkOnline
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/login/checkOnline",
+                headers=self.headers,
+                json={
+                    "appId": appid
+                }
+            ) as resp:
+                json_blob = await resp.json()
+                return json_blob['data']
+            
+    async def logout(self):
+        if self.appid:
+            online = await self.check_online(self.appid)
+            if online:
+                async with aiohttp.ClientSession() as session:
+                    async with session.post(
+                        f"{self.base_url}/login/logout",
+                        headers=self.headers,
+                        json={
+                            "appId": self.appid
+                        }
+                    ) as resp:
+                        json_blob = await resp.json()
+                        logger.info(f"登出结果: {json_blob}")
+        
+    async def login(self):
+        if self.token is None:
+            await self.get_token_id()
+            
+        self.multimedia_downloader = GeweDownloader(self.base_url, self.download_base_url, self.token)
+        
+        if self.appid:
+            online = await self.check_online(self.appid)
+            if online:
+                logger.info(f"APPID: {self.appid} 已在线")
+                return
+        
+        payload = {
+            "appId": self.appid
+        }
+        
+        if self.appid:
+            logger.info(f"使用 APPID: {self.appid}, {self.nickname}")
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/login/getLoginQrCode", 
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                if json_blob['ret'] != 200:
+                    raise Exception(f"获取二维码失败: {json_blob}")
+                qr_data = json_blob['data']['qrData']
+                qr_uuid = json_blob['data']['uuid']
+                appid = json_blob['data']['appId']
+                logger.info(f"APPID: {appid}")
+                logger.warning(f"请打开该网址，然后使用微信扫描二维码登录: https://api.cl2wm.cn/api/qrcode/code?text={qr_data}")
+        
+        # 执行登录
+        retry_cnt = 64
+        payload.update({
+            "uuid": qr_uuid,
+            "appId": appid
+        })
+        verify_flag = False
+        while retry_cnt > 0:
+            retry_cnt -= 1
+
+            # 需要验证码
+            if verify_flag or os.path.exists("data/temp/gewe_code"):
+                with open("data/temp/gewe_code", "r") as f:
+                    code = f.read().strip()
+                    if not code:
+                        logger.warning("未找到验证码，请在管理面板聊天页输入 /gewe_code 验证码 来验证，如 /gewe_code 123456")
+                        await asyncio.sleep(5)
+                        continue
+                    payload['captchCode'] = code
+                    logger.info(f"使用验证码: {code}")
+                    try:
+                        os.remove("data/temp/gewe_code")
+                    except:
+                        logger.warning("删除验证码文件 data/temp/gewe_code 失败。")
+
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    f"{self.base_url}/login/checkLogin",
+                    headers=self.headers,
+                    json=payload
+                ) as resp:
+                    json_blob = await resp.json()
+                    logger.info(f"检查登录状态: {json_blob}")
+
+                    ret = json_blob['ret']
+                    msg = ''
+                    if json_blob['data'] and 'msg' in json_blob['data']:
+                        msg = json_blob['data']['msg']
+                    if ret == 500 and '安全验证码' in msg:
+                        logger.warning("此次登录需要安全验证码，请在管理面板聊天页输入 /gewe_code 验证码 来验证，如 /gewe_code 123456")
+                        verify_flag = True
+                    else:
+                        status = json_blob['data']['status']
+                        nickname = json_blob['data'].get('nickName', '')
+                        if status == 1: 
+                            logger.info(f"等待确认...{nickname}")
+                        elif status == 2:
+                            logger.info(f"绿泡泡平台登录成功: {nickname}")
+                            break
+                        elif status == 0:
+                            logger.info("等待扫码...")
+                        else:
+                            logger.warning(f"未知状态: {status}")
+            await asyncio.sleep(5)
+            
+        if appid:
+            sp.put(f"gewechat-appid-{self.nickname}", appid)
+            self.appid = appid
+            logger.info(f"已保存 APPID: {appid}")
+    
+    '''API'''
+    
+    async def get_chatroom_member_list(self, chatroom_wxid: str):
+        payload = {
+            "appId": self.appid,
+            "chatroomId": chatroom_wxid
+        }
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/group/getChatroomMemberList",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                return json_blob['data']
+    
+    async def post_text(self, to_wxid, content: str, ats: str = ""):
+        payload = {
+            "appId": self.appid,
+            "toWxid": to_wxid,
+            "content": content,
+        }
+        if ats:
+            payload['ats'] = ats
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/message/postText",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                logger.debug(f"发送消息结果: {json_blob}")
+                
+    async def post_image(self, to_wxid, image_url: str):
+        payload = {
+            "appId": self.appid,
+            "toWxid": to_wxid,
+            "imgUrl": image_url,
+        }
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/message/postImage",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                logger.debug(f"发送图片结果: {json_blob}")
+                
+    async def post_voice(self, to_wxid, voice_url: str, voice_duration: int):
+        payload = {
+            "appId": self.appid,
+            "toWxid": to_wxid,
+            "voiceUrl": voice_url,
+            "voiceDuration": voice_duration
+        }
+        
+        logger.debug(f"发送语音: {payload}")
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/message/postVoice",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                logger.debug(f"发送语音结果: {json_blob}")
+                
+    async def post_file(self, to_wxid, file_url: str, file_name: str):
+        payload = {
+            "appId": self.appid,
+            "toWxid": to_wxid,
+            "fileUrl": file_url,
+            "fileName": file_name
+        }
+        
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{self.base_url}/message/postFile",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                json_blob = await resp.json()
+                logger.debug(f"发送文件结果: {json_blob}")

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

@@ -0,0 +1,51 @@
+from astrbot import logger
+import aiohttp
+import json
+
+class GeweDownloader():
+    def __init__(self, base_url: str, download_base_url: str, token: str):
+        self.base_url = base_url
+        self.download_base_url = download_base_url
+        self.headers = {
+            "Content-Type": "application/json",
+            "X-GEWE-TOKEN": token
+        }
+    
+    async def _post_json(self, baseurl: str, route: str, payload: dict):
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{baseurl}{route}",
+                headers=self.headers,
+                json=payload
+            ) as resp:
+                return await resp.read()
+            
+    async def download_voice(self, appid: str, xml: str, msg_id: str):
+        payload = {
+            "appId": appid,
+            "xml": xml,
+            "msgId": msg_id
+        }
+        return await self._post_json(self.base_url, "/message/downloadVoice", payload)
+    
+    async def download_image(self, appid: str, xml: str) -> str:
+        '''返回一个可下载的 URL'''
+        choices = [2, 3] #  2:常规图片 3:缩略图
+        
+        for choice in choices:
+            try:
+                payload = {
+                    "appId": appid,
+                    "xml": xml,
+                    "type": choice
+                }
+                data = await self._post_json(self.base_url, "/message/downloadImage", payload)
+                json_blob = json.loads(data)
+                if 'fileUrl' in json_blob['data']:
+                    return self.download_base_url + json_blob['data']['fileUrl']
+
+            except BaseException as e:
+                logger.error(f"gewe download image: {e}")
+                continue
+        
+        raise Exception("无法下载图片")

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

@@ -0,0 +1,139 @@
+import wave
+import uuid
+import traceback
+import os
+from astrbot.core.utils.io import save_temp_img, download_image_by_url, download_file
+from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk
+from astrbot.api import logger
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.platform import AstrBotMessage, PlatformMetadata
+from astrbot.api.message_components import Plain, Image, Record, At, File
+from .client import SimpleGewechatClient
+
+def get_wav_duration(file_path):
+    with wave.open(file_path, 'rb') as wav_file:
+        file_size = os.path.getsize(file_path)
+        n_channels, sampwidth, framerate, n_frames = wav_file.getparams()[:4]
+        if n_frames == 2147483647:
+            duration = (file_size - 44) / (n_channels * sampwidth * framerate)
+        elif n_frames == 0:
+            duration = (file_size - 44) / (n_channels * sampwidth * framerate)
+        else:
+            duration = n_frames / float(framerate)
+        return duration
+
+class GewechatPlatformEvent(AstrMessageEvent):
+    def __init__(
+            self, 
+            message_str: str, 
+            message_obj: AstrBotMessage, 
+            platform_meta: PlatformMetadata, 
+            session_id: str,
+            client: SimpleGewechatClient
+        ):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.client = client
+        
+    @staticmethod
+    async def send_with_client(message: MessageChain, user_name: str):
+        pass
+                
+        
+    async def send(self, message: MessageChain):
+        to_wxid = self.message_obj.raw_message.get('to_wxid', None)
+        
+        if not to_wxid:
+            logger.error("无法获取到 to_wxid。")
+            return
+        
+        #  检查@
+        ats = []
+        ats_names = []
+        for comp in message.chain:
+            if isinstance(comp, At):
+                ats.append(comp.qq)
+                ats_names.append(comp.name)
+        has_at = False
+        
+        for comp in message.chain:
+            if isinstance(comp, Plain):
+                text = comp.text
+                payload = {
+                    "to_wxid": to_wxid,
+                    "content": text,
+                }
+                if not has_at and ats:
+                    ats = f"{','.join(ats)}"
+                    ats_names = f"@{' @'.join(ats_names)}"
+                    text = f"{ats_names} {text}"
+                    payload["content"] = text
+                    payload["ats"] = ats
+                    has_at = True
+                await self.client.post_text(**payload)
+                
+            elif isinstance(comp, Image):
+                img_url = comp.file
+                img_path = ""
+                if img_url.startswith("file:///"):
+                    img_path = img_url[8:]
+                elif comp.file and comp.file.startswith("http"):
+                    img_path = await download_image_by_url(comp.file)
+                else:
+                    img_path = img_url
+                    
+                # 检查 record_path 是否在 data/temp 目录中, record_path 可能是绝对路径
+                temp_directory = os.path.abspath('data/temp')
+                img_path = os.path.abspath(img_path)
+                if os.path.commonpath([temp_directory, img_path]) != temp_directory:
+                    with open(img_path, "rb") as f:
+                        img_path = save_temp_img(f.read())
+
+                file_id = os.path.basename(img_path)
+                img_url = f"{self.client.file_server_url}/{file_id}"
+                logger.debug(f"gewe callback img url: {img_url}")
+                await self.client.post_image(to_wxid, img_url)
+            elif isinstance(comp, Record):
+                # 默认已经存在 data/temp 中
+                record_url = comp.file
+                record_path = ""
+                
+                if record_url.startswith("file:///"):
+                    record_path = record_url[8:]
+                elif record_url.startswith("http"):
+                    await download_file(record_url, f"data/temp/{uuid.uuid4()}.wav")
+                else:
+                    record_path = record_url
+                    
+                silk_path = f"data/temp/{uuid.uuid4()}.silk"
+                try:
+                    duration = await wav_to_tencent_silk(record_path, silk_path)
+                except Exception as e:
+                    logger.error(traceback.format_exc())
+                    await self.send(MessageChain().message(f"语音文件转换失败。{str(e)}"))
+                logger.info("Silk 语音文件格式转换至: " + record_path)
+                if duration == 0:
+                    duration = get_wav_duration(record_path)
+                file_id = os.path.basename(silk_path)
+                record_url = f"{self.client.file_server_url}/{file_id}"
+                logger.debug(f"gewe callback record url: {record_url}")
+                await self.client.post_voice(to_wxid, record_url, duration*1000)
+            elif isinstance(comp, File):
+                file_path = comp.file
+                file_name = comp.name
+                if file_path.startswith("file:///"):
+                    file_path = file_path[8:]
+                elif file_path.startswith("http"):
+                    await download_file(file_path, f"data/temp/{file_name}")
+                else:
+                    file_path = file_path
+                    
+                file_id = os.path.basename(file_path)
+                file_url = f"{self.client.file_server_url}/{file_id}"
+                logger.debug(f"gewe callback file url: {file_url}")
+                await self.client.post_file(to_wxid, file_url, file_id) 
+            elif isinstance(comp, At):
+                pass
+            else:
+                logger.debug(f"gewechat 忽略: {comp.type}")   
+        
+        await super().send(message)

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

@@ -0,0 +1,89 @@
+import sys
+import asyncio
+import os
+
+from astrbot.api.platform import Platform, AstrBotMessage, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from astrbot.api import logger
+from astrbot.core.platform.astr_message_event import MessageSesion
+from ...register import register_platform_adapter
+from .gewechat_event import GewechatPlatformEvent
+from .client import SimpleGewechatClient
+from astrbot.core.message.components import Plain
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+            
+
+@register_platform_adapter("gewechat", "基于 gewechat 的 Wechat 适配器")
+class GewechatPlatformAdapter(Platform):
+
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        self.config = platform_config
+        self.settingss = platform_settings
+        self.test_mode = os.environ.get('TEST_MODE', 'off') == 'on'
+        self.client = None
+    
+    @override
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        to_wxid = session.session_id
+        if not to_wxid:
+            logger.error("无法获取到 to_wxid。")
+            return
+        
+        for comp in message_chain.chain:
+            if isinstance(comp, Plain):
+                await self.client.post_text(to_wxid, comp.text)
+
+        await super().send_by_session(session, message_chain)
+    
+    @override
+    def meta(self) -> PlatformMetadata:
+        return PlatformMetadata(
+            "gewechat",
+            "基于 gewechat 的 Wechat 适配器",
+        )
+
+    @override
+    def run(self):
+        self.client = SimpleGewechatClient(
+            self.config['base_url'],
+            self.config['nickname'],
+            self.config['host'],
+            self.config['port'],
+            self._event_queue,
+        )
+        
+        async def on_event_received(abm: AstrBotMessage):
+            await self.handle_msg(abm)
+            
+        self.client.on_event_received = on_event_received
+        
+        return self._run()
+    
+    async def logout(self):
+        await self.client.logout()
+    
+    async def _run(self):
+        await self.client.login()
+        
+        await self.client.start_polling()
+        
+    
+    async def handle_msg(self, message: AstrBotMessage):
+        if message.type == MessageType.GROUP_MESSAGE:
+            if self.settingss['unique_session']:
+                message.session_id = message.sender.user_id + "_" + message.group_id
+        
+        message_event = GewechatPlatformEvent(
+            message_str=message.message_str,
+            message_obj=message,
+            platform_meta=self.meta(),
+            session_id=message.session_id,
+            client=self.client
+        )
+        
+        self.commit_event(message_event)

