mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-02 12:05:54 +00:00
Compare commits
1 Commits
feat/litel
...
pr/6mvp6/2
| Author | SHA1 | Date | |
|---|---|---|---|
|
6bb73297e0 |
2
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
2
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
@@ -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:
|
||||
|
||||
2
.github/ISSUE_TEMPLATE/bug-report_en.yml
vendored
2
.github/ISSUE_TEMPLATE/bug-report_en.yml
vendored
@@ -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:
|
||||
|
||||
@@ -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:
|
||||
|
||||
25
.github/workflows/check-i18n.yml
vendored
25
.github/workflows/check-i18n.yml
vendored
@@ -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
|
||||
4
.github/workflows/publish-to-pypi.yml
vendored
4
.github/workflows/publish-to-pypi.yml
vendored
@@ -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
|
||||
|
||||
171
.github/workflows/test-migrations.yml
vendored
171
.github/workflows/test-migrations.yml
vendored
@@ -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())
|
||||
"
|
||||
9
.gitignore
vendored
9
.gitignore
vendored
@@ -53,5 +53,10 @@ src/langbot/web/
|
||||
/build
|
||||
*.egg-info
|
||||
|
||||
# Next.js build cache (legacy)
|
||||
web/.next/
|
||||
# Docker 部署产生的本地文件
|
||||
docker/data/
|
||||
docker/docker-compose.override.yaml
|
||||
|
||||
# 备份目录
|
||||
LangBot_backup_*/
|
||||
*.bak
|
||||
|
||||
@@ -70,7 +70,7 @@ 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.
|
||||
- If you changed the definition of database entities, please update the migration file in `src/langbot/pkg/persistence/migrations/` and update the constants.py file in `src/langbot/pkg/utils/constants.py` with the new migration number.
|
||||
|
||||
## Some Principles
|
||||
|
||||
|
||||
12
Dockerfile
12
Dockerfile
@@ -4,20 +4,24 @@ 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
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Use Chinese mirror for faster and more reliable package downloads
|
||||
RUN sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list.d/debian.sources 2>/dev/null || \
|
||||
sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list 2>/dev/null || true
|
||||
|
||||
COPY . .
|
||||
|
||||
COPY --from=node /app/web/dist ./web/dist
|
||||
COPY --from=node /app/web/out ./web/out
|
||||
|
||||
RUN apt update \
|
||||
&& apt install gcc -y \
|
||||
&& python -m pip install --no-cache-dir uv \
|
||||
&& uv sync \
|
||||
&& python -m pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple uv \
|
||||
&& uv sync --index-url https://pypi.tuna.tsinghua.edu.cn/simple \
|
||||
&& touch /.dockerenv
|
||||
|
||||
CMD [ "uv", "run", "--no-sync", "main.py" ]
|
||||
12
README.md
12
README.md
@@ -19,9 +19,9 @@ English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
|
||||
<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://docs.langbot.app/en/insight/features">Features</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
|
||||
<a href="https://space.langbot.app/cloud">Cloud</a> ｜
|
||||
<a href="https://space.langbot.app">Plugin Market</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
|
||||
@@ -45,7 +45,7 @@ LangBot is an **open-source, production-grade platform** for building AI-powered
|
||||
- **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)
|
||||
[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
|
||||
|
||||
---
|
||||
|
||||
@@ -76,7 +76,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -124,7 +124,7 @@ docker compose up -d
|
||||
| [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
|
||||
|
||||
[→ View all integrations](https://link.langbot.app/en/docs/features)
|
||||
[→ View all integrations](https://docs.langbot.app/en/insight/features)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_CN.md
12
README_CN.md
@@ -21,9 +21,9 @@
|
||||
[](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://docs.langbot.app/zh/insight/features.html">特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app/cloud">Cloud</a> ｜
|
||||
<a href="https://space.langbot.app">插件市场</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路线图</a>
|
||||
@@ -45,7 +45,7 @@ LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时
|
||||
- **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)
|
||||
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -76,7 +76,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/zh-CN/templates/ZKTBDH)
|
||||
[](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)
|
||||
**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -125,7 +125,7 @@ docker compose up -d
|
||||
| [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
|
||||
| [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
|
||||
|
||||
[→ 查看完整集成列表](https://link.langbot.app/zh/docs/features)
|
||||
[→ 查看完整集成列表](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
### TTS（语音合成）
|
||||
|
||||
|
||||
12
README_ES.md
12
README_ES.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/en/insight/features.html">Características</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Mercado de Plugins</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot es una **plataforma de código abierto y grado de producción** para con
|
||||
- **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)
|
||||
[→ Conocer más sobre todas las funcionalidades](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
|
||||
|
||||
[→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)
|
||||
[→ Ver todas las integraciones](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_FR.md
12
README_FR.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Marché des Plugins</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot est une **plateforme open-source de niveau production** pour créer des
|
||||
- **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)
|
||||
[→ En savoir plus sur toutes les fonctionnalités](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
|
||||
|
||||
[→ Voir toutes les intégrations](https://link.langbot.app/en/docs/features)
|
||||
[→ Voir toutes les intégrations](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_JP.md
12
README_JP.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/ja/insight/features.html">機能</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">プラグインマーケット</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot は、AI搭載のインスタントメッセージングボットを構
|
||||
- **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)
|
||||
[→ すべての機能について詳しく見る](https://docs.langbot.app/ja/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [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 | ✅ |
|
||||
|
||||
[→ すべての統合を表示](https://link.langbot.app/en/docs/features)
|
||||
[→ すべての統合を表示](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_KO.md
12
README_KO.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/en/insight/features.html">기능</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">문서</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">플러그인 마켓</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈
|
||||
- **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)
|
||||
[→ 모든 기능 자세히 보기](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
|
||||
|
||||
[→ 모든 통합 보기](https://link.langbot.app/en/docs/features)
|
||||
[→ 모든 통합 보기](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_RU.md
12
README_RU.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/en/insight/features.html">Возможности</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Магазин плагинов</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot — это **платформа с открытым исходным к
|
||||
- **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)
|
||||
[→ Подробнее обо всех возможностях](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
|
||||
|
||||
[→ Смотреть все интеграции](https://link.langbot.app/en/docs/features)
|
||||
[→ Смотреть все интеграции](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_TW.md
12
README_TW.md
@@ -21,9 +21,9 @@
|
||||
[](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://docs.langbot.app/zh/insight/features.html">特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">外掛市場</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路線圖</a>
|
||||
|
||||
@@ -46,7 +46,7 @@ LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時
|
||||
- **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)
|
||||
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -77,7 +77,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/zh-CN/templates/ZKTBDH)
|
||||
[](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)
|
||||
**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [寶塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -139,7 +139,7 @@ docker compose up -d
|
||||
|-----------|------|
|
||||
| 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)
|
||||
[→ 查看完整整合列表](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
12
README_VI.md
12
README_VI.md
@@ -19,9 +19,9 @@
|
||||
[](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://docs.langbot.app/en/insight/features.html">Tính năng</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Chợ Plugin</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
|
||||
|
||||
@@ -44,7 +44,7 @@ LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để x
|
||||
- **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)
|
||||
[→ Tìm hiểu thêm về tất cả tính năng](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
@@ -75,7 +75,7 @@ docker compose up -d
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](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)
|
||||
**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
@@ -123,7 +123,7 @@ docker compose up -d
|
||||
| [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
|
||||
|
||||
[→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)
|
||||
[→ Xem tất cả tích hợp](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -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/)
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "langbot"
|
||||
version = "4.9.6"
|
||||
version = "4.9.4"
|
||||
description = "Production-grade platform for building agentic IM bots"
|
||||
readme = "README.md"
|
||||
license-files = ["LICENSE"]
|
||||
@@ -8,7 +8,7 @@ requires-python = ">=3.11,<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",
|
||||
@@ -16,7 +16,7 @@ dependencies = [
|
||||
"async-lru>=2.0.5",
|
||||
"certifi>=2025.4.26",
|
||||
"colorlog~=6.6.0",
|
||||
"cryptography>=46.0.7",
|
||||
"cryptography>=44.0.3",
|
||||
"dashscope>=1.25.10",
|
||||
"dingtalk-stream>=0.24.0",
|
||||
"discord-py>=2.5.2",
|
||||
@@ -27,7 +27,7 @@ dependencies = [
|
||||
"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",
|
||||
@@ -39,7 +39,6 @@ dependencies = [
|
||||
"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",
|
||||
@@ -50,7 +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",
|
||||
@@ -61,15 +60,11 @@ 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",
|
||||
"langchain-text-splitters>=0.0.1",
|
||||
"chromadb>=1.0.0,<2.0.0",
|
||||
"qdrant-client (>=1.15.1,<2.0.0)",
|
||||
"pyseekdb==1.1.0.post3",
|
||||
"langbot-plugin==0.3.8",
|
||||
"langbot-plugin==0.3.5",
|
||||
"asyncpg>=0.30.0",
|
||||
"line-bot-sdk>=3.19.0",
|
||||
"tboxsdk>=0.0.10",
|
||||
@@ -77,7 +72,6 @@ dependencies = [
|
||||
"pymilvus>=2.6.4",
|
||||
"pgvector>=0.4.1",
|
||||
"botocore>=1.42.39",
|
||||
"litellm>=1.0.0",
|
||||
]
|
||||
keywords = [
|
||||
"bot",
|
||||
@@ -117,12 +111,12 @@ 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",
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
"""LangBot - Production-grade platform for building agentic IM bots"""
|
||||
|
||||
__version__ = '4.9.6'
|
||||
__version__ = '4.9.4'
|
||||
|
||||
@@ -182,88 +182,6 @@ class DingTalkClient:
|
||||
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 +193,6 @@ 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()
|
||||
|
||||
@@ -359,25 +268,7 @@ 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':
|
||||
|
||||
@@ -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。
|
||||
|
||||
@@ -71,11 +71,6 @@ class StreamSession:
|
||||
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
|
||||
|
||||
@@ -219,17 +214,11 @@ 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:
|
||||
@@ -239,9 +228,6 @@ 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:
|
||||
@@ -448,10 +434,10 @@ async def parse_wecom_bot_message(
|
||||
}
|
||||
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
|
||||
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')
|
||||
@@ -463,12 +449,10 @@ async def parse_wecom_bot_message(
|
||||
'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}'
|
||||
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
|
||||
message_data['video'] = video_data
|
||||
elif msg_type == 'file':
|
||||
file_info = msg_json.get('file', {}) or {}
|
||||
@@ -482,15 +466,12 @@ async def parse_wecom_bot_message(
|
||||
'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}'
|
||||
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
|
||||
message_data['file'] = file_data
|
||||
elif msg_type == 'link':
|
||||
message_data['link'] = msg_json.get('link', {})
|
||||
@@ -606,120 +587,6 @@ async def parse_wecom_bot_message(
|
||||
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
|
||||
|
||||
|
||||
@@ -1031,38 +898,36 @@ class WecomBotClient:
|
||||
)
|
||||
|
||||
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}'
|
||||
f'反馈关联到会话: stream_id={session.stream_id}, msg_id={session.msg_id}, '
|
||||
f'user_id={session.user_id}'
|
||||
)
|
||||
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())
|
||||
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())
|
||||
await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话')
|
||||
|
||||
except Exception:
|
||||
await self.logger.error(traceback.format_exc())
|
||||
|
||||
@@ -147,10 +147,3 @@ class WecomBotEvent(dict):
|
||||
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', {})
|
||||
|
||||
@@ -20,7 +20,7 @@ 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.libs.wecom_ai_bot_api.api import parse_wecom_bot_message
|
||||
from langbot.pkg.platform.logger import EventLogger
|
||||
|
||||
DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
|
||||
@@ -96,12 +96,6 @@ class WecomBotWsClient:
|
||||
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 ──────────────────────────────────────────────────
|
||||
|
||||
@@ -170,27 +164,12 @@ class WecomBotWsClient:
|
||||
|
||||
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.
|
||||
|
||||
@@ -199,22 +178,17 @@ class WecomBotWsClient:
|
||||
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,
|
||||
'stream': {
|
||||
'id': stream_id,
|
||||
'finish': finish,
|
||||
'content': content,
|
||||
},
|
||||
}
|
||||
return await self._send_reply(req_id, body)
|
||||
|
||||
@@ -279,23 +253,11 @@ class WecomBotWsClient:
|
||||
# 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)
|
||||
await self.reply_stream(req_id, stream_id, content, finish=is_final)
|
||||
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()}')
|
||||
@@ -483,15 +445,6 @@ class WecomBotWsClient:
|
||||
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
|
||||
|
||||
@@ -501,7 +454,7 @@ class WecomBotWsClient:
|
||||
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)."""
|
||||
"""Handle an incoming event callback frame (enter_chat, template_card_event, etc.)."""
|
||||
try:
|
||||
body = frame.get('body', {})
|
||||
req_id = frame.get('headers', {}).get('req_id', '')
|
||||
@@ -526,54 +479,14 @@ class WecomBotWsClient:
|
||||
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)
|
||||
|
||||
# Dispatch to event-specific handlers
|
||||
if event_type in self._message_handlers:
|
||||
for handler in self._message_handlers[event_type]:
|
||||
await handler(event)
|
||||
|
||||
# Also dispatch to generic 'event' handlers
|
||||
if 'event' in self._message_handlers:
|
||||
for handler in self._message_handlers['event']:
|
||||
await handler(event)
|
||||
|
||||
@@ -97,51 +97,3 @@ 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()
|
||||
|
||||
@@ -15,7 +15,6 @@ class ModelProvidersRouterGroup(group.RouterGroup):
|
||||
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
|
||||
@@ -33,7 +32,6 @@ class ModelProvidersRouterGroup(group.RouterGroup):
|
||||
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
|
||||
@@ -45,12 +43,3 @@ class ModelProvidersRouterGroup(group.RouterGroup):
|
||||
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))
|
||||
|
||||
@@ -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}')
|
||||
@@ -105,24 +105,23 @@ 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
|
||||
elif path.startswith('home/'):
