Compare commits
604 Commits
v3.5.11
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copilot/fi
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80
.github/ISSUE_TEMPLATE/PLUGIN_PUBLISH.yml
vendored
80
.github/ISSUE_TEMPLATE/PLUGIN_PUBLISH.yml
vendored
@@ -1,40 +1,56 @@
|
||||
name: '🥳 发布插件'
|
||||
title: "[Plugin] 插件名"
|
||||
name: 🥳 发布插件
|
||||
description: 提交插件到插件市场
|
||||
labels: [ "plugin-publish" ]
|
||||
title: "[Plugin] 插件名"
|
||||
labels: ["plugin-publish"]
|
||||
assignees: []
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
欢迎发布插件到插件市场!请确保您的插件经过**完整的**测试。
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: 插件仓库
|
||||
description: 插件的 GitHub 仓库链接
|
||||
placeholder: >
|
||||
如 https://github.com/Soulter/astrbot-github-cards
|
||||
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: 描述
|
||||
value: |
|
||||
插件名:
|
||||
插件作者:
|
||||
插件简介:
|
||||
支持的消息平台:(必填,如 QQ、微信、飞书)
|
||||
标签:(可选)
|
||||
社交链接:(可选, 将会在插件市场作者名称上作为可点击的链接)
|
||||
description: 必填。请以列表的字段按顺序将插件名、插件作者、插件简介放在这里。如果您不知道支持哪些消息平台,请填写测试过的消息平台。
|
||||
|
||||
- type: checkboxes
|
||||
attributes:
|
||||
label: Code of Conduct
|
||||
options:
|
||||
- label: >
|
||||
我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
|
||||
required: true
|
||||
欢迎发布插件到插件市场!
|
||||
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: "❤️"
|
||||
value: |
|
||||
## 插件基本信息
|
||||
|
||||
请将插件信息填写到下方的 JSON 代码块中。其中 `tags`(插件标签)和 `social_link`(社交链接)选填。
|
||||
|
||||
不熟悉 JSON ?现在可以从 [这里](https://plugins.astrbot.app/#/submit) 获取你的 JSON 啦!获取到了记得复制粘贴过来哦!
|
||||
|
||||
- type: textarea
|
||||
id: plugin-info
|
||||
attributes:
|
||||
label: 插件信息
|
||||
description: 请在下方代码块中填写您的插件信息,确保反引号包裹了JSON
|
||||
value: |
|
||||
```json
|
||||
{
|
||||
"name": "插件名",
|
||||
"desc": "插件介绍",
|
||||
"author": "作者名",
|
||||
"repo": "插件仓库链接",
|
||||
"tags": [],
|
||||
"social_link": ""
|
||||
}
|
||||
```
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
## 检查
|
||||
|
||||
- type: checkboxes
|
||||
id: checks
|
||||
attributes:
|
||||
label: 插件检查清单
|
||||
description: 请确认以下所有项目
|
||||
options:
|
||||
- label: 我的插件经过完整的测试
|
||||
required: true
|
||||
- label: 我的插件不包含恶意代码
|
||||
required: true
|
||||
- label: 我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
|
||||
required: true
|
||||
|
||||
63
.github/copilot-instructions.md
vendored
Normal file
63
.github/copilot-instructions.md
vendored
Normal file
@@ -0,0 +1,63 @@
|
||||
# AstrBot Development Instructions
|
||||
|
||||
AstrBot is a multi-platform LLM chatbot and development framework written in Python with a Vue.js dashboard. It supports multiple messaging platforms (QQ, Telegram, Discord, etc.) and various LLM providers (OpenAI, Anthropic, Google Gemini, etc.).
|
||||
|
||||
Always reference these instructions first and fallback to search or bash commands only when you encounter unexpected information that does not match the info here.
|
||||
|
||||
## Working Effectively
|
||||
|
||||
### Bootstrap and Install Dependencies
|
||||
- **Python 3.10+ required** - Check `.python-version` file
|
||||
- Install UV package manager: `pip install uv`
|
||||
- Install project dependencies: `uv sync` -- takes 6-7 minutes. NEVER CANCEL. Set timeout to 10+ minutes.
|
||||
- Create required directories: `mkdir -p data/plugins data/config data/temp`
|
||||
|
||||
### Running the Application
|
||||
- Run main application: `uv run main.py` -- starts in ~3 seconds
|
||||
- Application creates WebUI on http://localhost:6185 (default credentials: `astrbot`/`astrbot`)
|
||||
- Application loads plugins automatically from `packages/` and `data/plugins/` directories
|
||||
|
||||
### Dashboard Build (Vue.js/Node.js)
|
||||
- **Prerequisites**: Node.js 20+ and npm 10+ required
|
||||
- Navigate to dashboard: `cd dashboard`
|
||||
- Install dashboard dependencies: `npm install` -- takes 2-3 minutes. NEVER CANCEL. Set timeout to 5+ minutes.
|
||||
- Build dashboard: `npm run build` -- takes 25-30 seconds. NEVER CANCEL.
|
||||
- Dashboard creates optimized production build in `dashboard/dist/`
|
||||
|
||||
### Testing
|
||||
- Do not generate test files for now.
|
||||
|
||||
### Code Quality and Linting
|
||||
- Install ruff linter: `uv add --dev ruff`
|
||||
- Check code style: `uv run ruff check .` -- takes <1 second
|
||||
- Check formatting: `uv run ruff format --check .` -- takes <1 second
|
||||
- Fix formatting: `uv run ruff format .`
|
||||
- **ALWAYS** run `uv run ruff check .` and `uv run ruff format .` before committing changes
|
||||
|
||||
### Plugin Development
|
||||
- Plugins load from `packages/` (built-in) and `data/plugins/` (user-installed)
|
||||
- Plugin system supports function tools and message handlers
|
||||
- Key plugins: python_interpreter, web_searcher, astrbot, reminder, session_controller
|
||||
|
||||
### Common Issues and Workarounds
|
||||
- **Dashboard download fails**: Known issue with "division by zero" error - application still works
|
||||
- **Import errors in tests**: Ensure `uv run` is used to run tests in proper environment
|
||||
=- **Build timeouts**: Always set appropriate timeouts (10+ minutes for uv sync, 5+ minutes for npm install)
|
||||
|
||||
## CI/CD Integration
|
||||
- GitHub Actions workflows in `.github/workflows/`
|
||||
- Docker builds supported via `Dockerfile`
|
||||
- Pre-commit hooks enforce ruff formatting and linting
|
||||
|
||||
## Docker Support
|
||||
- Primary deployment method: `docker run soulter/astrbot:latest`
|
||||
- Compose file available: `compose.yml`
|
||||
- Exposes ports: 6185 (WebUI), 6195 (WeChat), 6199 (QQ), etc.
|
||||
- Volume mount required: `./data:/AstrBot/data`
|
||||
|
||||
## Multi-language Support
|
||||
- Documentation in Chinese (README.md), English (README_en.md), Japanese (README_ja.md)
|
||||
- UI supports internationalization
|
||||
- Default language is Chinese
|
||||
|
||||
Remember: This is a production chatbot framework with real users. Always test thoroughly and ensure changes don't break existing functionality.
|
||||
13
.github/dependabot.yml
vendored
Normal file
13
.github/dependabot.yml
vendored
Normal file
@@ -0,0 +1,13 @@
|
||||
# Keep GitHub Actions up to date with GitHub's Dependabot...
|
||||
# https://docs.github.com/en/code-security/dependabot/working-with-dependabot/keeping-your-actions-up-to-date-with-dependabot
|
||||
# https://docs.github.com/en/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file#package-ecosystem
|
||||
version: 2
|
||||
updates:
|
||||
- package-ecosystem: github-actions
|
||||
directory: /
|
||||
groups:
|
||||
github-actions:
|
||||
patterns:
|
||||
- "*" # Group all Actions updates into a single larger pull request
|
||||
schedule:
|
||||
interval: weekly
|
||||
36
.github/workflows/auto_release.yml
vendored
36
.github/workflows/auto_release.yml
vendored
@@ -13,7 +13,7 @@ jobs:
|
||||
contents: write
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: Dashboard Build
|
||||
run: |
|
||||
@@ -23,6 +23,36 @@ jobs:
|
||||
echo "COMMIT_SHA=$(git rev-parse HEAD)" >> $GITHUB_ENV
|
||||
echo ${{ github.ref_name }} > dist/assets/version
|
||||
zip -r dist.zip dist
|
||||
|
||||
- name: Upload to Cloudflare R2
|
||||
env:
|
||||
R2_ACCOUNT_ID: ${{ secrets.R2_ACCOUNT_ID }}
|
||||
R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }}
|
||||
R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }}
|
||||
R2_BUCKET_NAME: "astrbot"
|
||||
R2_OBJECT_NAME: "astrbot-webui-latest.zip"
|
||||
VERSION_TAG: ${{ github.ref_name }}
|
||||
run: |
|
||||
echo "Installing rclone..."
|
||||
curl https://rclone.org/install.sh | sudo bash
|
||||
|
||||
echo "Configuring rclone remote..."
|
||||
mkdir -p ~/.config/rclone
|
||||
cat <<EOF > ~/.config/rclone/rclone.conf
|
||||
[r2]
|
||||
type = s3
|
||||
provider = Cloudflare
|
||||
access_key_id = $R2_ACCESS_KEY_ID
|
||||
secret_access_key = $R2_SECRET_ACCESS_KEY
|
||||
endpoint = https://${R2_ACCOUNT_ID}.r2.cloudflarestorage.com
|
||||
EOF
|
||||
|
||||
echo "Uploading dist.zip to R2 bucket: $R2_BUCKET_NAME/$R2_OBJECT_NAME"
|
||||
mv dashboard/dist.zip dashboard/$R2_OBJECT_NAME
|
||||
rclone copy dashboard/$R2_OBJECT_NAME r2:$R2_BUCKET_NAME --progress
|
||||
mv dashboard/$R2_OBJECT_NAME dashboard/astrbot-webui-${VERSION_TAG}.zip
|
||||
rclone copy dashboard/astrbot-webui-${VERSION_TAG}.zip r2:$R2_BUCKET_NAME --progress
|
||||
mv dashboard/astrbot-webui-${VERSION_TAG}.zip dashboard/dist.zip
|
||||
|
||||
- name: Fetch Changelog
|
||||
run: |
|
||||
@@ -40,10 +70,10 @@ jobs:
|
||||
needs: build-and-publish-to-github-release
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.10'
|
||||
|
||||
|
||||
2
.github/workflows/codeql.yml
vendored
2
.github/workflows/codeql.yml
vendored
@@ -56,7 +56,7 @@ jobs:
|
||||
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v5
|
||||
|
||||
# Initializes the CodeQL tools for scanning.
|
||||
- name: Initialize CodeQL
|
||||
|
||||
24
.github/workflows/coverage_test.yml
vendored
24
.github/workflows/coverage_test.yml
vendored
@@ -1,6 +1,6 @@
|
||||
name: Run tests and upload coverage
|
||||
|
||||
on:
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
@@ -8,6 +8,7 @@ on:
|
||||
- 'README.md'
|
||||
- 'changelogs/**'
|
||||
- 'dashboard/**'
|
||||
pull_request:
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
@@ -16,30 +17,29 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v5
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r requirements.txt
|
||||
pip install pytest pytest-cov pytest-asyncio
|
||||
pip install pytest pytest-asyncio pytest-cov
|
||||
pip install --editable .
|
||||
|
||||
- name: Run tests
|
||||
run: |
|
||||
mkdir data
|
||||
mkdir data/plugins
|
||||
mkdir data/config
|
||||
mkdir data/temp
|
||||
mkdir -p data/plugins
|
||||
mkdir -p data/config
|
||||
mkdir -p data/temp
|
||||
export TESTING=true
|
||||
export ZHIPU_API_KEY=${{ secrets.OPENAI_API_KEY }}
|
||||
PYTHONPATH=./ pytest --cov=. tests/ -v -o log_cli=true -o log_level=DEBUG
|
||||
pytest --cov=. -v -o log_cli=true -o log_level=DEBUG
|
||||
|
||||
- name: Upload results to Codecov
|
||||
uses: codecov/codecov-action@v4
|
||||
uses: codecov/codecov-action@v5
|
||||
with:
|
||||
token: ${{ secrets.CODECOV_TOKEN }}
|
||||
token: ${{ secrets.CODECOV_TOKEN }}
|
||||
|
||||
8
.github/workflows/dashboard_ci.yml
vendored
8
.github/workflows/dashboard_ci.yml
vendored
@@ -1,13 +1,17 @@
|
||||
name: AstrBot Dashboard CI
|
||||
|
||||
on: [push]
|
||||
on:
|
||||
push:
|
||||
branches: [ "master" ]
|
||||
pull_request:
|
||||
branches: [ "master" ]
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: npm install, build
|
||||
run: |
|
||||
|
||||
37
.github/workflows/docker-image.yml
vendored
37
.github/workflows/docker-image.yml
vendored
@@ -11,24 +11,42 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: 拉取源码
|
||||
uses: actions/checkout@v3
|
||||
- name: Pull The Codes
|
||||
uses: actions/checkout@v5
|
||||
with:
|
||||
fetch-depth: 1
|
||||
fetch-depth: 0 # Must be 0 so we can fetch tags
|
||||
|
||||
- name: 设置 QEMU
|
||||
- name: Get latest tag (only on manual trigger)
|
||||
id: get-latest-tag
|
||||
if: github.event_name == 'workflow_dispatch'
|
||||
run: |
|
||||
tag=$(git describe --tags --abbrev=0)
|
||||
echo "latest_tag=$tag" >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Checkout to latest tag (only on manual trigger)
|
||||
if: github.event_name == 'workflow_dispatch'
|
||||
run: git checkout ${{ steps.get-latest-tag.outputs.latest_tag }}
|
||||
|
||||
- name: Set QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
|
||||
- name: 设置 Docker Buildx
|
||||
- name: Set Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
- name: 登录到 DockerHub
|
||||
- name: Log in to 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
|
||||
- name: Login to GitHub Container Registry
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: Soulter
|
||||
password: ${{ secrets.GHCR_GITHUB_TOKEN }}
|
||||
|
||||
- name: Build and Push Docker to DockerHub and Github GHCR
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
@@ -36,8 +54,9 @@ jobs:
|
||||
push: true
|
||||
tags: |
|
||||
${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:latest
|
||||
${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:${{ github.ref_name }}
|
||||
${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
|
||||
ghcr.io/soulter/astrbot:latest
|
||||
ghcr.io/soulter/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
|
||||
|
||||
- name: Post build notifications
|
||||
run: echo "Docker image has been built and pushed successfully"
|
||||
|
||||
|
||||
2
.github/workflows/stale.yml
vendored
2
.github/workflows/stale.yml
vendored
@@ -18,7 +18,7 @@ jobs:
|
||||
pull-requests: write
|
||||
|
||||
steps:
|
||||
- uses: actions/stale@v5
|
||||
- uses: actions/stale@v9
|
||||
with:
|
||||
repo-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
stale-issue-message: 'Stale issue message'
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
FROM python:3.10-slim
|
||||
FROM python:3.11-slim
|
||||
WORKDIR /AstrBot
|
||||
|
||||
COPY . /AstrBot/
|
||||
|
||||
123
README.md
123
README.md
@@ -1,6 +1,6 @@
|
||||
<p align="center">
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
</p>
|
||||
|
||||
@@ -16,7 +16,7 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
|
||||
<a href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="QQ_community" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
|
||||
<a href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
|
||||
[](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
|
||||

|
||||

|
||||

|
||||
|
||||
<a href="https://github.com/Soulter/AstrBot/blob/master/README_en.md">English</a> |
|
||||
@@ -27,49 +27,50 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
|
||||
|
||||
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。
|
||||
|
||||
|
||||
<!-- [](https://codecov.io/gh/Soulter/AstrBot)
|
||||
-->
|
||||
|
||||
> [!NOTE]
|
||||
>
|
||||
> 个人微信接入所依赖的开源项目 Gewechat 近期已停止维护,`v3.5.10` 已经支持接入 WeChatPadPro 替换 gewechat 方式。详见文档 [WeChatPadPro](https://astrbot.app/deploy/platform/wechat/wechatpadpro.html)
|
||||
|
||||
## ✨ 近期更新
|
||||
|
||||
1. AstrBot 现已支持接入 [MCP](https://modelcontextprotocol.io/) 服务器!
|
||||
|
||||
## ✨ 主要功能
|
||||
|
||||
> [!NOTE]
|
||||
> 🪧 我们正基于前沿科研成果,设计并实现适用于角色扮演和情感陪伴的长短期记忆模型及情绪控制模型,旨在提升对话的真实性与情感表达能力。敬请期待 `v3.6.0` 版本!
|
||||
|
||||
1. **大语言模型对话**。支持各种大语言模型,包括 OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM 等,支持接入本地部署的大模型,通过 Ollama、LLMTuner。具有多轮对话、人格情境、多模态能力,支持图片理解、语音转文字(Whisper)。
|
||||
2. **多消息平台接入**。支持接入 QQ(OneBot)、QQ 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://dify.ai/),便捷接入 Dify 智能助手、知识库和 Dify 工作流。
|
||||
4. **插件扩展**。深度优化的插件机制,支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能,极简开发。已支持安装多个插件。
|
||||
5. **可视化管理面板**。支持可视化修改配置、插件管理、日志查看等功能,降低配置难度。集成 WebChat,可在面板上与大模型对话。
|
||||
6. **高稳定性、高模块化**。基于事件总线和流水线的架构设计,高度模块化,低耦合。
|
||||
|
||||
> [!TIP]
|
||||
> WebUI 在线体验 Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)
|
||||
>
|
||||
> 用户名: `astrbot`, 密码: `astrbot`。
|
||||
1. **大模型对话**。支持接入多种大模型服务。支持多模态、工具调用、MCP、原生知识库、人设等功能。
|
||||
2. **多消息平台支持**。支持接入 QQ、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK 等平台。支持速率限制、白名单、百度内容审核。
|
||||
3. **Agent**。完善适配的 Agentic 能力。支持多轮工具调用、内置沙盒代码执行器、网页搜索等功能。
|
||||
4. **插件扩展**。深度优化的插件机制,支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能,社区插件生态丰富。
|
||||
5. **WebUI**。可视化配置和管理机器人,功能齐全。
|
||||
|
||||
## ✨ 使用方式
|
||||
|
||||
#### Docker 部署
|
||||
|
||||
推荐使用 Docker / Docker Compose 方式部署 AstrBot。
|
||||
|
||||
请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
|
||||
|
||||
#### 宝塔面板部署
|
||||
|
||||
AstrBot 与宝塔面板合作,已上架至宝塔面板。
|
||||
|
||||
请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
|
||||
|
||||
#### 1Panel 部署
|
||||
|
||||
AstrBot 已由 1Panel 官方上架至 1Panel 面板。
|
||||
|
||||
请参阅官方文档 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html) 。
|
||||
|
||||
#### 在 雨云 上部署
|
||||
|
||||
AstrBot 已由雨云官方上架至云应用平台,可一键部署。
|
||||
|
||||
[](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
|
||||
|
||||
#### 在 Replit 上部署
|
||||
|
||||
社区贡献的部署方式。
|
||||
|
||||
[](https://repl.it/github/Soulter/AstrBot)
|
||||
|
||||
#### Windows 一键安装器部署
|
||||
|
||||
请参阅官方文档 [使用 Windows 一键安装器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html) 。
|
||||
|
||||
#### 宝塔面板部署
|
||||
|
||||
请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
|
||||
|
||||
#### CasaOS 部署
|
||||
|
||||
社区贡献的部署方式。
|
||||
@@ -93,42 +94,33 @@ git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
|
||||
uv run main.py
|
||||
```
|
||||
|
||||
或者,直接通过 uvx 安装 AstrBot:
|
||||
|
||||
```bash
|
||||
mkdir astrbot && cd astrbot
|
||||
uvx astrbot init
|
||||
# uvx astrbot run
|
||||
```
|
||||
|
||||
或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
|
||||
|
||||
#### Replit 部署
|
||||
|
||||
[](https://repl.it/github/Soulter/AstrBot)
|
||||
|
||||
## ⚡ 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 | ✔ | 私聊、群聊 | 文字、图片 |
|
||||
| 企业微信 | ✔ | 私聊 | 文字、图片、语音 |
|
||||
| 微信客服 | ✔ | 私聊 | 文字、图片 |
|
||||
| 飞书 | ✔ | 私聊、群聊 | 文字、图片 |
|
||||
| 钉钉 | ✔ | 私聊、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 | - |
|
||||
| 平台 | 支持性 |
|
||||
| -------- | ------- |
|
||||
| QQ(官方机器人接口) | ✔ |
|
||||
| QQ(OneBot) | ✔ |
|
||||
| Telegram | ✔ |
|
||||
| 企业微信 | ✔ |
|
||||
| 微信客服 | ✔ |
|
||||
| 微信公众号 | ✔ |
|
||||
| 飞书 | ✔ |
|
||||
| 钉钉 | ✔ |
|
||||
| Slack | ✔ |
|
||||
| Discord | ✔ |
|
||||
| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | ✔ |
|
||||
| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | ✔ |
|
||||
| 微信对话开放平台 | 🚧 |
|
||||
| WhatsApp | 🚧 |
|
||||
| 小爱音响 | 🚧 |
|
||||
|
||||
## ⚡ 提供商支持情况
|
||||
|
||||
| 名称 | 支持性 | 类型 | 备注 |
|
||||
| -------- | ------- | ------- | ------- |
|
||||
| OpenAI API | ✔ | 文本生成 | 也支持 DeepSeek、Google Gemini、GLM、Kimi、xAI 等兼容 OpenAI API 的服务 |
|
||||
| OpenAI API | ✔ | 文本生成 | 也支持 DeepSeek、Gemini、Kimi、xAI 等兼容 OpenAI API 的服务 |
|
||||
| Claude API | ✔ | 文本生成 | |
|
||||
| Google Gemini API | ✔ | 文本生成 | |
|
||||
| Dify | ✔ | LLMOps | |
|
||||
@@ -136,6 +128,8 @@ uvx astrbot init
|
||||
| Ollama | ✔ | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
|
||||
| LM Studio | ✔ | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
|
||||
| LLMTuner | ✔ | 模型加载器 | 本地加载 lora 等微调模型 |
|
||||
| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | ✔ | 模型 API 及算力服务平台 | |
|
||||
| [302.AI](https://share.302.ai/rr1M3l) | ✔ | 模型 API 服务平台 | |
|
||||
| 硅基流动 | ✔ | 模型 API 服务平台 | |
|
||||
| PPIO 派欧云 | ✔ | 模型 API 服务平台 | |
|
||||
| OneAPI | ✔ | LLM 分发系统 | |
|
||||
@@ -143,6 +137,7 @@ uvx astrbot init
|
||||
| SenseVoice | ✔ | 语音转文本 | 本地部署 |
|
||||
| OpenAI TTS API | ✔ | 文本转语音 | |
|
||||
| GSVI | ✔ | 文本转语音 | GPT-Sovits-Inference |
|
||||
| GPT-SoVITs | ✔ | 文本转语音 | GPT-Sovits-Inference |
|
||||
| FishAudio | ✔ | 文本转语音 | GPT-Sovits 作者参与的项目 |
|
||||
| Edge TTS | ✔ | 文本转语音 | Edge 浏览器的免费 TTS |
|
||||
| 阿里云百炼 TTS | ✔ | 文本转语音 | |
|
||||
@@ -171,7 +166,6 @@ pre-commit install
|
||||
|
||||
- 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
|
||||
|
||||
@@ -211,7 +205,7 @@ _✨ WebUI ✨_
|
||||
|
||||
此外,本项目的诞生离不开以下开源项目:
|
||||
|
||||
- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ)
|
||||
- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
|
||||
- [wechatpy/wechatpy](https://github.com/wechatpy/wechatpy)
|
||||
|
||||
## ⭐ Star History
|
||||
@@ -225,11 +219,8 @@ _✨ WebUI ✨_
|
||||
|
||||
</div>
|
||||
|
||||
## 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.
|
||||
|
||||
_私は、高性能ですから!_
|
||||
|
||||
|
||||
15
README_ja.md
15
README_ja.md
@@ -1,5 +1,5 @@
|
||||
<p align="center">
|
||||
|
||||
|
||||

|
||||
|
||||
</p>
|
||||
@@ -27,7 +27,7 @@ AstrBot は、疎結合、非同期、複数のメッセージプラットフォ
|
||||
## ✨ 主な機能
|
||||
|
||||
1. **大規模言語モデルの対話**。OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM など、さまざまな大規模言語モデルをサポートし、Ollama、LLMTuner を介してローカルにデプロイされた大規模モデルをサポートします。多輪対話、人格シナリオ、多モーダル機能を備え、画像理解、音声からテキストへの変換(Whisper)をサポートします。
|
||||
2. **複数のメッセージプラットフォームの接続**。QQ(OneBot)、QQ チャンネル、WeChat(Gewechat)、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
|
||||
2. **複数のメッセージプラットフォームの接続**。QQ(OneBot)、QQ チャンネル、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
|
||||
3. **エージェント**。一部のエージェント機能をネイティブにサポートし、コードエグゼキューター、自然言語タスク、ウェブ検索などを提供します。[Dify プラットフォーム](https://dify.ai/)と連携し、Dify スマートアシスタント、ナレッジベース、Dify ワークフローを簡単に接続できます。
|
||||
4. **プラグインの拡張**。深く最適化されたプラグインメカニズムを備え、[プラグインの開発](https://astrbot.app/dev/plugin.html)をサポートし、機能を拡張できます。複数のプラグインのインストールをサポートします。
|
||||
5. **ビジュアル管理パネル**。設定の視覚的な変更、プラグイン管理、ログの表示などをサポートし、設定の難易度を低減します。WebChat を統合し、パネル上で大規模モデルと対話できます。
|
||||
@@ -35,7 +35,7 @@ AstrBot は、疎結合、非同期、複数のメッセージプラットフォ
|
||||
|
||||
> [!TIP]
|
||||
> 管理パネルのオンラインデモを体験する: [https://demo.astrbot.app/](https://demo.astrbot.app/)
|
||||
>
|
||||
>
|
||||
> ユーザー名: `astrbot`, パスワード: `astrbot`。LLM が設定されていないため、チャットページで大規模モデルを使用することはできません。(デモのログインパスワードを変更しないでください 😭)
|
||||
|
||||
## ✨ 使用方法
|
||||
@@ -136,11 +136,11 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
|
||||
|
||||
## ⭐ Star History
|
||||
|
||||
> [!TIP]
|
||||
> [!TIP]
|
||||
> このプロジェクトがあなたの生活や仕事に役立った場合、またはこのプロジェクトの将来の発展に関心がある場合は、プロジェクトに Star を付けてください。これはこのオープンソースプロジェクトを維持するためのモチベーションです <3
|
||||
|
||||
<div align="center">
|
||||
|
||||
|
||||
[](https://star-history.com/#soulter/astrbot&Date)
|
||||
|
||||
</div>
|
||||
@@ -152,8 +152,7 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
|
||||
## 免責事項
|
||||
|
||||
1. このプロジェクトは `AGPL-v3` オープンソースライセンスの下で保護されています。
|
||||
2. WeChat(個人アカウント)のデプロイメントには [Gewechat](https://github.com/Devo919/Gewechat) サービスを利用しています。AstrBot は Gewechat との接続を保証するだけであり、アカウントのリスク管理に関しては、このプロジェクトの著者は一切の責任を負いません。
|
||||
3. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
|
||||
2. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
|
||||
|
||||
<!-- ## ✨ ATRI [ベータテスト]
|
||||
|
||||
@@ -165,6 +164,4 @@ _✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
|
||||
4. TTS
|
||||
-->
|
||||
|
||||
|
||||
_私は、高性能ですから!_
|
||||
|
||||
|
||||
@@ -1 +1 @@
|
||||
__version__ = "3.5.8"
|
||||
__version__ = "3.5.23"
|
||||
|
||||
@@ -3,7 +3,6 @@ import tempfile
|
||||
|
||||
import httpx
|
||||
import yaml
|
||||
import re
|
||||
from enum import Enum
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
@@ -59,7 +58,16 @@ def get_git_repo(url: str, target_path: Path, proxy: str | None = None):
|
||||
proxy=proxy if proxy else None, follow_redirects=True
|
||||
) as client:
|
||||
resp = client.get(download_url)
|
||||
resp.raise_for_status()
|
||||
if (
|
||||
resp.status_code == 404
|
||||
and "archive/refs/heads/master.zip" in download_url
|
||||
):
|
||||
alt_url = download_url.replace("master.zip", "main.zip")
|
||||
click.echo("master 分支不存在,尝试下载 main 分支")
|
||||
resp = client.get(alt_url)
|
||||
resp.raise_for_status()
|
||||
else:
|
||||
resp.raise_for_status()
|
||||
zip_content = BytesIO(resp.content)
|
||||
with ZipFile(zip_content) as z:
|
||||
z.extractall(temp_dir)
|
||||
@@ -91,39 +99,6 @@ def load_yaml_metadata(plugin_dir: Path) -> dict:
|
||||
return {}
|
||||
|
||||
|
||||
def extract_py_metadata(plugin_dir: Path) -> dict:
|
||||
"""从 Python 文件中提取插件元数据
|
||||
|
||||
Args:
|
||||
plugin_dir: 插件目录路径
|
||||
|
||||
Returns:
|
||||
dict: 包含元数据的字典,如果提取失败则返回空字典
|
||||
"""
|
||||
# 检查 main.py 或与目录同名的 py 文件
|
||||
for pattern in ["main.py", f"{plugin_dir.name}.py"]:
|
||||
for py_file in plugin_dir.glob(pattern):
|
||||
try:
|
||||
content = py_file.read_text(encoding="utf-8")
|
||||
register_match = re.search(
|
||||
r'@register_star\s*\(\s*"([^"]+)"\s*,\s*"([^"]+)"\s*,\s*"([^"]+)"\s*,\s*"([^"]+)"(?:\s*,\s*"?([^")]+)"?)?\s*\)',
|
||||
content,
|
||||
)
|
||||
if register_match:
|
||||
# 映射匹配组到元数据键
|
||||
metadata = {}
|
||||
keys = ["name", "author", "desc", "version", "repo"]
|
||||
for i, key in enumerate(keys):
|
||||
if i + 1 <= len(
|
||||
register_match.groups()
|
||||
) and register_match.group(i + 1):
|
||||
metadata[key] = register_match.group(i + 1)
|
||||
return metadata
|
||||
except Exception as e:
|
||||
click.echo(f"读取 {py_file} 失败: {e}", err=True)
|
||||
return {}
|
||||
|
||||
|
||||
def build_plug_list(plugins_dir: Path) -> list:
|
||||
"""构建插件列表,包含本地和在线插件信息
|
||||
|
||||
@@ -139,20 +114,16 @@ def build_plug_list(plugins_dir: Path) -> list:
|
||||
for plugin_name in [d.name for d in plugins_dir.glob("*") if d.is_dir()]:
|
||||
plugin_dir = plugins_dir / plugin_name
|
||||
|
||||
# 从不同来源加载元数据
|
||||
# 从 metadata.yaml 加载元数据
|
||||
metadata = load_yaml_metadata(plugin_dir)
|
||||
|
||||
# 如果元数据不完整,尝试从 Python 文件提取
|
||||
if not metadata or not all(
|
||||
if "desc" not in metadata and "description" in metadata:
|
||||
metadata["desc"] = metadata["description"]
|
||||
|
||||
# 如果成功加载元数据,添加到结果列表
|
||||
if metadata and all(
|
||||
k in metadata for k in ["name", "desc", "version", "author", "repo"]
|
||||
):
|
||||
py_metadata = extract_py_metadata(plugin_dir)
|
||||
# 合并元数据,保留已有的值
|
||||
for key, value in py_metadata.items():
|
||||
if key not in metadata or not metadata[key]:
|
||||
metadata[key] = value
|
||||
# 如果成功提取元数据,添加到结果列表
|
||||
if metadata:
|
||||
result.append(
|
||||
{
|
||||
"name": str(metadata.get("name", "")),
|
||||
|
||||
@@ -13,7 +13,6 @@ from .utils.astrbot_path import get_astrbot_data_path
|
||||
# 初始化数据存储文件夹
|
||||
os.makedirs(get_astrbot_data_path(), exist_ok=True)
|
||||
|
||||
WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"
|
||||
DEMO_MODE = os.getenv("DEMO_MODE", False)
|
||||
|
||||
astrbot_config = AstrBotConfig()
|
||||
@@ -29,6 +28,3 @@ pip_installer = PipInstaller(
|
||||
astrbot_config.get("pip_install_arg", ""),
|
||||
astrbot_config.get("pypi_index_url", None),
|
||||
)
|
||||
web_chat_queue = asyncio.Queue(maxsize=32)
|
||||
web_chat_back_queue = asyncio.Queue(maxsize=32)
|
||||
|
||||
|
||||
@@ -43,6 +43,7 @@ class AstrBotConfig(dict):
|
||||
"""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)
|
||||
object.__setattr__(self, "first_deploy", True) # 标记第一次部署
|
||||
|
||||
with open(config_path, "r", encoding="utf-8-sig") as f:
|
||||
conf_str = f.read()
|
||||
@@ -82,23 +83,61 @@ class AstrBotConfig(dict):
|
||||
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"""
|
||||
"""检查配置完整性,如果有新的配置项或顺序不一致则返回 True"""
|
||||
has_new = False
|
||||
|
||||
# 创建一个新的有序字典以保持参考配置的顺序
|
||||
new_conf = {}
|
||||
|
||||
# 先按照参考配置的顺序添加配置项
|
||||
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}")
|
||||
# 配置项不存在,插入默认值
|
||||
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
|
||||
new_conf[key] = value
|
||||
has_new = True
|
||||
else:
|
||||
if conf[key] is None:
|
||||
conf[key] = value
|
||||
# 配置项为 None,使用默认值
|
||||
new_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
|
||||
)
|
||||
# 递归检查子配置项
|
||||
if not isinstance(conf[key], dict):
|
||||
# 类型不匹配,使用默认值
|
||||
new_conf[key] = value
|
||||
has_new = True
|
||||
else:
|
||||
# 递归检查并同步顺序
|
||||
child_has_new = self.check_config_integrity(
|
||||
value, conf[key], path + "." + key if path else key
|
||||
)
|
||||
new_conf[key] = conf[key]
|
||||
has_new |= child_has_new
|
||||
else:
|
||||
# 直接使用现有配置
|
||||
new_conf[key] = conf[key]
|
||||
|
||||
# 检查是否存在参考配置中没有的配置项
|
||||
for key in list(conf.keys()):
|
||||
if key not in refer_conf:
|
||||
path_ = path + "." + key if path else key
|
||||
logger.info(f"检查到配置项 {path_} 不存在,将从当前配置中删除")
|
||||
has_new = True
|
||||
|
||||
# 顺序不一致也算作变更
|
||||
if list(conf.keys()) != list(new_conf.keys()):
|
||||
if path:
|
||||
logger.info(f"检查到配置项 {path} 的子项顺序不一致,已重新排序")
|
||||
else:
|
||||
logger.info("检查到配置项顺序不一致,已重新排序")
|
||||
has_new = True
|
||||
|
||||
# 更新原始配置
|
||||
conf.clear()
|
||||
conf.update(new_conf)
|
||||
|
||||
return has_new
|
||||
|
||||
def save_config(self, replace_config: Dict = None):
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -88,7 +88,10 @@ class ConversationManager:
|
||||
return self.session_conversations.get(unified_msg_origin, None)
|
||||
|
||||
async def get_conversation(
|
||||
self, unified_msg_origin: str, conversation_id: str
|
||||
self,
|
||||
unified_msg_origin: str,
|
||||
conversation_id: str,
|
||||
create_if_not_exists: bool = False,
|
||||
) -> Conversation:
|
||||
"""获取会话的对话
|
||||
|
||||
@@ -98,6 +101,13 @@ class ConversationManager:
|
||||
Returns:
|
||||
conversation (Conversation): 对话对象
|
||||
"""
|
||||
conv = self.db.get_conversation_by_user_id(unified_msg_origin, conversation_id)
|
||||
if not conv and create_if_not_exists:
|
||||
# 如果对话不存在且需要创建,则新建一个对话
|
||||
conversation_id = await self.new_conversation(unified_msg_origin)
|
||||
return self.db.get_conversation_by_user_id(
|
||||
unified_msg_origin, conversation_id
|
||||
)
|
||||
return self.db.get_conversation_by_user_id(unified_msg_origin, conversation_id)
|
||||
|
||||
async def get_conversations(self, unified_msg_origin: str) -> List[Conversation]:
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
"""
|
||||
Astrbot 核心生命周期管理类, 负责管理 AstrBot 的启动、停止、重启等操作。
|
||||
该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、EventBus等。
|
||||
该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、EventBus等。
|
||||
该类还负责加载和执行插件, 以及处理事件总线的分发。
|
||||
|
||||
工作流程:
|
||||
@@ -28,7 +28,6 @@ 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
|
||||
from astrbot.core.star.star_handler import star_handlers_registry, EventType
|
||||
from astrbot.core.star.star_handler import star_map
|
||||
@@ -37,7 +36,7 @@ from astrbot.core.star.star_handler import star_map
|
||||
class AstrBotCoreLifecycle:
|
||||
"""
|
||||
AstrBot 核心生命周期管理类, 负责管理 AstrBot 的启动、停止、重启等操作。
|
||||
该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、
|
||||
该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、
|
||||
EventBus 等。
|
||||
该类还负责加载和执行插件, 以及处理事件总线的分发。
|
||||
"""
|
||||
@@ -47,14 +46,17 @@ class AstrBotCoreLifecycle:
|
||||
self.astrbot_config = astrbot_config # 初始化配置
|
||||
self.db = db # 初始化数据库
|
||||
|
||||
# 根据环境变量设置代理
|
||||
os.environ["https_proxy"] = self.astrbot_config["http_proxy"]
|
||||
os.environ["http_proxy"] = self.astrbot_config["http_proxy"]
|
||||
# 设置代理
|
||||
if self.astrbot_config.get("http_proxy", ""):
|
||||
os.environ["https_proxy"] = self.astrbot_config["http_proxy"]
|
||||
os.environ["http_proxy"] = self.astrbot_config["http_proxy"]
|
||||
if proxy := os.environ.get("https_proxy"):
|
||||
logger.debug(f"Using proxy: {proxy}")
|
||||
os.environ["no_proxy"] = "localhost"
|
||||
|
||||
async def initialize(self):
|
||||
"""
|
||||
初始化 AstrBot 核心生命周期管理类, 负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、EventBus、AstrBotUpdator等。
|
||||
初始化 AstrBot 核心生命周期管理类, 负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、EventBus、AstrBotUpdator等。
|
||||
"""
|
||||
|
||||
# 初始化日志代理
|
||||
@@ -73,9 +75,6 @@ class AstrBotCoreLifecycle:
|
||||
# 初始化平台管理器
|
||||
self.platform_manager = PlatformManager(self.astrbot_config, self.event_queue)
|
||||
|
||||
# 初始化知识库管理器
|
||||
self.knowledge_db_manager = KnowledgeDBManager(self.astrbot_config)
|
||||
|
||||
# 初始化对话管理器
|
||||
self.conversation_manager = ConversationManager(self.db)
|
||||
|
||||
@@ -87,7 +86,6 @@ class AstrBotCoreLifecycle:
|
||||
self.provider_manager,
|
||||
self.platform_manager,
|
||||
self.conversation_manager,
|
||||
self.knowledge_db_manager,
|
||||
)
|
||||
|
||||
# 初始化插件管理器
|
||||
|
||||
@@ -1,113 +0,0 @@
|
||||
import json
|
||||
import aiosqlite
|
||||
import os
|
||||
from typing import Any
|
||||
from .plugin_storage import PluginStorage
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
DBPATH = os.path.join(get_astrbot_data_path(), "plugin_data", "sqlite", "plugin_data.db")
|
||||
|
||||
|
||||
class SQLitePluginStorage(PluginStorage):
|
||||
"""插件数据的 SQLite 存储实现类。
|
||||
|
||||
该类提供异步方式将插件数据存储到 SQLite 数据库中,支持数据的增删改查操作。
|
||||
所有数据以 (plugin, key) 作为复合主键进行索引。
|
||||
"""
|
||||
|
||||
_instance = None # Standalone instance of the class
|
||||
_db_conn = None
|
||||
db_path = None
|
||||
|
||||
def __new__(cls):
|
||||
"""
|
||||
创建或获取 SQLitePluginStorage 的单例实例。
|
||||
如果实例已存在,则返回现有实例;否则创建一个新实例。
|
||||
数据在 `data/plugin_data/sqlite/plugin_data.db` 下。
|
||||
"""
|
||||
os.makedirs(os.path.dirname(DBPATH), exist_ok=True)
|
||||
if cls._instance is None:
|
||||
cls._instance = super(SQLitePluginStorage, cls).__new__(cls)
|
||||
cls._instance.db_path = DBPATH
|
||||
return cls._instance
|
||||
|
||||
async def _init_db(self):
|
||||
"""初始化数据库连接(只执行一次)"""
|
||||
if SQLitePluginStorage._db_conn is None:
|
||||
SQLitePluginStorage._db_conn = await aiosqlite.connect(self.db_path)
|
||||
await self._setup_db()
|
||||
|
||||
async def _setup_db(self):
|
||||
"""
|
||||
异步初始化数据库。
|
||||
|
||||
创建插件数据表,如果表不存在则创建,表结构包含 plugin、key 和 value 字段,
|
||||
其中 plugin 和 key 组合作为主键。
|
||||
"""
|
||||
await self._db_conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS plugin_data (
|
||||
plugin TEXT,
|
||||
key TEXT,
|
||||
value TEXT,
|
||||
PRIMARY KEY (plugin, key)
|
||||
)
|
||||
""")
|
||||
await self._db_conn.commit()
|
||||
|
||||
async def set(self, plugin: str, key: str, value: Any):
|
||||
"""
|
||||
异步存储数据。
|
||||
|
||||
将指定插件的键值对存入数据库,如果键已存在则更新值。
|
||||
值会被序列化为 JSON 字符串后存储。
|
||||
|
||||
Args:
|
||||
plugin: 插件标识符
|
||||
key: 数据键名
|
||||
value: 要存储的数据值(任意类型,将被 JSON 序列化)
|
||||
"""
|
||||
await self._init_db()
|
||||
await self._db_conn.execute(
|
||||
"INSERT INTO plugin_data (plugin, key, value) VALUES (?, ?, ?) "
|
||||
"ON CONFLICT(plugin, key) DO UPDATE SET value = excluded.value",
|
||||
(plugin, key, json.dumps(value)),
|
||||
)
|
||||
await self._db_conn.commit()
|
||||
|
||||
async def get(self, plugin: str, key: str) -> Any:
|
||||
"""
|
||||
异步获取数据。
|
||||
|
||||
从数据库中获取指定插件和键名对应的值,
|
||||
返回的值会从 JSON 字符串反序列化为原始数据类型。
|
||||
|
||||
Args:
|
||||
plugin: 插件标识符
|
||||
key: 数据键名
|
||||
|
||||
Returns:
|
||||
Any: 存储的数据值,如果未找到则返回 None
|
||||
"""
|
||||
await self._init_db()
|
||||
async with self._db_conn.execute(
|
||||
"SELECT value FROM plugin_data WHERE plugin = ? AND key = ?",
|
||||
(plugin, key),
|
||||
) as cursor:
|
||||
row = await cursor.fetchone()
|
||||
return json.loads(row[0]) if row else None
|
||||
|
||||
async def delete(self, plugin: str, key: str):
|
||||
"""
|
||||
异步删除数据。
|
||||
|
||||
从数据库中删除指定插件和键名对应的数据项。
|
||||
|
||||
Args:
|
||||
plugin: 插件标识符
|
||||
key: 要删除的数据键名
|
||||
"""
|
||||
await self._init_db()
|
||||
await self._db_conn.execute(
|
||||
"DELETE FROM plugin_data WHERE plugin = ? AND key = ?", (plugin, key)
|
||||
)
|
||||
await self._db_conn.commit()
|
||||
@@ -11,7 +11,9 @@ class SQLiteDatabase(BaseDatabase):
|
||||
super().__init__()
|
||||
self.db_path = db_path
|
||||
|
||||
with open(os.path.dirname(__file__) + "/sqlite_init.sql", "r") as f:
|
||||
with open(
|
||||
os.path.dirname(__file__) + "/sqlite_init.sql", "r", encoding="utf-8"
|
||||
) as f:
|
||||
sql = f.read()
|
||||
|
||||
# 初始化数据库
|
||||
|
||||
46
astrbot/core/db/vec_db/base.py
Normal file
46
astrbot/core/db/vec_db/base.py
Normal file
@@ -0,0 +1,46 @@
|
||||
import abc
|
||||
from dataclasses import dataclass
|
||||
|
||||
|
||||
@dataclass
|
||||
class Result:
|
||||
similarity: float
|
||||
data: dict
|
||||
|
||||
|
||||
class BaseVecDB:
|
||||
async def initialize(self):
|
||||
"""
|
||||
初始化向量数据库
|
||||
"""
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def insert(self, content: str, metadata: dict = None, id: str = None) -> int:
|
||||
"""
|
||||
插入一条文本和其对应向量,自动生成 ID 并保持一致性。
|
||||
"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
async def retrieve(self, query: str, top_k: int = 5) -> list[Result]:
|
||||
"""
|
||||
搜索最相似的文档。
|
||||
Args:
|
||||
query (str): 查询文本
|
||||
top_k (int): 返回的最相似文档的数量
|
||||
Returns:
|
||||
List[Result]: 查询结果
|
||||
"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
async def delete(self, doc_id: str) -> bool:
|
||||
"""
|
||||
删除指定文档。
|
||||
Args:
|
||||
doc_id (str): 要删除的文档 ID
|
||||
Returns:
|
||||
bool: 删除是否成功
|
||||
"""
|
||||
...
|
||||
3
astrbot/core/db/vec_db/faiss_impl/__init__.py
Normal file
3
astrbot/core/db/vec_db/faiss_impl/__init__.py
Normal file
@@ -0,0 +1,3 @@
|
||||
from .vec_db import FaissVecDB
|
||||
|
||||
__all__ = ["FaissVecDB"]
|
||||
121
astrbot/core/db/vec_db/faiss_impl/document_storage.py
Normal file
121
astrbot/core/db/vec_db/faiss_impl/document_storage.py
Normal file
@@ -0,0 +1,121 @@
|
||||
import aiosqlite
|
||||
import os
|
||||
|
||||
|
||||
class DocumentStorage:
|
||||
def __init__(self, db_path: str):
|
||||
self.db_path = db_path
|
||||
self.connection = None
|
||||
self.sqlite_init_path = os.path.join(
|
||||
os.path.dirname(__file__), "sqlite_init.sql"
|
||||
)
|
||||
|
||||
async def initialize(self):
|
||||
"""Initialize the SQLite database and create the documents table if it doesn't exist."""
|
||||
if not os.path.exists(self.db_path):
|
||||
await self.connect()
|
||||
async with self.connection.cursor() as cursor:
|
||||
with open(self.sqlite_init_path, "r", encoding="utf-8") as f:
|
||||
sql_script = f.read()
|
||||
await cursor.executescript(sql_script)
|
||||
await self.connection.commit()
|
||||
else:
|
||||
await self.connect()
|
||||
|
||||
async def connect(self):
|
||||
"""Connect to the SQLite database."""
|
||||
self.connection = await aiosqlite.connect(self.db_path)
|
||||
|
||||
async def get_documents(self, metadata_filters: dict, ids: list = None):
|
||||
"""Retrieve documents by metadata filters and ids.
|
||||
|
||||
Args:
|
||||
metadata_filters (dict): The metadata filters to apply.
|
||||
|
||||
Returns:
|
||||
list: The list of document IDs(primary key, not doc_id) that match the filters.
|
||||
"""
|
||||
# metadata filter -> SQL WHERE clause
|
||||
where_clauses = []
|
||||
values = []
|
||||
for key, val in metadata_filters.items():
|
||||
where_clauses.append(f"json_extract(metadata, '$.{key}') = ?")
|
||||
values.append(val)
|
||||
if ids is not None and len(ids) > 0:
|
||||
ids = [str(i) for i in ids if i != -1]
|
||||
where_clauses.append("id IN ({})".format(",".join("?" * len(ids))))
|
||||
values.extend(ids)
|
||||
where_sql = " AND ".join(where_clauses) or "1=1"
|
||||
|
||||
result = []
|
||||
async with self.connection.cursor() as cursor:
|
||||
sql = "SELECT * FROM documents WHERE " + where_sql
|
||||
await cursor.execute(sql, values)
|
||||
for row in await cursor.fetchall():
|
||||
result.append(await self.tuple_to_dict(row))
|
||||
return result
|
||||
|
||||
async def get_document_by_doc_id(self, doc_id: str):
|
||||
"""Retrieve a document by its doc_id.
|
||||
|
||||
Args:
|
||||
doc_id (str): The doc_id of the document to retrieve.
|
||||
|
||||
Returns:
|
||||
dict: The document data.
|
||||
"""
|
||||
async with self.connection.cursor() as cursor:
|
||||
await cursor.execute("SELECT * FROM documents WHERE doc_id = ?", (doc_id,))
|
||||
row = await cursor.fetchone()
|
||||
if row:
|
||||
return await self.tuple_to_dict(row)
|
||||
else:
|
||||
return None
|
||||
|
||||
async def update_document_by_doc_id(self, doc_id: str, new_text: str):
|
||||
"""Retrieve a document by its doc_id.
|
||||
|
||||
Args:
|
||||
doc_id (str): The doc_id.
|
||||
new_text (str): The new text to update the document with.
|
||||
"""
|
||||
async with self.connection.cursor() as cursor:
|
||||
await cursor.execute(
|
||||
"UPDATE documents SET text = ? WHERE doc_id = ?", (new_text, doc_id)
|
||||
)
|
||||
await self.connection.commit()
|
||||
|
||||
async def get_user_ids(self) -> list[str]:
|
||||
"""Retrieve all user IDs from the documents table.
|
||||
|
||||
Returns:
|
||||
list: A list of user IDs.
|
||||
"""
|
||||
async with self.connection.cursor() as cursor:
|
||||
await cursor.execute("SELECT DISTINCT user_id FROM documents")
|
||||
rows = await cursor.fetchall()
|
||||
return [row[0] for row in rows]
|
||||
|
||||
async def tuple_to_dict(self, row):
|
||||
"""Convert a tuple to a dictionary.
|
||||
|
||||
Args:
|
||||
row (tuple): The row to convert.
|
||||
|
||||
Returns:
|
||||
dict: The converted dictionary.
|
||||
"""
|
||||
return {
|
||||
"id": row[0],
|
||||
"doc_id": row[1],
|
||||
"text": row[2],
|
||||
"metadata": row[3],
|
||||
"created_at": row[4],
|
||||
"updated_at": row[5],
|
||||
}
|
||||
|
||||
async def close(self):
|
||||
"""Close the connection to the SQLite database."""
|
||||
if self.connection:
|
||||
await self.connection.close()
|
||||
self.connection = None
|
||||
59
astrbot/core/db/vec_db/faiss_impl/embedding_storage.py
Normal file
59
astrbot/core/db/vec_db/faiss_impl/embedding_storage.py
Normal file
@@ -0,0 +1,59 @@
|
||||
try:
|
||||
import faiss
|
||||
except ModuleNotFoundError:
|
||||
raise ImportError(
|
||||
"faiss 未安装。请使用 'pip install faiss-cpu' 或 'pip install faiss-gpu' 安装。"
|
||||
)
|
||||
import os
|
||||
import numpy as np
|
||||
|
||||
|
||||
class EmbeddingStorage:
|
||||
def __init__(self, dimension: int, path: str = None):
|
||||
self.dimension = dimension
|
||||
self.path = path
|
||||
self.index = None
|
||||
if path and os.path.exists(path):
|
||||
self.index = faiss.read_index(path)
|
||||
else:
|
||||
base_index = faiss.IndexFlatL2(dimension)
|
||||
self.index = faiss.IndexIDMap(base_index)
|
||||
self.storage = {}
|
||||
|
||||
async def insert(self, vector: np.ndarray, id: int):
|
||||
"""插入向量
|
||||
|
||||
Args:
|
||||
vector (np.ndarray): 要插入的向量
|
||||
id (int): 向量的ID
|
||||
Raises:
|
||||
ValueError: 如果向量的维度与存储的维度不匹配
|
||||
"""
|
||||
if vector.shape[0] != self.dimension:
|
||||
raise ValueError(
|
||||
f"向量维度不匹配, 期望: {self.dimension}, 实际: {vector.shape[0]}"
|
||||
)
|
||||
self.index.add_with_ids(vector.reshape(1, -1), np.array([id]))
|
||||
self.storage[id] = vector
|
||||
await self.save_index()
|
||||
|
||||
async def search(self, vector: np.ndarray, k: int) -> tuple:
|
||||
"""搜索最相似的向量
|
||||
|
||||
Args:
|
||||
vector (np.ndarray): 查询向量
|
||||
k (int): 返回的最相似向量的数量
|
||||
Returns:
|
||||
tuple: (距离, 索引)
|
||||
"""
|
||||
faiss.normalize_L2(vector)
|
||||
distances, indices = self.index.search(vector, k)
|
||||
return distances, indices
|
||||
|
||||
async def save_index(self):
|
||||
"""保存索引
|
||||
|
||||
Args:
|
||||
path (str): 保存索引的路径
|
||||
"""
|
||||
faiss.write_index(self.index, self.path)
|
||||
17
astrbot/core/db/vec_db/faiss_impl/sqlite_init.sql
Normal file
17
astrbot/core/db/vec_db/faiss_impl/sqlite_init.sql
Normal file
@@ -0,0 +1,17 @@
|
||||
-- 创建文档存储表,包含 faiss 中文档的 id,文档文本,create_at,updated_at
|
||||
CREATE TABLE documents (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
doc_id TEXT NOT NULL,
|
||||
text TEXT NOT NULL,
|
||||
metadata TEXT,
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
|
||||
);
|
||||
|
||||
ALTER TABLE documents
|
||||
ADD COLUMN group_id TEXT GENERATED ALWAYS AS (json_extract(metadata, '$.group_id')) STORED;
|
||||
ALTER TABLE documents
|
||||
ADD COLUMN user_id TEXT GENERATED ALWAYS AS (json_extract(metadata, '$.user_id')) STORED;
|
||||
|
||||
CREATE INDEX idx_documents_user_id ON documents(user_id);
|
||||
CREATE INDEX idx_documents_group_id ON documents(group_id);
|
||||
117
astrbot/core/db/vec_db/faiss_impl/vec_db.py
Normal file
117
astrbot/core/db/vec_db/faiss_impl/vec_db.py
Normal file
@@ -0,0 +1,117 @@
|
||||
import uuid
|
||||
import json
|
||||
import numpy as np
|
||||
from .document_storage import DocumentStorage
|
||||
from .embedding_storage import EmbeddingStorage
|
||||
from ..base import Result, BaseVecDB
|
||||
from astrbot.core.provider.provider import EmbeddingProvider
|
||||
|
||||
|
||||
class FaissVecDB(BaseVecDB):
|
||||
"""
|
||||
A class to represent a vector database.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
doc_store_path: str,
|
||||
index_store_path: str,
|
||||
embedding_provider: EmbeddingProvider,
|
||||
):
|
||||
self.doc_store_path = doc_store_path
|
||||
self.index_store_path = index_store_path
|
||||
self.embedding_provider = embedding_provider
|
||||
self.document_storage = DocumentStorage(doc_store_path)
|
||||
self.embedding_storage = EmbeddingStorage(
|
||||
embedding_provider.get_dim(), index_store_path
|
||||
)
|
||||
self.embedding_provider = embedding_provider
|
||||
|
||||
async def initialize(self):
|
||||
await self.document_storage.initialize()
|
||||
|
||||
async def insert(self, content: str, metadata: dict = None, id: str = None) -> int:
|
||||
"""
|
||||
插入一条文本和其对应向量,自动生成 ID 并保持一致性。
|
||||
"""
|
||||
metadata = metadata or {}
|
||||
str_id = id or str(uuid.uuid4()) # 使用 UUID 作为原始 ID
|
||||
|
||||
vector = await self.embedding_provider.get_embedding(content)
|
||||
vector = np.array(vector, dtype=np.float32)
|
||||
async with self.document_storage.connection.cursor() as cursor:
|
||||
await cursor.execute(
|
||||
"INSERT INTO documents (doc_id, text, metadata) VALUES (?, ?, ?)",
|
||||
(str_id, content, json.dumps(metadata)),
|
||||
)
|
||||
await self.document_storage.connection.commit()
|
||||
result = await self.document_storage.get_document_by_doc_id(str_id)
|
||||
int_id = result["id"]
|
||||
|
||||
# 插入向量到 FAISS
|
||||
await self.embedding_storage.insert(vector, int_id)
|
||||
return int_id
|
||||
|
||||
async def retrieve(
|
||||
self, query: str, k: int = 5, fetch_k: int = 20, metadata_filters: dict = None
|
||||
) -> list[Result]:
|
||||
"""
|
||||
搜索最相似的文档。
|
||||
|
||||
Args:
|
||||
query (str): 查询文本
|
||||
k (int): 返回的最相似文档的数量
|
||||
fetch_k (int): 在根据 metadata 过滤前从 FAISS 中获取的数量
|
||||
metadata_filters (dict): 元数据过滤器
|
||||
|
||||
Returns:
|
||||
List[Result]: 查询结果
|
||||
"""
|
||||
embedding = await self.embedding_provider.get_embedding(query)
|
||||
scores, indices = await self.embedding_storage.search(
|
||||
vector=np.array([embedding]).astype("float32"),
|
||||
k=fetch_k if metadata_filters else k,
|
||||
)
|
||||
# TODO: rerank
|
||||
if len(indices[0]) == 0 or indices[0][0] == -1:
|
||||
return []
|
||||
# normalize scores
|
||||
scores[0] = 1.0 - (scores[0] / 2.0)
|
||||
# NOTE: maybe the size is less than k.
|
||||
fetched_docs = await self.document_storage.get_documents(
|
||||
metadata_filters=metadata_filters or {}, ids=indices[0]
|
||||
)
|
||||
if not fetched_docs:
|
||||
return []
|
||||
result_docs = []
|
||||
|
||||
idx_pos = {fetch_doc["id"]: idx for idx, fetch_doc in enumerate(fetched_docs)}
|
||||
for i, indice_idx in enumerate(indices[0]):
|
||||
pos = idx_pos.get(indice_idx)
|
||||
if pos is None:
|
||||
continue
|
||||
fetch_doc = fetched_docs[pos]
|
||||
score = scores[0][i]
|
||||
result_docs.append(Result(similarity=float(score), data=fetch_doc))
|
||||
return result_docs[:k]
|
||||
|
||||
async def delete(self, doc_id: int):
|
||||
"""
|
||||
删除一条文档
|
||||
"""
|
||||
await self.document_storage.connection.execute(
|
||||
"DELETE FROM documents WHERE doc_id = ?", (doc_id,)
|
||||
)
|
||||
await self.document_storage.connection.commit()
|
||||
|
||||
async def close(self):
|
||||
await self.document_storage.close()
|
||||
|
||||
async def count_documents(self) -> int:
|
||||
"""
|
||||
计算文档数量
|
||||
"""
|
||||
async with self.document_storage.connection.cursor() as cursor:
|
||||
await cursor.execute("SELECT COUNT(*) FROM documents")
|
||||
count = await cursor.fetchone()
|
||||
return count[0] if count else 0
|
||||
@@ -2,6 +2,8 @@ import asyncio
|
||||
import os
|
||||
import uuid
|
||||
import time
|
||||
from urllib.parse import urlparse, unquote
|
||||
import platform
|
||||
|
||||
|
||||
class FileTokenService:
|
||||
@@ -15,7 +17,9 @@ class FileTokenService:
|
||||
async def _cleanup_expired_tokens(self):
|
||||
"""清理过期的令牌"""
|
||||
now = time.time()
|
||||
expired_tokens = [token for token, (_, expire) in self.staged_files.items() if expire < now]
|
||||
expired_tokens = [
|
||||
token for token, (_, expire) in self.staged_files.items() if expire < now
|
||||
]
|
||||
for token in expired_tokens:
|
||||
self.staged_files.pop(token, None)
|
||||
|
||||
@@ -32,15 +36,35 @@ class FileTokenService:
|
||||
Raises:
|
||||
FileNotFoundError: 当路径不存在时抛出
|
||||
"""
|
||||
|
||||
# 处理 file:///
|
||||
try:
|
||||
parsed_uri = urlparse(file_path)
|
||||
if parsed_uri.scheme == "file":
|
||||
local_path = unquote(parsed_uri.path)
|
||||
if platform.system() == "Windows" and local_path.startswith("/"):
|
||||
local_path = local_path[1:]
|
||||
else:
|
||||
# 如果没有 file:/// 前缀,则认为是普通路径
|
||||
local_path = file_path
|
||||
except Exception:
|
||||
# 解析失败时,按原路径处理
|
||||
local_path = file_path
|
||||
|
||||
async with self.lock:
|
||||
await self._cleanup_expired_tokens()
|
||||
|
||||
if not os.path.exists(file_path):
|
||||
raise FileNotFoundError(f"文件不存在: {file_path}")
|
||||
if not os.path.exists(local_path):
|
||||
raise FileNotFoundError(
|
||||
f"文件不存在: {local_path} (原始输入: {file_path})"
|
||||
)
|
||||
|
||||
file_token = str(uuid.uuid4())
|
||||
expire_time = time.time() + (timeout if timeout is not None else self.default_timeout)
|
||||
self.staged_files[file_token] = (file_path, expire_time)
|
||||
expire_time = time.time() + (
|
||||
timeout if timeout is not None else self.default_timeout
|
||||
)
|
||||
# 存储转换后的真实路径
|
||||
self.staged_files[file_token] = (local_path, expire_time)
|
||||
return file_token
|
||||
|
||||
async def handle_file(self, file_token: str) -> str:
|
||||
|
||||
@@ -26,13 +26,14 @@ class InitialLoader:
|
||||
async def start(self):
|
||||
core_lifecycle = AstrBotCoreLifecycle(self.log_broker, self.db)
|
||||
|
||||
core_task = []
|
||||
try:
|
||||
await core_lifecycle.initialize()
|
||||
core_task = core_lifecycle.start()
|
||||
except Exception as e:
|
||||
logger.critical(traceback.format_exc())
|
||||
logger.critical(f"😭 初始化 AstrBot 失败:{e} !!!")
