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
518 changed files with 16094 additions and 89407 deletions

View File

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

View File

@@ -1,5 +1,5 @@
name: 漏洞反馈
description: 【供中文用户】报错或漏洞请使用这个模板创建不使用此模板创建的异常、漏洞相关issue将被直接关闭。由于自己操作不当/不甚了解所用技术栈引起的网络连接问题恕无法解决,请勿提 issue。容器间网络连接问题参考文档 https://link.langbot.app/zh/docs/network
description: 【供中文用户】报错或漏洞请使用这个模板创建不使用此模板创建的异常、漏洞相关issue将被直接关闭。由于自己操作不当/不甚了解所用技术栈引起的网络连接问题恕无法解决,请勿提 issue。容器间网络连接问题参考文档 https://docs.langbot.app/zh/workshop/network-details.html
title: "[Bug]: "
labels: ["bug?"]
body:
@@ -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

@@ -1,5 +1,5 @@
name: Bug report
description: Report bugs or vulnerabilities using this template. For container network connection issues, refer to the documentation https://link.langbot.app/en/docs/network
description: Report bugs or vulnerabilities using this template. For container network connection issues, refer to the documentation https://docs.langbot.app/en/workshop/network-details.html
title: "[Bug]: "
labels: ["bug?"]
body:
@@ -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

@@ -43,10 +43,10 @@ jobs:
run: |
cd /tmp/langbot_build_web/web
npm install
npx vite build
npm run build
- name: Package Output
run: |
cp -r /tmp/langbot_build_web/web/dist ./web
cp -r /tmp/langbot_build_web/web/out ./web
- name: Upload Artifact
uses: actions/upload-artifact@v4
with:

View File

@@ -1,25 +0,0 @@
name: Check i18n Keys
on:
push:
branches:
- main
- master
jobs:
check-i18n:
name: Check i18n Key Consistency
runs-on: ubuntu-latest
permissions:
contents: read
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
- name: Check i18n keys against en-US reference
run: node web/scripts/check-i18n.mjs

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

@@ -29,8 +29,8 @@ jobs:
npm install -g pnpm
pnpm install
pnpm build
mkdir -p ../src/langbot/web/dist
cp -r dist ../src/langbot/web/
mkdir -p ../src/langbot/web/out
cp -r out ../src/langbot/web/
- name: Install the latest version of uv
uses: astral-sh/setup-uv@v6

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:

View File

@@ -1,171 +0,0 @@
name: Test Migrations
on:
push:
branches:
- main
- master
- dev
paths:
- 'src/langbot/pkg/persistence/**'
- 'src/langbot/pkg/entity/persistence/**'
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
paths:
- 'src/langbot/pkg/persistence/**'
- 'src/langbot/pkg/entity/persistence/**'
jobs:
test-migrations-sqlite:
name: Migrations (SQLite)
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: Test Alembic upgrade (SQLite)
run: |
uv run python -c "
import asyncio
from sqlalchemy.ext.asyncio import create_async_engine
from langbot.pkg.entity.persistence.base import Base
from langbot.pkg.persistence.alembic_runner import run_alembic_upgrade, run_alembic_stamp, get_alembic_current
async def main():
engine = create_async_engine('sqlite+aiosqlite:///test_migrations.db')
# Create all tables (simulates existing DB)
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
# Stamp baseline
await run_alembic_stamp(engine, '0001_baseline')
rev = await get_alembic_current(engine)
assert rev == '0001_baseline', f'Expected 0001_baseline, got {rev}'
print(f'Stamped: {rev}')
# Upgrade to head
await run_alembic_upgrade(engine, 'head')
rev = await get_alembic_current(engine)
print(f'After upgrade: {rev}')
assert rev is not None, 'Expected a revision after upgrade'
# Verify idempotent
await run_alembic_upgrade(engine, 'head')
rev2 = await get_alembic_current(engine)
assert rev2 == rev, f'Expected {rev}, got {rev2}'
print(f'Idempotent check passed: {rev2}')
# Fresh DB: upgrade from scratch
engine2 = create_async_engine('sqlite+aiosqlite:///test_migrations_fresh.db')
async with engine2.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
await run_alembic_upgrade(engine2, 'head')
rev3 = await get_alembic_current(engine2)
print(f'Fresh DB upgrade: {rev3}')
assert rev3 is not None
print('All SQLite migration tests passed!')
asyncio.run(main())
"
test-migrations-postgres:
name: Migrations (PostgreSQL)
runs-on: ubuntu-latest
services:
postgres:
image: postgres:16
env:
POSTGRES_USER: langbot
POSTGRES_PASSWORD: langbot
POSTGRES_DB: langbot_test
ports:
- 5432:5432
options: >-
--health-cmd="pg_isready -U langbot"
--health-interval=5s
--health-timeout=5s
--health-retries=5
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: Test Alembic upgrade (PostgreSQL)
run: |
uv run python -c "
import asyncio
from sqlalchemy.ext.asyncio import create_async_engine
from langbot.pkg.entity.persistence.base import Base
from langbot.pkg.persistence.alembic_runner import run_alembic_upgrade, run_alembic_stamp, get_alembic_current
DB_URL = 'postgresql+asyncpg://langbot:langbot@localhost:5432/langbot_test'
async def main():
engine = create_async_engine(DB_URL)
# Create all tables
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
# Stamp baseline
await run_alembic_stamp(engine, '0001_baseline')
rev = await get_alembic_current(engine)
assert rev == '0001_baseline', f'Expected 0001_baseline, got {rev}'
print(f'Stamped: {rev}')
# Upgrade to head
await run_alembic_upgrade(engine, 'head')
rev = await get_alembic_current(engine)
print(f'After upgrade: {rev}')
assert rev is not None
# Verify idempotent
await run_alembic_upgrade(engine, 'head')
rev2 = await get_alembic_current(engine)
assert rev2 == rev, f'Expected {rev}, got {rev2}'
print(f'Idempotent check passed: {rev2}')
# Fresh DB: drop all and upgrade from scratch
engine2 = create_async_engine(DB_URL.replace('langbot_test', 'langbot_fresh'))
# Create fresh database
from sqlalchemy import text
async with engine.connect() as conn:
await conn.execute(text('COMMIT'))
await conn.execute(text('CREATE DATABASE langbot_fresh'))
async with engine2.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
await run_alembic_upgrade(engine2, 'head')
rev3 = await get_alembic_current(engine2)
print(f'Fresh DB upgrade: {rev3}')
assert rev3 is not None
print('All PostgreSQL migration tests passed!')
asyncio.run(main())
"

5
.gitignore vendored
View File

@@ -42,17 +42,14 @@ botpy.log*
test.py
/web_ui
.venv/
uv.lock
/test
plugins.bak
coverage.xml
.coverage
src/langbot/web/
testsdk/
# Build artifacts
/dist
/build
*.egg-info
# Next.js build cache (legacy)
web/.next/

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

@@ -9,14 +9,16 @@ repos:
# Run the formatter of backend.
- id: ruff-format
- repo: local
- repo: https://github.com/pre-commit/mirrors-prettier
rev: v3.1.0
hooks:
- id: prettier
name: prettier
entry: npx --prefix web prettier --write --ignore-unknown
language: system
types_or: [javascript, jsx, ts, tsx, css, scss]
additional_dependencies:
- prettier@3.1.0
- repo: local
hooks:
- id: lint-staged
name: lint-staged
entry: cd web && pnpm lint-staged

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.
- LangBot uses [Alembic](https://alembic.sqlalchemy.org/) to manage database migrations, supporting both SQLite and PostgreSQL. Migration files are located in `src/langbot/pkg/persistence/alembic/versions/`. If you changed the definition of database entities (ORM models), generate a new migration script by running `uv run python -m langbot.pkg.persistence.alembic_runner autogenerate "description of your change"` in the project root (requires `data/config.yaml` to exist). Review and edit the generated script before committing. Migrations are executed automatically on LangBot startup. For data migrations (e.g. modifying JSON field content), you need to manually add the migration code in the generated script.
## Some Principles

View File

@@ -4,7 +4,7 @@ WORKDIR /app
COPY web ./web
RUN cd web && npm install && npx vite build
RUN cd web && npm install && npm run build
FROM python:3.12.7-slim
@@ -12,7 +12,7 @@ WORKDIR /app
COPY . .
COPY --from=node /app/web/dist ./web/dist
COPY --from=node /app/web/out ./web/out
RUN apt update \
&& apt install gcc -y \
@@ -20,4 +20,4 @@ RUN apt update \
&& uv sync \
&& touch /.dockerenv
CMD [ "uv", "run", "--no-sync", "main.py" ]
CMD [ "uv", "run", "main.py" ]

233
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://link.langbot.app/en/docs/features">Features</a>
<a href="https://link.langbot.app/en/docs/guide">Docs</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/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
@@ -71,106 +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://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [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 |
|----------|--------|-------|
| Discord | ✅ | Official |
| Telegram | ✅ | Official |
| Slack | ✅ | Official |
| LINE | ✅ | Official |
| QQ | ✅ | Personal & Official API (Channel, DM, Group) |
| WeCom | ✅ | Enterprise WeChat, External CS, AI Bot |
| WeChat | ✅ | Personal & Official Account |
| Lark | ✅ | Official |
| DingTalk | ✅ | Official |
| KOOK | ✅ | Official |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Supports multiple bridged platforms such as Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, and more |
参考 [Kubernetes 部署](./docker/README_K8S.md) 文档。
---
## 😎 保持更新
## Supported LLMs & Integrations
点击仓库右上角 Star 和 Watch 按钮,获取最新动态。
| 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | Gateway | ✅ |
![star gif](https://docs.langbot.app/star.gif)
[→ View all integrations](https://link.langbot.app/en/docs/features)
## ✨ 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。
## Why LangBot?
详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
| 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 |
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
## Live Demo
| 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 | ✅ | |
**Try it now:** https://demo.langbot.dev/
### 大模型能力
- Email: `demo@langbot.app`
- Password: `langbot123456`
| 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 |
_Note: Public demo environment. Do not enter sensitive information._
### TTS
---
| 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) |
## Community
### 文生图
[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
| 平台/模型 | 备注 |
| --- | --- |
| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
- [Discord Community](https://discord.gg/wdNEHETs87)
## 😘 社区贡献
---
## 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

@@ -1,199 +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://link.langbot.app/zh/docs/features">特性</a>
<a href="https://link.langbot.app/zh/docs/guide">文档</a>
<a href="https://link.langbot.app/zh/docs/api">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>
---
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,跨进程的事件驱动架构,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://link.langbot.app/zh/docs/features)
---
## 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://link.langbot.app/zh/docs/docker) · [手动部署](https://link.langbot.app/zh/docs/manual-deploy) · [宝塔面板](https://link.langbot.app/zh/docs/bt-panel) · [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 | ✅ | 官方 |
| 钉钉 | ✅ | 官方 |
| Satori | ✅ | |
| Discord | ✅ | 官方 |
| Telegram | ✅ | 官方 |
| Slack | ✅ | 官方 |
| LINE | ✅ | 官方 |
| KOOK | ✅ | 官方 |
| Email | ✅ | 只 Matrix、Satori |
| Matrix | ✅ | 支持多种桥接平台,如 Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip 等 |
---
## 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 | ✅ |
| [七牛云Qiniu](https://www.qiniu.com/ai/agent) | 聚合平台 | ✅ |
[→ 查看完整集成列表](https://link.langbot.app/zh/docs/features)
### 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
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<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

@@ -1,174 +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://link.langbot.app/en/docs/features">Características</a>
<a href="https://link.langbot.app/en/docs/guide">Documentación</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
---
## Plataformas Soportadas
| Plataforma | Estado | Notas |
|----------|--------|-------|
| Discord | ✅ | Oficial |
| Telegram | ✅ | Oficial |
| Slack | ✅ | Oficial |
| LINE | ✅ | Oficial |
| QQ | ✅ | Personal y API Oficial (Canal, DM, Grupo) |
| WeCom | ✅ | WeChat Empresarial, CS Externo, AI Bot |
| WeChat | ✅ | Personal y Cuenta Oficial |
| Lark | ✅ | Oficial |
| DingTalk | ✅ | Oficial |
| KOOK | ✅ | Oficial |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Admite varias plataformas puenteadas como Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip y más |
---
## 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | Pasarela | ✅ |
[→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)
---
## ¿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>

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@@ -1,174 +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://link.langbot.app/en/docs/features">Fonctionnalités</a>
<a href="https://link.langbot.app/en/docs/guide">Documentation</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/en/docs/docker) · [Manuel](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
---
## Plateformes Supportées
| Plateforme | Statut | Notes |
|----------|--------|-------|
| Discord | ✅ | Officiel |
| Telegram | ✅ | Officiel |
| Slack | ✅ | Officiel |
| LINE | ✅ | Officiel |
| QQ | ✅ | Personnel & API Officielle (Canal, DM, Groupe) |
| WeCom | ✅ | WeChat Entreprise, CS Externe, AI Bot |
| WeChat | ✅ | Personnel & Compte Officiel |
| Lark | ✅ | Officiel |
| DingTalk | ✅ | Officiel |
| KOOK | ✅ | Officiel |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Prend en charge plusieurs plateformes via ponts, comme Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, etc. |
---
## 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | Passerelle | ✅ |
[→ Voir toutes les intégrations](https://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/ja/docs/features">機能</a>
<a href="https://link.langbot.app/ja/docs/guide">ドキュメント</a>
<a href="https://link.langbot.app/ja/docs/api">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://link.langbot.app/ja/docs/features)
---
## 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
@@ -70,104 +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://link.langbot.app/en/docs/docker) · [手動デプロイ](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [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 | ✅ | 公式 |
| Telegram | ✅ | 公式 |
| Slack | ✅ | 公式 |
| LINE | ✅ | 公式 |
| QQ | ✅ | 個人・公式APIチャンネル・DM・グループ |
| WeCom | ✅ | 企業WeChat、外部CS、AIボット |
| WeChat | ✅ | 個人・公式アカウント |
| Lark | ✅ | 公式 |
| DingTalk | ✅ | 公式 |
| KOOK | ✅ | 公式 |
| Satori | ✅ | |
| Email | ✅ | Matrix、Satori |
| Matrix | ✅ | Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip など複数のブリッジ先プラットフォームに対応 |
| --- | --- | --- |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| 個人QQ | ✅ | |
| QQ公式API | ✅ | |
| WeCom | ✅ | |
| WeComCS | ✅ | |
| WeCom AI Bot | ✅ | |
| 個人WeChat | ✅ | |
| Lark | ✅ | |
| DingTalk | ✅ | |
---
### 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | ゲートウェイ | ✅ |
## 🤝 コミュニティ貢献
[→ すべての統合を表示](https://link.langbot.app/en/docs/features)
---
## 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

@@ -1,174 +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://link.langbot.app/en/docs/features">기능</a>
<a href="https://link.langbot.app/en/docs/guide">문서</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/en/docs/docker) · [수동 배포](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
---
## 지원 플랫폼
| 플랫폼 | 상태 | 비고 |
|--------|------|------|
| Discord | ✅ | 공식 |
| Telegram | ✅ | 공식 |
| Slack | ✅ | 공식 |
| LINE | ✅ | 공식 |
| QQ | ✅ | 개인 및 공식 API (채널, DM, 그룹) |
| WeCom | ✅ | 기업 WeChat, 외부 CS, AI Bot |
| WeChat | ✅ | 개인 및 공식 계정 |
| Lark | ✅ | 공식 |
| DingTalk | ✅ | 공식 |
| KOOK | ✅ | 공식 |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip 등 여러 브리지 플랫폼 지원 |
---
## 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | 게이트웨이 | ✅ |
[→ 모든 통합 보기](https://link.langbot.app/en/docs/features)
---
## 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

@@ -1,174 +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://link.langbot.app/en/docs/features">Возможности</a>
<a href="https://link.langbot.app/en/docs/guide">Документация</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/en/docs/docker) · [Ручная установка](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
---
## Поддерживаемые платформы
| Платформа | Статус | Примечания |
|-----------|--------|------------|
| Discord | ✅ | Официальный |
| Telegram | ✅ | Официальный |
| Slack | ✅ | Официальный |
| LINE | ✅ | Официальный |
| QQ | ✅ | Личный и официальный API (Канал, ЛС, Группа) |
| WeCom | ✅ | Корпоративный WeChat, внешний CS, AI-бот |
| WeChat | ✅ | Личный и официальный аккаунт |
| Lark | ✅ | Официальный |
| DingTalk | ✅ | Официальный |
| KOOK | ✅ | Официальный |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Поддерживает несколько платформ через мосты, включая Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip и другие |
---
## 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | Шлюз | ✅ |
[→ Смотреть все интеграции](https://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/zh/docs/features">特性</a>
<a href="https://link.langbot.app/zh/docs/guide">文件</a>
<a href="https://link.langbot.app/zh/docs/api">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://link.langbot.app/zh/docs/features)
---
## 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
@@ -72,66 +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://link.langbot.app/zh/docs/docker) · [手動部署](https://link.langbot.app/zh/docs/manual-deploy) · [寶塔面板](https://link.langbot.app/zh/docs/bt-panel) · [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 |
|------|------|------|
| Discord | ✅ | 官方 |
| Telegram | ✅ | 官方 |
| Slack | ✅ | 官方 |
| LINE | ✅ | 官方 |
| QQ | ✅ | 個人號、官方機器人(頻道、私聊、群聊 |
| 企業微信 | ✅ | 應用訊息、對外客服、智能機器人 |
| 微信 | ✅ | 個人微信、微信公眾號 |
| 飛書 | ✅ | 官方 |
| 釘釘 | ✅ | 官方 |
| KOOK | ✅ | 官方 |
| Satori | ✅ | |
| Email | ✅ | 只 Matrix、Satori |
| Matrix | ✅ | 支援多種橋接平台,如 Signal、WhatsApp、Messenger、iMessage、Mattermost、Google Chat、IRC、XMPP、Zulip 等 |
| --- | --- | --- |
| Discord | ✅ | |
| Telegram | ✅ | |
| Slack | ✅ | |
| LINE | ✅ | |
| 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | 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) |
@@ -139,53 +135,12 @@ 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://link.langbot.app/zh/docs/features)
## 😘 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" />

View File

@@ -1,174 +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://link.langbot.app/en/docs/features">Tính năng</a>
<a href="https://link.langbot.app/en/docs/guide">Tài liệu</a>
<a href="https://link.langbot.app/en/docs/api">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://link.langbot.app/en/docs/features)
---
## 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://link.langbot.app/en/docs/docker) · [Thủ công](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
---
## Nền tảng được hỗ trợ
| Nền tảng | Trạng thái | Ghi chú |
|----------|--------|-------|
| Discord | ✅ | Chính thức |
| Telegram | ✅ | Chính thức |
| Slack | ✅ | Chính thức |
| LINE | ✅ | Chính thức |
| QQ | ✅ | Cá nhân & API chính thức (Kênh, DM, Nhóm) |
| WeCom | ✅ | WeChat doanh nghiệp, CS bên ngoài, AI Bot |
| WeChat | ✅ | Cá nhân & Tài khoản công khai |
| Lark | ✅ | Chính thức |
| DingTalk | ✅ | Chính thức |
| KOOK | ✅ | Chính thức |
| Satori | ✅ | |
| Email | ✅ | Matrix, Satori |
| Matrix | ✅ | Hỗ trợ nhiều nền tảng qua bridge như Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip và hơn thế nữa |
---
## 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 | ✅ |
| [Qiniu](https://www.qiniu.com/ai/agent) | Cổng | ✅ |
[→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)
---
## 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

@@ -312,7 +312,7 @@ spec:
### 参考资源
- [LangBot 官方文档](https://docs.langbot.app)
- [Docker 部署文档](https://link.langbot.app/zh/docs/docker)
- [Docker 部署文档](https://docs.langbot.app/zh/deploy/langbot/docker.html)
- [Kubernetes 官方文档](https://kubernetes.io/docs/)
---
@@ -625,5 +625,5 @@ spec:
### References
- [LangBot Official Documentation](https://docs.langbot.app)
- [Docker Deployment Guide](https://link.langbot.app/zh/docs/docker)
- [Docker Deployment Guide](https://docs.langbot.app/zh/deploy/langbot/docker.html)
- [Kubernetes Official Documentation](https://kubernetes.io/docs/)

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

View File

@@ -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

@@ -1,14 +1,14 @@
[project]
name = "langbot"
version = "4.9.7"
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",
"aiohttp>=3.13.4",
"aiohttp>=3.11.18",
"aioshutil>=1.5",
"aiosqlite>=0.21.0",
"anthropic>=0.51.0",
@@ -16,18 +16,18 @@ dependencies = [
"async-lru>=2.0.5",
"certifi>=2025.4.26",
"colorlog~=6.6.0",
"cryptography>=46.0.7",
"dashscope>=1.25.10",
"cryptography>=44.0.3",
"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>=1.5.5",
"mcp>=1.25.0",
"lark-oapi>=1.4.15",
"mcp>=1.8.1",
"nakuru-project-idk>=0.0.2.1",
"ollama>=0.4.8",
"openai>1.0.0",
"pillow>=12.2.0",
"pillow>=11.2.1",
"psutil>=7.0.0",
"pycryptodome>=3.22.0",
"pydantic>2.0",
@@ -35,12 +35,10 @@ dependencies = [
"python-telegram-bot>=22.0",
"pyyaml>=6.0.2",
"qq-botpy-rc>=1.2.1.6",
"qrcode>=7.4",
"quart>=0.20.0",
"quart-cors>=0.8.0",
"requests>=2.32.3",
"slack-sdk>=3.35.0",
"alembic>=1.15.0",
"sqlalchemy[asyncio]>=2.0.40",
"sqlmodel>=0.0.24",
"telegramify-markdown>=0.5.1",
@@ -51,7 +49,7 @@ dependencies = [
"pip>=25.1.1",
"ruff>=0.11.9",
"pre-commit>=4.2.0",
"uv>=0.11.6",
"uv>=0.7.11",
"mypy>=1.16.0",
"PyPDF2>=3.0.1",
"python-docx>=1.1.0",
@@ -62,23 +60,14 @@ dependencies = [
"ebooklib>=0.18",
"html2text>=2024.2.26",
"langchain>=0.2.0",
"langchain-core>=1.2.28",
"langsmith>=0.7.31",
"python-multipart>=0.0.26",
"Mako>=1.3.11",
"langchain-text-splitters>=1.1.2",
"chromadb>=1.0.0,<2.0.0",
"langchain-text-splitters>=0.0.1",
"chromadb>=0.4.24",
"qdrant-client (>=1.15.1,<2.0.0)",
"pyseekdb==1.1.0.post3",
"langbot-plugin==0.3.11",
"langbot-plugin==0.1.11b1",
"asyncpg>=0.30.0",
"line-bot-sdk>=3.19.0",
"matrix-nio>=0.25.2",
"tboxsdk>=0.0.10",
"boto3>=1.35.0",
"pymilvus>=2.6.4",
"pgvector>=0.4.1",
"botocore>=1.42.39",
]
keywords = [
"bot",
@@ -118,12 +107,12 @@ requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"
[tool.setuptools]
package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/dist/**", "pkg/persistence/alembic/**"] }
package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/out/**"] }
[dependency-groups]
dev = [
"pre-commit>=4.2.0",
"pytest>=9.0.3",
"pytest>=8.4.1",
"pytest-asyncio>=1.0.0",
"pytest-cov>=7.0.0",
"ruff>=0.11.9",

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__ = '4.9.7'
__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'
@@ -174,96 +170,11 @@ 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]:
await handler(event)
async def _parse_quoted_message(self, replied_msg: dict) -> dict:
"""Parse the quoted/replied message and extract its content.
Args:
replied_msg: The repliedMsg object from DingTalk message
Returns:
A dict containing the quoted message info with keys:
- message_id: The original message ID
- msg_type: The message type (text, file, picture, audio, etc.)
- content: The text content (if any)
- file_url: The file download URL (if file type)
- file_name: The file name (if file type)
- picture: The picture base64 (if picture type)
- audio: The audio base64 (if audio type)
"""
quote_info = {
'message_id': replied_msg.get('msgId', ''),
'msg_type': replied_msg.get('msgType', ''),
'sender_id': replied_msg.get('senderId', ''),
}
msg_type = replied_msg.get('msgType', '')
content = replied_msg.get('content', {})
# Handle content as string (JSON) or dict
if isinstance(content, str):
try:
content = json.loads(content)
except (json.JSONDecodeError, TypeError):
content = {}
if msg_type == 'text':
# Text message
if isinstance(content, dict):
quote_info['content'] = content.get('content', '')
else:
quote_info['content'] = str(content)
elif msg_type == 'file':
# File message
download_code = content.get('downloadCode')
file_name = content.get('fileName')
if download_code and file_name:
try:
quote_info['file_url'] = await self.get_file_url(download_code)
quote_info['file_name'] = file_name
except Exception as e:
if self.logger:
await self.logger.error(f'Failed to get quoted file URL: {e}')
elif msg_type == 'picture':
# Picture message
download_code = content.get('downloadCode')
if download_code:
try:
quote_info['picture'] = await self.download_image(download_code)
except Exception as e:
if self.logger:
await self.logger.error(f'Failed to download quoted image: {e}')
elif msg_type == 'audio':
# Audio message
download_code = content.get('downloadCode')
if download_code:
try:
quote_info['audio'] = await self.get_audio_url(download_code)
except Exception as e:
if self.logger:
await self.logger.error(f'Failed to get quoted audio: {e}')
elif msg_type == 'richText':
# Rich text message - extract text content
rich_text = content.get('richText', [])
texts = []
for item in rich_text:
if 'text' in item and item['text'] != '\n':
texts.append(item['text'])
quote_info['content'] = '\n'.join(texts)
return quote_info
async def get_message(self, incoming_message: dingtalk_stream.chatbot.ChatbotMessage):
try:
# print(json.dumps(incoming_message.to_dict(), indent=4, ensure_ascii=False))
@@ -275,15 +186,6 @@ class DingTalkClient:
elif str(incoming_message.conversation_type) == '2':
message_data['conversation_type'] = 'GroupMessage'
# Check for quoted/replied message
raw_data = incoming_message.to_dict()
text_data = raw_data.get('text', {})
if isinstance(text_data, dict) and text_data.get('isReplyMsg'):
replied_msg = text_data.get('repliedMsg', {})
if replied_msg:
quote_info = await self._parse_quoted_message(replied_msg)
message_data['QuotedMessage'] = quote_info
if incoming_message.message_type == 'richText':
data = incoming_message.rich_text_content.to_dict()
@@ -359,52 +261,19 @@ class DingTalkClient:
message_data['Type'] = 'image'
elif incoming_message.message_type == 'audio':
raw_content = incoming_message.to_dict().get('content', {})
# 兼容处理:如果 content 仍为 JSON 字符串则进行解析
if isinstance(raw_content, str):
try:
raw_content = json.loads(raw_content)
except (json.JSONDecodeError, TypeError):
raw_content = {}
if self.logger:
await self.logger.info(f'DingTalk audio raw content: {json.dumps(raw_content, ensure_ascii=False)}')
# 提取钉钉自带的语音转写文字Powered by Qwen
recognition = raw_content.get('recognition', '')
if recognition:
message_data['Content'] = recognition
download_code = raw_content.get('downloadCode')
if download_code:
message_data['Audio'] = await self.get_audio_url(download_code)
message_data['Audio'] = await self.get_audio_url(incoming_message.to_dict()['content']['downloadCode'])
message_data['Type'] = 'audio'
elif incoming_message.message_type == 'file':
# 获取原始数据字典并提取嵌套的文件信息
raw_data = incoming_message.to_dict()
file_info = raw_data.get('content', {})
# 兼容处理:如果 content 仍为 JSON 字符串则进行解析
if isinstance(file_info, str):
try:
file_info = json.loads(file_info)
except (json.JSONDecodeError, TypeError):
file_info = {}
download_code = file_info.get('downloadCode')
file_name = file_info.get('fileName')
if download_code and file_name:
# 转换 downloadCode 为可下载的真实 URL
message_data['File'] = await self.get_file_url(download_code)
message_data['Name'] = file_name
down_list = incoming_message.get_down_list()
if len(down_list) >= 2:
message_data['File'] = await self.get_file_url(down_list[0])
message_data['Name'] = down_list[1]
else:
if self.logger:
await self.logger.error(f'Failed to extract file info from message content: {file_info}')
await self.logger.error(f'get_down_list() returned fewer than 2 elements: {down_list}')
message_data['File'] = None
message_data['Name'] = None
message_data['Type'] = 'file'
copy_message_data = message_data.copy()
@@ -471,21 +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'] = ''
# 将用户的消息内容作为卡片的查询参数,方便后续处理
if incoming_message.message_type == 'text':
card_data['query'] = incoming_message.get_text_list()[0]
else:
card_data['query'] = '...'
content_key = 'content'
card_data = {content_key: ''}
card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message)
# print(card_instance)
@@ -520,70 +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