|
||||
# SPA fallback for /home/* sub-routes.
|
||||
# Entity detail views use query params (e.g. /home/bots?id=uuid),
|
||||
# so the pre-rendered list page is served directly via path + '.html'.
|
||||
# This fallback handles any remaining unmatched sub-paths.
|
||||
segments = path.rstrip('/').split('/')
|
||||
|
||||
# Fallback to index.html for SPA client-side routing
|
||||
# Walk up parent segments looking for matching .html files
|
||||
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
|
||||
# Final fallback to index.html for /home/* routes
|
||||
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'
|
||||
|
||||
@@ -367,162 +367,3 @@ class EmbeddingModelsService:
|
||||
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(**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.',
|
||||
],
|
||||
)
|
||||
|
||||
@@ -1224,83 +1224,30 @@ class MonitoringService:
|
||||
"""
|
||||
import json
|
||||
|
||||
now = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None)
|
||||
reasons_json = json.dumps(inaccurate_reasons, ensure_ascii=False) if inaccurate_reasons else None
|
||||
record_id = str(uuid.uuid4())
|
||||
record_data = {
|
||||
'id': record_id,
|
||||
'timestamp': datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None),
|
||||
'feedback_id': feedback_id,
|
||||
'feedback_type': feedback_type,
|
||||
'feedback_content': feedback_content,
|
||||
'inaccurate_reasons': json.dumps(inaccurate_reasons, ensure_ascii=False) if inaccurate_reasons else None,
|
||||
'bot_id': bot_id,
|
||||
'bot_name': bot_name,
|
||||
'pipeline_id': pipeline_id,
|
||||
'pipeline_name': pipeline_name,
|
||||
'session_id': session_id,
|
||||
'message_id': message_id,
|
||||
'stream_id': stream_id,
|
||||
'user_id': user_id,
|
||||
'platform': platform,
|
||||
}
|
||||
|
||||
MonitoringFeedback = persistence_monitoring.MonitoringFeedback
|
||||
|
||||
# Handle cancel feedback (type=3): delete existing record
|
||||
if feedback_type == 3:
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.delete(MonitoringFeedback).where(MonitoringFeedback.feedback_id == feedback_id)
|
||||
)
|
||||
return None
|
||||
|
||||
# Check if record with this feedback_id already exists
|
||||
existing_result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(MonitoringFeedback).where(MonitoringFeedback.feedback_id == feedback_id)
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.insert(persistence_monitoring.MonitoringFeedback).values(record_data)
|
||||
)
|
||||
existing_row = existing_result.first()
|
||||
|
||||
if existing_row:
|
||||
# UPDATE existing record
|
||||
existing = existing_row[0] if isinstance(existing_row, tuple) else existing_row
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.update(MonitoringFeedback)
|
||||
.where(MonitoringFeedback.feedback_id == feedback_id)
|
||||
.values(
|
||||
timestamp=now,
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=feedback_content,
|
||||
inaccurate_reasons=reasons_json,
|
||||
bot_id=bot_id or existing.bot_id,
|
||||
bot_name=bot_name or existing.bot_name,
|
||||
pipeline_id=pipeline_id or existing.pipeline_id,
|
||||
pipeline_name=pipeline_name or existing.pipeline_name,
|
||||
session_id=session_id or existing.session_id,
|
||||
message_id=message_id or existing.message_id,
|
||||
stream_id=stream_id or existing.stream_id,
|
||||
user_id=user_id or existing.user_id,
|
||||
platform=platform or existing.platform,
|
||||
)
|
||||
)
|
||||
return existing.id
|
||||
else:
|
||||
# INSERT new record with IntegrityError defense
|
||||
record_id = str(uuid.uuid4())
|
||||
record_data = {
|
||||
'id': record_id,
|
||||
'timestamp': now,
|
||||
'feedback_id': feedback_id,
|
||||
'feedback_type': feedback_type,
|
||||
'feedback_content': feedback_content,
|
||||
'inaccurate_reasons': reasons_json,
|
||||
'bot_id': bot_id,
|
||||
'bot_name': bot_name,
|
||||
'pipeline_id': pipeline_id,
|
||||
'pipeline_name': pipeline_name,
|
||||
'session_id': session_id,
|
||||
'message_id': message_id,
|
||||
'stream_id': stream_id,
|
||||
'user_id': user_id,
|
||||
'platform': platform,
|
||||
}
|
||||
try:
|
||||
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(MonitoringFeedback).values(record_data))
|
||||
return record_id
|
||||
except Exception:
|
||||
# UNIQUE constraint conflict (concurrent feedback for same feedback_id)
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.update(MonitoringFeedback)
|
||||
.where(MonitoringFeedback.feedback_id == feedback_id)
|
||||
.values(
|
||||
timestamp=now,
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=feedback_content,
|
||||
inaccurate_reasons=reasons_json,
|
||||
)
|
||||
)
|
||||
return feedback_id
|
||||
return record_id
|
||||
|
||||
async def get_feedback_stats(
|
||||
self,
|
||||
@@ -1354,19 +1301,28 @@ class MonitoringService:
|
||||
satisfaction_rate = (total_likes / total_feedback * 100) if total_feedback > 0 else 0
|
||||
|
||||
# Get feedback by bot
|
||||
bot_stats_query = sqlalchemy.select(
|
||||
persistence_monitoring.MonitoringFeedback.bot_id,
|
||||
persistence_monitoring.MonitoringFeedback.bot_name,
|
||||
sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id).label('total'),
|
||||
sqlalchemy.func.sum(
|
||||
sqlalchemy.case((persistence_monitoring.MonitoringFeedback.feedback_type == 1, 1), else_=0)
|
||||
).label('likes'),
|
||||
sqlalchemy.func.sum(
|
||||
sqlalchemy.case((persistence_monitoring.MonitoringFeedback.feedback_type == 2, 1), else_=0)
|
||||
).label('dislikes'),
|
||||
).group_by(
|
||||
persistence_monitoring.MonitoringFeedback.bot_id,
|
||||
persistence_monitoring.MonitoringFeedback.bot_name,
|
||||
bot_stats_query = (
|
||||
sqlalchemy.select(
|
||||
persistence_monitoring.MonitoringFeedback.bot_id,
|
||||
persistence_monitoring.MonitoringFeedback.bot_name,
|
||||
sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id).label('total'),
|
||||
sqlalchemy.func.sum(
|
||||
sqlalchemy.case(
|
||||
(persistence_monitoring.MonitoringFeedback.feedback_type == 1, 1),
|
||||
else_=0
|
||||
)
|
||||
).label('likes'),
|
||||
sqlalchemy.func.sum(
|
||||
sqlalchemy.case(
|
||||
(persistence_monitoring.MonitoringFeedback.feedback_type == 2, 1),
|
||||
else_=0
|
||||
)
|
||||
).label('dislikes'),
|
||||
)
|
||||
.group_by(
|
||||
persistence_monitoring.MonitoringFeedback.bot_id,
|
||||
persistence_monitoring.MonitoringFeedback.bot_name,
|
||||
)
|
||||
)
|
||||
if conditions:
|
||||
bot_stats_query = bot_stats_query.where(sqlalchemy.and_(*conditions))
|
||||
@@ -1477,9 +1433,7 @@ class MonitoringService:
|
||||
'id': row[0].id if isinstance(row, tuple) else row.id,
|
||||
'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
|
||||
'feedback_id': row[0].feedback_id if isinstance(row, tuple) else row.feedback_id,
|
||||
'feedback_type': 'like'
|
||||
if (row[0].feedback_type if isinstance(row, tuple) else row.feedback_type) == 1
|
||||
else 'dislike',
|
||||
'feedback_type': 'like' if (row[0].feedback_type if isinstance(row, tuple) else row.feedback_type) == 1 else 'dislike',
|
||||
'feedback_content': row[0].feedback_content if isinstance(row, tuple) else row.feedback_content,
|
||||
'inaccurate_reasons': row[0].inaccurate_reasons if isinstance(row, tuple) else row.inaccurate_reasons,
|
||||
'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
import traceback
|
||||
|
||||
import sqlalchemy
|
||||
|
||||
@@ -98,14 +97,6 @@ class ModelProviderService:
|
||||
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
|
||||
@@ -130,14 +121,7 @@ class ModelProviderService:
|
||||
)
|
||||
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}
|
||||
return {'llm_count': llm_count, 'embedding_count': embedding_count}
|
||||
|
||||
async def find_or_create_provider(self, requester: str, base_url: str, api_keys: list) -> str:
|
||||
"""Find existing provider or create new one"""
|
||||
@@ -180,66 +164,3 @@ class ModelProviderService:
|
||||
.values(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}
|
||||
|
||||
@@ -179,7 +179,7 @@ class SpaceService:
|
||||
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:
|
||||
async with session.get(f'{space_url}/api/v1/models') as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to get models: {await response.text()}')
|
||||
data = await response.json()
|
||||
|
||||
@@ -65,8 +65,8 @@ class UserService:
|
||||
|
||||
user_obj = result_list[0]
|
||||
|
||||
# Check if this user has a local password set
|
||||
if not user_obj.password:
|
||||
# Check if this is a Space account
|
||||
if user_obj.account_type == 'space':
|
||||
raise ValueError('请使用 Space 账户登录')
|
||||
|
||||
ph = argon2.PasswordHasher()
|
||||
@@ -108,8 +108,9 @@ 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')
|
||||
# Space accounts cannot change password locally
|
||||
if user_obj.account_type == 'space':
|
||||
raise ValueError('Space account cannot change password locally')
|
||||
|
||||
ph.verify(user_obj.password, current_password)
|
||||
|
||||
|
||||
@@ -133,8 +133,6 @@ class Application:
|
||||
|
||||
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
|
||||
|
||||
@@ -61,9 +61,6 @@ class BuildAppStage(stage.BootingStage):
|
||||
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
|
||||
|
||||
|
||||
@@ -80,12 +80,8 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
|
||||
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
|
||||
if isinstance(current[key], (dict, list)):
|
||||
# Skip dict and list types
|
||||
pass
|
||||
else:
|
||||
# Valid scalar value - convert and set it
|
||||
|
||||
@@ -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,
|
||||
|
||||
@@ -59,22 +59,3 @@ class EmbeddingModel(Base):
|
||||
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,
|
||||
nullable=False,
|
||||
server_default=sqlalchemy.func.now(),
|
||||
onupdate=sqlalchemy.func.now(),
|
||||
)
|
||||
|
||||
@@ -1,51 +0,0 @@
|
||||
"""Alembic environment for LangBot.
|
||||
|
||||
This env.py is designed to be called programmatically (not via CLI).
|
||||
It supports both SQLite and PostgreSQL.
|
||||
|
||||
The sync connection is passed via config attributes by the runner.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from alembic import context
|
||||
from sqlalchemy.engine import Connection
|
||||
|
||||
from langbot.pkg.entity.persistence.base import Base
|
||||
|
||||
target_metadata = Base.metadata
|
||||
|
||||
|
||||
def run_migrations_offline() -> None:
|
||||
"""Run migrations in 'offline' mode — emit SQL without a live connection."""
|
||||
url = context.config.get_main_option('sqlalchemy.url')
|
||||
context.configure(
|
||||
url=url,
|
||||
target_metadata=target_metadata,
|
||||
literal_binds=True,
|
||||
dialect_opts={'paramstyle': 'named'},
|
||||
)
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
def run_migrations_online() -> None:
|
||||
"""Run migrations with a live sync connection passed via config attributes."""
|
||||
connection: Connection = context.config.attributes.get('connection')
|
||||
if connection is None:
|
||||
raise RuntimeError('connection not provided in alembic config attributes')
|
||||
|
||||
context.configure(
|
||||
connection=connection,
|
||||
target_metadata=target_metadata,
|
||||
# render_as_batch=True is critical for SQLite ALTER TABLE support
|
||||
render_as_batch=True,
|
||||
)
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
if context.is_offline_mode():
|
||||
run_migrations_offline()
|
||||
else:
|
||||
run_migrations_online()
|
||||
@@ -1,24 +0,0 @@
|
||||
# Alembic script.py.mako — template for auto-generated revisions
|
||||
"""${message}
|
||||
|
||||
Revision ID: ${up_revision}
|
||||
Revises: ${down_revision | comma,n}
|
||||
Create Date: ${create_date}
|
||||
"""
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
${imports if imports else ""}
|
||||
|
||||
# revision identifiers
|
||||
revision = ${repr(up_revision)}
|
||||
down_revision = ${repr(down_revision)}
|
||||
branch_labels = ${repr(branch_labels)}
|
||||
depends_on = ${repr(depends_on)}
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
${upgrades if upgrades else "pass"}
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
${downgrades if downgrades else "pass"}
|
||||
@@ -1,24 +0,0 @@
|
||||
"""baseline: stamp existing schema (db version 25)
|
||||
|
||||
This is a no-op migration that marks the starting point for Alembic.
|
||||
All tables already exist via create_all() + legacy DBMigration system.
|
||||
|
||||
Revision ID: 0001_baseline
|
||||
Revises: None
|
||||
Create Date: 2026-04-08
|
||||
"""
|
||||
|
||||
revision = '0001_baseline'
|
||||
down_revision = None
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# No-op: existing schema is already at database_version=25
|
||||
# This revision serves as the Alembic baseline.
|
||||
pass
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
pass
|
||||
@@ -1,62 +0,0 @@
|
||||
"""example: sample migration demonstrating Alembic patterns
|
||||
|
||||
This is a SAMPLE showing how to write migrations that work
|
||||
seamlessly across SQLite and PostgreSQL. Delete or adapt as needed.
|
||||
|
||||
Revision ID: 0002_sample
|
||||
Revises: 0001_baseline
|
||||
Create Date: 2026-04-08
|
||||
|
||||
Patterns demonstrated:
|
||||
1. Schema change (add column) — works on both DBs via render_as_batch
|
||||
2. Data migration (read + modify JSON) — pure SQLAlchemy, no dialect branching
|
||||
"""
|
||||
|
||||
revision = '0002_sample'
|
||||
down_revision = '0001_baseline'
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""
|
||||
EXAMPLE: Uncomment to use. This shows the patterns.
|
||||
|
||||
# --- Pattern 1: Schema change (add/drop column) ---
|
||||
# render_as_batch=True in env.py makes this work on SQLite too.
|
||||
#
|
||||
# op.add_column('pipelines', sa.Column('description', sa.String(512), server_default=''))
|
||||
|
||||
# --- Pattern 2: Data migration (read + modify JSON field) ---
|
||||
# No if/else for sqlite vs postgres needed!
|
||||
#
|
||||
# conn = op.get_bind()
|
||||
# rows = conn.execute(sa.text("SELECT uuid, config FROM pipelines")).fetchall()
|
||||
# for row in rows:
|
||||
# config = json.loads(row[1]) if isinstance(row[1], str) else row[1]
|
||||
# # Modify the config
|
||||
# config.setdefault('ai', {}).setdefault('some_new_key', 'default_value')
|
||||
# conn.execute(
|
||||
# sa.text("UPDATE pipelines SET config = :cfg WHERE uuid = :uuid"),
|
||||
# {"cfg": json.dumps(config), "uuid": row[0]}
|
||||
# )
|
||||
|
||||
# --- Pattern 3: Create a new table ---
|
||||
#
|
||||
# op.create_table(
|
||||
# 'audit_log',
|
||||
# sa.Column('id', sa.Integer, primary_key=True, autoincrement=True),
|
||||
# sa.Column('action', sa.String(255), nullable=False),
|
||||
# sa.Column('detail', sa.Text),
|
||||
# sa.Column('created_at', sa.DateTime, server_default=sa.func.now()),
|
||||
# )
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""
|
||||
# op.drop_column('pipelines', 'description')
|
||||
# op.drop_table('audit_log')
|
||||
"""
|
||||
pass
|
||||
@@ -1,35 +0,0 @@
|
||||
"""add rerank_models table
|
||||
|
||||
Revision ID: 0003_add_rerank_models
|
||||
Revises: 0002_sample
|
||||
Create Date: 2026-04-19
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
from alembic import op
|
||||
|
||||
revision = '0003_add_rerank_models'
|
||||
down_revision = '0002_sample'
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# Check if table already exists (may have been created by create_all())
|
||||
conn = op.get_bind()
|
||||
inspector = sa.inspect(conn)
|
||||
if 'rerank_models' not in inspector.get_table_names():
|
||||
op.create_table(
|
||||
'rerank_models',
|
||||
sa.Column('uuid', sa.String(255), primary_key=True, unique=True),
|
||||
sa.Column('name', sa.String(255), nullable=False),
|
||||
sa.Column('provider_uuid', sa.String(255), nullable=False),
|
||||
sa.Column('extra_args', sa.JSON, nullable=False, server_default='{}'),
|
||||
sa.Column('prefered_ranking', sa.Integer, nullable=False, server_default='0'),
|
||||
sa.Column('created_at', sa.DateTime, nullable=False, server_default=sa.func.now()),
|
||||
sa.Column('updated_at', sa.DateTime, nullable=False, server_default=sa.func.now()),
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
op.drop_table('rerank_models')
|
||||
@@ -1,150 +0,0 @@
|
||||
"""Programmatic Alembic runner for LangBot.
|
||||
|
||||
Usage from async code:
|
||||
from langbot.pkg.persistence.alembic_runner import run_alembic_upgrade
|
||||
await run_alembic_upgrade(async_engine)
|
||||
|
||||
CLI usage (autogenerate):
|
||||
python -m langbot.pkg.persistence.alembic_runner autogenerate "add description column"
|
||||
python -m langbot.pkg.persistence.alembic_runner upgrade
|
||||
python -m langbot.pkg.persistence.alembic_runner current
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from alembic.config import Config
|
||||
from alembic import command
|
||||
from alembic.runtime.migration import MigrationContext
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from sqlalchemy.ext.asyncio import AsyncEngine
|
||||
from sqlalchemy.engine import Connection
|
||||
|
||||
|
||||
_ALEMBIC_DIR = os.path.join(os.path.dirname(__file__), 'alembic')
|
||||
|
||||
|
||||
def _build_config(connection: Connection) -> Config:
|
||||
"""Build an Alembic Config with sync connection attached."""
|
||||
cfg = Config()
|
||||
cfg.set_main_option('script_location', _ALEMBIC_DIR)
|
||||
cfg.attributes['connection'] = connection
|
||||
return cfg
|
||||
|
||||
|
||||
def _do_upgrade(connection: Connection, revision: str = 'head') -> None:
|
||||
"""Synchronous upgrade — runs inside run_sync."""
|
||||
cfg = _build_config(connection)
|
||||
command.upgrade(cfg, revision)
|
||||
|
||||
|
||||
def _do_stamp(connection: Connection, revision: str = 'head') -> None:
|
||||
"""Synchronous stamp — runs inside run_sync."""
|
||||
cfg = _build_config(connection)
|
||||
command.stamp(cfg, revision)
|
||||
|
||||
|
||||
def _do_get_current(connection: Connection) -> str | None:
|
||||
"""Get current alembic revision synchronously."""
|
||||
ctx = MigrationContext.configure(connection)
|
||||
return ctx.get_current_revision()
|
||||
|
||||
|
||||
def _do_autogenerate(connection: Connection, message: str = 'auto migration') -> None:
|
||||
"""Synchronous autogenerate — runs inside run_sync."""
|
||||
cfg = _build_config(connection)
|
||||
command.revision(cfg, message=message, autogenerate=True)
|
||||
|
||||
|
||||
async def run_alembic_upgrade(async_engine: AsyncEngine, revision: str = 'head') -> None:
|
||||
"""Run Alembic upgrade to the given revision."""
|
||||
async with async_engine.connect() as conn:
|
||||
await conn.run_sync(_do_upgrade, revision)
|
||||
await conn.commit()
|
||||
|
||||
|
||||
async def run_alembic_stamp(async_engine: AsyncEngine, revision: str = 'head') -> None:
|
||||
"""Stamp the database with a revision without running migrations."""
|
||||
async with async_engine.connect() as conn:
|
||||
await conn.run_sync(_do_stamp, revision)
|
||||
await conn.commit()
|
||||
|
||||
|
||||
async def get_alembic_current(async_engine: AsyncEngine) -> str | None:
|
||||
"""Get current alembic revision, or None if not stamped."""
|
||||
async with async_engine.connect() as conn:
|
||||
return await conn.run_sync(_do_get_current)
|
||||
|
||||
|
||||
async def run_alembic_autogenerate(async_engine: AsyncEngine, message: str = 'auto migration') -> None:
|
||||
"""Compare ORM models against DB schema and generate a migration script."""
|
||||
async with async_engine.connect() as conn:
|
||||
await conn.run_sync(_do_autogenerate, message)
|
||||
|
||||
|
||||
# CLI entrypoint: python -m langbot.pkg.persistence.alembic_runner <command> [args]
|
||||
if __name__ == '__main__':
|
||||
import sys
|
||||
import asyncio
|
||||
|
||||
def _get_engine():
|
||||
"""Create engine from data/config.yaml or default SQLite."""
