chore: bump version 4.6.4

* feat(lark): 支持机器人进群发送欢迎消息

* perf: existence check and indent

---------

Co-authored-by: donghao <donghao@patsnap.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>

README.md

@@ -1,13 +1,15 @@
 
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>使用 LangBot 快速构建、调试、部署即时通信机器人。</h3>
+
 [English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -22,12 +24,10 @@
 <a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">插件介绍</a> ｜
 <a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
 
-
 </div>
 
 </p>
 
-LangBot 是一个开源的大语言模型原生即时通信机器人开发平台，旨在提供开箱即用的 IM 机器人开发体验，具有 Agent、RAG、MCP 等多种 LLM 应用功能，适配全球主流即时通信平台，并提供丰富的 API 接口，支持自定义开发。
 
 ## 📦 开始使用
 
@@ -83,6 +83,9 @@ docker compose up -d
 
 ## ✨ 特性
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-zh-rounded.png" />
+
+
 - 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态、流式输出能力，自带 RAG（知识库）实现，并深度适配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)等 LLMOps 平台。
 - 🤖 多平台支持：目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram、KOOK、Slack、LINE 等平台。
 - 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。

README_EN.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>Quickly build, debug, and ship IM bots with LangBot.</h3>
+
 English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,7 +25,6 @@ English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語]
 
 </p>
 
-LangBot is an open-source LLM native instant messaging robot development platform, aiming to provide out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, adapting to global instant messaging platforms, and providing rich API interfaces, supporting custom development.
 
 ## 📦 Getting Started
 
@@ -79,6 +80,9 @@ Click the Star and Watch button in the upper right corner of the repository to g
 
 ## ✨ Features
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io) etc. LLMOps platforms.
 - 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
 - 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.

README_ES.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>Cree, depure y despliegue bots de mensajería instantánea rápidamente con LangBot.</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / Español / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,7 +25,6 @@
 
 </p>
 
-LangBot es una plataforma de desarrollo de robots de mensajería instantánea nativa de LLM de código abierto, con el objetivo de proporcionar una experiencia de desarrollo de robots de mensajería instantánea lista para usar, con funciones de aplicación LLM como Agent, RAG, MCP, adaptándose a plataformas de mensajería instantánea globales y proporcionando interfaces API ricas, compatible con desarrollo personalizado.
 
 ## 📦 Comenzar
 
@@ -79,6 +80,9 @@ Haga clic en los botones Star y Watch en la esquina superior derecha del reposit
 
 ## ✨ Características
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 Chat con LLM / Agent: Compatible con múltiples LLMs, adaptado para chats grupales y privados; Admite conversaciones de múltiples rondas, llamadas a herramientas, capacidades multimodales y de salida en streaming. Implementación RAG (base de conocimientos) incorporada, e integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io) etc. LLMOps platforms.
 - 🤖 Soporte Multiplataforma: Actualmente compatible con QQ, QQ Channel, WeCom, WeChat personal, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
 - 🛠️ Alta Estabilidad, Rico en Funciones: Control de acceso nativo, limitación de velocidad, filtrado de palabras sensibles, etc.; Fácil de usar, admite múltiples métodos de despliegue. Compatible con múltiples configuraciones de pipeline, diferentes bots para diferentes escenarios.

README_FR.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>Créez, déboguez et déployez rapidement des bots de messagerie instantanée avec LangBot.</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / Français / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot est une plateforme de développement de robots de messagerie instantanée native LLM open source, visant à fournir une expérience de développement de robots de messagerie instantanée prête à l'emploi, avec des fonctionnalités d'application LLM telles qu'Agent, RAG, MCP, s'adaptant aux plateformes de messagerie instantanée mondiales et fournissant des interfaces API riches, prenant en charge le développement personnalisé.
-
 ## 📦 Commencer
 
 #### Démarrage Rapide
@@ -79,6 +79,9 @@ Cliquez sur les boutons Star et Watch dans le coin supérieur droit du dépôt p
 
 ## ✨ Fonctionnalités
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 Chat avec LLM / Agent : Prend en charge plusieurs LLM, adapté aux chats de groupe et privés ; Prend en charge les conversations multi-tours, les appels d'outils, les capacités multimodales et de sortie en streaming. Implémentation RAG (base de connaissances) intégrée, et intégration profonde avec [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io) etc. LLMOps platforms.
 - 🤖 Support Multi-plateforme : Actuellement compatible avec QQ, QQ Channel, WeCom, WeChat personnel, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
 - 🛠️ Haute Stabilité, Riche en Fonctionnalités : Contrôle d'accès natif, limitation de débit, filtrage de mots sensibles, etc. ; Facile à utiliser, prend en charge plusieurs méthodes de déploiement. Prend en charge plusieurs configurations de pipeline, différents bots pour différents scénarios.

README_JP.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>LangBotでIMボットを素早く構築、デバッグ、デプロイ。</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot は、エージェント、RAG、MCP などの LLM アプリケーション機能を備えた、オープンソースの LLM ネイティブのインスタントメッセージングロボット開発プラットフォームです。世界中のインスタントメッセージングプラットフォームに適応し、豊富な API インターフェースを提供し、カスタム開発をサポートします。
-
 ## 📦 始め方
 
 #### クイックスタート
@@ -79,6 +79,9 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 ## ✨ 機能
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル、ストリーミング出力機能をサポート、RAG（知識ベース）を組み込み、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io) などの LLMOps プラットフォームと深く統合。
 - 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram、KOOK、Slack、LINE など、複数のプラットフォームをサポートしています。
 - 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。

README_KO.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>LangBot으로 IM 봇을 빠르게 구축, 디버그 및 배포하세요.</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / 한국어 / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot은 오픈 소스 LLM 네이티브 인스턴트 메시징 로봇 개발 플랫폼으로, Agent, RAG, MCP 등 다양한 LLM 애플리케이션 기능을 갖춘 즉시 사용 가능한 IM 로봇 개발 경험을 제공하며, 글로벌 인스턴트 메시징 플랫폼에 적응하고 풍부한 API 인터페이스를 제공하여 맞춤형 개발을 지원합니다.
-
 ## 📦 시작하기
 
 #### 빠른 시작
@@ -79,6 +79,9 @@ LangBot은 BTPanel에 등록되어 있습니다. BTPanel을 설치한 경우 [
 
 ## ✨ 기능
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 LLM / Agent와 채팅: 여러 LLM을 지원하며 그룹 채팅 및 개인 채팅에 적응; 멀티 라운드 대화, 도구 호출, 멀티모달, 스트리밍 출력 기능을 지원합니다. 내장된 RAG(지식 베이스) 구현 및 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io) 등의 LLMOps 플랫폼과 깊이 통합됩니다.
 - 🤖 다중 플랫폼 지원: 현재 QQ, QQ Channel, WeCom, 개인 WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE 등을 지원합니다.
 - 🛠️ 높은 안정성, 풍부한 기능: 네이티브 액세스 제어, 속도 제한, 민감한 단어 필터링 등의 메커니즘; 사용하기 쉽고 여러 배포 방법을 지원합니다. 여러 파이프라인 구성을 지원하며 다양한 시나리오에 대해 다른 봇을 사용할 수 있습니다.

README_RU.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>Быстро создавайте, отлаживайте и развертывайте IM-ботов с LangBot.</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / Русский / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot — это платформа разработки ботов для мгновенных сообщений на основе LLM с открытым исходным кодом, целью которой является предоставление готового к использованию опыта разработки ботов для IM, с функциями приложений LLM, такими как Agent, RAG, MCP, адаптацией к глобальным платформам мгновенных сообщений и предоставлением богатых API-интерфейсов, поддерживающих пользовательскую разработку.
-
 ## 📦 Начало работы
 
 #### Быстрый старт
@@ -79,6 +79,9 @@ LangBot добавлен в BTPanel. Если у вас установлен BTP
 
 ## ✨ Функции
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 Чат с LLM / Agent: Поддержка нескольких LLM, адаптация к групповым и личным чатам; Поддержка многораундовых разговоров, вызовов инструментов, мультимодальных возможностей и потоковой передачи. Встроенная реализация RAG (база знаний) и глубокая интеграция с [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io) 등의 LLMOps 플랫포트폼과 깊이 통합됩니다.
 - 🤖 Многоплатформенная поддержка: В настоящее время поддерживает QQ, QQ Channel, WeCom, личный WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE и т.д.
 - 🛠️ Высокая стабильность, богатство функций: Нативный контроль доступа, ограничение скорости, фильтрация чувствительных слов и т.д.; Простота в использовании, поддержка нескольких методов развертывания. Поддержка нескольких конфигураций конвейера, разные боты для разных сценариев.

README_TW.md

@@ -1,10 +1,12 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center"><a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>使用 LangBot 快速建構、除錯和部署 IM 機器人。</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot 是一個開源的大語言模型原生即時通訊機器人開發平台，旨在提供開箱即用的 IM 機器人開發體驗，具有 Agent、RAG、MCP 等多種 LLM 應用功能，適配全球主流即時通訊平台，並提供豐富的 API 介面，支援自定義開發。
-
 ## 📦 開始使用
 
 #### 快速部署
@@ -79,6 +79,9 @@ docker compose up -d
 
 ## ✨ 特性
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 大模型對話、Agent：支援多種大模型，適配群聊和私聊；具有多輪對話、工具調用、多模態、流式輸出能力，自帶 RAG（知識庫）實現，並深度適配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io) 等 LLMOps 平台。
 - 🤖 多平台支援：目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram、KOOK、Slack、LINE 等平台。
 - 🛠️ 高穩定性、功能完備：原生支援訪問控制、限速、敏感詞過濾等機制；配置簡單，支援多種部署方式。支援多流水線配置，不同機器人用於不同應用場景。

README_VI.md

@@ -1,12 +1,14 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
+<h3>Xây dựng, gỡ lỗi và triển khai bot IM nhanh chóng với LangBot.</h3>
+
 [English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / Tiếng Việt
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
@@ -23,8 +25,6 @@
 
 </p>
 
-LangBot là một nền tảng phát triển robot nhắn tin tức thời gốc LLM mã nguồn mở, nhằm mục đích cung cấp trải nghiệm phát triển robot IM sẵn sàng sử dụng, với các chức năng ứng dụng LLM như Agent, RAG, MCP, thích ứng với các nền tảng nhắn tin tức thời toàn cầu và cung cấp giao diện API phong phú, hỗ trợ phát triển tùy chỉnh.
-
 ## 📦 Bắt đầu
 
 #### Khởi động Nhanh
@@ -79,6 +79,9 @@ Nhấp vào các nút Star và Watch ở góc trên bên phải của kho lưu t
 
 ## ✨ Tính năng
 
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
 - 💬 Chat với LLM / Agent: Hỗ trợ nhiều LLM, thích ứng với chat nhóm và chat riêng tư; Hỗ trợ các cuộc trò chuyện nhiều vòng, gọi công cụ, khả năng đa phương thức và đầu ra streaming. Triển khai RAG (cơ sở kiến thức) tích hợp sẵn và tích hợp sâu với [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io) v.v. LLMOps platforms.
 - 🤖 Hỗ trợ Đa nền tảng: Hiện hỗ trợ QQ, QQ Channel, WeCom, WeChat cá nhân, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, v.v.
 - 🛠️ Độ ổn định Cao, Tính năng Phong phú: Kiểm soát truy cập gốc, giới hạn tốc độ, lọc từ nhạy cảm, v.v.; Dễ sử dụng, hỗ trợ nhiều phương pháp triển khai. Hỗ trợ nhiều cấu hình pipeline, các bot khác nhau cho các kịch bản khác nhau.

docker/docker-compose.yaml

@@ -25,7 +25,6 @@ services:
     platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data:/app/data
-      - ./plugins:/app/plugins
     restart: on-failure
     environment:
       - TZ=Asia/Shanghai

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "langbot"
-version = "4.6.2"
+version = "4.6.4"
 description = "Easy-to-use global IM bot platform designed for LLM era"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -63,11 +63,13 @@ dependencies = [
     "langchain-text-splitters>=0.0.1",
     "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
-    "langbot-plugin==0.2.0",
+    "langbot-plugin==0.2.3",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
     "boto3>=1.35.0",
+    "pymilvus>=2.6.4",
+    "pgvector>=0.4.1",
 ]
 keywords = [
     "bot",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
 """LangBot - Easy-to-use global IM bot platform designed for LLM era"""
 
-__version__ = '4.6.2'
+__version__ = '4.6.4'

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -394,7 +394,6 @@ class WecomBotClient:
         """
         try:
             self.wxcpt = WXBizMsgCrypt(self.Token, self.EnCodingAESKey, '')
-            await self.logger.info(f'{req.method} {req.url} {str(req.args)}')
 
             if req.method == 'GET':
                 return await self._handle_get_callback(req)
@@ -458,32 +457,174 @@ class WecomBotClient:
     async def get_message(self, msg_json):
         message_data = {}
 
+        msg_type = msg_json.get('msgtype', '')
+        if msg_type:
+            message_data['msgtype'] = msg_type
+
         if msg_json.get('chattype', '') == 'single':
             message_data['type'] = 'single'
         elif msg_json.get('chattype', '') == 'group':
             message_data['type'] = 'group'
 
-        if msg_json.get('msgtype') == 'text':
+        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_json.get('msgtype') == 'image':
+        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 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
+            base64_data = await _safe_download(picurl)
-            message_data['picurl'] = base64
+            if base64_data:
-        elif msg_json.get('msgtype') == 'mixed':
+                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 = []
-            picurl = None
+            images = []
+            files = []
+            voices = []
+            videos = []
+            links = []
             for item in items:
-                if item.get('msgtype') == 'text':
+                item_type = item.get('msgtype')
+                if item_type == 'text':
                     texts.append(item.get('text', {}).get('content', ''))
-                elif item.get('msgtype') == 'image' and picurl is None:
+                elif item_type == 'image':
-                    picurl = item.get('image', {}).get('url')
+                    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
+                message_data['content'] = ' '.join(texts)  # 拼接所有 text
-            if picurl:
+            if images:
-                base64 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
+                message_data['images'] = images
-                message_data['picurl'] = base64  # 只保留第一个 image
+                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', {})

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

@@ -17,6 +17,13 @@ class WecomBotEvent(dict):
         """
         return self.get('type', '')
 
+    @property
+    def msgtype(self) -> str:
+        """
+        消息 msgtype
+        """
+        return self.get('msgtype', '')
+
     @property
     def userid(self) -> str:
         """
@@ -52,6 +59,55 @@ class WecomBotEvent(dict):
         """
         return self.get('picurl', '')
 