|
||||
return
|
||||
|
||||
core_task = core_lifecycle.start()
|
||||
|
||||
self.dashboard_server = AstrBotDashboard(
|
||||
core_lifecycle, self.db, core_lifecycle.dashboard_shutdown_event
|
||||
|
||||
@@ -96,8 +96,6 @@ class LogBroker:
|
||||
Queue: 订阅者的队列, 可用于接收日志消息
|
||||
"""
|
||||
q = Queue(maxsize=CACHED_SIZE + 10)
|
||||
for log in self.log_cache:
|
||||
q.put_nowait(log)
|
||||
self.subscribers.append(q)
|
||||
return q
|
||||
|
||||
|
||||
@@ -102,6 +102,10 @@ class BaseMessageComponent(BaseModel):
|
||||
data[k] = v
|
||||
return {"type": self.type.lower(), "data": data}
|
||||
|
||||
async def to_dict(self) -> dict:
|
||||
# 默认情况下,回退到旧的同步 toDict()
|
||||
return self.toDict()
|
||||
|
||||
|
||||
class Plain(BaseMessageComponent):
|
||||
type: ComponentType = "Plain"
|
||||
@@ -118,6 +122,12 @@ class Plain(BaseMessageComponent):
|
||||
self.text.replace("&", "&").replace("[", "[").replace("]", "]")
|
||||
)
|
||||
|
||||
def toDict(self):
|
||||
return {"type": "text", "data": {"text": self.text.strip()}}
|
||||
|
||||
async def to_dict(self):
|
||||
return {"type": "text", "data": {"text": self.text}}
|
||||
|
||||
|
||||
class Face(BaseMessageComponent):
|
||||
type: ComponentType = "Face"
|
||||
@@ -235,9 +245,6 @@ class Video(BaseMessageComponent):
|
||||
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
|
||||
@@ -250,6 +257,70 @@ class Video(BaseMessageComponent):
|
||||
return Video(file=url, **_)
|
||||
raise Exception("not a valid url")
|
||||
|
||||
async def convert_to_file_path(self) -> str:
|
||||
"""将这个视频统一转换为本地文件路径。这个方法避免了手动判断视频数据类型,直接返回视频数据的本地路径(如果是网络 URL,则会自动进行下载)。
|
||||
|
||||
Returns:
|
||||
str: 视频的本地路径,以绝对路径表示。
|
||||
"""
|
||||
url = self.file
|
||||
if url and url.startswith("file:///"):
|
||||
return url[8:]
|
||||
elif url and url.startswith("http"):
|
||||
download_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
video_file_path = os.path.join(download_dir, f"{uuid.uuid4().hex}")
|
||||
await download_file(url, video_file_path)
|
||||
if os.path.exists(video_file_path):
|
||||
return os.path.abspath(video_file_path)
|
||||
else:
|
||||
raise Exception(f"download failed: {url}")
|
||||
elif os.path.exists(url):
|
||||
return os.path.abspath(url)
|
||||
else:
|
||||
raise Exception(f"not a valid file: {url}")
|
||||
|
||||
async def register_to_file_service(self):
|
||||
"""
|
||||
将视频注册到文件服务。
|
||||
|
||||
Returns:
|
||||
str: 注册后的URL
|
||||
|
||||
Raises:
|
||||
Exception: 如果未配置 callback_api_base
|
||||
"""
|
||||
callback_host = astrbot_config.get("callback_api_base")
|
||||
|
||||
if not callback_host:
|
||||
raise Exception("未配置 callback_api_base,文件服务不可用")
|
||||
|
||||
file_path = await self.convert_to_file_path()
|
||||
|
||||
token = await file_token_service.register_file(file_path)
|
||||
|
||||
logger.debug(f"已注册:{callback_host}/api/file/{token}")
|
||||
|
||||
return f"{callback_host}/api/file/{token}"
|
||||
|
||||
async def to_dict(self):
|
||||
"""需要和 toDict 区分开,toDict 是同步方法"""
|
||||
url_or_path = self.file
|
||||
if url_or_path.startswith("http"):
|
||||
payload_file = url_or_path
|
||||
elif callback_host := astrbot_config.get("callback_api_base"):
|
||||
callback_host = str(callback_host).removesuffix("/")
|
||||
token = await file_token_service.register_file(url_or_path)
|
||||
payload_file = f"{callback_host}/api/file/{token}"
|
||||
logger.debug(f"Generated video file callback link: {payload_file}")
|
||||
else:
|
||||
payload_file = url_or_path
|
||||
return {
|
||||
"type": "video",
|
||||
"data": {
|
||||
"file": payload_file,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class At(BaseMessageComponent):
|
||||
type: ComponentType = "At"
|
||||
@@ -259,6 +330,12 @@ class At(BaseMessageComponent):
|
||||
def __init__(self, **_):
|
||||
super().__init__(**_)
|
||||
|
||||
def toDict(self):
|
||||
return {
|
||||
"type": "at",
|
||||
"data": {"qq": str(self.qq)},
|
||||
}
|
||||
|
||||
|
||||
class AtAll(At):
|
||||
qq: str = "all"
|
||||
@@ -514,27 +591,51 @@ class Node(BaseMessageComponent):
|
||||
id: T.Optional[int] = 0 # 忽略
|
||||
name: T.Optional[str] = "" # qq昵称
|
||||
uin: T.Optional[str] = "0" # qq号
|
||||
content: T.Optional[T.Union[str, list, dict]] = "" # 子消息段列表
|
||||
content: T.Optional[list[BaseMessageComponent]] = []
|
||||
seq: T.Optional[T.Union[str, list]] = "" # 忽略
|
||||
time: T.Optional[int] = 0 # 忽略
|
||||
|
||||
def __init__(self, content: T.Union[str, list, dict, "Node", T.List["Node"]], **_):
|
||||
if isinstance(content, list):
|
||||
_content = None
|
||||
if all(isinstance(item, Node) for item in content):
|
||||
_content = [node.toDict() for node in content]
|
||||
else:
|
||||
_content = ""
|
||||
for chain in content:
|
||||
_content += chain.toString()
|
||||
content = _content
|
||||
elif isinstance(content, Node):
|
||||
content = content.toDict()
|
||||
def __init__(self, content: list[BaseMessageComponent], **_):
|
||||
if isinstance(content, Node):
|
||||
# back
|
||||
content = [content]
|
||||
super().__init__(content=content, **_)
|
||||
|
||||
def toString(self):
|
||||
# logger.warn("Protocol: node doesn't support stringify")
|
||||
return ""
|
||||
async def to_dict(self):
|
||||
data_content = []
|
||||
for comp in self.content:
|
||||
if isinstance(comp, (Image, Record)):
|
||||
# For Image and Record segments, we convert them to base64
|
||||
bs64 = await comp.convert_to_base64()
|
||||
data_content.append(
|
||||
{
|
||||
"type": comp.type.lower(),
|
||||
"data": {"file": f"base64://{bs64}"},
|
||||
}
|
||||
)
|
||||
elif isinstance(comp, Plain):
|
||||
# For Plain segments, we need to handle the plain differently
|
||||
d = await comp.to_dict()
|
||||
data_content.append(d)
|
||||
elif isinstance(comp, File):
|
||||
# For File segments, we need to handle the file differently
|
||||
d = await comp.to_dict()
|
||||
data_content.append(d)
|
||||
elif isinstance(comp, (Node, Nodes)):
|
||||
# For Node segments, we recursively convert them to dict
|
||||
d = await comp.to_dict()
|
||||
data_content.append(d)
|
||||
else:
|
||||
d = comp.toDict()
|
||||
data_content.append(d)
|
||||
return {
|
||||
"type": "node",
|
||||
"data": {
|
||||
"user_id": str(self.uin),
|
||||
"nickname": self.name,
|
||||
"content": data_content,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class Nodes(BaseMessageComponent):
|
||||
@@ -545,12 +646,20 @@ class Nodes(BaseMessageComponent):
|
||||
super().__init__(nodes=nodes, **_)
|
||||
|
||||
def toDict(self):
|
||||
"""Deprecated. Use to_dict instead"""
|
||||
ret = {
|
||||
"messages": [],
|
||||
}
|
||||
for node in self.nodes:
|
||||
d = node.toDict()
|
||||
d["data"]["uin"] = str(node.uin) # 转为字符串
|
||||
ret["messages"].append(d)
|
||||
return ret
|
||||
|
||||
async def to_dict(self):
|
||||
"""将 Nodes 转换为字典格式,适用于 OneBot JSON 格式"""
|
||||
ret = {"messages": []}
|
||||
for node in self.nodes:
|
||||
d = await node.to_dict()
|
||||
ret["messages"].append(d)
|
||||
return ret
|
||||
|
||||
@@ -723,6 +832,26 @@ class File(BaseMessageComponent):
|
||||
|
||||
return f"{callback_host}/api/file/{token}"
|
||||
|
||||
async def to_dict(self):
|
||||
"""需要和 toDict 区分开,toDict 是同步方法"""
|
||||
url_or_path = await self.get_file(allow_return_url=True)
|
||||
if url_or_path.startswith("http"):
|
||||
payload_file = url_or_path
|
||||
elif callback_host := astrbot_config.get("callback_api_base"):
|
||||
callback_host = str(callback_host).removesuffix("/")
|
||||
token = await file_token_service.register_file(url_or_path)
|
||||
payload_file = f"{callback_host}/api/file/{token}"
|
||||
logger.debug(f"Generated file callback link: {payload_file}")
|
||||
else:
|
||||
payload_file = url_or_path
|
||||
return {
|
||||
"type": "file",
|
||||
"data": {
|
||||
"name": self.name,
|
||||
"file": payload_file,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class WechatEmoji(BaseMessageComponent):
|
||||
type: ComponentType = "WechatEmoji"
|
||||
|
||||
@@ -24,6 +24,8 @@ class MessageChain:
|
||||
|
||||
chain: List[BaseMessageComponent] = field(default_factory=list)
|
||||
use_t2i_: Optional[bool] = None # None 为跟随用户设置
|
||||
type: Optional[str] = None
|
||||
"""消息链承载的消息的类型。可选,用于让消息平台区分不同业务场景的消息链。"""
|
||||
|
||||
def message(self, message: str):
|
||||
"""添加一条文本消息到消息链 `chain` 中。
|
||||
@@ -98,6 +100,15 @@ class MessageChain:
|
||||
self.chain.append(Image.fromFileSystem(path))
|
||||
return self
|
||||
|
||||
def base64_image(self, base64_str: str):
|
||||
"""添加一条图片消息(base64 编码字符串)到消息链 `chain` 中。
|
||||
Example:
|
||||
|
||||
CommandResult().base64_image("iVBORw0KGgoAAAANSUhEUgAAAAUA...")
|
||||
"""
|
||||
self.chain.append(Image.fromBase64(base64_str))
|
||||
return self
|
||||
|
||||
def use_t2i(self, use_t2i: bool):
|
||||
"""设置是否使用文本转图片服务。
|
||||
|
||||
@@ -157,7 +168,7 @@ class ResultContentType(enum.Enum):
|
||||
"""普通的消息结果"""
|
||||
STREAMING_RESULT = enum.auto()
|
||||
"""调用 LLM 产生的流式结果"""
|
||||
STREAMING_FINISH= enum.auto()
|
||||
STREAMING_FINISH = enum.auto()
|
||||
"""流式输出完成"""
|
||||
|
||||
|
||||
|
||||
@@ -1,22 +1,24 @@
|
||||
from astrbot.core.message.message_event_result import (
|
||||
MessageEventResult,
|
||||
EventResultType,
|
||||
MessageEventResult,
|
||||
)
|
||||
|
||||
from .waking_check.stage import WakingCheckStage
|
||||
from .whitelist_check.stage import WhitelistCheckStage
|
||||
from .rate_limit_check.stage import RateLimitStage
|
||||
from .content_safety_check.stage import ContentSafetyCheckStage
|
||||
from .platform_compatibility.stage import PlatformCompatibilityStage
|
||||
from .preprocess_stage.stage import PreProcessStage
|
||||
from .process_stage.stage import ProcessStage
|
||||
from .result_decorate.stage import ResultDecorateStage
|
||||
from .rate_limit_check.stage import RateLimitStage
|
||||
from .respond.stage import RespondStage
|
||||
from .result_decorate.stage import ResultDecorateStage
|
||||
from .session_status_check.stage import SessionStatusCheckStage
|
||||
from .waking_check.stage import WakingCheckStage
|
||||
from .whitelist_check.stage import WhitelistCheckStage
|
||||
|
||||
# 管道阶段顺序
|
||||
STAGES_ORDER = [
|
||||
"WakingCheckStage", # 检查是否需要唤醒
|
||||
"WhitelistCheckStage", # 检查是否在群聊/私聊白名单
|
||||
"SessionStatusCheckStage", # 检查会话是否整体启用
|
||||
"RateLimitStage", # 检查会话是否超过频率限制
|
||||
"ContentSafetyCheckStage", # 检查内容安全
|
||||
"PlatformCompatibilityStage", # 检查所有处理器的平台兼容性
|
||||
@@ -29,6 +31,7 @@ STAGES_ORDER = [
|
||||
__all__ = [
|
||||
"WakingCheckStage",
|
||||
"WhitelistCheckStage",
|
||||
"SessionStatusCheckStage",
|
||||
"RateLimitStage",
|
||||
"ContentSafetyCheckStage",
|
||||
"PlatformCompatibilityStage",
|
||||
|
||||
@@ -1,6 +1,14 @@
|
||||
import inspect
|
||||
import traceback
|
||||
import typing as T
|
||||
from dataclasses import dataclass
|
||||
from astrbot.core.config.astrbot_config import AstrBotConfig
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.star import PluginManager
|
||||
from astrbot.api import logger
|
||||
from astrbot.core.star.star_handler import star_handlers_registry, EventType
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.message.message_event_result import MessageEventResult, CommandResult
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -9,3 +17,97 @@ class PipelineContext:
|
||||
|
||||
astrbot_config: AstrBotConfig # AstrBot 配置对象
|
||||
plugin_manager: PluginManager # 插件管理器对象
|
||||
|
||||
async def call_event_hook(
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
hook_type: EventType,
|
||||
*args,
|
||||
) -> bool:
|
||||
"""调用事件钩子函数
|
||||
|
||||
Returns:
|
||||
bool: 如果事件被终止,返回 True
|
||||
"""
|
||||
platform_id = event.get_platform_id()
|
||||
handlers = star_handlers_registry.get_handlers_by_event_type(
|
||||
hook_type, platform_id=platform_id
|
||||
)
|
||||
for handler in handlers:
|
||||
try:
|
||||
logger.debug(
|
||||
f"hook(on_llm_request) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
|
||||
)
|
||||
await handler.handler(event, *args)
|
||||
except BaseException:
|
||||
logger.error(traceback.format_exc())
|
||||
|
||||
if event.is_stopped():
|
||||
logger.info(
|
||||
f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
|
||||
)
|
||||
|
||||
return event.is_stopped()
|
||||
|
||||
async def call_handler(
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
handler: T.Awaitable,
|
||||
*args,
|
||||
**kwargs,
|
||||
) -> T.AsyncGenerator[None, None]:
|
||||
"""执行事件处理函数并处理其返回结果
|
||||
|
||||
该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数:
|
||||
1. 异步生成器: 实现洋葱模型,每次 yield 都会将控制权交回上层
|
||||
2. 协程: 执行一次并处理返回值
|
||||
|
||||
Args:
|
||||
ctx (PipelineContext): 消息管道上下文对象
|
||||
event (AstrMessageEvent): 事件对象
|
||||
handler (Awaitable): 事件处理函数
|
||||
|
||||
Returns:
|
||||
AsyncGenerator[None, None]: 异步生成器,用于在管道中传递控制流
|
||||
"""
|
||||
ready_to_call = None # 一个协程或者异步生成器
|
||||
|
||||
trace_ = None
|
||||
|
||||
try:
|
||||
ready_to_call = handler(event, *args, **kwargs)
|
||||
except TypeError as _:
|
||||
# 向下兼容
|
||||
trace_ = traceback.format_exc()
|
||||
# 以前的 handler 会额外传入一个参数, 但是 context 对象实际上在插件实例中有一份
|
||||
ready_to_call = handler(event, self.plugin_manager.context, *args, **kwargs)
|
||||
|
||||
if inspect.isasyncgen(ready_to_call):
|
||||
_has_yielded = False
|
||||
try:
|
||||
async for ret in ready_to_call:
|
||||
# 这里逐步执行异步生成器, 对于每个 yield 返回的 ret, 执行下面的代码
|
||||
# 返回值只能是 MessageEventResult 或者 None(无返回值)
|
||||
_has_yielded = True
|
||||
if isinstance(ret, (MessageEventResult, CommandResult)):
|
||||
# 如果返回值是 MessageEventResult, 设置结果并继续
|
||||
event.set_result(ret)
|
||||
yield
|
||||
else:
|
||||
# 如果返回值是 None, 则不设置结果并继续
|
||||
# 继续执行后续阶段
|
||||
yield ret
|
||||
if not _has_yielded:
|
||||
# 如果这个异步生成器没有执行到 yield 分支
|
||||
yield
|
||||
except Exception as e:
|
||||
logger.error(f"Previous Error: {trace_}")
|
||||
raise e
|
||||
elif inspect.iscoroutine(ready_to_call):
|
||||
# 如果只是一个协程, 直接执行
|
||||
ret = await ready_to_call
|
||||
if isinstance(ret, (MessageEventResult, CommandResult)):
|
||||
event.set_result(ret)
|
||||
yield
|
||||
else:
|
||||
yield ret
|
||||
|
||||
@@ -43,31 +43,31 @@ class PreProcessStage(Stage):
|
||||
# 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
|
||||
ctx = self.plugin_manager.context
|
||||
stt_provider = ctx.get_using_stt_provider(event.unified_msg_origin)
|
||||
if not stt_provider:
|
||||
return
|
||||
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
|
||||
|
||||
58
astrbot/core/pipeline/process_stage/agent_runner/base.py
Normal file
58
astrbot/core/pipeline/process_stage/agent_runner/base.py
Normal file
@@ -0,0 +1,58 @@
|
||||
import abc
|
||||
import typing as T
|
||||
from dataclasses import dataclass
|
||||
from astrbot.core.provider.entities import LLMResponse
|
||||
from ....message.message_event_result import MessageChain
|
||||
from enum import Enum, auto
|
||||
|
||||
|
||||
class AgentState(Enum):
|
||||
"""Agent 状态枚举"""
|
||||
|
||||
IDLE = auto() # 初始状态
|
||||
RUNNING = auto() # 运行中
|
||||
DONE = auto() # 完成
|
||||
ERROR = auto() # 错误状态
|
||||
|
||||
|
||||
class AgentResponseData(T.TypedDict):
|
||||
chain: MessageChain
|
||||
|
||||
|
||||
@dataclass
|
||||
class AgentResponse:
|
||||
type: str
|
||||
data: AgentResponseData
|
||||
|
||||
|
||||
class BaseAgentRunner:
|
||||
@abc.abstractmethod
|
||||
async def reset(self) -> None:
|
||||
"""
|
||||
Reset the agent to its initial state.
|
||||
This method should be called before starting a new run.
|
||||
"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
async def step(self) -> T.AsyncGenerator[AgentResponse, None]:
|
||||
"""
|
||||
Process a single step of the agent.
|
||||
"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
def done(self) -> bool:
|
||||
"""
|
||||
Check if the agent has completed its task.
|
||||
Returns True if the agent is done, False otherwise.
|
||||
"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
def get_final_llm_resp(self) -> LLMResponse | None:
|
||||
"""
|
||||
Get the final observation from the agent.
|
||||
This method should be called after the agent is done.
|
||||
"""
|
||||
...
|
||||
@@ -0,0 +1,306 @@
|
||||
import sys
|
||||
import traceback
|
||||
import typing as T
|
||||
from .base import BaseAgentRunner, AgentResponse, AgentResponseData, AgentState
|
||||
from ...context import PipelineContext
|
||||
from astrbot.core.provider.provider import Provider
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.message.message_event_result import (
|
||||
MessageChain,
|
||||
)
|
||||
from astrbot.core.provider.entities import (
|
||||
ProviderRequest,
|
||||
LLMResponse,
|
||||
ToolCallMessageSegment,
|
||||
AssistantMessageSegment,
|
||||
ToolCallsResult,
|
||||
)
|
||||
from mcp.types import (
|
||||
TextContent,
|
||||
ImageContent,
|
||||
EmbeddedResource,
|
||||
TextResourceContents,
|
||||
BlobResourceContents,
|
||||
)
|
||||
from astrbot.core.star.star_handler import EventType
|
||||
from astrbot import logger
|
||||
|
||||
if sys.version_info >= (3, 12):
|
||||
from typing import override
|
||||
else:
|
||||
from typing_extensions import override
|
||||
|
||||
|
||||
# TODO:
|
||||
# 1. 处理平台不兼容的处理器
|
||||
|
||||
|
||||
class ToolLoopAgent(BaseAgentRunner):
|
||||
def __init__(
|
||||
self, provider: Provider, event: AstrMessageEvent, pipeline_ctx: PipelineContext
|
||||
) -> None:
|
||||
self.provider = provider
|
||||
self.req = None
|
||||
self.event = event
|
||||
self.pipeline_ctx = pipeline_ctx
|
||||
self._state = AgentState.IDLE
|
||||
self.final_llm_resp = None
|
||||
self.streaming = False
|
||||
|
||||
@override
|
||||
async def reset(self, req: ProviderRequest, streaming: bool) -> None:
|
||||
self.req = req
|
||||
self.streaming = streaming
|
||||
self.final_llm_resp = None
|
||||
self._state = AgentState.IDLE
|
||||
|
||||
def _transition_state(self, new_state: AgentState) -> None:
|
||||
"""转换 Agent 状态"""
|
||||
if self._state != new_state:
|
||||
logger.debug(f"Agent state transition: {self._state} -> {new_state}")
|
||||
self._state = new_state
|
||||
|
||||
async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]:
|
||||
"""Yields chunks *and* a final LLMResponse."""
|
||||
if self.streaming:
|
||||
stream = self.provider.text_chat_stream(**self.req.__dict__)
|
||||
async for resp in stream: # type: ignore
|
||||
yield resp
|
||||
else:
|
||||
yield await self.provider.text_chat(**self.req.__dict__)
|
||||
|
||||
@override
|
||||
async def step(self):
|
||||
"""
|
||||
Process a single step of the agent.
|
||||
This method should return the result of the step.
|
||||
"""
|
||||
if not self.req:
|
||||
raise ValueError("Request is not set. Please call reset() first.")
|
||||
|
||||
# 开始处理,转换到运行状态
|
||||
self._transition_state(AgentState.RUNNING)
|
||||
llm_resp_result = None
|
||||
|
||||
async for llm_response in self._iter_llm_responses():
|
||||
assert isinstance(llm_response, LLMResponse)
|
||||
if llm_response.is_chunk:
|
||||
if llm_response.result_chain:
|
||||
yield AgentResponse(
|
||||
type="streaming_delta",
|
||||
data=AgentResponseData(chain=llm_response.result_chain),
|
||||
)
|
||||
else:
|
||||
yield AgentResponse(
|
||||
type="streaming_delta",
|
||||
data=AgentResponseData(
|
||||
chain=MessageChain().message(llm_response.completion_text)
|
||||
),
|
||||
)
|
||||
continue
|
||||
llm_resp_result = llm_response
|
||||
break # got final response
|
||||
|
||||
if not llm_resp_result:
|
||||
return
|
||||
|
||||
# 处理 LLM 响应
|
||||
llm_resp = llm_resp_result
|
||||
|
||||
if llm_resp.role == "err":
|
||||
# 如果 LLM 响应错误,转换到错误状态
|
||||
self.final_llm_resp = llm_resp
|
||||
self._transition_state(AgentState.ERROR)
|
||||
yield AgentResponse(
|
||||
type="err",
|
||||
data=AgentResponseData(
|
||||
chain=MessageChain().message(
|
||||
f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}"
|
||||
)
|
||||
),
|
||||
)
|
||||
|
||||
if not llm_resp.tools_call_name:
|
||||
# 如果没有工具调用,转换到完成状态
|
||||
self.final_llm_resp = llm_resp
|
||||
self._transition_state(AgentState.DONE)
|
||||
|
||||
# 执行事件钩子
|
||||
if await self.pipeline_ctx.call_event_hook(
|
||||
self.event, EventType.OnLLMResponseEvent, llm_resp
|
||||
):
|
||||
return
|
||||
|
||||
# 返回 LLM 结果
|
||||
if llm_resp.result_chain:
|
||||
yield AgentResponse(
|
||||
type="llm_result",
|
||||
data=AgentResponseData(chain=llm_resp.result_chain),
|
||||
)
|
||||
elif llm_resp.completion_text:
|
||||
yield AgentResponse(
|
||||
type="llm_result",
|
||||
data=AgentResponseData(
|
||||
chain=MessageChain().message(llm_resp.completion_text)
|
||||
),
|
||||
)
|
||||
|
||||
# 如果有工具调用,还需处理工具调用
|
||||
if llm_resp.tools_call_name:
|
||||
tool_call_result_blocks = []
|
||||
for tool_call_name in llm_resp.tools_call_name:
|
||||
yield AgentResponse(
|
||||
type="tool_call",
|
||||
data=AgentResponseData(
|
||||
chain=MessageChain().message(f"🔨 调用工具: {tool_call_name}")
|
||||
),
|
||||
)
|
||||
async for result in self._handle_function_tools(self.req, llm_resp):
|
||||
if isinstance(result, list):
|
||||
tool_call_result_blocks = result
|
||||
elif isinstance(result, MessageChain):
|
||||
yield AgentResponse(
|
||||
type="tool_call_result",
|
||||
data=AgentResponseData(chain=result),
|
||||
)
|
||||
# 将结果添加到上下文中
|
||||
tool_calls_result = ToolCallsResult(
|
||||
tool_calls_info=AssistantMessageSegment(
|
||||
role="assistant",
|
||||
tool_calls=llm_resp.to_openai_tool_calls(),
|
||||
content=llm_resp.completion_text,
|
||||
),
|
||||
tool_calls_result=tool_call_result_blocks,
|
||||
)
|
||||
self.req.append_tool_calls_result(tool_calls_result)
|
||||
|
||||
async def _handle_function_tools(
|
||||
self,
|
||||
req: ProviderRequest,
|
||||
llm_response: LLMResponse,
|
||||
) -> T.AsyncGenerator[MessageChain | list[ToolCallMessageSegment], None]:
|
||||
"""处理函数工具调用。"""
|
||||
tool_call_result_blocks: list[ToolCallMessageSegment] = []
|
||||
logger.info(f"Agent 使用工具: {llm_response.tools_call_name}")
|
||||
|
||||
# 执行函数调用
|
||||
for func_tool_name, func_tool_args, func_tool_id in zip(
|
||||
llm_response.tools_call_name,
|
||||
llm_response.tools_call_args,
|
||||
llm_response.tools_call_ids,
|
||||
):
|
||||
try:
|
||||
if not req.func_tool:
|
||||
return
|
||||
func_tool = req.func_tool.get_func(func_tool_name)
|
||||
if func_tool.origin == "mcp":
|
||||
logger.info(
|
||||
f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数:{func_tool.name},参数:{func_tool_args}"
|
||||
)
|
||||
client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name]
|
||||
res = await client.session.call_tool(func_tool.name, func_tool_args)
|
||||
if not res:
|
||||
continue
|
||||
if isinstance(res.content[0], TextContent):
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=res.content[0].text,
|
||||
)
|
||||
)
|
||||
yield MessageChain().message(res.content[0].text)
|
||||
elif isinstance(res.content[0], ImageContent):
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回了图片(已直接发送给用户)",
|
||||
)
|
||||
)
|
||||
yield MessageChain(type="tool_direct_result").base64_image(
|
||||
res.content[0].data
|
||||
)
|
||||
elif isinstance(res.content[0], EmbeddedResource):
|
||||
resource = res.content[0].resource
|
||||
if isinstance(resource, TextResourceContents):
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=resource.text,
|
||||
)
|
||||
)
|
||||
yield MessageChain().message(resource.text)
|
||||
elif (
|
||||
isinstance(resource, BlobResourceContents)
|
||||
and resource.mimeType
|
||||
and resource.mimeType.startswith("image/")
|
||||
):
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回了图片(已直接发送给用户)",
|
||||
)
|
||||
)
|
||||
yield MessageChain(type="tool_direct_result").base64_image(
|
||||
res.content[0].data
|
||||
)
|
||||
else:
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回的数据类型不受支持",
|
||||
)
|
||||
)
|
||||
yield MessageChain().message("返回的数据类型不受支持。")
|
||||
else:
|
||||
logger.info(f"使用工具:{func_tool_name},参数:{func_tool_args}")
|
||||
# 尝试调用工具函数
|
||||
wrapper = self.pipeline_ctx.call_handler(
|
||||
self.event, func_tool.handler, **func_tool_args
|
||||
)
|
||||
async for resp in wrapper:
|
||||
if resp is not None:
|
||||
# Tool 返回结果
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=resp,
|
||||
)
|
||||
)
|
||||
yield MessageChain().message(resp)
|
||||
else:
|
||||
# Tool 直接请求发送消息给用户
|
||||
# 这里我们将直接结束 Agent Loop。
|
||||
self._transition_state(AgentState.DONE)
|
||||
if res := self.event.get_result():
|
||||
if res.chain:
|
||||
yield MessageChain(
|
||||
chain=res.chain, type="tool_direct_result"
|
||||
)
|
||||
|
||||
self.event.clear_result()
|
||||
except Exception as e:
|
||||
logger.warning(traceback.format_exc())
|
||||
tool_call_result_blocks.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=f"error: {str(e)}",
|
||||
)
|
||||
)
|
||||
|
||||
# 处理函数调用响应
|
||||
if tool_call_result_blocks:
|
||||
yield tool_call_result_blocks
|
||||
|
||||
def done(self) -> bool:
|
||||
"""检查 Agent 是否已完成工作"""
|
||||
return self._state in (AgentState.DONE, AgentState.ERROR)
|
||||
|
||||
def get_final_llm_resp(self) -> LLMResponse | None:
|
||||
return self.final_llm_resp
|
||||
@@ -2,56 +2,47 @@
|
||||
本地 Agent 模式的 LLM 调用 Stage
|
||||
"""
|
||||
|
||||
import traceback
|
||||
import asyncio
|
||||
import copy
|
||||
import json
|
||||
from typing import Union, AsyncGenerator
|
||||
from ...context import PipelineContext
|
||||
from ..stage import Stage
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
import traceback
|
||||
from typing import AsyncGenerator, Union
|
||||
from astrbot.core import logger
|
||||
from astrbot.core.message.components import Image
|
||||
from astrbot.core.message.message_event_result import (
|
||||
MessageChain,
|
||||
MessageEventResult,
|
||||
ResultContentType,
|
||||
MessageChain,
|
||||
)
|
||||
from astrbot.core.message.components import Image
|
||||
from astrbot.core import logger
|
||||
from astrbot.core.utils.metrics import Metric
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.provider import Provider
|
||||
from astrbot.core.provider.entities import (
|
||||
ProviderRequest,
|
||||
LLMResponse,
|
||||
ToolCallMessageSegment,
|
||||
AssistantMessageSegment,
|
||||
ToolCallsResult,
|
||||
)
|
||||
from astrbot.core.star.star_handler import star_handlers_registry, EventType
|
||||
from astrbot.core.star.star import star_map
|
||||
from mcp.types import (
|
||||
TextContent,
|
||||
ImageContent,
|
||||
EmbeddedResource,
|
||||
TextResourceContents,
|
||||
BlobResourceContents,
|
||||
ProviderRequest,
|
||||
)
|
||||
from astrbot.core.star.session_llm_manager import SessionServiceManager
|
||||
from astrbot.core.star.star_handler import EventType
|
||||
from astrbot.core.utils.metrics import Metric
|
||||
from ...context import PipelineContext
|
||||
from ..agent_runner.tool_loop_agent import ToolLoopAgent
|
||||
from ..stage import Stage
|
||||
|
||||
|
||||
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
|
||||
self.max_context_length = ctx.astrbot_config["provider_settings"][
|
||||
"max_context_length"
|
||||
] # int
|
||||
self.dequeue_context_length = min(
|
||||
max(1, ctx.astrbot_config["provider_settings"]["dequeue_context_length"]),
|
||||
conf = ctx.astrbot_config
|
||||
settings = conf["provider_settings"]
|
||||
self.bot_wake_prefixs: list[str] = conf["wake_prefix"] # list
|
||||
self.provider_wake_prefix: str = settings["wake_prefix"] # str
|
||||
self.max_context_length = settings["max_context_length"] # int
|
||||
self.dequeue_context_length: int = min(
|
||||
max(1, settings["dequeue_context_length"]),
|
||||
self.max_context_length - 1,
|
||||
) # int
|
||||
self.streaming_response = ctx.astrbot_config["provider_settings"][
|
||||
"streaming_response"
|
||||
] # bool
|
||||
)
|
||||
self.streaming_response: bool = settings["streaming_response"]
|
||||
self.max_step: int = settings.get("max_agent_step", 10)
|
||||
self.show_tool_use: bool = settings.get("show_tool_use_status", True)
|
||||
|
||||
for bwp in self.bot_wake_prefixs:
|
||||
if self.provider_wake_prefix.startswith(bwp):
|
||||
@@ -62,12 +53,33 @@ class LLMRequestSubStage(Stage):
|
||||
|
||||
self.conv_manager = ctx.plugin_manager.context.conversation_manager
|
||||
|
||||
def _select_provider(self, event: AstrMessageEvent) -> Provider | None:
|
||||
"""选择使用的 LLM 提供商"""
|
||||
sel_provider = event.get_extra("selected_provider")
|
||||
_ctx = self.ctx.plugin_manager.context
|
||||
if sel_provider and isinstance(sel_provider, str):
|
||||
provider = _ctx.get_provider_by_id(sel_provider)
|
||||
if not provider:
|
||||
logger.error(f"未找到指定的提供商: {sel_provider}。")
|
||||
return provider
|
||||
|
||||
return _ctx.get_using_provider(umo=event.unified_msg_origin)
|
||||
|
||||
async def process(
|
||||
self, event: AstrMessageEvent, _nested: bool = False
|
||||
) -> Union[None, AsyncGenerator[None, None]]:
|
||||
req: ProviderRequest = None
|
||||
req: ProviderRequest | None = None
|
||||
|
||||
provider = self.ctx.plugin_manager.context.get_using_provider()
|
||||
if not self.ctx.astrbot_config["provider_settings"]["enable"]:
|
||||
logger.debug("未启用 LLM 能力,跳过处理。")
|
||||
return
|
||||
|
||||
# 检查会话级别的LLM启停状态
|
||||
if not SessionServiceManager.should_process_llm_request(event):
|
||||
logger.debug(f"会话 {event.unified_msg_origin} 禁用了 LLM,跳过处理。")
|
||||
return
|
||||
|
||||
provider = self._select_provider(event)
|
||||
if provider is None:
|
||||
return
|
||||
|
||||
@@ -78,13 +90,12 @@ class LLMRequestSubStage(Stage):
|
||||
)
|
||||
|
||||
if req.conversation:
|
||||
all_contexts = json.loads(req.conversation.history)
|
||||
req.contexts = self._process_tool_message_pairs(
|
||||
all_contexts, remove_tags=True
|
||||
)
|
||||
req.contexts = json.loads(req.conversation.history)
|
||||
|
||||
else:
|
||||
req = ProviderRequest(prompt="", image_urls=[])
|
||||
if sel_model := event.get_extra("selected_model"):
|
||||
req.model = sel_model
|
||||
if self.provider_wake_prefix:
|
||||
if not event.message_str.startswith(self.provider_wake_prefix):
|
||||
return
|
||||
@@ -122,26 +133,8 @@ class LLMRequestSubStage(Stage):
|
||||
return
|
||||
|
||||
# 执行请求 LLM 前事件钩子。
|
||||
# 装饰 system_prompt 等功能
|
||||
# 获取当前平台ID
|
||||
platform_id = event.get_platform_id()
|
||||
handlers = star_handlers_registry.get_handlers_by_event_type(
|
||||
EventType.OnLLMRequestEvent, platform_id=platform_id
|
||||
)
|
||||
for handler in handlers:
|
||||
try:
|
||||
logger.debug(
|
||||
f"hook(on_llm_request) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
|
||||
)
|
||||
await handler.handler(event, req)
|
||||
except BaseException:
|
||||
logger.error(traceback.format_exc())
|
||||
|
||||
if event.is_stopped():
|
||||
logger.info(
|
||||
f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
|
||||
)
|
||||
return
|
||||
if await self.ctx.call_event_hook(event, EventType.OnLLMRequestEvent, req):
|
||||
return
|
||||
|
||||
if isinstance(req.contexts, str):
|
||||
req.contexts = json.loads(req.contexts)
|
||||
@@ -171,77 +164,77 @@ class LLMRequestSubStage(Stage):
|
||||
if not req.session_id:
|
||||
req.session_id = event.unified_msg_origin
|
||||
|
||||
async def requesting(req: ProviderRequest):
|
||||
try:
|
||||
need_loop = True
|
||||
while need_loop:
|
||||
need_loop = False
|
||||
logger.debug(f"提供商请求 Payload: {req}")
|
||||
# fix messages
|
||||
req.contexts = self.fix_messages(req.contexts)
|
||||
|
||||
final_llm_response = None
|
||||
|
||||
if self.streaming_response:
|
||||
stream = provider.text_chat_stream(**req.__dict__)
|
||||
async for llm_response in stream:
|
||||
if llm_response.is_chunk:
|
||||
if llm_response.result_chain:
|
||||
yield llm_response.result_chain # MessageChain
|
||||
else:
|
||||
yield MessageChain().message(
|
||||
llm_response.completion_text
|
||||
)
|
||||
else:
|
||||
final_llm_response = llm_response
|
||||
else:
|
||||
final_llm_response = await provider.text_chat(
|
||||
**req.__dict__
|
||||
) # 请求 LLM
|
||||
|
||||
if not final_llm_response:
|
||||
raise Exception("LLM response is None.")
|
||||
|
||||
# 执行 LLM 响应后的事件钩子。
|
||||
handlers = star_handlers_registry.get_handlers_by_event_type(
|
||||
EventType.OnLLMResponseEvent
|
||||
)
|
||||
for handler in handlers:
|
||||
try:
|
||||
logger.debug(
|
||||
f"hook(on_llm_response) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
|
||||
)
|
||||
await handler.handler(event, final_llm_response)
|
||||
except BaseException:
|
||||
logger.error(traceback.format_exc())
|
||||
# Call Agent
|
||||
tool_loop_agent = ToolLoopAgent(
|
||||
provider=provider,
|
||||
event=event,
|
||||
pipeline_ctx=self.ctx,
|
||||
)
|
||||
logger.debug(
|
||||
f"handle provider[id: {provider.provider_config['id']}] request: {req}"
|
||||
)
|
||||
await tool_loop_agent.reset(req=req, streaming=self.streaming_response)
|
||||
|
||||
async def requesting():
|
||||
step_idx = 0
|
||||
while step_idx < self.max_step:
|
||||
step_idx += 1
|
||||
try:
|
||||
async for resp in tool_loop_agent.step():
|
||||
if event.is_stopped():
|
||||
logger.info(
|
||||
f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
|
||||
)
|
||||
return
|
||||
if resp.type == "tool_call_result":
|
||||
msg_chain = resp.data["chain"]
|
||||
if msg_chain.type == "tool_direct_result":
|
||||
# tool_direct_result 用于标记 llm tool 需要直接发送给用户的内容
|
||||
resp.data["chain"].type = "tool_call_result"
|
||||
await event.send(resp.data["chain"])
|
||||
continue
|
||||
# 对于其他情况,暂时先不处理
|
||||
continue
|
||||
elif resp.type == "tool_call":
|
||||
if self.streaming_response:
|
||||
# 用来标记流式响应需要分节
|
||||
yield MessageChain(chain=[], type="break")
|
||||
if (
|
||||
self.show_tool_use
|
||||
or event.get_platform_name() == "webchat"
|
||||
):
|
||||
resp.data["chain"].type = "tool_call"
|
||||
await event.send(resp.data["chain"])
|
||||
continue
|
||||
|
||||
if self.streaming_response:
|
||||
# 流式输出的处理
|
||||
async for result in self._handle_llm_stream_response(
|
||||
event, req, final_llm_response
|
||||
):
|
||||
if isinstance(result, ProviderRequest):
|
||||
# 有函数工具调用并且返回了结果,我们需要再次请求 LLM
|
||||
req = result
|
||||
need_loop = True
|
||||
else:
|
||||
yield
|
||||
else:
|
||||
# 非流式输出的处理
|
||||
async for result in self._handle_llm_response(
|
||||
event, req, final_llm_response
|
||||
):
|
||||
if isinstance(result, ProviderRequest):
|
||||
# 有函数工具调用并且返回了结果,我们需要再次请求 LLM
|
||||
req = result
|
||||
need_loop = True
|
||||
else:
|
||||
yield
|
||||
if not self.streaming_response:
|
||||
content_typ = (
|
||||
ResultContentType.LLM_RESULT
|
||||
if resp.type == "llm_result"
|
||||
else ResultContentType.GENERAL_RESULT
|
||||
)
|
||||
event.set_result(
|
||||
MessageEventResult(
|
||||
chain=resp.data["chain"].chain,
|
||||
result_content_type=content_typ,
|
||||
)
|
||||
)
|
||||
yield
|
||||
event.clear_result()
|
||||
else:
|
||||
if resp.type == "streaming_delta":
|
||||
yield resp.data["chain"] # MessageChain
|
||||
if tool_loop_agent.done():
|
||||
break
|
||||
|
||||
except Exception as e:
|
||||
logger.error(traceback.format_exc())
|
||||
event.set_result(
|
||||
MessageEventResult().message(
|
||||
f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}\n\n请在控制台查看和分享错误详情。\n"
|
||||
)
|
||||
)
|
||||
return
|
||||
asyncio.create_task(
|
||||
Metric.upload(
|
||||
llm_tick=1,
|
||||
@@ -250,357 +243,127 @@ class LLMRequestSubStage(Stage):
|
||||
)
|
||||
)
|
||||
|
||||
# 保存到历史记录
|
||||
await self._save_to_history(event, req, final_llm_response)
|
||||
|
||||
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)}"
|
||||
)
|
||||
)
|
||||
|
||||
if not self.streaming_response:
|
||||
event.set_extra("tool_call_result", None)
|
||||
async for _ in requesting(req):
|
||||
yield
|
||||
else:
|
||||
if self.streaming_response:
|
||||
# 流式响应
|
||||
event.set_result(
|
||||
MessageEventResult()
|
||||
.set_result_content_type(ResultContentType.STREAMING_RESULT)
|
||||
.set_async_stream(requesting(req))
|
||||
.set_async_stream(requesting())
|
||||
)
|
||||
# 这里使用yield来暂停当前阶段,等待流式输出完成后继续处理
|
||||
yield
|
||||
|
||||
if event.get_extra("tool_call_result"):
|
||||
event.set_result(event.get_extra("tool_call_result"))
|
||||
event.set_extra("tool_call_result", None)
|
||||
if tool_loop_agent.done():
|
||||
if final_llm_resp := tool_loop_agent.get_final_llm_resp():
|
||||
if final_llm_resp.completion_text:
|
||||
chain = (
|
||||
MessageChain().message(final_llm_resp.completion_text).chain
|
||||
)
|
||||
else:
|
||||
chain = final_llm_resp.result_chain.chain
|
||||
event.set_result(
|
||||
MessageEventResult(
|
||||
chain=chain,
|
||||
result_content_type=ResultContentType.STREAMING_FINISH,
|
||||
)
|
||||
)
|
||||
else:
|
||||
async for _ in requesting():
|
||||
yield
|
||||
|
||||
# 暂时直接发出去
|
||||
if img_b64 := event.get_extra("tool_call_img_respond"):
|
||||
await event.send(MessageChain(chain=[Image.fromBase64(img_b64)]))
|
||||
event.set_extra("tool_call_img_respond", None)
|
||||
yield
|
||||
# 异步处理 WebChat 特殊情况
|
||||
if event.get_platform_name() == "webchat":
|
||||
asyncio.create_task(self._handle_webchat(event, req, provider))
|
||||
|
||||
async def _handle_llm_response(
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
req: ProviderRequest,
|
||||
llm_response: LLMResponse,
|
||||
) -> AsyncGenerator[Union[None, ProviderRequest], None]:
|
||||
"""处理非流式 LLM 响应。
|
||||
await self._save_to_history(event, req, tool_loop_agent.get_final_llm_resp())
|
||||
|
||||
Returns:
|
||||
AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest,表示需要再次调用 LLM
|
||||
|
||||
Yields:
|
||||
Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM
|
||||
"""
|
||||
if llm_response.role == "assistant":
|
||||
# text completion
|
||||
if llm_response.result_chain:
|
||||
event.set_result(
|
||||
MessageEventResult(
|
||||
chain=llm_response.result_chain.chain
|
||||
).set_result_content_type(ResultContentType.LLM_RESULT)
|
||||
)
|
||||
else:
|
||||
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":
|
||||
# 处理函数工具调用
|
||||
async for result in self._handle_function_tools(event, req, llm_response):
|
||||
yield result
|
||||
|
||||
async def _handle_llm_stream_response(
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
req: ProviderRequest,
|
||||
llm_response: LLMResponse,
|
||||
) -> AsyncGenerator[Union[None, ProviderRequest], None]:
|
||||
"""处理流式 LLM 响应。
|
||||
|
||||
专门用于处理流式输出完成后的响应,与非流式响应处理分离。
|
||||
|
||||
Returns:
|
||||
AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest,表示需要再次调用 LLM
|
||||
|
||||
Yields:
|
||||
Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM
|
||||
"""
|
||||
if llm_response.role == "assistant":
|
||||
# text completion
|
||||
if llm_response.result_chain:
|
||||
event.set_result(
|
||||
MessageEventResult(
|
||||
chain=llm_response.result_chain.chain
|
||||
).set_result_content_type(ResultContentType.STREAMING_FINISH)
|
||||
)
|
||||
else:
|
||||
event.set_result(
|
||||
MessageEventResult()
|
||||
.message(llm_response.completion_text)
|
||||
.set_result_content_type(ResultContentType.STREAMING_FINISH)
|
||||
)
|
||||
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":
|
||||
# 处理函数工具调用
|
||||
async for result in self._handle_function_tools(event, req, llm_response):
|
||||
yield result
|
||||
|
||||
async def _handle_function_tools(
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
req: ProviderRequest,
|
||||
llm_response: LLMResponse,
|
||||
) -> AsyncGenerator[Union[None, ProviderRequest], None]:
|
||||
"""处理函数工具调用。
|
||||
|
||||
Returns:
|
||||
AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest,表示需要再次调用 LLM
|
||||
"""
|
||||
# function calling
|
||||
tool_call_result: list[ToolCallMessageSegment] = []
|
||||
logger.info(
|
||||
f"触发 {len(llm_response.tools_call_name)} 个函数调用: {llm_response.tools_call_name}"
|
||||
async def _handle_webchat(
|
||||
self, event: AstrMessageEvent, req: ProviderRequest, prov: Provider
|
||||
):
|
||||
"""处理 WebChat 平台的特殊情况,包括第一次 LLM 对话时总结对话内容生成 title"""
|
||||
conversation = await self.conv_manager.get_conversation(
|
||||
event.unified_msg_origin, req.conversation.cid
|
||||
)
|
||||
for func_tool_name, func_tool_args, func_tool_id in zip(
|
||||
llm_response.tools_call_name,
|
||||
llm_response.tools_call_args,
|
||||
llm_response.tools_call_ids,
|
||||
):
|
||||
try:
|
||||
func_tool = req.func_tool.get_func(func_tool_name)
|
||||
if func_tool.origin == "mcp":
|
||||
logger.info(
|
||||
f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数:{func_tool.name},参数:{func_tool_args}"
|
||||
)
|
||||
client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name]
|
||||
res = await client.session.call_tool(func_tool.name, func_tool_args)
|
||||
if res:
|
||||
# TODO 仅对ImageContent | EmbeddedResource进行了简单的Fallback
|
||||
if isinstance(res.content[0], TextContent):
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=res.content[0].text,
|
||||
)
|
||||
)
|
||||
elif isinstance(res.content[0], ImageContent):
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回了图片(已直接发送给用户)",
|
||||
)
|
||||
)
|
||||
event.set_extra(
|
||||
"tool_call_img_respond",
|
||||
res.content[0].data,
|
||||
)
|
||||
elif isinstance(res.content[0], EmbeddedResource):
|
||||
resource = res.content[0].resource
|
||||
if isinstance(resource, TextResourceContents):
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=resource.text,
|
||||
)
|
||||
)
|
||||
elif (
|
||||
isinstance(resource, BlobResourceContents)
|
||||
and resource.mimeType
|
||||
and resource.mimeType.startswith("image/")
|
||||
):
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回了图片(已直接发送给用户)",
|
||||
)
|
||||
)
|
||||
event.set_extra(
|
||||
"tool_call_img_respond",
|
||||
res.content[0].data,
|
||||
)
|
||||
else:
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content="返回的数据类型不受支持",
|
||||
)
|
||||
)
|
||||
else:
|
||||
# 获取处理器,过滤掉平台不兼容的处理器
|
||||
platform_id = event.get_platform_id()
|
||||
star_md = star_map.get(func_tool.handler_module_path)
|
||||
if (
|
||||
star_md
|
||||
and platform_id in star_md.supported_platforms
|
||||
and not star_md.supported_platforms[platform_id]
|
||||
):
|
||||
logger.debug(
|
||||
f"处理器 {func_tool_name}({star_md.name}) 在当前平台不兼容或者被禁用,跳过执行"
|
||||
)
|
||||
# 直接跳过,不添加任何消息到tool_call_result
|
||||
continue
|
||||
|
||||
logger.info(
|
||||
f"调用工具函数:{func_tool_name},参数:{func_tool_args}"
|
||||
)
|
||||
# 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
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=resp,
|
||||
)
|
||||
)
|
||||
else:
|
||||
res = event.get_result()
|
||||
if res and res.chain:
|
||||
event.set_extra("tool_call_result", res)
|
||||
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())
|
||||
tool_call_result.append(
|
||||
ToolCallMessageSegment(
|
||||
role="tool",
|
||||
tool_call_id=func_tool_id,
|
||||
content=f"error: {str(e)}",
|
||||
)
|
||||
)
|
||||
if tool_call_result:
|
||||
# 函数调用结果
|
||||
req.func_tool = None # 暂时不支持递归工具调用
|
||||
assistant_msg_seg = AssistantMessageSegment(
|
||||
role="assistant", tool_calls=llm_response.to_openai_tool_calls()
|
||||
if conversation and not req.conversation.title:
|
||||
messages = json.loads(conversation.history)
|
||||
latest_pair = messages[-2:]
|
||||
if not latest_pair:
|
||||
return
|
||||
cleaned_text = "User: " + latest_pair[0].get("content", "").strip()
|
||||
logger.debug(f"WebChat 对话标题生成请求,清理后的文本: {cleaned_text}")
|
||||
llm_resp = await prov.text_chat(
|
||||
system_prompt="You are expert in summarizing user's query.",
|
||||
prompt=(
|
||||
f"Please summarize the following query of user:\n"
|
||||
f"{cleaned_text}\n"
|
||||
"Only output the summary within 10 words, DO NOT INCLUDE any other text."
|
||||
"You must use the same language as the user."