|
||||
from sqlalchemy.ext.asyncio import create_async_engine
|
||||
|
||||
try:
|
||||
import yaml
|
||||
|
||||
with open('data/config.yaml') as f:
|
||||
config = yaml.safe_load(f)
|
||||
db_cfg = config.get('database', {})
|
||||
db_type = db_cfg.get('use', 'sqlite')
|
||||
if db_type == 'postgresql':
|
||||
pg = db_cfg.get('postgresql', {})
|
||||
url = (
|
||||
f'postgresql+asyncpg://{pg.get("user", "postgres")}:{pg.get("password", "postgres")}'
|
||||
f'@{pg.get("host", "127.0.0.1")}:{pg.get("port", 5432)}/{pg.get("database", "postgres")}'
|
||||
)
|
||||
else:
|
||||
path = db_cfg.get('sqlite', {}).get('path', 'data/langbot.db')
|
||||
url = f'sqlite+aiosqlite:///{path}'
|
||||
except Exception:
|
||||
url = 'sqlite+aiosqlite:///data/langbot.db'
|
||||
|
||||
return create_async_engine(url)
|
||||
|
||||
def main():
|
||||
if len(sys.argv) < 2:
|
||||
print('Usage: python -m langbot.pkg.persistence.alembic_runner <command> [args]')
|
||||
print('Commands:')
|
||||
print(' autogenerate "message" — Generate migration from ORM model diff')
|
||||
print(' upgrade [revision] — Upgrade database (default: head)')
|
||||
print(' stamp [revision] — Stamp revision without running (default: head)')
|
||||
print(' current — Show current revision')
|
||||
sys.exit(1)
|
||||
|
||||
cmd = sys.argv[1]
|
||||
engine = _get_engine()
|
||||
|
||||
if cmd == 'autogenerate':
|
||||
msg = sys.argv[2] if len(sys.argv) > 2 else 'auto migration'
|
||||
asyncio.run(run_alembic_autogenerate(engine, msg))
|
||||
print(f'Migration generated: {msg}')
|
||||
elif cmd == 'upgrade':
|
||||
rev = sys.argv[2] if len(sys.argv) > 2 else 'head'
|
||||
asyncio.run(run_alembic_upgrade(engine, rev))
|
||||
print(f'Upgraded to: {rev}')
|
||||
elif cmd == 'stamp':
|
||||
rev = sys.argv[2] if len(sys.argv) > 2 else 'head'
|
||||
asyncio.run(run_alembic_stamp(engine, rev))
|
||||
print(f'Stamped: {rev}')
|
||||
elif cmd == 'current':
|
||||
rev = asyncio.run(get_alembic_current(engine))
|
||||
print(f'Current revision: {rev}')
|
||||
else:
|
||||
print(f'Unknown command: {cmd}')
|
||||
sys.exit(1)
|
||||
|
||||
main()
|
||||
@@ -76,9 +76,6 @@ class PersistenceManager:
|
||||
|
||||
self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
|
||||
|
||||
# Run Alembic migrations (new migration system)
|
||||
await self._run_alembic_migrations()
|
||||
|
||||
await self.write_space_model_providers()
|
||||
|
||||
async def create_tables(self):
|
||||
@@ -138,28 +135,6 @@ class PersistenceManager:
|
||||
|
||||
# =================================
|
||||
|
||||
async def _run_alembic_migrations(self):
|
||||
"""Run Alembic-based migrations after legacy migrations complete."""
|
||||
from . import alembic_runner
|
||||
|
||||
engine = self.get_db_engine()
|
||||
|
||||
try:
|
||||
current_rev = await alembic_runner.get_alembic_current(engine)
|
||||
|
||||
if current_rev is None:
|
||||
# First time: stamp baseline so Alembic knows existing schema is up-to-date
|
||||
self.ap.logger.info('Alembic: no revision found, stamping baseline...')
|
||||
await alembic_runner.run_alembic_stamp(engine, '0001_baseline')
|
||||
current_rev = '0001_baseline'
|
||||
|
||||
# Upgrade to head
|
||||
await alembic_runner.run_alembic_upgrade(engine, 'head')
|
||||
self.ap.logger.info('Alembic migrations completed.')
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Alembic migration failed: {e}', exc_info=True)
|
||||
raise
|
||||
|
||||
async def execute_async(self, *args, **kwargs) -> sqlalchemy.engine.cursor.CursorResult:
|
||||
async with self.get_db_engine().connect() as conn:
|
||||
result = await conn.execute(*args, **kwargs)
|
||||
|
||||
@@ -1,15 +0,0 @@
|
||||
import sqlalchemy
|
||||
from .. import migration
|
||||
|
||||
|
||||
@migration.migration_class(25)
|
||||
class DBMigrateBotPipelineRoutingRules(migration.DBMigration):
|
||||
"""Add pipeline_routing_rules column to bots table"""
|
||||
|
||||
async def upgrade(self):
|
||||
sql_text = sqlalchemy.text("ALTER TABLE bots ADD COLUMN pipeline_routing_rules JSON NOT NULL DEFAULT '[]'")
|
||||
await self.ap.persistence_mgr.execute_async(sql_text)
|
||||
|
||||
async def downgrade(self):
|
||||
sql_text = sqlalchemy.text('ALTER TABLE bots DROP COLUMN pipeline_routing_rules')
|
||||
await self.ap.persistence_mgr.execute_async(sql_text)
|
||||
@@ -0,0 +1,75 @@
|
||||
import sqlalchemy
|
||||
from .. import migration
|
||||
|
||||
|
||||
@migration.migration_class(25)
|
||||
class DBMigrateFeedbackStats(migration.DBMigration):
|
||||
"""Add monitoring_feedback table for storing user feedback from AI Bot conversations"""
|
||||
|
||||
async def _table_exists(self, table_name: str) -> bool:
|
||||
"""Check if a table exists (works for both SQLite and PostgreSQL)."""
|
||||
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 bool(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 upgrade(self):
|
||||
"""Create monitoring_feedback table."""
|
||||
if await self._table_exists('monitoring_feedback'):
|
||||
self.ap.logger.debug('monitoring_feedback table already exists, skipping migration.')
|
||||
return
|
||||
|
||||
# Create monitoring_feedback table with all columns
|
||||
create_table_sql = '''
|
||||
CREATE TABLE monitoring_feedback (
|
||||
id VARCHAR(255) PRIMARY KEY,
|
||||
timestamp DATETIME NOT NULL,
|
||||
feedback_id VARCHAR(255) NOT NULL UNIQUE,
|
||||
feedback_type INTEGER NOT NULL,
|
||||
feedback_content TEXT,
|
||||
inaccurate_reasons TEXT,
|
||||
bot_id VARCHAR(255),
|
||||
bot_name VARCHAR(255),
|
||||
pipeline_id VARCHAR(255),
|
||||
pipeline_name VARCHAR(255),
|
||||
session_id VARCHAR(255),
|
||||
message_id VARCHAR(255),
|
||||
stream_id VARCHAR(255),
|
||||
user_id VARCHAR(255),
|
||||
platform VARCHAR(255)
|
||||
)
|
||||
'''
|
||||
await self.ap.persistence_mgr.execute_async(sqlalchemy.text(create_table_sql))
|
||||
|
||||
# Create indexes
|
||||
indexes = [
|
||||
'CREATE INDEX ix_monitoring_feedback_timestamp ON monitoring_feedback (timestamp)',
|
||||
'CREATE UNIQUE INDEX ix_monitoring_feedback_feedback_id ON monitoring_feedback (feedback_id)',
|
||||
'CREATE INDEX ix_monitoring_feedback_bot_id ON monitoring_feedback (bot_id)',
|
||||
'CREATE INDEX ix_monitoring_feedback_pipeline_id ON monitoring_feedback (pipeline_id)',
|
||||
'CREATE INDEX ix_monitoring_feedback_session_id ON monitoring_feedback (session_id)',
|
||||
'CREATE INDEX ix_monitoring_feedback_message_id ON monitoring_feedback (message_id)',
|
||||
'CREATE INDEX ix_monitoring_feedback_stream_id ON monitoring_feedback (stream_id)',
|
||||
]
|
||||
for index_sql in indexes:
|
||||
await self.ap.persistence_mgr.execute_async(sqlalchemy.text(index_sql))
|
||||
|
||||
self.ap.logger.info('Created monitoring_feedback table with indexes.')
|
||||
|
||||
async def downgrade(self):
|
||||
"""Drop monitoring_feedback table."""
|
||||
if await self._table_exists('monitoring_feedback'):
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.text('DROP TABLE monitoring_feedback')
|
||||
)
|
||||
self.ap.logger.info('Dropped monitoring_feedback table.')
|
||||
@@ -37,7 +37,6 @@ class PendingMessage:
|
||||
message_chain: platform_message.MessageChain
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter
|
||||
pipeline_uuid: typing.Optional[str]
|
||||
routed_by_rule: bool = False
|
||||
timestamp: float = field(default_factory=time.time)
|
||||
|
||||
|
||||
@@ -126,7 +125,6 @@ class MessageAggregator:
|
||||
message_chain: platform_message.MessageChain,
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
|
||||
pipeline_uuid: typing.Optional[str] = None,
|
||||
routed_by_rule: bool = False,
|
||||
) -> None:
|
||||
"""Add a message to the aggregation buffer
|
||||
|
||||
@@ -147,7 +145,6 @@ class MessageAggregator:
|
||||
message_chain=message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
routed_by_rule=routed_by_rule,
|
||||
)
|
||||
return
|
||||
|
||||
@@ -162,7 +159,6 @@ class MessageAggregator:
|
||||
message_chain=message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
routed_by_rule=routed_by_rule,
|
||||
)
|
||||
|
||||
force_flush = False
|
||||
@@ -221,7 +217,6 @@ class MessageAggregator:
|
||||
message_chain=msg.message_chain,
|
||||
adapter=msg.adapter,
|
||||
pipeline_uuid=msg.pipeline_uuid,
|
||||
routed_by_rule=msg.routed_by_rule,
|
||||
)
|
||||
return
|
||||
|
||||
@@ -236,7 +231,6 @@ class MessageAggregator:
|
||||
message_chain=merged_msg.message_chain,
|
||||
adapter=merged_msg.adapter,
|
||||
pipeline_uuid=merged_msg.pipeline_uuid,
|
||||
routed_by_rule=merged_msg.routed_by_rule,
|
||||
)
|
||||
|
||||
def _merge_messages(self, messages: list[PendingMessage]) -> PendingMessage:
|
||||
|
||||
@@ -63,14 +63,6 @@ class Controller:
|
||||
pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(pipeline_uuid)
|
||||
if pipeline:
|
||||
await pipeline.run(selected_query)
|
||||
else:
|
||||
self.ap.logger.warning(
|
||||
f'Pipeline {pipeline_uuid} not found for query {selected_query.query_id}, query dropped'
|
||||
)
|
||||
else:
|
||||
self.ap.logger.warning(
|
||||
f'No pipeline_uuid for query {selected_query.query_id}, query dropped'
|
||||
)
|
||||
|
||||
async with self.ap.query_pool:
|
||||
(await self.ap.sess_mgr.get_session(selected_query))._semaphore.release()
|
||||
|
||||
@@ -353,3 +353,62 @@ class LLMCallMonitor:
|
||||
)
|
||||
|
||||
return False # Don't suppress exceptions
|
||||
|
||||
|
||||
class FeedbackMonitor:
|
||||
"""Helper for recording user feedback from AI Bot conversations"""
|
||||
|
||||
@staticmethod
|
||||
async def record_feedback(
|
||||
ap: app.Application,
|
||||
feedback_id: str,
|
||||
feedback_type: int,
|
||||
feedback_content: str | None = None,
|
||||
inaccurate_reasons: list[str] | None = None,
|
||||
bot_id: str | None = None,
|
||||
bot_name: str | None = None,
|
||||
pipeline_id: str | None = None,
|
||||
pipeline_name: str | None = None,
|
||||
session_id: str | None = None,
|
||||
message_id: str | None = None,
|
||||
stream_id: str | None = None,
|
||||
user_id: str | None = None,
|
||||
platform: str = 'wecom',
|
||||
):
|
||||
"""Record user feedback (like/dislike) from AI Bot conversation.
|
||||
|
||||
Args:
|
||||
ap: Application instance
|
||||
feedback_id: Unique feedback identifier from platform
|
||||
feedback_type: 1 = like, 2 = dislike
|
||||
feedback_content: Optional user feedback text
|
||||
inaccurate_reasons: List of reasons for inaccurate response
|
||||
bot_id: Bot UUID
|
||||
bot_name: Bot name
|
||||
pipeline_id: Pipeline UUID
|
||||
pipeline_name: Pipeline name
|
||||
session_id: Session ID
|
||||
message_id: Message ID
|
||||
stream_id: Stream ID
|
||||
user_id: User ID
|
||||
platform: Platform name (default: wecom)
|
||||
"""
|
||||
try:
|
||||
await ap.monitoring_service.record_feedback(
|
||||
feedback_id=feedback_id,
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=feedback_content,
|
||||
inaccurate_reasons=inaccurate_reasons,
|
||||
bot_id=bot_id,
|
||||
bot_name=bot_name,
|
||||
pipeline_id=pipeline_id,
|
||||
pipeline_name=pipeline_name,
|
||||
session_id=session_id,
|
||||
message_id=message_id,
|
||||
stream_id=stream_id,
|
||||
user_id=user_id,
|
||||
platform=platform,
|
||||
)
|
||||
ap.logger.info(f'Recorded feedback: feedback_id={feedback_id}, type={feedback_type}')
|
||||
except Exception as e:
|
||||
ap.logger.error(f'Failed to record feedback: {e}')
|
||||
|
||||
@@ -297,9 +297,6 @@ class RuntimePipeline:
|
||||
)
|
||||
# Store message_id in query variables for LLM call monitoring
|
||||
query.variables['_monitoring_message_id'] = message_id
|
||||
# Notify adapter so it can map platform-specific IDs to monitoring message ID
|
||||
if hasattr(query.adapter, 'on_monitoring_message_created'):
|
||||
await query.adapter.on_monitoring_message_created(query, message_id)
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Failed to record query start: {e}')
|
||||
|
||||
@@ -326,9 +323,6 @@ class RuntimePipeline:
|
||||
event_ctx = await self.ap.plugin_connector.emit_event(event_obj, bound_plugins)
|
||||
|
||||
if event_ctx.is_prevented_default():
|
||||
self.ap.logger.debug(
|
||||
f'MessageReceived event prevented default for query {query.query_id}, pipeline={pipeline_name}'
|
||||
)
|
||||
return
|
||||
|
||||
self.ap.logger.debug(f'Processing query {query.query_id}')
|
||||
|
||||
@@ -41,7 +41,6 @@ class QueryPool:
|
||||
message_chain: platform_message.MessageChain,
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
|
||||
pipeline_uuid: typing.Optional[str] = None,
|
||||
routed_by_rule: bool = False,
|
||||
) -> pipeline_query.Query:
|
||||
async with self.condition:
|
||||
query_id = self.query_id_counter
|
||||
@@ -53,7 +52,7 @@ class QueryPool:
|
||||
sender_id=sender_id,
|
||||
message_event=message_event,
|
||||
message_chain=message_chain,
|
||||
variables={'_routed_by_rule': routed_by_rule},
|
||||
variables={},
|
||||
resp_messages=[],
|
||||
resp_message_chain=[],
|
||||
adapter=adapter,
|
||||
|
||||
@@ -160,6 +160,7 @@ class PreProcessor(stage.PipelineStage):
|
||||
elif me.url:
|
||||
content_list.append(provider_message.ContentElement.from_file_url(me.url, 'voice'))
|
||||
elif isinstance(me, platform_message.File):
|
||||
# if me.url is not None:
|
||||
content_list.append(provider_message.ContentElement.from_file_url(me.url, me.name))
|
||||
elif isinstance(me, platform_message.Quote) and quote_msg:
|
||||
for msg in me.origin:
|
||||
@@ -171,15 +172,6 @@ class PreProcessor(stage.PipelineStage):
|
||||
):
|
||||
if msg.base64 is not None:
|
||||
content_list.append(provider_message.ContentElement.from_image_base64(msg.base64))
|
||||
elif isinstance(msg, platform_message.File):
|
||||
content_list.append(provider_message.ContentElement.from_file_url(msg.url, msg.name))
|
||||
elif isinstance(msg, platform_message.Voice):
|
||||
if msg.base64:
|
||||
content_list.append(
|
||||
provider_message.ContentElement.from_file_base64(msg.base64, 'voice.silk')
|
||||
)
|
||||
elif msg.url:
|
||||
content_list.append(provider_message.ContentElement.from_file_url(msg.url, 'voice'))
|
||||
|
||||
query.variables['user_message_text'] = plain_text
|
||||
|
||||
|
||||
@@ -61,9 +61,6 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
|
||||
yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
else:
|
||||
self.ap.logger.debug(
|
||||
f'NormalMessageReceived event prevented default for query {query.query_id} without reply'
|
||||
)
|
||||
yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
|
||||
else:
|
||||
if event_ctx.event.user_message_alter is not None:
|
||||
@@ -208,7 +205,6 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
'model_name': model_name,
|
||||
'version': constants.semantic_version,
|
||||
'instance_id': constants.instance_id,
|
||||
'edition': constants.edition,
|
||||
'pipeline_plugins': pipeline_plugins,
|
||||
'error': locals().get('error_info', None),
|
||||
'timestamp': datetime.utcnow().isoformat(),
|
||||
|
||||
@@ -37,10 +37,6 @@ class GroupRespondRuleCheckStage(stage.PipelineStage):
|
||||
if query.launcher_type.value != 'group': # 只处理群消息
|
||||
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
|
||||
# 通过路由规则明确指定的流水线，跳过群响应规则检查
|
||||
if query.variables and query.variables.get('_routed_by_rule', False):
|
||||
return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
|
||||
|
||||
rules = query.pipeline_config['trigger']['group-respond-rules']
|
||||
|
||||
use_rule = rules
|
||||
|
||||
@@ -1,8 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import re
|
||||
import traceback
|
||||
import sqlalchemy
|
||||
|
||||
@@ -54,148 +52,6 @@ class RuntimeBot:
|
||||
self.task_context = taskmgr.TaskContext()
|
||||
self.logger = logger
|
||||
|
||||
@staticmethod
|
||||
def _match_operator(actual: str, operator: str, expected: str) -> bool:
|
||||
"""Evaluate a single operator condition."""
