Compare commits

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25 Commits

Author SHA1 Message Date
Junyan Qin
4011a302af chore: bump version 4.6.0b2 for testing 2025-11-16 19:28:52 +08:00
Junyan Qin
deb725a2e2 fix: send adapters and requesters icons 2025-11-16 19:26:30 +08:00
Junyan Qin
33eb866660 chore: add templates/** 2025-11-16 19:20:43 +08:00
Junyan Qin
34e2fa03ce chore: bump version 4.6.0-beta.1 for testing 2025-11-16 19:11:02 +08:00
Junyan Qin
7b63bcdc39 ci: publish pypi 2025-11-16 19:09:24 +08:00
Junyan Qin
d26e81620d fix: tests 2025-11-16 18:39:45 +08:00
Junyan Qin
e7885539a7 fix: read default-pipeline-config.json 2025-11-16 18:13:10 +08:00
Junyan Qin
f216505237 fix: read default-pipeline-config.json 2025-11-16 18:12:29 +08:00
Junyan Qin
8b11eefd0c Merge branch 'master' into copilot/create-langbot-python-package 2025-11-16 17:50:37 +08:00
Junyan Qin
418cddd657 chore: fix imports 2025-11-16 17:44:18 +08:00
Junyan Qin
75edeb7a01 chore: adjust dir structure 2025-11-16 16:28:04 +08:00
Junyan Qin
c5aa5be4d8 chore: update 2025-11-07 23:19:51 +08:00
Junyan Qin
92614062cc chore: update 2025-11-07 23:10:57 +08:00
Junyan Qin
09307d8c6d chore: update 2025-11-07 23:04:49 +08:00
Junyan Qin
894db240ae chore: update 2025-11-07 23:02:50 +08:00
Junyan Qin
f79cde5b0c chore: update 2025-11-07 22:55:33 +08:00
Junyan Qin
d43c2c498c chore: try pack templates in langbot/ 2025-11-07 22:51:30 +08:00
Junyan Qin
5f6036c5a8 chore: update pyproject.toml 2025-11-07 22:19:15 +08:00
copilot-swe-agent[bot]
dead0794b1 Simplify package configuration and document behavioral differences
- Removed redundant package-data configuration, relying on MANIFEST.in
- Added documentation about behavioral differences between package and source installation
- Clarified that include-package-data=true uses MANIFEST.in for data files

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 14:08:57 +00:00
copilot-swe-agent[bot]
f784bad08b Fix code review issues
- Use specific exception types instead of bare except
- Fix misleading comments about directory levels
- Remove redundant existence check before makedirs with exist_ok=True
- Use context manager for file opening to ensure proper cleanup

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 14:06:49 +00:00
copilot-swe-agent[bot]
4e86e1c93d Address code review feedback
- Made package-data configuration more specific to langbot package only
- Improved path detection with caching to avoid repeated file I/O
- Removed sys.path searching which was incorrect for package data
- Removed interactive input() call for non-interactive environment compatibility
- Simplified error messages for version check

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 14:04:47 +00:00
copilot-swe-agent[bot]
c0eec966ac Add PyPI installation documentation
- Created PYPI_INSTALLATION.md with detailed installation and usage instructions
- Updated README.md to feature uvx/pip installation as recommended method
- Updated README_EN.md with same changes for English documentation

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 14:02:49 +00:00
copilot-swe-agent[bot]
62d6dae4f5 Add PyPI publishing workflow and update license
- Created GitHub Actions workflow to build frontend and publish to PyPI
- Added license field to pyproject.toml to fix deprecation warning
- Updated .gitignore to exclude build artifacts
- Tested package building successfully

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 14:01:07 +00:00
copilot-swe-agent[bot]
cab573f3e2 Add package structure and resource path utilities
- Created langbot/ package with __init__.py and __main__.py entry point
- Added paths utility to find frontend and resource files from package installation
- Updated config loading to use resource paths
- Updated frontend serving to use resource paths
- Added MANIFEST.in for package data inclusion
- Updated pyproject.toml with build system and entry points

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
2025-11-07 13:58:18 +00:00
copilot-swe-agent[bot]
8fe59da302 Initial plan 2025-11-07 13:48:46 +00:00
331 changed files with 8757 additions and 50484 deletions

View File

@@ -1,8 +0,0 @@
.github
.venv
.vscode
.data
.temp
web/.next
web/node_modules
web/.env

View File

@@ -19,7 +19,7 @@ body:
- type: textarea
attributes:
label: 复现步骤
description: 提供越多信息,我们会越快解决问题,建议多提供配置截图;**如果涉及 Dify、n8n、Langflow 等外部平台,请提供应用的导出文件(如 Dify 应用的 DSL我们将更快回复您。**
description: 提供越多信息,我们会越快解决问题,建议多提供配置截图;**如果你不认真填写(只一两句话概括),我们会很生气并且立即关闭 issue 或两年后才回复你**
validations:
required: false
- type: textarea

View File

@@ -19,7 +19,7 @@ body:
- type: textarea
attributes:
label: Reproduction steps
description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem.
description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem. 【注意】请务必认真填写此部分,若不提供完整信息(如只有一两句话的概括),我们将不会回复!
validations:
required: false
- type: textarea

View File

@@ -2,17 +2,6 @@
> 请在此部分填写你实现/解决/优化的内容:
> Summary of what you implemented/solved/optimized:
>
### 更改前后对比截图 / Screenshots
> 请在此部分粘贴更改前后对比截图(可以是界面截图、控制台输出、对话截图等):
> Please paste the screenshots of changes before and after here (can be interface screenshots, console output, conversation screenshots, etc.):
>
> 修改前 / Before:
>
> 修改后 / After:
>
## 检查清单 / Checklist

View File

@@ -3,6 +3,7 @@ on:
## 发布release的时候会自动构建
release:
types: [published]
workflow_dispatch:
jobs:
publish-docker-image:
runs-on: ubuntu-latest
@@ -41,7 +42,7 @@ jobs:
run: docker buildx create --name mybuilder --use
- name: Build for Release # only relase, exlude pre-release
if: ${{ github.event.release.prerelease == false }}
run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
- name: Build for Pre-release # no update for latest tag
if: ${{ github.event.release.prerelease == true }}
run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push
run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

View File

@@ -1,60 +0,0 @@
name: Lint
on:
push:
branches:
- main
- master
- dev
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
jobs:
ruff:
name: Ruff Lint & Format
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.12'
- name: Install uv
uses: astral-sh/setup-uv@v4
- name: Install dependencies
run: uv sync --dev
- name: Run ruff check
run: uv run ruff check src
- name: Run ruff format
run: uv run ruff format src --check
frontend:
name: Frontend Lint
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '25'
- name: Install pnpm
uses: pnpm/action-setup@v4
with:
version: 9
- name: Install dependencies
working-directory: web
run: pnpm install
- name: Run lint
working-directory: web
run: pnpm lint

View File

@@ -26,7 +26,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.11', '3.12', '3.13']
python-version: ['3.10', '3.11', '3.12']
fail-fast: false
steps:

1
.gitignore vendored
View File

@@ -42,6 +42,7 @@ botpy.log*
test.py
/web_ui
.venv/
uv.lock
/test
plugins.bak
coverage.xml

View File

@@ -1,37 +0,0 @@
{
"mcpServers": {
"shadcn": {
"command": "npx",
"args": [
"shadcn@latest",
"mcp"
]
},
"sequential-thinking": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-sequential-thinking"],
"env": {}
},
"github": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_PERSONAL_ACCESS_TOKEN}"
}
},
"fetch": {
"type": "stdio",
"command": "uvx",
"args": ["mcp-server-fetch"],
"env": {}
},
"playwright": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@playwright/mcp@latest"],
"env": {}
}
}
}

View File

@@ -8,17 +8,16 @@ LangBot is a open-source LLM native instant messaging bot development platform,
LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
- `./src/langbot`: The main python package of the project, below are the main modules in this package:
- `./pkg`: The core python package of the project backend.
- `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
- `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
- `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
- `./pkg/api`: The api module of the project, containing the http api controllers and services.
- `./pkg/plugin`: LangBot bridge for connecting with plugin system.
- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
- `./templates`: Templates of config files, components, etc.
- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
- `./docker`: docker-compose deployment files.
- `./pkg`: The core python package of the project backend.
- `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
- `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
- `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
- `./pkg/api`: The api module of the project, containing the http api controllers and services.
- `./pkg/plugin`: LangBot bridge for connecting with plugin system.
- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
- `./templates`: Templates of config files, components, etc.
- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
- `./docker`: docker-compose deployment files.
## Backend Development
@@ -70,7 +69,6 @@ Plugin Runtime automatically starts each installed plugin and interacts through
- type: must be a specific type, such as feat (new feature), fix (bug fix), docs (documentation), style (code style), refactor (refactoring), perf (performance optimization), etc.
- scope: the scope of the commit, such as the package name, the file name, the function name, the class name, the module name, etc.
- subject: the subject of the commit, such as the description of the commit, the reason for the commit, the impact of the commit, etc.
- If you changed the definition of database entities, please update the migration file in `src/langbot/pkg/persistence/migrations/` and update the constants.py file in `src/langbot/pkg/utils/constants.py` with the new migration number.
## Some Principles

View File

@@ -20,4 +20,4 @@ RUN apt update \
&& uv sync \
&& touch /.dockerenv
CMD [ "uv", "run", "--no-sync", "main.py" ]
CMD [ "uv", "run", "main.py" ]

239
README.md
View File

@@ -1,69 +1,56 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="FeaturedHelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>Production-grade platform for building agentic IM bots.</h3>
<h4>Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.</h4>
English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
<a href="https://langbot.app">项目主页</a>
<a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a>
<a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">插件介绍</a>
<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
<a href="https://langbot.app">Website</a>
<a href="https://docs.langbot.app/en/insight/features">Features</a>
<a href="https://docs.langbot.app/en/insight/guide">Docs</a>
<a href="https://docs.langbot.app/en/tags/readme">API</a>
<a href="https://space.langbot.app/cloud">Cloud</a>
<a href="https://space.langbot.app">Plugin Market</a>
<a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
</div>
</p>
---
LangBot 是一个开源的大语言模型原生即时通信机器人开发平台,旨在提供开箱即用的 IM 机器人开发体验,具有 Agent、RAG、MCP 等多种 LLM 应用功能,适配全球主流即时通信平台,并提供丰富的 API 接口,支持自定义开发。
## What is LangBot?
## 📦 开始使用
LangBot is an **open-source, production-grade platform** for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.
#### 快速体验(推荐)
### Key Capabilities
- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Universal IM Platform Support** — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Production-Ready** — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
- **Plugin Ecosystem** — Hundreds of plugins, event-driven architecture, component extensions, and [MCP protocol](https://modelcontextprotocol.io/) support.
- **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
- **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
---
## Quick Start
### ☁️ LangBot Cloud (Recommended)
**[LangBot Cloud](https://space.langbot.app/cloud)** — Zero deployment, ready to use.
### One-Line Launch
使用 `uvx` 一键启动(无需安装):
```bash
uvx langbot
```
> Requires [uv](https://docs.astral.sh/uv/getting-started/installation/). Visit http://localhost:5300 — done.
或使用 `pip` 安装后运行:
### Docker Compose
```bash
pip install langbot
langbot
```
访问 http://localhost:5300 即可开始使用。
详细文档[PyPI 安装](docs/PYPI_INSTALLATION.md)。
#### Docker Compose 部署
```bash
git clone https://github.com/langbot-app/LangBot
@@ -71,102 +58,122 @@ cd LangBot/docker
docker compose up -d
```
### One-Click Cloud Deploy
访问 http://localhost:5300 即可开始使用。
详细文档[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
#### 宝塔面板部署
已上架宝塔面板,若您已安装宝塔面板,可以根据[文档](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
#### Zeabur 云部署
社区贡献的 Zeabur 模板。
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
#### Railway 云部署
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
#### 手动部署
---
直接使用发行版运行,查看文档[手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
## Supported Platforms
#### Kubernetes 部署
| Platform | Status | Notes |
|----------|--------|-------|
参考 [Kubernetes 部署](./docker/README_K8S.md) 文档。
## 😎 保持更新
点击仓库右上角 Star 和 Watch 按钮,获取最新动态。
![star gif](https://docs.langbot.app/star.gif)
## ✨ 特性
- 💬 大模型对话、Agent支持多种大模型适配群聊和私聊具有多轮对话、工具调用、多模态、流式输出能力自带 RAG知识库实现并深度适配 [Dify](https://dify.ai)。
- 🤖 多平台支持:目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
- 🛠️ 高稳定性、功能完备:原生支持访问控制、限速、敏感词过滤等机制;配置简单,支持多种部署方式。支持多流水线配置,不同机器人用于不同应用场景。
- 🧩 插件扩展、活跃社区:支持事件驱动、组件扩展等插件机制;适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/);目前已有数百个插件。
- 😻 Web 管理面板:支持通过浏览器管理 LangBot 实例,不再需要手动编写配置文件。
详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
或访问 demo 环境https://demo.langbot.dev/
- 登录信息:邮箱:`demo@langbot.app` 密码:`langbot123456`
- 注意:仅展示 WebUI 效果,公开环境,请不要在其中填入您的任何敏感信息。
### 消息平台
| 平台 | 状态 | 备注 |
| --- | --- | --- |
| QQ 个人号 | ✅ | QQ 个人号私聊、群聊 |
| QQ 官方机器人 | ✅ | QQ 官方机器人,支持频道、私聊、群聊 |
| 企业微信 | ✅ | |
| 企微对外客服 | ✅ | |
| 企微智能机器人 | ✅ | |
| 个人微信 | ✅ | |
| 微信公众号 | ✅ | |
| 飞书 | ✅ | |
| 钉钉 | ✅ | |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | Personal & Official API |
| WeCom | ✅ | Enterprise WeChat, External CS, AI Bot |
| WeChat | ✅ | Personal & Official Account |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
### 大模型能力
## Supported LLMs & Integrations
| 模型 | 状态 | 备注 |
| --- | --- | --- |
| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 接口格式模型 |
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
| [Anthropic](https://www.anthropic.com/) | ✅ | |
| [xAI](https://x.ai/) | ✅ | |
| [智谱AI](https://open.bigmodel.cn/) | ✅ | |
| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 全球大模型都可调用(友情推荐) |
| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台,专注全球大模型接入 |
| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
| [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 |
| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型运行平台 |
| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型接口聚合平台 |
| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
| [小马算力](https://www.tokenpony.cn/453z1) | ✅ | 大模型聚合平台 |
| [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台每月免费10亿大模型Token |
| Provider | Type | Status |
|----------|------|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | Local LLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | Local LLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | Protocol | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | Gateway | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Gateway | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Gateway | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Gateway | ✅ |
| [GiteeAI](https://ai.gitee.com/) | Gateway | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU Platform | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU Platform | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU Platform | ✅ |
| [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
### TTS
[→ View all integrations](https://docs.langbot.app/en/insight/features)
| 平台/模型 | 备注 |
| --- | --- |
| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
---
### 文生图
## Why LangBot?
| 平台/模型 | 备注 |
| --- | --- |
| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
| Use Case | How LangBot Helps |
|----------|-------------------|
| **Customer Support** | Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base |
| **Internal Tools** | Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes |
| **Community Management** | Moderate QQ/Discord groups with AI-powered content filtering and interaction |
| **Multi-Platform Presence** | One bot, all platforms. Manage from a single dashboard |
## 😘 社区贡献
---
## Live Demo
**Try it now:** https://demo.langbot.dev/
- Email: `demo@langbot.app`
- Password: `langbot123456`
*Note: Public demo environment. Do not enter sensitive information.*
---
## Community
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Discord Community](https://discord.gg/wdNEHETs87)
---
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## Contributors
Thanks to all [contributors](https://github.com/langbot-app/LangBot/graphs/contributors) who have helped make LangBot better:
感谢以下[代码贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>
<!--
## For Code Agents
If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
-->

View File

@@ -1,197 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="FeaturedHelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>生产级 AI 即时通信机器人开发平台。</h3>
<h4>快速构建、调试和部署 AI 机器人到微信、QQ、飞书、Slack、Discord、Telegram 等平台。</h4>
[English](README.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
<a href="https://langbot.app">官网</a>
<a href="https://docs.langbot.app/zh/insight/features.html">特性</a>
<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a>
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a>
<a href="https://space.langbot.app/cloud">Cloud</a>
<a href="https://space.langbot.app">插件市场</a>
<a href="https://langbot.featurebase.app/roadmap">路线图</a>
</div>
</p>
---
## 什么是 LangBot
LangBot 是一个**开源的生产级平台**,用于构建 AI 驱动的即时通信机器人。它将大语言模型LLM连接到各种聊天平台帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
### 核心能力
- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG知识库深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
- **全平台支持** — 一套代码,覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
- **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理,已被多家企业采用。
- **插件生态** — 数百个插件,事件驱动架构,组件扩展,适配 [MCP 协议](https://modelcontextprotocol.io/)。
- **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人,无需手动编辑配置文件。
- **多流水线架构** — 不同机器人用于不同场景,具备全面的监控和异常处理能力。
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
---
## 快速开始
### ☁️ LangBot Cloud推荐
**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署,开箱即用。
### 一键启动
```bash
uvx langbot
```
> 需要安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)。访问 http://localhost:5300 即可使用。
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### 一键云部署
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**更多方式:** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## 支持的平台
| 平台 | 状态 | 备注 |
|------|------|------|
| QQ | ✅ | 个人号、官方机器人(频道、私聊、群聊) |
| 微信 | ✅ | 个人微信、微信公众号 |
| 企业微信 | ✅ | 应用消息、对外客服、智能机器人 |
| 飞书 | ✅ | |
| 钉钉 | ✅ | |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| KOOK | ✅ | |
---
## 支持的大模型与集成
| 提供商 | 类型 | 状态 |
|--------|------|------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [智谱AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | 协议 | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
| [阿里云百炼](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
| [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
| [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
[→ 查看完整集成列表](https://docs.langbot.app/zh/insight/features.html)
### TTS语音合成
| 平台/模型 | 备注 |
|-----------|------|
| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
### 文生图
| 平台/模型 | 备注 |
|-----------|------|
| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
---
## 为什么选择 LangBot
| 使用场景 | LangBot 如何帮助 |
|----------|------------------|
| **客户服务** | 将 AI Agent 部署到微信/企微/钉钉/飞书,基于知识库自动回答用户问题 |
| **内部工具** | 将 n8n/Dify 工作流接入企微/钉钉,实现业务流程自动化 |
| **社群运营** | 在 QQ/Discord 群中使用 AI 驱动的内容审核与智能互动 |
| **多平台触达** | 一个机器人,覆盖所有平台。通过统一面板集中管理 |
---
## 在线演示
**立即体验:** https://demo.langbot.dev/
- 邮箱:`demo@langbot.app`
- 密码:`langbot123456`
*注意:公开演示环境,请不要在其中填入任何敏感信息。*
---
## 社区
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
- [Discord 社区](https://discord.gg/wdNEHETs87)
- [QQ 社区群](https://qm.qq.com/q/DxZZcNxM1W)
---
## Star 趋势
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## 贡献者
感谢所有[贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)对 LangBot 的帮助:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>
<!--
## For Code Agents
If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
-->

150
README_EN.md Normal file
View File

@@ -0,0 +1,150 @@
<p align="center">
<a href="https://langbot.app">
<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
</a>
<div align="center">
English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
<a href="https://langbot.app">Home</a>
<a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a>
<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a>
<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
</div>
</p>
LangBot is an open-source LLM native instant messaging robot development platform, aiming to provide out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, adapting to global instant messaging platforms, and providing rich API interfaces, supporting custom development.
## 📦 Getting Started
#### Quick Start (Recommended)
Use `uvx` to start with one command (no installation required):
```bash
uvx langbot
```
Or install with `pip` and run:
```bash
pip install langbot
langbot
```
Visit http://localhost:5300 to start using it.
Detailed documentation [PyPI Installation](docs/PYPI_INSTALLATION.md).
#### Docker Compose Deployment
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
Visit http://localhost:5300 to start using it.
Detailed documentation [Docker Deployment](https://docs.langbot.app/en/deploy/langbot/docker.html).
#### One-click Deployment on BTPanel
LangBot has been listed on the BTPanel, if you have installed the BTPanel, you can use the [document](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) to use it.
#### Zeabur Cloud Deployment
Community contributed Zeabur template.
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
#### Railway Cloud Deployment
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
#### Other Deployment Methods
Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
#### Kubernetes Deployment
Refer to the [Kubernetes Deployment](./docker/README_K8S.md) documentation.
## 😎 Stay Ahead
Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
![star gif](https://docs.langbot.app/star.gif)
## ✨ Features
- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai).
- 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
- 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
- 😻 Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
Or visit the demo environment: https://demo.langbot.dev/
- Login information: Email: `demo@langbot.app` Password: `langbot123456`
- Note: For WebUI demo only, please do not fill in any sensitive information in the public environment.
### Message Platform
| Platform | Status | Remarks |
| --- | --- | --- |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| Personal QQ | ✅ | |
| QQ Official API | ✅ | |
| WeCom | ✅ | |
| WeComCS | ✅ | |
| WeCom AI Bot | ✅ | |
| Personal WeChat | ✅ | |
| Lark | ✅ | |
| DingTalk | ✅ | |
### LLMs
| LLM | Status | Remarks |
| --- | --- | --- |
| [OpenAI](https://platform.openai.com/) | ✅ | Available for any OpenAI interface format model |
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
| [Anthropic](https://www.anthropic.com/) | ✅ | |
| [xAI](https://x.ai/) | ✅ | |
| [Zhipu AI](https://open.bigmodel.cn/) | ✅ | |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform |
| [Dify](https://dify.ai) | ✅ | LLMOps platform |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
| [接口 AI](https://jiekou.ai/) | ✅ | LLM aggregation platform, dedicated to global LLMs |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform |
| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
| [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |
| [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform |
| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM interface gateway(MaaS) |
| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM gateway(MaaS) |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM gateway(MaaS), LLMOps platform |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM gateway(MaaS), LLMOps platform |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM gateway(MaaS) |
| [MCP](https://modelcontextprotocol.io/) | ✅ | Support tool access through MCP protocol |
## 🤝 Community Contribution
Thank you for the following [code contributors](https://github.com/langbot-app/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -1,171 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>Plataforma de grado de producción para construir bots de mensajería instantánea con agentes de IA.</h3>
<h4>Construya, depure y despliegue bots de IA rápidamente en Slack, Discord, Telegram, WeChat y más.</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / Español / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">Inicio</a>
<a href="https://docs.langbot.app/en/insight/features.html">Características</a>
<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a>
<a href="https://docs.langbot.app/en/tags/readme.html">API</a>
<a href="https://space.langbot.app">Mercado de Plugins</a>
<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
</div>
</p>
---
## ¿Qué es LangBot?
LangBot es una **plataforma de código abierto y grado de producción** para construir bots de mensajería instantánea impulsados por IA. Conecta modelos de lenguaje de gran escala (LLMs) con cualquier plataforma de chat, permitiéndole crear agentes inteligentes que pueden conversar, ejecutar tareas e integrarse con sus flujos de trabajo existentes.
### Capacidades Clave
- **Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Soporte Universal de Plataformas de MI** — Un solo código base para Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Listo para Producción** — Control de acceso, limitación de velocidad, filtrado de palabras sensibles, monitoreo completo y manejo de excepciones. De confianza para empresas.
- **Ecosistema de Plugins** — Cientos de plugins, arquitectura basada en eventos, extensiones de componentes y soporte del [protocolo MCP](https://modelcontextprotocol.io/).
- **Panel de Gestión Web** — Configure, gestione y monitoree sus bots a través de una interfaz de navegador intuitiva. Sin necesidad de editar YAML.
- **Arquitectura Multi-Pipeline** — Diferentes bots para diferentes escenarios, con monitoreo completo y manejo de excepciones.
[→ Conocer más sobre todas las funcionalidades](https://docs.langbot.app/en/insight/features.html)
---
## Inicio Rápido
### ☁️ LangBot Cloud (Recomendado)
**[LangBot Cloud](https://space.langbot.app/cloud)** — Sin despliegue, listo para usar.
### Lanzamiento en una línea
```bash
uvx langbot
```
> Requiere [uv](https://docs.astral.sh/uv/getting-started/installation/). Visite http://localhost:5300 — listo.
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### Despliegue en la Nube con un Clic
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## Plataformas Soportadas
| Plataforma | Estado | Notas |
|----------|--------|-------|
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | Personal y API Oficial |
| WeCom | ✅ | WeChat Empresarial, CS Externo, AI Bot |
| WeChat | ✅ | Personal y Cuenta Oficial |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
## LLMs e Integraciones Soportadas
| Proveedor | Tipo | Estado |
|----------|------|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | LLM Local | ✅ |
| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | Protocolo | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | Pasarela | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Pasarela | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Pasarela | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Pasarela | ✅ |
| [GiteeAI](https://ai.gitee.com/) | Pasarela | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plataforma GPU | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plataforma GPU | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plataforma GPU | ✅ |
| [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
[→ Ver todas las integraciones](https://docs.langbot.app/en/insight/features.html)
---
## ¿Por qué LangBot?
| Caso de Uso | Cómo Ayuda LangBot |
|----------|-------------------|
| **Atención al cliente** | Despliegue agentes de IA en Slack/Discord/Telegram que respondan preguntas usando su base de conocimientos |
| **Herramientas internas** | Conecte flujos de trabajo de n8n/Dify a WeCom/DingTalk para procesos empresariales automatizados |
| **Gestión de comunidades** | Modere grupos de QQ/Discord con filtrado de contenido e interacción impulsados por IA |
| **Presencia multiplataforma** | Un solo bot, todas las plataformas. Gestione desde un único panel de control |
---
## Demo en Vivo
**Pruébelo ahora:** https://demo.langbot.dev/
- Correo electrónico: `demo@langbot.app`
- Contraseña: `langbot123456`
*Nota: Entorno de demostración público. No ingrese información confidencial.*
---
## Comunidad
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Comunidad de Discord](https://discord.gg/wdNEHETs87)
---
## Historial de Stars
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## Colaboradores
Gracias a todos los [colaboradores](https://github.com/langbot-app/LangBot/graphs/contributors) que han ayudado a mejorar LangBot:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -1,171 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>Plateforme de niveau production pour construire des bots de messagerie instantanée avec agents IA.</h3>
<h4>Créez, déboguez et déployez rapidement des bots IA sur Slack, Discord, Telegram, WeChat et plus.</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / Français / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">Accueil</a>
<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a>
<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a>
<a href="https://docs.langbot.app/en/tags/readme.html">API</a>
<a href="https://space.langbot.app">Marché des Plugins</a>
<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
</div>
</p>
---
## Qu'est-ce que LangBot ?
LangBot est une **plateforme open-source de niveau production** pour créer des bots de messagerie instantanée alimentés par l'IA. Elle connecte les grands modèles de langage (LLMs) à n'importe quelle plateforme de chat, vous permettant de créer des agents intelligents capables de converser, d'exécuter des tâches et de s'intégrer à vos workflows existants.
### Capacités Clés
- **Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Support Universel des Plateformes de MI** — Un seul code pour Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Prêt pour la Production** — Contrôle d'accès, limitation de débit, filtrage de mots sensibles, surveillance complète et gestion des exceptions. Approuvé par les entreprises.
- **Écosystème de Plugins** — Des centaines de plugins, architecture événementielle, extensions de composants, et support du [protocole MCP](https://modelcontextprotocol.io/).
- **Panneau de Gestion Web** — Configurez, gérez et surveillez vos bots via une interface navigateur intuitive. Aucune édition de YAML requise.
- **Architecture Multi-Pipeline** — Différents bots pour différents scénarios, avec surveillance complète et gestion des exceptions.
[→ En savoir plus sur toutes les fonctionnalités](https://docs.langbot.app/en/insight/features.html)
---
## Démarrage Rapide
### ☁️ LangBot Cloud (Recommandé)
**[LangBot Cloud](https://space.langbot.app/cloud)** — Sans déploiement, prêt à utiliser.
### Lancement en une ligne
```bash
uvx langbot
```
> Nécessite [uv](https://docs.astral.sh/uv/getting-started/installation/). Visitez http://localhost:5300 — c'est prêt.
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### Déploiement Cloud en un Clic
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## Plateformes Supportées
| Plateforme | Statut | Notes |
|----------|--------|-------|
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | Personnel & API Officielle |
| WeCom | ✅ | WeChat Entreprise, CS Externe, AI Bot |
| WeChat | ✅ | Personnel & Compte Officiel |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
## LLMs et Intégrations Supportés
| Fournisseur | Type | Statut |
|----------|------|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | LLM Local | ✅ |
| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | Protocole | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | Passerelle | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Passerelle | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Passerelle | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Passerelle | ✅ |
| [GiteeAI](https://ai.gitee.com/) | Passerelle | ✅ |
| [接口 AI](https://jiekou.ai/) | Passerelle | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | Passerelle | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plateforme GPU | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
[→ Voir toutes les intégrations](https://docs.langbot.app/en/insight/features.html)
---
## Pourquoi LangBot ?
| Cas d'Usage | Comment LangBot Aide |
|----------|-------------------|
| **Support Client** | Déployez des agents IA sur Slack/Discord/Telegram qui répondent aux questions en utilisant votre base de connaissances |
| **Outils Internes** | Connectez les workflows n8n/Dify à WeCom/DingTalk pour automatiser vos processus métier |
| **Gestion de Communauté** | Modérez les groupes QQ/Discord avec un filtrage de contenu et des interactions alimentés par l'IA |
| **Présence Multi-plateforme** | Un seul bot, toutes les plateformes. Gérez tout depuis un tableau de bord unique |
---
## Démo en Ligne
**Essayez maintenant :** https://demo.langbot.dev/
- Email : `demo@langbot.app`
- Mot de passe : `langbot123456`
*Note : Environnement de démonstration public. Ne saisissez pas d'informations sensibles.*
---
## Communauté
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Communauté Discord](https://discord.gg/wdNEHETs87)
---
## Historique des Stars
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## Contributeurs
Merci à tous les [contributeurs](https://github.com/langbot-app/LangBot/graphs/contributors) qui ont aidé à améliorer LangBot :
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -1,68 +1,31 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>AIエージェント搭載IMボットを構築するための本番グレードプラットフォーム。</h3>
<h4>Slack、Discord、Telegram、WeChat などに AI ボットを素早く構築、デバッグ、デプロイ。</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / 日本語 / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / (PR for your language)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">ホーム</a>
<a href="https://docs.langbot.app/ja/insight/features.html">機能</a>
<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a>
<a href="https://docs.langbot.app/ja/tags/readme.html">API</a>
<a href="https://space.langbot.app">プラグインマーケット</a>
<a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
<a href="https://docs.langbot.app/en/insight/guide.html">デプロイ</a>
<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">プラグイン</a>
<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
</div>
</p>
---
LangBot は、エージェント、RAG、MCP などの LLM アプリケーション機能を備えた、オープンソースの LLM ネイティブのインスタントメッセージングロボット開発プラットフォームです。世界中のインスタントメッセージングプラットフォームに適応し、豊富な API インターフェースを提供し、カスタム開発をサポートします。
## LangBot とは?
## 📦 始め方
LangBot は、AI搭載のインスタントメッセージングボットを構築するための**オープンソースの本番グレードプラットフォーム**です。大規模言語モデルLLMをあらゆるチャットプラットフォームに接続し、会話、タスク実行、既存のワークフローとの統合が可能なインテリジェントエージェントを作成できます。
### 主な機能
- **AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAGナレッジベースを内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) と深く統合。
- **ユニバーサルIMプラットフォーム対応** — 単一のコードベースで Discord、Telegram、Slack、LINE、QQ、WeChat、WeCom、Lark、DingTalk、KOOK に対応。
- **本番環境対応** — アクセス制御、レート制限、センシティブワードフィルタリング、包括的な監視、例外処理を搭載。エンタープライズの信頼に応える品質。
- **プラグインエコシステム** — 数百のプラグイン、イベント駆動アーキテクチャ、コンポーネント拡張、[MCPプロトコル](https://modelcontextprotocol.io/)対応。
- **Web管理パネル** — 直感的なブラウザインターフェースからボットの設定、管理、監視が可能。YAML編集は不要。
- **マルチパイプラインアーキテクチャ** — 異なるシナリオに異なるボットを配置し、包括的な監視と例外処理を実現。
[→ すべての機能について詳しく見る](https://docs.langbot.app/ja/insight/features.html)
---
## クイックスタート
### ☁️ LangBot Cloud推奨
**[LangBot Cloud](https://space.langbot.app/cloud)** — デプロイ不要、すぐに使えます。
### ワンライン起動
```bash
uvx langbot
```
> [uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です。http://localhost:5300 にアクセスして完了。
### Docker Compose
#### Docker Compose デプロイ
```bash
git clone https://github.com/langbot-app/LangBot
@@ -70,101 +33,98 @@ cd LangBot/docker
docker compose up -d
```
### ワンクリッククラウドデプロイ
http://localhost:5300 にアクセスして使用を開始します。
詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
#### Panelでのワンクリックデプロイ
LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
#### Zeaburクラウドデプロイ
コミュニティが提供するZeaburテンプレート。
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
#### Railwayクラウドデプロイ
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**その他:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
#### その他のデプロイ方法
---
リリースバージョンを直接使用して実行します。[手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html)のドキュメントを参照してください。
## 対応プラットフォーム
#### Kubernetes デプロイ
[Kubernetes デプロイ](./docker/README_K8S.md) ドキュメントを参照してください。
## 😎 最新情報を入手
リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
![star gif](https://docs.langbot.app/star.gif)
## ✨ 機能
- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル、ストリーミング出力機能をサポート、RAG知識ベースを組み込み、[Dify](https://dify.ai) と深く統合。
- 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
- 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/);豊富なエコシステム、現在数百のプラグインが存在。
- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
詳細な仕様については、[ドキュメント](https://docs.langbot.app/en/insight/features.html)を参照してください。
または、デモ環境にアクセスしてください: https://demo.langbot.dev/
- ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
- 注意: WebUI のデモンストレーションのみの場合、公開環境では機密情報を入力しないでください。
### メッセージプラットフォーム
| プラットフォーム | ステータス | 備考 |
|----------|--------|-------|
| --- | --- | --- |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | 個人 & 公式API |
| WeCom | ✅ | 企業WeChat、外部CS、AIボット |
| WeChat | ✅ | 個人 & 公式アカウント |
| 個人QQ | ✅ | |
| QQ公式API | ✅ | |
| WeCom | ✅ | |
| WeComCS | ✅ | |
| WeCom AI Bot | ✅ | |
| 個人WeChat | ✅ | |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
### LLMs
## 対応LLMと統合
| LLM | ステータス | 備考 |
| --- | --- | --- |
| [OpenAI](https://platform.openai.com/) | ✅ | 任意のOpenAIインターフェース形式モデルに対応 |
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
| [Anthropic](https://www.anthropic.com/) | ✅ | |
| [xAI](https://x.ai/) | ✅ | |
| [Zhipu AI](https://open.bigmodel.cn/) | ✅ | |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
| [接口 AI](https://jiekou.ai/) | ✅ | LLMゲートウェイ(MaaS) |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム |
| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
| [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |
| [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム |
| [LMStudio](https://lmstudio.ai/) | ✅ | ローカルLLM実行プラットフォーム |
| [GiteeAI](https://ai.gitee.com/) | ✅ | LLMインターフェースゲートウェイ(MaaS) |
| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLMゲートウェイ(MaaS) |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLMゲートウェイ(MaaS) |
| [MCP](https://modelcontextprotocol.io/) | ✅ | MCPプロトコルをサポート |
| プロバイダー | タイプ | ステータス |
|----------|------|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | ローカルLLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | ローカルLLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | プロトコル | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | ゲートウェイ | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ゲートウェイ | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ゲートウェイ | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ゲートウェイ | ✅ |
| [GiteeAI](https://ai.gitee.com/) | ゲートウェイ | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPUプラットフォーム | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPUプラットフォーム | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPUプラットフォーム | ✅ |
| [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
## 🤝 コミュニティ貢献
[→ すべての統合を表示](https://docs.langbot.app/en/insight/features.html)
---
## なぜ LangBot
| ユースケース | LangBot の活用方法 |
|----------|-------------------|
| **カスタマーサポート** | ナレッジベースを活用して質問に回答するAIエージェントをSlack/Discord/Telegramにデプロイ |
| **社内ツール** | n8n/Difyのワークフローを WeCom/DingTalk に接続し、業務プロセスを自動化 |
| **コミュニティ管理** | AI搭載のコンテンツフィルタリングとインタラクションでQQ/Discordグループをモデレーション |
| **マルチプラットフォーム展開** | 1つのボットで全プラットフォームに対応。単一のダッシュボードから管理 |
---
## ライブデモ
**今すぐ試す:** https://demo.langbot.dev/
- メール: `demo@langbot.app`
- パスワード: `langbot123456`
*注意: 公開デモ環境です。機密情報を入力しないでください。*
---
## コミュニティ
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Discord コミュニティ](https://discord.gg/wdNEHETs87)
---
## Star 推移
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## コントリビューター
LangBot をより良くするために貢献してくださったすべての[コントリビューター](https://github.com/langbot-app/LangBot/graphs/contributors)に感謝します:
LangBot への貢献に対して、以下の [コード貢献者](https://github.com/langbot-app/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