|
||||
"If you think the dialog is too short to summarize, only output a special mark: `<None>`"
|
||||
),
|
||||
)
|
||||
# 在多轮 Tool 调用的情况下,这里始终保持最新的 Tool 调用结果,减少上下文长度。
|
||||
req.tool_calls_result = ToolCallsResult(
|
||||
tool_calls_info=assistant_msg_seg,
|
||||
tool_calls_result=tool_call_result,
|
||||
)
|
||||
yield req # 再次执行 LLM 请求
|
||||
else:
|
||||
if llm_response.completion_text:
|
||||
event.set_result(
|
||||
MessageEventResult().message(llm_response.completion_text)
|
||||
if llm_resp and llm_resp.completion_text:
|
||||
logger.debug(
|
||||
f"WebChat 对话标题生成响应: {llm_resp.completion_text.strip()}"
|
||||
)
|
||||
title = llm_resp.completion_text.strip()
|
||||
if not title or "<None>" in title:
|
||||
return
|
||||
await self.conv_manager.update_conversation_title(
|
||||
event.unified_msg_origin, title=title
|
||||
)
|
||||
# 由于 WebChat 平台特殊性,其有两个对话,因此我们要更新两个对话的标题
|
||||
# webchat adapter 中,session_id 的格式是 f"webchat!{username}!{cid}"
|
||||
# TODO: 优化 WebChat 适配器的对话管理
|
||||
if event.session_id:
|
||||
username, cid = event.session_id.split("!")[1:3]
|
||||
db_helper = self.ctx.plugin_manager.context._db
|
||||
db_helper.update_conversation_title(
|
||||
user_id=username,
|
||||
cid=cid,
|
||||
title=title,
|
||||
)
|
||||
|
||||
async def _save_to_history(
|
||||
self, event: AstrMessageEvent, req: ProviderRequest, llm_response: LLMResponse
|
||||
self,
|
||||
event: AstrMessageEvent,
|
||||
req: ProviderRequest,
|
||||
llm_response: LLMResponse | None,
|
||||
):
|
||||
if not req or not req.conversation or not llm_response:
|
||||
if (
|
||||
not req
|
||||
or not req.conversation
|
||||
or not llm_response
|
||||
or llm_response.role != "assistant"
|
||||
):
|
||||
return
|
||||
|
||||
if llm_response.role == "assistant":
|
||||
# 文本回复
|
||||
contexts = req.contexts.copy()
|
||||
contexts.append(await req.assemble_context())
|
||||
# 历史上下文
|
||||
messages = copy.deepcopy(req.contexts)
|
||||
# 这一轮对话请求的用户输入
|
||||
messages.append(await req.assemble_context())
|
||||
# 这一轮对话的 LLM 响应
|
||||
if req.tool_calls_result:
|
||||
if not isinstance(req.tool_calls_result, list):
|
||||
messages.extend(req.tool_calls_result.to_openai_messages())
|
||||
elif isinstance(req.tool_calls_result, list):
|
||||
for tcr in req.tool_calls_result:
|
||||
messages.extend(tcr.to_openai_messages())
|
||||
messages.append({"role": "assistant", "content": llm_response.completion_text})
|
||||
messages = list(filter(lambda item: "_no_save" not in item, messages))
|
||||
await self.conv_manager.update_conversation(
|
||||
event.unified_msg_origin, req.conversation.cid, history=messages
|
||||
)
|
||||
|
||||
# 记录并标记函数调用结果
|
||||
if req.tool_calls_result:
|
||||
tool_calls_messages = req.tool_calls_result.to_openai_messages()
|
||||
|
||||
# 添加标记
|
||||
for message in tool_calls_messages:
|
||||
message["_tool_call_history"] = True
|
||||
|
||||
processed_tool_messages = self._process_tool_message_pairs(
|
||||
tool_calls_messages, remove_tags=False
|
||||
)
|
||||
|
||||
contexts.extend(processed_tool_messages)
|
||||
|
||||
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
|
||||
)
|
||||
|
||||
def _process_tool_message_pairs(self, messages, remove_tags=True):
|
||||
"""处理工具调用消息,确保assistant和tool消息成对出现
|
||||
|
||||
Args:
|
||||
messages (list): 消息列表
|
||||
remove_tags (bool): 是否移除_tool_call_history标记
|
||||
|
||||
Returns:
|
||||
list: 处理后的消息列表,保证了assistant和对应tool消息的成对出现
|
||||
"""
|
||||
result = []
|
||||
i = 0
|
||||
|
||||
while i < len(messages):
|
||||
current_msg = messages[i]
|
||||
|
||||
# 普通消息直接添加
|
||||
if "_tool_call_history" not in current_msg:
|
||||
result.append(current_msg.copy() if remove_tags else current_msg)
|
||||
i += 1
|
||||
continue
|
||||
|
||||
# 工具调用消息成对处理
|
||||
if current_msg.get("role") == "assistant" and "tool_calls" in current_msg:
|
||||
assistant_msg = current_msg.copy()
|
||||
|
||||
if remove_tags and "_tool_call_history" in assistant_msg:
|
||||
del assistant_msg["_tool_call_history"]
|
||||
|
||||
related_tools = []
|
||||
j = i + 1
|
||||
while (
|
||||
j < len(messages)
|
||||
and messages[j].get("role") == "tool"
|
||||
and "_tool_call_history" in messages[j]
|
||||
):
|
||||
tool_msg = messages[j].copy()
|
||||
|
||||
if remove_tags:
|
||||
del tool_msg["_tool_call_history"]
|
||||
|
||||
related_tools.append(tool_msg)
|
||||
j += 1
|
||||
|
||||
# 成对的时候添加到结果
|
||||
if related_tools:
|
||||
result.append(assistant_msg)
|
||||
result.extend(related_tools)
|
||||
|
||||
i = j # 跳过已处理
|
||||
def fix_messages(self, messages: list[dict]) -> list[dict]:
|
||||
"""验证并且修复上下文"""
|
||||
fixed_messages = []
|
||||
for message in messages:
|
||||
if message.get("role") == "tool":
|
||||
# tool block 前面必须要有 user 和 assistant block
|
||||
if len(fixed_messages) < 2:
|
||||
# 这种情况可能是上下文被截断导致的
|
||||
# 我们直接将之前的上下文都清空
|
||||
fixed_messages = []
|
||||
else:
|
||||
fixed_messages.append(message)
|
||||
else:
|
||||
# 单独的tool消息
|
||||
i += 1
|
||||
|
||||
return result
|
||||
fixed_messages.append(message)
|
||||
return fixed_messages
|
||||
|
||||
@@ -50,7 +50,7 @@ class StarRequestSubStage(Stage):
|
||||
logger.debug(
|
||||
f"plugin -> {star_map.get(handler.handler_module_path).name} - {handler.handler_name}"
|
||||
)
|
||||
wrapper = self._call_handler(self.ctx, event, handler.handler, **params)
|
||||
wrapper = self.ctx.call_handler(event, handler.handler, **params)
|
||||
async for ret in wrapper:
|
||||
yield ret
|
||||
event.clear_result() # 清除上一个 handler 的结果
|
||||
|
||||
@@ -13,6 +13,7 @@ from astrbot.core.message.message_event_result import BaseMessageComponent
|
||||
from astrbot.core.star.star_handler import star_handlers_registry, EventType
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.utils.path_util import path_Mapping
|
||||
from astrbot.core.utils.session_lock import session_lock_manager
|
||||
|
||||
|
||||
@register_stage
|
||||
@@ -29,11 +30,10 @@ class RespondStage(Stage):
|
||||
Comp.Image: lambda comp: bool(comp.file), # 图片
|
||||
Comp.Reply: lambda comp: bool(comp.id) and comp.sender_id is not None, # 回复
|
||||
Comp.Poke: lambda comp: comp.id != 0 and comp.qq != 0, # 戳一戳
|
||||
Comp.Node: lambda comp: bool(comp.name)
|
||||
and comp.uin != 0
|
||||
and bool(comp.content), # 一个转发节点
|
||||
Comp.Node: lambda comp: bool(comp.content), # 转发节点
|
||||
Comp.Nodes: lambda comp: bool(comp.nodes), # 多个转发节点
|
||||
Comp.File: lambda comp: bool(comp.file_ or comp.url),
|
||||
Comp.WechatEmoji: lambda comp: comp.md5 is not None, # 微信表情
|
||||
}
|
||||
|
||||
async def initialize(self, ctx: PipelineContext):
|
||||
@@ -129,9 +129,7 @@ class RespondStage(Stage):
|
||||
"streaming_segmented", False
|
||||
)
|
||||
logger.info(f"应用流式输出({event.get_platform_name()})")
|
||||
await event._pre_send()
|
||||
await event.send_streaming(result.async_stream, use_fallback)
|
||||
await event._post_send()
|
||||
return
|
||||
elif len(result.chain) > 0:
|
||||
# 检查路径映射
|
||||
@@ -142,8 +140,6 @@ class RespondStage(Stage):
|
||||
component.file = path_Mapping(mappings, component.file)
|
||||
event.get_result().chain[idx] = component
|
||||
|
||||
await event._pre_send()
|
||||
|
||||
# 检查消息链是否为空
|
||||
try:
|
||||
if await self._is_empty_message_chain(result.chain):
|
||||
@@ -159,9 +155,14 @@ class RespondStage(Stage):
|
||||
c for c in result.chain if not isinstance(c, Comp.Record)
|
||||
]
|
||||
|
||||
if self.enable_seg and (
|
||||
(self.only_llm_result and result.is_llm_result())
|
||||
or not self.only_llm_result
|
||||
if (
|
||||
self.enable_seg
|
||||
and (
|
||||
(self.only_llm_result and result.is_llm_result())
|
||||
or not self.only_llm_result
|
||||
)
|
||||
and event.get_platform_name()
|
||||
not in ["qq_official", "weixin_official_account", "dingtalk"]
|
||||
):
|
||||
decorated_comps = []
|
||||
if self.reply_with_mention:
|
||||
@@ -177,24 +178,26 @@ class RespondStage(Stage):
|
||||
result.chain.remove(comp)
|
||||
break
|
||||
|
||||
for rcomp in record_comps:
|
||||
i = await self._calc_comp_interval(rcomp)
|
||||
await asyncio.sleep(i)
|
||||
try:
|
||||
await event.send(MessageChain([rcomp]))
|
||||
except Exception as e:
|
||||
logger.error(f"发送消息失败: {e} chain: {result.chain}")
|
||||
break
|
||||
|
||||
# 分段回复
|
||||
for comp in non_record_comps:
|
||||
i = await self._calc_comp_interval(comp)
|
||||
await asyncio.sleep(i)
|
||||
try:
|
||||
await event.send(MessageChain([*decorated_comps, comp]))
|
||||
except Exception as e:
|
||||
logger.error(f"发送消息失败: {e} chain: {result.chain}")
|
||||
break
|
||||
# leverage lock to guarentee the order of message sending among different events
|
||||
async with session_lock_manager.acquire_lock(event.unified_msg_origin):
|
||||
for rcomp in record_comps:
|
||||
i = await self._calc_comp_interval(rcomp)
|
||||
await asyncio.sleep(i)
|
||||
try:
|
||||
await event.send(MessageChain([rcomp]))
|
||||
except Exception as e:
|
||||
logger.error(f"发送消息失败: {e} chain: {result.chain}")
|
||||
break
|
||||
# 分段回复
|
||||
for comp in non_record_comps:
|
||||
i = await self._calc_comp_interval(comp)
|
||||
await asyncio.sleep(i)
|
||||
try:
|
||||
await event.send(MessageChain([*decorated_comps, comp]))
|
||||
decorated_comps = [] # 清空已发送的装饰组件
|
||||
except Exception as e:
|
||||
logger.error(f"发送消息失败: {e} chain: {result.chain}")
|
||||
break
|
||||
else:
|
||||
for rcomp in record_comps:
|
||||
try:
|
||||
@@ -208,7 +211,6 @@ class RespondStage(Stage):
|
||||
logger.error(traceback.format_exc())
|
||||
logger.error(f"发送消息失败: {e} chain: {result.chain}")
|
||||
|
||||
await event._post_send()
|
||||
logger.info(
|
||||
f"AstrBot -> {event.get_sender_name()}/{event.get_sender_id()}: {event._outline_chain(result.chain)}"
|
||||
)
|
||||
|
||||
@@ -1,17 +1,19 @@
|
||||
import time
|
||||
import re
|
||||
import time
|
||||
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 typing import AsyncGenerator, Union
|
||||
|
||||
from astrbot.core import file_token_service, html_renderer, logger
|
||||
from astrbot.core.message.components import At, File, Image, Node, Plain, Record, Reply
|
||||
from astrbot.core.message.message_event_result import ResultContentType
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.platform.message_type import MessageType
|
||||
from astrbot.core 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
|
||||
from astrbot.core.star.session_llm_manager import SessionServiceManager
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.star.star_handler import EventType, star_handlers_registry
|
||||
|
||||
from ..context import PipelineContext
|
||||
from ..stage import Stage, register_stage, registered_stages
|
||||
|
||||
|
||||
@register_stage
|
||||
@@ -140,7 +142,11 @@ class ResultDecorateStage(Stage):
|
||||
break
|
||||
|
||||
# 分段回复
|
||||
if self.enable_segmented_reply:
|
||||
if self.enable_segmented_reply and event.get_platform_name() not in [
|
||||
"qq_official",
|
||||
"weixin_official_account",
|
||||
"dingtalk",
|
||||
]:
|
||||
if (
|
||||
self.only_llm_result and result.is_llm_result()
|
||||
) or not self.only_llm_result:
|
||||
@@ -168,30 +174,57 @@ class ResultDecorateStage(Stage):
|
||||
result.chain = new_chain
|
||||
|
||||
# TTS
|
||||
tts_provider = self.ctx.plugin_manager.context.get_using_tts_provider(
|
||||
event.unified_msg_origin
|
||||
)
|
||||
|
||||
if (
|
||||
self.ctx.astrbot_config["provider_tts_settings"]["enable"]
|
||||
and result.is_llm_result()
|
||||
and tts_provider
|
||||
and SessionServiceManager.should_process_tts_request(event)
|
||||
):
|
||||
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)
|
||||
logger.info(f"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)
|
||||
)
|
||||
if(self.ctx.astrbot_config["provider_tts_settings"]["dual_output"]):
|
||||
new_chain.append(comp)
|
||||
else:
|
||||
logger.info(f"TTS 结果: {audio_path}")
|
||||
if not audio_path:
|
||||
logger.error(
|
||||
f"由于 TTS 音频文件没找到,消息段转语音失败: {comp.text}"
|
||||
f"由于 TTS 音频文件未找到,消息段转语音失败: {comp.text}"
|
||||
)
|
||||
new_chain.append(comp)
|
||||
except BaseException:
|
||||
continue
|
||||
|
||||
use_file_service = self.ctx.astrbot_config[
|
||||
"provider_tts_settings"
|
||||
]["use_file_service"]
|
||||
callback_api_base = self.ctx.astrbot_config[
|
||||
"callback_api_base"
|
||||
]
|
||||
dual_output = self.ctx.astrbot_config[
|
||||
"provider_tts_settings"
|
||||
]["dual_output"]
|
||||
|
||||
url = None
|
||||
if use_file_service and callback_api_base:
|
||||
token = await file_token_service.register_file(
|
||||
audio_path
|
||||
)
|
||||
url = f"{callback_api_base}/api/file/{token}"
|
||||
logger.debug(f"已注册:{url}")
|
||||
|
||||
new_chain.append(
|
||||
Record(
|
||||
file=url or audio_path,
|
||||
url=url or audio_path,
|
||||
)
|
||||
)
|
||||
if dual_output:
|
||||
new_chain.append(comp)
|
||||
except Exception:
|
||||
logger.error(traceback.format_exc())
|
||||
logger.error("TTS 失败,使用文本发送。")
|
||||
new_chain.append(comp)
|
||||
@@ -225,6 +258,14 @@ class ResultDecorateStage(Stage):
|
||||
if url:
|
||||
if url.startswith("http"):
|
||||
result.chain = [Image.fromURL(url)]
|
||||
elif (
|
||||
self.ctx.astrbot_config["t2i_use_file_service"]
|
||||
and self.ctx.astrbot_config["callback_api_base"]
|
||||
):
|
||||
token = await file_token_service.register_file(url)
|
||||
url = f"{self.ctx.astrbot_config['callback_api_base']}/api/file/{token}"
|
||||
logger.debug(f"已注册:{url}")
|
||||
result.chain = [Image.fromURL(url)]
|
||||
else:
|
||||
result.chain = [Image.fromFileSystem(url)]
|
||||
|
||||
|
||||
@@ -73,7 +73,7 @@ class PipelineScheduler:
|
||||
await self._process_stages(event)
|
||||
|
||||
# 如果没有发送操作, 则发送一个空消息, 以便于后续的处理
|
||||
if not event._has_send_oper and event.get_platform_name() == "webchat":
|
||||
if event.get_platform_name() == "webchat":
|
||||
await event.send(None)
|
||||
|
||||
logger.debug("pipeline 执行完毕。")
|
||||
|
||||
22
astrbot/core/pipeline/session_status_check/stage.py
Normal file
22
astrbot/core/pipeline/session_status_check/stage.py
Normal file
@@ -0,0 +1,22 @@
|
||||
from ..stage import Stage, register_stage
|
||||
from ..context import PipelineContext
|
||||
from typing import AsyncGenerator, Union
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.star.session_llm_manager import SessionServiceManager
|
||||
from astrbot.core import logger
|
||||
|
||||
|
||||
@register_stage
|
||||
class SessionStatusCheckStage(Stage):
|
||||
"""检查会话是否整体启用"""
|
||||
|
||||
async def initialize(self, ctx: PipelineContext) -> None:
|
||||
pass
|
||||
|
||||
async def process(
|
||||
self, event: AstrMessageEvent
|
||||
) -> Union[None, AsyncGenerator[None, None]]:
|
||||
# 检查会话是否整体启用
|
||||
if not SessionServiceManager.is_session_enabled(event.unified_msg_origin):
|
||||
logger.debug(f"会话 {event.unified_msg_origin} 已被关闭,已终止事件传播。")
|
||||
event.stop_event()
|
||||
@@ -1,12 +1,8 @@
|
||||
from __future__ import annotations
|
||||
import abc
|
||||
import inspect
|
||||
import traceback
|
||||
from astrbot.api import logger
|
||||
from typing import List, AsyncGenerator, Union, Awaitable
|
||||
from typing import List, AsyncGenerator, Union
|
||||
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
|
||||
|
||||
@@ -41,70 +37,3 @@ class Stage(abc.ABC):
|
||||
Union[None, AsyncGenerator[None, None]]: 处理结果,可能是 None 或者异步生成器, 如果为 None 则表示不需要继续处理, 如果为异步生成器则表示需要继续处理(进入下一个阶段)
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def _call_handler(
|
||||
self,
|
||||
ctx: PipelineContext,
|
||||
event: AstrMessageEvent,
|
||||
handler: Awaitable,
|
||||
*args,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator[None, None]:
|
||||
"""执行事件处理函数并处理其返回结果
|
||||
|
||||
该方法负责调用处理函数并处理不同类型的返回值。它支持两种类型的处理函数:
|
||||
1. 异步生成器: 实现洋葱模型,每次yield都会将控制权交回上层
|
||||
2. 协程: 执行一次并处理返回值
|
||||
|
||||
Args:
|
||||
ctx (PipelineContext): 消息管道上下文对象
|
||||
event (AstrMessageEvent): 待处理的事件对象
|
||||
handler (Awaitable): 事件处理函数
|
||||
*args: 传递给handler的位置参数
|
||||
**kwargs: 传递给handler的关键字参数
|
||||
|
||||
Returns:
|
||||
AsyncGenerator[None, None]: 异步生成器,用于在管道中传递控制流
|
||||
"""
|
||||
ready_to_call = None # 一个协程或者异步生成器(async def)
|
||||
|
||||
trace_ = None
|
||||
|
||||
try:
|
||||
ready_to_call = handler(event, *args, **kwargs)
|
||||
except TypeError as _:
|
||||
# 向下兼容
|
||||
trace_ = traceback.format_exc()
|
||||
# 以前的handler会额外传入一个参数, 但是context对象实际上在插件实例中有一份
|
||||
ready_to_call = handler(event, ctx.plugin_manager.context, *args, **kwargs)
|
||||
|
||||
if isinstance(ready_to_call, AsyncGenerator):
|
||||
# 如果是一个异步生成器, 进入洋葱模型
|
||||
_has_yielded = False # 是否返回过值
|
||||
try:
|
||||
async for ret in ready_to_call:
|
||||
# 这里逐步执行异步生成器, 对于每个yield返回的ret, 执行下面的代码
|
||||
# 返回值只能是 MessageEventResult 或者 None(无返回值)
|
||||
_has_yielded = True
|
||||
if isinstance(ret, (MessageEventResult, CommandResult)):
|
||||
# 如果返回值是 MessageEventResult, 设置结果并继续
|
||||
event.set_result(ret)
|
||||
yield # 传递控制权给上一层的process函数
|
||||
else:
|
||||
# 如果返回值是 None, 则不设置结果并继续
|
||||
# 继续执行后续阶段
|
||||
yield ret # 传递控制权给上一层的process函数
|
||||
if not _has_yielded:
|
||||
# 如果这个异步生成器没有执行到yield分支
|
||||
yield
|
||||
except Exception as e:
|
||||
logger.error(f"Previous Error: {trace_}")
|
||||
raise e
|
||||
elif inspect.iscoroutine(ready_to_call):
|
||||
# 如果只是一个协程, 直接执行
|
||||
ret = await ready_to_call
|
||||
if isinstance(ret, (MessageEventResult, CommandResult)):
|
||||
event.set_result(ret)
|
||||
yield # 传递控制权给上一层的process函数
|
||||
else:
|
||||
yield ret # 传递控制权给上一层的process函数
|
||||
|
||||
@@ -1,13 +1,16 @@
|
||||
from ..stage import Stage, register_stage
|
||||
from ..context import PipelineContext
|
||||
from typing import AsyncGenerator, Union
|
||||
|
||||
from astrbot import logger
|
||||
from typing import Union, AsyncGenerator
|
||||
from astrbot.core.message.components import At, AtAll, Reply
|
||||
from astrbot.core.message.message_event_result import MessageChain, MessageEventResult
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.message.message_event_result import MessageEventResult, MessageChain
|
||||
from astrbot.core.message.components import At
|
||||
from astrbot.core.star.star_handler import star_handlers_registry, EventType
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.star.filter.permission import PermissionTypeFilter
|
||||
from astrbot.core.star.session_plugin_manager import SessionPluginManager
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.star.star_handler import EventType, star_handlers_registry
|
||||
|
||||
from ..context import PipelineContext
|
||||
from ..stage import Stage, register_stage
|
||||
|
||||
|
||||
@register_stage
|
||||
@@ -39,6 +42,9 @@ class WakingCheckStage(Stage):
|
||||
self.ignore_bot_self_message = self.ctx.astrbot_config["platform_settings"].get(
|
||||
"ignore_bot_self_message", False
|
||||
)
|
||||
self.ignore_at_all = self.ctx.astrbot_config["platform_settings"].get(
|
||||
"ignore_at_all", False
|
||||
)
|
||||
|
||||
async def process(
|
||||
self, event: AstrMessageEvent
|
||||
@@ -77,11 +83,18 @@ class WakingCheckStage(Stage):
|
||||
event.message_str = event.message_str[len(wake_prefix) :].strip()
|
||||
break
|
||||
if not is_wake:
|
||||
# 检查是否有 at 消息
|
||||
# 检查是否有at消息 / at全体成员消息 / 引用了bot的消息
|
||||
for message in messages:
|
||||
if isinstance(message, At) and (
|
||||
str(message.qq) == str(event.get_self_id())
|
||||
or str(message.qq) == "all"
|
||||
if (
|
||||
(
|
||||
isinstance(message, At)
|
||||
and (str(message.qq) == str(event.get_self_id()))
|
||||
)
|
||||
or (isinstance(message, AtAll) and not self.ignore_at_all)
|
||||
or (
|
||||
isinstance(message, Reply)
|
||||
and str(message.sender_id) == str(event.get_self_id())
|
||||
)
|
||||
):
|
||||
is_wake = True
|
||||
event.is_wake = True
|
||||
@@ -125,7 +138,6 @@ class WakingCheckStage(Stage):
|
||||
f"插件 {star_map[handler.handler_module_path].name}: {e}"
|
||||
)
|
||||
)
|
||||
await event._post_send()
|
||||
event.stop_event()
|
||||
passed = False
|
||||
break
|
||||
@@ -140,7 +152,6 @@ class WakingCheckStage(Stage):
|
||||
f"您(ID: {event.get_sender_id()})的权限不足以使用此指令。通过 /sid 获取 ID 并请管理员添加。"
|
||||
)
|
||||
)
|
||||
await event._post_send()
|
||||
logger.info(
|
||||
f"触发 {star_map[handler.handler_module_path].name} 时, 用户(ID={event.get_sender_id()}) 权限不足。"
|
||||
)
|
||||
@@ -156,7 +167,12 @@ class WakingCheckStage(Stage):
|
||||
"parsed_params"
|
||||
)
|
||||
|
||||
event.clear_extra()
|
||||
event._extras.pop("parsed_params", None)
|
||||
|
||||
# 根据会话配置过滤插件处理器
|
||||
activated_handlers = SessionPluginManager.filter_handlers_by_session(
|
||||
event, activated_handlers
|
||||
)
|
||||
|
||||
event.set_extra("activated_handlers", activated_handlers)
|
||||
event.set_extra("handlers_parsed_params", handlers_parsed_params)
|
||||
|
||||
@@ -227,7 +227,7 @@ class AstrMessageEvent(abc.ABC):
|
||||
):
|
||||
"""发送流式消息到消息平台,使用异步生成器。
|
||||
目前仅支持: telegram,qq official 私聊。
|
||||
Fallback仅支持 aiocqhttp, gewechat。
|
||||
Fallback仅支持 aiocqhttp。
|
||||
"""
|
||||
asyncio.create_task(
|
||||
Metric.upload(msg_event_tick=1, adapter_name=self.platform_meta.name)
|
||||
@@ -235,10 +235,10 @@ class AstrMessageEvent(abc.ABC):
|
||||
self._has_send_oper = True
|
||||
|
||||
async def _pre_send(self):
|
||||
"""调度器会在执行 send() 前调用该方法"""
|
||||
"""调度器会在执行 send() 前调用该方法 deprecated in v3.5.18"""
|
||||
|
||||
async def _post_send(self):
|
||||
"""调度器会在执行 send() 后调用该方法"""
|
||||
"""调度器会在执行 send() 后调用该方法 deprecated in v3.5.18"""
|
||||
|
||||
def set_result(self, result: Union[MessageEventResult, str]):
|
||||
"""设置消息事件的结果。
|
||||
@@ -419,7 +419,6 @@ class AstrMessageEvent(abc.ABC):
|
||||
|
||||
适配情况:
|
||||
|
||||
- gewechat
|
||||
- aiocqhttp(OneBotv11)
|
||||
"""
|
||||
...
|
||||
|
||||
@@ -58,10 +58,6 @@ class PlatformManager:
|
||||
from .sources.qqofficial_webhook.qo_webhook_adapter import (
|
||||
QQOfficialWebhookPlatformAdapter, # noqa: F401
|
||||
)
|
||||
case "gewechat":
|
||||
from .sources.gewechat.gewechat_platform_adapter import (
|
||||
GewechatPlatformAdapter, # noqa: F401
|
||||
)
|
||||
case "wechatpadpro":
|
||||
from .sources.wechatpadpro.wechatpadpro_adapter import (
|
||||
WeChatPadProAdapter, # noqa: F401
|
||||
@@ -77,7 +73,15 @@ class PlatformManager:
|
||||
case "wecom":
|
||||
from .sources.wecom.wecom_adapter import WecomPlatformAdapter # noqa: F401
|
||||
case "weixin_official_account":
|
||||
from .sources.weixin_official_account.weixin_offacc_adapter import WeixinOfficialAccountPlatformAdapter # noqa
|
||||
from .sources.weixin_official_account.weixin_offacc_adapter import (
|
||||
WeixinOfficialAccountPlatformAdapter, # noqa
|
||||
)
|
||||
case "discord":
|
||||
from .sources.discord.discord_platform_adapter import (
|
||||
DiscordPlatformAdapter, # noqa: F401
|
||||
)
|
||||
case "slack":
|
||||
from .sources.slack.slack_adapter import SlackAdapter # noqa: F401
|
||||
except (ImportError, ModuleNotFoundError) as e:
|
||||
logger.error(
|
||||
f"加载平台适配器 {platform_config['type']} 失败,原因:{e}。请检查依赖库是否安装。提示:可以在 管理面板->控制台->安装Pip库 中安装依赖库。"
|
||||
|
||||
@@ -1,11 +1,19 @@
|
||||
import asyncio
|
||||
import re
|
||||
from typing import AsyncGenerator, Dict, List
|
||||
from aiocqhttp import CQHttp
|
||||
from aiocqhttp import CQHttp, Event
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
from astrbot.api.message_components import At, Image, Node, Nodes, Plain, Record, File
|
||||
from astrbot.api.message_components import (
|
||||
Image,
|
||||
Node,
|
||||
Nodes,
|
||||
Plain,
|
||||
Record,
|
||||
Video,
|
||||
File,
|
||||
BaseMessageComponent,
|
||||
)
|
||||
from astrbot.api.platform import Group, MessageMember
|
||||
from astrbot.core import file_token_service, astrbot_config, logger
|
||||
|
||||
|
||||
class AiocqhttpMessageEvent(AstrMessageEvent):
|
||||
@@ -15,88 +23,120 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
|
||||
super().__init__(message_str, message_obj, platform_meta, session_id)
|
||||
self.bot = bot
|
||||
|
||||
@staticmethod
|
||||
async def _from_segment_to_dict(segment: BaseMessageComponent) -> dict:
|
||||
"""修复部分字段"""
|
||||
if isinstance(segment, (Image, Record)):
|
||||
# For Image and Record segments, we convert them to base64
|
||||
bs64 = await segment.convert_to_base64()
|
||||
return {
|
||||
"type": segment.type.lower(),
|
||||
"data": {
|
||||
"file": f"base64://{bs64}",
|
||||
},
|
||||
}
|
||||
elif isinstance(segment, File):
|
||||
# For File segments, we need to handle the file differently
|
||||
d = await segment.to_dict()
|
||||
return d
|
||||
elif isinstance(segment, Video):
|
||||
d = await segment.to_dict()
|
||||
return d
|
||||
else:
|
||||
# For other segments, we simply convert them to a dict by calling toDict
|
||||
return segment.toDict()
|
||||
|
||||
@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"
|
||||
d["data"]["text"] = segment.text.strip()
|
||||
# 如果是空文本或者只带换行符的文本,不发送
|
||||
if not d["data"]["text"]:
|
||||
if not segment.text.strip():
|
||||
continue
|
||||
elif isinstance(segment, (Image, Record)):
|
||||
# convert to base64
|
||||
bs64 = await segment.convert_to_base64()
|
||||
d["data"] = {
|
||||
"file": f"base64://{bs64}",
|
||||
}
|
||||
elif isinstance(segment, At):
|
||||
d["data"] = {
|
||||
"qq": str(segment.qq), # 转换为字符串
|
||||
}
|
||||
d = await AiocqhttpMessageEvent._from_segment_to_dict(segment)
|
||||
ret.append(d)
|
||||
return ret
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
@classmethod
|
||||
async def _dispatch_send(
|
||||
cls,
|
||||
bot: CQHttp,
|
||||
event: Event | None,
|
||||
is_group: bool,
|
||||
session_id: str,
|
||||
messages: list[dict],
|
||||
):
|
||||
if event:
|
||||
await bot.send(event=event, message=messages)
|
||||
elif is_group:
|
||||
await bot.send_group_msg(group_id=session_id, message=messages)
|
||||
else:
|
||||
await bot.send_private_msg(user_id=session_id, message=messages)
|
||||
|
||||
@classmethod
|
||||
async def send_message(
|
||||
cls,
|
||||
bot: CQHttp,
|
||||
message_chain: MessageChain,
|
||||
event: Event | None = None,
|
||||
is_group: bool = False,
|
||||
session_id: str = None,
|
||||
):
|
||||
"""发送消息"""
|
||||
|
||||
# 转发消息、文件消息不能和普通消息混在一起发送
|
||||
send_one_by_one = any(
|
||||
isinstance(seg, (Node, Nodes, File)) for seg in message.chain
|
||||
isinstance(seg, (Node, Nodes, File)) for seg in message_chain.chain
|
||||
)
|
||||
if send_one_by_one:
|
||||
for seg in message.chain:
|
||||
if isinstance(seg, (Node, Nodes)):
|
||||
# 合并转发消息
|
||||
|
||||
if isinstance(seg, Node):
|
||||
nodes = Nodes([seg])
|
||||
seg = nodes
|
||||
|
||||
payload = seg.toDict()
|
||||
if self.get_group_id():
|
||||
payload["group_id"] = self.get_group_id()
|
||||
await self.bot.call_action("send_group_forward_msg", **payload)
|
||||
else:
|
||||
payload["user_id"] = self.get_sender_id()
|
||||
await self.bot.call_action(
|
||||
"send_private_forward_msg", **payload
|
||||
)
|
||||
elif isinstance(seg, File):
|
||||
d = seg.toDict()
|
||||
url_or_path = await seg.get_file(allow_return_url=True)
|
||||
if url_or_path.startswith("http"):
|
||||
payload_file = url_or_path
|
||||
elif callback_host := astrbot_config.get("callback_api_base"):
|
||||
callback_host = str(callback_host).removesuffix("/")
|
||||
token = await file_token_service.register_file(url_or_path)
|
||||
payload_file = f"{callback_host}/api/file/{token}"
|
||||
logger.debug(f"Generated file callback link: {payload_file}")
|
||||
else:
|
||||
payload_file = url_or_path
|
||||
d["data"] = {
|
||||
"name": seg.name,
|
||||
"file": payload_file,
|
||||
}
|
||||
await self.bot.send(
|
||||
self.message_obj.raw_message,
|
||||
[d],
|
||||
)
|
||||
else:
|
||||
await self.bot.send(
|
||||
self.message_obj.raw_message,
|
||||
await AiocqhttpMessageEvent._parse_onebot_json(
|
||||
MessageChain([seg])
|
||||
),
|
||||
)
|
||||
await asyncio.sleep(0.5)
|
||||
else:
|
||||
ret = await AiocqhttpMessageEvent._parse_onebot_json(message)
|
||||
if not send_one_by_one:
|
||||
ret = await cls._parse_onebot_json(message_chain)
|
||||
if not ret:
|
||||
return
|
||||
await self.bot.send(self.message_obj.raw_message, ret)
|
||||
await cls._dispatch_send(bot, event, is_group, session_id, ret)
|
||||
return
|
||||
for seg in message_chain.chain:
|
||||
if isinstance(seg, (Node, Nodes)):
|
||||
# 合并转发消息
|
||||
if isinstance(seg, Node):
|
||||
nodes = Nodes([seg])
|
||||
seg = nodes
|
||||
|
||||
payload = await seg.to_dict()
|
||||
|
||||
if is_group:
|
||||
payload["group_id"] = session_id
|
||||
await bot.call_action("send_group_forward_msg", **payload)
|
||||
else:
|
||||
payload["user_id"] = session_id
|
||||
await bot.call_action("send_private_forward_msg", **payload)
|
||||
elif isinstance(seg, File):
|
||||
d = await cls._from_segment_to_dict(seg)
|
||||
await cls._dispatch_send(bot, event, is_group, session_id, [d])
|
||||
else:
|
||||
messages = await cls._parse_onebot_json(MessageChain([seg]))
|
||||
if not messages:
|
||||
continue
|
||||
await cls._dispatch_send(bot, event, is_group, session_id, messages)
|
||||
await asyncio.sleep(0.5)
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
"""发送消息"""
|
||||
event = self.message_obj.raw_message
|
||||
assert isinstance(event, Event), "Event must be an instance of aiocqhttp.Event"
|
||||
is_group = False
|
||||
if self.get_group_id():
|
||||
is_group = True
|
||||
session_id = self.get_group_id()
|
||||
else:
|
||||
session_id = self.get_sender_id()
|
||||
await self.send_message(
|
||||
bot=self.bot,
|
||||
message_chain=message,
|
||||
event=event,
|
||||
is_group=is_group,
|
||||
session_id=session_id,
|
||||
)
|
||||
await super().send(message)
|
||||
|
||||
async def send_streaming(
|
||||
|
||||
@@ -83,19 +83,18 @@ class AiocqhttpAdapter(Platform):
|
||||
async def send_by_session(
|
||||
self, session: MessageSesion, message_chain: MessageChain
|
||||
):
|
||||
ret = await AiocqhttpMessageEvent._parse_onebot_json(message_chain)
|
||||
match session.message_type.value:
|
||||
case MessageType.GROUP_MESSAGE.value:
|
||||
if "_" in session.session_id:
|
||||
# 独立会话
|
||||
_, group_id = session.session_id.split("_")
|
||||
await self.bot.send_group_msg(group_id=group_id, message=ret)
|
||||
else:
|
||||
await self.bot.send_group_msg(
|
||||
group_id=session.session_id, message=ret
|
||||
)
|
||||
case MessageType.FRIEND_MESSAGE.value:
|
||||
await self.bot.send_private_msg(user_id=session.session_id, message=ret)
|
||||
is_group = session.message_type == MessageType.GROUP_MESSAGE
|
||||
if is_group:
|
||||
session_id = session.session_id.split("_")[-1]
|
||||
else:
|
||||
session_id = session.session_id
|
||||
await AiocqhttpMessageEvent.send_message(
|
||||
bot=self.bot,
|
||||
message_chain=message_chain,
|
||||
event=None, # 这里不需要 event,因为是通过 session 发送的
|
||||
is_group=is_group,
|
||||
session_id=session_id,
|
||||
)
|
||||
await super().send_by_session(session, message_chain)
|
||||
|
||||
async def convert_message(self, event: Event) -> AstrBotMessage:
|
||||
@@ -168,9 +167,7 @@ class AiocqhttpAdapter(Platform):
|
||||
|
||||
if "sub_type" in event:
|
||||
if event["sub_type"] == "poke" and "target_id" in event:
|
||||
abm.message.append(
|
||||
Poke(qq=str(event["target_id"]), type="poke")
|
||||
) # noqa: F405
|
||||
abm.message.append(Poke(qq=str(event["target_id"]), type="poke")) # noqa: F405
|
||||
|
||||
return abm
|
||||
|
||||
@@ -221,6 +218,9 @@ class AiocqhttpAdapter(Platform):
|
||||
a = None
|
||||
if t == "text":
|
||||
current_text = "".join(m["data"]["text"] for m in m_group).strip()
|
||||
if not current_text:
|
||||
# 如果文本段为空,则跳过
|
||||
continue
|
||||
message_str += current_text
|
||||
a = ComponentTypes[t](text=current_text) # noqa: F405
|
||||
abm.message.append(a)
|
||||
@@ -270,8 +270,16 @@ class AiocqhttpAdapter(Platform):
|
||||
action="get_msg",
|
||||
message_id=int(m["data"]["id"]),
|
||||
)
|
||||
# 添加必要的 post_type 字段,防止 Event.from_payload 报错
|
||||
reply_event_data["post_type"] = "message"
|
||||
new_event = Event.from_payload(reply_event_data)
|
||||
if not new_event:
|
||||
logger.error(
|
||||
f"无法从回复消息数据构造 Event 对象: {reply_event_data}"
|
||||
)
|
||||
continue
|
||||
abm_reply = await self._convert_handle_message_event(
|
||||
Event.from_payload(reply_event_data), get_reply=False
|
||||
new_event, get_reply=False
|
||||
)
|
||||
|
||||
reply_seg = Reply(
|
||||
@@ -304,7 +312,9 @@ class AiocqhttpAdapter(Platform):
|
||||
user_id=int(m["data"]["qq"]),
|
||||
)
|
||||
if at_info:
|
||||
nickname = at_info.get("nick", "")
|
||||
nickname = at_info.get("nick", "") or at_info.get(
|
||||
"nickname", ""
|
||||
)
|
||||
is_at_self = str(m["data"]["qq"]) in {abm.self_id, "all"}
|
||||
|
||||
abm.message.append(
|
||||
@@ -319,7 +329,7 @@ class AiocqhttpAdapter(Platform):
|
||||
first_at_self_processed = True
|
||||
else:
|
||||
# 非第一个@机器人或@其他用户,添加到message_str
|
||||
message_str += f" @{nickname} "
|
||||
message_str += f" @{nickname}({m['data']['qq']}) "
|
||||
else:
|
||||
abm.message.append(At(qq=str(m["data"]["qq"]), name=""))
|
||||
except ActionFailed as e:
|
||||
|
||||
@@ -32,30 +32,31 @@ class DingtalkMessageEvent(AstrMessageEvent):
|
||||
)
|
||||
elif isinstance(segment, Comp.Image):
|
||||
markdown_str = ""
|
||||
if segment.file and segment.file.startswith("file:///"):
|
||||
logger.warning(
|
||||
"dingtalk only support url image, not: " + segment.file
|
||||
)
|
||||
continue
|
||||
elif segment.file and segment.file.startswith("http"):
|
||||
markdown_str += f"\n\n"
|
||||
elif segment.file and segment.file.startswith("base64://"):
|
||||
logger.warning("dingtalk only support url image, not base64")
|
||||
continue
|
||||
else:
|
||||
logger.warning(
|
||||
"dingtalk only support url image, not: " + segment.file
|
||||
)
|
||||
continue
|
||||
|
||||
ret = await asyncio.get_event_loop().run_in_executor(
|
||||
None,
|
||||
client.reply_markdown,
|
||||
"😄",
|
||||
markdown_str,
|
||||
self.message_obj.raw_message,
|
||||
)
|
||||
logger.debug(f"send image: {ret}")
|
||||
try:
|
||||
if not segment.file:
|
||||
logger.warning("钉钉图片 segment 缺少 file 字段,跳过")
|
||||
continue
|
||||
if segment.file.startswith(("http://", "https://")):
|
||||
image_url = segment.file
|
||||
else:
|
||||
image_url = await segment.register_to_file_service()
|
||||
|
||||
markdown_str = f"\n\n"
|
||||
|
||||
ret = await asyncio.get_event_loop().run_in_executor(
|
||||
None,
|
||||
client.reply_markdown,
|
||||
"😄",
|
||||
markdown_str,
|
||||
self.message_obj.raw_message,
|
||||
)
|
||||
logger.debug(f"send image: {ret}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"钉钉图片处理失败: {e}")
|
||||
logger.warning(f"跳过图片发送: {image_path}")
|
||||
continue
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
await self.send_with_client(self.client, message)
|
||||
|
||||
126
astrbot/core/platform/sources/discord/client.py
Normal file
126
astrbot/core/platform/sources/discord/client.py
Normal file
@@ -0,0 +1,126 @@
|
||||
import discord
|
||||
from astrbot import logger
|
||||
import sys
|
||||
|
||||
if sys.version_info >= (3, 12):
|
||||
from typing import override
|
||||
else:
|
||||
from typing_extensions import override
|
||||
|
||||
|
||||
# Discord Bot客户端
|
||||
class DiscordBotClient(discord.Bot):
|
||||
"""Discord客户端封装"""
|
||||
|
||||
def __init__(self, token: str, proxy: str = None):
|
||||
self.token = token
|
||||
self.proxy = proxy
|
||||
|
||||
# 设置Intent权限,遵循权限最小化原则
|
||||
intents = discord.Intents.default()
|
||||
intents.message_content = True # 订阅消息内容事件 (Privileged)
|
||||
intents.members = True # 订阅成员事件 (Privileged)
|
||||
|
||||
# 初始化Bot
|
||||
super().__init__(intents=intents, proxy=proxy)
|
||||
|
||||
# 回调函数
|
||||
self.on_message_received = None
|
||||
self.on_ready_once_callback = None
|
||||
self._ready_once_fired = False
|
||||
|
||||
@override
|
||||
async def on_ready(self):
|
||||
"""当机器人成功连接并准备就绪时触发"""
|
||||
logger.info(f"[Discord] 已作为 {self.user} (ID: {self.user.id}) 登录")
|
||||
logger.info("[Discord] 客户端已准备就绪。")
|
||||
|
||||
if self.on_ready_once_callback and not self._ready_once_fired:
|
||||
self._ready_once_fired = True
|
||||
try:
|
||||
await self.on_ready_once_callback()
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"[Discord] on_ready_once_callback 执行失败: {e}", exc_info=True
|
||||
)
|
||||
|
||||
def _create_message_data(self, message: discord.Message) -> dict:
|
||||
"""从 discord.Message 创建数据字典"""
|
||||
is_mentioned = self.user in message.mentions
|
||||
return {
|
||||
"message": message,
|
||||
"bot_id": str(self.user.id),
|
||||
"content": message.content,
|
||||
"username": message.author.display_name,
|
||||
"userid": str(message.author.id),
|
||||
"message_id": str(message.id),
|
||||
"channel_id": str(message.channel.id),
|
||||
"guild_id": str(message.guild.id) if message.guild else None,
|
||||
"type": "message",
|
||||
"is_mentioned": is_mentioned,
|
||||
"clean_content": message.clean_content,
|
||||
}
|
||||
|
||||
def _create_interaction_data(self, interaction: discord.Interaction) -> dict:
|
||||
"""从 discord.Interaction 创建数据字典"""
|
||||
return {
|
||||
"interaction": interaction,
|
||||
"bot_id": str(self.user.id),
|
||||
"content": self._extract_interaction_content(interaction),
|
||||
"username": interaction.user.display_name,
|
||||
"userid": str(interaction.user.id),
|
||||
"message_id": str(interaction.id),
|
||||
"channel_id": str(interaction.channel_id)
|
||||
if interaction.channel_id
|
||||
else None,
|
||||
"guild_id": str(interaction.guild_id) if interaction.guild_id else None,
|
||||
"type": "interaction",
|
||||
}
|
||||
|
||||
@override
|
||||
async def on_message(self, message: discord.Message):
|
||||
"""当接收到消息时触发"""
|
||||
if message.author.bot:
|
||||
return
|
||||
|
||||
logger.debug(
|
||||
f"[Discord] 收到原始消息 from {message.author.name}: {message.content}"
|
||||
)
|
||||
|
||||
if self.on_message_received:
|
||||
message_data = self._create_message_data(message)
|
||||
await self.on_message_received(message_data)
|
||||
|
||||
def _extract_interaction_content(self, interaction: discord.Interaction) -> str:
|
||||
"""从交互中提取内容"""
|
||||
interaction_type = interaction.type
|
||||
interaction_data = getattr(interaction, "data", {})
|
||||
|
||||
if not interaction_data:
|
||||
return ""
|
||||
|
||||
if interaction_type == discord.InteractionType.application_command:
|
||||
command_name = interaction_data.get("name", "")
|
||||
if options := interaction_data.get("options", []):
|
||||
params = " ".join(
|
||||
[f"{opt['name']}:{opt.get('value', '')}" for opt in options]
|
||||
)
|
||||
return f"/{command_name} {params}"
|
||||
return f"/{command_name}"
|
||||
|
||||
elif interaction_type == discord.InteractionType.component:
|
||||
custom_id = interaction_data.get("custom_id", "")
|
||||
component_type = interaction_data.get("component_type", "")
|
||||
return f"component:{custom_id}:{component_type}"
|
||||
|
||||
return str(interaction_data)
|
||||
|
||||
async def start_polling(self):
|
||||
"""开始轮询消息,这是个阻塞方法"""
|
||||
await self.start(self.token)
|
||||
|
||||
@override
|
||||
async def close(self):
|
||||
"""关闭客户端"""
|
||||
if not self.is_closed():
|
||||
await super().close()
|
||||
135
astrbot/core/platform/sources/discord/components.py
Normal file
135
astrbot/core/platform/sources/discord/components.py
Normal file
@@ -0,0 +1,135 @@
|
||||
import discord
|
||||
from typing import List
|
||||
from astrbot.api.message_components import BaseMessageComponent
|
||||
|
||||
|
||||
# Discord专用组件
|
||||
class DiscordEmbed(BaseMessageComponent):
|
||||
"""Discord Embed消息组件"""
|
||||
|
||||
type: str = "discord_embed"
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
title: str = None,
|
||||
description: str = None,
|
||||
color: int = None,
|
||||
url: str = None,
|
||||
thumbnail: str = None,
|
||||
image: str = None,
|
||||
footer: str = None,
|
||||
fields: List[dict] = None,
|
||||
):
|
||||
self.title = title
|
||||
self.description = description
|
||||
self.color = color
|
||||
self.url = url
|
||||
self.thumbnail = thumbnail
|
||||
self.image = image
|
||||
self.footer = footer
|
||||
self.fields = fields or []
|
||||
|
||||
def to_discord_embed(self) -> discord.Embed:
|
||||
"""转换为Discord Embed对象"""
|
||||
embed = discord.Embed()
|
||||
|
||||
if self.title:
|
||||
embed.title = self.title
|
||||
if self.description:
|
||||
embed.description = self.description
|
||||
if self.color:
|
||||
embed.color = self.color
|
||||
if self.url:
|
||||
embed.url = self.url
|
||||
if self.thumbnail:
|
||||
embed.set_thumbnail(url=self.thumbnail)
|
||||
if self.image:
|
||||
embed.set_image(url=self.image)
|
||||
if self.footer:
|
||||
embed.set_footer(text=self.footer)
|
||||
|
||||
for field in self.fields:
|
||||
embed.add_field(
|
||||
name=field.get("name", ""),
|
||||
value=field.get("value", ""),
|
||||
inline=field.get("inline", False),
|
||||
)
|
||||
|
||||
return embed
|
||||
|
||||
|
||||
class DiscordButton(BaseMessageComponent):
|
||||
"""Discord按钮组件"""
|
||||
|
||||
type: str = "discord_button"
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
label: str,
|
||||
custom_id: str = None,
|
||||
style: str = "primary",
|
||||
emoji: str = None,
|
||||
url: str = None,
|
||||
disabled: bool = False,
|
||||
):
|
||||
self.label = label
|
||||
self.custom_id = custom_id
|
||||
self.style = style
|
||||
self.emoji = emoji
|
||||
self.url = url
|
||||
self.disabled = disabled
|
||||
|
||||
|
||||
class DiscordReference(BaseMessageComponent):
|
||||
"""Discord引用组件"""
|
||||
|
||||
type: str = "discord_reference"
|
||||
|
||||
def __init__(self, message_id: str, channel_id: str):
|
||||
self.message_id = message_id
|
||||
self.channel_id = channel_id
|
||||
|
||||
|
||||
class DiscordView(BaseMessageComponent):
|
||||
"""Discord视图组件,包含按钮和选择菜单"""
|
||||
|
||||
type: str = "discord_view"
|
||||
|
||||
def __init__(
|
||||
self, components: List[BaseMessageComponent] = None, timeout: float = None
|
||||
):
|
||||
self.components = components or []
|
||||
self.timeout = timeout
|
||||
|
||||
def to_discord_view(self) -> discord.ui.View:
|
||||
"""转换为Discord View对象"""
|
||||
view = discord.ui.View(timeout=self.timeout)
|
||||
|
||||
for component in self.components:
|
||||
if isinstance(component, DiscordButton):
|
||||
button_style = getattr(
|
||||
discord.ButtonStyle, component.style, discord.ButtonStyle.primary
|
||||
)
|
||||
|
||||
if component.url:
|
||||
# URL按钮
|
||||
button = discord.ui.Button(
|
||||
label=component.label,
|
||||
style=discord.ButtonStyle.link,
|
||||
url=component.url,
|
||||
emoji=component.emoji,
|
||||
disabled=component.disabled,
|
||||
)
|
||||
else:
|
||||
# 普通按钮
|
||||
button = discord.ui.Button(
|
||||
label=component.label,
|
||||
style=button_style,
|
||||
custom_id=component.custom_id,
|
||||
emoji=component.emoji,
|
||||
disabled=component.disabled,
|
||||
)
|
||||
|
||||
view.add_item(button)
|
||||
|
||||
return view
|
||||
@@ -0,0 +1,455 @@
|
||||
import asyncio
|
||||
import discord
|
||||
import sys
|
||||
import re
|
||||
from discord.abc import Messageable
|
||||
from discord.channel import DMChannel
|
||||
from astrbot.api.platform import (
|
||||
Platform,
|
||||
AstrBotMessage,
|
||||
MessageMember,
|
||||
PlatformMetadata,
|
||||
MessageType,
|
||||
)
|
||||
from astrbot.api.event import MessageChain
|
||||
from astrbot.api.message_components import Plain, Image, File
|
||||
from astrbot.core.platform.astr_message_event import MessageSesion
|
||||
from astrbot.api.platform import register_platform_adapter
|
||||
from astrbot import logger
|
||||
from .client import DiscordBotClient
|
||||
from .discord_platform_event import DiscordPlatformEvent
|
||||
|
||||
from typing import Any, Tuple
|
||||
from astrbot.core.star.filter.command import CommandFilter
|
||||
from astrbot.core.star.filter.command_group import CommandGroupFilter
|
||||
from astrbot.core.star.star import star_map
|
||||
from astrbot.core.star.star_handler import StarHandlerMetadata, star_handlers_registry
|
||||
|
||||
if sys.version_info >= (3, 12):
|
||||
from typing import override
|
||||
else:
|
||||
from typing_extensions import override
|
||||
|
||||
|
||||
# 注册平台适配器
|
||||
@register_platform_adapter("discord", "Discord 适配器 (基于 Pycord)")
|
||||
class DiscordPlatformAdapter(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.client_self_id = None
|
||||
self.registered_handlers = []
|
||||
# 指令注册相关
|
||||
self.enable_command_register = self.config.get("discord_command_register", True)
|
||||
self.guild_id = self.config.get("discord_guild_id_for_debug", None)
|
||||
self.activity_name = self.config.get("discord_activity_name", None)
|
||||
self.shutdown_event = asyncio.Event()
|
||||
self._polling_task = None
|
||||
|
||||
@override
|
||||
async def send_by_session(
|
||||
self, session: MessageSesion, message_chain: MessageChain
|
||||
):
|
||||
"""通过会话发送消息"""
|
||||
# 创建一个 message_obj 以便在 event 中使用
|
||||
message_obj = AstrBotMessage()
|
||||
if "_" in session.session_id:
|
||||
session.session_id = session.session_id.split("_")[1]
|
||||
channel_id_str = session.session_id
|
||||
channel = None
|
||||
try:
|
||||
channel_id = int(channel_id_str)
|
||||
channel = self.client.get_channel(channel_id)
|
||||
except (ValueError, TypeError):
|
||||
logger.warning(f"[Discord] Invalid channel ID format: {channel_id_str}")
|
||||
|
||||
if channel:
|
||||
message_obj.type = self._get_message_type(channel)
|
||||
message_obj.group_id = self._get_channel_id(channel)
|
||||
else:
|
||||
logger.warning(
|
||||
f"[Discord] Can't get channel info for {channel_id_str}, will guess message type."