@@ -47,22 +47,6 @@ class DingTalkEvent(dict):
def conversation(self):
return self.get('conversation_type', '')
@property
def quoted_message(self) -> Optional[Dict[str, Any]]:
"""Get the quoted/replied message info if this is a reply message.
Returns:
A dict containing:
- message_id: The original message ID
- msg_type: The message type (text, file, picture, audio, etc.)
- content: The text content (if any)
- file_url: The file download URL (if file type)
- file_name: The file name (if file type)
- picture: The picture base64 (if picture type)
- audio: The audio base64 (if audio type)
"""
return self.get('QuotedMessage')
def __getattr__(self, key: str) -> Optional[Any]:
"""
允许通过属性访问数据中的任意字段。

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

@@ -1,3 +0,0 @@
from .client import OpenClawWeixinClient as OpenClawWeixinClient
from .types import ApiError as ApiError
from .types import LoginResult as LoginResult

View File

@@ -1,807 +0,0 @@
"""Async HTTP client for the OpenClaw WeChat API.
Implements the iLink Bot API protocol.
Reference: https://github.com/epiral/weixin-bot
Endpoints: getUpdates (long-poll), sendMessage, getUploadUrl, getConfig, sendTyping.
"""
from __future__ import annotations
import asyncio
import base64
import io
import logging
import os
import struct
import typing
import uuid
from typing import Optional
from urllib.parse import quote
import aiohttp
from .types import (
ApiError,
CDNMedia,
FileItem,
GetConfigResponse,
GetUpdatesResponse,
GetUploadUrlResponse,
ImageItem,
LoginResult,
MessageItem,
QRCodeResponse,
QRStatusResponse,
RefMessage,
TextItem,
VideoItem,
VoiceItem,
WeixinMessage,
)
logger = logging.getLogger('openclaw-weixin-sdk')
DEFAULT_BASE_URL = 'https://ilinkai.weixin.qq.com'
CDN_BASE_URL = 'https://novac2c.cdn.weixin.qq.com/c2c'
CHANNEL_VERSION = '1.0.0'
DEFAULT_API_TIMEOUT = 15
DEFAULT_LONG_POLL_TIMEOUT = 40
DEFAULT_CONFIG_TIMEOUT = 10
DEFAULT_QR_POLL_TIMEOUT = 35
SESSION_EXPIRED_ERRCODE = -14
DEFAULT_BOT_TYPE = '3'
# Maximum text length per message chunk (WeChat limit)
MAX_TEXT_CHUNK_SIZE = 2000
def _random_wechat_uin() -> str:
"""Generate the X-WECHAT-UIN header: random uint32 -> decimal string -> base64."""
rand_bytes = os.urandom(4)
uint32_val = struct.unpack('>I', rand_bytes)[0]
return base64.b64encode(str(uint32_val).encode('utf-8')).decode('utf-8')
def _build_base_info() -> dict:
"""Build the base_info payload included in every API request."""
return {'channel_version': CHANNEL_VERSION}
def _chunk_text(text: str, max_size: int = MAX_TEXT_CHUNK_SIZE) -> list[str]:
"""Split long text into chunks that fit within WeChat's message size limit."""
if len(text) <= max_size:
return [text]
chunks = []
while text:
chunks.append(text[:max_size])
text = text[max_size:]
return chunks
class OpenClawWeixinClient:
"""Async client for the OpenClaw WeChat HTTP JSON API."""
def __init__(self, base_url: str, token: str):
self.base_url = base_url.rstrip('/')
self.token = token
self._session: Optional[aiohttp.ClientSession] = None
async def _get_session(self) -> aiohttp.ClientSession:
if self._session is None or self._session.closed:
self._session = aiohttp.ClientSession()
return self._session
async def close(self):
if self._session and not self._session.closed:
await self._session.close()
def _build_headers(self) -> dict[str, str]:
headers = {
'Content-Type': 'application/json',
'AuthorizationType': 'ilink_bot_token',
'X-WECHAT-UIN': _random_wechat_uin(),
}
if self.token:
headers['Authorization'] = f'Bearer {self.token}'
return headers
async def _post(self, endpoint: str, payload: dict, timeout: float = DEFAULT_API_TIMEOUT) -> dict:
"""Make a POST request and return the JSON response.
Raises ApiError on HTTP errors or when the response contains a non-zero errcode.
"""
payload['base_info'] = _build_base_info()
session = await self._get_session()
url = f'{self.base_url}/{endpoint}'
headers = self._build_headers()
async with session.post(
url, json=payload, headers=headers, timeout=aiohttp.ClientTimeout(total=timeout)
) as resp:
if resp.status != 200:
text = await resp.text()
raise ApiError(
f'OpenClaw API error {resp.status}: {text}',
status=resp.status,
)
data = await resp.json(content_type=None)
# Check for application-level errors in the response body
errcode = data.get('errcode') or data.get('ret')
if errcode and errcode != 0:
raise ApiError(
data.get('errmsg') or f'API errcode {errcode}',
status=200,
code=errcode,
payload=data,
)
return data
async def get_updates(
self, get_updates_buf: str = '', timeout: float = DEFAULT_LONG_POLL_TIMEOUT
) -> GetUpdatesResponse:
"""Long-poll for new messages.
Note: This method does NOT raise ApiError for errcode responses —
it returns them in the GetUpdatesResponse so the caller can handle
session expiry and other errors with full context.
"""
try:
# Bypass the errcode check in _post since get_updates needs
# to return error info (e.g. session expired) to the caller.
payload: dict = {'get_updates_buf': get_updates_buf}
payload['base_info'] = _build_base_info()
session = await self._get_session()
url = f'{self.base_url}/ilink/bot/getupdates'
headers = self._build_headers()
async with session.post(
url,
json=payload,
headers=headers,
timeout=aiohttp.ClientTimeout(total=timeout),
) as resp:
if resp.status != 200:
text = await resp.text()
raise ApiError(
f'OpenClaw API error {resp.status}: {text}',
status=resp.status,
)
data = await resp.json(content_type=None)
except (asyncio.TimeoutError, aiohttp.ServerTimeoutError):
return GetUpdatesResponse(ret=0, msgs=[], get_updates_buf=get_updates_buf)
except ApiError:
raise
except Exception as e:
if 'timeout' in str(e).lower():
return GetUpdatesResponse(ret=0, msgs=[], get_updates_buf=get_updates_buf)
raise
return _parse_get_updates_response(data)
async def send_message(
self,
to_user_id: str,
item_list: list[MessageItem],
context_token: str = '',
) -> None:
"""Send a message to a user."""
items_payload = [_message_item_to_dict(item) for item in item_list]
payload = {
'msg': {
'from_user_id': '',
'to_user_id': to_user_id,
'client_id': f'langbot-{uuid.uuid4().hex[:16]}',
'message_type': WeixinMessage.TYPE_BOT,
'message_state': WeixinMessage.STATE_FINISH,
'item_list': items_payload,
'context_token': context_token or None,
}
}
await self._post('ilink/bot/sendmessage', payload)
async def send_text(self, to_user_id: str, text: str, context_token: str = '') -> None:
"""Send a plain text message, automatically chunking if too long."""
chunks = _chunk_text(text)
for chunk in chunks:
item = MessageItem(type=MessageItem.TEXT, text_item=TextItem(text=chunk))
await self.send_message(to_user_id, [item], context_token)
async def get_config(self, ilink_user_id: str, context_token: str = '') -> GetConfigResponse:
"""Get bot config including typing_ticket."""
data = await self._post(
'ilink/bot/getconfig',
{'ilink_user_id': ilink_user_id, 'context_token': context_token or None},
timeout=DEFAULT_CONFIG_TIMEOUT,
)
return GetConfigResponse(
ret=data.get('ret'),
errmsg=data.get('errmsg'),
typing_ticket=data.get('typing_ticket'),
)
async def send_typing(self, ilink_user_id: str, typing_ticket: str, status: int = 1) -> None:
"""Send typing indicator. status: 1=typing, 2=cancel."""
await self._post(
'ilink/bot/sendtyping',
{
'ilink_user_id': ilink_user_id,
'typing_ticket': typing_ticket,
'status': status,
},
timeout=DEFAULT_CONFIG_TIMEOUT,
)
async def stop_typing(self, ilink_user_id: str, typing_ticket: str) -> None:
"""Cancel the typing indicator for a user."""
await self.send_typing(ilink_user_id, typing_ticket, status=2)
async def download_media(
self,
media: CDNMedia,
) -> bytes:
"""Download and decrypt a file from the WeChat CDN.
Args:
media: CDNMedia object with encrypt_query_param and aes_key.
Returns:
Decrypted file bytes.
"""
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives.padding import PKCS7
if not media.encrypt_query_param:
raise ApiError('CDN media has no encrypt_query_param', status=0)
if not media.aes_key:
raise ApiError('CDN media has no aes_key', status=0)
# Derive 16-byte AES key
# aes_key is base64-encoded; the decoded content may be:
# - raw 16 bytes (direct AES key)
# - 32-char hex string (decode hex to get 16 bytes)
raw = base64.b64decode(media.aes_key)
if len(raw) == 16:
aes_key = raw
elif len(raw) == 32:
# Hex-encoded 16-byte key
aes_key = bytes.fromhex(raw.decode('utf-8'))
else:
raise ApiError(f'Invalid AES key length: {len(raw)} (expected 16 or 32)', status=0)
# Download encrypted bytes from CDN
session = await self._get_session()
cdn_url = f'{CDN_BASE_URL}/download?encrypted_query_param={quote(media.encrypt_query_param, safe="")}'
async with session.get(cdn_url, timeout=aiohttp.ClientTimeout(total=120)) as resp:
if resp.status != 200:
text = await resp.text()
raise ApiError(f'CDN download failed: {resp.status} {text}', status=resp.status)
encrypted = await resp.read()
# Decrypt AES-128-ECB with PKCS7 padding
cipher = Cipher(algorithms.AES(aes_key), modes.ECB())
decryptor = cipher.decryptor()
padded = decryptor.update(encrypted) + decryptor.finalize()
unpadder = PKCS7(128).unpadder()
return unpadder.update(padded) + unpadder.finalize()
async def upload_media(
self,
file_bytes: bytes,
to_user_id: str,
media_type: int,
) -> CDNMedia:
"""Encrypt and upload media to WeChat CDN.
Args:
file_bytes: Raw file bytes to upload.
to_user_id: Recipient user ID.
media_type: 1=IMAGE, 2=VIDEO, 3=FILE, 4=VOICE.
Returns:
CDNMedia with encrypt_query_param and aes_key for use in sendMessage.
"""
import hashlib
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives.padding import PKCS7
# 1. Generate random 16-byte AES key
raw_key = os.urandom(16)
aes_key_hex = raw_key.hex() # 32-char hex string
# 2. Encode key for CDNMedia: base64(hex_string) — same for all media types
# Matches official SDK: Buffer.from(aeskey_hex).toString("base64")
encoded_key = base64.b64encode(aes_key_hex.encode('utf-8')).decode('utf-8')
# 3. Encrypt file with AES-128-ECB + PKCS7
padder = PKCS7(128).padder()
padded = padder.update(file_bytes) + padder.finalize()
cipher = Cipher(algorithms.AES(raw_key), modes.ECB())
encryptor = cipher.encryptor()
encrypted = encryptor.update(padded) + encryptor.finalize()
# 4. Get upload URL
raw_md5 = hashlib.md5(file_bytes).hexdigest()
filekey = os.urandom(16).hex() # 32-char hex, matches official SDK
upload_resp = await self.get_upload_url(
filekey=filekey,
media_type=media_type,
to_user_id=to_user_id,
rawsize=len(file_bytes),
rawfilemd5=raw_md5,
filesize=len(encrypted),
aeskey=aes_key_hex, # hex string, as expected by the API
)
if not upload_resp.upload_param:
raise ApiError('Failed to get upload URL', status=0)
# 5. Upload to CDN
# upload_param is an opaque token from the server — pass it as-is
session = await self._get_session()
cdn_url = f'{CDN_BASE_URL}/upload?encrypted_query_param={quote(upload_resp.upload_param, safe="")}&filekey={quote(filekey, safe="")}'
logger.debug(
'CDN upload: url=%s raw_size=%d encrypted_size=%d md5=%s aeskey=%s',
cdn_url,
len(file_bytes),
len(encrypted),
raw_md5,
encoded_key,
)
async with session.post(
cdn_url,
data=encrypted,
headers={'Content-Type': 'application/octet-stream'},
timeout=aiohttp.ClientTimeout(total=120),
) as resp:
if resp.status != 200:
text = await resp.text()
logger.error('CDN upload failed: status=%d url=%s body=%s', resp.status, cdn_url, text[:500])
raise ApiError(f'CDN upload failed: {resp.status} {text}', status=resp.status)
download_param = resp.headers.get('x-encrypted-param', '')
if not download_param:
raise ApiError('CDN upload succeeded but no x-encrypted-param returned', status=0)
return CDNMedia(
encrypt_query_param=download_param,
aes_key=encoded_key,
encrypt_type=1,
)
async def send_image(
self,
to_user_id: str,
image_bytes: bytes,
context_token: str = '',
) -> None:
"""Upload an image to CDN and send it."""
media = await self.upload_media(image_bytes, to_user_id, media_type=1)
item = MessageItem(
type=MessageItem.IMAGE,
image_item=ImageItem(
media=media,
aeskey=media.aes_key,
),
)
await self.send_message(to_user_id, [item], context_token)
async def send_file(
self,
to_user_id: str,
file_bytes: bytes,
file_name: str,
context_token: str = '',
) -> None:
"""Upload a file to CDN and send it."""
import hashlib
media = await self.upload_media(file_bytes, to_user_id, media_type=3)
item = MessageItem(
type=MessageItem.FILE,
file_item=FileItem(
media=media,
file_name=file_name,
md5=hashlib.md5(file_bytes).hexdigest(),
len=str(len(file_bytes)),
),
)
await self.send_message(to_user_id, [item], context_token)
async def send_voice(
self,
to_user_id: str,
voice_bytes: bytes,
playtime: int = 0,
context_token: str = '',
) -> None:
"""Upload a voice message to CDN and send it."""
media = await self.upload_media(voice_bytes, to_user_id, media_type=4)
item = MessageItem(
type=MessageItem.VOICE,
voice_item=VoiceItem(
media=media,
playtime=playtime,
),
)
await self.send_message(to_user_id, [item], context_token)
async def get_upload_url(
self,
filekey: str,
media_type: int,
to_user_id: str,
rawsize: int,
rawfilemd5: str,
filesize: int,
thumb_rawsize: Optional[int] = None,
thumb_rawfilemd5: Optional[str] = None,
thumb_filesize: Optional[int] = None,
aeskey: Optional[str] = None,
) -> GetUploadUrlResponse:
"""Get a pre-signed CDN upload URL."""
payload: dict = {
'filekey': filekey,
'media_type': media_type,
'to_user_id': to_user_id,
'rawsize': rawsize,
'rawfilemd5': rawfilemd5,
'filesize': filesize,
'no_need_thumb': True,
}
if thumb_rawsize is not None:
payload['thumb_rawsize'] = thumb_rawsize
if thumb_rawfilemd5 is not None:
payload['thumb_rawfilemd5'] = thumb_rawfilemd5
if thumb_filesize is not None:
payload['thumb_filesize'] = thumb_filesize
if aeskey is not None:
payload['aeskey'] = aeskey
data = await self._post('ilink/bot/getuploadurl', payload)
logger.debug('get_upload_url response: %s', data)
return GetUploadUrlResponse(
upload_param=data.get('upload_param'),
thumb_upload_param=data.get('thumb_upload_param'),
)
# -----------------------------------------------------------------------
# QR Code Login
# -----------------------------------------------------------------------
async def fetch_qrcode(self, bot_type: str = DEFAULT_BOT_TYPE) -> QRCodeResponse:
"""Fetch a QR code for WeChat login authorization (GET, no auth needed)."""
session = await self._get_session()
url = f'{self.base_url}/ilink/bot/get_bot_qrcode?bot_type={bot_type}'
async with session.get(url, timeout=aiohttp.ClientTimeout(total=DEFAULT_API_TIMEOUT)) as resp:
if resp.status != 200:
text = await resp.text()
raise ApiError(
f'Failed to fetch QR code: {resp.status} {text}',
status=resp.status,
)
data = await resp.json(content_type=None)
logger.debug(
'fetch_qrcode response: qrcode=%s, img=%s', data.get('qrcode'), bool(data.get('qrcode_img_content'))
)
return QRCodeResponse(
qrcode=data.get('qrcode'),
qrcode_img_content=data.get('qrcode_img_content'),
)
async def _fetch_qr_image_base64(self, url: str) -> str:
"""Generate a QR code image from the URL and return a data URI string.
The qrcode_img_content URL points to an HTML page (not a raw image),
so we generate the QR code locally using the qrcode library.
"""
import qrcode
qr = qrcode.QRCode(error_correction=qrcode.constants.ERROR_CORRECT_L)
qr.add_data(url)
qr.make(fit=True)
img = qr.make_image(fill_color='black', back_color='white')
buf = io.BytesIO()
img.save(buf, format='PNG')
b64 = base64.b64encode(buf.getvalue()).decode('utf-8')
return f'data:image/png;base64,{b64}'
async def poll_qrcode_status(self, qrcode: str) -> QRStatusResponse:
"""Long-poll the QR code scan status (GET with iLink-App-ClientVersion header)."""
session = await self._get_session()
url = f'{self.base_url}/ilink/bot/get_qrcode_status?qrcode={quote(qrcode, safe="")}'
headers = {'iLink-App-ClientVersion': '1'}
try:
async with session.get(
url, headers=headers, timeout=aiohttp.ClientTimeout(total=DEFAULT_QR_POLL_TIMEOUT)
) as resp:
if resp.status != 200:
text = await resp.text()
raise ApiError(
f'Failed to poll QR status: {resp.status} {text}',
status=resp.status,
)
data = await resp.json(content_type=None)
logger.debug('QR status poll response: %s', data)
except (asyncio.TimeoutError, aiohttp.ServerTimeoutError):
return QRStatusResponse(status='wait')
return QRStatusResponse(
status=data.get('status'),
bot_token=data.get('bot_token'),
ilink_bot_id=data.get('ilink_bot_id'),
baseurl=data.get('baseurl'),
ilink_user_id=data.get('ilink_user_id'),
)
async def login(
self,
max_retries: int = 5,
poll_timeout_ms: int = 480_000,
on_qrcode: Optional[typing.Callable[[str, str], typing.Any]] = None,
on_status: Optional[typing.Callable[[str], typing.Any]] = None,
) -> LoginResult:
"""Complete QR code login flow with auto-retry on expiry.
Args:
max_retries: Max number of QR code refreshes on expiry.
poll_timeout_ms: Timeout per QR code in milliseconds.
on_qrcode: Callback(qr_image_base64, qr_url) called each time a
new QR code is fetched. Use this to display the QR code.
on_status: Callback(status_str) called on each status poll change.
Returns:
LoginResult with token, base_url, and account_id.
Raises:
ApiError: On unrecoverable API errors.
Exception: If all retries are exhausted.
"""
last_qr_base64: Optional[str] = None
for attempt in range(max_retries):
qr_resp = await self.fetch_qrcode()
if not qr_resp.qrcode or not qr_resp.qrcode_img_content:
raise ApiError('Failed to get QR code from server', status=0)
# Convert QR image to base64 and notify caller
last_qr_base64 = await self._fetch_qr_image_base64(qr_resp.qrcode_img_content)
if on_qrcode:
try:
result = on_qrcode(last_qr_base64, qr_resp.qrcode_img_content)
if asyncio.iscoroutine(result) or asyncio.isfuture(result):
await result
except Exception as e:
logger.warning('on_qrcode callback error: %s', e)
# Poll until confirmed / expired / timeout
loop = asyncio.get_running_loop()
deadline = loop.time() + poll_timeout_ms / 1000.0
while loop.time() < deadline:
try:
status_resp = await self.poll_qrcode_status(qr_resp.qrcode)
except Exception as e:
logger.error('Error polling QR status: %s', e)
await asyncio.sleep(2)
continue
if on_status:
try:
cb_result = on_status(status_resp.status or 'unknown')
if asyncio.iscoroutine(cb_result) or asyncio.isfuture(cb_result):
await cb_result
except Exception as e:
logger.warning('on_status callback error: %s', e)
if status_resp.status == 'confirmed' and status_resp.bot_token:
new_base_url = status_resp.baseurl or self.base_url
# Update this client instance as well
self.token = status_resp.bot_token
self.base_url = new_base_url.rstrip('/')
return LoginResult(
token=status_resp.bot_token,
base_url=new_base_url,
account_id=status_resp.ilink_bot_id or '',
qr_image_base64=last_qr_base64,
)
if status_resp.status == 'expired':
break # retry with a new QR code
await asyncio.sleep(1)
else:
# While-loop ended without break → poll timeout, treat as expired
pass
remaining = max_retries - attempt - 1
if remaining > 0:
logger.info('QR code expired, refreshing... (%d retries left)', remaining)
else:
raise ApiError('QR code login failed: max retries exceeded', status=0)
# Should not reach here, but just in case
raise ApiError('QR code login failed', status=0)
# ---------------------------------------------------------------------------
# Parsing helpers
# ---------------------------------------------------------------------------
def _parse_cdn_media(data: Optional[dict]) -> Optional[CDNMedia]:
if not data:
return None
return CDNMedia(
encrypt_query_param=data.get('encrypt_query_param'),
aes_key=data.get('aes_key'),
encrypt_type=data.get('encrypt_type'),
)
def _parse_message_item(data: dict) -> MessageItem:
item = MessageItem(
type=data.get('type'),
create_time_ms=data.get('create_time_ms'),
update_time_ms=data.get('update_time_ms'),
is_completed=data.get('is_completed'),
msg_id=data.get('msg_id'),
)
if data.get('text_item'):
item.text_item = TextItem(text=data['text_item'].get('text'))
if data.get('image_item'):
img = data['image_item']
item.image_item = ImageItem(
media=_parse_cdn_media(img.get('media')),
thumb_media=_parse_cdn_media(img.get('thumb_media')),
aeskey=img.get('aeskey'),
url=img.get('url'),
mid_size=img.get('mid_size'),
)
if data.get('voice_item'):
v = data['voice_item']
item.voice_item = VoiceItem(
media=_parse_cdn_media(v.get('media')),
encode_type=v.get('encode_type'),
playtime=v.get('playtime'),
text=v.get('text'),
)
if data.get('file_item'):
f = data['file_item']
item.file_item = FileItem(
media=_parse_cdn_media(f.get('media')),
file_name=f.get('file_name'),
md5=f.get('md5'),
len=f.get('len'),
)
if data.get('video_item'):
vid = data['video_item']
item.video_item = VideoItem(
media=_parse_cdn_media(vid.get('media')),
video_size=vid.get('video_size'),
play_length=vid.get('play_length'),
video_md5=vid.get('video_md5'),
thumb_media=_parse_cdn_media(vid.get('thumb_media')),
)
if data.get('ref_msg'):
ref = data['ref_msg']
item.ref_msg = RefMessage(
title=ref.get('title'),
message_item=_parse_message_item(ref['message_item']) if ref.get('message_item') else None,
)
return item
def _parse_weixin_message(data: dict) -> WeixinMessage:
msg = WeixinMessage(
seq=data.get('seq'),
message_id=data.get('message_id'),
from_user_id=data.get('from_user_id'),
to_user_id=data.get('to_user_id'),
client_id=data.get('client_id'),
create_time_ms=data.get('create_time_ms'),
session_id=data.get('session_id'),
group_id=data.get('group_id'),
message_type=data.get('message_type'),
message_state=data.get('message_state'),
context_token=data.get('context_token'),
)
if data.get('item_list'):
msg.item_list = [_parse_message_item(item) for item in data['item_list']]
return msg
def _parse_get_updates_response(data: dict) -> GetUpdatesResponse:
resp = GetUpdatesResponse(
ret=data.get('ret'),
errcode=data.get('errcode'),
errmsg=data.get('errmsg'),
get_updates_buf=data.get('get_updates_buf'),
longpolling_timeout_ms=data.get('longpolling_timeout_ms'),
)
if data.get('msgs'):
resp.msgs = [_parse_weixin_message(m) for m in data['msgs']]
return resp
def _cdn_media_to_dict(media: Optional[CDNMedia]) -> Optional[dict]:
if not media:
return None
d: dict = {}
if media.encrypt_query_param is not None:
d['encrypt_query_param'] = media.encrypt_query_param
if media.aes_key is not None:
d['aes_key'] = media.aes_key
if media.encrypt_type is not None:
d['encrypt_type'] = media.encrypt_type
return d or None
def _message_item_to_dict(item: MessageItem) -> dict:
d: dict = {'type': item.type}
if item.text_item:
d['text_item'] = {'text': item.text_item.text}
if item.image_item:
img_d: dict = {}
if item.image_item.media:
img_d['media'] = _cdn_media_to_dict(item.image_item.media)
if item.image_item.mid_size is not None:
img_d['mid_size'] = item.image_item.mid_size
d['image_item'] = img_d
if item.voice_item:
voice_d: dict = {}
if item.voice_item.media:
voice_d['media'] = _cdn_media_to_dict(item.voice_item.media)
if item.voice_item.playtime is not None:
voice_d['playtime'] = item.voice_item.playtime
d['voice_item'] = voice_d
if item.file_item:
file_d: dict = {}
if item.file_item.media:
file_d['media'] = _cdn_media_to_dict(item.file_item.media)
if item.file_item.file_name:
file_d['file_name'] = item.file_item.file_name
if item.file_item.len:
file_d['len'] = item.file_item.len
d['file_item'] = file_d
if item.video_item:
vid_d: dict = {}
if item.video_item.media:
vid_d['media'] = _cdn_media_to_dict(item.video_item.media)
if item.video_item.video_size is not None:
vid_d['video_size'] = item.video_item.video_size
d['video_item'] = vid_d
return d

View File

@@ -1,200 +0,0 @@
"""Type definitions for the OpenClaw WeChat API, mirroring the upstream protocol."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Optional
SESSION_EXPIRED_ERRCODE = -14
class ApiError(Exception):
"""Structured error raised by the OpenClaw WeChat API."""
def __init__(
self,
message: str,
*,
status: int = 0,
code: int | None = None,
payload: Any = None,
):
super().__init__(message)
self.status = status
self.code = code
self.payload = payload
@property
def is_session_expired(self) -> bool:
return self.code == SESSION_EXPIRED_ERRCODE
@dataclass
class CDNMedia:
encrypt_query_param: Optional[str] = None
aes_key: Optional[str] = None
encrypt_type: Optional[int] = None
@dataclass
class TextItem:
text: Optional[str] = None
@dataclass
class ImageItem:
media: Optional[CDNMedia] = None
thumb_media: Optional[CDNMedia] = None
aeskey: Optional[str] = None
url: Optional[str] = None
mid_size: Optional[int] = None
thumb_size: Optional[int] = None
thumb_height: Optional[int] = None
thumb_width: Optional[int] = None
hd_size: Optional[int] = None
_downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
@dataclass
class VoiceItem:
media: Optional[CDNMedia] = None
encode_type: Optional[int] = None
bits_per_sample: Optional[int] = None
sample_rate: Optional[int] = None
playtime: Optional[int] = None
text: Optional[str] = None
_downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
@dataclass
class FileItem:
media: Optional[CDNMedia] = None
file_name: Optional[str] = None
md5: Optional[str] = None
len: Optional[str] = None
_downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
@dataclass
class VideoItem:
media: Optional[CDNMedia] = None
video_size: Optional[int] = None
play_length: Optional[int] = None
video_md5: Optional[str] = None
thumb_media: Optional[CDNMedia] = None
thumb_size: Optional[int] = None
thumb_height: Optional[int] = None
thumb_width: Optional[int] = None
_downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
@dataclass
class RefMessage:
message_item: Optional[MessageItem] = None
title: Optional[str] = None
@dataclass
class MessageItem:
"""A single content item inside a WeixinMessage."""
# Item types
NONE = 0
TEXT = 1
IMAGE = 2
VOICE = 3
FILE = 4
VIDEO = 5
type: Optional[int] = None
create_time_ms: Optional[int] = None
update_time_ms: Optional[int] = None
is_completed: Optional[bool] = None
msg_id: Optional[str] = None
ref_msg: Optional[RefMessage] = None
text_item: Optional[TextItem] = None
image_item: Optional[ImageItem] = None
voice_item: Optional[VoiceItem] = None
file_item: Optional[FileItem] = None
video_item: Optional[VideoItem] = None
@dataclass
class WeixinMessage:
"""Unified message from getUpdates or for sendMessage."""
# Message types
TYPE_USER = 1
TYPE_BOT = 2
# Message states
STATE_NEW = 0
STATE_GENERATING = 1
STATE_FINISH = 2
seq: Optional[int] = None
message_id: Optional[int] = None
from_user_id: Optional[str] = None
to_user_id: Optional[str] = None
client_id: Optional[str] = None
create_time_ms: Optional[int] = None
update_time_ms: Optional[int] = None
delete_time_ms: Optional[int] = None
session_id: Optional[str] = None
group_id: Optional[str] = None
message_type: Optional[int] = None
message_state: Optional[int] = None
item_list: Optional[list[MessageItem]] = None
context_token: Optional[str] = None
@dataclass
class GetUpdatesResponse:
ret: Optional[int] = None
errcode: Optional[int] = None
errmsg: Optional[str] = None
msgs: list[WeixinMessage] = field(default_factory=list)
get_updates_buf: Optional[str] = None
longpolling_timeout_ms: Optional[int] = None
@dataclass
class GetConfigResponse:
ret: Optional[int] = None
errmsg: Optional[str] = None
typing_ticket: Optional[str] = None
@dataclass
class GetUploadUrlResponse:
upload_param: Optional[str] = None
thumb_upload_param: Optional[str] = None
@dataclass
class QRCodeResponse:
"""Response from get_bot_qrcode endpoint."""
qrcode: Optional[str] = None
qrcode_img_content: Optional[str] = None
@dataclass
class QRStatusResponse:
"""Response from get_qrcode_status endpoint."""
status: Optional[str] = None # "wait" | "scaned" | "confirmed" | "expired"
bot_token: Optional[str] = None
ilink_bot_id: Optional[str] = None
baseurl: Optional[str] = None
ilink_user_id: Optional[str] = None
@dataclass
class LoginResult:
"""Result returned by the login flow."""
token: str
base_url: str
account_id: str
qr_image_base64: Optional[str] = None # data URI of the last QR code shown