View File

@@ -1,171 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>AI 에이전트 IM 봇 구축을 위한 프로덕션 등급 플랫폼.</h3>
<h4>Slack, Discord, Telegram, WeChat 등에 AI 봇을 빠르게 구축, 디버그 및 배포.</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / 한국어 / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">홈</a>
<a href="https://docs.langbot.app/en/insight/features.html">기능</a>
<a href="https://docs.langbot.app/en/insight/guide.html">문서</a>
<a href="https://docs.langbot.app/en/tags/readme.html">API</a>
<a href="https://space.langbot.app">플러그인 마켓</a>
<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
</div>
</p>
---
## LangBot이란?
LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈소스 프로덕션 등급 플랫폼**입니다. 대규모 언어 모델(LLM)을 모든 채팅 플랫폼에 연결하여 대화, 작업 실행, 기존 워크플로우와의 통합이 가능한 지능형 에이전트를 만들 수 있습니다.
### 핵심 기능
- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) 심층 통합.
- **유니버설 IM 플랫폼 지원** — 단일 코드베이스로 Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK 지원.
- **프로덕션 레디** — 접근 제어, 속도 제한, 민감어 필터링, 종합 모니터링 및 예외 처리. 기업 환경에서 검증됨.
- **플러그인 생태계** — 수백 개의 플러그인, 이벤트 기반 아키텍처, 컴포넌트 확장, [MCP 프로토콜](https://modelcontextprotocol.io/) 지원.
- **웹 관리 패널** — 직관적인 브라우저 인터페이스로 봇을 구성, 관리 및 모니터링. YAML 편집 불필요.
- **멀티 파이프라인 아키텍처** — 다양한 시나리오에 맞는 다양한 봇 구성, 종합 모니터링 및 예외 처리.
[→ 모든 기능 자세히 보기](https://docs.langbot.app/en/insight/features.html)
---
## 빠른 시작
### ☁️ LangBot Cloud (추천)
**[LangBot Cloud](https://space.langbot.app/cloud)** — 배포 없이 바로 사용.
### 원라인 실행
```bash
uvx langbot
```
> [uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요. http://localhost:5300 방문 — 완료.
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### 원클릭 클라우드 배포
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## 지원 플랫폼
| 플랫폼 | 상태 | 비고 |
|--------|------|------|
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | 개인 및 공식 API |
| WeCom | ✅ | 기업 WeChat, 외부 CS, AI Bot |
| WeChat | ✅ | 개인 및 공식 계정 |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
## 지원 LLM 및 통합
| 제공자 | 유형 | 상태 |
|--------|------|------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | 로컬 LLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | 로컬 LLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | 프로토콜 | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | 게이트웨이 | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | 게이트웨이 | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 게이트웨이 | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 게이트웨이 | ✅ |
| [GiteeAI](https://ai.gitee.com/) | 게이트웨이 | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 플랫폼 | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 플랫폼 | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 플랫폼 | ✅ |
| [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
[→ 모든 통합 보기](https://docs.langbot.app/en/insight/features.html)
---
## 왜 LangBot인가?
| 사용 사례 | LangBot 활용 방법 |
|-----------|-------------------|
| **고객 지원** | 지식 베이스를 활용하여 질문에 답변하는 AI 에이전트를 Slack/Discord/Telegram에 배포 |
| **내부 도구** | n8n/Dify 워크플로우를 WeCom/DingTalk에 연결하여 비즈니스 프로세스 자동화 |
| **커뮤니티 관리** | AI 기반 콘텐츠 필터링 및 상호작용으로 QQ/Discord 그룹 관리 |
| **멀티 플랫폼** | 하나의 봇으로 모든 플랫폼 지원. 단일 대시보드에서 관리 |
---
## 라이브 데모
**지금 체험:** https://demo.langbot.dev/
- 이메일: `demo@langbot.app`
- 비밀번호: `langbot123456`
*참고: 공개 데모 환경입니다. 민감한 정보를 입력하지 마세요.*
---
## 커뮤니티
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Discord 커뮤니티](https://discord.gg/wdNEHETs87)
---
## Star 추이
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## 기여자
LangBot을 더 나은 프로젝트로 만들어 주신 모든 [기여자](https://github.com/langbot-app/LangBot/graphs/contributors)분들께 감사드립니다:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -1,171 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>Платформа производственного уровня для создания агентных IM-ботов.</h3>
<h4>Быстро создавайте, отлаживайте и развертывайте ИИ-ботов в Slack, Discord, Telegram, WeChat и других платформах.</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / Русский / [Tiếng Việt](README_VI.md)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">Главная</a>
<a href="https://docs.langbot.app/en/insight/features.html">Возможности</a>
<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a>
<a href="https://docs.langbot.app/en/tags/readme.html">API</a>
<a href="https://space.langbot.app">Магазин плагинов</a>
<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
</div>
</p>
---
## Что такое LangBot?
LangBot — это **платформа с открытым исходным кодом производственного уровня** для создания ИИ-ботов в мессенджерах. Она связывает большие языковые модели (LLM) с любой чат-платформой, позволяя создавать интеллектуальных агентов, которые могут вести диалоги, выполнять задачи и интегрироваться с вашими существующими рабочими процессами.
### Ключевые возможности
- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Универсальная поддержка IM-платформ** — Единая кодовая база для Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Готовность к продакшену** — Контроль доступа, ограничение скорости, фильтрация чувствительных слов, комплексный мониторинг и обработка исключений. Проверено в корпоративной среде.
- **Экосистема плагинов** — Сотни плагинов, событийно-ориентированная архитектура, расширения компонентов и поддержка [протокола MCP](https://modelcontextprotocol.io/).
- **Веб-панель управления** — Настраивайте, управляйте и мониторьте ваших ботов через интуитивный браузерный интерфейс. Ручное редактирование YAML не требуется.
- **Мультиконвейерная архитектура** — Разные боты для разных сценариев с комплексным мониторингом и обработкой исключений.
[→ Подробнее обо всех возможностях](https://docs.langbot.app/en/insight/features.html)
---
## Быстрый старт
### ☁️ LangBot Cloud (Рекомендуется)
**[LangBot Cloud](https://space.langbot.app/cloud)** — Без развёртывания, готово к использованию.
### Запуск одной командой
```bash
uvx langbot
```
> Требуется [uv](https://docs.astral.sh/uv/getting-started/installation/). Откройте http://localhost:5300 — готово.
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### Облачное развертывание одним кликом
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## Поддерживаемые платформы
| Платформа | Статус | Примечания |
|-----------|--------|------------|
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | Личный и официальный API |
| WeCom | ✅ | Корпоративный WeChat, внешний CS, AI-бот |
| WeChat | ✅ | Личный и официальный аккаунт |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
## Поддерживаемые LLM и интеграции
| Провайдер | Тип | Статус |
|-----------|-----|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | Локальный LLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | Локальный LLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | Протокол | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | Шлюз | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Шлюз | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Шлюз | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Шлюз | ✅ |
| [GiteeAI](https://ai.gitee.com/) | Шлюз | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | Шлюз | ✅ |
| [接口 AI](https://jiekou.ai/) | Шлюз | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Платформа GPU | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
[→ Смотреть все интеграции](https://docs.langbot.app/en/insight/features.html)
---
## Почему LangBot?
| Сценарий использования | Как помогает LangBot |
|------------------------|----------------------|
| **Поддержка клиентов** | Разверните ИИ-агентов в Slack/Discord/Telegram, которые отвечают на вопросы, используя вашу базу знаний |
| **Внутренние инструменты** | Подключите рабочие процессы n8n/Dify к WeCom/DingTalk для автоматизации бизнес-процессов |
| **Управление сообществом** | Модерируйте группы QQ/Discord с помощью ИИ-фильтрации контента и взаимодействия |
| **Мультиплатформенное присутствие** | Один бот — все платформы. Управляйте из единой панели |
---
## Демо
**Попробуйте прямо сейчас:** https://demo.langbot.dev/
- Email: `demo@langbot.app`
- Пароль: `langbot123456`
*Примечание: Публичная демо-среда. Не вводите конфиденциальную информацию.*
---
## Сообщество
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Сообщество Discord](https://discord.gg/wdNEHETs87)
---
## История Stars
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## Участники
Спасибо всем [участникам](https://github.com/langbot-app/LangBot/graphs/contributors), которые помогли сделать LangBot лучше:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -1,70 +1,33 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
</a>
<div align="center">
<div align="center"><a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="FeaturedHelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="FeaturedHelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>生產級 AI 即時通訊機器人開發平台。</h3>
<h4>快速建構、除錯和部署 AI 機器人到微信、QQ、飛書、Slack、Discord、Telegram 等平台。</h4>
[English](README.md) / [简体中文](README_CN.md) / 繁體中文 / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / (PR for your language)
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
<a href="https://langbot.app">官網</a>
<a href="https://docs.langbot.app/zh/insight/features.html">特性</a>
<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a>
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a>
<a href="https://space.langbot.app">外掛市場</a>
<a href="https://langbot.featurebase.app/roadmap">路線圖</a>
<a href="https://langbot.app">主頁</a>
<a href="https://docs.langbot.app/zh/insight/guide.html">部署文件</a>
<a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">外掛介紹</a>
<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交外掛</a>
</div>
</p>
---
LangBot 是一個開源的大語言模型原生即時通訊機器人開發平台,旨在提供開箱即用的 IM 機器人開發體驗,具有 Agent、RAG、MCP 等多種 LLM 應用功能,適配全球主流即時通訊平台,並提供豐富的 API 介面,支援自定義開發。
## 什麼是 LangBot
## 📦 開始使用
LangBot 是一個**開源的生產級平台**,用於建構 AI 驅動的即時通訊機器人。它將大語言模型LLM連接到各種聊天平台幫助你創建能夠對話、執行任務、並整合到現有工作流程中的智能 Agent。
### 核心能力
- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG知識庫深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
- **全平台支援** — 一套程式碼,覆蓋 QQ、微信、企業微信、飛書、釘釘、Discord、Telegram、Slack、LINE、KOOK 等平台。
- **生產就緒** — 存取控制、限速、敏感詞過濾、全面監控與異常處理,已被多家企業採用。
- **外掛生態** — 數百個外掛,事件驅動架構,組件擴展,適配 [MCP 協議](https://modelcontextprotocol.io/)。
- **Web 管理面板** — 透過瀏覽器直觀地配置、管理和監控機器人,無需手動編輯設定檔。
- **多流水線架構** — 不同機器人用於不同場景,具備全面的監控和異常處理能力。
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
---
## 快速開始
### ☁️ LangBot Cloud推薦
**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署,開箱即用。
### 一鍵啟動
```bash
uvx langbot
```
> 需要安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/)。訪問 http://localhost:5300 即可使用。
### Docker Compose
#### Docker Compose 部署
```bash
git clone https://github.com/langbot-app/LangBot
@@ -72,63 +35,99 @@ cd LangBot/docker
docker compose up -d
```
### 一鍵雲端部署
訪問 http://localhost:5300 即可開始使用。
詳細文件[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
#### 寶塔面板部署
已上架寶塔面板,若您已安裝寶塔面板,可以根據[文件](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
#### Zeabur 雲端部署
社群貢獻的 Zeabur 模板。
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
#### Railway 雲端部署
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**更多方式:** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [寶塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
#### 手動部署
---
直接使用發行版運行,查看文件[手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
## 支援的平台
#### Kubernetes 部署
參考 [Kubernetes 部署](./docker/README_K8S.md) 文件。
## 😎 保持更新
點擊倉庫右上角 Star 和 Watch 按鈕,獲取最新動態。
![star gif](https://docs.langbot.app/star.gif)
## ✨ 特性
- 💬 大模型對話、Agent支援多種大模型適配群聊和私聊具有多輪對話、工具調用、多模態、流式輸出能力自帶 RAG知識庫實現並深度適配 [Dify](https://dify.ai)。
- 🤖 多平台支援:目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram 等平台。
- 🛠️ 高穩定性、功能完備:原生支援訪問控制、限速、敏感詞過濾等機制;配置簡單,支援多種部署方式。支援多流水線配置,不同機器人用於不同應用場景。
- 🧩 外掛擴展、活躍社群:支援事件驅動、組件擴展等外掛機制;適配 Anthropic [MCP 協議](https://modelcontextprotocol.io/);目前已有數百個外掛。
- 😻 Web 管理面板:支援通過瀏覽器管理 LangBot 實例,不再需要手動編寫配置文件。
詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。
或訪問 demo 環境https://demo.langbot.dev/
- 登入資訊:郵箱:`demo@langbot.app` 密碼:`langbot123456`
- 注意:僅展示 WebUI 效果,公開環境,請不要在其中填入您的任何敏感資訊。
### 訊息平台
| 平台 | 狀態 | 備註 |
|------|------|------|
| QQ | ✅ | 個人號、官方機器人(頻道、私聊、群聊) |
| 微信 | ✅ | 個人微信、微信公眾號 |
| 企業微信 | ✅ | 應用訊息、對外客服、智能機器人 |
| 飛書 | ✅ | |
| 釘釘 | ✅ | |
| --- | --- | --- |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
| QQ 個人號 | ✅ | QQ 個人號私聊、群聊 |
| QQ 官方機器人 | ✅ | QQ 官方機器人,支援頻道、私聊、群聊 |
| 微信 | ✅ | |
| 企微對外客服 | ✅ | |
| 企微智能機器人 | ✅ | |
| 微信公眾號 | ✅ | |
| Lark | ✅ | |
| DingTalk | ✅ | |
---
### 大模型能力
## 支援的大模型與整合
| 模型 | 狀態 | 備註 |
| --- | --- | --- |
| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 介面格式模型 |
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
| [Anthropic](https://www.anthropic.com/) | ✅ | |
| [xAI](https://x.ai/) | ✅ | |
| [智譜AI](https://open.bigmodel.cn/) | ✅ | |
| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 |
| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 |
| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台,專注全球大模型接入 |
| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
| [Ollama](https://ollama.com/) | ✅ | 本地大模型運行平台 |
| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型運行平台 |
| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型介面聚合平台 |
| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
| [阿里雲百煉](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支援通過 MCP 協議獲取工具 |
| 提供商 | 類型 | 狀態 |
|--------|------|------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [智譜AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | 協議 | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
| [阿里雲百煉](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
### TTS語音合成
### TTS
| 平台/模型 | 備註 |
|-----------|------|
| --- | --- |
| [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
| [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) |
@@ -136,54 +135,13 @@ docker compose up -d
### 文生圖
| 平台/模型 | 備註 |
|-----------|------|
| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
| --- | --- |
| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
[→ 查看完整整合列表](https://docs.langbot.app/zh/insight/features.html)
## 😘 社群貢獻
---
## 為什麼選擇 LangBot
| 使用場景 | LangBot 如何幫助 |
|----------|------------------|
| **客戶服務** | 將 AI Agent 部署到微信/企微/釘釘/飛書,基於知識庫自動回答使用者問題 |
| **內部工具** | 將 n8n/Dify 工作流接入企微/釘釘,實現業務流程自動化 |
| **社群運營** | 在 QQ/Discord 群中使用 AI 驅動的內容審核與智能互動 |
| **多平台觸達** | 一個機器人,覆蓋所有平台。透過統一面板集中管理 |
---
## 線上演示
**立即體驗:** https://demo.langbot.dev/
- 信箱:`demo@langbot.app`
- 密碼:`langbot123456`
*注意:公開演示環境,請不要在其中填入任何敏感資訊。*
---
## 社群
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
- [Discord 社群](https://discord.gg/wdNEHETs87)
- [QQ 社群群](https://qm.qq.com/q/JLi38whHum)
---
## Star 趨勢
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## 貢獻者
感謝所有[貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)對 LangBot 的幫助:
感謝以下[程式碼貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)和社群裡其他成員對 LangBot 的貢獻:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>
</a>

View File

@@ -1,171 +0,0 @@
<p align="center">
<a href="https://langbot.app">
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
</a>
<div align="center">
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
<h3>Nền tảng cấp sản xuất để xây dựng bot IM với AI agent.</h3>
<h4>Xây dựng, gỡ lỗi và triển khai bot AI nhanh chóng trên Slack, Discord, Telegram, WeChat và nhiều nền tảng khác.</h4>
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / Tiếng Việt
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
<a href="https://langbot.app">Trang chủ</a>
<a href="https://docs.langbot.app/en/insight/features.html">Tính năng</a>
<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a>
<a href="https://docs.langbot.app/en/tags/readme.html">API</a>
<a href="https://space.langbot.app">Chợ Plugin</a>
<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
</div>
</p>
---
## LangBot là gì?
LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để xây dựng bot nhắn tin tức thời được hỗ trợ bởi AI. Nó kết nối các Mô hình Ngôn ngữ Lớn (LLM) với bất kỳ nền tảng chat nào, cho phép bạn tạo các agent thông minh có thể trò chuyện, thực hiện tác vụ và tích hợp với quy trình làm việc hiện có của bạn.
### Khả năng chính
- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
- **Hỗ trợ đa nền tảng IM** — Một mã nguồn cho Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
- **Sẵn sàng cho sản xuất** — Kiểm soát truy cập, giới hạn tốc độ, lọc từ nhạy cảm, giám sát toàn diện và xử lý ngoại lệ. Được doanh nghiệp tin dùng.
- **Hệ sinh thái Plugin** — Hàng trăm plugin, kiến trúc hướng sự kiện, mở rộng thành phần, và hỗ trợ [giao thức MCP](https://modelcontextprotocol.io/).
- **Bảng quản lý Web** — Cấu hình, quản lý và giám sát bot thông qua giao diện trình duyệt trực quan. Không cần chỉnh sửa YAML.
- **Kiến trúc đa Pipeline** — Các bot khác nhau cho các kịch bản khác nhau, với giám sát toàn diện và xử lý ngoại lệ.
[→ Tìm hiểu thêm về tất cả tính năng](https://docs.langbot.app/en/insight/features.html)
---
## Bắt đầu nhanh
### ☁️ LangBot Cloud (Khuyên dùng)
**[LangBot Cloud](https://space.langbot.app/cloud)** — Không cần triển khai, sẵn sàng sử dụng.
### Khởi chạy một dòng
```bash
uvx langbot
```
> Yêu cầu [uv](https://docs.astral.sh/uv/getting-started/installation/). Truy cập http://localhost:5300 — xong.
### Docker Compose
```bash
git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose up -d
```
### Triển khai đám mây một cú nhấp
[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
---
## Nền tảng được hỗ trợ
| Nền tảng | Trạng thái | Ghi chú |
|----------|--------|-------|
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| QQ | ✅ | Cá nhân & API chính thức |
| WeCom | ✅ | WeChat doanh nghiệp, CS bên ngoài, AI Bot |
| WeChat | ✅ | Cá nhân & Tài khoản công khai |
| Lark | ✅ | |
| DingTalk | ✅ | |
| KOOK | ✅ | |
| Satori | ✅ | |
---
## LLM và tích hợp được hỗ trợ
| Nhà cung cấp | Loại | Trạng thái |
|----------|------|--------|
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
| [xAI](https://x.ai/) | LLM | ✅ |
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
| [Ollama](https://ollama.com/) | LLM cục bộ | ✅ |
| [LM Studio](https://lmstudio.ai/) | LLM cục bộ | ✅ |
| [Dify](https://dify.ai) | LLMOps | ✅ |
| [MCP](https://modelcontextprotocol.io/) | Giao thức | ✅ |
| [SiliconFlow](https://siliconflow.cn/) | Cổng | ✅ |
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Cổng | ✅ |
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Cổng | ✅ |
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Cổng | ✅ |
| [GiteeAI](https://ai.gitee.com/) | Cổng | ✅ |
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Nền tảng GPU | ✅ |
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Nền tảng GPU | ✅ |
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Nền tảng GPU | ✅ |
| [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
[→ Xem tất cả tích hợp](https://docs.langbot.app/en/insight/features.html)
---
## Tại sao chọn LangBot?
| Trường hợp sử dụng | LangBot giúp như thế nào |
|----------|-------------------|
| **Hỗ trợ khách hàng** | Triển khai agent AI trên Slack/Discord/Telegram để trả lời câu hỏi bằng cơ sở kiến thức của bạn |
| **Công cụ nội bộ** | Kết nối quy trình n8n/Dify với WeCom/DingTalk để tự động hóa quy trình kinh doanh |
| **Quản lý cộng đồng** | Quản lý nhóm QQ/Discord với tính năng lọc nội dung và tương tác được hỗ trợ bởi AI |
| **Đa nền tảng** | Một bot, tất cả nền tảng. Quản lý từ một bảng điều khiển duy nhất |
---
## Demo trực tuyến
**Thử ngay:** https://demo.langbot.dev/
- Email: `demo@langbot.app`
- Mật khẩu: `langbot123456`
*Lưu ý: Môi trường demo công khai. Không nhập thông tin nhạy cảm.*
---
## Cộng đồng
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
- [Cộng đồng Discord](https://discord.gg/wdNEHETs87)
---
## Lịch sử Star
[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
---
## Người đóng góp
Cảm ơn tất cả [người đóng góp](https://github.com/langbot-app/LangBot/graphs/contributors) đã giúp LangBot trở nên tốt hơn:
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
</a>

View File

@@ -14,7 +14,7 @@ services:
restart: on-failure
environment:
- TZ=Asia/Shanghai
command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "rt"]
command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
networks:
- langbot_network
@@ -23,12 +23,13 @@ services:
container_name: langbot
volumes:
- ./data:/app/data
- ./plugins:/app/plugins
restart: on-failure
environment:
- TZ=Asia/Shanghai
ports:
- 5300:5300 # For web ui and webhook callback
- 2280-2285:2280-2285 # For platform reverse connection
- 5300:5300 # For web ui
- 2280-2290:2280-2290 # For platform webhook
networks:
- langbot_network

