feat: modify frontend

Migration 0003 failed when rerank_models table already exists from create_all().
Add table existence check to prevent duplicate creation error in CI environments with cached database.

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -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://docs.langbot.app/zh/workshop/network-details.html  
+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  
 title: "[Bug]: "
 labels: ["bug?"]
 body:

.github/ISSUE_TEMPLATE/bug-report_en.yml

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

.github/workflows/build-release-artifacts.yaml

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

.github/workflows/check-i18n.yml

@@ -0,0 +1,25 @@
+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

.github/workflows/publish-to-pypi.yml

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

.github/workflows/test-migrations.yml

@@ -0,0 +1,171 @@
+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())
+          "

.gitignore

@@ -52,3 +52,6 @@ src/langbot/web/
 /dist
 /build
 *.egg-info
+
+# Next.js build cache (legacy)
+web/.next/

.pre-commit-config.yaml

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

AGENTS.md

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

Dockerfile

@@ -4,7 +4,7 @@ WORKDIR /app
 
 COPY web ./web
 
-RUN cd web && npm install && npm run build
+RUN cd web && npm install && npx vite build
 
 FROM python:3.12.7-slim
 
@@ -12,7 +12,7 @@ WORKDIR /app
 
 COPY . .
 
-COPY --from=node /app/web/out ./web/out
+COPY --from=node /app/web/dist ./web/dist
 
 RUN apt update \
     && apt install gcc -y \

README.md

@@ -19,9 +19,9 @@ English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Website</a> ｜
-<a href="https://docs.langbot.app/en/insight/features">Features</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Features</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Docs</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app/cloud">Cloud</a> ｜
 <a href="https://space.langbot.app">Plugin Market</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
@@ -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://docs.langbot.app/en/insight/features)
+[→ Learn more about all features](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -76,7 +76,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features)
+[→ View all integrations](https://link.langbot.app/en/docs/features)
 
 ---
 

README_CN.md

@@ -21,9 +21,9 @@
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 
 <a href="https://langbot.app">官网</a> ｜
-<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
-<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
-<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/zh/docs/features">特性</a> ｜
+<a href="https://link.langbot.app/zh/docs/guide">文档</a> ｜
+<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
 <a href="https://space.langbot.app/cloud">Cloud</a> ｜
 <a href="https://space.langbot.app">插件市场</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">路线图</a>
@@ -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://docs.langbot.app/zh/insight/features.html)
+[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
 
 ---
 
@@ -76,7 +76,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/zh/insight/features.html)
+[→ 查看完整集成列表](https://link.langbot.app/zh/docs/features)
 
 ### TTS（语音合成）
 

README_ES.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Inicio</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Características</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Características</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Documentación</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app">Mercado de Plugins</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Conocer más sobre todas las funcionalidades](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)
 
 ---
 

README_FR.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Accueil</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Fonctionnalités</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Documentation</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app">Marché des Plugins</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ En savoir plus sur toutes les fonctionnalités](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Voir toutes les intégrations](https://link.langbot.app/en/docs/features)
 
 ---
 

README_JP.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">ホーム</a> ｜
-<a href="https://docs.langbot.app/ja/insight/features.html">機能</a> ｜
-<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a> ｜
-<a href="https://docs.langbot.app/ja/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/ja/docs/features">機能</a> ｜
+<a href="https://link.langbot.app/ja/docs/guide">ドキュメント</a> ｜
+<a href="https://link.langbot.app/ja/docs/api">API</a> ｜
 <a href="https://space.langbot.app">プラグインマーケット</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
 
@@ -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://docs.langbot.app/ja/insight/features.html)
+[→ すべての機能について詳しく見る](https://link.langbot.app/ja/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**その他:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**その他:** [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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ すべての統合を表示](https://link.langbot.app/en/docs/features)
 
 ---
 

README_KO.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">홈</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">기능</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">문서</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">기능</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">문서</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app">플러그인 마켓</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">로드맵</a>
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ 모든 기능 자세히 보기](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ 모든 통합 보기](https://link.langbot.app/en/docs/features)
 
 ---
 

README_RU.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Главная</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Возможности</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Возможности</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Документация</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app">Магазин плагинов</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Подробнее обо всех возможностях](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Смотреть все интеграции](https://link.langbot.app/en/docs/features)
 
 ---
 

README_TW.md

@@ -21,9 +21,9 @@
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 
 <a href="https://langbot.app">官網</a> ｜
-<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
-<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a> ｜
-<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/zh/docs/features">特性</a> ｜
+<a href="https://link.langbot.app/zh/docs/guide">文件</a> ｜
+<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
 <a href="https://space.langbot.app">外掛市場</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">路線圖</a>
 
@@ -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://docs.langbot.app/zh/insight/features.html)
+[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
 
 ---
 
@@ -77,7 +77,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](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)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/zh/insight/features.html)
+[→ 查看完整整合列表](https://link.langbot.app/zh/docs/features)
 
 ---
 

README_VI.md

@@ -19,9 +19,9 @@
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Trang chủ</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Tính năng</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
+<a href="https://link.langbot.app/en/docs/features">Tính năng</a> ｜
+<a href="https://link.langbot.app/en/docs/guide">Tài liệu</a> ｜
+<a href="https://link.langbot.app/en/docs/api">API</a> ｜
 <a href="https://space.langbot.app">Chợ Plugin</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Tìm hiểu thêm về tất cả tính năng](https://link.langbot.app/en/docs/features)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+**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)
 
 ---
 
@@ -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://docs.langbot.app/en/insight/features.html)
+[→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)
 
 ---
 

docker/README_K8S.md

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

docker/docker-compose.yaml

@@ -34,4 +34,4 @@ services:
 
 networks:
   langbot_network:
-    driver: bridge
+    driver: bridge

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "langbot"
-version = "4.9.4"
+version = "4.9.6"
 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>=3.11.18",
+    "aiohttp>=3.13.4",
     "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>=44.0.3",
+    "cryptography>=46.0.7",
     "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>=11.2.1",
+    "pillow>=12.2.0",
     "psutil>=7.0.0",
     "pycryptodome>=3.22.0",
     "pydantic>2.0",
@@ -39,6 +39,7 @@ 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",
@@ -49,7 +50,7 @@ dependencies = [
     "pip>=25.1.1",
     "ruff>=0.11.9",
     "pre-commit>=4.2.0",
-    "uv>=0.7.11",
+    "uv>=0.11.6",
     "mypy>=1.16.0",
     "PyPDF2>=3.0.1",
     "python-docx>=1.1.0",
@@ -60,11 +61,15 @@ dependencies = [
     "ebooklib>=0.18",
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
-    "langchain-text-splitters>=0.0.1",
+    "langchain-core>=1.2.28",
+    "langsmith>=0.7.31",
+    "python-multipart>=0.0.26",
+    "Mako>=1.3.11",
+    "langchain-text-splitters>=1.1.2",
     "chromadb>=1.0.0,<2.0.0",
     "qdrant-client (>=1.15.1,<2.0.0)",
     "pyseekdb==1.1.0.post3",
-    "langbot-plugin==0.3.5",
+    "langbot-plugin==0.3.8",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
@@ -111,12 +116,12 @@ requires = ["setuptools>=61.0", "wheel"]
 build-backend = "setuptools.build_meta"
 
 [tool.setuptools]
-package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/out/**"] }
+package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/dist/**", "pkg/persistence/alembic/**"] }
 
 [dependency-groups]
 dev = [
     "pre-commit>=4.2.0",
-    "pytest>=8.4.1",
+    "pytest>=9.0.3",
     "pytest-asyncio>=1.0.0",
     "pytest-cov>=7.0.0",
     "ruff>=0.11.9",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
 """LangBot - Production-grade platform for building agentic IM bots"""
 
-__version__ = '4.9.4'
+__version__ = '4.9.6'

src/langbot/libs/dingtalk_api/api.py

@@ -182,6 +182,88 @@ 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))
@@ -193,6 +275,15 @@ 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()
 
@@ -268,19 +359,52 @@ class DingTalkClient:
 
                 message_data['Type'] = 'image'
             elif incoming_message.message_type == 'audio':
-                message_data['Audio'] = await self.get_audio_url(incoming_message.to_dict()['content']['downloadCode'])
+                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['Type'] = 'audio'
             elif incoming_message.message_type == 'file':
-                down_list = incoming_message.get_down_list()
-                if len(down_list) >= 2:
-                    message_data['File'] = await self.get_file_url(down_list[0])
-                    message_data['Name'] = down_list[1]
+                # 获取原始数据字典并提取嵌套的文件信息
+                raw_data = incoming_message.to_dict()
+                file_info = raw_data.get('content', {})
+
+                # 兼容处理：如果 content 仍为 JSON 字符串则进行解析
+                if isinstance(file_info, str):
+                    try:
+                        file_info = json.loads(file_info)
+                    except (json.JSONDecodeError, TypeError):
+                        file_info = {}
+
+                download_code = file_info.get('downloadCode')
+                file_name = file_info.get('fileName')
+
+                if download_code and file_name:
+                    # 转换 downloadCode 为可下载的真实 URL
+                    message_data['File'] = await self.get_file_url(download_code)
+                    message_data['Name'] = file_name
                 else:
                     if self.logger:
-                        await self.logger.error(f'get_down_list() returned fewer than 2 elements: {down_list}')
+                        await self.logger.error(f'Failed to extract file info from message content: {file_info}')
                     message_data['File'] = None
                     message_data['Name'] = None
+
                 message_data['Type'] = 'file'
 
             copy_message_data = message_data.copy()

src/langbot/libs/dingtalk_api/dingtalkevent.py

@@ -47,6 +47,22 @@ 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。

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -6,7 +6,8 @@ import traceback
 import uuid
 import xml.etree.ElementTree as ET
 from dataclasses import dataclass, field
-from typing import Any, Callable, Optional
+import re
+from typing import Any, Callable, Optional, Tuple
 from urllib.parse import unquote
 
 import httpx
@@ -63,16 +64,25 @@ class StreamSession:
     # 缓存最近一次片段，处理重试或超时兜底
     last_chunk: Optional[StreamChunk] = None
 
+    # 反馈 ID，用于接收用户点赞/点踩反馈
+    feedback_id: Optional[str] = None
+
 
 class StreamSessionManager:
     """管理 stream 会话的生命周期，并负责队列的生产消费。"""
 
+    # Sessions with registered feedback_ids use a longer TTL to survive the
+    # full like → cancel → dislike feedback flow. Must align with the adapter's
+    # _stream_to_monitoring_msg TTL (wecombot.py).
+    _FEEDBACK_SESSION_TTL = 600  # 10 minutes
+
     def __init__(self, logger: EventLogger, ttl: int = 60) -> None:
         self.logger = logger
 
         self.ttl = ttl  # 超时时间（秒），超过该时间未被访问的会话会被清理由 cleanup
         self._sessions: dict[str, StreamSession] = {}  # stream_id -> StreamSession 映射
         self._msg_index: dict[str, str] = {}  # msgid -> stream_id 映射，便于流水线根据消息 ID 找到会话
+        self._feedback_index: dict[str, str] = {}  # feedback_id -> stream_id 映射
 
     def get_stream_id_by_msg(self, msg_id: str) -> Optional[str]:
         if not msg_id:
@@ -82,6 +92,32 @@ class StreamSessionManager:
     def get_session(self, stream_id: str) -> Optional[StreamSession]:
         return self._sessions.get(stream_id)
 
+    def get_session_by_feedback_id(self, feedback_id: str) -> Optional[StreamSession]:
+        """根据 feedback_id 查找会话。
+
+        Args:
+            feedback_id: 企业微信反馈事件中的反馈 ID。
+
+        Returns:
+            Optional[StreamSession]: 找到的会话实例，未找到返回 None。
+        """
+        if not feedback_id:
+            return None
+        stream_id = self._feedback_index.get(feedback_id)
+        if stream_id:
+            return self._sessions.get(stream_id)
+        return None
+
+    def register_feedback_id(self, stream_id: str, feedback_id: str) -> None:
+        """注册 feedback_id 与 stream_id 的映射。
+
+        Args:
+            stream_id: 企业微信流式会话 ID。
+            feedback_id: 反馈 ID。
+        """
+        if feedback_id and stream_id:
+            self._feedback_index[feedback_id] = stream_id
+
     def create_or_get(self, msg_json: dict[str, Any]) -> tuple[StreamSession, bool]:
         """根据企业微信回调创建或获取会话。
 
@@ -183,11 +219,17 @@ 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。"""
+        """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。
+        """
         now = time.time()
         expired: list[str] = []
         for stream_id, session in self._sessions.items():
-            if now - session.last_access > self.ttl:
+            # 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:
                 expired.append(stream_id)
 
         for stream_id in expired:
@@ -197,54 +239,144 @@ 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)
 
 
-async def download_encrypted_file(download_url: str, encoding_aes_key: str, logger: EventLogger) -> Optional[str]:
-    """Download an AES-encrypted file from WeChat Work and return as data URI.
+def _decrypt_file(encrypted_data: bytes, aes_key_str: str) -> bytes:
+    """Decrypt AES-256-CBC encrypted file data.
+
+    Aligned with the official WeCom AI Bot Python SDK (crypto_utils.py).
 
     Args:
-        download_url: The encrypted file download URL.
-        encoding_aes_key: The AES key used for decryption (base64-encoded, without trailing '=').
-        logger: Logger instance.
+        encrypted_data: The raw encrypted bytes.
+        aes_key_str: Base64-encoded AES key (may lack padding).
 
