feat: update version to 4.9.0 in pyproject.toml, __init__.py, and uv.lock

Merge branch 'master' into feat/dbm20-rag

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

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

.pre-commit-config.yaml

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

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://link.langbot.app/en/docs/features">Features</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">Docs</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features">Features</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
 <a href="https://space.langbot.app/cloud">Cloud</a> ｜
 <a href="https://space.langbot.app">Plugin Market</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
@@ -45,7 +45,7 @@ LangBot is an **open-source, production-grade platform** for building AI-powered
 - **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
 - **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
 
-[→ Learn more about all features](https://link.langbot.app/en/docs/features)
+[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
 
 ---
 
@@ -76,7 +76,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**More options:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -124,7 +124,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
 
-[→ View all integrations](https://link.langbot.app/en/docs/features)
+[→ View all integrations](https://docs.langbot.app/en/insight/features)
 
 ---
 

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://link.langbot.app/zh/docs/features">特性</a> ｜
-<a href="https://link.langbot.app/zh/docs/guide">文档</a> ｜
-<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
+<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
+<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app/cloud">Cloud</a> ｜
 <a href="https://space.langbot.app">插件市场</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">路线图</a>
@@ -34,6 +34,8 @@
 
 ---
 
+## 什么是 LangBot？
+
 LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
 
 ### 核心能力
@@ -41,11 +43,11 @@ LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时
 - **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
 - **全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
 - **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
-- **插件生态** — 数百个插件，跨进程的事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
+- **插件生态** — 数百个插件，事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
 - **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
 - **多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
 
-[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
+[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
 
 ---
 
@@ -76,7 +78,7 @@ 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://link.langbot.app/zh/docs/docker) · [手动部署](https://link.langbot.app/zh/docs/manual-deploy) · [宝塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -125,7 +127,7 @@ docker compose up -d
 | [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
 | [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
 
-[→ 查看完整集成列表](https://link.langbot.app/zh/docs/features)
+[→ 查看完整集成列表](https://docs.langbot.app/zh/insight/features.html)
 
 ### TTS（语音合成）
 

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://link.langbot.app/en/docs/features">Características</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">Documentación</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Características</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">Mercado de Plugins</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
 
@@ -44,7 +44,7 @@ LangBot es una **plataforma de código abierto y grado de producción** para con
 - **Panel de Gestión Web** — Configure, gestione y monitoree sus bots a través de una interfaz de navegador intuitiva. Sin necesidad de editar YAML.
 - **Arquitectura Multi-Pipeline** — Diferentes bots para diferentes escenarios, con monitoreo completo y manejo de excepciones.
 
-[→ Conocer más sobre todas las funcionalidades](https://link.langbot.app/en/docs/features)
+[→ Conocer más sobre todas las funcionalidades](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Más opciones:** [Docker](https://link.langbot.app/en/docs/docker) · [Manual](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
 
-[→ Ver todas las integraciones](https://link.langbot.app/en/docs/features)
+[→ Ver todas las integraciones](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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://link.langbot.app/en/docs/features">Fonctionnalités</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">Documentation</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">Marché des Plugins</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
 
@@ -44,7 +44,7 @@ LangBot est une **plateforme open-source de niveau production** pour créer des
 - **Panneau de Gestion Web** — Configurez, gérez et surveillez vos bots via une interface navigateur intuitive. Aucune édition de YAML requise.
 - **Architecture Multi-Pipeline** — Différents bots pour différents scénarios, avec surveillance complète et gestion des exceptions.
 
-[→ En savoir plus sur toutes les fonctionnalités](https://link.langbot.app/en/docs/features)
+[→ En savoir plus sur toutes les fonctionnalités](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Plus d'options :** [Docker](https://link.langbot.app/en/docs/docker) · [Manuel](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
 
-[→ Voir toutes les intégrations](https://link.langbot.app/en/docs/features)
+[→ Voir toutes les intégrations](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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://link.langbot.app/ja/docs/features">機能</a> ｜
-<a href="https://link.langbot.app/ja/docs/guide">ドキュメント</a> ｜
-<a href="https://link.langbot.app/ja/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/ja/insight/features.html">機能</a> ｜
+<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a> ｜
+<a href="https://docs.langbot.app/ja/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">プラグインマーケット</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
 
@@ -44,7 +44,7 @@ LangBot は、AI搭載のインスタントメッセージングボットを構
 - **Web管理パネル** — 直感的なブラウザインターフェースからボットの設定、管理、監視が可能。YAML編集は不要。
 - **マルチパイプラインアーキテクチャ** — 異なるシナリオに異なるボットを配置し、包括的な監視と例外処理を実現。
 
-[→ すべての機能について詳しく見る](https://link.langbot.app/ja/docs/features)
+[→ すべての機能について詳しく見る](https://docs.langbot.app/ja/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![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://link.langbot.app/en/docs/docker) · [手動デプロイ](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**その他:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
 
-[→ すべての統合を表示](https://link.langbot.app/en/docs/features)
+[→ すべての統合を表示](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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://link.langbot.app/en/docs/features">기능</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">문서</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">기능</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">문서</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">플러그인 마켓</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">로드맵</a>
 
@@ -44,7 +44,7 @@ LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈
 - **웹 관리 패널** — 직관적인 브라우저 인터페이스로 봇을 구성, 관리 및 모니터링. YAML 편집 불필요.
 - **멀티 파이프라인 아키텍처** — 다양한 시나리오에 맞는 다양한 봇 구성, 종합 모니터링 및 예외 처리.
 
-[→ 모든 기능 자세히 보기](https://link.langbot.app/en/docs/features)
+[→ 모든 기능 자세히 보기](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**더 많은 옵션:** [Docker](https://link.langbot.app/en/docs/docker) · [수동 배포](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
 
-[→ 모든 통합 보기](https://link.langbot.app/en/docs/features)
+[→ 모든 통합 보기](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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://link.langbot.app/en/docs/features">Возможности</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">Документация</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Возможности</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">Магазин плагинов</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
 
@@ -44,7 +44,7 @@ LangBot — это **платформа с открытым исходным к
 - **Веб-панель управления** — Настраивайте, управляйте и мониторьте ваших ботов через интуитивный браузерный интерфейс. Ручное редактирование YAML не требуется.
 - **Мультиконвейерная архитектура** — Разные боты для разных сценариев с комплексным мониторингом и обработкой исключений.
 
-[→ Подробнее обо всех возможностях](https://link.langbot.app/en/docs/features)
+[→ Подробнее обо всех возможностях](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Другие варианты:** [Docker](https://link.langbot.app/en/docs/docker) · [Ручная установка](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
 | [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
 
-[→ Смотреть все интеграции](https://link.langbot.app/en/docs/features)
+[→ Смотреть все интеграции](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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://link.langbot.app/zh/docs/features">特性</a> ｜
-<a href="https://link.langbot.app/zh/docs/guide">文件</a> ｜
-<a href="https://link.langbot.app/zh/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
+<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a> ｜
+<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">外掛市場</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">路線圖</a>
 
@@ -46,7 +46,7 @@ LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時
 - **Web 管理面板** — 透過瀏覽器直觀地配置、管理和監控機器人，無需手動編輯設定檔。
 - **多流水線架構** — 不同機器人用於不同場景，具備全面的監控和異常處理能力。
 
-[→ 了解更多功能特性](https://link.langbot.app/zh/docs/features)
+[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
 
 ---
 
@@ -77,7 +77,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**更多方式：** [Docker](https://link.langbot.app/zh/docs/docker) · [手動部署](https://link.langbot.app/zh/docs/manual-deploy) · [寶塔面板](https://link.langbot.app/zh/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [寶塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -139,7 +139,7 @@ docker compose up -d
 |-----------|------|
 | 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
 
-[→ 查看完整整合列表](https://link.langbot.app/zh/docs/features)
+[→ 查看完整整合列表](https://docs.langbot.app/zh/insight/features.html)
 
 ---
 

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://link.langbot.app/en/docs/features">Tính năng</a> ｜
-<a href="https://link.langbot.app/en/docs/guide">Tài liệu</a> ｜
-<a href="https://link.langbot.app/en/docs/api">API</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Tính năng</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">Chợ Plugin</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
 
@@ -44,7 +44,7 @@ LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để x
 - **Bảng quản lý Web** — Cấu hình, quản lý và giám sát bot thông qua giao diện trình duyệt trực quan. Không cần chỉnh sửa YAML.
 - **Kiến trúc đa Pipeline** — Các bot khác nhau cho các kịch bản khác nhau, với giám sát toàn diện và xử lý ngoại lệ.
 
-[→ Tìm hiểu thêm về tất cả tính năng](https://link.langbot.app/en/docs/features)
+[→ Tìm hiểu thêm về tất cả tính năng](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
@@ -75,7 +75,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Thêm tùy chọn:** [Docker](https://link.langbot.app/en/docs/docker) · [Thủ công](https://link.langbot.app/en/docs/manual-deploy) · [BTPanel](https://link.langbot.app/en/docs/bt-panel) · [Kubernetes](./docker/README_K8S.md)
+**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -123,7 +123,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
 
-[→ Xem tất cả tích hợp](https://link.langbot.app/en/docs/features)
+[→ Xem tất cả tích hợp](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

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

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 = "4.9.5"
+version = "4.9.0"
 description = "Production-grade platform for building agentic IM bots"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -61,10 +61,10 @@ dependencies = [
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
     "langchain-text-splitters>=0.0.1",
-    "chromadb>=1.0.0,<2.0.0",
+    "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
     "pyseekdb==1.1.0.post3",
-    "langbot-plugin==0.3.6",
+    "langbot-plugin==0.3.0",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
 """LangBot - Production-grade platform for building agentic IM bots"""
 
-__version__ = '4.9.5'
+__version__ = '4.9.0'

src/langbot/libs/dingtalk_api/api.py

@@ -272,30 +272,15 @@ class DingTalkClient:
 
                 message_data['Type'] = 'audio'
             elif incoming_message.message_type == 'file':
-                # 获取原始数据字典并提取嵌套的文件信息
-                raw_data = incoming_message.to_dict()
-                file_info = raw_data.get('content', {})
-
-                # 兼容处理：如果 content 仍为 JSON 字符串则进行解析
-                if isinstance(file_info, str):
-                    try:
-                        file_info = json.loads(file_info)
-                    except (json.JSONDecodeError, TypeError):
-                        file_info = {}
-
-                download_code = file_info.get('downloadCode')
-                file_name = file_info.get('fileName')
-
-                if download_code and file_name:
-                    # 转换 downloadCode 为可下载的真实 URL
-                    message_data['File'] = await self.get_file_url(download_code)
-                    message_data['Name'] = file_name
+                down_list = incoming_message.get_down_list()
+                if len(down_list) >= 2:
+                    message_data['File'] = await self.get_file_url(down_list[0])
+                    message_data['Name'] = down_list[1]
                 else:
                     if self.logger:
-                        await self.logger.error(f'Failed to extract file info from message content: {file_info}')
+                        await self.logger.error(f'get_down_list() returned fewer than 2 elements: {down_list}')
                     message_data['File'] = None
                     message_data['Name'] = None
-
                 message_data['Type'] = 'file'
 
             copy_message_data = message_data.copy()

src/langbot/libs/openclaw_weixin_api/__init__.py

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

src/langbot/libs/openclaw_weixin_api/client.py

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

src/langbot/libs/openclaw_weixin_api/types.py

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

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -6,8 +6,7 @@ import traceback
 import uuid
 import xml.etree.ElementTree as ET
 from dataclasses import dataclass, field
-import re
-from typing import Any, Callable, Optional, Tuple
+from typing import Any, Callable, Optional
 from urllib.parse import unquote
 
 import httpx
@@ -64,9 +63,6 @@ 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。"""
@@ -77,7 +73,6 @@ class StreamSessionManager:
         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:
@@ -87,32 +82,6 @@ class StreamSessionManager:
     def get_session(self, stream_id: str) -> Optional[StreamSession]:
         return self._sessions.get(stream_id)
 
-    def get_session_by_feedback_id(self, feedback_id: str) -> Optional[StreamSession]:
-        """根据 feedback_id 查找会话。
-
-        Args:
-            feedback_id: 企业微信反馈事件中的反馈 ID。
-
-        Returns:
-            Optional[StreamSession]: 找到的会话实例，未找到返回 None。
-        """
-        if not feedback_id:
-            return None
-        stream_id = self._feedback_index.get(feedback_id)
-        if stream_id:
-            return self._sessions.get(stream_id)
-        return None
-
-    def register_feedback_id(self, stream_id: str, feedback_id: str) -> None:
-        """注册 feedback_id 与 stream_id 的映射。
-
-        Args:
-            stream_id: 企业微信流式会话 ID。
-            feedback_id: 反馈 ID。
-        """
-        if feedback_id and stream_id:
-            self._feedback_index[feedback_id] = stream_id
-
     def create_or_get(self, msg_json: dict[str, Any]) -> tuple[StreamSession, bool]:
         """根据企业微信回调创建或获取会话。
 
@@ -230,366 +199,6 @@ class StreamSessionManager:
                 self._msg_index.pop(msg_id, None)
 
 
-def _decrypt_file(encrypted_data: bytes, aes_key_str: str) -> bytes:
-    """Decrypt AES-256-CBC encrypted file data.
-
-    Aligned with the official WeCom AI Bot Python SDK (crypto_utils.py).
-
-    Args:
-        encrypted_data: The raw encrypted bytes.
-        aes_key_str: Base64-encoded AES key (may lack padding).
-
-    Returns:
-        Decrypted bytes with PKCS#7 padding removed.
-    """
-    if not encrypted_data:
-        raise ValueError('encrypted_data is empty')
-    if not aes_key_str:
-        raise ValueError('aes_key is empty')
-
-    # Python's base64.b64decode requires proper padding (length % 4 == 0).
-    # Node.js Buffer.from tolerates missing '=', so we must pad manually.
-    remainder = len(aes_key_str) % 4
-    if remainder != 0:
-        aes_key_str = aes_key_str + '=' * (4 - remainder)
-    key = base64.b64decode(aes_key_str)
-
-    iv = key[:16]
-
-    cipher = AES.new(key, AES.MODE_CBC, iv)
-
-    # Ensure encrypted data is aligned to AES block size (16 bytes).
-    # Node.js setAutoPadding(false) silently handles unaligned data,
-    # but PyCryptodome will raise an error.
-    block_size = 16
-    data_remainder = len(encrypted_data) % block_size
-    if data_remainder != 0:
-        encrypted_data = encrypted_data + b'\x00' * (block_size - data_remainder)
-
-    decrypted = cipher.decrypt(encrypted_data)
-
-    # Remove PKCS#7 padding with validation
-    if len(decrypted) == 0:
-        raise ValueError('Decrypted data is empty')
-
-    pad_len = decrypted[-1]
-    if pad_len < 1 or pad_len > 32 or pad_len > len(decrypted):
-        raise ValueError(f'Invalid PKCS#7 padding value: {pad_len}')
-
-    # Verify all padding bytes are consistent
-    for i in range(len(decrypted) - pad_len, len(decrypted)):
-        if decrypted[i] != pad_len:
-            raise ValueError('Invalid PKCS#7 padding: padding bytes mismatch')
-
-    return decrypted[: len(decrypted) - pad_len]
-
-
-def _extract_filename(content_disposition: str) -> Optional[str]:
-    """Extract filename from a Content-Disposition header value."""
-    if not content_disposition:
-        return None
-    # RFC 5987: filename*=UTF-8''xxx
-    utf8_match = re.search(r"filename\*=UTF-8''([^;\s]+)", content_disposition, re.IGNORECASE)
-    if utf8_match:
-        return unquote(utf8_match.group(1))
-    # Standard: filename="xxx" or filename=xxx
-    match = re.search(r'filename="?([^";\s]+)"?', content_disposition, re.IGNORECASE)
-    if match:
-        return unquote(match.group(1))
-    return None
-
-
-def _bytes_to_data_uri(data: bytes) -> str:
-    """Convert raw bytes to a data URI with auto-detected MIME type."""
-    if data.startswith(b'\xff\xd8'):
-        mime_type = 'image/jpeg'
-    elif data.startswith(b'\x89PNG'):
-        mime_type = 'image/png'
-    elif data.startswith((b'GIF87a', b'GIF89a')):
-        mime_type = 'image/gif'
-    elif data.startswith(b'BM'):
-        mime_type = 'image/bmp'
-    elif data.startswith(b'II*\x00') or data.startswith(b'MM\x00*'):
-        mime_type = 'image/tiff'
-    elif data[:4] == b'%PDF':
-        mime_type = 'application/pdf'
-    elif data[:4] == b'PK\x03\x04':
-        mime_type = 'application/zip'
-    else:
-        mime_type = 'application/octet-stream'
-
-    base64_str = base64.b64encode(data).decode('utf-8')
-    return f'data:{mime_type};base64,{base64_str}'
-
-
-async def download_encrypted_file(
-    download_url: str, aes_key: str, logger: EventLogger
-) -> Tuple[Optional[bytes], Optional[str]]:
-    """Download an AES-encrypted file from WeChat Work and decrypt it.
-
-    Args:
-        download_url: The encrypted file download URL.
-        aes_key: The AES key for decryption (base64-encoded, per-message aeskey
-                 or platform EncodingAESKey).
-        logger: Logger instance.
-
-    Returns:
-        A tuple of (decrypted_bytes, filename) or (None, None) on failure.
-    """
-    if not download_url:
-        return None, None
-    if not aes_key:
-        await logger.error('download_encrypted_file: aes_key is empty, cannot decrypt')
-        return None, None
-
-    filename: Optional[str] = None
-    try:
-        async with httpx.AsyncClient(timeout=30.0) as client:
-            response = await client.get(download_url)
-            if response.status_code != 200:
-                await logger.error(f'Failed to download file (HTTP {response.status_code}): {response.text[:200]}')
-                return None, None
-            encrypted_bytes = response.content
-            filename = _extract_filename(response.headers.get('content-disposition', ''))
-    except Exception:
-        await logger.error(f'Failed to download file: {traceback.format_exc()}')
-        return None, None
-
-    try:
-        decrypted = _decrypt_file(encrypted_bytes, aes_key)
-        return decrypted, filename
-    except Exception:
-        await logger.error(f'Failed to decrypt file: {traceback.format_exc()}')
-        return None, None
-
-
-async def parse_wecom_bot_message(
-    msg_json: dict[str, Any], encoding_aes_key: str, logger: EventLogger
-) -> dict[str, Any]:
-    """Parse a decrypted WeChat Work AI Bot message JSON into a unified message dict.
-
-    This is the shared message parsing logic used by both webhook and WebSocket modes.
-
-    Args:
-        msg_json: The decrypted message JSON from WeChat Work.
-        encoding_aes_key: AES key for file decryption.
-        logger: Logger instance.
-
-    Returns:
-        A dict suitable for constructing a WecomBotEvent.
-    """
-    message_data: dict[str, Any] = {}
-
-    msg_type = msg_json.get('msgtype', '')
-    if msg_type:
-        message_data['msgtype'] = msg_type
-
-    if msg_json.get('chattype', '') == 'single':
-        message_data['type'] = 'single'
-    elif msg_json.get('chattype', '') == 'group':
-        message_data['type'] = 'group'
-
-    max_inline_file_size = 5 * 1024 * 1024
-
-    async def _safe_download(url: str, per_msg_aeskey: str = '') -> Tuple[Optional[bytes], Optional[str]]:
-        """Download and decrypt a file, preferring per-message aeskey over platform key."""
-        if not url:
-            return None, None
-        key = per_msg_aeskey or encoding_aes_key
-        if not key:
-            await logger.warning('No AES key available for file decryption, skipping download')
-            return None, None
-        return await download_encrypted_file(url, key, logger)
-
-    async def _safe_download_as_data_uri(url: str, per_msg_aeskey: str = '') -> Optional[str]:
-        """Download, decrypt, and convert to data URI for backward compatibility."""
-        data, _filename = await _safe_download(url, per_msg_aeskey)
-        if data:
-            return _bytes_to_data_uri(data)
-        return None
-
-    if msg_type == 'text':
-        message_data['content'] = msg_json.get('text', {}).get('content')
-    elif msg_type == 'markdown':
-        message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
-            'content', ''
-        )
-    elif msg_type == 'image':
-        image_info = msg_json.get('image', {})
-        picurl = image_info.get('url', '')
-        per_msg_aeskey = image_info.get('aeskey', '')
-        base64_data = await _safe_download_as_data_uri(picurl, per_msg_aeskey)
-        if base64_data:
-            message_data['picurl'] = base64_data
-            message_data['images'] = [base64_data]
-    elif msg_type == 'voice':
-        voice_info = msg_json.get('voice', {}) or {}
-        download_url = voice_info.get('url')
-        per_msg_aeskey = voice_info.get('aeskey', '')
-        message_data['voice'] = {
-            'url': download_url,
-            'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-            'filesize': voice_info.get('filesize') or voice_info.get('size'),
-            'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-        }
-        if voice_info.get('content'):
-            message_data['content'] = voice_info.get('content')
-        if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
-            voice_base64 = await _safe_download_as_data_uri(download_url, per_msg_aeskey)
-            if voice_base64:
-                message_data['voice']['base64'] = voice_base64
-    elif msg_type == 'video':
-        video_info = msg_json.get('video', {}) or {}
-        download_url = video_info.get('url')
-        per_msg_aeskey = video_info.get('aeskey', '')
-        video_data = {
-            'url': download_url,
-            'filesize': video_info.get('filesize') or video_info.get('size'),
-            'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-            'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-            'filename': video_info.get('filename') or video_info.get('name'),
-        }
-        if (video_data.get('filesize') or 0) <= max_inline_file_size:
-            video_base64 = await _safe_download_as_data_uri(download_url, per_msg_aeskey)
-            if video_base64:
-                video_data['base64'] = video_base64
-        message_data['video'] = video_data
-    elif msg_type == 'file':
-        file_info = msg_json.get('file', {}) or {}
-        download_url = file_info.get('url') or file_info.get('fileurl')
-        per_msg_aeskey = file_info.get('aeskey', '')
-        file_data = {
-            'filename': file_info.get('filename') or file_info.get('name'),
-            'filesize': file_info.get('filesize') or file_info.get('size'),
-            'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-            'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-            'download_url': download_url,
-            'extra': file_info,
-        }
-        if (file_data.get('filesize') or 0) <= max_inline_file_size:
-            file_bytes, dl_filename = await _safe_download(download_url, per_msg_aeskey)
-            if file_bytes:
-                file_data['base64'] = _bytes_to_data_uri(file_bytes)
-                if dl_filename and not file_data.get('filename'):
-                    file_data['filename'] = dl_filename
-        message_data['file'] = file_data
-    elif msg_type == 'link':
-        message_data['link'] = msg_json.get('link', {})
-        if not message_data.get('content'):
-            title = message_data['link'].get('title', '')
-            desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
-            message_data['content'] = '\n'.join(filter(None, [title, desc]))
-    elif msg_type == 'mixed':
-        items = msg_json.get('mixed', {}).get('msg_item', [])
-        texts = []
-        images = []
-        files = []
-        voices = []
-        videos = []
-        links = []
-        for item in items:
-            item_type = item.get('msgtype')
-            if item_type == 'text':
-                texts.append(item.get('text', {}).get('content', ''))
-            elif item_type == 'image':
-                img_info = item.get('image', {})
-                img_url = img_info.get('url')
-                img_aeskey = img_info.get('aeskey', '')
-                base64_data = await _safe_download_as_data_uri(img_url, img_aeskey)
-                if base64_data:
-                    images.append(base64_data)
-            elif item_type == 'file':
-                file_info = item.get('file', {}) or {}
-                download_url = file_info.get('url') or file_info.get('fileurl')
-                item_aeskey = file_info.get('aeskey', '')
-                file_data = {
-                    'filename': file_info.get('filename') or file_info.get('name'),
-                    'filesize': file_info.get('filesize') or file_info.get('size'),
-                    'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-                    'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-                    'download_url': download_url,
-                    'extra': file_info,
-                }
-                if (file_data.get('filesize') or 0) <= max_inline_file_size:
-                    file_bytes, dl_filename = await _safe_download(download_url, item_aeskey)
-                    if file_bytes:
-                        file_data['base64'] = _bytes_to_data_uri(file_bytes)
-                        if dl_filename and not file_data.get('filename'):
-                            file_data['filename'] = dl_filename
-                files.append(file_data)
-            elif item_type == 'voice':
-                voice_info = item.get('voice', {}) or {}
-                download_url = voice_info.get('url')
-                item_aeskey = voice_info.get('aeskey', '')
-                voice_data = {
-                    'url': download_url,
-                    'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-                    'filesize': voice_info.get('filesize') or voice_info.get('size'),
-                    'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-                }
-                if voice_info.get('content'):
-                    texts.append(voice_info.get('content'))
-                if (voice_data.get('filesize') or 0) <= max_inline_file_size:
-                    voice_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
-                    if voice_base64:
-                        voice_data['base64'] = voice_base64
-                voices.append(voice_data)
-            elif item_type == 'video':
-                video_info = item.get('video', {}) or {}
-                download_url = video_info.get('url')
-                item_aeskey = video_info.get('aeskey', '')
-                video_data = {
-                    'url': download_url,
-                    'filesize': video_info.get('filesize') or video_info.get('size'),
-                    'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-                    'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-                    'filename': video_info.get('filename') or video_info.get('name'),
-                }
-                if (video_data.get('filesize') or 0) <= max_inline_file_size:
-                    video_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
-                    if video_base64:
-                        video_data['base64'] = video_base64
-                videos.append(video_data)
-            elif item_type == 'link':
-                links.append(item.get('link', {}))
-
-        if texts:
-            message_data['content'] = ' '.join(texts)
-        if images:
-            message_data['images'] = images
-            message_data['picurl'] = images[0]
-        if files:
-            message_data['files'] = files
-            message_data['file'] = files[0]
-        if voices:
-            message_data['voices'] = voices
-            message_data['voice'] = voices[0]
-        if videos:
-            message_data['videos'] = videos
-            message_data['video'] = videos[0]
-        if links:
-            message_data['link'] = links[0]
-        if items:
-            message_data['attachments'] = items
-    else:
-        message_data['raw_msg'] = msg_json
-
-    from_info = msg_json.get('from', {})
-    message_data['userid'] = from_info.get('userid', '')
-    message_data['username'] = from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
-
-    if msg_json.get('chattype', '') == 'group':
-        message_data['chatid'] = msg_json.get('chatid', '')
-        message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
-
-    message_data['msgid'] = msg_json.get('msgid', '')
-
-    if msg_json.get('aibotid'):
-        message_data['aibotid'] = msg_json.get('aibotid', '')
-
-    return message_data
-
-
 class WecomBotClient:
     def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger, unified_mode: bool = False):
         """企业微信智能机器人客户端。
@@ -627,27 +236,14 @@ class WecomBotClient:
         self.stream_sessions = StreamSessionManager(logger=logger)
         self.stream_poll_timeout = 0.5
 
-        self._feedback_callback: Optional[Callable] = None
-
-    def set_feedback_callback(self, callback: Callable) -> None:
-        """设置反馈回调函数。
-
-        Args:
-            callback: 反馈回调函数，签名: async def callback(feedback_id, feedback_type, feedback_content, inaccurate_reasons, session)
-        """
-        self._feedback_callback = callback
-
     @staticmethod
-    def _build_stream_payload(
-        stream_id: str, content: str, finish: bool, feedback_id: Optional[str] = None
-    ) -> dict[str, Any]:
+    def _build_stream_payload(stream_id: str, content: str, finish: bool) -> dict[str, Any]:
         """按照企业微信协议拼装返回报文。
 