|
||||
)
|
||||
message_obj.type = MessageType.GROUP_MESSAGE
|
||||
message_obj.group_id = session.session_id
|
||||
|
||||
message_obj.message_str = message_chain.get_plain_text()
|
||||
message_obj.sender = MessageMember(
|
||||
user_id=str(self.client_self_id), nickname=self.client.user.display_name
|
||||
)
|
||||
message_obj.self_id = self.client_self_id
|
||||
message_obj.session_id = session.session_id
|
||||
message_obj.message = message_chain
|
||||
|
||||
# 创建临时事件对象来发送消息
|
||||
temp_event = DiscordPlatformEvent(
|
||||
message_str=message_chain.get_plain_text(),
|
||||
message_obj=message_obj,
|
||||
platform_meta=self.meta(),
|
||||
session_id=session.session_id,
|
||||
client=self.client,
|
||||
)
|
||||
await temp_event.send(message_chain)
|
||||
await super().send_by_session(session, message_chain)
|
||||
|
||||
@override
|
||||
def meta(self) -> PlatformMetadata:
|
||||
"""返回平台元数据"""
|
||||
return PlatformMetadata(
|
||||
"discord",
|
||||
"Discord 适配器",
|
||||
id=self.config.get("id"),
|
||||
default_config_tmpl=self.config,
|
||||
)
|
||||
|
||||
@override
|
||||
async def run(self):
|
||||
"""主要运行逻辑"""
|
||||
|
||||
# 初始化回调函数
|
||||
async def on_received(message_data):
|
||||
logger.debug(f"[Discord] 收到消息: {message_data}")
|
||||
if self.client_self_id is None:
|
||||
self.client_self_id = message_data.get("bot_id")
|
||||
abm = await self.convert_message(data=message_data)
|
||||
await self.handle_msg(abm)
|
||||
|
||||
# 初始化 Discord 客户端
|
||||
token = str(self.config.get("discord_token"))
|
||||
if not token:
|
||||
logger.error("[Discord] Bot Token 未配置。请在配置文件中正确设置 token。")
|
||||
return
|
||||
|
||||
proxy = self.config.get("discord_proxy") or None
|
||||
self.client = DiscordBotClient(token, proxy)
|
||||
self.client.on_message_received = on_received
|
||||
|
||||
async def callback():
|
||||
if self.enable_command_register:
|
||||
await self._collect_and_register_commands()
|
||||
if self.activity_name:
|
||||
await self.client.change_presence(
|
||||
status=discord.Status.online,
|
||||
activity=discord.CustomActivity(name=self.activity_name),
|
||||
)
|
||||
|
||||
self.client.on_ready_once_callback = callback
|
||||
|
||||
try:
|
||||
self._polling_task = asyncio.create_task(self.client.start_polling())
|
||||
await self.shutdown_event.wait()
|
||||
except discord.errors.LoginFailure:
|
||||
logger.error("[Discord] 登录失败。请检查你的 Bot Token 是否正确。")
|
||||
except discord.errors.ConnectionClosed:
|
||||
logger.warning("[Discord] 与 Discord 的连接已关闭。")
|
||||
except Exception as e:
|
||||
logger.error(f"[Discord] 适配器运行时发生意外错误: {e}", exc_info=True)
|
||||
|
||||
def _get_message_type(
|
||||
self, channel: Messageable, guild_id: int | None = None
|
||||
) -> MessageType:
|
||||
"""根据 channel 对象和 guild_id 判断消息类型"""
|
||||
if guild_id is not None:
|
||||
return MessageType.GROUP_MESSAGE
|
||||
if isinstance(channel, DMChannel) or getattr(channel, "guild", None) is None:
|
||||
return MessageType.FRIEND_MESSAGE
|
||||
return MessageType.GROUP_MESSAGE
|
||||
|
||||
def _get_channel_id(self, channel: Messageable) -> str:
|
||||
"""根据 channel 对象获取ID"""
|
||||
return str(getattr(channel, "id", None))
|
||||
|
||||
def _convert_message_to_abm(self, data: dict) -> AstrBotMessage:
|
||||
"""将普通消息转换为 AstrBotMessage"""
|
||||
message: discord.Message = data["message"]
|
||||
|
||||
content = message.content
|
||||
|
||||
# 如果机器人被@,移除@部分
|
||||
# 剥离 User Mention (<@id>, <@!id>)
|
||||
if self.client and self.client.user:
|
||||
mention_str = f"<@{self.client.user.id}>"
|
||||
mention_str_nickname = f"<@!{self.client.user.id}>"
|
||||
if content.startswith(mention_str):
|
||||
content = content[len(mention_str) :].lstrip()
|
||||
elif content.startswith(mention_str_nickname):
|
||||
content = content[len(mention_str_nickname) :].lstrip()
|
||||
|
||||
# 剥离 Role Mention(bot 拥有的任一角色被提及,<@&role_id>)
|
||||
if (
|
||||
hasattr(message, "role_mentions")
|
||||
and hasattr(message, "guild")
|
||||
and message.guild
|
||||
):
|
||||
bot_member = (
|
||||
message.guild.get_member(self.client.user.id)
|
||||
if self.client and self.client.user
|
||||
else None
|
||||
)
|
||||
if bot_member and hasattr(bot_member, "roles"):
|
||||
for role in bot_member.roles:
|
||||
role_mention_str = f"<@&{role.id}>"
|
||||
if content.startswith(role_mention_str):
|
||||
content = content[len(role_mention_str) :].lstrip()
|
||||
break # 只剥离第一个匹配的角色 mention
|
||||
|
||||
abm = AstrBotMessage()
|
||||
abm.type = self._get_message_type(message.channel)
|
||||
abm.group_id = self._get_channel_id(message.channel)
|
||||
abm.message_str = content
|
||||
abm.sender = MessageMember(
|
||||
user_id=str(message.author.id), nickname=message.author.display_name
|
||||
)
|
||||
message_chain = []
|
||||
if abm.message_str:
|
||||
message_chain.append(Plain(text=abm.message_str))
|
||||
if message.attachments:
|
||||
for attachment in message.attachments:
|
||||
if attachment.content_type and attachment.content_type.startswith(
|
||||
"image/"
|
||||
):
|
||||
message_chain.append(
|
||||
Image(file=attachment.url, filename=attachment.filename)
|
||||
)
|
||||
else:
|
||||
message_chain.append(
|
||||
File(name=attachment.filename, url=attachment.url)
|
||||
)
|
||||
abm.message = message_chain
|
||||
abm.raw_message = message
|
||||
abm.self_id = self.client_self_id
|
||||
abm.session_id = str(message.channel.id)
|
||||
abm.message_id = str(message.id)
|
||||
return abm
|
||||
|
||||
async def convert_message(self, data: dict) -> AstrBotMessage:
|
||||
"""将平台消息转换成 AstrBotMessage"""
|
||||
# 由于 on_interaction 已被禁用,我们只处理普通消息
|
||||
return self._convert_message_to_abm(data)
|
||||
|
||||
async def handle_msg(self, message: AstrBotMessage, followup_webhook=None):
|
||||
"""处理消息"""
|
||||
message_event = DiscordPlatformEvent(
|
||||
message_str=message.message_str,
|
||||
message_obj=message,
|
||||
platform_meta=self.meta(),
|
||||
session_id=message.session_id,
|
||||
client=self.client,
|
||||
interaction_followup_webhook=followup_webhook,
|
||||
)
|
||||
|
||||
# 检查是否为斜杠指令
|
||||
is_slash_command = message_event.interaction_followup_webhook is not None
|
||||
|
||||
# 检查是否被@(User Mention 或 Bot 拥有的 Role Mention)
|
||||
is_mention = False
|
||||
# User Mention
|
||||
if (
|
||||
self.client
|
||||
and self.client.user
|
||||
and hasattr(message.raw_message, "mentions")
|
||||
):
|
||||
if self.client.user in message.raw_message.mentions:
|
||||
is_mention = True
|
||||
# Role Mention(Bot 拥有的角色被提及)
|
||||
if not is_mention and hasattr(message.raw_message, "role_mentions"):
|
||||
bot_member = None
|
||||
if hasattr(message.raw_message, "guild") and message.raw_message.guild:
|
||||
try:
|
||||
bot_member = message.raw_message.guild.get_member(
|
||||
self.client.user.id
|
||||
)
|
||||
except Exception:
|
||||
bot_member = None
|
||||
if bot_member and hasattr(bot_member, "roles"):
|
||||
bot_roles = set(bot_member.roles)
|
||||
mentioned_roles = set(message.raw_message.role_mentions)
|
||||
if (
|
||||
bot_roles
|
||||
and mentioned_roles
|
||||
and bot_roles.intersection(mentioned_roles)
|
||||
):
|
||||
is_mention = True
|
||||
|
||||
# 如果是斜杠指令或被@的消息,设置为唤醒状态
|
||||
if is_slash_command or is_mention:
|
||||
message_event.is_wake = True
|
||||
message_event.is_at_or_wake_command = True
|
||||
|
||||
self.commit_event(message_event)
|
||||
|
||||
@override
|
||||
async def terminate(self):
|
||||
"""终止适配器"""
|
||||
logger.info("[Discord] 正在终止适配器... (step 1: cancel polling task)")
|
||||
self.shutdown_event.set()
|
||||
# 优先 cancel polling_task
|
||||
if self._polling_task:
|
||||
self._polling_task.cancel()
|
||||
try:
|
||||
await asyncio.wait_for(self._polling_task, timeout=10)
|
||||
except asyncio.CancelledError:
|
||||
logger.info("[Discord] polling_task 已取消。")
|
||||
except Exception as e:
|
||||
logger.warning(f"[Discord] polling_task 取消异常: {e}")
|
||||
logger.info("[Discord] 正在清理已注册的斜杠指令... (step 2)")
|
||||
# 清理指令
|
||||
if self.enable_command_register and self.client:
|
||||
try:
|
||||
await asyncio.wait_for(
|
||||
self.client.sync_commands(
|
||||
commands=[],
|
||||
guild_ids=[self.guild_id] if self.guild_id else None,
|
||||
),
|
||||
timeout=10,
|
||||
)
|
||||
logger.info("[Discord] 指令清理完成。")
|
||||
except Exception as e:
|
||||
logger.error(f"[Discord] 清理指令时发生错误: {e}", exc_info=True)
|
||||
logger.info("[Discord] 正在关闭 Discord 客户端... (step 3)")
|
||||
if self.client and hasattr(self.client, "close"):
|
||||
try:
|
||||
await asyncio.wait_for(self.client.close(), timeout=10)
|
||||
except Exception as e:
|
||||
logger.warning(f"[Discord] 客户端关闭异常: {e}")
|
||||
logger.info("[Discord] 适配器已终止。")
|
||||
|
||||
def register_handler(self, handler_info):
|
||||
"""注册处理器信息"""
|
||||
self.registered_handlers.append(handler_info)
|
||||
|
||||
async def _collect_and_register_commands(self):
|
||||
"""收集所有指令并注册到Discord"""
|
||||
logger.info("[Discord] 开始收集并注册斜杠指令...")
|
||||
registered_commands = []
|
||||
|
||||
for handler_md in star_handlers_registry:
|
||||
if not star_map[handler_md.handler_module_path].activated:
|
||||
continue
|
||||
for event_filter in handler_md.event_filters:
|
||||
cmd_info = self._extract_command_info(event_filter, handler_md)
|
||||
if not cmd_info:
|
||||
continue
|
||||
|
||||
cmd_name, description, cmd_filter_instance = cmd_info
|
||||
|
||||
# 创建动态回调
|
||||
callback = self._create_dynamic_callback(cmd_name)
|
||||
|
||||
# 创建一个通用的参数选项来接收所有文本输入
|
||||
options = [
|
||||
discord.Option(
|
||||
name="params",
|
||||
description="指令的所有参数",
|
||||
type=discord.SlashCommandOptionType.string,
|
||||
required=False,
|
||||
)
|
||||
]
|
||||
|
||||
# 创建SlashCommand
|
||||
slash_command = discord.SlashCommand(
|
||||
name=cmd_name,
|
||||
description=description,
|
||||
func=callback,
|
||||
options=options,
|
||||
guild_ids=[self.guild_id] if self.guild_id else None,
|
||||
)
|
||||
self.client.add_application_command(slash_command)
|
||||
registered_commands.append(cmd_name)
|
||||
|
||||
if registered_commands:
|
||||
logger.info(
|
||||
f"[Discord] 准备同步 {len(registered_commands)} 个指令: {', '.join(registered_commands)}"
|
||||
)
|
||||
else:
|
||||
logger.info("[Discord] 没有发现可注册的指令。")
|
||||
|
||||
# 使用 Pycord 的方法同步指令
|
||||
# 注意:这可能需要一些时间,并且有频率限制
|
||||
await self.client.sync_commands()
|
||||
logger.info("[Discord] 指令同步完成。")
|
||||
|
||||
def _create_dynamic_callback(self, cmd_name: str):
|
||||
"""为每个指令动态创建一个异步回调函数"""
|
||||
|
||||
async def dynamic_callback(ctx: discord.ApplicationContext, params: str = None):
|
||||
# 将平台特定的前缀'/'剥离,以适配通用的CommandFilter
|
||||
logger.debug(f"[Discord] 回调函数触发: {cmd_name}")
|
||||
logger.debug(f"[Discord] 回调函数参数: {ctx}")
|
||||
logger.debug(f"[Discord] 回调函数参数: {params}")
|
||||
message_str_for_filter = cmd_name
|
||||
if params:
|
||||
message_str_for_filter += f" {params}"
|
||||
|
||||
logger.debug(
|
||||
f"[Discord] 斜杠指令 '{cmd_name}' 被触发。 "
|
||||
f"原始参数: '{params}'. "
|
||||
f"构建的指令字符串: '{message_str_for_filter}'"
|
||||
)
|
||||
|
||||
# 尝试立即响应,防止超时
|
||||
followup_webhook = None
|
||||
try:
|
||||
await ctx.defer()
|
||||
followup_webhook = ctx.followup
|
||||
except Exception as e:
|
||||
logger.warning(f"[Discord] 指令 '{cmd_name}' defer 失败: {e}")
|
||||
|
||||
# 2. 构建 AstrBotMessage
|
||||
abm = AstrBotMessage()
|
||||
abm.type = self._get_message_type(ctx.channel, ctx.guild_id)
|
||||
abm.group_id = self._get_channel_id(ctx.channel)
|
||||
abm.message_str = message_str_for_filter
|
||||
abm.sender = MessageMember(
|
||||
user_id=str(ctx.author.id), nickname=ctx.author.display_name
|
||||
)
|
||||
abm.message = [Plain(text=message_str_for_filter)]
|
||||
abm.raw_message = ctx.interaction
|
||||
abm.self_id = self.client_self_id
|
||||
abm.session_id = str(ctx.channel_id)
|
||||
abm.message_id = str(ctx.interaction.id)
|
||||
|
||||
# 3. 将消息和 webhook 分别交给 handle_msg 处理
|
||||
await self.handle_msg(abm, followup_webhook)
|
||||
|
||||
return dynamic_callback
|
||||
|
||||
@staticmethod
|
||||
def _extract_command_info(
|
||||
event_filter: Any, handler_metadata: StarHandlerMetadata
|
||||
) -> Tuple[str, str, CommandFilter] | None:
|
||||
"""从事件过滤器中提取指令信息"""
|
||||
cmd_name = None
|
||||
# is_group = False
|
||||
cmd_filter_instance = None
|
||||
|
||||
if isinstance(event_filter, CommandFilter):
|
||||
# 暂不支持子指令注册为斜杠指令
|
||||
if (
|
||||
event_filter.parent_command_names
|
||||
and event_filter.parent_command_names != [""]
|
||||
):
|
||||
return None
|
||||
cmd_name = event_filter.command_name
|
||||
cmd_filter_instance = event_filter
|
||||
|
||||
elif isinstance(event_filter, CommandGroupFilter):
|
||||
# 暂不支持指令组直接注册为斜杠指令,因为它们没有 handle 方法
|
||||
return None
|
||||
|
||||
if not cmd_name:
|
||||
return None
|
||||
|
||||
# Discord 斜杠指令名称规范
|
||||
if not re.match(r"^[a-z0-9_-]{1,32}$", cmd_name):
|
||||
logger.debug(f"[Discord] 跳过不符合规范的指令: {cmd_name}")
|
||||
return None
|
||||
|
||||
description = handler_metadata.desc or f"指令: {cmd_name}"
|
||||
if len(description) > 100:
|
||||
description = f"{description[:97]}..."
|
||||
|
||||
return cmd_name, description, cmd_filter_instance
|
||||
296
astrbot/core/platform/sources/discord/discord_platform_event.py
Normal file
296
astrbot/core/platform/sources/discord/discord_platform_event.py
Normal file
@@ -0,0 +1,296 @@
|
||||
import asyncio
|
||||
import discord
|
||||
import base64
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
import sys
|
||||
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
from astrbot.api.platform import AstrBotMessage, PlatformMetadata, At
|
||||
from astrbot.api.message_components import (
|
||||
Plain,
|
||||
Image,
|
||||
File,
|
||||
BaseMessageComponent,
|
||||
Reply,
|
||||
)
|
||||
from astrbot import logger
|
||||
from .client import DiscordBotClient
|
||||
from .components import DiscordEmbed, DiscordView
|
||||
|
||||
if sys.version_info >= (3, 12):
|
||||
from typing import override
|
||||
else:
|
||||
from typing_extensions import override
|
||||
|
||||
|
||||
# 自定义Discord视图组件(兼容旧版本)
|
||||
class DiscordViewComponent(BaseMessageComponent):
|
||||
type: str = "discord_view"
|
||||
|
||||
def __init__(self, view: discord.ui.View):
|
||||
self.view = view
|
||||
|
||||
|
||||
class DiscordPlatformEvent(AstrMessageEvent):
|
||||
def __init__(
|
||||
self,
|
||||
message_str: str,
|
||||
message_obj: AstrBotMessage,
|
||||
platform_meta: PlatformMetadata,
|
||||
session_id: str,
|
||||
client: DiscordBotClient,
|
||||
interaction_followup_webhook: Optional[discord.Webhook] = None,
|
||||
):
|
||||
super().__init__(message_str, message_obj, platform_meta, session_id)
|
||||
self.client = client
|
||||
self.interaction_followup_webhook = interaction_followup_webhook
|
||||
|
||||
@override
|
||||
async def send(self, message: MessageChain):
|
||||
"""发送消息到Discord平台"""
|
||||
|
||||
# 解析消息链为 Discord 所需的对象
|
||||
try:
|
||||
(
|
||||
content,
|
||||
files,
|
||||
view,
|
||||
embeds,
|
||||
reference_message_id,
|
||||
) = await self._parse_to_discord(message)
|
||||
except Exception as e:
|
||||
logger.error(f"[Discord] 解析消息链时失败: {e}", exc_info=True)
|
||||
return
|
||||
|
||||
kwargs = {}
|
||||
if content:
|
||||
kwargs["content"] = content
|
||||
if files:
|
||||
kwargs["files"] = files
|
||||
if view:
|
||||
kwargs["view"] = view
|
||||
if embeds:
|
||||
kwargs["embeds"] = embeds
|
||||
if reference_message_id and not self.interaction_followup_webhook:
|
||||
kwargs["reference"] = self.client.get_message(int(reference_message_id))
|
||||
if not kwargs:
|
||||
logger.debug("[Discord] 尝试发送空消息,已忽略。")
|
||||
return
|
||||
|
||||
# 根据上下文执行发送/回复操作
|
||||
try:
|
||||
# -- 斜杠指令/交互上下文 --
|
||||
if self.interaction_followup_webhook:
|
||||
await self.interaction_followup_webhook.send(**kwargs)
|
||||
|
||||
# -- 常规消息上下文 --
|
||||
else:
|
||||
channel = await self._get_channel()
|
||||
if not channel:
|
||||
return
|
||||
else:
|
||||
await channel.send(**kwargs)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Discord] 发送消息时发生未知错误: {e}", exc_info=True)
|
||||
|
||||
await super().send(message)
|
||||
|
||||
async def _get_channel(self) -> Optional[discord.abc.Messageable]:
|
||||
"""获取当前事件对应的频道对象"""
|
||||
try:
|
||||
channel_id = int(self.session_id)
|
||||
return self.client.get_channel(
|
||||
channel_id
|
||||
) or await self.client.fetch_channel(channel_id)
|
||||
except (ValueError, discord.errors.NotFound, discord.errors.Forbidden):
|
||||
logger.error(f"[Discord] 无法获取频道 {self.session_id}")
|
||||
return None
|
||||
|
||||
async def _parse_to_discord(
|
||||
self,
|
||||
message: MessageChain,
|
||||
) -> tuple[str, list[discord.File], Optional[discord.ui.View], list[discord.Embed]]:
|
||||
"""将 MessageChain 解析为 Discord 发送所需的内容"""
|
||||
content = ""
|
||||
files = []
|
||||
view = None
|
||||
embeds = []
|
||||
reference_message_id = None
|
||||
for i in message.chain: # 遍历消息链
|
||||
if isinstance(i, Plain): # 如果是文字类型的
|
||||
content += i.text
|
||||
elif isinstance(i, Reply):
|
||||
reference_message_id = i.id
|
||||
elif isinstance(i, At):
|
||||
content += f"<@{i.qq}>"
|
||||
elif isinstance(i, Image):
|
||||
logger.debug(f"[Discord] 开始处理 Image 组件: {i}")
|
||||
try:
|
||||
filename = getattr(i, "filename", None)
|
||||
file_content = getattr(i, "file", None)
|
||||
|
||||
if not file_content:
|
||||
logger.warning(f"[Discord] Image 组件没有 file 属性: {i}")
|
||||
continue
|
||||
|
||||
discord_file = None
|
||||
|
||||
# 1. URL
|
||||
if file_content.startswith("http"):
|
||||
logger.debug(f"[Discord] 处理 URL 图片: {file_content}")
|
||||
embed = discord.Embed().set_image(url=file_content)
|
||||
embeds.append(embed)
|
||||
continue
|
||||
|
||||
# 2. File URI
|
||||
elif file_content.startswith("file:///"):
|
||||
logger.debug(f"[Discord] 处理 File URI: {file_content}")
|
||||
path = Path(file_content[8:])
|
||||
if await asyncio.to_thread(path.exists):
|
||||
file_bytes = await asyncio.to_thread(path.read_bytes)
|
||||
discord_file = discord.File(
|
||||
BytesIO(file_bytes), filename=filename or path.name
|
||||
)
|
||||
else:
|
||||
logger.warning(f"[Discord] 图片文件不存在: {path}")
|
||||
|
||||
# 3. Base64 URI
|
||||
elif file_content.startswith("base64://"):
|
||||
logger.debug("[Discord] 处理 Base64 URI")
|
||||
b64_data = file_content.split("base64://", 1)[1]
|
||||
missing_padding = len(b64_data) % 4
|
||||
if missing_padding:
|
||||
b64_data += "=" * (4 - missing_padding)
|
||||
img_bytes = base64.b64decode(b64_data)
|
||||
discord_file = discord.File(
|
||||
BytesIO(img_bytes), filename=filename or "image.png"
|
||||
)
|
||||
|
||||
# 4. 裸 Base64 或本地路径
|
||||
else:
|
||||
try:
|
||||
logger.debug("[Discord] 尝试作为裸 Base64 处理")
|
||||
b64_data = file_content
|
||||
missing_padding = len(b64_data) % 4
|
||||
if missing_padding:
|
||||
b64_data += "=" * (4 - missing_padding)
|
||||
img_bytes = base64.b64decode(b64_data)
|
||||
discord_file = discord.File(
|
||||
BytesIO(img_bytes), filename=filename or "image.png"
|
||||
)
|
||||
except (ValueError, TypeError, base64.binascii.Error):
|
||||
logger.debug(
|
||||
f"[Discord] 裸 Base64 解码失败,作为本地路径处理: {file_content}"
|
||||
)
|
||||
path = Path(file_content)
|
||||
if await asyncio.to_thread(path.exists):
|
||||
file_bytes = await asyncio.to_thread(path.read_bytes)
|
||||
discord_file = discord.File(
|
||||
BytesIO(file_bytes), filename=filename or path.name
|
||||
)
|
||||
else:
|
||||
logger.warning(f"[Discord] 图片文件不存在: {path}")
|
||||
|
||||
if discord_file:
|
||||
files.append(discord_file)
|
||||
|
||||
except Exception:
|
||||
# 使用 getattr 来安全地访问 i.file,以防 i 本身就是问题
|
||||
file_info = getattr(i, "file", "未知")
|
||||
logger.error(
|
||||
f"[Discord] 处理图片时发生未知严重错误: {file_info}",
|
||||
exc_info=True,
|
||||
)
|
||||
elif isinstance(i, File):
|
||||
try:
|
||||
file_path_str = await i.get_file()
|
||||
if file_path_str:
|
||||
path = Path(file_path_str)
|
||||
if await asyncio.to_thread(path.exists):
|
||||
file_bytes = await asyncio.to_thread(path.read_bytes)
|
||||
files.append(
|
||||
discord.File(BytesIO(file_bytes), filename=i.name)
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
f"[Discord] 获取文件失败,路径不存在: {file_path_str}"
|
||||
)
|
||||
else:
|
||||
logger.warning(f"[Discord] 获取文件失败: {i.name}")
|
||||
except Exception as e:
|
||||
logger.warning(f"[Discord] 处理文件失败: {i.name}, 错误: {e}")
|
||||
elif isinstance(i, DiscordEmbed):
|
||||
# Discord Embed消息
|
||||
embeds.append(i.to_discord_embed())
|
||||
elif isinstance(i, DiscordView):
|
||||
# Discord视图组件(按钮、选择菜单等)
|
||||
view = i.to_discord_view()
|
||||
elif isinstance(i, DiscordViewComponent):
|
||||
# 如果消息链中包含Discord视图组件(兼容旧版本)
|
||||
if isinstance(i.view, discord.ui.View):
|
||||
view = i.view
|
||||
else:
|
||||
logger.debug(f"[Discord] 忽略了不支持的消息组件: {i.type}")
|
||||
|
||||
if len(content) > 2000:
|
||||
logger.warning("[Discord] 消息内容超过2000字符,将被截断。")
|
||||
content = content[:2000]
|
||||
return content, files, view, embeds, reference_message_id
|
||||
|
||||
async def react(self, emoji: str):
|
||||
"""对原消息添加反应"""
|
||||
try:
|
||||
if hasattr(self.message_obj, "raw_message") and hasattr(
|
||||
self.message_obj.raw_message, "add_reaction"
|
||||
):
|
||||
await self.message_obj.raw_message.add_reaction(emoji)
|
||||
except Exception as e:
|
||||
logger.error(f"[Discord] 添加反应失败: {e}")
|
||||
|
||||
def is_slash_command(self) -> bool:
|
||||
"""判断是否为斜杠命令"""
|
||||
return (
|
||||
hasattr(self.message_obj, "raw_message")
|
||||
and hasattr(self.message_obj.raw_message, "type")
|
||||
and self.message_obj.raw_message.type
|
||||
== discord.InteractionType.application_command
|
||||
)
|
||||
|
||||
def is_button_interaction(self) -> bool:
|
||||
"""判断是否为按钮交互"""
|
||||
return (
|
||||
hasattr(self.message_obj, "raw_message")
|
||||
and hasattr(self.message_obj.raw_message, "type")
|
||||
and self.message_obj.raw_message.type == discord.InteractionType.component
|
||||
)
|
||||
|
||||
def get_interaction_custom_id(self) -> str:
|
||||
"""获取交互组件的custom_id"""
|
||||
if self.is_button_interaction():
|
||||
try:
|
||||
return self.message_obj.raw_message.data.get("custom_id", "")
|
||||
except Exception:
|
||||
pass
|
||||
return ""
|
||||
|
||||
def is_mentioned(self) -> bool:
|
||||
"""判断机器人是否被@"""
|
||||
if hasattr(self.message_obj, "raw_message") and hasattr(
|
||||
self.message_obj.raw_message, "mentions"
|
||||
):
|
||||
return any(
|
||||
mention.id == int(self.message_obj.self_id)
|
||||
for mention in self.message_obj.raw_message.mentions
|
||||
)
|
||||
return False
|
||||
|
||||
def get_mention_clean_content(self) -> str:
|
||||
"""获取去除@后的清洁内容"""
|
||||
if hasattr(self.message_obj, "raw_message") and hasattr(
|
||||
self.message_obj.raw_message, "clean_content"
|
||||
):
|
||||
return self.message_obj.raw_message.clean_content
|
||||
return self.message_str
|
||||
@@ -1,812 +0,0 @@
|
||||
import asyncio
|
||||
import base64
|
||||
import datetime
|
||||
import os
|
||||
import re
|
||||
import uuid
|
||||
import threading
|
||||
|
||||
import aiohttp
|
||||
import anyio
|
||||
import quart
|
||||
|
||||
from astrbot.api import logger, sp
|
||||
from astrbot.api.message_components import Plain, Image, At, Record, Video
|
||||
from astrbot.api.platform import AstrBotMessage, MessageMember, MessageType
|
||||
from astrbot.core.utils.io import download_image_by_url
|
||||
from .downloader import GeweDownloader
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
try:
|
||||
from .xml_data_parser import GeweDataParser
|
||||
except (ImportError, ModuleNotFoundError) as e:
|
||||
logger.warning(
|
||||
f"警告: 可能未安装 defusedxml 依赖库,将导致无法解析微信的 表情包、引用 类型的消息: {str(e)}"
|
||||
)
|
||||
|
||||
|
||||
class SimpleGewechatClient:
|
||||
"""针对 Gewechat 的简单实现。
|
||||
|
||||
@author: Soulter
|
||||
@website: https://github.com/Soulter
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
base_url: str,
|
||||
nickname: str,
|
||||
host: str,
|
||||
port: int,
|
||||
event_queue: asyncio.Queue,
|
||||
):
|
||||
self.base_url = base_url
|
||||
if self.base_url.endswith("/"):
|
||||
self.base_url = self.base_url[:-1]
|
||||
|
||||
self.download_base_url = self.base_url.split(":")[:-1] # 去掉端口
|
||||
self.download_base_url = ":".join(self.download_base_url) + ":2532/download/"
|
||||
|
||||
self.base_url += "/v2/api"
|
||||
|
||||
logger.info(f"Gewechat API: {self.base_url}")
|
||||
logger.info(f"Gewechat 下载 API: {self.download_base_url}")
|
||||
|
||||
if isinstance(port, str):
|
||||
port = int(port)
|
||||
|
||||
self.token = None
|
||||
self.headers = {}
|
||||
self.nickname = nickname
|
||||
self.appid = sp.get(f"gewechat-appid-{nickname}", "")
|
||||
|
||||
self.server = quart.Quart(__name__)
|
||||
self.server.add_url_rule(
|
||||
"/astrbot-gewechat/callback", view_func=self._callback, methods=["POST"]
|
||||
)
|
||||
self.server.add_url_rule(
|
||||
"/astrbot-gewechat/file/<file_token>",
|
||||
view_func=self._handle_file,
|
||||
methods=["GET"],
|
||||
)
|
||||
|
||||
self.host = host
|
||||
self.port = port
|
||||
self.callback_url = f"http://{self.host}:{self.port}/astrbot-gewechat/callback"
|
||||
self.file_server_url = f"http://{self.host}:{self.port}/astrbot-gewechat/file"
|
||||
|
||||
self.event_queue = event_queue
|
||||
|
||||
self.multimedia_downloader = None
|
||||
|
||||
self.userrealnames = {}
|
||||
|
||||
self.shutdown_event = asyncio.Event()
|
||||
|
||||
self.staged_files = {}
|
||||
"""存储了允许外部访问的文件列表。auth_token: file_path。通过 register_file 方法注册。"""
|
||||
|
||||
self.lock = asyncio.Lock()
|
||||
|
||||
async def get_token_id(self):
|
||||
"""获取 Gewechat Token。"""
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(f"{self.base_url}/tools/getTokenId") as resp:
|
||||
json_blob = await resp.json()
|
||||
self.token = json_blob["data"]
|
||||
logger.info(f"获取到 Gewechat Token: {self.token}")
|
||||
self.headers = {"X-GEWE-TOKEN": self.token}
|
||||
|
||||
async def _convert(self, data: dict) -> AstrBotMessage:
|
||||
if "TypeName" in data:
|
||||
type_name = data["TypeName"]
|
||||
elif "type_name" in data:
|
||||
type_name = data["type_name"]
|
||||
else:
|
||||
raise Exception("无法识别的消息类型")
|
||||
|
||||
# 以下没有业务处理,只是避免控制台打印太多的日志
|
||||
if type_name == "ModContacts":
|
||||
logger.info("gewechat下发:ModContacts消息通知。")
|
||||
return
|
||||
if type_name == "DelContacts":
|
||||
logger.info("gewechat下发:DelContacts消息通知。")
|
||||
return
|
||||
|
||||
if type_name == "Offline":
|
||||
logger.critical("收到 gewechat 下线通知。")
|
||||
return
|
||||
|
||||
d = None
|
||||
if "Data" in data:
|
||||
d = data["Data"]
|
||||
elif "data" in data:
|
||||
d = data["data"]
|
||||
|
||||
if not d:
|
||||
logger.warning(f"消息不含 data 字段: {data}")
|
||||
return
|
||||
|
||||
if "CreateTime" in d:
|
||||
# 得到系统 UTF+8 的 ts
|
||||
tz_offset = datetime.timedelta(hours=8)
|
||||
tz = datetime.timezone(tz_offset)
|
||||
ts = datetime.datetime.now(tz).timestamp()
|
||||
create_time = d["CreateTime"]
|
||||
if create_time < ts - 30:
|
||||
logger.warning(f"消息时间戳过旧: {create_time},当前时间戳: {ts}")
|
||||
return
|
||||
|
||||
abm = AstrBotMessage()
|
||||
|
||||
from_user_name = d["FromUserName"]["string"] # 消息来源
|
||||
d["to_wxid"] = from_user_name # 用于发信息
|
||||
|
||||
abm.message_id = str(d.get("MsgId"))
|
||||
abm.session_id = from_user_name
|
||||
abm.self_id = data["Wxid"] # 机器人的 wxid
|
||||
|
||||
user_id = "" # 发送人 wxid
|
||||
content = d["Content"]["string"] # 消息内容
|
||||
|
||||
at_me = False
|
||||
at_wxids = []
|
||||
if "@chatroom" in from_user_name:
|
||||
abm.type = MessageType.GROUP_MESSAGE
|
||||
_t = content.split(":\n")
|
||||
user_id = _t[0]
|
||||
content = _t[1]
|
||||
# at
|
||||
msg_source = d["MsgSource"]
|
||||
if "\u2005" in content:
|
||||
# at
|
||||
# content = content.split('\u2005')[1]
|
||||
content = re.sub(r"@[^\u2005]*\u2005", "", content)
|
||||
at_wxids = re.findall(
|
||||
r"<atuserlist><!\[CDATA\[.*?(?:,|\b)([^,]+?)(?=,|\]\]></atuserlist>)",
|
||||
msg_source,
|
||||
)
|
||||
|
||||
abm.group_id = from_user_name
|
||||
|
||||
if (
|
||||
f"<atuserlist><![CDATA[,{abm.self_id}]]>" in msg_source
|
||||
or f"<atuserlist><![CDATA[{abm.self_id}]]>" in msg_source
|
||||
):
|
||||
at_me = True
|
||||
if "在群聊中@了你" in d.get("PushContent", ""):
|
||||
at_me = True
|
||||
else:
|
||||
abm.type = MessageType.FRIEND_MESSAGE
|
||||
user_id = from_user_name
|
||||
|
||||
# 检查消息是否由自己发送,若是则忽略
|
||||
# 已经有可配置项专门配置是否需要响应自己的消息,因此这里注释掉。
|
||||
# if user_id == abm.self_id:
|
||||
# logger.info("忽略自己发送的消息")
|
||||
# return None
|
||||
|
||||
abm.message = []
|
||||
|
||||
# 解析用户真实名字
|
||||
user_real_name = "unknown"
|
||||
if abm.group_id:
|
||||
if (
|
||||
abm.group_id not in self.userrealnames
|
||||
or user_id not in self.userrealnames[abm.group_id]
|
||||
):
|
||||
# 获取群成员列表,并且缓存
|
||||
if abm.group_id not in self.userrealnames:
|
||||
self.userrealnames[abm.group_id] = {}
|
||||
member_list = await self.get_chatroom_member_list(abm.group_id)
|
||||
logger.debug(f"获取到 {abm.group_id} 的群成员列表。")
|
||||
if member_list and "memberList" in member_list:
|
||||
for member in member_list["memberList"]:
|
||||
self.userrealnames[abm.group_id][member["wxid"]] = member[
|
||||
"nickName"
|
||||
]
|
||||
if user_id in self.userrealnames[abm.group_id]:
|
||||
user_real_name = self.userrealnames[abm.group_id][user_id]
|
||||
else:
|
||||
user_real_name = self.userrealnames[abm.group_id][user_id]
|
||||
else:
|
||||
try:
|
||||
info = (await self.get_user_or_group_info(user_id))["data"][0]
|
||||
user_real_name = info["nickName"]
|
||||
except Exception as e:
|
||||
logger.debug(f"获取用户 {user_id} 昵称失败: {e}")
|
||||
user_real_name = user_id
|
||||
|
||||
if at_me:
|
||||
abm.message.insert(0, At(qq=abm.self_id, name=self.nickname))
|
||||
for wxid in at_wxids:
|
||||
# 群聊里 At 其他人的列表
|
||||
_username = self.userrealnames.get(abm.group_id, {}).get(wxid, wxid)
|
||||
abm.message.append(At(qq=wxid, name=_username))
|
||||
|
||||
abm.sender = MessageMember(user_id, user_real_name)
|
||||
abm.raw_message = d
|
||||
abm.message_str = ""
|
||||
|
||||
if user_id == "weixin":
|
||||
# 忽略微信团队消息
|
||||
return
|
||||
|
||||
# 不同消息类型
|
||||
match d["MsgType"]:
|
||||
case 1:
|
||||
# 文本消息
|
||||
abm.message.append(Plain(content))
|
||||
abm.message_str = content
|
||||
case 3:
|
||||
# 图片消息
|
||||
file_url = await self.multimedia_downloader.download_image(
|
||||
self.appid, content
|
||||
)
|
||||
logger.debug(f"下载图片: {file_url}")
|
||||
file_path = await download_image_by_url(file_url)
|
||||
abm.message.append(Image(file=file_path, url=file_path))
|
||||
|
||||
case 34:
|
||||
# 语音消息
|
||||
if "ImgBuf" in d and "buffer" in d["ImgBuf"]:
|
||||
voice_data = base64.b64decode(d["ImgBuf"]["buffer"])
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
file_path = os.path.join(
|
||||
temp_dir, f"gewe_voice_{abm.message_id}.silk"
|
||||
)
|
||||
|
||||
async with await anyio.open_file(file_path, "wb") as f:
|
||||
await f.write(voice_data)
|
||||
abm.message.append(Record(file=file_path, url=file_path))
|
||||
|
||||
# 以下已知消息类型,没有业务处理,只是避免控制台打印太多的日志
|
||||
case 37: # 好友申请
|
||||
logger.info("消息类型(37):好友申请")
|
||||
case 42: # 名片
|
||||
logger.info("消息类型(42):名片")
|
||||
case 43: # 视频
|
||||
video = Video(file="", cover=content)
|
||||
abm.message.append(video)
|
||||
case 47: # emoji
|
||||
data_parser = GeweDataParser(content, abm.group_id == "")
|
||||
emoji = data_parser.parse_emoji()
|
||||
abm.message.append(emoji)
|
||||
case 48: # 地理位置
|
||||
logger.info("消息类型(48):地理位置")
|
||||
case 49: # 公众号/文件/小程序/引用/转账/红包/视频号/群聊邀请
|
||||
data_parser = GeweDataParser(content, abm.group_id == "")
|
||||
segments = data_parser.parse_mutil_49()
|
||||
if segments:
|
||||
abm.message.extend(segments)
|
||||
for seg in segments:
|
||||
if isinstance(seg, Plain):
|
||||
abm.message_str += seg.text
|
||||
case 51: # 帐号消息同步?
|
||||
logger.info("消息类型(51):帐号消息同步?")
|
||||
case 10000: # 被踢出群聊/更换群主/修改群名称
|
||||
logger.info("消息类型(10000):被踢出群聊/更换群主/修改群名称")
|
||||
case 10002: # 撤回/拍一拍/成员邀请/被移出群聊/解散群聊/群公告/群待办
|
||||
logger.info(
|
||||
"消息类型(10002):撤回/拍一拍/成员邀请/被移出群聊/解散群聊/群公告/群待办"
|
||||
)
|
||||
|
||||
case _:
|
||||
logger.info(f"未实现的消息类型: {d['MsgType']}")
|
||||
abm.raw_message = d
|
||||
|
||||
logger.debug(f"abm: {abm}")
|
||||
return abm
|
||||
|
||||
async def _callback(self):
|
||||
data = await quart.request.json
|
||||
logger.debug(f"收到 gewechat 回调: {data}")
|
||||
|
||||
if data.get("testMsg", None):
|
||||
return quart.jsonify({"r": "AstrBot ACK"})
|
||||
|
||||
abm = None
|
||||
try:
|
||||
abm = await self._convert(data)
|
||||
except BaseException as e:
|
||||
logger.warning(
|
||||
f"尝试解析 GeweChat 下发的消息时遇到问题: {e}。下发消息内容: {data}。"
|
||||
)
|
||||
|
||||
if abm:
|
||||
coro = getattr(self, "on_event_received")
|
||||
if coro:
|
||||
await coro(abm)
|
||||
|
||||
return quart.jsonify({"r": "AstrBot ACK"})
|
||||
|
||||
async def _register_file(self, file_path: str) -> str:
|
||||
"""向 AstrBot 回调服务器 注册一个允许外部访问的文件。
|
||||
|
||||
Args:
|
||||
file_path (str): 文件路径。
|
||||
Returns:
|
||||
str: 返回一个 auth_token,文件路径为 file_path。通过 /astrbot-gewechat/file/auth_token 得到文件。
|
||||
"""
|
||||
async with self.lock:
|
||||
if not os.path.exists(file_path):
|
||||
raise Exception(f"文件不存在: {file_path}")
|
||||
|
||||
file_token = str(uuid.uuid4())
|
||||
self.staged_files[file_token] = file_path
|
||||
return file_token
|
||||
|
||||
async def _handle_file(self, file_token):
|
||||
async with self.lock:
|
||||
if file_token not in self.staged_files:
|
||||
logger.warning(f"请求的文件 {file_token} 不存在。")
|
||||
return quart.abort(404)
|
||||
if not os.path.exists(self.staged_files[file_token]):
|
||||
logger.warning(f"请求的文件 {self.staged_files[file_token]} 不存在。")
|
||||
return quart.abort(404)
|
||||
file_path = self.staged_files[file_token]
|
||||
self.staged_files.pop(file_token, None)
|
||||
return await quart.send_file(file_path)
|
||||
|
||||
async def _set_callback_url(self):
|
||||
logger.info("设置回调,请等待...")
|
||||
await asyncio.sleep(3)
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/tools/setCallback",
|
||||
headers=self.headers,
|
||||
json={"token": self.token, "callbackUrl": self.callback_url},
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.info(f"设置回调结果: {json_blob}")
|
||||
if json_blob["ret"] != 200:
|
||||
raise Exception(f"设置回调失败: {json_blob}")
|
||||
logger.info(
|
||||
f"将在 {self.callback_url} 上接收 gewechat 下发的消息。如果一直没收到消息请先尝试重启 AstrBot。如果仍没收到请到管理面板聊天页输入 /gewe_logout 重新登录。"
|
||||
)
|
||||
|
||||
async def start_polling(self):
|
||||
threading.Thread(target=asyncio.run, args=(self._set_callback_url(),)).start()
|
||||
await self.server.run_task(
|
||||
host="0.0.0.0",
|
||||
port=self.port,
|
||||
shutdown_trigger=self.shutdown_trigger,
|
||||
)
|
||||
|
||||
async def shutdown_trigger(self):
|
||||
await self.shutdown_event.wait()
|
||||
|
||||
async def check_online(self, appid: str):
|
||||
"""检查 APPID 对应的设备是否在线。"""
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/login/checkOnline",
|
||||
headers=self.headers,
|
||||
json={"appId": appid},
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
return json_blob["data"]
|
||||
|
||||
async def logout(self):
|
||||
"""登出 gewechat。"""
|
||||
if self.appid:
|
||||
online = await self.check_online(self.appid)
|
||||
if online:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/login/logout",
|
||||
headers=self.headers,
|
||||
json={"appId": self.appid},
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.info(f"登出结果: {json_blob}")
|
||||
|
||||
async def login(self):
|
||||
"""登录 gewechat。一般来说插件用不到这个方法。"""
|
||||
if self.token is None:
|
||||
await self.get_token_id()
|
||||
|
||||
self.multimedia_downloader = GeweDownloader(
|
||||
self.base_url, self.download_base_url, self.token
|
||||
)
|
||||
|
||||
if self.appid:
|
||||
try:
|
||||
online = await self.check_online(self.appid)
|
||||
if online:
|
||||
logger.info(f"APPID: {self.appid} 已在线")
|
||||
return
|
||||
except Exception as e:
|
||||
logger.error(f"检查在线状态失败: {e}")
|
||||
sp.put(f"gewechat-appid-{self.nickname}", "")
|
||||
self.appid = None
|
||||
|
||||
payload = {"appId": self.appid}
|
||||
|
||||
if self.appid:
|
||||
logger.info(f"使用 APPID: {self.appid}, {self.nickname}")
|
||||
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/login/getLoginQrCode",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
if json_blob["ret"] != 200:
|
||||
error_msg = json_blob.get("data", {}).get("msg", "")
|
||||
if "设备不存在" in error_msg:
|
||||
logger.error(
|
||||
f"检测到无效的appid: {self.appid},将清除并重新登录。"
|
||||
)
|
||||
sp.put(f"gewechat-appid-{self.nickname}", "")
|
||||
self.appid = None
|
||||
return await self.login()
|
||||
else:
|
||||
raise Exception(f"获取二维码失败: {json_blob}")
|
||||
qr_data = json_blob["data"]["qrData"]
|
||||
qr_uuid = json_blob["data"]["uuid"]
|
||||
appid = json_blob["data"]["appId"]
|
||||
logger.info(f"APPID: {appid}")
|
||||
logger.warning(
|
||||
f"请打开该网址,然后使用微信扫描二维码登录: https://api.cl2wm.cn/api/qrcode/code?text={qr_data}"
|
||||
)
|
||||
except Exception as e:
|
||||
raise e
|
||||
|
||||
# 执行登录
|
||||
retry_cnt = 64
|
||||
payload.update({"uuid": qr_uuid, "appId": appid})
|
||||
while retry_cnt > 0:
|
||||
retry_cnt -= 1
|
||||
|
||||
# 需要验证码
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
code_file_path = os.path.join(temp_dir, "gewe_code")
|
||||
if os.path.exists(code_file_path):
|
||||
with open(code_file_path, "r") as f:
|
||||
code = f.read().strip()
|
||||
if not code:
|
||||
logger.warning(
|
||||
"未找到验证码,请在管理面板聊天页输入 /gewe_code 验证码 来验证,如 /gewe_code 123456"
|
||||
)
|
||||
await asyncio.sleep(5)
|
||||
continue
|
||||
payload["captchCode"] = code
|
||||
logger.info(f"使用验证码: {code}")
|
||||
try:
|
||||
os.remove(code_file_path)
|
||||
except Exception:
|
||||
logger.warning(f"删除验证码文件 {code_file_path} 失败。")
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/login/checkLogin",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.info(f"检查登录状态: {json_blob}")
|
||||
|
||||
ret = json_blob["ret"]
|
||||
msg = ""
|
||||
if json_blob["data"] and "msg" in json_blob["data"]:
|
||||
msg = json_blob["data"]["msg"]
|
||||
if ret == 500 and "安全验证码" in msg:
|
||||
logger.warning(
|
||||
"此次登录需要安全验证码,请在管理面板聊天页输入 /gewe_code 验证码 来验证,如 /gewe_code 123456"
|
||||
)
|
||||
else:
|
||||
if "status" in json_blob["data"]:
|
||||
status = json_blob["data"]["status"]
|
||||
nickname = json_blob["data"].get("nickName", "")
|
||||
if status == 1:
|
||||
logger.info(f"等待确认...{nickname}")
|
||||
elif status == 2:
|
||||
logger.info(f"绿泡泡平台登录成功: {nickname}")
|
||||
break
|
||||
elif status == 0:
|
||||
logger.info("等待扫码...")