     Returns:
-        A data URI string (e.g. 'data:image/jpeg;base64,...') or None on failure.
+        Decrypted bytes with PKCS#7 padding removed.
     """
-    if not download_url:
-        return None
-    async with httpx.AsyncClient() as client:
-        response = await client.get(download_url)
-        if response.status_code != 200:
-            await logger.error(f'failed to get file: {response.text}')
-            return None
-        encrypted_bytes = response.content
+    if not encrypted_data:
+        raise ValueError('encrypted_data is empty')
+    if not aes_key_str:
+        raise ValueError('aes_key is empty')
 
-    aes_key = base64.b64decode(encoding_aes_key + '=')
-    iv = aes_key[:16]
+    # Python's base64.b64decode requires proper padding (length % 4 == 0).
+    # Node.js Buffer.from tolerates missing '=', so we must pad manually.
+    remainder = len(aes_key_str) % 4
+    if remainder != 0:
+        aes_key_str = aes_key_str + '=' * (4 - remainder)
+    key = base64.b64decode(aes_key_str)
 
-    cipher = AES.new(aes_key, AES.MODE_CBC, iv)
-    decrypted = cipher.decrypt(encrypted_bytes)
+    iv = key[:16]
+
+    cipher = AES.new(key, AES.MODE_CBC, iv)
+
+    # Ensure encrypted data is aligned to AES block size (16 bytes).
+    # Node.js setAutoPadding(false) silently handles unaligned data,
+    # but PyCryptodome will raise an error.
+    block_size = 16
+    data_remainder = len(encrypted_data) % block_size
+    if data_remainder != 0:
+        encrypted_data = encrypted_data + b'\x00' * (block_size - data_remainder)
+
+    decrypted = cipher.decrypt(encrypted_data)
+
+    # Remove PKCS#7 padding with validation
+    if len(decrypted) == 0:
+        raise ValueError('Decrypted data is empty')
 
     pad_len = decrypted[-1]
-    decrypted = decrypted[:-pad_len]
+    if pad_len < 1 or pad_len > 32 or pad_len > len(decrypted):
+        raise ValueError(f'Invalid PKCS#7 padding value: {pad_len}')
 
-    if decrypted.startswith(b'\xff\xd8'):
+    # Verify all padding bytes are consistent
+    for i in range(len(decrypted) - pad_len, len(decrypted)):
+        if decrypted[i] != pad_len:
+            raise ValueError('Invalid PKCS#7 padding: padding bytes mismatch')
+
+    return decrypted[: len(decrypted) - pad_len]
+
+
+def _extract_filename(content_disposition: str) -> Optional[str]:
+    """Extract filename from a Content-Disposition header value."""
+    if not content_disposition:
+        return None
+    # RFC 5987: filename*=UTF-8''xxx
+    utf8_match = re.search(r"filename\*=UTF-8''([^;\s]+)", content_disposition, re.IGNORECASE)
+    if utf8_match:
+        return unquote(utf8_match.group(1))
+    # Standard: filename="xxx" or filename=xxx
+    match = re.search(r'filename="?([^";\s]+)"?', content_disposition, re.IGNORECASE)
+    if match:
+        return unquote(match.group(1))
+    return None
+
+
+def _bytes_to_data_uri(data: bytes) -> str:
+    """Convert raw bytes to a data URI with auto-detected MIME type."""
+    if data.startswith(b'\xff\xd8'):
         mime_type = 'image/jpeg'
-    elif decrypted.startswith(b'\x89PNG'):
+    elif data.startswith(b'\x89PNG'):
         mime_type = 'image/png'
-    elif decrypted.startswith((b'GIF87a', b'GIF89a')):
+    elif data.startswith((b'GIF87a', b'GIF89a')):
         mime_type = 'image/gif'
-    elif decrypted.startswith(b'BM'):
+    elif data.startswith(b'BM'):
         mime_type = 'image/bmp'
-    elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'):
+    elif data.startswith(b'II*\x00') or data.startswith(b'MM\x00*'):
         mime_type = 'image/tiff'
+    elif data[:4] == b'%PDF':
+        mime_type = 'application/pdf'
+    elif data[:4] == b'PK\x03\x04':
+        mime_type = 'application/zip'
     else:
         mime_type = 'application/octet-stream'
 
-    base64_str = base64.b64encode(decrypted).decode('utf-8')
+    base64_str = base64.b64encode(data).decode('utf-8')
     return f'data:{mime_type};base64,{base64_str}'
 
 
+async def download_encrypted_file(
+    download_url: str, aes_key: str, logger: EventLogger
+) -> Tuple[Optional[bytes], Optional[str]]:
+    """Download an AES-encrypted file from WeChat Work and decrypt it.
+
+    Args:
+        download_url: The encrypted file download URL.
+        aes_key: The AES key for decryption (base64-encoded, per-message aeskey
+                 or platform EncodingAESKey).
+        logger: Logger instance.
+
+    Returns:
+        A tuple of (decrypted_bytes, filename) or (None, None) on failure.
+    """
+    if not download_url:
+        return None, None
+    if not aes_key:
+        await logger.error('download_encrypted_file: aes_key is empty, cannot decrypt')
+        return None, None
+
+    filename: Optional[str] = None
+    try:
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            response = await client.get(download_url)
+            if response.status_code != 200:
+                await logger.error(f'Failed to download file (HTTP {response.status_code}): {response.text[:200]}')
+                return None, None
+            encrypted_bytes = response.content
+            filename = _extract_filename(response.headers.get('content-disposition', ''))
+    except Exception:
+        await logger.error(f'Failed to download file: {traceback.format_exc()}')
+        return None, None
+
+    try:
+        decrypted = _decrypt_file(encrypted_bytes, aes_key)
+        return decrypted, filename
+    except Exception:
+        await logger.error(f'Failed to decrypt file: {traceback.format_exc()}')
+        return None, None
+
+
 async def parse_wecom_bot_message(
     msg_json: dict[str, Any], encoding_aes_key: str, logger: EventLogger
 ) -> dict[str, Any]:
@@ -273,10 +405,22 @@ async def parse_wecom_bot_message(
 
     max_inline_file_size = 5 * 1024 * 1024
 
-    async def _safe_download(url: str):
+    async def _safe_download(url: str, per_msg_aeskey: str = '') -> Tuple[Optional[bytes], Optional[str]]:
+        """Download and decrypt a file, preferring per-message aeskey over platform key."""
         if not url:
-            return None
-        return await download_encrypted_file(url, encoding_aes_key, logger)
+            return None, None
+        key = per_msg_aeskey or encoding_aes_key
+        if not key:
+            await logger.warning('No AES key available for file decryption, skipping download')
+            return None, None
+        return await download_encrypted_file(url, key, logger)
+
+    async def _safe_download_as_data_uri(url: str, per_msg_aeskey: str = '') -> Optional[str]:
+        """Download, decrypt, and convert to data URI for backward compatibility."""
+        data, _filename = await _safe_download(url, per_msg_aeskey)
+        if data:
+            return _bytes_to_data_uri(data)
+        return None
 
     if msg_type == 'text':
         message_data['content'] = msg_json.get('text', {}).get('content')
@@ -285,14 +429,17 @@ async def parse_wecom_bot_message(
             'content', ''
         )
     elif msg_type == 'image':
-        picurl = msg_json.get('image', {}).get('url', '')
-        base64_data = await _safe_download(picurl)
+        image_info = msg_json.get('image', {})
+        picurl = image_info.get('url', '')
+        per_msg_aeskey = image_info.get('aeskey', '')
+        base64_data = await _safe_download_as_data_uri(picurl, per_msg_aeskey)
         if base64_data:
             message_data['picurl'] = base64_data
             message_data['images'] = [base64_data]
     elif msg_type == 'voice':
         voice_info = msg_json.get('voice', {}) or {}
         download_url = voice_info.get('url')
+        per_msg_aeskey = voice_info.get('aeskey', '')
         message_data['voice'] = {
             'url': download_url,
             'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
@@ -301,13 +448,14 @@ 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(download_url)
-            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')
+        per_msg_aeskey = video_info.get('aeskey', '')
         video_data = {
             'url': download_url,
             'filesize': video_info.get('filesize') or video_info.get('size'),
@@ -315,14 +463,17 @@ 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(download_url)
-            if video_base64:
-                video_data['base64'] = video_base64
+        # if (video_data.get('filesize') or 0) <= max_inline_file_size:
+        #     video_base64 = await _safe_download_as_data_uri(download_url, per_msg_aeskey)
+        #     if video_base64:
+        #         video_data['base64'] = video_base64
+        # 应为需要解密，但是目前暂时不能下载到内部进行解密，所以先将下载链接拼接aeskey返回给用户，由插件去处理该链接的下载和解密逻辑
+        video_data['download_url'] = download_url + f'?aeskey={per_msg_aeskey}'
         message_data['video'] = video_data
     elif msg_type == 'file':
         file_info = msg_json.get('file', {}) or {}
         download_url = file_info.get('url') or file_info.get('fileurl')
+        per_msg_aeskey = file_info.get('aeskey', '')
         file_data = {
             'filename': file_info.get('filename') or file_info.get('name'),
             'filesize': file_info.get('filesize') or file_info.get('size'),
@@ -331,10 +482,15 @@ 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_base64 = await _safe_download(download_url)
-            if file_base64:
-                file_data['base64'] = file_base64
+        # if (file_data.get('filesize') or 0) <= max_inline_file_size:
+        #     file_bytes, dl_filename = await _safe_download(download_url, per_msg_aeskey)
+        #     if file_bytes:
+        #         file_data['base64'] = _bytes_to_data_uri(file_bytes)
+        #         if dl_filename and not file_data.get('filename'):
+        #             file_data['filename'] = dl_filename
+
+        # 应为需要解密，但是目前暂时不能下载到内部进行解密，所以先将下载链接拼接aeskey返回给用户，由插件去处理该链接的下载和解密逻辑
+        file_data['download_url'] = download_url + f'?aeskey={per_msg_aeskey}'
         message_data['file'] = file_data
     elif msg_type == 'link':
         message_data['link'] = msg_json.get('link', {})
@@ -355,13 +511,16 @@ async def parse_wecom_bot_message(
             if item_type == 'text':
                 texts.append(item.get('text', {}).get('content', ''))
             elif item_type == 'image':
-                img_url = item.get('image', {}).get('url')
-                base64_data = await _safe_download(img_url)
+                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'),
@@ -371,13 +530,16 @@ async def parse_wecom_bot_message(
                     'extra': file_info,
                 }
                 if (file_data.get('filesize') or 0) <= max_inline_file_size:
-                    file_base64 = await _safe_download(download_url)
-                    if file_base64:
-                        file_data['base64'] = file_base64
+                    file_bytes, dl_filename = await _safe_download(download_url, item_aeskey)
+                    if file_bytes:
+                        file_data['base64'] = _bytes_to_data_uri(file_bytes)
+                        if dl_filename and not file_data.get('filename'):
+                            file_data['filename'] = dl_filename
                 files.append(file_data)
             elif item_type == 'voice':
                 voice_info = item.get('voice', {}) or {}
                 download_url = voice_info.get('url')
+                item_aeskey = voice_info.get('aeskey', '')
                 voice_data = {
                     'url': download_url,
                     'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
@@ -387,13 +549,14 @@ async def parse_wecom_bot_message(
                 if voice_info.get('content'):
                     texts.append(voice_info.get('content'))
                 if (voice_data.get('filesize') or 0) <= max_inline_file_size:
-                    voice_base64 = await _safe_download(download_url)
+                    voice_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
                     if voice_base64:
                         voice_data['base64'] = voice_base64
                 voices.append(voice_data)
             elif item_type == 'video':
                 video_info = item.get('video', {}) or {}
                 download_url = video_info.get('url')
+                item_aeskey = video_info.get('aeskey', '')
                 video_data = {
                     'url': download_url,
                     'filesize': video_info.get('filesize') or video_info.get('size'),
@@ -402,7 +565,7 @@ async def parse_wecom_bot_message(
                     'filename': video_info.get('filename') or video_info.get('name'),
                 }
                 if (video_data.get('filesize') or 0) <= max_inline_file_size:
-                    video_base64 = await _safe_download(download_url)
+                    video_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
                     if video_base64:
                         video_data['base64'] = video_base64
                 videos.append(video_data)
@@ -443,6 +606,120 @@ 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
 
 
@@ -483,14 +760,27 @@ class WecomBotClient:
         self.stream_sessions = StreamSessionManager(logger=logger)
         self.stream_poll_timeout = 0.5
 
+        self._feedback_callback: Optional[Callable] = None
+
+    def set_feedback_callback(self, callback: Callable) -> None:
+        """设置反馈回调函数。
+
+        Args:
+            callback: 反馈回调函数，签名: async def callback(feedback_id, feedback_type, feedback_content, inaccurate_reasons, session)
+        """
+        self._feedback_callback = callback
+
     @staticmethod
-    def _build_stream_payload(stream_id: str, content: str, finish: bool) -> dict[str, Any]:
+    def _build_stream_payload(
+        stream_id: str, content: str, finish: bool, feedback_id: Optional[str] = None
+    ) -> dict[str, Any]:
         """按照企业微信协议拼装返回报文。
 
         Args:
             stream_id: 企业微信会话 ID。
             content: 推送的文本内容。
             finish: 是否为最终片段。
+            feedback_id: 反馈 ID，用于接收用户点赞/点踩反馈。
 
         Returns:
             dict[str, Any]: 可直接加密返回的 payload。
@@ -498,13 +788,16 @@ class WecomBotClient:
         Example:
             组装 `{'msgtype': 'stream', 'stream': {'id': 'sid', ...}}` 结构。
         """
+        stream_payload = {
+            'id': stream_id,
+            'finish': finish,
+            'content': content,
+        }
+        if feedback_id:
+            stream_payload['feedback'] = {'id': feedback_id}
         return {
             'msgtype': 'stream',
-            'stream': {
-                'id': stream_id,
-                'finish': finish,
-                'content': content,
-            },
+            'stream': stream_payload,
         }
 
     async def _encrypt_and_reply(self, payload: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -560,9 +853,14 @@ class WecomBotClient:
         """
         session, is_new = self.stream_sessions.create_or_get(msg_json)
 
+        feedback_id = str(uuid.uuid4())
+        session.feedback_id = feedback_id
+        self.stream_sessions.register_feedback_id(session.stream_id, feedback_id)
+
         message_data = await self.get_message(msg_json)
         if message_data:
             message_data['stream_id'] = session.stream_id
+            message_data['feedback_id'] = feedback_id
             try:
                 event = wecombotevent.WecomBotEvent(message_data)
             except Exception:
@@ -571,7 +869,7 @@ class WecomBotClient:
                 if is_new:
                     asyncio.create_task(self._dispatch_event(event))
 
-        payload = self._build_stream_payload(session.stream_id, '', False)
+        payload = self._build_stream_payload(session.stream_id, '', False, feedback_id)
         return await self._encrypt_and_reply(payload, nonce)
 
     async def _handle_post_followup_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -696,11 +994,81 @@ class WecomBotClient:
 
         msg_json = json.loads(decrypted_xml)
 
+        event = msg_json.get('event', {})
+        event_type = event.get('eventtype', '')
+
+        if event_type == 'feedback_event':
+            return await self._handle_feedback_event(msg_json, nonce)
+
         if msg_json.get('msgtype') == 'stream':
             return await self._handle_post_followup_response(msg_json, nonce)
 
         return await self._handle_post_initial_response(msg_json, nonce)
 
+    async def _handle_feedback_event(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
+        """处理企业微信用户反馈事件（点赞/点踩）。
+
+        Args:
+            msg_json: 解密后的企业微信反馈事件 JSON。
+            nonce: 企业微信回调参数 nonce。
+
+        Returns:
+            Tuple[Response, int]: Quart Response 及状态码。
+
+        Note:
+            企业微信协议要求：反馈事件目前仅支持回复空包。
+        """
+        try:
+            feedback_event = msg_json.get('event', {}).get('feedback_event', {})
+            feedback_id = feedback_event.get('id', '')
+            feedback_type = feedback_event.get('type', 0)
+            feedback_content = feedback_event.get('content', '')
+            inaccurate_reasons = feedback_event.get('inaccurate_reason_list', [])
+
+            await self.logger.info(
+                f'收到用户反馈事件: feedback_id={feedback_id}, type={feedback_type}, '
+                f'content={feedback_content}, reasons={inaccurate_reasons}'
+            )
+
+            session = self.stream_sessions.get_session_by_feedback_id(feedback_id)
+
+            if session:
+                await self.logger.info(
+                    f'反馈关联到会话: stream_id={session.stream_id}, msg_id={session.msg_id}, user_id={session.user_id}'
+                )
+            else:
+                await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话，仍将记录反馈')
+
+            # Dispatch feedback event regardless of session availability
+            for handler in self._message_handlers.get('feedback', []):
+                try:
+                    await handler(
+                        feedback_id=feedback_id,
+                        feedback_type=feedback_type,
+                        feedback_content=feedback_content,
+                        inaccurate_reasons=inaccurate_reasons,
+                        session=session,
+                    )
+                except Exception:
+                    await self.logger.error(traceback.format_exc())
+
+            if self._feedback_callback:
+                try:
+                    await self._feedback_callback(
+                        feedback_id=feedback_id,
+                        feedback_type=feedback_type,
+                        feedback_content=feedback_content,
+                        inaccurate_reasons=inaccurate_reasons,
+                        session=session,
+                    )
+                except Exception:
+                    await self.logger.error(traceback.format_exc())
+
+        except Exception:
+            await self.logger.error(traceback.format_exc())
+
+        return await self._encrypt_and_reply({}, nonce)
+
     async def get_message(self, msg_json):
         return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
 
@@ -769,8 +1137,20 @@ class WecomBotClient:
 
         return decorator
 
+    def on_feedback(self):
+        def decorator(func: Callable):
+            if 'feedback' not in self._message_handlers:
+                self._message_handlers['feedback'] = []
+            self._message_handlers['feedback'].append(func)
+            return func
+
+        return decorator
+
     async def download_url_to_base64(self, download_url, encoding_aes_key):
-        return await download_encrypted_file(download_url, encoding_aes_key, self.logger)
+        data, _filename = await download_encrypted_file(download_url, encoding_aes_key, self.logger)
+        if data:
+            return _bytes_to_data_uri(data)
+        return None
 
     async def run_task(self, host: str, port: int, *args, **kwargs):
         """

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

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

src/langbot/libs/wecom_ai_bot_api/ws_client.py

@@ -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
+from langbot.libs.wecom_ai_bot_api.api import parse_wecom_bot_message, StreamSession
 from langbot.pkg.platform.logger import EventLogger
 
 DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
@@ -96,6 +96,12 @@ 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 ──────────────────────────────────────────────────
 
@@ -164,12 +170,27 @@ 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.
 