+    @property
+    def images(self):
+        """
+        图片列表（兼容 mixed）
+        """
+        return self.get('images', [])
+
+    @property
+    def file(self):
+        """
+        文件信息
+        """
+        return self.get('file', {})
+
+    @property
+    def voice(self):
+        """
+        语音信息
+        """
+        return self.get('voice', {})
+
+    @property
+    def video(self):
+        """
+        视频信息
+        """
+        return self.get('video', {})
+
+    @property
+    def link(self):
+        """
+        链接消息信息
+        """
+        return self.get('link', {})
+
+    @property
+    def location(self):
+        """
+        位置信息
+        """
+        return self.get('location', {})
+
+    @property
+    def attachments(self):
+        """
+        原始 mixed 中的附件项
+        """
+        return self.get('attachments', [])
+
     @property
     def chatid(self) -> str:
         """

src/langbot/libs/wecom_api/api.py

@@ -139,6 +139,58 @@ class WecomClient:
                 await self.logger.error(f'发送图片失败:{data}')
                 raise Exception('Failed to send image: ' + str(data))
 
+    async def send_voice(self, user_id: str, agent_id: int, media_id: str):
+        if not await self.check_access_token():
+            self.access_token = await self.get_access_token(self.secret)
+        url = self.base_url + '/message/send?access_token=' + self.access_token
+        async with httpx.AsyncClient() as client:
+            params = {
+                'touser': user_id,
+                'msgtype': 'voice',
+                'agentid': agent_id,
+                'voice': {
+                    'media_id': media_id,
+                },
+                'safe': 0,
+                'enable_id_trans': 0,
+                'enable_duplicate_check': 0,
+                'duplicate_check_interval': 1800,
+            }
+            response = await client.post(url, json=params)
+            data = response.json()
+            if data['errcode'] == 40014 or data['errcode'] == 42001:
+                self.access_token = await self.get_access_token(self.secret)
+                return await self.send_voice(user_id, agent_id, media_id)
+            if data['errcode'] != 0:
+                await self.logger.error(f'发送语音失败:{data}')
+                raise Exception('Failed to send voice: ' + str(data))
+
+    async def send_file(self, user_id: str, agent_id: int, media_id: str):
+        if not await self.check_access_token():
+            self.access_token = await self.get_access_token(self.secret)
+        url = self.base_url + '/message/send?access_token=' + self.access_token
+        async with httpx.AsyncClient() as client:
+            params = {
+                'touser': user_id,
+                'msgtype': 'file',
+                'agentid': agent_id,
+                'file': {
+                    'media_id': media_id,
+                },
+                'safe': 0,
+                'enable_id_trans': 0,
+                'enable_duplicate_check': 0,
+                'duplicate_check_interval': 1800,
+            }
+            response = await client.post(url, json=params)
+            data = response.json()
+            if data['errcode'] == 40014 or data['errcode'] == 42001:
+                self.access_token = await self.get_access_token(self.secret)
+                return await self.send_file(user_id, agent_id, media_id)
+            if data['errcode'] != 0:
+                await self.logger.error(f'发送文件失败:{data}')
+                raise Exception('Failed to send file: ' + str(data))
+
     async def send_private_msg(self, user_id: str, agent_id: int, content: str):
         if not await self.check_access_token():
             self.access_token = await self.get_access_token(self.secret)
@@ -287,7 +339,7 @@ class WecomClient:
                 return ext
         return 'jpg'  # 默认返回jpg
 
-    async def upload_to_work(self, image: platform_message.Image):
+    async def upload_image_to_work(self, image: platform_message.Image):
         """
         获取 media_id
         """
@@ -304,7 +356,7 @@ class WecomClient:
                 file_bytes = await f.read()
                 file_name = image.path.split('/')[-1]
         elif image.url:
-            file_bytes = await self.download_image_to_bytes(image.url)
+            file_bytes = await self.download_media_to_bytes(image.url)
             file_name = image.url.split('/')[-1]
         elif image.base64:
             try:
@@ -339,7 +391,7 @@ class WecomClient:
             data = response.json()
             if data['errcode'] == 40014 or data['errcode'] == 42001:
                 self.access_token = await self.get_access_token(self.secret)
-                media_id = await self.upload_to_work(image)
+                media_id = await self.upload_image_to_work(image)
             if data.get('errcode', 0) != 0:
                 await self.logger.error(f'上传图片失败:{data}')
                 raise Exception('failed to upload file')
@@ -347,13 +399,128 @@ class WecomClient:
             media_id = data.get('media_id')
             return media_id
 
-    async def download_image_to_bytes(self, url: str) -> bytes:
+    async def upload_voice_to_work(self, voice: platform_message.Voice):
+        """
+        上传语音文件到企业微信
+        """
+        if not await self.check_access_token():
+            self.access_token = await self.get_access_token(self.secret)
+        url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
+        file_bytes = None
+        file_name = 'voice.mp3'
+
+        if voice.path:
+            async with aiofiles.open(voice.path, 'rb') as f:
+                file_bytes = await f.read()
+                file_name = voice.path.split('/')[-1]
+        elif voice.url:
+            file_bytes = await self.download_media_to_bytes(voice.url)
+            file_name = voice.url.split('/')[-1]
+        elif voice.base64:
+            try:
+                base64_data = voice.base64
+                if ',' in base64_data:
+                    base64_data = base64_data.split(',', 1)[1]
+                padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
+                padded_base64 = base64_data + '=' * padding
+                file_bytes = base64.b64decode(padded_base64)
+            except binascii.Error as e:
+                raise ValueError(f'Invalid base64 string: {str(e)}')
+        else:
+            await self.logger.error('Voice对象出错')
+            raise ValueError('voice对象出错')
+
+        boundary = '-------------------------acebdf13572468'
+        headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
+        body = (
+            (
+                f'--{boundary}\r\n'
+                f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
+                f'Content-Type: application/octet-stream\r\n\r\n'
+            ).encode('utf-8')
+            + file_bytes
+            + f'\r\n--{boundary}--\r\n'.encode('utf-8')
+        )
+
+        # print(body)
+        async with httpx.AsyncClient() as client:
+            response = await client.post(url, headers=headers, content=body)
+            data = response.json()
+            if data['errcode'] == 40014 or data['errcode'] == 42001:
+                self.access_token = await self.get_access_token(self.secret)
+                media_id = await self.upload_voice_to_work(voice)
+            if data.get('errcode', 0) != 0:
+                await self.logger.error(f'上传语音文件失败:{data}')
+                raise Exception('failed to upload file')
+            media_id = data.get('media_id')
+            return media_id
+
+    async def upload_file_to_work(self, file: platform_message.File):
+        """
+        上传文件到企业微信
+        """
+        if not await self.check_access_token():
+            self.access_token = await self.get_access_token(self.secret)
+        url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
+        file_bytes = None
+        file_name = 'file.txt'
+        if file.path:
+            async with aiofiles.open(file.path, 'rb') as f:
+                file_bytes = await f.read()
+                file_name = file.path.split('/')[-1]
+        elif file.url:
+            file_bytes = await self.download_media_to_bytes(file.url)
+            file_name = file.url.split('/')[-1]
+        elif file.base64:
+            try:
+                base64_data = file.base64
+                if ',' in base64_data:
+                    base64_data = base64_data.split(',', 1)[1]
+                padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
+                padded_base64 = base64_data + '=' * padding
+                file_bytes = base64.b64decode(padded_base64)
+            except binascii.Error as e:
+                raise ValueError(f'Invalid base64 string: {str(e)}')
+        else:
+            await self.logger.error('File对象出错')
+            raise ValueError('file对象出错')
+        boundary = '-------------------------acebdf13572468'
+        headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
+        body = (
+            (
+                f'--{boundary}\r\n'
+                f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
+                f'Content-Type: application/octet-stream\r\n\r\n'
+            ).encode('utf-8')
+            + file_bytes
+            + f'\r\n--{boundary}--\r\n'.encode('utf-8')
+        )
+        async with httpx.AsyncClient() as client:
+            response = await client.post(url, headers=headers, content=body)
+            data = response.json()
+            if data['errcode'] == 40014 or data['errcode'] == 42001:
+                self.access_token = await self.get_access_token(self.secret)
+                media_id = await self.upload_file_to_work(file)
+            if data.get('errcode', 0) != 0:
+                await self.logger.error(f'上传文件失败:{data}')
+                raise Exception('failed to upload file')
+            media_id = data.get('media_id')
+            return media_id
+
+    async def download_media_to_bytes(self, url: str) -> bytes:
         async with httpx.AsyncClient() as client:
             response = await client.get(url)
             response.raise_for_status()
             return response.content
 
     # 进行media_id的获取
-    async def get_media_id(self, image: platform_message.Image):
+    async def get_media_id(self, media: platform_message.Image | platform_message.Voice | platform_message.File):
-        media_id = await self.upload_to_work(image=image)
+        if isinstance(media, platform_message.Image):
+            media_id = await self.upload_image_to_work(image=media)
+        elif isinstance(media, platform_message.Voice):
+            media_id = await self.upload_voice_to_work(voice=media)
+        elif isinstance(media, platform_message.File):
+            media_id = await self.upload_file_to_work(file=media)
+        else:
+            raise ValueError('Unsupported media type')
         return media_id

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

@@ -92,7 +92,11 @@ class HTTPController:
 
         @self.quart_app.route('/')
         async def index():
-            return await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
+            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
 
         @self.quart_app.route('/<path:path>')
         async def static_file(path: str):

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

@@ -59,7 +59,7 @@ class BotService:
             adapter_runtime_values['bot_account_id'] = runtime_bot.adapter.bot_account_id
 
         # Webhook URL for unified webhook adapters (independent of bot running state)
-        if persistence_bot['adapter'] in ['wecom', 'wecombot', 'officialaccount', 'qqofficial', 'slack', 'wecomcs', 'LINE']:
+        if persistence_bot['adapter'] in ['wecom', 'wecombot', 'officialaccount', 'qqofficial', 'slack', 'wecomcs', 'LINE', 'lark']:
             webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
             webhook_url = f'/bots/{bot_uuid}'
             adapter_runtime_values['webhook_url'] = webhook_url

src/langbot/pkg/persistence/migrations/dbm002_combine_quote_msg_config.py

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

src/langbot/pkg/persistence/migrations/dbm003_n8n_config.py

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

src/langbot/pkg/persistence/migrations/dbm004_rag_kb_uuid.py

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

src/langbot/pkg/persistence/migrations/dbm005_pipeline_remove_cot_config.py

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

src/langbot/pkg/persistence/migrations/dbm006_langflow_api_config.py

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

src/langbot/pkg/persistence/migrations/dbm010_pipeline_multi_knowledge_base.py

@@ -1,8 +1,7 @@
 from .. import migration
 
 import sqlalchemy
-
+import json
-from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(10)
@@ -11,16 +10,20 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # read all pipelines
+        # Read all pipelines using raw SQL
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
+        )
+        pipelines = result.fetchall()
 
-        for pipeline in pipelines:
+        current_version = self.ap.ver_mgr.get_current_version()
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-            config = serialized_pipeline['config']
+        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]
 
             # Convert knowledge-base from string to array
-            if 'local-agent' in config['ai']:
+            if 'ai' in config and 'local-agent' in config['ai']:
                 current_kb = config['ai']['local-agent'].get('knowledge-base', '')
 
                 # If it's already a list, skip
@@ -37,29 +40,38 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
                 if 'knowledge-base' in config['ai']['local-agent']:
                     del config['ai']['local-agent']['knowledge-base']
 
-            await self.ap.persistence_mgr.execute_async(
+                # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                if self.ap.persistence_mgr.db.name == 'postgresql':
-                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                    await self.ap.persistence_mgr.execute_async(
-                .values(
+                        sqlalchemy.text(
-                    {
+                            'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                        'config': config,
+                        ),
-                        'for_version': self.ap.ver_mgr.get_current_version(),
+                        {'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"""
-        # read all pipelines
+        # Read all pipelines using raw SQL
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
+        )
+        pipelines = result.fetchall()
 
-        for pipeline in pipelines:
+        current_version = self.ap.ver_mgr.get_current_version()
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-            config = serialized_pipeline['config']
+        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]
 
             # Convert knowledge-bases from array back to string
-            if 'local-agent' in config['ai']:
+            if 'ai' in config and 'local-agent' in config['ai']:
                 current_kbs = config['ai']['local-agent'].get('knowledge-bases', [])
 
                 # If it's already a string, skip
@@ -76,13 +88,18 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
                 if 'knowledge-bases' in config['ai']['local-agent']:
                     del config['ai']['local-agent']['knowledge-bases']
 
-            await self.ap.persistence_mgr.execute_async(
+                # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                if self.ap.persistence_mgr.db.name == 'postgresql':
-                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                    await self.ap.persistence_mgr.execute_async(
-                .values(
+                        sqlalchemy.text(
-                    {
+                            'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                        'config': config,
+                        ),
-                        'for_version': self.ap.ver_mgr.get_current_version(),
+                        {'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/dbm011_dify_base_prompt_config.py

@@ -1,8 +1,7 @@
 from .. import migration
 
 import sqlalchemy
-
+import json
-from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(11)
@@ -11,29 +10,45 @@ class DBMigrateDifyApiConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # read all pipelines
+        # Read all pipelines using raw SQL
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
+        )
+        pipelines = result.fetchall()
 
-        for pipeline in pipelines:
+        current_version = self.ap.ver_mgr.get_current_version()
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-            config = serialized_pipeline['config']
+        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]
 
+            # Ensure nested structure exists
+            if 'ai' not in config:
+                config['ai'] = {}
+            if 'dify-service-api' not in config['ai']:
+                config['ai']['dify-service-api'] = {}
+
+            # Add 'base-prompt' if not exists
             if 'base-prompt' not in config['ai']['dify-service-api']:
                 config['ai']['dify-service-api']['base-prompt'] = (
                     'When the file content is readable, please read the content of this file. When the file is an image, describe the content of this image.',
                 )
 
-            await self.ap.persistence_mgr.execute_async(
+            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+            if self.ap.persistence_mgr.db.name == 'postgresql':
-                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                await self.ap.persistence_mgr.execute_async(
-                .values(
+                    sqlalchemy.text(
-                    {
+                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                        'config': config,
+                    ),
-                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    {'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"""

src/langbot/pkg/persistence/migrations/dbm012_pipeline_extensions_enable_all.py

@@ -1,8 +1,7 @@
 from .. import migration
 
 import sqlalchemy
-
+import json
-from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(12)
@@ -11,14 +10,25 @@ class DBMigratePipelineExtensionsEnableAll(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # read all pipelines
+        # Read all pipelines using raw SQL
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.text('SELECT uuid, extensions_preferences FROM legacy_pipelines')
+        )
+        pipelines = result.fetchall()
 