         Args:
             stream_id: 企业微信会话 ID。
             content: 推送的文本内容。
             finish: 是否为最终片段。
-            feedback_id: 反馈 ID，用于接收用户点赞/点踩反馈。
 
         Returns:
             dict[str, Any]: 可直接加密返回的 payload。
@@ -655,16 +251,13 @@ class WecomBotClient:
         Example:
             组装 `{'msgtype': 'stream', 'stream': {'id': 'sid', ...}}` 结构。
         """
-        stream_payload = {
-            'id': stream_id,
-            'finish': finish,
-            'content': content,
-        }
-        if feedback_id:
-            stream_payload['feedback'] = {'id': feedback_id}
         return {
             'msgtype': 'stream',
-            'stream': stream_payload,
+            'stream': {
+                'id': stream_id,
+                'finish': finish,
+                'content': content,
+            },
         }
 
     async def _encrypt_and_reply(self, payload: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -720,14 +313,9 @@ class WecomBotClient:
         """
         session, is_new = self.stream_sessions.create_or_get(msg_json)
 
-        feedback_id = str(uuid.uuid4())
-        session.feedback_id = feedback_id
-        self.stream_sessions.register_feedback_id(session.stream_id, feedback_id)
-
         message_data = await self.get_message(msg_json)
         if message_data:
             message_data['stream_id'] = session.stream_id
-            message_data['feedback_id'] = feedback_id
             try:
                 event = wecombotevent.WecomBotEvent(message_data)
             except Exception:
@@ -736,7 +324,7 @@ class WecomBotClient:
                 if is_new:
                     asyncio.create_task(self._dispatch_event(event))
 
-        payload = self._build_stream_payload(session.stream_id, '', False, feedback_id)
+        payload = self._build_stream_payload(session.stream_id, '', False)
         return await self._encrypt_and_reply(payload, nonce)
 
     async def _handle_post_followup_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -861,80 +449,202 @@ 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}'
-                )
-                for handler in self._message_handlers.get('feedback', []):
-                    try:
-                        await handler(
-                            feedback_id=feedback_id,
-                            feedback_type=feedback_type,
-                            feedback_content=feedback_content,
-                            inaccurate_reasons=inaccurate_reasons,
-                            session=session,
-                        )
-                    except Exception:
-                        await self.logger.error(traceback.format_exc())
-
-                if self._feedback_callback:
-                    try:
-                        await self._feedback_callback(
-                            feedback_id=feedback_id,
-                            feedback_type=feedback_type,
-                            feedback_content=feedback_content,
-                            inaccurate_reasons=inaccurate_reasons,
-                            session=session,
-                        )
-                    except Exception:
-                        await self.logger.error(traceback.format_exc())
-            else:
-                await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话')
-
-        except Exception:
-            await self.logger.error(traceback.format_exc())
-
-        return await self._encrypt_and_reply({}, nonce)
-
     async def get_message(self, msg_json):
-        return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
+        message_data = {}
+
+        msg_type = msg_json.get('msgtype', '')
+        if msg_type:
+            message_data['msgtype'] = msg_type
+
+        if msg_json.get('chattype', '') == 'single':
+            message_data['type'] = 'single'
+        elif msg_json.get('chattype', '') == 'group':
+            message_data['type'] = 'group'
+
+        max_inline_file_size = 5 * 1024 * 1024  # avoid decoding very large payloads by default
+
+        async def _safe_download(url: str):
+            if not url:
+                return None
+            return await self.download_url_to_base64(url, self.EnCodingAESKey)
+
+        if msg_type == 'text':
+            message_data['content'] = msg_json.get('text', {}).get('content')
+        elif msg_type == 'markdown':
+            message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
+                'content', ''
+            )
+        elif msg_type == 'image':
+            picurl = msg_json.get('image', {}).get('url', '')
+            base64_data = await _safe_download(picurl)
+            if base64_data:
+                message_data['picurl'] = base64_data
+                message_data['images'] = [base64_data]
+        elif msg_type == 'voice':
+            voice_info = msg_json.get('voice', {}) or {}
+            download_url = voice_info.get('url')
+            message_data['voice'] = {
+                'url': download_url,
+                'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
+                'filesize': voice_info.get('filesize') or voice_info.get('size'),
+                'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
+            }
+            # 企业微信智能转写文本（如果已有）直接复用，避免重复转写
+            if voice_info.get('content'):
+                message_data['content'] = voice_info.get('content')
+            if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
+                voice_base64 = await _safe_download(download_url)
+                if voice_base64:
+                    message_data['voice']['base64'] = voice_base64
+        elif msg_type == 'video':
+            video_info = msg_json.get('video', {}) or {}
+            download_url = video_info.get('url')
+            video_data = {
+                'url': download_url,
+                'filesize': video_info.get('filesize') or video_info.get('size'),
+                'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
+                'md5sum': video_info.get('md5sum') or video_info.get('md5'),
+                'filename': video_info.get('filename') or video_info.get('name'),
+            }
+            if (video_data.get('filesize') or 0) <= max_inline_file_size:
+                video_base64 = await _safe_download(download_url)
+                if video_base64:
+                    video_data['base64'] = video_base64
+            message_data['video'] = video_data
+        elif msg_type == 'file':
+            file_info = msg_json.get('file', {}) or {}
+            download_url = file_info.get('url') or file_info.get('fileurl')
+            file_data = {
+                'filename': file_info.get('filename') or file_info.get('name'),
+                'filesize': file_info.get('filesize') or file_info.get('size'),
+                'md5sum': file_info.get('md5sum') or file_info.get('md5'),
+                'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
+                'download_url': download_url,
+                'extra': file_info,
+            }
+            if (file_data.get('filesize') or 0) <= max_inline_file_size:
+                file_base64 = await _safe_download(download_url)
+                if file_base64:
+                    file_data['base64'] = file_base64
+            message_data['file'] = file_data
+        elif msg_type == 'link':
+            message_data['link'] = msg_json.get('link', {})
+            if not message_data.get('content'):
+                title = message_data['link'].get('title', '')
+                desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
+                message_data['content'] = '\n'.join(filter(None, [title, desc]))
+        elif msg_type == 'mixed':
+            items = msg_json.get('mixed', {}).get('msg_item', [])
+            texts = []
+            images = []
+            files = []
+            voices = []
+            videos = []
+            links = []
+            for item in items:
+                item_type = item.get('msgtype')
+                if item_type == 'text':
+                    texts.append(item.get('text', {}).get('content', ''))
+                elif item_type == 'image':
+                    img_url = item.get('image', {}).get('url')
+                    base64_data = await _safe_download(img_url)
+                    if base64_data:
+                        images.append(base64_data)
+                elif item_type == 'file':
+                    file_info = item.get('file', {}) or {}
+                    download_url = file_info.get('url') or file_info.get('fileurl')
+                    file_data = {
+                        'filename': file_info.get('filename') or file_info.get('name'),
+                        'filesize': file_info.get('filesize') or file_info.get('size'),
+                        'md5sum': file_info.get('md5sum') or file_info.get('md5'),
+                        'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
+                        'download_url': download_url,
+                        'extra': file_info,
+                    }
+                    if (file_data.get('filesize') or 0) <= max_inline_file_size:
+                        file_base64 = await _safe_download(download_url)
+                        if file_base64:
+                            file_data['base64'] = file_base64
+                    files.append(file_data)
+                elif item_type == 'voice':
+                    voice_info = item.get('voice', {}) or {}
+                    download_url = voice_info.get('url')
+                    voice_data = {
+                        'url': download_url,
+                        'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
+                        'filesize': voice_info.get('filesize') or voice_info.get('size'),
+                        'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
+                    }
+                    if voice_info.get('content'):
+                        texts.append(voice_info.get('content'))
+                    if (voice_data.get('filesize') or 0) <= max_inline_file_size:
+                        voice_base64 = await _safe_download(download_url)
+                        if voice_base64:
+                            voice_data['base64'] = voice_base64
+                    voices.append(voice_data)
+                elif item_type == 'video':
+                    video_info = item.get('video', {}) or {}
+                    download_url = video_info.get('url')
+                    video_data = {
+                        'url': download_url,
+                        'filesize': video_info.get('filesize') or video_info.get('size'),
+                        'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
+                        'md5sum': video_info.get('md5sum') or video_info.get('md5'),
+                        'filename': video_info.get('filename') or video_info.get('name'),
+                    }
+                    if (video_data.get('filesize') or 0) <= max_inline_file_size:
+                        video_base64 = await _safe_download(download_url)
+                        if video_base64:
+                            video_data['base64'] = video_base64
+                    videos.append(video_data)
+                elif item_type == 'link':
+                    links.append(item.get('link', {}))
+
+            if texts:
+                message_data['content'] = ' '.join(texts)  # 拼接所有 text
+            if images:
+                message_data['images'] = images
+                message_data['picurl'] = images[0]  # 只保留第一个 image
+            if files:
+                message_data['files'] = files
+                message_data['file'] = files[0]
+            if voices:
+                message_data['voices'] = voices
+                message_data['voice'] = voices[0]
+            if videos:
+                message_data['videos'] = videos
+                message_data['video'] = videos[0]
+            if links:
+                message_data['link'] = links[0]
+            if items:
+                message_data['attachments'] = items
+        else:
+            message_data['raw_msg'] = msg_json
+
+        # Extract user information
+        from_info = msg_json.get('from', {})
+        message_data['userid'] = from_info.get('userid', '')
+        message_data['username'] = (
+            from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
+        )
+
+        # Extract chat/group information
+        if msg_json.get('chattype', '') == 'group':
+            message_data['chatid'] = msg_json.get('chatid', '')
+            # Try to get group name if available
+            message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
+
+        message_data['msgid'] = msg_json.get('msgid', '')
+
+        if msg_json.get('aibotid'):
+            message_data['aibotid'] = msg_json.get('aibotid', '')
+
+        return message_data
 
     async def _handle_message(self, event: wecombotevent.WecomBotEvent):
         """
@@ -1001,20 +711,40 @@ class WecomBotClient:
 
         return decorator
 
-    def on_feedback(self):
-        def decorator(func: Callable):
-            if 'feedback' not in self._message_handlers:
-                self._message_handlers['feedback'] = []
-            self._message_handlers['feedback'].append(func)
-            return func
-
-        return decorator
-
     async def download_url_to_base64(self, download_url, encoding_aes_key):
-        data, _filename = await download_encrypted_file(download_url, encoding_aes_key, self.logger)
-        if data:
-            return _bytes_to_data_uri(data)
-        return None
+        async with httpx.AsyncClient() as client:
+            response = await client.get(download_url)
+            if response.status_code != 200:
+                await self.logger.error(f'failed to get file: {response.text}')
+                return None
+
+            encrypted_bytes = response.content
+
+        aes_key = base64.b64decode(encoding_aes_key + '=')  # base64 补齐
+        iv = aes_key[:16]
+
+        cipher = AES.new(aes_key, AES.MODE_CBC, iv)
+        decrypted = cipher.decrypt(encrypted_bytes)
+
+        pad_len = decrypted[-1]
+        decrypted = decrypted[:-pad_len]
+
+        if decrypted.startswith(b'\xff\xd8'):  # JPEG
+            mime_type = 'image/jpeg'
+        elif decrypted.startswith(b'\x89PNG'):  # PNG
+            mime_type = 'image/png'
+        elif decrypted.startswith((b'GIF87a', b'GIF89a')):  # GIF
+            mime_type = 'image/gif'
+        elif decrypted.startswith(b'BM'):  # BMP
+            mime_type = 'image/bmp'
+        elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'):  # TIFF
+            mime_type = 'image/tiff'
+        else:
+            mime_type = 'application/octet-stream'
+
+        # 转 base64
+        base64_str = base64.b64encode(decrypted).decode('utf-8')
+        return f'data:{mime_type};base64,{base64_str}'
 
     async def run_task(self, host: str, port: int, *args, **kwargs):
         """

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

@@ -133,17 +133,3 @@ class WecomBotEvent(dict):
         AI Bot ID
         """
         return self.get('aibotid', '')
-
-    @property
-    def feedback_id(self) -> str:
-        """
-        反馈 ID，用于关联用户点赞/点踩反馈
-        """
-        return self.get('feedback_id', '')
-
-    @property
-    def stream_id(self) -> str:
-        """
-        流式消息 ID
-        """
-        return self.get('stream_id', '')

src/langbot/libs/wecom_ai_bot_api/ws_client.py

@@ -1,596 +0,0 @@
-"""WeChat Work AI Bot WebSocket long connection client.
-
-Implements the WebSocket protocol for receiving messages and sending replies
-via a persistent connection to wss://openws.work.weixin.qq.com, as an
-alternative to the HTTP callback (webhook) mode.
-
-Protocol reference: https://developer.work.weixin.qq.com/document/path/101463
-Official Node.js SDK: https://github.com/WecomTeam/aibot-node-sdk
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import secrets
-import time
-import traceback
-from typing import Any, Callable, Optional
-
-import aiohttp
-
-from langbot.libs.wecom_ai_bot_api import wecombotevent
-from langbot.libs.wecom_ai_bot_api.api import parse_wecom_bot_message
-from langbot.pkg.platform.logger import EventLogger
-
-DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
-
-# WebSocket frame command constants
-CMD_SUBSCRIBE = 'aibot_subscribe'
-CMD_HEARTBEAT = 'ping'
-CMD_MSG_CALLBACK = 'aibot_msg_callback'
-CMD_EVENT_CALLBACK = 'aibot_event_callback'
-CMD_RESPOND_MSG = 'aibot_respond_msg'
-CMD_RESPOND_WELCOME = 'aibot_respond_welcome_msg'
-CMD_RESPOND_UPDATE = 'aibot_respond_update_msg'
-CMD_SEND_MSG = 'aibot_send_msg'
-
-
-def _generate_req_id(prefix: str) -> str:
-    """Generate a unique request ID in the format: {prefix}_{timestamp}_{random}."""
-    ts = int(time.time() * 1000)
-    rand = secrets.token_hex(4)
-    return f'{prefix}_{ts}_{rand}'
-
-
-class WecomBotWsClient:
-    """WeChat Work AI Bot WebSocket long connection client.
-
-    Provides message receiving, streaming reply, proactive message sending,
-    and event callback handling over a persistent WebSocket connection.
-    """
-
-    def __init__(
-        self,
-        bot_id: str,
-        secret: str,
-        logger: EventLogger,
-        encoding_aes_key: str = '',
-        ws_url: str = DEFAULT_WS_URL,
-        heartbeat_interval: float = 30.0,
-        max_reconnect_attempts: int = -1,
-        reconnect_base_delay: float = 1.0,
-        reconnect_max_delay: float = 30.0,
-    ):
-        self.bot_id = bot_id
-        self.secret = secret
-        self.logger = logger
-        self.encoding_aes_key = encoding_aes_key
-        self.ws_url = ws_url
-        self.heartbeat_interval = heartbeat_interval
-        self.max_reconnect_attempts = max_reconnect_attempts
-        self.reconnect_base_delay = reconnect_base_delay
-        self.reconnect_max_delay = reconnect_max_delay
-
-        self._ws: Optional[aiohttp.ClientWebSocketResponse] = None
-        self._session: Optional[aiohttp.ClientSession] = None
-        self._running = False
-        self._heartbeat_task: Optional[asyncio.Task] = None
-        self._missed_pong_count = 0
-        self._max_missed_pong = 2
-        self._reconnect_attempts = 0
-
-        # Message handler registry (same pattern as WecomBotClient)
-        self._message_handlers: dict[str, list[Callable]] = {}
-        # Message deduplication
-        self._msg_id_map: dict[str, int] = {}
-
-        # Pending ACK futures: req_id -> Future[dict]
-        self._pending_acks: dict[str, asyncio.Future] = {}
-        # Per-req_id serial reply queues
-        self._reply_queues: dict[str, asyncio.Queue] = {}
-        self._reply_workers: dict[str, asyncio.Task] = {}
-        self._reply_ack_timeout = 5.0
-
-        # Stream ID tracking for WebSocket mode
-        self._stream_ids: dict[str, str] = {}  # msg_id -> req_id|stream_id
-        # Dedup: skip sending when content hasn't changed
-        self._stream_last_content: dict[str, str] = {}  # msg_id -> last content sent
-
-    # ── Public API ──────────────────────────────────────────────────
-
-    async def connect(self):
-        """Connect to WebSocket server with automatic reconnection.
-
-        This method blocks until disconnect() is called or max reconnect
-        attempts are exhausted.
-        """
-        self._running = True
-        self._reconnect_attempts = 0
-
-        while self._running:
-            try:
-                await self._connect_once()
-            except Exception:
-                if not self._running:
-                    break
-                await self.logger.error(f'WebSocket connection error: {traceback.format_exc()}')
-
-            if not self._running:
-                break
-
-            # Reconnect with exponential backoff
-            if self.max_reconnect_attempts != -1 and self._reconnect_attempts >= self.max_reconnect_attempts:
-                await self.logger.error(f'Max reconnect attempts reached ({self.max_reconnect_attempts}), giving up')
-                break
-
-            self._reconnect_attempts += 1
-            delay = min(
-                self.reconnect_base_delay * (2 ** (self._reconnect_attempts - 1)),
-                self.reconnect_max_delay,
-            )
-            await self.logger.info(f'Reconnecting in {delay:.1f}s (attempt {self._reconnect_attempts})...')
-            await asyncio.sleep(delay)
-
-    async def disconnect(self):
-        """Gracefully disconnect from the WebSocket server."""
-        self._running = False
-        if self._heartbeat_task and not self._heartbeat_task.done():
-            self._heartbeat_task.cancel()
-        for task in self._reply_workers.values():
-            if not task.done():
-                task.cancel()
-        if self._ws and not self._ws.closed:
-            await self._ws.close()
-        self._ws = None
-        if self._session and not self._session.closed:
-            await self._session.close()
-        self._session = None
-
-    def on_message(self, msg_type: str) -> Callable:
-        """Decorator to register a message handler.
-
-        Same interface as WecomBotClient.on_message for compatibility.
-
-        Args:
-            msg_type: 'single', 'group', or specific message type.
-        """
-
-        def decorator(func: Callable[[wecombotevent.WecomBotEvent], Any]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-    async def reply_stream(
-        self,
-        req_id: str,
-        stream_id: str,
-        content: str,
-        finish: bool = False,
-    ) -> Optional[dict]:
-        """Send a streaming reply frame.
-
-        Args:
-            req_id: The req_id from the original message frame (must be passed through).
-            stream_id: The stream ID for this streaming session.
-            content: The content to send (supports Markdown).
-            finish: Whether this is the final chunk.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        body = {
-            'msgtype': 'stream',
-            'stream': {
-                'id': stream_id,
-                'finish': finish,
-                'content': content,
-            },
-        }
-        return await self._send_reply(req_id, body)
-
-    async def reply_text(self, req_id: str, content: str) -> Optional[dict]:
-        """Send a non-streaming text reply.
-
-        Args:
-            req_id: The req_id from the original message frame.
-            content: The text content to reply.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        body = {
-            'msgtype': 'markdown',
-            'markdown': {
-                'content': content,
-            },
-        }
-        return await self._send_reply(req_id, body)
-
-    async def send_message(self, chat_id: str, content: str, msgtype: str = 'markdown') -> Optional[dict]:
-        """Proactively send a message to a specified chat.
-
-        Args:
-            chat_id: The chat ID (userid for single chat, chatid for group chat).
-            content: The message content.
-            msgtype: Message type, 'markdown' by default.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        req_id = _generate_req_id(CMD_SEND_MSG)
-        body: dict[str, Any] = {
-            'chatid': chat_id,
-            'msgtype': msgtype,
-        }
-        if msgtype == 'markdown':
-            body['markdown'] = {'content': content}
-        elif msgtype == 'text':
-            body['text'] = {'content': content}
-        return await self._send_reply(req_id, body, cmd=CMD_SEND_MSG)
-
-    async def push_stream_chunk(self, msg_id: str, content: str, is_final: bool = False) -> bool:
-        """Push a streaming chunk for a given message ID.
-
-        Compatible interface with WecomBotClient.push_stream_chunk.
-
-        Args:
-            msg_id: The original message ID.
-            content: The cumulative content from the pipeline.
-            is_final: Whether this is the final chunk.
-
-        Returns:
-            True if the stream session exists and chunk was sent.
-        """
-        key = self._stream_ids.get(msg_id)
-        if not key:
-            return False
-        req_id, stream_id = key.split('|', 1)
-        try:
-            # Skip sending if content hasn't changed (e.g. during tool call argument streaming)
-            if not is_final and content == self._stream_last_content.get(msg_id):
-                return True
-            await self.reply_stream(req_id, stream_id, content, finish=is_final)
-            self._stream_last_content[msg_id] = content
-            if is_final:
-                self._stream_ids.pop(msg_id, None)
-                self._stream_last_content.pop(msg_id, None)
-            return True
-        except Exception:
-            await self.logger.error(f'Failed to push stream chunk: {traceback.format_exc()}')
-            return False
-
-    async def set_message(self, msg_id: str, content: str):
-        """Fallback: send content as a final stream chunk or direct reply.
-
-        Compatible interface with WecomBotClient.set_message.
-        """
-        handled = await self.push_stream_chunk(msg_id, content, is_final=True)
-        if not handled:
-            await self.logger.warning(f'No active stream for msg_id={msg_id}, message dropped')
-
-    # ── Connection lifecycle ────────────────────────────────────────
-
-    async def _connect_once(self):
-        """Establish a single WebSocket connection, authenticate, and listen."""
-        await self.logger.info(f'Connecting to {self.ws_url}...')
-
-        self._session = aiohttp.ClientSession()
-        try:
-            self._ws = await self._session.ws_connect(self.ws_url)
-            self._missed_pong_count = 0
-            self._reconnect_attempts = 0
-            await self.logger.info('WebSocket connected, sending auth...')
-
-            await self._send_auth()
-
-            # Wait for auth response
-            auth_ok = await self._wait_for_auth()
-            if not auth_ok:
-                await self.logger.error('Authentication failed')
-                return
-
-            await self.logger.info('Authenticated successfully')
-
-            # Start heartbeat
-            self._heartbeat_task = asyncio.create_task(self._heartbeat_loop())
-
-            try:
-                await self._listen_loop()
-            finally:
-                if self._heartbeat_task and not self._heartbeat_task.done():
-                    self._heartbeat_task.cancel()
-                self._clear_pending_acks('Connection closed')
-        finally:
-            if self._ws and not self._ws.closed:
-                await self._ws.close()
-            self._ws = None
-            if self._session and not self._session.closed:
-                await self._session.close()
-            self._session = None
-
-    async def _send_auth(self):
-        """Send the authentication frame."""
-        frame = {
-            'cmd': CMD_SUBSCRIBE,
-            'headers': {'req_id': _generate_req_id(CMD_SUBSCRIBE)},
-            'body': {
-                'bot_id': self.bot_id,
-                'secret': self.secret,
-            },
-        }
-        await self._send_frame(frame)
-
-    async def _wait_for_auth(self) -> bool:
-        """Wait for and validate the authentication response."""
-        try:
-            msg = await asyncio.wait_for(self._ws.receive(), timeout=10.0)
-            if msg.type in (aiohttp.WSMsgType.TEXT,):
-                frame = json.loads(msg.data)
-                req_id = frame.get('headers', {}).get('req_id', '')
-                if req_id.startswith(CMD_SUBSCRIBE) and frame.get('errcode') == 0:
-                    return True
-                await self.logger.error(f'Auth response: errcode={frame.get("errcode")}, errmsg={frame.get("errmsg")}')
-                return False
-            elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
-                await self.logger.error(f'WebSocket closed during auth: {msg.type}')
-                return False
-            await self.logger.error(f'Unexpected message type during auth: {msg.type}')
-            return False
-        except asyncio.TimeoutError:
-            await self.logger.error('Auth response timeout')
-            return False
-
-    async def _heartbeat_loop(self):
-        """Periodically send heartbeat pings."""
-        try:
-            while self._running and self._ws and not self._ws.closed:
-                await asyncio.sleep(self.heartbeat_interval)
-                if not self._running or not self._ws or self._ws.closed:
-                    break
-
-                if self._missed_pong_count >= self._max_missed_pong:
-                    await self.logger.warning(
-                        f'No heartbeat ack for {self._missed_pong_count} consecutive pings, connection considered dead'
-                    )
-                    await self._ws.close()
-                    break
-
-                self._missed_pong_count += 1
-                frame = {
-                    'cmd': CMD_HEARTBEAT,
-                    'headers': {'req_id': _generate_req_id(CMD_HEARTBEAT)},
-                }
-                try:
-                    await self._send_frame(frame)
-                except Exception:
-                    break
-        except asyncio.CancelledError:
-            pass
-
-    async def _listen_loop(self):
-        """Listen for incoming WebSocket frames and dispatch them."""
-        async for msg in self._ws:
-            if not self._running:
-                break
-            if msg.type == aiohttp.WSMsgType.TEXT:
-                try:
-                    frame = json.loads(msg.data)
-                    await self._handle_frame(frame)
-                except json.JSONDecodeError:
-                    await self.logger.error(f'Failed to parse WebSocket message: {str(msg.data)[:200]}')
-                except Exception:
-                    await self.logger.error(f'Error handling frame: {traceback.format_exc()}')
-            elif msg.type == aiohttp.WSMsgType.BINARY:
-                try:
-                    frame = json.loads(msg.data)
-                    await self._handle_frame(frame)
-                except Exception:
-                    await self.logger.error(f'Error handling binary frame: {traceback.format_exc()}')
-            elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
-                await self.logger.warning(f'WebSocket connection closed: {msg.type}')
-                break
-
-    # ── Frame handling ──────────────────────────────────────────────
-
-    async def _handle_frame(self, frame: dict):
-        """Route an incoming frame to the appropriate handler."""
-        cmd = frame.get('cmd', '')
-
-        # Message push
-        if cmd == CMD_MSG_CALLBACK:
-            asyncio.create_task(self._handle_message_callback(frame))
-            return
-
-        # Event push
-        if cmd == CMD_EVENT_CALLBACK:
-            asyncio.create_task(self._handle_event_callback(frame))
-            return
-
-        # No cmd → response/ACK frame, dispatch by req_id prefix
-        req_id = frame.get('headers', {}).get('req_id', '')
-
-        # Check pending ACKs first
-        if req_id in self._pending_acks:
-            future = self._pending_acks.pop(req_id)
-            if not future.done():
-                future.set_result(frame)
-            return
-
-        # Heartbeat response
-        if req_id.startswith(CMD_HEARTBEAT):
-            if frame.get('errcode') == 0:
-                self._missed_pong_count = 0
-            return
-
-        # Unknown frame
-        await self.logger.warning(f'Unknown frame: {json.dumps(frame, ensure_ascii=False)[:200]}')
-
-    async def _handle_message_callback(self, frame: dict):
-        """Handle an incoming message callback frame."""
-        try:
-            body = frame.get('body', {})
-            req_id = frame.get('headers', {}).get('req_id', '')
-
-            # Parse message using shared logic
-            message_data = await parse_wecom_bot_message(body, self.encoding_aes_key, self.logger)
-            if not message_data:
-                return
-
-            # Generate stream_id for this message and store the mapping
-            stream_id = _generate_req_id('stream')
-            msg_id = message_data.get('msgid', '')
-            if msg_id:
-                self._stream_ids[msg_id] = f'{req_id}|{stream_id}'
-            message_data['stream_id'] = stream_id
-            message_data['req_id'] = req_id
-
-            event = wecombotevent.WecomBotEvent(message_data)
-            await self._dispatch_event(event)
-        except Exception:
-            await self.logger.error(f'Error in message callback: {traceback.format_exc()}')
-
-    async def _handle_event_callback(self, frame: dict):
-        """Handle an incoming event callback frame (enter_chat, template_card_event, etc.)."""
-        try:
-            body = frame.get('body', {})
-            req_id = frame.get('headers', {}).get('req_id', '')
-
-            event_info = body.get('event', {})
-            event_type = event_info.get('eventtype', '')
-
-            message_data = {
-                'msgtype': 'event',
-                'type': body.get('chattype', 'single'),
-                'event': event_info,
-                'eventtype': event_type,
-                'msgid': body.get('msgid', ''),
-                'aibotid': body.get('aibotid', ''),
-                'req_id': req_id,
-            }
-
-            from_info = body.get('from', {})
-            message_data['userid'] = from_info.get('userid', '')
-            message_data['username'] = from_info.get('alias', '') or from_info.get('userid', '')
-
-            if body.get('chatid'):
-                message_data['chatid'] = body.get('chatid', '')
-
-            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)
-
-        except Exception:
-            await self.logger.error(f'Error in event callback: {traceback.format_exc()}')
-
-    async def _dispatch_event(self, event: wecombotevent.WecomBotEvent):
-        """Dispatch a message event to registered handlers with deduplication."""
-        try:
-            message_id = event.message_id
-            if message_id in self._msg_id_map:
-                self._msg_id_map[message_id] += 1
-                return
-            self._msg_id_map[message_id] = 1
-
-            msg_type = event.type
-            if msg_type in self._message_handlers:
-                for handler in self._message_handlers[msg_type]:
-                    await handler(event)
-        except Exception:
-            await self.logger.error(f'Error dispatching event: {traceback.format_exc()}')
-
-    # ── Reply sending with serial queue ─────────────────────────────
-
-    async def _send_reply(
-        self,
-        req_id: str,
-        body: dict,
-        cmd: str = CMD_RESPOND_MSG,
-    ) -> Optional[dict]:
-        """Send a reply frame and wait for ACK.
-
-        Replies with the same req_id are serialized to maintain ordering.
-        """
-        if not self._ws or self._ws.closed:
-            return None
-
-        frame = {
-            'cmd': cmd,
-            'headers': {'req_id': req_id},
-            'body': body,
-        }
-
-        # Ensure serial delivery per req_id
-        if req_id not in self._reply_queues:
-            self._reply_queues[req_id] = asyncio.Queue()
-            self._reply_workers[req_id] = asyncio.create_task(self._reply_queue_worker(req_id))
-
-        future: asyncio.Future = asyncio.get_event_loop().create_future()
-        await self._reply_queues[req_id].put((frame, future))
-        return await future
-
-    async def _reply_queue_worker(self, req_id: str):
-        """Process reply queue items serially for a given req_id."""
-        queue = self._reply_queues[req_id]
-        try:
-            while self._running:
-                try:
-                    frame, future = await asyncio.wait_for(queue.get(), timeout=60.0)
-                except asyncio.TimeoutError:
-                    # Queue idle, clean up worker
-                    break
-
-                try:
-                    ack = await self._send_and_wait_ack(frame)
-                    if not future.done():
-                        future.set_result(ack)
-                except Exception as e:
-                    if not future.done():
-                        future.set_exception(e)
-        except asyncio.CancelledError:
-            pass
-        finally:
-            self._reply_queues.pop(req_id, None)
-            self._reply_workers.pop(req_id, None)
-
-    async def _send_and_wait_ack(self, frame: dict) -> Optional[dict]:
-        """Send a frame and wait for the corresponding ACK."""
-        req_id = frame['headers']['req_id']
-        ack_future: asyncio.Future = asyncio.get_event_loop().create_future()
-        self._pending_acks[req_id] = ack_future
-
-        try:
-            await self._send_frame(frame)
-            result = await asyncio.wait_for(ack_future, timeout=self._reply_ack_timeout)
-            if result.get('errcode', 0) != 0:
-                await self.logger.warning(
-                    f'Reply ACK error: errcode={result.get("errcode")}, errmsg={result.get("errmsg")}'
-                )
-            return result
-        except asyncio.TimeoutError:
-            self._pending_acks.pop(req_id, None)
-            await self.logger.warning(f'Reply ACK timeout ({self._reply_ack_timeout}s) for req_id={req_id}')
-            return None
-
-    async def _send_frame(self, frame: dict):
-        """Send a JSON frame over the WebSocket connection."""
-        if self._ws and not self._ws.closed:
-            await self._ws.send_str(json.dumps(frame, ensure_ascii=False))
-
-    def _clear_pending_acks(self, reason: str):
-        """Reject all pending ACK futures on disconnection."""
-        for req_id, future in self._pending_acks.items():
-            if not future.done():
-                future.set_exception(ConnectionError(reason))
-        self._pending_acks.clear()