View File

@@ -1,10 +1,8 @@
import re
import time
import asyncio
from quart import request
import httpx
from quart import Quart
from typing import Callable, Dict, Any, Optional
from typing import Callable, Dict, Any
import langbot_plugin.api.entities.builtin.platform.events as platform_events
from .qqofficialevent import QQOfficialEvent
import json
@@ -12,20 +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
@@ -34,8 +50,6 @@ class QQOfficialClient:
self.access_token = ''
self.access_token_expiry_time = None
self.logger = logger
self._msg_seq_counter = 0
self._token_refresh_task: Optional[asyncio.Task] = None
async def check_access_token(self):
"""检查access_token是否存在"""
@@ -54,57 +68,32 @@ class QQOfficialClient:
headers = {
'content-type': 'application/json',
}
response = await client.post(url, json=params, headers=headers)
if response.status_code != 200:
raise Exception(f'Failed to get access_token: HTTP {response.status_code} {response.text}')
response_data = response.json()
access_token = response_data.get('access_token')
expires_in = int(response_data.get('expires_in', 7200))
self.access_token_expiry_time = time.time() + expires_in - 60
if access_token:
self.access_token = access_token
await self.logger.info(f'access_token obtained, expires_in={expires_in}s')
else:
raise Exception('Failed to get access_token: no access_token in response')
try:
response = await client.post(url, json=params, headers=headers)
if response.status_code == 200:
response_data = response.json()
access_token = response_data.get('access_token')
expires_in = int(response_data.get('expires_in', 7200))
self.access_token_expiry_time = time.time() + expires_in - 60
if access_token:
self.access_token = access_token
except Exception as e:
await self.logger.error(f'获取access_token失败: {response_data}')
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()
await self.logger.info(f'Received request, body length: {len(body)}')
if not body or len(body) == 0:
await self.logger.info('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)
@@ -142,24 +131,21 @@ class QQOfficialClient:
async def get_message(self, msg: dict) -> Dict[str, Any]:
"""获取消息"""
d = msg.get('d', {})
if not isinstance(d, dict):
return {}
message_data = {
't': msg.get('t', {}),
'user_openid': d.get('author', {}).get('user_openid', {}),
'timestamp': d.get('timestamp', {}),
'd_author_id': d.get('author', {}).get('id', {}),
'content': d.get('content', {}),
'd_id': d.get('id', {}),
'user_openid': msg.get('d', {}).get('author', {}).get('user_openid', {}),
'timestamp': msg.get('d', {}).get('timestamp', {}),
'd_author_id': msg.get('d', {}).get('author', {}).get('id', {}),
'content': msg.get('d', {}).get('content', {}),
'd_id': msg.get('d', {}).get('id', {}),
'id': msg.get('id', {}),
'channel_id': d.get('channel_id', {}),
'username': d.get('author', {}).get('username', {}),
'guild_id': d.get('guild_id', {}),
'member_openid': d.get('author', {}).get('openid', {}),
'group_openid': d.get('group_openid', {}),
'channel_id': msg.get('d', {}).get('channel_id', {}),
'username': msg.get('d', {}).get('author', {}).get('username', {}),
'guild_id': msg.get('d', {}).get('guild_id', {}),
'member_openid': msg.get('d', {}).get('author', {}).get('openid', {}),
'group_openid': msg.get('d', {}).get('group_openid', {}),
}
attachments = d.get('attachments', [])
attachments = msg.get('d', {}).get('attachments', [])
image_attachments = [attachment['url'] for attachment in attachments if await self.is_image(attachment)]
image_attachments_type = [
attachment['content_type'] for attachment in attachments if await self.is_image(attachment)
@@ -198,7 +184,7 @@ class QQOfficialClient:
if response.status_code == 200:
return
else:
await self.logger.error(f'Failed to send private message: {response_data}')
await self.logger.error(f'发送私聊消息失败: {response_data}')
raise ValueError(response)
async def send_group_text_msg(self, group_openid: str, content: str, msg_id: str):
@@ -221,7 +207,7 @@ class QQOfficialClient:
if response.status_code == 200:
return
else:
await self.logger.error(f'Failed to send group message: {response.json()}')
await self.logger.error(f'发送群聊消息失败:{response.json()}')
raise Exception(response.read().decode())
async def send_channle_group_text_msg(self, channel_id: str, content: str, msg_id: str):
@@ -244,7 +230,7 @@ class QQOfficialClient:
if response.status_code == 200:
return True
else:
await self.logger.error(f'Failed to send channel group message: {response.json()}')
await self.logger.error(f'发送频道群聊消息失败: {response.json()}')
raise Exception(response)
async def send_channle_private_text_msg(self, guild_id: str, content: str, msg_id: str):
@@ -267,571 +253,11 @@ class QQOfficialClient:
if response.status_code == 200:
return True
else:
await self.logger.error(f'Failed to send channel private message: {response.json()}')
await self.logger.error(f'发送频道私聊消息失败: {response.json()}')
raise Exception(response)
# ---- 富媒体消息 ----
# 媒体文件类型
MEDIA_TYPE_IMAGE = 1
MEDIA_TYPE_VIDEO = 2
MEDIA_TYPE_VOICE = 3
MEDIA_TYPE_FILE = 4
async def upload_media(
self,
target_type: str,
target_id: str,
file_type: int,
file_url: str = None,
file_data: str = None,
file_name: str = None,
) -> str:
"""上传媒体文件,返回 file_info。
Args:
target_type: 'c2c' | 'group'
target_id: 用户 openid 或群 openid
file_type: 1=图片, 2=视频, 3=语音, 4=文件
file_url: 在线 URL与 file_data 二选一)
file_data: base64 编码的文件数据或 data URL与 file_url 二选一)
file_name: 文件名file_type=4 时必填)
"""
if not await self.check_access_token():
await self.get_access_token()
if target_type == 'c2c':
url = f'{self.base_url}/v2/users/{target_id}/files'
elif target_type == 'group':
url = f'{self.base_url}/v2/groups/{target_id}/files'
else:
raise ValueError(f'Unsupported target_type: {target_type}')
body = {
'file_type': file_type,
'srv_send_msg': False,
}
if file_url:
body['url'] = file_url
elif file_data:
# 处理 data URL 格式: data:image/png;base64,xxxxx
if file_data.startswith('data:'):
match = re.match(r'^data:[^;]+;base64,(.+)$', file_data, re.DOTALL)
if match:
body['file_data'] = match.group(1)
else:
body['file_data'] = file_data
else:
body['file_data'] = file_data
else:
raise ValueError('file_url or file_data is required')
if file_type == self.MEDIA_TYPE_FILE and file_name:
body['file_name'] = file_name
async with httpx.AsyncClient(timeout=120) as client:
headers = {
'Authorization': f'QQBot {self.access_token}',
'Content-Type': 'application/json',
}
response = await client.post(url, headers=headers, json=body)
if response.status_code == 200:
data = response.json()
file_info = data.get('file_info', '')
preview = file_info[:80] + '...' if len(file_info) > 80 else file_info
await self.logger.info(f'Upload media success, file_info={preview}')
return file_info
else:
raise Exception(f'Failed to upload media: HTTP {response.status_code} {response.text}')
async def _send_media_msg(
self,
target_type: str,
target_id: str,
file_info: str,
msg_id: str = None,
content: str = None,
):
"""发送富媒体消息msg_type=7"""
if not await self.check_access_token():
await self.get_access_token()
if target_type == 'c2c':
url = f'{self.base_url}/v2/users/{target_id}/messages'
elif target_type == 'group':
url = f'{self.base_url}/v2/groups/{target_id}/messages'
else:
raise ValueError(f'Unsupported target_type: {target_type}')
self._msg_seq_counter += 1
msg_seq = self._msg_seq_counter
body = {
'msg_type': 7,
'media': {'file_info': file_info},
'msg_seq': msg_seq,
}
if content:
body['content'] = content
if msg_id:
body['msg_id'] = msg_id
async with httpx.AsyncClient(timeout=120) as client:
headers = {
'Authorization': f'QQBot {self.access_token}',
'Content-Type': 'application/json',
}
await self.logger.info(f'Sending rich media: {json.dumps(body, ensure_ascii=False)[:200]}')
response = await client.post(url, headers=headers, json=body)
if response.status_code != 200:
raise Exception(f'Failed to send rich media message: HTTP {response.status_code} {response.text}')
async def send_image_msg(
self,
target_type: str,
target_id: str,
file_url: str = None,
file_data: str = None,
msg_id: str = None,
content: str = None,
):
"""发送图片消息"""
file_info = await self.upload_media(
target_type,
target_id,
self.MEDIA_TYPE_IMAGE,
file_url=file_url,
file_data=file_data,
)
await self._send_media_msg(target_type, target_id, file_info, msg_id, content)
async def send_voice_msg(
self,
target_type: str,
target_id: str,
file_url: str = None,
file_data: str = None,
msg_id: str = None,
):
"""发送语音消息"""
file_info = await self.upload_media(
target_type,
target_id,
self.MEDIA_TYPE_VOICE,
file_url=file_url,
file_data=file_data,
)
await self._send_media_msg(target_type, target_id, file_info, msg_id)
async def send_file_msg(
self,
target_type: str,
target_id: str,
file_url: str = None,
file_data: str = None,
file_name: str = None,
msg_id: str = None,
):
"""发送文件消息(含视频)"""
file_info = await self.upload_media(
target_type,
target_id,
self.MEDIA_TYPE_FILE,
file_url=file_url,
file_data=file_data,
file_name=file_name,
)
await self._send_media_msg(target_type, target_id, file_info, msg_id)
async def send_stream_msg(
self,
user_openid: str,
content: str,
event_id: str,
msg_id: str,
msg_seq: int = 1,
index: int = 0,
stream_msg_id: str = None,
input_state: int = 1,
):
"""发送流式消息C2C 私聊)。
Args:
input_state: 1=生成中, 10=生成结束
"""
if not await self.check_access_token():
await self.get_access_token()
url = f'{self.base_url}/v2/users/{user_openid}/stream_messages'
body = {
'input_mode': 'replace',
'input_state': input_state,
'content_type': 'markdown',
'content_raw': content,
'event_id': event_id,
'msg_id': msg_id,
'msg_seq': msg_seq,
'index': index,
}
if stream_msg_id:
body['stream_msg_id'] = stream_msg_id
async with httpx.AsyncClient(timeout=120) as client:
headers = {
'Authorization': f'QQBot {self.access_token}',
'Content-Type': 'application/json',
}
response = await client.post(url, headers=headers, json=body)
if response.status_code != 200:
raise Exception(f'Failed to send stream message: HTTP {response.status_code} {response.text}')
return response.json()
async def is_token_expired(self):
"""检查token是否过期"""
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
# ---- WebSocket Gateway ----
# Reference: https://bot.q.qq.com/wiki/develop/api-v2/dev-prepare/interface-framework/event-emit.html
INTENT_GUILDS = 1 << 0
INTENT_GUILD_MEMBERS = 1 << 1
INTENT_PUBLIC_GUILD_MESSAGES = 1 << 30
INTENT_DIRECT_MESSAGE = 1 << 12
INTENT_GROUP_AND_C2C = 1 << 25
INTENT_INTERACTION = 1 << 26
FULL_INTENTS = (
INTENT_GUILDS
| INTENT_GUILD_MEMBERS
| INTENT_PUBLIC_GUILD_MESSAGES
| INTENT_DIRECT_MESSAGE
| INTENT_GROUP_AND_C2C
| INTENT_INTERACTION
)
async def get_gateway_url(self) -> str:
"""获取 WebSocket 网关地址"""
if not await self.check_access_token():
await self.get_access_token()
url = f'{self.base_url}/gateway'
async with httpx.AsyncClient() as client:
headers = {
'Authorization': f'QQBot {self.access_token}',
}
response = await client.get(url, headers=headers)
if response.status_code == 200:
data = response.json()
ws_url = data.get('url', '')
if not ws_url:
raise Exception('Gateway URL is empty')
return ws_url
else:
raise Exception(f'Failed to get Gateway URL: HTTP {response.status_code} {response.text}')
async def _background_token_refresh(self):
"""在 token 到期前主动刷新"""
try:
while True:
if self.access_token_expiry_time:
remain = self.access_token_expiry_time - time.time()
if remain > 120:
await asyncio.sleep(remain - 60)
continue
self.access_token = ''
self.access_token_expiry_time = None
if await self.check_access_token():
await asyncio.sleep(60)
else:
await self.get_access_token()
await asyncio.sleep(60)
except asyncio.CancelledError:
pass
async def connect_gateway(
self,
on_event: Callable[[str, dict], Any],
on_ready: Optional[Callable[[], Any]] = None,
on_error: Optional[Callable[[Exception], Any]] = None,
):
"""WebSocket 网关连接,含重连逻辑。持续重连直到达到最大次数或被取消。
Args:
on_event: 收到 op=0 Dispatch 事件时的回调,参数为 (event_type, event_data)
on_ready: 连接就绪 (收到 READY) 时的回调
on_error: 发生错误时的回调
"""
import websockets
session_id = ''
last_seq = 0
reconnect_attempts = 0
max_reconnect_attempts = 100
backoff_delays = [1, 2, 5, 10, 30, 60]
rate_limit_delay = 60
# Cancel previous token refresh task if any
if self._token_refresh_task and not self._token_refresh_task.done():
self._token_refresh_task.cancel()
try:
await self._token_refresh_task
except asyncio.CancelledError:
pass
self._token_refresh_task = None
while reconnect_attempts <= max_reconnect_attempts:
heartbeat_interval = 45000
should_refresh_token = False
ws = None
heartbeat_task = None
# Refresh token if needed
if should_refresh_token:
self.access_token = ''
self.access_token_expiry_time = None
try:
ws_url = await self.get_gateway_url()
await self.logger.info(f'Gateway URL obtained: {ws_url[:60]}...')
except Exception as e:
error_msg = str(e)
await self.logger.error(f'Failed to get gateway URL: {e}')
reconnect_attempts += 1
if '100017' in error_msg or '频率' in error_msg or 'Too many' in error_msg:
delay = rate_limit_delay
else:
delay = backoff_delays[min(reconnect_attempts - 1, len(backoff_delays) - 1)]
await self.logger.info(f'Reconnecting in {delay}s (attempt {reconnect_attempts})')
await asyncio.sleep(delay)
continue
try:
await self.logger.info('Connecting to WebSocket gateway...')
ws = await websockets.connect(ws_url)
await self.logger.info('WebSocket connected')
except Exception as e:
await self.logger.error(f'WebSocket connection failed: {e}')
reconnect_attempts += 1
delay = backoff_delays[min(reconnect_attempts - 1, len(backoff_delays) - 1)]
await self.logger.info(f'Reconnecting in {delay}s (attempt {reconnect_attempts})')
await asyncio.sleep(delay)
continue
try:
async for raw_msg in ws:
try:
payload = json.loads(raw_msg)
except json.JSONDecodeError:
await self.logger.error(f'Failed to parse message: {raw_msg}')
continue
op = payload.get('op')
d = payload.get('d', {})
s = payload.get('s')
t = payload.get('t')
if not isinstance(d, dict):
d = {}
if op == 10: # Hello
heartbeat_interval = d.get('heartbeat_interval', 45000)
await self.logger.info(f'Received Hello, heartbeat_interval={heartbeat_interval}ms')
# Send Identify or Resume
if session_id and last_seq > 0:
resume_payload = {
'op': 6,
'd': {
'token': f'QQBot {self.access_token}',
'session_id': session_id,
'seq': last_seq,
},
}
await ws.send(json.dumps(resume_payload))
await self.logger.info(f'Sent Resume, session_id={session_id}, seq={last_seq}')
else:
identify_payload = {
'op': 2,
'd': {
'token': f'QQBot {self.access_token}',
'intents': self.FULL_INTENTS,
'shard': [0, 1],
},
}
await ws.send(json.dumps(identify_payload))
await self.logger.info(f'Sent Identify, intents={self.FULL_INTENTS}')
# Start heartbeat
async def _heartbeat_loop(conn, interval_ms):
interval_sec = interval_ms / 1000.0
try:
while True:
await asyncio.sleep(interval_sec)
try:
hb_payload = {'op': 1, 'd': last_seq}
await conn.send(json.dumps(hb_payload))
except Exception:
break
except asyncio.CancelledError:
pass
heartbeat_task = asyncio.create_task(_heartbeat_loop(ws, heartbeat_interval))
elif op == 0: # Dispatch
if s is not None:
last_seq = s
if t == 'READY':
session_id = d.get('session_id', '')
reconnect_attempts = 0
await self.logger.info(f'READY, session_id={session_id}')
if on_ready:
try:
result = on_ready()
if asyncio.iscoroutine(result):
await result
except Exception:
pass
# Track token refresh task to avoid leaks
if self._token_refresh_task and not self._token_refresh_task.done():
self._token_refresh_task.cancel()
try:
await self._token_refresh_task
except asyncio.CancelledError:
pass
self._token_refresh_task = asyncio.create_task(self._background_token_refresh())
elif t == 'RESUMED':
reconnect_attempts = 0
await self.logger.info('RESUMED')
else:
await self.logger.debug(f'Received event: {t}, seq={s}')
if on_event:
try:
result = on_event(t, d)
if asyncio.iscoroutine(result):
await result
except Exception:
await self.logger.error(f'Error handling event {t}: {traceback.format_exc()}')
elif op == 11: # Heartbeat ACK
pass
elif op == 7: # Reconnect
await self.logger.info('Received Reconnect directive')
break
elif op == 9: # Invalid Session
can_resume = d.get('can_resume', False)
await self.logger.warning(f'Invalid Session, can_resume={can_resume}')
if not can_resume:
session_id = ''
last_seq = 0
should_refresh_token = True
break
# Connection closed normally (end of async for)
try:
close_code = ws.close_code
close_reason = ws.close_reason or ''
except Exception:
close_code = None
close_reason = ''
await self.logger.info(f'Connection closed, code={close_code}, reason={close_reason}')
if close_code == 4004:
should_refresh_token = True
elif close_code in (4006, 4007, 4009):
session_id = ''
last_seq = 0
should_refresh_token = True
elif close_code == 4008:
reconnect_attempts += 1
delay = rate_limit_delay
await self.logger.info(
f'Rate limited, waiting {delay}s before reconnect (attempt {reconnect_attempts})'
)
await asyncio.sleep(delay)
continue
elif close_code in (4914, 4915):
err = Exception(f'Bot disconnected/banned (close_code={close_code})')
if on_error:
await self._safe_callback(on_error, err)
return
elif close_code in (4900, 4901, 4902, 4903, 4904, 4905, 4906, 4907, 4908, 4909, 4910, 4911, 4912, 4913):
session_id = ''
last_seq = 0
if close_code == 1000:
return
except asyncio.CancelledError:
raise
except Exception:
await self.logger.error(f'Unexpected error in WebSocket loop: {traceback.format_exc()}')
finally:
if heartbeat_task:
heartbeat_task.cancel()
try:
await heartbeat_task
except asyncio.CancelledError:
pass
if ws:
try:
await ws.close()
except Exception:
pass
# If we reach here, we need to reconnect
reconnect_attempts += 1
if reconnect_attempts > max_reconnect_attempts:
await self.logger.error(f'Max reconnect attempts ({max_reconnect_attempts}) reached, stopping')
if on_error:
await self._safe_callback(on_error, Exception('Max reconnect attempts reached'))
return
delay = backoff_delays[min(reconnect_attempts - 1, len(backoff_delays) - 1)]
await self.logger.info(f'Reconnecting in {delay}s (attempt {reconnect_attempts})')
await asyncio.sleep(delay)
async def _safe_callback(self, callback, *args):
"""Safely invoke a callback, handling both sync and async functions."""
try:
result = callback(*args)
if asyncio.iscoroutine(result):
await result
except Exception:
pass
async def connect_gateway_loop(
self,
on_event: Callable[[str, dict], Any],
on_ready: Optional[Callable[[], Any]] = None,
on_error: Optional[Callable[[Exception], Any]] = None,
):
"""持续重连的网关循环。"""
await self.connect_gateway(on_event, on_ready, on_error)

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

@@ -1,5 +1,5 @@
import requests
from langbot.pkg.utils import httpclient
import aiohttp
def post_json(base_url, token, data=None):
@@ -63,16 +63,16 @@ async def async_request(
"""
headers = {'Content-Type': 'application/json'}
url = f'{base_url}?key={token_key}'
session = httpclient.get_session()
async with session.request(
method=method, url=url, params=params, headers=headers, data=data, json=json
) as response:
response.raise_for_status() # 如果状态码不是200抛出异常
result = await response.json()
# print(result)
return result
# if result.get('Code') == 200:
#
# return await result
# else:
# raise RuntimeError("请求失败",response.text)
async with aiohttp.ClientSession() as session:
async with session.request(
method=method, url=url, params=params, headers=headers, data=data, json=json
) as response:
response.raise_for_status() # 如果状态码不是200抛出异常
result = await response.json()
# print(result)
return result
# if result.get('Code') == 200:
#
# return await result
# else:
# raise RuntimeError("请求失败",response.text)