astrbot/core/platform/sources/lark/lark_adapter.py

@@ -0,0 +1,175 @@
+import base64
+import time
+import asyncio
+import json
+import re
+
+from astrbot.api.platform import Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from typing import Union, List
+from astrbot.api.message_components import Image, Plain, At
+from astrbot.core.platform.astr_message_event import MessageSesion
+from .lark_event import LarkMessageEvent
+from ...register import register_platform_adapter
+from astrbot.core.message.components import BaseMessageComponent
+from astrbot import logger
+import lark_oapi as lark
+from lark_oapi.api.im.v1 import *
+
+@register_platform_adapter("lark", "飞书机器人官方 API 适配器")
+class LarkPlatformAdapter(Platform):
+
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        
+        self.config = platform_config
+        
+        self.unique_session = platform_settings['unique_session']
+
+        self.appid = platform_config['app_id']
+        self.appsecret = platform_config['app_secret']
+        self.domain = platform_config.get('domain', lark.FEISHU_DOMAIN)
+        self.bot_name = platform_config.get('lark_bot_name', "astrbot")
+        
+        if not self.bot_name:
+            logger.warning("未设置飞书机器人名称，@ 机器人可能得不到回复。")
+        
+        async def on_msg_event_recv(event: lark.im.v1.P2ImMessageReceiveV1):
+            await self.convert_msg(event)
+        
+        def do_v2_msg_event(event: lark.im.v1.P2ImMessageReceiveV1):
+            asyncio.create_task(on_msg_event_recv(event))
+        
+        self.event_handler = lark.EventDispatcherHandler.builder("", "") \
+            .register_p2_im_message_receive_v1(do_v2_msg_event) \
+            .build()
+             
+        self.client = lark.ws.Client(
+            app_id=self.appid,
+            app_secret=self.appsecret,
+            log_level=lark.LogLevel.ERROR,
+            domain=self.domain,
+            event_handler=self.event_handler
+        )
+        
+        self.lark_api = (
+            lark.Client.builder()
+            .app_id(self.appid)
+            .app_secret(self.appsecret)
+            .build()
+        )
+        
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        raise NotImplementedError("QQ 机器人官方 API 适配器不支持 send_by_session")
+        
+    def meta(self) -> PlatformMetadata:
+        return PlatformMetadata(
+            "lark",
+            "飞书机器人官方 API 适配器",
+        )
+        
+    async def convert_msg(self, event: lark.im.v1.P2ImMessageReceiveV1):
+        message = event.event.message
+        abm = AstrBotMessage()
+        abm.timestamp = int(message.create_time) / 1000
+        abm.message = []
+        abm.type = MessageType.GROUP_MESSAGE if message.chat_type == 'group' else MessageType.FRIEND_MESSAGE
+        if message.chat_type == 'group':
+            abm.group_id = message.chat_id
+        abm.self_id = self.bot_name
+        abm.message_str = ""
+        
+        at_list = {}
+        if message.mentions:
+            for m in message.mentions:
+                at_list[m.key] = At(qq=m.id.open_id, name=m.name)
+                if m.name == self.bot_name:
+                    abm.self_id = m.id.open_id
+                    
+        content_json_b = json.loads(message.content)
+        
+        if message.message_type == 'text':
+            message_str_raw = content_json_b['text'] # 带有 @ 的消息
+            at_pattern = r"(@_user_\d+)"  # 可以根据需求修改正则
+            at_users = re.findall(at_pattern, message_str_raw)
+            # 拆分文本，去掉AT符号部分
+            parts = re.split(at_pattern, message_str_raw)
+            for i in range(len(parts)):
+                s = parts[i].strip()
+                if not s:
+                    continue
+                if s in at_list:
+                    abm.message.append(at_list[s])
+                else:
+                    abm.message.append(Plain(parts[i].strip()))
+        elif message.message_type == 'post':
+            _ls = []
+            
+            content_ls = content_json_b.get('content', [])
+            for comp in content_ls:
+                if isinstance(comp, list):
+                    _ls.extend(comp)
+                elif isinstance(comp, dict):
+                    _ls.append(comp)
+            content_json_b = _ls
+        elif message.message_type == 'image':
+            content_json_b = [
+                {"tag": "img", "image_key": content_json_b["image_key"], "style": []}
+            ]
+            
+        if message.message_type in ('post', 'image'):    
+            for comp in content_json_b:
+                if comp['tag'] == 'at':
+                    abm.message.append(at_list[comp['user_id']])
+                elif comp['tag'] == 'text' and comp['text'].strip():
+                    abm.message.append(Plain(comp['text'].strip()))
+                elif comp['tag'] == 'img':
+                    image_key = comp['image_key']
+                    request = GetMessageResourceRequest.builder() \
+                        .message_id(message.message_id) \
+                        .file_key(image_key) \
+                        .type("image") \
+                        .build()
+                    response = await self.lark_api.im.v1.message_resource.aget(request)
+                    if not response.success():
+                        logger.error(f"无法下载飞书图片: {image_key}")
+                    image_bytes = response.file.read()
+                    image_base64 = base64.b64encode(image_bytes).decode()
+                    abm.message.append(Image.fromBase64(image_base64))
+        
+        for comp in abm.message:
+            if isinstance(comp, Plain):
+                abm.message_str += comp.text
+        abm.message_id = message.message_id
+        abm.raw_message = message
+        abm.sender = MessageMember(
+            user_id=event.event.sender.sender_id.open_id,
+            nickname=event.event.sender.sender_id.open_id[:8]
+        )
+        # 独立会话
+        if not self.unique_session:
+            if abm.type == MessageType.GROUP_MESSAGE:
+                abm.session_id = abm.group_id
+            else:
+                abm.session_id = abm.sender.user_id
+        else:
+            abm.session_id = abm.sender.user_id
+            
+        logger.debug(abm)
+        await self.handle_msg(abm)
+        
+    async def handle_msg(self, abm: AstrBotMessage):
+        event = LarkMessageEvent(
+            message_str=abm.message_str,
+            message_obj=abm,
+            platform_meta=self.meta(),
+            session_id=abm.session_id,
+            bot=self.lark_api
+        )
+        
+        self._event_queue.put_nowait(event)
+        
+    async def run(self):
+        # self.client.start()
+        await self.client._connect()
+        

astrbot/core/platform/sources/lark/lark_event.py

@@ -0,0 +1,96 @@
+import json
+import uuid
+import lark_oapi as lark
+from typing import List
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.message_components import Plain, Image as AstrBotImage, Record, At, Node, Music, Video
+from astrbot.core.utils.io import file_to_base64, download_image_by_url
+from lark_oapi.api.im.v1 import *
+from astrbot import logger
+
+class LarkMessageEvent(AstrMessageEvent):
+    def __init__(self, message_str, message_obj, platform_meta, session_id, bot: lark.Client):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.bot = bot
+    
+    @staticmethod
+    async def _convert_to_lark(message: MessageChain, lark_client: lark.Client) -> List:
+        ret = []
+        _stage = []
+        for comp in message.chain:
+            if isinstance(comp, Plain):
+                _stage.append({
+                    "tag": "md",
+                    "text": comp.text
+                })
+            elif isinstance(comp, At):
+                _stage.append({
+                    "tag": "at",
+                    "user_id": comp.qq,
+                    "style": []
+                })
+            elif isinstance(comp, AstrBotImage):
+                file_path = ""
+                if comp.file and comp.file.startswith("file:///"):
+                    file_path = comp.file.replace('file:///', '')
+                elif comp.file and comp.file.startswith("http"):
+                    image_file_path = await download_image_by_url(comp.file)
+                    file_path = image_file_path
+                elif comp.file and comp.file.startswith("base64://"):
+                    pass
+                else:
+                    file_path = comp.file
+                
+                request = CreateImageRequest.builder() \
+                        .request_body( \
+                            CreateImageRequestBody.builder() \
+                            .image_type("message") \
+                            .image(open(file_path, 'rb')) \
+                            .build() \
+                        ) \
+                        .build()
+                response = await lark_client.im.v1.image.acreate(request)
+                if not response.success():
+                    logger.error(f"无法上传飞书图片({response.code}): {response.msg}")
+                image_key = response.data.image_key
+                print(image_key)
+                ret.append(_stage)
+                ret.append([{
+                    "tag": "img",
+                    "image_key": image_key
+                }])
+                _stage.clear()
+            else:
+                logger.warning(f"飞书 暂时不支持消息段: {comp.type}")
+
+        if _stage:
+            ret.append(_stage)            
+        return ret
+
+    async def send(self, message: MessageChain):
+        res = await LarkMessageEvent._convert_to_lark(message, self.bot)
+        wrapped = {
+            "zh_cn": {
+                "title": "",
+                "content": res,
+            }
+        }
+
+        request = ReplyMessageRequest.builder() \
+            .message_id(self.message_obj.message_id) \
+            .request_body( \
+                ReplyMessageRequestBody.builder() \
+                .content(json.dumps(wrapped)) \
+                .msg_type("post") \
+                .uuid(str(uuid.uuid4())) \
+                .reply_in_thread(False) \
+                .build() \
+            ) \
+            .build()
+
+        response = await self.bot.im.v1.message.areply(request)
+        
+        if not response.success():
+            logger.error(f"回复飞书消息失败({response.code}): {response.msg}")
+    
+        await super().send(message)

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

@@ -0,0 +1,102 @@
+import botpy
+import botpy.message
+import botpy.types
+import botpy.types.message
+from astrbot.core.utils.io import file_to_base64, download_image_by_url
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.platform import AstrBotMessage, PlatformMetadata
+from astrbot.api.message_components import Plain, Image
+from botpy import Client
+from botpy.http import Route
+from astrbot.api import logger
+
+
+class QQOfficialMessageEvent(AstrMessageEvent):
+    def __init__(self, message_str: str, message_obj: AstrBotMessage, platform_meta: PlatformMetadata, session_id: str, bot: Client):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.bot = bot
+        self.send_buffer = None
+        
+    async def send(self, message: MessageChain):
+        if not self.send_buffer:
+            self.send_buffer = message
+        else:
+            self.send_buffer.chain.extend(message.chain)
+
+    async def _post_send(self):
+        '''QQ 官方 API 仅支持回复一次'''
+        source = self.message_obj.raw_message
+        assert isinstance(source, (botpy.message.Message, botpy.message.GroupMessage, botpy.message.DirectMessage, botpy.message.C2CMessage))
+        
+        plain_text, image_base64, image_path = await QQOfficialMessageEvent._parse_to_qqofficial(self.send_buffer)
+        
+        if not plain_text and not image_base64 and not image_path:
+            return
+        
+        payload = {
+            'content': plain_text,
+            'msg_id': self.message_obj.message_id,
+        }
+        
+        match type(source):
+            case botpy.message.GroupMessage:
+                if image_base64:
+                    media = await self.upload_group_and_c2c_image(image_base64, 1, group_openid=source.group_openid)
+                    payload['media'] = media
+                    payload['msg_type'] = 7
+                await self.bot.api.post_group_message(group_openid=source.group_openid, **payload)
+            case botpy.message.C2CMessage:
+                if image_base64:
+                    media = await self.upload_group_and_c2c_image(image_base64, 1, openid=source.author.user_openid)
+                    payload['media'] = media
+                    payload['msg_type'] = 7
+                await self.bot.api.post_c2c_message(openid=source.author.user_openid, **payload)
+            case botpy.message.Message:
+                if image_path:
+                    payload['file_image'] = image_path
+                await self.bot.api.post_message(channel_id=source.channel_id, **payload)
+            case botpy.message.DirectMessage:
+                if image_path:
+                    payload['file_image'] = image_path
+                await self.bot.api.post_dms(guild_id=source.guild_id, **payload)
+
+        await super().send(self.send_buffer)
+        
+        self.send_buffer = None
+            
+    async def upload_group_and_c2c_image(self, image_base64: str, file_type: int, **kwargs) -> botpy.types.message.Media:
+        payload = {
+            'file_data': image_base64,
+            'file_type': file_type,
+            "srv_send_msg": False
+        }
+        if 'openid' in kwargs:
+            payload['openid'] = kwargs['openid']
+            route = Route("POST", "/v2/users/{openid}/files", openid=kwargs['openid'])
+            return await self.bot.api._http.request(route, json=payload)
+        elif 'group_openid' in kwargs:
+            payload['group_openid'] = kwargs['group_openid']
+            route = Route("POST", "/v2/groups/{group_openid}/files", group_openid=kwargs['group_openid'])
+            return await self.bot.api._http.request(route, json=payload)
+            
+    @staticmethod
+    async def _parse_to_qqofficial(message: MessageChain):
+        plain_text = ""
+        image_base64 = None  # only one img supported
+        image_file_path = None
+        for i in message.chain:
+            if isinstance(i, Plain):
+                plain_text += i.text
+            elif isinstance(i, Image) and not image_base64:
+                if i.file and i.file.startswith("file:///"):
+                    image_base64 = file_to_base64(i.file[8:]).replace("base64://", "")
+                    image_file_path = i.file[8:]
+                elif i.file and i.file.startswith("http"):
+                    image_file_path = await download_image_by_url(i.file)
+                    image_base64 = file_to_base64(image_file_path).replace("base64://", "")
+                else:
+                    image_base64 = file_to_base64(i.file).replace("base64://", "")
+                    image_file_path = i.file
+            else:
+                logger.debug(f"qq_official 忽略 {i.type}")
+        return plain_text, image_base64, image_file_path

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

@@ -0,0 +1,182 @@
+from __future__ import annotations
+
+import botpy
+import logging
+import time
+import asyncio
+import botpy.message
+import botpy.types
+import botpy.types.message
+import os
+
+from botpy import Client
+from astrbot.api.platform import Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from typing import Union, List
+from astrbot.api.message_components import Image, Plain, At
+from astrbot.core.platform.astr_message_event import MessageSesion
+from .qqofficial_message_event import QQOfficialMessageEvent
+from ...register import register_platform_adapter
+from astrbot.core.message.components import BaseMessageComponent
+
+# remove logger handler
+for handler in logging.root.handlers[:]:
+    logging.root.removeHandler(handler)
+
+# QQ 机器人官方框架
+class botClient(Client):
+    def set_platform(self, platform: 'QQOfficialPlatformAdapter'):
+        self.platform = platform
+        
+    # 收到群消息
+    async def on_group_at_message_create(self, message: botpy.message.GroupMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.GROUP_MESSAGE)
+        abm.session_id = abm.sender.user_id if self.platform.unique_session else message.group_openid
+        self._commit(abm)
+
+    # 收到频道消息
+    async def on_at_message_create(self, message: botpy.message.Message):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.GROUP_MESSAGE)
+        abm.session_id = abm.sender.user_id if self.platform.unique_session else message.channel_id
+        self._commit(abm)
+        
+    # 收到私聊消息
+    async def on_direct_message_create(self, message: botpy.message.DirectMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.FRIEND_MESSAGE)
+        abm.session_id = abm.sender.user_id
+        self._commit(abm)
+        
+    # 收到 C2C 消息
+    async def on_c2c_message_create(self, message: botpy.message.C2CMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.FRIEND_MESSAGE)
+        abm.session_id = abm.sender.user_id
+        self._commit(abm)
+        
+    def _commit(self, abm: AstrBotMessage):
+        self.platform.commit_event(QQOfficialMessageEvent(
+            abm.message_str,
+            abm,
+            self.platform.meta(),
+            abm.session_id,
+            self.platform.client
+        ))
+@register_platform_adapter("qq_official", "QQ 机器人官方 API 适配器")
+class QQOfficialPlatformAdapter(Platform):
+
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        
+        self.config = platform_config
+        
+        self.appid = platform_config['appid']
+        self.secret = platform_config['secret']
+        self.unique_session = platform_settings['unique_session']
+        qq_group = platform_config['enable_group_c2c']
+        guild_dm = platform_config['enable_guild_direct_message']
+
+        if qq_group:
+            self.intents = botpy.Intents(
+                public_messages=True,
+                public_guild_messages=True,
+                direct_message=guild_dm
+            )
+        else:
+            self.intents = botpy.Intents(
+                public_guild_messages=True,
+                direct_message=guild_dm
+            )
+        self.client = botClient(
+            intents=self.intents,
+            bot_log=False,
+            timeout=20,
+        )
+
+        self.client.set_platform(self)
+        
+        self.test_mode = os.environ.get('TEST_MODE', 'off') == 'on'
+        
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        raise NotImplementedError("QQ 机器人官方 API 适配器不支持 send_by_session")
+        
+    def meta(self) -> PlatformMetadata:
+        return PlatformMetadata(
+            "qq_official",
+            "QQ 机器人官方 API 适配器",
+        )
+
+    @staticmethod
+    def _parse_from_qqofficial(message: Union[botpy.message.Message, botpy.message.GroupMessage],
+                                  message_type: MessageType):
+        abm = AstrBotMessage()
+        abm.type = message_type
+        abm.timestamp = int(time.time())
+        abm.raw_message = message
+        abm.message_id = message.id
+        abm.tag = "qq_official"
+        msg: List[BaseMessageComponent] = []
+        
+
+        if isinstance(message, botpy.message.GroupMessage) or isinstance(message, botpy.message.C2CMessage):
+            if isinstance(message, botpy.message.GroupMessage):
+                abm.sender = MessageMember(
+                    message.author.member_openid,
+                    ""
+                )
+                abm.group_id = message.group_openid
+            else:
+                abm.sender = MessageMember(
+                    message.author.user_openid,
+                    ""
+                )
+            abm.message_str = message.content.strip()
+            abm.self_id = "unknown_selfid"
+            msg.append(At(qq="qq_official"))
+            msg.append(Plain(abm.message_str))
+            if message.attachments:
+                for i in message.attachments:
+                    if i.content_type.startswith("image"):
+                        url = i.url
+                        if not url.startswith("http"):
+                            url = "https://"+url
+                        img = Image.fromURL(url)
+                        msg.append(img)
+            abm.message = msg
+
+        elif isinstance(message, botpy.message.Message) or isinstance(message, botpy.message.DirectMessage):
+            try:
+                abm.self_id = str(message.mentions[0].id)
+            except BaseException as _:
+                abm.self_id = ""
+
+            plain_content = message.content.replace(
+                "<@!"+str(abm.self_id)+">", "").strip()
+
+            if message.attachments:
+                for i in message.attachments:
+                    if i.content_type.startswith("image"):
+                        url = i.url
+                        if not url.startswith("http"):
+                            url = "https://"+url
+                        img = Image.fromURL(url)
+                        msg.append(img)
+            abm.message = msg
+            abm.message_str = plain_content
+            abm.sender = MessageMember(
+                str(message.author.id),
+                str(message.author.username)
+            )
+            msg.append(At(qq="qq_official"))
+            msg.append(Plain(plain_content))
+            
+            if isinstance(message, botpy.message.Message):
+                abm.group_id = message.channel_id
+        else:
+            raise ValueError(f"Unknown message type: {message_type}")
+        abm.self_id = "qq_official"
+        return abm
+
+    def run(self):
+        return self.client.start(
+            appid=self.appid,
+            secret=self.secret
+        )