@@ -178,17 +199,22 @@ 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': {
-                'id': stream_id,
-                'finish': finish,
-                'content': content,
-            },
+            'stream': stream_payload,
         }
         return await self._send_reply(req_id, body)
 
@@ -253,11 +279,23 @@ 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
-            await self.reply_stream(req_id, stream_id, content, finish=is_final)
+
+            # Generate feedback_id for final chunk
+            feedback_id = ''
+            if is_final:
+                feedback_id = _generate_req_id('feedback')
+                self._msg_feedback_ids[msg_id] = feedback_id
+                # Store session info for feedback tracking
+                session_info = self._stream_sessions.get(msg_id)
+                if session_info:
+                    self._feedback_sessions[feedback_id] = session_info
+
+            await self.reply_stream(req_id, stream_id, content, finish=is_final, feedback_id=feedback_id)
             self._stream_last_content[msg_id] = content
             if is_final:
                 self._stream_ids.pop(msg_id, None)
                 self._stream_last_content.pop(msg_id, None)
+                self._stream_sessions.pop(msg_id, None)
             return True
         except Exception:
             await self.logger.error(f'Failed to push stream chunk: {traceback.format_exc()}')
@@ -445,6 +483,15 @@ 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
 
@@ -454,7 +501,7 @@ 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, etc.)."""
+        """Handle an incoming event callback frame (enter_chat, template_card_event, feedback_event, disconnected_event)."""
         try:
             body = frame.get('body', {})
             req_id = frame.get('headers', {}).get('req_id', '')
@@ -479,14 +526,54 @@ 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)

src/langbot/pkg/api/http/controller/groups/monitoring.py

@@ -456,6 +456,31 @@ class MonitoringRouterGroup(group.RouterGroup):
                     'platform',
                     'user_id',
                 ]
+            elif export_type == 'feedback':
+                data = await self.ap.monitoring_service.export_feedback(
+                    bot_ids=bot_ids if bot_ids else None,
+                    pipeline_ids=pipeline_ids if pipeline_ids else None,
+                    start_time=start_time,
+                    end_time=end_time,
+                    limit=limit,
+                )
+                headers = [
+                    'id',
+                    'timestamp',
+                    'feedback_id',
+                    'feedback_type',
+                    'feedback_content',
+                    'inaccurate_reasons',
+                    'bot_id',
+                    'bot_name',
+                    'pipeline_id',
+                    'pipeline_name',
+                    'session_id',
+                    'message_id',
+                    'stream_id',
+                    'user_id',
+                    'platform',
+                ]
             else:
                 return self.error(message=f'Invalid export type: {export_type}', code=400)
 
@@ -486,3 +511,63 @@ class MonitoringRouterGroup(group.RouterGroup):
             )
 
             return response, 200
+
+        @self.route('/feedback/stats', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def get_feedback_stats() -> str:
+            """Get feedback statistics"""
+            # Parse query parameters
+            bot_ids = quart.request.args.getlist('botId')
+            pipeline_ids = quart.request.args.getlist('pipelineId')
+            start_time_str = quart.request.args.get('startTime')
+            end_time_str = quart.request.args.get('endTime')
+
+            # Parse datetime
+            start_time = parse_iso_datetime(start_time_str)
+            end_time = parse_iso_datetime(end_time_str)
+
+            stats = await self.ap.monitoring_service.get_feedback_stats(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                start_time=start_time,
+                end_time=end_time,
+            )
+
+            return self.success(data=stats)
+
+        @self.route('/feedback', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def get_feedback() -> str:
+            """Get feedback list"""
+            # Parse query parameters
+            bot_ids = quart.request.args.getlist('botId')
+            pipeline_ids = quart.request.args.getlist('pipelineId')
+            feedback_type_str = quart.request.args.get('feedbackType')
+            start_time_str = quart.request.args.get('startTime')
+            end_time_str = quart.request.args.get('endTime')
+            limit = int(quart.request.args.get('limit', 100))
+            offset = int(quart.request.args.get('offset', 0))
+
+            # Parse datetime
+            start_time = parse_iso_datetime(start_time_str)
+            end_time = parse_iso_datetime(end_time_str)
+
+            # Parse feedback type
+            feedback_type = int(feedback_type_str) if feedback_type_str else None
+
+            feedback_list, total = await self.ap.monitoring_service.get_feedback_list(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                feedback_type=feedback_type,
+                start_time=start_time,
+                end_time=end_time,
+                limit=limit,
+                offset=offset,
+            )
+
+            return self.success(
+                data={
+                    'feedback': feedback_list,
+                    'total': total,
+                    'limit': limit,
+                    'offset': offset,
+                }
+            )

src/langbot/pkg/api/http/controller/groups/plugins.py

@@ -265,6 +265,8 @@ class PluginsRouterGroup(group.RouterGroup):
                 return self.http_status(400, -1, 'Missing asset_url parameter')
 
             ctx = taskmgr.TaskContext.new()
+            ctx.metadata['plugin_name'] = f'{owner}/{repo}'
+            ctx.metadata['install_source'] = 'github'
             install_info = {
                 'asset_url': asset_url,
                 'owner': owner,
@@ -295,12 +297,17 @@ class PluginsRouterGroup(group.RouterGroup):
 
             data = await quart.request.json
 
+            plugin_author = data.get('plugin_author', '')
+            plugin_name = data.get('plugin_name', '')
+
             ctx = taskmgr.TaskContext.new()
+            ctx.metadata['plugin_name'] = f'{plugin_author}/{plugin_name}'
+            ctx.metadata['install_source'] = 'marketplace'
             wrapper = self.ap.task_mgr.create_user_task(
                 self.ap.plugin_connector.install_plugin(PluginInstallSource.MARKETPLACE, data, task_context=ctx),
                 kind='plugin-operation',
                 name='plugin-install-marketplace',
-                label=f'Installing plugin from marketplace ...{data}',
+                label=f'Installing plugin from marketplace {plugin_author}/{plugin_name}',
                 context=ctx,
             )
 
@@ -323,11 +330,13 @@ class PluginsRouterGroup(group.RouterGroup):
             }
 
             ctx = taskmgr.TaskContext.new()
+            ctx.metadata['plugin_name'] = file.filename or 'local plugin'
+            ctx.metadata['install_source'] = 'local'
             wrapper = self.ap.task_mgr.create_user_task(
                 self.ap.plugin_connector.install_plugin(PluginInstallSource.LOCAL, data, task_context=ctx),
                 kind='plugin-operation',
                 name='plugin-install-local',
-                label=f'Installing plugin from local ...{file.filename}',
+                label=f'Installing plugin from local {file.filename}',
                 context=ctx,
             )
 

src/langbot/pkg/api/http/controller/groups/provider/models.py

@@ -97,3 +97,51 @@ 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()

src/langbot/pkg/api/http/controller/groups/provider/providers.py

@@ -15,6 +15,7 @@ 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
@@ -32,6 +33,7 @@ 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
@@ -43,3 +45,12 @@ 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))

src/langbot/pkg/api/http/controller/groups/resources/tools.py

@@ -0,0 +1,45 @@
+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}')

src/langbot/pkg/api/http/controller/groups/system.py

@@ -1,7 +1,11 @@
+import json
+
 import quart
+import sqlalchemy
 
 from .. import group
 from .....utils import constants
+from .....entity.persistence.metadata import Metadata
 
 
 @group.group_class('system', '/api/v1/system')
@@ -9,6 +13,24 @@ class SystemRouterGroup(group.RouterGroup):
     async def initialize(self) -> None:
         @self.route('/info', methods=['GET'], auth_type=group.AuthType.NONE)
         async def _() -> str:
+            # Read wizard_status and wizard_progress from metadata table
+            wizard_status = 'none'
+            wizard_progress = None
+            try:
+                result = await self.ap.persistence_mgr.execute_async(
+                    sqlalchemy.select(Metadata).where(Metadata.key.in_(['wizard_status', 'wizard_progress']))
+                )
+                for row in result:
+                    if row.key == 'wizard_status':
+                        wizard_status = row.value
+                    elif row.key == 'wizard_progress':
+                        try:
+                            wizard_progress = json.loads(row.value)
+                        except (json.JSONDecodeError, TypeError):
+                            wizard_progress = None
+            except Exception:
+                pass
+
             return self.success(
                 data={
                     'version': constants.semantic_version,
@@ -27,17 +49,83 @@ class SystemRouterGroup(group.RouterGroup):
                         'disable_models_service', False
                     ),
                     'limitation': self.ap.instance_config.data.get('system', {}).get('limitation', {}),
+                    'wizard_status': wizard_status,
+                    'wizard_progress': wizard_progress,
                 }
             )
 
+        @self.route('/wizard/completed', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
+        async def _() -> str:
+            """Mark wizard status in metadata table and clear progress.
+
+            Accepts JSON body: { "status": "skipped" | "completed" }
+            """
+            data = await quart.request.get_json(silent=True) or {}
+            status = data.get('status', 'completed')
+            if status not in ('skipped', 'completed'):
+                return self.http_status(400, 400, f'Invalid wizard status: {status}')
+
+            try:
+                result = await self.ap.persistence_mgr.execute_async(
+                    sqlalchemy.select(Metadata).where(Metadata.key == 'wizard_status')
+                )
+                if result.first():
+                    await self.ap.persistence_mgr.execute_async(
+                        sqlalchemy.update(Metadata).where(Metadata.key == 'wizard_status').values(value=status)
+                    )
+                else:
+                    await self.ap.persistence_mgr.execute_async(
+                        sqlalchemy.insert(Metadata).values(key='wizard_status', value=status)
+                    )
+
+                # Clear wizard progress when wizard is completed/skipped
+                await self.ap.persistence_mgr.execute_async(
+                    sqlalchemy.delete(Metadata).where(Metadata.key == 'wizard_progress')
+                )
+            except Exception as e:
+                return self.http_status(500, 500, f'Failed to update wizard status: {e}')
+
+            return self.success(data={})
+
+        @self.route('/wizard/progress', methods=['PUT'], auth_type=group.AuthType.USER_TOKEN)
+        async def _() -> str:
+            """Save wizard progress to metadata table.
+
+            Accepts JSON body with wizard state fields:
+            { "step": int, "selected_adapter": str|null, "created_bot_uuid": str|null,
+              "bot_saved": bool, "selected_runner": str|null }
+            """
+            data = await quart.request.get_json(silent=True) or {}
+            progress_json = json.dumps(data, ensure_ascii=False)
+
+            try:
+                result = await self.ap.persistence_mgr.execute_async(
+                    sqlalchemy.select(Metadata).where(Metadata.key == 'wizard_progress')
+                )
+                if result.first():
+                    await self.ap.persistence_mgr.execute_async(
+                        sqlalchemy.update(Metadata).where(Metadata.key == 'wizard_progress').values(value=progress_json)
+                    )
+                else:
+                    await self.ap.persistence_mgr.execute_async(
+                        sqlalchemy.insert(Metadata).values(key='wizard_progress', value=progress_json)
+                    )
+            except Exception as e:
+                return self.http_status(500, 500, f'Failed to save wizard progress: {e}')
+
+            return self.success(data={})
+
         @self.route('/tasks', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _() -> str:
             task_type = quart.request.args.get('type')
+            task_kind = quart.request.args.get('kind')
 
             if task_type == '':
                 task_type = None
+            if task_kind == '':
+                task_kind = None
 
-            return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type))
+            return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type, task_kind))
 
         @self.route('/tasks/<task_id>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _(task_id: str) -> str:

src/langbot/pkg/api/http/controller/main.py

@@ -105,6 +105,29 @@ class HTTPController:
             ):
                 if os.path.exists(os.path.join(frontend_path, path + '.html')):
                     path += '.html'
+                elif not path.startswith('api/'):
+                    # SPA fallback: serve index.html for all non-API, non-static routes
+                    # so that React Router can handle client-side routing (Vite SPA).
+                    # For /home/* sub-routes, first try parent .html files (pre-rendered pages).
+                    if path.startswith('home/'):
+                        segments = path.rstrip('/').split('/')
+                        for i in range(len(segments) - 1, 0, -1):
+                            parent_path = '/'.join(segments[:i]) + '.html'
+                            if os.path.exists(os.path.join(frontend_path, parent_path)):
+                                response = await quart.send_from_directory(
+                                    frontend_path, parent_path, mimetype='text/html'
+                                )
+                                response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
+                                response.headers['Pragma'] = 'no-cache'
+                                response.headers['Expires'] = '0'
+                                return response
+
+                    # Fallback to index.html for SPA client-side routing
+                    response = await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
+                    response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
+                    response.headers['Pragma'] = 'no-cache'
+                    response.headers['Expires'] = '0'
+                    return response
                 else:
                     return await quart.send_from_directory(frontend_path, '404.html')
 

src/langbot/pkg/api/http/service/model.py

@@ -367,3 +367,162 @@ 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.',
+            ],
+        )

src/langbot/pkg/api/http/service/monitoring.py

@@ -16,6 +16,57 @@ class MonitoringService:
     def __init__(self, ap: app.Application) -> None:
         self.ap = ap
 