src/langbot/libs/wecom_api/api.py

@@ -4,7 +4,6 @@ import base64
 import binascii
 import httpx
 import traceback
-from urllib.parse import quote
 from quart import Quart
 import xml.etree.ElementTree as ET
 from typing import Callable, Dict, Any
@@ -68,31 +67,6 @@ class WecomClient:
                 await self.logger.error(f'获取accesstoken失败:{response.json()}')
                 raise Exception(f'未获取access token: {data}')
 
-    async def get_user_info(self, userid: str) -> dict:
-        """
-        Get user information by user ID using the application secret.
-
-        Args:
-            userid: The user ID to look up.
-
-        Returns:
-            dict: User information including 'name' field.
-        """
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = self.base_url + '/user/get?access_token=' + self.access_token + '&userid=' + quote(userid)
-        async with httpx.AsyncClient() as client:
-            response = await client.get(url)
-            data = response.json()
-            if data.get('errcode') == 40014 or data.get('errcode') == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.get_user_info(userid)
-            if data.get('errcode', 0) != 0:
-                await self.logger.error(f'获取用户信息失败:{data}')
-                return {}
-            return data
-
     async def get_users(self):
         if not self.check_access_token_for_contacts():
             self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)

src/langbot/libs/wecom_customer_service_api/api.py

@@ -10,7 +10,6 @@ from typing import Callable
 from .wecomcsevent import WecomCSEvent
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import aiofiles
-import time
 
 
 class WecomCSClient:
@@ -35,10 +34,6 @@ class WecomCSClient:
         self.unified_mode = unified_mode
         self.app = Quart(__name__)
 
-        # Customer info cache: {external_userid: (info_dict, timestamp)}
-        self._customer_cache: dict[str, tuple[dict, float]] = {}
-        self._cache_ttl = 60  # Cache TTL in seconds (1 minute)
-
         # 只有在非统一模式下才注册独立路由
         if not self.unified_mode:
             self.app.add_url_rule(
@@ -383,53 +378,3 @@ class WecomCSClient:
     async def get_media_id(self, image: platform_message.Image):
         media_id = await self.upload_to_work(image=image)
         return media_id
-
-    async def get_customer_info(self, external_userid: str) -> dict | None:
-        """
-        Get customer information by external_userid with caching.
-
-        Uses a 1-minute cache to avoid repeated API calls for the same user.
-
-        Args:
-            external_userid: The external user ID of the customer.
-
-        Returns:
-            Customer info dict with 'nickname', 'avatar', etc., or None if not found.
-        """
-        # Check cache first
-        current_time = time.time()
-        if external_userid in self._customer_cache:
-            cached_info, cached_time = self._customer_cache[external_userid]
-            if current_time - cached_time < self._cache_ttl:
-                return cached_info
-
-        # Cache miss or expired, fetch from API
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = f'{self.base_url}/kf/customer/batchget?access_token={self.access_token}'
-
-        payload = {
-            'external_userid_list': [external_userid],
-        }
-
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, json=payload)
-            data = response.json()
-
-            if data.get('errcode') in [40014, 42001]:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.get_customer_info(external_userid)
-
-            if data.get('errcode', 0) != 0:
-                if self.logger:
-                    await self.logger.warning(f'Failed to get customer info: {data}')
-                return None
-
-            customer_list = data.get('customer_list', [])
-            if customer_list:
-                customer_info = customer_list[0]
-                # Store in cache
-                self._customer_cache[external_userid] = (customer_info, current_time)
-                return customer_info
-            return None

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

@@ -13,9 +13,9 @@ from .. import group
 @group.group_class('files', '/api/v1/files')
 class FilesRouterGroup(group.RouterGroup):
     async def initialize(self) -> None:
-        @self.route('/image/<path:image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
+        @self.route('/image/<image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
         async def _(image_key: str) -> quart.Response:
-            if '..' in image_key or '\\' in image_key:
+            if '/' in image_key or '\\' in image_key:
                 return quart.Response(status=404)
 
             if not await self.ap.storage_mgr.storage_provider.exists(image_key):

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

@@ -456,31 +456,6 @@ 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)
 
@@ -511,63 +486,3 @@ 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

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

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

@@ -1,11 +1,7 @@
-import json
-
 import quart
-import sqlalchemy
 
 from .. import group
 from .....utils import constants
-from .....entity.persistence.metadata import Metadata
 
 
 @group.group_class('system', '/api/v1/system')
@@ -13,24 +9,6 @@ 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,
@@ -49,83 +27,17 @@ 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, task_kind))
+            return self.success(data=self.ap.task_mgr.get_tasks_dict(task_type))
 
         @self.route('/tasks/<task_id>', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
         async def _(task_id: str) -> str:

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

@@ -105,28 +105,6 @@ class HTTPController:
             ):
                 if os.path.exists(os.path.join(frontend_path, path + '.html')):
                     path += '.html'
-                elif path.startswith('home/'):
-                    # SPA fallback for /home/* sub-routes.
-                    # Entity detail views use query params (e.g. /home/bots?id=uuid),
-                    # so the pre-rendered list page is served directly via path + '.html'.
-                    # This fallback handles any remaining unmatched sub-paths.
-                    segments = path.rstrip('/').split('/')
-
-                    # Walk up parent segments looking for matching .html files
-                    for i in range(len(segments) - 1, 0, -1):
-                        parent_path = '/'.join(segments[:i]) + '.html'
-                        if os.path.exists(os.path.join(frontend_path, parent_path)):
-                            response = await quart.send_from_directory(frontend_path, parent_path, mimetype='text/html')
-                            response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
-                            response.headers['Pragma'] = 'no-cache'
-                            response.headers['Expires'] = '0'
-                            return response
-                    # Final fallback to index.html for /home/* routes
-                    response = await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
-                    response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
-                    response.headers['Pragma'] = 'no-cache'
-                    response.headers['Expires'] = '0'
-                    return response
                 else:
                     return await quart.send_from_directory(frontend_path, '404.html')
 

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

@@ -70,17 +70,12 @@ class BotService:
             'lark',
         ]:
             webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
-            extra_webhook_prefix = self.ap.instance_config.data['api'].get('extra_webhook_prefix', '')
             webhook_url = f'/bots/{bot_uuid}'
             adapter_runtime_values['webhook_url'] = webhook_url
             adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
-            adapter_runtime_values['extra_webhook_full_url'] = (
-                f'{extra_webhook_prefix}{webhook_url}' if extra_webhook_prefix else ''
-            )
         else:
             adapter_runtime_values['webhook_url'] = None
             adapter_runtime_values['webhook_full_url'] = None
-            adapter_runtime_values['extra_webhook_full_url'] = None
 
         persistence_bot['adapter_runtime_values'] = adapter_runtime_values
 

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

@@ -105,16 +105,11 @@ class LLMModelsService:
                 )
             )
             pipeline = result.first()
-            if pipeline is not None:
-                model_config = pipeline.config.get('ai', {}).get('local-agent', {}).get('model', {})
-                if not model_config.get('primary', ''):
-                    pipeline_config = pipeline.config
-                    pipeline_config['ai']['local-agent']['model'] = {
-                        'primary': model_data['uuid'],
-                        'fallbacks': [],
-                    }
-                    pipeline_data = {'config': pipeline_config}
-                    await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
+            if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
+                pipeline_config = pipeline.config
+                pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
+                pipeline_data = {'config': pipeline_config}
+                await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
 
         return model_data['uuid']
 

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

@@ -16,57 +16,6 @@ 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(
@@ -81,7 +30,6 @@ class MonitoringService:
         level: str = 'info',
         platform: str | None = None,
         user_id: str | None = None,
-        user_name: str | None = None,
         runner_name: str | None = None,
         variables: str | None = None,
         role: str = 'user',
@@ -101,7 +49,6 @@ class MonitoringService:
             'level': level,
             'platform': platform,
             'user_id': user_id,
-            'user_name': user_name,
             'runner_name': runner_name,
             'variables': variables,
             'role': role,
@@ -205,7 +152,6 @@ class MonitoringService:
         pipeline_name: str,
         platform: str | None = None,
         user_id: str | None = None,
-        user_name: str | None = None,
     ) -> None:
         """Record a new session"""
         session_data = {
@@ -220,7 +166,6 @@ class MonitoringService:
             'is_active': True,
             'platform': platform,
             'user_id': user_id,
-            'user_name': user_name,
         }
 
         await self.ap.persistence_mgr.execute_async(
@@ -1183,261 +1128,3 @@ 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
-
-        record_id = str(uuid.uuid4())
-        record_data = {
-            'id': record_id,
-            'timestamp': datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None),
-            'feedback_id': feedback_id,
-            'feedback_type': feedback_type,
-            'feedback_content': feedback_content,
-            'inaccurate_reasons': json.dumps(inaccurate_reasons, ensure_ascii=False) if inaccurate_reasons else None,
-            'bot_id': bot_id,
-            'bot_name': bot_name,
-            'pipeline_id': pipeline_id,
-            'pipeline_name': pipeline_name,
-            'session_id': session_id,
-            'message_id': message_id,
-            'stream_id': stream_id,
-            'user_id': user_id,
-            'platform': platform,
-        }
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(persistence_monitoring.MonitoringFeedback).values(record_data)
-        )
-
-        return record_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/core/app.py

@@ -9,7 +9,6 @@ from ..platform import botmgr as im_mgr
 from ..platform.webhook_pusher import WebhookPusher
 from ..provider.session import sessionmgr as llm_session_mgr
 from ..provider.modelmgr import modelmgr as llm_model_mgr
-
 from langbot.pkg.provider.tools import toolmgr as llm_tool_mgr
 from ..config import manager as config_mgr
 from ..command import cmdmgr
@@ -31,7 +30,6 @@ from ..api.http.service import mcp as mcp_service
 from ..api.http.service import apikey as apikey_service
 from ..api.http.service import webhook as webhook_service
 from ..api.http.service import monitoring as monitoring_service
-
 from ..discover import engine as discover_engine
 from ..storage import mgr as storagemgr
 from ..utils import logcache
@@ -188,34 +186,6 @@ class Application:
                 scopes=[core_entities.LifecycleControlScope.APPLICATION],
             )
 
-            # Start monitoring data cleanup task if enabled
-            monitoring_cfg = self.instance_config.data.get('monitoring', {})
-            auto_cleanup_cfg = monitoring_cfg.get('auto_cleanup', {})
-            if auto_cleanup_cfg.get('enabled', True):
-                retention_days = 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/load_config.py

@@ -74,26 +74,20 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
         current = cfg
 
         for i, key in enumerate(keys):
-            if not isinstance(current, dict):
+            if not isinstance(current, dict) or key not in current:
                 break
 
             if i == len(keys) - 1:
-                # At the final key
-                if key in current:
-                    if isinstance(current[key], (dict, list)):
-                        # Skip dict and list types
-                        pass
-                    else:
-                        # Valid scalar value - convert and set it
-                        converted_value = convert_value(env_value, current[key])
-                        current[key] = converted_value
+                # At the final key - check if it's a scalar value
+                if isinstance(current[key], (dict, list)):
+                    # Skip dict and list types
+                    pass
                 else:
-                    # Key doesn't exist yet - create it as string
-                    current[key] = env_value
+                    # Valid scalar value - convert and set it
+                    converted_value = convert_value(env_value, current[key])
+                    current[key] = converted_value
             else:
-                # Navigate deeper - create intermediate dict if needed
-                if key not in current:
-                    current[key] = {}
+                # Navigate deeper
                 current = current[key]
 
     return cfg
@@ -152,50 +146,16 @@ class LoadConfigStage(stage.BootingStage):
         await ap.instance_config.dump_config()
 
         # load or generate instance id
-        # Priority:
-        # 1. system.instance_id from config.yaml (can be set via SYSTEM__INSTANCE_ID env var)
-        # 2. data/labels/instance_id.json (if file exists)
-        # 3. Generate new and save to file
-        config_instance_id = ap.instance_config.data.get('system', {}).get('instance_id', '')
+        ap.instance_id = await config.load_json_config(
+            'data/labels/instance_id.json',
+            template_data={
+                'instance_id': f'instance_{str(uuid.uuid4())}',
+                'instance_create_ts': int(time.time()),
+            },
+            completion=False,
+        )
 
-        if config_instance_id:
-            # Use the instance_id from config.yaml
-            constants.instance_id = config_instance_id
-            # Still load/create the file for backward compat, but don't use its value
-            ap.instance_id = await config.load_json_config(
-                'data/labels/instance_id.json',
-                template_data={
-                    'instance_id': f'instance_{str(uuid.uuid4())}',
-                    'instance_create_ts': int(time.time()),
-                },
-                completion=False,
-            )
-        else:
-            # Try loading file-based instance id
-            instance_id_path = os.path.join('data', 'labels', 'instance_id.json')
-            if os.path.exists(instance_id_path):
-                # File exists, read it
-                ap.instance_id = await config.load_json_config(
-                    'data/labels/instance_id.json',
-                    template_data={
-                        'instance_id': '',
-                        'instance_create_ts': 0,
-                    },
-                    completion=False,
-                )
-                constants.instance_id = ap.instance_id.data['instance_id']
-            else:
-                # Neither config nor file, generate new and save to file
-                new_id = f'instance_{str(uuid.uuid4())}'
-                ap.instance_id = await config.load_json_config(
-                    'data/labels/instance_id.json',
-                    template_data={
-                        'instance_id': new_id,
-                        'instance_create_ts': int(time.time()),
-                    },
-                    completion=False,
-                )
-                constants.instance_id = new_id
+        constants.instance_id = ap.instance_id.data['instance_id']
         constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
 
         print(f'LangBot instance id: {constants.instance_id}')

src/langbot/pkg/core/taskmgr.py

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

src/langbot/pkg/discover/engine.py

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

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

@@ -20,7 +20,6 @@ class MonitoringMessage(Base):
     level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # info, warning, error, debug
     platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
     runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # Runner name for this query
     variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # Query variables as JSON string
     role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user')  # user, assistant
@@ -65,7 +64,6 @@ class MonitoringSession(Base):
     is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
     platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
 
 
 class MonitoringError(Base):
@@ -106,26 +104,3 @@ 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/mgr.py

@@ -2,16 +2,18 @@ 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, metadata, model as persistence_model
+from ..entity.persistence import base, pipeline, 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)
@@ -76,6 +78,7 @@ class PersistenceManager:
 
             self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
 
+        await self.write_default_pipeline()
         await self.write_space_model_providers()
 
     async def create_tables(self):
@@ -98,6 +101,29 @@ 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'

src/langbot/pkg/persistence/migrations/dbm021_merge_exception_handling.py

@@ -1,74 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(21)
-class DBMigrateMergeExceptionHandling(migration.DBMigration):
-    """Merge hide-exception and block-failed-request-output into a single exception-handling select option,
-    and add failure-hint field.
-
-    Conversion logic:
-    - block-failed-request-output=true  ->  exception-handling: hide
-    - hide-exception=true               ->  exception-handling: show-hint
-    - hide-exception=false              ->  exception-handling: show-error
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'output' not in config:
-                config['output'] = {}
-            if 'misc' not in config['output']:
-                config['output']['misc'] = {}
-
-            misc = config['output']['misc']
-
-            # Determine new exception-handling value from legacy fields
-            hide_exception = misc.get('hide-exception', True)
-            block_failed = misc.get('block-failed-request-output', False)
-
-            if block_failed:
-                exception_handling = 'hide'
-            elif hide_exception:
-                exception_handling = 'show-hint'
-            else:
-                exception_handling = 'show-error'
-
-            misc['exception-handling'] = exception_handling
-
-            # Add failure-hint with default value
-            misc['failure-hint'] = 'Request failed.'
-
-            # Remove legacy fields
-            misc.pop('hide-exception', None)
-
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm022_monitoring_user_name.py

@@ -1,73 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(22)
-class DBMigrateMonitoringUserId(migration.DBMigration):
-    """Add user_id and user_name columns to monitoring_sessions table
-
-    This migration adds the missing user_id column and also ensures user_name
-    column exists (in case migration 21 failed or was skipped).
-    """
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return bool(result.scalar())
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _get_table_columns(self, table_name: str) -> list[str]:
-        """Get column names from a table (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT column_name FROM information_schema.columns WHERE table_name = :table_name;'
-                ).bindparams(table_name=table_name)
-            )
-            return [row[0] for row in result.fetchall()]
-        else:
-            if not table_name.isidentifier():
-                raise ValueError(f'Invalid table name: {table_name}')
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            return [row[1] for row in result.fetchall()]
-
-    async def _add_column_if_not_exists(self, table_name: str, column_name: str, column_type: str):
-        """Add a column to a table if it does not already exist."""
-        columns = await self._get_table_columns(table_name)
-        if column_name in columns:
-            self.ap.logger.debug('%s column already exists in %s.', column_name, table_name)
-            return
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text(f'ALTER TABLE {table_name} ADD COLUMN {column_name} {column_type};')
-        )
-        self.ap.logger.info('Added %s column to %s table.', column_name, table_name)
-
-    async def upgrade(self):
-        # Check if monitoring_sessions table exists
-        if not await self._table_exists('monitoring_sessions'):
-            self.ap.logger.warning('monitoring_sessions table does not exist, skipping migration.')
-            return
-
-        # Add user_id column to monitoring_sessions table
-        await self._add_column_if_not_exists('monitoring_sessions', 'user_id', 'VARCHAR(255)')
-
-        # Add user_name column to monitoring_sessions table (in case migration 21 failed)
-        await self._add_column_if_not_exists('monitoring_sessions', 'user_name', 'VARCHAR(255)')
-
-        # Add user_name column to monitoring_messages table (in case migration 21 failed)
-        if await self._table_exists('monitoring_messages'):
-            await self._add_column_if_not_exists('monitoring_messages', 'user_name', 'VARCHAR(255)')
-
-    async def downgrade(self):
-        pass

src/langbot/pkg/persistence/migrations/dbm023_model_fallback_config.py

@@ -1,102 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(23)
-class DBMigrateModelFallbackConfig(migration.DBMigration):
-    """Convert model field from plain UUID string to object with primary/fallbacks"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'ai' not in config or 'local-agent' not in config['ai']:
-                continue
-
-            local_agent = config['ai']['local-agent']
-            changed = False
-
-            # Convert model from string to object
-            model_value = local_agent.get('model', '')
-            if isinstance(model_value, str):
-                local_agent['model'] = {
-                    'primary': model_value,
-                    'fallbacks': [],
-                }
-                changed = True
-
-            # Remove leftover fallback-models field if present
-            if 'fallback-models' in local_agent:
-                del local_agent['fallback-models']
-                changed = True
-
-            if not changed:
-                continue
-
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'ai' not in config or 'local-agent' not in config['ai']:
-                continue
-
-            local_agent = config['ai']['local-agent']
-
-            # Convert model from object back to string
-            model_value = local_agent.get('model', '')
-            if isinstance(model_value, dict):
-                local_agent['model'] = model_value.get('primary', '')
-            else:
-                continue
-
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )

src/langbot/pkg/persistence/migrations/dbm024_wecombot_websocket_mode.py

@@ -1,49 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(24)
-class DBMigrateWecomBotWebSocketMode(migration.DBMigration):
-    """Add enable-webhook field to existing wecombot adapter configs.
-
-    Existing wecombot bots were all using webhook mode, so we set
-    enable-webhook=true to preserve their behavior after the new
-    WebSocket long connection mode is introduced as default.
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text("SELECT uuid, adapter_config FROM bots WHERE adapter = 'wecombot'")
-        )
-        bots = result.fetchall()
-
-        for bot_row in bots:
-            bot_uuid = bot_row[0]
-            adapter_config = json.loads(bot_row[1]) if isinstance(bot_row[1], str) else bot_row[1]
-
-            if 'enable-webhook' in adapter_config:
-                continue
-
-            # Determine mode based on existing config: if webhook fields are present, keep webhook mode
-            has_webhook_config = bool(
-                adapter_config.get('Token') and adapter_config.get('EncodingAESKey') and adapter_config.get('Corpid')
-            )
-            adapter_config['enable-webhook'] = has_webhook_config
-
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('UPDATE bots SET adapter_config = :config::jsonb WHERE uuid = :uuid'),
-                    {'config': json.dumps(adapter_config), 'uuid': bot_uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('UPDATE bots SET adapter_config = :config WHERE uuid = :uuid'),
-                    {'config': json.dumps(adapter_config), 'uuid': bot_uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/pipeline/monitoring_helper.py

@@ -34,15 +34,6 @@ class MonitoringHelper:
             # Check if session exists, if not, record session start
             session_id = f'{query.launcher_type}_{query.launcher_id}'
 
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
             # Try to record message
             # Use JSON serialization to preserve message chain structure (including image URLs, etc.)
             if hasattr(query, 'message_chain') and hasattr(query.message_chain, 'model_dump'):
@@ -66,7 +57,6 @@ class MonitoringHelper:
                 if hasattr(query.launcher_type, 'value')
                 else str(query.launcher_type),
                 user_id=query.sender_id,
-                user_name=sender_name,
                 runner_name=runner_name,
                 variables=None,  # Will be updated in record_query_success
             )
@@ -90,7 +80,6 @@ class MonitoringHelper:
                     if hasattr(query.launcher_type, 'value')
                     else str(query.launcher_type),
                     user_id=query.sender_id,
-                    user_name=sender_name,
                 )
 
             return message_id
@@ -139,15 +128,6 @@ class MonitoringHelper:
         try:
             session_id = f'{query.launcher_type}_{query.launcher_id}'
 
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
             # Extract response content from resp_message_chain
             if hasattr(query, 'resp_message_chain') and query.resp_message_chain:
                 # Serialize the last response message chain
@@ -182,7 +162,6 @@ class MonitoringHelper:
                 if hasattr(query.launcher_type, 'value')
                 else str(query.launcher_type),
                 user_id=query.sender_id,
-                user_name=sender_name,
                 runner_name=runner_name,
                 role='assistant',
             )
@@ -204,15 +183,6 @@ class MonitoringHelper:
         try:
             session_id = f'{query.launcher_type}_{query.launcher_id}'
 
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
             # Record error message
             message_id = await ap.monitoring_service.record_message(
                 bot_id=bot_id,
@@ -227,7 +197,6 @@ class MonitoringHelper:
                 if hasattr(query.launcher_type, 'value')
                 else str(query.launcher_type),
                 user_id=query.sender_id,
-                user_name=sender_name,
                 runner_name=runner_name,
             )
 

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

@@ -36,36 +36,17 @@ class PreProcessor(stage.PipelineStage):
         session = await self.ap.sess_mgr.get_session(query)
 