astrbot/core/platform/sources/qqofficial_webhook/qo_webhook_adapter.py

@@ -0,0 +1,99 @@
+import botpy
+import logging
+import asyncio
+import botpy.message
+import botpy.types
+import botpy.types.message
+
+from botpy import Client
+from astrbot.api.platform import Platform, AstrBotMessage, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from astrbot.core.platform.astr_message_event import MessageSesion
+from .qo_webhook_event import QQOfficialWebhookMessageEvent
+from ...register import register_platform_adapter
+from .qo_webhook_server import QQOfficialWebhook
+from ..qqofficial.qqofficial_platform_adapter import QQOfficialPlatformAdapter
+
+# remove logger handler
+for handler in logging.root.handlers[:]:
+    logging.root.removeHandler(handler)
+    
+# QQ 机器人官方框架
+class botClient(Client):
+    def set_platform(self, platform: 'QQOfficialWebhookPlatformAdapter'):
+        self.platform = platform
+        
+    # 收到群消息
+    async def on_group_at_message_create(self, message: botpy.message.GroupMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.GROUP_MESSAGE)
+        abm.session_id = abm.sender.user_id if self.platform.unique_session else message.group_openid
+        self._commit(abm)
+
+    # 收到频道消息
+    async def on_at_message_create(self, message: botpy.message.Message):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.GROUP_MESSAGE)
+        abm.session_id = abm.sender.user_id if self.platform.unique_session else message.channel_id
+        self._commit(abm)
+        
+    # 收到私聊消息
+    async def on_direct_message_create(self, message: botpy.message.DirectMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.FRIEND_MESSAGE)
+        abm.session_id = abm.sender.user_id
+        self._commit(abm)
+        
+    # 收到 C2C 消息
+    async def on_c2c_message_create(self, message: botpy.message.C2CMessage):
+        abm = QQOfficialPlatformAdapter._parse_from_qqofficial(message, MessageType.FRIEND_MESSAGE)
+        abm.session_id = abm.sender.user_id
+        self._commit(abm)
+        
+    def _commit(self, abm: AstrBotMessage):
+        self.platform.commit_event(QQOfficialWebhookMessageEvent(
+            abm.message_str,
+            abm,
+            self.platform.meta(),
+            abm.session_id,
+            self
+        ))
+        
+@register_platform_adapter("qq_official_webhook", "QQ 机器人官方 API 适配器(Webhook)")
+class QQOfficialWebhookPlatformAdapter(Platform):
+
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        
+        self.config = platform_config
+        
+        self.appid = platform_config['appid']
+        self.secret = platform_config['secret']
+        self.unique_session = platform_settings['unique_session']
+
+        intents = botpy.Intents(
+            public_messages=True,
+            public_guild_messages=True,
+            direct_message=True
+        )
+        self.client = botClient(
+            intents=intents, # 已经无用
+            bot_log=False,
+            timeout=20,
+        )
+        self.client.set_platform(self)
+
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        raise NotImplementedError("QQ 机器人官方 API 适配器不支持 send_by_session")
+        
+    def meta(self) -> PlatformMetadata:
+        return PlatformMetadata(
+            "qq_official_webhook",
+            "QQ 机器人官方 API 适配器",
+        )
+
+    async def run(self):
+        self.webhook_helper = QQOfficialWebhook(
+            self.config,
+            self._event_queue,
+            self.client
+        )
+        await self.webhook_helper.initialize()
+        await self.webhook_helper.start_polling()

astrbot/core/platform/sources/qqofficial_webhook/qo_webhook_event.py

@@ -0,0 +1,18 @@
+import botpy
+import botpy.message
+import botpy.types
+import botpy.types.message
+from astrbot.core.utils.io import file_to_base64, download_image_by_url
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.platform import AstrBotMessage, PlatformMetadata
+from astrbot.api.message_components import Plain, Image, Reply
+from botpy import Client
+from botpy.http import Route
+from astrbot.api import logger
+from ..qqofficial.qqofficial_message_event import QQOfficialMessageEvent
+
+
+class QQOfficialWebhookMessageEvent(QQOfficialMessageEvent):
+    def __init__(self, message_str: str, message_obj: AstrBotMessage, platform_meta: PlatformMetadata, session_id: str, bot: Client):
+        super().__init__(message_str, message_obj, platform_meta, session_id, bot)
+    

astrbot/core/platform/sources/qqofficial_webhook/qo_webhook_server.py

@@ -0,0 +1,108 @@
+import aiohttp
+import quart
+import json
+import logging
+import asyncio
+import typing
+from botpy import BotAPI, BotHttp, Client, Token, BotWebSocket, ConnectionSession
+from astrbot.api import logger
+import traceback
+from cryptography.hazmat.primitives.asymmetric import ed25519
+
+# remove logger handler
+for handler in logging.root.handlers[:]:
+    logging.root.removeHandler(handler)
+
+class QQOfficialWebhook():
+    def __init__(self, config: dict, event_queue: asyncio.Queue, botpy_client: Client):
+        self.appid = config['appid']
+        self.secret = config['secret']
+        self.port = config.get("port", 6196)
+        
+        if isinstance(self.port, str):
+            self.port = int(self.port)
+        
+        self.http: BotHttp = BotHttp(timeout=300)
+        self.api: BotAPI = BotAPI(http=self.http)
+        self.token = Token(self.appid, self.secret)
+        
+        self.server = quart.Quart(__name__)
+        self.server.add_url_rule('/astrbot-qo-webhook/callback', view_func=self.callback, methods=['POST'])
+        self.client = botpy_client
+        self.event_queue = event_queue
+        
+    async def initialize(self):
+        logger.info(f"正在登录到 QQ 官方机器人...")
+        self.user = await self.http.login(self.token)
+        logger.info(f"已登录 QQ 官方机器人账号: {self.user}")
+        # 直接注入到 botpy 的 Client，移花接木！
+        self.client.api = self.api
+        self.client.http = self.http
+        
+        async def bot_connect():
+            pass
+        
+        self._connection = ConnectionSession(
+            max_async=1,
+            connect=bot_connect,
+            dispatch=self.client.ws_dispatch,
+            loop=asyncio.get_event_loop(),
+            api=self.api,
+        )
+
+    async def repeat_seed(self, bot_secret: str, target_size: int = 32) -> bytes:
+        seed = bot_secret
+        while len(seed) < target_size:
+            seed *= 2
+        return seed[:target_size].encode('utf-8')
+
+        
+    async def webhook_validation(self, validation_payload: dict):
+        seed = await self.repeat_seed(self.secret)
+        private_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed)
+        msg = validation_payload.get("event_ts", "") + validation_payload.get("plain_token", "")
+        # sign
+        signature = private_key.sign(msg.encode()).hex()
+        response = {
+            "plain_token": validation_payload.get("plain_token"),
+            "signature": signature
+        }
+        return response
+        
+    async def callback(self):
+        msg: dict = await quart.request.json
+        logger.debug(f"收到 qq_official_webhook 回调: {msg}")
+
+        event = msg.get("t")
+        opcode = msg.get("op")
+        data = msg.get("d")
+        
+        if opcode == 13:
+            # validation
+            signed = await self.webhook_validation(data)
+            print(signed)
+            return signed
+
+        if event and opcode == BotWebSocket.WS_DISPATCH_EVENT:
+            event = msg["t"].lower()
+            try:
+                func = self._connection.parser[event]
+            except KeyError:
+                logger.error("_parser unknown event %s.", event)
+            else:
+                func(msg)
+                
+        return {"opcode": 12}
+    
+    async def start_polling(self):
+        await self.server.run_task(
+            host='0.0.0.0', 
+            port=self.port, 
+            shutdown_trigger=self.shutdown_trigger_placeholder
+        )
+        
+    async def shutdown_trigger_placeholder(self):
+        while not self.event_queue.closed:
+            await asyncio.sleep(1)
+        logger.info("qq_official_webhook 适配器已关闭。")
+        

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

@@ -0,0 +1,112 @@
+import time
+import asyncio
+import uuid
+import os
+from typing import Awaitable, Any
+from astrbot.api.platform import Platform, AstrBotMessage, MessageMember, MessageType, PlatformMetadata
+from astrbot.api.event import MessageChain
+from astrbot.api.message_components import Plain, Image, Record  # noqa: F403
+from astrbot.api import logger
+from astrbot.core import web_chat_queue, web_chat_back_queue
+from .webchat_event import WebChatMessageEvent
+from astrbot.core.platform.astr_message_event import MessageSesion
+from ...register import register_platform_adapter
+
+class QueueListener:
+    def __init__(self, queue: asyncio.Queue, callback: callable) -> None:
+        self.queue = queue
+        self.callback = callback
+        
+    async def run(self):
+        while True:
+            data = await self.queue.get()
+            await self.callback(data)
+
+@register_platform_adapter("webchat", "webchat")
+class WebChatAdapter(Platform):
+    def __init__(self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue) -> None:
+        super().__init__(event_queue)
+        
+        self.config = platform_config
+        self.settings = platform_settings
+        self.unique_session = platform_settings['unique_session']
+        self.imgs_dir = "data/webchat/imgs"
+
+        self.metadata = PlatformMetadata(
+            "webchat",
+            "webchat",
+        )
+        
+    async def send_by_session(self, session: MessageSesion, message_chain: MessageChain):
+        # abm.session_id = f"webchat!{username}!{cid}"
+        plain = ""
+        cid = session.session_id.split("!")[-1]
+        for comp in message_chain.chain:
+            if isinstance(comp, Plain):
+                plain += comp.text
+        web_chat_back_queue.put_nowait((plain, cid))
+        
+        await super().send_by_session(session, message_chain)
+        
+    async def convert_message(self, data: tuple) -> AstrBotMessage:
+        username, cid, payload = data
+        
+        
+        abm = AstrBotMessage()
+        abm.self_id = "webchat"
+        abm.tag = "webchat"
+        abm.sender = MessageMember(username, username)        
+
+        abm.type = MessageType.FRIEND_MESSAGE
+        
+        abm.session_id = f"webchat!{username}!{cid}"
+        
+        abm.message_id = str(uuid.uuid4())
+        abm.message = []
+        
+        if payload['message']:
+            abm.message.append(Plain(payload['message']))
+        if payload['image_url']:
+            if isinstance(payload['image_url'], list):
+                for img in payload['image_url']:
+                    abm.message.append(Image.fromFileSystem(os.path.join(self.imgs_dir, img)))
+            else:
+                abm.message.append(Image.fromFileSystem(os.path.join(self.imgs_dir, payload['image_url'])))
+        if payload['audio_url']:
+            if isinstance(payload['audio_url'], list):
+                for audio in payload['audio_url']:
+                    path = os.path.join(self.imgs_dir, audio)
+                    abm.message.append(Record(file=path, path=path))
+            else:
+                path = os.path.join(self.imgs_dir, payload['audio_url'])
+                abm.message.append(Record(file=path, path=path))
+            
+        logger.debug(f"WebChatAdapter: {abm.message}")
+        
+        message_str = payload['message']
+        abm.timestamp = int(time.time())
+        abm.message_str = message_str
+        abm.raw_message = data
+        return abm
+    
+    def run(self) -> Awaitable[Any]:
+        async def callback(data: tuple):
+            abm = await self.convert_message(data)
+            await self.handle_msg(abm)
+            
+        bot = QueueListener(web_chat_queue, callback)
+        return bot.run()
+    
+    def meta(self) -> PlatformMetadata:
+        return self.metadata
+
+    async def handle_msg(self, message: AstrBotMessage):
+        
+        message_event = WebChatMessageEvent(
+            message_str=message.message_str,
+            message_obj=message,
+            platform_meta=self.meta(),
+            session_id=message.session_id
+        )
+        
+        self.commit_event(message_event)