+    # ========== Cleanup Methods ==========
+
+    async def cleanup_expired_records(self, retention_days: int) -> dict[str, int]:
+        """Delete monitoring records older than the specified retention period.
+
+        Args:
+            retention_days: Number of days to retain records.
+
+        Returns:
+            A dict mapping table name to the number of deleted rows.
+        """
+        cutoff = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) - datetime.timedelta(
+            days=retention_days
+        )
+
+        tables_and_columns: list[tuple[str, type, sqlalchemy.Column]] = [
+            (
+                'monitoring_messages',
+                persistence_monitoring.MonitoringMessage,
+                persistence_monitoring.MonitoringMessage.timestamp,
+            ),
+            (
+                'monitoring_llm_calls',
+                persistence_monitoring.MonitoringLLMCall,
+                persistence_monitoring.MonitoringLLMCall.timestamp,
+            ),
+            (
+                'monitoring_embedding_calls',
+                persistence_monitoring.MonitoringEmbeddingCall,
+                persistence_monitoring.MonitoringEmbeddingCall.timestamp,
+            ),
+            (
+                'monitoring_errors',
+                persistence_monitoring.MonitoringError,
+                persistence_monitoring.MonitoringError.timestamp,
+            ),
+            (
+                'monitoring_sessions',
+                persistence_monitoring.MonitoringSession,
+                persistence_monitoring.MonitoringSession.last_activity,
+            ),
+        ]
+
+        deleted_counts: dict[str, int] = {}
+
+        for table_name, model_cls, ts_column in tables_and_columns:
+            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.delete(model_cls).where(ts_column < cutoff))
+            deleted_counts[table_name] = result.rowcount
+
+        return deleted_counts
+
     # ========== Recording Methods ==========
 
     async def record_message(
@@ -1132,3 +1183,314 @@ class MonitoringService:
             }
             for row in rows
         ]
+
+    # ========== Feedback Methods ==========
+
+    async def record_feedback(
+        self,
+        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 | None = None,
+    ) -> str:
+        """Record user feedback (like/dislike) from AI Bot conversation.
+
+        Args:
+            feedback_id: Unique feedback identifier from platform (e.g., WeChat Work)
+            feedback_type: 1 = like (thumbs up), 2 = dislike (thumbs down)
+            feedback_content: Optional user feedback text
+            inaccurate_reasons: List of reasons for inaccurate response (for dislike)
+            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 (for WeChat Work streaming messages)
+            user_id: User ID
+            platform: Platform name (e.g., 'wecom')
+
+        Returns:
+            The record ID
+        """
+        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
+
+        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)
+        )
+        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
+
+    async def get_feedback_stats(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+    ) -> dict:
+        """Get feedback statistics.
+
+        Returns:
+            Dictionary with total likes, dislikes, and breakdown by bot/pipeline
+        """
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        # Get total likes (feedback_type = 1)
+        likes_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id)).where(
+            persistence_monitoring.MonitoringFeedback.feedback_type == 1
+        )
+        if conditions:
+            likes_query = likes_query.where(sqlalchemy.and_(*conditions))
+        likes_result = await self.ap.persistence_mgr.execute_async(likes_query)
+        total_likes = likes_result.scalar() or 0
+
+        # Get total dislikes (feedback_type = 2)
+        dislikes_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id)).where(
+            persistence_monitoring.MonitoringFeedback.feedback_type == 2
+        )
+        if conditions:
+            dislikes_query = dislikes_query.where(sqlalchemy.and_(*conditions))
+        dislikes_result = await self.ap.persistence_mgr.execute_async(dislikes_query)
+        total_dislikes = dislikes_result.scalar() or 0
+
+        # Get total feedback count
+        total_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id))
+        if conditions:
+            total_query = total_query.where(sqlalchemy.and_(*conditions))
+        total_result = await self.ap.persistence_mgr.execute_async(total_query)
+        total_feedback = total_result.scalar() or 0
+
+        # Calculate satisfaction rate
+        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,
+        )
+        if conditions:
+            bot_stats_query = bot_stats_query.where(sqlalchemy.and_(*conditions))
+        bot_stats_result = await self.ap.persistence_mgr.execute_async(bot_stats_query)
+        bot_stats = [
+            {
+                'bot_id': row.bot_id,
+                'bot_name': row.bot_name,
+                'total': row.total,
+                'likes': row.likes or 0,
+                'dislikes': row.dislikes or 0,
+            }
+            for row in bot_stats_result.all()
+        ]
+
+        return {
+            'total_feedback': total_feedback,
+            'total_likes': total_likes,
+            'total_dislikes': total_dislikes,
+            'satisfaction_rate': round(satisfaction_rate, 2),
+            'by_bot': bot_stats,
+        }
+
+    async def get_feedback_list(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        feedback_type: int | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+        limit: int = 100,
+        offset: int = 0,
+    ) -> tuple[list[dict], int]:
+        """Get feedback list with filters."""
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if feedback_type is not None:
+            conditions.append(persistence_monitoring.MonitoringFeedback.feedback_type == feedback_type)
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        # Get total count
+        count_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id))
+        if conditions:
+            count_query = count_query.where(sqlalchemy.and_(*conditions))
+        count_result = await self.ap.persistence_mgr.execute_async(count_query)
+        total = count_result.scalar() or 0
+
+        # Get feedback list
+        query = sqlalchemy.select(persistence_monitoring.MonitoringFeedback).order_by(
+            persistence_monitoring.MonitoringFeedback.timestamp.desc()
+        )
+        if conditions:
+            query = query.where(sqlalchemy.and_(*conditions))
+        query = query.limit(limit).offset(offset)
+
+        result = await self.ap.persistence_mgr.execute_async(query)
+        rows = result.all()
+
+        return (
+            [
+                self.ap.persistence_mgr.serialize_model(
+                    persistence_monitoring.MonitoringFeedback, row[0] if isinstance(row, tuple) else row
+                )
+                for row in rows
+            ],
+            total,
+        )
+
+    async def export_feedback(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+        limit: int = 100000,
+    ) -> list[dict]:
+        """Export feedback as list of dictionaries for CSV conversion."""
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        query = sqlalchemy.select(persistence_monitoring.MonitoringFeedback).order_by(
+            persistence_monitoring.MonitoringFeedback.timestamp.desc()
+        )
+        if conditions:
+            query = query.where(sqlalchemy.and_(*conditions))
+        query = query.limit(limit)
+
+        result = await self.ap.persistence_mgr.execute_async(query)
+        rows = result.all()
+
+        return [
+            {
+                '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_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,
+                'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
+                'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
+                'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
+                'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
+                'message_id': row[0].message_id if isinstance(row, tuple) else row.message_id,
+                'stream_id': row[0].stream_id if isinstance(row, tuple) else row.stream_id,
+                'user_id': row[0].user_id if isinstance(row, tuple) else row.user_id,
+                'platform': row[0].platform if isinstance(row, tuple) else row.platform,
+            }
+            for row in rows
+        ]

src/langbot/pkg/api/http/service/provider.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import uuid
+import traceback
 
 import sqlalchemy
 
@@ -97,6 +98,14 @@ 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
@@ -121,7 +130,14 @@ class ModelProviderService:
         )
         embedding_count = embedding_result.scalar() or 0
 
-        return {'llm_count': llm_count, 'embedding_count': embedding_count}
+        rerank_result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(sqlalchemy.func.count())
+            .select_from(persistence_model.RerankModel)
+            .where(persistence_model.RerankModel.provider_uuid == provider_uuid)
+        )
+        rerank_count = rerank_result.scalar() or 0
+
+        return {'llm_count': llm_count, 'embedding_count': embedding_count, 'rerank_count': rerank_count}
 
     async def find_or_create_provider(self, requester: str, base_url: str, api_keys: list) -> str:
         """Find existing provider or create new one"""
@@ -164,3 +180,66 @@ 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}

src/langbot/pkg/api/http/service/user.py

@@ -65,8 +65,8 @@ class UserService:
 
         user_obj = result_list[0]
 
-        # Check if this is a Space account
-        if user_obj.account_type == 'space':
+        # Check if this user has a local password set
+        if not user_obj.password:
             raise ValueError('请使用 Space 账户登录')
 
         ph = argon2.PasswordHasher()
@@ -108,9 +108,8 @@ class UserService:
         if user_obj is None:
             raise ValueError('User not found')
 
-        # Space accounts cannot change password locally
-        if user_obj.account_type == 'space':
-            raise ValueError('Space account cannot change password locally')
+        if not user_obj.password:
+            raise ValueError('No local password set, please set a password first')
 
         ph.verify(user_obj.password, current_password)
 

src/langbot/pkg/core/app.py

@@ -133,6 +133,8 @@ 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
@@ -188,6 +190,34 @@ class Application:
                 scopes=[core_entities.LifecycleControlScope.APPLICATION],
             )
 
+            # Start monitoring data cleanup task if enabled
+            monitoring_cfg = self.instance_config.data.get('monitoring', {})
+            auto_cleanup_cfg = monitoring_cfg.get('auto_cleanup', {})
+            if auto_cleanup_cfg.get('enabled', True):
+                retention_days = auto_cleanup_cfg.get('retention_days', 30)
+                check_interval_hours = auto_cleanup_cfg.get('check_interval_hours', 1)
+
+                async def monitoring_cleanup_loop():
+                    check_interval_seconds = check_interval_hours * 3600
+                    while True:
+                        try:
+                            deleted = await self.monitoring_service.cleanup_expired_records(retention_days)
+                            total_deleted = sum(deleted.values())
+                            if total_deleted > 0:
+                                self.logger.info(
+                                    f'Monitoring auto-cleanup: deleted {total_deleted} expired records '
+                                    f'(retention={retention_days}d): {deleted}'
+                                )
+                        except Exception as e:
+                            self.logger.warning(f'Monitoring auto-cleanup error: {e}')
+                        await asyncio.sleep(check_interval_seconds)
+
+                self.task_mgr.create_task(
+                    monitoring_cleanup_loop(),
+                    name='monitoring-cleanup',
+                    scopes=[core_entities.LifecycleControlScope.APPLICATION],
+                )
+
             self.task_mgr.create_task(
                 never_ending(),
                 name='never-ending-task',

src/langbot/pkg/core/stages/build_app.py

@@ -61,6 +61,9 @@ 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
 

src/langbot/pkg/core/stages/load_config.py

@@ -80,8 +80,12 @@ 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], (dict, list)):
-                        # Skip dict and list types
+                    if isinstance(current[key], list):
+                        # Convert comma-separated string to list
+                        # e.g., SYSTEM__DISABLED_ADAPTERS="aiocqhttp,dingtalk"
+                        current[key] = [item.strip() for item in env_value.split(',') if item.strip()]
+                    elif isinstance(current[key], dict):
+                        # Skip dict types
                         pass
                     else:
                         # Valid scalar value - convert and set it

src/langbot/pkg/core/taskmgr.py

@@ -17,9 +17,13 @@ class TaskContext:
     log: str
     """Log"""
 
+    metadata: dict
+    """Structured metadata for progress reporting"""
+
     def __init__(self):
         self.current_action = 'default'
         self.log = ''
+        self.metadata = {}
 
     def _log(self, msg: str):
         self.log += msg + '\n'
@@ -38,7 +42,7 @@ class TaskContext:
         self._log(f'{datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")} | {self.current_action} | {msg}')
 
     def to_dict(self) -> dict:
-        return {'current_action': self.current_action, 'log': self.log}
+        return {'current_action': self.current_action, 'log': self.log, 'metadata': self.metadata}
 
     @staticmethod
     def new() -> TaskContext:
@@ -211,9 +215,14 @@ class AsyncTaskManager:
     def get_tasks_dict(
         self,
         type: str = None,
+        kind: str = None,
     ) -> dict:
         return {
-            'tasks': [t.to_dict() for t in self.tasks if type is None or t.task_type == type],
+            'tasks': [
+                t.to_dict()
+                for t in self.tasks
+                if (type is None or t.task_type == type) and (kind is None or t.kind == kind)
+            ],
             'id_index': TaskWrapper._id_index,
         }
 

src/langbot/pkg/discover/engine.py

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

src/langbot/pkg/entity/persistence/bot.py

@@ -16,6 +16,7 @@ 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,

src/langbot/pkg/entity/persistence/model.py

@@ -59,3 +59,22 @@ 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(),
+    )

src/langbot/pkg/entity/persistence/monitoring.py

@@ -106,3 +106,26 @@ class MonitoringEmbeddingCall(Base):
     session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
     message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
     call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True)  # embedding, retrieve
+
+
+class MonitoringFeedback(Base):
+    """User feedback records (like/dislike) from AI Bot conversations"""
+
+    __tablename__ = 'monitoring_feedback'
+
+    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
+    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
+    feedback_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, unique=True, index=True)
+    feedback_type = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)  # 1=like, 2=dislike
+    feedback_content = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # User feedback text
+    inaccurate_reasons = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # JSON list of inaccurate reasons
+    # Context fields
+    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    stream_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # e.g., wecom

src/langbot/pkg/persistence/alembic/env.py

@@ -0,0 +1,51 @@
+"""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()

src/langbot/pkg/persistence/alembic/script.py.mako

@@ -0,0 +1,24 @@
+# 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"}

src/langbot/pkg/persistence/alembic/versions/0001_baseline.py

@@ -0,0 +1,24 @@
+"""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

src/langbot/pkg/persistence/alembic/versions/0002_sample.py

@@ -0,0 +1,62 @@
+"""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

src/langbot/pkg/persistence/alembic/versions/0003_add_rerank_models.py

@@ -0,0 +1,35 @@
+"""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')

src/langbot/pkg/persistence/alembic_runner.py

@@ -0,0 +1,150 @@
+"""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()

src/langbot/pkg/persistence/mgr.py

@@ -2,18 +2,16 @@ from __future__ import annotations
 
 import datetime
 import typing
-import json
-import uuid
+
 
 import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
 import sqlalchemy
 
 from . import database, migration
-from ..entity.persistence import base, pipeline, metadata, model as persistence_model
+from ..entity.persistence import base, metadata, model as persistence_model
 from ..entity import persistence
 from ..core import app
 from ..utils import constants, importutil
-from ..api.http.service import pipeline as pipeline_service
 from . import databases, migrations
 
 importutil.import_modules_in_pkg(databases)
@@ -78,7 +76,9 @@ class PersistenceManager:
 
             self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
 
-        await self.write_default_pipeline()
+        # Run Alembic migrations (new migration system)
+        await self._run_alembic_migrations()
+
         await self.write_space_model_providers()
 
     async def create_tables(self):
@@ -101,29 +101,6 @@ class PersistenceManager:
             if row is None:
                 await self.execute_async(sqlalchemy.insert(metadata.Metadata).values(item))
 