-        for pipeline in pipelines:
+        current_version = self.ap.ver_mgr.get_current_version()
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-            extensions_preferences = serialized_pipeline['extensions_preferences']
+        for pipeline_row in pipelines:
+            uuid = pipeline_row[0]
+            extensions_preferences = (
+                json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            )
 
+            # Ensure extensions_preferences is a dict
+            if extensions_preferences is None:
+                extensions_preferences = {}
+
+            # Add 'enable_all_plugins' if not exists
             if 'enable_all_plugins' not in extensions_preferences:
                 if 'plugins' in extensions_preferences:
                     extensions_preferences['enable_all_plugins'] = False
@@ -26,6 +36,7 @@ class DBMigratePipelineExtensionsEnableAll(migration.DBMigration):
                     extensions_preferences['enable_all_plugins'] = True
                     extensions_preferences['plugins'] = []
 
+            # Add 'enable_all_mcp_servers' if not exists
             if 'enable_all_mcp_servers' not in extensions_preferences:
                 if 'mcp_servers' in extensions_preferences:
                     extensions_preferences['enable_all_mcp_servers'] = False
@@ -33,14 +44,29 @@ class DBMigratePipelineExtensionsEnableAll(migration.DBMigration):
                     extensions_preferences['enable_all_mcp_servers'] = True
                     extensions_preferences['mcp_servers'] = []
 
-            await self.ap.persistence_mgr.execute_async(
+            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+            if self.ap.persistence_mgr.db.name == 'postgresql':
-                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                await self.ap.persistence_mgr.execute_async(
-                .values(
+                    sqlalchemy.text(
-                    extensions_preferences=extensions_preferences,
+                        'UPDATE legacy_pipelines SET extensions_preferences = :extensions_preferences::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    for_version=self.ap.ver_mgr.get_current_version(),
+                    ),
+                    {
+                        'extensions_preferences': json.dumps(extensions_preferences),
+                        'for_version': current_version,
+                        'uuid': uuid,
+                    },
+                )
+            else:
+                await self.ap.persistence_mgr.execute_async(
+                    sqlalchemy.text(
+                        'UPDATE legacy_pipelines SET extensions_preferences = :extensions_preferences, for_version = :for_version WHERE uuid = :uuid'
+                    ),
+                    {
+                        'extensions_preferences': json.dumps(extensions_preferences),
+                        'for_version': current_version,
+                        'uuid': uuid,
+                    },
                 )
-            )
 
     async def downgrade(self):
         """Downgrade"""

src/langbot/pkg/pipeline/pipelinemgr.py

@@ -237,6 +237,7 @@ class RuntimePipeline:
                 launcher_type=query.launcher_type.value,
                 launcher_id=query.launcher_id,
                 sender_id=query.sender_id,
+                message_event=query.message_event,
                 message_chain=query.message_chain,
             )
 

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

@@ -7,6 +7,7 @@ from langbot_plugin.api.entities.builtin.provider import message as provider_mes
 import langbot_plugin.api.entities.events as events
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
+import langbot_plugin.api.entities.builtin.platform.events as platform_events
 
 
 @stage.stage_class('PreProcessor')
@@ -74,12 +75,26 @@ class PreProcessor(stage.PipelineStage):
                 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):
+            sender_name = query.message_event.sender.member_name
+        elif isinstance(query.message_event, platform_events.FriendMessage):
+            sender_name = query.message_event.sender.nickname
+
         variables = {
+            'launcher_type': query.session.launcher_type.value,
+            'launcher_id': query.session.launcher_id,
+            'sender_id': query.sender_id,
             'session_id': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
             'conversation_id': conversation.uuid,
             'msg_create_time': (
                 int(query.message_event.time) if query.message_event.time else int(datetime.datetime.now().timestamp())
             ),
+            'group_name': query.message_event.group.name
+            if isinstance(query.message_event, platform_events.GroupMessage)
+            else '',
+            'sender_name': sender_name,
         }
         query.variables.update(variables)
 
@@ -111,6 +126,12 @@ class PreProcessor(stage.PipelineStage):
                 ):
                     if me.base64 is not None:
                         content_list.append(provider_message.ContentElement.from_image_base64(me.base64))
+            elif isinstance(me, platform_message.Voice):
+                # 转成文件链接，让下游 runner 上传到目标模型
+                if me.base64:
+                    content_list.append(provider_message.ContentElement.from_file_base64(me.base64, 'voice.silk'))
+                elif me.url:
+                    content_list.append(provider_message.ContentElement.from_file_url(me.url, 'voice'))
             elif isinstance(me, platform_message.File):
                 # if me.url is not None:
                 content_list.append(provider_message.ContentElement.from_file_url(me.url, me.name))

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

@@ -40,6 +40,7 @@ class ChatMessageHandler(handler.MessageHandler):
             launcher_id=query.launcher_id,
             sender_id=query.sender_id,
             text_message=str(query.message_chain),
+            message_event=query.message_event,
             message_chain=query.message_chain,
             query=query,
         )
@@ -75,7 +76,7 @@ class ChatMessageHandler(handler.MessageHandler):
                         runner = r(self.ap, query.pipeline_config)
                         break
                 else:
-                    raise ValueError(f'未找到请求运行器: {query.pipeline_config["ai"]["runner"]["runner"]}')
+                    raise ValueError(f'Request Runner not found: {query.pipeline_config["ai"]["runner"]["runner"]}')
                 if is_stream:
                     resp_message_id = uuid.uuid4()
 
@@ -90,7 +91,9 @@ class ChatMessageHandler(handler.MessageHandler):
                             await query.adapter.create_message_card(str(resp_message_id), query.message_event)
                             is_create_card = True
                         query.resp_messages.append(result)
-                        self.ap.logger.info(f'对话({query.query_id})流式响应: {self.cut_str(result.readable_str())}')
+                        self.ap.logger.info(
+                            f'Conversation({query.query_id}) Streaming Response: {self.cut_str(result.readable_str())}'
+                        )
 
                         if result.content is not None:
                             text_length += len(result.content)
@@ -101,7 +104,9 @@ class ChatMessageHandler(handler.MessageHandler):
                     async for result in runner.run(query):
                         query.resp_messages.append(result)
 
-                        self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
+                        self.ap.logger.info(
+                            f'Conversation({query.query_id}) Response: {self.cut_str(result.readable_str())}'
+                        )
 
                         if result.content is not None:
                             text_length += len(result.content)
@@ -112,7 +117,7 @@ class ChatMessageHandler(handler.MessageHandler):
 
                 query.session.using_conversation.messages.extend(query.resp_messages)
             except Exception as e:
-                self.ap.logger.error(f'对话({query.query_id})请求失败: {type(e).__name__} {str(e)}')
+                self.ap.logger.error(f'Conversation({query.query_id}) Request Failed: {type(e).__name__} {str(e)}')
                 traceback.print_exc()
 
                 hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']

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

@@ -327,9 +327,6 @@ class AiocqhttpEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title=event.sender['title'] if 'title' in event.sender else '',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=yiri_chain,
                 time=event.time,

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

@@ -119,9 +119,6 @@ class DingTalkEventConverter(abstract_platform_adapter.AbstractEventConverter):
                     permission=platform_entities.Permission.Member,
                 ),
                 special_title='',
-                join_timestamp=0,
-                last_speak_timestamp=0,
-                mute_time_remaining=0,
             )
             time = event.incoming_message.create_at
             return platform_events.GroupMessage(

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

@@ -8,6 +8,9 @@ import base64
 import uuid
 import os
 import datetime
+
+# 使用BytesIO创建文件对象，避免路径问题
+import io
 import asyncio
 from enum import Enum
 
@@ -594,7 +597,7 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
                 break
 
         text_string = ''
-        image_files = []
+        files = []
 
         for ele in message_chain:
             if isinstance(ele, platform_message.Image):
@@ -668,22 +671,67 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
                         continue  # 跳过读取失败的文件
 
                 if image_bytes:
-                    # 使用BytesIO创建文件对象，避免路径问题
+                    files.append(discord.File(fp=io.BytesIO(image_bytes), filename=filename))
-                    import io
-
-                    image_files.append(discord.File(fp=io.BytesIO(image_bytes), filename=filename))
             elif isinstance(ele, platform_message.Plain):
                 text_string += ele.text
+            elif isinstance(ele, platform_message.Voice):
+                file_bytes = None
+                filename = f'{uuid.uuid4()}.mp3'
+                if ele.base64:
+                    if ele.base64.startswith('data:'):
+                        data_header = ele.base64.split(',')[0]
+                        if 'wav' in data_header:
+                            filename = f'{uuid.uuid4()}.wav'
+                        elif 'mp3' in data_header:
+                            filename = f'{uuid.uuid4()}.mp3'
+                        elif 'ogg' in data_header:
+                            filename = f'{uuid.uuid4()}.ogg'
+                        elif 'm4a' in data_header:
+                            filename = f'{uuid.uuid4()}.m4a'
+                        elif 'aac' in data_header:
+                            filename = f'{uuid.uuid4()}.aac'
+                        elif 'flac' in data_header:
+                            filename = f'{uuid.uuid4()}.flac'
+                        elif 'alac' in data_header:
+                            filename = f'{uuid.uuid4()}.alac'
+                        elif 'opus' in data_header:
+                            filename = f'{uuid.uuid4()}.opus'
+                        elif 'webm' in data_header:
+                            filename = f'{uuid.uuid4()}.webm'
+
+                    file_base64 = ele.base64.split(',')[-1]
+                    file_bytes = base64.b64decode(file_base64)
+                elif ele.url:
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(ele.url) as response:
+                            file_bytes = await response.read()
+                if file_bytes:
+                    files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
+            elif isinstance(ele, platform_message.File):
+                file_bytes = None
+                filename = f'{uuid.uuid4()}.{ele.name.split(".")[-1]}'
+                if ele.base64:
+                    if ele.base64.startswith('data:'):
+                        file_base64 = ele.base64.split(',')[1]
+                        file_bytes = base64.b64decode(file_base64)
+                    else:
+                        file_bytes = base64.b64decode(ele.base64)
+                elif ele.url:
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(ele.url) as response:
+                            file_bytes = await response.read()
+                if file_bytes:
+                    files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
             elif isinstance(ele, platform_message.Forward):
                 for node in ele.node_list:
                     (
                         node_text,
-                        node_images,
+                        node_files,
                     ) = await DiscordMessageConverter.yiri2target(node.message_chain)
                     text_string += node_text
-                    image_files.extend(node_images)
+                    files.extend(node_files)
 
-        return text_string, image_files
+        return text_string, files
 
     @staticmethod
     async def target2yiri(message: discord.Message) -> platform_message.MessageChain:
@@ -769,9 +817,6 @@ class DiscordEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event.created_at.timestamp(),
@@ -993,7 +1038,7 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             await self.voice_manager.cleanup_inactive_connections()
 
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        msg_to_send, image_files = await self.message_converter.yiri2target(message)
+        msg_to_send, files = await self.message_converter.yiri2target(message)
 
         try:
             # 获取频道对象
@@ -1006,8 +1051,8 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 'content': msg_to_send,
             }
 
-            if len(image_files) > 0:
+            if len(files) > 0:
-                args['files'] = image_files
+                args['files'] = files
 
             await channel.send(**args)
 
@@ -1021,15 +1066,16 @@ class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         message: platform_message.MessageChain,
         quote_origin: bool = False,
     ):
-        msg_to_send, image_files = await self.message_converter.yiri2target(message)
+        msg_to_send, files = await self.message_converter.yiri2target(message)
+
         assert isinstance(message_source.source_platform_object, discord.Message)
 
         args = {
             'content': msg_to_send,
         }
 
-        if len(image_files) > 0:
+        if len(files) > 0:
-            args['files'] = image_files
+            args['files'] = files
 
         if quote_origin:
             args['reference'] = message_source.source_platform_object

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

@@ -137,7 +137,11 @@ class KookMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             # For file messages, content is typically the file URL
             attachments = extra.get('attachments', {})
             file_name = attachments.get('name', 'file')
-            components.append(platform_message.Plain(text=f'[File: {file_name}]'))
+            components.append(platform_message.File(url=content, name=file_name))
+        elif msg_type == 8:  # Audio message
+            # For audio messages, content is typically the audio URL
+            attachments = extra.get('attachments', {})
+            components.append(platform_message.Voice(url=content))
         elif msg_type == 9:  # KMarkdown message
             # Note: content is already stripped of mention patterns above
             if content:
@@ -219,9 +223,6 @@ class KookEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event_time,
@@ -320,9 +321,6 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     data = await response.json()
                     if data.get('code') == 0:
                         user_info = data['data']
-                        await self.logger.info(
-                            f'Retrieved bot user info: {user_info.get("username")} (ID: {user_info.get("id")})'
-                        )
                         return user_info
                     else:
                         raise Exception(f'Failed to get bot user info: {data.get("message")}')
@@ -346,11 +344,10 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         # Ignore messages from bot itself to prevent infinite loops
         if self.bot_account_id and str(author_id) == self.bot_account_id:
-            await self.logger.debug(f'Ignoring message from bot itself (author_id: {author_id})')
             return
 
-        # Only process text messages (type 1, 2, 4, 9, 10) in GROUP or PERSON channels
+        # Only process text messages (type 1, 2, 4, 8, 9, 10) in GROUP or PERSON channels
-        if event_type in [1, 2, 4, 9, 10] and channel_type in ['GROUP', 'PERSON']:
+        if event_type in [1, 2, 4, 8, 9, 10] and channel_type in ['GROUP', 'PERSON']:
             try:
                 # Convert to LangBot event
                 lb_event = await self.event_converter.target2yiri(data, self.bot_account_id)
@@ -380,7 +377,6 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                             'sn': self.current_sn,
                         }
                         await self.ws.send(json.dumps(ping_msg))
-                        await self.logger.debug(f'Sent PING with sn={self.current_sn}')
                     except Exception:
                         # Connection closed or send failed, exit loop
                         break
@@ -401,10 +397,9 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     self.gateway_url = await self._get_gateway_url()
 