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

@@ -0,0 +1,50 @@
+import os
+import uuid
+import base64
+from astrbot.api import logger
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.message_components import Plain, Image
+from astrbot.core.utils.io import download_image_by_url
+from astrbot.core import web_chat_back_queue
+
+class WebChatMessageEvent(AstrMessageEvent):
+    def __init__(self, message_str, message_obj, platform_meta, session_id):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.imgs_dir = "data/webchat/imgs"
+        os.makedirs(self.imgs_dir, exist_ok=True)        
+
+    async def send(self, message: MessageChain):
+        if not message:
+            web_chat_back_queue.put_nowait(None)
+            return
+        
+        cid = self.session_id.split("!")[-1]
+        
+        for comp in message.chain:
+            if isinstance(comp, Plain):
+                web_chat_back_queue.put_nowait((comp.text, cid))
+            elif isinstance(comp, Image):
+                # save image to local
+                filename = str(uuid.uuid4()) + ".jpg"
+                path = os.path.join(self.imgs_dir, filename)
+                if comp.file and comp.file.startswith("file:///"):
+                    ph = comp.file[8:]
+                    with open(path, "wb") as f:
+                        with open(ph, "rb") as f2:
+                            f.write(f2.read())
+                elif comp.file.startswith("base64://"):
+                    base64_str = comp.file[9:]
+                    image_data = base64.b64decode(base64_str)
+                    with open(path, "wb") as f:
+                        f.write(image_data)
+                elif comp.file and comp.file.startswith("http"):
+                    await download_image_by_url(comp.file, path=path)
+                else:
+                    with open(path, "wb") as f:
+                        with open(comp.file, "rb") as f2:
+                            f.write(f2.read())
+                web_chat_back_queue.put_nowait((f"[IMAGE]{filename}", cid))
+            else:
+                logger.debug(f"webchat 忽略: {comp.type}")
+        web_chat_back_queue.put_nowait(None)
+        await super().send(message)

astrbot/core/provider/__init__.py

@@ -0,0 +1,10 @@
+from .provider import Provider, Personality, STTProvider
+
+from .entites import ProviderMetaData
+
+__all__ = [
+    "Provider",
+    "Personality",
+    "ProviderMetaData",
+    "STTProvider"
+]

astrbot/core/provider/entites.py

@@ -0,0 +1,64 @@
+import enum
+from dataclasses import dataclass, field
+from typing import List, Dict, Type
+from .func_tool_manager import FuncCall
+from openai.types.chat.chat_completion import ChatCompletion
+from astrbot.core.db.po import Conversation
+
+
+class ProviderType(enum.Enum):
+    CHAT_COMPLETION = "chat_completion"
+    SPEECH_TO_TEXT = "speech_to_text"
+    TEXT_TO_SPEECH = "text_to_speech"
+    
+@dataclass
+class ProviderMetaData():
+    type: str
+    '''提供商适配器名称，如 openai, ollama'''
+    desc: str = ""
+    '''提供商适配器描述.'''
+    provider_type: ProviderType = ProviderType.CHAT_COMPLETION
+    cls_type: Type = None
+    
+    default_config_tmpl: dict = None
+    '''平台的默认配置模板'''
+    provider_display_name: str = None
+    '''显示在 WebUI 配置页中的提供商名称，如空则是 type'''
+
+@dataclass
+class ProviderRequest():
+    prompt: str
+    '''提示词'''
+    session_id: str = ""
+    '''会话 ID'''
+    image_urls: List[str] = None
+    '''图片 URL 列表'''
+    func_tool: FuncCall = None
+    '''工具'''
+    contexts: List = None
+    '''上下文。格式与 openai 的上下文格式一致：
+    参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
+    '''
+    system_prompt: str = ""
+    '''系统提示词'''
+    conversation: Conversation = None
+    
+    def __repr__(self):
+        return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self.contexts}, system_prompt={self.system_prompt})"
+    
+    def __str__(self):
+        return self.__repr__()
+    
+@dataclass
+class LLMResponse:
+    role: str
+    '''角色, assistant, tool, err'''
+    completion_text: str = ""
+    '''LLM 返回的文本'''
+    tools_call_args: List[Dict[str, any]] = field(default_factory=list)
+    '''工具调用参数'''
+    tools_call_name: List[str] = field(default_factory=list)
+    '''工具调用名称'''
+    
+    raw_completion: ChatCompletion = None
+    _new_record: Dict[str, any] = None

astrbot/core/provider/func_tool_manager.py

@@ -0,0 +1,228 @@
+import json
+import textwrap
+from typing import Dict, List, Awaitable
+from dataclasses import dataclass
+
+
+@dataclass
+class FuncTool:
+    """
+    用于描述一个函数调用工具。
+    """
+
+    name: str
+    parameters: Dict
+    description: str
+    handler: Awaitable
+    handler_module_path: str = None # 必须要保留这个，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'''
+
+SUPPORTED_TYPES = [
+    "string",
+    "number",
+    "object",
+    "array",
+    "boolean",
+]  # json schema 支持的数据类型
+
+
+class FuncCall:
+    def __init__(self) -> None:
+        self.func_list: List[FuncTool] = []
+
+    def empty(self) -> bool:
+        return len(self.func_list) == 0
+
+    def add_func(
+        self,
+        name: str,
+        func_args: list,
+        desc: str,
+        handler: Awaitable,
+    ) -> None:
+        """
+        为函数调用（function-calling / tools-use）添加工具。
+
+        @param name: 函数名
+        @param func_args: 函数参数列表，格式为 [{"type": "string", "name": "arg_name", "description": "arg_description"}, ...]
+        @param desc: 函数描述
+        @param func_obj: 处理函数
+        """
+        params = {
+            "type": "object",  # hard-coded here
+            "properties": {},
+        }
+        for param in func_args:
+            params["properties"][param["name"]] = {
+                "type": param["type"],
+                "description": param["description"],
+            }
+        _func = FuncTool(
+            name=name,
+            parameters=params,
+            description=desc,
+            handler=handler,
+        )
+        self.func_list.append(_func)
+
+    def remove_func(self, name: str) -> None:
+        """
+        删除一个函数调用工具。
+        """
+        for i, f in enumerate(self.func_list):
+            if f["name"] == name:
+                self.func_list.pop(i)
+                break
+
+    def get_func(self, name) -> FuncTool:
+        for f in self.func_list:
+            if f.name == name:
+                return f
+        return None
+
+    def get_func_desc_openai_style(self) -> list:
+        """
+        获得 OpenAI API 风格的**已经激活**的工具描述
+        """
+        _l = []
+        for f in self.func_list:
+            if not f.active:
+                continue
+            _l.append(
+                {
+                    "type": "function",
+                    "function": {
+                        "name": f.name,
+                        "parameters": f.parameters,
+                        "description": f.description,
+                    },
+                }
+            )
+        return _l
+    
+    def get_func_desc_anthropic_style(self) -> list:
+        """
+        获得 Anthropic API 风格的**已经激活**的工具描述
+        """
+        tools = []
+        for f in self.func_list:
+            if not f.active:
+                continue
+
+            # Convert internal format to Anthropic style
+            tool = {
+                "name": f.name,
+                "description": f.description,
+                "input_schema": {
+                    "type": "object",
+                    "properties": f.parameters.get("properties", {}),
+                    # Keep the required field from the original parameters if it exists
+                    "required": f.parameters.get("required", [])
+                }
+            }
+            tools.append(tool)
+        return tools
+    
+    def get_func_desc_google_genai_style(self) -> Dict:
+        declarations = {}
+        tools = []
+        for f in self.func_list:
+            if not f.active:
+                continue
+
+            func_declaration = {
+                "name": f.name,
+                "description": f.description
+            }
+
+            # 检查并添加非空的properties参数
+            params = f.parameters if isinstance(f.parameters, dict) else {}
+            if params.get("properties", {}):
+                func_declaration["parameters"] = params
+
+            tools.append(func_declaration)
+
+        if tools:
+            declarations["function_declarations"] = tools
+        return declarations
+        
+
+    async def func_call(self, question: str, session_id: str, provider) -> tuple:
+        _l = []
+        for f in self.func_list:
+            if not f.active:
+                continue
+            _l.append(
+                {
+                    "name": f["name"],
+                    "parameters": f["parameters"],
+                    "description": f["description"],
+                }
+            )
+        func_definition = json.dumps(_l, ensure_ascii=False)
+
+        prompt = textwrap.dedent(f"""
+            ROLE:
+            你是一个 Function calling AI Agent, 你的任务是将用户的提问转化为函数调用。
+
+            TOOLS:
+            可用的函数列表:
+
+            {func_definition}
+
+            LIMIT:
+            1. 你返回的内容应当能够被 Python 的 json 模块解析的 Json 格式字符串。
+            2. 你的 Json 返回的格式如下：`[{{"name": "<func_name>", "args": <arg_dict>}}, ...]`。参数根据上面提供的函数列表中的参数来填写。
+            3. 允许必要时返回多个函数调用，但需保证这些函数调用的顺序正确。
+            4. 如果用户的提问中不需要用到给定的函数，请直接返回 `{{"res": False}}`。
+
+            EXAMPLE:
+            1. `用户提问`：请问一下天气怎么样？ `函数调用`：[{{"name": "get_weather", "args": {{"city": "北京"}}}}]
+
+            用户的提问是：{question}
+        """)
+
+        _c = 0
+        while _c < 3:
+            try:
+                res = await provider.text_chat(prompt, session_id)
+                if res.find("```") != -1:
+                    res = res[res.find("```json") + 7 : res.rfind("```")]
+                res = json.loads(res)
+                break
+            except Exception as e:
+                _c += 1
+                if _c == 3:
+                    raise e
+                if "The message you submitted was too long" in str(e):
+                    raise e
+
+        if "res" in res and not res["res"]:
+            return "", False
+
+        tool_call_result = []
+        for tool in res:
+            # 说明有函数调用
+            func_name = tool["name"]
+            args = tool["args"]
+            # 调用函数
+            tool_callable = None
+            for func in self.func_list:
+                if func.name == func_name:
+                    tool_callable = func.star_handler_metadata.handler
+                    break
+            if not tool_callable:
+                raise Exception(f"Request function {func_name} not found.")
+            ret = await tool_callable(**args)
+            if ret:
+                tool_call_result.append(str(ret))
+        return tool_call_result, True
+
+    
+    def __str__(self):
+        return str(self.func_list)
+    
+    def __repr__(self):
+        return str(self.func_list)

astrbot/core/provider/manager.py

@@ -0,0 +1,244 @@
+import traceback
+import uuid
+from astrbot.core.config.astrbot_config import AstrBotConfig
+from .provider import Provider, STTProvider, TTSProvider, Personality
+from .entites import ProviderType
+from typing import List
+from astrbot.core.db import BaseDatabase
+from collections import defaultdict
+from .register import provider_cls_map, llm_tools
+from astrbot.core import logger, sp
+
+class ProviderManager():
+    def __init__(self, config: AstrBotConfig, db_helper: BaseDatabase):
+        self.providers_config: List = config['provider']
+        self.provider_settings: dict = config['provider_settings']
+        self.provider_stt_settings: dict = config.get('provider_stt_settings', {})
+        self.provider_tts_settings: dict = config.get('provider_tts_settings', {})
+        self.persona_configs: list = config.get('persona', [])
+        
+        # 人格情景管理
+        # 目前没有拆成独立的模块
+        self.default_persona_name = self.provider_settings.get('default_personality', 'default')
+        self.personas: List[Personality] = []
+        self.selected_default_persona = None
+        for persona in self.persona_configs:
+            begin_dialogs = persona.get("begin_dialogs", [])
+            mood_imitation_dialogs = persona.get("mood_imitation_dialogs", [])
+            bd_processed = []
+            mid_processed = ""
+            if begin_dialogs:
+                if len(begin_dialogs) % 2 != 0:
+                    logger.error(f"{persona['name']} 人格情景预设对话格式不对，条数应该为偶数。")
+                    begin_dialogs = []
+                user_turn = True
+                for dialog in begin_dialogs:
+                    bd_processed.append({
+                        "role": "user" if user_turn else "assistant",
+                        "content": dialog,
+                        "_no_save": None # 不持久化到 db
+                    })
+                    user_turn = not user_turn
+            if mood_imitation_dialogs:
+                if len(mood_imitation_dialogs) % 2 != 0:
+                    logger.error(f"{persona['name']} 对话风格对话格式不对，条数应该为偶数。")
+                    mood_imitation_dialogs = []
+                user_turn = True
+                for dialog in mood_imitation_dialogs:
+                    role = "A" if user_turn else "B"
+                    mid_processed += f"{role}: {dialog}\n"
+                    if not user_turn:
+                        mid_processed += '\n'
+                    user_turn = not user_turn
+            
+            try:
+                persona = Personality(
+                    **persona, 
+                    _begin_dialogs_processed=bd_processed,
+                    _mood_imitation_dialogs_processed=mid_processed
+                )
+                if persona['name'] == self.default_persona_name:
+                    self.selected_default_persona = persona
+                self.personas.append(persona)
+            except Exception as e:
+                logger.error(f"解析 Persona 配置失败：{e}")
+        
+        if not self.selected_default_persona and len(self.personas) > 0:
+            # 默认选择第一个
+            self.selected_default_persona = self.personas[0]
+            
+        if not self.selected_default_persona:
+            self.selected_default_persona = Personality(
+                prompt="You are a helpful and friendly assistant.",
+                name="default",
+                _begin_dialogs_processed=[],
+                _mood_imitation_dialogs_processed=""
+            )
+            self.personas.append(self.selected_default_persona)
+                
+        
+        self.provider_insts: List[Provider] = []
+        '''加载的 Provider 的实例'''
+        self.stt_provider_insts: List[STTProvider] = []
+        '''加载的 Speech To Text Provider 的实例'''
+        self.tts_provider_insts: List[TTSProvider] = []
+        '''加载的 Text To Speech Provider 的实例'''
+        self.llm_tools = llm_tools
+        self.curr_provider_inst: Provider = None
+        '''当前使用的 Provider 实例'''
+        self.curr_stt_provider_inst: STTProvider = None
+        '''当前使用的 Speech To Text Provider 实例'''
+        self.curr_tts_provider_inst: TTSProvider = None
+        '''当前使用的 Text To Speech Provider 实例'''
+        self.loaded_ids = defaultdict(bool)
+        self.db_helper = db_helper
+        
+        # kdb(experimental)
+        self.curr_kdb_name = ""
+        kdb_cfg = config.get("knowledge_db", {})
+        if kdb_cfg and len(kdb_cfg):
+            self.curr_kdb_name = list(kdb_cfg.keys())[0]
+        
+        changed = False
+        for provider_cfg in self.providers_config:
+            if not provider_cfg['enable']:
+                continue
+            
+            if provider_cfg['id'] in self.loaded_ids:
+                new_id = f"{provider_cfg['id']}_{str(uuid.uuid4())[:8]}"
+                logger.info(f"Provider ID 重复：{provider_cfg['id']}。已自动更改为 {new_id}。")
+                provider_cfg['id'] = new_id
+                changed = True
+            self.loaded_ids[provider_cfg['id']] = True
+            
+            try:
+                match provider_cfg['type']:
+                    case "openai_chat_completion":
+                        from .sources.openai_source import ProviderOpenAIOfficial as ProviderOpenAIOfficial
+                    case "zhipu_chat_completion":
+                        from .sources.zhipu_source import ProviderZhipu as ProviderZhipu
+                    case "anthropic_chat_completion":
+                        from .sources.anthropic_source import ProviderAnthropic as ProviderAnthropic
+                    case "llm_tuner":
+                        logger.info("加载 LLM Tuner 工具 ...")
+                        from .sources.llmtuner_source import LLMTunerModelLoader as LLMTunerModelLoader
+                    case "dify":
+                        from .sources.dify_source import ProviderDify as ProviderDify
+                    case "dashscope":
+                        from .sources.dashscope_source import ProviderDashscope as ProviderDashscope
+                    case "googlegenai_chat_completion":
+                        from .sources.gemini_source import ProviderGoogleGenAI as ProviderGoogleGenAI
+                    case "openai_whisper_api":
+                        from .sources.whisper_api_source import ProviderOpenAIWhisperAPI as ProviderOpenAIWhisperAPI
+                    case "openai_whisper_selfhost":
+                        from .sources.whisper_selfhosted_source import ProviderOpenAIWhisperSelfHost as ProviderOpenAIWhisperSelfHost
+                    case "openai_tts_api":
+                        from .sources.openai_tts_api_source import ProviderOpenAITTSAPI as ProviderOpenAITTSAPI
+                    case "fishaudio_tts_api":
+                        from .sources.fishaudio_tts_api_source import ProviderFishAudioTTSAPI as ProviderFishAudioTTSAPI
+            except (ImportError, ModuleNotFoundError) as e:
+                logger.critical(f"加载 {provider_cfg['type']}({provider_cfg['id']}) 提供商适配器失败：{e}。可能是因为有未安装的依赖。")
+                continue
+            except Exception as e:
+                logger.critical(f"加载 {provider_cfg['type']}({provider_cfg['id']}) 提供商适配器失败：{e}。未知原因")
+                continue
+        
+        if changed:
+            try:
+                config.save_config()
+            except Exception as e:
+                logger.warning(f"保存配置文件失败：{e}")
+
+    async def initialize(self):
+        
+        selected_provider_id = sp.get("curr_provider")
+        selected_stt_provider_id = self.provider_stt_settings.get("provider_id")
+        selected_tts_provider_id = self.provider_settings.get("provider_id")
+        provider_enabled = self.provider_settings.get("enable", False)
+        stt_enabled = self.provider_stt_settings.get("enable", False)
+        tts_enabled = self.provider_tts_settings.get("enable", False)
+            
+        for provider_config in self.providers_config:
+            if not provider_config['enable']:
+                continue
+            if provider_config['type'] not in provider_cls_map:
+                logger.error(f"未找到适用于 {provider_config['type']}({provider_config['id']}) 的提供商适配器，请检查是否已经安装或者名称填写错误。已跳过。")
+                continue
+
+            provider_metadata = provider_cls_map[provider_config['type']]
+            logger.debug(f"尝试实例化 {provider_config['type']}({provider_config['id']}) 提供商适配器 ...")
+            try:
+                # 按任务实例化提供商
+                
+                if provider_metadata.provider_type == ProviderType.SPEECH_TO_TEXT:
+                    # STT 任务
+                    inst = provider_metadata.cls_type(provider_config, self.provider_settings)
+                    
+                    if getattr(inst, "initialize", None):
+                        await inst.initialize()
+                    
+                    self.stt_provider_insts.append(inst)
+                    if selected_stt_provider_id == provider_config['id'] and stt_enabled:
+                        self.curr_stt_provider_inst = inst
+                        logger.info(f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前语音转文本提供商适配器。")
+                        
+                elif provider_metadata.provider_type == ProviderType.TEXT_TO_SPEECH:
+                    # TTS 任务
+                    inst = provider_metadata.cls_type(provider_config, self.provider_settings)
+                    
+                    if getattr(inst, "initialize", None):
+                        await inst.initialize()
+                    
+                    self.tts_provider_insts.append(inst)
+                    if selected_tts_provider_id == provider_config['id'] and tts_enabled:
+                        self.curr_tts_provider_inst = inst
+                        logger.info(f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前文本转语音提供商适配器。")
+                    
+                elif provider_metadata.provider_type == ProviderType.CHAT_COMPLETION:
+                    # 文本生成任务
+                    inst = provider_metadata.cls_type(
+                        provider_config, 
+                        self.provider_settings, 
+                        self.db_helper,
+                        self.provider_settings.get('persistant_history', True),
+                        self.selected_default_persona
+                    )
+                    
+                    if getattr(inst, "initialize", None):
+                        await inst.initialize()
+                    
+                    self.provider_insts.append(inst)
+                    if selected_provider_id == provider_config['id'] and provider_enabled:
+                        self.curr_provider_inst = inst
+                        logger.info(f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前提供商适配器。")
+                        
+            except Exception as e:
+                traceback.print_exc()
+                logger.error(f"实例化 {provider_config['type']}({provider_config['id']}) 提供商适配器失败：{e}")
+        
+        if len(self.provider_insts) > 0 and not self.curr_provider_inst and provider_enabled:
+            self.curr_provider_inst = self.provider_insts[0]
+            
+        if len(self.stt_provider_insts) > 0 and not self.curr_stt_provider_inst and stt_enabled:
+            self.curr_stt_provider_inst = self.stt_provider_insts[0]
+            
+        if len(self.tts_provider_insts) > 0 and not self.curr_tts_provider_inst and tts_enabled:
+            self.curr_tts_provider_inst = self.tts_provider_insts[0]
+            
+        if not self.curr_provider_inst:
+            logger.warning("未启用任何用于 文本生成 的提供商适配器。")
+            
+        if stt_enabled and not self.curr_stt_provider_inst:
+                logger.warning("未启用任何用于 语音转文本 的提供商适配器。")
+        
+        if tts_enabled and not self.curr_tts_provider_inst:
+                logger.warning("未启用任何用于 文本转语音 的提供商适配器。")
+        
+
+    def get_insts(self):
+        return self.provider_insts
+    
+    async def terminate(self):
+        for provider_inst in self.provider_insts:
+            if hasattr(provider_inst, "terminate"):
+                await provider_inst.terminate()