         # When not local-agent, llm_model is None
-        llm_model = None
-        if selected_runner == 'local-agent':
-            # Read model config — new format is { primary: str, fallbacks: [str] },
-            # but handle legacy plain string for backward compatibility
-            model_config = query.pipeline_config['ai']['local-agent'].get('model', {})
-            if isinstance(model_config, str):
-                # Legacy format: plain UUID string
-                primary_uuid = model_config
-                fallback_uuids = []
-            else:
-                primary_uuid = model_config.get('primary', '')
-                fallback_uuids = model_config.get('fallbacks', [])
-
-            if primary_uuid:
-                try:
-                    llm_model = await self.ap.model_mgr.get_model_by_uuid(primary_uuid)
-                except ValueError:
-                    self.ap.logger.warning(f'LLM model {primary_uuid} not found or not configured')
-
-            # Resolve fallback model UUIDs
-            if fallback_uuids:
-                valid_fallbacks = []
-                for fb_uuid in fallback_uuids:
-                    try:
-                        await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
-                        valid_fallbacks.append(fb_uuid)
-                    except ValueError:
-                        self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
-                if valid_fallbacks:
-                    query.variables['_fallback_model_uuids'] = valid_fallbacks
+        try:
+            llm_model = (
+                await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
+                if selected_runner == 'local-agent'
+                else None
+            )
+        except ValueError:
+            self.ap.logger.warning(
+                f'LLM model {query.pipeline_config["ai"]["local-agent"]["model"] + " "}not found or not configured'
+            )
+            llm_model = None
 
         conversation = await self.ap.sess_mgr.get_conversation(
             query,
@@ -80,28 +61,20 @@ class PreProcessor(stage.PipelineStage):
         query.prompt = conversation.prompt.copy()
         query.messages = conversation.messages.copy()
 
-        if selected_runner == 'local-agent':
+        if selected_runner == 'local-agent' and llm_model:
             query.use_funcs = []
-            if llm_model:
-                query.use_llm_model_uuid = llm_model.model_entity.uuid
+            query.use_llm_model_uuid = llm_model.model_entity.uuid
 
-                if llm_model.model_entity.abilities.__contains__('func_call'):
-                    # Get bound plugins and MCP servers for filtering tools
-                    bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
-                    bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
-                    query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
-
-                    self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
-                    self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
-                    self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
-
-            # If primary model doesn't support func_call but fallback models exist,
-            # load tools anyway since fallback models may support them
-            if not query.use_funcs and query.variables.get('_fallback_model_uuids'):
+            if llm_model.model_entity.abilities.__contains__('func_call'):
+                # Get bound plugins and MCP servers for filtering tools
                 bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
                 bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
                 query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
 
+                self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
+                self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
+                self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
+
         sender_name = ''
 
         if isinstance(query.message_event, platform_events.GroupMessage):
@@ -176,16 +149,6 @@ class PreProcessor(stage.PipelineStage):
         query.variables['user_message_text'] = plain_text
 
         query.user_message = provider_message.Message(role='user', content=content_list)
-
-        # Extract knowledge base UUIDs into query variables so plugins can modify them
-        # during PromptPreProcessing before the runner performs retrieval.
-        kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
-        if not kb_uuids:
-            old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
-            if old_kb_uuid and old_kb_uuid != '__none__':
-                kb_uuids = [old_kb_uuid]
-        query.variables['_knowledge_base_uuids'] = list(kb_uuids)
-
         # =========== 触发事件 PromptPreProcessing
 
         event = events.PromptPreProcessing(

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

@@ -149,19 +149,12 @@ class ChatMessageHandler(handler.MessageHandler):
                 self.ap.logger.error(f'Conversation({query.query_id}) Request Failed: {error_info}')
                 traceback.print_exc()
 
-                exception_handling = query.pipeline_config['output']['misc'].get('exception-handling', 'show-hint')
-
-                if exception_handling == 'show-error':
-                    user_notice = f'{e}'
-                elif exception_handling == 'show-hint':
-                    user_notice = query.pipeline_config['output']['misc'].get('failure-hint', 'Request failed.')
-                else:  # hide
-                    user_notice = None
+                hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
 
                 yield entities.StageProcessResult(
                     result_type=entities.ResultType.INTERRUPT,
                     new_query=query,
-                    user_notice=user_notice,
+                    user_notice='请求失败' if hide_exception_info else f'{e}',
                     error_notice=f'{e}',
                     debug_notice=traceback.format_exc(),
                 )

src/langbot/pkg/platform/botmgr.py

@@ -9,7 +9,6 @@ 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
 
@@ -142,50 +141,6 @@ class RuntimeBot:
         self.adapter.register_listener(platform_events.FriendMessage, on_friend_message)
         self.adapter.register_listener(platform_events.GroupMessage, on_group_message)
 
-        # Register feedback listener (only effective on adapters that support it)
-        async def on_feedback(
-            event: platform_events.FeedbackEvent,
-            adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
-        ):
-            try:
-                # Resolve pipeline name
-                pipeline_name = ''
-                if self.bot_entity.use_pipeline_uuid:
-                    try:
-                        pipeline_result = await self.ap.persistence_mgr.execute_async(
-                            sqlalchemy.select(persistence_pipeline.LegacyPipeline.name).where(
-                                persistence_pipeline.LegacyPipeline.uuid == self.bot_entity.use_pipeline_uuid
-                            )
-                        )
-                        pipeline_row = pipeline_result.first()
-                        if pipeline_row:
-                            pipeline_name = pipeline_row[0]
-                    except Exception:
-                        pass
-
-                await self.ap.monitoring_service.record_feedback(
-                    feedback_id=event.feedback_id,
-                    feedback_type=event.feedback_type,
-                    feedback_content=event.feedback_content,
-                    inaccurate_reasons=event.inaccurate_reasons,
-                    bot_id=self.bot_entity.uuid,
-                    bot_name=self.bot_entity.name,
-                    pipeline_id=self.bot_entity.use_pipeline_uuid or '',
-                    pipeline_name=pipeline_name,
-                    session_id=event.session_id,
-                    message_id=event.message_id,
-                    stream_id=event.stream_id,
-                    user_id=event.user_id,
-                    platform=adapter.__class__.__name__,
-                )
-                await self.logger.info(
-                    f'Recorded feedback: feedback_id={event.feedback_id}, type={event.feedback_type}'
-                )
-            except Exception:
-                await self.logger.error(f'Failed to record feedback: {traceback.format_exc()}')
-
-        self.adapter.register_listener(platform_events.FeedbackEvent, on_feedback)
-
     async def run(self):
         async def exception_wrapper():
             try:

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

@@ -5,29 +5,19 @@ metadata:
   label:
     en_US: OneBot v11
     zh_Hans: OneBot v11
-    zh_Hant: OneBot v11
   description:
-    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
+    en_US: OneBot v11 Adapter
+    zh_Hans: OneBot v11 适配器，请查看文档了解使用方式
   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
@@ -35,11 +25,9 @@ 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
@@ -47,11 +35,9 @@ 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.yaml

@@ -5,25 +5,16 @@ 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: ""
@@ -31,7 +22,6 @@ 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: ""
@@ -39,7 +29,6 @@ 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: ""
@@ -47,7 +36,6 @@ 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: ""
@@ -55,7 +43,6 @@ 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
@@ -63,11 +50,9 @@ 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
@@ -75,7 +60,6 @@ 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
@@ -83,7 +67,6 @@ 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

@@ -5,38 +5,16 @@ 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，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
+    zh_Hans: Discord 适配器，请查看文档了解使用方式
   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: ""
@@ -44,11 +22,6 @@ 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

@@ -5,25 +5,16 @@ 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

@@ -575,127 +575,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
 
 
 class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    _processed_thread_quote_cache: typing.ClassVar[dict[str, float]] = {}
-    _processed_thread_quote_cache_max_size: typing.ClassVar[int] = 4096
-    _processed_thread_quote_cache_ttl_seconds: typing.ClassVar[int] = 86400
-
-    @classmethod
-    def _prune_processed_thread_quote_cache(cls, now: typing.Optional[float] = None) -> None:
-        if now is None:
-            now = time.time()
-
-        expire_before = now - cls._processed_thread_quote_cache_ttl_seconds
-        while cls._processed_thread_quote_cache:
-            oldest_key, oldest_ts = next(iter(cls._processed_thread_quote_cache.items()))
-            if oldest_ts >= expire_before:
-                break
-            cls._processed_thread_quote_cache.pop(oldest_key, None)
-
-        while len(cls._processed_thread_quote_cache) > cls._processed_thread_quote_cache_max_size:
-            oldest_key = next(iter(cls._processed_thread_quote_cache))
-            cls._processed_thread_quote_cache.pop(oldest_key, None)
-
-    @classmethod
-    def _mark_thread_quote_processed(cls, thread_id: str) -> None:
-        now = time.time()
-        cls._prune_processed_thread_quote_cache(now)
-        cls._processed_thread_quote_cache[thread_id] = now
-
-    @classmethod
-    def _extract_quote_message_id(cls, message: EventMessage) -> typing.Optional[str]:
-        """
-        Extract the message ID to quote from the given message.
-
-        Rules:
-        - First thread reply in a topic: return parent_id and mark topic as processed
-        - Follow-up thread replies in the same topic: return None
-        - Non-thread message: return parent_id if valid (non-empty, different from message_id)
-
-        Thread reply state is kept in a bounded TTL cache to avoid unbounded memory growth.
-        """
-        parent_id = getattr(message, 'parent_id', None)
-        if not parent_id:
-            return None
-
-        message_id = getattr(message, 'message_id', None)
-        if parent_id == message_id:
-            return None
-
-        thread_id = getattr(message, 'thread_id', None)
-        if thread_id:
-            cls._prune_processed_thread_quote_cache()
-            if thread_id in cls._processed_thread_quote_cache:
-                return None
-            cls._mark_thread_quote_processed(thread_id)
-
-        return parent_id
-
-    @staticmethod
-    def _build_event_message_from_message_item(message_item: Message) -> typing.Optional[EventMessage]:
-        """
-        Build EventMessage from SDK typed Message item.
-
-        Returns None if body or content is missing.
-        """
-        body = getattr(message_item, 'body', None)
-        if not body:
-            return None
-
-        content = getattr(body, 'content', None)
-        if not content:
-            return None
-
-        event_data = {
-            'message_id': message_item.message_id,
-            'message_type': message_item.msg_type,
-            'content': content,
-            'create_time': message_item.create_time,
-            'mentions': getattr(message_item, 'mentions', []) or [],
-        }
-
-        # Preserve thread-related fields
-        if hasattr(message_item, 'parent_id') and message_item.parent_id:
-            event_data['parent_id'] = message_item.parent_id
-        if hasattr(message_item, 'root_id') and message_item.root_id:
-            event_data['root_id'] = message_item.root_id
-        if hasattr(message_item, 'thread_id') and message_item.thread_id:
-            event_data['thread_id'] = message_item.thread_id
-        if hasattr(message_item, 'chat_id') and message_item.chat_id:
-            event_data['chat_id'] = message_item.chat_id
-
-        return EventMessage(event_data)
-
-    @staticmethod
-    async def _fetch_quoted_message(
-        quote_message_id: str,
-        api_client: lark_oapi.Client,
-    ) -> typing.Optional[platform_message.MessageChain]:
-        """
-        Fetch the quoted message and convert to MessageChain.
-
-        Returns None if:
-        - API call fails
-        - Response items is empty
-        - Message item normalization fails
-        """
-        request = GetMessageRequest.builder().message_id(quote_message_id).build()
-        response = await api_client.im.v1.message.aget(request)
-
-        if not response.success():
-            return None
-
-        items = getattr(response.data, 'items', None)
-        if not items:
-            return None
-
-        message_item = items[0]
-        event_message = LarkEventConverter._build_event_message_from_message_item(message_item)
-        if event_message is None:
-            return None
-
-        quote_chain = await LarkMessageConverter.target2yiri(event_message, api_client)
-        return quote_chain
-
     @staticmethod
     async def yiri2target(
         event: platform_events.MessageEvent,
@@ -708,23 +587,6 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
     ) -> platform_events.Event:
         message_chain = await LarkMessageConverter.target2yiri(event.event.message, api_client)
 
-        # Check for quote/reply message
-        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,
-                        )
-                    )
-
         if event.event.message.chat_type == 'p2p':
             return platform_events.FriendMessage(
                 sender=platform_entities.Friend(
@@ -908,32 +770,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             self.request_tenant_access_token(tenant_key)
         return self.tenant_access_tokens.get(tenant_key)['token'] if self.tenant_access_tokens.get(tenant_key) else None
 
-    def get_launcher_id(self, event: platform_events.MessageEvent) -> str | None:
-        """
-        Get topic-scoped launcher_id for thread-aware session isolation.
-
-        For group thread messages, returns "{group_id}_{thread_id}"
-        to ensure conversation context stays stable per topic.
-
-        Returns None for non-thread messages or P2P messages.
-        """
-        source_event = getattr(event.source_platform_object, 'event', None)
-        if not source_event:
-            return None
-
-        message = getattr(source_event, 'message', None)
-        if not message:
-            return None
-
-        thread_id = getattr(message, 'thread_id', None)
-        if not thread_id:
-            return None
-
-        if isinstance(event, platform_events.GroupMessage):
-            return f'{event.group.id}_{thread_id}'
-
-        return None
-
     def build_api_client(self, config):
         app_id = config['app_id']
         app_secret = config['app_secret']

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

@@ -5,30 +5,16 @@ metadata:
   label:
     en_US: Lark
     zh_Hans: 飞书
-    zh_Hant: 飛書
-    ja_JP: Lark
   description:
-    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。
+    en_US: Lark Adapter
+    zh_Hans: 飞书适配器，请查看文档了解使用方式
   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: ""
@@ -36,8 +22,6 @@ 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: ""
@@ -45,13 +29,9 @@ 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: ""
@@ -59,63 +39,29 @@ 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
@@ -123,40 +69,28 @@ 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

@@ -5,56 +5,20 @@ 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, 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
+    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
   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: 頻道存取令牌
-        th_TH: โทเค็นการเข้าถึงช่อง
-        vi_VN: Mã truy cập kênh
-        es_ES: Token de acceso del canal
+        zh_Hant: 頻道訪問令牌
       type: string
       required: true
       default: ""
@@ -63,18 +27,12 @@ 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: 訊息密鑰
-        th_TH: รหัสลับช่อง
-        vi_VN: Khóa bí mật kênh
-        es_ES: Secreto del canal
+        zh_Hant: 消息密钥
       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: 請填寫加密密鑰
-        th_TH: กรุณากรอกคีย์เข้ารหัส
-        vi_VN: Vui lòng điền khóa mã hóa
-        es_ES: Por favor, introduzca la clave de cifrado
+        zh_Hant: 請填寫加密密钥
       type: string
       required: true
       default: ""

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

@@ -5,44 +5,23 @@ 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，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
+    zh_Hans: 微信公众号适配器，请查看文档了解使用方式
   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
-        zh_Hant: 令牌
+      type: string
       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: ""
@@ -50,7 +29,6 @@ spec:
       label:
         en_US: App ID
         zh_Hans: 应用ID
-        zh_Hant: 應用ID
       type: string
       required: true
       default: ""
@@ -58,7 +36,6 @@ spec:
       label:
         en_US: App Secret
         zh_Hans: 应用密钥
-        zh_Hant: 應用密鑰
       type: string
       required: true
       default: ""
@@ -66,7 +43,6 @@ spec:
       label:
         en_US: Mode
         zh_Hans: 接入模式
-        zh_Hant: 接入模式
       type: string
       required: true
       default: "drop"
@@ -74,7 +50,6 @@ 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。"
@@ -82,11 +57,9 @@ 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.py

@@ -1,577 +0,0 @@
-"""OpenClaw WeChat adapter for LangBot.
-
-Uses the OpenClaw WeChat HTTP JSON API (long-poll getUpdates + sendMessage)
-to integrate personal WeChat accounts with LangBot.
-
-Reference: https://github.com/epiral/weixin-bot
-"""
-
-from __future__ import annotations
-
-import asyncio
-import base64
-import traceback
-import typing
-
-import pydantic
-import sqlalchemy
-
-from langbot.libs.openclaw_weixin_api.client import (
-    DEFAULT_BASE_URL,
-    SESSION_EXPIRED_ERRCODE,
-    OpenClawWeixinClient,
-)
-from langbot.libs.openclaw_weixin_api.types import (
-    MessageItem,
-    WeixinMessage,
-)
-from langbot.pkg.entity.persistence import bot as persistence_bot
-
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger
-import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-
-
-class OpenClawWeixinMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
-    """Converts between LangBot MessageChain and OpenClaw WeChat message items."""
-
-    @staticmethod
-    async def yiri2target(message_chain: platform_message.MessageChain) -> list[dict]:
-        """Convert LangBot MessageChain to a list of OpenClaw message item dicts."""
-        items = []
-        for component in message_chain:
-            if isinstance(component, platform_message.Plain):
-                items.append({'type': MessageItem.TEXT, 'text_item': {'text': component.text}})
-            elif isinstance(component, platform_message.Image):
-                # OpenClaw WeChat only supports text messages without CDN upload.
-                # For images, we send a placeholder text with the URL if available.
-                if component.url:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': f'[Image: {component.url}]'},
-                        }
-                    )
-                elif component.base64:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': '[Image]'},
-                        }
-                    )
-            elif isinstance(component, platform_message.File):
-                if component.name:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': f'[File: {component.name}]'},
-                        }
-                    )
-            elif isinstance(component, platform_message.Forward):
-                for node in component.node_list:
-                    if node.message_chain:
-                        items.extend(await OpenClawWeixinMessageConverter.yiri2target(node.message_chain))
-        return items
-
-    @staticmethod
-    async def target2yiri(
-        msg: WeixinMessage,
-    ) -> platform_message.MessageChain:
-        """Convert an OpenClaw WeixinMessage to LangBot MessageChain."""
-        components: list[platform_message.MessageComponent] = []
-
-        if not msg.item_list:
-            return platform_message.MessageChain(components)
-
-        for item in msg.item_list:
-            if item.type == MessageItem.TEXT and item.text_item and item.text_item.text:
-                text = item.text_item.text
-
-                # Handle quoted messages
-                if item.ref_msg:
-                    ref_parts = []
-                    if item.ref_msg.title:
-                        ref_parts.append(item.ref_msg.title)
-                    if item.ref_msg.message_item:
-                        ref_item = item.ref_msg.message_item
-                        if ref_item.text_item and ref_item.text_item.text:
-                            ref_parts.append(ref_item.text_item.text)
-                    if ref_parts:
-                        components.append(
-                            platform_message.Quote(
-                                sender_id='',
-                                origin=platform_message.MessageChain(
-                                    [platform_message.Plain(text=' | '.join(ref_parts))]
-                                ),
-                            )
-                        )
-
-                components.append(platform_message.Plain(text=text))
-
-            elif item.type == MessageItem.IMAGE and item.image_item:
-                if hasattr(item.image_item, '_downloaded_bytes') and item.image_item._downloaded_bytes:
-                    b64 = base64.b64encode(item.image_item._downloaded_bytes).decode('utf-8')
-                    components.append(platform_message.Image(base64=f'data:image/jpeg;base64,{b64}'))
-                else:
-                    components.append(platform_message.Unknown(text='[Image]'))
-
-            elif item.type == MessageItem.VOICE and item.voice_item:
-                # Voice with speech-to-text: use the transcribed text
-                if item.voice_item.text:
-                    components.append(platform_message.Plain(text=item.voice_item.text))
-                else:
-                    components.append(platform_message.Unknown(text='[Voice]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.VOICE and item.voice_item:
-            #     if item.voice_item.text:
-            #         components.append(platform_message.Plain(text=item.voice_item.text))
-            #     elif hasattr(item.voice_item, '_downloaded_bytes') and item.voice_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.voice_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.Voice(
-            #                 base64=b64,
-            #                 length=item.voice_item.playtime or 0,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.Voice(
-            #                 length=item.voice_item.playtime or 0,
-            #             )
-            #         )
-
-            elif item.type == MessageItem.FILE and item.file_item:
-                components.append(platform_message.Unknown(text=f'[File: {item.file_item.file_name or ""}]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.FILE and item.file_item:
-            #     file_name = item.file_item.file_name or ''
-            #     file_size = int(item.file_item.len) if item.file_item.len else 0
-            #     if hasattr(item.file_item, '_downloaded_bytes') and item.file_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.file_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.File(
-            #                 name=file_name,
-            #                 size=file_size,
-            #                 base64=b64,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.File(
-            #                 name=file_name,
-            #                 size=file_size,
-            #             )
-            #         )
-
-            elif item.type == MessageItem.VIDEO and item.video_item:
-                components.append(platform_message.Unknown(text='[Video]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.VIDEO and item.video_item:
-            #     if hasattr(item.video_item, '_downloaded_bytes') and item.video_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.video_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.File(
-            #                 name='video.mp4',
-            #                 size=item.video_item.video_size or 0,
-            #                 base64=b64,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.File(
-            #                 name='video.mp4',
-            #                 size=item.video_item.video_size or 0,
-            #             )
-            #         )
-
-            else:
-                components.append(platform_message.Unknown(text='[Unknown message type]'))
-
-        return platform_message.MessageChain(components)
-
-
-class OpenClawWeixinEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    """Converts OpenClaw WeChat messages to LangBot events."""
-
-    @staticmethod
-    async def yiri2target(event: platform_events.MessageEvent) -> dict:
-        return event.source_platform_object
-
-    @staticmethod
-    async def target2yiri(msg: WeixinMessage) -> typing.Optional[platform_events.MessageEvent]:
-        """Convert an inbound WeixinMessage to a LangBot event."""
-        if msg.message_type != WeixinMessage.TYPE_USER:
-            return None
-
-        from_user_id = msg.from_user_id or ''
-        if not from_user_id:
-            return None
-
-        message_chain = await OpenClawWeixinMessageConverter.target2yiri(msg)
-        if not message_chain:
-            return None
-
-        timestamp = (msg.create_time_ms or 0) / 1000.0
-
-        return platform_events.FriendMessage(
-            sender=platform_entities.Friend(
-                id=from_user_id,
-                nickname=from_user_id,
-                remark='',
-            ),
-            message_chain=message_chain,
-            time=timestamp,
-            source_platform_object=msg,
-        )
-
-
-class OpenClawWeixinAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    """LangBot adapter for OpenClaw WeChat (long-poll based)."""
-
-    name: str = 'openclaw-weixin'
-
-    client: OpenClawWeixinClient = pydantic.Field(exclude=True)
-
-    config: dict
-
-    message_converter: OpenClawWeixinMessageConverter = OpenClawWeixinMessageConverter()
-    event_converter: OpenClawWeixinEventConverter = OpenClawWeixinEventConverter()
-
-    # context_token cache: from_user_id -> context_token
-    _context_tokens: dict[str, str] = pydantic.PrivateAttr(default_factory=dict)
-
-    _polling: bool = pydantic.PrivateAttr(default=False)
-    _poll_task: typing.Optional[asyncio.Task] = pydantic.PrivateAttr(default=None)
-    _bot_uuid: typing.Optional[str] = pydantic.PrivateAttr(default=None)
-
-    listeners: typing.Dict[
-        typing.Type[platform_events.Event],
-        typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ] = {}
-
-    def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger):
-        client = OpenClawWeixinClient(
-            base_url=config.get('base_url', DEFAULT_BASE_URL),
-            token=config.get('token', ''),
-        )
-        super().__init__(
-            config=config,
-            logger=logger,
-            client=client,
-            bot_account_id='',
-            listeners={},
-            name='openclaw-weixin',
-        )
-
-    def set_bot_uuid(self, bot_uuid: str):
-        """Called by BotManager to provide the bot's UUID for config persistence."""
-        self._bot_uuid = bot_uuid
-
-    async def _persist_config(self) -> None:
-        """Persist current self.config to the database so token survives restart."""
-        if not self._bot_uuid:
-            return
-        try:
-            ap = self.logger.ap
-            await ap.persistence_mgr.execute_async(
-                sqlalchemy.update(persistence_bot.Bot)
-                .where(persistence_bot.Bot.uuid == self._bot_uuid)
-                .values(adapter_config=self.config)
-            )
-        except Exception as e:
-            await self.logger.warning(f'Failed to persist adapter config: {e}')
-
-    async def _do_login(self) -> None:
-        """Run the QR code login flow via client.login() and update config."""
-        adapter_logger = self.logger
-
-        async def _on_qrcode(qr_base64: str, _qr_url: str):
-            await adapter_logger.info(
-                f'Please scan the QR code to login WeChat: {_qr_url}',
-                images=[platform_message.Image(base64=qr_base64)],
-            )
-
-        login_result = await self.client.login(
-            on_qrcode=_on_qrcode,
-        )
-
-        # client.login() already updates client.token and client.base_url
-        self.config['token'] = login_result.token
-        self.config['base_url'] = login_result.base_url
-        if login_result.account_id:
-            self.config['account_id'] = login_result.account_id
-
-        await self.logger.info(f'WeChat login successful! account_id={login_result.account_id}')
-
-        # Persist token to database so it survives restart
-        await self._persist_config()
-
-    async def send_message(
-        self,
-        target_type: str,
-        target_id: str,
-        message: platform_message.MessageChain,
-    ):
-        """Send a message to a user."""
-        context_token = self._context_tokens.get(target_id, '')
-
-        for component in message:
-            try:
-                if isinstance(component, platform_message.Plain):
-                    if component.text:
-                        await self.client.send_text(target_id, component.text, context_token)
-
-                elif isinstance(component, platform_message.Image):
-                    img_bytes, _ = await component.get_bytes()
-                    await self.client.send_image(target_id, img_bytes, context_token)
-
-                elif isinstance(component, platform_message.File):
-                    file_bytes = await self._get_component_bytes(component)
-                    if file_bytes:
-                        await self.client.send_file(target_id, file_bytes, component.name or 'file', context_token)
-
-                elif isinstance(component, platform_message.Voice):
-                    voice_bytes = await self._get_component_bytes(component)
-                    if voice_bytes:
-                        await self.client.send_voice(target_id, voice_bytes, component.length or 0, context_token)
-
-                elif isinstance(component, platform_message.Forward):
-                    for node in component.node_list:
-                        if node.message_chain:
-                            await self.send_message(target_type, target_id, node.message_chain)
-
-            except Exception:
-                await self.logger.error(
-                    f'Failed to send component {type(component).__name__}: {traceback.format_exc()}'
-                )
-
-    async def reply_message(
-        self,
-        message_source: platform_events.MessageEvent,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-    ):
-        """Reply to a received message."""
-        source_msg = message_source.source_platform_object
-        if isinstance(source_msg, WeixinMessage):
-            target_id = source_msg.from_user_id or ''
-            if target_id:
-                await self.send_message('friend', target_id, message)
-
-    async def is_muted(self, group_id: int) -> bool:
-        return False
-
-    @staticmethod
-    async def _get_component_bytes(component: platform_message.MessageComponent) -> typing.Optional[bytes]:
-        """Extract raw bytes from a File or Voice component."""
-        b64_val = getattr(component, 'base64', None)
-        url_val = getattr(component, 'url', None)
-        path_val = getattr(component, 'path', None)
-
-        if b64_val:
-            return base64.b64decode(b64_val)
-        elif url_val and url_val.startswith(('http://', 'https://')):
-            import aiohttp
-
-            async with aiohttp.ClientSession() as session:
-                async with session.get(url_val) as resp:
-                    if resp.status == 200:
-                        return await resp.read()
-        elif path_val:
-            import asyncio
-
-            with open(path_val, 'rb') as f:
-                return await asyncio.to_thread(f.read)
-        return None
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter],
-            None,
-        ],
-    ):
-        self.listeners[event_type] = callback
-
-    def unregister_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter],
-            None,
-        ],
-    ):
-        self.listeners.pop(event_type, None)
-
-    async def run_async(self):
-        """Start the adapter. If no token is configured, trigger QR code login first."""
-        base_url = self.config.get('base_url', DEFAULT_BASE_URL)
-        token = self.config.get('token', '')
-
-        await self.logger.info('OpenClaw WeChat adapter starting...')
-
-        # QR code login flow when no token is provided
-        if not token:
-            await self.logger.info('No token configured, starting QR code login...')
-            try:
-                await self._do_login()
-            except Exception as e:
-                await self.logger.error(f'QR code login failed: {e}')
-                raise
-
-        # Rebuild client with the (possibly updated) config
-        self.client = OpenClawWeixinClient(
-            base_url=self.config.get('base_url', base_url),
-            token=self.config.get('token', token),
-        )
-        self.bot_account_id = self.config.get('account_id', 'openclaw-weixin')
-        self._polling = True
-
-        # Start the long-poll loop
-        self._poll_task = asyncio.create_task(self._poll_loop())
-        await self.logger.info('OpenClaw WeChat adapter running')
-
-        try:
-            await self._poll_task
-        except asyncio.CancelledError:
-            pass
-
-    async def _poll_loop(self):
-        """Long-poll loop: call getUpdates continuously.
-
-        Error handling follows the weixin-bot SDK pattern:
-        - Exponential backoff (1s -> 10s max) on failures
-        - Session expired (errcode -14) triggers automatic re-login
-        """
-        get_updates_buf = ''
-        poll_timeout = float(self.config.get('poll_timeout', 35))
-
-        backoff_delay = 1.0
-        max_backoff = 10.0
-
-        while self._polling:
-            try:
-                resp = await self.client.get_updates(
-                    get_updates_buf=get_updates_buf,
-                    timeout=poll_timeout + 5,
-                )
-
-                if resp.longpolling_timeout_ms and resp.longpolling_timeout_ms > 0:
-                    poll_timeout = resp.longpolling_timeout_ms / 1000.0
-
-                is_api_error = (resp.ret is not None and resp.ret != 0) or (
-                    resp.errcode is not None and resp.errcode != 0
-                )
-                if is_api_error:
-                    is_session_expired = resp.errcode == SESSION_EXPIRED_ERRCODE or resp.ret == SESSION_EXPIRED_ERRCODE
-
-                    if is_session_expired:
-                        await self.logger.error('OpenClaw WeChat session expired, attempting re-login...')
-                        try:
-                            await self._do_login()
-                            # Rebuild client with new credentials
-                            self.client = OpenClawWeixinClient(
-                                base_url=self.config.get('base_url', DEFAULT_BASE_URL),
-                                token=self.config.get('token', ''),
-                            )
-                            self._context_tokens.clear()
-                            get_updates_buf = ''
-                            backoff_delay = 1.0
-                            continue
-                        except Exception:
-                            await self.logger.error(f'Re-login failed: {traceback.format_exc()}')
-                            break
-
-                    await self.logger.error(
-                        f'OpenClaw getUpdates failed: ret={resp.ret} errcode={resp.errcode} errmsg={resp.errmsg}'
-                    )
-                    await asyncio.sleep(backoff_delay)
-                    backoff_delay = min(backoff_delay * 2, max_backoff)
-                    continue
-
-                backoff_delay = 1.0
-
-                if resp.get_updates_buf:
-                    get_updates_buf = resp.get_updates_buf
-
-                for msg in resp.msgs:
-                    try:
-                        await self._handle_inbound_message(msg)
-                    except Exception:
-                        await self.logger.error(f'Error handling message: {traceback.format_exc()}')
-
-            except asyncio.CancelledError:
-                break
-            except Exception:
-                await self.logger.error(f'OpenClaw poll error: {traceback.format_exc()}')
-                await asyncio.sleep(backoff_delay)
-                backoff_delay = min(backoff_delay * 2, max_backoff)
-
-    async def _handle_inbound_message(self, msg: WeixinMessage):
-        """Process a single inbound message from getUpdates."""
-        if msg.context_token and msg.from_user_id:
-            self._context_tokens[msg.from_user_id] = msg.context_token
-
-        # Download CDN media (files, images) before converting to LangBot events
-        await self._download_media_items(msg)
-
-        event = await OpenClawWeixinEventConverter.target2yiri(msg)
-        if event is None:
-            return
-
-        if type(event) in self.listeners:
-            await self.listeners[type(event)](event, self)
-
-    async def _download_media_items(self, msg: WeixinMessage):
-        """Download CDN media for image items in the message."""
-        if not msg.item_list:
-            return
-
-        for item in msg.item_list:
-            try:
-                if item.type == MessageItem.IMAGE and item.image_item:
-                    if (
-                        item.image_item.media
-                        and item.image_item.media.encrypt_query_param
-                        and item.image_item.media.aes_key
-                    ):
-                        img_bytes = await self.client.download_media(item.image_item.media)
-                        item.image_item._downloaded_bytes = img_bytes
-
-                # TODO: enable after full testing
-                # elif item.type == MessageItem.FILE and item.file_item and item.file_item.media:
-                #     if item.file_item.media.encrypt_query_param and item.file_item.media.aes_key:
-                #         file_bytes = await self.client.download_media(item.file_item.media)
-                #         item.file_item._downloaded_bytes = file_bytes
-                #
-                # elif item.type == MessageItem.VOICE and item.voice_item and item.voice_item.media:
-                #     if item.voice_item.media.encrypt_query_param and item.voice_item.media.aes_key:
-                #         voice_bytes = await self.client.download_media(item.voice_item.media)
-                #         item.voice_item._downloaded_bytes = voice_bytes
-                #
-                # elif item.type == MessageItem.VIDEO and item.video_item and item.video_item.media:
-                #     if item.video_item.media.encrypt_query_param and item.video_item.media.aes_key:
-                #         video_bytes = await self.client.download_media(item.video_item.media)
-                #         item.video_item._downloaded_bytes = video_bytes
-
-            except Exception:
-                await self.logger.warning(f'Failed to download CDN media: {traceback.format_exc()}')
-
-    async def kill(self) -> bool:
-        """Stop the adapter."""
-        self._polling = False
-        if self._poll_task and not self._poll_task.done():
-            self._poll_task.cancel()
-            try:
-                await self._poll_task
-            except asyncio.CancelledError:
-                pass
-        await self.client.close()
-        await self.logger.info('OpenClaw WeChat adapter stopped')
-        return True

