chore: update Python versions in CI workflow

* fix: Incomplete JSON data returned by N8N streaming data causes the loss of chunks.

.dockerignore

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

.github/workflows/build-docker-image.yml

@@ -3,7 +3,6 @@ on:
   ## 发布release的时候会自动构建
   release:
     types: [published]
-  workflow_dispatch:
 jobs:
   publish-docker-image:
     runs-on: ubuntu-latest
@@ -42,7 +41,7 @@ jobs:
         run: docker buildx create --name mybuilder --use
       - name: Build for Release # only relase, exlude pre-release
         if: ${{ github.event.release.prerelease == false }}
-        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
       - name: Build for Pre-release # no update for latest tag
         if: ${{ github.event.release.prerelease == true }}
-        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push
+        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.github/workflows/run-tests.yml

@@ -26,7 +26,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.11', '3.12', '3.13']
       fail-fast: false
 
     steps:

AGENTS.md

@@ -8,16 +8,17 @@ LangBot is a open-source LLM native instant messaging bot development platform,
 
 LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
 
-- `./pkg`: The core python package of the project backend.
-    - `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
-    - `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
-    - `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
-    - `./pkg/api`: The api module of the project, containing the http api controllers and services.
-    - `./pkg/plugin`: LangBot bridge for connecting with plugin system.
-- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
-- `./templates`: Templates of config files, components, etc.
-- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
-- `./docker`: docker-compose deployment files.
+- `./src/langbot`: The main python package of the project, below are the main modules in this package:
+    - `./pkg`: The core python package of the project backend.
+        - `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
+        - `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
+        - `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
+        - `./pkg/api`: The api module of the project, containing the http api controllers and services.
+        - `./pkg/plugin`: LangBot bridge for connecting with plugin system.
+    - `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
+    - `./templates`: Templates of config files, components, etc.
+    - `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
+    - `./docker`: docker-compose deployment files.
 
 ## Backend Development
 

Dockerfile

@@ -20,4 +20,4 @@ RUN apt update \
     && uv sync \
     && touch /.dockerenv
 
-CMD [ "uv", "run", "main.py" ]
+CMD [ "uv", "run", "--no-sync", "main.py" ]

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

@@ -7,7 +7,6 @@ services:
   langbot_plugin_runtime:
     image: rockchin/langbot:latest
     container_name: langbot_plugin_runtime
-    platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data/plugins:/app/data/plugins
     ports:
@@ -22,7 +21,6 @@ services:
   langbot:
     image: rockchin/langbot:latest
     container_name: langbot
-    platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data:/app/data
     restart: on-failure

docs/SEEKDB_INTEGRATION.md

@@ -0,0 +1,259 @@
+# SeekDB Vector Database Integration
+
+This document describes how to use OceanBase SeekDB as the vector database backend for LangBot's knowledge base feature.
+
+## What is SeekDB?
+
+**OceanBase SeekDB** is an AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows. It's developed by OceanBase and released under Apache 2.0 license.
+
+### Key Features
+
+- **Hybrid Search**: Combine vector search, full-text search and relational query in a single statement
+- **Multi-Model Support**: Support relational, vector, text, JSON and GIS in a single engine
+- **Lightweight**: Requires as little as 1 CPU core and 2 GB of memory
+- **Multiple Deployment Modes**: Supports both embedded mode and client/server mode
+- **MySQL Compatible**: Powered by OceanBase engine with full ACID compliance and MySQL compatibility
+
+## Installation
+
+SeekDB support is automatically included when you install LangBot. The required dependency `pyseekdb` is listed in `pyproject.toml`.
+
+If you need to install it manually:
+
+```bash
+pip install pyseekdb
+```
+
+## ⚠️ Platform Compatibility
+
+### Embedded Mode
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| Linux | ✅ Supported | Full embedded mode support via `pylibseekdb` |
+| macOS | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
+| Windows | ❌ Not Supported | `pylibseekdb` is Linux-only; use server mode instead |
+
+**Important**: Embedded mode requires the `pylibseekdb` library, which is only available on Linux. If you're on macOS or Windows, you must use server mode.
+
+### Server Mode (Docker)
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| Linux | ✅ Supported | Full Docker support |
+| macOS | ⚠️ Known Issue | Docker container initialization failure - [See Issue #36](https://github.com/oceanbase/seekdb/issues/36) |
+| Windows | ⚠️ Untested | Should work but not yet tested |
+
+**macOS Users**: Currently, SeekDB Docker containers have an initialization issue on macOS ([oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36)). Until this is resolved, we recommend:
+- Using ChromaDB or Qdrant as alternatives
+- Connecting to a remote SeekDB server on Linux if available
+
+### Server Mode (Remote Connection)
+
+| Platform | Status | Notes |
+|----------|--------|-------|
+| All Platforms | ✅ Supported | Connect to SeekDB running on a remote Linux server |
+
+**Recommendation for macOS/Windows users**: Deploy SeekDB on a Linux server and connect via server mode configuration.
+
+## Configuration
+
+### Embedded Mode (Recommended for Development)
+
+Embedded mode runs SeekDB directly within the LangBot process, storing data locally. This is the simplest setup and requires no external services.
+
+Edit your `config.yaml`:
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: embedded
+    path: './data/seekdb'  # Path to store SeekDB data
+    database: 'langbot'    # Database name
+```
+
+### Server Mode (For Production)
+
+Server mode connects to a remote SeekDB server or OceanBase server. This is recommended for production deployments.
+
+#### SeekDB Server
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'localhost'
+    port: 2881
+    database: 'langbot'
+    user: 'root'
+    password: ''  # Can also use SEEKDB_PASSWORD env var
+```
+
+#### OceanBase Server
+
+If you're using OceanBase with seekdb capabilities:
+
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'localhost'
+    port: 2881
+    tenant: 'sys'        # OceanBase tenant name
+    database: 'langbot'
+    user: 'root'
+    password: ''
+```
+
+## Configuration Parameters
+
+| Parameter  | Required | Default      | Description |
+|-----------|----------|--------------|-------------|
+| `mode`    | No       | `embedded`   | Deployment mode: `embedded` or `server` |
+| `path`    | No       | `./data/seekdb` | Data directory for embedded mode |
+| `database` | No      | `langbot`    | Database name |
+| `host`    | No       | `localhost`  | Server host (server mode only) |
+| `port`    | No       | `2881`       | Server port (server mode only) |
+| `user`    | No       | `root`       | Username (server mode only) |
+| `password` | No      | `''`         | Password (server mode only) |
+| `tenant`  | No       | None         | OceanBase tenant (optional, server mode only) |
+
+## Usage
+
+Once configured, SeekDB will be used automatically for all knowledge base operations in LangBot:
+
+1. **Creating Knowledge Bases**: Vectors will be stored in SeekDB collections
+2. **Adding Documents**: Document embeddings will be indexed in SeekDB
+3. **Searching**: Vector similarity search will use SeekDB's efficient indexing
+4. **Deleting**: Document removal will delete vectors from SeekDB
+
+No code changes are required - just update your configuration!
+
+## Architecture Details
+
+### Implementation
+
+The SeekDB adapter is implemented in `src/langbot/pkg/vector/vdbs/seekdb.py` and follows the same `VectorDatabase` interface as Chroma and Qdrant adapters.
+
+Key methods:
+- `add_embeddings()`: Add vectors with metadata to a collection
+- `search()`: Perform vector similarity search
+- `delete_by_file_id()`: Delete vectors by file ID metadata
+- `get_or_create_collection()`: Manage collections
+- `delete_collection()`: Remove entire collections
+
+### Vector Storage
+
+- Collections are created with HNSW (Hierarchical Navigable Small World) index
+- Default distance metric: Cosine similarity
+- Default vector dimension: 384 (adjusts automatically based on embeddings)
+- Metadata is stored alongside vectors for filtering
+
+## Advantages Over Other Vector Databases
+
+### vs. ChromaDB
+- ✅ Better MySQL compatibility
+- ✅ Hybrid search capabilities (vector + full-text + SQL)
+- ✅ Production-grade distributed mode support
+- ✅ Lightweight embedded mode
+
+### vs. Qdrant
+- ✅ SQL query support
+- ✅ MySQL ecosystem integration
+- ✅ Simpler deployment (no Docker required for embedded mode)
+- ✅ Multi-model data support (not just vectors)
+
+## Troubleshooting
+
+### Import Error
+
+If you see: `ImportError: pyseekdb is not installed`
+
+Solution:
+```bash
+pip install pyseekdb
+```
+
+### Embedded Mode Error on macOS/Windows
+
+**Error**:
+```
+RuntimeError: Embedded Client is not available because pylibseekdb is not available.
+Please install pylibseekdb (Linux only) or use RemoteServerClient (host/port) instead.
+```
+
+**Cause**: `pylibseekdb` is only available on Linux platforms.
+
+**Solution**: Use server mode instead:
+1. Deploy SeekDB on a Linux server or VM
+2. Configure LangBot to use server mode:
+```yaml
+vdb:
+  use: seekdb
+  seekdb:
+    mode: server
+    host: 'your-seekdb-server-ip'
+    port: 2881
+    database: 'langbot'
+    user: 'root'
+    password: ''
+```
+
+**Alternative**: Use ChromaDB or Qdrant, which work on all platforms:
+```yaml
+vdb:
+  use: chroma  # or qdrant
+```
+
+### Docker Container Fails on macOS
+
+**Symptoms**:
+```bash
+docker run -d -p 2881:2881 oceanbase/seekdb:latest
+# Container exits immediately with code 30
+```
+
+**Error in logs**:
+```
+[ERROR] Code: Agent.SeekDB.Not.Exists
+Message: initialize failed: init agent failed: SeekDB not exists in current directory.
+```
+
+**Cause**: This is a known issue with SeekDB Docker containers on macOS. See [oceanbase/seekdb#36](https://github.com/oceanbase/seekdb/issues/36).
+
+**Status**: Under investigation by OceanBase team.
+
+**Workaround Options**:
+1. **Use alternatives**: ChromaDB or Qdrant work perfectly on macOS
+2. **Remote server**: Deploy SeekDB on a Linux server and connect remotely
+3. **Wait for fix**: Monitor the GitHub issue for updates
+
+### Connection Error (Server Mode)
+
+If SeekDB server is not reachable, check:
+1. Server is running: `ps aux | grep observer`
+2. Port is accessible: `nc -zv localhost 2881`
+3. Credentials are correct in config
+4. Firewall allows connections on port 2881
+
+### Performance Issues
+
+For large datasets:
+- Use server mode instead of embedded mode
+- Ensure adequate memory allocation
+- Consider using OceanBase distributed mode for very large scale
+- Adjust HNSW index parameters if needed
+
+## Resources
+
+- SeekDB GitHub: https://github.com/oceanbase/seekdb
+- pyseekdb SDK: https://github.com/oceanbase/pyseekdb
+- OceanBase Documentation: https://oceanbase.ai
+- LangBot Documentation: https://docs.langbot.app
+
+## License
+
+SeekDB is licensed under Apache License 2.0.

pyproject.toml

@@ -1,10 +1,10 @@
 [project]
 name = "langbot"
-version = "4.6.3"
+version = "4.6.5"
 description = "Easy-to-use global IM bot platform designed for LLM era"
 readme = "README.md"
 license-files = ["LICENSE"]
-requires-python = ">=3.10.1,<4.0"
+requires-python = ">=3.11,<4.0"
 dependencies = [
     "aiocqhttp>=1.4.4",
     "aiofiles>=24.1.0",
@@ -63,7 +63,8 @@ dependencies = [
     "langchain-text-splitters>=0.0.1",
     "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
-    "langbot-plugin==0.2.1",
+    "pyseekdb>=0.1.0",
+    "langbot-plugin==0.2.4",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
 """LangBot - Easy-to-use global IM bot platform designed for LLM era"""
 