astrbot/core/provider/provider.py

@@ -0,0 +1,152 @@
+import abc
+import json
+from collections import defaultdict
+from typing import List
+from astrbot.core.db import BaseDatabase
+from astrbot.core import logger
+from typing import TypedDict
+from astrbot.core.provider.func_tool_manager import FuncCall
+from astrbot.core.provider.entites import LLMResponse
+from dataclasses import dataclass
+
+
+class Personality(TypedDict):
+    prompt: str = ""
+    name: str = ""
+    begin_dialogs: List[str] = []
+    mood_imitation_dialogs: List[str] = []
+    
+    # cache
+    _begin_dialogs_processed: List[dict] = []
+    _mood_imitation_dialogs_processed: str = ""
+    
+    
+@dataclass
+class ProviderMeta():
+    id: str
+    model: str
+    type: str
+    
+    
+class AbstractProvider(abc.ABC):
+    def __init__(self, provider_config: dict) -> None:
+        super().__init__()
+        self.model_name = ""
+        self.provider_config = provider_config
+
+    def set_model(self, model_name: str):
+        '''设置当前使用的模型名称'''
+        self.model_name = model_name
+    
+    def get_model(self) -> str:
+        '''获得当前使用的模型名称'''
+        return self.model_name
+    
+    def meta(self) -> ProviderMeta:
+        '''获取 Provider 的元数据'''
+        return ProviderMeta(
+            id=self.provider_config['id'],
+            model=self.get_model(),
+            type=self.provider_config['type']
+        )
+
+
+class Provider(AbstractProvider):
+    def __init__(
+        self, 
+        provider_config: dict,
+        provider_settings: dict, 
+        persistant_history: bool = True,
+        db_helper: BaseDatabase = None,
+        default_persona: Personality = None
+    ) -> None:
+        super().__init__(provider_config)
+        
+        self.provider_settings = provider_settings
+        
+        self.curr_personality: Personality = default_persona
+        '''维护了当前的使用的 persona，即人格。可能为 None'''
+
+    @abc.abstractmethod
+    def get_current_key(self) -> str:
+        raise NotImplementedError()
+    
+    def get_keys(self) -> List[str]:
+        '''获得提供商 Key'''
+        return self.provider_config.get("key", [])
+    
+    @abc.abstractmethod
+    def set_key(self, key: str):
+        raise NotImplementedError()
+    
+    @abc.abstractmethod
+    def get_models(self) -> List[str]:
+        '''获得支持的模型列表'''
+        raise NotImplementedError()
+    
+    @abc.abstractmethod
+    async def text_chat(self,
+                        prompt: str,
+                        session_id: str=None,
+                        image_urls: List[str]=None,
+                        func_tool: FuncCall=None,
+                        contexts: List=None,
+                        system_prompt: str=None,
+                        **kwargs) -> LLMResponse:
+        '''获得 LLM 的文本对话结果。会使用当前的模型进行对话。
+        
+        Args:
+            prompt: 提示词
+            session_id: 会话 ID(此属性已经被废弃)
+            image_urls: 图片 URL 列表
+            tools: Function-calling 工具
+            contexts: 上下文
+            kwargs: 其他参数
+            
+        Notes:
+            - 如果传入了 image_urls，将会在对话时附上图片。如果模型不支持图片输入，将会抛出错误。
+            - 如果传入了 tools，将会使用 tools 进行 Function-calling。如果模型不支持 Function-calling，将会抛出错误。
+        '''
+        raise NotImplementedError()
+
+    async def pop_record(self, context: List):
+        '''
+        弹出 context 第一条非系统提示词对话记录
+        '''
+        poped = 0
+        indexs_to_pop = []
+        for idx, record in enumerate(context):
+            if record["role"] == "system":
+                continue
+            else:
+                indexs_to_pop.append(idx)
+                poped += 1
+                if poped == 2:
+                    break
+                
+        for idx in reversed(indexs_to_pop):
+            context.pop(idx)
+
+        
+class STTProvider(AbstractProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+    
+    @abc.abstractmethod
+    async def get_text(self, audio_url: str) -> str:
+        '''获取音频的文本'''
+        raise NotImplementedError()
+
+
+class TTSProvider(AbstractProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+    
+    @abc.abstractmethod
+    async def get_audio(self, text: str) -> str:
+        '''获取文本的音频，返回音频文件路径'''
+        raise NotImplementedError()

astrbot/core/provider/register.py

@@ -0,0 +1,47 @@
+from typing import List, Dict, Type
+from .entites import ProviderMetaData, ProviderType
+from astrbot.core import logger
+from .func_tool_manager import FuncCall
+
+provider_registry: List[ProviderMetaData] = []
+'''维护了通过装饰器注册的 Provider'''
+provider_cls_map: Dict[str, ProviderMetaData] = {}
+'''维护了 Provider 类型名称和 ProviderMetadata 的映射'''
+
+llm_tools = FuncCall()
+
+def register_provider_adapter(
+    provider_type_name: str, 
+    desc: str, 
+    provider_type: ProviderType = ProviderType.CHAT_COMPLETION,
+    default_config_tmpl: dict = None,
+    provider_display_name: str = None
+):
+    '''用于注册平台适配器的带参装饰器'''
+    def decorator(cls):
+        if provider_type_name in provider_cls_map:
+            raise ValueError(f"检测到大模型提供商适配器 {provider_type_name} 已经注册，可能发生了大模型提供商适配器类型命名冲突。")
+        
+        # 添加必备选项
+        if default_config_tmpl:
+            if 'type' not in default_config_tmpl:
+                default_config_tmpl['type'] = provider_type_name
+            if 'enable' not in default_config_tmpl:
+                default_config_tmpl['enable'] = False
+            if 'id' not in default_config_tmpl:
+                default_config_tmpl['id'] = provider_type_name
+
+        pm = ProviderMetaData(
+            type=provider_type_name,
+            desc=desc,
+            provider_type=provider_type,
+            cls_type=cls,
+            default_config_tmpl=default_config_tmpl,
+            provider_display_name=provider_display_name
+        )
+        provider_registry.append(pm)
+        provider_cls_map[provider_type_name] = pm
+        logger.debug(f"服务提供商 Provider {provider_type_name} 已注册")
+        return cls
+    
+    return decorator

astrbot/core/provider/sources/anthropic_source.py

@@ -0,0 +1,189 @@
+from typing import List
+from mimetypes import guess_type
+
+from anthropic import AsyncAnthropic
+from anthropic.types import Message
+
+from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.db import BaseDatabase
+from astrbot.api.provider import Provider, Personality
+from astrbot import logger
+from astrbot.core.provider.func_tool_manager import FuncCall
+from ..register import register_provider_adapter
+from astrbot.core.provider.entites import LLMResponse
+from .openai_source import ProviderOpenAIOfficial
+
+@register_provider_adapter("anthropic_chat_completion", "Anthropic Claude API 提供商适配器")
+class ProviderAnthropic(ProviderOpenAIOfficial):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+        db_helper: BaseDatabase,
+        persistant_history = True,
+        default_persona: Personality = None
+    ) -> None:
+        # Skip OpenAI's __init__ and call Provider's __init__ directly
+        Provider.__init__(self, provider_config, provider_settings, persistant_history, db_helper, default_persona)
+
+        self.chosen_api_key = None
+        self.api_keys: List = provider_config.get("key", [])
+        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.base_url = provider_config.get("api_base", "https://api.anthropic.com")
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+
+        self.client = AsyncAnthropic(
+            api_key=self.chosen_api_key,
+            timeout=self.timeout,
+            base_url=self.base_url
+        )
+        
+        self.set_model(provider_config['model_config']['model'])
+
+    async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
+        if tools:
+            tool_list = tools.get_func_desc_anthropic_style()
+            if tool_list:
+                payloads['tools'] = tool_list
+
+        completion = await self.client.messages.create(
+            **payloads,
+            stream=False
+        )
+
+        assert isinstance(completion, Message)
+        logger.debug(f"completion: {completion}")
+
+        if len(completion.content) == 0:
+            raise Exception("API 返回的 completion 为空。")
+        # TODO: 如果进行函数调用，思维链被截断，用户可能需要思维链的内容
+        # 选最后一条消息，如果要进行函数调用，anthropic会先返回文本消息的思维链，然后再返回函数调用请求
+        content = completion.content[-1]
+        
+        llm_response = LLMResponse("assistant")
+                
+        if content.type == "text":
+            # text completion
+            completion_text = str(content.text).strip()
+            llm_response.completion_text = completion_text
+        
+        # Anthropic每次只返回一个函数调用
+        if completion.stop_reason == "tool_use":
+            # tools call (function calling)
+            args_ls = []
+            func_name_ls = []
+            func_name_ls.append(content.name)
+            args_ls.append(content.input)
+            llm_response.role = "tool"
+            llm_response.tools_call_args = args_ls
+            llm_response.tools_call_name = func_name_ls
+
+        if not llm_response.completion_text and not llm_response.tools_call_args:
+            logger.error(f"API 返回的 completion 无法解析：{completion}。")
+            raise Exception(f"API 返回的 completion 无法解析：{completion}。")
+        
+        llm_response.raw_completion = completion
+        
+        return llm_response
+        
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        func_tool: FuncCall = None,
+        contexts=[],
+        system_prompt=None,
+        **kwargs
+    ) -> LLMResponse:
+        
+        if not prompt:
+            prompt = "<image>"
+    
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = [*contexts, new_record]
+
+        for part in context_query:
+            if '_no_save' in part:
+                del part['_no_save']
+
+        model_config = self.provider_config.get("model_config", {})
+
+        payloads = {
+            "messages": context_query,
+            **model_config
+        }
+        # Anthropic has a different way of handling system prompts
+        if system_prompt:
+            payloads['system'] = system_prompt
+
+        llm_response = None
+        try:
+            llm_response = await self._query(payloads, func_tool)
+
+        except Exception as e:
+            if "maximum context length" in str(e):
+                retry_cnt = 20
+                while retry_cnt > 0:
+                    logger.warning(f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}")
+                    try:
+                        await self.pop_record(context_query)
+                        response = await self.client.messages.create(
+                            messages=context_query,
+                            **model_config
+                        )
+                        llm_response = LLMResponse("assistant")
+                        llm_response.completion_text = response.content[0].text
+                        llm_response.raw_completion = response
+                        return llm_response
+                    except Exception as e:
+                        if "maximum context length" in str(e):
+                            retry_cnt -= 1
+                        else:
+                            raise e
+                return LLMResponse("err", "err: 请尝试 /reset 清除会话记录。")
+            else:
+                logger.error(f"发生了错误。Provider 配置如下: {model_config}")
+                raise e
+            
+        return llm_response
+
+    async def assemble_context(self, text: str, image_urls: List[str] = None):
+        '''组装上下文，支持文本和图片'''
+        if not image_urls:
+            return {"role": "user", "content": text}
+            
+        content = []
+        content.append({"type": "text", "text": text})
+        
+        for image_url in image_urls:
+            if image_url.startswith("http"):
+                image_path = await download_image_by_url(image_url)
+                image_data = await self.encode_image_bs64(image_path)
+            elif image_url.startswith("file:///"):
+                image_path = image_url.replace("file:///", "")
+                image_data = await self.encode_image_bs64(image_path)
+            else:
+                image_data = await self.encode_image_bs64(image_url)
+                
+            if not image_data:
+                logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
+                continue
+                
+            # Get mime type for the image
+            mime_type, _ = guess_type(image_url)
+            if not mime_type:
+                mime_type = "image/jpeg"  # Default to JPEG if can't determine
+                
+            content.append({
+                "type": "image",
+                "source": {
+                    "type": "base64",
+                    "media_type": mime_type,
+                    "data": image_data.split("base64,")[1] if "base64," in image_data else image_data
+                }
+            })
+            
+        return {"role": "user", "content": content}