|
||||
if operator == 'eq':
|
||||
return actual == expected
|
||||
elif operator == 'neq':
|
||||
return actual != expected
|
||||
elif operator == 'contains':
|
||||
return expected in actual
|
||||
elif operator == 'not_contains':
|
||||
return expected not in actual
|
||||
elif operator == 'starts_with':
|
||||
return actual.startswith(expected)
|
||||
elif operator == 'regex':
|
||||
try:
|
||||
return bool(re.search(expected, actual))
|
||||
except re.error:
|
||||
return False
|
||||
return False
|
||||
|
||||
PIPELINE_DISCARD = '__discard__'
|
||||
PIPELINE_DISCARD_DISPLAY_NAME = 'Discarded'
|
||||
|
||||
def resolve_pipeline_uuid(
|
||||
self,
|
||||
launcher_type: str,
|
||||
launcher_id: str,
|
||||
message_text: str,
|
||||
message_element_types: list[str] | None = None,
|
||||
) -> tuple[str | None, bool]:
|
||||
"""Resolve pipeline UUID based on routing rules.
|
||||
|
||||
Rules are evaluated in order; first match wins.
|
||||
Falls back to use_pipeline_uuid if no rule matches.
|
||||
|
||||
Rule types:
|
||||
- launcher_type: session type ("person" / "group")
|
||||
- launcher_id: session / group id
|
||||
- message_content: message text content
|
||||
- message_has_element: message contains element of given type
|
||||
(Image, Voice, File, Forward, Face, At, AtAll, Quote)
|
||||
Operators: eq (has), neq (doesn't have)
|
||||
|
||||
Operators: eq, neq, contains, not_contains, starts_with, regex
|
||||
|
||||
When pipeline_uuid is ``__discard__``, the message should be
|
||||
silently dropped by the caller.
|
||||
|
||||
Returns:
|
||||
tuple: (pipeline_uuid, routed_by_rule) - routed_by_rule is True
|
||||
when a routing rule matched, False when falling back to default.
|
||||
"""
|
||||
rules = self.bot_entity.pipeline_routing_rules or []
|
||||
element_type_set = set(message_element_types or [])
|
||||
|
||||
for rule in rules:
|
||||
rule_type = rule.get('type')
|
||||
operator = rule.get('operator', 'eq')
|
||||
rule_value = rule.get('value', '')
|
||||
target_uuid = rule.get('pipeline_uuid')
|
||||
if not rule_type or not target_uuid:
|
||||
continue
|
||||
|
||||
if rule_type == 'launcher_type':
|
||||
if self._match_operator(launcher_type, operator, rule_value):
|
||||
return target_uuid, True
|
||||
elif rule_type == 'launcher_id':
|
||||
if self._match_operator(str(launcher_id), operator, str(rule_value)):
|
||||
return target_uuid, True
|
||||
elif rule_type == 'message_content':
|
||||
if self._match_operator(message_text, operator, rule_value):
|
||||
return target_uuid, True
|
||||
elif rule_type == 'message_has_element':
|
||||
has_element = rule_value in element_type_set
|
||||
if operator == 'eq' and has_element:
|
||||
return target_uuid, True
|
||||
elif operator == 'neq' and not has_element:
|
||||
return target_uuid, True
|
||||
|
||||
return self.bot_entity.use_pipeline_uuid, False
|
||||
|
||||
async def _record_discarded_message(
|
||||
self,
|
||||
launcher_type: provider_session.LauncherTypes,
|
||||
launcher_id: str | int,
|
||||
sender_id: str | int,
|
||||
message_event: platform_events.MessageEvent,
|
||||
message_chain: platform_message.MessageChain,
|
||||
) -> None:
|
||||
"""Record a discarded message in the monitoring system."""
|
||||
try:
|
||||
if hasattr(message_chain, 'model_dump'):
|
||||
message_content = json.dumps(message_chain.model_dump(), ensure_ascii=False)
|
||||
else:
|
||||
message_content = str(message_chain)
|
||||
|
||||
sender_name = None
|
||||
if hasattr(message_event, 'sender'):
|
||||
if hasattr(message_event.sender, 'nickname'):
|
||||
sender_name = message_event.sender.nickname
|
||||
elif hasattr(message_event.sender, 'member_name'):
|
||||
sender_name = message_event.sender.member_name
|
||||
|
||||
# Use the same session_id format as monitoring_helper.py
|
||||
session_id = f'{launcher_type}_{launcher_id}'
|
||||
platform = launcher_type.value if hasattr(launcher_type, 'value') else str(launcher_type)
|
||||
|
||||
await self.ap.monitoring_service.record_message(
|
||||
bot_id=self.bot_entity.uuid,
|
||||
bot_name=self.bot_entity.name or self.bot_entity.uuid,
|
||||
pipeline_id=self.PIPELINE_DISCARD,
|
||||
pipeline_name=self.PIPELINE_DISCARD_DISPLAY_NAME,
|
||||
message_content=message_content,
|
||||
session_id=session_id,
|
||||
status='discarded',
|
||||
level='info',
|
||||
platform=platform,
|
||||
user_id=str(sender_id),
|
||||
user_name=sender_name,
|
||||
)
|
||||
|
||||
# Ensure the session exists so the message appears in the session monitor.
|
||||
# Don't overwrite pipeline info — a session may have messages from
|
||||
# multiple pipelines; discarding shouldn't change the displayed pipeline.
|
||||
session_updated = await self.ap.monitoring_service.update_session_activity(
|
||||
session_id,
|
||||
)
|
||||
if not session_updated:
|
||||
# No session yet (first message for this launcher was discarded).
|
||||
await self.ap.monitoring_service.record_session_start(
|
||||
session_id=session_id,
|
||||
bot_id=self.bot_entity.uuid,
|
||||
bot_name=self.bot_entity.name or self.bot_entity.uuid,
|
||||
pipeline_id=self.PIPELINE_DISCARD,
|
||||
pipeline_name=self.PIPELINE_DISCARD_DISPLAY_NAME,
|
||||
platform=platform,
|
||||
user_id=str(sender_id),
|
||||
user_name=sender_name,
|
||||
)
|
||||
except Exception as e:
|
||||
await self.logger.error(f'Failed to record discarded message: {e}')
|
||||
|
||||
async def initialize(self):
|
||||
async def on_friend_message(
|
||||
event: platform_events.FriendMessage,
|
||||
@@ -227,23 +83,6 @@ class RuntimeBot:
|
||||
if custom_launcher_id:
|
||||
launcher_id = custom_launcher_id
|
||||
|
||||
message_text = str(event.message_chain)
|
||||
element_types = [comp.type for comp in event.message_chain]
|
||||
pipeline_uuid, routed_by_rule = self.resolve_pipeline_uuid(
|
||||
'person', launcher_id, message_text, element_types
|
||||
)
|
||||
|
||||
if pipeline_uuid == self.PIPELINE_DISCARD:
|
||||
await self.logger.info('Person message discarded by routing rule')
|
||||
await self._record_discarded_message(
|
||||
provider_session.LauncherTypes.PERSON,
|
||||
launcher_id,
|
||||
event.sender.id,
|
||||
event,
|
||||
event.message_chain,
|
||||
)
|
||||
return
|
||||
|
||||
await self.ap.msg_aggregator.add_message(
|
||||
bot_uuid=self.bot_entity.uuid,
|
||||
launcher_type=provider_session.LauncherTypes.PERSON,
|
||||
@@ -252,8 +91,7 @@ class RuntimeBot:
|
||||
message_event=event,
|
||||
message_chain=event.message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
routed_by_rule=routed_by_rule,
|
||||
pipeline_uuid=self.bot_entity.use_pipeline_uuid,
|
||||
)
|
||||
else:
|
||||
await self.logger.info('Pipeline skipped for person message due to webhook response')
|
||||
@@ -288,23 +126,6 @@ class RuntimeBot:
|
||||
if custom_launcher_id:
|
||||
launcher_id = custom_launcher_id
|
||||
|
||||
message_text = str(event.message_chain)
|
||||
element_types = [comp.type for comp in event.message_chain]
|
||||
pipeline_uuid, routed_by_rule = self.resolve_pipeline_uuid(
|
||||
'group', launcher_id, message_text, element_types
|
||||
)
|
||||
|
||||
if pipeline_uuid == self.PIPELINE_DISCARD:
|
||||
await self.logger.info('Group message discarded by routing rule')
|
||||
await self._record_discarded_message(
|
||||
provider_session.LauncherTypes.GROUP,
|
||||
launcher_id,
|
||||
event.sender.id,
|
||||
event,
|
||||
event.message_chain,
|
||||
)
|
||||
return
|
||||
|
||||
await self.ap.msg_aggregator.add_message(
|
||||
bot_uuid=self.bot_entity.uuid,
|
||||
launcher_type=provider_session.LauncherTypes.GROUP,
|
||||
@@ -313,8 +134,7 @@ class RuntimeBot:
|
||||
message_event=event,
|
||||
message_chain=event.message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
routed_by_rule=routed_by_rule,
|
||||
pipeline_uuid=self.bot_entity.use_pipeline_uuid,
|
||||
)
|
||||
else:
|
||||
await self.logger.info('Pipeline skipped for group message due to webhook response')
|
||||
@@ -322,50 +142,6 @@ class RuntimeBot:
|
||||
self.adapter.register_listener(platform_events.FriendMessage, on_friend_message)
|
||||
self.adapter.register_listener(platform_events.GroupMessage, on_group_message)
|
||||
|
||||
# Register feedback listener (only effective on adapters that support it)
|
||||
async def on_feedback(
|
||||
event: platform_events.FeedbackEvent,
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
|
||||
):
|
||||
try:
|
||||
# Resolve pipeline name
|
||||
pipeline_name = ''
|
||||
if self.bot_entity.use_pipeline_uuid:
|
||||
try:
|
||||
pipeline_result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_pipeline.LegacyPipeline.name).where(
|
||||
persistence_pipeline.LegacyPipeline.uuid == self.bot_entity.use_pipeline_uuid
|
||||
)
|
||||
)
|
||||
pipeline_row = pipeline_result.first()
|
||||
if pipeline_row:
|
||||
pipeline_name = pipeline_row[0]
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
await self.ap.monitoring_service.record_feedback(
|
||||
feedback_id=event.feedback_id,
|
||||
feedback_type=event.feedback_type,
|
||||
feedback_content=event.feedback_content,
|
||||
inaccurate_reasons=event.inaccurate_reasons,
|
||||
bot_id=self.bot_entity.uuid,
|
||||
bot_name=self.bot_entity.name,
|
||||
pipeline_id=self.bot_entity.use_pipeline_uuid or '',
|
||||
pipeline_name=pipeline_name,
|
||||
session_id=event.session_id,
|
||||
message_id=event.message_id,
|
||||
stream_id=event.stream_id,
|
||||
user_id=event.user_id,
|
||||
platform=adapter.__class__.__name__,
|
||||
)
|
||||
await self.logger.info(
|
||||
f'Recorded feedback: feedback_id={event.feedback_id}, type={event.feedback_type}'
|
||||
)
|
||||
except Exception:
|
||||
await self.logger.error(f'Failed to record feedback: {traceback.format_exc()}')
|
||||
|
||||
self.adapter.register_listener(platform_events.FeedbackEvent, on_feedback)
|
||||
|
||||
async def run(self):
|
||||
async def exception_wrapper():
|
||||
try:
|
||||
@@ -421,20 +197,12 @@ class PlatformManager:
|
||||
# delete all bot log images
|
||||
await self.ap.storage_mgr.storage_provider.delete_dir_recursive('bot_log_images')
|
||||
|
||||
disabled_adapters = self.ap.instance_config.data.get('system', {}).get('disabled_adapters', []) or []
|
||||
|
||||
self.adapter_components = self.ap.discover.get_components_by_kind('MessagePlatformAdapter')
|
||||
adapter_dict: dict[str, type[abstract_platform_adapter.AbstractMessagePlatformAdapter]] = {}
|
||||
for component in self.adapter_components:
|
||||
if component.metadata.name in disabled_adapters:
|
||||
continue
|
||||
adapter_dict[component.metadata.name] = component.get_python_component_class()
|
||||
self.adapter_dict = adapter_dict
|
||||
|
||||
# Filter out disabled adapters from components list (for API responses)
|
||||
if disabled_adapters:
|
||||
self.adapter_components = [c for c in self.adapter_components if c.metadata.name not in disabled_adapters]
|
||||
|
||||
# initialize websocket adapter
|
||||
websocket_adapter_class = self.adapter_dict['websocket']
|
||||
websocket_logger = EventLogger(name='websocket-adapter', ap=self.ap)
|
||||
@@ -500,12 +268,35 @@ class PlatformManager:
|
||||
adapter_inst = self.adapter_dict[bot_entity.adapter](
|
||||
bot_entity.adapter_config,
|
||||
logger,
|
||||
ap=self.ap,
|
||||
)
|
||||
|
||||
# 如果 adapter 支持 set_bot_uuid 方法，设置 bot_uuid（用于统一 webhook）
|
||||
if hasattr(adapter_inst, 'set_bot_uuid'):
|
||||
adapter_inst.set_bot_uuid(bot_entity.uuid)
|
||||
|
||||
# 如果 adapter 支持 set_bot_info 方法，设置 bot 信息（用于监控记录）
|
||||
if hasattr(adapter_inst, 'set_bot_info'):
|
||||
pipeline_name = ''
|
||||
if bot_entity.use_pipeline_uuid:
|
||||
try:
|
||||
pipeline_result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_pipeline.LegacyPipeline.name).where(
|
||||
persistence_pipeline.LegacyPipeline.uuid == bot_entity.use_pipeline_uuid
|
||||
)
|
||||
)
|
||||
pipeline_row = pipeline_result.first()
|
||||
if pipeline_row:
|
||||
pipeline_name = pipeline_row[0]
|
||||
except Exception:
|
||||
pass
|
||||
adapter_inst.set_bot_info(
|
||||
bot_id=bot_entity.uuid,
|
||||
bot_name=bot_entity.name,
|
||||
pipeline_id=bot_entity.use_pipeline_uuid or '',
|
||||
pipeline_name=pipeline_name,
|
||||
)
|
||||
|
||||
runtime_bot = RuntimeBot(ap=self.ap, bot_entity=bot_entity, adapter=adapter_inst, logger=logger)
|
||||
|
||||
await runtime_bot.initialize()
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- protocol
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/aiocqhttp
|
||||
en: https://link.langbot.app/en/platforms/aiocqhttp
|
||||
ja: https://link.langbot.app/ja/platforms/aiocqhttp
|
||||
config:
|
||||
- name: host
|
||||
label:
|
||||
|
||||
@@ -71,8 +71,7 @@ class DingTalkMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
yiri_msg_list.append(platform_message.Image(base64=element['Picture']))
|
||||
else:
|
||||
# 回退到原有简单逻辑
|
||||
# 对于音频消息，content 来自 recognition 转写文字，在下方音频处理块中统一处理
|
||||
if event.content and event.type != 'audio':
|
||||
if event.content:
|
||||
text_content = event.content.replace('@' + bot_name, '')
|
||||
yiri_msg_list.append(platform_message.Plain(text=text_content))
|
||||
if event.picture:
|
||||
@@ -82,38 +81,7 @@ class DingTalkMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
if event.file:
|
||||
yiri_msg_list.append(platform_message.File(url=event.file, name=event.name))
|
||||
if event.audio:
|
||||
# 优先使用钉钉自带的语音转写文字（recognition字段）
|
||||
if event.content and event.type == 'audio':
|
||||
yiri_msg_list.append(platform_message.Plain(text=event.content))
|
||||
else:
|
||||
yiri_msg_list.append(platform_message.Voice(base64=event.audio))
|
||||
|
||||
# Handle quoted/replied message - extract content as top-level components
|
||||
# so that plugins like FileReader can process them the same way as direct messages
|
||||
if event.quoted_message:
|
||||
quote_info = event.quoted_message
|
||||
msg_type = quote_info.get('msg_type', '')
|
||||
|
||||
# Process quoted file - add as top-level File component (same as private chat)
|
||||
if msg_type == 'file' and quote_info.get('file_url'):
|
||||
file_name = quote_info.get('file_name', 'file')
|
||||
yiri_msg_list.append(platform_message.File(url=quote_info['file_url'], name=file_name))
|
||||
|
||||
# Process quoted image - add as top-level Image component
|
||||
elif msg_type == 'picture' and quote_info.get('picture'):
|
||||
yiri_msg_list.append(platform_message.Image(base64=quote_info['picture']))
|
||||
|
||||
# Process quoted audio - add as top-level Voice component
|
||||
elif msg_type == 'audio' and quote_info.get('audio'):
|
||||
yiri_msg_list.append(platform_message.Voice(base64=quote_info['audio']))
|
||||
|
||||
# Process quoted text - add as Plain text with context prefix
|
||||
elif msg_type == 'text' and quote_info.get('content'):
|
||||
yiri_msg_list.append(platform_message.Plain(text=f'[引用消息] {quote_info["content"]}'))
|
||||
|
||||
# Process quoted rich text - add as Plain text with context prefix
|
||||
elif msg_type == 'richText' and quote_info.get('content'):
|
||||
yiri_msg_list.append(platform_message.Plain(text=f'[引用消息] {quote_info["content"]}'))
|
||||
yiri_msg_list.append(platform_message.Voice(base64=event.audio))
|
||||
|
||||
chain = platform_message.MessageChain(yiri_msg_list)
|
||||
|
||||
@@ -171,7 +139,7 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
dict # 回复卡片消息字典，key为消息id，value为回复卡片实例id，用于在流式消息时判断是否发送到指定卡片
|
||||
)
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
required_keys = [
|
||||
'client_id',
|
||||
'client_secret',
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/dingtalk
|
||||
en: https://link.langbot.app/en/platforms/dingtalk
|
||||
ja: https://link.langbot.app/ja/platforms/dingtalk
|
||||
config:
|
||||
- name: client_id
|
||||
label:
|
||||
|
||||
@@ -23,10 +23,6 @@ spec:
|
||||
categories:
|
||||
- popular
|
||||
- global
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/discord
|
||||
en: https://link.langbot.app/en/platforms/discord
|
||||
ja: https://link.langbot.app/ja/platforms/discord
|
||||
config:
|
||||
- name: client_id
|
||||
label:
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/kook
|
||||
en: https://link.langbot.app/en/platforms/kook
|
||||
ja: https://link.langbot.app/ja/platforms/kook
|
||||
config:
|
||||
- name: token
|
||||
label:
|
||||
|
||||
@@ -709,29 +709,21 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
|
||||
message_chain = await LarkMessageConverter.target2yiri(event.event.message, api_client)
|
||||
|
||||
# Check for quote/reply message
|
||||
# Extract files/images/voice from quote and add them as top-level components
|
||||