-__version__ = '4.6.3'
+__version__ = '4.6.5'

src/langbot/libs/dingtalk_api/api.py

@@ -1,8 +1,11 @@
+import asyncio
 import base64
 import json
 import time
+import urllib.parse
 from typing import Callable
 import dingtalk_stream  # type: ignore
+import websockets
 from .EchoHandler import EchoTextHandler
 from .dingtalkevent import DingTalkEvent
 import httpx
@@ -36,6 +39,7 @@ class DingTalkClient:
         self.access_token_expiry_time = ''
         self.markdown_card = markdown_card
         self.logger = logger
+        self._stopped = False  # Flag to control the event loop
 
     async def get_access_token(self):
         url = 'https://api.dingtalk.com/v1.0/oauth2/accessToken'
@@ -170,6 +174,9 @@ class DingTalkClient:
         """
         处理消息事件。
         """
+        # Skip message handling if stopped
+        if self._stopped:
+            return
         msg_type = event.conversation
         if msg_type in self._message_handlers:
             for handler in self._message_handlers[msg_type]:
@@ -378,4 +385,70 @@ class DingTalkClient:
 
     async def start(self):
         """启动 WebSocket 连接，监听消息"""
-        await self.client.start()
+        self._stopped = False
+        self.client.pre_start()
+
+        while not self._stopped:
+            try:
+                connection = self.client.open_connection()
+
+                if not connection:
+                    if self.logger:
+                        await self.logger.error('DingTalk: open connection failed')
+                    await asyncio.sleep(10)
+                    continue
+
+                uri = '%s?ticket=%s' % (connection['endpoint'], urllib.parse.quote_plus(connection['ticket']))
+                async with websockets.connect(uri) as websocket:
+                    self.client.websocket = websocket
+                    keepalive_task = asyncio.create_task(self._keepalive(websocket))
+                    try:
+                        async for raw_message in websocket:
+                            if self._stopped:
+                                break
+                            json_message = json.loads(raw_message)
+                            asyncio.create_task(self.client.background_task(json_message))
+                    finally:
+                        keepalive_task.cancel()
+                        try:
+                            await keepalive_task
+                        except asyncio.CancelledError:
+                            pass
+            except asyncio.CancelledError:
+                # Properly exit when task is cancelled
+                break
+            except websockets.exceptions.ConnectionClosedError as e:
+                if self._stopped:
+                    break
+                if self.logger:
+                    await self.logger.error(f'DingTalk: connection closed, reconnecting... error={e}')
+                await asyncio.sleep(5)
+                continue
+            except Exception as e:
+                if self._stopped:
+                    break
+                if self.logger:
+                    await self.logger.error(f'DingTalk: unknown exception, reconnecting... error={e}')
+                await asyncio.sleep(3)
+                continue
+
+    async def _keepalive(self, ws, ping_interval=60):
+        """Keep WebSocket connection alive"""
+        while not self._stopped:
+            await asyncio.sleep(ping_interval)
+            try:
+                await ws.ping()
+            except websockets.exceptions.ConnectionClosed:
+                break
+
+    async def stop(self):
+        """停止 WebSocket 连接"""
+        self._stopped = True
+        # Close WebSocket connection if exists
+        if self.client.websocket:
+            try:
+                await self.client.websocket.close()
+            except Exception:
+                pass
+        # Clear message handlers to prevent stale callbacks
+        self._message_handlers = {'example': []}

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

@@ -49,6 +49,14 @@ class PipelinesRouterGroup(group.RouterGroup):
 
                 return self.success()
 
+        @self.route('/<pipeline_uuid>/copy', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
+        async def _(pipeline_uuid: str) -> str:
+            try:
+                new_uuid = await self.ap.pipeline_service.copy_pipeline(pipeline_uuid)
+                return self.success(data={'uuid': new_uuid})
+            except ValueError as e:
+                return self.http_status(404, -1, str(e))
+
         @self.route(
             '/<pipeline_uuid>/extensions', methods=['GET', 'PUT'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
         )

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

@@ -23,6 +23,9 @@ class SystemRouterGroup(group.RouterGroup):
                         if 'cloud_service_url' in self.ap.instance_config.data.get('plugin', {})
                         else 'https://space.langbot.app'
                     ),
+                    'allow_change_password': self.ap.instance_config.data.get('system', {}).get(
+                        'allow_change_password', True
+                    ),
                 }
             )
 

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

@@ -70,6 +70,13 @@ class UserRouterGroup(group.RouterGroup):
 
         @self.route('/change-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
         async def _(user_email: str) -> str:
+            # Check if password change is allowed
+            allow_change_password = self.ap.instance_config.data.get('system', {}).get(
+                'allow_change_password', True
+            )
+            if not allow_change_password:
+                return self.http_status(403, -1, 'Password change is disabled')
+
             json_data = await quart.request.json
 
             current_password = json_data['current_password']

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/api/http/service/pipeline.py

@@ -151,6 +151,52 @@ class PipelineService:
         )
         await self.ap.pipeline_mgr.remove_pipeline(pipeline_uuid)
 
+    async def copy_pipeline(self, pipeline_uuid: str) -> str:
+        """Copy a pipeline with all its configurations"""
+        # Get the original pipeline
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
+                persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid
+            )
+        )
+
+        original_pipeline = result.first()
+        if original_pipeline is None:
+            raise ValueError(f'Pipeline {pipeline_uuid} not found')
+
+        # Create new pipeline data
+        new_uuid = str(uuid.uuid4())
+        new_pipeline_data = {
+            'uuid': new_uuid,
+            'name': f'{original_pipeline.name} (Copy)',
+            'description': original_pipeline.description,
+            'for_version': self.ap.ver_mgr.get_current_version(),
+            'stages': original_pipeline.stages.copy() if original_pipeline.stages else default_stage_order.copy(),
+            'config': original_pipeline.config.copy() if original_pipeline.config else {},
+            'is_default': False,
+            'extensions_preferences': (
+                original_pipeline.extensions_preferences.copy()
+                if original_pipeline.extensions_preferences
+                else {
+                    'enable_all_plugins': True,
+                    'enable_all_mcp_servers': True,
+                    'plugins': [],
+                    'mcp_servers': [],
+                }
+            ),
+        }
+
+        # Insert the new pipeline
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.insert(persistence_pipeline.LegacyPipeline).values(**new_pipeline_data)
+        )
+
+        # Load the new pipeline
+        pipeline = await self.get_pipeline(new_uuid)
+        await self.ap.pipeline_mgr.load_pipeline(pipeline)
+
+        return new_uuid
+
     async def update_pipeline_extensions(
         self,
         pipeline_uuid: str,

src/langbot/pkg/core/bootutils/log.py

@@ -1,4 +1,5 @@
 import logging
+import logging.handlers
 import sys
 import time
 
@@ -15,6 +16,10 @@ log_colors_config = {
     'CRITICAL': 'cyan',
 }
 
+# Log rotation configuration to prevent unbounded log file growth
+LOG_FILE_MAX_BYTES = 10 * 1024 * 1024  # 10MB per file
+LOG_FILE_BACKUP_COUNT = 5  # Keep 5 backup files (total ~50MB max)
+
 
 async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.Logger:
     # Remove all existing loggers
@@ -43,9 +48,17 @@ async def init_logging(extra_handlers: list[logging.Handler] = None) -> logging.
     # stream_handler.setFormatter(color_formatter)
     stream_handler.stream = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=1)
 
+    # Use RotatingFileHandler to prevent unbounded log file growth
+    rotating_file_handler = logging.handlers.RotatingFileHandler(
+        log_file_name,
+        encoding='utf-8',
+        maxBytes=LOG_FILE_MAX_BYTES,
+        backupCount=LOG_FILE_BACKUP_COUNT,
+    )
+
     log_handlers: list[logging.Handler] = [
         stream_handler,
-        logging.FileHandler(log_file_name, encoding='utf-8'),
+        rotating_file_handler,
     ]
     log_handlers += extra_handlers if extra_handlers is not None else []
 

src/langbot/pkg/pipeline/controller.py

@@ -33,11 +33,14 @@ class Controller:
 
                     for query in queries:
                         session = await self.ap.sess_mgr.get_session(query)
-                        self.ap.logger.debug(f'Checking query {query} session {session}')
+                        # Debug logging removed from tight loop to prevent excessive log generation
+                        # that can cause memory overflow in high-traffic scenarios
 
                         if not session._semaphore.locked():
                             selected_query = query
                             await session._semaphore.acquire()
+                            # Only log when actually selecting a query
+                            self.ap.logger.debug(f'Selected query {query.query_id} for processing')
 
                             break
 

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

@@ -14,6 +14,7 @@ from ....utils import importutil
 from ....provider import runners
 import langbot_plugin.api.entities.builtin.provider.session as provider_session
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
+import langbot_plugin.api.entities.builtin.provider.message as provider_message
 
 
 importutil.import_modules_in_pkg(runners)
@@ -61,8 +62,14 @@ class ChatMessageHandler(handler.MessageHandler):
                 yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
         else:
             if event_ctx.event.user_message_alter is not None:
-                # if isinstance(event_ctx.event, str):  # 现在暂时不考虑多模态alter
-                query.user_message.content = event_ctx.event.user_message_alter
+                if isinstance(event_ctx.event.user_message_alter, list):
+                    query.user_message.content = event_ctx.event.user_message_alter
+                elif isinstance(event_ctx.event.user_message_alter, str):
+                    query.user_message.content = [
+                        provider_message.ContentElement.from_text(event_ctx.event.user_message_alter)
+                    ]
+                elif isinstance(event_ctx.event.user_message_alter, provider_message.ContentElement):
+                    query.user_message.content = [event_ctx.event.user_message_alter]
 
             text_length = 0
             try:
@@ -79,6 +86,7 @@ class ChatMessageHandler(handler.MessageHandler):
                     raise ValueError(f'Request Runner not found: {query.pipeline_config["ai"]["runner"]["runner"]}')
                 if is_stream:
                     resp_message_id = uuid.uuid4()
+                    chunk_count = 0  # Track streaming chunks to reduce excessive logging
 
                     async for result in runner.run(query):
                         result.resp_message_id = str(resp_message_id)
@@ -91,15 +99,30 @@ 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'Conversation({query.query_id}) Streaming Response: {self.cut_str(result.readable_str())}'
-                        )
+
+                        chunk_count += 1
+                        # Only log every 10th chunk to reduce excessive logging during streaming
+                        # This prevents memory overflow from thousands of log entries per conversation
+                        # First chunk uses INFO level to confirm connection establishment
+                        if chunk_count == 1:
+                            self.ap.logger.info(
+                                f'Conversation({query.query_id}) Streaming started: {self.cut_str(result.readable_str())}'
+                            )
+                        elif chunk_count % 10 == 0:
+                            self.ap.logger.debug(
+                                f'Conversation({query.query_id}) Streaming chunk {chunk_count}: {self.cut_str(result.readable_str())}'
+                            )
 
                         if result.content is not None:
                             text_length += len(result.content)
 
                         yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
 
+                    # Log final summary after streaming completes
+                    self.ap.logger.info(
+                        f'Conversation({query.query_id}) Streaming completed: {chunk_count} chunks, {text_length} chars'
+                    )
+
                 else:
                     async for result in runner.run(query):
                         query.resp_messages.append(result)

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

@@ -31,4 +31,8 @@ class AtBotRule(rule_model.GroupRespondRule):
         remove_at(message_chain)
         remove_at(message_chain)  # 回复消息时会at两次，检查并删除重复的
 
+        should_respond_at = rule_dict.get('at', None)
+        if should_respond_at is not None:
+            return entities.RuleJudgeResult(matching=found and bool(should_respond_at), replacement=message_chain)
+
         return entities.RuleJudgeResult(matching=found, replacement=message_chain)

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

@@ -260,7 +260,8 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         await self.bot.start()
 
     async def kill(self) -> bool:
-        return False
+        await self.bot.stop()
+        return True
 
     async def is_muted(self) -> bool:
         return False

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

@@ -9,9 +9,13 @@ import re
 import base64
 import uuid
 import json
+import time
 import datetime
 import hashlib
 from Crypto.Cipher import AES
+import tempfile
+import os
+import mimetypes
 
 import aiohttp
 import lark_oapi.ws.exception
@@ -19,6 +23,8 @@ import quart
 from lark_oapi.api.im.v1 import *
 import pydantic
 from lark_oapi.api.cardkit.v1 import *
+from lark_oapi.api.auth.v3 import *
+from lark_oapi.core.model import *
 
 import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
@@ -238,6 +244,7 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
 
         lb_msg_list.append(platform_message.Source(id=message.message_id, time=msg_create_time))
 
+
         if message.message_type == 'text':
             element_list = []
 