astrbot/core/provider/sources/dashscope_source.py

@@ -0,0 +1,128 @@
+import asyncio
+import functools
+from typing import List
+from .. import Provider, Personality
+from ..entites import LLMResponse
+from ..func_tool_manager import FuncCall
+from astrbot.core.db import BaseDatabase
+from ..register import register_provider_adapter
+from .openai_source import ProviderOpenAIOfficial
+from astrbot.core import logger, sp
+from dashscope import Application
+
+
+@register_provider_adapter("dashscope", "Dashscope APP 适配器。")
+class ProviderDashscope(ProviderOpenAIOfficial):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+        db_helper: BaseDatabase,
+        persistant_history=False,
+        default_persona: Personality = None,
+    ) -> None:
+        Provider.__init__(
+            self,
+            provider_config,
+            provider_settings,
+            persistant_history,
+            db_helper,
+            default_persona,
+        )
+        self.api_key = provider_config.get("dashscope_api_key", "")
+        if not self.api_key:
+            raise Exception("阿里云百炼 API Key 不能为空。")
+        self.app_id = provider_config.get("dashscope_app_id", "")
+        if not self.app_id:
+            raise Exception("阿里云百炼 APP ID 不能为空。")
+        self.dashscope_app_type = provider_config.get("dashscope_app_type", "")
+        if not self.dashscope_app_type:
+            raise Exception("阿里云百炼 APP 类型不能为空。")
+        self.model_name = "dashscope"
+        self.variables: dict = provider_config.get("variables", {})
+
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        func_tool: FuncCall = None,
+        contexts: List = None,
+        system_prompt: str = None,
+        **kwargs,
+    ) -> LLMResponse:
+        # 获得会话变量
+        payload_vars = self.variables.copy()
+        # 动态变量
+        session_vars = sp.get("session_variables", {})
+        session_var = session_vars.get(session_id, {})
+        payload_vars.update(session_var)
+
+        if self.dashscope_app_type in ["agent", "dialog-workflow"]:
+            # 支持多轮对话的
+            new_record = {"role": "user", "content": prompt}
+            if image_urls:
+                logger.warning("阿里云百炼暂不支持图片输入，将自动忽略图片内容。")
+            contexts_no_img = await self._remove_image_from_context(contexts)
+            context_query = [*contexts_no_img, new_record]
+            if system_prompt:
+                context_query.insert(0, {"role": "system", "content": system_prompt})
+            for part in context_query:
+                if "_no_save" in part:
+                    del part["_no_save"]
+            # 调用阿里云百炼 API
+            partial = functools.partial(
+                Application.call,
+                app_id=self.app_id,
+                api_key=self.api_key,
+                messages=context_query,
+                biz_params=payload_vars or None,
+            )
+            response = await asyncio.get_event_loop().run_in_executor(None, partial)
+        else:
+            # 不支持多轮对话的
+            # 调用阿里云百炼 API
+            partial = functools.partial(
+                Application.call,
+                app_id=self.app_id,
+                promtp=prompt,
+                api_key=self.api_key,
+                biz_params=payload_vars or None,
+            )
+            response = await asyncio.get_event_loop().run_in_executor(None, partial)
+
+        logger.debug(f"dashscope resp: {response}")
+
+        if response.status_code != 200:
+            logger.error(
+                f"阿里云百炼请求失败: request_id={response.request_id}, code={response.status_code}, message={response.message}, 请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code"
+            )
+            return LLMResponse(
+                role="err",
+                completion_text=f"阿里云百炼请求失败: message={response.message} code={response.status_code}",
+            )
+
+        output_text = response.output.get("text", "")
+        return LLMResponse(role="assistant", completion_text=output_text)
+
+    async def forget(self, session_id):
+        return True
+
+    async def get_current_key(self):
+        return self.api_key
+
+    async def set_key(self, key):
+        raise Exception("阿里云百炼 适配器不支持设置 API Key。")
+
+    async def get_models(self):
+        return [self.get_model()]
+
+    async def get_human_readable_context(self, session_id, page, page_size):
+        raise Exception("暂不支持获得 阿里云百炼 的历史消息记录。")
+
+    async def terminate(self):
+        pass

astrbot/core/provider/sources/dify_source.py

@@ -0,0 +1,152 @@
+from typing import List
+from .. import Provider, Personality
+from ..entites import LLMResponse
+from ..func_tool_manager import FuncCall
+from astrbot.core.db import BaseDatabase
+from ..register import register_provider_adapter
+from astrbot.core.utils.dify_api_client import DifyAPIClient
+from astrbot.core.utils.io import download_image_by_url
+from astrbot.core import logger, sp
+
+@register_provider_adapter("dify", "Dify APP 适配器。")
+class ProviderDify(Provider):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+        db_helper: BaseDatabase,
+        persistant_history=False,
+        default_persona: Personality=None
+    ) -> None:
+        super().__init__(
+            provider_config, provider_settings, persistant_history, db_helper, default_persona
+        )
+        self.api_key = provider_config.get("dify_api_key", "")
+        if not self.api_key:
+            raise Exception("Dify API Key 不能为空。")
+        api_base = provider_config.get("dify_api_base", "https://api.dify.ai/v1")
+        self.api_client = DifyAPIClient(self.api_key, api_base)
+        self.api_type = provider_config.get("dify_api_type", "")
+        if not self.api_type:
+            raise Exception("Dify API 类型不能为空。")
+        self.model_name = "dify"
+        self.workflow_output_key = provider_config.get("dify_workflow_output_key", "astrbot_wf_output")
+        self.dify_query_input_key = provider_config.get("dify_query_input_key", "astrbot_text_query")
+        self.variables: dict = provider_config.get("variables", {})
+        if not self.dify_query_input_key:
+            self.dify_query_input_key = "astrbot_text_query"
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+        self.conversation_ids = {}
+        '''记录当前 session id 的对话 ID'''
+
+
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        func_tool: FuncCall = None,
+        contexts: List = None,
+        system_prompt: str = None,
+        **kwargs,
+    ) -> LLMResponse:
+        result = ""
+        conversation_id = self.conversation_ids.get(session_id, "")
+        
+        files_payload = []
+        for image_url in image_urls:
+            if image_url.startswith("http"):
+                image_path = await download_image_by_url(image_url)
+                file_response = await self.api_client.file_upload(image_path, user=session_id)
+                if 'id' not in file_response:
+                    logger.warning(f"上传图片后得到未知的 Dify 响应：{file_response}，图片将忽略。")
+                    continue
+                files_payload.append({
+                    "type": "image",
+                    "transfer_method": "local_file",
+                    "upload_file_id": file_response['id'],
+                })
+            else:
+                # TODO: 处理更多情况
+                logger.warning(f"未知的图片链接：{image_url}，图片将忽略。")
+        
+        # 获得会话变量
+        payload_vars = self.variables.copy()
+        # 动态变量
+        session_vars = sp.get("session_variables", {})
+        session_var = session_vars.get(session_id, {})
+        payload_vars.update(session_var)
+        
+        try:
+            match self.api_type:
+                case "chat" | "agent":
+                    async for chunk in self.api_client.chat_messages(
+                        inputs={
+                            **payload_vars,
+                        },
+                        query=prompt,
+                        user=session_id,
+                        conversation_id=conversation_id,
+                        files=files_payload,
+                        timeout=self.timeout
+                    ):
+                        logger.debug(f"dify resp chunk: {chunk}")
+                        if chunk['event'] == "message" or \
+                            chunk['event'] == "agent_message":
+                            result += chunk['answer']
+                            if not conversation_id:
+                                self.conversation_ids[session_id] = chunk['conversation_id']
+                                conversation_id = chunk['conversation_id']
+                
+                case "workflow":
+                    async for chunk in self.api_client.workflow_run(
+                        inputs={
+                            self.dify_query_input_key: prompt,
+                            "astrbot_session_id": session_id,
+                            **payload_vars,
+                        },
+                        user=session_id,
+                        files=files_payload,
+                        timeout=self.timeout
+                    ):
+                        match chunk['event']:
+                            case "workflow_started":
+                                logger.info(f"Dify 工作流(ID: {chunk['workflow_run_id']})开始运行。")
+                            case "node_finished":
+                                logger.debug(f"Dify 工作流节点(ID: {chunk['data']['node_id']} Title: {chunk['data'].get('title', '')})运行结束。")
+                            case "workflow_finished":
+                                logger.info(f"Dify 工作流(ID: {chunk['workflow_run_id']})运行结束。")
+                                if chunk['data']['error']:
+                                    logger.error(f"Dify 工作流出现错误：{chunk['data']['error']}")
+                                    raise Exception(f"Dify 工作流出现错误：{chunk['data']['error']}")
+                                if self.workflow_output_key not in chunk['data']['outputs']:
+                                    raise Exception(f"Dify 工作流的输出不包含指定的键名：{self.workflow_output_key}")
+                                result = chunk['data']['outputs'][self.workflow_output_key]
+                case _:
+                    raise Exception(f"未知的 Dify API 类型：{self.api_type}")
+        except Exception as e:
+            logger.error(f"Dify 请求失败：{str(e)}")
+            return LLMResponse(role="err", completion_text=f"Dify 请求失败：{str(e)}")
+        
+        return LLMResponse(role="assistant", completion_text=result)
+
+    async def forget(self, session_id):
+        self.conversation_ids[session_id] = ""
+        return True
+
+    async def get_current_key(self):
+        return self.api_key
+
+    async def set_key(self, key):
+        raise Exception("Dify 适配器不支持设置 API Key。")
+
+    async def get_models(self):
+        return [self.get_model()]
+
+    async def get_human_readable_context(self, session_id, page, page_size):
+        raise Exception("暂不支持获得 Dify 的历史消息记录。")
+
+    async def terminate(self):
+        await self.api_client.close()

astrbot/core/provider/sources/fishaudio_tts_api_source.py

@@ -0,0 +1,105 @@
+import uuid
+import ormsgpack
+from pydantic import BaseModel, conint
+from httpx import AsyncClient
+from typing import Annotated, Literal
+from ..provider import TTSProvider
+from ..entites import ProviderType
+from ..register import register_provider_adapter
+
+
+class ServeReferenceAudio(BaseModel):
+    audio: bytes
+    text: str
+
+
+class ServeTTSRequest(BaseModel):
+    text: str
+    chunk_length: Annotated[int, conint(ge=100, le=300, strict=True)] = 200
+    # 音频格式
+    format: Literal["wav", "pcm", "mp3"] = "mp3"
+    mp3_bitrate: Literal[64, 128, 192] = 128
+    # 参考音频
+    references: list[ServeReferenceAudio] = []
+    # 参考模型 ID
+    # 例如 https://fish.audio/m/7f92f8afb8ec43bf81429cc1c9199cb1/
+    # 其中reference_id为 7f92f8afb8ec43bf81429cc1c9199cb1
+    reference_id: str | None = None
+    # 对中英文文本进行标准化，这可以提高数字的稳定性
+    normalize: bool = True
+    # 平衡模式将延迟减少到300毫秒，但可能会降低稳定性
+    latency: Literal["normal", "balanced"] = "normal"
+
+
+@register_provider_adapter(
+    "fishaudio_tts_api", "FishAudio TTS API", provider_type=ProviderType.TEXT_TO_SPEECH
+)
+class ProviderFishAudioTTSAPI(TTSProvider):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.chosen_api_key: str = provider_config.get("api_key", "")
+        self.character: str = provider_config.get("fishaudio-tts-character", "可莉")
+        self.api_base: str = provider_config.get(
+            "api_base", "https://api.fish-audio.cn/v1"
+        )
+        self.headers = {
+            "Authorization": f"Bearer {self.chosen_api_key}",
+        }
+        self.set_model(provider_config.get("model", None))
+
+    async def _get_reference_id_by_character(self, character: str) -> str:
+        """
+        获取角色的reference_id
+
+        Args:
+            character: 角色名称
+
+        Returns:
+            reference_id: 角色的reference_id
+
+        exception:
+            APIException: 获取语音角色列表为空
+        """
+        sort_options = ["score", "task_count", "created_at"]
+        async with AsyncClient(base_url=self.api_base.replace("/v1", "")) as client:
+            for sort_by in sort_options:
+                params = {"title": character, "sort_by": sort_by}
+                response = await client.get(
+                    "/model", params=params, headers=self.headers
+                )
+                resp_data = response.json()
+                if resp_data["total"] == 0:
+                    continue
+                for item in resp_data["items"]:
+                    if character in item["title"]:
+                        return item["_id"]
+            return None
+
+    async def _generate_request(self, text: str) -> dict:
+        return ServeTTSRequest(
+            text=text,
+            format="wav",
+            reference_id=await self._get_reference_id_by_character(self.character),
+        )
+
+    async def get_audio(self, text: str) -> str:
+        path = f"data/temp/fishaudio_tts_api_{uuid.uuid4()}.wav"
+        self.headers["content-type"] = "application/msgpack"
+        request = await self._generate_request(text)
+        async with AsyncClient(base_url=self.api_base).stream(
+            "POST",
+            "/tts",
+            headers=self.headers,
+            content=ormsgpack.packb(request, option=ormsgpack.OPT_SERIALIZE_PYDANTIC),
+        ) as response:
+            if response.headers["content-type"] == "audio/wav":
+                with open(path, "wb") as f:
+                    async for chunk in response.aiter_bytes():
+                        f.write(chunk)
+                return path
+            text = await response.aread()
+            raise Exception(f"Fish Audio API请求失败: {text}")