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

@@ -1,74 +0,0 @@
-apiVersion: v1
-kind: MessagePlatformAdapter
-metadata:
-  name: openclaw-weixin
-  label:
-    en_US: OpenClaw WeChat
-    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: 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"
-    - name: token
-      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。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: ""
-    - name: account_id
-      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"
-    - name: poll_timeout
-      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
-execution:
-  python:
-    path: ./openclaw_weixin.py
-    attr: OpenClawWeixinAdapter

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

@@ -5,37 +5,16 @@ 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)，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
+    zh_Hans: QQ 官方 API (Webhook)，请查看文档了解使用方式
   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: ""
@@ -43,7 +22,6 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥
-        zh_Hant: 密鑰
       type: string
       required: true
       default: ""
@@ -51,7 +29,6 @@ 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

@@ -5,70 +5,36 @@ 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: 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
+    zh_Hans: 古明地觉协议适配器
   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
@@ -76,10 +42,6 @@ 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"
@@ -87,10 +49,6 @@ 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"
@@ -98,10 +56,6 @@ 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

@@ -5,58 +5,16 @@ 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，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
+    zh_Hans: Slack 适配器，请查看文档了解使用方式
   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: ""
@@ -64,11 +22,6 @@ 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.py

@@ -42,25 +42,6 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
                         photo_bytes = f.read()
 
                 components.append({'type': 'photo', 'photo': photo_bytes})
-            elif isinstance(component, platform_message.File):
-                file_bytes = None
-
-                if component.base64:
-                    # Strip data URI prefix if present (e.g. "data:application/pdf;base64,...")
-                    b64_data = component.base64
-                    if ';base64,' in b64_data:
-                        b64_data = b64_data.split(';base64,', 1)[1]
-                    file_bytes = base64.b64decode(b64_data)
-                elif component.url:
-                    session = httpclient.get_session()
-                    async with session.get(component.url) as response:
-                        file_bytes = await response.read()
-                elif component.path:
-                    with open(component.path, 'rb') as f:
-                        file_bytes = f.read()
-
-                file_name = getattr(component, 'name', None) or 'file'
-                components.append({'type': 'document', 'document': file_bytes, 'filename': file_name})
             elif isinstance(component, platform_message.Forward):
                 for node in component.node_list:
                     components.extend(await TelegramMessageConverter.yiri2target(node.message_chain, bot))
@@ -123,27 +104,6 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
                 )
             )
 
-        if message.document:
-            if message.caption:
-                message_components.extend(parse_message_text(message.caption))
-
-            file = await message.document.get_file()
-            file_name = message.document.file_name or 'document'
-            file_size = message.document.file_size or 0
-            file_format = message.document.mime_type or 'application/octet-stream'
-
-            file_bytes = None
-            async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
-                file_bytes = await response.read()
-
-            message_components.append(
-                platform_message.File(
-                    name=file_name,
-                    size=file_size,
-                    base64=f'data:{file_format};base64,{base64.b64encode(file_bytes).decode("utf-8")}',
-                )
-            )
-
         return platform_message.MessageChain(message_components)
 
 
@@ -219,10 +179,7 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         application = ApplicationBuilder().token(config['token']).build()
         bot = application.bot
         application.add_handler(
-            MessageHandler(
-                filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE | filters.Document.ALL,
-                telegram_callback,
-            )
+            MessageHandler(filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE, telegram_callback)
         )
         super().__init__(
             config=config,
@@ -261,13 +218,6 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     continue
                 args['photo'] = telegram.InputFile(photo)
                 await self.bot.send_photo(**args)
-            elif component_type == 'document':
-                doc = component.get('document')
-                if doc is None:
-                    continue
-                filename = component.get('filename', 'file')
-                args['document'] = telegram.InputFile(doc, filename=filename)
-                await self.bot.send_document(**args)
 
     async def reply_message(
         self,

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

@@ -5,50 +5,23 @@ 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: 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
+    zh_Hans: 电报适配器，请查看文档了解使用方式
   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: "token_from_botfather"
+      default: ""
     - 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
@@ -56,19 +29,9 @@ 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

@@ -5,21 +5,11 @@ 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

@@ -4,26 +4,17 @@ metadata:
   name: wechatpad
   label:
     en_US: WeChatPad
-    zh_Hans: WeChatPad（个人微信ipad）
-    zh_Hant: WeChatPad（個人微信iPad）
+    zh_CN: WeChatPad（个人微信ipad）
   description:
     en_US: WeChatPad Adapter
-    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
+    zh_CN: WeChatPad 适配器
   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: ""
@@ -31,7 +22,6 @@ spec:
       label:
         en_US: WeChatPad_Ws
         zh_CN: WeChatPad_Ws
-        zh_Hant: WeChatPad_Ws
       type: string
       required: true
       default: ""
@@ -39,7 +29,6 @@ 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: ""
@@ -47,7 +36,6 @@ spec:
       label:
         en_US: Token
         zh_CN: 令牌
-        zh_Hant: 令牌
       type: string
       required: true
       default: ""
@@ -55,7 +43,6 @@ spec:
       label:
         en_US: wxid
         zh_CN: wxid
-        zh_Hant: wxid
       type: string
       required: true
       default: ""

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

@@ -148,54 +148,51 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
             pass
 
         if type(event) is platform_events.FriendMessage:
-            return event.source_platform_object
+            payload = {
+                'MsgType': 'text',
+                'Content': '',
+                'FromUserName': event.sender.id,
+                'ToUserName': bot_account_id,
+                'CreateTime': int(datetime.datetime.now().timestamp()),
+                'AgentID': event.sender.nickname,
+            }
+            wecom_event = WecomEvent.from_payload(payload=payload)
+            if not wecom_event:
+                raise ValueError('无法从 message_data 构造 WecomEvent 对象')
+
+            return wecom_event
 
     @staticmethod
-    async def target2yiri(event: WecomEvent, bot: WecomClient = None):
+    async def target2yiri(event: WecomEvent):
         """
         将 WecomEvent 转换为平台的 FriendMessage 对象。
 
         Args:
             event (WecomEvent): 企业微信事件。
-            bot (WecomClient): 企业微信客户端，用于获取用户信息。
 
         Returns:
             platform_events.FriendMessage: 转换后的 FriendMessage 对象。
         """
-        # Try to get the user's real name from the WeCom API
-        nickname = str(event.user_id)
-        if bot and event.user_id:
-            try:
-                user_info = await bot.get_user_info(event.user_id)
-                if user_info and user_info.get('name'):
-                    nickname = user_info.get('name')
-            except Exception:
-                pass  # Fall back to user_id as nickname
-
         # 转换消息链
         if event.type == 'text':
             yiri_chain = await WecomMessageConverter.target2yiri(event.message, event.message_id)
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.agent_id),
                 remark='',
             )
 
-            return platform_events.FriendMessage(
-                sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
-            )
+            return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
         elif event.type == 'image':
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.agent_id),
                 remark='',
             )
 
             yiri_chain = await WecomMessageConverter.target2yiri_image(picurl=event.picurl, message_id=event.message_id)
 
-            return platform_events.FriendMessage(
-                sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
-            )
+            return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
 
 
 class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
@@ -213,6 +210,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             'secret',
             'token',
             'EncodingAESKey',
+            'contacts_secret',
         ]
 
         missing_keys = [key for key in required_keys if key not in config]
@@ -225,7 +223,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             secret=config['secret'],
             token=config['token'],
             EncodingAESKey=config['EncodingAESKey'],
-            contacts_secret=config.get('contacts_secret', ''),  # Optional, kept for backward compatibility
+            contacts_secret=config['contacts_secret'],
             logger=logger,
             unified_mode=True,
             api_base_url=config.get('api_base_url', 'https://qyapi.weixin.qq.com/cgi-bin'),
@@ -250,17 +248,18 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     ):
         Wecom_event = await WecomEventConverter.yiri2target(message_source, self.bot_account_id, self.bot)
         content_list = await WecomMessageConverter.yiri2target(message, self.bot)
-        # user_id is the original FromUserName from WecomEvent
-        user_id = Wecom_event.user_id
+        fixed_user_id = Wecom_event.user_id
+        # 删掉开头的u
+        fixed_user_id = fixed_user_id[1:]
         for content in content_list:
             if content['type'] == 'text':
-                await self.bot.send_private_msg(user_id, Wecom_event.agent_id, content['content'])
+                await self.bot.send_private_msg(fixed_user_id, Wecom_event.agent_id, content['content'])
             elif content['type'] == 'image':
-                await self.bot.send_image(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_image(fixed_user_id, Wecom_event.agent_id, content['media_id'])
             elif content['type'] == 'voice':
-                await self.bot.send_voice(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_voice(fixed_user_id, Wecom_event.agent_id, content['media_id'])
             elif content['type'] == 'file':
-                await self.bot.send_file(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_file(fixed_user_id, Wecom_event.agent_id, content['media_id'])
 
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
         content_list = await WecomMessageConverter.yiri2target(message, self.bot)
@@ -288,7 +287,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         async def on_message(event: WecomEvent):
             self.bot_account_id = event.receiver_id
             try:
-                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+                return await callback(await self.event_converter.target2yiri(event), self)
             except Exception:
                 await self.logger.error(f'Error in wecom callback: {traceback.format_exc()}')
 

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

@@ -5,38 +5,16 @@ 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
+    zh_Hans: 企业微信适配器，请查看文档了解使用方式
   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: ""
@@ -44,7 +22,6 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥 (Secret)
-        zh_Hant: 密鑰 (Secret)
       type: string
       required: true
       default: ""
@@ -52,7 +29,6 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌 (Token)
-        zh_Hant: 令牌 (Token)
       type: string
       required: true
       default: ""
@@ -60,7 +36,13 @@ 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: ""
+    - name: contacts_secret
+      label:
+        en_US: Contacts Secret
+        zh_Hans: 通讯录密钥
       type: string
       required: true
       default: ""
@@ -68,11 +50,9 @@ 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

@@ -11,7 +11,6 @@ import langbot_plugin.api.entities.builtin.platform.entities as platform_entitie
 from ..logger import EventLogger
 from langbot.libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
 from langbot.libs.wecom_ai_bot_api.api import WecomBotClient
-from langbot.libs.wecom_ai_bot_api.ws_client import WecomBotWsClient
 
 
 class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
@@ -24,18 +23,14 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
         return content
 
     @staticmethod
-    async def target2yiri(event: WecomBotEvent, bot_name: str = ''):
+    async def target2yiri(event: WecomBotEvent):
         yiri_msg_list = []
         if event.type == 'group':
             yiri_msg_list.append(platform_message.At(target=event.ai_bot_id))
-
         yiri_msg_list.append(platform_message.Source(id=event.message_id, time=datetime.datetime.now()))
 
         if event.content:
-            content = event.content
-            if bot_name:
-                content = content.replace(f'@{bot_name}', '').strip()
-            yiri_msg_list.append(platform_message.Plain(text=content))
+            yiri_msg_list.append(platform_message.Plain(text=event.content))
 
         images = []
         if event.images:
@@ -138,15 +133,13 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
 
 
 class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    def __init__(self, bot_name: str = ''):
-        self.bot_name = bot_name
-
     @staticmethod
     async def yiri2target(event: platform_events.MessageEvent):
         return event.source_platform_object
 
-    async def target2yiri(self, event: WecomBotEvent):
-        message_chain = await WecomBotMessageConverter.target2yiri(event, bot_name=self.bot_name)
+    @staticmethod
+    async def target2yiri(event: WecomBotEvent):
+        message_chain = await WecomBotMessageConverter.target2yiri(event)
         if event.type == 'single':
             return platform_events.FriendMessage(
                 sender=platform_entities.Friend(
@@ -183,53 +176,34 @@ class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
 
 
 class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    bot: typing.Union[WecomBotClient, WecomBotWsClient]
+    bot: WecomBotClient
     bot_account_id: str
     message_converter: WecomBotMessageConverter = WecomBotMessageConverter()
-    event_converter: WecomBotEventConverter
+    event_converter: WecomBotEventConverter = WecomBotEventConverter()
     config: dict
     bot_uuid: str = None
-    _ws_mode: bool = False
-    bot_name: str = ''
-    listeners: dict = {}
 
     def __init__(self, config: dict, logger: EventLogger):
-        enable_webhook = config.get('enable-webhook', False)
-        bot_name = config.get('robot_name', '')
+        required_keys = ['Token', 'EncodingAESKey', 'Corpid', 'BotId']
+        missing_keys = [key for key in required_keys if key not in config]
+        if missing_keys:
+            raise Exception(f'WecomBot 缺少配置项: {missing_keys}')
 
-        if not enable_webhook:
-            bot = WecomBotWsClient(
-                bot_id=config['BotId'],
-                secret=config['Secret'],
-                logger=logger,
-                encoding_aes_key=config.get('EncodingAESKey', ''),
-            )
-        else:
-            # Webhook callback mode
-            required_keys = ['Token', 'EncodingAESKey', 'Corpid']
-            missing_keys = [key for key in required_keys if key not in config or not config[key]]
-            if missing_keys:
-                raise Exception(f'WecomBot webhook mode missing config: {missing_keys}')
+        bot = WecomBotClient(
+            Token=config['Token'],
+            EnCodingAESKey=config['EncodingAESKey'],
+            Corpid=config['Corpid'],
+            logger=logger,
+            unified_mode=True,
+        )
+        bot_account_id = config['BotId']
 
-            bot = WecomBotClient(
-                Token=config['Token'],
-                EnCodingAESKey=config['EncodingAESKey'],
-                Corpid=config['Corpid'],
-                logger=logger,
-                unified_mode=True,
-            )
-
-        bot_account_id = config.get('BotId', '')
-        event_converter = WecomBotEventConverter(bot_name=bot_name)
         super().__init__(
             config=config,
             logger=logger,
             bot=bot,
             bot_account_id=bot_account_id,
-            bot_name=bot_name,
-            event_converter=event_converter,
         )
-        self.listeners = {}
 
     async def reply_message(
         self,
@@ -238,17 +212,7 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         quote_origin: bool = False,
     ):
         content = await self.message_converter.yiri2target(message)
-        _ws_mode = not self.config.get('enable-webhook', False)
-
-        if _ws_mode:
-            event = message_source.source_platform_object
-            req_id = event.get('req_id', '')
-            if req_id:
-                await self.bot.reply_text(req_id, content)
-            else:
-                await self.bot.set_message(event.message_id, content)
-        else:
-            await self.bot.set_message(message_source.source_platform_object.message_id, content)
+        await self.bot.set_message(message_source.source_platform_object.message_id, content)
 
     async def reply_message_chunk(
         self,
@@ -258,44 +222,44 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         quote_origin: bool = False,
         is_final: bool = False,
     ):
+        """将流水线增量输出写入企业微信 stream 会话。
+
+        Args:
+            message_source: 流水线提供的原始消息事件。
+            bot_message: 当前片段对应的模型元信息（未使用）。
+            message: 需要回复的消息链。
+            quote_origin: 是否引用原消息（企业微信暂不支持）。
+            is_final: 标记当前片段是否为最终回复。
+
+        Returns:
+            dict: 包含 `stream` 键，标识写入是否成功。
+
+        Example:
+            在流水线 `reply_message_chunk` 调用中自动触发，无需手动调用。
+        """
+        # 转换为纯文本（智能机器人当前协议仅支持文本流）
         content = await self.message_converter.yiri2target(message)
         msg_id = message_source.source_platform_object.message_id
-        _ws_mode = not self.config.get('enable-webhook', False)
 
-        if _ws_mode:
-            success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
-            if not success and is_final:
-                event = message_source.source_platform_object
-                req_id = event.get('req_id', '')
-                if req_id:
-                    await self.bot.reply_text(req_id, content)
-            return {'stream': success}
-        else:
-            success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
-            if not success and is_final:
-                await self.bot.set_message(msg_id, content)
-            return {'stream': success}
+        # 将片段推送到 WecomBotClient 中的队列，返回值用于判断是否走降级逻辑
+        success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
+        if not success and is_final:
+            # 未命中流式队列时使用旧有 set_message 兜底
+            await self.bot.set_message(msg_id, content)
+        return {'stream': success}
 
     async def is_stream_output_supported(self) -> bool:
-        """Whether streaming output is enabled for this bot instance."""
-        return self.config.get('enable-stream-reply', True)
+        """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
 
     async def send_message(self, target_type, target_id, message):
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            content = await self.message_converter.yiri2target(message)
-            await self.bot.send_message(target_id, content)
-        else:
-            pass
-
-    async def on_message(self, event: WecomBotEvent):
-        try:
-            lb_event = await self.event_converter.target2yiri(event)
-            if lb_event:
-                await self.listeners[type(lb_event)](lb_event, self)
-        except Exception:
-            await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
-            print(traceback.format_exc())
+        pass
 
     def register_listener(
         self,
@@ -304,16 +268,18 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
         ],
     ):
-        self.listeners[event_type] = callback
+        async def on_message(event: WecomBotEvent):
+            try:
+                return await callback(await self.event_converter.target2yiri(event), self)
+            except Exception:
+                await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
+                print(traceback.format_exc())
 
         try:
             if event_type == platform_events.FriendMessage:
-                self.bot.on_message('single')(self.on_message)
+                self.bot.on_message('single')(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)
+                self.bot.on_message('group')(on_message)
         except Exception:
             print(traceback.format_exc())
 
@@ -321,68 +287,30 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         """设置 bot UUID（用于生成 webhook URL）"""
         self.bot_uuid = bot_uuid
 
-    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
-            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
-
-            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=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:
-            return None
+        """处理统一 webhook 请求。
+
+        Args:
+            bot_uuid: Bot 的 UUID
+            path: 子路径（如果有的话）
+            request: Quart Request 对象
+
+        Returns:
+            响应数据
+        """
         return await self.bot.handle_unified_webhook(request)
 
     async def run_async(self):
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            await self.bot.connect()
-        else:
+        # 统一 webhook 模式下，不启动独立的 Quart 应用
+        # 保持运行但不启动独立端口
 
-            async def keep_alive():
-                while True:
-                    await asyncio.sleep(1)
+        async def keep_alive():
+            while True:
+                await asyncio.sleep(1)
 
-            await keep_alive()
+        await keep_alive()
 
     async def kill(self) -> bool:
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            await self.bot.disconnect()
-            return True
         return False
 
     async def unregister_listener(

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

@@ -5,125 +5,41 @@ 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，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
+    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
   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: ""
-    - name: robot_name
-      label:
-        en_US: Robot Name
-        zh_Hans: 机器人名称
-        zh_Hant: 機器人名稱
-      type: string
-      required: true
-      default: ""
-    - name: enable-webhook
-      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: ""
     - name: Corpid
       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
+      required: true
       default: ""
     - name: Token
       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
+      required: true
       default: ""
     - name: EncodingAESKey
       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: true
+      default: ""
+    - name: BotId
+      label:
+        en_US: BotId
+        zh_Hans: 机器人ID
       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
-    attr: WecomBotAdapter
+    attr: WecomBotAdapter

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

@@ -81,33 +81,22 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
             return event.source_platform_object
 
     @staticmethod
-    async def target2yiri(event: WecomCSEvent, bot: WecomCSClient = None):
+    async def target2yiri(event: WecomCSEvent):
         """
         将 WecomEvent 转换为平台的 FriendMessage 对象。
 
         Args:
             event (WecomEvent): 企业微信客服事件。
-            bot (WecomCSClient): 企业微信客服客户端，用于获取用户信息。
 
         Returns:
             platform_events.FriendMessage: 转换后的 FriendMessage 对象。
         """
-        # Try to get customer nickname from WeChat API
-        nickname = str(event.user_id)
-        if bot and event.user_id:
-            try:
-                customer_info = await bot.get_customer_info(event.user_id)
-                if customer_info and customer_info.get('nickname'):
-                    nickname = customer_info.get('nickname')
-            except Exception:
-                pass  # Fall back to user_id as nickname
-
         # 转换消息链
         if event.type == 'text':
             yiri_chain = await WecomMessageConverter.target2yiri(event.message, event.message_id)
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.user_id),
                 remark='',
             )
 
@@ -117,7 +106,7 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
         elif event.type == 'image':
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.user_id),
                 remark='',
             )
 
@@ -198,7 +187,7 @@ class WecomCSAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         async def on_message(event: WecomCSEvent):
             self.bot_account_id = event.receiver_id
             try:
-                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+                return await callback(await self.event_converter.target2yiri(event), self)
             except Exception:
                 await self.logger.error(f'Error in wecomcs callback: {traceback.format_exc()}')
 

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

@@ -5,37 +5,16 @@ 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
+    zh_Hans: 企业微信客服适配器
   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: ""
@@ -43,7 +22,6 @@ spec:
       label:
         en_US: Secret
         zh_Hans: 密钥
-        zh_Hant: 密鑰
       type: string
       required: true
       default: ""
@@ -51,7 +29,6 @@ spec:
       label:
         en_US: Token
         zh_Hans: 令牌
-        zh_Hant: 令牌
       type: string
       required: true
       default: ""
@@ -59,7 +36,6 @@ 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: ""
@@ -67,11 +43,9 @@ 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

@@ -2,9 +2,6 @@
 from __future__ import annotations
 
 import asyncio
-import io
-import time
-import zipfile
 from typing import Any
 import typing
 import os
@@ -195,30 +192,6 @@ 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,
@@ -228,44 +201,23 @@ 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 with streaming progress
+            # download and transfer file
             try:
                 async with httpx.AsyncClient(
                     trust_env=True,
                     follow_redirects=True,
-                    timeout=60,
+                    timeout=20,
                 ) as client:
-                    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)
+                    response = await client.get(
+                        install_info['asset_url'],
+                    )
+                    response.raise_for_status()
+                    file_bytes = response.content
                     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')
@@ -284,11 +236,6 @@ 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/plugin/handler.py