@@ -301,6 +308,10 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             message_content['content'] = [
                 {'tag': 'file', 'file_key': message_content['file_key'], 'file_name': message_content['file_name']}
             ]
+        elif message.message_type == 'audio':
+            message_content['content'] = [
+                {'tag': 'audio', 'file_key': message_content['file_key'], "duration": message_content.get('duration',0)}
+            ]
 
         for ele in message_content['content']:
             if ele['tag'] == 'text':
@@ -331,6 +342,60 @@ 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'] == 'audio':
+                file_key = ele['file_key']
+                duration = ele['duration']
+
+                # Download audio file
+                request: GetMessageResourceRequest = (
+                    GetMessageResourceRequest.builder()
+                    .message_id(message.message_id)
+                    .file_key(file_key)
+                    .type('file')
+                    .build()
+                )
+
+                try:
+                    response: GetMessageResourceResponse = await api_client.im.v1.message_resource.aget(request)
+
+                    if not response.success():
+                        print(f'Failed to download audio: code: {response.code}, msg: {response.msg}')
+                        lb_msg_list.append(platform_message.Plain(text='[Audio file download failed]'))
+                        return platform_message.MessageChain(lb_msg_list)
+
+                    # Read audio bytes
+                    audio_bytes = response.file.read()
+                    audio_base64 = base64.b64encode(audio_bytes).decode()
+
+
+                    # Get content type from response headers
+                    content_type = response.raw.headers.get('content-type', 'audio/mpeg')
+
+
+
+                    mime_main = content_type.split(';')[0].strip()
+                    ext = mimetypes.guess_extension(mime_main) or '.bin'
+                    temp_dir = tempfile.gettempdir()
+                    temp_file_path = os.path.join(temp_dir, f'lark_audio_{file_key}{ext}')
+
+                    with open(temp_file_path, 'wb') as f:
+                        f.write(audio_bytes)
+
+                    # Create Voice message: prefer path/url + length, include base64 as optional data URI
+                    lb_msg_list.append(
+                        platform_message.Voice(
+                            voice_id=file_key,
+                            url=f'file://{temp_file_path}',
+                            path=temp_file_path,
+                            base64=f'data:{content_type};base64,{audio_base64}',
+                            length=(duration // 1000) if duration else None,
+                        )
+                    )
+                except Exception as e:
+                    print(f'Error downloading audio: {e}')
+                    traceback.print_exc()
+                    lb_msg_list.append(platform_message.Plain(text='[Audio file download error]'))
+
             elif ele['tag'] == 'file':
                 file_key = ele['file_key']
                 file_name = ele['file_name']
@@ -353,12 +418,42 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 file_bytes = response.file.read()
                 file_base64 = base64.b64encode(file_bytes).decode()
 
+
                 file_format = response.raw.headers['content-type']
 
+                file_size = len(file_bytes)
+
+                # Determine extension from content-type if possible
+                content_type = response.raw.headers.get('content-type', '')
+                mime_main = content_type.split(';')[0].strip() if content_type else ''
+                ext = mimetypes.guess_extension(mime_main) or ''
+
+                # Ensure a safe filename (avoid path components)
+                safe_name = os.path.basename(file_name).replace('/', '_').replace('\\', '_')
+                if ext and not safe_name.lower().endswith(ext.lower()):
+                    filename_with_ext = f'{safe_name}{ext}'
+                else:
+                    filename_with_ext = safe_name
+
+                temp_dir = tempfile.gettempdir()
+                temp_file_path = os.path.join(temp_dir, f'lark_{file_key}_{filename_with_ext}')
+
+                with open(temp_file_path, 'wb') as f:
+                    f.write(file_bytes)
+
+                # Create File message with local path and file:// URL
                 lb_msg_list.append(
-                    platform_message.File(base64=f'data:{file_format};base64,{file_base64}', name=file_name)
+                    platform_message.File(
+                        id=file_key,
+                        name=file_name,
+                        size=file_size,
+                        url=f'file://{temp_file_path}',
+                        path=temp_file_path,
+                        base64=f'data:{file_format};base64,{file_base64}',  # not including base64 by default to save memory; can be added if needed
+                    )
                 )
 
+
         return platform_message.MessageChain(lb_msg_list)
 
 
@@ -384,6 +479,7 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
                 ),
                 message_chain=message_chain,
                 time=event.event.message.create_time,
+                source_platform_object=event,
             )
         elif event.event.message.chat_type == 'group':
             return platform_events.GroupMessage(
@@ -400,6 +496,7 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
                 ),
                 message_chain=message_chain,
                 time=event.event.message.create_time,
+                source_platform_object=event,
             )
 
 
@@ -416,6 +513,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
     message_converter: LarkMessageConverter = LarkMessageConverter()
     event_converter: LarkEventConverter = LarkEventConverter()
+    cipher: AESCipher
 
     listeners: typing.Dict[
         typing.Type[platform_events.Event],
@@ -427,51 +525,15 @@ 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
+    app_ticket: str = None  # 商店应用用到
+    app_access_token: str = None  # 商店应用用到
+    app_access_token_expire_at: int = None
+    tenant_access_tokens: dict[str, dict[str, str]] = {}  # 租户access_token映射
 
     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)
 
@@ -487,7 +549,9 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         bot_account_id = config['bot_name']
 
         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()
+        api_client = self.build_api_client(config)
+        cipher = AESCipher(config.get('encrypt-key', ''))
+        self.request_app_ticket(api_client, config)
 
         super().__init__(
             config=config,
@@ -500,9 +564,105 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             bot=bot,
             api_client=api_client,
             bot_account_id=bot_account_id,
+            cipher=cipher,
             **kwargs,
         )
 
+    def request_app_ticket(self, api_client, config):
+        app_id = config['app_id']
+        app_secret = config['app_secret']
+        print(f'Requesting app ticket for app_id: {app_id[:3]}***{app_id[-3:]}')
+        if 'isv' == config.get('app_type', 'self'):
+            request: ResendAppTicketRequest = (
+                ResendAppTicketRequest.builder()
+                .request_body(ResendAppTicketRequestBody.builder().app_id(app_id).app_secret(app_secret).build())
+                .build()
+            )
+            response: ResendAppTicketResponse = api_client.auth.v3.app_ticket.resend(request)
+            if not response.success():
+                raise Exception(
+                    f'client.auth.v3.auth.app_ticket_resend 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)}'
+                )
+
+    def request_app_access_token(self):
+        app_id = self.config['app_id']
+        app_secret = self.config['app_secret']
+        if 'isv' == self.config.get('app_type', 'self'):
+            request: CreateAppAccessTokenRequest = (
+                CreateAppAccessTokenRequest.builder()
+                .request_body(
+                    CreateAppAccessTokenRequestBody.builder()
+                    .app_id(app_id)
+                    .app_secret(app_secret)
+                    .app_ticket(self.app_ticket)
+                    .build()
+                )
+                .build()
+            )
+            response: CreateAppAccessTokenResponse = self.api_client.auth.v3.app_access_token.create(request)
+            if not response.success():
+                raise Exception(
+                    f'client.auth.v3.auth.app_access_token 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)}'
+                )
+            content = json.loads(response.raw.content)
+            self.app_access_token = content['app_access_token']
+            self.app_access_token_expire_at = int(time.time()) + content['expire'] - 300
+
+    def get_app_access_token(self):
+        if 'isv' != self.config.get('app_type', 'self'):
+            return None
+        if (
+            self.app_access_token is None
+            or self.app_access_token_expire_at is None
+            or int(time.time()) >= self.app_access_token_expire_at
+        ):
+            self.request_app_access_token()
+        return self.app_access_token
+
+    def request_tenant_access_token(self, tenant_key: str):
+        app_access_token = self.get_app_access_token()
+        if 'isv' == self.config.get('app_type', 'self'):
+            request: CreateTenantAccessTokenRequest = (
+                CreateTenantAccessTokenRequest.builder()
+                .request_body(
+                    CreateTenantAccessTokenRequestBody.builder()
+                    .app_access_token(app_access_token)
+                    .tenant_key(tenant_key)
+                    .build()
+                )
+                .build()
+            )
+            response: CreateTenantAccessTokenResponse = self.api_client.auth.v3.tenant_access_token.create(request)
+            if not response.success():
+                raise Exception(
+                    f'client.auth.v3.auth.tenant_access_token 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)}'
+                )
+            content = json.loads(response.raw.content)
+            tenant_access_token = content['tenant_access_token']
+            expire = content['expire']
+            self.tenant_access_tokens[tenant_key] = {
+                'token': tenant_access_token,
+                'expire_at': int(time.time()) + expire - 300,
+            }
+
+    def get_tenant_access_token(self, tenant_key: str):
+        if tenant_key is None or 'isv' != self.config.get('app_type', 'self'):
+            return None
+        tenant_access_token = self.tenant_access_tokens.get(tenant_key)
+        if tenant_access_token is None or int(time.time()) >= tenant_access_token['expire_at']:
+            self.request_tenant_access_token(tenant_key)
+        return self.tenant_access_tokens.get(tenant_key)['token'] if self.tenant_access_tokens.get(tenant_key) else None
+
+    def build_api_client(self, config):
+        app_id = config['app_id']
+        app_secret = config['app_secret']
+        api_client = lark_oapi.Client.builder().app_id(app_id).app_secret(app_secret).build()
+        if 'isv' == config.get('app_type', 'self'):
+            api_client = (
+                lark_oapi.Client.builder().app_id(app_id).app_secret(app_secret).app_type(lark_oapi.AppType.ISV).build()
+            )
+        return api_client
+
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
         pass
 
@@ -730,9 +890,19 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             )
             .build()
         )
-
+        tenant_key = event.source_platform_object.header.tenant_key if event.source_platform_object else None
+        app_access_token = self.get_app_access_token()
+        tenant_access_token = self.get_tenant_access_token(tenant_key)
+        req_opt: RequestOption = (
+            RequestOption.builder()
+            .app_ticket(self.app_ticket)
+            .tenant_key(tenant_key)
+            .app_access_token(app_access_token)
+            .tenant_access_token(tenant_access_token)
+            .build()
+        )
         # 发起请求
-        response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
+        response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
 
         # 处理失败返回
         if not response.success():
@@ -759,7 +929,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     'content': text_elements,
                 },
             }
-
             request: ReplyMessageRequest = (
                 ReplyMessageRequest.builder()
                 .message_id(message_source.message_chain.message_id)
@@ -774,7 +943,22 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 .build()
             )
 
-            response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
+            tenant_key = (
+                message_source.source_platform_object.header.tenant_key
+                if message_source.source_platform_object
+                else None
+            )
+            app_access_token = self.get_app_access_token()
+            tenant_access_token = self.get_tenant_access_token(tenant_key)
+            req_opt: RequestOption = (
+                RequestOption.builder()
+                .app_ticket(self.app_ticket)
+                .tenant_key(tenant_key)
+                .app_access_token(app_access_token)
+                .tenant_access_token(tenant_access_token)
+                .build()
+            )
+            response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
 
             if not response.success():
                 raise Exception(
@@ -799,7 +983,22 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 .build()
             )
 
-            response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request)
+            tenant_key = (
+                message_source.source_platform_object.header.tenant_key
+                if message_source.source_platform_object
+                else None
+            )
+            app_access_token = self.get_app_access_token()
+            tenant_access_token = self.get_tenant_access_token(tenant_key)
+            req_opt: RequestOption = (
+                RequestOption.builder()
+                .app_ticket(self.app_ticket)
+                .tenant_key(tenant_key)
+                .app_access_token(app_access_token)
+                .tenant_access_token(tenant_access_token)
+                .build()
+            )
+            response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(request, req_opt)
 
             if not response.success():
                 raise Exception(
@@ -853,8 +1052,24 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             if is_final and bot_message.tool_calls is None:
                 # self.seq = 1  # 消息回复结束之后重置seq
                 self.card_id_dict.pop(message_id)  # 清理已经使用过的卡片
+
+            tenant_key = (
+                message_source.source_platform_object.header.tenant_key
+                if message_source.source_platform_object
+                else None
+            )
+            app_access_token = self.get_app_access_token()
+            tenant_access_token = self.get_tenant_access_token(tenant_key)
+            req_opt: RequestOption = (
+                RequestOption.builder()
+                .app_ticket(self.app_ticket)
+                .tenant_key(tenant_key)
+                .app_access_token(app_access_token)
+                .tenant_access_token(tenant_access_token)
+                .build()
+            )
             # 发起请求
-            response: ContentCardElementResponse = self.api_client.cardkit.v1.card_element.content(request)
+            response: ContentCardElementResponse = self.api_client.cardkit.v1.card_element.content(request, req_opt)
 