-    async def write_default_pipeline(self):
-        # write default pipeline
-        result = await self.execute_async(sqlalchemy.select(pipeline.LegacyPipeline))
-        default_pipeline_uuid = None
-        if result.first() is None:
-            self.ap.logger.info('Creating default pipeline...')
-
-            pipeline_config = json.loads(importutil.read_resource_file('templates/default-pipeline-config.json'))
-
-            default_pipeline_uuid = str(uuid.uuid4())
-            pipeline_data = {
-                'uuid': default_pipeline_uuid,
-                'for_version': self.ap.ver_mgr.get_current_version(),
-                'stages': pipeline_service.default_stage_order,
-                'is_default': True,
-                'name': 'ChatPipeline',
-                'description': 'Default pipeline, new bots will be bound to this pipeline | 默认提供的流水线，您配置的机器人将自动绑定到此流水线',
-                'config': pipeline_config,
-                'extensions_preferences': {},
-            }
-
-            await self.execute_async(sqlalchemy.insert(pipeline.LegacyPipeline).values(pipeline_data))
-
     async def write_space_model_providers(self):
         space_models_gateway_api_url = self.ap.instance_config.data.get('space', {}).get(
             'models_gateway_api_url', 'https://api.langbot.cloud/v1'
@@ -161,6 +138,28 @@ 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)

src/langbot/pkg/persistence/migrations/dbm025_bot_pipeline_routing_rules.py

@@ -0,0 +1,15 @@
+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)

src/langbot/pkg/pipeline/aggregator.py

@@ -37,6 +37,7 @@ 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)
 
 
@@ -125,6 +126,7 @@ 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
 
@@ -145,6 +147,7 @@ class MessageAggregator:
                 message_chain=message_chain,
                 adapter=adapter,
                 pipeline_uuid=pipeline_uuid,
+                routed_by_rule=routed_by_rule,
             )
             return
 
@@ -159,6 +162,7 @@ class MessageAggregator:
             message_chain=message_chain,
             adapter=adapter,
             pipeline_uuid=pipeline_uuid,
+            routed_by_rule=routed_by_rule,
         )
 
         force_flush = False
@@ -217,6 +221,7 @@ class MessageAggregator:
                 message_chain=msg.message_chain,
                 adapter=msg.adapter,
                 pipeline_uuid=msg.pipeline_uuid,
+                routed_by_rule=msg.routed_by_rule,
             )
             return
 
@@ -231,6 +236,7 @@ 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:

src/langbot/pkg/pipeline/controller.py

@@ -63,6 +63,14 @@ 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()

src/langbot/pkg/pipeline/pipelinemgr.py

@@ -297,6 +297,9 @@ 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}')
 
@@ -323,6 +326,9 @@ 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}')

src/langbot/pkg/pipeline/pool.py

@@ -41,6 +41,7 @@ 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
@@ -52,7 +53,7 @@ class QueryPool:
                 sender_id=sender_id,
                 message_event=message_event,
                 message_chain=message_chain,
-                variables={},
+                variables={'_routed_by_rule': routed_by_rule},
                 resp_messages=[],
                 resp_message_chain=[],
                 adapter=adapter,

src/langbot/pkg/pipeline/preproc/preproc.py

@@ -160,7 +160,6 @@ 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:
@@ -172,6 +171,15 @@ 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
 

src/langbot/pkg/pipeline/process/handlers/chat.py

@@ -61,6 +61,9 @@ 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:
@@ -205,6 +208,7 @@ 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(),

src/langbot/pkg/pipeline/resprule/resprule.py

@@ -37,6 +37,10 @@ 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

src/langbot/pkg/platform/botmgr.py

@@ -1,6 +1,8 @@
 from __future__ import annotations
 
 import asyncio
+import json
+import re
 import traceback
 import sqlalchemy
 
@@ -9,6 +11,7 @@ from ..core import app, entities as core_entities, taskmgr
 from ..discover import engine
 
 from ..entity.persistence import bot as persistence_bot
+from ..entity.persistence import pipeline as persistence_pipeline
 
 from ..entity.errors import platform as platform_errors
 
@@ -51,6 +54,148 @@ 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,
@@ -82,6 +227,23 @@ 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,
@@ -90,7 +252,8 @@ class RuntimeBot:
                     message_event=event,
                     message_chain=event.message_chain,
                     adapter=adapter,
-                    pipeline_uuid=self.bot_entity.use_pipeline_uuid,
+                    pipeline_uuid=pipeline_uuid,
+                    routed_by_rule=routed_by_rule,
                 )
             else:
                 await self.logger.info('Pipeline skipped for person message due to webhook response')
@@ -125,6 +288,23 @@ 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,
@@ -133,7 +313,8 @@ class RuntimeBot:
                     message_event=event,
                     message_chain=event.message_chain,
                     adapter=adapter,
-                    pipeline_uuid=self.bot_entity.use_pipeline_uuid,
+                    pipeline_uuid=pipeline_uuid,
+                    routed_by_rule=routed_by_rule,
                 )
             else:
                 await self.logger.info('Pipeline skipped for group message due to webhook response')
@@ -141,6 +322,50 @@ 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:
@@ -196,12 +421,20 @@ 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)

src/langbot/pkg/platform/sources/aiocqhttp.yaml

@@ -5,19 +5,29 @@ metadata:
   label:
     en_US: OneBot v11
     zh_Hans: OneBot v11
+    zh_Hant: OneBot v11
   description:
-    en_US: OneBot v11 Adapter
-    zh_Hans: OneBot v11 适配器，请查看文档了解使用方式
+    en_US: OneBot v11 Adapter, used for QQ bots
+    zh_Hans: OneBot v11 适配器，用于接入 QQ 机器人协议端，请查看文档了解使用方式
+    zh_Hant: OneBot v11 適配器，用於接入 QQ 機器人協定端，請查看文件了解使用方式
   icon: onebot.png
 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:
         en_US: Host
         zh_Hans: 主机
+        zh_Hant: 主機
       description:
         en_US: The host that OneBot v11 listens on for reverse WebSocket connections. Unless you know what you're doing, use 0.0.0.0
         zh_Hans: OneBot v11 监听的反向 WS 主机，除非你知道自己在做什么，否则请写 0.0.0.0
+        zh_Hant: OneBot v11 監聽的反向 WS 主機，除非你知道自己在做什麼，否則請填 0.0.0.0
       type: string
       required: true
       default: 0.0.0.0
@@ -25,9 +35,11 @@ spec:
       label:
         en_US: Port
         zh_Hans: 端口
+        zh_Hant: 連接埠
       description:
         en_US: Port
         zh_Hans: 监听的端口
+        zh_Hant: 監聽的連接埠
       type: integer
       required: true
       default: 2280
@@ -35,9 +47,11 @@ spec:
       label:
         en_US: Access Token
         zh_Hans: 访问令牌
+        zh_Hant: 存取令牌
       description:
         en_US: Custom connection token for the protocol endpoint. If the protocol endpoint is not set, don't fill it
         zh_Hans: 自定义的与协议端的连接令牌，若协议端未设置，则不填
+        zh_Hant: 自訂的與協定端的連線令牌，若協定端未設定，則不填
       type: string
       required: false
       default: ""

src/langbot/pkg/platform/sources/dingtalk.py

@@ -71,7 +71,8 @@ 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
-            if event.content:
+            # 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':
                 text_content = event.content.replace('@' + bot_name, '')
                 yiri_msg_list.append(platform_message.Plain(text=text_content))
             if event.picture:
@@ -81,7 +82,38 @@ 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:
-            yiri_msg_list.append(platform_message.Voice(base64=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"]}'))
 
         chain = platform_message.MessageChain(yiri_msg_list)
 

src/langbot/pkg/platform/sources/dingtalk.yaml

@@ -5,16 +5,25 @@ metadata:
   label:
     en_US: DingTalk
     zh_Hans: 钉钉
+    zh_Hant: 釘釘
   description:
     en_US: DingTalk Adapter
     zh_Hans: 钉钉适配器，请查看文档了解使用方式
+    zh_Hant: 釘釘適配器，請查看文件了解使用方式
   icon: dingtalk.svg
 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:
         en_US: Client ID
         zh_Hans: 客户端ID
+        zh_Hant: 用戶端ID
       type: string
       required: true
       default: ""
@@ -22,6 +31,7 @@ spec:
       label:
         en_US: Client Secret
         zh_Hans: 客户端密钥
+        zh_Hant: 用戶端密鑰
       type: string
       required: true
       default: ""
@@ -29,6 +39,7 @@ spec:
       label:
         en_US: Robot Code
         zh_Hans: 机器人代码
+        zh_Hant: 機器人代碼
       type: string
       required: true
       default: ""
@@ -36,6 +47,7 @@ spec:
       label:
         en_US: Robot Name
         zh_Hans: 机器人名称
+        zh_Hant: 機器人名稱
       type: string
       required: true
       default: ""
@@ -43,6 +55,7 @@ spec:
       label:
         en_US: Markdown Card
         zh_Hans: 是否使用 Markdown 卡片
+        zh_Hant: 是否使用 Markdown 卡片
       type: boolean
       required: false
       default: true
@@ -50,9 +63,11 @@ spec:
       label:
         en_US: Enable Stream Reply Mode
         zh_Hans: 启用钉钉卡片流式回复模式
+        zh_Hant: 啟用釘釘卡片串流回覆模式
       description:
         en_US: If enabled, the bot will use the stream of lark reply mode
         zh_Hans: 如果启用，将使用钉钉卡片流式方式来回复内容
+        zh_Hant: 如果啟用，將使用釘釘卡片串流方式來回覆內容
       type: boolean
       required: true
       default: false
@@ -60,6 +75,7 @@ spec:
       label:
         en_US: Card Auto Layout
         zh_Hans: 卡片宽屏自动布局
+        zh_Hant: 卡片寬螢幕自動佈局
       type: boolean
       required: false
       default: false
@@ -67,6 +83,7 @@ spec:
       label:
         en_US: card template id
         zh_Hans: 卡片模板ID
+        zh_Hant: 卡片範本ID
       type: string
       required: true
       default: "填写你的卡片template_id"

src/langbot/pkg/platform/sources/discord.yaml

@@ -5,16 +5,38 @@ metadata:
   label:
     en_US: Discord
     zh_Hans: Discord
+    zh_Hant: Discord
+    ja_JP: Discord
+    th_TH: Discord
+    vi_VN: Discord
+    es_ES: Discord
   description:
     en_US: Discord Adapter
-    zh_Hans: Discord 适配器，请查看文档了解使用方式
+    zh_Hans: Discord 适配器，需要可连接 Discord 服务器的网络环境
+    zh_Hant: Discord 適配器，需要可連線 Discord 伺服器的網路環境
+    ja_JP: Discord アダプター、Discord サーバーに接続可能なネットワーク環境が必要です
+    th_TH: อะแดปเตอร์ Discord ต้องการสภาพแวดล้อมเครือข่ายที่สามารถเชื่อมต่อกับเซิร์ฟเวอร์ Discord ได้
+    vi_VN: Bộ điều hợp Discord, cần môi trường mạng có thể kết nối với máy chủ Discord
+    es_ES: Adaptador de Discord, requiere un entorno de red con acceso al servidor de Discord
   icon: discord.svg
 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:
         en_US: Client ID
         zh_Hans: 客户端ID
+        zh_Hant: 用戶端ID
+        ja_JP: クライアント ID
+        th_TH: รหัสไคลเอนต์
+        vi_VN: ID khách hàng
+        es_ES: ID de cliente
       type: string
       required: true
       default: ""
@@ -22,6 +44,11 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
+        ja_JP: トークン
+        th_TH: โทเค็น
+        vi_VN: Mã thông báo
+        es_ES: Token
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/kook.yaml

@@ -5,16 +5,25 @@ metadata:
   label:
     en_US: KOOK
     zh_Hans: KOOK
+    zh_Hant: KOOK
   description:
     en_US: KOOK Adapter (formerly KaiHeiLa)
     zh_Hans: KOOK 适配器(原开黑啦)，支持频道消息和私聊消息
+    zh_Hant: KOOK 適配器（原開黑啦），支援頻道訊息和私聊訊息
   icon: kook.png
 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:
         en_US: Bot Token
         zh_Hans: 机器人令牌
+        zh_Hant: 機器人令牌
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/lark.py

@@ -709,21 +709,29 @@ 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_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,
-                        )
-                    )
+                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}'))
 
         if event.event.message.chat_type == 'p2p':
             return platform_events.FriendMessage(
@@ -779,6 +787,13 @@ 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
@@ -797,8 +812,71 @@ 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).build()
+            lark_oapi.EventDispatcherHandler.builder('', '')
+            .register_p2_im_message_receive_v1(sync_on_message)
+            .register_p2_card_action_trigger(sync_on_card_action)
+            .build()
         )
 
         bot_account_id = config['bot_name']
@@ -813,6 +891,8 @@ 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,
@@ -953,6 +1033,22 @@ 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......')
@@ -1088,6 +1184,7 @@ 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',
                                         }
                                     ],
@@ -1111,6 +1208,7 @@ 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',
                                         }
                                     ],
@@ -1190,6 +1288,18 @@ 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(
@@ -1472,6 +1582,58 @@ 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', '')