# so that plugins like FileReader can process them the same way as direct messages
|
||||
quote_message_id = LarkEventConverter._extract_quote_message_id(event.event.message)
|
||||
if quote_message_id:
|
||||
quote_chain = await LarkEventConverter._fetch_quoted_message(quote_message_id, api_client)
|
||||
if quote_chain:
|
||||
# Filter out Source component from quoted chain, keep only content
|
||||
quote_components = [comp for comp in quote_chain if not isinstance(comp, platform_message.Source)]
|
||||
|
||||
# Add quoted content as top-level components instead of wrapping in Quote
|
||||
for comp in quote_components:
|
||||
if isinstance(comp, platform_message.File):
|
||||
# Add file as top-level component (same as direct message)
|
||||
message_chain.append(comp)
|
||||
elif isinstance(comp, platform_message.Image):
|
||||
# Add image as top-level component
|
||||
message_chain.append(comp)
|
||||
elif isinstance(comp, platform_message.Voice):
|
||||
# Add voice as top-level component
|
||||
message_chain.append(comp)
|
||||
elif isinstance(comp, platform_message.Plain):
|
||||
# Add text with context prefix
|
||||
message_chain.append(platform_message.Plain(text=f'[引用消息] {comp.text}'))
|
||||
quote_origin = platform_message.MessageChain(
|
||||
[comp for comp in quote_chain if not isinstance(comp, platform_message.Source)]
|
||||
)
|
||||
if quote_origin:
|
||||
message_chain.append(
|
||||
platform_message.Quote(
|
||||
message_id=quote_message_id,
|
||||
origin=quote_origin,
|
||||
)
|
||||
)
|
||||
|
||||
if event.event.message.chat_type == 'p2p':
|
||||
return platform_events.FriendMessage(
|
||||
@@ -787,13 +779,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
card_id_dict: dict[str, str] # 消息id到卡片id的映射，便于创建卡片后的发送消息到指定卡片
|
||||
|
||||
# Monitoring message ID mapping for feedback correlation
|
||||
# Temp: user Lark message ID → monitoring_message_id (populated by on_monitoring_message_created, consumed by create_message_card)
|
||||
pending_monitoring_msg: dict[str, str]
|
||||
# Final: reply Lark message ID → (monitoring_message_id, timestamp) (used by feedback callbacks)
|
||||
reply_to_monitoring_msg: dict[str, tuple[str, float]]
|
||||
_MONITORING_MAPPING_TTL = 600 # 10 minutes
|
||||
|
||||
seq: int # 用于在发送卡片消息中识别消息顺序，直接以seq作为标识
|
||||
bot_uuid: str = None # 机器人UUID
|
||||
app_ticket: str = None # 商店应用用到
|
||||
@@ -812,71 +797,8 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
def sync_on_message(event: lark_oapi.im.v1.P2ImMessageReceiveV1):
|
||||
asyncio.create_task(on_message(event))
|
||||
|
||||
def sync_on_card_action(event):
|
||||
try:
|
||||
action_value_obj = getattr(getattr(event.event, 'action', None), 'value', {})
|
||||
action_value = action_value_obj.get('feedback', '') if isinstance(action_value_obj, dict) else ''
|
||||
|
||||
if action_value == '有帮助':
|
||||
feedback_type = 1
|
||||
elif action_value == '无帮助':
|
||||
feedback_type = 2
|
||||
else:
|
||||
from lark_oapi.event.callback.model.p2_card_action_trigger import P2CardActionTriggerResponse
|
||||
|
||||
return P2CardActionTriggerResponse({'toast': {'type': 'success', 'content': '操作成功'}})
|
||||
|
||||
operator = getattr(event.event, 'operator', None)
|
||||
context = getattr(event.event, 'context', None)
|
||||
|
||||
user_id = getattr(operator, 'open_id', None) or getattr(operator, 'user_id', None)
|
||||
open_chat_id = getattr(context, 'open_chat_id', None)
|
||||
open_message_id = getattr(context, 'open_message_id', None)
|
||||
|
||||
if open_chat_id:
|
||||
session_id = f'group_{open_chat_id}'
|
||||
elif user_id:
|
||||
session_id = f'person_{user_id}'
|
||||
else:
|
||||
session_id = None
|
||||
|
||||
# Resolve monitoring message ID from reply message mapping
|
||||
monitoring_msg_id = None
|
||||
if open_message_id and open_message_id in self.reply_to_monitoring_msg:
|
||||
monitoring_msg_id = self.reply_to_monitoring_msg[open_message_id][0]
|
||||
|
||||
feedback_event = platform_events.FeedbackEvent(
|
||||
feedback_id=getattr(event.header, 'event_id', str(uuid.uuid4())),
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=action_value,
|
||||
user_id=user_id,
|
||||
session_id=session_id,
|
||||
message_id=open_message_id,
|
||||
stream_id=monitoring_msg_id,
|
||||
source_platform_object=event,
|
||||
)
|
||||
|
||||
if platform_events.FeedbackEvent in self.listeners:
|
||||
loop = asyncio.get_event_loop()
|
||||
if loop.is_running():
|
||||
asyncio.create_task(self.listeners[platform_events.FeedbackEvent](feedback_event, self))
|
||||
else:
|
||||
loop.run_until_complete(self.listeners[platform_events.FeedbackEvent](feedback_event, self))
|
||||
|
||||
from lark_oapi.event.callback.model.p2_card_action_trigger import P2CardActionTriggerResponse
|
||||
|
||||
return P2CardActionTriggerResponse({'toast': {'type': 'success', 'content': '感谢您的反馈'}})
|
||||
except Exception:
|
||||
asyncio.create_task(self.logger.error(f'Error in lark card action callback: {traceback.format_exc()}'))
|
||||
from lark_oapi.event.callback.model.p2_card_action_trigger import P2CardActionTriggerResponse
|
||||
|
||||
return P2CardActionTriggerResponse({'toast': {'type': 'error', 'content': '反馈处理失败'}})
|
||||
|
||||
event_handler = (
|
||||
lark_oapi.EventDispatcherHandler.builder('', '')
|
||||
.register_p2_im_message_receive_v1(sync_on_message)
|
||||
.register_p2_card_action_trigger(sync_on_card_action)
|
||||
.build()
|
||||
lark_oapi.EventDispatcherHandler.builder('', '').register_p2_im_message_receive_v1(sync_on_message).build()
|
||||
)
|
||||
|
||||
bot_account_id = config['bot_name']
|
||||
@@ -891,8 +813,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
logger=logger,
|
||||
lark_tenant_key=config.get('lark_tenant_key', ''),
|
||||
card_id_dict={},
|
||||
pending_monitoring_msg={},
|
||||
reply_to_monitoring_msg={},
|
||||
seq=1,
|
||||
listeners={},
|
||||
quart_app=quart_app,
|
||||
@@ -1033,22 +953,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
is_stream = True
|
||||
return is_stream
|
||||
|
||||
async def on_monitoring_message_created(self, query, monitoring_message_id: str):
|
||||
"""Called by pipeline after monitoring message is created, to map user message ID to monitoring message ID."""
|
||||
try:
|
||||
user_msg_id = query.message_event.message_chain.message_id
|
||||
if user_msg_id:
|
||||
self.pending_monitoring_msg[user_msg_id] = monitoring_message_id
|
||||
except Exception as e:
|
||||
await self.logger.debug(f'Failed to map message to monitoring message: {e}')
|
||||
|
||||
def _cleanup_monitoring_mapping(self):
|
||||
"""Remove entries older than TTL from the reply-to-monitoring mapping."""
|
||||
now = time.time()
|
||||
expired = [k for k, (_, ts) in self.reply_to_monitoring_msg.items() if now - ts > self._MONITORING_MAPPING_TTL]
|
||||
for k in expired:
|
||||
del self.reply_to_monitoring_msg[k]
|
||||
|
||||
async def create_card_id(self, message_id):
|
||||
try:
|
||||
# self.logger.debug('飞书支持stream输出,创建卡片......')
|
||||
@@ -1184,7 +1088,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
'size': 'medium',
|
||||
'icon': {'tag': 'standard_icon', 'token': 'thumbsup_outlined'},
|
||||
'hover_tips': {'tag': 'plain_text', 'content': '有帮助'},
|
||||
'behaviors': [{'type': 'callback', 'value': {'feedback': '有帮助'}}],
|
||||
'margin': '0px 0px 0px 0px',
|
||||
}
|
||||
],
|
||||
@@ -1208,7 +1111,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
'size': 'medium',
|
||||
'icon': {'tag': 'standard_icon', 'token': 'thumbdown_outlined'},
|
||||
'hover_tips': {'tag': 'plain_text', 'content': '无帮助'},
|
||||
'behaviors': [{'type': 'callback', 'value': {'feedback': '无帮助'}}],
|
||||
'margin': '0px 0px 0px 0px',
|
||||
}
|
||||
],
|
||||
@@ -1288,18 +1190,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
raise Exception(
|
||||
f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
|
||||
)
|
||||
|
||||
# Transfer monitoring message mapping: user msg ID → reply msg ID
|
||||
try:
|
||||
user_msg_id = event.message_chain.message_id
|
||||
reply_msg_id = getattr(response.data, 'message_id', None)
|
||||
monitoring_msg_id = self.pending_monitoring_msg.pop(user_msg_id, None)
|
||||
if reply_msg_id and monitoring_msg_id:
|
||||
self.reply_to_monitoring_msg[reply_msg_id] = (monitoring_msg_id, time.time())
|
||||
self._cleanup_monitoring_mapping()
|
||||
except Exception as e:
|
||||
asyncio.create_task(self.logger.debug(f'Failed to transfer monitoring mapping in create_message_card: {e}'))
|
||||
|
||||
return True
|
||||
|
||||
async def reply_message(
|
||||
@@ -1582,58 +1472,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
if event.__class__ in self.listeners:
|
||||
await self.listeners[event.__class__](event, self)
|
||||
elif 'card.action.trigger' == type:
|
||||
try:
|
||||
event_data = data.get('event', {})
|
||||
operator = event_data.get('operator', {})
|
||||
action = event_data.get('action', {})
|
||||
context_data = event_data.get('context', {})
|
||||
|
||||
action_value_obj = action.get('value', {})
|
||||
action_value = action_value_obj.get('feedback', '') if isinstance(action_value_obj, dict) else ''
|
||||
|
||||
if action_value == '有帮助':
|
||||
feedback_type = 1
|
||||
elif action_value == '无帮助':
|
||||
feedback_type = 2
|
||||
else:
|
||||
return {'toast': {'type': 'success', 'content': '操作成功'}}
|
||||
|
||||
user_id = operator.get('open_id') or operator.get('user_id')
|
||||
open_chat_id = context_data.get('open_chat_id')
|
||||
open_message_id = context_data.get('open_message_id')
|
||||
|
||||
if open_chat_id:
|
||||
session_id = f'group_{open_chat_id}'
|
||||
elif user_id:
|
||||
session_id = f'person_{user_id}'
|
||||
else:
|
||||
session_id = None
|
||||
|
||||
# Resolve monitoring message ID from reply message mapping
|
||||
monitoring_msg_id = None
|
||||
if open_message_id and open_message_id in self.reply_to_monitoring_msg:
|
||||
monitoring_msg_id = self.reply_to_monitoring_msg[open_message_id][0]
|
||||
|
||||
feedback_event = platform_events.FeedbackEvent(
|
||||
feedback_id=data.get('header', {}).get('event_id', str(uuid.uuid4())),
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=action_value,
|
||||
user_id=user_id,
|
||||
session_id=session_id,
|
||||
message_id=open_message_id,
|
||||
stream_id=monitoring_msg_id,
|
||||
source_platform_object=data,
|
||||
)
|
||||
|
||||
if platform_events.FeedbackEvent in self.listeners:
|
||||
await self.listeners[platform_events.FeedbackEvent](feedback_event, self)
|
||||
|
||||
return {'toast': {'type': 'success', 'content': '感谢您的反馈'}}
|
||||
except Exception:
|
||||
await self.logger.error(f'Error in lark card action callback: {traceback.format_exc()}')
|
||||
return {'toast': {'type': 'error', 'content': '反馈处理失败'}}
|
||||
|
||||
elif 'im.chat.member.bot.added_v1' == type:
|
||||
try:
|
||||
bot_added_welcome_msg = self.config.get('bot_added_welcome', '')
|
||||
|
||||
@@ -18,10 +18,6 @@ spec:
|
||||
- popular
|
||||
- china
|
||||
- global
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/lark
|
||||
en: https://link.langbot.app/en/platforms/lark
|
||||
ja: https://link.langbot.app/ja/platforms/lark
|
||||
config:
|
||||
- name: app_id
|
||||
label:
|
||||
|
||||
@@ -136,7 +136,7 @@ class LINEAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
seq: int # 用于在发送卡片消息中识别消息顺序，直接以seq作为标识
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
configuration = Configuration(access_token=config['channel_access_token'])
|
||||
line_webhook = WebhookHandler(config['channel_secret'])
|
||||
parser = WebhookParser(config['channel_secret'])
|
||||
|
||||
@@ -21,10 +21,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- global
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/line
|
||||
en: https://link.langbot.app/en/platforms/line
|
||||
ja: https://link.langbot.app/ja/platforms/line
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -60,7 +60,7 @@ class OfficialAccountAdapter(abstract_platform_adapter.AbstractMessagePlatformAd
|
||||
bot: typing.Union[OAClient, OAClientForLongerResponse] = pydantic.Field(exclude=True)
|
||||
bot_uuid: str = None
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
# 校验必填项
|
||||
required_keys = ['token', 'EncodingAESKey', 'AppSecret', 'AppID', 'Mode']
|
||||
missing_keys = [k for k in required_keys if k not in config]
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/officialaccount
|
||||
en: https://link.langbot.app/en/platforms/officialaccount
|
||||
ja: https://link.langbot.app/ja/platforms/officialaccount
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -15,10 +15,6 @@ spec:
|
||||
categories:
|
||||
- popular
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/openclaw_weixin
|
||||
en: https://link.langbot.app/en/platforms/openclaw_weixin
|
||||
ja: https://link.langbot.app/ja/platforms/openclaw_weixin
|
||||
config:
|
||||
- name: base_url
|
||||
label:
|
||||
|
||||
@@ -132,7 +132,7 @@ class QQOfficialAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter
|
||||
message_converter: QQOfficialMessageConverter = QQOfficialMessageConverter()
|
||||
event_converter: QQOfficialEventConverter = QQOfficialEventConverter()
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
bot = QQOfficialClient(
|
||||
app_id=config['appid'], secret=config['secret'], token=config['token'], logger=logger, unified_mode=True
|
||||
)
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/qqofficial
|
||||
en: https://link.langbot.app/en/platforms/qqofficial
|
||||
ja: https://link.langbot.app/ja/platforms/qqofficial
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -20,10 +20,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- protocol
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/satori
|
||||
en: https://link.langbot.app/en/platforms/satori
|
||||
ja: https://link.langbot.app/ja/platforms/satori
|
||||
config:
|
||||
- name: platform
|
||||
label:
|
||||
|
||||
@@ -99,7 +99,7 @@ class SlackAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
event_converter: SlackEventConverter = SlackEventConverter()
|
||||
config: dict
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
required_keys = [
|
||||
'bot_token',
|
||||
'signing_secret',
|
||||
|
||||
@@ -23,10 +23,6 @@ spec:
|
||||
categories:
|
||||
- popular
|
||||
- global
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/slack
|
||||
en: https://link.langbot.app/en/platforms/slack
|
||||
ja: https://link.langbot.app/ja/platforms/slack
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -23,10 +23,6 @@ spec:
|
||||
categories:
|
||||
- popular
|
||||
- global
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/telegram
|
||||
en: https://link.langbot.app/en/platforms/telegram
|
||||
ja: https://link.langbot.app/ja/platforms/telegram
|
||||
config:
|
||||
- name: token
|
||||
label:
|
||||
|
||||
@@ -539,7 +539,7 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
|
||||
typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
|
||||
] = {}
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
quart_app = quart.Quart(__name__)
|
||||
|
||||
message_converter = WeChatPadMessageConverter(config, logger)
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/wechatpad
|
||||
en: https://link.langbot.app/en/platforms/wechatpad
|
||||
ja: https://link.langbot.app/ja/platforms/wechatpad
|
||||
config:
|
||||
- name: wechatpad_url
|
||||
label:
|
||||
|
||||
@@ -206,7 +206,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
config: dict
|
||||
bot_uuid: str = None
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
|
||||
# 校验必填项
|
||||
required_keys = [
|
||||
'corpid',
|
||||
|
||||
@@ -15,10 +15,6 @@ spec:
|
||||
categories:
|
||||
- popular
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/wecom
|
||||
en: https://link.langbot.app/en/platforms/wecom
|
||||
ja: https://link.langbot.app/ja/platforms/wecom
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
from __future__ import annotations
|
||||
import typing
|
||||
import asyncio
|
||||
import time
|
||||
import traceback
|
||||
|
||||
import datetime
|
||||
@@ -11,8 +10,10 @@ import langbot_plugin.api.entities.builtin.platform.events as platform_events
|
||||
import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
|
||||
from ..logger import EventLogger
|
||||
from langbot.libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
|
||||
from langbot.libs.wecom_ai_bot_api.api import WecomBotClient
|
||||
from langbot.libs.wecom_ai_bot_api.api import WecomBotClient, StreamSession
|
||||
from langbot.libs.wecom_ai_bot_api.ws_client import WecomBotWsClient
|
||||
from ...core import app as langbot_app
|
||||