View File

@@ -1,412 +0,0 @@
# WebChat 到 WebSocket 迁移总结
## 概述
已完全移除旧的基于SSE的WebChat系统并替换为基于WebSocket的双向实时通信系统。这是一个内置在LangBot中的完整IM系统支持流式输出。
## 已删除的文件
### 后端
-`src/langbot/pkg/api/http/controller/groups/pipelines/webchat.py` - 旧的SSE路由
-`src/langbot/pkg/platform/sources/webchat.py` - 旧的WebChat适配器
-`src/langbot/pkg/platform/sources/webchat.yaml` - 旧的配置文件
### 前端
- ❌ BackendClient中所有SSE相关代码已完全移除
- ❌ DebugDialog中所有SSE相关逻辑已完全替换
## 新增的文件
### 后端核心文件
**1. WebSocket连接管理器**
```
src/langbot/pkg/platform/sources/websocket_manager.py
```
- 管理所有并发WebSocket连接
- 线程安全的连接池
- 按流水线、会话类型分组
- 广播和单播消息功能
- 连接统计和监控
**2. WebSocket适配器**
```
src/langbot/pkg/platform/sources/websocket_adapter.py
```
- 实现平台适配器接口
- **完整流式支持** (`reply_message_chunk` 方法)
- 双向消息流处理
- 消息历史管理
- 会话管理
**3. WebSocket路由控制器**
```
src/langbot/pkg/api/http/controller/groups/pipelines/websocket_chat.py
```
- WebSocket端点处理
- REST API接口
- 心跳机制
- 连接生命周期管理
**4. 配置文件**
```
src/langbot/pkg/platform/sources/websocket.yaml
```
- WebSocket适配器元数据
### 前端核心文件
**1. WebSocket客户端**
```
web/src/app/infra/websocket/WebSocketClient.ts
```
- WebSocket连接管理
- 自动重连最多5次
- 心跳机制30秒
- 事件回调系统
**2. 更新的组件**
```
web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx
```
- 完全重写使用WebSocket
- 实时连接状态显示
- 流式消息支持
- 自动重连
**3. HTTP客户端更新**
```
web/src/app/infra/http/BackendClient.ts
```
- 移除所有旧的WebChat API
- 仅保留WebSocket API
### 测试工具
**Python测试客户端**
```
test_websocket_client.py
```
- 单连接交互测试
- 多连接并发测试
- 命令行工具
### 文档
**使用文档**
```
WEBSOCKET_README.md
```
- 完整的API文档
- 架构说明
- 使用示例
- 故障排查
## 核心变更
### 后端变更
**1. botmgr.py**
- ❌ 移除 `webchat_proxy_bot`
- ✅ 仅保留 `websocket_proxy_bot`
- ✅ 更新适配器过滤逻辑(排除`websocket`而非`webchat`
**2. 适配器注册**
```python
# 旧代码(已删除)
webchat_adapter_class = self.adapter_dict['webchat']
self.webchat_proxy_bot = RuntimeBot(...)
# 新代码
websocket_adapter_class = self.adapter_dict['websocket']
self.websocket_proxy_bot = RuntimeBot(
uuid='websocket-proxy-bot',
name='WebSocket',
adapter='websocket',
...
)
```
### 前端变更
**1. API调用完全更换**
旧代码(已删除):
```typescript
// SSE流式请求
await fetch(url, {
method: 'POST',
body: JSON.stringify({ is_stream: true })
})
// 手动解析 text/event-stream
```
新代码:
```typescript
// WebSocket实时通信
const wsClient = new WebSocketClient(pipelineId, sessionType);
await wsClient.connect();
wsClient.onMessage((message) => {
// 流式消息自动处理
setMessages(prev => [...prev, message]);
});
wsClient.sendMessage(messageChain);
```
**2. 连接状态管理**
新增功能:
- ✅ 实时连接状态指示器(绿色/红色圆点)
- ✅ 连接/断开toast提示
- ✅ 自动重连逻辑
- ✅ 心跳保活
**3. 流式支持**
完整的流式消息处理:
```typescript
wsClient.onMessage((message) => {
if (message.is_final) {
// 最终消息
finalizeBotMessage(message);
} else {
// 中间消息块实时更新UI
updateBotMessage(message);
}
});
```
## API对比
### WebSocket端点
**连接**
```
ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
```
**消息格式**
客户端发送:
```json
{
"type": "message",
"message": [
{"type": "Plain", "text": "你好"}
]
}
```
服务器响应(流式):
```json
{
"type": "response",
"data": {
"id": 1,
"role": "assistant",
"content": "你好,我是...",
"is_final": false,
"timestamp": "2025-01-28T..."
}
}
```
### REST API
| 端点 | 方法 | 说明 |
|------|------|------|
| `/api/v1/pipelines/<uuid>/ws/messages/<type>` | GET | 获取消息历史 |
| `/api/v1/pipelines/<uuid>/ws/reset/<type>` | POST | 重置会话 |
| `/api/v1/pipelines/<uuid>/ws/connections` | GET | 获取连接统计 |
| `/api/v1/pipelines/<uuid>/ws/broadcast` | POST | 广播消息 |
## 流式支持详解
### 后端流式实现
**WebSocket Adapter**
```python
async def reply_message_chunk(
self,
message_source: platform_events.MessageEvent,
bot_message,
message: platform_message.MessageChain,
quote_origin: bool = False,
is_final: bool = False,
) -> dict:
"""回复消息块 - 流式"""
message_data = WebSocketMessage(
id=-1,
role='assistant',
content=str(message),
message_chain=[component.__dict__ for component in message],
timestamp=datetime.now().isoformat(),
is_final=is_final and bot_message.tool_calls is None,
)
# 发送到队列由WebSocket连接处理发送
await session.resp_queues[message_id].put(message_data)
return message_data.model_dump()
async def is_stream_output_supported(self) -> bool:
"""WebSocket始终支持流式输出"""
return True
```
### 前端流式处理
**DebugDialog组件**
```typescript
wsClient.onMessage((message) => {
setMessages((prevMessages) => {
const existingIndex = prevMessages.findIndex(
(msg) => msg.role === 'assistant' && msg.content === 'Generating...'
);
if (existingIndex !== -1) {
// 更新正在生成的消息
const updatedMessages = [...prevMessages];
updatedMessages[existingIndex] = message;
return updatedMessages;
} else {
// 添加新消息
return [...prevMessages, message];
}
});
});
```
## 兼容性说明
### ⚠️ 不兼容旧版本
此次迁移**完全不兼容**旧的WebChat系统
1. **API端点变更**
- 旧: `/api/v1/pipelines/<uuid>/chat/send`
- 新: `ws://.../<uuid>/ws/connect`
2. **通信协议变更**
- 旧: HTTP + SSE (Server-Sent Events)
- 新: WebSocket (双向)
3. **流式实现变更**
- 旧: `text/event-stream` 格式
- 新: WebSocket JSON消息
### 迁移要求
使用新系统需要:
1. ✅ 前端必须支持WebSocket
2. ✅ 后端必须运行新的WebSocket适配器
3. ✅ 清除旧的WebChat相关配置
## 优势对比
| 特性 | 旧WebChat (SSE) | 新WebSocket |
|------|----------------|-------------|
| 双向通信 | ❌ 单向(服务器→客户端) | ✅ 双向 |
| 主动推送 | ❌ 不支持 | ✅ 支持 |
| 连接管理 | ❌ 无状态 | ✅ 有状态,完整生命周期 |
| 流式输出 | ✅ 支持 | ✅ 支持(更优) |
| 心跳机制 | ❌ 无 | ✅ 30秒心跳 |
| 自动重连 | ❌ 无 | ✅ 最多5次 |
| 多连接 | ⚠️ 难以管理 | ✅ 完整支持 |
| 连接状态 | ❌ 不可见 | ✅ 实时显示 |
| 广播功能 | ❌ 不支持 | ✅ 支持 |
## 测试方式
### 1. Python测试客户端
```bash
# 单连接测试
python test_websocket_client.py <pipeline_uuid>
# 指定会话类型
python test_websocket_client.py <pipeline_uuid> --session-type group
# 多连接并发测试5个连接
python test_websocket_client.py <pipeline_uuid> --multi 5
```
### 2. 前端测试
1. 启动LangBot服务器
2. 访问前端界面
3. 打开流水线调试对话框
4. 观察连接状态指示器(左下角圆点)
5. 发送消息测试流式响应
### 3. 浏览器控制台测试
```javascript
const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/<uuid>/ws/connect?session_type=person');
ws.onopen = () => {
console.log('已连接');
ws.send(JSON.stringify({
type: 'message',
message: [{type: 'Plain', text: '你好'}]
}));
};
ws.onmessage = (event) => {
console.log('收到:', JSON.parse(event.data));
};
```
## 常见问题
### Q: 为什么完全删除旧代码而不保留兼容性?
A: 根据需求,不需要考虑任何对老版本的兼容性,彻底迁移可以避免代码冗余和维护负担。
### Q: 流式输出如何工作?
A:
1. 后端通过`reply_message_chunk`发送消息块
2. 消息块放入队列
3. WebSocket连接从队列取出并发送
4. 前端实时更新UI
5. `is_final=true`表示最后一块
### Q: 如何确保连接不断开?
A:
1. 客户端每30秒发送心跳ping
2. 服务器响应pong
3. 连接断开时自动重连最多5次
### Q: 如何实现后端主动推送?
A:
1. 调用 `/api/v1/pipelines/<uuid>/ws/broadcast` API
2. 消息会被推送到该流水线的所有连接
3. 前端通过`onBroadcast`回调接收
## 总结
**完成的工作**
- 完全移除旧的WebChat/SSE系统
- 实现完整的WebSocket双向通信系统
- 支持流式输出
- 支持多连接并发
- 实现自动重连和心跳机制
- 提供完整的测试工具和文档
**核心特性**
- 双向实时通信
- 流式消息支持
- 多连接管理
- 自动重连
- 心跳保活
- 连接状态可视化
- 广播消息
**技术亮点**
- 异步架构asyncio
- 线程安全的连接管理
- 独立的消息队列
- 完整的错误处理
- 模块化设计
🎉 系统已完全迁移到WebSocket无任何旧代码遗留

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@@ -1,259 +0,0 @@
# SeekDB Vector Database Integration
This document describes how to use OceanBase SeekDB as the vector database backend for LangBot's knowledge base feature.
## What is SeekDB?
**OceanBase SeekDB** is an AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows. It's developed by OceanBase and released under Apache 2.0 license.
### Key Features
- **Hybrid Search**: Combine vector search, full-text search and relational query in a single statement
- **Multi-Model Support**: Support relational, vector, text, JSON and GIS in a single engine
- **Lightweight**: Requires as little as 1 CPU core and 2 GB of memory
- **Multiple Deployment Modes**: Supports both embedded mode and client/server mode
- **MySQL Compatible**: Powered by OceanBase engine with full ACID compliance and MySQL compatibility
## Installation
SeekDB support is automatically included when you install LangBot. The required dependency `pyseekdb` is listed in `pyproject.toml`.
If you need to install it manually:
```bash
pip install pyseekdb
```
## ⚠️ Platform Compatibility
### Embedded Mode
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full embedded mode support via `pylibseekdb` |
| macOS | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
| Windows | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
**Important**: Embedded mode requires the `pylibseekdb` library, which is only available on Linux. If you're on macOS or Windows, you must use server mode.
### Server Mode (Docker)
| Platform | Status | Notes |
|----------|--------|-------|
| Linux | ✅ Supported | Full Docker support |
| macOS | ⚠️ Known Issue | Docker container initialization failure - [See Issue #36](https://github.com/oceanbase/seekdb/issues/36) |
| Windows | ⚠️ Untested | Should work but not yet tested |
**macOS Users**: Currently, SeekDB Docker containers have an initialization issue on macOS ([oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36)). Until this is resolved, we recommend:
- Using ChromaDB or Qdrant as alternatives
- Connecting to a remote SeekDB server on Linux if available
### Server Mode (Remote Connection)
| Platform | Status | Notes |
|----------|--------|-------|
| All Platforms | ✅ Supported | Connect to SeekDB running on a remote Linux server |
**Recommendation for macOS/Windows users**: Deploy SeekDB on a Linux server and connect via server mode configuration.
## Configuration
### Embedded Mode (Recommended for Development)
Embedded mode runs SeekDB directly within the LangBot process, storing data locally. This is the simplest setup and requires no external services.
Edit your `config.yaml`:
```yaml
vdb:
use: seekdb
seekdb:
mode: embedded
path: './data/seekdb' # Path to store SeekDB data
database: 'langbot' # Database name
```
### Server Mode (For Production)
Server mode connects to a remote SeekDB server or OceanBase server. This is recommended for production deployments.
#### SeekDB Server
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
database: 'langbot'
user: 'root'
password: '' # Can also use SEEKDB_PASSWORD env var
```
#### OceanBase Server
If you're using OceanBase with seekdb capabilities:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'localhost'
port: 2881
tenant: 'sys' # OceanBase tenant name
database: 'langbot'
user: 'root'
password: ''
```
## Configuration Parameters
| Parameter | Required | Default | Description |
|-----------|----------|--------------|-------------|
| `mode` | No | `embedded` | Deployment mode: `embedded` or `server` |
| `path` | No | `./data/seekdb` | Data directory for embedded mode |
| `database` | No | `langbot` | Database name |
| `host` | No | `localhost` | Server host (server mode only) |
| `port` | No | `2881` | Server port (server mode only) |
| `user` | No | `root` | Username (server mode only) |
| `password` | No | `''` | Password (server mode only) |
| `tenant` | No | None | OceanBase tenant (optional, server mode only) |
## Usage
Once configured, SeekDB will be used automatically for all knowledge base operations in LangBot:
1. **Creating Knowledge Bases**: Vectors will be stored in SeekDB collections
2. **Adding Documents**: Document embeddings will be indexed in SeekDB
3. **Searching**: Vector similarity search will use SeekDB's efficient indexing
4. **Deleting**: Document removal will delete vectors from SeekDB
No code changes are required - just update your configuration!
## Architecture Details
### Implementation
The SeekDB adapter is implemented in `src/langbot/pkg/vector/vdbs/seekdb.py` and follows the same `VectorDatabase` interface as Chroma and Qdrant adapters.
Key methods:
- `add_embeddings()`: Add vectors with metadata to a collection
- `search()`: Perform vector similarity search
- `delete_by_file_id()`: Delete vectors by file ID metadata
- `get_or_create_collection()`: Manage collections
- `delete_collection()`: Remove entire collections
### Vector Storage
- Collections are created with HNSW (Hierarchical Navigable Small World) index
- Default distance metric: Cosine similarity
- Default vector dimension: 384 (adjusts automatically based on embeddings)
- Metadata is stored alongside vectors for filtering
## Advantages Over Other Vector Databases
### vs. ChromaDB
- ✅ Better MySQL compatibility
- ✅ Hybrid search capabilities (vector + full-text + SQL)
- ✅ Production-grade distributed mode support
- ✅ Lightweight embedded mode
### vs. Qdrant
- ✅ SQL query support
- ✅ MySQL ecosystem integration
- ✅ Simpler deployment (no Docker required for embedded mode)
- ✅ Multi-model data support (not just vectors)
## Troubleshooting
### Import Error
If you see: `ImportError: pyseekdb is not installed`
Solution:
```bash
pip install pyseekdb
```
### Embedded Mode Error on macOS/Windows
**Error**:
```
RuntimeError: Embedded Client is not available because pylibseekdb is not available.
Please install pylibseekdb (Linux only) or use RemoteServerClient (host/port) instead.
```
**Cause**: `pylibseekdb` is only available on Linux platforms.
**Solution**: Use server mode instead:
1. Deploy SeekDB on a Linux server or VM
2. Configure LangBot to use server mode:
```yaml
vdb:
use: seekdb
seekdb:
mode: server
host: 'your-seekdb-server-ip'
port: 2881
database: 'langbot'
user: 'root'
password: ''
```
**Alternative**: Use ChromaDB or Qdrant, which work on all platforms:
```yaml
vdb:
use: chroma # or qdrant
```
### Docker Container Fails on macOS
**Symptoms**:
```bash
docker run -d -p 2881:2881 oceanbase/seekdb:latest
# Container exits immediately with code 30
```
**Error in logs**:
```
[ERROR] Code: Agent.SeekDB.Not.Exists
Message: initialize failed: init agent failed: SeekDB not exists in current directory.
```
**Cause**: This is a known issue with SeekDB Docker containers on macOS. See [oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36).
**Status**: Under investigation by OceanBase team.
**Workaround Options**:
1. **Use alternatives**: ChromaDB or Qdrant work perfectly on macOS
2. **Remote server**: Deploy SeekDB on a Linux server and connect remotely
3. **Wait for fix**: Monitor the GitHub issue for updates
### Connection Error (Server Mode)
If SeekDB server is not reachable, check:
1. Server is running: `ps aux | grep observer`
2. Port is accessible: `nc -zv localhost 2881`
3. Credentials are correct in config
4. Firewall allows connections on port 2881
### Performance Issues
For large datasets:
- Use server mode instead of embedded mode
- Ensure adequate memory allocation
- Consider using OceanBase distributed mode for very large scale
- Adjust HNSW index parameters if needed
## Resources
- SeekDB GitHub: https://github.com/oceanbase/seekdb
- pyseekdb SDK: https://github.com/oceanbase/pyseekdb
- OceanBase Documentation: https://oceanbase.ai
- LangBot Documentation: https://docs.langbot.app
## License
SeekDB is licensed under Apache License 2.0.

View File

@@ -1,394 +0,0 @@
# LangBot WebSocket 双向通信系统
## 概述
这是一个内置在 LangBot 中的完整 IM (即时通讯) 系统,支持:
- ✅ WebSocket 双向实时通信
- ✅ 多个客户端并发连接
- ✅ 前端到后端的消息发送
- ✅ 后端到前端的主动推送
- ✅ 流式响应支持
- ✅ 连接管理和会话隔离
- ✅ 心跳机制
- ✅ 广播消息功能
## 架构设计
### 核心组件
1. **WebSocketConnectionManager** (`websocket_manager.py`)
- 管理所有活跃的 WebSocket 连接
- 支持按流水线、会话类型查询连接
- 提供广播和单播功能
- 线程安全的并发访问控制
2. **WebSocketAdapter** (`websocket_adapter.py`)
- 实现平台适配器接口
- 处理消息的接收和发送
- 支持流式输出
- 管理消息历史
3. **WebSocketChatRouterGroup** (`websocket_chat.py`)
- WebSocket 路由控制器
- 处理连接建立、消息收发
- 实现心跳机制
- 提供 REST API 接口
## API 接口
### WebSocket 连接
#### 建立连接
```
ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
```
**参数:**
- `pipeline_uuid`: 流水线 UUID (必需)
- `session_type`: 会话类型,可选 `person``group` (默认: `person`)
**连接成功响应:**
```json
{
"type": "connected",
"connection_id": "550e8400-e29b-41d4-a716-446655440000",
"pipeline_uuid": "your-pipeline-uuid",
"session_type": "person",
"timestamp": "2025-01-28T12:00:00"
}
```
### 消息格式
#### 客户端发送消息
**发送聊天消息:**
```json
{
"type": "message",
"message": [
{
"type": "Plain",
"text": "你好,这是一条测试消息"
}
]
}
```
**发送心跳:**
```json
{
"type": "ping"
}
```
**主动断开连接:**
```json
{
"type": "disconnect"
}
```
#### 服务器响应消息
**聊天响应 (流式):**
```json
{
"type": "response",
"data": {
"id": 1,
"role": "assistant",
"content": "这是机器人的回复",
"message_chain": [...],
"timestamp": "2025-01-28T12:00:00",
"is_final": false,
"connection_id": "..."
}
}
```
**心跳响应:**
```json
{
"type": "pong",
"timestamp": "2025-01-28T12:00:00"
}
```
**广播消息:**
```json
{
"type": "broadcast",
"message": "这是一条广播消息",
"timestamp": "2025-01-28T12:00:00"
}
```
**错误消息:**
```json
{
"type": "error",
"message": "错误描述"
}
```
### REST API 接口
#### 1. 获取消息历史
```http
GET /api/v1/pipelines/<pipeline_uuid>/ws/messages/<session_type>
```
**响应:**
```json
{
"code": 0,
"msg": "ok",
"data": {
"messages": [...]
}
}
```
#### 2. 重置会话
```http
POST /api/v1/pipelines/<pipeline_uuid>/ws/reset/<session_type>
```
**响应:**
```json
{
"code": 0,
"msg": "ok",
"data": {
"message": "Session reset successfully"
}
}
```
#### 3. 获取连接统计
```http
GET /api/v1/pipelines/<pipeline_uuid>/ws/connections
```
**响应:**
```json
{
"code": 0,
"msg": "ok",
"data": {
"stats": {
"total_connections": 5,
"pipelines": 2,
"connections_by_pipeline": {
"pipeline-1": 3,
"pipeline-2": 2
},
"connections_by_session_type": {
"person": 4,
"group": 1
}
},
"connections": [
{
"connection_id": "...",
"session_type": "person",
"created_at": "2025-01-28T12:00:00",
"last_active": "2025-01-28T12:05:00",
"is_active": true
}
]
}
}
```
#### 4. 广播消息 (后端主动推送)
```http
POST /api/v1/pipelines/<pipeline_uuid>/ws/broadcast
Content-Type: application/json
{
"message": "广"
}
```
**响应:**
```json
{
"code": 0,
"msg": "ok",
"data": {
"message": "Broadcast sent successfully"
}
}
```
## 使用示例
### Python 客户端示例
使用提供的测试客户端:
```bash
# 安装依赖
pip install websockets
# 单个连接测试
python test_websocket_client.py <pipeline_uuid>
# 指定会话类型
python test_websocket_client.py <pipeline_uuid> --session-type group
# 多连接并发测试
python test_websocket_client.py <pipeline_uuid> --multi 5
```
### JavaScript 客户端示例
```javascript
// 建立 WebSocket 连接
const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/your-pipeline-uuid/ws/connect?session_type=person');
// 连接建立
ws.onopen = () => {
console.log('WebSocket 连接已建立');
// 发送消息
ws.send(JSON.stringify({
type: 'message',
message: [
{
type: 'Plain',
text: '你好'
}
]
}));
};
// 接收消息
ws.onmessage = (event) => {
const data = JSON.parse(event.data);
if (data.type === 'connected') {
console.log('连接成功:', data.connection_id);
} else if (data.type === 'response') {
console.log('机器人回复:', data.data.content);
if (data.data.is_final) {
console.log('响应完成');
}
} else if (data.type === 'broadcast') {
console.log('收到广播:', data.message);
}
};
// 连接关闭
ws.onclose = () => {
console.log('WebSocket 连接已关闭');
};
// 错误处理
ws.onerror = (error) => {
console.error('WebSocket 错误:', error);
};
// 发送心跳
setInterval(() => {
if (ws.readyState === WebSocket.OPEN) {
ws.send(JSON.stringify({ type: 'ping' }));
}
}, 30000); // 每 30 秒发送一次心跳
```
## 特性说明
### 1. 多连接支持
系统支持同时建立多个 WebSocket 连接,每个连接都有唯一的 `connection_id`。连接按照流水线和会话类型进行分组管理。
### 2. 双向通信
- **前端 → 后端**: 客户端可以主动发送消息给服务器
- **后端 → 前端**: 服务器可以通过广播 API 主动推送消息给客户端
### 3. 流式响应
支持流式输出,机器人的响应会分块发送,客户端可以实时显示部分响应内容。
### 4. 会话隔离
支持 `person``group` 两种会话类型,不同类型的会话消息历史互不影响。
### 5. 连接管理
- 自动追踪连接状态
- 记录最后活跃时间
- 支持连接统计查询
- 连接断开时自动清理资源
### 6. 心跳机制
客户端可以定期发送 `ping` 消息,服务器会响应 `pong`,用于保持连接活跃和检测连接状态。
## 架构优势
1. **高并发**: 使用 asyncio 异步架构,支持大量并发连接
2. **可扩展**: 模块化设计,易于扩展新功能
3. **线程安全**: 连接管理器使用锁机制保证并发安全
4. **消息队列**: 每个连接独立的发送队列,避免消息混乱
5. **灵活路由**: 支持按流水线、会话类型灵活路由消息
## 注意事项
1. **认证**: 当前 WebSocket 连接不需要认证,生产环境建议添加认证机制
2. **心跳**: 建议客户端实现心跳机制,避免连接超时
3. **重连**: 客户端应实现断线重连逻辑
4. **消息大小**: 注意控制单条消息大小,避免内存溢出
5. **连接数限制**: 生产环境建议设置最大连接数限制
## 故障排查
### 连接失败
1. 检查流水线 UUID 是否正确
2. 检查服务器是否正常运行
3. 检查防火墙设置
### 消息发送失败
1. 检查消息格式是否正确
2. 检查连接是否仍然活跃
3. 查看服务器日志获取详细错误信息
### 性能问题
1. 检查并发连接数是否过多
2. 检查消息处理速度
3. 考虑使用连接池或负载均衡
## 开发调试
启用详细日志:
```python
import logging
logging.getLogger('langbot.pkg.platform.sources.websocket_adapter').setLevel(logging.DEBUG)
logging.getLogger('langbot.pkg.platform.sources.websocket_manager').setLevel(logging.DEBUG)
logging.getLogger('langbot.pkg.api.http.controller.groups.pipelines.websocket_chat').setLevel(logging.DEBUG)
```
## 后续改进建议
1. 添加用户认证和授权机制
2. 实现消息持久化
3. 添加消息加密
4. 实现更丰富的消息类型 (图片、文件等)
5. 添加消息已读/未读状态
6. 实现群组聊天功能
7. 添加在线状态显示
8. 实现消息撤回功能

View File

@@ -9,7 +9,7 @@
"url": "https://langbot.app"
},
"license": {
"name": "Apache-2.0",
"name": "AGPL-3.0",
"url": "https://github.com/langbot-app/LangBot/blob/master/LICENSE"
}
},

View File

@@ -1,10 +1,10 @@
[project]
name = "langbot"
version = "4.8.6"
description = "Production-grade platform for building agentic IM bots"
version = "4.6.0-beta.2"
description = "Easy-to-use global IM bot platform designed for LLM era"
readme = "README.md"
license-files = ["LICENSE"]
requires-python = ">=3.11,<4.0"
requires-python = ">=3.10.1,<4.0"
dependencies = [
"aiocqhttp>=1.4.4",
"aiofiles>=24.1.0",
@@ -17,13 +17,13 @@ dependencies = [
"certifi>=2025.4.26",
"colorlog~=6.6.0",
"cryptography>=44.0.3",
"dashscope>=1.25.10",
"dashscope>=1.23.2",
"dingtalk-stream>=0.24.0",
"discord-py>=2.5.2",
"pynacl>=1.5.0", # Required for Discord voice support
"gewechat-client>=0.1.5",
"lark-oapi>=1.4.15",
"mcp>=1.25.0",
"mcp>=1.8.1",
"nakuru-project-idk>=0.0.2.1",
"ollama>=0.4.8",
"openai>1.0.0",
@@ -63,14 +63,11 @@ dependencies = [
"langchain-text-splitters>=0.0.1",
"chromadb>=0.4.24",
"qdrant-client (>=1.15.1,<2.0.0)",
"pyseekdb==1.0.0b7",
"langbot-plugin==0.2.7",
"langbot-plugin==0.1.11b1",
"asyncpg>=0.30.0",
"line-bot-sdk>=3.19.0",
"tboxsdk>=0.0.10",
"boto3>=1.35.0",
"pymilvus>=2.6.4",
"pgvector>=0.4.1",
]
keywords = [
"bot",

View File

@@ -26,7 +26,7 @@ markers =
# Coverage options (when using pytest-cov)
[coverage:run]
source = langbot
source = langbot.pkg
omit =
*/tests/*
*/test_*.py

Binary file not shown.

Before

Width:  |  Height:  |  Size: 24 KiB

View File

@@ -22,7 +22,7 @@ echo "Running all unit tests..."
# Run tests with coverage
pytest tests/unit_tests/ -v --tb=short \
--cov=langbot \
--cov=pkg \
--cov-report=xml \
"$@"

View File

@@ -1,3 +1,3 @@
"""LangBot - Production-grade platform for building agentic IM bots"""
"""LangBot - Easy-to-use global IM bot platform designed for LLM era"""
__version__ = '4.8.6'
__version__ = '4.6.0-beta.2'

View File

@@ -32,7 +32,6 @@ class AsyncDifyServiceClient:
conversation_id: str = '',
files: list[dict[str, typing.Any]] = [],
timeout: float = 30.0,
model_config: dict[str, typing.Any] | None = None,
) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
"""发送消息"""
if response_mode != 'streaming':
@@ -43,16 +42,6 @@ class AsyncDifyServiceClient:
trust_env=True,
timeout=timeout,
) as client:
payload = {
'inputs': inputs,
'query': query,
'user': user,
'response_mode': response_mode,
'conversation_id': conversation_id,
'files': files,
'model_config': model_config or {},
}
async with client.stream(
'POST',
'/chat-messages',
@@ -60,7 +49,14 @@ class AsyncDifyServiceClient:
'Authorization': f'Bearer {self.api_key}',
'Content-Type': 'application/json',
},
json=payload,
json={
'inputs': inputs,
'query': query,
'user': user,
'response_mode': response_mode,
'conversation_id': conversation_id,
'files': files,
},
) as r:
async for chunk in r.aiter_lines():
if r.status_code != 200:

View File

@@ -1,11 +1,8 @@
import asyncio
import base64
import json
import time
import urllib.parse
from typing import Callable
import dingtalk_stream # type: ignore
import websockets
from .EchoHandler import EchoTextHandler
from .dingtalkevent import DingTalkEvent
import httpx
@@ -39,7 +36,6 @@ class DingTalkClient:
self.access_token_expiry_time = ''
self.markdown_card = markdown_card
self.logger = logger
self._stopped = False # Flag to control the event loop
async def get_access_token(self):
url = 'https://api.dingtalk.com/v1.0/oauth2/accessToken'
@@ -174,9 +170,6 @@ class DingTalkClient:
"""
处理消息事件。
"""
# Skip message handling if stopped
if self._stopped:
return
msg_type = event.conversation
if msg_type in self._message_handlers:
for handler in self._message_handlers[msg_type]:
@@ -347,15 +340,10 @@ class DingTalkClient:
raise Exception(f'failed to send proactive massage to group: {traceback.format_exc()}')
async def create_and_card(
self,
temp_card_id: str,
incoming_message: dingtalk_stream.ChatbotMessage,
quote_origin: bool = False,
card_auto_layout: bool = False,
self, temp_card_id: str, incoming_message: dingtalk_stream.ChatbotMessage, quote_origin: bool = False
):
card_data = {}
card_data['config'] = json.dumps({'autoLayout': card_auto_layout})
card_data['content'] = ''
content_key = 'content'
card_data = {content_key: ''}
card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message)
# print(card_instance)
@@ -390,70 +378,4 @@ class DingTalkClient:
async def start(self):
"""启动 WebSocket 连接,监听消息"""
self._stopped = False
self.client.pre_start()
while not self._stopped:
try:
connection = self.client.open_connection()
if not connection:
if self.logger:
await self.logger.error('DingTalk: open connection failed')
await asyncio.sleep(10)
continue
uri = '%s?ticket=%s' % (connection['endpoint'], urllib.parse.quote_plus(connection['ticket']))
async with websockets.connect(uri) as websocket:
self.client.websocket = websocket
keepalive_task = asyncio.create_task(self._keepalive(websocket))
try:
async for raw_message in websocket:
if self._stopped:
break
json_message = json.loads(raw_message)
asyncio.create_task(self.client.background_task(json_message))
finally:
keepalive_task.cancel()
try:
await keepalive_task
except asyncio.CancelledError:
pass
except asyncio.CancelledError:
# Properly exit when task is cancelled
break
except websockets.exceptions.ConnectionClosedError as e:
if self._stopped:
break
if self.logger:
await self.logger.error(f'DingTalk: connection closed, reconnecting... error={e}')
await asyncio.sleep(5)
continue
except Exception as e:
if self._stopped:
break
if self.logger:
await self.logger.error(f'DingTalk: unknown exception, reconnecting... error={e}')
await asyncio.sleep(3)
continue
async def _keepalive(self, ws, ping_interval=60):
"""Keep WebSocket connection alive"""
while not self._stopped:
await asyncio.sleep(ping_interval)
try:
await ws.ping()
except websockets.exceptions.ConnectionClosed:
break
async def stop(self):
"""停止 WebSocket 连接"""
self._stopped = True
# Close WebSocket connection if exists
if self.client.websocket:
try:
await self.client.websocket.close()
except Exception:
pass
# Clear message handlers to prevent stale callbacks
self._message_handlers = {'example': []}
await self.client.start()

View File

@@ -23,34 +23,20 @@ xml_template = """
class OAClient:
def __init__(
self,
token: str,
EncodingAESKey: str,
AppID: str,
Appsecret: str,
logger: None,
unified_mode: bool = False,
api_base_url: str = 'https://api.weixin.qq.com',
):
def __init__(self, token: str, EncodingAESKey: str, AppID: str, Appsecret: str, logger: None):
self.token = token
self.aes = EncodingAESKey
self.appid = AppID
self.appsecret = Appsecret
self.base_url = api_base_url
self.base_url = 'https://api.weixin.qq.com'
self.access_token = ''
self.unified_mode = unified_mode
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self._message_handlers = {
'example': [],
}
@@ -60,39 +46,19 @@ class OAClient:
self.logger = logger
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""处理回调请求的内部实现,包括 GET 验证和 POST 消息接收。
Args:
req: Quart Request 对象
"""
try:
# 每隔100毫秒查询是否生成ai回答
start_time = time.time()
signature = req.args.get('signature', '')
timestamp = req.args.get('timestamp', '')
nonce = req.args.get('nonce', '')
echostr = req.args.get('echostr', '')
msg_signature = req.args.get('msg_signature', '')
signature = request.args.get('signature', '')
timestamp = request.args.get('timestamp', '')
nonce = request.args.get('nonce', '')
echostr = request.args.get('echostr', '')
msg_signature = request.args.get('msg_signature', '')
if msg_signature is None:
await self.logger.error('msg_signature不在请求体中')
raise Exception('msg_signature不在请求体中')
if req.method == 'GET':
if request.method == 'GET':
# 校验签名
check_str = ''.join(sorted([self.token, timestamp, nonce]))
check_signature = hashlib.sha1(check_str.encode('utf-8')).hexdigest()
@@ -102,8 +68,8 @@ class OAClient:
else:
await self.logger.error('拒绝请求')
raise Exception('拒绝请求')
elif req.method == 'POST':
encryt_msg = await req.data
elif request.method == 'POST':
encryt_msg = await request.data
wxcpt = WXBizMsgCrypt(self.token, self.aes, self.appid)
ret, xml_msg = wxcpt.DecryptMsg(encryt_msg, msg_signature, timestamp, nonce)
xml_msg = xml_msg.decode('utf-8')
@@ -216,27 +182,20 @@ class OAClientForLongerResponse:
Appsecret: str,
LoadingMessage: str,
logger: None,
unified_mode: bool = False,
api_base_url: str = 'https://api.weixin.qq.com',
):
self.token = token
self.aes = EncodingAESKey
self.appid = AppID
self.appsecret = Appsecret
self.base_url = api_base_url
self.base_url = 'https://api.weixin.qq.com'
self.access_token = ''
self.unified_mode = unified_mode
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self._message_handlers = {
'example': [],
}
@@ -247,44 +206,24 @@ class OAClientForLongerResponse:
self.logger = logger
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""处理回调请求的内部实现,包括 GET 验证和 POST 消息接收。
Args:
req: Quart Request 对象
"""
try:
signature = req.args.get('signature', '')
timestamp = req.args.get('timestamp', '')
nonce = req.args.get('nonce', '')
echostr = req.args.get('echostr', '')
msg_signature = req.args.get('msg_signature', '')
signature = request.args.get('signature', '')
timestamp = request.args.get('timestamp', '')
nonce = request.args.get('nonce', '')
echostr = request.args.get('echostr', '')
msg_signature = request.args.get('msg_signature', '')
if msg_signature is None:
await self.logger.error('msg_signature不在请求体中')
raise Exception('msg_signature不在请求体中')
if req.method == 'GET':
if request.method == 'GET':
check_str = ''.join(sorted([self.token, timestamp, nonce]))
check_signature = hashlib.sha1(check_str.encode('utf-8')).hexdigest()
return echostr if check_signature == signature else '拒绝请求'
elif req.method == 'POST':
encryt_msg = await req.data
elif request.method == 'POST':
encryt_msg = await request.data
wxcpt = WXBizMsgCrypt(self.token, self.aes, self.appid)
ret, xml_msg = wxcpt.DecryptMsg(encryt_msg, msg_signature, timestamp, nonce)
xml_msg = xml_msg.decode('utf-8')