src/langbot/pkg/platform/sources/lark.yaml

@@ -5,16 +5,30 @@ metadata:
   label:
     en_US: Lark
     zh_Hans: 飞书
+    zh_Hant: 飛書
+    ja_JP: Lark
   description:
-    en_US: Lark Adapter
-    zh_Hans: 飞书适配器，请查看文档了解使用方式
+    en_US: Lark Adapter, supports both long connection and Webhook modes. Please refer to the documentation for usage details.
+    zh_Hans: 飞书适配器，支持长连接和 Webhook 两种接入方式，请查看文档了解使用方式
+    zh_Hant: 飛書適配器，支援長連線和 Webhook 兩種接入方式，請查看文件了解使用方式
+    ja_JP: Lark アダプター、長期接続およびWebhookモードの両方をサポートしています。使用方法の詳細については、ドキュメントを参照してください。
   icon: lark.svg
 spec:
+  categories:
+    - 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:
         en_US: App ID
         zh_Hans: 应用ID
+        zh_Hant: 應用ID
+        ja_JP: アプリ ID
       type: string
       required: true
       default: ""
@@ -22,6 +36,8 @@ spec:
       label:
         en_US: App Secret
         zh_Hans: 应用密钥
+        zh_Hant: 應用密鑰
+        ja_JP: アプリシークレット
       type: string
       required: true
       default: ""
@@ -29,9 +45,13 @@ spec:
       label:
         en_US: Bot Name
         zh_Hans: 机器人名称
+        zh_Hant: 機器人名稱
+        ja_JP: ボット名
       description:
         en_US: Must be the same as the name of the bot in Lark, otherwise the bot will not be able to receive messages in the group
         zh_Hans: 必须与飞书机器人名称一致，否则机器人将无法在群内正常接收消息
+        zh_Hant: 必須與飛書機器人名稱一致，否則機器人將無法在群組內正常接收訊息
+        ja_JP: Lark のボット名と一致する必要があります。一致しない場合、グループ内でメッセージを受信できません
       type: string
       required: true
       default: ""
@@ -39,29 +59,63 @@ spec:
       label:
         en_US: Enable Webhook Mode
         zh_Hans: 启用Webhook模式
+        zh_Hant: 啟用 Webhook 模式
+        ja_JP: Webhook モードを有効化
       description:
         en_US: If enabled, the bot will use webhook mode to receive messages. Otherwise, it will use WS long connection mode
         zh_Hans: 如果启用，机器人将使用 Webhook 模式接收消息。否则，将使用 WS 长连接模式
+        zh_Hant: 如果啟用，機器人將使用 Webhook 模式接收訊息。否則，將使用 WS 長連線模式
+        ja_JP: 有効にすると、ボットは Webhook モードでメッセージを受信します。無効の場合は WS 長期接続モードを使用します
       type: boolean
       required: true
       default: false
+    - name: webhook_url
+      label:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+        ja_JP: Webhook コールバック URL
+      description:
+        en_US: Copy this URL and paste it into your Lark app's webhook configuration
+        zh_Hans: 复制此地址并粘贴到飞书应用的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到飛書應用的 Webhook 設定中
+        ja_JP: この URL をコピーして Lark アプリの Webhook 設定に貼り付けてください
+      type: webhook-url
+      required: false
+      default: ""
+      show_if:
+        field: enable-webhook
+        operator: eq
+        value: true
     - name: encrypt-key
       label:
         en_US: Encrypt Key
         zh_Hans: 加密密钥
+        zh_Hant: 加密密鑰
+        ja_JP: 暗号化キー
       description:
         en_US: Only valid when webhook mode is enabled, please fill in the encrypt key
         zh_Hans: 仅在启用 Webhook 模式时有效，请填写加密密钥
+        zh_Hant: 僅在啟用 Webhook 模式時有效，請填寫加密密鑰
+        ja_JP: Webhook モードが有効な場合にのみ有効です。暗号化キーを入力してください
       type: string
       required: true
       default: ""
+      show_if:
+        field: enable-webhook
+        operator: eq
+        value: true
     - name: enable-stream-reply
       label:
         en_US: Enable Stream Reply Mode
         zh_Hans: 启用飞书流式回复模式
+        zh_Hant: 啟用飛書串流回覆模式
+        ja_JP: ストリーミング返信モードを有効化
       description:
         en_US: If enabled, the bot will use the stream of lark reply mode
         zh_Hans: 如果启用，将使用飞书流式方式来回复内容
+        zh_Hant: 如果啟用，將使用飛書串流方式來回覆內容
+        ja_JP: 有効にすると、ボットはストリーミングモードでメッセージに返信します
       type: boolean
       required: true
       default: false
@@ -69,28 +123,40 @@ spec:
       label:
         en_US: App Type
         zh_Hans: 应用类型
+        zh_Hant: 應用類型
+        ja_JP: アプリタイプ
       description:
         en_US: Default to self-built application, refer to https://open.feishu.cn/document/platform-overveiw/overview
         zh_Hans: 默认为企业自建应用，参考 https://open.feishu.cn/document/platform-overveiw/overview
+        zh_Hant: 預設為企業自建應用，參考 https://open.feishu.cn/document/platform-overveiw/overview
+        ja_JP: デフォルトはカスタムアプリです。詳細は https://open.feishu.cn/document/platform-overveiw/overview を参照してください
       type: select
       options:
         - name: self
           label:
             en_US: Self-built Application
             zh_Hans: 自建应用
+            zh_Hant: 自建應用
+            ja_JP: カスタムアプリ
         - name: isv
           label:
             en_US: Store Application
             zh_Hans: 商店应用
+            zh_Hant: 商店應用
+            ja_JP: ストアアプリ
       required: false
       default: self
     - name: bot_added_welcome
       label:
         en_US: Bot Welcome Message
         zh_Hans: 机器人进群欢迎语
+        zh_Hant: 機器人進群歡迎語
+        ja_JP: ボット参加時のウェルカムメッセージ
       description:
         en_US: Welcome message when the bot is added to a group, supports Markdown format
         zh_Hans: 机器人进群欢迎语，支持 Markdown 格式
+        zh_Hant: 機器人進群歡迎語，支援 Markdown 格式
+        ja_JP: ボットがグループに追加された際のウェルカムメッセージ。Markdown 形式に対応しています
       type: text
       required: false
       default: ""

src/langbot/pkg/platform/sources/line.yaml

@@ -5,20 +5,56 @@ metadata:
   label:
     en_US: LINE
     zh_Hans: LINE
+    zh_Hant: LINE
+    th_TH: LINE
+    vi_VN: LINE
+    es_ES: LINE
   description:
-    en_US: LINE Adapter
-    zh_Hans: LINE适配器，请查看文档了解使用方式
-    ja_JP: LINEアダプター、ドキュメントを参照してください
-    zh_Hant: LINE適配器，請查看文檔了解使用方式
+    en_US: LINE Adapter, requires a public URL to receive LINE message pushes, please refer to the documentation for usage details
+    zh_Hans: LINE适配器，需要公网地址以接收 LINE 消息推送，请查看文档了解使用方式
+    zh_Hant: LINE 適配器，需要公網地址以接收 LINE 訊息推送，請查看文件了解使用方式
+    ja_JP: LINEアダプター、LINEのメッセージプッシュを受信するためにパブリックURLが必要です。使用方法の詳細については、ドキュメントを参照してください。
+    th_TH: อะแดปเตอร์ LINE ต้องการ URL สาธารณะเพื่อรับการแจ้งเตือนข้อความจาก LINE โปรดดูเอกสารประกอบสำหรับรายละเอียดการใช้งาน
+    vi_VN: Bộ điều hợp LINE, cần URL công cộng để nhận thông báo tin nhắn LINE, vui lòng xem tài liệu để biết chi tiết cách sử dụng
+    es_ES: Adaptador de LINE, requiere una URL pública para recibir notificaciones de mensajes de LINE, consulte la documentación para obtener detalles de uso
   icon: line.png
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        ja_JP: Webhook コールバック URL
+        zh_Hant: Webhook 回調地址
+        th_TH: URL การเรียกกลับ Webhook
+        vi_VN: URL gọi lại Webhook
+        es_ES: URL de devolución de llamada Webhook
+      description:
+        en_US: Copy this URL and paste it into your LINE channel's webhook configuration
+        zh_Hans: 复制此地址并粘贴到 LINE 频道的 Webhook 配置中
+        ja_JP: この URL をコピーして LINE チャンネルの Webhook 設定に貼り付けてください
+        zh_Hant: 複製此地址並貼到 LINE 頻道的 Webhook 設定中
+        th_TH: คัดลอก URL นี้แล้ววางในการตั้งค่า Webhook ของช่อง LINE ของคุณ
+        vi_VN: Sao chép URL này và dán vào cấu hình webhook của kênh LINE của bạn
+        es_ES: Copie esta URL y péguela en la configuración de webhook de su canal LINE
+      type: webhook-url
+      required: false
+      default: ""
     - name: channel_access_token
       label:
         en_US: Channel access token
         zh_Hans: 频道访问令牌
         ja_JP: チャンネルアクセストークン
-        zh_Hant: 頻道訪問令牌
+        zh_Hant: 頻道存取令牌
+        th_TH: โทเค็นการเข้าถึงช่อง
+        vi_VN: Mã truy cập kênh
+        es_ES: Token de acceso del canal
       type: string
       required: true
       default: ""
@@ -27,12 +63,18 @@ spec:
         en_US: Channel secret
         zh_Hans: 消息密钥
         ja_JP: チャンネルシークレット
-        zh_Hant: 消息密钥
+        zh_Hant: 訊息密鑰
+        th_TH: รหัสลับช่อง
+        vi_VN: Khóa bí mật kênh
+        es_ES: Secreto del canal
       description:
         en_US: Only valid when webhook mode is enabled, please fill in the encrypt key
         zh_Hans: 请填写加密密钥
         ja_JP: Webhookモードが有効な場合にのみ、暗号化キーを入力してください
-        zh_Hant: 請填寫加密密钥
+        zh_Hant: 請填寫加密密鑰
+        th_TH: กรุณากรอกคีย์เข้ารหัส
+        vi_VN: Vui lòng điền khóa mã hóa
+        es_ES: Por favor, introduzca la clave de cifrado
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/officialaccount.yaml

@@ -5,23 +5,44 @@ metadata:
   label:
     en_US: Official Account
     zh_Hans: 微信公众号
+    zh_Hant: 微信公眾號
   description:
     en_US: Official Account Adapter
-    zh_Hans: 微信公众号适配器，请查看文档了解使用方式
+    zh_Hans: 微信公众号适配器，需要公网地址以接收消息推送，请查看文档了解使用方式
+    zh_Hant: 微信公眾號適配器，需要公網地址以接收訊息推送，請查看文件了解使用方式
   icon: officialaccount.png
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+      description:
+        en_US: Copy this URL and paste it into your Official Account webhook configuration
+        zh_Hans: 复制此地址并粘贴到微信公众号的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到微信公眾號的 Webhook 設定中
+      type: webhook-url
+      required: false
+      default: ""
     - name: token
       label:
         en_US: Token
         zh_Hans: 令牌
-      type: string
+        zh_Hant: 令牌
       required: true
       default: ""
     - name: EncodingAESKey
       label:
         en_US: EncodingAESKey
         zh_Hans: 消息加解密密钥
+        zh_Hant: 訊息加解密密鑰
       type: string
       required: true
       default: ""
@@ -29,6 +50,7 @@ spec:
       label:
         en_US: App ID
         zh_Hans: 应用ID
+        zh_Hant: 應用ID
       type: string
       required: true
       default: ""
@@ -36,6 +58,7 @@ spec:
       label:
         en_US: App Secret
         zh_Hans: 应用密钥
+        zh_Hant: 應用密鑰
       type: string
       required: true
       default: ""
@@ -43,6 +66,7 @@ spec:
       label:
         en_US: Mode
         zh_Hans: 接入模式
+        zh_Hant: 接入模式
       type: string
       required: true
       default: "drop"
@@ -50,6 +74,7 @@ spec:
       label:
         en_US: Loading Message
         zh_Hans: 加载消息
+        zh_Hant: 載入訊息
       type: string
       required: true
       default: "AI正在思考中，请发送任意内容获取回复。"
@@ -57,9 +82,11 @@ spec:
       label:
         en_US: API Base URL
         zh_Hans: API 基础 URL
+        zh_Hant: API 基礎 URL
       description:
         en_US: API Base URL, used for accessing the Official Account API. If you are deploying in an internal network environment and accessing the Official Account API through a reverse proxy, please fill in this item according to the documentation.
         zh_Hans: 可选，若您部署在内网环境并通过反向代理访问微信公众号 API，可根据文档修改此项
+        zh_Hant: 可選，若您部署在內網環境並透過反向代理存取微信公眾號 API，可根據文件修改此項
       type: string
       required: false
       default: "https://api.weixin.qq.com"

src/langbot/pkg/platform/sources/openclaw_weixin.yaml

@@ -4,20 +4,31 @@ metadata:
   name: openclaw-weixin
   label:
     en_US: OpenClaw WeChat
-    zh_Hans: OpenClaw 微信
+    zh_Hans: 个人微信机器人
+    zh_Hant: 個人微信機器人
   description:
     en_US: OpenClaw WeChat adapter, supports personal WeChat via QR code login
-    zh_Hans: OpenClaw 微信适配器，通过扫码登录支持个人微信
+    zh_Hans: 微信官方个人助手，扫码即可登录使用
+    zh_Hant: 微信官方個人助手，掃碼即可登入使用
   icon: wechat.png
 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:
         en_US: API Base URL
         zh_Hans: API 基础地址
+        zh_Hant: API 基礎地址
       description:
         en_US: The base URL of the OpenClaw WeChat backend API
         zh_Hans: OpenClaw 微信后端 API 的基础地址
+        zh_Hant: OpenClaw 微信後端 API 的基礎地址
       type: string
       required: true
       default: "https://ilinkai.weixin.qq.com"
@@ -25,9 +36,11 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
       description:
         en_US: Bearer token obtained after QR code login authorization. Leave empty to trigger QR code login on startup.
-        zh_Hans: 扫码登录授权后获取的 Bearer 令牌。留空则启动时自动触发扫码登录。
+        zh_Hans: 扫码登录授权后获取的 Bearer 令牌。请留空并保存，将在启动时输出二维码到日志，扫码后即可自动登录。
+        zh_Hant: 掃碼登入授權後取得的 Bearer 令牌。請留空並儲存，將在啟動時輸出 QR Code 到日誌，掃碼後即可自動登入。
       type: string
       required: false
       default: ""
@@ -35,9 +48,11 @@ spec:
       label:
         en_US: Account ID
         zh_Hans: 账号标识
+        zh_Hant: 帳號標識
       description:
         en_US: A label for this WeChat account (used for display purposes)
         zh_Hans: 此微信账号的标识（用于显示）
+        zh_Hant: 此微信帳號的標識（用於顯示）
       type: string
       required: false
       default: "openclaw-weixin"
@@ -45,9 +60,11 @@ spec:
       label:
         en_US: Poll Timeout (seconds)
         zh_Hans: 轮询超时（秒）
+        zh_Hant: 輪詢逾時（秒）
       description:
         en_US: Long-poll timeout for getUpdates, the server may hold the request up to this duration
         zh_Hans: getUpdates 长轮询超时时间，服务端最多持有请求的时长
+        zh_Hant: getUpdates 長輪詢逾時時間，伺服端最多持有請求的時長
       type: integer
       required: false
       default: 35

src/langbot/pkg/platform/sources/qqofficial.yaml

@@ -5,16 +5,37 @@ metadata:
   label:
     en_US: QQ Official API
     zh_Hans: QQ 官方 API
+    zh_Hant: QQ 官方 API
   description:
     en_US: QQ Official API (Webhook)
-    zh_Hans: QQ 官方 API (Webhook)，请查看文档了解使用方式
+    zh_Hans: QQ 官方 API (Webhook)，需要公网地址以接收消息推送，请查看文档了解使用方式
+    zh_Hant: QQ 官方 API (Webhook)，需要公網地址以接收訊息推送，請查看文件了解使用方式
   icon: qqofficial.svg
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+      description:
+        en_US: Copy this URL and paste it into your QQ Official API webhook configuration
+        zh_Hans: 复制此地址并粘贴到 QQ 官方 API 的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到 QQ 官方 API 的 Webhook 設定中
+      type: webhook-url
+      required: false
+      default: ""
     - name: appid
       label:
         en_US: App ID
         zh_Hans: 应用ID
+        zh_Hant: 應用ID
       type: string
       required: true
       default: ""
@@ -22,6 +43,7 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥
+        zh_Hant: 密鑰
       type: string
       required: true
       default: ""
@@ -29,6 +51,7 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/satori.yaml