from ...pipeline.monitoring_helper import FeedbackMonitor
|
||||
|
||||
|
||||
class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
@@ -127,107 +128,6 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
if summary:
|
||||
yiri_msg_list.append(platform_message.Plain(text=summary))
|
||||
|
||||
# Handle quoted message (引用消息) - important for group chat file references
|
||||
# Extract files/images/voice from quote and add them as top-level components
|
||||
# so that plugins like FileReader can process them the same way as direct messages
|
||||
quote_info = event.quote or {}
|
||||
if quote_info:
|
||||
# Process quote text content - add as Plain for context
|
||||
if quote_info.get('content'):
|
||||
yiri_msg_list.append(platform_message.Plain(text=f'[引用消息] {quote_info.get("content")}'))
|
||||
|
||||
# Process quote images - add as top-level Image components
|
||||
quote_images = quote_info.get('images', [])
|
||||
if not quote_images and quote_info.get('picurl'):
|
||||
quote_images = [quote_info.get('picurl')]
|
||||
for img_data in quote_images:
|
||||
if img_data:
|
||||
yiri_msg_list.append(platform_message.Image(base64=img_data))
|
||||
|
||||
# Process quote file - add as top-level File component (same as private chat)
|
||||
quote_file = quote_info.get('file') or {}
|
||||
if quote_file:
|
||||
file_url = (
|
||||
quote_file.get('base64')
|
||||
or quote_file.get('download_url')
|
||||
or quote_file.get('url')
|
||||
or quote_file.get('fileurl')
|
||||
)
|
||||
file_name = quote_file.get('filename') or quote_file.get('name')
|
||||
file_size = quote_file.get('filesize') or quote_file.get('size')
|
||||
if file_url or file_name:
|
||||
file_kwargs = {}
|
||||
if file_url:
|
||||
file_kwargs['url'] = file_url
|
||||
if file_name:
|
||||
file_kwargs['name'] = file_name
|
||||
if file_size is not None:
|
||||
file_kwargs['size'] = file_size
|
||||
try:
|
||||
yiri_msg_list.append(platform_message.File(**file_kwargs))
|
||||
except Exception:
|
||||
yiri_msg_list.append(platform_message.Unknown(text='[quoted file unsupported]'))
|
||||
|
||||
# Process quote voice - add as top-level Voice/File component
|
||||
quote_voice = quote_info.get('voice') or {}
|
||||
if quote_voice:
|
||||
voice_payload = quote_voice.get('base64') or quote_voice.get('url')
|
||||
if voice_payload:
|
||||
if quote_voice.get('base64') and not voice_payload.startswith('data:'):
|
||||
voice_payload = f'data:audio/mpeg;base64,{quote_voice.get("base64")}'
|
||||
try:
|
||||
yiri_msg_list.append(platform_message.Voice(base64=voice_payload))
|
||||
except Exception:
|
||||
try:
|
||||
voice_kwargs = {'url': voice_payload}
|
||||
voice_name = quote_voice.get('filename') or quote_voice.get('name')
|
||||
voice_size = quote_voice.get('filesize') or quote_voice.get('size')
|
||||
if voice_name:
|
||||
voice_kwargs['name'] = voice_name
|
||||
if voice_size is not None:
|
||||
voice_kwargs['size'] = voice_size
|
||||
yiri_msg_list.append(platform_message.File(**voice_kwargs))
|
||||
except Exception:
|
||||
yiri_msg_list.append(platform_message.Unknown(text='[quoted voice unsupported]'))
|
||||
|
||||
# Process quote video - add as top-level File component
|
||||
quote_video = quote_info.get('video') or {}
|
||||
if quote_video:
|
||||
video_payload = (
|
||||
quote_video.get('base64')
|
||||
or quote_video.get('url')
|
||||
or quote_video.get('download_url')
|
||||
or quote_video.get('fileurl')
|
||||
)
|
||||
if video_payload:
|
||||
video_kwargs = {'url': video_payload}
|
||||
video_name = quote_video.get('filename') or quote_video.get('name')
|
||||
video_size = quote_video.get('filesize') or quote_video.get('size')
|
||||
if video_name:
|
||||
video_kwargs['name'] = video_name
|
||||
if video_size is not None:
|
||||
video_kwargs['size'] = video_size
|
||||
try:
|
||||
yiri_msg_list.append(platform_message.File(**video_kwargs))
|
||||
except Exception:
|
||||
yiri_msg_list.append(platform_message.Unknown(text='[quoted video unsupported]'))
|
||||
|
||||
# Process quote link - add as Plain text
|
||||
quote_link = quote_info.get('link') or {}
|
||||
if quote_link:
|
||||
link_summary = '\n'.join(
|
||||
filter(
|
||||
None,
|
||||
[
|
||||
quote_link.get('title', ''),
|
||||
quote_link.get('description') or quote_link.get('digest', ''),
|
||||
quote_link.get('url', ''),
|
||||
],
|
||||
)
|
||||
)
|
||||
if link_summary:
|
||||
yiri_msg_list.append(platform_message.Plain(text=f'[引用链接] {link_summary}'))
|
||||
|
||||
has_content_element = any(
|
||||
not isinstance(element, (platform_message.Source, platform_message.At)) for element in yiri_msg_list
|
||||
)
|
||||
@@ -294,10 +194,10 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
_ws_mode: bool = False
|
||||
bot_name: str = ''
|
||||
listeners: dict = {}
|
||||
_stream_to_monitoring_msg: dict = {} # Maps stream_id to (monitoring_message_id, timestamp)
|
||||
_STREAM_MAPPING_TTL = 600 # 10 minutes
|
||||
ap: langbot_app.Application = None # Application reference for monitoring
|
||||
_bot_info: dict = None # Bot info for monitoring (bot_id, bot_name, pipeline_id, pipeline_name)
|
||||
|
||||
def __init__(self, config: dict, logger: EventLogger):
|
||||
def __init__(self, config: dict, logger: EventLogger, ap: langbot_app.Application = None, **kwargs):
|
||||
enable_webhook = config.get('enable-webhook', False)
|
||||
bot_name = config.get('robot_name', '')
|
||||
|
||||
@@ -332,9 +232,14 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
bot_account_id=bot_account_id,
|
||||
bot_name=bot_name,
|
||||
event_converter=event_converter,
|
||||
listeners={},
|
||||
_stream_to_monitoring_msg={},
|
||||
**kwargs,
|
||||
)
|
||||
self.listeners = {}
|
||||
object.__setattr__(self, '_ws_mode', ws_mode)
|
||||
object.__setattr__(self, 'ap', ap)
|
||||
|
||||
# Register feedback handler for monitoring
|
||||
self._register_feedback_handler()
|
||||
|
||||
async def reply_message(
|
||||
self,
|
||||
@@ -416,9 +321,6 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
self.bot.on_message('single')(self.on_message)
|
||||
elif event_type == platform_events.GroupMessage:
|
||||
self.bot.on_message('group')(self.on_message)
|
||||
elif event_type == platform_events.FeedbackEvent:
|
||||
if hasattr(self.bot, 'on_feedback'):
|
||||
self.bot.on_feedback()(self._on_feedback)
|
||||
except Exception:
|
||||
print(traceback.format_exc())
|
||||
|
||||
@@ -426,74 +328,65 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
"""设置 bot UUID（用于生成 webhook URL）"""
|
||||
self.bot_uuid = bot_uuid
|
||||
|
||||
async def on_monitoring_message_created(self, query, monitoring_message_id: str):
|
||||
"""Called by pipeline after monitoring message is created, to map stream_id to monitoring message ID."""
|
||||
try:
|
||||
stream_id = query.message_event.source_platform_object.stream_id
|
||||
if stream_id:
|
||||
self._stream_to_monitoring_msg[stream_id] = (monitoring_message_id, time.time())
|
||||
self._cleanup_stream_mapping()
|
||||
except Exception as e:
|
||||
await self.logger.debug(f'Failed to map stream_id to monitoring message: {e}')
|
||||
def set_bot_info(
|
||||
self,
|
||||
bot_id: str,
|
||||
bot_name: str,
|
||||
pipeline_id: str,
|
||||
pipeline_name: str,
|
||||
):
|
||||
"""设置 bot 信息（用于监控记录）"""
|
||||
self._bot_info = {
|
||||
'bot_id': bot_id,
|
||||
'bot_name': bot_name,
|
||||
'pipeline_id': pipeline_id,
|
||||
'pipeline_name': pipeline_name,
|
||||
}
|
||||
|
||||
def _cleanup_stream_mapping(self):
|
||||
"""Remove entries older than TTL from the stream_id to monitoring message mapping."""
|
||||
now = time.time()
|
||||
expired = [k for k, (_, ts) in self._stream_to_monitoring_msg.items() if now - ts > self._STREAM_MAPPING_TTL]
|
||||
for k in expired:
|
||||
del self._stream_to_monitoring_msg[k]
|
||||
def _register_feedback_handler(self):
|
||||
"""注册用户反馈处理器，用于持久化反馈数据到监控服务"""
|
||||
|
||||
async def _on_feedback(self, **kwargs):
|
||||
"""Handle feedback event from WeChat Work AI Bot SDK and dispatch as FeedbackEvent."""
|
||||
try:
|
||||
feedback_id = kwargs.get('feedback_id', '')
|
||||
feedback_type = kwargs.get('feedback_type', 0)
|
||||
feedback_content = kwargs.get('feedback_content', '') or None
|
||||
inaccurate_reasons = kwargs.get('inaccurate_reasons', []) or None
|
||||
# WeChat Work returns integer reason codes, but FeedbackEvent expects strings
|
||||
if inaccurate_reasons:
|
||||
inaccurate_reasons = [str(r) for r in inaccurate_reasons]
|
||||
session = kwargs.get('session')
|
||||
async def handle_feedback(
|
||||
feedback_id: str,
|
||||
feedback_type: int,
|
||||
feedback_content: str,
|
||||
inaccurate_reasons: list[str],
|
||||
session: StreamSession,
|
||||
):
|
||||
"""处理用户反馈事件，持久化到监控服务"""
|
||||
if not self.ap or not self._bot_info:
|
||||
return
|
||||
|
||||
session_id = None
|
||||
user_id = None
|
||||
message_id = None
|
||||
stream_id = None
|
||||
if session:
|
||||
try:
|
||||
# Build session_id from session info
|
||||
session_id = None
|
||||
if session.chat_id:
|
||||
session_id = f'group_{session.chat_id}'
|
||||
elif session.user_id:
|
||||
session_id = f'person_{session.user_id}'
|
||||
user_id = session.user_id
|
||||
message_id = session.msg_id
|
||||
stream_id = session.stream_id
|
||||
|
||||
# Resolve stream_id to LangBot monitoring message ID if available
|
||||
monitoring_msg_id = None
|
||||
if stream_id and stream_id in self._stream_to_monitoring_msg:
|
||||
monitoring_msg_id = self._stream_to_monitoring_msg[stream_id][0]
|
||||
await FeedbackMonitor.record_feedback(
|
||||
ap=self.ap,
|
||||
feedback_id=feedback_id,
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=feedback_content if feedback_content else None,
|
||||
inaccurate_reasons=inaccurate_reasons if inaccurate_reasons else None,
|
||||
bot_id=self._bot_info['bot_id'],
|
||||
bot_name=self._bot_info['bot_name'],
|
||||
pipeline_id=self._bot_info['pipeline_id'],
|
||||
pipeline_name=self._bot_info['pipeline_name'],
|
||||
session_id=session_id,
|
||||
message_id=session.msg_id if session else None,
|
||||
stream_id=session.stream_id if session else None,
|
||||
user_id=session.user_id if session else None,
|
||||
platform='wecom',
|
||||
)
|
||||
except Exception:
|
||||
await self.logger.error(f'Failed to record feedback: {traceback.format_exc()}')
|
||||
|
||||
await self.logger.info(
|
||||
f'Feedback event: feedback_id={feedback_id}, type={feedback_type}, '
|
||||
f'session_id={session_id}, user_id={user_id}, message_id={message_id}'
|
||||
)
|
||||
|
||||
event = platform_events.FeedbackEvent(
|
||||
feedback_id=feedback_id,
|
||||
feedback_type=feedback_type,
|
||||
feedback_content=feedback_content,
|
||||
inaccurate_reasons=inaccurate_reasons,
|
||||
user_id=user_id,
|
||||
session_id=session_id,
|
||||
message_id=message_id,
|
||||
stream_id=monitoring_msg_id or stream_id,
|
||||
source_platform_object=session,
|
||||
)
|
||||
|
||||
if platform_events.FeedbackEvent in self.listeners:
|
||||
await self.listeners[platform_events.FeedbackEvent](event, self)
|
||||
except Exception:
|
||||
await self.logger.error(f'Error in wecombot feedback callback: {traceback.format_exc()}')
|
||||
# Register the feedback handler with the bot client
|
||||
if hasattr(self.bot, 'on_feedback'):
|
||||
self.bot.on_feedback()(handle_feedback)
|
||||
|
||||
async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
|
||||
_ws_mode = not self.config.get('enable-webhook', False)
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/wecombot
|
||||
en: https://link.langbot.app/en/platforms/wecombot
|
||||
ja: https://link.langbot.app/ja/platforms/wecombot
|
||||
config:
|
||||
- name: BotId
|
||||
label:
|
||||
|
||||
@@ -14,10 +14,6 @@ metadata:
|
||||
spec:
|
||||
categories:
|
||||
- china
|
||||
help_links:
|
||||
zh: https://link.langbot.app/zh/platforms/wecomcs
|
||||
en: https://link.langbot.app/en/platforms/wecomcs
|
||||
ja: https://link.langbot.app/ja/platforms/wecomcs
|
||||
config:
|
||||
- name: webhook_url
|
||||
label:
|
||||
|
||||
@@ -4,12 +4,12 @@ import sqlalchemy
|
||||
import traceback
|
||||
|
||||
from . import requester
|
||||
from .requesters import litellmchat
|
||||
from ...core import app
|
||||
from ...discover import engine
|
||||
from . import token
|
||||
from ...entity.persistence import model as persistence_model
|
||||
from ...entity.errors import provider as provider_errors
|
||||
from async_lru import alru_cache
|
||||
|
||||
|
||||
class ModelManager:
|
||||
@@ -24,8 +24,6 @@ class ModelManager:
|
||||
|
||||
embedding_models: list[requester.RuntimeEmbeddingModel]
|
||||
|
||||
rerank_models: list[requester.RuntimeRerankModel]
|
||||
|
||||
requester_components: list[engine.Component]
|
||||
|
||||
requester_dict: dict[str, type[requester.ProviderAPIRequester]]
|
||||
@@ -34,7 +32,6 @@ class ModelManager:
|
||||
self.ap = ap
|
||||
self.llm_models = []
|
||||
self.embedding_models = []
|
||||
self.rerank_models = []
|
||||
self.requester_components = []
|
||||
self.requester_dict = {}
|
||||
|
||||
@@ -43,13 +40,6 @@ class ModelManager:
|
||||
|
||||
requester_dict: dict[str, type[requester.ProviderAPIRequester]] = {}
|
||||
for component in self.requester_components:
|
||||
# Skip components that use litellm_provider (they will use litellmchat.py instead)
|
||||
if component.spec.get('litellm_provider'):
|
||||
self.ap.logger.debug(
|
||||
f'Skipping Python class loading for {component.metadata.name} '
|
||||
f'(uses litellm_provider={component.spec.get("litellm_provider")})'
|
||||
)
|
||||
continue
|
||||
requester_dict[component.metadata.name] = component.get_python_component_class()
|
||||
|
||||
self.requester_dict = requester_dict
|
||||
@@ -74,7 +64,8 @@ class ModelManager:
|
||||
|
||||
self.llm_models = []
|
||||
self.embedding_models = []
|
||||
self.rerank_models = []
|
||||
|
||||
# Load all providers first
|
||||
self.provider_dict = {}
|
||||
providers_result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_model.ModelProvider)
|
||||
@@ -119,22 +110,6 @@ class ModelManager:
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Failed to load model {embedding_model.uuid}: {e}\n{traceback.format_exc()}')
|
||||
|
||||
# Load rerank models
|
||||
result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.RerankModel))
|
||||
rerank_models = result.all()
|
||||
for rerank_model in rerank_models:
|
||||
try:
|
||||
provider = self.provider_dict.get(rerank_model.provider_uuid)
|
||||
if provider is None:
|
||||
self.ap.logger.warning(
|
||||
f'Provider {rerank_model.provider_uuid} not found for model {rerank_model.uuid}'
|
||||
)
|
||||
continue
|
||||
runtime_rerank_model = await self.load_rerank_model_with_provider(rerank_model, provider)
|
||||
self.rerank_models.append(runtime_rerank_model)
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Failed to load model {rerank_model.uuid}: {e}\n{traceback.format_exc()}')
|
||||
|
||||
async def sync_new_models_from_space(self):
|
||||
"""Sync models from Space"""
|
||||
space_model_provider = await self.ap.persistence_mgr.execute_async(
|
||||
@@ -237,26 +212,6 @@ class ModelManager:
|
||||
|
||||
return runtime_embedding_model
|
||||
|
||||
async def init_temporary_runtime_rerank_model(
|
||||
self,
|
||||
model_info: dict,
|
||||
) -> requester.RuntimeRerankModel:
|
||||
"""Initialize runtime rerank model from dict (for testing)"""
|
||||
provider_info = model_info.get('provider', {})
|
||||
runtime_provider = await self.load_provider(provider_info)
|
||||
|
||||
runtime_rerank_model = requester.RuntimeRerankModel(
|
||||
model_entity=persistence_model.RerankModel(
|
||||
uuid=model_info.get('uuid', ''),
|
||||
name=model_info.get('name', ''),
|
||||
provider_uuid='',
|
||||
extra_args=model_info.get('extra_args', {}),
|
||||
),
|
||||
provider=runtime_provider,
|
||||
)
|
||||
|
||||
return runtime_rerank_model
|
||||
|
||||
async def load_provider(
|
||||
self, provider_info: persistence_model.ModelProvider | sqlalchemy.Row | dict
|
||||
) -> requester.RuntimeProvider:
|
||||
@@ -268,34 +223,12 @@ class ModelManager:
|
||||
else:
|
||||
provider_entity = provider_info
|
||||
|
||||
# Get requester manifest to check for litellm_provider
|
||||
requester_manifest = self.get_available_requester_manifest_by_name(provider_entity.requester)
|
||||
|
||||
# Build config from base_url
|
||||
config = {'base_url': provider_entity.base_url}
|
||||
|
||||
# Check if requester manifest specifies litellm_provider
|
||||
if requester_manifest and requester_manifest.spec.get('litellm_provider'):
|
||||
# Use unified LiteLLMRequester with provider prefix
|
||||