View File

@@ -6,8 +6,7 @@ import traceback
import uuid
import xml.etree.ElementTree as ET
from dataclasses import dataclass, field
import re
from typing import Any, Callable, Optional, Tuple
from typing import Any, Callable, Optional
from urllib.parse import unquote
import httpx
@@ -64,25 +63,16 @@ class StreamSession:
# 缓存最近一次片段,处理重试或超时兜底
last_chunk: Optional[StreamChunk] = None
# 反馈 ID用于接收用户点赞/点踩反馈
feedback_id: Optional[str] = None
class StreamSessionManager:
"""管理 stream 会话的生命周期,并负责队列的生产消费。"""
# Sessions with registered feedback_ids use a longer TTL to survive the
# full like → cancel → dislike feedback flow. Must align with the adapter's
# _stream_to_monitoring_msg TTL (wecombot.py).
_FEEDBACK_SESSION_TTL = 600 # 10 minutes
def __init__(self, logger: EventLogger, ttl: int = 60) -> None:
self.logger = logger
self.ttl = ttl # 超时时间(秒),超过该时间未被访问的会话会被清理由 cleanup
self._sessions: dict[str, StreamSession] = {} # stream_id -> StreamSession 映射
self._msg_index: dict[str, str] = {} # msgid -> stream_id 映射,便于流水线根据消息 ID 找到会话
self._feedback_index: dict[str, str] = {} # feedback_id -> stream_id 映射
def get_stream_id_by_msg(self, msg_id: str) -> Optional[str]:
if not msg_id:
@@ -92,32 +82,6 @@ class StreamSessionManager:
def get_session(self, stream_id: str) -> Optional[StreamSession]:
return self._sessions.get(stream_id)
def get_session_by_feedback_id(self, feedback_id: str) -> Optional[StreamSession]:
"""根据 feedback_id 查找会话。
Args:
feedback_id: 企业微信反馈事件中的反馈 ID。
Returns:
Optional[StreamSession]: 找到的会话实例,未找到返回 None。
"""
if not feedback_id:
return None
stream_id = self._feedback_index.get(feedback_id)
if stream_id:
return self._sessions.get(stream_id)
return None
def register_feedback_id(self, stream_id: str, feedback_id: str) -> None:
"""注册 feedback_id 与 stream_id 的映射。
Args:
stream_id: 企业微信流式会话 ID。
feedback_id: 反馈 ID。
"""
if feedback_id and stream_id:
self._feedback_index[feedback_id] = stream_id
def create_or_get(self, msg_json: dict[str, Any]) -> tuple[StreamSession, bool]:
"""根据企业微信回调创建或获取会话。
@@ -219,17 +183,11 @@ class StreamSessionManager:
session.last_access = time.time()
def cleanup(self) -> None:
"""定期清理过期会话,防止队列与映射无上限累积。
已注册 feedback_id 的会话使用更长的 TTL确保用户在点赞/取消/点踩流程中
不会因为 session 被提前清除而丢失上下文信息。
"""
"""定期清理过期会话,防止队列与映射无上限累积。"""
now = time.time()
expired: list[str] = []
for stream_id, session in self._sessions.items():
# Sessions with registered feedback_ids use a longer TTL
effective_ttl = self._FEEDBACK_SESSION_TTL if session.feedback_id else self.ttl
if now - session.last_access > effective_ttl:
if now - session.last_access > self.ttl:
expired.append(stream_id)
for stream_id in expired:
@@ -239,492 +197,10 @@ class StreamSessionManager:
msg_id = session.msg_id
if msg_id and self._msg_index.get(msg_id) == stream_id:
self._msg_index.pop(msg_id, None)
# Clean up feedback index for expired sessions
if session.feedback_id:
self._feedback_index.pop(session.feedback_id, None)
def _decrypt_file(encrypted_data: bytes, aes_key_str: str) -> bytes:
"""Decrypt AES-256-CBC encrypted file data.
Aligned with the official WeCom AI Bot Python SDK (crypto_utils.py).
Args:
encrypted_data: The raw encrypted bytes.
aes_key_str: Base64-encoded AES key (may lack padding).
Returns:
Decrypted bytes with PKCS#7 padding removed.
"""
if not encrypted_data:
raise ValueError('encrypted_data is empty')
if not aes_key_str:
raise ValueError('aes_key is empty')
# Python's base64.b64decode requires proper padding (length % 4 == 0).
# Node.js Buffer.from tolerates missing '=', so we must pad manually.
remainder = len(aes_key_str) % 4
if remainder != 0:
aes_key_str = aes_key_str + '=' * (4 - remainder)
key = base64.b64decode(aes_key_str)
iv = key[:16]
cipher = AES.new(key, AES.MODE_CBC, iv)
# Ensure encrypted data is aligned to AES block size (16 bytes).
# Node.js setAutoPadding(false) silently handles unaligned data,
# but PyCryptodome will raise an error.
block_size = 16
data_remainder = len(encrypted_data) % block_size
if data_remainder != 0:
encrypted_data = encrypted_data + b'\x00' * (block_size - data_remainder)
decrypted = cipher.decrypt(encrypted_data)
# Remove PKCS#7 padding with validation
if len(decrypted) == 0:
raise ValueError('Decrypted data is empty')
pad_len = decrypted[-1]
if pad_len < 1 or pad_len > 32 or pad_len > len(decrypted):
raise ValueError(f'Invalid PKCS#7 padding value: {pad_len}')
# Verify all padding bytes are consistent
for i in range(len(decrypted) - pad_len, len(decrypted)):
if decrypted[i] != pad_len:
raise ValueError('Invalid PKCS#7 padding: padding bytes mismatch')
return decrypted[: len(decrypted) - pad_len]
def _extract_filename(content_disposition: str) -> Optional[str]:
"""Extract filename from a Content-Disposition header value."""
if not content_disposition:
return None
# RFC 5987: filename*=UTF-8''xxx
utf8_match = re.search(r"filename\*=UTF-8''([^;\s]+)", content_disposition, re.IGNORECASE)
if utf8_match:
return unquote(utf8_match.group(1))
# Standard: filename="xxx" or filename=xxx
match = re.search(r'filename="?([^";\s]+)"?', content_disposition, re.IGNORECASE)
if match:
return unquote(match.group(1))
return None
def _bytes_to_data_uri(data: bytes) -> str:
"""Convert raw bytes to a data URI with auto-detected MIME type."""
if data.startswith(b'\xff\xd8'):
mime_type = 'image/jpeg'
elif data.startswith(b'\x89PNG'):
mime_type = 'image/png'
elif data.startswith((b'GIF87a', b'GIF89a')):
mime_type = 'image/gif'
elif data.startswith(b'BM'):
mime_type = 'image/bmp'
elif data.startswith(b'II*\x00') or data.startswith(b'MM\x00*'):
mime_type = 'image/tiff'
elif data[:4] == b'%PDF':
mime_type = 'application/pdf'
elif data[:4] == b'PK\x03\x04':
mime_type = 'application/zip'
else:
mime_type = 'application/octet-stream'
base64_str = base64.b64encode(data).decode('utf-8')
return f'data:{mime_type};base64,{base64_str}'
async def download_encrypted_file(
download_url: str, aes_key: str, logger: EventLogger
) -> Tuple[Optional[bytes], Optional[str]]:
"""Download an AES-encrypted file from WeChat Work and decrypt it.
Args:
download_url: The encrypted file download URL.
aes_key: The AES key for decryption (base64-encoded, per-message aeskey
or platform EncodingAESKey).
logger: Logger instance.
Returns:
A tuple of (decrypted_bytes, filename) or (None, None) on failure.
"""
if not download_url:
return None, None
if not aes_key:
await logger.error('download_encrypted_file: aes_key is empty, cannot decrypt')
return None, None
filename: Optional[str] = None
try:
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.get(download_url)
if response.status_code != 200:
await logger.error(f'Failed to download file (HTTP {response.status_code}): {response.text[:200]}')
return None, None
encrypted_bytes = response.content
filename = _extract_filename(response.headers.get('content-disposition', ''))
except Exception:
await logger.error(f'Failed to download file: {traceback.format_exc()}')
return None, None
try:
decrypted = _decrypt_file(encrypted_bytes, aes_key)
return decrypted, filename
except Exception:
await logger.error(f'Failed to decrypt file: {traceback.format_exc()}')
return None, None
async def parse_wecom_bot_message(
msg_json: dict[str, Any], encoding_aes_key: str, logger: EventLogger
) -> dict[str, Any]:
"""Parse a decrypted WeChat Work AI Bot message JSON into a unified message dict.
This is the shared message parsing logic used by both webhook and WebSocket modes.
Args:
msg_json: The decrypted message JSON from WeChat Work.
encoding_aes_key: AES key for file decryption.
logger: Logger instance.
Returns:
A dict suitable for constructing a WecomBotEvent.
"""
message_data: dict[str, Any] = {}
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
async def _safe_download(url: str, per_msg_aeskey: str = '') -> Tuple[Optional[bytes], Optional[str]]:
"""Download and decrypt a file, preferring per-message aeskey over platform key."""
if not url:
return None, None
key = per_msg_aeskey or encoding_aes_key
if not key:
await logger.warning('No AES key available for file decryption, skipping download')
return None, None
return await download_encrypted_file(url, key, logger)
async def _safe_download_as_data_uri(url: str, per_msg_aeskey: str = '') -> Optional[str]:
"""Download, decrypt, and convert to data URI for backward compatibility."""
data, _filename = await _safe_download(url, per_msg_aeskey)
if data:
return _bytes_to_data_uri(data)
return None
if msg_type == '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':
image_info = msg_json.get('image', {})
picurl = image_info.get('url', '')
per_msg_aeskey = image_info.get('aeskey', '')
base64_data = await _safe_download_as_data_uri(picurl, per_msg_aeskey)
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')
per_msg_aeskey = voice_info.get('aeskey', '')
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'),
}
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_as_data_uri(download_url, per_msg_aeskey)
# 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')
per_msg_aeskey = video_info.get('aeskey', '')
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_as_data_uri(download_url, per_msg_aeskey)
# if video_base64:
# video_data['base64'] = video_base64
# 应为需要解密但是目前暂时不能下载到内部进行解密所以先将下载链接拼接aeskey返回给用户由插件去处理该链接的下载和解密逻辑
video_data['download_url'] = download_url + f'?aeskey={per_msg_aeskey}'
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')
per_msg_aeskey = file_info.get('aeskey', '')
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_bytes, dl_filename = await _safe_download(download_url, per_msg_aeskey)
# if file_bytes:
# file_data['base64'] = _bytes_to_data_uri(file_bytes)
# if dl_filename and not file_data.get('filename'):
# file_data['filename'] = dl_filename
# 应为需要解密但是目前暂时不能下载到内部进行解密所以先将下载链接拼接aeskey返回给用户由插件去处理该链接的下载和解密逻辑
file_data['download_url'] = download_url + f'?aeskey={per_msg_aeskey}'
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':
items = msg_json.get('mixed', {}).get('msg_item', [])
texts = []
images = []
files = []
voices = []
videos = []
links = []
for item in items:
item_type = item.get('msgtype')
if item_type == 'text':
texts.append(item.get('text', {}).get('content', ''))
elif item_type == 'image':
img_info = item.get('image', {})
img_url = img_info.get('url')
img_aeskey = img_info.get('aeskey', '')
base64_data = await _safe_download_as_data_uri(img_url, img_aeskey)
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')
item_aeskey = file_info.get('aeskey', '')
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_bytes, dl_filename = await _safe_download(download_url, item_aeskey)
if file_bytes:
file_data['base64'] = _bytes_to_data_uri(file_bytes)
if dl_filename and not file_data.get('filename'):
file_data['filename'] = dl_filename
files.append(file_data)
elif item_type == 'voice':
voice_info = item.get('voice', {}) or {}
download_url = voice_info.get('url')
item_aeskey = voice_info.get('aeskey', '')
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_as_data_uri(download_url, item_aeskey)
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')
item_aeskey = video_info.get('aeskey', '')
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_as_data_uri(download_url, item_aeskey)
if video_base64:
video_data['base64'] = video_base64
videos.append(video_data)
elif item_type == 'link':
links.append(item.get('link', {}))
if texts:
message_data['content'] = ' '.join(texts)
if images:
message_data['images'] = images
message_data['picurl'] = images[0]
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
from_info = msg_json.get('from', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
if msg_json.get('chattype', '') == 'group':
message_data['chatid'] = msg_json.get('chatid', '')
message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
message_data['msgid'] = msg_json.get('msgid', '')
if msg_json.get('aibotid'):
message_data['aibotid'] = msg_json.get('aibotid', '')
# Handle quote (referenced message) - important for group chat file references
quote_info = msg_json.get('quote')
if quote_info:
quote_data: dict[str, Any] = {}
quote_type = quote_info.get('msgtype', '')
quote_data['msgtype'] = quote_type
if quote_type == 'text':
quote_data['content'] = quote_info.get('text', {}).get('content', '')
elif quote_type == 'image':
img_info = quote_info.get('image', {})
img_url = img_info.get('url', '')
img_aeskey = img_info.get('aeskey', '')
base64_data = await _safe_download_as_data_uri(img_url, img_aeskey)
if base64_data:
quote_data['picurl'] = base64_data
quote_data['images'] = [base64_data]
elif quote_type == 'file':
file_info = quote_info.get('file', {}) or {}
download_url = file_info.get('url') or file_info.get('fileurl')
item_aeskey = file_info.get('aeskey', '')
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,
}
# Same as private chat: append aeskey to download_url for plugin processing
if download_url and item_aeskey:
file_data['download_url'] = download_url + f'?aeskey={item_aeskey}'
quote_data['file'] = file_data
elif quote_type == 'voice':
voice_info = quote_info.get('voice', {}) or {}
download_url = voice_info.get('url')
item_aeskey = voice_info.get('aeskey', '')
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'):
quote_data['content'] = voice_info.get('content')
# Same as private chat: append aeskey to url for plugin processing
if download_url and item_aeskey:
voice_data['url'] = download_url + f'?aeskey={item_aeskey}'
quote_data['voice'] = voice_data
elif quote_type == 'video':
video_info = quote_info.get('video', {}) or {}
download_url = video_info.get('url')
item_aeskey = video_info.get('aeskey', '')
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'),
}
# Same as private chat: append aeskey to download_url for plugin processing
if download_url and item_aeskey:
video_data['download_url'] = download_url + f'?aeskey={item_aeskey}'
quote_data['video'] = video_data
elif quote_type == 'link':
quote_data['link'] = quote_info.get('link', {})
link = quote_data['link']
title = link.get('title', '')
desc = link.get('description') or link.get('digest', '')
quote_data['content'] = '\n'.join(filter(None, [title, desc]))
elif quote_type == 'mixed':
# Handle mixed type in quote (text + images + files etc.)
items = quote_info.get('mixed', {}).get('msg_item', [])
texts = []
images = []
files = []
for item in items:
item_type = item.get('msgtype')
if item_type == 'text':
texts.append(item.get('text', {}).get('content', ''))
elif item_type == 'image':
img_info = item.get('image', {})
img_url = img_info.get('url')
img_aeskey = img_info.get('aeskey', '')
base64_data = await _safe_download_as_data_uri(img_url, img_aeskey)
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')
item_aeskey = file_info.get('aeskey', '')
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,
}
# Same as private chat: append aeskey to download_url for plugin processing
if download_url and item_aeskey:
file_data['download_url'] = download_url + f'?aeskey={item_aeskey}'
files.append(file_data)
if texts:
quote_data['content'] = ' '.join(texts)
if images:
quote_data['images'] = images
quote_data['picurl'] = images[0]
if files:
quote_data['files'] = files
quote_data['file'] = files[0]
message_data['quote'] = quote_data
return message_data
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:
@@ -732,7 +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)
@@ -742,15 +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': [],
}
@@ -760,27 +230,14 @@ class WecomBotClient:
self.stream_sessions = StreamSessionManager(logger=logger)
self.stream_poll_timeout = 0.5
self._feedback_callback: Optional[Callable] = None
def set_feedback_callback(self, callback: Callable) -> None:
"""设置反馈回调函数。
Args:
callback: 反馈回调函数,签名: async def callback(feedback_id, feedback_type, feedback_content, inaccurate_reasons, session)
"""
self._feedback_callback = callback
@staticmethod
def _build_stream_payload(
stream_id: str, content: str, finish: bool, feedback_id: Optional[str] = None
) -> dict[str, Any]:
def _build_stream_payload(stream_id: str, content: str, finish: bool) -> dict[str, Any]:
"""按照企业微信协议拼装返回报文。
Args:
stream_id: 企业微信会话 ID。
content: 推送的文本内容。
finish: 是否为最终片段。
feedback_id: 反馈 ID用于接收用户点赞/点踩反馈。
Returns:
dict[str, Any]: 可直接加密返回的 payload。
@@ -788,16 +245,13 @@ class WecomBotClient:
Example:
组装 `{'msgtype': 'stream', 'stream': {'id': 'sid', ...}}` 结构。
"""
stream_payload = {
'id': stream_id,
'finish': finish,
'content': content,
}
if feedback_id:
stream_payload['feedback'] = {'id': feedback_id}
return {
'msgtype': 'stream',
'stream': stream_payload,
'stream': {
'id': stream_id,
'finish': finish,
'content': content,
},
}
async def _encrypt_and_reply(self, payload: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -853,14 +307,9 @@ class WecomBotClient:
"""
session, is_new = self.stream_sessions.create_or_get(msg_json)
feedback_id = str(uuid.uuid4())
session.feedback_id = feedback_id
self.stream_sessions.register_feedback_id(session.stream_id, feedback_id)
message_data = await self.get_message(msg_json)
if message_data:
message_data['stream_id'] = session.stream_id
message_data['feedback_id'] = feedback_id
try:
event = wecombotevent.WecomBotEvent(message_data)
except Exception:
@@ -869,7 +318,7 @@ class WecomBotClient:
if is_new:
asyncio.create_task(self._dispatch_event(event))
payload = self._build_stream_payload(session.stream_id, '', False, feedback_id)
payload = self._build_stream_payload(session.stream_id, '', False)
return await self._encrypt_and_reply(payload, nonce)
async def _handle_post_followup_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -910,7 +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。
@@ -918,33 +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)
@@ -952,13 +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')
@@ -971,16 +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")
@@ -994,83 +425,60 @@ class WecomBotClient:
msg_json = json.loads(decrypted_xml)
event = msg_json.get('event', {})
event_type = event.get('eventtype', '')
if event_type == 'feedback_event':
return await self._handle_feedback_event(msg_json, nonce)
if msg_json.get('msgtype') == 'stream':
return await self._handle_post_followup_response(msg_json, nonce)
return await self._handle_post_initial_response(msg_json, nonce)
async def _handle_feedback_event(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
"""处理企业微信用户反馈事件(点赞/点踩)。
Args:
msg_json: 解密后的企业微信反馈事件 JSON。
nonce: 企业微信回调参数 nonce。
Returns:
Tuple[Response, int]: Quart Response 及状态码。
Note:
企业微信协议要求:反馈事件目前仅支持回复空包。
"""
try:
feedback_event = msg_json.get('event', {}).get('feedback_event', {})
feedback_id = feedback_event.get('id', '')
feedback_type = feedback_event.get('type', 0)
feedback_content = feedback_event.get('content', '')
inaccurate_reasons = feedback_event.get('inaccurate_reason_list', [])
await self.logger.info(
f'收到用户反馈事件: feedback_id={feedback_id}, type={feedback_type}, '
f'content={feedback_content}, reasons={inaccurate_reasons}'
)
session = self.stream_sessions.get_session_by_feedback_id(feedback_id)
if session:
await self.logger.info(
f'反馈关联到会话: stream_id={session.stream_id}, msg_id={session.msg_id}, user_id={session.user_id}'
)
else:
await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话,仍将记录反馈')
# Dispatch feedback event regardless of session availability
for handler in self._message_handlers.get('feedback', []):
try:
await handler(
feedback_id=feedback_id,
feedback_type=feedback_type,
feedback_content=feedback_content,
inaccurate_reasons=inaccurate_reasons,
session=session,
)
except Exception:
await self.logger.error(traceback.format_exc())
if self._feedback_callback:
try:
await self._feedback_callback(
feedback_id=feedback_id,
feedback_type=feedback_type,
feedback_content=feedback_content,
inaccurate_reasons=inaccurate_reasons,
session=session,
)
except Exception:
await self.logger.error(traceback.format_exc())
except Exception:
await self.logger.error(traceback.format_exc())
return await self._encrypt_and_reply({}, nonce)
async def get_message(self, msg_json):
return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
message_data = {}
if msg_json.get('chattype', '') == 'single':
message_data['type'] = 'single'
elif msg_json.get('chattype', '') == 'group':
message_data['type'] = 'group'
if msg_json.get('msgtype') == 'text':
message_data['content'] = msg_json.get('text', {}).get('content')
elif msg_json.get('msgtype') == 'image':
picurl = msg_json.get('image', {}).get('url', '')
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 = []
picurl = None
for item in items:
if item.get('msgtype') == 'text':
texts.append(item.get('text', {}).get('content', ''))
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 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', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = (
from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
)
# Extract chat/group information
if msg_json.get('chattype', '') == 'group':
message_data['chatid'] = msg_json.get('chatid', '')
# Try to get group name if available
message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
message_data['msgid'] = msg_json.get('msgid', '')
if msg_json.get('aibotid'):
message_data['aibotid'] = msg_json.get('aibotid', '')
return message_data
async def _handle_message(self, event: wecombotevent.WecomBotEvent):
"""
@@ -1137,20 +545,40 @@ class WecomBotClient:
return decorator
def on_feedback(self):
def decorator(func: Callable):
if 'feedback' not in self._message_handlers:
self._message_handlers['feedback'] = []
self._message_handlers['feedback'].append(func)
return func
return decorator
async def download_url_to_base64(self, download_url, encoding_aes_key):
data, _filename = await download_encrypted_file(download_url, encoding_aes_key, self.logger)
if data:
return _bytes_to_data_uri(data)
return None
async with httpx.AsyncClient() as client:
response = await client.get(download_url)
if response.status_code != 200:
await self.logger.error(f'failed to get file: {response.text}')
return None
encrypted_bytes = response.content
aes_key = base64.b64decode(encoding_aes_key + '=') # base64 补齐
iv = aes_key[:16]
cipher = AES.new(aes_key, AES.MODE_CBC, iv)
decrypted = cipher.decrypt(encrypted_bytes)
pad_len = decrypted[-1]
decrypted = decrypted[:-pad_len]
if decrypted.startswith(b'\xff\xd8'): # JPEG
mime_type = 'image/jpeg'
elif decrypted.startswith(b'\x89PNG'): # PNG
mime_type = 'image/png'
elif decrypted.startswith((b'GIF87a', b'GIF89a')): # GIF
mime_type = 'image/gif'
elif decrypted.startswith(b'BM'): # BMP
mime_type = 'image/bmp'
elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'): # TIFF
mime_type = 'image/tiff'
else:
mime_type = 'application/octet-stream'
# 转 base64
base64_str = base64.b64encode(decrypted).decode('utf-8')
return f'data:{mime_type};base64,{base64_str}'
async def run_task(self, host: str, port: int, *args, **kwargs):
"""

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:
"""
@@ -133,24 +77,3 @@ class WecomBotEvent(dict):
AI Bot ID
"""
return self.get('aibotid', '')
@property
def feedback_id(self) -> str:
"""
反馈 ID用于关联用户点赞/点踩反馈
"""
return self.get('feedback_id', '')
@property
def stream_id(self) -> str:
"""
流式消息 ID
"""
return self.get('stream_id', '')
@property
def quote(self):
"""
引用消息信息(群聊中用户引用其他消息时返回)
"""
return self.get('quote', {})

View File

@@ -1,683 +0,0 @@
"""WeChat Work AI Bot WebSocket long connection client.
Implements the WebSocket protocol for receiving messages and sending replies
via a persistent connection to wss://openws.work.weixin.qq.com, as an
alternative to the HTTP callback (webhook) mode.
Protocol reference: https://developer.work.weixin.qq.com/document/path/101463
Official Node.js SDK: https://github.com/WecomTeam/aibot-node-sdk
"""
from __future__ import annotations
import asyncio
import json
import secrets
import time
import traceback
from typing import Any, Callable, Optional
import aiohttp
from langbot.libs.wecom_ai_bot_api import wecombotevent
from langbot.libs.wecom_ai_bot_api.api import parse_wecom_bot_message, StreamSession
from langbot.pkg.platform.logger import EventLogger
DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
# WebSocket frame command constants
CMD_SUBSCRIBE = 'aibot_subscribe'
CMD_HEARTBEAT = 'ping'
CMD_MSG_CALLBACK = 'aibot_msg_callback'
CMD_EVENT_CALLBACK = 'aibot_event_callback'
CMD_RESPOND_MSG = 'aibot_respond_msg'
CMD_RESPOND_WELCOME = 'aibot_respond_welcome_msg'
CMD_RESPOND_UPDATE = 'aibot_respond_update_msg'
CMD_SEND_MSG = 'aibot_send_msg'
def _generate_req_id(prefix: str) -> str:
"""Generate a unique request ID in the format: {prefix}_{timestamp}_{random}."""
ts = int(time.time() * 1000)
rand = secrets.token_hex(4)
return f'{prefix}_{ts}_{rand}'
class WecomBotWsClient:
"""WeChat Work AI Bot WebSocket long connection client.
Provides message receiving, streaming reply, proactive message sending,
and event callback handling over a persistent WebSocket connection.
"""
def __init__(
self,
bot_id: str,
secret: str,
logger: EventLogger,
encoding_aes_key: str = '',
ws_url: str = DEFAULT_WS_URL,
heartbeat_interval: float = 30.0,
max_reconnect_attempts: int = -1,
reconnect_base_delay: float = 1.0,
reconnect_max_delay: float = 30.0,
):
self.bot_id = bot_id
self.secret = secret
self.logger = logger
self.encoding_aes_key = encoding_aes_key
self.ws_url = ws_url
self.heartbeat_interval = heartbeat_interval
self.max_reconnect_attempts = max_reconnect_attempts
self.reconnect_base_delay = reconnect_base_delay
self.reconnect_max_delay = reconnect_max_delay
self._ws: Optional[aiohttp.ClientWebSocketResponse] = None
self._session: Optional[aiohttp.ClientSession] = None
self._running = False
self._heartbeat_task: Optional[asyncio.Task] = None
self._missed_pong_count = 0
self._max_missed_pong = 2
self._reconnect_attempts = 0
# Message handler registry (same pattern as WecomBotClient)
self._message_handlers: dict[str, list[Callable]] = {}
# Message deduplication
self._msg_id_map: dict[str, int] = {}
# Pending ACK futures: req_id -> Future[dict]
self._pending_acks: dict[str, asyncio.Future] = {}
# Per-req_id serial reply queues
self._reply_queues: dict[str, asyncio.Queue] = {}
self._reply_workers: dict[str, asyncio.Task] = {}
self._reply_ack_timeout = 5.0
# Stream ID tracking for WebSocket mode
self._stream_ids: dict[str, str] = {} # msg_id -> req_id|stream_id
# Dedup: skip sending when content hasn't changed
self._stream_last_content: dict[str, str] = {} # msg_id -> last content sent
# Stream session info for feedback tracking
self._stream_sessions: dict[str, dict] = {} # msg_id -> session info
# Feedback tracking: feedback_id -> session info
self._feedback_sessions: dict[str, dict] = {} # feedback_id -> {msg_id, user_id, chat_id, stream_id, req_id}
# msg_id -> feedback_id (for associating feedback with message)
self._msg_feedback_ids: dict[str, str] = {} # msg_id -> feedback_id
# ── Public API ──────────────────────────────────────────────────
async def connect(self):
"""Connect to WebSocket server with automatic reconnection.
This method blocks until disconnect() is called or max reconnect
attempts are exhausted.
"""
self._running = True
self._reconnect_attempts = 0
while self._running:
try:
await self._connect_once()
except Exception:
if not self._running:
break
await self.logger.error(f'WebSocket connection error: {traceback.format_exc()}')
if not self._running:
break
# Reconnect with exponential backoff
if self.max_reconnect_attempts != -1 and self._reconnect_attempts >= self.max_reconnect_attempts:
await self.logger.error(f'Max reconnect attempts reached ({self.max_reconnect_attempts}), giving up')
break
self._reconnect_attempts += 1
delay = min(
self.reconnect_base_delay * (2 ** (self._reconnect_attempts - 1)),
self.reconnect_max_delay,
)
await self.logger.info(f'Reconnecting in {delay:.1f}s (attempt {self._reconnect_attempts})...')
await asyncio.sleep(delay)
async def disconnect(self):
"""Gracefully disconnect from the WebSocket server."""
self._running = False
if self._heartbeat_task and not self._heartbeat_task.done():
self._heartbeat_task.cancel()
for task in self._reply_workers.values():
if not task.done():
task.cancel()
if self._ws and not self._ws.closed:
await self._ws.close()
self._ws = None
if self._session and not self._session.closed:
await self._session.close()
self._session = None
def on_message(self, msg_type: str) -> Callable:
"""Decorator to register a message handler.
Same interface as WecomBotClient.on_message for compatibility.
Args:
msg_type: 'single', 'group', or specific message type.
"""
def decorator(func: Callable[[wecombotevent.WecomBotEvent], Any]):
if msg_type not in self._message_handlers:
self._message_handlers[msg_type] = []
self._message_handlers[msg_type].append(func)
return func
return decorator
def on_feedback(self) -> Callable:
"""Decorator to register a feedback event handler.
Same interface as WecomBotClient.on_feedback for compatibility.
"""
def decorator(func: Callable):
if 'feedback' not in self._message_handlers:
self._message_handlers['feedback'] = []
self._message_handlers['feedback'].append(func)
return func
return decorator
async def reply_stream(
self,
req_id: str,
stream_id: str,
content: str,
finish: bool = False,
feedback_id: str = '',
) -> Optional[dict]:
"""Send a streaming reply frame.
Args:
req_id: The req_id from the original message frame (must be passed through).
stream_id: The stream ID for this streaming session.
content: The content to send (supports Markdown).
finish: Whether this is the final chunk.
feedback_id: Optional feedback ID for receiving user feedback (like/dislike).
Returns:
The ACK frame dict, or None on failure.
"""
stream_payload = {
'id': stream_id,
'finish': finish,
'content': content,
}
if feedback_id:
stream_payload['feedback'] = {'id': feedback_id}
body = {
'msgtype': 'stream',
'stream': stream_payload,
}
return await self._send_reply(req_id, body)
async def reply_text(self, req_id: str, content: str) -> Optional[dict]:
"""Send a non-streaming text reply.
Args:
req_id: The req_id from the original message frame.
content: The text content to reply.
Returns:
The ACK frame dict, or None on failure.
"""
body = {
'msgtype': 'markdown',
'markdown': {
'content': content,
},
}
return await self._send_reply(req_id, body)
async def send_message(self, chat_id: str, content: str, msgtype: str = 'markdown') -> Optional[dict]:
"""Proactively send a message to a specified chat.
Args:
chat_id: The chat ID (userid for single chat, chatid for group chat).
content: The message content.
msgtype: Message type, 'markdown' by default.
Returns:
The ACK frame dict, or None on failure.
"""
req_id = _generate_req_id(CMD_SEND_MSG)
body: dict[str, Any] = {
'chatid': chat_id,
'msgtype': msgtype,
}
if msgtype == 'markdown':
body['markdown'] = {'content': content}
elif msgtype == 'text':
body['text'] = {'content': content}
return await self._send_reply(req_id, body, cmd=CMD_SEND_MSG)
async def push_stream_chunk(self, msg_id: str, content: str, is_final: bool = False) -> bool:
"""Push a streaming chunk for a given message ID.
Compatible interface with WecomBotClient.push_stream_chunk.
Args:
msg_id: The original message ID.
content: The cumulative content from the pipeline.
is_final: Whether this is the final chunk.
Returns:
True if the stream session exists and chunk was sent.
"""
key = self._stream_ids.get(msg_id)
if not key:
return False
req_id, stream_id = key.split('|', 1)
try:
# Skip sending if content hasn't changed (e.g. during tool call argument streaming)
if not is_final and content == self._stream_last_content.get(msg_id):
return True
# Generate feedback_id for final chunk
feedback_id = ''
if is_final:
feedback_id = _generate_req_id('feedback')
self._msg_feedback_ids[msg_id] = feedback_id
# Store session info for feedback tracking
session_info = self._stream_sessions.get(msg_id)
if session_info:
self._feedback_sessions[feedback_id] = session_info
await self.reply_stream(req_id, stream_id, content, finish=is_final, feedback_id=feedback_id)
self._stream_last_content[msg_id] = content
if is_final:
self._stream_ids.pop(msg_id, None)
self._stream_last_content.pop(msg_id, None)
self._stream_sessions.pop(msg_id, None)
return True
except Exception:
await self.logger.error(f'Failed to push stream chunk: {traceback.format_exc()}')
return False
async def set_message(self, msg_id: str, content: str):
"""Fallback: send content as a final stream chunk or direct reply.
Compatible interface with WecomBotClient.set_message.
"""
handled = await self.push_stream_chunk(msg_id, content, is_final=True)
if not handled:
await self.logger.warning(f'No active stream for msg_id={msg_id}, message dropped')
# ── Connection lifecycle ────────────────────────────────────────
async def _connect_once(self):
"""Establish a single WebSocket connection, authenticate, and listen."""
await self.logger.info(f'Connecting to {self.ws_url}...')
self._session = aiohttp.ClientSession()
try:
self._ws = await self._session.ws_connect(self.ws_url)
self._missed_pong_count = 0
self._reconnect_attempts = 0
await self.logger.info('WebSocket connected, sending auth...')
await self._send_auth()
# Wait for auth response
auth_ok = await self._wait_for_auth()
if not auth_ok:
await self.logger.error('Authentication failed')
return
await self.logger.info('Authenticated successfully')
# Start heartbeat
self._heartbeat_task = asyncio.create_task(self._heartbeat_loop())
try:
await self._listen_loop()
finally:
if self._heartbeat_task and not self._heartbeat_task.done():
self._heartbeat_task.cancel()
self._clear_pending_acks('Connection closed')
finally:
if self._ws and not self._ws.closed:
await self._ws.close()
self._ws = None
if self._session and not self._session.closed:
await self._session.close()
self._session = None
async def _send_auth(self):
"""Send the authentication frame."""
frame = {
'cmd': CMD_SUBSCRIBE,
'headers': {'req_id': _generate_req_id(CMD_SUBSCRIBE)},
'body': {
'bot_id': self.bot_id,
'secret': self.secret,
},
}
await self._send_frame(frame)
async def _wait_for_auth(self) -> bool:
"""Wait for and validate the authentication response."""
try:
msg = await asyncio.wait_for(self._ws.receive(), timeout=10.0)
if msg.type in (aiohttp.WSMsgType.TEXT,):
frame = json.loads(msg.data)
req_id = frame.get('headers', {}).get('req_id', '')
if req_id.startswith(CMD_SUBSCRIBE) and frame.get('errcode') == 0:
return True
await self.logger.error(f'Auth response: errcode={frame.get("errcode")}, errmsg={frame.get("errmsg")}')
return False
elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
await self.logger.error(f'WebSocket closed during auth: {msg.type}')
return False
await self.logger.error(f'Unexpected message type during auth: {msg.type}')
return False
except asyncio.TimeoutError:
await self.logger.error('Auth response timeout')
return False
async def _heartbeat_loop(self):
"""Periodically send heartbeat pings."""
try:
while self._running and self._ws and not self._ws.closed:
await asyncio.sleep(self.heartbeat_interval)
if not self._running or not self._ws or self._ws.closed:
break
if self._missed_pong_count >= self._max_missed_pong:
await self.logger.warning(
f'No heartbeat ack for {self._missed_pong_count} consecutive pings, connection considered dead'
)
await self._ws.close()
break
self._missed_pong_count += 1
frame = {
'cmd': CMD_HEARTBEAT,
'headers': {'req_id': _generate_req_id(CMD_HEARTBEAT)},
}
try:
await self._send_frame(frame)
except Exception:
break
except asyncio.CancelledError:
pass
async def _listen_loop(self):
"""Listen for incoming WebSocket frames and dispatch them."""
async for msg in self._ws:
if not self._running:
break
if msg.type == aiohttp.WSMsgType.TEXT:
try:
frame = json.loads(msg.data)
await self._handle_frame(frame)
except json.JSONDecodeError:
await self.logger.error(f'Failed to parse WebSocket message: {str(msg.data)[:200]}')
except Exception:
await self.logger.error(f'Error handling frame: {traceback.format_exc()}')
elif msg.type == aiohttp.WSMsgType.BINARY:
try:
frame = json.loads(msg.data)
await self._handle_frame(frame)
except Exception:
await self.logger.error(f'Error handling binary frame: {traceback.format_exc()}')
elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
await self.logger.warning(f'WebSocket connection closed: {msg.type}')
break
# ── Frame handling ──────────────────────────────────────────────
async def _handle_frame(self, frame: dict):
"""Route an incoming frame to the appropriate handler."""
cmd = frame.get('cmd', '')
# Message push
if cmd == CMD_MSG_CALLBACK:
asyncio.create_task(self._handle_message_callback(frame))
return
# Event push
if cmd == CMD_EVENT_CALLBACK:
asyncio.create_task(self._handle_event_callback(frame))
return
# No cmd → response/ACK frame, dispatch by req_id prefix
req_id = frame.get('headers', {}).get('req_id', '')
# Check pending ACKs first
if req_id in self._pending_acks:
future = self._pending_acks.pop(req_id)
if not future.done():
future.set_result(frame)
return
# Heartbeat response
if req_id.startswith(CMD_HEARTBEAT):
if frame.get('errcode') == 0:
self._missed_pong_count = 0
return
# Unknown frame
await self.logger.warning(f'Unknown frame: {json.dumps(frame, ensure_ascii=False)[:200]}')
async def _handle_message_callback(self, frame: dict):
"""Handle an incoming message callback frame."""
try:
body = frame.get('body', {})
req_id = frame.get('headers', {}).get('req_id', '')
# Parse message using shared logic
message_data = await parse_wecom_bot_message(body, self.encoding_aes_key, self.logger)
if not message_data:
return
# Generate stream_id for this message and store the mapping
stream_id = _generate_req_id('stream')
msg_id = message_data.get('msgid', '')
if msg_id:
self._stream_ids[msg_id] = f'{req_id}|{stream_id}'
# Store session info for feedback tracking
self._stream_sessions[msg_id] = {
'req_id': req_id,
'stream_id': stream_id,
'msg_id': msg_id,
'user_id': message_data.get('userid', ''),
'chat_id': message_data.get('chatid', ''),
'chat_type': message_data.get('type', 'single'),
}
message_data['stream_id'] = stream_id
message_data['req_id'] = req_id
event = wecombotevent.WecomBotEvent(message_data)
await self._dispatch_event(event)
except Exception:
await self.logger.error(f'Error in message callback: {traceback.format_exc()}')
async def _handle_event_callback(self, frame: dict):
"""Handle an incoming event callback frame (enter_chat, template_card_event, feedback_event, disconnected_event)."""
try:
body = frame.get('body', {})
req_id = frame.get('headers', {}).get('req_id', '')
event_info = body.get('event', {})
event_type = event_info.get('eventtype', '')
message_data = {
'msgtype': 'event',
'type': body.get('chattype', 'single'),
'event': event_info,
'eventtype': event_type,
'msgid': body.get('msgid', ''),
'aibotid': body.get('aibotid', ''),
'req_id': req_id,
}
from_info = body.get('from', {})
message_data['userid'] = from_info.get('userid', '')
message_data['username'] = from_info.get('alias', '') or from_info.get('userid', '')
if body.get('chatid'):
message_data['chatid'] = body.get('chatid', '')
if event_type == 'feedback_event':
feedback_event = event_info.get('feedback_event', {})
feedback_id = feedback_event.get('id', '')
feedback_type = feedback_event.get('type', 0)
feedback_content = feedback_event.get('content', '')
inaccurate_reasons = feedback_event.get('inaccurate_reason_list', [])
await self.logger.info(
f'收到用户反馈事件: feedback_id={feedback_id}, type={feedback_type}, '
f'content={feedback_content}, reasons={inaccurate_reasons}'
)
# Look up session by feedback_id
session_info = self._feedback_sessions.get(feedback_id)
session = None
if session_info:
session = StreamSession(
stream_id=session_info.get('stream_id', ''),
msg_id=session_info.get('msg_id', ''),
chat_id=session_info.get('chat_id') or None,
user_id=session_info.get('user_id') or None,
feedback_id=feedback_id,
)
await self.logger.info(
f'反馈关联到会话: stream_id={session.stream_id}, msg_id={session.msg_id}, user_id={session.user_id}'
)
else:
await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话')
for handler in self._message_handlers.get('feedback', []):
try:
await handler(
feedback_id=feedback_id,
feedback_type=feedback_type,
feedback_content=feedback_content,
inaccurate_reasons=inaccurate_reasons,
session=session,
)
except Exception:
await self.logger.error(f'Error in feedback handler: {traceback.format_exc()}')
return
event = wecombotevent.WecomBotEvent(message_data)
if event_type in self._message_handlers:
for handler in self._message_handlers[event_type]:
await handler(event)
if 'event' in self._message_handlers:
for handler in self._message_handlers['event']:
await handler(event)
except Exception:
await self.logger.error(f'Error in event callback: {traceback.format_exc()}')
async def _dispatch_event(self, event: wecombotevent.WecomBotEvent):
"""Dispatch a message event to registered handlers with deduplication."""
try:
message_id = event.message_id
if message_id in self._msg_id_map:
self._msg_id_map[message_id] += 1
return
self._msg_id_map[message_id] = 1
msg_type = event.type
if msg_type in self._message_handlers:
for handler in self._message_handlers[msg_type]:
await handler(event)
except Exception:
await self.logger.error(f'Error dispatching event: {traceback.format_exc()}')
# ── Reply sending with serial queue ─────────────────────────────
async def _send_reply(
self,
req_id: str,
body: dict,
cmd: str = CMD_RESPOND_MSG,
) -> Optional[dict]:
"""Send a reply frame and wait for ACK.
Replies with the same req_id are serialized to maintain ordering.
"""
if not self._ws or self._ws.closed:
return None
frame = {
'cmd': cmd,
'headers': {'req_id': req_id},
'body': body,
}
# Ensure serial delivery per req_id
if req_id not in self._reply_queues:
self._reply_queues[req_id] = asyncio.Queue()
self._reply_workers[req_id] = asyncio.create_task(self._reply_queue_worker(req_id))
future: asyncio.Future = asyncio.get_event_loop().create_future()
await self._reply_queues[req_id].put((frame, future))
return await future
async def _reply_queue_worker(self, req_id: str):
"""Process reply queue items serially for a given req_id."""
queue = self._reply_queues[req_id]
try:
while self._running:
try:
frame, future = await asyncio.wait_for(queue.get(), timeout=60.0)
except asyncio.TimeoutError:
# Queue idle, clean up worker
break
try:
ack = await self._send_and_wait_ack(frame)
if not future.done():
future.set_result(ack)
except Exception as e:
if not future.done():
future.set_exception(e)
except asyncio.CancelledError:
pass
finally:
self._reply_queues.pop(req_id, None)
self._reply_workers.pop(req_id, None)
async def _send_and_wait_ack(self, frame: dict) -> Optional[dict]:
"""Send a frame and wait for the corresponding ACK."""
req_id = frame['headers']['req_id']
ack_future: asyncio.Future = asyncio.get_event_loop().create_future()
self._pending_acks[req_id] = ack_future
try:
await self._send_frame(frame)
result = await asyncio.wait_for(ack_future, timeout=self._reply_ack_timeout)
if result.get('errcode', 0) != 0:
await self.logger.warning(
f'Reply ACK error: errcode={result.get("errcode")}, errmsg={result.get("errmsg")}'
)
return result
except asyncio.TimeoutError:
self._pending_acks.pop(req_id, None)
await self.logger.warning(f'Reply ACK timeout ({self._reply_ack_timeout}s) for req_id={req_id}')
return None
async def _send_frame(self, frame: dict):
"""Send a JSON frame over the WebSocket connection."""
if self._ws and not self._ws.closed:
await self._ws.send_str(json.dumps(frame, ensure_ascii=False))
def _clear_pending_acks(self, reason: str):
"""Reject all pending ACK futures on disconnection."""
for req_id, future in self._pending_acks.items():
if not future.done():
future.set_exception(ConnectionError(reason))
self._pending_acks.clear()