             # 处理失败返回
             if not response.success():
@@ -884,8 +1099,110 @@ 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
+
+    def get_event_type(self, data):
+        schema = '1.0'
+        if 'schema' in data:
+            schema = data['schema']
+        if '2.0' == schema:
+            return data['header']['event_type']
+        elif 'event' in data:
+            return data['event']['type']
+        else:
+            return data['type']
+
+    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 = self.get_event_type(data)
+            context = EventContext(data)
+            if 'url_verification' == type:
+                # todo 验证verification token
+                return {'challenge': data.get('challenge')}
+            elif 'app_ticket' == type:
+                self.app_ticket = context.event['app_ticket']
+            elif 'im.message.receive_v1' == type:
+                try:
+                    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
+                    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': [[{'tag': 'md', 'text': 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()
+                        )
+                        tenant_key = context.header.tenant_key if context.header else None
+                        app_access_token = self.get_app_access_token()
+                        tenant_access_token = self.get_tenant_access_token(tenant_key)
+                        req_opt: RequestOption = (
+                            RequestOption.builder()
+                            .app_ticket(self.app_ticket)
+                            .tenant_key(tenant_key)
+                            .app_access_token(app_access_token)
+                            .tenant_access_token(tenant_access_token)
+                            .build()
+                        )
+                        response: CreateMessageResponse = self.api_client.im.v1.message.create(request, req_opt)
+
+                        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 as e:
+                    print(f'im.chat.member.bot.added_v1: {e}')
+                    await self.logger.error(f'Error in lark callback: {traceback.format_exc()}')
+
+            return {'code': 200, 'message': 'ok'}
+        except Exception as e:
+            print(f'Error in lark callback: {e}')
+            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:
@@ -900,16 +1217,14 @@ 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(
-                host='0.0.0.0',
-                port=port,
-                shutdown_trigger=shutdown_trigger_placeholder,
-            )
+            await keep_alive()
 
     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 +65,35 @@ spec:
       type: boolean
       required: true
       default: false
+    - name: app_type
+      label:
+        en_US: App Type
+        zh_Hans: 应用类型
+      description:
+        en_US: Default to self-built application, refer to https://open.feishu.cn/document/platform-overveiw/overview
+        zh_Hans: 默认为企业自建应用，参考 https://open.feishu.cn/document/platform-overveiw/overview
+      type: select
+      options:
+        - name: self
+          label:
+            en_US: Self-built Application
+            zh_Hans: 自建应用
+        - name: isv
+          label:
+            en_US: Store Application
+            zh_Hans: 商店应用
+      required: false
+      default: self
+    - 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/websocket_adapter.py

@@ -65,6 +65,10 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
     outbound_message_queue: asyncio.Queue = pydantic.Field(default_factory=asyncio.Queue, exclude=True)
     """后端主动推送消息的队列"""
 
+    # 流式输出开关
+    stream_enabled: bool = pydantic.Field(default=True, exclude=True)
+    """是否启用流式输出"""
+
     def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs):
         super().__init__(
             config=config,
@@ -77,6 +81,7 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
 
         self.bot_account_id = 'websocketbot'
         self.outbound_message_queue = asyncio.Queue()
+        self.stream_enabled = True
 
     async def send_message(
         self,
@@ -212,8 +217,8 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         return message_data.model_dump()
 
     async def is_stream_output_supported(self) -> bool:
-        """WebSocket始终支持流式输出"""
-        return True
+        """根据stream_enabled标志返回是否支持流式输出"""
+        return self.stream_enabled
 
     def register_listener(
         self,
@@ -314,11 +319,16 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
 
         Args:
             connection: WebSocket连接对象
-            message_data: 消息数据
+            message_data: 消息数据，包含:
+                - message: 消息链
+                - stream: 是否启用流式输出 (可选，默认True)
         """
         pipeline_uuid = connection.pipeline_uuid
         session_type = connection.session_type
 
+        # 获取stream参数，默认为True
+        self.stream_enabled = message_data.get('stream', True)
+
         # 选择会话
         use_session = self.websocket_group_session if session_type == 'group' else self.websocket_person_session
 

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

@@ -0,0 +1,8 @@
+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+  <rect width="24" height="24" rx="5" fill="#1E3A5F"/>
+  <path d="M6 12C6 8.68629 8.68629 6 12 6C15.3137 6 18 8.68629 18 12" stroke="#4FC3F7" stroke-width="2" stroke-linecap="round"/>
+  <path d="M18 12C18 15.3137 15.3137 18 12 18C8.68629 18 6 15.3137 6 12" stroke="#81D4FA" stroke-width="2" stroke-linecap="round"/>
+  <circle cx="12" cy="12" r="2" fill="#4FC3F7"/>
+  <circle cx="6" cy="12" r="1.5" fill="#81D4FA"/>
+  <circle cx="18" cy="12" r="1.5" fill="#4FC3F7"/>
+</svg>

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

@@ -0,0 +1,59 @@
+from __future__ import annotations
+
+import typing
+
+from .. import requester
+
+REQUESTER_NAME: str = 'seekdb-embedding'
+
+
+class SeekDBEmbedding(requester.ProviderAPIRequester):
+    """SeekDB built-in embedding requester.
+
+    Uses pyseekdb's local embedding function (all-MiniLM-L6-v2).
+    The base_url config is reserved for future remote embedding support.
+    """
+
+    default_config: dict[str, typing.Any] = {
+        'base_url': '',
+    }
+
+    _embedding_function = None
+
+    async def initialize(self):
+        try:
+            import pyseekdb
+        except ImportError:
+            raise ImportError('pyseekdb is not installed. Install it with: pip install pyseekdb')
+
+        self._embedding_function = pyseekdb.get_default_embedding_function()
+
+    async def invoke_llm(
+        self,
+        query,
+        model: requester.RuntimeLLMModel,
+        messages: typing.List,
+        funcs: typing.List = None,
+        extra_args: dict[str, typing.Any] = {},
+        remove_think: bool = False,
+    ):
+        raise NotImplementedError('SeekDB embedding does not support LLM inference')
+
+    async def invoke_embedding(
+        self,
+        model: requester.RuntimeEmbeddingModel,
+        input_text: typing.List[str],
+        extra_args: dict[str, typing.Any] = {},
+    ) -> typing.List[typing.List[float]]:
+        """Generate embeddings using SeekDB's built-in embedding function."""
+        try:
+            if self._embedding_function is None:
+                await self.initialize()
+
+            if self._embedding_function is None:
+                raise RuntimeError("SeekDB embedding function initialization failed")
+
+            return self._embedding_function(input_text)
+        except Exception as e:
+            from .. import errors
+            raise errors.RequesterError(f'SeekDB embedding failed: {str(e)}')

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

@@ -0,0 +1,21 @@
+apiVersion: v1
+kind: LLMAPIRequester
+metadata:
+  name: seekdb-embedding
+  label:
+    en_US: SeekDB Embedding
+    zh_Hans: SeekDB 嵌入
+  description:
+    en_US: SeekDB Python library built-in embedding model (all-MiniLM-L6-v2), it will take time to download the model file for the first time
+    zh_Hans: 使用来自 SeekDB Python 库的内置嵌入模型 (all-MiniLM-L6-v2)，首次使用时将会花费时间自动下载模型文件
+    ja_JP: SeekDB Python ライブラリの組み込み埋め込みモデル (all-MiniLM-L6-v2) を使用します。初回使用時にモデルファイルのダウンロードに時間がかかります。
+  icon: seekdb.svg
+spec:
+  config: []
+  support_type:
+  - text-embedding
+  provider_category: builtin
+execution:
+  python:
+    path: ./seekdbembed.py
+    attr: SeekDBEmbedding

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

@@ -152,7 +152,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.Message, None]:
         """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
+        cov_id = query.session.using_conversation.uuid or None
         query.variables['conversation_id'] = cov_id
 
         plain_text, upload_files = await self._preprocess_user_message(query)
@@ -218,7 +218,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.Message, None]:
         """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
+        cov_id = query.session.using_conversation.uuid or None
         query.variables['conversation_id'] = cov_id
 
         plain_text, upload_files = await self._preprocess_user_message(query)
@@ -387,7 +387,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
         """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
+        cov_id = query.session.using_conversation.uuid or None
         query.variables['conversation_id'] = cov_id
 
         plain_text, upload_files = await self._preprocess_user_message(query)
@@ -471,7 +471,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.MessageChunk, None]:
         """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
+        cov_id = query.session.using_conversation.uuid or None
         query.variables['conversation_id'] = cov_id
 
         plain_text, upload_files = await self._preprocess_user_message(query)

src/langbot/pkg/provider/runners/n8nsvapi.py

@@ -70,30 +70,88 @@ class N8nServiceAPIRunner(runner.RequestRunner):
 
     async def _process_stream_response(self, response: aiohttp.ClientResponse) -> typing.AsyncGenerator[
         provider_message.Message, None]:
-        """处理流式响应"""
+        """处理流式响应——支持部分 JSON 和多个 JSON 对象在同一 chunk 的情况"""
         full_content = ""
-        message_idx = 0
+        chunk_idx = 0
         is_final = False
-        async for chunk in response.content.iter_chunked(1024):
-            if not chunk:
+        message_idx = 0
+
+        buffer = ""
+        decoder = json.JSONDecoder()
+
+        async for raw_chunk in response.content.iter_chunked(1024):
+            if not raw_chunk:
                 continue
 
             try:
-                data = json.loads(chunk)
-                if data.get('type') == 'item' and 'content' in data:
+                # 将 bytes 解码为字符串（容忍错误）
+                if isinstance(raw_chunk, (bytes, bytearray)):
+                    chunk_str = raw_chunk.decode('utf-8', errors='replace')
+                else:
+                    chunk_str = str(raw_chunk)
+
+                buffer += chunk_str
+
+                # 尝试从 buffer 中循环解析出 JSON 对象（处理多个对象或部分对象）
+                while buffer:
+                    buffer = buffer.lstrip()
+                    if not buffer:
+                        break
+                    try:
+                        obj, idx = decoder.raw_decode(buffer)
+                        buffer = buffer[idx:]
+
+                        if not isinstance(obj, dict):
+                            # 忽略非字典类型的顶级 JSON
+                            continue
+
+                        if obj.get('type') == 'item' and 'content' in obj:
+                            chunk_idx += 1
+                            content = obj['content']
+                            full_content += content
+                        elif obj.get('type') == 'end':
+                            is_final = True
+
+                        if is_final or chunk_idx % 8 == 0:
+                            message_idx += 1
+                            yield provider_message.MessageChunk(
+                                role='assistant',
+                                content=full_content,
+                                is_final=is_final,
+                                msg_sequence=message_idx,
+                            )
+                    except json.JSONDecodeError:
+                        # buffer 末尾可能是一个不完整的 JSON，等待更多数据
+                        break
+            except Exception as e:
+                # 记录解析失败并继续接收后续 chunk
+                try:
+                    preview = chunk_str[:200]
+                except Exception:
+                    preview = '<unavailable>'
+                self.ap.logger.warning(f"Failed to process chunk: {e}; chunk preview: {preview}")
+
+        # 流结束后，尝试解析残余 buffer
+        if buffer:
+            try:
+                buffer = buffer.strip()
+                if buffer:
+                    obj, _ = decoder.raw_decode(buffer)
+                    if isinstance(obj, dict):
+                        if obj.get('type') == 'item' and 'content' in obj:
+                            full_content += obj['content']
+                        elif obj.get('type') == 'end':
+                            is_final = True
                     message_idx += 1
-                    content = data['content']
-                    full_content += content
-                elif data.get('type') == 'end':
-                    is_final = True
-                if is_final or message_idx % 8 == 0:
                     yield provider_message.MessageChunk(
                         role='assistant',
                         content=full_content,
                         is_final=is_final,
+                        msg_sequence=message_idx,
                     )
-            except json.JSONDecodeError:
-                self.ap.logger.warning(f"Failed to parse final JSON line: {response.text()}")
+            except Exception as e:
+                preview = buffer[:200]
+                self.ap.logger.warning(f"Failed to parse remaining buffer: {e}; buffer preview: {preview}")
 
     async def _call_webhook(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
         """调用n8n webhook"""

src/langbot/pkg/utils/image.py

@@ -153,7 +153,9 @@ async def get_qq_image_bytes(image_url: str, query: dict = {}) -> tuple[bytes, s
     ssl_context.check_hostname = False
     ssl_context.verify_mode = ssl.CERT_NONE
     async with aiohttp.ClientSession(trust_env=False) as session:
-        async with session.get(image_url, params=query, ssl=ssl_context) as resp:
+        async with session.get(
+            image_url, params=query, ssl=ssl_context, timeout=aiohttp.ClientTimeout(total=30.0)
+        ) as resp:
             resp.raise_for_status()
             file_bytes = await resp.read()
             content_type = resp.headers.get('Content-Type')

src/langbot/pkg/vector/mgr.py

@@ -4,6 +4,7 @@ from ..core import app
 from .vdb import VectorDatabase
 from .vdbs.chroma import ChromaVectorDatabase
 from .vdbs.qdrant import QdrantVectorDatabase
+from .vdbs.seekdb import SeekDBVectorDatabase
 from .vdbs.milvus import MilvusVectorDatabase
 from .vdbs.pgvector_db import PgVectorDatabase
 