# Map litellm_provider (YAML spec) to custom_llm_provider (config)
|
||||
config['custom_llm_provider'] = requester_manifest.spec['litellm_provider']
|
||||
requester_inst = litellmchat.LiteLLMRequester(
|
||||
ap=self.ap,
|
||||
config=config,
|
||||
)
|
||||
self.ap.logger.debug(
|
||||
f'Using LiteLLMRequester for {provider_entity.requester} '
|
||||
f'with custom_llm_provider={config["custom_llm_provider"]}'
|
||||
)
|
||||
else:
|
||||
# Use original requester class (for backward compatibility)
|
||||
if provider_entity.requester not in self.requester_dict:
|
||||
raise provider_errors.RequesterNotFoundError(provider_entity.requester)
|
||||
requester_inst = self.requester_dict[provider_entity.requester](
|
||||
ap=self.ap,
|
||||
config=config,
|
||||
)
|
||||
if provider_entity.requester not in self.requester_dict:
|
||||
raise provider_errors.RequesterNotFoundError(provider_entity.requester)
|
||||
|
||||
requester_inst = self.requester_dict[provider_entity.requester](
|
||||
ap=self.ap, config={'base_url': provider_entity.base_url}
|
||||
)
|
||||
await requester_inst.initialize()
|
||||
|
||||
token_mgr = token.TokenManager(name=provider_entity.uuid, tokens=provider_entity.api_keys or [])
|
||||
@@ -335,9 +268,6 @@ class ModelManager:
|
||||
for model in self.embedding_models:
|
||||
if model.provider.provider_entity.uuid == provider_uuid:
|
||||
model.provider = new_runtime_provider
|
||||
for model in self.rerank_models:
|
||||
if model.provider.provider_entity.uuid == provider_uuid:
|
||||
model.provider = new_runtime_provider
|
||||
|
||||
# update ref in provider dict
|
||||
self.provider_dict[provider_uuid] = new_runtime_provider
|
||||
@@ -374,22 +304,6 @@ class ModelManager:
|
||||
|
||||
return runtime_embedding_model
|
||||
|
||||
async def load_rerank_model_with_provider(
|
||||
self,
|
||||
model_info: persistence_model.RerankModel | sqlalchemy.Row,
|
||||
provider: requester.RuntimeProvider,
|
||||
) -> requester.RuntimeRerankModel:
|
||||
"""Load rerank model with provider info"""
|
||||
if isinstance(model_info, sqlalchemy.Row):
|
||||
model_info = persistence_model.RerankModel(**model_info._mapping)
|
||||
|
||||
runtime_rerank_model = requester.RuntimeRerankModel(
|
||||
model_entity=model_info,
|
||||
provider=provider,
|
||||
)
|
||||
|
||||
return runtime_rerank_model
|
||||
|
||||
async def load_llm_model(self, model_info: dict):
|
||||
"""Load LLM model from dict (with provider info)"""
|
||||
provider_info = model_info.get('provider', {})
|
||||
@@ -437,6 +351,7 @@ class ModelManager:
|
||||
|
||||
await self.load_embedding_model_with_provider(model_entity, provider_entity)
|
||||
|
||||
@alru_cache(ttl=60 * 5)
|
||||
async def get_model_by_uuid(self, uuid: str) -> requester.RuntimeLLMModel:
|
||||
"""Get LLM model by uuid"""
|
||||
for model in self.llm_models:
|
||||
@@ -444,6 +359,7 @@ class ModelManager:
|
||||
return model
|
||||
raise ValueError(f'LLM model {uuid} not found')
|
||||
|
||||
@alru_cache(ttl=60 * 5)
|
||||
async def get_embedding_model_by_uuid(self, uuid: str) -> requester.RuntimeEmbeddingModel:
|
||||
"""Get embedding model by uuid"""
|
||||
for model in self.embedding_models:
|
||||
@@ -451,13 +367,6 @@ class ModelManager:
|
||||
return model
|
||||
raise ValueError(f'Embedding model {uuid} not found')
|
||||
|
||||
async def get_rerank_model_by_uuid(self, uuid: str) -> requester.RuntimeRerankModel:
|
||||
"""Get rerank model by uuid"""
|
||||
for model in self.rerank_models:
|
||||
if model.model_entity.uuid == uuid:
|
||||
return model
|
||||
raise ValueError(f'Rerank model {uuid} not found')
|
||||
|
||||
async def remove_llm_model(self, model_uuid: str):
|
||||
"""Remove LLM model"""
|
||||
for model in self.llm_models:
|
||||
@@ -472,13 +381,6 @@ class ModelManager:
|
||||
self.embedding_models.remove(model)
|
||||
return
|
||||
|
||||
async def remove_rerank_model(self, model_uuid: str):
|
||||
"""Remove rerank model"""
|
||||
for model in self.rerank_models:
|
||||
if model.model_entity.uuid == model_uuid:
|
||||
self.rerank_models.remove(model)
|
||||
return
|
||||
|
||||
def get_available_requesters_info(self, model_type: str) -> list[dict]:
|
||||
"""Get all available requesters"""
|
||||
if model_type != '':
|
||||
|
||||
@@ -67,8 +67,8 @@ class RuntimeProvider:
|
||||
if isinstance(result, tuple):
|
||||
msg, usage_info = result
|
||||
if usage_info:
|
||||
input_tokens = usage_info.get('prompt_tokens', 0)
|
||||
output_tokens = usage_info.get('completion_tokens', 0)
|
||||
input_tokens = usage_info.get('input_tokens', 0)
|
||||
output_tokens = usage_info.get('output_tokens', 0)
|
||||
return msg
|
||||
else:
|
||||
return result
|
||||
@@ -128,6 +128,7 @@ class RuntimeProvider:
|
||||
start_time = time.time()
|
||||
status = 'success'
|
||||
error_message = None
|
||||
# Note: Stream doesn't easily provide token counts, set to 0
|
||||
input_tokens = 0
|
||||
output_tokens = 0
|
||||
|
||||
@@ -142,15 +143,6 @@ class RuntimeProvider:
|
||||
remove_think=remove_think,
|
||||
):
|
||||
yield chunk
|
||||
# Extract usage from stream if available (stored by LiteLLM requester)
|
||||
if query:
|
||||
if query.variables is None:
|
||||
query.variables = {}
|
||||
if '_stream_usage' in query.variables:
|
||||
usage_info = query.variables['_stream_usage']
|
||||
input_tokens = usage_info.get('prompt_tokens', 0)
|
||||
output_tokens = usage_info.get('completion_tokens', 0)
|
||||
del query.variables['_stream_usage']
|
||||
except Exception as e:
|
||||
status = 'error'
|
||||
error_message = str(e)
|
||||
@@ -255,40 +247,6 @@ class RuntimeProvider:
|
||||
except Exception as monitor_err:
|
||||
self.requester.ap.logger.error(f'[Monitoring] Failed to record embedding call: {monitor_err}')
|
||||
|
||||
async def invoke_rerank(
|
||||
self,
|
||||
model: RuntimeRerankModel,
|
||||
query: str,
|
||||
documents: typing.List[str],
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
) -> typing.List[dict]:
|
||||
"""Bridge method for invoking rerank with monitoring"""
|
||||
start_time = time.time()
|
||||
status = 'success'
|
||||
|
||||
try:
|
||||
result = await self.requester.invoke_rerank(
|
||||
model=model,
|
||||
query=query,
|
||||
documents=documents,
|
||||
extra_args=extra_args,
|
||||
)
|
||||
return result
|
||||
|
||||
except Exception:
|
||||
status = 'error'
|
||||
raise
|
||||
finally:
|
||||
duration_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
try:
|
||||
self.requester.ap.logger.debug(
|
||||
f'[Rerank] model={model.model_entity.name} docs={len(documents)} '
|
||||
f'duration={duration_ms}ms status={status}'
|
||||
)
|
||||
except Exception as monitor_err:
|
||||
self.requester.ap.logger.error(f'[Monitoring] Failed to record rerank call: {monitor_err}')
|
||||
|
||||
|
||||
class RuntimeLLMModel:
|
||||
"""运行时模型"""
|
||||
@@ -326,24 +284,6 @@ class RuntimeEmbeddingModel:
|
||||
self.provider = provider
|
||||
|
||||
|
||||
class RuntimeRerankModel:
|
||||
"""运行时 Rerank 模型"""
|
||||
|
||||
model_entity: persistence_model.RerankModel
|
||||
"""模型数据"""
|
||||
|
||||
provider: RuntimeProvider
|
||||
"""提供商实例"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
model_entity: persistence_model.RerankModel,
|
||||
provider: RuntimeProvider,
|
||||
):
|
||||
self.model_entity = model_entity
|
||||
self.provider = provider
|
||||
|
||||
|
||||
class ProviderAPIRequester(metaclass=abc.ABCMeta):
|
||||
"""Provider API请求器"""
|
||||
|
||||
@@ -363,14 +303,6 @@ class ProviderAPIRequester(metaclass=abc.ABCMeta):
|
||||
async def initialize(self):
|
||||
pass
|
||||
|
||||
async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any] | list[dict[str, typing.Any]]:
|
||||
"""Scan models supported by the provider.
|
||||
|
||||
The default implementation does not support scanning. Requesters that
|
||||
can enumerate remote models should override this method.
|
||||
"""
|
||||
raise NotImplementedError('This provider does not support model scanning')
|
||||
|
||||
@abc.abstractmethod
|
||||
async def invoke_llm(
|
||||
self,
|
||||
@@ -436,23 +368,3 @@ class ProviderAPIRequester(metaclass=abc.ABCMeta):
|
||||
或者 tuple[typing.List[typing.List[float]], dict]: 返回 (embedding 向量, usage_info)
|
||||
"""
|
||||
pass
|
||||
|
||||
async def invoke_rerank(
|
||||
self,
|
||||
model: RuntimeRerankModel,
|
||||
query: str,
|
||||
documents: typing.List[str],
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
) -> typing.List[dict]:
|
||||
"""调用 Rerank API
|
||||
|
||||
Args:
|
||||
model (RuntimeRerankModel): 使用的模型信息
|
||||
query (str): 查询文本
|
||||
documents (typing.List[str]): 待重排序的文档列表
|
||||
extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
|
||||
|
||||
Returns:
|
||||
typing.List[dict]: [{"index": int, "relevance_score": float}, ...]
|
||||
"""
|
||||
raise NotImplementedError('This requester does not support rerank')
|
||||
|
||||
@@ -25,7 +25,6 @@ spec:
|
||||
support_type:
|
||||
- llm
|
||||
- text-embedding
|
||||
- rerank
|
||||
provider_category: maas
|
||||
execution:
|
||||
python:
|
||||
|
||||
@@ -24,7 +24,6 @@ spec:
|
||||
default: 120
|
||||
support_type:
|
||||
- llm
|
||||
- rerank
|
||||
provider_category: maas
|
||||
execution:
|
||||
python:
|
||||
|
||||
@@ -31,192 +31,6 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
|
||||
http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
|
||||
)
|
||||
|
||||
def _mask_api_key(self, api_key: str | None) -> str:
|
||||
if not api_key:
|
||||
return ''
|
||||
if len(api_key) <= 8:
|
||||
return '****'
|
||||
return f'{api_key[:4]}...{api_key[-4:]}'
|
||||
|
||||
def _infer_model_type(self, model_id: str) -> str:
|
||||
normalized_model_id = (model_id or '').lower()
|
||||
embedding_keywords = (
|
||||
'embedding',
|
||||
'embed',
|
||||
'bge-',
|
||||
'e5-',
|
||||
'm3e',
|
||||
'gte-',
|
||||
'multilingual-e5',
|
||||
'text-embedding',
|
||||
)
|
||||
return 'embedding' if any(keyword in normalized_model_id for keyword in embedding_keywords) else 'llm'
|
||||
|
||||
def _infer_model_abilities(self, item: dict[str, typing.Any], model_id: str) -> list[str]:
|
||||
normalized_model_id = (model_id or '').lower()
|
||||
abilities: set[str] = set()
|
||||
|
||||
def _flatten(value: typing.Any) -> list[str]:
|
||||
if value is None:
|
||||
return []
|
||||
if isinstance(value, str):
|
||||
return [value.lower()]
|
||||
if isinstance(value, dict):
|
||||
flattened: list[str] = []
|
||||
for nested_value in value.values():
|
||||
flattened.extend(_flatten(nested_value))
|
||||
return flattened
|
||||
if isinstance(value, (list, tuple, set)):
|
||||
flattened: list[str] = []
|
||||
for nested_value in value:
|
||||
flattened.extend(_flatten(nested_value))
|
||||
return flattened
|
||||
return [str(value).lower()]
|
||||
|
||||
capability_tokens = _flatten(item.get('capabilities'))
|
||||
capability_tokens.extend(_flatten(item.get('modalities')))
|
||||
capability_tokens.extend(_flatten(item.get('input_modalities')))
|
||||
capability_tokens.extend(_flatten(item.get('output_modalities')))
|
||||
capability_tokens.extend(_flatten(item.get('supported_generation_methods')))
|
||||
capability_tokens.extend(_flatten(item.get('supported_parameters')))
|
||||
capability_tokens.extend(_flatten(item.get('architecture')))
|
||||
|
||||
combined_tokens = capability_tokens + [normalized_model_id]
|
||||
|
||||
vision_keywords = (
|
||||
'vision',
|
||||
'image',
|
||||
'file',
|
||||
'video',
|
||||
'multimodal',
|
||||
'vl',
|
||||
'ocr',
|
||||
'omni',
|
||||
)
|
||||
function_call_keywords = (
|
||||
'function',
|
||||
'tool',
|
||||
'tools',
|
||||
'tool_choice',
|
||||
'tool_call',
|
||||
'tool-use',
|
||||
'tool_use',
|
||||
)
|
||||
|
||||
if any(any(keyword in token for keyword in vision_keywords) for token in combined_tokens):
|
||||
abilities.add('vision')
|
||||
|
||||
if any(any(keyword in token for keyword in function_call_keywords) for token in combined_tokens):
|
||||
abilities.add('func_call')
|
||||
|
||||
return sorted(abilities)
|
||||
|
||||
def _normalize_modalities(self, value: typing.Any) -> list[str]:
|
||||
normalized: list[str] = []
|
||||
|
||||
def _collect(item: typing.Any):
|
||||
if item is None:
|
||||
return
|
||||
if isinstance(item, str):
|
||||
for part in item.replace('->', ',').replace('+', ',').split(','):
|
||||
token = part.strip().lower()
|
||||
if token and token not in normalized:
|
||||
normalized.append(token)
|
||||
return
|
||||
if isinstance(item, dict):
|
||||
for nested in item.values():
|
||||
_collect(nested)
|
||||
return
|
||||
if isinstance(item, (list, tuple, set)):
|
||||
for nested in item:
|
||||
_collect(nested)
|
||||
return
|
||||
|
||||
_collect(value)
|
||||
return normalized
|
||||
|
||||
def _extract_scan_metadata(self, item: dict[str, typing.Any], model_id: str) -> dict[str, typing.Any]:
|
||||
display_name = item.get('name')
|
||||
if not isinstance(display_name, str) or not display_name.strip() or display_name == model_id:
|
||||
display_name = ''
|
||||
|
||||
description = item.get('description')
|
||||
if not isinstance(description, str) or not description.strip():
|
||||
description = ''
|
||||
|
||||
context_length = item.get('context_length')
|
||||
if context_length is None and isinstance(item.get('top_provider'), dict):
|
||||
context_length = item['top_provider'].get('context_length')
|
||||
|
||||
if not isinstance(context_length, int):
|
||||
try:
|
||||
context_length = int(context_length) if context_length is not None else None
|
||||
except (TypeError, ValueError):
|
||||
context_length = None
|
||||
|
||||
input_modalities = self._normalize_modalities(item.get('input_modalities'))
|
||||
output_modalities = self._normalize_modalities(item.get('output_modalities'))
|
||||
|
||||
if isinstance(item.get('architecture'), dict):
|
||||
if not input_modalities:
|
||||
input_modalities = self._normalize_modalities(item['architecture'].get('input_modalities'))
|
||||
if not output_modalities:
|
||||
output_modalities = self._normalize_modalities(item['architecture'].get('output_modalities'))
|
||||
|
||||
owned_by = item.get('owned_by')
|
||||
if not isinstance(owned_by, str) or not owned_by.strip():
|
||||
owned_by = ''
|
||||
|
||||
return {
|
||||
'display_name': display_name or None,
|
||||
'description': description or None,
|
||||
'context_length': context_length,
|
||||
'owned_by': owned_by or None,
|
||||
'input_modalities': input_modalities,
|
||||
'output_modalities': output_modalities,
|
||||
}
|
||||
|
||||
async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
|
||||
headers = {}
|
||||
if api_key:
|
||||
headers['Authorization'] = f'Bearer {api_key}'
|
||||
|
||||
models_url = f'{self.requester_cfg["base_url"].rstrip("/")}/models'
|
||||
async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
|
||||
response = await client.get(models_url, headers=headers)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
|
||||
models = []
|
||||
for item in payload.get('data', []):
|
||||
model_id = item.get('id')
|
||||
if not model_id:
|
||||
continue
|
||||
models.append(
|
||||
{
|
||||
'id': model_id,
|
||||
'name': model_id,
|
||||
'type': self._infer_model_type(model_id),
|
||||
'abilities': self._infer_model_abilities(item, model_id),
|
||||
**self._extract_scan_metadata(item, model_id),
|
||||
}
|
||||
)
|
||||
|
||||
models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
|
||||
return {
|
||||
'models': models,
|
||||
'debug': {
|
||||
'request': {
|
||||
'method': 'GET',
|
||||
'url': models_url,
|
||||
'headers': {
|
||||
'Authorization': f'Bearer {self._mask_api_key(api_key)}' if api_key else '',
|
||||
},
|
||||
},
|
||||
'response': payload,
|
||||
},
|
||||
}
|
||||
|
||||
async def _req(
|
||||
self,
|
||||
args: dict,
|
||||
@@ -615,88 +429,3 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
|
||||
raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
|
||||
except openai.APIError as e:
|
||||
raise errors.RequesterError(f'请求错误: {e.message}')
|
||||
|
||||
async def invoke_rerank(
|
||||
self,
|
||||
model: requester.RuntimeRerankModel,
|
||||
query: str,
|
||||
documents: typing.List[str],
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
) -> typing.List[dict]:
|
||||
"""Standard /rerank endpoint (Jina/Cohere/SiliconFlow/Voyage/DashScope compatible)
|
||||
|
||||
Supports extra_args from model.extra_args:
|
||||
- rerank_url: full URL override (e.g. "https://dashscope.aliyuncs.com/compatible-api/v1/reranks")
|
||||
- rerank_path: path override appended to base_url (e.g. "reranks" instead of default "rerank")
|
||||
- Any other fields are merged into the request payload.