View File

@@ -4,7 +4,6 @@ import base64
import binascii
import httpx
import traceback
from urllib.parse import quote
from quart import Quart
import xml.etree.ElementTree as ET
from typing import Callable, Dict, Any
@@ -22,30 +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': [],
}
@@ -58,7 +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()
@@ -68,31 +60,6 @@ class WecomClient:
await self.logger.error(f'获取accesstoken失败:{response.json()}')
raise Exception(f'未获取access token: {data}')
async def get_user_info(self, userid: str) -> dict:
"""
Get user information by user ID using the application secret.
Args:
userid: The user ID to look up.
Returns:
dict: User information including 'name' field.
"""
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = self.base_url + '/user/get?access_token=' + self.access_token + '&userid=' + quote(userid)
async with httpx.AsyncClient() as client:
response = await client.get(url)
data = response.json()
if data.get('errcode') == 40014 or data.get('errcode') == 42001:
self.access_token = await self.get_access_token(self.secret)
return await self.get_user_info(userid)
if data.get('errcode', 0) != 0:
await self.logger.error(f'获取用户信息失败:{data}')
return {}
return data
async def get_users(self):
if not self.check_access_token_for_contacts():
self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)
@@ -142,13 +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,
},
@@ -157,73 +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',
@@ -246,43 +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')
@@ -366,7 +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
"""
@@ -383,7 +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:
@@ -418,7 +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')
@@ -426,128 +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

@@ -10,41 +10,22 @@ from typing import Callable
from .wecomcsevent import WecomCSEvent
import langbot_plugin.api.entities.builtin.platform.message as platform_message
import aiofiles
import time
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__)
# Customer info cache: {external_userid: (info_dict, timestamp)}
self._customer_cache: dict[str, tuple[dict, float]] = {}
self._cache_ttl = 60 # Cache TTL in seconds (1 minute)
# 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': [],
}
@@ -80,7 +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()
@@ -186,7 +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,
@@ -211,45 +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}')
@@ -383,53 +346,3 @@ class WecomCSClient:
async def get_media_id(self, image: platform_message.Image):
media_id = await self.upload_to_work(image=image)
return media_id
async def get_customer_info(self, external_userid: str) -> dict | None:
"""
Get customer information by external_userid with caching.
Uses a 1-minute cache to avoid repeated API calls for the same user.
Args:
external_userid: The external user ID of the customer.
Returns:
Customer info dict with 'nickname', 'avatar', etc., or None if not found.
"""
# Check cache first
current_time = time.time()
if external_userid in self._customer_cache:
cached_info, cached_time = self._customer_cache[external_userid]
if current_time - cached_time < self._cache_ttl:
return cached_info
# Cache miss or expired, fetch from API
if not await self.check_access_token():
self.access_token = await self.get_access_token(self.secret)
url = f'{self.base_url}/kf/customer/batchget?access_token={self.access_token}'
payload = {
'external_userid_list': [external_userid],
}
async with httpx.AsyncClient() as client:
response = await client.post(url, json=payload)
data = response.json()
if data.get('errcode') in [40014, 42001]:
self.access_token = await self.get_access_token(self.secret)
return await self.get_customer_info(external_userid)
if data.get('errcode', 0) != 0:
if self.logger:
await self.logger.warning(f'Failed to get customer info: {data}')
return None
customer_list = data.get('customer_list', [])
if customer_list:
customer_info = customer_list[0]
# Store in cache
self._customer_cache[external_userid] = (customer_info, current_time)
return customer_info
return None

View File

@@ -13,9 +13,9 @@ from .. import group
@group.group_class('files', '/api/v1/files')
class FilesRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/image/<path:image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
@self.route('/image/<image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
async def _(image_key: str) -> quart.Response:
if '..' in image_key or '\\' in image_key:
if '/' in image_key or '\\' in image_key:
return quart.Response(status=404)
if not await self.ap.storage_mgr.storage_provider.exists(image_key):
@@ -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()
@@ -13,10 +13,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
elif quart.request.method == 'POST':
json_data = await quart.request.json
try:
knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
except ValueError as e:
return self.http_status(400, -1, str(e))
knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
return self.success(data={'uuid': knowledge_base_uuid})
return self.http_status(405, -1, 'Method not allowed')
@@ -24,7 +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':
@@ -42,7 +38,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
elif quart.request.method == 'PUT':
json_data = await quart.request.json
await self.ap.knowledge_service.update_knowledge_base(knowledge_base_uuid, json_data)
return self.success(data={'uuid': knowledge_base_uuid})
return self.success({})
elif quart.request.method == 'DELETE':
await self.ap.knowledge_service.delete_knowledge_base(knowledge_base_uuid)
@@ -51,7 +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':
@@ -68,12 +63,8 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
if not file_id:
return self.http_status(400, -1, 'File ID is required')
parser_plugin_id = json_data.get('parser_plugin_id')
# 调用服务层方法将文件与知识库关联
task_id = await self.ap.knowledge_service.store_file(
knowledge_base_uuid, file_id, parser_plugin_id=parser_plugin_id
)
task_id = await self.ap.knowledge_service.store_file(knowledge_base_uuid, file_id)
return self.success(
{
'task_id': task_id,
@@ -83,7 +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)
@@ -92,18 +82,9 @@ 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
query = json_data.get('query')
if not query or not query.strip():
return self.http_status(400, -1, 'Query is required and cannot be empty')
# Extract retrieval_settings to allow dynamic control over Knowledge Engine behavior (e.g. top_k, filters)
retrieval_settings = json_data.get('retrieval_settings', {})
results = await self.ap.knowledge_service.retrieve_knowledge_base(
knowledge_base_uuid, query, retrieval_settings
)
results = await self.ap.knowledge_service.retrieve_knowledge_base(knowledge_base_uuid, query)
return self.success(data={'results': results})

View File

@@ -1,45 +0,0 @@
import quart
from urllib.parse import unquote
from ... import group
@group.group_class('knowledge_engines', '/api/v1/knowledge/engines')
class KnowledgeEnginesRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def list_knowledge_engines() -> quart.Response:
"""List all available Knowledge Engines from plugins.
Returns a list of Knowledge Engines with their capabilities and configuration schemas.
This is used by the frontend to render the knowledge base creation wizard.
"""
engines = await self.ap.knowledge_service.list_knowledge_engines()
return self.success(data={'engines': engines})
@self.route(
'/<path:plugin_id>/creation-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
)
async def get_engine_creation_schema(plugin_id: str) -> quart.Response:
"""Get creation settings schema for a specific Knowledge Engine.
plugin_id is in 'author/name' format, captured via <path:> converter.
"""
plugin_id = unquote(plugin_id)
if '/' not in plugin_id:
return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
schema = await self.ap.knowledge_service.get_engine_creation_schema(plugin_id)
return self.success(data={'schema': schema})
@self.route(
'/<path:plugin_id>/retrieval-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
)
async def get_engine_retrieval_schema(plugin_id: str) -> quart.Response:
"""Get retrieval settings schema for a specific Knowledge Engine.
plugin_id is in 'author/name' format, captured via <path:> converter.
"""
plugin_id = unquote(plugin_id)
if '/' not in plugin_id:
return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
schema = await self.ap.knowledge_service.get_engine_retrieval_schema(plugin_id)
return self.success(data={'schema': schema})

View File

@@ -1,372 +0,0 @@
import asyncio
import json
import httpx
import quart
import sqlalchemy
from ... import group
from ......core import taskmgr
from ......entity.persistence import metadata as persistence_metadata
from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
LANGRAG_PLUGIN_AUTHOR = 'langbot-team'
LANGRAG_PLUGIN_NAME = 'LangRAG'
LANGRAG_PLUGIN_ID = f'{LANGRAG_PLUGIN_AUTHOR}/{LANGRAG_PLUGIN_NAME}'
DEFAULT_SPACE_URL = 'https://space.langbot.app'
# Old Retriever plugin_name -> New Connector plugin_name
EXTERNAL_PLUGIN_NAME_MAPPING = {
'DifyDatasetsRetriever': 'DifyDatasetsConnector',
'RAGFlowRetriever': 'RAGFlowConnector',
'FastGPTRetriever': 'FastGPTConnector',
}
# Per-plugin: which old retriever_config fields belong to creation_settings.
# Remaining fields go to retrieval_settings.
# None means ALL fields go to creation_settings (no retrieval_schema).
EXTERNAL_PLUGIN_CREATION_FIELDS: dict[str, set[str] | None] = {
'langbot-team/DifyDatasetsConnector': {'api_base_url', 'dify_apikey', 'dataset_id'},
'langbot-team/RAGFlowConnector': {'api_base_url', 'api_key', 'dataset_ids'},
'langbot-team/FastGPTConnector': None, # all fields -> creation_settings
}
@group.group_class('knowledge/migration', '/api/v1/knowledge/migration')
class KnowledgeMigrationRouterGroup(group.RouterGroup):
async def _get_migration_flag(self) -> bool:
"""Check if rag_plugin_migration_needed flag is set."""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_metadata.Metadata).where(
persistence_metadata.Metadata.key == 'rag_plugin_migration_needed'
)
)
row = result.first()
return row is not None and row.value == 'true'
async def _set_migration_flag(self, value: str):
"""Set rag_plugin_migration_needed flag."""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_metadata.Metadata)
.where(persistence_metadata.Metadata.key == 'rag_plugin_migration_needed')
.values(value=value)
)
async def _table_exists(self, table_name: str) -> bool:
"""Check if a table exists."""
if self.ap.persistence_mgr.db.name == 'postgresql':
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
).bindparams(table_name=table_name)
)
return result.scalar()
else:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
table_name=table_name
)
)
return result.first() is not None
async def _install_plugin_from_marketplace(
self, plugin_id: str, task_context: taskmgr.TaskContext, space_url: str
) -> None:
"""Install a single plugin from the marketplace."""
p_author, p_name = plugin_id.split('/', 1)
self.ap.logger.info(f'RAG migration: installing plugin {plugin_id} from marketplace...')
task_context.trace(f'Installing plugin {plugin_id} from marketplace...')
async with httpx.AsyncClient(trust_env=True, timeout=15) as client:
resp = await client.get(f'{space_url}/api/v1/marketplace/plugins/{p_author}/{p_name}')
resp.raise_for_status()
p_data = resp.json().get('data', {}).get('plugin', {})
p_version = p_data.get('latest_version')
if not p_version:
raise Exception(f'Could not determine latest version for {plugin_id}')
await self.ap.plugin_connector.install_plugin(
PluginInstallSource.MARKETPLACE,
{
'plugin_author': p_author,
'plugin_name': p_name,
'plugin_version': p_version,
},
task_context=task_context,
)
self.ap.logger.info(f'RAG migration: plugin {plugin_id} install request sent.')
async def _execute_rag_migration(self, task_context: taskmgr.TaskContext, install_plugin: bool = True):
"""Execute RAG migration: install required plugins and restore backup data."""
warnings = []
# Collect all plugins we need: LangRAG (always) + connector plugins (from external KBs)
needed_plugins: dict[str, str] = {
LANGRAG_PLUGIN_ID: LANGRAG_PLUGIN_NAME,
}
has_external = await self._table_exists('external_knowledge_bases')
if has_external:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT DISTINCT plugin_author, plugin_name FROM external_knowledge_bases;')
)
for row in result.fetchall():
plugin_author = row[0] or ''
plugin_name = row[1] or ''
mapped_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
plugin_id = f'{plugin_author}/{mapped_name}'
if plugin_id not in needed_plugins:
needed_plugins[plugin_id] = mapped_name
self.ap.logger.info(f'RAG migration: plugins needed: {list(needed_plugins.keys())}')
if install_plugin:
# Step 1: Install all required plugins from marketplace
task_context.trace('Installing required plugins...', action='install-plugin')
space_url = self.ap.instance_config.data.get('space', {}).get('url', DEFAULT_SPACE_URL).rstrip('/')
for plugin_id in needed_plugins:
try:
await self._install_plugin_from_marketplace(plugin_id, task_context, space_url)
except Exception as e:
self.ap.logger.warning(f'RAG migration: plugin {plugin_id} install returned: {e}')
task_context.trace(f'Plugin install note ({plugin_id}): {e}')
# Step 2: Wait for all plugins to become available as knowledge engines
task_context.trace(
f'Waiting for plugins to become available: {list(needed_plugins.keys())}...',
action='wait-plugin',
)
max_retries = 30
engine_id_set: set[str] = set()
for i in range(max_retries):
try:
engines = await self.ap.plugin_connector.list_knowledge_engines()
engine_id_set = {e.get('plugin_id') for e in engines}
except Exception:
pass
if all(pid in engine_id_set for pid in needed_plugins):
self.ap.logger.info(f'RAG migration: all plugins ready: {engine_id_set}')
task_context.trace('All required plugins are ready.')
break
if i == max_retries - 1:
still_missing = [pid for pid in needed_plugins if pid not in engine_id_set]
warning = f'Plugin(s) {still_missing} did not become available after {max_retries} retries'
self.ap.logger.warning(f'RAG migration: {warning}')
warnings.append(warning)
task_context.trace(warning)
await asyncio.sleep(2)
else:
try:
engines = await self.ap.plugin_connector.list_knowledge_engines()
engine_id_set = {e.get('plugin_id') for e in engines}
except Exception:
engine_id_set = set()
# Step 3: Restore internal knowledge bases from backup
task_context.trace('Restoring internal knowledge bases...', action='restore-internal')
if await self._table_exists('knowledge_bases_backup'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT * FROM knowledge_bases_backup;')
)
rows = result.fetchall()
columns = result.keys()
for row in rows:
row_dict = dict(zip(columns, row))
kb_uuid = row_dict.get('uuid')
name = row_dict.get('name', 'Untitled')
description = row_dict.get('description', '')
emoji = row_dict.get('emoji', '\U0001f4da')
embedding_model_uuid = row_dict.get('embedding_model_uuid', '')
top_k = row_dict.get('top_k', 5)
created_at = row_dict.get('created_at')
updated_at = row_dict.get('updated_at')
creation_settings = json.dumps({'embedding_model_uuid': embedding_model_uuid})
retrieval_settings = json.dumps({'top_k': top_k})
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'INSERT INTO knowledge_bases '
'(uuid, name, description, emoji, created_at, updated_at, '
'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
).bindparams(
uuid=kb_uuid,
name=name,
description=description,
emoji=emoji,
created_at=created_at,
updated_at=updated_at,
plugin_id=LANGRAG_PLUGIN_ID,
collection_id=kb_uuid,
creation_settings=creation_settings,
retrieval_settings=retrieval_settings,
)
)
try:
config = {'embedding_model_uuid': embedding_model_uuid}
await self.ap.plugin_connector.rag_on_kb_create(LANGRAG_PLUGIN_ID, kb_uuid, config)
task_context.trace(f'Restored internal KB: {name} ({kb_uuid})')
except Exception as e:
warning = f'Failed to notify plugin for KB {name} ({kb_uuid}): {e}'
warnings.append(warning)
task_context.trace(warning)
await self.ap.rag_mgr.load_knowledge_bases_from_db()
# Step 4: Restore external knowledge bases
task_context.trace('Restoring external knowledge bases...', action='restore-external')
if has_external:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT * FROM external_knowledge_bases;')
)
rows = result.fetchall()
columns = result.keys()
self.ap.logger.info(
f'RAG migration: {len(rows)} external KB(s) to restore. Available engines: {engine_id_set}'
)
task_context.trace(f'Found {len(rows)} external KB(s). Available engines: {engine_id_set}')
for row in rows:
row_dict = dict(zip(columns, row))
kb_uuid = row_dict.get('uuid')
name = row_dict.get('name', 'Untitled')
description = row_dict.get('description', '')
emoji = row_dict.get('emoji', '\U0001f517')
plugin_author = row_dict.get('plugin_author', '')
plugin_name = row_dict.get('plugin_name', '')
retriever_config = row_dict.get('retriever_config', {})
created_at = row_dict.get('created_at')
mapped_plugin_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
external_plugin_id = f'{plugin_author}/{mapped_plugin_name}'
self.ap.logger.info(
f'RAG migration: processing external KB "{name}" ({kb_uuid}), '
f'plugin: {plugin_author}/{plugin_name} -> {external_plugin_id}'
)
if isinstance(retriever_config, str):
try:
retriever_config = json.loads(retriever_config)
except (json.JSONDecodeError, TypeError):
retriever_config = {}
creation_fields = EXTERNAL_PLUGIN_CREATION_FIELDS.get(external_plugin_id)
if creation_fields is None:
creation_settings_dict = retriever_config
retrieval_settings_dict = {}
else:
creation_settings_dict = {k: v for k, v in retriever_config.items() if k in creation_fields}
retrieval_settings_dict = {k: v for k, v in retriever_config.items() if k not in creation_fields}
await self.ap.persistence_mgr.execute_async(
sqlalchemy.text(
'INSERT INTO knowledge_bases '
'(uuid, name, description, emoji, created_at, updated_at, '
'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
).bindparams(
uuid=kb_uuid,
name=name,
description=description,
emoji=emoji,
created_at=created_at,
updated_at=created_at,
plugin_id=external_plugin_id,
collection_id=kb_uuid,
creation_settings=json.dumps(creation_settings_dict),
retrieval_settings=json.dumps(retrieval_settings_dict),
)
)
if external_plugin_id not in engine_id_set:
warning = (
f'External KB "{name}" ({kb_uuid}) record saved, but plugin {external_plugin_id} '
f'is not installed yet. Install the connector plugin to use it.'
)
warnings.append(warning)
task_context.trace(warning)
else:
try:
await self.ap.plugin_connector.rag_on_kb_create(
external_plugin_id, kb_uuid, creation_settings_dict
)
task_context.trace(f'Restored external KB: {name} ({kb_uuid})')
except Exception as e:
warning = f'Failed to notify plugin for external KB {name} ({kb_uuid}): {e}'
warnings.append(warning)
task_context.trace(warning)
await self.ap.rag_mgr.load_knowledge_bases_from_db()
# Step 5: Clear migration flag
await self._set_migration_flag('false')
task_context.trace('RAG migration completed.', action='done')
if warnings:
task_context.trace(f'Completed with {len(warnings)} warning(s).')
async def initialize(self) -> None:
@self.route('/status', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
internal_kb_count = 0
external_kb_count = 0
if needed:
if await self._table_exists('knowledge_bases_backup'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases_backup;')
)
internal_kb_count = result.scalar() or 0
if await self._table_exists('external_knowledge_bases'):
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
)
external_kb_count = result.scalar() or 0
return self.success(
data={
'needed': needed,
'internal_kb_count': internal_kb_count,
'external_kb_count': external_kb_count,
}
)
@self.route('/execute', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
if not needed:
return self.http_status(400, -1, 'RAG migration is not needed')
data = await quart.request.get_json(silent=True) or {}
install_plugin = data.get('install_plugin', True)
ctx = taskmgr.TaskContext.new()
wrapper = self.ap.task_mgr.create_user_task(
self._execute_rag_migration(task_context=ctx, install_plugin=install_plugin),
kind='rag-migration',
name='rag-migration-execute',
label='Migrating knowledge bases to plugin architecture',
context=ctx,
)
return self.success(data={'task_id': wrapper.id})
@self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
needed = await self._get_migration_flag()
if not needed:
return self.http_status(400, -1, 'RAG migration is not needed')
await self._set_migration_flag('false')
return self.success()

View File

@@ -1,16 +0,0 @@
import quart
from ... import group
@group.group_class('parsers', '/api/v1/knowledge/parsers')
class ParsersRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def list_parsers() -> quart.Response:
"""List all available parsers from plugins.
Optional query parameter `mime_type` to filter parsers by supported MIME type.
"""
mime_type = quart.request.args.get('mime_type')
parsers = await self.ap.knowledge_service.list_parsers(mime_type)
return self.success(data={'parsers': parsers})

View File

@@ -1,573 +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',
]
elif export_type == 'feedback':
data = await self.ap.monitoring_service.export_feedback(
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',
'feedback_id',
'feedback_type',
'feedback_content',
'inaccurate_reasons',
'bot_id',
'bot_name',
'pipeline_id',
'pipeline_name',
'session_id',
'message_id',
'stream_id',
'user_id',
'platform',
]
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
@self.route('/feedback/stats', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_feedback_stats() -> str:
"""Get feedback statistics"""
# 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)
stats = await self.ap.monitoring_service.get_feedback_stats(
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=stats)
@self.route('/feedback', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def get_feedback() -> str:
"""Get feedback list"""
# Parse query parameters
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
feedback_type_str = quart.request.args.get('feedbackType')
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)
# Parse feedback type
feedback_type = int(feedback_type_str) if feedback_type_str else None
feedback_list, total = await self.ap.monitoring_service.get_feedback_list(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
feedback_type=feedback_type,
start_time=start_time,
end_time=end_time,
limit=limit,
offset=offset,
)
return self.success(
data={
'feedback': feedback_list,
'total': total,
'limit': limit,
'offset': offset,
}
)