@@ -314,11 +314,11 @@ class RuntimeConnectionHandler(handler.Handler):
 
         @self.action(PluginToRuntimeAction.GET_LLM_MODELS)
         async def get_llm_models(data: dict[str, Any]) -> handler.ActionResponse:
-            """Get llm models, returns list of UUID strings"""
+            """Get llm models"""
             llm_models = await self.ap.llm_model_service.get_llm_models(include_secret=False)
             return handler.ActionResponse.success(
                 data={
-                    'llm_models': [m['uuid'] for m in llm_models],
+                    'llm_models': llm_models,
                 },
             )
 
@@ -531,7 +531,6 @@ class RuntimeConnectionHandler(handler.Handler):
             filters = data.get('filters')
             search_type = data.get('search_type', 'vector')
             query_text = data.get('query_text', '')
-            vector_weight = data.get('vector_weight')
             try:
                 results = await self.ap.rag_runtime_service.vector_search(
                     collection_id,
@@ -540,7 +539,6 @@ class RuntimeConnectionHandler(handler.Handler):
                     filters,
                     search_type,
                     query_text,
-                    vector_weight=vector_weight,
                 )
                 return handler.ActionResponse.success(data={'results': results})
             except Exception as e:
@@ -557,18 +555,6 @@ class RuntimeConnectionHandler(handler.Handler):
             except Exception as e:
                 return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
 
-        @self.action(PluginToRuntimeAction.VECTOR_LIST)
-        async def vector_list(data: dict[str, Any]) -> handler.ActionResponse:
-            collection_id = data['collection_id']
-            filters = data.get('filters')
-            limit = data.get('limit', 20)
-            offset = data.get('offset', 0)
-            try:
-                items, total = await self.ap.rag_runtime_service.vector_list(collection_id, filters, limit, offset)
-                return handler.ActionResponse.success(data={'items': items, 'total': total})
-            except Exception as e:
-                return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
-
         @self.action(PluginToRuntimeAction.GET_KNOWLEDEGE_FILE_STREAM)
         async def get_knowledge_file_stream(data: dict[str, Any]) -> handler.ActionResponse:
             storage_path = data['storage_path']
@@ -579,16 +565,6 @@ class RuntimeConnectionHandler(handler.Handler):
             except Exception as e:
                 return _make_rag_error_response(e, 'FileServiceError', storage_path=storage_path)
 
-        @self.action(PluginToRuntimeAction.LIST_PARSERS)
-        async def list_parsers(data: dict[str, Any]) -> handler.ActionResponse:
-            """Plugin requests host to list available parser plugins."""
-            mime_type = data.get('mime_type')
-            try:
-                parsers = await self.ap.knowledge_service.list_parsers(mime_type)
-                return handler.ActionResponse.success(data={'parsers': parsers})
-            except Exception as e:
-                return _make_rag_error_response(e, 'ParserDiscoveryError', mime_type=mime_type)
-
         @self.action(PluginToRuntimeAction.INVOKE_PARSER)
         async def invoke_parser(data: dict[str, Any]) -> handler.ActionResponse:
             """Plugin requests host to invoke a parser plugin."""
@@ -613,139 +589,6 @@ class RuntimeConnectionHandler(handler.Handler):
             except Exception as e:
                 return _make_rag_error_response(e, 'ParserError')
 
-        # ================= Knowledge Base Query APIs =================
-
-        @self.action(PluginToRuntimeAction.LIST_KNOWLEDGE_BASES)
-        async def list_knowledge_bases(data: dict[str, Any]) -> handler.ActionResponse:
-            """List all knowledge bases available in the LangBot instance (unrestricted)."""
-            knowledge_bases = []
-            for kb_uuid, kb in self.ap.rag_mgr.knowledge_bases.items():
-                knowledge_bases.append(
-                    {
-                        'uuid': kb.get_uuid(),
-                        'name': kb.get_name(),
-                        'description': kb.knowledge_base_entity.description or '',
-                    }
-                )
-            return handler.ActionResponse.success(data={'knowledge_bases': knowledge_bases})
-
-        @self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE)
-        async def retrieve_knowledge(data: dict[str, Any]) -> handler.ActionResponse:
-            """Retrieve documents from any knowledge base (unrestricted)."""
-            kb_id = data['kb_id']
-            query_text = data['query_text']
-            top_k = data.get('top_k', 5)
-            filters = data.get('filters', {})
-
-            kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_id)
-            if not kb:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} not found',
-                )
-
-            try:
-                entries = await kb.retrieve(
-                    query_text,
-                    settings={
-                        'top_k': top_k,
-                        'filters': filters,
-                    },
-                )
-                results = [entry.model_dump(mode='json') for entry in entries]
-                return handler.ActionResponse.success(data={'results': results})
-            except Exception as e:
-                return _make_rag_error_response(e, 'RetrievalError', kb_id=kb_id)
-
-        @self.action(PluginToRuntimeAction.LIST_PIPELINE_KNOWLEDGE_BASES)
-        async def list_pipeline_knowledge_bases(data: dict[str, Any]) -> handler.ActionResponse:
-            """List knowledge bases configured for the current query's pipeline."""
-            query_id = data['query_id']
-
-            if query_id not in self.ap.query_pool.cached_queries:
-                return handler.ActionResponse.error(
-                    message=f'Query with query_id {query_id} not found',
-                )
-
-            query = self.ap.query_pool.cached_queries[query_id]
-
-            kb_uuids = []
-            if query.pipeline_config:
-                local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
-                kb_uuids = local_agent_config.get('knowledge-bases', [])
-                # Backward compatibility
-                if not kb_uuids:
-                    old_kb_uuid = local_agent_config.get('knowledge-base', '')
-                    if old_kb_uuid and old_kb_uuid != '__none__':
-                        kb_uuids = [old_kb_uuid]
-
-            knowledge_bases = []
-            for kb_uuid in kb_uuids:
-                kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
-                if kb:
-                    knowledge_bases.append(
-                        {
-                            'uuid': kb.get_uuid(),
-                            'name': kb.get_name(),
-                            'description': kb.knowledge_base_entity.description or '',
-                        }
-                    )
-
-            return handler.ActionResponse.success(data={'knowledge_bases': knowledge_bases})
-
-        @self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE_BASE)
-        async def retrieve_knowledge_base(data: dict[str, Any]) -> handler.ActionResponse:
-            """Retrieve documents from a knowledge base within the pipeline's scope."""
-            query_id = data['query_id']
-            kb_id = data['kb_id']
-            query_text = data['query_text']
-            top_k = data.get('top_k', 5)
-            filters = data.get('filters', {})
-
-            if query_id not in self.ap.query_pool.cached_queries:
-                return handler.ActionResponse.error(
-                    message=f'Query with query_id {query_id} not found',
-                )
-
-            query = self.ap.query_pool.cached_queries[query_id]
-
-            # Validate kb_id is in pipeline's allowed list
-            allowed_kb_uuids = []
-            if query.pipeline_config:
-                local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
-                allowed_kb_uuids = local_agent_config.get('knowledge-bases', [])
-                if not allowed_kb_uuids:
-                    old_kb_uuid = local_agent_config.get('knowledge-base', '')
-                    if old_kb_uuid and old_kb_uuid != '__none__':
-                        allowed_kb_uuids = [old_kb_uuid]
-
-            if kb_id not in allowed_kb_uuids:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} is not configured for this pipeline',
-                )
-
-            kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_id)
-            if not kb:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} not found',
-                )
-
-            try:
-                session_name = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
-                entries = await kb.retrieve(
-                    query_text,
-                    settings={
-                        'top_k': top_k,
-                        'filters': filters,
-                        'session_name': session_name,
-                        'bot_uuid': query.bot_uuid or '',
-                        'sender_id': str(query.sender_id),
-                    },
-                )
-                results = [entry.model_dump(mode='json') for entry in entries]
-                return handler.ActionResponse.success(data={'results': results})
-            except Exception as e:
-                return _make_rag_error_response(e, 'RetrievalError', kb_id=kb_id)
-
         @self.action(CommonAction.PING)
         async def ping(data: dict[str, Any]) -> handler.ActionResponse:
             """Ping"""
@@ -1052,7 +895,7 @@ class RuntimeConnectionHandler(handler.Handler):
         result = await self.call_action(
             LangBotToRuntimeAction.RAG_INGEST_DOCUMENT,
             {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'context': context_data},
-            timeout=1200,  # Ingestion can be slow for large documents
+            timeout=300,  # Ingestion can be slow
         )
         return result
 

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

@@ -288,10 +288,10 @@ class AnthropicMessages(requester.ProviderAPIRequester):
             think_started = False
             think_ended = False
             finish_reason = False
+            content = ''
             tool_name = ''
             tool_id = ''
             async for chunk in await self.client.messages.create(**args):
-                content = ''
                 tool_call = {'id': None, 'function': {'name': None, 'arguments': None}, 'type': 'function'}
                 if isinstance(
                     chunk, anthropic.types.raw_content_block_start_event.RawContentBlockStartEvent

src/langbot/pkg/provider/runners/difysvapi.py

@@ -441,7 +441,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         is_final = False
         think_start = False
         think_end = False
-        yielded_final = False
 
         remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
 
@@ -494,19 +493,13 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                     if answer:
                         basic_mode_pending_chunk = answer
 
-            if (
-                not yielded_final
-                and (is_final or message_idx % 8 == 0)
-                and (basic_mode_pending_chunk != '' or is_final)
-            ):
+            if (is_final or message_idx % 8 == 0) and (basic_mode_pending_chunk != '' or is_final):
                 # content, _ = self._process_thinking_content(basic_mode_pending_chunk)
                 yield provider_message.MessageChunk(
                     role='assistant',
                     content=basic_mode_pending_chunk,
                     is_final=is_final,
                 )
-                if is_final:
-                    yielded_final = True
 
         if chunk is None:
             raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')

src/langbot/pkg/provider/runners/localagent.py

@@ -4,7 +4,6 @@ import json
 import copy
 import typing
 from .. import runner
-from ..modelmgr import requester as modelmgr_requester
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
 import langbot_plugin.api.entities.builtin.provider.message as provider_message
 import langbot_plugin.api.entities.builtin.rag.context as rag_context
@@ -27,114 +26,29 @@ Respond in the same language as the user's input.
 
 @runner.runner_class('local-agent')
 class LocalAgentRunner(runner.RequestRunner):
-    """Local agent request runner"""
+    """本地Agent请求运行器"""
 
-    async def _get_model_candidates(
-        self,
-        query: pipeline_query.Query,
-    ) -> list[modelmgr_requester.RuntimeLLMModel]:
-        """Build ordered list of models to try: primary model + fallback models."""
-        candidates = []
+    class ToolCallTracker:
+        """工具调用追踪器"""
 
-        # Primary model
-        if query.use_llm_model_uuid:
-            try:
-                primary = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
-                candidates.append(primary)
-            except ValueError:
-                self.ap.logger.warning(f'Primary model {query.use_llm_model_uuid} not found')
-
-        # Fallback models
-        fallback_uuids = (query.variables or {}).get('_fallback_model_uuids', [])
-        for fb_uuid in fallback_uuids:
-            try:
-                fb_model = await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
-                candidates.append(fb_model)
-            except ValueError:
-                self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
-
-        return candidates
-
-    async def _invoke_with_fallback(
-        self,
-        query: pipeline_query.Query,
-        candidates: list[modelmgr_requester.RuntimeLLMModel],
-        messages: list,
-        funcs: list,
-        remove_think: bool,
-    ) -> tuple[provider_message.Message, modelmgr_requester.RuntimeLLMModel]:
-        """Try non-streaming invocation with sequential fallback. Returns (message, model_used)."""
-        last_error = None
-        for model in candidates:
-            try:
-                msg = await model.provider.invoke_llm(
-                    query,
-                    model,
-                    messages,
-                    funcs if model.model_entity.abilities.__contains__('func_call') else [],
-                    extra_args=model.model_entity.extra_args,
-                    remove_think=remove_think,
-                )
-                return msg, model
-            except Exception as e:
-                last_error = e
-                self.ap.logger.warning(f'Model {model.model_entity.name} failed: {e}, trying next fallback...')
-        raise last_error or RuntimeError('No model candidates available')
-
-    async def _invoke_stream_with_fallback(
-        self,
-        query: pipeline_query.Query,
-        candidates: list[modelmgr_requester.RuntimeLLMModel],
-        messages: list,
-        funcs: list,
-        remove_think: bool,
-    ) -> tuple[typing.AsyncGenerator, modelmgr_requester.RuntimeLLMModel]:
-        """Try streaming invocation with sequential fallback. Returns (stream_generator, model_used).
-
-        Fallback is only possible before any chunks have been yielded to the client.
-        Once streaming starts, the model is committed.
-        """
-        last_error = None
-        for model in candidates:
-            try:
-                stream = model.provider.invoke_llm_stream(
-                    query,
-                    model,
-                    messages,
-                    funcs if model.model_entity.abilities.__contains__('func_call') else [],
-                    extra_args=model.model_entity.extra_args,
-                    remove_think=remove_think,
-                )
-                # Attempt to get the first chunk to verify the stream works
-                first_chunk = await stream.__anext__()
-
-                async def _chain_stream(first, rest):
-                    yield first
-                    async for chunk in rest:
-                        yield chunk
-
-                return _chain_stream(first_chunk, stream), model
-            except StopAsyncIteration:
-                # Empty stream — treat as success (model returned nothing)
-                async def _empty_stream():
-                    return
-                    yield  # make it a generator
-
-                return _empty_stream(), model
-            except Exception as e:
-                last_error = e
-                self.ap.logger.warning(f'Model {model.model_entity.name} stream failed: {e}, trying next fallback...')
-        raise last_error or RuntimeError('No model candidates available')
+        def __init__(self):
+            self.active_calls: dict[str, dict] = {}
+            self.completed_calls: list[provider_message.ToolCall] = []
 
     async def run(
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
-        """Run request"""
+        """运行请求"""
         pending_tool_calls = []
 
-        # Get knowledge bases list from query variables (set by PreProcessor,
-        # may have been modified by plugins during PromptPreProcessing)
-        kb_uuids = query.variables.get('_knowledge_base_uuids', [])
+        # Get knowledge bases list (new field)
+        kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
+
+        # Fallback to old field for backward compatibility
+        if not kb_uuids:
+            old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
+            if old_kb_uuid and old_kb_uuid != '__none__':
+                kb_uuids = [old_kb_uuid]
 
         user_message = copy.deepcopy(query.user_message)
 
@@ -160,14 +74,7 @@ class LocalAgentRunner(runner.RequestRunner):
                     self.ap.logger.warning(f'Knowledge base {kb_uuid} not found, skipping')
                     continue
 
-                result = await kb.retrieve(
-                    user_message_text,
-                    settings={
-                        'bot_uuid': query.bot_uuid or '',
-                        'sender_id': str(query.sender_id),
-                        'session_name': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-                    },
-                )
+                result = await kb.retrieve(user_message_text)
 
                 if result:
                     all_results.extend(result)
@@ -206,51 +113,51 @@ class LocalAgentRunner(runner.RequestRunner):
 
         remove_think = query.pipeline_config['output'].get('misc', '').get('remove-think')
 
-        # Build ordered candidate list (primary + fallbacks)
-        candidates = await self._get_model_candidates(query)
-        if not candidates:
-            raise RuntimeError('No LLM model configured for local-agent runner')
+        use_llm_model = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
 
         self.ap.logger.debug(
-            f'localagent req: query={query.query_id} req_messages={req_messages} '
-            f'candidates={[m.model_entity.name for m in candidates]}'
+            f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
         )
 
         if not is_stream:
-            # Non-streaming: invoke with fallback
-            msg, use_llm_model = await self._invoke_with_fallback(
+            # 非流式输出，直接请求
+
+            msg = await use_llm_model.provider.invoke_llm(
                 query,
-                candidates,
+                use_llm_model,
                 req_messages,
                 query.use_funcs,
-                remove_think,
+                extra_args=use_llm_model.model_entity.extra_args,
+                remove_think=remove_think,
             )
             yield msg
             final_msg = msg
         else:
-            # Streaming: invoke with fallback
+            # 流式输出，需要处理工具调用
             tool_calls_map: dict[str, provider_message.ToolCall] = {}
             msg_idx = 0
-            accumulated_content = ''
+            accumulated_content = ''  # 从开始累积的所有内容
             last_role = 'assistant'
             msg_sequence = 1
-
-            stream_src, use_llm_model = await self._invoke_stream_with_fallback(
+            async for msg in use_llm_model.provider.invoke_llm_stream(
                 query,
-                candidates,
+                use_llm_model,
                 req_messages,
                 query.use_funcs,
-                remove_think,
-            )
-            async for msg in stream_src:
+                extra_args=use_llm_model.model_entity.extra_args,
+                remove_think=remove_think,
+            ):
                 msg_idx = msg_idx + 1
 
+                # 记录角色
                 if msg.role:
                     last_role = msg.role
 
+                # 累积内容
                 if msg.content:
                     accumulated_content += msg.content
 
+                # 处理工具调用
                 if msg.tool_calls:
                     for tool_call in msg.tool_calls:
                         if tool_call.id not in tool_calls_map:
@@ -262,18 +169,21 @@ class LocalAgentRunner(runner.RequestRunner):
                                 ),
                             )
                         if tool_call.function and tool_call.function.arguments:
+                            # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
                             tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
-
+                # continue
+                # 每8个chunk或最后一个chunk时，输出所有累积的内容
                 if msg_idx % 8 == 0 or msg.is_final:
                     msg_sequence += 1
                     yield provider_message.MessageChunk(
                         role=last_role,
-                        content=accumulated_content,
+                        content=accumulated_content,  # 输出所有累积内容
                         tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
                         is_final=msg.is_final,
                         msg_sequence=msg_sequence,
                     )
 
+            # 创建最终消息用于后续处理
             final_msg = provider_message.MessageChunk(
                 role=last_role,
                 content=accumulated_content,
@@ -288,8 +198,7 @@ class LocalAgentRunner(runner.RequestRunner):
 
         req_messages.append(final_msg)
 
-        # Once a model succeeds, commit to it for the tool call loop
-        # (no fallback mid-conversation — different models may interpret tool results differently)
+        # 持续请求，只要还有待处理的工具调用就继续处理调用
         while pending_tool_calls:
             for tool_call in pending_tool_calls:
                 try:
@@ -330,6 +239,7 @@ class LocalAgentRunner(runner.RequestRunner):
 
                     req_messages.append(msg)
                 except Exception as e:
+                    # 工具调用出错，添加一个报错信息到 req_messages
                     err_msg = provider_message.Message(role='tool', content=f'err: {e}', tool_call_id=tool_call.id)
 
                     yield err_msg
@@ -337,38 +247,39 @@ class LocalAgentRunner(runner.RequestRunner):
                     req_messages.append(err_msg)
 
             self.ap.logger.debug(
-                f'localagent req: query={query.query_id} req_messages={req_messages} '
-                f'use_llm_model={use_llm_model.model_entity.name}'
+                f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
             )
 
             if is_stream:
                 tool_calls_map = {}
                 msg_idx = 0
-                accumulated_content = ''
+                accumulated_content = ''  # 从开始累积的所有内容
                 last_role = 'assistant'
                 msg_sequence = first_end_sequence
 
-                tool_stream_src = use_llm_model.provider.invoke_llm_stream(
+                async for msg in use_llm_model.provider.invoke_llm_stream(
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
+                    query.use_funcs,
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
-                )
-                async for msg in tool_stream_src:
+                ):
                     msg_idx += 1
 
+                    # 记录角色
                     if msg.role:
                         last_role = msg.role
 
-                    # Prepend first-round content on first chunk of tool-call round
+                    # 第一次请求工具调用时的内容
                     if msg_idx == 1:
                         accumulated_content = first_content if first_content is not None else accumulated_content
 
+                    # 累积内容
                     if msg.content:
                         accumulated_content += msg.content
 
+                    # 处理工具调用
                     if msg.tool_calls:
                         for tool_call in msg.tool_calls:
                             if tool_call.id not in tool_calls_map:
@@ -380,13 +291,15 @@ class LocalAgentRunner(runner.RequestRunner):
                                     ),
                                 )
                             if tool_call.function and tool_call.function.arguments:
+                                # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
                                 tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
 
+                    # 每8个chunk或最后一个chunk时，输出所有累积的内容
                     if msg_idx % 8 == 0 or msg.is_final:
                         msg_sequence += 1
                         yield provider_message.MessageChunk(
                             role=last_role,
-                            content=accumulated_content,
+                            content=accumulated_content,  # 输出所有累积内容
                             tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
                             is_final=msg.is_final,
                             msg_sequence=msg_sequence,
@@ -399,12 +312,12 @@ class LocalAgentRunner(runner.RequestRunner):
                     msg_sequence=msg_sequence,
                 )
             else:
-                # Non-streaming: use committed model directly (no fallback in tool loop)
+                # 处理完所有调用，再次请求
                 msg = await use_llm_model.provider.invoke_llm(
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
+                    query.use_funcs,
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
                 )

src/langbot/pkg/rag/knowledge/kbmgr.py

@@ -321,19 +321,13 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
         if not plugin_id:
             raise ValueError(f'No RAG plugin ID configured for KB {kb.uuid}. Retrieval failed.')
 
-        # Session context (e.g. session_name) stays in retrieval_settings
-        # for plugins that need it. Do NOT move them into filters, as filters
-        # are passed directly to vector_search by some plugins (e.g. LangRAG)
-        # and would cause empty results when the metadata field doesn't exist.
-        filters = settings.pop('filters', {})
-
         retrieval_context = {
             'query': query,
             'knowledge_base_id': kb.uuid,
             'collection_id': kb.collection_id or kb.uuid,
             'retrieval_settings': settings,
             'creation_settings': kb.creation_settings or {},
-            'filters': filters,
+            'filters': settings.pop('filters', {}),
         }
 
         result = await self.ap.plugin_connector.call_rag_retrieve(

src/langbot/pkg/rag/service/runtime.py

@@ -41,7 +41,6 @@ class RAGRuntimeService:
         filters: dict[str, Any] | None = None,
         search_type: str = 'vector',
         query_text: str = '',
-        vector_weight: float | None = None,
     ) -> list[dict[str, Any]]:
         """Handle VECTOR_SEARCH action."""
         return await self.ap.vector_db_mgr.search(
@@ -51,7 +50,6 @@ class RAGRuntimeService:
             filter=filters,
             search_type=search_type,
             query_text=query_text,
-            vector_weight=vector_weight,
         )
 
     async def vector_delete(
@@ -77,31 +75,6 @@ class RAGRuntimeService:
             count = await self.ap.vector_db_mgr.delete_by_filter(collection_name=collection_id, filter=filters)
         return count
 
-    async def vector_list(
-        self,
-        collection_id: str,
-        filters: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        """Handle VECTOR_LIST action.
-
-        Args:
-            collection_id: The collection to list from.
-            filters: Optional metadata filters.
-            limit: Maximum number of items to return.
-            offset: Number of items to skip.
-
-        Returns:
-            Tuple of (items, total).
-        """
-        return await self.ap.vector_db_mgr.list_by_filter(
-            collection_name=collection_id,
-            filter=filters,
-            limit=limit,
-            offset=offset,
-        )
-
     async def get_file_stream(self, storage_path: str) -> bytes:
         """Handle GET_KNOWLEDEGE_FILE_STREAM action.
 

src/langbot/pkg/utils/constants.py

@@ -2,7 +2,7 @@ import langbot
 
 semantic_version = f'v{langbot.__version__}'
 
-required_database_version = 24
+required_database_version = 20
 """Tag the version of the database schema, used to check if the database needs to be migrated"""
 
 debug_mode = False

src/langbot/pkg/utils/version.py

@@ -203,7 +203,7 @@ class VersionManager:
         try:
             if await self.ap.ver_mgr.is_new_version_available():
                 return (
-                    'New version available:\n有新版本可用，根据文档更新: \nhttps://link.langbot.app/zh/docs/update',
+                    'New version available:\n有新版本可用，根据文档更新: \nhttps://docs.langbot.app/zh/deploy/update.html',
                     logging.INFO,
                 )
 

src/langbot/pkg/vector/filter_utils.py

@@ -49,25 +49,17 @@ def normalize_filter(
 def strip_unsupported_fields(
     triples: list[tuple[str, str, Any]],
     supported_fields: set[str],
-    field_aliases: dict[str, str] | None = None,
 ) -> list[tuple[str, str, Any]]:
     """Return only triples whose field is in *supported_fields*.
 
-    If *field_aliases* is provided, aliased field names are mapped to the
-    canonical backend name before the support check.  For example,
-    ``{'uuid': 'chunk_uuid'}`` allows callers to use ``uuid`` which is
-    transparently rewritten to ``chunk_uuid``.
-
     Dropped fields are logged at WARNING level so the caller knows they were
     silently ignored (useful for Milvus / pgvector which only store a fixed
     schema).
     """
-    aliases = field_aliases or {}
     kept: list[tuple[str, str, Any]] = []
     for field, op, value in triples:
-        resolved = aliases.get(field, field)
-        if resolved in supported_fields:
-            kept.append((resolved, op, value))
+        if field in supported_fields:
+            kept.append((field, op, value))
         else:
             logger.warning(
                 'Filter field %r is not supported by this backend and will be ignored (supported: %s)',

src/langbot/pkg/vector/mgr.py

@@ -97,11 +97,10 @@ class VectorDBManager:
         filter: dict | None = None,
         search_type: str = 'vector',
         query_text: str = '',
-        vector_weight: float | None = None,
     ) -> list[dict]:
         """Proxy: Search vectors.
 
-        Returns a list of dicts with keys: 'id', 'distance', 'metadata'.
+        Returns a list of dicts with keys: 'id', 'score', 'metadata'.
         The underlying VectorDatabase.search returns Chroma-style format:
         { 'ids': [['id1']], 'distances': [[0.1]], 'metadatas': [[{}]] }
         """
@@ -112,7 +111,6 @@ class VectorDBManager:
             search_type=search_type,
             query_text=query_text,
             filter=filter,
-            vector_weight=vector_weight,
         )
 
         if not results or 'ids' not in results or not results['ids']:
@@ -132,7 +130,7 @@ class VectorDBManager:
             parsed_results.append(
                 {
                     'id': id_val,
-                    'distance': r_dists[i] if r_dists and i < len(r_dists) else 0.0,
+                    'score': r_dists[i] if r_dists and i < len(r_dists) else 0.0,
                     'metadata': r_metas[i] if r_metas and i < len(r_metas) else {},
                 }
             )
@@ -159,17 +157,3 @@ class VectorDBManager:
             Number of deleted vectors (best-effort; some backends return 0).
         """
         return await self.vector_db.delete_by_filter(collection_name, filter)
-
-    async def list_by_filter(
-        self,
-        collection_name: str,
-        filter: dict | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict], int]:
-        """Proxy: List vectors by metadata filter with pagination.
-
-        Returns:
-            Tuple of (items, total).
-        """
-        return await self.vector_db.list_by_filter(collection_name, filter, limit, offset)

src/langbot/pkg/vector/vdb.py

@@ -53,7 +53,6 @@ class VectorDatabase(abc.ABC):
         search_type: str = 'vector',
         query_text: str = '',
         filter: dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> Dict[str, Any]:
         """Search for the most similar vectors in the specified collection.
 