@@ -27,6 +28,9 @@ class VectorDBManager:
             elif vdb_type == 'qdrant':
                 self.vector_db = QdrantVectorDatabase(self.ap)
                 self.ap.logger.info('Initialized Qdrant vector database backend.')
+            elif vdb_type == 'seekdb':
+                self.vector_db = SeekDBVectorDatabase(self.ap)
+                self.ap.logger.info('Initialized SeekDB vector database backend.')
 
             elif vdb_type == 'milvus':
                 # Get Milvus configuration

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

@@ -0,0 +1,7 @@
+"""Vector database implementations for LangBot."""
+
+from .chroma import ChromaVectorDatabase
+from .qdrant import QdrantVectorDatabase
+from .seekdb import SeekDBVectorDatabase
+
+__all__ = ['ChromaVectorDatabase', 'QdrantVectorDatabase', 'SeekDBVectorDatabase']

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

@@ -0,0 +1,252 @@
+from __future__ import annotations
+
+import asyncio
+from typing import Any, Dict, List
+
+import sqlalchemy
+
+from langbot.pkg.core import app
+from langbot.pkg.entity.persistence import model as persistence_model
+from langbot.pkg.vector.vdb import VectorDatabase
+
+try:
+    import pyseekdb
+    from pyseekdb import HNSWConfiguration
+
+    SEEKDB_AVAILABLE = True
+except ImportError:
+    SEEKDB_AVAILABLE = False
+
+SEEKDB_EMBEDDING_MODEL_UUID = 'seekdb-builtin-embedding'
+SEEKDB_EMBEDDING_REQUESTER = 'seekdb-embedding'
+
+
+class SeekDBVectorDatabase(VectorDatabase):
+    """SeekDB vector database adapter for LangBot.
+
+    SeekDB is an AI-native search database by OceanBase that unifies
+    relational, vector, text, JSON and GIS in a single engine.
+
+    Supports both embedded mode and remote server mode.
+    """
+
+    def __init__(self, ap: app.Application):
+        if not SEEKDB_AVAILABLE:
+            raise ImportError('pyseekdb is not installed. Install it with: pip install pyseekdb')
+
+        self.ap = ap
+        config = self.ap.instance_config.data['vdb']['seekdb']
+
+        # Determine connection mode based on config
+        mode = config.get('mode', 'embedded')  # 'embedded' or 'server'
+
+        if mode == 'embedded':
+            # Embedded mode: local database
+            path = config.get('path', './data/seekdb')
+            database = config.get('database', 'langbot')
+
+            # Use AdminClient for database management operations
+            admin_client = pyseekdb.AdminClient(path=path)
+            # Check if database exists using public API
+            existing_dbs = [db.name for db in admin_client.list_databases()]
+            if database not in existing_dbs:
+                # Use public API to create database
+                admin_client.create_database(database)
+                self.ap.logger.info(f"Created SeekDB database '{database}'")
+
+            self.client = pyseekdb.Client(path=path, database=database)
+            self.ap.logger.info(f"Initialized SeekDB in embedded mode at '{path}', database '{database}'")
+        elif mode == 'server':
+            # Server mode: remote SeekDB or OceanBase server
+            host = config.get('host', 'localhost')
+            port = config.get('port', 2881)
+            database = config.get('database', 'langbot')
+            user = config.get('user', 'root')
+            password = config.get('password', '')
+            tenant = config.get('tenant', None)  # Optional, for OceanBase
+
+            connection_params = {
+                'host': host,
+                'port': int(port),
+                'database': database,
+                'user': user,
+                'password': password,
+            }
+
+            if tenant:
+                connection_params['tenant'] = tenant
+
+            self.client = pyseekdb.Client(**connection_params)
+            self.ap.logger.info(
+                f"Initialized SeekDB in server mode: {host}:{port}, database '{database}'"
+                + (f", tenant '{tenant}'" if tenant else '')
+            )
+        else:
+            raise ValueError(f"Invalid SeekDB mode: {mode}. Must be 'embedded' or 'server'")
+
+        self._collections: Dict[str, Any] = {}
+        self._collection_configs: Dict[str, HNSWConfiguration] = {}
+
+        self._escape_table = str.maketrans({
+            '\x00': '',
+            '\\': '\\\\',
+            '"': '\\"',
+            '\n': '\\n',
+            '\r': '\\r',
+            '\t': '\\t',
+        })
+
+    async def _get_or_create_collection_internal(self, collection: str, vector_size: int = None) -> Any:
+        """Internal method to get or create a collection with proper configuration."""
+        if collection in self._collections:
+            return self._collections[collection]
+
+        # Check if collection exists
+        if await asyncio.to_thread(self.client.has_collection, collection):
+            # Collection exists, get it
+            coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
+            self._collections[collection] = coll
+            self.ap.logger.info(f"SeekDB collection '{collection}' retrieved.")
+            return coll
+
+        # Collection doesn't exist, create it
+        if vector_size is None:
+            # Default dimension if not specified
+            vector_size = 384
+
+        # Create HNSW configuration
+        config = HNSWConfiguration(dimension=vector_size, distance='cosine')
+        self._collection_configs[collection] = config
+
+        # Create collection without embedding function (we manage embeddings externally)
+        coll = await asyncio.to_thread(
+            self.client.create_collection,
+            name=collection,
+            configuration=config,
+            embedding_function=None,  # Disable automatic embedding
+        )
+
+        self._collections[collection] = coll
+        self.ap.logger.info(f"SeekDB collection '{collection}' created with dimension={vector_size}, distance='cosine'")
+        return coll
+
+    def _clean_metadata(self, meta: Dict[str, Any]) -> Dict[str, Any]:
+        """SeekDB metadata doesn't support \\ and ", insert will error 3104"""
+        return {
+            k: v.translate(self._escape_table) if isinstance(v, str)
+            else v if v is None or isinstance(v, (int, float, bool))
+            else str(v)
+            for k, v in meta.items()
+            if v is not None
+        }
+
+    async def get_or_create_collection(self, collection: str):
+        """Get or create collection (without vector size - will use default)."""
+        return await self._get_or_create_collection_internal(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 the specified collection.
+
+        Args:
+            collection: Collection name
+            ids: List of document IDs
+            embeddings_list: List of embedding vectors
+            metadatas: List of metadata dictionaries
+        """
+        if not embeddings_list:
+            return
+
+        # Ensure collection exists with correct dimension
+        vector_size = len(embeddings_list[0])
+        coll = await self._get_or_create_collection_internal(collection, vector_size)
+
+        cleaned_metadatas = [self._clean_metadata(meta) for meta in metadatas]
+
+        await asyncio.to_thread(coll.add, ids=ids, embeddings=embeddings_list, metadatas=cleaned_metadatas)
+
+        self.ap.logger.info(f"Added {len(ids)} embeddings to SeekDB collection '{collection}'")
+
+    async def search(self, collection: str, query_embedding: List[float], k: int = 5) -> Dict[str, Any]:
+        """Search for the most similar vectors in the specified collection.
+
+        Args:
+            collection: Collection name
+            query_embedding: Query vector
+            k: Number of results to return
+
+        Returns:
+            Dictionary with 'ids', 'metadatas', 'distances' keys
+        """
+        # Check if collection exists
+        exists = await asyncio.to_thread(self.client.has_collection, collection)
+        if not exists:
+            return {'ids': [[]], 'metadatas': [[]], 'distances': [[]]}
+
+        # Get collection
+        if collection not in self._collections:
+            coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
+            self._collections[collection] = coll
+        else:
+            coll = self._collections[collection]
+
+        # Perform query
+        # SeekDB's query() returns: {'ids': [[...]], 'metadatas': [[...]], 'distances': [[...]]}
+        results = await asyncio.to_thread(coll.query, query_embeddings=query_embedding, n_results=k)
+
+        self.ap.logger.info(f"SeekDB search in '{collection}' returned {len(results.get('ids', [[]])[0])} results")
+
+        return results
+
+    async def delete_by_file_id(self, collection: str, file_id: str) -> None:
+        """Delete vectors from the collection by file_id metadata.
+
+        Args:
+            collection: Collection name
+            file_id: File ID to delete
+        """
+        # Check if collection exists
+        exists = await asyncio.to_thread(self.client.has_collection, collection)
+        if not exists:
+            self.ap.logger.warning(f"SeekDB collection '{collection}' not found for deletion")
+            return
+
+        # Get collection
+        if collection not in self._collections:
+            coll = await asyncio.to_thread(self.client.get_collection, collection, embedding_function=None)
+            self._collections[collection] = coll
+        else:
+            coll = self._collections[collection]
+
+        # SeekDB's delete() expects a where clause for filtering
+        # Delete all records where metadata['file_id'] == file_id
+        await asyncio.to_thread(coll.delete, where={'file_id': file_id})
+
+        self.ap.logger.info(f"Deleted embeddings from SeekDB collection '{collection}' with file_id: {file_id}")
+
+    async def delete_collection(self, collection: str):
+        """Delete the entire collection.
+
+        Args:
+            collection: Collection name
+        """
+        # Remove from cache
+        if collection in self._collections:
+            del self._collections[collection]
+        if collection in self._collection_configs:
+            del self._collection_configs[collection]
+
+        # Check if collection exists
+        exists = await asyncio.to_thread(self.client.has_collection, collection)
+        if not exists:
+            self.ap.logger.warning(f"SeekDB collection '{collection}' not found for deletion")
+            return
+
+        # Delete collection
+        await asyncio.to_thread(self.client.delete_collection, collection)
+        self.ap.logger.info(f"SeekDB collection '{collection}' deleted")

src/langbot/templates/config.yaml

@@ -16,6 +16,7 @@ proxy:
     https: ''
 system:
     recovery_key: ''
+    allow_change_password: true
     jwt:
         expire: 604800
         secret: ''
@@ -36,6 +37,17 @@ vdb:
         host: localhost
         port: 6333
         api_key: ''
+    seekdb:
+        mode: embedded  # 'embedded' or 'server'
+        # Embedded mode options:
+        path: './data/seekdb'
+        database: 'langbot'
+        # Server mode options (used when mode='server'):
+        host: 'localhost'
+        port: 2881
+        user: 'root'
+        password: ''
+        tenant: ''  # Optional, for OceanBase server
     milvus:
         uri: 'http://127.0.0.1:19530'
         token: ''

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": "~15.5.9",
     "next-themes": "^0.4.6",
     "postcss": "^8.5.3",
-    "react": "^19.0.0",
-    "react-dom": "^19.0.0",
+    "react": "19.2.1",
+    "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-dom": "^19",
+    "@types/react": "~19.2.7",
+    "@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');
@@ -283,6 +310,7 @@ export default function BotForm({
               name: item.name,
               required: item.required,
               type: parseDynamicFormItemType(item.type),
+              options: item.options,
             }),
         ),
       );
@@ -498,34 +526,36 @@ export default function BotForm({
                 </div>
 
                 {/* Webhook 地址显示（统一 Webhook 模式） */}
-                {webhookUrl && (
-                  <FormItem>
-                    <FormLabel>{t('bots.webhookUrl')}</FormLabel>
-                    <div className="flex items-center gap-2">
-                      <Input
-                        ref={webhookInputRef}
-                        value={webhookUrl}
-                        readOnly
-                        className="flex-1 bg-gray-50 dark:bg-gray-900"
-                        onClick={(e) => {
-                          // 点击输入框时自动全选
-                          (e.target as HTMLInputElement).select();
-                        }}
-                      />
-                      <Button
-                        type="button"
-                        variant="outline"
-                        size="sm"
-                        onClick={copyToClipboard}
-                      >
-                        {t('common.copy')}
-                      </Button>
-                    </div>
-                    <p className="text-sm text-gray-500 mt-1">
-                      {t('bots.webhookUrlHint')}
-                    </p>
-                  </FormItem>
-                )}
+                {webhookUrl &&
+                  (currentAdapter !== 'lark' ||
+                    currentAdapterConfig?.['enable-webhook'] !== false) && (
+                    <FormItem>
+                      <FormLabel>{t('bots.webhookUrl')}</FormLabel>
+                      <div className="flex items-center gap-2">
+                        <Input
+                          ref={webhookInputRef}
+                          value={webhookUrl}
+                          readOnly
+                          className="flex-1 bg-gray-50 dark:bg-gray-900"
+                          onClick={(e) => {
+                            // 点击输入框时自动全选
+                            (e.target as HTMLInputElement).select();
+                          }}
+                        />
+                        <Button
+                          type="button"
+                          variant="outline"
+                          size="sm"
+                          onClick={copyToClipboard}
+                        >
+                          {t('common.copy')}
+                        </Button>
+                      </div>
+                      <p className="text-sm text-gray-500 mt-1">
+                        {t('bots.webhookUrlHint')}
+                      </p>
+                    </FormItem>
+                  )}
               </>
             )}
 