View File

@@ -1,384 +0,0 @@
"""Embed widget routes - serve embeddable chat widget for external websites.
All user-facing URLs are keyed by **bot_uuid** (not pipeline_uuid) so that
internal pipeline identifiers are never exposed to end-users. Each handler
resolves the bot_uuid to the owning ``web_page_bot`` RuntimeBot and extracts
the bound pipeline_uuid for internal routing.
"""
import asyncio
import datetime
import json
import logging
import uuid
import hmac
import hashlib
import time
import re
import httpx
import quart
from ... import group
from ......utils import paths
from ......platform.sources.websocket_manager import ws_connection_manager
logger = logging.getLogger(__name__)
# Cache the widget template content
_widget_template_cache: str | None = None
_logo_bytes_cache: bytes | None = None
def _is_valid_uuid(s: str) -> bool:
return bool(re.match(r'^[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}$', s))
def _get_widget_template() -> str:
"""Load and cache the widget JS template."""
global _widget_template_cache
if _widget_template_cache is None:
template_path = paths.get_resource_path('templates/embed/widget.js')
with open(template_path, 'r', encoding='utf-8') as f:
_widget_template_cache = f.read()
return _widget_template_cache
def _get_logo_bytes() -> bytes:
"""Load and cache the logo image."""
global _logo_bytes_cache
if _logo_bytes_cache is None:
logo_path = paths.get_resource_path('templates/embed/logo.webp')
with open(logo_path, 'rb') as f:
_logo_bytes_cache = f.read()
return _logo_bytes_cache
@group.group_class('embed', '/api/v1/embed')
class EmbedRouterGroup(group.RouterGroup):
# -- helpers -------------------------------------------------------------
def _resolve_bot(self, bot_uuid: str):
"""Resolve *bot_uuid* to ``(runtime_bot, pipeline_uuid)``.
Returns ``(None, None)`` when the bot does not exist, is not a
``web_page_bot``, is disabled, or has no pipeline bound.
"""
for bot in self.ap.platform_mgr.bots:
if (
bot.bot_entity.uuid == bot_uuid
and bot.bot_entity.adapter == 'web_page_bot'
and bot.bot_entity.enable
and bot.bot_entity.use_pipeline_uuid
):
return bot, bot.bot_entity.use_pipeline_uuid
return None, None
def _get_bot_config(self, bot_uuid: str) -> dict:
for bot in self.ap.platform_mgr.bots:
if bot.bot_entity.uuid == bot_uuid and bot.bot_entity.adapter == 'web_page_bot':
return bot.bot_entity.adapter_config
return {}
async def _verify_session_token(self, request, bot_uuid: str) -> bool:
config = self._get_bot_config(bot_uuid)
secret = config.get('turnstile_secret_key', '')
if not secret:
return True
auth_header = request.headers.get('Authorization', '')
if not auth_header.startswith('Bearer '):
return False
token = auth_header[7:]
try:
ts_str, mac = token.split('.', 1)
ts = float(ts_str)
if time.time() - ts > 86400:
return False
expected_mac = hmac.new(secret.encode(), f'{ts_str}'.encode(), hashlib.sha256).hexdigest()
return hmac.compare_digest(mac, expected_mac)
except Exception:
return False
# -- routes --------------------------------------------------------------
async def initialize(self) -> None:
@self.route('/<bot_uuid>/turnstile/verify', methods=['POST'], auth_type=group.AuthType.NONE)
async def verify_turnstile(bot_uuid: str) -> str:
if not _is_valid_uuid(bot_uuid):
return self.http_status(400, -1, 'Invalid bot_uuid format')
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
return self.http_status(404, -1, 'Bot not found or not available')
try:
data = await quart.request.get_json()
token = data.get('token')
if not token:
return self.http_status(400, -1, 'Token is required')
config = self._get_bot_config(bot_uuid)
secret = config.get('turnstile_secret_key', '')
if not secret:
ts = time.time()
return self.success(data={'token': f'{ts}.dummy'})
async with httpx.AsyncClient() as client:
resp = await client.post(
'https://challenges.cloudflare.com/turnstile/v0/siteverify',
data={'secret': secret, 'response': token},
)
result = resp.json()
if not result.get('success'):
return self.http_status(403, -1, 'Turnstile verification failed')
ts = time.time()
mac = hmac.new(secret.encode(), f'{ts}'.encode(), hashlib.sha256).hexdigest()
session_token = f'{ts}.{mac}'
return self.success(data={'token': session_token})
except Exception as e:
logger.error(f'Turnstile verify failed: {e}', exc_info=True)
return self.http_status(500, -1, 'Internal server error')
@self.route('/<bot_uuid>/widget.js', methods=['GET'], auth_type=group.AuthType.NONE)
async def serve_widget(bot_uuid: str) -> quart.Response:
"""Serve the embed widget JavaScript with injected configuration."""
if not _is_valid_uuid(bot_uuid):
return self.http_status(400, -1, 'Invalid bot_uuid format')
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
return quart.Response(
'// Bot not found or not available', status=404, content_type='application/javascript'
)
try:
template = _get_widget_template()
except FileNotFoundError:
return quart.Response('// Widget template not found', status=404, content_type='application/javascript')
base_url = quart.request.host_url.rstrip('/')
webhook_prefix = self.ap.instance_config.data.get('api', {}).get('webhook_prefix', '')
if webhook_prefix:
base_url = webhook_prefix.rstrip('/')
if not re.match(r'^https?://[a-zA-Z0-9._:/-]+$', base_url):
base_url = quart.request.host_url.rstrip('/')
config = self._get_bot_config(bot_uuid)
site_key = config.get('turnstile_site_key', '')
locale = config.get('language', 'en_US') or 'en_US'
bubble_icon = config.get('bubble_icon', 'logo') or 'logo'
widget_js = template.replace('__LANGBOT_TURNSTILE_SITE_KEY__', site_key)
widget_js = widget_js.replace('__LANGBOT_BOT_UUID__', bot_uuid)
widget_js = widget_js.replace('__LANGBOT_BASE_URL__', base_url)
widget_js = widget_js.replace('__LANGBOT_LOCALE__', locale)
widget_js = widget_js.replace('__LANGBOT_BUBBLE_ICON__', bubble_icon)
response = quart.Response(widget_js, content_type='application/javascript; charset=utf-8')
response.headers['Cache-Control'] = 'public, max-age=300'
return response
@self.route('/logo', methods=['GET'], auth_type=group.AuthType.NONE)
async def serve_logo() -> quart.Response:
"""Serve the LangBot logo for the embed widget."""
try:
logo_data = _get_logo_bytes()
except FileNotFoundError:
return quart.Response('', status=404)
response = quart.Response(logo_data, content_type='image/webp')
response.headers['Cache-Control'] = 'public, max-age=86400'
return response
@self.route('/<bot_uuid>/messages/<session_type>', methods=['GET'], auth_type=group.AuthType.NONE)
async def get_embed_messages(bot_uuid: str, session_type: str) -> str:
if not _is_valid_uuid(bot_uuid):
return self.http_status(400, -1, 'Invalid bot_uuid format')
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
return self.http_status(404, -1, 'Bot not found or not available')
if not await self._verify_session_token(quart.request, bot_uuid):
return self.http_status(403, -1, 'Unauthorized or session expired')
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:
logger.error(f'Failed to get embed messages: {e}', exc_info=True)
return self.http_status(500, -1, 'Internal server error')
@self.route('/<bot_uuid>/reset/<session_type>', methods=['POST'], auth_type=group.AuthType.NONE)
async def reset_embed_session(bot_uuid: str, session_type: str) -> str:
if not _is_valid_uuid(bot_uuid):
return self.http_status(400, -1, 'Invalid bot_uuid format')
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
return self.http_status(404, -1, 'Bot not found or not available')
if not await self._verify_session_token(quart.request, bot_uuid):
return self.http_status(403, -1, 'Unauthorized or session expired')
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:
logger.error(f'Failed to reset embed session: {e}', exc_info=True)
return self.http_status(500, -1, 'Internal server error')
@self.route('/<bot_uuid>/feedback', methods=['POST'], auth_type=group.AuthType.NONE)
async def submit_feedback(bot_uuid: str) -> str:
if not _is_valid_uuid(bot_uuid):
return self.http_status(400, -1, 'Invalid bot_uuid format')
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
return self.http_status(404, -1, 'Bot not found or not available')
if not await self._verify_session_token(quart.request, bot_uuid):
return self.http_status(403, -1, 'Unauthorized or session expired')
try:
data = await quart.request.get_json()
message_id = data.get('message_id', '')
feedback_type = data.get('feedback_type')
if feedback_type not in (1, 2, 3):
return self.http_status(400, -1, 'feedback_type must be 1 (like), 2 (dislike), or 3 (cancel)')
feedback_id = f'embed_{uuid.uuid4().hex[:12]}'
await self.ap.monitoring_service.record_feedback(
feedback_id=feedback_id,
feedback_type=feedback_type,
bot_id=runtime_bot.bot_entity.uuid,
bot_name=runtime_bot.bot_entity.name or bot_uuid,
pipeline_id=pipeline_uuid,
message_id=str(message_id),
platform='web_page_bot',
)
return self.success(data={'feedback_id': feedback_id})
except Exception as e:
logger.error(f'Failed to record feedback: {e}', exc_info=True)
return self.http_status(500, -1, 'Internal server error')
# -- Embed WebSocket endpoint ----------------------------------------
@self.quart_app.websocket(self.path + '/<bot_uuid>/ws/connect')
async def embed_websocket_connect(bot_uuid: str):
"""WebSocket connection for embed widget, keyed by bot_uuid."""
if not _is_valid_uuid(bot_uuid):
await quart.websocket.send(json.dumps({'type': 'error', 'message': 'Invalid bot_uuid format'}))
return
runtime_bot, pipeline_uuid = self._resolve_bot(bot_uuid)
if runtime_bot is None:
await quart.websocket.send(json.dumps({'type': 'error', 'message': 'Bot not found or not available'}))
return
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
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
try:
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', '')},
)
await quart.websocket.send(
json.dumps(
{
'type': 'connected',
'connection_id': connection.connection_id,
'bot_uuid': bot_uuid,
'session_type': session_type,
'timestamp': connection.created_at.isoformat(),
}
)
)
logger.debug(
f'Embed WebSocket connected: {connection.connection_id} '
f'(bot={bot_uuid}, pipeline={pipeline_uuid}, session_type={session_type})'
)
receive_task = asyncio.create_task(self._handle_receive(connection, websocket_adapter, runtime_bot))
send_task = asyncio.create_task(self._handle_send(connection))
try:
await asyncio.gather(receive_task, send_task)
except Exception as e:
logger.error(f'Embed WebSocket task error: {e}')
finally:
await ws_connection_manager.remove_connection(connection.connection_id)
except Exception as e:
logger.error(f'Embed WebSocket connection error: {e}', exc_info=True)
try:
await quart.websocket.send(json.dumps({'type': 'error', 'message': 'Internal server error'}))
except Exception:
pass
# -- WebSocket receive/send helpers --------------------------------------
async def _handle_receive(self, connection, websocket_adapter, owner_bot):
try:
while connection.is_active:
message = await quart.websocket.receive()
await ws_connection_manager.update_activity(connection.connection_id)
try:
data = json.loads(message)
message_type = data.get('type', 'message')
if message_type == 'ping':
await connection.send_queue.put(
{'type': 'pong', 'timestamp': datetime.datetime.now().isoformat()}
)
elif message_type == 'message':
await websocket_adapter.handle_websocket_message(connection, data, owner_bot=owner_bot)
elif message_type == 'disconnect':
break
except json.JSONDecodeError:
await connection.send_queue.put({'type': 'error', 'message': 'Invalid JSON format'})
except Exception as e:
logger.error(f'Embed receive error: {e}', exc_info=True)
finally:
connection.is_active = False
async def _handle_send(self, connection):
try:
while connection.is_active:
try:
message = await asyncio.wait_for(connection.send_queue.get(), timeout=1.0)
await quart.websocket.send(json.dumps(message))
except asyncio.TimeoutError:
continue
except Exception as e:
logger.error(f'Embed send error: {e}', exc_info=True)
finally:
connection.is_active = False

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 KnowledgeEngine 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

@@ -1,253 +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
# Find the owning bot for this pipeline (e.g. a web_page_bot)
owner_bot = self._find_owner_bot(pipeline_uuid)
# 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, owner_bot))
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)}')
def _find_owner_bot(self, pipeline_uuid: str):
"""Find a user-created bot (e.g. web_page_bot) that owns this pipeline."""
for bot in self.ap.platform_mgr.bots:
if bot.bot_entity.adapter == 'web_page_bot' and bot.bot_entity.use_pipeline_uuid == pipeline_uuid:
return bot
return None
async def _handle_receive(self, connection, websocket_adapter, owner_bot=None):
"""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, owner_bot=owner_bot)
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

@@ -1,6 +1,5 @@
import quart
import mimetypes
import asyncio
from ... import group
from langbot.pkg.utils import importutil
@@ -36,640 +35,3 @@ class AdaptersRouterGroup(group.RouterGroup):
return quart.Response(
importutil.read_resource_file_bytes(icon_path), mimetype=mimetypes.guess_type(icon_path)[0]
)
# In-memory session store for active registrations
_create_app_sessions: dict = {}
_SESSION_TTL = 900 # 15 minutes
def _cleanup_expired_sessions():
"""Remove sessions that have exceeded their TTL."""
import time
now = time.time()
expired = [sid for sid, s in _create_app_sessions.items() if now - s.get('created_at', 0) > _SESSION_TTL]
for sid in expired:
session = _create_app_sessions.pop(sid, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
@self.route('/lark/create-app', methods=['POST'])
async def _() -> str:
"""Start Feishu one-click app registration. Returns session_id + QR code URL."""
import uuid
import time
import lark_oapi as lark
from lark_oapi.scene.registration.errors import AppAccessDeniedError, AppExpiredError
_cleanup_expired_sessions()
session_id = str(uuid.uuid4())
loop = asyncio.get_running_loop()
session = {
'status': 'pending',
'qr_url': None,
'expire_at': None,
'app_id': None,
'app_secret': None,
'error': None,
'created_at': time.time(),
}
_create_app_sessions[session_id] = session
def on_qr_code(info):
# May be called from a background thread by the SDK;
# use call_soon_threadsafe to safely update session state.
def _update():
session['qr_url'] = info['url']
session['expire_at'] = time.time() + 600 # 10 minutes
session['status'] = 'waiting'
loop.call_soon_threadsafe(_update)
async def run_registration():
try:
result = await lark.aregister_app(
on_qr_code=on_qr_code,
source='langbot',
)
session['status'] = 'success'
session['app_id'] = result['client_id']
session['app_secret'] = result['client_secret']
except AppAccessDeniedError:
session['status'] = 'error'
session['error'] = 'User denied authorization'
except AppExpiredError:
session['status'] = 'error'
session['error'] = 'QR code expired'
except Exception as e:
session['status'] = 'error'
session['error'] = str(e)
task = asyncio.create_task(run_registration())
session['task'] = task
# Wait for QR code to be ready (max 10 seconds)
for _ in range(20):
if session['qr_url']:
break
await asyncio.sleep(0.5)
if not session['qr_url']:
task.cancel()
session['status'] = 'error'
session['error'] = 'Timeout waiting for QR code'
return self.http_status(504, -1, 'Timeout waiting for QR code')
return self.success(
data={
'session_id': session_id,
'qr_url': session['qr_url'],
'expire_at': session['expire_at'],
}
)
@self.route('/lark/create-app/status/<session_id>', methods=['GET'])
async def _(session_id: str) -> str:
"""Poll registration status."""
session = _create_app_sessions.get(session_id)
if not session:
return self.http_status(404, -1, 'Session not found')
data = {'status': session['status']}
if session['status'] == 'success':
data['app_id'] = session['app_id']
data['app_secret'] = session['app_secret']
_create_app_sessions.pop(session_id, None)
elif session['status'] == 'error':
data['error'] = session['error']
_create_app_sessions.pop(session_id, None)
return self.success(data=data)
@self.route('/lark/create-app/<session_id>', methods=['DELETE'])
async def _(session_id: str) -> str:
"""Cancel and clean up a registration session."""
session = _create_app_sessions.pop(session_id, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
return self.success(data={})
# -----------------------------------------------------------------------
# WeChat QR Code Login
# -----------------------------------------------------------------------
_weixin_login_sessions: dict = {}
_WEIXIN_SESSION_TTL = 600 # 10 minutes (3 retries × 3 min QR validity)
def _cleanup_expired_weixin_sessions():
import time
now = time.time()
expired = [
sid for sid, s in _weixin_login_sessions.items() if now - s.get('created_at', 0) > _WEIXIN_SESSION_TTL
]
for sid in expired:
session = _weixin_login_sessions.pop(sid, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
@self.route('/weixin/login', methods=['POST'])
async def _() -> str:
"""Start WeChat QR code login. Returns session_id + QR code data URL."""
import uuid
import time
import io
import base64
from langbot.libs.openclaw_weixin_api.client import OpenClawWeixinClient, DEFAULT_BASE_URL
_cleanup_expired_weixin_sessions()
session_id = str(uuid.uuid4())
loop = asyncio.get_running_loop()
session = {
'status': 'pending',
'qr_data_url': None,
'expire_at': None,
'token': None,
'base_url': None,
'account_id': None,
'error': None,
'created_at': time.time(),
}
_weixin_login_sessions[session_id] = session
client = OpenClawWeixinClient(
base_url=DEFAULT_BASE_URL,
token='',
)
async def run_login():
try:
import qrcode as qr_lib
for _attempt in range(3):
qr_resp = await client.fetch_qrcode()
if not qr_resp.qrcode or not qr_resp.qrcode_img_content:
raise Exception('Failed to get QR code from server')
# Generate QR code image locally
qr = qr_lib.QRCode(error_correction=qr_lib.constants.ERROR_CORRECT_L)
qr.add_data(qr_resp.qrcode_img_content)
qr.make(fit=True)
img = qr.make_image(fill_color='black', back_color='white')
buf = io.BytesIO()
img.save(buf, format='PNG')
b64 = base64.b64encode(buf.getvalue()).decode('utf-8')
data_url = f'data:image/png;base64,{b64}'
def _update_qr():
session['qr_data_url'] = data_url
session['expire_at'] = time.time() + 480 # 8 minutes
session['status'] = 'waiting'
loop.call_soon_threadsafe(_update_qr)
# Poll for scan status
deadline = loop.time() + 180
while loop.time() < deadline:
try:
status_resp = await client.poll_qrcode_status(qr_resp.qrcode)
except Exception:
await asyncio.sleep(2)
continue
if status_resp.status == 'confirmed' and status_resp.bot_token:
session['status'] = 'success'
session['token'] = status_resp.bot_token
session['base_url'] = status_resp.baseurl or client.base_url
session['account_id'] = status_resp.ilink_bot_id or ''
return
if status_resp.status == 'expired':
break # retry with new QR code
await asyncio.sleep(1)
else:
pass # timeout, retry
# All retries exhausted
session['status'] = 'error'
session['error'] = 'QR code login failed: max retries exceeded'
except Exception as e:
session['status'] = 'error'
session['error'] = str(e)
finally:
await client.close()
task = asyncio.create_task(run_login())
session['task'] = task
# Wait for QR code to be ready (max 10 seconds)
for _ in range(20):
if session['qr_data_url']:
break
await asyncio.sleep(0.5)
if not session['qr_data_url']:
task.cancel()
session['status'] = 'error'
session['error'] = 'Timeout waiting for QR code'
return self.http_status(504, -1, 'Timeout waiting for QR code')
return self.success(
data={
'session_id': session_id,
'qr_data_url': session['qr_data_url'],
'expire_at': session['expire_at'],
}
)
@self.route('/weixin/login/status/<session_id>', methods=['GET'])
async def _(session_id: str) -> str:
"""Poll WeChat login status."""
session = _weixin_login_sessions.get(session_id)
if not session:
return self.http_status(404, -1, 'Session not found')
data = {'status': session['status']}
if session['status'] == 'success':
data['token'] = session['token']
data['base_url'] = session['base_url']
data['account_id'] = session['account_id']
_weixin_login_sessions.pop(session_id, None)
elif session['status'] == 'error':
data['error'] = session['error']
_weixin_login_sessions.pop(session_id, None)
return self.success(data=data)
@self.route('/weixin/login/<session_id>', methods=['DELETE'])
async def _(session_id: str) -> str:
"""Cancel and clean up a WeChat login session."""
session = _weixin_login_sessions.pop(session_id, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
return self.success(data={})
# -----------------------------------------------------------------------
# DingTalk Device Flow QR Code Login
# -----------------------------------------------------------------------
_dingtalk_sessions: dict = {}
_DINGTALK_SESSION_TTL = 600 # 10 minutes (QR code validity window)
def _cleanup_expired_dingtalk_sessions():
import time
now = time.time()
expired = [
sid for sid, s in _dingtalk_sessions.items() if now - s.get('created_at', 0) > _DINGTALK_SESSION_TTL
]
for sid in expired:
session = _dingtalk_sessions.pop(sid, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
@self.route('/dingtalk/create-app', methods=['POST'])
async def _() -> str:
"""Start DingTalk one-click app creation via Device Flow. Returns session_id + QR code URL."""
import uuid
import time
import aiohttp
DINGTALK_BASE_URL = 'https://oapi.dingtalk.com'
_cleanup_expired_dingtalk_sessions()
session_id = str(uuid.uuid4())
session = {
'status': 'pending',
'qr_url': None,
'expire_at': None,
'client_id': None,
'client_secret': None,
'error': None,
'created_at': time.time(),
'device_code': None,
'interval': 5,
}
_dingtalk_sessions[session_id] = session
async def run_device_flow():
try:
timeout = aiohttp.ClientTimeout(total=10)
async with aiohttp.ClientSession(timeout=timeout) as http:
# Step 1: Init — get nonce
async with http.post(
f'{DINGTALK_BASE_URL}/app/registration/init',
json={'source': 'langbot'},
) as resp:
try:
data = await resp.json()
except (aiohttp.ContentTypeError, ValueError):
session['status'] = 'error'
session['error'] = 'Invalid response from DingTalk service'
return
if data.get('errcode', -1) != 0:
session['status'] = 'error'
session['error'] = data.get('errmsg', 'Failed to init')
return
nonce = data['nonce']
# Step 2: Begin — get device_code + QR URL
async with http.post(
f'{DINGTALK_BASE_URL}/app/registration/begin',
json={'nonce': nonce},
) as resp:
try:
data = await resp.json()
except (aiohttp.ContentTypeError, ValueError):
session['status'] = 'error'
session['error'] = 'Invalid response from DingTalk service'
return
if data.get('errcode', -1) != 0:
session['status'] = 'error'
session['error'] = data.get('errmsg', 'Failed to begin authorization')
return
device_code = data['device_code']
verification_uri_complete = data.get('verification_uri_complete', '')
expires_in = data.get('expires_in', 7200)
interval = data.get('interval', 5)
session['device_code'] = device_code
session['interval'] = interval
session['qr_url'] = verification_uri_complete
session['expire_at'] = time.time() + 600 # QR code valid for ~10 min
session['status'] = 'waiting'
# Step 3: Poll for authorization result
deadline = time.time() + expires_in
while time.time() < deadline:
await asyncio.sleep(interval)
async with http.post(
f'{DINGTALK_BASE_URL}/app/registration/poll',
json={'device_code': device_code},
) as poll_resp:
try:
poll_data = await poll_resp.json()
except (aiohttp.ContentTypeError, ValueError):
continue
if poll_data.get('errcode', -1) != 0:
session['status'] = 'error'
session['error'] = poll_data.get('errmsg', 'Poll failed')
return
status = poll_data.get('status', '')
if status == 'SUCCESS':
session['status'] = 'success'
session['client_id'] = poll_data.get('client_id', '')
session['client_secret'] = poll_data.get('client_secret', '')
return
elif status == 'FAIL':
session['status'] = 'error'
session['error'] = poll_data.get('fail_reason', 'Authorization failed')
return
elif status == 'EXPIRED':
session['status'] = 'error'
session['error'] = 'QR code expired'
return
# status == 'WAITING': continue polling
# Timeout
session['status'] = 'error'
session['error'] = 'QR code expired'
except asyncio.CancelledError:
return
except Exception as e:
session['status'] = 'error'
session['error'] = str(e)
task = asyncio.create_task(run_device_flow())
session['task'] = task
# Wait for QR code to be ready (max 10 seconds)
for _ in range(20):
if session['qr_url'] or session['error']:
break
await asyncio.sleep(0.5)
if session['error']:
task.cancel()
return self.http_status(502, -1, session['error'])
if not session['qr_url']:
task.cancel()
session['status'] = 'error'
session['error'] = 'Timeout waiting for QR code'
return self.http_status(504, -1, 'Timeout waiting for QR code')
return self.success(
data={
'session_id': session_id,
'qr_url': session['qr_url'],
'expire_at': session['expire_at'],
}
)
@self.route('/dingtalk/create-app/status/<session_id>', methods=['GET'])
async def _(session_id: str) -> str:
"""Poll DingTalk Device Flow status."""
_cleanup_expired_dingtalk_sessions()
session = _dingtalk_sessions.get(session_id)
if not session:
return self.http_status(404, -1, 'Session not found')
data = {'status': session['status']}
if session['status'] == 'success':
data['client_id'] = session['client_id']
data['client_secret'] = session['client_secret']
_dingtalk_sessions.pop(session_id, None)
elif session['status'] == 'error':
data['error'] = session['error']
_dingtalk_sessions.pop(session_id, None)
return self.success(data=data)
@self.route('/dingtalk/create-app/<session_id>', methods=['DELETE'])
async def _(session_id: str) -> str:
"""Cancel and clean up a DingTalk Device Flow session."""
session = _dingtalk_sessions.pop(session_id, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
return self.success(data={})
# -----------------------------------------------------------------------
# WeComBot QR Code One-Click Create
# -----------------------------------------------------------------------
_wecombot_sessions: dict = {}
_WECOMBOT_SESSION_TTL = 300 # 5 minutes (WeCom QR validity window)
def _cleanup_expired_wecombot_sessions():
import time
now = time.time()
expired = [
sid for sid, s in _wecombot_sessions.items() if now - s.get('created_at', 0) > _WECOMBOT_SESSION_TTL
]
for sid in expired:
session = _wecombot_sessions.pop(sid, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
@self.route('/wecombot/create-bot', methods=['POST'])
async def _() -> str:
"""Start WeComBot one-click creation via QR code. Returns session_id + QR code URL."""
import uuid
import time
import aiohttp
WECOM_QC_GENERATE_URL = 'https://work.weixin.qq.com/ai/qc/generate'
WECOM_QC_QUERY_URL = 'https://work.weixin.qq.com/ai/qc/query_result'
_cleanup_expired_wecombot_sessions()
session_id = str(uuid.uuid4())
session = {
'status': 'pending',
'qr_url': None,
'expire_at': None,
'botid': None,
'secret': None,
'error': None,
'created_at': time.time(),
'scode': None,
'task': None,
}
_wecombot_sessions[session_id] = session
async def run_qr_flow():
try:
timeout = aiohttp.ClientTimeout(total=10)
async with aiohttp.ClientSession(timeout=timeout) as http:
# Step 1: Generate QR code
async with http.get(
f'{WECOM_QC_GENERATE_URL}?source=langbot&plat=0',
) as resp:
try:
data = await resp.json()
except (aiohttp.ContentTypeError, ValueError):
session['status'] = 'error'
session['error'] = 'Invalid response from WeCom service'
return
if not data.get('data', {}).get('scode') or not data.get('data', {}).get('auth_url'):
session['status'] = 'error'
session['error'] = data.get('errmsg', 'Failed to generate QR code')
return
scode = data['data']['scode']
auth_url = data['data']['auth_url']
session['scode'] = scode
session['qr_url'] = auth_url
session['expire_at'] = time.time() + _WECOMBOT_SESSION_TTL
session['status'] = 'waiting'
# Step 2: Poll for scan result
deadline = time.time() + _WECOMBOT_SESSION_TTL
while time.time() < deadline:
await asyncio.sleep(3)
async with http.get(
f'{WECOM_QC_QUERY_URL}?scode={scode}',
) as poll_resp:
try:
poll_data = await poll_resp.json()
except (aiohttp.ContentTypeError, ValueError):
continue
status = poll_data.get('data', {}).get('status', '')
if status == 'success':
bot_info = poll_data.get('data', {}).get('bot_info', {})
if bot_info.get('botid') and bot_info.get('secret'):
session['status'] = 'success'
session['botid'] = bot_info['botid']
session['secret'] = bot_info['secret']
return
else:
session['status'] = 'error'
session['error'] = 'Scan succeeded but bot info is incomplete'
return
# Timeout
session['status'] = 'error'
session['error'] = 'QR code expired'
except asyncio.CancelledError:
return
except Exception as e:
session['status'] = 'error'
session['error'] = str(e)
task = asyncio.create_task(run_qr_flow())
session['task'] = task
# Wait for QR code to be ready (max 10 seconds)
for _ in range(20):
if session['qr_url'] or session['error']:
break
await asyncio.sleep(0.5)
if session['error']:
task.cancel()
return self.http_status(502, -1, session['error'])
if not session['qr_url']:
task.cancel()
session['status'] = 'error'
session['error'] = 'Timeout waiting for QR code'
return self.http_status(504, -1, 'Timeout waiting for QR code')
return self.success(
data={
'session_id': session_id,
'qr_url': session['qr_url'],
'expire_at': session['expire_at'],
}
)
@self.route('/wecombot/create-bot/status/<session_id>', methods=['GET'])
async def _(session_id: str) -> str:
"""Poll WeComBot creation status."""
_cleanup_expired_wecombot_sessions()
session = _wecombot_sessions.get(session_id)
if not session:
return self.http_status(404, -1, 'Session not found')
data = {'status': session['status']}
if session['status'] == 'success':
data['botid'] = session['botid']
data['secret'] = session['secret']
_wecombot_sessions.pop(session_id, None)
elif session['status'] == 'error':
data['error'] = session['error']
_wecombot_sessions.pop(session_id, None)
return self.success(data=data)
@self.route('/wecombot/create-bot/<session_id>', methods=['DELETE'])
async def _(session_id: str) -> str:
"""Cancel and clean up a WeComBot creation session."""
session = _wecombot_sessions.pop(session_id, None)
if session and session.get('task') and not session['task'].done():
session['task'].cancel()
return self.success(data={})