@@ -71,8 +70,6 @@ class VectorDatabase(abc.ABC):
                     {"file_id": "abc"}
                     {"created_at": {"$gte": 1700000000}}
                     {"file_type": {"$in": ["pdf", "docx"]}}
-            vector_weight: Weight for vector search in hybrid mode (0.0–1.0).
-                ``None`` means use equal weights (backward compatible).
         """
         pass
 
@@ -95,28 +92,6 @@ class VectorDatabase(abc.ABC):
         """
         pass
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        """List vectors matching the given metadata filter with pagination.
-
-        Args:
-            collection: Collection name.
-            filter: Optional metadata filter dict in canonical format.
-            limit: Maximum number of items to return.
-            offset: Number of items to skip.
-
-        Returns:
-            Tuple of (items, total) where items is a list of dicts with
-            keys 'id', 'document', 'metadata', and total is the best-effort
-            count of all matching vectors (-1 if unknown).
-        """
-        return [], -1
-
     @abc.abstractmethod
     async def get_or_create_collection(self, collection: str):
         """Get or create collection."""

src/langbot/pkg/vector/vdbs/chroma.py

@@ -2,14 +2,11 @@ from __future__ import annotations
 import asyncio
 from typing import Any
 from chromadb import PersistentClient
-from langbot.pkg.vector.vdb import VectorDatabase, SearchType
+from langbot.pkg.vector.vdb import VectorDatabase
 from langbot.pkg.core import app
 import chromadb
 import chromadb.errors
 
-# RRF smoothing constant (standard value from the literature)
-_RRF_K = 60
-
 
 class ChromaVectorDatabase(VectorDatabase):
     def __init__(self, ap: app.Application, base_path: str = './data/chroma'):
@@ -17,10 +14,6 @@ class ChromaVectorDatabase(VectorDatabase):
         self.client = PersistentClient(path=base_path)
         self._collections = {}
 
-    @classmethod
-    def supported_search_types(cls) -> list[SearchType]:
-        return [SearchType.VECTOR, SearchType.FULL_TEXT, SearchType.HYBRID]
-
     async def get_or_create_collection(self, collection: str) -> chromadb.Collection:
         if collection not in self._collections:
             self._collections[collection] = await asyncio.to_thread(
@@ -41,8 +34,8 @@ class ChromaVectorDatabase(VectorDatabase):
         kwargs: dict[str, Any] = dict(embeddings=embeddings_list, ids=ids, metadatas=metadatas)
         if documents is not None:
             kwargs['documents'] = documents
-        await asyncio.to_thread(col.upsert, **kwargs)
-        self.ap.logger.info(f"Upserted {len(ids)} embeddings to Chroma collection '{collection}'.")
+        await asyncio.to_thread(col.add, **kwargs)
+        self.ap.logger.info(f"Added {len(ids)} embeddings to Chroma collection '{collection}'.")
 
     async def search(
         self,
@@ -52,28 +45,8 @@ class ChromaVectorDatabase(VectorDatabase):
         search_type: str = 'vector',
         query_text: str = '',
         filter: dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> dict[str, Any]:
         col = await self.get_or_create_collection(collection)
-
-        if search_type == SearchType.FULL_TEXT:
-            return await self._full_text_search(col, collection, k, query_text, filter)
-        elif search_type == SearchType.HYBRID:
-            return await self._hybrid_search(
-                col, collection, query_embedding, k, query_text, filter, vector_weight=vector_weight
-            )
-
-        # Default: vector search
-        return await self._vector_search(col, collection, query_embedding, k, filter)
-
-    async def _vector_search(
-        self,
-        col: chromadb.Collection,
-        collection: str,
-        query_embedding: list[float],
-        k: int,
-        filter: dict[str, Any] | None,
-    ) -> dict[str, Any]:
         query_kwargs: dict[str, Any] = dict(
             query_embeddings=query_embedding,
             n_results=k,
@@ -82,154 +55,9 @@ class ChromaVectorDatabase(VectorDatabase):
         if filter:
             query_kwargs['where'] = filter
         results = await asyncio.to_thread(col.query, **query_kwargs)
-        self.ap.logger.info(
-            f"Chroma vector search in '{collection}' returned {len(results.get('ids', [[]])[0])} results."
-        )
+        self.ap.logger.info(f"Chroma search in '{collection}' returned {len(results.get('ids', [[]])[0])} results.")
         return results
 
-    async def _full_text_search(
-        self,
-        col: chromadb.Collection,
-        collection: str,
-        k: int,
-        query_text: str,
-        filter: dict[str, Any] | None,
-    ) -> dict[str, Any]:
-        if not query_text:
-            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
-
-        get_kwargs: dict[str, Any] = dict(
-            where_document={'$contains': query_text},
-            include=['metadatas', 'documents'],
-            limit=k,
-        )
-        if filter:
-            get_kwargs['where'] = filter
-        results = await asyncio.to_thread(col.get, **get_kwargs)
-
-        # col.get returns flat lists; wrap into column-major format.
-        # Distances are all 0.0 because Chroma's local $contains is a boolean
-        # filter with no relevance scoring.  Chroma's BM25 sparse embedding
-        # function (ChromaBm25EmbeddingFunction) can generate scored sparse
-        # vectors, but sparse vector *indexing* is only available on Chroma
-        # Cloud, not locally.  For ranked results, use hybrid mode or apply a
-        # reranker in a downstream stage.
-        ids = results.get('ids', [])
-        metadatas = results.get('metadatas', []) or [None] * len(ids)
-        documents = results.get('documents', []) or [None] * len(ids)
-        distances = [0.0] * len(ids)
-
-        self.ap.logger.info(f"Chroma full-text search in '{collection}' returned {len(ids)} results.")
-        return {'ids': [ids], 'metadatas': [metadatas], 'distances': [distances], 'documents': [documents]}
-
-    async def _hybrid_search(
-        self,
-        col: chromadb.Collection,
-        collection: str,
-        query_embedding: list[float],
-        k: int,
-        query_text: str,
-        filter: dict[str, Any] | None,
-        vector_weight: float | None = None,
-    ) -> dict[str, Any]:
-        # Fall back to pure vector search when no text is provided
-        if not query_text:
-            return await self._vector_search(col, collection, query_embedding, k, filter)
-
-        # Run vector search and full-text search in parallel
-        vector_task = self._vector_search(col, collection, query_embedding, k, filter)
-        text_task = self._full_text_search(col, collection, k, query_text, filter)
-        vector_results, text_results = await asyncio.gather(vector_task, text_task)
-
-        vector_ids = vector_results.get('ids', [[]])[0]
-        text_ids = text_results.get('ids', [[]])[0]
-
-        if not vector_ids and not text_ids:
-            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
-
-        # RRF fusion
-        weights = None
-        if vector_weight is not None:
-            weights = [vector_weight, 1.0 - vector_weight]
-        self.ap.logger.info(
-            f"Chroma hybrid fusion config in '{collection}': "
-            f'vector_weight={vector_weight}, weights={weights or [1.0, 1.0]}, '
-            f'vector_hits={len(vector_ids)}, text_hits={len(text_ids)}'
-        )
-        fused = self._rrf_fuse([vector_ids, text_ids], k, weights=weights)
-        if not fused:
-            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]], 'documents': [[]]}
-
-        fused_ids = [doc_id for doc_id, _ in fused]
-
-        # Fetch full metadata and documents for fused results
-        fetched = await asyncio.to_thread(col.get, ids=fused_ids, include=['metadatas', 'documents'])
-
-        # col.get returns results in arbitrary order; re-order to match fused ranking
-        fetched_map: dict[str, tuple] = {}
-        for i, fid in enumerate(fetched.get('ids', [])):
-            meta = (fetched.get('metadatas') or [None] * len(fetched['ids']))[i]
-            doc = (fetched.get('documents') or [None] * len(fetched['ids']))[i]
-            fetched_map[fid] = (meta, doc)
-
-        ordered_ids = []
-        ordered_metas = []
-        ordered_docs = []
-        ordered_dists = []
-
-        # Normalize RRF scores to 0~1 distances via min-max scaling.
-        # Raw RRF scores are tiny (e.g. 0.016~0.033 with k=60) so a naive
-        # ``1 - score`` would compress all distances into a narrow 0.96~0.98
-        # band with almost no discriminative power.  Min-max normalization
-        # spreads them across the full 0~1 range (0.0 = best match).
-        max_score = fused[0][1]
-        min_score = fused[-1][1]
-        score_range = max_score - min_score
-
-        for doc_id, score in fused:
-            if doc_id in fetched_map:
-                meta, doc = fetched_map[doc_id]
-                ordered_ids.append(doc_id)
-                ordered_metas.append(meta)
-                ordered_docs.append(doc)
-                if score_range > 0:
-                    ordered_dists.append(1.0 - (score - min_score) / score_range)
-                else:
-                    ordered_dists.append(0.0)
-
-        self.ap.logger.info(
-            f"Chroma hybrid search in '{collection}' returned {len(ordered_ids)} results "
-            f'(vector={len(vector_ids)}, text={len(text_ids)}).'
-        )
-        return {
-            'ids': [ordered_ids],
-            'metadatas': [ordered_metas],
-            'distances': [ordered_dists],
-            'documents': [ordered_docs],
-        }
-
-    @staticmethod
-    def _rrf_fuse(result_lists: list[list[str]], k: int, weights: list[float] | None = None) -> list[tuple[str, float]]:
-        """Reciprocal Rank Fusion over multiple ranked ID lists.
-
-        Returns a list of (doc_id, rrf_score) sorted by descending score,
-        truncated to *k* entries.
-
-        Args:
-            result_lists: Ranked ID lists from different search methods.
-            k: Number of results to return.
-            weights: Per-list weights.  ``None`` means equal weight (1.0 each).
-        """
-        if weights is None:
-            weights = [1.0] * len(result_lists)
-        scores: dict[str, float] = {}
-        for list_idx, ranked_ids in enumerate(result_lists):
-            w = weights[list_idx]
-            for rank, doc_id in enumerate(ranked_ids):
-                scores[doc_id] = scores.get(doc_id, 0.0) + w / (_RRF_K + rank + 1)
-        sorted_results = sorted(scores.items(), key=lambda x: x[1], reverse=True)
-        return sorted_results[:k]
-
     async def delete_by_file_id(self, collection: str, file_id: str) -> None:
         col = await self.get_or_create_collection(collection)
         await asyncio.to_thread(col.delete, where={'file_id': file_id})
@@ -241,41 +69,6 @@ class ChromaVectorDatabase(VectorDatabase):
         self.ap.logger.info(f"Deleted embeddings from Chroma collection '{collection}' by filter")
         return 0  # Chroma delete does not return a count
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        col = await self.get_or_create_collection(collection)
-        get_kwargs: dict[str, Any] = dict(
-            include=['metadatas', 'documents'],
-            limit=limit,
-            offset=offset,
-        )
-        if filter:
-            get_kwargs['where'] = filter
-        results = await asyncio.to_thread(col.get, **get_kwargs)
-
-        ids = results.get('ids', [])
-        metadatas = results.get('metadatas', []) or [None] * len(ids)
-        documents = results.get('documents', []) or [None] * len(ids)
-
-        items = []
-        for i, vid in enumerate(ids):
-            items.append(
-                {
-                    'id': vid,
-                    'document': documents[i] if i < len(documents) else None,
-                    'metadata': metadatas[i] if i < len(metadatas) else {},
-                }
-            )
-
-        # Chroma col.count() gives total in collection; filtered count not available
-        total = await asyncio.to_thread(col.count) if not filter else -1
-        return items, total
-
     async def delete_collection(self, collection: str):
         if collection in self._collections:
             del self._collections[collection]

src/langbot/pkg/vector/vdbs/milvus.py

@@ -11,14 +11,11 @@ from langbot.pkg.core import app
 # silently dropped with a warning.
 _MILVUS_SUPPORTED_FIELDS = {'text', 'file_id', 'chunk_uuid'}
 
-# Callers use canonical metadata key 'uuid' but Milvus stores it as 'chunk_uuid'.
-_MILVUS_FIELD_ALIASES = {'uuid': 'chunk_uuid'}
-
 
 def _build_milvus_expr(filter_dict: dict[str, Any]) -> str:
     """Translate canonical filter dict into a Milvus boolean expression string."""
     triples = normalize_filter(filter_dict)
-    triples = strip_unsupported_fields(triples, _MILVUS_SUPPORTED_FIELDS, _MILVUS_FIELD_ALIASES)
+    triples = strip_unsupported_fields(triples, _MILVUS_SUPPORTED_FIELDS)
     if not triples:
         return ''
 
@@ -255,7 +252,6 @@ class MilvusVectorDatabase(VectorDatabase):
         search_type: str = 'vector',
         query_text: str = '',
         filter: dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> Dict[str, Any]:
         """Search for similar vectors in Milvus collection
 
@@ -344,62 +340,6 @@ class MilvusVectorDatabase(VectorDatabase):
         self.ap.logger.info(f"Deleted embeddings from Milvus collection '{collection}' by filter")
         return 0  # Milvus delete does not return a count
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        collection = self._normalize_collection_name(collection)
-        await self.get_or_create_collection(collection)
-
-        query_kwargs: dict[str, Any] = dict(
-            collection_name=collection,
-            output_fields=['text', 'file_id', 'chunk_uuid'],
-            limit=limit,
-            offset=offset,
-        )
-        if filter:
-            expr = _build_milvus_expr(filter)
-            if expr:
-                query_kwargs['filter'] = expr
-
-        results = await asyncio.to_thread(self.client.query, **query_kwargs)
-
-        items = []
-        for row in results:
-            items.append(
-                {
-                    'id': row.get('id', ''),
-                    'document': row.get('text'),
-                    'metadata': {
-                        'text': row.get('text', ''),
-                        'file_id': row.get('file_id', ''),
-                        'uuid': row.get('chunk_uuid', ''),
-                    },
-                }
-            )
-
-        # Milvus query with count(*)
-        total = -1
-        try:
-            count_kwargs: dict[str, Any] = dict(
-                collection_name=collection,
-                output_fields=['count(*)'],
-            )
-            if filter:
-                expr = _build_milvus_expr(filter)
-                if expr:
-                    count_kwargs['filter'] = expr
-            count_result = await asyncio.to_thread(self.client.query, **count_kwargs)
-            if count_result:
-                total = count_result[0].get('count(*)', -1)
-        except Exception:
-            pass
-
-        return items, total
-
     async def delete_collection(self, collection: str):
         """Delete a Milvus collection
 

src/langbot/pkg/vector/vdbs/pgvector_db.py

@@ -13,9 +13,6 @@ Base = declarative_base()
 # pgvector schema only stores these metadata fields.
 _PG_SUPPORTED_FIELDS = {'text', 'file_id', 'chunk_uuid'}
 
-# Callers use canonical metadata key 'uuid' but pgvector stores it as 'chunk_uuid'.
-_PG_FIELD_ALIASES = {'uuid': 'chunk_uuid'}
-
 # Map schema field names to SQLAlchemy columns (resolved lazily from PgVectorEntry).
 _PG_COLUMN_MAP = {
     'text': 'text',
@@ -40,7 +37,7 @@ class PgVectorEntry(Base):
 def _build_pg_conditions(filter_dict: dict[str, Any]) -> list:
     """Translate canonical filter dict into a list of SQLAlchemy conditions."""
     triples = normalize_filter(filter_dict)
-    triples = strip_unsupported_fields(triples, _PG_SUPPORTED_FIELDS, _PG_FIELD_ALIASES)
+    triples = strip_unsupported_fields(triples, _PG_SUPPORTED_FIELDS)
 
     conditions = []
     for field, op, value in triples:
@@ -192,7 +189,6 @@ class PgVectorDatabase(VectorDatabase):
         search_type: str = 'vector',
         query_text: str = '',
         filter: dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> Dict[str, Any]:
         """Search for similar vectors using cosine distance
 
@@ -313,65 +309,6 @@ class PgVectorDatabase(VectorDatabase):
                 self.ap.logger.error(f'Error deleting from pgvector by filter: {e}')
                 raise
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        await self.get_or_create_collection(collection)
-
-        async with self.AsyncSessionLocal() as session:
-            try:
-                from sqlalchemy import select, func
-
-                stmt = (
-                    select(
-                        PgVectorEntry.id,
-                        PgVectorEntry.text,
-                        PgVectorEntry.file_id,
-                        PgVectorEntry.chunk_uuid,
-                    )
-                    .filter(PgVectorEntry.collection == collection)
-                    .offset(offset)
-                    .limit(limit)
-                )
-
-                count_stmt = (
-                    select(func.count()).select_from(PgVectorEntry).filter(PgVectorEntry.collection == collection)
-                )
-
-                if filter:
-                    for cond in _build_pg_conditions(filter):
-                        stmt = stmt.filter(cond)
-                        count_stmt = count_stmt.filter(cond)
-
-                result = await session.execute(stmt)
-                rows = result.fetchall()
-
-                count_result = await session.execute(count_stmt)
-                total = count_result.scalar() or 0
-
-                items = []
-                for row in rows:
-                    items.append(
-                        {
-                            'id': row.id,
-                            'document': row.text or '',
-                            'metadata': {
-                                'text': row.text or '',
-                                'file_id': row.file_id or '',
-                                'uuid': row.chunk_uuid or '',
-                            },
-                        }
-                    )
-
-                return items, total
-            except Exception as e:
-                self.ap.logger.error(f'Error listing from pgvector: {e}')
-                raise
-
     async def delete_collection(self, collection: str):
         """Delete all vectors in a collection
 

src/langbot/pkg/vector/vdbs/qdrant.py

@@ -100,7 +100,6 @@ class QdrantVectorDatabase(VectorDatabase):
         search_type: str = 'vector',
         query_text: str = '',
         filter: dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> dict[str, Any]:
         exists = await self.client.collection_exists(collection)
         if not exists:
@@ -151,97 +150,6 @@ class QdrantVectorDatabase(VectorDatabase):
         self.ap.logger.info(f"Deleted embeddings from Qdrant collection '{collection}' by filter")
         return 0  # Qdrant delete does not return a count
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        exists = await self.client.collection_exists(collection)
-        if not exists:
-            return [], 0
-
-        qdrant_filter = _build_qdrant_filter(filter) if filter else None
-
-        # Qdrant scroll uses cursor-based pagination (offset = point ID),
-        # not numeric skip.  To support numeric offset we scroll through
-        # `offset + limit` items and discard the first `offset`.
-        remaining_to_skip = offset
-        remaining_to_collect = limit
-        cursor: int | str | None = None
-        collected: list[dict[str, Any]] = []
-
-        while remaining_to_skip > 0 or remaining_to_collect > 0:
-            batch_size = remaining_to_skip + remaining_to_collect if remaining_to_skip > 0 else remaining_to_collect
-            scroll_kwargs: dict[str, Any] = dict(
-                collection_name=collection,
-                limit=min(batch_size, 256),
-                with_payload=True if remaining_to_skip == 0 else False,
-                with_vectors=False,
-            )
-            if qdrant_filter:
-                scroll_kwargs['scroll_filter'] = qdrant_filter
-            if cursor is not None:
-                scroll_kwargs['offset'] = cursor
-
-            points, next_cursor = await self.client.scroll(**scroll_kwargs)
-            if not points:
-                break
-
-            for point in points:
-                if remaining_to_skip > 0:
-                    remaining_to_skip -= 1
-                    continue
-                if remaining_to_collect <= 0:
-                    break
-                # Re-fetch payload if we skipped it during the skip phase
-                payload = point.payload or {}
-                collected.append(
-                    {
-                        'id': str(point.id),
-                        'document': payload.get('text') or payload.get('document'),
-                        'metadata': payload,
-                    }
-                )
-                remaining_to_collect -= 1
-
-            if next_cursor is None:
-                break
-            cursor = next_cursor
-
-        # If we skipped without payload, re-fetch the collected items' payloads
-        # (only needed when offset > 0 and items were collected in a skip batch)
-        if offset > 0 and collected:
-            refetch_ids = [item['id'] for item in collected if not item.get('metadata')]
-            if refetch_ids:
-                fetched_points = await self.client.retrieve(
-                    collection_name=collection,
-                    ids=refetch_ids,
-                    with_payload=True,
-                    with_vectors=False,
-                )
-                payload_map = {str(p.id): p.payload or {} for p in fetched_points}
-                for item in collected:
-                    if item['id'] in payload_map:
-                        payload = payload_map[item['id']]
-                        item['metadata'] = payload
-                        item['document'] = payload.get('text') or payload.get('document')
-
-        # Use count() for accurate total (supports filter)
-        total = -1
-        try:
-            count_result = await self.client.count(
-                collection_name=collection,
-                count_filter=qdrant_filter,
-                exact=True,
-            )
-            total = count_result.count
-        except Exception:
-            pass
-
-        return collected, total
-
     async def delete_collection(self, collection: str):
         try:
             await self.client.delete_collection(collection)

src/langbot/pkg/vector/vdbs/seekdb.py

@@ -1,8 +1,6 @@
 from __future__ import annotations
 
 import asyncio
-from decimal import Decimal
-import re
 from typing import Any, Dict, List
 
 
@@ -103,28 +101,8 @@ class SeekDBVectorDatabase(VectorDatabase):
             }
         )
 
-    def _normalize_collection_name(self, collection: str) -> str:
-        """SeekDB only accepts [a-zA-Z0-9_], while LangBot uses UUID-like KB IDs."""
-        normalized = re.sub(r'[^A-Za-z0-9_]', '_', collection)
-        if normalized != collection:
-            self.ap.logger.info(f"Normalized SeekDB collection name: '{collection}' -> '{normalized}'")
-        return normalized
-
-    def _json_safe(self, value: Any) -> Any:
-        """Convert SeekDB result values into JSON-serializable Python primitives."""
-        if isinstance(value, Decimal):
-            return float(value)
-        if isinstance(value, dict):
-            return {k: self._json_safe(v) for k, v in value.items()}
-        if isinstance(value, list):
-            return [self._json_safe(v) for v in value]
-        if isinstance(value, tuple):
-            return [self._json_safe(v) for v in value]
-        return value
-
     async def _get_or_create_collection_internal(self, collection: str, vector_size: int = None) -> Any:
         """Internal method to get or create a collection with proper configuration."""
-        collection = self._normalize_collection_name(collection)
         if collection in self._collections:
             return self._collections[collection]
 
@@ -195,7 +173,6 @@ class SeekDBVectorDatabase(VectorDatabase):
         if not embeddings_list:
             return
 
-        collection = self._normalize_collection_name(collection)
         # Ensure collection exists with correct dimension
         vector_size = len(embeddings_list[0])
         coll = await self._get_or_create_collection_internal(collection, vector_size)
@@ -217,7 +194,6 @@ class SeekDBVectorDatabase(VectorDatabase):
         search_type: str = 'vector',
         query_text: str = '',
         filter: Dict[str, Any] | None = None,
-        vector_weight: float | None = None,
     ) -> Dict[str, Any]:
         """Search for the most similar vectors in the specified collection.
 
@@ -234,7 +210,6 @@ class SeekDBVectorDatabase(VectorDatabase):
         Returns:
             Dictionary with 'ids', 'metadatas', 'distances' keys
         """
-        collection = self._normalize_collection_name(collection)
         # Check if collection exists
         exists = await asyncio.to_thread(self.client.has_collection, collection)
         if not exists:
@@ -296,17 +271,6 @@ class SeekDBVectorDatabase(VectorDatabase):
                     query_cfg['where'] = filter
                     knn_cfg['where'] = filter
 
-                # Apply vector_weight via pyseekdb's native boost parameter
-                if vector_weight is not None:
-                    knn_cfg['boost'] = vector_weight
-                    query_cfg['boost'] = 1.0 - vector_weight
-                self.ap.logger.info(
-                    f"SeekDB hybrid fusion config in '{collection}': "
-                    f'vector_weight={vector_weight}, '
-                    f'knn_boost={knn_cfg.get("boost", 1.0)}, '
-                    f'query_boost={query_cfg.get("boost", 1.0)}'
-                )
-
                 results = await asyncio.to_thread(
                     coll.hybrid_search,
                     query=query_cfg,
@@ -315,9 +279,6 @@ class SeekDBVectorDatabase(VectorDatabase):
                     n_results=k,
                     include=['documents', 'metadatas'],
                 )
-                self.ap.logger.info(
-                    f"SeekDB hybrid search in '{collection}' returned {len(results.get('ids', [[]])[0])} results."
-                )
         else:
             # Default: vector search via query()
             query_kwargs = {'n_results': k, 'query_embeddings': query_embedding}
@@ -325,7 +286,6 @@ class SeekDBVectorDatabase(VectorDatabase):
                 query_kwargs['where'] = filter
             results = await asyncio.to_thread(coll.query, **query_kwargs)
 
-        results = self._json_safe(results)
         self.ap.logger.info(
             f"SeekDB {search_type} search in '{collection}' returned {len(results.get('ids', [[]])[0])} results"
         )
@@ -339,7 +299,6 @@ class SeekDBVectorDatabase(VectorDatabase):
             collection: Collection name
             file_id: File ID to delete
         """
-        collection = self._normalize_collection_name(collection)
         # Check if collection exists
         exists = await asyncio.to_thread(self.client.has_collection, collection)
         if not exists:
@@ -366,7 +325,6 @@ class SeekDBVectorDatabase(VectorDatabase):
             collection: Collection name
             filter: Chroma-style ``where`` filter dict
         """
-        collection = self._normalize_collection_name(collection)
         exists = await asyncio.to_thread(self.client.has_collection, collection)
         if not exists:
             self.ap.logger.warning(f"SeekDB collection '{collection}' not found for deletion")
@@ -382,59 +340,12 @@ class SeekDBVectorDatabase(VectorDatabase):
         self.ap.logger.info(f"Deleted embeddings from SeekDB collection '{collection}' by filter")
         return 0  # SeekDB delete does not return a count
 
-    async def list_by_filter(
-        self,
-        collection: str,
-        filter: Dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[Dict[str, Any]], int]:
-        collection = self._normalize_collection_name(collection)
-        exists = await asyncio.to_thread(self.client.has_collection, collection)
-        if not exists:
-            return [], 0
-
-        if collection not in self._collections:
-            coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
-            self._collections[collection] = coll
-        else:
-            coll = self._collections[collection]
-
-        get_kwargs: Dict[str, Any] = dict(
-            include=['metadatas', 'documents'],
-            limit=limit,
-            offset=offset,
-        )
-        if filter:
-            get_kwargs['where'] = filter
-
-        results = await asyncio.to_thread(coll.get, **get_kwargs)
-
-        results = self._json_safe(results)
-        ids = results.get('ids', [])
-        metadatas = results.get('metadatas', []) or [None] * len(ids)
-        documents = results.get('documents', []) or [None] * len(ids)
-
-        items = []
-        for i, vid in enumerate(ids):
-            items.append(
-                {
-                    'id': vid,
-                    'document': documents[i] if i < len(documents) else None,
-                    'metadata': metadatas[i] if i < len(metadatas) else {},
-                }
-            )
-
-        total = await asyncio.to_thread(coll.count) if not filter else -1
-        return items, total
-
     async def delete_collection(self, collection: str):
         """Delete the entire collection.
 