View File

@@ -10,20 +10,38 @@ import traceback
from cryptography.hazmat.primitives.asymmetric import ed25519
def handle_validation(body: dict, bot_secret: str):
# bot正确的secert是32位的此处仅为了适配演示demo
while len(bot_secret) < 32:
bot_secret = bot_secret * 2
bot_secret = bot_secret[:32]
# 实际使用场景中以上三行内容可清除
seed_bytes = bot_secret.encode()
signing_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed_bytes)
msg = body['d']['event_ts'] + body['d']['plain_token']
msg_bytes = msg.encode()
signature = signing_key.sign(msg_bytes)
signature_hex = signature.hex()
response = {'plain_token': body['d']['plain_token'], 'signature': signature_hex}
return response
class QQOfficialClient:
def __init__(self, secret: str, token: str, app_id: str, logger: None, unified_mode: bool = False):
self.unified_mode = unified_mode
def __init__(self, secret: str, token: str, app_id: str, logger: None):
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self.secret = secret
self.token = token
self.app_id = app_id
@@ -64,43 +82,18 @@ class QQOfficialClient:
raise Exception(f'获取access_token失败: {e}')
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""处理回调请求的内部实现。
Args:
req: Quart Request 对象
"""
"""处理回调请求"""
try:
body = await req.get_data()
print(f'[QQ Official] Received request, body length: {len(body)}')
if not body or len(body) == 0:
print('[QQ Official] Received empty body, might be health check or GET request')
return {'code': 0, 'message': 'ok'}, 200
# 读取请求数据
body = await request.get_data()
payload = json.loads(body)
# 验证是否为回调验证请求
if payload.get('op') == 13:
validation_data = payload.get('d')
if not validation_data:
return {'error': "missing 'd' field"}, 400
response = await self.verify(validation_data)
return response, 200
# 生成签名
response = handle_validation(payload, self.secret)
return response
if payload.get('op') == 0:
message_data = await self.get_message(payload)
@@ -111,7 +104,6 @@ class QQOfficialClient:
return {'code': 0, 'message': 'success'}
except Exception as e:
print(f'[QQ Official] ERROR: {traceback.format_exc()}')
await self.logger.error(f'Error in handle_callback_request: {traceback.format_exc()}')
return {'error': str(e)}, 400
@@ -269,26 +261,3 @@ class QQOfficialClient:
if self.access_token_expiry_time is None:
return True
return time.time() > self.access_token_expiry_time
async def repeat_seed(self, bot_secret: str, target_size: int = 32) -> bytes:
seed = bot_secret
while len(seed) < target_size:
seed *= 2
return seed[:target_size].encode('utf-8')
async def verify(self, validation_payload: dict):
seed = await self.repeat_seed(self.secret)
private_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed)
event_ts = validation_payload.get('event_ts', '')
plain_token = validation_payload.get('plain_token', '')
msg = event_ts + plain_token
# sign
signature = private_key.sign(msg.encode()).hex()
response = {
'plain_token': plain_token,
'signature': signature,
}
return response

View File

@@ -8,19 +8,14 @@ import langbot_plugin.api.entities.builtin.platform.events as platform_events
class SlackClient:
def __init__(self, bot_token: str, signing_secret: str, logger: None, unified_mode: bool = False):
def __init__(self, bot_token: str, signing_secret: str, logger: None):
self.bot_token = bot_token
self.signing_secret = signing_secret
self.unified_mode = unified_mode
self.app = Quart(__name__)
self.client = AsyncWebClient(self.bot_token)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
)
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
)
self._message_handlers = {
'example': [],
}
@@ -28,28 +23,8 @@ class SlackClient:
self.logger = logger
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""处理回调请求的内部实现。
Args:
req: Quart Request 对象
"""
try:
body = await req.get_data()
body = await request.get_data()
data = json.loads(body)
if 'type' in data:
if data['type'] == 'url_verification':

View File

@@ -200,7 +200,7 @@ class StreamSessionManager:
class WecomBotClient:
def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger, unified_mode: bool = False):
def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger):
"""企业微信智能机器人客户端。
Args:
@@ -208,7 +208,6 @@ class WecomBotClient:
EnCodingAESKey: 企业微信消息加解密密钥。
Corpid: 企业 ID。
logger: 日志记录器。
unified_mode: 是否使用统一 webhook 模式(默认 False
Example:
>>> client = WecomBotClient(Token='token', EnCodingAESKey='aeskey', Corpid='corp', logger=logger)
@@ -218,15 +217,10 @@ class WecomBotClient:
self.EnCodingAESKey = EnCodingAESKey
self.Corpid = Corpid
self.ReceiveId = ''
self.unified_mode = unified_mode
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['POST', 'GET']
)
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['POST', 'GET']
)
self._message_handlers = {
'example': [],
}
@@ -365,7 +359,7 @@ class WecomBotClient:
return await self._encrypt_and_reply(payload, nonce)
async def handle_callback_request(self):
"""企业微信回调入口(独立端口模式,使用全局 request
"""企业微信回调入口。
Returns:
Quart Response: 根据请求类型返回验证、首包或刷新结果。
@@ -373,33 +367,15 @@ class WecomBotClient:
Example:
作为 Quart 路由处理函数直接注册并使用。
"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""处理回调请求的内部实现,包括 GET 验证和 POST 消息接收。
Args:
req: Quart Request 对象
"""
try:
self.wxcpt = WXBizMsgCrypt(self.Token, self.EnCodingAESKey, '')
await self.logger.info(f'{request.method} {request.url} {str(request.args)}')
if req.method == 'GET':
return await self._handle_get_callback(req)
if request.method == 'GET':
return await self._handle_get_callback()
if req.method == 'POST':
return await self._handle_post_callback(req)
if request.method == 'POST':
return await self._handle_post_callback()
return Response('', status=405)
@@ -407,13 +383,13 @@ class WecomBotClient:
await self.logger.error(traceback.format_exc())
return Response('Internal Server Error', status=500)
async def _handle_get_callback(self, req) -> tuple[Response, int] | Response:
async def _handle_get_callback(self) -> tuple[Response, int] | Response:
"""处理企业微信的 GET 验证请求。"""
msg_signature = unquote(req.args.get('msg_signature', ''))
timestamp = unquote(req.args.get('timestamp', ''))
nonce = unquote(req.args.get('nonce', ''))
echostr = unquote(req.args.get('echostr', ''))
msg_signature = unquote(request.args.get('msg_signature', ''))
timestamp = unquote(request.args.get('timestamp', ''))
nonce = unquote(request.args.get('nonce', ''))
echostr = unquote(request.args.get('echostr', ''))
if not all([msg_signature, timestamp, nonce, echostr]):
await self.logger.error('请求参数缺失')
@@ -426,16 +402,16 @@ class WecomBotClient:
return Response(decrypted_str, mimetype='text/plain')
async def _handle_post_callback(self, req) -> tuple[Response, int] | Response:
async def _handle_post_callback(self) -> tuple[Response, int] | Response:
"""处理企业微信的 POST 回调请求。"""
self.stream_sessions.cleanup()
msg_signature = unquote(req.args.get('msg_signature', ''))
timestamp = unquote(req.args.get('timestamp', ''))
nonce = unquote(req.args.get('nonce', ''))
msg_signature = unquote(request.args.get('msg_signature', ''))
timestamp = unquote(request.args.get('timestamp', ''))
nonce = unquote(request.args.get('nonce', ''))
encrypted_json = await req.get_json()
encrypted_json = await request.get_json()
encrypted_msg = (encrypted_json or {}).get('encrypt', '')
if not encrypted_msg:
await self.logger.error("请求体中缺少 'encrypt' 字段")
@@ -457,174 +433,32 @@ class WecomBotClient:
async def get_message(self, msg_json):
message_data = {}
msg_type = msg_json.get('msgtype', '')
if msg_type:
message_data['msgtype'] = msg_type
if msg_json.get('chattype', '') == 'single':
message_data['type'] = 'single'
elif msg_json.get('chattype', '') == 'group':
message_data['type'] = 'group'
max_inline_file_size = 5 * 1024 * 1024 # avoid decoding very large payloads by default
async def _safe_download(url: str):
if not url:
return None
return await self.download_url_to_base64(url, self.EnCodingAESKey)
if msg_type == 'text':
if msg_json.get('msgtype') == 'text':
message_data['content'] = msg_json.get('text', {}).get('content')
elif msg_type == 'markdown':
message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
'content', ''
)
elif msg_type == 'image':
elif msg_json.get('msgtype') == 'image':
picurl = msg_json.get('image', {}).get('url', '')
base64_data = await _safe_download(picurl)
if base64_data:
message_data['picurl'] = base64_data
message_data['images'] = [base64_data]
elif msg_type == 'voice':
voice_info = msg_json.get('voice', {}) or {}
download_url = voice_info.get('url')
message_data['voice'] = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
# 企业微信智能转写文本(如果已有)直接复用,避免重复转写
if voice_info.get('content'):
message_data['content'] = voice_info.get('content')
if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
message_data['voice']['base64'] = voice_base64
elif msg_type == 'video':
video_info = msg_json.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
message_data['video'] = video_data
elif msg_type == 'file':
file_info = msg_json.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
message_data['file'] = file_data
elif msg_type == 'link':
message_data['link'] = msg_json.get('link', {})
if not message_data.get('content'):
title = message_data['link'].get('title', '')
desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
message_data['content'] = '\n'.join(filter(None, [title, desc]))
elif msg_type == 'mixed':
base64 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
message_data['picurl'] = base64
elif msg_json.get('msgtype') == 'mixed':
items = msg_json.get('mixed', {}).get('msg_item', [])
texts = []
images = []
files = []
voices = []
videos = []
links = []
picurl = None
for item in items:
item_type = item.get('msgtype')
if item_type == 'text':
if item.get('msgtype') == 'text':
texts.append(item.get('text', {}).get('content', ''))
elif item_type == 'image':
img_url = item.get('image', {}).get('url')
base64_data = await _safe_download(img_url)
if base64_data:
images.append(base64_data)
elif item_type == 'file':
file_info = item.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
file_data = {
'filename': file_info.get('filename') or file_info.get('name'),
'filesize': file_info.get('filesize') or file_info.get('size'),
'md5sum': file_info.get('md5sum') or file_info.get('md5'),
'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
'download_url': download_url,
'extra': file_info,
}
if (file_data.get('filesize') or 0) <= max_inline_file_size:
file_base64 = await _safe_download(download_url)
if file_base64:
file_data['base64'] = file_base64
files.append(file_data)
elif item_type == 'voice':
voice_info = item.get('voice', {}) or {}
download_url = voice_info.get('url')
voice_data = {
'url': download_url,
'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
'filesize': voice_info.get('filesize') or voice_info.get('size'),
'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
}
if voice_info.get('content'):
texts.append(voice_info.get('content'))
if (voice_data.get('filesize') or 0) <= max_inline_file_size:
voice_base64 = await _safe_download(download_url)
if voice_base64:
voice_data['base64'] = voice_base64
voices.append(voice_data)
elif item_type == 'video':
video_info = item.get('video', {}) or {}
download_url = video_info.get('url')
video_data = {
'url': download_url,
'filesize': video_info.get('filesize') or video_info.get('size'),
'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
'md5sum': video_info.get('md5sum') or video_info.get('md5'),
'filename': video_info.get('filename') or video_info.get('name'),
}
if (video_data.get('filesize') or 0) <= max_inline_file_size:
video_base64 = await _safe_download(download_url)
if video_base64:
video_data['base64'] = video_base64
videos.append(video_data)
elif item_type == 'link':
links.append(item.get('link', {}))
elif item.get('msgtype') == 'image' and picurl is None:
picurl = item.get('image', {}).get('url')
if texts:
message_data['content'] = ' '.join(texts) # 拼接所有 text
if images:
message_data['images'] = images
message_data['picurl'] = images[0] # 只保留第一个 image
if files:
message_data['files'] = files
message_data['file'] = files[0]
if voices:
message_data['voices'] = voices
message_data['voice'] = voices[0]
if videos:
message_data['videos'] = videos
message_data['video'] = videos[0]
if links:
message_data['link'] = links[0]
if items:
message_data['attachments'] = items
else:
message_data['raw_msg'] = msg_json
message_data['content'] = ''.join(texts) # 拼接所有 text
if picurl:
base64 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
message_data['picurl'] = base64 # 只保留第一个 image
# Extract user information
from_info = msg_json.get('from', {})

View File

@@ -17,13 +17,6 @@ class WecomBotEvent(dict):
"""
return self.get('type', '')
@property
def msgtype(self) -> str:
"""
消息 msgtype
"""
return self.get('msgtype', '')
@property
def userid(self) -> str:
"""
@@ -64,55 +57,6 @@ class WecomBotEvent(dict):
"""
return self.get('picurl', '')
@property
def images(self):
"""
图片列表(兼容 mixed
"""
return self.get('images', [])
@property
def file(self):
"""
文件信息
"""
return self.get('file', {})
@property
def voice(self):
"""
语音信息
"""
return self.get('voice', {})
@property
def video(self):
"""
视频信息
"""
return self.get('video', {})
@property
def link(self):
"""
链接消息信息
"""
return self.get('link', {})
@property
def location(self):
"""
位置信息
"""
return self.get('location', {})
@property
def attachments(self):
"""
原始 mixed 中的附件项
"""
return self.get('attachments', [])
@property
def chatid(self) -> str:
"""

View File

@@ -21,30 +21,23 @@ class WecomClient:
EncodingAESKey: str,
contacts_secret: str,
logger: None,
unified_mode: bool = False,
api_base_url: str = 'https://qyapi.weixin.qq.com/cgi-bin',
):
self.corpid = corpid
self.secret = secret
self.access_token_for_contacts = ''
self.token = token
self.aes = EncodingAESKey
self.base_url = api_base_url
self.base_url = 'https://qyapi.weixin.qq.com/cgi-bin'
self.access_token = ''
self.secret_for_contacts = contacts_secret
self.logger = logger
self.unified_mode = unified_mode
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self.app.add_url_rule(
'/callback/command',
'handle_callback',
self.handle_callback_request,
methods=['GET', 'POST'],
)
self._message_handlers = {
'example': [],
}
@@ -57,7 +50,7 @@ class WecomClient:
return bool(self.access_token_for_contacts and self.access_token_for_contacts.strip())
async def get_access_token(self, secret):
url = f'{self.base_url}/gettoken?corpid={self.corpid}&corpsecret={secret}'
url = f'https://qyapi.weixin.qq.com/cgi-bin/gettoken?corpid={self.corpid}&corpsecret={secret}'
async with httpx.AsyncClient() as client:
response = await client.get(url)
data = response.json()
@@ -116,13 +109,14 @@ class WecomClient:
async def send_image(self, user_id: str, agent_id: int, media_id: str):
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/message/send?access_token=' + self.access_token
url = self.base_url + '/media/upload?access_token=' + self.access_token
async with httpx.AsyncClient() as client:
params = {
'touser': user_id,
'msgtype': 'image',
'toparty': '',
'totag': '',
'agentid': agent_id,
'msgtype': 'image',
'image': {
'media_id': media_id,
},
@@ -131,73 +125,27 @@ class WecomClient:
'enable_duplicate_check': 0,
'duplicate_check_interval': 1800,
}
response = await client.post(url, json=params)
data = response.json()
try:
response = await client.post(url, json=params)
data = response.json()
except Exception as e:
await self.logger.error(f'发送图片失败:{data}')
raise Exception('Failed to send image: ' + str(e))
# 企业微信错误码40014和42001代表accesstoken问题
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
return await self.send_image(user_id, agent_id, media_id)
if data['errcode'] != 0:
await self.logger.error(f'发送图片失败:{data}')
raise Exception('Failed to send image: ' + str(data))
async def send_voice(self, user_id: str, agent_id: int, media_id: str):
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/message/send?access_token=' + self.access_token
async with httpx.AsyncClient() as client:
params = {
'touser': user_id,
'msgtype': 'voice',
'agentid': agent_id,
'voice': {
'media_id': media_id,
},
'safe': 0,
'enable_id_trans': 0,
'enable_duplicate_check': 0,
'duplicate_check_interval': 1800,
}
response = await client.post(url, json=params)
data = response.json()
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
return await self.send_voice(user_id, agent_id, media_id)
if data['errcode'] != 0:
await self.logger.error(f'发送语音失败:{data}')
raise Exception('Failed to send voice: ' + str(data))
async def send_file(self, user_id: str, agent_id: int, media_id: str):
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/message/send?access_token=' + self.access_token
async with httpx.AsyncClient() as client:
params = {
'touser': user_id,
'msgtype': 'file',
'agentid': agent_id,
'file': {
'media_id': media_id,
},
'safe': 0,
'enable_id_trans': 0,
'enable_duplicate_check': 0,
'duplicate_check_interval': 1800,
}
response = await client.post(url, json=params)
data = response.json()
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
return await self.send_file(user_id, agent_id, media_id)
if data['errcode'] != 0:
await self.logger.error(f'发送文件失败:{data}')
raise Exception('Failed to send file: ' + str(data))
async def send_private_msg(self, user_id: str, agent_id: int, content: str):
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/message/send?access_token=' + self.access_token
async with httpx.AsyncClient(timeout=None) as client:
async with httpx.AsyncClient() as client:
params = {
'touser': user_id,
'msgtype': 'text',
@@ -220,43 +168,25 @@ class WecomClient:
raise Exception('Failed to send message: ' + str(data))
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""
处理回调请求的内部实现,包括 GET 验证和 POST 消息接收。
Args:
req: Quart Request 对象
处理回调请求,包括 GET 验证和 POST 消息接收。
"""
try:
msg_signature = req.args.get('msg_signature')
timestamp = req.args.get('timestamp')
nonce = req.args.get('nonce')
msg_signature = request.args.get('msg_signature')
timestamp = request.args.get('timestamp')
nonce = request.args.get('nonce')
wxcpt = WXBizMsgCrypt(self.token, self.aes, self.corpid)
if req.method == 'GET':
echostr = req.args.get('echostr')
if request.method == 'GET':
echostr = request.args.get('echostr')
ret, reply_echo_str = wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
if ret != 0:
await self.logger.error('验证失败')
raise Exception(f'验证失败,错误码: {ret}')
return reply_echo_str
elif req.method == 'POST':
encrypt_msg = await req.data
elif request.method == 'POST':
encrypt_msg = await request.data
ret, xml_msg = wxcpt.DecryptMsg(encrypt_msg, msg_signature, timestamp, nonce)
if ret != 0:
await self.logger.error('消息解密失败')
@@ -340,7 +270,7 @@ class WecomClient:
return ext
return 'jpg' # 默认返回jpg
async def upload_image_to_work(self, image: platform_message.Image):
async def upload_to_work(self, image: platform_message.Image):
"""
获取 media_id
"""
@@ -357,7 +287,7 @@ class WecomClient:
file_bytes = await f.read()
file_name = image.path.split('/')[-1]
elif image.url:
file_bytes = await self.download_media_to_bytes(image.url)
file_bytes = await self.download_image_to_bytes(image.url)
file_name = image.url.split('/')[-1]
elif image.base64:
try:
@@ -392,7 +322,7 @@ class WecomClient:
data = response.json()
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
media_id = await self.upload_image_to_work(image)
media_id = await self.upload_to_work(image)
if data.get('errcode', 0) != 0:
await self.logger.error(f'上传图片失败:{data}')
raise Exception('failed to upload file')
@@ -400,128 +330,13 @@ class WecomClient:
media_id = data.get('media_id')
return media_id
async def upload_voice_to_work(self, voice: platform_message.Voice):
"""
上传语音文件到企业微信
"""
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
file_bytes = None
file_name = 'voice.mp3'
if voice.path:
async with aiofiles.open(voice.path, 'rb') as f:
file_bytes = await f.read()
file_name = voice.path.split('/')[-1]
elif voice.url:
file_bytes = await self.download_media_to_bytes(voice.url)
file_name = voice.url.split('/')[-1]
elif voice.base64:
try:
base64_data = voice.base64
if ',' in base64_data:
base64_data = base64_data.split(',', 1)[1]
padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
padded_base64 = base64_data + '=' * padding
file_bytes = base64.b64decode(padded_base64)
except binascii.Error as e:
raise ValueError(f'Invalid base64 string: {str(e)}')
else:
await self.logger.error('Voice对象出错')
raise ValueError('voice对象出错')
boundary = '-------------------------acebdf13572468'
headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
body = (
(
f'--{boundary}\r\n'
f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
f'Content-Type: application/octet-stream\r\n\r\n'
).encode('utf-8')
+ file_bytes
+ f'\r\n--{boundary}--\r\n'.encode('utf-8')
)
# print(body)
async with httpx.AsyncClient() as client:
response = await client.post(url, headers=headers, content=body)
data = response.json()
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
media_id = await self.upload_voice_to_work(voice)
if data.get('errcode', 0) != 0:
await self.logger.error(f'上传语音文件失败:{data}')
raise Exception('failed to upload file')
media_id = data.get('media_id')
return media_id
async def upload_file_to_work(self, file: platform_message.File):
"""
上传文件到企业微信
"""
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
file_bytes = None
file_name = 'file.txt'
if file.path:
async with aiofiles.open(file.path, 'rb') as f:
file_bytes = await f.read()
file_name = file.path.split('/')[-1]
elif file.url:
file_bytes = await self.download_media_to_bytes(file.url)
file_name = file.url.split('/')[-1]
elif file.base64:
try:
base64_data = file.base64
if ',' in base64_data:
base64_data = base64_data.split(',', 1)[1]
padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
padded_base64 = base64_data + '=' * padding
file_bytes = base64.b64decode(padded_base64)
except binascii.Error as e:
raise ValueError(f'Invalid base64 string: {str(e)}')
else:
await self.logger.error('File对象出错')
raise ValueError('file对象出错')
boundary = '-------------------------acebdf13572468'
headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
body = (
(
f'--{boundary}\r\n'
f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
f'Content-Type: application/octet-stream\r\n\r\n'
).encode('utf-8')
+ file_bytes
+ f'\r\n--{boundary}--\r\n'.encode('utf-8')
)
async with httpx.AsyncClient() as client:
response = await client.post(url, headers=headers, content=body)
data = response.json()
if data['errcode'] == 40014 or data['errcode'] == 42001:
self.access_token = await self.get_access_token(self.secret)
media_id = await self.upload_file_to_work(file)
if data.get('errcode', 0) != 0:
await self.logger.error(f'上传文件失败:{data}')
raise Exception('failed to upload file')
media_id = data.get('media_id')
return media_id
async def download_media_to_bytes(self, url: str) -> bytes:
async def download_image_to_bytes(self, url: str) -> bytes:
async with httpx.AsyncClient() as client:
response = await client.get(url)
response.raise_for_status()
return response.content
# 进行media_id的获取
async def get_media_id(self, media: platform_message.Image | platform_message.Voice | platform_message.File):
if isinstance(media, platform_message.Image):
media_id = await self.upload_image_to_work(image=media)
elif isinstance(media, platform_message.Voice):
media_id = await self.upload_voice_to_work(voice=media)
elif isinstance(media, platform_message.File):
media_id = await self.upload_file_to_work(file=media)
else:
raise ValueError('Unsupported media type')
async def get_media_id(self, image: platform_message.Image):
media_id = await self.upload_to_work(image=image)
return media_id

View File

@@ -13,33 +13,19 @@ import aiofiles
class WecomCSClient:
def __init__(
self,
corpid: str,
secret: str,
token: str,
EncodingAESKey: str,
logger: None,
unified_mode: bool = False,
api_base_url: str = 'https://qyapi.weixin.qq.com/cgi-bin',
):
def __init__(self, corpid: str, secret: str, token: str, EncodingAESKey: str, logger: None):
self.corpid = corpid
self.secret = secret
self.access_token_for_contacts = ''
self.token = token
self.aes = EncodingAESKey
self.base_url = api_base_url
self.base_url = 'https://qyapi.weixin.qq.com/cgi-bin'
self.access_token = ''
self.logger = logger
self.unified_mode = unified_mode
self.app = Quart(__name__)
# 只有在非统一模式下才注册独立路由
if not self.unified_mode:
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
)
self.app.add_url_rule(
'/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
)
self._message_handlers = {
'example': [],
}
@@ -75,7 +61,7 @@ class WecomCSClient:
return bool(self.access_token_for_contacts and self.access_token_for_contacts.strip())
async def get_access_token(self, secret):
url = f'{self.base_url}/gettoken?corpid={self.corpid}&corpsecret={secret}'
url = f'https://qyapi.weixin.qq.com/cgi-bin/gettoken?corpid={self.corpid}&corpsecret={secret}'
async with httpx.AsyncClient() as client:
response = await client.get(url)
data = response.json()
@@ -181,7 +167,7 @@ class WecomCSClient:
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = f'{self.base_url}/kf/send_msg?access_token={self.access_token}'
url = f'https://qyapi.weixin.qq.com/cgi-bin/kf/send_msg?access_token={self.access_token}'
payload = {
'touser': external_userid,
@@ -206,45 +192,27 @@ class WecomCSClient:
return data
async def handle_callback_request(self):
"""处理回调请求(独立端口模式,使用全局 request"""
return await self._handle_callback_internal(request)
async def handle_unified_webhook(self, req):
"""处理回调请求(统一 webhook 模式,显式传递 request
Args:
req: Quart Request 对象
Returns:
响应数据
"""
return await self._handle_callback_internal(req)
async def _handle_callback_internal(self, req):
"""
处理回调请求的内部实现,包括 GET 验证和 POST 消息接收。
Args:
req: Quart Request 对象
处理回调请求,包括 GET 验证和 POST 消息接收。
"""
try:
msg_signature = req.args.get('msg_signature')
timestamp = req.args.get('timestamp')
nonce = req.args.get('nonce')
msg_signature = request.args.get('msg_signature')
timestamp = request.args.get('timestamp')
nonce = request.args.get('nonce')
try:
wxcpt = WXBizMsgCrypt(self.token, self.aes, self.corpid)
except Exception as e:
raise Exception(f'初始化失败,错误码: {e}')
if req.method == 'GET':
echostr = req.args.get('echostr')
if request.method == 'GET':
echostr = request.args.get('echostr')
ret, reply_echo_str = wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
if ret != 0:
raise Exception(f'验证失败,错误码: {ret}')
return reply_echo_str
elif req.method == 'POST':
encrypt_msg = await req.data
elif request.method == 'POST':
encrypt_msg = await request.data
ret, xml_msg = wxcpt.DecryptMsg(encrypt_msg, msg_signature, timestamp, nonce)
if ret != 0:
raise Exception(f'消息解密失败,错误码: {ret}')

View File

@@ -28,56 +28,8 @@ class FilesRouterGroup(group.RouterGroup):
return quart.Response(image_bytes, mimetype=mime_type)
@self.route('/images', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def upload_image() -> quart.Response:
request = quart.request
# Check file size limit before reading the file
content_length = request.content_length
if content_length and content_length > group.MAX_FILE_SIZE:
return self.fail(400, 'Image size exceeds 10MB limit.')
# get file bytes from 'file'
files = await request.files
if 'file' not in files:
return self.fail(400, 'No image file provided')
file = files['file']
assert isinstance(file, quart.datastructures.FileStorage)
file_bytes = await asyncio.to_thread(file.stream.read)
# Double-check actual file size after reading
if len(file_bytes) > group.MAX_FILE_SIZE:
return self.fail(400, 'Image size exceeds 10MB limit.')
# Validate image file extension
allowed_extensions = {'jpg', 'jpeg', 'png', 'gif', 'webp'}
if '.' in file.filename:
file_name, extension = file.filename.rsplit('.', 1)
extension = extension.lower()
else:
return self.fail(400, 'Invalid image file: no file extension')
if extension not in allowed_extensions:
return self.fail(400, f'Invalid image format. Allowed formats: {", ".join(allowed_extensions)}')
# check if file name contains '/' or '\'
if '/' in file_name or '\\' in file_name:
return self.fail(400, 'File name contains invalid characters')
file_key = file_name + '_' + str(uuid.uuid4())[:8] + '.' + extension
# save file to storage
await self.ap.storage_mgr.storage_provider.save(file_key, file_bytes)
return self.success(
data={
'file_key': file_key,
}
)
@self.route('/documents', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def upload_document() -> quart.Response:
@self.route('/documents', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> quart.Response:
request = quart.request
# Check file size limit before reading the file

View File

@@ -5,7 +5,7 @@ from ... import group
@group.group_class('knowledge_base', '/api/v1/knowledge/bases')
class KnowledgeBaseRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['POST', 'GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@self.route('', methods=['POST', 'GET'])
async def handle_knowledge_bases() -> quart.Response:
if quart.request.method == 'GET':
knowledge_bases = await self.ap.knowledge_service.get_knowledge_bases()
@@ -21,7 +21,6 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
@self.route(
'/<knowledge_base_uuid>',
methods=['GET', 'DELETE', 'PUT'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def handle_specific_knowledge_base(knowledge_base_uuid: str) -> quart.Response:
if quart.request.method == 'GET':
@@ -48,7 +47,6 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
@self.route(
'/<knowledge_base_uuid>/files',
methods=['GET', 'POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def get_knowledge_base_files(knowledge_base_uuid: str) -> str:
if quart.request.method == 'GET':
@@ -76,7 +74,6 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
@self.route(
'/<knowledge_base_uuid>/files/<file_id>',
methods=['DELETE'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def delete_specific_file_in_kb(file_id: str, knowledge_base_uuid: str) -> str:
await self.ap.knowledge_service.delete_file(knowledge_base_uuid, file_id)
@@ -85,7 +82,6 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
@self.route(
'/<knowledge_base_uuid>/retrieve',
methods=['POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def retrieve_knowledge_base(knowledge_base_uuid: str) -> str:
json_data = await quart.request.json

View File

@@ -1,61 +0,0 @@
import quart
from ... import group
@group.group_class('external_knowledge_base', '/api/v1/knowledge/external-bases')
class ExternalKnowledgeBaseRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/retrievers', methods=['GET'])
async def list_knowledge_retrievers() -> quart.Response:
"""List all available knowledge retrievers from plugins."""
retrievers = await self.ap.plugin_connector.list_knowledge_retrievers()
return self.success(data={'retrievers': retrievers})
@self.route('', methods=['POST', 'GET'])
async def handle_external_knowledge_bases() -> quart.Response:
if quart.request.method == 'GET':
external_kbs = await self.ap.external_kb_service.get_external_knowledge_bases()
return self.success(data={'bases': external_kbs})
elif quart.request.method == 'POST':
json_data = await quart.request.json
kb_uuid = await self.ap.external_kb_service.create_external_knowledge_base(json_data)
return self.success(data={'uuid': kb_uuid})
return self.http_status(405, -1, 'Method not allowed')
@self.route(
'/<kb_uuid>',
methods=['GET', 'DELETE', 'PUT'],
)
async def handle_specific_external_knowledge_base(kb_uuid: str) -> quart.Response:
if quart.request.method == 'GET':
external_kb = await self.ap.external_kb_service.get_external_knowledge_base(kb_uuid)
if external_kb is None:
return self.http_status(404, -1, 'external knowledge base not found')
return self.success(
data={
'base': external_kb,
}
)
elif quart.request.method == 'PUT':
json_data = await quart.request.json
await self.ap.external_kb_service.update_external_knowledge_base(kb_uuid, json_data)
return self.success({})
elif quart.request.method == 'DELETE':
await self.ap.external_kb_service.delete_external_knowledge_base(kb_uuid)
return self.success({})
@self.route(
'/<kb_uuid>/retrieve',
methods=['POST'],
)
async def retrieve_external_knowledge_base(kb_uuid: str) -> str:
json_data = await quart.request.json
query = json_data.get('query')
results = await self.ap.external_kb_service.retrieve_external_knowledge_base(kb_uuid, query)
return self.success(data={'results': results})