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

@@ -6,99 +6,25 @@ import re
import httpx
import uuid
import os
import posixpath
from .....core import taskmgr
from .. import group
from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
# Resolve the built-in page SDK JS from the langbot_plugin package
_PAGE_SDK_PATH = None
try:
import langbot_plugin.assets as _assets_pkg
_candidate = os.path.join(os.path.dirname(_assets_pkg.__file__), 'langbot-page-sdk.js')
if os.path.exists(_candidate):
_PAGE_SDK_PATH = _candidate
except Exception:
pass
def _normalize_plugin_asset_path(filepath: str) -> str | None:
filepath = filepath.replace('\\', '/')
if filepath.startswith('/'):
return None
normalized = posixpath.normpath(filepath)
if normalized == '.' or normalized.startswith('../') or normalized == '..':
return None
if normalized.startswith('components/pages/'):
return normalized
return f'assets/{normalized}'
def _get_request_origin() -> str:
"""Return the public request origin, respecting reverse-proxy headers."""
forwarded_proto = quart.request.headers.get('X-Forwarded-Proto', '').split(',')[0].strip()
forwarded_host = quart.request.headers.get('X-Forwarded-Host', '').split(',')[0].strip()
scheme = forwarded_proto or quart.request.scheme
host = forwarded_host or quart.request.host
return f'{scheme}://{host}'
@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('/_sdk/page-sdk.js', methods=['GET'], auth_type=group.AuthType.NONE)
async def _() -> quart.Response:
"""Serve the built-in LangBot page SDK JavaScript."""
if _PAGE_SDK_PATH and os.path.exists(_PAGE_SDK_PATH):
with open(_PAGE_SDK_PATH, 'r') as f:
content = f.read()
return quart.Response(content, mimetype='application/javascript')
return quart.Response('// SDK not found', status=404, mimetype='application/javascript')
@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()
@@ -114,7 +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':
@@ -140,7 +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)
@@ -156,16 +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'],
@@ -180,65 +96,7 @@ class PluginsRouterGroup(group.RouterGroup):
return quart.Response(icon_data, mimetype=mime_type)
@self.route(
'/<author>/<plugin_name>/assets/<path:filepath>',
methods=['GET'],
auth_type=group.AuthType.NONE,
)
async def _(author: str, plugin_name: str, filepath: str) -> quart.Response:
asset_path = _normalize_plugin_asset_path(filepath)
if asset_path is None:
return quart.Response('Asset not found', status=404)
asset_data = await self.ap.plugin_connector.get_plugin_assets(author, plugin_name, asset_path)
if not asset_data.get('asset_base64'):
return quart.Response('Asset not found', status=404)
asset_bytes = base64.b64decode(asset_data['asset_base64'])
mime_type = asset_data['mime_type']
resp = quart.Response(asset_bytes, mimetype=mime_type)
# CSP for HTML pages served to sandboxed iframes (opaque origin).
# 'self' doesn't work in sandboxed iframes — use actual server origin.
if mime_type and mime_type.startswith('text/html'):
origin = _get_request_origin()
resp.headers['Content-Security-Policy'] = (
f'default-src {origin}; '
f"script-src {origin} 'unsafe-inline'; "
f"style-src {origin} 'unsafe-inline'; "
f'img-src {origin} data:; '
f'connect-src {origin}; '
"frame-src 'none'; "
"object-src 'none'"
)
return resp
@self.route(
'/<author>/<plugin_name>/page-api',
methods=['POST'],
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
)
async def _(author: str, plugin_name: str) -> str:
"""Forward a page API request to the plugin."""
data = await quart.request.json
if not isinstance(data, dict):
return self.http_status(400, -1, 'invalid request body')
page_id = data.get('page_id', '')
endpoint = data.get('endpoint', '')
method = data.get('method', 'POST')
body = data.get('body')
if not isinstance(page_id, str) or not isinstance(endpoint, str) or not isinstance(method, str):
return self.http_status(400, -1, 'invalid page api request')
if not endpoint.startswith('/') or '..' in endpoint:
return self.http_status(400, -1, 'invalid endpoint')
result = await self.ap.plugin_connector.handle_page_api(
author, plugin_name, page_id, endpoint, method.upper(), body
)
if result.get('error'):
return self.http_status(400, -1, result['error'])
return self.success(data=result.get('data'))
@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
@@ -287,7 +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"""
@@ -341,13 +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', '')
@@ -358,8 +212,6 @@ class PluginsRouterGroup(group.RouterGroup):
return self.http_status(400, -1, 'Missing asset_url parameter')
ctx = taskmgr.TaskContext.new()
ctx.metadata['plugin_name'] = f'{owner}/{repo}'
ctx.metadata['install_source'] = 'github'
install_info = {
'asset_url': asset_url,
'owner': owner,
@@ -381,37 +233,24 @@ 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
plugin_author = data.get('plugin_author', '')
plugin_name = data.get('plugin_name', '')
ctx = taskmgr.TaskContext.new()
ctx.metadata['plugin_name'] = f'{plugin_author}/{plugin_name}'
ctx.metadata['install_source'] = 'marketplace'
wrapper = self.ap.task_mgr.create_user_task(
self.ap.plugin_connector.install_plugin(PluginInstallSource.MARKETPLACE, data, task_context=ctx),
kind='plugin-operation',
name='plugin-install-marketplace',
label=f'Installing plugin from marketplace {plugin_author}/{plugin_name}',
label=f'Installing plugin from marketplace ...{data}',
context=ctx,
)
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')
@@ -423,13 +262,11 @@ class PluginsRouterGroup(group.RouterGroup):
}
ctx = taskmgr.TaskContext.new()
ctx.metadata['plugin_name'] = file.filename or 'local plugin'
ctx.metadata['install_source'] = 'local'
wrapper = self.ap.task_mgr.create_user_task(
self.ap.plugin_connector.install_plugin(PluginInstallSource.LOCAL, data, task_context=ctx),
kind='plugin-operation',
name='plugin-install-local',
label=f'Installing plugin from local {file.filename}',
label=f'Installing plugin from local ...{file.filename}',
context=ctx,
)

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)
@@ -97,51 +87,3 @@ class EmbeddingModelsRouterGroup(group.RouterGroup):
await self.ap.embedding_models_service.test_embedding_model(model_uuid, json_data)
return self.success()
@group.group_class('models/rerank', '/api/v1/provider/models/rerank')
class RerankModelsRouterGroup(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':
provider_uuid = quart.request.args.get('provider_uuid')
if provider_uuid:
return self.success(
data={
'models': await self.ap.rerank_models_service.get_rerank_models_by_provider(provider_uuid)
}
)
return self.success(data={'models': await self.ap.rerank_models_service.get_rerank_models()})
elif quart.request.method == 'POST':
json_data = await quart.request.json
model_uuid = await self.ap.rerank_models_service.create_rerank_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)
async def _(model_uuid: str) -> str:
if quart.request.method == 'GET':
model = await self.ap.rerank_models_service.get_rerank_model(model_uuid)
if model is None:
return self.http_status(404, -1, 'model not found')
return self.success(data={'model': model})
elif quart.request.method == 'PUT':
json_data = await quart.request.json
await self.ap.rerank_models_service.update_rerank_model(model_uuid, json_data)
return self.success()
elif quart.request.method == 'DELETE':
await self.ap.rerank_models_service.delete_rerank_model(model_uuid)
return self.success()
@self.route('/<model_uuid>/test', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _(model_uuid: str) -> str:
json_data = await quart.request.json
await self.ap.rerank_models_service.test_rerank_model(model_uuid, json_data)
return self.success()

View File

@@ -1,56 +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']
provider['rerank_count'] = counts['rerank_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']
provider['rerank_count'] = counts['rerank_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))
@self.route('/<provider_uuid>/scan-models', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
async def _(provider_uuid: str) -> str:
try:
model_type = quart.request.args.get('type')
result = await self.ap.provider_service.scan_provider_models(provider_uuid, model_type)
return self.success(data=result)
except ValueError as e:
return self.http_status(400, -1, str(e))

View File

@@ -1,45 +0,0 @@
from __future__ import annotations
from ... import group
@group.group_class('tools', '/api/v1/tools')
class ToolsRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
"""获取所有可用工具列表"""
tools = await self.ap.tool_mgr.get_all_tools()
tool_list = []
for tool in tools:
tool_list.append(
{
'name': tool.name,
'description': tool.description,
'human_desc': tool.human_desc,
'parameters': tool.parameters,
}
)
return self.success(data={'tools': tool_list})
@self.route('/<tool_name>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _(tool_name: str) -> str:
"""获取特定工具详情"""
tools = await self.ap.tool_mgr.get_all_tools()
for tool in tools:
if tool.name == tool_name:
return self.success(
data={
'tool': {
'name': tool.name,
'description': tool.description,
'human_desc': tool.human_desc,
'parameters': tool.parameters,
}
}
)
return self.http_status(404, -1, f'Tool not found: {tool_name}')

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

@@ -1,11 +1,7 @@
import json
import quart
import sqlalchemy
from .. import group
from .....utils import constants
from .....entity.persistence.metadata import Metadata
@group.group_class('system', '/api/v1/system')
@@ -13,119 +9,31 @@ class SystemRouterGroup(group.RouterGroup):
async def initialize(self) -> None:
@self.route('/info', methods=['GET'], auth_type=group.AuthType.NONE)
async def _() -> str:
# Read wizard_status and wizard_progress from metadata table
wizard_status = 'none'
wizard_progress = None
try:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(Metadata).where(Metadata.key.in_(['wizard_status', 'wizard_progress']))
)
for row in result:
if row.key == 'wizard_status':
wizard_status = row.value
elif row.key == 'wizard_progress':
try:
wizard_progress = json.loads(row.value)
except (json.JSONDecodeError, TypeError):
wizard_progress = None
except Exception:
pass
return self.success(
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', {}),
'wizard_status': wizard_status,
'wizard_progress': wizard_progress,
}
)
@self.route('/wizard/completed', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
"""Mark wizard status in metadata table and clear progress.
Accepts JSON body: { "status": "skipped" | "completed" }
"""
data = await quart.request.get_json(silent=True) or {}
status = data.get('status', 'completed')
if status not in ('skipped', 'completed'):
return self.http_status(400, 400, f'Invalid wizard status: {status}')
try:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(Metadata).where(Metadata.key == 'wizard_status')
)
if result.first():
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(Metadata).where(Metadata.key == 'wizard_status').values(value=status)
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(Metadata).values(key='wizard_status', value=status)
)
# Clear wizard progress when wizard is completed/skipped
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(Metadata).where(Metadata.key == 'wizard_progress')
)
except Exception as e:
return self.http_status(500, 500, f'Failed to update wizard status: {e}')
return self.success(data={})
@self.route('/wizard/progress', methods=['PUT'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
"""Save wizard progress to metadata table.
Accepts JSON body with wizard state fields:
{ "step": int, "selected_adapter": str|null, "created_bot_uuid": str|null,
"bot_saved": bool, "selected_runner": str|null }
"""
data = await quart.request.get_json(silent=True) or {}
progress_json = json.dumps(data, ensure_ascii=False)
try:
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(Metadata).where(Metadata.key == 'wizard_progress')
)
if result.first():
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(Metadata).where(Metadata.key == 'wizard_progress').values(value=progress_json)
)
else:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(Metadata).values(key='wizard_progress', value=progress_json)
)
except Exception as e:
return self.http_status(500, 500, f'Failed to save wizard progress: {e}')
return self.success(data={})
@self.route('/tasks', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
task_type = quart.request.args.get('type')
task_kind = quart.request.args.get('kind')
if task_type == '':
task_type = None
if task_kind == '':
task_kind = None
return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type, task_kind))
return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type))
@self.route('/tasks/<task_id>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _(task_id: str) -> str:
@@ -136,10 +44,6 @@ class SystemRouterGroup(group.RouterGroup):
return self.success(data=task.to_dict())
@self.route('/storage-analysis', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
return self.success(data=await self.ap.maintenance_service.get_storage_analysis())
@self.route('/debug/exec', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
async def _() -> str:
if not constants.debug_mode:
@@ -151,6 +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']
@@ -94,170 +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()
self.ap.logger.warning(f'Space OAuth callback failed: {e}')
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):
@@ -105,29 +101,6 @@ class HTTPController:
):
if os.path.exists(os.path.join(frontend_path, path + '.html')):
path += '.html'
elif not path.startswith('api/'):
# SPA fallback: serve index.html for all non-API, non-static routes
# so that React Router can handle client-side routing (Vite SPA).
# For /home/* sub-routes, first try parent .html files (pre-rendered pages).
if path.startswith('home/'):
segments = path.rstrip('/').split('/')
for i in range(len(segments) - 1, 0, -1):
parent_path = '/'.join(segments[:i]) + '.html'
if os.path.exists(os.path.join(frontend_path, parent_path)):
response = await quart.send_from_directory(
frontend_path, parent_path, mimetype='text/html'
)
response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
response.headers['Pragma'] = 'no-cache'
response.headers['Expires'] = '0'
return response
# Fallback to index.html for SPA client-side routing
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
else:
return await quart.send_from_directory(frontend_path, '404.html')

View File

@@ -58,52 +58,20 @@ 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')
extra_webhook_prefix = self.ap.instance_config.data['api'].get('extra_webhook_prefix', '')
webhook_url = f'/bots/{bot_uuid}'
adapter_runtime_values['webhook_url'] = webhook_url
adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
adapter_runtime_values['extra_webhook_full_url'] = (
f'{extra_webhook_prefix}{webhook_url}' if extra_webhook_prefix else ''
)
else:
adapter_runtime_values['webhook_url'] = None
adapter_runtime_values['webhook_full_url'] = None
adapter_runtime_values['extra_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())
# bind the most recently updated pipeline if any exist
# checkout the default pipeline
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_pipeline.LegacyPipeline)
.order_by(persistence_pipeline.LegacyPipeline.updated_at.desc())
.limit(1)
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
persistence_pipeline.LegacyPipeline.is_default == True
)
)
pipeline = result.first()
if pipeline is not None:
@@ -171,29 +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

@@ -1,5 +1,6 @@
from __future__ import annotations
import uuid
import sqlalchemy
from ....core import app
@@ -16,210 +17,70 @@ class KnowledgeService:
async def get_knowledge_bases(self) -> list[dict]:
"""获取所有知识库"""
return await self.ap.rag_mgr.get_all_knowledge_base_details()
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
knowledge_bases = result.all()
return [
self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
for knowledge_base in knowledge_bases
]
async def get_knowledge_base(self, kb_uuid: str) -> dict | None:
"""获取知识库"""
return await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
)
knowledge_base = result.first()
if knowledge_base is None:
return None
return self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
async def create_knowledge_base(self, kb_data: dict) -> str:
"""创建知识库"""
# In new architecture, we delegate entirely to RAGManager which uses plugins.
# Legacy internal KB creation is removed.
kb_data['uuid'] = str(uuid.uuid4())
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.KnowledgeBase).values(kb_data))
knowledge_engine_plugin_id = kb_data.get('knowledge_engine_plugin_id')
if not knowledge_engine_plugin_id:
raise ValueError('knowledge_engine_plugin_id is required')
kb = await self.get_knowledge_base(kb_data['uuid'])
creation_settings = kb_data.get('creation_settings', {})
retrieval_settings = kb_data.get('retrieval_settings', {})
await self.ap.rag_mgr.load_knowledge_base(kb)
# Validate required fields based on plugin's creation_schema and retrieval_schema
await self._validate_schema_required_fields(
knowledge_engine_plugin_id,
creation_settings,
retrieval_settings,
)
kb = await self.ap.rag_mgr.create_knowledge_base(
name=kb_data.get('name', 'Untitled'),
knowledge_engine_plugin_id=knowledge_engine_plugin_id,
creation_settings=creation_settings,
retrieval_settings=retrieval_settings,
description=kb_data.get('description', ''),
)
return kb.uuid
async def _validate_schema_required_fields(
self,
plugin_id: str,
creation_settings: dict,
retrieval_settings: dict,
) -> None:
"""Validate required fields based on plugin's creation_schema and retrieval_schema.
This is a business-agnostic validation that checks all fields marked as
required in the plugin's schema, regardless of field type.
Args:
plugin_id: Knowledge Engine plugin ID.
creation_settings: User-provided creation settings.
retrieval_settings: User-provided retrieval settings.
Raises:
ValueError: If any required field is missing or empty.
"""
# Validate creation_schema
try:
creation_schema = await self.ap.plugin_connector.get_rag_creation_schema(plugin_id)
self._check_required_fields(creation_schema, creation_settings, 'creation_settings')
except ValueError:
raise
except Exception as e:
self.ap.logger.warning(f'Failed to get creation_schema for validation: {e}')
# Validate retrieval_schema
try:
retrieval_schema = await self.ap.plugin_connector.get_rag_retrieval_schema(plugin_id)
self._check_required_fields(retrieval_schema, retrieval_settings, 'retrieval_settings')
except ValueError:
raise
except Exception as e:
self.ap.logger.warning(f'Failed to get retrieval_schema for validation: {e}')
def _check_required_fields(
self,
schema: dict | list,
settings: dict,
context: str,
) -> None:
"""Check required fields in schema against provided settings.
Args:
schema: Plugin-defined schema (can be list or dict with 'schema' key).
settings: User-provided settings values.
context: Context name for error messages (e.g., 'creation_settings').
Raises:
ValueError: If a required field is missing or empty.
"""
if not schema:
return
# schema can be a list directly, or a dict with 'schema' key
items = schema if isinstance(schema, list) else schema.get('schema', [])
if not items:
return
for item in items:
field_name = item.get('name')
if not field_name:
continue
is_required = item.get('required', False)
if not is_required:
continue
# Check show_if condition - if field is conditionally shown, only validate when condition is met
show_if = item.get('show_if')
if show_if:
depend_field = show_if.get('field')
operator = show_if.get('operator')
expected_value = show_if.get('value')
if depend_field and operator:
depend_value = settings.get(depend_field)
# If show_if condition is not met, skip validation for this field
if operator == 'eq' and depend_value != expected_value:
continue
if operator == 'neq' and depend_value == expected_value:
continue
if operator == 'in' and isinstance(expected_value, list) and depend_value not in expected_value:
continue
value = settings.get(field_name)
# Validate required field has a non-empty value
if value is None or (isinstance(value, str) and value.strip() == ''):
# Get field label for friendly error message
label = item.get('label', {})
field_label = (
label.get('en_US', field_name)
or label.get('zh_Hans', field_name)
or label.get('zh_Hant', field_name)
or field_name
)
raise ValueError(f'{field_label} is required ({context}.{field_name})')
return kb_data['uuid']
async def update_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
"""更新知识库"""
# Filter to only mutable fields
filtered_data = {k: v for k, v in kb_data.items() if k in persistence_rag.KnowledgeBase.MUTABLE_FIELDS}
if 'uuid' in kb_data:
del kb_data['uuid']
if not filtered_data:
return
if 'embedding_model_uuid' in kb_data:
del kb_data['embedding_model_uuid']
await self.ap.persistence_mgr.execute_async(
sqlalchemy.update(persistence_rag.KnowledgeBase)
.values(filtered_data)
.values(kb_data)
.where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
)
await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
kb = await self.get_knowledge_base(kb_uuid)
if kb is None:
raise Exception('Knowledge base not found after update')
await self.ap.rag_mgr.load_knowledge_base(kb)
async def _check_doc_capability(self, kb_uuid: str, operation: str) -> None:
"""Check if the KB's Knowledge Engine supports document operations.
Args:
kb_uuid: Knowledge base UUID.
operation: Human-readable operation name for error messages.
Raises:
Exception: If the KB does not support doc_ingestion.
"""
kb_info = await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
if not kb_info:
raise Exception('Knowledge base not found')
capabilities = kb_info.get('knowledge_engine', {}).get('capabilities', [])
if 'doc_ingestion' not in capabilities:
raise Exception(f'This knowledge base does not support {operation}')
async def store_file(self, kb_uuid: str, file_id: str, parser_plugin_id: str | None = None) -> str:
async def store_file(self, kb_uuid: str, file_id: str) -> int:
"""存储文件"""
# await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(kb_id=kb_uuid, file_id=file_id))
# await self.ap.rag_mgr.store_file(file_id)
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 await runtime_kb.store_file(file_id)
await self._check_doc_capability(kb_uuid, 'document upload')
result = await runtime_kb.store_file(file_id, parser_plugin_id=parser_plugin_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
async def retrieve_knowledge_base(
self, kb_uuid: str, query: str, retrieval_settings: dict | None = None
) -> list[dict]:
async def retrieve_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
"""检索知识库"""
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')
# Pass retrieval_settings
results = await runtime_kb.retrieve(query, settings=retrieval_settings)
return [result.model_dump() for result in results]
return [
result.model_dump() for result in await runtime_kb.retrieve(query, runtime_kb.knowledge_base_entity.top_k)
]
async def get_files_by_knowledge_base(self, kb_uuid: str) -> list[dict]:
"""获取知识库文件"""
@@ -234,28 +95,17 @@ 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')
await self._check_doc_capability(kb_uuid, 'document 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"""
# Delete from DB first to commit the deletion, then clean up runtime/plugin (best-effort)
await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
)
# delete files
# NOTE: Chunk cleanup is for legacy (pre-plugin) KBs that stored chunks locally.
# For plugin-based Knowledge Engines, the Chunk table is not populated, so this is a no-op.
files = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_rag.File).where(persistence_rag.File.kb_id == kb_uuid)
)
@@ -268,53 +118,3 @@ class KnowledgeService:
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file.uuid)
)
# Remove from runtime and notify plugin (best-effort, DB is already cleaned up)
await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
# ================= Knowledge Engine Discovery =================
async def list_knowledge_engines(self) -> list[dict]:
"""List all available Knowledge Engines from plugins."""
engines = []
if not self.ap.plugin_connector.is_enable_plugin:
return engines
# Get KnowledgeEngine plugins
try:
knowledge_engines = await self.ap.plugin_connector.list_knowledge_engines()
engines.extend(knowledge_engines)
except Exception as e:
self.ap.logger.warning(f'Failed to list Knowledge Engines from plugins: {e}')
return engines
async def list_parsers(self, mime_type: str | None = None) -> list[dict]:
"""List available parsers, optionally filtered by MIME type."""
if not self.ap.plugin_connector.is_enable_plugin:
return []
try:
parsers = await self.ap.plugin_connector.list_parsers()
if mime_type:
parsers = [p for p in parsers if mime_type in p.get('supported_mime_types', [])]
return parsers
except Exception as e:
self.ap.logger.warning(f'Failed to list parsers: {e}')
return []
async def get_engine_creation_schema(self, plugin_id: str) -> dict:
"""Get creation settings schema for a specific Knowledge Engine."""
try:
return await self.ap.plugin_connector.get_rag_creation_schema(plugin_id)
except Exception as e:
self.ap.logger.warning(f'Failed to get creation schema for {plugin_id}: {e}')
return {}
async def get_engine_retrieval_schema(self, plugin_id: str) -> dict:
"""Get retrieval settings schema for a specific Knowledge Engine."""
try:
return await self.ap.plugin_connector.get_rag_retrieval_schema(plugin_id)
except Exception as e:
self.ap.logger.warning(f'Failed to get retrieval schema for {plugin_id}: {e}')
return {}