         Args:
             collection: Collection name
         """
-        collection = self._normalize_collection_name(collection)
         # Remove from cache
         if collection in self._collections:
             del self._collections[collection]

src/langbot/templates/config.yaml

@@ -2,7 +2,6 @@ admins: []
 api:
     port: 5300
     webhook_prefix: 'http://127.0.0.1:5300'
-    extra_webhook_prefix: ''
 command:
     enable: true
     prefix:
@@ -16,7 +15,6 @@ proxy:
     http: ''
     https: ''
 system:
-    instance_id: ''
     edition: community
     recovery_key: ''
     allow_modify_login_info: true
@@ -78,14 +76,6 @@ plugin:
     runtime_ws_url: 'ws://langbot_plugin_runtime:5400/control/ws'
     enable_marketplace: true
     display_plugin_debug_url: 'ws://localhost:5401/plugin/debug/ws'
-monitoring:
-    auto_cleanup:
-        # Enable automatic cleanup of expired monitoring records
-        enabled: true
-        # Retention period in days, records older than this will be deleted
-        retention_days: 30
-        # Cleanup check interval in hours
-        check_interval_hours: 1
 space:
     # Space service URL for OAuth and API
     url: 'https://space.langbot.app'

src/langbot/templates/default-pipeline-config.json

@@ -41,10 +41,7 @@
             "runner": "local-agent"
         },
         "local-agent": {
-            "model": {
-                "primary": "",
-                "fallbacks": []
-            },
+            "model": "",
             "max-round": 10,
             "prompt": [
                 {
@@ -98,12 +95,11 @@
             "max": 0
         },
         "misc": {
-            "exception-handling": "show-hint",
-            "failure-hint": "Request failed.",
+            "hide-exception": true,
             "at-sender": true,
             "quote-origin": true,
             "track-function-calls": false,
             "remove-think": false
         }
     }
-}
+}

src/langbot/templates/metadata/pipeline/ai.yaml

@@ -23,30 +23,30 @@ stages:
             label:
               en_US: Local Agent
               zh_Hans: 内置 Agent
-          - name: dify-service-api
-            label:
-              en_US: Dify Service API
-              zh_Hans: Dify 服务 API
-          - name: n8n-service-api
-            label:
-              en_US: n8n Workflow API
-              zh_Hans: n8n 工作流 API
-          - name: coze-api
-            label:
-              en_US: Coze API
-              zh_Hans: 扣子 API
           - name: tbox-app-api
             label:
               en_US: Tbox App API
               zh_Hans: 蚂蚁百宝箱平台 API
+          - name: dify-service-api
+            label:
+              en_US: Dify Service API
+              zh_Hans: Dify 服务 API
           - name: dashscope-app-api
             label:
               en_US: Aliyun Dashscope App API
               zh_Hans: 阿里云百炼平台 API
+          - name: n8n-service-api
+            label:
+              en_US: n8n Workflow API
+              zh_Hans: n8n 工作流 API
           - name: langflow-api
             label:
               en_US: Langflow API
               zh_Hans: Langflow API
+          - name: coze-api
+            label:
+              en_US: Coze API
+              zh_Hans: 扣子 API
   - name: local-agent
     label:
       en_US: Local Agent
@@ -59,11 +59,8 @@ stages:
         label:
           en_US: Model
           zh_Hans: 模型
-        type: model-fallback-selector
+        type: llm-model-selector
         required: true
-        default:
-          primary: ''
-          fallbacks: []
       - name: max-round
         label:
           en_US: Max Round
@@ -74,10 +71,6 @@ stages:
         type: integer
         required: true
         default: 10
-        show_if:
-          field: __system.is_wizard
-          operator: neq
-          value: true
       - name: prompt
         label:
           en_US: Prompt
@@ -87,9 +80,6 @@ stages:
           zh_Hans: 除非您了解消息结构，否则请只使用 system 单提示词
         type: prompt-editor
         required: true
-        default:
-          - role: system
-            content: "You are a helpful assistant."
       - name: knowledge-bases
         label:
           en_US: Knowledge Bases
@@ -100,10 +90,26 @@ stages:
         type: knowledge-base-multi-selector
         required: false
         default: []
-        show_if:
-          field: __system.is_wizard
-          operator: neq
-          value: true
+  - name: tbox-app-api
+    label:
+      en_US: Tbox App API
+      zh_Hans: 蚂蚁百宝箱平台 API
+    description:
+      en_US: Configure the Tbox App API of the pipeline
+      zh_Hans: 配置蚂蚁百宝箱平台 API
+    config:
+      - name: api-key
+        label:
+          en_US: API Key
+          zh_Hans: API 密钥
+        type: string
+        required: true
+      - name: app-id
+        label:
+          en_US: App ID
+          zh_Hans: 应用 ID
+        type: string
+        required: true
   - name: dify-service-api
     label:
       en_US: Dify Service API
@@ -118,12 +124,6 @@ stages:
           zh_Hans: 基础 URL
         type: string
         required: true
-        options:
-          - name: 'https://api.dify.ai/v1'
-            label:
-              en_US: Dify Cloud
-              zh_Hans: Dify 云服务
-        default: 'https://api.dify.ai/v1'
       - name: base-prompt
         label:
           en_US: Base PROMPT
@@ -160,7 +160,52 @@ stages:
           zh_Hans: API 密钥
         type: string
         required: true
-        default: 'your-api-key'
+  - name: dashscope-app-api
+    label:
+      en_US: Aliyun Dashscope App API
+      zh_Hans: 阿里云百炼平台 API
+    description:
+      en_US: Configure the Aliyun Dashscope App API of the pipeline
+      zh_Hans: 配置阿里云百炼平台 API
+    config:
+      - name: app-type
+        label:
+          en_US: App Type
+          zh_Hans: 应用类型
+        type: select
+        required: true
+        default: agent
+        options:
+          - name: agent
+            label:
+              en_US: Agent
+              zh_Hans: Agent
+          - name: workflow
+            label:
+              en_US: Workflow
+              zh_Hans: 工作流
+      - name: api-key
+        label:
+          en_US: API Key
+          zh_Hans: API 密钥
+        type: string
+        required: true
+      - name: app-id
+        label:
+          en_US: App ID
+          zh_Hans: 应用 ID
+        type: string
+        required: true
+      - name: references_quote
+        label:
+          en_US: References Quote
+          zh_Hans: 引用文本
+        description:
+          en_US: The text prompt when the references are included
+          zh_Hans: 包含引用资料时的文本提示
+        type: string
+        required: false
+        default: '参考资料来自:'
   - name: n8n-service-api
     label:
       en_US: n8n Workflow API
@@ -178,7 +223,6 @@ stages:
           zh_Hans: n8n 工作流的 webhook URL
         type: string
         required: true
-        default: 'http://your-n8n-webhook-url'
       - name: auth-type
         label:
           en_US: Authentication Type
@@ -216,10 +260,6 @@ stages:
         type: string
         required: false
         default: ''
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'basic'
       - name: basic-password
         label:
           en_US: Password
@@ -230,10 +270,6 @@ stages:
         type: string
         required: false
         default: ''
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'basic'
       - name: jwt-secret
         label:
           en_US: Secret
@@ -244,10 +280,6 @@ stages:
         type: string
         required: false
         default: ''
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'jwt'
       - name: jwt-algorithm
         label:
           en_US: Algorithm
@@ -258,10 +290,6 @@ stages:
         type: string
         required: false
         default: 'HS256'
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'jwt'
       - name: header-name
         label:
           en_US: Header Name
@@ -272,10 +300,6 @@ stages:
         type: string
         required: false
         default: ''
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'header'
       - name: header-value
         label:
           en_US: Header Value
@@ -286,10 +310,6 @@ stages:
         type: string
         required: false
         default: ''
-        show_if:
-          field: auth-type
-          operator: eq
-          value: 'header'
       - name: timeout
         label:
           en_US: Timeout
@@ -310,140 +330,6 @@ stages:
         type: string
         required: false
         default: 'response'
-  - name: coze-api
-    label:
-      en_US: coze API
-      zh_Hans: 扣子 API
-    description:
-      en_US: Configure the Coze API of the pipeline
-      zh_Hans: 配置Coze API
-    config:
-      - name: api-key
-        label:
-          en_US: API Key
-          zh_Hans: API 密钥
-        description:
-          en_US: The API key for the Coze server
-          zh_Hans: Coze服务器的 API 密钥
-        type: string
-        required: true
-        default: ''
-      - name: bot-id
-        label:
-          en_US: Bot ID
-          zh_Hans: 机器人 ID
-        description:
-          en_US: The ID of the bot to run
-          zh_Hans: 要运行的机器人 ID
-        type: string
-        required: true
-        default: ''
-      - name: api-base
-        label:
-          en_US: API Base URL
-          zh_Hans: API 基础 URL
-        description:
-          en_US: The base URL for the Coze API, please use https://api.coze.com for global Coze edition(coze.com).
-          zh_Hans: Coze API 的基础 URL，请使用 https://api.coze.com 用于全球 Coze 版（coze.com）
-        type: string
-        options:
-          - name: 'https://api.coze.cn'
-            label:
-              en_US: Coze China
-              zh_Hans: Coze 中国版
-          - name: 'https://api.coze.com'
-            label:
-              en_US: Coze Global
-              zh_Hans: Coze 全球版
-        default: "https://api.coze.cn"
-      - name: auto-save-history
-        label:
-          en_US: Auto Save History
-          zh_Hans: 自动保存历史
-        description:
-          en_US: Whether to automatically save conversation history
-          zh_Hans: 是否自动保存对话历史
-        type: boolean
-        default: true
-      - name: timeout
-        label:
-          en_US: Request Timeout
-          zh_Hans: 请求超时
-        description:
-          en_US: Timeout in seconds for API requests
-          zh_Hans: API 请求超时时间（秒）
-        type: number
-        default: 120
-  - name: tbox-app-api
-    label:
-      en_US: Tbox App API
-      zh_Hans: 蚂蚁百宝箱平台 API
-    description:
-      en_US: Configure the Tbox App API of the pipeline
-      zh_Hans: 配置蚂蚁百宝箱平台 API
-    config:
-      - name: api-key
-        label:
-          en_US: API Key
-          zh_Hans: API 密钥
-        type: string
-        required: true
-        default: ''
-      - name: app-id
-        label:
-          en_US: App ID
-          zh_Hans: 应用 ID
-        type: string
-        required: true
-        default: ''
-  - name: dashscope-app-api
-    label:
-      en_US: Aliyun Dashscope App API
-      zh_Hans: 阿里云百炼平台 API
-    description:
-      en_US: Configure the Aliyun Dashscope App API of the pipeline
-      zh_Hans: 配置阿里云百炼平台 API
-    config:
-      - name: app-type
-        label:
-          en_US: App Type
-          zh_Hans: 应用类型
-        type: select
-        required: true
-        default: agent
-        options:
-          - name: agent
-            label:
-              en_US: Agent
-              zh_Hans: Agent
-          - name: workflow
-            label:
-              en_US: Workflow
-              zh_Hans: 工作流
-      - name: api-key
-        label:
-          en_US: API Key
-          zh_Hans: API 密钥
-        type: string
-        required: true
-        default: 'your-api-key'
-      - name: app-id
-        label:
-          en_US: App ID
-          zh_Hans: 应用 ID
-        type: string
-        required: true
-        default: 'your-app-id'
-      - name: references_quote
-        label:
-          en_US: References Quote
-          zh_Hans: 引用文本
-        description:
-          en_US: The text prompt when the references are included
-          zh_Hans: 包含引用资料时的文本提示
-        type: string
-        required: false
-        default: '参考资料来自:'
   - name: langflow-api
     label:
       en_US: Langflow API
@@ -461,7 +347,6 @@ stages:
           zh_Hans: Langflow 服务器的基础 URL
         type: string
         required: true
-        default: 'http://localhost:7860'
       - name: api-key
         label:
           en_US: API Key
@@ -471,7 +356,6 @@ stages:
           zh_Hans: Langflow 服务器的 API 密钥
         type: string
         required: true
-        default: 'your-api-key'
       - name: flow-id
         label:
           en_US: Flow ID
@@ -481,7 +365,6 @@ stages:
           zh_Hans: 要运行的流程 ID
         type: string
         required: true
-        default: 'your-flow-id'
       - name: input-type
         label:
           en_US: Input Type
@@ -511,4 +394,57 @@ stages:
           zh_Hans: 可选的流程调整参数
         type: json
         required: false
-        default: '{}'
+        default: '{}'
+  - name: coze-api
+    label:
+      en_US: coze API
+      zh_Hans: 扣子 API
+    description:
+      en_US: Configure the Coze API of the pipeline
+      zh_Hans: 配置Coze API
+    config:
+      - name: api-key
+        label:
+          en_US: API Key
+          zh_Hans: API 密钥
+        description:
+          en_US: The API key for the Coze server
+          zh_Hans: Coze服务器的 API 密钥
+        type: string
+        required: true
+      - name: bot-id
+        label:
+          en_US: Bot ID
+          zh_Hans: 机器人 ID
+        description:
+          en_US: The ID of the bot to run
+          zh_Hans: 要运行的机器人 ID
+        type: string
+        required: true
+      - name: api-base
+        label:
+          en_US: API Base URL
+          zh_Hans: API 基础 URL
+        description:
+          en_US: The base URL for the Coze API, please use https://api.coze.com for global Coze edition(coze.com).
+          zh_Hans: Coze API 的基础 URL，请使用 https://api.coze.com 用于全球 Coze 版（coze.com）
+        type: string
+        default: "https://api.coze.cn"
+      - name: auto-save-history
+        label:
+          en_US: Auto Save History
+          zh_Hans: 自动保存历史
+        description:
+          en_US: Whether to automatically save conversation history
+          zh_Hans: 是否自动保存对话历史
+        type: boolean
+        default: true
+      - name: timeout
+        label:
+          en_US: Request Timeout
+          zh_Hans: 请求超时
+        description:
+          en_US: Timeout in seconds for API requests
+          zh_Hans: API 请求超时时间（秒）
+        type: number
+        default: 120

src/langbot/templates/metadata/pipeline/output.yaml

@@ -78,39 +78,13 @@ stages:
       en_US: Misc
       zh_Hans: 杂项
     config:
-      - name: exception-handling
+      - name: hide-exception
         label:
-          en_US: Exception Handling Strategy
-          zh_Hans: 异常处理策略
-        description:
-          en_US: Controls how error messages are displayed to the user when an AI request fails
-          zh_Hans: 控制 AI 请求失败时向用户展示错误信息的方式
-        type: select
+          en_US: Hide Exception
+          zh_Hans: 不输出异常信息给用户
+        type: boolean
         required: true
-        default: show-hint
-        options:
-          - name: show-error
-            label:
-              en_US: Show Full Error
-              zh_Hans: 显示完整报错信息
-          - name: show-hint
-            label:
-              en_US: Show Failure Hint
-              zh_Hans: 仅文字提示
-          - name: hide
-            label:
-              en_US: Hide All
-              zh_Hans: 不显示任何异常信息
-      - name: failure-hint
-        label:
-          en_US: Failure Hint Text
-          zh_Hans: 失败提示文本
-        description:
-          en_US: The text to display when a request fails. Only effective when Exception Handling Strategy is set to "Show Failure Hint"
-          zh_Hans: 请求失败时显示的提示文本，仅在异常处理策略设置为"仅文字提示"时生效
-        type: string
-        required: false
-        default: 'Request failed.'
+        default: true
       - name: at-sender
         label:
           en_US: At Sender
@@ -145,4 +119,3 @@ stages:
         type: boolean
         required: true
         default: false
-

src/langbot/templates/metadata/sensitive-words.json

@@ -2,5 +2,77 @@
     "说明": "mask将替换敏感词中的每一个字，若mask_word值不为空，则将敏感词整个替换为mask_word的值",
     "mask": "*",
     "mask_word": "",
-    "words": []
+    "words": [
+        "习近平",
+        "胡锦涛",
+        "江泽民",
+        "温家宝",
+        "李克强",
+        "李长春",
+        "毛泽东",
+        "邓小平",
+        "周恩来",
+        "马克思",
+        "社会主义",
+        "共产党",
+        "共产主义",
+        "大陆官方",
+        "北京政权",
+        "中华帝国",
+        "中国政府",
+        "共狗",
+        "六四事件",
+        "天安门",
+        "六四",
+        "政治局常委",
+        "两会",
+        "共青团",
+        "学潮",
+        "八九",
+        "二十大",
+        "民进党",
+        "台独",
+        "台湾独立",
+        "台湾国",
+        "国民党",
+        "台湾民国",
+        "中华民国",
+        "pornhub",
+        "Pornhub",
+        "[Yy]ou[Pp]orn",
+        "porn",
+        "Porn",
+        "[Xx][Vv]ideos",
+        "[Rr]ed[Tt]ube",
+        "[Xx][Hh]amster",
+        "[Ss]pank[Ww]ire",
+        "[Ss]pank[Bb]ang",
+        "[Tt]ube8",
+        "[Yy]ou[Jj]izz",
+        "[Bb]razzers",
+        "[Nn]aughty[ ]?[Aa]merica",
+        "作爱",
+        "做爱",
+        "性交",
+        "性爱",
+        "自慰",
+        "阴茎",
+        "淫妇",
+        "肛交",
+        "交配",
+        "性关系",
+        "性活动",
+        "色情",
+        "色图",
+        "涩图",
+        "裸体",
+        "小穴",
+        "淫荡",
+        "性爱",
+        "翻墙",
+        "VPN",
+        "科学上网",
+        "挂梯子",
+        "GFW"
+    ]
 }

tests/unit_tests/config/test_webhook_display_prefix.py

@@ -91,15 +91,14 @@ class TestWebhookDisplayPrefix:
 
     def test_default_webhook_prefix(self):
         """Test that the default webhook display prefix is correctly set"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
+        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
 
         # Should have the default value
         assert cfg['api']['webhook_prefix'] == 'http://127.0.0.1:5300'
-        assert cfg['api']['extra_webhook_prefix'] == ''
 
     def test_webhook_prefix_env_override(self):
         """Test overriding webhook_prefix via environment variable"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
+        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
 
         # Set environment variable
         os.environ['API__WEBHOOK_PREFIX'] = 'https://example.com:8080'
@@ -113,7 +112,7 @@ class TestWebhookDisplayPrefix:
 
     def test_webhook_prefix_with_custom_domain(self):
         """Test webhook_prefix with custom domain"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
+        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
 
         # Set to a custom domain
         os.environ['API__WEBHOOK_PREFIX'] = 'https://bot.mycompany.com'
@@ -127,7 +126,7 @@ class TestWebhookDisplayPrefix:
 
     def test_webhook_prefix_with_subdirectory(self):
         """Test webhook_prefix with subdirectory path"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
+        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300'}}
 
         # Set to a URL with subdirectory
         os.environ['API__WEBHOOK_PREFIX'] = 'https://example.com/langbot'
@@ -139,37 +138,6 @@ class TestWebhookDisplayPrefix:
         # Cleanup
         del os.environ['API__WEBHOOK_PREFIX']
 
-    def test_extra_webhook_prefix_default_empty(self):
-        """Test that extra_webhook_prefix defaults to empty string"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
-
-        bot_uuid = 'test-bot-uuid'
-        webhook_prefix = cfg['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
-        extra_webhook_prefix = cfg['api'].get('extra_webhook_prefix', '')
-        webhook_url = f'/bots/{bot_uuid}'
-
-        assert f'{webhook_prefix}{webhook_url}' == 'http://127.0.0.1:5300/bots/test-bot-uuid'
-        # extra should be empty when not configured
-        assert extra_webhook_prefix == ''
-
-    def test_extra_webhook_prefix_env_override(self):
-        """Test overriding extra_webhook_prefix via environment variable"""
-        cfg = {'api': {'port': 5300, 'webhook_prefix': 'http://127.0.0.1:5300', 'extra_webhook_prefix': ''}}
-
-        os.environ['API__EXTRA_WEBHOOK_PREFIX'] = 'https://extra.example.com'
-
-        result = _apply_env_overrides_to_config(cfg)
-
-        assert result['api']['extra_webhook_prefix'] == 'https://extra.example.com'
-
-        bot_uuid = 'test-bot-uuid'
-        extra_prefix = result['api']['extra_webhook_prefix']
-        webhook_url = f'/bots/{bot_uuid}'
-        assert f'{extra_prefix}{webhook_url}' == 'https://extra.example.com/bots/test-bot-uuid'
-
-        # Cleanup
-        del os.environ['API__EXTRA_WEBHOOK_PREFIX']
-
 
 if __name__ == '__main__':
     pytest.main([__file__, '-v'])

tests/unit_tests/pipeline/conftest.py

@@ -194,7 +194,7 @@ def sample_query(sample_message_chain, sample_message_event, mock_adapter):
         pipeline_config={
             'ai': {
                 'runner': {'runner': 'local-agent'},
-                'local-agent': {'model': {'primary': 'test-model-uuid', 'fallbacks': []}, 'prompt': 'test-prompt'},
+                'local-agent': {'model': 'test-model-uuid', 'prompt': 'test-prompt'},
             },
             'output': {'misc': {'at-sender': False, 'quote-origin': False}},
             'trigger': {'misc': {'combine-quote-message': False}},
@@ -219,7 +219,7 @@ def sample_pipeline_config():
     return {
         'ai': {
             'runner': {'runner': 'local-agent'},
-            'local-agent': {'model': {'primary': 'test-model-uuid', 'fallbacks': []}, 'prompt': 'test-prompt'},
+            'local-agent': {'model': 'test-model-uuid', 'prompt': 'test-prompt'},
         },
         'output': {'misc': {'at-sender': False, 'quote-origin': False}},
         'trigger': {'misc': {'combine-quote-message': False}},

uv.lock

@@ -1112,7 +1112,7 @@ wheels = [
 
 [[package]]
 name = "flask"
-version = "3.1.3"
+version = "3.1.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "blinker" },
@@ -1122,9 +1122,9 @@ dependencies = [
     { name = "markupsafe" },
     { name = "werkzeug" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/26/00/35d85dcce6c57fdc871f3867d465d780f302a175ea360f62533f12b27e2b/flask-3.1.3.tar.gz", hash = "sha256:0ef0e52b8a9cd932855379197dd8f94047b359ca0a78695144304cb45f87c9eb", size = 759004, upload-time = "2026-02-19T05:00:57.678Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/dc/6d/cfe3c0fcc5e477df242b98bfe186a4c34357b4847e87ecaef04507332dab/flask-3.1.2.tar.gz", hash = "sha256:bf656c15c80190ed628ad08cdfd3aaa35beb087855e2f494910aa3774cc4fd87", size = 720160, upload-time = "2025-08-19T21:03:21.205Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7f/9c/34f6962f9b9e9c71f6e5ed806e0d0ff03c9d1b0b2340088a0cf4bce09b18/flask-3.1.3-py3-none-any.whl", hash = "sha256:f4bcbefc124291925f1a26446da31a5178f9483862233b23c0c96a20701f670c", size = 103424, upload-time = "2026-02-19T05:00:56.027Z" },
+    { url = "https://files.pythonhosted.org/packages/ec/f9/7f9263c5695f4bd0023734af91bedb2ff8209e8de6ead162f35d8dc762fd/flask-3.1.2-py3-none-any.whl", hash = "sha256:ca1d8112ec8a6158cc29ea4858963350011b5c846a414cdb7a954aa9e967d03c", size = 103308, upload-time = "2025-08-19T21:03:19.499Z" },
 ]
 
 [[package]]
@@ -1832,7 +1832,7 @@ wheels = [
 
 [[package]]
 name = "langbot"
-version = "4.9.5"
+version = "4.9.0"
 source = { editable = "." }
 dependencies = [
     { name = "aiocqhttp" },
@@ -1928,7 +1928,7 @@ requires-dist = [
     { name = "botocore", specifier = ">=1.42.39" },
     { name = "certifi", specifier = ">=2025.4.26" },
     { name = "chardet", specifier = ">=5.2.0" },
-    { name = "chromadb", specifier = ">=1.0.0,<2.0.0" },
+    { name = "chromadb", specifier = ">=0.4.24" },
     { name = "colorlog", specifier = "~=6.6.0" },
     { name = "cryptography", specifier = ">=44.0.3" },
     { name = "dashscope", specifier = ">=1.25.10" },
@@ -1937,7 +1937,7 @@ requires-dist = [
     { name = "ebooklib", specifier = ">=0.18" },
     { name = "gewechat-client", specifier = ">=0.1.5" },
     { name = "html2text", specifier = ">=2024.2.26" },
-    { name = "langbot-plugin", specifier = "==0.3.6" },
+    { name = "langbot-plugin", specifier = "==0.3.0" },
     { name = "langchain", specifier = ">=0.2.0" },
     { name = "langchain-text-splitters", specifier = ">=0.0.1" },
     { name = "lark-oapi", specifier = ">=1.4.15" },
@@ -1993,7 +1993,7 @@ dev = [
 
 [[package]]
 name = "langbot-plugin"
-version = "0.3.6"
+version = "0.3.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiofiles" },
@@ -2011,28 +2011,28 @@ dependencies = [
     { name = "watchdog" },
     { name = "websockets" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ff/f0/e5561bd1ebda0b9345ad6b98718b5f002bb3ca79b5ec294dc77cc10957b9/langbot_plugin-0.3.6.tar.gz", hash = "sha256:20db981e416a640f22246e54517abc2a095d8ccf5e69e06c2674fb8a443f5dbe", size = 179266, upload-time = "2026-03-30T15:58:58.523Z" }
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+version = "1.2.7"
 source = { registry = "https://pypi.org/simple" }
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     { name = "langgraph" },
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+version = "1.2.7"
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+version = "1.0.7"
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@@ -2073,9 +2073,9 @@ dependencies = [
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     { name = "xxhash" },
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 [[package]]
@@ -2093,15 +2093,15 @@ wheels = [
 
 [[package]]
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-version = "1.0.8"
+version = "1.0.7"
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     { name = "langgraph-checkpoint" },
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web/README.md

@@ -1,3 +1,3 @@
 # Debug LangBot Frontend
 
-Please refer to the [Development Guide](https://link.langbot.app/en/docs/dev-config) for more information.
+Please refer to the [Development Guide](https://docs.langbot.app/en/develop/dev-config.html) for more information.

web/package.json

@@ -25,7 +25,6 @@
     "@dnd-kit/utilities": "^3.2.2",
     "@hookform/resolvers": "^5.0.1",
     "@radix-ui/react-alert-dialog": "^1.1.15",
-    "@radix-ui/react-avatar": "^1.1.11",
     "@radix-ui/react-checkbox": "^1.3.1",
     "@radix-ui/react-collapsible": "^1.1.12",
     "@radix-ui/react-context-menu": "^2.2.15",
@@ -34,7 +33,6 @@
     "@radix-ui/react-hover-card": "^1.1.13",
     "@radix-ui/react-label": "^2.1.6",
     "@radix-ui/react-popover": "^1.1.14",
-    "@radix-ui/react-progress": "^1.1.8",
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     "@radix-ui/react-select": "^2.2.4",
     "@radix-ui/react-separator": "^1.1.8",
@@ -104,10 +102,5 @@
     "typescript": "^5.8.3",
     "typescript-eslint": "^8.31.1"
   },
-  "packageManager": "pnpm@8.9.2+sha512.b9d35fe91b2a5854dadc43034a3e7b2e675fa4b56e20e8e09ef078fa553c18f8aed44051e7b36e8b8dd435f97eb0c44c4ff3b44fc7c6fa7d21e1fac17bbe661e",
-  "pnpm": {
-    "overrides": {
-      "minimatch": "3.1.3"
-    }
-  }
-}
+  "packageManager": "pnpm@8.9.2+sha512.b9d35fe91b2a5854dadc43034a3e7b2e675fa4b56e20e8e09ef078fa553c18f8aed44051e7b36e8b8dd435f97eb0c44c4ff3b44fc7c6fa7d21e1fac17bbe661e"
+}

web/src/app/auth/space/callback/page.tsx

@@ -46,12 +46,8 @@ function SpaceOAuthCallbackContent() {
         }
         setStatus('success');
         toast.success(t('common.spaceLoginSuccess'));
-
-        // If wizard state exists, redirect back to wizard instead of home
-        const wizardState = localStorage.getItem('langbot_wizard_state');
-        const redirectTo = wizardState ? '/wizard' : '/home';
         setTimeout(() => {
-          router.push(redirectTo);
+          router.push('/home');
         }, 1000);
       } catch (err) {
         setStatus('error');