View File

@@ -1,488 +0,0 @@
from __future__ import annotations
import datetime
import quart
from .. import group
def parse_iso_datetime(datetime_str: str | None) -> datetime.datetime | None:
"""Parse ISO 8601 datetime string, handling 'Z' suffix for UTC timezone"""
if not datetime_str:
return None
# Replace 'Z' with '+00:00' for Python 3.10 compatibility
if datetime_str.endswith('Z'):
datetime_str = datetime_str[:-1] + '+00:00'
dt = datetime.datetime.fromisoformat(datetime_str)
# Convert to UTC and remove timezone info to match database storage (which stores UTC as naive datetime)
if dt.tzinfo is not None:
# Convert to UTC and remove timezone info
dt = dt.astimezone(datetime.timezone.utc).replace(tzinfo=None)
return dt
@group.group_class('monitoring', '/api/v1/monitoring')
class MonitoringRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/overview', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_overview() -> str:
"""Get overview metrics"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
metrics = await self.ap.monitoring_service.get_overview_metrics(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
)
return self.success(data=metrics)
@self.route('/messages', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_messages() -> str:
"""Get message logs"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
session_ids = quart.request.args.getlist('sessionId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 100))
offset = int(quart.request.args.get('offset', 0))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
messages, total = await self.ap.monitoring_service.get_messages(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
session_ids=session_ids if session_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=offset,
)
return self.success(
data={
'messages': messages,
'total': total,
'limit': limit,
'offset': offset,
}
)
@self.route('/llm-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_llm_calls() -> str:
"""Get LLM call records"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 100))
offset = int(quart.request.args.get('offset', 0))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
llm_calls, total = await self.ap.monitoring_service.get_llm_calls(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=offset,
)
return self.success(
data={
'llm_calls': llm_calls,
'total': total,
'limit': limit,
'offset': offset,
}
)
@self.route('/embedding-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_embedding_calls() -> str:
"""Get embedding call records"""
# Parse query parameters
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
knowledge_base_id = quart.request.args.get('knowledgeBaseId')
limit = int(quart.request.args.get('limit', 100))
offset = int(quart.request.args.get('offset', 0))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
embedding_calls, total = await self.ap.monitoring_service.get_embedding_calls(
start_time=start_time,
end_time=end_time,
knowledge_base_id=knowledge_base_id if knowledge_base_id else None,
limit=limit,
offset=offset,
)
return self.success(
data={
'embedding_calls': embedding_calls,
'total': total,
'limit': limit,
'offset': offset,
}
)
@self.route('/sessions', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_sessions() -> str:
"""Get session information"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
is_active_str = quart.request.args.get('isActive')
limit = int(quart.request.args.get('limit', 100))
offset = int(quart.request.args.get('offset', 0))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
# Parse is_active
is_active = None
if is_active_str:
is_active = is_active_str.lower() == 'true'
sessions, total = await self.ap.monitoring_service.get_sessions(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
is_active=is_active,
limit=limit,
offset=offset,
)
return self.success(
data={
'sessions': sessions,
'total': total,
'limit': limit,
'offset': offset,
}
)
@self.route('/errors', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_errors() -> str:
"""Get error logs"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 100))
offset = int(quart.request.args.get('offset', 0))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
errors, total = await self.ap.monitoring_service.get_errors(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=offset,
)
return self.success(
data={
'errors': errors,
'total': total,
'limit': limit,
'offset': offset,
}
)
@self.route('/data', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_all_data() -> str:
"""Get all monitoring data in a single request"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 50))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
# Get overview metrics
overview = await self.ap.monitoring_service.get_overview_metrics(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
)
# Get messages
messages, messages_total = await self.ap.monitoring_service.get_messages(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=0,
)
# Get LLM calls
llm_calls, llm_calls_total = await self.ap.monitoring_service.get_llm_calls(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=0,
)
# Get sessions
sessions, sessions_total = await self.ap.monitoring_service.get_sessions(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
is_active=None,
limit=limit,
offset=0,
)
# Get errors
errors, errors_total = await self.ap.monitoring_service.get_errors(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=0,
)
# Get embedding calls
embedding_calls, embedding_calls_total = await self.ap.monitoring_service.get_embedding_calls(
start_time=start_time,
end_time=end_time,
limit=limit,
offset=0,
)
return self.success(
data={
'overview': overview,
'messages': messages,
'llmCalls': llm_calls,
'embeddingCalls': embedding_calls,
'sessions': sessions,
'errors': errors,
'totalCount': {
'messages': messages_total,
'llmCalls': llm_calls_total,
'embeddingCalls': embedding_calls_total,
'sessions': sessions_total,
'errors': errors_total,
},
}
)
@self.route('/sessions/<session_id>/analysis', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_session_analysis(session_id: str) -> str:
"""Get detailed analysis for a specific session"""
analysis = await self.ap.monitoring_service.get_session_analysis(session_id)
# Always return success with the analysis data
# The frontend will handle the 'found: false' case
return self.success(data=analysis)
@self.route('/messages/<message_id>/details', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_message_details(message_id: str) -> str:
"""Get detailed information for a specific message"""
details = await self.ap.monitoring_service.get_message_details(message_id)
if not details.get('found'):
return self.error(message=f'Message {message_id} not found', code=404)
return self.success(data=details)
@self.route('/export', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def export_data() -> tuple[str, int]:
"""Export monitoring data as CSV"""
# Parse query parameters
export_type = quart.request.args.get('type', 'messages')
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 100000))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
# Get data based on export type
if export_type == 'messages':
data = await self.ap.monitoring_service.export_messages(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = [
'id',
'timestamp',
'bot_id',
'bot_name',
'pipeline_id',
'pipeline_name',
'runner_name',
'message_content',
'message_text',
'session_id',
'status',
'level',
'platform',
'user_id',
]
elif export_type == 'llm-calls':
data = await self.ap.monitoring_service.export_llm_calls(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = [
'id',
'timestamp',
'model_name',
'input_tokens',
'output_tokens',
'total_tokens',
'duration_ms',
'cost',
'status',
'bot_id',
'bot_name',
'pipeline_id',
'pipeline_name',
'session_id',
'message_id',
'error_message',
]
elif export_type == 'embedding-calls':
data = await self.ap.monitoring_service.export_embedding_calls(
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = [
'id',
'timestamp',
'model_name',
'prompt_tokens',
'total_tokens',
'duration_ms',
'input_count',
'status',
'error_message',
'knowledge_base_id',
'query_text',
'session_id',
'message_id',
'call_type',
]
elif export_type == 'errors':
data = await self.ap.monitoring_service.export_errors(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = [
'id',
'timestamp',
'error_type',
'error_message',
'bot_id',
'bot_name',
'pipeline_id',
'pipeline_name',
'session_id',
'message_id',
'stack_trace',
]
elif export_type == 'sessions':
data = await self.ap.monitoring_service.export_sessions(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = [
'session_id',
'bot_id',
'bot_name',
'pipeline_id',
'pipeline_name',
'message_count',
'start_time',
'last_activity',
'is_active',
'platform',
'user_id',
]
else:
return self.error(message=f'Invalid export type: {export_type}', code=400)
# Generate CSV content with UTF-8 BOM for Excel compatibility
import io
output = io.StringIO()
# Write UTF-8 BOM for Excel
output.write('\ufeff')
# Write header
output.write(','.join(headers) + '\n')
# Escape and write each row
for row in data:
escaped_values = []
for header in headers:
value = row.get(header, '')
escaped_values.append(self.ap.monitoring_service._escape_csv_field(value))
output.write(','.join(escaped_values) + '\n')
csv_content = output.getvalue()
# Return as file download
response = await quart.make_response(csv_content)
response.headers['Content-Type'] = 'text/csv; charset=utf-8'
response.headers['Content-Disposition'] = (
f'attachment; filename="monitoring-{export_type}-{int(datetime.datetime.now().timestamp())}.csv"'
)
return response, 200

View File

@@ -49,14 +49,6 @@ class PipelinesRouterGroup(group.RouterGroup):
return self.success()
@self.route('/<pipeline_uuid>/copy', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _(pipeline_uuid: str) -> str:
try:
new_uuid = await self.ap.pipeline_service.copy_pipeline(pipeline_uuid)
return self.success(data={'uuid': new_uuid})
except ValueError as e:
return self.http_status(404, -1, str(e))
@self.route(
'/<pipeline_uuid>/extensions', methods=['GET', 'PUT'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
)
@@ -67,33 +59,25 @@ class PipelinesRouterGroup(group.RouterGroup):
if pipeline is None:
return self.http_status(404, -1, 'pipeline not found')
# Only include plugins with pipeline-related components (Command, EventListener, Tool)
# Plugins that only have KnowledgeRetriever components are not suitable for pipeline extensions
pipeline_component_kinds = ['Command', 'EventListener', 'Tool']
plugins = await self.ap.plugin_connector.list_plugins(component_kinds=pipeline_component_kinds)
plugins = await self.ap.plugin_connector.list_plugins()
mcp_servers = await self.ap.mcp_service.get_mcp_servers(contain_runtime_info=True)
extensions_prefs = pipeline.get('extensions_preferences', {})
return self.success(
data={
'enable_all_plugins': extensions_prefs.get('enable_all_plugins', True),
'enable_all_mcp_servers': extensions_prefs.get('enable_all_mcp_servers', True),
'bound_plugins': extensions_prefs.get('plugins', []),
'bound_plugins': pipeline.get('extensions_preferences', {}).get('plugins', []),
'available_plugins': plugins,
'bound_mcp_servers': extensions_prefs.get('mcp_servers', []),
'bound_mcp_servers': pipeline.get('extensions_preferences', {}).get('mcp_servers', []),
'available_mcp_servers': mcp_servers,
}
)
elif quart.request.method == 'PUT':
# Update bound plugins and MCP servers for this pipeline
json_data = await quart.request.json
enable_all_plugins = json_data.get('enable_all_plugins', True)
enable_all_mcp_servers = json_data.get('enable_all_mcp_servers', True)
bound_plugins = json_data.get('bound_plugins', [])
bound_mcp_servers = json_data.get('bound_mcp_servers', [])
await self.ap.pipeline_service.update_pipeline_extensions(
pipeline_uuid, bound_plugins, bound_mcp_servers, enable_all_plugins, enable_all_mcp_servers
pipeline_uuid, bound_plugins, bound_mcp_servers
)
return self.success()

View File

@@ -0,0 +1,109 @@
import json
import quart
from ... import group
@group.group_class('webchat', '/api/v1/pipelines/<pipeline_uuid>/chat')
class WebChatDebugRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/send', methods=['POST'])
async def send_message(pipeline_uuid: str) -> str:
"""Send a message to the pipeline for debugging"""
async def stream_generator(generator):
yield 'data: {"type": "start"}\n\n'
async for message in generator:
yield f'data: {json.dumps({"message": message})}\n\n'
yield 'data: {"type": "end"}\n\n'
try:
data = await quart.request.get_json()
session_type = data.get('session_type', 'person')
message_chain_obj = data.get('message', [])
is_stream = data.get('is_stream', False)
if not message_chain_obj:
return self.http_status(400, -1, 'message is required')
if session_type not in ['person', 'group']:
return self.http_status(400, -1, 'session_type must be person or group')
webchat_adapter = self.ap.platform_mgr.webchat_proxy_bot.adapter
if not webchat_adapter:
return self.http_status(404, -1, 'WebChat adapter not found')
if is_stream:
generator = webchat_adapter.send_webchat_message(
pipeline_uuid, session_type, message_chain_obj, is_stream
)
# 设置正确的响应头
headers = {
'Content-Type': 'text/event-stream',
'Transfer-Encoding': 'chunked',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
}
return quart.Response(stream_generator(generator), mimetype='text/event-stream', headers=headers)
else: # non-stream
result = None
async for message in webchat_adapter.send_webchat_message(
pipeline_uuid, session_type, message_chain_obj
):
result = message
if result is not None:
return self.success(
data={
'message': result,
}
)
else:
return self.http_status(400, -1, 'message is required')
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
@self.route('/messages/<session_type>', methods=['GET'])
async def get_messages(pipeline_uuid: str, session_type: str) -> str:
"""Get the message history of the pipeline for debugging"""
try:
if session_type not in ['person', 'group']:
return self.http_status(400, -1, 'session_type must be person or group')
webchat_adapter = self.ap.platform_mgr.webchat_proxy_bot.adapter
if not webchat_adapter:
return self.http_status(404, -1, 'WebChat adapter not found')
messages = webchat_adapter.get_webchat_messages(pipeline_uuid, session_type)
return self.success(data={'messages': messages})
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
@self.route('/reset/<session_type>', methods=['POST'])
async def reset_session(session_type: str) -> str:
"""Reset the debug session"""
try:
if session_type not in ['person', 'group']:
return self.http_status(400, -1, 'session_type must be person or group')
webchat_adapter = None
for bot in self.ap.platform_mgr.bots:
if hasattr(bot.adapter, '__class__') and bot.adapter.__class__.__name__ == 'WebChatAdapter':
webchat_adapter = bot.adapter
break
if not webchat_adapter:
return self.http_status(404, -1, 'WebChat adapter not found')
webchat_adapter.reset_debug_session(session_type)
return self.success(data={'message': 'Session reset successfully'})
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')

View File

@@ -1,243 +0,0 @@
"""WebSocket聊天路由 - 支持双向实时通信"""
import asyncio
import datetime
import json
import logging
import quart
from ... import group
from ......platform.sources.websocket_manager import ws_connection_manager
logger = logging.getLogger(__name__)
@group.group_class('websocket_chat', '/api/v1/pipelines/<pipeline_uuid>/ws')
class WebSocketChatRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
# 直接使用 quart_app 注册 WebSocket 路由
@self.quart_app.websocket(self.path + '/connect')
async def websocket_connect(pipeline_uuid: str):
"""
建立WebSocket连接
URL参数:
- pipeline_uuid: 流水线UUID
- session_type: 会话类型 (person/group)
"""
try:
# 获取参数 - 在WebSocket上下文中使用 quart.websocket.args
session_type = quart.websocket.args.get('session_type', 'person')
if session_type not in ['person', 'group']:
await quart.websocket.send(
json.dumps({'type': 'error', 'message': 'session_type must be person or group'})
)
return
# 获取WebSocket适配器
websocket_adapter = self.ap.platform_mgr.websocket_proxy_bot.adapter
if not websocket_adapter:
await quart.websocket.send(json.dumps({'type': 'error', 'message': 'WebSocket adapter not found'}))
return
# 注册连接
connection = await ws_connection_manager.add_connection(
websocket=quart.websocket._get_current_object(),
pipeline_uuid=pipeline_uuid,
session_type=session_type,
metadata={'user_agent': quart.websocket.headers.get('User-Agent', '')},
)
# 发送连接成功消息
await quart.websocket.send(
json.dumps(
{
'type': 'connected',
'connection_id': connection.connection_id,
'pipeline_uuid': pipeline_uuid,
'session_type': session_type,
'timestamp': connection.created_at.isoformat(),
}
)
)
logger.debug(
f'WebSocket connection established: {connection.connection_id} '
f'(pipeline={pipeline_uuid}, session_type={session_type})'
)
# 创建接收和发送任务
receive_task = asyncio.create_task(self._handle_receive(connection, websocket_adapter))
send_task = asyncio.create_task(self._handle_send(connection))
# 等待任务完成
try:
await asyncio.gather(receive_task, send_task)
except Exception as e:
logger.error(f'WebSocket task execution error: {e}')
finally:
# 清理连接
await ws_connection_manager.remove_connection(connection.connection_id)
logger.debug(f'WebSocket connection cleaned: {connection.connection_id}')
except Exception as e:
logger.error(f'WebSocket connection error: {e}', exc_info=True)
try:
await quart.websocket.send(json.dumps({'type': 'error', 'message': str(e)}))
except:
pass
@self.route('/messages/<session_type>', methods=['GET'])
async def get_messages(pipeline_uuid: str, session_type: str) -> str:
"""获取消息历史"""
try:
if session_type not in ['person', 'group']:
return self.http_status(400, -1, 'session_type must be person or group')
websocket_adapter = self.ap.platform_mgr.websocket_proxy_bot.adapter
if not websocket_adapter:
return self.http_status(404, -1, 'WebSocket adapter not found')
messages = websocket_adapter.get_websocket_messages(pipeline_uuid, session_type)
return self.success(data={'messages': messages})
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
@self.route('/reset/<session_type>', methods=['POST'])
async def reset_session(pipeline_uuid: str, session_type: str) -> str:
"""重置会话"""
try:
if session_type not in ['person', 'group']:
return self.http_status(400, -1, 'session_type must be person or group')
websocket_adapter = self.ap.platform_mgr.websocket_proxy_bot.adapter
if not websocket_adapter:
return self.http_status(404, -1, 'WebSocket adapter not found')
websocket_adapter.reset_session(pipeline_uuid, session_type)
return self.success(data={'message': 'Session reset successfully'})
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
@self.route('/connections', methods=['GET'])
async def get_connections(pipeline_uuid: str) -> str:
"""获取当前连接统计"""
try:
stats = ws_connection_manager.get_stats()
connections = await ws_connection_manager.get_connections_by_pipeline(pipeline_uuid)
return self.success(
data={
'stats': stats,
'connections': [
{
'connection_id': conn.connection_id,
'session_type': conn.session_type,
'created_at': conn.created_at.isoformat(),
'last_active': conn.last_active.isoformat(),
'is_active': conn.is_active,
}
for conn in connections
],
}
)
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
@self.route('/broadcast', methods=['POST'])
async def broadcast_message(pipeline_uuid: str) -> str:
"""向所有连接广播消息(后端主动推送)"""
try:
data = await quart.request.get_json()
message = data.get('message')
if not message:
return self.http_status(400, -1, 'message is required')
# 广播消息
broadcast_data = {
'type': 'broadcast',
'message': message,
'timestamp': datetime.datetime.now().isoformat(),
}
await ws_connection_manager.broadcast_to_pipeline(pipeline_uuid, broadcast_data)
return self.success(data={'message': 'Broadcast sent successfully'})
except Exception as e:
return self.http_status(500, -1, f'Internal server error: {str(e)}')
async def _handle_receive(self, connection, websocket_adapter):
"""处理接收消息的任务"""
try:
while connection.is_active:
# 接收消息
message = await quart.websocket.receive()
# 更新活跃时间
await ws_connection_manager.update_activity(connection.connection_id)
try:
data = json.loads(message)
message_type = data.get('type', 'message')
if message_type == 'ping':
# 心跳响应
await connection.send_queue.put(
{'type': 'pong', 'timestamp': datetime.datetime.now().isoformat()}
)
elif message_type == 'message':
# 处理用户消息
logger.debug(f'收到消息: {data} from {connection.connection_id}')
# 处理消息不等待响应响应会通过broadcast异步发送
await websocket_adapter.handle_websocket_message(connection, data)
elif message_type == 'disconnect':
# 客户端主动断开
logger.debug(f'Client disconnected: {connection.connection_id}')
break
else:
logger.warning(f'Unknown message type: {message_type}')
except json.JSONDecodeError:
logger.error(f'Invalid JSON message: {message}')
await connection.send_queue.put({'type': 'error', 'message': 'Invalid JSON format'})
except Exception as e:
logger.error(f'Receive message error: {e}', exc_info=True)
finally:
connection.is_active = False
async def _handle_send(self, connection):
"""处理发送消息的任务"""
try:
while connection.is_active:
# 从队列获取消息
try:
message = await asyncio.wait_for(connection.send_queue.get(), timeout=1.0)
# 发送消息
await quart.websocket.send(json.dumps(message))
except asyncio.TimeoutError:
# 超时继续循环
continue
except Exception as e:
logger.error(f'Send message error: {e}', exc_info=True)
finally:
connection.is_active = False

View File

@@ -18,8 +18,7 @@ class BotsRouterGroup(group.RouterGroup):
@self.route('/<bot_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _(bot_uuid: str) -> str:
if quart.request.method == 'GET':
# 返回运行时信息包括webhook地址等
bot = await self.ap.bot_service.get_runtime_bot_info(bot_uuid)
bot = await self.ap.bot_service.get_bot(bot_uuid)
if bot is None:
return self.http_status(404, -1, 'bot not found')
return self.success(data={'bot': bot})
@@ -43,32 +42,3 @@ class BotsRouterGroup(group.RouterGroup):
'total_count': total_count,
}
)
@self.route('/<bot_uuid>/send_message', methods=['POST'], auth_type=group.AuthType.API_KEY)
async def _(bot_uuid: str) -> str:
"""Send message to a specific target via bot"""
json_data = await quart.request.json
target_type = json_data.get('target_type')
target_id = json_data.get('target_id')
message_chain_data = json_data.get('message_chain')
# Validate required fields
if not target_type:
return self.http_status(400, -1, 'target_type is required')
if not target_id:
return self.http_status(400, -1, 'target_id is required')
if not message_chain_data:
return self.http_status(400, -1, 'message_chain is required')
# Validate target_type
if target_type not in ['person', 'group']:
return self.http_status(400, -1, 'target_type must be either "person" or "group"')
try:
await self.ap.bot_service.send_message(bot_uuid, target_type, target_id, message_chain_data)
return self.success(data={'sent': True})
except Exception as e:
import traceback
traceback.print_exc()
return self.http_status(500, -1, f'Failed to send message: {str(e)}')

View File

@@ -14,45 +14,17 @@ from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
@group.group_class('plugins', '/api/v1/plugins')
class PluginsRouterGroup(group.RouterGroup):
async def _check_extensions_limit(self) -> str | None:
"""Check if extensions limit is reached. Returns error response if limit exceeded, None otherwise."""
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
max_extensions = limitation.get('max_extensions', -1)
if max_extensions >= 0:
plugins = await self.ap.plugin_connector.list_plugins()
mcp_servers = await self.ap.mcp_service.get_mcp_servers()
total_extensions = len(plugins) + len(mcp_servers)
if total_extensions >= max_extensions:
return self.http_status(400, -1, f'Maximum number of extensions ({max_extensions}) reached')
return None
async def initialize(self) -> None:
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
plugins = await self.ap.plugin_connector.list_plugins()
return self.success(data={'plugins': plugins})
@self.route('/debug-info', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _() -> str:
"""Get plugin debug information including debug URL and key"""
debug_info = await self.ap.plugin_connector.get_debug_info()
# Get debug URL from config
plugin_config = self.ap.instance_config.data.get('plugin', {})
debug_url = plugin_config.get('display_plugin_debug_url', 'http://localhost:5401')
return self.success(
data={
'debug_url': debug_url,
'plugin_debug_key': debug_info.get('plugin_debug_key', ''),
}
)
@self.route(
'/<author>/<plugin_name>/upgrade',
methods=['POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
auth_type=group.AuthType.USER_TOKEN,
)
async def _(author: str, plugin_name: str) -> str:
ctx = taskmgr.TaskContext.new()
@@ -68,7 +40,7 @@ class PluginsRouterGroup(group.RouterGroup):
@self.route(
'/<author>/<plugin_name>',
methods=['GET', 'DELETE'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
auth_type=group.AuthType.USER_TOKEN,
)
async def _(author: str, plugin_name: str) -> str:
if quart.request.method == 'GET':
@@ -94,7 +66,7 @@ class PluginsRouterGroup(group.RouterGroup):
@self.route(
'/<author>/<plugin_name>/config',
methods=['GET', 'PUT'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
auth_type=group.AuthType.USER_TOKEN,
)
async def _(author: str, plugin_name: str) -> quart.Response:
plugin = await self.ap.plugin_connector.get_plugin_info(author, plugin_name)
@@ -110,16 +82,6 @@ class PluginsRouterGroup(group.RouterGroup):
return self.success(data={})
@self.route(
'/<author>/<plugin_name>/readme',
methods=['GET'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def _(author: str, plugin_name: str) -> quart.Response:
language = quart.request.args.get('language', 'en')
readme = await self.ap.plugin_connector.get_plugin_readme(author, plugin_name, language=language)
return self.success(data={'readme': readme})
@self.route(
'/<author>/<plugin_name>/icon',
methods=['GET'],
@@ -134,18 +96,7 @@ class PluginsRouterGroup(group.RouterGroup):
return quart.Response(icon_data, mimetype=mime_type)
@self.route(
'/<author>/<plugin_name>/assets/<filepath>',
methods=['GET'],
auth_type=group.AuthType.NONE,
)
async def _(author: str, plugin_name: str, filepath: str) -> quart.Response:
asset_data = await self.ap.plugin_connector.get_plugin_assets(author, plugin_name, filepath)
asset_bytes = base64.b64decode(asset_data['asset_base64'])
mime_type = asset_data['mime_type']
return quart.Response(asset_bytes, mimetype=mime_type)
@self.route('/github/releases', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@self.route('/github/releases', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
"""Get releases from a GitHub repository URL"""
data = await quart.request.json
@@ -194,7 +145,7 @@ class PluginsRouterGroup(group.RouterGroup):
@self.route(
'/github/release-assets',
methods=['POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
auth_type=group.AuthType.USER_TOKEN,
)
async def _() -> str:
"""Get assets from a specific GitHub release"""
@@ -248,13 +199,9 @@ class PluginsRouterGroup(group.RouterGroup):
except httpx.RequestError as e:
return self.http_status(500, -1, f'Failed to fetch release assets: {str(e)}')
@self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
"""Install plugin from GitHub release asset"""
limit_error = await self._check_extensions_limit()
if limit_error is not None:
return limit_error
data = await quart.request.json
asset_url = data.get('asset_url', '')
owner = data.get('owner', '')
@@ -286,13 +233,9 @@ class PluginsRouterGroup(group.RouterGroup):
@self.route(
'/install/marketplace',
methods=['POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
auth_type=group.AuthType.USER_TOKEN,
)
async def _() -> str:
limit_error = await self._check_extensions_limit()
if limit_error is not None:
return limit_error
data = await quart.request.json
ctx = taskmgr.TaskContext.new()
@@ -306,12 +249,8 @@ class PluginsRouterGroup(group.RouterGroup):
return self.success(data={'task_id': wrapper.id})
@self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
limit_error = await self._check_extensions_limit()
if limit_error is not None:
return limit_error
file = (await quart.request.files).get('file')
if file is None:
return self.http_status(400, -1, 'file is required')

View File

@@ -9,15 +9,12 @@ class LLMModelsRouterGroup(group.RouterGroup):
@self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _() -> str:
if quart.request.method == 'GET':
provider_uuid = quart.request.args.get('provider_uuid')
if provider_uuid:
return self.success(
data={'models': await self.ap.llm_model_service.get_llm_models_by_provider(provider_uuid)}
)
return self.success(data={'models': await self.ap.llm_model_service.get_llm_models()})
elif quart.request.method == 'POST':
json_data = await quart.request.json
model_uuid = await self.ap.llm_model_service.create_llm_model(json_data)
return self.success(data={'uuid': model_uuid})
@self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@@ -55,19 +52,12 @@ class EmbeddingModelsRouterGroup(group.RouterGroup):
@self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _() -> str:
if quart.request.method == 'GET':
provider_uuid = quart.request.args.get('provider_uuid')
if provider_uuid:
return self.success(
data={
'models': await self.ap.embedding_models_service.get_embedding_models_by_provider(
provider_uuid
)
}
)
return self.success(data={'models': await self.ap.embedding_models_service.get_embedding_models()})
elif quart.request.method == 'POST':
json_data = await quart.request.json
model_uuid = await self.ap.embedding_models_service.create_embedding_model(json_data)
return self.success(data={'uuid': model_uuid})
@self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)

View File

@@ -1,45 +0,0 @@
import quart
from ... import group
@group.group_class('models/providers', '/api/v1/provider/providers')
class ModelProvidersRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _() -> str:
if quart.request.method == 'GET':
providers = await self.ap.provider_service.get_providers()
# Add model counts
for provider in providers:
counts = await self.ap.provider_service.get_provider_model_counts(provider['uuid'])
provider['llm_count'] = counts['llm_count']
provider['embedding_count'] = counts['embedding_count']
return self.success(data={'providers': providers})
elif quart.request.method == 'POST':
json_data = await quart.request.json
provider_uuid = await self.ap.provider_service.create_provider(json_data)
return self.success(data={'uuid': provider_uuid})
@self.route(
'/<provider_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
)
async def _(provider_uuid: str) -> str:
if quart.request.method == 'GET':
provider = await self.ap.provider_service.get_provider(provider_uuid)
if provider is None:
return self.http_status(404, -1, 'provider not found')
counts = await self.ap.provider_service.get_provider_model_counts(provider_uuid)
provider['llm_count'] = counts['llm_count']
provider['embedding_count'] = counts['embedding_count']
return self.success(data={'provider': provider})
elif quart.request.method == 'PUT':
json_data = await quart.request.json
await self.ap.provider_service.update_provider(provider_uuid, json_data)
return self.success()
elif quart.request.method == 'DELETE':
try:
await self.ap.provider_service.delete_provider(provider_uuid)
return self.success()
except ValueError as e:
return self.http_status(400, -1, str(e))

View File

@@ -1,47 +0,0 @@
import quart
from .. import group
@group.group_class('survey', '/api/v1/survey')
class SurveyRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/pending', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _get_pending() -> str:
"""Get pending survey for the frontend to display."""
survey = self.ap.survey.get_pending_survey() if self.ap.survey else None
return self.success(data={'survey': survey})
@self.route('/respond', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _respond() -> str:
"""Submit survey response."""
json_data = await quart.request.json
survey_id = json_data.get('survey_id')
answers = json_data.get('answers', {})
completed = json_data.get('completed', True)
if not survey_id:
return self.fail(1, 'survey_id required')
if self.ap.survey:
ok = await self.ap.survey.submit_response(survey_id, answers, completed)
if ok:
return self.success()
return self.fail(2, 'Failed to submit response')
return self.fail(3, 'Survey not available')
@self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _dismiss() -> str:
"""Dismiss survey."""
json_data = await quart.request.json
survey_id = json_data.get('survey_id')
if not survey_id:
return self.fail(1, 'survey_id required')
if self.ap.survey:
ok = await self.ap.survey.dismiss_survey(survey_id)
if ok:
return self.success()
return self.fail(2, 'Failed to dismiss')
return self.fail(3, 'Survey not available')

View File

@@ -13,20 +13,16 @@ class SystemRouterGroup(group.RouterGroup):
data={
'version': constants.semantic_version,
'debug': constants.debug_mode,
'edition': constants.edition,
'enable_marketplace': self.ap.instance_config.data.get('plugin', {}).get(
'enable_marketplace', True
),
'cloud_service_url': (
self.ap.instance_config.data.get('space', {}).get('url', 'https://space.langbot.app')
self.ap.instance_config.data.get('plugin', {}).get(
'cloud_service_url', 'https://space.langbot.app'
)
if 'cloud_service_url' in self.ap.instance_config.data.get('plugin', {})
else 'https://space.langbot.app'
),
'allow_modify_login_info': self.ap.instance_config.data.get('system', {}).get(
'allow_modify_login_info', True
),
'disable_models_service': self.ap.instance_config.data.get('space', {}).get(
'disable_models_service', False
),
'limitation': self.ap.instance_config.data.get('system', {}).get('limitation', {}),
}
)
@@ -59,6 +55,17 @@ class SystemRouterGroup(group.RouterGroup):
return self.success(data=exec(py_code, {'ap': ap}))
@self.route('/debug/tools/call', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
if not constants.debug_mode:
return self.http_status(403, 403, 'Forbidden')
data = await quart.request.json
return self.success(
data=await self.ap.tool_mgr.execute_func_call(data['tool_name'], data['tool_parameters'])
)
@self.route(
'/debug/plugin/action',
methods=['POST'],