@@ -5,36 +5,70 @@ metadata:
   label:
     en_US: Satori
     zh_Hans: Satori
+    zh_Hant: Satori
+    th_TH: Satori
+    vi_VN: Satori
+    es_ES: Satori
   description:
     en_US: SatoriAdapter
-    zh_Hans: 古明地觉协议适配器
+    zh_Hans: Satori 协议适配器，支持多种平台的接入，请查看文档了解使用方式
+    zh_Hant: Satori 協定適配器，支援多種平台的接入，請查看文件了解使用方式
+    th_TH: อะแดปเตอร์โปรโตคอล Satori รองรับการเชื่อมต่อหลายแพลตฟอร์ม โปรดดูเอกสารประกอบสำหรับวิธีการใช้งาน
+    vi_VN: Bộ điều hợp giao thức Satori, hỗ trợ kết nối nhiều nền tảng, vui lòng xem tài liệu để biết cách sử dụng
+    es_ES: Adaptador del protocolo Satori, soporta acceso a múltiples plataformas, consulte la documentación para obtener instrucciones de uso
   icon: satori.png
 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:
         en_US: Platform
         zh_Hans: 平台名称
+        zh_Hant: 平台名稱
+        th_TH: ชื่อแพลตฟอร์ม
+        vi_VN: Tên nền tảng
+        es_ES: Nombre de la plataforma
       type: string
       required: true
       default: "llonebot"
       description:
         en_US: The platform name (e.g., llonebot, discord, telegram)
         zh_Hans: 平台名称（如 llonebot, discord, telegram）
+        zh_Hant: 平台名稱（如 llonebot、discord、telegram）
+        th_TH: ชื่อแพลตฟอร์ม (เช่น llonebot, discord, telegram)
+        vi_VN: "Tên nền tảng (ví dụ: llonebot, discord, telegram)"
+        es_ES: El nombre de la plataforma (p. ej., llonebot, discord, telegram)
     - name: host
       label:
         en_US: Host
         zh_Hans: 主机地址
+        zh_Hant: 主機地址
+        th_TH: ที่อยู่โฮสต์
+        vi_VN: Địa chỉ máy chủ
+        es_ES: Dirección del host
       type: string
       required: true
       default: "127.0.0.1"
       description:
         en_US: The host address of LLOneBot Satori server (e.g., 127.0.0.1, localhost, 192.168.1.100)
         zh_Hans: LLOneBot Satori服务器的主机地址（如 127.0.0.1, localhost, 192.168.1.100）
+        zh_Hant: LLOneBot Satori 伺服器的主機地址（如 127.0.0.1、localhost、192.168.1.100）
+        th_TH: ที่อยู่โฮสต์ของเซิร์ฟเวอร์ LLOneBot Satori (เช่น 127.0.0.1, localhost, 192.168.1.100)
+        vi_VN: "Địa chỉ máy chủ LLOneBot Satori (ví dụ: 127.0.0.1, localhost, 192.168.1.100)"
+        es_ES: La dirección del host del servidor LLOneBot Satori (p. ej., 127.0.0.1, localhost, 192.168.1.100)
     - name: port
       label:
         en_US: Port
         zh_Hans: 监听端口
+        zh_Hant: 監聽連接埠
+        th_TH: พอร์ต
+        vi_VN: Cổng
+        es_ES: Puerto
       type: integer
       required: true
       default: 5600
@@ -42,6 +76,10 @@ spec:
       label:
         en_US: Satori API Endpoint
         zh_Hans: Satori API 终结点
+        zh_Hant: Satori API 端點
+        th_TH: จุดปลาย Satori API
+        vi_VN: Điểm cuối Satori API
+        es_ES: Punto de acceso de la API Satori
       type: string
       required: true
       default: "http://localhost:5600/v1"
@@ -49,6 +87,10 @@ spec:
       label:
         en_US: Satori WebSocket Endpoint
         zh_Hans: Satori WebSocket 终结点
+        zh_Hant: Satori WebSocket 端點
+        th_TH: จุดปลาย Satori WebSocket
+        vi_VN: Điểm cuối Satori WebSocket
+        es_ES: Punto de acceso WebSocket de Satori
       type: string
       required: true
       default: "ws://localhost:5600/v1/events"
@@ -56,6 +98,10 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
+        th_TH: โทเค็น
+        vi_VN: Mã thông báo
+        es_ES: Token
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/slack.yaml

@@ -5,16 +5,58 @@ metadata:
   label:
     en_US: Slack
     zh_Hans: Slack
+    zh_Hant: Slack
+    ja_JP: Slack
+    th_TH: Slack
+    vi_VN: Slack
+    es_ES: Slack
   description:
     en_US: Slack Adapter
-    zh_Hans: Slack 适配器，请查看文档了解使用方式
+    zh_Hans: Slack 适配器，需要公网地址以接收 Slack 消息推送，请查看文档了解使用方式
+    zh_Hant: Slack 適配器，需要公網地址以接收 Slack 訊息推送，請查看文件了解使用方式
+    ja_JP: Slack アダプター、Slackのメッセージプッシュを受信するためにパブリックURLが必要です。使用方法の詳細については、ドキュメントを参照してください。
+    th_TH: อะแดปเตอร์ Slack ต้องการที่อยู่สาธารณะเพื่อรับการแจ้งเตือนข้อความจาก Slack โปรดดูเอกสารประกอบสำหรับวิธีการใช้งาน
+    vi_VN: Bộ điều hợp Slack, cần địa chỉ công cộng để nhận thông báo tin nhắn từ Slack, vui lòng xem tài liệu để biết cách sử dụng
+    es_ES: Adaptador de Slack, requiere una dirección pública para recibir notificaciones de mensajes de Slack, consulte la documentación para obtener instrucciones de uso
   icon: slack.png
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+        ja_JP: Webhook コールバック URL
+        th_TH: URL การเรียกกลับ Webhook
+        vi_VN: URL gọi lại Webhook
+        es_ES: URL de devolución de llamada Webhook
+      description:
+        en_US: Copy this URL and paste it into your Slack app's event subscription configuration
+        zh_Hans: 复制此地址并粘贴到 Slack 应用的事件订阅配置中
+        zh_Hant: 複製此地址並貼到 Slack 應用的事件訂閱設定中
+        ja_JP: この URL をコピーして Slack アプリのイベントサブスクリプション設定に貼り付けてください
+        th_TH: คัดลอก URL นี้แล้ววางในการตั้งค่าการสมัครรับเหตุการณ์ของแอป Slack ของคุณ
+        vi_VN: Sao chép URL này và dán vào cấu hình đăng ký sự kiện của ứng dụng Slack của bạn
+        es_ES: Copie esta URL y péguela en la configuración de suscripción de eventos de su aplicación Slack
+      type: webhook-url
+      required: false
+      default: ""
     - name: bot_token
       label:
         en_US: Bot Token
         zh_Hans: 机器人令牌
+        zh_Hant: 機器人令牌
+        ja_JP: ボットトークン
+        th_TH: โทเค็นบอท
+        vi_VN: Mã thông báo Bot
+        es_ES: Token del bot
       type: string
       required: true
       default: ""
@@ -22,6 +64,11 @@ spec:
       label:
         en_US: signing_secret
         zh_Hans: 密钥
+        zh_Hant: 密鑰
+        ja_JP: 署名シークレット
+        th_TH: คีย์ลายเซ็น
+        vi_VN: Khóa ký
+        es_ES: Secreto de firma
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/telegram.yaml

@@ -5,23 +5,50 @@ metadata:
   label:
     en_US: Telegram
     zh_Hans: 电报
+    zh_Hant: Telegram
+    ja_JP: Telegram
+    th_TH: Telegram
+    vi_VN: Telegram
+    es_ES: Telegram
   description:
     en_US: Telegram Adapter
-    zh_Hans: 电报适配器，请查看文档了解使用方式
+    zh_Hans: Telegram 适配器，请查看文档了解使用方式
+    zh_Hant: Telegram 適配器，請查看文件了解使用方式
+    ja_JP: Telegram アダプター。使用方法の詳細については、ドキュメントを参照してください。
+    th_TH: อะแดปเตอร์ Telegram โปรดดูเอกสารประกอบสำหรับวิธีการใช้งาน
+    vi_VN: Bộ điều hợp Telegram, vui lòng xem tài liệu để biết cách sử dụng
+    es_ES: Adaptador de Telegram, consulte la documentación para obtener instrucciones de uso
   icon: telegram.svg
 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:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
+        ja_JP: トークン
+        th_TH: โทเค็น
+        vi_VN: Mã thông báo
+        es_ES: Token
       type: string
       required: true
-      default: ""
+      default: "token_from_botfather"
     - name: markdown_card
       label:
         en_US: Markdown Card
         zh_Hans: 是否使用 Markdown 卡片
+        zh_Hant: 是否使用 Markdown 卡片
+        ja_JP: Markdown カードを使用
+        th_TH: การ์ด Markdown
+        vi_VN: Thẻ Markdown
+        es_ES: Tarjeta Markdown
       type: boolean
       required: false
       default: true
@@ -29,9 +56,19 @@ spec:
       label:
         en_US: Enable Stream Reply Mode
         zh_Hans: 启用电报流式回复模式
+        zh_Hant: 啟用 Telegram 串流回覆模式
+        ja_JP: ストリーミング返信モードを有効化
+        th_TH: เปิดใช้งานโหมดตอบกลับแบบสตรีม
+        vi_VN: Bật chế độ trả lời trực tuyến
+        es_ES: Habilitar modo de respuesta en streaming
       description:
         en_US: If enabled, the bot will use the stream of telegram reply mode
         zh_Hans: 如果启用，将使用电报流式方式来回复内容
+        zh_Hant: 如果啟用，將使用 Telegram 串流方式來回覆內容
+        ja_JP: 有効にすると、ボットはストリーミングモードでメッセージに返信します
+        th_TH: หากเปิดใช้งาน บอทจะใช้โหมดสตรีมของ Telegram ในการตอบกลับ
+        vi_VN: Nếu bật, bot sẽ sử dụng chế độ trả lời trực tuyến của Telegram
+        es_ES: Si está habilitado, el bot usará el modo de respuesta en streaming de Telegram
       type: boolean
       required: true
       default: false

src/langbot/pkg/platform/sources/websocket.yaml

@@ -5,11 +5,21 @@ metadata:
   label:
     en_US: "WebSocket Chat"
     zh_Hans: "WebSocket 聊天"
+    zh_Hant: "WebSocket 聊天"
+    th_TH: "แชท WebSocket"
+    vi_VN: "Trò chuyện WebSocket"
+    es_ES: "Chat WebSocket"
   description:
     en_US: "WebSocket adapter for bidirectional real-time communication"
     zh_Hans: "用于双向实时通信的 WebSocket 适配器"
+    zh_Hant: "用於雙向即時通訊的 WebSocket 適配器"
+    th_TH: "อะแดปเตอร์ WebSocket สำหรับการสื่อสารแบบเรียลไทม์สองทิศทาง"
+    vi_VN: "Bộ điều hợp WebSocket cho giao tiếp thời gian thực hai chiều"
+    es_ES: "Adaptador WebSocket para comunicación bidireccional en tiempo real"
   icon: ""
 spec:
+  categories:
+    - protocol
   config: []
 execution:
   python:

src/langbot/pkg/platform/sources/wechatpad.yaml

@@ -4,17 +4,26 @@ metadata:
   name: wechatpad
   label:
     en_US: WeChatPad
-    zh_CN: WeChatPad（个人微信ipad）
+    zh_Hans: WeChatPad（个人微信ipad）
+    zh_Hant: WeChatPad（個人微信iPad）
   description:
     en_US: WeChatPad Adapter
-    zh_CN: WeChatPad 适配器
+    zh_Hans: WeChatPad 适配器，基于WeChatPad的个人微信解决方案，请查看文档了解使用方式
+    zh_Hant: WeChatPad 適配器，基於 WeChatPad 的個人微信解決方案，請查看文件了解使用方式
   icon: wechatpad.png
 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:
         en_US: WeChatPad ERL
         zh_CN: WeChatPad URL
+        zh_Hant: WeChatPad URL
       type: string
       required: true
       default: ""
@@ -22,6 +31,7 @@ spec:
       label:
         en_US: WeChatPad_Ws
         zh_CN: WeChatPad_Ws
+        zh_Hant: WeChatPad_Ws
       type: string
       required: true
       default: ""
@@ -29,6 +39,7 @@ spec:
       label:
         en_US: Admin_Key
         zh_CN: 管理员密匙
+        zh_Hant: 管理員密鑰
       type: string
       required: true
       default: ""
@@ -36,6 +47,7 @@ spec:
       label:
         en_US: Token
         zh_CN: 令牌
+        zh_Hant: 令牌
       type: string
       required: true
       default: ""
@@ -43,6 +55,7 @@ spec:
       label:
         en_US: wxid
         zh_CN: wxid
+        zh_Hant: wxid
       type: string
       required: true
       default: ""

src/langbot/pkg/platform/sources/wecom.yaml

@@ -5,16 +5,38 @@ metadata:
   label:
     en_US: WeCom
     zh_Hans: 企业微信
+    zh_Hant: 企業微信
   description:
     en_US: WeCom Adapter
-    zh_Hans: 企业微信适配器，请查看文档了解使用方式
+    zh_Hans: 企业微信内部机器人，请查看文档了解使用方式
+    zh_Hant: 企業微信內部機器人，請查看文件了解使用方式
   icon: wecom.png
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+      description:
+        en_US: Copy this URL and paste it into your WeCom app's webhook configuration
+        zh_Hans: 复制此地址并粘贴到企业微信应用的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到企業微信應用的 Webhook 設定中
+      type: webhook-url
+      required: false
+      default: ""
     - name: corpid
       label:
         en_US: Corpid
         zh_Hans: 企业ID
+        zh_Hant: 企業ID
       type: string
       required: true
       default: ""
@@ -22,6 +44,7 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥 (Secret)
+        zh_Hant: 密鑰 (Secret)
       type: string
       required: true
       default: ""
@@ -29,6 +52,7 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌 (Token)
+        zh_Hant: 令牌 (Token)
       type: string
       required: true
       default: ""
@@ -36,6 +60,7 @@ spec:
       label:
         en_US: EncodingAESKey
         zh_Hans: 消息加解密密钥 (EncodingAESKey)
+        zh_Hant: 訊息加解密密鑰 (EncodingAESKey)
       type: string
       required: true
       default: ""
@@ -43,9 +68,11 @@ spec:
       label:
         en_US: API Base URL
         zh_Hans: API 基础 URL
+        zh_Hant: API 基礎 URL
       description:
         en_US: API Base URL, used for accessing the WeCom API. If you are deploying in an internal network environment and accessing the WeCom Customer Service API through a reverse proxy, please fill in this item according to the documentation.
         zh_Hans: 可选，若您部署在内网环境并通过反向代理访问企业微信 API，可根据文档填写此项
+        zh_Hant: 可選，若您部署在內網環境並透過反向代理存取企業微信 API，可根據文件填寫此項
       type: string
       required: false
       default: "https://qyapi.weixin.qq.com/cgi-bin"

src/langbot/pkg/platform/sources/wecombot.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 import typing
 import asyncio
+import time
 import traceback
 
 import datetime
@@ -126,6 +127,107 @@ 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
         )
@@ -192,6 +294,8 @@ 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
 
     def __init__(self, config: dict, logger: EventLogger):
         enable_webhook = config.get('enable-webhook', False)
@@ -228,8 +332,9 @@ 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={},
         )
-        self.listeners = {}
 
     async def reply_message(
         self,
@@ -277,14 +382,8 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             return {'stream': success}
 
     async def is_stream_output_supported(self) -> bool:
-        """智能机器人侧默认开启流式能力。
-
-        Returns:
-            bool: 恒定返回 True。
-
-        Example:
-            流水线执行阶段会调用此方法以确认是否启用流式。"""
-        return True
+        """Whether streaming output is enabled for this bot instance."""
+        return self.config.get('enable-stream-reply', True)
 
     async def send_message(self, target_type, target_id, message):
         _ws_mode = not self.config.get('enable-webhook', False)
@@ -317,6 +416,9 @@ 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())
 