|
||||
else:
|
||||
logger.warning(f"未知状态: {status}")
|
||||
await asyncio.sleep(5)
|
||||
|
||||
if appid:
|
||||
sp.put(f"gewechat-appid-{self.nickname}", appid)
|
||||
self.appid = appid
|
||||
logger.info(f"已保存 APPID: {appid}")
|
||||
|
||||
"""API 部分。Gewechat 的 API 文档请参考: https://apifox.com/apidoc/shared/69ba62ca-cb7d-437e-85e4-6f3d3df271b1
|
||||
"""
|
||||
|
||||
async def get_chatroom_member_list(self, chatroom_wxid: str) -> dict:
|
||||
"""获取群成员列表。
|
||||
|
||||
Args:
|
||||
chatroom_wxid (str): 微信群聊的id。可以通过 event.get_group_id() 获取。
|
||||
|
||||
Returns:
|
||||
dict: 返回群成员列表字典。其中键为 memberList 的值为群成员列表。
|
||||
"""
|
||||
payload = {"appId": self.appid, "chatroomId": chatroom_wxid}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/group/getChatroomMemberList",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
return json_blob["data"]
|
||||
|
||||
async def post_text(self, to_wxid, content: str, ats: str = ""):
|
||||
"""发送纯文本消息"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"content": content,
|
||||
}
|
||||
if ats:
|
||||
payload["ats"] = ats
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postText", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"发送消息结果: {json_blob}")
|
||||
|
||||
async def post_image(self, to_wxid, image_url: str):
|
||||
"""发送图片消息"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"imgUrl": image_url,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postImage", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"发送图片结果: {json_blob}")
|
||||
|
||||
async def post_emoji(self, to_wxid, emoji_md5, emoji_size, cdnurl=""):
|
||||
"""发送emoji消息"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"emojiMd5": emoji_md5,
|
||||
"emojiSize": emoji_size,
|
||||
}
|
||||
|
||||
# 优先表情包,若拿不到表情包的md5,就用当作图片发
|
||||
try:
|
||||
if emoji_md5 != "" and emoji_size != "":
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postEmoji",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.info(
|
||||
f"发送emoji消息结果: {json_blob.get('msg', '操作失败')}"
|
||||
)
|
||||
else:
|
||||
await self.post_image(to_wxid, cdnurl)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(e)
|
||||
|
||||
async def post_video(
|
||||
self, to_wxid, video_url: str, thumb_url: str, video_duration: int
|
||||
):
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"videoUrl": video_url,
|
||||
"thumbUrl": thumb_url,
|
||||
"videoDuration": video_duration,
|
||||
}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postVideo", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"发送视频结果: {json_blob}")
|
||||
|
||||
async def forward_video(self, to_wxid, cnd_xml: str):
|
||||
"""转发视频
|
||||
|
||||
Args:
|
||||
to_wxid (str): 发送给谁
|
||||
cnd_xml (str): 视频消息的cdn信息
|
||||
"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"xml": cnd_xml,
|
||||
}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/forwardVideo",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"转发视频结果: {json_blob}")
|
||||
|
||||
async def post_voice(self, to_wxid, voice_url: str, voice_duration: int):
|
||||
"""发送语音信息
|
||||
|
||||
Args:
|
||||
voice_url (str): 语音文件的网络链接
|
||||
voice_duration (int): 语音时长,毫秒
|
||||
"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"voiceUrl": voice_url,
|
||||
"voiceDuration": voice_duration,
|
||||
}
|
||||
|
||||
logger.debug(f"发送语音: {payload}")
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postVoice", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.info(f"发送语音结果: {json_blob.get('msg', '操作失败')}")
|
||||
|
||||
async def post_file(self, to_wxid, file_url: str, file_name: str):
|
||||
"""发送文件
|
||||
|
||||
Args:
|
||||
to_wxid (string): 微信ID
|
||||
file_url (str): 文件的网络链接
|
||||
file_name (str): 文件名
|
||||
"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"toWxid": to_wxid,
|
||||
"fileUrl": file_url,
|
||||
"fileName": file_name,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/message/postFile", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"发送文件结果: {json_blob}")
|
||||
|
||||
async def add_friend(self, v3: str, v4: str, content: str):
|
||||
"""申请添加好友"""
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"scene": 3,
|
||||
"content": content,
|
||||
"v4": v4,
|
||||
"v3": v3,
|
||||
"option": 2,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/contacts/addContacts",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"申请添加好友结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def get_group(self, group_id: str):
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"chatroomId": group_id,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/group/getChatroomInfo",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取群信息结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def get_group_member(self, group_id: str):
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"chatroomId": group_id,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/group/getChatroomMemberList",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取群信息结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def accept_group_invite(self, url: str):
|
||||
"""同意进群"""
|
||||
payload = {"appId": self.appid, "url": url}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/group/agreeJoinRoom",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取群信息结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def add_group_member_to_friend(
|
||||
self, group_id: str, to_wxid: str, content: str
|
||||
):
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"chatroomId": group_id,
|
||||
"content": content,
|
||||
"memberWxid": to_wxid,
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/group/addGroupMemberAsFriend",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取群信息结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def get_user_or_group_info(self, *ids):
|
||||
"""
|
||||
获取用户或群组信息。
|
||||
|
||||
:param ids: 可变数量的 wxid 参数
|
||||
"""
|
||||
|
||||
wxids_str = list(ids)
|
||||
|
||||
payload = {
|
||||
"appId": self.appid,
|
||||
"wxids": wxids_str, # 使用逗号分隔的字符串
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/contacts/getDetailInfo",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取群信息结果: {json_blob}")
|
||||
return json_blob
|
||||
|
||||
async def get_contacts_list(self):
|
||||
"""
|
||||
获取通讯录列表
|
||||
见 https://apifox.com/apidoc/shared/69ba62ca-cb7d-437e-85e4-6f3d3df271b1/api-196794504
|
||||
"""
|
||||
payload = {"appId": self.appid}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{self.base_url}/contacts/fetchContactsList",
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
) as resp:
|
||||
json_blob = await resp.json()
|
||||
logger.debug(f"获取通讯录列表结果: {json_blob}")
|
||||
return json_blob
|
||||
@@ -1,55 +0,0 @@
|
||||
from astrbot import logger
|
||||
import aiohttp
|
||||
import json
|
||||
|
||||
|
||||
class GeweDownloader:
|
||||
def __init__(self, base_url: str, download_base_url: str, token: str):
|
||||
self.base_url = base_url
|
||||
self.download_base_url = download_base_url
|
||||
self.headers = {"Content-Type": "application/json", "X-GEWE-TOKEN": token}
|
||||
|
||||
async def _post_json(self, baseurl: str, route: str, payload: dict):
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f"{baseurl}{route}", headers=self.headers, json=payload
|
||||
) as resp:
|
||||
return await resp.read()
|
||||
|
||||
async def download_voice(self, appid: str, xml: str, msg_id: str):
|
||||
payload = {"appId": appid, "xml": xml, "msgId": msg_id}
|
||||
return await self._post_json(self.base_url, "/message/downloadVoice", payload)
|
||||
|
||||
async def download_image(self, appid: str, xml: str) -> str:
|
||||
"""返回一个可下载的 URL"""
|
||||
choices = [2, 3] # 2:常规图片 3:缩略图
|
||||
|
||||
for choice in choices:
|
||||
try:
|
||||
payload = {"appId": appid, "xml": xml, "type": choice}
|
||||
data = await self._post_json(
|
||||
self.base_url, "/message/downloadImage", payload
|
||||
)
|
||||
json_blob = json.loads(data)
|
||||
if "fileUrl" in json_blob["data"]:
|
||||
return self.download_base_url + json_blob["data"]["fileUrl"]
|
||||
|
||||
except BaseException as e:
|
||||
logger.error(f"gewe download image: {e}")
|
||||
continue
|
||||
|
||||
raise Exception("无法下载图片")
|
||||
|
||||
async def download_emoji_md5(self, app_id, emoji_md5):
|
||||
"""下载emoji"""
|
||||
try:
|
||||
payload = {"appId": app_id, "emojiMd5": emoji_md5}
|
||||
|
||||
# gewe 计划中的接口,暂时没有实现。返回代码404
|
||||
data = await self._post_json(
|
||||
self.base_url, "/message/downloadEmojiMd5", payload
|
||||
)
|
||||
json_blob = json.loads(data)
|
||||
return json_blob
|
||||
except BaseException as e:
|
||||
logger.error(f"gewe download emoji: {e}")
|
||||
@@ -1,264 +0,0 @@
|
||||
import asyncio
|
||||
import re
|
||||
import wave
|
||||
import uuid
|
||||
import traceback
|
||||
import os
|
||||
|
||||
from typing import AsyncGenerator
|
||||
from astrbot.core.utils.io import download_file
|
||||
from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk
|
||||
from astrbot.api import logger
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
from astrbot.api.platform import AstrBotMessage, PlatformMetadata, Group, MessageMember
|
||||
from astrbot.api.message_components import (
|
||||
Plain,
|
||||
Image,
|
||||
Record,
|
||||
At,
|
||||
File,
|
||||
Video,
|
||||
WechatEmoji as Emoji,
|
||||
)
|
||||
from .client import SimpleGewechatClient
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
def get_wav_duration(file_path):
|
||||
with wave.open(file_path, "rb") as wav_file:
|
||||
file_size = os.path.getsize(file_path)
|
||||
n_channels, sampwidth, framerate, n_frames = wav_file.getparams()[:4]
|
||||
if n_frames == 2147483647:
|
||||
duration = (file_size - 44) / (n_channels * sampwidth * framerate)
|
||||
elif n_frames == 0:
|
||||
duration = (file_size - 44) / (n_channels * sampwidth * framerate)
|
||||
else:
|
||||
duration = n_frames / float(framerate)
|
||||
return duration
|
||||
|
||||
|
||||
class GewechatPlatformEvent(AstrMessageEvent):
|
||||
def __init__(
|
||||
self,
|
||||
message_str: str,
|
||||
message_obj: AstrBotMessage,
|
||||
platform_meta: PlatformMetadata,
|
||||
session_id: str,
|
||||
client: SimpleGewechatClient,
|
||||
):
|
||||
super().__init__(message_str, message_obj, platform_meta, session_id)
|
||||
self.client = client
|
||||
|
||||
@staticmethod
|
||||
async def send_with_client(
|
||||
message: MessageChain, to_wxid: str, client: SimpleGewechatClient
|
||||
):
|
||||
if not to_wxid:
|
||||
logger.error("无法获取到 to_wxid。")
|
||||
return
|
||||
|
||||
# 检查@
|
||||
ats = []
|
||||
ats_names = []
|
||||
for comp in message.chain:
|
||||
if isinstance(comp, At):
|
||||
ats.append(comp.qq)
|
||||
ats_names.append(comp.name)
|
||||
has_at = False
|
||||
|
||||
for comp in message.chain:
|
||||
if isinstance(comp, Plain):
|
||||
text = comp.text
|
||||
payload = {
|
||||
"to_wxid": to_wxid,
|
||||
"content": text,
|
||||
}
|
||||
if not has_at and ats:
|
||||
ats = f"{','.join(ats)}"
|
||||
ats_names = f"@{' @'.join(ats_names)}"
|
||||
text = f"{ats_names} {text}"
|
||||
payload["content"] = text
|
||||
payload["ats"] = ats
|
||||
has_at = True
|
||||
await client.post_text(**payload)
|
||||
|
||||
elif isinstance(comp, Image):
|
||||
img_path = await comp.convert_to_file_path()
|
||||
# 为了安全,向 AstrBot 回调服务注册可被 gewechat 访问的文件,并获得文件 token
|
||||
token = await client._register_file(img_path)
|
||||
img_url = f"{client.file_server_url}/{token}"
|
||||
logger.debug(f"gewe callback img url: {img_url}")
|
||||
await client.post_image(to_wxid, img_url)
|
||||
elif isinstance(comp, Video):
|
||||
if comp.cover != "":
|
||||
await client.forward_video(to_wxid, comp.cover)
|
||||
else:
|
||||
try:
|
||||
from pyffmpeg import FFmpeg
|
||||
except (ImportError, ModuleNotFoundError):
|
||||
logger.error(
|
||||
"需要安装 pyffmpeg 库才能发送视频: pip install pyffmpeg"
|
||||
)
|
||||
raise ModuleNotFoundError(
|
||||
"需要安装 pyffmpeg 库才能发送视频: pip install pyffmpeg"
|
||||
)
|
||||
|
||||
video_url = comp.file
|
||||
# 根据 url 下载视频
|
||||
if video_url.startswith("http"):
|
||||
video_filename = f"{uuid.uuid4()}.mp4"
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
video_path = os.path.join(temp_dir, video_filename)
|
||||
await download_file(video_url, video_path)
|
||||
else:
|
||||
video_path = video_url
|
||||
|
||||
video_token = await client._register_file(video_path)
|
||||
video_callback_url = f"{client.file_server_url}/{video_token}"
|
||||
|
||||
# 获取视频第一帧
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
thumb_path = os.path.join(
|
||||
temp_dir, f"gewechat_video_thumb_{uuid.uuid4()}.jpg"
|
||||
)
|
||||
|
||||
video_path = video_path.replace(" ", "\\ ")
|
||||
try:
|
||||
ff = FFmpeg()
|
||||
command = f"-i {video_path} -ss 0 -vframes 1 {thumb_path}"
|
||||
ff.options(command)
|
||||
thumb_token = await client._register_file(thumb_path)
|
||||
thumb_url = f"{client.file_server_url}/{thumb_token}"
|
||||
except Exception as e:
|
||||
logger.error(f"获取视频第一帧失败: {e}")
|
||||
|
||||
# 获取视频时长
|
||||
try:
|
||||
from pyffmpeg import FFprobe
|
||||
|
||||
# 创建 FFprobe 实例
|
||||
ffprobe = FFprobe(video_url)
|
||||
# 获取时长字符串
|
||||
duration_str = ffprobe.duration
|
||||
# 处理时长字符串
|
||||
video_duration = float(duration_str.replace(":", ""))
|
||||
except Exception as e:
|
||||
logger.error(f"获取时长失败: {e}")
|
||||
video_duration = 10
|
||||
|
||||
# 发送视频
|
||||
await client.post_video(
|
||||
to_wxid, video_callback_url, thumb_url, video_duration
|
||||
)
|
||||
|
||||
# 删除临时缩略图文件
|
||||
if os.path.exists(thumb_path):
|
||||
os.remove(thumb_path)
|
||||
elif isinstance(comp, Record):
|
||||
# 默认已经存在 data/temp 中
|
||||
record_url = comp.file
|
||||
record_path = await comp.convert_to_file_path()
|
||||
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
silk_path = os.path.join(temp_dir, f"{uuid.uuid4()}.silk")
|
||||
try:
|
||||
duration = await wav_to_tencent_silk(record_path, silk_path)
|
||||
except Exception as e:
|
||||
logger.error(traceback.format_exc())
|
||||
await client.post_text(to_wxid, f"语音文件转换失败。{str(e)}")
|
||||
logger.info("Silk 语音文件格式转换至: " + record_path)
|
||||
if duration == 0:
|
||||
duration = get_wav_duration(record_path)
|
||||
token = await client._register_file(silk_path)
|
||||
record_url = f"{client.file_server_url}/{token}"
|
||||
logger.debug(f"gewe callback record url: {record_url}")
|
||||
await client.post_voice(to_wxid, record_url, duration * 1000)
|
||||
elif isinstance(comp, File):
|
||||
file_path = comp.file
|
||||
file_name = comp.name
|
||||
if file_path.startswith("file:///"):
|
||||
file_path = file_path[8:]
|
||||
elif file_path.startswith("http"):
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
temp_file_path = os.path.join(temp_dir, file_name)
|
||||
await download_file(file_path, temp_file_path)
|
||||
file_path = temp_file_path
|
||||
else:
|
||||
file_path = file_path
|
||||
|
||||
token = await client._register_file(file_path)
|
||||
file_url = f"{client.file_server_url}/{token}"
|
||||
logger.debug(f"gewe callback file url: {file_url}")
|
||||
await client.post_file(to_wxid, file_url, file_name)
|
||||
elif isinstance(comp, Emoji):
|
||||
await client.post_emoji(to_wxid, comp.md5, comp.md5_len, comp.cdnurl)
|
||||
elif isinstance(comp, At):
|
||||
pass
|
||||
else:
|
||||
logger.debug(f"gewechat 忽略: {comp.type}")
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
to_wxid = self.message_obj.raw_message.get("to_wxid", None)
|
||||
await GewechatPlatformEvent.send_with_client(message, to_wxid, self.client)
|
||||
await super().send(message)
|
||||
|
||||
async def get_group(self, group_id=None, **kwargs):
|
||||
# 确定有效的 group_id
|
||||
if group_id is None:
|
||||
group_id = self.get_group_id()
|
||||
|
||||
if not group_id:
|
||||
return None
|
||||
|
||||
res = await self.client.get_group(group_id)
|
||||
data: dict = res["data"]
|
||||
|
||||
if not data["chatroomId"]:
|
||||
return None
|
||||
|
||||
members = [
|
||||
MessageMember(user_id=member["wxid"], nickname=member["nickName"])
|
||||
for member in data.get("memberList", [])
|
||||
]
|
||||
|
||||
return Group(
|
||||
group_id=data["chatroomId"],
|
||||
group_name=data.get("nickName"),
|
||||
group_avatar=data.get("smallHeadImgUrl"),
|
||||
group_owner=data.get("chatRoomOwner"),
|
||||
members=members,
|
||||
)
|
||||
|
||||
async def send_streaming(
|
||||
self, generator: AsyncGenerator, use_fallback: bool = False
|
||||
):
|
||||
if not use_fallback:
|
||||
buffer = None
|
||||
async for chain in generator:
|
||||
if not buffer:
|
||||
buffer = chain
|
||||
else:
|
||||
buffer.chain.extend(chain.chain)
|
||||
if not buffer:
|
||||
return
|
||||
buffer.squash_plain()
|
||||
await self.send(buffer)
|
||||
return await super().send_streaming(generator, use_fallback)
|
||||
|
||||
buffer = ""
|
||||
pattern = re.compile(r"[^。?!~…]+[。?!~…]+")
|
||||
|
||||
async for chain in generator:
|
||||
if isinstance(chain, MessageChain):
|
||||
for comp in chain.chain:
|
||||
if isinstance(comp, Plain):
|
||||
buffer += comp.text
|
||||
if any(p in buffer for p in "。?!~…"):
|
||||
buffer = await self.process_buffer(buffer, pattern)
|
||||
else:
|
||||
await self.send(MessageChain(chain=[comp]))
|
||||
await asyncio.sleep(1.5) # 限速
|
||||
|
||||
if buffer.strip():
|
||||
await self.send(MessageChain([Plain(buffer)]))
|
||||
return await super().send_streaming(generator, use_fallback)
|
||||
@@ -1,103 +0,0 @@
|
||||
import sys
|
||||
import asyncio
|
||||
import os
|
||||
|
||||
from astrbot.api.platform import Platform, AstrBotMessage, MessageType, PlatformMetadata
|
||||
from astrbot.api.event import MessageChain
|
||||
from astrbot.core.platform.astr_message_event import MessageSesion
|
||||
from ...register import register_platform_adapter
|
||||
from .gewechat_event import GewechatPlatformEvent
|
||||
from .client import SimpleGewechatClient
|
||||
from astrbot import logger
|
||||
|
||||
if sys.version_info >= (3, 12):
|
||||
from typing import override
|
||||
else:
|
||||
from typing_extensions import override
|
||||
|
||||
|
||||
@register_platform_adapter("gewechat", "基于 gewechat 的 Wechat 适配器")
|
||||
class GewechatPlatformAdapter(Platform):
|
||||
def __init__(
|
||||
self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue
|
||||
) -> None:
|
||||
super().__init__(event_queue)
|
||||
self.config = platform_config
|
||||
self.settingss = platform_settings
|
||||
self.test_mode = os.environ.get("TEST_MODE", "off") == "on"
|
||||
self.client = None
|
||||
|
||||
self.client = SimpleGewechatClient(
|
||||
self.config["base_url"],
|
||||
self.config["nickname"],
|
||||
self.config["host"],
|
||||
self.config["port"],
|
||||
self._event_queue,
|
||||
)
|
||||
|
||||
async def on_event_received(abm: AstrBotMessage):
|
||||
await self.handle_msg(abm)
|
||||
|
||||
self.client.on_event_received = on_event_received
|
||||
|
||||
@override
|
||||
async def send_by_session(
|
||||
self, session: MessageSesion, message_chain: MessageChain
|
||||
):
|
||||
session_id = session.session_id
|
||||
if "#" in session_id:
|
||||
# unique session
|
||||
to_wxid = session_id.split("#")[1]
|
||||
else:
|
||||
to_wxid = session_id
|
||||
|
||||
await GewechatPlatformEvent.send_with_client(
|
||||
message_chain, to_wxid, self.client
|
||||
)
|
||||
|
||||
await super().send_by_session(session, message_chain)
|
||||
|
||||
@override
|
||||
def meta(self) -> PlatformMetadata:
|
||||
return PlatformMetadata(
|
||||
name="gewechat",
|
||||
description="基于 gewechat 的 Wechat 适配器",
|
||||
id=self.config.get("id"),
|
||||
)
|
||||
|
||||
async def terminate(self):
|
||||
self.client.shutdown_event.set()
|
||||
try:
|
||||
await self.client.server.shutdown()
|
||||
except Exception as _:
|
||||
pass
|
||||
logger.info("Gewechat 适配器已被优雅地关闭。")
|
||||
|
||||
async def logout(self):
|
||||
await self.client.logout()
|
||||
|
||||
@override
|
||||
def run(self):
|
||||
return self._run()
|
||||
|
||||
async def _run(self):
|
||||
await self.client.login()
|
||||
await self.client.start_polling()
|
||||
|
||||
async def handle_msg(self, message: AstrBotMessage):
|
||||
if message.type == MessageType.GROUP_MESSAGE:
|
||||
if self.settingss["unique_session"]:
|
||||
message.session_id = message.sender.user_id + "#" + message.group_id
|
||||
|
||||
message_event = GewechatPlatformEvent(
|
||||
message_str=message.message_str,
|
||||
message_obj=message,
|
||||
platform_meta=self.meta(),
|
||||
session_id=message.session_id,
|
||||
client=self.client,
|
||||
)
|
||||
|
||||
self.commit_event(message_event)
|
||||
|
||||
def get_client(self) -> SimpleGewechatClient:
|
||||
return self.client
|
||||
@@ -1,110 +0,0 @@
|
||||
from defusedxml import ElementTree as eT
|
||||
from astrbot.api import logger
|
||||
from astrbot.api.message_components import (
|
||||
WechatEmoji as Emoji,
|
||||
Reply,
|
||||
Plain,
|
||||
BaseMessageComponent,
|
||||
)
|
||||
|
||||
|
||||
class GeweDataParser:
|
||||
def __init__(self, data, is_private_chat):
|
||||
self.data = data
|
||||
self.is_private_chat = is_private_chat
|
||||
|
||||
def _format_to_xml(self):
|
||||
return eT.fromstring(self.data)
|
||||
|
||||
def parse_mutil_49(self) -> list[BaseMessageComponent] | None:
|
||||
appmsg_type = self._format_to_xml().find(".//appmsg/type")
|
||||
if appmsg_type is None:
|
||||
return
|
||||
|
||||
match appmsg_type.text:
|
||||
case "57":
|
||||
return self.parse_reply()
|
||||
|
||||
def parse_emoji(self) -> Emoji | None:
|
||||
try:
|
||||
emoji_element = self._format_to_xml().find(".//emoji")
|
||||
# 提取 md5 和 len 属性
|
||||
if emoji_element is not None:
|
||||
md5_value = emoji_element.get("md5")
|
||||
emoji_size = emoji_element.get("len")
|
||||
cdnurl = emoji_element.get("cdnurl")
|
||||
|
||||
return Emoji(md5=md5_value, md5_len=emoji_size, cdnurl=cdnurl)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"gewechat: parse_emoji failed, {e}")
|
||||
|
||||
def parse_reply(self) -> list[Reply, Plain] | None:
|
||||
"""解析引用消息
|
||||
|
||||
Returns:
|
||||
list[Reply, Plain]: 一个包含两个元素的列表。Reply 消息对象和引用者说的文本内容。微信平台下引用消息时只能发送文本消息。
|
||||
"""
|
||||
try:
|
||||
replied_id = -1
|
||||
replied_uid = 0
|
||||
replied_nickname = ""
|
||||
replied_content = "" # 被引用者说的内容
|
||||
content = "" # 引用者说的内容
|
||||
|
||||
root = self._format_to_xml()
|
||||
refermsg = root.find(".//refermsg")
|
||||
if refermsg is not None:
|
||||
# 被引用的信息
|
||||
svrid = refermsg.find("svrid")
|
||||
fromusr = refermsg.find("fromusr")
|
||||
displayname = refermsg.find("displayname")
|
||||
refermsg_content = refermsg.find("content")
|
||||
if svrid is not None:
|
||||
replied_id = svrid.text
|
||||
if fromusr is not None:
|
||||
replied_uid = fromusr.text
|
||||
if displayname is not None:
|
||||
replied_nickname = displayname.text
|
||||
if refermsg_content is not None:
|
||||
# 处理引用嵌套,包括嵌套公众号消息
|
||||
if refermsg_content.text.startswith(
|
||||
"<msg>"
|
||||
) or refermsg_content.text.startswith("<?xml"):
|
||||
try:
|
||||
logger.debug("gewechat: Reference message is nested")
|
||||
refer_root = eT.fromstring(refermsg_content.text)
|
||||
img = refer_root.find("img")
|
||||
if img is not None:
|
||||
replied_content = "[图片]"
|
||||
else:
|
||||
app_msg = refer_root.find("appmsg")
|
||||
refermsg_content_title = app_msg.find("title")
|
||||
logger.debug(
|
||||
f"gewechat: Reference message nesting: {refermsg_content_title.text}"
|
||||
)
|
||||
replied_content = refermsg_content_title.text
|
||||
except Exception as e:
|
||||
logger.error(f"gewechat: nested failed, {e}")
|
||||
# 处理异常情况
|
||||
replied_content = refermsg_content.text
|
||||
else:
|
||||
replied_content = refermsg_content.text
|
||||
|
||||
# 提取引用者说的内容
|
||||
title = root.find(".//appmsg/title")
|
||||
if title is not None:
|
||||
content = title.text
|
||||
|
||||
reply_seg = Reply(
|
||||
id=replied_id,
|
||||
chain=[Plain(replied_content)],
|
||||
sender_id=replied_uid,
|
||||
sender_nickname=replied_nickname,
|
||||
message_str=replied_content,
|
||||
)
|
||||
plain_seg = Plain(content)
|
||||
return [reply_seg, plain_seg]
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"gewechat: parse_reply failed, {e}")
|
||||
@@ -28,10 +28,8 @@ class QQOfficialMessageEvent(AstrMessageEvent):
|
||||
self.send_buffer = None
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
if not self.send_buffer:
|
||||
self.send_buffer = message
|
||||
else:
|
||||
self.send_buffer.chain.extend(message.chain)
|
||||
self.send_buffer = message
|
||||
await self._post_send()
|
||||
|
||||
async def send_streaming(self, generator, use_fallback: bool = False):
|
||||
"""流式输出仅支持消息列表私聊"""
|
||||
|
||||
162
astrbot/core/platform/sources/slack/client.py
Normal file
162
astrbot/core/platform/sources/slack/client.py
Normal file
@@ -0,0 +1,162 @@
|
||||
import json
|
||||
import hmac
|
||||
import hashlib
|
||||
import asyncio
|
||||
import logging
|
||||
from typing import Callable, Optional
|
||||
from quart import Quart, request, Response
|
||||
from slack_sdk.web.async_client import AsyncWebClient
|
||||
from slack_sdk.socket_mode.aiohttp import SocketModeClient
|
||||
from slack_sdk.socket_mode.request import SocketModeRequest
|
||||
from slack_sdk.socket_mode.response import SocketModeResponse
|
||||
from astrbot.api import logger
|
||||
|
||||
|
||||
class SlackWebhookClient:
|
||||
"""Slack Webhook 模式客户端,使用 Quart 作为 Web 服务器"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
web_client: AsyncWebClient,
|
||||
signing_secret: str,
|
||||
host: str = "0.0.0.0",
|
||||
port: int = 3000,
|
||||
path: str = "/slack/events",
|
||||
event_handler: Optional[Callable] = None,
|
||||
):
|
||||
self.web_client = web_client
|
||||
self.signing_secret = signing_secret
|
||||
self.host = host
|
||||
self.port = port
|
||||
self.path = path
|
||||
self.event_handler = event_handler
|
||||
|
||||
self.app = Quart(__name__)
|
||||
self._setup_routes()
|
||||
|
||||
# 禁用 Quart 的默认日志输出
|
||||
logging.getLogger("quart.app").setLevel(logging.WARNING)
|
||||
logging.getLogger("quart.serving").setLevel(logging.WARNING)
|
||||
|
||||
self.shutdown_event = asyncio.Event()
|
||||
|
||||
def _setup_routes(self):
|
||||
"""设置路由"""
|
||||
|
||||
@self.app.route(self.path, methods=["POST"])
|
||||
async def slack_events():
|
||||
"""处理 Slack 事件"""
|
||||
try:
|
||||
# 获取请求体和头部
|
||||
body = await request.get_data()
|
||||
event_data = json.loads(body.decode("utf-8"))
|
||||
|
||||
# Verify Slack request signature
|
||||
timestamp = request.headers.get("X-Slack-Request-Timestamp")
|
||||
signature = request.headers.get("X-Slack-Signature")
|
||||
if not timestamp or not signature:
|
||||
return Response("Missing headers", status=400)
|
||||
# Calculate the HMAC signature
|
||||
sig_basestring = f"v0:{timestamp}:{body.decode('utf-8')}"
|
||||
my_signature = (
|
||||
"v0="
|
||||
+ hmac.new(
|
||||
self.signing_secret.encode("utf-8"),
|
||||
sig_basestring.encode("utf-8"),
|
||||
hashlib.sha256,
|
||||
).hexdigest()
|
||||
)
|
||||
# Verify the signature
|
||||
if not hmac.compare_digest(my_signature, signature):
|
||||
logger.warning("Slack request signature verification failed")
|
||||
return Response("Invalid signature", status=400)
|
||||
logger.info(f"Received Slack event: {event_data}")
|
||||
|
||||
# 处理 URL 验证事件
|
||||
if event_data.get("type") == "url_verification":
|
||||
return {"challenge": event_data.get("challenge")}
|
||||
# 处理事件
|
||||
if self.event_handler and event_data.get("type") == "event_callback":
|
||||
await self.event_handler(event_data)
|
||||
|
||||
return Response("", status=200)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理 Slack 事件时出错: {e}")
|
||||
return Response("Internal Server Error", status=500)
|
||||
|
||||
@self.app.route("/health", methods=["GET"])
|
||||
async def health_check():
|
||||
"""健康检查端点"""
|
||||
return {"status": "ok", "service": "slack-webhook"}
|
||||
|
||||
async def start(self):
|
||||
"""启动 Webhook 服务器"""
|
||||
logger.info(
|
||||
f"Slack Webhook 服务器启动中,监听 {self.host}:{self.port}{self.path}..."
|
||||
)
|
||||
|
||||
await self.app.run_task(
|
||||
host=self.host,
|
||||
port=self.port,
|
||||
debug=False,
|
||||
shutdown_trigger=self.shutdown_trigger,
|
||||
)
|
||||
|
||||
async def shutdown_trigger(self):
|
||||
await self.shutdown_event.wait()
|
||||
|
||||
async def stop(self):
|
||||
"""停止 Webhook 服务器"""
|
||||
self.shutdown_event.set()
|
||||
logger.info("Slack Webhook 服务器已停止")
|
||||
|
||||
|
||||
class SlackSocketClient:
|
||||
"""Slack Socket 模式客户端"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
web_client: AsyncWebClient,
|
||||
app_token: str,
|
||||
event_handler: Optional[Callable] = None,
|
||||
):
|
||||
self.web_client = web_client
|
||||
self.app_token = app_token
|
||||
self.event_handler = event_handler
|
||||
self.socket_client = None
|
||||
|
||||
async def _handle_events(self, _: SocketModeClient, req: SocketModeRequest):
|
||||
"""处理 Socket Mode 事件"""
|
||||
try:
|
||||
# 确认收到事件
|
||||
response = SocketModeResponse(envelope_id=req.envelope_id)
|
||||
await self.socket_client.send_socket_mode_response(response)
|
||||
|
||||
# 处理事件
|
||||
if self.event_handler:
|
||||
await self.event_handler(req)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理 Socket Mode 事件时出错: {e}")
|
||||
|
||||
async def start(self):
|
||||
"""启动 Socket Mode 连接"""
|
||||
self.socket_client = SocketModeClient(
|
||||
app_token=self.app_token,
|
||||
logger=logger,
|
||||
web_client=self.web_client,
|
||||
)
|
||||
|
||||
# 注册事件处理器
|
||||
self.socket_client.socket_mode_request_listeners.append(self._handle_events)
|
||||
|
||||
logger.info("Slack Socket Mode 客户端启动中...")
|
||||
await self.socket_client.connect()
|
||||
|
||||
async def stop(self):
|
||||
"""停止 Socket Mode 连接"""
|
||||
if self.socket_client:
|
||||
await self.socket_client.disconnect()
|
||||
await self.socket_client.close()
|
||||
logger.info("Slack Socket Mode 客户端已停止")
|
||||
398
astrbot/core/platform/sources/slack/slack_adapter.py
Normal file
398
astrbot/core/platform/sources/slack/slack_adapter.py
Normal file
@@ -0,0 +1,398 @@
|
||||
import time
|
||||
import asyncio
|
||||
import uuid
|
||||
import aiohttp
|
||||
import re
|
||||
import base64
|
||||
from typing import Awaitable, Any
|
||||
from slack_sdk.web.async_client import AsyncWebClient
|
||||
from slack_sdk.socket_mode.request import SocketModeRequest
|
||||
from astrbot.api.platform import (
|
||||
Platform,
|
||||
AstrBotMessage,
|
||||
MessageMember,
|
||||
MessageType,
|
||||
PlatformMetadata,
|
||||
)
|
||||
from astrbot.api.event import MessageChain
|
||||
from .slack_event import SlackMessageEvent
|
||||
from .client import SlackWebhookClient, SlackSocketClient
|
||||
from astrbot.api.message_components import * # noqa: F403
|
||||
from astrbot.api import logger
|
||||
from astrbot.core.platform.astr_message_event import MessageSesion
|
||||
from ...register import register_platform_adapter
|
||||
|
||||
|
||||
@register_platform_adapter(
|
||||
"slack", "适用于 Slack 的消息平台适配器,支持 Socket Mode 和 Webhook Mode。"
|
||||
)
|
||||
class SlackAdapter(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.get("unique_session", False)
|
||||
|
||||
self.bot_token = platform_config.get("bot_token")
|
||||
self.app_token = platform_config.get("app_token")
|
||||
self.signing_secret = platform_config.get("signing_secret")
|
||||
self.connection_mode = platform_config.get("slack_connection_mode", "socket")
|
||||
self.webhook_host = platform_config.get("slack_webhook_host", "0.0.0.0")
|
||||
self.webhook_port = platform_config.get("slack_webhook_port", 3000)
|
||||
self.webhook_path = platform_config.get(
|
||||
"slack_webhook_path", "/astrbot-slack-webhook/callback"
|
||||
)
|
||||
|
||||
if not self.bot_token:
|
||||
raise ValueError("Slack bot_token 是必需的")
|
||||
|
||||
if self.connection_mode == "socket" and not self.app_token:
|
||||
raise ValueError("Socket Mode 需要 app_token")
|
||||
|
||||
if self.connection_mode == "webhook" and not self.signing_secret:
|
||||
raise ValueError("Webhook Mode 需要 signing_secret")
|
||||
|
||||
self.metadata = PlatformMetadata(
|
||||
name="slack",
|
||||
description="适用于 Slack 的消息平台适配器,支持 Socket Mode 和 Webhook Mode。",
|
||||
id=self.config.get("id"),
|
||||
)
|
||||
|
||||
# 初始化 Slack Web Client
|
||||
self.web_client = AsyncWebClient(token=self.bot_token, logger=logger)
|
||||
self.socket_client = None
|
||||
self.webhook_client = None
|
||||
|
||||
self.bot_self_id = None
|
||||
|
||||
async def send_by_session(
|
||||
self, session: MessageSesion, message_chain: MessageChain
|
||||
):
|
||||
blocks, text = SlackMessageEvent._parse_slack_blocks(
|
||||
message_chain=message_chain, web_client=self.web_client
|
||||
)
|
||||
|
||||
try:
|
||||
if session.message_type == MessageType.GROUP_MESSAGE:
|
||||
# 发送到频道
|
||||
channel_id = (
|
||||
session.session_id.split("_")[-1]
|
||||
if "_" in session.session_id
|
||||
else session.session_id
|
||||
)
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=channel_id,
|
||||
text=text,
|
||||
blocks=blocks if blocks else None,
|
||||
)
|
||||
else:
|
||||
# 发送私信
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=session.session_id,
|
||||
text=text,
|
||||
blocks=blocks if blocks else None,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Slack 发送消息失败: {e}")
|
||||
|
||||
await super().send_by_session(session, message_chain)
|
||||
|
||||
async def convert_message(self, event: dict) -> AstrBotMessage:
|
||||
logger.debug(f"[slack] RawMessage {event}")
|
||||
|
||||
abm = AstrBotMessage()
|
||||
abm.self_id = self.bot_self_id
|
||||
|
||||
# 获取用户信息
|
||||
user_id = event.get("user", "")
|
||||
try:
|
||||
user_info = await self.web_client.users_info(user=user_id)
|
||||
user_data = user_info["user"]
|
||||
user_name = user_data.get("real_name") or user_data.get("name", user_id)
|
||||
except Exception:
|
||||
user_name = user_id
|
||||
|
||||
abm.sender = MessageMember(user_id=user_id, nickname=user_name)
|
||||
|
||||
# 判断消息类型
|
||||
channel_id = event.get("channel", "")
|
||||
try:
|
||||
channel_info = await self.web_client.conversations_info(channel=channel_id)
|
||||
is_im = channel_info["channel"]["is_im"]
|
||||
|
||||
if is_im:
|
||||
abm.type = MessageType.FRIEND_MESSAGE
|
||||
else:
|
||||
abm.type = MessageType.GROUP_MESSAGE
|
||||
abm.group_id = channel_id
|
||||
except Exception:
|
||||
# 默认作为群组消息处理
|
||||
abm.type = MessageType.GROUP_MESSAGE
|
||||
abm.group_id = channel_id
|
||||
|
||||
# 设置会话ID
|
||||
if self.unique_session and abm.type == MessageType.GROUP_MESSAGE:
|
||||
abm.session_id = f"{user_id}_{channel_id}"
|
||||
else:
|
||||
abm.session_id = (
|
||||
channel_id if abm.type == MessageType.GROUP_MESSAGE else user_id
|
||||
)
|
||||
|
||||
abm.message_id = event.get("client_msg_id", uuid.uuid4().hex)
|
||||
abm.timestamp = int(float(event.get("ts", time.time())))
|
||||
|
||||
# 处理消息内容
|
||||
message_text = event.get("text", "")
|
||||
abm.message_str = message_text
|
||||
abm.message = []
|
||||
|
||||
# 优先使用 blocks 字段解析消息
|
||||
if "blocks" in event and event["blocks"]:
|
||||
abm.message = self._parse_blocks(event["blocks"])
|
||||
# 更新 message_str
|
||||
abm.message_str = ""
|
||||
for component in abm.message:
|
||||
if isinstance(component, Plain):
|
||||
abm.message_str += component.text
|
||||
elif message_text:
|
||||
# 处理传统的文本消息
|
||||
if "<@" in message_text:
|
||||
mentions = re.findall(r"<@([^>]+)>", message_text)
|
||||
for mention in mentions:
|
||||
try:
|
||||
mentioned_user = await self.web_client.users_info(user=mention)
|
||||
user_data = mentioned_user["user"]
|
||||
user_name = user_data.get("real_name") or user_data.get(
|
||||
"name", mention
|
||||
)
|
||||
abm.message.append(At(qq=mention, name=user_name))
|
||||
except Exception:
|
||||
abm.message.append(At(qq=mention, name=""))
|
||||
|
||||
# 清理消息文本中的@标记
|
||||
if clean_text := re.sub(r"<@[^>]+>", "", message_text).strip():
|
||||
abm.message.append(Plain(text=clean_text))
|
||||
else:
|
||||
abm.message.append(Plain(text=message_text))
|
||||
|
||||
# 处理文件附件
|
||||
if "files" in event:
|
||||
for file_info in event["files"]:
|
||||
file_name = file_info.get("name", "unknown")
|
||||
file_url = file_info.get("url_private", "")
|
||||
if file_info.get("mimetype", "").startswith("image/"):
|
||||
file_url = await self.get_file_base64(file_url)
|
||||
abm.message.append(Image.fromBase64(base64=file_url))
|
||||
else:
|
||||
# TODO: 下载鉴权
|
||||
abm.message.append(
|
||||
File(name=file_name, file=file_url, url=file_url)
|
||||
)
|
||||
|
||||
abm.raw_message = event
|
||||
return abm
|
||||
|
||||
def _parse_blocks(self, blocks: list) -> list:
|
||||
"""解析 Slack blocks 格式的消息内容"""
|
||||
message_components = []
|
||||
|
||||
for block in blocks:
|
||||
block_type = block.get("type", "")
|
||||
|
||||
if block_type == "rich_text":
|
||||
# 处理富文本块
|
||||
elements = block.get("elements", [])
|
||||
for element in elements:
|
||||
if element.get("type") == "rich_text_section":
|
||||
# 处理富文本段落
|
||||
section_elements = element.get("elements", [])
|
||||
text_content = ""
|
||||
|
||||
for section_element in section_elements:
|
||||
element_type = section_element.get("type", "")
|
||||
|
||||
if element_type == "text":
|
||||
# 普通文本
|
||||
text_content += section_element.get("text", "")
|
||||
elif element_type == "user":
|
||||
# @用户提及
|
||||
user_id = section_element.get("user_id", "")
|
||||
if user_id:
|
||||
# 将之前的文本内容先添加到组件中
|
||||
if text_content.strip():
|
||||
message_components.append(
|
||||
Plain(text=text_content)
|
||||
)
|
||||
text_content = ""
|
||||
# 添加@提及组件
|
||||
message_components.append(At(qq=user_id, name=""))
|
||||
elif element_type == "channel":
|
||||
# #频道提及
|
||||
channel_id = section_element.get("channel_id", "")
|
||||
text_content += f"#{channel_id}"
|
||||
elif element_type == "link":
|
||||
# 链接
|
||||
url = section_element.get("url", "")
|
||||
link_text = section_element.get("text", url)
|
||||
text_content += f"[{link_text}]({url})"
|
||||
elif element_type == "emoji":
|
||||
# 表情符号
|
||||
emoji_name = section_element.get("name", "")
|
||||
text_content += f":{emoji_name}:"
|
||||
|
||||
if text_content.strip():
|
||||
message_components.append(Plain(text=text_content))
|
||||
|
||||
elif element.get("type") == "rich_text_list":
|
||||
# 处理列表
|
||||
list_items = element.get("elements", [])
|
||||
list_text = ""
|
||||
for item in list_items:
|
||||
if item.get("type") == "rich_text_section":
|
||||
item_elements = item.get("elements", [])
|
||||
item_text = ""
|
||||
for item_element in item_elements:
|
||||
if item_element.get("type") == "text":
|
||||
item_text += item_element.get("text", "")
|
||||
list_text += f"• {item_text}\n"
|
||||
|
||||
if list_text.strip():
|
||||
message_components.append(Plain(text=list_text.strip()))
|
||||
|
||||
elif block_type == "section":
|
||||
# 处理段落块
|
||||
if "text" in block:
|
||||
text_obj = block["text"]
|
||||
if text_obj.get("type") == "mrkdwn":
|
||||
text_content = text_obj.get("text", "")
|
||||
message_components.append(Plain(text=text_content))
|
||||
|
||||
return message_components
|
||||
|
||||
async def _handle_socket_event(self, req: SocketModeRequest):
|
||||
"""处理 Socket Mode 事件"""
|
||||
if req.type == "events_api":
|
||||
# 事件 API
|
||||
event = req.payload.get("event", {})
|
||||
|
||||
# 忽略机器人自己的消息和消息编辑
|
||||
if event.get("subtype") in [
|
||||
"bot_message",
|
||||
"message_changed",
|
||||
"message_deleted",
|
||||
]:
|
||||
return
|
||||
|
||||
if event.get("bot_id"):
|
||||
return
|
||||
|
||||
if event.get("type") in ["message", "app_mention"]:
|
||||
abm = await self.convert_message(event)
|
||||
if abm:
|
||||
await self.handle_msg(abm)
|
||||
|
||||
async def get_bot_user_id(self):
|
||||
auth_info = await self.web_client.auth_test()
|
||||
return auth_info.get("user_id")
|
||||
|
||||
async def get_file_base64(self, url: str) -> str:
|
||||
"""下载 Slack 文件并返回 Base64 编码的内容"""
|
||||
headers = {"Authorization": f"Bearer {self.bot_token}"}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(url, headers=headers) as resp:
|
||||
if resp.status == 200:
|
||||
content = await resp.read()
|
||||
base64_content = base64.b64encode(content).decode("utf-8")
|
||||
return base64_content
|
||||
else:
|
||||
logger.error(
|
||||
f"Failed to download slack file: {resp.status} {await resp.text()}"
|
||||
)
|
||||
raise Exception(f"下载文件失败: {resp.status}")
|
||||
|
||||
async def run(self) -> Awaitable[Any]:
|
||||
self.bot_self_id = await self.get_bot_user_id()
|
||||
logger.info(f"Slack auth test OK. Bot ID: {self.bot_self_id}")
|
||||
|
||||
if self.connection_mode == "socket":
|
||||
if not self.app_token:
|
||||
raise ValueError("Socket Mode 需要 app_token")
|
||||
|
||||
# 创建 Socket 客户端
|
||||
self.socket_client = SlackSocketClient(
|
||||
self.web_client, self.app_token, self._handle_socket_event
|
||||
)
|
||||
|
||||
logger.info("Slack 适配器 (Socket Mode) 启动中...")
|
||||
await self.socket_client.start()
|
||||
|
||||
elif self.connection_mode == "webhook":
|
||||
if not self.signing_secret:
|
||||
raise ValueError("Webhook Mode 需要 signing_secret")
|
||||
|
||||
# 创建 Webhook 客户端
|
||||
self.webhook_client = SlackWebhookClient(
|
||||
self.web_client,
|
||||
self.signing_secret,
|
||||
self.webhook_host,
|
||||
self.webhook_port,
|
||||
self.webhook_path,
|
||||
self._handle_webhook_event,
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"Slack 适配器 (Webhook Mode) 启动中,监听 {self.webhook_host}:{self.webhook_port}{self.webhook_path}..."
|
||||
)
|
||||
await self.webhook_client.start()
|
||||
|
||||
else:
|
||||
raise ValueError(
|
||||
f"不支持的连接模式: {self.connection_mode},请使用 'socket' 或 'webhook'"
|
||||
)
|
||||
|
||||
async def _handle_webhook_event(self, event_data: dict):
|
||||
"""处理 Webhook 事件"""
|
||||
event = event_data.get("event", {})
|
||||
|
||||
# 忽略机器人自己的消息和消息编辑
|
||||
if event.get("subtype") in [
|
||||
"bot_message",
|
||||
"message_changed",
|
||||
"message_deleted",
|
||||
]:
|
||||
return
|
||||
|
||||
if event.get("bot_id"):
|
||||
return
|
||||
|
||||
if event.get("type") in ["message", "app_mention"]:
|
||||
abm = await self.convert_message(event)
|
||||
if abm:
|
||||
await self.handle_msg(abm)
|
||||
|
||||
async def terminate(self):
|
||||
if self.socket_client:
|
||||
await self.socket_client.stop()
|
||||
if self.webhook_client:
|
||||
await self.webhook_client.stop()
|
||||
logger.info("Slack 适配器已被优雅地关闭")
|
||||
|
||||
def meta(self) -> PlatformMetadata:
|
||||
return self.metadata
|
||||
|
||||
async def handle_msg(self, message: AstrBotMessage):
|
||||
message_event = SlackMessageEvent(
|
||||
message_str=message.message_str,
|
||||
message_obj=message,
|
||||
platform_meta=self.meta(),
|
||||
session_id=message.session_id,
|
||||
web_client=self.web_client,
|
||||
)
|
||||
|
||||
self.commit_event(message_event)
|
||||
|
||||
def get_client(self):
|
||||
return self.web_client
|
||||
243
astrbot/core/platform/sources/slack/slack_event.py
Normal file
243
astrbot/core/platform/sources/slack/slack_event.py
Normal file
@@ -0,0 +1,243 @@
|
||||
import asyncio
|
||||
import re
|
||||
from typing import AsyncGenerator
|
||||
from slack_sdk.web.async_client import AsyncWebClient
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
from astrbot.api.message_components import (
|
||||
Image,
|
||||
Plain,
|
||||
File,
|
||||
BaseMessageComponent,
|
||||
)
|
||||
from astrbot.api.platform import Group, MessageMember
|
||||
from astrbot.api import logger
|
||||
|
||||
|
||||
class SlackMessageEvent(AstrMessageEvent):
|
||||
def __init__(
|
||||
self,
|
||||
message_str,
|
||||
message_obj,
|
||||
platform_meta,
|
||||
session_id,
|
||||
web_client: AsyncWebClient,
|
||||
):
|
||||
super().__init__(message_str, message_obj, platform_meta, session_id)
|
||||
self.web_client = web_client
|
||||
|
||||
@staticmethod
|
||||
async def _from_segment_to_slack_block(
|
||||
segment: BaseMessageComponent, web_client: AsyncWebClient
|
||||
) -> dict:
|
||||
"""将消息段转换为 Slack 块格式"""
|
||||
if isinstance(segment, Plain):
|
||||
return {"type": "section", "text": {"type": "mrkdwn", "text": segment.text}}
|
||||
elif isinstance(segment, Image):
|
||||
# upload file
|
||||
url = segment.url or segment.file
|
||||
if url.startswith("http"):
|
||||
return {
|
||||
"type": "image",
|
||||
"image_url": url,
|
||||
"alt_text": "图片",
|
||||
}
|
||||
path = await segment.convert_to_file_path()
|
||||
response = await web_client.files_upload_v2(
|
||||
file=path,
|
||||
filename="image.jpg",
|
||||
)
|
||||
if not response["ok"]:
|
||||
logger.error(f"Slack file upload failed: {response['error']}")
|
||||
return {
|
||||
"type": "section",
|
||||
"text": {"type": "mrkdwn", "text": "图片上传失败"},
|
||||
}
|
||||
image_url = response["files"][0]["url_private"]
|
||||
logger.debug(f"Slack file upload response: {response}")
|
||||
return {
|
||||
"type": "image",
|
||||
"slack_file": {
|
||||
"url": image_url,
|
||||
},
|
||||
"alt_text": "图片",
|
||||
}
|
||||
elif isinstance(segment, File):
|
||||
# upload file
|
||||
url = segment.url or segment.file
|
||||
response = await web_client.files_upload_v2(
|
||||
file=url,
|
||||
filename=segment.name or "file",
|
||||
)
|
||||
if not response["ok"]:
|
||||
logger.error(f"Slack file upload failed: {response['error']}")
|
||||
return {
|
||||
"type": "section",
|
||||
"text": {"type": "mrkdwn", "text": "文件上传失败"},
|
||||
}
|
||||
file_url = response["files"][0]["permalink"]
|
||||
return {
|
||||
"type": "section",
|
||||
"text": {
|
||||
"type": "mrkdwn",
|
||||
"text": f"文件: <{file_url}|{segment.name or '文件'}>",
|
||||
},
|
||||
}
|
||||
else:
|
||||
return {"type": "section", "text": {"type": "mrkdwn", "text": str(segment)}}
|
||||
|
||||
@staticmethod
|
||||
async def _parse_slack_blocks(
|
||||
message_chain: MessageChain, web_client: AsyncWebClient
|
||||
):
|
||||
"""解析成 Slack 块格式"""
|
||||
blocks = []
|
||||
text_content = ""
|
||||
|
||||
for segment in message_chain.chain:
|
||||
if isinstance(segment, Plain):
|
||||
text_content += segment.text
|
||||
else:
|
||||
# 如果有文本内容,先添加文本块
|
||||
if text_content.strip():
|
||||
blocks.append(
|
||||
{
|
||||
"type": "section",
|
||||
"text": {"type": "mrkdwn", "text": text_content},
|
||||
}
|
||||
)
|
||||
text_content = ""
|
||||
|
||||
# 添加其他类型的块
|
||||
block = await SlackMessageEvent._from_segment_to_slack_block(
|
||||
segment, web_client
|
||||
)
|
||||
blocks.append(block)
|
||||
|
||||
# 如果最后还有文本内容
|
||||
if text_content.strip():
|
||||
blocks.append(
|
||||
{"type": "section", "text": {"type": "mrkdwn", "text": text_content}}
|
||||
)
|
||||
|
||||
return blocks, "" if blocks else text_content
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
blocks, text = await SlackMessageEvent._parse_slack_blocks(
|
||||
message, self.web_client
|
||||
)
|
||||
|
||||
try:
|
||||
if self.get_group_id():
|
||||
# 发送到频道
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=self.get_group_id(),
|
||||
text=text,
|
||||
blocks=blocks or None,
|
||||
)
|
||||
else:
|
||||
# 发送私信
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=self.get_sender_id(),
|
||||
text=text,
|
||||
blocks=blocks or None,
|
||||
)
|
||||
except Exception:
|
||||
# 如果块发送失败,尝试只发送文本
|
||||
fallback_text = ""
|
||||
for segment in message.chain:
|
||||
if isinstance(segment, Plain):
|
||||
fallback_text += segment.text
|
||||
elif isinstance(segment, File):
|
||||
fallback_text += f" [文件: {segment.name}] "
|
||||
elif isinstance(segment, Image):
|
||||
fallback_text += " [图片] "
|
||||
|
||||
if self.get_group_id():
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=self.get_group_id(), text=fallback_text
|
||||
)
|
||||
else:
|
||||
await self.web_client.chat_postMessage(
|
||||
channel=self.get_sender_id(), text=fallback_text
|
||||
)
|
||||
|
||||
await super().send(message)
|
||||
|
||||
async def send_streaming(
|
||||
self, generator: AsyncGenerator, use_fallback: bool = False
|
||||
):
|
||||
if not use_fallback:
|
||||
buffer = None
|
||||
async for chain in generator:
|
||||
if not buffer:
|
||||
buffer = chain
|
||||
else:
|
||||
buffer.chain.extend(chain.chain)
|
||||
if not buffer:
|
||||
return
|
||||
buffer.squash_plain()
|
||||
await self.send(buffer)
|
||||
return await super().send_streaming(generator, use_fallback)
|
||||
|
||||
buffer = ""
|
||||
pattern = re.compile(r"[^。?!~…]+[。?!~…]+")
|
||||
|
||||
async for chain in generator:
|
||||
if isinstance(chain, MessageChain):
|
||||
for comp in chain.chain:
|
||||
if isinstance(comp, Plain):
|
||||
buffer += comp.text
|
||||
if any(p in buffer for p in "。?!~…"):
|
||||
buffer = await self.process_buffer(buffer, pattern)
|
||||
else:
|
||||
await self.send(MessageChain(chain=[comp]))
|
||||
await asyncio.sleep(1.5) # 限速
|
||||
|
||||
if buffer.strip():
|
||||
await self.send(MessageChain([Plain(buffer)]))
|
||||
return await super().send_streaming(generator, use_fallback)
|
||||
|
||||
async def get_group(self, group_id=None, **kwargs):
|
||||
if group_id:
|
||||
channel_id = group_id
|
||||
elif self.get_group_id():
|
||||
channel_id = self.get_group_id()
|
||||
else:
|
||||
return None
|
||||
|
||||
try:
|
||||
# 获取频道信息
|
||||
channel_info = await self.web_client.conversations_info(channel=channel_id)
|
||||
|
||||
# 获取频道成员
|
||||
members_response = await self.web_client.conversations_members(
|
||||
channel=channel_id
|
||||
)
|
||||
|
||||
members = []
|
||||
for member_id in members_response["members"]:
|
||||
try:
|
||||
user_info = await self.web_client.users_info(user=member_id)
|
||||
user_data = user_info["user"]
|
||||
members.append(
|
||||
MessageMember(
|
||||
user_id=member_id,
|
||||
nickname=user_data.get("real_name")
|
||||
or user_data.get("name", member_id),
|
||||
)
|
||||
)
|
||||
except Exception:
|
||||
# 如果获取用户信息失败,使用默认信息
|
||||
members.append(MessageMember(user_id=member_id, nickname=member_id))
|
||||
|
||||
channel_data = channel_info["channel"]
|
||||
return Group(
|
||||
group_id=channel_id,
|
||||
group_name=channel_data.get("name", ""),
|
||||
group_avatar="",
|
||||
group_admins=[], # Slack 的管理员信息需要特殊权限获取
|
||||
group_owner=channel_data.get("creator", ""),
|
||||
members=members,
|
||||
)
|
||||
except Exception:
|
||||
return None
|
||||
@@ -144,8 +144,8 @@ class TelegramPlatformAdapter(Platform):
|
||||
command_dict = {}
|
||||
skip_commands = {"start"}
|
||||
|
||||
for handler_md in star_handlers_registry._handlers:
|
||||
handler_metadata = handler_md[1]
|
||||
for handler_md in star_handlers_registry:
|
||||
handler_metadata = handler_md
|
||||
if not star_map[handler_metadata.handler_module_path].activated:
|
||||
continue
|
||||
for event_filter in handler_metadata.event_filters:
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import os
|
||||
import re
|
||||
import asyncio
|
||||
import telegramify_markdown
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
@@ -18,6 +19,16 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class TelegramPlatformEvent(AstrMessageEvent):
|
||||
# Telegram 的最大消息长度限制
|
||||
MAX_MESSAGE_LENGTH = 4096
|
||||
|
||||
SPLIT_PATTERNS = {
|
||||
"paragraph": re.compile(r"\n\n"),
|
||||
"line": re.compile(r"\n"),
|
||||
"sentence": re.compile(r"[.!?。!?]"),
|
||||
"word": re.compile(r"\s"),
|
||||
}
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
message_str: str,
|
||||
@@ -29,8 +40,35 @@ class TelegramPlatformEvent(AstrMessageEvent):
|
||||
super().__init__(message_str, message_obj, platform_meta, session_id)
|
||||
self.client = client
|
||||
|
||||
@staticmethod
|
||||
async def send_with_client(client: ExtBot, message: MessageChain, user_name: str):
|
||||
@classmethod
|
||||
def _split_message(cls, text: str) -> list[str]:
|
||||
if len(text) <= cls.MAX_MESSAGE_LENGTH:
|
||||
return [text]
|
||||
|
||||
chunks = []
|
||||
while text:
|
||||
if len(text) <= cls.MAX_MESSAGE_LENGTH:
|
||||
chunks.append(text)
|
||||
break
|
||||
|
||||
split_point = cls.MAX_MESSAGE_LENGTH
|
||||
segment = text[: cls.MAX_MESSAGE_LENGTH]
|
||||
|
||||
for _, pattern in cls.SPLIT_PATTERNS.items():
|
||||
if matches := list(pattern.finditer(segment)):
|
||||
last_match = matches[-1]
|
||||
split_point = last_match.end()
|
||||
break
|
||||
|
||||
chunks.append(text[:split_point])
|
||||
text = text[split_point:].lstrip()
|
||||
|
||||
return chunks
|
||||
|
||||
@classmethod
|
||||
async def send_with_client(
|
||||
cls, client: ExtBot, message: MessageChain, user_name: str
|
||||
):
|
||||
image_path = None
|
||||
|
||||
has_reply = False
|
||||
@@ -59,19 +97,22 @@ class TelegramPlatformEvent(AstrMessageEvent):
|
||||
|
||||
if isinstance(i, Plain):
|
||||
if at_user_id and not at_flag:
|
||||
i.text = f"@{at_user_id} " + i.text
|
||||
i.text = f"@{at_user_id} {i.text}"
|
||||
at_flag = True
|
||||
text = i.text
|
||||
try:
|
||||
text = telegramify_markdown.markdownify(
|
||||
i.text, max_line_length=None, normalize_whitespace=False
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
f"MarkdownV2 conversion failed: {e}. Using plain text instead."
|
||||
)
|
||||
return
|
||||
await client.send_message(text=text, parse_mode="MarkdownV2", **payload)
|
||||
chunks = cls._split_message(i.text)
|
||||
for chunk in chunks:
|
||||
try:
|
||||
md_text = telegramify_markdown.markdownify(
|
||||
chunk, max_line_length=None, normalize_whitespace=False
|
||||
)
|
||||
await client.send_message(
|
||||
text=md_text, parse_mode="MarkdownV2", **payload
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
f"MarkdownV2 send failed: {e}. Using plain text instead."
|
||||
)
|
||||
await client.send_message(text=chunk, **payload)
|
||||
elif isinstance(i, Image):
|
||||
image_path = await i.convert_to_file_path()
|
||||
await client.send_photo(photo=image_path, **payload)
|
||||
@@ -119,6 +160,12 @@ class TelegramPlatformEvent(AstrMessageEvent):
|
||||
|
||||
async for chain in generator:
|
||||
if isinstance(chain, MessageChain):
|
||||
if chain.type == "break":
|
||||
# 分割符
|
||||
message_id = None # 重置消息 ID
|
||||
delta = "" # 重置 delta
|
||||
continue
|
||||
|
||||
# 处理消息链中的每个组件
|
||||
for i in chain.chain:
|
||||
if isinstance(i, Plain):
|
||||
@@ -147,17 +194,7 @@ class TelegramPlatformEvent(AstrMessageEvent):
|
||||
continue
|
||||
|
||||
# Plain
|
||||
if not message_id:
|
||||
try:
|
||||
msg = await self.client.send_message(text=delta, **payload)
|
||||
current_content = delta
|
||||
except Exception as e:
|
||||
logger.warning(f"发送消息失败(streaming): {e!s}")
|
||||
message_id = msg.message_id
|
||||
last_edit_time = (
|
||||
asyncio.get_event_loop().time()
|
||||
) # 记录初始消息发送时间
|
||||
else:
|
||||
if message_id and len(delta) <= self.MAX_MESSAGE_LENGTH:
|
||||
current_time = asyncio.get_event_loop().time()
|
||||
time_since_last_edit = current_time - last_edit_time
|
||||
|
||||
@@ -176,6 +213,18 @@ class TelegramPlatformEvent(AstrMessageEvent):
|
||||
last_edit_time = (
|
||||
asyncio.get_event_loop().time()
|
||||
) # 更新上次编辑的时间
|
||||
else:
|
||||
# delta 长度一般不会大于 4096,因此这里直接发送
|
||||
try:
|
||||
msg = await self.client.send_message(text=delta, **payload)
|
||||
current_content = delta
|
||||
delta = ""
|
||||
except Exception as e:
|
||||
logger.warning(f"发送消息失败(streaming): {e!s}")
|
||||
message_id = msg.message_id
|
||||
last_edit_time = (
|
||||
asyncio.get_event_loop().time()
|
||||
) # 记录初始消息发送时间
|
||||
|
||||
try:
|
||||
if delta and current_content != delta:
|
||||
|
||||
@@ -2,7 +2,7 @@ import time
|
||||
import asyncio
|
||||
import uuid
|
||||
import os
|
||||
from typing import Awaitable, Any
|
||||
from typing import Awaitable, Any, Callable
|
||||
from astrbot.core.platform import (
|
||||
Platform,
|
||||
AstrBotMessage,
|
||||
@@ -13,7 +13,7 @@ from astrbot.core.platform import (
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from astrbot.core.message.components import Plain, Image, Record # noqa: F403
|
||||
from astrbot import logger
|
||||
from astrbot.core import web_chat_queue
|
||||
from .webchat_queue_mgr import webchat_queue_mgr, WebChatQueueMgr
|
||||
from .webchat_event import WebChatMessageEvent
|
||||
from astrbot.core.platform.astr_message_event import MessageSesion
|
||||
from ...register import register_platform_adapter
|
||||
@@ -21,14 +21,46 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class QueueListener:
|
||||
def __init__(self, queue: asyncio.Queue, callback: callable) -> None:
|
||||
self.queue = queue
|
||||
def __init__(self, webchat_queue_mgr: WebChatQueueMgr, callback: Callable) -> None:
|
||||
self.webchat_queue_mgr = webchat_queue_mgr
|
||||
self.callback = callback
|
||||
self.running_tasks = set()
|
||||
|
||||
async def listen_to_queue(self, conversation_id: str):
|
||||
"""Listen to a specific conversation queue"""
|
||||
queue = self.webchat_queue_mgr.get_or_create_queue(conversation_id)
|
||||
while True:
|
||||
try:
|
||||
data = await queue.get()
|
||||
await self.callback(data)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Error processing message from conversation {conversation_id}: {e}"
|
||||
)
|
||||
break
|
||||
|
||||
async def run(self):
|
||||
"""Monitor for new conversation queues and start listeners"""
|
||||
monitored_conversations = set()
|
||||
|
||||
while True:
|
||||
data = await self.queue.get()
|
||||
await self.callback(data)
|
||||
# Check for new conversations
|
||||
current_conversations = set(self.webchat_queue_mgr.queues.keys())
|
||||
new_conversations = current_conversations - monitored_conversations
|
||||
|
||||
# Start listeners for new conversations
|
||||
for conversation_id in new_conversations:
|
||||
task = asyncio.create_task(self.listen_to_queue(conversation_id))
|
||||
self.running_tasks.add(task)
|
||||
task.add_done_callback(self.running_tasks.discard)
|
||||
monitored_conversations.add(conversation_id)
|
||||
logger.debug(f"Started listener for conversation: {conversation_id}")
|
||||
|
||||
# Clean up monitored conversations that no longer exist
|
||||
removed_conversations = monitored_conversations - current_conversations
|
||||
monitored_conversations -= removed_conversations
|
||||
|
||||
await asyncio.sleep(1) # Check for new conversations every second
|
||||
|
||||
|
||||
@register_platform_adapter("webchat", "webchat")
|
||||
@@ -45,7 +77,7 @@ class WebChatAdapter(Platform):
|
||||
os.makedirs(self.imgs_dir, exist_ok=True)
|
||||
|
||||
self.metadata = PlatformMetadata(
|
||||
name="webchat", description="webchat", id=self.config.get("id")
|
||||
name="webchat", description="webchat", id=self.config.get("id", "")
|
||||
)
|
||||
|
||||
async def send_by_session(
|
||||
@@ -105,7 +137,7 @@ class WebChatAdapter(Platform):
|
||||
abm = await self.convert_message(data)
|
||||
await self.handle_msg(abm)
|
||||
|
||||
bot = QueueListener(web_chat_queue, callback)
|
||||
bot = QueueListener(webchat_queue_mgr, callback)
|
||||
return bot.run()
|
||||
|
||||
def meta(self) -> PlatformMetadata:
|
||||
@@ -119,6 +151,10 @@ class WebChatAdapter(Platform):
|
||||
session_id=message.session_id,
|
||||
)
|
||||
|
||||
_, _, payload = message.raw_message # type: ignore
|
||||
message_event.set_extra("selected_provider", payload.get("selected_provider"))
|
||||
message_event.set_extra("selected_model", payload.get("selected_model"))
|
||||
|
||||
self.commit_event(message_event)
|
||||
|
||||
async def terminate(self):
|
||||
|
||||
@@ -5,8 +5,8 @@ from astrbot.api import logger
|
||||
from astrbot.api.event import AstrMessageEvent, MessageChain
|
||||
from astrbot.api.message_components import Plain, Image, Record
|
||||
from astrbot.core.utils.io import download_image_by_url
|
||||
from astrbot.core import web_chat_back_queue
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
from .webchat_queue_mgr import webchat_queue_mgr
|
||||
|
||||
imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
|
||||
|
||||
@@ -18,13 +18,18 @@ class WebChatMessageEvent(AstrMessageEvent):
|
||||
|
||||
@staticmethod
|
||||
async def _send(message: MessageChain, session_id: str, streaming: bool = False):
|
||||
cid = session_id.split("!")[-1]
|
||||
web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
|
||||
if not message:
|
||||
await web_chat_back_queue.put(
|
||||
{"type": "end", "data": "", "streaming": False}
|
||||
{
|
||||
"type": "end",
|
||||
"data": "",
|
||||
"streaming": False,
|
||||
} # end means this request is finished
|
||||
)
|
||||
return ""
|
||||
|
||||
cid = session_id.split("!")[-1]
|
||||
data = ""
|
||||
for comp in message.chain:
|
||||
if isinstance(comp, Plain):
|
||||
@@ -35,6 +40,7 @@ class WebChatMessageEvent(AstrMessageEvent):
|
||||
"cid": cid,
|
||||
"data": data,
|
||||
"streaming": streaming,
|
||||
"chain_type": message.type,
|
||||
}
|
||||
)
|
||||
elif isinstance(comp, Image):
|
||||
@@ -97,29 +103,35 @@ class WebChatMessageEvent(AstrMessageEvent):
|
||||
|
||||
async def send(self, message: MessageChain):
|
||||
await WebChatMessageEvent._send(message, session_id=self.session_id)
|
||||
await web_chat_back_queue.put(
|
||||
{
|
||||
"type": "end",
|
||||
"data": "",
|
||||
"streaming": False,
|
||||
"cid": self.session_id.split("!")[-1],
|
||||
}
|
||||
)
|
||||
await super().send(message)
|
||||
|
||||
async def send_streaming(self, generator, use_fallback: bool = False):
|
||||
final_data = ""
|
||||
cid = self.session_id.split("!")[-1]
|
||||
web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
|
||||
async for chain in generator:
|
||||
if chain.type == "break" and final_data:
|
||||
# 分割符
|
||||
await web_chat_back_queue.put(
|
||||
{
|
||||
"type": "break", # break means a segment end
|
||||
"data": final_data,
|
||||
"streaming": True,
|
||||
"cid": cid,
|
||||
}
|
||||
)
|
||||
final_data = ""
|
||||
continue
|
||||
final_data += await WebChatMessageEvent._send(
|
||||
chain, session_id=self.session_id, streaming=True
|
||||
)
|
||||
|
||||
await web_chat_back_queue.put(
|
||||
{
|
||||
"type": "end",
|
||||
"type": "complete", # complete means we return the final result
|
||||
"data": final_data,
|
||||
"streaming": True,
|
||||
"cid": self.session_id.split("!")[-1],
|
||||
"cid": cid,
|
||||
}
|
||||
)
|
||||
await super().send_streaming(generator, use_fallback)
|
||||
|
||||
35
astrbot/core/platform/sources/webchat/webchat_queue_mgr.py
Normal file
35
astrbot/core/platform/sources/webchat/webchat_queue_mgr.py
Normal file
@@ -0,0 +1,35 @@
|
||||
import asyncio
|
||||
|
||||
|
||||
class WebChatQueueMgr:
|
||||
def __init__(self) -> None:
|
||||
self.queues = {}
|
||||
"""Conversation ID to asyncio.Queue mapping"""
|
||||
self.back_queues = {}
|
||||
"""Conversation ID to asyncio.Queue mapping for responses"""
|
||||
|
||||
def get_or_create_queue(self, conversation_id: str) -> asyncio.Queue:
|
||||
"""Get or create a queue for the given conversation ID"""
|
||||
if conversation_id not in self.queues:
|
||||
self.queues[conversation_id] = asyncio.Queue()
|
||||
return self.queues[conversation_id]
|
||||
|
||||
def get_or_create_back_queue(self, conversation_id: str) -> asyncio.Queue:
|
||||
"""Get or create a back queue for the given conversation ID"""
|
||||
if conversation_id not in self.back_queues:
|
||||
self.back_queues[conversation_id] = asyncio.Queue()
|
||||
return self.back_queues[conversation_id]
|
||||
|
||||
def remove_queues(self, conversation_id: str):
|
||||
"""Remove queues for the given conversation ID"""
|
||||
if conversation_id in self.queues:
|
||||
del self.queues[conversation_id]
|
||||
if conversation_id in self.back_queues:
|
||||
del self.back_queues[conversation_id]
|
||||
|
||||
def has_queue(self, conversation_id: str) -> bool:
|
||||
"""Check if a queue exists for the given conversation ID"""
|
||||
return conversation_id in self.queues
|
||||
|
||||
|
||||
webchat_queue_mgr = WebChatQueueMgr()
|
||||
@@ -1,14 +1,16 @@
|
||||
import asyncio
|
||||
import base64
|
||||
import json
|
||||
import os
|
||||
import traceback
|
||||
import time
|
||||
from typing import Optional
|
||||
|
||||
import aiohttp
|
||||
import anyio
|
||||
import websockets
|
||||
|
||||
from astrbot import logger
|
||||
from astrbot.api.message_components import Plain, Image
|
||||
from astrbot.api.message_components import Plain, Image, At, Record
|
||||
from astrbot.api.platform import Platform, PlatformMetadata
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from astrbot.core.platform.astrbot_message import (
|
||||
@@ -22,6 +24,13 @@ from astrbot.core.platform.astr_message_event import MessageSesion
|
||||
from ...register import register_platform_adapter
|
||||
from .wechatpadpro_message_event import WeChatPadProMessageEvent
|
||||
|
||||
try:
|
||||
from .xml_data_parser import GeweDataParser
|
||||
except ImportError as e:
|
||||
logger.warning(
|
||||
f"警告: 可能未安装 defusedxml 依赖库,将导致无法解析微信的 表情包、引用 类型的消息: {str(e)}"
|
||||
)
|
||||
|
||||
|
||||
@register_platform_adapter("wechatpadpro", "WeChatPadPro 消息平台适配器")
|
||||
class WeChatPadProAdapter(Platform):
|
||||
@@ -59,6 +68,18 @@ class WeChatPadProAdapter(Platform):
|
||||
) # 持久化文件路径
|
||||
self.ws_handle_task = None
|
||||
|
||||
# 添加图片消息缓存,用于引用消息处理
|
||||
self.cached_images = {}
|
||||
"""缓存图片消息。key是NewMsgId (对应引用消息的svrid),value是图片的base64数据"""
|
||||
# 设置缓存大小限制,避免内存占用过大
|
||||
self.max_image_cache = 50
|
||||
|
||||
# 添加文本消息缓存,用于引用消息处理
|
||||
self.cached_texts = {}
|
||||
"""缓存文本消息。key是NewMsgId (对应引用消息的svrid),value是消息文本内容"""
|
||||
# 设置文本缓存大小限制
|
||||
self.max_text_cache = 100
|
||||
|
||||
async def run(self) -> None:
|
||||
"""
|
||||
启动平台适配器的运行实例。
|
||||
@@ -102,7 +123,7 @@ class WeChatPadProAdapter(Platform):
|
||||
logger.warning("登录失败或超时,WeChatPadPro 适配器将关闭。")
|
||||
await self.terminate()
|
||||
return
|
||||
|
||||
|
||||
# 登录成功后,连接 WebSocket 接收消息
|
||||
self.ws_handle_task = asyncio.create_task(self.connect_websocket())
|
||||
|
||||
@@ -138,7 +159,6 @@ class WeChatPadProAdapter(Platform):
|
||||
os.makedirs(data_dir, exist_ok=True)
|
||||
with open(self.credentials_file, "w") as f:
|
||||
json.dump(credentials, f)
|
||||
logger.info("成功保存 WeChatPadPro 凭据。")
|
||||
except Exception as e:
|
||||
logger.error(f"保存 WeChatPadPro 凭据失败: {e}")
|
||||
|
||||
@@ -146,6 +166,8 @@ class WeChatPadProAdapter(Platform):
|
||||
"""
|
||||
检查 WeChatPadPro 设备是否在线。
|
||||
"""
|
||||
if not self.auth_key:
|
||||
return False
|
||||
url = f"{self.base_url}/login/GetLoginStatus"
|
||||
params = {"key": self.auth_key}
|
||||
|
||||
@@ -161,34 +183,43 @@ class WeChatPadProAdapter(Platform):
|
||||
return True
|
||||
# login_state == 3 为离线状态
|
||||
elif login_state == 3:
|
||||
logger.info(
|
||||
"WeChatPadPro 设备不在线。"
|
||||
)
|
||||
logger.info("WeChatPadPro 设备不在线。")
|
||||
return False
|
||||
else:
|
||||
logger.error(
|
||||
f"未知的在线状态: {login_state:}"
|
||||
)
|
||||
logger.error(f"未知的在线状态: {response_data}")
|
||||
return False
|
||||
# Code == 300 为微信退出状态。
|
||||
elif response.status == 200 and response_data.get("Code") == 300:
|
||||
logger.info(
|
||||
"WeChatPadPro 设备已退出。"
|
||||
)
|
||||
logger.info("WeChatPadPro 设备已退出。")
|
||||
return False
|
||||
elif response.status == 200 and response_data.get("Code") == -2:
|
||||
# 该链接不存在
|
||||
self.auth_key = None
|
||||
return False
|
||||
else:
|
||||
logger.error(
|
||||
f"检查在线状态失败: {response.status}, {response_data}"
|
||||
)
|
||||
return False
|
||||
|
||||
|
||||
except aiohttp.ClientConnectorError as e:
|
||||
logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"检查在线状态时发生错误: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
return False
|
||||
|
||||
def _extract_auth_key(self, data):
|
||||
"""Helper method to extract auth_key from response data."""