View File

@@ -1,10 +1,8 @@
import quart
import argon2
import asyncio
import traceback
from .. import group
from .....entity.errors import account as account_errors
@group.group_class('user', '/api/v1/user')
@@ -35,8 +33,6 @@ class UserRouterGroup(group.RouterGroup):
token = await self.ap.user_service.authenticate(json_data['user'], json_data['password'])
except argon2.exceptions.VerifyMismatchError:
return self.fail(1, 'Invalid username or password')
except ValueError as e:
return self.fail(1, str(e))
return self.success(data={'token': token})
@@ -74,13 +70,6 @@ class UserRouterGroup(group.RouterGroup):
@self.route('/change-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _(user_email: str) -> str:
# Check if password change is allowed
allow_modify_login_info = self.ap.instance_config.data.get('system', {}).get(
'allow_modify_login_info', True
)
if not allow_modify_login_info:
return self.http_status(403, -1, 'Modifying login info is disabled')
json_data = await quart.request.json
current_password = json_data['current_password']
@@ -94,169 +83,3 @@ class UserRouterGroup(group.RouterGroup):
return self.http_status(400, -1, str(e))
return self.success(data={'user': user_email})
# Space OAuth endpoints (redirect flow)
@self.route('/space/authorize-url', methods=['GET'], auth_type=group.AuthType.NONE)
async def _() -> str:
"""Get Space OAuth authorization URL for redirect"""
redirect_uri = quart.request.args.get('redirect_uri', '')
state = quart.request.args.get('state', '')
if not redirect_uri:
return self.fail(1, 'Missing redirect_uri parameter')
try:
authorize_url = self.ap.space_service.get_oauth_authorize_url(redirect_uri, state)
return self.success(data={'authorize_url': authorize_url})
except Exception as e:
return self.fail(1, str(e))
@self.route('/space/callback', methods=['POST'], auth_type=group.AuthType.NONE)
async def _() -> str:
"""Handle OAuth callback - exchange code for tokens and authenticate"""
json_data = await quart.request.json
code = json_data.get('code')
if not code:
return self.fail(1, 'Missing authorization code')
try:
# Exchange code for tokens
token_data = await self.ap.space_service.exchange_oauth_code(code)
access_token = token_data.get('access_token')
refresh_token = token_data.get('refresh_token')
expires_in = token_data.get('expires_in', 0)
if not access_token:
return self.fail(1, 'Failed to get access token from Space')
# Authenticate and create/update local user
jwt_token, user_obj = await self.ap.user_service.authenticate_space_user(
access_token, refresh_token, expires_in
)
return self.success(
data={
'token': jwt_token,
'user': user_obj.user,
}
)
except account_errors.AccountEmailMismatchError as e:
return self.fail(3, str(e))
except ValueError as e:
traceback.print_exc()
return self.fail(1, str(e))
except Exception as e:
traceback.print_exc()
return self.fail(2, f'OAuth callback failed: {str(e)}')
@self.route('/info', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _(user_email: str) -> str:
"""Get current user information including account type"""
user_obj = await self.ap.user_service.get_user_by_email(user_email)
if user_obj is None:
return self.http_status(404, -1, 'User not found')
return self.success(
data={
'user': user_obj.user,
'account_type': user_obj.account_type,
'has_password': bool(user_obj.password and user_obj.password.strip()),
}
)
@self.route('/space-credits', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _(user_email: str) -> str:
"""Get Space credits balance for current user"""
credits = await self.ap.space_service.get_credits(user_email)
return self.success(data={'credits': credits})
@self.route('/account-info', methods=['GET'], auth_type=group.AuthType.NONE)
async def _() -> str:
"""Get account info for login page (account type and has_password)"""
if not await self.ap.user_service.is_initialized():
return self.success(data={'initialized': False})
user_obj = await self.ap.user_service.get_first_user()
if user_obj is None:
return self.success(data={'initialized': False})
return self.success(
data={
'initialized': True,
'account_type': user_obj.account_type,
'has_password': bool(user_obj.password and user_obj.password.strip()),
}
)
@self.route('/set-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _(user_email: str) -> str:
"""Set password for Space account (first time) or change password"""
json_data = await quart.request.json
new_password = json_data.get('new_password')
current_password = json_data.get('current_password')
if not new_password:
return self.http_status(400, -1, 'New password is required')
user_obj = await self.ap.user_service.get_user_by_email(user_email)
if user_obj is None:
return self.http_status(404, -1, 'User not found')
try:
await self.ap.user_service.set_password(user_email, new_password, current_password)
return self.success(data={'user': user_email})
except ValueError as e:
return self.http_status(400, -1, str(e))
except argon2.exceptions.VerifyMismatchError:
return self.http_status(400, -1, 'Current password is incorrect')
@self.route('/bind-space', methods=['POST'], auth_type=group.AuthType.NONE)
async def _() -> str:
"""Bind Space account to existing local account"""
# Check if modifying login info is allowed
allow_modify_login_info = self.ap.instance_config.data.get('system', {}).get(
'allow_modify_login_info', True
)
if not allow_modify_login_info:
return self.http_status(403, -1, 'Modifying login info is disabled')
json_data = await quart.request.json
code = json_data.get('code')
state = json_data.get('state') # JWT token passed as state
if not code:
return self.http_status(400, -1, 'Missing authorization code')
if not state:
return self.http_status(400, -1, 'Missing state parameter')
# Verify state is a valid JWT token
try:
user_email = await self.ap.user_service.verify_jwt_token(state)
except Exception:
return self.http_status(401, -1, 'Invalid or expired state')
user_obj = await self.ap.user_service.get_user_by_email(user_email)
if user_obj is None:
return self.http_status(404, -1, 'User not found')
if user_obj.account_type != 'local':
return self.http_status(400, -1, 'Only local accounts can bind to Space')
try:
updated_user = await self.ap.user_service.bind_space_account(user_email, code)
jwt_token = await self.ap.user_service.generate_jwt_token(updated_user.user)
return self.success(
data={
'token': jwt_token,
'user': updated_user.user,
'account_type': updated_user.account_type,
}
)
except ValueError as e:
return self.http_status(400, -1, str(e))
except Exception as e:
return self.http_status(500, -1, f'Failed to bind Space account: {str(e)}')

View File

@@ -1,49 +0,0 @@
import quart
from .. import group
@group.group_class('webhook_mgmt', '/api/v1/webhooks')
class WebhookManagementRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['GET', 'POST'])
async def _() -> str:
if quart.request.method == 'GET':
webhooks = await self.ap.webhook_service.get_webhooks()
return self.success(data={'webhooks': webhooks})
elif quart.request.method == 'POST':
json_data = await quart.request.json
name = json_data.get('name', '')
url = json_data.get('url', '')
description = json_data.get('description', '')
enabled = json_data.get('enabled', True)
if not name:
return self.http_status(400, -1, 'Name is required')
if not url:
return self.http_status(400, -1, 'URL is required')
webhook = await self.ap.webhook_service.create_webhook(name, url, description, enabled)
return self.success(data={'webhook': webhook})
@self.route('/<int:webhook_id>', methods=['GET', 'PUT', 'DELETE'])
async def _(webhook_id: int) -> str:
if quart.request.method == 'GET':
webhook = await self.ap.webhook_service.get_webhook(webhook_id)
if webhook is None:
return self.http_status(404, -1, 'Webhook not found')
return self.success(data={'webhook': webhook})
elif quart.request.method == 'PUT':
json_data = await quart.request.json
name = json_data.get('name')
url = json_data.get('url')
description = json_data.get('description')
enabled = json_data.get('enabled')
await self.ap.webhook_service.update_webhook(webhook_id, name, url, description, enabled)
return self.success()
elif quart.request.method == 'DELETE':
await self.ap.webhook_service.delete_webhook(webhook_id)
return self.success()

View File

@@ -1,54 +1,49 @@
from __future__ import annotations
import quart
import traceback
from .. import group
@group.group_class('webhooks', '/bots')
class WebhookRouterGroup(group.RouterGroup):
@group.group_class('webhooks', '/api/v1/webhooks')
class WebhooksRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/<bot_uuid>', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
async def handle_webhook(bot_uuid: str):
"""处理 bot webhook 回调(无子路径)"""
return await self._dispatch_webhook(bot_uuid, '')
@self.route('', methods=['GET', 'POST'])
async def _() -> str:
if quart.request.method == 'GET':
webhooks = await self.ap.webhook_service.get_webhooks()
return self.success(data={'webhooks': webhooks})
elif quart.request.method == 'POST':
json_data = await quart.request.json
name = json_data.get('name', '')
url = json_data.get('url', '')
description = json_data.get('description', '')
enabled = json_data.get('enabled', True)
@self.route('/<bot_uuid>/<path:path>', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
async def handle_webhook_with_path(bot_uuid: str, path: str):
"""处理 bot webhook 回调(带子路径)"""
return await self._dispatch_webhook(bot_uuid, path)
if not name:
return self.http_status(400, -1, 'Name is required')
if not url:
return self.http_status(400, -1, 'URL is required')
async def _dispatch_webhook(self, bot_uuid: str, path: str):
"""分发 webhook 请求到对应的 bot adapter
webhook = await self.ap.webhook_service.create_webhook(name, url, description, enabled)
return self.success(data={'webhook': webhook})
Args:
bot_uuid: Bot 的 UUID
path: 子路径(如果有的话)
@self.route('/<int:webhook_id>', methods=['GET', 'PUT', 'DELETE'])
async def _(webhook_id: int) -> str:
if quart.request.method == 'GET':
webhook = await self.ap.webhook_service.get_webhook(webhook_id)
if webhook is None:
return self.http_status(404, -1, 'Webhook not found')
return self.success(data={'webhook': webhook})
Returns:
适配器返回的响应
"""
try:
runtime_bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
elif quart.request.method == 'PUT':
json_data = await quart.request.json
name = json_data.get('name')
url = json_data.get('url')
description = json_data.get('description')
enabled = json_data.get('enabled')
if not runtime_bot:
return quart.jsonify({'error': 'Bot not found'}), 404
await self.ap.webhook_service.update_webhook(webhook_id, name, url, description, enabled)
return self.success()
if not runtime_bot.enable:
return quart.jsonify({'error': 'Bot is disabled'}), 403
if not hasattr(runtime_bot.adapter, 'handle_unified_webhook'):
return quart.jsonify({'error': 'Adapter does not support unified webhook'}), 501
response = await runtime_bot.adapter.handle_unified_webhook(
bot_uuid=bot_uuid,
path=path,
request=quart.request,
)
return response
except Exception as e:
self.ap.logger.error(f'Webhook dispatch error for bot {bot_uuid}: {traceback.format_exc()}')
return quart.jsonify({'error': str(e)}), 500
elif quart.request.method == 'DELETE':
await self.ap.webhook_service.delete_webhook(webhook_id)
return self.success()

View File

@@ -92,11 +92,7 @@ class HTTPController:
@self.quart_app.route('/')
async def index():
response = await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
response.headers['Pragma'] = 'no-cache'
response.headers['Expires'] = '0'
return response
return await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
@self.quart_app.route('/<path:path>')
async def static_file(path: str):

View File

@@ -58,39 +58,12 @@ class BotService:
if runtime_bot is not None:
adapter_runtime_values['bot_account_id'] = runtime_bot.adapter.bot_account_id
# Webhook URL for unified webhook adapters (independent of bot running state)
if persistence_bot['adapter'] in [
'wecom',
'wecombot',
'officialaccount',
'qqofficial',
'slack',
'wecomcs',
'LINE',
'lark',
]:
webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
webhook_url = f'/bots/{bot_uuid}'
adapter_runtime_values['webhook_url'] = webhook_url
adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
else:
adapter_runtime_values['webhook_url'] = None
adapter_runtime_values['webhook_full_url'] = None
persistence_bot['adapter_runtime_values'] = adapter_runtime_values
return persistence_bot
async def create_bot(self, bot_data: dict) -> str:
"""Create bot"""
# Check limitation
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
max_bots = limitation.get('max_bots', -1)
if max_bots >= 0:
existing_bots = await self.get_bots()
if len(existing_bots) >= max_bots:
raise ValueError(f'Maximum number of bots ({max_bots}) reached')
# TODO: 检查配置信息格式
bot_data['uuid'] = str(uuid.uuid4())
@@ -166,29 +139,3 @@ class BotService:
logs, total_count = await runtime_bot.logger.get_logs(from_index, max_count)
return [log.to_json() for log in logs], total_count
async def send_message(self, bot_uuid: str, target_type: str, target_id: str, message_chain_data: dict) -> None:
"""Send message to a specific target via bot
Args:
bot_uuid: The UUID of the bot
target_type: The type of the target, can be "group", "person"
target_id: The ID of the target
message_chain_data: The message chain data in dict format
"""
# Import here to avoid circular imports
import langbot_plugin.api.entities.builtin.platform.message as platform_message
# Get runtime bot
runtime_bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
if runtime_bot is None:
raise Exception(f'Bot not found: {bot_uuid}')
# Validate and convert message chain
try:
message_chain = platform_message.MessageChain.model_validate(message_chain_data)
except Exception as e:
raise Exception(f'Invalid message_chain format: {str(e)}')
# Send message via adapter
await runtime_bot.adapter.send_message(target_type, str(target_id), message_chain)

View File

@@ -1,80 +0,0 @@
from __future__ import annotations
from ....core import app
import sqlalchemy
from langbot.pkg.entity.persistence import rag as persistence_rag
import uuid
class ExternalKBService:
"""External KB service"""
ap: app.Application
def __init__(self, ap: app.Application) -> None:
self.ap = ap
# External Knowledge Base methods
async def get_external_knowledge_bases(self) -> list[dict]:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.ExternalKnowledgeBase))
external_kbs = result.all()
return [
self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
for external_kb in external_kbs
]
async def get_external_knowledge_base(self, kb_uuid: str) -> dict | None:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_rag.ExternalKnowledgeBase).where(
persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
)
)
external_kb = result.first()
if external_kb is None:
return None
return self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
async def create_external_knowledge_base(self, kb_data: dict) -> str:
kb_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_rag.ExternalKnowledgeBase).values(kb_data)
)
kb = await self.get_external_knowledge_base(kb_data['uuid'])
await self.ap.rag_mgr.load_external_knowledge_base(kb)
return kb_data['uuid']
async def retrieve_external_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
"""Retrieve external knowledge base"""
runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
if runtime_kb is None:
raise Exception('Knowledge base not found')
return [
result.model_dump() for result in await runtime_kb.retrieve(query, 5)
] # top_k is just a placeholder for external knowledge base
async def update_external_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
if 'uuid' in kb_data:
del kb_data['uuid']
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_rag.ExternalKnowledgeBase)
.values(kb_data)
.where(persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid)
)
await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
kb = await self.get_external_knowledge_base(kb_uuid)
await self.ap.rag_mgr.load_external_knowledge_base(kb)
async def delete_external_knowledge_base(self, kb_uuid: str) -> None:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_rag.ExternalKnowledgeBase).where(
persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
)
)
await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)

View File

@@ -71,19 +71,7 @@ class KnowledgeService:
runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
if runtime_kb is None:
raise Exception('Knowledge base not found')
# Only internal KBs support file storage
if runtime_kb.get_type() != 'internal':
raise Exception('Only internal knowledge bases support file storage')
result = await runtime_kb.store_file(file_id)
# Update the KB's updated_at timestamp
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_rag.KnowledgeBase)
.values(updated_at=sqlalchemy.func.now())
.where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
)
return result
return await runtime_kb.store_file(file_id)
async def retrieve_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
"""检索知识库"""
@@ -107,18 +95,8 @@ class KnowledgeService:
runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
if runtime_kb is None:
raise Exception('Knowledge base not found')
# Only internal KBs support file deletion
if runtime_kb.get_type() != 'internal':
raise Exception('Only internal knowledge bases support file deletion')
await runtime_kb.delete_file(file_id)
# Update the KB's updated_at timestamp
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_rag.KnowledgeBase)
.values(updated_at=sqlalchemy.func.now())
.where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
)
async def delete_knowledge_base(self, kb_uuid: str) -> None:
"""删除知识库"""
await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)

View File

@@ -38,16 +38,6 @@ class MCPService:
return serialized_servers
async def create_mcp_server(self, server_data: dict) -> str:
# Check limitation (extensions = MCP servers + plugins)
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
max_extensions = limitation.get('max_extensions', -1)
if max_extensions >= 0:
existing_mcp_servers = await self.get_mcp_servers()
plugins = await self.ap.plugin_connector.list_plugins()
total_extensions = len(existing_mcp_servers) + len(plugins)
if total_extensions >= max_extensions:
raise ValueError(f'Maximum number of extensions ({max_extensions}) reached')
server_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_mcp.MCPServer).values(server_data))

View File

@@ -11,18 +11,6 @@ from ....entity.persistence import pipeline as persistence_pipeline
from ....provider.modelmgr import requester as model_requester
def _parse_provider_api_keys(provider_dict: dict) -> dict:
"""Parse api_keys if it's a JSON string"""
if isinstance(provider_dict.get('api_keys'), str):
import json
try:
provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
except Exception:
provider_dict['api_keys'] = []
return provider_dict
class LLMModelsService:
ap: app.Application
@@ -30,131 +18,59 @@ class LLMModelsService:
self.ap = ap
async def get_llm_models(self, include_secret: bool = True) -> list[dict]:
"""Get all LLM models with provider info"""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
models = result.all()
# Get all providers for lookup
providers_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider)
)
providers = {p.uuid: p for p in providers_result.all()}
masked_columns = []
if not include_secret:
masked_columns = ['api_keys']
models_list = []
for model in models:
model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
provider = providers.get(model.provider_uuid)
if provider:
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
provider_dict = _parse_provider_api_keys(provider_dict)
if not include_secret:
provider_dict['api_keys'] = ['***'] * len(provider_dict.get('api_keys', []))
model_dict['provider'] = provider_dict
models_list.append(model_dict)
return [
self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model, masked_columns)
for model in models
]
return models_list
async def get_llm_models_by_provider(self, provider_uuid: str) -> list[dict]:
"""Get LLM models by provider UUID"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.LLMModel).where(
persistence_model.LLMModel.provider_uuid == provider_uuid
)
)
models = result.all()
return [self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, m) for m in models]
async def create_llm_model(
self, model_data: dict, preserve_uuid: bool = False, auto_set_to_default_pipeline: bool = True
) -> str:
"""Create a new LLM model"""
if not preserve_uuid:
model_data['uuid'] = str(uuid.uuid4())
# Handle provider creation if needed
if 'provider' in model_data:
provider_data = model_data.pop('provider')
if provider_data.get('uuid'):
model_data['provider_uuid'] = provider_data['uuid']
else:
# Create new provider
provider_uuid = await self.ap.provider_service.find_or_create_provider(
requester=provider_data.get('requester', ''),
base_url=provider_data.get('base_url', ''),
api_keys=provider_data.get('api_keys', []),
)
model_data['provider_uuid'] = provider_uuid
async def create_llm_model(self, model_data: dict) -> str:
model_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_model.LLMModel).values(**model_data))
runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
if runtime_provider is None:
raise Exception('provider not found')
llm_model = await self.get_llm_model(model_data['uuid'])
runtime_llm_model = await self.ap.model_mgr.load_llm_model_with_provider(
persistence_model.LLMModel(**model_data),
runtime_provider,
)
self.ap.model_mgr.llm_models.append(runtime_llm_model)
await self.ap.model_mgr.load_llm_model(llm_model)
if auto_set_to_default_pipeline:
# set the default pipeline model to this model
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
persistence_pipeline.LegacyPipeline.is_default == True
)
# check if default pipeline has no model bound
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
persistence_pipeline.LegacyPipeline.is_default == True
)
pipeline = result.first()
if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
pipeline_config = pipeline.config
pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
pipeline_data = {'config': pipeline_config}
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
)
pipeline = result.first()
if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
pipeline_config = pipeline.config
pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
pipeline_data = {'config': pipeline_config}
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
return model_data['uuid']
async def get_llm_model(self, model_uuid: str) -> dict | None:
"""Get a single LLM model with provider info"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
)
model = result.first()
if model is None:
return None
model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
# Get provider
provider_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.uuid == model.provider_uuid
)
)
provider = provider_result.first()
if provider:
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
model_dict['provider'] = _parse_provider_api_keys(provider_dict)
return model_dict
return self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
async def update_llm_model(self, model_uuid: str, model_data: dict) -> None:
"""Update an existing LLM model"""
if 'uuid' in model_data:
del model_data['uuid']
# Handle provider update if needed
if 'provider' in model_data:
provider_data = model_data.pop('provider')
if provider_data.get('uuid'):
model_data['provider_uuid'] = provider_data['uuid']
else:
provider_uuid = await self.ap.provider_service.find_or_create_provider(
requester=provider_data.get('requester', ''),
base_url=provider_data.get('base_url', ''),
api_keys=provider_data.get('api_keys', []),
)
model_data['provider_uuid'] = provider_uuid
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_model.LLMModel)
.where(persistence_model.LLMModel.uuid == model_uuid)
@@ -163,25 +79,18 @@ class LLMModelsService:
await self.ap.model_mgr.remove_llm_model(model_uuid)
runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
if runtime_provider is None:
raise Exception('provider not found')
llm_model = await self.get_llm_model(model_uuid)
runtime_llm_model = await self.ap.model_mgr.load_llm_model_with_provider(
persistence_model.LLMModel(**model_data),
runtime_provider,
)
self.ap.model_mgr.llm_models.append(runtime_llm_model)
await self.ap.model_mgr.load_llm_model(llm_model)
async def delete_llm_model(self, model_uuid: str) -> None:
"""Delete an LLM model"""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
)
await self.ap.model_mgr.remove_llm_model(model_uuid)
async def test_llm_model(self, model_uuid: str, model_data: dict) -> None:
"""Test an LLM model"""
runtime_llm_model: model_requester.RuntimeLLMModel | None = None
if model_uuid != '_':
@@ -189,18 +98,25 @@ class LLMModelsService:
if model.model_entity.uuid == model_uuid:
runtime_llm_model = model
break
if runtime_llm_model is None:
raise Exception('model not found')
else:
runtime_llm_model = await self.ap.model_mgr.init_temporary_runtime_llm_model(model_data)
extra_args = model_data.get('extra_args', {})
await runtime_llm_model.provider.invoke_llm(
else:
runtime_llm_model = await self.ap.model_mgr.init_runtime_llm_model(model_data)
# Mon Nov 10 2025: Commented for some providers may not support thinking parameter
# # 有些模型厂商默认开启了思考功能,测试容易延迟
# extra_args = model_data.get('extra_args', {})
# if not extra_args or 'thinking' not in extra_args:
# extra_args['thinking'] = {'type': 'disabled'}
await runtime_llm_model.requester.invoke_llm(
query=None,
model=runtime_llm_model,
messages=[provider_message.Message(role='user', content='Hello, world! Please just reply a "Hello".')],
funcs=[],
extra_args=extra_args,
# extra_args=extra_args,
)
@@ -211,111 +127,42 @@ class EmbeddingModelsService:
self.ap = ap
async def get_embedding_models(self) -> list[dict]:
"""Get all embedding models with provider info"""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel))
models = result.all()
return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model) for model in models]
providers_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider)
)
providers = {p.uuid: p for p in providers_result.all()}
models_list = []
for model in models:
model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
provider = providers.get(model.provider_uuid)
if provider:
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
model_dict['provider'] = _parse_provider_api_keys(provider_dict)
models_list.append(model_dict)
return models_list
async def get_embedding_models_by_provider(self, provider_uuid: str) -> list[dict]:
"""Get embedding models by provider UUID"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.EmbeddingModel).where(
persistence_model.EmbeddingModel.provider_uuid == provider_uuid
)
)
models = result.all()
return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, m) for m in models]
async def create_embedding_model(self, model_data: dict, preserve_uuid: bool = False) -> str:
"""Create a new embedding model"""
if not preserve_uuid:
model_data['uuid'] = str(uuid.uuid4())
if 'provider' in model_data:
provider_data = model_data.pop('provider')
if provider_data.get('uuid'):
model_data['provider_uuid'] = provider_data['uuid']
else:
provider_uuid = await self.ap.provider_service.find_or_create_provider(
requester=provider_data.get('requester', ''),
base_url=provider_data.get('base_url', ''),
api_keys=provider_data.get('api_keys', []),
)
model_data['provider_uuid'] = provider_uuid
async def create_embedding_model(self, model_data: dict) -> str:
model_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_model.EmbeddingModel).values(**model_data)
)
runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
if runtime_provider is None:
raise Exception('provider not found')
embedding_model = await self.get_embedding_model(model_data['uuid'])
runtime_embedding_model = await self.ap.model_mgr.load_embedding_model_with_provider(
persistence_model.EmbeddingModel(**model_data),
runtime_provider,
)
self.ap.model_mgr.embedding_models.append(runtime_embedding_model)
await self.ap.model_mgr.load_embedding_model(embedding_model)
return model_data['uuid']
async def get_embedding_model(self, model_uuid: str) -> dict | None:
"""Get a single embedding model with provider info"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.EmbeddingModel).where(
persistence_model.EmbeddingModel.uuid == model_uuid
)
)
model = result.first()
if model is None:
return None
model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
provider_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.uuid == model.provider_uuid
)
)
provider = provider_result.first()
if provider:
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
model_dict['provider'] = _parse_provider_api_keys(provider_dict)
return model_dict
return self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
async def update_embedding_model(self, model_uuid: str, model_data: dict) -> None:
"""Update an existing embedding model"""
if 'uuid' in model_data:
del model_data['uuid']
if 'provider' in model_data:
provider_data = model_data.pop('provider')
if provider_data.get('uuid'):
model_data['provider_uuid'] = provider_data['uuid']
else:
provider_uuid = await self.ap.provider_service.find_or_create_provider(
requester=provider_data.get('requester', ''),
base_url=provider_data.get('base_url', ''),
api_keys=provider_data.get('api_keys', []),
)
model_data['provider_uuid'] = provider_uuid
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_model.EmbeddingModel)
.where(persistence_model.EmbeddingModel.uuid == model_uuid)
@@ -324,27 +171,20 @@ class EmbeddingModelsService:
await self.ap.model_mgr.remove_embedding_model(model_uuid)
runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
if runtime_provider is None:
raise Exception('provider not found')
embedding_model = await self.get_embedding_model(model_uuid)
runtime_embedding_model = await self.ap.model_mgr.load_embedding_model_with_provider(
persistence_model.EmbeddingModel(**model_data),
runtime_provider,
)
self.ap.model_mgr.embedding_models.append(runtime_embedding_model)
await self.ap.model_mgr.load_embedding_model(embedding_model)
async def delete_embedding_model(self, model_uuid: str) -> None:
"""Delete an embedding model"""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_model.EmbeddingModel).where(
persistence_model.EmbeddingModel.uuid == model_uuid
)
)
await self.ap.model_mgr.remove_embedding_model(model_uuid)
async def test_embedding_model(self, model_uuid: str, model_data: dict) -> None:
"""Test an embedding model"""
runtime_embedding_model: model_requester.RuntimeEmbeddingModel | None = None
if model_uuid != '_':
@@ -352,12 +192,14 @@ class EmbeddingModelsService:
if model.model_entity.uuid == model_uuid:
runtime_embedding_model = model
break
if runtime_embedding_model is None:
raise Exception('model not found')
else:
runtime_embedding_model = await self.ap.model_mgr.init_temporary_runtime_embedding_model(model_data)
await runtime_embedding_model.provider.invoke_embedding(
else:
runtime_embedding_model = await self.ap.model_mgr.init_runtime_embedding_model(model_data)
await runtime_embedding_model.requester.invoke_embedding(
model=runtime_embedding_model,
input_text=['Hello, world!'],
extra_args={},

File diff suppressed because it is too large Load Diff

View File

@@ -76,14 +76,6 @@ class PipelineService:
async def create_pipeline(self, pipeline_data: dict, default: bool = False) -> str:
from ....utils import paths as path_utils
# Check limitation
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
max_pipelines = limitation.get('max_pipelines', -1)
if max_pipelines >= 0:
existing_pipelines = await self.get_pipelines()
if len(existing_pipelines) >= max_pipelines:
raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
pipeline_data['uuid'] = str(uuid.uuid4())
pipeline_data['for_version'] = self.ap.ver_mgr.get_current_version()
pipeline_data['stages'] = default_stage_order.copy()
@@ -93,15 +85,6 @@ class PipelineService:
with open(template_path, 'r', encoding='utf-8') as f:
pipeline_data['config'] = json.load(f)
# Ensure extensions_preferences is set with enable_all_plugins and enable_all_mcp_servers=True by default
if 'extensions_preferences' not in pipeline_data:
pipeline_data['extensions_preferences'] = {
'enable_all_plugins': True,
'enable_all_mcp_servers': True,
'plugins': [],
'mcp_servers': [],
}
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_pipeline.LegacyPipeline).values(**pipeline_data)
)
@@ -159,67 +142,8 @@ class PipelineService:
)
await self.ap.pipeline_mgr.remove_pipeline(pipeline_uuid)
async def copy_pipeline(self, pipeline_uuid: str) -> str:
"""Copy a pipeline with all its configurations"""
# Check limitation
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
max_pipelines = limitation.get('max_pipelines', -1)
if max_pipelines >= 0:
existing_pipelines = await self.get_pipelines()
if len(existing_pipelines) >= max_pipelines:
raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
# Get the original pipeline
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid
)
)
original_pipeline = result.first()
if original_pipeline is None:
raise ValueError(f'Pipeline {pipeline_uuid} not found')
# Create new pipeline data
new_uuid = str(uuid.uuid4())
new_pipeline_data = {
'uuid': new_uuid,
'name': f'{original_pipeline.name} (Copy)',
'description': original_pipeline.description,
'for_version': self.ap.ver_mgr.get_current_version(),
'stages': original_pipeline.stages.copy() if original_pipeline.stages else default_stage_order.copy(),
'config': original_pipeline.config.copy() if original_pipeline.config else {},
'is_default': False,
'extensions_preferences': (
original_pipeline.extensions_preferences.copy()
if original_pipeline.extensions_preferences
else {
'enable_all_plugins': True,
'enable_all_mcp_servers': True,
'plugins': [],
'mcp_servers': [],
}
),
}
# Insert the new pipeline
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_pipeline.LegacyPipeline).values(**new_pipeline_data)
)
# Load the new pipeline
pipeline = await self.get_pipeline(new_uuid)
await self.ap.pipeline_mgr.load_pipeline(pipeline)
return new_uuid
async def update_pipeline_extensions(
self,
pipeline_uuid: str,
bound_plugins: list[dict],
bound_mcp_servers: list[str] = None,
enable_all_plugins: bool = True,
enable_all_mcp_servers: bool = True,
self, pipeline_uuid: str, bound_plugins: list[dict], bound_mcp_servers: list[str] = None
) -> None:
"""Update the bound plugins and MCP servers for a pipeline"""
# Get current pipeline
@@ -235,8 +159,6 @@ class PipelineService:
# Update extensions_preferences
extensions_preferences = pipeline.extensions_preferences or {}
extensions_preferences['enable_all_plugins'] = enable_all_plugins
extensions_preferences['enable_all_mcp_servers'] = enable_all_mcp_servers
extensions_preferences['plugins'] = bound_plugins
if bound_mcp_servers is not None:
extensions_preferences['mcp_servers'] = bound_mcp_servers