@@ -622,13 +652,13 @@ 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/components/home-sidebar/HomeSidebar.tsx

@@ -12,7 +12,16 @@ import langbotIcon from '@/app/assets/langbot-logo.webp';
 import { systemInfo } from '@/app/infra/http/HttpClient';
 import { getCloudServiceClientSync } from '@/app/infra/http';
 import { useTranslation } from 'react-i18next';
-import { Moon, Sun, Monitor } from 'lucide-react';
+import {
+  Moon,
+  Sun,
+  Monitor,
+  CircleHelp,
+  Lightbulb,
+  Lock,
+  LogOut,
+  KeyRound,
+} from 'lucide-react';
 import { useTheme } from 'next-themes';
 
 import {
@@ -184,23 +193,6 @@ export default function HomeSidebar({
           </div>
         )}
 
-        <SidebarChild
-          onClick={() => {
-            setApiKeyDialogOpen(true);
-          }}
-          isSelected={false}
-          icon={
-            <svg
-              xmlns="http://www.w3.org/2000/svg"
-              viewBox="0 0 24 24"
-              fill="currentColor"
-            >
-              <path d="M10.7577 11.8281L18.6066 3.97919L20.0208 5.3934L18.6066 6.80761L21.0815 9.28249L19.6673 10.6967L17.1924 8.22183L15.7782 9.63604L17.8995 11.7574L16.4853 13.1716L14.364 11.0503L12.1719 13.2423C13.4581 15.1837 13.246 17.8251 11.5355 19.5355C9.58291 21.4882 6.41709 21.4882 4.46447 19.5355C2.51184 17.5829 2.51184 14.4171 4.46447 12.4645C6.17493 10.754 8.81633 10.5419 10.7577 11.8281ZM10.1213 18.1213C11.2929 16.9497 11.2929 15.0503 10.1213 13.8787C8.94975 12.7071 7.05025 12.7071 5.87868 13.8787C4.70711 15.0503 4.70711 16.9497 5.87868 18.1213C7.05025 19.2929 8.94975 19.2929 10.1213 18.1213Z"></path>
-            </svg>
-          }
-          name={t('common.apiIntegration')}
-        />
-
         <Popover
           open={popoverOpen}
           onOpenChange={(open) => {
@@ -262,6 +254,23 @@ export default function HomeSidebar({
               />
             </div>
 
+            <div className="flex flex-col gap-2 w-full">
+              <span className="text-sm font-medium">
+                {t('common.integration')}
+              </span>
+              <Button
+                variant="ghost"
+                className="w-full justify-start font-normal"
+                onClick={() => {
+                  setApiKeyDialogOpen(true);
+                  setPopoverOpen(false);
+                }}
+              >
+                <KeyRound className="w-4 h-4 mr-2" />
+                {t('common.apiIntegration')}
+              </Button>
+            </div>
+
             <div className="flex flex-col gap-2 w-full">
               <span className="text-sm font-medium">{t('common.account')}</span>
               <Button
@@ -289,34 +298,36 @@ export default function HomeSidebar({
                   setPopoverOpen(false);
                 }}
               >
-                <svg
-                  xmlns="http://www.w3.org/2000/svg"
-                  viewBox="0 0 24 24"
-                  fill="currentColor"
-                  className="w-4 h-4 mr-2"
-                >
-                  <path d="M12 22C6.47715 22 2 17.5228 2 12C2 6.47715 6.47715 2 12 2C17.5228 2 22 6.47715 22 12C22 17.5228 17.5228 22 12 22ZM12 20C16.4183 20 20 16.4183 20 12C20 7.58172 16.4183 4 12 4C7.58172 4 4 7.58172 4 12C4 16.4183 7.58172 20 12 20ZM11 15H13V17H11V15ZM13 13.3551V14H11V12.5C11 11.9477 11.4477 11.5 12 11.5C12.8284 11.5 13.5 10.8284 13.5 10C13.5 9.17157 12.8284 8.5 12 8.5C11.2723 8.5 10.6656 9.01823 10.5288 9.70577L8.56731 9.31346C8.88637 7.70919 10.302 6.5 12 6.5C13.933 6.5 15.5 8.067 15.5 10C15.5 11.5855 14.4457 12.9248 13 13.3551Z"></path>
-                </svg>
+                <CircleHelp className="w-4 h-4 mr-2" />
                 {t('common.helpDocs')}
               </Button>
               <Button
                 variant="ghost"
                 className="w-full justify-start font-normal"
                 onClick={() => {
-                  setPasswordChangeOpen(true);
+                  window.open(
+                    'https://github.com/langbot-app/LangBot/issues',
+                    '_blank',
+                  );
                   setPopoverOpen(false);
                 }}
               >
-                <svg
-                  xmlns="http://www.w3.org/2000/svg"
-                  viewBox="0 0 24 24"
-                  fill="currentColor"
-                  className="w-4 h-4 mr-2"
-                >
-                  <path d="M6 8V7C6 3.68629 8.68629 1 12 1C15.3137 1 18 3.68629 18 7V8H20C20.5523 8 21 8.44772 21 9V21C21 21.5523 20.5523 22 20 22H4C3.44772 22 3 21.5523 3 21V9C3 8.44772 3.44772 8 4 8H6ZM19 10H5V20H19V10ZM11 15.7324C10.4022 15.3866 10 14.7403 10 14C10 12.8954 10.8954 12 12 12C13.1046 12 14 12.8954 14 14C14 14.7403 13.5978 15.3866 13 15.7324V18H11V15.7324ZM8 8H16V7C16 4.79086 14.2091 3 12 3C9.79086 3 8 4.79086 8 7V8Z"></path>
-                </svg>
-                {t('common.changePassword')}
+                <Lightbulb className="w-4 h-4 mr-2" />
+                {t('common.featureRequest')}
               </Button>
+              {systemInfo?.allow_change_password && (
+                <Button
+                  variant="ghost"
+                  className="w-full justify-start font-normal"
+                  onClick={() => {
+                    setPasswordChangeOpen(true);
+                    setPopoverOpen(false);
+                  }}
+                >
+                  <Lock className="w-4 h-4 mr-2" />
+                  {t('common.changePassword')}
+                </Button>
+              )}
               <Button
                 variant="ghost"
                 className="w-full justify-start font-normal"
@@ -324,14 +335,7 @@ export default function HomeSidebar({
                   handleLogout();
                 }}
               >
-                <svg
-                  xmlns="http://www.w3.org/2000/svg"
-                  viewBox="0 0 24 24"
-                  fill="currentColor"
-                  className="w-4 h-4 mr-2"
-                >
-                  <path d="M4 18H6V20H18V4H6V6H4V3C4 2.44772 4.44772 2 5 2H19C19.5523 2 20 2.44772 20 3V21C20 21.5523 19.5523 22 19 22H5C4.44772 22 4 21.5523 4 21V18ZM6 11H13V13H6V16L1 12L6 8V11Z"></path>
-                </svg>
+                <LogOut className="w-4 h-4 mr-2" />
                 {t('common.logout')}
               </Button>
             </div>

web/src/app/home/models/component/ChooseRequesterEntity.ts

@@ -2,4 +2,5 @@ export interface IChooseRequesterEntity {
   label: string;
   value: string;
   provider_category?: string;
+  description?: string;
 }

web/src/app/home/models/component/embedding-card/EmbeddingCard.tsx

@@ -33,19 +33,21 @@ export default function EmbeddingCard({ cardVO }: { cardVO: EmbeddingCardVO }) {
             </span>
           </div>
           {/* baseURL */}
-          <div className={`${styles.baseURLContainer}`}>
-            <svg
-              className={`${styles.baseURLIcon}`}
-              xmlns="http://www.w3.org/2000/svg"
-              viewBox="0 0 24 24"
-              width="36"
-              height="36"
-              fill="rgba(98,98,98,1)"
-            >
-              <path d="M13.0607 8.11097L14.4749 9.52518C17.2086 12.2589 17.2086 16.691 14.4749 19.4247L14.1214 19.7782C11.3877 22.5119 6.95555 22.5119 4.22188 19.7782C1.48821 17.0446 1.48821 12.6124 4.22188 9.87874L5.6361 11.293C3.68348 13.2456 3.68348 16.4114 5.6361 18.364C7.58872 20.3166 10.7545 20.3166 12.7072 18.364L13.0607 18.0105C15.0133 16.0578 15.0133 12.892 13.0607 10.9394L11.6465 9.52518L13.0607 8.11097ZM19.7782 14.1214L18.364 12.7072C20.3166 10.7545 20.3166 7.58872 18.364 5.6361C16.4114 3.68348 13.2456 3.68348 11.293 5.6361L10.9394 5.98965C8.98678 7.94227 8.98678 11.1081 10.9394 13.0607L12.3536 14.4749L10.9394 15.8891L9.52518 14.4749C6.79151 11.7413 6.79151 7.30911 9.52518 4.57544L9.87874 4.22188C12.6124 1.48821 17.0446 1.48821 19.7782 4.22188C22.5119 6.95555 22.5119 11.3877 19.7782 14.1214Z"></path>
-            </svg>
-            <span className={`${styles.baseURLText}`}>{cardVO.baseURL}</span>
-          </div>
+          {cardVO.baseURL && (
+            <div className={`${styles.baseURLContainer}`}>
+              <svg
+                className={`${styles.baseURLIcon}`}
+                xmlns="http://www.w3.org/2000/svg"
+                viewBox="0 0 24 24"
+                width="36"
+                height="36"
+                fill="rgba(98,98,98,1)"
+              >
+                <path d="M13.0607 8.11097L14.4749 9.52518C17.2086 12.2589 17.2086 16.691 14.4749 19.4247L14.1214 19.7782C11.3877 22.5119 6.95555 22.5119 4.22188 19.7782C1.48821 17.0446 1.48821 12.6124 4.22188 9.87874L5.6361 11.293C3.68348 13.2456 3.68348 16.4114 5.6361 18.364C7.58872 20.3166 10.7545 20.3166 12.7072 18.364L13.0607 18.0105C15.0133 16.0578 15.0133 12.892 13.0607 10.9394L11.6465 9.52518L13.0607 8.11097ZM19.7782 14.1214L18.364 12.7072C20.3166 10.7545 20.3166 7.58872 18.364 5.6361C16.4114 3.68348 13.2456 3.68348 11.293 5.6361L10.9394 5.98965C8.98678 7.94227 8.98678 11.1081 10.9394 13.0607L12.3536 14.4749L10.9394 15.8891L9.52518 14.4749C6.79151 11.7413 6.79151 7.30911 9.52518 4.57544L9.87874 4.22188C12.6124 1.48821 17.0446 1.48821 19.7782 4.22188C22.5119 6.95555 22.5119 11.3877 19.7782 14.1214Z"></path>
+              </svg>
+              <span className={`${styles.baseURLText}`}>{cardVO.baseURL}</span>
+            </div>
+          )}
         </div>
       </div>
     </div>

web/src/app/home/models/component/embedding-form/EmbeddingForm.tsx

@@ -75,7 +75,7 @@ const getFormSchema = (t: (key: string) => string) =>
     model_provider: z
       .string()
       .min(1, { message: t('models.modelProviderRequired') }),
-    url: z.string().min(1, { message: t('models.requestURLRequired') }),
+    url: z.string().optional(),
     api_key: z.string().optional(),
     extra_args: z.array(getExtraArgSchema(t)).optional(),
   });
@@ -188,6 +188,7 @@ export default function EmbeddingForm({
           label: extractI18nObject(item.label),
           value: item.name,
           provider_category: item.spec.provider_category || 'manufacturer',
+          description: extractI18nObject(item.description) || undefined,
         };
       }),
     );
@@ -243,7 +244,7 @@ export default function EmbeddingForm({
       description: '',
       requester: value.model_provider,
       requester_config: {
-        base_url: value.url,
+        base_url: value.url || '',
         timeout: 120,
       },
       extra_args: extraArgsObj,
@@ -320,7 +321,7 @@ export default function EmbeddingForm({
         description: '',
         requester: form.getValues('model_provider'),
         requester_config: {
-          base_url: form.getValues('url'),
+          base_url: form.getValues('url') ?? '',
           timeout: 120,
         },
         api_keys: apiKey ? [apiKey] : [],
@@ -425,6 +426,18 @@ export default function EmbeddingForm({
                         />
                       </SelectTrigger>
                       <SelectContent>
+                        <SelectGroup>
+                          <SelectLabel>{t('models.builtin')}</SelectLabel>
+                          {requesterNameList
+                            .filter(
+                              (item) => item.provider_category === 'builtin',
+                            )
+                            .map((item) => (
+                              <SelectItem key={item.value} value={item.value}>
+                                {item.label}
+                              </SelectItem>
+                            ))}
+                        </SelectGroup>
                         <SelectGroup>
                           <SelectLabel>
                             {t('models.modelManufacturer')}
@@ -468,29 +481,42 @@ export default function EmbeddingForm({
                       </SelectContent>
                     </Select>
                   </FormControl>
+                  {currentModelProvider &&
+                    requesterNameList.find(
+                      (item) => item.value === currentModelProvider,
+                    )?.description && (
+                      <FormDescription>
+                        {
+                          requesterNameList.find(
+                            (item) => item.value === currentModelProvider,
+                          )?.description
+                        }
+                      </FormDescription>
+                    )}
                   <FormMessage />
                 </FormItem>
               )}
             />
 