                 # Connect to WebSocket
-                await self.logger.info(f'Connecting to KOOK WebSocket: {self.gateway_url}')
                 async with websockets.connect(self.gateway_url) as ws:
+                    await self.logger.info(f'Connected to KOOK WebSocket: {self.gateway_url}')
                     self.ws = ws
-                    await self.logger.info('KOOK WebSocket connected')
 
                     # Start heartbeat
                     self.heartbeat_task = asyncio.create_task(self._heartbeat_loop())
@@ -455,10 +450,11 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                             elif signal == 3:  # PONG
                                 await self._handle_pong(msg_data.get('d', {}))
                             elif signal == 5:  # RECONNECT
-                                await self.logger.info('Received RECONNECT signal')
+                                # await self.logger.info('Received RECONNECT signal')
                                 break  # Break to reconnect
                             elif signal == 6:  # RESUME ACK
-                                await self.logger.info('Resume successful')
+                                # await self.logger.info('Resume successful')
+                                pass
                         except json.JSONDecodeError:
                             await self.logger.error(f'Failed to parse message: {message}')
                         except Exception as e:
@@ -571,6 +567,8 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         if quote_origin and msg_id:
             payload['quote'] = msg_id
 
+        payload['reply_msg_id'] = msg_id
+
         headers = {
             'Authorization': f'Bot {self.config["token"]}',
             'Content-Type': 'application/json',

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

@@ -55,9 +55,7 @@ class AESCipher(object):
 
 class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
     @staticmethod
-    async def upload_image_to_lark(
+    async def upload_image_to_lark(msg: platform_message.Image, api_client: lark_oapi.Client) -> typing.Optional[str]:
-        msg: platform_message.Image, api_client: lark_oapi.Client
-    ) -> typing.Optional[str]:
         """Upload an image to Lark and return the image_key, or None if upload fails."""
         image_bytes = None
 
@@ -95,7 +93,9 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 return None
 
         if image_bytes is None:
-            print(f'No image data available for Image message (url={msg.url}, base64={bool(msg.base64)}, path={msg.path})')
+            print(
+                f'No image data available for Image message (url={msg.url}, base64={bool(msg.base64)}, path={msg.path})'
+            )
             return None
 
         try:
@@ -113,10 +113,7 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 request = (
                     CreateImageRequest.builder()
                     .request_body(
-                        CreateImageRequestBody.builder()
+                        CreateImageRequestBody.builder().image_type('message').image(open(temp_file_path, 'rb')).build()
-                        .image_type('message')
-                        .image(open(temp_file_path, 'rb'))
-                        .build()
                     )
                     .build()
                 )
@@ -143,7 +140,7 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
         message_chain: platform_message.MessageChain, api_client: lark_oapi.Client
     ) -> typing.Tuple[list, list]:
         """Convert message chain to Lark format.
-        
+
         Returns:
             Tuple of (text_elements, image_keys):
             - text_elements: List of paragraphs for post message format
@@ -159,24 +156,24 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
         async def process_text_with_images(text: str) -> typing.Tuple[str, list]:
             """Extract Markdown images from text and return cleaned text + image URLs."""
             extracted_urls = []
-            
+
             # Find all Markdown images
             matches = list(markdown_image_pattern.finditer(text))
             if not matches:
                 return text, []
-            
+
             # Extract URLs and remove image syntax from text
             cleaned_text = text
             for match in reversed(matches):  # Reverse to maintain correct positions
                 url = match.group(2)
                 extracted_urls.insert(0, url)  # Insert at beginning since we're going in reverse
                 # Replace image syntax with empty string or a placeholder
-                cleaned_text = cleaned_text[:match.start()] + cleaned_text[match.end():]
+                cleaned_text = cleaned_text[: match.start()] + cleaned_text[match.end() :]
-            
+
             # Clean up multiple consecutive newlines that might result from removing images
             cleaned_text = re.sub(r'\n{3,}', '\n\n', cleaned_text)
             cleaned_text = cleaned_text.strip()
-            
+
             return cleaned_text, extracted_urls
 
         for msg in message_chain:
@@ -189,14 +186,14 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                         text = msg.text.encode('latin1').decode('utf-8')
                     except UnicodeError:
                         text = msg.text.encode('utf-8', errors='replace').decode('utf-8')
-                
+
                 # Check for and extract Markdown images from text
                 cleaned_text, extracted_urls = await process_text_with_images(text)
-                
+
                 # Add cleaned text if not empty
                 if cleaned_text:
                     pending_paragraph.append({'tag': 'md', 'text': cleaned_text})
-                
+
                 # Process extracted image URLs
                 for url in extracted_urls:
                     # Create a temporary Image message to upload
@@ -204,7 +201,7 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                     image_key = await LarkMessageConverter.upload_image_to_lark(temp_image, api_client)
                     if image_key:
                         image_keys.append(image_key)
-                        
+
             elif isinstance(msg, platform_message.At):
                 pending_paragraph.append({'tag': 'at', 'user_id': msg.target, 'style': []})
             elif isinstance(msg, platform_message.AtAll):
@@ -300,6 +297,10 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             message_content['content'] = new_list
         elif message.message_type == 'image':
             message_content['content'] = [{'tag': 'img', 'image_key': message_content['image_key'], 'style': []}]
+        elif message.message_type == 'file':
+            message_content['content'] = [
+                {'tag': 'file', 'file_key': message_content['file_key'], 'file_name': message_content['file_name']}
+            ]
 
         for ele in message_content['content']:
             if ele['tag'] == 'text':
@@ -330,6 +331,33 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 image_format = response.raw.headers['content-type']
 
                 lb_msg_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
+            elif ele['tag'] == 'file':
+                file_key = ele['file_key']
+                file_name = ele['file_name']
+
+                request: GetMessageResourceRequest = (
+                    GetMessageResourceRequest.builder()
+                    .message_id(message.message_id)
+                    .file_key(file_key)
+                    .type('file')
+                    .build()
+                )
+
+                response: GetMessageResourceResponse = await api_client.im.v1.message_resource.aget(request)
+
+                if not response.success():
+                    raise Exception(
+                        f'client.im.v1.message_resource.get failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
+                    )
+
+                file_bytes = response.file.read()
+                file_base64 = base64.b64encode(file_bytes).decode()
+
+                file_format = response.raw.headers['content-type']
+
+                lb_msg_list.append(
+                    platform_message.File(base64=f'data:{file_format};base64,{file_base64}', name=file_name)
+                )
 
         return platform_message.MessageChain(lb_msg_list)
 
@@ -369,9 +397,6 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event.event.message.create_time,
@@ -391,6 +416,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
     message_converter: LarkMessageConverter = LarkMessageConverter()
     event_converter: LarkEventConverter = LarkEventConverter()
+    cipher: AESCipher
 
     listeners: typing.Dict[
         typing.Type[platform_events.Event],
@@ -402,51 +428,11 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     card_id_dict: dict[str, str]  # 消息id到卡片id的映射，便于创建卡片后的发送消息到指定卡片
 
     seq: int  # 用于在发送卡片消息中识别消息顺序，直接以seq作为标识
+    bot_uuid: str = None  # 机器人UUID
 
     def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs):
         quart_app = quart.Quart(__name__)
 
-        @quart_app.route('/lark/callback', methods=['POST'])
-        async def lark_callback():
-            try:
-                data = await quart.request.json
-
-                if 'encrypt' in data:
-                    cipher = AESCipher(config['encrypt-key'])
-                    data = cipher.decrypt_string(data['encrypt'])
-                    data = json.loads(data)
-
-                type = data.get('type')
-                if type is None:
-                    context = EventContext(data)
-                    type = context.header.event_type
-
-                if 'url_verification' == type:
-                    # todo 验证verification token
-                    return {'challenge': data.get('challenge')}
-                context = EventContext(data)
-                type = context.header.event_type
-                p2v1 = P2ImMessageReceiveV1()
-                p2v1.header = context.header
-                event = P2ImMessageReceiveV1Data()
-                event.message = EventMessage(context.event['message'])
-                event.sender = EventSender(context.event['sender'])
-                p2v1.event = event
-                p2v1.schema = context.schema
-                if 'im.message.receive_v1' == type:
-                    try:
-                        event = await self.event_converter.target2yiri(p2v1, self.api_client)
-                    except Exception:
-                        await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
-
-                    if event.__class__ in self.listeners:
-                        await self.listeners[event.__class__](event, self)
-
-                return {'code': 200, 'message': 'ok'}
-            except Exception:
-                await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
-                return {'code': 500, 'message': 'error'}
-
         async def on_message(event: lark_oapi.im.v1.P2ImMessageReceiveV1):
             lb_event = await self.event_converter.target2yiri(event, self.api_client)
 
@@ -463,6 +449,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         bot = lark_oapi.ws.Client(config['app_id'], config['app_secret'], event_handler=event_handler)
         api_client = lark_oapi.Client.builder().app_id(config['app_id']).app_secret(config['app_secret']).build()
+        cipher = AESCipher(config.get('encrypt-key', ''))
 
         super().__init__(
             config=config,
@@ -475,6 +462,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             bot=bot,
             api_client=api_client,
             bot_account_id=bot_account_id,
+            cipher=cipher,
             **kwargs,
         )
 
@@ -859,8 +847,89 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     ):
         self.listeners.pop(event_type)
 
+    def set_bot_uuid(self, bot_uuid: str):
+        """设置 bot UUID（用于生成 webhook URL）"""
+        self.bot_uuid = bot_uuid
+
+    async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
+        """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
+        """
+        try:
+            data = await request.json
+
+            if 'encrypt' in data:
+                data = self.cipher.decrypt_string(data['encrypt'])
+                data = json.loads(data)
+            type = data.get('type')
+            if type is None:
+                context = EventContext(data)
+                type = context.header.event_type
+
+            if 'url_verification' == type:
+                # todo 验证verification token
+                return {'challenge': data.get('challenge')}
+            context = EventContext(data)
+            type = context.header.event_type
+            p2v1 = P2ImMessageReceiveV1()
+            p2v1.header = context.header
+            event = P2ImMessageReceiveV1Data()
+            if 'im.message.receive_v1' == type:
+                try:
+                    event.message = EventMessage(context.event['message'])
+                    event.sender = EventSender(context.event['sender'])
+                    p2v1.event = event
+                    p2v1.schema = context.schema
+                    event = await self.event_converter.target2yiri(p2v1, self.api_client)
+                except Exception:
+                    await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
+
+                if event.__class__ in self.listeners:
+                    await self.listeners[event.__class__](event, self)
+            elif 'im.chat.member.bot.added_v1' == type:
+                try:
+                    bot_added_welcome_msg = self.config.get('bot_added_welcome', '')
+                    if bot_added_welcome_msg:
+                        final_content = {
+                            'zh_Hans': {
+                                'title': '',
+                                'content': bot_added_welcome_msg,
+                            },
+                        }
+                        chat_id = context.event['chat_id']
+                        request: CreateMessageRequest = (
+                            CreateMessageRequest.builder()
+                            .receive_id_type('chat_id')
+                            .request_body(
+                                CreateMessageRequestBody.builder()
+                                .receive_id(chat_id)
+                                .content(json.dumps(final_content))
+                                .msg_type('post')
+                                .uuid(str(uuid.uuid4()))
+                                .build()
+                            )
+                            .build()
+                        )
+                        response: CreateMessageResponse = self.api_client.im.v1.message.create(request)
+
+                        if not response.success():
+                            raise Exception(
+                                f'client.im.v1.message.create failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
+                            )
+                except Exception:
+                    await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
+
+            return {'code': 200, 'message': 'ok'}
+        except Exception:
+            await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
+            return {'code': 500, 'message': 'error'}
+
     async def run_async(self):
-        port = self.config['port']
         enable_webhook = self.config['enable-webhook']
 
         if not enable_webhook:
@@ -875,16 +944,14 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 else:
                     raise e
         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 shutdown_trigger_placeholder():
+            async def keep_alive():
                 while True:
                     await asyncio.sleep(1)
 
-            await self.quart_app.run_task(
+            await keep_alive()
-                host='0.0.0.0',
-                port=port,
-                shutdown_trigger=shutdown_trigger_placeholder,
-            )
 
     async def kill(self) -> bool:
         # 需要断开连接，不然旧的连接会继续运行，导致飞书消息来时会随机选择一个连接

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

@@ -45,16 +45,6 @@ spec:
       type: boolean
       required: true
       default: false
-    - name: port
-      label:
-        en_US: Webhook Port
-        zh_Hans: Webhook端口
-      description:
-        en_US: Only valid when webhook mode is enabled, please fill in the webhook port
-        zh_Hans: 仅在启用 Webhook 模式时有效，请填写 Webhook 端口
-      type: integer
-      required: true
-      default: 2285
     - name: encrypt-key
       label:
         en_US: Encrypt Key
@@ -75,6 +65,16 @@ spec:
       type: boolean
       required: true
       default: false
+    - name: bot_added_welcome
+      label:
+        en_US: Bot Welcome Message
+        zh_Hans: 机器人进群欢迎语
+      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
+      type: text
+      required: false
+      default: ""
 execution:
   python:
     path: ./lark.py

src/langbot/pkg/platform/sources/legacy/gewechat.py

@@ -437,9 +437,6 @@ class GewechatEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event['Data']['CreateTime'],

src/langbot/pkg/platform/sources/legacy/nakuru.py

@@ -153,9 +153,6 @@ class NakuruProjectEventConverter(abstract_platform_adapter.AbstractEventConvert
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title=event.sender.title,
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=yiri_chain,
                 time=event.time,

src/langbot/pkg/platform/sources/legacy/qqbotpy.py

@@ -279,11 +279,6 @@ class OfficialEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=int(
-                        datetime.datetime.strptime(event.member.joined_at, '%Y-%m-%dT%H:%M:%S%z').timestamp()
-                    ),
-                    last_speak_timestamp=datetime.datetime.now().timestamp(),
-                    mute_time_remaining=0,
                 ),
                 message_chain=OfficialMessageConverter.extract_message_chain_from_obj(event, event.id),
                 time=int(datetime.datetime.strptime(event.timestamp, '%Y-%m-%dT%H:%M:%S%z').timestamp()),
@@ -312,9 +307,6 @@ class OfficialEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=int(0),
-                    last_speak_timestamp=datetime.datetime.now().timestamp(),
-                    mute_time_remaining=0,
                 ),
                 message_chain=OfficialMessageConverter.extract_message_chain_from_obj(event, event.id),
                 time=int(datetime.datetime.strptime(event.timestamp, '%Y-%m-%dT%H:%M:%S%z').timestamp()),