View File

@@ -1,166 +0,0 @@
from __future__ import annotations
import uuid
import sqlalchemy
from ....core import app
from ....entity.persistence import model as persistence_model
class ModelProviderService:
"""Service for managing model providers"""
ap: app.Application
def __init__(self, ap: app.Application) -> None:
self.ap = ap
async def get_providers(self) -> list[dict]:
"""Get all providers"""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.ModelProvider))
providers = result.all()
providers_list = []
for p in providers:
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, p)
# Parse api_keys if it's a JSON string
if isinstance(provider_dict.get('api_keys'), str):
import json
try:
provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
except Exception:
provider_dict['api_keys'] = []
providers_list.append(provider_dict)
return providers_list
async def get_provider(self, provider_uuid: str) -> dict | None:
"""Get a single provider by UUID"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.uuid == provider_uuid
)
)
provider = result.first()
if provider is None:
return None
provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
# Parse api_keys if it's a JSON string
if isinstance(provider_dict.get('api_keys'), str):
import json
try:
provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
except Exception:
provider_dict['api_keys'] = []
return provider_dict
async def create_provider(self, provider_data: dict) -> str:
"""Create a new provider"""
provider_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_model.ModelProvider).values(**provider_data)
)
# load to runtime
runtime_provider = await self.ap.model_mgr.load_provider(provider_data)
self.ap.model_mgr.provider_dict[runtime_provider.provider_entity.uuid] = runtime_provider
return provider_data['uuid']
async def update_provider(self, provider_uuid: str, provider_data: dict) -> None:
"""Update an existing provider"""
if 'uuid' in provider_data:
del provider_data['uuid']
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_model.ModelProvider)
.where(persistence_model.ModelProvider.uuid == provider_uuid)
.values(**provider_data)
)
await self.ap.model_mgr.reload_provider(provider_uuid)
async def delete_provider(self, provider_uuid: str) -> None:
"""Delete a provider (only if no models reference it)"""
# Check if any models use this provider
llm_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.LLMModel).where(
persistence_model.LLMModel.provider_uuid == provider_uuid
)
)
if llm_result.first() is not None:
raise ValueError('Cannot delete provider: LLM models still reference it')
embedding_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.EmbeddingModel).where(
persistence_model.EmbeddingModel.provider_uuid == provider_uuid
)
)
if embedding_result.first() is not None:
raise ValueError('Cannot delete provider: Embedding models still reference it')
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.uuid == provider_uuid
)
)
await self.ap.model_mgr.remove_provider(provider_uuid)
async def get_provider_model_counts(self, provider_uuid: str) -> dict:
"""Get count of models using this provider"""
llm_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(sqlalchemy.func.count())
.select_from(persistence_model.LLMModel)
.where(persistence_model.LLMModel.provider_uuid == provider_uuid)
)
llm_count = llm_result.scalar() or 0
embedding_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(sqlalchemy.func.count())
.select_from(persistence_model.EmbeddingModel)
.where(persistence_model.EmbeddingModel.provider_uuid == provider_uuid)
)
embedding_count = embedding_result.scalar() or 0
return {'llm_count': llm_count, 'embedding_count': embedding_count}
async def find_or_create_provider(self, requester: str, base_url: str, api_keys: list) -> str:
"""Find existing provider or create new one"""
# Try to find existing provider with same config
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.requester == requester,
persistence_model.ModelProvider.base_url == base_url,
)
)
for provider in result.all():
if sorted(provider.api_keys or []) == sorted(api_keys or []):
return provider.uuid
# Create new provider
provider_name = requester
if base_url:
try:
from urllib.parse import urlparse
parsed = urlparse(base_url)
provider_name = parsed.netloc or requester
except Exception:
pass
return await self.create_provider(
{
'name': provider_name,
'requester': requester,
'base_url': base_url,
'api_keys': api_keys or [],
}
)
async def update_space_model_provider_api_keys(self, api_key: str) -> None:
"""Update Space model provider API keys"""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_model.ModelProvider)
.where(persistence_model.ModelProvider.uuid == '00000000-0000-0000-0000-000000000000')
.values(api_keys=[api_key])
)
await self.ap.model_mgr.reload_provider('00000000-0000-0000-0000-000000000000')

View File

@@ -1,189 +0,0 @@
from __future__ import annotations
import aiohttp
import typing
import datetime
import time
import sqlalchemy
from ....core import app
from ....entity.persistence import user
from ....entity.dto.space_model import SpaceModel
class SpaceService:
"""Service for interacting with LangBot Space API"""
ap: app.Application
_credits_cache: typing.Dict[str, typing.Tuple[int, float]] # {user_email: (credits, timestamp)}
def __init__(self, ap: app.Application) -> None:
self.ap = ap
self._credits_cache = {}
def _get_space_config(self) -> typing.Dict[str, str]:
"""Get Space configuration from config file"""
space_config = self.ap.instance_config.data.get('space', {})
return {
'url': space_config.get('url', 'https://space.langbot.app'),
'oauth_authorize_url': space_config.get('oauth_authorize_url', 'https://space.langbot.app/auth/authorize'),
}
async def _get_user_by_email(self, user_email: str) -> user.User | None:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(user.User).where(user.User.user == user_email)
)
result_list = result.all()
return result_list[0] if result_list else None
async def _ensure_valid_token(self, user_email: str) -> str | None:
"""Ensure access token is valid, refresh if expired. Returns valid access_token or None."""
user_obj = await self._get_user_by_email(user_email)
if not user_obj or user_obj.account_type != 'space':
return None
if not user_obj.space_access_token:
return None
# Check if token is expired (with 60s buffer)
if user_obj.space_access_token_expires_at:
if datetime.datetime.now() >= user_obj.space_access_token_expires_at - datetime.timedelta(seconds=60):
# Token expired, try to refresh
if user_obj.space_refresh_token:
try:
new_token = await self._refresh_and_save_token(user_obj)
return new_token
except Exception:
return None
return None
return user_obj.space_access_token
async def _refresh_and_save_token(self, user_obj: user.User) -> str:
"""Refresh token and save to database"""
token_data = await self.refresh_token(user_obj.space_refresh_token)
access_token = token_data.get('access_token')
expires_in = token_data.get('expires_in', 0)
if not access_token:
raise ValueError('Failed to refresh token')
expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User)
.where(user.User.user == user_obj.user)
.values(
space_access_token=access_token,
space_access_token_expires_at=expires_at,
)
)
return access_token
# === Raw API calls (no token validation) ===
def get_oauth_authorize_url(self, redirect_uri: str, state: str = '') -> str:
"""Get the Space OAuth authorization URL for redirect"""
space_config = self._get_space_config()
authorize_url = space_config['oauth_authorize_url']
params = f'redirect_uri={redirect_uri}'
if state:
params += f'&state={state}'
return f'{authorize_url}?{params}'
async def exchange_oauth_code(self, code: str) -> typing.Dict:
"""Exchange OAuth authorization code for tokens"""
from langbot.pkg.utils import constants
space_config = self._get_space_config()
space_url = space_config['url']
async with aiohttp.ClientSession() as session:
async with session.post(
f'{space_url}/api/v1/accounts/oauth/token',
json={'code': code, 'instance_id': constants.instance_id},
) as response:
if response.status != 200:
raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
data = await response.json()
if data.get('code') != 0:
raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
return data.get('data', {})
async def refresh_token(self, refresh_token: str) -> typing.Dict:
"""Refresh Space access token"""
space_config = self._get_space_config()
space_url = space_config['url']
async with aiohttp.ClientSession() as session:
async with session.post(
f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
) as response:
if response.status != 200:
raise ValueError(f'Failed to refresh token: {await response.text()}')
data = await response.json()
if data.get('code') != 0:
raise ValueError(f'Failed to refresh token: {data.get("msg")}')
return data.get('data', {})
async def get_user_info_raw(self, access_token: str) -> typing.Dict:
"""Get user info from Space using access token (no validation)"""
space_config = self._get_space_config()
space_url = space_config['url']
async with aiohttp.ClientSession() as session:
async with session.get(
f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
) as response:
if response.status != 200:
raise ValueError(f'Failed to get user info: {await response.text()}')
data = await response.json()
if data.get('code') != 0:
raise ValueError(f'Failed to get user info: {data.get("msg")}')
return data.get('data', {})
# === API calls with token validation ===
async def get_user_info(self, user_email: str) -> typing.Dict | None:
"""Get user info from Space (with token validation)"""
access_token = await self._ensure_valid_token(user_email)
if not access_token:
return None
return await self.get_user_info_raw(access_token)
async def get_credits(self, user_email: str, force_refresh: bool = False) -> int | None:
"""Get Space credits for user with caching (60s TTL)"""
cache_ttl = 60
if not force_refresh and user_email in self._credits_cache:
credits, ts = self._credits_cache[user_email]
if time.time() - ts < cache_ttl:
return credits
try:
info = await self.get_user_info(user_email)
if info is None:
return None
credits = info.get('credits')
if credits is not None:
self._credits_cache[user_email] = (credits, time.time())
return credits
except Exception:
return self._credits_cache.get(user_email, (None, 0))[0]
async def get_models(self) -> typing.List[SpaceModel]:
"""Get models from Space"""
space_config = self._get_space_config()
space_url = space_config['url']
async with aiohttp.ClientSession() as session:
async with session.get(f'{space_url}/api/v1/models') as response:
if response.status != 200:
raise ValueError(f'Failed to get models: {await response.text()}')
data = await response.json()
if data.get('code') != 0:
raise ValueError(f'Failed to get models: {data.get("msg")}')
models_data = data.get('data', {}).get('models', [])
return [SpaceModel.model_validate(model_dict) for model_dict in models_data]

View File

@@ -4,22 +4,17 @@ import sqlalchemy
import argon2
import jwt
import datetime
import typing
import asyncio
from ....core import app
from ....entity.persistence import user
from ....utils import constants
from ....entity.errors import account as account_errors
class UserService:
ap: app.Application
_create_user_lock: asyncio.Lock
def __init__(self, ap: app.Application) -> None:
self.ap = ap
self._create_user_lock = asyncio.Lock()
async def is_initialized(self) -> bool:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
@@ -33,7 +28,7 @@ class UserService:
hashed_password = ph.hash(password)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password, account_type='local')
sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password)
)
async def get_user_by_email(self, user_email: str) -> user.User | None:
@@ -44,15 +39,6 @@ class UserService:
result_list = result.all()
return result_list[0] if result_list is not None and len(result_list) > 0 else None
async def get_user_by_space_account_uuid(self, space_account_uuid: str) -> user.User | None:
"""Get user by Space account UUID"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(user.User).where(user.User.space_account_uuid == space_account_uuid)
)
result_list = result.all()
return result_list[0] if result_list is not None and len(result_list) > 0 else None
async def authenticate(self, user_email: str, password: str) -> str | None:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(user.User).where(user.User.user == user_email)
@@ -65,10 +51,6 @@ class UserService:
user_obj = result_list[0]
# Check if this is a Space account
if user_obj.account_type == 'space':
raise ValueError('请使用 Space 账户登录')
ph = argon2.PasswordHasher()
ph.verify(user_obj.password, password)
@@ -108,10 +90,6 @@ class UserService:
if user_obj is None:
raise ValueError('User not found')
# Space accounts cannot change password locally
if user_obj.account_type == 'space':
raise ValueError('Space account cannot change password locally')
ph.verify(user_obj.password, current_password)
hashed_password = ph.hash(new_password)
@@ -119,183 +97,3 @@ class UserService:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password)
)
# Space user management
async def create_or_update_space_user(
self,
space_account_uuid: str,
email: str,
access_token: str,
refresh_token: str,
api_key: str,
expires_in: int = 0,
) -> user.User:
"""Create or update a Space user account (only if system not initialized or user exists)"""
expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
async with self._create_user_lock:
# Check if user with this Space UUID already exists
existing_user = await self.get_user_by_space_account_uuid(space_account_uuid)
if existing_user:
# Update existing user's tokens
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User)
.where(user.User.space_account_uuid == space_account_uuid)
.values(
space_access_token=access_token,
space_refresh_token=refresh_token,
space_api_key=api_key,
space_access_token_expires_at=expires_at,
)
)
await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
return await self.get_user_by_space_account_uuid(space_account_uuid)
# Check if user with same email exists
existing_email_user = await self.get_user_by_email(email)
if existing_email_user:
# Update existing user to link with Space account
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User)
.where(user.User.user == email)
.values(
account_type='space',
space_account_uuid=space_account_uuid,
space_access_token=access_token,
space_refresh_token=refresh_token,
space_api_key=api_key,
space_access_token_expires_at=expires_at,
)
)
await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
return await self.get_user_by_email(email)
# Check if system is already initialized
is_initialized = await self.is_initialized()
if is_initialized:
raise account_errors.AccountEmailMismatchError()
# Create new Space user (first time initialization)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(user.User).values(
user=email,
password='', # Space users don't have local password
account_type='space',
space_account_uuid=space_account_uuid,
space_access_token=access_token,
space_refresh_token=refresh_token,
space_api_key=api_key,
space_access_token_expires_at=expires_at,
)
)
await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
return await self.get_user_by_space_account_uuid(space_account_uuid)
async def authenticate_space_user(
self, access_token: str, refresh_token: str, expires_in: int = 0
) -> typing.Tuple[str, user.User]:
"""Authenticate with Space and return JWT token"""
# Get user info from Space using raw API (token just obtained, no need to validate)
user_info = await self.ap.space_service.get_user_info_raw(access_token)
account = user_info.get('account', {})
api_key = user_info.get('api_key', '')
space_account_uuid = account.get('uuid')
email = account.get('email')
if not space_account_uuid or not email:
raise ValueError('Invalid Space user info')
# Create or update Space user in local database
user_obj = await self.create_or_update_space_user(
space_account_uuid=space_account_uuid,
email=email,
access_token=access_token,
refresh_token=refresh_token,
api_key=api_key,
expires_in=expires_in,
)
# Generate JWT token
jwt_token = await self.generate_jwt_token(email)
return jwt_token, user_obj
async def get_first_user(self) -> user.User | None:
"""Get the first user (for single-user mode)"""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
result_list = result.all()
return result_list[0] if result_list else None
async def set_password(self, user_email: str, new_password: str, current_password: str | None = None) -> None:
"""Set or change password for a user"""
ph = argon2.PasswordHasher()
user_obj = await self.get_user_by_email(user_email)
if user_obj is None:
raise ValueError('User not found')
# If user already has a password, verify current password
has_password = bool(user_obj.password and user_obj.password.strip())
if has_password:
if not current_password:
raise ValueError('Current password is required')
ph.verify(user_obj.password, current_password)
hashed_password = ph.hash(new_password)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password)
)
async def bind_space_account(self, user_email: str, code: str) -> user.User:
"""Bind Space account to existing local account"""
# Exchange code for tokens
token_data = await self.ap.space_service.exchange_oauth_code(code)
access_token = token_data.get('access_token')
refresh_token = token_data.get('refresh_token')
expires_in = token_data.get('expires_in', 0)
if not access_token:
raise ValueError('Failed to get access token from Space')
expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
# Get Space user info (token just obtained, use raw API)
user_info = await self.ap.space_service.get_user_info_raw(access_token)
account = user_info.get('account', {})
api_key = user_info.get('api_key', '')
space_account_uuid = account.get('uuid')
space_email = account.get('email')
if not space_account_uuid or not space_email:
raise ValueError('Invalid Space user info')
# Check if this Space account is already bound to another user
existing_space_user = await self.get_user_by_space_account_uuid(space_account_uuid)
if existing_space_user and existing_space_user.user != user_email:
raise ValueError('This Space account is already bound to another user')
# Update local account to Space account
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(user.User)
.where(user.User.user == user_email)
.values(
user=space_email, # Update email to Space email
account_type='space',
space_account_uuid=space_account_uuid,
space_access_token=access_token,
space_refresh_token=refresh_token,
space_api_key=api_key,
space_access_token_expires_at=expires_at,
)
)
# Update Space model provider API keys
await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
return await self.get_user_by_email(space_email)

View File

@@ -15,22 +15,17 @@ from ..command import cmdmgr
from ..plugin import connector as plugin_connector
from ..pipeline import pool
from ..pipeline import controller, pipelinemgr
from ..pipeline import aggregator as message_aggregator
from ..utils import version as version_mgr, proxy as proxy_mgr
from ..persistence import mgr as persistencemgr
from ..api.http.controller import main as http_controller
from ..api.http.service import user as user_service
from ..api.http.service import space as space_service
from ..api.http.service import model as model_service
from ..api.http.service import provider as provider_service
from ..api.http.service import pipeline as pipeline_service
from ..api.http.service import bot as bot_service
from ..api.http.service import knowledge as knowledge_service
from ..api.http.service import mcp as mcp_service
from ..api.http.service import apikey as apikey_service
from ..api.http.service import webhook as webhook_service
from ..api.http.service import external_kb as external_kb_service
from ..api.http.service import monitoring as monitoring_service
from ..discover import engine as discover_engine
from ..storage import mgr as storagemgr
from ..utils import logcache
@@ -38,8 +33,6 @@ from . import taskmgr
from . import entities as core_entities
from ..rag.knowledge import kbmgr as rag_mgr
from ..vector import mgr as vectordb_mgr
from ..telemetry import telemetry as telemetry_module
from ..survey import manager as survey_module
class Application:
@@ -81,8 +74,6 @@ class Application:
instance_config: config_mgr.ConfigManager = None
instance_id: config_mgr.ConfigManager = None # used to identify the instance
# ======= Metadata config manager =======
sensitive_meta: config_mgr.ConfigManager = None
@@ -98,8 +89,6 @@ class Application:
query_pool: pool.QueryPool = None
msg_aggregator: message_aggregator.MessageAggregator = None
ctrl: controller.Controller = None
pipeline_mgr: pipelinemgr.PipelineManager = None
@@ -124,34 +113,22 @@ class Application:
user_service: user_service.UserService = None
space_service: space_service.SpaceService = None
llm_model_service: model_service.LLMModelsService = None
embedding_models_service: model_service.EmbeddingModelsService = None
provider_service: provider_service.ModelProviderService = None
pipeline_service: pipeline_service.PipelineService = None
bot_service: bot_service.BotService = None
knowledge_service: knowledge_service.KnowledgeService = None
external_kb_service: external_kb_service.ExternalKBService = None
mcp_service: mcp_service.MCPService = None
apikey_service: apikey_service.ApiKeyService = None
webhook_service: webhook_service.WebhookService = None
telemetry: telemetry_module.TelemetryManager = None
survey: survey_module.SurveyManager = None
monitoring_service: monitoring_service.MonitoringService = None
def __init__(self):
pass

View File

@@ -1,5 +1,4 @@
import logging
import logging.handlers
import sys
import time
@@ -16,10 +15,6 @@ log_colors_config = {
'CRITICAL': 'cyan',
}
# Log rotation configuration to prevent unbounded log file growth
LOG_FILE_MAX_BYTES = 10 * 1024 * 1024 # 10MB per file
LOG_FILE_BACKUP_COUNT = 5 # Keep 5 backup files (total ~50MB max)
async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.Logger:
# Remove all existing loggers
@@ -48,17 +43,9 @@ async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.
# stream_handler.setFormatter(color_formatter)
stream_handler.stream = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=1)
# Use RotatingFileHandler to prevent unbounded log file growth
rotating_file_handler = logging.handlers.RotatingFileHandler(
log_file_name,
encoding='utf-8',
maxBytes=LOG_FILE_MAX_BYTES,
backupCount=LOG_FILE_BACKUP_COUNT,
)
log_handlers: list[logging.Handler] = [
stream_handler,
rotating_file_handler,
logging.FileHandler(log_file_name, encoding='utf-8'),
]
log_handlers += extra_handlers if extra_handlers is not None else []

View File

@@ -1,17 +0,0 @@
from __future__ import annotations
from .. import migration
@migration.migration_class('dingtalk_card_auto_layout', 41)
class DingTalkCardAutoLayoutMigration(migration.Migration):
"""迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return True
async def run(self):
"""执行迁移"""
self.ap.platform_cfg.data['platform-adapters']['app']['dingtalk']['card_auto_layout'] = False
await self.ap.platform_cfg.dump_config()

View File

@@ -5,7 +5,6 @@ import asyncio
from .. import stage, app
from ...utils import version, proxy
from ...pipeline import pool, controller, pipelinemgr
from ...pipeline import aggregator as message_aggregator
from ...plugin import connector as plugin_connector
from ...command import cmdmgr
from ...provider.session import sessionmgr as llm_session_mgr
@@ -17,24 +16,18 @@ from ...platform.webhook_pusher import WebhookPusher
from ...persistence import mgr as persistencemgr
from ...api.http.controller import main as http_controller
from ...api.http.service import user as user_service
from ...api.http.service import space as space_service
from ...api.http.service import model as model_service
from ...api.http.service import provider as provider_service
from ...api.http.service import pipeline as pipeline_service
from ...api.http.service import bot as bot_service
from ...api.http.service import knowledge as knowledge_service
from ...api.http.service import mcp as mcp_service
from ...api.http.service import apikey as apikey_service
from ...api.http.service import webhook as webhook_service
from ...api.http.service import external_kb as external_kb_service
from ...api.http.service import monitoring as monitoring_service
from ...discover import engine as discover_engine
from ...storage import mgr as storagemgr
from ...utils import logcache
from ...vector import mgr as vectordb_mgr
from .. import taskmgr
from ...telemetry import telemetry as telemetry_module
from ...survey import manager as survey_module
@stage.stage_class('BuildAppStage')
@@ -49,42 +42,6 @@ class BuildAppStage(stage.BootingStage):
discover.discover_blueprint('templates/components.yaml')
ap.discover = discover
user_service_inst = user_service.UserService(ap)
ap.user_service = user_service_inst
space_service_inst = space_service.SpaceService(ap)
ap.space_service = space_service_inst
llm_model_service_inst = model_service.LLMModelsService(ap)
ap.llm_model_service = llm_model_service_inst
embedding_models_service_inst = model_service.EmbeddingModelsService(ap)
ap.embedding_models_service = embedding_models_service_inst
provider_service_inst = provider_service.ModelProviderService(ap)
ap.provider_service = provider_service_inst
pipeline_service_inst = pipeline_service.PipelineService(ap)
ap.pipeline_service = pipeline_service_inst
bot_service_inst = bot_service.BotService(ap)
ap.bot_service = bot_service_inst
knowledge_service_inst = knowledge_service.KnowledgeService(ap)
ap.knowledge_service = knowledge_service_inst
external_kb_service_inst = external_kb_service.ExternalKBService(ap)
ap.external_kb_service = external_kb_service_inst
mcp_service_inst = mcp_service.MCPService(ap)
ap.mcp_service = mcp_service_inst
apikey_service_inst = apikey_service.ApiKeyService(ap)
ap.apikey_service = apikey_service_inst
webhook_service_inst = webhook_service.WebhookService(ap)
ap.webhook_service = webhook_service_inst
proxy_mgr = proxy.ProxyManager(ap)
await proxy_mgr.initialize()
ap.proxy_mgr = proxy_mgr
@@ -106,23 +63,21 @@ class BuildAppStage(stage.BootingStage):
ap.persistence_mgr = persistence_mgr_inst
await persistence_mgr_inst.initialize()
# Telemetry manager: attach to app so other components can call via self.ap.telemetry
telemetry_inst = telemetry_module.TelemetryManager(ap)
await telemetry_inst.initialize()
ap.telemetry = telemetry_inst
async def runtime_disconnect_callback(connector: plugin_connector.PluginRuntimeConnector) -> None:
await asyncio.sleep(3)
await plugin_connector_inst.initialize()
# Survey manager
survey_inst = survey_module.SurveyManager(ap)
await survey_inst.initialize()
ap.survey = survey_inst
plugin_connector_inst = plugin_connector.PluginRuntimeConnector(ap, runtime_disconnect_callback)
await plugin_connector_inst.initialize()
ap.plugin_connector = plugin_connector_inst
cmd_mgr_inst = cmdmgr.CommandManager(ap)
await cmd_mgr_inst.initialize()
ap.cmd_mgr = cmd_mgr_inst
llm_model_mgr_inst = llm_model_mgr.ModelManager(ap)
ap.model_mgr = llm_model_mgr_inst
await llm_model_mgr_inst.initialize()
ap.model_mgr = llm_model_mgr_inst
llm_session_mgr_inst = llm_session_mgr.SessionManager(ap)
await llm_session_mgr_inst.initialize()
@@ -144,10 +99,6 @@ class BuildAppStage(stage.BootingStage):
await pipeline_mgr.initialize()
ap.pipeline_mgr = pipeline_mgr
# Initialize message aggregator (after pipeline_mgr, as it needs pipeline config)
msg_aggregator_inst = message_aggregator.MessageAggregator(ap)
ap.msg_aggregator = msg_aggregator_inst
rag_mgr_inst = rag_mgr.RAGManager(ap)
await rag_mgr_inst.initialize()
ap.rag_mgr = rag_mgr_inst
@@ -161,16 +112,32 @@ class BuildAppStage(stage.BootingStage):
await http_ctrl.initialize()
ap.http_ctrl = http_ctrl
monitoring_service_inst = monitoring_service.MonitoringService(ap)
ap.monitoring_service = monitoring_service_inst
user_service_inst = user_service.UserService(ap)
ap.user_service = user_service_inst
async def runtime_disconnect_callback(connector: plugin_connector.PluginRuntimeConnector) -> None:
await asyncio.sleep(3)
await plugin_connector_inst.initialize()
llm_model_service_inst = model_service.LLMModelsService(ap)
ap.llm_model_service = llm_model_service_inst
plugin_connector_inst = plugin_connector.PluginRuntimeConnector(ap, runtime_disconnect_callback)
await plugin_connector_inst.initialize()
ap.plugin_connector = plugin_connector_inst
embedding_models_service_inst = model_service.EmbeddingModelsService(ap)
ap.embedding_models_service = embedding_models_service_inst
pipeline_service_inst = pipeline_service.PipelineService(ap)
ap.pipeline_service = pipeline_service_inst
bot_service_inst = bot_service.BotService(ap)
ap.bot_service = bot_service_inst
knowledge_service_inst = knowledge_service.KnowledgeService(ap)
ap.knowledge_service = knowledge_service_inst
mcp_service_inst = mcp_service.MCPService(ap)
ap.mcp_service = mcp_service_inst
apikey_service_inst = apikey_service.ApiKeyService(ap)
ap.apikey_service = apikey_service_inst
webhook_service_inst = webhook_service.WebhookService(ap)
ap.webhook_service = webhook_service_inst
ctrl = controller.Controller(ap)
ap.ctrl = ctrl

View File

@@ -2,11 +2,8 @@ from __future__ import annotations
import os
from typing import Any
from langbot.pkg.utils import constants
import yaml
import importlib.resources as resources
import uuid
import time
from .. import stage, app
from ..bootutils import config
@@ -145,24 +142,6 @@ class LoadConfigStage(stage.BootingStage):
await ap.instance_config.dump_config()
# load or generate instance id
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': f'instance_{str(uuid.uuid4())}',
'instance_create_ts': int(time.time()),
},
completion=False,
)
constants.instance_id = ap.instance_id.data['instance_id']
constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
print(f'LangBot instance id: {constants.instance_id}')
print(f'LangBot edition: {constants.edition}')
await ap.instance_id.dump_config()
ap.sensitive_meta = await config.load_json_config(
'data/metadata/sensitive-words.json',
'metadata/sensitive-words.json',

View File

@@ -1,49 +0,0 @@
# [
# {
# "uuid": "7652ebdb-54dc-412c-a830-e9268ac88471",
# "model_id": "claude-opus-4-5-20251101",
# "display_name": {
# "en_US": "claude-opus-4-5-20251101",
# "zh_Hans": "claude-opus-4-5-20251101"
# },
# "description": {},
# "provider": "anthropic",
# "category": "chat",
# "icon_url": "Claude.Color",
# "tags": {},
# "is_featured": true,
# "featured_order": 999,
# "model_ratio": 2.5,
# "completion_ratio": 5,
# "quota_type": 0,
# "model_price": 0,
# "input_credits": 500,
# "output_credits": 2500,
# "vendor_id": 1,
# "vendor_name": "Anthropic",
# "vendor_icon": "Claude.Color",
# "supported_endpoints": [
# "anthropic",
# "openai"
# ],
# "status": "active",
# "metadata": null,
# "created_at": "2025-12-30T22:23:38.337207+08:00",
# "updated_at": "2025-12-30T22:23:38.337207+08:00"
# }
# ]
import pydantic
class SpaceModel(pydantic.BaseModel):
uuid: str
model_id: str
provider: str
category: str # chat / embedding
llm_abilities: list[str] | None = None
is_featured: bool = False
featured_order: int = 0
status: str
created_at: str | None = None
updated_at: str | None = None

View File

@@ -1,6 +0,0 @@
from __future__ import annotations
class AccountEmailMismatchError(Exception):
def __str__(self):
return 'Account email mismatch'

View File

@@ -7,11 +7,3 @@ class RequesterNotFoundError(Exception):
def __str__(self):
return f'Requester {self.requester_name} not found'
class ProviderNotFoundError(Exception):
def __init__(self, provider_name: str):
self.provider_name = provider_name
def __str__(self):
return f'Provider {self.provider_name} not found'

View File

@@ -9,7 +9,7 @@ class MCPServer(Base):
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
enable = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
mode = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) # stdio, sse, http
mode = sqlalchemy.Column(sqlalchemy.String(255), nullable=False) # stdio, sse
extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(

View File

@@ -3,25 +3,6 @@ import sqlalchemy
from .base import Base
class ModelProvider(Base):
"""Model provider"""
__tablename__ = 'model_providers'
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
base_url = sqlalchemy.Column(sqlalchemy.String(512), nullable=False)
api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default=[])
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,
nullable=False,
server_default=sqlalchemy.func.now(),
onupdate=sqlalchemy.func.now(),
)
class LLMModel(Base):
"""LLM model"""
@@ -29,10 +10,12 @@ class LLMModel(Base):
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
provider_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
abilities = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default=[])
extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
prefered_ranking = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,
@@ -43,15 +26,17 @@ class LLMModel(Base):
class EmbeddingModel(Base):
"""Embedding model"""
"""Embedding 模型"""
__tablename__ = 'embedding_models'
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
provider_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
prefered_ranking = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,

View File

@@ -1,106 +0,0 @@
import sqlalchemy
from .base import Base
class MonitoringMessage(Base):
"""Monitoring message records"""
__tablename__ = 'monitoring_messages'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
message_content = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error, pending
level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # info, warning, error, debug
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # Runner name for this query
variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # Query variables as JSON string
role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user') # user, assistant
class MonitoringLLMCall(Base):
"""LLM call records"""
__tablename__ = 'monitoring_llm_calls'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
input_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
output_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
cost = sqlalchemy.Column(sqlalchemy.Float, nullable=True)
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
class MonitoringSession(Base):
"""Session tracking records"""
__tablename__ = 'monitoring_sessions'
session_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
message_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
start_time = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
last_activity = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
class MonitoringError(Base):
"""Error log records"""
__tablename__ = 'monitoring_errors'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
error_type = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
stack_trace = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True) # Associated message ID
class MonitoringEmbeddingCall(Base):
"""Embedding call records"""
__tablename__ = 'monitoring_embedding_calls'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
prompt_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # milliseconds
input_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # Number of input texts
status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False) # success, error
error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
# Optional context fields
knowledge_base_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
query_text = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # For retrieval calls
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True) # embedding, retrieve

View File

@@ -11,7 +11,6 @@ class LegacyPipeline(Base):
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='⚙️')
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,
@@ -23,11 +22,7 @@ class LegacyPipeline(Base):
is_default = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
stages = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
extensions_preferences = sqlalchemy.Column(
sqlalchemy.JSON,
nullable=False,
default={'enable_all_plugins': True, 'enable_all_mcp_servers': True, 'plugins': [], 'mcp_servers': []},
)
extensions_preferences = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
class PipelineRunRecord(Base):