|
||||
if isinstance(data, dict):
|
||||
auth_keys = data.get("authKeys") # 新接口
|
||||
if isinstance(auth_keys, list) and auth_keys:
|
||||
return auth_keys[0]
|
||||
elif isinstance(data, list) and data: # 旧接口
|
||||
return data[0]
|
||||
return None
|
||||
|
||||
async def generate_auth_key(self):
|
||||
"""
|
||||
生成授权码。
|
||||
@@ -197,28 +228,30 @@ class WeChatPadProAdapter(Platform):
|
||||
params = {"key": self.admin_key}
|
||||
payload = {"Count": 1, "Days": 365} # 生成一个有效期365天的授权码
|
||||
|
||||
self.auth_key = None # Reset auth_key before generating a new one
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
try:
|
||||
async with session.post(url, params=params, json=payload) as response:
|
||||
if response.status != 200:
|
||||
logger.error(
|
||||
f"生成授权码失败: {response.status}, {await response.text()}"
|
||||
)
|
||||
return
|
||||
|
||||
response_data = await response.json()
|
||||
# 修正成功判断条件和授权码提取路径
|
||||
if response.status == 200 and response_data.get("Code") == 200:
|
||||
# 授权码在 Data 字段的列表中
|
||||
if (
|
||||
response_data.get("Data")
|
||||
and isinstance(response_data["Data"], list)
|
||||
and len(response_data["Data"]) > 0
|
||||
):
|
||||
self.auth_key = response_data["Data"][0]
|
||||
if response_data.get("Code") == 200:
|
||||
if data := response_data.get("Data"):
|
||||
self.auth_key = self._extract_auth_key(data)
|
||||
|
||||
if self.auth_key:
|
||||
logger.info("成功获取授权码")
|
||||
else:
|
||||
logger.error(
|
||||
f"生成授权码成功但未找到授权码: {response_data}"
|
||||
)
|
||||
else:
|
||||
logger.error(
|
||||
f"生成授权码失败: {response.status}, {response_data}"
|
||||
)
|
||||
logger.error(f"生成授权码失败: {response_data}")
|
||||
except aiohttp.ClientConnectorError as e:
|
||||
logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
|
||||
except Exception as e:
|
||||
@@ -236,7 +269,6 @@ class WeChatPadProAdapter(Platform):
|
||||
try:
|
||||
async with session.post(url, params=params, json=payload) as response:
|
||||
response_data = await response.json()
|
||||
# 修正成功判断条件和数据提取路径
|
||||
if response.status == 200 and response_data.get("Code") == 200:
|
||||
# 二维码地址在 Data.QrCodeUrl 字段中
|
||||
if response_data.get("Data") and response_data["Data"].get(
|
||||
@@ -248,6 +280,13 @@ class WeChatPadProAdapter(Platform):
|
||||
f"获取登录二维码成功但未找到二维码地址: {response_data}"
|
||||
)
|
||||
return None
|
||||
elif "该 key 无效" in response_data.get("Text"):
|
||||
logger.error(
|
||||
"授权码无效,已经清除。请重新启动 AstrBot 或者本消息适配器。原因也可能是 WeChatPadPro 的 MySQL 服务没有启动成功,请检查 WeChatPadPro 服务的日志。"
|
||||
)
|
||||
self.auth_key = None
|
||||
self.save_credentials()
|
||||
return None
|
||||
else:
|
||||
logger.error(
|
||||
f"获取登录二维码失败: {response.status}, {response_data}"
|
||||
@@ -340,7 +379,7 @@ class WeChatPadProAdapter(Platform):
|
||||
while True:
|
||||
try:
|
||||
async with websockets.connect(ws_url) as websocket:
|
||||
logger.info("WebSocket 连接成功。")
|
||||
logger.debug("WebSocket 连接成功。")
|
||||
# 设置空闲超时重连
|
||||
wait_time = (
|
||||
self.active_message_poll_interval
|
||||
@@ -355,9 +394,7 @@ class WeChatPadProAdapter(Platform):
|
||||
# logger.debug(message) # 不显示原始消息内容
|
||||
asyncio.create_task(self.handle_websocket_message(message))
|
||||
except asyncio.TimeoutError:
|
||||
logger.warning(
|
||||
f"WebSocket 连接空闲超过 {wait_time} s"
|
||||
)
|
||||
logger.debug(f"WebSocket 连接空闲超过 {wait_time} s")
|
||||
break
|
||||
except websockets.exceptions.ConnectionClosedOK:
|
||||
logger.info("WebSocket 连接正常关闭。")
|
||||
@@ -366,7 +403,9 @@ class WeChatPadProAdapter(Platform):
|
||||
logger.error(f"处理 WebSocket 消息时发生错误: {e}")
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"WebSocket 连接失败: {e}, 请检查WeChatPadPro服务状态,或尝试重启WeChatPadPro适配器。")
|
||||
logger.error(
|
||||
f"WebSocket 连接失败: {e}, 请检查WeChatPadPro服务状态,或尝试重启WeChatPadPro适配器。"
|
||||
)
|
||||
await asyncio.sleep(5)
|
||||
|
||||
async def handle_websocket_message(self, message: str):
|
||||
@@ -441,7 +480,7 @@ class WeChatPadProAdapter(Platform):
|
||||
):
|
||||
# 再根据消息类型处理消息内容
|
||||
await self._process_message_content(abm, raw_message, msg_type, content)
|
||||
|
||||
|
||||
return abm
|
||||
return None
|
||||
|
||||
@@ -459,6 +498,7 @@ class WeChatPadProAdapter(Platform):
|
||||
"""
|
||||
if from_user_name == "weixin":
|
||||
return False
|
||||
at_me = False
|
||||
if "@chatroom" in from_user_name:
|
||||
abm.type = MessageType.GROUP_MESSAGE
|
||||
abm.group_id = from_user_name
|
||||
@@ -477,9 +517,17 @@ class WeChatPadProAdapter(Platform):
|
||||
|
||||
# 对于群聊,session_id 可以是群聊 ID 或发送者 ID + 群聊 ID (如果 unique_session 为 True)
|
||||
if self.unique_session:
|
||||
abm.session_id = f"{from_user_name}_{to_user_name}"
|
||||
abm.session_id = f"{from_user_name}#{abm.sender.user_id}"
|
||||
else:
|
||||
abm.session_id = from_user_name
|
||||
|
||||
msg_source = raw_message.get("msg_source", "")
|
||||
if self.wxid in msg_source:
|
||||
at_me = True
|
||||
if "在群聊中@了你" in raw_message.get("push_content", ""):
|
||||
at_me = True
|
||||
if at_me:
|
||||
abm.message.insert(0, At(qq=abm.self_id, name=""))
|
||||
else:
|
||||
abm.type = MessageType.FRIEND_MESSAGE
|
||||
abm.group_id = ""
|
||||
@@ -560,6 +608,32 @@ class WeChatPadProAdapter(Platform):
|
||||
logger.error(f"下载图片时发生错误: {e}")
|
||||
return None
|
||||
|
||||
async def download_voice(
|
||||
self, to_user_name: str, new_msg_id: str, bufid: str, length: int
|
||||
):
|
||||
"""下载原始音频。"""
|
||||
url = f"{self.base_url}/message/GetMsgVoice"
|
||||
params = {"key": self.auth_key}
|
||||
payload = {
|
||||
"Bufid": bufid,
|
||||
"ToUserName": to_user_name,
|
||||
"NewMsgId": new_msg_id,
|
||||
"Length": length,
|
||||
}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
try:
|
||||
async with session.post(url, params=params, json=payload) as response:
|
||||
if response.status == 200:
|
||||
return await response.json()
|
||||
logger.error(f"下载音频失败: {response.status}")
|
||||
return None
|
||||
except aiohttp.ClientConnectorError as e:
|
||||
logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"下载音频时发生错误: {e}")
|
||||
return None
|
||||
|
||||
async def _process_message_content(
|
||||
self, abm: AstrBotMessage, raw_message: dict, msg_type: int, content: str
|
||||
):
|
||||
@@ -571,12 +645,82 @@ class WeChatPadProAdapter(Platform):
|
||||
if abm.type == MessageType.GROUP_MESSAGE:
|
||||
parts = content.split(":\n", 1)
|
||||
if len(parts) == 2:
|
||||
abm.message_str = parts[1]
|
||||
abm.message.append(Plain(abm.message_str))
|
||||
message_content = parts[1]
|
||||
abm.message_str = message_content
|
||||
|
||||
# 检查是否@了机器人,参考 gewechat 的实现方式
|
||||
# 微信大部分客户端在@用户昵称后面,紧接着是一个\u2005字符(四分之一空格)
|
||||
at_me = False
|
||||
|
||||
# 检查 msg_source 中是否包含机器人的 wxid
|
||||
# wechatpadpro 的格式: <atuserlist>wxid</atuserlist>
|
||||
# gewechat 的格式: <atuserlist><![CDATA[wxid]]></atuserlist>
|
||||
msg_source = raw_message.get("msg_source", "")
|
||||
if (
|
||||
f"<atuserlist>{abm.self_id}</atuserlist>" in msg_source
|
||||
or f"<atuserlist>{abm.self_id}," in msg_source
|
||||
or f",{abm.self_id}</atuserlist>" in msg_source
|
||||
):
|
||||
at_me = True
|
||||
|
||||
# 也检查 push_content 中是否有@提示
|
||||
push_content = raw_message.get("push_content", "")
|
||||
if "在群聊中@了你" in push_content:
|
||||
at_me = True
|
||||
|
||||
if at_me:
|
||||
# 被@了,在消息开头插入At组件(参考gewechat的做法)
|
||||
bot_nickname = await self._get_group_member_nickname(
|
||||
abm.group_id, abm.self_id
|
||||
)
|
||||
abm.message.insert(
|
||||
0, At(qq=abm.self_id, name=bot_nickname or abm.self_id)
|
||||
)
|
||||
|
||||
# 只有当消息内容不仅仅是@时才添加Plain组件
|
||||
if "\u2005" in message_content:
|
||||
# 检查@之后是否还有其他内容
|
||||
parts = message_content.split("\u2005")
|
||||
if len(parts) > 1 and any(
|
||||
part.strip() for part in parts[1:]
|
||||
):
|
||||
abm.message.append(Plain(message_content))
|
||||
else:
|
||||
# 检查是否只包含@机器人
|
||||
is_pure_at = False
|
||||
if (
|
||||
bot_nickname
|
||||
and message_content.strip() == f"@{bot_nickname}"
|
||||
):
|
||||
is_pure_at = True
|
||||
if not is_pure_at:
|
||||
abm.message.append(Plain(message_content))
|
||||
else:
|
||||
# 没有@机器人,作为普通文本处理
|
||||
abm.message.append(Plain(message_content))
|
||||
else:
|
||||
abm.message.append(Plain(abm.message_str))
|
||||
else: # 私聊消息
|
||||
abm.message.append(Plain(abm.message_str))
|
||||
|
||||
# 缓存文本消息,以便引用消息可以查找
|
||||
try:
|
||||
# 获取msg_id作为缓存的key
|
||||
new_msg_id = raw_message.get("new_msg_id")
|
||||
if new_msg_id:
|
||||
# 限制缓存大小
|
||||
if (
|
||||
len(self.cached_texts) >= self.max_text_cache
|
||||
and self.cached_texts
|
||||
):
|
||||
# 删除最早的一条缓存
|
||||
oldest_key = next(iter(self.cached_texts))
|
||||
self.cached_texts.pop(oldest_key)
|
||||
|
||||
logger.debug(f"缓存文本消息,new_msg_id={new_msg_id}")
|
||||
self.cached_texts[str(new_msg_id)] = content
|
||||
except Exception as e:
|
||||
logger.error(f"缓存文本消息失败: {e}")
|
||||
elif msg_type == 3:
|
||||
# 图片消息
|
||||
from_user_name = raw_message.get("from_user_name", {}).get("str", "")
|
||||
@@ -590,15 +734,87 @@ class WeChatPadProAdapter(Platform):
|
||||
)
|
||||
if image_bs64_data:
|
||||
abm.message.append(Image.fromBase64(image_bs64_data))
|
||||
# 缓存图片,以便引用消息可以查找
|
||||
try:
|
||||
# 获取msg_id作为缓存的key
|
||||
new_msg_id = raw_message.get("new_msg_id")
|
||||
if new_msg_id:
|
||||
# 限制缓存大小
|
||||
if (
|
||||
len(self.cached_images) >= self.max_image_cache
|
||||
and self.cached_images
|
||||
):
|
||||
# 删除最早的一条缓存
|
||||
oldest_key = next(iter(self.cached_images))
|
||||
self.cached_images.pop(oldest_key)
|
||||
|
||||
logger.debug(f"缓存图片消息,new_msg_id={new_msg_id}")
|
||||
self.cached_images[str(new_msg_id)] = image_bs64_data
|
||||
except Exception as e:
|
||||
logger.error(f"缓存图片消息失败: {e}")
|
||||
elif msg_type == 47:
|
||||
# 视频消息 (注意:表情消息也是 47,需要区分)
|
||||
logger.warning("收到视频消息,待实现。")
|
||||
data_parser = GeweDataParser(
|
||||
content=content,
|
||||
is_private_chat=(abm.type != MessageType.GROUP_MESSAGE),
|
||||
raw_message=raw_message,
|
||||
)
|
||||
emoji_message = data_parser.parse_emoji()
|
||||
if emoji_message is not None:
|
||||
abm.message.append(emoji_message)
|
||||
elif msg_type == 50:
|
||||
# 语音/视频
|
||||
logger.warning("收到语音/视频消息,待实现。")
|
||||
elif msg_type == 34:
|
||||
# 语音消息
|
||||
bufid = 0
|
||||
to_user_name = raw_message.get("to_user_name", {}).get("str", "")
|
||||
new_msg_id = raw_message.get("new_msg_id")
|
||||
data_parser = GeweDataParser(
|
||||
content=content,
|
||||
is_private_chat=(abm.type != MessageType.GROUP_MESSAGE),
|
||||
raw_message=raw_message,
|
||||
)
|
||||
|
||||
voicemsg = data_parser._format_to_xml().find("voicemsg")
|
||||
bufid = voicemsg.get("bufid") or "0"
|
||||
length = int(voicemsg.get("length") or 0)
|
||||
voice_resp = await self.download_voice(
|
||||
to_user_name=to_user_name,
|
||||
new_msg_id=new_msg_id,
|
||||
bufid=bufid,
|
||||
length=length,
|
||||
)
|
||||
voice_bs64_data = voice_resp.get("Data", {}).get("Base64", None)
|
||||
if voice_bs64_data:
|
||||
voice_bs64_data = base64.b64decode(voice_bs64_data)
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
file_path = os.path.join(
|
||||
temp_dir, f"wechatpadpro_voice_{abm.message_id}.silk"
|
||||
)
|
||||
|
||||
async with await anyio.open_file(file_path, "wb") as f:
|
||||
await f.write(voice_bs64_data)
|
||||
abm.message.append(Record(file=file_path, url=file_path))
|
||||
elif msg_type == 49:
|
||||
# 引用消息
|
||||
logger.warning("收到引用消息,待实现。")
|
||||
try:
|
||||
parser = GeweDataParser(
|
||||
content=content,
|
||||
is_private_chat=(abm.type != MessageType.GROUP_MESSAGE),
|
||||
cached_texts=self.cached_texts,
|
||||
cached_images=self.cached_images,
|
||||
raw_message=raw_message,
|
||||
downloader=self._download_raw_image,
|
||||
)
|
||||
components = await parser.parse_mutil_49()
|
||||
if components:
|
||||
abm.message.extend(components)
|
||||
abm.message_str = "\n".join(
|
||||
c.text for c in components if isinstance(c, Plain)
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"msg_type 49 处理失败: {e}")
|
||||
abm.message.append(Plain("[XML 消息处理失败]"))
|
||||
abm.message_str = "[XML 消息处理失败]"
|
||||
else:
|
||||
logger.warning(f"收到未处理的消息类型: {msg_type}。")
|
||||
|
||||
@@ -628,7 +844,10 @@ class WeChatPadProAdapter(Platform):
|
||||
# 根据 session_id 判断消息类型
|
||||
if "@chatroom" in session.session_id:
|
||||
dummy_message_obj.type = MessageType.GROUP_MESSAGE
|
||||
dummy_message_obj.group_id = session.session_id
|
||||
if "#" in session.session_id:
|
||||
dummy_message_obj.group_id = session.session_id.split("#")[0]
|
||||
else:
|
||||
dummy_message_obj.group_id = session.session_id
|
||||
dummy_message_obj.sender = MessageMember(user_id="", nickname="")
|
||||
else:
|
||||
dummy_message_obj.type = MessageType.FRIEND_MESSAGE
|
||||
@@ -643,3 +862,67 @@ class WeChatPadProAdapter(Platform):
|
||||
)
|
||||
# 调用实例方法 send
|
||||
await sending_event.send(message_chain)
|
||||
|
||||
async def get_contact_list(self):
|
||||
"""
|
||||
获取联系人列表。
|
||||
"""
|
||||
url = f"{self.base_url}/friend/GetContactList"
|
||||
params = {"key": self.auth_key}
|
||||
payload = {"CurrentChatRoomContactSeq": 0, "CurrentWxcontactSeq": 0}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
try:
|
||||
async with session.post(url, params=params, json=payload) as response:
|
||||
if response.status != 200:
|
||||
logger.error(f"获取联系人列表失败: {response.status}")
|
||||
return None
|
||||
result = await response.json()
|
||||
if result.get("Code") == 200 and result.get("Data"):
|
||||
contact_list = (
|
||||
result.get("Data", {})
|
||||
.get("ContactList", {})
|
||||
.get("contactUsernameList", [])
|
||||
)
|
||||
return contact_list
|
||||
else:
|
||||
logger.error(f"获取联系人列表失败: {result}")
|
||||
return None
|
||||
except aiohttp.ClientConnectorError as e:
|
||||
logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"获取联系人列表时发生错误: {e}")
|
||||
return None
|
||||
|
||||
async def get_contact_details_list(
|
||||
self, room_wx_id_list: list[str] = None, user_names: list[str] = None
|
||||
) -> Optional[dict]:
|
||||
"""
|
||||
获取联系人详情列表。
|
||||
"""
|
||||
if room_wx_id_list is None:
|
||||
room_wx_id_list = []
|
||||
if user_names is None:
|
||||
user_names = []
|
||||
url = f"{self.base_url}/friend/GetContactDetailsList"
|
||||
params = {"key": self.auth_key}
|
||||
payload = {"RoomWxIDList": room_wx_id_list, "UserNames": user_names}
|
||||
async with aiohttp.ClientSession() as session:
|
||||
try:
|
||||
async with session.post(url, params=params, json=payload) as response:
|
||||
if response.status != 200:
|
||||
logger.error(f"获取联系人详情列表失败: {response.status}")
|
||||
return None
|
||||
result = await response.json()
|
||||
if result.get("Code") == 200 and result.get("Data"):
|
||||
contact_list = result.get("Data", {}).get("contactList", {})
|
||||
return contact_list
|
||||
else:
|
||||
logger.error(f"获取联系人详情列表失败: {result}")
|
||||
return None
|
||||
except aiohttp.ClientConnectorError as e:
|
||||
logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"获取联系人详情列表时发生错误: {e}")
|
||||
return None
|
||||
|
||||
@@ -7,11 +7,17 @@ import aiohttp
|
||||
from PIL import Image as PILImage # 使用别名避免冲突
|
||||
|
||||
from astrbot import logger
|
||||
from astrbot.core.message.components import Image, Plain # Import Image
|
||||
from astrbot.core.message.components import (
|
||||
Image,
|
||||
Plain,
|
||||
WechatEmoji,
|
||||
Record,
|
||||
) # Import Image
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from astrbot.core.platform.astr_message_event import AstrMessageEvent
|
||||
from astrbot.core.platform.astrbot_message import AstrBotMessage, MessageType
|
||||
from astrbot.core.platform.platform_metadata import PlatformMetadata
|
||||
from astrbot.core.utils.tencent_record_helper import audio_to_tencent_silk_base64
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .wechatpadpro_adapter import WeChatPadProAdapter
|
||||
@@ -38,6 +44,10 @@ class WeChatPadProMessageEvent(AstrMessageEvent):
|
||||
await self._send_text(session, comp.text)
|
||||
elif isinstance(comp, Image):
|
||||
await self._send_image(session, comp)
|
||||
elif isinstance(comp, WechatEmoji):
|
||||
await self._send_emoji(session, comp)
|
||||
elif isinstance(comp, Record):
|
||||
await self._send_voice(session, comp)
|
||||
await super().send(message)
|
||||
|
||||
async def _send_image(self, session: aiohttp.ClientSession, comp: Image):
|
||||
@@ -71,14 +81,48 @@ class WeChatPadProMessageEvent(AstrMessageEvent):
|
||||
# logger.info(f"已添加 @ 信息: {message_text}")
|
||||
else:
|
||||
message_text = text
|
||||
if self.get_group_id() and "#" in self.session_id:
|
||||
session_id = self.session_id.split("#")[0]
|
||||
else:
|
||||
session_id = self.session_id
|
||||
payload = {
|
||||
"MsgItem": [
|
||||
{"MsgType": 1, "TextContent": message_text, "ToUserName": self.session_id}
|
||||
{
|
||||
"MsgType": 1,
|
||||
"TextContent": message_text,
|
||||
"ToUserName": session_id,
|
||||
}
|
||||
]
|
||||
}
|
||||
url = f"{self.adapter.base_url}/message/SendTextMessage"
|
||||
await self._post(session, url, payload)
|
||||
|
||||
async def _send_emoji(self, session: aiohttp.ClientSession, comp: WechatEmoji):
|
||||
payload = {
|
||||
"EmojiList": [
|
||||
{
|
||||
"EmojiMd5": comp.md5,
|
||||
"EmojiSize": comp.md5_len,
|
||||
"ToUserName": self.session_id,
|
||||
}
|
||||
]
|
||||
}
|
||||
url = f"{self.adapter.base_url}/message/SendEmojiMessage"
|
||||
await self._post(session, url, payload)
|
||||
|
||||
async def _send_voice(self, session: aiohttp.ClientSession, comp: Record):
|
||||
record_path = await comp.convert_to_file_path()
|
||||
# 默认已经存在 data/temp 中
|
||||
b64, duration = await audio_to_tencent_silk_base64(record_path)
|
||||
payload = {
|
||||
"ToUserName": self.session_id,
|
||||
"VoiceData": b64,
|
||||
"VoiceFormat": 4,
|
||||
"VoiceSecond": duration,
|
||||
}
|
||||
url = f"{self.adapter.base_url}/message/SendVoice"
|
||||
await self._post(session, url, payload)
|
||||
|
||||
@staticmethod
|
||||
def _validate_base64(b64: str) -> bytes:
|
||||
return base64.b64decode(b64, validate=True)
|
||||
|
||||
160
astrbot/core/platform/sources/wechatpadpro/xml_data_parser.py
Normal file
160
astrbot/core/platform/sources/wechatpadpro/xml_data_parser.py
Normal file
@@ -0,0 +1,160 @@
|
||||
from defusedxml import ElementTree as eT
|
||||
from astrbot.api import logger
|
||||
from astrbot.api.message_components import (
|
||||
WechatEmoji as Emoji,
|
||||
Plain,
|
||||
Image,
|
||||
BaseMessageComponent,
|
||||
)
|
||||
|
||||
|
||||
class GeweDataParser:
|
||||
def __init__(
|
||||
self,
|
||||
content: str,
|
||||
is_private_chat: bool = False,
|
||||
cached_texts=None,
|
||||
cached_images=None,
|
||||
raw_message: dict = None,
|
||||
downloader=None,
|
||||
):
|
||||
self._xml = None
|
||||
self.content = content
|
||||
self.is_private_chat = is_private_chat
|
||||
self.cached_texts = cached_texts or {}
|
||||
self.cached_images = cached_images or {}
|
||||
self.downloader = downloader
|
||||
|
||||
raw_message = raw_message or {}
|
||||
self.from_user_name = raw_message.get("from_user_name", {}).get("str", "")
|
||||
self.to_user_name = raw_message.get("to_user_name", {}).get("str", "")
|
||||
self.msg_id = raw_message.get("msg_id", "")
|
||||
|
||||
def _format_to_xml(self):
|
||||
if self._xml:
|
||||
return self._xml
|
||||
|
||||
try:
|
||||
msg_str = self.content
|
||||
if not self.is_private_chat:
|
||||
parts = self.content.split(":\n", 1)
|
||||
msg_str = parts[1] if len(parts) == 2 else self.content
|
||||
|
||||
self._xml = eT.fromstring(msg_str)
|
||||
return self._xml
|
||||
except Exception as e:
|
||||
logger.error(f"[XML解析失败] {e}")
|
||||
raise
|
||||
|
||||
async def parse_mutil_49(self) -> list[BaseMessageComponent] | None:
|
||||
"""
|
||||
处理 msg_type == 49 的多种 appmsg 类型(目前支持 type==57)
|
||||
"""
|
||||
try:
|
||||
appmsg_type = self._format_to_xml().findtext(".//appmsg/type")
|
||||
if appmsg_type == "57":
|
||||
return await self.parse_reply()
|
||||
except Exception as e:
|
||||
logger.warning(f"[parse_mutil_49] 解析失败: {e}")
|
||||
return None
|
||||
|
||||
async def parse_reply(self) -> list[BaseMessageComponent]:
|
||||
"""
|
||||
处理 type == 57 的引用消息:支持文本(1)、图片(3)、嵌套49(49)
|
||||
"""
|
||||
components = []
|
||||
|
||||
try:
|
||||
appmsg = self._format_to_xml().find("appmsg")
|
||||
if appmsg is None:
|
||||
return [Plain("[引用消息解析失败]")]
|
||||
|
||||
refermsg = appmsg.find("refermsg")
|
||||
if refermsg is None:
|
||||
return [Plain("[引用消息解析失败]")]
|
||||
|
||||
quote_type = int(refermsg.findtext("type", "0"))
|
||||
nickname = refermsg.findtext("displayname", "未知发送者")
|
||||
quote_content = refermsg.findtext("content", "")
|
||||
svrid = refermsg.findtext("svrid")
|
||||
|
||||
match quote_type:
|
||||
case 1: # 文本引用
|
||||
quoted_text = self.cached_texts.get(str(svrid), quote_content)
|
||||
components.append(Plain(f"[引用] {nickname}: {quoted_text}"))
|
||||
|
||||
case 3: # 图片引用
|
||||
quoted_image_b64 = self.cached_images.get(str(svrid))
|
||||
if not quoted_image_b64:
|
||||
try:
|
||||
quote_xml = eT.fromstring(quote_content)
|
||||
img = quote_xml.find("img")
|
||||
cdn_url = (
|
||||
img.get("cdnbigimgurl") or img.get("cdnmidimgurl")
|
||||
if img is not None
|
||||
else None
|
||||
)
|
||||
if cdn_url and self.downloader:
|
||||
image_resp = await self.downloader(
|
||||
self.from_user_name, self.to_user_name, self.msg_id
|
||||
)
|
||||
quoted_image_b64 = (
|
||||
image_resp.get("Data", {})
|
||||
.get("Data", {})
|
||||
.get("Buffer")
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"[引用图片解析失败] svrid={svrid} err={e}")
|
||||
|
||||
if quoted_image_b64:
|
||||
components.extend(
|
||||
[
|
||||
Image.fromBase64(quoted_image_b64),
|
||||
Plain(f"[引用] {nickname}: [引用的图片]"),
|
||||
]
|
||||
)
|
||||
else:
|
||||
components.append(
|
||||
Plain(f"[引用] {nickname}: [引用的图片 - 未能获取]")
|
||||
)
|
||||
|
||||
case 49: # 嵌套引用
|
||||
try:
|
||||
nested_root = eT.fromstring(quote_content)
|
||||
nested_title = nested_root.findtext(".//appmsg/title", "")
|
||||
components.append(Plain(f"[引用] {nickname}: {nested_title}"))
|
||||
except Exception as e:
|
||||
logger.warning(f"[嵌套引用解析失败] err={e}")
|
||||
components.append(Plain(f"[引用] {nickname}: [嵌套引用消息]"))
|
||||
|
||||
case _: # 其他未识别类型
|
||||
logger.info(f"[未知引用类型] quote_type={quote_type}")
|
||||
components.append(Plain(f"[引用] {nickname}: [不支持的引用类型]"))
|
||||
|
||||
# 主消息标题
|
||||
title = appmsg.findtext("title", "")
|
||||
if title:
|
||||
components.append(Plain(title))
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[parse_reply] 总体解析失败: {e}")
|
||||
return [Plain("[引用消息解析失败]")]
|
||||
|
||||
return components
|
||||
|
||||
def parse_emoji(self) -> Emoji | None:
|
||||
"""
|
||||
处理 msg_type == 47 的表情消息(emoji)
|
||||
"""
|
||||
try:
|
||||
emoji_element = self._format_to_xml().find(".//emoji")
|
||||
if emoji_element is not None:
|
||||
return Emoji(
|
||||
md5=emoji_element.get("md5"),
|
||||
md5_len=emoji_element.get("len"),
|
||||
cdnurl=emoji_element.get("cdnurl"),
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"[parse_emoji] 解析失败: {e}")
|
||||
|
||||
return None
|
||||
@@ -303,6 +303,7 @@ class WecomPlatformAdapter(Platform):
|
||||
abm.session_id = external_userid
|
||||
abm.type = MessageType.FRIEND_MESSAGE
|
||||
abm.message_id = msg.get("msgid", uuid.uuid4().hex[:8])
|
||||
abm.message_str = ""
|
||||
if msgtype == "text":
|
||||
text = msg.get("text", {}).get("content", "").strip()
|
||||
abm.message = [Plain(text=text)]
|
||||
@@ -316,7 +317,29 @@ class WecomPlatformAdapter(Platform):
|
||||
with open(path, "wb") as f:
|
||||
f.write(resp.content)
|
||||
abm.message = [Image(file=path, url=path)]
|
||||
abm.message_str = "[图片]"
|
||||
elif msgtype == "voice":
|
||||
media_id = msg.get("voice", {}).get("media_id", "")
|
||||
resp: Response = await asyncio.get_event_loop().run_in_executor(
|
||||
None, self.client.media.download, media_id
|
||||
)
|
||||
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
path = os.path.join(temp_dir, f"weixinkefu_{media_id}.amr")
|
||||
with open(path, "wb") as f:
|
||||
f.write(resp.content)
|
||||
|
||||
try:
|
||||
from pydub import AudioSegment
|
||||
|
||||
path_wav = os.path.join(temp_dir, f"weixinkefu_{media_id}.wav")
|
||||
audio = AudioSegment.from_file(path)
|
||||
audio.export(path_wav, format="wav")
|
||||
except Exception as e:
|
||||
logger.error(f"转换音频失败: {e}。如果没有安装 ffmpeg 请先安装。")
|
||||
path_wav = path
|
||||
return
|
||||
|
||||
abm.message = [Record(file=path_wav, url=path_wav)]
|
||||
else:
|
||||
logger.warning(f"未实现的微信客服消息事件: {msg}")
|
||||
return
|
||||
|
||||
@@ -120,6 +120,30 @@ class WecomPlatformEvent(AstrMessageEvent):
|
||||
self.get_self_id(),
|
||||
response["media_id"],
|
||||
)
|
||||
elif isinstance(comp, Record):
|
||||
record_path = await comp.convert_to_file_path()
|
||||
# 转成amr
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
record_path_amr = os.path.join(temp_dir, f"{uuid.uuid4()}.amr")
|
||||
pydub.AudioSegment.from_wav(record_path).export(
|
||||
record_path_amr, format="amr"
|
||||
)
|
||||
|
||||
with open(record_path_amr, "rb") as f:
|
||||
try:
|
||||
response = self.client.media.upload("voice", f)
|
||||
except Exception as e:
|
||||
logger.error(f"微信客服上传语音失败: {e}")
|
||||
await self.send(
|
||||
MessageChain().message(f"微信客服上传语音失败: {e}")
|
||||
)
|
||||
return
|
||||
logger.info(f"微信客服上传语音返回: {response}")
|
||||
kf_message_api.send_voice(
|
||||
user_id,
|
||||
self.get_self_id(),
|
||||
response["media_id"],
|
||||
)
|
||||
else:
|
||||
logger.warning(f"还没实现这个消息类型的发送逻辑: {comp.type}。")
|
||||
else:
|
||||
|
||||
@@ -48,7 +48,12 @@ class WeChatKF(BaseWeChatAPI):
|
||||
注意:可能会出现返回条数少于limit的情况,需结合返回的has_more字段判断是否继续请求。
|
||||
:return: 接口调用结果
|
||||
"""
|
||||
data = {"token": token, "cursor": cursor, "limit": limit, "open_kfid": open_kfid}
|
||||
data = {
|
||||
"token": token,
|
||||
"cursor": cursor,
|
||||
"limit": limit,
|
||||
"open_kfid": open_kfid,
|
||||
}
|
||||
return self._post("kf/sync_msg", data=data)
|
||||
|
||||
def get_service_state(self, open_kfid, external_userid):
|
||||
@@ -72,7 +77,9 @@ class WeChatKF(BaseWeChatAPI):
|
||||
}
|
||||
return self._post("kf/service_state/get", data=data)
|
||||
|
||||
def trans_service_state(self, open_kfid, external_userid, service_state, servicer_userid=""):
|
||||
def trans_service_state(
|
||||
self, open_kfid, external_userid, service_state, servicer_userid=""
|
||||
):
|
||||
"""
|
||||
变更会话状态
|
||||
|
||||
@@ -180,7 +187,9 @@ class WeChatKF(BaseWeChatAPI):
|
||||
"""
|
||||
return self._get("kf/customer/get_upgrade_service_config")
|
||||
|
||||
def upgrade_service(self, open_kfid, external_userid, service_type, member=None, groupchat=None):
|
||||
def upgrade_service(
|
||||
self, open_kfid, external_userid, service_type, member=None, groupchat=None
|
||||
):
|
||||
"""
|
||||
为客户升级为专员或客户群服务
|
||||
|
||||
@@ -246,7 +255,9 @@ class WeChatKF(BaseWeChatAPI):
|
||||
data = {"open_kfid": open_kfid, "start_time": start_time, "end_time": end_time}
|
||||
return self._post("kf/get_corp_statistic", data=data)
|
||||
|
||||
def get_servicer_statistic(self, start_time, end_time, open_kfid=None, servicer_userid=None):
|
||||
def get_servicer_statistic(
|
||||
self, start_time, end_time, open_kfid=None, servicer_userid=None
|
||||
):
|
||||
"""
|
||||
获取「客户数据统计」接待人员明细数据
|
||||
|
||||
|
||||
@@ -26,6 +26,7 @@ from optionaldict import optionaldict
|
||||
|
||||
from wechatpy.client.api.base import BaseWeChatAPI
|
||||
|
||||
|
||||
class WeChatKFMessage(BaseWeChatAPI):
|
||||
"""
|
||||
发送微信客服消息
|
||||
@@ -125,35 +126,55 @@ class WeChatKFMessage(BaseWeChatAPI):
|
||||
msg={"msgtype": "news", "link": {"link": articles_data}},
|
||||
)
|
||||
|
||||
def send_msgmenu(self, user_id, open_kfid, head_content, menu_list, tail_content, msgid=""):
|
||||
def send_msgmenu(
|
||||
self, user_id, open_kfid, head_content, menu_list, tail_content, msgid=""
|
||||
):
|
||||
return self.send(
|
||||
user_id,
|
||||
open_kfid,
|
||||
msgid,
|
||||
msg={
|
||||
"msgtype": "msgmenu",
|
||||
"msgmenu": {"head_content": head_content, "list": menu_list, "tail_content": tail_content},
|
||||
"msgmenu": {
|
||||
"head_content": head_content,
|
||||
"list": menu_list,
|
||||
"tail_content": tail_content,
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
def send_location(self, user_id, open_kfid, name, address, latitude, longitude, msgid=""):
|
||||
def send_location(
|
||||
self, user_id, open_kfid, name, address, latitude, longitude, msgid=""
|
||||
):
|
||||
return self.send(
|
||||
user_id,
|
||||
open_kfid,
|
||||
msgid,
|
||||
msg={
|
||||
"msgtype": "location",
|
||||
"msgmenu": {"name": name, "address": address, "latitude": latitude, "longitude": longitude},
|
||||
"msgmenu": {
|
||||
"name": name,
|
||||
"address": address,
|
||||
"latitude": latitude,
|
||||
"longitude": longitude,
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
def send_miniprogram(self, user_id, open_kfid, appid, title, thumb_media_id, pagepath, msgid=""):
|
||||
def send_miniprogram(
|
||||
self, user_id, open_kfid, appid, title, thumb_media_id, pagepath, msgid=""
|
||||
):
|
||||
return self.send(
|
||||
user_id,
|
||||
open_kfid,
|
||||
msgid,
|
||||
msg={
|
||||
"msgtype": "miniprogram",
|
||||
"msgmenu": {"appid": appid, "title": title, "thumb_media_id": thumb_media_id, "pagepath": pagepath},
|
||||
"msgmenu": {
|
||||
"appid": appid,
|
||||
"title": title,
|
||||
"thumb_media_id": thumb_media_id,
|
||||
"pagepath": pagepath,
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
@@ -160,7 +160,9 @@ class WeixinOfficialAccountPlatformAdapter(Platform):
|
||||
self.wexin_event_workers[msg.id] = future
|
||||
await self.convert_message(msg, future)
|
||||
# I love shield so much!
|
||||
result = await asyncio.wait_for(asyncio.shield(future), 60) # wait for 60s
|
||||
result = await asyncio.wait_for(
|
||||
asyncio.shield(future), 60
|
||||
) # wait for 60s
|
||||
logger.debug(f"Got future result: {result}")
|
||||
self.wexin_event_workers.pop(msg.id, None)
|
||||
return result # xml. see weixin_offacc_event.py
|
||||
|
||||
@@ -150,7 +150,6 @@ class WeixinOfficialAccountPlatformEvent(AstrMessageEvent):
|
||||
return
|
||||
logger.info(f"微信公众平台上传语音返回: {response}")
|
||||
|
||||
|
||||
if active_send_mode:
|
||||
self.client.message.send_voice(
|
||||
message_obj.sender.user_id,
|
||||
|
||||
@@ -19,6 +19,7 @@ class ProviderType(enum.Enum):
|
||||
CHAT_COMPLETION = "chat_completion"
|
||||
SPEECH_TO_TEXT = "speech_to_text"
|
||||
TEXT_TO_SPEECH = "text_to_speech"
|
||||
EMBEDDING = "embedding"
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -57,7 +58,7 @@ class AssistantMessageSegment:
|
||||
"""OpenAI 格式的上下文中 role 为 assistant 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
|
||||
|
||||
content: str = None
|
||||
tool_calls: List[ChatCompletionMessageToolCall | Dict] = None
|
||||
tool_calls: List[ChatCompletionMessageToolCall | Dict] = field(default_factory=list)
|
||||
role: str = "assistant"
|
||||
|
||||
def to_dict(self):
|
||||
@@ -66,7 +67,7 @@ class AssistantMessageSegment:
|
||||
}
|
||||
if self.content:
|
||||
ret["content"] = self.content
|
||||
elif self.tool_calls:
|
||||
if self.tool_calls:
|
||||
ret["tool_calls"] = self.tool_calls
|
||||
return ret
|
||||
|
||||
@@ -94,27 +95,38 @@ class ProviderRequest:
|
||||
"""提示词"""
|
||||
session_id: str = ""
|
||||
"""会话 ID"""
|
||||
image_urls: List[str] = None
|
||||
image_urls: list[str] = field(default_factory=list)
|
||||
"""图片 URL 列表"""
|
||||
func_tool: FuncCall = None
|
||||
func_tool: FuncCall | None = None
|
||||
"""可用的函数工具"""
|
||||
contexts: List = None
|
||||
contexts: list[dict] = field(default_factory=list)
|
||||
"""上下文。格式与 openai 的上下文格式一致:
|
||||
参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
|
||||
"""
|
||||
system_prompt: str = ""
|
||||
"""系统提示词"""
|
||||
conversation: Conversation = None
|
||||
conversation: Conversation | None = None
|
||||
|
||||
tool_calls_result: ToolCallsResult = None
|
||||
tool_calls_result: list[ToolCallsResult] | ToolCallsResult | None = None
|
||||
"""附加的上次请求后工具调用的结果。参考: https://platform.openai.com/docs/guides/function-calling#handling-function-calls"""
|
||||
|
||||
model: str | None = None
|
||||
"""模型名称,为 None 时使用提供商的默认模型"""
|
||||
|
||||
def __repr__(self):
|
||||
return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self._print_friendly_context()}, system_prompt={self.system_prompt.strip()}, tool_calls_result={self.tool_calls_result})"
|
||||
|
||||
def __str__(self):
|
||||
return self.__repr__()
|
||||
|
||||
def append_tool_calls_result(self, tool_calls_result: ToolCallsResult):
|
||||
"""添加工具调用结果到请求中"""
|
||||
if not self.tool_calls_result:
|
||||
self.tool_calls_result = []
|
||||
if isinstance(self.tool_calls_result, ToolCallsResult):
|
||||
self.tool_calls_result = [self.tool_calls_result]
|
||||
self.tool_calls_result.append(tool_calls_result)
|
||||
|
||||
def _print_friendly_context(self):
|
||||
"""打印友好的消息上下文。将 image_url 的值替换为 <Image>"""
|
||||
if not self.contexts:
|
||||
@@ -155,7 +167,9 @@ class ProviderRequest:
|
||||
if self.image_urls:
|
||||
user_content = {
|
||||
"role": "user",
|
||||
"content": [{"type": "text", "text": self.prompt if self.prompt else "[图片]"}],
|
||||
"content": [
|
||||
{"type": "text", "text": self.prompt if self.prompt else "[图片]"}
|
||||
],
|
||||
}
|
||||
for image_url in self.image_urls:
|
||||
if image_url.startswith("http"):
|
||||
|
||||
@@ -4,6 +4,7 @@ import textwrap
|
||||
import os
|
||||
import asyncio
|
||||
import logging
|
||||
from datetime import timedelta
|
||||
|
||||
from typing import Dict, List, Awaitable, Literal, Any
|
||||
from dataclasses import dataclass
|
||||
@@ -20,6 +21,13 @@ try:
|
||||
except (ModuleNotFoundError, ImportError):
|
||||
logger.warning("警告: 缺少依赖库 'mcp',将无法使用 MCP 服务。")
|
||||
|
||||
try:
|
||||
from mcp.client.streamable_http import streamablehttp_client
|
||||
except (ModuleNotFoundError, ImportError):
|
||||
logger.warning(
|
||||
"警告: 缺少依赖库 'mcp' 或者 mcp 库版本过低,无法使用 Streamable HTTP 连接方式。"
|
||||
)
|
||||
|
||||
DEFAULT_MCP_CONFIG = {"mcpServers": {}}
|
||||
|
||||
SUPPORTED_TYPES = [
|
||||
@@ -31,6 +39,72 @@ SUPPORTED_TYPES = [
|
||||
] # json schema 支持的数据类型
|
||||
|
||||
|
||||
def _prepare_config(config: dict) -> dict:
|
||||
"""准备配置,处理嵌套格式"""
|
||||
if "mcpServers" in config and config["mcpServers"]:
|
||||
first_key = next(iter(config["mcpServers"]))
|
||||
config = config["mcpServers"][first_key]
|
||||
config.pop("active", None)
|
||||
return config
|
||||
|
||||
|
||||
async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
|
||||
"""快速测试 MCP 服务器可达性"""
|
||||
import aiohttp
|
||||
|
||||
cfg = _prepare_config(config.copy())
|
||||
|
||||
url = cfg["url"]
|
||||
headers = cfg.get("headers", {})
|
||||
timeout = cfg.get("timeout", 10)
|
||||
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
if cfg.get("transport") == "streamable_http":
|
||||
test_payload = {
|
||||
"jsonrpc": "2.0",
|
||||
"method": "initialize",
|
||||
"id": 0,
|
||||
"params": {
|
||||
"protocolVersion": "2024-11-05",
|
||||
"capabilities": {},
|
||||
"clientInfo": {"name": "test-client", "version": "1.2.3"},
|
||||
},
|
||||
}
|
||||
async with session.post(
|
||||
url,
|
||||
headers={
|
||||
**headers,
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "application/json, text/event-stream",
|
||||
},
|
||||
json=test_payload,
|
||||
timeout=aiohttp.ClientTimeout(total=timeout),
|
||||
) as response:
|
||||
if response.status == 200:
|
||||
return True, ""
|
||||
else:
|
||||
return False, f"HTTP {response.status}: {response.reason}"
|
||||
else:
|
||||
async with session.get(
|
||||
url,
|
||||
headers={
|
||||
**headers,
|
||||
"Accept": "application/json, text/event-stream",
|
||||
},
|
||||
timeout=aiohttp.ClientTimeout(total=timeout),
|
||||
) as response:
|
||||
if response.status == 200:
|
||||
return True, ""
|
||||
else:
|
||||
return False, f"HTTP {response.status}: {response.reason}"
|
||||
|
||||
except asyncio.TimeoutError:
|
||||
return False, f"连接超时: {timeout}秒"
|
||||
except Exception as e:
|
||||
return False, f"{e!s}"
|
||||
|
||||
|
||||
@dataclass
|
||||
class FuncTool:
|
||||
"""
|
||||
@@ -72,12 +146,10 @@ class FuncTool:
|
||||
if not self.mcp_client or not self.mcp_client.session:
|
||||
raise Exception(f"MCP client for {self.name} is not available")
|
||||
# 使用name属性而不是额外的mcp_tool_name
|
||||
if ":" in self.name:
|
||||
# 如果名字是格式为 mcp:server:tool_name,提取实际的工具名
|
||||
actual_tool_name = self.name.split(":")[-1]
|
||||
return await self.mcp_client.session.call_tool(actual_tool_name, args)
|
||||
else:
|
||||
return await self.mcp_client.session.call_tool(self.name, args)
|
||||
actual_tool_name = (
|
||||
self.name.split(":")[-1] if ":" in self.name else self.name
|
||||
)
|
||||
return await self.mcp_client.session.call_tool(actual_tool_name, args)
|
||||
else:
|
||||
raise Exception(f"Unknown function origin: {self.origin}")
|
||||
|
||||
@@ -92,31 +164,78 @@ class MCPClient:
|
||||
self.active: bool = True
|
||||
self.tools: List[mcp.Tool] = []
|
||||
self.server_errlogs: List[str] = []
|
||||
self.running_event = asyncio.Event()
|
||||
|
||||
async def connect_to_server(self, mcp_server_config: dict, name: str):
|
||||
"""连接到 MCP 服务器
|
||||
|
||||
如果 `url` 参数存在,则使用 SSE 的方式连接到 MCP 服务。
|
||||
如果 `url` 参数存在:
|
||||
1. 当 transport 指定为 `streamable_http` 时,使用 Streamable HTTP 连接方式。
|
||||
1. 当 transport 指定为 `sse` 时,使用 SSE 连接方式。
|
||||
2. 如果没有指定,默认使用 SSE 的方式连接到 MCP 服务。
|
||||
|
||||
Args:
|
||||
mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server
|
||||
"""
|
||||
cfg = mcp_server_config.copy()
|
||||
if "mcpServers" in cfg and len(cfg["mcpServers"]) > 0:
|
||||
key_0 = list(cfg["mcpServers"].keys())[0]
|
||||
cfg = cfg["mcpServers"][key_0]
|
||||
cfg.pop("active", None) # Remove active flag from config
|
||||
cfg = _prepare_config(mcp_server_config.copy())
|
||||
|
||||
def logging_callback(msg: str):
|
||||
# 处理 MCP 服务的错误日志
|
||||
print(f"MCP Server {name} Error: {msg}")
|
||||
self.server_errlogs.append(msg)
|
||||
|
||||
if "url" in cfg:
|
||||
# SSE transport method
|
||||
self._streams_context = sse_client(url=cfg["url"])
|
||||
streams = await self._streams_context.__aenter__()
|
||||
success, error_msg = await _quick_test_mcp_connection(cfg)
|
||||
if not success:
|
||||
raise Exception(error_msg)
|
||||
|
||||
# Create a new client session
|
||||
# self.session = await self._session_context.__aenter__()
|
||||
self.session = await self.exit_stack.enter_async_context(
|
||||
mcp.ClientSession(*streams)
|
||||
)
|
||||
if cfg.get("transport") != "streamable_http":
|
||||
# SSE transport method
|
||||
self._streams_context = sse_client(
|
||||
url=cfg["url"],
|
||||
headers=cfg.get("headers", {}),
|
||||
timeout=cfg.get("timeout", 5),
|
||||
sse_read_timeout=cfg.get("sse_read_timeout", 60 * 5),
|
||||
)
|
||||
streams = await self.exit_stack.enter_async_context(
|
||||
self._streams_context
|
||||
)
|
||||
|
||||
# Create a new client session
|
||||
read_timeout = timedelta(seconds=cfg.get("session_read_timeout", 20))
|
||||
self.session = await self.exit_stack.enter_async_context(
|
||||
mcp.ClientSession(
|
||||
*streams,
|
||||
read_timeout_seconds=read_timeout,
|
||||
logging_callback=logging_callback, # type: ignore
|
||||
)
|
||||
)
|
||||
else:
|
||||
timeout = timedelta(seconds=cfg.get("timeout", 30))
|
||||
sse_read_timeout = timedelta(
|
||||
seconds=cfg.get("sse_read_timeout", 60 * 5)
|
||||
)
|
||||
self._streams_context = streamablehttp_client(
|
||||
url=cfg["url"],
|
||||
headers=cfg.get("headers", {}),
|
||||
timeout=timeout,
|
||||
sse_read_timeout=sse_read_timeout,
|
||||
terminate_on_close=cfg.get("terminate_on_close", True),
|
||||
)
|
||||
read_s, write_s, _ = await self.exit_stack.enter_async_context(
|
||||
self._streams_context
|
||||
)
|
||||
|
||||
# Create a new client session
|
||||
read_timeout = timedelta(seconds=cfg.get("session_read_timeout", 20))
|
||||
self.session = await self.exit_stack.enter_async_context(
|
||||
mcp.ClientSession(
|
||||
read_stream=read_s,
|
||||
write_stream=write_s,
|
||||
read_timeout_seconds=read_timeout,
|
||||
logging_callback=logging_callback, # type: ignore
|
||||
)
|
||||
)
|
||||
|
||||
else:
|
||||
server_params = mcp.StdioServerParameters(
|
||||
@@ -135,7 +254,7 @@ class MCPClient:
|
||||
logger=logger,
|
||||
identifier=f"MCPServer-{name}",
|
||||
callback=callback,
|
||||
),
|
||||
), # type: ignore
|
||||
),
|
||||
)
|
||||
|
||||
@@ -143,19 +262,18 @@ class MCPClient:
|
||||
self.session = await self.exit_stack.enter_async_context(
|
||||
mcp.ClientSession(*stdio_transport)
|
||||
)
|
||||
|
||||
await self.session.initialize()
|
||||
|
||||
async def list_tools_and_save(self) -> mcp.ListToolsResult:
|
||||
"""List all tools from the server and save them to self.tools"""
|
||||
response = await self.session.list_tools()
|
||||
logger.debug(f"MCP server {self.name} list tools response: {response}")
|
||||
self.tools = response.tools
|
||||
return response
|
||||
|
||||
async def cleanup(self):
|
||||
"""Clean up resources"""
|
||||
await self.exit_stack.aclose()
|
||||
self.running_event.set() # Set the running event to indicate cleanup is done
|
||||
|
||||
|
||||
class FuncCall:
|
||||
@@ -164,8 +282,6 @@ class FuncCall:
|
||||
"""内部加载的 func tools"""
|
||||
self.mcp_client_dict: Dict[str, MCPClient] = {}
|
||||
"""MCP 服务列表"""
|
||||
self.mcp_service_queue = asyncio.Queue()
|
||||
"""用于外部控制 MCP 服务的启停"""
|
||||
self.mcp_client_event: Dict[str, asyncio.Event] = {}
|
||||
|
||||
def empty(self) -> bool:
|
||||
@@ -221,7 +337,7 @@ class FuncCall:
|
||||
return f
|
||||
return None
|
||||
|
||||
async def _init_mcp_clients(self) -> None:
|
||||
async def init_mcp_clients(self) -> None:
|
||||
"""从项目根目录读取 mcp_server.json 文件,初始化 MCP 服务列表。文件格式如下:
|
||||
```
|
||||
{
|
||||
@@ -263,113 +379,64 @@ class FuncCall:
|
||||
)
|
||||
self.mcp_client_event[name] = event
|
||||
|
||||
async def mcp_service_selector(self):
|
||||
"""为了避免在不同异步任务中控制 MCP 服务导致的报错,整个项目统一通过这个 Task 来控制
|
||||
|
||||
使用 self.mcp_service_queue.put_nowait() 来控制 MCP 服务的启停,数据格式如下:
|
||||
|
||||
{"type": "init"} 初始化所有MCP客户端
|
||||
|
||||
{"type": "init", "name": "mcp_server_name", "cfg": {...}} 初始化指定的MCP客户端
|
||||
|
||||
{"type": "terminate"} 终止所有MCP客户端
|
||||
|
||||
{"type": "terminate", "name": "mcp_server_name"} 终止指定的MCP客户端
|
||||
"""
|
||||
while True:
|
||||
data = await self.mcp_service_queue.get()
|
||||
if data["type"] == "init":
|
||||
if "name" in data:
|
||||
event = asyncio.Event()
|
||||
asyncio.create_task(
|
||||
self._init_mcp_client_task_wrapper(
|
||||
data["name"], data["cfg"], event
|
||||
)
|
||||
)
|
||||
self.mcp_client_event[data["name"]] = event
|
||||
else:
|
||||
await self._init_mcp_clients()
|
||||
elif data["type"] == "terminate":
|
||||
if "name" in data:
|
||||
# await self._terminate_mcp_client(data["name"])
|
||||
if data["name"] in self.mcp_client_event:
|
||||
self.mcp_client_event[data["name"]].set()
|
||||
self.mcp_client_event.pop(data["name"], None)
|
||||
self.func_list = [
|
||||
f
|
||||
for f in self.func_list
|
||||
if not (
|
||||
f.origin == "mcp" and f.mcp_server_name == data["name"]
|
||||
)
|
||||
]
|
||||
else:
|
||||
for name in self.mcp_client_dict.keys():
|
||||
# await self._terminate_mcp_client(name)
|
||||
# self.mcp_client_event[name].set()
|
||||
if name in self.mcp_client_event:
|
||||
self.mcp_client_event[name].set()
|
||||
self.mcp_client_event.pop(name, None)
|
||||
self.func_list = [f for f in self.func_list if f.origin != "mcp"]
|
||||
|
||||
async def _init_mcp_client_task_wrapper(
|
||||
self, name: str, cfg: dict, event: asyncio.Event
|
||||
self,
|
||||
name: str,
|
||||
cfg: dict,
|
||||
event: asyncio.Event,
|
||||
ready_future: asyncio.Future = None,
|
||||
) -> None:
|
||||
"""初始化 MCP 客户端的包装函数,用于捕获异常"""
|
||||
try:
|
||||
await self._init_mcp_client(name, cfg)
|
||||
tools = await self.mcp_client_dict[name].list_tools_and_save()
|
||||
if ready_future and not ready_future.done():
|
||||
# tell the caller we are ready
|
||||
ready_future.set_result(tools)
|
||||
await event.wait()
|
||||
logger.info(f"收到 MCP 客户端 {name} 终止信号")
|
||||
await self._terminate_mcp_client(name)
|
||||
except Exception as e:
|
||||
import traceback
|
||||
|
||||
traceback.print_exc()
|
||||
logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
|
||||
logger.error(f"初始化 MCP 客户端 {name} 失败", exc_info=True)
|
||||
if ready_future and not ready_future.done():
|
||||
ready_future.set_exception(e)
|
||||
finally:
|
||||
# 无论如何都能清理
|
||||
await self._terminate_mcp_client(name)
|
||||
|
||||
async def _init_mcp_client(self, name: str, config: dict) -> None:
|
||||
"""初始化单个MCP客户端"""
|
||||
try:
|
||||
# 先清理之前的客户端,如果存在
|
||||
if name in self.mcp_client_dict:
|
||||
await self._terminate_mcp_client(name)
|
||||
# 先清理之前的客户端,如果存在
|
||||
if name in self.mcp_client_dict:
|
||||
await self._terminate_mcp_client(name)
|
||||
|
||||
mcp_client = MCPClient()
|
||||
mcp_client.name = name
|
||||
self.mcp_client_dict[name] = mcp_client
|
||||
await mcp_client.connect_to_server(config, name)
|
||||
tools_res = await mcp_client.list_tools_and_save()
|
||||
tool_names = [tool.name for tool in tools_res.tools]
|
||||
mcp_client = MCPClient()
|
||||
mcp_client.name = name
|
||||
self.mcp_client_dict[name] = mcp_client
|
||||
await mcp_client.connect_to_server(config, name)
|
||||
tools_res = await mcp_client.list_tools_and_save()
|
||||
logger.debug(f"MCP server {name} list tools response: {tools_res}")
|
||||
tool_names = [tool.name for tool in tools_res.tools]
|
||||
|
||||
# 移除该MCP服务之前的工具(如有)
|
||||
self.func_list = [
|
||||
f
|
||||
for f in self.func_list
|
||||
if not (f.origin == "mcp" and f.mcp_server_name == name)
|
||||
]
|
||||
# 移除该MCP服务之前的工具(如有)
|
||||
self.func_list = [
|
||||
f
|
||||
for f in self.func_list
|
||||
if not (f.origin == "mcp" and f.mcp_server_name == name)
|
||||
]
|
||||
|
||||
# 将 MCP 工具转换为 FuncTool 并添加到 func_list
|
||||
for tool in mcp_client.tools:
|
||||
func_tool = FuncTool(
|
||||
name=tool.name,
|
||||
parameters=tool.inputSchema,
|
||||
description=tool.description,
|
||||
origin="mcp",
|
||||
mcp_server_name=name,
|
||||
mcp_client=mcp_client,
|
||||
)
|
||||
self.func_list.append(func_tool)
|
||||
# 将 MCP 工具转换为 FuncTool 并添加到 func_list
|
||||
for tool in mcp_client.tools:
|
||||
func_tool = FuncTool(
|
||||
name=tool.name,
|
||||
parameters=tool.inputSchema,
|
||||
description=tool.description,
|
||||
origin="mcp",
|
||||
mcp_server_name=name,
|
||||
mcp_client=mcp_client,
|
||||
)
|
||||
self.func_list.append(func_tool)
|
||||
|
||||
logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
|
||||
return
|
||||
except Exception as e:
|
||||
import traceback
|
||||
|
||||
logger.error(traceback.format_exc())
|
||||
logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
|
||||
# 发生错误时确保客户端被清理
|
||||
if name in self.mcp_client_dict:
|
||||
await self._terminate_mcp_client(name)
|
||||
return
|
||||
logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
|
||||
|
||||
async def _terminate_mcp_client(self, name: str) -> None:
|
||||
"""关闭并清理MCP客户端"""
|
||||
@@ -377,9 +444,9 @@ class FuncCall:
|
||||
try:
|
||||
# 关闭MCP连接
|
||||
await self.mcp_client_dict[name].cleanup()
|
||||
del self.mcp_client_dict[name]
|
||||
self.mcp_client_dict.pop(name)
|
||||
except Exception as e:
|
||||
logger.info(f"清空 MCP 客户端资源 {name}: {e}。")
|
||||
logger.error(f"清空 MCP 客户端资源 {name}: {e}。")
|
||||
# 移除关联的FuncTool
|
||||
self.func_list = [
|
||||
f
|
||||
@@ -388,6 +455,103 @@ class FuncCall:
|
||||
]
|
||||
logger.info(f"已关闭 MCP 服务 {name}")
|
||||
|
||||
@staticmethod
|
||||
async def test_mcp_server_connection(config: dict) -> list[str]:
|
||||
if "url" in config:
|
||||
success, error_msg = await _quick_test_mcp_connection(config)
|
||||
if not success:
|
||||
raise Exception(error_msg)
|
||||
|
||||
mcp_client = MCPClient()
|
||||
try:
|
||||
logger.debug(f"testing MCP server connection with config: {config}")
|
||||
await mcp_client.connect_to_server(config, "test")
|
||||
tools_res = await mcp_client.list_tools_and_save()
|
||||
tool_names = [tool.name for tool in tools_res.tools]
|
||||
finally:
|
||||
logger.debug("Cleaning up MCP client after testing connection.")