-            <FormField
-              control={form.control}
-              name="url"
-              render={({ field }) => (
-                <FormItem>
-                  <FormLabel>
-                    {t('models.requestURL')}
-                    <span className="text-red-500">*</span>
-                  </FormLabel>
-                  <FormControl>
-                    <Input {...field} />
-                  </FormControl>
-                  <FormMessage />
-                </FormItem>
-              )}
-            />
+            {!['seekdb-embedding'].includes(currentModelProvider) && (
+              <FormField
+                control={form.control}
+                name="url"
+                render={({ field }) => (
+                  <FormItem>
+                    <FormLabel>{t('models.requestURL')}</FormLabel>
+                    <FormControl>
+                      <Input {...field} />
+                    </FormControl>
+                    <FormMessage />
+                  </FormItem>
+                )}
+              />
+            )}
 
-            {!['ollama-chat'].includes(currentModelProvider) && (
+            {!['ollama-chat', 'seekdb-embedding'].includes(
+              currentModelProvider,
+            ) && (
               <FormField
                 control={form.control}
                 name="api_key"

web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx

@@ -5,6 +5,7 @@ import { DialogContent } from '@/components/ui/dialog';
 import { Button } from '@/components/ui/button';
 import { Input } from '@/components/ui/input';
 import { ScrollArea } from '@/components/ui/scroll-area';
+import { Switch } from '@/components/ui/switch';
 import { cn } from '@/lib/utils';
 import {
   Message,
@@ -60,6 +61,7 @@ export default function DebugDialog({
   const [rawModeMessages, setRawModeMessages] = useState<Set<string>>(
     new Set(),
   );
+  const [streamOutput, setStreamOutput] = useState(true);
   const messagesEndRef = useRef<HTMLDivElement>(null);
   const inputRef = useRef<HTMLInputElement>(null);
   const popoverRef = useRef<HTMLDivElement>(null);
@@ -384,7 +386,7 @@ export default function DebugDialog({
 
       // 通过WebSocket发送消息
       // 不在本地添加消息，等待后端广播回来（带有正确的ID）
-      wsClientRef.current.sendMessage(messageChain);
+      wsClientRef.current.sendMessage(messageChain, streamOutput);
     } catch (error) {
       console.error('Failed to send message:', error);
       toast.error(t('pipelines.debugDialog.sendFailed'));
@@ -897,7 +899,18 @@ export default function DebugDialog({
         )}
 
         <div className="p-4 pb-0 bg-white dark:bg-black flex gap-2">
-          <div className="flex gap-2">
+          <div className="flex gap-2 items-center">
+            <div className="flex items-center gap-1">
+              <span className="text-xs text-gray-500 dark:text-gray-400">
+                {t('pipelines.debugDialog.streamOutput')}
+              </span>
+              <Switch
+                checked={streamOutput}
+                onCheckedChange={setStreamOutput}
+                disabled={!isConnected}
+                className="data-[state=checked]:bg-[#2288ee]"
+              />
+            </div>
             <input
               ref={fileInputRef}
               type="file"

web/src/app/home/pipelines/components/pipeline-form/PipelineFormComponent.tsx

@@ -52,6 +52,7 @@ export default function PipelineFormComponent({
 }) {
   const { t } = useTranslation();
   const [showDeleteConfirm, setShowDeleteConfirm] = useState(false);
+  const [showCopyConfirm, setShowCopyConfirm] = useState(false);
   const [isDefaultPipeline, setIsDefaultPipeline] = useState<boolean>(false);
 
   const formSchema = isEditMode
@@ -345,25 +346,17 @@ export default function PipelineFormComponent({
   };
 
   const handleCopy = () => {
+    setShowCopyConfirm(true);
+  };
+
+  const confirmCopy = () => {
     if (pipelineId) {
-      let newPipelineName = '';
       httpClient
-        .getPipeline(pipelineId)
-        .then((resp) => {
-          const originalPipeline = resp.pipeline;
-          newPipelineName = `${originalPipeline.name}${t(
-            'pipelines.copySuffix',
-          )}`;
-          const newPipeline: Pipeline = {
-            name: newPipelineName,
-            description: originalPipeline.description,
-            config: originalPipeline.config,
-          };
-          return httpClient.createPipeline(newPipeline);
-        })
+        .copyPipeline(pipelineId)
         .then(() => {
           onFinish();
-          toast.success(`${t('common.copySuccess')}: ${newPipelineName}`);
+          toast.success(t('common.copySuccess'));
+          setShowCopyConfirm(false);
           onCancel();
         })
         .catch((err) => {
@@ -547,6 +540,22 @@ export default function PipelineFormComponent({
           </DialogFooter>
         </DialogContent>
       </Dialog>
+
+      {/* 复制确认对话框 */}
+      <Dialog open={showCopyConfirm} onOpenChange={setShowCopyConfirm}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>{t('pipelines.copyConfirmTitle')}</DialogTitle>
+          </DialogHeader>
+          <div className="py-4">{t('pipelines.copyConfirmation')}</div>
+          <DialogFooter>
+            <Button variant="outline" onClick={() => setShowCopyConfirm(false)}>
+              {t('common.cancel')}
+            </Button>
+            <Button onClick={confirmCopy}>{t('common.confirm')}</Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
     </>
   );
 }

web/src/app/home/plugins/components/plugin-installed/PluginCardVO.ts

@@ -13,6 +13,7 @@ export interface IPluginCardVO {
   status: string;
   components: PluginComponent[];
   debug: boolean;
+  hasUpdate?: boolean;
 }
 
 export class PluginCardVO implements IPluginCardVO {
@@ -28,6 +29,7 @@ export class PluginCardVO implements IPluginCardVO {
   install_info: Record<string, any>; // eslint-disable-line @typescript-eslint/no-explicit-any
   status: string;
   components: PluginComponent[];
+  hasUpdate?: boolean;
 
   constructor(prop: IPluginCardVO) {
     this.author = prop.author;
@@ -42,5 +44,6 @@ export class PluginCardVO implements IPluginCardVO {
     this.debug = prop.debug;
     this.install_source = prop.install_source;
     this.install_info = prop.install_info;
+    this.hasUpdate = prop.hasUpdate;
   }
 }

web/src/app/home/plugins/components/plugin-installed/PluginInstalledComponent.tsx

@@ -7,6 +7,8 @@ import PluginForm from '@/app/home/plugins/components/plugin-installed/plugin-fo
 import PluginReadme from '@/app/home/plugins/components/plugin-installed/plugin-readme/PluginReadme';
 import styles from '@/app/home/plugins/plugins.module.css';
 import { httpClient } from '@/app/infra/http/HttpClient';
+import { getCloudServiceClientSync } from '@/app/infra/http';
+import { isNewerVersion } from '@/app/utils/versionCompare';
 import {
   Dialog,
   DialogContent,
@@ -72,10 +74,68 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
       getPluginList();
     }
 
-    function getPluginList() {
-      httpClient.getPlugins().then((value) => {
+    async function getPluginList() {
+      try {
+        // 获取已安装插件列表
+        const installedPluginsResp = await httpClient.getPlugins();
+        const installedPlugins = installedPluginsResp.plugins;
+
+        // 获取市场插件列表
+        const client = getCloudServiceClientSync();
+        const marketplaceResp = await client.getMarketplacePlugins(1, 100);
+        const marketplacePlugins = marketplaceResp.plugins;
+
+        // 创建市场插件映射，便于快速查找
+        const marketplacePluginMap = new Map();
+        marketplacePlugins.forEach((plugin) => {
+          const key = `${plugin.author}/${plugin.name}`;
+          marketplacePluginMap.set(key, plugin);
+        });
+
+        // 转换并比较版本号
+        const pluginCards = installedPlugins.map((plugin) => {
+          const cardVO = new PluginCardVO({
+            author: plugin.manifest.manifest.metadata.author ?? '',
+            label: extractI18nObject(plugin.manifest.manifest.metadata.label),
+            description: extractI18nObject(
+              plugin.manifest.manifest.metadata.description ?? {
+                en_US: '',
+                zh_Hans: '',
+              },
+            ),
+            debug: plugin.debug,
+            enabled: plugin.enabled,
+            name: plugin.manifest.manifest.metadata.name,
+            version: plugin.manifest.manifest.metadata.version ?? '',
+            status: plugin.status,
+            components: plugin.components,
+            priority: plugin.priority,
+            install_source: plugin.install_source,
+            install_info: plugin.install_info,
+          });
+
+          // 检查是否来自市场且有更新
+          if (cardVO.install_source === 'marketplace') {
+            const marketplaceKey = `${cardVO.author}/${cardVO.name}`;
+            const marketplacePlugin = marketplacePluginMap.get(marketplaceKey);
+            if (marketplacePlugin && marketplacePlugin.latest_version) {
+              cardVO.hasUpdate = isNewerVersion(
+                marketplacePlugin.latest_version,
+                cardVO.version,
+              );
+            }
+          }
+
+          return cardVO;
+        });
+
+        setPluginList(pluginCards);
+      } catch (error) {
+        console.error('获取插件列表失败:', error);
+        // 失败时仍显示已安装插件，不影响用户体验
+        const installedPluginsResp = await httpClient.getPlugins();
         setPluginList(
-          value.plugins.map((plugin) => {
+          installedPluginsResp.plugins.map((plugin) => {
             return new PluginCardVO({
               author: plugin.manifest.manifest.metadata.author ?? '',
               label: extractI18nObject(plugin.manifest.manifest.metadata.label),
@@ -97,7 +157,7 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
             });
           }),
         );
-      });
+      }
     }
 
     useImperativeHandle(ref, () => ({

web/src/app/home/plugins/components/plugin-installed/plugin-card/PluginCardComponent.tsx

@@ -159,12 +159,17 @@ export default function PluginCardComponent({
                 }}
               >
                 <DropdownMenuTrigger asChild>
-                  <Button
-                    variant="ghost"
-                    className="bg-white dark:bg-[#1f1f22] hover:bg-gray-100 dark:hover:bg-[#2a2a2d]"
-                  >
-                    <Ellipsis className="w-4 h-4" />
-                  </Button>
+                  <div className="relative">
+                    <Button
+                      variant="ghost"
+                      className="bg-white dark:bg-[#1f1f22] hover:bg-gray-100 dark:hover:bg-[#2a2a2d]"
+                    >
+                      <Ellipsis className="w-4 h-4" />
+                    </Button>
+                    {cardVO.hasUpdate && (
+                      <div className="absolute -top-0.5 -right-0.5 w-2.5 h-2.5 bg-red-500 rounded-full border-2 border-white dark:border-[#1f1f22]"></div>
+                    )}
+                  </div>
                 </DropdownMenuTrigger>
                 <DropdownMenuContent>
                   {/**upgrade */}
@@ -179,6 +184,11 @@ export default function PluginCardComponent({
                     >
                       <ArrowUp className="w-4 h-4" />
                       <span>{t('plugins.update')}</span>
+                      {cardVO.hasUpdate && (
+                        <Badge className="ml-auto bg-red-500 hover:bg-red-500 text-white text-[0.6rem] px-1.5 py-0 h-4">
+                          {t('plugins.new')}
+                        </Badge>
+                      )}
                     </DropdownMenuItem>
                   )}
                   {/**view source */}

web/src/app/infra/entities/api/index.ts

@@ -235,6 +235,7 @@ export interface ApiRespSystemInfo {
   version: string;
   cloud_service_url: string;
   enable_marketplace: boolean;
+  allow_change_password: boolean;
 }
 
 export interface ApiRespPluginSystemStatus {

web/src/app/infra/http/BackendClient.ts

@@ -172,6 +172,10 @@ export class BackendClient extends BaseHttpClient {
     return this.delete(`/api/v1/pipelines/${uuid}`);
   }
 