|
||||
"""
|
||||
api_key = model.provider.token_mgr.get_token()
|
||||
base_url = self.requester_cfg.get('base_url', '').rstrip('/')
|
||||
timeout = self.requester_cfg.get('timeout', 120)
|
||||
|
||||
merged_args = {}
|
||||
if model.model_entity.extra_args:
|
||||
merged_args.update(model.model_entity.extra_args)
|
||||
if extra_args:
|
||||
merged_args.update(extra_args)
|
||||
|
||||
rerank_url = merged_args.pop('rerank_url', None)
|
||||
rerank_path = merged_args.pop('rerank_path', 'rerank')
|
||||
if not rerank_url:
|
||||
rerank_url = f'{base_url}/{rerank_path}'
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': f'Bearer {api_key}',
|
||||
}
|
||||
|
||||
payload = {
|
||||
'model': model.model_entity.name,
|
||||
'query': query,
|
||||
'documents': documents[:64],
|
||||
'top_n': min(len(documents), 64),
|
||||
}
|
||||
|
||||
if merged_args:
|
||||
payload.update(merged_args)
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(trust_env=True, timeout=timeout) as client:
|
||||
resp = await client.post(rerank_url, headers=headers, json=payload)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
|
||||
results = self._parse_rerank_response(data)
|
||||
|
||||
if results:
|
||||
scores = [r.get('relevance_score', 0.0) for r in results]
|
||||
min_score = min(scores)
|
||||
max_score = max(scores)
|
||||
if max_score - min_score > 1e-6:
|
||||
for r in results:
|
||||
r['relevance_score'] = (r['relevance_score'] - min_score) / (max_score - min_score)
|
||||
|
||||
return results
|
||||
except httpx.HTTPStatusError as e:
|
||||
raise errors.RequesterError(f'Rerank request failed: {e.response.status_code} - {e.response.text}')
|
||||
except httpx.TimeoutException:
|
||||
raise errors.RequesterError('Rerank request timed out')
|
||||
except Exception as e:
|
||||
raise errors.RequesterError(f'Rerank request error: {str(e)}')
|
||||
|
||||
@staticmethod
|
||||
def _parse_rerank_response(data: dict) -> typing.List[dict]:
|
||||
"""Parse rerank response from various providers.
|
||||
|
||||
Handles:
|
||||
- Jina/Cohere/SiliconFlow: {"results": [{"index", "relevance_score"}]}
|
||||
- Voyage AI: {"data": [{"index", "relevance_score"}]}
|
||||
- DashScope: {"output": {"results": [{"index", "relevance_score"}]}}
|
||||
"""
|
||||
if 'results' in data:
|
||||
return data['results']
|
||||
if 'data' in data:
|
||||
return data['data']
|
||||
if 'output' in data and isinstance(data['output'], dict):
|
||||
return data['output'].get('results', [])
|
||||
return []
|
||||
|
||||
@@ -25,7 +25,6 @@ spec:
|
||||
support_type:
|
||||
- llm
|
||||
- text-embedding
|
||||
- rerank
|
||||
provider_category: manufacturer
|
||||
execution:
|
||||
python:
|
||||
|
||||
@@ -1,8 +0,0 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 128 128" id="Chroma--Streamline-Svg-Logos" height="128" width="128">
|
||||
<desc>
|
||||
Chroma Streamline Icon: https://streamlinehq.com
|
||||
</desc>
|
||||
<path fill="#ffde2d" d="M84.88839999999999 104.10666666666665c23.0732 0 41.77773333333333 -17.956266666666664 41.77773333333333 -40.10653333333333 0 -22.150266666666667 -18.70453333333333 -40.10653333333333 -41.77773333333333 -40.10653333333333 -23.0732 0 -41.77773333333333 17.956266666666664 -41.77773333333333 40.10653333333333 0 22.150266666666667 18.70453333333333 40.10653333333333 41.77773333333333 40.10653333333333Z" stroke-width="1.3333"></path>
|
||||
<path fill="#327eff" d="M43.111066666666666 104.10666666666665c23.0732 0 41.77773333333333 -17.956266666666664 41.77773333333333 -40.10653333333333 0 -22.150266666666667 -18.70453333333333 -40.10653333333333 -41.77773333333333 -40.10653333333333C20.037866666666666 23.8936 1.3333333333333333 41.849866666666664 1.3333333333333333 64.00013333333334 1.3333333333333333 86.15039999999999 20.037866666666666 104.10666666666665 43.111066666666666 104.10666666666665Z" stroke-width="1.3333"></path>
|
||||
<path fill="#ff6446" d="M84.88866666666667 64.00013333333334c0 22.150399999999998 -18.704666666666665 40.10626666666666 -41.778 40.10626666666666V64.00013333333334h41.778Zm-41.778 0c0 -22.150266666666667 18.70453333333333 -40.10653333333333 41.778 -40.10653333333333v40.10653333333333H43.11066666666666Z" stroke-width="1.3333"></path>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 1.5 KiB |
@@ -1,61 +0,0 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
|
||||
from .. import requester
|
||||
|
||||
REQUESTER_NAME: str = 'chroma-embedding'
|
||||
|
||||
|
||||
class ChromaEmbedding(requester.ProviderAPIRequester):
|
||||
"""Chroma built-in embedding requester.
|
||||
|
||||
Uses chromadb's DefaultEmbeddingFunction (all-MiniLM-L6-v2).
|
||||
The embedding function runs locally using ONNX Runtime.
|
||||
"""
|
||||
|
||||
default_config: dict[str, typing.Any] = {
|
||||
'base_url': '',
|
||||
}
|
||||
|
||||
_embedding_function = None
|
||||
|
||||
async def initialize(self):
|
||||
try:
|
||||
from chromadb.utils import embedding_functions
|
||||
except ImportError:
|
||||
raise ImportError('chromadb is not installed. Install it with: pip install chromadb')
|
||||
|
||||
self._embedding_function = embedding_functions.DefaultEmbeddingFunction()
|
||||
|
||||
async def invoke_llm(
|
||||
self,
|
||||
query,
|
||||
model: requester.RuntimeLLMModel,
|
||||
messages: typing.List,
|
||||
funcs: typing.List = None,
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
remove_think: bool = False,
|
||||
):
|
||||
raise NotImplementedError('Chroma embedding does not support LLM inference')
|
||||
|
||||
async def invoke_embedding(
|
||||
self,
|
||||
model: requester.RuntimeEmbeddingModel,
|
||||
input_text: typing.List[str],
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
) -> typing.List[typing.List[float]]:
|
||||
"""Generate embeddings using Chroma's DefaultEmbeddingFunction."""
|
||||
if self._embedding_function is None:
|
||||
await self.initialize()
|
||||
|
||||
try:
|
||||
result = self._embedding_function(input_text)
|
||||
# DefaultEmbeddingFunction returns list of ndarray, convert for JSON
|
||||
if isinstance(result, list):
|
||||
return [item.tolist() if hasattr(item, 'tolist') else item for item in result]
|
||||
return result.tolist() if hasattr(result, 'tolist') else result
|
||||
except Exception as e:
|
||||
from .. import errors
|
||||
|
||||
raise errors.RequesterError(f'Chroma embedding failed: {str(e)}')
|
||||
@@ -1,21 +0,0 @@
|
||||
apiVersion: v1
|
||||
kind: LLMAPIRequester
|
||||
metadata:
|
||||
name: chroma-embedding
|
||||
label:
|
||||
en_US: Chroma Embedding
|
||||
zh_Hans: Chroma 嵌入
|
||||
description:
|
||||
en_US: Chroma built-in embedding model (all-MiniLM-L6-v2), runs locally using ONNX Runtime. First-time use will download model files automatically.
|
||||
zh_Hans: 使用 Chroma 内置嵌入模型 (all-MiniLM-L6-v2)，基于 ONNX Runtime 本地运行。首次使用时将自动下载模型文件。
|
||||
ja_JP: Chroma 組み込み埋め込みモデル (all-MiniLM-L6-v2) を使用します。ONNX Runtime でローカル実行。初回使用時にモデルファイルが自動ダウンロードされます。
|
||||
icon: chroma.svg
|
||||
spec:
|
||||
config: []
|
||||
support_type:
|
||||
- text-embedding
|
||||
provider_category: builtin
|
||||
execution:
|
||||
python:
|
||||
path: ./chromaembed.py
|
||||
attr: ChromaEmbedding
|
||||
@@ -1 +0,0 @@
|
||||
<svg height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Cohere</title><path clip-rule="evenodd" d="M8.128 14.099c.592 0 1.77-.033 3.398-.703 1.897-.781 5.672-2.2 8.395-3.656 1.905-1.018 2.74-2.366 2.74-4.18A4.56 4.56 0 0018.1 1H7.549A6.55 6.55 0 001 7.55c0 3.617 2.745 6.549 7.128 6.549z" fill="#39594D" fill-rule="evenodd"></path><path clip-rule="evenodd" d="M9.912 18.61a4.387 4.387 0 012.705-4.052l3.323-1.38c3.361-1.394 7.06 1.076 7.06 4.715a5.104 5.104 0 01-5.105 5.104l-3.597-.001a4.386 4.386 0 01-4.386-4.387z" fill="#D18EE2" fill-rule="evenodd"></path><path d="M4.776 14.962A3.775 3.775 0 001 18.738v.489a3.776 3.776 0 007.551 0v-.49a3.775 3.775 0 00-3.775-3.775z" fill="#FF7759"></path></svg>
|
||||
|
Before Width: | Height: | Size: 769 B |
@@ -1,31 +0,0 @@
|
||||
apiVersion: v1
|
||||
kind: LLMAPIRequester
|
||||
metadata:
|
||||
name: cohere-rerank
|
||||
label:
|
||||
en_US: Cohere
|
||||
zh_Hans: Cohere
|
||||
icon: cohere.svg
|
||||
spec:
|
||||
config:
|
||||
- name: base_url
|
||||
label:
|
||||
en_US: Base URL
|
||||
zh_Hans: 基础 URL
|
||||
type: string
|
||||
required: true
|
||||
default: https://api.cohere.com/v2
|
||||
- name: timeout
|
||||
label:
|
||||
en_US: Timeout
|
||||
zh_Hans: 超时时间
|
||||
type: integer
|
||||
required: true
|
||||
default: 120
|
||||
support_type:
|
||||
- rerank
|
||||
provider_category: manufacturer
|
||||
execution:
|
||||
python:
|
||||
path: ./chatcmpl.py
|
||||
attr: OpenAIChatCompletions
|
||||
@@ -1,7 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
import httpx
|
||||
|
||||
from . import chatcmpl
|
||||
|
||||
@@ -21,68 +20,6 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
|
||||
'timeout': 120,
|
||||
}
|
||||
|
||||
async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
|
||||
models_url = 'https://generativelanguage.googleapis.com/v1beta/models'
|
||||
params = {'key': api_key} if api_key else {}
|
||||
|
||||
all_models: list[dict[str, typing.Any]] = []
|
||||
next_page_token = ''
|
||||
last_payload: dict[str, typing.Any] = {}
|
||||
|
||||
async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
|
||||
while True:
|
||||
request_params = dict(params)
|
||||
if next_page_token:
|
||||
request_params['pageToken'] = next_page_token
|
||||
|
||||
response = await client.get(models_url, params=request_params)
|
||||
response.raise_for_status()
|
||||
payload = response.json()
|
||||
last_payload = payload
|
||||
|
||||
for item in payload.get('models', []):
|
||||
model_name = item.get('name', '')
|
||||
model_id = model_name.replace('models/', '', 1)
|
||||
if not model_id:
|
||||
continue
|
||||
|
||||
supported_methods = item.get('supportedGenerationMethods', []) or []
|
||||
if 'embedContent' in supported_methods and 'generateContent' not in supported_methods:
|
||||
model_type = 'embedding'
|
||||
else:
|
||||
model_type = 'llm'
|
||||
|
||||
all_models.append(
|
||||
{
|
||||
'id': model_id,
|
||||
'name': model_id,
|
||||
'type': model_type,
|
||||
'abilities': self._infer_model_abilities(item, model_id),
|
||||
'display_name': item.get('displayName') or None,
|
||||
'description': item.get('description') or None,
|
||||
'context_length': item.get('inputTokenLimit'),
|
||||
'input_modalities': self._normalize_modalities(item.get('inputModalities')),
|
||||
'output_modalities': self._normalize_modalities(item.get('outputModalities')),
|
||||
}
|
||||
)
|
||||
|
||||
next_page_token = payload.get('nextPageToken', '')
|
||||
if not next_page_token:
|
||||
break
|
||||
|
||||
all_models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
|
||||
return {
|
||||
'models': all_models,
|
||||
'debug': {
|
||||
'request': {
|
||||
'method': 'GET',
|
||||
'url': models_url,
|
||||
'query': {'key': self._mask_api_key(api_key)} if api_key else {},
|
||||
},
|
||||
'response': last_payload,
|
||||
},
|
||||
}
|
||||
|
||||
async def _closure_stream(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
|
||||
@@ -25,7 +25,6 @@ spec:
|
||||
support_type:
|
||||
- llm
|
||||
- text-embedding
|
||||
- rerank
|
||||
provider_category: maas
|
||||
execution:
|
||||
python:
|
||||
|
||||
@@ -1 +0,0 @@
|
||||
<svg fill="currentColor" fill-rule="evenodd" height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Jina</title><path d="M6.608 21.416a4.608 4.608 0 100-9.217 4.608 4.608 0 000 9.217zM20.894 2.015c.614 0 1.106.492 1.106 1.106v9.002c0 5.13-4.148 9.309-9.217 9.37v-9.355l-.03-9.032c0-.614.491-1.106 1.106-1.106h7.158l-.123.015z"></path></svg>
|
||||
|
Before Width: | Height: | Size: 404 B |
@@ -1,31 +0,0 @@
|
||||
apiVersion: v1
|
||||
kind: LLMAPIRequester
|
||||
metadata:
|
||||
name: jina-rerank
|
||||
label:
|
||||
en_US: Jina
|
||||
zh_Hans: Jina
|
||||
icon: jina.svg
|
||||
spec:
|
||||
config:
|
||||
- name: base_url
|
||||
label:
|
||||
en_US: Base URL
|
||||
zh_Hans: 基础 URL
|
||||
type: string
|
||||
required: true
|
||||
default: https://api.jina.ai/v1
|
||||
- name: timeout
|
||||
label:
|
||||
en_US: Timeout
|
||||
zh_Hans: 超时时间
|
||||
type: integer
|
||||
required: true
|
||||
default: 120
|
||||
support_type:
|
||||
- rerank
|
||||
provider_category: manufacturer
|
||||
execution:
|
||||
python:
|
||||
path: ./chatcmpl.py
|
||||
attr: OpenAIChatCompletions
|
||||
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Reference in New Issue
Block a user