|
||||
await mcp_client.cleanup()
|
||||
return tool_names
|
||||
|
||||
async def enable_mcp_server(
|
||||
self,
|
||||
name: str,
|
||||
config: dict,
|
||||
event: asyncio.Event | None = None,
|
||||
ready_future: asyncio.Future | None = None,
|
||||
timeout: int = 30,
|
||||
) -> None:
|
||||
"""Enable_mcp_server a new MCP server to the manager and initialize it.
|
||||
|
||||
Args:
|
||||
name (str): The name of the MCP server.
|
||||
config (dict): Configuration for the MCP server.
|
||||
event (asyncio.Event): Event to signal when the MCP client is ready.
|
||||
ready_future (asyncio.Future): Future to signal when the MCP client is ready.
|
||||
timeout (int): Timeout for the initialization.
|
||||
Raises:
|
||||
TimeoutError: If the initialization does not complete within the specified timeout.
|
||||
Exception: If there is an error during initialization.
|
||||
"""
|
||||
if not event:
|
||||
event = asyncio.Event()
|
||||
if not ready_future:
|
||||
ready_future = asyncio.Future()
|
||||
if name in self.mcp_client_dict:
|
||||
return
|
||||
asyncio.create_task(
|
||||
self._init_mcp_client_task_wrapper(name, config, event, ready_future)
|
||||
)
|
||||
try:
|
||||
await asyncio.wait_for(ready_future, timeout=timeout)
|
||||
finally:
|
||||
self.mcp_client_event[name] = event
|
||||
|
||||
if ready_future.done() and ready_future.exception():
|
||||
exc = ready_future.exception()
|
||||
if exc is not None:
|
||||
raise exc
|
||||
|
||||
async def disable_mcp_server(
|
||||
self, name: str | None = None, timeout: float = 10
|
||||
) -> None:
|
||||
"""Disable an MCP server by its name.
|
||||
|
||||
Args:
|
||||
name (str): The name of the MCP server to disable. If None, ALL MCP servers will be disabled.
|
||||
timeout (int): Timeout.
|
||||
"""
|
||||
if name:
|
||||
if name not in self.mcp_client_event:
|
||||
return
|
||||
client = self.mcp_client_dict.get(name)
|
||||
self.mcp_client_event[name].set()
|
||||
if not client:
|
||||
return
|
||||
client_running_event = client.running_event
|
||||
try:
|
||||
await asyncio.wait_for(client_running_event.wait(), timeout=timeout)
|
||||
finally:
|
||||
self.mcp_client_event.pop(name, None)
|
||||
self.func_list = [
|
||||
f
|
||||
for f in self.func_list
|
||||
if f.origin != "mcp" or f.mcp_server_name != name
|
||||
]
|
||||
else:
|
||||
running_events = [
|
||||
client.running_event.wait() for client in self.mcp_client_dict.values()
|
||||
]
|
||||
for key, event in self.mcp_client_event.items():
|
||||
event.set()
|
||||
# waiting for all clients to finish
|
||||
try:
|
||||
await asyncio.wait_for(asyncio.gather(*running_events), timeout=timeout)
|
||||
finally:
|
||||
self.mcp_client_event.clear()
|
||||
self.mcp_client_dict.clear()
|
||||
self.func_list = [f for f in self.func_list if f.origin != "mcp"]
|
||||
|
||||
def get_func_desc_openai_style(self, omit_empty_parameter_field=False) -> list:
|
||||
"""
|
||||
获得 OpenAI API 风格的**已经激活**的工具描述
|
||||
@@ -592,8 +756,3 @@ class FuncCall:
|
||||
|
||||
def __repr__(self):
|
||||
return str(self.func_list)
|
||||
|
||||
async def terminate(self):
|
||||
for name in self.mcp_client_dict.keys():
|
||||
await self._terminate_mcp_client(name)
|
||||
logger.debug(f"清理 MCP 客户端 {name} 资源")
|
||||
|
||||
@@ -1,12 +1,14 @@
|
||||
import traceback
|
||||
import asyncio
|
||||
from astrbot.core.config.astrbot_config import AstrBotConfig
|
||||
from .provider import Provider, STTProvider, TTSProvider, Personality
|
||||
from .entities import ProviderType
|
||||
import traceback
|
||||
from typing import List
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from .register import provider_cls_map, llm_tools
|
||||
|
||||
from astrbot.core import logger, sp
|
||||
from astrbot.core.config.astrbot_config import AstrBotConfig
|
||||
from astrbot.core.db import BaseDatabase
|
||||
|
||||
from .entities import ProviderType
|
||||
from .provider import Personality, Provider, STTProvider, TTSProvider, EmbeddingProvider
|
||||
from .register import llm_tools, provider_cls_map
|
||||
|
||||
|
||||
class ProviderManager:
|
||||
@@ -18,13 +20,6 @@ class ProviderManager:
|
||||
self.persona_configs: list = config.get("persona", [])
|
||||
self.astrbot_config = config
|
||||
|
||||
self.selected_provider_id = sp.get("curr_provider")
|
||||
self.selected_stt_provider_id = self.provider_stt_settings.get("provider_id")
|
||||
self.selected_tts_provider_id = self.provider_settings.get("provider_id")
|
||||
self.provider_enabled = self.provider_settings.get("enable", False)
|
||||
self.stt_enabled = self.provider_stt_settings.get("enable", False)
|
||||
self.tts_enabled = self.provider_tts_settings.get("enable", False)
|
||||
|
||||
# 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(
|
||||
@@ -98,15 +93,18 @@ class ProviderManager:
|
||||
"""加载的 Speech To Text Provider 的实例"""
|
||||
self.tts_provider_insts: List[TTSProvider] = []
|
||||
"""加载的 Text To Speech Provider 的实例"""
|
||||
self.inst_map = {}
|
||||
self.embedding_provider_insts: List[EmbeddingProvider] = []
|
||||
"""加载的 Embedding Provider 的实例"""
|
||||
self.inst_map: dict[str, Provider] = {}
|
||||
"""Provider 实例映射. key: provider_id, value: Provider 实例"""
|
||||
self.llm_tools = llm_tools
|
||||
self.curr_provider_inst: Provider = None
|
||||
"""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.curr_provider_inst: Provider | None = None
|
||||
"""默认的 Provider 实例"""
|
||||
self.curr_stt_provider_inst: STTProvider | None = None
|
||||
"""默认的 Speech To Text Provider 实例"""
|
||||
self.curr_tts_provider_inst: TTSProvider | None = None
|
||||
"""默认的 Text To Speech Provider 实例"""
|
||||
self.db_helper = db_helper
|
||||
|
||||
# kdb(experimental)
|
||||
@@ -115,24 +113,63 @@ class ProviderManager:
|
||||
if kdb_cfg and len(kdb_cfg):
|
||||
self.curr_kdb_name = list(kdb_cfg.keys())[0]
|
||||
|
||||
async def set_provider(
|
||||
self, provider_id: str, provider_type: ProviderType, umo: str = None
|
||||
):
|
||||
"""设置提供商。
|
||||
|
||||
Args:
|
||||
provider_id (str): 提供商 ID。
|
||||
provider_type (ProviderType): 提供商类型。
|
||||
umo (str, optional): 用户会话 ID,用于提供商会话隔离。当用户启用了提供商会话隔离时此参数才生效。
|
||||
"""
|
||||
if provider_id not in self.inst_map:
|
||||
raise ValueError(f"提供商 {provider_id} 不存在,无法设置。")
|
||||
if umo and self.provider_settings["separate_provider"]:
|
||||
perf = sp.get("session_provider_perf", {})
|
||||
session_perf = perf.get(umo, {})
|
||||
session_perf[provider_type.value] = provider_id
|
||||
perf[umo] = session_perf
|
||||
sp.put("session_provider_perf", perf)
|
||||
return
|
||||
# 不启用提供商会话隔离模式的情况
|
||||
self.curr_provider_inst = self.inst_map[provider_id]
|
||||
if provider_type == ProviderType.TEXT_TO_SPEECH:
|
||||
sp.put("curr_provider_tts", provider_id)
|
||||
elif provider_type == ProviderType.SPEECH_TO_TEXT:
|
||||
sp.put("curr_provider_stt", provider_id)
|
||||
elif provider_type == ProviderType.CHAT_COMPLETION:
|
||||
sp.put("curr_provider", provider_id)
|
||||
|
||||
async def initialize(self):
|
||||
# 逐个初始化提供商
|
||||
for provider_config in self.providers_config:
|
||||
await self.load_provider(provider_config)
|
||||
|
||||
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。")
|
||||
# 设置默认提供商
|
||||
selected_provider_id = sp.get(
|
||||
"curr_provider", self.provider_settings.get("default_provider_id")
|
||||
)
|
||||
selected_stt_provider_id = sp.get(
|
||||
"curr_provider_stt", self.provider_stt_settings.get("provider_id")
|
||||
)
|
||||
selected_tts_provider_id = sp.get(
|
||||
"curr_provider_tts", self.provider_tts_settings.get("provider_id")
|
||||
)
|
||||
self.curr_provider_inst = self.inst_map.get(selected_provider_id)
|
||||
if not self.curr_provider_inst and self.provider_insts:
|
||||
self.curr_provider_inst = self.provider_insts[0]
|
||||
|
||||
if self.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。")
|
||||
self.curr_stt_provider_inst = self.inst_map.get(selected_stt_provider_id)
|
||||
if not self.curr_stt_provider_inst and self.stt_provider_insts:
|
||||
self.curr_stt_provider_inst = self.stt_provider_insts[0]
|
||||
|
||||
if self.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。")
|
||||
self.curr_tts_provider_inst = self.inst_map.get(selected_tts_provider_id)
|
||||
if not self.curr_tts_provider_inst and self.tts_provider_insts:
|
||||
self.curr_tts_provider_inst = self.tts_provider_insts[0]
|
||||
|
||||
# 初始化 MCP Client 连接
|
||||
asyncio.create_task(
|
||||
self.llm_tools.mcp_service_selector(), name="mcp-service-handler"
|
||||
)
|
||||
self.llm_tools.mcp_service_queue.put_nowait({"type": "init"})
|
||||
asyncio.create_task(self.llm_tools.init_mcp_clients(), name="init_mcp_clients")
|
||||
|
||||
async def load_provider(self, provider_config: dict):
|
||||
if not provider_config["enable"]:
|
||||
@@ -155,11 +192,6 @@ class ProviderManager:
|
||||
from .sources.anthropic_source import (
|
||||
ProviderAnthropic as ProviderAnthropic,
|
||||
)
|
||||
case "llm_tuner":
|
||||
logger.info("加载 LLM Tuner 工具 ...")
|
||||
from .sources.llmtuner_source import (
|
||||
LLMTunerModelLoader as LLMTunerModelLoader,
|
||||
)
|
||||
case "dify":
|
||||
from .sources.dify_source import ProviderDify as ProviderDify
|
||||
case "dashscope":
|
||||
@@ -190,6 +222,10 @@ class ProviderManager:
|
||||
from .sources.edge_tts_source import (
|
||||
ProviderEdgeTTS as ProviderEdgeTTS,
|
||||
)
|
||||
case "gsv_tts_selfhost":
|
||||
from .sources.gsv_selfhosted_source import (
|
||||
ProviderGSVTTS as ProviderGSVTTS,
|
||||
)
|
||||
case "gsvi_tts_api":
|
||||
from .sources.gsvi_tts_source import (
|
||||
ProviderGSVITTS as ProviderGSVITTS,
|
||||
@@ -214,6 +250,18 @@ class ProviderManager:
|
||||
from .sources.volcengine_tts import (
|
||||
ProviderVolcengineTTS as ProviderVolcengineTTS,
|
||||
)
|
||||
case "gemini_tts":
|
||||
from .sources.gemini_tts_source import (
|
||||
ProviderGeminiTTSAPI as ProviderGeminiTTSAPI,
|
||||
)
|
||||
case "openai_embedding":
|
||||
from .sources.openai_embedding_source import (
|
||||
OpenAIEmbeddingProvider as OpenAIEmbeddingProvider,
|
||||
)
|
||||
case "gemini_embedding":
|
||||
from .sources.gemini_embedding_source import (
|
||||
GeminiEmbeddingProvider as GeminiEmbeddingProvider,
|
||||
)
|
||||
except (ImportError, ModuleNotFoundError) as e:
|
||||
logger.critical(
|
||||
f"加载 {provider_config['type']}({provider_config['id']}) 提供商适配器失败:{e}。可能是因为有未安装的依赖。"
|
||||
@@ -246,14 +294,14 @@ class ProviderManager:
|
||||
|
||||
self.stt_provider_insts.append(inst)
|
||||
if (
|
||||
self.selected_stt_provider_id == provider_config["id"]
|
||||
and self.stt_enabled
|
||||
self.provider_stt_settings.get("provider_id")
|
||||
== provider_config["id"]
|
||||
):
|
||||
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。"
|
||||
)
|
||||
if not self.curr_stt_provider_inst and self.stt_enabled:
|
||||
if not self.curr_stt_provider_inst:
|
||||
self.curr_stt_provider_inst = inst
|
||||
|
||||
elif provider_metadata.provider_type == ProviderType.TEXT_TO_SPEECH:
|
||||
@@ -266,15 +314,12 @@ class ProviderManager:
|
||||
await inst.initialize()
|
||||
|
||||
self.tts_provider_insts.append(inst)
|
||||
if (
|
||||
self.selected_tts_provider_id == provider_config["id"]
|
||||
and self.tts_enabled
|
||||
):
|
||||
if self.provider_settings.get("provider_id") == provider_config["id"]:
|
||||
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。"
|
||||
)
|
||||
if not self.curr_tts_provider_inst and self.tts_enabled:
|
||||
if not self.curr_tts_provider_inst:
|
||||
self.curr_tts_provider_inst = inst
|
||||
|
||||
elif provider_metadata.provider_type == ProviderType.CHAT_COMPLETION:
|
||||
@@ -282,8 +327,6 @@ class ProviderManager:
|
||||
inst = provider_metadata.cls_type(
|
||||
provider_config,
|
||||
self.provider_settings,
|
||||
self.db_helper,
|
||||
self.provider_settings.get("persistant_history", True),
|
||||
self.selected_default_persona,
|
||||
)
|
||||
|
||||
@@ -292,16 +335,24 @@ class ProviderManager:
|
||||
|
||||
self.provider_insts.append(inst)
|
||||
if (
|
||||
self.selected_provider_id == provider_config["id"]
|
||||
and self.provider_enabled
|
||||
self.provider_settings.get("default_provider_id")
|
||||
== provider_config["id"]
|
||||
):
|
||||
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。"
|
||||
)
|
||||
if not self.curr_provider_inst and self.provider_enabled:
|
||||
if not self.curr_provider_inst:
|
||||
self.curr_provider_inst = inst
|
||||
|
||||
elif provider_metadata.provider_type == ProviderType.EMBEDDING:
|
||||
inst = provider_metadata.cls_type(
|
||||
provider_config, self.provider_settings
|
||||
)
|
||||
if getattr(inst, "initialize", None):
|
||||
await inst.initialize()
|
||||
self.embedding_provider_insts.append(inst)
|
||||
|
||||
self.inst_map[provider_config["id"]] = inst
|
||||
except Exception as e:
|
||||
logger.error(traceback.format_exc())
|
||||
@@ -322,39 +373,24 @@ class ProviderManager:
|
||||
|
||||
if len(self.provider_insts) == 0:
|
||||
self.curr_provider_inst = None
|
||||
elif (
|
||||
self.curr_provider_inst is None
|
||||
and len(self.provider_insts) > 0
|
||||
and self.provider_enabled
|
||||
):
|
||||
elif self.curr_provider_inst is None and len(self.provider_insts) > 0:
|
||||
self.curr_provider_inst = self.provider_insts[0]
|
||||
self.selected_provider_id = self.curr_provider_inst.meta().id
|
||||
logger.info(
|
||||
f"自动选择 {self.curr_provider_inst.meta().id} 作为当前提供商适配器。"
|
||||
)
|
||||
|
||||
if len(self.stt_provider_insts) == 0:
|
||||
self.curr_stt_provider_inst = None
|
||||
elif (
|
||||
self.curr_stt_provider_inst is None
|
||||
and len(self.stt_provider_insts) > 0
|
||||
and self.stt_enabled
|
||||
):
|
||||
elif self.curr_stt_provider_inst is None and len(self.stt_provider_insts) > 0:
|
||||
self.curr_stt_provider_inst = self.stt_provider_insts[0]
|
||||
self.selected_stt_provider_id = self.curr_stt_provider_inst.meta().id
|
||||
logger.info(
|
||||
f"自动选择 {self.curr_stt_provider_inst.meta().id} 作为当前语音转文本提供商适配器。"
|
||||
)
|
||||
|
||||
if len(self.tts_provider_insts) == 0:
|
||||
self.curr_tts_provider_inst = None
|
||||
elif (
|
||||
self.curr_tts_provider_inst is None
|
||||
and len(self.tts_provider_insts) > 0
|
||||
and self.tts_enabled
|
||||
):
|
||||
elif self.curr_tts_provider_inst is None and len(self.tts_provider_insts) > 0:
|
||||
self.curr_tts_provider_inst = self.tts_provider_insts[0]
|
||||
self.selected_tts_provider_id = self.curr_tts_provider_inst.meta().id
|
||||
logger.info(
|
||||
f"自动选择 {self.curr_tts_provider_inst.meta().id} 作为当前文本转语音提供商适配器。"
|
||||
)
|
||||
@@ -383,7 +419,7 @@ class ProviderManager:
|
||||
self.curr_tts_provider_inst = None
|
||||
|
||||
if getattr(self.inst_map[provider_id], "terminate", None):
|
||||
await self.inst_map[provider_id].terminate()
|
||||
await self.inst_map[provider_id].terminate() # type: ignore
|
||||
|
||||
logger.info(
|
||||
f"{provider_id} 提供商适配器已终止({len(self.provider_insts)}, {len(self.stt_provider_insts)}, {len(self.tts_provider_insts)})"
|
||||
@@ -393,6 +429,8 @@ class ProviderManager:
|
||||
async def terminate(self):
|
||||
for provider_inst in self.provider_insts:
|
||||
if hasattr(provider_inst, "terminate"):
|
||||
await provider_inst.terminate()
|
||||
# 清理 MCP Client 连接
|
||||
await self.llm_tools.mcp_service_queue.put({"type": "terminate"})
|
||||
await provider_inst.terminate() # type: ignore
|
||||
try:
|
||||
await self.llm_tools.disable_mcp_server()
|
||||
except Exception:
|
||||
logger.error("Error while disabling MCP servers", exc_info=True)
|
||||
|
||||
@@ -1,9 +1,9 @@
|
||||
import abc
|
||||
from typing import List
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from typing import TypedDict, AsyncGenerator
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
|
||||
from astrbot.core.provider.entities import LLMResponse, ToolCallsResult, ProviderType
|
||||
from astrbot.core.provider.register import provider_cls_map
|
||||
from dataclasses import dataclass
|
||||
|
||||
|
||||
@@ -23,6 +23,7 @@ class ProviderMeta:
|
||||
id: str
|
||||
model: str
|
||||
type: str
|
||||
provider_type: ProviderType
|
||||
|
||||
|
||||
class AbstractProvider(abc.ABC):
|
||||
@@ -41,10 +42,14 @@ class AbstractProvider(abc.ABC):
|
||||
|
||||
def meta(self) -> ProviderMeta:
|
||||
"""获取 Provider 的元数据"""
|
||||
provider_type_name = self.provider_config["type"]
|
||||
meta_data = provider_cls_map.get(provider_type_name)
|
||||
provider_type = meta_data.provider_type if meta_data else None
|
||||
return ProviderMeta(
|
||||
id=self.provider_config["id"],
|
||||
model=self.get_model(),
|
||||
type=self.provider_config["type"],
|
||||
type=provider_type_name,
|
||||
provider_type=provider_type,
|
||||
)
|
||||
|
||||
|
||||
@@ -53,15 +58,13 @@ class Provider(AbstractProvider):
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
persistant_history: bool = True,
|
||||
db_helper: BaseDatabase = None,
|
||||
default_persona: Personality = None,
|
||||
default_persona: Personality | None = None,
|
||||
) -> None:
|
||||
super().__init__(provider_config)
|
||||
|
||||
self.provider_settings = provider_settings
|
||||
|
||||
self.curr_personality: Personality = default_persona
|
||||
self.curr_personality = default_persona
|
||||
"""维护了当前的使用的 persona,即人格。可能为 None"""
|
||||
|
||||
@abc.abstractmethod
|
||||
@@ -86,11 +89,12 @@ class Provider(AbstractProvider):
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = None,
|
||||
image_urls: list[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: List = None,
|
||||
contexts: list = None,
|
||||
system_prompt: str = None,
|
||||
tool_calls_result: ToolCallsResult = None,
|
||||
tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None,
|
||||
model: str | None = None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
"""获得 LLM 的文本对话结果。会使用当前的模型进行对话。
|
||||
@@ -114,11 +118,12 @@ class Provider(AbstractProvider):
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = None,
|
||||
image_urls: list[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: List = None,
|
||||
contexts: list = None,
|
||||
system_prompt: str = None,
|
||||
tool_calls_result: ToolCallsResult = None,
|
||||
tool_calls_result: ToolCallsResult | list[ToolCallsResult] = None,
|
||||
model: str | None = None,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator[LLMResponse, None]:
|
||||
"""获得 LLM 的流式文本对话结果。会使用当前的模型进行对话。在生成的最后会返回一次完整的结果。
|
||||
@@ -179,3 +184,25 @@ class TTSProvider(AbstractProvider):
|
||||
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()
|
||||
|
||||
|
||||
class EmbeddingProvider(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_embedding(self, text: str) -> list[float]:
|
||||
"""获取文本的向量"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
async def get_embeddings(self, text: list[str]) -> list[list[float]]:
|
||||
"""批量获取文本的向量"""
|
||||
...
|
||||
|
||||
@abc.abstractmethod
|
||||
def get_dim(self) -> int:
|
||||
"""获取向量的维度"""
|
||||
...
|
||||
|
||||
@@ -1,3 +1,6 @@
|
||||
import json
|
||||
import anthropic
|
||||
import base64
|
||||
from typing import List
|
||||
from mimetypes import guess_type
|
||||
|
||||
@@ -5,41 +8,33 @@ from anthropic import AsyncAnthropic
|
||||
from anthropic.types import Message
|
||||
|
||||
from astrbot.core.utils.io import download_image_by_url
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from astrbot.api.provider import Provider, Personality
|
||||
from astrbot.api.provider import Provider
|
||||
from astrbot import logger
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
from ..register import register_provider_adapter
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
|
||||
from .openai_source import ProviderOpenAIOfficial
|
||||
from astrbot.core.provider.entities import LLMResponse
|
||||
from typing import AsyncGenerator
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"anthropic_chat_completion", "Anthropic Claude API 提供商适配器"
|
||||
)
|
||||
class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
class ProviderAnthropic(Provider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=True,
|
||||
default_persona: Personality = None,
|
||||
provider_config,
|
||||
provider_settings,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
# Skip OpenAI's __init__ and call Provider's __init__ directly
|
||||
Provider.__init__(
|
||||
self,
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
|
||||
self.chosen_api_key = None
|
||||
self.chosen_api_key: str = ""
|
||||
self.api_keys: List = provider_config.get("key", [])
|
||||
self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
|
||||
self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else ""
|
||||
self.base_url = provider_config.get("api_base", "https://api.anthropic.com")
|
||||
self.timeout = provider_config.get("timeout", 120)
|
||||
if isinstance(self.timeout, str):
|
||||
@@ -51,10 +46,63 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
|
||||
self.set_model(provider_config["model_config"]["model"])
|
||||
|
||||
def _prepare_payload(self, messages: list[dict]):
|
||||
"""准备 Anthropic API 的请求 payload
|
||||
|
||||
Args:
|
||||
messages: OpenAI 格式的消息列表,包含用户输入和系统提示等信息
|
||||
Returns:
|
||||
system_prompt: 系统提示内容
|
||||
new_messages: 处理后的消息列表,去除系统提示
|
||||
"""
|
||||
system_prompt = ""
|
||||
new_messages = []
|
||||
for message in messages:
|
||||
if message["role"] == "system":
|
||||
system_prompt = message["content"]
|
||||
elif message["role"] == "assistant":
|
||||
blocks = []
|
||||
if isinstance(message["content"], str):
|
||||
blocks.append({"type": "text", "text": message["content"]})
|
||||
if "tool_calls" in message:
|
||||
for tool_call in message["tool_calls"]:
|
||||
blocks.append( # noqa: PERF401
|
||||
{
|
||||
"type": "tool_use",
|
||||
"name": tool_call["function"]["name"],
|
||||
"input": json.loads(tool_call["function"]["arguments"])
|
||||
if isinstance(tool_call["function"]["arguments"], str)
|
||||
else tool_call["function"]["arguments"],
|
||||
"id": tool_call["id"],
|
||||
}
|
||||
)
|
||||
new_messages.append(
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": blocks,
|
||||
}
|
||||
)
|
||||
elif message["role"] == "tool":
|
||||
new_messages.append(
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "tool_result",
|
||||
"tool_use_id": message["tool_call_id"],
|
||||
"content": message["content"],
|
||||
}
|
||||
],
|
||||
}
|
||||
)
|
||||
else:
|
||||
new_messages.append(message)
|
||||
|
||||
return system_prompt, new_messages
|
||||
|
||||
async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
|
||||
if tools:
|
||||
tool_list = tools.get_func_desc_anthropic_style()
|
||||
if tool_list:
|
||||
if tool_list := tools.get_func_desc_anthropic_style():
|
||||
payloads["tools"] = tool_list
|
||||
|
||||
completion = await self.client.messages.create(**payloads, stream=False)
|
||||
@@ -64,68 +112,158 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
|
||||
if len(completion.content) == 0:
|
||||
raise Exception("API 返回的 completion 为空。")
|
||||
# TODO: 如果进行函数调用,思维链被截断,用户可能需要思维链的内容
|
||||
# 选最后一条消息,如果要进行函数调用,anthropic会先返回文本消息的思维链,然后再返回函数调用请求
|
||||
content = completion.content[-1]
|
||||
|
||||
llm_response = LLMResponse("assistant")
|
||||
llm_response = LLMResponse(role="assistant")
|
||||
|
||||
if content.type == "text":
|
||||
# text completion
|
||||
completion_text = str(content.text).strip()
|
||||
# llm_response.completion_text = completion_text
|
||||
llm_response.result_chain = MessageChain().message(completion_text)
|
||||
|
||||
# Anthropic每次只返回一个函数调用
|
||||
if completion.stop_reason == "tool_use":
|
||||
# tools call (function calling)
|
||||
args_ls = []
|
||||
func_name_ls = []
|
||||
tool_use_ids = []
|
||||
func_name_ls.append(content.name)
|
||||
args_ls.append(content.input)
|
||||
tool_use_ids.append(content.id)
|
||||
llm_response.role = "tool"
|
||||
llm_response.tools_call_args = args_ls
|
||||
llm_response.tools_call_name = func_name_ls
|
||||
llm_response.tools_call_ids = tool_use_ids
|
||||
for content_block in completion.content:
|
||||
if content_block.type == "text":
|
||||
completion_text = str(content_block.text).strip()
|
||||
llm_response.completion_text = completion_text
|
||||
|
||||
if content_block.type == "tool_use":
|
||||
llm_response.tools_call_args.append(content_block.input)
|
||||
llm_response.tools_call_name.append(content_block.name)
|
||||
llm_response.tools_call_ids.append(content_block.id)
|
||||
# TODO(Soulter): 处理 end_turn 情况
|
||||
if not llm_response.completion_text and not llm_response.tools_call_args:
|
||||
logger.error(f"API 返回的 completion 无法解析:{completion}。")
|
||||
raise Exception(f"API 返回的 completion 无法解析:{completion}。")
|
||||
|
||||
llm_response.raw_completion = completion
|
||||
raise Exception(f"Anthropic API 返回的 completion 无法解析:{completion}。")
|
||||
|
||||
return llm_response
|
||||
|
||||
async def _query_stream(
|
||||
self, payloads: dict, tools: FuncCall
|
||||
) -> AsyncGenerator[LLMResponse, None]:
|
||||
if tools:
|
||||
if tool_list := tools.get_func_desc_anthropic_style():
|
||||
payloads["tools"] = tool_list
|
||||
|
||||
# 用于累积工具调用信息
|
||||
tool_use_buffer = {}
|
||||
# 用于累积最终结果
|
||||
final_text = ""
|
||||
final_tool_calls = []
|
||||
|
||||
async with self.client.messages.stream(**payloads) as stream:
|
||||
assert isinstance(stream, anthropic.AsyncMessageStream)
|
||||
async for event in stream:
|
||||
if event.type == "content_block_start":
|
||||
if event.content_block.type == "text":
|
||||
# 文本块开始
|
||||
yield LLMResponse(
|
||||
role="assistant", completion_text="", is_chunk=True
|
||||
)
|
||||
elif event.content_block.type == "tool_use":
|
||||
# 工具使用块开始,初始化缓冲区
|
||||
tool_use_buffer[event.index] = {
|
||||
"id": event.content_block.id,
|
||||
"name": event.content_block.name,
|
||||
"input": {},
|
||||
}
|
||||
|
||||
elif event.type == "content_block_delta":
|
||||
if event.delta.type == "text_delta":
|
||||
# 文本增量
|
||||
final_text += event.delta.text
|
||||
yield LLMResponse(
|
||||
role="assistant",
|
||||
completion_text=event.delta.text,
|
||||
is_chunk=True,
|
||||
)
|
||||
elif event.delta.type == "input_json_delta":
|
||||
# 工具调用参数增量
|
||||
if event.index in tool_use_buffer:
|
||||
# 累积 JSON 输入
|
||||
if "input_json" not in tool_use_buffer[event.index]:
|
||||
tool_use_buffer[event.index]["input_json"] = ""
|
||||
tool_use_buffer[event.index]["input_json"] += (
|
||||
event.delta.partial_json
|
||||
)
|
||||
|
||||
elif event.type == "content_block_stop":
|
||||
# 内容块结束
|
||||
if event.index in tool_use_buffer:
|
||||
# 解析完整的工具调用
|
||||
tool_info = tool_use_buffer[event.index]
|
||||
try:
|
||||
if "input_json" in tool_info:
|
||||
tool_info["input"] = json.loads(tool_info["input_json"])
|
||||
|
||||
# 添加到最终结果
|
||||
final_tool_calls.append(
|
||||
{
|
||||
"id": tool_info["id"],
|
||||
"name": tool_info["name"],
|
||||
"input": tool_info["input"],
|
||||
}
|
||||
)
|
||||
|
||||
yield LLMResponse(
|
||||
role="tool",
|
||||
completion_text="",
|
||||
tools_call_args=[tool_info["input"]],
|
||||
tools_call_name=[tool_info["name"]],
|
||||
tools_call_ids=[tool_info["id"]],
|
||||
is_chunk=True,
|
||||
)
|
||||
except json.JSONDecodeError:
|
||||
# JSON 解析失败,跳过这个工具调用
|
||||
logger.warning(f"工具调用参数 JSON 解析失败: {tool_info}")
|
||||
|
||||
# 清理缓冲区
|
||||
del tool_use_buffer[event.index]
|
||||
|
||||
# 返回最终的完整结果
|
||||
final_response = LLMResponse(
|
||||
role="assistant", completion_text=final_text, is_chunk=False
|
||||
)
|
||||
|
||||
if final_tool_calls:
|
||||
final_response.tools_call_args = [
|
||||
call["input"] for call in final_tool_calls
|
||||
]
|
||||
final_response.tools_call_name = [call["name"] for call in final_tool_calls]
|
||||
final_response.tools_call_ids = [call["id"] for call in final_tool_calls]
|
||||
|
||||
yield final_response
|
||||
|
||||
async def text_chat(
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = [],
|
||||
func_tool: FuncCall = None,
|
||||
contexts=[],
|
||||
prompt,
|
||||
session_id=None,
|
||||
image_urls=None,
|
||||
func_tool=None,
|
||||
contexts=None,
|
||||
system_prompt=None,
|
||||
tool_calls_result: ToolCallsResult = None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
if not prompt:
|
||||
prompt = "<image>"
|
||||
|
||||
if contexts is None:
|
||||
contexts = []
|
||||
new_record = await self.assemble_context(prompt, image_urls)
|
||||
context_query = [*contexts, new_record]
|
||||
if system_prompt:
|
||||
context_query.insert(0, {"role": "system", "content": system_prompt})
|
||||
|
||||
for part in context_query:
|
||||
if "_no_save" in part:
|
||||
del part["_no_save"]
|
||||
|
||||
# tool calls result
|
||||
if tool_calls_result:
|
||||
# 暂时这样写。
|
||||
prompt += f"Here are the related results via using tools: {str(tool_calls_result.tool_calls_result)}"
|
||||
if not isinstance(tool_calls_result, list):
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
else:
|
||||
for tcr in tool_calls_result:
|
||||
context_query.extend(tcr.to_openai_messages())
|
||||
|
||||
system_prompt, new_messages = self._prepare_payload(context_query)
|
||||
|
||||
model_config = self.provider_config.get("model_config", {})
|
||||
model_config["model"] = model or self.get_model()
|
||||
|
||||
payloads = {"messages": new_messages, **model_config}
|
||||
|
||||
payloads = {"messages": context_query, **model_config}
|
||||
# Anthropic has a different way of handling system prompts
|
||||
if system_prompt:
|
||||
payloads["system"] = system_prompt
|
||||
@@ -133,32 +271,9 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
llm_response = None
|
||||
try:
|
||||
llm_response = await self._query(payloads, func_tool)
|
||||
|
||||
except Exception as e:
|
||||
if "maximum context length" in str(e):
|
||||
retry_cnt = 20
|
||||
while retry_cnt > 0:
|
||||
logger.warning(
|
||||
f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}"
|
||||
)
|
||||
try:
|
||||
await self.pop_record(context_query)
|
||||
response = await self.client.messages.create(
|
||||
messages=context_query, **model_config
|
||||
)
|
||||
llm_response = LLMResponse("assistant")
|
||||
llm_response.result_chain = MessageChain().message(response.content[0].text)
|
||||
llm_response.raw_completion = response
|
||||
return llm_response
|
||||
except Exception as e:
|
||||
if "maximum context length" in str(e):
|
||||
retry_cnt -= 1
|
||||
else:
|
||||
raise e
|
||||
return LLMResponse("err", "err: 请尝试 /reset 清除会话记录。")
|
||||
else:
|
||||
logger.error(f"发生了错误。Provider 配置如下: {model_config}")
|
||||
raise e
|
||||
logger.error(f"发生了错误。Provider 配置如下: {model_config}")
|
||||
raise e
|
||||
|
||||
return llm_response
|
||||
|
||||
@@ -171,23 +286,41 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
contexts=...,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
):
|
||||
# raise NotImplementedError("This method is not implemented yet.")
|
||||
# 调用 text_chat 模拟流式
|
||||
llm_response = await self.text_chat(
|
||||
prompt=prompt,
|
||||
session_id=session_id,
|
||||
image_urls=image_urls,
|
||||
func_tool=func_tool,
|
||||
contexts=contexts,
|
||||
system_prompt=system_prompt,
|
||||
tool_calls_result=tool_calls_result,
|
||||
)
|
||||
llm_response.is_chunk = True
|
||||
yield llm_response
|
||||
llm_response.is_chunk = False
|
||||
yield llm_response
|
||||
if contexts is None:
|
||||
contexts = []
|
||||
new_record = await self.assemble_context(prompt, image_urls)
|
||||
context_query = [*contexts, new_record]
|
||||
if system_prompt:
|
||||
context_query.insert(0, {"role": "system", "content": system_prompt})
|
||||
|
||||
for part in context_query:
|
||||
if "_no_save" in part:
|
||||
del part["_no_save"]
|
||||
|
||||
# tool calls result
|
||||
if tool_calls_result:
|
||||
if not isinstance(tool_calls_result, list):
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
else:
|
||||
for tcr in tool_calls_result:
|
||||
context_query.extend(tcr.to_openai_messages())
|
||||
|
||||
system_prompt, new_messages = self._prepare_payload(context_query)
|
||||
|
||||
model_config = self.provider_config.get("model_config", {})
|
||||
model_config["model"] = model or self.get_model()
|
||||
|
||||
payloads = {"messages": new_messages, **model_config}
|
||||
|
||||
# Anthropic has a different way of handling system prompts
|
||||
if system_prompt:
|
||||
payloads["system"] = system_prompt
|
||||
|
||||
async for llm_response in self._query_stream(payloads, func_tool):
|
||||
yield llm_response
|
||||
|
||||
async def assemble_context(self, text: str, image_urls: List[str] = None):
|
||||
"""组装上下文,支持文本和图片"""
|
||||
@@ -230,3 +363,28 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
|
||||
)
|
||||
|
||||
return {"role": "user", "content": content}
|
||||
|
||||
async def encode_image_bs64(self, image_url: str) -> str:
|
||||
"""
|
||||
将图片转换为 base64
|
||||
"""
|
||||
if image_url.startswith("base64://"):
|
||||
return image_url.replace("base64://", "data:image/jpeg;base64,")
|
||||
with open(image_url, "rb") as f:
|
||||
image_bs64 = base64.b64encode(f.read()).decode("utf-8")
|
||||
return "data:image/jpeg;base64," + image_bs64
|
||||
return ""
|
||||
|
||||
def get_current_key(self) -> str:
|
||||
return self.chosen_api_key
|
||||
|
||||
async def get_models(self) -> List[str]:
|
||||
models_str = []
|
||||
models = await self.client.models.list()
|
||||
models = sorted(models.data, key=lambda x: x.id)
|
||||
for model in models:
|
||||
models_str.append(model.id)
|
||||
return models_str
|
||||
|
||||
def set_key(self, key: str):
|
||||
self.chosen_api_key = key
|
||||
|
||||
@@ -19,6 +19,7 @@ from ..register import register_provider_adapter
|
||||
TEMP_DIR = Path("data/temp/azure_tts")
|
||||
TEMP_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
|
||||
class OTTSProvider:
|
||||
def __init__(self, config: Dict):
|
||||
self.skey = config["OTTS_SKEY"]
|
||||
@@ -70,12 +71,12 @@ class OTTSProvider:
|
||||
"style": voice_params["style"],
|
||||
"role": voice_params["role"],
|
||||
"rate": voice_params["rate"],
|
||||
"volume": voice_params["volume"]
|
||||
"volume": voice_params["volume"],
|
||||
},
|
||||
headers={
|
||||
"User-Agent": f"AstrBot/{VERSION}",
|
||||
"UAK": "AstrBot/AzureTTS"
|
||||
}
|
||||
"UAK": "AstrBot/AzureTTS",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
file_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
@@ -88,14 +89,19 @@ class OTTSProvider:
|
||||
raise RuntimeError(f"OTTS请求失败: {str(e)}") from e
|
||||
await asyncio.sleep(0.5 * (attempt + 1))
|
||||
|
||||
|
||||
class AzureNativeProvider(TTSProvider):
|
||||
def __init__(self, provider_config: dict, provider_settings: dict):
|
||||
super().__init__(provider_config, provider_settings)
|
||||
self.subscription_key = provider_config.get("azure_tts_subscription_key", "").strip()
|
||||
self.subscription_key = provider_config.get(
|
||||
"azure_tts_subscription_key", ""
|
||||
).strip()
|
||||
if not re.fullmatch(r"^[a-zA-Z0-9]{32}$", self.subscription_key):
|
||||
raise ValueError("无效的Azure订阅密钥")
|
||||
self.region = provider_config.get("azure_tts_region", "eastus").strip()
|
||||
self.endpoint = f"https://{self.region}.tts.speech.microsoft.com/cognitiveservices/v1"
|
||||
self.endpoint = (
|
||||
f"https://{self.region}.tts.speech.microsoft.com/cognitiveservices/v1"
|
||||
)
|
||||
self.client = None
|
||||
self.token = None
|
||||
self.token_expire = 0
|
||||
@@ -104,15 +110,17 @@ class AzureNativeProvider(TTSProvider):
|
||||
"style": provider_config.get("azure_tts_style", "cheerful"),
|
||||
"role": provider_config.get("azure_tts_role", "Boy"),
|
||||
"rate": provider_config.get("azure_tts_rate", "1"),
|
||||
"volume": provider_config.get("azure_tts_volume", "100")
|
||||
"volume": provider_config.get("azure_tts_volume", "100"),
|
||||
}
|
||||
|
||||
async def __aenter__(self):
|
||||
self.client = AsyncClient(headers={
|
||||
"User-Agent": f"AstrBot/{VERSION}",
|
||||
"Content-Type": "application/ssml+xml",
|
||||
"X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm"
|
||||
})
|
||||
self.client = AsyncClient(
|
||||
headers={
|
||||
"User-Agent": f"AstrBot/{VERSION}",
|
||||
"Content-Type": "application/ssml+xml",
|
||||
"X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm",
|
||||
}
|
||||
)
|
||||
return self
|
||||
|
||||
async def __aexit__(self, exc_type, exc_val, exc_tb):
|
||||
@@ -120,10 +128,11 @@ class AzureNativeProvider(TTSProvider):
|
||||
await self.client.aclose()
|
||||
|
||||
async def _refresh_token(self):
|
||||
token_url = f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
|
||||
token_url = (
|
||||
f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
|
||||
)
|
||||
response = await self.client.post(
|
||||
token_url,
|
||||
headers={"Ocp-Apim-Subscription-Key": self.subscription_key}
|
||||
token_url, headers={"Ocp-Apim-Subscription-Key": self.subscription_key}
|
||||
)
|
||||
response.raise_for_status()
|
||||
self.token = response.text
|
||||
@@ -150,8 +159,8 @@ class AzureNativeProvider(TTSProvider):
|
||||
content=ssml,
|
||||
headers={
|
||||
"Authorization": f"Bearer {self.token}",
|
||||
"User-Agent": f"AstrBot/{VERSION}"
|
||||
}
|
||||
"User-Agent": f"AstrBot/{VERSION}",
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
file_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
@@ -160,6 +169,7 @@ class AzureNativeProvider(TTSProvider):
|
||||
f.write(chunk)
|
||||
return str(file_path.resolve())
|
||||
|
||||
|
||||
@register_provider_adapter("azure_tts", "Azure TTS", ProviderType.TEXT_TO_SPEECH)
|
||||
class AzureTTSProvider(TTSProvider):
|
||||
def __init__(self, provider_config: dict, provider_settings: dict):
|
||||
@@ -183,7 +193,7 @@ class AzureTTSProvider(TTSProvider):
|
||||
error_msg = (
|
||||
f"JSON解析失败,请检查格式(错误位置:行 {e.lineno} 列 {e.colno})\n"
|
||||
f"错误详情: {e.msg}\n"
|
||||
f"错误上下文: {json_str[max(0, e.pos-30):e.pos+30]}"
|
||||
f"错误上下文: {json_str[max(0, e.pos - 30) : e.pos + 30]}"
|
||||
)
|
||||
raise ValueError(error_msg) from e
|
||||
except KeyError as e:
|
||||
@@ -202,8 +212,8 @@ class AzureTTSProvider(TTSProvider):
|
||||
"style": self.provider_config.get("azure_tts_style"),
|
||||
"role": self.provider_config.get("azure_tts_role"),
|
||||
"rate": self.provider_config.get("azure_tts_rate"),
|
||||
"volume": self.provider_config.get("azure_tts_volume")
|
||||
}
|
||||
"volume": self.provider_config.get("azure_tts_volume"),
|
||||
},
|
||||
)
|
||||
else:
|
||||
async with self.provider as provider:
|
||||
|
||||
@@ -5,7 +5,6 @@ from typing import List
|
||||
from .. import Provider, Personality
|
||||
from ..entities import LLMResponse
|
||||
from ..func_tool_manager import FuncCall
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from ..register import register_provider_adapter
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from .openai_source import ProviderOpenAIOfficial
|
||||
@@ -19,16 +18,12 @@ class ProviderDashscope(ProviderOpenAIOfficial):
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=False,
|
||||
default_persona: Personality = None,
|
||||
default_persona: Personality | None = None,
|
||||
) -> None:
|
||||
Provider.__init__(
|
||||
self,
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
self.api_key = provider_config.get("dashscope_api_key", "")
|
||||
@@ -72,8 +67,11 @@ class ProviderDashscope(ProviderOpenAIOfficial):
|
||||
func_tool: FuncCall = None,
|
||||
contexts: List = None,
|
||||
system_prompt: str = None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
if contexts is None:
|
||||
contexts = []
|
||||
# 获得会话变量
|
||||
payload_vars = self.variables.copy()
|
||||
# 动态变量
|
||||
@@ -166,6 +164,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
|
||||
contexts=...,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
):
|
||||
# raise NotImplementedError("This method is not implemented yet.")
|
||||
|
||||
@@ -1,10 +1,9 @@
|
||||
import astrbot.core.message.components as Comp
|
||||
import os
|
||||
from typing import List
|
||||
from .. import Provider, Personality
|
||||
from .. import Provider
|
||||
from ..entities import LLMResponse
|
||||
from ..func_tool_manager import FuncCall
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from ..register import register_provider_adapter
|
||||
from astrbot.core.utils.dify_api_client import DifyAPIClient
|
||||
from astrbot.core.utils.io import download_image_by_url, download_file
|
||||
@@ -17,17 +16,13 @@ from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
class ProviderDify(Provider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=False,
|
||||
default_persona: Personality = None,
|
||||
provider_config,
|
||||
provider_settings,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
self.api_key = provider_config.get("dify_api_key", "")
|
||||
@@ -61,13 +56,18 @@ class ProviderDify(Provider):
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = [],
|
||||
image_urls: List[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: List = None,
|
||||
system_prompt: str = None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
if image_urls is None:
|
||||
image_urls = []
|
||||
result = ""
|
||||
session_id = session_id or kwargs.get("user") or "unknown" # 1734
|
||||
conversation_id = self.conversation_ids.get(session_id, "")
|
||||
|
||||
files_payload = []
|
||||
@@ -100,6 +100,7 @@ class ProviderDify(Provider):
|
||||
session_vars = sp.get("session_variables", {})
|
||||
session_var = session_vars.get(session_id, {})
|
||||
payload_vars.update(session_var)
|
||||
payload_vars["system_prompt"] = system_prompt
|
||||
|
||||
try:
|
||||
match self.api_type:
|
||||
@@ -199,6 +200,7 @@ class ProviderDify(Provider):
|
||||
contexts=...,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
):