astrbot/core/provider/sources/gemini_source.py

@@ -0,0 +1,284 @@
+import base64
+import aiohttp
+import random
+from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.db import BaseDatabase
+from astrbot.api.provider import Provider, Personality
+from astrbot import logger
+from astrbot.core.provider.func_tool_manager import FuncCall
+from typing import List
+from ..register import register_provider_adapter
+from astrbot.core.provider.entites import LLMResponse
+
+class SimpleGoogleGenAIClient():
+    def __init__(self, api_key: str, api_base: str, timeout: int=120) -> None:
+        self.api_key = api_key
+        if api_base.endswith("/"):
+            self.api_base = api_base[:-1]
+        else:
+            self.api_base = api_base
+        self.client = aiohttp.ClientSession(trust_env=True)
+        self.timeout = timeout
+        
+    async def models_list(self) -> List[str]:
+        request_url = f"{self.api_base}/v1beta/models?key={self.api_key}"
+        async with self.client.get(request_url, timeout=self.timeout) as resp:
+            response = await resp.json()
+            
+            models = []
+            for model in response["models"]:
+                if 'generateContent' in model["supportedGenerationMethods"]:
+                    models.append(model["name"].replace("models/", ""))
+            return models
+
+    async def generate_content(
+        self, 
+        contents: List[dict], 
+        model: str="gemini-1.5-flash", 
+        system_instruction: str="",
+        tools: dict=None
+    ):
+        payload = {}
+        if system_instruction:
+            payload["system_instruction"] = {
+                "parts": {"text": system_instruction}
+            }
+        if tools:
+            payload["tools"] = [tools]
+        payload["contents"] = contents
+        logger.debug(f"payload: {payload}")
+        request_url = f"{self.api_base}/v1beta/models/{model}:generateContent?key={self.api_key}"
+        async with self.client.post(request_url, json=payload, timeout=self.timeout) as resp:
+            if "application/json" in resp.headers.get("Content-Type"):
+                try:
+                    response = await resp.json()
+                except Exception as e:
+                    text = await resp.text()
+                    logger.error(f"Gemini 返回了非 json 数据: {text}")
+                    raise e
+                return response
+            else:
+                text = await resp.text()
+                logger.error(f"Gemini 返回了非 json 数据: {text}")
+                raise Exception("Gemini 返回了非 json 数据： ")
+
+
+@register_provider_adapter("googlegenai_chat_completion", "Google Gemini Chat Completion 提供商适配器")
+class ProviderGoogleGenAI(Provider):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+        db_helper: BaseDatabase, 
+        persistant_history = True,
+        default_persona: Personality=None
+    ) -> None:
+        super().__init__(provider_config, provider_settings, persistant_history, db_helper, default_persona)
+        self.chosen_api_key = None
+        self.api_keys: List = provider_config.get("key", [])
+        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.timeout = provider_config.get("timeout", 180)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+        self.client = SimpleGoogleGenAIClient(
+            api_key=self.chosen_api_key,
+            api_base=provider_config.get("api_base", None),
+            timeout=self.timeout
+        )
+        self.set_model(provider_config['model_config']['model'])
+
+    async def get_models(self):
+        return await self.client.models_list()
+    
+    async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
+        tool = None
+        if tools:
+            tool = tools.get_func_desc_google_genai_style()
+            if not tool:
+                tool = None
+        
+        system_instruction = ""
+        for message in payloads["messages"]:
+            if message["role"] == "system":
+                system_instruction = message["content"]
+                break
+        
+        google_genai_conversation = []
+        for message in payloads["messages"]:
+            if message["role"] == "user":
+                if isinstance(message["content"], str):
+                    if not message['content']:
+                        message['content'] = "<empty_content>"
+                    
+                    google_genai_conversation.append({
+                        "role": "user",
+                        "parts": [{"text": message["content"]}]
+                    })
+                elif isinstance(message["content"], list):
+                    # images
+                    parts = []
+                    for part in message["content"]:
+                        if part["type"] == "text":
+                            if not part["text"]:
+                                part["text"] = "<empty_content>"
+                            parts.append({"text": part["text"]})
+                        elif part["type"] == "image_url":
+                            parts.append({"inline_data": {
+                                "mime_type": "image/jpeg",
+                                "data": part["image_url"]["url"].replace("data:image/jpeg;base64,", "") # base64
+                            }})
+                    google_genai_conversation.append({
+                        "role": "user",
+                        "parts": parts
+                    })
+                        
+            elif message["role"] == "assistant":
+                if not message["content"]:
+                    message["content"] = "<empty_content>"
+                google_genai_conversation.append({
+                    "role": "model",
+                    "parts": [{"text": message["content"]}]
+                })
+
+        logger.debug(f"google_genai_conversation: {google_genai_conversation}")
+        
+        result = await self.client.generate_content(
+            contents=google_genai_conversation,
+            model=self.get_model(),
+            system_instruction=system_instruction,
+            tools=tool
+        )
+        logger.debug(f"result: {result}")
+        
+        if "candidates" not in result:
+            raise Exception("Gemini 返回异常结果: " + str(result))
+        
+        candidates = result["candidates"][0]['content']['parts']
+        llm_response = LLMResponse("assistant")
+        for candidate in candidates:
+            if 'text' in candidate:
+                llm_response.completion_text += candidate['text']
+            elif 'functionCall' in candidate:
+                llm_response.role = "tool"
+                llm_response.tools_call_args.append(candidate['functionCall']['args'])
+                llm_response.tools_call_name.append(candidate['functionCall']['name'])
+        
+        llm_response.completion_text = llm_response.completion_text.strip()
+        return llm_response
+
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str]=None,
+        func_tool: FuncCall=None,
+        contexts=[],
+        system_prompt=None,
+        **kwargs
+    ) -> LLMResponse: 
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = []
+        context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+            
+        for part in context_query:
+            if '_no_save' in part:
+                del part['_no_save']
+                
+        model_config = self.provider_config.get("model_config", {})
+        model_config['model'] = self.get_model()
+
+        payloads = {
+            "messages": context_query,
+            **model_config
+        }
+        llm_response = None
+        
+        retry = 10
+        keys = self.api_keys.copy()
+        chosen_key = random.choice(keys)
+        
+        for i in range(retry):
+            try:
+                self.client.api_key = chosen_key 
+                llm_response = await self._query(payloads, func_tool)
+                break
+            except Exception as e:
+                if "maximum context length" in str(e):
+                    retry_cnt = 20
+                    while retry_cnt > 0:
+                        logger.warning(f"请求失败：{e}。上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}")
+                        try:
+                            await self.pop_record(context_query)
+                            llm_response = await self._query(payloads, func_tool)
+                            break
+                        except Exception as e:
+                            if "maximum context length" in str(e):
+                                retry_cnt -= 1
+                            else:
+                                raise e
+                    if retry_cnt == 0:
+                        llm_response = LLMResponse("err", "err: 请尝试  /reset 重置会话")
+                elif "Function calling is not enabled" in str(e):
+                    logger.info(f"{self.get_model()} 不支持函数工具调用，已自动去除，不影响使用。")
+                    if 'tools' in payloads:
+                        del payloads['tools']
+                    llm_response = await self._query(payloads, None)
+                elif "429" in str(e) or "API key not valid" in str(e):
+                    keys.remove(chosen_key)
+                    if len(keys) > 0:
+                        chosen_key = random.choice(keys)
+                        logger.info(f"检测到 Key 异常({str(e)})，正在尝试更换 API Key 重试... 当前 Key: {chosen_key[:12]}...")
+                        continue
+                    else:
+                        logger.error(f"A检测到 Key 异常({str(e)})，且已没有可用的 Key。 当前 Key: {chosen_key[:12]}...")
+                        raise Exception("API 资源已耗尽，且没有可用的 Key 重试...")
+                else:
+                    logger.error(f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}")
+                    raise e
+
+        return llm_response
+
+    def get_current_key(self) -> str:
+        return self.client.api_key
+
+    def get_keys(self) -> List[str]:
+        return self.api_keys
+    
+    def set_key(self, key):
+        self.client.api_key = key
+        
+    async def assemble_context(self, text: str, image_urls: List[str] = None):
+        '''
+        组装上下文。
+        '''
+        if image_urls:
+            user_content = {"role": "user","content": [{"type": "text", "text": text}]}
+            for image_url in image_urls:
+                if image_url.startswith("http"):
+                    image_path = await download_image_by_url(image_url)
+                    image_data = await self.encode_image_bs64(image_path)
+                elif image_url.startswith("file:///"):
+                    image_path = image_url.replace("file:///", "")
+                    image_data = await self.encode_image_bs64(image_path)
+                else:
+                    image_data = await self.encode_image_bs64(image_url)
+                if not image_data:
+                    logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
+                    continue
+                user_content["content"].append({"type": "image_url", "image_url": {"url": image_data}})
+            return user_content
+        else:
+            return {"role": "user","content": text}
+
+    async def encode_image_bs64(self, image_url: str) -> str:
+        '''
+        将图片转换为 base64
+        '''
+        if image_url.startswith("base64://"):
+            return image_url.replace("base64://", "data:image/jpeg;base64,")
+        with open(image_url, "rb") as f:
+            image_bs64 = base64.b64encode(f.read()).decode('utf-8')
+            return "data:image/jpeg;base64," + image_bs64
+        return ''

astrbot/core/provider/sources/llmtuner_source.py

@@ -0,0 +1,102 @@
+import json
+import os
+from llmtuner.chat import ChatModel
+from typing import List
+from .. import Provider, Personality
+from ..entites import LLMResponse
+from ..func_tool_manager import FuncCall
+from astrbot.core.db import BaseDatabase
+from ..register import register_provider_adapter
+
+
+@register_provider_adapter(
+    "llm_tuner", "LLMTuner 适配器, 用于装载使用 LlamaFactory 微调后的模型"
+)
+class LLMTunerModelLoader(Provider):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+        db_helper: BaseDatabase,
+        persistant_history=True,
+        default_persona=None,
+    ) -> None:
+        super().__init__(
+            provider_config, provider_settings, persistant_history, db_helper, default_persona
+        )
+        if not os.path.exists(provider_config["base_model_path"]) or not os.path.exists(
+            provider_config["adapter_model_path"]
+        ):
+            raise FileNotFoundError("模型文件路径不存在。")
+        self.base_model_path = provider_config["base_model_path"]
+        self.adapter_model_path = provider_config["adapter_model_path"]
+        self.model = ChatModel(
+            {
+                "model_name_or_path": self.base_model_path,
+                "adapter_name_or_path": self.adapter_model_path,
+                "template": provider_config["llmtuner_template"],
+                "finetuning_type": provider_config["finetuning_type"],
+                "quantization_bit": provider_config["quantization_bit"],
+            }
+        )
+        self.set_model(
+            os.path.basename(self.base_model_path)
+            + "_"
+            + os.path.basename(self.adapter_model_path)
+        )
+
+    async def assemble_context(self, text: str, image_urls: List[str] = None):
+        """
+        组装上下文。
+        """
+        return {"role": "user", "content": text}
+
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = None,
+        func_tool: FuncCall = None,
+        contexts: List = [],
+        system_prompt: str = None,
+        **kwargs,
+    ) -> LLMResponse:
+        system_prompt = ""
+        new_record = {"role": "user", "content": prompt}
+        query_context = [*contexts, new_record]
+
+        # 提取出系统提示
+        system_idxs = []
+        for idx, context in enumerate(query_context):
+            if context["role"] == "system":
+                system_idxs.append(idx)
+                
+            if '_no_save' in context:
+                del context['_no_save']
+            
+        for idx in reversed(system_idxs):
+            system_prompt += " " + query_context.pop(idx)["content"]
+
+        conf = {
+            "messages": query_context,
+            "system": system_prompt,
+        }
+        if func_tool:
+            tool_list = func_tool.get_func_desc_openai_style()
+            if tool_list:
+                conf['tools'] = tool_list
+
+        responses = await self.model.achat(**conf)
+
+        llm_response = LLMResponse("assistant", responses[-1].response_text)
+                
+        return llm_response
+
+    async def get_current_key(self):
+        return "none"
+
+    async def set_key(self, key):
+        pass
+
+    async def get_models(self):
+        return [self.get_model()]