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

@@ -108,9 +108,6 @@ class LINEEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event.timestamp,
@@ -262,19 +259,6 @@ class LINEAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         # 保持运行但不启动独立端口
 
         # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f'http://127.0.0.1:{api_port}/bots/{self.bot_uuid}'
-                webhook_url_public = f'http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}'
-
-                await self.logger.info('LINE Webhook 回调地址:')
-                await self.logger.info(f'  本地地址: {webhook_url}')
-                await self.logger.info(f'  公网地址: {webhook_url_public}')
-                await self.logger.info('请在 LINE 后台配置此回调地址')
-            except Exception as e:
-                await self.logger.warning(f'无法生成 webhook URL: {e}')
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)

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

@@ -155,20 +155,6 @@ class OfficialAccountAdapter(abstract_platform_adapter.AbstractMessagePlatformAd
         # 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
 
-        # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f'http://127.0.0.1:{api_port}/bots/{self.bot_uuid}'
-                webhook_url_public = f'http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}'
-
-                await self.logger.info('微信公众号 Webhook 回调地址:')
-                await self.logger.info(f'  本地地址: {webhook_url}')
-                await self.logger.info(f'  公网地址: {webhook_url_public}')
-                await self.logger.info('请在微信公众号后台配置此回调地址')
-            except Exception as e:
-                await self.logger.warning(f'无法生成 webhook URL: {e}')
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)

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

@@ -94,9 +94,6 @@ class QQOfficialEventConverter(abstract_platform_adapter.AbstractEventConverter)
                     permission=platform_entities.Permission.Member,
                 ),
                 special_title='',
-                join_timestamp=0,
-                last_speak_timestamp=0,
-                mute_time_remaining=0,
             )
             time = int(datetime.datetime.strptime(event.timestamp, '%Y-%m-%dT%H:%M:%S%z').timestamp())
             return platform_events.GroupMessage(
@@ -117,9 +114,6 @@ class QQOfficialEventConverter(abstract_platform_adapter.AbstractEventConverter)
                     permission=platform_entities.Permission.Member,
                 ),
                 special_title='',
-                join_timestamp=0,
-                last_speak_timestamp=0,
-                mute_time_remaining=0,
             )
             time = int(datetime.datetime.strptime(event.timestamp, '%Y-%m-%dT%H:%M:%S%z').timestamp())
             return platform_events.GroupMessage(
@@ -247,20 +241,6 @@ class QQOfficialAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter
         # 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
 
-        # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f'http://127.0.0.1:{api_port}/bots/{self.bot_uuid}'
-                webhook_url_public = f'http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}'
-
-                await self.logger.info('QQ 官方机器人 Webhook 回调地址:')
-                await self.logger.info(f'  本地地址: {webhook_url}')
-                await self.logger.info(f'  公网地址: {webhook_url_public}')
-                await self.logger.info('请在 QQ 官方机器人后台配置此回调地址')
-            except Exception as e:
-                await self.logger.warning(f'无法生成 webhook URL: {e}')
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)

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

@@ -76,9 +76,6 @@ class SlackEventConverter(abstract_platform_adapter.AbstractEventConverter):
                     id=event.channel_id, name='MEMBER', permission=platform_entities.Permission.Member
                 ),
                 special_title='',
-                join_timestamp=0,
-                last_speak_timestamp=0,
-                mute_time_remaining=0,
             )
             time = int(datetime.datetime.utcnow().timestamp())
             return platform_events.GroupMessage(
@@ -112,10 +109,7 @@ class SlackAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             raise command_errors.ParamNotEnoughError('Slack机器人缺少相关配置项，请查看文档或联系管理员')
 
         bot = SlackClient(
-            bot_token=config['bot_token'],
+            bot_token=config['bot_token'], signing_secret=config['signing_secret'], logger=logger, unified_mode=True
-            signing_secret=config['signing_secret'],
-            logger=logger,
-            unified_mode=True
         )
 
         super().__init__(
@@ -194,24 +188,10 @@ class SlackAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     async def run_async(self):
         # 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
-
-        # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f"http://127.0.0.1:{api_port}/bots/{self.bot_uuid}"
-                webhook_url_public = f"http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}"
-
-                await self.logger.info(f"Slack 机器人 Webhook 回调地址:")
-                await self.logger.info(f"  本地地址: {webhook_url}")
-                await self.logger.info(f"  公网地址: {webhook_url_public}")
-                await self.logger.info(f"请在 Slack 后台配置此回调地址")
-            except Exception as e:
-                await self.logger.warning(f"无法生成 webhook URL: {e}")
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)
+
         await keep_alive()
 
     async def kill(self) -> bool:

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

@@ -120,9 +120,6 @@ class TelegramEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=lb_message,
                 time=event.message.date.timestamp(),

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

@@ -97,8 +97,6 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         # 推送到所有相关连接
         await self.outbound_message_queue.put(message_data)
 
-        await self.logger.info(f'Send message to {target_id}: {message}')
-
         return message_data
 
     async def reply_message(
@@ -242,7 +240,6 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
 
     async def run_async(self):
         """运行适配器"""
-        await self.logger.info('WebSocket适配器已启动')
 
         try:
             while True:
@@ -258,12 +255,11 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
 
                 await asyncio.sleep(0.1)
         except asyncio.CancelledError:
-            await self.logger.info('WebSocket适配器已停止')
             raise
 
     async def kill(self):
         """停止适配器"""
-        await self.logger.info('WebSocket适配器正在停止')
+        pass
 
     async def _process_image_components(self, message_chain_obj: list):
         """

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

@@ -501,9 +501,6 @@ class WeChatPadEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 ),
                 message_chain=message_chain,
                 time=event['create_time'],

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

@@ -35,6 +35,20 @@ class WecomMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                         'media_id': await bot.get_media_id(msg),
                     }
                 )
+            elif type(msg) is platform_message.Voice:
+                content_list.append(
+                    {
+                        'type': 'voice',
+                        'media_id': await bot.get_media_id(msg),
+                    }
+                )
+            elif type(msg) is platform_message.File:
+                content_list.append(
+                    {
+                        'type': 'file',
+                        'media_id': await bot.get_media_id(msg),
+                    }
+                )
             elif type(msg) is platform_message.Forward:
                 for node in msg.node_list:
                     content_list.extend((await WecomMessageConverter.yiri2target(node.message_chain, bot)))
@@ -185,6 +199,10 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 await self.bot.send_private_msg(fixed_user_id, Wecom_event.agent_id, content['content'])
             elif content['type'] == 'image':
                 await self.bot.send_image(fixed_user_id, Wecom_event.agent_id, content['media_id'])
+            elif content['type'] == 'voice':
+                await self.bot.send_voice(fixed_user_id, Wecom_event.agent_id, content['media_id'])
+            elif content['type'] == 'file':
+                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)
@@ -197,6 +215,10 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     await self.bot.send_private_msg(user_id, agent_id, content['content'])
                 if content['type'] == 'image':
                     await self.bot.send_image(user_id, agent_id, content['media'])
+                if content['type'] == 'voice':
+                    await self.bot.send_voice(user_id, agent_id, content['media'])
+                if content['type'] == 'file':
+                    await self.bot.send_file(user_id, agent_id, content['media'])
 
     def register_listener(
         self,
@@ -232,19 +254,6 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         return await self.bot.handle_unified_webhook(request)
 
     async def run_async(self):
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f'http://127.0.0.1:{api_port}/bots/{self.bot_uuid}'
-                webhook_url_public = f'http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}'
-
-                await self.logger.info('企业微信 Webhook 回调地址:')
-                await self.logger.info(f'  本地地址: {webhook_url}')
-                await self.logger.info(f'  公网地址: {webhook_url_public}')
-                await self.logger.info('请在企业微信后台配置此回调地址')
-            except Exception as e:
-                await self.logger.warning(f'无法生成 webhook URL: {e}')
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)

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

@@ -21,21 +21,21 @@ spec:
     - name: secret
       label:
         en_US: Secret
-        zh_Hans: 密钥
+        zh_Hans: 密钥 (Secret)
       type: string
       required: true
       default: ""
     - name: token
       label:
         en_US: Token
-        zh_Hans: 令牌
+        zh_Hans: 令牌 (Token)
       type: string
       required: true
       default: ""
     - name: EncodingAESKey
       label:
         en_US: EncodingAESKey
-        zh_Hans: 消息加解密密钥
+        zh_Hans: 消息加解密密钥 (EncodingAESKey)
       type: string
       required: true
       default: ""

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

@@ -28,9 +28,105 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
         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()))
-        yiri_msg_list.append(platform_message.Plain(text=event.content))
+
-        if event.picurl != '':
+        if event.content:
-            yiri_msg_list.append(platform_message.Image(base64=event.picurl))
+            yiri_msg_list.append(platform_message.Plain(text=event.content))
+
+        images = []
+        if event.images:
+            images.extend([img for img in event.images if img])
+        if not images and event.picurl:
+            images.append(event.picurl)
+        for image_base64 in images:
+            if image_base64:
+                yiri_msg_list.append(platform_message.Image(base64=image_base64))
+
+        file_info = event.file or {}
+        if file_info:
+            file_url = (
+                file_info.get('download_url')
+                or file_info.get('url')
+                or file_info.get('fileurl')
+                or file_info.get('path')
+            )
+            file_base64 = file_info.get('base64')
+            file_name = file_info.get('filename') or file_info.get('name')
+            file_size = file_info.get('filesize') or file_info.get('size')
+            file_data = file_url or file_base64
+            if file_data or file_name:
+                file_kwargs = {}
+                if file_data:
+                    file_kwargs['url'] = file_data
+                if file_name:
+                    file_kwargs['name'] = file_name
+                if file_size is not None:
+                    file_kwargs['size'] = file_size
+                try:
+                    yiri_msg_list.append(platform_message.File(**file_kwargs))
+                except Exception:
+                    # 兜底
+                    yiri_msg_list.append(platform_message.Unknown(text='[file message unsupported]'))
+
+        voice_info = event.voice or {}
+        if voice_info:
+            voice_payload = voice_info.get('base64') or voice_info.get('url')
+            if voice_payload:
+                if voice_info.get('base64') and not voice_payload.startswith('data:'):
+                    voice_payload = f'data:audio/mpeg;base64,{voice_info.get("base64")}'
+                try:
+                    yiri_msg_list.append(platform_message.Voice(base64=voice_payload))
+                except Exception:
+                    try:
+                        voice_kwargs = {'url': voice_payload}
+                        voice_name = voice_info.get('filename') or voice_info.get('name')
+                        voice_size = voice_info.get('filesize') or voice_info.get('size')
+                        if voice_name:
+                            voice_kwargs['name'] = voice_name
+                        if voice_size is not None:
+                            voice_kwargs['size'] = voice_size
+                        yiri_msg_list.append(platform_message.File(**voice_kwargs))
+                    except Exception:
+                        yiri_msg_list.append(platform_message.Unknown(text='[voice message unsupported]'))
+
+        video_info = event.video or {}
+        if video_info:
+            video_payload = (
+                video_info.get('base64')
+                or video_info.get('url')
+                or video_info.get('download_url')
+                or video_info.get('fileurl')
+            )
+            if video_payload:
+                video_kwargs = {'url': video_payload}
+                video_name = video_info.get('filename') or video_info.get('name')
+                video_size = video_info.get('filesize') or video_info.get('size')
+                if video_name:
+                    video_kwargs['name'] = video_name
+                if video_size is not None:
+                    video_kwargs['size'] = video_size
+                try:
+                    # 没有专门的视频类型，沿用 File 传递给上层
+                    yiri_msg_list.append(platform_message.File(**video_kwargs))
+                except Exception:
+                    yiri_msg_list.append(platform_message.Unknown(text='[video message unsupported]'))
+
+        if event.msgtype == 'link' and event.link:
+            link = event.link
+            summary = '\n'.join(
+                filter(
+                    None,
+                    [link.get('title', ''), link.get('description') or link.get('digest', ''), link.get('url', '')],
+                )
+            )
+            if summary:
+                yiri_msg_list.append(platform_message.Plain(text=summary))
+
+        has_content_element = any(
+            not isinstance(element, (platform_message.Source, platform_message.At)) for element in yiri_msg_list
+        )
+        if not has_content_element:
+            fallback_type = event.msgtype or 'unknown'
+            yiri_msg_list.append(platform_message.Unknown(text=f'[unsupported wecom msgtype: {fallback_type}]'))
         chain = platform_message.MessageChain(yiri_msg_list)
 
         return chain
@@ -67,9 +163,6 @@ class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
                         permission=platform_entities.Permission.Member,
                     ),
                     special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
                 )
                 time = datetime.datetime.now().timestamp()
                 return platform_events.GroupMessage(
@@ -211,20 +304,6 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         # 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
 
-        # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f'http://127.0.0.1:{api_port}/bots/{self.bot_uuid}'
-                webhook_url_public = f'http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}'
-
-                await self.logger.info('企业微信机器人 Webhook 回调地址:')
-                await self.logger.info(f'  本地地址: {webhook_url}')
-                await self.logger.info(f'  公网地址: {webhook_url_public}')
-                await self.logger.info('请在企业微信后台配置此回调地址')
-            except Exception as e:
-                await self.logger.warning(f'无法生成 webhook URL: {e}')
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)

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

@@ -21,14 +21,14 @@ spec:
     - name: Token
       label:
         en_US: Token
-        zh_Hans: 令牌
+        zh_Hans: 令牌 (Token)
       type: string
       required: true
       default: ""
     - name: EncodingAESKey
       label:
         en_US: EncodingAESKey
-        zh_Hans: 消息加解密密钥
+        zh_Hans: 消息加解密密钥 (EncodingAESKey)
       type: string
       required: true
       default: ""

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

@@ -213,23 +213,10 @@ class WecomCSAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         # 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
 
-        # 打印 webhook 回调地址
-        if self.bot_uuid and hasattr(self.logger, 'ap'):
-            try:
-                api_port = self.logger.ap.instance_config.data['api']['port']
-                webhook_url = f"http://127.0.0.1:{api_port}/bots/{self.bot_uuid}"
-                webhook_url_public = f"http://<Your-Public-IP>:{api_port}/bots/{self.bot_uuid}"
-
-                await self.logger.info(f"企业微信客服 Webhook 回调地址:")
-                await self.logger.info(f"  本地地址: {webhook_url}")
-                await self.logger.info(f"  公网地址: {webhook_url_public}")
-                await self.logger.info(f"请在企业微信后台配置此回调地址")
-            except Exception as e:
-                await self.logger.warning(f"无法生成 webhook URL: {e}")
-
         async def keep_alive():
             while True:
                 await asyncio.sleep(1)
+
         await keep_alive()
 
     async def kill(self) -> bool:

src/langbot/pkg/plugin/handler.py

@@ -139,6 +139,8 @@ class RuntimeConnectionHandler(handler.Handler):
 
             message_chain_obj = platform_message.MessageChain.model_validate(message_chain)
 