View File

@@ -1,309 +0,0 @@
from __future__ import annotations
import datetime
import os
import re
from pathlib import Path
from typing import Any
import sqlalchemy
from ....core import app
from ....entity.persistence import bstorage as persistence_bstorage
from ....entity.persistence import monitoring as persistence_monitoring
LOG_FILE_PATTERN = re.compile(r'^langbot-(\d{4}-\d{2}-\d{2})\.log(?:\.\d+)?$')
DEFAULT_UPLOAD_FILE_RETENTION_DAYS = 7
DEFAULT_LOG_RETENTION_DAYS = 3
class MaintenanceService:
"""Storage maintenance and diagnostics."""
ap: app.Application
def __init__(self, ap: app.Application) -> None:
self.ap = ap
async def cleanup_expired_files(self) -> dict[str, int]:
cleanup_cfg = self.ap.instance_config.data.get('storage', {}).get('cleanup', {})
upload_retention_days = self._positive_int(
cleanup_cfg.get('uploaded_file_retention_days'),
DEFAULT_UPLOAD_FILE_RETENTION_DAYS,
'storage.cleanup.uploaded_file_retention_days',
)
log_retention_days = self._positive_int(
cleanup_cfg.get('log_retention_days'),
DEFAULT_LOG_RETENTION_DAYS,
'storage.cleanup.log_retention_days',
)
return {
'uploaded_files': await self._cleanup_expired_uploaded_files(upload_retention_days),
'log_files': self._cleanup_expired_log_files(log_retention_days),
}
async def get_storage_analysis(self) -> dict[str, Any]:
cleanup_cfg = self.ap.instance_config.data.get('storage', {}).get('cleanup', {})
upload_retention_days = self._positive_int(
cleanup_cfg.get('uploaded_file_retention_days'),
DEFAULT_UPLOAD_FILE_RETENTION_DAYS,
'storage.cleanup.uploaded_file_retention_days',
)
log_retention_days = self._positive_int(
cleanup_cfg.get('log_retention_days'),
DEFAULT_LOG_RETENTION_DAYS,
'storage.cleanup.log_retention_days',
)
database_cfg = self.ap.instance_config.data.get('database', {})
database_type = database_cfg.get('use', 'sqlite')
database_path = (
Path(database_cfg.get('sqlite', {}).get('path', 'data/langbot.db')) if database_type == 'sqlite' else None
)
roots: list[tuple[str, Path | None]] = [
('database', database_path),
('logs', Path('data/logs')),
('storage', Path('data/storage')),
('vector_store', Path('data/chroma')),
('plugins', Path('data/plugins')),
('mcp', Path('data/mcp')),
('temp', Path('data/temp')),
]
sections = []
for key, path in roots:
sections.append(
{
'key': key,
'path': str(path) if path else '',
'exists': path.exists() if path else False,
'size_bytes': self._path_size(path) if path else 0,
'file_count': self._file_count(path) if path else 0,
}
)
monitoring_counts = await self._monitoring_counts()
binary_storage = await self._binary_storage_stats()
upload_candidates = await self._expired_uploaded_candidates(upload_retention_days)
log_candidates = self._expired_log_candidates(log_retention_days)
return {
'generated_at': datetime.datetime.now(datetime.timezone.utc).isoformat(),
'cleanup_policy': {
'uploaded_file_retention_days': upload_retention_days,
'log_retention_days': log_retention_days,
},
'sections': sections,
'database': {
'type': database_type,
'monitoring_counts': monitoring_counts,
'binary_storage': binary_storage,
},
'cleanup_candidates': {
'uploaded_files': upload_candidates,
'log_files': log_candidates,
},
'tasks': self.ap.task_mgr.get_stats() if self.ap.task_mgr else {},
}
async def _cleanup_expired_uploaded_files(self, retention_days: int) -> int:
provider = self.ap.storage_mgr.storage_provider
provider_name = provider.__class__.__name__
if provider_name == 'LocalStorageProvider':
candidates = self._expired_local_upload_candidates(retention_days, include_paths=True)
deleted = 0
for item in candidates:
try:
os.remove(item['path'])
deleted += 1
except FileNotFoundError:
pass
except Exception as e:
self.ap.logger.warning(f'Failed to delete expired uploaded file {item["key"]}: {e}')
return deleted
if provider_name == 'S3StorageProvider':
return await self._cleanup_expired_s3_uploaded_files(retention_days)
return 0
async def _expired_uploaded_candidates(self, retention_days: int) -> list[dict[str, Any]]:
provider_name = self.ap.storage_mgr.storage_provider.__class__.__name__
if provider_name == 'LocalStorageProvider':
return self._expired_local_upload_candidates(retention_days)
if provider_name == 'S3StorageProvider':
return await self._expired_s3_upload_candidates(retention_days)
return []
async def _cleanup_expired_s3_uploaded_files(self, retention_days: int) -> int:
provider = self.ap.storage_mgr.storage_provider
candidates = await self._expired_s3_upload_candidates(retention_days)
deleted = 0
for item in candidates:
await provider.delete(item['key'])
deleted += 1
return deleted
async def _expired_s3_upload_candidates(self, retention_days: int) -> list[dict[str, Any]]:
provider = self.ap.storage_mgr.storage_provider
cutoff = datetime.datetime.now(datetime.timezone.utc) - datetime.timedelta(days=retention_days)
candidates = []
paginator = provider.s3_client.get_paginator('list_objects_v2')
for page in paginator.paginate(Bucket=provider.bucket_name):
for obj in page.get('Contents', []):
key = obj.get('Key', '')
last_modified = obj.get('LastModified')
if not self._is_uploaded_file_key(key):
continue
if last_modified and last_modified < cutoff:
candidates.append(
{
'key': key,
'size_bytes': obj.get('Size', 0),
'modified_at': last_modified.isoformat(),
}
)
return candidates
def _cleanup_expired_log_files(self, retention_days: int) -> int:
deleted = 0
for item in self._expired_log_candidates(retention_days, include_paths=True):
try:
os.remove(item['path'])
deleted += 1
except FileNotFoundError:
pass
except Exception as e:
self.ap.logger.warning(f'Failed to delete expired log file {item["name"]}: {e}')
return deleted
def _expired_local_upload_candidates(
self, retention_days: int, include_paths: bool = False
) -> list[dict[str, Any]]:
storage_root = Path('data/storage')
if not storage_root.exists():
return []
cutoff = datetime.datetime.now().timestamp() - retention_days * 86400
candidates = []
for entry in storage_root.iterdir():
if not entry.is_file() or not self._is_uploaded_file_key(entry.name):
continue
stat = entry.stat()
if stat.st_mtime >= cutoff:
continue
item = {
'key': entry.name,
'size_bytes': stat.st_size,
'modified_at': datetime.datetime.fromtimestamp(stat.st_mtime, datetime.timezone.utc).isoformat(),
}
if include_paths:
item['path'] = str(entry)
candidates.append(item)
return candidates
def _expired_log_candidates(self, retention_days: int, include_paths: bool = False) -> list[dict[str, Any]]:
log_root = Path('data/logs')
if not log_root.exists():
return []
cutoff_date = datetime.date.today() - datetime.timedelta(days=retention_days - 1)
candidates = []
for entry in log_root.iterdir():
if not entry.is_file():
continue
match = LOG_FILE_PATTERN.match(entry.name)
if not match:
continue
try:
file_date = datetime.date.fromisoformat(match.group(1))
except ValueError:
continue
if file_date >= cutoff_date:
continue
stat = entry.stat()
item = {
'name': entry.name,
'date': file_date.isoformat(),
'size_bytes': stat.st_size,
}
if include_paths:
item['path'] = str(entry)
candidates.append(item)
return candidates
def _is_uploaded_file_key(self, key: str) -> bool:
return '/' not in key and not key.startswith('plugin_config_')
async def _monitoring_counts(self) -> dict[str, int]:
tables = {
'messages': persistence_monitoring.MonitoringMessage.id,
'llm_calls': persistence_monitoring.MonitoringLLMCall.id,
'embedding_calls': persistence_monitoring.MonitoringEmbeddingCall.id,
'errors': persistence_monitoring.MonitoringError.id,
'sessions': persistence_monitoring.MonitoringSession.session_id,
'feedback': persistence_monitoring.MonitoringFeedback.id,
}
counts: dict[str, int] = {}
for key, column in tables.items():
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(sqlalchemy.func.count(column)))
counts[key] = result.scalar() or 0
return counts
async def _binary_storage_stats(self) -> dict[str, Any]:
count_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(sqlalchemy.func.count(persistence_bstorage.BinaryStorage.unique_key))
)
size_bytes = None
try:
size_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(sqlalchemy.func.sum(sqlalchemy.func.length(persistence_bstorage.BinaryStorage.value)))
)
size_bytes = size_result.scalar() or 0
except Exception as e:
self.ap.logger.warning(f'Failed to estimate binary storage size: {e}')
return {
'count': count_result.scalar() or 0,
'size_bytes': size_bytes,
}
def _path_size(self, path: Path) -> int:
if not path.exists():
return 0
if path.is_file():
return path.stat().st_size
total = 0
for root, _, files in os.walk(path):
for file_name in files:
file_path = Path(root) / file_name
try:
total += file_path.stat().st_size
except FileNotFoundError:
pass
return total
def _file_count(self, path: Path) -> int:
if not path.exists():
return 0
if path.is_file():
return 1
count = 0
for _, _, files in os.walk(path):
count += len(files)
return count
def _positive_int(self, value: Any, default: int, name: str) -> int:
try:
parsed = int(value)
except (TypeError, ValueError):
self.ap.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
if parsed < 1:
self.ap.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
return parsed

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

@@ -11,29 +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
def _runtime_model_data(model_uuid: str, model_data: dict) -> dict:
"""Return model data for rebuilding runtime models after an update.
Update payloads intentionally omit uuid before writing to the database.
Runtime model entities still need the stable uuid so pipeline configs can
resolve the in-memory model immediately after an edit, without requiring a
process restart.
"""
return {**model_data, 'uuid': model_uuid}
class LLMModelsService:
ap: app.Application
@@ -41,136 +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:
model_config = pipeline.config.get('ai', {}).get('local-agent', {}).get('model', {})
if not model_config.get('primary', ''):
pipeline_config = pipeline.config
pipeline_config['ai']['local-agent']['model'] = {
'primary': model_data['uuid'],
'fallbacks': [],
}
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)
@@ -179,25 +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(**_runtime_model_data(model_uuid, 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 != '_':
@@ -205,18 +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,
)
@@ -227,111 +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)
@@ -340,27 +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(**_runtime_model_data(model_uuid, 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 != '_':
@@ -368,172 +192,15 @@ 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={},
)
class RerankModelsService:
ap: app.Application
def __init__(self, ap: app.Application) -> None:
self.ap = ap
async def get_rerank_models(self) -> list[dict]:
"""Get all rerank models with provider info"""
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.RerankModel))
models = result.all()
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.RerankModel, 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_rerank_models_by_provider(self, provider_uuid: str) -> list[dict]:
"""Get rerank models by provider UUID"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.RerankModel).where(
persistence_model.RerankModel.provider_uuid == provider_uuid
)
)
models = result.all()
return [self.ap.persistence_mgr.serialize_model(persistence_model.RerankModel, m) for m in models]
async def create_rerank_model(self, model_data: dict, preserve_uuid: bool = False) -> str:
"""Create a new rerank 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
await self.ap.persistence_mgr.execute_async(
sqlalchemy.insert(persistence_model.RerankModel).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')
runtime_rerank_model = await self.ap.model_mgr.load_rerank_model_with_provider(
persistence_model.RerankModel(**model_data),
runtime_provider,
)
self.ap.model_mgr.rerank_models.append(runtime_rerank_model)
return model_data['uuid']
async def get_rerank_model(self, model_uuid: str) -> dict | None:
"""Get a single rerank model with provider info"""
result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.RerankModel).where(persistence_model.RerankModel.uuid == model_uuid)
)
model = result.first()
if model is None:
return None
model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.RerankModel, 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
async def update_rerank_model(self, model_uuid: str, model_data: dict) -> None:
"""Update an existing rerank 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.RerankModel)
.where(persistence_model.RerankModel.uuid == model_uuid)
.values(**model_data)
)
await self.ap.model_mgr.remove_rerank_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')
runtime_rerank_model = await self.ap.model_mgr.load_rerank_model_with_provider(
persistence_model.RerankModel(**_runtime_model_data(model_uuid, model_data)),
runtime_provider,
)
self.ap.model_mgr.rerank_models.append(runtime_rerank_model)
async def delete_rerank_model(self, model_uuid: str) -> None:
"""Delete a rerank model"""
await self.ap.persistence_mgr.execute_async(
sqlalchemy.delete(persistence_model.RerankModel).where(persistence_model.RerankModel.uuid == model_uuid)
)
await self.ap.model_mgr.remove_rerank_model(model_uuid)
async def test_rerank_model(self, model_uuid: str, model_data: dict) -> None:
"""Test a rerank model"""
runtime_rerank_model: model_requester.RuntimeRerankModel | None = None
if model_uuid != '_':
for model in self.ap.model_mgr.rerank_models:
if model.model_entity.uuid == model_uuid:
runtime_rerank_model = model
break
if runtime_rerank_model is None:
raise Exception('model not found')
else:
runtime_rerank_model = await self.ap.model_mgr.init_temporary_runtime_rerank_model(model_data)
await runtime_rerank_model.provider.invoke_rerank(
model=runtime_rerank_model,
query='What is artificial intelligence?',
documents=[
'Artificial intelligence is a branch of computer science.',
'The weather is nice today.',
],
)

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

@@ -1,268 +0,0 @@
from __future__ import annotations
import uuid
import traceback
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
@staticmethod
def _normalize_api_keys(api_keys: str | list[str] | tuple[str, ...] | None) -> list[str]:
if api_keys is None:
return []
raw_keys = [api_keys] if isinstance(api_keys, str) else list(api_keys)
normalized_keys = []
seen_keys = set()
for raw_key in raw_keys:
normalized_key = raw_key.strip() if isinstance(raw_key, str) else ''
if not normalized_key or normalized_key in seen_keys:
continue
normalized_keys.append(normalized_key)
seen_keys.add(normalized_key)
return normalized_keys
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())
provider_data['api_keys'] = self._normalize_api_keys(provider_data.get('api_keys'))
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']
if 'api_keys' in provider_data:
provider_data['api_keys'] = self._normalize_api_keys(provider_data.get('api_keys'))
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')
rerank_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(persistence_model.RerankModel).where(
persistence_model.RerankModel.provider_uuid == provider_uuid
)
)
if rerank_result.first() is not None:
raise ValueError('Cannot delete provider: Rerank 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
rerank_result = await self.ap.persistence_mgr.execute_async(
sqlalchemy.select(sqlalchemy.func.count())
.select_from(persistence_model.RerankModel)
.where(persistence_model.RerankModel.provider_uuid == provider_uuid)
)
rerank_count = rerank_result.scalar() or 0
return {'llm_count': llm_count, 'embedding_count': embedding_count, 'rerank_count': rerank_count}
async def find_or_create_provider(self, requester: str, base_url: str, api_keys: list) -> str:
"""Find existing provider or create new one"""
api_keys = self._normalize_api_keys(api_keys)
# 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,
}
)
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=self._normalize_api_keys(api_key))
)
await self.ap.model_mgr.reload_provider('00000000-0000-0000-0000-000000000000')
async def scan_provider_models(self, provider_uuid: str, model_type: str | None = None) -> dict:
provider = await self.get_provider(provider_uuid)
if provider is None:
raise ValueError('provider not found')
runtime_provider = await self.ap.model_mgr.load_provider(provider)
try:
scan_result = await runtime_provider.requester.scan_models(
runtime_provider.token_mgr.get_token() if runtime_provider.token_mgr.tokens else None
)
except NotImplementedError:
raise ValueError('current provider does not support model scanning')
except Exception as exc:
self.ap.logger.warning(
f'Failed to scan models for provider {provider_uuid}: {exc}\n{traceback.format_exc()}'
)
raise ValueError(str(exc)) from exc
if isinstance(scan_result, dict):
scanned_models = scan_result.get('models', [])
debug_info = scan_result.get('debug')
else:
scanned_models = scan_result
debug_info = None
llm_models = await self.ap.llm_model_service.get_llm_models_by_provider(provider_uuid)
embedding_models = await self.ap.embedding_models_service.get_embedding_models_by_provider(provider_uuid)
existing_llm_names = {model['name'] for model in llm_models}
existing_embedding_names = {model['name'] for model in embedding_models}
filtered_models = []
for model in scanned_models:
scanned_type = model.get('type', 'llm')
if model_type and scanned_type != model_type:
continue
model_name = model.get('name') or model.get('id')
if not model_name:
continue
filtered_models.append(
{
'id': model.get('id', model_name),
'name': model_name,
'type': scanned_type,
'abilities': model.get('abilities', []),
'display_name': model.get('display_name'),
'description': model.get('description'),
'context_length': model.get('context_length'),
'owned_by': model.get('owned_by'),
'input_modalities': model.get('input_modalities', []),
'output_modalities': model.get('output_modalities', []),
'already_added': (
model_name in existing_embedding_names
if scanned_type == 'embedding'
else model_name in existing_llm_names
),
}
)
return {'models': filtered_models, 'debug': debug_info}

View File

@@ -1,189 +0,0 @@
from __future__ import annotations
from langbot.pkg.utils import httpclient
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']
session = httpclient.get_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']
session = httpclient.get_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']
session = httpclient.get_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']
session = httpclient.get_session()
async with session.get(f'{space_url}/api/v1/models', params={'page_size': 100}) 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 user has a local password set
if not user_obj.password:
raise ValueError('请使用 Space 账户登录')
ph = argon2.PasswordHasher()
ph.verify(user_obj.password, password)
@@ -108,9 +90,6 @@ class UserService:
if user_obj is None:
raise ValueError('User not found')
if not user_obj.password:
raise ValueError('No local password set, please set a password first')
ph.verify(user_obj.password, current_password)
hashed_password = ph.hash(new_password)
@@ -118,183 +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

@@ -9,40 +9,30 @@ from ..platform import botmgr as im_mgr
from ..platform.webhook_pusher import WebhookPusher
from ..provider.session import sessionmgr as llm_session_mgr
from ..provider.modelmgr import modelmgr as llm_model_mgr
from langbot.pkg.provider.tools import toolmgr as llm_tool_mgr
from ..config import manager as config_mgr
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 monitoring as monitoring_service
from ..api.http.service import maintenance as maintenance_service
from ..discover import engine as discover_engine
from ..storage import mgr as storagemgr
from ..utils import logcache
from . import taskmgr
from . import entities as core_entities
from ..rag.knowledge import kbmgr as rag_mgr
from ..rag.service import RAGRuntimeService
from ..vector import mgr as vectordb_mgr
from ..telemetry import telemetry as telemetry_module
from ..survey import manager as survey_module
class Application:
@@ -66,7 +56,6 @@ class Application:
model_mgr: llm_model_mgr.ModelManager = None
rag_mgr: rag_mgr.RAGManager = None
rag_runtime_service: RAGRuntimeService = None
# TODO move to pipeline
tool_mgr: llm_tool_mgr.ToolManager = None
@@ -85,8 +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
@@ -102,8 +89,6 @@ class Application:
query_pool: pool.QueryPool = None
msg_aggregator: message_aggregator.MessageAggregator = None
ctrl: controller.Controller = None
pipeline_mgr: pipelinemgr.PipelineManager = None
@@ -128,16 +113,10 @@ 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
rerank_models_service: model_service.RerankModelsService = None
provider_service: provider_service.ModelProviderService = None
pipeline_service: pipeline_service.PipelineService = None
bot_service: bot_service.BotService = None
@@ -150,14 +129,6 @@ class Application:
webhook_service: webhook_service.WebhookService = None
telemetry: telemetry_module.TelemetryManager = None
survey: survey_module.SurveyManager = None
monitoring_service: monitoring_service.MonitoringService = None
maintenance_service: maintenance_service.MaintenanceService = None
def __init__(self):
pass
@@ -193,77 +164,6 @@ class Application:
scopes=[core_entities.LifecycleControlScope.APPLICATION],
)
# Start monitoring data cleanup task if enabled
monitoring_cfg = self.instance_config.data.get('monitoring', {})
auto_cleanup_cfg = monitoring_cfg.get('auto_cleanup', {})
if auto_cleanup_cfg.get('enabled', True):
retention_days = self._get_positive_int_config(
auto_cleanup_cfg.get('retention_days', 30),
default=30,
name='monitoring.auto_cleanup.retention_days',
)
delete_batch_size = self._get_positive_int_config(
auto_cleanup_cfg.get('delete_batch_size', 1000),
default=1000,
name='monitoring.auto_cleanup.delete_batch_size',
)
check_interval_hours = self._get_positive_float_config(
auto_cleanup_cfg.get('check_interval_hours', 1),
default=1,
name='monitoring.auto_cleanup.check_interval_hours',
)
async def monitoring_cleanup_loop():
check_interval_seconds = check_interval_hours * 3600
while True:
try:
deleted = await self.monitoring_service.cleanup_expired_records(
retention_days,
batch_size=delete_batch_size,
)
total_deleted = sum(deleted.values())
if total_deleted > 0:
self.logger.info(
f'Monitoring auto-cleanup: deleted {total_deleted} expired records '
f'(retention={retention_days}d): {deleted}'
)
except Exception as e:
self.logger.warning(f'Monitoring auto-cleanup error: {e}')
await asyncio.sleep(check_interval_seconds)
self.task_mgr.create_task(
monitoring_cleanup_loop(),
name='monitoring-cleanup',
scopes=[core_entities.LifecycleControlScope.APPLICATION],
)
# Start storage/log maintenance task if enabled
storage_cleanup_cfg = self.instance_config.data.get('storage', {}).get('cleanup', {})
if storage_cleanup_cfg.get('enabled', True) and self.maintenance_service is not None:
check_interval_hours = self._get_positive_float_config(
storage_cleanup_cfg.get('check_interval_hours', 1),
default=1,
name='storage.cleanup.check_interval_hours',
)
async def storage_cleanup_loop():
check_interval_seconds = check_interval_hours * 3600
while True:
try:
deleted = await self.maintenance_service.cleanup_expired_files()
total_deleted = sum(deleted.values())
if total_deleted > 0:
self.logger.info(f'Storage maintenance: deleted expired files: {deleted}')
except Exception as e:
self.logger.warning(f'Storage maintenance error: {e}')
await asyncio.sleep(check_interval_seconds)
self.task_mgr.create_task(
storage_cleanup_loop(),
name='storage-maintenance',
scopes=[core_entities.LifecycleControlScope.APPLICATION],
)
self.task_mgr.create_task(
never_ending(),
name='never-ending-task',
@@ -278,28 +178,6 @@ class Application:
self.logger.error(f'Application runtime fatal exception: {e}')
self.logger.debug(f'Traceback: {traceback.format_exc()}')
def _get_positive_int_config(self, value, default: int, name: str) -> int:
try:
parsed = int(value)
except (TypeError, ValueError):
self.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
if parsed < 1:
self.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
return parsed
def _get_positive_float_config(self, value, default: float, name: str) -> float:
try:
parsed = float(value)
except (TypeError, ValueError):
self.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
if parsed <= 0:
self.logger.warning(f'Invalid {name}: {value!r}, using {default}')
return default
return parsed
def dispose(self):
self.plugin_connector.dispose()

View File

@@ -1,4 +1,3 @@
import importlib.util
import pip
import os
from ...utils import pkgmgr
@@ -50,10 +49,9 @@ async def check_deps() -> list[str]:
missing_deps = []
for dep in required_deps:
# Use find_spec instead of __import__ to avoid actually loading
# all modules into memory. find_spec only checks if the module
# can be found, without executing module-level code.
if importlib.util.find_spec(dep) is None:
try:
__import__(dep)
except ImportError:
missing_deps.append(dep)
return missing_deps

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

@@ -5,37 +5,29 @@ 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
from ...provider.modelmgr import modelmgr as llm_model_mgr
from ...provider.tools import toolmgr as llm_tool_mgr
from ...rag.knowledge import kbmgr as rag_mgr
from ...rag.service import RAGRuntimeService
from ...platform import botmgr as im_mgr
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 monitoring as monitoring_service
from ...api.http.service import maintenance as maintenance_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')
@@ -50,42 +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
rerank_models_service_inst = model_service.RerankModelsService(ap)
ap.rerank_models_service = rerank_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
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
@@ -107,23 +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()
@@ -145,17 +99,10 @@ 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
# Initialize RAG Runtime Service for plugins
ap.rag_runtime_service = RAGRuntimeService(ap)
# 初始化向量数据库管理器
vectordb_mgr_inst = vectordb_mgr.VectorDBManager(ap)
await vectordb_mgr_inst.initialize()
@@ -165,19 +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
maintenance_service_inst = maintenance_service.MaintenanceService(ap)
ap.maintenance_service = maintenance_service_inst
llm_model_service_inst = model_service.LLMModelsService(ap)
ap.llm_model_service = llm_model_service_inst
async def runtime_disconnect_callback(connector: plugin_connector.PluginRuntimeConnector) -> None:
await asyncio.sleep(3)
await plugin_connector_inst.initialize()
embedding_models_service_inst = model_service.EmbeddingModelsService(ap)
ap.embedding_models_service = embedding_models_service_inst
plugin_connector_inst = plugin_connector.PluginRuntimeConnector(ap, runtime_disconnect_callback)
await plugin_connector_inst.initialize()
ap.plugin_connector = plugin_connector_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
@@ -74,30 +71,20 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
current = cfg
for i, key in enumerate(keys):
if not isinstance(current, dict):
if not isinstance(current, dict) or key not in current:
break
if i == len(keys) - 1:
# At the final key
if key in current:
if isinstance(current[key], list):
# Convert comma-separated string to list
# e.g., SYSTEM__DISABLED_ADAPTERS="aiocqhttp,dingtalk"
current[key] = [item.strip() for item in env_value.split(',') if item.strip()]
elif isinstance(current[key], dict):
# Skip dict types
pass
else:
# Valid scalar value - convert and set it
converted_value = convert_value(env_value, current[key])
current[key] = converted_value
# At the final key - check if it's a scalar value
if isinstance(current[key], (dict, list)):
# Skip dict and list types
pass
else:
# Key doesn't exist yet - create it as string
current[key] = env_value
# Valid scalar value - convert and set it
converted_value = convert_value(env_value, current[key])
current[key] = converted_value
else:
# Navigate deeper - create intermediate dict if needed
if key not in current:
current[key] = {}
# Navigate deeper
current = current[key]
return cfg
@@ -155,58 +142,6 @@ class LoadConfigStage(stage.BootingStage):
await ap.instance_config.dump_config()
# load or generate instance id
# Priority:
# 1. system.instance_id from config.yaml (can be set via SYSTEM__INSTANCE_ID env var)
# 2. data/labels/instance_id.json (if file exists)
# 3. Generate new and save to file
config_instance_id = ap.instance_config.data.get('system', {}).get('instance_id', '')
if config_instance_id:
# Use the instance_id from config.yaml
constants.instance_id = config_instance_id
# Still load/create the file for backward compat, but don't use its value
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,
)
else:
# Try loading file-based instance id
instance_id_path = os.path.join('data', 'labels', 'instance_id.json')
if os.path.exists(instance_id_path):
# File exists, read it
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': '',
'instance_create_ts': 0,
},
completion=False,
)
constants.instance_id = ap.instance_id.data['instance_id']
else:
# Neither config nor file, generate new and save to file
new_id = f'instance_{str(uuid.uuid4())}'
ap.instance_id = await config.load_json_config(
'data/labels/instance_id.json',
template_data={
'instance_id': new_id,
'instance_create_ts': int(time.time()),
},
completion=False,
)
constants.instance_id = new_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

@@ -3,7 +3,6 @@ from __future__ import annotations
import asyncio
import typing
import datetime
import time
from . import app
from . import entities as core_entities
@@ -18,13 +17,9 @@ class TaskContext:
log: str
"""Log"""
metadata: dict
"""Structured metadata for progress reporting"""
def __init__(self):
self.current_action = 'default'
self.log = ''
self.metadata = {}
def _log(self, msg: str):
self.log += msg + '\n'
@@ -43,7 +38,7 @@ class TaskContext:
self._log(f'{datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")} | {self.current_action} | {msg}')
def to_dict(self) -> dict:
return {'current_action': self.current_action, 'log': self.log, 'metadata': self.metadata}
return {'current_action': self.current_action, 'log': self.log}
@staticmethod
def new() -> TaskContext:
@@ -120,7 +115,6 @@ class TaskWrapper:
self.label = label if label != '' else name
self.task.set_name(name)
self.scopes = scopes
self.created_at = time.time()
def assume_exception(self):
try:
@@ -156,7 +150,6 @@ class TaskWrapper:
'name': self.name,
'label': self.label,
'scopes': [scope.value for scope in self.scopes],
'created_at': self.created_at,
'task_context': self.task_context.to_dict(),
'runtime': {
'done': self.task.done(),
@@ -196,8 +189,6 @@ class AsyncTaskManager:
) -> TaskWrapper:
wrapper = TaskWrapper(self.ap, coro, task_type, kind, name, label, context, scopes)
self.tasks.append(wrapper)
wrapper.task.add_done_callback(lambda _: self._prune_completed_tasks())
self._prune_completed_tasks()
return wrapper
def create_user_task(
@@ -220,23 +211,9 @@ class AsyncTaskManager:
def get_tasks_dict(
self,
type: str = None,
kind: str = None,
) -> dict:
return {
'tasks': [
t.to_dict()
for t in self.tasks
if (type is None or t.task_type == type) and (kind is None or t.kind == kind)
],
'id_index': TaskWrapper._id_index,
}
def get_stats(self) -> dict:
completed = sum(1 for t in self.tasks if t.task.done())
return {
'total': len(self.tasks),
'running': len(self.tasks) - completed,
'completed': completed,
'tasks': [t.to_dict() for t in self.tasks if type is None or t.task_type == type],
'id_index': TaskWrapper._id_index,
}
@@ -257,27 +234,3 @@ class AsyncTaskManager:
if not wrapper.task.done():
wrapper.task.cancel()
return
def _prune_completed_tasks(self):
completed_limit = (
self.ap.instance_config.data.get('system', {})
.get('task_retention', {})
.get(
'completed_limit',
200,
)
)
try:
completed_limit = int(completed_limit)
except (TypeError, ValueError):
completed_limit = 200
if completed_limit < 1:
completed_limit = 1
completed_tasks = [wrapper for wrapper in self.tasks if wrapper.task.done()]
overflow = len(completed_tasks) - completed_limit
if overflow <= 0:
return
remove_ids = {wrapper.id for wrapper in completed_tasks[:overflow]}
self.tasks = [wrapper for wrapper in self.tasks if wrapper.id not in remove_ids]

View File

@@ -17,23 +17,11 @@ class I18nString(pydantic.BaseModel):
"""英文"""
zh_Hans: typing.Optional[str] = None
"""简体中文"""
zh_Hant: typing.Optional[str] = None
"""繁体中文"""
"""中文"""
ja_JP: typing.Optional[str] = None
"""日文"""
th_TH: typing.Optional[str] = None
"""泰文"""
vi_VN: typing.Optional[str] = None
"""越南文"""
es_ES: typing.Optional[str] = None
"""西班牙文"""
def to_dict(self) -> dict:
"""转换为字典"""
dic = {}
@@ -41,16 +29,8 @@ class I18nString(pydantic.BaseModel):
dic['en_US'] = self.en_US
if self.zh_Hans is not None:
dic['zh_Hans'] = self.zh_Hans
if self.zh_Hant is not None:
dic['zh_Hant'] = self.zh_Hant
if self.ja_JP is not None:
dic['ja_JP'] = self.ja_JP
if self.th_TH is not None:
dic['th_TH'] = self.th_TH
if self.vi_VN is not None:
dic['vi_VN'] = self.vi_VN
if self.es_ES is not None:
dic['es_ES'] = self.es_ES
return dic

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

@@ -16,7 +16,6 @@ class Bot(Base):
enable = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
use_pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
use_pipeline_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
pipeline_routing_rules = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, server_default='[]')
created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
updated_at = sqlalchemy.Column(
sqlalchemy.DateTime,

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,
@@ -43,34 +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,
nullable=False,
server_default=sqlalchemy.func.now(),
onupdate=sqlalchemy.func.now(),
)
class RerankModel(Base):
"""Rerank model"""
__tablename__ = 'rerank_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)
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

@@ -1,131 +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)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
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)
user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # User display name
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
class MonitoringFeedback(Base):
"""User feedback records (like/dislike) from AI Bot conversations"""
__tablename__ = 'monitoring_feedback'
id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
feedback_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, unique=True, index=True)
feedback_type = sqlalchemy.Column(sqlalchemy.Integer, nullable=False) # 1=like, 2=dislike
feedback_content = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # User feedback text
inaccurate_reasons = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # JSON list of inaccurate reasons
# Context fields
bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
stream_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # e.g., wecom

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):

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