+  public copyPipeline(uuid: string): Promise<{ uuid: string }> {
+    return this.post(`/api/v1/pipelines/${uuid}/copy`);
+  }
+
   public getPipelineExtensions(uuid: string): Promise<{
     enable_all_plugins: boolean;
     enable_all_mcp_servers: boolean;

web/src/app/infra/http/index.ts

@@ -8,6 +8,7 @@ export let systemInfo: ApiRespSystemInfo = {
   version: '',
   enable_marketplace: true,
   cloud_service_url: '',
+  allow_change_password: true,
 };
 
 /**

web/src/app/infra/websocket/WebSocketClient.ts

@@ -204,6 +204,7 @@ export class WebSocketClient {
    */
   public sendMessage(
     messageChain: Array<{ type: string; text?: string; target?: string }>,
+    stream: boolean = true,
   ) {
     if (!this.ws || this.ws.readyState !== WebSocket.OPEN) {
       throw new Error('WebSocket未连接');
@@ -212,6 +213,7 @@ export class WebSocketClient {
     const message = {
       type: 'message',
       message: messageChain,
+      stream: stream,
     };
 
     this.ws.send(JSON.stringify(message));

web/src/app/utils/versionCompare.ts

@@ -0,0 +1,45 @@
+/**
+ * Compare two version strings and determine if the first is newer than the second.
+ * Supports semantic versioning format (e.g., "1.2.3", "1.0.0-beta.1").
+ *
+ * @param version1 - The version to compare (potentially newer)
+ * @param version2 - The version to compare against (base version)
+ * @returns true if version1 is newer than version2, false otherwise
+ */
+export function isNewerVersion(version1: string, version2: string): boolean {
+  if (!version1 || !version2) {
+    return false;
+  }
+
+  // Remove any leading 'v' prefix
+  const v1 = version1.replace(/^v/, '');
+  const v2 = version2.replace(/^v/, '');
+
+  // Split into main version and pre-release parts
+  const [main1, pre1] = v1.split('-');
+  const [main2, pre2] = v2.split('-');
+
+  // Split main version into numeric parts
+  const parts1 = main1.split('.').map((p) => parseInt(p, 10) || 0);
+  const parts2 = main2.split('.').map((p) => parseInt(p, 10) || 0);
+
+  // Normalize length
+  const maxLen = Math.max(parts1.length, parts2.length);
+  while (parts1.length < maxLen) parts1.push(0);
+  while (parts2.length < maxLen) parts2.push(0);
+
+  // Compare main version parts
+  for (let i = 0; i < maxLen; i++) {
+    if (parts1[i] > parts2[i]) return true;
+    if (parts1[i] < parts2[i]) return false;
+  }
+
+  // Main versions are equal, compare pre-release
+  // A version without pre-release is newer than one with pre-release
+  if (!pre1 && pre2) return true;
+  if (pre1 && !pre2) return false;
+  if (!pre1 && !pre2) return false;
+
+  // Both have pre-release, compare lexicographically
+  return pre1! > pre2!;
+}

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

@@ -2,8 +2,9 @@ const enUS = {
   common: {
     login: 'Login',
     logout: 'Logout',
-    accountOptions: 'Account',
+    accountOptions: 'Settings',
     account: 'Account',
+    integration: 'Integration',
     email: 'Email',
     password: 'Password',
     welcome: 'Welcome back to LangBot 👋',
@@ -16,6 +17,7 @@ const enUS = {
     emptyPassword: 'Please enter your password',
     language: 'Language',
     helpDocs: 'Get Help',
+    featureRequest: 'Feature Request',
     create: 'Create',
     edit: 'Edit',
     delete: 'Delete',
@@ -141,10 +143,11 @@ const enUS = {
     boolean: 'Boolean',
     selectModelProvider: 'Select Model Provider',
     modelProviderDescription:
-      'Please fill in the model name provided by the supplier',
+      'Please fill in the model name provided by the provider',
     modelManufacturer: 'Model Manufacturer',
     aggregationPlatform: 'Aggregation Platform',
     selfDeployed: 'Self-deployed',
+    builtin: 'Built-in',
     selectModel: 'Select Model',
     testSuccess: 'Test successful',
     testError: 'Test failed, please check your model configuration',
@@ -288,6 +291,7 @@ const enUS = {
     noComponents: 'No components',
     delete: 'Delete Plugin',
     update: 'Update Plugin',
+    new: 'New',
     updateConfirm: 'Update Confirmation',
     confirmUpdatePlugin:
       'Are you sure you want to update the plugin ({{author}}/{{name}})?',
@@ -492,6 +496,9 @@ const enUS = {
     defaultPipelineCannotDelete: 'Default pipeline cannot be deleted',
     deleteSuccess: 'Deleted successfully',
     deleteError: 'Delete failed: ',
+    copyConfirmTitle: 'Confirm Copy',
+    copyConfirmation:
+      'Are you sure you want to copy this pipeline? This will create a new pipeline with all configurations.',
     extensions: {
       title: 'Extensions',
       loadError: 'Failed to load plugins',
@@ -535,6 +542,7 @@ const enUS = {
       loadPipelinesFailed: 'Failed to load pipelines',
       atTips: 'Mention the bot',
       streaming: 'Streaming',
+      streamOutput: 'Stream',
       connected: 'WebSocket connected',
       disconnected: 'WebSocket disconnected',
       connectionError: 'WebSocket connection error',

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

@@ -2,8 +2,9 @@ const jaJP = {
   common: {
     login: 'ログイン',
     logout: 'ログアウト',
-    accountOptions: 'アカウントオプション',
+    accountOptions: 'システム設定',
     account: 'アカウント',
+    integration: '連携',
     email: 'メールアドレス',
     password: 'パスワード',
     welcome: 'LangBot へおかえりなさい 👋',
@@ -17,6 +18,7 @@ const jaJP = {
     emptyPassword: 'パスワードを入力してください',
     language: '言語',
     helpDocs: 'ヘルプドキュメント',
+    featureRequest: '機能リクエスト',
     create: '作成',
     edit: '編集',
     delete: '削除',
@@ -148,6 +150,7 @@ const jaJP = {
     modelManufacturer: 'モデルメーカー',
     aggregationPlatform: 'アグリゲーションプラットフォーム',
     selfDeployed: 'セルフデプロイ',
+    builtin: 'ビルトイン',
     selectModel: 'モデルを選択してください',
     testSuccess: 'テストに成功しました',
     testError: 'テストに失敗しました。モデル設定を確認してください',
@@ -289,6 +292,7 @@ const jaJP = {
     noComponents: '部品がありません',
     delete: 'プラグインを削除',
     update: 'プラグインを更新',
+    new: 'New',
     updateConfirm: '更新の確認',
     confirmUpdatePlugin:
       'プラグイン「{{author}}/{{name}}」を更新してもよろしいですか？',
@@ -495,6 +499,9 @@ const jaJP = {
     defaultPipelineCannotDelete: 'デフォルトパイプラインは削除できません',
     deleteSuccess: '削除に成功しました',
     deleteError: '削除に失敗しました：',
+    copyConfirmTitle: 'コピーの確認',
+    copyConfirmation:
+      'このパイプラインをコピーしますか？すべての設定を含む新しいパイプラインが作成されます。',
     extensions: {
       title: 'プラグイン統合',
       loadError: 'プラグインリストの読み込みに失敗しました',
@@ -538,6 +545,7 @@ const jaJP = {
       loadPipelinesFailed: 'パイプラインの読み込みに失敗しました',
       atTips: 'ボットをメンション',
       streaming: 'ストリーミング',
+      streamOutput: 'ストリーム',
       connected: 'WebSocket接続済み',
       disconnected: 'WebSocket未接続',
       connectionError: 'WebSocket接続エラー',

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

@@ -2,8 +2,9 @@ const zhHans = {
   common: {
     login: '登录',
     logout: '退出登录',
-    accountOptions: '账户选项',
+    accountOptions: '系统设置',
     account: '账户',
+    integration: '连接',
     email: '邮箱',
     password: '密码',
     welcome: '欢迎回到 LangBot 👋',
@@ -16,6 +17,7 @@ const zhHans = {
     emptyPassword: '请输入密码',
     language: '语言',
     helpDocs: '帮助文档',
+    featureRequest: '需求建议',
     create: '创建',
     edit: '编辑',
     delete: '删除',
@@ -142,6 +144,7 @@ const zhHans = {
     modelManufacturer: '模型厂商',
     aggregationPlatform: '中转平台',
     selfDeployed: '自部署',
+    builtin: '内置',
     selectModel: '请选择模型',
     testSuccess: '测试成功',
     testError: '测试失败，请检查模型配置',
@@ -275,6 +278,7 @@ const zhHans = {
     noComponents: '无组件',
     delete: '删除插件',
     update: '更新插件',
+    new: '新',
     updateConfirm: '更新确认',
     confirmUpdatePlugin: '你确定要更新插件（{{author}}/{{name}}）吗？',
     confirmUpdate: '确认更新',
@@ -474,6 +478,9 @@ const zhHans = {
     defaultPipelineCannotDelete: '默认流水线不可删除',
     deleteSuccess: '删除成功',
     deleteError: '删除失败：',
+    copyConfirmTitle: '确认复制',
+    copyConfirmation:
+      '确定要复制这个流水线吗？复制将创建一个包含完整配置的新流水线。',
     extensions: {
       title: '扩展集成',
       loadError: '加载插件列表失败',
@@ -517,6 +524,7 @@ const zhHans = {
       loadPipelinesFailed: '加载流水线失败',
       atTips: '提及机器人',
       streaming: '流式传输',
+      streamOutput: '流式',
       connected: 'WebSocket已连接',
       disconnected: 'WebSocket未连接',
       connectionError: 'WebSocket连接错误',

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

@@ -2,8 +2,9 @@ const zhHant = {
   common: {
     login: '登入',
     logout: '登出',
-    accountOptions: '帳戶選項',
+    accountOptions: '系統設定',
     account: '帳戶',
+    integration: '連接',
     email: '電子郵件',
     password: '密碼',
     welcome: '歡迎回到 LangBot 👋',
@@ -16,6 +17,7 @@ const zhHant = {
     emptyPassword: '請輸入密碼',
     language: '語言',
     helpDocs: '輔助說明',
+    featureRequest: '需求建議',
     create: '建立',
     edit: '編輯',
     delete: '刪除',
@@ -142,6 +144,7 @@ const zhHant = {
     modelManufacturer: '模型廠商',
     aggregationPlatform: '中轉平台',
     selfDeployed: '自部署',
+    builtin: '內建',
     selectModel: '請選擇模型',
     testSuccess: '測試成功',
     testError: '測試失敗，請檢查模型設定',
@@ -274,6 +277,7 @@ const zhHant = {
     noComponents: '無組件',
     delete: '刪除插件',
     update: '更新插件',
+    new: '新',
     updateConfirm: '更新確認',
     confirmUpdatePlugin: '您確定要更新插件（{{author}}/{{name}}）嗎？',
     confirmUpdate: '確認更新',
@@ -472,6 +476,9 @@ const zhHant = {
     defaultPipelineCannotDelete: '預設流程線不可刪除',
     deleteSuccess: '刪除成功',
     deleteError: '刪除失敗：',
+    copyConfirmTitle: '確認複製',
+    copyConfirmation:
+      '確定要複製這個流程線嗎？複製將創建一個包含完整配置的新流程線。',
     extensions: {
       title: '擴展集成',
       loadError: '載入插件清單失敗',
@@ -515,6 +522,7 @@ const zhHant = {
       loadPipelinesFailed: '載入流程線失敗',
       atTips: '提及機器人',
       streaming: '串流傳輸',
+      streamOutput: '串流',
       connected: 'WebSocket已連接',
       disconnected: 'WebSocket未連接',
       connectionError: 'WebSocket連接錯誤',