+            self.ap.logger.debug(f'Reply message: {message_chain_obj.model_dump(serialize_as_any=False)}')
+
             await query.adapter.reply_message(
                 query.message_event,
                 message_chain_obj,
@@ -563,7 +565,7 @@ class RuntimeConnectionHandler(handler.Handler):
                 'event_context': event_context,
                 'include_plugins': include_plugins,
             },
-            timeout=60,
+            timeout=180,
         )
 
         return result

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

@@ -4,6 +4,7 @@ import typing
 import json
 import uuid
 import base64
+import mimetypes
 
 
 from langbot.pkg.provider import runner
@@ -12,6 +13,7 @@ import langbot_plugin.api.entities.builtin.provider.message as provider_message
 from langbot.pkg.utils import image
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
 from langbot.libs.dify_service_api.v1 import client, errors
+import httpx
 
 
 @runner.runner_class('dify-service-api')
@@ -70,14 +72,43 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                 content = f'<think>\n{thinking_content}\n</think>\n{content}'.strip()
             return content, thinking_content
 
-    async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[str]]:
+    async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[dict]]:
-        """预处理用户消息，提取纯文本，并将图片上传到 Dify 服务
+        """预处理用户消息，提取纯文本，并将图片/文件上传到 Dify 服务
 
         Returns:
-            tuple[str, list[str]]: 纯文本和图片的 Dify 服务图片 ID
+            tuple[str, list[dict]]: 纯文本和上传后的文件描述（包含 type 与 id）
         """
         plain_text = ''
-        file_ids = []
+        upload_files: list[dict] = []
+        user_tag = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
+
+        async def upload_file_bytes(file_name: str, file_bytes: bytes, content_type: str) -> str:
+            file_name = file_name or 'file'
+            content_type = content_type or 'application/octet-stream'
+            file = (file_name, file_bytes, content_type)
+            resp = await self.dify_client.upload_file(file, user_tag)
+            return resp['id']
+
+        async def download_file(file_url: str) -> tuple[bytes, str]:
+            """Download file from url (supports data url)."""
+
+            async with httpx.AsyncClient() as client_session:
+                resp = await client_session.get(file_url)
+                resp.raise_for_status()
+                content_type = (
+                    resp.headers.get('content-type') or mimetypes.guess_type(file_url)[0] or 'application/octet-stream'
+                )
+                return resp.content, content_type
+
+        def _detect_file_type(content_type: str) -> str:
+            """Map MIME to dify file type."""
+            if content_type and content_type.startswith('image/'):
+                return 'image'
+            if content_type and content_type.startswith('audio/'):
+                return 'audio'
+            if content_type and content_type.startswith('video/'):
+                return 'video'
+            return 'document'
 
         if isinstance(query.user_message.content, list):
             for ce in query.user_message.content:
@@ -86,30 +117,36 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                 elif ce.type == 'image_base64':
                     image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
                     file_bytes = base64.b64decode(image_b64)
-                    file = ('img.png', file_bytes, f'image/{image_format}')
+                    image_id = await upload_file_bytes(f'img.{image_format}', file_bytes, f'image/{image_format}')
-                    file_upload_resp = await self.dify_client.upload_file(
+                    upload_files.append({'type': 'image', 'id': image_id})
-                        file,
+                elif ce.type == 'file_url':
-                        f'{query.session.launcher_type.value}_{query.session.launcher_id}',
+                    file_url = getattr(ce, 'file_url', None)
-                    )
+                    file_name = getattr(ce, 'file_name', None) or 'file'
-                    image_id = file_upload_resp['id']
+                    try:
-                    file_ids.append(image_id)
+                        file_bytes, content_type = await download_file(file_url)
-                # elif ce.type == "file_url":
+                        file_id = await upload_file_bytes(file_name, file_bytes, content_type)
-                #     file_bytes = base64.b64decode(ce.file_url)
+                        file_type = _detect_file_type(content_type)
-                #     file_upload_resp = await self.dify_client.upload_file(
+                        upload_files.append({'type': file_type, 'id': file_id})
-                #         file_bytes,
+                    except Exception as e:
-                #         f'{query.session.launcher_type.value}_{query.session.launcher_id}',
+                        self.ap.logger.warning(f'dify file upload failed: {e}')
-                #     )
+                elif ce.type == 'file_base64':
-                #     file_id = file_upload_resp['id']
+                    file_name = getattr(ce, 'file_name', None) or 'file'
-                #     file_ids.append(file_id)
+
+                    header, b64_data = ce.file_base64.split(',', 1)
+                    content_type = 'application/octet-stream'
+                    if ';' in header:
+                        content_type = header.split(';')[0][5:] or content_type
+                    file_bytes = base64.b64decode(b64_data)
+                    file_id = await upload_file_bytes(file_name, file_bytes, content_type)
+                    file_type = _detect_file_type(content_type)
+                    upload_files.append({'type': file_type, 'id': file_id})
+
         elif isinstance(query.user_message.content, str):
             plain_text = query.user_message.content
-        # plain_text = "When the file content is readable, please read the content of this file. When the file is an image, describe the content of this image." if file_ids and not plain_text else plain_text
+
-        # plain_text = "The user message type cannot be parsed." if not file_ids and not plain_text else plain_text
-        # plain_text = plain_text if plain_text else "When the file content is readable, please read the content of this file. When the file is an image, describe the content of this image."
-        # print(self.pipeline_config['ai'])
         plain_text = plain_text if plain_text else self.pipeline_config['ai']['dify-service-api']['base-prompt']
 
-        return plain_text, file_ids
+        return plain_text, upload_files
 
     async def _chat_messages(
         self, query: pipeline_query.Query
@@ -118,14 +155,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         cov_id = query.session.using_conversation.uuid or ''
         query.variables['conversation_id'] = cov_id
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
-                'upload_file_id': image_id,
+                'transfer_method': 'local_file',
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         mode = 'basic'  # 标记是基础编排还是工作流编排
@@ -183,15 +221,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         cov_id = query.session.using_conversation.uuid or ''
         query.variables['conversation_id'] = cov_id
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
                 'transfer_method': 'local_file',
-                'upload_file_id': image_id,
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         ignored_events = []
@@ -280,15 +318,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
 
         query.variables['conversation_id'] = query.session.using_conversation.uuid
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
                 'transfer_method': 'local_file',
-                'upload_file_id': image_id,
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         ignored_events = ['text_chunk', 'workflow_started']
@@ -352,15 +390,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         cov_id = query.session.using_conversation.uuid or ''
         query.variables['conversation_id'] = cov_id
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
                 'transfer_method': 'local_file',
-                'upload_file_id': image_id,
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         basic_mode_pending_chunk = ''
@@ -436,15 +474,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         cov_id = query.session.using_conversation.uuid or ''
         query.variables['conversation_id'] = cov_id
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
                 'transfer_method': 'local_file',
-                'upload_file_id': image_id,
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         ignored_events = []
@@ -558,15 +596,15 @@ class DifyServiceAPIRunner(runner.RequestRunner):
 
         query.variables['conversation_id'] = query.session.using_conversation.uuid
 
-        plain_text, image_ids = await self._preprocess_user_message(query)
+        plain_text, upload_files = await self._preprocess_user_message(query)
 
         files = [
             {
-                'type': 'image',
+                'type': f['type'],
                 'transfer_method': 'local_file',
-                'upload_file_id': image_id,
+                'upload_file_id': f['id'],
             }
-            for image_id in image_ids
+            for f in upload_files
         ]
 
         ignored_events = ['workflow_started']

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

@@ -94,7 +94,6 @@ class LangflowAPIRunner(runner.RequestRunner):
             if is_stream:
                 # 流式请求
                 async with client.stream('POST', url, json=payload, headers=headers, timeout=120.0) as response:
-                    print(response)
                     response.raise_for_status()
 
                     accumulated_content = ''

src/langbot/pkg/provider/session/sessionmgr.py

@@ -33,6 +33,7 @@ class SessionManager:
         session = provider_session.Session(
             launcher_type=query.launcher_type,
             launcher_id=query.launcher_id,
+            sender_id=query.sender_id,
         )
         session._semaphore = asyncio.Semaphore(session_concurrency)
         self.session_list.append(session)

src/langbot/pkg/vector/mgr.py

@@ -4,6 +4,8 @@ from ..core import app
 from .vdb import VectorDatabase
 from .vdbs.chroma import ChromaVectorDatabase
 from .vdbs.qdrant import QdrantVectorDatabase
+from .vdbs.milvus import MilvusVectorDatabase
+from .vdbs.pgvector_db import PgVectorDatabase
 
 
 class VectorDBManager:
@@ -16,12 +18,47 @@ class VectorDBManager:
     async def initialize(self):
         kb_config = self.ap.instance_config.data.get('vdb')
         if kb_config:
-            if kb_config.get('use') == 'chroma':
+            vdb_type = kb_config.get('use')
+
+            if vdb_type == 'chroma':
                 self.vector_db = ChromaVectorDatabase(self.ap)
                 self.ap.logger.info('Initialized Chroma vector database backend.')
-            elif kb_config.get('use') == 'qdrant':
+
+            elif vdb_type == 'qdrant':
                 self.vector_db = QdrantVectorDatabase(self.ap)
                 self.ap.logger.info('Initialized Qdrant vector database backend.')
+
+            elif vdb_type == 'milvus':
+                # Get Milvus configuration
+                milvus_config = kb_config.get('milvus', {})
+                uri = milvus_config.get('uri', './data/milvus.db')
+                token = milvus_config.get('token')
+                self.vector_db = MilvusVectorDatabase(self.ap, uri=uri, token=token)
+                self.ap.logger.info('Initialized Milvus vector database backend.')
+
+            elif vdb_type == 'pgvector':
+                # Get pgvector configuration
+                pgvector_config = kb_config.get('pgvector', {})
+                connection_string = pgvector_config.get('connection_string')
+                if connection_string:
+                    self.vector_db = PgVectorDatabase(self.ap, connection_string=connection_string)
+                else:
+                    # Use individual parameters
+                    host = pgvector_config.get('host', 'localhost')
+                    port = pgvector_config.get('port', 5432)
+                    database = pgvector_config.get('database', 'langbot')
+                    user = pgvector_config.get('user', 'postgres')
+                    password = pgvector_config.get('password', 'postgres')
+                    self.vector_db = PgVectorDatabase(
+                        self.ap,
+                        host=host,
+                        port=port,
+                        database=database,
+                        user=user,
+                        password=password
+                    )
+                self.ap.logger.info('Initialized pgvector database backend.')
+
             else:
                 self.vector_db = ChromaVectorDatabase(self.ap)
                 self.ap.logger.warning('No valid vector database backend configured, defaulting to Chroma.')