astrbot/core/provider/sources/openai_source.py

@@ -0,0 +1,273 @@
+import base64
+import json
+import os
+
+from openai import AsyncOpenAI, AsyncAzureOpenAI
+from openai.types.chat.chat_completion import ChatCompletion
+from openai._exceptions import NotFoundError, UnprocessableEntityError
+from astrbot.core.utils.io import download_image_by_url
+
+from astrbot.core.db import BaseDatabase
+from astrbot.api.provider import Provider, Personality
+from astrbot import logger
+from astrbot.core.provider.func_tool_manager import FuncCall
+from typing import List
+from ..register import register_provider_adapter
+from astrbot.core.provider.entites import LLMResponse
+
+@register_provider_adapter("openai_chat_completion", "OpenAI API Chat Completion 提供商适配器")
+class ProviderOpenAIOfficial(Provider):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+        db_helper: BaseDatabase, 
+        persistant_history = True,
+        default_persona: Personality = None
+    ) -> None:
+        super().__init__(provider_config, provider_settings, persistant_history, db_helper, default_persona)
+        self.chosen_api_key = None
+        self.api_keys: List = provider_config.get("key", [])
+        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+        # 适配 azure openai #332
+        if "api_version" in provider_config:
+            # 使用 azure api
+            self.client = AsyncAzureOpenAI(
+                api_key=self.chosen_api_key,
+                api_version=provider_config.get("api_version", None),
+                base_url=provider_config.get("api_base", None),
+                timeout=self.timeout
+            )
+        else:
+            # 使用 openai api
+            self.client = AsyncOpenAI(
+                api_key=self.chosen_api_key,
+                base_url=provider_config.get("api_base", None),
+                timeout=self.timeout
+            )
+        
+        model_config = provider_config.get("model_config", {})
+        model = model_config.get("model", "unknown")
+        self.set_model(model)
+
+    async def get_models(self):
+        try:
+            models_str = []
+            models = await self.client.models.list()
+            models = sorted(models.data, key=lambda x: x.id)
+            for model in models:
+                models_str.append(model.id)
+            return models_str
+        except NotFoundError as e:
+            raise Exception(f"获取模型列表失败：{e}")
+    
+    async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
+        if tools:
+            tool_list = tools.get_func_desc_openai_style()
+            if tool_list:
+                payloads['tools'] = tool_list
+        
+        completion = await self.client.chat.completions.create(
+            **payloads,
+            stream=False
+        )
+
+        assert isinstance(completion, ChatCompletion)
+        logger.debug(f"completion: {completion}")
+
+        if len(completion.choices) == 0:
+            raise Exception("API 返回的 completion 为空。")
+        choice = completion.choices[0]
+        
+        llm_response = LLMResponse("assistant")
+                
+        if choice.message.content:
+            # text completion
+            completion_text = str(choice.message.content).strip()
+            llm_response.completion_text = completion_text
+        
+        if choice.message.tool_calls:
+            # tools call (function calling)
+            args_ls = []
+            func_name_ls = []
+            for tool_call in choice.message.tool_calls:
+                for tool in tools.func_list:
+                    if tool.name == tool_call.function.name:
+                        args = json.loads(tool_call.function.arguments)
+                        args_ls.append(args)
+                        func_name_ls.append(tool_call.function.name)
+            llm_response.role = "tool"
+            llm_response.tools_call_args = args_ls
+            llm_response.tools_call_name = func_name_ls
+            
+        if choice.finish_reason == 'content_filter':
+            raise Exception("API 返回的 completion 由于内容安全过滤被拒绝(非 AstrBot)。")
+
+        if not llm_response.completion_text and not llm_response.tools_call_args:
+            logger.error(f"API 返回的 completion 无法解析：{completion}。")
+            raise Exception(f"API 返回的 completion 无法解析：{completion}。")
+        
+        llm_response.raw_completion = completion
+        
+        return llm_response
+
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str=None,
+        image_urls: List[str]=[],
+        func_tool: FuncCall=None,
+        contexts=[],
+        system_prompt=None,
+        **kwargs
+    ) -> LLMResponse: 
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+
+        for part in context_query:
+            if '_no_save' in part:
+                del part['_no_save']
+                
+                
+        model_config = self.provider_config.get("model_config", {})
+        model_config['model'] = self.get_model()
+
+        payloads = {
+            "messages": context_query,
+            **model_config
+        }
+        llm_response = None
+        try:
+            llm_response = await self._query(payloads, func_tool)
+        except UnprocessableEntityError as e:
+            logger.warning(f"不可处理的实体错误：{e}，尝试删除图片。")
+            # 尝试删除所有 image
+            new_contexts = await self._remove_image_from_context(context_query)
+            payloads['messages'] = new_contexts
+            context_query = new_contexts
+            llm_response = await self._query(payloads, func_tool)
+        except Exception as e:
+            if "maximum context length" in str(e):
+                # 重试 10 次
+                retry_cnt = 20
+                while retry_cnt > 0:
+                    logger.warning(f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}")
+                    try:
+                        await self.pop_record(context_query)
+                        llm_response = await self._query(payloads, func_tool)
+                        break
+                    except Exception as e:
+                        if "maximum context length" in str(e):
+                            retry_cnt -= 1
+                        else:
+                            raise e
+                if retry_cnt == 0:
+                    llm_response = LLMResponse("err", "err: 请尝试 /reset 清除会话记录。")
+            elif "The model is not a VLM" in str(e): # siliconcloud
+                # 尝试删除所有 image
+                new_contexts = await self._remove_image_from_context(context_query)
+                payloads['messages'] = new_contexts
+                llm_response = await self._query(payloads, func_tool)
+
+            # openai, ollama, gemini openai, siliconcloud 的错误提示与 code 不统一，只能通过字符串匹配
+            elif 'does not support Function Calling' in str(e) \
+                or 'does not support tools' in str(e)  \
+                or 'Function call is not supported' in str(e) \
+                or 'Function calling is not enabled' in str(e) \
+                or 'Tool calling is not supported' in str(e) \
+                or 'No endpoints found that support tool use' in str(e) \
+                or 'model does not support function calling' in str(e) \
+                or ('tool' in str(e) and 'support' in str(e).lower()) \
+                or ('function' in str(e) and 'support' in str(e).lower()):
+                    logger.info(f"{self.get_model()} 不支持函数工具调用，已自动去除，不影响使用。")
+                    if 'tools' in payloads:
+                        del payloads['tools']
+                    llm_response = await self._query(payloads, None)
+            else:
+                logger.error(f"发生了错误。Provider 配置如下: {self.provider_config}")
+                
+                if 'tool' in str(e).lower() and 'support' in str(e).lower():
+                    logger.error("疑似该模型不支持函数调用工具调用。请输入 /tool off_all")
+                
+                if 'Connection error.' in str(e):
+                    proxy = os.environ.get("http_proxy", None)
+                    if proxy:
+                        logger.error(f"可能为代理原因，请检查代理是否正常。当前代理: {proxy}")
+                
+                raise e
+        
+        return llm_response
+    
+    async def _remove_image_from_context(self, contexts: List):
+        '''
+        从上下文中删除所有带有 image 的记录
+        '''
+        new_contexts = []
+        
+        flag = False
+        for context in contexts:
+            if flag:
+                flag = False # 删除 image 后，下一条（LLM 响应）也要删除
+                continue
+            if isinstance(context['content'], list):
+                flag = True
+                # continue
+                new_content = []
+                for item in context['content']:
+                    if isinstance(item, dict) and 'image_url' in item:
+                        continue
+                    new_content.append(item)
+                if not new_content:
+                    # 用户只发了图片
+                    new_content = [{"type": "text", "text": "[图片]"}]
+                context['content'] = new_content
+            new_contexts.append(context)
+        return new_contexts
+    
+    def get_current_key(self) -> str:
+        return self.client.api_key
+
+    def get_keys(self) -> List[str]:
+        return self.api_keys
+    
+    def set_key(self, key):
+        self.client.api_key = key
+        
+    async def assemble_context(self, text: str, image_urls: List[str] = None):
+        '''
+        组装上下文。
+        '''
+        if image_urls:
+            user_content = {"role": "user","content": [{"type": "text", "text": text}]}
+            for image_url in image_urls:
+                if image_url.startswith("http"):
+                    image_path = await download_image_by_url(image_url)
+                    image_data = await self.encode_image_bs64(image_path)
+                elif image_url.startswith("file:///"):
+                    image_path = image_url.replace("file:///", "")
+                    image_data = await self.encode_image_bs64(image_path)
+                else:
+                    image_data = await self.encode_image_bs64(image_url)
+                if not image_data:
+                    logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
+                    continue
+                user_content["content"].append({"type": "image_url", "image_url": {"url": image_data}})
+            return user_content
+        else:
+            return {"role": "user","content": text}
+
+    async def encode_image_bs64(self, image_url: str) -> str:
+        '''
+        将图片转换为 base64
+        '''
+        if image_url.startswith("base64://"):
+            return image_url.replace("base64://", "data:image/jpeg;base64,")
+        with open(image_url, "rb") as f:
+            image_bs64 = base64.b64encode(f.read()).decode('utf-8')
+            return "data:image/jpeg;base64," + image_bs64
+        return ''

astrbot/core/provider/sources/openai_tts_api_source.py

@@ -0,0 +1,40 @@
+import uuid
+import os
+from openai import AsyncOpenAI, NOT_GIVEN
+from ..provider import TTSProvider
+from ..entites import ProviderType
+from ..register import register_provider_adapter
+
+
+@register_provider_adapter("openai_tts_api", "OpenAI TTS API", provider_type=ProviderType.TEXT_TO_SPEECH)
+class ProviderOpenAITTSAPI(TTSProvider):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.chosen_api_key = provider_config.get("api_key", "")
+        self.voice = provider_config.get("openai-tts-voice", "alloy")
+
+        self.client = AsyncOpenAI(
+            api_key=self.chosen_api_key,
+            base_url=provider_config.get("api_base", None),
+            timeout=provider_config.get("timeout", NOT_GIVEN),
+        )
+        
+        self.set_model(provider_config.get("model", None))
+
+
+    async def get_audio(self, text: str) -> str:
+        path = f'data/temp/openai_tts_api_{uuid.uuid4()}.wav'
+        async with self.client.audio.speech.with_streaming_response.create(
+            model=self.model_name,
+            voice=self.voice,
+            response_format='wav',
+            input=text
+        ) as response:
+            with open(path, 'wb') as f:
+                async for chunk in response.iter_bytes(chunk_size=1024):
+                    f.write(chunk)
+        return path

astrbot/core/provider/sources/whisper_api_source.py

@@ -0,0 +1,74 @@
+import uuid
+import os
+from openai import AsyncOpenAI, NOT_GIVEN
+from ..provider import STTProvider
+from ..entites import ProviderType
+from astrbot.core.utils.io import download_file
+from ..register import register_provider_adapter
+from astrbot.core import logger
+from astrbot.core.utils.tencent_record_helper import tencent_silk_to_wav
+
+@register_provider_adapter("openai_whisper_api", "OpenAI Whisper API", provider_type=ProviderType.SPEECH_TO_TEXT)
+class ProviderOpenAIWhisperAPI(STTProvider):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.chosen_api_key = provider_config.get("api_key", "")
+
+        self.client = AsyncOpenAI(
+            api_key=self.chosen_api_key,
+            base_url=provider_config.get("api_base", None),
+            timeout=provider_config.get("timeout", NOT_GIVEN),
+        )
+        
+        self.set_model(provider_config.get("model", None))
+        
+    async def _convert_audio(self, path: str) -> str:
+        from pyffmpeg import FFmpeg
+        filename = str(uuid.uuid4()) + '.mp3'
+        ff = FFmpeg()
+        output_path = ff.convert(path, os.path.join('data/temp', filename))
+        return output_path
+    
+    async def _is_silk_file(self, file_path):
+        silk_header = b"SILK"
+        with open(file_path, "rb") as f:
+            file_header = f.read(8)
+
+        if silk_header in file_header:
+            return True
+        else:
+            return False
+
+    async def get_text(self, audio_url: str) -> str:
+        '''only supports mp3, mp4, mpeg, m4a, wav, webm'''
+        is_tencent = False
+        
+        if audio_url.startswith("http"):
+            if "multimedia.nt.qq.com.cn" in audio_url:
+                is_tencent = True
+            
+            name = str(uuid.uuid4())
+            path = os.path.join("data/temp", name)
+            await download_file(audio_url, path)
+            audio_url = path
+        
+        if not os.path.exists(audio_url):
+            raise FileNotFoundError(f"文件不存在: {audio_url}")
+        
+        if audio_url.endswith(".amr") or audio_url.endswith(".silk") or is_tencent:
+            is_silk = await self._is_silk_file(audio_url)
+            if is_silk:
+                logger.info("Converting silk file to wav ...")
+                output_path = os.path.join('data/temp', str(uuid.uuid4()) + '.wav')
+                await tencent_silk_to_wav(audio_url, output_path)
+                audio_url = output_path
+        
+        result = await self.client.audio.transcriptions.create(
+            model=self.model_name,
+            file=open(audio_url, "rb"),
+        )
+        return result.text

astrbot/core/provider/sources/whisper_selfhosted_source.py

@@ -0,0 +1,72 @@
+import uuid
+import os
+import asyncio
+import whisper
+from ..provider import STTProvider
+from ..entites import ProviderType
+from astrbot.core.utils.io import download_file
+from ..register import register_provider_adapter
+from astrbot.core import logger
+from astrbot.core.utils.tencent_record_helper import tencent_silk_to_wav
+
+@register_provider_adapter("openai_whisper_selfhost", "OpenAI Whisper 模型部署", provider_type=ProviderType.SPEECH_TO_TEXT)
+class ProviderOpenAIWhisperSelfHost(STTProvider):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.set_model(provider_config.get("model", None))
+        self.model = None
+    
+    async def initialize(self):
+        loop = asyncio.get_event_loop()
+        logger.info("下载或者加载 Whisper 模型中，这可能需要一些时间 ...")
+        self.model = await loop.run_in_executor(None, whisper.load_model, self.model_name)
+        logger.info("Whisper 模型加载完成。")
+        
+    async def _convert_audio(self, path: str) -> str:
+        from pyffmpeg import FFmpeg
+        filename = str(uuid.uuid4()) + '.mp3'
+        ff = FFmpeg()
+        output_path = ff.convert(path, os.path.join('data/temp', filename))
+        return output_path
+    
+    async def _is_silk_file(self, file_path):
+        silk_header = b"SILK"
+        with open(file_path, "rb") as f:
+            file_header = f.read(8)
+
+        if silk_header in file_header:
+            return True
+        else:
+            return False
+
+    async def get_text(self, audio_url: str) -> str:
+        loop = asyncio.get_event_loop()
+        
+        is_tencent = False
+        
+        if audio_url.startswith("http"):
+            if "multimedia.nt.qq.com.cn" in audio_url:
+                is_tencent = True
+            
+            name = str(uuid.uuid4())
+            path = os.path.join("data/temp", name)
+            await download_file(audio_url, path)
+            audio_url = path
+        
+        if not os.path.exists(audio_url):
+            raise FileNotFoundError(f"文件不存在: {audio_url}")
+        
+        if audio_url.endswith(".amr") or audio_url.endswith(".silk") or is_tencent:
+            is_silk = await self._is_silk_file(audio_url)
+            if is_silk:
+                logger.info("Converting silk file to wav ...")
+                output_path = os.path.join('data/temp', str(uuid.uuid4()) + '.wav')
+                await tencent_silk_to_wav(audio_url, output_path)
+                audio_url = output_path
+                
+        result = await loop.run_in_executor(None, self.model.transcribe, audio_url)
+        return result['text']

astrbot/core/provider/sources/zhipu_source.py

@@ -0,0 +1,78 @@
+import traceback
+from astrbot.core.db import BaseDatabase
+from astrbot import logger
+from astrbot.core.provider.func_tool_manager import FuncCall
+from typing import List
+from ..register import register_provider_adapter
+from astrbot.core.provider.entites import LLMResponse
+from .openai_source import ProviderOpenAIOfficial
+
+@register_provider_adapter("zhipu_chat_completion", "智浦 Chat Completion 提供商适配器")
+class ProviderZhipu(ProviderOpenAIOfficial):
+    def __init__(
+        self, 
+        provider_config: dict, 
+        provider_settings: dict,
+        db_helper: BaseDatabase, 
+        persistant_history = True,
+        default_persona = None
+    ) -> None:
+        super().__init__(provider_config, provider_settings, db_helper, persistant_history, default_persona)
+    
+    async def text_chat(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str]=None,
+        func_tool: FuncCall=None,
+        contexts=[],
+        system_prompt=None,
+        **kwargs
+    ) -> LLMResponse: 
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = []
+        
+        context_query = [*contexts, new_record]
+        
+        model_cfgs: dict = self.provider_config.get("model_config", {})
+        model = self.get_model()
+        # glm-4v-flash 只支持一张图片
+        if model.lower() == 'glm-4v-flash' and image_urls and len(context_query) > 1:
+            logger.debug("glm-4v-flash 只支持一张图片，将只保留最后一张图片")
+            logger.debug(context_query)
+            new_context_query_ = []
+            for i in range(0, len(context_query) - 1, 2):
+                if isinstance(context_query[i].get("content", ""), list):
+                    continue
+                new_context_query_.append(context_query[i])
+                new_context_query_.append(context_query[i+1])
+            new_context_query_.append(context_query[-1]) # 保留最后一条记录
+            context_query = new_context_query_
+            logger.debug(context_query)
+            
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+            
+        payloads = {
+            "messages": context_query,
+            **model_cfgs
+        }
+        try:
+            llm_response = await self._query(payloads, func_tool)
+            return llm_response
+        except Exception as e:
+            if "maximum context length" in str(e):
+                retry_cnt = 10
+                while retry_cnt > 0:
+                    logger.warning(f"请求失败：{e}。上下文长度超过限制。尝试弹出最早的记录然后重试。")
+                    try:
+                        self.pop_record(session_id)
+                        llm_response = await self._query(payloads, func_tool)
+                        break
+                    except Exception as e:
+                        if "maximum context length" in str(e):
+                            retry_cnt -= 1
+                        else:
+                            raise e
+            else:
+                raise e