|
||||
# raise NotImplementedError("This method is not implemented yet.")
|
||||
|
||||
63
astrbot/core/provider/sources/gemini_embedding_source.py
Normal file
63
astrbot/core/provider/sources/gemini_embedding_source.py
Normal file
@@ -0,0 +1,63 @@
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
from google.genai.errors import APIError
|
||||
from ..provider import EmbeddingProvider
|
||||
from ..register import register_provider_adapter
|
||||
from ..entities import ProviderType
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"gemini_embedding",
|
||||
"Google Gemini Embedding 提供商适配器",
|
||||
provider_type=ProviderType.EMBEDDING,
|
||||
)
|
||||
class GeminiEmbeddingProvider(EmbeddingProvider):
|
||||
def __init__(self, provider_config: dict, provider_settings: dict) -> None:
|
||||
super().__init__(provider_config, provider_settings)
|
||||
self.provider_config = provider_config
|
||||
self.provider_settings = provider_settings
|
||||
|
||||
api_key: str = provider_config.get("embedding_api_key")
|
||||
api_base: str = provider_config.get("embedding_api_base", None)
|
||||
timeout: int = int(provider_config.get("timeout", 20))
|
||||
|
||||
http_options = types.HttpOptions(timeout=timeout * 1000)
|
||||
if api_base:
|
||||
if api_base.endswith("/"):
|
||||
api_base = api_base[:-1]
|
||||
http_options.base_url = api_base
|
||||
|
||||
self.client = genai.Client(api_key=api_key, http_options=http_options).aio
|
||||
|
||||
self.model = provider_config.get(
|
||||
"embedding_model", "gemini-embedding-exp-03-07"
|
||||
)
|
||||
self.dimension = provider_config.get("embedding_dimensions", 768)
|
||||
|
||||
async def get_embedding(self, text: str) -> list[float]:
|
||||
"""
|
||||
获取文本的嵌入
|
||||
"""
|
||||
try:
|
||||
result = await self.client.models.embed_content(
|
||||
model=self.model, contents=text
|
||||
)
|
||||
return result.embeddings[0].values
|
||||
except APIError as e:
|
||||
raise Exception(f"Gemini Embedding API请求失败: {e.message}")
|
||||
|
||||
async def get_embeddings(self, texts: list[str]) -> list[list[float]]:
|
||||
"""
|
||||
批量获取文本的嵌入
|
||||
"""
|
||||
try:
|
||||
result = await self.client.models.embed_content(
|
||||
model=self.model, contents=texts
|
||||
)
|
||||
return [embedding.values for embedding in result.embeddings]
|
||||
except APIError as e:
|
||||
raise Exception(f"Gemini Embedding API批量请求失败: {e.message}")
|
||||
|
||||
def get_dim(self) -> int:
|
||||
"""获取向量的维度"""
|
||||
return self.dimension
|
||||
@@ -12,10 +12,9 @@ from google.genai.errors import APIError
|
||||
|
||||
import astrbot.core.message.components as Comp
|
||||
from astrbot import logger
|
||||
from astrbot.api.provider import Personality, Provider
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from astrbot.api.provider import Provider
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
|
||||
from astrbot.core.provider.entities import LLMResponse
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
from astrbot.core.utils.io import download_image_by_url
|
||||
|
||||
@@ -52,17 +51,13 @@ class ProviderGoogleGenAI(Provider):
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=True,
|
||||
default_persona: Personality = None,
|
||||
provider_config,
|
||||
provider_settings,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
self.api_keys: list = provider_config.get("key", [])
|
||||
@@ -141,24 +136,66 @@ class ProviderGoogleGenAI(Provider):
|
||||
logger.warning("流式输出不支持图片模态,已自动降级为文本模态")
|
||||
modalities = ["Text"]
|
||||
|
||||
tool_list = None
|
||||
tool_list = []
|
||||
model_name = self.get_model()
|
||||
native_coderunner = self.provider_config.get("gm_native_coderunner", False)
|
||||
native_search = self.provider_config.get("gm_native_search", False)
|
||||
url_context = self.provider_config.get("gm_url_context", False)
|
||||
|
||||
if native_coderunner:
|
||||
tool_list = [types.Tool(code_execution=types.ToolCodeExecution())]
|
||||
if native_search:
|
||||
logger.warning("已启用代码执行工具,搜索工具将被忽略")
|
||||
if tools:
|
||||
logger.warning("已启用代码执行工具,函数工具将被忽略")
|
||||
elif native_search:
|
||||
tool_list = [types.Tool(google_search=types.GoogleSearch())]
|
||||
if tools:
|
||||
logger.warning("已启用搜索工具,函数工具将被忽略")
|
||||
if "gemini-2.5" in model_name:
|
||||
if native_coderunner:
|
||||
tool_list.append(types.Tool(code_execution=types.ToolCodeExecution()))
|
||||
if native_search:
|
||||
logger.warning("代码执行工具与搜索工具互斥,已忽略搜索工具")
|
||||
if url_context:
|
||||
logger.warning(
|
||||
"代码执行工具与URL上下文工具互斥,已忽略URL上下文工具"
|
||||
)
|
||||
else:
|
||||
if native_search:
|
||||
tool_list.append(types.Tool(google_search=types.GoogleSearch()))
|
||||
|
||||
if url_context:
|
||||
if hasattr(types, "UrlContext"):
|
||||
tool_list.append(types.Tool(url_context=types.UrlContext()))
|
||||
else:
|
||||
logger.warning(
|
||||
"当前 SDK 版本不支持 URL 上下文工具,已忽略该设置,请升级 google-genai 包"
|
||||
)
|
||||
|
||||
elif "gemini-2.0-lite" in model_name:
|
||||
if native_coderunner or native_search or url_context:
|
||||
logger.warning(
|
||||
"gemini-2.0-lite 不支持代码执行、搜索工具和URL上下文,将忽略这些设置"
|
||||
)
|
||||
tool_list = None
|
||||
|
||||
else:
|
||||
if native_coderunner:
|
||||
tool_list.append(types.Tool(code_execution=types.ToolCodeExecution()))
|
||||
if native_search:
|
||||
logger.warning("代码执行工具与搜索工具互斥,已忽略搜索工具")
|
||||
elif native_search:
|
||||
tool_list.append(types.Tool(google_search=types.GoogleSearch()))
|
||||
|
||||
if url_context and not native_coderunner:
|
||||
if hasattr(types, "UrlContext"):
|
||||
tool_list.append(types.Tool(url_context=types.UrlContext()))
|
||||
else:
|
||||
logger.warning(
|
||||
"当前 SDK 版本不支持 URL 上下文工具,已忽略该设置,请升级 google-genai 包"
|
||||
)
|
||||
|
||||
if not tool_list:
|
||||
tool_list = None
|
||||
|
||||
if tools and tool_list:
|
||||
logger.warning("已启用原生工具,函数工具将被忽略")
|
||||
elif tools and (func_desc := tools.get_func_desc_google_genai_style()):
|
||||
tool_list = [
|
||||
types.Tool(function_declarations=func_desc["function_declarations"])
|
||||
]
|
||||
|
||||
return types.GenerateContentConfig(
|
||||
system_instruction=system_instruction,
|
||||
temperature=temperature,
|
||||
@@ -433,6 +470,10 @@ class ProviderGoogleGenAI(Provider):
|
||||
raise
|
||||
continue
|
||||
|
||||
# Accumulate the complete response text for the final response
|
||||
accumulated_text = ""
|
||||
final_response = None
|
||||
|
||||
async for chunk in result:
|
||||
llm_response = LLMResponse("assistant", is_chunk=True)
|
||||
|
||||
@@ -444,32 +485,47 @@ class ProviderGoogleGenAI(Provider):
|
||||
chunk, llm_response
|
||||
)
|
||||
yield llm_response
|
||||
break
|
||||
return
|
||||
|
||||
if chunk.text:
|
||||
accumulated_text += chunk.text
|
||||
llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)])
|
||||
yield llm_response
|
||||
|
||||
if chunk.candidates[0].finish_reason:
|
||||
llm_response = LLMResponse("assistant", is_chunk=False)
|
||||
if not chunk.candidates[0].content.parts:
|
||||
llm_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
|
||||
else:
|
||||
llm_response.result_chain = self._process_content_parts(
|
||||
chunk, llm_response
|
||||
# Process the final chunk for potential tool calls or other content
|
||||
if chunk.candidates[0].content.parts:
|
||||
final_response = LLMResponse("assistant", is_chunk=False)
|
||||
final_response.result_chain = self._process_content_parts(
|
||||
chunk, final_response
|
||||
)
|
||||
yield llm_response
|
||||
break
|
||||
|
||||
# Yield final complete response with accumulated text
|
||||
if not final_response:
|
||||
final_response = LLMResponse("assistant", is_chunk=False)
|
||||
|
||||
# Set the complete accumulated text in the final response
|
||||
if accumulated_text:
|
||||
final_response.result_chain = MessageChain(
|
||||
chain=[Comp.Plain(accumulated_text)]
|
||||
)
|
||||
elif not final_response.result_chain:
|
||||
# If no text was accumulated and no final response was set, provide empty space
|
||||
final_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
|
||||
|
||||
yield final_response
|
||||
|
||||
async def text_chat(
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: list[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: list = None,
|
||||
system_prompt: str = None,
|
||||
tool_calls_result: ToolCallsResult = None,
|
||||
session_id=None,
|
||||
image_urls=None,
|
||||
func_tool=None,
|
||||
contexts=None,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
if contexts is None:
|
||||
@@ -485,10 +541,14 @@ class ProviderGoogleGenAI(Provider):
|
||||
|
||||
# tool calls result
|
||||
if tool_calls_result:
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
if not isinstance(tool_calls_result, list):
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
else:
|
||||
for tcr in tool_calls_result:
|
||||
context_query.extend(tcr.to_openai_messages())
|
||||
|
||||
model_config = self.provider_config.get("model_config", {})
|
||||
model_config["model"] = self.get_model()
|
||||
model_config["model"] = model or self.get_model()
|
||||
|
||||
payloads = {"messages": context_query, **model_config}
|
||||
|
||||
@@ -505,13 +565,14 @@ class ProviderGoogleGenAI(Provider):
|
||||
|
||||
async def text_chat_stream(
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: list[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: str = None,
|
||||
system_prompt: str = None,
|
||||
tool_calls_result: ToolCallsResult = None,
|
||||
prompt,
|
||||
session_id=None,
|
||||
image_urls=None,
|
||||
func_tool=None,
|
||||
contexts=None,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator[LLMResponse, None]:
|
||||
if contexts is None:
|
||||
@@ -527,10 +588,14 @@ class ProviderGoogleGenAI(Provider):
|
||||
|
||||
# tool calls result
|
||||
if tool_calls_result:
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
if not isinstance(tool_calls_result, list):
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
else:
|
||||
for tcr in tool_calls_result:
|
||||
context_query.extend(tcr.to_openai_messages())
|
||||
|
||||
model_config = self.provider_config.get("model_config", {})
|
||||
model_config["model"] = self.get_model()
|
||||
model_config["model"] = model or self.get_model()
|
||||
|
||||
payloads = {"messages": context_query, **model_config}
|
||||
|
||||
@@ -590,7 +655,10 @@ class ProviderGoogleGenAI(Provider):
|
||||
logger.warning(f"图片 {image_url} 得到的结果为空,将忽略。")
|
||||
continue
|
||||
user_content["content"].append(
|
||||
{"type": "image_url", "image_url": {"url": image_data}}
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": image_data},
|
||||
}
|
||||
)
|
||||
return user_content
|
||||
else:
|
||||
|
||||
79
astrbot/core/provider/sources/gemini_tts_source.py
Normal file
79
astrbot/core/provider/sources/gemini_tts_source.py
Normal file
@@ -0,0 +1,79 @@
|
||||
import os
|
||||
import uuid
|
||||
import wave
|
||||
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
from ..entities import ProviderType
|
||||
from ..provider import TTSProvider
|
||||
from ..register import register_provider_adapter
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"gemini_tts", "Gemini TTS API", provider_type=ProviderType.TEXT_TO_SPEECH
|
||||
)
|
||||
class ProviderGeminiTTSAPI(TTSProvider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
) -> None:
|
||||
super().__init__(provider_config, provider_settings)
|
||||
api_key: str = provider_config.get("gemini_tts_api_key", "")
|
||||
api_base: str | None = provider_config.get("gemini_tts_api_base")
|
||||
timeout: int = int(provider_config.get("gemini_tts_timeout", 20))
|
||||
http_options = types.HttpOptions(timeout=timeout * 1000)
|
||||
|
||||
if api_base:
|
||||
if api_base.endswith("/"):
|
||||
api_base = api_base[:-1]
|
||||
http_options.base_url = api_base
|
||||
|
||||
self.client = genai.Client(api_key=api_key, http_options=http_options).aio
|
||||
self.model: str = provider_config.get(
|
||||
"gemini_tts_model", "gemini-2.5-flash-preview-tts"
|
||||
)
|
||||
self.prefix: str | None = provider_config.get(
|
||||
"gemini_tts_prefix",
|
||||
)
|
||||
self.voice_name: str = provider_config.get("gemini_tts_voice_name", "Leda")
|
||||
|
||||
async def get_audio(self, text: str) -> str:
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
path = os.path.join(temp_dir, f"gemini_tts_{uuid.uuid4()}.wav")
|
||||
prompt = f"{self.prefix}: {text}" if self.prefix else text
|
||||
response = await self.client.models.generate_content(
|
||||
model=self.model,
|
||||
contents=prompt,
|
||||
config=types.GenerateContentConfig(
|
||||
response_modalities=["AUDIO"],
|
||||
speech_config=types.SpeechConfig(
|
||||
voice_config=types.VoiceConfig(
|
||||
prebuilt_voice_config=types.PrebuiltVoiceConfig(
|
||||
voice_name=self.voice_name,
|
||||
)
|
||||
)
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
# 不想看类型检查报错
|
||||
if (
|
||||
not response.candidates
|
||||
or not response.candidates[0].content
|
||||
or not response.candidates[0].content.parts
|
||||
or not response.candidates[0].content.parts[0].inline_data
|
||||
or not response.candidates[0].content.parts[0].inline_data.data
|
||||
):
|
||||
raise Exception("No audio content returned from Gemini TTS API.")
|
||||
|
||||
with wave.open(path, "wb") as wf:
|
||||
wf.setnchannels(1)
|
||||
wf.setsampwidth(2)
|
||||
wf.setframerate(24000)
|
||||
wf.writeframes(response.candidates[0].content.parts[0].inline_data.data)
|
||||
|
||||
return path
|
||||
148
astrbot/core/provider/sources/gsv_selfhosted_source.py
Normal file
148
astrbot/core/provider/sources/gsv_selfhosted_source.py
Normal file
@@ -0,0 +1,148 @@
|
||||
import asyncio
|
||||
import os
|
||||
import uuid
|
||||
|
||||
import aiohttp
|
||||
from ..provider import TTSProvider
|
||||
from ..entities import ProviderType
|
||||
from ..register import register_provider_adapter
|
||||
from astrbot import logger
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
provider_type_name="gsv_tts_selfhost",
|
||||
desc="GPT-SoVITS TTS(本地加载)",
|
||||
provider_type=ProviderType.TEXT_TO_SPEECH,
|
||||
)
|
||||
class ProviderGSVTTS(TTSProvider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
) -> None:
|
||||
super().__init__(provider_config, provider_settings)
|
||||
|
||||
self.api_base = provider_config.get("api_base", "http://127.0.0.1:9880").rstrip(
|
||||
"/"
|
||||
)
|
||||
self.gpt_weights_path: str = provider_config.get("gpt_weights_path", "")
|
||||
self.sovits_weights_path: str = provider_config.get("sovits_weights_path", "")
|
||||
|
||||
# TTS 请求的默认参数,移除前缀gsv_
|
||||
self.default_params: dict = {
|
||||
key.removeprefix("gsv_"): str(value).lower()
|
||||
for key, value in provider_config.get("gsv_default_parms", {}).items()
|
||||
}
|
||||
self.timeout = provider_config.get("timeout", 60)
|
||||
self._session: aiohttp.ClientSession | None = None
|
||||
|
||||
async def initialize(self):
|
||||
"""异步初始化:在 ProviderManager 中被调用"""
|
||||
self._session = aiohttp.ClientSession(
|
||||
timeout=aiohttp.ClientTimeout(total=self.timeout)
|
||||
)
|
||||
try:
|
||||
await self._set_model_weights()
|
||||
logger.info("[GSV TTS] 初始化完成")
|
||||
except Exception as e:
|
||||
logger.error(f"[GSV TTS] 初始化失败:{e}")
|
||||
raise
|
||||
|
||||
def get_session(self) -> aiohttp.ClientSession:
|
||||
if not self._session or self._session.closed:
|
||||
raise RuntimeError(
|
||||
"[GSV TTS] Provider HTTP session is not ready or closed."
|
||||
)
|
||||
return self._session
|
||||
|
||||
async def _make_request(
|
||||
self, endpoint: str, params=None, retries: int = 3
|
||||
) -> bytes | None:
|
||||
"""发起请求"""
|
||||
for attempt in range(retries):
|
||||
logger.debug(f"[GSV TTS] 请求地址:{endpoint},参数:{params}")
|
||||
try:
|
||||
async with self.get_session().get(endpoint, params=params) as response:
|
||||
if response.status != 200:
|
||||
error_text = await response.text()
|
||||
raise Exception(
|
||||
f"[GSV TTS] Request to {endpoint} failed with status {response.status}: {error_text}"
|
||||
)
|
||||
return await response.read()
|
||||
except Exception as e:
|
||||
if attempt < retries - 1:
|
||||
logger.warning(
|
||||
f"[GSV TTS] 请求 {endpoint} 第 {attempt + 1} 次失败:{e},重试中..."
|
||||
)
|
||||
await asyncio.sleep(1)
|
||||
else:
|
||||
logger.error(f"[GSV TTS] 请求 {endpoint} 最终失败:{e}")
|
||||
raise
|
||||
|
||||
async def _set_model_weights(self):
|
||||
"""设置模型路径"""
|
||||
try:
|
||||
if self.gpt_weights_path:
|
||||
await self._make_request(
|
||||
f"{self.api_base}/set_gpt_weights",
|
||||
{"weights_path": self.gpt_weights_path},
|
||||
)
|
||||
logger.info(f"[GSV TTS] 成功设置 GPT 模型路径:{self.gpt_weights_path}")
|
||||
else:
|
||||
logger.info("[GSV TTS] GPT 模型路径未配置,将使用内置 GPT 模型")
|
||||
|
||||
if self.sovits_weights_path:
|
||||
await self._make_request(
|
||||
f"{self.api_base}/set_sovits_weights",
|
||||
{"weights_path": self.sovits_weights_path},
|
||||
)
|
||||
logger.info(
|
||||
f"[GSV TTS] 成功设置 SoVITS 模型路径:{self.sovits_weights_path}"
|
||||
)
|
||||
else:
|
||||
logger.info("[GSV TTS] SoVITS 模型路径未配置,将使用内置 SoVITS 模型")
|
||||
except aiohttp.ClientError as e:
|
||||
logger.error(f"[GSV TTS] 设置模型路径时发生网络错误:{e}")
|
||||
except Exception as e:
|
||||
logger.error(f"[GSV TTS] 设置模型路径时发生未知错误:{e}")
|
||||
|
||||
async def get_audio(self, text: str) -> str:
|
||||
"""实现 TTS 核心方法,根据文本内容自动切换情绪"""
|
||||
if not text.strip():
|
||||
raise ValueError("[GSV TTS] TTS 文本不能为空")
|
||||
|
||||
endpoint = f"{self.api_base}/tts"
|
||||
|
||||
params = self.build_synthesis_params(text)
|
||||
|
||||
temp_dir = os.path.join(get_astrbot_data_path(), "temp")
|
||||
os.makedirs(temp_dir, exist_ok=True)
|
||||
path = os.path.join(temp_dir, f"gsv_tts_{uuid.uuid4().hex}.wav")
|
||||
|
||||
logger.debug(f"[GSV TTS] 正在调用语音合成接口,参数:{params}")
|
||||
|
||||
result = await self._make_request(endpoint, params)
|
||||
if isinstance(result, bytes):
|
||||
with open(path, "wb") as f:
|
||||
f.write(result)
|
||||
return path
|
||||
else:
|
||||
raise Exception(f"[GSV TTS] 合成失败,输入文本:{text},错误信息:{result}")
|
||||
|
||||
def build_synthesis_params(self, text: str) -> dict:
|
||||
"""
|
||||
构建语音合成所需的参数字典。
|
||||
|
||||
当前仅包含默认参数 + 文本,未来可在此基础上动态添加如情绪、角色等语义控制字段。
|
||||
"""
|
||||
params = self.default_params.copy()
|
||||
params["text"] = text
|
||||
# TODO: 在此处添加情绪分析,例如 params["emotion"] = detect_emotion(text)
|
||||
return params
|
||||
|
||||
async def terminate(self):
|
||||
"""终止释放资源:在 ProviderManager 中被调用"""
|
||||
if self._session and not self._session.closed:
|
||||
await self._session.close()
|
||||
logger.info("[GSV TTS] Session 已关闭")
|
||||
@@ -1,132 +0,0 @@
|
||||
import os
|
||||
from llmtuner.chat import ChatModel
|
||||
from typing import List
|
||||
from .. import Provider
|
||||
from ..entities import LLMResponse
|
||||
from ..func_tool_manager import FuncCall
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from ..register import register_provider_adapter
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"llm_tuner", "LLMTuner 适配器, 用于装载使用 LlamaFactory 微调后的模型"
|
||||
)
|
||||
class LLMTunerModelLoader(Provider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=True,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
if not os.path.exists(provider_config["base_model_path"]) or not os.path.exists(
|
||||
provider_config["adapter_model_path"]
|
||||
):
|
||||
raise FileNotFoundError("模型文件路径不存在。")
|
||||
self.base_model_path = provider_config["base_model_path"]
|
||||
self.adapter_model_path = provider_config["adapter_model_path"]
|
||||
self.model = ChatModel(
|
||||
{
|
||||
"model_name_or_path": self.base_model_path,
|
||||
"adapter_name_or_path": self.adapter_model_path,
|
||||
"template": provider_config["llmtuner_template"],
|
||||
"finetuning_type": provider_config["finetuning_type"],
|
||||
"quantization_bit": provider_config["quantization_bit"],
|
||||
}
|
||||
)
|
||||
self.set_model(
|
||||
os.path.basename(self.base_model_path)
|
||||
+ "_"
|
||||
+ os.path.basename(self.adapter_model_path)
|
||||
)
|
||||
|
||||
async def assemble_context(self, text: str, image_urls: List[str] = None):
|
||||
"""
|
||||
组装上下文。
|
||||
"""
|
||||
return {"role": "user", "content": text}
|
||||
|
||||
async def text_chat(
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: List = [],
|
||||
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 text_chat_stream(
|
||||
self,
|
||||
prompt,
|
||||
session_id=None,
|
||||
image_urls=...,
|
||||
func_tool=None,
|
||||
contexts=...,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
**kwargs,
|
||||
):
|
||||
# raise NotImplementedError("This method is not implemented yet.")
|
||||
# 调用 text_chat 模拟流式
|
||||
llm_response = await self.text_chat(
|
||||
prompt=prompt,
|
||||
session_id=session_id,
|
||||
image_urls=image_urls,
|
||||
func_tool=func_tool,
|
||||
contexts=contexts,
|
||||
system_prompt=system_prompt,
|
||||
tool_calls_result=tool_calls_result,
|
||||
)
|
||||
llm_response.is_chunk = True
|
||||
yield llm_response
|
||||
llm_response.is_chunk = False
|
||||
yield llm_response
|
||||
|
||||
async def get_current_key(self):
|
||||
return "none"
|
||||
|
||||
async def set_key(self, key):
|
||||
pass
|
||||
|
||||
async def get_models(self):
|
||||
return [self.get_model()]
|
||||
43
astrbot/core/provider/sources/openai_embedding_source.py
Normal file
43
astrbot/core/provider/sources/openai_embedding_source.py
Normal file
@@ -0,0 +1,43 @@
|
||||
from openai import AsyncOpenAI
|
||||
from ..provider import EmbeddingProvider
|
||||
from ..register import register_provider_adapter
|
||||
from ..entities import ProviderType
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"openai_embedding",
|
||||
"OpenAI API Embedding 提供商适配器",
|
||||
provider_type=ProviderType.EMBEDDING,
|
||||
)
|
||||
class OpenAIEmbeddingProvider(EmbeddingProvider):
|
||||
def __init__(self, provider_config: dict, provider_settings: dict) -> None:
|
||||
super().__init__(provider_config, provider_settings)
|
||||
self.provider_config = provider_config
|
||||
self.provider_settings = provider_settings
|
||||
self.client = AsyncOpenAI(
|
||||
api_key=provider_config.get("embedding_api_key"),
|
||||
base_url=provider_config.get(
|
||||
"embedding_api_base", "https://api.openai.com/v1"
|
||||
),
|
||||
timeout=int(provider_config.get("timeout", 20)),
|
||||
)
|
||||
self.model = provider_config.get("embedding_model", "text-embedding-3-small")
|
||||
self.dimension = provider_config.get("embedding_dimensions", 1024)
|
||||
|
||||
async def get_embedding(self, text: str) -> list[float]:
|
||||
"""
|
||||
获取文本的嵌入
|
||||
"""
|
||||
embedding = await self.client.embeddings.create(input=text, model=self.model)
|
||||
return embedding.data[0].embedding
|
||||
|
||||
async def get_embeddings(self, texts: list[str]) -> list[list[float]]:
|
||||
"""
|
||||
批量获取文本的嵌入
|
||||
"""
|
||||
embeddings = await self.client.embeddings.create(input=texts, model=self.model)
|
||||
return [item.embedding for item in embeddings.data]
|
||||
|
||||
def get_dim(self) -> int:
|
||||
"""获取向量的维度"""
|
||||
return self.dimension
|
||||
@@ -9,14 +9,12 @@ import astrbot.core.message.components as Comp
|
||||
from openai import AsyncOpenAI, AsyncAzureOpenAI
|
||||
from openai.types.chat.chat_completion import ChatCompletion
|
||||
|
||||
# from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
|
||||
from openai._exceptions import NotFoundError, UnprocessableEntityError
|
||||
from openai.lib.streaming.chat._completions import ChatCompletionStreamState
|
||||
from astrbot.core.utils.io import download_image_by_url
|
||||
from astrbot.core.message.message_event_result import MessageChain
|
||||
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from astrbot.api.provider import Provider, Personality
|
||||
from astrbot.api.provider import Provider
|
||||
from astrbot import logger
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
from typing import List, AsyncGenerator
|
||||
@@ -30,17 +28,13 @@ from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
|
||||
class ProviderOpenAIOfficial(Provider):
|
||||
def __init__(
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=True,
|
||||
default_persona: Personality = None,
|
||||
provider_config,
|
||||
provider_settings,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
persistant_history,
|
||||
db_helper,
|
||||
default_persona,
|
||||
)
|
||||
self.chosen_api_key = None
|
||||
@@ -87,6 +81,17 @@ class ProviderOpenAIOfficial(Provider):
|
||||
|
||||
async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
|
||||
if tools:
|
||||
# Check if we need to add googleSearch function for Gemini(OpenAI Compatible)
|
||||
if (
|
||||
self.provider_config.get("enable_google_search", False)
|
||||
and self.provider_config.get("api_base", "").find(
|
||||
"generativelanguage.googleapis.com"
|
||||
)
|
||||
!= -1
|
||||
):
|
||||
# Add googleSearch function as alias to web_search
|
||||
await self._add_google_search_tool(tools)
|
||||
|
||||
model = payloads.get("model", "").lower()
|
||||
omit_empty_param_field = "gemini" in model
|
||||
tool_list = tools.get_func_desc_openai_style(
|
||||
@@ -105,6 +110,11 @@ class ProviderOpenAIOfficial(Provider):
|
||||
for key in to_del:
|
||||
del payloads[key]
|
||||
|
||||
# 针对 qwen3 模型的特殊处理:非流式调用必须设置 enable_thinking=false
|
||||
model = payloads.get("model", "")
|
||||
if "qwen3" in model.lower():
|
||||
extra_body["enable_thinking"] = False
|
||||
|
||||
completion = await self.client.chat.completions.create(
|
||||
**payloads, stream=False, extra_body=extra_body
|
||||
)
|
||||
@@ -125,6 +135,17 @@ class ProviderOpenAIOfficial(Provider):
|
||||
) -> AsyncGenerator[LLMResponse, None]:
|
||||
"""流式查询API,逐步返回结果"""
|
||||
if tools:
|
||||
# Check if we need to add googleSearch function for Gemini(OpenAI Compatible)
|
||||
if (
|
||||
self.provider_config.get("enable_google_search", False)
|
||||
and self.provider_config.get("api_base", "").find(
|
||||
"generativelanguage.googleapis.com"
|
||||
)
|
||||
!= -1
|
||||
):
|
||||
# Add googleSearch function as alias to web_search
|
||||
await self._add_google_search_tool(tools)
|
||||
|
||||
model = payloads.get("model", "").lower()
|
||||
omit_empty_param_field = "gemini" in model
|
||||
tool_list = tools.get_func_desc_openai_style(
|
||||
@@ -182,7 +203,7 @@ class ProviderOpenAIOfficial(Provider):
|
||||
raise Exception("API 返回的 completion 为空。")
|
||||
choice = completion.choices[0]
|
||||
|
||||
if choice.message.content:
|
||||
if choice.message.content is not None:
|
||||
# text completion
|
||||
completion_text = str(choice.message.content).strip()
|
||||
llm_response.result_chain = MessageChain().message(completion_text)
|
||||
@@ -193,9 +214,16 @@ class ProviderOpenAIOfficial(Provider):
|
||||
func_name_ls = []
|
||||
tool_call_ids = []
|
||||
for tool_call in choice.message.tool_calls:
|
||||
if isinstance(tool_call, str):
|
||||
# workaround for #1359
|
||||
tool_call = json.loads(tool_call)
|
||||
for tool in tools.func_list:
|
||||
if tool.name == tool_call.function.name:
|
||||
args = json.loads(tool_call.function.arguments)
|
||||
# workaround for #1454
|
||||
if isinstance(tool_call.function.arguments, str):
|
||||
args = json.loads(tool_call.function.arguments)
|
||||
else:
|
||||
args = tool_call.function.arguments
|
||||
args_ls.append(args)
|
||||
func_name_ls.append(tool_call.function.name)
|
||||
tool_call_ids.append(tool_call.id)
|
||||
@@ -209,7 +237,7 @@ class ProviderOpenAIOfficial(Provider):
|
||||
"API 返回的 completion 由于内容安全过滤被拒绝(非 AstrBot)。"
|
||||
)
|
||||
|
||||
if not llm_response.completion_text and not llm_response.tools_call_args:
|
||||
if llm_response.completion_text is None and not llm_response.tools_call_args:
|
||||
logger.error(f"API 返回的 completion 无法解析:{completion}。")
|
||||
raise Exception(f"API 返回的 completion 无法解析:{completion}。")
|
||||
|
||||
@@ -220,12 +248,11 @@ class ProviderOpenAIOfficial(Provider):
|
||||
async def _prepare_chat_payload(
|
||||
self,
|
||||
prompt: str,
|
||||
session_id: str = None,
|
||||
image_urls: list[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts: list=None,
|
||||
system_prompt: str=None,
|
||||
tool_calls_result: ToolCallsResult=None,
|
||||
image_urls: list[str] | None = None,
|
||||
contexts: list | None = None,
|
||||
system_prompt: str | None = None,
|
||||
tool_calls_result: ToolCallsResult | list[ToolCallsResult] | None = None,
|
||||
model: str | None = None,
|
||||
**kwargs,
|
||||
) -> tuple:
|
||||
"""准备聊天所需的有效载荷和上下文"""
|
||||
@@ -242,14 +269,18 @@ class ProviderOpenAIOfficial(Provider):
|
||||
|
||||
# tool calls result
|
||||
if tool_calls_result:
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
if isinstance(tool_calls_result, ToolCallsResult):
|
||||
context_query.extend(tool_calls_result.to_openai_messages())
|
||||
else:
|
||||
for tcr in tool_calls_result:
|
||||
context_query.extend(tcr.to_openai_messages())
|
||||
|
||||
model_config = self.provider_config.get("model_config", {})
|
||||
model_config["model"] = self.get_model()
|
||||
model_config["model"] = model or self.get_model()
|
||||
|
||||
payloads = {"messages": context_query, **model_config}
|
||||
|
||||
return payloads, context_query, func_tool
|
||||
return payloads, context_query
|
||||
|
||||
async def _handle_api_error(
|
||||
self,
|
||||
@@ -340,22 +371,22 @@ class ProviderOpenAIOfficial(Provider):
|
||||
async def text_chat(
|
||||
self,
|
||||
prompt,
|
||||
session_id = None,
|
||||
image_urls = None,
|
||||
func_tool = None,
|
||||
session_id=None,
|
||||
image_urls=None,
|
||||
func_tool=None,
|
||||
contexts=None,
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
payloads, context_query, func_tool = await self._prepare_chat_payload(
|
||||
payloads, context_query = await self._prepare_chat_payload(
|
||||
prompt,
|
||||
session_id,
|
||||
image_urls,
|
||||
func_tool,
|
||||
contexts,
|
||||
system_prompt,
|
||||
tool_calls_result,
|
||||
model=model,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
@@ -415,17 +446,17 @@ class ProviderOpenAIOfficial(Provider):
|
||||
contexts=[],
|
||||
system_prompt=None,
|
||||
tool_calls_result=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator[LLMResponse, None]:
|
||||
"""流式对话,与服务商交互并逐步返回结果"""
|
||||
payloads, context_query, func_tool = await self._prepare_chat_payload(
|
||||
payloads, context_query = await self._prepare_chat_payload(
|
||||
prompt,
|
||||
session_id,
|
||||
image_urls,
|
||||
func_tool,
|
||||
contexts,
|
||||
system_prompt,
|
||||
tool_calls_result,
|
||||
model=model,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
@@ -481,13 +512,8 @@ class ProviderOpenAIOfficial(Provider):
|
||||
"""
|
||||
new_contexts = []
|
||||
|
||||
flag = False
|
||||
for context in contexts:
|
||||
if flag:
|
||||
flag = False # 删除 image 后,下一条(LLM 响应)也要删除
|
||||
continue
|
||||
if isinstance(context["content"], list):
|
||||
flag = True
|
||||
if "content" in context and isinstance(context["content"], list):
|
||||
# continue
|
||||
new_content = []
|
||||
for item in context["content"]:
|
||||
@@ -530,7 +556,10 @@ class ProviderOpenAIOfficial(Provider):
|
||||
logger.warning(f"图片 {image_url} 得到的结果为空,将忽略。")
|
||||
continue
|
||||
user_content["content"].append(
|
||||
{"type": "image_url", "image_url": {"url": image_data}}
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": image_data},
|
||||
}
|
||||
)
|
||||
return user_content
|
||||
else:
|
||||
@@ -546,3 +575,35 @@ class ProviderOpenAIOfficial(Provider):
|
||||
image_bs64 = base64.b64encode(f.read()).decode("utf-8")
|
||||
return "data:image/jpeg;base64," + image_bs64
|
||||
return ""
|
||||
|
||||
async def _add_google_search_tool(self, tools: FuncCall) -> None:
|
||||
"""Add googleSearch function as an alias to web_search for Gemini(OpenAI Compatible)"""
|
||||
# Check if googleSearch is already added
|
||||
for func in tools.func_list:
|
||||
if func.name == "googleSearch":
|
||||
return
|
||||
|
||||
# Check if web_search exists
|
||||
web_search_func = None
|
||||
for func in tools.func_list:
|
||||
if func.name == "web_search":
|
||||
web_search_func = func
|
||||
break
|
||||
|
||||
if web_search_func is None:
|
||||
# If web_search is not available, don't add googleSearch
|
||||
return
|
||||
|
||||
# Add googleSearch as an alias to web_search with English description
|
||||
tools.add_func(
|
||||
name="googleSearch",
|
||||
func_args=[
|
||||
{
|
||||
"type": "string",
|
||||
"name": "query",
|
||||
"description": "The most relevant search keywords for the user's question, used to search on Google.",
|
||||
}
|
||||
],
|
||||
desc="Search the internet to answer user questions using Google search. Call this tool when users need to search the web for real-time information.",
|
||||
handler=web_search_func.handler,
|
||||
)
|
||||
|
||||
@@ -5,12 +5,12 @@ import os
|
||||
import traceback
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import requests
|
||||
from ..provider import TTSProvider
|
||||
from ..entities import ProviderType
|
||||
from ..register import register_provider_adapter
|
||||
from astrbot import logger
|
||||
|
||||
|
||||
@register_provider_adapter(
|
||||
"volcengine_tts", "火山引擎 TTS", provider_type=ProviderType.TEXT_TO_SPEECH
|
||||
)
|
||||
@@ -22,7 +22,9 @@ class ProviderVolcengineTTS(TTSProvider):
|
||||
self.cluster = provider_config.get("volcengine_cluster", "")
|
||||
self.voice_type = provider_config.get("volcengine_voice_type", "")
|
||||
self.speed_ratio = provider_config.get("volcengine_speed_ratio", 1.0)
|
||||
self.api_base = provider_config.get("api_base", f"https://openspeech.bytedance.com/api/v1/tts")
|
||||
self.api_base = provider_config.get(
|
||||
"api_base", "https://openspeech.bytedance.com/api/v1/tts"
|
||||
)
|
||||
self.timeout = provider_config.get("timeout", 20)
|
||||
|
||||
def _build_request_payload(self, text: str) -> dict:
|
||||
@@ -30,11 +32,9 @@ class ProviderVolcengineTTS(TTSProvider):
|
||||
"app": {
|
||||
"appid": self.appid,
|
||||
"token": self.api_key,
|
||||
"cluster": self.cluster
|
||||
},
|
||||
"user": {
|
||||
"uid": str(uuid.uuid4())
|
||||
"cluster": self.cluster,
|
||||
},
|
||||
"user": {"uid": str(uuid.uuid4())},
|
||||
"audio": {
|
||||
"voice_type": self.voice_type,
|
||||
"encoding": "mp3",
|
||||
@@ -48,60 +48,61 @@ class ProviderVolcengineTTS(TTSProvider):
|
||||
"text_type": "plain",
|
||||
"operation": "query",
|
||||
"with_frontend": 1,
|
||||
"frontend_type": "unitTson"
|
||||
}
|
||||
"frontend_type": "unitTson",
|
||||
},
|
||||
}
|
||||
|
||||
async def get_audio(self, text: str) -> str:
|
||||
"""异步方法获取语音文件路径"""
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer; {self.api_key}"
|
||||
"Authorization": f"Bearer; {self.api_key}",
|
||||
}
|
||||
|
||||
|
||||
payload = self._build_request_payload(text)
|
||||
|
||||
|
||||
logger.debug(f"请求头: {headers}")
|
||||
logger.debug(f"请求 URL: {self.api_base}")
|
||||
logger.debug(f"请求体: {json.dumps(payload, ensure_ascii=False)[:100]}...")
|
||||
|
||||
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
self.api_base,
|
||||
data=json.dumps(payload),
|
||||
data=json.dumps(payload),
|
||||
headers=headers,
|
||||
timeout=self.timeout
|
||||
timeout=self.timeout,
|
||||
) as response:
|
||||
logger.debug(f"响应状态码: {response.status}")
|
||||
|
||||
|
||||
response_text = await response.text()
|
||||
logger.debug(f"响应内容: {response_text[:200]}...")
|
||||
|
||||
|
||||
if response.status == 200:
|
||||
resp_data = json.loads(response_text)
|
||||
|
||||
|
||||
if "data" in resp_data:
|
||||
audio_data = base64.b64decode(resp_data["data"])
|
||||
|
||||
|
||||
os.makedirs("data/temp", exist_ok=True)
|
||||
|
||||
|
||||
file_path = f"data/temp/volcengine_tts_{uuid.uuid4()}.mp3"
|
||||
|
||||
|
||||
loop = asyncio.get_running_loop()
|
||||
await loop.run_in_executor(
|
||||
None,
|
||||
lambda: open(file_path, "wb").write(audio_data)
|
||||
None, lambda: open(file_path, "wb").write(audio_data)
|
||||
)
|
||||
|
||||
|
||||
return file_path
|
||||
else:
|
||||
error_msg = resp_data.get("message", "未知错误")
|
||||
raise Exception(f"火山引擎 TTS API 返回错误: {error_msg}")
|
||||
else:
|
||||
raise Exception(f"火山引擎 TTS API 请求失败: {response.status}, {response_text}")
|
||||
|
||||
raise Exception(
|
||||
f"火山引擎 TTS API 请求失败: {response.status}, {response_text}"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
error_details = traceback.format_exc()
|
||||
logger.debug(f"火山引擎 TTS 异常详情: {error_details}")
|
||||
raise Exception(f"火山引擎 TTS 异常: {str(e)}")
|
||||
raise Exception(f"火山引擎 TTS 异常: {str(e)}")
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from astrbot import logger
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
from typing import List
|
||||
@@ -13,15 +12,11 @@ class ProviderZhipu(ProviderOpenAIOfficial):
|
||||
self,
|
||||
provider_config: dict,
|
||||
provider_settings: dict,
|
||||
db_helper: BaseDatabase,
|
||||
persistant_history=True,
|
||||
default_persona=None,
|
||||
) -> None:
|
||||
super().__init__(
|
||||
provider_config,
|
||||
provider_settings,
|
||||
db_helper,
|
||||
persistant_history,
|
||||
default_persona,
|
||||
)
|
||||
|
||||
@@ -31,17 +26,20 @@ class ProviderZhipu(ProviderOpenAIOfficial):
|
||||
session_id: str = None,
|
||||
image_urls: List[str] = None,
|
||||
func_tool: FuncCall = None,
|
||||
contexts=[],
|
||||
contexts=None,
|
||||
system_prompt=None,
|
||||
model=None,
|
||||
**kwargs,
|
||||
) -> LLMResponse:
|
||||
if contexts is None:
|
||||
contexts = []
|
||||
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()
|
||||
model = model or self.get_model()
|
||||
# glm-4v-flash 只支持一张图片
|
||||
if model.lower() == "glm-4v-flash" and image_urls and len(context_query) > 1:
|
||||
logger.debug("glm-4v-flash 只支持一张图片,将只保留最后一张图片")
|
||||
|
||||
@@ -1,20 +0,0 @@
|
||||
from typing import List
|
||||
from openai import AsyncOpenAI
|
||||
|
||||
|
||||
class SimpleOpenAIEmbedding:
|
||||
def __init__(
|
||||
self,
|
||||
model,
|
||||
api_key,
|
||||
api_base=None,
|
||||
) -> None:
|
||||
self.client = AsyncOpenAI(api_key=api_key, base_url=api_base)
|
||||
self.model = model
|
||||
|
||||
async def get_embedding(self, text) -> List[float]:
|
||||
"""
|
||||
获取文本的嵌入
|
||||
"""
|
||||
embedding = await self.client.embeddings.create(input=text, model=self.model)
|
||||
return embedding.data[0].embedding
|
||||
@@ -1,95 +0,0 @@
|
||||
import os
|
||||
from typing import List, Dict
|
||||
from astrbot.core import logger
|
||||
from .store import Store
|
||||
from astrbot.core.config import AstrBotConfig
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class KnowledgeDBManager:
|
||||
def __init__(self, astrbot_config: AstrBotConfig) -> None:
|
||||
self.db_path = os.path.join(get_astrbot_data_path(), "knowledge_db")
|
||||
self.config = astrbot_config.get("knowledge_db", {})
|
||||
self.astrbot_config = astrbot_config
|
||||
if not os.path.exists(self.db_path):
|
||||
os.makedirs(self.db_path)
|
||||
self.store_insts: Dict[str, Store] = {}
|
||||
for name, cfg in self.config.items():
|
||||
if cfg["strategy"] == "embedding":
|
||||
logger.info(f"加载 Chroma Vector Store:{name}")
|
||||
try:
|
||||
from .store.chroma_db import ChromaVectorStore
|
||||
except ImportError as ie:
|
||||
logger.error(f"{ie} 可能未安装 chromadb 库。")
|
||||
continue
|
||||
self.store_insts[name] = ChromaVectorStore(
|
||||
name, cfg["embedding_config"]
|
||||
)
|
||||
else:
|
||||
logger.error(f"不支持的策略:{cfg['strategy']}")
|
||||
|
||||
async def list_knowledge_db(self) -> List[str]:
|
||||
return [
|
||||
f
|
||||
for f in os.listdir(self.db_path)
|
||||
if os.path.isfile(os.path.join(self.db_path, f))
|
||||
]
|
||||
|
||||
async def create_knowledge_db(self, name: str, config: Dict):
|
||||
"""
|
||||
config 格式:
|
||||
```
|
||||
{
|
||||
"strategy": "embedding", # 目前只支持 embedding
|
||||
"chunk_method": {
|
||||
"strategy": "fixed",
|
||||
"chunk_size": 100,
|
||||
"overlap_size": 10
|
||||
},
|
||||
"embedding_config": {
|
||||
"strategy": "openai",
|
||||
"base_url": "",
|
||||
"model": "",
|
||||
"api_key": ""
|
||||
}
|
||||
}
|
||||
```
|
||||
"""
|
||||
if name in self.config:
|
||||
raise ValueError(f"知识库已存在:{name}")
|
||||
|
||||
self.config[name] = config
|
||||
self.astrbot_config["knowledge_db"] = self.config
|
||||
self.astrbot_config.save_config()
|
||||
|
||||
async def insert_record(self, name: str, text: str):
|
||||
if name not in self.store_insts:
|
||||
raise ValueError(f"未找到知识库:{name}")
|
||||
|
||||
ret = []
|
||||
match self.config[name]["chunk_method"]["strategy"]:
|
||||
case "fixed":
|
||||
chunk_size = self.config[name]["chunk_method"]["chunk_size"]
|
||||
chunk_overlap = self.config[name]["chunk_method"]["overlap_size"]
|
||||
ret = self._fixed_chunk(text, chunk_size, chunk_overlap)
|
||||
case _:
|
||||
pass
|
||||
|
||||
for chunk in ret:
|
||||
await self.store_insts[name].save(chunk)
|
||||
|
||||
async def retrive_records(self, name: str, query: str, top_n: int = 3) -> List[str]:
|
||||
if name not in self.store_insts:
|
||||
raise ValueError(f"未找到知识库:{name}")
|
||||
|
||||
inst = self.store_insts[name]
|
||||
return await inst.query(query, top_n)
|
||||
|
||||
def _fixed_chunk(self, text: str, chunk_size: int, chunk_overlap: int) -> List[str]:
|
||||
chunks = []
|
||||
start = 0
|
||||
while start < len(text):
|
||||
end = start + chunk_size
|
||||
chunks.append(text[start:end])
|
||||
start += chunk_size - chunk_overlap
|
||||
return chunks
|
||||
@@ -1,9 +0,0 @@
|
||||
from typing import List
|
||||
|
||||
|
||||
class Store:
|
||||
async def save(self, text: str):
|
||||
pass
|
||||
|
||||
async def query(self, query: str, top_n: int = 3) -> List[str]:
|
||||
pass
|
||||
@@ -1,44 +0,0 @@
|
||||
import chromadb
|
||||
import uuid
|
||||
from typing import List, Dict
|
||||
from astrbot.api import logger
|
||||
from ..embedding.openai_source import SimpleOpenAIEmbedding
|
||||
from . import Store
|
||||
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
|
||||
|
||||
|
||||
class ChromaVectorStore(Store):
|
||||
def __init__(self, name: str, embedding_cfg: Dict) -> None:
|
||||
import os
|
||||
self.chroma_client = chromadb.PersistentClient(
|
||||
path=os.path.join(get_astrbot_data_path(), "long_term_memory_chroma.db")
|
||||
)
|
||||
self.collection = self.chroma_client.get_or_create_collection(name=name)
|
||||
self.embedding = None
|
||||
if embedding_cfg["strategy"] == "openai":
|
||||
self.embedding = SimpleOpenAIEmbedding(
|
||||
model=embedding_cfg["model"],
|
||||
api_key=embedding_cfg["api_key"],
|
||||
api_base=embedding_cfg.get("base_url", None),
|
||||
)
|
||||
|
||||
async def save(self, text: str, metadata: Dict = None):
|
||||
logger.debug(f"Saving text: {text}")
|
||||
embedding = await self.embedding.get_embedding(text)
|
||||
|
||||
self.collection.upsert(
|
||||
documents=text,
|
||||
metadatas=metadata,
|
||||
ids=str(uuid.uuid4()),
|
||||
embeddings=embedding,
|
||||
)
|
||||
|
||||
async def query(
|
||||
self, query: str, top_n=3, metadata_filter: Dict = None
|
||||
) -> List[str]:
|
||||
embedding = await self.embedding.get_embedding(query)
|
||||
|
||||
results = self.collection.query(
|
||||
query_embeddings=embedding, n_results=top_n, where=metadata_filter
|
||||
)
|
||||
return results["documents"][0]
|
||||
@@ -1,4 +1,4 @@
|
||||
from .star import StarMetadata
|
||||
from .star import StarMetadata, star_map, star_registry
|
||||
from .star_manager import PluginManager
|
||||
from .context import Context
|
||||
from astrbot.core.provider import Provider
|
||||
@@ -10,23 +10,48 @@ from astrbot.core.star.star_tools import StarTools
|
||||
class Star(CommandParserMixin):
|
||||
"""所有插件(Star)的父类,所有插件都应该继承于这个类"""
|
||||
|
||||
def __init__(self, context: Context):
|
||||
def __init__(self, context: Context, config: dict | None = None):
|
||||
StarTools.initialize(context)
|
||||
self.context = context
|
||||
|
||||
async def text_to_image(self, text: str, return_url=True) -> str:
|
||||
def __init_subclass__(cls, **kwargs):
|
||||
super().__init_subclass__(**kwargs)
|
||||
if not star_map.get(cls.__module__):
|
||||
metadata = StarMetadata(
|
||||
star_cls_type=cls,
|
||||
module_path=cls.__module__,
|
||||
)
|
||||
star_map[cls.__module__] = metadata
|
||||
star_registry.append(metadata)
|
||||
else:
|
||||
star_map[cls.__module__].star_cls_type = cls
|
||||
star_map[cls.__module__].module_path = cls.__module__
|
||||
|
||||
@staticmethod
|
||||
async def text_to_image(text: str, return_url=True) -> str:
|
||||
"""将文本转换为图片"""
|
||||
return await html_renderer.render_t2i(text, return_url=return_url)
|
||||
|
||||
async def html_render(self, tmpl: str, data: dict, return_url=True) -> str:
|
||||
@staticmethod
|
||||
async def html_render(
|
||||
tmpl: str, data: dict, return_url=True, options: dict = None
|
||||
) -> str:
|
||||
"""渲染 HTML"""
|
||||
return await html_renderer.render_custom_template(
|
||||
tmpl, data, return_url=return_url
|
||||
tmpl, data, return_url=return_url, options=options
|
||||
)
|
||||
|
||||
async def initialize(self):
|
||||
"""当插件被激活时会调用这个方法"""
|
||||
pass
|
||||
|
||||
async def terminate(self):
|
||||
"""当插件被禁用、重载插件时会调用这个方法"""
|
||||
pass
|
||||
|
||||
def __del__(self):
|
||||
"""[Deprecated] 当插件被禁用、重载插件时会调用这个方法"""
|
||||
pass
|
||||
|
||||
|
||||
__all__ = ["Star", "StarMetadata", "PluginManager", "Context", "Provider", "StarTools"]
|
||||
|
||||
@@ -2,7 +2,13 @@ from asyncio import Queue
|
||||
from typing import List, Union
|
||||
|
||||
from astrbot.core import sp
|
||||
from astrbot.core.provider.provider import Provider, TTSProvider, STTProvider
|
||||
from astrbot.core.provider.provider import (
|
||||
Provider,
|
||||
TTSProvider,
|
||||
STTProvider,
|
||||
EmbeddingProvider,
|
||||
)
|
||||
from astrbot.core.provider.entities import ProviderType
|
||||
from astrbot.core.db import BaseDatabase
|
||||
from astrbot.core.config.astrbot_config import AstrBotConfig
|
||||
from astrbot.core.provider.func_tool_manager import FuncCall
|
||||
@@ -16,7 +22,6 @@ from .star_handler import star_handlers_registry, StarHandlerMetadata, EventType
|
||||
from .filter.command import CommandFilter
|
||||
from .filter.regex import RegexFilter
|
||||
from typing import Awaitable
|
||||
from astrbot.core.rag.knowledge_db_mgr import KnowledgeDBManager
|
||||
from astrbot.core.conversation_mgr import ConversationManager
|
||||
from astrbot.core.star.filter.platform_adapter_type import (
|
||||
PlatformAdapterType,
|
||||
@@ -42,6 +47,8 @@ class Context:
|
||||
|
||||
platform_manager: PlatformManager = None
|
||||
|
||||
registered_web_apis: list = []
|
||||
|
||||
# back compatibility
|
||||
_register_tasks: List[Awaitable] = []
|
||||
_star_manager = None
|
||||
@@ -54,14 +61,12 @@ class Context:
|
||||
provider_manager: ProviderManager = None,
|
||||
platform_manager: PlatformManager = None,
|
||||
conversation_manager: ConversationManager = None,
|
||||
knowledge_db_manager: KnowledgeDBManager = None,
|
||||
):
|
||||
self._event_queue = event_queue
|
||||
self._config = config
|
||||
self._db = db
|
||||
self.provider_manager = provider_manager
|
||||
self.platform_manager = platform_manager
|
||||
self.knowledge_db_manager = knowledge_db_manager
|
||||
self.conversation_manager = conversation_manager
|
||||
|
||||
def get_registered_star(self, star_name: str) -> StarMetadata:
|
||||
@@ -126,11 +131,8 @@ class Context:
|
||||
self.provider_manager.provider_insts.append(provider)
|
||||
|
||||
def get_provider_by_id(self, provider_id: str) -> Provider:
|
||||
"""通过 ID 获取用于文本生成任务的 LLM Provider(Chat_Completion 类型)。"""
|
||||
for provider in self.provider_manager.provider_insts:
|
||||
if provider.meta().id == provider_id:
|
||||
return provider
|
||||
return None
|
||||
"""通过 ID 获取对应的 LLM Provider(Chat_Completion 类型)。"""
|
||||
return self.provider_manager.inst_map.get(provider_id)
|
||||
|
||||
def get_all_providers(self) -> List[Provider]:
|
||||
"""获取所有用于文本生成任务的 LLM Provider(Chat_Completion 类型)。"""
|
||||
@@ -144,24 +146,50 @@ class Context:
|
||||
"""获取所有用于 STT 任务的 Provider。"""
|
||||
return self.provider_manager.stt_provider_insts
|
||||
|
||||
def get_using_provider(self) -> Provider:
|
||||
"""
|
||||
获取当前使用的用于文本生成任务的 LLM Provider(Chat_Completion 类型)。
|
||||
def get_all_embedding_providers(self) -> List[EmbeddingProvider]:
|
||||
"""获取所有用于 Embedding 任务的 Provider。"""
|
||||
return self.provider_manager.embedding_provider_insts
|
||||
|
||||
通过 /provider 指令切换。
|
||||
def get_using_provider(self, umo: str = None) -> Provider:
|
||||
"""
|
||||
获取当前使用的用于文本生成任务的 LLM Provider(Chat_Completion 类型)。通过 /provider 指令切换。
|
||||
|
||||
Args:
|
||||
umo(str): unified_message_origin 值,如果传入并且用户启用了提供商会话隔离,则使用该会话偏好的提供商。
|
||||
"""
|
||||
if umo and self._config["provider_settings"]["separate_provider"]:
|
||||
perf = sp.get("session_provider_perf", {})
|
||||
prov_id = perf.get(umo, {}).get(ProviderType.CHAT_COMPLETION.value, None)
|
||||
if inst := self.provider_manager.inst_map.get(prov_id, None):
|
||||
return inst
|
||||
return self.provider_manager.curr_provider_inst
|
||||
|
||||
def get_using_tts_provider(self) -> TTSProvider:
|
||||
def get_using_tts_provider(self, umo: str = None) -> TTSProvider:
|
||||
"""
|
||||
获取当前使用的用于 TTS 任务的 Provider。
|
||||
|
||||
Args:
|
||||
umo(str): unified_message_origin 值,如果传入,则使用该会话偏好的提供商。
|
||||
"""
|
||||
if umo and self._config["provider_settings"]["separate_provider"]:
|
||||
perf = sp.get("session_provider_perf", {})
|
||||
prov_id = perf.get(umo, {}).get(ProviderType.TEXT_TO_SPEECH.value, None)
|
||||
if inst := self.provider_manager.inst_map.get(prov_id, None):
|
||||
return inst
|
||||
return self.provider_manager.curr_tts_provider_inst
|
||||
|
||||
def get_using_stt_provider(self) -> STTProvider:
|
||||
def get_using_stt_provider(self, umo: str = None) -> STTProvider:
|
||||
"""
|
||||
获取当前使用的用于 STT 任务的 Provider。
|
||||
|
||||
Args:
|
||||
umo(str): unified_message_origin 值,如果传入,则使用该会话偏好的提供商。
|
||||
"""
|
||||
if umo and self._config["provider_settings"]["separate_provider"]:
|
||||
perf = sp.get("session_provider_perf", {})
|
||||
prov_id = perf.get(umo, {}).get(ProviderType.SPEECH_TO_TEXT.value, None)
|
||||
if inst := self.provider_manager.inst_map.get(prov_id, None):
|
||||
return inst
|
||||
return self.provider_manager.curr_stt_provider_inst
|
||||
|
||||
def get_config(self) -> AstrBotConfig:
|
||||
@@ -301,3 +329,12 @@ class Context:
|
||||
注册一个异步任务。
|
||||
"""
|
||||
self._register_tasks.append(task)
|
||||
|
||||
def register_web_api(
|
||||
self, route: str, view_handler: Awaitable, methods: list, desc: str
|
||||
):
|
||||
for idx, api in enumerate(self.registered_web_apis):
|
||||
if api[0] == route and methods == api[2]:
|
||||
self.registered_web_apis[idx] = (route, view_handler, methods, desc)
|
||||
return
|
||||
self.registered_web_apis.append((route, view_handler, methods, desc))
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user