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

@@ -0,0 +1,249 @@
+from __future__ import annotations
+import asyncio
+from typing import Any, Dict
+from pymilvus import MilvusClient, DataType
+from langbot.pkg.vector.vdb import VectorDatabase
+from langbot.pkg.core import app
+
+
+class MilvusVectorDatabase(VectorDatabase):
+    """Milvus vector database implementation"""
+
+    def __init__(self, ap: app.Application, uri: str = "milvus.db", token: str = None):
+        """Initialize Milvus vector database
+
+        Args:
+            ap: Application instance
+            uri: Milvus connection URI. For local file: "milvus.db"
+                 For remote server: "http://localhost:19530"
+            token: Optional authentication token for remote connections
+        """
+        self.ap = ap
+        self.uri = uri
+        self.token = token
+        self.client = None
+        self._collections = {}
+        self._initialize_client()
+
+    def _initialize_client(self):
+        """Initialize Milvus client connection"""
+        try:
+            if self.token:
+                self.client = MilvusClient(uri=self.uri, token=self.token)
+            else:
+                self.client = MilvusClient(uri=self.uri)
+            self.ap.logger.info(f"Connected to Milvus at {self.uri}")
+        except Exception as e:
+            self.ap.logger.error(f"Failed to connect to Milvus: {e}")
+            raise
+
+    async def get_or_create_collection(self, collection: str):
+        """Get or create a Milvus collection
+
+        Args:
+            collection: Collection name (corresponds to knowledge base UUID)
+        """
+        if collection in self._collections:
+            return self._collections[collection]
+
+        # Check if collection exists
+        has_collection = await asyncio.to_thread(
+            self.client.has_collection, collection_name=collection
+        )
+
+        if not has_collection:
+            # Create collection with custom schema to support string IDs
+            from pymilvus import CollectionSchema, FieldSchema, DataType
+
+            fields = [
+                FieldSchema(name="id", dtype=DataType.VARCHAR, is_primary=True, max_length=255),
+                FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=1536),
+                FieldSchema(name="text", dtype=DataType.VARCHAR, max_length=65535),
+                FieldSchema(name="file_id", dtype=DataType.VARCHAR, max_length=255),
+                FieldSchema(name="chunk_uuid", dtype=DataType.VARCHAR, max_length=255),
+            ]
+
+            schema = CollectionSchema(fields=fields, description="LangBot knowledge base vectors")
+
+            await asyncio.to_thread(
+                self.client.create_collection,
+                collection_name=collection,
+                schema=schema,
+                metric_type="COSINE",
+            )
+
+            # Create index for vector field (required for loading/searching)
+            index_params = {
+                "metric_type": "COSINE",
+                "index_type": "AUTOINDEX",
+                "params": {}
+            }
+            await asyncio.to_thread(
+                self.client.create_index,
+                collection_name=collection,
+                field_name="vector",
+                index_params=index_params
+            )
+
+            self.ap.logger.info(f"Created Milvus collection '{collection}' with index")
+        else:
+            self.ap.logger.info(f"Milvus collection '{collection}' already exists")
+
+        self._collections[collection] = collection
+        return collection
+
+    async def add_embeddings(
+        self,
+        collection: str,
+        ids: list[str],
+        embeddings_list: list[list[float]],
+        metadatas: list[dict[str, Any]],
+    ) -> None:
+        """Add vector embeddings to Milvus collection
+
+        Args:
+            collection: Collection name
+            ids: List of unique IDs for each vector
+            embeddings_list: List of embedding vectors
+            metadatas: List of metadata dictionaries for each vector
+        """
+        await self.get_or_create_collection(collection)
+
+        # Prepare data in Milvus format
+        data = []
+        for i, vector_id in enumerate(ids):
+            entry = {
+                "id": vector_id,
+                "vector": embeddings_list[i],
+            }
+            # Add metadata fields
+            if metadatas and i < len(metadatas):
+                metadata = metadatas[i]
+                # Add common metadata fields
+                if "text" in metadata:
+                    entry["text"] = metadata["text"]
+                if "file_id" in metadata:
+                    entry["file_id"] = metadata["file_id"]
+                if "uuid" in metadata:
+                    entry["chunk_uuid"] = metadata["uuid"]
+            data.append(entry)
+
+        # Insert data into Milvus
+        await asyncio.to_thread(
+            self.client.insert,
+            collection_name=collection,
+            data=data
+        )
+
+        # Load collection for searching (Milvus requires this)
+        await asyncio.to_thread(
+            self.client.load_collection,
+            collection_name=collection
+        )
+
+        self.ap.logger.info(f"Added {len(ids)} embeddings to Milvus collection '{collection}'")
+
+    async def search(
+        self, collection: str, query_embedding: list[float], k: int = 5
+    ) -> Dict[str, Any]:
+        """Search for similar vectors in Milvus collection
+
+        Args:
+            collection: Collection name
+            query_embedding: Query vector
+            k: Number of top results to return
+
+        Returns:
+            Dictionary with search results in Chroma-compatible format
+        """
+        await self.get_or_create_collection(collection)
+
+        # Perform search
+        search_params = {
+            "metric_type": "COSINE",
+            "params": {}
+        }
+
+        results = await asyncio.to_thread(
+            self.client.search,
+            collection_name=collection,
+            data=[query_embedding],
+            limit=k,
+            search_params=search_params,
+            output_fields=["text", "file_id", "chunk_uuid"]
+        )
+
+        # Convert results to Chroma-compatible format
+        # Milvus returns: [[ {id, distance, entity: {...}} ]]
+        ids = []
+        distances = []
+        metadatas = []
+
+        if results and len(results) > 0:
+            for hit in results[0]:
+                ids.append(hit.get("id", ""))
+                distances.append(hit.get("distance", 0.0))
+
+                # Build metadata from entity fields
+                entity = hit.get("entity", {})
+                metadata = {}
+                if "text" in entity:
+                    metadata["text"] = entity["text"]
+                if "file_id" in entity:
+                    metadata["file_id"] = entity["file_id"]
+                if "chunk_uuid" in entity:
+                    metadata["uuid"] = entity["chunk_uuid"]
+                metadatas.append(metadata)
+
+        # Return in Chroma-compatible format (nested lists)
+        result = {
+            "ids": [ids],
+            "distances": [distances],
+            "metadatas": [metadatas]
+        }
+
+        self.ap.logger.info(
+            f"Milvus search in '{collection}' returned {len(ids)} results"
+        )
+        return result
+
+    async def delete_by_file_id(self, collection: str, file_id: str) -> None:
+        """Delete vectors from collection by file_id
+
+        Args:
+            collection: Collection name
+            file_id: File ID to filter deletion
+        """
+        await self.get_or_create_collection(collection)
+
+        # Delete entities matching the file_id
+        await asyncio.to_thread(
+            self.client.delete,
+            collection_name=collection,
+            filter=f'file_id == "{file_id}"'
+        )
+        self.ap.logger.info(
+            f"Deleted embeddings from Milvus collection '{collection}' with file_id: {file_id}"
+        )
+
+    async def delete_collection(self, collection: str):
+        """Delete a Milvus collection
+
+        Args:
+            collection: Collection name to delete
+        """
+        if collection in self._collections:
+            del self._collections[collection]
+
+        # Check if collection exists before attempting deletion
+        has_collection = await asyncio.to_thread(
+            self.client.has_collection, collection_name=collection
+        )
+
+        if has_collection:
+            await asyncio.to_thread(
+                self.client.drop_collection, collection_name=collection
+            )
+            self.ap.logger.info(f"Deleted Milvus collection '{collection}'")
+        else:
+            self.ap.logger.warning(f"Milvus collection '{collection}' not found")

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

@@ -0,0 +1,286 @@
+from __future__ import annotations
+import asyncio
+from typing import Any, Dict
+from sqlalchemy import create_engine, text, Column, String, Text
+from sqlalchemy.orm import declarative_base, sessionmaker, Session
+from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession, async_sessionmaker
+from pgvector.sqlalchemy import Vector
+from langbot.pkg.vector.vdb import VectorDatabase
+from langbot.pkg.core import app
+import uuid
+
+Base = declarative_base()
+
+
+class PgVectorEntry(Base):
+    """SQLAlchemy model for pgvector entries"""
+    __tablename__ = 'langbot_vectors'
+
+    id = Column(String, primary_key=True)
+    collection = Column(String, index=True, nullable=False)
+    embedding = Column(Vector(1536))  # Default dimension, will be created dynamically
+    text = Column(Text)
+    file_id = Column(String, index=True)
+    chunk_uuid = Column(String)
+
+
+class PgVectorDatabase(VectorDatabase):
+    """PostgreSQL with pgvector extension database implementation"""
+
+    def __init__(
+        self,
+        ap: app.Application,
+        connection_string: str = None,
+        host: str = "localhost",
+        port: int = 5432,
+        database: str = "langbot",
+        user: str = "postgres",
+        password: str = "postgres"
+    ):
+        """Initialize pgvector database
+
+        Args:
+            ap: Application instance
+            connection_string: Full PostgreSQL connection string (overrides other params)
+            host: PostgreSQL host
+            port: PostgreSQL port
+            database: Database name
+            user: Database user
+            password: Database password
+        """
+        self.ap = ap
+
+        # Build connection string if not provided
+        if connection_string:
+            self.connection_string = connection_string
+        else:
+            self.connection_string = (
+                f"postgresql+psycopg://{user}:{password}@{host}:{port}/{database}"
+            )
+
+        self.async_connection_string = self.connection_string.replace(
+            "postgresql://", "postgresql+asyncpg://"
+        ).replace(
+            "postgresql+psycopg://", "postgresql+asyncpg://"
+        )
+
+        self.engine = None
+        self.async_engine = None
+        self.SessionLocal = None
+        self.AsyncSessionLocal = None
+        self._collections = set()
+        self._initialize_db()
+
+    def _initialize_db(self):
+        """Initialize database connection and create tables"""
+        try:
+            # Create async engine for async operations
+            self.async_engine = create_async_engine(
+                self.async_connection_string,
+                echo=False,
+                pool_pre_ping=True
+            )
+            self.AsyncSessionLocal = async_sessionmaker(
+                self.async_engine,
+                class_=AsyncSession,
+                expire_on_commit=False
+            )
+
+            # Create sync engine for table creation
+            sync_connection_string = self.connection_string.replace(
+                "postgresql+asyncpg://", "postgresql+psycopg://"
+            )
+            self.engine = create_engine(sync_connection_string, echo=False)
+
+            # Create pgvector extension and tables
+            with self.engine.connect() as conn:
+                # Enable pgvector extension
+                conn.execute(text("CREATE EXTENSION IF NOT EXISTS vector"))
+                conn.commit()
+
+            # Create tables
+            Base.metadata.create_all(self.engine)
+
+            self.ap.logger.info(f"Connected to PostgreSQL with pgvector")
+        except Exception as e:
+            self.ap.logger.error(f"Failed to connect to PostgreSQL: {e}")
+            raise
+
+    async def get_or_create_collection(self, collection: str):
+        """Get or create a collection (logical grouping in pgvector)
+
+        Args:
+            collection: Collection name (knowledge base UUID)
+        """
+        # In pgvector, collections are logical - we just track them
+        if collection not in self._collections:
+            self._collections.add(collection)
+            self.ap.logger.info(f"Registered pgvector collection '{collection}'")
+        return collection
+
+    async def add_embeddings(
+        self,
+        collection: str,
+        ids: list[str],
+        embeddings_list: list[list[float]],
+        metadatas: list[dict[str, Any]],
+    ) -> None:
+        """Add vector embeddings to pgvector
+
+        Args:
+            collection: Collection name
+            ids: List of unique IDs for each vector
+            embeddings_list: List of embedding vectors
+            metadatas: List of metadata dictionaries
+        """
+        await self.get_or_create_collection(collection)
+
+        async with self.AsyncSessionLocal() as session:
+            try:
+                for i, vector_id in enumerate(ids):
+                    metadata = metadatas[i] if i < len(metadatas) else {}
+
+                    entry = PgVectorEntry(
+                        id=vector_id,
+                        collection=collection,
+                        embedding=embeddings_list[i],
+                        text=metadata.get("text", ""),
+                        file_id=metadata.get("file_id", ""),
+                        chunk_uuid=metadata.get("uuid", "")
+                    )
+                    session.add(entry)
+
+                await session.commit()
+                self.ap.logger.info(
+                    f"Added {len(ids)} embeddings to pgvector collection '{collection}'"
+                )
+            except Exception as e:
+                await session.rollback()
+                self.ap.logger.error(f"Error adding embeddings to pgvector: {e}")
+                raise
+
+    async def search(
+        self, collection: str, query_embedding: list[float], k: int = 5
+    ) -> Dict[str, Any]:
+        """Search for similar vectors using cosine distance
+
+        Args:
+            collection: Collection name
+            query_embedding: Query vector
+            k: Number of top results to return
+
+        Returns:
+            Dictionary with search results in Chroma-compatible format
+        """
+        await self.get_or_create_collection(collection)
+
+        async with self.AsyncSessionLocal() as session:
+            try:
+                # Use cosine distance for similarity search
+                from sqlalchemy import select, func
+
+                # Query for similar vectors
+                stmt = (
+                    select(
+                        PgVectorEntry.id,
+                        PgVectorEntry.text,
+                        PgVectorEntry.file_id,
+                        PgVectorEntry.chunk_uuid,
+                        PgVectorEntry.embedding.cosine_distance(query_embedding).label('distance')
+                    )
+                    .filter(PgVectorEntry.collection == collection)
+                    .order_by(PgVectorEntry.embedding.cosine_distance(query_embedding))
+                    .limit(k)
+                )
+
+                result = await session.execute(stmt)
+                rows = result.fetchall()
+
+                # Convert to Chroma-compatible format
+                ids = []
+                distances = []
+                metadatas = []
+
+                for row in rows:
+                    ids.append(row.id)
+                    distances.append(float(row.distance))
+                    metadatas.append({
+                        "text": row.text or "",
+                        "file_id": row.file_id or "",
+                        "uuid": row.chunk_uuid or ""
+                    })
+
+                result_dict = {
+                    "ids": [ids],
+                    "distances": [distances],
+                    "metadatas": [metadatas]
+                }
+
+                self.ap.logger.info(
+                    f"pgvector search in '{collection}' returned {len(ids)} results"
+                )
+                return result_dict
+
+            except Exception as e:
+                self.ap.logger.error(f"Error searching pgvector: {e}")
+                raise
+
+    async def delete_by_file_id(self, collection: str, file_id: str) -> None:
+        """Delete vectors by file_id
+
+        Args:
+            collection: Collection name
+            file_id: File ID to filter deletion
+        """
+        await self.get_or_create_collection(collection)
+
+        async with self.AsyncSessionLocal() as session:
+            try:
+                from sqlalchemy import delete
+
+                stmt = delete(PgVectorEntry).where(
+                    PgVectorEntry.collection == collection,
+                    PgVectorEntry.file_id == file_id
+                )
+                await session.execute(stmt)
+                await session.commit()
+
+                self.ap.logger.info(
+                    f"Deleted embeddings from pgvector collection '{collection}' with file_id: {file_id}"
+                )
+            except Exception as e:
+                await session.rollback()
+                self.ap.logger.error(f"Error deleting from pgvector: {e}")
+                raise
+
+    async def delete_collection(self, collection: str):
+        """Delete all vectors in a collection
+
+        Args:
+            collection: Collection name to delete
+        """
+        if collection in self._collections:
+            self._collections.remove(collection)
+
+        async with self.AsyncSessionLocal() as session:
+            try:
+                from sqlalchemy import delete
+
+                stmt = delete(PgVectorEntry).where(
+                    PgVectorEntry.collection == collection
+                )
+                await session.execute(stmt)
+                await session.commit()
+
+                self.ap.logger.info(f"Deleted pgvector collection '{collection}'")
+            except Exception as e:
+                await session.rollback()
+                self.ap.logger.error(f"Error deleting pgvector collection: {e}")
+                raise
+
+    async def close(self):
+        """Close database connections"""
+        if self.async_engine:
+            await self.async_engine.dispose()
+        if self.engine:
+            self.engine.dispose()

src/langbot/templates/config.yaml

@@ -36,6 +36,15 @@ vdb:
         host: localhost
         port: 6333
         api_key: ''
+    milvus:
+        uri: 'http://127.0.0.1:19530'
+        token: ''
+    pgvector:
+        host: '127.0.0.1'
+        port: 5433
+        database: 'langbot'
+        user: 'postgres'
+        password: 'postgres'
 storage:
     use: local
     s3:
@@ -49,4 +58,4 @@ plugin:
     runtime_ws_url: 'ws://langbot_plugin_runtime:5400/control/ws'
     enable_marketplace: true
     cloud_service_url: 'https://space.langbot.app'
-    display_plugin_debug_url: 'http://localhost:5401'
+    display_plugin_debug_url: 'ws://localhost:5401/plugin/debug/ws'

tests/unit_tests/pipeline/conftest.py

@@ -14,6 +14,8 @@ from unittest.mock import AsyncMock, Mock
 
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
+import langbot_plugin.api.entities.builtin.platform.events as platform_events
+import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
 import langbot_plugin.api.entities.builtin.provider.session as provider_session
 
 from langbot.pkg.pipeline import entities as pipeline_entities
@@ -159,12 +161,18 @@ def sample_message_chain():
 
 @pytest.fixture
 def sample_message_event(sample_message_chain):
-    """Provides sample message event"""
+    """Provides sample message event (FriendMessage)"""
-    event = Mock()
+    sender = platform_entities.Friend(
-    event.sender = Mock()
+        id=12345,
-    event.sender.id = 12345
+        nickname='TestUser',
-    event.time = 1609459200  # 2021-01-01 00:00:00
+        remark=None,
-    return event
+    )
+    return platform_events.FriendMessage(
+        type='FriendMessage',
+        sender=sender,
+        message_chain=sample_message_chain,
+        time=1609459200,  # 2021-01-01 00:00:00
+    )
 