View File

@@ -1,15 +1,27 @@
import sqlalchemy
from .base import Base
# Base = declarative_base()
# DATABASE_URL = os.getenv('DATABASE_URL', 'sqlite:///./rag_knowledge.db')
# print("Using database URL:", DATABASE_URL)
# engine = create_engine(DATABASE_URL, connect_args={'check_same_thread': False})
# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
# def create_db_and_tables():
# """Creates all database tables defined in the Base."""
# Base.metadata.create_all(bind=engine)
# print('Database tables created or already exist.')
class KnowledgeBase(Base):
__tablename__ = 'knowledge_bases'
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String, index=True)
description = sqlalchemy.Column(sqlalchemy.Text)
emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='📚')
created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now(), onupdate=sqlalchemy.func.now())
embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='')
top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5)
@@ -31,14 +43,8 @@ class Chunk(Base):
text = sqlalchemy.Column(sqlalchemy.Text)
class ExternalKnowledgeBase(Base):
__tablename__ = 'external_knowledge_bases'
uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
name = sqlalchemy.Column(sqlalchemy.String, index=True)
description = sqlalchemy.Column(sqlalchemy.Text)
emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='🔗')
plugin_author = sqlalchemy.Column(sqlalchemy.String, nullable=False)
plugin_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
retriever_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
retriever_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
# class Vector(Base):
# __tablename__ = 'knowledge_base_vectors'
# uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
# chunk_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
# embedding = sqlalchemy.Column(sqlalchemy.LargeBinary)

View File

@@ -9,17 +9,6 @@ class User(Base):
id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
user = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
password = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
# Account type: 'local' (default) or 'space'
account_type = sqlalchemy.Column(sqlalchemy.String(32), nullable=False, server_default='local')
# Space account fields (nullable, only used when account_type='space')
space_account_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
space_access_token = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
space_refresh_token = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
space_access_token_expires_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=True)
space_api_key = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,

View File

@@ -0,0 +1,13 @@
from __future__ import annotations
import pydantic
from typing import Any
class RetrieveResultEntry(pydantic.BaseModel):
id: str
metadata: dict[str, Any]
distance: float

View File

@@ -9,7 +9,7 @@ import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
import sqlalchemy
from . import database, migration
from ..entity.persistence import base, pipeline, metadata, model as persistence_model
from ..entity.persistence import base, pipeline, metadata
from ..entity import persistence
from ..core import app
from ..utils import constants, importutil
@@ -79,7 +79,6 @@ class PersistenceManager:
self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
await self.write_default_pipeline()
await self.write_space_model_providers()
async def create_tables(self):
# create tables
@@ -124,42 +123,7 @@ class PersistenceManager:
await self.execute_async(sqlalchemy.insert(pipeline.LegacyPipeline).values(pipeline_data))
async def write_space_model_providers(self):
space_models_gateway_api_url = self.ap.instance_config.data.get('space', {}).get(
'models_gateway_api_url', 'https://api.langbot.cloud/v1'
)
# write space model providers
result = await self.execute_async(
sqlalchemy.select(persistence_model.ModelProvider).where(
persistence_model.ModelProvider.requester == 'space-chat-completions'
)
)
exists_space_chat_completions_model_provider = result.first()
# api keys will be set/updated when the oauth callback
if exists_space_chat_completions_model_provider is None:
self.ap.logger.info('Creating space model providers...')
space_chat_completions_model_provider = {
'uuid': '00000000-0000-0000-0000-000000000000',
'name': 'LangBot Models',
'requester': 'space-chat-completions',
'base_url': space_models_gateway_api_url,
'api_keys': [],
}
await self.execute_async(
sqlalchemy.insert(persistence_model.ModelProvider).values(space_chat_completions_model_provider)
)
else:
if exists_space_chat_completions_model_provider.base_url != space_models_gateway_api_url:
await self.execute_async(
sqlalchemy.update(persistence_model.ModelProvider)
.where(persistence_model.ModelProvider.uuid == exists_space_chat_completions_model_provider.uuid)
.values({'base_url': space_models_gateway_api_url})
)
# =================================
# =================================
async def execute_async(self, *args, **kwargs) -> sqlalchemy.engine.cursor.CursorResult:
async with self.get_db_engine().connect() as conn:

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(2)
@@ -10,45 +11,30 @@ class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure 'trigger' exists
if 'trigger' not in config:
config['trigger'] = {}
# Ensure 'misc' exists in 'trigger'
if 'misc' not in config['trigger']:
config['trigger']['misc'] = {}
# Add 'combine-quote-message' if not exists
if 'combine-quote-message' not in config['trigger']['misc']:
config['trigger']['misc']['combine-quote-message'] = False
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(3)
@@ -10,23 +11,14 @@ class DBMigrateN8nConfig(migration.DBMigration):
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure 'ai' exists
if 'ai' not in config:
config['ai'] = {}
# Add 'n8n-service-api' if not exists
if 'n8n-service-api' not in config['ai']:
config['ai']['n8n-service-api'] = {
'webhook-url': 'http://your-n8n-webhook-url',
@@ -41,21 +33,16 @@ class DBMigrateN8nConfig(migration.DBMigration):
'output-key': 'response',
}
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(4)
@@ -10,43 +11,27 @@ class DBMigrateRAGKBUUID(migration.DBMigration):
async def upgrade(self):
"""升级"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure nested structure exists
if 'ai' not in config:
config['ai'] = {}
if 'local-agent' not in config['ai']:
config['ai']['local-agent'] = {}
# Add 'knowledge-base' if not exists
if 'knowledge-base' not in config['ai']['local-agent']:
config['ai']['local-agent']['knowledge-base'] = ''
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""降级"""

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(5)
@@ -10,43 +11,27 @@ class DBMigratePipelineRemoveCotConfig(migration.DBMigration):
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure nested structure exists
if 'output' not in config:
config['output'] = {}
if 'misc' not in config['output']:
config['output']['misc'] = {}
# Add 'remove-think' if not exists
if 'remove-think' not in config['output']['misc']:
config['output']['misc']['remove-think'] = False
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(6)
@@ -10,23 +11,14 @@ class DBMigrateLangflowApiConfig(migration.DBMigration):
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure 'ai' exists
if 'ai' not in config:
config['ai'] = {}
# Add 'langflow-api' if not exists
if 'langflow-api' not in config['ai']:
config['ai']['langflow-api'] = {
'base-url': 'http://localhost:7860',
@@ -37,21 +29,16 @@ class DBMigrateLangflowApiConfig(migration.DBMigration):
'tweaks': '{}',
}
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""

View File

@@ -1,7 +1,8 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(10)
@@ -10,20 +11,16 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Convert knowledge-base from string to array
if 'ai' in config and 'local-agent' in config['ai']:
if 'local-agent' in config['ai']:
current_kb = config['ai']['local-agent'].get('knowledge-base', '')
# If it's already a list, skip
@@ -40,38 +37,29 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
if 'knowledge-base' in config['ai']['local-agent']:
del config['ai']['local-agent']['knowledge-base']
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Convert knowledge-bases from array back to string
if 'ai' in config and 'local-agent' in config['ai']:
if 'local-agent' in config['ai']:
current_kbs = config['ai']['local-agent'].get('knowledge-bases', [])
# If it's already a string, skip
@@ -88,18 +76,13 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
if 'knowledge-bases' in config['ai']['local-agent']:
del config['ai']['local-agent']['knowledge-bases']
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)

View File

@@ -1,54 +1,39 @@
from .. import migration
import sqlalchemy
import json
from ...entity.persistence import pipeline as persistence_pipeline
@migration.migration_class(11)
class DBMigrateDifyApiConfig(migration.DBMigration):
"""Dify base prompt config"""
"""Langflow API config"""
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
)
pipelines = result.fetchall()
# read all pipelines
pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
current_version = self.ap.ver_mgr.get_current_version()
for pipeline in pipelines:
serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
for pipeline_row in pipelines:
uuid = pipeline_row[0]
config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
config = serialized_pipeline['config']
# Ensure nested structure exists
if 'ai' not in config:
config['ai'] = {}
if 'dify-service-api' not in config['ai']:
config['ai']['dify-service-api'] = {}
# Add 'base-prompt' if not exists
if 'base-prompt' not in config['ai']['dify-service-api']:
config['ai']['dify-service-api']['base-prompt'] = (
'When the file content is readable, please read the content of this file. When the file is an image, describe the content of this image.',
)
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
),
{'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_pipeline.LegacyPipeline)
.where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
.values(
{
'config': config,
'for_version': self.ap.ver_mgr.get_current_version(),
}
)
)
async def downgrade(self):
"""Downgrade"""

View File

@@ -1,73 +0,0 @@
from .. import migration
import sqlalchemy
import json
@migration.migration_class(12)
class DBMigratePipelineExtensionsEnableAll(migration.DBMigration):
"""Pipeline extensions enable all"""
async def upgrade(self):
"""Upgrade"""
# Read all pipelines using raw SQL
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, extensions_preferences FROM legacy_pipelines')
)
pipelines = result.fetchall()
current_version = self.ap.ver_mgr.get_current_version()
for pipeline_row in pipelines:
uuid = pipeline_row[0]
extensions_preferences = (
json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
)
# Ensure extensions_preferences is a dict
if extensions_preferences is None:
extensions_preferences = {}
# Add 'enable_all_plugins' if not exists
if 'enable_all_plugins' not in extensions_preferences:
if 'plugins' in extensions_preferences:
extensions_preferences['enable_all_plugins'] = False
else:
extensions_preferences['enable_all_plugins'] = True
extensions_preferences['plugins'] = []
# Add 'enable_all_mcp_servers' if not exists
if 'enable_all_mcp_servers' not in extensions_preferences:
if 'mcp_servers' in extensions_preferences:
extensions_preferences['enable_all_mcp_servers'] = False
else:
extensions_preferences['enable_all_mcp_servers'] = True
extensions_preferences['mcp_servers'] = []
# Update using raw SQL with compatibility for both SQLite and PostgreSQL
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET extensions_preferences = :extensions_preferences::jsonb, for_version = :for_version WHERE uuid = :uuid'
),
{
'extensions_preferences': json.dumps(extensions_preferences),
'for_version': current_version,
'uuid': uuid,
},
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'UPDATE legacy_pipelines SET extensions_preferences = :extensions_preferences, for_version = :for_version WHERE uuid = :uuid'
),
{
'extensions_preferences': json.dumps(extensions_preferences),
'for_version': current_version,
'uuid': uuid,
},
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,49 +0,0 @@
import sqlalchemy
from .. import migration
@migration.migration_class(13)
class DBMigrateKnowledgeBaseUpdatedAt(migration.DBMigration):
"""Add updated_at field to knowledge_bases table"""
async def upgrade(self):
"""Upgrade"""
# Get all column names from the table
columns = []
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
"SELECT column_name FROM information_schema.columns WHERE table_name = 'knowledge_bases';"
)
)
all_result = result.fetchall()
columns = [row[0] for row in all_result]
else:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('PRAGMA table_info(knowledge_bases);'))
all_result = result.fetchall()
columns = [row[1] for row in all_result]
# Check and add updated_at column
if 'updated_at' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'ALTER TABLE knowledge_bases ADD COLUMN updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP'
)
)
else:
# SQLite doesn't support DEFAULT CURRENT_TIMESTAMP in ALTER TABLE
# Add column without default first
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE knowledge_bases ADD COLUMN updated_at DATETIME')
)
# Set initial updated_at values to created_at for existing records
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE knowledge_bases SET updated_at = created_at WHERE updated_at IS NULL')
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,94 +0,0 @@
import sqlalchemy
from .. import migration
@migration.migration_class(14)
class DBMigrateSpaceAccountSupport(migration.DBMigration):
"""Add Space account support fields to users table"""
async def upgrade(self):
"""Upgrade"""
# Get all column names from the users table
columns = []
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT column_name FROM information_schema.columns WHERE table_name = 'users';")
)
all_result = result.fetchall()
columns = [row[0] for row in all_result]
else:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('PRAGMA table_info(users);'))
all_result = result.fetchall()
columns = [row[1] for row in all_result]
# Add account_type column
if 'account_type' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("ALTER TABLE users ADD COLUMN account_type VARCHAR(32) DEFAULT 'local' NOT NULL")
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("ALTER TABLE users ADD COLUMN account_type VARCHAR(32) DEFAULT 'local' NOT NULL")
)
# Add space_account_uuid column
if 'space_account_uuid' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_account_uuid VARCHAR(255)')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_account_uuid VARCHAR(255)')
)
# Add space_access_token column
if 'space_access_token' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token TEXT')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token TEXT')
)
# Add space_refresh_token column
if 'space_refresh_token' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_refresh_token TEXT')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_refresh_token TEXT')
)
# Add space_access_token_expires_at column
if 'space_access_token_expires_at' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token_expires_at TIMESTAMP')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token_expires_at DATETIME')
)
# Add space_api_key column
if 'space_api_key' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_api_key VARCHAR(255)')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE users ADD COLUMN space_api_key VARCHAR(255)')
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,15 +0,0 @@
from .. import migration
# this is a deprecated migration
@migration.migration_class(15)
class DBMigrateModelSourceTracking(migration.DBMigration):
"""Add source tracking fields to models tables for Space integration"""
async def upgrade(self):
"""Upgrade"""
pass
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,305 +0,0 @@
import uuid as uuid_lib
import sqlalchemy
from .. import migration
@migration.migration_class(16)
class DBMigrateModelProviderRefactor(migration.DBMigration):
"""Refactor model structure: create providers from existing models and update references"""
async def upgrade(self):
"""Upgrade"""
# Step 1: Create model_providers table if not exists
await self._create_providers_table()
# Step 2: Migrate existing models to use providers
await self._migrate_llm_models()
await self._migrate_embedding_models()
# Step 3: Remove deprecated columns
await self._cleanup_columns()
async def _create_providers_table(self):
"""Create model_providers table"""
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("""
CREATE TABLE IF NOT EXISTS model_providers (
uuid VARCHAR(255) PRIMARY KEY,
name VARCHAR(255) NOT NULL,
requester VARCHAR(255) NOT NULL,
base_url VARCHAR(512) NOT NULL,
api_keys JSONB NOT NULL DEFAULT '[]',
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
)
""")
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("""
CREATE TABLE IF NOT EXISTS model_providers (
uuid VARCHAR(255) PRIMARY KEY,
name VARCHAR(255) NOT NULL,
requester VARCHAR(255) NOT NULL,
base_url VARCHAR(512) NOT NULL,
api_keys JSON NOT NULL DEFAULT '[]',
created_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP
)
""")
)
async def _migrate_llm_models(self):
"""Migrate LLM models to use providers"""
llm_columns = await self._get_columns('llm_models')
# Add provider_uuid column if not exists
if 'provider_uuid' not in llm_columns:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE llm_models ADD COLUMN provider_uuid VARCHAR(255)')
)
# Add prefered_ranking column if not exists
if 'prefered_ranking' not in llm_columns:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE llm_models ADD COLUMN prefered_ranking INTEGER NOT NULL DEFAULT 0')
)
# Only migrate if old columns exist
if 'requester' not in llm_columns:
return
# Get all LLM models with old structure
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, name, requester, requester_config, api_keys FROM llm_models')
)
models = result.fetchall()
# Create providers and update models
provider_cache = {} # (requester, base_url, api_keys_str) -> provider_uuid
for model in models:
model_uuid, model_name, requester, requester_config, api_keys = model
# Extract base_url from requester_config
base_url = ''
if requester_config:
if isinstance(requester_config, str):
import json
requester_config = json.loads(requester_config)
base_url = requester_config.get('base_url', '') or requester_config.get('base-url', '')
# Parse api_keys if it's a string
if isinstance(api_keys, str):
import json
try:
api_keys = json.loads(api_keys)
except Exception:
api_keys = []
if not api_keys:
api_keys = []
# Create cache key
api_keys_str = str(sorted(api_keys)) if api_keys else '[]'
cache_key = (requester, base_url, api_keys_str)
if cache_key in provider_cache:
provider_uuid = provider_cache[cache_key]
else:
# Create new provider
provider_uuid = str(uuid_lib.uuid4())
provider_name = f'{requester}'
if base_url:
# Extract domain for name
try:
from urllib.parse import urlparse
parsed = urlparse(base_url)
provider_name = parsed.netloc or requester
except Exception:
pass
import json
api_keys_json = json.dumps(api_keys) if api_keys else '[]'
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("""
INSERT INTO model_providers (uuid, name, requester, base_url, api_keys)
VALUES (:uuid, :name, :requester, :base_url, :api_keys)
"""),
{
'uuid': provider_uuid,
'name': provider_name,
'requester': requester,
'base_url': base_url,
'api_keys': api_keys_json,
},
)
provider_cache[cache_key] = provider_uuid
# Update model with provider_uuid
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE llm_models SET provider_uuid = :provider_uuid WHERE uuid = :uuid'),
{'provider_uuid': provider_uuid, 'uuid': model_uuid},
)
async def _migrate_embedding_models(self):
"""Migrate embedding models to use providers"""
embedding_columns = await self._get_columns('embedding_models')
# Add provider_uuid column if not exists
if 'provider_uuid' not in embedding_columns:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE embedding_models ADD COLUMN provider_uuid VARCHAR(255)')
)
# Add prefered_ranking column if not exists
if 'prefered_ranking' not in embedding_columns:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('ALTER TABLE embedding_models ADD COLUMN prefered_ranking INTEGER NOT NULL DEFAULT 0')
)
# Only migrate if old columns exist
if 'requester' not in embedding_columns:
return
# Get all embedding models with old structure
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, name, requester, requester_config, api_keys FROM embedding_models')
)
models = result.fetchall()
# Get existing providers
provider_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT uuid, requester, base_url, api_keys FROM model_providers')
)
existing_providers = provider_result.fetchall()
provider_cache = {}
for p in existing_providers:
p_uuid, p_requester, p_base_url, p_api_keys = p
api_keys_str = str(sorted(p_api_keys)) if p_api_keys else '[]'
provider_cache[(p_requester, p_base_url, api_keys_str)] = p_uuid
for model in models:
model_uuid, model_name, requester, requester_config, api_keys = model
base_url = ''
if requester_config:
if isinstance(requester_config, str):
import json
requester_config = json.loads(requester_config)
base_url = requester_config.get('base_url', '') or requester_config.get('base-url', '')
# Parse api_keys if it's a string
if isinstance(api_keys, str):
import json
try:
api_keys = json.loads(api_keys)
except Exception:
api_keys = []
if not api_keys:
api_keys = []
api_keys_str = str(sorted(api_keys)) if api_keys else '[]'
cache_key = (requester, base_url, api_keys_str)
if cache_key in provider_cache:
provider_uuid = provider_cache[cache_key]
else:
provider_uuid = str(uuid_lib.uuid4())
provider_name = f'{requester}'
if base_url:
try:
from urllib.parse import urlparse
parsed = urlparse(base_url)
provider_name = parsed.netloc or requester
except Exception:
pass
import json
api_keys_json = json.dumps(api_keys) if api_keys else '[]'
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("""
INSERT INTO model_providers (uuid, name, requester, base_url, api_keys)
VALUES (:uuid, :name, :requester, :base_url, :api_keys)
"""),
{
'uuid': provider_uuid,
'name': provider_name,
'requester': requester,
'base_url': base_url,
'api_keys': api_keys_json,
},
)
provider_cache[cache_key] = provider_uuid
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('UPDATE embedding_models SET provider_uuid = :provider_uuid WHERE uuid = :uuid'),
{'provider_uuid': provider_uuid, 'uuid': model_uuid},
)
async def _cleanup_columns(self):
"""Remove deprecated columns from model tables"""
llm_columns = await self._get_columns('llm_models')
deprecated_llm_cols = ['requester', 'requester_config', 'api_keys', 'description', 'source', 'space_model_id']
for col in deprecated_llm_cols:
if col in llm_columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE llm_models DROP COLUMN IF EXISTS {col}')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE llm_models DROP COLUMN {col}')
)
embedding_columns = await self._get_columns('embedding_models')
deprecated_embedding_cols = [
'requester',
'requester_config',
'api_keys',
'description',
'source',
'space_model_id',
]
for col in deprecated_embedding_cols:
if col in embedding_columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE embedding_models DROP COLUMN IF EXISTS {col}')
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE embedding_models DROP COLUMN {col}')
)
async def _get_columns(self, table_name: str) -> list:
"""Get column names for a table"""
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table_name}';"
)
)
all_result = result.fetchall()
return [row[0] for row in all_result]
else:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
all_result = result.fetchall()
return [row[1] for row in all_result]
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,25 +0,0 @@
from .. import migration
@migration.migration_class(17)
class MoveCloudServiceUrl(migration.DBMigration):
"""迁移云服务 URL 配置"""
async def upgrade(self):
"""升级"""
if 'space' not in self.ap.instance_config.data:
self.ap.instance_config.data['space'] = {
'url': 'https://space.langbot.app',
'models_gateway_api_url': 'https://api.langbot.cloud/v1',
'oauth_authorize_url': 'https://space.langbot.app/auth/authorize',
'disable_models_service': False,
}
if 'plugin' in self.ap.instance_config.data:
self.ap.instance_config.data['plugin'].pop('cloud_service_url', None)
await self.ap.instance_config.dump_config()
async def downgrade(self):
"""降级"""
pass

View File

@@ -1,58 +0,0 @@
import sqlalchemy
from .. import migration
@migration.migration_class(18)
class DBMigrateAddEmojiSupport(migration.DBMigration):
"""Add emoji field to knowledge_bases, external_knowledge_bases and legacy_pipelines tables"""
async def upgrade(self):
"""Upgrade"""
# Add emoji field to knowledge_bases
await self._add_emoji_to_table('knowledge_bases', '📚')
# Add emoji field to external_knowledge_bases
await self._add_emoji_to_table('external_knowledge_bases', '🔗')
# Add emoji field to legacy_pipelines
await self._add_emoji_to_table('legacy_pipelines', '⚙️')
async def _add_emoji_to_table(self, table_name: str, default_emoji: str):
"""Add emoji column to specified table if it doesn't exist"""
# Get all column names from the table
columns = []
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table_name}';"
)
)
all_result = result.fetchall()
columns = [row[0] for row in all_result]
else:
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
all_result = result.fetchall()
columns = [row[1] for row in all_result]
# Check and add emoji column
if 'emoji' not in columns:
if self.ap.persistence_mgr.db.name == 'postgresql':
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f"ALTER TABLE {table_name} ADD COLUMN emoji VARCHAR(10) DEFAULT '{default_emoji}'")
)
else:
# SQLite doesn't support DEFAULT with emoji directly in ALTER TABLE
# Add column without default first
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f'ALTER TABLE {table_name} ADD COLUMN emoji VARCHAR(10)')
)
# Set default emoji value for existing records
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(f"UPDATE {table_name} SET emoji = '{default_emoji}' WHERE emoji IS NULL")
)
async def downgrade(self):
"""Downgrade"""
pass

View File

@@ -1,24 +0,0 @@
import sqlalchemy
from .. import migration
@migration.migration_class(19)
class DBMigrateMonitoringMessageRole(migration.DBMigration):
"""Add role column to monitoring_messages table"""
async def upgrade(self):
"""Upgrade"""
try:
sql_text = sqlalchemy.text("ALTER TABLE monitoring_messages ADD COLUMN role VARCHAR(50) DEFAULT 'user'")
await self.ap.persistence_mgr.execute_async(sql_text)
except Exception:
# Column may already exist
pass
async def downgrade(self):
"""Downgrade"""
try:
sql_text = sqlalchemy.text('ALTER TABLE monitoring_messages DROP COLUMN role')
await self.ap.persistence_mgr.execute_async(sql_text)
except Exception:
pass

View File

@@ -1,289 +0,0 @@
"""Message Aggregator Module
This module provides message aggregation/debounce functionality.
When users send multiple messages consecutively, the aggregator will wait
for a configurable delay period and merge them into a single message
before processing.
"""
from __future__ import annotations
import asyncio
import time
import typing
from dataclasses import dataclass, field
import langbot_plugin.api.entities.builtin.platform.message as platform_message
import langbot_plugin.api.entities.builtin.platform.events as platform_events
import langbot_plugin.api.entities.builtin.provider.session as provider_session
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
if typing.TYPE_CHECKING:
from ..core import app
# Maximum number of messages to buffer before forcing a flush
MAX_BUFFER_MESSAGES = 10
@dataclass
class PendingMessage:
"""A pending message waiting to be aggregated"""
bot_uuid: str
launcher_type: provider_session.LauncherTypes
launcher_id: typing.Union[int, str]
sender_id: typing.Union[int, str]
message_event: platform_events.MessageEvent
message_chain: platform_message.MessageChain
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter
pipeline_uuid: typing.Optional[str]
timestamp: float = field(default_factory=time.time)
@dataclass
class SessionBuffer:
"""Buffer for a single session's pending messages"""
session_id: str
messages: list[PendingMessage] = field(default_factory=list)
timer_task: typing.Optional[asyncio.Task] = None
last_message_time: float = field(default_factory=time.time)
class MessageAggregator:
"""Message aggregator that buffers and merges consecutive messages
This class implements a debounce mechanism for incoming messages.
When a message arrives, it starts a timer. If more messages arrive
before the timer expires, they are buffered. When the timer expires,
all buffered messages are merged and sent to the query pool.
"""
ap: app.Application
buffers: dict[str, SessionBuffer]
"""Session ID -> SessionBuffer mapping"""
lock: asyncio.Lock
"""Lock for thread-safe buffer operations"""
def __init__(self, ap: app.Application):
self.ap = ap
self.buffers = {}
self.lock = asyncio.Lock()
def _get_session_id(
self,
bot_uuid: str,
launcher_type: provider_session.LauncherTypes,
launcher_id: typing.Union[int, str],
) -> str:
"""Generate a unique session ID"""
return f'{bot_uuid}:{launcher_type.value}:{launcher_id}'
async def _get_aggregation_config(self, pipeline_uuid: typing.Optional[str]) -> tuple[bool, float]:
"""Get aggregation configuration for a pipeline
Returns:
tuple: (enabled, delay_seconds)
"""
default_enabled = False
default_delay = 1.5
if pipeline_uuid is None:
return default_enabled, default_delay
# Get pipeline from pipeline manager
pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(pipeline_uuid)
if pipeline is None:
return default_enabled, default_delay
config = pipeline.pipeline_entity.config or {}
trigger_config = config.get('trigger', {})
aggregation_config = trigger_config.get('message-aggregation', {})
enabled = aggregation_config.get('enabled', default_enabled)
delay_raw = aggregation_config.get('delay', default_delay)
try:
delay = float(delay_raw)
except (TypeError, ValueError):
delay = default_delay
# Clamp delay to valid range
delay = max(1.0, min(10.0, delay))
return enabled, delay
async def add_message(
self,
bot_uuid: str,
launcher_type: provider_session.LauncherTypes,
launcher_id: typing.Union[int, str],
sender_id: typing.Union[int, str],
message_event: platform_events.MessageEvent,
message_chain: platform_message.MessageChain,
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
pipeline_uuid: typing.Optional[str] = None,
) -> None:
"""Add a message to the aggregation buffer
If aggregation is disabled for the pipeline, the message is sent
directly to the query pool. Otherwise, it's buffered and will be
merged with other messages from the same session.
"""
enabled, delay = await self._get_aggregation_config(pipeline_uuid)
if not enabled:
# Aggregation disabled, send directly to query pool
await self.ap.query_pool.add_query(
bot_uuid=bot_uuid,
launcher_type=launcher_type,
launcher_id=launcher_id,
sender_id=sender_id,
message_event=message_event,
message_chain=message_chain,
adapter=adapter,
pipeline_uuid=pipeline_uuid,
)
return
session_id = self._get_session_id(bot_uuid, launcher_type, launcher_id)
pending_msg = PendingMessage(
bot_uuid=bot_uuid,
launcher_type=launcher_type,
launcher_id=launcher_id,
sender_id=sender_id,
message_event=message_event,
message_chain=message_chain,
adapter=adapter,
pipeline_uuid=pipeline_uuid,
)
force_flush = False
async with self.lock:
if session_id in self.buffers:
buffer = self.buffers[session_id]
# Cancel existing timer (just cancel, don't await inside lock)
if buffer.timer_task and not buffer.timer_task.done():
buffer.timer_task.cancel()
buffer.messages.append(pending_msg)
else:
buffer = SessionBuffer(
session_id=session_id,
messages=[pending_msg],
)
self.buffers[session_id] = buffer
buffer.last_message_time = time.time()
# Check if buffer reached max capacity
if len(buffer.messages) >= MAX_BUFFER_MESSAGES:
force_flush = True
else:
# Start new timer
buffer.timer_task = asyncio.create_task(self._delayed_flush(session_id, delay))
if force_flush:
await self._flush_buffer(session_id)
async def _delayed_flush(self, session_id: str, delay: float) -> None:
"""Wait for delay then flush the buffer"""
try:
await asyncio.sleep(delay)
await self._flush_buffer(session_id)
except asyncio.CancelledError:
# Timer was cancelled, new message arrived
pass
async def _flush_buffer(self, session_id: str) -> None:
"""Flush the buffer for a session, merging all messages"""
async with self.lock:
buffer = self.buffers.pop(session_id, None)
if buffer is None or not buffer.messages:
return
if len(buffer.messages) == 1:
# Only one message, no need to merge
msg = buffer.messages[0]
await self.ap.query_pool.add_query(
bot_uuid=msg.bot_uuid,
launcher_type=msg.launcher_type,
launcher_id=msg.launcher_id,
sender_id=msg.sender_id,
message_event=msg.message_event,
message_chain=msg.message_chain,
adapter=msg.adapter,
pipeline_uuid=msg.pipeline_uuid,
)
return
# Merge multiple messages
merged_msg = self._merge_messages(buffer.messages)
await self.ap.query_pool.add_query(
bot_uuid=merged_msg.bot_uuid,
launcher_type=merged_msg.launcher_type,
launcher_id=merged_msg.launcher_id,
sender_id=merged_msg.sender_id,
message_event=merged_msg.message_event,
message_chain=merged_msg.message_chain,
adapter=merged_msg.adapter,
pipeline_uuid=merged_msg.pipeline_uuid,
)
def _merge_messages(self, messages: list[PendingMessage]) -> PendingMessage:
"""Merge multiple messages into one
The merged message uses the first message as base and combines
all message chains with newline separators.
The original message_event is kept unmodified to preserve
message metadata (message_id, etc.) for reply/quote.
"""
if len(messages) == 1:
return messages[0]
base_msg = messages[0]
# Build merged message chain
merged_chain = platform_message.MessageChain([])
for i, msg in enumerate(messages):
if i > 0:
# Add newline separator between messages
merged_chain.append(platform_message.Plain(text='\n'))
# Copy all components from this message
for component in msg.message_chain:
merged_chain.append(component)
# Keep message_event unmodified (preserves original message_id and
# metadata for reply/quote), only pass merged chain separately
return PendingMessage(
bot_uuid=base_msg.bot_uuid,
launcher_type=base_msg.launcher_type,
launcher_id=base_msg.launcher_id,
sender_id=base_msg.sender_id,
message_event=base_msg.message_event,
message_chain=merged_chain,
adapter=base_msg.adapter,
pipeline_uuid=base_msg.pipeline_uuid,
)
async def flush_all(self) -> None:
"""Flush all pending buffers immediately
This is useful during shutdown to ensure no messages are lost.
"""
# Snapshot session IDs and cancel all timers under lock
async with self.lock:
session_ids = list(self.buffers.keys())
for sid in session_ids:
buffer = self.buffers.get(sid)
if buffer and buffer.timer_task and not buffer.timer_task.done():
buffer.timer_task.cancel()
# Flush each buffer outside the lock
for session_id in session_ids:
await self._flush_buffer(session_id)

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