@@ -324,6 +426,75 @@ 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 _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]
+
+    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')
+
+            session_id = None
+            user_id = None
+            message_id = None
+            stream_id = None
+            if session:
+                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 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()}')
+
     async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
         _ws_mode = not self.config.get('enable-webhook', False)
         if _ws_mode:

src/langbot/pkg/platform/sources/wecombot.yaml

@@ -5,16 +5,25 @@ metadata:
   label:
     en_US: WeComBot
     zh_Hans: 企业微信智能机器人
+    zh_Hant: 企業微信智慧機器人
   description:
     en_US: WeComBot Adapter
-    zh_Hans: 企业微信智能机器人适配器，请查看文档了解使用方式
+    zh_Hans: 企业微信智能机器人，支持长连接和 Webhook 两种接入方式，请查看文档了解使用方式
+    zh_Hant: 企業微信智慧機器人，支援長連線和 Webhook 兩種接入方式，請查看文件了解使用方式
   icon: wecombot.png
 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:
         en_US: BotId
         zh_Hans: 机器人ID (BotId)
+        zh_Hant: 機器人ID (BotId)
       type: string
       required: true
       default: ""
@@ -22,6 +31,7 @@ spec:
       label:
         en_US: Robot Name
         zh_Hans: 机器人名称
+        zh_Hant: 機器人名稱
       type: string
       required: true
       default: ""
@@ -29,19 +39,39 @@ spec:
       label:
         en_US: Enable Webhook Mode
         zh_Hans: 启用Webhook模式
+        zh_Hant: 啟用 Webhook 模式
       description:
         en_US: If enabled, the bot will use webhook mode to receive messages. Otherwise, it will use WS long connection mode
         zh_Hans: 如果启用，机器人将使用 Webhook 模式接收消息。否则，将使用 WS 长连接模式
+        zh_Hant: 如果啟用，機器人將使用 Webhook 模式接收訊息。否則，將使用 WS 長連線模式
       type: boolean
       required: true
       default: false
+    - name: webhook_url
+      label:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+      description:
+        en_US: Copy this URL and paste it into your WeComBot webhook configuration
+        zh_Hans: 复制此地址并粘贴到企业微信智能机器人的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到企業微信智慧機器人的 Webhook 設定中
+      type: webhook-url
+      required: false
+      default: ""
+      show_if:
+        field: enable-webhook
+        operator: eq
+        value: true
     - name: Secret
       label:
         en_US: Secret
         zh_Hans: 机器人密钥 (Secret)
+        zh_Hant: 機器人密鑰 (Secret)
       description:
         en_US: Required for WebSocket long connection mode
         zh_Hans: 使用 WS 长连接模式时必填
+        zh_Hant: 使用 WS 長連線模式時必填
       type: string
       required: false
       default: ""
@@ -49,9 +79,11 @@ spec:
       label:
         en_US: Corpid
         zh_Hans: 企业ID
+        zh_Hant: 企業ID
       description:
         en_US: Required for Webhook mode
         zh_Hans: 使用 Webhook 模式时必填
+        zh_Hant: 使用 Webhook 模式時必填
       type: string
       required: false
       default: ""
@@ -59,9 +91,11 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌 (Token)
+        zh_Hant: 令牌 (Token)
       description:
         en_US: Required for Webhook mode
         zh_Hans: 使用 Webhook 模式时必填
+        zh_Hant: 使用 Webhook 模式時必填
       type: string
       required: false
       default: ""
@@ -69,12 +103,26 @@ spec:
       label:
         en_US: EncodingAESKey
         zh_Hans: 消息加解密密钥 (EncodingAESKey)
+        zh_Hant: 訊息加解密密鑰 (EncodingAESKey)
       description:
         en_US: Required for Webhook mode. Optional for WebSocket mode (used for file decryption)
         zh_Hans: 使用 Webhook 模式时必填。WebSocket 模式下可选（用于文件解密）
+        zh_Hant: 使用 Webhook 模式時必填。WebSocket 模式下可選（用於檔案解密）
       type: string
       required: false
       default: ""
+    - name: enable-stream-reply
+      label:
+        en_US: Enable Stream Reply
+        zh_Hans: 启用流式回复
+        zh_Hant: 啟用串流回覆
+      description:
+        en_US: If enabled, the bot will use streaming mode to reply messages
+        zh_Hans: 如果启用，机器人将使用流式模式回复消息
+        zh_Hant: 如果啟用，機器人將使用串流模式回覆訊息
+      type: boolean
+      required: false
+      default: true
 execution:
   python:
     path: ./wecombot.py

src/langbot/pkg/platform/sources/wecomcs.yaml

@@ -5,16 +5,37 @@ metadata:
   label:
     en_US: WeComCustomerService
     zh_Hans: 企业微信客服
+    zh_Hant: 企業微信客服
   description:
     en_US: WeComCSAdapter
-    zh_Hans: 企业微信客服适配器
+    zh_Hans: 企业微信对外客服机器人，需要公网地址以接收消息推送，请查看文档了解使用方式
+    zh_Hant: 企業微信對外客服機器人，需要公網地址以接收訊息推送，請查看文件了解使用方式
   icon: wecom.png
 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:
+        en_US: Webhook Callback URL
+        zh_Hans: Webhook 回调地址
+        zh_Hant: Webhook 回調地址
+      description:
+        en_US: Copy this URL and paste it into your WeCom Customer Service webhook configuration
+        zh_Hans: 复制此地址并粘贴到企业微信客服的 Webhook 配置中
+        zh_Hant: 複製此地址並貼到企業微信客服的 Webhook 設定中
+      type: webhook-url
+      required: false
+      default: ""
     - name: corpid
       label:
         en_US: Corpid
         zh_Hans: 企业ID
+        zh_Hant: 企業ID
       type: string
       required: true
       default: ""
@@ -22,6 +43,7 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥
+        zh_Hant: 密鑰
       type: string
       required: true
       default: ""
@@ -29,6 +51,7 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
+        zh_Hant: 令牌
       type: string
       required: true
       default: ""
@@ -36,6 +59,7 @@ spec:
       label:
         en_US: EncodingAESKey
         zh_Hans: 消息加解密密钥
+        zh_Hant: 訊息加解密密鑰
       type: string
       required: true
       default: ""
@@ -43,9 +67,11 @@ spec:
       label:
         en_US: API Base URL
         zh_Hans: API 基础 URL
+        zh_Hant: API 基礎 URL
       description:
         en_US: API Base URL, used for accessing the WeCom API. If you are deploying in an internal network environment and accessing the WeCom Customer Service API through a reverse proxy, please fill in this item according to the documentation.
         zh_Hans: 可选，若您部署在内网环境并通过反向代理访问企业微信 API，可根据文档修改此项
+        zh_Hant: 可選，若您部署在內網環境並透過反向代理存取企業微信 API，可根據文件修改此項
       type: string
       required: false
       default: "https://qyapi.weixin.qq.com/cgi-bin"

src/langbot/pkg/plugin/connector.py

@@ -2,6 +2,9 @@
 from __future__ import annotations
 
 import asyncio
+import io
+import time
+import zipfile
 from typing import Any
 import typing
 import os
@@ -192,6 +195,30 @@ class PluginRuntimeConnector:
 
         return await self.handler.ping()
 
+    def _extract_deps_metadata(
+        self,
+        file_bytes: bytes,
+        task_context: taskmgr.TaskContext | None,
+    ):
+        """Extract dependency count from requirements.txt inside plugin zip."""
+        if task_context is None:
+            return
+        try:
+            with zipfile.ZipFile(io.BytesIO(file_bytes)) as zf:
+                for name in zf.namelist():
+                    if name.endswith('requirements.txt'):
+                        content = zf.read(name).decode('utf-8', errors='ignore')
+                        deps = [
+                            line.strip()
+                            for line in content.splitlines()
+                            if line.strip() and not line.strip().startswith('#')
+                        ]
+                        task_context.metadata['deps_total'] = len(deps)
+                        task_context.metadata['deps_list'] = deps
+                        break
+        except Exception:
+            pass
+
     async def install_plugin(
         self,
         install_source: PluginInstallSource,
@@ -201,23 +228,44 @@ class PluginRuntimeConnector:
         if install_source == PluginInstallSource.LOCAL:
             # transfer file before install
             file_bytes = install_info['plugin_file']
+            self._extract_deps_metadata(file_bytes, task_context)
             file_key = await self.handler.send_file(file_bytes, 'lbpkg')
             install_info['plugin_file_key'] = file_key
             del install_info['plugin_file']
             self.ap.logger.info(f'Transfered file {file_key} to plugin runtime')
         elif install_source == PluginInstallSource.GITHUB:
-            # download and transfer file
+            # download and transfer file with streaming progress
             try:
                 async with httpx.AsyncClient(
                     trust_env=True,
                     follow_redirects=True,
-                    timeout=20,
+                    timeout=60,
                 ) as client:
-                    response = await client.get(
-                        install_info['asset_url'],
-                    )
-                    response.raise_for_status()
-                    file_bytes = response.content
+                    async with client.stream('GET', install_info['asset_url']) as response:
+                        response.raise_for_status()
+                        total = int(response.headers.get('content-length', 0))
+                        downloaded = 0
+                        chunks: list[bytes] = []
+                        start_time = time.time()
+
+                        if task_context is not None:
+                            task_context.set_current_action('downloading plugin package')
+                            task_context.metadata['download_total'] = total
+                            task_context.metadata['download_current'] = 0
+                            task_context.metadata['download_speed'] = 0
+
+                        async for chunk in response.aiter_bytes(chunk_size=8192):
+                            chunks.append(chunk)
+                            downloaded += len(chunk)
+
+                            if task_context is not None:
+                                elapsed = time.time() - start_time
+                                task_context.metadata['download_current'] = downloaded
+                                task_context.metadata['download_total'] = total
+                                task_context.metadata['download_speed'] = downloaded / elapsed if elapsed > 0 else 0
+
+                    file_bytes = b''.join(chunks)
+                    self._extract_deps_metadata(file_bytes, task_context)
                     file_key = await self.handler.send_file(file_bytes, 'lbpkg')
                     install_info['plugin_file_key'] = file_key
                     self.ap.logger.info(f'Transfered file {file_key} to plugin runtime')
@@ -236,6 +284,11 @@ class PluginRuntimeConnector:
                 if task_context is not None:
                     task_context.trace(trace)
 
+            # Forward structured metadata from runtime
+            metadata = ret.get('metadata', None)
+            if metadata is not None and task_context is not None:
+                task_context.metadata.update(metadata)
+
     async def upgrade_plugin(
         self,
         plugin_author: str,

src/langbot/pkg/provider/modelmgr/modelmgr.py

@@ -9,7 +9,6 @@ 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:
@@ -24,6 +23,8 @@ class ModelManager:
 
     embedding_models: list[requester.RuntimeEmbeddingModel]
 
+    rerank_models: list[requester.RuntimeRerankModel]
+
     requester_components: list[engine.Component]
 
     requester_dict: dict[str, type[requester.ProviderAPIRequester]]
@@ -32,6 +33,7 @@ class ModelManager:
         self.ap = ap
         self.llm_models = []
         self.embedding_models = []
+        self.rerank_models = []
         self.requester_components = []
         self.requester_dict = {}
 
@@ -64,8 +66,7 @@ class ModelManager:
 
         self.llm_models = []
         self.embedding_models = []
-
-        # Load all providers first
+        self.rerank_models = []
         self.provider_dict = {}
         providers_result = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(persistence_model.ModelProvider)
@@ -110,6 +111,22 @@ 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(
@@ -212,6 +229,26 @@ 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:
@@ -227,7 +264,8 @@ class ModelManager:
             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}
+            ap=self.ap,
+            config={'base_url': provider_entity.base_url},
         )
         await requester_inst.initialize()
 
@@ -268,6 +306,9 @@ 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
@@ -304,6 +345,22 @@ 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', {})
@@ -351,7 +408,6 @@ 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:
@@ -359,7 +415,6 @@ 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:
@@ -367,6 +422,13 @@ 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:
@@ -381,6 +443,13 @@ 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 != '':

src/langbot/pkg/provider/modelmgr/requester.py

@@ -247,6 +247,40 @@ 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"""
@@ -284,6 +318,24 @@ 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"""
 
@@ -303,6 +355,14 @@ 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,
@@ -368,3 +428,23 @@ 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')

src/langbot/pkg/provider/modelmgr/requesters/302aichatcmpl.yaml

@@ -25,6 +25,7 @@ spec:
   support_type:
   - llm
   - text-embedding
+  - rerank
   provider_category: maas
 execution:
   python:

src/langbot/pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml

@@ -24,6 +24,7 @@ spec:
     default: 120
   support_type:
   - llm
+  - rerank
   provider_category: maas
 execution:
   python:

src/langbot/pkg/provider/modelmgr/requesters/chatcmpl.py

@@ -31,6 +31,192 @@ 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,
@@ -429,3 +615,88 @@ 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 []

src/langbot/pkg/provider/modelmgr/requesters/chatcmpl.yaml

@@ -25,6 +25,7 @@ spec:
   support_type:
   - llm
   - text-embedding
+  - rerank
   provider_category: manufacturer
 execution:
   python:

src/langbot/pkg/provider/modelmgr/requesters/chroma.svg

@@ -0,0 +1,8 @@
+<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>

src/langbot/pkg/provider/modelmgr/requesters/chromaembed.py

@@ -0,0 +1,61 @@
+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)}')

src/langbot/pkg/provider/modelmgr/requesters/chromaembed.yaml

@@ -0,0 +1,21 @@
+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

src/langbot/pkg/provider/modelmgr/requesters/cohere.svg

@@ -0,0 +1 @@
+<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>

src/langbot/pkg/provider/modelmgr/requesters/coherererank.yaml

@@ -0,0 +1,31 @@
+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

src/langbot/pkg/provider/modelmgr/requesters/geminichatcmpl.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import typing
+import httpx
 
 from . import chatcmpl
 
@@ -20,6 +21,68 @@ 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,

src/langbot/pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml

@@ -25,6 +25,7 @@ spec:
   support_type:
   - llm
   - text-embedding
+  - rerank
   provider_category: maas
 execution:
   python:

src/langbot/pkg/provider/modelmgr/requesters/jina.svg

@@ -0,0 +1 @@
+<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>