 
 @pytest.fixture

web/.gitignore

@@ -40,5 +40,3 @@ yarn-error.log*
 # typescript
 *.tsbuildinfo
 next-env.d.ts
-
-pnpm-lock.yaml

web/package.json

@@ -51,11 +51,11 @@
     "input-otp": "^1.4.2",
     "lodash": "^4.17.21",
     "lucide-react": "^0.507.0",
-    "next": "15.4.8",
+    "next": "~15.5.7",
     "next-themes": "^0.4.6",
     "postcss": "^8.5.3",
-    "react": "^19.0.0",
+    "react": "19.2.1",
-    "react-dom": "^19.0.0",
+    "react-dom": "19.2.1",
     "react-hook-form": "^7.56.3",
     "react-i18next": "^15.5.1",
     "react-markdown": "^10.1.0",
@@ -82,8 +82,8 @@
     "@types/mdast": "^4.0.4",
     "@types/ms": "^2.1.0",
     "@types/node": "^20",
-    "@types/react": "^19",
+    "@types/react": "~19.2.7",
-    "@types/react-dom": "^19",
+    "@types/react-dom": "~19.2.3",
     "@types/react-syntax-highlighter": "^15.5.13",
     "@types/unist": "^3.0.3",
     "eslint": "^9",

web/src/app/home/bots/components/bot-form/BotForm.tsx

@@ -111,14 +111,41 @@ export default function BotForm({
   const [dynamicFormConfigList, setDynamicFormConfigList] = useState<
     IDynamicFormItemSchema[]
   >([]);
+  const [filteredDynamicFormConfigList, setFilteredDynamicFormConfigList] =
+    useState<IDynamicFormItemSchema[]>([]);
   const [, setIsLoading] = useState<boolean>(false);
   const [webhookUrl, setWebhookUrl] = useState<string>('');
   const webhookInputRef = React.useRef<HTMLInputElement>(null);
 
+  // Watch adapter and adapter_config for filtering
+  const currentAdapter = form.watch('adapter');
+  const currentAdapterConfig = form.watch('adapter_config');
+
   useEffect(() => {
     setBotFormValues();
   }, []);
 
+  // Filter dynamic form config list based on enable-webhook status for Lark adapter
+  useEffect(() => {
+    if (currentAdapter === 'lark') {
+      const enableWebhook = currentAdapterConfig?.['enable-webhook'];
+      if (enableWebhook === false) {
+        // Hide encrypt-key field when webhook is disabled
+        setFilteredDynamicFormConfigList(
+          dynamicFormConfigList.filter(
+            (config) => config.name !== 'encrypt-key',
+          ),
+        );
+      } else {
+        // Show all fields when webhook is enabled or undefined
+        setFilteredDynamicFormConfigList(dynamicFormConfigList);
+      }
+    } else {
+      // For non-Lark adapters, show all fields
+      setFilteredDynamicFormConfigList(dynamicFormConfigList);
+    }
+  }, [currentAdapter, currentAdapterConfig, dynamicFormConfigList]);
+
   // 复制到剪贴板的辅助函数 - 使用页面上的真实input元素
   const copyToClipboard = () => {
     console.log('[Copy] Attempting to copy from input element');
@@ -498,34 +525,36 @@ export default function BotForm({
                 </div>
 
                 {/* Webhook 地址显示（统一 Webhook 模式） */}
-                {webhookUrl && (
+                {webhookUrl &&
-                  <FormItem>
+                  (currentAdapter !== 'lark' ||
-                    <FormLabel>{t('bots.webhookUrl')}</FormLabel>
+                    currentAdapterConfig?.['enable-webhook'] !== false) && (
-                    <div className="flex items-center gap-2">
+                    <FormItem>
-                      <Input
+                      <FormLabel>{t('bots.webhookUrl')}</FormLabel>
-                        ref={webhookInputRef}
+                      <div className="flex items-center gap-2">
-                        value={webhookUrl}
+                        <Input
-                        readOnly
+                          ref={webhookInputRef}
-                        className="flex-1 bg-gray-50 dark:bg-gray-900"
+                          value={webhookUrl}
-                        onClick={(e) => {
+                          readOnly
-                          // 点击输入框时自动全选
+                          className="flex-1 bg-gray-50 dark:bg-gray-900"
-                          (e.target as HTMLInputElement).select();
+                          onClick={(e) => {
-                        }}
+                            // 点击输入框时自动全选
-                      />
+                            (e.target as HTMLInputElement).select();
-                      <Button
+                          }}
-                        type="button"
+                        />
-                        variant="outline"
+                        <Button
-                        size="sm"
+                          type="button"
-                        onClick={copyToClipboard}
+                          variant="outline"
-                      >
+                          size="sm"
-                        {t('common.copy')}
+                          onClick={copyToClipboard}
-                      </Button>
+                        >
-                    </div>
+                          {t('common.copy')}
-                    <p className="text-sm text-gray-500 mt-1">
+                        </Button>
-                      {t('bots.webhookUrlHint')}
+                      </div>
-                    </p>
+                      <p className="text-sm text-gray-500 mt-1">
-                  </FormItem>
+                        {t('bots.webhookUrlHint')}
-                )}
+                      </p>
+                    </FormItem>
+                  )}
               </>
             )}
 
@@ -622,13 +651,13 @@ export default function BotForm({
               </div>
             )}
 
-            {showDynamicForm && dynamicFormConfigList.length > 0 && (
+            {showDynamicForm && filteredDynamicFormConfigList.length > 0 && (
               <div className="space-y-4">
                 <div className="text-lg font-medium">
                   {t('bots.adapterConfig')}
                 </div>
                 <DynamicFormComponent
-                  itemConfigList={dynamicFormConfigList}
+                  itemConfigList={filteredDynamicFormConfigList}
                   initialValues={form.watch('adapter_config')}
                   onSubmit={(values) => {
                     form.setValue('adapter_config', values);

web/src/app/home/bots/components/bot-log/view/BotLogCard.tsx

@@ -44,12 +44,35 @@ export function BotLogCard({ botLog }: { botLog: BotLog }) {
     const strArr = str.split('');
     return strArr;
   }
+
+  // 根据日志级别返回对应的样式类
+  function getLevelStyles(level: string) {
+    switch (level.toLowerCase()) {
+      case 'error':
+        return 'bg-red-100 text-red-800 dark:bg-red-900/30 dark:text-red-400';
+      case 'warning':
+        return 'bg-orange-100 text-orange-800 dark:bg-orange-900/30 dark:text-orange-400';
+      case 'info':
+        return 'bg-blue-100 text-blue-800 dark:bg-blue-900/30 dark:text-blue-400';
+      case 'debug':
+        return 'bg-gray-100 text-gray-800 dark:bg-gray-900/30 dark:text-gray-400';
+      default:
+        return 'bg-gray-100 text-gray-800 dark:bg-gray-900/30 dark:text-gray-400';
+    }
+  }
+
   return (
     <div className={`${styles.botLogCardContainer}`}>
       {/* 头部标签，时间 */}
       <div className={`${styles.cardTitleContainer}`}>
         <div className={`flex flex-row gap-2 items-center`}>
-          <div className={`${styles.tag}`}>{botLog.level}</div>
+          <div
+            className={`px-2 py-1 rounded text-xs font-medium uppercase ${getLevelStyles(
+              botLog.level,
+            )}`}
+          >
+            {botLog.level}
+          </div>
           {botLog.message_session_id && (
             <div
               className={`${styles.tag} ${styles.chatTag}`}

web/src/app/home/bots/components/bot-log/view/BotLogListComponent.tsx

@@ -1,11 +1,19 @@
 'use client';
 
 import { BotLogManager } from '@/app/home/bots/components/bot-log/BotLogManager';
-import { useCallback, useEffect, useRef, useState } from 'react';
+import { useCallback, useEffect, useRef, useState, useMemo } from 'react';
 import { BotLog } from '@/app/infra/http/requestParam/bots/GetBotLogsResponse';
 import { BotLogCard } from '@/app/home/bots/components/bot-log/view/BotLogCard';
 import styles from './botLog.module.css';
 import { Switch } from '@/components/ui/switch';
+import {
+  Popover,
+  PopoverContent,
+  PopoverTrigger,
+} from '@/components/ui/popover';
+import { Button } from '@/components/ui/button';
+import { Checkbox } from '@/components/ui/checkbox';
+import { ChevronDownIcon } from 'lucide-react';
 import { debounce } from 'lodash';
 import { useTranslation } from 'react-i18next';
 
@@ -14,9 +22,21 @@ export function BotLogListComponent({ botId }: { botId: string }) {
   const manager = useRef(new BotLogManager(botId)).current;
   const [botLogList, setBotLogList] = useState<BotLog[]>([]);
   const [autoFlush, setAutoFlush] = useState(true);
+  const [selectedLevels, setSelectedLevels] = useState<string[]>([
+    'info',
+    'warning',
+    'error',
+  ]);
   const listContainerRef = useRef<HTMLDivElement>(null);
   const botLogListRef = useRef<BotLog[]>(botLogList);
 
+  const logLevels = [
+    { value: 'error', label: 'ERROR' },
+    { value: 'warning', label: 'WARNING' },
+    { value: 'info', label: 'INFO' },
+    { value: 'debug', label: 'DEBUG' },
+  ];
+
   useEffect(() => {
     initComponent();
     return () => {
@@ -28,6 +48,42 @@ export function BotLogListComponent({ botId }: { botId: string }) {
     botLogListRef.current = botLogList;
   }, [botLogList]);
 
+  // 根据级别过滤日志
+  const filteredLogs = useMemo(() => {
+    if (selectedLevels.length === 0) {
+      return botLogList;
+    }
+    return botLogList.filter((log) => selectedLevels.includes(log.level));
+  }, [botLogList, selectedLevels]);
+
+  const handleLevelToggle = (levelValue: string) => {
+    setSelectedLevels((prev) => {
+      if (prev.includes(levelValue)) {
+        return prev.filter((l) => l !== levelValue);
+      } else {
+        return [...prev, levelValue];
+      }
+    });
+  };
+
+  const getDisplayText = () => {
+    if (selectedLevels.length === 0) {
+      return t('bots.selectLevel');
+    }
+    if (selectedLevels.length === logLevels.length) {
+      return t('bots.allLevels');
+    }
+    // 如果选中3个或以上，显示数量
+    if (selectedLevels.length >= 3) {
+      return `${selectedLevels.length} ${t('bots.levelsSelected')}`;
+    }
+    // 显示选中级别的标签（大写形式）
+    return logLevels
+      .filter((level) => selectedLevels.includes(level.value))
+      .map((level) => level.label)
+      .join(', ');
+  };
+
   // 观测自动刷新状态
   useEffect(() => {
     if (autoFlush) {
@@ -116,9 +172,43 @@ export function BotLogListComponent({ botId }: { botId: string }) {
       <div className={`${styles.listHeader}`}>
         <div className={'mr-2'}>{t('bots.enableAutoRefresh')}</div>
         <Switch checked={autoFlush} onCheckedChange={(e) => setAutoFlush(e)} />
+        <div className={'ml-4 mr-2'}>{t('bots.logLevel')}</div>
+        <Popover>
+          <PopoverTrigger asChild>
+            <Button
+              variant="outline"
+              size="sm"
+              className="w-[180px] flex items-center justify-between"
+            >
+              <span className="text-sm truncate flex-1 text-left">
+                {getDisplayText()}
+              </span>
+              <ChevronDownIcon className="ml-2 h-4 w-4 flex-shrink-0" />
+            </Button>
+          </PopoverTrigger>
+          <PopoverContent className="w-[180px] p-2">
+            <div className="flex flex-col gap-2">
+              {logLevels.map((level) => (
+                <div key={level.value} className="flex items-center space-x-2">
+                  <Checkbox
+                    id={level.value}
+                    checked={selectedLevels.includes(level.value)}
+                    onCheckedChange={() => handleLevelToggle(level.value)}
+                  />
+                  <label
+                    htmlFor={level.value}
+                    className="text-sm font-medium leading-none peer-disabled:cursor-not-allowed peer-disabled:opacity-70 cursor-pointer"
+                  >
+                    {level.label}
+                  </label>
+                </div>
+              ))}
+            </div>
+          </PopoverContent>
+        </Popover>
       </div>
 
-      {botLogList.map((botLog) => {
+      {filteredLogs.map((botLog) => {
         return <BotLogCard botLog={botLog} key={botLog.seq_id} />;
       })}
     </div>

web/src/i18n/locales/en-US.ts

@@ -192,6 +192,10 @@ const enUS = {
     webhookUrlCopied: 'Webhook URL copied',
     webhookUrlHint:
       'Click the input to select all, then press Ctrl+C (Mac: Cmd+C) to copy, or click the button',
+    logLevel: 'Log Level',
+    allLevels: 'All Levels',
+    selectLevel: 'Select Level',
+    levelsSelected: 'levels selected',
   },
   plugins: {
     title: 'Extensions',

web/src/i18n/locales/ja-JP.ts

@@ -194,6 +194,10 @@ const jaJP = {
     webhookUrlCopied: 'Webhook URL をコピーしました',
     webhookUrlHint:
       '入力ボックスをクリックして全選択し、Ctrl+C (Mac: Cmd+C) でコピーするか、右側のボタンをクリックしてください',
+    logLevel: 'ログレベル',
+    allLevels: 'すべてのレベル',
+    selectLevel: 'レベルを選択',
+    levelsSelected: 'レベル選択済み',
   },
   plugins: {
     title: '拡張機能',

web/src/i18n/locales/zh-Hans.ts

@@ -187,6 +187,10 @@ const zhHans = {
     webhookUrlCopied: 'Webhook 地址已复制',
     webhookUrlHint:
       '点击输入框自动全选，然后按 Ctrl+C (Mac: Cmd+C) 复制，或点击右侧按钮',
+    logLevel: '日志级别',
+    allLevels: '全部级别',
+    selectLevel: '选择级别',
+    levelsSelected: '个级别已选',
   },
   plugins: {
     title: '插件扩展',

web/src/i18n/locales/zh-Hant.ts

@@ -187,6 +187,10 @@ const zhHant = {
     webhookUrlCopied: 'Webhook 位址已複製',
     webhookUrlHint:
       '點擊輸入框自動全選，然後按 Ctrl+C (Mac: Cmd+C) 複製，或點擊右側按鈕',
+    logLevel: '日誌級別',
+    allLevels: '全部級別',
+    selectLevel: '選擇級別',
+    levelsSelected: '個級別已選',
   },
   plugins: {
     title: '外掛擴展',